From 93963f019b634d014dc739cb5c51b67fb47bfa26 Mon Sep 17 00:00:00 2001 From: Michael Charles Berutti <mberutti-temp@igsascewlt-MMD2.gs.doi.net> Date: Fri, 12 Jul 2019 16:39:57 -0500 Subject: [PATCH 1/7] Preliminary unit test framework and some simple unit tests made. --- test/test_random.py | 147 ++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 147 insertions(+) create mode 100644 test/test_random.py diff --git a/test/test_random.py b/test/test_random.py new file mode 100644 index 0000000..f721f5d --- /dev/null +++ b/test/test_random.py @@ -0,0 +1,147 @@ +import unittest + +import h5py +import numpy as np +import os + +from fluegg.random import * + + +class TestNormalRandomNumbers(unittest.TestCase): + + def test_output_type(self): + + number = NormalRandomNumbers().random(50, 25) + self.assertTrue(isinstance(number, float)) + + def test_wrong_argument_quantity_input(self): + + with self.assertRaises(TypeError): + number = NormalRandomNumbers().random(50) + + with self.assertRaises(TypeError): + number = NormalRandomNumbers().random(50, 25, 12.5) + + def test_wrong_type_input(self): + + with self.assertRaises(ValueError): + number = NormalRandomNumbers().random('fifty', 25) + + with self.assertRaises(ValueError): + number = NormalRandomNumbers().random(50, 'twenty-five') + + with self.assertRaises(ValueError): + number = NormalRandomNumbers().random('fifty', 'twenty-five') + + def test_output_type_array(self): + + numbers = NormalRandomNumbers().random_array(50, 25, 12) + self.assertTrue(isinstance(numbers, np.ndarray)) + self.assertTrue(isinstance(numbers[0], float)) + + def test_wrong_argument_quantity_input_array(self): + + with self.assertRaises(TypeError): + numbers = NormalRandomNumbers().random_array(50, 25) + + with self.assertRaises(TypeError): + numbers = NormalRandomNumbers().random_array(50, 25, 12, 6.25) + + def test_wrong_type_input_array(self): + + with self.assertRaises(ValueError): + numbers = NormalRandomNumbers().random_array('fifty', 25, 12) + + with self.assertRaises(ValueError): + numbers = NormalRandomNumbers().random_array(50, 'twenty-five', 12) + + with self.assertRaises(TypeError): + numbers = NormalRandomNumbers().random_array(50, 25, 'twelve') + + with self.assertRaises(ValueError): + numbers = NormalRandomNumbers().random_array('fifty', 'twenty-five', 12) + + with self.assertRaises(ValueError): + numbers = NormalRandomNumbers().random_array(50, 'twenty-five', 'twelve') + + with self.assertRaises(ValueError): + numbers = NormalRandomNumbers().random_array('fifty', 25, 'twelve') + + with self.assertRaises(ValueError): + numbers = NormalRandomNumbers().random_array('fifty', 'twenty-five', 'twelve') + + with self.assertRaises(TypeError): + numbers = NormalRandomNumbers().random_array(50, 25, 12.5) + + +class TestNonRandomNumbers(unittest.TestCase): + + pass + + +class TestHDF5NormalRandomNumbers(unittest.TestCase): + + def setUp(self): + + self._remove_test_saves() + + def _create_HDF5_file(self): + + with h5py.File('UNIT TEST HDF5 TEST FILE.hdf', 'w') as f: + f.create_dataset('TEST DATA SET', (100,)) + + def _get_file_path(self): + + cwd = os.getcwd() + return cwd + r'\UNIT TEST HDF5 TEST FILE.hdf' + + def _remove_test_saves(self): + # Removes all saved results with 'UNIT TEST' in its file name. + if os.path.isdir(r'.\results'): + for file in os.listdir(r'.\results'): + if 'UNIT TEST' in file: + # print("Removed {}\n".format(file)) + os.remove(r'.\results\{}'.format(file)) + + def test_HDF5_input(self): + ''' Needs way to validate the results + ''' + self._create_HDF5_file() + file_path = self._get_file_path() + arr = np.random.normal(25, 50, 100) + + with self.assertRaises(TypeError): + numbers = HDF5NormalRandomNumbers( + 18, 'TEST DATA SET').random( + arr, 70) + + with self.assertRaises(AttributeError): + numbers = HDF5NormalRandomNumbers(file_path, 53).random(arr, 70) + + with self.assertRaises(AttributeError): + numbers = HDF5NormalRandomNumbers( + file_path, 'TEST DATA SET').random( + 'arr', 70) + + with self.assertRaises(TypeError): + numbers = HDF5NormalRandomNumbers( + file_path, 'TEST DATA SET').random( + arr, 'seventy') + + numbers = HDF5NormalRandomNumbers( + file_path, 'TEST DATA SET').random( + arr, 70) + + def test_HDF5_array(self): + ''' Needs way to validate the results + ''' + self._create_HDF5_file() + file_path = self._get_file_path() + arr = np.random.normal(25, 50, 100) + numbers = HDF5NormalRandomNumbers( + file_path, 'TEST DATA SET').random_array( + arr, 70, 100) + + def tearDown(self): + + self._remove_test_saves() -- GitLab From 3ce334392abbe227fbae3aa920c10ebb9b46ed5b Mon Sep 17 00:00:00 2001 From: Michael Charles Berutti <mberutti-temp@igsascewlt-MMD2.gs.doi.net> Date: Mon, 15 Jul 2019 10:34:00 -0500 Subject: [PATCH 2/7] Refined HDF5 tests and added Nonrandom Numbers tests --- test/test_random.py | 63 ++++++++++++++++++++++++++++++++++++++------- 1 file changed, 54 insertions(+), 9 deletions(-) diff --git a/test/test_random.py b/test/test_random.py index f721f5d..b78ea76 100644 --- a/test/test_random.py +++ b/test/test_random.py @@ -76,7 +76,24 @@ class TestNormalRandomNumbers(unittest.TestCase): class TestNonRandomNumbers(unittest.TestCase): - pass + def test_non_random_numbers(self): + + self.assertEqual(NonRandomNumbers().random([5], 1), [5]) + + with self.assertRaises(TypeError): + NonRandomNumbers().random(5) + + with self.assertRaises(TypeError): + NonRandomNumbers().random(5, 1, 5) + + with self.assertRaises(TypeError): + NonRandomNumbers().random_array(5) + + with self.assertRaises(TypeError): + NonRandomNumbers().random_array(5, 1) + + with self.assertRaises(TypeError): + NonRandomNumbers().random_array(5, 1, 5, 1) class TestHDF5NormalRandomNumbers(unittest.TestCase): @@ -85,10 +102,18 @@ class TestHDF5NormalRandomNumbers(unittest.TestCase): self._remove_test_saves() + def _average(self, numbers): + + sum = 0 + for number in numbers: + sum += number + return float(sum) / len(numbers) + def _create_HDF5_file(self): with h5py.File('UNIT TEST HDF5 TEST FILE.hdf', 'w') as f: - f.create_dataset('TEST DATA SET', (100,)) + arr = np.random.normal(0, 1, 1000) + f.create_dataset('TEST DATA SET', data=arr) def _get_file_path(self): @@ -104,8 +129,7 @@ class TestHDF5NormalRandomNumbers(unittest.TestCase): os.remove(r'.\results\{}'.format(file)) def test_HDF5_input(self): - ''' Needs way to validate the results - ''' + self._create_HDF5_file() file_path = self._get_file_path() arr = np.random.normal(25, 50, 100) @@ -132,15 +156,36 @@ class TestHDF5NormalRandomNumbers(unittest.TestCase): file_path, 'TEST DATA SET').random( arr, 70) - def test_HDF5_array(self): - ''' Needs way to validate the results - ''' + def test_HDF5_array_output_dimensions(self): + self._create_HDF5_file() file_path = self._get_file_path() - arr = np.random.normal(25, 50, 100) numbers = HDF5NormalRandomNumbers( file_path, 'TEST DATA SET').random_array( - arr, 70, 100) + 0, 70, 100) + + self.assertEqual(len(numbers), 100) + + def test_HDF5_array_output_value(self): + + self._create_HDF5_file() + file_path = self._get_file_path() + numbers = HDF5NormalRandomNumbers( + file_path, 'TEST DATA SET').random_array( + 0, 1, 100) + avg = self._average(numbers) + + self.assertTrue(-1 < avg < 1) + + def test_HDF5_array_size(self): + + self._create_HDF5_file() + file_path = self._get_file_path() + + with self.assertRaises(ValueError): + numbers = HDF5NormalRandomNumbers( + file_path, 'TEST DATA SET').random_array( + 0, 70, 2500) def tearDown(self): -- GitLab From 46e9992510a65bfe4caeff49552ed7c2fcbb6f54 Mon Sep 17 00:00:00 2001 From: Michael Charles Berutti <mberutti-temp@igsascewlt-MMD2.gs.doi.net> Date: Thu, 18 Jul 2019 16:40:04 -0500 Subject: [PATCH 3/7] Merged with origin. --- coverage_report/coverage_html.js | 584 +++++ coverage_report/fluegg___init___py.html | 89 + coverage_report/fluegg_asiancarpeggs_py.html | 1305 ++++++++++++ coverage_report/fluegg_drift_py.html | 393 ++++ coverage_report/fluegg_gui___init___py.html | 89 + coverage_report/fluegg_gui_gui_layout_py.html | 665 ++++++ coverage_report/fluegg_gui_gui_py.html | 923 ++++++++ .../fluegg_gui_hecras_dialog_py.html | 337 +++ coverage_report/fluegg_hydraulics_py.html | 1883 +++++++++++++++++ coverage_report/fluegg_kml_py.html | 907 ++++++++ coverage_report/fluegg_random_py.html | 271 +++ coverage_report/fluegg_ras_py.html | 1007 +++++++++ coverage_report/fluegg_simclock_py.html | 361 ++++ coverage_report/fluegg_simulation_py.html | 723 +++++++ coverage_report/fluegg_transporter_py.html | 1809 ++++++++++++++++ coverage_report/index.html | 230 ++ .../jquery.ba-throttle-debounce.min.js | 9 + coverage_report/jquery.hotkeys.js | 99 + coverage_report/jquery.isonscreen.js | 53 + coverage_report/jquery.min.js | 4 + coverage_report/jquery.tablesorter.min.js | 2 + coverage_report/keybd_closed.png | Bin 0 -> 112 bytes coverage_report/keybd_open.png | Bin 0 -> 112 bytes coverage_report/status.json | 1 + coverage_report/style.css | 375 ++++ coverage_report/test_fluegg_py.html | 165 ++ notebooks/vertical transporter - Copy.ipynb | 326 +++ .../ras/unsteadyflume/HEC-RASFlumeCase.dsc | 308 +++ .../ras/unsteadyflume/HEC-RASFlumeCase.rasmap | 187 ++ test/test_transporter.py | 9 + 30 files changed, 13114 insertions(+) create mode 100644 coverage_report/coverage_html.js create mode 100644 coverage_report/fluegg___init___py.html create mode 100644 coverage_report/fluegg_asiancarpeggs_py.html create mode 100644 coverage_report/fluegg_drift_py.html create mode 100644 coverage_report/fluegg_gui___init___py.html create mode 100644 coverage_report/fluegg_gui_gui_layout_py.html create mode 100644 coverage_report/fluegg_gui_gui_py.html create mode 100644 coverage_report/fluegg_gui_hecras_dialog_py.html create mode 100644 coverage_report/fluegg_hydraulics_py.html create mode 100644 coverage_report/fluegg_kml_py.html create mode 100644 coverage_report/fluegg_random_py.html create mode 100644 coverage_report/fluegg_ras_py.html create mode 100644 coverage_report/fluegg_simclock_py.html create mode 100644 coverage_report/fluegg_simulation_py.html create mode 100644 coverage_report/fluegg_transporter_py.html create mode 100644 coverage_report/index.html create mode 100644 coverage_report/jquery.ba-throttle-debounce.min.js create mode 100644 coverage_report/jquery.hotkeys.js create mode 100644 coverage_report/jquery.isonscreen.js create mode 100644 coverage_report/jquery.min.js create mode 100644 coverage_report/jquery.tablesorter.min.js create mode 100644 coverage_report/keybd_closed.png create mode 100644 coverage_report/keybd_open.png create mode 100644 coverage_report/status.json create mode 100644 coverage_report/style.css create mode 100644 coverage_report/test_fluegg_py.html create mode 100644 notebooks/vertical transporter - Copy.ipynb create mode 100644 test/data/ras/unsteadyflume/HEC-RASFlumeCase.dsc create mode 100644 test/data/ras/unsteadyflume/HEC-RASFlumeCase.rasmap create mode 100644 test/test_transporter.py diff --git a/coverage_report/coverage_html.js b/coverage_report/coverage_html.js new file mode 100644 index 0000000..f6f5de2 --- /dev/null +++ b/coverage_report/coverage_html.js @@ -0,0 +1,584 @@ +// Licensed under the Apache License: http://www.apache.org/licenses/LICENSE-2.0 +// For details: https://bitbucket.org/ned/coveragepy/src/default/NOTICE.txt + +// Coverage.py HTML report browser code. +/*jslint browser: true, sloppy: true, vars: true, plusplus: true, maxerr: 50, indent: 4 */ +/*global coverage: true, document, window, $ */ + +coverage = {}; + +// Find all the elements with shortkey_* class, and use them to assign a shortcut key. +coverage.assign_shortkeys = function () { + $("*[class*='shortkey_']").each(function (i, e) { + $.each($(e).attr("class").split(" "), function (i, c) { + if (/^shortkey_/.test(c)) { + $(document).bind('keydown', c.substr(9), function () { + $(e).click(); + }); + } + }); + }); +}; + +// Create the events for the help panel. +coverage.wire_up_help_panel = function () { + $("#keyboard_icon").click(function () { + // Show the help panel, and position it so the keyboard icon in the + // panel is in the same place as the keyboard icon in the header. + $(".help_panel").show(); + var koff = $("#keyboard_icon").offset(); + var poff = $("#panel_icon").position(); + $(".help_panel").offset({ + top: koff.top-poff.top, + left: koff.left-poff.left + }); + }); + $("#panel_icon").click(function () { + $(".help_panel").hide(); + }); +}; + +// Create the events for the filter box. +coverage.wire_up_filter = function () { + // Cache elements. + var table = $("table.index"); + var table_rows = table.find("tbody tr"); + var table_row_names = table_rows.find("td.name a"); + var no_rows = $("#no_rows"); + + // Create a duplicate table footer that we can modify with dynamic summed values. + var table_footer = $("table.index tfoot tr"); + var table_dynamic_footer = table_footer.clone(); + table_dynamic_footer.attr('class', 'total_dynamic hidden'); + table_footer.after(table_dynamic_footer); + + // Observe filter keyevents. + $("#filter").on("keyup change", $.debounce(150, function (event) { + var filter_value = $(this).val(); + + if (filter_value === "") { + // Filter box is empty, remove all filtering. + table_rows.removeClass("hidden"); + + // Show standard footer, hide dynamic footer. + table_footer.removeClass("hidden"); + table_dynamic_footer.addClass("hidden"); + + // Hide placeholder, show table. + if (no_rows.length > 0) { + no_rows.hide(); + } + table.show(); + + } + else { + // Filter table items by value. + var hidden = 0; + var shown = 0; + + // Hide / show elements. + $.each(table_row_names, function () { + var element = $(this).parents("tr"); + + if ($(this).text().indexOf(filter_value) === -1) { + // hide + element.addClass("hidden"); + hidden++; + } + else { + // show + element.removeClass("hidden"); + shown++; + } + }); + + // Show placeholder if no rows will be displayed. + if (no_rows.length > 0) { + if (shown === 0) { + // Show placeholder, hide table. + no_rows.show(); + table.hide(); + } + else { + // Hide placeholder, show table. + no_rows.hide(); + table.show(); + } + } + + // Manage dynamic header: + if (hidden > 0) { + // Calculate new dynamic sum values based on visible rows. + for (var column = 2; column < 20; column++) { + // Calculate summed value. + var cells = table_rows.find('td:nth-child(' + column + ')'); + if (!cells.length) { + // No more columns...! + break; + } + + var sum = 0, numer = 0, denom = 0; + $.each(cells.filter(':visible'), function () { + var ratio = $(this).data("ratio"); + if (ratio) { + var splitted = ratio.split(" "); + numer += parseInt(splitted[0], 10); + denom += parseInt(splitted[1], 10); + } + else { + sum += parseInt(this.innerHTML, 10); + } + }); + + // Get footer cell element. + var footer_cell = table_dynamic_footer.find('td:nth-child(' + column + ')'); + + // Set value into dynamic footer cell element. + if (cells[0].innerHTML.indexOf('%') > -1) { + // Percentage columns use the numerator and denominator, + // and adapt to the number of decimal places. + var match = /\.([0-9]+)/.exec(cells[0].innerHTML); + var places = 0; + if (match) { + places = match[1].length; + } + var pct = numer * 100 / denom; + footer_cell.text(pct.toFixed(places) + '%'); + } + else { + footer_cell.text(sum); + } + } + + // Hide standard footer, show dynamic footer. + table_footer.addClass("hidden"); + table_dynamic_footer.removeClass("hidden"); + } + else { + // Show standard footer, hide dynamic footer. + table_footer.removeClass("hidden"); + table_dynamic_footer.addClass("hidden"); + } + } + })); + + // Trigger change event on setup, to force filter on page refresh + // (filter value may still be present). + $("#filter").trigger("change"); +}; + +// Loaded on index.html +coverage.index_ready = function ($) { + // Look for a cookie containing previous sort settings: + var sort_list = []; + var cookie_name = "COVERAGE_INDEX_SORT"; + var i; + + // This almost makes it worth installing the jQuery cookie plugin: + if (document.cookie.indexOf(cookie_name) > -1) { + var cookies = document.cookie.split(";"); + for (i = 0; i < cookies.length; i++) { + var parts = cookies[i].split("="); + + if ($.trim(parts[0]) === cookie_name && parts[1]) { + sort_list = eval("[[" + parts[1] + "]]"); + break; + } + } + } + + // Create a new widget which exists only to save and restore + // the sort order: + $.tablesorter.addWidget({ + id: "persistentSort", + + // Format is called by the widget before displaying: + format: function (table) { + if (table.config.sortList.length === 0 && sort_list.length > 0) { + // This table hasn't been sorted before - we'll use + // our stored settings: + $(table).trigger('sorton', [sort_list]); + } + else { + // This is not the first load - something has + // already defined sorting so we'll just update + // our stored value to match: + sort_list = table.config.sortList; + } + } + }); + + // Configure our tablesorter to handle the variable number of + // columns produced depending on report options: + var headers = []; + var col_count = $("table.index > thead > tr > th").length; + + headers[0] = { sorter: 'text' }; + for (i = 1; i < col_count-1; i++) { + headers[i] = { sorter: 'digit' }; + } + headers[col_count-1] = { sorter: 'percent' }; + + // Enable the table sorter: + $("table.index").tablesorter({ + widgets: ['persistentSort'], + headers: headers + }); + + coverage.assign_shortkeys(); + coverage.wire_up_help_panel(); + coverage.wire_up_filter(); + + // Watch for page unload events so we can save the final sort settings: + $(window).unload(function () { + document.cookie = cookie_name + "=" + sort_list.toString() + "; path=/"; + }); +}; + +// -- pyfile stuff -- + +coverage.pyfile_ready = function ($) { + // If we're directed to a particular line number, highlight the line. + var frag = location.hash; + if (frag.length > 2 && frag[1] === 'n') { + $(frag).addClass('highlight'); + coverage.set_sel(parseInt(frag.substr(2), 10)); + } + else { + coverage.set_sel(0); + } + + $(document) + .bind('keydown', 'j', coverage.to_next_chunk_nicely) + .bind('keydown', 'k', coverage.to_prev_chunk_nicely) + .bind('keydown', '0', coverage.to_top) + .bind('keydown', '1', coverage.to_first_chunk) + ; + + $(".button_toggle_run").click(function (evt) {coverage.toggle_lines(evt.target, "run");}); + $(".button_toggle_exc").click(function (evt) {coverage.toggle_lines(evt.target, "exc");}); + $(".button_toggle_mis").click(function (evt) {coverage.toggle_lines(evt.target, "mis");}); + $(".button_toggle_par").click(function (evt) {coverage.toggle_lines(evt.target, "par");}); + + coverage.assign_shortkeys(); + coverage.wire_up_help_panel(); + + coverage.init_scroll_markers(); + + // Rebuild scroll markers after window high changing + $(window).resize(coverage.resize_scroll_markers); +}; + +coverage.toggle_lines = function (btn, cls) { + btn = $(btn); + var hide = "hide_"+cls; + if (btn.hasClass(hide)) { + $("#source ."+cls).removeClass(hide); + btn.removeClass(hide); + } + else { + $("#source ."+cls).addClass(hide); + btn.addClass(hide); + } +}; + +// Return the nth line div. +coverage.line_elt = function (n) { + return $("#t" + n); +}; + +// Return the nth line number div. +coverage.num_elt = function (n) { + return $("#n" + n); +}; + +// Return the container of all the code. +coverage.code_container = function () { + return $(".linenos"); +}; + +// Set the selection. b and e are line numbers. +coverage.set_sel = function (b, e) { + // The first line selected. + coverage.sel_begin = b; + // The next line not selected. + coverage.sel_end = (e === undefined) ? b+1 : e; +}; + +coverage.to_top = function () { + coverage.set_sel(0, 1); + coverage.scroll_window(0); +}; + +coverage.to_first_chunk = function () { + coverage.set_sel(0, 1); + coverage.to_next_chunk(); +}; + +coverage.is_transparent = function (color) { + // Different browsers return different colors for "none". + return color === "transparent" || color === "rgba(0, 0, 0, 0)"; +}; + +coverage.to_next_chunk = function () { + var c = coverage; + + // Find the start of the next colored chunk. + var probe = c.sel_end; + var color, probe_line; + while (true) { + probe_line = c.line_elt(probe); + if (probe_line.length === 0) { + return; + } + color = probe_line.css("background-color"); + if (!c.is_transparent(color)) { + break; + } + probe++; + } + + // There's a next chunk, `probe` points to it. + var begin = probe; + + // Find the end of this chunk. + var next_color = color; + while (next_color === color) { + probe++; + probe_line = c.line_elt(probe); + next_color = probe_line.css("background-color"); + } + c.set_sel(begin, probe); + c.show_selection(); +}; + +coverage.to_prev_chunk = function () { + var c = coverage; + + // Find the end of the prev colored chunk. + var probe = c.sel_begin-1; + var probe_line = c.line_elt(probe); + if (probe_line.length === 0) { + return; + } + var color = probe_line.css("background-color"); + while (probe > 0 && c.is_transparent(color)) { + probe--; + probe_line = c.line_elt(probe); + if (probe_line.length === 0) { + return; + } + color = probe_line.css("background-color"); + } + + // There's a prev chunk, `probe` points to its last line. + var end = probe+1; + + // Find the beginning of this chunk. + var prev_color = color; + while (prev_color === color) { + probe--; + probe_line = c.line_elt(probe); + prev_color = probe_line.css("background-color"); + } + c.set_sel(probe+1, end); + c.show_selection(); +}; + +// Return the line number of the line nearest pixel position pos +coverage.line_at_pos = function (pos) { + var l1 = coverage.line_elt(1), + l2 = coverage.line_elt(2), + result; + if (l1.length && l2.length) { + var l1_top = l1.offset().top, + line_height = l2.offset().top - l1_top, + nlines = (pos - l1_top) / line_height; + if (nlines < 1) { + result = 1; + } + else { + result = Math.ceil(nlines); + } + } + else { + result = 1; + } + return result; +}; + +// Returns 0, 1, or 2: how many of the two ends of the selection are on +// the screen right now? +coverage.selection_ends_on_screen = function () { + if (coverage.sel_begin === 0) { + return 0; + } + + var top = coverage.line_elt(coverage.sel_begin); + var next = coverage.line_elt(coverage.sel_end-1); + + return ( + (top.isOnScreen() ? 1 : 0) + + (next.isOnScreen() ? 1 : 0) + ); +}; + +coverage.to_next_chunk_nicely = function () { + coverage.finish_scrolling(); + if (coverage.selection_ends_on_screen() === 0) { + // The selection is entirely off the screen: select the top line on + // the screen. + var win = $(window); + coverage.select_line_or_chunk(coverage.line_at_pos(win.scrollTop())); + } + coverage.to_next_chunk(); +}; + +coverage.to_prev_chunk_nicely = function () { + coverage.finish_scrolling(); + if (coverage.selection_ends_on_screen() === 0) { + var win = $(window); + coverage.select_line_or_chunk(coverage.line_at_pos(win.scrollTop() + win.height())); + } + coverage.to_prev_chunk(); +}; + +// Select line number lineno, or if it is in a colored chunk, select the +// entire chunk +coverage.select_line_or_chunk = function (lineno) { + var c = coverage; + var probe_line = c.line_elt(lineno); + if (probe_line.length === 0) { + return; + } + var the_color = probe_line.css("background-color"); + if (!c.is_transparent(the_color)) { + // The line is in a highlighted chunk. + // Search backward for the first line. + var probe = lineno; + var color = the_color; + while (probe > 0 && color === the_color) { + probe--; + probe_line = c.line_elt(probe); + if (probe_line.length === 0) { + break; + } + color = probe_line.css("background-color"); + } + var begin = probe + 1; + + // Search forward for the last line. + probe = lineno; + color = the_color; + while (color === the_color) { + probe++; + probe_line = c.line_elt(probe); + color = probe_line.css("background-color"); + } + + coverage.set_sel(begin, probe); + } + else { + coverage.set_sel(lineno); + } +}; + +coverage.show_selection = function () { + var c = coverage; + + // Highlight the lines in the chunk + c.code_container().find(".highlight").removeClass("highlight"); + for (var probe = c.sel_begin; probe > 0 && probe < c.sel_end; probe++) { + c.num_elt(probe).addClass("highlight"); + } + + c.scroll_to_selection(); +}; + +coverage.scroll_to_selection = function () { + // Scroll the page if the chunk isn't fully visible. + if (coverage.selection_ends_on_screen() < 2) { + // Need to move the page. The html,body trick makes it scroll in all + // browsers, got it from http://stackoverflow.com/questions/3042651 + var top = coverage.line_elt(coverage.sel_begin); + var top_pos = parseInt(top.offset().top, 10); + coverage.scroll_window(top_pos - 30); + } +}; + +coverage.scroll_window = function (to_pos) { + $("html,body").animate({scrollTop: to_pos}, 200); +}; + +coverage.finish_scrolling = function () { + $("html,body").stop(true, true); +}; + +coverage.init_scroll_markers = function () { + var c = coverage; + // Init some variables + c.lines_len = $('td.text p').length; + c.body_h = $('body').height(); + c.header_h = $('div#header').height(); + c.missed_lines = $('td.text p.mis, td.text p.par'); + + // Build html + c.resize_scroll_markers(); +}; + +coverage.resize_scroll_markers = function () { + var c = coverage, + min_line_height = 3, + max_line_height = 10, + visible_window_h = $(window).height(); + + $('#scroll_marker').remove(); + // Don't build markers if the window has no scroll bar. + if (c.body_h <= visible_window_h) { + return; + } + + $("body").append("<div id='scroll_marker'> </div>"); + var scroll_marker = $('#scroll_marker'), + marker_scale = scroll_marker.height() / c.body_h, + line_height = scroll_marker.height() / c.lines_len; + + // Line height must be between the extremes. + if (line_height > min_line_height) { + if (line_height > max_line_height) { + line_height = max_line_height; + } + } + else { + line_height = min_line_height; + } + + var previous_line = -99, + last_mark, + last_top; + + c.missed_lines.each(function () { + var line_top = Math.round($(this).offset().top * marker_scale), + id_name = $(this).attr('id'), + line_number = parseInt(id_name.substring(1, id_name.length)); + + if (line_number === previous_line + 1) { + // If this solid missed block just make previous mark higher. + last_mark.css({ + 'height': line_top + line_height - last_top + }); + } + else { + // Add colored line in scroll_marker block. + scroll_marker.append('<div id="m' + line_number + '" class="marker"></div>'); + last_mark = $('#m' + line_number); + last_mark.css({ + 'height': line_height, + 'top': line_top + }); + last_top = line_top; + } + + previous_line = line_number; + }); +}; diff --git a/coverage_report/fluegg___init___py.html b/coverage_report/fluegg___init___py.html new file mode 100644 index 0000000..40a6073 --- /dev/null +++ b/coverage_report/fluegg___init___py.html @@ -0,0 +1,89 @@ + + + +<!DOCTYPE html> +<html> +<head> + <meta http-equiv="Content-Type" content="text/html; charset=utf-8"> + + + <meta http-equiv="X-UA-Compatible" content="IE=emulateIE7" /> + <title>Coverage for fluegg\__init__.py: 100%</title> + <link rel="stylesheet" href="style.css" type="text/css"> + + <script type="text/javascript" src="jquery.min.js"></script> + <script type="text/javascript" src="jquery.hotkeys.js"></script> + <script type="text/javascript" src="jquery.isonscreen.js"></script> + <script type="text/javascript" src="coverage_html.js"></script> + <script type="text/javascript"> + jQuery(document).ready(coverage.pyfile_ready); + </script> +</head> +<body class="pyfile"> + +<div id="header"> + <div class="content"> + <h1>Coverage for <b>fluegg\__init__.py</b> : + <span class="pc_cov">100%</span> + </h1> + + <img id="keyboard_icon" src="keybd_closed.png" alt="Show keyboard shortcuts" /> + + <h2 class="stats"> + 0 statements + <span class="run hide_run shortkey_r button_toggle_run">0 run</span> + <span class="mis shortkey_m button_toggle_mis">0 missing</span> + <span class="exc shortkey_x button_toggle_exc">0 excluded</span> + + + </h2> + </div> +</div> + +<div class="help_panel"> + <img id="panel_icon" src="keybd_open.png" alt="Hide keyboard shortcuts" /> + <p class="legend">Hot-keys on this page</p> + <div> + <p class="keyhelp"> + <span class="key">r</span> + <span class="key">m</span> + <span class="key">x</span> + <span class="key">p</span> toggle line displays + </p> + <p class="keyhelp"> + <span class="key">j</span> + <span class="key">k</span> next/prev highlighted chunk + </p> + <p class="keyhelp"> + <span class="key">0</span> (zero) top of page + </p> + <p class="keyhelp"> + <span class="key">1</span> (one) first highlighted chunk + </p> + </div> +</div> + +<div id="source"> + <table> + <tr> + <td class="linenos"> + + </td> + <td class="text"> + + </td> + </tr> + </table> +</div> + +<div id="footer"> + <div class="content"> + <p> + <a class="nav" href="index.html">« index</a> <a class="nav" href="https://coverage.readthedocs.io">coverage.py v4.5.3</a>, + created at 2019-07-09 15:15 + </p> + </div> +</div> + +</body> +</html> diff --git a/coverage_report/fluegg_asiancarpeggs_py.html b/coverage_report/fluegg_asiancarpeggs_py.html new file mode 100644 index 0000000..8838376 --- /dev/null +++ b/coverage_report/fluegg_asiancarpeggs_py.html @@ -0,0 +1,1305 @@ + + + +<!DOCTYPE html> +<html> +<head> + <meta http-equiv="Content-Type" content="text/html; charset=utf-8"> + + + <meta http-equiv="X-UA-Compatible" content="IE=emulateIE7" /> + <title>Coverage for fluegg\asiancarpeggs.py: 92%</title> + <link rel="stylesheet" href="style.css" type="text/css"> + + <script type="text/javascript" src="jquery.min.js"></script> + <script type="text/javascript" src="jquery.hotkeys.js"></script> + <script type="text/javascript" src="jquery.isonscreen.js"></script> + <script type="text/javascript" src="coverage_html.js"></script> + <script type="text/javascript"> + jQuery(document).ready(coverage.pyfile_ready); + </script> +</head> +<body class="pyfile"> + +<div id="header"> + <div class="content"> + <h1>Coverage for <b>fluegg\asiancarpeggs.py</b> : + <span class="pc_cov">92%</span> + </h1> + + <img id="keyboard_icon" src="keybd_closed.png" alt="Show keyboard shortcuts" /> + + <h2 class="stats"> + 226 statements + <span class="run hide_run shortkey_r button_toggle_run">209 run</span> + <span class="mis shortkey_m button_toggle_mis">17 missing</span> + <span class="exc shortkey_x button_toggle_exc">0 excluded</span> + + + </h2> + </div> +</div> + +<div class="help_panel"> + <img id="panel_icon" src="keybd_open.png" alt="Hide keyboard shortcuts" /> + <p class="legend">Hot-keys on this page</p> + <div> + <p class="keyhelp"> + <span class="key">r</span> + <span class="key">m</span> + <span class="key">x</span> + <span class="key">p</span> toggle line displays + </p> + <p class="keyhelp"> + <span class="key">j</span> + <span class="key">k</span> next/prev highlighted chunk + </p> + <p class="keyhelp"> + <span class="key">0</span> (zero) top of page + </p> + <p class="keyhelp"> + <span class="key">1</span> (one) first highlighted chunk + </p> + </div> +</div> + +<div id="source"> + <table> + <tr> + <td class="linenos"> +<p id="n1" class="stm run hide_run"><a href="#n1">1</a></p> +<p id="n2" class="pln"><a href="#n2">2</a></p> +<p id="n3" class="stm run hide_run"><a href="#n3">3</a></p> +<p id="n4" class="pln"><a href="#n4">4</a></p> +<p id="n5" class="stm 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href="#n469">469</a></p> +<p id="n470" class="stm run hide_run"><a href="#n470">470</a></p> +<p id="n471" class="stm run hide_run"><a href="#n471">471</a></p> +<p id="n472" class="pln"><a href="#n472">472</a></p> +<p id="n473" class="stm run hide_run"><a href="#n473">473</a></p> +<p id="n474" class="stm run hide_run"><a href="#n474">474</a></p> +<p id="n475" class="pln"><a href="#n475">475</a></p> +<p id="n476" class="stm run hide_run"><a href="#n476">476</a></p> +<p id="n477" class="stm run hide_run"><a href="#n477">477</a></p> +<p id="n478" class="pln"><a href="#n478">478</a></p> +<p id="n479" class="stm run hide_run"><a href="#n479">479</a></p> +<p id="n480" class="pln"><a href="#n480">480</a></p> +<p id="n481" class="pln"><a href="#n481">481</a></p> +<p id="n482" class="stm run hide_run"><a href="#n482">482</a></p> +<p id="n483" class="stm run hide_run"><a href="#n483">483</a></p> +<p id="n484" class="pln"><a href="#n484">484</a></p> +<p id="n485" class="pln"><a 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href="#n536">536</a></p> +<p id="n537" class="pln"><a href="#n537">537</a></p> +<p id="n538" class="pln"><a href="#n538">538</a></p> +<p id="n539" class="pln"><a href="#n539">539</a></p> +<p id="n540" class="pln"><a href="#n540">540</a></p> +<p id="n541" class="pln"><a href="#n541">541</a></p> +<p id="n542" class="stm run hide_run"><a href="#n542">542</a></p> +<p id="n543" class="stm run hide_run"><a href="#n543">543</a></p> +<p id="n544" class="stm run hide_run"><a href="#n544">544</a></p> +<p id="n545" class="stm run hide_run"><a href="#n545">545</a></p> +<p id="n546" class="pln"><a href="#n546">546</a></p> +<p id="n547" class="stm run hide_run"><a href="#n547">547</a></p> +<p id="n548" class="pln"><a href="#n548">548</a></p> +<p id="n549" class="pln"><a href="#n549">549</a></p> +<p id="n550" class="pln"><a href="#n550">550</a></p> +<p id="n551" class="pln"><a href="#n551">551</a></p> +<p id="n552" class="pln"><a href="#n552">552</a></p> +<p id="n553" class="pln"><a href="#n553">553</a></p> +<p id="n554" class="pln"><a href="#n554">554</a></p> +<p id="n555" class="stm run hide_run"><a href="#n555">555</a></p> +<p id="n556" class="stm run hide_run"><a href="#n556">556</a></p> +<p id="n557" class="stm run hide_run"><a href="#n557">557</a></p> +<p id="n558" class="pln"><a href="#n558">558</a></p> +<p id="n559" class="stm run hide_run"><a href="#n559">559</a></p> +<p id="n560" class="pln"><a href="#n560">560</a></p> +<p id="n561" class="pln"><a href="#n561">561</a></p> +<p id="n562" class="pln"><a href="#n562">562</a></p> +<p id="n563" class="pln"><a href="#n563">563</a></p> +<p id="n564" class="pln"><a href="#n564">564</a></p> +<p id="n565" class="pln"><a href="#n565">565</a></p> +<p id="n566" class="pln"><a href="#n566">566</a></p> +<p id="n567" class="stm run hide_run"><a href="#n567">567</a></p> +<p id="n568" class="stm run hide_run"><a href="#n568">568</a></p> +<p id="n569" class="stm run hide_run"><a href="#n569">569</a></p> +<p id="n570" class="stm run hide_run"><a href="#n570">570</a></p> +<p id="n571" class="pln"><a href="#n571">571</a></p> +<p id="n572" class="stm run hide_run"><a href="#n572">572</a></p> +<p id="n573" class="pln"><a href="#n573">573</a></p> +<p id="n574" class="pln"><a href="#n574">574</a></p> +<p id="n575" class="pln"><a href="#n575">575</a></p> +<p id="n576" class="pln"><a href="#n576">576</a></p> +<p id="n577" class="pln"><a href="#n577">577</a></p> +<p id="n578" class="pln"><a href="#n578">578</a></p> +<p id="n579" class="pln"><a href="#n579">579</a></p> +<p id="n580" class="stm run hide_run"><a href="#n580">580</a></p> +<p id="n581" class="stm run hide_run"><a href="#n581">581</a></p> +<p id="n582" class="stm run hide_run"><a href="#n582">582</a></p> +<p id="n583" class="stm run hide_run"><a href="#n583">583</a></p> +<p id="n584" class="pln"><a href="#n584">584</a></p> +<p id="n585" class="stm run hide_run"><a href="#n585">585</a></p> +<p id="n586" class="stm run hide_run"><a href="#n586">586</a></p> +<p id="n587" class="pln"><a href="#n587">587</a></p> +<p id="n588" class="stm run hide_run"><a href="#n588">588</a></p> +<p id="n589" class="stm run hide_run"><a href="#n589">589</a></p> +<p id="n590" class="pln"><a href="#n590">590</a></p> +<p id="n591" class="stm run hide_run"><a href="#n591">591</a></p> +<p id="n592" class="pln"><a href="#n592">592</a></p> +<p id="n593" class="pln"><a href="#n593">593</a></p> +<p id="n594" class="stm run hide_run"><a href="#n594">594</a></p> +<p id="n595" class="stm run hide_run"><a href="#n595">595</a></p> +<p id="n596" class="pln"><a href="#n596">596</a></p> +<p id="n597" class="pln"><a href="#n597">597</a></p> +<p id="n598" class="pln"><a href="#n598">598</a></p> +<p id="n599" class="pln"><a href="#n599">599</a></p> +<p id="n600" class="pln"><a href="#n600">600</a></p> +<p id="n601" class="pln"><a href="#n601">601</a></p> +<p id="n602" class="pln"><a href="#n602">602</a></p> +<p id="n603" class="pln"><a href="#n603">603</a></p> +<p id="n604" class="pln"><a href="#n604">604</a></p> +<p id="n605" class="stm run hide_run"><a href="#n605">605</a></p> +<p id="n606" class="stm run hide_run"><a href="#n606">606</a></p> +<p id="n607" class="stm run hide_run"><a href="#n607">607</a></p> +<p id="n608" class="stm run hide_run"><a href="#n608">608</a></p> + + </td> + <td class="text"> +<p id="t1" class="stm run hide_run"><span class="key">from</span> <span class="nam">abc</span> <span class="key">import</span> <span class="nam">abstractmethod</span><span class="strut"> </span></p> +<p id="t2" class="pln"><span class="strut"> </span></p> +<p id="t3" class="stm run hide_run"><span class="key">import</span> <span class="nam">numpy</span> <span class="key">as</span> <span class="nam">np</span><span class="strut"> </span></p> +<p id="t4" class="pln"><span class="strut"> </span></p> +<p id="t5" class="stm run hide_run"><span class="key">from</span> <span class="nam">fluegg</span><span class="op">.</span><span class="nam">drift</span> <span class="key">import</span> <span class="nam">DriftingParticle</span><span class="strut"> </span></p> +<p id="t6" class="stm run hide_run"><span class="key">from</span> <span class="nam">fluegg</span><span class="op">.</span><span class="nam">random</span> <span class="key">import</span> <span class="nam">NormalRandomNumbers</span><span class="strut"> </span></p> +<p id="t7" class="pln"><span class="strut"> </span></p> +<p id="t8" class="pln"><span class="strut"> </span></p> +<p id="t9" class="stm run hide_run"><span class="key">class</span> <span class="nam">CarpEggs</span><span class="op">(</span><span class="nam">DriftingParticle</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t10" class="pln"> <span class="str">"""Class representing a collection of carp eggs</span><span class="strut"> </span></p> +<p id="t11" class="pln"><span class="strut"> </span></p> +<p id="t12" class="pln"><span class="str"> Parameters</span><span class="strut"> </span></p> +<p id="t13" class="pln"><span class="str"> ----------</span><span class="strut"> </span></p> +<p id="t14" class="pln"><span class="str"> initial_position : numpy.ndarray</span><span class="strut"> </span></p> +<p id="t15" class="pln"><span class="str"> Must be an n by 3 array, where n is the number of eggs</span><span class="strut"> </span></p> +<p id="t16" class="pln"><span class="strut"> </span></p> +<p id="t17" class="pln"><span class="str"> simulation_clock : simulation.SimulationClock</span><span class="strut"> </span></p> +<p id="t18" class="pln"><span class="str"> Simulation clock</span><span class="strut"> </span></p> +<p id="t19" class="pln"><span class="strut"> </span></p> +<p id="t20" class="pln"><span class="str"> random_numbers : fluegg.random.RandomNumbers, optional</span><span class="strut"> </span></p> +<p id="t21" class="pln"><span class="str"> Random number source</span><span class="strut"> </span></p> +<p id="t22" class="pln"><span class="strut"> </span></p> +<p id="t23" class="pln"><span class="str"> characteristic_temperature : float, optional</span><span class="strut"> </span></p> +<p id="t24" class="pln"><span class="str"> The default is None</span><span class="strut"> </span></p> +<p id="t25" class="pln"><span class="strut"> </span></p> +<p id="t26" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t27" class="pln"><span class="strut"> </span></p> +<p id="t28" class="stm run hide_run"> <span class="nam">_reference_temperature</span> <span class="op">=</span> <span class="num">22</span> <span class="com"># degrees Celsius</span><span class="strut"> </span></p> +<p id="t29" class="pln"><span class="strut"> </span></p> +<p id="t30" class="stm run hide_run"> <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">initial_position</span><span class="op">,</span> <span class="nam">simulation_clock</span><span class="op">,</span> <span class="nam">random_numbers</span><span class="op">=</span><span class="key">None</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t31" class="pln"> <span class="nam">characteristic_temperature</span><span class="op">=</span><span class="key">None</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t32" class="pln"><span class="strut"> </span></p> +<p id="t33" class="stm run hide_run"> <span class="key">if</span> <span class="nam">initial_position</span><span class="op">.</span><span class="nam">shape</span><span class="op">[</span><span class="num">1</span><span class="op">]</span> <span class="op">==</span> <span class="num">3</span> <span class="key">and</span> <span class="nam">initial_position</span><span class="op">.</span><span class="nam">ndim</span> <span class="op">==</span> <span class="num">2</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t34" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_position</span> <span class="op">=</span> <span class="nam">initial_position</span><span class="strut"> </span></p> +<p id="t35" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_number_of_eggs</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_position</span><span class="op">.</span><span class="nam">shape</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t36" class="pln"> <span class="key">else</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t37" class="stm run hide_run"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="str">'Initial position array must be n by 3'</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t38" class="pln"><span class="strut"> </span></p> +<p id="t39" class="stm run hide_run"> <span class="key">if</span> <span class="nam">random_numbers</span> <span class="key">is</span> <span class="key">None</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t40" class="stm run hide_run"> <span class="nam">random_numbers</span> <span class="op">=</span> <span class="nam">NormalRandomNumbers</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t41" class="pln"><span class="strut"> </span></p> +<p id="t42" class="pln"> <span class="com"># Note: Diameters internally stored in mm, diameter() outputs in m</span><span class="strut"> </span></p> +<p id="t43" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_simulation_clock</span> <span class="op">=</span> <span class="nam">simulation_clock</span><span class="strut"> </span></p> +<p id="t44" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_diameter_array</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_init_diameter_array</span><span class="op">(</span><span class="nam">random_numbers</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t45" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_reference_density_array</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_init_reference_density_array</span><span class="op">(</span><span class="strut"> </span></p> +<p id="t46" class="pln"> <span class="nam">random_numbers</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t47" class="pln"><span class="strut"> </span></p> +<p id="t48" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_hatching_time</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">hatching_time</span><span class="op">(</span><span class="nam">characteristic_temperature</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t49" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_gas_bladder_inflation_time</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">gas_bladder_inflation_time</span><span class="op">(</span><span class="strut"> </span></p> +<p id="t50" class="pln"> <span class="nam">characteristic_temperature</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t51" class="pln"><span class="strut"> </span></p> +<p id="t52" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_calc_density_std</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">a</span><span class="op">,</span> <span class="nam">b</span><span class="op">,</span> <span class="nam">c</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t53" class="pln"> <span class="str">"""Returns an array of the density standard deviation (kg/m**3)</span><span class="strut"> </span></p> +<p id="t54" class="pln"><span class="str"> of the collection of carp eggs at each time step</span><span class="strut"> </span></p> +<p id="t55" class="pln"><span class="strut"> </span></p> +<p id="t56" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t57" class="stm run hide_run"> <span class="nam">time_array</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_simulation_clock</span><span class="op">.</span><span class="nam">time_array</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t58" class="stm run hide_run"> <span class="key">return</span> <span class="nam">a</span> <span class="op">*</span> <span class="nam">np</span><span class="op">.</span><span class="nam">exp</span><span class="op">(</span><span class="op">-</span><span class="nam">time_array</span> <span class="op">/</span> <span class="nam">b</span><span class="op">)</span> <span class="op">+</span> <span class="nam">c</span><span class="strut"> </span></p> +<p id="t59" class="pln"><span class="strut"> </span></p> +<p id="t60" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_calc_diameter_std</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">a</span><span class="op">,</span> <span class="nam">b</span><span class="op">,</span> <span class="nam">c</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t61" class="pln"> <span class="str">"""Returns an array of the diameter standard deviation (mm)</span><span class="strut"> </span></p> +<p id="t62" class="pln"><span class="str"> of the collection of carp eggs at each time step</span><span class="strut"> </span></p> +<p id="t63" class="pln"><span class="strut"> </span></p> +<p id="t64" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t65" class="stm run hide_run"> <span class="nam">time_array</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_simulation_clock</span><span class="op">.</span><span class="nam">time_array</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t66" class="stm run hide_run"> <span class="key">return</span> <span class="nam">a</span> <span class="op">*</span> <span class="nam">np</span><span class="op">.</span><span class="nam">exp</span><span class="op">(</span><span class="op">-</span><span class="nam">time_array</span> <span class="op">/</span> <span class="nam">b</span><span class="op">)</span> <span class="op">+</span> <span class="nam">c</span><span class="strut"> </span></p> +<p id="t67" class="pln"><span class="strut"> </span></p> +<p id="t68" class="stm run hide_run"> <span class="op">@</span><span class="nam">classmethod</span><span class="strut"> </span></p> +<p id="t69" class="pln"> <span class="key">def</span> <span class="nam">_calc_gas_bladder_inflation_time</span><span class="op">(</span><span class="nam">cls</span><span class="op">,</span> <span class="nam">tmin2</span><span class="op">,</span> <span class="nam">meanctu_gas_bladder</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t70" class="pln"> <span class="nam">characteristic_temperature</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t71" class="pln"><span class="strut"> </span></p> +<p id="t72" class="stm run hide_run"> <span class="key">if</span> <span class="nam">characteristic_temperature</span> <span class="key">is</span> <span class="key">None</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t73" class="stm run hide_run"> <span class="nam">characteristic_temperature</span> <span class="op">=</span> <span class="nam">cls</span><span class="op">.</span><span class="nam">_reference_temperature</span><span class="strut"> </span></p> +<p id="t74" class="pln"><span class="strut"> </span></p> +<p id="t75" class="pln"> <span class="com"># gas bladder inflation time in hours to seconds</span><span class="strut"> </span></p> +<p id="t76" class="stm run hide_run"> <span class="key">return</span> <span class="nam">meanctu_gas_bladder</span><span class="op">/</span><span class="op">(</span><span class="nam">characteristic_temperature</span> <span class="op">-</span> <span class="nam">tmin2</span><span class="op">)</span> <span class="op">*</span> <span class="num">3600</span><span class="strut"> </span></p> +<p id="t77" class="pln"><span class="strut"> </span></p> +<p id="t78" class="stm run hide_run"> <span class="op">@</span><span class="nam">classmethod</span><span class="strut"> </span></p> +<p id="t79" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_calc_hatching_time</span><span class="op">(</span><span class="nam">cls</span><span class="op">,</span> <span class="nam">a</span><span class="op">,</span> <span class="nam">b</span><span class="op">,</span> <span class="nam">c</span><span class="op">,</span> <span class="nam">temperature</span><span class="op">=</span><span class="key">None</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t80" class="pln"> <span class="str">"""Returns the hatching time (hours) of the collection of eggs</span><span class="strut"> </span></p> +<p id="t81" class="pln"><span class="strut"> </span></p> +<p id="t82" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t83" class="pln"><span class="strut"> </span></p> +<p id="t84" class="stm run hide_run"> <span class="key">if</span> <span class="nam">temperature</span> <span class="key">is</span> <span class="key">None</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t85" class="stm run hide_run"> <span class="nam">temperature</span> <span class="op">=</span> <span class="nam">cls</span><span class="op">.</span><span class="nam">_reference_temperature</span><span class="strut"> </span></p> +<p id="t86" class="pln"><span class="strut"> </span></p> +<p id="t87" class="stm run hide_run"> <span class="key">return</span> <span class="num">3600</span> <span class="op">*</span> <span class="op">(</span><span class="nam">a</span> <span class="op">*</span> <span class="nam">temperature</span> <span class="op">**</span> <span class="nam">b</span> <span class="op">+</span> <span class="nam">c</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t88" class="pln"><span class="strut"> </span></p> +<p id="t89" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_calc_mean_density</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">a</span><span class="op">,</span> <span class="nam">b</span><span class="op">,</span> <span class="nam">c</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t90" class="pln"> <span class="str">"""Returns an array of the mean density (kg/m**3) of the collection</span><span class="strut"> </span></p> +<p id="t91" class="pln"><span class="str"> of carp eggs at each time step</span><span class="strut"> </span></p> +<p id="t92" class="pln"><span class="strut"> </span></p> +<p id="t93" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t94" class="stm run hide_run"> <span class="nam">time_array</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_simulation_clock</span><span class="op">.</span><span class="nam">time_array</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t95" class="stm run hide_run"> <span class="key">return</span> <span class="nam">a</span> <span class="op">*</span> <span class="nam">np</span><span class="op">.</span><span class="nam">exp</span><span class="op">(</span><span class="op">-</span><span class="nam">time_array</span> <span class="op">/</span> <span class="nam">b</span><span class="op">)</span> <span class="op">+</span> <span class="nam">c</span><span class="strut"> </span></p> +<p id="t96" class="pln"><span class="strut"> </span></p> +<p id="t97" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_calc_mean_diameter</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">a</span><span class="op">,</span> <span class="nam">b</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t98" class="pln"> <span class="str">"""Returns an array of the mean diameter (mm) of the collection</span><span class="strut"> </span></p> +<p id="t99" class="pln"><span class="str"> of carp eggs at each time step</span><span class="strut"> </span></p> +<p id="t100" class="pln"><span class="strut"> </span></p> +<p id="t101" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t102" class="stm run hide_run"> <span class="nam">time_array</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_simulation_clock</span><span class="op">.</span><span class="nam">time_array</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t103" class="stm run hide_run"> <span class="key">return</span> <span class="nam">a</span> <span class="op">*</span> <span class="op">(</span><span class="num">1</span> <span class="op">-</span> <span class="nam">np</span><span class="op">.</span><span class="nam">exp</span><span class="op">(</span><span class="op">-</span><span class="nam">time_array</span> <span class="op">/</span> <span class="nam">b</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t104" class="pln"><span class="strut"> </span></p> +<p id="t105" class="stm run hide_run"> <span class="op">@</span><span class="nam">staticmethod</span><span class="strut"> </span></p> +<p id="t106" class="stm run hide_run"> <span class="op">@</span><span class="nam">abstractmethod</span><span class="strut"> </span></p> +<p id="t107" class="pln"> <span class="key">def</span> <span class="nam">_check_density_range</span><span class="op">(</span><span class="nam">density_array</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t108" class="stm mis"> <span class="key">raise</span> <span class="nam">NotImplementedError</span><span class="strut"> </span></p> +<p id="t109" class="pln"><span class="strut"> </span></p> +<p id="t110" class="stm run hide_run"> <span class="op">@</span><span class="nam">staticmethod</span><span class="strut"> </span></p> +<p id="t111" class="stm run hide_run"> <span class="op">@</span><span class="nam">abstractmethod</span><span class="strut"> </span></p> +<p id="t112" class="pln"> <span class="key">def</span> <span class="nam">_check_diameter_range</span><span class="op">(</span><span class="nam">diameter_array</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t113" class="stm mis"> <span class="key">raise</span> <span class="nam">NotImplementedError</span><span class="strut"> </span></p> +<p id="t114" class="pln"><span class="strut"> </span></p> +<p id="t115" class="stm run hide_run"> <span class="op">@</span><span class="nam">abstractmethod</span><span class="strut"> </span></p> +<p id="t116" class="pln"> <span class="key">def</span> <span class="nam">_mean_density</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t117" class="stm mis"> <span class="key">raise</span> <span class="nam">NotImplementedError</span><span class="strut"> </span></p> +<p id="t118" class="pln"><span class="strut"> </span></p> +<p id="t119" class="stm run hide_run"> <span class="op">@</span><span class="nam">abstractmethod</span><span class="strut"> </span></p> +<p id="t120" class="pln"> <span class="key">def</span> <span class="nam">_mean_diameter</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t121" class="stm mis"> <span class="key">raise</span> <span class="nam">NotImplementedError</span><span class="strut"> </span></p> +<p id="t122" class="pln"><span class="strut"> </span></p> +<p id="t123" class="stm run hide_run"> <span class="op">@</span><span class="nam">abstractmethod</span><span class="strut"> </span></p> +<p id="t124" class="pln"> <span class="key">def</span> <span class="nam">_density_std</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t125" class="stm mis"> <span class="key">raise</span> <span class="nam">NotImplementedError</span><span class="strut"> </span></p> +<p id="t126" class="pln"><span class="strut"> </span></p> +<p id="t127" class="stm run hide_run"> <span class="op">@</span><span class="nam">abstractmethod</span><span class="strut"> </span></p> +<p id="t128" class="pln"> <span class="key">def</span> <span class="nam">_diameter_std</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t129" class="stm mis"> <span class="key">raise</span> <span class="nam">NotImplementedError</span><span class="strut"> </span></p> +<p id="t130" class="pln"><span class="strut"> </span></p> +<p id="t131" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_init_diameter_array</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">random_numbers</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t132" class="pln"> <span class="str">"""Returns an array of the diameter (mm) of the collection</span><span class="strut"> </span></p> +<p id="t133" class="pln"><span class="str"> of carp eggs at each time step pulled from a normal distribution</span><span class="strut"> </span></p> +<p id="t134" class="pln"><span class="strut"> </span></p> +<p id="t135" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t136" class="stm run hide_run"> <span class="nam">mean_diameter</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_mean_diameter</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t137" class="stm run hide_run"> <span class="nam">diameter_std</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_diameter_std</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t138" class="pln"><span class="strut"> </span></p> +<p id="t139" class="stm run hide_run"> <span class="nam">diameter_array</span> <span class="op">=</span> <span class="nam">random_numbers</span><span class="op">.</span><span class="nam">random</span><span class="op">(</span><span class="nam">mean_diameter</span><span class="op">,</span> <span class="nam">diameter_std</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t140" class="pln"><span class="strut"> </span></p> +<p id="t141" class="stm run hide_run"> <span class="nam">low_outliers</span> <span class="op">=</span> <span class="nam">mean_diameter</span> <span class="op">-</span> <span class="nam">diameter_std</span><span class="strut"> </span></p> +<p id="t142" class="stm run hide_run"> <span class="nam">high_outliers</span> <span class="op">=</span> <span class="nam">mean_diameter</span> <span class="op">+</span> <span class="nam">diameter_std</span><span class="strut"> </span></p> +<p id="t143" class="pln"><span class="strut"> </span></p> +<p id="t144" class="stm run hide_run"> <span class="nam">outlier_index</span> <span class="op">=</span> <span class="op">(</span><span class="nam">diameter_array</span> <span class="op"><=</span> <span class="nam">low_outliers</span><span class="op">)</span> <span class="op">&</span> <span class="op">(</span><span class="strut"> </span></p> +<p id="t145" class="pln"> <span class="nam">high_outliers</span> <span class="op"><=</span> <span class="nam">diameter_array</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t146" class="pln"><span class="strut"> </span></p> +<p id="t147" class="stm run hide_run"> <span class="key">while</span> <span class="nam">np</span><span class="op">.</span><span class="nam">any</span><span class="op">(</span><span class="nam">outlier_index</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t148" class="stm mis"> <span class="nam">diameter_array</span><span class="op">[</span><span class="nam">outlier_index</span><span class="op">]</span> <span class="op">=</span> <span class="nam">random_numbers</span><span class="op">.</span><span class="nam">random</span><span class="op">(</span><span class="strut"> </span></p> +<p id="t149" class="pln"> <span class="nam">mean_diameter</span><span class="op">[</span><span class="nam">outlier_index</span><span class="op">]</span><span class="op">,</span> <span class="nam">diameter_std</span><span class="op">[</span><span class="nam">outlier_index</span><span class="op">]</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t150" class="stm mis"> <span class="nam">outlier_index</span> <span class="op">=</span> <span class="op">(</span><span class="nam">diameter_array</span> <span class="op"><=</span> <span class="nam">low_outliers</span><span class="op">)</span> <span class="op">&</span> <span class="op">(</span><span class="strut"> </span></p> +<p id="t151" class="pln"> <span class="nam">high_outliers</span> <span class="op"><=</span> <span class="nam">diameter_array</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t152" class="pln"><span class="strut"> </span></p> +<p id="t153" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_check_diameter_range</span><span class="op">(</span><span class="nam">diameter_array</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t154" class="pln"><span class="strut"> </span></p> +<p id="t155" class="stm run hide_run"> <span class="key">return</span> <span class="nam">diameter_array</span><span class="strut"> </span></p> +<p id="t156" class="pln"><span class="strut"> </span></p> +<p id="t157" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_init_reference_density_array</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">random_numbers</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t158" class="pln"> <span class="str">"""Returns an array of the density (kg/m**3) of the collection</span><span class="strut"> </span></p> +<p id="t159" class="pln"><span class="str"> of carp eggs at each time step pulled from a normal distribution</span><span class="strut"> </span></p> +<p id="t160" class="pln"><span class="strut"> </span></p> +<p id="t161" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t162" class="stm run hide_run"> <span class="nam">mean_density</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_mean_density</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t163" class="stm run hide_run"> <span class="nam">density_std</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_density_std</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t164" class="pln"><span class="strut"> </span></p> +<p id="t165" class="stm run hide_run"> <span class="nam">density_array</span> <span class="op">=</span> <span class="nam">random_numbers</span><span class="op">.</span><span class="nam">random</span><span class="op">(</span><span class="nam">mean_density</span><span class="op">,</span> <span class="nam">density_std</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t166" class="pln"><span class="strut"> </span></p> +<p id="t167" class="stm run hide_run"> <span class="nam">low_outliers</span> <span class="op">=</span> <span class="nam">mean_density</span> <span class="op">-</span> <span class="nam">density_std</span><span class="strut"> </span></p> +<p id="t168" class="stm run hide_run"> <span class="nam">high_outliers</span> <span class="op">=</span> <span class="nam">mean_density</span> <span class="op">+</span> <span class="nam">density_std</span><span class="strut"> </span></p> +<p id="t169" class="pln"><span class="strut"> </span></p> +<p id="t170" class="stm run hide_run"> <span class="nam">outlier_index</span> <span class="op">=</span> <span class="op">(</span><span class="nam">density_array</span> <span class="op"><=</span> <span class="nam">low_outliers</span><span class="op">)</span> <span class="op">&</span> <span class="op">(</span><span class="strut"> </span></p> +<p id="t171" class="pln"> <span class="nam">high_outliers</span> <span class="op"><=</span> <span class="nam">density_array</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t172" class="pln"><span class="strut"> </span></p> +<p id="t173" class="stm run hide_run"> <span class="key">while</span> <span class="nam">np</span><span class="op">.</span><span class="nam">any</span><span class="op">(</span><span class="nam">outlier_index</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t174" class="stm mis"> <span class="nam">density_array</span><span class="op">[</span><span class="nam">outlier_index</span><span class="op">]</span> <span class="op">=</span> <span class="nam">random_numbers</span><span class="op">.</span><span class="nam">random</span><span class="op">(</span><span class="strut"> </span></p> +<p id="t175" class="pln"> <span class="nam">mean_density</span><span class="op">[</span><span class="nam">outlier_index</span><span class="op">]</span><span class="op">,</span> <span class="nam">density_std</span><span class="op">[</span><span class="nam">outlier_index</span><span class="op">]</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t176" class="stm mis"> <span class="nam">outlier_index</span> <span class="op">=</span> <span class="op">(</span><span class="nam">density_array</span> <span class="op"><=</span> <span class="nam">low_outliers</span><span class="op">)</span> <span class="op">&</span> <span class="op">(</span><span class="strut"> </span></p> +<p id="t177" class="pln"> <span class="nam">high_outliers</span> <span class="op"><=</span> <span class="nam">density_array</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t178" class="pln"><span class="strut"> </span></p> +<p id="t179" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_check_density_range</span><span class="op">(</span><span class="nam">density_array</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t180" class="pln"><span class="strut"> </span></p> +<p id="t181" class="stm run hide_run"> <span class="key">return</span> <span class="nam">density_array</span><span class="strut"> </span></p> +<p id="t182" class="pln"><span class="strut"> </span></p> +<p id="t183" class="stm run hide_run"> <span class="key">def</span> <span class="nam">density</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">temperature</span><span class="op">=</span><span class="key">None</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t184" class="pln"> <span class="str">"""Returns the density of the collection of eggs</span><span class="strut"> </span></p> +<p id="t185" class="pln"><span class="strut"> </span></p> +<p id="t186" class="pln"><span class="str"> Parameters</span><span class="strut"> </span></p> +<p id="t187" class="pln"><span class="str"> ----------</span><span class="strut"> </span></p> +<p id="t188" class="pln"><span class="str"> temperature : float</span><span class="strut"> </span></p> +<p id="t189" class="pln"><span class="str"> the temperature of the eggs (Celsius)</span><span class="strut"> </span></p> +<p id="t190" class="pln"><span class="strut"> </span></p> +<p id="t191" class="pln"><span class="str"> Returns</span><span class="strut"> </span></p> +<p id="t192" class="pln"><span class="str"> -------</span><span class="strut"> </span></p> +<p id="t193" class="pln"><span class="str"> float</span><span class="strut"> </span></p> +<p id="t194" class="pln"><span class="strut"> </span></p> +<p id="t195" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t196" class="pln"><span class="strut"> </span></p> +<p id="t197" class="stm run hide_run"> <span class="key">if</span> <span class="nam">temperature</span> <span class="key">is</span> <span class="key">None</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t198" class="stm mis"> <span class="nam">temperature</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_reference_temperature</span><span class="strut"> </span></p> +<p id="t199" class="stm run hide_run"> <span class="nam">density_index</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_simulation_clock</span><span class="op">.</span><span class="nam">current_time_index</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t200" class="stm run hide_run"> <span class="nam">reference_density</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_reference_density_array</span><span class="op">[</span><span class="nam">density_index</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t201" class="stm run hide_run"> <span class="key">return</span> <span class="nam">reference_density</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t202" class="pln"> <span class="op">+</span> <span class="num">0.20646</span><span class="op">*</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_reference_temperature</span> <span class="op">-</span> <span class="nam">temperature</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t203" class="pln"><span class="strut"> </span></p> +<p id="t204" class="stm run hide_run"> <span class="key">def</span> <span class="nam">diameter</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t205" class="pln"> <span class="str">"""Returns the diameter of the collection of eggs in m</span><span class="strut"> </span></p> +<p id="t206" class="pln"><span class="strut"> </span></p> +<p id="t207" class="pln"><span class="str"> Returns</span><span class="strut"> </span></p> +<p id="t208" class="pln"><span class="str"> -------</span><span class="strut"> </span></p> +<p id="t209" class="pln"><span class="str"> float</span><span class="strut"> </span></p> +<p id="t210" class="pln"><span class="strut"> </span></p> +<p id="t211" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t212" class="stm run hide_run"> <span class="nam">diameter_index</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_simulation_clock</span><span class="op">.</span><span class="nam">current_time_index</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t213" class="pln"> <span class="com"># Convert from mm to m</span><span class="strut"> </span></p> +<p id="t214" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_diameter_array</span><span class="op">[</span><span class="nam">diameter_index</span><span class="op">]</span> <span class="op">/</span> <span class="num">1000</span><span class="strut"> </span></p> +<p id="t215" class="pln"><span class="strut"> </span></p> +<p id="t216" class="stm run hide_run"> <span class="key">def</span> <span class="nam">fall_velocity</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">hydraulic_results</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t217" class="pln"> <span class="str">"""Returns fall velocity</span><span class="strut"> </span></p> +<p id="t218" class="pln"><span class="strut"> </span></p> +<p id="t219" class="pln"><span class="str"> Parameters</span><span class="strut"> </span></p> +<p id="t220" class="pln"><span class="str"> ----------</span><span class="strut"> </span></p> +<p id="t221" class="pln"><span class="str"> hydraulic_results : numpy.ndarray</span><span class="strut"> </span></p> +<p id="t222" class="pln"><span class="str"> Hydrauilc results</span><span class="strut"> </span></p> +<p id="t223" class="pln"><span class="strut"> </span></p> +<p id="t224" class="pln"><span class="str"> Returns</span><span class="strut"> </span></p> +<p id="t225" class="pln"><span class="str"> -------</span><span class="strut"> </span></p> +<p id="t226" class="pln"><span class="str"> numpy.ndarray</span><span class="strut"> </span></p> +<p id="t227" class="pln"><span class="strut"> </span></p> +<p id="t228" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t229" class="pln"><span class="strut"> </span></p> +<p id="t230" class="stm mis"> <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_simulation_clock</span><span class="op">.</span><span class="nam">current_time</span><span class="op">(</span><span class="op">)</span> <span class="op">></span> <span class="nam">self</span><span class="op">.</span><span class="nam">_hatching_time</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t231" class="stm mis"> <span class="nam">fall_velocity</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">zeros</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_position</span><span class="op">.</span><span class="nam">shape</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t232" class="pln"> <span class="key">else</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t233" class="stm mis"> <span class="nam">fall_velocity</span> <span class="op">=</span> <span class="nam">super</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">fall_velocity</span><span class="op">(</span><span class="nam">hydraulic_results</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t234" class="pln"><span class="strut"> </span></p> +<p id="t235" class="stm mis"> <span class="key">return</span> <span class="nam">fall_velocity</span><span class="strut"> </span></p> +<p id="t236" class="pln"><span class="strut"> </span></p> +<p id="t237" class="stm run hide_run"> <span class="op">@</span><span class="nam">classmethod</span><span class="strut"> </span></p> +<p id="t238" class="stm run hide_run"> <span class="op">@</span><span class="nam">abstractmethod</span><span class="strut"> </span></p> +<p id="t239" class="stm run hide_run"> <span class="key">def</span> <span class="nam">gas_bladder_inflation_time</span><span class="op">(</span><span class="nam">cls</span><span class="op">,</span> <span class="nam">temperature</span><span class="op">=</span><span class="key">None</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t240" class="stm mis"> <span class="key">raise</span> <span class="nam">NotImplementedError</span><span class="strut"> </span></p> +<p id="t241" class="pln"><span class="strut"> </span></p> +<p id="t242" class="stm run hide_run"> <span class="op">@</span><span class="nam">classmethod</span><span class="strut"> </span></p> +<p id="t243" class="stm run hide_run"> <span class="op">@</span><span class="nam">abstractmethod</span><span class="strut"> </span></p> +<p id="t244" class="stm run hide_run"> <span class="key">def</span> <span class="nam">hatching_time</span><span class="op">(</span><span class="nam">cls</span><span class="op">,</span> <span class="nam">temperature</span><span class="op">=</span><span class="key">None</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t245" class="stm mis"> <span class="key">raise</span> <span class="nam">NotImplementedError</span><span class="strut"> </span></p> +<p id="t246" class="pln"><span class="strut"> </span></p> +<p id="t247" class="stm run hide_run"> <span class="key">def</span> <span class="nam">position</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t248" class="pln"> <span class="str">"""Returns the 3D positions of the collection of eggs in meters</span><span class="strut"> </span></p> +<p id="t249" class="pln"><span class="strut"> </span></p> +<p id="t250" class="pln"><span class="str"> The shape of the returned array is (number_of_eggs, 3)</span><span class="strut"> </span></p> +<p id="t251" class="pln"><span class="strut"> </span></p> +<p id="t252" class="pln"><span class="str"> Returns</span><span class="strut"> </span></p> +<p id="t253" class="pln"><span class="str"> -------</span><span class="strut"> </span></p> +<p id="t254" class="pln"><span class="str"> numpy.ndarray</span><span class="strut"> </span></p> +<p id="t255" class="pln"><span class="strut"> </span></p> +<p id="t256" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t257" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_position</span><span class="strut"> </span></p> +<p id="t258" class="pln"><span class="strut"> </span></p> +<p id="t259" class="stm run hide_run"> <span class="key">def</span> <span class="nam">set_position</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">position</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t260" class="pln"> <span class="str">"""Sets the 3D positions of the collection of eggs</span><span class="strut"> </span></p> +<p id="t261" class="pln"><span class="strut"> </span></p> +<p id="t262" class="pln"><span class="str"> :param: positions of the colllection of eggs (m)</span><span class="strut"> </span></p> +<p id="t263" class="pln"><span class="str"> :type: numpy.ndarray(number_of_eggs, 3)</span><span class="strut"> </span></p> +<p id="t264" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t265" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_position</span> <span class="op">=</span> <span class="nam">position</span><span class="strut"> </span></p> +<p id="t266" class="pln"><span class="strut"> </span></p> +<p id="t267" class="pln"><span class="strut"> </span></p> +<p id="t268" class="stm run hide_run"><span class="key">class</span> <span class="nam">BigheadCarpEggs</span><span class="op">(</span><span class="nam">CarpEggs</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t269" class="pln"> <span class="str">"""Class representing a collection of Bighead carp egg</span><span class="strut"> </span></p> +<p id="t270" class="pln"><span class="strut"> </span></p> +<p id="t271" class="pln"><span class="str"> See CarpEggs for accurate signature.</span><span class="strut"> </span></p> +<p id="t272" class="pln"><span class="strut"> </span></p> +<p id="t273" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t274" class="pln"><span class="strut"> </span></p> +<p id="t275" class="stm run hide_run"> <span class="op">@</span><span class="nam">staticmethod</span><span class="strut"> </span></p> +<p id="t276" class="pln"> <span class="key">def</span> <span class="nam">_check_density_range</span><span class="op">(</span><span class="nam">density_array</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t277" class="pln"> <span class="str">"""Modifies input array so any outlier densities are set</span><span class="strut"> </span></p> +<p id="t278" class="pln"><span class="str"> to the respective min or max of the range</span><span class="strut"> </span></p> +<p id="t279" class="pln"><span class="strut"> </span></p> +<p id="t280" class="pln"><span class="str"> :param density_array: input density array (kg/m**3)</span><span class="strut"> </span></p> +<p id="t281" class="pln"><span class="str"> :type: np.ndarray</span><span class="strut"> </span></p> +<p id="t282" class="pln"><span class="strut"> </span></p> +<p id="t283" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t284" class="stm run hide_run"> <span class="nam">max_density</span> <span class="op">=</span> <span class="num">1040.4</span><span class="strut"> </span></p> +<p id="t285" class="stm run hide_run"> <span class="nam">min_density</span> <span class="op">=</span> <span class="num">998.5357</span><span class="strut"> </span></p> +<p id="t286" class="stm run hide_run"> <span class="nam">density_array</span><span class="op">[</span><span class="nam">density_array</span> <span class="op">></span> <span class="nam">max_density</span><span class="op">]</span> <span class="op">=</span> <span class="nam">max_density</span><span class="strut"> </span></p> +<p id="t287" class="stm run hide_run"> <span class="nam">density_array</span><span class="op">[</span><span class="nam">density_array</span> <span class="op"><</span> <span class="nam">min_density</span><span class="op">]</span> <span class="op">=</span> <span class="nam">min_density</span><span class="strut"> </span></p> +<p id="t288" class="pln"><span class="strut"> </span></p> +<p id="t289" class="stm run hide_run"> <span class="op">@</span><span class="nam">staticmethod</span><span class="strut"> </span></p> +<p id="t290" class="pln"> <span class="key">def</span> <span class="nam">_check_diameter_range</span><span class="op">(</span><span class="nam">diameter_array</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t291" class="pln"> <span class="str">"""Modifies input array so any outlier diameters are set</span><span class="strut"> </span></p> +<p id="t292" class="pln"><span class="str"> to the respective min or max of the range</span><span class="strut"> </span></p> +<p id="t293" class="pln"><span class="strut"> </span></p> +<p id="t294" class="pln"><span class="str"> :param diameter_array: input diameter array (mm)</span><span class="strut"> </span></p> +<p id="t295" class="pln"><span class="str"> :type: np.ndarray</span><span class="strut"> </span></p> +<p id="t296" class="pln"><span class="strut"> </span></p> +<p id="t297" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t298" class="stm run hide_run"> <span class="nam">max_diameter</span> <span class="op">=</span> <span class="num">7.1334</span><span class="strut"> </span></p> +<p id="t299" class="stm run hide_run"> <span class="nam">min_diameter</span> <span class="op">=</span> <span class="num">1.5970</span><span class="strut"> </span></p> +<p id="t300" class="stm run hide_run"> <span class="nam">diameter_array</span><span class="op">[</span><span class="nam">diameter_array</span> <span class="op">></span> <span class="nam">max_diameter</span><span class="op">]</span> <span class="op">=</span> <span class="nam">max_diameter</span><span class="strut"> </span></p> +<p id="t301" class="stm run hide_run"> <span class="nam">diameter_array</span><span class="op">[</span><span class="nam">diameter_array</span> <span class="op"><</span> <span class="nam">min_diameter</span><span class="op">]</span> <span class="op">=</span> <span class="nam">min_diameter</span><span class="strut"> </span></p> +<p id="t302" class="pln"><span class="strut"> </span></p> +<p id="t303" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_mean_density</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t304" class="pln"> <span class="str">"""Returns an array of the mean density (kg/m**3) of the</span><span class="strut"> </span></p> +<p id="t305" class="pln"><span class="str"> collection carp eggs at each time step</span><span class="strut"> </span></p> +<p id="t306" class="pln"><span class="strut"> </span></p> +<p id="t307" class="pln"><span class="str"> :return: mean density (kg/m**3) of carp eggs</span><span class="strut"> </span></p> +<p id="t308" class="pln"><span class="str"> :rtype: float</span><span class="strut"> </span></p> +<p id="t309" class="pln"><span class="strut"> </span></p> +<p id="t310" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t311" class="stm run hide_run"> <span class="nam">a</span> <span class="op">=</span> <span class="num">30.58</span><span class="strut"> </span></p> +<p id="t312" class="stm run hide_run"> <span class="nam">b</span> <span class="op">=</span> <span class="num">1716</span><span class="strut"> </span></p> +<p id="t313" class="stm run hide_run"> <span class="nam">c</span> <span class="op">=</span> <span class="num">999.4</span><span class="strut"> </span></p> +<p id="t314" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_calc_mean_density</span><span class="op">(</span><span class="nam">a</span><span class="op">,</span> <span class="nam">b</span><span class="op">,</span> <span class="nam">c</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t315" class="pln"><span class="strut"> </span></p> +<p id="t316" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_mean_diameter</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t317" class="pln"> <span class="str">"""Returns an array of the mean diameter (mm) of the</span><span class="strut"> </span></p> +<p id="t318" class="pln"><span class="str"> collection of carp eggs at each time step</span><span class="strut"> </span></p> +<p id="t319" class="pln"><span class="strut"> </span></p> +<p id="t320" class="pln"><span class="str"> :return: array of mean diameter (mm) of carp eggs at each time step</span><span class="strut"> </span></p> +<p id="t321" class="pln"><span class="str"> :rtype: np.ndarray</span><span class="strut"> </span></p> +<p id="t322" class="pln"><span class="strut"> </span></p> +<p id="t323" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t324" class="stm run hide_run"> <span class="nam">a</span> <span class="op">=</span> <span class="num">5.82</span><span class="strut"> </span></p> +<p id="t325" class="stm run hide_run"> <span class="nam">b</span> <span class="op">=</span> <span class="num">3506.7</span><span class="strut"> </span></p> +<p id="t326" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_calc_mean_diameter</span><span class="op">(</span><span class="nam">a</span><span class="op">,</span> <span class="nam">b</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t327" class="pln"><span class="strut"> </span></p> +<p id="t328" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_density_std</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t329" class="pln"> <span class="str">"""Returns an array of the density standard deviation (kg/m**3)</span><span class="strut"> </span></p> +<p id="t330" class="pln"><span class="str"> of the collection of carp eggs at each time step</span><span class="strut"> </span></p> +<p id="t331" class="pln"><span class="strut"> </span></p> +<p id="t332" class="pln"><span class="str"> :return: density std array (kg/m**3) of carp eggs at each time step</span><span class="strut"> </span></p> +<p id="t333" class="pln"><span class="str"> :rtype: np.ndarray</span><span class="strut"> </span></p> +<p id="t334" class="pln"><span class="strut"> </span></p> +<p id="t335" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t336" class="stm run hide_run"> <span class="nam">a</span> <span class="op">=</span> <span class="num">63.12</span><span class="strut"> </span></p> +<p id="t337" class="stm run hide_run"> <span class="nam">b</span> <span class="op">=</span> <span class="num">595</span><span class="strut"> </span></p> +<p id="t338" class="stm run hide_run"> <span class="nam">c</span> <span class="op">=</span> <span class="num">0.6292</span><span class="strut"> </span></p> +<p id="t339" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_calc_density_std</span><span class="op">(</span><span class="nam">a</span><span class="op">,</span> <span class="nam">b</span><span class="op">,</span> <span class="nam">c</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t340" class="pln"><span class="strut"> </span></p> +<p id="t341" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_diameter_std</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t342" class="pln"> <span class="str">"""Returns an array of the diameter standard deviation (mm)</span><span class="strut"> </span></p> +<p id="t343" class="pln"><span class="str"> of the collection of carp eggs at each time step</span><span class="strut"> </span></p> +<p id="t344" class="pln"><span class="strut"> </span></p> +<p id="t345" class="pln"><span class="str"> :return: diamter std array (mm) of carp eggs at each time step</span><span class="strut"> </span></p> +<p id="t346" class="pln"><span class="str"> :rtype: np.ndarray</span><span class="strut"> </span></p> +<p id="t347" class="pln"><span class="strut"> </span></p> +<p id="t348" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t349" class="stm run hide_run"> <span class="nam">a</span> <span class="op">=</span> <span class="num">0.1788</span><span class="strut"> </span></p> +<p id="t350" class="stm run hide_run"> <span class="nam">b</span> <span class="op">=</span> <span class="num">13570.0</span><span class="strut"> </span></p> +<p id="t351" class="stm run hide_run"> <span class="nam">c</span> <span class="op">=</span> <span class="num">0.44</span><span class="strut"> </span></p> +<p id="t352" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_calc_diameter_std</span><span class="op">(</span><span class="nam">a</span><span class="op">,</span> <span class="nam">b</span><span class="op">,</span> <span class="nam">c</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t353" class="pln"><span class="strut"> </span></p> +<p id="t354" class="stm run hide_run"> <span class="op">@</span><span class="nam">classmethod</span><span class="strut"> </span></p> +<p id="t355" class="stm run hide_run"> <span class="key">def</span> <span class="nam">gas_bladder_inflation_time</span><span class="op">(</span><span class="nam">cls</span><span class="op">,</span> <span class="nam">temperature</span><span class="op">=</span><span class="key">None</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t356" class="pln"> <span class="str">"""</span><span class="strut"> </span></p> +<p id="t357" class="pln"><span class="strut"> </span></p> +<p id="t358" class="pln"><span class="str"> :param temperature:</span><span class="strut"> </span></p> +<p id="t359" class="pln"><span class="str"> :return:</span><span class="strut"> </span></p> +<p id="t360" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t361" class="pln"><span class="strut"> </span></p> +<p id="t362" class="stm run hide_run"> <span class="nam">tmin2</span> <span class="op">=</span> <span class="num">13.4</span><span class="strut"> </span></p> +<p id="t363" class="stm run hide_run"> <span class="nam">meanctu_gas_bladder</span> <span class="op">=</span> <span class="num">1161.07</span><span class="strut"> </span></p> +<p id="t364" class="pln"><span class="strut"> </span></p> +<p id="t365" class="stm run hide_run"> <span class="key">return</span> <span class="nam">cls</span><span class="op">.</span><span class="nam">_calc_gas_bladder_inflation_time</span><span class="op">(</span><span class="nam">tmin2</span><span class="op">,</span> <span class="nam">meanctu_gas_bladder</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t366" class="pln"> <span class="nam">temperature</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t367" class="pln"><span class="strut"> </span></p> +<p id="t368" class="stm run hide_run"> <span class="op">@</span><span class="nam">classmethod</span><span class="strut"> </span></p> +<p id="t369" class="stm run hide_run"> <span class="key">def</span> <span class="nam">hatching_time</span><span class="op">(</span><span class="nam">cls</span><span class="op">,</span> <span class="nam">temperature</span><span class="op">=</span><span class="key">None</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t370" class="pln"> <span class="str">"""Returns the hatching time of carp eggs</span><span class="strut"> </span></p> +<p id="t371" class="pln"><span class="str"> based on input temperature</span><span class="strut"> </span></p> +<p id="t372" class="pln"><span class="strut"> </span></p> +<p id="t373" class="pln"><span class="str"> :param temperature: Temperature of eggs(Celsius)</span><span class="strut"> </span></p> +<p id="t374" class="pln"><span class="str"> :type: float</span><span class="strut"> </span></p> +<p id="t375" class="pln"><span class="str"> :return: hatching time of eggs (s)</span><span class="strut"> </span></p> +<p id="t376" class="pln"><span class="str"> :rtype: float</span><span class="strut"> </span></p> +<p id="t377" class="pln"><span class="strut"> </span></p> +<p id="t378" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t379" class="pln"><span class="strut"> </span></p> +<p id="t380" class="stm run hide_run"> <span class="nam">a</span> <span class="op">=</span> <span class="num">35703</span><span class="strut"> </span></p> +<p id="t381" class="stm run hide_run"> <span class="nam">b</span> <span class="op">=</span> <span class="op">-</span><span class="num">2.223</span><span class="strut"> </span></p> +<p id="t382" class="stm run hide_run"> <span class="nam">c</span> <span class="op">=</span> <span class="num">0.0</span><span class="strut"> </span></p> +<p id="t383" class="pln"><span class="strut"> </span></p> +<p id="t384" class="stm run hide_run"> <span class="key">return</span> <span class="nam">cls</span><span class="op">.</span><span class="nam">_calc_hatching_time</span><span class="op">(</span><span class="nam">a</span><span class="op">,</span> <span class="nam">b</span><span class="op">,</span> <span class="nam">c</span><span class="op">,</span> <span class="nam">temperature</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t385" class="pln"><span class="strut"> </span></p> +<p id="t386" class="pln"><span class="strut"> </span></p> +<p id="t387" class="stm run hide_run"><span class="key">class</span> <span class="nam">SilverCarpEggs</span><span class="op">(</span><span class="nam">CarpEggs</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t388" class="pln"> <span class="str">"""Class representing a collection of Silver carp eggs</span><span class="strut"> </span></p> +<p id="t389" class="pln"><span class="strut"> </span></p> +<p id="t390" class="pln"><span class="str"> See CarpEggs for accurate signature</span><span class="strut"> </span></p> +<p id="t391" class="pln"><span class="strut"> </span></p> +<p id="t392" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t393" class="pln"><span class="strut"> </span></p> +<p id="t394" class="stm run hide_run"> <span class="op">@</span><span class="nam">staticmethod</span><span class="strut"> </span></p> +<p id="t395" class="pln"> <span class="key">def</span> <span class="nam">_check_density_range</span><span class="op">(</span><span class="nam">density_array</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t396" class="pln"> <span class="str">"""Modifies input array so any outlier densities are set</span><span class="strut"> </span></p> +<p id="t397" class="pln"><span class="str"> to the respective min or max of the range</span><span class="strut"> </span></p> +<p id="t398" class="pln"><span class="strut"> </span></p> +<p id="t399" class="pln"><span class="str"> :param density_array: input density array (kg/m**3)</span><span class="strut"> </span></p> +<p id="t400" class="pln"><span class="str"> :type: np.ndarray</span><span class="strut"> </span></p> +<p id="t401" class="pln"><span class="strut"> </span></p> +<p id="t402" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t403" class="stm run hide_run"> <span class="nam">max_density</span> <span class="op">=</span> <span class="num">1036.1</span><span class="strut"> </span></p> +<p id="t404" class="stm run hide_run"> <span class="nam">min_density</span> <span class="op">=</span> <span class="num">998.7680</span><span class="strut"> </span></p> +<p id="t405" class="stm run hide_run"> <span class="nam">density_array</span><span class="op">[</span><span class="nam">density_array</span> <span class="op">></span> <span class="nam">max_density</span><span class="op">]</span> <span class="op">=</span> <span class="nam">max_density</span><span class="strut"> </span></p> +<p id="t406" class="stm run hide_run"> <span class="nam">density_array</span><span class="op">[</span><span class="nam">density_array</span> <span class="op"><</span> <span class="nam">min_density</span><span class="op">]</span> <span class="op">=</span> <span class="nam">min_density</span><span class="strut"> </span></p> +<p id="t407" class="pln"><span class="strut"> </span></p> +<p id="t408" class="stm run hide_run"> <span class="op">@</span><span class="nam">staticmethod</span><span class="strut"> </span></p> +<p id="t409" class="pln"> <span class="key">def</span> <span class="nam">_check_diameter_range</span><span class="op">(</span><span class="nam">diameter_array</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t410" class="pln"> <span class="str">"""Modifies input array so any outlier diameters are set</span><span class="strut"> </span></p> +<p id="t411" class="pln"><span class="str"> to the respective min or max of the range</span><span class="strut"> </span></p> +<p id="t412" class="pln"><span class="strut"> </span></p> +<p id="t413" class="pln"><span class="str"> :param diameter_array: input diameter array (mm)</span><span class="strut"> </span></p> +<p id="t414" class="pln"><span class="str"> :type: np.ndarray</span><span class="strut"> </span></p> +<p id="t415" class="pln"><span class="strut"> </span></p> +<p id="t416" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t417" class="stm run hide_run"> <span class="nam">max_diameter</span> <span class="op">=</span> <span class="num">5.6000</span><span class="strut"> </span></p> +<p id="t418" class="stm run hide_run"> <span class="nam">min_diameter</span> <span class="op">=</span> <span class="num">1.6980</span><span class="strut"> </span></p> +<p id="t419" class="stm run hide_run"> <span class="nam">diameter_array</span><span class="op">[</span><span class="nam">diameter_array</span> <span class="op">></span> <span class="nam">max_diameter</span><span class="op">]</span> <span class="op">=</span> <span class="nam">max_diameter</span><span class="strut"> </span></p> +<p id="t420" class="stm run hide_run"> <span class="nam">diameter_array</span><span class="op">[</span><span class="nam">diameter_array</span> <span class="op"><</span> <span class="nam">min_diameter</span><span class="op">]</span> <span class="op">=</span> <span class="nam">min_diameter</span><span class="strut"> </span></p> +<p id="t421" class="pln"><span class="strut"> </span></p> +<p id="t422" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_mean_density</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t423" class="pln"> <span class="str">"""Returns an array of the mean density (kg/m**3) of the</span><span class="strut"> </span></p> +<p id="t424" class="pln"><span class="str"> collection carp eggs at each time step</span><span class="strut"> </span></p> +<p id="t425" class="pln"><span class="strut"> </span></p> +<p id="t426" class="pln"><span class="str"> :return: mean density (kg/m**3) of carp eggs</span><span class="strut"> </span></p> +<p id="t427" class="pln"><span class="str"> :rtype: float</span><span class="strut"> </span></p> +<p id="t428" class="pln"><span class="strut"> </span></p> +<p id="t429" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t430" class="stm run hide_run"> <span class="nam">a</span> <span class="op">=</span> <span class="num">25.2</span><span class="strut"> </span></p> +<p id="t431" class="stm run hide_run"> <span class="nam">b</span> <span class="op">=</span> <span class="num">2259</span><span class="strut"> </span></p> +<p id="t432" class="stm run hide_run"> <span class="nam">c</span> <span class="op">=</span> <span class="num">999.3</span><span class="strut"> </span></p> +<p id="t433" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_calc_mean_density</span><span class="op">(</span><span class="nam">a</span><span class="op">,</span> <span class="nam">b</span><span class="op">,</span> <span class="nam">c</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t434" class="pln"><span class="strut"> </span></p> +<p id="t435" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_mean_diameter</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t436" class="pln"> <span class="str">"""Returns an array of the mean diameter (mm) of the</span><span class="strut"> </span></p> +<p id="t437" class="pln"><span class="str"> collection of carp eggs at each time step</span><span class="strut"> </span></p> +<p id="t438" class="pln"><span class="strut"> </span></p> +<p id="t439" class="pln"><span class="str"> :return: array of mean diameter (mm) of carp eggs at each time step</span><span class="strut"> </span></p> +<p id="t440" class="pln"><span class="str"> :rtype: np.ndarray</span><span class="strut"> </span></p> +<p id="t441" class="pln"><span class="strut"> </span></p> +<p id="t442" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t443" class="stm run hide_run"> <span class="nam">a</span> <span class="op">=</span> <span class="num">4.66</span><span class="strut"> </span></p> +<p id="t444" class="stm run hide_run"> <span class="nam">b</span> <span class="op">=</span> <span class="num">2635.9</span><span class="strut"> </span></p> +<p id="t445" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_calc_mean_diameter</span><span class="op">(</span><span class="nam">a</span><span class="op">,</span> <span class="nam">b</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t446" class="pln"><span class="strut"> </span></p> +<p id="t447" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_density_std</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t448" class="pln"> <span class="str">"""Returns an array of the density standard deviation (kg/m**3)</span><span class="strut"> </span></p> +<p id="t449" class="pln"><span class="str"> of the collection of carp eggs at each time step</span><span class="strut"> </span></p> +<p id="t450" class="pln"><span class="strut"> </span></p> +<p id="t451" class="pln"><span class="str"> :return: density std array (kg/m**3) of carp eggs at each time step</span><span class="strut"> </span></p> +<p id="t452" class="pln"><span class="str"> :rtype: np.ndarray</span><span class="strut"> </span></p> +<p id="t453" class="pln"><span class="strut"> </span></p> +<p id="t454" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t455" class="stm run hide_run"> <span class="nam">a</span> <span class="op">=</span> <span class="num">22.4</span><span class="strut"> </span></p> +<p id="t456" class="stm run hide_run"> <span class="nam">b</span> <span class="op">=</span> <span class="num">1894</span><span class="strut"> </span></p> +<p id="t457" class="stm run hide_run"> <span class="nam">c</span> <span class="op">=</span> <span class="num">0.4103</span><span class="strut"> </span></p> +<p id="t458" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_calc_density_std</span><span class="op">(</span><span class="nam">a</span><span class="op">,</span> <span class="nam">b</span><span class="op">,</span> <span class="nam">c</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t459" class="pln"><span class="strut"> </span></p> +<p id="t460" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_diameter_std</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t461" class="pln"> <span class="str">"""Returns an array of the diameter standard deviation (mm)</span><span class="strut"> </span></p> +<p id="t462" class="pln"><span class="str"> of the collection of carp eggs at each time step</span><span class="strut"> </span></p> +<p id="t463" class="pln"><span class="strut"> </span></p> +<p id="t464" class="pln"><span class="str"> :return: diamter std array (mm) of carp eggs at each time step</span><span class="strut"> </span></p> +<p id="t465" class="pln"><span class="str"> :rtype: np.ndarray</span><span class="strut"> </span></p> +<p id="t466" class="pln"><span class="strut"> </span></p> +<p id="t467" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t468" class="stm run hide_run"> <span class="nam">a</span> <span class="op">=</span> <span class="num">0.2631</span><span class="strut"> </span></p> +<p id="t469" class="stm run hide_run"> <span class="nam">b</span> <span class="op">=</span> <span class="num">22410</span><span class="strut"> </span></p> +<p id="t470" class="stm run hide_run"> <span class="nam">c</span> <span class="op">=</span> <span class="num">0.3073</span><span class="strut"> </span></p> +<p id="t471" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_calc_diameter_std</span><span class="op">(</span><span class="nam">a</span><span class="op">,</span> <span class="nam">b</span><span class="op">,</span> <span class="nam">c</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t472" class="pln"><span class="strut"> </span></p> +<p id="t473" class="stm run hide_run"> <span class="op">@</span><span class="nam">classmethod</span><span class="strut"> </span></p> +<p id="t474" class="stm run hide_run"> <span class="key">def</span> <span class="nam">gas_bladder_inflation_time</span><span class="op">(</span><span class="nam">cls</span><span class="op">,</span> <span class="nam">temperature</span><span class="op">=</span><span class="key">None</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t475" class="pln"><span class="strut"> </span></p> +<p id="t476" class="stm run hide_run"> <span class="nam">tmin2</span> <span class="op">=</span> <span class="num">13.3</span><span class="strut"> </span></p> +<p id="t477" class="stm run hide_run"> <span class="nam">meanctu_gas_bladder</span> <span class="op">=</span> <span class="num">1084.59</span><span class="strut"> </span></p> +<p id="t478" class="pln"><span class="strut"> </span></p> +<p id="t479" class="stm run hide_run"> <span class="key">return</span> <span class="nam">cls</span><span class="op">.</span><span class="nam">_calc_gas_bladder_inflation_time</span><span class="op">(</span><span class="nam">tmin2</span><span class="op">,</span> <span class="nam">meanctu_gas_bladder</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t480" class="pln"> <span class="nam">temperature</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t481" class="pln"><span class="strut"> </span></p> +<p id="t482" class="stm run hide_run"> <span class="op">@</span><span class="nam">classmethod</span><span class="strut"> </span></p> +<p id="t483" class="stm run hide_run"> <span class="key">def</span> <span class="nam">hatching_time</span><span class="op">(</span><span class="nam">cls</span><span class="op">,</span> <span class="nam">temperature</span><span class="op">=</span><span class="key">None</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t484" class="pln"> <span class="str">"""Returns the hatching time of carp eggs</span><span class="strut"> </span></p> +<p id="t485" class="pln"><span class="str"> based on input temperature</span><span class="strut"> </span></p> +<p id="t486" class="pln"><span class="strut"> </span></p> +<p id="t487" class="pln"><span class="str"> :param temperature: Temperature of eggs(Celsius)</span><span class="strut"> </span></p> +<p id="t488" class="pln"><span class="str"> :type: float</span><span class="strut"> </span></p> +<p id="t489" class="pln"><span class="str"> :return: hatching time of eggs (hr)</span><span class="strut"> </span></p> +<p id="t490" class="pln"><span class="str"> :rtype: float</span><span class="strut"> </span></p> +<p id="t491" class="pln"><span class="strut"> </span></p> +<p id="t492" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t493" class="stm run hide_run"> <span class="nam">a</span> <span class="op">=</span> <span class="num">1.2087e+7</span><span class="strut"> </span></p> +<p id="t494" class="stm run hide_run"> <span class="nam">b</span> <span class="op">=</span> <span class="op">-</span><span class="num">4.2664</span><span class="strut"> </span></p> +<p id="t495" class="stm run hide_run"> <span class="nam">c</span> <span class="op">=</span> <span class="num">10.242</span><span class="strut"> </span></p> +<p id="t496" class="stm run hide_run"> <span class="key">return</span> <span class="nam">cls</span><span class="op">.</span><span class="nam">_calc_hatching_time</span><span class="op">(</span><span class="nam">a</span><span class="op">,</span> <span class="nam">b</span><span class="op">,</span> <span class="nam">c</span><span class="op">,</span> <span class="nam">temperature</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t497" class="pln"><span class="strut"> </span></p> +<p id="t498" class="pln"><span class="strut"> </span></p> +<p id="t499" class="stm run hide_run"><span class="key">class</span> <span class="nam">GrassCarpEggs</span><span class="op">(</span><span class="nam">CarpEggs</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t500" class="pln"> <span class="str">"""Class representing a collection of Grass carp eggs</span><span class="strut"> </span></p> +<p id="t501" class="pln"><span class="strut"> </span></p> +<p id="t502" class="pln"><span class="str"> See CarpEggs for accurate signature</span><span class="strut"> </span></p> +<p id="t503" class="pln"><span class="strut"> </span></p> +<p id="t504" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t505" class="pln"><span class="strut"> </span></p> +<p id="t506" class="stm run hide_run"> <span class="op">@</span><span class="nam">staticmethod</span><span class="strut"> </span></p> +<p id="t507" class="pln"> <span class="key">def</span> <span class="nam">_check_density_range</span><span class="op">(</span><span class="nam">density_array</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t508" class="pln"> <span class="str">"""Modifies input array so any outlier densities are set</span><span class="strut"> </span></p> +<p id="t509" class="pln"><span class="str"> to the respective min or max of the range</span><span class="strut"> </span></p> +<p id="t510" class="pln"><span class="strut"> </span></p> +<p id="t511" class="pln"><span class="str"> :param density_array: input density array (kg/m**3)</span><span class="strut"> </span></p> +<p id="t512" class="pln"><span class="str"> :type: np.ndarray</span><span class="strut"> </span></p> +<p id="t513" class="pln"><span class="strut"> </span></p> +<p id="t514" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t515" class="stm run hide_run"> <span class="nam">max_density</span> <span class="op">=</span> <span class="num">1.0473e+3</span><span class="strut"> </span></p> +<p id="t516" class="stm run hide_run"> <span class="nam">min_density</span> <span class="op">=</span> <span class="num">998.4118</span><span class="strut"> </span></p> +<p id="t517" class="stm run hide_run"> <span class="nam">density_array</span><span class="op">[</span><span class="nam">density_array</span> <span class="op">></span> <span class="nam">max_density</span><span class="op">]</span> <span class="op">=</span> <span class="nam">max_density</span><span class="strut"> </span></p> +<p id="t518" class="stm run hide_run"> <span class="nam">density_array</span><span class="op">[</span><span class="nam">density_array</span> <span class="op"><</span> <span class="nam">min_density</span><span class="op">]</span> <span class="op">=</span> <span class="nam">min_density</span><span class="strut"> </span></p> +<p id="t519" class="pln"><span class="strut"> </span></p> +<p id="t520" class="stm run hide_run"> <span class="op">@</span><span class="nam">staticmethod</span><span class="strut"> </span></p> +<p id="t521" class="pln"> <span class="key">def</span> <span class="nam">_check_diameter_range</span><span class="op">(</span><span class="nam">diameter_array</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t522" class="pln"> <span class="str">"""Modifies input array so any outlier diameters are set</span><span class="strut"> </span></p> +<p id="t523" class="pln"><span class="str"> to the respective min or max of the range</span><span class="strut"> </span></p> +<p id="t524" class="pln"><span class="strut"> </span></p> +<p id="t525" class="pln"><span class="str"> :param diameter_array: input diameter array (mm)</span><span class="strut"> </span></p> +<p id="t526" class="pln"><span class="str"> :type: np.ndarray</span><span class="strut"> </span></p> +<p id="t527" class="pln"><span class="strut"> </span></p> +<p id="t528" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t529" class="stm run hide_run"> <span class="nam">max_diameter</span> <span class="op">=</span> <span class="num">5.6750</span><span class="strut"> </span></p> +<p id="t530" class="stm run hide_run"> <span class="nam">min_diameter</span> <span class="op">=</span> <span class="num">1.2250</span><span class="strut"> </span></p> +<p id="t531" class="stm run hide_run"> <span class="nam">diameter_array</span><span class="op">[</span><span class="nam">diameter_array</span> <span class="op">></span> <span class="nam">max_diameter</span><span class="op">]</span> <span class="op">=</span> <span class="nam">max_diameter</span><span class="strut"> </span></p> +<p id="t532" class="stm run hide_run"> <span class="nam">diameter_array</span><span class="op">[</span><span class="nam">diameter_array</span> <span class="op"><</span> <span class="nam">min_diameter</span><span class="op">]</span> <span class="op">=</span> <span class="nam">min_diameter</span><span class="strut"> </span></p> +<p id="t533" class="pln"><span class="strut"> </span></p> +<p id="t534" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_mean_density</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t535" class="pln"> <span class="str">"""Returns an array of the mean density (kg/m**3) of the</span><span class="strut"> </span></p> +<p id="t536" class="pln"><span class="str"> collection carp eggs at each time step</span><span class="strut"> </span></p> +<p id="t537" class="pln"><span class="strut"> </span></p> +<p id="t538" class="pln"><span class="str"> :return: mean density (kg/m**3) of carp eggs</span><span class="strut"> </span></p> +<p id="t539" class="pln"><span class="str"> :rtype: float</span><span class="strut"> </span></p> +<p id="t540" class="pln"><span class="strut"> </span></p> +<p id="t541" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t542" class="stm run hide_run"> <span class="nam">a</span> <span class="op">=</span> <span class="num">29.09</span><span class="strut"> </span></p> +<p id="t543" class="stm run hide_run"> <span class="nam">b</span> <span class="op">=</span> <span class="num">1812</span><span class="strut"> </span></p> +<p id="t544" class="stm run hide_run"> <span class="nam">c</span> <span class="op">=</span> <span class="num">999.8</span><span class="strut"> </span></p> +<p id="t545" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_calc_mean_density</span><span class="op">(</span><span class="nam">a</span><span class="op">,</span> <span class="nam">b</span><span class="op">,</span> <span class="nam">c</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t546" class="pln"><span class="strut"> </span></p> +<p id="t547" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_mean_diameter</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t548" class="pln"> <span class="str">"""Returns an array of the mean diameter (mm) of the</span><span class="strut"> </span></p> +<p id="t549" class="pln"><span class="str"> collection of carp eggs at each time step</span><span class="strut"> </span></p> +<p id="t550" class="pln"><span class="strut"> </span></p> +<p id="t551" class="pln"><span class="str"> :return: array of mean diameter (mm) of carp eggs at each time step</span><span class="strut"> </span></p> +<p id="t552" class="pln"><span class="str"> :rtype: np.ndarray</span><span class="strut"> </span></p> +<p id="t553" class="pln"><span class="strut"> </span></p> +<p id="t554" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t555" class="stm run hide_run"> <span class="nam">a</span> <span class="op">=</span> <span class="num">4.56</span><span class="strut"> </span></p> +<p id="t556" class="stm run hide_run"> <span class="nam">b</span> <span class="op">=</span> <span class="num">2314</span><span class="strut"> </span></p> +<p id="t557" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_calc_mean_diameter</span><span class="op">(</span><span class="nam">a</span><span class="op">,</span> <span class="nam">b</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t558" class="pln"><span class="strut"> </span></p> +<p id="t559" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_density_std</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t560" class="pln"> <span class="str">"""Returns an array of the density standard deviation (kg/m**3)</span><span class="strut"> </span></p> +<p id="t561" class="pln"><span class="str"> of the collection of carp eggs at each time step</span><span class="strut"> </span></p> +<p id="t562" class="pln"><span class="strut"> </span></p> +<p id="t563" class="pln"><span class="str"> :return: density std array (kg/m**3) of carp eggs at each time step</span><span class="strut"> </span></p> +<p id="t564" class="pln"><span class="str"> :rtype: np.ndarray</span><span class="strut"> </span></p> +<p id="t565" class="pln"><span class="strut"> </span></p> +<p id="t566" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t567" class="stm run hide_run"> <span class="nam">a</span> <span class="op">=</span> <span class="num">19.28</span><span class="strut"> </span></p> +<p id="t568" class="stm run hide_run"> <span class="nam">b</span> <span class="op">=</span> <span class="num">1973</span><span class="strut"> </span></p> +<p id="t569" class="stm run hide_run"> <span class="nam">c</span> <span class="op">=</span> <span class="num">1.029</span><span class="strut"> </span></p> +<p id="t570" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_calc_density_std</span><span class="op">(</span><span class="nam">a</span><span class="op">,</span> <span class="nam">b</span><span class="op">,</span> <span class="nam">c</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t571" class="pln"><span class="strut"> </span></p> +<p id="t572" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_diameter_std</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t573" class="pln"> <span class="str">"""Returns an array of the diameter standard deviation (mm)</span><span class="strut"> </span></p> +<p id="t574" class="pln"><span class="str"> of the collection of carp eggs at each time step</span><span class="strut"> </span></p> +<p id="t575" class="pln"><span class="strut"> </span></p> +<p id="t576" class="pln"><span class="str"> :return: diamter std array (mm) of carp eggs at each time step</span><span class="strut"> </span></p> +<p id="t577" class="pln"><span class="str"> :rtype: np.ndarray</span><span class="strut"> </span></p> +<p id="t578" class="pln"><span class="strut"> </span></p> +<p id="t579" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t580" class="stm run hide_run"> <span class="nam">a</span> <span class="op">=</span> <span class="num">0.4759</span><span class="strut"> </span></p> +<p id="t581" class="stm run hide_run"> <span class="nam">b</span> <span class="op">=</span> <span class="num">14150</span><span class="strut"> </span></p> +<p id="t582" class="stm run hide_run"> <span class="nam">c</span> <span class="op">=</span> <span class="num">0.4586</span><span class="strut"> </span></p> +<p id="t583" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_calc_diameter_std</span><span class="op">(</span><span class="nam">a</span><span class="op">,</span> <span class="nam">b</span><span class="op">,</span> <span class="nam">c</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t584" class="pln"><span class="strut"> </span></p> +<p id="t585" class="stm run hide_run"> <span class="op">@</span><span class="nam">classmethod</span><span class="strut"> </span></p> +<p id="t586" class="stm run hide_run"> <span class="key">def</span> <span class="nam">gas_bladder_inflation_time</span><span class="op">(</span><span class="nam">cls</span><span class="op">,</span> <span class="nam">temperature</span><span class="op">=</span><span class="key">None</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t587" class="pln"><span class="strut"> </span></p> +<p id="t588" class="stm run hide_run"> <span class="nam">tmin2</span> <span class="op">=</span> <span class="num">13.3</span><span class="strut"> </span></p> +<p id="t589" class="stm run hide_run"> <span class="nam">meanctu_gas_bladder</span> <span class="op">=</span> <span class="num">1100.82</span><span class="strut"> </span></p> +<p id="t590" class="pln"><span class="strut"> </span></p> +<p id="t591" class="stm run hide_run"> <span class="key">return</span> <span class="nam">cls</span><span class="op">.</span><span class="nam">_calc_gas_bladder_inflation_time</span><span class="op">(</span><span class="nam">tmin2</span><span class="op">,</span> <span class="nam">meanctu_gas_bladder</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t592" class="pln"> <span class="nam">temperature</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t593" class="pln"><span class="strut"> </span></p> +<p id="t594" class="stm run hide_run"> <span class="op">@</span><span class="nam">classmethod</span><span class="strut"> </span></p> +<p id="t595" class="stm run hide_run"> <span class="key">def</span> <span class="nam">hatching_time</span><span class="op">(</span><span class="nam">cls</span><span class="op">,</span> <span class="nam">temperature</span><span class="op">=</span><span class="key">None</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t596" class="pln"> <span class="str">"""Returns the hatching time of carp eggs</span><span class="strut"> </span></p> +<p id="t597" class="pln"><span class="str"> based on input temperature</span><span class="strut"> </span></p> +<p id="t598" class="pln"><span class="strut"> </span></p> +<p id="t599" class="pln"><span class="str"> :param temperature: Temperature of eggs(Celsius)</span><span class="strut"> </span></p> +<p id="t600" class="pln"><span class="str"> :type: float</span><span class="strut"> </span></p> +<p id="t601" class="pln"><span class="str"> :return: hatching time of eggs (hr)</span><span class="strut"> </span></p> +<p id="t602" class="pln"><span class="str"> :rtype: float</span><span class="strut"> </span></p> +<p id="t603" class="pln"><span class="strut"> </span></p> +<p id="t604" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t605" class="stm run hide_run"> <span class="nam">a</span> <span class="op">=</span> <span class="num">3.677e+7</span><span class="strut"> </span></p> +<p id="t606" class="stm run hide_run"> <span class="nam">b</span> <span class="op">=</span> <span class="op">-</span><span class="num">4.788</span><span class="strut"> </span></p> +<p id="t607" class="stm run hide_run"> <span class="nam">c</span> <span class="op">=</span> <span class="num">18.87</span><span class="strut"> </span></p> +<p id="t608" class="stm run hide_run"> <span class="key">return</span> <span class="nam">cls</span><span class="op">.</span><span class="nam">_calc_hatching_time</span><span class="op">(</span><span class="nam">a</span><span class="op">,</span> <span class="nam">b</span><span class="op">,</span> <span class="nam">c</span><span class="op">,</span> <span class="nam">temperature</span><span class="op">)</span><span class="strut"> </span></p> + + </td> + </tr> + </table> +</div> + +<div id="footer"> + <div class="content"> + <p> + <a class="nav" href="index.html">« index</a> <a class="nav" href="https://coverage.readthedocs.io">coverage.py v4.5.3</a>, + created at 2019-07-09 15:15 + </p> + </div> +</div> + +</body> +</html> diff --git a/coverage_report/fluegg_drift_py.html b/coverage_report/fluegg_drift_py.html new file mode 100644 index 0000000..a4b7b4c --- /dev/null +++ b/coverage_report/fluegg_drift_py.html @@ -0,0 +1,393 @@ + + + +<!DOCTYPE html> +<html> +<head> + <meta http-equiv="Content-Type" content="text/html; charset=utf-8"> + + + <meta http-equiv="X-UA-Compatible" content="IE=emulateIE7" /> + <title>Coverage for fluegg\drift.py: 89%</title> + <link rel="stylesheet" href="style.css" type="text/css"> + + <script type="text/javascript" src="jquery.min.js"></script> + <script type="text/javascript" src="jquery.hotkeys.js"></script> + <script type="text/javascript" src="jquery.isonscreen.js"></script> + <script type="text/javascript" src="coverage_html.js"></script> + <script type="text/javascript"> + jQuery(document).ready(coverage.pyfile_ready); + </script> +</head> +<body class="pyfile"> + +<div id="header"> + <div class="content"> + <h1>Coverage for <b>fluegg\drift.py</b> : + <span class="pc_cov">89%</span> + </h1> + + <img id="keyboard_icon" src="keybd_closed.png" alt="Show keyboard shortcuts" /> + + <h2 class="stats"> + 56 statements + <span class="run hide_run shortkey_r button_toggle_run">50 run</span> + <span class="mis shortkey_m button_toggle_mis">6 missing</span> + <span class="exc shortkey_x 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href="#n146">146</a></p> +<p id="n147" class="pln"><a href="#n147">147</a></p> +<p id="n148" class="pln"><a href="#n148">148</a></p> +<p id="n149" class="pln"><a href="#n149">149</a></p> +<p id="n150" class="pln"><a href="#n150">150</a></p> +<p id="n151" class="pln"><a href="#n151">151</a></p> +<p id="n152" class="stm run hide_run"><a href="#n152">152</a></p> + + </td> + <td class="text"> +<p id="t1" class="stm run hide_run"><span class="key">from</span> <span class="nam">abc</span> <span class="key">import</span> <span class="nam">abstractmethod</span><span class="strut"> </span></p> +<p id="t2" class="pln"><span class="strut"> </span></p> +<p id="t3" class="stm run hide_run"><span class="key">import</span> <span class="nam">numpy</span> <span class="key">as</span> <span class="nam">np</span><span class="strut"> </span></p> +<p id="t4" class="pln"><span class="strut"> </span></p> +<p id="t5" class="pln"><span class="strut"> </span></p> +<p id="t6" class="stm run hide_run"><span class="key">class</span> <span class="nam">DriftingParticle</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t7" class="pln"><span class="strut"> </span></p> +<p id="t8" class="stm run hide_run"> <span class="op">@</span><span class="nam">staticmethod</span><span class="strut"> </span></p> +<p id="t9" class="pln"> <span class="key">def</span> <span class="nam">_dietrich_equation</span><span class="op">(</span><span class="nam">water_viscosity</span><span class="op">,</span> <span class="nam">water_density</span><span class="op">,</span> <span class="nam">particle_diameter</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t10" class="pln"> <span class="nam">particle_density</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t11" class="pln"> <span class="str">"""Returns the settling velocity (cm/s) of particles</span><span class="strut"> </span></p> +<p id="t12" class="pln"><span class="str"> calculated using the Dietrich equation.</span><span class="strut"> </span></p> +<p id="t13" class="pln"><span class="strut"> </span></p> +<p id="t14" class="pln"><span class="str"> :param water_viscosity: water viscosity (cm**2/s)</span><span class="strut"> </span></p> +<p id="t15" class="pln"><span class="str"> :type: numpy.ndarray</span><span class="strut"> </span></p> +<p id="t16" class="pln"><span class="str"> :param water_density: water density (kg/m**3)</span><span class="strut"> </span></p> +<p id="t17" class="pln"><span class="str"> :type: numpy.ndarray</span><span class="strut"> </span></p> +<p id="t18" class="pln"><span class="str"> :param particle_diameter: particle diameter (cm)</span><span class="strut"> </span></p> +<p id="t19" class="pln"><span class="str"> :type: numpy.ndarray</span><span class="strut"> </span></p> +<p id="t20" class="pln"><span class="str"> :param particle_density: particle density (kg/m**3)</span><span class="strut"> </span></p> +<p id="t21" class="pln"><span class="str"> :type: numpy.ndarray</span><span class="strut"> </span></p> +<p id="t22" class="pln"><span class="str"> :return: settling velocity of particle in water (cm/s)</span><span class="strut"> </span></p> +<p id="t23" class="pln"><span class="str"> :rtype: numpy.ndarray</span><span class="strut"> </span></p> +<p id="t24" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t25" class="pln"><span class="strut"> </span></p> +<p id="t26" class="pln"> <span class="com"># Specific gravity of particle</span><span class="strut"> </span></p> +<p id="t27" class="stm run hide_run"> <span class="nam">specific_gravity</span> <span class="op">=</span> <span class="nam">particle_density</span> <span class="op">/</span> <span class="nam">water_density</span><span class="strut"> </span></p> +<p id="t28" class="pln"> <span class="com"># Gravitational acceleration (cm/s**2)</span><span class="strut"> </span></p> +<p id="t29" class="stm run hide_run"> <span class="nam">gravity</span> <span class="op">=</span> <span class="num">981</span><span class="strut"> </span></p> +<p id="t30" class="pln"> <span class="com"># Constants</span><span class="strut"> </span></p> +<p id="t31" class="stm run hide_run"> <span class="nam">b1</span> <span class="op">=</span> <span class="num">2.891394</span><span class="strut"> </span></p> +<p id="t32" class="stm run hide_run"> <span class="nam">b2</span> <span class="op">=</span> <span class="num">0.95296</span><span class="strut"> </span></p> +<p id="t33" class="stm run hide_run"> <span class="nam">b3</span> <span class="op">=</span> <span class="num">0.056835</span><span class="strut"> </span></p> +<p id="t34" class="stm run hide_run"> <span class="nam">b4</span> <span class="op">=</span> <span class="num">0.002892</span><span class="strut"> </span></p> +<p id="t35" class="stm run hide_run"> <span class="nam">b5</span> <span class="op">=</span> <span class="num">0.000245</span><span class="strut"> </span></p> +<p id="t36" class="pln"> <span class="com"># Particle Reynold's number</span><span class="strut"> </span></p> +<p id="t37" class="stm run hide_run"> <span class="nam">temporary</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">sqrt</span><span class="op">(</span><span class="op">(</span><span class="nam">specific_gravity</span> <span class="op">-</span> <span class="num">1</span><span class="op">)</span> <span class="op">*</span><span class="strut"> </span></p> +<p id="t38" class="pln"> <span class="nam">gravity</span> <span class="op">*</span> <span class="nam">particle_diameter</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t39" class="stm run hide_run"> <span class="nam">reynolds_number</span> <span class="op">=</span> <span class="op">(</span><span class="nam">particle_diameter</span> <span class="op">*</span> <span class="nam">temporary</span><span class="op">)</span> <span class="op">/</span> <span class="nam">water_viscosity</span><span class="strut"> </span></p> +<p id="t40" class="pln"> <span class="com"># Rf = Dimensionless terminal particle settling velocity</span><span class="strut"> </span></p> +<p id="t41" class="stm run hide_run"> <span class="nam">Rf</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">exp</span><span class="op">(</span><span class="op">-</span><span class="nam">b1</span> <span class="op">+</span> <span class="op">(</span><span class="nam">b2</span> <span class="op">*</span> <span class="op">(</span><span class="nam">np</span><span class="op">.</span><span class="nam">log</span><span class="op">(</span><span class="nam">reynolds_number</span><span class="op">)</span><span class="op">)</span><span class="op">)</span> <span class="op">-</span><span class="strut"> </span></p> +<p id="t42" class="pln"> <span class="op">(</span><span class="nam">b3</span> <span class="op">*</span> <span class="op">(</span><span class="op">(</span><span class="nam">np</span><span class="op">.</span><span class="nam">log</span><span class="op">(</span><span class="nam">reynolds_number</span><span class="op">)</span><span class="op">)</span> <span class="op">**</span> <span class="num">2</span><span class="op">)</span><span class="op">)</span> <span class="op">-</span><span class="strut"> </span></p> +<p id="t43" class="pln"> <span class="op">(</span><span class="nam">b4</span> <span class="op">*</span> <span class="op">(</span><span class="op">(</span><span class="nam">np</span><span class="op">.</span><span class="nam">log</span><span class="op">(</span><span class="nam">reynolds_number</span><span class="op">)</span><span class="op">)</span> <span class="op">**</span> <span class="num">3</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span><span class="strut"> </span></p> +<p id="t44" class="pln"> <span class="op">(</span><span class="nam">b5</span> <span class="op">*</span> <span class="op">(</span><span class="op">(</span><span class="nam">np</span><span class="op">.</span><span class="nam">log</span><span class="op">(</span><span class="nam">reynolds_number</span><span class="op">)</span><span class="op">)</span> <span class="op">**</span> <span class="num">4</span><span class="op">)</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t45" class="stm run hide_run"> <span class="nam">settling_velocity</span> <span class="op">=</span> <span class="nam">Rf</span> <span class="op">*</span> <span class="nam">temporary</span><span class="strut"> </span></p> +<p id="t46" class="stm run hide_run"> <span class="key">return</span> <span class="nam">settling_velocity</span><span class="strut"> </span></p> +<p id="t47" class="pln"><span class="strut"> </span></p> +<p id="t48" class="stm run hide_run"> <span class="op">@</span><span class="nam">abstractmethod</span><span class="strut"> </span></p> +<p id="t49" class="pln"> <span class="key">def</span> <span class="nam">density</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="op">*</span><span class="nam">args</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t50" class="stm mis"> <span class="key">raise</span> <span class="nam">NotImplementedError</span><span class="strut"> </span></p> +<p id="t51" class="pln"><span class="strut"> </span></p> +<p id="t52" class="stm run hide_run"> <span class="op">@</span><span class="nam">abstractmethod</span><span class="strut"> </span></p> +<p id="t53" class="pln"> <span class="key">def</span> <span class="nam">diameter</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t54" class="stm mis"> <span class="key">raise</span> <span class="nam">NotImplementedError</span><span class="strut"> </span></p> +<p id="t55" class="pln"><span class="strut"> </span></p> +<p id="t56" class="stm run hide_run"> <span class="key">def</span> <span class="nam">fall_velocity</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">hydraulic_results</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t57" class="pln"> <span class="str">"""Wrapper for the dietrich equation, returns fall velocity of</span><span class="strut"> </span></p> +<p id="t58" class="pln"><span class="str"> particles (m/s)</span><span class="strut"> </span></p> +<p id="t59" class="pln"><span class="strut"> </span></p> +<p id="t60" class="pln"><span class="str"> :param hydraulic_results: hydraulic results at current particle</span><span class="strut"> </span></p> +<p id="t61" class="pln"><span class="str"> positions</span><span class="strut"> </span></p> +<p id="t62" class="pln"><span class="str"> :type: hydraulics.HydraulicResults</span><span class="strut"> </span></p> +<p id="t63" class="pln"><span class="str"> :return: settling velocity of particle in water (m/s)</span><span class="strut"> </span></p> +<p id="t64" class="pln"><span class="str"> :rtype: numpy.ndarray</span><span class="strut"> </span></p> +<p id="t65" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t66" class="pln"><span class="strut"> </span></p> +<p id="t67" class="pln"> <span class="com"># Calculate the fall velocity using Dietrich Equation based on</span><span class="strut"> </span></p> +<p id="t68" class="pln"> <span class="com"># particle data</span><span class="strut"> </span></p> +<p id="t69" class="stm run hide_run"> <span class="nam">temperature</span> <span class="op">=</span> <span class="nam">hydraulic_results</span><span class="op">.</span><span class="nam">temperature</span><span class="op">(</span><span class="op">)</span> <span class="com"># Celsius</span><span class="strut"> </span></p> +<p id="t70" class="stm run hide_run"> <span class="nam">water_viscosity</span> <span class="op">=</span> <span class="nam">hydraulic_results</span><span class="op">.</span><span class="nam">water_viscosity</span><span class="op">(</span><span class="strut"> </span></p> +<p id="t71" class="pln"> <span class="op">)</span> <span class="op">*</span> <span class="num">100</span> <span class="op">**</span> <span class="num">2</span> <span class="com"># Convert from m**2/s to cm**2/s</span><span class="strut"> </span></p> +<p id="t72" class="stm run hide_run"> <span class="nam">water_density</span> <span class="op">=</span> <span class="nam">hydraulic_results</span><span class="op">.</span><span class="nam">water_density</span><span class="op">(</span><span class="op">)</span> <span class="com"># kg/m**3</span><span class="strut"> </span></p> +<p id="t73" class="stm run hide_run"> <span class="nam">particle_diameter</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">diameter</span><span class="op">(</span><span class="op">)</span> <span class="op">*</span> <span class="num">100</span> <span class="com"># Convert from m to cm</span><span class="strut"> </span></p> +<p id="t74" class="stm run hide_run"> <span class="nam">particle_density</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">density</span><span class="op">(</span><span class="nam">temperature</span><span class="op">)</span> <span class="com"># kg/m**3</span><span class="strut"> </span></p> +<p id="t75" class="pln"><span class="strut"> </span></p> +<p id="t76" class="pln"> <span class="com"># calculate fall velocity as cm/s</span><span class="strut"> </span></p> +<p id="t77" class="stm run hide_run"> <span class="nam">fall_velocity</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_dietrich_equation</span><span class="op">(</span><span class="strut"> </span></p> +<p id="t78" class="pln"> <span class="nam">water_viscosity</span><span class="op">,</span> <span class="nam">water_density</span><span class="op">,</span> <span class="nam">particle_diameter</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t79" class="pln"> <span class="nam">particle_density</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t80" class="pln"><span class="strut"> </span></p> +<p id="t81" class="pln"> <span class="com"># change fall velocity sign to coordinate system</span><span class="strut"> </span></p> +<p id="t82" class="stm run hide_run"> <span class="nam">fall_velocity</span> <span class="op">=</span> <span class="op">-</span><span class="nam">fall_velocity</span><span class="strut"> </span></p> +<p id="t83" class="pln"><span class="strut"> </span></p> +<p id="t84" class="pln"> <span class="com"># convert fall velocity from cm/s to m/s</span><span class="strut"> </span></p> +<p id="t85" class="stm run hide_run"> <span class="key">return</span> <span class="nam">fall_velocity</span> <span class="op">/</span> <span class="num">100</span><span class="strut"> </span></p> +<p id="t86" class="pln"><span class="strut"> </span></p> +<p id="t87" class="stm run hide_run"> <span class="op">@</span><span class="nam">abstractmethod</span><span class="strut"> </span></p> +<p id="t88" class="pln"> <span class="key">def</span> <span class="nam">position</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t89" class="stm mis"> <span class="key">raise</span> <span class="nam">NotImplementedError</span><span class="strut"> </span></p> +<p id="t90" class="pln"><span class="strut"> </span></p> +<p id="t91" class="stm run hide_run"> <span class="op">@</span><span class="nam">abstractmethod</span><span class="strut"> </span></p> +<p id="t92" class="pln"> <span class="key">def</span> <span class="nam">set_position</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">position</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t93" class="stm mis"> <span class="key">raise</span> <span class="nam">NotImplementedError</span><span class="strut"> </span></p> +<p id="t94" class="pln"><span class="strut"> </span></p> +<p id="t95" class="pln"><span class="strut"> </span></p> +<p id="t96" class="stm run hide_run"><span class="key">class</span> <span class="nam">ConstantDriftingParticle</span><span class="op">(</span><span class="nam">DriftingParticle</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t97" class="pln"><span class="strut"> </span></p> +<p id="t98" class="stm run hide_run"> <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">density</span><span class="op">,</span> <span class="nam">diameter</span><span class="op">,</span> <span class="nam">initial_position</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t99" class="pln"><span class="strut"> </span></p> +<p id="t100" class="stm run hide_run"> <span class="nam">initial_position</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">array</span><span class="op">(</span><span class="nam">initial_position</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t101" class="stm run hide_run"> <span class="nam">density</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">array</span><span class="op">(</span><span class="nam">density</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t102" class="stm run hide_run"> <span class="nam">diameter</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">array</span><span class="op">(</span><span class="nam">diameter</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t103" class="pln"><span class="strut"> </span></p> +<p id="t104" class="stm run hide_run"> <span class="key">if</span> <span class="nam">initial_position</span><span class="op">.</span><span class="nam">shape</span><span class="op">[</span><span class="num">1</span><span class="op">]</span> <span class="op">==</span> <span class="num">3</span> <span class="key">and</span> <span class="nam">initial_position</span><span class="op">.</span><span class="nam">ndim</span> <span class="op">==</span> <span class="num">2</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t105" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_position</span> <span class="op">=</span> <span class="nam">initial_position</span><span class="strut"> </span></p> +<p id="t106" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_number_of_eggs</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_position</span><span class="op">.</span><span class="nam">shape</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t107" class="pln"> <span class="key">else</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t108" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="str">'Initial position array must be n by 3'</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t109" class="pln"><span class="strut"> </span></p> +<p id="t110" class="stm run hide_run"> <span class="nam">number_of_particles</span> <span class="op">=</span> <span class="nam">initial_position</span><span class="op">.</span><span class="nam">shape</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t111" class="pln"><span class="strut"> </span></p> +<p id="t112" class="stm run hide_run"> <span class="key">if</span> <span class="nam">density</span><span class="op">.</span><span class="nam">shape</span><span class="op">[</span><span class="num">0</span><span class="op">]</span> <span class="op">!=</span> <span class="nam">number_of_particles</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t113" class="pln"> <span class="key">or</span> <span class="nam">diameter</span><span class="op">.</span><span class="nam">shape</span><span class="op">[</span><span class="num">0</span><span class="op">]</span> <span class="op">!=</span> <span class="nam">number_of_particles</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t114" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="strut"> </span></p> +<p id="t115" class="pln"> <span class="str">'The zero axis of density, diameter, and initial_position '</span> <span class="op">+</span><span class="strut"> </span></p> +<p id="t116" class="pln"> <span class="str">'must be consistent'</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t117" class="pln"><span class="strut"> </span></p> +<p id="t118" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_density</span> <span class="op">=</span> <span class="nam">density</span><span class="strut"> </span></p> +<p id="t119" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_diameter</span> <span class="op">=</span> <span class="nam">diameter</span><span class="strut"> </span></p> +<p id="t120" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_position</span> <span class="op">=</span> <span class="nam">initial_position</span><span class="strut"> </span></p> +<p id="t121" class="pln"><span class="strut"> </span></p> +<p id="t122" class="stm run hide_run"> <span class="key">def</span> <span class="nam">density</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="op">*</span><span class="nam">args</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t123" class="pln"> <span class="str">"""</span><span class="strut"> </span></p> +<p id="t124" class="pln"><span class="strut"> </span></p> +<p id="t125" class="pln"><span class="str"> :return:</span><span class="strut"> </span></p> +<p id="t126" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t127" class="pln"><span class="strut"> </span></p> +<p id="t128" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_density</span><span class="strut"> </span></p> +<p id="t129" class="pln"><span class="strut"> </span></p> +<p id="t130" class="stm run hide_run"> <span class="key">def</span> <span class="nam">diameter</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t131" class="pln"> <span class="str">"""</span><span class="strut"> </span></p> +<p id="t132" class="pln"><span class="strut"> </span></p> +<p id="t133" class="pln"><span class="str"> :return:</span><span class="strut"> </span></p> +<p id="t134" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t135" class="pln"><span class="strut"> </span></p> +<p id="t136" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_diameter</span><span class="strut"> </span></p> +<p id="t137" class="pln"><span class="strut"> </span></p> +<p id="t138" class="stm run hide_run"> <span class="key">def</span> <span class="nam">position</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t139" class="pln"> <span class="str">"""</span><span class="strut"> </span></p> +<p id="t140" class="pln"><span class="strut"> </span></p> +<p id="t141" class="pln"><span class="str"> :return:</span><span class="strut"> </span></p> +<p id="t142" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t143" class="pln"><span class="strut"> </span></p> +<p id="t144" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_position</span><span class="strut"> </span></p> +<p id="t145" class="pln"><span class="strut"> </span></p> +<p id="t146" class="stm run hide_run"> <span class="key">def</span> <span class="nam">set_position</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">position</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t147" class="pln"> <span class="str">"""</span><span class="strut"> </span></p> +<p id="t148" class="pln"><span class="strut"> </span></p> +<p id="t149" class="pln"><span class="str"> :return:</span><span class="strut"> </span></p> +<p id="t150" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t151" class="pln"><span class="strut"> </span></p> +<p id="t152" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_position</span> <span class="op">=</span> <span class="nam">position</span><span class="strut"> </span></p> + + </td> + </tr> + </table> +</div> + +<div id="footer"> + <div class="content"> + <p> + <a class="nav" href="index.html">« index</a> <a class="nav" href="https://coverage.readthedocs.io">coverage.py v4.5.3</a>, + created at 2019-07-09 15:15 + </p> + </div> +</div> + +</body> +</html> diff --git a/coverage_report/fluegg_gui___init___py.html b/coverage_report/fluegg_gui___init___py.html new file mode 100644 index 0000000..f798c84 --- /dev/null +++ b/coverage_report/fluegg_gui___init___py.html @@ -0,0 +1,89 @@ + + + +<!DOCTYPE html> +<html> +<head> + <meta http-equiv="Content-Type" content="text/html; charset=utf-8"> + + + <meta http-equiv="X-UA-Compatible" content="IE=emulateIE7" /> + <title>Coverage for fluegg\gui\__init__.py: 100%</title> + <link rel="stylesheet" href="style.css" type="text/css"> + + <script type="text/javascript" src="jquery.min.js"></script> + <script type="text/javascript" src="jquery.hotkeys.js"></script> + <script type="text/javascript" src="jquery.isonscreen.js"></script> + <script type="text/javascript" src="coverage_html.js"></script> + <script type="text/javascript"> + jQuery(document).ready(coverage.pyfile_ready); + </script> +</head> +<body class="pyfile"> + +<div id="header"> + <div class="content"> + <h1>Coverage for <b>fluegg\gui\__init__.py</b> : + <span class="pc_cov">100%</span> + </h1> + + <img id="keyboard_icon" src="keybd_closed.png" alt="Show keyboard shortcuts" /> + + <h2 class="stats"> + 0 statements + <span class="run hide_run shortkey_r button_toggle_run">0 run</span> + <span class="mis shortkey_m button_toggle_mis">0 missing</span> + <span class="exc shortkey_x button_toggle_exc">0 excluded</span> + + + </h2> + </div> +</div> + +<div class="help_panel"> + <img id="panel_icon" src="keybd_open.png" alt="Hide keyboard shortcuts" /> + <p class="legend">Hot-keys on this page</p> + <div> + <p class="keyhelp"> + <span class="key">r</span> + <span class="key">m</span> + <span class="key">x</span> + <span class="key">p</span> toggle line displays + </p> + <p class="keyhelp"> + <span class="key">j</span> + <span class="key">k</span> next/prev highlighted chunk + </p> + <p class="keyhelp"> + <span class="key">0</span> (zero) top of page + </p> + <p class="keyhelp"> + <span class="key">1</span> (one) first highlighted chunk + </p> + </div> +</div> + +<div id="source"> + <table> + <tr> + <td class="linenos"> + + </td> + <td class="text"> + + </td> + </tr> + </table> +</div> + +<div id="footer"> + <div class="content"> + <p> + <a class="nav" href="index.html">« index</a> <a class="nav" href="https://coverage.readthedocs.io">coverage.py v4.5.3</a>, + created at 2019-07-09 15:15 + </p> + </div> +</div> + +</body> +</html> diff --git a/coverage_report/fluegg_gui_gui_layout_py.html b/coverage_report/fluegg_gui_gui_layout_py.html new file mode 100644 index 0000000..78a11f3 --- /dev/null +++ b/coverage_report/fluegg_gui_gui_layout_py.html @@ -0,0 +1,665 @@ + + + +<!DOCTYPE html> +<html> +<head> + <meta http-equiv="Content-Type" content="text/html; charset=utf-8"> + + + <meta http-equiv="X-UA-Compatible" content="IE=emulateIE7" /> + <title>Coverage for fluegg\gui\gui_layout.py: 1%</title> + <link rel="stylesheet" href="style.css" type="text/css"> + + <script type="text/javascript" src="jquery.min.js"></script> + <script type="text/javascript" src="jquery.hotkeys.js"></script> + <script type="text/javascript" src="jquery.isonscreen.js"></script> + <script type="text/javascript" src="coverage_html.js"></script> + <script type="text/javascript"> + jQuery(document).ready(coverage.pyfile_ready); + </script> +</head> +<body class="pyfile"> + +<div id="header"> + <div class="content"> + <h1>Coverage for <b>fluegg\gui\gui_layout.py</b> : + <span class="pc_cov">1%</span> + </h1> + + <img id="keyboard_icon" src="keybd_closed.png" alt="Show keyboard shortcuts" /> + + <h2 class="stats"> + 276 statements + <span class="run hide_run shortkey_r button_toggle_run">4 run</span> + <span class="mis shortkey_m button_toggle_mis">272 missing</span> + <span class="exc shortkey_x button_toggle_exc">0 excluded</span> + + + </h2> + </div> +</div> + +<div class="help_panel"> + <img id="panel_icon" src="keybd_open.png" alt="Hide keyboard shortcuts" /> + <p class="legend">Hot-keys on this page</p> + <div> + <p class="keyhelp"> + <span class="key">r</span> + <span class="key">m</span> + <span class="key">x</span> + <span class="key">p</span> toggle line displays + </p> + <p class="keyhelp"> + <span class="key">j</span> + <span class="key">k</span> next/prev highlighted chunk + </p> + <p class="keyhelp"> + <span class="key">0</span> (zero) top of page + </p> + <p class="keyhelp"> + <span class="key">1</span> (one) first highlighted chunk + </p> + </div> +</div> + +<div id="source"> + <table> + <tr> + <td class="linenos"> +<p id="n1" class="pln"><a href="#n1">1</a></p> +<p id="n2" class="pln"><a href="#n2">2</a></p> +<p id="n3" class="pln"><a href="#n3">3</a></p> +<p id="n4" class="pln"><a href="#n4">4</a></p> +<p id="n5" class="pln"><a href="#n5">5</a></p> +<p id="n6" class="pln"><a href="#n6">6</a></p> +<p id="n7" class="pln"><a href="#n7">7</a></p> +<p id="n8" class="pln"><a href="#n8">8</a></p> +<p id="n9" class="stm run hide_run"><a href="#n9">9</a></p> +<p id="n10" class="pln"><a href="#n10">10</a></p> +<p id="n11" class="stm run hide_run"><a href="#n11">11</a></p> +<p id="n12" class="stm run hide_run"><a href="#n12">12</a></p> +<p id="n13" class="stm mis"><a href="#n13">13</a></p> +<p id="n14" class="stm mis"><a href="#n14">14</a></p> +<p id="n15" class="stm mis"><a href="#n15">15</a></p> +<p id="n16" class="stm mis"><a href="#n16">16</a></p> +<p id="n17" class="stm mis"><a href="#n17">17</a></p> +<p id="n18" class="stm mis"><a href="#n18">18</a></p> +<p id="n19" class="stm mis"><a href="#n19">19</a></p> +<p id="n20" class="stm mis"><a href="#n20">20</a></p> +<p id="n21" class="stm mis"><a href="#n21">21</a></p> +<p id="n22" class="stm mis"><a href="#n22">22</a></p> +<p id="n23" class="stm mis"><a href="#n23">23</a></p> +<p id="n24" class="stm mis"><a href="#n24">24</a></p> +<p id="n25" class="stm mis"><a href="#n25">25</a></p> +<p id="n26" class="stm mis"><a href="#n26">26</a></p> +<p id="n27" class="stm mis"><a href="#n27">27</a></p> +<p id="n28" class="stm mis"><a href="#n28">28</a></p> +<p id="n29" class="stm mis"><a href="#n29">29</a></p> +<p id="n30" class="stm mis"><a href="#n30">30</a></p> +<p id="n31" class="stm mis"><a href="#n31">31</a></p> +<p id="n32" class="stm mis"><a href="#n32">32</a></p> +<p id="n33" class="stm mis"><a href="#n33">33</a></p> +<p id="n34" class="stm mis"><a href="#n34">34</a></p> +<p id="n35" class="stm mis"><a href="#n35">35</a></p> +<p id="n36" class="stm mis"><a href="#n36">36</a></p> +<p id="n37" class="stm mis"><a href="#n37">37</a></p> +<p id="n38" class="stm mis"><a href="#n38">38</a></p> +<p id="n39" class="stm mis"><a href="#n39">39</a></p> +<p id="n40" class="stm mis"><a href="#n40">40</a></p> +<p id="n41" class="stm mis"><a href="#n41">41</a></p> +<p id="n42" class="stm mis"><a href="#n42">42</a></p> +<p id="n43" class="stm mis"><a href="#n43">43</a></p> +<p id="n44" class="stm mis"><a href="#n44">44</a></p> +<p id="n45" class="stm mis"><a href="#n45">45</a></p> +<p id="n46" class="stm mis"><a href="#n46">46</a></p> +<p id="n47" class="stm mis"><a href="#n47">47</a></p> +<p id="n48" class="stm mis"><a href="#n48">48</a></p> +<p id="n49" class="stm mis"><a href="#n49">49</a></p> +<p id="n50" class="stm mis"><a href="#n50">50</a></p> +<p id="n51" class="stm mis"><a href="#n51">51</a></p> +<p id="n52" class="stm mis"><a href="#n52">52</a></p> +<p id="n53" class="stm mis"><a href="#n53">53</a></p> +<p id="n54" class="stm mis"><a href="#n54">54</a></p> +<p id="n55" class="stm mis"><a href="#n55">55</a></p> +<p id="n56" class="stm mis"><a href="#n56">56</a></p> +<p id="n57" class="stm mis"><a href="#n57">57</a></p> +<p id="n58" class="stm mis"><a href="#n58">58</a></p> +<p id="n59" class="stm mis"><a href="#n59">59</a></p> +<p id="n60" class="stm mis"><a href="#n60">60</a></p> +<p id="n61" class="stm mis"><a href="#n61">61</a></p> +<p id="n62" class="stm mis"><a href="#n62">62</a></p> +<p id="n63" class="stm mis"><a href="#n63">63</a></p> +<p id="n64" class="stm mis"><a href="#n64">64</a></p> +<p id="n65" class="stm mis"><a href="#n65">65</a></p> +<p id="n66" class="stm mis"><a href="#n66">66</a></p> +<p id="n67" class="stm mis"><a href="#n67">67</a></p> +<p id="n68" class="stm mis"><a href="#n68">68</a></p> +<p id="n69" class="stm mis"><a href="#n69">69</a></p> +<p id="n70" class="stm mis"><a href="#n70">70</a></p> +<p id="n71" class="stm mis"><a href="#n71">71</a></p> +<p id="n72" class="stm mis"><a href="#n72">72</a></p> +<p id="n73" class="stm mis"><a href="#n73">73</a></p> +<p id="n74" class="stm mis"><a href="#n74">74</a></p> +<p id="n75" class="stm mis"><a href="#n75">75</a></p> +<p id="n76" class="stm mis"><a href="#n76">76</a></p> +<p id="n77" class="stm mis"><a href="#n77">77</a></p> +<p id="n78" class="stm mis"><a href="#n78">78</a></p> +<p id="n79" class="stm mis"><a href="#n79">79</a></p> +<p id="n80" class="stm mis"><a href="#n80">80</a></p> +<p id="n81" class="stm mis"><a href="#n81">81</a></p> +<p id="n82" class="stm mis"><a href="#n82">82</a></p> +<p id="n83" class="stm mis"><a href="#n83">83</a></p> +<p id="n84" class="stm mis"><a href="#n84">84</a></p> +<p id="n85" class="stm mis"><a href="#n85">85</a></p> +<p id="n86" class="stm mis"><a href="#n86">86</a></p> +<p id="n87" class="stm mis"><a href="#n87">87</a></p> +<p id="n88" class="stm mis"><a href="#n88">88</a></p> +<p id="n89" class="stm mis"><a href="#n89">89</a></p> +<p id="n90" class="stm mis"><a href="#n90">90</a></p> +<p id="n91" class="stm mis"><a href="#n91">91</a></p> +<p id="n92" class="stm mis"><a href="#n92">92</a></p> +<p id="n93" class="stm mis"><a href="#n93">93</a></p> +<p id="n94" class="stm mis"><a href="#n94">94</a></p> +<p id="n95" class="stm mis"><a href="#n95">95</a></p> +<p id="n96" class="stm mis"><a href="#n96">96</a></p> +<p id="n97" class="stm mis"><a href="#n97">97</a></p> +<p id="n98" class="stm mis"><a href="#n98">98</a></p> +<p id="n99" class="stm mis"><a href="#n99">99</a></p> +<p id="n100" class="stm mis"><a href="#n100">100</a></p> +<p id="n101" class="stm mis"><a href="#n101">101</a></p> +<p id="n102" class="stm mis"><a href="#n102">102</a></p> +<p id="n103" class="stm mis"><a href="#n103">103</a></p> +<p id="n104" class="stm mis"><a href="#n104">104</a></p> +<p id="n105" class="stm mis"><a href="#n105">105</a></p> +<p id="n106" class="stm mis"><a href="#n106">106</a></p> +<p id="n107" class="stm mis"><a href="#n107">107</a></p> +<p id="n108" class="stm mis"><a href="#n108">108</a></p> +<p id="n109" class="stm mis"><a href="#n109">109</a></p> +<p id="n110" class="stm mis"><a href="#n110">110</a></p> +<p id="n111" class="stm mis"><a href="#n111">111</a></p> +<p id="n112" class="stm mis"><a href="#n112">112</a></p> +<p id="n113" class="stm mis"><a href="#n113">113</a></p> +<p id="n114" class="stm mis"><a href="#n114">114</a></p> +<p id="n115" class="stm mis"><a href="#n115">115</a></p> +<p id="n116" class="stm mis"><a href="#n116">116</a></p> +<p id="n117" class="stm mis"><a href="#n117">117</a></p> +<p id="n118" class="stm mis"><a href="#n118">118</a></p> +<p id="n119" class="stm mis"><a href="#n119">119</a></p> +<p id="n120" class="stm mis"><a href="#n120">120</a></p> +<p id="n121" class="stm mis"><a href="#n121">121</a></p> +<p id="n122" class="stm mis"><a href="#n122">122</a></p> +<p id="n123" class="stm mis"><a href="#n123">123</a></p> +<p id="n124" class="stm mis"><a href="#n124">124</a></p> +<p id="n125" class="stm mis"><a href="#n125">125</a></p> +<p id="n126" class="stm mis"><a href="#n126">126</a></p> +<p id="n127" class="stm mis"><a href="#n127">127</a></p> +<p id="n128" class="stm mis"><a href="#n128">128</a></p> +<p id="n129" class="stm mis"><a href="#n129">129</a></p> +<p id="n130" class="stm mis"><a href="#n130">130</a></p> +<p id="n131" class="stm mis"><a href="#n131">131</a></p> +<p id="n132" class="stm mis"><a href="#n132">132</a></p> +<p id="n133" class="stm mis"><a href="#n133">133</a></p> +<p id="n134" class="stm mis"><a href="#n134">134</a></p> +<p id="n135" class="stm mis"><a href="#n135">135</a></p> +<p id="n136" class="stm mis"><a href="#n136">136</a></p> +<p id="n137" class="stm mis"><a href="#n137">137</a></p> +<p id="n138" class="stm mis"><a href="#n138">138</a></p> +<p id="n139" class="stm mis"><a href="#n139">139</a></p> +<p id="n140" class="stm mis"><a href="#n140">140</a></p> +<p id="n141" class="stm mis"><a href="#n141">141</a></p> +<p id="n142" class="stm mis"><a href="#n142">142</a></p> +<p id="n143" class="stm mis"><a href="#n143">143</a></p> +<p id="n144" class="stm mis"><a href="#n144">144</a></p> +<p id="n145" class="stm mis"><a href="#n145">145</a></p> +<p id="n146" class="stm mis"><a href="#n146">146</a></p> +<p id="n147" class="stm mis"><a href="#n147">147</a></p> +<p id="n148" class="stm mis"><a href="#n148">148</a></p> +<p id="n149" class="stm mis"><a href="#n149">149</a></p> +<p id="n150" class="stm mis"><a href="#n150">150</a></p> +<p id="n151" class="stm mis"><a href="#n151">151</a></p> +<p id="n152" class="stm mis"><a href="#n152">152</a></p> +<p id="n153" class="stm mis"><a href="#n153">153</a></p> +<p id="n154" class="stm mis"><a href="#n154">154</a></p> +<p id="n155" class="stm mis"><a href="#n155">155</a></p> +<p id="n156" class="stm mis"><a href="#n156">156</a></p> +<p id="n157" class="stm mis"><a href="#n157">157</a></p> +<p id="n158" class="stm mis"><a href="#n158">158</a></p> +<p id="n159" class="stm mis"><a href="#n159">159</a></p> +<p id="n160" class="stm mis"><a href="#n160">160</a></p> +<p id="n161" class="stm mis"><a href="#n161">161</a></p> +<p id="n162" class="stm mis"><a href="#n162">162</a></p> +<p id="n163" class="stm mis"><a href="#n163">163</a></p> +<p id="n164" class="stm mis"><a href="#n164">164</a></p> +<p id="n165" class="stm mis"><a href="#n165">165</a></p> +<p id="n166" class="stm mis"><a href="#n166">166</a></p> +<p id="n167" class="stm mis"><a href="#n167">167</a></p> +<p id="n168" class="stm mis"><a href="#n168">168</a></p> +<p id="n169" class="stm mis"><a href="#n169">169</a></p> +<p id="n170" class="stm mis"><a href="#n170">170</a></p> +<p id="n171" class="stm mis"><a href="#n171">171</a></p> +<p id="n172" class="stm mis"><a href="#n172">172</a></p> +<p id="n173" class="stm mis"><a href="#n173">173</a></p> +<p id="n174" class="stm mis"><a href="#n174">174</a></p> +<p id="n175" class="stm mis"><a href="#n175">175</a></p> +<p id="n176" class="stm mis"><a href="#n176">176</a></p> +<p id="n177" class="stm mis"><a href="#n177">177</a></p> +<p id="n178" class="stm mis"><a href="#n178">178</a></p> +<p id="n179" class="stm mis"><a href="#n179">179</a></p> +<p id="n180" class="stm mis"><a href="#n180">180</a></p> +<p id="n181" class="stm mis"><a href="#n181">181</a></p> +<p id="n182" class="stm mis"><a href="#n182">182</a></p> +<p id="n183" class="stm mis"><a href="#n183">183</a></p> +<p id="n184" class="stm mis"><a href="#n184">184</a></p> +<p id="n185" class="stm mis"><a href="#n185">185</a></p> +<p id="n186" class="stm mis"><a href="#n186">186</a></p> +<p id="n187" class="stm mis"><a href="#n187">187</a></p> +<p id="n188" class="stm mis"><a href="#n188">188</a></p> +<p id="n189" class="stm mis"><a href="#n189">189</a></p> +<p id="n190" class="stm mis"><a href="#n190">190</a></p> +<p id="n191" class="stm mis"><a href="#n191">191</a></p> +<p id="n192" class="stm mis"><a href="#n192">192</a></p> +<p id="n193" class="stm mis"><a href="#n193">193</a></p> +<p id="n194" class="stm mis"><a href="#n194">194</a></p> +<p id="n195" class="stm mis"><a href="#n195">195</a></p> +<p id="n196" class="stm mis"><a href="#n196">196</a></p> +<p id="n197" class="stm mis"><a href="#n197">197</a></p> +<p id="n198" class="stm mis"><a href="#n198">198</a></p> +<p id="n199" class="stm mis"><a href="#n199">199</a></p> +<p id="n200" class="stm mis"><a href="#n200">200</a></p> +<p id="n201" class="stm mis"><a href="#n201">201</a></p> +<p id="n202" class="stm mis"><a href="#n202">202</a></p> +<p id="n203" class="stm mis"><a href="#n203">203</a></p> +<p id="n204" class="stm mis"><a href="#n204">204</a></p> +<p id="n205" class="stm mis"><a href="#n205">205</a></p> +<p id="n206" class="stm mis"><a href="#n206">206</a></p> +<p id="n207" class="stm mis"><a href="#n207">207</a></p> +<p id="n208" class="stm mis"><a href="#n208">208</a></p> +<p id="n209" class="stm mis"><a href="#n209">209</a></p> +<p id="n210" class="stm mis"><a href="#n210">210</a></p> +<p id="n211" class="stm mis"><a href="#n211">211</a></p> +<p id="n212" class="stm mis"><a href="#n212">212</a></p> +<p id="n213" class="stm mis"><a href="#n213">213</a></p> +<p id="n214" class="stm mis"><a href="#n214">214</a></p> +<p id="n215" class="stm mis"><a href="#n215">215</a></p> +<p id="n216" class="stm mis"><a href="#n216">216</a></p> +<p id="n217" class="stm mis"><a href="#n217">217</a></p> +<p id="n218" class="stm mis"><a href="#n218">218</a></p> +<p id="n219" class="stm mis"><a href="#n219">219</a></p> +<p id="n220" class="stm mis"><a href="#n220">220</a></p> +<p id="n221" class="stm mis"><a href="#n221">221</a></p> +<p id="n222" class="stm mis"><a href="#n222">222</a></p> +<p id="n223" class="stm mis"><a href="#n223">223</a></p> +<p id="n224" class="stm mis"><a href="#n224">224</a></p> +<p id="n225" class="stm mis"><a href="#n225">225</a></p> +<p id="n226" class="stm mis"><a href="#n226">226</a></p> +<p id="n227" class="stm mis"><a href="#n227">227</a></p> +<p id="n228" class="stm mis"><a href="#n228">228</a></p> +<p id="n229" class="stm mis"><a href="#n229">229</a></p> +<p id="n230" class="stm mis"><a href="#n230">230</a></p> +<p id="n231" class="stm mis"><a href="#n231">231</a></p> +<p id="n232" class="stm mis"><a href="#n232">232</a></p> +<p id="n233" class="stm mis"><a href="#n233">233</a></p> +<p id="n234" class="stm mis"><a href="#n234">234</a></p> +<p id="n235" class="stm mis"><a href="#n235">235</a></p> +<p id="n236" class="stm mis"><a href="#n236">236</a></p> +<p id="n237" class="stm mis"><a href="#n237">237</a></p> +<p id="n238" class="stm mis"><a href="#n238">238</a></p> +<p id="n239" class="stm mis"><a href="#n239">239</a></p> +<p id="n240" class="stm mis"><a href="#n240">240</a></p> +<p id="n241" class="stm mis"><a href="#n241">241</a></p> +<p id="n242" class="stm mis"><a href="#n242">242</a></p> +<p id="n243" class="stm mis"><a href="#n243">243</a></p> +<p id="n244" class="stm mis"><a href="#n244">244</a></p> +<p id="n245" class="stm mis"><a href="#n245">245</a></p> +<p id="n246" class="stm mis"><a href="#n246">246</a></p> +<p id="n247" class="stm mis"><a href="#n247">247</a></p> +<p id="n248" class="stm mis"><a href="#n248">248</a></p> +<p id="n249" class="stm mis"><a href="#n249">249</a></p> +<p id="n250" class="stm mis"><a href="#n250">250</a></p> +<p id="n251" class="stm mis"><a href="#n251">251</a></p> +<p id="n252" class="pln"><a href="#n252">252</a></p> +<p id="n253" class="stm mis"><a href="#n253">253</a></p> +<p id="n254" class="stm mis"><a href="#n254">254</a></p> +<p id="n255" class="pln"><a href="#n255">255</a></p> +<p id="n256" class="stm run hide_run"><a href="#n256">256</a></p> +<p id="n257" class="stm mis"><a href="#n257">257</a></p> +<p id="n258" class="stm mis"><a href="#n258">258</a></p> +<p id="n259" class="stm mis"><a href="#n259">259</a></p> +<p id="n260" class="stm mis"><a href="#n260">260</a></p> +<p id="n261" class="stm mis"><a href="#n261">261</a></p> +<p id="n262" class="stm mis"><a href="#n262">262</a></p> +<p id="n263" class="stm mis"><a href="#n263">263</a></p> +<p id="n264" class="stm mis"><a href="#n264">264</a></p> +<p id="n265" class="stm mis"><a href="#n265">265</a></p> +<p id="n266" class="stm mis"><a href="#n266">266</a></p> +<p id="n267" class="stm mis"><a href="#n267">267</a></p> +<p id="n268" class="stm mis"><a href="#n268">268</a></p> +<p id="n269" class="stm mis"><a href="#n269">269</a></p> +<p id="n270" class="stm mis"><a href="#n270">270</a></p> +<p id="n271" class="stm mis"><a href="#n271">271</a></p> +<p id="n272" class="stm mis"><a href="#n272">272</a></p> +<p id="n273" class="stm mis"><a href="#n273">273</a></p> +<p id="n274" class="stm mis"><a href="#n274">274</a></p> +<p id="n275" class="stm mis"><a href="#n275">275</a></p> +<p id="n276" class="stm mis"><a href="#n276">276</a></p> +<p id="n277" class="stm mis"><a href="#n277">277</a></p> +<p id="n278" class="stm mis"><a href="#n278">278</a></p> +<p id="n279" class="stm mis"><a href="#n279">279</a></p> +<p id="n280" class="stm mis"><a href="#n280">280</a></p> +<p id="n281" class="stm mis"><a href="#n281">281</a></p> +<p id="n282" class="stm mis"><a href="#n282">282</a></p> +<p id="n283" class="stm mis"><a href="#n283">283</a></p> +<p id="n284" class="stm mis"><a href="#n284">284</a></p> +<p id="n285" class="stm mis"><a href="#n285">285</a></p> +<p id="n286" class="stm mis"><a href="#n286">286</a></p> +<p id="n287" class="stm mis"><a href="#n287">287</a></p> +<p id="n288" class="pln"><a href="#n288">288</a></p> + + </td> + <td class="text"> +<p id="t1" class="pln"><span class="com"># -*- coding: utf-8 -*-</span><span class="strut"> </span></p> +<p id="t2" class="pln"><span class="strut"> </span></p> +<p id="t3" class="pln"><span class="com"># Form implementation generated from reading ui file 'gui_layout.ui'</span><span class="strut"> </span></p> +<p id="t4" class="pln"><span class="com">#</span><span class="strut"> </span></p> +<p id="t5" class="pln"><span class="com"># Created by: PyQt5 UI code generator 5.11.3</span><span class="strut"> </span></p> +<p id="t6" class="pln"><span class="com">#</span><span class="strut"> </span></p> +<p id="t7" class="pln"><span class="com"># WARNING! All changes made in this file will be lost!</span><span class="strut"> </span></p> +<p id="t8" class="pln"><span class="strut"> </span></p> +<p id="t9" class="stm run hide_run"><span class="key">from</span> <span class="nam">PyQt5</span> <span class="key">import</span> <span class="nam">QtCore</span><span class="op">,</span> <span class="nam">QtGui</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="strut"> </span></p> +<p id="t10" class="pln"><span class="strut"> </span></p> +<p id="t11" class="stm run hide_run"><span class="key">class</span> <span class="nam">Ui_MainWindow</span><span class="op">(</span><span class="nam">object</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t12" class="stm run hide_run"> <span class="key">def</span> <span class="nam">setupUi</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">MainWindow</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t13" class="stm mis"> <span class="nam">MainWindow</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"MainWindow"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t14" class="stm mis"> <span class="nam">MainWindow</span><span class="op">.</span><span class="nam">resize</span><span class="op">(</span><span class="num">334</span><span class="op">,</span> <span class="num">523</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t15" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">centralwidget</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QWidget</span><span class="op">(</span><span class="nam">MainWindow</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t16" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">centralwidget</span><span class="op">.</span><span class="nam">setEnabled</span><span class="op">(</span><span class="key">True</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t17" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">centralwidget</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"centralwidget"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t18" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_5</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QVBoxLayout</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">centralwidget</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t19" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_5</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"verticalLayout_5"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t20" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_4</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QVBoxLayout</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t21" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_4</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"verticalLayout_4"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t22" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">groupBox</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QGroupBox</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">centralwidget</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t23" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">groupBox</span><span class="op">.</span><span class="nam">setWhatsThis</span><span class="op">(</span><span class="str">""</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t24" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">groupBox</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"groupBox"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t25" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_11</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QVBoxLayout</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">groupBox</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t26" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_11</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"verticalLayout_11"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t27" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">widget</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">groupBox</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t28" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">widget</span><span class="op">.</span><span class="nam">setWhatsThis</span><span class="op">(</span><span class="str">""</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t29" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">widget</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"widget"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t30" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_14</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QVBoxLayout</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">widget</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t31" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_14</span><span class="op">.</span><span class="nam">setContentsMargins</span><span class="op">(</span><span class="num">0</span><span class="op">,</span> <span class="num">0</span><span class="op">,</span> <span class="num">0</span><span class="op">,</span> <span class="num">0</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t32" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_14</span><span class="op">.</span><span class="nam">setSpacing</span><span class="op">(</span><span class="num">6</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t33" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_14</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"verticalLayout_14"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t34" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QHBoxLayout</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t35" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout</span><span class="op">.</span><span class="nam">setSpacing</span><span class="op">(</span><span class="num">6</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t36" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"horizontalLayout"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t37" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QVBoxLayout</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t38" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"verticalLayout"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t39" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_csv</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QRadioButton</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">widget</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t40" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_csv</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"radioButton_csv"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t41" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_csv</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t42" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_csv</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QLineEdit</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">widget</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t43" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_csv</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="str">""</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t44" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_csv</span><span class="op">.</span><span class="nam">setReadOnly</span><span class="op">(</span><span class="key">True</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t45" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_csv</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"lineEdit_csv"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t46" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_csv</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t47" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout</span><span class="op">.</span><span class="nam">addLayout</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t48" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_2</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QVBoxLayout</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t49" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_2</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"verticalLayout_2"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t50" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_hecras</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QRadioButton</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">widget</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t51" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_hecras</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"radioButton_hecras"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t52" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_2</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_hecras</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t53" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_hecras</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QLineEdit</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">widget</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t54" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_hecras</span><span class="op">.</span><span class="nam">setEnabled</span><span class="op">(</span><span class="key">True</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t55" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_hecras</span><span class="op">.</span><span class="nam">setReadOnly</span><span class="op">(</span><span class="key">True</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t56" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_hecras</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"lineEdit_hecras"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t57" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_2</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_hecras</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t58" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout</span><span class="op">.</span><span class="nam">addLayout</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_2</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t59" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">pushButton_browse</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QPushButton</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">widget</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t60" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">pushButton_browse</span><span class="op">.</span><span class="nam">setEnabled</span><span class="op">(</span><span class="key">False</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t61" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">pushButton_browse</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"pushButton_browse"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t62" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">pushButton_browse</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t63" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_14</span><span class="op">.</span><span class="nam">addLayout</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t64" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_11</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">widget</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t65" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">widget_5</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">groupBox</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t66" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">widget_5</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"widget_5"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t67" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_7</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QVBoxLayout</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">widget_5</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t68" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_7</span><span class="op">.</span><span class="nam">setContentsMargins</span><span class="op">(</span><span class="num">0</span><span class="op">,</span> <span class="num">0</span><span class="op">,</span> <span class="num">0</span><span class="op">,</span> <span class="num">0</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t69" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_7</span><span class="op">.</span><span class="nam">setSpacing</span><span class="op">(</span><span class="num">0</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t70" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_7</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"verticalLayout_7"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t71" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_2</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QHBoxLayout</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t72" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_2</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"horizontalLayout_2"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t73" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_parabolic_constant</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QRadioButton</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">widget_5</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t74" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_parabolic_constant</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"radioButton_parabolic_constant"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t75" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_2</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_parabolic_constant</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t76" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_parabolic</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QRadioButton</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">widget_5</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t77" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_parabolic</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"radioButton_parabolic"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t78" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_2</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_parabolic</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t79" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_constant</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QRadioButton</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">widget_5</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t80" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_constant</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"radioButton_constant"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t81" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_2</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_constant</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t82" class="stm mis"> <span class="nam">spacerItem</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSpacerItem</span><span class="op">(</span><span class="num">40</span><span class="op">,</span> <span class="num">20</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSizePolicy</span><span class="op">.</span><span class="nam">Expanding</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSizePolicy</span><span class="op">.</span><span class="nam">Minimum</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t83" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_2</span><span class="op">.</span><span class="nam">addItem</span><span class="op">(</span><span class="nam">spacerItem</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t84" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_7</span><span class="op">.</span><span class="nam">addLayout</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_2</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t85" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_11</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">widget_5</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t86" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_4</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">groupBox</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t87" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">groupBox_3</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QGroupBox</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">centralwidget</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t88" class="stm mis"> <span class="nam">font</span> <span class="op">=</span> <span class="nam">QtGui</span><span class="op">.</span><span class="nam">QFont</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t89" class="stm mis"> <span class="nam">font</span><span class="op">.</span><span class="nam">setBold</span><span class="op">(</span><span class="key">False</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t90" class="stm mis"> <span class="nam">font</span><span class="op">.</span><span class="nam">setWeight</span><span class="op">(</span><span class="num">50</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t91" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">groupBox_3</span><span class="op">.</span><span class="nam">setFont</span><span class="op">(</span><span class="nam">font</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t92" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">groupBox_3</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"groupBox_3"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t93" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_3</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QVBoxLayout</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">groupBox_3</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t94" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_3</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"verticalLayout_3"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t95" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_8</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QHBoxLayout</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t96" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_8</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"horizontalLayout_8"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t97" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_x</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QLabel</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">groupBox_3</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t98" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_x</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"label_x"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t99" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_8</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">label_x</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t100" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_x</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QLineEdit</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">groupBox_3</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t101" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_x</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"lineEdit_x"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t102" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_8</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_x</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t103" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_y</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QLabel</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">groupBox_3</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t104" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_y</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"label_y"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t105" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_8</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">label_y</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t106" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_y</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QLineEdit</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">groupBox_3</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t107" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_y</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"lineEdit_y"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t108" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_8</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_y</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t109" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_z</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QLabel</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">groupBox_3</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t110" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_z</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"label_z"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t111" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_8</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">label_z</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t112" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_z</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QLineEdit</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">groupBox_3</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t113" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_z</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"lineEdit_z"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t114" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_8</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_z</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t115" class="stm mis"> <span class="nam">spacerItem1</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSpacerItem</span><span class="op">(</span><span class="num">40</span><span class="op">,</span> <span class="num">20</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSizePolicy</span><span class="op">.</span><span class="nam">Expanding</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSizePolicy</span><span class="op">.</span><span class="nam">Minimum</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t116" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_8</span><span class="op">.</span><span class="nam">addItem</span><span class="op">(</span><span class="nam">spacerItem1</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t117" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_3</span><span class="op">.</span><span class="nam">addLayout</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_8</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t118" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_9</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QHBoxLayout</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t119" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_9</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"horizontalLayout_9"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t120" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_number_of_eggs</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QLabel</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">groupBox_3</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t121" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_number_of_eggs</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"label_number_of_eggs"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t122" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_9</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">label_number_of_eggs</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t123" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_number_of_eggs</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QLineEdit</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">groupBox_3</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t124" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_number_of_eggs</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"lineEdit_number_of_eggs"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t125" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_9</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_number_of_eggs</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t126" class="stm mis"> <span class="nam">spacerItem2</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSpacerItem</span><span class="op">(</span><span class="num">40</span><span class="op">,</span> <span class="num">20</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSizePolicy</span><span class="op">.</span><span class="nam">Expanding</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSizePolicy</span><span class="op">.</span><span class="nam">Minimum</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t127" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_9</span><span class="op">.</span><span class="nam">addItem</span><span class="op">(</span><span class="nam">spacerItem2</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t128" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_3</span><span class="op">.</span><span class="nam">addLayout</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_9</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t129" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">widget_7</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">groupBox_3</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t130" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">widget_7</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"widget_7"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t131" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_9</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QVBoxLayout</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">widget_7</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t132" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_9</span><span class="op">.</span><span class="nam">setContentsMargins</span><span class="op">(</span><span class="num">0</span><span class="op">,</span> <span class="num">0</span><span class="op">,</span> <span class="num">0</span><span class="op">,</span> <span class="num">0</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t133" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_9</span><span class="op">.</span><span class="nam">setSpacing</span><span class="op">(</span><span class="num">0</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t134" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_9</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"verticalLayout_9"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t135" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_7</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QHBoxLayout</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t136" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_7</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"horizontalLayout_7"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t137" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_grass</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QRadioButton</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">widget_7</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t138" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_grass</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"radioButton_grass"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t139" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_7</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_grass</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t140" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_silver</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QRadioButton</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">widget_7</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t141" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_silver</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"radioButton_silver"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t142" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_7</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_silver</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t143" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_bighead</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QRadioButton</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">widget_7</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t144" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_bighead</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"radioButton_bighead"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t145" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_7</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_bighead</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t146" class="stm mis"> <span class="nam">spacerItem3</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSpacerItem</span><span class="op">(</span><span class="num">40</span><span class="op">,</span> <span class="num">20</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSizePolicy</span><span class="op">.</span><span class="nam">Expanding</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSizePolicy</span><span class="op">.</span><span class="nam">Minimum</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t147" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_7</span><span class="op">.</span><span class="nam">addItem</span><span class="op">(</span><span class="nam">spacerItem3</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t148" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_9</span><span class="op">.</span><span class="nam">addLayout</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_7</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t149" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_3</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">widget_7</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t150" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">widget_8</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">groupBox_3</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t151" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">widget_8</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"widget_8"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t152" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_12</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QVBoxLayout</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">widget_8</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t153" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_12</span><span class="op">.</span><span class="nam">setContentsMargins</span><span class="op">(</span><span class="num">0</span><span class="op">,</span> <span class="num">0</span><span class="op">,</span> <span class="num">0</span><span class="op">,</span> <span class="num">0</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t154" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_12</span><span class="op">.</span><span class="nam">setSpacing</span><span class="op">(</span><span class="num">0</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t155" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_12</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"verticalLayout_12"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t156" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_10</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QHBoxLayout</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t157" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_10</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"horizontalLayout_10"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t158" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_varying_dd</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QRadioButton</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">widget_8</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t159" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_varying_dd</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"radioButton_varying_dd"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t160" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_10</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_varying_dd</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t161" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_constant_dd</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QRadioButton</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">widget_8</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t162" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_constant_dd</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"radioButton_constant_dd"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t163" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_10</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_constant_dd</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t164" class="stm mis"> <span class="nam">spacerItem4</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSpacerItem</span><span class="op">(</span><span class="num">40</span><span class="op">,</span> <span class="num">20</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSizePolicy</span><span class="op">.</span><span class="nam">Expanding</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSizePolicy</span><span class="op">.</span><span class="nam">Minimum</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t165" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_10</span><span class="op">.</span><span class="nam">addItem</span><span class="op">(</span><span class="nam">spacerItem4</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t166" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_12</span><span class="op">.</span><span class="nam">addLayout</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_10</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t167" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_3</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">widget_8</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t168" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_4</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">groupBox_3</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t169" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">groupBox_2</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QGroupBox</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">centralwidget</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t170" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">groupBox_2</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"groupBox_2"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t171" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_10</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QVBoxLayout</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">groupBox_2</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t172" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_10</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"verticalLayout_10"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t173" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">widget_9</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">groupBox_2</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t174" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">widget_9</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"widget_9"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t175" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_13</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QVBoxLayout</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">widget_9</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t176" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_13</span><span class="op">.</span><span class="nam">setContentsMargins</span><span class="op">(</span><span class="num">0</span><span class="op">,</span> <span class="num">0</span><span class="op">,</span> <span class="num">0</span><span class="op">,</span> <span class="num">0</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t177" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_13</span><span class="op">.</span><span class="nam">setSpacing</span><span class="op">(</span><span class="num">0</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t178" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_13</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"verticalLayout_13"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t179" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_5</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QHBoxLayout</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t180" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_5</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"horizontalLayout_5"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t181" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_forward</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QRadioButton</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">widget_9</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t182" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_forward</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"radioButton_forward"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t183" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_5</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_forward</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t184" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_reverse</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QRadioButton</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">widget_9</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t185" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_reverse</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"radioButton_reverse"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t186" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_5</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_reverse</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t187" class="stm mis"> <span class="nam">spacerItem5</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSpacerItem</span><span class="op">(</span><span class="num">40</span><span class="op">,</span> <span class="num">20</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSizePolicy</span><span class="op">.</span><span class="nam">Expanding</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSizePolicy</span><span class="op">.</span><span class="nam">Minimum</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t188" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_5</span><span class="op">.</span><span class="nam">addItem</span><span class="op">(</span><span class="nam">spacerItem5</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t189" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_13</span><span class="op">.</span><span class="nam">addLayout</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_5</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t190" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_10</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">widget_9</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t191" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_3</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QHBoxLayout</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t192" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_3</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"horizontalLayout_3"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t193" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_duration</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QLabel</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">groupBox_2</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t194" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_duration</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"label_duration"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t195" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_3</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">label_duration</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t196" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_duration</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QLineEdit</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">groupBox_2</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t197" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_duration</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"lineEdit_duration"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t198" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_3</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_duration</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t199" class="stm mis"> <span class="nam">spacerItem6</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSpacerItem</span><span class="op">(</span><span class="num">40</span><span class="op">,</span> <span class="num">20</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSizePolicy</span><span class="op">.</span><span class="nam">Expanding</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSizePolicy</span><span class="op">.</span><span class="nam">Minimum</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t200" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_3</span><span class="op">.</span><span class="nam">addItem</span><span class="op">(</span><span class="nam">spacerItem6</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t201" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_10</span><span class="op">.</span><span class="nam">addLayout</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_3</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t202" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_4</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QHBoxLayout</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t203" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_4</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"horizontalLayout_4"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t204" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_time_step</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QLabel</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">groupBox_2</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t205" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_time_step</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"label_time_step"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t206" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_4</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">label_time_step</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t207" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_time_step</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QLineEdit</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">groupBox_2</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t208" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_time_step</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"lineEdit_time_step"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t209" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_4</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_time_step</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t210" class="stm mis"> <span class="nam">spacerItem7</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSpacerItem</span><span class="op">(</span><span class="num">40</span><span class="op">,</span> <span class="num">20</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSizePolicy</span><span class="op">.</span><span class="nam">Expanding</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSizePolicy</span><span class="op">.</span><span class="nam">Minimum</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t211" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_4</span><span class="op">.</span><span class="nam">addItem</span><span class="op">(</span><span class="nam">spacerItem7</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t212" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_10</span><span class="op">.</span><span class="nam">addLayout</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_4</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t213" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_11</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QHBoxLayout</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t214" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_11</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"horizontalLayout_11"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t215" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_simulation_name</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QLabel</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">groupBox_2</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t216" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_simulation_name</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"label_simulation_name"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t217" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_11</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">label_simulation_name</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t218" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_simulation_name</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QLineEdit</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">groupBox_2</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t219" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_simulation_name</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="str">""</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t220" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_simulation_name</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"lineEdit_simulation_name"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t221" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_11</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_simulation_name</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t222" class="stm mis"> <span class="nam">spacerItem8</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSpacerItem</span><span class="op">(</span><span class="num">40</span><span class="op">,</span> <span class="num">20</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSizePolicy</span><span class="op">.</span><span class="nam">Expanding</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSizePolicy</span><span class="op">.</span><span class="nam">Minimum</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t223" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_11</span><span class="op">.</span><span class="nam">addItem</span><span class="op">(</span><span class="nam">spacerItem8</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t224" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_10</span><span class="op">.</span><span class="nam">addLayout</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_11</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t225" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_15</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QHBoxLayout</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t226" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_15</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"horizontalLayout_15"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t227" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">pushButton_run</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QPushButton</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">groupBox_2</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t228" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">pushButton_run</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"pushButton_run"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t229" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_15</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">pushButton_run</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t230" class="stm mis"> <span class="nam">spacerItem9</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSpacerItem</span><span class="op">(</span><span class="num">40</span><span class="op">,</span> <span class="num">20</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSizePolicy</span><span class="op">.</span><span class="nam">Expanding</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSizePolicy</span><span class="op">.</span><span class="nam">Minimum</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t231" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_15</span><span class="op">.</span><span class="nam">addItem</span><span class="op">(</span><span class="nam">spacerItem9</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t232" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_10</span><span class="op">.</span><span class="nam">addLayout</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_15</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t233" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_4</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">groupBox_2</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t234" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_5</span><span class="op">.</span><span class="nam">addLayout</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_4</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t235" class="stm mis"> <span class="nam">MainWindow</span><span class="op">.</span><span class="nam">setCentralWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">centralwidget</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t236" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">menubar</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QMenuBar</span><span class="op">(</span><span class="nam">MainWindow</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t237" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">menubar</span><span class="op">.</span><span class="nam">setGeometry</span><span class="op">(</span><span class="nam">QtCore</span><span class="op">.</span><span class="nam">QRect</span><span class="op">(</span><span class="num">0</span><span class="op">,</span> <span class="num">0</span><span class="op">,</span> <span class="num">334</span><span class="op">,</span> <span class="num">22</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t238" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">menubar</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"menubar"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t239" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">menuAbout</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QMenu</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">menubar</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t240" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">menuAbout</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"menuAbout"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t241" class="stm mis"> <span class="nam">MainWindow</span><span class="op">.</span><span class="nam">setMenuBar</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">menubar</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t242" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">statusbar</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QStatusBar</span><span class="op">(</span><span class="nam">MainWindow</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t243" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">statusbar</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"statusbar"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t244" class="stm mis"> <span class="nam">MainWindow</span><span class="op">.</span><span class="nam">setStatusBar</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">statusbar</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t245" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">actionVersion</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QAction</span><span class="op">(</span><span class="nam">MainWindow</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t246" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">actionVersion</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"actionVersion"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t247" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">actionHelp</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QAction</span><span class="op">(</span><span class="nam">MainWindow</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t248" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">actionHelp</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"actionHelp"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t249" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">menuAbout</span><span class="op">.</span><span class="nam">addAction</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">actionVersion</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t250" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">menuAbout</span><span class="op">.</span><span class="nam">addAction</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">actionHelp</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t251" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">menubar</span><span class="op">.</span><span class="nam">addAction</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">menuAbout</span><span class="op">.</span><span class="nam">menuAction</span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t252" class="pln"><span class="strut"> </span></p> +<p id="t253" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">retranslateUi</span><span class="op">(</span><span class="nam">MainWindow</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t254" class="stm mis"> <span class="nam">QtCore</span><span class="op">.</span><span class="nam">QMetaObject</span><span class="op">.</span><span class="nam">connectSlotsByName</span><span class="op">(</span><span class="nam">MainWindow</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t255" class="pln"><span class="strut"> </span></p> +<p id="t256" class="stm run hide_run"> <span class="key">def</span> <span class="nam">retranslateUi</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">MainWindow</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t257" class="stm mis"> <span class="nam">_translate</span> <span class="op">=</span> <span class="nam">QtCore</span><span class="op">.</span><span class="nam">QCoreApplication</span><span class="op">.</span><span class="nam">translate</span><span class="strut"> </span></p> +<p id="t258" class="stm mis"> <span class="nam">MainWindow</span><span class="op">.</span><span class="nam">setWindowTitle</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"MainWindow"</span><span class="op">,</span> <span class="str">"MainWindow"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t259" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">groupBox</span><span class="op">.</span><span class="nam">setTitle</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"MainWindow"</span><span class="op">,</span> <span class="str">"1) Hydraulic Channel"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t260" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_csv</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"MainWindow"</span><span class="op">,</span> <span class="str">"CSV"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t261" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_csv</span><span class="op">.</span><span class="nam">setPlaceholderText</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"MainWindow"</span><span class="op">,</span> <span class="str">"path/to/hydraulics.csv"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t262" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_hecras</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"MainWindow"</span><span class="op">,</span> <span class="str">"HECRAS"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t263" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_hecras</span><span class="op">.</span><span class="nam">setPlaceholderText</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"MainWindow"</span><span class="op">,</span> <span class="str">"hecras project"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t264" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">pushButton_browse</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"MainWindow"</span><span class="op">,</span> <span class="str">"Browse"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t265" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_parabolic_constant</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"MainWindow"</span><span class="op">,</span> <span class="str">"Parabolic-Constant"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t266" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_parabolic</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"MainWindow"</span><span class="op">,</span> <span class="str">"Parabolic"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t267" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_constant</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"MainWindow"</span><span class="op">,</span> <span class="str">"Constant"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t268" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">groupBox_3</span><span class="op">.</span><span class="nam">setTitle</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"MainWindow"</span><span class="op">,</span> <span class="str">"2) Eggs"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t269" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_x</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"MainWindow"</span><span class="op">,</span> <span class="str">"Initial Position (m): X"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t270" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_y</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"MainWindow"</span><span class="op">,</span> <span class="str">"Y"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t271" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_z</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"MainWindow"</span><span class="op">,</span> <span class="str">"Z"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t272" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_number_of_eggs</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"MainWindow"</span><span class="op">,</span> <span class="str">"Number of Eggs"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t273" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_grass</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"MainWindow"</span><span class="op">,</span> <span class="str">"Grass"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t274" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_silver</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"MainWindow"</span><span class="op">,</span> <span class="str">"Silver"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t275" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_bighead</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"MainWindow"</span><span class="op">,</span> <span class="str">"Bighead"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t276" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_varying_dd</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"MainWindow"</span><span class="op">,</span> <span class="str">"Varying ρ / d"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t277" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_constant_dd</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"MainWindow"</span><span class="op">,</span> <span class="str">"Constant ρ / d"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t278" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">groupBox_2</span><span class="op">.</span><span class="nam">setTitle</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"MainWindow"</span><span class="op">,</span> <span class="str">"3) Simulation"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t279" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_forward</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"MainWindow"</span><span class="op">,</span> <span class="str">"Forward"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t280" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_reverse</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"MainWindow"</span><span class="op">,</span> <span class="str">"Reverse"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t281" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_duration</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"MainWindow"</span><span class="op">,</span> <span class="str">"Duration (s)"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t282" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_time_step</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"MainWindow"</span><span class="op">,</span> <span class="str">"Δt (s)"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t283" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_simulation_name</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"MainWindow"</span><span class="op">,</span> <span class="str">"Simulation Name"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t284" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">pushButton_run</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"MainWindow"</span><span class="op">,</span> <span class="str">"Run"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t285" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">menuAbout</span><span class="op">.</span><span class="nam">setTitle</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"MainWindow"</span><span class="op">,</span> <span class="str">"About"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t286" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">actionVersion</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"MainWindow"</span><span class="op">,</span> <span class="str">"Version"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t287" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">actionHelp</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"MainWindow"</span><span class="op">,</span> <span class="str">"Help"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t288" class="pln"><span class="strut"> </span></p> + + </td> + </tr> + </table> +</div> + +<div id="footer"> + <div class="content"> + <p> + <a class="nav" href="index.html">« index</a> <a class="nav" href="https://coverage.readthedocs.io">coverage.py v4.5.3</a>, + created at 2019-07-09 15:15 + </p> + </div> +</div> + +</body> +</html> diff --git a/coverage_report/fluegg_gui_gui_py.html b/coverage_report/fluegg_gui_gui_py.html new file mode 100644 index 0000000..67e6762 --- /dev/null +++ b/coverage_report/fluegg_gui_gui_py.html @@ -0,0 +1,923 @@ + + + +<!DOCTYPE html> +<html> +<head> + <meta http-equiv="Content-Type" content="text/html; charset=utf-8"> + + + <meta http-equiv="X-UA-Compatible" content="IE=emulateIE7" /> + <title>Coverage for fluegg\gui\gui.py: 11%</title> + <link rel="stylesheet" href="style.css" type="text/css"> + + <script type="text/javascript" src="jquery.min.js"></script> + <script type="text/javascript" src="jquery.hotkeys.js"></script> + <script type="text/javascript" src="jquery.isonscreen.js"></script> + <script type="text/javascript" src="coverage_html.js"></script> + <script type="text/javascript"> + jQuery(document).ready(coverage.pyfile_ready); + </script> +</head> +<body class="pyfile"> + +<div id="header"> + <div class="content"> + <h1>Coverage for <b>fluegg\gui\gui.py</b> : + <span class="pc_cov">11%</span> + </h1> + + <img id="keyboard_icon" src="keybd_closed.png" alt="Show keyboard shortcuts" /> + + <h2 class="stats"> + 254 statements + <span class="run hide_run shortkey_r button_toggle_run">29 run</span> + <span class="mis shortkey_m button_toggle_mis">225 missing</span> + <span class="exc shortkey_x button_toggle_exc">0 excluded</span> + + + </h2> + </div> +</div> + +<div class="help_panel"> + <img id="panel_icon" src="keybd_open.png" alt="Hide keyboard shortcuts" /> + <p class="legend">Hot-keys on this page</p> + <div> + <p class="keyhelp"> + <span class="key">r</span> + <span class="key">m</span> + <span class="key">x</span> + <span class="key">p</span> toggle line displays + </p> + <p class="keyhelp"> + <span class="key">j</span> + <span class="key">k</span> next/prev highlighted chunk + </p> + <p class="keyhelp"> + <span class="key">0</span> (zero) top of page + </p> + <p class="keyhelp"> + <span class="key">1</span> (one) first highlighted chunk + </p> + </div> +</div> + +<div id="source"> + <table> + <tr> + <td class="linenos"> +<p id="n1" class="pln"><a href="#n1">1</a></p> +<p id="n2" class="stm run hide_run"><a href="#n2">2</a></p> +<p id="n3" class="stm run hide_run"><a href="#n3">3</a></p> +<p id="n4" class="stm run hide_run"><a href="#n4">4</a></p> +<p id="n5" class="stm run hide_run"><a href="#n5">5</a></p> +<p id="n6" class="pln"><a href="#n6">6</a></p> +<p id="n7" class="stm run hide_run"><a href="#n7">7</a></p> +<p id="n8" class="pln"><a href="#n8">8</a></p> +<p id="n9" class="stm run hide_run"><a href="#n9">9</a></p> +<p id="n10" class="stm run hide_run"><a href="#n10">10</a></p> +<p id="n11" class="stm run hide_run"><a href="#n11">11</a></p> +<p id="n12" class="stm run hide_run"><a href="#n12">12</a></p> +<p id="n13" class="pln"><a href="#n13">13</a></p> +<p id="n14" class="stm run hide_run"><a href="#n14">14</a></p> +<p id="n15" class="pln"><a href="#n15">15</a></p> +<p id="n16" class="pln"><a href="#n16">16</a></p> +<p id="n17" class="stm run hide_run"><a href="#n17">17</a></p> +<p id="n18" class="pln"><a href="#n18">18</a></p> +<p id="n19" class="stm mis"><a href="#n19">19</a></p> +<p id="n20" class="stm mis"><a href="#n20">20</a></p> +<p id="n21" class="stm mis"><a href="#n21">21</a></p> +<p 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id="n183" class="stm mis"><a href="#n183">183</a></p> +<p id="n184" class="stm mis"><a href="#n184">184</a></p> +<p id="n185" class="stm mis"><a href="#n185">185</a></p> +<p id="n186" class="pln"><a href="#n186">186</a></p> +<p id="n187" class="pln"><a href="#n187">187</a></p> +<p id="n188" class="stm mis"><a href="#n188">188</a></p> +<p id="n189" class="stm mis"><a href="#n189">189</a></p> +<p id="n190" class="pln"><a href="#n190">190</a></p> +<p id="n191" class="pln"><a href="#n191">191</a></p> +<p id="n192" class="stm mis"><a href="#n192">192</a></p> +<p id="n193" class="pln"><a href="#n193">193</a></p> +<p id="n194" class="pln"><a href="#n194">194</a></p> +<p id="n195" class="stm mis"><a href="#n195">195</a></p> +<p id="n196" class="stm mis"><a href="#n196">196</a></p> +<p id="n197" class="pln"><a href="#n197">197</a></p> +<p id="n198" class="pln"><a href="#n198">198</a></p> +<p id="n199" class="stm mis"><a href="#n199">199</a></p> +<p id="n200" class="stm mis"><a href="#n200">200</a></p> +<p id="n201" class="stm mis"><a href="#n201">201</a></p> +<p id="n202" class="stm mis"><a href="#n202">202</a></p> +<p id="n203" class="stm mis"><a href="#n203">203</a></p> +<p id="n204" class="stm mis"><a href="#n204">204</a></p> +<p id="n205" class="pln"><a href="#n205">205</a></p> +<p id="n206" class="pln"><a href="#n206">206</a></p> +<p id="n207" class="stm mis"><a href="#n207">207</a></p> +<p id="n208" class="stm mis"><a href="#n208">208</a></p> +<p id="n209" class="stm mis"><a href="#n209">209</a></p> +<p id="n210" class="pln"><a href="#n210">210</a></p> +<p id="n211" class="pln"><a href="#n211">211</a></p> +<p id="n212" class="pln"><a href="#n212">212</a></p> +<p id="n213" class="stm mis"><a href="#n213">213</a></p> +<p id="n214" class="stm mis"><a href="#n214">214</a></p> +<p id="n215" class="pln"><a href="#n215">215</a></p> +<p id="n216" class="stm mis"><a href="#n216">216</a></p> +<p id="n217" class="stm mis"><a href="#n217">217</a></p> +<p id="n218" class="pln"><a href="#n218">218</a></p> +<p id="n219" class="pln"><a href="#n219">219</a></p> +<p id="n220" class="pln"><a href="#n220">220</a></p> +<p id="n221" class="stm mis"><a href="#n221">221</a></p> +<p id="n222" class="stm mis"><a href="#n222">222</a></p> +<p id="n223" class="stm mis"><a href="#n223">223</a></p> +<p id="n224" class="pln"><a href="#n224">224</a></p> +<p id="n225" class="stm mis"><a href="#n225">225</a></p> +<p id="n226" class="stm mis"><a href="#n226">226</a></p> +<p id="n227" class="pln"><a href="#n227">227</a></p> +<p id="n228" class="pln"><a href="#n228">228</a></p> +<p id="n229" class="stm mis"><a href="#n229">229</a></p> +<p id="n230" class="pln"><a href="#n230">230</a></p> +<p id="n231" class="pln"><a href="#n231">231</a></p> +<p id="n232" class="stm mis"><a href="#n232">232</a></p> +<p id="n233" class="stm mis"><a href="#n233">233</a></p> +<p id="n234" class="stm mis"><a href="#n234">234</a></p> +<p id="n235" class="stm mis"><a href="#n235">235</a></p> +<p id="n236" class="stm mis"><a href="#n236">236</a></p> +<p id="n237" class="pln"><a href="#n237">237</a></p> +<p id="n238" class="pln"><a href="#n238">238</a></p> +<p id="n239" class="stm mis"><a href="#n239">239</a></p> +<p id="n240" class="stm mis"><a href="#n240">240</a></p> +<p id="n241" class="stm mis"><a href="#n241">241</a></p> +<p id="n242" class="stm mis"><a href="#n242">242</a></p> +<p id="n243" class="stm mis"><a href="#n243">243</a></p> +<p id="n244" class="stm mis"><a href="#n244">244</a></p> +<p id="n245" class="stm mis"><a href="#n245">245</a></p> +<p id="n246" class="pln"><a href="#n246">246</a></p> +<p id="n247" class="pln"><a href="#n247">247</a></p> +<p id="n248" class="stm mis"><a href="#n248">248</a></p> +<p id="n249" class="pln"><a href="#n249">249</a></p> +<p id="n250" class="stm run hide_run"><a href="#n250">250</a></p> +<p id="n251" class="pln"><a href="#n251">251</a></p> +<p id="n252" class="stm mis"><a href="#n252">252</a></p> +<p id="n253" class="pln"><a href="#n253">253</a></p> +<p id="n254" class="stm run hide_run"><a href="#n254">254</a></p> +<p id="n255" class="pln"><a href="#n255">255</a></p> +<p id="n256" class="stm mis"><a href="#n256">256</a></p> +<p id="n257" class="pln"><a href="#n257">257</a></p> +<p id="n258" class="stm run hide_run"><a href="#n258">258</a></p> +<p id="n259" class="pln"><a href="#n259">259</a></p> +<p id="n260" class="pln"><a href="#n260">260</a></p> +<p id="n261" class="stm mis"><a href="#n261">261</a></p> +<p id="n262" class="stm mis"><a href="#n262">262</a></p> +<p id="n263" class="stm mis"><a href="#n263">263</a></p> +<p id="n264" class="stm mis"><a href="#n264">264</a></p> +<p id="n265" class="stm mis"><a href="#n265">265</a></p> +<p id="n266" class="stm mis"><a href="#n266">266</a></p> +<p id="n267" class="pln"><a href="#n267">267</a></p> +<p id="n268" class="stm run hide_run"><a href="#n268">268</a></p> +<p id="n269" class="pln"><a href="#n269">269</a></p> +<p id="n270" class="stm mis"><a href="#n270">270</a></p> +<p id="n271" class="pln"><a href="#n271">271</a></p> +<p id="n272" class="stm mis"><a href="#n272">272</a></p> +<p id="n273" class="stm mis"><a href="#n273">273</a></p> +<p id="n274" class="pln"><a href="#n274">274</a></p> +<p id="n275" class="pln"><a href="#n275">275</a></p> +<p id="n276" class="stm mis"><a href="#n276">276</a></p> +<p id="n277" class="pln"><a href="#n277">277</a></p> +<p id="n278" class="stm mis"><a href="#n278">278</a></p> +<p id="n279" class="pln"><a href="#n279">279</a></p> +<p id="n280" class="pln"><a href="#n280">280</a></p> +<p id="n281" class="stm mis"><a href="#n281">281</a></p> +<p id="n282" class="stm mis"><a href="#n282">282</a></p> +<p id="n283" class="pln"><a href="#n283">283</a></p> +<p id="n284" class="pln"><a href="#n284">284</a></p> +<p id="n285" class="stm mis"><a href="#n285">285</a></p> +<p id="n286" class="pln"><a href="#n286">286</a></p> +<p id="n287" class="pln"><a href="#n287">287</a></p> +<p id="n288" class="stm mis"><a href="#n288">288</a></p> +<p id="n289" class="stm mis"><a href="#n289">289</a></p> +<p id="n290" class="stm mis"><a href="#n290">290</a></p> +<p id="n291" class="stm mis"><a href="#n291">291</a></p> +<p id="n292" class="pln"><a href="#n292">292</a></p> +<p id="n293" class="stm run hide_run"><a href="#n293">293</a></p> +<p id="n294" class="pln"><a href="#n294">294</a></p> +<p id="n295" class="pln"><a href="#n295">295</a></p> +<p id="n296" class="stm mis"><a href="#n296">296</a></p> +<p id="n297" class="pln"><a href="#n297">297</a></p> +<p id="n298" class="stm mis"><a href="#n298">298</a></p> +<p id="n299" class="pln"><a href="#n299">299</a></p> +<p id="n300" class="pln"><a href="#n300">300</a></p> +<p id="n301" class="stm mis"><a href="#n301">301</a></p> +<p id="n302" class="pln"><a href="#n302">302</a></p> +<p id="n303" class="stm mis"><a href="#n303">303</a></p> +<p id="n304" class="pln"><a href="#n304">304</a></p> +<p id="n305" class="stm mis"><a href="#n305">305</a></p> +<p id="n306" class="pln"><a href="#n306">306</a></p> +<p id="n307" class="pln"><a href="#n307">307</a></p> +<p id="n308" class="stm mis"><a href="#n308">308</a></p> +<p id="n309" class="stm mis"><a href="#n309">309</a></p> +<p id="n310" class="stm mis"><a href="#n310">310</a></p> +<p id="n311" class="pln"><a href="#n311">311</a></p> +<p id="n312" class="pln"><a href="#n312">312</a></p> +<p id="n313" class="stm mis"><a href="#n313">313</a></p> +<p id="n314" class="stm mis"><a href="#n314">314</a></p> +<p id="n315" class="pln"><a href="#n315">315</a></p> +<p id="n316" class="pln"><a href="#n316">316</a></p> +<p id="n317" class="stm mis"><a href="#n317">317</a></p> +<p id="n318" class="stm mis"><a href="#n318">318</a></p> +<p id="n319" class="stm mis"><a href="#n319">319</a></p> +<p id="n320" class="stm mis"><a href="#n320">320</a></p> +<p id="n321" class="pln"><a href="#n321">321</a></p> +<p id="n322" class="stm mis"><a href="#n322">322</a></p> +<p id="n323" class="stm mis"><a href="#n323">323</a></p> +<p id="n324" class="pln"><a href="#n324">324</a></p> +<p id="n325" class="stm mis"><a href="#n325">325</a></p> +<p id="n326" class="stm mis"><a href="#n326">326</a></p> +<p id="n327" class="stm mis"><a href="#n327">327</a></p> +<p id="n328" class="stm mis"><a href="#n328">328</a></p> +<p id="n329" class="stm mis"><a href="#n329">329</a></p> +<p id="n330" class="stm mis"><a href="#n330">330</a></p> +<p id="n331" class="stm mis"><a href="#n331">331</a></p> +<p id="n332" class="stm mis"><a href="#n332">332</a></p> +<p id="n333" class="stm mis"><a href="#n333">333</a></p> +<p id="n334" class="stm mis"><a href="#n334">334</a></p> +<p id="n335" class="pln"><a href="#n335">335</a></p> +<p id="n336" class="stm mis"><a href="#n336">336</a></p> +<p id="n337" class="stm mis"><a href="#n337">337</a></p> +<p id="n338" class="pln"><a href="#n338">338</a></p> +<p id="n339" class="pln"><a href="#n339">339</a></p> +<p id="n340" class="stm mis"><a href="#n340">340</a></p> +<p id="n341" class="stm mis"><a href="#n341">341</a></p> +<p id="n342" class="pln"><a href="#n342">342</a></p> +<p id="n343" class="stm mis"><a href="#n343">343</a></p> +<p id="n344" class="stm mis"><a href="#n344">344</a></p> +<p id="n345" class="pln"><a href="#n345">345</a></p> +<p id="n346" class="stm mis"><a href="#n346">346</a></p> +<p id="n347" class="stm mis"><a href="#n347">347</a></p> +<p id="n348" class="pln"><a href="#n348">348</a></p> +<p id="n349" class="stm mis"><a href="#n349">349</a></p> +<p id="n350" class="stm mis"><a href="#n350">350</a></p> +<p id="n351" class="pln"><a href="#n351">351</a></p> +<p id="n352" class="stm mis"><a href="#n352">352</a></p> +<p id="n353" class="pln"><a href="#n353">353</a></p> +<p id="n354" class="stm mis"><a href="#n354">354</a></p> +<p id="n355" class="stm mis"><a href="#n355">355</a></p> +<p id="n356" class="stm mis"><a href="#n356">356</a></p> +<p id="n357" class="pln"><a href="#n357">357</a></p> +<p id="n358" class="stm mis"><a href="#n358">358</a></p> +<p id="n359" class="stm mis"><a href="#n359">359</a></p> +<p id="n360" class="pln"><a href="#n360">360</a></p> +<p id="n361" class="stm mis"><a href="#n361">361</a></p> +<p id="n362" class="stm mis"><a href="#n362">362</a></p> +<p id="n363" class="pln"><a href="#n363">363</a></p> +<p id="n364" class="stm mis"><a href="#n364">364</a></p> +<p id="n365" class="stm mis"><a href="#n365">365</a></p> +<p id="n366" class="pln"><a href="#n366">366</a></p> +<p id="n367" class="stm mis"><a href="#n367">367</a></p> +<p id="n368" class="stm mis"><a href="#n368">368</a></p> +<p id="n369" class="pln"><a href="#n369">369</a></p> +<p id="n370" class="stm mis"><a href="#n370">370</a></p> +<p id="n371" class="stm mis"><a href="#n371">371</a></p> +<p id="n372" class="pln"><a href="#n372">372</a></p> +<p id="n373" class="stm mis"><a href="#n373">373</a></p> +<p id="n374" class="stm mis"><a href="#n374">374</a></p> +<p id="n375" class="pln"><a href="#n375">375</a></p> +<p id="n376" class="pln"><a href="#n376">376</a></p> +<p id="n377" class="stm mis"><a href="#n377">377</a></p> +<p id="n378" class="stm mis"><a href="#n378">378</a></p> +<p id="n379" class="pln"><a href="#n379">379</a></p> +<p id="n380" class="stm mis"><a href="#n380">380</a></p> +<p id="n381" class="stm mis"><a href="#n381">381</a></p> +<p id="n382" class="pln"><a href="#n382">382</a></p> +<p id="n383" class="pln"><a href="#n383">383</a></p> +<p id="n384" class="stm mis"><a href="#n384">384</a></p> +<p id="n385" class="stm mis"><a href="#n385">385</a></p> +<p id="n386" class="pln"><a href="#n386">386</a></p> +<p id="n387" class="stm mis"><a href="#n387">387</a></p> +<p id="n388" class="stm mis"><a href="#n388">388</a></p> +<p id="n389" class="pln"><a href="#n389">389</a></p> +<p id="n390" class="stm mis"><a href="#n390">390</a></p> +<p id="n391" class="stm mis"><a href="#n391">391</a></p> +<p id="n392" class="pln"><a href="#n392">392</a></p> +<p id="n393" class="stm mis"><a href="#n393">393</a></p> +<p id="n394" class="stm mis"><a href="#n394">394</a></p> +<p id="n395" class="pln"><a href="#n395">395</a></p> +<p id="n396" class="stm mis"><a href="#n396">396</a></p> +<p id="n397" class="stm mis"><a href="#n397">397</a></p> +<p id="n398" class="pln"><a href="#n398">398</a></p> +<p id="n399" class="stm mis"><a href="#n399">399</a></p> +<p id="n400" class="stm mis"><a href="#n400">400</a></p> +<p id="n401" class="pln"><a href="#n401">401</a></p> +<p id="n402" class="stm mis"><a href="#n402">402</a></p> +<p id="n403" class="stm mis"><a href="#n403">403</a></p> +<p id="n404" class="pln"><a href="#n404">404</a></p> +<p id="n405" class="pln"><a href="#n405">405</a></p> +<p id="n406" class="stm mis"><a href="#n406">406</a></p> +<p id="n407" class="pln"><a href="#n407">407</a></p> +<p id="n408" class="stm mis"><a href="#n408">408</a></p> +<p id="n409" class="stm mis"><a href="#n409">409</a></p> +<p id="n410" class="stm mis"><a href="#n410">410</a></p> +<p id="n411" class="stm mis"><a href="#n411">411</a></p> +<p id="n412" class="pln"><a href="#n412">412</a></p> +<p id="n413" class="stm mis"><a href="#n413">413</a></p> +<p id="n414" class="stm mis"><a href="#n414">414</a></p> +<p id="n415" class="stm mis"><a href="#n415">415</a></p> +<p id="n416" class="pln"><a href="#n416">416</a></p> +<p id="n417" class="stm mis"><a href="#n417">417</a></p> + + </td> + <td class="text"> +<p id="t1" class="pln"><span class="com"># Import PyQT for gui</span><span class="strut"> </span></p> +<p id="t2" class="stm run hide_run"><span class="key">import</span> <span class="nam">sys</span><span class="strut"> </span></p> +<p id="t3" class="stm run hide_run"><span class="key">import</span> <span class="nam">traceback</span><span class="strut"> </span></p> +<p id="t4" class="stm run hide_run"><span class="key">import</span> <span class="nam">datetime</span><span class="strut"> </span></p> +<p id="t5" class="stm run hide_run"><span class="key">import</span> <span class="nam">platform</span><span class="strut"> </span></p> +<p id="t6" class="pln"><span class="strut"> </span></p> +<p id="t7" class="stm run hide_run"><span class="key">from</span> <span class="nam">PyQt5</span><span class="op">.</span><span class="nam">QtWidgets</span> <span class="key">import</span> <span class="nam">QMainWindow</span><span class="op">,</span> <span class="nam">QApplication</span><span class="op">,</span> <span class="nam">QMessageBox</span><span class="op">,</span> <span class="nam">QDialog</span><span class="op">,</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t8" class="pln"> <span class="nam">QAction</span><span class="op">,</span> <span class="nam">QWidget</span><span class="op">,</span> <span class="nam">QDesktopWidget</span><span class="op">,</span> <span class="nam">QFileDialog</span><span class="op">,</span> <span class="nam">QProgressBar</span><span class="strut"> </span></p> +<p id="t9" class="stm run hide_run"><span class="key">from</span> <span class="nam">PyQt5</span> <span class="key">import</span> <span class="nam">QtCore</span><span class="op">,</span> <span class="nam">QtGui</span><span class="op">,</span> <span class="nam">uic</span><span class="strut"> </span></p> +<p id="t10" class="stm run hide_run"><span class="key">from</span> <span class="nam">fluegg</span><span class="op">.</span><span class="nam">gui</span><span class="op">.</span><span class="nam">gui_layout</span> <span class="key">import</span> <span class="nam">Ui_MainWindow</span><span class="strut"> </span></p> +<p id="t11" class="stm run hide_run"><span class="key">from</span> <span class="nam">fluegg</span><span class="op">.</span><span class="nam">gui</span><span class="op">.</span><span class="nam">hecras_dialog</span> <span class="key">import</span> <span class="nam">Ui_HecrasDialog</span><span class="strut"> </span></p> +<p id="t12" class="stm run hide_run"><span class="key">from</span> <span class="nam">fluegg</span><span class="op">.</span><span class="nam">simulation</span> <span class="key">import</span> <span class="nam">from_input_dict</span><span class="strut"> </span></p> +<p id="t13" class="pln"><span class="strut"> </span></p> +<p id="t14" class="stm run hide_run"><span class="key">from</span> <span class="nam">fluegg</span><span class="op">.</span><span class="nam">ras</span> <span class="key">import</span> <span class="nam">RASProject</span><span class="strut"> </span></p> +<p id="t15" class="pln"><span class="strut"> </span></p> +<p id="t16" class="pln"><span class="strut"> </span></p> +<p id="t17" class="stm run hide_run"><span class="key">def</span> <span class="nam">get_checked_radio_button</span><span class="op">(</span><span class="nam">buttons</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t18" class="pln"> <span class="str">"""Given a list of grouped radio buttons, returns the checked one"""</span><span class="strut"> </span></p> +<p id="t19" class="stm mis"> <span class="nam">checked</span> <span class="op">=</span> <span class="key">None</span><span class="strut"> </span></p> +<p id="t20" class="stm mis"> <span class="key">for</span> <span class="nam">button</span> <span class="key">in</span> <span class="nam">buttons</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t21" class="stm mis"> <span class="key">if</span> <span class="nam">button</span><span class="op">.</span><span class="nam">isChecked</span><span class="op">(</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t22" class="stm mis"> <span class="nam">checked</span> <span class="op">=</span> <span class="nam">button</span><span class="strut"> </span></p> +<p id="t23" class="stm mis"> <span class="key">return</span> <span class="nam">checked</span><span class="strut"> </span></p> +<p id="t24" class="pln"><span class="strut"> </span></p> +<p id="t25" class="pln"><span class="strut"> </span></p> +<p id="t26" class="stm run hide_run"><span class="key">class</span> <span class="nam">HecrasDialog</span><span class="op">(</span><span class="nam">QDialog</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t27" class="stm run hide_run"> <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">main_window</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t28" class="pln"> <span class="com"># Initialization</span><span class="strut"> </span></p> +<p id="t29" class="stm mis"> <span class="nam">super</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">__init__</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t30" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span> <span class="op">=</span> <span class="nam">Ui_HecrasDialog</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t31" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">setupUi</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t32" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">setWindowTitle</span><span class="op">(</span><span class="str">"Hecras Settings"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t33" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">main_window</span> <span class="op">=</span> <span class="nam">main_window</span><span class="strut"> </span></p> +<p id="t34" class="pln"><span class="strut"> </span></p> +<p id="t35" class="pln"> <span class="com"># Set line edit validators</span><span class="strut"> </span></p> +<p id="t36" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">doubleV</span> <span class="op">=</span> <span class="nam">QtGui</span><span class="op">.</span><span class="nam">QDoubleValidator</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t37" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_temperature</span><span class="op">.</span><span class="nam">setValidator</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">doubleV</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t38" class="pln"><span class="strut"> </span></p> +<p id="t39" class="pln"> <span class="com"># Push button handles</span><span class="strut"> </span></p> +<p id="t40" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">pushButton_ok</span><span class="op">.</span><span class="nam">clicked</span><span class="op">.</span><span class="nam">connect</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">handle_ok</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t41" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">pushButton_cancel</span><span class="op">.</span><span class="nam">clicked</span><span class="op">.</span><span class="nam">connect</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">handle_cancel</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t42" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">pushButton_browse</span><span class="op">.</span><span class="nam">clicked</span><span class="op">.</span><span class="nam">connect</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">handle_browse</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t43" class="pln"><span class="strut"> </span></p> +<p id="t44" class="pln"> <span class="com"># Combo box handles</span><span class="strut"> </span></p> +<p id="t45" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">comboBox_plan</span><span class="op">.</span><span class="nam">currentIndexChanged</span><span class="op">.</span><span class="nam">connect</span><span class="op">(</span><span class="strut"> </span></p> +<p id="t46" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">handle_plan_change</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t47" class="pln"><span class="strut"> </span></p> +<p id="t48" class="pln"> <span class="com"># Radio button handles</span><span class="strut"> </span></p> +<p id="t49" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">radioButton_unsteady</span><span class="op">.</span><span class="nam">clicked</span><span class="op">.</span><span class="nam">connect</span><span class="op">(</span><span class="strut"> </span></p> +<p id="t50" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">handle_steadiness_change</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t51" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">radioButton_steady</span><span class="op">.</span><span class="nam">clicked</span><span class="op">.</span><span class="nam">connect</span><span class="op">(</span><span class="strut"> </span></p> +<p id="t52" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">handle_steadiness_change</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t53" class="pln"><span class="strut"> </span></p> +<p id="t54" class="stm run hide_run"> <span class="key">def</span> <span class="nam">setup</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t55" class="pln"> <span class="str">"""Initial setup of dialog"""</span><span class="strut"> </span></p> +<p id="t56" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">radioButton_steady</span><span class="op">.</span><span class="nam">setChecked</span><span class="op">(</span><span class="key">True</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t57" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">populate_plans</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t58" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">populate_profiles</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t59" class="pln"><span class="strut"> </span></p> +<p id="t60" class="stm run hide_run"> <span class="key">def</span> <span class="nam">handle_ok</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t61" class="pln"> <span class="str">"""Handle function for clicking OK"""</span><span class="strut"> </span></p> +<p id="t62" class="pln"> <span class="com"># Initialize variables</span><span class="strut"> </span></p> +<p id="t63" class="stm mis"> <span class="nam">valid_inputs</span> <span class="op">=</span> <span class="key">True</span><span class="strut"> </span></p> +<p id="t64" class="stm mis"> <span class="nam">error_message</span> <span class="op">=</span> <span class="str">''</span><span class="strut"> </span></p> +<p id="t65" class="pln"><span class="strut"> </span></p> +<p id="t66" class="pln"> <span class="com"># Check to ensure all fields filled</span><span class="strut"> </span></p> +<p id="t67" class="stm mis"> <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_project</span><span class="op">.</span><span class="nam">text</span><span class="op">(</span><span class="op">)</span> <span class="op">==</span> <span class="str">''</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t68" class="stm mis"> <span class="nam">valid_inputs</span> <span class="op">=</span> <span class="key">False</span><span class="strut"> </span></p> +<p id="t69" class="stm mis"> <span class="nam">error_message</span> <span class="op">+=</span> <span class="str">'--Choose a RAS project.\n'</span><span class="strut"> </span></p> +<p id="t70" class="stm mis"> <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">comboBox_plan</span><span class="op">.</span><span class="nam">currentText</span><span class="op">(</span><span class="op">)</span> <span class="op">==</span> <span class="str">''</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t71" class="stm mis"> <span class="nam">valid_inputs</span> <span class="op">=</span> <span class="key">False</span><span class="strut"> </span></p> +<p id="t72" class="stm mis"> <span class="nam">error_message</span> <span class="op">+=</span> <span class="str">'--Choose a RAS plan.\n'</span><span class="strut"> </span></p> +<p id="t73" class="stm mis"> <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">comboBox_profile</span><span class="op">.</span><span class="nam">currentText</span><span class="op">(</span><span class="op">)</span> <span class="op">==</span> <span class="str">''</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t74" class="stm mis"> <span class="nam">valid_inputs</span> <span class="op">=</span> <span class="key">False</span><span class="strut"> </span></p> +<p id="t75" class="stm mis"> <span class="nam">error_message</span> <span class="op">+=</span> <span class="str">'--Choose a RAS profile.\n'</span><span class="strut"> </span></p> +<p id="t76" class="stm mis"> <span class="nam">steadiness_buttons</span> <span class="op">=</span> <span class="op">[</span><span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">radioButton_steady</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t77" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">radioButton_unsteady</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t78" class="stm mis"> <span class="key">if</span> <span class="nam">get_checked_radio_button</span><span class="op">(</span><span class="nam">steadiness_buttons</span><span class="op">)</span> <span class="key">is</span> <span class="key">None</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t79" class="stm mis"> <span class="nam">valid_inputs</span> <span class="op">=</span> <span class="key">False</span><span class="strut"> </span></p> +<p id="t80" class="stm mis"> <span class="nam">error_message</span> <span class="op">+=</span> <span class="str">'--Choose a steadiness type.\n'</span><span class="strut"> </span></p> +<p id="t81" class="stm mis"> <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_temperature</span><span class="op">.</span><span class="nam">text</span><span class="op">(</span><span class="op">)</span> <span class="op">==</span> <span class="str">''</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t82" class="stm mis"> <span class="nam">valid_inputs</span> <span class="op">=</span> <span class="key">False</span><span class="strut"> </span></p> +<p id="t83" class="stm mis"> <span class="nam">error_message</span> <span class="op">+=</span> <span class="str">'--Input a valid temperature.\n'</span><span class="strut"> </span></p> +<p id="t84" class="pln"><span class="strut"> </span></p> +<p id="t85" class="pln"> <span class="com"># Save inputs if valid input</span><span class="strut"> </span></p> +<p id="t86" class="stm mis"> <span class="key">if</span> <span class="nam">valid_inputs</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t87" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">save_hecras_settings</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t88" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">close</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t89" class="pln"> <span class="com"># Display error message if invalid inputs</span><span class="strut"> </span></p> +<p id="t90" class="pln"> <span class="key">else</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t91" class="stm mis"> <span class="nam">QMessageBox</span><span class="op">.</span><span class="nam">warning</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="str">'Error'</span><span class="op">,</span> <span class="nam">error_message</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t92" class="pln"><span class="strut"> </span></p> +<p id="t93" class="stm run hide_run"> <span class="key">def</span> <span class="nam">handle_cancel</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t94" class="pln"> <span class="str">"""Handle function for clicking Cancel"""</span><span class="strut"> </span></p> +<p id="t95" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">close</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t96" class="pln"><span class="strut"> </span></p> +<p id="t97" class="stm run hide_run"> <span class="key">def</span> <span class="nam">handle_browse</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t98" class="pln"> <span class="str">"""Handle function for clicking Browse"""</span><span class="strut"> </span></p> +<p id="t99" class="pln"> <span class="com"># File exploring dialog</span><span class="strut"> </span></p> +<p id="t100" class="stm mis"> <span class="nam">dlg</span> <span class="op">=</span> <span class="nam">QFileDialog</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t101" class="stm mis"> <span class="nam">file_path</span> <span class="op">=</span> <span class="nam">dlg</span><span class="op">.</span><span class="nam">getOpenFileName</span><span class="op">(</span><span class="strut"> </span></p> +<p id="t102" class="pln"> <span class="nam">self</span><span class="op">,</span> <span class="str">"QFileDialog.getOpenFileName()"</span><span class="op">,</span> <span class="str">""</span><span class="op">,</span> <span class="str">"HECRAS Project File (*.prj)"</span><span class="op">)</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t103" class="stm mis"> <span class="key">if</span> <span class="nam">file_path</span> <span class="op">==</span> <span class="str">''</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t104" class="stm mis"> <span class="key">return</span><span class="strut"> </span></p> +<p id="t105" class="pln"><span class="strut"> </span></p> +<p id="t106" class="pln"> <span class="com"># Update line edits</span><span class="strut"> </span></p> +<p id="t107" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_project</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">file_path</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t108" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">main_window</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_hecras</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">file_path</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t109" class="pln"><span class="strut"> </span></p> +<p id="t110" class="pln"> <span class="com"># Populate dialog with ras options</span><span class="strut"> </span></p> +<p id="t111" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">populate_plans</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t112" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">populate_profiles</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t113" class="pln"><span class="strut"> </span></p> +<p id="t114" class="stm run hide_run"> <span class="key">def</span> <span class="nam">handle_plan_change</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t115" class="pln"> <span class="str">"""Handle function for changing current plan"""</span><span class="strut"> </span></p> +<p id="t116" class="pln"> <span class="com"># Populate profile based on current plan in ras project</span><span class="strut"> </span></p> +<p id="t117" class="stm mis"> <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">comboBox_plan</span><span class="op">.</span><span class="nam">hasFocus</span><span class="op">(</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t118" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">populate_profiles</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t119" class="pln"><span class="strut"> </span></p> +<p id="t120" class="stm run hide_run"> <span class="key">def</span> <span class="nam">handle_steadiness_change</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t121" class="pln"> <span class="str">"""Handle function for changing steadiness option (steady vs. unsteady)"""</span><span class="strut"> </span></p> +<p id="t122" class="stm mis"> <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">radioButton_steady</span><span class="op">.</span><span class="nam">isChecked</span><span class="op">(</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t123" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">comboBox_profile</span><span class="op">.</span><span class="nam">setEnabled</span><span class="op">(</span><span class="key">True</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t124" class="stm mis"> <span class="key">elif</span> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">radioButton_unsteady</span><span class="op">.</span><span class="nam">isChecked</span><span class="op">(</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t125" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">comboBox_profile</span><span class="op">.</span><span class="nam">setEnabled</span><span class="op">(</span><span class="key">False</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t126" class="pln"><span class="strut"> </span></p> +<p id="t127" class="stm run hide_run"> <span class="key">def</span> <span class="nam">populate_plans</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t128" class="pln"> <span class="str">"""Populates the plans combo box"""</span><span class="strut"> </span></p> +<p id="t129" class="pln"> <span class="com"># Populate plans using current project</span><span class="strut"> </span></p> +<p id="t130" class="stm mis"> <span class="nam">file_path</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_project</span><span class="op">.</span><span class="nam">text</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t131" class="stm mis"> <span class="key">if</span> <span class="nam">file_path</span> <span class="op">!=</span> <span class="str">''</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t132" class="stm mis"> <span class="key">with</span> <span class="nam">RASProject</span><span class="op">(</span><span class="nam">file_path</span><span class="op">)</span> <span class="key">as</span> <span class="nam">rp</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t133" class="pln"> <span class="com"># Clear and populate plans</span><span class="strut"> </span></p> +<p id="t134" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">comboBox_plan</span><span class="op">.</span><span class="nam">clear</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t135" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">comboBox_plan</span><span class="op">.</span><span class="nam">addItems</span><span class="op">(</span><span class="nam">rp</span><span class="op">.</span><span class="nam">plan_names</span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t136" class="pln"> <span class="com"># Set current plan to 1st plan</span><span class="strut"> </span></p> +<p id="t137" class="stm mis"> <span class="nam">rp</span><span class="op">.</span><span class="nam">set_current_plan</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">comboBox_plan</span><span class="op">.</span><span class="nam">currentText</span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t138" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">comboBox_plan</span><span class="op">.</span><span class="nam">setCurrentIndex</span><span class="op">(</span><span class="num">0</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t139" class="pln"><span class="strut"> </span></p> +<p id="t140" class="stm run hide_run"> <span class="key">def</span> <span class="nam">populate_profiles</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t141" class="pln"> <span class="str">"""Populates the profiles combo box</span><span class="strut"> </span></p> +<p id="t142" class="pln"><span class="str"> enables the combo box when steady is checked</span><span class="strut"> </span></p> +<p id="t143" class="pln"><span class="str"> disables the combo box when unsteady is checked"""</span><span class="strut"> </span></p> +<p id="t144" class="pln"> <span class="com"># Populate profiles using current project</span><span class="strut"> </span></p> +<p id="t145" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">comboBox_profile</span><span class="op">.</span><span class="nam">setEnabled</span><span class="op">(</span><span class="key">True</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t146" class="stm mis"> <span class="nam">file_path</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_project</span><span class="op">.</span><span class="nam">text</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t147" class="stm mis"> <span class="key">if</span> <span class="nam">file_path</span> <span class="op">!=</span> <span class="str">''</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t148" class="stm mis"> <span class="key">with</span> <span class="nam">RASProject</span><span class="op">(</span><span class="nam">file_path</span><span class="op">)</span> <span class="key">as</span> <span class="nam">rp</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t149" class="stm mis"> <span class="nam">rp</span><span class="op">.</span><span class="nam">set_current_plan</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">comboBox_plan</span><span class="op">.</span><span class="nam">currentText</span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t150" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">comboBox_profile</span><span class="op">.</span><span class="nam">clear</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t151" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">comboBox_profile</span><span class="op">.</span><span class="nam">addItems</span><span class="op">(</span><span class="nam">rp</span><span class="op">.</span><span class="nam">profile_names</span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t152" class="pln"><span class="strut"> </span></p> +<p id="t153" class="pln"> <span class="com"># Disable profiles when unsteady button is checked</span><span class="strut"> </span></p> +<p id="t154" class="stm mis"> <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">radioButton_unsteady</span><span class="op">.</span><span class="nam">isChecked</span><span class="op">(</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t155" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">comboBox_profile</span><span class="op">.</span><span class="nam">setEnabled</span><span class="op">(</span><span class="key">False</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t156" class="pln"><span class="strut"> </span></p> +<p id="t157" class="stm run hide_run"> <span class="key">def</span> <span class="nam">save_hecras_settings</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t158" class="pln"> <span class="str">"""Saves settings from hecras dialog to main window"""</span><span class="strut"> </span></p> +<p id="t159" class="stm mis"> <span class="nam">mw</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">main_window</span><span class="strut"> </span></p> +<p id="t160" class="stm mis"> <span class="nam">mw</span><span class="op">.</span><span class="nam">hecras_project</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_project</span><span class="op">.</span><span class="nam">text</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t161" class="stm mis"> <span class="nam">mw</span><span class="op">.</span><span class="nam">hecras_plan</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">comboBox_plan</span><span class="op">.</span><span class="nam">currentText</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t162" class="stm mis"> <span class="nam">steadiness_buttons</span> <span class="op">=</span> <span class="op">[</span><span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">radioButton_steady</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t163" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">radioButton_unsteady</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t164" class="stm mis"> <span class="nam">mw</span><span class="op">.</span><span class="nam">hecras_steadiness</span> <span class="op">=</span> <span class="nam">get_checked_radio_button</span><span class="op">(</span><span class="strut"> </span></p> +<p id="t165" class="pln"> <span class="nam">steadiness_buttons</span><span class="op">)</span><span class="op">.</span><span class="nam">objectName</span><span class="op">(</span><span class="op">)</span><span class="op">[</span><span class="num">12</span><span class="op">:</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t166" class="stm mis"> <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">radioButton_steady</span><span class="op">.</span><span class="nam">isChecked</span><span class="op">(</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t167" class="stm mis"> <span class="nam">mw</span><span class="op">.</span><span class="nam">hecras_profile</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">comboBox_profile</span><span class="op">.</span><span class="nam">currentText</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t168" class="stm mis"> <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">radioButton_unsteady</span><span class="op">.</span><span class="nam">isChecked</span><span class="op">(</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t169" class="stm mis"> <span class="nam">mw</span><span class="op">.</span><span class="nam">hecras_profile</span> <span class="op">=</span> <span class="str">'Unsteady'</span><span class="strut"> </span></p> +<p id="t170" class="stm mis"> <span class="nam">mw</span><span class="op">.</span><span class="nam">hecras_temperature</span> <span class="op">=</span> <span class="nam">float</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_temperature</span><span class="op">.</span><span class="nam">text</span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t171" class="pln"> <span class="com"># Get datetime</span><span class="strut"> </span></p> +<p id="t172" class="stm mis"> <span class="nam">dt</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">dateTimeEdit_start_time</span><span class="op">.</span><span class="nam">dateTime</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t173" class="stm mis"> <span class="nam">mw</span><span class="op">.</span><span class="nam">hecras_start_time</span> <span class="op">=</span> <span class="nam">dt</span><span class="op">.</span><span class="nam">toPyDateTime</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t174" class="pln"><span class="strut"> </span></p> +<p id="t175" class="pln"><span class="strut"> </span></p> +<p id="t176" class="stm run hide_run"><span class="key">class</span> <span class="nam">AppWindow</span><span class="op">(</span><span class="nam">QMainWindow</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t177" class="pln"> <span class="str">"""Class that defines the main window of the ui.</span><span class="strut"> </span></p> +<p id="t178" class="pln"><span class="str"> It links the pre-generated ui created by the .ui to .py GUI files</span><span class="strut"> </span></p> +<p id="t179" class="pln"><span class="str"> with the functionality of the main_functions methods"""</span><span class="strut"> </span></p> +<p id="t180" class="pln"><span class="strut"> </span></p> +<p id="t181" class="stm run hide_run"> <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t182" class="pln"> <span class="com"># Initialization of ui window</span><span class="strut"> </span></p> +<p id="t183" class="stm mis"> <span class="nam">super</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">__init__</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t184" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span> <span class="op">=</span> <span class="nam">Ui_MainWindow</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t185" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">setupUi</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t186" class="pln"><span class="strut"> </span></p> +<p id="t187" class="pln"> <span class="com"># FluEgg version</span><span class="strut"> </span></p> +<p id="t188" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">version</span> <span class="op">=</span> <span class="str">'FluEgg 0.0 - Python3.7'</span><span class="strut"> </span></p> +<p id="t189" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">setWindowTitle</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">version</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t190" class="pln"><span class="strut"> </span></p> +<p id="t191" class="pln"> <span class="com"># FluEgg help message</span><span class="strut"> </span></p> +<p id="t192" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">help</span> <span class="op">=</span> <span class="str">''</span><span class="strut"> </span></p> +<p id="t193" class="pln"><span class="strut"> </span></p> +<p id="t194" class="pln"> <span class="com"># Input validators</span><span class="strut"> </span></p> +<p id="t195" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">intV</span> <span class="op">=</span> <span class="nam">QtGui</span><span class="op">.</span><span class="nam">QIntValidator</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t196" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">doubleV</span> <span class="op">=</span> <span class="nam">QtGui</span><span class="op">.</span><span class="nam">QDoubleValidator</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t197" class="pln"><span class="strut"> </span></p> +<p id="t198" class="pln"> <span class="com"># Set line edit validators</span><span class="strut"> </span></p> +<p id="t199" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_duration</span><span class="op">.</span><span class="nam">setValidator</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">intV</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t200" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_number_of_eggs</span><span class="op">.</span><span class="nam">setValidator</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">intV</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t201" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_time_step</span><span class="op">.</span><span class="nam">setValidator</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">intV</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t202" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_x</span><span class="op">.</span><span class="nam">setValidator</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">doubleV</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t203" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_y</span><span class="op">.</span><span class="nam">setValidator</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">doubleV</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t204" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_z</span><span class="op">.</span><span class="nam">setValidator</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">doubleV</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t205" class="pln"><span class="strut"> </span></p> +<p id="t206" class="pln"> <span class="com"># Scale ui window to half desktop size</span><span class="strut"> </span></p> +<p id="t207" class="stm mis"> <span class="nam">width</span> <span class="op">=</span> <span class="nam">QDesktopWidget</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">availableGeometry</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">size</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">width</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t208" class="stm mis"> <span class="nam">height</span> <span class="op">=</span> <span class="nam">QDesktopWidget</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">availableGeometry</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">size</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">height</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t209" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">resize</span><span class="op">(</span><span class="nam">int</span><span class="op">(</span><span class="nam">width</span><span class="op">*</span><span class="num">.2</span><span class="op">)</span><span class="op">,</span> <span class="nam">int</span><span class="op">(</span><span class="nam">height</span><span class="op">*</span><span class="num">0.4</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t210" class="pln"><span class="strut"> </span></p> +<p id="t211" class="pln"> <span class="com"># Define connections between ui events and handle functions</span><span class="strut"> </span></p> +<p id="t212" class="pln"> <span class="com"># Menu Buttons</span><span class="strut"> </span></p> +<p id="t213" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">actionVersion</span><span class="op">.</span><span class="nam">triggered</span><span class="op">.</span><span class="nam">connect</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">handle_version</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t214" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">actionHelp</span><span class="op">.</span><span class="nam">triggered</span><span class="op">.</span><span class="nam">connect</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">handle_help</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t215" class="pln"> <span class="com"># Hydraulic Channel</span><span class="strut"> </span></p> +<p id="t216" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">radioButton_csv</span><span class="op">.</span><span class="nam">clicked</span><span class="op">.</span><span class="nam">connect</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">handle_hydraulic_change</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t217" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">radioButton_hecras</span><span class="op">.</span><span class="nam">clicked</span><span class="op">.</span><span class="nam">connect</span><span class="op">(</span><span class="strut"> </span></p> +<p id="t218" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">handle_hydraulic_change</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t219" class="pln"><span class="strut"> </span></p> +<p id="t220" class="pln"> <span class="com"># disable ras options if not on Windows</span><span class="strut"> </span></p> +<p id="t221" class="stm mis"> <span class="key">if</span> <span class="key">not</span> <span class="nam">RASProject</span><span class="op">.</span><span class="nam">ras_controller_loaded</span><span class="op">(</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t222" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">radioButton_hecras</span><span class="op">.</span><span class="nam">setEnabled</span><span class="op">(</span><span class="key">False</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t223" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_hecras</span><span class="op">.</span><span class="nam">setEnabled</span><span class="op">(</span><span class="key">False</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t224" class="pln"><span class="strut"> </span></p> +<p id="t225" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">pushButton_browse</span><span class="op">.</span><span class="nam">clicked</span><span class="op">.</span><span class="nam">connect</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">handle_browse</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t226" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">pushButton_browse</span><span class="op">.</span><span class="nam">setEnabled</span><span class="op">(</span><span class="key">True</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t227" class="pln"> <span class="com"># Eggs</span><span class="strut"> </span></p> +<p id="t228" class="pln"> <span class="com"># Simulation</span><span class="strut"> </span></p> +<p id="t229" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">pushButton_run</span><span class="op">.</span><span class="nam">clicked</span><span class="op">.</span><span class="nam">connect</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">handle_run</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t230" class="pln"><span class="strut"> </span></p> +<p id="t231" class="pln"> <span class="com"># default selection</span><span class="strut"> </span></p> +<p id="t232" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">radioButton_csv</span><span class="op">.</span><span class="nam">setChecked</span><span class="op">(</span><span class="key">True</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t233" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">radioButton_parabolic_constant</span><span class="op">.</span><span class="nam">setChecked</span><span class="op">(</span><span class="key">True</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t234" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">radioButton_grass</span><span class="op">.</span><span class="nam">setChecked</span><span class="op">(</span><span class="key">True</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t235" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">radioButton_varying_dd</span><span class="op">.</span><span class="nam">setChecked</span><span class="op">(</span><span class="key">True</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t236" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">radioButton_forward</span><span class="op">.</span><span class="nam">setChecked</span><span class="op">(</span><span class="key">True</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t237" class="pln"><span class="strut"> </span></p> +<p id="t238" class="pln"> <span class="com"># Hecras saved information</span><span class="strut"> </span></p> +<p id="t239" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">hw</span> <span class="op">=</span> <span class="key">None</span><span class="strut"> </span></p> +<p id="t240" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">hecras_project</span> <span class="op">=</span> <span class="str">''</span><span class="strut"> </span></p> +<p id="t241" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">hecras_plan</span> <span class="op">=</span> <span class="str">''</span><span class="strut"> </span></p> +<p id="t242" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">hecras_profile</span> <span class="op">=</span> <span class="str">''</span><span class="strut"> </span></p> +<p id="t243" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">hecras_steadiness</span> <span class="op">=</span> <span class="str">''</span><span class="strut"> </span></p> +<p id="t244" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">hecras_temperature</span> <span class="op">=</span> <span class="str">''</span><span class="strut"> </span></p> +<p id="t245" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">hecras_start_time</span> <span class="op">=</span> <span class="num">0</span><span class="strut"> </span></p> +<p id="t246" class="pln"><span class="strut"> </span></p> +<p id="t247" class="pln"> <span class="com"># Display the ui</span><span class="strut"> </span></p> +<p id="t248" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">show</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t249" class="pln"><span class="strut"> </span></p> +<p id="t250" class="stm run hide_run"> <span class="key">def</span> <span class="nam">handle_version</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t251" class="pln"> <span class="str">"""Handle function for clicking About > Version"""</span><span class="strut"> </span></p> +<p id="t252" class="stm mis"> <span class="nam">QMessageBox</span><span class="op">.</span><span class="nam">about</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="str">'Version'</span><span class="op">,</span> <span class="nam">self</span><span class="op">.</span><span class="nam">version</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t253" class="pln"><span class="strut"> </span></p> +<p id="t254" class="stm run hide_run"> <span class="key">def</span> <span class="nam">handle_help</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t255" class="pln"> <span class="str">"""Handle function for clicking About > Help"""</span><span class="strut"> </span></p> +<p id="t256" class="stm mis"> <span class="nam">QMessageBox</span><span class="op">.</span><span class="nam">about</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="str">'Help'</span><span class="op">,</span> <span class="nam">self</span><span class="op">.</span><span class="nam">help</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t257" class="pln"><span class="strut"> </span></p> +<p id="t258" class="stm run hide_run"> <span class="key">def</span> <span class="nam">handle_hydraulic_change</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t259" class="pln"> <span class="str">"""Handle function for changing the Hydraulic Channel input"""</span><span class="strut"> </span></p> +<p id="t260" class="pln"> <span class="com"># self.ui.pushButton_browse.setEnabled(True)</span><span class="strut"> </span></p> +<p id="t261" class="stm mis"> <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">radioButton_csv</span><span class="op">.</span><span class="nam">isChecked</span><span class="op">(</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t262" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_csv</span><span class="op">.</span><span class="nam">setEnabled</span><span class="op">(</span><span class="key">True</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t263" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_hecras</span><span class="op">.</span><span class="nam">setEnabled</span><span class="op">(</span><span class="key">False</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t264" class="stm mis"> <span class="key">elif</span> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">radioButton_hecras</span><span class="op">.</span><span class="nam">isChecked</span><span class="op">(</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t265" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_csv</span><span class="op">.</span><span class="nam">setEnabled</span><span class="op">(</span><span class="key">False</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t266" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_hecras</span><span class="op">.</span><span class="nam">setEnabled</span><span class="op">(</span><span class="key">True</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t267" class="pln"><span class="strut"> </span></p> +<p id="t268" class="stm run hide_run"> <span class="key">def</span> <span class="nam">handle_browse</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t269" class="pln"> <span class="str">"""Handle function for clicking Browse"""</span><span class="strut"> </span></p> +<p id="t270" class="stm mis"> <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">radioButton_csv</span><span class="op">.</span><span class="nam">isChecked</span><span class="op">(</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t271" class="pln"> <span class="com"># File exploring dialog</span><span class="strut"> </span></p> +<p id="t272" class="stm mis"> <span class="nam">dlg</span> <span class="op">=</span> <span class="nam">QFileDialog</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t273" class="stm mis"> <span class="nam">file_path</span> <span class="op">=</span> <span class="nam">dlg</span><span class="op">.</span><span class="nam">getOpenFileName</span><span class="op">(</span><span class="strut"> </span></p> +<p id="t274" class="pln"> <span class="nam">self</span><span class="op">,</span> <span class="str">"QFileDialog.getOpenFileName()"</span><span class="op">,</span> <span class="str">""</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t275" class="pln"> <span class="str">"CSV File (*.csv)"</span><span class="op">)</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t276" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_csv</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">file_path</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t277" class="pln"><span class="strut"> </span></p> +<p id="t278" class="stm mis"> <span class="key">elif</span> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">radioButton_hecras</span><span class="op">.</span><span class="nam">isChecked</span><span class="op">(</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t279" class="pln"><span class="strut"> </span></p> +<p id="t280" class="pln"> <span class="com"># File exploring dialog</span><span class="strut"> </span></p> +<p id="t281" class="stm mis"> <span class="nam">dlg</span> <span class="op">=</span> <span class="nam">QFileDialog</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t282" class="stm mis"> <span class="nam">file_path</span> <span class="op">=</span> <span class="nam">dlg</span><span class="op">.</span><span class="nam">getOpenFileName</span><span class="op">(</span><span class="strut"> </span></p> +<p id="t283" class="pln"> <span class="nam">self</span><span class="op">,</span> <span class="str">"QFileDialog.getOpenFileName()"</span><span class="op">,</span> <span class="str">""</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t284" class="pln"> <span class="str">"HECRAS Project File (*.prj)"</span><span class="op">)</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t285" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_hecras</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">file_path</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t286" class="pln"><span class="strut"> </span></p> +<p id="t287" class="pln"> <span class="com"># Hecras dialog</span><span class="strut"> </span></p> +<p id="t288" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">hw</span> <span class="op">=</span> <span class="nam">HecrasDialog</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t289" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">hw</span><span class="op">.</span><span class="nam">show</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t290" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">hw</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_project</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">file_path</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t291" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">hw</span><span class="op">.</span><span class="nam">setup</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t292" class="pln"><span class="strut"> </span></p> +<p id="t293" class="stm run hide_run"> <span class="key">def</span> <span class="nam">handle_run</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t294" class="pln"> <span class="str">"""Handle function for clicking Run"""</span><span class="strut"> </span></p> +<p id="t295" class="pln"> <span class="com"># Radio button groups</span><span class="strut"> </span></p> +<p id="t296" class="stm mis"> <span class="nam">hydraulic_inputs</span> <span class="op">=</span> <span class="op">[</span><span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">radioButton_csv</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t297" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">radioButton_hecras</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t298" class="stm mis"> <span class="nam">diffusitvities</span> <span class="op">=</span> <span class="op">[</span><span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">radioButton_parabolic</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t299" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">radioButton_parabolic_constant</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t300" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">radioButton_constant</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t301" class="stm mis"> <span class="nam">species</span> <span class="op">=</span> <span class="op">[</span><span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">radioButton_grass</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t302" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">radioButton_silver</span><span class="op">,</span> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">radioButton_bighead</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t303" class="stm mis"> <span class="nam">varying_dd</span> <span class="op">=</span> <span class="op">[</span><span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">radioButton_constant_dd</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t304" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">radioButton_varying_dd</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t305" class="stm mis"> <span class="nam">direction</span> <span class="op">=</span> <span class="op">[</span><span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">radioButton_forward</span><span class="op">,</span> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">radioButton_reverse</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t306" class="pln"><span class="strut"> </span></p> +<p id="t307" class="pln"> <span class="com"># Initialize input and error flag</span><span class="strut"> </span></p> +<p id="t308" class="stm mis"> <span class="nam">d</span> <span class="op">=</span> <span class="op">{</span><span class="op">}</span><span class="strut"> </span></p> +<p id="t309" class="stm mis"> <span class="nam">valid_inputs</span> <span class="op">=</span> <span class="key">True</span><span class="strut"> </span></p> +<p id="t310" class="stm mis"> <span class="nam">error_message</span> <span class="op">=</span> <span class="str">''</span><span class="strut"> </span></p> +<p id="t311" class="pln"><span class="strut"> </span></p> +<p id="t312" class="pln"> <span class="com"># Fill dictionary and perform input error checking</span><span class="strut"> </span></p> +<p id="t313" class="stm mis"> <span class="key">if</span> <span class="nam">get_checked_radio_button</span><span class="op">(</span><span class="nam">hydraulic_inputs</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t314" class="stm mis"> <span class="nam">d</span><span class="op">[</span><span class="str">'hydraulic_mode'</span><span class="op">]</span> <span class="op">=</span> <span class="nam">get_checked_radio_button</span><span class="op">(</span><span class="strut"> </span></p> +<p id="t315" class="pln"> <span class="nam">hydraulic_inputs</span><span class="op">)</span><span class="op">.</span><span class="nam">objectName</span><span class="op">(</span><span class="op">)</span><span class="op">[</span><span class="num">12</span><span class="op">:</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t316" class="pln"><span class="strut"> </span></p> +<p id="t317" class="stm mis"> <span class="key">if</span> <span class="nam">d</span><span class="op">[</span><span class="str">'hydraulic_mode'</span><span class="op">]</span> <span class="op">==</span> <span class="str">'csv'</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t318" class="stm mis"> <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_csv</span><span class="op">.</span><span class="nam">text</span><span class="op">(</span><span class="op">)</span> <span class="op">!=</span> <span class="str">''</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t319" class="stm mis"> <span class="nam">d</span><span class="op">[</span><span class="str">'csv_path'</span><span class="op">]</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_csv</span><span class="op">.</span><span class="nam">text</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t320" class="stm mis"> <span class="nam">d</span><span class="op">[</span><span class="str">'hecras_path'</span><span class="op">]</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_hecras</span><span class="op">.</span><span class="nam">text</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t321" class="pln"> <span class="key">else</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t322" class="stm mis"> <span class="nam">error_message</span> <span class="op">+=</span> <span class="str">'--Load the hydraulic csv file.\n'</span><span class="strut"> </span></p> +<p id="t323" class="stm mis"> <span class="nam">valid_inputs</span> <span class="op">=</span> <span class="key">False</span><span class="strut"> </span></p> +<p id="t324" class="pln"><span class="strut"> </span></p> +<p id="t325" class="stm mis"> <span class="key">if</span> <span class="nam">d</span><span class="op">[</span><span class="str">'hydraulic_mode'</span><span class="op">]</span> <span class="op">==</span> <span class="str">'hecras'</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t326" class="stm mis"> <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_hecras</span><span class="op">.</span><span class="nam">text</span><span class="op">(</span><span class="op">)</span> <span class="op">!=</span> <span class="str">''</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t327" class="stm mis"> <span class="nam">d</span><span class="op">[</span><span class="str">'csv_path'</span><span class="op">]</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_csv</span><span class="op">.</span><span class="nam">text</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t328" class="stm mis"> <span class="nam">d</span><span class="op">[</span><span class="str">'hecras_path'</span><span class="op">]</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_hecras</span><span class="op">.</span><span class="nam">text</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t329" class="stm mis"> <span class="nam">d</span><span class="op">[</span><span class="str">'hecras_project'</span><span class="op">]</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">hecras_project</span><span class="strut"> </span></p> +<p id="t330" class="stm mis"> <span class="nam">d</span><span class="op">[</span><span class="str">'hecras_plan'</span><span class="op">]</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">hecras_plan</span><span class="strut"> </span></p> +<p id="t331" class="stm mis"> <span class="nam">d</span><span class="op">[</span><span class="str">'hecras_profile'</span><span class="op">]</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">hecras_profile</span><span class="strut"> </span></p> +<p id="t332" class="stm mis"> <span class="nam">d</span><span class="op">[</span><span class="str">'hecras_steadiness'</span><span class="op">]</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">hecras_steadiness</span><span class="strut"> </span></p> +<p id="t333" class="stm mis"> <span class="nam">d</span><span class="op">[</span><span class="str">'hecras_temperature'</span><span class="op">]</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">hecras_temperature</span><span class="strut"> </span></p> +<p id="t334" class="stm mis"> <span class="nam">d</span><span class="op">[</span><span class="str">'hecras_start_time'</span><span class="op">]</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">hecras_start_time</span><span class="strut"> </span></p> +<p id="t335" class="pln"> <span class="key">else</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t336" class="stm mis"> <span class="nam">error_message</span> <span class="op">+=</span> <span class="str">'--Load the hydraulic hecras project.\n'</span><span class="strut"> </span></p> +<p id="t337" class="stm mis"> <span class="nam">valid_inputs</span> <span class="op">=</span> <span class="key">False</span><span class="strut"> </span></p> +<p id="t338" class="pln"><span class="strut"> </span></p> +<p id="t339" class="pln"> <span class="key">else</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t340" class="stm mis"> <span class="nam">error_message</span> <span class="op">+=</span> <span class="str">'--Choose a hydraulic data type.\n'</span><span class="strut"> </span></p> +<p id="t341" class="stm mis"> <span class="nam">valid_inputs</span> <span class="op">=</span> <span class="key">False</span><span class="strut"> </span></p> +<p id="t342" class="pln"><span class="strut"> </span></p> +<p id="t343" class="stm mis"> <span class="key">if</span> <span class="nam">get_checked_radio_button</span><span class="op">(</span><span class="nam">diffusitvities</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t344" class="stm mis"> <span class="nam">d</span><span class="op">[</span><span class="str">'diffusivity'</span><span class="op">]</span> <span class="op">=</span> <span class="nam">get_checked_radio_button</span><span class="op">(</span><span class="strut"> </span></p> +<p id="t345" class="pln"> <span class="nam">diffusitvities</span><span class="op">)</span><span class="op">.</span><span class="nam">objectName</span><span class="op">(</span><span class="op">)</span><span class="op">[</span><span class="num">12</span><span class="op">:</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t346" class="stm mis"> <span class="key">if</span> <span class="nam">d</span><span class="op">[</span><span class="str">'diffusivity'</span><span class="op">]</span> <span class="op">==</span> <span class="str">'parabolic_constant'</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t347" class="stm mis"> <span class="nam">d</span><span class="op">[</span><span class="str">'diffusivity'</span><span class="op">]</span> <span class="op">=</span> <span class="str">'parabolic-constant'</span><span class="strut"> </span></p> +<p id="t348" class="pln"> <span class="key">else</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t349" class="stm mis"> <span class="nam">error_message</span> <span class="op">+=</span> <span class="str">'--Choose a diffusivity profile.\n'</span><span class="strut"> </span></p> +<p id="t350" class="stm mis"> <span class="nam">valid_inputs</span> <span class="op">=</span> <span class="key">False</span><span class="strut"> </span></p> +<p id="t351" class="pln"><span class="strut"> </span></p> +<p id="t352" class="stm mis"> <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_x</span><span class="op">.</span><span class="nam">text</span><span class="op">(</span><span class="op">)</span> <span class="op">!=</span> <span class="str">''</span> <span class="key">and</span> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_y</span><span class="op">.</span><span class="nam">text</span><span class="op">(</span><span class="op">)</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t353" class="pln"> <span class="op">!=</span> <span class="str">''</span> <span class="key">and</span> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_z</span><span class="op">.</span><span class="nam">text</span><span class="op">(</span><span class="op">)</span> <span class="op">!=</span> <span class="str">''</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t354" class="stm mis"> <span class="nam">d</span><span class="op">[</span><span class="str">'x'</span><span class="op">]</span> <span class="op">=</span> <span class="nam">float</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_x</span><span class="op">.</span><span class="nam">text</span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t355" class="stm mis"> <span class="nam">d</span><span class="op">[</span><span class="str">'y'</span><span class="op">]</span> <span class="op">=</span> <span class="nam">float</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_y</span><span class="op">.</span><span class="nam">text</span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t356" class="stm mis"> <span class="nam">d</span><span class="op">[</span><span class="str">'z'</span><span class="op">]</span> <span class="op">=</span> <span class="nam">float</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_z</span><span class="op">.</span><span class="nam">text</span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t357" class="pln"> <span class="key">else</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t358" class="stm mis"> <span class="nam">error_message</span> <span class="op">+=</span> <span class="str">'--Input X,Y,Z values.\n'</span><span class="strut"> </span></p> +<p id="t359" class="stm mis"> <span class="nam">valid_inputs</span> <span class="op">=</span> <span class="key">False</span><span class="strut"> </span></p> +<p id="t360" class="pln"><span class="strut"> </span></p> +<p id="t361" class="stm mis"> <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_number_of_eggs</span><span class="op">.</span><span class="nam">text</span><span class="op">(</span><span class="op">)</span> <span class="op">!=</span> <span class="str">''</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t362" class="stm mis"> <span class="nam">d</span><span class="op">[</span><span class="str">'num_eggs'</span><span class="op">]</span> <span class="op">=</span> <span class="nam">int</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_number_of_eggs</span><span class="op">.</span><span class="nam">text</span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t363" class="pln"> <span class="key">else</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t364" class="stm mis"> <span class="nam">error_message</span> <span class="op">+=</span> <span class="str">'--Input number of eggs.\n'</span><span class="strut"> </span></p> +<p id="t365" class="stm mis"> <span class="nam">valid_inputs</span> <span class="op">=</span> <span class="key">False</span><span class="strut"> </span></p> +<p id="t366" class="pln"><span class="strut"> </span></p> +<p id="t367" class="stm mis"> <span class="key">if</span> <span class="nam">get_checked_radio_button</span><span class="op">(</span><span class="nam">species</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t368" class="stm mis"> <span class="nam">d</span><span class="op">[</span><span class="str">'species'</span><span class="op">]</span> <span class="op">=</span> <span class="nam">get_checked_radio_button</span><span class="op">(</span><span class="nam">species</span><span class="op">)</span><span class="op">.</span><span class="nam">objectName</span><span class="op">(</span><span class="op">)</span><span class="op">[</span><span class="num">12</span><span class="op">:</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t369" class="pln"> <span class="key">else</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t370" class="stm mis"> <span class="nam">error_message</span> <span class="op">+=</span> <span class="str">'--Choose species.\n'</span><span class="strut"> </span></p> +<p id="t371" class="stm mis"> <span class="nam">valid_inputs</span> <span class="op">=</span> <span class="key">False</span><span class="strut"> </span></p> +<p id="t372" class="pln"><span class="strut"> </span></p> +<p id="t373" class="stm mis"> <span class="key">if</span> <span class="nam">get_checked_radio_button</span><span class="op">(</span><span class="nam">varying_dd</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t374" class="stm mis"> <span class="nam">d</span><span class="op">[</span><span class="str">'varying_dd'</span><span class="op">]</span> <span class="op">=</span> <span class="nam">get_checked_radio_button</span><span class="op">(</span><span class="strut"> </span></p> +<p id="t375" class="pln"> <span class="nam">varying_dd</span><span class="op">)</span><span class="op">.</span><span class="nam">objectName</span><span class="op">(</span><span class="op">)</span><span class="op">[</span><span class="num">12</span><span class="op">:</span><span class="op">-</span><span class="num">3</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t376" class="pln"> <span class="key">else</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t377" class="stm mis"> <span class="nam">error_message</span> <span class="op">+=</span> <span class="str">'--Choose varying or constant density/diameter.\n'</span><span class="strut"> </span></p> +<p id="t378" class="stm mis"> <span class="nam">valid_inputs</span> <span class="op">=</span> <span class="key">False</span><span class="strut"> </span></p> +<p id="t379" class="pln"><span class="strut"> </span></p> +<p id="t380" class="stm mis"> <span class="key">if</span> <span class="nam">get_checked_radio_button</span><span class="op">(</span><span class="nam">direction</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t381" class="stm mis"> <span class="nam">d</span><span class="op">[</span><span class="str">'direction'</span><span class="op">]</span> <span class="op">=</span> <span class="nam">get_checked_radio_button</span><span class="op">(</span><span class="strut"> </span></p> +<p id="t382" class="pln"> <span class="nam">direction</span><span class="op">)</span><span class="op">.</span><span class="nam">objectName</span><span class="op">(</span><span class="op">)</span><span class="op">[</span><span class="num">12</span><span class="op">:</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t383" class="pln"> <span class="key">else</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t384" class="stm mis"> <span class="nam">error_message</span> <span class="op">+=</span> <span class="str">'--Choose simulation direction.\n'</span><span class="strut"> </span></p> +<p id="t385" class="stm mis"> <span class="nam">valid_inputs</span> <span class="op">=</span> <span class="key">False</span><span class="strut"> </span></p> +<p id="t386" class="pln"><span class="strut"> </span></p> +<p id="t387" class="stm mis"> <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_duration</span><span class="op">.</span><span class="nam">text</span><span class="op">(</span><span class="op">)</span> <span class="op">!=</span> <span class="str">''</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t388" class="stm mis"> <span class="nam">d</span><span class="op">[</span><span class="str">'duration'</span><span class="op">]</span> <span class="op">=</span> <span class="nam">int</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_duration</span><span class="op">.</span><span class="nam">text</span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t389" class="pln"> <span class="key">else</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t390" class="stm mis"> <span class="nam">error_message</span> <span class="op">+=</span> <span class="str">'--Input simulation duration.\n'</span><span class="strut"> </span></p> +<p id="t391" class="stm mis"> <span class="nam">valid_inputs</span> <span class="op">=</span> <span class="key">False</span><span class="strut"> </span></p> +<p id="t392" class="pln"><span class="strut"> </span></p> +<p id="t393" class="stm mis"> <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_time_step</span><span class="op">.</span><span class="nam">text</span><span class="op">(</span><span class="op">)</span> <span class="op">!=</span> <span class="str">''</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t394" class="stm mis"> <span class="nam">d</span><span class="op">[</span><span class="str">'time_step'</span><span class="op">]</span> <span class="op">=</span> <span class="nam">int</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_time_step</span><span class="op">.</span><span class="nam">text</span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t395" class="pln"> <span class="key">else</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t396" class="stm mis"> <span class="nam">error_message</span> <span class="op">+=</span> <span class="str">'--Input simulation time step.\n'</span><span class="strut"> </span></p> +<p id="t397" class="stm mis"> <span class="nam">valid_inputs</span> <span class="op">=</span> <span class="key">False</span><span class="strut"> </span></p> +<p id="t398" class="pln"><span class="strut"> </span></p> +<p id="t399" class="stm mis"> <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_simulation_name</span><span class="op">.</span><span class="nam">text</span><span class="op">(</span><span class="op">)</span> <span class="op">!=</span> <span class="str">''</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t400" class="stm mis"> <span class="nam">d</span><span class="op">[</span><span class="str">'sim_name'</span><span class="op">]</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_simulation_name</span><span class="op">.</span><span class="nam">text</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t401" class="pln"> <span class="key">else</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t402" class="stm mis"> <span class="nam">error_message</span> <span class="op">+=</span> <span class="str">'--Input simulation name.\n'</span><span class="strut"> </span></p> +<p id="t403" class="stm mis"> <span class="nam">valid_inputs</span> <span class="op">=</span> <span class="key">False</span><span class="strut"> </span></p> +<p id="t404" class="pln"><span class="strut"> </span></p> +<p id="t405" class="pln"> <span class="com"># Run simulation OR show gui error message.</span><span class="strut"> </span></p> +<p id="t406" class="stm mis"> <span class="key">if</span> <span class="nam">valid_inputs</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t407" class="pln"> <span class="com"># Show error message from backend gui so gui doesn't crash</span><span class="strut"> </span></p> +<p id="t408" class="stm mis"> <span class="key">try</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t409" class="stm mis"> <span class="nam">sim</span> <span class="op">=</span> <span class="nam">from_input_dict</span><span class="op">(</span><span class="nam">d</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t410" class="stm mis"> <span class="nam">results</span> <span class="op">=</span> <span class="nam">sim</span><span class="op">.</span><span class="nam">run</span><span class="op">(</span><span class="nam">configuration</span><span class="op">=</span><span class="nam">d</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t411" class="stm mis"> <span class="nam">results</span><span class="op">.</span><span class="nam">save_results</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t412" class="pln"><span class="strut"> </span></p> +<p id="t413" class="stm mis"> <span class="key">except</span> <span class="nam">Exception</span> <span class="key">as</span> <span class="nam">e</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t414" class="stm mis"> <span class="nam">traceback</span><span class="op">.</span><span class="nam">print_exc</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t415" class="stm mis"> <span class="nam">QMessageBox</span><span class="op">.</span><span class="nam">warning</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="str">'Error'</span><span class="op">,</span> <span class="nam">str</span><span class="op">(</span><span class="nam">e</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t416" class="pln"> <span class="key">else</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t417" class="stm mis"> <span class="nam">QMessageBox</span><span class="op">.</span><span class="nam">warning</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="str">'Error'</span><span class="op">,</span> <span class="nam">error_message</span><span class="op">)</span><span class="strut"> </span></p> + + </td> + </tr> + </table> +</div> + +<div id="footer"> + <div class="content"> + <p> + <a class="nav" href="index.html">« index</a> <a class="nav" href="https://coverage.readthedocs.io">coverage.py v4.5.3</a>, + created at 2019-07-09 15:15 + </p> + </div> +</div> + +</body> +</html> diff --git a/coverage_report/fluegg_gui_hecras_dialog_py.html b/coverage_report/fluegg_gui_hecras_dialog_py.html new file mode 100644 index 0000000..b01c1e2 --- /dev/null +++ b/coverage_report/fluegg_gui_hecras_dialog_py.html @@ -0,0 +1,337 @@ + + + +<!DOCTYPE html> +<html> +<head> + <meta http-equiv="Content-Type" content="text/html; charset=utf-8"> + + + <meta http-equiv="X-UA-Compatible" content="IE=emulateIE7" /> + <title>Coverage for fluegg\gui\hecras_dialog.py: 4%</title> + <link rel="stylesheet" href="style.css" type="text/css"> + + <script type="text/javascript" src="jquery.min.js"></script> + <script type="text/javascript" src="jquery.hotkeys.js"></script> + <script type="text/javascript" src="jquery.isonscreen.js"></script> + <script type="text/javascript" src="coverage_html.js"></script> + <script type="text/javascript"> + jQuery(document).ready(coverage.pyfile_ready); + </script> +</head> +<body class="pyfile"> + +<div id="header"> + <div class="content"> + <h1>Coverage for <b>fluegg\gui\hecras_dialog.py</b> : + <span class="pc_cov">4%</span> + </h1> + + <img id="keyboard_icon" src="keybd_closed.png" alt="Show keyboard shortcuts" /> + + <h2 class="stats"> + 112 statements + <span class="run hide_run shortkey_r button_toggle_run">4 run</span> + <span class="mis shortkey_m button_toggle_mis">108 missing</span> + <span class="exc shortkey_x button_toggle_exc">0 excluded</span> + + + </h2> + </div> +</div> + +<div class="help_panel"> + <img id="panel_icon" src="keybd_open.png" alt="Hide keyboard shortcuts" /> + <p class="legend">Hot-keys on this page</p> + <div> + <p class="keyhelp"> + <span class="key">r</span> + <span class="key">m</span> + <span class="key">x</span> + <span class="key">p</span> toggle line displays + </p> + <p class="keyhelp"> + <span class="key">j</span> + <span class="key">k</span> next/prev highlighted chunk + </p> + <p class="keyhelp"> + <span class="key">0</span> (zero) top of page + </p> + <p class="keyhelp"> + <span class="key">1</span> (one) first highlighted chunk + </p> + </div> +</div> + +<div id="source"> + <table> + <tr> + <td class="linenos"> +<p id="n1" class="pln"><a href="#n1">1</a></p> +<p id="n2" class="pln"><a href="#n2">2</a></p> +<p id="n3" class="pln"><a href="#n3">3</a></p> +<p id="n4" class="pln"><a href="#n4">4</a></p> +<p id="n5" class="pln"><a href="#n5">5</a></p> +<p id="n6" class="pln"><a href="#n6">6</a></p> +<p id="n7" class="pln"><a href="#n7">7</a></p> +<p id="n8" class="pln"><a href="#n8">8</a></p> +<p id="n9" class="stm run hide_run"><a href="#n9">9</a></p> +<p id="n10" class="pln"><a href="#n10">10</a></p> +<p id="n11" class="stm run hide_run"><a href="#n11">11</a></p> +<p id="n12" class="stm run hide_run"><a href="#n12">12</a></p> +<p id="n13" class="stm mis"><a href="#n13">13</a></p> +<p id="n14" class="stm mis"><a href="#n14">14</a></p> +<p id="n15" class="stm mis"><a href="#n15">15</a></p> +<p id="n16" class="stm mis"><a href="#n16">16</a></p> +<p id="n17" class="stm mis"><a href="#n17">17</a></p> +<p id="n18" class="stm mis"><a href="#n18">18</a></p> +<p id="n19" class="stm mis"><a href="#n19">19</a></p> +<p id="n20" class="stm mis"><a href="#n20">20</a></p> +<p id="n21" class="stm mis"><a href="#n21">21</a></p> +<p id="n22" class="stm mis"><a href="#n22">22</a></p> +<p id="n23" class="stm mis"><a href="#n23">23</a></p> +<p id="n24" class="stm mis"><a href="#n24">24</a></p> +<p id="n25" class="stm mis"><a href="#n25">25</a></p> +<p id="n26" class="stm mis"><a href="#n26">26</a></p> +<p id="n27" class="stm mis"><a href="#n27">27</a></p> +<p id="n28" class="stm mis"><a href="#n28">28</a></p> +<p id="n29" class="stm mis"><a href="#n29">29</a></p> +<p id="n30" class="stm mis"><a href="#n30">30</a></p> +<p id="n31" class="stm mis"><a href="#n31">31</a></p> +<p id="n32" class="stm mis"><a href="#n32">32</a></p> +<p id="n33" class="stm mis"><a href="#n33">33</a></p> +<p id="n34" class="stm mis"><a href="#n34">34</a></p> +<p id="n35" class="stm mis"><a href="#n35">35</a></p> +<p id="n36" class="stm mis"><a href="#n36">36</a></p> +<p id="n37" class="stm mis"><a href="#n37">37</a></p> +<p id="n38" class="stm mis"><a href="#n38">38</a></p> +<p id="n39" class="stm mis"><a href="#n39">39</a></p> +<p id="n40" class="stm mis"><a href="#n40">40</a></p> +<p id="n41" class="stm mis"><a href="#n41">41</a></p> +<p id="n42" class="stm mis"><a href="#n42">42</a></p> +<p id="n43" class="stm mis"><a href="#n43">43</a></p> +<p id="n44" class="stm mis"><a href="#n44">44</a></p> +<p id="n45" class="stm mis"><a href="#n45">45</a></p> +<p id="n46" class="stm mis"><a href="#n46">46</a></p> +<p id="n47" class="stm mis"><a href="#n47">47</a></p> +<p id="n48" class="stm mis"><a href="#n48">48</a></p> +<p id="n49" class="stm mis"><a href="#n49">49</a></p> +<p id="n50" class="stm mis"><a href="#n50">50</a></p> +<p id="n51" class="stm mis"><a href="#n51">51</a></p> +<p id="n52" class="stm mis"><a href="#n52">52</a></p> +<p id="n53" class="stm mis"><a href="#n53">53</a></p> +<p id="n54" class="stm mis"><a href="#n54">54</a></p> +<p id="n55" class="stm mis"><a href="#n55">55</a></p> +<p id="n56" class="stm mis"><a href="#n56">56</a></p> +<p id="n57" class="stm mis"><a href="#n57">57</a></p> +<p id="n58" class="stm mis"><a href="#n58">58</a></p> +<p id="n59" class="stm mis"><a href="#n59">59</a></p> +<p id="n60" class="stm mis"><a href="#n60">60</a></p> +<p id="n61" class="stm mis"><a href="#n61">61</a></p> +<p id="n62" class="stm mis"><a href="#n62">62</a></p> +<p id="n63" class="stm mis"><a href="#n63">63</a></p> +<p id="n64" class="stm mis"><a href="#n64">64</a></p> +<p id="n65" class="stm mis"><a href="#n65">65</a></p> +<p id="n66" class="stm mis"><a href="#n66">66</a></p> +<p id="n67" class="stm mis"><a href="#n67">67</a></p> +<p id="n68" class="stm mis"><a href="#n68">68</a></p> +<p id="n69" class="stm mis"><a href="#n69">69</a></p> +<p id="n70" class="stm mis"><a href="#n70">70</a></p> +<p id="n71" class="stm mis"><a href="#n71">71</a></p> +<p id="n72" class="stm mis"><a href="#n72">72</a></p> +<p id="n73" class="stm mis"><a href="#n73">73</a></p> +<p id="n74" class="stm mis"><a href="#n74">74</a></p> +<p id="n75" class="stm mis"><a href="#n75">75</a></p> +<p id="n76" class="stm mis"><a href="#n76">76</a></p> +<p id="n77" class="stm mis"><a href="#n77">77</a></p> +<p id="n78" class="stm mis"><a href="#n78">78</a></p> +<p id="n79" class="stm mis"><a href="#n79">79</a></p> +<p id="n80" class="stm mis"><a href="#n80">80</a></p> +<p id="n81" class="stm mis"><a href="#n81">81</a></p> +<p id="n82" class="stm mis"><a href="#n82">82</a></p> +<p id="n83" class="stm mis"><a href="#n83">83</a></p> +<p id="n84" class="stm mis"><a href="#n84">84</a></p> +<p id="n85" class="stm mis"><a href="#n85">85</a></p> +<p id="n86" class="stm mis"><a href="#n86">86</a></p> +<p id="n87" class="stm mis"><a href="#n87">87</a></p> +<p id="n88" class="stm mis"><a href="#n88">88</a></p> +<p id="n89" class="stm mis"><a href="#n89">89</a></p> +<p id="n90" class="stm mis"><a href="#n90">90</a></p> +<p id="n91" class="stm mis"><a href="#n91">91</a></p> +<p id="n92" class="stm mis"><a href="#n92">92</a></p> +<p id="n93" class="stm mis"><a href="#n93">93</a></p> +<p id="n94" class="stm mis"><a href="#n94">94</a></p> +<p id="n95" class="stm mis"><a href="#n95">95</a></p> +<p id="n96" class="stm mis"><a href="#n96">96</a></p> +<p id="n97" class="stm mis"><a href="#n97">97</a></p> +<p id="n98" class="stm mis"><a href="#n98">98</a></p> +<p id="n99" class="stm mis"><a href="#n99">99</a></p> +<p id="n100" class="stm mis"><a href="#n100">100</a></p> +<p id="n101" class="stm mis"><a href="#n101">101</a></p> +<p id="n102" class="stm mis"><a href="#n102">102</a></p> +<p id="n103" class="stm mis"><a href="#n103">103</a></p> +<p id="n104" class="stm mis"><a href="#n104">104</a></p> +<p id="n105" class="stm mis"><a href="#n105">105</a></p> +<p id="n106" class="stm mis"><a href="#n106">106</a></p> +<p id="n107" class="pln"><a href="#n107">107</a></p> +<p id="n108" class="stm mis"><a href="#n108">108</a></p> +<p id="n109" class="stm mis"><a href="#n109">109</a></p> +<p id="n110" class="pln"><a href="#n110">110</a></p> +<p id="n111" class="stm run hide_run"><a href="#n111">111</a></p> +<p id="n112" class="stm mis"><a href="#n112">112</a></p> +<p id="n113" class="stm mis"><a href="#n113">113</a></p> +<p id="n114" class="stm mis"><a href="#n114">114</a></p> +<p id="n115" class="stm mis"><a href="#n115">115</a></p> +<p id="n116" class="stm mis"><a href="#n116">116</a></p> +<p id="n117" class="stm mis"><a href="#n117">117</a></p> +<p id="n118" class="stm mis"><a href="#n118">118</a></p> +<p id="n119" class="stm mis"><a href="#n119">119</a></p> +<p id="n120" class="stm mis"><a href="#n120">120</a></p> +<p id="n121" class="stm mis"><a href="#n121">121</a></p> +<p id="n122" class="stm mis"><a href="#n122">122</a></p> +<p id="n123" class="stm mis"><a href="#n123">123</a></p> +<p id="n124" class="pln"><a href="#n124">124</a></p> + + </td> + <td class="text"> +<p id="t1" class="pln"><span class="com"># -*- coding: utf-8 -*-</span><span class="strut"> </span></p> +<p id="t2" class="pln"><span class="strut"> </span></p> +<p id="t3" class="pln"><span class="com"># Form implementation generated from reading ui file 'hecras_dialog.ui'</span><span class="strut"> </span></p> +<p id="t4" class="pln"><span class="com">#</span><span class="strut"> </span></p> +<p id="t5" class="pln"><span class="com"># Created by: PyQt5 UI code generator 5.11.3</span><span class="strut"> </span></p> +<p id="t6" class="pln"><span class="com">#</span><span class="strut"> </span></p> +<p id="t7" class="pln"><span class="com"># WARNING! All changes made in this file will be lost!</span><span class="strut"> </span></p> +<p id="t8" class="pln"><span class="strut"> </span></p> +<p id="t9" class="stm run hide_run"><span class="key">from</span> <span class="nam">PyQt5</span> <span class="key">import</span> <span class="nam">QtCore</span><span class="op">,</span> <span class="nam">QtGui</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="strut"> </span></p> +<p id="t10" class="pln"><span class="strut"> </span></p> +<p id="t11" class="stm run hide_run"><span class="key">class</span> <span class="nam">Ui_HecrasDialog</span><span class="op">(</span><span class="nam">object</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t12" class="stm run hide_run"> <span class="key">def</span> <span class="nam">setupUi</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">HecrasDialog</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t13" class="stm mis"> <span class="nam">HecrasDialog</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"HecrasDialog"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t14" class="stm mis"> <span class="nam">HecrasDialog</span><span class="op">.</span><span class="nam">resize</span><span class="op">(</span><span class="num">258</span><span class="op">,</span> <span class="num">295</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t15" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_2</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QVBoxLayout</span><span class="op">(</span><span class="nam">HecrasDialog</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t16" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_2</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"verticalLayout_2"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t17" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QVBoxLayout</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t18" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"verticalLayout"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t19" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QHBoxLayout</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t20" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"horizontalLayout"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t21" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_project</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QLabel</span><span class="op">(</span><span class="nam">HecrasDialog</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t22" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_project</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"label_project"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t23" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">label_project</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t24" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_project</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QLineEdit</span><span class="op">(</span><span class="nam">HecrasDialog</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t25" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_project</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"lineEdit_project"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t26" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_project</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t27" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">pushButton_browse</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QPushButton</span><span class="op">(</span><span class="nam">HecrasDialog</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t28" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">pushButton_browse</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"pushButton_browse"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t29" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">pushButton_browse</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t30" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout</span><span class="op">.</span><span class="nam">addLayout</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t31" class="stm mis"> <span class="nam">spacerItem</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSpacerItem</span><span class="op">(</span><span class="num">20</span><span class="op">,</span> <span class="num">40</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSizePolicy</span><span class="op">.</span><span class="nam">Minimum</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSizePolicy</span><span class="op">.</span><span class="nam">Expanding</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t32" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout</span><span class="op">.</span><span class="nam">addItem</span><span class="op">(</span><span class="nam">spacerItem</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t33" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_4</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QHBoxLayout</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t34" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_4</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"horizontalLayout_4"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t35" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_steady</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QRadioButton</span><span class="op">(</span><span class="nam">HecrasDialog</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t36" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_steady</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"radioButton_steady"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t37" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_4</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_steady</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t38" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_unsteady</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QRadioButton</span><span class="op">(</span><span class="nam">HecrasDialog</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t39" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_unsteady</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"radioButton_unsteady"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t40" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_4</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_unsteady</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t41" class="stm mis"> <span class="nam">spacerItem1</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSpacerItem</span><span class="op">(</span><span class="num">40</span><span class="op">,</span> <span class="num">20</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSizePolicy</span><span class="op">.</span><span class="nam">Expanding</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSizePolicy</span><span class="op">.</span><span class="nam">Minimum</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t42" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_4</span><span class="op">.</span><span class="nam">addItem</span><span class="op">(</span><span class="nam">spacerItem1</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t43" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout</span><span class="op">.</span><span class="nam">addLayout</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_4</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t44" class="stm mis"> <span class="nam">spacerItem2</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSpacerItem</span><span class="op">(</span><span class="num">20</span><span class="op">,</span> <span class="num">40</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSizePolicy</span><span class="op">.</span><span class="nam">Minimum</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSizePolicy</span><span class="op">.</span><span class="nam">Expanding</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t45" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout</span><span class="op">.</span><span class="nam">addItem</span><span class="op">(</span><span class="nam">spacerItem2</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t46" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_2</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QHBoxLayout</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t47" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_2</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"horizontalLayout_2"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t48" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_plan</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QLabel</span><span class="op">(</span><span class="nam">HecrasDialog</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t49" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_plan</span><span class="op">.</span><span class="nam">setMaximumSize</span><span class="op">(</span><span class="nam">QtCore</span><span class="op">.</span><span class="nam">QSize</span><span class="op">(</span><span class="num">60</span><span class="op">,</span> <span class="num">60</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t50" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_plan</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"label_plan"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t51" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_2</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">label_plan</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t52" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">comboBox_plan</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QComboBox</span><span class="op">(</span><span class="nam">HecrasDialog</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t53" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">comboBox_plan</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"comboBox_plan"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t54" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_2</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">comboBox_plan</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t55" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout</span><span class="op">.</span><span class="nam">addLayout</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_2</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t56" class="stm mis"> <span class="nam">spacerItem3</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSpacerItem</span><span class="op">(</span><span class="num">20</span><span class="op">,</span> <span class="num">40</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSizePolicy</span><span class="op">.</span><span class="nam">Minimum</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSizePolicy</span><span class="op">.</span><span class="nam">Expanding</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t57" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout</span><span class="op">.</span><span class="nam">addItem</span><span class="op">(</span><span class="nam">spacerItem3</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t58" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_3</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QHBoxLayout</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t59" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_3</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"horizontalLayout_3"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t60" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_profile</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QLabel</span><span class="op">(</span><span class="nam">HecrasDialog</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t61" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_profile</span><span class="op">.</span><span class="nam">setMaximumSize</span><span class="op">(</span><span class="nam">QtCore</span><span class="op">.</span><span class="nam">QSize</span><span class="op">(</span><span class="num">60</span><span class="op">,</span> <span class="num">60</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t62" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_profile</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"label_profile"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t63" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_3</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">label_profile</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t64" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">comboBox_profile</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QComboBox</span><span class="op">(</span><span class="nam">HecrasDialog</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t65" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">comboBox_profile</span><span class="op">.</span><span class="nam">setMaximumSize</span><span class="op">(</span><span class="nam">QtCore</span><span class="op">.</span><span class="nam">QSize</span><span class="op">(</span><span class="num">16777215</span><span class="op">,</span> <span class="num">16777215</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t66" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">comboBox_profile</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"comboBox_profile"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t67" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_3</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">comboBox_profile</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t68" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout</span><span class="op">.</span><span class="nam">addLayout</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_3</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t69" class="stm mis"> <span class="nam">spacerItem4</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSpacerItem</span><span class="op">(</span><span class="num">20</span><span class="op">,</span> <span class="num">40</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSizePolicy</span><span class="op">.</span><span class="nam">Minimum</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSizePolicy</span><span class="op">.</span><span class="nam">Expanding</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t70" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout</span><span class="op">.</span><span class="nam">addItem</span><span class="op">(</span><span class="nam">spacerItem4</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t71" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_5</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QHBoxLayout</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t72" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_5</span><span class="op">.</span><span class="nam">setSizeConstraint</span><span class="op">(</span><span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QLayout</span><span class="op">.</span><span class="nam">SetDefaultConstraint</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t73" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_5</span><span class="op">.</span><span class="nam">setContentsMargins</span><span class="op">(</span><span class="op">-</span><span class="num">1</span><span class="op">,</span> <span class="op">-</span><span class="num">1</span><span class="op">,</span> <span class="op">-</span><span class="num">1</span><span class="op">,</span> <span class="num">0</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t74" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_5</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"horizontalLayout_5"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t75" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_temperature</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QLabel</span><span class="op">(</span><span class="nam">HecrasDialog</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t76" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_temperature</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"label_temperature"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t77" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_5</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">label_temperature</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t78" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_temperature</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QLineEdit</span><span class="op">(</span><span class="nam">HecrasDialog</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t79" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_temperature</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"lineEdit_temperature"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t80" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_5</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_temperature</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t81" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout</span><span class="op">.</span><span class="nam">addLayout</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_5</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t82" class="stm mis"> <span class="nam">spacerItem5</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSpacerItem</span><span class="op">(</span><span class="num">20</span><span class="op">,</span> <span class="num">40</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSizePolicy</span><span class="op">.</span><span class="nam">Minimum</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSizePolicy</span><span class="op">.</span><span class="nam">Expanding</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t83" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout</span><span class="op">.</span><span class="nam">addItem</span><span class="op">(</span><span class="nam">spacerItem5</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t84" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_8</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QHBoxLayout</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t85" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_8</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"horizontalLayout_8"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t86" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_start_time</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QLabel</span><span class="op">(</span><span class="nam">HecrasDialog</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t87" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_start_time</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"label_start_time"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t88" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_8</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">label_start_time</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t89" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">dateTimeEdit_start_time</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QDateTimeEdit</span><span class="op">(</span><span class="nam">HecrasDialog</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t90" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">dateTimeEdit_start_time</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"dateTimeEdit_start_time"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t91" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_8</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">dateTimeEdit_start_time</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t92" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout</span><span class="op">.</span><span class="nam">addLayout</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_8</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t93" class="stm mis"> <span class="nam">spacerItem6</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSpacerItem</span><span class="op">(</span><span class="num">20</span><span class="op">,</span> <span class="num">40</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSizePolicy</span><span class="op">.</span><span class="nam">Minimum</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSizePolicy</span><span class="op">.</span><span class="nam">Expanding</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t94" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout</span><span class="op">.</span><span class="nam">addItem</span><span class="op">(</span><span class="nam">spacerItem6</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t95" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_6</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QHBoxLayout</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t96" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_6</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"horizontalLayout_6"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t97" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">pushButton_cancel</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QPushButton</span><span class="op">(</span><span class="nam">HecrasDialog</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t98" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">pushButton_cancel</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"pushButton_cancel"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t99" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_6</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">pushButton_cancel</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t100" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">pushButton_ok</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QPushButton</span><span class="op">(</span><span class="nam">HecrasDialog</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t101" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">pushButton_ok</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"pushButton_ok"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t102" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_6</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">pushButton_ok</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t103" class="stm mis"> <span class="nam">spacerItem7</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSpacerItem</span><span class="op">(</span><span class="num">40</span><span class="op">,</span> <span class="num">20</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSizePolicy</span><span class="op">.</span><span class="nam">Expanding</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSizePolicy</span><span class="op">.</span><span class="nam">Minimum</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t104" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_6</span><span class="op">.</span><span class="nam">addItem</span><span class="op">(</span><span class="nam">spacerItem7</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t105" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout</span><span class="op">.</span><span class="nam">addLayout</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_6</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t106" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_2</span><span class="op">.</span><span class="nam">addLayout</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t107" class="pln"><span class="strut"> </span></p> +<p id="t108" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">retranslateUi</span><span class="op">(</span><span class="nam">HecrasDialog</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t109" class="stm mis"> <span class="nam">QtCore</span><span class="op">.</span><span class="nam">QMetaObject</span><span class="op">.</span><span class="nam">connectSlotsByName</span><span class="op">(</span><span class="nam">HecrasDialog</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t110" class="pln"><span class="strut"> </span></p> +<p id="t111" class="stm run hide_run"> <span class="key">def</span> <span class="nam">retranslateUi</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">HecrasDialog</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t112" class="stm mis"> <span class="nam">_translate</span> <span class="op">=</span> <span class="nam">QtCore</span><span class="op">.</span><span class="nam">QCoreApplication</span><span class="op">.</span><span class="nam">translate</span><span class="strut"> </span></p> +<p id="t113" class="stm mis"> <span class="nam">HecrasDialog</span><span class="op">.</span><span class="nam">setWindowTitle</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"HecrasDialog"</span><span class="op">,</span> <span class="str">"Dialog"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t114" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_project</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"HecrasDialog"</span><span class="op">,</span> <span class="str">"Project"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t115" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">pushButton_browse</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"HecrasDialog"</span><span class="op">,</span> <span class="str">"Browse"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t116" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_steady</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"HecrasDialog"</span><span class="op">,</span> <span class="str">"Steady"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t117" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_unsteady</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"HecrasDialog"</span><span class="op">,</span> <span class="str">"Unsteady"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t118" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_plan</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"HecrasDialog"</span><span class="op">,</span> <span class="str">"Plan"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t119" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_profile</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"HecrasDialog"</span><span class="op">,</span> <span class="str">"Profile"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t120" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_temperature</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"HecrasDialog"</span><span class="op">,</span> <span class="str">"Temperature (C)"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t121" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_start_time</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"HecrasDialog"</span><span class="op">,</span> <span class="str">"Start Time"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t122" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">pushButton_cancel</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"HecrasDialog"</span><span class="op">,</span> <span class="str">"Cancel"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t123" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">pushButton_ok</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"HecrasDialog"</span><span class="op">,</span> <span class="str">"Ok"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t124" class="pln"><span class="strut"> </span></p> + + </td> + </tr> + </table> +</div> + +<div id="footer"> + <div class="content"> + <p> + <a class="nav" href="index.html">« index</a> <a class="nav" href="https://coverage.readthedocs.io">coverage.py v4.5.3</a>, + created at 2019-07-09 15:15 + </p> + </div> +</div> + +</body> +</html> diff --git a/coverage_report/fluegg_hydraulics_py.html b/coverage_report/fluegg_hydraulics_py.html new file mode 100644 index 0000000..39d8387 --- /dev/null +++ b/coverage_report/fluegg_hydraulics_py.html @@ -0,0 +1,1883 @@ + + + +<!DOCTYPE html> +<html> +<head> + <meta http-equiv="Content-Type" content="text/html; charset=utf-8"> + + + <meta http-equiv="X-UA-Compatible" content="IE=emulateIE7" /> + <title>Coverage for fluegg\hydraulics.py: 87%</title> + <link rel="stylesheet" href="style.css" type="text/css"> + + <script type="text/javascript" src="jquery.min.js"></script> + <script type="text/javascript" src="jquery.hotkeys.js"></script> + <script type="text/javascript" src="jquery.isonscreen.js"></script> + <script type="text/javascript" src="coverage_html.js"></script> + <script type="text/javascript"> + jQuery(document).ready(coverage.pyfile_ready); + </script> +</head> +<body class="pyfile"> + +<div id="header"> + <div class="content"> + <h1>Coverage for <b>fluegg\hydraulics.py</b> : + <span class="pc_cov">87%</span> + </h1> + + <img id="keyboard_icon" src="keybd_closed.png" alt="Show keyboard shortcuts" /> + + <h2 class="stats"> + 287 statements + <span class="run hide_run shortkey_r button_toggle_run">250 run</span> + <span class="mis shortkey_m button_toggle_mis">37 missing</span> + <span class="exc shortkey_x button_toggle_exc">0 excluded</span> + + + </h2> + </div> +</div> + +<div class="help_panel"> + <img id="panel_icon" src="keybd_open.png" alt="Hide keyboard shortcuts" /> + <p class="legend">Hot-keys on this page</p> + <div> + <p class="keyhelp"> + <span class="key">r</span> + <span class="key">m</span> + <span class="key">x</span> + <span class="key">p</span> toggle line displays + </p> + <p class="keyhelp"> + <span class="key">j</span> + <span class="key">k</span> next/prev highlighted chunk + </p> + <p class="keyhelp"> + <span class="key">0</span> (zero) top of page + </p> + <p class="keyhelp"> + <span class="key">1</span> (one) first highlighted chunk + </p> + </div> +</div> + +<div id="source"> + <table> + <tr> + <td class="linenos"> +<p id="n1" class="stm run hide_run"><a href="#n1">1</a></p> +<p id="n2" class="stm run hide_run"><a href="#n2">2</a></p> +<p id="n3" class="pln"><a href="#n3">3</a></p> +<p id="n4" class="stm run hide_run"><a href="#n4">4</a></p> +<p id="n5" class="stm run hide_run"><a href="#n5">5</a></p> +<p id="n6" class="stm run hide_run"><a href="#n6">6</a></p> +<p id="n7" 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href="#n287">287</a></p> +<p id="n288" class="stm run hide_run"><a href="#n288">288</a></p> +<p id="n289" class="stm run hide_run"><a href="#n289">289</a></p> +<p id="n290" class="stm run hide_run"><a href="#n290">290</a></p> +<p id="n291" class="stm run hide_run"><a href="#n291">291</a></p> +<p id="n292" class="stm run hide_run"><a href="#n292">292</a></p> +<p id="n293" class="pln"><a href="#n293">293</a></p> +<p id="n294" class="stm run hide_run"><a href="#n294">294</a></p> +<p id="n295" class="stm run hide_run"><a href="#n295">295</a></p> +<p id="n296" class="pln"><a href="#n296">296</a></p> +<p id="n297" class="stm run hide_run"><a href="#n297">297</a></p> +<p id="n298" class="pln"><a href="#n298">298</a></p> +<p id="n299" class="stm run hide_run"><a href="#n299">299</a></p> +<p id="n300" class="stm run hide_run"><a href="#n300">300</a></p> +<p id="n301" class="pln"><a href="#n301">301</a></p> +<p id="n302" class="stm run hide_run"><a href="#n302">302</a></p> +<p id="n303" class="pln"><a href="#n303">303</a></p> +<p id="n304" class="stm run hide_run"><a href="#n304">304</a></p> +<p id="n305" class="pln"><a href="#n305">305</a></p> +<p id="n306" class="stm run hide_run"><a href="#n306">306</a></p> +<p id="n307" class="pln"><a href="#n307">307</a></p> +<p id="n308" class="stm run hide_run"><a href="#n308">308</a></p> +<p id="n309" class="stm run hide_run"><a href="#n309">309</a></p> +<p id="n310" class="pln"><a href="#n310">310</a></p> +<p id="n311" class="pln"><a href="#n311">311</a></p> +<p id="n312" class="pln"><a href="#n312">312</a></p> +<p id="n313" class="stm run hide_run"><a href="#n313">313</a></p> +<p id="n314" class="pln"><a href="#n314">314</a></p> +<p id="n315" class="stm run hide_run"><a href="#n315">315</a></p> +<p id="n316" class="pln"><a href="#n316">316</a></p> +<p id="n317" class="pln"><a href="#n317">317</a></p> +<p id="n318" class="stm run hide_run"><a href="#n318">318</a></p> +<p id="n319" class="pln"><a href="#n319">319</a></p> +<p id="n320" class="pln"><a href="#n320">320</a></p> +<p id="n321" class="pln"><a href="#n321">321</a></p> +<p id="n322" class="pln"><a href="#n322">322</a></p> +<p id="n323" class="pln"><a href="#n323">323</a></p> +<p id="n324" class="pln"><a href="#n324">324</a></p> +<p id="n325" class="pln"><a href="#n325">325</a></p> +<p id="n326" class="pln"><a href="#n326">326</a></p> +<p id="n327" class="pln"><a href="#n327">327</a></p> +<p id="n328" class="stm mis"><a href="#n328">328</a></p> +<p id="n329" class="pln"><a href="#n329">329</a></p> +<p id="n330" class="pln"><a href="#n330">330</a></p> +<p id="n331" class="stm run hide_run"><a href="#n331">331</a></p> +<p id="n332" class="pln"><a href="#n332">332</a></p> +<p id="n333" class="pln"><a href="#n333">333</a></p> +<p id="n334" class="pln"><a href="#n334">334</a></p> +<p id="n335" class="pln"><a href="#n335">335</a></p> +<p id="n336" class="pln"><a href="#n336">336</a></p> +<p id="n337" class="pln"><a href="#n337">337</a></p> +<p id="n338" class="pln"><a href="#n338">338</a></p> +<p id="n339" class="pln"><a href="#n339">339</a></p> +<p id="n340" class="pln"><a href="#n340">340</a></p> +<p id="n341" class="pln"><a href="#n341">341</a></p> +<p id="n342" class="pln"><a href="#n342">342</a></p> +<p id="n343" class="pln"><a href="#n343">343</a></p> +<p id="n344" class="stm run hide_run"><a href="#n344">344</a></p> +<p id="n345" class="pln"><a href="#n345">345</a></p> +<p id="n346" class="pln"><a href="#n346">346</a></p> +<p id="n347" class="stm run hide_run"><a href="#n347">347</a></p> +<p id="n348" class="pln"><a href="#n348">348</a></p> +<p id="n349" class="stm run hide_run"><a href="#n349">349</a></p> +<p id="n350" class="pln"><a href="#n350">350</a></p> +<p id="n351" class="stm run hide_run"><a href="#n351">351</a></p> +<p id="n352" class="pln"><a href="#n352">352</a></p> +<p id="n353" class="pln"><a href="#n353">353</a></p> +<p id="n354" class="stm run hide_run"><a href="#n354">354</a></p> +<p id="n355" class="stm run 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id="n372" class="pln"><a href="#n372">372</a></p> +<p id="n373" class="pln"><a href="#n373">373</a></p> +<p id="n374" class="stm run hide_run"><a href="#n374">374</a></p> +<p id="n375" class="pln"><a href="#n375">375</a></p> +<p id="n376" class="stm run hide_run"><a href="#n376">376</a></p> +<p id="n377" class="stm run hide_run"><a href="#n377">377</a></p> +<p id="n378" class="pln"><a href="#n378">378</a></p> +<p id="n379" class="pln"><a href="#n379">379</a></p> +<p id="n380" class="stm run hide_run"><a href="#n380">380</a></p> +<p id="n381" class="pln"><a href="#n381">381</a></p> +<p id="n382" class="pln"><a href="#n382">382</a></p> +<p id="n383" class="pln"><a href="#n383">383</a></p> +<p id="n384" class="pln"><a href="#n384">384</a></p> +<p id="n385" class="pln"><a href="#n385">385</a></p> +<p id="n386" class="stm run hide_run"><a href="#n386">386</a></p> +<p id="n387" class="pln"><a href="#n387">387</a></p> +<p id="n388" class="stm run hide_run"><a href="#n388">388</a></p> +<p id="n389" class="stm run hide_run"><a href="#n389">389</a></p> +<p id="n390" class="pln"><a href="#n390">390</a></p> +<p id="n391" class="stm run hide_run"><a href="#n391">391</a></p> +<p id="n392" class="pln"><a href="#n392">392</a></p> +<p id="n393" class="pln"><a href="#n393">393</a></p> +<p id="n394" class="stm run hide_run"><a href="#n394">394</a></p> +<p id="n395" class="pln"><a href="#n395">395</a></p> +<p id="n396" class="stm run hide_run"><a href="#n396">396</a></p> +<p id="n397" class="pln"><a href="#n397">397</a></p> +<p id="n398" class="pln"><a href="#n398">398</a></p> +<p id="n399" class="stm run hide_run"><a href="#n399">399</a></p> +<p id="n400" class="pln"><a href="#n400">400</a></p> +<p id="n401" class="pln"><a href="#n401">401</a></p> +<p id="n402" class="pln"><a href="#n402">402</a></p> +<p id="n403" class="stm run hide_run"><a href="#n403">403</a></p> +<p id="n404" class="pln"><a href="#n404">404</a></p> +<p id="n405" class="stm run hide_run"><a href="#n405">405</a></p> +<p id="n406" class="pln"><a href="#n406">406</a></p> +<p id="n407" class="stm run hide_run"><a href="#n407">407</a></p> +<p id="n408" class="pln"><a href="#n408">408</a></p> +<p id="n409" class="pln"><a href="#n409">409</a></p> +<p id="n410" class="pln"><a href="#n410">410</a></p> +<p id="n411" class="stm run hide_run"><a href="#n411">411</a></p> +<p id="n412" class="stm run hide_run"><a href="#n412">412</a></p> +<p id="n413" class="stm run hide_run"><a href="#n413">413</a></p> +<p id="n414" class="stm run hide_run"><a href="#n414">414</a></p> +<p id="n415" class="pln"><a href="#n415">415</a></p> +<p id="n416" class="stm run hide_run"><a href="#n416">416</a></p> +<p id="n417" class="stm run hide_run"><a href="#n417">417</a></p> +<p id="n418" class="pln"><a href="#n418">418</a></p> +<p id="n419" class="stm run hide_run"><a href="#n419">419</a></p> +<p id="n420" class="pln"><a href="#n420">420</a></p> +<p id="n421" class="stm run hide_run"><a href="#n421">421</a></p> +<p id="n422" class="pln"><a href="#n422">422</a></p> +<p id="n423" class="pln"><a href="#n423">423</a></p> +<p id="n424" class="stm run hide_run"><a href="#n424">424</a></p> +<p id="n425" class="stm run hide_run"><a href="#n425">425</a></p> +<p id="n426" class="pln"><a href="#n426">426</a></p> +<p id="n427" class="stm run hide_run"><a href="#n427">427</a></p> +<p id="n428" class="pln"><a href="#n428">428</a></p> +<p id="n429" class="stm run hide_run"><a href="#n429">429</a></p> +<p id="n430" class="stm run hide_run"><a href="#n430">430</a></p> +<p id="n431" class="pln"><a href="#n431">431</a></p> +<p id="n432" class="stm run hide_run"><a href="#n432">432</a></p> +<p id="n433" class="stm run hide_run"><a href="#n433">433</a></p> +<p id="n434" class="stm run hide_run"><a href="#n434">434</a></p> +<p id="n435" class="stm run hide_run"><a href="#n435">435</a></p> +<p id="n436" class="stm run hide_run"><a href="#n436">436</a></p> +<p id="n437" class="stm run 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href="#n454">454</a></p> +<p id="n455" class="pln"><a href="#n455">455</a></p> +<p id="n456" class="pln"><a href="#n456">456</a></p> +<p id="n457" class="stm run hide_run"><a href="#n457">457</a></p> +<p id="n458" class="stm run hide_run"><a href="#n458">458</a></p> +<p id="n459" class="stm run hide_run"><a href="#n459">459</a></p> +<p id="n460" class="pln"><a href="#n460">460</a></p> +<p id="n461" class="pln"><a href="#n461">461</a></p> +<p id="n462" class="stm run hide_run"><a href="#n462">462</a></p> +<p id="n463" class="stm run hide_run"><a href="#n463">463</a></p> +<p id="n464" class="stm run hide_run"><a href="#n464">464</a></p> +<p id="n465" class="stm run hide_run"><a href="#n465">465</a></p> +<p id="n466" class="stm run hide_run"><a href="#n466">466</a></p> +<p id="n467" class="pln"><a href="#n467">467</a></p> +<p id="n468" class="stm run hide_run"><a href="#n468">468</a></p> +<p id="n469" class="pln"><a href="#n469">469</a></p> +<p id="n470" class="stm run hide_run"><a href="#n470">470</a></p> +<p id="n471" class="pln"><a href="#n471">471</a></p> +<p id="n472" class="stm run hide_run"><a href="#n472">472</a></p> +<p id="n473" class="stm run hide_run"><a href="#n473">473</a></p> +<p id="n474" class="pln"><a href="#n474">474</a></p> +<p id="n475" class="pln"><a href="#n475">475</a></p> +<p id="n476" class="stm run hide_run"><a href="#n476">476</a></p> +<p id="n477" class="pln"><a href="#n477">477</a></p> +<p id="n478" class="stm run hide_run"><a href="#n478">478</a></p> +<p id="n479" class="pln"><a href="#n479">479</a></p> +<p id="n480" class="stm run hide_run"><a href="#n480">480</a></p> +<p id="n481" class="stm run hide_run"><a href="#n481">481</a></p> +<p id="n482" class="stm run hide_run"><a href="#n482">482</a></p> +<p id="n483" class="pln"><a href="#n483">483</a></p> +<p id="n484" class="pln"><a href="#n484">484</a></p> +<p id="n485" class="pln"><a href="#n485">485</a></p> +<p id="n486" class="pln"><a href="#n486">486</a></p> +<p id="n487" class="stm run hide_run"><a href="#n487">487</a></p> +<p id="n488" class="pln"><a href="#n488">488</a></p> +<p id="n489" class="stm run hide_run"><a href="#n489">489</a></p> +<p id="n490" class="pln"><a href="#n490">490</a></p> +<p id="n491" class="stm run hide_run"><a href="#n491">491</a></p> +<p id="n492" class="pln"><a href="#n492">492</a></p> +<p id="n493" class="pln"><a href="#n493">493</a></p> +<p id="n494" class="pln"><a href="#n494">494</a></p> +<p id="n495" class="pln"><a href="#n495">495</a></p> +<p id="n496" class="pln"><a href="#n496">496</a></p> +<p id="n497" class="pln"><a href="#n497">497</a></p> +<p id="n498" class="pln"><a href="#n498">498</a></p> +<p id="n499" class="pln"><a href="#n499">499</a></p> +<p id="n500" class="pln"><a href="#n500">500</a></p> +<p id="n501" class="pln"><a href="#n501">501</a></p> +<p id="n502" class="pln"><a href="#n502">502</a></p> +<p id="n503" class="pln"><a href="#n503">503</a></p> +<p id="n504" class="pln"><a href="#n504">504</a></p> +<p id="n505" class="pln"><a href="#n505">505</a></p> +<p id="n506" class="pln"><a href="#n506">506</a></p> +<p id="n507" class="pln"><a href="#n507">507</a></p> +<p id="n508" class="pln"><a href="#n508">508</a></p> +<p id="n509" class="pln"><a href="#n509">509</a></p> +<p id="n510" class="pln"><a href="#n510">510</a></p> +<p id="n511" class="pln"><a href="#n511">511</a></p> +<p id="n512" class="pln"><a href="#n512">512</a></p> +<p id="n513" class="pln"><a href="#n513">513</a></p> +<p id="n514" class="pln"><a href="#n514">514</a></p> +<p id="n515" class="pln"><a href="#n515">515</a></p> +<p id="n516" class="pln"><a href="#n516">516</a></p> +<p id="n517" class="pln"><a href="#n517">517</a></p> +<p id="n518" class="pln"><a href="#n518">518</a></p> +<p id="n519" class="pln"><a href="#n519">519</a></p> +<p id="n520" class="pln"><a href="#n520">520</a></p> +<p id="n521" class="pln"><a href="#n521">521</a></p> +<p id="n522" class="pln"><a href="#n522">522</a></p> +<p id="n523" class="pln"><a href="#n523">523</a></p> +<p id="n524" class="pln"><a href="#n524">524</a></p> +<p id="n525" class="pln"><a href="#n525">525</a></p> +<p id="n526" class="pln"><a href="#n526">526</a></p> +<p id="n527" class="pln"><a href="#n527">527</a></p> +<p id="n528" class="pln"><a href="#n528">528</a></p> +<p id="n529" class="pln"><a href="#n529">529</a></p> +<p id="n530" class="stm run hide_run"><a href="#n530">530</a></p> +<p id="n531" class="stm run hide_run"><a href="#n531">531</a></p> +<p id="n532" class="stm run hide_run"><a href="#n532">532</a></p> +<p id="n533" class="stm run hide_run"><a href="#n533">533</a></p> +<p id="n534" class="pln"><a href="#n534">534</a></p> +<p id="n535" class="stm mis"><a href="#n535">535</a></p> +<p id="n536" class="pln"><a href="#n536">536</a></p> +<p id="n537" class="stm run hide_run"><a href="#n537">537</a></p> +<p id="n538" class="pln"><a href="#n538">538</a></p> +<p id="n539" class="stm run hide_run"><a href="#n539">539</a></p> +<p id="n540" class="pln"><a href="#n540">540</a></p> +<p id="n541" class="pln"><a href="#n541">541</a></p> +<p id="n542" class="pln"><a href="#n542">542</a></p> +<p id="n543" class="pln"><a href="#n543">543</a></p> +<p id="n544" class="pln"><a href="#n544">544</a></p> +<p id="n545" class="pln"><a href="#n545">545</a></p> +<p id="n546" class="pln"><a href="#n546">546</a></p> +<p id="n547" class="pln"><a href="#n547">547</a></p> +<p id="n548" class="pln"><a href="#n548">548</a></p> +<p id="n549" class="pln"><a href="#n549">549</a></p> +<p id="n550" class="pln"><a href="#n550">550</a></p> +<p id="n551" class="pln"><a href="#n551">551</a></p> +<p id="n552" class="pln"><a href="#n552">552</a></p> +<p id="n553" class="pln"><a href="#n553">553</a></p> +<p id="n554" class="pln"><a href="#n554">554</a></p> +<p id="n555" class="pln"><a href="#n555">555</a></p> +<p id="n556" class="pln"><a href="#n556">556</a></p> +<p id="n557" class="pln"><a href="#n557">557</a></p> +<p id="n558" class="pln"><a href="#n558">558</a></p> +<p id="n559" class="pln"><a href="#n559">559</a></p> +<p id="n560" class="pln"><a href="#n560">560</a></p> +<p id="n561" class="pln"><a href="#n561">561</a></p> +<p id="n562" class="pln"><a href="#n562">562</a></p> +<p id="n563" class="pln"><a href="#n563">563</a></p> +<p id="n564" class="pln"><a href="#n564">564</a></p> +<p id="n565" class="stm run hide_run"><a href="#n565">565</a></p> +<p id="n566" class="pln"><a href="#n566">566</a></p> +<p id="n567" class="stm run hide_run"><a href="#n567">567</a></p> +<p id="n568" class="stm run hide_run"><a href="#n568">568</a></p> +<p id="n569" class="pln"><a href="#n569">569</a></p> +<p id="n570" class="stm run hide_run"><a href="#n570">570</a></p> +<p id="n571" class="pln"><a href="#n571">571</a></p> +<p id="n572" class="stm run hide_run"><a href="#n572">572</a></p> +<p id="n573" class="pln"><a href="#n573">573</a></p> +<p id="n574" class="stm run hide_run"><a href="#n574">574</a></p> +<p id="n575" class="pln"><a href="#n575">575</a></p> +<p id="n576" class="stm run hide_run"><a href="#n576">576</a></p> +<p id="n577" class="pln"><a href="#n577">577</a></p> +<p id="n578" class="stm run hide_run"><a href="#n578">578</a></p> +<p id="n579" class="pln"><a href="#n579">579</a></p> +<p id="n580" class="stm run hide_run"><a href="#n580">580</a></p> +<p id="n581" class="pln"><a href="#n581">581</a></p> +<p id="n582" class="pln"><a href="#n582">582</a></p> +<p id="n583" class="stm run hide_run"><a href="#n583">583</a></p> +<p id="n584" class="stm run hide_run"><a href="#n584">584</a></p> +<p id="n585" class="pln"><a href="#n585">585</a></p> +<p id="n586" class="stm run hide_run"><a href="#n586">586</a></p> +<p id="n587" class="stm run hide_run"><a href="#n587">587</a></p> +<p id="n588" class="pln"><a href="#n588">588</a></p> +<p id="n589" class="stm run hide_run"><a href="#n589">589</a></p> +<p id="n590" class="stm run hide_run"><a href="#n590">590</a></p> +<p id="n591" class="stm run hide_run"><a href="#n591">591</a></p> +<p id="n592" class="pln"><a href="#n592">592</a></p> +<p id="n593" class="pln"><a href="#n593">593</a></p> +<p id="n594" class="pln"><a href="#n594">594</a></p> +<p id="n595" class="pln"><a href="#n595">595</a></p> +<p id="n596" class="pln"><a href="#n596">596</a></p> +<p id="n597" class="pln"><a href="#n597">597</a></p> +<p id="n598" class="stm run hide_run"><a href="#n598">598</a></p> +<p id="n599" class="stm run hide_run"><a href="#n599">599</a></p> +<p id="n600" class="pln"><a href="#n600">600</a></p> +<p id="n601" class="stm run hide_run"><a href="#n601">601</a></p> +<p id="n602" class="pln"><a href="#n602">602</a></p> +<p id="n603" class="pln"><a href="#n603">603</a></p> +<p id="n604" class="pln"><a href="#n604">604</a></p> +<p id="n605" class="pln"><a href="#n605">605</a></p> +<p id="n606" class="pln"><a href="#n606">606</a></p> +<p id="n607" class="stm run hide_run"><a href="#n607">607</a></p> +<p id="n608" class="pln"><a href="#n608">608</a></p> +<p id="n609" class="stm run hide_run"><a href="#n609">609</a></p> +<p id="n610" class="pln"><a href="#n610">610</a></p> +<p id="n611" class="pln"><a href="#n611">611</a></p> +<p id="n612" class="pln"><a href="#n612">612</a></p> +<p id="n613" class="pln"><a href="#n613">613</a></p> +<p id="n614" class="pln"><a href="#n614">614</a></p> +<p id="n615" class="pln"><a href="#n615">615</a></p> +<p id="n616" class="pln"><a href="#n616">616</a></p> +<p id="n617" class="stm mis"><a href="#n617">617</a></p> +<p id="n618" class="pln"><a href="#n618">618</a></p> +<p id="n619" class="stm mis"><a href="#n619">619</a></p> +<p id="n620" class="pln"><a href="#n620">620</a></p> +<p id="n621" class="pln"><a href="#n621">621</a></p> +<p id="n622" class="stm mis"><a href="#n622">622</a></p> +<p id="n623" class="pln"><a href="#n623">623</a></p> +<p id="n624" class="stm mis"><a href="#n624">624</a></p> +<p id="n625" class="pln"><a href="#n625">625</a></p> +<p id="n626" class="stm mis"><a href="#n626">626</a></p> +<p id="n627" class="stm mis"><a href="#n627">627</a></p> +<p id="n628" class="stm mis"><a href="#n628">628</a></p> +<p id="n629" class="stm mis"><a href="#n629">629</a></p> +<p id="n630" class="stm mis"><a href="#n630">630</a></p> +<p id="n631" class="stm mis"><a href="#n631">631</a></p> +<p id="n632" class="stm mis"><a href="#n632">632</a></p> +<p id="n633" class="stm mis"><a href="#n633">633</a></p> +<p id="n634" class="pln"><a href="#n634">634</a></p> +<p id="n635" class="stm mis"><a href="#n635">635</a></p> +<p id="n636" class="stm mis"><a href="#n636">636</a></p> +<p id="n637" class="stm mis"><a href="#n637">637</a></p> +<p id="n638" class="pln"><a href="#n638">638</a></p> +<p id="n639" class="stm mis"><a href="#n639">639</a></p> +<p id="n640" class="pln"><a href="#n640">640</a></p> +<p id="n641" class="stm mis"><a href="#n641">641</a></p> +<p id="n642" class="pln"><a href="#n642">642</a></p> +<p id="n643" class="stm mis"><a href="#n643">643</a></p> +<p id="n644" class="stm mis"><a href="#n644">644</a></p> +<p id="n645" class="pln"><a href="#n645">645</a></p> +<p id="n646" class="pln"><a href="#n646">646</a></p> +<p id="n647" class="pln"><a href="#n647">647</a></p> +<p id="n648" class="pln"><a href="#n648">648</a></p> +<p id="n649" class="pln"><a href="#n649">649</a></p> +<p id="n650" class="stm mis"><a href="#n650">650</a></p> +<p id="n651" class="pln"><a href="#n651">651</a></p> +<p id="n652" class="stm mis"><a href="#n652">652</a></p> +<p id="n653" class="pln"><a href="#n653">653</a></p> +<p id="n654" class="stm run hide_run"><a href="#n654">654</a></p> +<p id="n655" class="pln"><a href="#n655">655</a></p> +<p id="n656" class="pln"><a href="#n656">656</a></p> +<p id="n657" class="pln"><a href="#n657">657</a></p> +<p id="n658" class="pln"><a href="#n658">658</a></p> +<p id="n659" class="stm mis"><a href="#n659">659</a></p> +<p id="n660" class="pln"><a href="#n660">660</a></p> +<p id="n661" class="pln"><a href="#n661">661</a></p> +<p id="n662" class="stm run hide_run"><a href="#n662">662</a></p> +<p id="n663" class="pln"><a href="#n663">663</a></p> +<p id="n664" class="pln"><a href="#n664">664</a></p> +<p id="n665" class="pln"><a href="#n665">665</a></p> +<p id="n666" class="pln"><a href="#n666">666</a></p> +<p id="n667" class="pln"><a href="#n667">667</a></p> +<p id="n668" class="pln"><a href="#n668">668</a></p> +<p id="n669" class="pln"><a href="#n669">669</a></p> +<p id="n670" class="pln"><a href="#n670">670</a></p> +<p id="n671" class="pln"><a href="#n671">671</a></p> +<p id="n672" class="pln"><a href="#n672">672</a></p> +<p id="n673" class="pln"><a href="#n673">673</a></p> +<p id="n674" class="stm run hide_run"><a href="#n674">674</a></p> +<p id="n675" class="pln"><a href="#n675">675</a></p> +<p id="n676" class="pln"><a href="#n676">676</a></p> +<p id="n677" class="pln"><a href="#n677">677</a></p> +<p id="n678" class="pln"><a href="#n678">678</a></p> +<p id="n679" class="pln"><a href="#n679">679</a></p> +<p id="n680" class="pln"><a href="#n680">680</a></p> +<p id="n681" class="pln"><a href="#n681">681</a></p> +<p id="n682" class="pln"><a href="#n682">682</a></p> +<p id="n683" class="pln"><a href="#n683">683</a></p> +<p id="n684" class="stm run hide_run"><a href="#n684">684</a></p> +<p id="n685" class="pln"><a href="#n685">685</a></p> +<p id="n686" class="pln"><a href="#n686">686</a></p> +<p id="n687" class="stm run hide_run"><a href="#n687">687</a></p> +<p id="n688" class="pln"><a href="#n688">688</a></p> +<p id="n689" class="pln"><a href="#n689">689</a></p> +<p id="n690" class="stm run hide_run"><a href="#n690">690</a></p> +<p id="n691" class="pln"><a href="#n691">691</a></p> +<p id="n692" class="pln"><a href="#n692">692</a></p> +<p id="n693" class="stm run hide_run"><a href="#n693">693</a></p> +<p id="n694" class="pln"><a href="#n694">694</a></p> +<p id="n695" class="pln"><a href="#n695">695</a></p> +<p id="n696" class="pln"><a href="#n696">696</a></p> +<p id="n697" class="pln"><a href="#n697">697</a></p> +<p id="n698" class="stm run hide_run"><a href="#n698">698</a></p> +<p id="n699" class="pln"><a href="#n699">699</a></p> +<p id="n700" class="pln"><a href="#n700">700</a></p> +<p id="n701" class="stm run hide_run"><a href="#n701">701</a></p> +<p id="n702" class="pln"><a href="#n702">702</a></p> +<p id="n703" class="pln"><a href="#n703">703</a></p> +<p id="n704" class="pln"><a href="#n704">704</a></p> +<p id="n705" class="pln"><a href="#n705">705</a></p> +<p id="n706" class="stm run hide_run"><a href="#n706">706</a></p> +<p id="n707" class="stm mis"><a href="#n707">707</a></p> +<p id="n708" class="pln"><a href="#n708">708</a></p> +<p id="n709" class="pln"><a href="#n709">709</a></p> +<p id="n710" class="stm run hide_run"><a href="#n710">710</a></p> +<p id="n711" class="pln"><a href="#n711">711</a></p> +<p id="n712" class="pln"><a href="#n712">712</a></p> +<p id="n713" class="stm mis"><a href="#n713">713</a></p> +<p id="n714" class="pln"><a href="#n714">714</a></p> +<p id="n715" class="pln"><a href="#n715">715</a></p> +<p id="n716" class="pln"><a href="#n716">716</a></p> +<p id="n717" class="pln"><a href="#n717">717</a></p> +<p id="n718" class="stm mis"><a href="#n718">718</a></p> +<p id="n719" class="pln"><a href="#n719">719</a></p> +<p id="n720" class="pln"><a href="#n720">720</a></p> +<p id="n721" class="stm run hide_run"><a href="#n721">721</a></p> +<p id="n722" class="pln"><a href="#n722">722</a></p> +<p id="n723" class="pln"><a href="#n723">723</a></p> +<p id="n724" class="pln"><a href="#n724">724</a></p> +<p id="n725" class="pln"><a href="#n725">725</a></p> +<p id="n726" class="pln"><a href="#n726">726</a></p> +<p id="n727" class="pln"><a href="#n727">727</a></p> +<p id="n728" class="pln"><a href="#n728">728</a></p> +<p id="n729" class="pln"><a href="#n729">729</a></p> +<p id="n730" class="pln"><a href="#n730">730</a></p> +<p id="n731" class="pln"><a href="#n731">731</a></p> +<p id="n732" class="pln"><a href="#n732">732</a></p> +<p id="n733" class="pln"><a href="#n733">733</a></p> +<p id="n734" class="pln"><a href="#n734">734</a></p> +<p id="n735" class="pln"><a href="#n735">735</a></p> +<p id="n736" class="pln"><a href="#n736">736</a></p> +<p id="n737" class="pln"><a href="#n737">737</a></p> +<p id="n738" class="pln"><a href="#n738">738</a></p> +<p id="n739" class="pln"><a href="#n739">739</a></p> +<p id="n740" class="pln"><a href="#n740">740</a></p> +<p id="n741" class="pln"><a href="#n741">741</a></p> +<p id="n742" class="pln"><a href="#n742">742</a></p> +<p id="n743" class="pln"><a href="#n743">743</a></p> +<p id="n744" class="pln"><a href="#n744">744</a></p> +<p id="n745" class="pln"><a href="#n745">745</a></p> +<p id="n746" class="pln"><a href="#n746">746</a></p> +<p id="n747" class="pln"><a href="#n747">747</a></p> +<p id="n748" class="pln"><a href="#n748">748</a></p> +<p id="n749" class="pln"><a href="#n749">749</a></p> +<p id="n750" class="pln"><a href="#n750">750</a></p> +<p id="n751" class="pln"><a href="#n751">751</a></p> +<p id="n752" class="pln"><a href="#n752">752</a></p> +<p id="n753" class="pln"><a href="#n753">753</a></p> +<p id="n754" class="pln"><a href="#n754">754</a></p> +<p id="n755" class="pln"><a href="#n755">755</a></p> +<p id="n756" class="pln"><a href="#n756">756</a></p> +<p id="n757" class="pln"><a href="#n757">757</a></p> +<p id="n758" class="pln"><a href="#n758">758</a></p> +<p id="n759" class="stm run hide_run"><a href="#n759">759</a></p> +<p id="n760" class="pln"><a href="#n760">760</a></p> +<p id="n761" class="stm run hide_run"><a href="#n761">761</a></p> +<p id="n762" class="stm run hide_run"><a href="#n762">762</a></p> +<p id="n763" class="stm mis"><a href="#n763">763</a></p> +<p id="n764" class="stm mis"><a href="#n764">764</a></p> +<p id="n765" class="pln"><a href="#n765">765</a></p> +<p id="n766" class="stm mis"><a href="#n766">766</a></p> +<p id="n767" class="pln"><a href="#n767">767</a></p> +<p id="n768" class="stm run hide_run"><a href="#n768">768</a></p> +<p id="n769" class="pln"><a href="#n769">769</a></p> +<p id="n770" class="pln"><a href="#n770">770</a></p> +<p id="n771" class="stm run hide_run"><a href="#n771">771</a></p> +<p id="n772" class="pln"><a href="#n772">772</a></p> +<p id="n773" class="pln"><a href="#n773">773</a></p> +<p id="n774" class="pln"><a href="#n774">774</a></p> +<p id="n775" class="pln"><a href="#n775">775</a></p> +<p id="n776" class="pln"><a href="#n776">776</a></p> +<p id="n777" class="pln"><a href="#n777">777</a></p> +<p id="n778" class="pln"><a href="#n778">778</a></p> +<p id="n779" class="pln"><a href="#n779">779</a></p> +<p id="n780" class="pln"><a href="#n780">780</a></p> +<p id="n781" class="pln"><a href="#n781">781</a></p> +<p id="n782" class="pln"><a href="#n782">782</a></p> +<p id="n783" class="pln"><a href="#n783">783</a></p> +<p id="n784" class="stm run hide_run"><a href="#n784">784</a></p> +<p id="n785" class="pln"><a href="#n785">785</a></p> +<p id="n786" class="pln"><a href="#n786">786</a></p> +<p id="n787" class="stm run hide_run"><a href="#n787">787</a></p> +<p id="n788" class="pln"><a href="#n788">788</a></p> +<p id="n789" class="stm run hide_run"><a href="#n789">789</a></p> +<p id="n790" class="stm run hide_run"><a href="#n790">790</a></p> +<p id="n791" class="stm run hide_run"><a href="#n791">791</a></p> +<p id="n792" class="stm run hide_run"><a href="#n792">792</a></p> +<p id="n793" class="stm run hide_run"><a href="#n793">793</a></p> +<p id="n794" class="stm run hide_run"><a href="#n794">794</a></p> +<p id="n795" class="stm run hide_run"><a href="#n795">795</a></p> +<p id="n796" class="stm run hide_run"><a href="#n796">796</a></p> +<p id="n797" class="stm run hide_run"><a href="#n797">797</a></p> +<p id="n798" class="pln"><a href="#n798">798</a></p> +<p id="n799" class="stm run hide_run"><a href="#n799">799</a></p> +<p id="n800" class="pln"><a href="#n800">800</a></p> +<p id="n801" class="pln"><a href="#n801">801</a></p> +<p id="n802" class="pln"><a href="#n802">802</a></p> +<p id="n803" class="pln"><a href="#n803">803</a></p> +<p id="n804" class="pln"><a href="#n804">804</a></p> +<p id="n805" class="pln"><a href="#n805">805</a></p> +<p id="n806" class="pln"><a href="#n806">806</a></p> +<p id="n807" class="pln"><a href="#n807">807</a></p> +<p id="n808" class="pln"><a href="#n808">808</a></p> +<p id="n809" class="stm run hide_run"><a href="#n809">809</a></p> +<p id="n810" class="pln"><a href="#n810">810</a></p> +<p id="n811" class="stm run hide_run"><a href="#n811">811</a></p> +<p id="n812" class="pln"><a href="#n812">812</a></p> +<p id="n813" class="pln"><a href="#n813">813</a></p> +<p id="n814" class="pln"><a href="#n814">814</a></p> +<p id="n815" class="pln"><a href="#n815">815</a></p> +<p id="n816" class="pln"><a href="#n816">816</a></p> +<p id="n817" class="pln"><a href="#n817">817</a></p> +<p id="n818" class="pln"><a href="#n818">818</a></p> +<p id="n819" class="pln"><a href="#n819">819</a></p> +<p id="n820" class="stm run hide_run"><a href="#n820">820</a></p> +<p id="n821" class="pln"><a href="#n821">821</a></p> +<p id="n822" class="stm run hide_run"><a href="#n822">822</a></p> +<p id="n823" class="pln"><a href="#n823">823</a></p> +<p id="n824" class="pln"><a href="#n824">824</a></p> +<p id="n825" class="pln"><a href="#n825">825</a></p> +<p id="n826" class="pln"><a href="#n826">826</a></p> +<p id="n827" class="pln"><a href="#n827">827</a></p> +<p id="n828" class="pln"><a href="#n828">828</a></p> +<p id="n829" class="pln"><a href="#n829">829</a></p> +<p id="n830" class="pln"><a href="#n830">830</a></p> +<p id="n831" class="stm run hide_run"><a href="#n831">831</a></p> +<p id="n832" class="pln"><a href="#n832">832</a></p> +<p id="n833" class="stm run hide_run"><a href="#n833">833</a></p> +<p id="n834" class="pln"><a href="#n834">834</a></p> +<p id="n835" class="pln"><a href="#n835">835</a></p> +<p id="n836" class="pln"><a href="#n836">836</a></p> +<p id="n837" class="pln"><a href="#n837">837</a></p> +<p id="n838" class="pln"><a href="#n838">838</a></p> +<p id="n839" class="pln"><a href="#n839">839</a></p> +<p id="n840" class="pln"><a href="#n840">840</a></p> +<p id="n841" class="pln"><a href="#n841">841</a></p> +<p id="n842" class="stm run hide_run"><a href="#n842">842</a></p> +<p id="n843" class="pln"><a href="#n843">843</a></p> +<p id="n844" class="stm run hide_run"><a href="#n844">844</a></p> +<p id="n845" class="pln"><a href="#n845">845</a></p> +<p id="n846" class="pln"><a href="#n846">846</a></p> +<p id="n847" class="pln"><a href="#n847">847</a></p> +<p id="n848" class="pln"><a href="#n848">848</a></p> +<p id="n849" class="pln"><a href="#n849">849</a></p> +<p id="n850" class="pln"><a href="#n850">850</a></p> +<p id="n851" class="pln"><a href="#n851">851</a></p> +<p id="n852" class="pln"><a href="#n852">852</a></p> +<p id="n853" class="stm run hide_run"><a href="#n853">853</a></p> +<p id="n854" class="pln"><a href="#n854">854</a></p> +<p id="n855" class="stm run hide_run"><a href="#n855">855</a></p> +<p id="n856" class="pln"><a href="#n856">856</a></p> +<p id="n857" class="pln"><a href="#n857">857</a></p> +<p id="n858" class="pln"><a href="#n858">858</a></p> +<p id="n859" class="pln"><a href="#n859">859</a></p> +<p id="n860" class="pln"><a href="#n860">860</a></p> +<p id="n861" class="pln"><a href="#n861">861</a></p> +<p id="n862" class="pln"><a href="#n862">862</a></p> +<p id="n863" class="pln"><a href="#n863">863</a></p> +<p id="n864" class="stm run hide_run"><a href="#n864">864</a></p> +<p id="n865" class="pln"><a href="#n865">865</a></p> +<p id="n866" class="stm run hide_run"><a href="#n866">866</a></p> +<p id="n867" class="pln"><a href="#n867">867</a></p> +<p id="n868" class="pln"><a href="#n868">868</a></p> +<p id="n869" class="pln"><a href="#n869">869</a></p> +<p id="n870" class="pln"><a href="#n870">870</a></p> +<p id="n871" class="pln"><a href="#n871">871</a></p> +<p id="n872" class="pln"><a href="#n872">872</a></p> +<p id="n873" class="pln"><a href="#n873">873</a></p> +<p id="n874" class="pln"><a href="#n874">874</a></p> +<p id="n875" class="stm run hide_run"><a href="#n875">875</a></p> +<p id="n876" class="pln"><a href="#n876">876</a></p> +<p id="n877" class="stm run hide_run"><a href="#n877">877</a></p> +<p id="n878" class="pln"><a href="#n878">878</a></p> +<p id="n879" class="pln"><a href="#n879">879</a></p> +<p id="n880" class="pln"><a href="#n880">880</a></p> +<p id="n881" class="pln"><a href="#n881">881</a></p> +<p id="n882" class="pln"><a href="#n882">882</a></p> +<p id="n883" class="pln"><a href="#n883">883</a></p> +<p id="n884" class="pln"><a href="#n884">884</a></p> +<p id="n885" class="pln"><a href="#n885">885</a></p> +<p id="n886" class="stm run hide_run"><a href="#n886">886</a></p> +<p id="n887" class="pln"><a href="#n887">887</a></p> +<p id="n888" class="stm run hide_run"><a href="#n888">888</a></p> +<p id="n889" class="pln"><a href="#n889">889</a></p> +<p id="n890" class="pln"><a href="#n890">890</a></p> +<p id="n891" class="pln"><a href="#n891">891</a></p> +<p id="n892" class="pln"><a href="#n892">892</a></p> +<p id="n893" class="pln"><a href="#n893">893</a></p> +<p id="n894" class="pln"><a href="#n894">894</a></p> +<p id="n895" class="pln"><a href="#n895">895</a></p> +<p id="n896" class="pln"><a href="#n896">896</a></p> +<p id="n897" class="stm run hide_run"><a href="#n897">897</a></p> + + </td> + <td class="text"> +<p id="t1" class="stm run hide_run"><span class="key">from</span> <span class="nam">abc</span> <span class="key">import</span> <span class="nam">abstractmethod</span><span class="strut"> </span></p> +<p id="t2" class="stm run hide_run"><span class="key">from</span> <span class="nam">datetime</span> <span class="key">import</span> <span class="nam">timedelta</span><span class="strut"> </span></p> +<p id="t3" class="pln"><span class="strut"> </span></p> +<p id="t4" class="stm run hide_run"><span class="key">import</span> <span class="nam">numpy</span> <span class="key">as</span> <span class="nam">np</span><span class="strut"> </span></p> +<p id="t5" class="stm run hide_run"><span class="key">from</span> <span class="nam">scipy</span><span class="op">.</span><span class="nam">stats</span> <span class="key">import</span> <span class="nam">beta</span><span class="strut"> </span></p> +<p id="t6" class="stm run hide_run"><span class="key">import</span> <span class="nam">pandas</span> <span class="key">as</span> <span class="nam">pd</span><span class="strut"> </span></p> +<p id="t7" class="pln"><span class="strut"> </span></p> +<p id="t8" class="stm run hide_run"><span class="nam">VON_KARMAN_CONSTANT</span> <span class="op">=</span> <span class="num">0.41</span><span class="strut"> </span></p> +<p id="t9" class="pln"><span class="strut"> </span></p> +<p id="t10" class="pln"><span class="strut"> </span></p> +<p id="t11" class="stm run hide_run"><span class="key">def</span> <span class="nam">calc_water_density</span><span class="op">(</span><span class="nam">temperature</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t12" class="pln"> <span class="str">"""Calculate the temperature-dependent density of water</span><span class="strut"> </span></p> +<p id="t13" class="pln"><span class="strut"> </span></p> +<p id="t14" class="pln"><span class="str"> :param temperature: Water temperature in deg C</span><span class="strut"> </span></p> +<p id="t15" class="pln"><span class="str"> :return: Density of water in kg/m**3</span><span class="strut"> </span></p> +<p id="t16" class="pln"><span class="strut"> </span></p> +<p id="t17" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t18" class="pln"><span class="strut"> </span></p> +<p id="t19" class="stm run hide_run"> <span class="nam">a_0</span> <span class="op">=</span> <span class="num">999.842594</span><span class="strut"> </span></p> +<p id="t20" class="stm run hide_run"> <span class="nam">a_1</span> <span class="op">=</span> <span class="num">6.793952e-2</span><span class="strut"> </span></p> +<p id="t21" class="stm run hide_run"> <span class="nam">a_2</span> <span class="op">=</span> <span class="op">-</span><span class="num">9.09529e-3</span><span class="strut"> </span></p> +<p id="t22" class="stm run hide_run"> <span class="nam">a_3</span> <span class="op">=</span> <span class="num">1.001685e-4</span><span class="strut"> </span></p> +<p id="t23" class="stm run hide_run"> <span class="nam">a_4</span> <span class="op">=</span> <span class="op">-</span><span class="num">1.120083e-6</span><span class="strut"> </span></p> +<p id="t24" class="stm run hide_run"> <span class="nam">a_5</span> <span class="op">=</span> <span class="num">6.536332e-9</span><span class="strut"> </span></p> +<p id="t25" class="pln"><span class="strut"> </span></p> +<p id="t26" class="stm run hide_run"> <span class="key">return</span> <span class="nam">a_0</span> <span class="op">+</span> <span class="nam">a_1</span><span class="op">*</span><span class="nam">temperature</span> <span class="op">+</span> <span class="nam">a_2</span><span class="op">*</span><span class="nam">temperature</span><span class="op">**</span><span class="num">2</span> <span class="op">+</span> <span class="nam">a_3</span><span class="op">*</span><span class="nam">temperature</span><span class="op">**</span><span class="num">3</span> <span class="op">+</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t27" class="pln"> <span class="nam">a_4</span><span class="op">*</span><span class="nam">temperature</span><span class="op">**</span><span class="num">4</span> <span class="op">+</span> <span class="nam">a_5</span><span class="op">*</span><span class="nam">temperature</span><span class="op">**</span><span class="num">5</span><span class="strut"> </span></p> +<p id="t28" class="pln"><span class="strut"> </span></p> +<p id="t29" class="pln"><span class="strut"> </span></p> +<p id="t30" class="stm run hide_run"><span class="key">def</span> <span class="nam">calc_water_viscosity</span><span class="op">(</span><span class="nam">temperature</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t31" class="pln"> <span class="str">"""Calculate the temperature-dependent viscosity of water</span><span class="strut"> </span></p> +<p id="t32" class="pln"><span class="strut"> </span></p> +<p id="t33" class="pln"><span class="str"> :param temperature: Water temperature in deg C</span><span class="strut"> </span></p> +<p id="t34" class="pln"><span class="str"> :return: Viscosity of water in m**2/s</span><span class="strut"> </span></p> +<p id="t35" class="pln"><span class="strut"> </span></p> +<p id="t36" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t37" class="pln"><span class="strut"> </span></p> +<p id="t38" class="stm run hide_run"> <span class="key">return</span> <span class="num">1.79e-6</span> <span class="op">/</span> <span class="op">(</span><span class="num">1</span> <span class="op">+</span> <span class="op">(</span><span class="num">0.03368</span> <span class="op">*</span> <span class="nam">temperature</span><span class="op">)</span> <span class="op">+</span><span class="strut"> </span></p> +<p id="t39" class="pln"> <span class="op">(</span><span class="num">0.00021</span> <span class="op">*</span> <span class="op">(</span><span class="nam">temperature</span> <span class="op">**</span> <span class="num">2</span><span class="op">)</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t40" class="pln"><span class="strut"> </span></p> +<p id="t41" class="pln"><span class="strut"> </span></p> +<p id="t42" class="stm run hide_run"><span class="key">class</span> <span class="nam">HydraulicCell</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t43" class="pln"> <span class="str">"""Abstract base class for hydraulic cell data type. Do not initialize."""</span><span class="strut"> </span></p> +<p id="t44" class="pln"><span class="strut"> </span></p> +<p id="t45" class="stm run hide_run"> <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="op">*</span><span class="nam">args</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t46" class="pln"> <span class="str">"""</span><span class="strut"> </span></p> +<p id="t47" class="pln"><span class="strut"> </span></p> +<p id="t48" class="pln"><span class="str"> :param args:</span><span class="strut"> </span></p> +<p id="t49" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t50" class="pln"><span class="strut"> </span></p> +<p id="t51" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_depth</span> <span class="op">=</span> <span class="key">None</span><span class="strut"> </span></p> +<p id="t52" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_discharge</span> <span class="op">=</span> <span class="key">None</span><span class="strut"> </span></p> +<p id="t53" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_length</span> <span class="op">=</span> <span class="key">None</span><span class="strut"> </span></p> +<p id="t54" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_mean_xs_velocity</span> <span class="op">=</span> <span class="key">None</span><span class="strut"> </span></p> +<p id="t55" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_mean_lat_velocity</span> <span class="op">=</span> <span class="key">None</span><span class="strut"> </span></p> +<p id="t56" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_mean_long_velocity</span> <span class="op">=</span> <span class="key">None</span><span class="strut"> </span></p> +<p id="t57" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_mean_vert_velocity</span> <span class="op">=</span> <span class="key">None</span><span class="strut"> </span></p> +<p id="t58" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_shear_velocity</span> <span class="op">=</span> <span class="key">None</span><span class="strut"> </span></p> +<p id="t59" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_temperature</span> <span class="op">=</span> <span class="key">None</span><span class="strut"> </span></p> +<p id="t60" class="pln"><span class="strut"> </span></p> +<p id="t61" class="stm run hide_run"> <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">__class__</span> <span class="op">==</span> <span class="nam">HydraulicCell</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t62" class="stm mis"> <span class="key">raise</span> <span class="nam">NotImplementedError</span><span class="strut"> </span></p> +<p id="t63" class="pln"><span class="strut"> </span></p> +<p id="t64" class="stm run hide_run"> <span class="key">def</span> <span class="nam">depth</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t65" class="pln"> <span class="str">"""Returns the depth of this hydraulic cell</span><span class="strut"> </span></p> +<p id="t66" class="pln"><span class="strut"> </span></p> +<p id="t67" class="pln"><span class="str"> :return: Depth of this cell in m</span><span class="strut"> </span></p> +<p id="t68" class="pln"><span class="str"> :rtype: float</span><span class="strut"> </span></p> +<p id="t69" class="pln"><span class="strut"> </span></p> +<p id="t70" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t71" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_depth</span><span class="strut"> </span></p> +<p id="t72" class="pln"><span class="strut"> </span></p> +<p id="t73" class="stm run hide_run"> <span class="key">def</span> <span class="nam">discharge</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t74" class="pln"> <span class="str">"""Returns the water discharge in this hydraulic cell</span><span class="strut"> </span></p> +<p id="t75" class="pln"><span class="strut"> </span></p> +<p id="t76" class="pln"><span class="str"> :return: Water discharge in this cell in m**3/s</span><span class="strut"> </span></p> +<p id="t77" class="pln"><span class="str"> :rtype: float</span><span class="strut"> </span></p> +<p id="t78" class="pln"><span class="strut"> </span></p> +<p id="t79" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t80" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_discharge</span><span class="strut"> </span></p> +<p id="t81" class="pln"><span class="strut"> </span></p> +<p id="t82" class="stm run hide_run"> <span class="key">def</span> <span class="nam">length</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t83" class="pln"> <span class="str">"""Returns the longitudinal length of this hydraulic cell</span><span class="strut"> </span></p> +<p id="t84" class="pln"><span class="strut"> </span></p> +<p id="t85" class="pln"><span class="str"> :return: Length of this cell in m</span><span class="strut"> </span></p> +<p id="t86" class="pln"><span class="str"> :rtype: float</span><span class="strut"> </span></p> +<p id="t87" class="pln"><span class="strut"> </span></p> +<p id="t88" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t89" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_length</span><span class="strut"> </span></p> +<p id="t90" class="pln"><span class="strut"> </span></p> +<p id="t91" class="stm run hide_run"> <span class="key">def</span> <span class="nam">mean_xs_velocity</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t92" class="pln"> <span class="str">"""Returns the mean cross-section velocity for this cell.</span><span class="strut"> </span></p> +<p id="t93" class="pln"><span class="strut"> </span></p> +<p id="t94" class="pln"><span class="str"> :return: Mean cross-section velocity</span><span class="strut"> </span></p> +<p id="t95" class="pln"><span class="str"> :rtype: float</span><span class="strut"> </span></p> +<p id="t96" class="pln"><span class="strut"> </span></p> +<p id="t97" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t98" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_mean_xs_velocity</span><span class="strut"> </span></p> +<p id="t99" class="pln"><span class="strut"> </span></p> +<p id="t100" class="stm run hide_run"> <span class="key">def</span> <span class="nam">mean_lat_velocity</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t101" class="pln"> <span class="str">"""Returns the mean lateral (y direction) velocity for this cell.</span><span class="strut"> </span></p> +<p id="t102" class="pln"><span class="strut"> </span></p> +<p id="t103" class="pln"><span class="str"> :return: Mean lateral velocity</span><span class="strut"> </span></p> +<p id="t104" class="pln"><span class="str"> :rtype: float</span><span class="strut"> </span></p> +<p id="t105" class="pln"><span class="strut"> </span></p> +<p id="t106" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t107" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_mean_lat_velocity</span><span class="strut"> </span></p> +<p id="t108" class="pln"><span class="strut"> </span></p> +<p id="t109" class="stm run hide_run"> <span class="key">def</span> <span class="nam">mean_long_velocity</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t110" class="pln"> <span class="str">"""Returns the mean longitudinal (x direction) velocity for this cell.</span><span class="strut"> </span></p> +<p id="t111" class="pln"><span class="strut"> </span></p> +<p id="t112" class="pln"><span class="str"> :return:</span><span class="strut"> </span></p> +<p id="t113" class="pln"><span class="strut"> </span></p> +<p id="t114" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t115" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_mean_long_velocity</span><span class="strut"> </span></p> +<p id="t116" class="pln"><span class="strut"> </span></p> +<p id="t117" class="stm run hide_run"> <span class="key">def</span> <span class="nam">mean_vert_velocity</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t118" class="pln"> <span class="str">"""Returns the mean vertical (z direction) velocity for this cell.</span><span class="strut"> </span></p> +<p id="t119" class="pln"><span class="strut"> </span></p> +<p id="t120" class="pln"><span class="str"> :return: Mean vertical velocity</span><span class="strut"> </span></p> +<p id="t121" class="pln"><span class="str"> :rtype: float</span><span class="strut"> </span></p> +<p id="t122" class="pln"><span class="strut"> </span></p> +<p id="t123" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t124" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_mean_vert_velocity</span><span class="strut"> </span></p> +<p id="t125" class="pln"><span class="strut"> </span></p> +<p id="t126" class="stm run hide_run"> <span class="key">def</span> <span class="nam">shear_velocity</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t127" class="pln"> <span class="str">"""Returns the shear velocity of this cell.</span><span class="strut"> </span></p> +<p id="t128" class="pln"><span class="strut"> </span></p> +<p id="t129" class="pln"><span class="str"> :return: Shear velocity in m/s</span><span class="strut"> </span></p> +<p id="t130" class="pln"><span class="str"> :rtype: float</span><span class="strut"> </span></p> +<p id="t131" class="pln"><span class="strut"> </span></p> +<p id="t132" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t133" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_shear_velocity</span><span class="strut"> </span></p> +<p id="t134" class="pln"><span class="strut"> </span></p> +<p id="t135" class="stm run hide_run"> <span class="key">def</span> <span class="nam">temperature</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t136" class="pln"> <span class="str">"""Returns the temperature of this hydraulic cell</span><span class="strut"> </span></p> +<p id="t137" class="pln"><span class="strut"> </span></p> +<p id="t138" class="pln"><span class="str"> :return: Temperature of this cell in deg C</span><span class="strut"> </span></p> +<p id="t139" class="pln"><span class="str"> :rtype: float</span><span class="strut"> </span></p> +<p id="t140" class="pln"><span class="strut"> </span></p> +<p id="t141" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t142" class="pln"><span class="strut"> </span></p> +<p id="t143" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_temperature</span><span class="strut"> </span></p> +<p id="t144" class="pln"><span class="strut"> </span></p> +<p id="t145" class="stm run hide_run"> <span class="key">def</span> <span class="nam">width</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t146" class="pln"> <span class="str">"""Returns the lateral width of this hydraulic cell</span><span class="strut"> </span></p> +<p id="t147" class="pln"><span class="strut"> </span></p> +<p id="t148" class="pln"><span class="str"> :return: Width of this cell in m</span><span class="strut"> </span></p> +<p id="t149" class="pln"><span class="str"> :rtype: float</span><span class="strut"> </span></p> +<p id="t150" class="pln"><span class="strut"> </span></p> +<p id="t151" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t152" class="pln"><span class="strut"> </span></p> +<p id="t153" class="stm mis"> <span class="nam">discharge</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">discharge</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t154" class="stm mis"> <span class="nam">mean_xs_velocity</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">mean_xs_velocity</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t155" class="stm mis"> <span class="nam">depth</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">depth</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t156" class="stm mis"> <span class="nam">area</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">abs</span><span class="op">(</span><span class="nam">discharge</span> <span class="op">/</span> <span class="nam">mean_xs_velocity</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t157" class="stm mis"> <span class="key">return</span> <span class="nam">area</span> <span class="op">/</span> <span class="nam">depth</span><span class="strut"> </span></p> +<p id="t158" class="pln"><span class="strut"> </span></p> +<p id="t159" class="pln"><span class="strut"> </span></p> +<p id="t160" class="stm run hide_run"><span class="key">class</span> <span class="nam">SteadyStateHydraulicCell</span><span class="op">(</span><span class="nam">HydraulicCell</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t161" class="pln"> <span class="str">"""Data type representing a steady-state hydraulic cell.</span><span class="strut"> </span></p> +<p id="t162" class="pln"><span class="strut"> </span></p> +<p id="t163" class="pln"><span class="str"> A hydraulic cell typically represents a cell in a series of cells within a</span><span class="strut"> </span></p> +<p id="t164" class="pln"><span class="str"> river reach. This class implementation represents steady-state hydraulic</span><span class="strut"> </span></p> +<p id="t165" class="pln"><span class="str"> conditions.</span><span class="strut"> </span></p> +<p id="t166" class="pln"><span class="strut"> </span></p> +<p id="t167" class="pln"><span class="str"> Parameters</span><span class="strut"> </span></p> +<p id="t168" class="pln"><span class="str"> ----------</span><span class="strut"> </span></p> +<p id="t169" class="pln"><span class="str"> length : float</span><span class="strut"> </span></p> +<p id="t170" class="pln"><span class="str"> Length of this cell in m</span><span class="strut"> </span></p> +<p id="t171" class="pln"><span class="strut"> </span></p> +<p id="t172" class="pln"><span class="str"> depth : float</span><span class="strut"> </span></p> +<p id="t173" class="pln"><span class="str"> Depth of this cell in m</span><span class="strut"> </span></p> +<p id="t174" class="pln"><span class="strut"> </span></p> +<p id="t175" class="pln"><span class="str"> discharge : float</span><span class="strut"> </span></p> +<p id="t176" class="pln"><span class="str"> Discharge in this cell in m**3/s</span><span class="strut"> </span></p> +<p id="t177" class="pln"><span class="strut"> </span></p> +<p id="t178" class="pln"><span class="str"> mean_xs_velocity : float</span><span class="strut"> </span></p> +<p id="t179" class="pln"><span class="str"> Mean cross section velocity in this cell in m/s</span><span class="strut"> </span></p> +<p id="t180" class="pln"><span class="strut"> </span></p> +<p id="t181" class="pln"><span class="str"> mean_lat_velocity : float</span><span class="strut"> </span></p> +<p id="t182" class="pln"><span class="str"> Mean lateral velocity in this cell in m/s</span><span class="strut"> </span></p> +<p id="t183" class="pln"><span class="strut"> </span></p> +<p id="t184" class="pln"><span class="str"> mean_vert_velocity : float</span><span class="strut"> </span></p> +<p id="t185" class="pln"><span class="str"> Mean vertical velocity in this cell in m/s</span><span class="strut"> </span></p> +<p id="t186" class="pln"><span class="strut"> </span></p> +<p id="t187" class="pln"><span class="str"> shear_velocity : float</span><span class="strut"> </span></p> +<p id="t188" class="pln"><span class="str"> Shear velocity within this cell in m/s</span><span class="strut"> </span></p> +<p id="t189" class="pln"><span class="strut"> </span></p> +<p id="t190" class="pln"><span class="str"> temperature: float</span><span class="strut"> </span></p> +<p id="t191" class="pln"><span class="str"> Temperature of water within this cell in deg C</span><span class="strut"> </span></p> +<p id="t192" class="pln"><span class="strut"> </span></p> +<p id="t193" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t194" class="pln"><span class="strut"> </span></p> +<p id="t195" class="stm run hide_run"> <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">length</span><span class="op">,</span> <span class="nam">depth</span><span class="op">,</span> <span class="nam">discharge</span><span class="op">,</span> <span class="nam">mean_xs_velocity</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t196" class="pln"> <span class="nam">mean_lat_velocity</span><span class="op">,</span> <span class="nam">mean_vert_velocity</span><span class="op">,</span> <span class="nam">shear_velocity</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t197" class="pln"> <span class="nam">temperature</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t198" class="pln"> <span class="str">"""Initialize self. See help(type(self)) for accurate signature."""</span><span class="strut"> </span></p> +<p id="t199" class="pln"><span class="strut"> </span></p> +<p id="t200" class="stm run hide_run"> <span class="nam">super</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">__init__</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t201" class="pln"><span class="strut"> </span></p> +<p id="t202" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_length</span> <span class="op">=</span> <span class="nam">length</span><span class="strut"> </span></p> +<p id="t203" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_depth</span> <span class="op">=</span> <span class="nam">depth</span><span class="strut"> </span></p> +<p id="t204" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_discharge</span> <span class="op">=</span> <span class="nam">discharge</span><span class="strut"> </span></p> +<p id="t205" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_mean_xs_velocity</span> <span class="op">=</span> <span class="nam">mean_xs_velocity</span><span class="strut"> </span></p> +<p id="t206" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_mean_lat_velocity</span> <span class="op">=</span> <span class="nam">mean_lat_velocity</span><span class="strut"> </span></p> +<p id="t207" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_mean_vert_velocity</span> <span class="op">=</span> <span class="nam">mean_vert_velocity</span><span class="strut"> </span></p> +<p id="t208" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_shear_velocity</span> <span class="op">=</span> <span class="nam">shear_velocity</span><span class="strut"> </span></p> +<p id="t209" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_temperature</span> <span class="op">=</span> <span class="nam">temperature</span><span class="strut"> </span></p> +<p id="t210" class="pln"><span class="strut"> </span></p> +<p id="t211" class="stm run hide_run"> <span class="nam">flow_direction</span> <span class="op">=</span> <span class="nam">discharge</span><span class="op">/</span><span class="nam">np</span><span class="op">.</span><span class="nam">abs</span><span class="op">(</span><span class="nam">discharge</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t212" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_mean_long_velocity</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t213" class="pln"> <span class="nam">flow_direction</span><span class="op">*</span><span class="nam">np</span><span class="op">.</span><span class="nam">sqrt</span><span class="op">(</span><span class="nam">mean_xs_velocity</span><span class="op">**</span><span class="num">2</span> <span class="op">-</span><span class="strut"> </span></p> +<p id="t214" class="pln"> <span class="nam">mean_lat_velocity</span><span class="op">**</span><span class="num">2</span> <span class="op">-</span><span class="strut"> </span></p> +<p id="t215" class="pln"> <span class="nam">mean_vert_velocity</span><span class="op">**</span><span class="num">2</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t216" class="pln"><span class="strut"> </span></p> +<p id="t217" class="pln"><span class="strut"> </span></p> +<p id="t218" class="stm run hide_run"><span class="key">class</span> <span class="nam">UnsteadyHydraulicCell</span><span class="op">(</span><span class="nam">HydraulicCell</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t219" class="pln"> <span class="str">"""</span><span class="strut"> </span></p> +<p id="t220" class="pln"><span class="strut"> </span></p> +<p id="t221" class="pln"><span class="str"> Parameters</span><span class="strut"> </span></p> +<p id="t222" class="pln"><span class="str"> ----------</span><span class="strut"> </span></p> +<p id="t223" class="pln"><span class="str"> length : float</span><span class="strut"> </span></p> +<p id="t224" class="pln"><span class="str"> Length of this cell in m</span><span class="strut"> </span></p> +<p id="t225" class="pln"><span class="str"> temperature : float</span><span class="strut"> </span></p> +<p id="t226" class="pln"><span class="str"> Temperature of water within this cell in deg C</span><span class="strut"> </span></p> +<p id="t227" class="pln"><span class="str"> property_time_series : pandas.DataFrame</span><span class="strut"> </span></p> +<p id="t228" class="pln"><span class="str"> Pandas DataFrame containing a time series with the following columns</span><span class="strut"> </span></p> +<p id="t229" class="pln"><span class="strut"> </span></p> +<p id="t230" class="pln"><span class="str"> Depth_m Depth of the cell in m</span><span class="strut"> </span></p> +<p id="t231" class="pln"><span class="str"> Q_cms Discharge of the cell in m**3/s</span><span class="strut"> </span></p> +<p id="t232" class="pln"><span class="str"> Vmag_mps Cross-section average velocity in m/s</span><span class="strut"> </span></p> +<p id="t233" class="pln"><span class="str"> Vvert_mps Vertical component of velocity in m/s</span><span class="strut"> </span></p> +<p id="t234" class="pln"><span class="str"> Vlat_mps Lateral component of velocity in m/s</span><span class="strut"> </span></p> +<p id="t235" class="pln"><span class="str"> Ustar_mps Shear velocity in m/s</span><span class="strut"> </span></p> +<p id="t236" class="pln"><span class="str"> Temp_C Temperature in deg C</span><span class="strut"> </span></p> +<p id="t237" class="pln"><span class="strut"> </span></p> +<p id="t238" class="pln"><span class="str"> start_time : numpy.datetime64</span><span class="strut"> </span></p> +<p id="t239" class="pln"><span class="str"> simulation_clock : fluegg.simclock.SimulationClock</span><span class="strut"> </span></p> +<p id="t240" class="pln"><span class="str"> simulation : fluegg.simulation.Simulation</span><span class="strut"> </span></p> +<p id="t241" class="pln"><span class="strut"> </span></p> +<p id="t242" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t243" class="pln"><span class="strut"> </span></p> +<p id="t244" class="stm run hide_run"> <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">length</span><span class="op">,</span> <span class="nam">property_time_series</span><span class="op">,</span> <span class="nam">start_time</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t245" class="pln"> <span class="nam">simulation_clock</span><span class="op">,</span> <span class="nam">simulation</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t246" class="pln"> <span class="str">"""Initialize self. See help(type(self)) for accurate signature."""</span><span class="strut"> </span></p> +<p id="t247" class="pln"><span class="strut"> </span></p> +<p id="t248" class="stm run hide_run"> <span class="nam">super</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">__init__</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t249" class="pln"><span class="strut"> </span></p> +<p id="t250" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_length</span> <span class="op">=</span> <span class="nam">length</span><span class="strut"> </span></p> +<p id="t251" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_depth</span> <span class="op">=</span> <span class="key">None</span><span class="strut"> </span></p> +<p id="t252" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_discharge</span> <span class="op">=</span> <span class="key">None</span><span class="strut"> </span></p> +<p id="t253" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_mean_xs_velocity</span> <span class="op">=</span> <span class="key">None</span><span class="strut"> </span></p> +<p id="t254" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_mean_lat_velocity</span> <span class="op">=</span> <span class="key">None</span><span class="strut"> </span></p> +<p id="t255" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_mean_long_velocity</span> <span class="op">=</span> <span class="key">None</span><span class="strut"> </span></p> +<p id="t256" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_mean_vert_velocity</span> <span class="op">=</span> <span class="key">None</span><span class="strut"> </span></p> +<p id="t257" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_shear_velocity</span> <span class="op">=</span> <span class="key">None</span><span class="strut"> </span></p> +<p id="t258" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_temperature</span> <span class="op">=</span> <span class="key">None</span><span class="strut"> </span></p> +<p id="t259" class="pln"><span class="strut"> </span></p> +<p id="t260" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_time_series</span> <span class="op">=</span> <span class="nam">property_time_series</span><span class="op">.</span><span class="nam">copy</span><span class="op">(</span><span class="nam">deep</span><span class="op">=</span><span class="key">True</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t261" class="pln"><span class="strut"> </span></p> +<p id="t262" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_start_time</span> <span class="op">=</span> <span class="nam">start_time</span><span class="strut"> </span></p> +<p id="t263" class="pln"><span class="strut"> </span></p> +<p id="t264" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_simclock</span> <span class="op">=</span> <span class="nam">simulation_clock</span><span class="strut"> </span></p> +<p id="t265" class="pln"><span class="strut"> </span></p> +<p id="t266" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_current_time</span> <span class="op">=</span> <span class="key">None</span><span class="strut"> </span></p> +<p id="t267" class="pln"><span class="strut"> </span></p> +<p id="t268" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_update_properties</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t269" class="stm run hide_run"> <span class="nam">simulation</span><span class="op">.</span><span class="nam">add_time_step_function_call</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_update_properties</span><span class="op">,</span> <span class="op">[</span><span class="op">]</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t270" class="pln"><span class="strut"> </span></p> +<p id="t271" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_current_simulation_time</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t272" class="pln"><span class="strut"> </span></p> +<p id="t273" class="stm run hide_run"> <span class="nam">simulation_time_delta</span> <span class="op">=</span> <span class="nam">timedelta</span><span class="op">(</span><span class="strut"> </span></p> +<p id="t274" class="pln"> <span class="nam">seconds</span><span class="op">=</span><span class="nam">self</span><span class="op">.</span><span class="nam">_simclock</span><span class="op">.</span><span class="nam">current_time</span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t275" class="stm run hide_run"> <span class="nam">current_simulation_time</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_start_time</span> <span class="op">+</span> <span class="nam">simulation_time_delta</span><span class="strut"> </span></p> +<p id="t276" class="pln"><span class="strut"> </span></p> +<p id="t277" class="stm run hide_run"> <span class="nam">times</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_time_series</span><span class="op">.</span><span class="nam">index</span><span class="strut"> </span></p> +<p id="t278" class="pln"><span class="strut"> </span></p> +<p id="t279" class="stm run hide_run"> <span class="nam">current_time_index</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">nonzero</span><span class="op">(</span><span class="strut"> </span></p> +<p id="t280" class="pln"> <span class="nam">times</span> <span class="op"><=</span> <span class="nam">current_simulation_time</span><span class="op">)</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="op">.</span><span class="nam">max</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t281" class="pln"><span class="strut"> </span></p> +<p id="t282" class="stm run hide_run"> <span class="key">return</span> <span class="nam">times</span><span class="op">[</span><span class="nam">current_time_index</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t283" class="pln"><span class="strut"> </span></p> +<p id="t284" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_update_properties</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t285" class="pln"><span class="strut"> </span></p> +<p id="t286" class="stm run hide_run"> <span class="nam">depth_key</span> <span class="op">=</span> <span class="str">'Depth_m'</span><span class="strut"> </span></p> +<p id="t287" class="stm run hide_run"> <span class="nam">discharge_key</span> <span class="op">=</span> <span class="str">'Q_cms'</span><span class="strut"> </span></p> +<p id="t288" class="stm run hide_run"> <span class="nam">vmag_key</span> <span class="op">=</span> <span class="str">'Vmag_mps'</span><span class="strut"> </span></p> +<p id="t289" class="stm run hide_run"> <span class="nam">vvert_key</span> <span class="op">=</span> <span class="str">'Vvert_mps'</span><span class="strut"> </span></p> +<p id="t290" class="stm run hide_run"> <span class="nam">vlat_key</span> <span class="op">=</span> <span class="str">'Vlat_mps'</span><span class="strut"> </span></p> +<p id="t291" class="stm run hide_run"> <span class="nam">shear_velocity_key</span> <span class="op">=</span> <span class="str">'Ustar_mps'</span><span class="strut"> </span></p> +<p id="t292" class="stm run hide_run"> <span class="nam">temperature_key</span> <span class="op">=</span> <span class="str">'Temp_C'</span><span class="strut"> </span></p> +<p id="t293" class="pln"><span class="strut"> </span></p> +<p id="t294" class="stm run hide_run"> <span class="nam">last_current_time</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_current_time</span><span class="strut"> </span></p> +<p id="t295" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_current_time</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_current_simulation_time</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t296" class="pln"><span class="strut"> </span></p> +<p id="t297" class="stm run hide_run"> <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_current_time</span> <span class="op">!=</span> <span class="nam">last_current_time</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t298" class="pln"><span class="strut"> </span></p> +<p id="t299" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_depth</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_time_series</span><span class="op">.</span><span class="nam">loc</span><span class="op">[</span><span class="nam">self</span><span class="op">.</span><span class="nam">_current_time</span><span class="op">,</span> <span class="nam">depth_key</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t300" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_discharge</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t301" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">_time_series</span><span class="op">.</span><span class="nam">loc</span><span class="op">[</span><span class="nam">self</span><span class="op">.</span><span class="nam">_current_time</span><span class="op">,</span> <span class="nam">discharge_key</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t302" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_mean_xs_velocity</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t303" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">_time_series</span><span class="op">.</span><span class="nam">loc</span><span class="op">[</span><span class="nam">self</span><span class="op">.</span><span class="nam">_current_time</span><span class="op">,</span> <span class="nam">vmag_key</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t304" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_mean_lat_velocity</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t305" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">_time_series</span><span class="op">.</span><span class="nam">loc</span><span class="op">[</span><span class="nam">self</span><span class="op">.</span><span class="nam">_current_time</span><span class="op">,</span> <span class="nam">vlat_key</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t306" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_mean_vert_velocity</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t307" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">_time_series</span><span class="op">.</span><span class="nam">loc</span><span class="op">[</span><span class="nam">self</span><span class="op">.</span><span class="nam">_current_time</span><span class="op">,</span> <span class="nam">vvert_key</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t308" class="stm run hide_run"> <span class="nam">flow_direction</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_discharge</span> <span class="op">/</span> <span class="nam">np</span><span class="op">.</span><span class="nam">abs</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_discharge</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t309" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_mean_long_velocity</span> <span class="op">=</span> <span class="nam">flow_direction</span> <span class="op">*</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t310" class="pln"> <span class="nam">np</span><span class="op">.</span><span class="nam">sqrt</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_mean_xs_velocity</span> <span class="op">**</span> <span class="num">2</span> <span class="op">-</span><span class="strut"> </span></p> +<p id="t311" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">_mean_lat_velocity</span> <span class="op">**</span> <span class="num">2</span> <span class="op">-</span><span class="strut"> </span></p> +<p id="t312" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">_mean_vert_velocity</span> <span class="op">**</span> <span class="num">2</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t313" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_shear_velocity</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_time_series</span><span class="op">.</span><span class="nam">loc</span><span class="op">[</span><span class="nam">self</span><span class="op">.</span><span class="nam">_current_time</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t314" class="pln"> <span class="nam">shear_velocity_key</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t315" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_temperature</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_time_series</span><span class="op">.</span><span class="nam">loc</span><span class="op">[</span><span class="nam">self</span><span class="op">.</span><span class="nam">_current_time</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t316" class="pln"> <span class="nam">temperature_key</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t317" class="pln"><span class="strut"> </span></p> +<p id="t318" class="stm run hide_run"> <span class="key">def</span> <span class="nam">to_data_frame</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t319" class="pln"> <span class="str">"""Time series information from this cell in a Pandas DataFrame.</span><span class="strut"> </span></p> +<p id="t320" class="pln"><span class="strut"> </span></p> +<p id="t321" class="pln"><span class="str"> Returns</span><span class="strut"> </span></p> +<p id="t322" class="pln"><span class="str"> -------</span><span class="strut"> </span></p> +<p id="t323" class="pln"><span class="str"> pandas.DataFrame</span><span class="strut"> </span></p> +<p id="t324" class="pln"><span class="str"> DataFrame containing time series information from this cell.</span><span class="strut"> </span></p> +<p id="t325" class="pln"><span class="strut"> </span></p> +<p id="t326" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t327" class="pln"><span class="strut"> </span></p> +<p id="t328" class="stm mis"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_time_series</span><span class="op">.</span><span class="nam">copy</span><span class="op">(</span><span class="nam">deep</span><span class="op">=</span><span class="key">True</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t329" class="pln"><span class="strut"> </span></p> +<p id="t330" class="pln"><span class="strut"> </span></p> +<p id="t331" class="stm run hide_run"><span class="key">class</span> <span class="nam">SeriesOfHydraulicCells</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t332" class="pln"> <span class="str">"""Data type for hydraulic geometry represented by a series of hydraulic</span><span class="strut"> </span></p> +<p id="t333" class="pln"><span class="str"> cells.</span><span class="strut"> </span></p> +<p id="t334" class="pln"><span class="strut"> </span></p> +<p id="t335" class="pln"><span class="str"> Instantiate from a CSV file with from_csv.</span><span class="strut"> </span></p> +<p id="t336" class="pln"><span class="strut"> </span></p> +<p id="t337" class="pln"><span class="str"> Parameters</span><span class="strut"> </span></p> +<p id="t338" class="pln"><span class="str"> ----------</span><span class="strut"> </span></p> +<p id="t339" class="pln"><span class="str"> list_of_cells : list</span><span class="strut"> </span></p> +<p id="t340" class="pln"><span class="str"> List containing HydraulicCell elements.</span><span class="strut"> </span></p> +<p id="t341" class="pln"><span class="strut"> </span></p> +<p id="t342" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t343" class="pln"><span class="strut"> </span></p> +<p id="t344" class="stm run hide_run"> <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">list_of_cells</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t345" class="pln"> <span class="str">"""Initialize self. See help(type(self)) for accurate signature."""</span><span class="strut"> </span></p> +<p id="t346" class="pln"><span class="strut"> </span></p> +<p id="t347" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_cells</span> <span class="op">=</span> <span class="nam">list_of_cells</span><span class="strut"> </span></p> +<p id="t348" class="pln"><span class="strut"> </span></p> +<p id="t349" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_cell_edges</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_calc_cell_edges</span><span class="op">(</span><span class="nam">list_of_cells</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t350" class="pln"><span class="strut"> </span></p> +<p id="t351" class="stm run hide_run"> <span class="op">@</span><span class="nam">staticmethod</span><span class="strut"> </span></p> +<p id="t352" class="pln"> <span class="key">def</span> <span class="nam">_calc_cell_edges</span><span class="op">(</span><span class="nam">list_of_cells</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t353" class="pln"><span class="strut"> </span></p> +<p id="t354" class="stm run hide_run"> <span class="nam">cumulative_distance</span> <span class="op">=</span> <span class="num">0</span><span class="strut"> </span></p> +<p id="t355" class="stm run hide_run"> <span class="nam">cell_edges</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">tile</span><span class="op">(</span><span class="nam">np</span><span class="op">.</span><span class="nam">nan</span><span class="op">,</span> <span class="nam">len</span><span class="op">(</span><span class="nam">list_of_cells</span><span class="op">)</span><span class="op">+</span><span class="num">1</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t356" class="pln"><span class="strut"> </span></p> +<p id="t357" class="stm run hide_run"> <span class="nam">cell_edges</span><span class="op">[</span><span class="num">0</span><span class="op">]</span> <span class="op">=</span> <span class="nam">cumulative_distance</span><span class="strut"> </span></p> +<p id="t358" class="pln"><span class="strut"> </span></p> +<p id="t359" class="stm run hide_run"> <span class="key">for</span> <span class="nam">i</span><span class="op">,</span> <span class="nam">cell</span> <span class="key">in</span> <span class="nam">enumerate</span><span class="op">(</span><span class="nam">list_of_cells</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t360" class="stm run hide_run"> <span class="nam">cumulative_distance</span> <span class="op">+=</span> <span class="nam">cell</span><span class="op">.</span><span class="nam">length</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t361" class="stm run hide_run"> <span class="nam">cell_edges</span><span class="op">[</span><span class="nam">i</span><span class="op">+</span><span class="num">1</span><span class="op">]</span> <span class="op">=</span> <span class="nam">cumulative_distance</span><span class="strut"> </span></p> +<p id="t362" class="pln"><span class="strut"> </span></p> +<p id="t363" class="stm run hide_run"> <span class="key">return</span> <span class="nam">cell_edges</span><span class="strut"> </span></p> +<p id="t364" class="pln"><span class="strut"> </span></p> +<p id="t365" class="stm run hide_run"> <span class="op">@</span><span class="nam">abstractmethod</span><span class="strut"> </span></p> +<p id="t366" class="pln"> <span class="key">def</span> <span class="nam">_calc_log_law_velocity</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">vertical_location</span><span class="op">,</span> <span class="nam">shear_velocity</span><span class="op">,</span> <span class="nam">depth</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t367" class="pln"> <span class="nam">mean_xs_velocity</span><span class="op">,</span> <span class="nam">viscosity</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t368" class="stm mis"> <span class="key">raise</span> <span class="nam">NotImplementedError</span><span class="strut"> </span></p> +<p id="t369" class="pln"><span class="strut"> </span></p> +<p id="t370" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_calc_longitudinal_velocity</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">vertical_location</span><span class="op">,</span> <span class="nam">shear_velocity</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t371" class="pln"> <span class="nam">depth</span><span class="op">,</span> <span class="nam">mean_xs_velocity</span><span class="op">,</span> <span class="nam">viscosity</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t372" class="pln"> <span class="nam">lateral_location</span><span class="op">,</span> <span class="nam">width</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t373" class="pln"><span class="strut"> </span></p> +<p id="t374" class="stm run hide_run"> <span class="nam">distance_above_bed</span> <span class="op">=</span> <span class="nam">vertical_location</span> <span class="op">+</span> <span class="nam">depth</span><span class="strut"> </span></p> +<p id="t375" class="pln"><span class="strut"> </span></p> +<p id="t376" class="stm run hide_run"> <span class="nam">minimum_distance_above_bed</span> <span class="op">=</span> <span class="num">0.00001</span><span class="strut"> </span></p> +<p id="t377" class="stm run hide_run"> <span class="nam">distance_above_bed</span><span class="op">[</span><span class="nam">distance_above_bed</span> <span class="op"><</span> <span class="nam">minimum_distance_above_bed</span><span class="op">]</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t378" class="pln"> <span class="nam">minimum_distance_above_bed</span><span class="strut"> </span></p> +<p id="t379" class="pln"><span class="strut"> </span></p> +<p id="t380" class="stm run hide_run"> <span class="nam">log_law_velocity</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t381" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">_calc_log_law_velocity</span><span class="op">(</span><span class="strut"> </span></p> +<p id="t382" class="pln"> <span class="nam">distance_above_bed</span><span class="op">,</span> <span class="nam">shear_velocity</span><span class="op">,</span> <span class="nam">depth</span><span class="op">,</span> <span class="nam">mean_xs_velocity</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t383" class="pln"> <span class="nam">viscosity</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t384" class="pln"><span class="strut"> </span></p> +<p id="t385" class="pln"> <span class="com"># enforce the no-slip condition</span><span class="strut"> </span></p> +<p id="t386" class="stm run hide_run"> <span class="nam">log_law_velocity</span><span class="op">[</span><span class="nam">log_law_velocity</span> <span class="op"><</span> <span class="num">0</span><span class="op">]</span> <span class="op">=</span> <span class="num">0</span><span class="strut"> </span></p> +<p id="t387" class="pln"><span class="strut"> </span></p> +<p id="t388" class="stm run hide_run"> <span class="nam">a</span> <span class="op">=</span> <span class="num">2.51</span><span class="strut"> </span></p> +<p id="t389" class="stm run hide_run"> <span class="nam">b</span> <span class="op">=</span> <span class="num">2.47</span><span class="strut"> </span></p> +<p id="t390" class="pln"><span class="strut"> </span></p> +<p id="t391" class="stm run hide_run"> <span class="nam">streamwise_velocity</span> <span class="op">=</span> <span class="nam">log_law_velocity</span> <span class="op">*</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t392" class="pln"> <span class="nam">beta</span><span class="op">.</span><span class="nam">pdf</span><span class="op">(</span><span class="nam">lateral_location</span><span class="op">/</span><span class="nam">width</span><span class="op">,</span> <span class="nam">a</span><span class="op">,</span> <span class="nam">b</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t393" class="pln"><span class="strut"> </span></p> +<p id="t394" class="stm run hide_run"> <span class="key">return</span> <span class="nam">streamwise_velocity</span><span class="strut"> </span></p> +<p id="t395" class="pln"><span class="strut"> </span></p> +<p id="t396" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_cell_number_by_position</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">location</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t397" class="pln"><span class="strut"> </span></p> +<p id="t398" class="pln"> <span class="com"># Digitize egg positions</span><span class="strut"> </span></p> +<p id="t399" class="stm run hide_run"> <span class="nam">position_cell_number</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">digitize</span><span class="op">(</span><span class="nam">location</span><span class="op">,</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_cell_edges</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t400" class="pln"><span class="strut"> </span></p> +<p id="t401" class="pln"> <span class="com"># Eggs have travelled before the first hydraulic cell</span><span class="strut"> </span></p> +<p id="t402" class="pln"> <span class="com"># (reverse simulation)</span><span class="strut"> </span></p> +<p id="t403" class="stm run hide_run"> <span class="nam">position_cell_number</span><span class="op">[</span><span class="nam">location</span> <span class="op"><</span> <span class="num">0</span><span class="op">]</span> <span class="op">=</span> <span class="num">1</span><span class="strut"> </span></p> +<p id="t404" class="pln"><span class="strut"> </span></p> +<p id="t405" class="stm run hide_run"> <span class="key">return</span> <span class="nam">position_cell_number</span><span class="strut"> </span></p> +<p id="t406" class="pln"><span class="strut"> </span></p> +<p id="t407" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_cell_property_by_location</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">property_method</span><span class="op">,</span> <span class="nam">location</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t408" class="pln"><span class="strut"> </span></p> +<p id="t409" class="pln"> <span class="com"># make the extend the cell depth array by one cell to virtually extend</span><span class="strut"> </span></p> +<p id="t410" class="pln"> <span class="com"># the reach with the properties from the last cell</span><span class="strut"> </span></p> +<p id="t411" class="stm run hide_run"> <span class="nam">cell_property</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">tile</span><span class="op">(</span><span class="nam">np</span><span class="op">.</span><span class="nam">nan</span><span class="op">,</span> <span class="nam">len</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_cells</span><span class="op">)</span><span class="op">+</span><span class="num">1</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t412" class="stm run hide_run"> <span class="key">for</span> <span class="nam">i</span><span class="op">,</span> <span class="nam">cell</span> <span class="key">in</span> <span class="nam">enumerate</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_cells</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t413" class="stm run hide_run"> <span class="nam">cell_property</span><span class="op">[</span><span class="nam">i</span><span class="op">]</span> <span class="op">=</span> <span class="nam">getattr</span><span class="op">(</span><span class="nam">cell</span><span class="op">,</span> <span class="nam">property_method</span><span class="op">)</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t414" class="stm run hide_run"> <span class="nam">cell_property</span><span class="op">[</span><span class="op">-</span><span class="num">1</span><span class="op">]</span> <span class="op">=</span> <span class="nam">getattr</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_cells</span><span class="op">[</span><span class="op">-</span><span class="num">1</span><span class="op">]</span><span class="op">,</span> <span class="nam">property_method</span><span class="op">)</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t415" class="pln"><span class="strut"> </span></p> +<p id="t416" class="stm run hide_run"> <span class="nam">location_cell_number</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_cell_number_by_position</span><span class="op">(</span><span class="nam">location</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t417" class="stm run hide_run"> <span class="nam">location_property</span> <span class="op">=</span> <span class="nam">cell_property</span><span class="op">[</span><span class="nam">location_cell_number</span> <span class="op">-</span> <span class="num">1</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t418" class="pln"><span class="strut"> </span></p> +<p id="t419" class="stm run hide_run"> <span class="key">return</span> <span class="nam">location_property</span><span class="strut"> </span></p> +<p id="t420" class="pln"><span class="strut"> </span></p> +<p id="t421" class="stm run hide_run"> <span class="op">@</span><span class="nam">staticmethod</span><span class="strut"> </span></p> +<p id="t422" class="pln"> <span class="key">def</span> <span class="nam">_list_of_steady_cells</span><span class="op">(</span><span class="nam">data_frame</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t423" class="pln"><span class="strut"> </span></p> +<p id="t424" class="stm run hide_run"> <span class="nam">list_of_cells</span> <span class="op">=</span> <span class="op">[</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t425" class="stm run hide_run"> <span class="nam">cumulative_distance</span> <span class="op">=</span> <span class="num">0</span><span class="strut"> </span></p> +<p id="t426" class="pln"><span class="strut"> </span></p> +<p id="t427" class="stm run hide_run"> <span class="key">for</span> <span class="nam">_</span><span class="op">,</span> <span class="nam">row</span> <span class="key">in</span> <span class="nam">data_frame</span><span class="op">.</span><span class="nam">iterrows</span><span class="op">(</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t428" class="pln"> <span class="com"># convert kilometers to meters</span><span class="strut"> </span></p> +<p id="t429" class="stm run hide_run"> <span class="nam">cell_length</span> <span class="op">=</span> <span class="num">1000</span><span class="op">*</span><span class="op">(</span><span class="nam">row</span><span class="op">[</span><span class="str">'CumlDistance_km'</span><span class="op">]</span> <span class="op">-</span> <span class="nam">cumulative_distance</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t430" class="stm run hide_run"> <span class="nam">cumulative_distance</span> <span class="op">=</span> <span class="nam">row</span><span class="op">[</span><span class="str">'CumlDistance_km'</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t431" class="pln"><span class="strut"> </span></p> +<p id="t432" class="stm run hide_run"> <span class="nam">cell_depth</span> <span class="op">=</span> <span class="nam">row</span><span class="op">[</span><span class="str">'Depth_m'</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t433" class="stm run hide_run"> <span class="nam">cell_discharge</span> <span class="op">=</span> <span class="nam">row</span><span class="op">[</span><span class="str">'Q_cms'</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t434" class="stm run hide_run"> <span class="nam">cell_longitudinal_velocity</span> <span class="op">=</span> <span class="nam">row</span><span class="op">[</span><span class="str">'Vmag_mps'</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t435" class="stm run hide_run"> <span class="nam">cell_lateral_velocity</span> <span class="op">=</span> <span class="nam">row</span><span class="op">[</span><span class="str">'Vvert_mps'</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t436" class="stm run hide_run"> <span class="nam">cell_vertical_velocity</span> <span class="op">=</span> <span class="nam">row</span><span class="op">[</span><span class="str">'Vlat_mps'</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t437" class="stm run hide_run"> <span class="nam">cell_shear_velocity</span> <span class="op">=</span> <span class="nam">row</span><span class="op">[</span><span class="str">'Ustar_mps'</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t438" class="stm run hide_run"> <span class="nam">cell_temperature</span> <span class="op">=</span> <span class="nam">row</span><span class="op">[</span><span class="str">'Temp_C'</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t439" class="pln"><span class="strut"> </span></p> +<p id="t440" class="stm run hide_run"> <span class="nam">hydraulic_cell</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t441" class="pln"> <span class="nam">SteadyStateHydraulicCell</span><span class="op">(</span><span class="nam">cell_length</span><span class="op">,</span> <span class="nam">cell_depth</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t442" class="pln"> <span class="nam">cell_discharge</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t443" class="pln"> <span class="nam">cell_longitudinal_velocity</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t444" class="pln"> <span class="nam">cell_lateral_velocity</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t445" class="pln"> <span class="nam">cell_vertical_velocity</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t446" class="pln"> <span class="nam">cell_shear_velocity</span><span class="op">,</span> <span class="nam">cell_temperature</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t447" class="pln"><span class="strut"> </span></p> +<p id="t448" class="stm run hide_run"> <span class="nam">list_of_cells</span><span class="op">.</span><span class="nam">append</span><span class="op">(</span><span class="nam">hydraulic_cell</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t449" class="pln"><span class="strut"> </span></p> +<p id="t450" class="stm run hide_run"> <span class="key">return</span> <span class="nam">list_of_cells</span><span class="strut"> </span></p> +<p id="t451" class="pln"><span class="strut"> </span></p> +<p id="t452" class="stm run hide_run"> <span class="op">@</span><span class="nam">staticmethod</span><span class="strut"> </span></p> +<p id="t453" class="pln"> <span class="key">def</span> <span class="nam">_list_of_unsteady_cells</span><span class="op">(</span><span class="nam">data_frame</span><span class="op">,</span> <span class="op">**</span><span class="nam">kwargs</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t454" class="pln"> <span class="str">"""Returns a list of UnsteadyHydraulicCell instances."""</span><span class="strut"> </span></p> +<p id="t455" class="pln"><span class="strut"> </span></p> +<p id="t456" class="pln"> <span class="com"># unpack the keyword arguments</span><span class="strut"> </span></p> +<p id="t457" class="stm run hide_run"> <span class="nam">start_time</span> <span class="op">=</span> <span class="nam">kwargs</span><span class="op">[</span><span class="str">'start_time'</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t458" class="stm run hide_run"> <span class="nam">simulation_clock</span> <span class="op">=</span> <span class="nam">kwargs</span><span class="op">[</span><span class="str">'simulation_clock'</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t459" class="stm run hide_run"> <span class="nam">simulation</span> <span class="op">=</span> <span class="nam">kwargs</span><span class="op">[</span><span class="str">'simulation'</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t460" class="pln"><span class="strut"> </span></p> +<p id="t461" class="pln"> <span class="com"># get the cell cumulative distance</span><span class="strut"> </span></p> +<p id="t462" class="stm run hide_run"> <span class="nam">grouped_by_time</span> <span class="op">=</span> <span class="nam">data_frame</span><span class="op">.</span><span class="nam">groupby</span><span class="op">(</span><span class="nam">axis</span><span class="op">=</span><span class="num">0</span><span class="op">,</span> <span class="nam">level</span><span class="op">=</span><span class="num">0</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t463" class="stm run hide_run"> <span class="nam">initial_time_step</span> <span class="op">=</span> <span class="nam">list</span><span class="op">(</span><span class="nam">grouped_by_time</span><span class="op">.</span><span class="nam">groups</span><span class="op">.</span><span class="nam">keys</span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t464" class="stm run hide_run"> <span class="nam">initial_group</span> <span class="op">=</span> <span class="nam">grouped_by_time</span><span class="op">.</span><span class="nam">get_group</span><span class="op">(</span><span class="nam">initial_time_step</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t465" class="stm run hide_run"> <span class="nam">initial_group</span><span class="op">.</span><span class="nam">index</span> <span class="op">=</span> <span class="nam">initial_group</span><span class="op">.</span><span class="nam">index</span><span class="op">.</span><span class="nam">droplevel</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t466" class="stm run hide_run"> <span class="nam">cumulative_distance_series</span> <span class="op">=</span> <span class="nam">initial_group</span><span class="op">[</span><span class="str">'CumlDistance_km'</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t467" class="pln"><span class="strut"> </span></p> +<p id="t468" class="stm run hide_run"> <span class="nam">cumulative_distance</span> <span class="op">=</span> <span class="num">0</span><span class="strut"> </span></p> +<p id="t469" class="pln"><span class="strut"> </span></p> +<p id="t470" class="stm run hide_run"> <span class="nam">list_of_cells</span> <span class="op">=</span> <span class="op">[</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t471" class="pln"><span class="strut"> </span></p> +<p id="t472" class="stm run hide_run"> <span class="nam">grouped_by_cell</span> <span class="op">=</span> <span class="nam">data_frame</span><span class="op">.</span><span class="nam">groupby</span><span class="op">(</span><span class="nam">axis</span><span class="op">=</span><span class="num">0</span><span class="op">,</span> <span class="nam">level</span><span class="op">=</span><span class="num">1</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t473" class="stm run hide_run"> <span class="key">for</span> <span class="nam">cell_number</span> <span class="key">in</span> <span class="nam">grouped_by_cell</span><span class="op">.</span><span class="nam">groups</span><span class="op">.</span><span class="nam">keys</span><span class="op">(</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t474" class="pln"><span class="strut"> </span></p> +<p id="t475" class="pln"> <span class="com"># get the cell length and add it to the cumulative distance</span><span class="strut"> </span></p> +<p id="t476" class="stm run hide_run"> <span class="nam">cell_length</span> <span class="op">=</span> <span class="num">1000</span> <span class="op">*</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t477" class="pln"> <span class="op">(</span><span class="nam">cumulative_distance_series</span><span class="op">[</span><span class="nam">cell_number</span><span class="op">]</span> <span class="op">-</span> <span class="nam">cumulative_distance</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t478" class="stm run hide_run"> <span class="nam">cumulative_distance</span> <span class="op">=</span> <span class="nam">cumulative_distance_series</span><span class="op">[</span><span class="nam">cell_number</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t479" class="pln"><span class="strut"> </span></p> +<p id="t480" class="stm run hide_run"> <span class="nam">cell_time_series</span> <span class="op">=</span> <span class="nam">grouped_by_cell</span><span class="op">.</span><span class="nam">get_group</span><span class="op">(</span><span class="nam">cell_number</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t481" class="stm run hide_run"> <span class="nam">cell_time_series</span><span class="op">.</span><span class="nam">index</span> <span class="op">=</span> <span class="nam">cell_time_series</span><span class="op">.</span><span class="nam">index</span><span class="op">.</span><span class="nam">droplevel</span><span class="op">(</span><span class="num">1</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t482" class="stm run hide_run"> <span class="nam">hydraulic_cell</span> <span class="op">=</span> <span class="nam">UnsteadyHydraulicCell</span><span class="op">(</span><span class="nam">cell_length</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t483" class="pln"> <span class="nam">cell_time_series</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t484" class="pln"> <span class="nam">start_time</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t485" class="pln"> <span class="nam">simulation_clock</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t486" class="pln"> <span class="nam">simulation</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t487" class="stm run hide_run"> <span class="nam">list_of_cells</span><span class="op">.</span><span class="nam">append</span><span class="op">(</span><span class="nam">hydraulic_cell</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t488" class="pln"><span class="strut"> </span></p> +<p id="t489" class="stm run hide_run"> <span class="key">return</span> <span class="nam">list_of_cells</span><span class="strut"> </span></p> +<p id="t490" class="pln"><span class="strut"> </span></p> +<p id="t491" class="stm run hide_run"> <span class="op">@</span><span class="nam">classmethod</span><span class="strut"> </span></p> +<p id="t492" class="pln"> <span class="key">def</span> <span class="nam">from_data_frame</span><span class="op">(</span><span class="nam">cls</span><span class="op">,</span> <span class="nam">data_frame</span><span class="op">,</span> <span class="op">**</span><span class="nam">kwargs</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t493" class="pln"> <span class="str">"""Creates an instance of this class from a Pandas DataFrame.</span><span class="strut"> </span></p> +<p id="t494" class="pln"><span class="strut"> </span></p> +<p id="t495" class="pln"><span class="str"> This method handles the creation of a steady or unsteady series of</span><span class="strut"> </span></p> +<p id="t496" class="pln"><span class="str"> cells, depending on the DataFrame passed. For an unsteady model, level</span><span class="strut"> </span></p> +<p id="t497" class="pln"><span class="str"> 0 of the MultiIndex is the time, and level 1 is the cell number.</span><span class="strut"> </span></p> +<p id="t498" class="pln"><span class="strut"> </span></p> +<p id="t499" class="pln"><span class="str"> Parameters</span><span class="strut"> </span></p> +<p id="t500" class="pln"><span class="str"> ----------</span><span class="strut"> </span></p> +<p id="t501" class="pln"><span class="str"> data_frame : pandas.DataFrame</span><span class="strut"> </span></p> +<p id="t502" class="pln"><span class="str"> Pandas DataFrame containing hydraulic information</span><span class="strut"> </span></p> +<p id="t503" class="pln"><span class="str"> **kwargs</span><span class="strut"> </span></p> +<p id="t504" class="pln"><span class="str"> These keyword arguments are required when initializing a series of</span><span class="strut"> </span></p> +<p id="t505" class="pln"><span class="str"> unsteady cells.</span><span class="strut"> </span></p> +<p id="t506" class="pln"><span class="str"> start_time : numpy.datetime64</span><span class="strut"> </span></p> +<p id="t507" class="pln"><span class="str"> Simulation start time.</span><span class="strut"> </span></p> +<p id="t508" class="pln"><span class="str"> simulation_clock : fluegg.simclock.SimulationClock</span><span class="strut"> </span></p> +<p id="t509" class="pln"><span class="str"> simulation : fluegg.simulation.Simulation</span><span class="strut"> </span></p> +<p id="t510" class="pln"><span class="strut"> </span></p> +<p id="t511" class="pln"><span class="strut"> </span></p> +<p id="t512" class="pln"><span class="str"> Returns</span><span class="strut"> </span></p> +<p id="t513" class="pln"><span class="str"> -------</span><span class="strut"> </span></p> +<p id="t514" class="pln"><span class="str"> SeriesOfHydraulicCells</span><span class="strut"> </span></p> +<p id="t515" class="pln"><span class="strut"> </span></p> +<p id="t516" class="pln"><span class="str"> See Also</span><span class="strut"> </span></p> +<p id="t517" class="pln"><span class="str"> --------</span><span class="strut"> </span></p> +<p id="t518" class="pln"><span class="str"> SteadyStateHydraulicCell</span><span class="strut"> </span></p> +<p id="t519" class="pln"><span class="str"> UnsteadyHydraulicCell</span><span class="strut"> </span></p> +<p id="t520" class="pln"><span class="strut"> </span></p> +<p id="t521" class="pln"><span class="str"> Notes</span><span class="strut"> </span></p> +<p id="t522" class="pln"><span class="str"> -----</span><span class="strut"> </span></p> +<p id="t523" class="pln"><span class="str"> The method initializes steady or unsteady cells based on the number of</span><span class="strut"> </span></p> +<p id="t524" class="pln"><span class="str"> levels in the index of `data_frame`. Steady cells are initialized if</span><span class="strut"> </span></p> +<p id="t525" class="pln"><span class="str"> there is one level, and unsteady cells are initialized if there are</span><span class="strut"> </span></p> +<p id="t526" class="pln"><span class="str"> two.</span><span class="strut"> </span></p> +<p id="t527" class="pln"><span class="strut"> </span></p> +<p id="t528" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t529" class="pln"><span class="strut"> </span></p> +<p id="t530" class="stm run hide_run"> <span class="key">if</span> <span class="nam">data_frame</span><span class="op">.</span><span class="nam">index</span><span class="op">.</span><span class="nam">nlevels</span> <span class="op">==</span> <span class="num">1</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t531" class="stm run hide_run"> <span class="nam">list_of_cells</span> <span class="op">=</span> <span class="nam">cls</span><span class="op">.</span><span class="nam">_list_of_steady_cells</span><span class="op">(</span><span class="nam">data_frame</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t532" class="stm run hide_run"> <span class="key">elif</span> <span class="nam">data_frame</span><span class="op">.</span><span class="nam">index</span><span class="op">.</span><span class="nam">nlevels</span> <span class="op">==</span> <span class="num">2</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t533" class="stm run hide_run"> <span class="nam">list_of_cells</span> <span class="op">=</span> <span class="nam">cls</span><span class="op">.</span><span class="nam">_list_of_unsteady_cells</span><span class="op">(</span><span class="nam">data_frame</span><span class="op">,</span> <span class="op">**</span><span class="nam">kwargs</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t534" class="pln"> <span class="key">else</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t535" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="str">"Unrecognized DataFrame format"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t536" class="pln"><span class="strut"> </span></p> +<p id="t537" class="stm run hide_run"> <span class="key">return</span> <span class="nam">cls</span><span class="op">(</span><span class="nam">list_of_cells</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t538" class="pln"><span class="strut"> </span></p> +<p id="t539" class="stm run hide_run"> <span class="key">def</span> <span class="nam">hydraulic_results</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">position</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t540" class="pln"> <span class="str">"""Returns the results of a hydraulic simulation at the given positions</span><span class="strut"> </span></p> +<p id="t541" class="pln"><span class="str"> in space.</span><span class="strut"> </span></p> +<p id="t542" class="pln"><span class="strut"> </span></p> +<p id="t543" class="pln"><span class="str"> Position is an n by 3 numpy array, where n is the number of positions</span><span class="strut"> </span></p> +<p id="t544" class="pln"><span class="str"> requested (along axis=0).</span><span class="strut"> </span></p> +<p id="t545" class="pln"><span class="strut"> </span></p> +<p id="t546" class="pln"><span class="str"> The indices along axis=1 are:</span><span class="strut"> </span></p> +<p id="t547" class="pln"><span class="str"> 0 - The position in the longitudinal, or x, direction in m. The</span><span class="strut"> </span></p> +<p id="t548" class="pln"><span class="str"> positive direction is downstream.</span><span class="strut"> </span></p> +<p id="t549" class="pln"><span class="str"> 1 - The position in the lateral, or y, direction in m. The positive</span><span class="strut"> </span></p> +<p id="t550" class="pln"><span class="str"> direction is from the right bank.</span><span class="strut"> </span></p> +<p id="t551" class="pln"><span class="str"> 2 - The position in the vertical, or z, direction in m. The</span><span class="strut"> </span></p> +<p id="t552" class="pln"><span class="str"> positive direction is away from the bed.</span><span class="strut"> </span></p> +<p id="t553" class="pln"><span class="strut"> </span></p> +<p id="t554" class="pln"><span class="str"> In this coordinate system, the datum (0, 0, 0) is the point at the</span><span class="strut"> </span></p> +<p id="t555" class="pln"><span class="str"> upstream, right bank, water surface of the first cell.</span><span class="strut"> </span></p> +<p id="t556" class="pln"><span class="strut"> </span></p> +<p id="t557" class="pln"><span class="str"> position[:, 0] is the position in the longitudinal, or x, direction,</span><span class="strut"> </span></p> +<p id="t558" class="pln"><span class="str"> position[:, 1] is the position in the lateral, or y, direction, and</span><span class="strut"> </span></p> +<p id="t559" class="pln"><span class="str"> position[:, 2] is the position in the vertical, or z, direction.</span><span class="strut"> </span></p> +<p id="t560" class="pln"><span class="strut"> </span></p> +<p id="t561" class="pln"><span class="str"> :param position: Array containing position of results</span><span class="strut"> </span></p> +<p id="t562" class="pln"><span class="str"> :return: HydraulicResults</span><span class="strut"> </span></p> +<p id="t563" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t564" class="pln"><span class="strut"> </span></p> +<p id="t565" class="stm run hide_run"> <span class="nam">longitudinal_location</span> <span class="op">=</span> <span class="nam">position</span><span class="op">[</span><span class="op">:</span><span class="op">,</span> <span class="num">0</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t566" class="pln"><span class="strut"> </span></p> +<p id="t567" class="stm run hide_run"> <span class="nam">depth</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_cell_property_by_location</span><span class="op">(</span><span class="str">'depth'</span><span class="op">,</span> <span class="nam">longitudinal_location</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t568" class="stm run hide_run"> <span class="nam">discharge</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_cell_property_by_location</span><span class="op">(</span><span class="strut"> </span></p> +<p id="t569" class="pln"> <span class="str">'discharge'</span><span class="op">,</span> <span class="nam">longitudinal_location</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t570" class="stm run hide_run"> <span class="nam">mean_xs_velocity</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_cell_property_by_location</span><span class="op">(</span><span class="strut"> </span></p> +<p id="t571" class="pln"> <span class="str">'mean_xs_velocity'</span><span class="op">,</span> <span class="nam">longitudinal_location</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t572" class="stm run hide_run"> <span class="nam">mean_lat_velocity</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_cell_property_by_location</span><span class="op">(</span><span class="strut"> </span></p> +<p id="t573" class="pln"> <span class="str">'mean_lat_velocity'</span><span class="op">,</span> <span class="nam">longitudinal_location</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t574" class="stm run hide_run"> <span class="nam">mean_long_velocity</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_cell_property_by_location</span><span class="op">(</span><span class="strut"> </span></p> +<p id="t575" class="pln"> <span class="str">'mean_long_velocity'</span><span class="op">,</span> <span class="nam">longitudinal_location</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t576" class="stm run hide_run"> <span class="nam">mean_vert_velocity</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_cell_property_by_location</span><span class="op">(</span><span class="strut"> </span></p> +<p id="t577" class="pln"> <span class="str">'mean_vert_velocity'</span><span class="op">,</span> <span class="nam">longitudinal_location</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t578" class="stm run hide_run"> <span class="nam">shear_velocity</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_cell_property_by_location</span><span class="op">(</span><span class="strut"> </span></p> +<p id="t579" class="pln"> <span class="str">'shear_velocity'</span><span class="op">,</span> <span class="nam">longitudinal_location</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t580" class="stm run hide_run"> <span class="nam">temperature</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_cell_property_by_location</span><span class="op">(</span><span class="strut"> </span></p> +<p id="t581" class="pln"> <span class="str">'temperature'</span><span class="op">,</span> <span class="nam">longitudinal_location</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t582" class="pln"><span class="strut"> </span></p> +<p id="t583" class="stm run hide_run"> <span class="nam">area</span> <span class="op">=</span> <span class="nam">discharge</span> <span class="op">/</span> <span class="nam">mean_xs_velocity</span><span class="strut"> </span></p> +<p id="t584" class="stm run hide_run"> <span class="nam">width</span> <span class="op">=</span> <span class="nam">area</span> <span class="op">/</span> <span class="nam">depth</span><span class="strut"> </span></p> +<p id="t585" class="pln"><span class="strut"> </span></p> +<p id="t586" class="stm run hide_run"> <span class="nam">viscosity</span> <span class="op">=</span> <span class="nam">calc_water_viscosity</span><span class="op">(</span><span class="nam">temperature</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t587" class="stm run hide_run"> <span class="nam">density</span> <span class="op">=</span> <span class="nam">calc_water_density</span><span class="op">(</span><span class="nam">temperature</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t588" class="pln"><span class="strut"> </span></p> +<p id="t589" class="stm run hide_run"> <span class="nam">lateral_location</span> <span class="op">=</span> <span class="nam">position</span><span class="op">[</span><span class="op">:</span><span class="op">,</span> <span class="num">1</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t590" class="stm run hide_run"> <span class="nam">vertical_location</span> <span class="op">=</span> <span class="nam">position</span><span class="op">[</span><span class="op">:</span><span class="op">,</span> <span class="num">2</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t591" class="stm run hide_run"> <span class="nam">streamwise_velocity</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t592" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">_calc_longitudinal_velocity</span><span class="op">(</span><span class="nam">vertical_location</span><span class="op">,</span> <span class="nam">shear_velocity</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t593" class="pln"> <span class="nam">depth</span><span class="op">,</span> <span class="nam">mean_long_velocity</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t594" class="pln"> <span class="nam">viscosity</span><span class="op">,</span> <span class="nam">lateral_location</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t595" class="pln"> <span class="nam">width</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t596" class="pln"><span class="strut"> </span></p> +<p id="t597" class="pln"> <span class="com"># set the streamwise velocities above the water surface to nan</span><span class="strut"> </span></p> +<p id="t598" class="stm run hide_run"> <span class="nam">above_water_surface</span> <span class="op">=</span> <span class="nam">depth</span> <span class="op"><</span> <span class="nam">vertical_location</span><span class="strut"> </span></p> +<p id="t599" class="stm run hide_run"> <span class="nam">streamwise_velocity</span><span class="op">[</span><span class="nam">above_water_surface</span><span class="op">]</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">nan</span><span class="strut"> </span></p> +<p id="t600" class="pln"><span class="strut"> </span></p> +<p id="t601" class="stm run hide_run"> <span class="nam">hydraulic_data</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">stack</span><span class="op">(</span><span class="op">[</span><span class="nam">depth</span><span class="op">,</span> <span class="nam">width</span><span class="op">,</span> <span class="nam">temperature</span><span class="op">,</span> <span class="nam">viscosity</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t602" class="pln"> <span class="nam">density</span><span class="op">,</span> <span class="nam">streamwise_velocity</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t603" class="pln"> <span class="nam">shear_velocity</span><span class="op">,</span> <span class="nam">mean_lat_velocity</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t604" class="pln"> <span class="nam">mean_vert_velocity</span><span class="op">]</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t605" class="pln"> <span class="nam">axis</span><span class="op">=</span><span class="num">1</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t606" class="pln"><span class="strut"> </span></p> +<p id="t607" class="stm run hide_run"> <span class="key">return</span> <span class="nam">HydraulicResults</span><span class="op">(</span><span class="nam">hydraulic_data</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t608" class="pln"><span class="strut"> </span></p> +<p id="t609" class="stm run hide_run"> <span class="key">def</span> <span class="nam">to_data_frame</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t610" class="pln"> <span class="str">"""Create a Pandas DataFrame from information in this instance.</span><span class="strut"> </span></p> +<p id="t611" class="pln"><span class="strut"> </span></p> +<p id="t612" class="pln"><span class="str"> Returns</span><span class="strut"> </span></p> +<p id="t613" class="pln"><span class="str"> -------</span><span class="strut"> </span></p> +<p id="t614" class="pln"><span class="str"> pandas.DataFrame</span><span class="strut"> </span></p> +<p id="t615" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t616" class="pln"><span class="strut"> </span></p> +<p id="t617" class="stm mis"> <span class="key">if</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_cells</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="op">,</span> <span class="nam">SteadyStateHydraulicCell</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t618" class="pln"><span class="strut"> </span></p> +<p id="t619" class="stm mis"> <span class="nam">columns</span> <span class="op">=</span> <span class="op">[</span><span class="str">'CumlDistance_km'</span><span class="op">,</span> <span class="str">'Depth_m'</span><span class="op">,</span> <span class="str">'Q_cms'</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t620" class="pln"> <span class="str">'Vmag_mps'</span><span class="op">,</span> <span class="str">'Vvert_mps'</span><span class="op">,</span> <span class="str">'Vlat_mps'</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t621" class="pln"> <span class="str">'Ustar_mps'</span><span class="op">,</span> <span class="str">'Temp_C'</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t622" class="stm mis"> <span class="nam">data_dict</span> <span class="op">=</span> <span class="nam">dict</span><span class="op">(</span><span class="nam">zip</span><span class="op">(</span><span class="nam">columns</span><span class="op">,</span> <span class="op">[</span><span class="op">[</span><span class="op">]</span> <span class="key">for</span> <span class="nam">_</span> <span class="key">in</span> <span class="nam">range</span><span class="op">(</span><span class="nam">len</span><span class="op">(</span><span class="nam">columns</span><span class="op">)</span><span class="op">)</span><span class="op">]</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t623" class="pln"><span class="strut"> </span></p> +<p id="t624" class="stm mis"> <span class="key">for</span> <span class="nam">cell</span> <span class="key">in</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_cells</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t625" class="pln"><span class="strut"> </span></p> +<p id="t626" class="stm mis"> <span class="nam">data_dict</span><span class="op">[</span><span class="str">'CumlDistance_km'</span><span class="op">]</span><span class="op">.</span><span class="nam">append</span><span class="op">(</span><span class="nam">cell</span><span class="op">.</span><span class="nam">length</span><span class="op">(</span><span class="op">)</span> <span class="op">/</span> <span class="num">1000</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t627" class="stm mis"> <span class="nam">data_dict</span><span class="op">[</span><span class="str">'Depth_m'</span><span class="op">]</span><span class="op">.</span><span class="nam">append</span><span class="op">(</span><span class="nam">cell</span><span class="op">.</span><span class="nam">depth</span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t628" class="stm mis"> <span class="nam">data_dict</span><span class="op">[</span><span class="str">'Q_cms'</span><span class="op">]</span><span class="op">.</span><span class="nam">append</span><span class="op">(</span><span class="nam">cell</span><span class="op">.</span><span class="nam">discharge</span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t629" class="stm mis"> <span class="nam">data_dict</span><span class="op">[</span><span class="str">'Vmag_mps'</span><span class="op">]</span><span class="op">.</span><span class="nam">append</span><span class="op">(</span><span class="nam">cell</span><span class="op">.</span><span class="nam">mean_xs_velocity</span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t630" class="stm mis"> <span class="nam">data_dict</span><span class="op">[</span><span class="str">'Vvert_mps'</span><span class="op">]</span><span class="op">.</span><span class="nam">append</span><span class="op">(</span><span class="nam">cell</span><span class="op">.</span><span class="nam">mean_vert_velocity</span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t631" class="stm mis"> <span class="nam">data_dict</span><span class="op">[</span><span class="str">'Vlat_mps'</span><span class="op">]</span><span class="op">.</span><span class="nam">append</span><span class="op">(</span><span class="nam">cell</span><span class="op">.</span><span class="nam">mean_lat_velocity</span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t632" class="stm mis"> <span class="nam">data_dict</span><span class="op">[</span><span class="str">'Ustar_mps'</span><span class="op">]</span><span class="op">.</span><span class="nam">append</span><span class="op">(</span><span class="nam">cell</span><span class="op">.</span><span class="nam">shear_velocity</span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t633" class="stm mis"> <span class="nam">data_dict</span><span class="op">[</span><span class="str">'Temp_C'</span><span class="op">]</span><span class="op">.</span><span class="nam">append</span><span class="op">(</span><span class="nam">cell</span><span class="op">.</span><span class="nam">temperature</span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t634" class="pln"><span class="strut"> </span></p> +<p id="t635" class="stm mis"> <span class="nam">cell_numbers</span> <span class="op">=</span> <span class="nam">range</span><span class="op">(</span><span class="num">1</span><span class="op">,</span> <span class="nam">len</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_cells</span><span class="op">)</span> <span class="op">+</span> <span class="num">1</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t636" class="stm mis"> <span class="nam">df</span> <span class="op">=</span> <span class="nam">pd</span><span class="op">.</span><span class="nam">DataFrame</span><span class="op">(</span><span class="nam">data</span><span class="op">=</span><span class="nam">data_dict</span><span class="op">,</span> <span class="nam">index</span><span class="op">=</span><span class="nam">cell_numbers</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t637" class="stm mis"> <span class="nam">df</span><span class="op">[</span><span class="str">'CumlDistance_km'</span><span class="op">]</span> <span class="op">=</span> <span class="nam">df</span><span class="op">[</span><span class="str">'CumlDistance_km'</span><span class="op">]</span><span class="op">.</span><span class="nam">cumsum</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t638" class="pln"><span class="strut"> </span></p> +<p id="t639" class="stm mis"> <span class="nam">df</span><span class="op">.</span><span class="nam">index</span><span class="op">.</span><span class="nam">name</span> <span class="op">=</span> <span class="str">'CellNumber'</span><span class="strut"> </span></p> +<p id="t640" class="pln"><span class="strut"> </span></p> +<p id="t641" class="stm mis"> <span class="key">elif</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_cells</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="op">,</span> <span class="nam">UnsteadyHydraulicCell</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t642" class="pln"><span class="strut"> </span></p> +<p id="t643" class="stm mis"> <span class="nam">frames</span> <span class="op">=</span> <span class="op">[</span><span class="nam">cell</span><span class="op">.</span><span class="nam">to_data_frame</span><span class="op">(</span><span class="op">)</span> <span class="key">for</span> <span class="nam">cell</span> <span class="key">in</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_cells</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t644" class="stm mis"> <span class="nam">df</span> <span class="op">=</span> <span class="nam">pd</span><span class="op">.</span><span class="nam">concat</span><span class="op">(</span><span class="nam">frames</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t645" class="pln"> <span class="nam">keys</span><span class="op">=</span><span class="nam">range</span><span class="op">(</span><span class="num">1</span><span class="op">,</span> <span class="nam">len</span><span class="op">(</span><span class="nam">frames</span><span class="op">)</span><span class="op">+</span><span class="num">1</span><span class="op">)</span><span class="op">)</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t646" class="pln"> <span class="op">.</span><span class="nam">swaplevel</span><span class="op">(</span><span class="op">)</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t647" class="pln"> <span class="op">.</span><span class="nam">sort_index</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t648" class="pln"><span class="strut"> </span></p> +<p id="t649" class="pln"> <span class="key">else</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t650" class="stm mis"> <span class="key">raise</span> <span class="nam">RuntimeError</span><span class="op">(</span><span class="str">"Unknown subclass of HydraulicCell"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t651" class="pln"><span class="strut"> </span></p> +<p id="t652" class="stm mis"> <span class="key">return</span> <span class="nam">df</span><span class="strut"> </span></p> +<p id="t653" class="pln"><span class="strut"> </span></p> +<p id="t654" class="stm run hide_run"> <span class="key">def</span> <span class="nam">cell_edges</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t655" class="pln"> <span class="str">"""Returns the edges of each of the cells</span><span class="strut"> </span></p> +<p id="t656" class="pln"><span class="strut"> </span></p> +<p id="t657" class="pln"><span class="str"> :return: Edges of the hydraulic cells</span><span class="strut"> </span></p> +<p id="t658" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t659" class="stm mis"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_cell_edges</span><span class="strut"> </span></p> +<p id="t660" class="pln"><span class="strut"> </span></p> +<p id="t661" class="pln"><span class="strut"> </span></p> +<p id="t662" class="stm run hide_run"><span class="key">class</span> <span class="nam">RoughBottomSeriesOfHydraulicCells</span><span class="op">(</span><span class="nam">SeriesOfHydraulicCells</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t663" class="pln"> <span class="str">"""Series of hydraulic cells with velocity velocity calculated under a</span><span class="strut"> </span></p> +<p id="t664" class="pln"><span class="str"> rough bottom assumption</span><span class="strut"> </span></p> +<p id="t665" class="pln"><span class="strut"> </span></p> +<p id="t666" class="pln"><span class="str"> Parameters</span><span class="strut"> </span></p> +<p id="t667" class="pln"><span class="str"> ----------</span><span class="strut"> </span></p> +<p id="t668" class="pln"><span class="str"> list_of_cells : list</span><span class="strut"> </span></p> +<p id="t669" class="pln"><span class="str"> List containing HydraulicCell elements.</span><span class="strut"> </span></p> +<p id="t670" class="pln"><span class="strut"> </span></p> +<p id="t671" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t672" class="pln"><span class="strut"> </span></p> +<p id="t673" class="pln"><span class="strut"> </span></p> +<p id="t674" class="stm run hide_run"> <span class="op">@</span><span class="nam">staticmethod</span><span class="strut"> </span></p> +<p id="t675" class="pln"> <span class="key">def</span> <span class="nam">_calc_roughness_height</span><span class="op">(</span><span class="nam">depth</span><span class="op">,</span> <span class="nam">mean_xs_velocity</span><span class="op">,</span> <span class="nam">shear_velocity</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t676" class="pln"> <span class="str">"""Calculate roughness height (kc), in meters</span><span class="strut"> </span></p> +<p id="t677" class="pln"><span class="strut"> </span></p> +<p id="t678" class="pln"><span class="str"> :param depth: Depth of water column in m</span><span class="strut"> </span></p> +<p id="t679" class="pln"><span class="str"> :param mean_xs_velocity: Mean cross-section velocity in m/s</span><span class="strut"> </span></p> +<p id="t680" class="pln"><span class="str"> :param shear_velocity: Shear velocity in ms/</span><span class="strut"> </span></p> +<p id="t681" class="pln"><span class="str"> :return: Roughness height in m</span><span class="strut"> </span></p> +<p id="t682" class="pln"><span class="strut"> </span></p> +<p id="t683" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t684" class="stm run hide_run"> <span class="key">return</span> <span class="num">11</span> <span class="op">*</span> <span class="nam">depth</span> <span class="op">/</span> <span class="nam">np</span><span class="op">.</span><span class="nam">exp</span><span class="op">(</span><span class="op">(</span><span class="nam">mean_xs_velocity</span> <span class="op">*</span> <span class="nam">VON_KARMAN_CONSTANT</span><span class="op">)</span> <span class="op">/</span><span class="strut"> </span></p> +<p id="t685" class="pln"> <span class="nam">shear_velocity</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t686" class="pln"><span class="strut"> </span></p> +<p id="t687" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_calc_log_law_velocity</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">vertical_location</span><span class="op">,</span> <span class="nam">shear_velocity</span><span class="op">,</span> <span class="nam">depth</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t688" class="pln"> <span class="nam">mean_xs_velocity</span><span class="op">,</span> <span class="nam">viscosity</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t689" class="pln"><span class="strut"> </span></p> +<p id="t690" class="stm run hide_run"> <span class="nam">roughness_height</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_calc_roughness_height</span><span class="op">(</span><span class="strut"> </span></p> +<p id="t691" class="pln"> <span class="nam">depth</span><span class="op">,</span> <span class="nam">mean_xs_velocity</span><span class="op">,</span> <span class="nam">shear_velocity</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t692" class="pln"><span class="strut"> </span></p> +<p id="t693" class="stm run hide_run"> <span class="nam">log_law_velocity</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t694" class="pln"> <span class="nam">shear_velocity</span> <span class="op">*</span> <span class="op">(</span><span class="op">(</span><span class="num">1</span><span class="op">/</span><span class="nam">VON_KARMAN_CONSTANT</span><span class="op">)</span> <span class="op">*</span><span class="strut"> </span></p> +<p id="t695" class="pln"> <span class="nam">np</span><span class="op">.</span><span class="nam">log</span><span class="op">(</span><span class="nam">vertical_location</span> <span class="op">/</span> <span class="nam">roughness_height</span><span class="op">)</span> <span class="op">+</span><span class="strut"> </span></p> +<p id="t696" class="pln"> <span class="num">8.5</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t697" class="pln"><span class="strut"> </span></p> +<p id="t698" class="stm run hide_run"> <span class="key">return</span> <span class="nam">log_law_velocity</span><span class="strut"> </span></p> +<p id="t699" class="pln"><span class="strut"> </span></p> +<p id="t700" class="pln"><span class="strut"> </span></p> +<p id="t701" class="stm run hide_run"><span class="key">class</span> <span class="nam">SmoothBottomSeriesOfHydraulicCells</span><span class="op">(</span><span class="nam">SeriesOfHydraulicCells</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t702" class="pln"> <span class="str">"""Not implemented. Fails unit tests.</span><span class="strut"> </span></p> +<p id="t703" class="pln"><span class="strut"> </span></p> +<p id="t704" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t705" class="pln"><span class="strut"> </span></p> +<p id="t706" class="stm run hide_run"> <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="op">*</span><span class="nam">args</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t707" class="stm mis"> <span class="key">raise</span> <span class="nam">NotImplementedError</span><span class="op">(</span><span class="str">"This class is not implemented."</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t708" class="pln"><span class="strut"> </span></p> +<p id="t709" class="pln"><span class="strut"> </span></p> +<p id="t710" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_calc_log_law_velocity</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">distance_above_bed</span><span class="op">,</span> <span class="nam">shear_velocity</span><span class="op">,</span> <span class="nam">depth</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t711" class="pln"> <span class="nam">mean_xs_velocity</span><span class="op">,</span> <span class="nam">viscosity</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t712" class="pln"><span class="strut"> </span></p> +<p id="t713" class="stm mis"> <span class="nam">log_law_velocity</span> <span class="op">=</span> <span class="nam">shear_velocity</span> <span class="op">*</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t714" class="pln"> <span class="op">(</span><span class="num">1</span> <span class="op">/</span> <span class="nam">VON_KARMAN_CONSTANT</span> <span class="op">*</span> <span class="nam">np</span><span class="op">.</span><span class="nam">log</span><span class="op">(</span><span class="nam">shear_velocity</span> <span class="op">*</span><span class="strut"> </span></p> +<p id="t715" class="pln"> <span class="nam">distance_above_bed</span> <span class="op">/</span> <span class="nam">viscosity</span><span class="op">)</span> <span class="op">+</span><span class="strut"> </span></p> +<p id="t716" class="pln"> <span class="num">5.5</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t717" class="pln"><span class="strut"> </span></p> +<p id="t718" class="stm mis"> <span class="key">return</span> <span class="nam">log_law_velocity</span><span class="strut"> </span></p> +<p id="t719" class="pln"><span class="strut"> </span></p> +<p id="t720" class="pln"><span class="strut"> </span></p> +<p id="t721" class="stm run hide_run"><span class="key">def</span> <span class="nam">from_csv</span><span class="op">(</span><span class="nam">path</span><span class="op">,</span> <span class="nam">bed_roughness</span><span class="op">=</span><span class="str">'rough'</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t722" class="pln"> <span class="str">"""Construct a SeriesOfHydraulicCells from a CSV file.</span><span class="strut"> </span></p> +<p id="t723" class="pln"><span class="strut"> </span></p> +<p id="t724" class="pln"><span class="str"> The CSV file must contain the following columns</span><span class="strut"> </span></p> +<p id="t725" class="pln"><span class="strut"> </span></p> +<p id="t726" class="pln"><span class="str"> Column name Description</span><span class="strut"> </span></p> +<p id="t727" class="pln"><span class="str"> ----------- -----------</span><span class="strut"> </span></p> +<p id="t728" class="pln"><span class="str"> CellNumber Cell number, integer 1 to inf</span><span class="strut"> </span></p> +<p id="t729" class="pln"><span class="str"> CumlDistance_km Cumulative distance along the channel of the end of the</span><span class="strut"> </span></p> +<p id="t730" class="pln"><span class="str"> cell in km</span><span class="strut"> </span></p> +<p id="t731" class="pln"><span class="str"> Depth_m Depth of the cell in m</span><span class="strut"> </span></p> +<p id="t732" class="pln"><span class="str"> Q_cms Discharge of the cell in m**3/s</span><span class="strut"> </span></p> +<p id="t733" class="pln"><span class="str"> Vmag_mps Cross-section average velocity in m/s</span><span class="strut"> </span></p> +<p id="t734" class="pln"><span class="str"> Vvert_mps Vertical component of velocity in m/s</span><span class="strut"> </span></p> +<p id="t735" class="pln"><span class="str"> Vlat_mps Lateral component of velocity in m/s</span><span class="strut"> </span></p> +<p id="t736" class="pln"><span class="str"> Ustar_mps Shear velocity in m/s</span><span class="strut"> </span></p> +<p id="t737" class="pln"><span class="str"> Temp_C Temperature in degrees Celsius</span><span class="strut"> </span></p> +<p id="t738" class="pln"><span class="strut"> </span></p> +<p id="t739" class="pln"><span class="str"> The contents of a CSV file representing a reach may look like this.</span><span class="strut"> </span></p> +<p id="t740" class="pln"><span class="str"> CellNumber,CumlDistance_km,Depth_m,Q_cms,Vmag_mps,Vvert_mps,Vlat_mps,</span><span class="strut"> </span></p> +<p id="t741" class="pln"><span class="str"> Ustar_mps,Temp_C</span><span class="strut"> </span></p> +<p id="t742" class="pln"><span class="str"> 1,20,1,10,1,0,0,0.08,19</span><span class="strut"> </span></p> +<p id="t743" class="pln"><span class="str"> 2,40,2,20,2,0,0,0.08,20</span><span class="strut"> </span></p> +<p id="t744" class="pln"><span class="str"> 3,60,3,30,3,0,0,0.08,21</span><span class="strut"> </span></p> +<p id="t745" class="pln"><span class="str"> 4,80,4,40,4,0,0,0.08,22</span><span class="strut"> </span></p> +<p id="t746" class="pln"><span class="str"> 5,100,5,50,5,0,0,0.08,23</span><span class="strut"> </span></p> +<p id="t747" class="pln"><span class="strut"> </span></p> +<p id="t748" class="pln"><span class="str"> This 100 km reach has 5 cells and the discharge (Q_cms) increases from 10</span><span class="strut"> </span></p> +<p id="t749" class="pln"><span class="str"> to 50 m**3/s.</span><span class="strut"> </span></p> +<p id="t750" class="pln"><span class="strut"> </span></p> +<p id="t751" class="pln"><span class="str"> :param path: Path to CSV file</span><span class="strut"> </span></p> +<p id="t752" class="pln"><span class="str"> :type path: str</span><span class="strut"> </span></p> +<p id="t753" class="pln"><span class="str"> :param bed_roughness: 'rough' or 'smooth'</span><span class="strut"> </span></p> +<p id="t754" class="pln"><span class="str"> :type bed_roughness: str</span><span class="strut"> </span></p> +<p id="t755" class="pln"><span class="str"> :return: SeriesOfHydraulicCells</span><span class="strut"> </span></p> +<p id="t756" class="pln"><span class="strut"> </span></p> +<p id="t757" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t758" class="pln"><span class="strut"> </span></p> +<p id="t759" class="stm run hide_run"> <span class="nam">input_df</span> <span class="op">=</span> <span class="nam">pd</span><span class="op">.</span><span class="nam">read_csv</span><span class="op">(</span><span class="nam">path</span><span class="op">,</span> <span class="nam">index_col</span><span class="op">=</span><span class="num">0</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t760" class="pln"><span class="strut"> </span></p> +<p id="t761" class="stm run hide_run"> <span class="key">if</span> <span class="nam">bed_roughness</span> <span class="op">==</span> <span class="str">'rough'</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t762" class="stm run hide_run"> <span class="nam">cls</span> <span class="op">=</span> <span class="nam">RoughBottomSeriesOfHydraulicCells</span><span class="strut"> </span></p> +<p id="t763" class="stm mis"> <span class="key">elif</span> <span class="nam">bed_roughness</span> <span class="op">==</span> <span class="str">'smooth'</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t764" class="stm mis"> <span class="nam">cls</span> <span class="op">=</span> <span class="nam">SmoothBottomSeriesOfHydraulicCells</span><span class="strut"> </span></p> +<p id="t765" class="pln"> <span class="key">else</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t766" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="str">"Unknown bed roughness"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t767" class="pln"><span class="strut"> </span></p> +<p id="t768" class="stm run hide_run"> <span class="key">return</span> <span class="nam">cls</span><span class="op">.</span><span class="nam">from_data_frame</span><span class="op">(</span><span class="nam">input_df</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t769" class="pln"><span class="strut"> </span></p> +<p id="t770" class="pln"><span class="strut"> </span></p> +<p id="t771" class="stm run hide_run"><span class="key">class</span> <span class="nam">HydraulicResults</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t772" class="pln"> <span class="str">"""Data structure containing hydraulic results from a hydraulic model</span><span class="strut"> </span></p> +<p id="t773" class="pln"><span class="str"> simulation.</span><span class="strut"> </span></p> +<p id="t774" class="pln"><span class="strut"> </span></p> +<p id="t775" class="pln"><span class="str"> Instantiated from SeriesOfHydraulicCells.hydraulic_results(). Not to be</span><span class="strut"> </span></p> +<p id="t776" class="pln"><span class="str"> instantiated elsewhere.</span><span class="strut"> </span></p> +<p id="t777" class="pln"><span class="strut"> </span></p> +<p id="t778" class="pln"><span class="str"> See Also</span><span class="strut"> </span></p> +<p id="t779" class="pln"><span class="str"> --------</span><span class="strut"> </span></p> +<p id="t780" class="pln"><span class="str"> SeriesOfHydraulicCells.hydraulic_results()</span><span class="strut"> </span></p> +<p id="t781" class="pln"><span class="strut"> </span></p> +<p id="t782" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t783" class="pln"><span class="strut"> </span></p> +<p id="t784" class="stm run hide_run"> <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">hydraulic_data</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t785" class="pln"> <span class="str">"""Initialize self. See help(type(self)) for accurate signature."""</span><span class="strut"> </span></p> +<p id="t786" class="pln"><span class="strut"> </span></p> +<p id="t787" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_hydraulic_data</span> <span class="op">=</span> <span class="nam">hydraulic_data</span><span class="strut"> </span></p> +<p id="t788" class="pln"><span class="strut"> </span></p> +<p id="t789" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_depth_index</span> <span class="op">=</span> <span class="num">0</span><span class="strut"> </span></p> +<p id="t790" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_width_index</span> <span class="op">=</span> <span class="num">1</span><span class="strut"> </span></p> +<p id="t791" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_temperature_index</span> <span class="op">=</span> <span class="num">2</span><span class="strut"> </span></p> +<p id="t792" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_viscosity_index</span> <span class="op">=</span> <span class="num">3</span><span class="strut"> </span></p> +<p id="t793" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_density_index</span> <span class="op">=</span> <span class="num">4</span><span class="strut"> </span></p> +<p id="t794" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_streamwise_velocity_index</span> <span class="op">=</span> <span class="num">5</span><span class="strut"> </span></p> +<p id="t795" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_shear_velocity_index</span> <span class="op">=</span> <span class="num">6</span><span class="strut"> </span></p> +<p id="t796" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_lateral_velocity_index</span> <span class="op">=</span> <span class="num">7</span><span class="strut"> </span></p> +<p id="t797" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_vertical_velocity_index</span> <span class="op">=</span> <span class="num">8</span><span class="strut"> </span></p> +<p id="t798" class="pln"><span class="strut"> </span></p> +<p id="t799" class="stm run hide_run"> <span class="key">def</span> <span class="nam">depth</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t800" class="pln"> <span class="str">"""Returns the depth of the water column at a given position.</span><span class="strut"> </span></p> +<p id="t801" class="pln"><span class="strut"> </span></p> +<p id="t802" class="pln"><span class="str"> Returns a numpy array of length n, where n is the number of positions</span><span class="strut"> </span></p> +<p id="t803" class="pln"><span class="str"> passed to SeriesOfHydraulicCells.hydraulic_results().</span><span class="strut"> </span></p> +<p id="t804" class="pln"><span class="strut"> </span></p> +<p id="t805" class="pln"><span class="str"> :return: Depth of water column in m</span><span class="strut"> </span></p> +<p id="t806" class="pln"><span class="strut"> </span></p> +<p id="t807" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t808" class="pln"><span class="strut"> </span></p> +<p id="t809" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_hydraulic_data</span><span class="op">[</span><span class="op">:</span><span class="op">,</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_depth_index</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t810" class="pln"><span class="strut"> </span></p> +<p id="t811" class="stm run hide_run"> <span class="key">def</span> <span class="nam">lateral_velocity</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t812" class="pln"> <span class="str">"""Returns the lateral (y-direction) velocity for a given position.</span><span class="strut"> </span></p> +<p id="t813" class="pln"><span class="strut"> </span></p> +<p id="t814" class="pln"><span class="str"> Returns a numpy array of length n, where n is the number of positions</span><span class="strut"> </span></p> +<p id="t815" class="pln"><span class="str"> passed to SeriesOfHydraulicCells.hydraulic_results().</span><span class="strut"> </span></p> +<p id="t816" class="pln"><span class="strut"> </span></p> +<p id="t817" class="pln"><span class="str"> :return: Lateral velocity in m/s</span><span class="strut"> </span></p> +<p id="t818" class="pln"><span class="strut"> </span></p> +<p id="t819" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t820" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_hydraulic_data</span><span class="op">[</span><span class="op">:</span><span class="op">,</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_lateral_velocity_index</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t821" class="pln"><span class="strut"> </span></p> +<p id="t822" class="stm run hide_run"> <span class="key">def</span> <span class="nam">shear_velocity</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t823" class="pln"> <span class="str">"""Returns the shear velocity corresponding to a position.</span><span class="strut"> </span></p> +<p id="t824" class="pln"><span class="strut"> </span></p> +<p id="t825" class="pln"><span class="str"> Returns a numpy array of length n, where n is the number of positions</span><span class="strut"> </span></p> +<p id="t826" class="pln"><span class="str"> passed to SeriesOfHydraulicCells.hydraulic_results().</span><span class="strut"> </span></p> +<p id="t827" class="pln"><span class="strut"> </span></p> +<p id="t828" class="pln"><span class="str"> :return: Shear velocity in m/s</span><span class="strut"> </span></p> +<p id="t829" class="pln"><span class="strut"> </span></p> +<p id="t830" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t831" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_hydraulic_data</span><span class="op">[</span><span class="op">:</span><span class="op">,</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_shear_velocity_index</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t832" class="pln"><span class="strut"> </span></p> +<p id="t833" class="stm run hide_run"> <span class="key">def</span> <span class="nam">streamwise_velocity</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t834" class="pln"> <span class="str">"""Returns the streamwise (x-direction) velocity for a given position.</span><span class="strut"> </span></p> +<p id="t835" class="pln"><span class="strut"> </span></p> +<p id="t836" class="pln"><span class="str"> Returns a numpy array of length n, where n is the number of positions</span><span class="strut"> </span></p> +<p id="t837" class="pln"><span class="str"> passed to SeriesOfHydraulicCells.hydraulic_results().</span><span class="strut"> </span></p> +<p id="t838" class="pln"><span class="strut"> </span></p> +<p id="t839" class="pln"><span class="str"> :return: Streamwise velocity in m/s</span><span class="strut"> </span></p> +<p id="t840" class="pln"><span class="strut"> </span></p> +<p id="t841" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t842" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_hydraulic_data</span><span class="op">[</span><span class="op">:</span><span class="op">,</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_streamwise_velocity_index</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t843" class="pln"><span class="strut"> </span></p> +<p id="t844" class="stm run hide_run"> <span class="key">def</span> <span class="nam">temperature</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t845" class="pln"> <span class="str">"""Returns the temperature for a given position.</span><span class="strut"> </span></p> +<p id="t846" class="pln"><span class="strut"> </span></p> +<p id="t847" class="pln"><span class="str"> Returns a numpy array of length n, where n is the number of positions</span><span class="strut"> </span></p> +<p id="t848" class="pln"><span class="str"> passed to SeriesOfHydraulicCells.hydraulic_results().</span><span class="strut"> </span></p> +<p id="t849" class="pln"><span class="strut"> </span></p> +<p id="t850" class="pln"><span class="str"> :return: Temperature in deg C</span><span class="strut"> </span></p> +<p id="t851" class="pln"><span class="strut"> </span></p> +<p id="t852" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t853" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_hydraulic_data</span><span class="op">[</span><span class="op">:</span><span class="op">,</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_temperature_index</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t854" class="pln"><span class="strut"> </span></p> +<p id="t855" class="stm run hide_run"> <span class="key">def</span> <span class="nam">water_density</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t856" class="pln"> <span class="str">"""Returns the density of the water at a given position.</span><span class="strut"> </span></p> +<p id="t857" class="pln"><span class="strut"> </span></p> +<p id="t858" class="pln"><span class="str"> Returns a numpy array of length n, where n is the number of positions</span><span class="strut"> </span></p> +<p id="t859" class="pln"><span class="str"> passed to SeriesOfHydraulicCells.hydraulic_results().</span><span class="strut"> </span></p> +<p id="t860" class="pln"><span class="strut"> </span></p> +<p id="t861" class="pln"><span class="str"> :return: Water density in kg/m**3</span><span class="strut"> </span></p> +<p id="t862" class="pln"><span class="strut"> </span></p> +<p id="t863" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t864" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_hydraulic_data</span><span class="op">[</span><span class="op">:</span><span class="op">,</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_density_index</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t865" class="pln"><span class="strut"> </span></p> +<p id="t866" class="stm run hide_run"> <span class="key">def</span> <span class="nam">water_viscosity</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t867" class="pln"> <span class="str">"""Returns the viscosity of water at a given position.</span><span class="strut"> </span></p> +<p id="t868" class="pln"><span class="strut"> </span></p> +<p id="t869" class="pln"><span class="str"> Returns a numpy array of length n, where n is the number of positions</span><span class="strut"> </span></p> +<p id="t870" class="pln"><span class="str"> passed to SeriesOfHydraulicCells.hydraulic_results().</span><span class="strut"> </span></p> +<p id="t871" class="pln"><span class="strut"> </span></p> +<p id="t872" class="pln"><span class="str"> :return: Viscosity in m**2/s</span><span class="strut"> </span></p> +<p id="t873" class="pln"><span class="strut"> </span></p> +<p id="t874" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t875" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_hydraulic_data</span><span class="op">[</span><span class="op">:</span><span class="op">,</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_viscosity_index</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t876" class="pln"><span class="strut"> </span></p> +<p id="t877" class="stm run hide_run"> <span class="key">def</span> <span class="nam">width</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t878" class="pln"> <span class="str">"""Returns the width of the channel at a given position.</span><span class="strut"> </span></p> +<p id="t879" class="pln"><span class="strut"> </span></p> +<p id="t880" class="pln"><span class="str"> Returns a numpy array of length n, where n is the number of positions</span><span class="strut"> </span></p> +<p id="t881" class="pln"><span class="str"> passed to SeriesOfHydraulicCells.hydraulic_results().</span><span class="strut"> </span></p> +<p id="t882" class="pln"><span class="strut"> </span></p> +<p id="t883" class="pln"><span class="str"> :return: Width in m</span><span class="strut"> </span></p> +<p id="t884" class="pln"><span class="strut"> </span></p> +<p id="t885" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t886" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_hydraulic_data</span><span class="op">[</span><span class="op">:</span><span class="op">,</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_width_index</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t887" class="pln"><span class="strut"> </span></p> +<p id="t888" class="stm run hide_run"> <span class="key">def</span> <span class="nam">vertical_velocity</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t889" class="pln"> <span class="str">"""Returns the vertical (z-direction) velocity for a given position.</span><span class="strut"> </span></p> +<p id="t890" class="pln"><span class="strut"> </span></p> +<p id="t891" class="pln"><span class="str"> Returns a numpy array of length n, where n is the number of positions</span><span class="strut"> </span></p> +<p id="t892" class="pln"><span class="str"> passed to SeriesOfHydraulicCells.hydraulic_results().</span><span class="strut"> </span></p> +<p id="t893" class="pln"><span class="strut"> </span></p> +<p id="t894" class="pln"><span class="str"> :return: Vertical velocity in m/s</span><span class="strut"> </span></p> +<p id="t895" class="pln"><span class="strut"> </span></p> +<p id="t896" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t897" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_hydraulic_data</span><span class="op">[</span><span class="op">:</span><span class="op">,</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_vertical_velocity_index</span><span class="op">]</span><span class="strut"> </span></p> + + </td> + </tr> + </table> +</div> + +<div id="footer"> + <div class="content"> + <p> + <a class="nav" href="index.html">« index</a> <a class="nav" href="https://coverage.readthedocs.io">coverage.py v4.5.3</a>, + created at 2019-07-09 15:15 + </p> + </div> +</div> + +</body> +</html> diff --git a/coverage_report/fluegg_kml_py.html b/coverage_report/fluegg_kml_py.html new file mode 100644 index 0000000..b85f228 --- /dev/null +++ b/coverage_report/fluegg_kml_py.html @@ -0,0 +1,907 @@ + + + +<!DOCTYPE html> +<html> +<head> + <meta http-equiv="Content-Type" content="text/html; charset=utf-8"> + + + <meta http-equiv="X-UA-Compatible" content="IE=emulateIE7" /> + <title>Coverage for fluegg\kml.py: 13%</title> + <link rel="stylesheet" href="style.css" type="text/css"> + + <script type="text/javascript" src="jquery.min.js"></script> + <script type="text/javascript" src="jquery.hotkeys.js"></script> + <script type="text/javascript" src="jquery.isonscreen.js"></script> + <script type="text/javascript" src="coverage_html.js"></script> + <script type="text/javascript"> + jQuery(document).ready(coverage.pyfile_ready); + </script> +</head> +<body class="pyfile"> + +<div id="header"> + <div class="content"> + <h1>Coverage for <b>fluegg\kml.py</b> : + <span class="pc_cov">13%</span> + </h1> + + <img id="keyboard_icon" src="keybd_closed.png" alt="Show keyboard shortcuts" /> + + <h2 class="stats"> + 130 statements + <span class="run hide_run shortkey_r button_toggle_run">17 run</span> + <span class="mis shortkey_m button_toggle_mis">113 missing</span> + <span class="exc shortkey_x 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href="#n100">100</a></p> +<p id="n101" class="pln"><a href="#n101">101</a></p> +<p id="n102" class="pln"><a href="#n102">102</a></p> +<p id="n103" class="pln"><a href="#n103">103</a></p> +<p id="n104" class="pln"><a href="#n104">104</a></p> +<p id="n105" class="pln"><a href="#n105">105</a></p> +<p id="n106" class="pln"><a href="#n106">106</a></p> +<p id="n107" class="pln"><a href="#n107">107</a></p> +<p id="n108" class="pln"><a href="#n108">108</a></p> +<p id="n109" class="pln"><a href="#n109">109</a></p> +<p id="n110" class="pln"><a href="#n110">110</a></p> +<p id="n111" class="pln"><a href="#n111">111</a></p> +<p id="n112" class="stm run hide_run"><a href="#n112">112</a></p> +<p id="n113" class="pln"><a href="#n113">113</a></p> +<p id="n114" class="pln"><a href="#n114">114</a></p> +<p id="n115" class="pln"><a href="#n115">115</a></p> +<p id="n116" class="pln"><a href="#n116">116</a></p> +<p id="n117" class="stm mis"><a href="#n117">117</a></p> +<p id="n118" class="pln"><a href="#n118">118</a></p> +<p id="n119" class="stm mis"><a href="#n119">119</a></p> +<p id="n120" class="pln"><a href="#n120">120</a></p> +<p id="n121" class="pln"><a href="#n121">121</a></p> +<p id="n122" class="stm mis"><a href="#n122">122</a></p> +<p id="n123" class="pln"><a href="#n123">123</a></p> +<p id="n124" class="stm mis"><a href="#n124">124</a></p> +<p id="n125" class="pln"><a href="#n125">125</a></p> +<p id="n126" class="stm run hide_run"><a href="#n126">126</a></p> +<p id="n127" class="pln"><a href="#n127">127</a></p> +<p id="n128" class="pln"><a href="#n128">128</a></p> +<p id="n129" class="pln"><a href="#n129">129</a></p> +<p id="n130" class="pln"><a href="#n130">130</a></p> +<p id="n131" class="pln"><a href="#n131">131</a></p> +<p id="n132" class="pln"><a href="#n132">132</a></p> +<p id="n133" class="pln"><a href="#n133">133</a></p> +<p id="n134" class="pln"><a href="#n134">134</a></p> +<p id="n135" class="stm mis"><a href="#n135">135</a></p> +<p id="n136" class="stm mis"><a href="#n136">136</a></p> +<p id="n137" class="pln"><a href="#n137">137</a></p> +<p id="n138" class="stm mis"><a href="#n138">138</a></p> +<p id="n139" class="stm mis"><a href="#n139">139</a></p> +<p id="n140" class="pln"><a href="#n140">140</a></p> +<p id="n141" class="stm mis"><a href="#n141">141</a></p> +<p id="n142" class="pln"><a href="#n142">142</a></p> +<p id="n143" class="stm mis"><a href="#n143">143</a></p> +<p id="n144" class="stm mis"><a href="#n144">144</a></p> +<p id="n145" class="pln"><a href="#n145">145</a></p> +<p id="n146" class="stm run hide_run"><a href="#n146">146</a></p> +<p id="n147" class="pln"><a href="#n147">147</a></p> +<p id="n148" class="stm mis"><a href="#n148">148</a></p> +<p id="n149" class="stm mis"><a href="#n149">149</a></p> +<p id="n150" class="pln"><a href="#n150">150</a></p> +<p id="n151" class="stm mis"><a href="#n151">151</a></p> +<p id="n152" class="stm mis"><a href="#n152">152</a></p> +<p id="n153" class="pln"><a href="#n153">153</a></p> +<p id="n154" class="pln"><a href="#n154">154</a></p> +<p id="n155" class="stm mis"><a href="#n155">155</a></p> +<p id="n156" class="pln"><a href="#n156">156</a></p> +<p id="n157" class="pln"><a href="#n157">157</a></p> +<p id="n158" class="stm mis"><a href="#n158">158</a></p> +<p id="n159" class="stm mis"><a href="#n159">159</a></p> +<p id="n160" class="pln"><a href="#n160">160</a></p> +<p id="n161" class="pln"><a href="#n161">161</a></p> +<p id="n162" class="stm mis"><a href="#n162">162</a></p> +<p id="n163" class="stm mis"><a href="#n163">163</a></p> +<p id="n164" class="pln"><a href="#n164">164</a></p> +<p id="n165" class="pln"><a href="#n165">165</a></p> +<p id="n166" class="stm mis"><a href="#n166">166</a></p> +<p id="n167" class="stm mis"><a href="#n167">167</a></p> +<p id="n168" class="pln"><a href="#n168">168</a></p> +<p id="n169" class="pln"><a href="#n169">169</a></p> +<p id="n170" class="stm mis"><a href="#n170">170</a></p> +<p id="n171" class="stm mis"><a href="#n171">171</a></p> +<p id="n172" class="pln"><a href="#n172">172</a></p> +<p id="n173" class="pln"><a href="#n173">173</a></p> +<p id="n174" class="stm mis"><a href="#n174">174</a></p> +<p id="n175" class="stm mis"><a href="#n175">175</a></p> +<p id="n176" class="pln"><a href="#n176">176</a></p> +<p id="n177" class="pln"><a href="#n177">177</a></p> +<p id="n178" class="pln"><a href="#n178">178</a></p> +<p id="n179" class="stm mis"><a href="#n179">179</a></p> +<p id="n180" class="pln"><a href="#n180">180</a></p> +<p id="n181" class="stm mis"><a href="#n181">181</a></p> +<p id="n182" class="stm mis"><a href="#n182">182</a></p> +<p id="n183" class="stm mis"><a href="#n183">183</a></p> +<p id="n184" class="stm mis"><a href="#n184">184</a></p> +<p id="n185" class="pln"><a href="#n185">185</a></p> +<p id="n186" class="pln"><a href="#n186">186</a></p> +<p id="n187" class="stm mis"><a href="#n187">187</a></p> +<p id="n188" class="pln"><a href="#n188">188</a></p> +<p id="n189" class="stm run hide_run"><a href="#n189">189</a></p> +<p id="n190" class="pln"><a href="#n190">190</a></p> +<p id="n191" class="pln"><a href="#n191">191</a></p> +<p id="n192" class="pln"><a href="#n192">192</a></p> +<p id="n193" class="pln"><a href="#n193">193</a></p> +<p id="n194" class="pln"><a href="#n194">194</a></p> +<p id="n195" class="pln"><a href="#n195">195</a></p> +<p id="n196" class="pln"><a href="#n196">196</a></p> +<p id="n197" class="pln"><a href="#n197">197</a></p> +<p id="n198" class="pln"><a href="#n198">198</a></p> +<p id="n199" class="pln"><a href="#n199">199</a></p> +<p id="n200" class="pln"><a href="#n200">200</a></p> +<p id="n201" class="pln"><a href="#n201">201</a></p> +<p id="n202" class="stm mis"><a href="#n202">202</a></p> +<p id="n203" class="pln"><a href="#n203">203</a></p> +<p id="n204" class="pln"><a href="#n204">204</a></p> +<p id="n205" class="stm mis"><a href="#n205">205</a></p> +<p id="n206" class="pln"><a href="#n206">206</a></p> +<p id="n207" class="pln"><a href="#n207">207</a></p> +<p id="n208" class="pln"><a href="#n208">208</a></p> +<p id="n209" class="stm mis"><a href="#n209">209</a></p> +<p id="n210" class="pln"><a href="#n210">210</a></p> +<p id="n211" class="stm run hide_run"><a href="#n211">211</a></p> +<p id="n212" class="pln"><a href="#n212">212</a></p> +<p id="n213" class="pln"><a href="#n213">213</a></p> +<p id="n214" class="pln"><a href="#n214">214</a></p> +<p id="n215" class="pln"><a href="#n215">215</a></p> +<p id="n216" class="pln"><a href="#n216">216</a></p> +<p id="n217" class="pln"><a href="#n217">217</a></p> +<p id="n218" class="pln"><a href="#n218">218</a></p> +<p id="n219" class="pln"><a href="#n219">219</a></p> +<p id="n220" class="pln"><a href="#n220">220</a></p> +<p id="n221" class="pln"><a href="#n221">221</a></p> +<p id="n222" class="pln"><a href="#n222">222</a></p> +<p id="n223" class="pln"><a href="#n223">223</a></p> +<p id="n224" class="pln"><a href="#n224">224</a></p> +<p id="n225" class="pln"><a href="#n225">225</a></p> +<p id="n226" class="pln"><a href="#n226">226</a></p> +<p id="n227" class="pln"><a href="#n227">227</a></p> +<p id="n228" class="pln"><a href="#n228">228</a></p> +<p id="n229" class="pln"><a href="#n229">229</a></p> +<p id="n230" class="pln"><a href="#n230">230</a></p> +<p id="n231" class="pln"><a href="#n231">231</a></p> +<p id="n232" class="pln"><a href="#n232">232</a></p> +<p id="n233" class="pln"><a href="#n233">233</a></p> +<p id="n234" class="pln"><a href="#n234">234</a></p> +<p id="n235" class="pln"><a href="#n235">235</a></p> +<p id="n236" class="pln"><a href="#n236">236</a></p> +<p id="n237" class="stm mis"><a href="#n237">237</a></p> +<p id="n238" class="pln"><a href="#n238">238</a></p> +<p id="n239" class="stm mis"><a href="#n239">239</a></p> +<p id="n240" class="stm mis"><a href="#n240">240</a></p> +<p id="n241" class="pln"><a href="#n241">241</a></p> +<p id="n242" class="stm mis"><a href="#n242">242</a></p> +<p id="n243" class="stm mis"><a href="#n243">243</a></p> +<p id="n244" class="pln"><a href="#n244">244</a></p> +<p id="n245" class="stm mis"><a href="#n245">245</a></p> +<p id="n246" class="stm mis"><a href="#n246">246</a></p> +<p id="n247" class="pln"><a href="#n247">247</a></p> +<p id="n248" class="pln"><a href="#n248">248</a></p> +<p id="n249" class="stm mis"><a href="#n249">249</a></p> +<p id="n250" class="pln"><a href="#n250">250</a></p> +<p id="n251" class="stm mis"><a href="#n251">251</a></p> +<p id="n252" class="pln"><a href="#n252">252</a></p> +<p id="n253" class="stm mis"><a href="#n253">253</a></p> +<p id="n254" class="pln"><a href="#n254">254</a></p> +<p id="n255" class="stm mis"><a href="#n255">255</a></p> +<p id="n256" class="stm mis"><a href="#n256">256</a></p> +<p id="n257" class="stm mis"><a href="#n257">257</a></p> +<p id="n258" class="stm mis"><a href="#n258">258</a></p> +<p id="n259" class="pln"><a href="#n259">259</a></p> +<p id="n260" class="pln"><a href="#n260">260</a></p> +<p id="n261" class="stm mis"><a href="#n261">261</a></p> +<p id="n262" class="pln"><a href="#n262">262</a></p> +<p id="n263" class="stm mis"><a href="#n263">263</a></p> +<p id="n264" class="pln"><a href="#n264">264</a></p> +<p id="n265" class="stm mis"><a href="#n265">265</a></p> +<p id="n266" class="stm mis"><a href="#n266">266</a></p> +<p id="n267" class="pln"><a href="#n267">267</a></p> +<p id="n268" class="pln"><a href="#n268">268</a></p> +<p id="n269" class="stm mis"><a href="#n269">269</a></p> +<p id="n270" class="stm mis"><a href="#n270">270</a></p> +<p id="n271" class="pln"><a href="#n271">271</a></p> +<p id="n272" class="stm mis"><a href="#n272">272</a></p> +<p id="n273" class="stm mis"><a href="#n273">273</a></p> +<p id="n274" class="pln"><a href="#n274">274</a></p> +<p id="n275" class="stm mis"><a href="#n275">275</a></p> +<p id="n276" class="pln"><a href="#n276">276</a></p> +<p id="n277" class="stm mis"><a href="#n277">277</a></p> +<p id="n278" class="pln"><a href="#n278">278</a></p> +<p id="n279" class="stm run hide_run"><a href="#n279">279</a></p> +<p id="n280" class="pln"><a href="#n280">280</a></p> +<p id="n281" class="pln"><a href="#n281">281</a></p> +<p id="n282" class="pln"><a href="#n282">282</a></p> +<p id="n283" class="pln"><a href="#n283">283</a></p> +<p id="n284" class="pln"><a href="#n284">284</a></p> +<p id="n285" class="pln"><a href="#n285">285</a></p> +<p id="n286" class="pln"><a href="#n286">286</a></p> +<p id="n287" class="pln"><a href="#n287">287</a></p> +<p id="n288" class="pln"><a href="#n288">288</a></p> +<p id="n289" class="pln"><a href="#n289">289</a></p> +<p id="n290" class="pln"><a href="#n290">290</a></p> +<p id="n291" class="pln"><a href="#n291">291</a></p> +<p id="n292" class="stm mis"><a href="#n292">292</a></p> +<p id="n293" class="stm mis"><a href="#n293">293</a></p> +<p id="n294" class="pln"><a href="#n294">294</a></p> +<p id="n295" class="stm mis"><a href="#n295">295</a></p> +<p id="n296" class="pln"><a href="#n296">296</a></p> +<p id="n297" class="stm run hide_run"><a href="#n297">297</a></p> +<p id="n298" class="pln"><a href="#n298">298</a></p> +<p id="n299" class="pln"><a href="#n299">299</a></p> +<p id="n300" class="pln"><a href="#n300">300</a></p> +<p id="n301" class="pln"><a href="#n301">301</a></p> +<p id="n302" class="pln"><a href="#n302">302</a></p> +<p id="n303" class="pln"><a href="#n303">303</a></p> +<p id="n304" class="pln"><a href="#n304">304</a></p> +<p id="n305" class="pln"><a href="#n305">305</a></p> +<p id="n306" class="pln"><a href="#n306">306</a></p> +<p id="n307" class="pln"><a href="#n307">307</a></p> +<p id="n308" class="pln"><a href="#n308">308</a></p> +<p id="n309" class="pln"><a href="#n309">309</a></p> +<p id="n310" class="pln"><a href="#n310">310</a></p> +<p id="n311" class="pln"><a href="#n311">311</a></p> +<p id="n312" class="pln"><a href="#n312">312</a></p> +<p id="n313" class="pln"><a href="#n313">313</a></p> +<p id="n314" class="pln"><a href="#n314">314</a></p> +<p id="n315" class="pln"><a href="#n315">315</a></p> +<p id="n316" class="stm mis"><a href="#n316">316</a></p> +<p id="n317" class="pln"><a href="#n317">317</a></p> +<p id="n318" class="stm mis"><a href="#n318">318</a></p> +<p id="n319" class="pln"><a href="#n319">319</a></p> +<p id="n320" class="stm mis"><a href="#n320">320</a></p> +<p id="n321" class="pln"><a href="#n321">321</a></p> +<p id="n322" class="pln"><a href="#n322">322</a></p> +<p id="n323" class="stm mis"><a href="#n323">323</a></p> +<p id="n324" class="pln"><a href="#n324">324</a></p> +<p id="n325" class="stm mis"><a href="#n325">325</a></p> +<p id="n326" class="stm mis"><a href="#n326">326</a></p> +<p id="n327" class="stm mis"><a href="#n327">327</a></p> +<p id="n328" class="stm mis"><a href="#n328">328</a></p> +<p id="n329" class="stm mis"><a href="#n329">329</a></p> +<p id="n330" class="stm mis"><a href="#n330">330</a></p> +<p id="n331" class="stm mis"><a href="#n331">331</a></p> +<p id="n332" class="stm mis"><a href="#n332">332</a></p> +<p id="n333" class="stm mis"><a href="#n333">333</a></p> +<p id="n334" class="pln"><a href="#n334">334</a></p> +<p id="n335" class="stm mis"><a href="#n335">335</a></p> +<p id="n336" class="stm mis"><a href="#n336">336</a></p> +<p id="n337" class="stm mis"><a href="#n337">337</a></p> +<p id="n338" class="stm mis"><a href="#n338">338</a></p> +<p id="n339" class="pln"><a href="#n339">339</a></p> +<p id="n340" class="pln"><a href="#n340">340</a></p> +<p id="n341" class="stm mis"><a href="#n341">341</a></p> +<p id="n342" class="pln"><a href="#n342">342</a></p> +<p id="n343" class="stm mis"><a href="#n343">343</a></p> +<p id="n344" class="pln"><a href="#n344">344</a></p> +<p id="n345" class="stm mis"><a href="#n345">345</a></p> +<p id="n346" class="pln"><a href="#n346">346</a></p> +<p id="n347" class="stm run hide_run"><a href="#n347">347</a></p> +<p id="n348" class="pln"><a href="#n348">348</a></p> +<p id="n349" class="pln"><a href="#n349">349</a></p> +<p id="n350" class="pln"><a href="#n350">350</a></p> +<p id="n351" class="pln"><a href="#n351">351</a></p> +<p id="n352" class="pln"><a href="#n352">352</a></p> +<p id="n353" class="pln"><a href="#n353">353</a></p> +<p id="n354" class="pln"><a href="#n354">354</a></p> +<p id="n355" class="pln"><a href="#n355">355</a></p> +<p id="n356" class="pln"><a href="#n356">356</a></p> +<p id="n357" class="pln"><a href="#n357">357</a></p> +<p id="n358" class="pln"><a href="#n358">358</a></p> +<p id="n359" class="pln"><a href="#n359">359</a></p> +<p id="n360" class="pln"><a href="#n360">360</a></p> +<p id="n361" class="pln"><a href="#n361">361</a></p> +<p id="n362" class="pln"><a href="#n362">362</a></p> +<p id="n363" class="pln"><a href="#n363">363</a></p> +<p id="n364" class="pln"><a href="#n364">364</a></p> +<p id="n365" class="pln"><a href="#n365">365</a></p> +<p id="n366" class="pln"><a href="#n366">366</a></p> +<p id="n367" class="pln"><a href="#n367">367</a></p> +<p id="n368" class="pln"><a href="#n368">368</a></p> +<p id="n369" class="pln"><a href="#n369">369</a></p> +<p id="n370" class="pln"><a href="#n370">370</a></p> +<p id="n371" class="pln"><a href="#n371">371</a></p> +<p id="n372" class="stm mis"><a href="#n372">372</a></p> +<p id="n373" class="pln"><a href="#n373">373</a></p> +<p id="n374" class="stm mis"><a href="#n374">374</a></p> +<p id="n375" class="stm mis"><a href="#n375">375</a></p> +<p id="n376" class="pln"><a href="#n376">376</a></p> +<p id="n377" class="stm run hide_run"><a href="#n377">377</a></p> +<p id="n378" class="pln"><a href="#n378">378</a></p> +<p id="n379" class="pln"><a href="#n379">379</a></p> +<p id="n380" class="pln"><a href="#n380">380</a></p> +<p id="n381" class="pln"><a href="#n381">381</a></p> +<p id="n382" class="pln"><a href="#n382">382</a></p> +<p id="n383" class="pln"><a href="#n383">383</a></p> +<p id="n384" class="pln"><a href="#n384">384</a></p> +<p id="n385" class="pln"><a href="#n385">385</a></p> +<p id="n386" class="stm mis"><a href="#n386">386</a></p> +<p id="n387" class="pln"><a href="#n387">387</a></p> +<p id="n388" class="stm mis"><a href="#n388">388</a></p> +<p id="n389" class="stm mis"><a href="#n389">389</a></p> +<p id="n390" class="pln"><a href="#n390">390</a></p> +<p id="n391" class="stm run hide_run"><a href="#n391">391</a></p> +<p id="n392" class="pln"><a href="#n392">392</a></p> +<p id="n393" class="pln"><a href="#n393">393</a></p> +<p id="n394" class="pln"><a href="#n394">394</a></p> +<p id="n395" class="pln"><a href="#n395">395</a></p> +<p id="n396" class="pln"><a href="#n396">396</a></p> +<p id="n397" class="pln"><a href="#n397">397</a></p> +<p id="n398" class="pln"><a href="#n398">398</a></p> +<p id="n399" class="pln"><a href="#n399">399</a></p> +<p id="n400" class="pln"><a href="#n400">400</a></p> +<p id="n401" class="pln"><a href="#n401">401</a></p> +<p id="n402" class="pln"><a href="#n402">402</a></p> +<p id="n403" class="pln"><a href="#n403">403</a></p> +<p id="n404" class="pln"><a href="#n404">404</a></p> +<p id="n405" class="pln"><a href="#n405">405</a></p> +<p id="n406" class="stm mis"><a href="#n406">406</a></p> +<p id="n407" class="pln"><a href="#n407">407</a></p> +<p id="n408" class="stm mis"><a href="#n408">408</a></p> +<p id="n409" class="stm mis"><a href="#n409">409</a></p> + + </td> + <td class="text"> +<p id="t1" class="stm run hide_run"><span class="key">import</span> <span class="nam">xml</span><span class="op">.</span><span class="nam">etree</span><span class="op">.</span><span class="nam">ElementTree</span> <span class="key">as</span> <span class="nam">ElementTree</span><span class="strut"> </span></p> +<p id="t2" class="pln"><span class="strut"> </span></p> +<p id="t3" class="stm run hide_run"><span class="key">from</span> <span class="nam">matplotlib</span><span class="op">.</span><span class="nam">cm</span> <span class="key">import</span> <span class="nam">jet</span> <span class="key">as</span> <span class="nam">jet_cm</span><span class="strut"> </span></p> +<p id="t4" class="stm run hide_run"><span class="key">import</span> <span class="nam">numpy</span> <span class="key">as</span> <span class="nam">np</span><span class="strut"> </span></p> +<p id="t5" class="stm run hide_run"><span class="key">import</span> <span class="nam">simplekml</span><span class="strut"> </span></p> +<p id="t6" class="pln"><span class="strut"> </span></p> +<p id="t7" class="pln"><span class="strut"> </span></p> +<p id="t8" class="stm run hide_run"><span class="key">def</span> <span class="nam">kml_linestring_coordinates</span><span class="op">(</span><span class="nam">kml_path</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t9" class="pln"> <span class="str">"""Return lat, lon coordinates from a LineString contained in a KML file</span><span class="strut"> </span></p> +<p id="t10" class="pln"><span class="strut"> </span></p> +<p id="t11" class="pln"><span class="str"> This function looks for a LineString under the coordinates tag in the</span><span class="strut"> </span></p> +<p id="t12" class="pln"><span class="str"> following structure.</span><span class="strut"> </span></p> +<p id="t13" class="pln"><span class="strut"> </span></p> +<p id="t14" class="pln"><span class="str"> <kml xmlns="http://www.opengis.net/kml/2.2" ...></span><span class="strut"> </span></p> +<p id="t15" class="pln"><span class="str"> <Document></span><span class="strut"> </span></p> +<p id="t16" class="pln"><span class="str"> <Placemark></span><span class="strut"> </span></p> +<p id="t17" class="pln"><span class="str"> <LineString></span><span class="strut"> </span></p> +<p id="t18" class="pln"><span class="str"> <coordinates></span><span class="strut"> </span></p> +<p id="t19" class="pln"><span class="str"> "lat1,lon1,z1 lat2,lon2,z2 ..."</span><span class="strut"> </span></p> +<p id="t20" class="pln"><span class="str"> </coordinates></span><span class="strut"> </span></p> +<p id="t21" class="pln"><span class="str"> </LineString></span><span class="strut"> </span></p> +<p id="t22" class="pln"><span class="str"> </Placemark></span><span class="strut"> </span></p> +<p id="t23" class="pln"><span class="str"> </Document></span><span class="strut"> </span></p> +<p id="t24" class="pln"><span class="str"> </kml></span><span class="strut"> </span></p> +<p id="t25" class="pln"><span class="strut"> </span></p> +<p id="t26" class="pln"><span class="str"> Parameters</span><span class="strut"> </span></p> +<p id="t27" class="pln"><span class="str"> ----------</span><span class="strut"> </span></p> +<p id="t28" class="pln"><span class="str"> kml_path : str</span><span class="strut"> </span></p> +<p id="t29" class="pln"><span class="str"> Path to KML file containing a LineString</span><span class="strut"> </span></p> +<p id="t30" class="pln"><span class="strut"> </span></p> +<p id="t31" class="pln"><span class="str"> Returns</span><span class="strut"> </span></p> +<p id="t32" class="pln"><span class="str"> -------</span><span class="strut"> </span></p> +<p id="t33" class="pln"><span class="str"> numpy.ndarray</span><span class="strut"> </span></p> +<p id="t34" class="pln"><span class="strut"> </span></p> +<p id="t35" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t36" class="pln"><span class="strut"> </span></p> +<p id="t37" class="stm mis"> <span class="nam">ns</span> <span class="op">=</span> <span class="op">{</span><span class="str">'og'</span><span class="op">:</span> <span class="str">'http://www.opengis.net/kml/2.2'</span><span class="op">}</span><span class="strut"> </span></p> +<p id="t38" class="pln"><span class="strut"> </span></p> +<p id="t39" class="stm mis"> <span class="nam">tree</span> <span class="op">=</span> <span class="nam">ElementTree</span><span class="op">.</span><span class="nam">parse</span><span class="op">(</span><span class="nam">kml_path</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t40" class="stm mis"> <span class="nam">xml_root</span> <span class="op">=</span> <span class="nam">tree</span><span class="op">.</span><span class="nam">getroot</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t41" class="stm mis"> <span class="nam">document</span> <span class="op">=</span> <span class="nam">xml_root</span><span class="op">.</span><span class="nam">find</span><span class="op">(</span><span class="str">'og:Document'</span><span class="op">,</span> <span class="nam">ns</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t42" class="stm mis"> <span class="nam">placemark</span> <span class="op">=</span> <span class="nam">document</span><span class="op">.</span><span class="nam">find</span><span class="op">(</span><span class="str">'og:Placemark'</span><span class="op">,</span> <span class="nam">ns</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t43" class="stm mis"> <span class="nam">linestring</span> <span class="op">=</span> <span class="nam">placemark</span><span class="op">.</span><span class="nam">find</span><span class="op">(</span><span class="str">'og:LineString'</span><span class="op">,</span> <span class="nam">ns</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t44" class="stm mis"> <span class="nam">coordinates</span> <span class="op">=</span> <span class="nam">linestring</span><span class="op">.</span><span class="nam">find</span><span class="op">(</span><span class="str">'og:coordinates'</span><span class="op">,</span> <span class="nam">ns</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t45" class="pln"><span class="strut"> </span></p> +<p id="t46" class="stm mis"> <span class="nam">list_coordinates</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t47" class="pln"> <span class="op">[</span><span class="nam">cset</span><span class="op">.</span><span class="nam">split</span><span class="op">(</span><span class="str">','</span><span class="op">)</span> <span class="key">for</span> <span class="nam">cset</span> <span class="key">in</span> <span class="nam">coordinates</span><span class="op">.</span><span class="nam">text</span><span class="op">.</span><span class="nam">strip</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">split</span><span class="op">(</span><span class="str">' '</span><span class="op">)</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t48" class="stm mis"> <span class="nam">flt_coordinates</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t49" class="pln"> <span class="op">[</span><span class="op">[</span><span class="nam">float</span><span class="op">(</span><span class="nam">cset</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="op">)</span><span class="op">,</span> <span class="nam">float</span><span class="op">(</span><span class="nam">cset</span><span class="op">[</span><span class="num">1</span><span class="op">]</span><span class="op">)</span><span class="op">]</span> <span class="key">for</span> <span class="nam">cset</span> <span class="key">in</span> <span class="nam">list_coordinates</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t50" class="pln"><span class="strut"> </span></p> +<p id="t51" class="stm mis"> <span class="key">return</span> <span class="nam">np</span><span class="op">.</span><span class="nam">array</span><span class="op">(</span><span class="nam">flt_coordinates</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t52" class="pln"><span class="strut"> </span></p> +<p id="t53" class="pln"><span class="strut"> </span></p> +<p id="t54" class="stm run hide_run"><span class="key">def</span> <span class="nam">great_circle_dist</span><span class="op">(</span><span class="nam">coordinates</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t55" class="pln"> <span class="str">"""Computes great circle distance</span><span class="strut"> </span></p> +<p id="t56" class="pln"><span class="strut"> </span></p> +<p id="t57" class="pln"><span class="str"> Parameters</span><span class="strut"> </span></p> +<p id="t58" class="pln"><span class="str"> ----------</span><span class="strut"> </span></p> +<p id="t59" class="pln"><span class="str"> coordinates : np.ndarray</span><span class="strut"> </span></p> +<p id="t60" class="pln"><span class="str"> N x 2 ndarray, with column 0 as longitude and column 1 as latitude</span><span class="strut"> </span></p> +<p id="t61" class="pln"><span class="strut"> </span></p> +<p id="t62" class="pln"><span class="str"> Returns</span><span class="strut"> </span></p> +<p id="t63" class="pln"><span class="str"> -------</span><span class="strut"> </span></p> +<p id="t64" class="pln"><span class="str"> numpy.ndarray</span><span class="strut"> </span></p> +<p id="t65" class="pln"><span class="str"> Cumulative distance of array, in meters</span><span class="strut"> </span></p> +<p id="t66" class="pln"><span class="strut"> </span></p> +<p id="t67" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t68" class="pln"><span class="strut"> </span></p> +<p id="t69" class="stm mis"> <span class="nam">LATT_COLUMN</span> <span class="op">=</span> <span class="num">1</span><span class="strut"> </span></p> +<p id="t70" class="stm mis"> <span class="nam">LONG_COLUMN</span> <span class="op">=</span> <span class="num">0</span><span class="strut"> </span></p> +<p id="t71" class="pln"><span class="strut"> </span></p> +<p id="t72" class="stm mis"> <span class="nam">rads</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">radians</span><span class="op">(</span><span class="nam">coordinates</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t73" class="pln"><span class="strut"> </span></p> +<p id="t74" class="stm mis"> <span class="nam">start_latt</span> <span class="op">=</span> <span class="nam">rads</span><span class="op">[</span><span class="op">:</span><span class="op">-</span><span class="num">1</span><span class="op">,</span> <span class="nam">LATT_COLUMN</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t75" class="stm mis"> <span class="nam">end_latt</span> <span class="op">=</span> <span class="nam">rads</span><span class="op">[</span><span class="num">1</span><span class="op">:</span><span class="op">,</span> <span class="nam">LATT_COLUMN</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t76" class="pln"><span class="strut"> </span></p> +<p id="t77" class="stm mis"> <span class="nam">d_latt</span> <span class="op">=</span> <span class="nam">end_latt</span> <span class="op">-</span> <span class="nam">start_latt</span><span class="strut"> </span></p> +<p id="t78" class="stm mis"> <span class="nam">d_long</span> <span class="op">=</span> <span class="nam">rads</span><span class="op">[</span><span class="num">1</span><span class="op">:</span><span class="op">,</span> <span class="nam">LONG_COLUMN</span><span class="op">]</span> <span class="op">-</span> <span class="nam">rads</span><span class="op">[</span><span class="op">:</span><span class="op">-</span><span class="num">1</span><span class="op">,</span> <span class="nam">LONG_COLUMN</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t79" class="pln"><span class="strut"> </span></p> +<p id="t80" class="stm mis"> <span class="nam">a</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">sin</span><span class="op">(</span><span class="nam">d_latt</span><span class="op">/</span><span class="num">2</span><span class="op">)</span><span class="op">**</span><span class="num">2</span> <span class="op">+</span> <span class="nam">np</span><span class="op">.</span><span class="nam">cos</span><span class="op">(</span><span class="nam">start_latt</span><span class="op">)</span> <span class="op">*</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t81" class="pln"> <span class="nam">np</span><span class="op">.</span><span class="nam">cos</span><span class="op">(</span><span class="nam">end_latt</span><span class="op">)</span> <span class="op">*</span> <span class="nam">np</span><span class="op">.</span><span class="nam">sin</span><span class="op">(</span><span class="nam">d_long</span><span class="op">/</span><span class="num">2</span><span class="op">)</span><span class="op">**</span><span class="num">2</span><span class="strut"> </span></p> +<p id="t82" class="stm mis"> <span class="nam">c</span> <span class="op">=</span> <span class="num">2</span> <span class="op">*</span> <span class="nam">np</span><span class="op">.</span><span class="nam">arcsin</span><span class="op">(</span><span class="nam">np</span><span class="op">.</span><span class="nam">sqrt</span><span class="op">(</span><span class="nam">a</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t83" class="pln"><span class="strut"> </span></p> +<p id="t84" class="stm mis"> <span class="nam">dist</span> <span class="op">=</span> <span class="num">6371e3</span> <span class="op">*</span> <span class="nam">c</span><span class="strut"> </span></p> +<p id="t85" class="stm mis"> <span class="nam">cum_dist</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">insert</span><span class="op">(</span><span class="nam">np</span><span class="op">.</span><span class="nam">cumsum</span><span class="op">(</span><span class="nam">dist</span><span class="op">)</span><span class="op">,</span> <span class="num">0</span><span class="op">,</span> <span class="num">0</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t86" class="pln"><span class="strut"> </span></p> +<p id="t87" class="stm mis"> <span class="key">return</span> <span class="nam">cum_dist</span><span class="strut"> </span></p> +<p id="t88" class="pln"><span class="strut"> </span></p> +<p id="t89" class="pln"><span class="strut"> </span></p> +<p id="t90" class="stm run hide_run"><span class="key">class</span> <span class="nam">FluEggKML</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t91" class="pln"> <span class="str">"""Manages KML file output for FluEgg.</span><span class="strut"> </span></p> +<p id="t92" class="pln"><span class="strut"> </span></p> +<p id="t93" class="pln"><span class="str"> Parameters</span><span class="strut"> </span></p> +<p id="t94" class="pln"><span class="str"> ----------</span><span class="strut"> </span></p> +<p id="t95" class="pln"><span class="str"> centerline_kml_path : str</span><span class="strut"> </span></p> +<p id="t96" class="pln"><span class="str"> Path to stream centerline KML. The centerline KML must have uniform</span><span class="strut"> </span></p> +<p id="t97" class="pln"><span class="str"> spacing between the points.</span><span class="strut"> </span></p> +<p id="t98" class="pln"><span class="str"> spawing_location : float</span><span class="strut"> </span></p> +<p id="t99" class="pln"><span class="str"> Streamwise distance downstream of spawning location.</span><span class="strut"> </span></p> +<p id="t100" class="pln"><span class="strut"> </span></p> +<p id="t101" class="pln"><span class="str"> Notes</span><span class="strut"> </span></p> +<p id="t102" class="pln"><span class="str"> -----</span><span class="strut"> </span></p> +<p id="t103" class="pln"><span class="str"> Particle streamwise distances are mapped to geographic coordinates under</span><span class="strut"> </span></p> +<p id="t104" class="pln"><span class="str"> the assumption the points in the centerline KML are spaced equally along</span><span class="strut"> </span></p> +<p id="t105" class="pln"><span class="str"> the streamline.</span><span class="strut"> </span></p> +<p id="t106" class="pln"><span class="strut"> </span></p> +<p id="t107" class="pln"><span class="str"> The first coordinate in the KML centerline is assumed to be the upstream-</span><span class="strut"> </span></p> +<p id="t108" class="pln"><span class="str"> most point. The streamwise distance at this point is 0.</span><span class="strut"> </span></p> +<p id="t109" class="pln"><span class="strut"> </span></p> +<p id="t110" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t111" class="pln"><span class="strut"> </span></p> +<p id="t112" class="stm run hide_run"> <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">centerline_kml_path</span><span class="op">,</span> <span class="nam">spawning_location</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t113" class="pln"> <span class="str">"""see help(self) for initialization details"""</span><span class="strut"> </span></p> +<p id="t114" class="pln"><span class="strut"> </span></p> +<p id="t115" class="pln"> <span class="com"># coordinates and stream distances corresponding to the centerline</span><span class="strut"> </span></p> +<p id="t116" class="pln"> <span class="com"># points</span><span class="strut"> </span></p> +<p id="t117" class="stm mis"> <span class="nam">coordinates</span> <span class="op">=</span> <span class="nam">kml_linestring_coordinates</span><span class="op">(</span><span class="nam">centerline_kml_path</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t118" class="pln"><span class="strut"> </span></p> +<p id="t119" class="stm mis"> <span class="nam">dist</span> <span class="op">=</span> <span class="nam">great_circle_dist</span><span class="op">(</span><span class="nam">coordinates</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t120" class="pln"><span class="strut"> </span></p> +<p id="t121" class="pln"> <span class="com"># dist, lat, lon</span><span class="strut"> </span></p> +<p id="t122" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">_centerline_coords</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">hstack</span><span class="op">(</span><span class="op">(</span><span class="nam">dist</span><span class="op">[</span><span class="op">:</span><span class="op">,</span> <span class="nam">np</span><span class="op">.</span><span class="nam">newaxis</span><span class="op">]</span><span class="op">,</span> <span class="nam">coordinates</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t123" class="pln"><span class="strut"> </span></p> +<p id="t124" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">_spawning_location</span> <span class="op">=</span> <span class="nam">spawning_location</span><span class="strut"> </span></p> +<p id="t125" class="pln"><span class="strut"> </span></p> +<p id="t126" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_add_spawning_location</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">kml</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t127" class="pln"> <span class="str">"""Add the spawning location to a KML</span><span class="strut"> </span></p> +<p id="t128" class="pln"><span class="strut"> </span></p> +<p id="t129" class="pln"><span class="str"> Parameters</span><span class="strut"> </span></p> +<p id="t130" class="pln"><span class="str"> ----------</span><span class="strut"> </span></p> +<p id="t131" class="pln"><span class="str"> kml : simplekml.Kml</span><span class="strut"> </span></p> +<p id="t132" class="pln"><span class="strut"> </span></p> +<p id="t133" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t134" class="pln"><span class="strut"> </span></p> +<p id="t135" class="stm mis"> <span class="nam">spawning_style</span> <span class="op">=</span> <span class="nam">simplekml</span><span class="op">.</span><span class="nam">Style</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t136" class="stm mis"> <span class="nam">spawning_style</span><span class="op">.</span><span class="nam">iconstyle</span><span class="op">.</span><span class="nam">icon</span><span class="op">.</span><span class="nam">href</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t137" class="pln"> <span class="str">'http://maps.google.com/mapfiles/kml/shapes/fishing.png'</span><span class="strut"> </span></p> +<p id="t138" class="stm mis"> <span class="nam">spawning_style</span><span class="op">.</span><span class="nam">iconstyle</span><span class="op">.</span><span class="nam">color</span> <span class="op">=</span> <span class="str">'ffffff00'</span><span class="strut"> </span></p> +<p id="t139" class="stm mis"> <span class="nam">spawning_style</span><span class="op">.</span><span class="nam">iconstyle</span><span class="op">.</span><span class="nam">scale</span> <span class="op">=</span> <span class="num">1.2</span><span class="strut"> </span></p> +<p id="t140" class="pln"><span class="strut"> </span></p> +<p id="t141" class="stm mis"> <span class="nam">spawning_coords</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_interpolate_points</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_spawning_location</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t142" class="pln"><span class="strut"> </span></p> +<p id="t143" class="stm mis"> <span class="nam">spawning_location</span> <span class="op">=</span> <span class="nam">kml</span><span class="op">.</span><span class="nam">newpoint</span><span class="op">(</span><span class="nam">coords</span><span class="op">=</span><span class="op">[</span><span class="nam">spawning_coords</span><span class="op">]</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t144" class="stm mis"> <span class="nam">spawning_location</span><span class="op">.</span><span class="nam">style</span> <span class="op">=</span> <span class="nam">spawning_style</span><span class="strut"> </span></p> +<p id="t145" class="pln"><span class="strut"> </span></p> +<p id="t146" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_get_point_style</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">shape</span><span class="op">,</span> <span class="nam">color</span><span class="op">,</span> <span class="nam">scale</span><span class="op">,</span> <span class="nam">alphaint</span><span class="op">=</span><span class="num">128</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t147" class="pln"><span class="strut"> </span></p> +<p id="t148" class="stm mis"> <span class="key">if</span> <span class="nam">shape</span> <span class="op">==</span> <span class="str">'dot'</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t149" class="stm mis"> <span class="nam">icon_shape</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t150" class="pln"> <span class="str">'http://maps.google.com/mapfiles/kml/shapes/shaded_dot.png'</span><span class="strut"> </span></p> +<p id="t151" class="stm mis"> <span class="key">elif</span> <span class="nam">shape</span> <span class="op">==</span> <span class="str">'square'</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t152" class="stm mis"> <span class="nam">icon_shape</span> <span class="op">=</span> <span class="str">'http://maps.google.com/mapfiles/kml/shapes/'</span> <span class="op">+</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t153" class="pln"> <span class="str">'placemark_square.png'</span><span class="strut"> </span></p> +<p id="t154" class="pln"> <span class="key">else</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t155" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="str">"Unknown shape: {}"</span><span class="op">.</span><span class="nam">format</span><span class="op">(</span><span class="nam">shape</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t156" class="pln"><span class="strut"> </span></p> +<p id="t157" class="pln"> <span class="com"># blue</span><span class="strut"> </span></p> +<p id="t158" class="stm mis"> <span class="key">if</span> <span class="nam">color</span> <span class="op">==</span> <span class="str">'b'</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t159" class="stm mis"> <span class="nam">icon_color</span> <span class="op">=</span> <span class="nam">simplekml</span><span class="op">.</span><span class="nam">Color</span><span class="op">.</span><span class="nam">blue</span><span class="strut"> </span></p> +<p id="t160" class="pln"><span class="strut"> </span></p> +<p id="t161" class="pln"> <span class="com"># red</span><span class="strut"> </span></p> +<p id="t162" class="stm mis"> <span class="key">elif</span> <span class="nam">color</span> <span class="op">==</span> <span class="str">'r'</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t163" class="stm mis"> <span class="nam">icon_color</span> <span class="op">=</span> <span class="nam">simplekml</span><span class="op">.</span><span class="nam">Color</span><span class="op">.</span><span class="nam">red</span><span class="strut"> </span></p> +<p id="t164" class="pln"><span class="strut"> </span></p> +<p id="t165" class="pln"> <span class="com"># yellow</span><span class="strut"> </span></p> +<p id="t166" class="stm mis"> <span class="key">elif</span> <span class="nam">color</span> <span class="op">==</span> <span class="str">'y'</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t167" class="stm mis"> <span class="nam">icon_color</span> <span class="op">=</span> <span class="nam">simplekml</span><span class="op">.</span><span class="nam">Color</span><span class="op">.</span><span class="nam">yellow</span><span class="strut"> </span></p> +<p id="t168" class="pln"><span class="strut"> </span></p> +<p id="t169" class="pln"> <span class="com"># magenta</span><span class="strut"> </span></p> +<p id="t170" class="stm mis"> <span class="key">elif</span> <span class="nam">color</span> <span class="op">==</span> <span class="str">'m'</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t171" class="stm mis"> <span class="nam">icon_color</span> <span class="op">=</span> <span class="nam">simplekml</span><span class="op">.</span><span class="nam">Color</span><span class="op">.</span><span class="nam">magenta</span><span class="strut"> </span></p> +<p id="t172" class="pln"><span class="strut"> </span></p> +<p id="t173" class="pln"> <span class="com"># black</span><span class="strut"> </span></p> +<p id="t174" class="stm mis"> <span class="key">elif</span> <span class="nam">color</span> <span class="op">==</span> <span class="str">'k'</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t175" class="stm mis"> <span class="nam">icon_color</span> <span class="op">=</span> <span class="nam">simplekml</span><span class="op">.</span><span class="nam">Color</span><span class="op">.</span><span class="nam">black</span><span class="strut"> </span></p> +<p id="t176" class="pln"><span class="strut"> </span></p> +<p id="t177" class="pln"> <span class="com"># assume color is passed as a KML hex value</span><span class="strut"> </span></p> +<p id="t178" class="pln"> <span class="key">else</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t179" class="stm mis"> <span class="nam">icon_color</span> <span class="op">=</span> <span class="nam">color</span><span class="strut"> </span></p> +<p id="t180" class="pln"><span class="strut"> </span></p> +<p id="t181" class="stm mis"> <span class="nam">style</span> <span class="op">=</span> <span class="nam">simplekml</span><span class="op">.</span><span class="nam">Style</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t182" class="stm mis"> <span class="nam">style</span><span class="op">.</span><span class="nam">iconstyle</span><span class="op">.</span><span class="nam">scale</span> <span class="op">=</span> <span class="nam">scale</span><span class="strut"> </span></p> +<p id="t183" class="stm mis"> <span class="nam">style</span><span class="op">.</span><span class="nam">iconstyle</span><span class="op">.</span><span class="nam">icon</span><span class="op">.</span><span class="nam">href</span> <span class="op">=</span> <span class="nam">icon_shape</span><span class="strut"> </span></p> +<p id="t184" class="stm mis"> <span class="nam">style</span><span class="op">.</span><span class="nam">iconstyle</span><span class="op">.</span><span class="nam">color</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t185" class="pln"> <span class="nam">simplekml</span><span class="op">.</span><span class="nam">Color</span><span class="op">.</span><span class="nam">changealphaint</span><span class="op">(</span><span class="nam">alphaint</span><span class="op">,</span> <span class="nam">icon_color</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t186" class="pln"><span class="strut"> </span></p> +<p id="t187" class="stm mis"> <span class="key">return</span> <span class="nam">style</span><span class="strut"> </span></p> +<p id="t188" class="pln"><span class="strut"> </span></p> +<p id="t189" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_interpolate_points</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">point_dist</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t190" class="pln"> <span class="str">"""</span><span class="strut"> </span></p> +<p id="t191" class="pln"><span class="strut"> </span></p> +<p id="t192" class="pln"><span class="str"> Parameters</span><span class="strut"> </span></p> +<p id="t193" class="pln"><span class="str"> ----------</span><span class="strut"> </span></p> +<p id="t194" class="pln"><span class="str"> point_dist : float, numpy.ndarray</span><span class="strut"> </span></p> +<p id="t195" class="pln"><span class="strut"> </span></p> +<p id="t196" class="pln"><span class="str"> Returns</span><span class="strut"> </span></p> +<p id="t197" class="pln"><span class="str"> -------</span><span class="strut"> </span></p> +<p id="t198" class="pln"><span class="str"> latitude, longitude : float, numpy.ndarray</span><span class="strut"> </span></p> +<p id="t199" class="pln"><span class="strut"> </span></p> +<p id="t200" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t201" class="pln"><span class="strut"> </span></p> +<p id="t202" class="stm mis"> <span class="nam">latitude</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">interp</span><span class="op">(</span><span class="nam">point_dist</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t203" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">_centerline_coords</span><span class="op">[</span><span class="op">:</span><span class="op">,</span> <span class="num">0</span><span class="op">]</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t204" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">_centerline_coords</span><span class="op">[</span><span class="op">:</span><span class="op">,</span> <span class="num">1</span><span class="op">]</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t205" class="stm mis"> <span class="nam">longitude</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">interp</span><span class="op">(</span><span class="nam">point_dist</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t206" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">_centerline_coords</span><span class="op">[</span><span class="op">:</span><span class="op">,</span> <span class="num">0</span><span class="op">]</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t207" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">_centerline_coords</span><span class="op">[</span><span class="op">:</span><span class="op">,</span> <span class="num">2</span><span class="op">]</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t208" class="pln"><span class="strut"> </span></p> +<p id="t209" class="stm mis"> <span class="key">return</span> <span class="nam">latitude</span><span class="op">,</span> <span class="nam">longitude</span><span class="strut"> </span></p> +<p id="t210" class="pln"><span class="strut"> </span></p> +<p id="t211" class="stm run hide_run"> <span class="key">def</span> <span class="nam">kml_particle_locations</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">point_dist</span><span class="op">,</span> <span class="nam">depth_fraction</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t212" class="pln"> <span class="str">"""KML text containing georeferenced points</span><span class="strut"> </span></p> +<p id="t213" class="pln"><span class="strut"> </span></p> +<p id="t214" class="pln"><span class="str"> Parameters</span><span class="strut"> </span></p> +<p id="t215" class="pln"><span class="str"> ----------</span><span class="strut"> </span></p> +<p id="t216" class="pln"><span class="str"> point_dist : numpy.ndarray</span><span class="strut"> </span></p> +<p id="t217" class="pln"><span class="str"> Stream distance of points (distance downstream).</span><span class="strut"> </span></p> +<p id="t218" class="pln"><span class="str"> depth_fraction : numpy.ndarray</span><span class="strut"> </span></p> +<p id="t219" class="pln"><span class="str"> Depth fraction of points. Depth fraction is the fractional height</span><span class="strut"> </span></p> +<p id="t220" class="pln"><span class="strut"> </span></p> +<p id="t221" class="pln"><span class="str"> Returns</span><span class="strut"> </span></p> +<p id="t222" class="pln"><span class="str"> -------</span><span class="strut"> </span></p> +<p id="t223" class="pln"><span class="str"> str</span><span class="strut"> </span></p> +<p id="t224" class="pln"><span class="strut"> </span></p> +<p id="t225" class="pln"><span class="str"> Notes</span><span class="strut"> </span></p> +<p id="t226" class="pln"><span class="str"> -----</span><span class="strut"> </span></p> +<p id="t227" class="pln"><span class="str"> Particles with depth fractions greater than or equal to 0.05 are</span><span class="strut"> </span></p> +<p id="t228" class="pln"><span class="str"> shown as suspended particles.</span><span class="strut"> </span></p> +<p id="t229" class="pln"><span class="strut"> </span></p> +<p id="t230" class="pln"><span class="str"> See also</span><span class="strut"> </span></p> +<p id="t231" class="pln"><span class="str"> --------</span><span class="strut"> </span></p> +<p id="t232" class="pln"><span class="str"> write_locations : Write points to a KML file</span><span class="strut"> </span></p> +<p id="t233" class="pln"><span class="strut"> </span></p> +<p id="t234" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t235" class="pln"><span class="strut"> </span></p> +<p id="t236" class="pln"> <span class="com"># eggs greater than suspended_depth_fraction are shown as suspended</span><span class="strut"> </span></p> +<p id="t237" class="stm mis"> <span class="nam">suspended_depth_fraction</span> <span class="op">=</span> <span class="num">0.05</span><span class="strut"> </span></p> +<p id="t238" class="pln"><span class="strut"> </span></p> +<p id="t239" class="stm mis"> <span class="key">if</span> <span class="nam">point_dist</span><span class="op">.</span><span class="nam">ndim</span> <span class="op">!=</span> <span class="num">1</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t240" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="str">"point_dist must be a one-dimensional array"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t241" class="pln"><span class="strut"> </span></p> +<p id="t242" class="stm mis"> <span class="key">if</span> <span class="nam">depth_fraction</span><span class="op">.</span><span class="nam">ndim</span> <span class="op">!=</span> <span class="num">1</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t243" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="str">"depth_fraction must be a one-dimensional array"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t244" class="pln"><span class="strut"> </span></p> +<p id="t245" class="stm mis"> <span class="key">if</span> <span class="key">not</span> <span class="nam">point_dist</span><span class="op">.</span><span class="nam">shape</span> <span class="op">==</span> <span class="nam">depth_fraction</span><span class="op">.</span><span class="nam">shape</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t246" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="str">"point_dist and depth_fraction must have "</span> <span class="op">+</span><span class="strut"> </span></p> +<p id="t247" class="pln"> <span class="str">"the same shape"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t248" class="pln"><span class="strut"> </span></p> +<p id="t249" class="stm mis"> <span class="nam">suspended_index</span> <span class="op">=</span> <span class="nam">suspended_depth_fraction</span> <span class="op"><=</span> <span class="nam">depth_fraction</span><span class="strut"> </span></p> +<p id="t250" class="pln"><span class="strut"> </span></p> +<p id="t251" class="stm mis"> <span class="nam">latitude</span><span class="op">,</span> <span class="nam">longitude</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_interpolate_points</span><span class="op">(</span><span class="nam">point_dist</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t252" class="pln"><span class="strut"> </span></p> +<p id="t253" class="stm mis"> <span class="nam">kml</span> <span class="op">=</span> <span class="nam">simplekml</span><span class="op">.</span><span class="nam">Kml</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t254" class="pln"><span class="strut"> </span></p> +<p id="t255" class="stm mis"> <span class="nam">point_shape</span> <span class="op">=</span> <span class="str">'dot'</span><span class="strut"> </span></p> +<p id="t256" class="stm mis"> <span class="nam">point_scale</span> <span class="op">=</span> <span class="num">0.4</span><span class="strut"> </span></p> +<p id="t257" class="stm mis"> <span class="nam">suspended_color</span> <span class="op">=</span> <span class="str">'y'</span><span class="strut"> </span></p> +<p id="t258" class="stm mis"> <span class="nam">bottom_color</span> <span class="op">=</span> <span class="str">'m'</span><span class="strut"> </span></p> +<p id="t259" class="pln"><span class="strut"> </span></p> +<p id="t260" class="pln"> <span class="com"># add suspended points</span><span class="strut"> </span></p> +<p id="t261" class="stm mis"> <span class="nam">style</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_get_point_style</span><span class="op">(</span><span class="nam">point_shape</span><span class="op">,</span> <span class="nam">suspended_color</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t262" class="pln"> <span class="nam">point_scale</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t263" class="stm mis"> <span class="key">for</span> <span class="nam">lat</span><span class="op">,</span> <span class="nam">lon</span> <span class="key">in</span> <span class="nam">zip</span><span class="op">(</span><span class="nam">latitude</span><span class="op">[</span><span class="nam">suspended_index</span><span class="op">]</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t264" class="pln"> <span class="nam">longitude</span><span class="op">[</span><span class="nam">suspended_index</span><span class="op">]</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t265" class="stm mis"> <span class="nam">pnt</span> <span class="op">=</span> <span class="nam">kml</span><span class="op">.</span><span class="nam">newpoint</span><span class="op">(</span><span class="nam">coords</span><span class="op">=</span><span class="op">[</span><span class="op">(</span><span class="nam">lat</span><span class="op">,</span> <span class="nam">lon</span><span class="op">)</span><span class="op">]</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t266" class="stm mis"> <span class="nam">pnt</span><span class="op">.</span><span class="nam">style</span> <span class="op">=</span> <span class="nam">style</span><span class="strut"> </span></p> +<p id="t267" class="pln"><span class="strut"> </span></p> +<p id="t268" class="pln"> <span class="com"># add non-suspended (bottom) points</span><span class="strut"> </span></p> +<p id="t269" class="stm mis"> <span class="nam">style</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_get_point_style</span><span class="op">(</span><span class="nam">point_shape</span><span class="op">,</span> <span class="nam">bottom_color</span><span class="op">,</span> <span class="nam">point_scale</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t270" class="stm mis"> <span class="key">for</span> <span class="nam">lat</span><span class="op">,</span> <span class="nam">lon</span> <span class="key">in</span> <span class="nam">zip</span><span class="op">(</span><span class="nam">latitude</span><span class="op">[</span><span class="op">~</span><span class="nam">suspended_index</span><span class="op">]</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t271" class="pln"> <span class="nam">longitude</span><span class="op">[</span><span class="op">~</span><span class="nam">suspended_index</span><span class="op">]</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t272" class="stm mis"> <span class="nam">pnt</span> <span class="op">=</span> <span class="nam">kml</span><span class="op">.</span><span class="nam">newpoint</span><span class="op">(</span><span class="nam">coords</span><span class="op">=</span><span class="op">[</span><span class="op">(</span><span class="nam">lat</span><span class="op">,</span> <span class="nam">lon</span><span class="op">)</span><span class="op">]</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t273" class="stm mis"> <span class="nam">pnt</span><span class="op">.</span><span class="nam">style</span> <span class="op">=</span> <span class="nam">style</span><span class="strut"> </span></p> +<p id="t274" class="pln"><span class="strut"> </span></p> +<p id="t275" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">_add_spawning_location</span><span class="op">(</span><span class="nam">kml</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t276" class="pln"><span class="strut"> </span></p> +<p id="t277" class="stm mis"> <span class="key">return</span> <span class="nam">kml</span><span class="op">.</span><span class="nam">kml</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t278" class="pln"><span class="strut"> </span></p> +<p id="t279" class="stm run hide_run"> <span class="key">def</span> <span class="nam">kml_spawning_location</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t280" class="pln"> <span class="str">"""KML text containing georeferenced spawning location</span><span class="strut"> </span></p> +<p id="t281" class="pln"><span class="strut"> </span></p> +<p id="t282" class="pln"><span class="str"> Returns</span><span class="strut"> </span></p> +<p id="t283" class="pln"><span class="str"> -------</span><span class="strut"> </span></p> +<p id="t284" class="pln"><span class="str"> str</span><span class="strut"> </span></p> +<p id="t285" class="pln"><span class="strut"> </span></p> +<p id="t286" class="pln"><span class="str"> See also</span><span class="strut"> </span></p> +<p id="t287" class="pln"><span class="str"> --------</span><span class="strut"> </span></p> +<p id="t288" class="pln"><span class="str"> write_locations : Write points to a KML file</span><span class="strut"> </span></p> +<p id="t289" class="pln"><span class="strut"> </span></p> +<p id="t290" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t291" class="pln"><span class="strut"> </span></p> +<p id="t292" class="stm mis"> <span class="nam">kml</span> <span class="op">=</span> <span class="nam">simplekml</span><span class="op">.</span><span class="nam">Kml</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t293" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">_add_spawning_location</span><span class="op">(</span><span class="nam">kml</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t294" class="pln"><span class="strut"> </span></p> +<p id="t295" class="stm mis"> <span class="key">return</span> <span class="nam">kml</span><span class="op">.</span><span class="nam">kml</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t296" class="pln"><span class="strut"> </span></p> +<p id="t297" class="stm run hide_run"> <span class="key">def</span> <span class="nam">kml_quantiles</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">point_dist</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t298" class="pln"> <span class="str">"""KML text containing georeferenced quantiles of particle locations.</span><span class="strut"> </span></p> +<p id="t299" class="pln"><span class="strut"> </span></p> +<p id="t300" class="pln"><span class="str"> Parameters</span><span class="strut"> </span></p> +<p id="t301" class="pln"><span class="str"> ----------</span><span class="strut"> </span></p> +<p id="t302" class="pln"><span class="str"> point_dist : numpy.ndarray</span><span class="strut"> </span></p> +<p id="t303" class="pln"><span class="str"> Stream distance of points (distance downstream).</span><span class="strut"> </span></p> +<p id="t304" class="pln"><span class="strut"> </span></p> +<p id="t305" class="pln"><span class="str"> Returns</span><span class="strut"> </span></p> +<p id="t306" class="pln"><span class="str"> -------</span><span class="strut"> </span></p> +<p id="t307" class="pln"><span class="str"> str</span><span class="strut"> </span></p> +<p id="t308" class="pln"><span class="strut"> </span></p> +<p id="t309" class="pln"><span class="str"> Notes</span><span class="strut"> </span></p> +<p id="t310" class="pln"><span class="str"> -----</span><span class="strut"> </span></p> +<p id="t311" class="pln"><span class="str"> Locations for the 0, 0.10, 0.25, 0.50, 0.75, 0.90, and 1 quantiles are</span><span class="strut"> </span></p> +<p id="t312" class="pln"><span class="str"> included in the KML string.</span><span class="strut"> </span></p> +<p id="t313" class="pln"><span class="strut"> </span></p> +<p id="t314" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t315" class="pln"><span class="strut"> </span></p> +<p id="t316" class="stm mis"> <span class="nam">kml</span> <span class="op">=</span> <span class="nam">simplekml</span><span class="op">.</span><span class="nam">Kml</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t317" class="pln"><span class="strut"> </span></p> +<p id="t318" class="stm mis"> <span class="nam">quantiles</span> <span class="op">=</span> <span class="op">[</span><span class="num">0</span><span class="op">,</span> <span class="num">0.10</span><span class="op">,</span> <span class="num">0.25</span><span class="op">,</span> <span class="num">0.50</span><span class="op">,</span> <span class="num">0.75</span><span class="op">,</span> <span class="num">0.90</span><span class="op">,</span> <span class="num">1.</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t319" class="pln"><span class="strut"> </span></p> +<p id="t320" class="stm mis"> <span class="nam">computed_quantiles</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">quantile</span><span class="op">(</span><span class="nam">point_dist</span><span class="op">,</span> <span class="nam">quantiles</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t321" class="pln"> <span class="nam">interpolation</span><span class="op">=</span><span class="str">'nearest'</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t322" class="pln"><span class="strut"> </span></p> +<p id="t323" class="stm mis"> <span class="nam">la</span><span class="op">,</span> <span class="nam">lo</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_interpolate_points</span><span class="op">(</span><span class="nam">computed_quantiles</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t324" class="pln"><span class="strut"> </span></p> +<p id="t325" class="stm mis"> <span class="key">for</span> <span class="nam">i</span><span class="op">,</span> <span class="op">(</span><span class="nam">lat</span><span class="op">,</span> <span class="nam">lon</span><span class="op">)</span> <span class="key">in</span> <span class="nam">enumerate</span><span class="op">(</span><span class="nam">zip</span><span class="op">(</span><span class="nam">la</span><span class="op">,</span> <span class="nam">lo</span><span class="op">)</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t326" class="stm mis"> <span class="nam">q</span> <span class="op">=</span> <span class="nam">quantiles</span><span class="op">[</span><span class="nam">i</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t327" class="stm mis"> <span class="nam">pnt</span> <span class="op">=</span> <span class="nam">kml</span><span class="op">.</span><span class="nam">newpoint</span><span class="op">(</span><span class="nam">name</span><span class="op">=</span><span class="nam">str</span><span class="op">(</span><span class="nam">q</span><span class="op">)</span><span class="op">,</span> <span class="nam">coords</span><span class="op">=</span><span class="op">[</span><span class="op">(</span><span class="nam">lat</span><span class="op">,</span> <span class="nam">lon</span><span class="op">)</span><span class="op">]</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t328" class="stm mis"> <span class="nam">X</span> <span class="op">=</span> <span class="num">1</span> <span class="op">-</span> <span class="nam">abs</span><span class="op">(</span><span class="nam">q</span> <span class="op">-</span> <span class="num">0.5</span><span class="op">)</span><span class="op">/</span><span class="num">0.5</span><span class="strut"> </span></p> +<p id="t329" class="stm mis"> <span class="nam">rgba</span> <span class="op">=</span> <span class="nam">jet_cm</span><span class="op">(</span><span class="nam">X</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t330" class="stm mis"> <span class="nam">red_value</span> <span class="op">=</span> <span class="nam">int</span><span class="op">(</span><span class="nam">rgba</span><span class="op">[</span><span class="num">0</span><span class="op">]</span> <span class="op">*</span> <span class="num">255</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t331" class="stm mis"> <span class="nam">green_value</span> <span class="op">=</span> <span class="nam">int</span><span class="op">(</span><span class="nam">rgba</span><span class="op">[</span><span class="num">1</span><span class="op">]</span> <span class="op">*</span> <span class="num">255</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t332" class="stm mis"> <span class="nam">blue_value</span> <span class="op">=</span> <span class="nam">int</span><span class="op">(</span><span class="nam">rgba</span><span class="op">[</span><span class="num">2</span><span class="op">]</span> <span class="op">*</span> <span class="num">255</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t333" class="stm mis"> <span class="nam">color</span> <span class="op">=</span> <span class="nam">simplekml</span><span class="op">.</span><span class="nam">Color</span><span class="op">.</span><span class="nam">rgb</span><span class="op">(</span><span class="strut"> </span></p> +<p id="t334" class="pln"> <span class="nam">red_value</span><span class="op">,</span> <span class="nam">green_value</span><span class="op">,</span> <span class="nam">blue_value</span><span class="op">,</span> <span class="num">255</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t335" class="stm mis"> <span class="nam">style</span> <span class="op">=</span> <span class="nam">simplekml</span><span class="op">.</span><span class="nam">Style</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t336" class="stm mis"> <span class="nam">style</span><span class="op">.</span><span class="nam">iconstyle</span><span class="op">.</span><span class="nam">scale</span> <span class="op">=</span> <span class="num">1.25</span><span class="strut"> </span></p> +<p id="t337" class="stm mis"> <span class="nam">style</span><span class="op">.</span><span class="nam">iconstyle</span><span class="op">.</span><span class="nam">color</span> <span class="op">=</span> <span class="nam">color</span><span class="strut"> </span></p> +<p id="t338" class="stm mis"> <span class="nam">style</span><span class="op">.</span><span class="nam">iconstyle</span><span class="op">.</span><span class="nam">icon</span><span class="op">.</span><span class="nam">href</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t339" class="pln"> <span class="str">'http://maps.google.com/mapfiles/kml/shapes/'</span> <span class="op">+</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t340" class="pln"> <span class="str">'placemark_square.png'</span><span class="strut"> </span></p> +<p id="t341" class="stm mis"> <span class="nam">pnt</span><span class="op">.</span><span class="nam">style</span> <span class="op">=</span> <span class="nam">style</span><span class="strut"> </span></p> +<p id="t342" class="pln"><span class="strut"> </span></p> +<p id="t343" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">_add_spawning_location</span><span class="op">(</span><span class="nam">kml</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t344" class="pln"><span class="strut"> </span></p> +<p id="t345" class="stm mis"> <span class="key">return</span> <span class="nam">kml</span><span class="op">.</span><span class="nam">kml</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t346" class="pln"><span class="strut"> </span></p> +<p id="t347" class="stm run hide_run"> <span class="key">def</span> <span class="nam">write_locations</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">point_dist</span><span class="op">,</span> <span class="nam">depth_fraction</span><span class="op">,</span> <span class="nam">kml_path</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t348" class="pln"> <span class="str">"""Write particle locations to a KML file</span><span class="strut"> </span></p> +<p id="t349" class="pln"><span class="strut"> </span></p> +<p id="t350" class="pln"><span class="str"> Parameters</span><span class="strut"> </span></p> +<p id="t351" class="pln"><span class="str"> ----------</span><span class="strut"> </span></p> +<p id="t352" class="pln"><span class="str"> point_dist : numpy.ndarray</span><span class="strut"> </span></p> +<p id="t353" class="pln"><span class="str"> Stream distance of points (distance downstream).</span><span class="strut"> </span></p> +<p id="t354" class="pln"><span class="str"> depth_fraction : numpy.ndarray</span><span class="strut"> </span></p> +<p id="t355" class="pln"><span class="str"> Depth fraction of points. Depth fraction is the fractional height</span><span class="strut"> </span></p> +<p id="t356" class="pln"><span class="str"> above the bed.</span><span class="strut"> </span></p> +<p id="t357" class="pln"><span class="str"> kml_path : str</span><span class="strut"> </span></p> +<p id="t358" class="pln"><span class="str"> Path to write KML file to.</span><span class="strut"> </span></p> +<p id="t359" class="pln"><span class="strut"> </span></p> +<p id="t360" class="pln"><span class="str"> Notes</span><span class="strut"> </span></p> +<p id="t361" class="pln"><span class="str"> -----</span><span class="strut"> </span></p> +<p id="t362" class="pln"><span class="str"> Particles with depth fractions greater than or equal to 0.05 are</span><span class="strut"> </span></p> +<p id="t363" class="pln"><span class="str"> shown as suspended particles.</span><span class="strut"> </span></p> +<p id="t364" class="pln"><span class="strut"> </span></p> +<p id="t365" class="pln"><span class="str"> See also</span><span class="strut"> </span></p> +<p id="t366" class="pln"><span class="str"> --------</span><span class="strut"> </span></p> +<p id="t367" class="pln"><span class="str"> kml_particle_locations : KML text containing georeferenced particle</span><span class="strut"> </span></p> +<p id="t368" class="pln"><span class="str"> locations.</span><span class="strut"> </span></p> +<p id="t369" class="pln"><span class="strut"> </span></p> +<p id="t370" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t371" class="pln"><span class="strut"> </span></p> +<p id="t372" class="stm mis"> <span class="nam">kml</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">kml_particle_locations</span><span class="op">(</span><span class="nam">point_dist</span><span class="op">,</span> <span class="nam">depth_fraction</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t373" class="pln"><span class="strut"> </span></p> +<p id="t374" class="stm mis"> <span class="key">with</span> <span class="nam">open</span><span class="op">(</span><span class="nam">kml_path</span><span class="op">,</span> <span class="str">'w'</span><span class="op">)</span> <span class="key">as</span> <span class="nam">f</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t375" class="stm mis"> <span class="nam">f</span><span class="op">.</span><span class="nam">writelines</span><span class="op">(</span><span class="nam">kml</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t376" class="pln"><span class="strut"> </span></p> +<p id="t377" class="stm run hide_run"> <span class="key">def</span> <span class="nam">write_spawning_location</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">kml_path</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t378" class="pln"> <span class="str">"""Write spawning location to a KML file</span><span class="strut"> </span></p> +<p id="t379" class="pln"><span class="strut"> </span></p> +<p id="t380" class="pln"><span class="str"> Parameters</span><span class="strut"> </span></p> +<p id="t381" class="pln"><span class="str"> ----------</span><span class="strut"> </span></p> +<p id="t382" class="pln"><span class="str"> kml_path : str</span><span class="strut"> </span></p> +<p id="t383" class="pln"><span class="strut"> </span></p> +<p id="t384" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t385" class="pln"><span class="strut"> </span></p> +<p id="t386" class="stm mis"> <span class="nam">kml</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">kml_spawning_location</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t387" class="pln"><span class="strut"> </span></p> +<p id="t388" class="stm mis"> <span class="key">with</span> <span class="nam">open</span><span class="op">(</span><span class="nam">kml_path</span><span class="op">,</span> <span class="str">'w'</span><span class="op">)</span> <span class="key">as</span> <span class="nam">f</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t389" class="stm mis"> <span class="nam">f</span><span class="op">.</span><span class="nam">writelines</span><span class="op">(</span><span class="nam">kml</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t390" class="pln"><span class="strut"> </span></p> +<p id="t391" class="stm run hide_run"> <span class="key">def</span> <span class="nam">write_quantiles</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">point_dist</span><span class="op">,</span> <span class="nam">kml_path</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t392" class="pln"> <span class="str">"""</span><span class="strut"> </span></p> +<p id="t393" class="pln"><span class="strut"> </span></p> +<p id="t394" class="pln"><span class="str"> Parameters</span><span class="strut"> </span></p> +<p id="t395" class="pln"><span class="str"> ----------</span><span class="strut"> </span></p> +<p id="t396" class="pln"><span class="str"> point_dist : numpy.ndarray</span><span class="strut"> </span></p> +<p id="t397" class="pln"><span class="str"> kml_path : str</span><span class="strut"> </span></p> +<p id="t398" class="pln"><span class="strut"> </span></p> +<p id="t399" class="pln"><span class="str"> See also</span><span class="strut"> </span></p> +<p id="t400" class="pln"><span class="str"> --------</span><span class="strut"> </span></p> +<p id="t401" class="pln"><span class="str"> kml_quantiles : KML text containing georeferenced quantiles of particle</span><span class="strut"> </span></p> +<p id="t402" class="pln"><span class="str"> locations.</span><span class="strut"> </span></p> +<p id="t403" class="pln"><span class="strut"> </span></p> +<p id="t404" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t405" class="pln"><span class="strut"> </span></p> +<p id="t406" class="stm mis"> <span class="nam">kml</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">kml_quantiles</span><span class="op">(</span><span class="nam">point_dist</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t407" class="pln"><span class="strut"> </span></p> +<p id="t408" class="stm mis"> <span class="key">with</span> <span class="nam">open</span><span class="op">(</span><span class="nam">kml_path</span><span class="op">,</span> <span class="str">'w'</span><span class="op">)</span> <span class="key">as</span> <span class="nam">f</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t409" class="stm mis"> <span class="nam">f</span><span class="op">.</span><span class="nam">writelines</span><span class="op">(</span><span class="nam">kml</span><span class="op">)</span><span class="strut"> </span></p> + + </td> + </tr> + </table> +</div> + +<div id="footer"> + <div class="content"> + <p> + <a class="nav" href="index.html">« index</a> <a class="nav" href="https://coverage.readthedocs.io">coverage.py v4.5.3</a>, + created at 2019-07-09 15:15 + </p> + </div> +</div> + +</body> +</html> diff --git a/coverage_report/fluegg_random_py.html b/coverage_report/fluegg_random_py.html new file mode 100644 index 0000000..1726c11 --- /dev/null +++ b/coverage_report/fluegg_random_py.html @@ -0,0 +1,271 @@ + + + +<!DOCTYPE html> +<html> +<head> + <meta http-equiv="Content-Type" content="text/html; charset=utf-8"> + + + <meta http-equiv="X-UA-Compatible" content="IE=emulateIE7" /> + <title>Coverage for fluegg\random.py: 50%</title> + <link rel="stylesheet" href="style.css" type="text/css"> + + <script type="text/javascript" src="jquery.min.js"></script> + <script type="text/javascript" src="jquery.hotkeys.js"></script> + <script type="text/javascript" src="jquery.isonscreen.js"></script> + <script type="text/javascript" src="coverage_html.js"></script> + <script type="text/javascript"> + jQuery(document).ready(coverage.pyfile_ready); + </script> +</head> +<body class="pyfile"> + +<div id="header"> + <div class="content"> + <h1>Coverage for <b>fluegg\random.py</b> : + <span class="pc_cov">50%</span> + </h1> + + <img id="keyboard_icon" src="keybd_closed.png" alt="Show keyboard shortcuts" /> + + <h2 class="stats"> + 36 statements + <span class="run hide_run shortkey_r button_toggle_run">18 run</span> + <span class="mis shortkey_m button_toggle_mis">18 missing</span> + <span class="exc shortkey_x button_toggle_exc">0 excluded</span> + + + </h2> + </div> +</div> + +<div class="help_panel"> + <img id="panel_icon" src="keybd_open.png" alt="Hide keyboard shortcuts" /> + <p class="legend">Hot-keys on this page</p> + <div> + <p class="keyhelp"> + <span class="key">r</span> + <span class="key">m</span> + <span class="key">x</span> + <span class="key">p</span> toggle line displays + </p> + <p class="keyhelp"> + <span class="key">j</span> + <span class="key">k</span> next/prev highlighted chunk + </p> + <p class="keyhelp"> + <span class="key">0</span> (zero) top of page + </p> + <p class="keyhelp"> + <span class="key">1</span> (one) first highlighted chunk + </p> + </div> +</div> + +<div id="source"> + <table> + <tr> + <td class="linenos"> +<p id="n1" class="stm run hide_run"><a href="#n1">1</a></p> +<p id="n2" class="pln"><a href="#n2">2</a></p> +<p id="n3" class="stm run hide_run"><a href="#n3">3</a></p> +<p id="n4" class="stm run hide_run"><a href="#n4">4</a></p> +<p id="n5" class="pln"><a href="#n5">5</a></p> +<p id="n6" class="pln"><a href="#n6">6</a></p> +<p id="n7" class="stm run hide_run"><a href="#n7">7</a></p> +<p id="n8" class="pln"><a href="#n8">8</a></p> +<p id="n9" class="stm run hide_run"><a href="#n9">9</a></p> +<p id="n10" class="pln"><a href="#n10">10</a></p> +<p id="n11" class="stm mis"><a href="#n11">11</a></p> +<p id="n12" class="pln"><a href="#n12">12</a></p> +<p id="n13" class="pln"><a href="#n13">13</a></p> +<p id="n14" class="stm run hide_run"><a href="#n14">14</a></p> +<p id="n15" class="pln"><a href="#n15">15</a></p> +<p id="n16" class="pln"><a href="#n16">16</a></p> +<p id="n17" class="pln"><a href="#n17">17</a></p> +<p id="n18" class="pln"><a href="#n18">18</a></p> +<p id="n19" class="stm run hide_run"><a href="#n19">19</a></p> +<p id="n20" class="pln"><a href="#n20">20</a></p> +<p id="n21" class="pln"><a href="#n21">21</a></p> +<p id="n22" class="pln"><a href="#n22">22</a></p> +<p id="n23" class="pln"><a href="#n23">23</a></p> +<p id="n24" class="pln"><a href="#n24">24</a></p> +<p id="n25" class="pln"><a href="#n25">25</a></p> +<p id="n26" class="pln"><a href="#n26">26</a></p> +<p id="n27" class="stm run hide_run"><a href="#n27">27</a></p> +<p id="n28" class="pln"><a 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href="#n46">46</a></p> +<p id="n47" class="pln"><a href="#n47">47</a></p> +<p id="n48" class="stm run hide_run"><a href="#n48">48</a></p> +<p id="n49" class="pln"><a href="#n49">49</a></p> +<p id="n50" class="pln"><a href="#n50">50</a></p> +<p id="n51" class="pln"><a href="#n51">51</a></p> +<p id="n52" class="pln"><a href="#n52">52</a></p> +<p id="n53" class="pln"><a href="#n53">53</a></p> +<p id="n54" class="pln"><a href="#n54">54</a></p> +<p id="n55" class="pln"><a href="#n55">55</a></p> +<p id="n56" class="pln"><a href="#n56">56</a></p> +<p id="n57" class="pln"><a href="#n57">57</a></p> +<p id="n58" class="pln"><a href="#n58">58</a></p> +<p id="n59" class="pln"><a href="#n59">59</a></p> +<p id="n60" class="stm run hide_run"><a href="#n60">60</a></p> +<p id="n61" class="pln"><a href="#n61">61</a></p> +<p id="n62" class="stm mis"><a href="#n62">62</a></p> +<p id="n63" class="stm mis"><a href="#n63">63</a></p> +<p id="n64" class="pln"><a href="#n64">64</a></p> +<p id="n65" class="stm mis"><a href="#n65">65</a></p> +<p id="n66" class="stm mis"><a href="#n66">66</a></p> +<p id="n67" class="pln"><a href="#n67">67</a></p> +<p id="n68" class="stm run hide_run"><a href="#n68">68</a></p> +<p id="n69" class="pln"><a href="#n69">69</a></p> +<p id="n70" class="stm mis"><a href="#n70">70</a></p> +<p id="n71" class="stm mis"><a href="#n71">71</a></p> +<p id="n72" class="pln"><a href="#n72">72</a></p> +<p id="n73" class="stm mis"><a href="#n73">73</a></p> +<p id="n74" class="pln"><a href="#n74">74</a></p> +<p id="n75" class="stm mis"><a href="#n75">75</a></p> +<p id="n76" class="pln"><a href="#n76">76</a></p> +<p id="n77" class="stm run hide_run"><a href="#n77">77</a></p> +<p id="n78" class="pln"><a href="#n78">78</a></p> +<p id="n79" class="stm mis"><a href="#n79">79</a></p> +<p id="n80" class="stm mis"><a href="#n80">80</a></p> +<p id="n81" class="pln"><a href="#n81">81</a></p> +<p id="n82" class="stm mis"><a href="#n82">82</a></p> +<p id="n83" class="stm mis"><a href="#n83">83</a></p> +<p id="n84" class="pln"><a href="#n84">84</a></p> +<p id="n85" class="pln"><a href="#n85">85</a></p> +<p id="n86" class="stm mis"><a href="#n86">86</a></p> +<p id="n87" class="stm mis"><a href="#n87">87</a></p> +<p id="n88" class="pln"><a href="#n88">88</a></p> +<p id="n89" class="stm mis"><a href="#n89">89</a></p> +<p id="n90" class="pln"><a href="#n90">90</a></p> +<p id="n91" class="stm mis"><a href="#n91">91</a></p> + + </td> + <td class="text"> +<p id="t1" class="stm run hide_run"><span class="key">from</span> <span class="nam">abc</span> <span class="key">import</span> <span class="nam">abstractmethod</span><span class="strut"> </span></p> +<p id="t2" class="pln"><span class="strut"> </span></p> +<p id="t3" class="stm run hide_run"><span class="key">import</span> <span class="nam">h5py</span><span class="strut"> </span></p> +<p id="t4" class="stm run hide_run"><span class="key">import</span> <span class="nam">numpy</span> <span class="key">as</span> <span class="nam">np</span><span class="strut"> </span></p> +<p id="t5" class="pln"><span class="strut"> </span></p> +<p id="t6" class="pln"><span class="strut"> </span></p> +<p id="t7" class="stm run hide_run"><span class="key">class</span> <span class="nam">RandomNumbers</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t8" class="pln"><span class="strut"> </span></p> +<p id="t9" class="stm run hide_run"> <span class="op">@</span><span class="nam">abstractmethod</span><span class="strut"> </span></p> +<p id="t10" class="pln"> <span class="key">def</span> <span class="nam">random</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">mean</span><span class="op">,</span> <span class="nam">std</span><span class="op">,</span> <span class="nam">size</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t11" class="stm mis"> <span class="key">raise</span> <span class="nam">NotImplementedError</span><span class="strut"> </span></p> +<p id="t12" class="pln"><span class="strut"> </span></p> +<p id="t13" class="pln"><span class="strut"> </span></p> +<p id="t14" class="stm run hide_run"><span class="key">class</span> <span class="nam">NormalRandomNumbers</span><span class="op">(</span><span class="nam">RandomNumbers</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t15" class="pln"> <span class="str">"""Returns normally distributed random numbers.</span><span class="strut"> </span></p> +<p id="t16" class="pln"><span class="strut"> </span></p> +<p id="t17" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t18" class="pln"><span class="strut"> </span></p> +<p id="t19" class="stm run hide_run"> <span class="key">def</span> <span class="nam">random</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">mean</span><span class="op">,</span> <span class="nam">std</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t20" class="pln"> <span class="str">"""Returns a normally distributed random number</span><span class="strut"> </span></p> +<p id="t21" class="pln"><span class="strut"> </span></p> +<p id="t22" class="pln"><span class="str"> Notes</span><span class="strut"> </span></p> +<p id="t23" class="pln"><span class="str"> -----</span><span class="strut"> </span></p> +<p id="t24" class="pln"><span class="str"> Calls numpy.random.normal for random numbers</span><span class="strut"> </span></p> +<p id="t25" class="pln"><span class="strut"> </span></p> +<p id="t26" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t27" class="stm run hide_run"> <span class="key">return</span> <span class="nam">np</span><span class="op">.</span><span class="nam">random</span><span class="op">.</span><span class="nam">normal</span><span class="op">(</span><span class="nam">loc</span><span class="op">=</span><span class="nam">mean</span><span class="op">,</span> <span class="nam">scale</span><span class="op">=</span><span class="nam">std</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t28" class="pln"><span class="strut"> </span></p> +<p id="t29" class="stm run hide_run"> <span class="key">def</span> <span class="nam">random_array</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">mean</span><span class="op">,</span> <span class="nam">std</span><span class="op">,</span> <span class="nam">size</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t30" class="pln"> <span class="str">"""Returns an array of normally distributed random numbers</span><span class="strut"> </span></p> +<p id="t31" class="pln"><span class="strut"> </span></p> +<p id="t32" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t33" class="stm mis"> <span class="key">return</span> <span class="nam">np</span><span class="op">.</span><span class="nam">random</span><span class="op">.</span><span class="nam">normal</span><span class="op">(</span><span class="nam">loc</span><span class="op">=</span><span class="nam">mean</span><span class="op">,</span> <span class="nam">scale</span><span class="op">=</span><span class="nam">std</span><span class="op">,</span> <span class="nam">size</span><span class="op">=</span><span class="nam">size</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t34" class="pln"><span class="strut"> </span></p> +<p id="t35" class="pln"><span class="strut"> </span></p> +<p id="t36" class="stm run hide_run"><span class="key">class</span> <span class="nam">NonRandomNumbers</span><span class="op">(</span><span class="nam">RandomNumbers</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t37" class="pln"> <span class="str">"""Returns means instead of random numbers</span><span class="strut"> </span></p> +<p id="t38" class="pln"><span class="strut"> </span></p> +<p id="t39" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t40" class="pln"><span class="strut"> </span></p> +<p id="t41" class="stm run hide_run"> <span class="key">def</span> <span class="nam">random</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">mean</span><span class="op">,</span> <span class="nam">std</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t42" class="stm run hide_run"> <span class="key">return</span> <span class="nam">mean</span><span class="op">.</span><span class="nam">copy</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t43" class="pln"><span class="strut"> </span></p> +<p id="t44" class="stm run hide_run"> <span class="key">def</span> <span class="nam">random_array</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">mean</span><span class="op">,</span> <span class="nam">std</span><span class="op">,</span> <span class="nam">size</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t45" class="stm run hide_run"> <span class="key">return</span> <span class="nam">np</span><span class="op">.</span><span class="nam">tile</span><span class="op">(</span><span class="nam">mean</span><span class="op">,</span> <span class="nam">size</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t46" class="pln"><span class="strut"> </span></p> +<p id="t47" class="pln"><span class="strut"> </span></p> +<p id="t48" class="stm run hide_run"><span class="key">class</span> <span class="nam">HDF5NormalRandomNumbers</span><span class="op">(</span><span class="nam">RandomNumbers</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t49" class="pln"> <span class="str">"""Returns normal random numbers from an HDF5 file.</span><span class="strut"> </span></p> +<p id="t50" class="pln"><span class="strut"> </span></p> +<p id="t51" class="pln"><span class="str"> Parameters</span><span class="strut"> </span></p> +<p id="t52" class="pln"><span class="str"> ----------</span><span class="strut"> </span></p> +<p id="t53" class="pln"><span class="str"> file_path : str</span><span class="strut"> </span></p> +<p id="t54" class="pln"><span class="str"> Path to HDF5 file</span><span class="strut"> </span></p> +<p id="t55" class="pln"><span class="str"> data_set : str</span><span class="strut"> </span></p> +<p id="t56" class="pln"><span class="str"> Data set containing standard normal random numbers</span><span class="strut"> </span></p> +<p id="t57" class="pln"><span class="strut"> </span></p> +<p id="t58" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t59" class="pln"><span class="strut"> </span></p> +<p id="t60" class="stm run hide_run"> <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">file_path</span><span class="op">,</span> <span class="nam">data_set</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t61" class="pln"><span class="strut"> </span></p> +<p id="t62" class="stm mis"> <span class="key">with</span> <span class="nam">h5py</span><span class="op">.</span><span class="nam">File</span><span class="op">(</span><span class="nam">file_path</span><span class="op">,</span> <span class="str">'r'</span><span class="op">)</span> <span class="key">as</span> <span class="nam">f</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t63" class="stm mis"> <span class="nam">dset</span> <span class="op">=</span> <span class="nam">f</span><span class="op">[</span><span class="nam">data_set</span><span class="op">]</span><span class="op">[</span><span class="op">:</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t64" class="pln"><span class="strut"> </span></p> +<p id="t65" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">_dset</span> <span class="op">=</span> <span class="nam">dset</span><span class="strut"> </span></p> +<p id="t66" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">_index</span> <span class="op">=</span> <span class="num">0</span><span class="strut"> </span></p> +<p id="t67" class="pln"><span class="strut"> </span></p> +<p id="t68" class="stm run hide_run"> <span class="key">def</span> <span class="nam">random</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">mean</span><span class="op">,</span> <span class="nam">std</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t69" class="pln"><span class="strut"> </span></p> +<p id="t70" class="stm mis"> <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_index</span> <span class="op">></span> <span class="nam">len</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_dset</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t71" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="str">"No remaining random numbers"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t72" class="pln"><span class="strut"> </span></p> +<p id="t73" class="stm mis"> <span class="nam">size</span> <span class="op">=</span> <span class="nam">mean</span><span class="op">.</span><span class="nam">shape</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t74" class="pln"><span class="strut"> </span></p> +<p id="t75" class="stm mis"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">random_array</span><span class="op">(</span><span class="nam">mean</span><span class="op">,</span> <span class="nam">std</span><span class="op">,</span> <span class="nam">size</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t76" class="pln"><span class="strut"> </span></p> +<p id="t77" class="stm run hide_run"> <span class="key">def</span> <span class="nam">random_array</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">mean</span><span class="op">,</span> <span class="nam">std</span><span class="op">,</span> <span class="nam">size</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t78" class="pln"><span class="strut"> </span></p> +<p id="t79" class="stm mis"> <span class="nam">first_index</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_index</span><span class="strut"> </span></p> +<p id="t80" class="stm mis"> <span class="nam">last_index</span> <span class="op">=</span> <span class="nam">first_index</span> <span class="op">+</span> <span class="nam">size</span><span class="strut"> </span></p> +<p id="t81" class="pln"><span class="strut"> </span></p> +<p id="t82" class="stm mis"> <span class="key">if</span> <span class="nam">last_index</span> <span class="op">></span> <span class="nam">len</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_dset</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t83" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="strut"> </span></p> +<p id="t84" class="pln"> <span class="str">"`size` exceeds the number of remaining random numbers"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t85" class="pln"><span class="strut"> </span></p> +<p id="t86" class="stm mis"> <span class="nam">standard_values</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_dset</span><span class="op">[</span><span class="nam">first_index</span><span class="op">:</span><span class="nam">last_index</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t87" class="stm mis"> <span class="nam">scaled_values</span> <span class="op">=</span> <span class="nam">standard_values</span> <span class="op">*</span> <span class="nam">std</span> <span class="op">+</span> <span class="nam">mean</span><span class="strut"> </span></p> +<p id="t88" class="pln"><span class="strut"> </span></p> +<p id="t89" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">_index</span> <span class="op">=</span> <span class="nam">last_index</span><span class="strut"> </span></p> +<p id="t90" class="pln"><span class="strut"> </span></p> +<p id="t91" class="stm mis"> <span class="key">return</span> <span class="nam">scaled_values</span><span class="strut"> </span></p> + + </td> + </tr> + </table> +</div> + +<div id="footer"> + <div class="content"> + <p> + <a class="nav" href="index.html">« index</a> <a class="nav" href="https://coverage.readthedocs.io">coverage.py v4.5.3</a>, + created at 2019-07-09 15:15 + </p> + </div> +</div> + +</body> +</html> diff --git a/coverage_report/fluegg_ras_py.html b/coverage_report/fluegg_ras_py.html new file mode 100644 index 0000000..c68a2ca --- /dev/null +++ b/coverage_report/fluegg_ras_py.html @@ -0,0 +1,1007 @@ + + + +<!DOCTYPE html> +<html> +<head> + <meta http-equiv="Content-Type" content="text/html; charset=utf-8"> + + + <meta http-equiv="X-UA-Compatible" content="IE=emulateIE7" /> + <title>Coverage for fluegg\ras.py: 25%</title> + <link rel="stylesheet" href="style.css" type="text/css"> + + <script type="text/javascript" src="jquery.min.js"></script> + <script type="text/javascript" src="jquery.hotkeys.js"></script> + <script type="text/javascript" src="jquery.isonscreen.js"></script> + <script type="text/javascript" src="coverage_html.js"></script> + <script type="text/javascript"> + jQuery(document).ready(coverage.pyfile_ready); + </script> +</head> +<body class="pyfile"> + +<div id="header"> + <div class="content"> + <h1>Coverage for <b>fluegg\ras.py</b> : + <span class="pc_cov">25%</span> + </h1> + + <img id="keyboard_icon" src="keybd_closed.png" alt="Show keyboard shortcuts" /> + + <h2 class="stats"> + 197 statements + <span class="run hide_run shortkey_r button_toggle_run">49 run</span> + <span class="mis shortkey_m button_toggle_mis">148 missing</span> + <span class="exc shortkey_x button_toggle_exc">0 excluded</span> + + + </h2> + </div> +</div> + +<div class="help_panel"> + <img id="panel_icon" src="keybd_open.png" alt="Hide keyboard shortcuts" /> + <p class="legend">Hot-keys on this page</p> + <div> + <p class="keyhelp"> + <span class="key">r</span> + <span class="key">m</span> + <span class="key">x</span> + <span class="key">p</span> toggle line displays + </p> + <p class="keyhelp"> + <span class="key">j</span> + <span class="key">k</span> next/prev highlighted chunk + </p> + <p class="keyhelp"> + <span class="key">0</span> (zero) top of page + </p> + <p class="keyhelp"> + <span class="key">1</span> (one) first highlighted chunk + </p> + </div> +</div> + +<div id="source"> + <table> + <tr> + <td class="linenos"> +<p id="n1" class="stm run hide_run"><a href="#n1">1</a></p> +<p id="n2" class="stm run hide_run"><a href="#n2">2</a></p> +<p id="n3" class="stm run hide_run"><a href="#n3">3</a></p> +<p id="n4" class="stm run hide_run"><a 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class="pln"><a href="#n95">95</a></p> +<p id="n96" class="pln"><a href="#n96">96</a></p> +<p id="n97" class="stm mis"><a href="#n97">97</a></p> +<p id="n98" class="stm mis"><a href="#n98">98</a></p> +<p id="n99" class="pln"><a href="#n99">99</a></p> +<p id="n100" class="stm mis"><a href="#n100">100</a></p> +<p id="n101" class="stm mis"><a href="#n101">101</a></p> +<p id="n102" class="pln"><a href="#n102">102</a></p> +<p id="n103" class="stm mis"><a href="#n103">103</a></p> +<p id="n104" class="pln"><a href="#n104">104</a></p> +<p id="n105" class="stm mis"><a href="#n105">105</a></p> +<p id="n106" class="stm mis"><a href="#n106">106</a></p> +<p id="n107" class="stm mis"><a href="#n107">107</a></p> +<p id="n108" class="stm mis"><a href="#n108">108</a></p> +<p id="n109" class="stm mis"><a href="#n109">109</a></p> +<p id="n110" class="stm mis"><a href="#n110">110</a></p> +<p id="n111" class="stm mis"><a href="#n111">111</a></p> +<p id="n112" class="stm mis"><a href="#n112">112</a></p> +<p id="n113" class="pln"><a href="#n113">113</a></p> +<p id="n114" class="stm mis"><a href="#n114">114</a></p> +<p id="n115" class="pln"><a href="#n115">115</a></p> +<p id="n116" class="stm mis"><a href="#n116">116</a></p> +<p id="n117" class="stm mis"><a href="#n117">117</a></p> +<p id="n118" class="pln"><a href="#n118">118</a></p> +<p id="n119" class="stm mis"><a href="#n119">119</a></p> +<p id="n120" class="stm mis"><a href="#n120">120</a></p> +<p id="n121" class="pln"><a href="#n121">121</a></p> +<p id="n122" class="stm run hide_run"><a href="#n122">122</a></p> +<p id="n123" class="stm mis"><a href="#n123">123</a></p> +<p id="n124" class="pln"><a href="#n124">124</a></p> +<p id="n125" class="stm run hide_run"><a href="#n125">125</a></p> +<p id="n126" class="stm mis"><a href="#n126">126</a></p> +<p id="n127" class="pln"><a href="#n127">127</a></p> +<p id="n128" class="stm run hide_run"><a href="#n128">128</a></p> +<p id="n129" class="pln"><a href="#n129">129</a></p> +<p id="n130" class="stm mis"><a href="#n130">130</a></p> +<p id="n131" class="stm mis"><a href="#n131">131</a></p> +<p id="n132" class="stm mis"><a href="#n132">132</a></p> +<p id="n133" class="pln"><a href="#n133">133</a></p> +<p id="n134" class="stm mis"><a href="#n134">134</a></p> +<p id="n135" class="pln"><a href="#n135">135</a></p> +<p id="n136" class="stm mis"><a href="#n136">136</a></p> +<p id="n137" class="pln"><a href="#n137">137</a></p> +<p id="n138" class="pln"><a href="#n138">138</a></p> +<p id="n139" class="stm mis"><a href="#n139">139</a></p> +<p id="n140" class="pln"><a href="#n140">140</a></p> +<p id="n141" class="stm run hide_run"><a href="#n141">141</a></p> +<p id="n142" class="pln"><a href="#n142">142</a></p> +<p id="n143" class="pln"><a href="#n143">143</a></p> +<p id="n144" class="stm mis"><a href="#n144">144</a></p> +<p id="n145" class="stm mis"><a href="#n145">145</a></p> +<p id="n146" class="stm mis"><a href="#n146">146</a></p> +<p id="n147" class="pln"><a href="#n147">147</a></p> +<p id="n148" class="stm mis"><a href="#n148">148</a></p> +<p id="n149" class="stm mis"><a href="#n149">149</a></p> +<p id="n150" class="pln"><a href="#n150">150</a></p> +<p id="n151" class="stm mis"><a href="#n151">151</a></p> +<p id="n152" class="pln"><a href="#n152">152</a></p> +<p id="n153" class="stm run hide_run"><a href="#n153">153</a></p> +<p id="n154" class="pln"><a href="#n154">154</a></p> +<p id="n155" class="stm mis"><a href="#n155">155</a></p> +<p id="n156" class="pln"><a href="#n156">156</a></p> +<p id="n157" class="pln"><a href="#n157">157</a></p> +<p id="n158" class="stm mis"><a href="#n158">158</a></p> +<p id="n159" class="pln"><a href="#n159">159</a></p> +<p id="n160" class="stm mis"><a href="#n160">160</a></p> +<p id="n161" class="pln"><a href="#n161">161</a></p> +<p id="n162" class="stm mis"><a href="#n162">162</a></p> +<p id="n163" class="stm mis"><a href="#n163">163</a></p> +<p id="n164" class="pln"><a href="#n164">164</a></p> +<p id="n165" class="pln"><a href="#n165">165</a></p> +<p id="n166" class="stm mis"><a href="#n166">166</a></p> +<p id="n167" class="pln"><a href="#n167">167</a></p> +<p id="n168" class="stm mis"><a href="#n168">168</a></p> +<p id="n169" class="stm mis"><a href="#n169">169</a></p> +<p id="n170" class="pln"><a href="#n170">170</a></p> +<p id="n171" class="pln"><a href="#n171">171</a></p> +<p id="n172" class="stm mis"><a href="#n172">172</a></p> +<p id="n173" class="pln"><a href="#n173">173</a></p> +<p id="n174" class="stm mis"><a href="#n174">174</a></p> +<p id="n175" class="stm mis"><a href="#n175">175</a></p> +<p id="n176" class="pln"><a href="#n176">176</a></p> +<p id="n177" class="stm mis"><a href="#n177">177</a></p> +<p id="n178" class="pln"><a href="#n178">178</a></p> +<p id="n179" class="stm mis"><a href="#n179">179</a></p> +<p id="n180" class="pln"><a href="#n180">180</a></p> +<p id="n181" class="stm mis"><a href="#n181">181</a></p> +<p id="n182" class="pln"><a href="#n182">182</a></p> +<p id="n183" class="stm run hide_run"><a href="#n183">183</a></p> +<p id="n184" class="pln"><a href="#n184">184</a></p> +<p id="n185" class="stm mis"><a href="#n185">185</a></p> +<p id="n186" class="pln"><a href="#n186">186</a></p> +<p id="n187" class="stm mis"><a href="#n187">187</a></p> +<p id="n188" class="pln"><a href="#n188">188</a></p> +<p id="n189" class="pln"><a href="#n189">189</a></p> +<p id="n190" class="pln"><a href="#n190">190</a></p> +<p id="n191" class="stm mis"><a href="#n191">191</a></p> +<p id="n192" class="pln"><a href="#n192">192</a></p> +<p id="n193" class="pln"><a href="#n193">193</a></p> +<p id="n194" class="pln"><a href="#n194">194</a></p> +<p id="n195" class="stm mis"><a href="#n195">195</a></p> +<p id="n196" class="stm mis"><a href="#n196">196</a></p> +<p id="n197" class="pln"><a href="#n197">197</a></p> +<p id="n198" class="pln"><a href="#n198">198</a></p> +<p id="n199" class="pln"><a href="#n199">199</a></p> +<p id="n200" class="stm mis"><a href="#n200">200</a></p> +<p id="n201" class="pln"><a href="#n201">201</a></p> +<p id="n202" class="stm mis"><a href="#n202">202</a></p> +<p id="n203" class="stm mis"><a href="#n203">203</a></p> +<p id="n204" class="stm mis"><a href="#n204">204</a></p> +<p id="n205" class="stm mis"><a href="#n205">205</a></p> +<p id="n206" class="stm mis"><a href="#n206">206</a></p> +<p id="n207" class="pln"><a href="#n207">207</a></p> +<p id="n208" class="stm mis"><a href="#n208">208</a></p> +<p id="n209" class="pln"><a href="#n209">209</a></p> +<p id="n210" class="stm mis"><a href="#n210">210</a></p> +<p id="n211" class="stm mis"><a href="#n211">211</a></p> +<p id="n212" class="stm mis"><a href="#n212">212</a></p> +<p id="n213" class="stm mis"><a href="#n213">213</a></p> +<p id="n214" class="pln"><a href="#n214">214</a></p> +<p id="n215" class="stm mis"><a href="#n215">215</a></p> +<p id="n216" class="stm mis"><a href="#n216">216</a></p> +<p id="n217" class="pln"><a href="#n217">217</a></p> +<p id="n218" class="stm mis"><a href="#n218">218</a></p> +<p id="n219" class="pln"><a href="#n219">219</a></p> +<p id="n220" class="stm run hide_run"><a href="#n220">220</a></p> +<p id="n221" class="pln"><a href="#n221">221</a></p> +<p id="n222" class="stm mis"><a href="#n222">222</a></p> +<p id="n223" class="pln"><a href="#n223">223</a></p> +<p id="n224" class="stm mis"><a href="#n224">224</a></p> +<p id="n225" class="pln"><a href="#n225">225</a></p> +<p id="n226" class="pln"><a href="#n226">226</a></p> +<p id="n227" class="stm mis"><a href="#n227">227</a></p> +<p id="n228" class="stm mis"><a href="#n228">228</a></p> +<p id="n229" class="stm mis"><a href="#n229">229</a></p> +<p id="n230" class="stm mis"><a href="#n230">230</a></p> +<p id="n231" class="stm mis"><a href="#n231">231</a></p> +<p id="n232" class="stm mis"><a href="#n232">232</a></p> +<p id="n233" class="pln"><a href="#n233">233</a></p> +<p id="n234" class="pln"><a href="#n234">234</a></p> +<p id="n235" class="stm mis"><a href="#n235">235</a></p> +<p id="n236" class="stm mis"><a href="#n236">236</a></p> +<p id="n237" class="pln"><a href="#n237">237</a></p> +<p id="n238" class="pln"><a href="#n238">238</a></p> +<p id="n239" class="stm mis"><a href="#n239">239</a></p> +<p id="n240" class="pln"><a href="#n240">240</a></p> +<p id="n241" class="pln"><a href="#n241">241</a></p> +<p id="n242" class="stm mis"><a href="#n242">242</a></p> +<p id="n243" class="pln"><a href="#n243">243</a></p> +<p id="n244" class="stm mis"><a href="#n244">244</a></p> +<p id="n245" class="stm mis"><a href="#n245">245</a></p> +<p id="n246" class="pln"><a href="#n246">246</a></p> +<p id="n247" class="stm mis"><a href="#n247">247</a></p> +<p id="n248" class="pln"><a href="#n248">248</a></p> +<p id="n249" class="stm run hide_run"><a href="#n249">249</a></p> +<p id="n250" class="pln"><a href="#n250">250</a></p> +<p id="n251" class="stm mis"><a href="#n251">251</a></p> +<p id="n252" class="pln"><a href="#n252">252</a></p> +<p id="n253" class="stm mis"><a href="#n253">253</a></p> +<p id="n254" class="pln"><a href="#n254">254</a></p> +<p id="n255" class="pln"><a href="#n255">255</a></p> +<p id="n256" class="stm mis"><a href="#n256">256</a></p> +<p id="n257" class="stm mis"><a href="#n257">257</a></p> +<p id="n258" class="pln"><a href="#n258">258</a></p> +<p id="n259" class="pln"><a href="#n259">259</a></p> +<p id="n260" class="stm mis"><a href="#n260">260</a></p> +<p id="n261" class="pln"><a href="#n261">261</a></p> +<p id="n262" class="stm mis"><a href="#n262">262</a></p> +<p id="n263" class="pln"><a href="#n263">263</a></p> +<p id="n264" class="stm run hide_run"><a href="#n264">264</a></p> +<p id="n265" class="pln"><a href="#n265">265</a></p> +<p id="n266" class="stm mis"><a href="#n266">266</a></p> +<p id="n267" class="stm mis"><a href="#n267">267</a></p> +<p id="n268" class="pln"><a href="#n268">268</a></p> +<p id="n269" class="stm mis"><a href="#n269">269</a></p> +<p id="n270" class="stm mis"><a href="#n270">270</a></p> +<p id="n271" class="stm mis"><a href="#n271">271</a></p> +<p id="n272" class="pln"><a href="#n272">272</a></p> +<p id="n273" class="stm mis"><a href="#n273">273</a></p> +<p id="n274" class="pln"><a href="#n274">274</a></p> +<p id="n275" class="stm mis"><a href="#n275">275</a></p> +<p id="n276" class="stm mis"><a href="#n276">276</a></p> +<p id="n277" class="stm mis"><a href="#n277">277</a></p> +<p id="n278" class="pln"><a href="#n278">278</a></p> +<p id="n279" class="stm mis"><a href="#n279">279</a></p> +<p id="n280" class="pln"><a href="#n280">280</a></p> +<p id="n281" class="stm run hide_run"><a href="#n281">281</a></p> +<p id="n282" class="pln"><a href="#n282">282</a></p> +<p id="n283" class="pln"><a href="#n283">283</a></p> +<p id="n284" class="pln"><a href="#n284">284</a></p> +<p id="n285" class="pln"><a href="#n285">285</a></p> +<p id="n286" class="stm mis"><a href="#n286">286</a></p> +<p id="n287" class="stm mis"><a href="#n287">287</a></p> +<p id="n288" class="pln"><a href="#n288">288</a></p> +<p id="n289" class="stm mis"><a href="#n289">289</a></p> +<p id="n290" class="stm mis"><a href="#n290">290</a></p> +<p id="n291" class="pln"><a href="#n291">291</a></p> +<p id="n292" class="stm run hide_run"><a href="#n292">292</a></p> +<p id="n293" class="pln"><a href="#n293">293</a></p> +<p id="n294" class="pln"><a href="#n294">294</a></p> +<p id="n295" class="pln"><a href="#n295">295</a></p> +<p id="n296" class="pln"><a href="#n296">296</a></p> +<p id="n297" class="pln"><a href="#n297">297</a></p> +<p id="n298" class="pln"><a href="#n298">298</a></p> +<p id="n299" class="pln"><a href="#n299">299</a></p> +<p id="n300" class="stm mis"><a href="#n300">300</a></p> +<p id="n301" class="pln"><a href="#n301">301</a></p> +<p id="n302" class="stm mis"><a href="#n302">302</a></p> +<p id="n303" class="pln"><a href="#n303">303</a></p> +<p id="n304" class="stm run hide_run"><a href="#n304">304</a></p> +<p id="n305" class="pln"><a href="#n305">305</a></p> +<p id="n306" class="pln"><a href="#n306">306</a></p> +<p id="n307" class="pln"><a href="#n307">307</a></p> +<p id="n308" class="pln"><a href="#n308">308</a></p> +<p id="n309" class="pln"><a href="#n309">309</a></p> +<p id="n310" class="pln"><a href="#n310">310</a></p> +<p id="n311" class="pln"><a href="#n311">311</a></p> +<p id="n312" class="pln"><a href="#n312">312</a></p> +<p id="n313" class="stm mis"><a href="#n313">313</a></p> +<p id="n314" class="pln"><a href="#n314">314</a></p> +<p id="n315" class="stm mis"><a href="#n315">315</a></p> +<p id="n316" class="pln"><a href="#n316">316</a></p> +<p id="n317" class="stm run hide_run"><a href="#n317">317</a></p> +<p id="n318" class="pln"><a href="#n318">318</a></p> +<p id="n319" class="pln"><a href="#n319">319</a></p> +<p id="n320" class="pln"><a href="#n320">320</a></p> +<p id="n321" class="pln"><a href="#n321">321</a></p> +<p id="n322" class="pln"><a href="#n322">322</a></p> +<p id="n323" class="pln"><a href="#n323">323</a></p> +<p id="n324" class="pln"><a href="#n324">324</a></p> +<p id="n325" class="pln"><a href="#n325">325</a></p> +<p id="n326" class="stm mis"><a href="#n326">326</a></p> +<p id="n327" class="pln"><a href="#n327">327</a></p> +<p id="n328" class="stm mis"><a href="#n328">328</a></p> +<p id="n329" class="pln"><a href="#n329">329</a></p> +<p id="n330" class="stm run hide_run"><a href="#n330">330</a></p> +<p id="n331" class="pln"><a href="#n331">331</a></p> +<p id="n332" class="pln"><a href="#n332">332</a></p> +<p id="n333" class="pln"><a href="#n333">333</a></p> +<p id="n334" class="pln"><a href="#n334">334</a></p> +<p id="n335" class="pln"><a href="#n335">335</a></p> +<p id="n336" class="pln"><a href="#n336">336</a></p> +<p id="n337" class="pln"><a href="#n337">337</a></p> +<p id="n338" class="pln"><a href="#n338">338</a></p> +<p id="n339" class="pln"><a href="#n339">339</a></p> +<p id="n340" class="pln"><a href="#n340">340</a></p> +<p id="n341" class="pln"><a href="#n341">341</a></p> +<p id="n342" class="pln"><a href="#n342">342</a></p> +<p id="n343" class="pln"><a href="#n343">343</a></p> +<p id="n344" class="pln"><a href="#n344">344</a></p> +<p id="n345" class="pln"><a href="#n345">345</a></p> +<p id="n346" class="pln"><a href="#n346">346</a></p> +<p id="n347" class="pln"><a href="#n347">347</a></p> +<p id="n348" class="pln"><a href="#n348">348</a></p> +<p id="n349" class="stm mis"><a href="#n349">349</a></p> +<p id="n350" class="pln"><a href="#n350">350</a></p> +<p id="n351" class="stm mis"><a href="#n351">351</a></p> +<p id="n352" class="stm mis"><a href="#n352">352</a></p> +<p id="n353" class="stm mis"><a href="#n353">353</a></p> +<p id="n354" class="stm mis"><a href="#n354">354</a></p> +<p id="n355" class="pln"><a href="#n355">355</a></p> +<p id="n356" class="stm mis"><a href="#n356">356</a></p> +<p id="n357" class="pln"><a href="#n357">357</a></p> +<p id="n358" class="stm mis"><a href="#n358">358</a></p> +<p id="n359" class="pln"><a href="#n359">359</a></p> +<p id="n360" class="stm run hide_run"><a href="#n360">360</a></p> +<p id="n361" class="pln"><a href="#n361">361</a></p> +<p id="n362" class="pln"><a href="#n362">362</a></p> +<p id="n363" class="pln"><a href="#n363">363</a></p> +<p id="n364" class="pln"><a href="#n364">364</a></p> +<p id="n365" class="pln"><a href="#n365">365</a></p> +<p id="n366" class="pln"><a href="#n366">366</a></p> +<p id="n367" class="pln"><a href="#n367">367</a></p> +<p id="n368" class="pln"><a href="#n368">368</a></p> +<p id="n369" class="stm mis"><a href="#n369">369</a></p> +<p id="n370" class="stm mis"><a href="#n370">370</a></p> +<p id="n371" class="pln"><a href="#n371">371</a></p> +<p id="n372" class="stm mis"><a href="#n372">372</a></p> +<p id="n373" class="pln"><a href="#n373">373</a></p> +<p id="n374" class="pln"><a href="#n374">374</a></p> +<p id="n375" class="stm mis"><a href="#n375">375</a></p> +<p id="n376" class="pln"><a href="#n376">376</a></p> +<p id="n377" class="stm run hide_run"><a href="#n377">377</a></p> +<p id="n378" class="pln"><a href="#n378">378</a></p> +<p id="n379" class="pln"><a href="#n379">379</a></p> +<p id="n380" class="pln"><a href="#n380">380</a></p> +<p id="n381" class="pln"><a href="#n381">381</a></p> +<p id="n382" class="pln"><a href="#n382">382</a></p> +<p id="n383" class="pln"><a href="#n383">383</a></p> +<p id="n384" class="pln"><a href="#n384">384</a></p> +<p id="n385" class="pln"><a href="#n385">385</a></p> +<p id="n386" class="stm mis"><a href="#n386">386</a></p> +<p id="n387" class="stm mis"><a href="#n387">387</a></p> +<p id="n388" class="pln"><a href="#n388">388</a></p> +<p id="n389" class="stm mis"><a href="#n389">389</a></p> +<p id="n390" class="pln"><a href="#n390">390</a></p> +<p id="n391" class="stm mis"><a href="#n391">391</a></p> +<p id="n392" class="pln"><a href="#n392">392</a></p> +<p id="n393" class="stm run hide_run"><a href="#n393">393</a></p> +<p id="n394" class="pln"><a href="#n394">394</a></p> +<p id="n395" class="pln"><a href="#n395">395</a></p> +<p id="n396" class="pln"><a href="#n396">396</a></p> +<p id="n397" class="pln"><a href="#n397">397</a></p> +<p id="n398" class="pln"><a href="#n398">398</a></p> +<p id="n399" class="pln"><a href="#n399">399</a></p> +<p id="n400" class="pln"><a href="#n400">400</a></p> +<p id="n401" class="pln"><a href="#n401">401</a></p> +<p id="n402" class="stm mis"><a href="#n402">402</a></p> +<p id="n403" class="pln"><a href="#n403">403</a></p> +<p id="n404" class="stm run hide_run"><a href="#n404">404</a></p> +<p id="n405" class="pln"><a href="#n405">405</a></p> +<p id="n406" class="stm mis"><a href="#n406">406</a></p> +<p id="n407" class="pln"><a href="#n407">407</a></p> +<p id="n408" class="stm run hide_run"><a href="#n408">408</a></p> +<p id="n409" class="pln"><a href="#n409">409</a></p> +<p id="n410" class="pln"><a href="#n410">410</a></p> +<p id="n411" class="pln"><a href="#n411">411</a></p> +<p id="n412" class="pln"><a href="#n412">412</a></p> +<p 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id="n449" class="pln"><a href="#n449">449</a></p> +<p id="n450" class="pln"><a href="#n450">450</a></p> +<p id="n451" class="stm mis"><a href="#n451">451</a></p> +<p id="n452" class="stm mis"><a href="#n452">452</a></p> +<p id="n453" class="pln"><a href="#n453">453</a></p> +<p id="n454" class="stm mis"><a href="#n454">454</a></p> +<p id="n455" class="pln"><a href="#n455">455</a></p> +<p id="n456" class="stm mis"><a href="#n456">456</a></p> +<p id="n457" class="stm mis"><a href="#n457">457</a></p> +<p id="n458" class="pln"><a href="#n458">458</a></p> +<p id="n459" class="stm mis"><a href="#n459">459</a></p> + + </td> + <td class="text"> +<p id="t1" class="stm run hide_run"><span class="key">from</span> <span class="nam">datetime</span> <span class="key">import</span> <span class="nam">timedelta</span><span class="strut"> </span></p> +<p id="t2" class="stm run hide_run"><span class="key">import</span> <span class="nam">glob</span><span class="strut"> </span></p> +<p id="t3" class="stm run hide_run"><span class="key">import</span> <span class="nam">platform</span><span class="strut"> </span></p> +<p id="t4" class="stm run hide_run"><span class="key">import</span> <span class="nam">os</span><span class="strut"> </span></p> +<p id="t5" class="stm run hide_run"><span class="key">import</span> <span class="nam">re</span><span class="strut"> </span></p> +<p id="t6" class="pln"><span class="strut"> </span></p> +<p id="t7" class="stm run hide_run"><span class="key">import</span> <span class="nam">numpy</span> <span class="key">as</span> <span class="nam">np</span><span class="strut"> </span></p> +<p id="t8" class="stm run hide_run"><span class="key">import</span> <span class="nam">pandas</span> <span class="key">as</span> <span class="nam">pd</span><span class="strut"> </span></p> +<p id="t9" class="pln"><span class="strut"> </span></p> +<p id="t10" class="pln"><span class="strut"> </span></p> +<p id="t11" class="stm run hide_run"><span class="key">def</span> <span class="nam">_load_ras_controller</span><span class="op">(</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t12" class="pln"><span class="strut"> </span></p> +<p id="t13" class="stm run hide_run"> <span class="key">if</span> <span class="nam">platform</span><span class="op">.</span><span class="nam">system</span><span class="op">(</span><span class="op">)</span> <span class="op">==</span> <span class="str">'Windows'</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t14" class="stm run hide_run"> <span class="key">import</span> <span class="nam">winreg</span><span class="strut"> </span></p> +<p id="t15" class="stm run hide_run"> <span class="key">import</span> <span class="nam">win32com</span><span class="op">.</span><span class="nam">client</span><span class="strut"> </span></p> +<p id="t16" class="pln"> <span class="key">else</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t17" class="stm mis"> <span class="key">return</span> <span class="key">None</span><span class="strut"> </span></p> +<p id="t18" class="pln"><span class="strut"> </span></p> +<p id="t19" class="pln"> <span class="com"># find the version of RAS that are installed</span><span class="strut"> </span></p> +<p id="t20" class="stm run hide_run"> <span class="nam">ras_controller_pattern</span> <span class="op">=</span> <span class="str">r'^RAS[0-9]{3}.HECRASController$'</span><span class="strut"> </span></p> +<p id="t21" class="pln"><span class="strut"> </span></p> +<p id="t22" class="stm run hide_run"> <span class="key">with</span> <span class="nam">winreg</span><span class="op">.</span><span class="nam">OpenKey</span><span class="op">(</span><span class="nam">winreg</span><span class="op">.</span><span class="nam">HKEY_LOCAL_MACHINE</span><span class="op">,</span> <span class="str">r"SOFTWARE\Classes"</span><span class="op">)</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t23" class="pln"> <span class="key">as</span> <span class="nam">classes_key</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t24" class="pln"><span class="strut"> </span></p> +<p id="t25" class="stm run hide_run"> <span class="nam">ras_controller_prog_ids</span> <span class="op">=</span> <span class="op">[</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t26" class="stm run hide_run"> <span class="nam">n_keys</span><span class="op">,</span> <span class="nam">_</span><span class="op">,</span> <span class="nam">_</span> <span class="op">=</span> <span class="nam">winreg</span><span class="op">.</span><span class="nam">QueryInfoKey</span><span class="op">(</span><span class="nam">classes_key</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t27" class="stm run hide_run"> <span class="key">for</span> <span class="nam">i</span> <span class="key">in</span> <span class="nam">range</span><span class="op">(</span><span class="nam">n_keys</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t28" class="pln"><span class="strut"> </span></p> +<p id="t29" class="stm run hide_run"> <span class="nam">object_name</span> <span class="op">=</span> <span class="nam">winreg</span><span class="op">.</span><span class="nam">EnumKey</span><span class="op">(</span><span class="nam">classes_key</span><span class="op">,</span> <span class="nam">i</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t30" class="stm run hide_run"> <span class="key">if</span> <span class="nam">re</span><span class="op">.</span><span class="nam">match</span><span class="op">(</span><span class="nam">ras_controller_pattern</span><span class="op">,</span> <span class="nam">object_name</span><span class="op">)</span> <span class="key">is</span> <span class="key">not</span> <span class="key">None</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t31" class="stm run hide_run"> <span class="nam">ras_controller_prog_ids</span><span class="op">.</span><span class="nam">append</span><span class="op">(</span><span class="nam">object_name</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t32" class="pln"><span class="strut"> </span></p> +<p id="t33" class="pln"> <span class="com"># use the latest version of RAS installed</span><span class="strut"> </span></p> +<p id="t34" class="stm run hide_run"> <span class="nam">ras_controller_prog_ids</span><span class="op">.</span><span class="nam">sort</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t35" class="pln"><span class="strut"> </span></p> +<p id="t36" class="stm run hide_run"> <span class="key">if</span> <span class="nam">len</span><span class="op">(</span><span class="nam">ras_controller_prog_ids</span><span class="op">)</span> <span class="op">></span> <span class="num">0</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t37" class="stm run hide_run"> <span class="nam">prog_id</span> <span class="op">=</span> <span class="nam">ras_controller_prog_ids</span><span class="op">[</span><span class="op">-</span><span class="num">1</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t38" class="pln"><span class="strut"> </span></p> +<p id="t39" class="pln"> <span class="com"># start the RAS controller</span><span class="strut"> </span></p> +<p id="t40" class="stm run hide_run"> <span class="nam">ras_controller</span> <span class="op">=</span> <span class="nam">win32com</span><span class="op">.</span><span class="nam">client</span><span class="op">.</span><span class="nam">Dispatch</span><span class="op">(</span><span class="nam">prog_id</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t41" class="pln"> <span class="key">else</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t42" class="stm mis"> <span class="nam">ras_controller</span> <span class="op">=</span> <span class="key">None</span><span class="strut"> </span></p> +<p id="t43" class="pln"><span class="strut"> </span></p> +<p id="t44" class="stm run hide_run"> <span class="key">return</span> <span class="nam">ras_controller</span><span class="strut"> </span></p> +<p id="t45" class="pln"><span class="strut"> </span></p> +<p id="t46" class="pln"><span class="strut"> </span></p> +<p id="t47" class="stm run hide_run"><span class="nam">_ras_controller</span> <span class="op">=</span> <span class="nam">_load_ras_controller</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t48" class="pln"><span class="strut"> </span></p> +<p id="t49" class="pln"><span class="strut"> </span></p> +<p id="t50" class="stm run hide_run"><span class="key">def</span> <span class="nam">ras_controller_loaded</span><span class="op">(</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t51" class="stm mis"> <span class="key">return</span> <span class="nam">_ras_controller</span> <span class="key">is</span> <span class="key">not</span> <span class="key">None</span><span class="strut"> </span></p> +<p id="t52" class="pln"><span class="strut"> </span></p> +<p id="t53" class="pln"><span class="strut"> </span></p> +<p id="t54" class="stm run hide_run"><span class="key">class</span> <span class="nam">RASProject</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t55" class="pln"> <span class="str">"""RAS project.</span><span class="strut"> </span></p> +<p id="t56" class="pln"><span class="strut"> </span></p> +<p id="t57" class="pln"><span class="str"> After use, call close() to keep the RAS process from lingering. The</span><span class="strut"> </span></p> +<p id="t58" class="pln"><span class="str"> RASProject interface facilitates the use of the with-statement. See</span><span class="strut"> </span></p> +<p id="t59" class="pln"><span class="str"> below for an example.</span><span class="strut"> </span></p> +<p id="t60" class="pln"><span class="strut"> </span></p> +<p id="t61" class="pln"><span class="str"> ```</span><span class="strut"> </span></p> +<p id="t62" class="pln"><span class="str"> with RASProject(project_file_path) as rp:</span><span class="strut"> </span></p> +<p id="t63" class="pln"><span class="str"> hydrauilc_data = rp.hydraulic_model_data('Unsteady')</span><span class="strut"> </span></p> +<p id="t64" class="pln"><span class="str"> ```</span><span class="strut"> </span></p> +<p id="t65" class="pln"><span class="strut"> </span></p> +<p id="t66" class="pln"><span class="strut"> </span></p> +<p id="t67" class="pln"><span class="str"> Parameters</span><span class="strut"> </span></p> +<p id="t68" class="pln"><span class="str"> ----------</span><span class="strut"> </span></p> +<p id="t69" class="pln"><span class="str"> project_file_path : str</span><span class="strut"> </span></p> +<p id="t70" class="pln"><span class="str"> Path to RAS project file</span><span class="strut"> </span></p> +<p id="t71" class="pln"><span class="strut"> </span></p> +<p id="t72" class="pln"><span class="str"> Notes</span><span class="strut"> </span></p> +<p id="t73" class="pln"><span class="str"> -----</span><span class="strut"> </span></p> +<p id="t74" class="pln"><span class="str"> The values in the output of hydraulic_model_data are in metric units. If</span><span class="strut"> </span></p> +<p id="t75" class="pln"><span class="str"> the quantities in the RAS project are in English units, the output will be</span><span class="strut"> </span></p> +<p id="t76" class="pln"><span class="str"> converted.</span><span class="strut"> </span></p> +<p id="t77" class="pln"><span class="strut"> </span></p> +<p id="t78" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t79" class="pln"><span class="strut"> </span></p> +<p id="t80" class="stm run hide_run"> <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">project_file_path</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t81" class="pln"><span class="strut"> </span></p> +<p id="t82" class="stm mis"> <span class="key">if</span> <span class="nam">_ras_controller</span> <span class="key">is</span> <span class="key">None</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t83" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="str">"RAS controller not found"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t84" class="pln"><span class="strut"> </span></p> +<p id="t85" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">_ras_controller</span> <span class="op">=</span> <span class="nam">_ras_controller</span><span class="strut"> </span></p> +<p id="t86" class="pln"><span class="strut"> </span></p> +<p id="t87" class="pln"> <span class="com"># open the project</span><span class="strut"> </span></p> +<p id="t88" class="stm mis"> <span class="nam">absolute_project_path</span> <span class="op">=</span> <span class="nam">os</span><span class="op">.</span><span class="nam">path</span><span class="op">.</span><span class="nam">abspath</span><span class="op">(</span><span class="nam">project_file_path</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t89" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">_ras_controller</span><span class="op">.</span><span class="nam">Project_Open</span><span class="op">(</span><span class="nam">absolute_project_path</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t90" class="pln"><span class="strut"> </span></p> +<p id="t91" class="pln"> <span class="com"># set the units</span><span class="strut"> </span></p> +<p id="t92" class="stm mis"> <span class="nam">current_project_file_path</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_ras_controller</span><span class="op">.</span><span class="nam">CurrentProjectFile</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t93" class="stm mis"> <span class="key">with</span> <span class="nam">open</span><span class="op">(</span><span class="nam">current_project_file_path</span><span class="op">,</span> <span class="str">'r'</span><span class="op">)</span> <span class="key">as</span> <span class="nam">f</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t94" class="stm mis"> <span class="nam">project_file_contents</span> <span class="op">=</span> <span class="nam">f</span><span class="op">.</span><span class="nam">readlines</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t95" class="pln"><span class="strut"> </span></p> +<p id="t96" class="pln"> <span class="com"># set the current plan number</span><span class="strut"> </span></p> +<p id="t97" class="stm mis"> <span class="nam">current_plan_line</span> <span class="op">=</span> <span class="nam">project_file_contents</span><span class="op">[</span><span class="num">1</span><span class="op">]</span><span class="op">.</span><span class="nam">strip</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t98" class="stm mis"> <span class="nam">current_plan_name</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_get_current_plan_name</span><span class="op">(</span><span class="strut"> </span></p> +<p id="t99" class="pln"> <span class="nam">current_plan_line</span><span class="op">,</span> <span class="nam">current_project_file_path</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t100" class="stm mis"> <span class="nam">plan_names</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">plan_names</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t101" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">_current_plan_number</span> <span class="op">=</span> <span class="nam">plan_names</span><span class="op">.</span><span class="nam">index</span><span class="op">(</span><span class="nam">current_plan_name</span><span class="op">)</span> <span class="op">+</span> <span class="num">1</span><span class="strut"> </span></p> +<p id="t102" class="pln"><span class="strut"> </span></p> +<p id="t103" class="stm mis"> <span class="nam">units</span> <span class="op">=</span> <span class="nam">project_file_contents</span><span class="op">[</span><span class="num">3</span><span class="op">]</span><span class="op">.</span><span class="nam">strip</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t104" class="pln"><span class="strut"> </span></p> +<p id="t105" class="stm mis"> <span class="key">if</span> <span class="nam">units</span> <span class="op">==</span> <span class="str">'English Units'</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t106" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">_ras_units</span> <span class="op">=</span> <span class="str">'English'</span><span class="strut"> </span></p> +<p id="t107" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">_gravity</span> <span class="op">=</span> <span class="num">32.2</span><span class="strut"> </span></p> +<p id="t108" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">_n_conversion</span> <span class="op">=</span> <span class="num">1.4859</span><span class="strut"> </span></p> +<p id="t109" class="stm mis"> <span class="key">elif</span> <span class="nam">units</span> <span class="op">==</span> <span class="str">'SI Units'</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t110" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">_ras_units</span> <span class="op">=</span> <span class="str">'metric'</span><span class="strut"> </span></p> +<p id="t111" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">_gravity</span> <span class="op">=</span> <span class="num">9.81</span><span class="strut"> </span></p> +<p id="t112" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">_n_conversion</span> <span class="op">=</span> <span class="num">1</span><span class="strut"> </span></p> +<p id="t113" class="pln"> <span class="key">else</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t114" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="str">"Unknown units in project file"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t115" class="pln"><span class="strut"> </span></p> +<p id="t116" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">_current_river_number</span> <span class="op">=</span> <span class="num">1</span><span class="strut"> </span></p> +<p id="t117" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">_current_reach_number</span> <span class="op">=</span> <span class="num">1</span><span class="strut"> </span></p> +<p id="t118" class="pln"><span class="strut"> </span></p> +<p id="t119" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">_plan_has_steady_file</span> <span class="op">=</span> <span class="key">False</span><span class="strut"> </span></p> +<p id="t120" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">_plan_has_unsteady_file</span> <span class="op">=</span> <span class="key">False</span><span class="strut"> </span></p> +<p id="t121" class="pln"><span class="strut"> </span></p> +<p id="t122" class="stm run hide_run"> <span class="key">def</span> <span class="nam">__enter__</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t123" class="stm mis"> <span class="key">return</span> <span class="nam">self</span><span class="strut"> </span></p> +<p id="t124" class="pln"><span class="strut"> </span></p> +<p id="t125" class="stm run hide_run"> <span class="key">def</span> <span class="nam">__exit__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="op">*</span><span class="nam">args</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t126" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">close</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t127" class="pln"><span class="strut"> </span></p> +<p id="t128" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_calc_shear_velocity</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">cell_data</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t129" class="pln"><span class="strut"> </span></p> +<p id="t130" class="stm mis"> <span class="nam">manning_values</span> <span class="op">=</span> <span class="nam">cell_data</span><span class="op">[</span><span class="str">'Mann Wtd Chnl'</span><span class="op">]</span><span class="op">.</span><span class="nam">values</span><span class="strut"> </span></p> +<p id="t131" class="stm mis"> <span class="nam">hydraulic_radius</span> <span class="op">=</span> <span class="nam">cell_data</span><span class="op">[</span><span class="str">'Hydr Radius C'</span><span class="op">]</span><span class="op">.</span><span class="nam">values</span><span class="strut"> </span></p> +<p id="t132" class="stm mis"> <span class="nam">channel_velocity</span> <span class="op">=</span> <span class="nam">cell_data</span><span class="op">[</span><span class="str">'Vel Chnl'</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t133" class="pln"><span class="strut"> </span></p> +<p id="t134" class="stm mis"> <span class="nam">ks</span> <span class="op">=</span> <span class="op">(</span><span class="num">8.1</span> <span class="op">*</span> <span class="op">(</span><span class="nam">manning_values</span> <span class="op">/</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_n_conversion</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t135" class="pln"> <span class="op">*</span> <span class="nam">np</span><span class="op">.</span><span class="nam">sqrt</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_gravity</span><span class="op">)</span><span class="op">)</span><span class="op">**</span><span class="num">6</span><span class="strut"> </span></p> +<p id="t136" class="stm mis"> <span class="nam">shear_velocity</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">abs</span><span class="op">(</span><span class="strut"> </span></p> +<p id="t137" class="pln"> <span class="nam">channel_velocity</span> <span class="op">/</span> <span class="op">(</span><span class="num">8.1</span> <span class="op">*</span> <span class="op">(</span><span class="op">(</span><span class="nam">hydraulic_radius</span> <span class="op">/</span> <span class="nam">ks</span><span class="op">)</span> <span class="op">**</span> <span class="op">(</span><span class="num">1</span> <span class="op">/</span> <span class="num">6</span><span class="op">)</span><span class="op">)</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t138" class="pln"><span class="strut"> </span></p> +<p id="t139" class="stm mis"> <span class="key">return</span> <span class="nam">shear_velocity</span><span class="strut"> </span></p> +<p id="t140" class="pln"><span class="strut"> </span></p> +<p id="t141" class="stm run hide_run"> <span class="op">@</span><span class="nam">staticmethod</span><span class="strut"> </span></p> +<p id="t142" class="pln"> <span class="key">def</span> <span class="nam">_get_current_plan_name</span><span class="op">(</span><span class="nam">current_plan_line</span><span class="op">,</span> <span class="nam">current_project_file_path</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t143" class="pln"><span class="strut"> </span></p> +<p id="t144" class="stm mis"> <span class="nam">plan_file_extension</span> <span class="op">=</span> <span class="nam">current_plan_line</span><span class="op">.</span><span class="nam">split</span><span class="op">(</span><span class="str">'='</span><span class="op">)</span><span class="op">[</span><span class="op">-</span><span class="num">1</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t145" class="stm mis"> <span class="nam">path</span><span class="op">,</span> <span class="nam">_</span> <span class="op">=</span> <span class="nam">os</span><span class="op">.</span><span class="nam">path</span><span class="op">.</span><span class="nam">split</span><span class="op">(</span><span class="nam">current_project_file_path</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t146" class="stm mis"> <span class="nam">plan_file_list</span> <span class="op">=</span> <span class="nam">glob</span><span class="op">.</span><span class="nam">glob</span><span class="op">(</span><span class="nam">path</span> <span class="op">+</span> <span class="str">'/*.'</span> <span class="op">+</span> <span class="nam">plan_file_extension</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t147" class="pln"><span class="strut"> </span></p> +<p id="t148" class="stm mis"> <span class="key">with</span> <span class="nam">open</span><span class="op">(</span><span class="nam">plan_file_list</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="op">,</span> <span class="str">'r'</span><span class="op">)</span> <span class="key">as</span> <span class="nam">f</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t149" class="stm mis"> <span class="nam">plan_name_line</span> <span class="op">=</span> <span class="nam">f</span><span class="op">.</span><span class="nam">readline</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">strip</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t150" class="pln"><span class="strut"> </span></p> +<p id="t151" class="stm mis"> <span class="key">return</span> <span class="nam">plan_name_line</span><span class="op">.</span><span class="nam">split</span><span class="op">(</span><span class="str">'='</span><span class="op">)</span><span class="op">[</span><span class="op">-</span><span class="num">1</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t152" class="pln"><span class="strut"> </span></p> +<p id="t153" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_get_data_from_ras</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">profile_number</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t154" class="pln"><span class="strut"> </span></p> +<p id="t155" class="stm mis"> <span class="nam">_</span><span class="op">,</span> <span class="nam">output_var_names</span><span class="op">,</span> <span class="nam">_</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_ras_controller</span><span class="op">.</span><span class="nam">Output_Variables</span><span class="op">(</span><span class="strut"> </span></p> +<p id="t156" class="pln"> <span class="key">None</span><span class="op">,</span> <span class="key">None</span><span class="op">,</span> <span class="key">None</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t157" class="pln"><span class="strut"> </span></p> +<p id="t158" class="stm mis"> <span class="nam">var_name</span> <span class="op">=</span> <span class="op">[</span><span class="str">'Hydr Depth C'</span><span class="op">,</span> <span class="str">'Q Channel'</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t159" class="pln"> <span class="str">'Vel Chnl'</span><span class="op">,</span> <span class="str">'Mann Wtd Chnl'</span><span class="op">,</span> <span class="str">'Hydr Radius C'</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t160" class="stm mis"> <span class="nam">var_values</span> <span class="op">=</span> <span class="op">[</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t161" class="pln"><span class="strut"> </span></p> +<p id="t162" class="stm mis"> <span class="nam">channel_dist</span> <span class="op">=</span> <span class="key">None</span><span class="strut"> </span></p> +<p id="t163" class="stm mis"> <span class="nam">n_river_stations</span> <span class="op">=</span> <span class="num">0</span><span class="strut"> </span></p> +<p id="t164" class="pln"><span class="strut"> </span></p> +<p id="t165" class="pln"> <span class="com"># get the variable for the entire channel length</span><span class="strut"> </span></p> +<p id="t166" class="stm mis"> <span class="key">for</span> <span class="nam">name</span> <span class="key">in</span> <span class="nam">var_name</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t167" class="pln"><span class="strut"> </span></p> +<p id="t168" class="stm mis"> <span class="nam">var_number</span> <span class="op">=</span> <span class="nam">output_var_names</span><span class="op">.</span><span class="nam">index</span><span class="op">(</span><span class="nam">name</span><span class="op">)</span> <span class="op">+</span> <span class="num">1</span><span class="strut"> </span></p> +<p id="t169" class="stm mis"> <span class="nam">_</span><span class="op">,</span> <span class="nam">_</span><span class="op">,</span> <span class="nam">_</span><span class="op">,</span> <span class="nam">_</span><span class="op">,</span> <span class="nam">n_river_stations</span><span class="op">,</span> <span class="nam">_</span><span class="op">,</span> <span class="nam">channel_dist</span><span class="op">,</span> <span class="nam">values</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_ras_controller</span><span class="op">.</span><span class="nam">Output_ReachOutput</span><span class="op">(</span><span class="strut"> </span></p> +<p id="t170" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">_current_river_number</span><span class="op">,</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_current_reach_number</span><span class="op">,</span> <span class="nam">profile_number</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t171" class="pln"> <span class="nam">var_number</span><span class="op">,</span> <span class="key">None</span><span class="op">,</span> <span class="key">None</span><span class="op">,</span> <span class="key">None</span><span class="op">,</span> <span class="key">None</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t172" class="stm mis"> <span class="nam">var_values</span><span class="op">.</span><span class="nam">append</span><span class="op">(</span><span class="nam">values</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t173" class="pln"><span class="strut"> </span></p> +<p id="t174" class="stm mis"> <span class="nam">var_name</span><span class="op">.</span><span class="nam">append</span><span class="op">(</span><span class="str">'ChannelDist'</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t175" class="stm mis"> <span class="nam">var_values</span><span class="op">.</span><span class="nam">append</span><span class="op">(</span><span class="nam">channel_dist</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t176" class="pln"><span class="strut"> </span></p> +<p id="t177" class="stm mis"> <span class="nam">data_dict</span> <span class="op">=</span> <span class="nam">dict</span><span class="op">(</span><span class="nam">zip</span><span class="op">(</span><span class="nam">var_name</span><span class="op">,</span> <span class="nam">var_values</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t178" class="pln"><span class="strut"> </span></p> +<p id="t179" class="stm mis"> <span class="nam">cell_numbers</span> <span class="op">=</span> <span class="nam">range</span><span class="op">(</span><span class="num">1</span><span class="op">,</span> <span class="nam">n_river_stations</span><span class="op">+</span><span class="num">1</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t180" class="pln"><span class="strut"> </span></p> +<p id="t181" class="stm mis"> <span class="key">return</span> <span class="nam">pd</span><span class="op">.</span><span class="nam">DataFrame</span><span class="op">(</span><span class="nam">data_dict</span><span class="op">,</span> <span class="nam">index</span><span class="op">=</span><span class="nam">cell_numbers</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t182" class="pln"><span class="strut"> </span></p> +<p id="t183" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_get_profile_data</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">profile_number</span><span class="op">,</span> <span class="nam">temperature</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t184" class="pln"><span class="strut"> </span></p> +<p id="t185" class="stm mis"> <span class="nam">ras_data</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_get_data_from_ras</span><span class="op">(</span><span class="nam">profile_number</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t186" class="pln"><span class="strut"> </span></p> +<p id="t187" class="stm mis"> <span class="nam">column_map</span> <span class="op">=</span> <span class="op">{</span><span class="str">'Hydr Depth C'</span><span class="op">:</span> <span class="str">'Depth_m'</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t188" class="pln"> <span class="str">'Q Channel'</span><span class="op">:</span> <span class="str">'Q_cms'</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t189" class="pln"> <span class="str">'Vel Chnl'</span><span class="op">:</span> <span class="str">'Vmag_mps'</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t190" class="pln"> <span class="str">'ChannelDist'</span><span class="op">:</span> <span class="str">'CumlDistance_km'</span><span class="op">}</span><span class="strut"> </span></p> +<p id="t191" class="stm mis"> <span class="nam">profile_data</span> <span class="op">=</span> <span class="nam">ras_data</span><span class="op">.</span><span class="nam">rename</span><span class="op">(</span><span class="nam">mapper</span><span class="op">=</span><span class="nam">column_map</span><span class="op">,</span> <span class="nam">axis</span><span class="op">=</span><span class="num">1</span><span class="op">)</span><span class="op">.</span><span class="nam">drop</span><span class="op">(</span><span class="strut"> </span></p> +<p id="t192" class="pln"> <span class="op">[</span><span class="str">'Mann Wtd Chnl'</span><span class="op">,</span> <span class="str">'Hydr Radius C'</span><span class="op">]</span><span class="op">,</span> <span class="nam">axis</span><span class="op">=</span><span class="num">1</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t193" class="pln"><span class="strut"> </span></p> +<p id="t194" class="pln"> <span class="com"># convert from RAS distances to FluEgg distances</span><span class="strut"> </span></p> +<p id="t195" class="stm mis"> <span class="nam">number_of_cells</span> <span class="op">=</span> <span class="nam">profile_data</span><span class="op">.</span><span class="nam">shape</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t196" class="stm mis"> <span class="nam">profile_data</span><span class="op">.</span><span class="nam">loc</span><span class="op">[</span><span class="num">1</span><span class="op">:</span><span class="nam">number_of_cells</span> <span class="op">-</span> <span class="num">1</span><span class="op">,</span> <span class="str">'CumlDistance_km'</span><span class="op">]</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t197" class="pln"> <span class="num">0.5</span> <span class="op">*</span> <span class="op">(</span><span class="nam">profile_data</span><span class="op">.</span><span class="nam">loc</span><span class="op">[</span><span class="num">1</span><span class="op">:</span><span class="nam">number_of_cells</span> <span class="op">-</span> <span class="num">1</span><span class="op">,</span> <span class="str">'CumlDistance_km'</span><span class="op">]</span><span class="op">.</span><span class="nam">values</span><span class="strut"> </span></p> +<p id="t198" class="pln"> <span class="op">+</span> <span class="nam">profile_data</span><span class="op">.</span><span class="nam">loc</span><span class="op">[</span><span class="num">2</span><span class="op">:</span><span class="nam">number_of_cells</span><span class="op">,</span> <span class="str">'CumlDistance_km'</span><span class="op">]</span><span class="op">.</span><span class="nam">values</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t199" class="pln"><span class="strut"> </span></p> +<p id="t200" class="stm mis"> <span class="nam">profile_data</span><span class="op">[</span><span class="str">'CumlDistance_km'</span><span class="op">]</span> <span class="op">=</span> <span class="nam">profile_data</span><span class="op">[</span><span class="str">'CumlDistance_km'</span><span class="op">]</span><span class="op">/</span><span class="num">1000</span><span class="strut"> </span></p> +<p id="t201" class="pln"><span class="strut"> </span></p> +<p id="t202" class="stm mis"> <span class="nam">shear_velocity</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_calc_shear_velocity</span><span class="op">(</span><span class="nam">ras_data</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t203" class="stm mis"> <span class="nam">profile_data</span><span class="op">[</span><span class="str">'Ustar_mps'</span><span class="op">]</span> <span class="op">=</span> <span class="nam">shear_velocity</span><span class="strut"> </span></p> +<p id="t204" class="stm mis"> <span class="nam">profile_data</span><span class="op">[</span><span class="str">'Vvert_mps'</span><span class="op">]</span> <span class="op">=</span> <span class="num">0</span><span class="strut"> </span></p> +<p id="t205" class="stm mis"> <span class="nam">profile_data</span><span class="op">[</span><span class="str">'Vlat_mps'</span><span class="op">]</span> <span class="op">=</span> <span class="num">0</span><span class="strut"> </span></p> +<p id="t206" class="stm mis"> <span class="nam">profile_data</span><span class="op">[</span><span class="str">'Temp_C'</span><span class="op">]</span> <span class="op">=</span> <span class="nam">temperature</span><span class="strut"> </span></p> +<p id="t207" class="pln"><span class="strut"> </span></p> +<p id="t208" class="stm mis"> <span class="nam">feet_to_meters</span> <span class="op">=</span> <span class="op">(</span><span class="num">2.54</span> <span class="op">*</span> <span class="num">12</span><span class="op">)</span> <span class="op">/</span> <span class="num">100</span><span class="strut"> </span></p> +<p id="t209" class="pln"><span class="strut"> </span></p> +<p id="t210" class="stm mis"> <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_ras_units</span> <span class="op">==</span> <span class="str">'English'</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t211" class="stm mis"> <span class="nam">profile_data</span><span class="op">[</span><span class="str">'Depth_m'</span><span class="op">]</span> <span class="op">*=</span> <span class="nam">feet_to_meters</span><span class="strut"> </span></p> +<p id="t212" class="stm mis"> <span class="nam">profile_data</span><span class="op">[</span><span class="str">'Q_cms'</span><span class="op">]</span> <span class="op">*=</span> <span class="nam">feet_to_meters</span><span class="op">**</span><span class="num">3</span><span class="strut"> </span></p> +<p id="t213" class="stm mis"> <span class="nam">profile_data</span><span class="op">[</span><span class="str">'Vmag_mps'</span><span class="op">]</span> <span class="op">*=</span> <span class="nam">feet_to_meters</span><span class="strut"> </span></p> +<p id="t214" class="pln"> <span class="com"># already converted from m to km</span><span class="strut"> </span></p> +<p id="t215" class="stm mis"> <span class="nam">profile_data</span><span class="op">[</span><span class="str">'CumlDistance_km'</span><span class="op">]</span> <span class="op">*=</span> <span class="nam">feet_to_meters</span><span class="strut"> </span></p> +<p id="t216" class="stm mis"> <span class="nam">profile_data</span><span class="op">[</span><span class="str">'Ustar_mps'</span><span class="op">]</span> <span class="op">*=</span> <span class="nam">feet_to_meters</span><span class="strut"> </span></p> +<p id="t217" class="pln"><span class="strut"> </span></p> +<p id="t218" class="stm mis"> <span class="key">return</span> <span class="nam">profile_data</span><span class="strut"> </span></p> +<p id="t219" class="pln"><span class="strut"> </span></p> +<p id="t220" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_get_time_series_index</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t221" class="pln"><span class="strut"> </span></p> +<p id="t222" class="stm mis"> <span class="nam">hydraulic_times</span> <span class="op">=</span> <span class="op">[</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t223" class="pln"><span class="strut"> </span></p> +<p id="t224" class="stm mis"> <span class="key">for</span> <span class="nam">name</span> <span class="key">in</span> <span class="nam">self</span><span class="op">.</span><span class="nam">profile_names</span><span class="op">(</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t225" class="pln"><span class="strut"> </span></p> +<p id="t226" class="pln"> <span class="com"># convert string to Datetime instance</span><span class="strut"> </span></p> +<p id="t227" class="stm mis"> <span class="key">try</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t228" class="stm mis"> <span class="nam">day</span> <span class="op">=</span> <span class="nam">name</span><span class="op">[</span><span class="op">:</span><span class="num">2</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t229" class="stm mis"> <span class="nam">month</span> <span class="op">=</span> <span class="nam">name</span><span class="op">[</span><span class="num">2</span><span class="op">:</span><span class="num">5</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t230" class="stm mis"> <span class="nam">year</span> <span class="op">=</span> <span class="nam">name</span><span class="op">[</span><span class="num">5</span><span class="op">:</span><span class="num">9</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t231" class="stm mis"> <span class="nam">hour</span> <span class="op">=</span> <span class="nam">name</span><span class="op">[</span><span class="num">10</span><span class="op">:</span><span class="num">12</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t232" class="stm mis"> <span class="nam">minute</span> <span class="op">=</span> <span class="nam">name</span><span class="op">[</span><span class="num">12</span><span class="op">:</span><span class="num">14</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t233" class="pln"><span class="strut"> </span></p> +<p id="t234" class="pln"> <span class="com"># if the hour is midnight, convert to midnight at 00</span><span class="strut"> </span></p> +<p id="t235" class="stm mis"> <span class="key">if</span> <span class="nam">int</span><span class="op">(</span><span class="nam">hour</span><span class="op">)</span> <span class="op">==</span> <span class="num">24</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t236" class="stm mis"> <span class="nam">date_time</span> <span class="op">=</span> <span class="nam">pd</span><span class="op">.</span><span class="nam">to_datetime</span><span class="op">(</span><span class="strut"> </span></p> +<p id="t237" class="pln"> <span class="str">''</span><span class="op">.</span><span class="nam">join</span><span class="op">(</span><span class="op">[</span><span class="nam">day</span><span class="op">,</span> <span class="nam">month</span><span class="op">,</span> <span class="nam">year</span><span class="op">,</span> <span class="str">' 00'</span><span class="op">,</span> <span class="nam">minute</span><span class="op">]</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span> <span class="nam">timedelta</span><span class="op">(</span><span class="nam">days</span><span class="op">=</span><span class="num">1</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t238" class="pln"> <span class="key">else</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t239" class="stm mis"> <span class="nam">date_time</span> <span class="op">=</span> <span class="nam">pd</span><span class="op">.</span><span class="nam">to_datetime</span><span class="op">(</span><span class="strut"> </span></p> +<p id="t240" class="pln"> <span class="str">''</span><span class="op">.</span><span class="nam">join</span><span class="op">(</span><span class="op">[</span><span class="nam">day</span><span class="op">,</span> <span class="nam">month</span><span class="op">,</span> <span class="nam">year</span><span class="op">,</span> <span class="str">' '</span><span class="op">,</span> <span class="nam">hour</span><span class="op">,</span> <span class="nam">minute</span><span class="op">]</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t241" class="pln"><span class="strut"> </span></p> +<p id="t242" class="stm mis"> <span class="nam">hydraulic_times</span><span class="op">.</span><span class="nam">append</span><span class="op">(</span><span class="nam">date_time</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t243" class="pln"><span class="strut"> </span></p> +<p id="t244" class="stm mis"> <span class="key">except</span> <span class="nam">ValueError</span><span class="op">:</span> <span class="com"># skip profile name if ValueError is raised</span><span class="strut"> </span></p> +<p id="t245" class="stm mis"> <span class="key">continue</span><span class="strut"> </span></p> +<p id="t246" class="pln"><span class="strut"> </span></p> +<p id="t247" class="stm mis"> <span class="key">return</span> <span class="nam">pd</span><span class="op">.</span><span class="nam">DatetimeIndex</span><span class="op">(</span><span class="nam">hydraulic_times</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t248" class="pln"><span class="strut"> </span></p> +<p id="t249" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_get_unsteady_data</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">temperature</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t250" class="pln"><span class="strut"> </span></p> +<p id="t251" class="stm mis"> <span class="nam">profile_data</span> <span class="op">=</span> <span class="op">[</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t252" class="pln"><span class="strut"> </span></p> +<p id="t253" class="stm mis"> <span class="nam">profile_names</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">profile_names</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t254" class="pln"><span class="strut"> </span></p> +<p id="t255" class="pln"> <span class="com"># the first profile is the maximum water surface elevation, so skip it</span><span class="strut"> </span></p> +<p id="t256" class="stm mis"> <span class="key">for</span> <span class="nam">profile_number</span> <span class="key">in</span> <span class="nam">range</span><span class="op">(</span><span class="num">2</span><span class="op">,</span> <span class="nam">len</span><span class="op">(</span><span class="nam">profile_names</span><span class="op">)</span><span class="op">+</span><span class="num">1</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t257" class="stm mis"> <span class="nam">profile_data</span><span class="op">.</span><span class="nam">append</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_get_profile_data</span><span class="op">(</span><span class="strut"> </span></p> +<p id="t258" class="pln"> <span class="nam">profile_number</span><span class="op">,</span> <span class="nam">temperature</span><span class="op">)</span><span class="op">.</span><span class="nam">transpose</span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t259" class="pln"><span class="strut"> </span></p> +<p id="t260" class="stm mis"> <span class="nam">time_steps</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_get_time_series_index</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t261" class="pln"><span class="strut"> </span></p> +<p id="t262" class="stm mis"> <span class="key">return</span> <span class="nam">pd</span><span class="op">.</span><span class="nam">concat</span><span class="op">(</span><span class="nam">profile_data</span><span class="op">,</span> <span class="nam">keys</span><span class="op">=</span><span class="nam">time_steps</span><span class="op">,</span> <span class="nam">axis</span><span class="op">=</span><span class="num">1</span><span class="op">)</span><span class="op">.</span><span class="nam">transpose</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t263" class="pln"><span class="strut"> </span></p> +<p id="t264" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_ras_set_current_plan</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">plan_name</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t265" class="pln"><span class="strut"> </span></p> +<p id="t266" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">_ras_controller</span><span class="op">.</span><span class="nam">Plan_SetCurrent</span><span class="op">(</span><span class="nam">plan_name</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t267" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">_ras_controller</span><span class="op">.</span><span class="nam">Project_Save</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t268" class="pln"><span class="strut"> </span></p> +<p id="t269" class="stm mis"> <span class="nam">current_steady_file</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_ras_controller</span><span class="op">.</span><span class="nam">CurrentSteadyFile</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t270" class="stm mis"> <span class="key">if</span> <span class="nam">os</span><span class="op">.</span><span class="nam">path</span><span class="op">.</span><span class="nam">isfile</span><span class="op">(</span><span class="nam">current_steady_file</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t271" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">_plan_has_steady_file</span> <span class="op">=</span> <span class="key">True</span><span class="strut"> </span></p> +<p id="t272" class="pln"> <span class="key">else</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t273" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">_plan_has_steady_file</span> <span class="op">=</span> <span class="key">False</span><span class="strut"> </span></p> +<p id="t274" class="pln"><span class="strut"> </span></p> +<p id="t275" class="stm mis"> <span class="nam">current_unsteady_file</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_ras_controller</span><span class="op">.</span><span class="nam">CurrentUnSteadyFile</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t276" class="stm mis"> <span class="key">if</span> <span class="nam">os</span><span class="op">.</span><span class="nam">path</span><span class="op">.</span><span class="nam">isfile</span><span class="op">(</span><span class="nam">current_unsteady_file</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t277" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">_plan_has_unsteady_file</span> <span class="op">=</span> <span class="key">True</span><span class="strut"> </span></p> +<p id="t278" class="pln"> <span class="key">else</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t279" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">_plan_has_unsteady_file</span> <span class="op">=</span> <span class="key">False</span><span class="strut"> </span></p> +<p id="t280" class="pln"><span class="strut"> </span></p> +<p id="t281" class="stm run hide_run"> <span class="key">def</span> <span class="nam">close</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t282" class="pln"> <span class="str">"""Close the RAS controller</span><span class="strut"> </span></p> +<p id="t283" class="pln"><span class="strut"> </span></p> +<p id="t284" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t285" class="pln"><span class="strut"> </span></p> +<p id="t286" class="stm mis"> <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_ras_controller</span> <span class="key">is</span> <span class="key">None</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t287" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="str">"Operation on closed RASProject"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t288" class="pln"><span class="strut"> </span></p> +<p id="t289" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">_ras_controller</span><span class="op">.</span><span class="nam">QuitRas</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t290" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">_ras_controller</span> <span class="op">=</span> <span class="key">None</span><span class="strut"> </span></p> +<p id="t291" class="pln"><span class="strut"> </span></p> +<p id="t292" class="stm run hide_run"> <span class="key">def</span> <span class="nam">current_plan_name</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t293" class="pln"> <span class="str">"""Returns the current plan name</span><span class="strut"> </span></p> +<p id="t294" class="pln"><span class="strut"> </span></p> +<p id="t295" class="pln"><span class="str"> Returns</span><span class="strut"> </span></p> +<p id="t296" class="pln"><span class="str"> -------</span><span class="strut"> </span></p> +<p id="t297" class="pln"><span class="str"> str</span><span class="strut"> </span></p> +<p id="t298" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t299" class="pln"><span class="strut"> </span></p> +<p id="t300" class="stm mis"> <span class="nam">plan_names</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">plan_names</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t301" class="pln"><span class="strut"> </span></p> +<p id="t302" class="stm mis"> <span class="key">return</span> <span class="nam">plan_names</span><span class="op">[</span><span class="nam">self</span><span class="op">.</span><span class="nam">_current_plan_number</span><span class="op">-</span><span class="num">1</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t303" class="pln"><span class="strut"> </span></p> +<p id="t304" class="stm run hide_run"> <span class="key">def</span> <span class="nam">current_reach_name</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t305" class="pln"> <span class="str">"""Returns the current reach name</span><span class="strut"> </span></p> +<p id="t306" class="pln"><span class="strut"> </span></p> +<p id="t307" class="pln"><span class="str"> Returns</span><span class="strut"> </span></p> +<p id="t308" class="pln"><span class="str"> -------</span><span class="strut"> </span></p> +<p id="t309" class="pln"><span class="str"> str</span><span class="strut"> </span></p> +<p id="t310" class="pln"><span class="strut"> </span></p> +<p id="t311" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t312" class="pln"><span class="strut"> </span></p> +<p id="t313" class="stm mis"> <span class="nam">reach_names</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">reach_names</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t314" class="pln"><span class="strut"> </span></p> +<p id="t315" class="stm mis"> <span class="key">return</span> <span class="nam">reach_names</span><span class="op">[</span><span class="nam">self</span><span class="op">.</span><span class="nam">_current_reach_number</span><span class="op">-</span><span class="num">1</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t316" class="pln"><span class="strut"> </span></p> +<p id="t317" class="stm run hide_run"> <span class="key">def</span> <span class="nam">current_river_name</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t318" class="pln"> <span class="str">"""Returns the current river name</span><span class="strut"> </span></p> +<p id="t319" class="pln"><span class="strut"> </span></p> +<p id="t320" class="pln"><span class="str"> Returns</span><span class="strut"> </span></p> +<p id="t321" class="pln"><span class="str"> -------</span><span class="strut"> </span></p> +<p id="t322" class="pln"><span class="str"> str</span><span class="strut"> </span></p> +<p id="t323" class="pln"><span class="strut"> </span></p> +<p id="t324" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t325" class="pln"><span class="strut"> </span></p> +<p id="t326" class="stm mis"> <span class="nam">river_names</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">river_names</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t327" class="pln"><span class="strut"> </span></p> +<p id="t328" class="stm mis"> <span class="key">return</span> <span class="nam">river_names</span><span class="op">[</span><span class="nam">self</span><span class="op">.</span><span class="nam">_current_river_number</span><span class="op">-</span><span class="num">1</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t329" class="pln"><span class="strut"> </span></p> +<p id="t330" class="stm run hide_run"> <span class="key">def</span> <span class="nam">hydraulic_model_data</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">profile_name</span><span class="op">,</span> <span class="nam">temperature</span><span class="op">=</span><span class="num">22</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t331" class="pln"> <span class="str">"""Returns a pandas.DataFrame containing hydraulic data for the specified profile.</span><span class="strut"> </span></p> +<p id="t332" class="pln"><span class="strut"> </span></p> +<p id="t333" class="pln"><span class="str"> If 'Unsteady' is specified for profile_name, the index of the DataFrame will be a pandas.MultiIndex</span><span class="strut"> </span></p> +<p id="t334" class="pln"><span class="strut"> </span></p> +<p id="t335" class="pln"><span class="str"> Parameters</span><span class="strut"> </span></p> +<p id="t336" class="pln"><span class="str"> ----------</span><span class="strut"> </span></p> +<p id="t337" class="pln"><span class="str"> profile_name : str</span><span class="strut"> </span></p> +<p id="t338" class="pln"><span class="str"> Name of profile. The name must be in the list of profiles or 'Unsteady'. If 'Unsteady', the</span><span class="strut"> </span></p> +<p id="t339" class="pln"><span class="str"> RAS profile must have an associated unsteady file.</span><span class="strut"> </span></p> +<p id="t340" class="pln"><span class="str"> temperature : float</span><span class="strut"> </span></p> +<p id="t341" class="pln"><span class="str"> Water temperature</span><span class="strut"> </span></p> +<p id="t342" class="pln"><span class="strut"> </span></p> +<p id="t343" class="pln"><span class="str"> Returns</span><span class="strut"> </span></p> +<p id="t344" class="pln"><span class="str"> -------</span><span class="strut"> </span></p> +<p id="t345" class="pln"><span class="str"> pandas.DataFrame</span><span class="strut"> </span></p> +<p id="t346" class="pln"><span class="strut"> </span></p> +<p id="t347" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t348" class="pln"><span class="strut"> </span></p> +<p id="t349" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">_ras_set_current_plan</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">current_plan_name</span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t350" class="pln"><span class="strut"> </span></p> +<p id="t351" class="stm mis"> <span class="key">if</span> <span class="nam">profile_name</span> <span class="op">==</span> <span class="str">'Unsteady'</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t352" class="stm mis"> <span class="key">if</span> <span class="key">not</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_plan_has_unsteady_file</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t353" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="str">"Current plan does not have an unsteady file"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t354" class="stm mis"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_get_unsteady_data</span><span class="op">(</span><span class="nam">temperature</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t355" class="pln"> <span class="key">else</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t356" class="stm mis"> <span class="nam">profile_number</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">profile_names</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">index</span><span class="op">(</span><span class="strut"> </span></p> +<p id="t357" class="pln"> <span class="nam">profile_name</span><span class="op">)</span> <span class="op">+</span> <span class="num">1</span> <span class="com"># add one to profile_name index for RAS</span><span class="strut"> </span></p> +<p id="t358" class="stm mis"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_get_profile_data</span><span class="op">(</span><span class="nam">profile_number</span><span class="op">,</span> <span class="nam">temperature</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t359" class="pln"><span class="strut"> </span></p> +<p id="t360" class="stm run hide_run"> <span class="key">def</span> <span class="nam">plan_names</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t361" class="pln"> <span class="str">"""Returns a list of plan names in this RAS project.</span><span class="strut"> </span></p> +<p id="t362" class="pln"><span class="strut"> </span></p> +<p id="t363" class="pln"><span class="str"> Returns</span><span class="strut"> </span></p> +<p id="t364" class="pln"><span class="str"> -------</span><span class="strut"> </span></p> +<p id="t365" class="pln"><span class="str"> list</span><span class="strut"> </span></p> +<p id="t366" class="pln"><span class="strut"> </span></p> +<p id="t367" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t368" class="pln"><span class="strut"> </span></p> +<p id="t369" class="stm mis"> <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_ras_controller</span> <span class="key">is</span> <span class="key">None</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t370" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="str">"Operation on closed RASProject"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t371" class="pln"><span class="strut"> </span></p> +<p id="t372" class="stm mis"> <span class="nam">_</span><span class="op">,</span> <span class="nam">plan_names</span><span class="op">,</span> <span class="nam">_</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_ras_controller</span><span class="op">.</span><span class="nam">Plan_Names</span><span class="op">(</span><span class="strut"> </span></p> +<p id="t373" class="pln"> <span class="key">None</span><span class="op">,</span> <span class="key">None</span><span class="op">,</span> <span class="key">False</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t374" class="pln"><span class="strut"> </span></p> +<p id="t375" class="stm mis"> <span class="key">return</span> <span class="nam">list</span><span class="op">(</span><span class="nam">plan_names</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t376" class="pln"><span class="strut"> </span></p> +<p id="t377" class="stm run hide_run"> <span class="key">def</span> <span class="nam">profile_names</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t378" class="pln"> <span class="str">"""Returns a list of profile names in this RAS project.</span><span class="strut"> </span></p> +<p id="t379" class="pln"><span class="strut"> </span></p> +<p id="t380" class="pln"><span class="str"> Returns</span><span class="strut"> </span></p> +<p id="t381" class="pln"><span class="str"> -------</span><span class="strut"> </span></p> +<p id="t382" class="pln"><span class="str"> list</span><span class="strut"> </span></p> +<p id="t383" class="pln"><span class="strut"> </span></p> +<p id="t384" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t385" class="pln"><span class="strut"> </span></p> +<p id="t386" class="stm mis"> <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_ras_controller</span> <span class="key">is</span> <span class="key">None</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t387" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="str">"Operation on closed RASProject"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t388" class="pln"><span class="strut"> </span></p> +<p id="t389" class="stm mis"> <span class="nam">_</span><span class="op">,</span> <span class="nam">profile_names</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_ras_controller</span><span class="op">.</span><span class="nam">Output_GetProfiles</span><span class="op">(</span><span class="key">None</span><span class="op">,</span> <span class="key">None</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t390" class="pln"><span class="strut"> </span></p> +<p id="t391" class="stm mis"> <span class="key">return</span> <span class="nam">list</span><span class="op">(</span><span class="nam">profile_names</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t392" class="pln"><span class="strut"> </span></p> +<p id="t393" class="stm run hide_run"> <span class="key">def</span> <span class="nam">project_units</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t394" class="pln"> <span class="str">"""Returns the RAS project units.</span><span class="strut"> </span></p> +<p id="t395" class="pln"><span class="strut"> </span></p> +<p id="t396" class="pln"><span class="str"> Returns</span><span class="strut"> </span></p> +<p id="t397" class="pln"><span class="str"> -------</span><span class="strut"> </span></p> +<p id="t398" class="pln"><span class="str"> str</span><span class="strut"> </span></p> +<p id="t399" class="pln"><span class="strut"> </span></p> +<p id="t400" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t401" class="pln"><span class="strut"> </span></p> +<p id="t402" class="stm mis"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_ras_units</span><span class="strut"> </span></p> +<p id="t403" class="pln"><span class="strut"> </span></p> +<p id="t404" class="stm run hide_run"> <span class="op">@</span><span class="nam">staticmethod</span><span class="strut"> </span></p> +<p id="t405" class="pln"> <span class="key">def</span> <span class="nam">ras_controller_loaded</span><span class="op">(</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t406" class="stm mis"> <span class="key">return</span> <span class="nam">ras_controller_loaded</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t407" class="pln"><span class="strut"> </span></p> +<p id="t408" class="stm run hide_run"> <span class="key">def</span> <span class="nam">reach_names</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t409" class="pln"> <span class="str">"""Returns a list of reach names in this RAS project.</span><span class="strut"> </span></p> +<p id="t410" class="pln"><span class="strut"> </span></p> +<p id="t411" class="pln"><span class="str"> Returns</span><span class="strut"> </span></p> +<p id="t412" class="pln"><span class="str"> -------</span><span class="strut"> </span></p> +<p id="t413" class="pln"><span class="str"> list</span><span class="strut"> </span></p> +<p id="t414" class="pln"><span class="strut"> </span></p> +<p id="t415" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t416" class="pln"><span class="strut"> </span></p> +<p id="t417" class="stm mis"> <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_ras_controller</span> <span class="key">is</span> <span class="key">None</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t418" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="str">"Operation on closed RASProject"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t419" class="pln"><span class="strut"> </span></p> +<p id="t420" class="stm mis"> <span class="nam">_</span><span class="op">,</span> <span class="nam">_</span><span class="op">,</span> <span class="nam">reach_names</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_ras_controller</span><span class="op">.</span><span class="nam">Geometry_GetReaches</span><span class="op">(</span><span class="strut"> </span></p> +<p id="t421" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">_current_river_number</span><span class="op">,</span> <span class="key">None</span><span class="op">,</span> <span class="key">None</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t422" class="pln"><span class="strut"> </span></p> +<p id="t423" class="stm mis"> <span class="key">return</span> <span class="nam">list</span><span class="op">(</span><span class="nam">reach_names</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t424" class="pln"><span class="strut"> </span></p> +<p id="t425" class="stm run hide_run"> <span class="key">def</span> <span class="nam">river_names</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t426" class="pln"> <span class="str">"""Returns a list of river names in this RAS project.</span><span class="strut"> </span></p> +<p id="t427" class="pln"><span class="strut"> </span></p> +<p id="t428" class="pln"><span class="str"> Returns</span><span class="strut"> </span></p> +<p id="t429" class="pln"><span class="str"> -------</span><span class="strut"> </span></p> +<p id="t430" class="pln"><span class="str"> list</span><span class="strut"> </span></p> +<p id="t431" class="pln"><span class="strut"> </span></p> +<p id="t432" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t433" class="pln"><span class="strut"> </span></p> +<p id="t434" class="stm mis"> <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_ras_controller</span> <span class="key">is</span> <span class="key">None</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t435" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="str">"Operation on closed RASProject"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t436" class="pln"><span class="strut"> </span></p> +<p id="t437" class="stm mis"> <span class="nam">_</span><span class="op">,</span> <span class="nam">river_names</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_ras_controller</span><span class="op">.</span><span class="nam">Geometry_GetRivers</span><span class="op">(</span><span class="key">None</span><span class="op">,</span> <span class="key">None</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t438" class="pln"><span class="strut"> </span></p> +<p id="t439" class="stm mis"> <span class="key">return</span> <span class="nam">list</span><span class="op">(</span><span class="nam">river_names</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t440" class="pln"><span class="strut"> </span></p> +<p id="t441" class="stm run hide_run"> <span class="key">def</span> <span class="nam">set_current_plan</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">plan_name</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t442" class="pln"> <span class="str">"""Sets the current plan name for this RAS project.</span><span class="strut"> </span></p> +<p id="t443" class="pln"><span class="strut"> </span></p> +<p id="t444" class="pln"><span class="str"> Parameters</span><span class="strut"> </span></p> +<p id="t445" class="pln"><span class="str"> ----------</span><span class="strut"> </span></p> +<p id="t446" class="pln"><span class="str"> plan_name : str</span><span class="strut"> </span></p> +<p id="t447" class="pln"><span class="str"> Plan name. The plan name must be in the list of plan names of this project.</span><span class="strut"> </span></p> +<p id="t448" class="pln"><span class="strut"> </span></p> +<p id="t449" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t450" class="pln"><span class="strut"> </span></p> +<p id="t451" class="stm mis"> <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_ras_controller</span> <span class="key">is</span> <span class="key">None</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t452" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="str">"Operation on closed RASProject"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t453" class="pln"><span class="strut"> </span></p> +<p id="t454" class="stm mis"> <span class="nam">plan_names</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">plan_names</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t455" class="pln"><span class="strut"> </span></p> +<p id="t456" class="stm mis"> <span class="key">if</span> <span class="nam">plan_name</span> <span class="key">not</span> <span class="key">in</span> <span class="nam">plan_names</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t457" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="str">"Invalid plan name"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t458" class="pln"><span class="strut"> </span></p> +<p id="t459" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">_current_plan_number</span> <span class="op">=</span> <span class="nam">plan_names</span><span class="op">.</span><span class="nam">index</span><span class="op">(</span><span class="nam">plan_name</span><span class="op">)</span> <span class="op">+</span> <span class="num">1</span><span class="strut"> </span></p> + + </td> + </tr> + </table> +</div> + +<div id="footer"> + <div class="content"> + <p> + <a class="nav" href="index.html">« index</a> <a class="nav" href="https://coverage.readthedocs.io">coverage.py v4.5.3</a>, + created at 2019-07-09 15:15 + </p> + </div> +</div> + +</body> +</html> diff --git a/coverage_report/fluegg_simclock_py.html b/coverage_report/fluegg_simclock_py.html new file mode 100644 index 0000000..1ad0185 --- /dev/null +++ b/coverage_report/fluegg_simclock_py.html @@ -0,0 +1,361 @@ + + + +<!DOCTYPE html> +<html> +<head> + <meta http-equiv="Content-Type" content="text/html; charset=utf-8"> + + + <meta http-equiv="X-UA-Compatible" content="IE=emulateIE7" /> + <title>Coverage for fluegg\simclock.py: 89%</title> + <link rel="stylesheet" href="style.css" type="text/css"> + + <script type="text/javascript" src="jquery.min.js"></script> + <script type="text/javascript" src="jquery.hotkeys.js"></script> + <script type="text/javascript" src="jquery.isonscreen.js"></script> + <script type="text/javascript" src="coverage_html.js"></script> + <script type="text/javascript"> + jQuery(document).ready(coverage.pyfile_ready); + </script> +</head> +<body class="pyfile"> + +<div id="header"> + <div class="content"> + <h1>Coverage for <b>fluegg\simclock.py</b> : + <span class="pc_cov">89%</span> + </h1> + + <img id="keyboard_icon" src="keybd_closed.png" alt="Show keyboard shortcuts" /> + + <h2 class="stats"> + 46 statements + <span class="run hide_run shortkey_r button_toggle_run">41 run</span> + <span class="mis shortkey_m button_toggle_mis">5 missing</span> + <span class="exc shortkey_x button_toggle_exc">0 excluded</span> + + + </h2> + </div> +</div> + +<div class="help_panel"> + <img id="panel_icon" src="keybd_open.png" alt="Hide keyboard shortcuts" /> + <p class="legend">Hot-keys on this page</p> + <div> + <p class="keyhelp"> + <span class="key">r</span> + <span class="key">m</span> + <span class="key">x</span> + <span class="key">p</span> toggle line displays + </p> + <p class="keyhelp"> + <span class="key">j</span> + <span class="key">k</span> next/prev highlighted chunk + </p> + <p class="keyhelp"> + <span class="key">0</span> (zero) top of page + </p> + <p class="keyhelp"> + <span class="key">1</span> (one) first highlighted chunk + </p> + </div> +</div> + +<div id="source"> + <table> + <tr> + <td class="linenos"> +<p id="n1" class="stm run hide_run"><a href="#n1">1</a></p> +<p id="n2" class="pln"><a href="#n2">2</a></p> +<p id="n3" class="pln"><a href="#n3">3</a></p> +<p id="n4" class="stm run hide_run"><a href="#n4">4</a></p> +<p id="n5" class="pln"><a href="#n5">5</a></p> +<p id="n6" class="pln"><a href="#n6">6</a></p> +<p id="n7" class="pln"><a href="#n7">7</a></p> +<p id="n8" class="pln"><a href="#n8">8</a></p> +<p id="n9" 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href="#n133">133</a></p> +<p id="n134" class="stm mis"><a href="#n134">134</a></p> +<p id="n135" class="stm mis"><a href="#n135">135</a></p> +<p id="n136" class="pln"><a href="#n136">136</a></p> + + </td> + <td class="text"> +<p id="t1" class="stm run hide_run"><span class="key">import</span> <span class="nam">numpy</span> <span class="key">as</span> <span class="nam">np</span><span class="strut"> </span></p> +<p id="t2" class="pln"><span class="strut"> </span></p> +<p id="t3" class="pln"><span class="strut"> </span></p> +<p id="t4" class="stm run hide_run"><span class="key">class</span> <span class="nam">SimulationClock</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t5" class="pln"> <span class="str">"""Class representing a simulation clock</span><span class="strut"> </span></p> +<p id="t6" class="pln"><span class="strut"> </span></p> +<p id="t7" class="pln"><span class="str"> Parameters</span><span class="strut"> </span></p> +<p id="t8" class="pln"><span class="str"> ----------</span><span class="strut"> </span></p> +<p id="t9" class="pln"><span class="str"> time_step_size : int</span><span class="strut"> </span></p> +<p id="t10" class="pln"><span class="str"> Number of seconds per time step</span><span class="strut"> </span></p> +<p id="t11" class="pln"><span class="strut"> </span></p> +<p id="t12" class="pln"><span class="str"> total_simulation_time : int</span><span class="strut"> </span></p> +<p id="t13" class="pln"><span class="str"> Number of total seconds in the simulation</span><span class="strut"> </span></p> +<p id="t14" class="pln"><span class="strut"> </span></p> +<p id="t15" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t16" class="pln"><span class="strut"> </span></p> +<p id="t17" class="stm run hide_run"> <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">time_step_size</span><span class="op">,</span> <span class="nam">total_simulation_time</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t18" class="pln"><span class="strut"> </span></p> +<p id="t19" class="stm run hide_run"> <span class="key">if</span> <span class="nam">total_simulation_time</span> <span class="op">%</span> <span class="nam">time_step_size</span> <span class="op">==</span> <span class="num">0</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t20" class="stm run hide_run"> <span class="nam">time_array</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">arange</span><span class="op">(</span><span class="num">0</span><span class="op">,</span> <span class="nam">total_simulation_time</span> <span class="op">+</span> <span class="nam">time_step_size</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t21" class="pln"> <span class="nam">time_step_size</span><span class="op">,</span> <span class="nam">dtype</span><span class="op">=</span><span class="nam">float</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t22" class="pln"> <span class="key">else</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t23" class="stm run hide_run"> <span class="nam">time_array</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">arange</span><span class="op">(</span><span class="num">0</span><span class="op">,</span> <span class="nam">total_simulation_time</span><span class="op">,</span> <span class="nam">time_step_size</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t24" class="pln"> <span class="nam">dtype</span><span class="op">=</span><span class="nam">float</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t25" class="pln"><span class="strut"> </span></p> +<p id="t26" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_time_array</span> <span class="op">=</span> <span class="nam">time_array</span><span class="strut"> </span></p> +<p id="t27" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_current_time_index</span> <span class="op">=</span> <span class="num">0</span><span class="strut"> </span></p> +<p id="t28" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_time_step_size</span> <span class="op">=</span> <span class="nam">time_step_size</span><span class="strut"> </span></p> +<p id="t29" class="pln"><span class="strut"> </span></p> +<p id="t30" class="stm run hide_run"> <span class="key">def</span> <span class="nam">current_time</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t31" class="pln"> <span class="str">"""Returns the current simulation time in seconds</span><span class="strut"> </span></p> +<p id="t32" class="pln"><span class="strut"> </span></p> +<p id="t33" class="pln"><span class="str"> :return: sim time (s)</span><span class="strut"> </span></p> +<p id="t34" class="pln"><span class="str"> :rtype: float</span><span class="strut"> </span></p> +<p id="t35" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t36" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_time_array</span><span class="op">[</span><span class="nam">self</span><span class="op">.</span><span class="nam">_current_time_index</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t37" class="pln"><span class="strut"> </span></p> +<p id="t38" class="stm run hide_run"> <span class="key">def</span> <span class="nam">current_time_index</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t39" class="pln"> <span class="str">"""Returns the current simulation time index</span><span class="strut"> </span></p> +<p id="t40" class="pln"><span class="strut"> </span></p> +<p id="t41" class="pln"><span class="str"> :return: sim time index</span><span class="strut"> </span></p> +<p id="t42" class="pln"><span class="str"> :rtype: int</span><span class="strut"> </span></p> +<p id="t43" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t44" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_current_time_index</span><span class="strut"> </span></p> +<p id="t45" class="pln"><span class="strut"> </span></p> +<p id="t46" class="stm run hide_run"> <span class="key">def</span> <span class="nam">number_of_time_steps</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t47" class="pln"> <span class="str">"""Returns the total number of time steps in the simultaion</span><span class="strut"> </span></p> +<p id="t48" class="pln"><span class="strut"> </span></p> +<p id="t49" class="pln"><span class="str"> :return: num time steps</span><span class="strut"> </span></p> +<p id="t50" class="pln"><span class="str"> :rtype: int</span><span class="strut"> </span></p> +<p id="t51" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t52" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_time_array</span><span class="op">.</span><span class="nam">size</span><span class="strut"> </span></p> +<p id="t53" class="pln"><span class="strut"> </span></p> +<p id="t54" class="stm run hide_run"> <span class="key">def</span> <span class="nam">time_array</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t55" class="pln"> <span class="str">"""Returns the array of all time steps in seconds (s)</span><span class="strut"> </span></p> +<p id="t56" class="pln"><span class="strut"> </span></p> +<p id="t57" class="pln"><span class="str"> :return: array of all time steps (s)</span><span class="strut"> </span></p> +<p id="t58" class="pln"><span class="str"> :rtype: np.ndarray</span><span class="strut"> </span></p> +<p id="t59" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t60" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_time_array</span><span class="op">.</span><span class="nam">copy</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t61" class="pln"><span class="strut"> </span></p> +<p id="t62" class="stm run hide_run"> <span class="key">def</span> <span class="nam">time_step_size</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t63" class="pln"> <span class="str">"""Returns the simulation time step size in seconds</span><span class="strut"> </span></p> +<p id="t64" class="pln"><span class="strut"> </span></p> +<p id="t65" class="pln"><span class="str"> :return: time step size (s)</span><span class="strut"> </span></p> +<p id="t66" class="pln"><span class="str"> :rtype: float</span><span class="strut"> </span></p> +<p id="t67" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t68" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_time_step_size</span><span class="strut"> </span></p> +<p id="t69" class="pln"><span class="strut"> </span></p> +<p id="t70" class="stm run hide_run"> <span class="key">def</span> <span class="nam">iter_time_index</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t71" class="pln"><span class="strut"> </span></p> +<p id="t72" class="stm run hide_run"> <span class="key">return</span> <span class="nam">TimeStepIterable</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t73" class="pln"><span class="strut"> </span></p> +<p id="t74" class="stm run hide_run"> <span class="key">def</span> <span class="nam">set_time_index</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">time_index</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t75" class="pln"> <span class="str">"""</span><span class="strut"> </span></p> +<p id="t76" class="pln"><span class="strut"> </span></p> +<p id="t77" class="pln"><span class="str"> :param time_index:</span><span class="strut"> </span></p> +<p id="t78" class="pln"><span class="str"> :type time_index: int</span><span class="strut"> </span></p> +<p id="t79" class="pln"><span class="str"> :return: None</span><span class="strut"> </span></p> +<p id="t80" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t81" class="pln"><span class="strut"> </span></p> +<p id="t82" class="stm run hide_run"> <span class="key">if</span> <span class="op">(</span><span class="num">0</span> <span class="op"><=</span> <span class="nam">time_index</span><span class="op">)</span> <span class="key">and</span> <span class="op">(</span><span class="nam">time_index</span> <span class="op"><</span> <span class="nam">self</span><span class="op">.</span><span class="nam">number_of_time_steps</span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t83" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_current_time_index</span> <span class="op">=</span> <span class="nam">time_index</span><span class="strut"> </span></p> +<p id="t84" class="pln"> <span class="key">else</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t85" class="stm mis"> <span class="key">raise</span> <span class="nam">IndexError</span><span class="op">(</span><span class="str">"Time index out of bounds"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t86" class="pln"><span class="strut"> </span></p> +<p id="t87" class="pln"><span class="strut"> </span></p> +<p id="t88" class="stm run hide_run"><span class="key">class</span> <span class="nam">TimeStepIterable</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t89" class="pln"> <span class="str">"""</span><span class="strut"> </span></p> +<p id="t90" class="pln"><span class="strut"> </span></p> +<p id="t91" class="pln"><span class="str"> Parameters</span><span class="strut"> </span></p> +<p id="t92" class="pln"><span class="str"> ----------</span><span class="strut"> </span></p> +<p id="t93" class="pln"><span class="str"> simulation_clock : SimulationClock</span><span class="strut"> </span></p> +<p id="t94" class="pln"><span class="strut"> </span></p> +<p id="t95" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t96" class="pln"><span class="strut"> </span></p> +<p id="t97" class="stm run hide_run"> <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">simulation_clock</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t98" class="pln"><span class="strut"> </span></p> +<p id="t99" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_simulation_clock</span> <span class="op">=</span> <span class="nam">simulation_clock</span><span class="strut"> </span></p> +<p id="t100" class="pln"><span class="strut"> </span></p> +<p id="t101" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_number_of_time_steps</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t102" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">_simulation_clock</span><span class="op">.</span><span class="nam">number_of_time_steps</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t103" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_current_time_step_index</span> <span class="op">=</span> <span class="num">0</span><span class="strut"> </span></p> +<p id="t104" class="pln"><span class="strut"> </span></p> +<p id="t105" class="stm run hide_run"> <span class="key">def</span> <span class="nam">__iter__</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t106" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="strut"> </span></p> +<p id="t107" class="pln"><span class="strut"> </span></p> +<p id="t108" class="stm run hide_run"> <span class="key">def</span> <span class="nam">__next__</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t109" class="pln"><span class="strut"> </span></p> +<p id="t110" class="stm run hide_run"> <span class="nam">time_step_index</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_current_time_step_index</span><span class="strut"> </span></p> +<p id="t111" class="stm run hide_run"> <span class="key">if</span> <span class="nam">time_step_index</span> <span class="op">==</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_number_of_time_steps</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t112" class="stm run hide_run"> <span class="key">raise</span> <span class="nam">StopIteration</span><span class="strut"> </span></p> +<p id="t113" class="pln"><span class="strut"> </span></p> +<p id="t114" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_current_time_step_index</span> <span class="op">+=</span> <span class="num">1</span><span class="strut"> </span></p> +<p id="t115" class="pln"><span class="strut"> </span></p> +<p id="t116" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_simulation_clock</span><span class="op">.</span><span class="nam">set_time_index</span><span class="op">(</span><span class="nam">time_step_index</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t117" class="pln"><span class="strut"> </span></p> +<p id="t118" class="stm run hide_run"> <span class="key">return</span> <span class="nam">time_step_index</span><span class="strut"> </span></p> +<p id="t119" class="pln"><span class="strut"> </span></p> +<p id="t120" class="pln"><span class="strut"> </span></p> +<p id="t121" class="stm run hide_run"><span class="key">class</span> <span class="nam">ReverseSimulationClock</span><span class="op">(</span><span class="nam">SimulationClock</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t122" class="pln"><span class="strut"> </span></p> +<p id="t123" class="stm run hide_run"> <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">time_step_size</span><span class="op">,</span> <span class="nam">total_simulation_time</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t124" class="stm mis"> <span class="nam">SimulationClock</span><span class="op">.</span><span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">time_step_size</span><span class="op">,</span> <span class="nam">total_simulation_time</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t125" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">_current_time_index</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_time_array</span><span class="op">.</span><span class="nam">shape</span><span class="op">[</span><span class="num">0</span><span class="op">]</span> <span class="op">-</span> <span class="num">1</span><span class="strut"> </span></p> +<p id="t126" class="pln"><span class="strut"> </span></p> +<p id="t127" class="stm run hide_run"> <span class="key">def</span> <span class="nam">increment_time</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t128" class="pln"> <span class="str">"""Increments the simulation time by one time step (s) backwards</span><span class="strut"> </span></p> +<p id="t129" class="pln"><span class="strut"> </span></p> +<p id="t130" class="pln"><span class="str"> :return: time index, time (s)</span><span class="strut"> </span></p> +<p id="t131" class="pln"><span class="str"> :rtype: float, float</span><span class="strut"> </span></p> +<p id="t132" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t133" class="pln"><span class="strut"> </span></p> +<p id="t134" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">_current_time_index</span> <span class="op">-=</span> <span class="num">1</span><span class="strut"> </span></p> +<p id="t135" class="stm mis"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_current_time_index</span><span class="op">,</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t136" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">_time_array</span><span class="op">[</span><span class="nam">self</span><span class="op">.</span><span class="nam">_current_time_index</span><span class="op">]</span><span class="strut"> </span></p> + + </td> + </tr> + </table> +</div> + +<div id="footer"> + <div class="content"> + <p> + <a class="nav" href="index.html">« index</a> <a class="nav" href="https://coverage.readthedocs.io">coverage.py v4.5.3</a>, + created at 2019-07-09 15:15 + </p> + </div> +</div> + +</body> +</html> diff --git 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class="pc_cov">42%</span> + </h1> + + <img id="keyboard_icon" src="keybd_closed.png" alt="Show keyboard shortcuts" /> + + <h2 class="stats"> + 132 statements + <span class="run hide_run shortkey_r button_toggle_run">56 run</span> + <span class="mis shortkey_m button_toggle_mis">76 missing</span> + <span class="exc shortkey_x button_toggle_exc">0 excluded</span> + + + </h2> + </div> +</div> + +<div class="help_panel"> + <img id="panel_icon" src="keybd_open.png" alt="Hide keyboard shortcuts" /> + <p class="legend">Hot-keys on this page</p> + <div> + <p class="keyhelp"> + <span class="key">r</span> + <span class="key">m</span> + <span class="key">x</span> + <span class="key">p</span> toggle line displays + </p> + <p class="keyhelp"> + <span class="key">j</span> + <span class="key">k</span> next/prev highlighted chunk + </p> + <p class="keyhelp"> + <span class="key">0</span> (zero) top of page + </p> + <p class="keyhelp"> + <span class="key">1</span> (one) first highlighted chunk + </p> + 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id="n16" class="stm mis"><a href="#n16">16</a></p> +<p id="n17" class="stm mis"><a href="#n17">17</a></p> +<p id="n18" class="pln"><a href="#n18">18</a></p> +<p id="n19" class="pln"><a href="#n19">19</a></p> +<p id="n20" class="stm run hide_run"><a href="#n20">20</a></p> +<p id="n21" class="pln"><a href="#n21">21</a></p> +<p id="n22" class="pln"><a href="#n22">22</a></p> +<p id="n23" class="pln"><a href="#n23">23</a></p> +<p id="n24" class="pln"><a href="#n24">24</a></p> +<p id="n25" class="pln"><a href="#n25">25</a></p> +<p id="n26" class="pln"><a href="#n26">26</a></p> +<p id="n27" class="pln"><a href="#n27">27</a></p> +<p id="n28" class="pln"><a href="#n28">28</a></p> +<p id="n29" class="pln"><a href="#n29">29</a></p> +<p id="n30" class="pln"><a href="#n30">30</a></p> +<p id="n31" class="pln"><a href="#n31">31</a></p> +<p id="n32" class="pln"><a href="#n32">32</a></p> +<p id="n33" class="pln"><a href="#n33">33</a></p> +<p id="n34" class="pln"><a href="#n34">34</a></p> +<p id="n35" class="pln"><a href="#n35">35</a></p> +<p id="n36" class="pln"><a href="#n36">36</a></p> +<p id="n37" class="stm run hide_run"><a href="#n37">37</a></p> +<p id="n38" class="pln"><a href="#n38">38</a></p> +<p id="n39" class="stm run hide_run"><a href="#n39">39</a></p> +<p id="n40" class="stm run hide_run"><a href="#n40">40</a></p> +<p id="n41" class="stm run hide_run"><a href="#n41">41</a></p> +<p id="n42" class="stm run hide_run"><a href="#n42">42</a></p> +<p id="n43" class="pln"><a href="#n43">43</a></p> +<p id="n44" class="stm run hide_run"><a href="#n44">44</a></p> +<p id="n45" class="pln"><a href="#n45">45</a></p> +<p id="n46" class="stm run hide_run"><a href="#n46">46</a></p> +<p id="n47" class="pln"><a href="#n47">47</a></p> +<p id="n48" class="stm run hide_run"><a href="#n48">48</a></p> +<p id="n49" class="stm run hide_run"><a href="#n49">49</a></p> +<p id="n50" class="pln"><a href="#n50">50</a></p> +<p id="n51" class="stm run hide_run"><a href="#n51">51</a></p> +<p id="n52" class="pln"><a href="#n52">52</a></p> +<p id="n53" class="pln"><a href="#n53">53</a></p> +<p id="n54" class="pln"><a href="#n54">54</a></p> +<p id="n55" class="pln"><a href="#n55">55</a></p> +<p id="n56" class="pln"><a href="#n56">56</a></p> +<p id="n57" class="pln"><a href="#n57">57</a></p> +<p id="n58" class="pln"><a href="#n58">58</a></p> +<p id="n59" class="pln"><a href="#n59">59</a></p> +<p id="n60" class="pln"><a href="#n60">60</a></p> +<p id="n61" class="stm run hide_run"><a href="#n61">61</a></p> +<p id="n62" class="pln"><a href="#n62">62</a></p> +<p id="n63" class="stm run hide_run"><a href="#n63">63</a></p> +<p id="n64" class="pln"><a href="#n64">64</a></p> +<p id="n65" class="pln"><a href="#n65">65</a></p> +<p id="n66" class="pln"><a href="#n66">66</a></p> +<p id="n67" class="pln"><a href="#n67">67</a></p> +<p id="n68" class="pln"><a href="#n68">68</a></p> +<p id="n69" class="pln"><a href="#n69">69</a></p> +<p id="n70" class="pln"><a href="#n70">70</a></p> +<p id="n71" class="pln"><a href="#n71">71</a></p> +<p id="n72" class="pln"><a href="#n72">72</a></p> +<p id="n73" class="pln"><a href="#n73">73</a></p> +<p id="n74" class="stm run hide_run"><a href="#n74">74</a></p> +<p id="n75" class="pln"><a href="#n75">75</a></p> +<p id="n76" class="stm run hide_run"><a href="#n76">76</a></p> +<p id="n77" class="pln"><a href="#n77">77</a></p> +<p id="n78" class="pln"><a href="#n78">78</a></p> +<p id="n79" class="pln"><a href="#n79">79</a></p> +<p id="n80" class="pln"><a href="#n80">80</a></p> +<p id="n81" class="pln"><a href="#n81">81</a></p> +<p id="n82" class="pln"><a href="#n82">82</a></p> +<p id="n83" class="pln"><a href="#n83">83</a></p> +<p id="n84" class="pln"><a href="#n84">84</a></p> +<p id="n85" class="pln"><a href="#n85">85</a></p> +<p id="n86" class="pln"><a href="#n86">86</a></p> +<p id="n87" class="stm run hide_run"><a href="#n87">87</a></p> +<p id="n88" class="pln"><a href="#n88">88</a></p> +<p id="n89" class="stm run hide_run"><a href="#n89">89</a></p> +<p id="n90" class="pln"><a href="#n90">90</a></p> +<p id="n91" class="pln"><a href="#n91">91</a></p> +<p id="n92" class="stm run hide_run"><a href="#n92">92</a></p> +<p id="n93" class="pln"><a href="#n93">93</a></p> +<p id="n94" class="stm run hide_run"><a href="#n94">94</a></p> +<p id="n95" class="pln"><a href="#n95">95</a></p> +<p id="n96" class="pln"><a href="#n96">96</a></p> +<p id="n97" class="stm run hide_run"><a href="#n97">97</a></p> +<p id="n98" class="pln"><a href="#n98">98</a></p> +<p id="n99" class="pln"><a href="#n99">99</a></p> +<p id="n100" class="stm run hide_run"><a href="#n100">100</a></p> +<p id="n101" class="pln"><a href="#n101">101</a></p> +<p id="n102" class="stm run hide_run"><a href="#n102">102</a></p> +<p id="n103" class="stm mis"><a href="#n103">103</a></p> +<p id="n104" class="pln"><a href="#n104">104</a></p> +<p id="n105" class="stm run hide_run"><a href="#n105">105</a></p> +<p id="n106" class="pln"><a href="#n106">106</a></p> +<p id="n107" class="pln"><a href="#n107">107</a></p> +<p id="n108" class="stm run hide_run"><a href="#n108">108</a></p> +<p id="n109" class="pln"><a href="#n109">109</a></p> +<p id="n110" class="stm run hide_run"><a href="#n110">110</a></p> +<p id="n111" class="stm mis"><a href="#n111">111</a></p> +<p id="n112" class="stm mis"><a href="#n112">112</a></p> +<p id="n113" class="pln"><a href="#n113">113</a></p> +<p id="n114" class="stm run hide_run"><a href="#n114">114</a></p> +<p id="n115" class="pln"><a href="#n115">115</a></p> +<p id="n116" class="pln"><a href="#n116">116</a></p> +<p id="n117" class="pln"><a href="#n117">117</a></p> +<p id="n118" class="pln"><a href="#n118">118</a></p> +<p id="n119" class="pln"><a href="#n119">119</a></p> +<p id="n120" class="pln"><a href="#n120">120</a></p> +<p id="n121" class="stm run hide_run"><a href="#n121">121</a></p> +<p id="n122" class="pln"><a href="#n122">122</a></p> +<p id="n123" class="stm mis"><a href="#n123">123</a></p> +<p id="n124" class="pln"><a href="#n124">124</a></p> +<p id="n125" class="pln"><a href="#n125">125</a></p> +<p id="n126" class="stm mis"><a href="#n126">126</a></p> +<p id="n127" class="pln"><a href="#n127">127</a></p> +<p id="n128" class="pln"><a href="#n128">128</a></p> +<p id="n129" class="stm mis"><a href="#n129">129</a></p> +<p id="n130" class="pln"><a href="#n130">130</a></p> +<p id="n131" class="stm mis"><a href="#n131">131</a></p> +<p id="n132" class="stm mis"><a href="#n132">132</a></p> +<p id="n133" class="stm mis"><a href="#n133">133</a></p> +<p id="n134" class="stm mis"><a href="#n134">134</a></p> +<p id="n135" class="stm mis"><a href="#n135">135</a></p> +<p id="n136" class="stm mis"><a href="#n136">136</a></p> +<p id="n137" class="pln"><a href="#n137">137</a></p> +<p id="n138" class="pln"><a href="#n138">138</a></p> +<p id="n139" class="stm mis"><a href="#n139">139</a></p> +<p id="n140" class="pln"><a href="#n140">140</a></p> +<p id="n141" class="pln"><a href="#n141">141</a></p> +<p id="n142" class="pln"><a href="#n142">142</a></p> +<p id="n143" class="stm mis"><a href="#n143">143</a></p> +<p id="n144" class="pln"><a href="#n144">144</a></p> +<p id="n145" class="pln"><a href="#n145">145</a></p> +<p id="n146" class="stm mis"><a href="#n146">146</a></p> +<p id="n147" class="pln"><a href="#n147">147</a></p> +<p id="n148" class="stm mis"><a href="#n148">148</a></p> +<p id="n149" class="pln"><a href="#n149">149</a></p> +<p id="n150" class="stm mis"><a href="#n150">150</a></p> +<p id="n151" class="stm mis"><a href="#n151">151</a></p> +<p id="n152" class="stm mis"><a href="#n152">152</a></p> +<p id="n153" class="stm mis"><a href="#n153">153</a></p> +<p id="n154" class="stm mis"><a href="#n154">154</a></p> +<p id="n155" class="stm mis"><a href="#n155">155</a></p> +<p id="n156" class="stm mis"><a href="#n156">156</a></p> +<p id="n157" class="pln"><a href="#n157">157</a></p> +<p id="n158" class="stm mis"><a href="#n158">158</a></p> +<p id="n159" class="pln"><a href="#n159">159</a></p> +<p id="n160" class="pln"><a href="#n160">160</a></p> +<p id="n161" class="pln"><a href="#n161">161</a></p> +<p id="n162" class="pln"><a href="#n162">162</a></p> +<p id="n163" class="pln"><a href="#n163">163</a></p> +<p id="n164" class="pln"><a href="#n164">164</a></p> +<p id="n165" class="pln"><a href="#n165">165</a></p> +<p id="n166" class="stm mis"><a href="#n166">166</a></p> +<p id="n167" class="stm mis"><a href="#n167">167</a></p> +<p id="n168" class="pln"><a href="#n168">168</a></p> +<p id="n169" class="pln"><a href="#n169">169</a></p> +<p id="n170" class="stm mis"><a href="#n170">170</a></p> +<p id="n171" class="pln"><a href="#n171">171</a></p> +<p id="n172" class="pln"><a href="#n172">172</a></p> +<p id="n173" class="stm run hide_run"><a href="#n173">173</a></p> +<p id="n174" class="pln"><a href="#n174">174</a></p> +<p id="n175" class="pln"><a href="#n175">175</a></p> +<p id="n176" class="pln"><a href="#n176">176</a></p> +<p id="n177" class="pln"><a href="#n177">177</a></p> +<p id="n178" class="pln"><a href="#n178">178</a></p> +<p id="n179" class="pln"><a href="#n179">179</a></p> +<p id="n180" class="pln"><a href="#n180">180</a></p> +<p id="n181" class="pln"><a href="#n181">181</a></p> +<p id="n182" class="pln"><a href="#n182">182</a></p> +<p id="n183" class="pln"><a href="#n183">183</a></p> +<p id="n184" class="pln"><a href="#n184">184</a></p> +<p id="n185" class="pln"><a href="#n185">185</a></p> +<p id="n186" class="stm run hide_run"><a href="#n186">186</a></p> +<p id="n187" class="stm run hide_run"><a href="#n187">187</a></p> +<p id="n188" class="stm run hide_run"><a href="#n188">188</a></p> +<p id="n189" class="stm run hide_run"><a href="#n189">189</a></p> +<p id="n190" class="pln"><a href="#n190">190</a></p> +<p id="n191" class="pln"><a href="#n191">191</a></p> +<p id="n192" class="stm run hide_run"><a href="#n192">192</a></p> +<p id="n193" class="pln"><a href="#n193">193</a></p> +<p id="n194" class="stm run hide_run"><a href="#n194">194</a></p> +<p id="n195" class="pln"><a href="#n195">195</a></p> +<p id="n196" class="stm run hide_run"><a href="#n196">196</a></p> +<p id="n197" class="stm run hide_run"><a href="#n197">197</a></p> +<p id="n198" class="pln"><a href="#n198">198</a></p> +<p id="n199" class="stm run hide_run"><a href="#n199">199</a></p> +<p id="n200" class="pln"><a href="#n200">200</a></p> +<p id="n201" class="pln"><a href="#n201">201</a></p> +<p id="n202" class="pln"><a href="#n202">202</a></p> +<p id="n203" class="pln"><a href="#n203">203</a></p> +<p id="n204" class="pln"><a href="#n204">204</a></p> +<p id="n205" class="pln"><a href="#n205">205</a></p> +<p id="n206" class="pln"><a href="#n206">206</a></p> +<p id="n207" class="pln"><a href="#n207">207</a></p> +<p id="n208" class="pln"><a href="#n208">208</a></p> +<p id="n209" class="pln"><a href="#n209">209</a></p> +<p id="n210" class="pln"><a href="#n210">210</a></p> +<p id="n211" class="pln"><a href="#n211">211</a></p> +<p id="n212" class="pln"><a href="#n212">212</a></p> +<p id="n213" class="pln"><a href="#n213">213</a></p> +<p id="n214" class="pln"><a href="#n214">214</a></p> +<p id="n215" class="pln"><a href="#n215">215</a></p> +<p id="n216" class="pln"><a href="#n216">216</a></p> +<p id="n217" class="stm run hide_run"><a href="#n217">217</a></p> +<p id="n218" class="pln"><a href="#n218">218</a></p> +<p id="n219" class="stm run hide_run"><a href="#n219">219</a></p> +<p id="n220" class="pln"><a href="#n220">220</a></p> +<p id="n221" class="pln"><a href="#n221">221</a></p> +<p id="n222" class="pln"><a href="#n222">222</a></p> +<p id="n223" class="pln"><a href="#n223">223</a></p> +<p id="n224" class="pln"><a href="#n224">224</a></p> +<p id="n225" class="pln"><a href="#n225">225</a></p> +<p id="n226" class="pln"><a href="#n226">226</a></p> +<p id="n227" class="pln"><a href="#n227">227</a></p> +<p id="n228" class="stm run hide_run"><a href="#n228">228</a></p> +<p id="n229" class="pln"><a href="#n229">229</a></p> +<p id="n230" class="stm run hide_run"><a href="#n230">230</a></p> +<p id="n231" class="pln"><a href="#n231">231</a></p> +<p id="n232" class="pln"><a href="#n232">232</a></p> +<p id="n233" class="stm mis"><a href="#n233">233</a></p> +<p id="n234" class="pln"><a href="#n234">234</a></p> +<p id="n235" class="pln"><a href="#n235">235</a></p> +<p id="n236" class="stm mis"><a href="#n236">236</a></p> +<p id="n237" class="stm mis"><a href="#n237">237</a></p> +<p id="n238" class="stm mis"><a href="#n238">238</a></p> +<p id="n239" class="stm mis"><a href="#n239">239</a></p> +<p id="n240" class="stm mis"><a href="#n240">240</a></p> +<p id="n241" class="pln"><a href="#n241">241</a></p> +<p id="n242" class="pln"><a href="#n242">242</a></p> +<p id="n243" class="pln"><a href="#n243">243</a></p> +<p id="n244" class="stm mis"><a href="#n244">244</a></p> +<p id="n245" class="stm mis"><a href="#n245">245</a></p> +<p id="n246" class="stm mis"><a href="#n246">246</a></p> +<p id="n247" class="stm mis"><a href="#n247">247</a></p> +<p id="n248" class="pln"><a href="#n248">248</a></p> +<p id="n249" class="pln"><a href="#n249">249</a></p> +<p id="n250" class="stm mis"><a href="#n250">250</a></p> +<p id="n251" class="pln"><a href="#n251">251</a></p> +<p id="n252" class="stm mis"><a href="#n252">252</a></p> +<p id="n253" class="stm mis"><a href="#n253">253</a></p> +<p id="n254" class="stm mis"><a href="#n254">254</a></p> +<p id="n255" class="stm mis"><a href="#n255">255</a></p> +<p id="n256" class="pln"><a href="#n256">256</a></p> +<p id="n257" class="pln"><a href="#n257">257</a></p> +<p id="n258" class="pln"><a href="#n258">258</a></p> +<p id="n259" class="pln"><a href="#n259">259</a></p> +<p id="n260" class="stm mis"><a href="#n260">260</a></p> +<p id="n261" class="stm mis"><a href="#n261">261</a></p> +<p id="n262" class="stm mis"><a href="#n262">262</a></p> +<p id="n263" class="stm mis"><a href="#n263">263</a></p> +<p id="n264" class="pln"><a href="#n264">264</a></p> +<p id="n265" class="pln"><a href="#n265">265</a></p> +<p id="n266" class="stm run hide_run"><a href="#n266">266</a></p> +<p id="n267" class="pln"><a href="#n267">267</a></p> +<p id="n268" class="pln"><a href="#n268">268</a></p> +<p id="n269" class="pln"><a href="#n269">269</a></p> +<p id="n270" class="pln"><a href="#n270">270</a></p> +<p id="n271" class="pln"><a href="#n271">271</a></p> +<p id="n272" class="stm mis"><a href="#n272">272</a></p> +<p id="n273" class="stm mis"><a href="#n273">273</a></p> +<p id="n274" class="pln"><a href="#n274">274</a></p> +<p id="n275" class="stm mis"><a href="#n275">275</a></p> +<p id="n276" class="stm mis"><a href="#n276">276</a></p> +<p id="n277" class="pln"><a href="#n277">277</a></p> +<p id="n278" class="stm mis"><a href="#n278">278</a></p> +<p id="n279" class="stm mis"><a href="#n279">279</a></p> +<p id="n280" class="pln"><a href="#n280">280</a></p> +<p id="n281" class="stm mis"><a href="#n281">281</a></p> +<p id="n282" class="pln"><a href="#n282">282</a></p> +<p id="n283" class="pln"><a href="#n283">283</a></p> +<p id="n284" class="stm mis"><a href="#n284">284</a></p> +<p id="n285" class="pln"><a href="#n285">285</a></p> +<p id="n286" class="pln"><a href="#n286">286</a></p> +<p id="n287" class="stm mis"><a href="#n287">287</a></p> +<p id="n288" class="stm mis"><a href="#n288">288</a></p> +<p id="n289" class="stm mis"><a href="#n289">289</a></p> +<p id="n290" class="stm mis"><a href="#n290">290</a></p> +<p id="n291" class="stm mis"><a href="#n291">291</a></p> +<p id="n292" class="stm mis"><a href="#n292">292</a></p> +<p id="n293" class="pln"><a href="#n293">293</a></p> +<p id="n294" class="stm mis"><a href="#n294">294</a></p> +<p id="n295" class="stm mis"><a href="#n295">295</a></p> +<p id="n296" class="pln"><a href="#n296">296</a></p> +<p id="n297" class="stm mis"><a href="#n297">297</a></p> +<p id="n298" class="pln"><a href="#n298">298</a></p> +<p id="n299" class="pln"><a href="#n299">299</a></p> +<p id="n300" class="stm mis"><a href="#n300">300</a></p> +<p id="n301" class="pln"><a href="#n301">301</a></p> +<p id="n302" class="stm mis"><a href="#n302">302</a></p> +<p id="n303" class="stm mis"><a href="#n303">303</a></p> +<p id="n304" class="pln"><a href="#n304">304</a></p> +<p id="n305" class="stm mis"><a href="#n305">305</a></p> +<p id="n306" class="stm mis"><a href="#n306">306</a></p> +<p id="n307" class="pln"><a href="#n307">307</a></p> +<p id="n308" class="stm mis"><a href="#n308">308</a></p> +<p id="n309" class="pln"><a href="#n309">309</a></p> +<p id="n310" class="stm mis"><a href="#n310">310</a></p> +<p id="n311" class="pln"><a href="#n311">311</a></p> +<p id="n312" class="stm mis"><a href="#n312">312</a></p> +<p id="n313" class="pln"><a href="#n313">313</a></p> +<p id="n314" class="stm mis"><a href="#n314">314</a></p> +<p id="n315" class="pln"><a href="#n315">315</a></p> +<p id="n316" class="stm mis"><a href="#n316">316</a></p> +<p id="n317" class="stm mis"><a href="#n317">317</a></p> + + </td> + <td class="text"> +<p id="t1" class="stm run hide_run"><span class="key">import</span> <span class="nam">numpy</span> <span class="key">as</span> <span class="nam">np</span><span class="strut"> </span></p> +<p id="t2" class="stm run hide_run"><span class="key">from</span> <span class="nam">copy</span> <span class="key">import</span> <span class="nam">deepcopy</span><span class="strut"> </span></p> +<p id="t3" class="stm run hide_run"><span class="key">from</span> <span class="nam">fluegg</span><span class="op">.</span><span class="nam">hydraulics</span> <span class="key">import</span> <span class="nam">from_csv</span><span class="strut"> </span></p> +<p id="t4" class="stm run hide_run"><span class="key">from</span> <span class="nam">fluegg</span><span class="op">.</span><span class="nam">hydraulics</span> <span class="key">import</span> <span class="nam">RoughBottomSeriesOfHydraulicCells</span><span class="strut"> </span></p> +<p id="t5" class="stm run hide_run"><span class="key">from</span> <span class="nam">fluegg</span><span class="op">.</span><span class="nam">simclock</span> <span class="key">import</span> <span class="nam">SimulationClock</span><span class="strut"> </span></p> +<p id="t6" class="stm run hide_run"><span class="key">from</span> <span class="nam">fluegg</span><span class="op">.</span><span class="nam">asiancarpeggs</span> <span class="key">import</span> <span class="nam">BigheadCarpEggs</span><span class="strut"> </span></p> +<p id="t7" class="stm run hide_run"><span class="key">from</span> <span class="nam">fluegg</span><span class="op">.</span><span class="nam">asiancarpeggs</span> <span class="key">import</span> <span class="nam">SilverCarpEggs</span><span class="strut"> </span></p> +<p id="t8" class="stm run hide_run"><span class="key">from</span> <span class="nam">fluegg</span><span class="op">.</span><span class="nam">asiancarpeggs</span> <span class="key">import</span> <span class="nam">GrassCarpEggs</span><span class="strut"> </span></p> +<p id="t9" class="stm run hide_run"><span class="key">from</span> <span class="nam">fluegg</span><span class="op">.</span><span class="nam">transporter</span> <span class="key">import</span> <span class="nam">init_transporter</span><span class="strut"> </span></p> +<p id="t10" class="stm run hide_run"><span class="key">import</span> <span class="nam">h5py</span><span class="strut"> </span></p> +<p id="t11" class="stm run hide_run"><span class="key">import</span> <span class="nam">os</span><span class="strut"> </span></p> +<p id="t12" class="stm run hide_run"><span class="key">import</span> <span class="nam">datetime</span><span class="strut"> </span></p> +<p id="t13" class="pln"><span class="strut"> </span></p> +<p id="t14" class="stm run hide_run"><span class="key">try</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t15" class="stm run hide_run"> <span class="key">from</span> <span class="nam">fluegg</span><span class="op">.</span><span class="nam">ras</span> <span class="key">import</span> <span class="nam">RASProject</span><span class="strut"> </span></p> +<p id="t16" class="stm mis"><span class="key">except</span> <span class="nam">ModuleNotFoundError</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t17" class="stm mis"> <span class="key">pass</span><span class="strut"> </span></p> +<p id="t18" class="pln"><span class="strut"> </span></p> +<p id="t19" class="pln"><span class="strut"> </span></p> +<p id="t20" class="stm run hide_run"><span class="key">class</span> <span class="nam">Simulation</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t21" class="pln"> <span class="str">"""Class that controls the simulation by incrementing time</span><span class="strut"> </span></p> +<p id="t22" class="pln"><span class="str"> steps and calling simulation functions correctly.</span><span class="strut"> </span></p> +<p id="t23" class="pln"><span class="strut"> </span></p> +<p id="t24" class="pln"><span class="str"> Parameters</span><span class="strut"> </span></p> +<p id="t25" class="pln"><span class="str"> ----------</span><span class="strut"> </span></p> +<p id="t26" class="pln"><span class="str"> particles : fluegg.drift.DriftingParticles</span><span class="strut"> </span></p> +<p id="t27" class="pln"><span class="str"> Particles being drifted through the simulation</span><span class="strut"> </span></p> +<p id="t28" class="pln"><span class="strut"> </span></p> +<p id="t29" class="pln"><span class="str"> transporter : fluegg.transporter.Transporter</span><span class="strut"> </span></p> +<p id="t30" class="pln"><span class="str"> Class that physically transports each egg for each time step</span><span class="strut"> </span></p> +<p id="t31" class="pln"><span class="strut"> </span></p> +<p id="t32" class="pln"><span class="str"> simclock : fluegg.simclock.SimulationClock</span><span class="strut"> </span></p> +<p id="t33" class="pln"><span class="str"> Clock that keeps track of the time during the simulation</span><span class="strut"> </span></p> +<p id="t34" class="pln"><span class="strut"> </span></p> +<p id="t35" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t36" class="pln"><span class="strut"> </span></p> +<p id="t37" class="stm run hide_run"> <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">particles</span><span class="op">,</span> <span class="nam">transporter</span><span class="op">,</span> <span class="nam">simclock</span><span class="op">,</span> <span class="nam">hydraulic_cells</span><span class="op">=</span><span class="key">None</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t38" class="pln"><span class="strut"> </span></p> +<p id="t39" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_hydraulic_model</span> <span class="op">=</span> <span class="nam">hydraulic_cells</span><span class="strut"> </span></p> +<p id="t40" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_particles</span> <span class="op">=</span> <span class="nam">particles</span><span class="strut"> </span></p> +<p id="t41" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_transporter</span> <span class="op">=</span> <span class="nam">transporter</span><span class="strut"> </span></p> +<p id="t42" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_simclock</span> <span class="op">=</span> <span class="nam">simclock</span><span class="strut"> </span></p> +<p id="t43" class="pln"><span class="strut"> </span></p> +<p id="t44" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_time_step_function_calls</span> <span class="op">=</span> <span class="op">{</span><span class="op">}</span><span class="strut"> </span></p> +<p id="t45" class="pln"><span class="strut"> </span></p> +<p id="t46" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_call_time_step_functions</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t47" class="pln"><span class="strut"> </span></p> +<p id="t48" class="stm run hide_run"> <span class="key">for</span> <span class="nam">fun</span><span class="op">,</span> <span class="nam">args</span> <span class="key">in</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_time_step_function_calls</span><span class="op">.</span><span class="nam">items</span><span class="op">(</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t49" class="stm run hide_run"> <span class="nam">fun</span><span class="op">(</span><span class="op">*</span><span class="nam">args</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t50" class="pln"><span class="strut"> </span></p> +<p id="t51" class="stm run hide_run"> <span class="key">def</span> <span class="nam">add_time_step_function_call</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">fun</span><span class="op">,</span> <span class="nam">args</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t52" class="pln"> <span class="str">"""Adds a function that will be called at the beginning of a time step.</span><span class="strut"> </span></p> +<p id="t53" class="pln"><span class="strut"> </span></p> +<p id="t54" class="pln"><span class="str"> Parameters</span><span class="strut"> </span></p> +<p id="t55" class="pln"><span class="str"> ----------</span><span class="strut"> </span></p> +<p id="t56" class="pln"><span class="str"> fun : function</span><span class="strut"> </span></p> +<p id="t57" class="pln"><span class="str"> args : list</span><span class="strut"> </span></p> +<p id="t58" class="pln"><span class="strut"> </span></p> +<p id="t59" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t60" class="pln"><span class="strut"> </span></p> +<p id="t61" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_time_step_function_calls</span><span class="op">[</span><span class="nam">fun</span><span class="op">]</span> <span class="op">=</span> <span class="nam">args</span><span class="strut"> </span></p> +<p id="t62" class="pln"><span class="strut"> </span></p> +<p id="t63" class="stm run hide_run"> <span class="key">def</span> <span class="nam">set_hydraulic_model</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">hydraulic_model</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t64" class="pln"> <span class="str">"""Sets the hydraulic model used in this instance.</span><span class="strut"> </span></p> +<p id="t65" class="pln"><span class="strut"> </span></p> +<p id="t66" class="pln"><span class="str"> Required before calling run().</span><span class="strut"> </span></p> +<p id="t67" class="pln"><span class="strut"> </span></p> +<p id="t68" class="pln"><span class="str"> Parameters</span><span class="strut"> </span></p> +<p id="t69" class="pln"><span class="str"> ----------</span><span class="strut"> </span></p> +<p id="t70" class="pln"><span class="str"> hydraulic_model : fluegg.hydraulics.SeriesOfHydraulicCells</span><span class="strut"> </span></p> +<p id="t71" class="pln"><span class="strut"> </span></p> +<p id="t72" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t73" class="pln"><span class="strut"> </span></p> +<p id="t74" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_hydraulic_model</span> <span class="op">=</span> <span class="nam">hydraulic_model</span><span class="strut"> </span></p> +<p id="t75" class="pln"><span class="strut"> </span></p> +<p id="t76" class="stm run hide_run"> <span class="key">def</span> <span class="nam">run</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">configuration</span><span class="op">=</span><span class="op">{</span><span class="op">}</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t77" class="pln"> <span class="str">"""Runs the simulation and returns the time-stamped positions</span><span class="strut"> </span></p> +<p id="t78" class="pln"><span class="str"> of the particles throughout the simulation</span><span class="strut"> </span></p> +<p id="t79" class="pln"><span class="strut"> </span></p> +<p id="t80" class="pln"><span class="str"> Returns</span><span class="strut"> </span></p> +<p id="t81" class="pln"><span class="str"> -------</span><span class="strut"> </span></p> +<p id="t82" class="pln"><span class="str"> SimulationResults</span><span class="strut"> </span></p> +<p id="t83" class="pln"><span class="strut"> </span></p> +<p id="t84" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t85" class="pln"><span class="strut"> </span></p> +<p id="t86" class="pln"> <span class="com"># Initialize simulation results</span><span class="strut"> </span></p> +<p id="t87" class="stm run hide_run"> <span class="nam">simulation_results</span> <span class="op">=</span> <span class="nam">SimulationResults</span><span class="op">(</span><span class="strut"> </span></p> +<p id="t88" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">_simclock</span><span class="op">,</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_particles</span><span class="op">,</span> <span class="nam">configuration</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t89" class="stm run hide_run"> <span class="nam">simulation_results</span><span class="op">.</span><span class="nam">record_result</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t90" class="pln"><span class="strut"> </span></p> +<p id="t91" class="pln"> <span class="com"># Run through all time steps</span><span class="strut"> </span></p> +<p id="t92" class="stm run hide_run"> <span class="key">for</span> <span class="nam">_</span> <span class="key">in</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_simclock</span><span class="op">.</span><span class="nam">iter_time_index</span><span class="op">(</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t93" class="pln"><span class="strut"> </span></p> +<p id="t94" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_call_time_step_functions</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t95" class="pln"><span class="strut"> </span></p> +<p id="t96" class="pln"> <span class="com"># record the result in the current state</span><span class="strut"> </span></p> +<p id="t97" class="stm run hide_run"> <span class="nam">simulation_results</span><span class="op">.</span><span class="nam">record_result</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t98" class="pln"><span class="strut"> </span></p> +<p id="t99" class="pln"> <span class="com"># Get positions and hydraulic results</span><span class="strut"> </span></p> +<p id="t100" class="stm run hide_run"> <span class="nam">positions</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_particles</span><span class="op">.</span><span class="nam">position</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t101" class="pln"><span class="strut"> </span></p> +<p id="t102" class="stm run hide_run"> <span class="key">if</span> <span class="nam">np</span><span class="op">.</span><span class="nam">all</span><span class="op">(</span><span class="nam">np</span><span class="op">.</span><span class="nam">isnan</span><span class="op">(</span><span class="nam">positions</span><span class="op">)</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t103" class="stm mis"> <span class="key">break</span><span class="strut"> </span></p> +<p id="t104" class="pln"><span class="strut"> </span></p> +<p id="t105" class="stm run hide_run"> <span class="nam">hydraulic_results</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t106" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">_hydraulic_model</span><span class="op">.</span><span class="nam">hydraulic_results</span><span class="op">(</span><span class="nam">positions</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t107" class="pln"><span class="strut"> </span></p> +<p id="t108" class="stm run hide_run"> <span class="key">try</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t109" class="pln"> <span class="com"># Increment positions</span><span class="strut"> </span></p> +<p id="t110" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_transporter</span><span class="op">.</span><span class="nam">increment_positions</span><span class="op">(</span><span class="nam">hydraulic_results</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t111" class="stm mis"> <span class="key">except</span> <span class="nam">ValueError</span> <span class="key">as</span> <span class="nam">e</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t112" class="stm mis"> <span class="key">raise</span> <span class="nam">e</span><span class="strut"> </span></p> +<p id="t113" class="pln"><span class="strut"> </span></p> +<p id="t114" class="stm run hide_run"> <span class="key">return</span> <span class="nam">simulation_results</span><span class="strut"> </span></p> +<p id="t115" class="pln"><span class="strut"> </span></p> +<p id="t116" class="pln"> <span class="com"># Raise error if time step is too large</span><span class="strut"> </span></p> +<p id="t117" class="pln"> <span class="com"># if user_step > max_step:</span><span class="strut"> </span></p> +<p id="t118" class="pln"> <span class="com"># raise ValueError('User time step is', user_step, '. Must be at less than', max_step)</span><span class="strut"> </span></p> +<p id="t119" class="pln"><span class="strut"> </span></p> +<p id="t120" class="pln"><span class="strut"> </span></p> +<p id="t121" class="stm run hide_run"><span class="key">def</span> <span class="nam">from_input_dict</span><span class="op">(</span><span class="nam">d</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t122" class="pln"> <span class="str">"""Creates a Simulation object from an input dictionary"""</span><span class="strut"> </span></p> +<p id="t123" class="stm mis"> <span class="nam">input_dict_validator</span><span class="op">(</span><span class="nam">d</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t124" class="pln"><span class="strut"> </span></p> +<p id="t125" class="pln"> <span class="com"># Simulation Clock</span><span class="strut"> </span></p> +<p id="t126" class="stm mis"> <span class="nam">simulation_clock</span> <span class="op">=</span> <span class="nam">SimulationClock</span><span class="op">(</span><span class="nam">d</span><span class="op">[</span><span class="str">'time_step'</span><span class="op">]</span><span class="op">,</span> <span class="nam">d</span><span class="op">[</span><span class="str">'duration'</span><span class="op">]</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t127" class="pln"><span class="strut"> </span></p> +<p id="t128" class="pln"> <span class="com"># Drifting Particles</span><span class="strut"> </span></p> +<p id="t129" class="stm mis"> <span class="nam">initial_position</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">tile</span><span class="op">(</span><span class="strut"> </span></p> +<p id="t130" class="pln"> <span class="nam">np</span><span class="op">.</span><span class="nam">array</span><span class="op">(</span><span class="op">[</span><span class="nam">d</span><span class="op">[</span><span class="str">'x'</span><span class="op">]</span><span class="op">,</span> <span class="nam">d</span><span class="op">[</span><span class="str">'y'</span><span class="op">]</span><span class="op">,</span> <span class="nam">d</span><span class="op">[</span><span class="str">'z'</span><span class="op">]</span><span class="op">]</span><span class="op">)</span><span class="op">,</span> <span class="op">(</span><span class="nam">d</span><span class="op">[</span><span class="str">'num_eggs'</span><span class="op">]</span><span class="op">,</span> <span class="num">1</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t131" class="stm mis"> <span class="key">if</span> <span class="nam">d</span><span class="op">[</span><span class="str">'species'</span><span class="op">]</span> <span class="op">==</span> <span class="str">'grass'</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t132" class="stm mis"> <span class="nam">drift</span> <span class="op">=</span> <span class="nam">GrassCarpEggs</span><span class="op">(</span><span class="nam">initial_position</span><span class="op">,</span> <span class="nam">simulation_clock</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t133" class="stm mis"> <span class="key">elif</span> <span class="nam">d</span><span class="op">[</span><span class="str">'species'</span><span class="op">]</span> <span class="op">==</span> <span class="str">'silver'</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t134" class="stm mis"> <span class="nam">drift</span> <span class="op">=</span> <span class="nam">SilverCarpEggs</span><span class="op">(</span><span class="nam">initial_position</span><span class="op">,</span> <span class="nam">simulation_clock</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t135" class="stm mis"> <span class="key">elif</span> <span class="nam">d</span><span class="op">[</span><span class="str">'species'</span><span class="op">]</span> <span class="op">==</span> <span class="str">'bighead'</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t136" class="stm mis"> <span class="nam">drift</span> <span class="op">=</span> <span class="nam">BigheadCarpEggs</span><span class="op">(</span><span class="nam">initial_position</span><span class="op">,</span> <span class="nam">simulation_clock</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t137" class="pln"><span class="strut"> </span></p> +<p id="t138" class="pln"> <span class="com"># Transporter</span><span class="strut"> </span></p> +<p id="t139" class="stm mis"> <span class="nam">transporter_model</span> <span class="op">=</span> <span class="nam">init_transporter</span><span class="op">(</span><span class="strut"> </span></p> +<p id="t140" class="pln"> <span class="nam">simulation_clock</span><span class="op">,</span> <span class="nam">drift</span><span class="op">,</span> <span class="nam">d</span><span class="op">[</span><span class="str">'diffusivity'</span><span class="op">]</span><span class="op">,</span> <span class="nam">d</span><span class="op">[</span><span class="str">'direction'</span><span class="op">]</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t141" class="pln"><span class="strut"> </span></p> +<p id="t142" class="pln"> <span class="com"># Simulation</span><span class="strut"> </span></p> +<p id="t143" class="stm mis"> <span class="nam">sim</span> <span class="op">=</span> <span class="nam">Simulation</span><span class="op">(</span><span class="nam">drift</span><span class="op">,</span> <span class="nam">transporter_model</span><span class="op">,</span> <span class="nam">simulation_clock</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t144" class="pln"><span class="strut"> </span></p> +<p id="t145" class="pln"> <span class="com"># Hydraulic cells (csv vs. hecras)</span><span class="strut"> </span></p> +<p id="t146" class="stm mis"> <span class="key">if</span> <span class="nam">d</span><span class="op">[</span><span class="str">'hydraulic_mode'</span><span class="op">]</span> <span class="op">==</span> <span class="str">'csv'</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t147" class="pln"> <span class="com"># Hydraulic channel (CSV)</span><span class="strut"> </span></p> +<p id="t148" class="stm mis"> <span class="nam">hydraulic_cells</span> <span class="op">=</span> <span class="nam">from_csv</span><span class="op">(</span><span class="nam">d</span><span class="op">[</span><span class="str">'csv_path'</span><span class="op">]</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t149" class="pln"> <span class="com"># Hecras Mode</span><span class="strut"> </span></p> +<p id="t150" class="stm mis"> <span class="key">if</span> <span class="nam">d</span><span class="op">[</span><span class="str">'hydraulic_mode'</span><span class="op">]</span> <span class="op">==</span> <span class="str">'hecras'</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t151" class="stm mis"> <span class="key">with</span> <span class="nam">RASProject</span><span class="op">(</span><span class="nam">d</span><span class="op">[</span><span class="str">'hecras_path'</span><span class="op">]</span><span class="op">)</span> <span class="key">as</span> <span class="nam">rp</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t152" class="stm mis"> <span class="nam">plan_name</span> <span class="op">=</span> <span class="nam">d</span><span class="op">[</span><span class="str">'hecras_plan'</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t153" class="stm mis"> <span class="nam">rp</span><span class="op">.</span><span class="nam">set_current_plan</span><span class="op">(</span><span class="nam">plan_name</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t154" class="stm mis"> <span class="nam">profile_name</span> <span class="op">=</span> <span class="nam">d</span><span class="op">[</span><span class="str">'hecras_profile'</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t155" class="stm mis"> <span class="nam">temperature</span> <span class="op">=</span> <span class="nam">d</span><span class="op">[</span><span class="str">'hecras_temperature'</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t156" class="stm mis"> <span class="nam">hydraulic_data_frame</span> <span class="op">=</span> <span class="nam">rp</span><span class="op">.</span><span class="nam">hydraulic_model_data</span><span class="op">(</span><span class="strut"> </span></p> +<p id="t157" class="pln"> <span class="nam">profile_name</span><span class="op">,</span> <span class="nam">temperature</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t158" class="stm mis"> <span class="nam">hydraulic_cells</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t159" class="pln"> <span class="nam">RoughBottomSeriesOfHydraulicCells</span><span class="op">.</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t160" class="pln"> <span class="nam">from_data_frame</span><span class="op">(</span><span class="nam">hydraulic_data_frame</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t161" class="pln"> <span class="nam">start_time</span><span class="op">=</span><span class="nam">d</span><span class="op">[</span><span class="str">'hecras_start_time'</span><span class="op">]</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t162" class="pln"> <span class="nam">simulation_clock</span><span class="op">=</span><span class="nam">simulation_clock</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t163" class="pln"> <span class="nam">simulation</span><span class="op">=</span><span class="nam">sim</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t164" class="pln"><span class="strut"> </span></p> +<p id="t165" class="pln"> <span class="com"># Update sim & transporter with hydraulic cells</span><span class="strut"> </span></p> +<p id="t166" class="stm mis"> <span class="nam">sim</span><span class="op">.</span><span class="nam">set_hydraulic_model</span><span class="op">(</span><span class="nam">hydraulic_cells</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t167" class="stm mis"> <span class="nam">transporter_model</span><span class="op">.</span><span class="nam">set_hydraulic_model</span><span class="op">(</span><span class="nam">hydraulic_cells</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t168" class="pln"><span class="strut"> </span></p> +<p id="t169" class="pln"> <span class="com"># Return simulation</span><span class="strut"> </span></p> +<p id="t170" class="stm mis"> <span class="key">return</span> <span class="nam">sim</span><span class="strut"> </span></p> +<p id="t171" class="pln"><span class="strut"> </span></p> +<p id="t172" class="pln"><span class="strut"> </span></p> +<p id="t173" class="stm run hide_run"><span class="key">class</span> <span class="nam">SimulationResults</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t174" class="pln"> <span class="str">"""Data structure containing simulation results during a simulation run</span><span class="strut"> </span></p> +<p id="t175" class="pln"><span class="strut"> </span></p> +<p id="t176" class="pln"><span class="str"> Parameters</span><span class="strut"> </span></p> +<p id="t177" class="pln"><span class="str"> ----------</span><span class="strut"> </span></p> +<p id="t178" class="pln"><span class="str"> simclock : fluegg.simclock.SimulationClock</span><span class="strut"> </span></p> +<p id="t179" class="pln"><span class="str"> Representation of a simulation clock</span><span class="strut"> </span></p> +<p id="t180" class="pln"><span class="strut"> </span></p> +<p id="t181" class="pln"><span class="str"> particles : fluegg.drift.DriftingParticle</span><span class="strut"> </span></p> +<p id="t182" class="pln"><span class="str"> Particles that were are being drifted through the simulation</span><span class="strut"> </span></p> +<p id="t183" class="pln"><span class="strut"> </span></p> +<p id="t184" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t185" class="pln"><span class="strut"> </span></p> +<p id="t186" class="stm run hide_run"> <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">simclock</span><span class="op">,</span> <span class="nam">particles</span><span class="op">,</span> <span class="nam">configuration</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t187" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_simclock</span> <span class="op">=</span> <span class="nam">simclock</span><span class="strut"> </span></p> +<p id="t188" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_particles</span> <span class="op">=</span> <span class="nam">particles</span><span class="strut"> </span></p> +<p id="t189" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_positions</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">tile</span><span class="op">(</span><span class="strut"> </span></p> +<p id="t190" class="pln"> <span class="nam">np</span><span class="op">.</span><span class="nam">nan</span><span class="op">,</span> <span class="op">(</span><span class="nam">simclock</span><span class="op">.</span><span class="nam">number_of_time_steps</span><span class="op">(</span><span class="op">)</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t191" class="pln"> <span class="nam">particles</span><span class="op">.</span><span class="nam">position</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">shape</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="op">,</span> <span class="num">3</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t192" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_configuration</span> <span class="op">=</span> <span class="nam">configuration</span><span class="strut"> </span></p> +<p id="t193" class="pln"><span class="strut"> </span></p> +<p id="t194" class="stm run hide_run"> <span class="key">def</span> <span class="nam">record_result</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t195" class="pln"> <span class="str">"""Records the current particle positions in the positions array."""</span><span class="strut"> </span></p> +<p id="t196" class="stm run hide_run"> <span class="nam">time_index</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_simclock</span><span class="op">.</span><span class="nam">current_time_index</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t197" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_positions</span><span class="op">[</span><span class="nam">time_index</span><span class="op">]</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_particles</span><span class="op">.</span><span class="nam">position</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t198" class="pln"><span class="strut"> </span></p> +<p id="t199" class="stm run hide_run"> <span class="key">def</span> <span class="nam">results</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t200" class="pln"> <span class="str">"""Returns the positions of the particles logged throughout the</span><span class="strut"> </span></p> +<p id="t201" class="pln"><span class="str"> simulation.</span><span class="strut"> </span></p> +<p id="t202" class="pln"><span class="strut"> </span></p> +<p id="t203" class="pln"><span class="str"> The returned array is structured as</span><span class="strut"> </span></p> +<p id="t204" class="pln"><span class="strut"> </span></p> +<p id="t205" class="pln"><span class="str"> Axis Values Size</span><span class="strut"> </span></p> +<p id="t206" class="pln"><span class="str"> 0 Time step Number of time steps (N_t)</span><span class="strut"> </span></p> +<p id="t207" class="pln"><span class="str"> 1 Particle number Number of eggs (N_e)</span><span class="strut"> </span></p> +<p id="t208" class="pln"><span class="str"> 3 Position (x, y, z) 3</span><span class="strut"> </span></p> +<p id="t209" class="pln"><span class="strut"> </span></p> +<p id="t210" class="pln"><span class="str"> The shape of the array is (N_t, N_e, 3).</span><span class="strut"> </span></p> +<p id="t211" class="pln"><span class="strut"> </span></p> +<p id="t212" class="pln"><span class="str"> Returns</span><span class="strut"> </span></p> +<p id="t213" class="pln"><span class="str"> -------</span><span class="strut"> </span></p> +<p id="t214" class="pln"><span class="str"> numpy.ndarray</span><span class="strut"> </span></p> +<p id="t215" class="pln"><span class="strut"> </span></p> +<p id="t216" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t217" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_positions</span><span class="strut"> </span></p> +<p id="t218" class="pln"><span class="strut"> </span></p> +<p id="t219" class="stm run hide_run"> <span class="key">def</span> <span class="nam">time</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t220" class="pln"> <span class="str">"""Returns time array</span><span class="strut"> </span></p> +<p id="t221" class="pln"><span class="strut"> </span></p> +<p id="t222" class="pln"><span class="str"> Returns</span><span class="strut"> </span></p> +<p id="t223" class="pln"><span class="str"> -------</span><span class="strut"> </span></p> +<p id="t224" class="pln"><span class="str"> numpy.ndarray</span><span class="strut"> </span></p> +<p id="t225" class="pln"><span class="strut"> </span></p> +<p id="t226" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t227" class="pln"><span class="strut"> </span></p> +<p id="t228" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_simclock</span><span class="op">.</span><span class="nam">time_array</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t229" class="pln"><span class="strut"> </span></p> +<p id="t230" class="stm run hide_run"> <span class="key">def</span> <span class="nam">save_results</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">file_path</span><span class="op">=</span><span class="key">None</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t231" class="pln"> <span class="str">"""Save the results of a simulation to an hdf time-stamped file"""</span><span class="strut"> </span></p> +<p id="t232" class="pln"><span class="strut"> </span></p> +<p id="t233" class="stm mis"> <span class="key">if</span> <span class="nam">file_path</span> <span class="key">is</span> <span class="key">None</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t234" class="pln"><span class="strut"> </span></p> +<p id="t235" class="pln"> <span class="com"># Create results folder</span><span class="strut"> </span></p> +<p id="t236" class="stm mis"> <span class="nam">absolute_path</span><span class="op">,</span> <span class="nam">_</span> <span class="op">=</span> <span class="nam">os</span><span class="op">.</span><span class="nam">path</span><span class="op">.</span><span class="nam">split</span><span class="op">(</span><span class="nam">os</span><span class="op">.</span><span class="nam">path</span><span class="op">.</span><span class="nam">realpath</span><span class="op">(</span><span class="nam">__file__</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t237" class="stm mis"> <span class="nam">p</span> <span class="op">=</span> <span class="nam">os</span><span class="op">.</span><span class="nam">path</span><span class="op">.</span><span class="nam">abspath</span><span class="op">(</span><span class="nam">os</span><span class="op">.</span><span class="nam">path</span><span class="op">.</span><span class="nam">join</span><span class="op">(</span><span class="nam">absolute_path</span><span class="op">,</span> <span class="nam">os</span><span class="op">.</span><span class="nam">pardir</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t238" class="stm mis"> <span class="nam">p</span> <span class="op">=</span> <span class="nam">os</span><span class="op">.</span><span class="nam">path</span><span class="op">.</span><span class="nam">join</span><span class="op">(</span><span class="nam">p</span><span class="op">,</span> <span class="str">'results'</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t239" class="stm mis"> <span class="key">if</span> <span class="key">not</span> <span class="nam">os</span><span class="op">.</span><span class="nam">path</span><span class="op">.</span><span class="nam">exists</span><span class="op">(</span><span class="nam">p</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t240" class="stm mis"> <span class="nam">os</span><span class="op">.</span><span class="nam">makedirs</span><span class="op">(</span><span class="nam">p</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t241" class="pln"><span class="strut"> </span></p> +<p id="t242" class="pln"> <span class="com"># Check if sim_name exists in configuration, if not use current</span><span class="strut"> </span></p> +<p id="t243" class="pln"> <span class="com"># time</span><span class="strut"> </span></p> +<p id="t244" class="stm mis"> <span class="key">if</span> <span class="key">not</span> <span class="op">(</span><span class="str">'sim_name'</span> <span class="key">in</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_configuration</span><span class="op">.</span><span class="nam">keys</span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t245" class="stm mis"> <span class="nam">now</span> <span class="op">=</span> <span class="nam">datetime</span><span class="op">.</span><span class="nam">datetime</span><span class="op">.</span><span class="nam">now</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t246" class="stm mis"> <span class="nam">date_string</span> <span class="op">=</span> <span class="nam">now</span><span class="op">.</span><span class="nam">strftime</span><span class="op">(</span><span class="str">'%Y-%m-%d-%H-%M-%S'</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t247" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">_configuration</span><span class="op">[</span><span class="str">'sim_name'</span><span class="op">]</span> <span class="op">=</span> <span class="str">'fluegg_'</span> <span class="op">+</span> <span class="nam">date_string</span><span class="strut"> </span></p> +<p id="t248" class="pln"><span class="strut"> </span></p> +<p id="t249" class="pln"> <span class="com"># Check if results file already exists</span><span class="strut"> </span></p> +<p id="t250" class="stm mis"> <span class="nam">file_path</span> <span class="op">=</span> <span class="nam">os</span><span class="op">.</span><span class="nam">path</span><span class="op">.</span><span class="nam">join</span><span class="op">(</span><span class="strut"> </span></p> +<p id="t251" class="pln"> <span class="nam">p</span><span class="op">,</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_configuration</span><span class="op">[</span><span class="str">'sim_name'</span><span class="op">]</span><span class="op">)</span> <span class="op">+</span> <span class="str">'.h5'</span><span class="strut"> </span></p> +<p id="t252" class="stm mis"> <span class="key">if</span> <span class="nam">os</span><span class="op">.</span><span class="nam">path</span><span class="op">.</span><span class="nam">exists</span><span class="op">(</span><span class="nam">file_path</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t253" class="stm mis"> <span class="nam">now</span> <span class="op">=</span> <span class="nam">datetime</span><span class="op">.</span><span class="nam">datetime</span><span class="op">.</span><span class="nam">now</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t254" class="stm mis"> <span class="nam">date_string</span> <span class="op">=</span> <span class="nam">now</span><span class="op">.</span><span class="nam">strftime</span><span class="op">(</span><span class="str">'%Y-%m-%d-%H-%M-%S'</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t255" class="stm mis"> <span class="nam">file_path</span> <span class="op">=</span> <span class="nam">os</span><span class="op">.</span><span class="nam">path</span><span class="op">.</span><span class="nam">join</span><span class="op">(</span><span class="strut"> </span></p> +<p id="t256" class="pln"> <span class="nam">p</span><span class="op">,</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_configuration</span><span class="op">[</span><span class="str">'sim_name'</span><span class="op">]</span><span class="op">)</span> <span class="op">+</span> <span class="nam">str</span><span class="op">(</span><span class="nam">date_string</span><span class="op">)</span> <span class="op">+</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t257" class="pln"> <span class="str">'.h5'</span><span class="strut"> </span></p> +<p id="t258" class="pln"><span class="strut"> </span></p> +<p id="t259" class="pln"> <span class="com"># Save simulation results</span><span class="strut"> </span></p> +<p id="t260" class="stm mis"> <span class="key">with</span> <span class="nam">h5py</span><span class="op">.</span><span class="nam">File</span><span class="op">(</span><span class="nam">file_path</span><span class="op">,</span> <span class="str">'w'</span><span class="op">)</span> <span class="key">as</span> <span class="nam">f</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t261" class="stm mis"> <span class="nam">f</span><span class="op">.</span><span class="nam">create_dataset</span><span class="op">(</span><span class="str">'simclock'</span><span class="op">,</span> <span class="nam">data</span><span class="op">=</span><span class="nam">self</span><span class="op">.</span><span class="nam">_simclock</span><span class="op">.</span><span class="nam">time_array</span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t262" class="stm mis"> <span class="nam">f</span><span class="op">.</span><span class="nam">create_dataset</span><span class="op">(</span><span class="str">'positions'</span><span class="op">,</span> <span class="nam">data</span><span class="op">=</span><span class="nam">self</span><span class="op">.</span><span class="nam">_positions</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t263" class="stm mis"> <span class="nam">f</span><span class="op">.</span><span class="nam">create_dataset</span><span class="op">(</span><span class="str">'configuration'</span><span class="op">,</span> <span class="nam">data</span><span class="op">=</span><span class="nam">str</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_configuration</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t264" class="pln"><span class="strut"> </span></p> +<p id="t265" class="pln"><span class="strut"> </span></p> +<p id="t266" class="stm run hide_run"><span class="key">def</span> <span class="nam">input_dict_validator</span><span class="op">(</span><span class="nam">d</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t267" class="pln"> <span class="str">"""Validates a list of simulation inputs and runs the simlation if inputs</span><span class="strut"> </span></p> +<p id="t268" class="pln"><span class="str"> are valid</span><span class="strut"> </span></p> +<p id="t269" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t270" class="pln"><span class="strut"> </span></p> +<p id="t271" class="pln"> <span class="com"># Hydraulic Input Mode</span><span class="strut"> </span></p> +<p id="t272" class="stm mis"> <span class="key">if</span> <span class="key">not</span> <span class="nam">d</span><span class="op">[</span><span class="str">'hydraulic_mode'</span><span class="op">]</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t273" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="str">'hydraulic_mode must be type str'</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t274" class="pln"> <span class="com"># CSV path</span><span class="strut"> </span></p> +<p id="t275" class="stm mis"> <span class="key">if</span> <span class="key">not</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">d</span><span class="op">[</span><span class="str">'csv_path'</span><span class="op">]</span><span class="op">,</span> <span class="nam">str</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t276" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="str">'csv_path must be type str'</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t277" class="pln"> <span class="com"># Hecras path</span><span class="strut"> </span></p> +<p id="t278" class="stm mis"> <span class="key">if</span> <span class="key">not</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">d</span><span class="op">[</span><span class="str">'hecras_path'</span><span class="op">]</span><span class="op">,</span> <span class="nam">str</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t279" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="str">'hecras_path must be type str'</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t280" class="pln"> <span class="com"># Diffusivity</span><span class="strut"> </span></p> +<p id="t281" class="stm mis"> <span class="key">if</span> <span class="op">(</span><span class="nam">d</span><span class="op">[</span><span class="str">'diffusivity'</span><span class="op">]</span> <span class="op">!=</span> <span class="str">'parabolic'</span><span class="op">)</span> <span class="key">and</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t282" class="pln"> <span class="op">(</span><span class="nam">d</span><span class="op">[</span><span class="str">'diffusivity'</span><span class="op">]</span> <span class="op">!=</span> <span class="str">'constant'</span><span class="op">)</span> <span class="key">and</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t283" class="pln"> <span class="op">(</span><span class="nam">d</span><span class="op">[</span><span class="str">'diffusivity'</span><span class="op">]</span> <span class="op">!=</span> <span class="str">'parabolic-constant'</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t284" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="strut"> </span></p> +<p id="t285" class="pln"> <span class="str">'diffusivity must be parabolic, constant, or parabolic-constant'</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t286" class="pln"> <span class="com"># XYZ Position</span><span class="strut"> </span></p> +<p id="t287" class="stm mis"> <span class="key">if</span> <span class="op">(</span><span class="key">not</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">d</span><span class="op">[</span><span class="str">'x'</span><span class="op">]</span><span class="op">,</span> <span class="nam">float</span><span class="op">)</span><span class="op">)</span> <span class="key">and</span> <span class="op">(</span><span class="key">not</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">d</span><span class="op">[</span><span class="str">'x'</span><span class="op">]</span><span class="op">,</span> <span class="nam">int</span><span class="op">)</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t288" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="str">'x must be type float or int'</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t289" class="stm mis"> <span class="key">if</span> <span class="op">(</span><span class="key">not</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">d</span><span class="op">[</span><span class="str">'y'</span><span class="op">]</span><span class="op">,</span> <span class="nam">float</span><span class="op">)</span><span class="op">)</span> <span class="key">and</span> <span class="op">(</span><span class="key">not</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">d</span><span class="op">[</span><span class="str">'y'</span><span class="op">]</span><span class="op">,</span> <span class="nam">int</span><span class="op">)</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t290" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="str">'y must be type float or int'</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t291" class="stm mis"> <span class="key">if</span> <span class="op">(</span><span class="key">not</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">d</span><span class="op">[</span><span class="str">'z'</span><span class="op">]</span><span class="op">,</span> <span class="nam">float</span><span class="op">)</span><span class="op">)</span> <span class="key">and</span> <span class="op">(</span><span class="key">not</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">d</span><span class="op">[</span><span class="str">'z'</span><span class="op">]</span><span class="op">,</span> <span class="nam">int</span><span class="op">)</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t292" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="str">'z must be type float or int'</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t293" class="pln"> <span class="com"># Number of eggs</span><span class="strut"> </span></p> +<p id="t294" class="stm mis"> <span class="key">if</span> <span class="key">not</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">d</span><span class="op">[</span><span class="str">'num_eggs'</span><span class="op">]</span><span class="op">,</span> <span class="nam">int</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t295" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="str">'num_eggs must be type int'</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t296" class="pln"> <span class="com"># Species</span><span class="strut"> </span></p> +<p id="t297" class="stm mis"> <span class="key">if</span> <span class="op">(</span><span class="nam">d</span><span class="op">[</span><span class="str">'species'</span><span class="op">]</span> <span class="op">!=</span> <span class="str">'grass'</span><span class="op">)</span> <span class="key">and</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t298" class="pln"> <span class="op">(</span><span class="nam">d</span><span class="op">[</span><span class="str">'species'</span><span class="op">]</span> <span class="op">!=</span> <span class="str">'silver'</span><span class="op">)</span> <span class="key">and</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t299" class="pln"> <span class="op">(</span><span class="nam">d</span><span class="op">[</span><span class="str">'species'</span><span class="op">]</span> <span class="op">!=</span> <span class="str">'bighead'</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t300" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="str">'species must be grass, silver, or bighead'</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t301" class="pln"> <span class="com"># Varying density & diameter</span><span class="strut"> </span></p> +<p id="t302" class="stm mis"> <span class="key">if</span> <span class="op">(</span><span class="nam">d</span><span class="op">[</span><span class="str">'varying_dd'</span><span class="op">]</span> <span class="op">!=</span> <span class="str">'constant'</span><span class="op">)</span> <span class="key">and</span> <span class="op">(</span><span class="nam">d</span><span class="op">[</span><span class="str">'varying_dd'</span><span class="op">]</span> <span class="op">!=</span> <span class="str">'varying'</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t303" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="str">'varying_dd must be constant or varying.'</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t304" class="pln"> <span class="com"># Direction of simulation</span><span class="strut"> </span></p> +<p id="t305" class="stm mis"> <span class="key">if</span> <span class="op">(</span><span class="nam">d</span><span class="op">[</span><span class="str">'direction'</span><span class="op">]</span> <span class="op">!=</span> <span class="str">'forward'</span><span class="op">)</span> <span class="key">and</span> <span class="op">(</span><span class="nam">d</span><span class="op">[</span><span class="str">'direction'</span><span class="op">]</span> <span class="op">!=</span> <span class="str">'reverse'</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t306" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="str">'direction must be forward or reverse.'</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t307" class="pln"> <span class="com"># Duration</span><span class="strut"> </span></p> +<p id="t308" class="stm mis"> <span class="key">if</span> <span class="op">(</span><span class="key">not</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">d</span><span class="op">[</span><span class="str">'duration'</span><span class="op">]</span><span class="op">,</span> <span class="nam">float</span><span class="op">)</span><span class="op">)</span> <span class="key">and</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t309" class="pln"> <span class="op">(</span><span class="key">not</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">d</span><span class="op">[</span><span class="str">'duration'</span><span class="op">]</span><span class="op">,</span> <span class="nam">int</span><span class="op">)</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t310" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="str">'duration must be type float or int'</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t311" class="pln"> <span class="com"># Time step</span><span class="strut"> </span></p> +<p id="t312" class="stm mis"> <span class="key">if</span> <span class="op">(</span><span class="key">not</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">d</span><span class="op">[</span><span class="str">'time_step'</span><span class="op">]</span><span class="op">,</span> <span class="nam">float</span><span class="op">)</span><span class="op">)</span> <span class="key">and</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t313" class="pln"> <span class="op">(</span><span class="key">not</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">d</span><span class="op">[</span><span class="str">'time_step'</span><span class="op">]</span><span class="op">,</span> <span class="nam">int</span><span class="op">)</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t314" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="str">'time_step must be type float or int'</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t315" class="pln"> <span class="com"># Simulation name</span><span class="strut"> </span></p> +<p id="t316" class="stm mis"> <span class="key">if</span> <span class="key">not</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">d</span><span class="op">[</span><span class="str">'sim_name'</span><span class="op">]</span><span class="op">,</span> <span class="nam">str</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t317" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="str">'sim_name must be type str'</span><span class="op">)</span><span class="strut"> </span></p> + + </td> + </tr> + </table> +</div> + +<div id="footer"> + <div class="content"> + <p> + <a class="nav" href="index.html">« index</a> <a class="nav" href="https://coverage.readthedocs.io">coverage.py v4.5.3</a>, + created at 2019-07-09 15:15 + </p> + </div> +</div> + +</body> +</html> diff --git a/coverage_report/fluegg_transporter_py.html b/coverage_report/fluegg_transporter_py.html new file mode 100644 index 0000000..85a1edf --- /dev/null +++ b/coverage_report/fluegg_transporter_py.html @@ -0,0 +1,1809 @@ + + + +<!DOCTYPE html> +<html> +<head> + <meta http-equiv="Content-Type" content="text/html; charset=utf-8"> + + + <meta http-equiv="X-UA-Compatible" content="IE=emulateIE7" /> + <title>Coverage for fluegg\transporter.py: 80%</title> + <link rel="stylesheet" href="style.css" type="text/css"> + + <script type="text/javascript" src="jquery.min.js"></script> + <script type="text/javascript" src="jquery.hotkeys.js"></script> + <script type="text/javascript" src="jquery.isonscreen.js"></script> + <script type="text/javascript" src="coverage_html.js"></script> + <script type="text/javascript"> + jQuery(document).ready(coverage.pyfile_ready); + </script> +</head> +<body class="pyfile"> + +<div id="header"> + <div class="content"> + <h1>Coverage for <b>fluegg\transporter.py</b> : + <span class="pc_cov">80%</span> + </h1> + + <img id="keyboard_icon" src="keybd_closed.png" alt="Show keyboard shortcuts" /> + + <h2 class="stats"> + 285 statements + <span class="run hide_run shortkey_r button_toggle_run">229 run</span> + <span class="mis shortkey_m button_toggle_mis">56 missing</span> + <span class="exc shortkey_x button_toggle_exc">0 excluded</span> + + + </h2> + </div> +</div> + +<div class="help_panel"> + <img id="panel_icon" src="keybd_open.png" alt="Hide keyboard shortcuts" /> + <p class="legend">Hot-keys on this page</p> + <div> + <p class="keyhelp"> + <span class="key">r</span> + <span class="key">m</span> + <span class="key">x</span> + 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id="n274" class="stm mis"><a href="#n274">274</a></p> +<p id="n275" class="pln"><a href="#n275">275</a></p> +<p id="n276" class="pln"><a href="#n276">276</a></p> +<p id="n277" class="pln"><a href="#n277">277</a></p> +<p id="n278" class="stm mis"><a href="#n278">278</a></p> +<p id="n279" class="pln"><a href="#n279">279</a></p> +<p id="n280" class="pln"><a href="#n280">280</a></p> +<p id="n281" class="stm run hide_run"><a href="#n281">281</a></p> +<p id="n282" class="pln"><a href="#n282">282</a></p> +<p id="n283" class="stm run hide_run"><a href="#n283">283</a></p> +<p id="n284" class="pln"><a href="#n284">284</a></p> +<p id="n285" class="pln"><a href="#n285">285</a></p> +<p id="n286" class="pln"><a href="#n286">286</a></p> +<p id="n287" class="pln"><a href="#n287">287</a></p> +<p id="n288" class="pln"><a href="#n288">288</a></p> +<p id="n289" class="pln"><a href="#n289">289</a></p> +<p id="n290" class="pln"><a href="#n290">290</a></p> +<p id="n291" class="pln"><a href="#n291">291</a></p> +<p id="n292" class="pln"><a href="#n292">292</a></p> +<p id="n293" class="pln"><a href="#n293">293</a></p> +<p id="n294" class="pln"><a href="#n294">294</a></p> +<p id="n295" class="pln"><a href="#n295">295</a></p> +<p id="n296" class="pln"><a href="#n296">296</a></p> +<p id="n297" class="pln"><a href="#n297">297</a></p> +<p id="n298" class="pln"><a href="#n298">298</a></p> +<p id="n299" class="stm run hide_run"><a href="#n299">299</a></p> +<p id="n300" class="pln"><a href="#n300">300</a></p> +<p id="n301" class="stm run hide_run"><a href="#n301">301</a></p> +<p id="n302" class="pln"><a href="#n302">302</a></p> +<p id="n303" class="stm run hide_run"><a href="#n303">303</a></p> +<p id="n304" class="pln"><a href="#n304">304</a></p> +<p id="n305" class="stm run hide_run"><a href="#n305">305</a></p> +<p id="n306" class="stm run hide_run"><a href="#n306">306</a></p> +<p id="n307" class="pln"><a href="#n307">307</a></p> +<p id="n308" class="stm run hide_run"><a href="#n308">308</a></p> +<p id="n309" class="stm run hide_run"><a href="#n309">309</a></p> +<p id="n310" class="pln"><a href="#n310">310</a></p> +<p id="n311" class="stm run hide_run"><a href="#n311">311</a></p> +<p id="n312" class="pln"><a href="#n312">312</a></p> +<p id="n313" class="stm run hide_run"><a href="#n313">313</a></p> +<p id="n314" class="pln"><a href="#n314">314</a></p> +<p id="n315" class="stm run hide_run"><a href="#n315">315</a></p> +<p id="n316" class="pln"><a href="#n316">316</a></p> +<p id="n317" class="stm run hide_run"><a href="#n317">317</a></p> +<p id="n318" class="pln"><a href="#n318">318</a></p> +<p id="n319" class="pln"><a href="#n319">319</a></p> +<p id="n320" class="stm run hide_run"><a href="#n320">320</a></p> +<p id="n321" class="stm run hide_run"><a href="#n321">321</a></p> +<p id="n322" class="stm run hide_run"><a href="#n322">322</a></p> +<p id="n323" class="pln"><a href="#n323">323</a></p> +<p id="n324" class="stm run hide_run"><a href="#n324">324</a></p> +<p id="n325" class="pln"><a href="#n325">325</a></p> +<p id="n326" class="stm run hide_run"><a href="#n326">326</a></p> +<p id="n327" class="pln"><a href="#n327">327</a></p> +<p id="n328" class="pln"><a href="#n328">328</a></p> +<p id="n329" class="stm run hide_run"><a href="#n329">329</a></p> +<p id="n330" class="pln"><a href="#n330">330</a></p> +<p id="n331" class="pln"><a href="#n331">331</a></p> +<p id="n332" class="stm run hide_run"><a href="#n332">332</a></p> +<p id="n333" class="pln"><a href="#n333">333</a></p> +<p id="n334" class="stm run hide_run"><a href="#n334">334</a></p> +<p id="n335" class="pln"><a href="#n335">335</a></p> +<p id="n336" class="pln"><a href="#n336">336</a></p> +<p id="n337" class="pln"><a href="#n337">337</a></p> +<p id="n338" class="pln"><a href="#n338">338</a></p> +<p id="n339" class="pln"><a href="#n339">339</a></p> +<p id="n340" class="pln"><a href="#n340">340</a></p> +<p id="n341" class="pln"><a href="#n341">341</a></p> +<p id="n342" class="pln"><a href="#n342">342</a></p> +<p id="n343" class="pln"><a href="#n343">343</a></p> +<p id="n344" class="pln"><a href="#n344">344</a></p> +<p id="n345" class="pln"><a href="#n345">345</a></p> +<p id="n346" class="pln"><a href="#n346">346</a></p> +<p id="n347" class="pln"><a href="#n347">347</a></p> +<p id="n348" class="stm run hide_run"><a href="#n348">348</a></p> +<p id="n349" class="stm run hide_run"><a href="#n349">349</a></p> +<p id="n350" class="pln"><a href="#n350">350</a></p> +<p id="n351" class="pln"><a href="#n351">351</a></p> +<p id="n352" class="stm run hide_run"><a href="#n352">352</a></p> +<p id="n353" class="stm run hide_run"><a href="#n353">353</a></p> +<p id="n354" class="pln"><a href="#n354">354</a></p> +<p id="n355" class="stm run hide_run"><a href="#n355">355</a></p> +<p id="n356" class="pln"><a href="#n356">356</a></p> +<p id="n357" class="stm run hide_run"><a href="#n357">357</a></p> +<p id="n358" class="pln"><a href="#n358">358</a></p> +<p id="n359" class="pln"><a href="#n359">359</a></p> +<p id="n360" class="pln"><a href="#n360">360</a></p> +<p id="n361" class="pln"><a href="#n361">361</a></p> +<p id="n362" class="pln"><a href="#n362">362</a></p> +<p id="n363" class="pln"><a href="#n363">363</a></p> +<p id="n364" class="pln"><a href="#n364">364</a></p> +<p id="n365" class="pln"><a href="#n365">365</a></p> +<p id="n366" class="pln"><a href="#n366">366</a></p> +<p id="n367" class="pln"><a href="#n367">367</a></p> +<p id="n368" class="stm run hide_run"><a href="#n368">368</a></p> +<p id="n369" class="stm run hide_run"><a href="#n369">369</a></p> +<p id="n370" class="stm run hide_run"><a href="#n370">370</a></p> +<p id="n371" class="pln"><a href="#n371">371</a></p> +<p id="n372" class="pln"><a href="#n372">372</a></p> +<p id="n373" class="stm run hide_run"><a href="#n373">373</a></p> +<p id="n374" class="pln"><a href="#n374">374</a></p> +<p id="n375" class="stm run hide_run"><a href="#n375">375</a></p> +<p id="n376" class="pln"><a href="#n376">376</a></p> +<p id="n377" class="pln"><a href="#n377">377</a></p> +<p id="n378" class="pln"><a href="#n378">378</a></p> +<p id="n379" class="pln"><a href="#n379">379</a></p> +<p id="n380" class="pln"><a href="#n380">380</a></p> +<p id="n381" class="pln"><a href="#n381">381</a></p> +<p id="n382" class="stm mis"><a href="#n382">382</a></p> +<p id="n383" class="pln"><a href="#n383">383</a></p> +<p id="n384" class="stm run hide_run"><a href="#n384">384</a></p> +<p id="n385" class="pln"><a href="#n385">385</a></p> +<p id="n386" class="pln"><a href="#n386">386</a></p> +<p id="n387" class="pln"><a href="#n387">387</a></p> +<p id="n388" class="pln"><a href="#n388">388</a></p> +<p id="n389" class="pln"><a href="#n389">389</a></p> +<p id="n390" class="pln"><a href="#n390">390</a></p> +<p id="n391" class="stm mis"><a href="#n391">391</a></p> +<p id="n392" class="pln"><a href="#n392">392</a></p> +<p id="n393" class="stm run hide_run"><a href="#n393">393</a></p> +<p id="n394" class="pln"><a href="#n394">394</a></p> +<p id="n395" class="pln"><a href="#n395">395</a></p> +<p id="n396" class="pln"><a href="#n396">396</a></p> +<p id="n397" class="pln"><a href="#n397">397</a></p> +<p id="n398" class="pln"><a href="#n398">398</a></p> +<p id="n399" class="pln"><a href="#n399">399</a></p> +<p id="n400" class="stm mis"><a href="#n400">400</a></p> +<p id="n401" class="pln"><a href="#n401">401</a></p> +<p id="n402" class="stm run hide_run"><a href="#n402">402</a></p> +<p id="n403" class="pln"><a href="#n403">403</a></p> +<p id="n404" class="pln"><a href="#n404">404</a></p> +<p id="n405" class="pln"><a href="#n405">405</a></p> +<p id="n406" class="pln"><a href="#n406">406</a></p> +<p id="n407" class="pln"><a href="#n407">407</a></p> +<p id="n408" class="pln"><a href="#n408">408</a></p> +<p id="n409" class="pln"><a href="#n409">409</a></p> +<p id="n410" class="pln"><a href="#n410">410</a></p> +<p id="n411" class="pln"><a href="#n411">411</a></p> +<p id="n412" class="pln"><a href="#n412">412</a></p> +<p id="n413" class="pln"><a href="#n413">413</a></p> +<p id="n414" class="stm run hide_run"><a href="#n414">414</a></p> +<p id="n415" class="stm run hide_run"><a href="#n415">415</a></p> +<p id="n416" class="stm run hide_run"><a href="#n416">416</a></p> +<p id="n417" class="stm run hide_run"><a href="#n417">417</a></p> +<p id="n418" class="stm run hide_run"><a href="#n418">418</a></p> +<p id="n419" class="pln"><a href="#n419">419</a></p> +<p id="n420" class="stm run hide_run"><a href="#n420">420</a></p> +<p id="n421" class="pln"><a href="#n421">421</a></p> +<p id="n422" class="stm run hide_run"><a href="#n422">422</a></p> +<p id="n423" class="stm mis"><a href="#n423">423</a></p> +<p id="n424" class="pln"><a href="#n424">424</a></p> +<p id="n425" class="pln"><a href="#n425">425</a></p> +<p id="n426" class="pln"><a href="#n426">426</a></p> +<p id="n427" class="stm run hide_run"><a href="#n427">427</a></p> +<p id="n428" class="pln"><a href="#n428">428</a></p> +<p id="n429" class="stm run hide_run"><a href="#n429">429</a></p> +<p id="n430" class="pln"><a href="#n430">430</a></p> +<p id="n431" class="stm run hide_run"><a href="#n431">431</a></p> +<p id="n432" class="pln"><a href="#n432">432</a></p> +<p id="n433" class="stm run hide_run"><a href="#n433">433</a></p> +<p id="n434" class="pln"><a href="#n434">434</a></p> +<p id="n435" class="pln"><a href="#n435">435</a></p> +<p id="n436" class="stm run hide_run"><a href="#n436">436</a></p> +<p id="n437" class="pln"><a href="#n437">437</a></p> +<p id="n438" class="pln"><a href="#n438">438</a></p> +<p id="n439" class="stm run hide_run"><a href="#n439">439</a></p> +<p id="n440" class="pln"><a href="#n440">440</a></p> +<p id="n441" class="pln"><a href="#n441">441</a></p> +<p id="n442" class="pln"><a href="#n442">442</a></p> +<p id="n443" class="pln"><a href="#n443">443</a></p> +<p id="n444" class="pln"><a href="#n444">444</a></p> +<p id="n445" class="pln"><a href="#n445">445</a></p> +<p id="n446" class="stm run hide_run"><a href="#n446">446</a></p> +<p id="n447" class="pln"><a href="#n447">447</a></p> +<p id="n448" class="stm run hide_run"><a href="#n448">448</a></p> +<p id="n449" class="pln"><a href="#n449">449</a></p> +<p id="n450" class="pln"><a href="#n450">450</a></p> +<p id="n451" class="pln"><a href="#n451">451</a></p> +<p id="n452" class="pln"><a href="#n452">452</a></p> +<p id="n453" class="pln"><a href="#n453">453</a></p> +<p id="n454" class="pln"><a href="#n454">454</a></p> +<p id="n455" class="pln"><a href="#n455">455</a></p> +<p id="n456" class="pln"><a href="#n456">456</a></p> +<p id="n457" class="pln"><a href="#n457">457</a></p> +<p id="n458" class="pln"><a href="#n458">458</a></p> +<p id="n459" class="pln"><a href="#n459">459</a></p> +<p id="n460" class="pln"><a href="#n460">460</a></p> +<p id="n461" class="pln"><a href="#n461">461</a></p> +<p id="n462" class="pln"><a href="#n462">462</a></p> +<p id="n463" class="stm run hide_run"><a href="#n463">463</a></p> +<p id="n464" class="pln"><a href="#n464">464</a></p> +<p id="n465" class="pln"><a href="#n465">465</a></p> +<p id="n466" class="stm run hide_run"><a href="#n466">466</a></p> +<p id="n467" class="pln"><a href="#n467">467</a></p> +<p id="n468" class="pln"><a href="#n468">468</a></p> +<p id="n469" class="pln"><a href="#n469">469</a></p> +<p id="n470" class="stm run hide_run"><a href="#n470">470</a></p> +<p id="n471" class="pln"><a href="#n471">471</a></p> +<p id="n472" class="stm run hide_run"><a href="#n472">472</a></p> +<p id="n473" class="pln"><a href="#n473">473</a></p> +<p id="n474" class="stm run hide_run"><a href="#n474">474</a></p> +<p id="n475" class="pln"><a href="#n475">475</a></p> +<p id="n476" class="stm run hide_run"><a href="#n476">476</a></p> +<p id="n477" class="pln"><a href="#n477">477</a></p> +<p id="n478" class="pln"><a href="#n478">478</a></p> +<p id="n479" class="pln"><a href="#n479">479</a></p> +<p id="n480" class="pln"><a href="#n480">480</a></p> +<p id="n481" class="pln"><a href="#n481">481</a></p> +<p id="n482" class="pln"><a href="#n482">482</a></p> +<p id="n483" class="pln"><a href="#n483">483</a></p> +<p id="n484" class="pln"><a href="#n484">484</a></p> +<p id="n485" class="stm run hide_run"><a href="#n485">485</a></p> +<p id="n486" class="pln"><a href="#n486">486</a></p> +<p id="n487" class="stm run hide_run"><a href="#n487">487</a></p> +<p id="n488" class="pln"><a href="#n488">488</a></p> +<p id="n489" class="stm run hide_run"><a href="#n489">489</a></p> +<p id="n490" class="pln"><a href="#n490">490</a></p> +<p id="n491" class="stm run hide_run"><a href="#n491">491</a></p> +<p id="n492" class="pln"><a href="#n492">492</a></p> +<p id="n493" class="pln"><a href="#n493">493</a></p> +<p id="n494" class="pln"><a href="#n494">494</a></p> +<p id="n495" class="stm run hide_run"><a href="#n495">495</a></p> +<p id="n496" class="stm run hide_run"><a href="#n496">496</a></p> +<p id="n497" class="stm mis"><a href="#n497">497</a></p> +<p id="n498" class="stm mis"><a href="#n498">498</a></p> +<p id="n499" class="stm mis"><a href="#n499">499</a></p> +<p id="n500" class="pln"><a href="#n500">500</a></p> +<p id="n501" class="stm run hide_run"><a href="#n501">501</a></p> +<p id="n502" class="pln"><a href="#n502">502</a></p> +<p id="n503" class="stm run hide_run"><a href="#n503">503</a></p> +<p id="n504" class="pln"><a href="#n504">504</a></p> +<p id="n505" class="pln"><a href="#n505">505</a></p> +<p id="n506" class="stm run hide_run"><a href="#n506">506</a></p> +<p id="n507" class="pln"><a href="#n507">507</a></p> +<p id="n508" class="stm run hide_run"><a href="#n508">508</a></p> +<p id="n509" class="pln"><a href="#n509">509</a></p> +<p id="n510" class="pln"><a href="#n510">510</a></p> +<p id="n511" class="pln"><a href="#n511">511</a></p> +<p id="n512" class="pln"><a href="#n512">512</a></p> +<p id="n513" class="pln"><a href="#n513">513</a></p> +<p id="n514" class="pln"><a href="#n514">514</a></p> +<p id="n515" class="pln"><a href="#n515">515</a></p> +<p id="n516" class="pln"><a href="#n516">516</a></p> +<p id="n517" class="pln"><a href="#n517">517</a></p> +<p id="n518" class="stm run hide_run"><a href="#n518">518</a></p> +<p id="n519" class="stm run hide_run"><a href="#n519">519</a></p> +<p id="n520" class="pln"><a href="#n520">520</a></p> +<p id="n521" class="pln"><a href="#n521">521</a></p> +<p id="n522" class="stm run hide_run"><a href="#n522">522</a></p> +<p id="n523" class="pln"><a href="#n523">523</a></p> +<p id="n524" class="pln"><a href="#n524">524</a></p> +<p id="n525" class="pln"><a href="#n525">525</a></p> +<p id="n526" class="stm run hide_run"><a href="#n526">526</a></p> +<p id="n527" class="stm run hide_run"><a href="#n527">527</a></p> +<p id="n528" class="stm run hide_run"><a href="#n528">528</a></p> +<p id="n529" class="pln"><a href="#n529">529</a></p> +<p id="n530" class="pln"><a href="#n530">530</a></p> +<p id="n531" class="stm run hide_run"><a href="#n531">531</a></p> +<p id="n532" class="pln"><a href="#n532">532</a></p> +<p id="n533" class="stm run hide_run"><a href="#n533">533</a></p> +<p id="n534" class="pln"><a href="#n534">534</a></p> +<p id="n535" class="pln"><a href="#n535">535</a></p> +<p id="n536" class="pln"><a href="#n536">536</a></p> +<p id="n537" class="pln"><a href="#n537">537</a></p> +<p id="n538" class="pln"><a href="#n538">538</a></p> +<p id="n539" class="pln"><a href="#n539">539</a></p> +<p id="n540" class="pln"><a href="#n540">540</a></p> +<p id="n541" class="pln"><a href="#n541">541</a></p> +<p id="n542" class="pln"><a href="#n542">542</a></p> +<p id="n543" class="pln"><a href="#n543">543</a></p> +<p id="n544" class="stm run hide_run"><a href="#n544">544</a></p> +<p id="n545" class="stm run hide_run"><a href="#n545">545</a></p> +<p id="n546" class="pln"><a href="#n546">546</a></p> +<p id="n547" class="stm run hide_run"><a href="#n547">547</a></p> +<p id="n548" class="pln"><a href="#n548">548</a></p> +<p id="n549" class="stm run hide_run"><a href="#n549">549</a></p> +<p id="n550" class="pln"><a href="#n550">550</a></p> +<p id="n551" class="stm run hide_run"><a href="#n551">551</a></p> +<p id="n552" class="pln"><a href="#n552">552</a></p> +<p id="n553" class="pln"><a href="#n553">553</a></p> +<p id="n554" class="pln"><a href="#n554">554</a></p> +<p id="n555" class="pln"><a href="#n555">555</a></p> +<p id="n556" class="pln"><a href="#n556">556</a></p> +<p id="n557" class="pln"><a href="#n557">557</a></p> +<p id="n558" class="pln"><a href="#n558">558</a></p> +<p id="n559" class="pln"><a href="#n559">559</a></p> +<p id="n560" class="pln"><a href="#n560">560</a></p> +<p id="n561" class="pln"><a href="#n561">561</a></p> +<p id="n562" class="pln"><a href="#n562">562</a></p> +<p id="n563" class="stm run hide_run"><a href="#n563">563</a></p> +<p id="n564" class="stm run hide_run"><a href="#n564">564</a></p> +<p id="n565" class="pln"><a href="#n565">565</a></p> +<p id="n566" class="stm run hide_run"><a href="#n566">566</a></p> +<p id="n567" class="pln"><a href="#n567">567</a></p> +<p id="n568" class="stm run hide_run"><a href="#n568">568</a></p> +<p id="n569" class="pln"><a href="#n569">569</a></p> +<p id="n570" class="pln"><a href="#n570">570</a></p> +<p id="n571" class="stm run hide_run"><a href="#n571">571</a></p> +<p id="n572" class="pln"><a href="#n572">572</a></p> +<p id="n573" class="stm run hide_run"><a href="#n573">573</a></p> +<p id="n574" class="pln"><a href="#n574">574</a></p> +<p id="n575" class="pln"><a href="#n575">575</a></p> +<p id="n576" class="pln"><a href="#n576">576</a></p> +<p id="n577" class="pln"><a href="#n577">577</a></p> +<p id="n578" class="pln"><a href="#n578">578</a></p> +<p id="n579" class="pln"><a href="#n579">579</a></p> +<p id="n580" class="pln"><a href="#n580">580</a></p> +<p id="n581" class="pln"><a href="#n581">581</a></p> +<p id="n582" class="pln"><a href="#n582">582</a></p> +<p id="n583" class="stm mis"><a href="#n583">583</a></p> +<p id="n584" class="stm mis"><a href="#n584">584</a></p> +<p id="n585" class="stm mis"><a href="#n585">585</a></p> +<p id="n586" class="stm mis"><a href="#n586">586</a></p> +<p id="n587" class="pln"><a href="#n587">587</a></p> +<p id="n588" class="stm mis"><a href="#n588">588</a></p> +<p id="n589" class="pln"><a href="#n589">589</a></p> +<p id="n590" class="pln"><a href="#n590">590</a></p> +<p id="n591" class="stm mis"><a href="#n591">591</a></p> +<p id="n592" class="stm mis"><a href="#n592">592</a></p> +<p id="n593" class="pln"><a href="#n593">593</a></p> +<p id="n594" class="pln"><a href="#n594">594</a></p> +<p id="n595" class="stm mis"><a href="#n595">595</a></p> +<p id="n596" class="stm mis"><a href="#n596">596</a></p> +<p id="n597" class="stm mis"><a href="#n597">597</a></p> +<p id="n598" class="pln"><a href="#n598">598</a></p> +<p id="n599" class="pln"><a href="#n599">599</a></p> +<p id="n600" class="pln"><a href="#n600">600</a></p> +<p id="n601" class="pln"><a href="#n601">601</a></p> +<p id="n602" class="stm mis"><a href="#n602">602</a></p> +<p id="n603" class="stm mis"><a href="#n603">603</a></p> +<p id="n604" class="stm mis"><a href="#n604">604</a></p> +<p id="n605" class="pln"><a href="#n605">605</a></p> +<p id="n606" class="pln"><a href="#n606">606</a></p> +<p id="n607" class="stm mis"><a href="#n607">607</a></p> +<p id="n608" class="pln"><a href="#n608">608</a></p> +<p id="n609" class="stm run hide_run"><a href="#n609">609</a></p> +<p id="n610" class="pln"><a href="#n610">610</a></p> +<p id="n611" class="pln"><a href="#n611">611</a></p> +<p id="n612" class="pln"><a href="#n612">612</a></p> +<p id="n613" class="pln"><a href="#n613">613</a></p> +<p id="n614" class="pln"><a href="#n614">614</a></p> +<p id="n615" class="pln"><a href="#n615">615</a></p> +<p id="n616" class="pln"><a href="#n616">616</a></p> +<p id="n617" class="pln"><a href="#n617">617</a></p> +<p id="n618" class="pln"><a href="#n618">618</a></p> +<p id="n619" class="pln"><a href="#n619">619</a></p> +<p id="n620" class="stm mis"><a href="#n620">620</a></p> +<p id="n621" class="stm mis"><a href="#n621">621</a></p> +<p id="n622" class="stm mis"><a href="#n622">622</a></p> +<p id="n623" class="stm mis"><a href="#n623">623</a></p> +<p id="n624" class="pln"><a href="#n624">624</a></p> +<p id="n625" class="stm mis"><a href="#n625">625</a></p> +<p id="n626" class="pln"><a href="#n626">626</a></p> +<p id="n627" class="stm mis"><a href="#n627">627</a></p> +<p id="n628" class="pln"><a href="#n628">628</a></p> +<p id="n629" class="pln"><a href="#n629">629</a></p> +<p id="n630" class="stm mis"><a href="#n630">630</a></p> +<p id="n631" class="pln"><a href="#n631">631</a></p> +<p id="n632" class="stm run hide_run"><a href="#n632">632</a></p> +<p id="n633" class="pln"><a href="#n633">633</a></p> +<p id="n634" class="pln"><a href="#n634">634</a></p> +<p id="n635" class="pln"><a href="#n635">635</a></p> +<p id="n636" class="pln"><a href="#n636">636</a></p> +<p id="n637" class="pln"><a href="#n637">637</a></p> +<p id="n638" class="pln"><a href="#n638">638</a></p> +<p id="n639" class="pln"><a href="#n639">639</a></p> +<p id="n640" class="pln"><a href="#n640">640</a></p> +<p id="n641" class="pln"><a href="#n641">641</a></p> +<p id="n642" class="pln"><a href="#n642">642</a></p> +<p id="n643" class="pln"><a href="#n643">643</a></p> +<p id="n644" class="stm mis"><a href="#n644">644</a></p> +<p id="n645" class="stm mis"><a href="#n645">645</a></p> +<p id="n646" class="pln"><a href="#n646">646</a></p> +<p id="n647" class="stm mis"><a href="#n647">647</a></p> +<p id="n648" class="pln"><a href="#n648">648</a></p> +<p id="n649" class="pln"><a href="#n649">649</a></p> +<p id="n650" class="stm mis"><a href="#n650">650</a></p> +<p id="n651" class="pln"><a href="#n651">651</a></p> +<p id="n652" class="pln"><a href="#n652">652</a></p> +<p id="n653" class="stm run hide_run"><a href="#n653">653</a></p> +<p id="n654" class="pln"><a href="#n654">654</a></p> +<p id="n655" class="stm run hide_run"><a href="#n655">655</a></p> +<p id="n656" class="pln"><a href="#n656">656</a></p> +<p id="n657" class="pln"><a href="#n657">657</a></p> +<p id="n658" class="pln"><a href="#n658">658</a></p> +<p id="n659" class="pln"><a href="#n659">659</a></p> +<p id="n660" class="pln"><a href="#n660">660</a></p> +<p id="n661" class="pln"><a href="#n661">661</a></p> +<p id="n662" class="pln"><a href="#n662">662</a></p> +<p id="n663" class="pln"><a href="#n663">663</a></p> +<p id="n664" class="pln"><a href="#n664">664</a></p> +<p id="n665" class="stm run hide_run"><a href="#n665">665</a></p> +<p id="n666" class="stm run hide_run"><a href="#n666">666</a></p> +<p id="n667" class="stm run hide_run"><a href="#n667">667</a></p> +<p id="n668" class="stm run hide_run"><a href="#n668">668</a></p> +<p id="n669" class="stm run hide_run"><a href="#n669">669</a></p> +<p id="n670" class="pln"><a href="#n670">670</a></p> +<p id="n671" class="stm run hide_run"><a href="#n671">671</a></p> +<p id="n672" class="pln"><a href="#n672">672</a></p> +<p id="n673" class="stm run hide_run"><a href="#n673">673</a></p> +<p id="n674" class="pln"><a href="#n674">674</a></p> +<p id="n675" class="pln"><a href="#n675">675</a></p> +<p id="n676" class="stm run hide_run"><a href="#n676">676</a></p> +<p id="n677" class="stm run hide_run"><a href="#n677">677</a></p> +<p id="n678" class="pln"><a href="#n678">678</a></p> +<p id="n679" class="pln"><a href="#n679">679</a></p> +<p id="n680" class="pln"><a href="#n680">680</a></p> +<p id="n681" class="stm run hide_run"><a href="#n681">681</a></p> +<p id="n682" class="stm run hide_run"><a href="#n682">682</a></p> +<p id="n683" class="stm run hide_run"><a href="#n683">683</a></p> +<p id="n684" class="pln"><a href="#n684">684</a></p> +<p id="n685" class="pln"><a href="#n685">685</a></p> +<p id="n686" class="stm run hide_run"><a href="#n686">686</a></p> +<p id="n687" class="stm run hide_run"><a href="#n687">687</a></p> +<p id="n688" class="stm run hide_run"><a href="#n688">688</a></p> +<p id="n689" class="pln"><a href="#n689">689</a></p> +<p id="n690" class="pln"><a href="#n690">690</a></p> +<p id="n691" class="pln"><a href="#n691">691</a></p> +<p id="n692" class="pln"><a href="#n692">692</a></p> +<p id="n693" class="pln"><a href="#n693">693</a></p> +<p id="n694" class="pln"><a href="#n694">694</a></p> +<p id="n695" class="stm run hide_run"><a href="#n695">695</a></p> +<p id="n696" class="stm run hide_run"><a href="#n696">696</a></p> +<p id="n697" class="stm run hide_run"><a href="#n697">697</a></p> +<p id="n698" class="pln"><a href="#n698">698</a></p> +<p id="n699" class="pln"><a href="#n699">699</a></p> +<p id="n700" class="stm run hide_run"><a href="#n700">700</a></p> +<p id="n701" class="pln"><a href="#n701">701</a></p> +<p id="n702" class="stm run hide_run"><a href="#n702">702</a></p> +<p id="n703" class="pln"><a href="#n703">703</a></p> +<p id="n704" class="pln"><a href="#n704">704</a></p> +<p id="n705" class="pln"><a href="#n705">705</a></p> +<p id="n706" class="pln"><a href="#n706">706</a></p> +<p id="n707" class="pln"><a href="#n707">707</a></p> +<p id="n708" class="pln"><a href="#n708">708</a></p> +<p id="n709" class="pln"><a href="#n709">709</a></p> +<p id="n710" class="pln"><a href="#n710">710</a></p> +<p id="n711" class="pln"><a href="#n711">711</a></p> +<p id="n712" class="pln"><a href="#n712">712</a></p> +<p id="n713" class="stm run hide_run"><a href="#n713">713</a></p> +<p id="n714" class="stm run hide_run"><a href="#n714">714</a></p> +<p id="n715" class="stm run hide_run"><a href="#n715">715</a></p> +<p id="n716" class="stm run hide_run"><a href="#n716">716</a></p> +<p id="n717" class="stm run hide_run"><a href="#n717">717</a></p> +<p id="n718" class="pln"><a href="#n718">718</a></p> +<p id="n719" class="stm run hide_run"><a href="#n719">719</a></p> +<p id="n720" class="pln"><a href="#n720">720</a></p> +<p id="n721" class="pln"><a href="#n721">721</a></p> +<p id="n722" class="stm run hide_run"><a href="#n722">722</a></p> +<p id="n723" class="pln"><a href="#n723">723</a></p> +<p id="n724" class="stm run hide_run"><a href="#n724">724</a></p> +<p id="n725" class="stm run hide_run"><a href="#n725">725</a></p> +<p id="n726" class="pln"><a href="#n726">726</a></p> +<p id="n727" class="stm run hide_run"><a href="#n727">727</a></p> +<p id="n728" class="stm run hide_run"><a href="#n728">728</a></p> +<p id="n729" class="pln"><a href="#n729">729</a></p> +<p id="n730" class="pln"><a href="#n730">730</a></p> +<p id="n731" class="pln"><a href="#n731">731</a></p> +<p id="n732" class="stm run hide_run"><a href="#n732">732</a></p> +<p id="n733" class="pln"><a href="#n733">733</a></p> +<p id="n734" class="stm run hide_run"><a href="#n734">734</a></p> +<p id="n735" class="pln"><a href="#n735">735</a></p> +<p id="n736" class="pln"><a href="#n736">736</a></p> +<p id="n737" class="pln"><a href="#n737">737</a></p> +<p id="n738" class="pln"><a href="#n738">738</a></p> +<p id="n739" class="pln"><a href="#n739">739</a></p> +<p id="n740" class="pln"><a href="#n740">740</a></p> +<p id="n741" class="pln"><a href="#n741">741</a></p> +<p id="n742" class="pln"><a href="#n742">742</a></p> +<p id="n743" class="pln"><a href="#n743">743</a></p> +<p id="n744" class="pln"><a href="#n744">744</a></p> +<p id="n745" class="pln"><a href="#n745">745</a></p> +<p id="n746" class="stm run hide_run"><a href="#n746">746</a></p> +<p id="n747" class="stm run hide_run"><a href="#n747">747</a></p> +<p id="n748" class="stm run hide_run"><a href="#n748">748</a></p> +<p id="n749" class="stm run hide_run"><a href="#n749">749</a></p> +<p id="n750" class="stm run hide_run"><a href="#n750">750</a></p> +<p id="n751" class="pln"><a href="#n751">751</a></p> +<p id="n752" class="stm run hide_run"><a href="#n752">752</a></p> +<p id="n753" class="pln"><a href="#n753">753</a></p> +<p id="n754" class="pln"><a href="#n754">754</a></p> +<p id="n755" class="stm run hide_run"><a href="#n755">755</a></p> +<p id="n756" class="pln"><a href="#n756">756</a></p> +<p id="n757" class="stm run hide_run"><a href="#n757">757</a></p> +<p id="n758" class="stm run hide_run"><a href="#n758">758</a></p> +<p id="n759" class="pln"><a href="#n759">759</a></p> +<p id="n760" class="stm run hide_run"><a href="#n760">760</a></p> +<p id="n761" class="stm run hide_run"><a href="#n761">761</a></p> +<p id="n762" class="pln"><a href="#n762">762</a></p> +<p id="n763" class="pln"><a href="#n763">763</a></p> +<p id="n764" class="pln"><a href="#n764">764</a></p> +<p id="n765" class="stm run hide_run"><a href="#n765">765</a></p> +<p id="n766" class="pln"><a href="#n766">766</a></p> +<p id="n767" class="pln"><a href="#n767">767</a></p> +<p id="n768" class="stm run hide_run"><a href="#n768">768</a></p> +<p id="n769" class="pln"><a href="#n769">769</a></p> +<p id="n770" class="pln"><a href="#n770">770</a></p> +<p id="n771" class="pln"><a href="#n771">771</a></p> +<p id="n772" class="pln"><a href="#n772">772</a></p> +<p id="n773" class="pln"><a href="#n773">773</a></p> +<p id="n774" class="pln"><a href="#n774">774</a></p> +<p id="n775" class="pln"><a href="#n775">775</a></p> +<p id="n776" class="pln"><a href="#n776">776</a></p> +<p id="n777" class="stm run hide_run"><a href="#n777">777</a></p> +<p id="n778" class="stm mis"><a href="#n778">778</a></p> +<p id="n779" class="stm run hide_run"><a href="#n779">779</a></p> +<p id="n780" class="stm mis"><a href="#n780">780</a></p> +<p id="n781" class="stm run hide_run"><a href="#n781">781</a></p> +<p id="n782" class="stm run hide_run"><a href="#n782">782</a></p> +<p id="n783" class="pln"><a href="#n783">783</a></p> +<p id="n784" class="stm mis"><a href="#n784">784</a></p> +<p id="n785" class="pln"><a href="#n785">785</a></p> +<p id="n786" class="pln"><a href="#n786">786</a></p> +<p id="n787" class="stm run hide_run"><a href="#n787">787</a></p> +<p id="n788" class="stm run hide_run"><a href="#n788">788</a></p> +<p id="n789" class="stm mis"><a href="#n789">789</a></p> +<p id="n790" class="stm mis"><a href="#n790">790</a></p> +<p id="n791" class="pln"><a href="#n791">791</a></p> +<p id="n792" class="stm mis"><a href="#n792">792</a></p> +<p id="n793" class="pln"><a href="#n793">793</a></p> +<p id="n794" class="pln"><a href="#n794">794</a></p> +<p id="n795" class="stm run hide_run"><a href="#n795">795</a></p> +<p id="n796" class="pln"><a href="#n796">796</a></p> +<p id="n797" class="pln"><a href="#n797">797</a></p> +<p id="n798" class="pln"><a href="#n798">798</a></p> +<p id="n799" class="pln"><a href="#n799">799</a></p> +<p id="n800" class="pln"><a href="#n800">800</a></p> +<p id="n801" class="pln"><a href="#n801">801</a></p> +<p id="n802" class="pln"><a href="#n802">802</a></p> +<p id="n803" class="pln"><a href="#n803">803</a></p> +<p id="n804" class="pln"><a href="#n804">804</a></p> +<p id="n805" class="pln"><a href="#n805">805</a></p> +<p id="n806" class="pln"><a href="#n806">806</a></p> +<p id="n807" class="pln"><a href="#n807">807</a></p> +<p id="n808" class="stm run hide_run"><a href="#n808">808</a></p> +<p id="n809" class="pln"><a href="#n809">809</a></p> +<p id="n810" class="pln"><a href="#n810">810</a></p> +<p id="n811" class="pln"><a href="#n811">811</a></p> +<p id="n812" class="pln"><a href="#n812">812</a></p> +<p id="n813" class="pln"><a href="#n813">813</a></p> +<p id="n814" class="pln"><a href="#n814">814</a></p> +<p id="n815" class="pln"><a href="#n815">815</a></p> +<p id="n816" class="pln"><a href="#n816">816</a></p> +<p id="n817" class="pln"><a href="#n817">817</a></p> +<p id="n818" class="stm run hide_run"><a href="#n818">818</a></p> +<p id="n819" class="pln"><a href="#n819">819</a></p> +<p id="n820" class="pln"><a href="#n820">820</a></p> +<p id="n821" class="stm run hide_run"><a href="#n821">821</a></p> +<p id="n822" class="stm run hide_run"><a href="#n822">822</a></p> +<p id="n823" class="pln"><a href="#n823">823</a></p> +<p id="n824" class="pln"><a href="#n824">824</a></p> +<p id="n825" class="pln"><a href="#n825">825</a></p> +<p id="n826" class="stm run hide_run"><a href="#n826">826</a></p> +<p id="n827" class="pln"><a href="#n827">827</a></p> +<p id="n828" class="stm run hide_run"><a href="#n828">828</a></p> +<p id="n829" class="pln"><a href="#n829">829</a></p> +<p id="n830" class="pln"><a href="#n830">830</a></p> +<p id="n831" class="pln"><a href="#n831">831</a></p> +<p id="n832" class="pln"><a href="#n832">832</a></p> +<p id="n833" class="stm run hide_run"><a href="#n833">833</a></p> +<p id="n834" class="pln"><a href="#n834">834</a></p> +<p id="n835" class="pln"><a href="#n835">835</a></p> +<p id="n836" class="pln"><a href="#n836">836</a></p> +<p id="n837" class="pln"><a href="#n837">837</a></p> +<p id="n838" class="stm run hide_run"><a href="#n838">838</a></p> +<p id="n839" class="pln"><a href="#n839">839</a></p> +<p id="n840" class="stm run hide_run"><a href="#n840">840</a></p> +<p id="n841" class="pln"><a href="#n841">841</a></p> +<p id="n842" class="pln"><a href="#n842">842</a></p> +<p id="n843" class="stm run hide_run"><a href="#n843">843</a></p> +<p id="n844" class="pln"><a href="#n844">844</a></p> +<p id="n845" class="pln"><a href="#n845">845</a></p> +<p id="n846" class="pln"><a href="#n846">846</a></p> +<p id="n847" class="pln"><a href="#n847">847</a></p> +<p id="n848" class="pln"><a href="#n848">848</a></p> +<p id="n849" class="pln"><a href="#n849">849</a></p> +<p id="n850" class="pln"><a href="#n850">850</a></p> +<p id="n851" class="pln"><a href="#n851">851</a></p> +<p id="n852" class="pln"><a href="#n852">852</a></p> +<p id="n853" class="pln"><a href="#n853">853</a></p> +<p id="n854" class="pln"><a href="#n854">854</a></p> +<p id="n855" class="pln"><a href="#n855">855</a></p> +<p id="n856" class="stm mis"><a href="#n856">856</a></p> +<p id="n857" class="pln"><a href="#n857">857</a></p> +<p id="n858" class="pln"><a href="#n858">858</a></p> +<p id="n859" class="pln"><a href="#n859">859</a></p> +<p id="n860" class="stm mis"><a href="#n860">860</a></p> + + </td> + <td class="text"> +<p id="t1" class="stm run hide_run"><span class="key">from</span> <span class="nam">abc</span> <span class="key">import</span> <span class="nam">abstractmethod</span><span class="strut"> </span></p> +<p id="t2" class="pln"><span class="strut"> </span></p> +<p id="t3" class="stm run hide_run"><span class="key">import</span> <span class="nam">numpy</span> <span class="key">as</span> <span class="nam">np</span><span class="strut"> </span></p> +<p id="t4" class="pln"><span class="strut"> </span></p> +<p id="t5" class="stm run hide_run"><span class="key">import</span> <span class="nam">fluegg</span><span class="op">.</span><span class="nam">hydraulics</span> <span class="key">as</span> <span class="nam">hydraulics</span><span class="strut"> </span></p> +<p id="t6" class="pln"><span class="strut"> </span></p> +<p id="t7" class="pln"><span class="strut"> </span></p> +<p id="t8" class="stm run hide_run"><span class="key">class</span> <span class="nam">Transporter</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t9" class="pln"><span class="strut"> </span></p> +<p id="t10" class="stm run hide_run"> <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">simulation_clock</span><span class="op">,</span> <span class="nam">particles</span><span class="op">,</span> <span class="nam">random_numbers</span><span class="op">=</span><span class="key">None</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t11" class="pln"> <span class="str">"""</span><span class="strut"> </span></p> +<p id="t12" class="pln"><span class="strut"> </span></p> +<p id="t13" class="pln"><span class="str"> :param simulation_clock:</span><span class="strut"> </span></p> +<p id="t14" class="pln"><span class="str"> :param particles:</span><span class="strut"> </span></p> +<p id="t15" class="pln"><span class="str"> :param hydraulic_model:</span><span class="strut"> </span></p> +<p id="t16" class="pln"><span class="str"> :param random_numbers:</span><span class="strut"> </span></p> +<p id="t17" class="pln"><span class="str"> :type: fluegg.random.RandomNumbers</span><span class="strut"> </span></p> +<p id="t18" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t19" class="pln"><span class="strut"> </span></p> +<p id="t20" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_simulation_clock</span> <span class="op">=</span> <span class="nam">simulation_clock</span><span class="strut"> </span></p> +<p id="t21" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_particles</span> <span class="op">=</span> <span class="nam">particles</span><span class="strut"> </span></p> +<p id="t22" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_hydraulic_model</span> <span class="op">=</span> <span class="key">None</span><span class="strut"> </span></p> +<p id="t23" class="stm run hide_run"> <span class="key">if</span> <span class="nam">random_numbers</span> <span class="key">is</span> <span class="key">None</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t24" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">_random_func</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">random</span><span class="op">.</span><span class="nam">normal</span><span class="strut"> </span></p> +<p id="t25" class="pln"> <span class="key">else</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t26" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_random_func</span> <span class="op">=</span> <span class="nam">random_numbers</span><span class="op">.</span><span class="nam">random_array</span><span class="strut"> </span></p> +<p id="t27" class="pln"><span class="strut"> </span></p> +<p id="t28" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_random_num</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">size</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t29" class="pln"> <span class="str">"""Returns an array of random numbers pulled from</span><span class="strut"> </span></p> +<p id="t30" class="pln"><span class="str"> a normal distribution (mean=0, std=1)</span><span class="strut"> </span></p> +<p id="t31" class="pln"><span class="strut"> </span></p> +<p id="t32" class="pln"><span class="str"> :param size: Number of random numbers</span><span class="strut"> </span></p> +<p id="t33" class="pln"><span class="str"> :type: int</span><span class="strut"> </span></p> +<p id="t34" class="pln"><span class="str"> :return: random numbers</span><span class="strut"> </span></p> +<p id="t35" class="pln"><span class="str"> :rtype: numpy.ndarray</span><span class="strut"> </span></p> +<p id="t36" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t37" class="pln"><span class="strut"> </span></p> +<p id="t38" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_random_func</span><span class="op">(</span><span class="num">0</span><span class="op">,</span> <span class="num">1</span><span class="op">,</span> <span class="nam">size</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t39" class="pln"><span class="strut"> </span></p> +<p id="t40" class="stm run hide_run"> <span class="op">@</span><span class="nam">staticmethod</span><span class="strut"> </span></p> +<p id="t41" class="pln"> <span class="key">def</span> <span class="nam">_horizontal_turbulent_diffusion</span><span class="op">(</span><span class="nam">depth</span><span class="op">,</span> <span class="nam">shear_velocity</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t42" class="pln"> <span class="str">"""Returns the horizontal turbulent diffusion</span><span class="strut"> </span></p> +<p id="t43" class="pln"><span class="strut"> </span></p> +<p id="t44" class="pln"><span class="str"> :param depth: depth of water (m)</span><span class="strut"> </span></p> +<p id="t45" class="pln"><span class="str"> :type: numpy.ndarray</span><span class="strut"> </span></p> +<p id="t46" class="pln"><span class="str"> :param shear_velocity: shear velocity of water at depth (m/s)</span><span class="strut"> </span></p> +<p id="t47" class="pln"><span class="str"> :type: numpy.ndarray</span><span class="strut"> </span></p> +<p id="t48" class="pln"><span class="str"> :return: horizontal turbulent diffusion at input depth (m**2/s)</span><span class="strut"> </span></p> +<p id="t49" class="pln"><span class="str"> :rtype: numpy.ndarray</span><span class="strut"> </span></p> +<p id="t50" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t51" class="pln"><span class="strut"> </span></p> +<p id="t52" class="stm run hide_run"> <span class="key">return</span> <span class="num">0.6</span> <span class="op">*</span> <span class="nam">depth</span> <span class="op">*</span> <span class="nam">shear_velocity</span><span class="strut"> </span></p> +<p id="t53" class="pln"><span class="strut"> </span></p> +<p id="t54" class="stm run hide_run"> <span class="op">@</span><span class="nam">abstractmethod</span><span class="strut"> </span></p> +<p id="t55" class="pln"> <span class="key">def</span> <span class="nam">increment_positions</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">hydraulic_results</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t56" class="pln"> <span class="str">"""Increments positions of particles according to current time step.</span><span class="strut"> </span></p> +<p id="t57" class="pln"><span class="strut"> </span></p> +<p id="t58" class="pln"><span class="str"> :param hydraulic_results: hydraulic results at current particle</span><span class="strut"> </span></p> +<p id="t59" class="pln"><span class="str"> positions</span><span class="strut"> </span></p> +<p id="t60" class="pln"><span class="str"> :type hydraulic_results: fluegg.hydraulics.HydraulicResults</span><span class="strut"> </span></p> +<p id="t61" class="pln"><span class="strut"> </span></p> +<p id="t62" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t63" class="pln"><span class="strut"> </span></p> +<p id="t64" class="stm mis"> <span class="key">raise</span> <span class="nam">NotImplementedError</span><span class="strut"> </span></p> +<p id="t65" class="pln"><span class="strut"> </span></p> +<p id="t66" class="stm run hide_run"> <span class="key">def</span> <span class="nam">set_hydraulic_model</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">hydraulic_model</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t67" class="pln"> <span class="str">"""</span><span class="strut"> </span></p> +<p id="t68" class="pln"><span class="strut"> </span></p> +<p id="t69" class="pln"><span class="str"> :param hydraulic_model:</span><span class="strut"> </span></p> +<p id="t70" class="pln"><span class="str"> :type hydraulic_model: fluegg.hydraulics.SeriesOfHydraulicCells</span><span class="strut"> </span></p> +<p id="t71" class="pln"><span class="str"> :return: None</span><span class="strut"> </span></p> +<p id="t72" class="pln"><span class="strut"> </span></p> +<p id="t73" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t74" class="pln"><span class="strut"> </span></p> +<p id="t75" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_hydraulic_model</span> <span class="op">=</span> <span class="nam">hydraulic_model</span><span class="strut"> </span></p> +<p id="t76" class="pln"><span class="strut"> </span></p> +<p id="t77" class="stm run hide_run"> <span class="key">def</span> <span class="nam">max_time_step</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t78" class="pln"> <span class="str">"""Finds the maximum time step required for an accurate simulation.</span><span class="strut"> </span></p> +<p id="t79" class="pln"><span class="str"> Default is at infinity (i.e. no maximum time step)</span><span class="strut"> </span></p> +<p id="t80" class="pln"><span class="strut"> </span></p> +<p id="t81" class="pln"><span class="str"> :return: maximum time step criterion given the current time step</span><span class="strut"> </span></p> +<p id="t82" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t83" class="pln"><span class="strut"> </span></p> +<p id="t84" class="stm run hide_run"> <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_hydraulic_model</span> <span class="key">is</span> <span class="key">None</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t85" class="stm mis"> <span class="key">raise</span> <span class="nam">RuntimeError</span><span class="op">(</span><span class="str">"hydraulic_model attribute is set to None"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t86" class="pln"><span class="strut"> </span></p> +<p id="t87" class="stm run hide_run"> <span class="key">return</span> <span class="nam">float</span><span class="op">(</span><span class="str">"inf"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t88" class="pln"><span class="strut"> </span></p> +<p id="t89" class="stm run hide_run"> <span class="key">def</span> <span class="nam">increment_positions</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">hydraulic_results</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t90" class="pln"> <span class="str">"""</span><span class="strut"> </span></p> +<p id="t91" class="pln"><span class="strut"> </span></p> +<p id="t92" class="pln"><span class="str"> Parameters</span><span class="strut"> </span></p> +<p id="t93" class="pln"><span class="str"> ----------</span><span class="strut"> </span></p> +<p id="t94" class="pln"><span class="str"> hydraulic_results : fluegg.hydraulics.HydraulicResults</span><span class="strut"> </span></p> +<p id="t95" class="pln"><span class="strut"> </span></p> +<p id="t96" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t97" class="pln"><span class="strut"> </span></p> +<p id="t98" class="stm mis"> <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_hydraulic_model</span> <span class="key">is</span> <span class="key">None</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t99" class="stm mis"> <span class="key">raise</span> <span class="nam">RuntimeError</span><span class="op">(</span><span class="str">"hydraulic_model attribute is set to None"</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t100" class="pln"><span class="strut"> </span></p> +<p id="t101" class="pln"><span class="strut"> </span></p> +<p id="t102" class="stm run hide_run"><span class="key">class</span> <span class="nam">LateralTransporter</span><span class="op">(</span><span class="nam">Transporter</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t103" class="pln"><span class="strut"> </span></p> +<p id="t104" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_lateral_boundary_checks</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">hydraulic_results</span><span class="op">,</span> <span class="nam">next_position</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t105" class="pln"> <span class="str">"""</span><span class="strut"> </span></p> +<p id="t106" class="pln"><span class="strut"> </span></p> +<p id="t107" class="pln"><span class="str"> :param hydraulic_results:</span><span class="strut"> </span></p> +<p id="t108" class="pln"><span class="str"> :param next_position:</span><span class="strut"> </span></p> +<p id="t109" class="pln"><span class="str"> :return:</span><span class="strut"> </span></p> +<p id="t110" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t111" class="pln"><span class="strut"> </span></p> +<p id="t112" class="pln"> <span class="com"># Check lateral position</span><span class="strut"> </span></p> +<p id="t113" class="stm run hide_run"> <span class="nam">width</span> <span class="op">=</span> <span class="nam">hydraulic_results</span><span class="op">.</span><span class="nam">width</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t114" class="pln"><span class="strut"> </span></p> +<p id="t115" class="stm run hide_run"> <span class="nam">diameter</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_particles</span><span class="op">.</span><span class="nam">diameter</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t116" class="pln"><span class="strut"> </span></p> +<p id="t117" class="stm run hide_run"> <span class="nam">boundary_length</span> <span class="op">=</span> <span class="nam">width</span> <span class="op">-</span> <span class="nam">diameter</span><span class="strut"> </span></p> +<p id="t118" class="pln"><span class="strut"> </span></p> +<p id="t119" class="stm run hide_run"> <span class="nam">shifted_next_lateral_position</span> <span class="op">=</span> <span class="nam">next_position</span> <span class="op">-</span> <span class="nam">diameter</span> <span class="op">/</span> <span class="num">2</span><span class="strut"> </span></p> +<p id="t120" class="stm run hide_run"> <span class="nam">shifted_boundary_location</span> <span class="op">=</span> <span class="nam">boundary_length</span><span class="strut"> </span></p> +<p id="t121" class="pln"><span class="strut"> </span></p> +<p id="t122" class="stm run hide_run"> <span class="nam">right_of_boundary</span> <span class="op">=</span> <span class="nam">shifted_next_lateral_position</span> <span class="op"><</span> <span class="num">0</span><span class="strut"> </span></p> +<p id="t123" class="stm run hide_run"> <span class="nam">left_of_boundary</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t124" class="pln"> <span class="nam">shifted_next_lateral_position</span> <span class="op">></span> <span class="nam">shifted_boundary_location</span><span class="strut"> </span></p> +<p id="t125" class="stm run hide_run"> <span class="nam">out_of_bounds</span> <span class="op">=</span> <span class="nam">right_of_boundary</span> <span class="op">|</span> <span class="nam">left_of_boundary</span><span class="strut"> </span></p> +<p id="t126" class="pln"><span class="strut"> </span></p> +<p id="t127" class="stm run hide_run"> <span class="key">if</span> <span class="nam">np</span><span class="op">.</span><span class="nam">any</span><span class="op">(</span><span class="nam">out_of_bounds</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t128" class="pln"><span class="strut"> </span></p> +<p id="t129" class="stm run hide_run"> <span class="nam">reflections</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">floor_divide</span><span class="op">(</span><span class="nam">shifted_next_lateral_position</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t130" class="pln"> <span class="nam">shifted_boundary_location</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t131" class="stm run hide_run"> <span class="nam">remainder</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">mod</span><span class="op">(</span><span class="nam">shifted_next_lateral_position</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t132" class="pln"> <span class="nam">shifted_boundary_location</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t133" class="pln"><span class="strut"> </span></p> +<p id="t134" class="stm run hide_run"> <span class="nam">reflection_mod_2</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">mod</span><span class="op">(</span><span class="nam">reflections</span><span class="op">,</span> <span class="num">2</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t135" class="stm run hide_run"> <span class="nam">odd_reflections</span> <span class="op">=</span> <span class="op">(</span><span class="nam">reflection_mod_2</span> <span class="op">==</span> <span class="num">1</span><span class="op">)</span> <span class="op">&</span> <span class="nam">out_of_bounds</span><span class="strut"> </span></p> +<p id="t136" class="stm run hide_run"> <span class="nam">even_reflections</span> <span class="op">=</span> <span class="op">(</span><span class="nam">reflection_mod_2</span> <span class="op">==</span> <span class="num">0</span><span class="op">)</span> <span class="op">&</span> <span class="nam">out_of_bounds</span><span class="strut"> </span></p> +<p id="t137" class="pln"><span class="strut"> </span></p> +<p id="t138" class="stm run hide_run"> <span class="nam">shifted_next_lateral_position</span><span class="op">[</span><span class="nam">even_reflections</span><span class="op">]</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t139" class="pln"> <span class="nam">remainder</span><span class="op">[</span><span class="nam">even_reflections</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t140" class="stm run hide_run"> <span class="nam">shifted_next_lateral_position</span><span class="op">[</span><span class="nam">odd_reflections</span><span class="op">]</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t141" class="pln"> <span class="nam">boundary_length</span><span class="op">[</span><span class="nam">odd_reflections</span><span class="op">]</span> <span class="op">-</span> <span class="nam">remainder</span><span class="op">[</span><span class="nam">odd_reflections</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t142" class="pln"><span class="strut"> </span></p> +<p id="t143" class="stm run hide_run"> <span class="nam">next_position</span> <span class="op">=</span> <span class="nam">shifted_next_lateral_position</span> <span class="op">+</span> <span class="nam">diameter</span> <span class="op">/</span> <span class="num">2</span><span class="strut"> </span></p> +<p id="t144" class="pln"><span class="strut"> </span></p> +<p id="t145" class="stm run hide_run"> <span class="key">return</span> <span class="nam">next_position</span><span class="strut"> </span></p> +<p id="t146" class="pln"><span class="strut"> </span></p> +<p id="t147" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_next_lateral_positions</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">hydraulic_results</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t148" class="pln"> <span class="str">"""Returns incremented lateral particle positions</span><span class="strut"> </span></p> +<p id="t149" class="pln"><span class="strut"> </span></p> +<p id="t150" class="pln"><span class="str"> :param hydraulic_results: hydraulic results at current particle</span><span class="strut"> </span></p> +<p id="t151" class="pln"><span class="str"> positions</span><span class="strut"> </span></p> +<p id="t152" class="pln"><span class="str"> :type hydraulic_results: fluegg.hydraulics.HydraulicResults</span><span class="strut"> </span></p> +<p id="t153" class="pln"><span class="str"> :return: next lateral particle positions</span><span class="strut"> </span></p> +<p id="t154" class="pln"><span class="str"> :rtype: numpy.ndarray(num_particles)</span><span class="strut"> </span></p> +<p id="t155" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t156" class="pln"> <span class="com"># Initialize necessary calculations</span><span class="strut"> </span></p> +<p id="t157" class="stm run hide_run"> <span class="nam">lateral_position</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_particles</span><span class="op">.</span><span class="nam">position</span><span class="op">(</span><span class="op">)</span><span class="op">[</span><span class="op">:</span><span class="op">,</span> <span class="num">1</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t158" class="stm run hide_run"> <span class="nam">num_particles</span> <span class="op">=</span> <span class="nam">lateral_position</span><span class="op">.</span><span class="nam">shape</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t159" class="stm run hide_run"> <span class="nam">random_num</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_random_num</span><span class="op">(</span><span class="nam">num_particles</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t160" class="stm run hide_run"> <span class="nam">time_step</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_simulation_clock</span><span class="op">.</span><span class="nam">time_step_size</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t161" class="stm run hide_run"> <span class="nam">lateral_velocity</span> <span class="op">=</span> <span class="nam">hydraulic_results</span><span class="op">.</span><span class="nam">lateral_velocity</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t162" class="pln"><span class="strut"> </span></p> +<p id="t163" class="stm run hide_run"> <span class="nam">depth</span> <span class="op">=</span> <span class="nam">hydraulic_results</span><span class="op">.</span><span class="nam">depth</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t164" class="stm run hide_run"> <span class="nam">shear_velocity</span> <span class="op">=</span> <span class="nam">hydraulic_results</span><span class="op">.</span><span class="nam">shear_velocity</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t165" class="stm run hide_run"> <span class="nam">turbulent_diffusion</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t166" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">_horizontal_turbulent_diffusion</span><span class="op">(</span><span class="nam">depth</span><span class="op">,</span> <span class="nam">shear_velocity</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t167" class="pln"><span class="strut"> </span></p> +<p id="t168" class="pln"> <span class="com"># Calculate incremented lateral positions</span><span class="strut"> </span></p> +<p id="t169" class="stm run hide_run"> <span class="nam">next_lateral_position</span> <span class="op">=</span> <span class="nam">lateral_position</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t170" class="pln"> <span class="op">+</span> <span class="nam">lateral_velocity</span> <span class="op">*</span> <span class="nam">time_step</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t171" class="pln"> <span class="op">+</span> <span class="nam">random_num</span> <span class="op">*</span> <span class="nam">np</span><span class="op">.</span><span class="nam">sqrt</span><span class="op">(</span><span class="num">2</span> <span class="op">*</span> <span class="nam">turbulent_diffusion</span> <span class="op">*</span> <span class="nam">time_step</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t172" class="pln"><span class="strut"> </span></p> +<p id="t173" class="stm run hide_run"> <span class="key">return</span> <span class="nam">next_lateral_position</span><span class="strut"> </span></p> +<p id="t174" class="pln"><span class="strut"> </span></p> +<p id="t175" class="stm run hide_run"> <span class="key">def</span> <span class="nam">increment_positions</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">hydraulic_results</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t176" class="pln"> <span class="str">"""Increments positions of particles according to current time step.</span><span class="strut"> </span></p> +<p id="t177" class="pln"><span class="strut"> </span></p> +<p id="t178" class="pln"><span class="str"> :param hydraulic_results: hydraulic results at current particle</span><span class="strut"> </span></p> +<p id="t179" class="pln"><span class="str"> positions</span><span class="strut"> </span></p> +<p id="t180" class="pln"><span class="str"> :type hydraulic_results: fluegg.hydraulics.HydraulicResults</span><span class="strut"> </span></p> +<p id="t181" class="pln"><span class="strut"> </span></p> +<p id="t182" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t183" class="pln"><span class="strut"> </span></p> +<p id="t184" class="stm run hide_run"> <span class="nam">next_lateral_positions</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t185" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">_next_lateral_positions</span><span class="op">(</span><span class="nam">hydraulic_results</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t186" class="pln"><span class="strut"> </span></p> +<p id="t187" class="stm run hide_run"> <span class="nam">next_lateral_positions</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t188" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">_lateral_boundary_checks</span><span class="op">(</span><span class="nam">hydraulic_results</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t189" class="pln"> <span class="nam">next_lateral_positions</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t190" class="pln"><span class="strut"> </span></p> +<p id="t191" class="stm run hide_run"> <span class="nam">positions</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_particles</span><span class="op">.</span><span class="nam">position</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t192" class="pln"><span class="strut"> </span></p> +<p id="t193" class="stm run hide_run"> <span class="nam">positions</span><span class="op">[</span><span class="op">:</span><span class="op">,</span> <span class="num">1</span><span class="op">]</span> <span class="op">=</span> <span class="nam">next_lateral_positions</span><span class="strut"> </span></p> +<p id="t194" class="pln"><span class="strut"> </span></p> +<p id="t195" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_particles</span><span class="op">.</span><span class="nam">set_position</span><span class="op">(</span><span class="nam">positions</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t196" class="pln"><span class="strut"> </span></p> +<p id="t197" class="pln"><span class="strut"> </span></p> +<p id="t198" class="stm run hide_run"><span class="key">class</span> <span class="nam">LongitudinalTransporter</span><span class="op">(</span><span class="nam">Transporter</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t199" class="pln"><span class="strut"> </span></p> +<p id="t200" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_next_longitudinal_positions</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">hydraulic_results</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t201" class="pln"> <span class="str">"""Returns incremented longitudinal particle positions</span><span class="strut"> </span></p> +<p id="t202" class="pln"><span class="strut"> </span></p> +<p id="t203" class="pln"><span class="str"> :param hydraulic_results: hydraulic results at current particle</span><span class="strut"> </span></p> +<p id="t204" class="pln"><span class="str"> positions</span><span class="strut"> </span></p> +<p id="t205" class="pln"><span class="str"> :type: numpy.ndarray</span><span class="strut"> </span></p> +<p id="t206" class="pln"><span class="str"> :return: next longitudinal particle positions</span><span class="strut"> </span></p> +<p id="t207" class="pln"><span class="str"> :rtype: numpy.ndarray</span><span class="strut"> </span></p> +<p id="t208" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t209" class="pln"><span class="strut"> </span></p> +<p id="t210" class="pln"> <span class="com"># Initialize necessary calculations</span><span class="strut"> </span></p> +<p id="t211" class="stm run hide_run"> <span class="nam">longitudinal_position</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_particles</span><span class="op">.</span><span class="nam">position</span><span class="op">(</span><span class="op">)</span><span class="op">[</span><span class="op">:</span><span class="op">,</span> <span class="num">0</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t212" class="stm run hide_run"> <span class="nam">num_particles</span> <span class="op">=</span> <span class="nam">longitudinal_position</span><span class="op">.</span><span class="nam">shape</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t213" class="stm run hide_run"> <span class="nam">random_num</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_random_num</span><span class="op">(</span><span class="nam">num_particles</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t214" class="stm run hide_run"> <span class="nam">time_step</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_simulation_clock</span><span class="op">.</span><span class="nam">time_step_size</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t215" class="stm run hide_run"> <span class="nam">longitudinal_velocity</span> <span class="op">=</span> <span class="nam">hydraulic_results</span><span class="op">.</span><span class="nam">streamwise_velocity</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t216" class="stm run hide_run"> <span class="nam">depth</span> <span class="op">=</span> <span class="nam">hydraulic_results</span><span class="op">.</span><span class="nam">depth</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t217" class="stm run hide_run"> <span class="nam">shear_velocity</span> <span class="op">=</span> <span class="nam">hydraulic_results</span><span class="op">.</span><span class="nam">shear_velocity</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t218" class="stm run hide_run"> <span class="nam">turbulent_diffusion</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t219" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">_horizontal_turbulent_diffusion</span><span class="op">(</span><span class="nam">depth</span><span class="op">,</span> <span class="nam">shear_velocity</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t220" class="pln"><span class="strut"> </span></p> +<p id="t221" class="pln"> <span class="com"># Calculate incremented longitudinal positions</span><span class="strut"> </span></p> +<p id="t222" class="stm run hide_run"> <span class="nam">next_longitudinal_position</span> <span class="op">=</span> <span class="nam">longitudinal_position</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t223" class="pln"> <span class="op">+</span> <span class="nam">longitudinal_velocity</span> <span class="op">*</span> <span class="nam">time_step</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t224" class="pln"> <span class="op">+</span> <span class="nam">random_num</span> <span class="op">*</span> <span class="nam">np</span><span class="op">.</span><span class="nam">sqrt</span><span class="op">(</span><span class="num">2</span> <span class="op">*</span> <span class="nam">turbulent_diffusion</span> <span class="op">*</span> <span class="nam">time_step</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t225" class="pln"><span class="strut"> </span></p> +<p id="t226" class="stm run hide_run"> <span class="key">return</span> <span class="nam">next_longitudinal_position</span><span class="strut"> </span></p> +<p id="t227" class="pln"><span class="strut"> </span></p> +<p id="t228" class="stm run hide_run"> <span class="key">def</span> <span class="nam">increment_positions</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">hydraulic_results</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t229" class="pln"> <span class="str">"""Increments positions of particles according to current time step.</span><span class="strut"> </span></p> +<p id="t230" class="pln"><span class="strut"> </span></p> +<p id="t231" class="pln"><span class="str"> :param hydraulic_results: hydraulic results at current particle</span><span class="strut"> </span></p> +<p id="t232" class="pln"><span class="str"> positions</span><span class="strut"> </span></p> +<p id="t233" class="pln"><span class="str"> :type hydraulic_results: fluegg.hydraulics.HydraulicResults</span><span class="strut"> </span></p> +<p id="t234" class="pln"><span class="strut"> </span></p> +<p id="t235" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t236" class="pln"><span class="strut"> </span></p> +<p id="t237" class="stm run hide_run"> <span class="nam">next_longitudinal_positions</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t238" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">_next_longitudinal_positions</span><span class="op">(</span><span class="nam">hydraulic_results</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t239" class="pln"><span class="strut"> </span></p> +<p id="t240" class="stm run hide_run"> <span class="nam">positions</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_particles</span><span class="op">.</span><span class="nam">position</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t241" class="pln"><span class="strut"> </span></p> +<p id="t242" class="stm run hide_run"> <span class="nam">positions</span><span class="op">[</span><span class="op">:</span><span class="op">,</span> <span class="num">0</span><span class="op">]</span> <span class="op">=</span> <span class="nam">next_longitudinal_positions</span><span class="strut"> </span></p> +<p id="t243" class="pln"><span class="strut"> </span></p> +<p id="t244" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_particles</span><span class="op">.</span><span class="nam">set_position</span><span class="op">(</span><span class="nam">positions</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t245" class="pln"><span class="strut"> </span></p> +<p id="t246" class="pln"><span class="strut"> </span></p> +<p id="t247" class="stm run hide_run"><span class="key">class</span> <span class="nam">ReverseLongitudinalTransporter</span><span class="op">(</span><span class="nam">LongitudinalTransporter</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t248" class="pln"><span class="strut"> </span></p> +<p id="t249" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_get_next_longitudinal_positions</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">hydraulic_results</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t250" class="pln"> <span class="str">"""Returns incremented longitudinal particle positions</span><span class="strut"> </span></p> +<p id="t251" class="pln"><span class="strut"> </span></p> +<p id="t252" class="pln"><span class="str"> :param hydraulic_results: hydraulic results at current particle</span><span class="strut"> </span></p> +<p id="t253" class="pln"><span class="str"> positions</span><span class="strut"> </span></p> +<p id="t254" class="pln"><span class="str"> :type: numpy.ndarray</span><span class="strut"> </span></p> +<p id="t255" class="pln"><span class="str"> :return: next longitudinal particle positions</span><span class="strut"> </span></p> +<p id="t256" class="pln"><span class="str"> :rtype: numpy.ndarray</span><span class="strut"> </span></p> +<p id="t257" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t258" class="pln"><span class="strut"> </span></p> +<p id="t259" class="pln"> <span class="com"># Initialize necessary calculations</span><span class="strut"> </span></p> +<p id="t260" class="stm mis"> <span class="nam">longitudinal_position</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_particles</span><span class="op">.</span><span class="nam">get_position</span><span class="op">(</span><span class="op">)</span><span class="op">[</span><span class="op">:</span><span class="op">,</span> <span class="num">0</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t261" class="stm mis"> <span class="nam">num_particles</span> <span class="op">=</span> <span class="nam">longitudinal_position</span><span class="op">.</span><span class="nam">shape</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t262" class="stm mis"> <span class="nam">random_num</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_random_num</span><span class="op">(</span><span class="nam">num_particles</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t263" class="stm mis"> <span class="nam">time_step</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_simulation_clock</span><span class="op">.</span><span class="nam">get_time_step_size</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t264" class="stm mis"> <span class="nam">longitudinal_velocity</span> <span class="op">=</span> <span class="nam">hydraulic_results</span><span class="op">.</span><span class="nam">streamwise_velocity</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t265" class="stm mis"> <span class="nam">depth</span> <span class="op">=</span> <span class="nam">hydraulic_results</span><span class="op">.</span><span class="nam">depth</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t266" class="stm mis"> <span class="nam">shear_velocity</span> <span class="op">=</span> <span class="nam">hydraulic_results</span><span class="op">.</span><span class="nam">shear_velocity</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t267" class="stm mis"> <span class="nam">turbulent_diffusion</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t268" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">_horizontal_turbulent_diffusion</span><span class="op">(</span><span class="nam">depth</span><span class="op">,</span> <span class="nam">shear_velocity</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t269" class="pln"><span class="strut"> </span></p> +<p id="t270" class="pln"> <span class="com"># Reverse the advection direction</span><span class="strut"> </span></p> +<p id="t271" class="stm mis"> <span class="nam">reversal</span> <span class="op">=</span> <span class="op">-</span><span class="num">1</span><span class="strut"> </span></p> +<p id="t272" class="pln"><span class="strut"> </span></p> +<p id="t273" class="pln"> <span class="com"># Calculate incremented longitudinal positions</span><span class="strut"> </span></p> +<p id="t274" class="stm mis"> <span class="nam">next_longitudinal_position</span> <span class="op">=</span> <span class="nam">longitudinal_position</span> <span class="op">+</span> <span class="nam">reversal</span> <span class="op">*</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t275" class="pln"> <span class="nam">longitudinal_velocity</span> <span class="op">*</span> <span class="nam">time_step</span> <span class="op">+</span> <span class="nam">random_num</span> <span class="op">*</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t276" class="pln"> <span class="nam">np</span><span class="op">.</span><span class="nam">sqrt</span><span class="op">(</span><span class="num">2</span> <span class="op">*</span> <span class="nam">turbulent_diffusion</span> <span class="op">*</span> <span class="nam">time_step</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t277" class="pln"><span class="strut"> </span></p> +<p id="t278" class="stm mis"> <span class="key">return</span> <span class="nam">next_longitudinal_position</span><span class="strut"> </span></p> +<p id="t279" class="pln"><span class="strut"> </span></p> +<p id="t280" class="pln"><span class="strut"> </span></p> +<p id="t281" class="stm run hide_run"><span class="key">class</span> <span class="nam">VerticalTransporter</span><span class="op">(</span><span class="nam">Transporter</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t282" class="pln"><span class="strut"> </span></p> +<p id="t283" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_vertical_boundary_checks</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">hydraulic_results</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t284" class="pln"> <span class="nam">next_vertical_position</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t285" class="pln"> <span class="str">"""Checks whether positions are within the hydraulic boundary.</span><span class="strut"> </span></p> +<p id="t286" class="pln"><span class="str"> If not, returns the positions reflected on the boundary</span><span class="strut"> </span></p> +<p id="t287" class="pln"><span class="strut"> </span></p> +<p id="t288" class="pln"><span class="str"> :param hydraulic_results: hydraulic results at current particle</span><span class="strut"> </span></p> +<p id="t289" class="pln"><span class="str"> positions</span><span class="strut"> </span></p> +<p id="t290" class="pln"><span class="str"> :type: hydraulics.HydraulicResults</span><span class="strut"> </span></p> +<p id="t291" class="pln"><span class="str"> :param next_vertical_position: incremented vertical positions of</span><span class="strut"> </span></p> +<p id="t292" class="pln"><span class="str"> particles</span><span class="strut"> </span></p> +<p id="t293" class="pln"><span class="str"> :type: numpy.ndarray</span><span class="strut"> </span></p> +<p id="t294" class="pln"><span class="str"> :return: boundary-checked incremented position of a particle</span><span class="strut"> </span></p> +<p id="t295" class="pln"><span class="str"> :type: numpy.ndarray</span><span class="strut"> </span></p> +<p id="t296" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t297" class="pln"><span class="strut"> </span></p> +<p id="t298" class="pln"> <span class="com"># Check vertical position</span><span class="strut"> </span></p> +<p id="t299" class="stm run hide_run"> <span class="nam">depth</span> <span class="op">=</span> <span class="nam">hydraulic_results</span><span class="op">.</span><span class="nam">depth</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t300" class="pln"><span class="strut"> </span></p> +<p id="t301" class="stm run hide_run"> <span class="nam">diameter</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_particles</span><span class="op">.</span><span class="nam">diameter</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t302" class="pln"><span class="strut"> </span></p> +<p id="t303" class="stm run hide_run"> <span class="nam">boundary_length</span> <span class="op">=</span> <span class="nam">depth</span> <span class="op">-</span> <span class="nam">diameter</span><span class="strut"> </span></p> +<p id="t304" class="pln"><span class="strut"> </span></p> +<p id="t305" class="stm run hide_run"> <span class="nam">shifted_next_vertical_position</span> <span class="op">=</span> <span class="nam">next_vertical_position</span> <span class="op">+</span> <span class="nam">diameter</span><span class="op">/</span><span class="num">2</span><span class="strut"> </span></p> +<p id="t306" class="stm run hide_run"> <span class="nam">shifted_bottom_boundary_location</span> <span class="op">=</span> <span class="op">-</span><span class="nam">boundary_length</span><span class="strut"> </span></p> +<p id="t307" class="pln"><span class="strut"> </span></p> +<p id="t308" class="stm run hide_run"> <span class="nam">above_top_boundary</span> <span class="op">=</span> <span class="nam">shifted_next_vertical_position</span> <span class="op">></span> <span class="num">0</span><span class="strut"> </span></p> +<p id="t309" class="stm run hide_run"> <span class="nam">below_bottom_boundary</span> <span class="op">=</span> <span class="nam">shifted_next_vertical_position</span> <span class="op"><</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t310" class="pln"> <span class="nam">shifted_bottom_boundary_location</span><span class="strut"> </span></p> +<p id="t311" class="stm run hide_run"> <span class="nam">out_of_bounds</span> <span class="op">=</span> <span class="nam">above_top_boundary</span> <span class="op">|</span> <span class="nam">below_bottom_boundary</span><span class="strut"> </span></p> +<p id="t312" class="pln"><span class="strut"> </span></p> +<p id="t313" class="stm run hide_run"> <span class="key">if</span> <span class="nam">np</span><span class="op">.</span><span class="nam">any</span><span class="op">(</span><span class="nam">out_of_bounds</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t314" class="pln"><span class="strut"> </span></p> +<p id="t315" class="stm run hide_run"> <span class="nam">reflections</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">floor_divide</span><span class="op">(</span><span class="nam">shifted_next_vertical_position</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t316" class="pln"> <span class="nam">shifted_bottom_boundary_location</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t317" class="stm run hide_run"> <span class="nam">remainder</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">mod</span><span class="op">(</span><span class="nam">shifted_next_vertical_position</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t318" class="pln"> <span class="nam">shifted_bottom_boundary_location</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t319" class="pln"><span class="strut"> </span></p> +<p id="t320" class="stm run hide_run"> <span class="nam">reflection_mod_2</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">mod</span><span class="op">(</span><span class="nam">reflections</span><span class="op">,</span> <span class="num">2</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t321" class="stm run hide_run"> <span class="nam">odd_reflections</span> <span class="op">=</span> <span class="op">(</span><span class="nam">reflection_mod_2</span> <span class="op">==</span> <span class="num">1</span><span class="op">)</span> <span class="op">&</span> <span class="nam">out_of_bounds</span><span class="strut"> </span></p> +<p id="t322" class="stm run hide_run"> <span class="nam">even_reflections</span> <span class="op">=</span> <span class="op">(</span><span class="nam">reflection_mod_2</span> <span class="op">==</span> <span class="num">0</span><span class="op">)</span> <span class="op">&</span> <span class="nam">out_of_bounds</span><span class="strut"> </span></p> +<p id="t323" class="pln"><span class="strut"> </span></p> +<p id="t324" class="stm run hide_run"> <span class="nam">shifted_next_vertical_position</span><span class="op">[</span><span class="nam">even_reflections</span><span class="op">]</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t325" class="pln"> <span class="nam">remainder</span><span class="op">[</span><span class="nam">even_reflections</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t326" class="stm run hide_run"> <span class="nam">shifted_next_vertical_position</span><span class="op">[</span><span class="nam">odd_reflections</span><span class="op">]</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t327" class="pln"> <span class="op">-</span><span class="nam">boundary_length</span><span class="op">[</span><span class="nam">odd_reflections</span><span class="op">]</span> <span class="op">-</span> <span class="nam">remainder</span><span class="op">[</span><span class="nam">odd_reflections</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t328" class="pln"><span class="strut"> </span></p> +<p id="t329" class="stm run hide_run"> <span class="nam">next_vertical_position</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t330" class="pln"> <span class="nam">shifted_next_vertical_position</span> <span class="op">-</span> <span class="nam">diameter</span><span class="op">/</span><span class="num">2</span><span class="strut"> </span></p> +<p id="t331" class="pln"><span class="strut"> </span></p> +<p id="t332" class="stm run hide_run"> <span class="key">return</span> <span class="nam">next_vertical_position</span><span class="strut"> </span></p> +<p id="t333" class="pln"><span class="strut"> </span></p> +<p id="t334" class="stm run hide_run"> <span class="op">@</span><span class="nam">staticmethod</span><span class="strut"> </span></p> +<p id="t335" class="pln"> <span class="key">def</span> <span class="nam">_beta</span><span class="op">(</span><span class="nam">hydraulic_results</span><span class="op">,</span> <span class="nam">fall_velocity</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t336" class="pln"> <span class="str">"""Returns the factor beta used in calculation of the vertical</span><span class="strut"> </span></p> +<p id="t337" class="pln"><span class="str"> eddy diffusivity</span><span class="strut"> </span></p> +<p id="t338" class="pln"><span class="strut"> </span></p> +<p id="t339" class="pln"><span class="str"> :param hydraulic_results: hydraulic results at current particle</span><span class="strut"> </span></p> +<p id="t340" class="pln"><span class="str"> positions</span><span class="strut"> </span></p> +<p id="t341" class="pln"><span class="str"> :type: hydraulics.HydraulicResults</span><span class="strut"> </span></p> +<p id="t342" class="pln"><span class="str"> :param fall_velocity:</span><span class="strut"> </span></p> +<p id="t343" class="pln"><span class="str"> :type: numpy.ndarray</span><span class="strut"> </span></p> +<p id="t344" class="pln"><span class="str"> :return: beta factor for calculating eddy diffusivity</span><span class="strut"> </span></p> +<p id="t345" class="pln"><span class="str"> :rtype: numpy.ndarray</span><span class="strut"> </span></p> +<p id="t346" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t347" class="pln"> <span class="com"># Calculate beta coefficient</span><span class="strut"> </span></p> +<p id="t348" class="stm run hide_run"> <span class="nam">shear_velocity</span> <span class="op">=</span> <span class="nam">hydraulic_results</span><span class="op">.</span><span class="nam">shear_velocity</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t349" class="stm run hide_run"> <span class="nam">beta</span> <span class="op">=</span> <span class="num">1</span> <span class="op">+</span> <span class="num">2</span> <span class="op">*</span> <span class="op">(</span><span class="nam">np</span><span class="op">.</span><span class="nam">abs</span><span class="op">(</span><span class="op">(</span><span class="nam">fall_velocity</span> <span class="op">/</span> <span class="nam">shear_velocity</span><span class="op">)</span><span class="op">)</span> <span class="op">**</span> <span class="num">2</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t350" class="pln"><span class="strut"> </span></p> +<p id="t351" class="pln"> <span class="com"># set the values out of the function range to 3</span><span class="strut"> </span></p> +<p id="t352" class="stm run hide_run"> <span class="nam">out_of_range</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">abs</span><span class="op">(</span><span class="nam">fall_velocity</span><span class="op">)</span><span class="op">/</span><span class="nam">shear_velocity</span> <span class="op">></span> <span class="num">1</span><span class="strut"> </span></p> +<p id="t353" class="stm run hide_run"> <span class="nam">beta</span><span class="op">[</span><span class="nam">out_of_range</span><span class="op">]</span> <span class="op">=</span> <span class="num">3</span><span class="strut"> </span></p> +<p id="t354" class="pln"><span class="strut"> </span></p> +<p id="t355" class="stm run hide_run"> <span class="key">return</span> <span class="nam">beta</span><span class="strut"> </span></p> +<p id="t356" class="pln"><span class="strut"> </span></p> +<p id="t357" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_eddy_diffusivity_second_derivative</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">hydraulic_results</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t358" class="pln"> <span class="str">"""Returns the eddy diffusivity second derivative at the positions in</span><span class="strut"> </span></p> +<p id="t359" class="pln"><span class="str"> hydraulic_results</span><span class="strut"> </span></p> +<p id="t360" class="pln"><span class="strut"> </span></p> +<p id="t361" class="pln"><span class="str"> :param hydraulic_results: hydraulic results at current particle</span><span class="strut"> </span></p> +<p id="t362" class="pln"><span class="str"> positions</span><span class="strut"> </span></p> +<p id="t363" class="pln"><span class="str"> :type: hydraulics.HydraulicResults</span><span class="strut"> </span></p> +<p id="t364" class="pln"><span class="str"> :return: eddy diffusivity second derivative</span><span class="strut"> </span></p> +<p id="t365" class="pln"><span class="str"> :rtype: float</span><span class="strut"> </span></p> +<p id="t366" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t367" class="pln"><span class="strut"> </span></p> +<p id="t368" class="stm run hide_run"> <span class="nam">fall_velocity</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_particles</span><span class="op">.</span><span class="nam">fall_velocity</span><span class="op">(</span><span class="nam">hydraulic_results</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t369" class="stm run hide_run"> <span class="nam">beta</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_beta</span><span class="op">(</span><span class="nam">hydraulic_results</span><span class="op">,</span> <span class="nam">fall_velocity</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t370" class="stm run hide_run"> <span class="nam">second_derivative</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t371" class="pln"> <span class="nam">beta</span> <span class="op">*</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_eddy_viscosity_second_derivative</span><span class="op">(</span><span class="nam">hydraulic_results</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t372" class="pln"><span class="strut"> </span></p> +<p id="t373" class="stm run hide_run"> <span class="key">return</span> <span class="nam">second_derivative</span><span class="strut"> </span></p> +<p id="t374" class="pln"><span class="strut"> </span></p> +<p id="t375" class="stm run hide_run"> <span class="op">@</span><span class="nam">abstractmethod</span><span class="strut"> </span></p> +<p id="t376" class="pln"> <span class="key">def</span> <span class="nam">_eddy_viscosity</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">hydraulic_results</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t377" class="pln"> <span class="str">"""</span><span class="strut"> </span></p> +<p id="t378" class="pln"><span class="strut"> </span></p> +<p id="t379" class="pln"><span class="str"> :param hydraulic_results:</span><span class="strut"> </span></p> +<p id="t380" class="pln"><span class="str"> :return:</span><span class="strut"> </span></p> +<p id="t381" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t382" class="stm mis"> <span class="key">raise</span> <span class="nam">NotImplementedError</span><span class="strut"> </span></p> +<p id="t383" class="pln"><span class="strut"> </span></p> +<p id="t384" class="stm run hide_run"> <span class="op">@</span><span class="nam">abstractmethod</span><span class="strut"> </span></p> +<p id="t385" class="pln"> <span class="key">def</span> <span class="nam">_eddy_viscosity_gradient</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">hydraulic_results</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t386" class="pln"> <span class="str">"""</span><span class="strut"> </span></p> +<p id="t387" class="pln"><span class="strut"> </span></p> +<p id="t388" class="pln"><span class="str"> :param hydraulic_results:</span><span class="strut"> </span></p> +<p id="t389" class="pln"><span class="str"> :return:</span><span class="strut"> </span></p> +<p id="t390" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t391" class="stm mis"> <span class="key">raise</span> <span class="nam">NotImplementedError</span><span class="strut"> </span></p> +<p id="t392" class="pln"><span class="strut"> </span></p> +<p id="t393" class="stm run hide_run"> <span class="op">@</span><span class="nam">abstractmethod</span><span class="strut"> </span></p> +<p id="t394" class="pln"> <span class="key">def</span> <span class="nam">_eddy_viscosity_second_derivative</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">hydraulic_results</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t395" class="pln"> <span class="str">"""</span><span class="strut"> </span></p> +<p id="t396" class="pln"><span class="strut"> </span></p> +<p id="t397" class="pln"><span class="str"> :param hydraulic_results:</span><span class="strut"> </span></p> +<p id="t398" class="pln"><span class="str"> :return:</span><span class="strut"> </span></p> +<p id="t399" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t400" class="stm mis"> <span class="key">raise</span> <span class="nam">NotImplementedError</span><span class="strut"> </span></p> +<p id="t401" class="pln"><span class="strut"> </span></p> +<p id="t402" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_next_vertical_positions</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">hydraulic_results</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t403" class="pln"> <span class="str">"""Returns incremented vertical particle positions</span><span class="strut"> </span></p> +<p id="t404" class="pln"><span class="strut"> </span></p> +<p id="t405" class="pln"><span class="str"> :param hydraulic_results: hydraulic results at current particle</span><span class="strut"> </span></p> +<p id="t406" class="pln"><span class="str"> positions</span><span class="strut"> </span></p> +<p id="t407" class="pln"><span class="str"> :type: numpy.ndarray</span><span class="strut"> </span></p> +<p id="t408" class="pln"><span class="str"> :return: next vertical particle positions</span><span class="strut"> </span></p> +<p id="t409" class="pln"><span class="str"> :rtype: numpy.ndarray</span><span class="strut"> </span></p> +<p id="t410" class="pln"><span class="strut"> </span></p> +<p id="t411" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t412" class="pln"><span class="strut"> </span></p> +<p id="t413" class="pln"> <span class="com"># Initialize necessary variables for equation</span><span class="strut"> </span></p> +<p id="t414" class="stm run hide_run"> <span class="nam">positions</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_particles</span><span class="op">.</span><span class="nam">position</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t415" class="stm run hide_run"> <span class="nam">vertical_position</span> <span class="op">=</span> <span class="nam">positions</span><span class="op">[</span><span class="op">:</span><span class="op">,</span> <span class="num">2</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t416" class="stm run hide_run"> <span class="nam">num_particles</span> <span class="op">=</span> <span class="nam">positions</span><span class="op">.</span><span class="nam">shape</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t417" class="stm run hide_run"> <span class="nam">random_num</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_random_num</span><span class="op">(</span><span class="nam">num_particles</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t418" class="stm run hide_run"> <span class="nam">time_step_size</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_simulation_clock</span><span class="op">.</span><span class="nam">time_step_size</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t419" class="pln"><span class="strut"> </span></p> +<p id="t420" class="stm run hide_run"> <span class="nam">max_time_step</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">max_time_step</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t421" class="pln"><span class="strut"> </span></p> +<p id="t422" class="stm run hide_run"> <span class="key">if</span> <span class="op">(</span><span class="nam">max_time_step</span> <span class="op"><</span> <span class="nam">time_step_size</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t423" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="str">"Time step size is greater than maximum time "</span> <span class="op">+</span><span class="strut"> </span></p> +<p id="t424" class="pln"> <span class="str">"step of {}"</span><span class="op">.</span><span class="nam">format</span><span class="op">(</span><span class="nam">max_time_step</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t425" class="pln"><span class="strut"> </span></p> +<p id="t426" class="pln"> <span class="com"># Calculate fall velocity</span><span class="strut"> </span></p> +<p id="t427" class="stm run hide_run"> <span class="nam">fall_velocity</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_particles</span><span class="op">.</span><span class="nam">fall_velocity</span><span class="op">(</span><span class="nam">hydraulic_results</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t428" class="pln"><span class="strut"> </span></p> +<p id="t429" class="stm run hide_run"> <span class="nam">beta</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_beta</span><span class="op">(</span><span class="nam">hydraulic_results</span><span class="op">,</span> <span class="nam">fall_velocity</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t430" class="pln"><span class="strut"> </span></p> +<p id="t431" class="stm run hide_run"> <span class="nam">vertical_eddy_diffusivity_gradient</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t432" class="pln"> <span class="nam">beta</span> <span class="op">*</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_eddy_viscosity_gradient</span><span class="op">(</span><span class="nam">hydraulic_results</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t433" class="stm run hide_run"> <span class="nam">vertical_eddy_diffusivity</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t434" class="pln"> <span class="nam">beta</span> <span class="op">*</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_eddy_viscosity</span><span class="op">(</span><span class="nam">hydraulic_results</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t435" class="pln"><span class="strut"> </span></p> +<p id="t436" class="stm run hide_run"> <span class="nam">vertical_velocity</span> <span class="op">=</span> <span class="nam">hydraulic_results</span><span class="op">.</span><span class="nam">vertical_velocity</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t437" class="pln"><span class="strut"> </span></p> +<p id="t438" class="pln"> <span class="com"># Calculate the next step's vertical position</span><span class="strut"> </span></p> +<p id="t439" class="stm run hide_run"> <span class="nam">next_vertical_position</span> <span class="op">=</span> <span class="nam">vertical_position</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t440" class="pln"> <span class="op">+</span> <span class="nam">vertical_velocity</span> <span class="op">*</span> <span class="nam">time_step_size</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t441" class="pln"> <span class="op">+</span> <span class="nam">fall_velocity</span> <span class="op">*</span> <span class="nam">time_step_size</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t442" class="pln"> <span class="op">+</span> <span class="nam">vertical_eddy_diffusivity_gradient</span> <span class="op">*</span> <span class="nam">time_step_size</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t443" class="pln"> <span class="op">+</span> <span class="nam">random_num</span> <span class="op">*</span> <span class="nam">np</span><span class="op">.</span><span class="nam">sqrt</span><span class="op">(</span><span class="num">2</span> <span class="op">*</span> <span class="nam">vertical_eddy_diffusivity</span> <span class="op">*</span><span class="strut"> </span></p> +<p id="t444" class="pln"> <span class="nam">time_step_size</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t445" class="pln"><span class="strut"> </span></p> +<p id="t446" class="stm run hide_run"> <span class="key">return</span> <span class="nam">next_vertical_position</span><span class="strut"> </span></p> +<p id="t447" class="pln"><span class="strut"> </span></p> +<p id="t448" class="stm run hide_run"> <span class="key">def</span> <span class="nam">increment_positions</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">hydraulic_results</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t449" class="pln"> <span class="str">"""Increments positions of particles according to current time step.</span><span class="strut"> </span></p> +<p id="t450" class="pln"><span class="strut"> </span></p> +<p id="t451" class="pln"><span class="str"> :param hydraulic_results: hydraulic results at current particle</span><span class="strut"> </span></p> +<p id="t452" class="pln"><span class="str"> positions</span><span class="strut"> </span></p> +<p id="t453" class="pln"><span class="str"> :type hydraulic_results: fluegg.hydraulics.HydraulicResults</span><span class="strut"> </span></p> +<p id="t454" class="pln"><span class="strut"> </span></p> +<p id="t455" class="pln"><span class="str"> Raises</span><span class="strut"> </span></p> +<p id="t456" class="pln"><span class="str"> ------</span><span class="strut"> </span></p> +<p id="t457" class="pln"><span class="str"> ValueError</span><span class="strut"> </span></p> +<p id="t458" class="pln"><span class="str"> If the simulation clock time step is greater than the maximum time</span><span class="strut"> </span></p> +<p id="t459" class="pln"><span class="str"> step defined by self.max_time_step()</span><span class="strut"> </span></p> +<p id="t460" class="pln"><span class="strut"> </span></p> +<p id="t461" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t462" class="pln"><span class="strut"> </span></p> +<p id="t463" class="stm run hide_run"> <span class="nam">next_vertical_positions</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t464" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">_next_vertical_positions</span><span class="op">(</span><span class="nam">hydraulic_results</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t465" class="pln"><span class="strut"> </span></p> +<p id="t466" class="stm run hide_run"> <span class="nam">next_vertical_positions</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t467" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">_vertical_boundary_checks</span><span class="op">(</span><span class="nam">hydraulic_results</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t468" class="pln"> <span class="nam">next_vertical_positions</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t469" class="pln"><span class="strut"> </span></p> +<p id="t470" class="stm run hide_run"> <span class="nam">positions</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_particles</span><span class="op">.</span><span class="nam">position</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t471" class="pln"><span class="strut"> </span></p> +<p id="t472" class="stm run hide_run"> <span class="nam">positions</span><span class="op">[</span><span class="op">:</span><span class="op">,</span> <span class="num">2</span><span class="op">]</span> <span class="op">=</span> <span class="nam">next_vertical_positions</span><span class="strut"> </span></p> +<p id="t473" class="pln"><span class="strut"> </span></p> +<p id="t474" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_particles</span><span class="op">.</span><span class="nam">set_position</span><span class="op">(</span><span class="nam">positions</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t475" class="pln"><span class="strut"> </span></p> +<p id="t476" class="stm run hide_run"> <span class="key">def</span> <span class="nam">max_time_step</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t477" class="pln"> <span class="str">"""Finds the maximum time step required for an accurate simulation.</span><span class="strut"> </span></p> +<p id="t478" class="pln"><span class="strut"> </span></p> +<p id="t479" class="pln"><span class="str"> This is based on the the time step being <= 1/abs(vertical eddy</span><span class="strut"> </span></p> +<p id="t480" class="pln"><span class="str"> diffusivity second derivative)</span><span class="strut"> </span></p> +<p id="t481" class="pln"><span class="strut"> </span></p> +<p id="t482" class="pln"><span class="str"> :return: maximum time step criterion given the current time step</span><span class="strut"> </span></p> +<p id="t483" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t484" class="pln"><span class="strut"> </span></p> +<p id="t485" class="stm run hide_run"> <span class="nam">super</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">max_time_step</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t486" class="pln"><span class="strut"> </span></p> +<p id="t487" class="stm run hide_run"> <span class="nam">particle_positions</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_particles</span><span class="op">.</span><span class="nam">position</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t488" class="pln"><span class="strut"> </span></p> +<p id="t489" class="stm run hide_run"> <span class="nam">hydraulic_results</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t490" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">_hydraulic_model</span><span class="op">.</span><span class="nam">hydraulic_results</span><span class="op">(</span><span class="nam">particle_positions</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t491" class="stm run hide_run"> <span class="nam">criteria</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_eddy_diffusivity_second_derivative</span><span class="op">(</span><span class="nam">hydraulic_results</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t492" class="pln"><span class="strut"> </span></p> +<p id="t493" class="pln"> <span class="com"># Minimum inverse vertical eddy diffusivity second derivative is</span><span class="strut"> </span></p> +<p id="t494" class="pln"> <span class="com"># maximum time step</span><span class="strut"> </span></p> +<p id="t495" class="stm run hide_run"> <span class="nam">criteria</span> <span class="op">=</span> <span class="nam">criteria</span><span class="op">[</span><span class="nam">criteria</span> <span class="op">></span> <span class="num">0</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t496" class="stm run hide_run"> <span class="key">if</span> <span class="nam">len</span><span class="op">(</span><span class="nam">criteria</span> <span class="op">></span> <span class="num">0</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t497" class="stm mis"> <span class="nam">criteria</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">power</span><span class="op">(</span><span class="nam">criteria</span><span class="op">,</span> <span class="op">-</span><span class="num">1</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t498" class="stm mis"> <span class="nam">criteria</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">absolute</span><span class="op">(</span><span class="nam">criteria</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t499" class="stm mis"> <span class="nam">criterion</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">amin</span><span class="op">(</span><span class="nam">criteria</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t500" class="pln"> <span class="key">else</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t501" class="stm run hide_run"> <span class="nam">criterion</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">inf</span><span class="strut"> </span></p> +<p id="t502" class="pln"><span class="strut"> </span></p> +<p id="t503" class="stm run hide_run"> <span class="key">return</span> <span class="nam">criterion</span><span class="strut"> </span></p> +<p id="t504" class="pln"><span class="strut"> </span></p> +<p id="t505" class="pln"><span class="strut"> </span></p> +<p id="t506" class="stm run hide_run"><span class="key">class</span> <span class="nam">ConstantVerticalTransporter</span><span class="op">(</span><span class="nam">VerticalTransporter</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t507" class="pln"><span class="strut"> </span></p> +<p id="t508" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_eddy_viscosity</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">hydraulic_results</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t509" class="pln"> <span class="str">"""Returns the vertical eddy viscosity at the given position</span><span class="strut"> </span></p> +<p id="t510" class="pln"><span class="strut"> </span></p> +<p id="t511" class="pln"><span class="str"> :param hydraulic_results: hydraulic results at given particle positions</span><span class="strut"> </span></p> +<p id="t512" class="pln"><span class="str"> :type: hydraulics.HydraulicResults</span><span class="strut"> </span></p> +<p id="t513" class="pln"><span class="str"> :return: eddy viscosity</span><span class="strut"> </span></p> +<p id="t514" class="pln"><span class="str"> :rtype: float</span><span class="strut"> </span></p> +<p id="t515" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t516" class="pln"><span class="strut"> </span></p> +<p id="t517" class="pln"> <span class="com"># Initialize necessary information for calculation</span><span class="strut"> </span></p> +<p id="t518" class="stm run hide_run"> <span class="nam">depth</span> <span class="op">=</span> <span class="nam">hydraulic_results</span><span class="op">.</span><span class="nam">depth</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t519" class="stm run hide_run"> <span class="nam">shear_velocity</span> <span class="op">=</span> <span class="nam">hydraulic_results</span><span class="op">.</span><span class="nam">shear_velocity</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t520" class="pln"><span class="strut"> </span></p> +<p id="t521" class="pln"> <span class="com"># constant portion of profile</span><span class="strut"> </span></p> +<p id="t522" class="stm run hide_run"> <span class="nam">eddy_viscosity</span> <span class="op">=</span> <span class="num">1</span><span class="op">/</span><span class="num">15</span> <span class="op">*</span> <span class="nam">shear_velocity</span> <span class="op">*</span> <span class="nam">depth</span><span class="strut"> </span></p> +<p id="t523" class="pln"><span class="strut"> </span></p> +<p id="t524" class="pln"> <span class="com"># use fluid viscosity where eddy viscosity is less than the fluid</span><span class="strut"> </span></p> +<p id="t525" class="pln"> <span class="com"># viscosity</span><span class="strut"> </span></p> +<p id="t526" class="stm run hide_run"> <span class="nam">fluid_viscosity</span> <span class="op">=</span> <span class="nam">hydraulic_results</span><span class="op">.</span><span class="nam">water_viscosity</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t527" class="stm run hide_run"> <span class="nam">eddy_viscosity_lt_water_viscosity</span> <span class="op">=</span> <span class="nam">eddy_viscosity</span> <span class="op"><</span> <span class="nam">fluid_viscosity</span><span class="strut"> </span></p> +<p id="t528" class="stm run hide_run"> <span class="nam">eddy_viscosity</span><span class="op">[</span><span class="nam">eddy_viscosity_lt_water_viscosity</span><span class="op">]</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t529" class="pln"> <span class="nam">fluid_viscosity</span><span class="op">[</span><span class="nam">eddy_viscosity_lt_water_viscosity</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t530" class="pln"><span class="strut"> </span></p> +<p id="t531" class="stm run hide_run"> <span class="key">return</span> <span class="nam">eddy_viscosity</span><span class="strut"> </span></p> +<p id="t532" class="pln"><span class="strut"> </span></p> +<p id="t533" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_eddy_viscosity_gradient</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">hydraulic_results</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t534" class="pln"> <span class="str">"""Returns the eddy viscosity gradient with depth at the given position</span><span class="strut"> </span></p> +<p id="t535" class="pln"><span class="strut"> </span></p> +<p id="t536" class="pln"><span class="str"> :param hydraulic_results: hydraulic results at current particle</span><span class="strut"> </span></p> +<p id="t537" class="pln"><span class="str"> positions</span><span class="strut"> </span></p> +<p id="t538" class="pln"><span class="str"> :type: hydraulics.HydraulicResults</span><span class="strut"> </span></p> +<p id="t539" class="pln"><span class="str"> :return: eddy viscosity gradient m/s</span><span class="strut"> </span></p> +<p id="t540" class="pln"><span class="str"> :rtype: float</span><span class="strut"> </span></p> +<p id="t541" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t542" class="pln"><span class="strut"> </span></p> +<p id="t543" class="pln"> <span class="com"># Initialize necessary information for calculation</span><span class="strut"> </span></p> +<p id="t544" class="stm run hide_run"> <span class="nam">positions</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_particles</span><span class="op">.</span><span class="nam">position</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t545" class="stm run hide_run"> <span class="nam">num_particles</span> <span class="op">=</span> <span class="nam">positions</span><span class="op">.</span><span class="nam">shape</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t546" class="pln"> <span class="com"># Depending on profile, fill fluid eddy viscosity gradient array</span><span class="strut"> </span></p> +<p id="t547" class="stm run hide_run"> <span class="nam">eddy_viscosity_gradient</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">zeros</span><span class="op">(</span><span class="nam">num_particles</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t548" class="pln"><span class="strut"> </span></p> +<p id="t549" class="stm run hide_run"> <span class="key">return</span> <span class="nam">eddy_viscosity_gradient</span><span class="strut"> </span></p> +<p id="t550" class="pln"><span class="strut"> </span></p> +<p id="t551" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_eddy_viscosity_second_derivative</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">hydraulic_results</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t552" class="pln"> <span class="str">"""Returns the eddy viscosity second derivative with depth at the given</span><span class="strut"> </span></p> +<p id="t553" class="pln"><span class="str"> position</span><span class="strut"> </span></p> +<p id="t554" class="pln"><span class="strut"> </span></p> +<p id="t555" class="pln"><span class="str"> :param hydraulic_results: hydraulic results at current particle</span><span class="strut"> </span></p> +<p id="t556" class="pln"><span class="str"> positions</span><span class="strut"> </span></p> +<p id="t557" class="pln"><span class="str"> :type: hydraulics.HydraulicResults</span><span class="strut"> </span></p> +<p id="t558" class="pln"><span class="str"> :return: eddy viscosity second derivative m/s**2</span><span class="strut"> </span></p> +<p id="t559" class="pln"><span class="str"> :rtype: float</span><span class="strut"> </span></p> +<p id="t560" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t561" class="pln"><span class="strut"> </span></p> +<p id="t562" class="pln"> <span class="com"># Initialize necessary information for calculation</span><span class="strut"> </span></p> +<p id="t563" class="stm run hide_run"> <span class="nam">positions</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_particles</span><span class="op">.</span><span class="nam">position</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t564" class="stm run hide_run"> <span class="nam">num_particles</span> <span class="op">=</span> <span class="nam">positions</span><span class="op">.</span><span class="nam">shape</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t565" class="pln"> <span class="com"># Depending on profile, fill fluid eddy viscosity gradient array</span><span class="strut"> </span></p> +<p id="t566" class="stm run hide_run"> <span class="nam">eddy_viscosity_second_derivative</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">zeros</span><span class="op">(</span><span class="nam">num_particles</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t567" class="pln"><span class="strut"> </span></p> +<p id="t568" class="stm run hide_run"> <span class="key">return</span> <span class="nam">eddy_viscosity_second_derivative</span><span class="strut"> </span></p> +<p id="t569" class="pln"><span class="strut"> </span></p> +<p id="t570" class="pln"><span class="strut"> </span></p> +<p id="t571" class="stm run hide_run"><span class="key">class</span> <span class="nam">ParabolicVerticalTransporter</span><span class="op">(</span><span class="nam">VerticalTransporter</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t572" class="pln"><span class="strut"> </span></p> +<p id="t573" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_eddy_viscosity</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">hydraulic_results</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t574" class="pln"> <span class="str">"""Returns the vertical eddy viscosity at the given position</span><span class="strut"> </span></p> +<p id="t575" class="pln"><span class="strut"> </span></p> +<p id="t576" class="pln"><span class="str"> :param hydraulic_results: hydraulic results at given particle positions</span><span class="strut"> </span></p> +<p id="t577" class="pln"><span class="str"> :type: hydraulics.HydraulicResults</span><span class="strut"> </span></p> +<p id="t578" class="pln"><span class="str"> :return: eddy viscosity</span><span class="strut"> </span></p> +<p id="t579" class="pln"><span class="str"> :rtype: float</span><span class="strut"> </span></p> +<p id="t580" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t581" class="pln"><span class="strut"> </span></p> +<p id="t582" class="pln"> <span class="com"># Initialize necessary information for calculation</span><span class="strut"> </span></p> +<p id="t583" class="stm mis"> <span class="nam">positions</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_particles</span><span class="op">.</span><span class="nam">position</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t584" class="stm mis"> <span class="nam">vertical_position</span> <span class="op">=</span> <span class="nam">positions</span><span class="op">[</span><span class="op">:</span><span class="op">,</span> <span class="num">2</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t585" class="stm mis"> <span class="nam">depth</span> <span class="op">=</span> <span class="nam">hydraulic_results</span><span class="op">.</span><span class="nam">depth</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t586" class="stm mis"> <span class="nam">shear_velocity</span> <span class="op">=</span> <span class="nam">hydraulic_results</span><span class="op">.</span><span class="nam">shear_velocity</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t587" class="pln"><span class="strut"> </span></p> +<p id="t588" class="stm mis"> <span class="nam">distance_above_bed</span> <span class="op">=</span> <span class="nam">depth</span> <span class="op">+</span> <span class="nam">vertical_position</span><span class="strut"> </span></p> +<p id="t589" class="pln"><span class="strut"> </span></p> +<p id="t590" class="pln"> <span class="com"># parabolic portion of profile</span><span class="strut"> </span></p> +<p id="t591" class="stm mis"> <span class="nam">time_step_size</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_simulation_clock</span><span class="op">.</span><span class="nam">time_step_size</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t592" class="stm mis"> <span class="nam">eddy_viscosity_gradient</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t593" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">_eddy_viscosity_gradient</span><span class="op">(</span><span class="nam">hydraulic_results</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t594" class="pln"><span class="strut"> </span></p> +<p id="t595" class="stm mis"> <span class="nam">offset_distance</span> <span class="op">=</span> <span class="num">0.5</span> <span class="op">*</span> <span class="nam">eddy_viscosity_gradient</span> <span class="op">*</span> <span class="nam">time_step_size</span><span class="strut"> </span></p> +<p id="t596" class="stm mis"> <span class="nam">distance_above_bed_offset</span> <span class="op">=</span> <span class="nam">distance_above_bed</span> <span class="op">+</span> <span class="nam">offset_distance</span><span class="strut"> </span></p> +<p id="t597" class="stm mis"> <span class="nam">eddy_viscosity</span> <span class="op">=</span> <span class="nam">hydraulics</span><span class="op">.</span><span class="nam">VON_KARMAN_CONSTANT</span> <span class="op">*</span> <span class="nam">shear_velocity</span> <span class="op">*</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t598" class="pln"> <span class="nam">distance_above_bed_offset</span> <span class="op">*</span> <span class="op">(</span><span class="num">1</span> <span class="op">-</span> <span class="nam">distance_above_bed_offset</span> <span class="op">/</span> <span class="nam">depth</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t599" class="pln"><span class="strut"> </span></p> +<p id="t600" class="pln"> <span class="com"># use fluid viscosity where eddy viscosity is less than the fluid</span><span class="strut"> </span></p> +<p id="t601" class="pln"> <span class="com"># viscosity</span><span class="strut"> </span></p> +<p id="t602" class="stm mis"> <span class="nam">fluid_viscosity</span> <span class="op">=</span> <span class="nam">hydraulic_results</span><span class="op">.</span><span class="nam">water_viscosity</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t603" class="stm mis"> <span class="nam">eddy_viscosity_lt_water_viscosity</span> <span class="op">=</span> <span class="nam">eddy_viscosity</span> <span class="op"><</span> <span class="nam">fluid_viscosity</span><span class="strut"> </span></p> +<p id="t604" class="stm mis"> <span class="nam">eddy_viscosity</span><span class="op">[</span><span class="nam">eddy_viscosity_lt_water_viscosity</span><span class="op">]</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t605" class="pln"> <span class="nam">fluid_viscosity</span><span class="op">[</span><span class="nam">eddy_viscosity_lt_water_viscosity</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t606" class="pln"><span class="strut"> </span></p> +<p id="t607" class="stm mis"> <span class="key">return</span> <span class="nam">eddy_viscosity</span><span class="strut"> </span></p> +<p id="t608" class="pln"><span class="strut"> </span></p> +<p id="t609" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_eddy_viscosity_gradient</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">hydraulic_results</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t610" class="pln"> <span class="str">"""Returns the eddy viscosity gradient with depth at the given position</span><span class="strut"> </span></p> +<p id="t611" class="pln"><span class="strut"> </span></p> +<p id="t612" class="pln"><span class="str"> :param hydraulic_results: hydraulic results at current particle</span><span class="strut"> </span></p> +<p id="t613" class="pln"><span class="str"> positions</span><span class="strut"> </span></p> +<p id="t614" class="pln"><span class="str"> :type: hydraulics.HydraulicResults</span><span class="strut"> </span></p> +<p id="t615" class="pln"><span class="str"> :return: eddy viscosity gradient m/s</span><span class="strut"> </span></p> +<p id="t616" class="pln"><span class="str"> :rtype: float</span><span class="strut"> </span></p> +<p id="t617" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t618" class="pln"><span class="strut"> </span></p> +<p id="t619" class="pln"> <span class="com"># Initialize necessary information for calculation</span><span class="strut"> </span></p> +<p id="t620" class="stm mis"> <span class="nam">positions</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_particles</span><span class="op">.</span><span class="nam">position</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t621" class="stm mis"> <span class="nam">vertical_position</span> <span class="op">=</span> <span class="nam">positions</span><span class="op">[</span><span class="op">:</span><span class="op">,</span> <span class="num">2</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t622" class="stm mis"> <span class="nam">depth</span> <span class="op">=</span> <span class="nam">hydraulic_results</span><span class="op">.</span><span class="nam">depth</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t623" class="stm mis"> <span class="nam">shear_velocity</span> <span class="op">=</span> <span class="nam">hydraulic_results</span><span class="op">.</span><span class="nam">shear_velocity</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t624" class="pln"><span class="strut"> </span></p> +<p id="t625" class="stm mis"> <span class="nam">distance_above_bed</span> <span class="op">=</span> <span class="nam">vertical_position</span> <span class="op">+</span> <span class="nam">depth</span><span class="strut"> </span></p> +<p id="t626" class="pln"><span class="strut"> </span></p> +<p id="t627" class="stm mis"> <span class="nam">eddy_viscosity_gradient</span> <span class="op">=</span> <span class="nam">hydraulics</span><span class="op">.</span><span class="nam">VON_KARMAN_CONSTANT</span> <span class="op">*</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t628" class="pln"> <span class="nam">shear_velocity</span> <span class="op">*</span> <span class="op">(</span><span class="num">1</span> <span class="op">-</span> <span class="num">2</span><span class="op">*</span><span class="nam">distance_above_bed</span><span class="op">/</span><span class="nam">depth</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t629" class="pln"><span class="strut"> </span></p> +<p id="t630" class="stm mis"> <span class="key">return</span> <span class="nam">eddy_viscosity_gradient</span><span class="strut"> </span></p> +<p id="t631" class="pln"><span class="strut"> </span></p> +<p id="t632" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_eddy_viscosity_second_derivative</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">hydraulic_results</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t633" class="pln"> <span class="str">"""Returns the eddy viscosity second derivative with depth at the given</span><span class="strut"> </span></p> +<p id="t634" class="pln"><span class="str"> position</span><span class="strut"> </span></p> +<p id="t635" class="pln"><span class="strut"> </span></p> +<p id="t636" class="pln"><span class="str"> :param hydraulic_results: hydraulic results at current particle</span><span class="strut"> </span></p> +<p id="t637" class="pln"><span class="str"> positions</span><span class="strut"> </span></p> +<p id="t638" class="pln"><span class="str"> :type: hydraulics.HydraulicResults</span><span class="strut"> </span></p> +<p id="t639" class="pln"><span class="str"> :return: eddy viscosity second derivative m/s**2</span><span class="strut"> </span></p> +<p id="t640" class="pln"><span class="str"> :rtype: float</span><span class="strut"> </span></p> +<p id="t641" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t642" class="pln"><span class="strut"> </span></p> +<p id="t643" class="pln"> <span class="com"># Initialize necessary information for calculation</span><span class="strut"> </span></p> +<p id="t644" class="stm mis"> <span class="nam">depth</span> <span class="op">=</span> <span class="nam">hydraulic_results</span><span class="op">.</span><span class="nam">depth</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t645" class="stm mis"> <span class="nam">shear_velocity</span> <span class="op">=</span> <span class="nam">hydraulic_results</span><span class="op">.</span><span class="nam">shear_velocity</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t646" class="pln"><span class="strut"> </span></p> +<p id="t647" class="stm mis"> <span class="nam">eddy_viscosity_second_derivative</span> <span class="op">=</span> <span class="op">-</span> <span class="nam">hydraulics</span><span class="op">.</span><span class="nam">VON_KARMAN_CONSTANT</span> <span class="op">*</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t648" class="pln"> <span class="nam">shear_velocity</span> <span class="op">*</span> <span class="num">2</span> <span class="op">/</span> <span class="nam">depth</span><span class="strut"> </span></p> +<p id="t649" class="pln"><span class="strut"> </span></p> +<p id="t650" class="stm mis"> <span class="key">return</span> <span class="nam">eddy_viscosity_second_derivative</span><span class="strut"> </span></p> +<p id="t651" class="pln"><span class="strut"> </span></p> +<p id="t652" class="pln"><span class="strut"> </span></p> +<p id="t653" class="stm run hide_run"><span class="key">class</span> <span class="nam">ParabolicConstantVerticalTransporter</span><span class="op">(</span><span class="nam">VerticalTransporter</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t654" class="pln"><span class="strut"> </span></p> +<p id="t655" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_eddy_viscosity</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">hydraulic_results</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t656" class="pln"> <span class="str">"""Returns the vertical eddy viscosity at the given position</span><span class="strut"> </span></p> +<p id="t657" class="pln"><span class="strut"> </span></p> +<p id="t658" class="pln"><span class="str"> :param hydraulic_results: hydraulic results at given particle positions</span><span class="strut"> </span></p> +<p id="t659" class="pln"><span class="str"> :type: hydraulics.HydraulicResults</span><span class="strut"> </span></p> +<p id="t660" class="pln"><span class="str"> :return: eddy viscosity</span><span class="strut"> </span></p> +<p id="t661" class="pln"><span class="str"> :rtype: float</span><span class="strut"> </span></p> +<p id="t662" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t663" class="pln"><span class="strut"> </span></p> +<p id="t664" class="pln"> <span class="com"># Initialize necessary information for calculation</span><span class="strut"> </span></p> +<p id="t665" class="stm run hide_run"> <span class="nam">positions</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_particles</span><span class="op">.</span><span class="nam">position</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t666" class="stm run hide_run"> <span class="nam">vertical_position</span> <span class="op">=</span> <span class="nam">positions</span><span class="op">[</span><span class="op">:</span><span class="op">,</span> <span class="num">2</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t667" class="stm run hide_run"> <span class="nam">num_particles</span> <span class="op">=</span> <span class="nam">positions</span><span class="op">.</span><span class="nam">shape</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t668" class="stm run hide_run"> <span class="nam">depth</span> <span class="op">=</span> <span class="nam">hydraulic_results</span><span class="op">.</span><span class="nam">depth</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t669" class="stm run hide_run"> <span class="nam">shear_velocity</span> <span class="op">=</span> <span class="nam">hydraulic_results</span><span class="op">.</span><span class="nam">shear_velocity</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t670" class="pln"><span class="strut"> </span></p> +<p id="t671" class="stm run hide_run"> <span class="nam">distance_above_bed</span> <span class="op">=</span> <span class="nam">depth</span> <span class="op">+</span> <span class="nam">vertical_position</span><span class="strut"> </span></p> +<p id="t672" class="pln"><span class="strut"> </span></p> +<p id="t673" class="stm run hide_run"> <span class="nam">eddy_viscosity</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">zeros</span><span class="op">(</span><span class="nam">num_particles</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t674" class="pln"><span class="strut"> </span></p> +<p id="t675" class="pln"> <span class="com"># constant portion of profile</span><span class="strut"> </span></p> +<p id="t676" class="stm run hide_run"> <span class="nam">constant</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">where</span><span class="op">(</span><span class="nam">distance_above_bed</span> <span class="op">/</span> <span class="nam">depth</span> <span class="op">>=</span> <span class="num">0.5</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t677" class="stm run hide_run"> <span class="nam">eddy_viscosity</span><span class="op">[</span><span class="nam">constant</span><span class="op">]</span> <span class="op">=</span> <span class="num">0.25</span> <span class="op">*</span> <span class="nam">hydraulics</span><span class="op">.</span><span class="nam">VON_KARMAN_CONSTANT</span> <span class="op">*</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t678" class="pln"> <span class="nam">shear_velocity</span><span class="op">[</span><span class="nam">constant</span><span class="op">]</span> <span class="op">*</span> <span class="nam">depth</span><span class="op">[</span><span class="nam">constant</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t679" class="pln"><span class="strut"> </span></p> +<p id="t680" class="pln"> <span class="com"># parabolic portion of profile</span><span class="strut"> </span></p> +<p id="t681" class="stm run hide_run"> <span class="nam">parabolic</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">where</span><span class="op">(</span><span class="nam">distance_above_bed</span> <span class="op">/</span> <span class="nam">depth</span> <span class="op"><</span> <span class="num">0.5</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t682" class="stm run hide_run"> <span class="nam">time_step_size</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_simulation_clock</span><span class="op">.</span><span class="nam">time_step_size</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t683" class="stm run hide_run"> <span class="nam">eddy_viscosity_gradient</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t684" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">_eddy_viscosity_gradient</span><span class="op">(</span><span class="nam">hydraulic_results</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t685" class="pln"><span class="strut"> </span></p> +<p id="t686" class="stm run hide_run"> <span class="nam">offset_distance</span> <span class="op">=</span> <span class="num">0.5</span> <span class="op">*</span> <span class="nam">eddy_viscosity_gradient</span> <span class="op">*</span> <span class="nam">time_step_size</span><span class="strut"> </span></p> +<p id="t687" class="stm run hide_run"> <span class="nam">distance_above_bed_offset</span> <span class="op">=</span> <span class="nam">distance_above_bed</span> <span class="op">+</span> <span class="nam">offset_distance</span><span class="strut"> </span></p> +<p id="t688" class="stm run hide_run"> <span class="nam">eddy_viscosity</span><span class="op">[</span><span class="nam">parabolic</span><span class="op">]</span> <span class="op">=</span> <span class="nam">hydraulics</span><span class="op">.</span><span class="nam">VON_KARMAN_CONSTANT</span> <span class="op">*</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t689" class="pln"> <span class="nam">shear_velocity</span><span class="op">[</span><span class="nam">parabolic</span><span class="op">]</span> <span class="op">*</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t690" class="pln"> <span class="nam">distance_above_bed_offset</span><span class="op">[</span><span class="nam">parabolic</span><span class="op">]</span> <span class="op">*</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t691" class="pln"> <span class="op">(</span><span class="num">1</span> <span class="op">-</span> <span class="nam">distance_above_bed_offset</span><span class="op">[</span><span class="nam">parabolic</span><span class="op">]</span> <span class="op">/</span> <span class="nam">depth</span><span class="op">[</span><span class="nam">parabolic</span><span class="op">]</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t692" class="pln"><span class="strut"> </span></p> +<p id="t693" class="pln"> <span class="com"># use fluid viscosity where eddy viscosity is less than the fluid</span><span class="strut"> </span></p> +<p id="t694" class="pln"> <span class="com"># viscosity</span><span class="strut"> </span></p> +<p id="t695" class="stm run hide_run"> <span class="nam">fluid_viscosity</span> <span class="op">=</span> <span class="nam">hydraulic_results</span><span class="op">.</span><span class="nam">water_viscosity</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t696" class="stm run hide_run"> <span class="nam">eddy_viscosity_lt_water_viscosity</span> <span class="op">=</span> <span class="nam">eddy_viscosity</span> <span class="op"><</span> <span class="nam">fluid_viscosity</span><span class="strut"> </span></p> +<p id="t697" class="stm run hide_run"> <span class="nam">eddy_viscosity</span><span class="op">[</span><span class="nam">eddy_viscosity_lt_water_viscosity</span><span class="op">]</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t698" class="pln"> <span class="nam">fluid_viscosity</span><span class="op">[</span><span class="nam">eddy_viscosity_lt_water_viscosity</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t699" class="pln"><span class="strut"> </span></p> +<p id="t700" class="stm run hide_run"> <span class="key">return</span> <span class="nam">eddy_viscosity</span><span class="strut"> </span></p> +<p id="t701" class="pln"><span class="strut"> </span></p> +<p id="t702" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_eddy_viscosity_gradient</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">hydraulic_results</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t703" class="pln"> <span class="str">"""Returns the eddy viscosity gradient with depth at the given position</span><span class="strut"> </span></p> +<p id="t704" class="pln"><span class="strut"> </span></p> +<p id="t705" class="pln"><span class="str"> :param hydraulic_results: hydraulic results at current particle</span><span class="strut"> </span></p> +<p id="t706" class="pln"><span class="str"> positions</span><span class="strut"> </span></p> +<p id="t707" class="pln"><span class="str"> :type: hydraulics.HydraulicResults</span><span class="strut"> </span></p> +<p id="t708" class="pln"><span class="str"> :return: eddy viscosity gradient m/s</span><span class="strut"> </span></p> +<p id="t709" class="pln"><span class="str"> :rtype: float</span><span class="strut"> </span></p> +<p id="t710" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t711" class="pln"><span class="strut"> </span></p> +<p id="t712" class="pln"> <span class="com"># Initialize necessary information for calculation</span><span class="strut"> </span></p> +<p id="t713" class="stm run hide_run"> <span class="nam">positions</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_particles</span><span class="op">.</span><span class="nam">position</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t714" class="stm run hide_run"> <span class="nam">vertical_position</span> <span class="op">=</span> <span class="nam">positions</span><span class="op">[</span><span class="op">:</span><span class="op">,</span> <span class="num">2</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t715" class="stm run hide_run"> <span class="nam">num_particles</span> <span class="op">=</span> <span class="nam">positions</span><span class="op">.</span><span class="nam">shape</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t716" class="stm run hide_run"> <span class="nam">depth</span> <span class="op">=</span> <span class="nam">hydraulic_results</span><span class="op">.</span><span class="nam">depth</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t717" class="stm run hide_run"> <span class="nam">shear_velocity</span> <span class="op">=</span> <span class="nam">hydraulic_results</span><span class="op">.</span><span class="nam">shear_velocity</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t718" class="pln"><span class="strut"> </span></p> +<p id="t719" class="stm run hide_run"> <span class="nam">distance_above_bed</span> <span class="op">=</span> <span class="nam">vertical_position</span> <span class="op">+</span> <span class="nam">depth</span><span class="strut"> </span></p> +<p id="t720" class="pln"><span class="strut"> </span></p> +<p id="t721" class="pln"> <span class="com"># Depending on profile, fill fluid eddy viscosity gradient array</span><span class="strut"> </span></p> +<p id="t722" class="stm run hide_run"> <span class="nam">eddy_viscosity_gradient</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">zeros</span><span class="op">(</span><span class="nam">num_particles</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t723" class="pln"><span class="strut"> </span></p> +<p id="t724" class="stm run hide_run"> <span class="nam">constant</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">where</span><span class="op">(</span><span class="nam">distance_above_bed</span><span class="op">/</span><span class="nam">depth</span> <span class="op">>=</span> <span class="num">0.5</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t725" class="stm run hide_run"> <span class="nam">eddy_viscosity_gradient</span><span class="op">[</span><span class="nam">constant</span><span class="op">]</span> <span class="op">=</span> <span class="num">0.0</span><span class="strut"> </span></p> +<p id="t726" class="pln"><span class="strut"> </span></p> +<p id="t727" class="stm run hide_run"> <span class="nam">parabolic</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">where</span><span class="op">(</span><span class="nam">distance_above_bed</span><span class="op">/</span><span class="nam">depth</span> <span class="op"><</span> <span class="num">0.5</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t728" class="stm run hide_run"> <span class="nam">eddy_viscosity_gradient</span><span class="op">[</span><span class="nam">parabolic</span><span class="op">]</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t729" class="pln"> <span class="nam">hydraulics</span><span class="op">.</span><span class="nam">VON_KARMAN_CONSTANT</span> <span class="op">*</span> <span class="nam">shear_velocity</span><span class="op">[</span><span class="nam">parabolic</span><span class="op">]</span> <span class="op">*</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t730" class="pln"> <span class="op">(</span><span class="num">1</span> <span class="op">-</span> <span class="num">2</span><span class="op">*</span><span class="nam">distance_above_bed</span><span class="op">[</span><span class="nam">parabolic</span><span class="op">]</span><span class="op">/</span><span class="nam">depth</span><span class="op">[</span><span class="nam">parabolic</span><span class="op">]</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t731" class="pln"><span class="strut"> </span></p> +<p id="t732" class="stm run hide_run"> <span class="key">return</span> <span class="nam">eddy_viscosity_gradient</span><span class="strut"> </span></p> +<p id="t733" class="pln"><span class="strut"> </span></p> +<p id="t734" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_eddy_viscosity_second_derivative</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">hydraulic_results</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t735" class="pln"> <span class="str">"""Returns the eddy viscosity second derivative with depth at the given</span><span class="strut"> </span></p> +<p id="t736" class="pln"><span class="str"> position</span><span class="strut"> </span></p> +<p id="t737" class="pln"><span class="strut"> </span></p> +<p id="t738" class="pln"><span class="str"> :param hydraulic_results: hydraulic results at current particle</span><span class="strut"> </span></p> +<p id="t739" class="pln"><span class="str"> positions</span><span class="strut"> </span></p> +<p id="t740" class="pln"><span class="str"> :type: hydraulics.HydraulicResults</span><span class="strut"> </span></p> +<p id="t741" class="pln"><span class="str"> :return: eddy viscosity second derivative m/s**2</span><span class="strut"> </span></p> +<p id="t742" class="pln"><span class="str"> :rtype: float</span><span class="strut"> </span></p> +<p id="t743" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t744" class="pln"><span class="strut"> </span></p> +<p id="t745" class="pln"> <span class="com"># Initialize necessary information for calculation</span><span class="strut"> </span></p> +<p id="t746" class="stm run hide_run"> <span class="nam">positions</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_particles</span><span class="op">.</span><span class="nam">position</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t747" class="stm run hide_run"> <span class="nam">vertical_position</span> <span class="op">=</span> <span class="nam">positions</span><span class="op">[</span><span class="op">:</span><span class="op">,</span> <span class="num">2</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t748" class="stm run hide_run"> <span class="nam">num_particles</span> <span class="op">=</span> <span class="nam">positions</span><span class="op">.</span><span class="nam">shape</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t749" class="stm run hide_run"> <span class="nam">depth</span> <span class="op">=</span> <span class="nam">hydraulic_results</span><span class="op">.</span><span class="nam">depth</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t750" class="stm run hide_run"> <span class="nam">shear_velocity</span> <span class="op">=</span> <span class="nam">hydraulic_results</span><span class="op">.</span><span class="nam">shear_velocity</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t751" class="pln"><span class="strut"> </span></p> +<p id="t752" class="stm run hide_run"> <span class="nam">distance_above_bed</span> <span class="op">=</span> <span class="nam">vertical_position</span> <span class="op">+</span> <span class="nam">depth</span><span class="strut"> </span></p> +<p id="t753" class="pln"><span class="strut"> </span></p> +<p id="t754" class="pln"> <span class="com"># Depending on profile, fill fluid eddy viscosity gradient array</span><span class="strut"> </span></p> +<p id="t755" class="stm run hide_run"> <span class="nam">eddy_viscosity_second_derivative</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">zeros</span><span class="op">(</span><span class="nam">num_particles</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t756" class="pln"><span class="strut"> </span></p> +<p id="t757" class="stm run hide_run"> <span class="nam">constant</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">where</span><span class="op">(</span><span class="nam">distance_above_bed</span> <span class="op">/</span> <span class="nam">depth</span> <span class="op">>=</span> <span class="num">0.5</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t758" class="stm run hide_run"> <span class="nam">eddy_viscosity_second_derivative</span><span class="op">[</span><span class="nam">constant</span><span class="op">]</span> <span class="op">=</span> <span class="num">0.0</span><span class="strut"> </span></p> +<p id="t759" class="pln"><span class="strut"> </span></p> +<p id="t760" class="stm run hide_run"> <span class="nam">parabolic</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">where</span><span class="op">(</span><span class="nam">distance_above_bed</span> <span class="op">/</span> <span class="nam">depth</span> <span class="op"><</span> <span class="num">0.5</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t761" class="stm run hide_run"> <span class="nam">eddy_viscosity_second_derivative</span><span class="op">[</span><span class="nam">parabolic</span><span class="op">]</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t762" class="pln"> <span class="op">-</span> <span class="nam">hydraulics</span><span class="op">.</span><span class="nam">VON_KARMAN_CONSTANT</span> <span class="op">*</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t763" class="pln"> <span class="nam">shear_velocity</span><span class="op">[</span><span class="nam">parabolic</span><span class="op">]</span> <span class="op">*</span> <span class="num">2</span> <span class="op">/</span> <span class="nam">depth</span><span class="op">[</span><span class="nam">parabolic</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t764" class="pln"><span class="strut"> </span></p> +<p id="t765" class="stm run hide_run"> <span class="key">return</span> <span class="nam">eddy_viscosity_second_derivative</span><span class="strut"> </span></p> +<p id="t766" class="pln"><span class="strut"> </span></p> +<p id="t767" class="pln"><span class="strut"> </span></p> +<p id="t768" class="stm run hide_run"><span class="key">def</span> <span class="nam">fluegg_transporter_class_factory</span><span class="op">(</span><span class="nam">vertical_turbulence</span><span class="op">=</span><span class="str">'parabolic-constant'</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t769" class="pln"> <span class="nam">advection_direction</span><span class="op">=</span><span class="str">'forward'</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t770" class="pln"> <span class="str">"""</span><span class="strut"> </span></p> +<p id="t771" class="pln"><span class="strut"> </span></p> +<p id="t772" class="pln"><span class="str"> :param vertical_turbulence:</span><span class="strut"> </span></p> +<p id="t773" class="pln"><span class="str"> :param advection_direction:</span><span class="strut"> </span></p> +<p id="t774" class="pln"><span class="str"> :return: class</span><span class="strut"> </span></p> +<p id="t775" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t776" class="pln"><span class="strut"> </span></p> +<p id="t777" class="stm run hide_run"> <span class="key">if</span> <span class="nam">vertical_turbulence</span> <span class="op">==</span> <span class="str">'constant'</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t778" class="stm mis"> <span class="nam">vertical_base_class</span> <span class="op">=</span> <span class="nam">ConstantVerticalTransporter</span><span class="strut"> </span></p> +<p id="t779" class="stm run hide_run"> <span class="key">elif</span> <span class="nam">vertical_turbulence</span> <span class="op">==</span> <span class="str">'parabolic'</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t780" class="stm mis"> <span class="nam">vertical_base_class</span> <span class="op">=</span> <span class="nam">ParabolicVerticalTransporter</span><span class="strut"> </span></p> +<p id="t781" class="stm run hide_run"> <span class="key">elif</span> <span class="nam">vertical_turbulence</span> <span class="op">==</span> <span class="str">'parabolic-constant'</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t782" class="stm run hide_run"> <span class="nam">vertical_base_class</span> <span class="op">=</span> <span class="nam">ParabolicConstantVerticalTransporter</span><span class="strut"> </span></p> +<p id="t783" class="pln"> <span class="key">else</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t784" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="str">"vertical_turbulence must be \'constant\' "</span> <span class="op">+</span><span class="strut"> </span></p> +<p id="t785" class="pln"> <span class="str">"\'parabolic\' or \'parabolic-constant\'."</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t786" class="pln"><span class="strut"> </span></p> +<p id="t787" class="stm run hide_run"> <span class="key">if</span> <span class="nam">advection_direction</span> <span class="op">==</span> <span class="str">'forward'</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t788" class="stm run hide_run"> <span class="nam">longitudinal_base_class</span> <span class="op">=</span> <span class="nam">LongitudinalTransporter</span><span class="strut"> </span></p> +<p id="t789" class="stm mis"> <span class="key">elif</span> <span class="nam">advection_direction</span> <span class="op">==</span> <span class="str">'reverse'</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t790" class="stm mis"> <span class="nam">longitudinal_base_class</span> <span class="op">=</span> <span class="nam">ReverseLongitudinalTransporter</span><span class="strut"> </span></p> +<p id="t791" class="pln"> <span class="key">else</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t792" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="str">"advection_direction must be \'forward\' or "</span> <span class="op">+</span><span class="strut"> </span></p> +<p id="t793" class="pln"> <span class="str">"\'reverse\'."</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t794" class="pln"><span class="strut"> </span></p> +<p id="t795" class="stm run hide_run"> <span class="key">class</span> <span class="nam">FluEggTransporter</span><span class="op">(</span><span class="nam">vertical_base_class</span><span class="op">,</span> <span class="nam">LateralTransporter</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t796" class="pln"> <span class="nam">longitudinal_base_class</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t797" class="pln"> <span class="str">"""This class transports particles through hydraulic cells</span><span class="strut"> </span></p> +<p id="t798" class="pln"><span class="str"> using a parabolic-constant diffusivity profile.</span><span class="strut"> </span></p> +<p id="t799" class="pln"><span class="strut"> </span></p> +<p id="t800" class="pln"><span class="str"> :param LateralTransporter: A lateral transporter model</span><span class="strut"> </span></p> +<p id="t801" class="pln"><span class="str"> :type: transporter.LateralTranslporter</span><span class="strut"> </span></p> +<p id="t802" class="pln"><span class="str"> :param longitudinal_base_class: A longitudinal transporter model</span><span class="strut"> </span></p> +<p id="t803" class="pln"><span class="str"> :type: transporter.Translporter</span><span class="strut"> </span></p> +<p id="t804" class="pln"><span class="str"> :param vertical_base_class: A vertical transporter model</span><span class="strut"> </span></p> +<p id="t805" class="pln"><span class="str"> :type: transporter.Transporter</span><span class="strut"> </span></p> +<p id="t806" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t807" class="pln"><span class="strut"> </span></p> +<p id="t808" class="stm run hide_run"> <span class="key">def</span> <span class="nam">increment_positions</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">hydraulic_results</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t809" class="pln"> <span class="str">"""Increments particle positions to the next time step</span><span class="strut"> </span></p> +<p id="t810" class="pln"><span class="strut"> </span></p> +<p id="t811" class="pln"><span class="str"> :param hydraulic_results: hydraulic results at current particle</span><span class="strut"> </span></p> +<p id="t812" class="pln"><span class="str"> positions</span><span class="strut"> </span></p> +<p id="t813" class="pln"><span class="str"> :type: hydraulics.HydraulicResults</span><span class="strut"> </span></p> +<p id="t814" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t815" class="pln"><span class="strut"> </span></p> +<p id="t816" class="pln"> <span class="com"># Calculate new particle positions</span><span class="strut"> </span></p> +<p id="t817" class="pln"><span class="strut"> </span></p> +<p id="t818" class="stm run hide_run"> <span class="nam">longitudinal_positions</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t819" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">_next_longitudinal_positions</span><span class="op">(</span><span class="nam">hydraulic_results</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t820" class="pln"><span class="strut"> </span></p> +<p id="t821" class="stm run hide_run"> <span class="nam">lateral_positions</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_next_lateral_positions</span><span class="op">(</span><span class="nam">hydraulic_results</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t822" class="stm run hide_run"> <span class="nam">lateral_positions</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t823" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">_lateral_boundary_checks</span><span class="op">(</span><span class="nam">hydraulic_results</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t824" class="pln"> <span class="nam">lateral_positions</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t825" class="pln"><span class="strut"> </span></p> +<p id="t826" class="stm run hide_run"> <span class="nam">vertical_positions</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t827" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">_next_vertical_positions</span><span class="op">(</span><span class="nam">hydraulic_results</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t828" class="stm run hide_run"> <span class="nam">vertical_positions</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t829" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">_vertical_boundary_checks</span><span class="op">(</span><span class="nam">hydraulic_results</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t830" class="pln"> <span class="nam">vertical_positions</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t831" class="pln"><span class="strut"> </span></p> +<p id="t832" class="pln"> <span class="com"># [s, n, z]</span><span class="strut"> </span></p> +<p id="t833" class="stm run hide_run"> <span class="nam">next_positions</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">stack</span><span class="op">(</span><span class="op">(</span><span class="nam">longitudinal_positions</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t834" class="pln"> <span class="nam">lateral_positions</span><span class="op">,</span> <span class="nam">vertical_positions</span><span class="op">)</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t835" class="pln"> <span class="nam">axis</span><span class="op">=</span><span class="num">1</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t836" class="pln"><span class="strut"> </span></p> +<p id="t837" class="pln"> <span class="com"># Increment particle positions</span><span class="strut"> </span></p> +<p id="t838" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_particles</span><span class="op">.</span><span class="nam">set_position</span><span class="op">(</span><span class="nam">next_positions</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t839" class="pln"><span class="strut"> </span></p> +<p id="t840" class="stm run hide_run"> <span class="key">return</span> <span class="nam">FluEggTransporter</span><span class="strut"> </span></p> +<p id="t841" class="pln"><span class="strut"> </span></p> +<p id="t842" class="pln"><span class="strut"> </span></p> +<p id="t843" class="stm run hide_run"><span class="key">def</span> <span class="nam">init_transporter</span><span class="op">(</span><span class="nam">simulation_clock</span><span class="op">,</span> <span class="nam">particles</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t844" class="pln"> <span class="nam">vertical_turbulence</span><span class="op">=</span><span class="str">'parabolic-constant'</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t845" class="pln"> <span class="nam">advection_direction</span><span class="op">=</span><span class="str">'forward'</span><span class="op">,</span> <span class="nam">random_numbers</span><span class="op">=</span><span class="key">None</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t846" class="pln"> <span class="str">"""</span><span class="strut"> </span></p> +<p id="t847" class="pln"><span class="strut"> </span></p> +<p id="t848" class="pln"><span class="str"> :param simulation_clock:</span><span class="strut"> </span></p> +<p id="t849" class="pln"><span class="str"> :param particles:</span><span class="strut"> </span></p> +<p id="t850" class="pln"><span class="str"> :param vertical_turbulence:</span><span class="strut"> </span></p> +<p id="t851" class="pln"><span class="str"> :param advection_direction:</span><span class="strut"> </span></p> +<p id="t852" class="pln"><span class="str"> :return:</span><span class="strut"> </span></p> +<p id="t853" class="pln"><span class="strut"> </span></p> +<p id="t854" class="pln"><span class="str"> """</span><span class="strut"> </span></p> +<p id="t855" class="pln"><span class="strut"> </span></p> +<p id="t856" class="stm mis"> <span class="nam">FluEggTransporter</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t857" class="pln"> <span class="nam">fluegg_transporter_class_factory</span><span class="op">(</span><span class="nam">vertical_turbulence</span><span class="op">,</span><span class="strut"> </span></p> +<p id="t858" class="pln"> <span class="nam">advection_direction</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t859" class="pln"><span class="strut"> </span></p> +<p id="t860" class="stm mis"> <span class="key">return</span> <span class="nam">FluEggTransporter</span><span class="op">(</span><span class="nam">simulation_clock</span><span class="op">,</span> <span class="nam">particles</span><span class="op">,</span> <span class="nam">random_numbers</span><span class="op">)</span><span class="strut"> </span></p> + + </td> + </tr> + </table> +</div> + +<div id="footer"> + <div class="content"> + <p> + <a class="nav" href="index.html">« index</a> <a class="nav" href="https://coverage.readthedocs.io">coverage.py v4.5.3</a>, + created at 2019-07-09 15:15 + </p> + </div> +</div> + +</body> +</html> diff --git a/coverage_report/index.html b/coverage_report/index.html new file mode 100644 index 0000000..f97afe9 --- /dev/null +++ b/coverage_report/index.html @@ -0,0 +1,230 @@ + + + +<!DOCTYPE html> +<html> +<head> + <meta http-equiv="Content-Type" content="text/html; charset=utf-8"> + <title>Coverage report</title> + <link rel="stylesheet" href="style.css" type="text/css"> + + <script type="text/javascript" src="jquery.min.js"></script> + <script type="text/javascript" src="jquery.ba-throttle-debounce.min.js"></script> + <script type="text/javascript" src="jquery.tablesorter.min.js"></script> + <script type="text/javascript" src="jquery.hotkeys.js"></script> + <script type="text/javascript" src="coverage_html.js"></script> + <script type="text/javascript"> + jQuery(document).ready(coverage.index_ready); + </script> +</head> +<body class="indexfile"> + +<div id="header"> + <div class="content"> + <h1>Coverage report: + <span class="pc_cov">47%</span> + </h1> + + <img id="keyboard_icon" src="keybd_closed.png" alt="Show keyboard shortcuts" /> + + <form id="filter_container"> + <input id="filter" type="text" value="" placeholder="filter..." /> + </form> + </div> +</div> + +<div class="help_panel"> + <img id="panel_icon" src="keybd_open.png" alt="Hide keyboard shortcuts" /> + <p class="legend">Hot-keys on this page</p> + <div> + <p class="keyhelp"> + <span class="key">n</span> + <span class="key">s</span> + <span class="key">m</span> + <span class="key">x</span> + + <span class="key">c</span> change column sorting + </p> + </div> +</div> + +<div id="index"> + <table class="index"> + <thead> + + <tr class="tablehead" title="Click to sort"> + <th class="name left headerSortDown shortkey_n">Module</th> + <th class="shortkey_s">statements</th> + <th class="shortkey_m">missing</th> + <th class="shortkey_x">excluded</th> + + <th class="right shortkey_c">coverage</th> + </tr> + </thead> + + <tfoot> + <tr class="total"> + <td class="name left">Total</td> + <td>2060</td> + <td>1084</td> + <td>0</td> + + <td class="right" data-ratio="976 2060">47%</td> + </tr> + </tfoot> + <tbody> + + <tr class="file"> + <td class="name left"><a href="fluegg___init___py.html">fluegg\__init__.py</a></td> + <td>0</td> + <td>0</td> + <td>0</td> + + <td class="right" data-ratio="0 0">100%</td> + </tr> + + <tr class="file"> + <td class="name left"><a href="fluegg_asiancarpeggs_py.html">fluegg\asiancarpeggs.py</a></td> + <td>226</td> + <td>17</td> + <td>0</td> + + <td class="right" data-ratio="209 226">92%</td> + </tr> + + <tr class="file"> + <td class="name left"><a href="fluegg_drift_py.html">fluegg\drift.py</a></td> + <td>56</td> + <td>6</td> + <td>0</td> + + <td class="right" data-ratio="50 56">89%</td> + </tr> + + <tr class="file"> + <td class="name left"><a href="fluegg_gui___init___py.html">fluegg\gui\__init__.py</a></td> + <td>0</td> + <td>0</td> + <td>0</td> + + <td class="right" data-ratio="0 0">100%</td> + </tr> + + <tr class="file"> + <td class="name left"><a href="fluegg_gui_gui_py.html">fluegg\gui\gui.py</a></td> + <td>254</td> + <td>225</td> + <td>0</td> + + <td class="right" data-ratio="29 254">11%</td> + </tr> + + <tr class="file"> + <td class="name left"><a href="fluegg_gui_gui_layout_py.html">fluegg\gui\gui_layout.py</a></td> + <td>276</td> + <td>272</td> + <td>0</td> + + <td class="right" data-ratio="4 276">1%</td> + </tr> + + <tr class="file"> + <td class="name left"><a href="fluegg_gui_hecras_dialog_py.html">fluegg\gui\hecras_dialog.py</a></td> + <td>112</td> + <td>108</td> + <td>0</td> + + <td class="right" data-ratio="4 112">4%</td> + </tr> + + <tr class="file"> + <td class="name left"><a href="fluegg_hydraulics_py.html">fluegg\hydraulics.py</a></td> + <td>287</td> + <td>37</td> + <td>0</td> + + <td class="right" data-ratio="250 287">87%</td> + </tr> + + <tr class="file"> + <td class="name left"><a href="fluegg_kml_py.html">fluegg\kml.py</a></td> + <td>130</td> + <td>113</td> + <td>0</td> + + <td class="right" data-ratio="17 130">13%</td> + </tr> + + <tr class="file"> + <td class="name left"><a href="fluegg_random_py.html">fluegg\random.py</a></td> + <td>36</td> + <td>18</td> + <td>0</td> + + <td class="right" data-ratio="18 36">50%</td> + </tr> + + <tr class="file"> + <td class="name left"><a href="fluegg_ras_py.html">fluegg\ras.py</a></td> + <td>197</td> + <td>148</td> + <td>0</td> + + <td class="right" data-ratio="49 197">25%</td> + </tr> + + <tr class="file"> + <td class="name left"><a href="fluegg_simclock_py.html">fluegg\simclock.py</a></td> + <td>46</td> + <td>5</td> + <td>0</td> + + <td class="right" data-ratio="41 46">89%</td> + </tr> + + <tr class="file"> + <td class="name left"><a href="fluegg_simulation_py.html">fluegg\simulation.py</a></td> + <td>132</td> + <td>76</td> + <td>0</td> + + <td class="right" data-ratio="56 132">42%</td> + </tr> + + <tr class="file"> + <td class="name left"><a href="fluegg_transporter_py.html">fluegg\transporter.py</a></td> + <td>285</td> + <td>56</td> + <td>0</td> + + <td class="right" data-ratio="229 285">80%</td> + </tr> + + <tr class="file"> + <td class="name left"><a href="test_fluegg_py.html">test_fluegg.py</a></td> + <td>23</td> + <td>3</td> + <td>0</td> + + <td class="right" data-ratio="20 23">87%</td> + </tr> + + </tbody> + </table> + + <p id="no_rows"> + No items found using the specified filter. + </p> +</div> + +<div id="footer"> + <div class="content"> + <p> + <a class="nav" href="https://coverage.readthedocs.io">coverage.py v4.5.3</a>, + created at 2019-07-09 15:49 + </p> + </div> +</div> + +</body> +</html> diff --git a/coverage_report/jquery.ba-throttle-debounce.min.js b/coverage_report/jquery.ba-throttle-debounce.min.js new file mode 100644 index 0000000..648fe5d --- /dev/null +++ b/coverage_report/jquery.ba-throttle-debounce.min.js @@ -0,0 +1,9 @@ +/* + * jQuery throttle / debounce - v1.1 - 3/7/2010 + * http://benalman.com/projects/jquery-throttle-debounce-plugin/ + * + * Copyright (c) 2010 "Cowboy" Ben Alman + * Dual licensed under the MIT and GPL licenses. + * http://benalman.com/about/license/ + */ +(function(b,c){var $=b.jQuery||b.Cowboy||(b.Cowboy={}),a;$.throttle=a=function(e,f,j,i){var h,d=0;if(typeof f!=="boolean"){i=j;j=f;f=c}function g(){var o=this,m=+new Date()-d,n=arguments;function l(){d=+new Date();j.apply(o,n)}function k(){h=c}if(i&&!h){l()}h&&clearTimeout(h);if(i===c&&m>e){l()}else{if(f!==true){h=setTimeout(i?k:l,i===c?e-m:e)}}}if($.guid){g.guid=j.guid=j.guid||$.guid++}return g};$.debounce=function(d,e,f){return f===c?a(d,e,false):a(d,f,e!==false)}})(this); diff --git a/coverage_report/jquery.hotkeys.js b/coverage_report/jquery.hotkeys.js new file mode 100644 index 0000000..09b21e0 --- /dev/null +++ b/coverage_report/jquery.hotkeys.js @@ -0,0 +1,99 @@ +/* + * jQuery Hotkeys Plugin + * Copyright 2010, John Resig + * Dual licensed under the MIT or GPL Version 2 licenses. + * + * Based upon the plugin by Tzury Bar Yochay: + * http://github.com/tzuryby/hotkeys + * + * Original idea by: + * Binny V A, http://www.openjs.com/scripts/events/keyboard_shortcuts/ +*/ + +(function(jQuery){ + + jQuery.hotkeys = { + version: "0.8", + + specialKeys: { + 8: "backspace", 9: "tab", 13: "return", 16: "shift", 17: "ctrl", 18: "alt", 19: "pause", + 20: "capslock", 27: "esc", 32: "space", 33: "pageup", 34: "pagedown", 35: "end", 36: "home", + 37: "left", 38: "up", 39: "right", 40: "down", 45: "insert", 46: "del", + 96: "0", 97: "1", 98: "2", 99: "3", 100: "4", 101: "5", 102: "6", 103: "7", + 104: "8", 105: "9", 106: "*", 107: "+", 109: "-", 110: ".", 111 : "/", + 112: "f1", 113: "f2", 114: "f3", 115: "f4", 116: "f5", 117: "f6", 118: "f7", 119: "f8", + 120: "f9", 121: "f10", 122: "f11", 123: "f12", 144: "numlock", 145: "scroll", 191: "/", 224: "meta" + }, + + shiftNums: { + "`": "~", "1": "!", "2": "@", "3": "#", "4": "$", "5": "%", "6": "^", "7": "&", + "8": "*", "9": "(", "0": ")", "-": "_", "=": "+", ";": ": ", "'": "\"", ",": "<", + ".": ">", "/": "?", "\\": "|" + } + }; + + function keyHandler( handleObj ) { + // Only care when a possible input has been specified + if ( typeof handleObj.data !== "string" ) { + return; + } + + var origHandler = handleObj.handler, + keys = handleObj.data.toLowerCase().split(" "); + + handleObj.handler = function( event ) { + // Don't fire in text-accepting inputs that we didn't directly bind to + if ( this !== event.target && (/textarea|select/i.test( event.target.nodeName ) || + event.target.type === "text") ) { + return; + } + + // Keypress represents characters, not special keys + var special = event.type !== "keypress" && jQuery.hotkeys.specialKeys[ event.which ], + character = String.fromCharCode( event.which ).toLowerCase(), + key, modif = "", possible = {}; + + // check combinations (alt|ctrl|shift+anything) + if ( event.altKey && special !== "alt" ) { + modif += "alt+"; + } + + if ( event.ctrlKey && special !== "ctrl" ) { + modif += "ctrl+"; + } + + // TODO: Need to make sure this works consistently across platforms + if ( event.metaKey && !event.ctrlKey && special !== "meta" ) { + modif += "meta+"; + } + + if ( event.shiftKey && special !== "shift" ) { + modif += "shift+"; + } + + if ( special ) { + possible[ modif + special ] = true; + + } else { + possible[ modif + character ] = true; + possible[ modif + jQuery.hotkeys.shiftNums[ character ] ] = true; + + // "$" can be triggered as "Shift+4" or "Shift+$" or just "$" + if ( modif === "shift+" ) { + possible[ jQuery.hotkeys.shiftNums[ character ] ] = true; + } + } + + for ( var i = 0, l = keys.length; i < l; i++ ) { + if ( possible[ keys[i] ] ) { + return origHandler.apply( this, arguments ); + } + } + }; + } + + jQuery.each([ "keydown", "keyup", "keypress" ], function() { + jQuery.event.special[ this ] = { add: keyHandler }; + }); + +})( jQuery ); diff --git a/coverage_report/jquery.isonscreen.js b/coverage_report/jquery.isonscreen.js new file mode 100644 index 0000000..0182ebd --- /dev/null +++ b/coverage_report/jquery.isonscreen.js @@ -0,0 +1,53 @@ +/* Copyright (c) 2010 + * @author Laurence Wheway + * Dual licensed under the MIT (http://www.opensource.org/licenses/mit-license.php) + * and GPL (http://www.opensource.org/licenses/gpl-license.php) licenses. + * + * @version 1.2.0 + */ +(function($) { + jQuery.extend({ + isOnScreen: function(box, container) { + //ensure numbers come in as intgers (not strings) and remove 'px' is it's there + for(var i in box){box[i] = parseFloat(box[i])}; + for(var i in container){container[i] = parseFloat(container[i])}; + + if(!container){ + container = { + left: $(window).scrollLeft(), + top: $(window).scrollTop(), + width: $(window).width(), + height: $(window).height() + } + } + + if( box.left+box.width-container.left > 0 && + box.left < container.width+container.left && + box.top+box.height-container.top > 0 && + box.top < container.height+container.top + ) return true; + return false; + } + }) + + + jQuery.fn.isOnScreen = function (container) { + for(var i in container){container[i] = parseFloat(container[i])}; + + if(!container){ + container = { + left: $(window).scrollLeft(), + top: $(window).scrollTop(), + width: $(window).width(), + height: $(window).height() + } + } + + if( $(this).offset().left+$(this).width()-container.left > 0 && + $(this).offset().left < container.width+container.left && + $(this).offset().top+$(this).height()-container.top > 0 && + $(this).offset().top < container.height+container.top + ) return true; + return false; + } +})(jQuery); diff --git a/coverage_report/jquery.min.js b/coverage_report/jquery.min.js new 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td.name a { + text-decoration: none; + color: #000; + } +#index tr.total, +#index tr.total_dynamic { + } +#index tr.total td, +#index tr.total_dynamic td { + font-weight: bold; + border-top: 1px solid #ccc; + border-bottom: none; + } +#index tr.file:hover { + background: #eeeeee; + } +#index tr.file:hover td.name { + text-decoration: underline; + color: #000; + } + +/* scroll marker styles */ +#scroll_marker { + position: fixed; + right: 0; + top: 0; + width: 16px; + height: 100%; + background: white; + border-left: 1px solid #eee; + } + +#scroll_marker .marker { + background: #eedddd; + position: absolute; + min-height: 3px; + width: 100%; + } diff --git a/coverage_report/test_fluegg_py.html b/coverage_report/test_fluegg_py.html new file mode 100644 index 0000000..2a68b53 --- /dev/null +++ b/coverage_report/test_fluegg_py.html @@ -0,0 +1,165 @@ + + + +<!DOCTYPE html> +<html> +<head> + <meta http-equiv="Content-Type" content="text/html; charset=utf-8"> + + + <meta http-equiv="X-UA-Compatible" content="IE=emulateIE7" /> + <title>Coverage for test_fluegg.py: 87%</title> + <link rel="stylesheet" href="style.css" type="text/css"> + + <script type="text/javascript" src="jquery.min.js"></script> + <script type="text/javascript" src="jquery.hotkeys.js"></script> + <script type="text/javascript" src="jquery.isonscreen.js"></script> + <script type="text/javascript" src="coverage_html.js"></script> + <script type="text/javascript"> + jQuery(document).ready(coverage.pyfile_ready); + </script> +</head> +<body class="pyfile"> + +<div id="header"> + <div class="content"> + <h1>Coverage for <b>test_fluegg.py</b> : + <span class="pc_cov">87%</span> + </h1> + + <img id="keyboard_icon" src="keybd_closed.png" alt="Show keyboard shortcuts" /> + + <h2 class="stats"> + 23 statements + <span class="run hide_run shortkey_r button_toggle_run">20 run</span> + <span class="mis shortkey_m button_toggle_mis">3 missing</span> + <span class="exc shortkey_x button_toggle_exc">0 excluded</span> + + + </h2> + </div> +</div> + +<div class="help_panel"> + <img id="panel_icon" src="keybd_open.png" alt="Hide keyboard shortcuts" /> + <p class="legend">Hot-keys on this page</p> + <div> + <p class="keyhelp"> + <span class="key">r</span> + <span class="key">m</span> + <span class="key">x</span> + <span class="key">p</span> toggle line displays + </p> + <p class="keyhelp"> + <span class="key">j</span> + <span class="key">k</span> next/prev highlighted chunk + </p> + <p class="keyhelp"> + <span class="key">0</span> (zero) top of page + </p> + <p class="keyhelp"> + <span class="key">1</span> (one) first highlighted chunk + </p> + </div> +</div> + +<div id="source"> + <table> + <tr> + <td class="linenos"> +<p id="n1" class="stm run hide_run"><a href="#n1">1</a></p> +<p id="n2" class="stm run hide_run"><a href="#n2">2</a></p> +<p id="n3" class="stm run hide_run"><a href="#n3">3</a></p> +<p id="n4" class="stm run hide_run"><a href="#n4">4</a></p> +<p id="n5" class="pln"><a href="#n5">5</a></p> +<p id="n6" class="stm run hide_run"><a href="#n6">6</a></p> +<p id="n7" class="pln"><a href="#n7">7</a></p> +<p id="n8" class="stm run hide_run"><a href="#n8">8</a></p> +<p id="n9" class="pln"><a href="#n9">9</a></p> +<p id="n10" class="stm run hide_run"><a href="#n10">10</a></p> +<p id="n11" class="pln"><a href="#n11">11</a></p> +<p id="n12" class="pln"><a href="#n12">12</a></p> +<p id="n13" class="stm run hide_run"><a href="#n13">13</a></p> +<p id="n14" class="pln"><a href="#n14">14</a></p> +<p id="n15" class="pln"><a href="#n15">15</a></p> +<p id="n16" class="stm run hide_run"><a href="#n16">16</a></p> +<p id="n17" class="pln"><a href="#n17">17</a></p> +<p id="n18" class="stm run hide_run"><a href="#n18">18</a></p> +<p id="n19" class="pln"><a href="#n19">19</a></p> +<p id="n20" class="stm run hide_run"><a href="#n20">20</a></p> +<p id="n21" class="stm run hide_run"><a href="#n21">21</a></p> +<p id="n22" class="stm run hide_run"><a href="#n22">22</a></p> +<p id="n23" class="stm run hide_run"><a href="#n23">23</a></p> +<p id="n24" class="stm run hide_run"><a href="#n24">24</a></p> +<p id="n25" class="stm run hide_run"><a href="#n25">25</a></p> +<p id="n26" class="pln"><a href="#n26">26</a></p> +<p id="n27" class="stm run hide_run"><a href="#n27">27</a></p> +<p id="n28" class="pln"><a href="#n28">28</a></p> +<p id="n29" class="stm run hide_run"><a href="#n29">29</a></p> +<p id="n30" class="pln"><a href="#n30">30</a></p> +<p id="n31" class="stm run hide_run"><a href="#n31">31</a></p> +<p id="n32" class="pln"><a href="#n32">32</a></p> +<p id="n33" class="pln"><a href="#n33">33</a></p> +<p id="n34" class="stm run hide_run"><a href="#n34">34</a></p> +<p id="n35" class="stm mis"><a href="#n35">35</a></p> +<p id="n36" class="stm mis"><a href="#n36">36</a></p> +<p id="n37" class="stm mis"><a href="#n37">37</a></p> +<p id="n38" class="pln"><a href="#n38">38</a></p> + + </td> + <td class="text"> +<p id="t1" class="stm run hide_run"><span class="key">import</span> <span class="nam">os</span><span class="strut"> </span></p> +<p id="t2" class="stm run hide_run"><span class="key">import</span> <span class="nam">glob</span><span class="strut"> </span></p> +<p id="t3" class="stm run hide_run"><span class="key">import</span> <span class="nam">importlib</span><span class="strut"> </span></p> +<p id="t4" class="stm run hide_run"><span class="key">import</span> <span class="nam">unittest</span><span class="strut"> </span></p> +<p id="t5" class="pln"><span class="strut"> </span></p> +<p id="t6" class="stm run hide_run"><span class="nam">absolute_path</span><span class="op">,</span> <span class="nam">_</span> <span class="op">=</span> <span class="nam">os</span><span class="op">.</span><span class="nam">path</span><span class="op">.</span><span class="nam">split</span><span class="op">(</span><span class="nam">os</span><span class="op">.</span><span class="nam">path</span><span class="op">.</span><span class="nam">realpath</span><span class="op">(</span><span class="nam">__file__</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t7" class="pln"><span class="strut"> </span></p> +<p id="t8" class="stm run hide_run"><span class="nam">module_paths</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t9" class="pln"> <span class="op">[</span><span class="nam">path</span> <span class="key">for</span> <span class="nam">path</span> <span class="key">in</span> <span class="nam">glob</span><span class="op">.</span><span class="nam">glob</span><span class="op">(</span><span class="nam">os</span><span class="op">.</span><span class="nam">path</span><span class="op">.</span><span class="nam">join</span><span class="op">(</span><span class="nam">absolute_path</span><span class="op">,</span> <span class="str">'test'</span><span class="op">,</span> <span class="str">'*.py'</span><span class="op">)</span><span class="op">)</span> <span class="key">if</span> <span class="str">'__init__.py'</span> <span class="key">not</span> <span class="key">in</span> <span class="nam">path</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t10" class="stm run hide_run"><span class="nam">nonrandom_test_module_paths</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> +<p id="t11" class="pln"> <span class="op">[</span><span class="nam">path</span> <span class="key">for</span> <span class="nam">path</span> <span class="key">in</span> <span class="nam">glob</span><span class="op">.</span><span class="nam">glob</span><span class="op">(</span><span class="nam">os</span><span class="op">.</span><span class="nam">path</span><span class="op">.</span><span class="nam">join</span><span class="op">(</span><span class="nam">absolute_path</span><span class="op">,</span> <span class="str">'test'</span><span class="op">,</span> <span class="str">'nonrandom'</span><span class="op">,</span> <span class="str">'*.py'</span><span class="op">)</span><span class="op">)</span> <span class="key">if</span> <span class="str">'__init__.py'</span> <span class="key">not</span> <span class="key">in</span> <span class="nam">path</span><span class="op">]</span><span class="strut"> </span></p> +<p id="t12" class="pln"><span class="strut"> </span></p> +<p id="t13" class="stm run hide_run"><span class="nam">module_paths</span><span class="op">.</span><span class="nam">extend</span><span class="op">(</span><span class="nam">nonrandom_test_module_paths</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t14" class="pln"><span class="strut"> </span></p> +<p id="t15" class="pln"><span class="strut"> </span></p> +<p id="t16" class="stm run hide_run"><span class="key">def</span> <span class="nam">load_tests</span><span class="op">(</span><span class="nam">loader</span><span class="op">,</span> <span class="op">*</span><span class="nam">args</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t17" class="pln"><span class="strut"> </span></p> +<p id="t18" class="stm run hide_run"> <span class="nam">suite</span> <span class="op">=</span> <span class="nam">unittest</span><span class="op">.</span><span class="nam">TestSuite</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t19" class="pln"><span class="strut"> </span></p> +<p id="t20" class="stm run hide_run"> <span class="key">for</span> <span class="nam">path</span> <span class="key">in</span> <span class="nam">module_paths</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t21" class="stm run hide_run"> <span class="nam">_</span><span class="op">,</span> <span class="nam">module_file_name</span> <span class="op">=</span> <span class="nam">os</span><span class="op">.</span><span class="nam">path</span><span class="op">.</span><span class="nam">split</span><span class="op">(</span><span class="nam">path</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t22" class="stm run hide_run"> <span class="nam">module_name</span><span class="op">,</span> <span class="nam">_</span> <span class="op">=</span> <span class="nam">os</span><span class="op">.</span><span class="nam">path</span><span class="op">.</span><span class="nam">splitext</span><span class="op">(</span><span class="nam">module_file_name</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t23" class="stm run hide_run"> <span class="nam">spec</span> <span class="op">=</span> <span class="nam">importlib</span><span class="op">.</span><span class="nam">util</span><span class="op">.</span><span class="nam">spec_from_file_location</span><span class="op">(</span><span class="nam">module_name</span><span class="op">,</span> <span class="nam">path</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t24" class="stm run hide_run"> <span class="nam">module</span> <span class="op">=</span> <span class="nam">importlib</span><span class="op">.</span><span class="nam">util</span><span class="op">.</span><span class="nam">module_from_spec</span><span class="op">(</span><span class="nam">spec</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t25" class="stm run hide_run"> <span class="nam">spec</span><span class="op">.</span><span class="nam">loader</span><span class="op">.</span><span class="nam">exec_module</span><span class="op">(</span><span class="nam">module</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t26" class="pln"><span class="strut"> </span></p> +<p id="t27" class="stm run hide_run"> <span class="nam">tests</span> <span class="op">=</span> <span class="nam">loader</span><span class="op">.</span><span class="nam">loadTestsFromModule</span><span class="op">(</span><span class="nam">module</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t28" class="pln"><span class="strut"> </span></p> +<p id="t29" class="stm run hide_run"> <span class="nam">suite</span><span class="op">.</span><span class="nam">addTest</span><span class="op">(</span><span class="nam">tests</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t30" class="pln"><span class="strut"> </span></p> +<p id="t31" class="stm run hide_run"> <span class="key">return</span> <span class="nam">suite</span><span class="strut"> </span></p> +<p id="t32" class="pln"><span class="strut"> </span></p> +<p id="t33" class="pln"><span class="strut"> </span></p> +<p id="t34" class="stm run hide_run"><span class="key">if</span> <span class="nam">__name__</span> <span class="op">==</span> <span class="str">'__main__'</span><span class="op">:</span><span class="strut"> </span></p> +<p id="t35" class="stm mis"> <span class="nam">test_loader</span> <span class="op">=</span> <span class="nam">unittest</span><span class="op">.</span><span class="nam">defaultTestLoader</span><span class="strut"> </span></p> +<p id="t36" class="stm mis"> <span class="nam">test_suite</span> <span class="op">=</span> <span class="nam">load_tests</span><span class="op">(</span><span class="nam">test_loader</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t37" class="stm mis"> <span class="nam">unittest</span><span class="op">.</span><span class="nam">TextTestRunner</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">run</span><span class="op">(</span><span class="nam">test_suite</span><span class="op">)</span><span class="strut"> </span></p> +<p id="t38" class="pln"><span class="strut"> </span></p> + + </td> + </tr> + </table> +</div> + +<div id="footer"> + <div class="content"> + <p> + <a class="nav" href="index.html">« index</a> <a class="nav" href="https://coverage.readthedocs.io">coverage.py v4.5.3</a>, + created at 2019-07-09 15:15 + </p> + </div> +</div> + +</body> +</html> diff --git a/notebooks/vertical transporter - Copy.ipynb b/notebooks/vertical transporter - Copy.ipynb new file mode 100644 index 0000000..95df8cf --- /dev/null +++ b/notebooks/vertical transporter - Copy.ipynb @@ -0,0 +1,326 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "<div>\n", + "<style scoped>\n", + " .dataframe tbody tr th:only-of-type {\n", + " vertical-align: middle;\n", + " }\n", + "\n", + " .dataframe tbody tr th {\n", + " vertical-align: top;\n", + " }\n", + "\n", + " .dataframe thead th {\n", + " text-align: right;\n", + " }\n", + "</style>\n", + "<table border=\"1\" class=\"dataframe\">\n", + " <thead>\n", + " <tr style=\"text-align: right;\">\n", + " <th></th>\n", + " <th>CumlDistance_km</th>\n", + " <th>Depth_m</th>\n", + " <th>Q_cms</th>\n", + " <th>Vmag_mps</th>\n", + " <th>Vvert_mps</th>\n", + " <th>Vlat_mps</th>\n", + " <th>Ustar_mps</th>\n", + " <th>Temp_C</th>\n", + " </tr>\n", + " <tr>\n", + " <th>CellNumber</th>\n", + " <th></th>\n", + " <th></th>\n", + " <th></th>\n", + " <th></th>\n", + " <th></th>\n", + " <th></th>\n", + " <th></th>\n", + " <th></th>\n", + " </tr>\n", + " </thead>\n", + " <tbody>\n", + " <tr>\n", + " <th>1</th>\n", + " <td>20</td>\n", + " <td>1</td>\n", + " <td>10</td>\n", + " <td>1</td>\n", + " <td>0</td>\n", + " <td>0</td>\n", + " <td>0.08</td>\n", + " <td>19</td>\n", + " </tr>\n", + " <tr>\n", + " <th>2</th>\n", + " <td>40</td>\n", + " <td>2</td>\n", + " <td>20</td>\n", + " <td>2</td>\n", + " <td>0</td>\n", + " <td>0</td>\n", + " <td>0.08</td>\n", + " <td>20</td>\n", + " </tr>\n", + " <tr>\n", + " <th>3</th>\n", + " <td>60</td>\n", + " <td>3</td>\n", + " <td>30</td>\n", + " <td>3</td>\n", + " <td>0</td>\n", + " <td>0</td>\n", + " <td>0.08</td>\n", + " <td>21</td>\n", + " </tr>\n", + " <tr>\n", + " <th>4</th>\n", + " <td>80</td>\n", + " <td>4</td>\n", + " <td>40</td>\n", + " <td>4</td>\n", + " <td>0</td>\n", + " <td>0</td>\n", + " <td>0.08</td>\n", + " <td>22</td>\n", + " </tr>\n", + " <tr>\n", + " <th>5</th>\n", + " <td>100</td>\n", + " <td>5</td>\n", + " <td>50</td>\n", + " <td>5</td>\n", + " <td>0</td>\n", + " <td>0</td>\n", + " <td>0.08</td>\n", + " <td>23</td>\n", + " </tr>\n", + " </tbody>\n", + "</table>\n", + "</div>" + ], + "text/plain": [ + " CumlDistance_km Depth_m Q_cms Vmag_mps Vvert_mps Vlat_mps \\\n", + "CellNumber \n", + "1 20 1 10 1 0 0 \n", + "2 40 2 20 2 0 0 \n", + "3 60 3 30 3 0 0 \n", + "4 80 4 40 4 0 0 \n", + "5 100 5 50 5 0 0 \n", + "\n", + " Ustar_mps Temp_C \n", + "CellNumber \n", + "1 0.08 19 \n", + "2 0.08 20 \n", + "3 0.08 21 \n", + "4 0.08 22 \n", + "5 0.08 23 " + ] + }, + "execution_count": 1, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import os\n", + "\n", + "import pandas as pd\n", + "\n", + "\n", + "# show the hydraulic data contained in the CSV file\n", + "hydraulic_csv_path = os.path.join('..', 'test', 'data', 'multi-cell input.csv')\n", + "hydraulic_data = pd.read_csv(hydraulic_csv_path, index_col='CellNumber')\n", + "hydraulic_data" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "from fluegg.hydraulics import from_csv\n", + "\n", + "# initialize a hydraulic model as a series of hydraulic cells from the CSV\n", + "hydraulic_model = from_csv(hydraulic_csv_path)" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "from fluegg.asiancarpeggs import BigheadCarpEggs\n", + "from fluegg.simclock import SimulationClock\n", + "\n", + "# total_simulation_time = BigheadCarpEggs.hatching_time(hydraulic_data['Temp_C'].mean())\n", + "total_simulation_time = 1000 # seconds\n", + "time_step_size = 1 # seconds\n", + "\n", + "simulation_clock = SimulationClock(time_step_size, total_simulation_time)" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "\n", + "\n", + "first_cell_x_midpoint = 1000*hydraulic_data.loc[1, 'CumlDistance_km']/2\n", + "\n", + "depth = hydraulic_data.loc[1, 'Depth_m']\n", + "first_cell_z_midpoint = -depth/2\n", + "\n", + "area = hydraulic_data.loc[1, 'Q_cms']/hydraulic_data.loc[1, 'Vmag_mps']\n", + "width = area/depth\n", + "first_cell_y_midpoint = width/2\n", + "\n", + "initial_position = np.array([10, first_cell_y_midpoint, first_cell_z_midpoint])\n", + "\n", + "number_of_eggs = 10\n", + "initial_position = np.tile(initial_position, (number_of_eggs, 1))\n", + "\n", + "carp_eggs = BigheadCarpEggs(initial_position, simulation_clock)" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "from fluegg.transporter import ParabolicConstantVerticalTransporter\n", + "\n", + "transport_model = ParabolicConstantVerticalTransporter(simulation_clock, carp_eggs)\n", + "transport_model.set_hydraulic_model(hydraulic_model)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "from fluegg.simulation import Simulation\n", + "\n", + "fluegg_simulation = Simulation(carp_eggs, transport_model, simulation_clock)\n", + "fluegg_simulation.set_hydraulic_model(hydraulic_model)\n", + "\n", + "simulation_results = fluegg_simulation.run()" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 720x576 with 3 Axes>" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "%matplotlib inline\n", + "import matplotlib.pyplot as plt\n", + "\n", + "positions = simulation_results.results()\n", + "\n", + "time = simulation_clock.time_array()\n", + "\n", + "x = positions[:, :, 0]\n", + "y = positions[:, :, 1]\n", + "z = positions[:, :, 2]\n", + "\n", + "fig = plt.figure(figsize=(10,8))\n", + "\n", + "x_position_axes = fig.add_subplot(311)\n", + "_ = x_position_axes.plot(time, x, '.')\n", + "_ = x_position_axes.set_ylabel('x')\n", + "\n", + "y_position_axes = fig.add_subplot(312, sharex=x_position_axes)\n", + "_ = y_position_axes.plot(time, y, '.')\n", + "_ = y_position_axes.set_ylabel('y')\n", + "\n", + "z_position_axes = fig.add_subplot(313, sharex=x_position_axes)\n", + "_ = z_position_axes.plot(time, z, '.')\n", + "_ = z_position_axes.set_ylabel('z')\n", + "_ = z_position_axes.set_xlabel('time')" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 720x576 with 3 Axes>" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig = plt.figure(figsize=(10,8))\n", + "\n", + "xy_axes = fig.add_subplot(221)\n", + "_ = xy_axes.plot(x, y, '.')\n", + "_ = xy_axes.set_ylabel('y')\n", + "\n", + "xz_axes = fig.add_subplot(223, sharex=xy_axes)\n", + "_ = xz_axes.plot(x, z, '.')\n", + "_ = xz_axes.set_ylabel('z')\n", + "_ = xz_axes.set_xlabel('x')\n", + "\n", + "zy_axes = fig.add_subplot(222, sharey=xy_axes)\n", + "_ = zy_axes.plot(z, y, '.')\n", + "_ = zy_axes.set_xlabel('z')" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.6.6" + } + }, + "nbformat": 4, + 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b/test/data/ras/unsteadyflume/HEC-RASFlumeCase.rasmap new file mode 100644 index 0000000..c68a347 --- /dev/null +++ b/test/data/ras/unsteadyflume/HEC-RASFlumeCase.rasmap @@ -0,0 +1,187 @@ +<RASMapper> + <Version>2.0.13611</Version> + <Geometries TopNode="True"> + <Layer Name="Base Case 01 Geometry" Type="RASGeometry" Filename=".\HEC-RASFlumeCase.g02.hdf"> + <Layer Name="Rivers" Type="RASRiver" /> + <Layer Name="XS" Type="RASXS" /> + <Layer Name="Storage Areas" Type="RASStorageArea" /> + <Layer Name="2D Flow Areas" Type="RASD2FlowArea" /> + <Layer Name="..." Type="RASMoreLayers" /> + </Layer> + <Layer Name="Base Case 02 Geometry" Type="RASGeometry" Filename=".\HEC-RASFlumeCase.g03.hdf"> + <Layer Name="Rivers" Type="RASRiver" /> + <Layer Name="XS" Type="RASXS" /> + <Layer Name="Storage Areas" Type="RASStorageArea" /> + <Layer Name="2D Flow Areas" Type="RASD2FlowArea" /> + <Layer Name="..." Type="RASMoreLayers" /> + </Layer> + <Layer Name="Base Case 03 Geometry" Type="RASGeometry" Filename=".\HEC-RASFlumeCase.g01.hdf"> + <Layer Name="Rivers" Type="RASRiver" /> + <Layer Name="XS" Type="RASXS" /> + <Layer Name="Storage Areas" Type="RASStorageArea" /> + <Layer Name="2D Flow Areas" Type="RASD2FlowArea" /> + <Layer Name="..." Type="RASMoreLayers" /> + </Layer> + <Layer Name="Base Case 04 Geometry" Type="RASGeometry" Filename=".\HEC-RASFlumeCase.g04.hdf"> + <Layer Name="Rivers" Type="RASRiver" /> + <Layer Name="XS" Type="RASXS" /> + <Layer Name="Storage Areas" Type="RASStorageArea" /> + <Layer Name="2D Flow Areas" Type="RASD2FlowArea" /> + <Layer Name="..." Type="RASMoreLayers" /> + </Layer> + <Layer Name="Unsteady Geometry" Type="RASGeometry" Filename=".\HEC-RASFlumeCase.g05.hdf"> + <Layer Name="Rivers" Type="RASRiver" /> + <Layer Name="XS" Type="RASXS" /> + <Layer Name="Storage Areas" Type="RASStorageArea" /> + <Layer Name="2D Flow Areas" Type="RASD2FlowArea" /> + <Layer Name="..." Type="RASMoreLayers" /> + </Layer> + </Geometries> + <Results Expanded="True"> + <Layer Name="Flume Base Case 01" Type="RASResults" Filename=".\HEC-RASFlumeCase.p01.hdf"> + <Layer Name="Geometry" Type="RASGeometry" Filename=".\HEC-RASFlumeCase.p01.hdf"> + <Layer Name="Rivers" Type="RASRiver" /> + <Layer Name="XS" Type="RASXS" /> + <Layer Name="Storage Areas" Type="RASStorageArea" /> + <Layer Name="2D Flow Areas" Type="RASD2FlowArea" /> + <Layer Name="..." Type="RASMoreLayers" /> + </Layer> + <Layer Name="depth" Type="RASResultsMap"> + <SurfaceFill Alpha="255" Colors="-16711681,-16777077" Values="0,15" Stretched="True" /> + <Contour On="False" Interval="5" Color="-16777216" /> + <MapParameters MapType="depth" OutputMode="Dynamic Surface" ContourPolygonValue="0" ProfileIndex="2147483647" ProfileName="Max" ArrivalStartMode="0" Hours="True" /> + </Layer> + <Layer Name="velocity" Type="RASResultsMap"> + <SurfaceFill Alpha="255" Colors="-16777077,-16776961,-7278960,-256,-23296,-47872,-7667712" Values="0,2,4,6,8,10,15" Stretched="True" /> + <Contour On="False" Interval="5" Color="-16777216" /> + <MapParameters MapType="velocity" OutputMode="Dynamic Surface" ContourPolygonValue="0" ProfileIndex="2147483647" ProfileName="Max" ArrivalStartMode="0" Hours="True" /> + </Layer> + <Layer Name="elevation" Type="RASResultsMap"> + <SurfaceFill Alpha="255" Colors="-8388864,-16744448,-256,-23296,-65536,-16181,-65281" Values="0,16.6666666666667,33.3333333333333,50,66.6666666666667,83.3333333333333,100" Stretched="True" /> + <Contour On="False" Interval="5" Color="-16777216" /> + <MapParameters MapType="elevation" OutputMode="Dynamic Surface" ContourPolygonValue="0" ProfileIndex="2147483647" ProfileName="Max" ArrivalStartMode="0" Hours="True" /> + </Layer> + </Layer> + <Layer Name="BaseCase02" Type="RASResults" Filename=".\HEC-RASFlumeCase.p02.hdf"> + <Layer Name="Geometry" Type="RASGeometry" Filename=".\HEC-RASFlumeCase.p02.hdf"> + <Layer Name="Rivers" Type="RASRiver" /> + <Layer Name="XS" Type="RASXS" /> + <Layer Name="Storage Areas" Type="RASStorageArea" /> + <Layer Name="2D Flow Areas" Type="RASD2FlowArea" /> + <Layer Name="..." Type="RASMoreLayers" /> + </Layer> + <Layer Name="depth" Type="RASResultsMap"> + <SurfaceFill Alpha="255" Colors="-16711681,-16777077" Values="0,15" Stretched="True" /> + <Contour On="False" Interval="5" Color="-16777216" /> + <MapParameters MapType="depth" OutputMode="Dynamic Surface" ContourPolygonValue="0" ProfileIndex="2147483647" ProfileName="Max" ArrivalStartMode="0" Hours="True" /> + </Layer> + <Layer Name="velocity" Type="RASResultsMap"> + <SurfaceFill Alpha="255" Colors="-16777077,-16776961,-7278960,-256,-23296,-47872,-7667712" Values="0,2,4,6,8,10,15" Stretched="True" /> + <Contour On="False" Interval="5" Color="-16777216" /> + <MapParameters MapType="velocity" OutputMode="Dynamic Surface" ContourPolygonValue="0" ProfileIndex="2147483647" ProfileName="Max" ArrivalStartMode="0" Hours="True" /> + </Layer> + <Layer Name="elevation" Type="RASResultsMap"> + <SurfaceFill Alpha="255" Colors="-8388864,-16744448,-256,-23296,-65536,-16181,-65281" Values="0,16.6666666666667,33.3333333333333,50,66.6666666666667,83.3333333333333,100" Stretched="True" /> + <Contour On="False" Interval="5" Color="-16777216" /> + <MapParameters MapType="elevation" OutputMode="Dynamic Surface" ContourPolygonValue="0" ProfileIndex="2147483647" ProfileName="Max" ArrivalStartMode="0" Hours="True" /> + </Layer> + </Layer> + <Layer Name="BaseCase03" Type="RASResults" Filename=".\HEC-RASFlumeCase.p03.hdf"> + <Layer Name="Geometry" Type="RASGeometry" Filename=".\HEC-RASFlumeCase.p03.hdf"> + <Layer Name="Rivers" Type="RASRiver" /> + <Layer Name="XS" Type="RASXS" /> + <Layer Name="Storage Areas" Type="RASStorageArea" /> + <Layer Name="2D Flow Areas" Type="RASD2FlowArea" /> + <Layer Name="..." Type="RASMoreLayers" /> + </Layer> + <Layer Name="depth" Type="RASResultsMap"> + <SurfaceFill Alpha="255" Colors="-16711681,-16777077" Values="0,15" Stretched="True" /> + <Contour On="False" Interval="5" Color="-16777216" /> + <MapParameters MapType="depth" OutputMode="Dynamic Surface" ContourPolygonValue="0" ProfileIndex="2147483647" ProfileName="Max" ArrivalStartMode="0" Hours="True" /> + </Layer> + <Layer Name="velocity" Type="RASResultsMap"> + <SurfaceFill Alpha="255" Colors="-16777077,-16776961,-7278960,-256,-23296,-47872,-7667712" Values="0,2,4,6,8,10,15" Stretched="True" /> + <Contour On="False" Interval="5" Color="-16777216" /> + <MapParameters MapType="velocity" OutputMode="Dynamic Surface" ContourPolygonValue="0" ProfileIndex="2147483647" ProfileName="Max" ArrivalStartMode="0" Hours="True" /> + </Layer> + <Layer Name="elevation" Type="RASResultsMap"> + <SurfaceFill Alpha="255" Colors="-8388864,-16744448,-256,-23296,-65536,-16181,-65281" Values="0,16.6666666666667,33.3333333333333,50,66.6666666666667,83.3333333333333,100" Stretched="True" /> + <Contour On="False" Interval="5" Color="-16777216" /> + <MapParameters MapType="elevation" OutputMode="Dynamic Surface" ContourPolygonValue="0" ProfileIndex="2147483647" ProfileName="Max" ArrivalStartMode="0" Hours="True" /> + </Layer> + </Layer> + <Layer Name="BaseCase04" Type="RASResults" Filename=".\HEC-RASFlumeCase.p04.hdf"> + <Layer Name="Geometry" Type="RASGeometry" Filename=".\HEC-RASFlumeCase.p04.hdf"> + <Layer Name="Rivers" Type="RASRiver" /> + <Layer Name="XS" Type="RASXS" /> + <Layer Name="Storage Areas" Type="RASStorageArea" /> + <Layer Name="2D Flow Areas" Type="RASD2FlowArea" /> + <Layer Name="..." Type="RASMoreLayers" /> + </Layer> + <Layer Name="depth" Type="RASResultsMap"> + <SurfaceFill Alpha="255" Colors="-16711681,-16777077" Values="0,15" Stretched="True" /> + <Contour On="False" Interval="5" Color="-16777216" /> + <MapParameters MapType="depth" OutputMode="Dynamic Surface" ContourPolygonValue="0" ProfileIndex="2147483647" ProfileName="Max" ArrivalStartMode="0" Hours="True" /> + </Layer> + <Layer Name="velocity" Type="RASResultsMap"> + <SurfaceFill Alpha="255" Colors="-16777077,-16776961,-7278960,-256,-23296,-47872,-7667712" Values="0,2,4,6,8,10,15" Stretched="True" /> + <Contour On="False" Interval="5" Color="-16777216" /> + <MapParameters MapType="velocity" OutputMode="Dynamic Surface" ContourPolygonValue="0" ProfileIndex="2147483647" ProfileName="Max" ArrivalStartMode="0" Hours="True" /> + </Layer> + <Layer Name="elevation" Type="RASResultsMap"> + <SurfaceFill Alpha="255" Colors="-8388864,-16744448,-256,-23296,-65536,-16181,-65281" Values="0,16.6666666666667,33.3333333333333,50,66.6666666666667,83.3333333333333,100" Stretched="True" /> + <Contour On="False" Interval="5" Color="-16777216" /> + <MapParameters MapType="elevation" OutputMode="Dynamic Surface" ContourPolygonValue="0" ProfileIndex="2147483647" ProfileName="Max" ArrivalStartMode="0" Hours="True" /> + </Layer> + </Layer> + <Layer Name="Unsteady" Type="RASResults" Expanded="True" Selected="True" Filename=".\HEC-RASFlumeCase.p05.hdf"> + <Layer Name="Geometry" Type="RASGeometry" Filename=".\HEC-RASFlumeCase.p05.hdf"> + <Layer Name="Rivers" Type="RASRiver" /> + <Layer Name="XS" Type="RASXS" /> + <Layer Name="Storage Areas" Type="RASStorageArea" /> + <Layer Name="2D Flow Areas" Type="RASD2FlowArea" /> + <Layer Name="..." Type="RASMoreLayers" /> + </Layer> + <Layer Name="depth" Type="RASResultsMap"> + <SurfaceFill Alpha="255" Colors="-16711681,-16777077" Values="0,15" Stretched="True" /> + <Contour On="False" Interval="5" Color="-16777216" /> + <MapParameters MapType="depth" OutputMode="Dynamic Surface" ContourPolygonValue="0" ProfileIndex="2147483647" ProfileName="Max" ArrivalStartMode="0" Hours="True" /> + </Layer> + <Layer Name="velocity" Type="RASResultsMap"> + <SurfaceFill Alpha="255" Colors="-16777077,-16776961,-7278960,-256,-23296,-47872,-7667712" Values="0,2,4,6,8,10,15" Stretched="True" /> + <Contour On="False" Interval="5" Color="-16777216" /> + <MapParameters MapType="velocity" OutputMode="Dynamic Surface" ContourPolygonValue="0" ProfileIndex="2147483647" ProfileName="Max" ArrivalStartMode="0" Hours="True" /> + </Layer> + <Layer Name="elevation" Type="RASResultsMap"> + <SurfaceFill Alpha="255" Colors="-8388864,-16744448,-256,-23296,-65536,-16181,-65281" Values="100.0166015625,102.104797363281,104.192993164063,106.281188964844,108.369384765625,110.457580566406,112.545776367188" Stretched="True" /> + <Contour On="False" Interval="5" Color="-16777216" /> + <MapParameters MapType="elevation" OutputMode="Dynamic Surface" ContourPolygonValue="0" ProfileIndex="2147483647" ProfileName="Max" ArrivalStartMode="0" Hours="True" /> + </Layer> + </Layer> + </Results> + <MapLayers /> + <Terrains /> + <CurrentView> + <MaxX>1.06769596199525</MaxX> + <MinX>0.0676959619952494</MinX> + <MaxY>0.989311163895487</MaxY> + <MinY>-0.010688836104513</MinY> + </CurrentView> + <VelocitySettings> + <Density>1.5</Density> + <Lifetime>100</Lifetime> + <Radius>0.75</Radius> + <Method>2</Method> + <Timestep>1</Timestep> + <StaticColor>Black</StaticColor> + </VelocitySettings> + <AnimationSettings> + <DelayTimer>0</DelayTimer> + </AnimationSettings> + <ProjectSettings> + <Units>US Customary</Units> + </ProjectSettings> + <CurrentSettings> + <Folders /> + </CurrentSettings> +</RASMapper> \ No newline at end of file diff --git a/test/test_transporter.py b/test/test_transporter.py new file mode 100644 index 0000000..ef37a92 --- /dev/null +++ b/test/test_transporter.py @@ -0,0 +1,9 @@ +import unittest + +from fluegg.transporter import * + +class TestMaxTimeStep(unittest.TestCase): + + def test_time_step(self): + + \ No newline at end of file -- GitLab From f65e5d20e93856fc3cf4a6f484eb2aa5dd212ffa Mon Sep 17 00:00:00 2001 From: "Berutti, Michael (Contractor) Charles" <mberutti@contractor.usgs.gov> Date: Wed, 7 Aug 2019 17:56:17 +0000 Subject: [PATCH 4/7] Revert "Refined HDF5 tests and added Nonrandom Numbers tests" This reverts commit 3ce334392abbe227fbae3aa920c10ebb9b46ed5b --- test/test_random.py | 63 +++++++-------------------------------------- 1 file changed, 9 insertions(+), 54 deletions(-) diff --git a/test/test_random.py b/test/test_random.py index b78ea76..f721f5d 100644 --- a/test/test_random.py +++ b/test/test_random.py @@ -76,24 +76,7 @@ class TestNormalRandomNumbers(unittest.TestCase): class TestNonRandomNumbers(unittest.TestCase): - def test_non_random_numbers(self): - - self.assertEqual(NonRandomNumbers().random([5], 1), [5]) - - with self.assertRaises(TypeError): - NonRandomNumbers().random(5) - - with self.assertRaises(TypeError): - NonRandomNumbers().random(5, 1, 5) - - with self.assertRaises(TypeError): - NonRandomNumbers().random_array(5) - - with self.assertRaises(TypeError): - NonRandomNumbers().random_array(5, 1) - - with self.assertRaises(TypeError): - NonRandomNumbers().random_array(5, 1, 5, 1) + pass class TestHDF5NormalRandomNumbers(unittest.TestCase): @@ -102,18 +85,10 @@ class TestHDF5NormalRandomNumbers(unittest.TestCase): self._remove_test_saves() - def _average(self, numbers): - - sum = 0 - for number in numbers: - sum += number - return float(sum) / len(numbers) - def _create_HDF5_file(self): with h5py.File('UNIT TEST HDF5 TEST FILE.hdf', 'w') as f: - arr = np.random.normal(0, 1, 1000) - f.create_dataset('TEST DATA SET', data=arr) + f.create_dataset('TEST DATA SET', (100,)) def _get_file_path(self): @@ -129,7 +104,8 @@ class TestHDF5NormalRandomNumbers(unittest.TestCase): os.remove(r'.\results\{}'.format(file)) def test_HDF5_input(self): - + ''' Needs way to validate the results + ''' self._create_HDF5_file() file_path = self._get_file_path() arr = np.random.normal(25, 50, 100) @@ -156,36 +132,15 @@ class TestHDF5NormalRandomNumbers(unittest.TestCase): file_path, 'TEST DATA SET').random( arr, 70) - def test_HDF5_array_output_dimensions(self): - - self._create_HDF5_file() - file_path = self._get_file_path() - numbers = HDF5NormalRandomNumbers( - file_path, 'TEST DATA SET').random_array( - 0, 70, 100) - - self.assertEqual(len(numbers), 100) - - def test_HDF5_array_output_value(self): - + def test_HDF5_array(self): + ''' Needs way to validate the results + ''' self._create_HDF5_file() file_path = self._get_file_path() + arr = np.random.normal(25, 50, 100) numbers = HDF5NormalRandomNumbers( file_path, 'TEST DATA SET').random_array( - 0, 1, 100) - avg = self._average(numbers) - - self.assertTrue(-1 < avg < 1) - - def test_HDF5_array_size(self): - - self._create_HDF5_file() - file_path = self._get_file_path() - - with self.assertRaises(ValueError): - numbers = HDF5NormalRandomNumbers( - file_path, 'TEST DATA SET').random_array( - 0, 70, 2500) + arr, 70, 100) def tearDown(self): -- GitLab From 62f5342004e40b4c8bb713f84733c34316fb2cf8 Mon Sep 17 00:00:00 2001 From: Berutti <mberutti@contractor.usgs.gov> Date: Wed, 7 Aug 2019 13:04:10 -0500 Subject: [PATCH 5/7] Removed other files. --- coverage_report/coverage_html.js | 584 -- coverage_report/fluegg___init___py.html | 89 - coverage_report/fluegg_asiancarpeggs_py.html | 1305 --- coverage_report/fluegg_drift_py.html | 393 - coverage_report/fluegg_gui___init___py.html | 89 - coverage_report/fluegg_gui_gui_layout_py.html | 665 -- coverage_report/fluegg_gui_gui_py.html | 923 --- .../fluegg_gui_hecras_dialog_py.html | 337 - coverage_report/fluegg_hydraulics_py.html | 1883 ----- coverage_report/fluegg_kml_py.html | 907 -- coverage_report/fluegg_random_py.html | 271 - coverage_report/fluegg_ras_py.html | 1007 --- coverage_report/fluegg_simclock_py.html | 361 - coverage_report/fluegg_simulation_py.html | 723 -- coverage_report/fluegg_transporter_py.html | 1809 ---- coverage_report/index.html | 230 - .../jquery.ba-throttle-debounce.min.js | 9 - coverage_report/jquery.hotkeys.js | 99 - coverage_report/jquery.isonscreen.js | 53 - coverage_report/jquery.min.js | 4 - coverage_report/jquery.tablesorter.min.js | 2 - coverage_report/keybd_closed.png | Bin 112 -> 0 bytes coverage_report/keybd_open.png | Bin 112 -> 0 bytes coverage_report/status.json | 1 - coverage_report/style.css | 375 - coverage_report/test_fluegg_py.html | 165 - notebooks/asian carp eggs.ipynb | 98 - notebooks/fall velocity discrepancy.ipynb | 292 - notebooks/fluegg-tutorial-steady-ras.ipynb | 510 -- notebooks/fluegg-tutorial.ipynb | 485 -- notebooks/hydraulic model.ipynb | 300 - notebooks/lateral transporter.ipynb | 339 - notebooks/longitudinal transporter.ipynb | 326 - notebooks/mean velocity test.ipynb | 479 -- notebooks/nonrandom constant particle.ipynb | 259 - notebooks/nonrandom single egg.ipynb | 259 - notebooks/ras.ipynb | 311 - .../reverse longitudinal transporter.ipynb | 326 - notebooks/reverse simulation clock.ipynb | 7353 ----------------- notebooks/reverse simulation.ipynb | 361 - 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left: koff.left-poff.left - }); - }); - $("#panel_icon").click(function () { - $(".help_panel").hide(); - }); -}; - -// Create the events for the filter box. -coverage.wire_up_filter = function () { - // Cache elements. - var table = $("table.index"); - var table_rows = table.find("tbody tr"); - var table_row_names = table_rows.find("td.name a"); - var no_rows = $("#no_rows"); - - // Create a duplicate table footer that we can modify with dynamic summed values. - var table_footer = $("table.index tfoot tr"); - var table_dynamic_footer = table_footer.clone(); - table_dynamic_footer.attr('class', 'total_dynamic hidden'); - table_footer.after(table_dynamic_footer); - - // Observe filter keyevents. - $("#filter").on("keyup change", $.debounce(150, function (event) { - var filter_value = $(this).val(); - - if (filter_value === "") { - // Filter box is empty, remove all filtering. - table_rows.removeClass("hidden"); - - // Show standard footer, hide dynamic footer. - table_footer.removeClass("hidden"); - table_dynamic_footer.addClass("hidden"); - - // Hide placeholder, show table. - if (no_rows.length > 0) { - no_rows.hide(); - } - table.show(); - - } - else { - // Filter table items by value. - var hidden = 0; - var shown = 0; - - // Hide / show elements. - $.each(table_row_names, function () { - var element = $(this).parents("tr"); - - if ($(this).text().indexOf(filter_value) === -1) { - // hide - element.addClass("hidden"); - hidden++; - } - else { - // show - element.removeClass("hidden"); - shown++; - } - }); - - // Show placeholder if no rows will be displayed. - if (no_rows.length > 0) { - if (shown === 0) { - // Show placeholder, hide table. - no_rows.show(); - table.hide(); - } - else { - // Hide placeholder, show table. - no_rows.hide(); - table.show(); - } - } - - // Manage dynamic header: - if (hidden > 0) { - // Calculate new dynamic sum values based on visible rows. - for (var column = 2; column < 20; column++) { - // Calculate summed value. - var cells = table_rows.find('td:nth-child(' + column + ')'); - 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probe = lineno; - color = the_color; - while (color === the_color) { - probe++; - probe_line = c.line_elt(probe); - color = probe_line.css("background-color"); - } - - coverage.set_sel(begin, probe); - } - else { - coverage.set_sel(lineno); - } -}; - -coverage.show_selection = function () { - var c = coverage; - - // Highlight the lines in the chunk - c.code_container().find(".highlight").removeClass("highlight"); - for (var probe = c.sel_begin; probe > 0 && probe < c.sel_end; probe++) { - c.num_elt(probe).addClass("highlight"); - } - - c.scroll_to_selection(); -}; - -coverage.scroll_to_selection = function () { - // Scroll the page if the chunk isn't fully visible. - if (coverage.selection_ends_on_screen() < 2) { - // Need to move the page. The html,body trick makes it scroll in all - // browsers, got it from http://stackoverflow.com/questions/3042651 - var top = coverage.line_elt(coverage.sel_begin); - var top_pos = parseInt(top.offset().top, 10); - coverage.scroll_window(top_pos - 30); - } -}; - -coverage.scroll_window = function (to_pos) { - $("html,body").animate({scrollTop: to_pos}, 200); -}; - -coverage.finish_scrolling = function () { - $("html,body").stop(true, true); -}; - -coverage.init_scroll_markers = function () { - var c = coverage; - // Init some variables - c.lines_len = $('td.text p').length; - c.body_h = $('body').height(); - c.header_h = $('div#header').height(); - c.missed_lines = $('td.text p.mis, td.text p.par'); - - // Build html - c.resize_scroll_markers(); -}; - -coverage.resize_scroll_markers = function () { - var c = coverage, - min_line_height = 3, - max_line_height = 10, - visible_window_h = $(window).height(); - - $('#scroll_marker').remove(); - // Don't build markers if the window has no scroll bar. - if (c.body_h <= visible_window_h) { - return; - } - - $("body").append("<div id='scroll_marker'> </div>"); - var scroll_marker = $('#scroll_marker'), - marker_scale = scroll_marker.height() / c.body_h, - line_height = scroll_marker.height() / c.lines_len; - - // Line height must be between the extremes. - if (line_height > min_line_height) { - if (line_height > max_line_height) { - line_height = max_line_height; - } - } - else { - line_height = min_line_height; - } - - var previous_line = -99, - last_mark, - last_top; - - c.missed_lines.each(function () { - var line_top = Math.round($(this).offset().top * marker_scale), - id_name = $(this).attr('id'), - line_number = parseInt(id_name.substring(1, id_name.length)); - - if (line_number === previous_line + 1) { - // If this solid missed block just make previous mark higher. - last_mark.css({ - 'height': line_top + line_height - last_top - }); - } - else { - // Add colored line in scroll_marker block. - scroll_marker.append('<div id="m' + line_number + '" class="marker"></div>'); - last_mark = $('#m' + line_number); - last_mark.css({ - 'height': line_height, - 'top': line_top - }); - last_top = line_top; - } - - previous_line = line_number; - }); -}; diff --git a/coverage_report/fluegg___init___py.html b/coverage_report/fluegg___init___py.html deleted file mode 100644 index 40a6073..0000000 --- a/coverage_report/fluegg___init___py.html +++ /dev/null @@ -1,89 +0,0 @@ - - - -<!DOCTYPE html> -<html> -<head> - <meta http-equiv="Content-Type" content="text/html; charset=utf-8"> - - - <meta http-equiv="X-UA-Compatible" content="IE=emulateIE7" /> - <title>Coverage for fluegg\__init__.py: 100%</title> - <link rel="stylesheet" href="style.css" type="text/css"> - - <script type="text/javascript" src="jquery.min.js"></script> - <script type="text/javascript" src="jquery.hotkeys.js"></script> - <script type="text/javascript" src="jquery.isonscreen.js"></script> - <script type="text/javascript" src="coverage_html.js"></script> - <script type="text/javascript"> - jQuery(document).ready(coverage.pyfile_ready); - </script> -</head> -<body class="pyfile"> - -<div id="header"> - <div class="content"> - <h1>Coverage for <b>fluegg\__init__.py</b> : - <span class="pc_cov">100%</span> - </h1> - - <img id="keyboard_icon" src="keybd_closed.png" alt="Show keyboard shortcuts" /> - - <h2 class="stats"> - 0 statements - <span class="run hide_run shortkey_r button_toggle_run">0 run</span> - <span class="mis shortkey_m button_toggle_mis">0 missing</span> - <span class="exc shortkey_x button_toggle_exc">0 excluded</span> - - - </h2> - </div> -</div> - -<div class="help_panel"> - <img id="panel_icon" src="keybd_open.png" alt="Hide keyboard shortcuts" /> - <p class="legend">Hot-keys on this page</p> - <div> - <p class="keyhelp"> - <span class="key">r</span> - <span class="key">m</span> - <span class="key">x</span> - <span class="key">p</span> toggle line displays - </p> - <p class="keyhelp"> - <span class="key">j</span> - <span class="key">k</span> next/prev highlighted chunk - </p> - <p class="keyhelp"> - <span class="key">0</span> (zero) top of page - </p> - <p class="keyhelp"> - <span class="key">1</span> (one) first highlighted chunk - </p> - </div> -</div> - -<div id="source"> - <table> - <tr> - <td class="linenos"> - - </td> - <td class="text"> - - </td> - </tr> - </table> -</div> - -<div id="footer"> - <div class="content"> - <p> - <a class="nav" href="index.html">« index</a> <a class="nav" href="https://coverage.readthedocs.io">coverage.py v4.5.3</a>, - created at 2019-07-09 15:15 - </p> - </div> -</div> - -</body> -</html> diff --git a/coverage_report/fluegg_asiancarpeggs_py.html b/coverage_report/fluegg_asiancarpeggs_py.html deleted file mode 100644 index 8838376..0000000 --- a/coverage_report/fluegg_asiancarpeggs_py.html +++ /dev/null @@ -1,1305 +0,0 @@ - - - -<!DOCTYPE html> -<html> -<head> - <meta http-equiv="Content-Type" content="text/html; charset=utf-8"> - - - <meta http-equiv="X-UA-Compatible" content="IE=emulateIE7" /> - <title>Coverage for fluegg\asiancarpeggs.py: 92%</title> - <link rel="stylesheet" href="style.css" type="text/css"> - - <script type="text/javascript" src="jquery.min.js"></script> - <script type="text/javascript" src="jquery.hotkeys.js"></script> - <script type="text/javascript" src="jquery.isonscreen.js"></script> - <script type="text/javascript" src="coverage_html.js"></script> - <script type="text/javascript"> - jQuery(document).ready(coverage.pyfile_ready); - </script> -</head> -<body class="pyfile"> - -<div id="header"> - <div class="content"> - <h1>Coverage for <b>fluegg\asiancarpeggs.py</b> : - <span class="pc_cov">92%</span> - </h1> - - <img id="keyboard_icon" src="keybd_closed.png" alt="Show keyboard shortcuts" /> - - <h2 class="stats"> - 226 statements - <span class="run hide_run shortkey_r button_toggle_run">209 run</span> - <span class="mis shortkey_m button_toggle_mis">17 missing</span> - <span class="exc shortkey_x button_toggle_exc">0 excluded</span> - - - </h2> - </div> -</div> - -<div class="help_panel"> - <img id="panel_icon" src="keybd_open.png" alt="Hide keyboard shortcuts" /> - <p class="legend">Hot-keys on this page</p> - <div> - <p class="keyhelp"> - <span class="key">r</span> - <span class="key">m</span> - <span class="key">x</span> - <span class="key">p</span> toggle line displays - </p> - <p class="keyhelp"> - <span class="key">j</span> - <span class="key">k</span> next/prev highlighted chunk - </p> - <p class="keyhelp"> - <span class="key">0</span> (zero) top of page - </p> - <p class="keyhelp"> - <span class="key">1</span> (one) first highlighted chunk - </p> - </div> -</div> - -<div id="source"> - <table> - <tr> - <td class="linenos"> -<p id="n1" class="stm run hide_run"><a href="#n1">1</a></p> -<p id="n2" class="pln"><a href="#n2">2</a></p> -<p id="n3" class="stm run hide_run"><a href="#n3">3</a></p> -<p id="n4" class="pln"><a href="#n4">4</a></p> -<p id="n5" class="stm 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href="#n196">196</a></p> -<p id="n197" class="stm run hide_run"><a href="#n197">197</a></p> -<p id="n198" class="stm mis"><a href="#n198">198</a></p> -<p id="n199" class="stm run hide_run"><a href="#n199">199</a></p> -<p id="n200" class="stm run hide_run"><a href="#n200">200</a></p> -<p id="n201" class="stm run hide_run"><a href="#n201">201</a></p> -<p id="n202" class="pln"><a href="#n202">202</a></p> -<p id="n203" class="pln"><a href="#n203">203</a></p> -<p id="n204" class="stm run hide_run"><a href="#n204">204</a></p> -<p id="n205" class="pln"><a href="#n205">205</a></p> -<p id="n206" class="pln"><a href="#n206">206</a></p> -<p id="n207" class="pln"><a href="#n207">207</a></p> -<p id="n208" class="pln"><a href="#n208">208</a></p> -<p id="n209" class="pln"><a href="#n209">209</a></p> -<p id="n210" class="pln"><a href="#n210">210</a></p> -<p id="n211" class="pln"><a href="#n211">211</a></p> -<p id="n212" class="stm run hide_run"><a href="#n212">212</a></p> -<p id="n213" class="pln"><a href="#n213">213</a></p> -<p id="n214" class="stm run hide_run"><a href="#n214">214</a></p> -<p id="n215" class="pln"><a href="#n215">215</a></p> -<p id="n216" class="stm run hide_run"><a href="#n216">216</a></p> -<p id="n217" class="pln"><a href="#n217">217</a></p> -<p id="n218" class="pln"><a href="#n218">218</a></p> -<p id="n219" class="pln"><a href="#n219">219</a></p> -<p id="n220" class="pln"><a href="#n220">220</a></p> -<p id="n221" class="pln"><a href="#n221">221</a></p> -<p id="n222" class="pln"><a href="#n222">222</a></p> -<p id="n223" class="pln"><a href="#n223">223</a></p> -<p id="n224" class="pln"><a href="#n224">224</a></p> -<p id="n225" class="pln"><a href="#n225">225</a></p> -<p id="n226" class="pln"><a href="#n226">226</a></p> -<p id="n227" class="pln"><a href="#n227">227</a></p> -<p id="n228" class="pln"><a href="#n228">228</a></p> -<p id="n229" class="pln"><a href="#n229">229</a></p> -<p id="n230" class="stm mis"><a href="#n230">230</a></p> -<p id="n231" class="stm mis"><a href="#n231">231</a></p> -<p id="n232" class="pln"><a href="#n232">232</a></p> -<p id="n233" class="stm mis"><a href="#n233">233</a></p> -<p id="n234" class="pln"><a href="#n234">234</a></p> -<p id="n235" class="stm mis"><a href="#n235">235</a></p> -<p id="n236" class="pln"><a href="#n236">236</a></p> -<p id="n237" class="stm run hide_run"><a href="#n237">237</a></p> -<p id="n238" class="stm run hide_run"><a href="#n238">238</a></p> -<p id="n239" class="stm run hide_run"><a href="#n239">239</a></p> -<p id="n240" class="stm mis"><a href="#n240">240</a></p> -<p id="n241" class="pln"><a href="#n241">241</a></p> -<p id="n242" class="stm run hide_run"><a href="#n242">242</a></p> -<p id="n243" class="stm run hide_run"><a href="#n243">243</a></p> -<p id="n244" class="stm run hide_run"><a href="#n244">244</a></p> -<p id="n245" class="stm mis"><a href="#n245">245</a></p> -<p id="n246" class="pln"><a href="#n246">246</a></p> -<p id="n247" class="stm run hide_run"><a href="#n247">247</a></p> -<p id="n248" class="pln"><a href="#n248">248</a></p> -<p id="n249" class="pln"><a href="#n249">249</a></p> -<p id="n250" class="pln"><a href="#n250">250</a></p> -<p id="n251" class="pln"><a href="#n251">251</a></p> -<p id="n252" class="pln"><a href="#n252">252</a></p> -<p id="n253" class="pln"><a href="#n253">253</a></p> -<p id="n254" class="pln"><a href="#n254">254</a></p> -<p id="n255" class="pln"><a href="#n255">255</a></p> -<p id="n256" class="pln"><a href="#n256">256</a></p> -<p id="n257" class="stm run hide_run"><a href="#n257">257</a></p> -<p id="n258" class="pln"><a href="#n258">258</a></p> -<p id="n259" class="stm run hide_run"><a href="#n259">259</a></p> -<p id="n260" class="pln"><a href="#n260">260</a></p> -<p id="n261" class="pln"><a href="#n261">261</a></p> -<p id="n262" class="pln"><a href="#n262">262</a></p> -<p id="n263" class="pln"><a href="#n263">263</a></p> -<p id="n264" class="pln"><a href="#n264">264</a></p> -<p id="n265" class="stm run hide_run"><a href="#n265">265</a></p> -<p id="n266" class="pln"><a href="#n266">266</a></p> -<p id="n267" class="pln"><a href="#n267">267</a></p> -<p id="n268" class="stm run hide_run"><a href="#n268">268</a></p> -<p id="n269" class="pln"><a href="#n269">269</a></p> -<p id="n270" class="pln"><a href="#n270">270</a></p> -<p id="n271" class="pln"><a href="#n271">271</a></p> -<p id="n272" class="pln"><a href="#n272">272</a></p> -<p id="n273" class="pln"><a href="#n273">273</a></p> -<p id="n274" class="pln"><a href="#n274">274</a></p> -<p id="n275" class="stm run hide_run"><a href="#n275">275</a></p> -<p id="n276" class="pln"><a href="#n276">276</a></p> -<p id="n277" class="pln"><a href="#n277">277</a></p> -<p id="n278" class="pln"><a href="#n278">278</a></p> -<p id="n279" class="pln"><a href="#n279">279</a></p> -<p id="n280" class="pln"><a href="#n280">280</a></p> -<p id="n281" class="pln"><a href="#n281">281</a></p> -<p id="n282" class="pln"><a href="#n282">282</a></p> -<p id="n283" class="pln"><a href="#n283">283</a></p> -<p id="n284" class="stm run hide_run"><a href="#n284">284</a></p> -<p id="n285" class="stm run hide_run"><a href="#n285">285</a></p> -<p id="n286" class="stm run hide_run"><a href="#n286">286</a></p> -<p id="n287" class="stm run hide_run"><a href="#n287">287</a></p> -<p id="n288" class="pln"><a href="#n288">288</a></p> -<p id="n289" class="stm run hide_run"><a href="#n289">289</a></p> -<p id="n290" class="pln"><a href="#n290">290</a></p> -<p id="n291" class="pln"><a href="#n291">291</a></p> -<p id="n292" class="pln"><a href="#n292">292</a></p> -<p id="n293" class="pln"><a href="#n293">293</a></p> -<p id="n294" class="pln"><a href="#n294">294</a></p> -<p id="n295" class="pln"><a href="#n295">295</a></p> -<p id="n296" class="pln"><a href="#n296">296</a></p> -<p id="n297" class="pln"><a href="#n297">297</a></p> -<p id="n298" class="stm run hide_run"><a href="#n298">298</a></p> -<p id="n299" class="stm run hide_run"><a href="#n299">299</a></p> -<p id="n300" class="stm run hide_run"><a href="#n300">300</a></p> -<p id="n301" class="stm run hide_run"><a href="#n301">301</a></p> -<p id="n302" class="pln"><a href="#n302">302</a></p> -<p id="n303" class="stm run hide_run"><a href="#n303">303</a></p> -<p id="n304" class="pln"><a href="#n304">304</a></p> -<p id="n305" class="pln"><a href="#n305">305</a></p> -<p id="n306" class="pln"><a href="#n306">306</a></p> -<p id="n307" class="pln"><a href="#n307">307</a></p> -<p id="n308" class="pln"><a href="#n308">308</a></p> -<p id="n309" class="pln"><a href="#n309">309</a></p> -<p id="n310" class="pln"><a href="#n310">310</a></p> -<p id="n311" class="stm run hide_run"><a href="#n311">311</a></p> -<p id="n312" class="stm run hide_run"><a href="#n312">312</a></p> -<p id="n313" class="stm run hide_run"><a href="#n313">313</a></p> -<p id="n314" class="stm run hide_run"><a href="#n314">314</a></p> -<p id="n315" class="pln"><a href="#n315">315</a></p> -<p id="n316" class="stm run hide_run"><a href="#n316">316</a></p> -<p id="n317" class="pln"><a href="#n317">317</a></p> -<p id="n318" class="pln"><a href="#n318">318</a></p> -<p id="n319" class="pln"><a href="#n319">319</a></p> -<p id="n320" class="pln"><a href="#n320">320</a></p> -<p id="n321" class="pln"><a href="#n321">321</a></p> -<p id="n322" class="pln"><a href="#n322">322</a></p> -<p id="n323" class="pln"><a href="#n323">323</a></p> -<p id="n324" class="stm run hide_run"><a href="#n324">324</a></p> -<p id="n325" class="stm run hide_run"><a href="#n325">325</a></p> -<p id="n326" class="stm run hide_run"><a href="#n326">326</a></p> -<p id="n327" class="pln"><a href="#n327">327</a></p> -<p id="n328" class="stm run hide_run"><a href="#n328">328</a></p> -<p id="n329" class="pln"><a href="#n329">329</a></p> -<p id="n330" class="pln"><a href="#n330">330</a></p> -<p id="n331" class="pln"><a href="#n331">331</a></p> -<p id="n332" class="pln"><a href="#n332">332</a></p> -<p id="n333" class="pln"><a href="#n333">333</a></p> -<p id="n334" class="pln"><a href="#n334">334</a></p> -<p id="n335" class="pln"><a href="#n335">335</a></p> -<p id="n336" class="stm run hide_run"><a href="#n336">336</a></p> -<p id="n337" class="stm run hide_run"><a href="#n337">337</a></p> -<p id="n338" class="stm run hide_run"><a href="#n338">338</a></p> -<p id="n339" class="stm run hide_run"><a href="#n339">339</a></p> -<p id="n340" class="pln"><a href="#n340">340</a></p> -<p id="n341" class="stm run hide_run"><a href="#n341">341</a></p> -<p id="n342" class="pln"><a href="#n342">342</a></p> -<p id="n343" class="pln"><a href="#n343">343</a></p> -<p id="n344" class="pln"><a href="#n344">344</a></p> -<p id="n345" class="pln"><a href="#n345">345</a></p> -<p id="n346" class="pln"><a href="#n346">346</a></p> -<p id="n347" class="pln"><a href="#n347">347</a></p> -<p id="n348" class="pln"><a href="#n348">348</a></p> -<p id="n349" class="stm run hide_run"><a href="#n349">349</a></p> -<p id="n350" class="stm run hide_run"><a href="#n350">350</a></p> -<p id="n351" class="stm run hide_run"><a href="#n351">351</a></p> -<p id="n352" class="stm run hide_run"><a href="#n352">352</a></p> -<p id="n353" class="pln"><a href="#n353">353</a></p> -<p id="n354" class="stm run hide_run"><a href="#n354">354</a></p> -<p id="n355" class="stm run hide_run"><a href="#n355">355</a></p> -<p id="n356" class="pln"><a href="#n356">356</a></p> -<p id="n357" class="pln"><a href="#n357">357</a></p> -<p id="n358" class="pln"><a href="#n358">358</a></p> -<p id="n359" class="pln"><a href="#n359">359</a></p> -<p id="n360" class="pln"><a href="#n360">360</a></p> -<p id="n361" class="pln"><a href="#n361">361</a></p> -<p id="n362" class="stm run hide_run"><a href="#n362">362</a></p> -<p id="n363" class="stm run hide_run"><a href="#n363">363</a></p> -<p id="n364" class="pln"><a href="#n364">364</a></p> -<p id="n365" class="stm run hide_run"><a href="#n365">365</a></p> -<p id="n366" class="pln"><a href="#n366">366</a></p> -<p id="n367" class="pln"><a href="#n367">367</a></p> -<p id="n368" class="stm run hide_run"><a href="#n368">368</a></p> -<p id="n369" class="stm run hide_run"><a href="#n369">369</a></p> -<p id="n370" class="pln"><a href="#n370">370</a></p> -<p id="n371" class="pln"><a href="#n371">371</a></p> -<p id="n372" class="pln"><a href="#n372">372</a></p> -<p id="n373" class="pln"><a href="#n373">373</a></p> -<p id="n374" class="pln"><a href="#n374">374</a></p> -<p id="n375" class="pln"><a href="#n375">375</a></p> -<p id="n376" class="pln"><a href="#n376">376</a></p> -<p id="n377" class="pln"><a href="#n377">377</a></p> -<p id="n378" class="pln"><a href="#n378">378</a></p> -<p id="n379" class="pln"><a href="#n379">379</a></p> -<p id="n380" class="stm run hide_run"><a href="#n380">380</a></p> -<p id="n381" class="stm run hide_run"><a href="#n381">381</a></p> -<p id="n382" class="stm run hide_run"><a href="#n382">382</a></p> -<p id="n383" class="pln"><a href="#n383">383</a></p> -<p id="n384" class="stm run hide_run"><a href="#n384">384</a></p> -<p id="n385" class="pln"><a href="#n385">385</a></p> -<p id="n386" class="pln"><a href="#n386">386</a></p> -<p id="n387" class="stm run hide_run"><a href="#n387">387</a></p> -<p id="n388" class="pln"><a href="#n388">388</a></p> -<p id="n389" class="pln"><a href="#n389">389</a></p> -<p id="n390" class="pln"><a href="#n390">390</a></p> -<p id="n391" class="pln"><a href="#n391">391</a></p> -<p id="n392" class="pln"><a href="#n392">392</a></p> -<p id="n393" class="pln"><a href="#n393">393</a></p> -<p id="n394" class="stm run hide_run"><a href="#n394">394</a></p> -<p id="n395" class="pln"><a href="#n395">395</a></p> -<p id="n396" class="pln"><a href="#n396">396</a></p> -<p id="n397" class="pln"><a href="#n397">397</a></p> -<p id="n398" class="pln"><a href="#n398">398</a></p> -<p id="n399" class="pln"><a href="#n399">399</a></p> -<p id="n400" class="pln"><a href="#n400">400</a></p> -<p id="n401" class="pln"><a href="#n401">401</a></p> -<p id="n402" class="pln"><a href="#n402">402</a></p> -<p id="n403" class="stm run hide_run"><a href="#n403">403</a></p> -<p id="n404" class="stm run hide_run"><a href="#n404">404</a></p> -<p id="n405" class="stm run hide_run"><a href="#n405">405</a></p> -<p id="n406" class="stm run hide_run"><a href="#n406">406</a></p> -<p id="n407" class="pln"><a href="#n407">407</a></p> -<p id="n408" class="stm run hide_run"><a href="#n408">408</a></p> -<p id="n409" class="pln"><a href="#n409">409</a></p> -<p id="n410" class="pln"><a href="#n410">410</a></p> -<p id="n411" class="pln"><a href="#n411">411</a></p> -<p id="n412" class="pln"><a href="#n412">412</a></p> -<p id="n413" class="pln"><a href="#n413">413</a></p> -<p id="n414" class="pln"><a href="#n414">414</a></p> -<p id="n415" class="pln"><a href="#n415">415</a></p> -<p id="n416" class="pln"><a href="#n416">416</a></p> -<p id="n417" class="stm run hide_run"><a href="#n417">417</a></p> -<p id="n418" class="stm run hide_run"><a href="#n418">418</a></p> -<p id="n419" class="stm run hide_run"><a href="#n419">419</a></p> -<p id="n420" class="stm run hide_run"><a href="#n420">420</a></p> -<p id="n421" class="pln"><a href="#n421">421</a></p> -<p id="n422" class="stm run hide_run"><a href="#n422">422</a></p> -<p id="n423" class="pln"><a href="#n423">423</a></p> -<p id="n424" class="pln"><a href="#n424">424</a></p> -<p id="n425" class="pln"><a href="#n425">425</a></p> -<p id="n426" class="pln"><a href="#n426">426</a></p> -<p id="n427" class="pln"><a href="#n427">427</a></p> -<p id="n428" class="pln"><a href="#n428">428</a></p> -<p id="n429" class="pln"><a href="#n429">429</a></p> -<p id="n430" class="stm run hide_run"><a href="#n430">430</a></p> -<p id="n431" class="stm run hide_run"><a href="#n431">431</a></p> -<p id="n432" class="stm run hide_run"><a href="#n432">432</a></p> -<p id="n433" class="stm run hide_run"><a href="#n433">433</a></p> -<p id="n434" class="pln"><a href="#n434">434</a></p> -<p id="n435" class="stm run hide_run"><a href="#n435">435</a></p> -<p id="n436" class="pln"><a href="#n436">436</a></p> -<p id="n437" class="pln"><a href="#n437">437</a></p> -<p id="n438" class="pln"><a href="#n438">438</a></p> -<p id="n439" class="pln"><a href="#n439">439</a></p> -<p id="n440" class="pln"><a href="#n440">440</a></p> -<p id="n441" class="pln"><a href="#n441">441</a></p> -<p id="n442" class="pln"><a href="#n442">442</a></p> -<p id="n443" class="stm run hide_run"><a href="#n443">443</a></p> -<p id="n444" class="stm run hide_run"><a href="#n444">444</a></p> -<p id="n445" class="stm run hide_run"><a href="#n445">445</a></p> -<p id="n446" class="pln"><a href="#n446">446</a></p> -<p id="n447" class="stm run hide_run"><a href="#n447">447</a></p> -<p id="n448" class="pln"><a href="#n448">448</a></p> -<p id="n449" class="pln"><a href="#n449">449</a></p> -<p id="n450" class="pln"><a href="#n450">450</a></p> -<p id="n451" class="pln"><a href="#n451">451</a></p> -<p id="n452" class="pln"><a href="#n452">452</a></p> -<p id="n453" class="pln"><a href="#n453">453</a></p> -<p id="n454" class="pln"><a href="#n454">454</a></p> -<p id="n455" class="stm run hide_run"><a href="#n455">455</a></p> -<p id="n456" class="stm run hide_run"><a href="#n456">456</a></p> -<p id="n457" class="stm run hide_run"><a href="#n457">457</a></p> -<p id="n458" class="stm run hide_run"><a href="#n458">458</a></p> -<p id="n459" class="pln"><a href="#n459">459</a></p> -<p id="n460" class="stm run hide_run"><a href="#n460">460</a></p> -<p id="n461" class="pln"><a href="#n461">461</a></p> -<p id="n462" class="pln"><a href="#n462">462</a></p> -<p id="n463" class="pln"><a href="#n463">463</a></p> -<p id="n464" class="pln"><a href="#n464">464</a></p> -<p id="n465" class="pln"><a href="#n465">465</a></p> -<p id="n466" class="pln"><a href="#n466">466</a></p> -<p id="n467" class="pln"><a href="#n467">467</a></p> -<p id="n468" class="stm run hide_run"><a href="#n468">468</a></p> -<p id="n469" class="stm run hide_run"><a href="#n469">469</a></p> -<p id="n470" class="stm run hide_run"><a href="#n470">470</a></p> -<p id="n471" class="stm run hide_run"><a href="#n471">471</a></p> -<p id="n472" class="pln"><a href="#n472">472</a></p> -<p id="n473" class="stm run hide_run"><a href="#n473">473</a></p> -<p id="n474" class="stm run hide_run"><a href="#n474">474</a></p> -<p id="n475" class="pln"><a href="#n475">475</a></p> -<p id="n476" class="stm run hide_run"><a href="#n476">476</a></p> -<p id="n477" class="stm run hide_run"><a href="#n477">477</a></p> -<p id="n478" class="pln"><a href="#n478">478</a></p> -<p id="n479" class="stm run hide_run"><a href="#n479">479</a></p> -<p id="n480" class="pln"><a href="#n480">480</a></p> -<p id="n481" class="pln"><a href="#n481">481</a></p> -<p id="n482" class="stm run hide_run"><a href="#n482">482</a></p> -<p id="n483" class="stm run hide_run"><a href="#n483">483</a></p> -<p id="n484" class="pln"><a href="#n484">484</a></p> -<p id="n485" class="pln"><a 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href="#n519">519</a></p> -<p id="n520" class="stm run hide_run"><a href="#n520">520</a></p> -<p id="n521" class="pln"><a href="#n521">521</a></p> -<p id="n522" class="pln"><a href="#n522">522</a></p> -<p id="n523" class="pln"><a href="#n523">523</a></p> -<p id="n524" class="pln"><a href="#n524">524</a></p> -<p id="n525" class="pln"><a href="#n525">525</a></p> -<p id="n526" class="pln"><a href="#n526">526</a></p> -<p id="n527" class="pln"><a href="#n527">527</a></p> -<p id="n528" class="pln"><a href="#n528">528</a></p> -<p id="n529" class="stm run hide_run"><a href="#n529">529</a></p> -<p id="n530" class="stm run hide_run"><a href="#n530">530</a></p> -<p id="n531" class="stm run hide_run"><a href="#n531">531</a></p> -<p id="n532" class="stm run hide_run"><a href="#n532">532</a></p> -<p id="n533" class="pln"><a href="#n533">533</a></p> -<p id="n534" class="stm run hide_run"><a href="#n534">534</a></p> -<p id="n535" class="pln"><a href="#n535">535</a></p> -<p id="n536" class="pln"><a href="#n536">536</a></p> -<p id="n537" class="pln"><a href="#n537">537</a></p> -<p id="n538" class="pln"><a href="#n538">538</a></p> -<p id="n539" class="pln"><a href="#n539">539</a></p> -<p id="n540" class="pln"><a href="#n540">540</a></p> -<p id="n541" class="pln"><a href="#n541">541</a></p> -<p id="n542" class="stm run hide_run"><a href="#n542">542</a></p> -<p id="n543" class="stm run hide_run"><a href="#n543">543</a></p> -<p id="n544" class="stm run hide_run"><a href="#n544">544</a></p> -<p id="n545" class="stm run hide_run"><a href="#n545">545</a></p> -<p id="n546" class="pln"><a href="#n546">546</a></p> -<p id="n547" class="stm run hide_run"><a href="#n547">547</a></p> -<p id="n548" class="pln"><a href="#n548">548</a></p> -<p id="n549" class="pln"><a href="#n549">549</a></p> -<p id="n550" class="pln"><a href="#n550">550</a></p> -<p id="n551" class="pln"><a href="#n551">551</a></p> -<p id="n552" class="pln"><a href="#n552">552</a></p> -<p id="n553" class="pln"><a href="#n553">553</a></p> -<p id="n554" class="pln"><a href="#n554">554</a></p> -<p id="n555" class="stm run hide_run"><a href="#n555">555</a></p> -<p id="n556" class="stm run hide_run"><a href="#n556">556</a></p> -<p id="n557" class="stm run hide_run"><a href="#n557">557</a></p> -<p id="n558" class="pln"><a href="#n558">558</a></p> -<p id="n559" class="stm run hide_run"><a href="#n559">559</a></p> -<p id="n560" class="pln"><a href="#n560">560</a></p> -<p id="n561" class="pln"><a href="#n561">561</a></p> -<p id="n562" class="pln"><a href="#n562">562</a></p> -<p id="n563" class="pln"><a href="#n563">563</a></p> -<p id="n564" class="pln"><a href="#n564">564</a></p> -<p id="n565" class="pln"><a href="#n565">565</a></p> -<p id="n566" class="pln"><a href="#n566">566</a></p> -<p id="n567" class="stm run hide_run"><a href="#n567">567</a></p> -<p id="n568" class="stm run hide_run"><a href="#n568">568</a></p> -<p id="n569" class="stm run hide_run"><a href="#n569">569</a></p> -<p id="n570" class="stm run hide_run"><a href="#n570">570</a></p> -<p id="n571" class="pln"><a href="#n571">571</a></p> -<p id="n572" class="stm run hide_run"><a href="#n572">572</a></p> -<p id="n573" class="pln"><a href="#n573">573</a></p> -<p id="n574" class="pln"><a href="#n574">574</a></p> -<p id="n575" class="pln"><a href="#n575">575</a></p> -<p id="n576" class="pln"><a href="#n576">576</a></p> -<p id="n577" class="pln"><a href="#n577">577</a></p> -<p id="n578" class="pln"><a href="#n578">578</a></p> -<p id="n579" class="pln"><a href="#n579">579</a></p> -<p id="n580" class="stm run hide_run"><a href="#n580">580</a></p> -<p id="n581" class="stm run hide_run"><a href="#n581">581</a></p> -<p id="n582" class="stm run hide_run"><a href="#n582">582</a></p> -<p id="n583" class="stm run hide_run"><a href="#n583">583</a></p> -<p id="n584" class="pln"><a href="#n584">584</a></p> -<p id="n585" class="stm run hide_run"><a href="#n585">585</a></p> -<p id="n586" class="stm run hide_run"><a href="#n586">586</a></p> -<p id="n587" class="pln"><a href="#n587">587</a></p> -<p id="n588" class="stm run hide_run"><a href="#n588">588</a></p> -<p id="n589" class="stm run hide_run"><a href="#n589">589</a></p> -<p id="n590" class="pln"><a href="#n590">590</a></p> -<p id="n591" class="stm run hide_run"><a href="#n591">591</a></p> -<p id="n592" class="pln"><a href="#n592">592</a></p> -<p id="n593" class="pln"><a href="#n593">593</a></p> -<p id="n594" class="stm run hide_run"><a href="#n594">594</a></p> -<p id="n595" class="stm run hide_run"><a href="#n595">595</a></p> -<p id="n596" class="pln"><a href="#n596">596</a></p> -<p id="n597" class="pln"><a href="#n597">597</a></p> -<p id="n598" class="pln"><a href="#n598">598</a></p> -<p id="n599" class="pln"><a href="#n599">599</a></p> -<p id="n600" class="pln"><a href="#n600">600</a></p> -<p id="n601" class="pln"><a href="#n601">601</a></p> -<p id="n602" class="pln"><a href="#n602">602</a></p> -<p id="n603" class="pln"><a href="#n603">603</a></p> -<p id="n604" class="pln"><a href="#n604">604</a></p> -<p id="n605" class="stm run hide_run"><a href="#n605">605</a></p> -<p id="n606" class="stm run hide_run"><a href="#n606">606</a></p> -<p id="n607" class="stm run hide_run"><a href="#n607">607</a></p> -<p id="n608" class="stm run hide_run"><a href="#n608">608</a></p> - - </td> - <td class="text"> -<p id="t1" class="stm run hide_run"><span class="key">from</span> <span class="nam">abc</span> <span class="key">import</span> <span class="nam">abstractmethod</span><span class="strut"> </span></p> -<p id="t2" class="pln"><span class="strut"> </span></p> -<p id="t3" class="stm run hide_run"><span class="key">import</span> <span class="nam">numpy</span> <span class="key">as</span> <span class="nam">np</span><span class="strut"> </span></p> -<p id="t4" class="pln"><span class="strut"> </span></p> -<p id="t5" class="stm run hide_run"><span class="key">from</span> <span class="nam">fluegg</span><span class="op">.</span><span class="nam">drift</span> <span class="key">import</span> <span class="nam">DriftingParticle</span><span class="strut"> </span></p> -<p id="t6" class="stm run hide_run"><span class="key">from</span> <span class="nam">fluegg</span><span class="op">.</span><span class="nam">random</span> <span class="key">import</span> <span class="nam">NormalRandomNumbers</span><span class="strut"> </span></p> -<p id="t7" class="pln"><span class="strut"> </span></p> -<p id="t8" class="pln"><span class="strut"> </span></p> -<p id="t9" class="stm run hide_run"><span class="key">class</span> <span class="nam">CarpEggs</span><span class="op">(</span><span class="nam">DriftingParticle</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t10" class="pln"> <span class="str">"""Class representing a collection of carp eggs</span><span class="strut"> </span></p> -<p id="t11" class="pln"><span class="strut"> </span></p> -<p id="t12" class="pln"><span class="str"> Parameters</span><span class="strut"> </span></p> -<p id="t13" class="pln"><span class="str"> ----------</span><span class="strut"> </span></p> -<p id="t14" class="pln"><span class="str"> initial_position : numpy.ndarray</span><span class="strut"> </span></p> -<p id="t15" class="pln"><span class="str"> Must be an n by 3 array, where n is the number of eggs</span><span class="strut"> </span></p> -<p id="t16" class="pln"><span class="strut"> </span></p> -<p id="t17" class="pln"><span class="str"> simulation_clock : simulation.SimulationClock</span><span class="strut"> </span></p> -<p id="t18" class="pln"><span class="str"> Simulation clock</span><span class="strut"> </span></p> -<p id="t19" class="pln"><span class="strut"> </span></p> -<p id="t20" class="pln"><span class="str"> random_numbers : fluegg.random.RandomNumbers, optional</span><span class="strut"> </span></p> -<p id="t21" class="pln"><span class="str"> Random number source</span><span class="strut"> </span></p> -<p id="t22" class="pln"><span class="strut"> </span></p> -<p id="t23" class="pln"><span class="str"> characteristic_temperature : float, optional</span><span class="strut"> </span></p> -<p id="t24" class="pln"><span class="str"> The default is None</span><span class="strut"> </span></p> -<p id="t25" class="pln"><span class="strut"> </span></p> -<p id="t26" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t27" class="pln"><span class="strut"> </span></p> -<p id="t28" class="stm run hide_run"> <span class="nam">_reference_temperature</span> <span class="op">=</span> <span class="num">22</span> <span class="com"># degrees Celsius</span><span class="strut"> </span></p> -<p id="t29" class="pln"><span class="strut"> </span></p> -<p id="t30" class="stm run hide_run"> <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">initial_position</span><span class="op">,</span> <span class="nam">simulation_clock</span><span class="op">,</span> <span class="nam">random_numbers</span><span class="op">=</span><span class="key">None</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t31" class="pln"> <span class="nam">characteristic_temperature</span><span class="op">=</span><span class="key">None</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t32" class="pln"><span class="strut"> </span></p> -<p id="t33" class="stm run hide_run"> <span class="key">if</span> <span class="nam">initial_position</span><span class="op">.</span><span class="nam">shape</span><span class="op">[</span><span class="num">1</span><span class="op">]</span> <span class="op">==</span> <span class="num">3</span> <span class="key">and</span> <span class="nam">initial_position</span><span class="op">.</span><span class="nam">ndim</span> <span class="op">==</span> <span class="num">2</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t34" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_position</span> <span class="op">=</span> <span class="nam">initial_position</span><span class="strut"> </span></p> -<p id="t35" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_number_of_eggs</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_position</span><span class="op">.</span><span class="nam">shape</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t36" class="pln"> <span class="key">else</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t37" class="stm run hide_run"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="str">'Initial position array must be n by 3'</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t38" class="pln"><span class="strut"> </span></p> -<p id="t39" class="stm run hide_run"> <span class="key">if</span> <span class="nam">random_numbers</span> <span class="key">is</span> <span class="key">None</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t40" class="stm run hide_run"> <span class="nam">random_numbers</span> <span class="op">=</span> <span class="nam">NormalRandomNumbers</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t41" class="pln"><span class="strut"> </span></p> -<p id="t42" class="pln"> <span class="com"># Note: Diameters internally stored in mm, diameter() outputs in m</span><span class="strut"> </span></p> -<p id="t43" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_simulation_clock</span> <span class="op">=</span> <span class="nam">simulation_clock</span><span class="strut"> </span></p> -<p id="t44" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_diameter_array</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_init_diameter_array</span><span class="op">(</span><span class="nam">random_numbers</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t45" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_reference_density_array</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_init_reference_density_array</span><span class="op">(</span><span class="strut"> </span></p> -<p id="t46" class="pln"> <span class="nam">random_numbers</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t47" class="pln"><span class="strut"> </span></p> -<p id="t48" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_hatching_time</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">hatching_time</span><span class="op">(</span><span class="nam">characteristic_temperature</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t49" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_gas_bladder_inflation_time</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">gas_bladder_inflation_time</span><span class="op">(</span><span class="strut"> </span></p> -<p id="t50" class="pln"> <span class="nam">characteristic_temperature</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t51" class="pln"><span class="strut"> </span></p> -<p id="t52" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_calc_density_std</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">a</span><span class="op">,</span> <span class="nam">b</span><span class="op">,</span> <span class="nam">c</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t53" class="pln"> <span class="str">"""Returns an array of the density standard deviation (kg/m**3)</span><span class="strut"> </span></p> -<p id="t54" class="pln"><span class="str"> of the collection of carp eggs at each time step</span><span class="strut"> </span></p> -<p id="t55" class="pln"><span class="strut"> </span></p> -<p id="t56" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t57" class="stm run hide_run"> <span class="nam">time_array</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_simulation_clock</span><span class="op">.</span><span class="nam">time_array</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t58" class="stm run hide_run"> <span class="key">return</span> <span class="nam">a</span> <span class="op">*</span> <span class="nam">np</span><span class="op">.</span><span class="nam">exp</span><span class="op">(</span><span class="op">-</span><span class="nam">time_array</span> <span class="op">/</span> <span class="nam">b</span><span class="op">)</span> <span class="op">+</span> <span class="nam">c</span><span class="strut"> </span></p> -<p id="t59" class="pln"><span class="strut"> </span></p> -<p id="t60" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_calc_diameter_std</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">a</span><span class="op">,</span> <span class="nam">b</span><span class="op">,</span> <span class="nam">c</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t61" class="pln"> <span class="str">"""Returns an array of the diameter standard deviation (mm)</span><span class="strut"> </span></p> -<p id="t62" class="pln"><span class="str"> of the collection of carp eggs at each time step</span><span class="strut"> </span></p> -<p id="t63" class="pln"><span class="strut"> </span></p> -<p id="t64" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t65" class="stm run hide_run"> <span class="nam">time_array</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_simulation_clock</span><span class="op">.</span><span class="nam">time_array</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t66" class="stm run hide_run"> <span class="key">return</span> <span class="nam">a</span> <span class="op">*</span> <span class="nam">np</span><span class="op">.</span><span class="nam">exp</span><span class="op">(</span><span class="op">-</span><span class="nam">time_array</span> <span class="op">/</span> <span class="nam">b</span><span class="op">)</span> <span class="op">+</span> <span class="nam">c</span><span class="strut"> </span></p> -<p id="t67" class="pln"><span class="strut"> </span></p> -<p id="t68" class="stm run hide_run"> <span class="op">@</span><span class="nam">classmethod</span><span class="strut"> </span></p> -<p id="t69" class="pln"> <span class="key">def</span> <span class="nam">_calc_gas_bladder_inflation_time</span><span class="op">(</span><span class="nam">cls</span><span class="op">,</span> <span class="nam">tmin2</span><span class="op">,</span> <span class="nam">meanctu_gas_bladder</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t70" class="pln"> <span class="nam">characteristic_temperature</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t71" class="pln"><span class="strut"> </span></p> -<p id="t72" class="stm run hide_run"> <span class="key">if</span> <span class="nam">characteristic_temperature</span> <span class="key">is</span> <span class="key">None</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t73" class="stm run hide_run"> <span class="nam">characteristic_temperature</span> <span class="op">=</span> <span class="nam">cls</span><span class="op">.</span><span class="nam">_reference_temperature</span><span class="strut"> </span></p> -<p id="t74" class="pln"><span class="strut"> </span></p> -<p id="t75" class="pln"> <span class="com"># gas bladder inflation time in hours to seconds</span><span class="strut"> </span></p> -<p id="t76" class="stm run hide_run"> <span class="key">return</span> <span class="nam">meanctu_gas_bladder</span><span class="op">/</span><span class="op">(</span><span class="nam">characteristic_temperature</span> <span class="op">-</span> <span class="nam">tmin2</span><span class="op">)</span> <span class="op">*</span> <span class="num">3600</span><span class="strut"> </span></p> -<p id="t77" class="pln"><span class="strut"> </span></p> -<p id="t78" class="stm run hide_run"> <span class="op">@</span><span class="nam">classmethod</span><span class="strut"> </span></p> -<p id="t79" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_calc_hatching_time</span><span class="op">(</span><span class="nam">cls</span><span class="op">,</span> <span class="nam">a</span><span class="op">,</span> <span class="nam">b</span><span class="op">,</span> <span class="nam">c</span><span class="op">,</span> <span class="nam">temperature</span><span class="op">=</span><span class="key">None</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t80" class="pln"> <span class="str">"""Returns the hatching time (hours) of the collection of eggs</span><span class="strut"> </span></p> -<p id="t81" class="pln"><span class="strut"> </span></p> -<p id="t82" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t83" class="pln"><span class="strut"> </span></p> -<p id="t84" class="stm run hide_run"> <span class="key">if</span> <span class="nam">temperature</span> <span class="key">is</span> <span class="key">None</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t85" class="stm run hide_run"> <span class="nam">temperature</span> <span class="op">=</span> <span class="nam">cls</span><span class="op">.</span><span class="nam">_reference_temperature</span><span class="strut"> </span></p> -<p id="t86" class="pln"><span class="strut"> </span></p> -<p id="t87" class="stm run hide_run"> <span class="key">return</span> <span class="num">3600</span> <span class="op">*</span> <span class="op">(</span><span class="nam">a</span> <span class="op">*</span> <span class="nam">temperature</span> <span class="op">**</span> <span class="nam">b</span> <span class="op">+</span> <span class="nam">c</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t88" class="pln"><span class="strut"> </span></p> -<p id="t89" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_calc_mean_density</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">a</span><span class="op">,</span> <span class="nam">b</span><span class="op">,</span> <span class="nam">c</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t90" class="pln"> <span class="str">"""Returns an array of the mean density (kg/m**3) of the collection</span><span class="strut"> </span></p> -<p id="t91" class="pln"><span class="str"> of carp eggs at each time step</span><span class="strut"> </span></p> -<p id="t92" class="pln"><span class="strut"> </span></p> -<p id="t93" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t94" class="stm run hide_run"> <span class="nam">time_array</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_simulation_clock</span><span class="op">.</span><span class="nam">time_array</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t95" class="stm run hide_run"> <span class="key">return</span> <span class="nam">a</span> <span class="op">*</span> <span class="nam">np</span><span class="op">.</span><span class="nam">exp</span><span class="op">(</span><span class="op">-</span><span class="nam">time_array</span> <span class="op">/</span> <span class="nam">b</span><span class="op">)</span> <span class="op">+</span> <span class="nam">c</span><span class="strut"> </span></p> -<p id="t96" class="pln"><span class="strut"> </span></p> -<p id="t97" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_calc_mean_diameter</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">a</span><span class="op">,</span> <span class="nam">b</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t98" class="pln"> <span class="str">"""Returns an array of the mean diameter (mm) of the collection</span><span class="strut"> </span></p> -<p id="t99" class="pln"><span class="str"> of carp eggs at each time step</span><span class="strut"> </span></p> -<p id="t100" class="pln"><span class="strut"> </span></p> -<p id="t101" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t102" class="stm run hide_run"> <span class="nam">time_array</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_simulation_clock</span><span class="op">.</span><span class="nam">time_array</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t103" class="stm run hide_run"> <span class="key">return</span> <span class="nam">a</span> <span class="op">*</span> <span class="op">(</span><span class="num">1</span> <span class="op">-</span> <span class="nam">np</span><span class="op">.</span><span class="nam">exp</span><span class="op">(</span><span class="op">-</span><span class="nam">time_array</span> <span class="op">/</span> <span class="nam">b</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t104" class="pln"><span class="strut"> </span></p> -<p id="t105" class="stm run hide_run"> <span class="op">@</span><span class="nam">staticmethod</span><span class="strut"> </span></p> -<p id="t106" class="stm run hide_run"> <span class="op">@</span><span class="nam">abstractmethod</span><span class="strut"> </span></p> -<p id="t107" class="pln"> <span class="key">def</span> <span class="nam">_check_density_range</span><span class="op">(</span><span class="nam">density_array</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t108" class="stm mis"> <span class="key">raise</span> <span class="nam">NotImplementedError</span><span class="strut"> </span></p> -<p id="t109" class="pln"><span class="strut"> </span></p> -<p id="t110" class="stm run hide_run"> <span class="op">@</span><span class="nam">staticmethod</span><span class="strut"> </span></p> -<p id="t111" class="stm run hide_run"> <span class="op">@</span><span class="nam">abstractmethod</span><span class="strut"> </span></p> -<p id="t112" class="pln"> <span class="key">def</span> <span class="nam">_check_diameter_range</span><span class="op">(</span><span class="nam">diameter_array</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t113" class="stm mis"> <span class="key">raise</span> <span class="nam">NotImplementedError</span><span class="strut"> </span></p> -<p id="t114" class="pln"><span class="strut"> </span></p> -<p id="t115" class="stm run hide_run"> <span class="op">@</span><span class="nam">abstractmethod</span><span class="strut"> </span></p> -<p id="t116" class="pln"> <span class="key">def</span> <span class="nam">_mean_density</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t117" class="stm mis"> <span class="key">raise</span> <span class="nam">NotImplementedError</span><span class="strut"> </span></p> -<p id="t118" class="pln"><span class="strut"> </span></p> -<p id="t119" class="stm run hide_run"> <span class="op">@</span><span class="nam">abstractmethod</span><span class="strut"> </span></p> -<p id="t120" class="pln"> <span class="key">def</span> <span class="nam">_mean_diameter</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t121" class="stm mis"> <span class="key">raise</span> <span class="nam">NotImplementedError</span><span class="strut"> </span></p> -<p id="t122" class="pln"><span class="strut"> </span></p> -<p id="t123" class="stm run hide_run"> <span class="op">@</span><span class="nam">abstractmethod</span><span class="strut"> </span></p> -<p id="t124" class="pln"> <span class="key">def</span> <span class="nam">_density_std</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t125" class="stm mis"> <span class="key">raise</span> <span class="nam">NotImplementedError</span><span class="strut"> </span></p> -<p id="t126" class="pln"><span class="strut"> </span></p> -<p id="t127" class="stm run hide_run"> <span class="op">@</span><span class="nam">abstractmethod</span><span class="strut"> </span></p> -<p id="t128" class="pln"> <span class="key">def</span> <span class="nam">_diameter_std</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t129" class="stm mis"> <span class="key">raise</span> <span class="nam">NotImplementedError</span><span class="strut"> </span></p> -<p id="t130" class="pln"><span class="strut"> </span></p> -<p id="t131" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_init_diameter_array</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">random_numbers</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t132" class="pln"> <span class="str">"""Returns an array of the diameter (mm) of the collection</span><span class="strut"> </span></p> -<p id="t133" class="pln"><span class="str"> of carp eggs at each time step pulled from a normal distribution</span><span class="strut"> </span></p> -<p id="t134" class="pln"><span class="strut"> </span></p> -<p id="t135" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t136" class="stm run hide_run"> <span class="nam">mean_diameter</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_mean_diameter</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t137" class="stm run hide_run"> <span class="nam">diameter_std</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_diameter_std</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t138" class="pln"><span class="strut"> </span></p> -<p id="t139" class="stm run hide_run"> <span class="nam">diameter_array</span> <span class="op">=</span> <span class="nam">random_numbers</span><span class="op">.</span><span class="nam">random</span><span class="op">(</span><span class="nam">mean_diameter</span><span class="op">,</span> <span class="nam">diameter_std</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t140" class="pln"><span class="strut"> </span></p> -<p id="t141" class="stm run hide_run"> <span class="nam">low_outliers</span> <span class="op">=</span> <span class="nam">mean_diameter</span> <span class="op">-</span> <span class="nam">diameter_std</span><span class="strut"> </span></p> -<p id="t142" class="stm run hide_run"> <span class="nam">high_outliers</span> <span class="op">=</span> <span class="nam">mean_diameter</span> <span class="op">+</span> <span class="nam">diameter_std</span><span class="strut"> </span></p> -<p id="t143" class="pln"><span class="strut"> </span></p> -<p id="t144" class="stm run hide_run"> <span class="nam">outlier_index</span> <span class="op">=</span> <span class="op">(</span><span class="nam">diameter_array</span> <span class="op"><=</span> <span class="nam">low_outliers</span><span class="op">)</span> <span class="op">&</span> <span class="op">(</span><span class="strut"> </span></p> -<p id="t145" class="pln"> <span class="nam">high_outliers</span> <span class="op"><=</span> <span class="nam">diameter_array</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t146" class="pln"><span class="strut"> </span></p> -<p id="t147" class="stm run hide_run"> <span class="key">while</span> <span class="nam">np</span><span class="op">.</span><span class="nam">any</span><span class="op">(</span><span class="nam">outlier_index</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t148" class="stm mis"> <span class="nam">diameter_array</span><span class="op">[</span><span class="nam">outlier_index</span><span class="op">]</span> <span class="op">=</span> <span class="nam">random_numbers</span><span class="op">.</span><span class="nam">random</span><span class="op">(</span><span class="strut"> </span></p> -<p id="t149" class="pln"> <span class="nam">mean_diameter</span><span class="op">[</span><span class="nam">outlier_index</span><span class="op">]</span><span class="op">,</span> <span class="nam">diameter_std</span><span class="op">[</span><span class="nam">outlier_index</span><span class="op">]</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t150" class="stm mis"> <span class="nam">outlier_index</span> <span class="op">=</span> <span class="op">(</span><span class="nam">diameter_array</span> <span class="op"><=</span> <span class="nam">low_outliers</span><span class="op">)</span> <span class="op">&</span> <span class="op">(</span><span class="strut"> </span></p> -<p id="t151" class="pln"> <span class="nam">high_outliers</span> <span class="op"><=</span> <span class="nam">diameter_array</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t152" class="pln"><span class="strut"> </span></p> -<p id="t153" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_check_diameter_range</span><span class="op">(</span><span class="nam">diameter_array</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t154" class="pln"><span class="strut"> </span></p> -<p id="t155" class="stm run hide_run"> <span class="key">return</span> <span class="nam">diameter_array</span><span class="strut"> </span></p> -<p id="t156" class="pln"><span class="strut"> </span></p> -<p id="t157" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_init_reference_density_array</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">random_numbers</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t158" class="pln"> <span class="str">"""Returns an array of the density (kg/m**3) of the collection</span><span class="strut"> </span></p> -<p id="t159" class="pln"><span class="str"> of carp eggs at each time step pulled from a normal distribution</span><span class="strut"> </span></p> -<p id="t160" class="pln"><span class="strut"> </span></p> -<p id="t161" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t162" class="stm run hide_run"> <span class="nam">mean_density</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_mean_density</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t163" class="stm run hide_run"> <span class="nam">density_std</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_density_std</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t164" class="pln"><span class="strut"> </span></p> -<p id="t165" class="stm run hide_run"> <span class="nam">density_array</span> <span class="op">=</span> <span class="nam">random_numbers</span><span class="op">.</span><span class="nam">random</span><span class="op">(</span><span class="nam">mean_density</span><span class="op">,</span> <span class="nam">density_std</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t166" class="pln"><span class="strut"> </span></p> -<p id="t167" class="stm run hide_run"> <span class="nam">low_outliers</span> <span class="op">=</span> <span class="nam">mean_density</span> <span class="op">-</span> <span class="nam">density_std</span><span class="strut"> </span></p> -<p id="t168" class="stm run hide_run"> <span class="nam">high_outliers</span> <span class="op">=</span> <span class="nam">mean_density</span> <span class="op">+</span> <span class="nam">density_std</span><span class="strut"> </span></p> -<p id="t169" class="pln"><span class="strut"> </span></p> -<p id="t170" class="stm run hide_run"> <span class="nam">outlier_index</span> <span class="op">=</span> <span class="op">(</span><span class="nam">density_array</span> <span class="op"><=</span> <span class="nam">low_outliers</span><span class="op">)</span> <span class="op">&</span> <span class="op">(</span><span class="strut"> </span></p> -<p id="t171" class="pln"> <span class="nam">high_outliers</span> <span class="op"><=</span> <span class="nam">density_array</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t172" class="pln"><span class="strut"> </span></p> -<p id="t173" class="stm run hide_run"> <span class="key">while</span> <span class="nam">np</span><span class="op">.</span><span class="nam">any</span><span class="op">(</span><span class="nam">outlier_index</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t174" class="stm mis"> <span class="nam">density_array</span><span class="op">[</span><span class="nam">outlier_index</span><span class="op">]</span> <span class="op">=</span> <span class="nam">random_numbers</span><span class="op">.</span><span class="nam">random</span><span class="op">(</span><span class="strut"> </span></p> -<p id="t175" class="pln"> <span class="nam">mean_density</span><span class="op">[</span><span class="nam">outlier_index</span><span class="op">]</span><span class="op">,</span> <span class="nam">density_std</span><span class="op">[</span><span class="nam">outlier_index</span><span class="op">]</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t176" class="stm mis"> <span class="nam">outlier_index</span> <span class="op">=</span> <span class="op">(</span><span class="nam">density_array</span> <span class="op"><=</span> <span class="nam">low_outliers</span><span class="op">)</span> <span class="op">&</span> <span class="op">(</span><span class="strut"> </span></p> -<p id="t177" class="pln"> <span class="nam">high_outliers</span> <span class="op"><=</span> <span class="nam">density_array</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t178" class="pln"><span class="strut"> </span></p> -<p id="t179" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_check_density_range</span><span class="op">(</span><span class="nam">density_array</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t180" class="pln"><span class="strut"> </span></p> -<p id="t181" class="stm run hide_run"> <span class="key">return</span> <span class="nam">density_array</span><span class="strut"> </span></p> -<p id="t182" class="pln"><span class="strut"> </span></p> -<p id="t183" class="stm run hide_run"> <span class="key">def</span> <span class="nam">density</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">temperature</span><span class="op">=</span><span class="key">None</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t184" class="pln"> <span class="str">"""Returns the density of the collection of eggs</span><span class="strut"> </span></p> -<p id="t185" class="pln"><span class="strut"> </span></p> -<p id="t186" class="pln"><span class="str"> Parameters</span><span class="strut"> </span></p> -<p id="t187" class="pln"><span class="str"> ----------</span><span class="strut"> </span></p> -<p id="t188" class="pln"><span class="str"> temperature : float</span><span class="strut"> </span></p> -<p id="t189" class="pln"><span class="str"> the temperature of the eggs (Celsius)</span><span class="strut"> </span></p> -<p id="t190" class="pln"><span class="strut"> </span></p> -<p id="t191" class="pln"><span class="str"> Returns</span><span class="strut"> </span></p> -<p id="t192" class="pln"><span class="str"> -------</span><span class="strut"> </span></p> -<p id="t193" class="pln"><span class="str"> float</span><span class="strut"> </span></p> -<p id="t194" class="pln"><span class="strut"> </span></p> -<p id="t195" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t196" class="pln"><span class="strut"> </span></p> -<p id="t197" class="stm run hide_run"> <span class="key">if</span> <span class="nam">temperature</span> <span class="key">is</span> <span class="key">None</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t198" class="stm mis"> <span class="nam">temperature</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_reference_temperature</span><span class="strut"> </span></p> -<p id="t199" class="stm run hide_run"> <span class="nam">density_index</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_simulation_clock</span><span class="op">.</span><span class="nam">current_time_index</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t200" class="stm run hide_run"> <span class="nam">reference_density</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_reference_density_array</span><span class="op">[</span><span class="nam">density_index</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t201" class="stm run hide_run"> <span class="key">return</span> <span class="nam">reference_density</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t202" class="pln"> <span class="op">+</span> <span class="num">0.20646</span><span class="op">*</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_reference_temperature</span> <span class="op">-</span> <span class="nam">temperature</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t203" class="pln"><span class="strut"> </span></p> -<p id="t204" class="stm run hide_run"> <span class="key">def</span> <span class="nam">diameter</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t205" class="pln"> <span class="str">"""Returns the diameter of the collection of eggs in m</span><span class="strut"> </span></p> -<p id="t206" class="pln"><span class="strut"> </span></p> -<p id="t207" class="pln"><span class="str"> Returns</span><span class="strut"> </span></p> -<p id="t208" class="pln"><span class="str"> -------</span><span class="strut"> </span></p> -<p id="t209" class="pln"><span class="str"> float</span><span class="strut"> </span></p> -<p id="t210" class="pln"><span class="strut"> </span></p> -<p id="t211" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t212" class="stm run hide_run"> <span class="nam">diameter_index</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_simulation_clock</span><span class="op">.</span><span class="nam">current_time_index</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t213" class="pln"> <span class="com"># Convert from mm to m</span><span class="strut"> </span></p> -<p id="t214" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_diameter_array</span><span class="op">[</span><span class="nam">diameter_index</span><span class="op">]</span> <span class="op">/</span> <span class="num">1000</span><span class="strut"> </span></p> -<p id="t215" class="pln"><span class="strut"> </span></p> -<p id="t216" class="stm run hide_run"> <span class="key">def</span> <span class="nam">fall_velocity</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">hydraulic_results</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t217" class="pln"> <span class="str">"""Returns fall velocity</span><span class="strut"> </span></p> -<p id="t218" class="pln"><span class="strut"> </span></p> -<p id="t219" class="pln"><span class="str"> Parameters</span><span class="strut"> </span></p> -<p id="t220" class="pln"><span class="str"> ----------</span><span class="strut"> </span></p> -<p id="t221" class="pln"><span class="str"> hydraulic_results : numpy.ndarray</span><span class="strut"> </span></p> -<p id="t222" class="pln"><span class="str"> Hydrauilc results</span><span class="strut"> </span></p> -<p id="t223" class="pln"><span class="strut"> </span></p> -<p id="t224" class="pln"><span class="str"> Returns</span><span class="strut"> </span></p> -<p id="t225" class="pln"><span class="str"> -------</span><span class="strut"> </span></p> -<p id="t226" class="pln"><span class="str"> numpy.ndarray</span><span class="strut"> </span></p> -<p id="t227" class="pln"><span class="strut"> </span></p> -<p id="t228" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t229" class="pln"><span class="strut"> </span></p> -<p id="t230" class="stm mis"> <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_simulation_clock</span><span class="op">.</span><span class="nam">current_time</span><span class="op">(</span><span class="op">)</span> <span class="op">></span> <span class="nam">self</span><span class="op">.</span><span class="nam">_hatching_time</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t231" class="stm mis"> <span class="nam">fall_velocity</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">zeros</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_position</span><span class="op">.</span><span class="nam">shape</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t232" class="pln"> <span class="key">else</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t233" class="stm mis"> <span class="nam">fall_velocity</span> <span class="op">=</span> <span class="nam">super</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">fall_velocity</span><span class="op">(</span><span class="nam">hydraulic_results</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t234" class="pln"><span class="strut"> </span></p> -<p id="t235" class="stm mis"> <span class="key">return</span> <span class="nam">fall_velocity</span><span class="strut"> </span></p> -<p id="t236" class="pln"><span class="strut"> </span></p> -<p id="t237" class="stm run hide_run"> <span class="op">@</span><span class="nam">classmethod</span><span class="strut"> </span></p> -<p id="t238" class="stm run hide_run"> <span class="op">@</span><span class="nam">abstractmethod</span><span class="strut"> </span></p> -<p id="t239" class="stm run hide_run"> <span class="key">def</span> <span class="nam">gas_bladder_inflation_time</span><span class="op">(</span><span class="nam">cls</span><span class="op">,</span> <span class="nam">temperature</span><span class="op">=</span><span class="key">None</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t240" class="stm mis"> <span class="key">raise</span> <span class="nam">NotImplementedError</span><span class="strut"> </span></p> -<p id="t241" class="pln"><span class="strut"> </span></p> -<p id="t242" class="stm run hide_run"> <span class="op">@</span><span class="nam">classmethod</span><span class="strut"> </span></p> -<p id="t243" class="stm run hide_run"> <span class="op">@</span><span class="nam">abstractmethod</span><span class="strut"> </span></p> -<p id="t244" class="stm run hide_run"> <span class="key">def</span> <span class="nam">hatching_time</span><span class="op">(</span><span class="nam">cls</span><span class="op">,</span> <span class="nam">temperature</span><span class="op">=</span><span class="key">None</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t245" class="stm mis"> <span class="key">raise</span> <span class="nam">NotImplementedError</span><span class="strut"> </span></p> -<p id="t246" class="pln"><span class="strut"> </span></p> -<p id="t247" class="stm run hide_run"> <span class="key">def</span> <span class="nam">position</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t248" class="pln"> <span class="str">"""Returns the 3D positions of the collection of eggs in meters</span><span class="strut"> </span></p> -<p id="t249" class="pln"><span class="strut"> </span></p> -<p id="t250" class="pln"><span class="str"> The shape of the returned array is (number_of_eggs, 3)</span><span class="strut"> </span></p> -<p id="t251" class="pln"><span class="strut"> </span></p> -<p id="t252" class="pln"><span class="str"> Returns</span><span class="strut"> </span></p> -<p id="t253" class="pln"><span class="str"> -------</span><span class="strut"> </span></p> -<p id="t254" class="pln"><span class="str"> numpy.ndarray</span><span class="strut"> </span></p> -<p id="t255" class="pln"><span class="strut"> </span></p> -<p id="t256" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t257" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_position</span><span class="strut"> </span></p> -<p id="t258" class="pln"><span class="strut"> </span></p> -<p id="t259" class="stm run hide_run"> <span class="key">def</span> <span class="nam">set_position</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">position</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t260" class="pln"> <span class="str">"""Sets the 3D positions of the collection of eggs</span><span class="strut"> </span></p> -<p id="t261" class="pln"><span class="strut"> </span></p> -<p id="t262" class="pln"><span class="str"> :param: positions of the colllection of eggs (m)</span><span class="strut"> </span></p> -<p id="t263" class="pln"><span class="str"> :type: numpy.ndarray(number_of_eggs, 3)</span><span class="strut"> </span></p> -<p id="t264" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t265" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_position</span> <span class="op">=</span> <span class="nam">position</span><span class="strut"> </span></p> -<p id="t266" class="pln"><span class="strut"> </span></p> -<p id="t267" class="pln"><span class="strut"> </span></p> -<p id="t268" class="stm run hide_run"><span class="key">class</span> <span class="nam">BigheadCarpEggs</span><span class="op">(</span><span class="nam">CarpEggs</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t269" class="pln"> <span class="str">"""Class representing a collection of Bighead carp egg</span><span class="strut"> </span></p> -<p id="t270" class="pln"><span class="strut"> </span></p> -<p id="t271" class="pln"><span class="str"> See CarpEggs for accurate signature.</span><span class="strut"> </span></p> -<p id="t272" class="pln"><span class="strut"> </span></p> -<p id="t273" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t274" class="pln"><span class="strut"> </span></p> -<p id="t275" class="stm run hide_run"> <span class="op">@</span><span class="nam">staticmethod</span><span class="strut"> </span></p> -<p id="t276" class="pln"> <span class="key">def</span> <span class="nam">_check_density_range</span><span class="op">(</span><span class="nam">density_array</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t277" class="pln"> <span class="str">"""Modifies input array so any outlier densities are set</span><span class="strut"> </span></p> -<p id="t278" class="pln"><span class="str"> to the respective min or max of the range</span><span class="strut"> </span></p> -<p id="t279" class="pln"><span class="strut"> </span></p> -<p id="t280" class="pln"><span class="str"> :param density_array: input density array (kg/m**3)</span><span class="strut"> </span></p> -<p id="t281" class="pln"><span class="str"> :type: np.ndarray</span><span class="strut"> </span></p> -<p id="t282" class="pln"><span class="strut"> </span></p> -<p id="t283" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t284" class="stm run hide_run"> <span class="nam">max_density</span> <span class="op">=</span> <span class="num">1040.4</span><span class="strut"> </span></p> -<p id="t285" class="stm run hide_run"> <span class="nam">min_density</span> <span class="op">=</span> <span class="num">998.5357</span><span class="strut"> </span></p> -<p id="t286" class="stm run hide_run"> <span class="nam">density_array</span><span class="op">[</span><span class="nam">density_array</span> <span class="op">></span> <span class="nam">max_density</span><span class="op">]</span> <span class="op">=</span> <span class="nam">max_density</span><span class="strut"> </span></p> -<p id="t287" class="stm run hide_run"> <span class="nam">density_array</span><span class="op">[</span><span class="nam">density_array</span> <span class="op"><</span> <span class="nam">min_density</span><span class="op">]</span> <span class="op">=</span> <span class="nam">min_density</span><span class="strut"> </span></p> -<p id="t288" class="pln"><span class="strut"> </span></p> -<p id="t289" class="stm run hide_run"> <span class="op">@</span><span class="nam">staticmethod</span><span class="strut"> </span></p> -<p id="t290" class="pln"> <span class="key">def</span> <span class="nam">_check_diameter_range</span><span class="op">(</span><span class="nam">diameter_array</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t291" class="pln"> <span class="str">"""Modifies input array so any outlier diameters are set</span><span class="strut"> </span></p> -<p id="t292" class="pln"><span class="str"> to the respective min or max of the range</span><span class="strut"> </span></p> -<p id="t293" class="pln"><span class="strut"> </span></p> -<p id="t294" class="pln"><span class="str"> :param diameter_array: input diameter array (mm)</span><span class="strut"> </span></p> -<p id="t295" class="pln"><span class="str"> :type: np.ndarray</span><span class="strut"> </span></p> -<p id="t296" class="pln"><span class="strut"> </span></p> -<p id="t297" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t298" class="stm run hide_run"> <span class="nam">max_diameter</span> <span class="op">=</span> <span class="num">7.1334</span><span class="strut"> </span></p> -<p id="t299" class="stm run hide_run"> <span class="nam">min_diameter</span> <span class="op">=</span> <span class="num">1.5970</span><span class="strut"> </span></p> -<p id="t300" class="stm run hide_run"> <span class="nam">diameter_array</span><span class="op">[</span><span class="nam">diameter_array</span> <span class="op">></span> <span class="nam">max_diameter</span><span class="op">]</span> <span class="op">=</span> <span class="nam">max_diameter</span><span class="strut"> </span></p> -<p id="t301" class="stm run hide_run"> <span class="nam">diameter_array</span><span class="op">[</span><span class="nam">diameter_array</span> <span class="op"><</span> <span class="nam">min_diameter</span><span class="op">]</span> <span class="op">=</span> <span class="nam">min_diameter</span><span class="strut"> </span></p> -<p id="t302" class="pln"><span class="strut"> </span></p> -<p id="t303" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_mean_density</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t304" class="pln"> <span class="str">"""Returns an array of the mean density (kg/m**3) of the</span><span class="strut"> </span></p> -<p id="t305" class="pln"><span class="str"> collection carp eggs at each time step</span><span class="strut"> </span></p> -<p id="t306" class="pln"><span class="strut"> </span></p> -<p id="t307" class="pln"><span class="str"> :return: mean density (kg/m**3) of carp eggs</span><span class="strut"> </span></p> -<p id="t308" class="pln"><span class="str"> :rtype: float</span><span class="strut"> </span></p> -<p id="t309" class="pln"><span class="strut"> </span></p> -<p id="t310" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t311" class="stm run hide_run"> <span class="nam">a</span> <span class="op">=</span> <span class="num">30.58</span><span class="strut"> </span></p> -<p id="t312" class="stm run hide_run"> <span class="nam">b</span> <span class="op">=</span> <span class="num">1716</span><span class="strut"> </span></p> -<p id="t313" class="stm run hide_run"> <span class="nam">c</span> <span class="op">=</span> <span class="num">999.4</span><span class="strut"> </span></p> -<p id="t314" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_calc_mean_density</span><span class="op">(</span><span class="nam">a</span><span class="op">,</span> <span class="nam">b</span><span class="op">,</span> <span class="nam">c</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t315" class="pln"><span class="strut"> </span></p> -<p id="t316" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_mean_diameter</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t317" class="pln"> <span class="str">"""Returns an array of the mean diameter (mm) of the</span><span class="strut"> </span></p> -<p id="t318" class="pln"><span class="str"> collection of carp eggs at each time step</span><span class="strut"> </span></p> -<p id="t319" class="pln"><span class="strut"> </span></p> -<p id="t320" class="pln"><span class="str"> :return: array of mean diameter (mm) of carp eggs at each time step</span><span class="strut"> </span></p> -<p id="t321" class="pln"><span class="str"> :rtype: np.ndarray</span><span class="strut"> </span></p> -<p id="t322" class="pln"><span class="strut"> </span></p> -<p id="t323" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t324" class="stm run hide_run"> <span class="nam">a</span> <span class="op">=</span> <span class="num">5.82</span><span class="strut"> </span></p> -<p id="t325" class="stm run hide_run"> <span class="nam">b</span> <span class="op">=</span> <span class="num">3506.7</span><span class="strut"> </span></p> -<p id="t326" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_calc_mean_diameter</span><span class="op">(</span><span class="nam">a</span><span class="op">,</span> <span class="nam">b</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t327" class="pln"><span class="strut"> </span></p> -<p id="t328" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_density_std</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t329" class="pln"> <span class="str">"""Returns an array of the density standard deviation (kg/m**3)</span><span class="strut"> </span></p> -<p id="t330" class="pln"><span class="str"> of the collection of carp eggs at each time step</span><span class="strut"> </span></p> -<p id="t331" class="pln"><span class="strut"> </span></p> -<p id="t332" class="pln"><span class="str"> :return: density std array (kg/m**3) of carp eggs at each time step</span><span class="strut"> </span></p> -<p id="t333" class="pln"><span class="str"> :rtype: np.ndarray</span><span class="strut"> </span></p> -<p id="t334" class="pln"><span class="strut"> </span></p> -<p id="t335" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t336" class="stm run hide_run"> <span class="nam">a</span> <span class="op">=</span> <span class="num">63.12</span><span class="strut"> </span></p> -<p id="t337" class="stm run hide_run"> <span class="nam">b</span> <span class="op">=</span> <span class="num">595</span><span class="strut"> </span></p> -<p id="t338" class="stm run hide_run"> <span class="nam">c</span> <span class="op">=</span> <span class="num">0.6292</span><span class="strut"> </span></p> -<p id="t339" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_calc_density_std</span><span class="op">(</span><span class="nam">a</span><span class="op">,</span> <span class="nam">b</span><span class="op">,</span> <span class="nam">c</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t340" class="pln"><span class="strut"> </span></p> -<p id="t341" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_diameter_std</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t342" class="pln"> <span class="str">"""Returns an array of the diameter standard deviation (mm)</span><span class="strut"> </span></p> -<p id="t343" class="pln"><span class="str"> of the collection of carp eggs at each time step</span><span class="strut"> </span></p> -<p id="t344" class="pln"><span class="strut"> </span></p> -<p id="t345" class="pln"><span class="str"> :return: diamter std array (mm) of carp eggs at each time step</span><span class="strut"> </span></p> -<p id="t346" class="pln"><span class="str"> :rtype: np.ndarray</span><span class="strut"> </span></p> -<p id="t347" class="pln"><span class="strut"> </span></p> -<p id="t348" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t349" class="stm run hide_run"> <span class="nam">a</span> <span class="op">=</span> <span class="num">0.1788</span><span class="strut"> </span></p> -<p id="t350" class="stm run hide_run"> <span class="nam">b</span> <span class="op">=</span> <span class="num">13570.0</span><span class="strut"> </span></p> -<p id="t351" class="stm run hide_run"> <span class="nam">c</span> <span class="op">=</span> <span class="num">0.44</span><span class="strut"> </span></p> -<p id="t352" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_calc_diameter_std</span><span class="op">(</span><span class="nam">a</span><span class="op">,</span> <span class="nam">b</span><span class="op">,</span> <span class="nam">c</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t353" class="pln"><span class="strut"> </span></p> -<p id="t354" class="stm run hide_run"> <span class="op">@</span><span class="nam">classmethod</span><span class="strut"> </span></p> -<p id="t355" class="stm run hide_run"> <span class="key">def</span> <span class="nam">gas_bladder_inflation_time</span><span class="op">(</span><span class="nam">cls</span><span class="op">,</span> <span class="nam">temperature</span><span class="op">=</span><span class="key">None</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t356" class="pln"> <span class="str">"""</span><span class="strut"> </span></p> -<p id="t357" class="pln"><span class="strut"> </span></p> -<p id="t358" class="pln"><span class="str"> :param temperature:</span><span class="strut"> </span></p> -<p id="t359" class="pln"><span class="str"> :return:</span><span class="strut"> </span></p> -<p id="t360" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t361" class="pln"><span class="strut"> </span></p> -<p id="t362" class="stm run hide_run"> <span class="nam">tmin2</span> <span class="op">=</span> <span class="num">13.4</span><span class="strut"> </span></p> -<p id="t363" class="stm run hide_run"> <span class="nam">meanctu_gas_bladder</span> <span class="op">=</span> <span class="num">1161.07</span><span class="strut"> </span></p> -<p id="t364" class="pln"><span class="strut"> </span></p> -<p id="t365" class="stm run hide_run"> <span class="key">return</span> <span class="nam">cls</span><span class="op">.</span><span class="nam">_calc_gas_bladder_inflation_time</span><span class="op">(</span><span class="nam">tmin2</span><span class="op">,</span> <span class="nam">meanctu_gas_bladder</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t366" class="pln"> <span class="nam">temperature</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t367" class="pln"><span class="strut"> </span></p> -<p id="t368" class="stm run hide_run"> <span class="op">@</span><span class="nam">classmethod</span><span class="strut"> </span></p> -<p id="t369" class="stm run hide_run"> <span class="key">def</span> <span class="nam">hatching_time</span><span class="op">(</span><span class="nam">cls</span><span class="op">,</span> <span class="nam">temperature</span><span class="op">=</span><span class="key">None</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t370" class="pln"> <span class="str">"""Returns the hatching time of carp eggs</span><span class="strut"> </span></p> -<p id="t371" class="pln"><span class="str"> based on input temperature</span><span class="strut"> </span></p> -<p id="t372" class="pln"><span class="strut"> </span></p> -<p id="t373" class="pln"><span class="str"> :param temperature: Temperature of eggs(Celsius)</span><span class="strut"> </span></p> -<p id="t374" class="pln"><span class="str"> :type: float</span><span class="strut"> </span></p> -<p id="t375" class="pln"><span class="str"> :return: hatching time of eggs (s)</span><span class="strut"> </span></p> -<p id="t376" class="pln"><span class="str"> :rtype: float</span><span class="strut"> </span></p> -<p id="t377" class="pln"><span class="strut"> </span></p> -<p id="t378" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t379" class="pln"><span class="strut"> </span></p> -<p id="t380" class="stm run hide_run"> <span class="nam">a</span> <span class="op">=</span> <span class="num">35703</span><span class="strut"> </span></p> -<p id="t381" class="stm run hide_run"> <span class="nam">b</span> <span class="op">=</span> <span class="op">-</span><span class="num">2.223</span><span class="strut"> </span></p> -<p id="t382" class="stm run hide_run"> <span class="nam">c</span> <span class="op">=</span> <span class="num">0.0</span><span class="strut"> </span></p> -<p id="t383" class="pln"><span class="strut"> </span></p> -<p id="t384" class="stm run hide_run"> <span class="key">return</span> <span class="nam">cls</span><span class="op">.</span><span class="nam">_calc_hatching_time</span><span class="op">(</span><span class="nam">a</span><span class="op">,</span> <span class="nam">b</span><span class="op">,</span> <span class="nam">c</span><span class="op">,</span> <span class="nam">temperature</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t385" class="pln"><span class="strut"> </span></p> -<p id="t386" class="pln"><span class="strut"> </span></p> -<p id="t387" class="stm run hide_run"><span class="key">class</span> <span class="nam">SilverCarpEggs</span><span class="op">(</span><span class="nam">CarpEggs</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t388" class="pln"> <span class="str">"""Class representing a collection of Silver carp eggs</span><span class="strut"> </span></p> -<p id="t389" class="pln"><span class="strut"> </span></p> -<p id="t390" class="pln"><span class="str"> See CarpEggs for accurate signature</span><span class="strut"> </span></p> -<p id="t391" class="pln"><span class="strut"> </span></p> -<p id="t392" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t393" class="pln"><span class="strut"> </span></p> -<p id="t394" class="stm run hide_run"> <span class="op">@</span><span class="nam">staticmethod</span><span class="strut"> </span></p> -<p id="t395" class="pln"> <span class="key">def</span> <span class="nam">_check_density_range</span><span class="op">(</span><span class="nam">density_array</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t396" class="pln"> <span class="str">"""Modifies input array so any outlier densities are set</span><span class="strut"> </span></p> -<p id="t397" class="pln"><span class="str"> to the respective min or max of the range</span><span class="strut"> </span></p> -<p id="t398" class="pln"><span class="strut"> </span></p> -<p id="t399" class="pln"><span class="str"> :param density_array: input density array (kg/m**3)</span><span class="strut"> </span></p> -<p id="t400" class="pln"><span class="str"> :type: np.ndarray</span><span class="strut"> </span></p> -<p id="t401" class="pln"><span class="strut"> </span></p> -<p id="t402" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t403" class="stm run hide_run"> <span class="nam">max_density</span> <span class="op">=</span> <span class="num">1036.1</span><span class="strut"> </span></p> -<p id="t404" class="stm run hide_run"> <span class="nam">min_density</span> <span class="op">=</span> <span class="num">998.7680</span><span class="strut"> </span></p> -<p id="t405" class="stm run hide_run"> <span class="nam">density_array</span><span class="op">[</span><span class="nam">density_array</span> <span class="op">></span> <span class="nam">max_density</span><span class="op">]</span> <span class="op">=</span> <span class="nam">max_density</span><span class="strut"> </span></p> -<p id="t406" class="stm run hide_run"> <span class="nam">density_array</span><span class="op">[</span><span class="nam">density_array</span> <span class="op"><</span> <span class="nam">min_density</span><span class="op">]</span> <span class="op">=</span> <span class="nam">min_density</span><span class="strut"> </span></p> -<p id="t407" class="pln"><span class="strut"> </span></p> -<p id="t408" class="stm run hide_run"> <span class="op">@</span><span class="nam">staticmethod</span><span class="strut"> </span></p> -<p id="t409" class="pln"> <span class="key">def</span> <span class="nam">_check_diameter_range</span><span class="op">(</span><span class="nam">diameter_array</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t410" class="pln"> <span class="str">"""Modifies input array so any outlier diameters are set</span><span class="strut"> </span></p> -<p id="t411" class="pln"><span class="str"> to the respective min or max of the range</span><span class="strut"> </span></p> -<p id="t412" class="pln"><span class="strut"> </span></p> -<p id="t413" class="pln"><span class="str"> :param diameter_array: input diameter array (mm)</span><span class="strut"> </span></p> -<p id="t414" class="pln"><span class="str"> :type: np.ndarray</span><span class="strut"> </span></p> -<p id="t415" class="pln"><span class="strut"> </span></p> -<p id="t416" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t417" class="stm run hide_run"> <span class="nam">max_diameter</span> <span class="op">=</span> <span class="num">5.6000</span><span class="strut"> </span></p> -<p id="t418" class="stm run hide_run"> <span class="nam">min_diameter</span> <span class="op">=</span> <span class="num">1.6980</span><span class="strut"> </span></p> -<p id="t419" class="stm run hide_run"> <span class="nam">diameter_array</span><span class="op">[</span><span class="nam">diameter_array</span> <span class="op">></span> <span class="nam">max_diameter</span><span class="op">]</span> <span class="op">=</span> <span class="nam">max_diameter</span><span class="strut"> </span></p> -<p id="t420" class="stm run hide_run"> <span class="nam">diameter_array</span><span class="op">[</span><span class="nam">diameter_array</span> <span class="op"><</span> <span class="nam">min_diameter</span><span class="op">]</span> <span class="op">=</span> <span class="nam">min_diameter</span><span class="strut"> </span></p> -<p id="t421" class="pln"><span class="strut"> </span></p> -<p id="t422" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_mean_density</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t423" class="pln"> <span class="str">"""Returns an array of the mean density (kg/m**3) of the</span><span class="strut"> </span></p> -<p id="t424" class="pln"><span class="str"> collection carp eggs at each time step</span><span class="strut"> </span></p> -<p id="t425" class="pln"><span class="strut"> </span></p> -<p id="t426" class="pln"><span class="str"> :return: mean density (kg/m**3) of carp eggs</span><span class="strut"> </span></p> -<p id="t427" class="pln"><span class="str"> :rtype: float</span><span class="strut"> </span></p> -<p id="t428" class="pln"><span class="strut"> </span></p> -<p id="t429" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t430" class="stm run hide_run"> <span class="nam">a</span> <span class="op">=</span> <span class="num">25.2</span><span class="strut"> </span></p> -<p id="t431" class="stm run hide_run"> <span class="nam">b</span> <span class="op">=</span> <span class="num">2259</span><span class="strut"> </span></p> -<p id="t432" class="stm run hide_run"> <span class="nam">c</span> <span class="op">=</span> <span class="num">999.3</span><span class="strut"> </span></p> -<p id="t433" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_calc_mean_density</span><span class="op">(</span><span class="nam">a</span><span class="op">,</span> <span class="nam">b</span><span class="op">,</span> <span class="nam">c</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t434" class="pln"><span class="strut"> </span></p> -<p id="t435" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_mean_diameter</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t436" class="pln"> <span class="str">"""Returns an array of the mean diameter (mm) of the</span><span class="strut"> </span></p> -<p id="t437" class="pln"><span class="str"> collection of carp eggs at each time step</span><span class="strut"> </span></p> -<p id="t438" class="pln"><span class="strut"> </span></p> -<p id="t439" class="pln"><span class="str"> :return: array of mean diameter (mm) of carp eggs at each time step</span><span class="strut"> </span></p> -<p id="t440" class="pln"><span class="str"> :rtype: np.ndarray</span><span class="strut"> </span></p> -<p id="t441" class="pln"><span class="strut"> </span></p> -<p id="t442" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t443" class="stm run hide_run"> <span class="nam">a</span> <span class="op">=</span> <span class="num">4.66</span><span class="strut"> </span></p> -<p id="t444" class="stm run hide_run"> <span class="nam">b</span> <span class="op">=</span> <span class="num">2635.9</span><span class="strut"> </span></p> -<p id="t445" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_calc_mean_diameter</span><span class="op">(</span><span class="nam">a</span><span class="op">,</span> <span class="nam">b</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t446" class="pln"><span class="strut"> </span></p> -<p id="t447" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_density_std</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t448" class="pln"> <span class="str">"""Returns an array of the density standard deviation (kg/m**3)</span><span class="strut"> </span></p> -<p id="t449" class="pln"><span class="str"> of the collection of carp eggs at each time step</span><span class="strut"> </span></p> -<p id="t450" class="pln"><span class="strut"> </span></p> -<p id="t451" class="pln"><span class="str"> :return: density std array (kg/m**3) of carp eggs at each time step</span><span class="strut"> </span></p> -<p id="t452" class="pln"><span class="str"> :rtype: np.ndarray</span><span class="strut"> </span></p> -<p id="t453" class="pln"><span class="strut"> </span></p> -<p id="t454" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t455" class="stm run hide_run"> <span class="nam">a</span> <span class="op">=</span> <span class="num">22.4</span><span class="strut"> </span></p> -<p id="t456" class="stm run hide_run"> <span class="nam">b</span> <span class="op">=</span> <span class="num">1894</span><span class="strut"> </span></p> -<p id="t457" class="stm run hide_run"> <span class="nam">c</span> <span class="op">=</span> <span class="num">0.4103</span><span class="strut"> </span></p> -<p id="t458" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_calc_density_std</span><span class="op">(</span><span class="nam">a</span><span class="op">,</span> <span class="nam">b</span><span class="op">,</span> <span class="nam">c</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t459" class="pln"><span class="strut"> </span></p> -<p id="t460" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_diameter_std</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t461" class="pln"> <span class="str">"""Returns an array of the diameter standard deviation (mm)</span><span class="strut"> </span></p> -<p id="t462" class="pln"><span class="str"> of the collection of carp eggs at each time step</span><span class="strut"> </span></p> -<p id="t463" class="pln"><span class="strut"> </span></p> -<p id="t464" class="pln"><span class="str"> :return: diamter std array (mm) of carp eggs at each time step</span><span class="strut"> </span></p> -<p id="t465" class="pln"><span class="str"> :rtype: np.ndarray</span><span class="strut"> </span></p> -<p id="t466" class="pln"><span class="strut"> </span></p> -<p id="t467" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t468" class="stm run hide_run"> <span class="nam">a</span> <span class="op">=</span> <span class="num">0.2631</span><span class="strut"> </span></p> -<p id="t469" class="stm run hide_run"> <span class="nam">b</span> <span class="op">=</span> <span class="num">22410</span><span class="strut"> </span></p> -<p id="t470" class="stm run hide_run"> <span class="nam">c</span> <span class="op">=</span> <span class="num">0.3073</span><span class="strut"> </span></p> -<p id="t471" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_calc_diameter_std</span><span class="op">(</span><span class="nam">a</span><span class="op">,</span> <span class="nam">b</span><span class="op">,</span> <span class="nam">c</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t472" class="pln"><span class="strut"> </span></p> -<p id="t473" class="stm run hide_run"> <span class="op">@</span><span class="nam">classmethod</span><span class="strut"> </span></p> -<p id="t474" class="stm run hide_run"> <span class="key">def</span> <span class="nam">gas_bladder_inflation_time</span><span class="op">(</span><span class="nam">cls</span><span class="op">,</span> <span class="nam">temperature</span><span class="op">=</span><span class="key">None</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t475" class="pln"><span class="strut"> </span></p> -<p id="t476" class="stm run hide_run"> <span class="nam">tmin2</span> <span class="op">=</span> <span class="num">13.3</span><span class="strut"> </span></p> -<p id="t477" class="stm run hide_run"> <span class="nam">meanctu_gas_bladder</span> <span class="op">=</span> <span class="num">1084.59</span><span class="strut"> </span></p> -<p id="t478" class="pln"><span class="strut"> </span></p> -<p id="t479" class="stm run hide_run"> <span class="key">return</span> <span class="nam">cls</span><span class="op">.</span><span class="nam">_calc_gas_bladder_inflation_time</span><span class="op">(</span><span class="nam">tmin2</span><span class="op">,</span> <span class="nam">meanctu_gas_bladder</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t480" class="pln"> <span class="nam">temperature</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t481" class="pln"><span class="strut"> </span></p> -<p id="t482" class="stm run hide_run"> <span class="op">@</span><span class="nam">classmethod</span><span class="strut"> </span></p> -<p id="t483" class="stm run hide_run"> <span class="key">def</span> <span class="nam">hatching_time</span><span class="op">(</span><span class="nam">cls</span><span class="op">,</span> <span class="nam">temperature</span><span class="op">=</span><span class="key">None</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t484" class="pln"> <span class="str">"""Returns the hatching time of carp eggs</span><span class="strut"> </span></p> -<p id="t485" class="pln"><span class="str"> based on input temperature</span><span class="strut"> </span></p> -<p id="t486" class="pln"><span class="strut"> </span></p> -<p id="t487" class="pln"><span class="str"> :param temperature: Temperature of eggs(Celsius)</span><span class="strut"> </span></p> -<p id="t488" class="pln"><span class="str"> :type: float</span><span class="strut"> </span></p> -<p id="t489" class="pln"><span class="str"> :return: hatching time of eggs (hr)</span><span class="strut"> </span></p> -<p id="t490" class="pln"><span class="str"> :rtype: float</span><span class="strut"> </span></p> -<p id="t491" class="pln"><span class="strut"> </span></p> -<p id="t492" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t493" class="stm run hide_run"> <span class="nam">a</span> <span class="op">=</span> <span class="num">1.2087e+7</span><span class="strut"> </span></p> -<p id="t494" class="stm run hide_run"> <span class="nam">b</span> <span class="op">=</span> <span class="op">-</span><span class="num">4.2664</span><span class="strut"> </span></p> -<p id="t495" class="stm run hide_run"> <span class="nam">c</span> <span class="op">=</span> <span class="num">10.242</span><span class="strut"> </span></p> -<p id="t496" class="stm run hide_run"> <span class="key">return</span> <span class="nam">cls</span><span class="op">.</span><span class="nam">_calc_hatching_time</span><span class="op">(</span><span class="nam">a</span><span class="op">,</span> <span class="nam">b</span><span class="op">,</span> <span class="nam">c</span><span class="op">,</span> <span class="nam">temperature</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t497" class="pln"><span class="strut"> </span></p> -<p id="t498" class="pln"><span class="strut"> </span></p> -<p id="t499" class="stm run hide_run"><span class="key">class</span> <span class="nam">GrassCarpEggs</span><span class="op">(</span><span class="nam">CarpEggs</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t500" class="pln"> <span class="str">"""Class representing a collection of Grass carp eggs</span><span class="strut"> </span></p> -<p id="t501" class="pln"><span class="strut"> </span></p> -<p id="t502" class="pln"><span class="str"> See CarpEggs for accurate signature</span><span class="strut"> </span></p> -<p id="t503" class="pln"><span class="strut"> </span></p> -<p id="t504" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t505" class="pln"><span class="strut"> </span></p> -<p id="t506" class="stm run hide_run"> <span class="op">@</span><span class="nam">staticmethod</span><span class="strut"> </span></p> -<p id="t507" class="pln"> <span class="key">def</span> <span class="nam">_check_density_range</span><span class="op">(</span><span class="nam">density_array</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t508" class="pln"> <span class="str">"""Modifies input array so any outlier densities are set</span><span class="strut"> </span></p> -<p id="t509" class="pln"><span class="str"> to the respective min or max of the range</span><span class="strut"> </span></p> -<p id="t510" class="pln"><span class="strut"> </span></p> -<p id="t511" class="pln"><span class="str"> :param density_array: input density array (kg/m**3)</span><span class="strut"> </span></p> -<p id="t512" class="pln"><span class="str"> :type: np.ndarray</span><span class="strut"> </span></p> -<p id="t513" class="pln"><span class="strut"> </span></p> -<p id="t514" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t515" class="stm run hide_run"> <span class="nam">max_density</span> <span class="op">=</span> <span class="num">1.0473e+3</span><span class="strut"> </span></p> -<p id="t516" class="stm run hide_run"> <span class="nam">min_density</span> <span class="op">=</span> <span class="num">998.4118</span><span class="strut"> </span></p> -<p id="t517" class="stm run hide_run"> <span class="nam">density_array</span><span class="op">[</span><span class="nam">density_array</span> <span class="op">></span> <span class="nam">max_density</span><span class="op">]</span> <span class="op">=</span> <span class="nam">max_density</span><span class="strut"> </span></p> -<p id="t518" class="stm run hide_run"> <span class="nam">density_array</span><span class="op">[</span><span class="nam">density_array</span> <span class="op"><</span> <span class="nam">min_density</span><span class="op">]</span> <span class="op">=</span> <span class="nam">min_density</span><span class="strut"> </span></p> -<p id="t519" class="pln"><span class="strut"> </span></p> -<p id="t520" class="stm run hide_run"> <span class="op">@</span><span class="nam">staticmethod</span><span class="strut"> </span></p> -<p id="t521" class="pln"> <span class="key">def</span> <span class="nam">_check_diameter_range</span><span class="op">(</span><span class="nam">diameter_array</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t522" class="pln"> <span class="str">"""Modifies input array so any outlier diameters are set</span><span class="strut"> </span></p> -<p id="t523" class="pln"><span class="str"> to the respective min or max of the range</span><span class="strut"> </span></p> -<p id="t524" class="pln"><span class="strut"> </span></p> -<p id="t525" class="pln"><span class="str"> :param diameter_array: input diameter array (mm)</span><span class="strut"> </span></p> -<p id="t526" class="pln"><span class="str"> :type: np.ndarray</span><span class="strut"> </span></p> -<p id="t527" class="pln"><span class="strut"> </span></p> -<p id="t528" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t529" class="stm run hide_run"> <span class="nam">max_diameter</span> <span class="op">=</span> <span class="num">5.6750</span><span class="strut"> </span></p> -<p id="t530" class="stm run hide_run"> <span class="nam">min_diameter</span> <span class="op">=</span> <span class="num">1.2250</span><span class="strut"> </span></p> -<p id="t531" class="stm run hide_run"> <span class="nam">diameter_array</span><span class="op">[</span><span class="nam">diameter_array</span> <span class="op">></span> <span class="nam">max_diameter</span><span class="op">]</span> <span class="op">=</span> <span class="nam">max_diameter</span><span class="strut"> </span></p> -<p id="t532" class="stm run hide_run"> <span class="nam">diameter_array</span><span class="op">[</span><span class="nam">diameter_array</span> <span class="op"><</span> <span class="nam">min_diameter</span><span class="op">]</span> <span class="op">=</span> <span class="nam">min_diameter</span><span class="strut"> </span></p> -<p id="t533" class="pln"><span class="strut"> </span></p> -<p id="t534" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_mean_density</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t535" class="pln"> <span class="str">"""Returns an array of the mean density (kg/m**3) of the</span><span class="strut"> </span></p> -<p id="t536" class="pln"><span class="str"> collection carp eggs at each time step</span><span class="strut"> </span></p> -<p id="t537" class="pln"><span class="strut"> </span></p> -<p id="t538" class="pln"><span class="str"> :return: mean density (kg/m**3) of carp eggs</span><span class="strut"> </span></p> -<p id="t539" class="pln"><span class="str"> :rtype: float</span><span class="strut"> </span></p> -<p id="t540" class="pln"><span class="strut"> </span></p> -<p id="t541" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t542" class="stm run hide_run"> <span class="nam">a</span> <span class="op">=</span> <span class="num">29.09</span><span class="strut"> </span></p> -<p id="t543" class="stm run hide_run"> <span class="nam">b</span> <span class="op">=</span> <span class="num">1812</span><span class="strut"> </span></p> -<p id="t544" class="stm run hide_run"> <span class="nam">c</span> <span class="op">=</span> <span class="num">999.8</span><span class="strut"> </span></p> -<p id="t545" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_calc_mean_density</span><span class="op">(</span><span class="nam">a</span><span class="op">,</span> <span class="nam">b</span><span class="op">,</span> <span class="nam">c</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t546" class="pln"><span class="strut"> </span></p> -<p id="t547" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_mean_diameter</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t548" class="pln"> <span class="str">"""Returns an array of the mean diameter (mm) of the</span><span class="strut"> </span></p> -<p id="t549" class="pln"><span class="str"> collection of carp eggs at each time step</span><span class="strut"> </span></p> -<p id="t550" class="pln"><span class="strut"> </span></p> -<p id="t551" class="pln"><span class="str"> :return: array of mean diameter (mm) of carp eggs at each time step</span><span class="strut"> </span></p> -<p id="t552" class="pln"><span class="str"> :rtype: np.ndarray</span><span class="strut"> </span></p> -<p id="t553" class="pln"><span class="strut"> </span></p> -<p id="t554" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t555" class="stm run hide_run"> <span class="nam">a</span> <span class="op">=</span> <span class="num">4.56</span><span class="strut"> </span></p> -<p id="t556" class="stm run hide_run"> <span class="nam">b</span> <span class="op">=</span> <span class="num">2314</span><span class="strut"> </span></p> -<p id="t557" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_calc_mean_diameter</span><span class="op">(</span><span class="nam">a</span><span class="op">,</span> <span class="nam">b</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t558" class="pln"><span class="strut"> </span></p> -<p id="t559" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_density_std</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t560" class="pln"> <span class="str">"""Returns an array of the density standard deviation (kg/m**3)</span><span class="strut"> </span></p> -<p id="t561" class="pln"><span class="str"> of the collection of carp eggs at each time step</span><span class="strut"> </span></p> -<p id="t562" class="pln"><span class="strut"> </span></p> -<p id="t563" class="pln"><span class="str"> :return: density std array (kg/m**3) of carp eggs at each time step</span><span class="strut"> </span></p> -<p id="t564" class="pln"><span class="str"> :rtype: np.ndarray</span><span class="strut"> </span></p> -<p id="t565" class="pln"><span class="strut"> </span></p> -<p id="t566" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t567" class="stm run hide_run"> <span class="nam">a</span> <span class="op">=</span> <span class="num">19.28</span><span class="strut"> </span></p> -<p id="t568" class="stm run hide_run"> <span class="nam">b</span> <span class="op">=</span> <span class="num">1973</span><span class="strut"> </span></p> -<p id="t569" class="stm run hide_run"> <span class="nam">c</span> <span class="op">=</span> <span class="num">1.029</span><span class="strut"> </span></p> -<p id="t570" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_calc_density_std</span><span class="op">(</span><span class="nam">a</span><span class="op">,</span> <span class="nam">b</span><span class="op">,</span> <span class="nam">c</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t571" class="pln"><span class="strut"> </span></p> -<p id="t572" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_diameter_std</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t573" class="pln"> <span class="str">"""Returns an array of the diameter standard deviation (mm)</span><span class="strut"> </span></p> -<p id="t574" class="pln"><span class="str"> of the collection of carp eggs at each time step</span><span class="strut"> </span></p> -<p id="t575" class="pln"><span class="strut"> </span></p> -<p id="t576" class="pln"><span class="str"> :return: diamter std array (mm) of carp eggs at each time step</span><span class="strut"> </span></p> -<p id="t577" class="pln"><span class="str"> :rtype: np.ndarray</span><span class="strut"> </span></p> -<p id="t578" class="pln"><span class="strut"> </span></p> -<p id="t579" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t580" class="stm run hide_run"> <span class="nam">a</span> <span class="op">=</span> <span class="num">0.4759</span><span class="strut"> </span></p> -<p id="t581" class="stm run hide_run"> <span class="nam">b</span> <span class="op">=</span> <span class="num">14150</span><span class="strut"> </span></p> -<p id="t582" class="stm run hide_run"> <span class="nam">c</span> <span class="op">=</span> <span class="num">0.4586</span><span class="strut"> </span></p> -<p id="t583" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_calc_diameter_std</span><span class="op">(</span><span class="nam">a</span><span class="op">,</span> <span class="nam">b</span><span class="op">,</span> <span class="nam">c</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t584" class="pln"><span class="strut"> </span></p> -<p id="t585" class="stm run hide_run"> <span class="op">@</span><span class="nam">classmethod</span><span class="strut"> </span></p> -<p id="t586" class="stm run hide_run"> <span class="key">def</span> <span class="nam">gas_bladder_inflation_time</span><span class="op">(</span><span class="nam">cls</span><span class="op">,</span> <span class="nam">temperature</span><span class="op">=</span><span class="key">None</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t587" class="pln"><span class="strut"> </span></p> -<p id="t588" class="stm run hide_run"> <span class="nam">tmin2</span> <span class="op">=</span> <span class="num">13.3</span><span class="strut"> </span></p> -<p id="t589" class="stm run hide_run"> <span class="nam">meanctu_gas_bladder</span> <span class="op">=</span> <span class="num">1100.82</span><span class="strut"> </span></p> -<p id="t590" class="pln"><span class="strut"> </span></p> -<p id="t591" class="stm run hide_run"> <span class="key">return</span> <span class="nam">cls</span><span class="op">.</span><span class="nam">_calc_gas_bladder_inflation_time</span><span class="op">(</span><span class="nam">tmin2</span><span class="op">,</span> <span class="nam">meanctu_gas_bladder</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t592" class="pln"> <span class="nam">temperature</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t593" class="pln"><span class="strut"> </span></p> -<p id="t594" class="stm run hide_run"> <span class="op">@</span><span class="nam">classmethod</span><span class="strut"> </span></p> -<p id="t595" class="stm run hide_run"> <span class="key">def</span> <span class="nam">hatching_time</span><span class="op">(</span><span class="nam">cls</span><span class="op">,</span> <span class="nam">temperature</span><span class="op">=</span><span class="key">None</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t596" class="pln"> <span class="str">"""Returns the hatching time of carp eggs</span><span class="strut"> </span></p> -<p id="t597" class="pln"><span class="str"> based on input temperature</span><span class="strut"> </span></p> -<p id="t598" class="pln"><span class="strut"> </span></p> -<p id="t599" class="pln"><span class="str"> :param temperature: Temperature of eggs(Celsius)</span><span class="strut"> </span></p> -<p id="t600" class="pln"><span class="str"> :type: float</span><span class="strut"> </span></p> -<p id="t601" class="pln"><span class="str"> :return: hatching time of eggs (hr)</span><span class="strut"> </span></p> -<p id="t602" class="pln"><span class="str"> :rtype: float</span><span class="strut"> </span></p> -<p id="t603" class="pln"><span class="strut"> </span></p> -<p id="t604" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t605" class="stm run hide_run"> <span class="nam">a</span> <span class="op">=</span> <span class="num">3.677e+7</span><span class="strut"> </span></p> -<p id="t606" class="stm run hide_run"> <span class="nam">b</span> <span class="op">=</span> <span class="op">-</span><span class="num">4.788</span><span class="strut"> </span></p> -<p id="t607" class="stm run hide_run"> <span class="nam">c</span> <span class="op">=</span> <span class="num">18.87</span><span class="strut"> </span></p> -<p id="t608" class="stm run hide_run"> <span class="key">return</span> <span class="nam">cls</span><span class="op">.</span><span class="nam">_calc_hatching_time</span><span class="op">(</span><span class="nam">a</span><span class="op">,</span> <span class="nam">b</span><span class="op">,</span> <span class="nam">c</span><span class="op">,</span> <span class="nam">temperature</span><span class="op">)</span><span class="strut"> </span></p> - - </td> - </tr> - </table> -</div> - -<div id="footer"> - <div class="content"> - <p> - <a class="nav" href="index.html">« index</a> <a class="nav" href="https://coverage.readthedocs.io">coverage.py v4.5.3</a>, - created at 2019-07-09 15:15 - </p> - </div> -</div> - -</body> -</html> diff --git a/coverage_report/fluegg_drift_py.html b/coverage_report/fluegg_drift_py.html deleted file mode 100644 index a4b7b4c..0000000 --- a/coverage_report/fluegg_drift_py.html +++ /dev/null @@ -1,393 +0,0 @@ - - - -<!DOCTYPE html> -<html> -<head> - <meta http-equiv="Content-Type" content="text/html; charset=utf-8"> - - - <meta http-equiv="X-UA-Compatible" content="IE=emulateIE7" /> - <title>Coverage for fluegg\drift.py: 89%</title> - <link rel="stylesheet" href="style.css" type="text/css"> - - <script type="text/javascript" src="jquery.min.js"></script> - <script type="text/javascript" src="jquery.hotkeys.js"></script> - <script type="text/javascript" src="jquery.isonscreen.js"></script> - <script type="text/javascript" src="coverage_html.js"></script> - <script type="text/javascript"> - jQuery(document).ready(coverage.pyfile_ready); - </script> -</head> -<body class="pyfile"> - -<div id="header"> - <div class="content"> - <h1>Coverage for <b>fluegg\drift.py</b> : - <span class="pc_cov">89%</span> - </h1> - - <img id="keyboard_icon" src="keybd_closed.png" alt="Show keyboard shortcuts" /> - - <h2 class="stats"> - 56 statements - <span class="run hide_run shortkey_r button_toggle_run">50 run</span> - <span class="mis shortkey_m button_toggle_mis">6 missing</span> - <span class="exc shortkey_x 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href="#n146">146</a></p> -<p id="n147" class="pln"><a href="#n147">147</a></p> -<p id="n148" class="pln"><a href="#n148">148</a></p> -<p id="n149" class="pln"><a href="#n149">149</a></p> -<p id="n150" class="pln"><a href="#n150">150</a></p> -<p id="n151" class="pln"><a href="#n151">151</a></p> -<p id="n152" class="stm run hide_run"><a href="#n152">152</a></p> - - </td> - <td class="text"> -<p id="t1" class="stm run hide_run"><span class="key">from</span> <span class="nam">abc</span> <span class="key">import</span> <span class="nam">abstractmethod</span><span class="strut"> </span></p> -<p id="t2" class="pln"><span class="strut"> </span></p> -<p id="t3" class="stm run hide_run"><span class="key">import</span> <span class="nam">numpy</span> <span class="key">as</span> <span class="nam">np</span><span class="strut"> </span></p> -<p id="t4" class="pln"><span class="strut"> </span></p> -<p id="t5" class="pln"><span class="strut"> </span></p> -<p id="t6" class="stm run hide_run"><span class="key">class</span> <span class="nam">DriftingParticle</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t7" class="pln"><span class="strut"> </span></p> -<p id="t8" class="stm run hide_run"> <span class="op">@</span><span class="nam">staticmethod</span><span class="strut"> </span></p> -<p id="t9" class="pln"> <span class="key">def</span> <span class="nam">_dietrich_equation</span><span class="op">(</span><span class="nam">water_viscosity</span><span class="op">,</span> <span class="nam">water_density</span><span class="op">,</span> <span class="nam">particle_diameter</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t10" class="pln"> <span class="nam">particle_density</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t11" class="pln"> <span class="str">"""Returns the settling velocity (cm/s) of particles</span><span class="strut"> </span></p> -<p id="t12" class="pln"><span class="str"> calculated using the Dietrich equation.</span><span class="strut"> </span></p> -<p id="t13" class="pln"><span class="strut"> </span></p> -<p id="t14" class="pln"><span class="str"> :param water_viscosity: water viscosity (cm**2/s)</span><span class="strut"> </span></p> -<p id="t15" class="pln"><span class="str"> :type: numpy.ndarray</span><span class="strut"> </span></p> -<p id="t16" class="pln"><span class="str"> :param water_density: water density (kg/m**3)</span><span class="strut"> </span></p> -<p id="t17" class="pln"><span class="str"> :type: numpy.ndarray</span><span class="strut"> </span></p> -<p id="t18" class="pln"><span class="str"> :param particle_diameter: particle diameter (cm)</span><span class="strut"> </span></p> -<p id="t19" class="pln"><span class="str"> :type: numpy.ndarray</span><span class="strut"> </span></p> -<p id="t20" class="pln"><span class="str"> :param particle_density: particle density (kg/m**3)</span><span class="strut"> </span></p> -<p id="t21" class="pln"><span class="str"> :type: numpy.ndarray</span><span class="strut"> </span></p> -<p id="t22" class="pln"><span class="str"> :return: settling velocity of particle in water (cm/s)</span><span class="strut"> </span></p> -<p id="t23" class="pln"><span class="str"> :rtype: numpy.ndarray</span><span class="strut"> </span></p> -<p id="t24" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t25" class="pln"><span class="strut"> </span></p> -<p id="t26" class="pln"> <span class="com"># Specific gravity of particle</span><span class="strut"> </span></p> -<p id="t27" class="stm run hide_run"> <span class="nam">specific_gravity</span> <span class="op">=</span> <span class="nam">particle_density</span> <span class="op">/</span> <span class="nam">water_density</span><span class="strut"> </span></p> -<p id="t28" class="pln"> <span class="com"># Gravitational acceleration (cm/s**2)</span><span class="strut"> </span></p> -<p id="t29" class="stm run hide_run"> <span class="nam">gravity</span> <span class="op">=</span> <span class="num">981</span><span class="strut"> </span></p> -<p id="t30" class="pln"> <span class="com"># Constants</span><span class="strut"> </span></p> -<p id="t31" class="stm run hide_run"> <span class="nam">b1</span> <span class="op">=</span> <span class="num">2.891394</span><span class="strut"> </span></p> -<p id="t32" class="stm run hide_run"> <span class="nam">b2</span> <span class="op">=</span> <span class="num">0.95296</span><span class="strut"> </span></p> -<p id="t33" class="stm run hide_run"> <span class="nam">b3</span> <span class="op">=</span> <span class="num">0.056835</span><span class="strut"> </span></p> -<p id="t34" class="stm run hide_run"> <span class="nam">b4</span> <span class="op">=</span> <span class="num">0.002892</span><span class="strut"> </span></p> -<p id="t35" class="stm run hide_run"> <span class="nam">b5</span> <span class="op">=</span> <span class="num">0.000245</span><span class="strut"> </span></p> -<p id="t36" class="pln"> <span class="com"># Particle Reynold's number</span><span class="strut"> </span></p> -<p id="t37" class="stm run hide_run"> <span class="nam">temporary</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">sqrt</span><span class="op">(</span><span class="op">(</span><span class="nam">specific_gravity</span> <span class="op">-</span> <span class="num">1</span><span class="op">)</span> <span class="op">*</span><span class="strut"> </span></p> -<p id="t38" class="pln"> <span class="nam">gravity</span> <span class="op">*</span> <span class="nam">particle_diameter</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t39" class="stm run hide_run"> <span class="nam">reynolds_number</span> <span class="op">=</span> <span class="op">(</span><span class="nam">particle_diameter</span> <span class="op">*</span> <span class="nam">temporary</span><span class="op">)</span> <span class="op">/</span> <span class="nam">water_viscosity</span><span class="strut"> </span></p> -<p id="t40" class="pln"> <span class="com"># Rf = Dimensionless terminal particle settling velocity</span><span class="strut"> </span></p> -<p id="t41" class="stm run hide_run"> <span class="nam">Rf</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">exp</span><span class="op">(</span><span class="op">-</span><span class="nam">b1</span> <span class="op">+</span> <span class="op">(</span><span class="nam">b2</span> <span class="op">*</span> <span class="op">(</span><span class="nam">np</span><span class="op">.</span><span class="nam">log</span><span class="op">(</span><span class="nam">reynolds_number</span><span class="op">)</span><span class="op">)</span><span class="op">)</span> <span class="op">-</span><span class="strut"> </span></p> -<p id="t42" class="pln"> <span class="op">(</span><span class="nam">b3</span> <span class="op">*</span> <span class="op">(</span><span class="op">(</span><span class="nam">np</span><span class="op">.</span><span class="nam">log</span><span class="op">(</span><span class="nam">reynolds_number</span><span class="op">)</span><span class="op">)</span> <span class="op">**</span> <span class="num">2</span><span class="op">)</span><span class="op">)</span> <span class="op">-</span><span class="strut"> </span></p> -<p id="t43" class="pln"> <span class="op">(</span><span class="nam">b4</span> <span class="op">*</span> <span class="op">(</span><span class="op">(</span><span class="nam">np</span><span class="op">.</span><span class="nam">log</span><span class="op">(</span><span class="nam">reynolds_number</span><span class="op">)</span><span class="op">)</span> <span class="op">**</span> <span class="num">3</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span><span class="strut"> </span></p> -<p id="t44" class="pln"> <span class="op">(</span><span class="nam">b5</span> <span class="op">*</span> <span class="op">(</span><span class="op">(</span><span class="nam">np</span><span class="op">.</span><span class="nam">log</span><span class="op">(</span><span class="nam">reynolds_number</span><span class="op">)</span><span class="op">)</span> <span class="op">**</span> <span class="num">4</span><span class="op">)</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t45" class="stm run hide_run"> <span class="nam">settling_velocity</span> <span class="op">=</span> <span class="nam">Rf</span> <span class="op">*</span> <span class="nam">temporary</span><span class="strut"> </span></p> -<p id="t46" class="stm run hide_run"> <span class="key">return</span> <span class="nam">settling_velocity</span><span class="strut"> </span></p> -<p id="t47" class="pln"><span class="strut"> </span></p> -<p id="t48" class="stm run hide_run"> <span class="op">@</span><span class="nam">abstractmethod</span><span class="strut"> </span></p> -<p id="t49" class="pln"> <span class="key">def</span> <span class="nam">density</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="op">*</span><span class="nam">args</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t50" class="stm mis"> <span class="key">raise</span> <span class="nam">NotImplementedError</span><span class="strut"> </span></p> -<p id="t51" class="pln"><span class="strut"> </span></p> -<p id="t52" class="stm run hide_run"> <span class="op">@</span><span class="nam">abstractmethod</span><span class="strut"> </span></p> -<p id="t53" class="pln"> <span class="key">def</span> <span class="nam">diameter</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t54" class="stm mis"> <span class="key">raise</span> <span class="nam">NotImplementedError</span><span class="strut"> </span></p> -<p id="t55" class="pln"><span class="strut"> </span></p> -<p id="t56" class="stm run hide_run"> <span class="key">def</span> <span class="nam">fall_velocity</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">hydraulic_results</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t57" class="pln"> <span class="str">"""Wrapper for the dietrich equation, returns fall velocity of</span><span class="strut"> </span></p> -<p id="t58" class="pln"><span class="str"> particles (m/s)</span><span class="strut"> </span></p> -<p id="t59" class="pln"><span class="strut"> </span></p> -<p id="t60" class="pln"><span class="str"> :param hydraulic_results: hydraulic results at current particle</span><span class="strut"> </span></p> -<p id="t61" class="pln"><span class="str"> positions</span><span class="strut"> </span></p> -<p id="t62" class="pln"><span class="str"> :type: hydraulics.HydraulicResults</span><span class="strut"> </span></p> -<p id="t63" class="pln"><span class="str"> :return: settling velocity of particle in water (m/s)</span><span class="strut"> </span></p> -<p id="t64" class="pln"><span class="str"> :rtype: numpy.ndarray</span><span class="strut"> </span></p> -<p id="t65" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t66" class="pln"><span class="strut"> </span></p> -<p id="t67" class="pln"> <span class="com"># Calculate the fall velocity using Dietrich Equation based on</span><span class="strut"> </span></p> -<p id="t68" class="pln"> <span class="com"># particle data</span><span class="strut"> </span></p> -<p id="t69" class="stm run hide_run"> <span class="nam">temperature</span> <span class="op">=</span> <span class="nam">hydraulic_results</span><span class="op">.</span><span class="nam">temperature</span><span class="op">(</span><span class="op">)</span> <span class="com"># Celsius</span><span class="strut"> </span></p> -<p id="t70" class="stm run hide_run"> <span class="nam">water_viscosity</span> <span class="op">=</span> <span class="nam">hydraulic_results</span><span class="op">.</span><span class="nam">water_viscosity</span><span class="op">(</span><span class="strut"> </span></p> -<p id="t71" class="pln"> <span class="op">)</span> <span class="op">*</span> <span class="num">100</span> <span class="op">**</span> <span class="num">2</span> <span class="com"># Convert from m**2/s to cm**2/s</span><span class="strut"> </span></p> -<p id="t72" class="stm run hide_run"> <span class="nam">water_density</span> <span class="op">=</span> <span class="nam">hydraulic_results</span><span class="op">.</span><span class="nam">water_density</span><span class="op">(</span><span class="op">)</span> <span class="com"># kg/m**3</span><span class="strut"> </span></p> -<p id="t73" class="stm run hide_run"> <span class="nam">particle_diameter</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">diameter</span><span class="op">(</span><span class="op">)</span> <span class="op">*</span> <span class="num">100</span> <span class="com"># Convert from m to cm</span><span class="strut"> </span></p> -<p id="t74" class="stm run hide_run"> <span class="nam">particle_density</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">density</span><span class="op">(</span><span class="nam">temperature</span><span class="op">)</span> <span class="com"># kg/m**3</span><span class="strut"> </span></p> -<p id="t75" class="pln"><span class="strut"> </span></p> -<p id="t76" class="pln"> <span class="com"># calculate fall velocity as cm/s</span><span class="strut"> </span></p> -<p id="t77" class="stm run hide_run"> <span class="nam">fall_velocity</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_dietrich_equation</span><span class="op">(</span><span class="strut"> </span></p> -<p id="t78" class="pln"> <span class="nam">water_viscosity</span><span class="op">,</span> <span class="nam">water_density</span><span class="op">,</span> <span class="nam">particle_diameter</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t79" class="pln"> <span class="nam">particle_density</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t80" class="pln"><span class="strut"> </span></p> -<p id="t81" class="pln"> <span class="com"># change fall velocity sign to coordinate system</span><span class="strut"> </span></p> -<p id="t82" class="stm run hide_run"> <span class="nam">fall_velocity</span> <span class="op">=</span> <span class="op">-</span><span class="nam">fall_velocity</span><span class="strut"> </span></p> -<p id="t83" class="pln"><span class="strut"> </span></p> -<p id="t84" class="pln"> <span class="com"># convert fall velocity from cm/s to m/s</span><span class="strut"> </span></p> -<p id="t85" class="stm run hide_run"> <span class="key">return</span> <span class="nam">fall_velocity</span> <span class="op">/</span> <span class="num">100</span><span class="strut"> </span></p> -<p id="t86" class="pln"><span class="strut"> </span></p> -<p id="t87" class="stm run hide_run"> <span class="op">@</span><span class="nam">abstractmethod</span><span class="strut"> </span></p> -<p id="t88" class="pln"> <span class="key">def</span> <span class="nam">position</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t89" class="stm mis"> <span class="key">raise</span> <span class="nam">NotImplementedError</span><span class="strut"> </span></p> -<p id="t90" class="pln"><span class="strut"> </span></p> -<p id="t91" class="stm run hide_run"> <span class="op">@</span><span class="nam">abstractmethod</span><span class="strut"> </span></p> -<p id="t92" class="pln"> <span class="key">def</span> <span class="nam">set_position</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">position</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t93" class="stm mis"> <span class="key">raise</span> <span class="nam">NotImplementedError</span><span class="strut"> </span></p> -<p id="t94" class="pln"><span class="strut"> </span></p> -<p id="t95" class="pln"><span class="strut"> </span></p> -<p id="t96" class="stm run hide_run"><span class="key">class</span> <span class="nam">ConstantDriftingParticle</span><span class="op">(</span><span class="nam">DriftingParticle</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t97" class="pln"><span class="strut"> </span></p> -<p id="t98" class="stm run hide_run"> <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">density</span><span class="op">,</span> <span class="nam">diameter</span><span class="op">,</span> <span class="nam">initial_position</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t99" class="pln"><span class="strut"> </span></p> -<p id="t100" class="stm run hide_run"> <span class="nam">initial_position</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">array</span><span class="op">(</span><span class="nam">initial_position</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t101" class="stm run hide_run"> <span class="nam">density</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">array</span><span class="op">(</span><span class="nam">density</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t102" class="stm run hide_run"> <span class="nam">diameter</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">array</span><span class="op">(</span><span class="nam">diameter</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t103" class="pln"><span class="strut"> </span></p> -<p id="t104" class="stm run hide_run"> <span class="key">if</span> <span class="nam">initial_position</span><span class="op">.</span><span class="nam">shape</span><span class="op">[</span><span class="num">1</span><span class="op">]</span> <span class="op">==</span> <span class="num">3</span> <span class="key">and</span> <span class="nam">initial_position</span><span class="op">.</span><span class="nam">ndim</span> <span class="op">==</span> <span class="num">2</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t105" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_position</span> <span class="op">=</span> <span class="nam">initial_position</span><span class="strut"> </span></p> -<p id="t106" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_number_of_eggs</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_position</span><span class="op">.</span><span class="nam">shape</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t107" class="pln"> <span class="key">else</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t108" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="str">'Initial position array must be n by 3'</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t109" class="pln"><span class="strut"> </span></p> -<p id="t110" class="stm run hide_run"> <span class="nam">number_of_particles</span> <span class="op">=</span> <span class="nam">initial_position</span><span class="op">.</span><span class="nam">shape</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t111" class="pln"><span class="strut"> </span></p> -<p id="t112" class="stm run hide_run"> <span class="key">if</span> <span class="nam">density</span><span class="op">.</span><span class="nam">shape</span><span class="op">[</span><span class="num">0</span><span class="op">]</span> <span class="op">!=</span> <span class="nam">number_of_particles</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t113" class="pln"> <span class="key">or</span> <span class="nam">diameter</span><span class="op">.</span><span class="nam">shape</span><span class="op">[</span><span class="num">0</span><span class="op">]</span> <span class="op">!=</span> <span class="nam">number_of_particles</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t114" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="strut"> </span></p> -<p id="t115" class="pln"> <span class="str">'The zero axis of density, diameter, and initial_position '</span> <span class="op">+</span><span class="strut"> </span></p> -<p id="t116" class="pln"> <span class="str">'must be consistent'</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t117" class="pln"><span class="strut"> </span></p> -<p id="t118" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_density</span> <span class="op">=</span> <span class="nam">density</span><span class="strut"> </span></p> -<p id="t119" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_diameter</span> <span class="op">=</span> <span class="nam">diameter</span><span class="strut"> </span></p> -<p id="t120" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_position</span> <span class="op">=</span> <span class="nam">initial_position</span><span class="strut"> </span></p> -<p id="t121" class="pln"><span class="strut"> </span></p> -<p id="t122" class="stm run hide_run"> <span class="key">def</span> <span class="nam">density</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="op">*</span><span class="nam">args</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t123" class="pln"> <span class="str">"""</span><span class="strut"> </span></p> -<p id="t124" class="pln"><span class="strut"> </span></p> -<p id="t125" class="pln"><span class="str"> :return:</span><span class="strut"> </span></p> -<p id="t126" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t127" class="pln"><span class="strut"> </span></p> -<p id="t128" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_density</span><span class="strut"> </span></p> -<p id="t129" class="pln"><span class="strut"> </span></p> -<p id="t130" class="stm run hide_run"> <span class="key">def</span> <span class="nam">diameter</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t131" class="pln"> <span class="str">"""</span><span class="strut"> </span></p> -<p id="t132" class="pln"><span class="strut"> </span></p> -<p id="t133" class="pln"><span class="str"> :return:</span><span class="strut"> </span></p> -<p id="t134" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t135" class="pln"><span class="strut"> </span></p> -<p id="t136" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_diameter</span><span class="strut"> </span></p> -<p id="t137" class="pln"><span class="strut"> </span></p> -<p id="t138" class="stm run hide_run"> <span class="key">def</span> <span class="nam">position</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t139" class="pln"> <span class="str">"""</span><span class="strut"> </span></p> -<p id="t140" class="pln"><span class="strut"> </span></p> -<p id="t141" class="pln"><span class="str"> :return:</span><span class="strut"> </span></p> -<p id="t142" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t143" class="pln"><span class="strut"> </span></p> -<p id="t144" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_position</span><span class="strut"> </span></p> -<p id="t145" class="pln"><span class="strut"> </span></p> -<p id="t146" class="stm run hide_run"> <span class="key">def</span> <span class="nam">set_position</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">position</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t147" class="pln"> <span class="str">"""</span><span class="strut"> </span></p> -<p id="t148" class="pln"><span class="strut"> </span></p> -<p id="t149" class="pln"><span class="str"> :return:</span><span class="strut"> </span></p> -<p id="t150" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t151" class="pln"><span class="strut"> </span></p> -<p id="t152" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_position</span> <span class="op">=</span> <span class="nam">position</span><span class="strut"> </span></p> - - </td> - </tr> - </table> -</div> - -<div id="footer"> - <div class="content"> - <p> - <a class="nav" href="index.html">« index</a> <a class="nav" href="https://coverage.readthedocs.io">coverage.py v4.5.3</a>, - created at 2019-07-09 15:15 - </p> - </div> -</div> - -</body> -</html> diff --git a/coverage_report/fluegg_gui___init___py.html b/coverage_report/fluegg_gui___init___py.html deleted file mode 100644 index f798c84..0000000 --- a/coverage_report/fluegg_gui___init___py.html +++ /dev/null @@ -1,89 +0,0 @@ - - - -<!DOCTYPE html> -<html> -<head> - <meta http-equiv="Content-Type" content="text/html; charset=utf-8"> - - - <meta http-equiv="X-UA-Compatible" content="IE=emulateIE7" /> - <title>Coverage for fluegg\gui\__init__.py: 100%</title> - <link rel="stylesheet" href="style.css" type="text/css"> - - <script type="text/javascript" src="jquery.min.js"></script> - <script type="text/javascript" src="jquery.hotkeys.js"></script> - <script type="text/javascript" src="jquery.isonscreen.js"></script> - <script type="text/javascript" src="coverage_html.js"></script> - <script type="text/javascript"> - jQuery(document).ready(coverage.pyfile_ready); - </script> -</head> -<body class="pyfile"> - -<div id="header"> - <div class="content"> - <h1>Coverage for <b>fluegg\gui\__init__.py</b> : - <span class="pc_cov">100%</span> - </h1> - - <img id="keyboard_icon" src="keybd_closed.png" alt="Show keyboard shortcuts" /> - - <h2 class="stats"> - 0 statements - <span class="run hide_run shortkey_r button_toggle_run">0 run</span> - <span class="mis shortkey_m button_toggle_mis">0 missing</span> - <span class="exc shortkey_x button_toggle_exc">0 excluded</span> - - - </h2> - </div> -</div> - -<div class="help_panel"> - <img id="panel_icon" src="keybd_open.png" alt="Hide keyboard shortcuts" /> - <p class="legend">Hot-keys on this page</p> - <div> - <p class="keyhelp"> - <span class="key">r</span> - <span class="key">m</span> - <span class="key">x</span> - <span class="key">p</span> toggle line displays - </p> - <p class="keyhelp"> - <span class="key">j</span> - <span class="key">k</span> next/prev highlighted chunk - </p> - <p class="keyhelp"> - <span class="key">0</span> (zero) top of page - </p> - <p class="keyhelp"> - <span class="key">1</span> (one) first highlighted chunk - </p> - </div> -</div> - -<div id="source"> - <table> - <tr> - <td class="linenos"> - - </td> - <td class="text"> - - </td> - </tr> - </table> -</div> - -<div id="footer"> - <div class="content"> - <p> - <a class="nav" href="index.html">« index</a> <a class="nav" href="https://coverage.readthedocs.io">coverage.py v4.5.3</a>, - created at 2019-07-09 15:15 - </p> - </div> -</div> - -</body> -</html> diff --git a/coverage_report/fluegg_gui_gui_layout_py.html b/coverage_report/fluegg_gui_gui_layout_py.html deleted file mode 100644 index 78a11f3..0000000 --- a/coverage_report/fluegg_gui_gui_layout_py.html +++ /dev/null @@ -1,665 +0,0 @@ - - - -<!DOCTYPE html> -<html> -<head> - <meta http-equiv="Content-Type" content="text/html; charset=utf-8"> - - - <meta http-equiv="X-UA-Compatible" content="IE=emulateIE7" /> - <title>Coverage for fluegg\gui\gui_layout.py: 1%</title> - <link rel="stylesheet" href="style.css" type="text/css"> - - <script type="text/javascript" src="jquery.min.js"></script> - <script type="text/javascript" src="jquery.hotkeys.js"></script> - <script type="text/javascript" src="jquery.isonscreen.js"></script> - <script type="text/javascript" src="coverage_html.js"></script> - <script type="text/javascript"> - jQuery(document).ready(coverage.pyfile_ready); - </script> -</head> -<body class="pyfile"> - -<div id="header"> - <div class="content"> - <h1>Coverage for <b>fluegg\gui\gui_layout.py</b> : - <span class="pc_cov">1%</span> - </h1> - - <img id="keyboard_icon" src="keybd_closed.png" alt="Show keyboard shortcuts" /> - - <h2 class="stats"> - 276 statements - <span class="run hide_run shortkey_r button_toggle_run">4 run</span> - <span class="mis shortkey_m button_toggle_mis">272 missing</span> - <span class="exc shortkey_x button_toggle_exc">0 excluded</span> - - - </h2> - </div> -</div> - -<div class="help_panel"> - <img id="panel_icon" src="keybd_open.png" alt="Hide keyboard shortcuts" /> - <p class="legend">Hot-keys on this page</p> - <div> - <p class="keyhelp"> - <span class="key">r</span> - <span class="key">m</span> - <span class="key">x</span> - <span class="key">p</span> toggle line displays - </p> - <p class="keyhelp"> - <span class="key">j</span> - <span class="key">k</span> next/prev highlighted chunk - </p> - <p class="keyhelp"> - <span class="key">0</span> (zero) top of page - </p> - <p class="keyhelp"> - <span class="key">1</span> (one) first highlighted chunk - </p> - </div> -</div> - -<div id="source"> - <table> - <tr> - <td class="linenos"> -<p id="n1" class="pln"><a href="#n1">1</a></p> -<p id="n2" class="pln"><a href="#n2">2</a></p> -<p id="n3" class="pln"><a href="#n3">3</a></p> -<p id="n4" class="pln"><a href="#n4">4</a></p> -<p id="n5" class="pln"><a href="#n5">5</a></p> -<p id="n6" class="pln"><a href="#n6">6</a></p> -<p id="n7" class="pln"><a href="#n7">7</a></p> -<p id="n8" class="pln"><a href="#n8">8</a></p> -<p id="n9" class="stm run hide_run"><a href="#n9">9</a></p> -<p id="n10" class="pln"><a href="#n10">10</a></p> -<p id="n11" class="stm run hide_run"><a href="#n11">11</a></p> -<p id="n12" class="stm run hide_run"><a href="#n12">12</a></p> -<p id="n13" class="stm mis"><a href="#n13">13</a></p> -<p id="n14" class="stm mis"><a href="#n14">14</a></p> -<p id="n15" class="stm mis"><a href="#n15">15</a></p> -<p id="n16" class="stm mis"><a href="#n16">16</a></p> -<p id="n17" class="stm mis"><a href="#n17">17</a></p> -<p id="n18" class="stm mis"><a href="#n18">18</a></p> -<p id="n19" class="stm mis"><a href="#n19">19</a></p> -<p id="n20" class="stm mis"><a href="#n20">20</a></p> -<p id="n21" class="stm mis"><a href="#n21">21</a></p> -<p id="n22" class="stm mis"><a href="#n22">22</a></p> -<p id="n23" class="stm mis"><a href="#n23">23</a></p> -<p id="n24" class="stm mis"><a href="#n24">24</a></p> -<p id="n25" class="stm mis"><a href="#n25">25</a></p> -<p id="n26" class="stm mis"><a href="#n26">26</a></p> -<p id="n27" class="stm mis"><a href="#n27">27</a></p> -<p id="n28" class="stm mis"><a href="#n28">28</a></p> -<p id="n29" class="stm mis"><a href="#n29">29</a></p> -<p id="n30" class="stm mis"><a href="#n30">30</a></p> -<p id="n31" class="stm mis"><a href="#n31">31</a></p> -<p id="n32" class="stm mis"><a href="#n32">32</a></p> -<p id="n33" class="stm mis"><a href="#n33">33</a></p> -<p id="n34" class="stm mis"><a href="#n34">34</a></p> -<p id="n35" class="stm mis"><a href="#n35">35</a></p> -<p id="n36" class="stm mis"><a href="#n36">36</a></p> -<p id="n37" class="stm mis"><a href="#n37">37</a></p> -<p id="n38" class="stm mis"><a href="#n38">38</a></p> -<p id="n39" class="stm mis"><a href="#n39">39</a></p> -<p id="n40" class="stm mis"><a href="#n40">40</a></p> -<p id="n41" class="stm mis"><a href="#n41">41</a></p> -<p id="n42" class="stm mis"><a href="#n42">42</a></p> -<p id="n43" class="stm mis"><a href="#n43">43</a></p> -<p id="n44" class="stm mis"><a href="#n44">44</a></p> -<p id="n45" class="stm mis"><a href="#n45">45</a></p> -<p id="n46" class="stm mis"><a href="#n46">46</a></p> -<p id="n47" class="stm mis"><a href="#n47">47</a></p> -<p id="n48" class="stm mis"><a href="#n48">48</a></p> -<p id="n49" class="stm mis"><a href="#n49">49</a></p> -<p id="n50" class="stm mis"><a href="#n50">50</a></p> -<p id="n51" class="stm mis"><a href="#n51">51</a></p> -<p id="n52" class="stm mis"><a href="#n52">52</a></p> -<p id="n53" class="stm mis"><a href="#n53">53</a></p> -<p id="n54" class="stm mis"><a href="#n54">54</a></p> -<p id="n55" class="stm mis"><a href="#n55">55</a></p> -<p id="n56" class="stm mis"><a href="#n56">56</a></p> -<p id="n57" class="stm mis"><a href="#n57">57</a></p> -<p id="n58" class="stm mis"><a href="#n58">58</a></p> -<p id="n59" class="stm mis"><a href="#n59">59</a></p> -<p id="n60" class="stm mis"><a href="#n60">60</a></p> -<p id="n61" class="stm mis"><a href="#n61">61</a></p> -<p id="n62" class="stm mis"><a href="#n62">62</a></p> -<p id="n63" class="stm mis"><a href="#n63">63</a></p> -<p id="n64" class="stm mis"><a href="#n64">64</a></p> -<p id="n65" class="stm mis"><a href="#n65">65</a></p> -<p id="n66" class="stm mis"><a href="#n66">66</a></p> -<p id="n67" class="stm mis"><a href="#n67">67</a></p> -<p id="n68" class="stm mis"><a href="#n68">68</a></p> -<p id="n69" class="stm mis"><a href="#n69">69</a></p> -<p id="n70" class="stm mis"><a href="#n70">70</a></p> -<p id="n71" class="stm mis"><a href="#n71">71</a></p> -<p id="n72" class="stm mis"><a href="#n72">72</a></p> -<p id="n73" class="stm mis"><a href="#n73">73</a></p> -<p id="n74" class="stm mis"><a href="#n74">74</a></p> -<p id="n75" class="stm mis"><a href="#n75">75</a></p> -<p id="n76" class="stm mis"><a href="#n76">76</a></p> -<p id="n77" class="stm mis"><a href="#n77">77</a></p> -<p id="n78" class="stm mis"><a href="#n78">78</a></p> -<p id="n79" class="stm mis"><a href="#n79">79</a></p> -<p id="n80" class="stm mis"><a href="#n80">80</a></p> -<p id="n81" class="stm mis"><a href="#n81">81</a></p> -<p id="n82" class="stm mis"><a href="#n82">82</a></p> -<p id="n83" class="stm mis"><a href="#n83">83</a></p> -<p id="n84" class="stm mis"><a href="#n84">84</a></p> -<p id="n85" class="stm mis"><a href="#n85">85</a></p> -<p id="n86" class="stm mis"><a href="#n86">86</a></p> -<p id="n87" class="stm mis"><a href="#n87">87</a></p> -<p id="n88" class="stm mis"><a href="#n88">88</a></p> -<p id="n89" class="stm mis"><a href="#n89">89</a></p> -<p id="n90" class="stm mis"><a href="#n90">90</a></p> -<p id="n91" class="stm mis"><a href="#n91">91</a></p> -<p id="n92" class="stm mis"><a href="#n92">92</a></p> -<p id="n93" class="stm mis"><a href="#n93">93</a></p> -<p id="n94" class="stm mis"><a href="#n94">94</a></p> -<p id="n95" class="stm mis"><a href="#n95">95</a></p> -<p id="n96" class="stm mis"><a href="#n96">96</a></p> -<p id="n97" class="stm mis"><a href="#n97">97</a></p> -<p id="n98" class="stm mis"><a href="#n98">98</a></p> -<p id="n99" class="stm mis"><a href="#n99">99</a></p> -<p id="n100" class="stm mis"><a href="#n100">100</a></p> -<p id="n101" class="stm mis"><a href="#n101">101</a></p> -<p id="n102" class="stm mis"><a href="#n102">102</a></p> -<p id="n103" class="stm mis"><a href="#n103">103</a></p> -<p id="n104" class="stm mis"><a href="#n104">104</a></p> -<p id="n105" class="stm mis"><a href="#n105">105</a></p> -<p id="n106" class="stm mis"><a href="#n106">106</a></p> -<p id="n107" class="stm mis"><a href="#n107">107</a></p> -<p id="n108" class="stm mis"><a href="#n108">108</a></p> -<p id="n109" class="stm mis"><a href="#n109">109</a></p> -<p id="n110" class="stm mis"><a href="#n110">110</a></p> -<p id="n111" class="stm mis"><a href="#n111">111</a></p> -<p id="n112" class="stm mis"><a href="#n112">112</a></p> -<p id="n113" class="stm mis"><a href="#n113">113</a></p> -<p id="n114" class="stm mis"><a href="#n114">114</a></p> -<p id="n115" class="stm mis"><a href="#n115">115</a></p> -<p id="n116" class="stm mis"><a href="#n116">116</a></p> -<p id="n117" class="stm mis"><a href="#n117">117</a></p> -<p id="n118" class="stm mis"><a href="#n118">118</a></p> -<p id="n119" class="stm mis"><a href="#n119">119</a></p> -<p id="n120" class="stm mis"><a href="#n120">120</a></p> -<p id="n121" class="stm mis"><a href="#n121">121</a></p> -<p id="n122" class="stm mis"><a href="#n122">122</a></p> -<p id="n123" class="stm mis"><a href="#n123">123</a></p> -<p id="n124" class="stm mis"><a href="#n124">124</a></p> -<p id="n125" class="stm mis"><a href="#n125">125</a></p> -<p id="n126" class="stm mis"><a href="#n126">126</a></p> -<p id="n127" class="stm mis"><a href="#n127">127</a></p> -<p id="n128" class="stm mis"><a href="#n128">128</a></p> -<p id="n129" class="stm mis"><a href="#n129">129</a></p> -<p id="n130" class="stm mis"><a href="#n130">130</a></p> -<p id="n131" class="stm mis"><a href="#n131">131</a></p> -<p id="n132" class="stm mis"><a href="#n132">132</a></p> -<p id="n133" class="stm mis"><a href="#n133">133</a></p> -<p id="n134" class="stm mis"><a href="#n134">134</a></p> -<p id="n135" class="stm mis"><a href="#n135">135</a></p> -<p id="n136" class="stm mis"><a href="#n136">136</a></p> -<p id="n137" class="stm mis"><a href="#n137">137</a></p> -<p id="n138" class="stm mis"><a href="#n138">138</a></p> -<p id="n139" class="stm mis"><a href="#n139">139</a></p> -<p id="n140" class="stm mis"><a href="#n140">140</a></p> -<p id="n141" class="stm mis"><a href="#n141">141</a></p> -<p id="n142" class="stm mis"><a href="#n142">142</a></p> -<p id="n143" class="stm mis"><a href="#n143">143</a></p> -<p id="n144" class="stm mis"><a href="#n144">144</a></p> -<p id="n145" class="stm mis"><a href="#n145">145</a></p> -<p id="n146" class="stm mis"><a href="#n146">146</a></p> -<p id="n147" class="stm mis"><a href="#n147">147</a></p> -<p id="n148" class="stm mis"><a href="#n148">148</a></p> -<p id="n149" class="stm mis"><a href="#n149">149</a></p> -<p id="n150" class="stm mis"><a href="#n150">150</a></p> -<p id="n151" class="stm mis"><a href="#n151">151</a></p> -<p id="n152" class="stm mis"><a href="#n152">152</a></p> -<p id="n153" class="stm mis"><a href="#n153">153</a></p> -<p id="n154" class="stm mis"><a href="#n154">154</a></p> -<p id="n155" class="stm mis"><a href="#n155">155</a></p> -<p id="n156" class="stm mis"><a href="#n156">156</a></p> -<p id="n157" class="stm mis"><a href="#n157">157</a></p> -<p id="n158" class="stm mis"><a href="#n158">158</a></p> -<p id="n159" class="stm mis"><a href="#n159">159</a></p> -<p id="n160" class="stm mis"><a href="#n160">160</a></p> -<p id="n161" class="stm mis"><a href="#n161">161</a></p> -<p id="n162" class="stm mis"><a href="#n162">162</a></p> -<p id="n163" class="stm mis"><a href="#n163">163</a></p> -<p id="n164" class="stm mis"><a href="#n164">164</a></p> -<p id="n165" class="stm mis"><a href="#n165">165</a></p> -<p id="n166" class="stm mis"><a href="#n166">166</a></p> -<p id="n167" class="stm mis"><a href="#n167">167</a></p> -<p id="n168" class="stm mis"><a href="#n168">168</a></p> -<p id="n169" class="stm mis"><a href="#n169">169</a></p> -<p id="n170" class="stm mis"><a href="#n170">170</a></p> -<p id="n171" class="stm mis"><a href="#n171">171</a></p> -<p id="n172" class="stm mis"><a href="#n172">172</a></p> -<p id="n173" class="stm mis"><a href="#n173">173</a></p> -<p id="n174" class="stm mis"><a href="#n174">174</a></p> -<p id="n175" class="stm mis"><a href="#n175">175</a></p> -<p id="n176" class="stm mis"><a href="#n176">176</a></p> -<p id="n177" class="stm mis"><a href="#n177">177</a></p> -<p id="n178" class="stm mis"><a href="#n178">178</a></p> -<p id="n179" class="stm mis"><a href="#n179">179</a></p> -<p id="n180" class="stm mis"><a href="#n180">180</a></p> -<p id="n181" class="stm mis"><a href="#n181">181</a></p> -<p id="n182" class="stm mis"><a href="#n182">182</a></p> -<p id="n183" class="stm mis"><a href="#n183">183</a></p> -<p id="n184" class="stm mis"><a href="#n184">184</a></p> -<p id="n185" class="stm mis"><a href="#n185">185</a></p> -<p id="n186" class="stm mis"><a href="#n186">186</a></p> -<p id="n187" class="stm mis"><a href="#n187">187</a></p> -<p id="n188" class="stm mis"><a href="#n188">188</a></p> -<p id="n189" class="stm mis"><a href="#n189">189</a></p> -<p id="n190" class="stm mis"><a href="#n190">190</a></p> -<p id="n191" class="stm mis"><a href="#n191">191</a></p> -<p id="n192" class="stm mis"><a href="#n192">192</a></p> -<p id="n193" class="stm mis"><a href="#n193">193</a></p> -<p id="n194" class="stm mis"><a href="#n194">194</a></p> -<p id="n195" class="stm mis"><a href="#n195">195</a></p> -<p id="n196" class="stm mis"><a href="#n196">196</a></p> -<p id="n197" class="stm mis"><a href="#n197">197</a></p> -<p id="n198" class="stm mis"><a href="#n198">198</a></p> -<p id="n199" class="stm mis"><a href="#n199">199</a></p> -<p id="n200" class="stm mis"><a href="#n200">200</a></p> -<p id="n201" class="stm mis"><a href="#n201">201</a></p> -<p id="n202" class="stm mis"><a href="#n202">202</a></p> -<p id="n203" class="stm mis"><a href="#n203">203</a></p> -<p id="n204" class="stm mis"><a href="#n204">204</a></p> -<p id="n205" class="stm mis"><a href="#n205">205</a></p> -<p id="n206" class="stm mis"><a href="#n206">206</a></p> -<p id="n207" class="stm mis"><a href="#n207">207</a></p> -<p id="n208" class="stm mis"><a href="#n208">208</a></p> -<p id="n209" class="stm mis"><a href="#n209">209</a></p> -<p id="n210" class="stm mis"><a href="#n210">210</a></p> -<p id="n211" class="stm mis"><a href="#n211">211</a></p> -<p id="n212" class="stm mis"><a href="#n212">212</a></p> -<p id="n213" class="stm mis"><a href="#n213">213</a></p> -<p id="n214" class="stm mis"><a href="#n214">214</a></p> -<p id="n215" class="stm mis"><a href="#n215">215</a></p> -<p id="n216" class="stm mis"><a href="#n216">216</a></p> -<p id="n217" class="stm mis"><a href="#n217">217</a></p> -<p id="n218" class="stm mis"><a href="#n218">218</a></p> -<p id="n219" class="stm mis"><a href="#n219">219</a></p> -<p id="n220" class="stm mis"><a href="#n220">220</a></p> -<p id="n221" class="stm mis"><a href="#n221">221</a></p> -<p id="n222" class="stm mis"><a href="#n222">222</a></p> -<p id="n223" class="stm mis"><a href="#n223">223</a></p> -<p id="n224" class="stm mis"><a href="#n224">224</a></p> -<p id="n225" class="stm mis"><a href="#n225">225</a></p> -<p id="n226" class="stm mis"><a href="#n226">226</a></p> -<p id="n227" class="stm mis"><a href="#n227">227</a></p> -<p id="n228" class="stm mis"><a href="#n228">228</a></p> -<p id="n229" class="stm mis"><a href="#n229">229</a></p> -<p id="n230" class="stm mis"><a href="#n230">230</a></p> -<p id="n231" class="stm mis"><a href="#n231">231</a></p> -<p id="n232" class="stm mis"><a href="#n232">232</a></p> -<p id="n233" class="stm mis"><a href="#n233">233</a></p> -<p id="n234" class="stm mis"><a href="#n234">234</a></p> -<p id="n235" class="stm mis"><a href="#n235">235</a></p> -<p id="n236" class="stm mis"><a href="#n236">236</a></p> -<p id="n237" class="stm mis"><a href="#n237">237</a></p> -<p id="n238" class="stm mis"><a href="#n238">238</a></p> -<p id="n239" class="stm mis"><a href="#n239">239</a></p> -<p id="n240" class="stm mis"><a href="#n240">240</a></p> -<p id="n241" class="stm mis"><a href="#n241">241</a></p> -<p id="n242" class="stm mis"><a href="#n242">242</a></p> -<p id="n243" class="stm mis"><a href="#n243">243</a></p> -<p id="n244" class="stm mis"><a href="#n244">244</a></p> -<p id="n245" class="stm mis"><a href="#n245">245</a></p> -<p id="n246" class="stm mis"><a href="#n246">246</a></p> -<p id="n247" class="stm mis"><a href="#n247">247</a></p> -<p id="n248" class="stm mis"><a href="#n248">248</a></p> -<p id="n249" class="stm mis"><a href="#n249">249</a></p> -<p id="n250" class="stm mis"><a href="#n250">250</a></p> -<p id="n251" class="stm mis"><a href="#n251">251</a></p> -<p id="n252" class="pln"><a href="#n252">252</a></p> -<p id="n253" class="stm mis"><a href="#n253">253</a></p> -<p id="n254" class="stm mis"><a href="#n254">254</a></p> -<p id="n255" class="pln"><a href="#n255">255</a></p> -<p id="n256" class="stm run hide_run"><a href="#n256">256</a></p> -<p id="n257" class="stm mis"><a href="#n257">257</a></p> -<p id="n258" class="stm mis"><a href="#n258">258</a></p> -<p id="n259" class="stm mis"><a href="#n259">259</a></p> -<p id="n260" class="stm mis"><a href="#n260">260</a></p> -<p id="n261" class="stm mis"><a href="#n261">261</a></p> -<p id="n262" class="stm mis"><a href="#n262">262</a></p> -<p id="n263" class="stm mis"><a href="#n263">263</a></p> -<p id="n264" class="stm mis"><a href="#n264">264</a></p> -<p id="n265" class="stm mis"><a href="#n265">265</a></p> -<p id="n266" class="stm mis"><a href="#n266">266</a></p> -<p id="n267" class="stm mis"><a href="#n267">267</a></p> -<p id="n268" class="stm mis"><a href="#n268">268</a></p> -<p id="n269" class="stm mis"><a href="#n269">269</a></p> -<p id="n270" class="stm mis"><a href="#n270">270</a></p> -<p id="n271" class="stm mis"><a href="#n271">271</a></p> -<p id="n272" class="stm mis"><a href="#n272">272</a></p> -<p id="n273" class="stm mis"><a href="#n273">273</a></p> -<p id="n274" class="stm mis"><a href="#n274">274</a></p> -<p id="n275" class="stm mis"><a href="#n275">275</a></p> -<p id="n276" class="stm mis"><a href="#n276">276</a></p> -<p id="n277" class="stm mis"><a href="#n277">277</a></p> -<p id="n278" class="stm mis"><a href="#n278">278</a></p> -<p id="n279" class="stm mis"><a href="#n279">279</a></p> -<p id="n280" class="stm mis"><a href="#n280">280</a></p> -<p id="n281" class="stm mis"><a href="#n281">281</a></p> -<p id="n282" class="stm mis"><a href="#n282">282</a></p> -<p id="n283" class="stm mis"><a href="#n283">283</a></p> -<p id="n284" class="stm mis"><a href="#n284">284</a></p> -<p id="n285" class="stm mis"><a href="#n285">285</a></p> -<p id="n286" class="stm mis"><a href="#n286">286</a></p> -<p id="n287" class="stm mis"><a href="#n287">287</a></p> -<p id="n288" class="pln"><a href="#n288">288</a></p> - - </td> - <td class="text"> -<p id="t1" class="pln"><span class="com"># -*- coding: utf-8 -*-</span><span class="strut"> </span></p> -<p id="t2" class="pln"><span class="strut"> </span></p> -<p id="t3" class="pln"><span class="com"># Form implementation generated from reading ui file 'gui_layout.ui'</span><span class="strut"> </span></p> -<p id="t4" class="pln"><span class="com">#</span><span class="strut"> </span></p> -<p id="t5" class="pln"><span class="com"># Created by: PyQt5 UI code generator 5.11.3</span><span class="strut"> </span></p> -<p id="t6" class="pln"><span class="com">#</span><span class="strut"> </span></p> -<p id="t7" class="pln"><span class="com"># WARNING! All changes made in this file will be lost!</span><span class="strut"> </span></p> -<p id="t8" class="pln"><span class="strut"> </span></p> -<p id="t9" class="stm run hide_run"><span class="key">from</span> <span class="nam">PyQt5</span> <span class="key">import</span> <span class="nam">QtCore</span><span class="op">,</span> <span class="nam">QtGui</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="strut"> </span></p> -<p id="t10" class="pln"><span class="strut"> </span></p> -<p id="t11" class="stm run hide_run"><span class="key">class</span> <span class="nam">Ui_MainWindow</span><span class="op">(</span><span class="nam">object</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t12" class="stm run hide_run"> <span class="key">def</span> <span class="nam">setupUi</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">MainWindow</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t13" class="stm mis"> <span class="nam">MainWindow</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"MainWindow"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t14" class="stm mis"> <span class="nam">MainWindow</span><span class="op">.</span><span class="nam">resize</span><span class="op">(</span><span class="num">334</span><span class="op">,</span> <span class="num">523</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t15" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">centralwidget</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QWidget</span><span class="op">(</span><span class="nam">MainWindow</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t16" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">centralwidget</span><span class="op">.</span><span class="nam">setEnabled</span><span class="op">(</span><span class="key">True</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t17" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">centralwidget</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"centralwidget"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t18" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_5</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QVBoxLayout</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">centralwidget</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t19" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_5</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"verticalLayout_5"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t20" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_4</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QVBoxLayout</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t21" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_4</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"verticalLayout_4"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t22" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">groupBox</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QGroupBox</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">centralwidget</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t23" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">groupBox</span><span class="op">.</span><span class="nam">setWhatsThis</span><span class="op">(</span><span class="str">""</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t24" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">groupBox</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"groupBox"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t25" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_11</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QVBoxLayout</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">groupBox</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t26" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_11</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"verticalLayout_11"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t27" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">widget</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">groupBox</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t28" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">widget</span><span class="op">.</span><span class="nam">setWhatsThis</span><span class="op">(</span><span class="str">""</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t29" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">widget</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"widget"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t30" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_14</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QVBoxLayout</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">widget</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t31" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_14</span><span class="op">.</span><span class="nam">setContentsMargins</span><span class="op">(</span><span class="num">0</span><span class="op">,</span> <span class="num">0</span><span class="op">,</span> <span class="num">0</span><span class="op">,</span> <span class="num">0</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t32" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_14</span><span class="op">.</span><span class="nam">setSpacing</span><span class="op">(</span><span class="num">6</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t33" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_14</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"verticalLayout_14"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t34" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QHBoxLayout</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t35" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout</span><span class="op">.</span><span class="nam">setSpacing</span><span class="op">(</span><span class="num">6</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t36" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"horizontalLayout"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t37" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QVBoxLayout</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t38" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"verticalLayout"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t39" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_csv</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QRadioButton</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">widget</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t40" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_csv</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"radioButton_csv"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t41" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_csv</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t42" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_csv</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QLineEdit</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">widget</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t43" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_csv</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="str">""</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t44" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_csv</span><span class="op">.</span><span class="nam">setReadOnly</span><span class="op">(</span><span class="key">True</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t45" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_csv</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"lineEdit_csv"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t46" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_csv</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t47" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout</span><span class="op">.</span><span class="nam">addLayout</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t48" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_2</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QVBoxLayout</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t49" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_2</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"verticalLayout_2"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t50" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_hecras</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QRadioButton</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">widget</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t51" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_hecras</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"radioButton_hecras"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t52" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_2</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_hecras</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t53" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_hecras</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QLineEdit</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">widget</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t54" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_hecras</span><span class="op">.</span><span class="nam">setEnabled</span><span class="op">(</span><span class="key">True</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t55" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_hecras</span><span class="op">.</span><span class="nam">setReadOnly</span><span class="op">(</span><span class="key">True</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t56" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_hecras</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"lineEdit_hecras"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t57" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_2</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_hecras</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t58" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout</span><span class="op">.</span><span class="nam">addLayout</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_2</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t59" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">pushButton_browse</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QPushButton</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">widget</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t60" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">pushButton_browse</span><span class="op">.</span><span class="nam">setEnabled</span><span class="op">(</span><span class="key">False</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t61" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">pushButton_browse</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"pushButton_browse"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t62" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">pushButton_browse</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t63" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_14</span><span class="op">.</span><span class="nam">addLayout</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t64" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_11</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">widget</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t65" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">widget_5</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">groupBox</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t66" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">widget_5</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"widget_5"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t67" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_7</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QVBoxLayout</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">widget_5</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t68" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_7</span><span class="op">.</span><span class="nam">setContentsMargins</span><span class="op">(</span><span class="num">0</span><span class="op">,</span> <span class="num">0</span><span class="op">,</span> <span class="num">0</span><span class="op">,</span> <span class="num">0</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t69" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_7</span><span class="op">.</span><span class="nam">setSpacing</span><span class="op">(</span><span class="num">0</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t70" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_7</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"verticalLayout_7"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t71" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_2</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QHBoxLayout</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t72" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_2</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"horizontalLayout_2"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t73" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_parabolic_constant</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QRadioButton</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">widget_5</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t74" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_parabolic_constant</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"radioButton_parabolic_constant"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t75" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_2</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_parabolic_constant</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t76" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_parabolic</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QRadioButton</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">widget_5</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t77" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_parabolic</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"radioButton_parabolic"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t78" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_2</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_parabolic</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t79" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_constant</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QRadioButton</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">widget_5</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t80" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_constant</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"radioButton_constant"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t81" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_2</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_constant</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t82" class="stm mis"> <span class="nam">spacerItem</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSpacerItem</span><span class="op">(</span><span class="num">40</span><span class="op">,</span> <span class="num">20</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSizePolicy</span><span class="op">.</span><span class="nam">Expanding</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSizePolicy</span><span class="op">.</span><span class="nam">Minimum</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t83" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_2</span><span class="op">.</span><span class="nam">addItem</span><span class="op">(</span><span class="nam">spacerItem</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t84" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_7</span><span class="op">.</span><span class="nam">addLayout</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_2</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t85" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_11</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">widget_5</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t86" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_4</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">groupBox</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t87" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">groupBox_3</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QGroupBox</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">centralwidget</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t88" class="stm mis"> <span class="nam">font</span> <span class="op">=</span> <span class="nam">QtGui</span><span class="op">.</span><span class="nam">QFont</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t89" class="stm mis"> <span class="nam">font</span><span class="op">.</span><span class="nam">setBold</span><span class="op">(</span><span class="key">False</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t90" class="stm mis"> <span class="nam">font</span><span class="op">.</span><span class="nam">setWeight</span><span class="op">(</span><span class="num">50</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t91" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">groupBox_3</span><span class="op">.</span><span class="nam">setFont</span><span class="op">(</span><span class="nam">font</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t92" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">groupBox_3</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"groupBox_3"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t93" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_3</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QVBoxLayout</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">groupBox_3</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t94" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_3</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"verticalLayout_3"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t95" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_8</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QHBoxLayout</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t96" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_8</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"horizontalLayout_8"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t97" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_x</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QLabel</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">groupBox_3</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t98" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_x</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"label_x"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t99" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_8</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">label_x</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t100" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_x</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QLineEdit</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">groupBox_3</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t101" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_x</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"lineEdit_x"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t102" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_8</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_x</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t103" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_y</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QLabel</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">groupBox_3</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t104" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_y</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"label_y"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t105" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_8</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">label_y</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t106" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_y</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QLineEdit</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">groupBox_3</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t107" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_y</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"lineEdit_y"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t108" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_8</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_y</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t109" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_z</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QLabel</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">groupBox_3</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t110" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_z</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"label_z"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t111" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_8</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">label_z</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t112" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_z</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QLineEdit</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">groupBox_3</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t113" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_z</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"lineEdit_z"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t114" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_8</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_z</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t115" class="stm mis"> <span class="nam">spacerItem1</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSpacerItem</span><span class="op">(</span><span class="num">40</span><span class="op">,</span> <span class="num">20</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSizePolicy</span><span class="op">.</span><span class="nam">Expanding</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSizePolicy</span><span class="op">.</span><span class="nam">Minimum</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t116" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_8</span><span class="op">.</span><span class="nam">addItem</span><span class="op">(</span><span class="nam">spacerItem1</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t117" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_3</span><span class="op">.</span><span class="nam">addLayout</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_8</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t118" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_9</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QHBoxLayout</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t119" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_9</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"horizontalLayout_9"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t120" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_number_of_eggs</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QLabel</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">groupBox_3</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t121" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_number_of_eggs</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"label_number_of_eggs"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t122" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_9</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">label_number_of_eggs</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t123" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_number_of_eggs</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QLineEdit</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">groupBox_3</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t124" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_number_of_eggs</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"lineEdit_number_of_eggs"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t125" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_9</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_number_of_eggs</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t126" class="stm mis"> <span class="nam">spacerItem2</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSpacerItem</span><span class="op">(</span><span class="num">40</span><span class="op">,</span> <span class="num">20</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSizePolicy</span><span class="op">.</span><span class="nam">Expanding</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSizePolicy</span><span class="op">.</span><span class="nam">Minimum</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t127" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_9</span><span class="op">.</span><span class="nam">addItem</span><span class="op">(</span><span class="nam">spacerItem2</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t128" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_3</span><span class="op">.</span><span class="nam">addLayout</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_9</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t129" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">widget_7</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">groupBox_3</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t130" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">widget_7</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"widget_7"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t131" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_9</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QVBoxLayout</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">widget_7</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t132" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_9</span><span class="op">.</span><span class="nam">setContentsMargins</span><span class="op">(</span><span class="num">0</span><span class="op">,</span> <span class="num">0</span><span class="op">,</span> <span class="num">0</span><span class="op">,</span> <span class="num">0</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t133" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_9</span><span class="op">.</span><span class="nam">setSpacing</span><span class="op">(</span><span class="num">0</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t134" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_9</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"verticalLayout_9"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t135" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_7</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QHBoxLayout</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t136" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_7</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"horizontalLayout_7"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t137" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_grass</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QRadioButton</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">widget_7</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t138" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_grass</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"radioButton_grass"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t139" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_7</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_grass</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t140" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_silver</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QRadioButton</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">widget_7</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t141" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_silver</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"radioButton_silver"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t142" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_7</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_silver</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t143" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_bighead</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QRadioButton</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">widget_7</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t144" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_bighead</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"radioButton_bighead"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t145" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_7</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_bighead</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t146" class="stm mis"> <span class="nam">spacerItem3</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSpacerItem</span><span class="op">(</span><span class="num">40</span><span class="op">,</span> <span class="num">20</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSizePolicy</span><span class="op">.</span><span class="nam">Expanding</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSizePolicy</span><span class="op">.</span><span class="nam">Minimum</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t147" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_7</span><span class="op">.</span><span class="nam">addItem</span><span class="op">(</span><span class="nam">spacerItem3</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t148" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_9</span><span class="op">.</span><span class="nam">addLayout</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_7</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t149" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_3</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">widget_7</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t150" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">widget_8</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">groupBox_3</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t151" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">widget_8</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"widget_8"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t152" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_12</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QVBoxLayout</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">widget_8</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t153" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_12</span><span class="op">.</span><span class="nam">setContentsMargins</span><span class="op">(</span><span class="num">0</span><span class="op">,</span> <span class="num">0</span><span class="op">,</span> <span class="num">0</span><span class="op">,</span> <span class="num">0</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t154" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_12</span><span class="op">.</span><span class="nam">setSpacing</span><span class="op">(</span><span class="num">0</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t155" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_12</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"verticalLayout_12"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t156" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_10</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QHBoxLayout</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t157" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_10</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"horizontalLayout_10"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t158" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_varying_dd</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QRadioButton</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">widget_8</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t159" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_varying_dd</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"radioButton_varying_dd"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t160" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_10</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_varying_dd</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t161" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_constant_dd</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QRadioButton</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">widget_8</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t162" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_constant_dd</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"radioButton_constant_dd"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t163" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_10</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_constant_dd</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t164" class="stm mis"> <span class="nam">spacerItem4</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSpacerItem</span><span class="op">(</span><span class="num">40</span><span class="op">,</span> <span class="num">20</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSizePolicy</span><span class="op">.</span><span class="nam">Expanding</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSizePolicy</span><span class="op">.</span><span class="nam">Minimum</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t165" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_10</span><span class="op">.</span><span class="nam">addItem</span><span class="op">(</span><span class="nam">spacerItem4</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t166" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_12</span><span class="op">.</span><span class="nam">addLayout</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_10</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t167" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_3</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">widget_8</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t168" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_4</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">groupBox_3</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t169" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">groupBox_2</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QGroupBox</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">centralwidget</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t170" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">groupBox_2</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"groupBox_2"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t171" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_10</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QVBoxLayout</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">groupBox_2</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t172" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_10</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"verticalLayout_10"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t173" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">widget_9</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">groupBox_2</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t174" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">widget_9</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"widget_9"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t175" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_13</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QVBoxLayout</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">widget_9</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t176" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_13</span><span class="op">.</span><span class="nam">setContentsMargins</span><span class="op">(</span><span class="num">0</span><span class="op">,</span> <span class="num">0</span><span class="op">,</span> <span class="num">0</span><span class="op">,</span> <span class="num">0</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t177" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_13</span><span class="op">.</span><span class="nam">setSpacing</span><span class="op">(</span><span class="num">0</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t178" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_13</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"verticalLayout_13"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t179" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_5</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QHBoxLayout</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t180" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_5</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"horizontalLayout_5"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t181" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_forward</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QRadioButton</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">widget_9</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t182" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_forward</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"radioButton_forward"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t183" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_5</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_forward</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t184" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_reverse</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QRadioButton</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">widget_9</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t185" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_reverse</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"radioButton_reverse"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t186" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_5</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_reverse</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t187" class="stm mis"> <span class="nam">spacerItem5</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSpacerItem</span><span class="op">(</span><span class="num">40</span><span class="op">,</span> <span class="num">20</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSizePolicy</span><span class="op">.</span><span class="nam">Expanding</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSizePolicy</span><span class="op">.</span><span class="nam">Minimum</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t188" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_5</span><span class="op">.</span><span class="nam">addItem</span><span class="op">(</span><span class="nam">spacerItem5</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t189" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_13</span><span class="op">.</span><span class="nam">addLayout</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_5</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t190" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_10</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">widget_9</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t191" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_3</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QHBoxLayout</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t192" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_3</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"horizontalLayout_3"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t193" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_duration</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QLabel</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">groupBox_2</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t194" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_duration</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"label_duration"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t195" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_3</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">label_duration</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t196" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_duration</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QLineEdit</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">groupBox_2</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t197" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_duration</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"lineEdit_duration"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t198" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_3</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_duration</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t199" class="stm mis"> <span class="nam">spacerItem6</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSpacerItem</span><span class="op">(</span><span class="num">40</span><span class="op">,</span> <span class="num">20</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSizePolicy</span><span class="op">.</span><span class="nam">Expanding</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSizePolicy</span><span class="op">.</span><span class="nam">Minimum</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t200" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_3</span><span class="op">.</span><span class="nam">addItem</span><span class="op">(</span><span class="nam">spacerItem6</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t201" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_10</span><span class="op">.</span><span class="nam">addLayout</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_3</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t202" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_4</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QHBoxLayout</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t203" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_4</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"horizontalLayout_4"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t204" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_time_step</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QLabel</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">groupBox_2</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t205" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_time_step</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"label_time_step"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t206" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_4</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">label_time_step</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t207" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_time_step</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QLineEdit</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">groupBox_2</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t208" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_time_step</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"lineEdit_time_step"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t209" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_4</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_time_step</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t210" class="stm mis"> <span class="nam">spacerItem7</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSpacerItem</span><span class="op">(</span><span class="num">40</span><span class="op">,</span> <span class="num">20</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSizePolicy</span><span class="op">.</span><span class="nam">Expanding</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSizePolicy</span><span class="op">.</span><span class="nam">Minimum</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t211" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_4</span><span class="op">.</span><span class="nam">addItem</span><span class="op">(</span><span class="nam">spacerItem7</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t212" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_10</span><span class="op">.</span><span class="nam">addLayout</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_4</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t213" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_11</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QHBoxLayout</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t214" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_11</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"horizontalLayout_11"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t215" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_simulation_name</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QLabel</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">groupBox_2</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t216" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_simulation_name</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"label_simulation_name"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t217" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_11</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">label_simulation_name</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t218" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_simulation_name</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QLineEdit</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">groupBox_2</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t219" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_simulation_name</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="str">""</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t220" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_simulation_name</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"lineEdit_simulation_name"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t221" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_11</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_simulation_name</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t222" class="stm mis"> <span class="nam">spacerItem8</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSpacerItem</span><span class="op">(</span><span class="num">40</span><span class="op">,</span> <span class="num">20</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSizePolicy</span><span class="op">.</span><span class="nam">Expanding</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSizePolicy</span><span class="op">.</span><span class="nam">Minimum</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t223" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_11</span><span class="op">.</span><span class="nam">addItem</span><span class="op">(</span><span class="nam">spacerItem8</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t224" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_10</span><span class="op">.</span><span class="nam">addLayout</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_11</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t225" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_15</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QHBoxLayout</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t226" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_15</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"horizontalLayout_15"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t227" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">pushButton_run</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QPushButton</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">groupBox_2</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t228" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">pushButton_run</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"pushButton_run"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t229" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_15</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">pushButton_run</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t230" class="stm mis"> <span class="nam">spacerItem9</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSpacerItem</span><span class="op">(</span><span class="num">40</span><span class="op">,</span> <span class="num">20</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSizePolicy</span><span class="op">.</span><span class="nam">Expanding</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSizePolicy</span><span class="op">.</span><span class="nam">Minimum</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t231" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_15</span><span class="op">.</span><span class="nam">addItem</span><span class="op">(</span><span class="nam">spacerItem9</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t232" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_10</span><span class="op">.</span><span class="nam">addLayout</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_15</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t233" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_4</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">groupBox_2</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t234" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_5</span><span class="op">.</span><span class="nam">addLayout</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_4</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t235" class="stm mis"> <span class="nam">MainWindow</span><span class="op">.</span><span class="nam">setCentralWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">centralwidget</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t236" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">menubar</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QMenuBar</span><span class="op">(</span><span class="nam">MainWindow</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t237" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">menubar</span><span class="op">.</span><span class="nam">setGeometry</span><span class="op">(</span><span class="nam">QtCore</span><span class="op">.</span><span class="nam">QRect</span><span class="op">(</span><span class="num">0</span><span class="op">,</span> <span class="num">0</span><span class="op">,</span> <span class="num">334</span><span class="op">,</span> <span class="num">22</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t238" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">menubar</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"menubar"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t239" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">menuAbout</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QMenu</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">menubar</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t240" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">menuAbout</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"menuAbout"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t241" class="stm mis"> <span class="nam">MainWindow</span><span class="op">.</span><span class="nam">setMenuBar</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">menubar</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t242" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">statusbar</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QStatusBar</span><span class="op">(</span><span class="nam">MainWindow</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t243" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">statusbar</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"statusbar"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t244" class="stm mis"> <span class="nam">MainWindow</span><span class="op">.</span><span class="nam">setStatusBar</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">statusbar</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t245" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">actionVersion</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QAction</span><span class="op">(</span><span class="nam">MainWindow</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t246" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">actionVersion</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"actionVersion"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t247" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">actionHelp</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QAction</span><span class="op">(</span><span class="nam">MainWindow</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t248" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">actionHelp</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"actionHelp"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t249" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">menuAbout</span><span class="op">.</span><span class="nam">addAction</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">actionVersion</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t250" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">menuAbout</span><span class="op">.</span><span class="nam">addAction</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">actionHelp</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t251" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">menubar</span><span class="op">.</span><span class="nam">addAction</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">menuAbout</span><span class="op">.</span><span class="nam">menuAction</span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t252" class="pln"><span class="strut"> </span></p> -<p id="t253" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">retranslateUi</span><span class="op">(</span><span class="nam">MainWindow</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t254" class="stm mis"> <span class="nam">QtCore</span><span class="op">.</span><span class="nam">QMetaObject</span><span class="op">.</span><span class="nam">connectSlotsByName</span><span class="op">(</span><span class="nam">MainWindow</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t255" class="pln"><span class="strut"> </span></p> -<p id="t256" class="stm run hide_run"> <span class="key">def</span> <span class="nam">retranslateUi</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">MainWindow</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t257" class="stm mis"> <span class="nam">_translate</span> <span class="op">=</span> <span class="nam">QtCore</span><span class="op">.</span><span class="nam">QCoreApplication</span><span class="op">.</span><span class="nam">translate</span><span class="strut"> </span></p> -<p id="t258" class="stm mis"> <span class="nam">MainWindow</span><span class="op">.</span><span class="nam">setWindowTitle</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"MainWindow"</span><span class="op">,</span> <span class="str">"MainWindow"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t259" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">groupBox</span><span class="op">.</span><span class="nam">setTitle</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"MainWindow"</span><span class="op">,</span> <span class="str">"1) Hydraulic Channel"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t260" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_csv</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"MainWindow"</span><span class="op">,</span> <span class="str">"CSV"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t261" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_csv</span><span class="op">.</span><span class="nam">setPlaceholderText</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"MainWindow"</span><span class="op">,</span> <span class="str">"path/to/hydraulics.csv"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t262" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_hecras</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"MainWindow"</span><span class="op">,</span> <span class="str">"HECRAS"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t263" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_hecras</span><span class="op">.</span><span class="nam">setPlaceholderText</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"MainWindow"</span><span class="op">,</span> <span class="str">"hecras project"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t264" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">pushButton_browse</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"MainWindow"</span><span class="op">,</span> <span class="str">"Browse"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t265" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_parabolic_constant</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"MainWindow"</span><span class="op">,</span> <span class="str">"Parabolic-Constant"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t266" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_parabolic</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"MainWindow"</span><span class="op">,</span> <span class="str">"Parabolic"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t267" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_constant</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"MainWindow"</span><span class="op">,</span> <span class="str">"Constant"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t268" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">groupBox_3</span><span class="op">.</span><span class="nam">setTitle</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"MainWindow"</span><span class="op">,</span> <span class="str">"2) Eggs"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t269" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_x</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"MainWindow"</span><span class="op">,</span> <span class="str">"Initial Position (m): X"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t270" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_y</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"MainWindow"</span><span class="op">,</span> <span class="str">"Y"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t271" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_z</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"MainWindow"</span><span class="op">,</span> <span class="str">"Z"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t272" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_number_of_eggs</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"MainWindow"</span><span class="op">,</span> <span class="str">"Number of Eggs"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t273" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_grass</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"MainWindow"</span><span class="op">,</span> <span class="str">"Grass"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t274" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_silver</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"MainWindow"</span><span class="op">,</span> <span class="str">"Silver"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t275" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_bighead</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"MainWindow"</span><span class="op">,</span> <span class="str">"Bighead"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t276" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_varying_dd</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"MainWindow"</span><span class="op">,</span> <span class="str">"Varying ρ / d"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t277" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_constant_dd</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"MainWindow"</span><span class="op">,</span> <span class="str">"Constant ρ / d"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t278" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">groupBox_2</span><span class="op">.</span><span class="nam">setTitle</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"MainWindow"</span><span class="op">,</span> <span class="str">"3) Simulation"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t279" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_forward</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"MainWindow"</span><span class="op">,</span> <span class="str">"Forward"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t280" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_reverse</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"MainWindow"</span><span class="op">,</span> <span class="str">"Reverse"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t281" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_duration</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"MainWindow"</span><span class="op">,</span> <span class="str">"Duration (s)"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t282" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_time_step</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"MainWindow"</span><span class="op">,</span> <span class="str">"Δt (s)"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t283" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_simulation_name</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"MainWindow"</span><span class="op">,</span> <span class="str">"Simulation Name"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t284" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">pushButton_run</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"MainWindow"</span><span class="op">,</span> <span class="str">"Run"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t285" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">menuAbout</span><span class="op">.</span><span class="nam">setTitle</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"MainWindow"</span><span class="op">,</span> <span class="str">"About"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t286" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">actionVersion</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"MainWindow"</span><span class="op">,</span> <span class="str">"Version"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t287" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">actionHelp</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"MainWindow"</span><span class="op">,</span> <span class="str">"Help"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t288" class="pln"><span class="strut"> </span></p> - - </td> - </tr> - </table> -</div> - -<div id="footer"> - <div class="content"> - <p> - <a class="nav" href="index.html">« index</a> <a class="nav" href="https://coverage.readthedocs.io">coverage.py v4.5.3</a>, - created at 2019-07-09 15:15 - </p> - </div> -</div> - -</body> -</html> diff --git a/coverage_report/fluegg_gui_gui_py.html b/coverage_report/fluegg_gui_gui_py.html deleted file mode 100644 index 67e6762..0000000 --- a/coverage_report/fluegg_gui_gui_py.html +++ /dev/null @@ -1,923 +0,0 @@ - - - -<!DOCTYPE html> -<html> -<head> - <meta http-equiv="Content-Type" content="text/html; charset=utf-8"> - - - <meta http-equiv="X-UA-Compatible" content="IE=emulateIE7" /> - <title>Coverage for fluegg\gui\gui.py: 11%</title> - <link rel="stylesheet" href="style.css" type="text/css"> - - <script type="text/javascript" src="jquery.min.js"></script> - <script type="text/javascript" src="jquery.hotkeys.js"></script> - <script type="text/javascript" src="jquery.isonscreen.js"></script> - <script type="text/javascript" src="coverage_html.js"></script> - <script type="text/javascript"> - jQuery(document).ready(coverage.pyfile_ready); - </script> -</head> -<body class="pyfile"> - -<div id="header"> - <div class="content"> - <h1>Coverage for <b>fluegg\gui\gui.py</b> : - <span class="pc_cov">11%</span> - </h1> - - <img id="keyboard_icon" src="keybd_closed.png" alt="Show keyboard shortcuts" /> - - <h2 class="stats"> - 254 statements - <span class="run hide_run shortkey_r button_toggle_run">29 run</span> - <span class="mis shortkey_m button_toggle_mis">225 missing</span> - <span class="exc shortkey_x button_toggle_exc">0 excluded</span> - - - </h2> - </div> -</div> - -<div class="help_panel"> - <img id="panel_icon" src="keybd_open.png" alt="Hide keyboard shortcuts" /> - <p class="legend">Hot-keys on this page</p> - <div> - <p class="keyhelp"> - <span class="key">r</span> - <span class="key">m</span> - <span class="key">x</span> - <span class="key">p</span> toggle line displays - </p> - <p class="keyhelp"> - <span class="key">j</span> - <span class="key">k</span> next/prev highlighted chunk - </p> - <p class="keyhelp"> - <span class="key">0</span> (zero) top of page - </p> - <p class="keyhelp"> - <span class="key">1</span> (one) first highlighted chunk - </p> - </div> -</div> - -<div id="source"> - <table> - <tr> - <td class="linenos"> -<p id="n1" class="pln"><a href="#n1">1</a></p> -<p id="n2" class="stm run hide_run"><a href="#n2">2</a></p> -<p id="n3" class="stm run hide_run"><a href="#n3">3</a></p> -<p id="n4" class="stm run hide_run"><a href="#n4">4</a></p> -<p id="n5" class="stm run hide_run"><a href="#n5">5</a></p> -<p id="n6" class="pln"><a href="#n6">6</a></p> -<p id="n7" class="stm run hide_run"><a href="#n7">7</a></p> -<p id="n8" class="pln"><a href="#n8">8</a></p> -<p id="n9" class="stm run hide_run"><a href="#n9">9</a></p> -<p id="n10" class="stm run hide_run"><a href="#n10">10</a></p> -<p id="n11" class="stm run hide_run"><a href="#n11">11</a></p> -<p id="n12" class="stm run hide_run"><a href="#n12">12</a></p> -<p id="n13" class="pln"><a href="#n13">13</a></p> -<p id="n14" class="stm run hide_run"><a href="#n14">14</a></p> -<p id="n15" class="pln"><a href="#n15">15</a></p> -<p id="n16" class="pln"><a href="#n16">16</a></p> -<p id="n17" class="stm run hide_run"><a href="#n17">17</a></p> -<p id="n18" class="pln"><a href="#n18">18</a></p> -<p id="n19" class="stm mis"><a href="#n19">19</a></p> -<p id="n20" class="stm mis"><a href="#n20">20</a></p> -<p id="n21" class="stm mis"><a 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href="#n181">181</a></p> -<p id="n182" class="pln"><a href="#n182">182</a></p> -<p id="n183" class="stm mis"><a href="#n183">183</a></p> -<p id="n184" class="stm mis"><a href="#n184">184</a></p> -<p id="n185" class="stm mis"><a href="#n185">185</a></p> -<p id="n186" class="pln"><a href="#n186">186</a></p> -<p id="n187" class="pln"><a href="#n187">187</a></p> -<p id="n188" class="stm mis"><a href="#n188">188</a></p> -<p id="n189" class="stm mis"><a href="#n189">189</a></p> -<p id="n190" class="pln"><a href="#n190">190</a></p> -<p id="n191" class="pln"><a href="#n191">191</a></p> -<p id="n192" class="stm mis"><a href="#n192">192</a></p> -<p id="n193" class="pln"><a href="#n193">193</a></p> -<p id="n194" class="pln"><a href="#n194">194</a></p> -<p id="n195" class="stm mis"><a href="#n195">195</a></p> -<p id="n196" class="stm mis"><a href="#n196">196</a></p> -<p id="n197" class="pln"><a href="#n197">197</a></p> -<p id="n198" class="pln"><a href="#n198">198</a></p> -<p id="n199" class="stm mis"><a href="#n199">199</a></p> -<p id="n200" class="stm mis"><a href="#n200">200</a></p> -<p id="n201" class="stm mis"><a href="#n201">201</a></p> -<p id="n202" class="stm mis"><a href="#n202">202</a></p> -<p id="n203" class="stm mis"><a href="#n203">203</a></p> -<p id="n204" class="stm mis"><a href="#n204">204</a></p> -<p id="n205" class="pln"><a href="#n205">205</a></p> -<p id="n206" class="pln"><a href="#n206">206</a></p> -<p id="n207" class="stm mis"><a href="#n207">207</a></p> -<p id="n208" class="stm mis"><a href="#n208">208</a></p> -<p id="n209" class="stm mis"><a href="#n209">209</a></p> -<p id="n210" class="pln"><a href="#n210">210</a></p> -<p id="n211" class="pln"><a href="#n211">211</a></p> -<p id="n212" class="pln"><a href="#n212">212</a></p> -<p id="n213" class="stm mis"><a href="#n213">213</a></p> -<p id="n214" class="stm mis"><a href="#n214">214</a></p> -<p id="n215" class="pln"><a href="#n215">215</a></p> -<p id="n216" class="stm mis"><a href="#n216">216</a></p> -<p id="n217" class="stm mis"><a href="#n217">217</a></p> -<p id="n218" class="pln"><a href="#n218">218</a></p> -<p id="n219" class="pln"><a href="#n219">219</a></p> -<p id="n220" class="pln"><a href="#n220">220</a></p> -<p id="n221" class="stm mis"><a href="#n221">221</a></p> -<p id="n222" class="stm mis"><a href="#n222">222</a></p> -<p id="n223" class="stm mis"><a href="#n223">223</a></p> -<p id="n224" class="pln"><a href="#n224">224</a></p> -<p id="n225" class="stm mis"><a href="#n225">225</a></p> -<p id="n226" class="stm mis"><a href="#n226">226</a></p> -<p id="n227" class="pln"><a href="#n227">227</a></p> -<p id="n228" class="pln"><a href="#n228">228</a></p> -<p id="n229" class="stm mis"><a href="#n229">229</a></p> -<p id="n230" class="pln"><a href="#n230">230</a></p> -<p id="n231" class="pln"><a href="#n231">231</a></p> -<p id="n232" class="stm mis"><a href="#n232">232</a></p> -<p id="n233" class="stm mis"><a href="#n233">233</a></p> -<p id="n234" class="stm mis"><a href="#n234">234</a></p> -<p id="n235" class="stm mis"><a href="#n235">235</a></p> -<p id="n236" class="stm mis"><a href="#n236">236</a></p> -<p id="n237" class="pln"><a href="#n237">237</a></p> -<p id="n238" class="pln"><a href="#n238">238</a></p> -<p id="n239" class="stm mis"><a href="#n239">239</a></p> -<p id="n240" class="stm mis"><a href="#n240">240</a></p> -<p id="n241" class="stm mis"><a href="#n241">241</a></p> -<p id="n242" class="stm mis"><a href="#n242">242</a></p> -<p id="n243" class="stm mis"><a href="#n243">243</a></p> -<p id="n244" class="stm mis"><a href="#n244">244</a></p> -<p id="n245" class="stm mis"><a href="#n245">245</a></p> -<p id="n246" class="pln"><a href="#n246">246</a></p> -<p id="n247" class="pln"><a href="#n247">247</a></p> -<p id="n248" class="stm mis"><a href="#n248">248</a></p> -<p id="n249" class="pln"><a href="#n249">249</a></p> -<p id="n250" class="stm run hide_run"><a href="#n250">250</a></p> -<p id="n251" class="pln"><a href="#n251">251</a></p> -<p id="n252" class="stm mis"><a href="#n252">252</a></p> -<p id="n253" class="pln"><a href="#n253">253</a></p> -<p id="n254" class="stm run hide_run"><a href="#n254">254</a></p> -<p id="n255" class="pln"><a href="#n255">255</a></p> -<p id="n256" class="stm mis"><a href="#n256">256</a></p> -<p id="n257" class="pln"><a href="#n257">257</a></p> -<p id="n258" class="stm run hide_run"><a href="#n258">258</a></p> -<p id="n259" class="pln"><a href="#n259">259</a></p> -<p id="n260" class="pln"><a href="#n260">260</a></p> -<p id="n261" class="stm mis"><a href="#n261">261</a></p> -<p id="n262" class="stm mis"><a href="#n262">262</a></p> -<p id="n263" class="stm mis"><a href="#n263">263</a></p> -<p id="n264" class="stm mis"><a href="#n264">264</a></p> -<p id="n265" class="stm mis"><a href="#n265">265</a></p> -<p id="n266" class="stm mis"><a href="#n266">266</a></p> -<p id="n267" class="pln"><a href="#n267">267</a></p> -<p id="n268" class="stm run hide_run"><a href="#n268">268</a></p> -<p id="n269" class="pln"><a href="#n269">269</a></p> -<p id="n270" class="stm mis"><a href="#n270">270</a></p> -<p id="n271" class="pln"><a href="#n271">271</a></p> -<p id="n272" class="stm mis"><a href="#n272">272</a></p> -<p id="n273" class="stm mis"><a href="#n273">273</a></p> -<p id="n274" class="pln"><a href="#n274">274</a></p> -<p id="n275" class="pln"><a href="#n275">275</a></p> -<p id="n276" class="stm mis"><a href="#n276">276</a></p> -<p id="n277" class="pln"><a href="#n277">277</a></p> -<p id="n278" class="stm mis"><a href="#n278">278</a></p> -<p id="n279" class="pln"><a href="#n279">279</a></p> -<p id="n280" class="pln"><a href="#n280">280</a></p> -<p id="n281" class="stm mis"><a href="#n281">281</a></p> -<p id="n282" class="stm mis"><a href="#n282">282</a></p> -<p id="n283" class="pln"><a href="#n283">283</a></p> -<p id="n284" class="pln"><a href="#n284">284</a></p> -<p id="n285" class="stm mis"><a href="#n285">285</a></p> -<p id="n286" class="pln"><a href="#n286">286</a></p> -<p id="n287" class="pln"><a href="#n287">287</a></p> -<p id="n288" class="stm mis"><a href="#n288">288</a></p> -<p id="n289" class="stm mis"><a href="#n289">289</a></p> -<p id="n290" class="stm mis"><a href="#n290">290</a></p> -<p id="n291" class="stm mis"><a href="#n291">291</a></p> -<p id="n292" class="pln"><a href="#n292">292</a></p> -<p id="n293" class="stm run hide_run"><a href="#n293">293</a></p> -<p id="n294" class="pln"><a href="#n294">294</a></p> -<p id="n295" class="pln"><a href="#n295">295</a></p> -<p id="n296" class="stm mis"><a href="#n296">296</a></p> -<p id="n297" class="pln"><a href="#n297">297</a></p> -<p id="n298" class="stm mis"><a href="#n298">298</a></p> -<p id="n299" class="pln"><a href="#n299">299</a></p> -<p id="n300" class="pln"><a href="#n300">300</a></p> -<p id="n301" class="stm mis"><a href="#n301">301</a></p> -<p id="n302" class="pln"><a href="#n302">302</a></p> -<p id="n303" class="stm mis"><a href="#n303">303</a></p> -<p id="n304" class="pln"><a href="#n304">304</a></p> -<p id="n305" class="stm mis"><a href="#n305">305</a></p> -<p id="n306" class="pln"><a href="#n306">306</a></p> -<p id="n307" class="pln"><a href="#n307">307</a></p> -<p id="n308" class="stm mis"><a href="#n308">308</a></p> -<p id="n309" class="stm mis"><a href="#n309">309</a></p> -<p id="n310" class="stm mis"><a href="#n310">310</a></p> -<p id="n311" class="pln"><a href="#n311">311</a></p> -<p id="n312" class="pln"><a href="#n312">312</a></p> -<p id="n313" class="stm mis"><a href="#n313">313</a></p> -<p id="n314" class="stm mis"><a href="#n314">314</a></p> -<p id="n315" class="pln"><a href="#n315">315</a></p> -<p id="n316" class="pln"><a href="#n316">316</a></p> -<p id="n317" class="stm mis"><a href="#n317">317</a></p> -<p id="n318" class="stm mis"><a href="#n318">318</a></p> -<p id="n319" class="stm mis"><a href="#n319">319</a></p> -<p id="n320" class="stm mis"><a href="#n320">320</a></p> -<p id="n321" class="pln"><a href="#n321">321</a></p> -<p id="n322" class="stm mis"><a href="#n322">322</a></p> -<p id="n323" class="stm mis"><a href="#n323">323</a></p> -<p id="n324" class="pln"><a href="#n324">324</a></p> -<p id="n325" class="stm mis"><a href="#n325">325</a></p> -<p id="n326" class="stm mis"><a href="#n326">326</a></p> -<p id="n327" class="stm mis"><a href="#n327">327</a></p> -<p id="n328" class="stm mis"><a href="#n328">328</a></p> -<p id="n329" class="stm mis"><a href="#n329">329</a></p> -<p id="n330" class="stm mis"><a href="#n330">330</a></p> -<p id="n331" class="stm mis"><a href="#n331">331</a></p> -<p id="n332" class="stm mis"><a href="#n332">332</a></p> -<p id="n333" class="stm mis"><a href="#n333">333</a></p> -<p id="n334" class="stm mis"><a href="#n334">334</a></p> -<p id="n335" class="pln"><a href="#n335">335</a></p> -<p id="n336" class="stm mis"><a href="#n336">336</a></p> -<p id="n337" class="stm mis"><a href="#n337">337</a></p> -<p id="n338" class="pln"><a href="#n338">338</a></p> -<p id="n339" class="pln"><a href="#n339">339</a></p> -<p id="n340" class="stm mis"><a href="#n340">340</a></p> -<p id="n341" class="stm mis"><a href="#n341">341</a></p> -<p id="n342" class="pln"><a href="#n342">342</a></p> -<p id="n343" class="stm mis"><a href="#n343">343</a></p> -<p id="n344" class="stm mis"><a href="#n344">344</a></p> -<p id="n345" class="pln"><a href="#n345">345</a></p> -<p id="n346" class="stm mis"><a href="#n346">346</a></p> -<p id="n347" class="stm mis"><a href="#n347">347</a></p> -<p id="n348" class="pln"><a href="#n348">348</a></p> -<p id="n349" class="stm mis"><a href="#n349">349</a></p> -<p id="n350" class="stm mis"><a href="#n350">350</a></p> -<p id="n351" class="pln"><a href="#n351">351</a></p> -<p id="n352" class="stm mis"><a href="#n352">352</a></p> -<p id="n353" class="pln"><a href="#n353">353</a></p> -<p id="n354" class="stm mis"><a href="#n354">354</a></p> -<p id="n355" class="stm mis"><a href="#n355">355</a></p> -<p id="n356" class="stm mis"><a href="#n356">356</a></p> -<p id="n357" class="pln"><a href="#n357">357</a></p> -<p id="n358" class="stm mis"><a href="#n358">358</a></p> -<p id="n359" class="stm mis"><a href="#n359">359</a></p> -<p id="n360" class="pln"><a href="#n360">360</a></p> -<p id="n361" class="stm mis"><a href="#n361">361</a></p> -<p id="n362" class="stm mis"><a href="#n362">362</a></p> -<p id="n363" class="pln"><a href="#n363">363</a></p> -<p id="n364" class="stm mis"><a href="#n364">364</a></p> -<p id="n365" class="stm mis"><a href="#n365">365</a></p> -<p id="n366" class="pln"><a href="#n366">366</a></p> -<p id="n367" class="stm mis"><a href="#n367">367</a></p> -<p id="n368" class="stm mis"><a href="#n368">368</a></p> -<p id="n369" class="pln"><a href="#n369">369</a></p> -<p id="n370" class="stm mis"><a href="#n370">370</a></p> -<p id="n371" class="stm mis"><a href="#n371">371</a></p> -<p id="n372" class="pln"><a href="#n372">372</a></p> -<p id="n373" class="stm mis"><a href="#n373">373</a></p> -<p id="n374" class="stm mis"><a href="#n374">374</a></p> -<p id="n375" class="pln"><a href="#n375">375</a></p> -<p id="n376" class="pln"><a href="#n376">376</a></p> -<p id="n377" class="stm mis"><a href="#n377">377</a></p> -<p id="n378" class="stm mis"><a href="#n378">378</a></p> -<p id="n379" class="pln"><a href="#n379">379</a></p> -<p id="n380" class="stm mis"><a href="#n380">380</a></p> -<p id="n381" class="stm mis"><a href="#n381">381</a></p> -<p id="n382" class="pln"><a href="#n382">382</a></p> -<p id="n383" class="pln"><a href="#n383">383</a></p> -<p id="n384" class="stm mis"><a href="#n384">384</a></p> -<p id="n385" class="stm mis"><a href="#n385">385</a></p> -<p id="n386" class="pln"><a href="#n386">386</a></p> -<p id="n387" class="stm mis"><a href="#n387">387</a></p> -<p id="n388" class="stm mis"><a href="#n388">388</a></p> -<p id="n389" class="pln"><a href="#n389">389</a></p> -<p id="n390" class="stm mis"><a href="#n390">390</a></p> -<p id="n391" class="stm mis"><a href="#n391">391</a></p> -<p id="n392" class="pln"><a href="#n392">392</a></p> -<p id="n393" class="stm mis"><a href="#n393">393</a></p> -<p id="n394" class="stm mis"><a href="#n394">394</a></p> -<p id="n395" class="pln"><a href="#n395">395</a></p> -<p id="n396" class="stm mis"><a href="#n396">396</a></p> -<p id="n397" class="stm mis"><a href="#n397">397</a></p> -<p id="n398" class="pln"><a href="#n398">398</a></p> -<p id="n399" class="stm mis"><a href="#n399">399</a></p> -<p id="n400" class="stm mis"><a href="#n400">400</a></p> -<p id="n401" class="pln"><a href="#n401">401</a></p> -<p id="n402" class="stm mis"><a href="#n402">402</a></p> -<p id="n403" class="stm mis"><a href="#n403">403</a></p> -<p id="n404" class="pln"><a href="#n404">404</a></p> -<p id="n405" class="pln"><a href="#n405">405</a></p> -<p id="n406" class="stm mis"><a href="#n406">406</a></p> -<p id="n407" class="pln"><a href="#n407">407</a></p> -<p id="n408" class="stm mis"><a href="#n408">408</a></p> -<p id="n409" class="stm mis"><a href="#n409">409</a></p> -<p id="n410" class="stm mis"><a href="#n410">410</a></p> -<p id="n411" class="stm mis"><a href="#n411">411</a></p> -<p id="n412" class="pln"><a href="#n412">412</a></p> -<p id="n413" class="stm mis"><a href="#n413">413</a></p> -<p id="n414" class="stm mis"><a href="#n414">414</a></p> -<p id="n415" class="stm mis"><a href="#n415">415</a></p> -<p id="n416" class="pln"><a href="#n416">416</a></p> -<p id="n417" class="stm mis"><a href="#n417">417</a></p> - - </td> - <td class="text"> -<p id="t1" class="pln"><span class="com"># Import PyQT for gui</span><span class="strut"> </span></p> -<p id="t2" class="stm run hide_run"><span class="key">import</span> <span class="nam">sys</span><span class="strut"> </span></p> -<p id="t3" class="stm run hide_run"><span class="key">import</span> <span class="nam">traceback</span><span class="strut"> </span></p> -<p id="t4" class="stm run hide_run"><span class="key">import</span> <span class="nam">datetime</span><span class="strut"> </span></p> -<p id="t5" class="stm run hide_run"><span class="key">import</span> <span class="nam">platform</span><span class="strut"> </span></p> -<p id="t6" class="pln"><span class="strut"> </span></p> -<p id="t7" class="stm run hide_run"><span class="key">from</span> <span class="nam">PyQt5</span><span class="op">.</span><span class="nam">QtWidgets</span> <span class="key">import</span> <span class="nam">QMainWindow</span><span class="op">,</span> <span class="nam">QApplication</span><span class="op">,</span> <span class="nam">QMessageBox</span><span class="op">,</span> <span class="nam">QDialog</span><span class="op">,</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t8" class="pln"> <span class="nam">QAction</span><span class="op">,</span> <span class="nam">QWidget</span><span class="op">,</span> <span class="nam">QDesktopWidget</span><span class="op">,</span> <span class="nam">QFileDialog</span><span class="op">,</span> <span class="nam">QProgressBar</span><span class="strut"> </span></p> -<p id="t9" class="stm run hide_run"><span class="key">from</span> <span class="nam">PyQt5</span> <span class="key">import</span> <span class="nam">QtCore</span><span class="op">,</span> <span class="nam">QtGui</span><span class="op">,</span> <span class="nam">uic</span><span class="strut"> </span></p> -<p id="t10" class="stm run hide_run"><span class="key">from</span> <span class="nam">fluegg</span><span class="op">.</span><span class="nam">gui</span><span class="op">.</span><span class="nam">gui_layout</span> <span class="key">import</span> <span class="nam">Ui_MainWindow</span><span class="strut"> </span></p> -<p id="t11" class="stm run hide_run"><span class="key">from</span> <span class="nam">fluegg</span><span class="op">.</span><span class="nam">gui</span><span class="op">.</span><span class="nam">hecras_dialog</span> <span class="key">import</span> <span class="nam">Ui_HecrasDialog</span><span class="strut"> </span></p> -<p id="t12" class="stm run hide_run"><span class="key">from</span> <span class="nam">fluegg</span><span class="op">.</span><span class="nam">simulation</span> <span class="key">import</span> <span class="nam">from_input_dict</span><span class="strut"> </span></p> -<p id="t13" class="pln"><span class="strut"> </span></p> -<p id="t14" class="stm run hide_run"><span class="key">from</span> <span class="nam">fluegg</span><span class="op">.</span><span class="nam">ras</span> <span class="key">import</span> <span class="nam">RASProject</span><span class="strut"> </span></p> -<p id="t15" class="pln"><span class="strut"> </span></p> -<p id="t16" class="pln"><span class="strut"> </span></p> -<p id="t17" class="stm run hide_run"><span class="key">def</span> <span class="nam">get_checked_radio_button</span><span class="op">(</span><span class="nam">buttons</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t18" class="pln"> <span class="str">"""Given a list of grouped radio buttons, returns the checked one"""</span><span class="strut"> </span></p> -<p id="t19" class="stm mis"> <span class="nam">checked</span> <span class="op">=</span> <span class="key">None</span><span class="strut"> </span></p> -<p id="t20" class="stm mis"> <span class="key">for</span> <span class="nam">button</span> <span class="key">in</span> <span class="nam">buttons</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t21" class="stm mis"> <span class="key">if</span> <span class="nam">button</span><span class="op">.</span><span class="nam">isChecked</span><span class="op">(</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t22" class="stm mis"> <span class="nam">checked</span> <span class="op">=</span> <span class="nam">button</span><span class="strut"> </span></p> -<p id="t23" class="stm mis"> <span class="key">return</span> <span class="nam">checked</span><span class="strut"> </span></p> -<p id="t24" class="pln"><span class="strut"> </span></p> -<p id="t25" class="pln"><span class="strut"> </span></p> -<p id="t26" class="stm run hide_run"><span class="key">class</span> <span class="nam">HecrasDialog</span><span class="op">(</span><span class="nam">QDialog</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t27" class="stm run hide_run"> <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">main_window</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t28" class="pln"> <span class="com"># Initialization</span><span class="strut"> </span></p> -<p id="t29" class="stm mis"> <span class="nam">super</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">__init__</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t30" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span> <span class="op">=</span> <span class="nam">Ui_HecrasDialog</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t31" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">setupUi</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t32" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">setWindowTitle</span><span class="op">(</span><span class="str">"Hecras Settings"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t33" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">main_window</span> <span class="op">=</span> <span class="nam">main_window</span><span class="strut"> </span></p> -<p id="t34" class="pln"><span class="strut"> </span></p> -<p id="t35" class="pln"> <span class="com"># Set line edit validators</span><span class="strut"> </span></p> -<p id="t36" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">doubleV</span> <span class="op">=</span> <span class="nam">QtGui</span><span class="op">.</span><span class="nam">QDoubleValidator</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t37" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_temperature</span><span class="op">.</span><span class="nam">setValidator</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">doubleV</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t38" class="pln"><span class="strut"> </span></p> -<p id="t39" class="pln"> <span class="com"># Push button handles</span><span class="strut"> </span></p> -<p id="t40" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">pushButton_ok</span><span class="op">.</span><span class="nam">clicked</span><span class="op">.</span><span class="nam">connect</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">handle_ok</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t41" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">pushButton_cancel</span><span class="op">.</span><span class="nam">clicked</span><span class="op">.</span><span class="nam">connect</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">handle_cancel</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t42" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">pushButton_browse</span><span class="op">.</span><span class="nam">clicked</span><span class="op">.</span><span class="nam">connect</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">handle_browse</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t43" class="pln"><span class="strut"> </span></p> -<p id="t44" class="pln"> <span class="com"># Combo box handles</span><span class="strut"> </span></p> -<p id="t45" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">comboBox_plan</span><span class="op">.</span><span class="nam">currentIndexChanged</span><span class="op">.</span><span class="nam">connect</span><span class="op">(</span><span class="strut"> </span></p> -<p id="t46" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">handle_plan_change</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t47" class="pln"><span class="strut"> </span></p> -<p id="t48" class="pln"> <span class="com"># Radio button handles</span><span class="strut"> </span></p> -<p id="t49" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">radioButton_unsteady</span><span class="op">.</span><span class="nam">clicked</span><span class="op">.</span><span class="nam">connect</span><span class="op">(</span><span class="strut"> </span></p> -<p id="t50" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">handle_steadiness_change</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t51" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">radioButton_steady</span><span class="op">.</span><span class="nam">clicked</span><span class="op">.</span><span class="nam">connect</span><span class="op">(</span><span class="strut"> </span></p> -<p id="t52" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">handle_steadiness_change</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t53" class="pln"><span class="strut"> </span></p> -<p id="t54" class="stm run hide_run"> <span class="key">def</span> <span class="nam">setup</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t55" class="pln"> <span class="str">"""Initial setup of dialog"""</span><span class="strut"> </span></p> -<p id="t56" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">radioButton_steady</span><span class="op">.</span><span class="nam">setChecked</span><span class="op">(</span><span class="key">True</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t57" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">populate_plans</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t58" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">populate_profiles</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t59" class="pln"><span class="strut"> </span></p> -<p id="t60" class="stm run hide_run"> <span class="key">def</span> <span class="nam">handle_ok</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t61" class="pln"> <span class="str">"""Handle function for clicking OK"""</span><span class="strut"> </span></p> -<p id="t62" class="pln"> <span class="com"># Initialize variables</span><span class="strut"> </span></p> -<p id="t63" class="stm mis"> <span class="nam">valid_inputs</span> <span class="op">=</span> <span class="key">True</span><span class="strut"> </span></p> -<p id="t64" class="stm mis"> <span class="nam">error_message</span> <span class="op">=</span> <span class="str">''</span><span class="strut"> </span></p> -<p id="t65" class="pln"><span class="strut"> </span></p> -<p id="t66" class="pln"> <span class="com"># Check to ensure all fields filled</span><span class="strut"> </span></p> -<p id="t67" class="stm mis"> <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_project</span><span class="op">.</span><span class="nam">text</span><span class="op">(</span><span class="op">)</span> <span class="op">==</span> <span class="str">''</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t68" class="stm mis"> <span class="nam">valid_inputs</span> <span class="op">=</span> <span class="key">False</span><span class="strut"> </span></p> -<p id="t69" class="stm mis"> <span class="nam">error_message</span> <span class="op">+=</span> <span class="str">'--Choose a RAS project.\n'</span><span class="strut"> </span></p> -<p id="t70" class="stm mis"> <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">comboBox_plan</span><span class="op">.</span><span class="nam">currentText</span><span class="op">(</span><span class="op">)</span> <span class="op">==</span> <span class="str">''</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t71" class="stm mis"> <span class="nam">valid_inputs</span> <span class="op">=</span> <span class="key">False</span><span class="strut"> </span></p> -<p id="t72" class="stm mis"> <span class="nam">error_message</span> <span class="op">+=</span> <span class="str">'--Choose a RAS plan.\n'</span><span class="strut"> </span></p> -<p id="t73" class="stm mis"> <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">comboBox_profile</span><span class="op">.</span><span class="nam">currentText</span><span class="op">(</span><span class="op">)</span> <span class="op">==</span> <span class="str">''</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t74" class="stm mis"> <span class="nam">valid_inputs</span> <span class="op">=</span> <span class="key">False</span><span class="strut"> </span></p> -<p id="t75" class="stm mis"> <span class="nam">error_message</span> <span class="op">+=</span> <span class="str">'--Choose a RAS profile.\n'</span><span class="strut"> </span></p> -<p id="t76" class="stm mis"> <span class="nam">steadiness_buttons</span> <span class="op">=</span> <span class="op">[</span><span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">radioButton_steady</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t77" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">radioButton_unsteady</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t78" class="stm mis"> <span class="key">if</span> <span class="nam">get_checked_radio_button</span><span class="op">(</span><span class="nam">steadiness_buttons</span><span class="op">)</span> <span class="key">is</span> <span class="key">None</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t79" class="stm mis"> <span class="nam">valid_inputs</span> <span class="op">=</span> <span class="key">False</span><span class="strut"> </span></p> -<p id="t80" class="stm mis"> <span class="nam">error_message</span> <span class="op">+=</span> <span class="str">'--Choose a steadiness type.\n'</span><span class="strut"> </span></p> -<p id="t81" class="stm mis"> <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_temperature</span><span class="op">.</span><span class="nam">text</span><span class="op">(</span><span class="op">)</span> <span class="op">==</span> <span class="str">''</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t82" class="stm mis"> <span class="nam">valid_inputs</span> <span class="op">=</span> <span class="key">False</span><span class="strut"> </span></p> -<p id="t83" class="stm mis"> <span class="nam">error_message</span> <span class="op">+=</span> <span class="str">'--Input a valid temperature.\n'</span><span class="strut"> </span></p> -<p id="t84" class="pln"><span class="strut"> </span></p> -<p id="t85" class="pln"> <span class="com"># Save inputs if valid input</span><span class="strut"> </span></p> -<p id="t86" class="stm mis"> <span class="key">if</span> <span class="nam">valid_inputs</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t87" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">save_hecras_settings</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t88" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">close</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t89" class="pln"> <span class="com"># Display error message if invalid inputs</span><span class="strut"> </span></p> -<p id="t90" class="pln"> <span class="key">else</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t91" class="stm mis"> <span class="nam">QMessageBox</span><span class="op">.</span><span class="nam">warning</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="str">'Error'</span><span class="op">,</span> <span class="nam">error_message</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t92" class="pln"><span class="strut"> </span></p> -<p id="t93" class="stm run hide_run"> <span class="key">def</span> <span class="nam">handle_cancel</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t94" class="pln"> <span class="str">"""Handle function for clicking Cancel"""</span><span class="strut"> </span></p> -<p id="t95" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">close</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t96" class="pln"><span class="strut"> </span></p> -<p id="t97" class="stm run hide_run"> <span class="key">def</span> <span class="nam">handle_browse</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t98" class="pln"> <span class="str">"""Handle function for clicking Browse"""</span><span class="strut"> </span></p> -<p id="t99" class="pln"> <span class="com"># File exploring dialog</span><span class="strut"> </span></p> -<p id="t100" class="stm mis"> <span class="nam">dlg</span> <span class="op">=</span> <span class="nam">QFileDialog</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t101" class="stm mis"> <span class="nam">file_path</span> <span class="op">=</span> <span class="nam">dlg</span><span class="op">.</span><span class="nam">getOpenFileName</span><span class="op">(</span><span class="strut"> </span></p> -<p id="t102" class="pln"> <span class="nam">self</span><span class="op">,</span> <span class="str">"QFileDialog.getOpenFileName()"</span><span class="op">,</span> <span class="str">""</span><span class="op">,</span> <span class="str">"HECRAS Project File (*.prj)"</span><span class="op">)</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t103" class="stm mis"> <span class="key">if</span> <span class="nam">file_path</span> <span class="op">==</span> <span class="str">''</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t104" class="stm mis"> <span class="key">return</span><span class="strut"> </span></p> -<p id="t105" class="pln"><span class="strut"> </span></p> -<p id="t106" class="pln"> <span class="com"># Update line edits</span><span class="strut"> </span></p> -<p id="t107" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_project</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">file_path</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t108" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">main_window</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_hecras</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">file_path</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t109" class="pln"><span class="strut"> </span></p> -<p id="t110" class="pln"> <span class="com"># Populate dialog with ras options</span><span class="strut"> </span></p> -<p id="t111" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">populate_plans</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t112" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">populate_profiles</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t113" class="pln"><span class="strut"> </span></p> -<p id="t114" class="stm run hide_run"> <span class="key">def</span> <span class="nam">handle_plan_change</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t115" class="pln"> <span class="str">"""Handle function for changing current plan"""</span><span class="strut"> </span></p> -<p id="t116" class="pln"> <span class="com"># Populate profile based on current plan in ras project</span><span class="strut"> </span></p> -<p id="t117" class="stm mis"> <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">comboBox_plan</span><span class="op">.</span><span class="nam">hasFocus</span><span class="op">(</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t118" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">populate_profiles</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t119" class="pln"><span class="strut"> </span></p> -<p id="t120" class="stm run hide_run"> <span class="key">def</span> <span class="nam">handle_steadiness_change</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t121" class="pln"> <span class="str">"""Handle function for changing steadiness option (steady vs. unsteady)"""</span><span class="strut"> </span></p> -<p id="t122" class="stm mis"> <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">radioButton_steady</span><span class="op">.</span><span class="nam">isChecked</span><span class="op">(</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t123" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">comboBox_profile</span><span class="op">.</span><span class="nam">setEnabled</span><span class="op">(</span><span class="key">True</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t124" class="stm mis"> <span class="key">elif</span> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">radioButton_unsteady</span><span class="op">.</span><span class="nam">isChecked</span><span class="op">(</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t125" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">comboBox_profile</span><span class="op">.</span><span class="nam">setEnabled</span><span class="op">(</span><span class="key">False</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t126" class="pln"><span class="strut"> </span></p> -<p id="t127" class="stm run hide_run"> <span class="key">def</span> <span class="nam">populate_plans</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t128" class="pln"> <span class="str">"""Populates the plans combo box"""</span><span class="strut"> </span></p> -<p id="t129" class="pln"> <span class="com"># Populate plans using current project</span><span class="strut"> </span></p> -<p id="t130" class="stm mis"> <span class="nam">file_path</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_project</span><span class="op">.</span><span class="nam">text</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t131" class="stm mis"> <span class="key">if</span> <span class="nam">file_path</span> <span class="op">!=</span> <span class="str">''</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t132" class="stm mis"> <span class="key">with</span> <span class="nam">RASProject</span><span class="op">(</span><span class="nam">file_path</span><span class="op">)</span> <span class="key">as</span> <span class="nam">rp</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t133" class="pln"> <span class="com"># Clear and populate plans</span><span class="strut"> </span></p> -<p id="t134" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">comboBox_plan</span><span class="op">.</span><span class="nam">clear</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t135" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">comboBox_plan</span><span class="op">.</span><span class="nam">addItems</span><span class="op">(</span><span class="nam">rp</span><span class="op">.</span><span class="nam">plan_names</span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t136" class="pln"> <span class="com"># Set current plan to 1st plan</span><span class="strut"> </span></p> -<p id="t137" class="stm mis"> <span class="nam">rp</span><span class="op">.</span><span class="nam">set_current_plan</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">comboBox_plan</span><span class="op">.</span><span class="nam">currentText</span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t138" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">comboBox_plan</span><span class="op">.</span><span class="nam">setCurrentIndex</span><span class="op">(</span><span class="num">0</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t139" class="pln"><span class="strut"> </span></p> -<p id="t140" class="stm run hide_run"> <span class="key">def</span> <span class="nam">populate_profiles</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t141" class="pln"> <span class="str">"""Populates the profiles combo box</span><span class="strut"> </span></p> -<p id="t142" class="pln"><span class="str"> enables the combo box when steady is checked</span><span class="strut"> </span></p> -<p id="t143" class="pln"><span class="str"> disables the combo box when unsteady is checked"""</span><span class="strut"> </span></p> -<p id="t144" class="pln"> <span class="com"># Populate profiles using current project</span><span class="strut"> </span></p> -<p id="t145" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">comboBox_profile</span><span class="op">.</span><span class="nam">setEnabled</span><span class="op">(</span><span class="key">True</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t146" class="stm mis"> <span class="nam">file_path</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_project</span><span class="op">.</span><span class="nam">text</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t147" class="stm mis"> <span class="key">if</span> <span class="nam">file_path</span> <span class="op">!=</span> <span class="str">''</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t148" class="stm mis"> <span class="key">with</span> <span class="nam">RASProject</span><span class="op">(</span><span class="nam">file_path</span><span class="op">)</span> <span class="key">as</span> <span class="nam">rp</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t149" class="stm mis"> <span class="nam">rp</span><span class="op">.</span><span class="nam">set_current_plan</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">comboBox_plan</span><span class="op">.</span><span class="nam">currentText</span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t150" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">comboBox_profile</span><span class="op">.</span><span class="nam">clear</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t151" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">comboBox_profile</span><span class="op">.</span><span class="nam">addItems</span><span class="op">(</span><span class="nam">rp</span><span class="op">.</span><span class="nam">profile_names</span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t152" class="pln"><span class="strut"> </span></p> -<p id="t153" class="pln"> <span class="com"># Disable profiles when unsteady button is checked</span><span class="strut"> </span></p> -<p id="t154" class="stm mis"> <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">radioButton_unsteady</span><span class="op">.</span><span class="nam">isChecked</span><span class="op">(</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t155" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">comboBox_profile</span><span class="op">.</span><span class="nam">setEnabled</span><span class="op">(</span><span class="key">False</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t156" class="pln"><span class="strut"> </span></p> -<p id="t157" class="stm run hide_run"> <span class="key">def</span> <span class="nam">save_hecras_settings</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t158" class="pln"> <span class="str">"""Saves settings from hecras dialog to main window"""</span><span class="strut"> </span></p> -<p id="t159" class="stm mis"> <span class="nam">mw</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">main_window</span><span class="strut"> </span></p> -<p id="t160" class="stm mis"> <span class="nam">mw</span><span class="op">.</span><span class="nam">hecras_project</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_project</span><span class="op">.</span><span class="nam">text</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t161" class="stm mis"> <span class="nam">mw</span><span class="op">.</span><span class="nam">hecras_plan</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">comboBox_plan</span><span class="op">.</span><span class="nam">currentText</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t162" class="stm mis"> <span class="nam">steadiness_buttons</span> <span class="op">=</span> <span class="op">[</span><span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">radioButton_steady</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t163" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">radioButton_unsteady</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t164" class="stm mis"> <span class="nam">mw</span><span class="op">.</span><span class="nam">hecras_steadiness</span> <span class="op">=</span> <span class="nam">get_checked_radio_button</span><span class="op">(</span><span class="strut"> </span></p> -<p id="t165" class="pln"> <span class="nam">steadiness_buttons</span><span class="op">)</span><span class="op">.</span><span class="nam">objectName</span><span class="op">(</span><span class="op">)</span><span class="op">[</span><span class="num">12</span><span class="op">:</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t166" class="stm mis"> <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">radioButton_steady</span><span class="op">.</span><span class="nam">isChecked</span><span class="op">(</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t167" class="stm mis"> <span class="nam">mw</span><span class="op">.</span><span class="nam">hecras_profile</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">comboBox_profile</span><span class="op">.</span><span class="nam">currentText</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t168" class="stm mis"> <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">radioButton_unsteady</span><span class="op">.</span><span class="nam">isChecked</span><span class="op">(</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t169" class="stm mis"> <span class="nam">mw</span><span class="op">.</span><span class="nam">hecras_profile</span> <span class="op">=</span> <span class="str">'Unsteady'</span><span class="strut"> </span></p> -<p id="t170" class="stm mis"> <span class="nam">mw</span><span class="op">.</span><span class="nam">hecras_temperature</span> <span class="op">=</span> <span class="nam">float</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_temperature</span><span class="op">.</span><span class="nam">text</span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t171" class="pln"> <span class="com"># Get datetime</span><span class="strut"> </span></p> -<p id="t172" class="stm mis"> <span class="nam">dt</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">dateTimeEdit_start_time</span><span class="op">.</span><span class="nam">dateTime</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t173" class="stm mis"> <span class="nam">mw</span><span class="op">.</span><span class="nam">hecras_start_time</span> <span class="op">=</span> <span class="nam">dt</span><span class="op">.</span><span class="nam">toPyDateTime</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t174" class="pln"><span class="strut"> </span></p> -<p id="t175" class="pln"><span class="strut"> </span></p> -<p id="t176" class="stm run hide_run"><span class="key">class</span> <span class="nam">AppWindow</span><span class="op">(</span><span class="nam">QMainWindow</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t177" class="pln"> <span class="str">"""Class that defines the main window of the ui.</span><span class="strut"> </span></p> -<p id="t178" class="pln"><span class="str"> It links the pre-generated ui created by the .ui to .py GUI files</span><span class="strut"> </span></p> -<p id="t179" class="pln"><span class="str"> with the functionality of the main_functions methods"""</span><span class="strut"> </span></p> -<p id="t180" class="pln"><span class="strut"> </span></p> -<p id="t181" class="stm run hide_run"> <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t182" class="pln"> <span class="com"># Initialization of ui window</span><span class="strut"> </span></p> -<p id="t183" class="stm mis"> <span class="nam">super</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">__init__</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t184" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span> <span class="op">=</span> <span class="nam">Ui_MainWindow</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t185" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">setupUi</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t186" class="pln"><span class="strut"> </span></p> -<p id="t187" class="pln"> <span class="com"># FluEgg version</span><span class="strut"> </span></p> -<p id="t188" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">version</span> <span class="op">=</span> <span class="str">'FluEgg 0.0 - Python3.7'</span><span class="strut"> </span></p> -<p id="t189" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">setWindowTitle</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">version</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t190" class="pln"><span class="strut"> </span></p> -<p id="t191" class="pln"> <span class="com"># FluEgg help message</span><span class="strut"> </span></p> -<p id="t192" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">help</span> <span class="op">=</span> <span class="str">''</span><span class="strut"> </span></p> -<p id="t193" class="pln"><span class="strut"> </span></p> -<p id="t194" class="pln"> <span class="com"># Input validators</span><span class="strut"> </span></p> -<p id="t195" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">intV</span> <span class="op">=</span> <span class="nam">QtGui</span><span class="op">.</span><span class="nam">QIntValidator</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t196" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">doubleV</span> <span class="op">=</span> <span class="nam">QtGui</span><span class="op">.</span><span class="nam">QDoubleValidator</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t197" class="pln"><span class="strut"> </span></p> -<p id="t198" class="pln"> <span class="com"># Set line edit validators</span><span class="strut"> </span></p> -<p id="t199" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_duration</span><span class="op">.</span><span class="nam">setValidator</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">intV</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t200" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_number_of_eggs</span><span class="op">.</span><span class="nam">setValidator</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">intV</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t201" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_time_step</span><span class="op">.</span><span class="nam">setValidator</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">intV</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t202" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_x</span><span class="op">.</span><span class="nam">setValidator</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">doubleV</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t203" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_y</span><span class="op">.</span><span class="nam">setValidator</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">doubleV</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t204" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_z</span><span class="op">.</span><span class="nam">setValidator</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">doubleV</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t205" class="pln"><span class="strut"> </span></p> -<p id="t206" class="pln"> <span class="com"># Scale ui window to half desktop size</span><span class="strut"> </span></p> -<p id="t207" class="stm mis"> <span class="nam">width</span> <span class="op">=</span> <span class="nam">QDesktopWidget</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">availableGeometry</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">size</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">width</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t208" class="stm mis"> <span class="nam">height</span> <span class="op">=</span> <span class="nam">QDesktopWidget</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">availableGeometry</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">size</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">height</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t209" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">resize</span><span class="op">(</span><span class="nam">int</span><span class="op">(</span><span class="nam">width</span><span class="op">*</span><span class="num">.2</span><span class="op">)</span><span class="op">,</span> <span class="nam">int</span><span class="op">(</span><span class="nam">height</span><span class="op">*</span><span class="num">0.4</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t210" class="pln"><span class="strut"> </span></p> -<p id="t211" class="pln"> <span class="com"># Define connections between ui events and handle functions</span><span class="strut"> </span></p> -<p id="t212" class="pln"> <span class="com"># Menu Buttons</span><span class="strut"> </span></p> -<p id="t213" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">actionVersion</span><span class="op">.</span><span class="nam">triggered</span><span class="op">.</span><span class="nam">connect</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">handle_version</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t214" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">actionHelp</span><span class="op">.</span><span class="nam">triggered</span><span class="op">.</span><span class="nam">connect</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">handle_help</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t215" class="pln"> <span class="com"># Hydraulic Channel</span><span class="strut"> </span></p> -<p id="t216" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">radioButton_csv</span><span class="op">.</span><span class="nam">clicked</span><span class="op">.</span><span class="nam">connect</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">handle_hydraulic_change</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t217" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">radioButton_hecras</span><span class="op">.</span><span class="nam">clicked</span><span class="op">.</span><span class="nam">connect</span><span class="op">(</span><span class="strut"> </span></p> -<p id="t218" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">handle_hydraulic_change</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t219" class="pln"><span class="strut"> </span></p> -<p id="t220" class="pln"> <span class="com"># disable ras options if not on Windows</span><span class="strut"> </span></p> -<p id="t221" class="stm mis"> <span class="key">if</span> <span class="key">not</span> <span class="nam">RASProject</span><span class="op">.</span><span class="nam">ras_controller_loaded</span><span class="op">(</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t222" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">radioButton_hecras</span><span class="op">.</span><span class="nam">setEnabled</span><span class="op">(</span><span class="key">False</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t223" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_hecras</span><span class="op">.</span><span class="nam">setEnabled</span><span class="op">(</span><span class="key">False</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t224" class="pln"><span class="strut"> </span></p> -<p id="t225" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">pushButton_browse</span><span class="op">.</span><span class="nam">clicked</span><span class="op">.</span><span class="nam">connect</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">handle_browse</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t226" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">pushButton_browse</span><span class="op">.</span><span class="nam">setEnabled</span><span class="op">(</span><span class="key">True</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t227" class="pln"> <span class="com"># Eggs</span><span class="strut"> </span></p> -<p id="t228" class="pln"> <span class="com"># Simulation</span><span class="strut"> </span></p> -<p id="t229" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">pushButton_run</span><span class="op">.</span><span class="nam">clicked</span><span class="op">.</span><span class="nam">connect</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">handle_run</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t230" class="pln"><span class="strut"> </span></p> -<p id="t231" class="pln"> <span class="com"># default selection</span><span class="strut"> </span></p> -<p id="t232" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">radioButton_csv</span><span class="op">.</span><span class="nam">setChecked</span><span class="op">(</span><span class="key">True</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t233" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">radioButton_parabolic_constant</span><span class="op">.</span><span class="nam">setChecked</span><span class="op">(</span><span class="key">True</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t234" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">radioButton_grass</span><span class="op">.</span><span class="nam">setChecked</span><span class="op">(</span><span class="key">True</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t235" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">radioButton_varying_dd</span><span class="op">.</span><span class="nam">setChecked</span><span class="op">(</span><span class="key">True</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t236" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">radioButton_forward</span><span class="op">.</span><span class="nam">setChecked</span><span class="op">(</span><span class="key">True</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t237" class="pln"><span class="strut"> </span></p> -<p id="t238" class="pln"> <span class="com"># Hecras saved information</span><span class="strut"> </span></p> -<p id="t239" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">hw</span> <span class="op">=</span> <span class="key">None</span><span class="strut"> </span></p> -<p id="t240" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">hecras_project</span> <span class="op">=</span> <span class="str">''</span><span class="strut"> </span></p> -<p id="t241" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">hecras_plan</span> <span class="op">=</span> <span class="str">''</span><span class="strut"> </span></p> -<p id="t242" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">hecras_profile</span> <span class="op">=</span> <span class="str">''</span><span class="strut"> </span></p> -<p id="t243" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">hecras_steadiness</span> <span class="op">=</span> <span class="str">''</span><span class="strut"> </span></p> -<p id="t244" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">hecras_temperature</span> <span class="op">=</span> <span class="str">''</span><span class="strut"> </span></p> -<p id="t245" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">hecras_start_time</span> <span class="op">=</span> <span class="num">0</span><span class="strut"> </span></p> -<p id="t246" class="pln"><span class="strut"> </span></p> -<p id="t247" class="pln"> <span class="com"># Display the ui</span><span class="strut"> </span></p> -<p id="t248" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">show</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t249" class="pln"><span class="strut"> </span></p> -<p id="t250" class="stm run hide_run"> <span class="key">def</span> <span class="nam">handle_version</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t251" class="pln"> <span class="str">"""Handle function for clicking About > Version"""</span><span class="strut"> </span></p> -<p id="t252" class="stm mis"> <span class="nam">QMessageBox</span><span class="op">.</span><span class="nam">about</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="str">'Version'</span><span class="op">,</span> <span class="nam">self</span><span class="op">.</span><span class="nam">version</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t253" class="pln"><span class="strut"> </span></p> -<p id="t254" class="stm run hide_run"> <span class="key">def</span> <span class="nam">handle_help</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t255" class="pln"> <span class="str">"""Handle function for clicking About > Help"""</span><span class="strut"> </span></p> -<p id="t256" class="stm mis"> <span class="nam">QMessageBox</span><span class="op">.</span><span class="nam">about</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="str">'Help'</span><span class="op">,</span> <span class="nam">self</span><span class="op">.</span><span class="nam">help</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t257" class="pln"><span class="strut"> </span></p> -<p id="t258" class="stm run hide_run"> <span class="key">def</span> <span class="nam">handle_hydraulic_change</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t259" class="pln"> <span class="str">"""Handle function for changing the Hydraulic Channel input"""</span><span class="strut"> </span></p> -<p id="t260" class="pln"> <span class="com"># self.ui.pushButton_browse.setEnabled(True)</span><span class="strut"> </span></p> -<p id="t261" class="stm mis"> <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">radioButton_csv</span><span class="op">.</span><span class="nam">isChecked</span><span class="op">(</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t262" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_csv</span><span class="op">.</span><span class="nam">setEnabled</span><span class="op">(</span><span class="key">True</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t263" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_hecras</span><span class="op">.</span><span class="nam">setEnabled</span><span class="op">(</span><span class="key">False</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t264" class="stm mis"> <span class="key">elif</span> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">radioButton_hecras</span><span class="op">.</span><span class="nam">isChecked</span><span class="op">(</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t265" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_csv</span><span class="op">.</span><span class="nam">setEnabled</span><span class="op">(</span><span class="key">False</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t266" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_hecras</span><span class="op">.</span><span class="nam">setEnabled</span><span class="op">(</span><span class="key">True</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t267" class="pln"><span class="strut"> </span></p> -<p id="t268" class="stm run hide_run"> <span class="key">def</span> <span class="nam">handle_browse</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t269" class="pln"> <span class="str">"""Handle function for clicking Browse"""</span><span class="strut"> </span></p> -<p id="t270" class="stm mis"> <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">radioButton_csv</span><span class="op">.</span><span class="nam">isChecked</span><span class="op">(</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t271" class="pln"> <span class="com"># File exploring dialog</span><span class="strut"> </span></p> -<p id="t272" class="stm mis"> <span class="nam">dlg</span> <span class="op">=</span> <span class="nam">QFileDialog</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t273" class="stm mis"> <span class="nam">file_path</span> <span class="op">=</span> <span class="nam">dlg</span><span class="op">.</span><span class="nam">getOpenFileName</span><span class="op">(</span><span class="strut"> </span></p> -<p id="t274" class="pln"> <span class="nam">self</span><span class="op">,</span> <span class="str">"QFileDialog.getOpenFileName()"</span><span class="op">,</span> <span class="str">""</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t275" class="pln"> <span class="str">"CSV File (*.csv)"</span><span class="op">)</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t276" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_csv</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">file_path</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t277" class="pln"><span class="strut"> </span></p> -<p id="t278" class="stm mis"> <span class="key">elif</span> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">radioButton_hecras</span><span class="op">.</span><span class="nam">isChecked</span><span class="op">(</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t279" class="pln"><span class="strut"> </span></p> -<p id="t280" class="pln"> <span class="com"># File exploring dialog</span><span class="strut"> </span></p> -<p id="t281" class="stm mis"> <span class="nam">dlg</span> <span class="op">=</span> <span class="nam">QFileDialog</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t282" class="stm mis"> <span class="nam">file_path</span> <span class="op">=</span> <span class="nam">dlg</span><span class="op">.</span><span class="nam">getOpenFileName</span><span class="op">(</span><span class="strut"> </span></p> -<p id="t283" class="pln"> <span class="nam">self</span><span class="op">,</span> <span class="str">"QFileDialog.getOpenFileName()"</span><span class="op">,</span> <span class="str">""</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t284" class="pln"> <span class="str">"HECRAS Project File (*.prj)"</span><span class="op">)</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t285" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_hecras</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">file_path</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t286" class="pln"><span class="strut"> </span></p> -<p id="t287" class="pln"> <span class="com"># Hecras dialog</span><span class="strut"> </span></p> -<p id="t288" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">hw</span> <span class="op">=</span> <span class="nam">HecrasDialog</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t289" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">hw</span><span class="op">.</span><span class="nam">show</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t290" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">hw</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_project</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">file_path</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t291" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">hw</span><span class="op">.</span><span class="nam">setup</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t292" class="pln"><span class="strut"> </span></p> -<p id="t293" class="stm run hide_run"> <span class="key">def</span> <span class="nam">handle_run</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t294" class="pln"> <span class="str">"""Handle function for clicking Run"""</span><span class="strut"> </span></p> -<p id="t295" class="pln"> <span class="com"># Radio button groups</span><span class="strut"> </span></p> -<p id="t296" class="stm mis"> <span class="nam">hydraulic_inputs</span> <span class="op">=</span> <span class="op">[</span><span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">radioButton_csv</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t297" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">radioButton_hecras</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t298" class="stm mis"> <span class="nam">diffusitvities</span> <span class="op">=</span> <span class="op">[</span><span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">radioButton_parabolic</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t299" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">radioButton_parabolic_constant</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t300" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">radioButton_constant</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t301" class="stm mis"> <span class="nam">species</span> <span class="op">=</span> <span class="op">[</span><span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">radioButton_grass</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t302" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">radioButton_silver</span><span class="op">,</span> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">radioButton_bighead</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t303" class="stm mis"> <span class="nam">varying_dd</span> <span class="op">=</span> <span class="op">[</span><span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">radioButton_constant_dd</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t304" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">radioButton_varying_dd</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t305" class="stm mis"> <span class="nam">direction</span> <span class="op">=</span> <span class="op">[</span><span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">radioButton_forward</span><span class="op">,</span> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">radioButton_reverse</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t306" class="pln"><span class="strut"> </span></p> -<p id="t307" class="pln"> <span class="com"># Initialize input and error flag</span><span class="strut"> </span></p> -<p id="t308" class="stm mis"> <span class="nam">d</span> <span class="op">=</span> <span class="op">{</span><span class="op">}</span><span class="strut"> </span></p> -<p id="t309" class="stm mis"> <span class="nam">valid_inputs</span> <span class="op">=</span> <span class="key">True</span><span class="strut"> </span></p> -<p id="t310" class="stm mis"> <span class="nam">error_message</span> <span class="op">=</span> <span class="str">''</span><span class="strut"> </span></p> -<p id="t311" class="pln"><span class="strut"> </span></p> -<p id="t312" class="pln"> <span class="com"># Fill dictionary and perform input error checking</span><span class="strut"> </span></p> -<p id="t313" class="stm mis"> <span class="key">if</span> <span class="nam">get_checked_radio_button</span><span class="op">(</span><span class="nam">hydraulic_inputs</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t314" class="stm mis"> <span class="nam">d</span><span class="op">[</span><span class="str">'hydraulic_mode'</span><span class="op">]</span> <span class="op">=</span> <span class="nam">get_checked_radio_button</span><span class="op">(</span><span class="strut"> </span></p> -<p id="t315" class="pln"> <span class="nam">hydraulic_inputs</span><span class="op">)</span><span class="op">.</span><span class="nam">objectName</span><span class="op">(</span><span class="op">)</span><span class="op">[</span><span class="num">12</span><span class="op">:</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t316" class="pln"><span class="strut"> </span></p> -<p id="t317" class="stm mis"> <span class="key">if</span> <span class="nam">d</span><span class="op">[</span><span class="str">'hydraulic_mode'</span><span class="op">]</span> <span class="op">==</span> <span class="str">'csv'</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t318" class="stm mis"> <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_csv</span><span class="op">.</span><span class="nam">text</span><span class="op">(</span><span class="op">)</span> <span class="op">!=</span> <span class="str">''</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t319" class="stm mis"> <span class="nam">d</span><span class="op">[</span><span class="str">'csv_path'</span><span class="op">]</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_csv</span><span class="op">.</span><span class="nam">text</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t320" class="stm mis"> <span class="nam">d</span><span class="op">[</span><span class="str">'hecras_path'</span><span class="op">]</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_hecras</span><span class="op">.</span><span class="nam">text</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t321" class="pln"> <span class="key">else</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t322" class="stm mis"> <span class="nam">error_message</span> <span class="op">+=</span> <span class="str">'--Load the hydraulic csv file.\n'</span><span class="strut"> </span></p> -<p id="t323" class="stm mis"> <span class="nam">valid_inputs</span> <span class="op">=</span> <span class="key">False</span><span class="strut"> </span></p> -<p id="t324" class="pln"><span class="strut"> </span></p> -<p id="t325" class="stm mis"> <span class="key">if</span> <span class="nam">d</span><span class="op">[</span><span class="str">'hydraulic_mode'</span><span class="op">]</span> <span class="op">==</span> <span class="str">'hecras'</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t326" class="stm mis"> <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_hecras</span><span class="op">.</span><span class="nam">text</span><span class="op">(</span><span class="op">)</span> <span class="op">!=</span> <span class="str">''</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t327" class="stm mis"> <span class="nam">d</span><span class="op">[</span><span class="str">'csv_path'</span><span class="op">]</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_csv</span><span class="op">.</span><span class="nam">text</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t328" class="stm mis"> <span class="nam">d</span><span class="op">[</span><span class="str">'hecras_path'</span><span class="op">]</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_hecras</span><span class="op">.</span><span class="nam">text</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t329" class="stm mis"> <span class="nam">d</span><span class="op">[</span><span class="str">'hecras_project'</span><span class="op">]</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">hecras_project</span><span class="strut"> </span></p> -<p id="t330" class="stm mis"> <span class="nam">d</span><span class="op">[</span><span class="str">'hecras_plan'</span><span class="op">]</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">hecras_plan</span><span class="strut"> </span></p> -<p id="t331" class="stm mis"> <span class="nam">d</span><span class="op">[</span><span class="str">'hecras_profile'</span><span class="op">]</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">hecras_profile</span><span class="strut"> </span></p> -<p id="t332" class="stm mis"> <span class="nam">d</span><span class="op">[</span><span class="str">'hecras_steadiness'</span><span class="op">]</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">hecras_steadiness</span><span class="strut"> </span></p> -<p id="t333" class="stm mis"> <span class="nam">d</span><span class="op">[</span><span class="str">'hecras_temperature'</span><span class="op">]</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">hecras_temperature</span><span class="strut"> </span></p> -<p id="t334" class="stm mis"> <span class="nam">d</span><span class="op">[</span><span class="str">'hecras_start_time'</span><span class="op">]</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">hecras_start_time</span><span class="strut"> </span></p> -<p id="t335" class="pln"> <span class="key">else</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t336" class="stm mis"> <span class="nam">error_message</span> <span class="op">+=</span> <span class="str">'--Load the hydraulic hecras project.\n'</span><span class="strut"> </span></p> -<p id="t337" class="stm mis"> <span class="nam">valid_inputs</span> <span class="op">=</span> <span class="key">False</span><span class="strut"> </span></p> -<p id="t338" class="pln"><span class="strut"> </span></p> -<p id="t339" class="pln"> <span class="key">else</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t340" class="stm mis"> <span class="nam">error_message</span> <span class="op">+=</span> <span class="str">'--Choose a hydraulic data type.\n'</span><span class="strut"> </span></p> -<p id="t341" class="stm mis"> <span class="nam">valid_inputs</span> <span class="op">=</span> <span class="key">False</span><span class="strut"> </span></p> -<p id="t342" class="pln"><span class="strut"> </span></p> -<p id="t343" class="stm mis"> <span class="key">if</span> <span class="nam">get_checked_radio_button</span><span class="op">(</span><span class="nam">diffusitvities</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t344" class="stm mis"> <span class="nam">d</span><span class="op">[</span><span class="str">'diffusivity'</span><span class="op">]</span> <span class="op">=</span> <span class="nam">get_checked_radio_button</span><span class="op">(</span><span class="strut"> </span></p> -<p id="t345" class="pln"> <span class="nam">diffusitvities</span><span class="op">)</span><span class="op">.</span><span class="nam">objectName</span><span class="op">(</span><span class="op">)</span><span class="op">[</span><span class="num">12</span><span class="op">:</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t346" class="stm mis"> <span class="key">if</span> <span class="nam">d</span><span class="op">[</span><span class="str">'diffusivity'</span><span class="op">]</span> <span class="op">==</span> <span class="str">'parabolic_constant'</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t347" class="stm mis"> <span class="nam">d</span><span class="op">[</span><span class="str">'diffusivity'</span><span class="op">]</span> <span class="op">=</span> <span class="str">'parabolic-constant'</span><span class="strut"> </span></p> -<p id="t348" class="pln"> <span class="key">else</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t349" class="stm mis"> <span class="nam">error_message</span> <span class="op">+=</span> <span class="str">'--Choose a diffusivity profile.\n'</span><span class="strut"> </span></p> -<p id="t350" class="stm mis"> <span class="nam">valid_inputs</span> <span class="op">=</span> <span class="key">False</span><span class="strut"> </span></p> -<p id="t351" class="pln"><span class="strut"> </span></p> -<p id="t352" class="stm mis"> <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_x</span><span class="op">.</span><span class="nam">text</span><span class="op">(</span><span class="op">)</span> <span class="op">!=</span> <span class="str">''</span> <span class="key">and</span> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_y</span><span class="op">.</span><span class="nam">text</span><span class="op">(</span><span class="op">)</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t353" class="pln"> <span class="op">!=</span> <span class="str">''</span> <span class="key">and</span> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_z</span><span class="op">.</span><span class="nam">text</span><span class="op">(</span><span class="op">)</span> <span class="op">!=</span> <span class="str">''</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t354" class="stm mis"> <span class="nam">d</span><span class="op">[</span><span class="str">'x'</span><span class="op">]</span> <span class="op">=</span> <span class="nam">float</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_x</span><span class="op">.</span><span class="nam">text</span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t355" class="stm mis"> <span class="nam">d</span><span class="op">[</span><span class="str">'y'</span><span class="op">]</span> <span class="op">=</span> <span class="nam">float</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_y</span><span class="op">.</span><span class="nam">text</span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t356" class="stm mis"> <span class="nam">d</span><span class="op">[</span><span class="str">'z'</span><span class="op">]</span> <span class="op">=</span> <span class="nam">float</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_z</span><span class="op">.</span><span class="nam">text</span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t357" class="pln"> <span class="key">else</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t358" class="stm mis"> <span class="nam">error_message</span> <span class="op">+=</span> <span class="str">'--Input X,Y,Z values.\n'</span><span class="strut"> </span></p> -<p id="t359" class="stm mis"> <span class="nam">valid_inputs</span> <span class="op">=</span> <span class="key">False</span><span class="strut"> </span></p> -<p id="t360" class="pln"><span class="strut"> </span></p> -<p id="t361" class="stm mis"> <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_number_of_eggs</span><span class="op">.</span><span class="nam">text</span><span class="op">(</span><span class="op">)</span> <span class="op">!=</span> <span class="str">''</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t362" class="stm mis"> <span class="nam">d</span><span class="op">[</span><span class="str">'num_eggs'</span><span class="op">]</span> <span class="op">=</span> <span class="nam">int</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_number_of_eggs</span><span class="op">.</span><span class="nam">text</span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t363" class="pln"> <span class="key">else</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t364" class="stm mis"> <span class="nam">error_message</span> <span class="op">+=</span> <span class="str">'--Input number of eggs.\n'</span><span class="strut"> </span></p> -<p id="t365" class="stm mis"> <span class="nam">valid_inputs</span> <span class="op">=</span> <span class="key">False</span><span class="strut"> </span></p> -<p id="t366" class="pln"><span class="strut"> </span></p> -<p id="t367" class="stm mis"> <span class="key">if</span> <span class="nam">get_checked_radio_button</span><span class="op">(</span><span class="nam">species</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t368" class="stm mis"> <span class="nam">d</span><span class="op">[</span><span class="str">'species'</span><span class="op">]</span> <span class="op">=</span> <span class="nam">get_checked_radio_button</span><span class="op">(</span><span class="nam">species</span><span class="op">)</span><span class="op">.</span><span class="nam">objectName</span><span class="op">(</span><span class="op">)</span><span class="op">[</span><span class="num">12</span><span class="op">:</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t369" class="pln"> <span class="key">else</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t370" class="stm mis"> <span class="nam">error_message</span> <span class="op">+=</span> <span class="str">'--Choose species.\n'</span><span class="strut"> </span></p> -<p id="t371" class="stm mis"> <span class="nam">valid_inputs</span> <span class="op">=</span> <span class="key">False</span><span class="strut"> </span></p> -<p id="t372" class="pln"><span class="strut"> </span></p> -<p id="t373" class="stm mis"> <span class="key">if</span> <span class="nam">get_checked_radio_button</span><span class="op">(</span><span class="nam">varying_dd</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t374" class="stm mis"> <span class="nam">d</span><span class="op">[</span><span class="str">'varying_dd'</span><span class="op">]</span> <span class="op">=</span> <span class="nam">get_checked_radio_button</span><span class="op">(</span><span class="strut"> </span></p> -<p id="t375" class="pln"> <span class="nam">varying_dd</span><span class="op">)</span><span class="op">.</span><span class="nam">objectName</span><span class="op">(</span><span class="op">)</span><span class="op">[</span><span class="num">12</span><span class="op">:</span><span class="op">-</span><span class="num">3</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t376" class="pln"> <span class="key">else</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t377" class="stm mis"> <span class="nam">error_message</span> <span class="op">+=</span> <span class="str">'--Choose varying or constant density/diameter.\n'</span><span class="strut"> </span></p> -<p id="t378" class="stm mis"> <span class="nam">valid_inputs</span> <span class="op">=</span> <span class="key">False</span><span class="strut"> </span></p> -<p id="t379" class="pln"><span class="strut"> </span></p> -<p id="t380" class="stm mis"> <span class="key">if</span> <span class="nam">get_checked_radio_button</span><span class="op">(</span><span class="nam">direction</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t381" class="stm mis"> <span class="nam">d</span><span class="op">[</span><span class="str">'direction'</span><span class="op">]</span> <span class="op">=</span> <span class="nam">get_checked_radio_button</span><span class="op">(</span><span class="strut"> </span></p> -<p id="t382" class="pln"> <span class="nam">direction</span><span class="op">)</span><span class="op">.</span><span class="nam">objectName</span><span class="op">(</span><span class="op">)</span><span class="op">[</span><span class="num">12</span><span class="op">:</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t383" class="pln"> <span class="key">else</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t384" class="stm mis"> <span class="nam">error_message</span> <span class="op">+=</span> <span class="str">'--Choose simulation direction.\n'</span><span class="strut"> </span></p> -<p id="t385" class="stm mis"> <span class="nam">valid_inputs</span> <span class="op">=</span> <span class="key">False</span><span class="strut"> </span></p> -<p id="t386" class="pln"><span class="strut"> </span></p> -<p id="t387" class="stm mis"> <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_duration</span><span class="op">.</span><span class="nam">text</span><span class="op">(</span><span class="op">)</span> <span class="op">!=</span> <span class="str">''</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t388" class="stm mis"> <span class="nam">d</span><span class="op">[</span><span class="str">'duration'</span><span class="op">]</span> <span class="op">=</span> <span class="nam">int</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_duration</span><span class="op">.</span><span class="nam">text</span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t389" class="pln"> <span class="key">else</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t390" class="stm mis"> <span class="nam">error_message</span> <span class="op">+=</span> <span class="str">'--Input simulation duration.\n'</span><span class="strut"> </span></p> -<p id="t391" class="stm mis"> <span class="nam">valid_inputs</span> <span class="op">=</span> <span class="key">False</span><span class="strut"> </span></p> -<p id="t392" class="pln"><span class="strut"> </span></p> -<p id="t393" class="stm mis"> <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_time_step</span><span class="op">.</span><span class="nam">text</span><span class="op">(</span><span class="op">)</span> <span class="op">!=</span> <span class="str">''</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t394" class="stm mis"> <span class="nam">d</span><span class="op">[</span><span class="str">'time_step'</span><span class="op">]</span> <span class="op">=</span> <span class="nam">int</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_time_step</span><span class="op">.</span><span class="nam">text</span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t395" class="pln"> <span class="key">else</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t396" class="stm mis"> <span class="nam">error_message</span> <span class="op">+=</span> <span class="str">'--Input simulation time step.\n'</span><span class="strut"> </span></p> -<p id="t397" class="stm mis"> <span class="nam">valid_inputs</span> <span class="op">=</span> <span class="key">False</span><span class="strut"> </span></p> -<p id="t398" class="pln"><span class="strut"> </span></p> -<p id="t399" class="stm mis"> <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_simulation_name</span><span class="op">.</span><span class="nam">text</span><span class="op">(</span><span class="op">)</span> <span class="op">!=</span> <span class="str">''</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t400" class="stm mis"> <span class="nam">d</span><span class="op">[</span><span class="str">'sim_name'</span><span class="op">]</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">ui</span><span class="op">.</span><span class="nam">lineEdit_simulation_name</span><span class="op">.</span><span class="nam">text</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t401" class="pln"> <span class="key">else</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t402" class="stm mis"> <span class="nam">error_message</span> <span class="op">+=</span> <span class="str">'--Input simulation name.\n'</span><span class="strut"> </span></p> -<p id="t403" class="stm mis"> <span class="nam">valid_inputs</span> <span class="op">=</span> <span class="key">False</span><span class="strut"> </span></p> -<p id="t404" class="pln"><span class="strut"> </span></p> -<p id="t405" class="pln"> <span class="com"># Run simulation OR show gui error message.</span><span class="strut"> </span></p> -<p id="t406" class="stm mis"> <span class="key">if</span> <span class="nam">valid_inputs</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t407" class="pln"> <span class="com"># Show error message from backend gui so gui doesn't crash</span><span class="strut"> </span></p> -<p id="t408" class="stm mis"> <span class="key">try</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t409" class="stm mis"> <span class="nam">sim</span> <span class="op">=</span> <span class="nam">from_input_dict</span><span class="op">(</span><span class="nam">d</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t410" class="stm mis"> <span class="nam">results</span> <span class="op">=</span> <span class="nam">sim</span><span class="op">.</span><span class="nam">run</span><span class="op">(</span><span class="nam">configuration</span><span class="op">=</span><span class="nam">d</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t411" class="stm mis"> <span class="nam">results</span><span class="op">.</span><span class="nam">save_results</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t412" class="pln"><span class="strut"> </span></p> -<p id="t413" class="stm mis"> <span class="key">except</span> <span class="nam">Exception</span> <span class="key">as</span> <span class="nam">e</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t414" class="stm mis"> <span class="nam">traceback</span><span class="op">.</span><span class="nam">print_exc</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t415" class="stm mis"> <span class="nam">QMessageBox</span><span class="op">.</span><span class="nam">warning</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="str">'Error'</span><span class="op">,</span> <span class="nam">str</span><span class="op">(</span><span class="nam">e</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t416" class="pln"> <span class="key">else</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t417" class="stm mis"> <span class="nam">QMessageBox</span><span class="op">.</span><span class="nam">warning</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="str">'Error'</span><span class="op">,</span> <span class="nam">error_message</span><span class="op">)</span><span class="strut"> </span></p> - - </td> - </tr> - </table> -</div> - -<div id="footer"> - <div class="content"> - <p> - <a class="nav" href="index.html">« index</a> <a class="nav" href="https://coverage.readthedocs.io">coverage.py v4.5.3</a>, - created at 2019-07-09 15:15 - </p> - </div> -</div> - -</body> -</html> diff --git a/coverage_report/fluegg_gui_hecras_dialog_py.html b/coverage_report/fluegg_gui_hecras_dialog_py.html deleted file mode 100644 index b01c1e2..0000000 --- a/coverage_report/fluegg_gui_hecras_dialog_py.html +++ /dev/null @@ -1,337 +0,0 @@ - - - -<!DOCTYPE html> -<html> -<head> - <meta http-equiv="Content-Type" content="text/html; charset=utf-8"> - - - <meta http-equiv="X-UA-Compatible" content="IE=emulateIE7" /> - <title>Coverage for fluegg\gui\hecras_dialog.py: 4%</title> - <link rel="stylesheet" href="style.css" type="text/css"> - - <script type="text/javascript" src="jquery.min.js"></script> - <script type="text/javascript" src="jquery.hotkeys.js"></script> - <script type="text/javascript" src="jquery.isonscreen.js"></script> - <script type="text/javascript" src="coverage_html.js"></script> - <script type="text/javascript"> - jQuery(document).ready(coverage.pyfile_ready); - </script> -</head> -<body class="pyfile"> - -<div id="header"> - <div class="content"> - <h1>Coverage for <b>fluegg\gui\hecras_dialog.py</b> : - <span class="pc_cov">4%</span> - </h1> - - <img id="keyboard_icon" src="keybd_closed.png" alt="Show keyboard shortcuts" /> - - <h2 class="stats"> - 112 statements - <span class="run hide_run shortkey_r button_toggle_run">4 run</span> - <span class="mis shortkey_m button_toggle_mis">108 missing</span> - <span class="exc shortkey_x button_toggle_exc">0 excluded</span> - - - </h2> - </div> -</div> - -<div class="help_panel"> - <img id="panel_icon" src="keybd_open.png" alt="Hide keyboard shortcuts" /> - <p class="legend">Hot-keys on this page</p> - <div> - <p class="keyhelp"> - <span class="key">r</span> - <span class="key">m</span> - <span class="key">x</span> - <span class="key">p</span> toggle line displays - </p> - <p class="keyhelp"> - <span class="key">j</span> - <span class="key">k</span> next/prev highlighted chunk - </p> - <p class="keyhelp"> - <span class="key">0</span> (zero) top of page - </p> - <p class="keyhelp"> - <span class="key">1</span> (one) first highlighted chunk - </p> - </div> -</div> - -<div id="source"> - <table> - <tr> - <td class="linenos"> -<p id="n1" class="pln"><a href="#n1">1</a></p> -<p id="n2" class="pln"><a href="#n2">2</a></p> -<p id="n3" class="pln"><a href="#n3">3</a></p> -<p id="n4" class="pln"><a href="#n4">4</a></p> -<p id="n5" class="pln"><a href="#n5">5</a></p> -<p id="n6" class="pln"><a href="#n6">6</a></p> -<p id="n7" class="pln"><a href="#n7">7</a></p> -<p id="n8" class="pln"><a href="#n8">8</a></p> -<p id="n9" class="stm run hide_run"><a href="#n9">9</a></p> -<p id="n10" class="pln"><a href="#n10">10</a></p> -<p id="n11" class="stm run hide_run"><a href="#n11">11</a></p> -<p id="n12" class="stm run hide_run"><a href="#n12">12</a></p> -<p id="n13" class="stm mis"><a href="#n13">13</a></p> -<p id="n14" class="stm mis"><a href="#n14">14</a></p> -<p id="n15" class="stm mis"><a href="#n15">15</a></p> -<p id="n16" class="stm mis"><a href="#n16">16</a></p> -<p id="n17" class="stm mis"><a href="#n17">17</a></p> -<p id="n18" class="stm mis"><a href="#n18">18</a></p> -<p id="n19" class="stm mis"><a href="#n19">19</a></p> -<p id="n20" class="stm mis"><a href="#n20">20</a></p> -<p id="n21" class="stm mis"><a href="#n21">21</a></p> -<p id="n22" class="stm mis"><a href="#n22">22</a></p> -<p id="n23" class="stm mis"><a href="#n23">23</a></p> -<p id="n24" class="stm mis"><a href="#n24">24</a></p> -<p id="n25" class="stm mis"><a href="#n25">25</a></p> -<p id="n26" class="stm mis"><a href="#n26">26</a></p> -<p id="n27" class="stm mis"><a href="#n27">27</a></p> -<p id="n28" class="stm mis"><a href="#n28">28</a></p> -<p id="n29" class="stm mis"><a href="#n29">29</a></p> -<p id="n30" class="stm mis"><a href="#n30">30</a></p> -<p id="n31" class="stm mis"><a href="#n31">31</a></p> -<p id="n32" class="stm mis"><a href="#n32">32</a></p> -<p id="n33" class="stm mis"><a 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href="#n87">87</a></p> -<p id="n88" class="stm mis"><a href="#n88">88</a></p> -<p id="n89" class="stm mis"><a href="#n89">89</a></p> -<p id="n90" class="stm mis"><a href="#n90">90</a></p> -<p id="n91" class="stm mis"><a href="#n91">91</a></p> -<p id="n92" class="stm mis"><a href="#n92">92</a></p> -<p id="n93" class="stm mis"><a href="#n93">93</a></p> -<p id="n94" class="stm mis"><a href="#n94">94</a></p> -<p id="n95" class="stm mis"><a href="#n95">95</a></p> -<p id="n96" class="stm mis"><a href="#n96">96</a></p> -<p id="n97" class="stm mis"><a href="#n97">97</a></p> -<p id="n98" class="stm mis"><a href="#n98">98</a></p> -<p id="n99" class="stm mis"><a href="#n99">99</a></p> -<p id="n100" class="stm mis"><a href="#n100">100</a></p> -<p id="n101" class="stm mis"><a href="#n101">101</a></p> -<p id="n102" class="stm mis"><a href="#n102">102</a></p> -<p id="n103" class="stm mis"><a href="#n103">103</a></p> -<p id="n104" class="stm mis"><a href="#n104">104</a></p> -<p id="n105" class="stm mis"><a href="#n105">105</a></p> -<p id="n106" class="stm mis"><a href="#n106">106</a></p> -<p id="n107" class="pln"><a href="#n107">107</a></p> -<p id="n108" class="stm mis"><a href="#n108">108</a></p> -<p id="n109" class="stm mis"><a href="#n109">109</a></p> -<p id="n110" class="pln"><a href="#n110">110</a></p> -<p id="n111" class="stm run hide_run"><a href="#n111">111</a></p> -<p id="n112" class="stm mis"><a href="#n112">112</a></p> -<p id="n113" class="stm mis"><a href="#n113">113</a></p> -<p id="n114" class="stm mis"><a href="#n114">114</a></p> -<p id="n115" class="stm mis"><a href="#n115">115</a></p> -<p id="n116" class="stm mis"><a href="#n116">116</a></p> -<p id="n117" class="stm mis"><a href="#n117">117</a></p> -<p id="n118" class="stm mis"><a href="#n118">118</a></p> -<p id="n119" class="stm mis"><a href="#n119">119</a></p> -<p id="n120" class="stm mis"><a href="#n120">120</a></p> -<p id="n121" class="stm mis"><a href="#n121">121</a></p> -<p id="n122" class="stm mis"><a href="#n122">122</a></p> -<p id="n123" class="stm mis"><a href="#n123">123</a></p> -<p id="n124" class="pln"><a href="#n124">124</a></p> - - </td> - <td class="text"> -<p id="t1" class="pln"><span class="com"># -*- coding: utf-8 -*-</span><span class="strut"> </span></p> -<p id="t2" class="pln"><span class="strut"> </span></p> -<p id="t3" class="pln"><span class="com"># Form implementation generated from reading ui file 'hecras_dialog.ui'</span><span class="strut"> </span></p> -<p id="t4" class="pln"><span class="com">#</span><span class="strut"> </span></p> -<p id="t5" class="pln"><span class="com"># Created by: PyQt5 UI code generator 5.11.3</span><span class="strut"> </span></p> -<p id="t6" class="pln"><span class="com">#</span><span class="strut"> </span></p> -<p id="t7" class="pln"><span class="com"># WARNING! All changes made in this file will be lost!</span><span class="strut"> </span></p> -<p id="t8" class="pln"><span class="strut"> </span></p> -<p id="t9" class="stm run hide_run"><span class="key">from</span> <span class="nam">PyQt5</span> <span class="key">import</span> <span class="nam">QtCore</span><span class="op">,</span> <span class="nam">QtGui</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="strut"> </span></p> -<p id="t10" class="pln"><span class="strut"> </span></p> -<p id="t11" class="stm run hide_run"><span class="key">class</span> <span class="nam">Ui_HecrasDialog</span><span class="op">(</span><span class="nam">object</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t12" class="stm run hide_run"> <span class="key">def</span> <span class="nam">setupUi</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">HecrasDialog</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t13" class="stm mis"> <span class="nam">HecrasDialog</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"HecrasDialog"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t14" class="stm mis"> <span class="nam">HecrasDialog</span><span class="op">.</span><span class="nam">resize</span><span class="op">(</span><span class="num">258</span><span class="op">,</span> <span class="num">295</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t15" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_2</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QVBoxLayout</span><span class="op">(</span><span class="nam">HecrasDialog</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t16" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_2</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"verticalLayout_2"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t17" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QVBoxLayout</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t18" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"verticalLayout"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t19" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QHBoxLayout</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t20" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"horizontalLayout"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t21" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_project</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QLabel</span><span class="op">(</span><span class="nam">HecrasDialog</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t22" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_project</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"label_project"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t23" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">label_project</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t24" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_project</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QLineEdit</span><span class="op">(</span><span class="nam">HecrasDialog</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t25" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_project</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"lineEdit_project"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t26" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_project</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t27" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">pushButton_browse</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QPushButton</span><span class="op">(</span><span class="nam">HecrasDialog</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t28" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">pushButton_browse</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"pushButton_browse"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t29" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">pushButton_browse</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t30" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout</span><span class="op">.</span><span class="nam">addLayout</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t31" class="stm mis"> <span class="nam">spacerItem</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSpacerItem</span><span class="op">(</span><span class="num">20</span><span class="op">,</span> <span class="num">40</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSizePolicy</span><span class="op">.</span><span class="nam">Minimum</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSizePolicy</span><span class="op">.</span><span class="nam">Expanding</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t32" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout</span><span class="op">.</span><span class="nam">addItem</span><span class="op">(</span><span class="nam">spacerItem</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t33" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_4</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QHBoxLayout</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t34" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_4</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"horizontalLayout_4"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t35" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_steady</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QRadioButton</span><span class="op">(</span><span class="nam">HecrasDialog</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t36" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_steady</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"radioButton_steady"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t37" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_4</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_steady</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t38" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_unsteady</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QRadioButton</span><span class="op">(</span><span class="nam">HecrasDialog</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t39" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_unsteady</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"radioButton_unsteady"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t40" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_4</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_unsteady</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t41" class="stm mis"> <span class="nam">spacerItem1</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSpacerItem</span><span class="op">(</span><span class="num">40</span><span class="op">,</span> <span class="num">20</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSizePolicy</span><span class="op">.</span><span class="nam">Expanding</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSizePolicy</span><span class="op">.</span><span class="nam">Minimum</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t42" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_4</span><span class="op">.</span><span class="nam">addItem</span><span class="op">(</span><span class="nam">spacerItem1</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t43" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout</span><span class="op">.</span><span class="nam">addLayout</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_4</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t44" class="stm mis"> <span class="nam">spacerItem2</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSpacerItem</span><span class="op">(</span><span class="num">20</span><span class="op">,</span> <span class="num">40</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSizePolicy</span><span class="op">.</span><span class="nam">Minimum</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSizePolicy</span><span class="op">.</span><span class="nam">Expanding</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t45" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout</span><span class="op">.</span><span class="nam">addItem</span><span class="op">(</span><span class="nam">spacerItem2</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t46" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_2</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QHBoxLayout</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t47" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_2</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"horizontalLayout_2"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t48" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_plan</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QLabel</span><span class="op">(</span><span class="nam">HecrasDialog</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t49" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_plan</span><span class="op">.</span><span class="nam">setMaximumSize</span><span class="op">(</span><span class="nam">QtCore</span><span class="op">.</span><span class="nam">QSize</span><span class="op">(</span><span class="num">60</span><span class="op">,</span> <span class="num">60</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t50" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_plan</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"label_plan"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t51" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_2</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">label_plan</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t52" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">comboBox_plan</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QComboBox</span><span class="op">(</span><span class="nam">HecrasDialog</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t53" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">comboBox_plan</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"comboBox_plan"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t54" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_2</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">comboBox_plan</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t55" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout</span><span class="op">.</span><span class="nam">addLayout</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_2</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t56" class="stm mis"> <span class="nam">spacerItem3</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSpacerItem</span><span class="op">(</span><span class="num">20</span><span class="op">,</span> <span class="num">40</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSizePolicy</span><span class="op">.</span><span class="nam">Minimum</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSizePolicy</span><span class="op">.</span><span class="nam">Expanding</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t57" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout</span><span class="op">.</span><span class="nam">addItem</span><span class="op">(</span><span class="nam">spacerItem3</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t58" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_3</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QHBoxLayout</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t59" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_3</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"horizontalLayout_3"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t60" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_profile</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QLabel</span><span class="op">(</span><span class="nam">HecrasDialog</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t61" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_profile</span><span class="op">.</span><span class="nam">setMaximumSize</span><span class="op">(</span><span class="nam">QtCore</span><span class="op">.</span><span class="nam">QSize</span><span class="op">(</span><span class="num">60</span><span class="op">,</span> <span class="num">60</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t62" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_profile</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"label_profile"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t63" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_3</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">label_profile</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t64" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">comboBox_profile</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QComboBox</span><span class="op">(</span><span class="nam">HecrasDialog</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t65" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">comboBox_profile</span><span class="op">.</span><span class="nam">setMaximumSize</span><span class="op">(</span><span class="nam">QtCore</span><span class="op">.</span><span class="nam">QSize</span><span class="op">(</span><span class="num">16777215</span><span class="op">,</span> <span class="num">16777215</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t66" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">comboBox_profile</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"comboBox_profile"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t67" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_3</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">comboBox_profile</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t68" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout</span><span class="op">.</span><span class="nam">addLayout</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_3</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t69" class="stm mis"> <span class="nam">spacerItem4</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSpacerItem</span><span class="op">(</span><span class="num">20</span><span class="op">,</span> <span class="num">40</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSizePolicy</span><span class="op">.</span><span class="nam">Minimum</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSizePolicy</span><span class="op">.</span><span class="nam">Expanding</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t70" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout</span><span class="op">.</span><span class="nam">addItem</span><span class="op">(</span><span class="nam">spacerItem4</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t71" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_5</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QHBoxLayout</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t72" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_5</span><span class="op">.</span><span class="nam">setSizeConstraint</span><span class="op">(</span><span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QLayout</span><span class="op">.</span><span class="nam">SetDefaultConstraint</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t73" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_5</span><span class="op">.</span><span class="nam">setContentsMargins</span><span class="op">(</span><span class="op">-</span><span class="num">1</span><span class="op">,</span> <span class="op">-</span><span class="num">1</span><span class="op">,</span> <span class="op">-</span><span class="num">1</span><span class="op">,</span> <span class="num">0</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t74" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_5</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"horizontalLayout_5"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t75" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_temperature</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QLabel</span><span class="op">(</span><span class="nam">HecrasDialog</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t76" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_temperature</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"label_temperature"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t77" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_5</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">label_temperature</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t78" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_temperature</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QLineEdit</span><span class="op">(</span><span class="nam">HecrasDialog</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t79" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_temperature</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"lineEdit_temperature"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t80" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_5</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">lineEdit_temperature</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t81" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout</span><span class="op">.</span><span class="nam">addLayout</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_5</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t82" class="stm mis"> <span class="nam">spacerItem5</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSpacerItem</span><span class="op">(</span><span class="num">20</span><span class="op">,</span> <span class="num">40</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSizePolicy</span><span class="op">.</span><span class="nam">Minimum</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSizePolicy</span><span class="op">.</span><span class="nam">Expanding</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t83" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout</span><span class="op">.</span><span class="nam">addItem</span><span class="op">(</span><span class="nam">spacerItem5</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t84" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_8</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QHBoxLayout</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t85" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_8</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"horizontalLayout_8"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t86" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_start_time</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QLabel</span><span class="op">(</span><span class="nam">HecrasDialog</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t87" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_start_time</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"label_start_time"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t88" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_8</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">label_start_time</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t89" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">dateTimeEdit_start_time</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QDateTimeEdit</span><span class="op">(</span><span class="nam">HecrasDialog</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t90" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">dateTimeEdit_start_time</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"dateTimeEdit_start_time"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t91" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_8</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">dateTimeEdit_start_time</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t92" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout</span><span class="op">.</span><span class="nam">addLayout</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_8</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t93" class="stm mis"> <span class="nam">spacerItem6</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSpacerItem</span><span class="op">(</span><span class="num">20</span><span class="op">,</span> <span class="num">40</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSizePolicy</span><span class="op">.</span><span class="nam">Minimum</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSizePolicy</span><span class="op">.</span><span class="nam">Expanding</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t94" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout</span><span class="op">.</span><span class="nam">addItem</span><span class="op">(</span><span class="nam">spacerItem6</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t95" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_6</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QHBoxLayout</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t96" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_6</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"horizontalLayout_6"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t97" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">pushButton_cancel</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QPushButton</span><span class="op">(</span><span class="nam">HecrasDialog</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t98" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">pushButton_cancel</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"pushButton_cancel"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t99" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_6</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">pushButton_cancel</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t100" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">pushButton_ok</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QPushButton</span><span class="op">(</span><span class="nam">HecrasDialog</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t101" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">pushButton_ok</span><span class="op">.</span><span class="nam">setObjectName</span><span class="op">(</span><span class="str">"pushButton_ok"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t102" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_6</span><span class="op">.</span><span class="nam">addWidget</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">pushButton_ok</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t103" class="stm mis"> <span class="nam">spacerItem7</span> <span class="op">=</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSpacerItem</span><span class="op">(</span><span class="num">40</span><span class="op">,</span> <span class="num">20</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSizePolicy</span><span class="op">.</span><span class="nam">Expanding</span><span class="op">,</span> <span class="nam">QtWidgets</span><span class="op">.</span><span class="nam">QSizePolicy</span><span class="op">.</span><span class="nam">Minimum</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t104" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_6</span><span class="op">.</span><span class="nam">addItem</span><span class="op">(</span><span class="nam">spacerItem7</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t105" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout</span><span class="op">.</span><span class="nam">addLayout</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">horizontalLayout_6</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t106" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout_2</span><span class="op">.</span><span class="nam">addLayout</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">verticalLayout</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t107" class="pln"><span class="strut"> </span></p> -<p id="t108" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">retranslateUi</span><span class="op">(</span><span class="nam">HecrasDialog</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t109" class="stm mis"> <span class="nam">QtCore</span><span class="op">.</span><span class="nam">QMetaObject</span><span class="op">.</span><span class="nam">connectSlotsByName</span><span class="op">(</span><span class="nam">HecrasDialog</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t110" class="pln"><span class="strut"> </span></p> -<p id="t111" class="stm run hide_run"> <span class="key">def</span> <span class="nam">retranslateUi</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">HecrasDialog</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t112" class="stm mis"> <span class="nam">_translate</span> <span class="op">=</span> <span class="nam">QtCore</span><span class="op">.</span><span class="nam">QCoreApplication</span><span class="op">.</span><span class="nam">translate</span><span class="strut"> </span></p> -<p id="t113" class="stm mis"> <span class="nam">HecrasDialog</span><span class="op">.</span><span class="nam">setWindowTitle</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"HecrasDialog"</span><span class="op">,</span> <span class="str">"Dialog"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t114" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_project</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"HecrasDialog"</span><span class="op">,</span> <span class="str">"Project"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t115" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">pushButton_browse</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"HecrasDialog"</span><span class="op">,</span> <span class="str">"Browse"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t116" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_steady</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"HecrasDialog"</span><span class="op">,</span> <span class="str">"Steady"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t117" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">radioButton_unsteady</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"HecrasDialog"</span><span class="op">,</span> <span class="str">"Unsteady"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t118" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_plan</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"HecrasDialog"</span><span class="op">,</span> <span class="str">"Plan"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t119" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_profile</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"HecrasDialog"</span><span class="op">,</span> <span class="str">"Profile"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t120" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_temperature</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"HecrasDialog"</span><span class="op">,</span> <span class="str">"Temperature (C)"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t121" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">label_start_time</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"HecrasDialog"</span><span class="op">,</span> <span class="str">"Start Time"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t122" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">pushButton_cancel</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"HecrasDialog"</span><span class="op">,</span> <span class="str">"Cancel"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t123" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">pushButton_ok</span><span class="op">.</span><span class="nam">setText</span><span class="op">(</span><span class="nam">_translate</span><span class="op">(</span><span class="str">"HecrasDialog"</span><span class="op">,</span> <span class="str">"Ok"</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t124" class="pln"><span class="strut"> </span></p> - - </td> - </tr> - </table> -</div> - -<div id="footer"> - <div class="content"> - <p> - <a class="nav" href="index.html">« index</a> <a class="nav" href="https://coverage.readthedocs.io">coverage.py v4.5.3</a>, - created at 2019-07-09 15:15 - </p> - </div> -</div> - -</body> -</html> diff --git a/coverage_report/fluegg_hydraulics_py.html b/coverage_report/fluegg_hydraulics_py.html deleted file mode 100644 index 39d8387..0000000 --- a/coverage_report/fluegg_hydraulics_py.html +++ /dev/null @@ -1,1883 +0,0 @@ - - - -<!DOCTYPE html> -<html> -<head> - <meta http-equiv="Content-Type" content="text/html; charset=utf-8"> - - - <meta http-equiv="X-UA-Compatible" content="IE=emulateIE7" /> - <title>Coverage for fluegg\hydraulics.py: 87%</title> - <link rel="stylesheet" href="style.css" type="text/css"> - - <script type="text/javascript" src="jquery.min.js"></script> - <script type="text/javascript" src="jquery.hotkeys.js"></script> - <script type="text/javascript" src="jquery.isonscreen.js"></script> - <script type="text/javascript" src="coverage_html.js"></script> - <script type="text/javascript"> - jQuery(document).ready(coverage.pyfile_ready); - </script> -</head> -<body class="pyfile"> - -<div id="header"> - <div class="content"> - <h1>Coverage for <b>fluegg\hydraulics.py</b> : - <span class="pc_cov">87%</span> - </h1> - - <img id="keyboard_icon" src="keybd_closed.png" alt="Show keyboard shortcuts" /> - - <h2 class="stats"> - 287 statements - <span class="run hide_run shortkey_r button_toggle_run">250 run</span> - <span class="mis shortkey_m button_toggle_mis">37 missing</span> - <span class="exc shortkey_x button_toggle_exc">0 excluded</span> - - - </h2> - </div> -</div> - -<div class="help_panel"> - <img id="panel_icon" src="keybd_open.png" alt="Hide keyboard shortcuts" /> - <p class="legend">Hot-keys on this page</p> - <div> - <p class="keyhelp"> - <span class="key">r</span> - <span class="key">m</span> - <span class="key">x</span> - <span class="key">p</span> toggle line displays - </p> - <p class="keyhelp"> - <span class="key">j</span> - <span class="key">k</span> next/prev highlighted chunk - </p> - <p class="keyhelp"> - <span class="key">0</span> (zero) top of page - </p> - <p class="keyhelp"> - <span class="key">1</span> (one) first highlighted chunk - </p> - </div> -</div> - -<div id="source"> - <table> - <tr> - <td class="linenos"> -<p id="n1" class="stm run hide_run"><a href="#n1">1</a></p> -<p id="n2" class="stm run hide_run"><a href="#n2">2</a></p> -<p id="n3" class="pln"><a href="#n3">3</a></p> -<p id="n4" class="stm run hide_run"><a href="#n4">4</a></p> -<p id="n5" class="stm run hide_run"><a href="#n5">5</a></p> -<p id="n6" class="stm run hide_run"><a href="#n6">6</a></p> 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href="#n286">286</a></p> -<p id="n287" class="stm run hide_run"><a href="#n287">287</a></p> -<p id="n288" class="stm run hide_run"><a href="#n288">288</a></p> -<p id="n289" class="stm run hide_run"><a href="#n289">289</a></p> -<p id="n290" class="stm run hide_run"><a href="#n290">290</a></p> -<p id="n291" class="stm run hide_run"><a href="#n291">291</a></p> -<p id="n292" class="stm run hide_run"><a href="#n292">292</a></p> -<p id="n293" class="pln"><a href="#n293">293</a></p> -<p id="n294" class="stm run hide_run"><a href="#n294">294</a></p> -<p id="n295" class="stm run hide_run"><a href="#n295">295</a></p> -<p id="n296" class="pln"><a href="#n296">296</a></p> -<p id="n297" class="stm run hide_run"><a href="#n297">297</a></p> -<p id="n298" class="pln"><a href="#n298">298</a></p> -<p id="n299" class="stm run hide_run"><a href="#n299">299</a></p> -<p id="n300" class="stm run hide_run"><a href="#n300">300</a></p> -<p id="n301" class="pln"><a href="#n301">301</a></p> -<p id="n302" class="stm run hide_run"><a href="#n302">302</a></p> -<p id="n303" class="pln"><a href="#n303">303</a></p> -<p id="n304" class="stm run hide_run"><a href="#n304">304</a></p> -<p id="n305" class="pln"><a href="#n305">305</a></p> -<p id="n306" class="stm run hide_run"><a href="#n306">306</a></p> -<p id="n307" class="pln"><a href="#n307">307</a></p> -<p id="n308" class="stm run hide_run"><a href="#n308">308</a></p> -<p id="n309" class="stm run hide_run"><a href="#n309">309</a></p> -<p id="n310" class="pln"><a href="#n310">310</a></p> -<p id="n311" class="pln"><a href="#n311">311</a></p> -<p id="n312" class="pln"><a href="#n312">312</a></p> -<p id="n313" class="stm run hide_run"><a href="#n313">313</a></p> -<p id="n314" class="pln"><a href="#n314">314</a></p> -<p id="n315" class="stm run hide_run"><a href="#n315">315</a></p> -<p id="n316" class="pln"><a href="#n316">316</a></p> -<p id="n317" class="pln"><a href="#n317">317</a></p> -<p id="n318" class="stm run hide_run"><a href="#n318">318</a></p> -<p id="n319" class="pln"><a href="#n319">319</a></p> -<p id="n320" class="pln"><a href="#n320">320</a></p> -<p id="n321" class="pln"><a href="#n321">321</a></p> -<p id="n322" class="pln"><a href="#n322">322</a></p> -<p id="n323" class="pln"><a href="#n323">323</a></p> -<p id="n324" class="pln"><a href="#n324">324</a></p> -<p id="n325" class="pln"><a href="#n325">325</a></p> -<p id="n326" class="pln"><a href="#n326">326</a></p> -<p id="n327" class="pln"><a href="#n327">327</a></p> -<p id="n328" class="stm mis"><a href="#n328">328</a></p> -<p id="n329" class="pln"><a href="#n329">329</a></p> -<p id="n330" class="pln"><a href="#n330">330</a></p> -<p id="n331" class="stm run hide_run"><a href="#n331">331</a></p> -<p id="n332" class="pln"><a href="#n332">332</a></p> -<p id="n333" class="pln"><a href="#n333">333</a></p> -<p id="n334" class="pln"><a href="#n334">334</a></p> -<p id="n335" class="pln"><a href="#n335">335</a></p> -<p id="n336" class="pln"><a href="#n336">336</a></p> -<p id="n337" class="pln"><a href="#n337">337</a></p> -<p id="n338" class="pln"><a href="#n338">338</a></p> -<p id="n339" class="pln"><a href="#n339">339</a></p> -<p id="n340" class="pln"><a href="#n340">340</a></p> -<p id="n341" class="pln"><a href="#n341">341</a></p> -<p id="n342" class="pln"><a href="#n342">342</a></p> -<p id="n343" class="pln"><a href="#n343">343</a></p> -<p id="n344" class="stm run hide_run"><a href="#n344">344</a></p> -<p id="n345" class="pln"><a href="#n345">345</a></p> -<p id="n346" class="pln"><a href="#n346">346</a></p> -<p id="n347" class="stm run hide_run"><a href="#n347">347</a></p> -<p id="n348" class="pln"><a href="#n348">348</a></p> -<p id="n349" class="stm run hide_run"><a href="#n349">349</a></p> -<p id="n350" class="pln"><a href="#n350">350</a></p> -<p id="n351" class="stm run hide_run"><a href="#n351">351</a></p> -<p id="n352" class="pln"><a href="#n352">352</a></p> -<p id="n353" class="pln"><a href="#n353">353</a></p> -<p id="n354" class="stm run hide_run"><a href="#n354">354</a></p> -<p id="n355" class="stm run hide_run"><a href="#n355">355</a></p> -<p id="n356" class="pln"><a href="#n356">356</a></p> -<p id="n357" class="stm run hide_run"><a href="#n357">357</a></p> -<p id="n358" class="pln"><a href="#n358">358</a></p> -<p id="n359" class="stm run hide_run"><a href="#n359">359</a></p> -<p id="n360" class="stm run hide_run"><a href="#n360">360</a></p> -<p id="n361" class="stm run hide_run"><a href="#n361">361</a></p> -<p id="n362" class="pln"><a href="#n362">362</a></p> -<p id="n363" class="stm run hide_run"><a href="#n363">363</a></p> -<p id="n364" class="pln"><a href="#n364">364</a></p> -<p id="n365" class="stm run hide_run"><a href="#n365">365</a></p> -<p id="n366" class="pln"><a href="#n366">366</a></p> -<p id="n367" class="pln"><a href="#n367">367</a></p> -<p id="n368" class="stm mis"><a href="#n368">368</a></p> -<p id="n369" class="pln"><a href="#n369">369</a></p> -<p id="n370" class="stm run hide_run"><a href="#n370">370</a></p> -<p id="n371" class="pln"><a href="#n371">371</a></p> -<p id="n372" class="pln"><a href="#n372">372</a></p> -<p id="n373" class="pln"><a href="#n373">373</a></p> -<p id="n374" class="stm run hide_run"><a href="#n374">374</a></p> -<p id="n375" class="pln"><a href="#n375">375</a></p> -<p id="n376" class="stm run hide_run"><a href="#n376">376</a></p> -<p id="n377" class="stm run hide_run"><a href="#n377">377</a></p> -<p id="n378" class="pln"><a href="#n378">378</a></p> -<p id="n379" class="pln"><a href="#n379">379</a></p> -<p id="n380" class="stm run hide_run"><a href="#n380">380</a></p> -<p id="n381" class="pln"><a href="#n381">381</a></p> -<p id="n382" class="pln"><a href="#n382">382</a></p> -<p id="n383" class="pln"><a href="#n383">383</a></p> -<p id="n384" class="pln"><a href="#n384">384</a></p> -<p id="n385" class="pln"><a href="#n385">385</a></p> -<p id="n386" class="stm run hide_run"><a href="#n386">386</a></p> -<p id="n387" class="pln"><a href="#n387">387</a></p> -<p id="n388" class="stm run hide_run"><a href="#n388">388</a></p> -<p id="n389" class="stm run hide_run"><a href="#n389">389</a></p> -<p id="n390" class="pln"><a href="#n390">390</a></p> -<p id="n391" class="stm run hide_run"><a href="#n391">391</a></p> -<p id="n392" class="pln"><a href="#n392">392</a></p> -<p id="n393" class="pln"><a href="#n393">393</a></p> -<p id="n394" class="stm run hide_run"><a href="#n394">394</a></p> -<p id="n395" class="pln"><a href="#n395">395</a></p> -<p id="n396" class="stm run hide_run"><a href="#n396">396</a></p> -<p id="n397" class="pln"><a href="#n397">397</a></p> -<p id="n398" class="pln"><a href="#n398">398</a></p> -<p id="n399" class="stm run hide_run"><a href="#n399">399</a></p> -<p id="n400" class="pln"><a href="#n400">400</a></p> -<p id="n401" class="pln"><a href="#n401">401</a></p> -<p id="n402" class="pln"><a href="#n402">402</a></p> -<p id="n403" class="stm run hide_run"><a href="#n403">403</a></p> -<p id="n404" class="pln"><a href="#n404">404</a></p> -<p id="n405" class="stm run hide_run"><a href="#n405">405</a></p> -<p id="n406" class="pln"><a href="#n406">406</a></p> -<p id="n407" class="stm run hide_run"><a href="#n407">407</a></p> -<p id="n408" class="pln"><a href="#n408">408</a></p> -<p id="n409" class="pln"><a href="#n409">409</a></p> -<p id="n410" class="pln"><a href="#n410">410</a></p> -<p id="n411" class="stm run hide_run"><a href="#n411">411</a></p> -<p id="n412" class="stm run hide_run"><a href="#n412">412</a></p> -<p id="n413" class="stm run hide_run"><a href="#n413">413</a></p> -<p id="n414" class="stm run hide_run"><a href="#n414">414</a></p> -<p id="n415" class="pln"><a href="#n415">415</a></p> -<p id="n416" class="stm run hide_run"><a href="#n416">416</a></p> -<p id="n417" class="stm run hide_run"><a href="#n417">417</a></p> -<p id="n418" class="pln"><a href="#n418">418</a></p> -<p id="n419" class="stm run hide_run"><a href="#n419">419</a></p> -<p id="n420" class="pln"><a href="#n420">420</a></p> -<p id="n421" class="stm run hide_run"><a href="#n421">421</a></p> -<p id="n422" class="pln"><a href="#n422">422</a></p> -<p id="n423" class="pln"><a href="#n423">423</a></p> -<p id="n424" class="stm run hide_run"><a href="#n424">424</a></p> -<p id="n425" class="stm run hide_run"><a href="#n425">425</a></p> -<p id="n426" class="pln"><a href="#n426">426</a></p> -<p id="n427" class="stm run hide_run"><a href="#n427">427</a></p> -<p id="n428" class="pln"><a href="#n428">428</a></p> -<p id="n429" class="stm run hide_run"><a href="#n429">429</a></p> -<p id="n430" class="stm run hide_run"><a href="#n430">430</a></p> -<p id="n431" class="pln"><a href="#n431">431</a></p> -<p id="n432" class="stm run hide_run"><a href="#n432">432</a></p> -<p id="n433" class="stm run hide_run"><a href="#n433">433</a></p> -<p id="n434" class="stm run hide_run"><a href="#n434">434</a></p> -<p id="n435" class="stm run hide_run"><a href="#n435">435</a></p> -<p id="n436" class="stm run hide_run"><a href="#n436">436</a></p> -<p id="n437" class="stm run hide_run"><a href="#n437">437</a></p> -<p id="n438" class="stm run hide_run"><a href="#n438">438</a></p> -<p id="n439" class="pln"><a href="#n439">439</a></p> -<p id="n440" class="stm run hide_run"><a href="#n440">440</a></p> -<p id="n441" class="pln"><a href="#n441">441</a></p> -<p id="n442" class="pln"><a href="#n442">442</a></p> -<p id="n443" class="pln"><a href="#n443">443</a></p> -<p id="n444" class="pln"><a href="#n444">444</a></p> -<p id="n445" class="pln"><a href="#n445">445</a></p> -<p id="n446" class="pln"><a href="#n446">446</a></p> -<p id="n447" class="pln"><a href="#n447">447</a></p> -<p id="n448" class="stm run hide_run"><a href="#n448">448</a></p> -<p id="n449" class="pln"><a href="#n449">449</a></p> -<p id="n450" class="stm run hide_run"><a href="#n450">450</a></p> -<p id="n451" class="pln"><a href="#n451">451</a></p> -<p id="n452" class="stm run hide_run"><a href="#n452">452</a></p> -<p id="n453" class="pln"><a href="#n453">453</a></p> -<p id="n454" class="pln"><a href="#n454">454</a></p> -<p id="n455" class="pln"><a href="#n455">455</a></p> -<p id="n456" class="pln"><a href="#n456">456</a></p> -<p id="n457" class="stm run hide_run"><a href="#n457">457</a></p> -<p id="n458" class="stm run hide_run"><a href="#n458">458</a></p> -<p id="n459" class="stm run hide_run"><a href="#n459">459</a></p> -<p id="n460" class="pln"><a href="#n460">460</a></p> -<p id="n461" class="pln"><a href="#n461">461</a></p> -<p id="n462" class="stm run hide_run"><a href="#n462">462</a></p> -<p id="n463" class="stm run hide_run"><a href="#n463">463</a></p> -<p id="n464" class="stm run hide_run"><a href="#n464">464</a></p> -<p id="n465" class="stm run hide_run"><a href="#n465">465</a></p> -<p id="n466" class="stm run hide_run"><a href="#n466">466</a></p> -<p id="n467" class="pln"><a href="#n467">467</a></p> -<p id="n468" class="stm run hide_run"><a href="#n468">468</a></p> -<p id="n469" class="pln"><a href="#n469">469</a></p> -<p id="n470" class="stm run hide_run"><a href="#n470">470</a></p> -<p id="n471" class="pln"><a href="#n471">471</a></p> -<p id="n472" class="stm run hide_run"><a href="#n472">472</a></p> -<p id="n473" class="stm run hide_run"><a href="#n473">473</a></p> -<p id="n474" class="pln"><a href="#n474">474</a></p> -<p id="n475" class="pln"><a href="#n475">475</a></p> -<p id="n476" class="stm run hide_run"><a href="#n476">476</a></p> -<p id="n477" class="pln"><a href="#n477">477</a></p> -<p id="n478" class="stm run hide_run"><a href="#n478">478</a></p> -<p id="n479" class="pln"><a href="#n479">479</a></p> -<p id="n480" class="stm run hide_run"><a href="#n480">480</a></p> -<p id="n481" class="stm run hide_run"><a href="#n481">481</a></p> -<p id="n482" class="stm run hide_run"><a href="#n482">482</a></p> -<p id="n483" class="pln"><a href="#n483">483</a></p> -<p id="n484" class="pln"><a href="#n484">484</a></p> -<p id="n485" class="pln"><a href="#n485">485</a></p> -<p id="n486" class="pln"><a href="#n486">486</a></p> -<p id="n487" class="stm run hide_run"><a href="#n487">487</a></p> -<p id="n488" class="pln"><a href="#n488">488</a></p> -<p id="n489" class="stm run hide_run"><a href="#n489">489</a></p> -<p id="n490" class="pln"><a href="#n490">490</a></p> -<p id="n491" class="stm run hide_run"><a href="#n491">491</a></p> -<p id="n492" class="pln"><a href="#n492">492</a></p> -<p id="n493" class="pln"><a href="#n493">493</a></p> -<p id="n494" class="pln"><a href="#n494">494</a></p> -<p id="n495" class="pln"><a href="#n495">495</a></p> -<p id="n496" class="pln"><a href="#n496">496</a></p> -<p id="n497" class="pln"><a href="#n497">497</a></p> -<p id="n498" class="pln"><a href="#n498">498</a></p> -<p id="n499" class="pln"><a href="#n499">499</a></p> -<p id="n500" class="pln"><a href="#n500">500</a></p> -<p id="n501" class="pln"><a href="#n501">501</a></p> -<p id="n502" class="pln"><a href="#n502">502</a></p> -<p id="n503" class="pln"><a href="#n503">503</a></p> -<p id="n504" class="pln"><a href="#n504">504</a></p> -<p id="n505" class="pln"><a href="#n505">505</a></p> -<p id="n506" class="pln"><a href="#n506">506</a></p> -<p id="n507" class="pln"><a href="#n507">507</a></p> -<p id="n508" class="pln"><a href="#n508">508</a></p> -<p id="n509" class="pln"><a href="#n509">509</a></p> -<p id="n510" class="pln"><a href="#n510">510</a></p> -<p id="n511" class="pln"><a href="#n511">511</a></p> -<p id="n512" class="pln"><a href="#n512">512</a></p> -<p id="n513" class="pln"><a href="#n513">513</a></p> -<p id="n514" class="pln"><a href="#n514">514</a></p> -<p id="n515" class="pln"><a href="#n515">515</a></p> -<p id="n516" class="pln"><a href="#n516">516</a></p> -<p id="n517" class="pln"><a href="#n517">517</a></p> -<p id="n518" class="pln"><a href="#n518">518</a></p> -<p id="n519" class="pln"><a href="#n519">519</a></p> -<p id="n520" class="pln"><a href="#n520">520</a></p> -<p id="n521" class="pln"><a href="#n521">521</a></p> -<p id="n522" class="pln"><a href="#n522">522</a></p> -<p id="n523" class="pln"><a href="#n523">523</a></p> -<p id="n524" class="pln"><a href="#n524">524</a></p> -<p id="n525" class="pln"><a href="#n525">525</a></p> -<p id="n526" class="pln"><a href="#n526">526</a></p> -<p id="n527" class="pln"><a href="#n527">527</a></p> -<p id="n528" class="pln"><a href="#n528">528</a></p> -<p id="n529" class="pln"><a href="#n529">529</a></p> -<p id="n530" class="stm run hide_run"><a href="#n530">530</a></p> -<p id="n531" class="stm run hide_run"><a href="#n531">531</a></p> -<p id="n532" class="stm run hide_run"><a href="#n532">532</a></p> -<p id="n533" class="stm run hide_run"><a href="#n533">533</a></p> -<p id="n534" class="pln"><a href="#n534">534</a></p> -<p id="n535" class="stm mis"><a href="#n535">535</a></p> -<p id="n536" class="pln"><a href="#n536">536</a></p> -<p id="n537" class="stm run hide_run"><a href="#n537">537</a></p> -<p id="n538" class="pln"><a href="#n538">538</a></p> -<p id="n539" class="stm run hide_run"><a href="#n539">539</a></p> -<p id="n540" class="pln"><a href="#n540">540</a></p> -<p id="n541" class="pln"><a href="#n541">541</a></p> -<p id="n542" class="pln"><a href="#n542">542</a></p> -<p id="n543" class="pln"><a href="#n543">543</a></p> -<p id="n544" class="pln"><a href="#n544">544</a></p> -<p id="n545" class="pln"><a href="#n545">545</a></p> -<p id="n546" class="pln"><a href="#n546">546</a></p> -<p id="n547" class="pln"><a href="#n547">547</a></p> -<p id="n548" class="pln"><a href="#n548">548</a></p> -<p id="n549" class="pln"><a href="#n549">549</a></p> -<p id="n550" class="pln"><a href="#n550">550</a></p> -<p id="n551" class="pln"><a href="#n551">551</a></p> -<p id="n552" class="pln"><a href="#n552">552</a></p> -<p id="n553" class="pln"><a href="#n553">553</a></p> -<p id="n554" class="pln"><a href="#n554">554</a></p> -<p id="n555" class="pln"><a href="#n555">555</a></p> -<p id="n556" class="pln"><a href="#n556">556</a></p> -<p id="n557" class="pln"><a href="#n557">557</a></p> -<p id="n558" class="pln"><a href="#n558">558</a></p> -<p id="n559" class="pln"><a href="#n559">559</a></p> -<p id="n560" class="pln"><a href="#n560">560</a></p> -<p id="n561" class="pln"><a href="#n561">561</a></p> -<p id="n562" class="pln"><a href="#n562">562</a></p> -<p id="n563" class="pln"><a href="#n563">563</a></p> -<p id="n564" class="pln"><a href="#n564">564</a></p> -<p id="n565" class="stm run hide_run"><a href="#n565">565</a></p> -<p id="n566" class="pln"><a href="#n566">566</a></p> -<p id="n567" class="stm run hide_run"><a href="#n567">567</a></p> -<p id="n568" class="stm run hide_run"><a href="#n568">568</a></p> -<p id="n569" class="pln"><a href="#n569">569</a></p> -<p id="n570" class="stm run hide_run"><a href="#n570">570</a></p> -<p id="n571" class="pln"><a href="#n571">571</a></p> -<p id="n572" class="stm run hide_run"><a href="#n572">572</a></p> -<p id="n573" class="pln"><a href="#n573">573</a></p> -<p id="n574" class="stm run hide_run"><a href="#n574">574</a></p> -<p id="n575" class="pln"><a href="#n575">575</a></p> -<p id="n576" class="stm run hide_run"><a href="#n576">576</a></p> -<p id="n577" class="pln"><a href="#n577">577</a></p> -<p id="n578" class="stm run hide_run"><a href="#n578">578</a></p> -<p id="n579" class="pln"><a href="#n579">579</a></p> -<p id="n580" class="stm run hide_run"><a href="#n580">580</a></p> -<p id="n581" class="pln"><a href="#n581">581</a></p> -<p id="n582" class="pln"><a href="#n582">582</a></p> -<p id="n583" class="stm run hide_run"><a href="#n583">583</a></p> -<p id="n584" class="stm run hide_run"><a href="#n584">584</a></p> -<p id="n585" class="pln"><a href="#n585">585</a></p> -<p id="n586" class="stm run hide_run"><a href="#n586">586</a></p> -<p id="n587" class="stm run hide_run"><a href="#n587">587</a></p> -<p id="n588" class="pln"><a href="#n588">588</a></p> -<p id="n589" class="stm run hide_run"><a href="#n589">589</a></p> -<p id="n590" class="stm run hide_run"><a href="#n590">590</a></p> -<p id="n591" class="stm run hide_run"><a href="#n591">591</a></p> -<p id="n592" class="pln"><a href="#n592">592</a></p> -<p id="n593" class="pln"><a href="#n593">593</a></p> -<p id="n594" class="pln"><a href="#n594">594</a></p> -<p id="n595" class="pln"><a href="#n595">595</a></p> -<p id="n596" class="pln"><a href="#n596">596</a></p> -<p id="n597" class="pln"><a href="#n597">597</a></p> -<p id="n598" class="stm run hide_run"><a href="#n598">598</a></p> -<p id="n599" class="stm run hide_run"><a href="#n599">599</a></p> -<p id="n600" class="pln"><a href="#n600">600</a></p> -<p id="n601" class="stm run hide_run"><a href="#n601">601</a></p> -<p id="n602" class="pln"><a href="#n602">602</a></p> -<p id="n603" class="pln"><a href="#n603">603</a></p> -<p id="n604" class="pln"><a href="#n604">604</a></p> -<p id="n605" class="pln"><a href="#n605">605</a></p> -<p id="n606" class="pln"><a href="#n606">606</a></p> -<p id="n607" class="stm run hide_run"><a href="#n607">607</a></p> -<p id="n608" class="pln"><a href="#n608">608</a></p> -<p id="n609" class="stm run hide_run"><a href="#n609">609</a></p> -<p id="n610" class="pln"><a href="#n610">610</a></p> -<p id="n611" class="pln"><a href="#n611">611</a></p> -<p id="n612" class="pln"><a href="#n612">612</a></p> -<p id="n613" class="pln"><a href="#n613">613</a></p> -<p id="n614" class="pln"><a href="#n614">614</a></p> -<p id="n615" class="pln"><a href="#n615">615</a></p> -<p id="n616" class="pln"><a href="#n616">616</a></p> -<p id="n617" class="stm mis"><a href="#n617">617</a></p> -<p id="n618" class="pln"><a href="#n618">618</a></p> -<p id="n619" class="stm mis"><a href="#n619">619</a></p> -<p id="n620" class="pln"><a href="#n620">620</a></p> -<p id="n621" class="pln"><a href="#n621">621</a></p> -<p id="n622" class="stm mis"><a href="#n622">622</a></p> -<p id="n623" class="pln"><a href="#n623">623</a></p> -<p id="n624" class="stm mis"><a href="#n624">624</a></p> -<p id="n625" class="pln"><a href="#n625">625</a></p> -<p id="n626" class="stm mis"><a href="#n626">626</a></p> -<p id="n627" class="stm mis"><a href="#n627">627</a></p> -<p id="n628" class="stm mis"><a href="#n628">628</a></p> -<p id="n629" class="stm mis"><a href="#n629">629</a></p> -<p id="n630" class="stm mis"><a href="#n630">630</a></p> -<p id="n631" class="stm mis"><a href="#n631">631</a></p> -<p id="n632" class="stm mis"><a href="#n632">632</a></p> -<p id="n633" class="stm mis"><a href="#n633">633</a></p> -<p id="n634" class="pln"><a href="#n634">634</a></p> -<p id="n635" class="stm mis"><a href="#n635">635</a></p> -<p id="n636" class="stm mis"><a href="#n636">636</a></p> -<p id="n637" class="stm mis"><a href="#n637">637</a></p> -<p id="n638" class="pln"><a href="#n638">638</a></p> -<p id="n639" class="stm mis"><a href="#n639">639</a></p> -<p id="n640" class="pln"><a href="#n640">640</a></p> -<p id="n641" class="stm mis"><a href="#n641">641</a></p> -<p id="n642" class="pln"><a href="#n642">642</a></p> -<p id="n643" class="stm mis"><a href="#n643">643</a></p> -<p id="n644" class="stm mis"><a href="#n644">644</a></p> -<p id="n645" class="pln"><a href="#n645">645</a></p> -<p id="n646" class="pln"><a href="#n646">646</a></p> -<p id="n647" class="pln"><a href="#n647">647</a></p> -<p id="n648" class="pln"><a href="#n648">648</a></p> -<p id="n649" class="pln"><a href="#n649">649</a></p> -<p id="n650" class="stm mis"><a href="#n650">650</a></p> -<p id="n651" class="pln"><a href="#n651">651</a></p> -<p id="n652" class="stm mis"><a href="#n652">652</a></p> -<p id="n653" class="pln"><a href="#n653">653</a></p> -<p id="n654" class="stm run hide_run"><a href="#n654">654</a></p> -<p id="n655" class="pln"><a href="#n655">655</a></p> -<p id="n656" class="pln"><a href="#n656">656</a></p> -<p id="n657" class="pln"><a href="#n657">657</a></p> -<p id="n658" class="pln"><a href="#n658">658</a></p> -<p id="n659" class="stm mis"><a href="#n659">659</a></p> -<p id="n660" class="pln"><a href="#n660">660</a></p> -<p id="n661" class="pln"><a href="#n661">661</a></p> -<p id="n662" class="stm run hide_run"><a href="#n662">662</a></p> -<p id="n663" class="pln"><a href="#n663">663</a></p> -<p id="n664" class="pln"><a href="#n664">664</a></p> -<p id="n665" class="pln"><a href="#n665">665</a></p> -<p id="n666" class="pln"><a href="#n666">666</a></p> -<p id="n667" class="pln"><a href="#n667">667</a></p> -<p id="n668" class="pln"><a href="#n668">668</a></p> -<p id="n669" class="pln"><a href="#n669">669</a></p> -<p id="n670" class="pln"><a href="#n670">670</a></p> -<p id="n671" class="pln"><a href="#n671">671</a></p> -<p id="n672" class="pln"><a href="#n672">672</a></p> -<p id="n673" class="pln"><a href="#n673">673</a></p> -<p id="n674" class="stm run hide_run"><a href="#n674">674</a></p> -<p id="n675" class="pln"><a href="#n675">675</a></p> -<p id="n676" class="pln"><a href="#n676">676</a></p> -<p id="n677" class="pln"><a href="#n677">677</a></p> -<p id="n678" class="pln"><a href="#n678">678</a></p> -<p id="n679" class="pln"><a href="#n679">679</a></p> -<p id="n680" class="pln"><a href="#n680">680</a></p> -<p id="n681" class="pln"><a href="#n681">681</a></p> -<p id="n682" class="pln"><a href="#n682">682</a></p> -<p id="n683" class="pln"><a href="#n683">683</a></p> -<p id="n684" class="stm run hide_run"><a href="#n684">684</a></p> -<p id="n685" class="pln"><a href="#n685">685</a></p> -<p id="n686" class="pln"><a href="#n686">686</a></p> -<p id="n687" class="stm run hide_run"><a href="#n687">687</a></p> -<p id="n688" class="pln"><a href="#n688">688</a></p> -<p id="n689" class="pln"><a href="#n689">689</a></p> -<p id="n690" class="stm run hide_run"><a href="#n690">690</a></p> -<p id="n691" class="pln"><a href="#n691">691</a></p> -<p id="n692" class="pln"><a href="#n692">692</a></p> -<p id="n693" class="stm run hide_run"><a href="#n693">693</a></p> -<p id="n694" class="pln"><a href="#n694">694</a></p> -<p id="n695" class="pln"><a href="#n695">695</a></p> -<p id="n696" class="pln"><a href="#n696">696</a></p> -<p id="n697" class="pln"><a href="#n697">697</a></p> -<p id="n698" class="stm run hide_run"><a href="#n698">698</a></p> -<p id="n699" class="pln"><a href="#n699">699</a></p> -<p id="n700" class="pln"><a href="#n700">700</a></p> -<p id="n701" class="stm run hide_run"><a href="#n701">701</a></p> -<p id="n702" class="pln"><a href="#n702">702</a></p> -<p id="n703" class="pln"><a href="#n703">703</a></p> -<p id="n704" class="pln"><a href="#n704">704</a></p> -<p id="n705" class="pln"><a href="#n705">705</a></p> -<p id="n706" class="stm run hide_run"><a href="#n706">706</a></p> -<p id="n707" class="stm mis"><a href="#n707">707</a></p> -<p id="n708" class="pln"><a href="#n708">708</a></p> -<p id="n709" class="pln"><a href="#n709">709</a></p> -<p id="n710" class="stm run hide_run"><a href="#n710">710</a></p> -<p id="n711" class="pln"><a href="#n711">711</a></p> -<p id="n712" class="pln"><a href="#n712">712</a></p> -<p id="n713" class="stm mis"><a href="#n713">713</a></p> -<p id="n714" class="pln"><a href="#n714">714</a></p> -<p id="n715" class="pln"><a href="#n715">715</a></p> -<p id="n716" class="pln"><a href="#n716">716</a></p> -<p id="n717" class="pln"><a href="#n717">717</a></p> -<p id="n718" class="stm mis"><a href="#n718">718</a></p> -<p id="n719" class="pln"><a href="#n719">719</a></p> -<p id="n720" class="pln"><a href="#n720">720</a></p> -<p id="n721" class="stm run hide_run"><a href="#n721">721</a></p> -<p id="n722" class="pln"><a href="#n722">722</a></p> -<p id="n723" class="pln"><a href="#n723">723</a></p> -<p id="n724" class="pln"><a href="#n724">724</a></p> -<p id="n725" class="pln"><a href="#n725">725</a></p> -<p id="n726" class="pln"><a href="#n726">726</a></p> -<p id="n727" class="pln"><a href="#n727">727</a></p> -<p id="n728" class="pln"><a href="#n728">728</a></p> -<p id="n729" class="pln"><a href="#n729">729</a></p> -<p id="n730" class="pln"><a href="#n730">730</a></p> -<p id="n731" class="pln"><a href="#n731">731</a></p> -<p id="n732" class="pln"><a href="#n732">732</a></p> -<p id="n733" class="pln"><a href="#n733">733</a></p> -<p id="n734" class="pln"><a href="#n734">734</a></p> -<p id="n735" class="pln"><a href="#n735">735</a></p> -<p id="n736" class="pln"><a href="#n736">736</a></p> -<p id="n737" class="pln"><a href="#n737">737</a></p> -<p id="n738" class="pln"><a href="#n738">738</a></p> -<p id="n739" class="pln"><a href="#n739">739</a></p> -<p id="n740" class="pln"><a href="#n740">740</a></p> -<p id="n741" class="pln"><a href="#n741">741</a></p> -<p id="n742" class="pln"><a href="#n742">742</a></p> -<p id="n743" class="pln"><a href="#n743">743</a></p> -<p id="n744" class="pln"><a href="#n744">744</a></p> -<p id="n745" class="pln"><a href="#n745">745</a></p> -<p id="n746" class="pln"><a href="#n746">746</a></p> -<p id="n747" class="pln"><a href="#n747">747</a></p> -<p id="n748" class="pln"><a href="#n748">748</a></p> -<p id="n749" class="pln"><a href="#n749">749</a></p> -<p id="n750" class="pln"><a href="#n750">750</a></p> -<p id="n751" class="pln"><a href="#n751">751</a></p> -<p id="n752" class="pln"><a href="#n752">752</a></p> -<p id="n753" class="pln"><a href="#n753">753</a></p> -<p id="n754" class="pln"><a href="#n754">754</a></p> -<p id="n755" class="pln"><a href="#n755">755</a></p> -<p id="n756" class="pln"><a href="#n756">756</a></p> -<p id="n757" class="pln"><a href="#n757">757</a></p> -<p id="n758" class="pln"><a href="#n758">758</a></p> -<p id="n759" class="stm run hide_run"><a href="#n759">759</a></p> -<p id="n760" class="pln"><a href="#n760">760</a></p> -<p id="n761" class="stm run hide_run"><a href="#n761">761</a></p> -<p id="n762" class="stm run hide_run"><a href="#n762">762</a></p> -<p id="n763" class="stm mis"><a href="#n763">763</a></p> -<p id="n764" class="stm mis"><a href="#n764">764</a></p> -<p id="n765" class="pln"><a href="#n765">765</a></p> -<p id="n766" class="stm mis"><a href="#n766">766</a></p> -<p id="n767" class="pln"><a href="#n767">767</a></p> -<p id="n768" class="stm run hide_run"><a href="#n768">768</a></p> -<p id="n769" class="pln"><a href="#n769">769</a></p> -<p id="n770" class="pln"><a href="#n770">770</a></p> -<p id="n771" class="stm run hide_run"><a href="#n771">771</a></p> -<p id="n772" class="pln"><a href="#n772">772</a></p> -<p id="n773" class="pln"><a href="#n773">773</a></p> -<p id="n774" class="pln"><a href="#n774">774</a></p> -<p id="n775" class="pln"><a href="#n775">775</a></p> -<p id="n776" class="pln"><a href="#n776">776</a></p> -<p id="n777" class="pln"><a href="#n777">777</a></p> -<p id="n778" class="pln"><a href="#n778">778</a></p> -<p id="n779" class="pln"><a href="#n779">779</a></p> -<p id="n780" class="pln"><a href="#n780">780</a></p> -<p id="n781" class="pln"><a href="#n781">781</a></p> -<p id="n782" class="pln"><a href="#n782">782</a></p> -<p id="n783" class="pln"><a href="#n783">783</a></p> -<p id="n784" class="stm run hide_run"><a href="#n784">784</a></p> -<p id="n785" class="pln"><a href="#n785">785</a></p> -<p id="n786" class="pln"><a href="#n786">786</a></p> -<p id="n787" class="stm run hide_run"><a href="#n787">787</a></p> -<p id="n788" class="pln"><a href="#n788">788</a></p> -<p id="n789" class="stm run hide_run"><a href="#n789">789</a></p> -<p id="n790" class="stm run hide_run"><a href="#n790">790</a></p> -<p id="n791" class="stm run hide_run"><a href="#n791">791</a></p> -<p id="n792" class="stm run hide_run"><a href="#n792">792</a></p> -<p id="n793" class="stm run hide_run"><a href="#n793">793</a></p> -<p id="n794" class="stm run hide_run"><a href="#n794">794</a></p> -<p id="n795" class="stm run hide_run"><a href="#n795">795</a></p> -<p id="n796" class="stm run hide_run"><a href="#n796">796</a></p> -<p id="n797" class="stm run hide_run"><a href="#n797">797</a></p> -<p id="n798" class="pln"><a href="#n798">798</a></p> -<p id="n799" class="stm run hide_run"><a href="#n799">799</a></p> -<p id="n800" class="pln"><a href="#n800">800</a></p> -<p id="n801" class="pln"><a href="#n801">801</a></p> -<p id="n802" class="pln"><a href="#n802">802</a></p> -<p id="n803" class="pln"><a href="#n803">803</a></p> -<p id="n804" class="pln"><a href="#n804">804</a></p> -<p id="n805" class="pln"><a href="#n805">805</a></p> -<p id="n806" class="pln"><a href="#n806">806</a></p> -<p id="n807" class="pln"><a href="#n807">807</a></p> -<p id="n808" class="pln"><a href="#n808">808</a></p> -<p id="n809" class="stm run hide_run"><a href="#n809">809</a></p> -<p id="n810" class="pln"><a href="#n810">810</a></p> -<p id="n811" class="stm run hide_run"><a href="#n811">811</a></p> -<p id="n812" class="pln"><a href="#n812">812</a></p> -<p id="n813" class="pln"><a href="#n813">813</a></p> -<p id="n814" class="pln"><a href="#n814">814</a></p> -<p id="n815" class="pln"><a href="#n815">815</a></p> -<p id="n816" class="pln"><a href="#n816">816</a></p> -<p id="n817" class="pln"><a href="#n817">817</a></p> -<p id="n818" class="pln"><a href="#n818">818</a></p> -<p id="n819" class="pln"><a href="#n819">819</a></p> -<p id="n820" class="stm run hide_run"><a href="#n820">820</a></p> -<p id="n821" class="pln"><a href="#n821">821</a></p> -<p id="n822" class="stm run hide_run"><a href="#n822">822</a></p> -<p id="n823" class="pln"><a href="#n823">823</a></p> -<p id="n824" class="pln"><a href="#n824">824</a></p> -<p id="n825" class="pln"><a href="#n825">825</a></p> -<p id="n826" class="pln"><a href="#n826">826</a></p> -<p id="n827" class="pln"><a href="#n827">827</a></p> -<p id="n828" class="pln"><a href="#n828">828</a></p> -<p id="n829" class="pln"><a href="#n829">829</a></p> -<p id="n830" class="pln"><a href="#n830">830</a></p> -<p id="n831" class="stm run hide_run"><a href="#n831">831</a></p> -<p id="n832" class="pln"><a href="#n832">832</a></p> -<p id="n833" class="stm run hide_run"><a href="#n833">833</a></p> -<p id="n834" class="pln"><a href="#n834">834</a></p> -<p id="n835" class="pln"><a href="#n835">835</a></p> -<p id="n836" class="pln"><a href="#n836">836</a></p> -<p id="n837" class="pln"><a href="#n837">837</a></p> -<p id="n838" class="pln"><a href="#n838">838</a></p> -<p id="n839" class="pln"><a href="#n839">839</a></p> -<p id="n840" class="pln"><a href="#n840">840</a></p> -<p id="n841" class="pln"><a href="#n841">841</a></p> -<p id="n842" class="stm run hide_run"><a href="#n842">842</a></p> -<p id="n843" class="pln"><a href="#n843">843</a></p> -<p id="n844" class="stm run hide_run"><a href="#n844">844</a></p> -<p id="n845" class="pln"><a href="#n845">845</a></p> -<p id="n846" class="pln"><a href="#n846">846</a></p> -<p id="n847" class="pln"><a href="#n847">847</a></p> -<p id="n848" class="pln"><a href="#n848">848</a></p> -<p id="n849" class="pln"><a href="#n849">849</a></p> -<p id="n850" class="pln"><a href="#n850">850</a></p> -<p id="n851" class="pln"><a href="#n851">851</a></p> -<p id="n852" class="pln"><a href="#n852">852</a></p> -<p id="n853" class="stm run hide_run"><a href="#n853">853</a></p> -<p id="n854" class="pln"><a href="#n854">854</a></p> -<p id="n855" class="stm run hide_run"><a href="#n855">855</a></p> -<p id="n856" class="pln"><a href="#n856">856</a></p> -<p id="n857" class="pln"><a href="#n857">857</a></p> -<p id="n858" class="pln"><a href="#n858">858</a></p> -<p id="n859" class="pln"><a href="#n859">859</a></p> -<p id="n860" class="pln"><a href="#n860">860</a></p> -<p id="n861" class="pln"><a href="#n861">861</a></p> -<p id="n862" class="pln"><a href="#n862">862</a></p> -<p id="n863" class="pln"><a href="#n863">863</a></p> -<p id="n864" class="stm run hide_run"><a href="#n864">864</a></p> -<p id="n865" class="pln"><a href="#n865">865</a></p> -<p id="n866" class="stm run hide_run"><a href="#n866">866</a></p> -<p id="n867" class="pln"><a href="#n867">867</a></p> -<p id="n868" class="pln"><a href="#n868">868</a></p> -<p id="n869" class="pln"><a href="#n869">869</a></p> -<p id="n870" class="pln"><a href="#n870">870</a></p> -<p id="n871" class="pln"><a href="#n871">871</a></p> -<p id="n872" class="pln"><a href="#n872">872</a></p> -<p id="n873" class="pln"><a href="#n873">873</a></p> -<p id="n874" class="pln"><a href="#n874">874</a></p> -<p id="n875" class="stm run hide_run"><a href="#n875">875</a></p> -<p id="n876" class="pln"><a href="#n876">876</a></p> -<p id="n877" class="stm run hide_run"><a href="#n877">877</a></p> -<p id="n878" class="pln"><a href="#n878">878</a></p> -<p id="n879" class="pln"><a href="#n879">879</a></p> -<p id="n880" class="pln"><a href="#n880">880</a></p> -<p id="n881" class="pln"><a href="#n881">881</a></p> -<p id="n882" class="pln"><a href="#n882">882</a></p> -<p id="n883" class="pln"><a href="#n883">883</a></p> -<p id="n884" class="pln"><a href="#n884">884</a></p> -<p id="n885" class="pln"><a href="#n885">885</a></p> -<p id="n886" class="stm run hide_run"><a href="#n886">886</a></p> -<p id="n887" class="pln"><a href="#n887">887</a></p> -<p id="n888" class="stm run hide_run"><a href="#n888">888</a></p> -<p id="n889" class="pln"><a href="#n889">889</a></p> -<p id="n890" class="pln"><a href="#n890">890</a></p> -<p id="n891" class="pln"><a href="#n891">891</a></p> -<p id="n892" class="pln"><a href="#n892">892</a></p> -<p id="n893" class="pln"><a href="#n893">893</a></p> -<p id="n894" class="pln"><a href="#n894">894</a></p> -<p id="n895" class="pln"><a href="#n895">895</a></p> -<p id="n896" class="pln"><a href="#n896">896</a></p> -<p id="n897" class="stm run hide_run"><a href="#n897">897</a></p> - - </td> - <td class="text"> -<p id="t1" class="stm run hide_run"><span class="key">from</span> <span class="nam">abc</span> <span class="key">import</span> <span class="nam">abstractmethod</span><span class="strut"> </span></p> -<p id="t2" class="stm run hide_run"><span class="key">from</span> <span class="nam">datetime</span> <span class="key">import</span> <span class="nam">timedelta</span><span class="strut"> </span></p> -<p id="t3" class="pln"><span class="strut"> </span></p> -<p id="t4" class="stm run hide_run"><span class="key">import</span> <span class="nam">numpy</span> <span class="key">as</span> <span class="nam">np</span><span class="strut"> </span></p> -<p id="t5" class="stm run hide_run"><span class="key">from</span> <span class="nam">scipy</span><span class="op">.</span><span class="nam">stats</span> <span class="key">import</span> <span class="nam">beta</span><span class="strut"> </span></p> -<p id="t6" class="stm run hide_run"><span class="key">import</span> <span class="nam">pandas</span> <span class="key">as</span> <span class="nam">pd</span><span class="strut"> </span></p> -<p id="t7" class="pln"><span class="strut"> </span></p> -<p id="t8" class="stm run hide_run"><span class="nam">VON_KARMAN_CONSTANT</span> <span class="op">=</span> <span class="num">0.41</span><span class="strut"> </span></p> -<p id="t9" class="pln"><span class="strut"> </span></p> -<p id="t10" class="pln"><span class="strut"> </span></p> -<p id="t11" class="stm run hide_run"><span class="key">def</span> <span class="nam">calc_water_density</span><span class="op">(</span><span class="nam">temperature</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t12" class="pln"> <span class="str">"""Calculate the temperature-dependent density of water</span><span class="strut"> </span></p> -<p id="t13" class="pln"><span class="strut"> </span></p> -<p id="t14" class="pln"><span class="str"> :param temperature: Water temperature in deg C</span><span class="strut"> </span></p> -<p id="t15" class="pln"><span class="str"> :return: Density of water in kg/m**3</span><span class="strut"> </span></p> -<p id="t16" class="pln"><span class="strut"> </span></p> -<p id="t17" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t18" class="pln"><span class="strut"> </span></p> -<p id="t19" class="stm run hide_run"> <span class="nam">a_0</span> <span class="op">=</span> <span class="num">999.842594</span><span class="strut"> </span></p> -<p id="t20" class="stm run hide_run"> <span class="nam">a_1</span> <span class="op">=</span> <span class="num">6.793952e-2</span><span class="strut"> </span></p> -<p id="t21" class="stm run hide_run"> <span class="nam">a_2</span> <span class="op">=</span> <span class="op">-</span><span class="num">9.09529e-3</span><span class="strut"> </span></p> -<p id="t22" class="stm run hide_run"> <span class="nam">a_3</span> <span class="op">=</span> <span class="num">1.001685e-4</span><span class="strut"> </span></p> -<p id="t23" class="stm run hide_run"> <span class="nam">a_4</span> <span class="op">=</span> <span class="op">-</span><span class="num">1.120083e-6</span><span class="strut"> </span></p> -<p id="t24" class="stm run hide_run"> <span class="nam">a_5</span> <span class="op">=</span> <span class="num">6.536332e-9</span><span class="strut"> </span></p> -<p id="t25" class="pln"><span class="strut"> </span></p> -<p id="t26" class="stm run hide_run"> <span class="key">return</span> <span class="nam">a_0</span> <span class="op">+</span> <span class="nam">a_1</span><span class="op">*</span><span class="nam">temperature</span> <span class="op">+</span> <span class="nam">a_2</span><span class="op">*</span><span class="nam">temperature</span><span class="op">**</span><span class="num">2</span> <span class="op">+</span> <span class="nam">a_3</span><span class="op">*</span><span class="nam">temperature</span><span class="op">**</span><span class="num">3</span> <span class="op">+</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t27" class="pln"> <span class="nam">a_4</span><span class="op">*</span><span class="nam">temperature</span><span class="op">**</span><span class="num">4</span> <span class="op">+</span> <span class="nam">a_5</span><span class="op">*</span><span class="nam">temperature</span><span class="op">**</span><span class="num">5</span><span class="strut"> </span></p> -<p id="t28" class="pln"><span class="strut"> </span></p> -<p id="t29" class="pln"><span class="strut"> </span></p> -<p id="t30" class="stm run hide_run"><span class="key">def</span> <span class="nam">calc_water_viscosity</span><span class="op">(</span><span class="nam">temperature</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t31" class="pln"> <span class="str">"""Calculate the temperature-dependent viscosity of water</span><span class="strut"> </span></p> -<p id="t32" class="pln"><span class="strut"> </span></p> -<p id="t33" class="pln"><span class="str"> :param temperature: Water temperature in deg C</span><span class="strut"> </span></p> -<p id="t34" class="pln"><span class="str"> :return: Viscosity of water in m**2/s</span><span class="strut"> </span></p> -<p id="t35" class="pln"><span class="strut"> </span></p> -<p id="t36" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t37" class="pln"><span class="strut"> </span></p> -<p id="t38" class="stm run hide_run"> <span class="key">return</span> <span class="num">1.79e-6</span> <span class="op">/</span> <span class="op">(</span><span class="num">1</span> <span class="op">+</span> <span class="op">(</span><span class="num">0.03368</span> <span class="op">*</span> <span class="nam">temperature</span><span class="op">)</span> <span class="op">+</span><span class="strut"> </span></p> -<p id="t39" class="pln"> <span class="op">(</span><span class="num">0.00021</span> <span class="op">*</span> <span class="op">(</span><span class="nam">temperature</span> <span class="op">**</span> <span class="num">2</span><span class="op">)</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t40" class="pln"><span class="strut"> </span></p> -<p id="t41" class="pln"><span class="strut"> </span></p> -<p id="t42" class="stm run hide_run"><span class="key">class</span> <span class="nam">HydraulicCell</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t43" class="pln"> <span class="str">"""Abstract base class for hydraulic cell data type. Do not initialize."""</span><span class="strut"> </span></p> -<p id="t44" class="pln"><span class="strut"> </span></p> -<p id="t45" class="stm run hide_run"> <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="op">*</span><span class="nam">args</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t46" class="pln"> <span class="str">"""</span><span class="strut"> </span></p> -<p id="t47" class="pln"><span class="strut"> </span></p> -<p id="t48" class="pln"><span class="str"> :param args:</span><span class="strut"> </span></p> -<p id="t49" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t50" class="pln"><span class="strut"> </span></p> -<p id="t51" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_depth</span> <span class="op">=</span> <span class="key">None</span><span class="strut"> </span></p> -<p id="t52" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_discharge</span> <span class="op">=</span> <span class="key">None</span><span class="strut"> </span></p> -<p id="t53" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_length</span> <span class="op">=</span> <span class="key">None</span><span class="strut"> </span></p> -<p id="t54" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_mean_xs_velocity</span> <span class="op">=</span> <span class="key">None</span><span class="strut"> </span></p> -<p id="t55" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_mean_lat_velocity</span> <span class="op">=</span> <span class="key">None</span><span class="strut"> </span></p> -<p id="t56" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_mean_long_velocity</span> <span class="op">=</span> <span class="key">None</span><span class="strut"> </span></p> -<p id="t57" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_mean_vert_velocity</span> <span class="op">=</span> <span class="key">None</span><span class="strut"> </span></p> -<p id="t58" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_shear_velocity</span> <span class="op">=</span> <span class="key">None</span><span class="strut"> </span></p> -<p id="t59" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_temperature</span> <span class="op">=</span> <span class="key">None</span><span class="strut"> </span></p> -<p id="t60" class="pln"><span class="strut"> </span></p> -<p id="t61" class="stm run hide_run"> <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">__class__</span> <span class="op">==</span> <span class="nam">HydraulicCell</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t62" class="stm mis"> <span class="key">raise</span> <span class="nam">NotImplementedError</span><span class="strut"> </span></p> -<p id="t63" class="pln"><span class="strut"> </span></p> -<p id="t64" class="stm run hide_run"> <span class="key">def</span> <span class="nam">depth</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t65" class="pln"> <span class="str">"""Returns the depth of this hydraulic cell</span><span class="strut"> </span></p> -<p id="t66" class="pln"><span class="strut"> </span></p> -<p id="t67" class="pln"><span class="str"> :return: Depth of this cell in m</span><span class="strut"> </span></p> -<p id="t68" class="pln"><span class="str"> :rtype: float</span><span class="strut"> </span></p> -<p id="t69" class="pln"><span class="strut"> </span></p> -<p id="t70" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t71" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_depth</span><span class="strut"> </span></p> -<p id="t72" class="pln"><span class="strut"> </span></p> -<p id="t73" class="stm run hide_run"> <span class="key">def</span> <span class="nam">discharge</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t74" class="pln"> <span class="str">"""Returns the water discharge in this hydraulic cell</span><span class="strut"> </span></p> -<p id="t75" class="pln"><span class="strut"> </span></p> -<p id="t76" class="pln"><span class="str"> :return: Water discharge in this cell in m**3/s</span><span class="strut"> </span></p> -<p id="t77" class="pln"><span class="str"> :rtype: float</span><span class="strut"> </span></p> -<p id="t78" class="pln"><span class="strut"> </span></p> -<p id="t79" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t80" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_discharge</span><span class="strut"> </span></p> -<p id="t81" class="pln"><span class="strut"> </span></p> -<p id="t82" class="stm run hide_run"> <span class="key">def</span> <span class="nam">length</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t83" class="pln"> <span class="str">"""Returns the longitudinal length of this hydraulic cell</span><span class="strut"> </span></p> -<p id="t84" class="pln"><span class="strut"> </span></p> -<p id="t85" class="pln"><span class="str"> :return: Length of this cell in m</span><span class="strut"> </span></p> -<p id="t86" class="pln"><span class="str"> :rtype: float</span><span class="strut"> </span></p> -<p id="t87" class="pln"><span class="strut"> </span></p> -<p id="t88" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t89" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_length</span><span class="strut"> </span></p> -<p id="t90" class="pln"><span class="strut"> </span></p> -<p id="t91" class="stm run hide_run"> <span class="key">def</span> <span class="nam">mean_xs_velocity</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t92" class="pln"> <span class="str">"""Returns the mean cross-section velocity for this cell.</span><span class="strut"> </span></p> -<p id="t93" class="pln"><span class="strut"> </span></p> -<p id="t94" class="pln"><span class="str"> :return: Mean cross-section velocity</span><span class="strut"> </span></p> -<p id="t95" class="pln"><span class="str"> :rtype: float</span><span class="strut"> </span></p> -<p id="t96" class="pln"><span class="strut"> </span></p> -<p id="t97" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t98" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_mean_xs_velocity</span><span class="strut"> </span></p> -<p id="t99" class="pln"><span class="strut"> </span></p> -<p id="t100" class="stm run hide_run"> <span class="key">def</span> <span class="nam">mean_lat_velocity</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t101" class="pln"> <span class="str">"""Returns the mean lateral (y direction) velocity for this cell.</span><span class="strut"> </span></p> -<p id="t102" class="pln"><span class="strut"> </span></p> -<p id="t103" class="pln"><span class="str"> :return: Mean lateral velocity</span><span class="strut"> </span></p> -<p id="t104" class="pln"><span class="str"> :rtype: float</span><span class="strut"> </span></p> -<p id="t105" class="pln"><span class="strut"> </span></p> -<p id="t106" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t107" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_mean_lat_velocity</span><span class="strut"> </span></p> -<p id="t108" class="pln"><span class="strut"> </span></p> -<p id="t109" class="stm run hide_run"> <span class="key">def</span> <span class="nam">mean_long_velocity</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t110" class="pln"> <span class="str">"""Returns the mean longitudinal (x direction) velocity for this cell.</span><span class="strut"> </span></p> -<p id="t111" class="pln"><span class="strut"> </span></p> -<p id="t112" class="pln"><span class="str"> :return:</span><span class="strut"> </span></p> -<p id="t113" class="pln"><span class="strut"> </span></p> -<p id="t114" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t115" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_mean_long_velocity</span><span class="strut"> </span></p> -<p id="t116" class="pln"><span class="strut"> </span></p> -<p id="t117" class="stm run hide_run"> <span class="key">def</span> <span class="nam">mean_vert_velocity</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t118" class="pln"> <span class="str">"""Returns the mean vertical (z direction) velocity for this cell.</span><span class="strut"> </span></p> -<p id="t119" class="pln"><span class="strut"> </span></p> -<p id="t120" class="pln"><span class="str"> :return: Mean vertical velocity</span><span class="strut"> </span></p> -<p id="t121" class="pln"><span class="str"> :rtype: float</span><span class="strut"> </span></p> -<p id="t122" class="pln"><span class="strut"> </span></p> -<p id="t123" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t124" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_mean_vert_velocity</span><span class="strut"> </span></p> -<p id="t125" class="pln"><span class="strut"> </span></p> -<p id="t126" class="stm run hide_run"> <span class="key">def</span> <span class="nam">shear_velocity</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t127" class="pln"> <span class="str">"""Returns the shear velocity of this cell.</span><span class="strut"> </span></p> -<p id="t128" class="pln"><span class="strut"> </span></p> -<p id="t129" class="pln"><span class="str"> :return: Shear velocity in m/s</span><span class="strut"> </span></p> -<p id="t130" class="pln"><span class="str"> :rtype: float</span><span class="strut"> </span></p> -<p id="t131" class="pln"><span class="strut"> </span></p> -<p id="t132" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t133" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_shear_velocity</span><span class="strut"> </span></p> -<p id="t134" class="pln"><span class="strut"> </span></p> -<p id="t135" class="stm run hide_run"> <span class="key">def</span> <span class="nam">temperature</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t136" class="pln"> <span class="str">"""Returns the temperature of this hydraulic cell</span><span class="strut"> </span></p> -<p id="t137" class="pln"><span class="strut"> </span></p> -<p id="t138" class="pln"><span class="str"> :return: Temperature of this cell in deg C</span><span class="strut"> </span></p> -<p id="t139" class="pln"><span class="str"> :rtype: float</span><span class="strut"> </span></p> -<p id="t140" class="pln"><span class="strut"> </span></p> -<p id="t141" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t142" class="pln"><span class="strut"> </span></p> -<p id="t143" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_temperature</span><span class="strut"> </span></p> -<p id="t144" class="pln"><span class="strut"> </span></p> -<p id="t145" class="stm run hide_run"> <span class="key">def</span> <span class="nam">width</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t146" class="pln"> <span class="str">"""Returns the lateral width of this hydraulic cell</span><span class="strut"> </span></p> -<p id="t147" class="pln"><span class="strut"> </span></p> -<p id="t148" class="pln"><span class="str"> :return: Width of this cell in m</span><span class="strut"> </span></p> -<p id="t149" class="pln"><span class="str"> :rtype: float</span><span class="strut"> </span></p> -<p id="t150" class="pln"><span class="strut"> </span></p> -<p id="t151" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t152" class="pln"><span class="strut"> </span></p> -<p id="t153" class="stm mis"> <span class="nam">discharge</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">discharge</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t154" class="stm mis"> <span class="nam">mean_xs_velocity</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">mean_xs_velocity</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t155" class="stm mis"> <span class="nam">depth</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">depth</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t156" class="stm mis"> <span class="nam">area</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">abs</span><span class="op">(</span><span class="nam">discharge</span> <span class="op">/</span> <span class="nam">mean_xs_velocity</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t157" class="stm mis"> <span class="key">return</span> <span class="nam">area</span> <span class="op">/</span> <span class="nam">depth</span><span class="strut"> </span></p> -<p id="t158" class="pln"><span class="strut"> </span></p> -<p id="t159" class="pln"><span class="strut"> </span></p> -<p id="t160" class="stm run hide_run"><span class="key">class</span> <span class="nam">SteadyStateHydraulicCell</span><span class="op">(</span><span class="nam">HydraulicCell</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t161" class="pln"> <span class="str">"""Data type representing a steady-state hydraulic cell.</span><span class="strut"> </span></p> -<p id="t162" class="pln"><span class="strut"> </span></p> -<p id="t163" class="pln"><span class="str"> A hydraulic cell typically represents a cell in a series of cells within a</span><span class="strut"> </span></p> -<p id="t164" class="pln"><span class="str"> river reach. This class implementation represents steady-state hydraulic</span><span class="strut"> </span></p> -<p id="t165" class="pln"><span class="str"> conditions.</span><span class="strut"> </span></p> -<p id="t166" class="pln"><span class="strut"> </span></p> -<p id="t167" class="pln"><span class="str"> Parameters</span><span class="strut"> </span></p> -<p id="t168" class="pln"><span class="str"> ----------</span><span class="strut"> </span></p> -<p id="t169" class="pln"><span class="str"> length : float</span><span class="strut"> </span></p> -<p id="t170" class="pln"><span class="str"> Length of this cell in m</span><span class="strut"> </span></p> -<p id="t171" class="pln"><span class="strut"> </span></p> -<p id="t172" class="pln"><span class="str"> depth : float</span><span class="strut"> </span></p> -<p id="t173" class="pln"><span class="str"> Depth of this cell in m</span><span class="strut"> </span></p> -<p id="t174" class="pln"><span class="strut"> </span></p> -<p id="t175" class="pln"><span class="str"> discharge : float</span><span class="strut"> </span></p> -<p id="t176" class="pln"><span class="str"> Discharge in this cell in m**3/s</span><span class="strut"> </span></p> -<p id="t177" class="pln"><span class="strut"> </span></p> -<p id="t178" class="pln"><span class="str"> mean_xs_velocity : float</span><span class="strut"> </span></p> -<p id="t179" class="pln"><span class="str"> Mean cross section velocity in this cell in m/s</span><span class="strut"> </span></p> -<p id="t180" class="pln"><span class="strut"> </span></p> -<p id="t181" class="pln"><span class="str"> mean_lat_velocity : float</span><span class="strut"> </span></p> -<p id="t182" class="pln"><span class="str"> Mean lateral velocity in this cell in m/s</span><span class="strut"> </span></p> -<p id="t183" class="pln"><span class="strut"> </span></p> -<p id="t184" class="pln"><span class="str"> mean_vert_velocity : float</span><span class="strut"> </span></p> -<p id="t185" class="pln"><span class="str"> Mean vertical velocity in this cell in m/s</span><span class="strut"> </span></p> -<p id="t186" class="pln"><span class="strut"> </span></p> -<p id="t187" class="pln"><span class="str"> shear_velocity : float</span><span class="strut"> </span></p> -<p id="t188" class="pln"><span class="str"> Shear velocity within this cell in m/s</span><span class="strut"> </span></p> -<p id="t189" class="pln"><span class="strut"> </span></p> -<p id="t190" class="pln"><span class="str"> temperature: float</span><span class="strut"> </span></p> -<p id="t191" class="pln"><span class="str"> Temperature of water within this cell in deg C</span><span class="strut"> </span></p> -<p id="t192" class="pln"><span class="strut"> </span></p> -<p id="t193" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t194" class="pln"><span class="strut"> </span></p> -<p id="t195" class="stm run hide_run"> <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">length</span><span class="op">,</span> <span class="nam">depth</span><span class="op">,</span> <span class="nam">discharge</span><span class="op">,</span> <span class="nam">mean_xs_velocity</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t196" class="pln"> <span class="nam">mean_lat_velocity</span><span class="op">,</span> <span class="nam">mean_vert_velocity</span><span class="op">,</span> <span class="nam">shear_velocity</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t197" class="pln"> <span class="nam">temperature</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t198" class="pln"> <span class="str">"""Initialize self. See help(type(self)) for accurate signature."""</span><span class="strut"> </span></p> -<p id="t199" class="pln"><span class="strut"> </span></p> -<p id="t200" class="stm run hide_run"> <span class="nam">super</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">__init__</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t201" class="pln"><span class="strut"> </span></p> -<p id="t202" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_length</span> <span class="op">=</span> <span class="nam">length</span><span class="strut"> </span></p> -<p id="t203" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_depth</span> <span class="op">=</span> <span class="nam">depth</span><span class="strut"> </span></p> -<p id="t204" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_discharge</span> <span class="op">=</span> <span class="nam">discharge</span><span class="strut"> </span></p> -<p id="t205" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_mean_xs_velocity</span> <span class="op">=</span> <span class="nam">mean_xs_velocity</span><span class="strut"> </span></p> -<p id="t206" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_mean_lat_velocity</span> <span class="op">=</span> <span class="nam">mean_lat_velocity</span><span class="strut"> </span></p> -<p id="t207" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_mean_vert_velocity</span> <span class="op">=</span> <span class="nam">mean_vert_velocity</span><span class="strut"> </span></p> -<p id="t208" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_shear_velocity</span> <span class="op">=</span> <span class="nam">shear_velocity</span><span class="strut"> </span></p> -<p id="t209" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_temperature</span> <span class="op">=</span> <span class="nam">temperature</span><span class="strut"> </span></p> -<p id="t210" class="pln"><span class="strut"> </span></p> -<p id="t211" class="stm run hide_run"> <span class="nam">flow_direction</span> <span class="op">=</span> <span class="nam">discharge</span><span class="op">/</span><span class="nam">np</span><span class="op">.</span><span class="nam">abs</span><span class="op">(</span><span class="nam">discharge</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t212" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_mean_long_velocity</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t213" class="pln"> <span class="nam">flow_direction</span><span class="op">*</span><span class="nam">np</span><span class="op">.</span><span class="nam">sqrt</span><span class="op">(</span><span class="nam">mean_xs_velocity</span><span class="op">**</span><span class="num">2</span> <span class="op">-</span><span class="strut"> </span></p> -<p id="t214" class="pln"> <span class="nam">mean_lat_velocity</span><span class="op">**</span><span class="num">2</span> <span class="op">-</span><span class="strut"> </span></p> -<p id="t215" class="pln"> <span class="nam">mean_vert_velocity</span><span class="op">**</span><span class="num">2</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t216" class="pln"><span class="strut"> </span></p> -<p id="t217" class="pln"><span class="strut"> </span></p> -<p id="t218" class="stm run hide_run"><span class="key">class</span> <span class="nam">UnsteadyHydraulicCell</span><span class="op">(</span><span class="nam">HydraulicCell</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t219" class="pln"> <span class="str">"""</span><span class="strut"> </span></p> -<p id="t220" class="pln"><span class="strut"> </span></p> -<p id="t221" class="pln"><span class="str"> Parameters</span><span class="strut"> </span></p> -<p id="t222" class="pln"><span class="str"> ----------</span><span class="strut"> </span></p> -<p id="t223" class="pln"><span class="str"> length : float</span><span class="strut"> </span></p> -<p id="t224" class="pln"><span class="str"> Length of this cell in m</span><span class="strut"> </span></p> -<p id="t225" class="pln"><span class="str"> temperature : float</span><span class="strut"> </span></p> -<p id="t226" class="pln"><span class="str"> Temperature of water within this cell in deg C</span><span class="strut"> </span></p> -<p id="t227" class="pln"><span class="str"> property_time_series : pandas.DataFrame</span><span class="strut"> </span></p> -<p id="t228" class="pln"><span class="str"> Pandas DataFrame containing a time series with the following columns</span><span class="strut"> </span></p> -<p id="t229" class="pln"><span class="strut"> </span></p> -<p id="t230" class="pln"><span class="str"> Depth_m Depth of the cell in m</span><span class="strut"> </span></p> -<p id="t231" class="pln"><span class="str"> Q_cms Discharge of the cell in m**3/s</span><span class="strut"> </span></p> -<p id="t232" class="pln"><span class="str"> Vmag_mps Cross-section average velocity in m/s</span><span class="strut"> </span></p> -<p id="t233" class="pln"><span class="str"> Vvert_mps Vertical component of velocity in m/s</span><span class="strut"> </span></p> -<p id="t234" class="pln"><span class="str"> Vlat_mps Lateral component of velocity in m/s</span><span class="strut"> </span></p> -<p id="t235" class="pln"><span class="str"> Ustar_mps Shear velocity in m/s</span><span class="strut"> </span></p> -<p id="t236" class="pln"><span class="str"> Temp_C Temperature in deg C</span><span class="strut"> </span></p> -<p id="t237" class="pln"><span class="strut"> </span></p> -<p id="t238" class="pln"><span class="str"> start_time : numpy.datetime64</span><span class="strut"> </span></p> -<p id="t239" class="pln"><span class="str"> simulation_clock : fluegg.simclock.SimulationClock</span><span class="strut"> </span></p> -<p id="t240" class="pln"><span class="str"> simulation : fluegg.simulation.Simulation</span><span class="strut"> </span></p> -<p id="t241" class="pln"><span class="strut"> </span></p> -<p id="t242" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t243" class="pln"><span class="strut"> </span></p> -<p id="t244" class="stm run hide_run"> <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">length</span><span class="op">,</span> <span class="nam">property_time_series</span><span class="op">,</span> <span class="nam">start_time</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t245" class="pln"> <span class="nam">simulation_clock</span><span class="op">,</span> <span class="nam">simulation</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t246" class="pln"> <span class="str">"""Initialize self. See help(type(self)) for accurate signature."""</span><span class="strut"> </span></p> -<p id="t247" class="pln"><span class="strut"> </span></p> -<p id="t248" class="stm run hide_run"> <span class="nam">super</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">__init__</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t249" class="pln"><span class="strut"> </span></p> -<p id="t250" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_length</span> <span class="op">=</span> <span class="nam">length</span><span class="strut"> </span></p> -<p id="t251" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_depth</span> <span class="op">=</span> <span class="key">None</span><span class="strut"> </span></p> -<p id="t252" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_discharge</span> <span class="op">=</span> <span class="key">None</span><span class="strut"> </span></p> -<p id="t253" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_mean_xs_velocity</span> <span class="op">=</span> <span class="key">None</span><span class="strut"> </span></p> -<p id="t254" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_mean_lat_velocity</span> <span class="op">=</span> <span class="key">None</span><span class="strut"> </span></p> -<p id="t255" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_mean_long_velocity</span> <span class="op">=</span> <span class="key">None</span><span class="strut"> </span></p> -<p id="t256" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_mean_vert_velocity</span> <span class="op">=</span> <span class="key">None</span><span class="strut"> </span></p> -<p id="t257" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_shear_velocity</span> <span class="op">=</span> <span class="key">None</span><span class="strut"> </span></p> -<p id="t258" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_temperature</span> <span class="op">=</span> <span class="key">None</span><span class="strut"> </span></p> -<p id="t259" class="pln"><span class="strut"> </span></p> -<p id="t260" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_time_series</span> <span class="op">=</span> <span class="nam">property_time_series</span><span class="op">.</span><span class="nam">copy</span><span class="op">(</span><span class="nam">deep</span><span class="op">=</span><span class="key">True</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t261" class="pln"><span class="strut"> </span></p> -<p id="t262" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_start_time</span> <span class="op">=</span> <span class="nam">start_time</span><span class="strut"> </span></p> -<p id="t263" class="pln"><span class="strut"> </span></p> -<p id="t264" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_simclock</span> <span class="op">=</span> <span class="nam">simulation_clock</span><span class="strut"> </span></p> -<p id="t265" class="pln"><span class="strut"> </span></p> -<p id="t266" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_current_time</span> <span class="op">=</span> <span class="key">None</span><span class="strut"> </span></p> -<p id="t267" class="pln"><span class="strut"> </span></p> -<p id="t268" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_update_properties</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t269" class="stm run hide_run"> <span class="nam">simulation</span><span class="op">.</span><span class="nam">add_time_step_function_call</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_update_properties</span><span class="op">,</span> <span class="op">[</span><span class="op">]</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t270" class="pln"><span class="strut"> </span></p> -<p id="t271" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_current_simulation_time</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t272" class="pln"><span class="strut"> </span></p> -<p id="t273" class="stm run hide_run"> <span class="nam">simulation_time_delta</span> <span class="op">=</span> <span class="nam">timedelta</span><span class="op">(</span><span class="strut"> </span></p> -<p id="t274" class="pln"> <span class="nam">seconds</span><span class="op">=</span><span class="nam">self</span><span class="op">.</span><span class="nam">_simclock</span><span class="op">.</span><span class="nam">current_time</span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t275" class="stm run hide_run"> <span class="nam">current_simulation_time</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_start_time</span> <span class="op">+</span> <span class="nam">simulation_time_delta</span><span class="strut"> </span></p> -<p id="t276" class="pln"><span class="strut"> </span></p> -<p id="t277" class="stm run hide_run"> <span class="nam">times</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_time_series</span><span class="op">.</span><span class="nam">index</span><span class="strut"> </span></p> -<p id="t278" class="pln"><span class="strut"> </span></p> -<p id="t279" class="stm run hide_run"> <span class="nam">current_time_index</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">nonzero</span><span class="op">(</span><span class="strut"> </span></p> -<p id="t280" class="pln"> <span class="nam">times</span> <span class="op"><=</span> <span class="nam">current_simulation_time</span><span class="op">)</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="op">.</span><span class="nam">max</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t281" class="pln"><span class="strut"> </span></p> -<p id="t282" class="stm run hide_run"> <span class="key">return</span> <span class="nam">times</span><span class="op">[</span><span class="nam">current_time_index</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t283" class="pln"><span class="strut"> </span></p> -<p id="t284" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_update_properties</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t285" class="pln"><span class="strut"> </span></p> -<p id="t286" class="stm run hide_run"> <span class="nam">depth_key</span> <span class="op">=</span> <span class="str">'Depth_m'</span><span class="strut"> </span></p> -<p id="t287" class="stm run hide_run"> <span class="nam">discharge_key</span> <span class="op">=</span> <span class="str">'Q_cms'</span><span class="strut"> </span></p> -<p id="t288" class="stm run hide_run"> <span class="nam">vmag_key</span> <span class="op">=</span> <span class="str">'Vmag_mps'</span><span class="strut"> </span></p> -<p id="t289" class="stm run hide_run"> <span class="nam">vvert_key</span> <span class="op">=</span> <span class="str">'Vvert_mps'</span><span class="strut"> </span></p> -<p id="t290" class="stm run hide_run"> <span class="nam">vlat_key</span> <span class="op">=</span> <span class="str">'Vlat_mps'</span><span class="strut"> </span></p> -<p id="t291" class="stm run hide_run"> <span class="nam">shear_velocity_key</span> <span class="op">=</span> <span class="str">'Ustar_mps'</span><span class="strut"> </span></p> -<p id="t292" class="stm run hide_run"> <span class="nam">temperature_key</span> <span class="op">=</span> <span class="str">'Temp_C'</span><span class="strut"> </span></p> -<p id="t293" class="pln"><span class="strut"> </span></p> -<p id="t294" class="stm run hide_run"> <span class="nam">last_current_time</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_current_time</span><span class="strut"> </span></p> -<p id="t295" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_current_time</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_current_simulation_time</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t296" class="pln"><span class="strut"> </span></p> -<p id="t297" class="stm run hide_run"> <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_current_time</span> <span class="op">!=</span> <span class="nam">last_current_time</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t298" class="pln"><span class="strut"> </span></p> -<p id="t299" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_depth</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_time_series</span><span class="op">.</span><span class="nam">loc</span><span class="op">[</span><span class="nam">self</span><span class="op">.</span><span class="nam">_current_time</span><span class="op">,</span> <span class="nam">depth_key</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t300" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_discharge</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t301" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">_time_series</span><span class="op">.</span><span class="nam">loc</span><span class="op">[</span><span class="nam">self</span><span class="op">.</span><span class="nam">_current_time</span><span class="op">,</span> <span class="nam">discharge_key</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t302" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_mean_xs_velocity</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t303" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">_time_series</span><span class="op">.</span><span class="nam">loc</span><span class="op">[</span><span class="nam">self</span><span class="op">.</span><span class="nam">_current_time</span><span class="op">,</span> <span class="nam">vmag_key</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t304" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_mean_lat_velocity</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t305" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">_time_series</span><span class="op">.</span><span class="nam">loc</span><span class="op">[</span><span class="nam">self</span><span class="op">.</span><span class="nam">_current_time</span><span class="op">,</span> <span class="nam">vlat_key</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t306" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_mean_vert_velocity</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t307" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">_time_series</span><span class="op">.</span><span class="nam">loc</span><span class="op">[</span><span class="nam">self</span><span class="op">.</span><span class="nam">_current_time</span><span class="op">,</span> <span class="nam">vvert_key</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t308" class="stm run hide_run"> <span class="nam">flow_direction</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_discharge</span> <span class="op">/</span> <span class="nam">np</span><span class="op">.</span><span class="nam">abs</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_discharge</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t309" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_mean_long_velocity</span> <span class="op">=</span> <span class="nam">flow_direction</span> <span class="op">*</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t310" class="pln"> <span class="nam">np</span><span class="op">.</span><span class="nam">sqrt</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_mean_xs_velocity</span> <span class="op">**</span> <span class="num">2</span> <span class="op">-</span><span class="strut"> </span></p> -<p id="t311" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">_mean_lat_velocity</span> <span class="op">**</span> <span class="num">2</span> <span class="op">-</span><span class="strut"> </span></p> -<p id="t312" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">_mean_vert_velocity</span> <span class="op">**</span> <span class="num">2</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t313" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_shear_velocity</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_time_series</span><span class="op">.</span><span class="nam">loc</span><span class="op">[</span><span class="nam">self</span><span class="op">.</span><span class="nam">_current_time</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t314" class="pln"> <span class="nam">shear_velocity_key</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t315" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_temperature</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_time_series</span><span class="op">.</span><span class="nam">loc</span><span class="op">[</span><span class="nam">self</span><span class="op">.</span><span class="nam">_current_time</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t316" class="pln"> <span class="nam">temperature_key</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t317" class="pln"><span class="strut"> </span></p> -<p id="t318" class="stm run hide_run"> <span class="key">def</span> <span class="nam">to_data_frame</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t319" class="pln"> <span class="str">"""Time series information from this cell in a Pandas DataFrame.</span><span class="strut"> </span></p> -<p id="t320" class="pln"><span class="strut"> </span></p> -<p id="t321" class="pln"><span class="str"> Returns</span><span class="strut"> </span></p> -<p id="t322" class="pln"><span class="str"> -------</span><span class="strut"> </span></p> -<p id="t323" class="pln"><span class="str"> pandas.DataFrame</span><span class="strut"> </span></p> -<p id="t324" class="pln"><span class="str"> DataFrame containing time series information from this cell.</span><span class="strut"> </span></p> -<p id="t325" class="pln"><span class="strut"> </span></p> -<p id="t326" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t327" class="pln"><span class="strut"> </span></p> -<p id="t328" class="stm mis"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_time_series</span><span class="op">.</span><span class="nam">copy</span><span class="op">(</span><span class="nam">deep</span><span class="op">=</span><span class="key">True</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t329" class="pln"><span class="strut"> </span></p> -<p id="t330" class="pln"><span class="strut"> </span></p> -<p id="t331" class="stm run hide_run"><span class="key">class</span> <span class="nam">SeriesOfHydraulicCells</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t332" class="pln"> <span class="str">"""Data type for hydraulic geometry represented by a series of hydraulic</span><span class="strut"> </span></p> -<p id="t333" class="pln"><span class="str"> cells.</span><span class="strut"> </span></p> -<p id="t334" class="pln"><span class="strut"> </span></p> -<p id="t335" class="pln"><span class="str"> Instantiate from a CSV file with from_csv.</span><span class="strut"> </span></p> -<p id="t336" class="pln"><span class="strut"> </span></p> -<p id="t337" class="pln"><span class="str"> Parameters</span><span class="strut"> </span></p> -<p id="t338" class="pln"><span class="str"> ----------</span><span class="strut"> </span></p> -<p id="t339" class="pln"><span class="str"> list_of_cells : list</span><span class="strut"> </span></p> -<p id="t340" class="pln"><span class="str"> List containing HydraulicCell elements.</span><span class="strut"> </span></p> -<p id="t341" class="pln"><span class="strut"> </span></p> -<p id="t342" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t343" class="pln"><span class="strut"> </span></p> -<p id="t344" class="stm run hide_run"> <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">list_of_cells</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t345" class="pln"> <span class="str">"""Initialize self. See help(type(self)) for accurate signature."""</span><span class="strut"> </span></p> -<p id="t346" class="pln"><span class="strut"> </span></p> -<p id="t347" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_cells</span> <span class="op">=</span> <span class="nam">list_of_cells</span><span class="strut"> </span></p> -<p id="t348" class="pln"><span class="strut"> </span></p> -<p id="t349" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_cell_edges</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_calc_cell_edges</span><span class="op">(</span><span class="nam">list_of_cells</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t350" class="pln"><span class="strut"> </span></p> -<p id="t351" class="stm run hide_run"> <span class="op">@</span><span class="nam">staticmethod</span><span class="strut"> </span></p> -<p id="t352" class="pln"> <span class="key">def</span> <span class="nam">_calc_cell_edges</span><span class="op">(</span><span class="nam">list_of_cells</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t353" class="pln"><span class="strut"> </span></p> -<p id="t354" class="stm run hide_run"> <span class="nam">cumulative_distance</span> <span class="op">=</span> <span class="num">0</span><span class="strut"> </span></p> -<p id="t355" class="stm run hide_run"> <span class="nam">cell_edges</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">tile</span><span class="op">(</span><span class="nam">np</span><span class="op">.</span><span class="nam">nan</span><span class="op">,</span> <span class="nam">len</span><span class="op">(</span><span class="nam">list_of_cells</span><span class="op">)</span><span class="op">+</span><span class="num">1</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t356" class="pln"><span class="strut"> </span></p> -<p id="t357" class="stm run hide_run"> <span class="nam">cell_edges</span><span class="op">[</span><span class="num">0</span><span class="op">]</span> <span class="op">=</span> <span class="nam">cumulative_distance</span><span class="strut"> </span></p> -<p id="t358" class="pln"><span class="strut"> </span></p> -<p id="t359" class="stm run hide_run"> <span class="key">for</span> <span class="nam">i</span><span class="op">,</span> <span class="nam">cell</span> <span class="key">in</span> <span class="nam">enumerate</span><span class="op">(</span><span class="nam">list_of_cells</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t360" class="stm run hide_run"> <span class="nam">cumulative_distance</span> <span class="op">+=</span> <span class="nam">cell</span><span class="op">.</span><span class="nam">length</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t361" class="stm run hide_run"> <span class="nam">cell_edges</span><span class="op">[</span><span class="nam">i</span><span class="op">+</span><span class="num">1</span><span class="op">]</span> <span class="op">=</span> <span class="nam">cumulative_distance</span><span class="strut"> </span></p> -<p id="t362" class="pln"><span class="strut"> </span></p> -<p id="t363" class="stm run hide_run"> <span class="key">return</span> <span class="nam">cell_edges</span><span class="strut"> </span></p> -<p id="t364" class="pln"><span class="strut"> </span></p> -<p id="t365" class="stm run hide_run"> <span class="op">@</span><span class="nam">abstractmethod</span><span class="strut"> </span></p> -<p id="t366" class="pln"> <span class="key">def</span> <span class="nam">_calc_log_law_velocity</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">vertical_location</span><span class="op">,</span> <span class="nam">shear_velocity</span><span class="op">,</span> <span class="nam">depth</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t367" class="pln"> <span class="nam">mean_xs_velocity</span><span class="op">,</span> <span class="nam">viscosity</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t368" class="stm mis"> <span class="key">raise</span> <span class="nam">NotImplementedError</span><span class="strut"> </span></p> -<p id="t369" class="pln"><span class="strut"> </span></p> -<p id="t370" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_calc_longitudinal_velocity</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">vertical_location</span><span class="op">,</span> <span class="nam">shear_velocity</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t371" class="pln"> <span class="nam">depth</span><span class="op">,</span> <span class="nam">mean_xs_velocity</span><span class="op">,</span> <span class="nam">viscosity</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t372" class="pln"> <span class="nam">lateral_location</span><span class="op">,</span> <span class="nam">width</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t373" class="pln"><span class="strut"> </span></p> -<p id="t374" class="stm run hide_run"> <span class="nam">distance_above_bed</span> <span class="op">=</span> <span class="nam">vertical_location</span> <span class="op">+</span> <span class="nam">depth</span><span class="strut"> </span></p> -<p id="t375" class="pln"><span class="strut"> </span></p> -<p id="t376" class="stm run hide_run"> <span class="nam">minimum_distance_above_bed</span> <span class="op">=</span> <span class="num">0.00001</span><span class="strut"> </span></p> -<p id="t377" class="stm run hide_run"> <span class="nam">distance_above_bed</span><span class="op">[</span><span class="nam">distance_above_bed</span> <span class="op"><</span> <span class="nam">minimum_distance_above_bed</span><span class="op">]</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t378" class="pln"> <span class="nam">minimum_distance_above_bed</span><span class="strut"> </span></p> -<p id="t379" class="pln"><span class="strut"> </span></p> -<p id="t380" class="stm run hide_run"> <span class="nam">log_law_velocity</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t381" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">_calc_log_law_velocity</span><span class="op">(</span><span class="strut"> </span></p> -<p id="t382" class="pln"> <span class="nam">distance_above_bed</span><span class="op">,</span> <span class="nam">shear_velocity</span><span class="op">,</span> <span class="nam">depth</span><span class="op">,</span> <span class="nam">mean_xs_velocity</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t383" class="pln"> <span class="nam">viscosity</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t384" class="pln"><span class="strut"> </span></p> -<p id="t385" class="pln"> <span class="com"># enforce the no-slip condition</span><span class="strut"> </span></p> -<p id="t386" class="stm run hide_run"> <span class="nam">log_law_velocity</span><span class="op">[</span><span class="nam">log_law_velocity</span> <span class="op"><</span> <span class="num">0</span><span class="op">]</span> <span class="op">=</span> <span class="num">0</span><span class="strut"> </span></p> -<p id="t387" class="pln"><span class="strut"> </span></p> -<p id="t388" class="stm run hide_run"> <span class="nam">a</span> <span class="op">=</span> <span class="num">2.51</span><span class="strut"> </span></p> -<p id="t389" class="stm run hide_run"> <span class="nam">b</span> <span class="op">=</span> <span class="num">2.47</span><span class="strut"> </span></p> -<p id="t390" class="pln"><span class="strut"> </span></p> -<p id="t391" class="stm run hide_run"> <span class="nam">streamwise_velocity</span> <span class="op">=</span> <span class="nam">log_law_velocity</span> <span class="op">*</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t392" class="pln"> <span class="nam">beta</span><span class="op">.</span><span class="nam">pdf</span><span class="op">(</span><span class="nam">lateral_location</span><span class="op">/</span><span class="nam">width</span><span class="op">,</span> <span class="nam">a</span><span class="op">,</span> <span class="nam">b</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t393" class="pln"><span class="strut"> </span></p> -<p id="t394" class="stm run hide_run"> <span class="key">return</span> <span class="nam">streamwise_velocity</span><span class="strut"> </span></p> -<p id="t395" class="pln"><span class="strut"> </span></p> -<p id="t396" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_cell_number_by_position</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">location</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t397" class="pln"><span class="strut"> </span></p> -<p id="t398" class="pln"> <span class="com"># Digitize egg positions</span><span class="strut"> </span></p> -<p id="t399" class="stm run hide_run"> <span class="nam">position_cell_number</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">digitize</span><span class="op">(</span><span class="nam">location</span><span class="op">,</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_cell_edges</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t400" class="pln"><span class="strut"> </span></p> -<p id="t401" class="pln"> <span class="com"># Eggs have travelled before the first hydraulic cell</span><span class="strut"> </span></p> -<p id="t402" class="pln"> <span class="com"># (reverse simulation)</span><span class="strut"> </span></p> -<p id="t403" class="stm run hide_run"> <span class="nam">position_cell_number</span><span class="op">[</span><span class="nam">location</span> <span class="op"><</span> <span class="num">0</span><span class="op">]</span> <span class="op">=</span> <span class="num">1</span><span class="strut"> </span></p> -<p id="t404" class="pln"><span class="strut"> </span></p> -<p id="t405" class="stm run hide_run"> <span class="key">return</span> <span class="nam">position_cell_number</span><span class="strut"> </span></p> -<p id="t406" class="pln"><span class="strut"> </span></p> -<p id="t407" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_cell_property_by_location</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">property_method</span><span class="op">,</span> <span class="nam">location</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t408" class="pln"><span class="strut"> </span></p> -<p id="t409" class="pln"> <span class="com"># make the extend the cell depth array by one cell to virtually extend</span><span class="strut"> </span></p> -<p id="t410" class="pln"> <span class="com"># the reach with the properties from the last cell</span><span class="strut"> </span></p> -<p id="t411" class="stm run hide_run"> <span class="nam">cell_property</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">tile</span><span class="op">(</span><span class="nam">np</span><span class="op">.</span><span class="nam">nan</span><span class="op">,</span> <span class="nam">len</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_cells</span><span class="op">)</span><span class="op">+</span><span class="num">1</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t412" class="stm run hide_run"> <span class="key">for</span> <span class="nam">i</span><span class="op">,</span> <span class="nam">cell</span> <span class="key">in</span> <span class="nam">enumerate</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_cells</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t413" class="stm run hide_run"> <span class="nam">cell_property</span><span class="op">[</span><span class="nam">i</span><span class="op">]</span> <span class="op">=</span> <span class="nam">getattr</span><span class="op">(</span><span class="nam">cell</span><span class="op">,</span> <span class="nam">property_method</span><span class="op">)</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t414" class="stm run hide_run"> <span class="nam">cell_property</span><span class="op">[</span><span class="op">-</span><span class="num">1</span><span class="op">]</span> <span class="op">=</span> <span class="nam">getattr</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_cells</span><span class="op">[</span><span class="op">-</span><span class="num">1</span><span class="op">]</span><span class="op">,</span> <span class="nam">property_method</span><span class="op">)</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t415" class="pln"><span class="strut"> </span></p> -<p id="t416" class="stm run hide_run"> <span class="nam">location_cell_number</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_cell_number_by_position</span><span class="op">(</span><span class="nam">location</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t417" class="stm run hide_run"> <span class="nam">location_property</span> <span class="op">=</span> <span class="nam">cell_property</span><span class="op">[</span><span class="nam">location_cell_number</span> <span class="op">-</span> <span class="num">1</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t418" class="pln"><span class="strut"> </span></p> -<p id="t419" class="stm run hide_run"> <span class="key">return</span> <span class="nam">location_property</span><span class="strut"> </span></p> -<p id="t420" class="pln"><span class="strut"> </span></p> -<p id="t421" class="stm run hide_run"> <span class="op">@</span><span class="nam">staticmethod</span><span class="strut"> </span></p> -<p id="t422" class="pln"> <span class="key">def</span> <span class="nam">_list_of_steady_cells</span><span class="op">(</span><span class="nam">data_frame</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t423" class="pln"><span class="strut"> </span></p> -<p id="t424" class="stm run hide_run"> <span class="nam">list_of_cells</span> <span class="op">=</span> <span class="op">[</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t425" class="stm run hide_run"> <span class="nam">cumulative_distance</span> <span class="op">=</span> <span class="num">0</span><span class="strut"> </span></p> -<p id="t426" class="pln"><span class="strut"> </span></p> -<p id="t427" class="stm run hide_run"> <span class="key">for</span> <span class="nam">_</span><span class="op">,</span> <span class="nam">row</span> <span class="key">in</span> <span class="nam">data_frame</span><span class="op">.</span><span class="nam">iterrows</span><span class="op">(</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t428" class="pln"> <span class="com"># convert kilometers to meters</span><span class="strut"> </span></p> -<p id="t429" class="stm run hide_run"> <span class="nam">cell_length</span> <span class="op">=</span> <span class="num">1000</span><span class="op">*</span><span class="op">(</span><span class="nam">row</span><span class="op">[</span><span class="str">'CumlDistance_km'</span><span class="op">]</span> <span class="op">-</span> <span class="nam">cumulative_distance</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t430" class="stm run hide_run"> <span class="nam">cumulative_distance</span> <span class="op">=</span> <span class="nam">row</span><span class="op">[</span><span class="str">'CumlDistance_km'</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t431" class="pln"><span class="strut"> </span></p> -<p id="t432" class="stm run hide_run"> <span class="nam">cell_depth</span> <span class="op">=</span> <span class="nam">row</span><span class="op">[</span><span class="str">'Depth_m'</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t433" class="stm run hide_run"> <span class="nam">cell_discharge</span> <span class="op">=</span> <span class="nam">row</span><span class="op">[</span><span class="str">'Q_cms'</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t434" class="stm run hide_run"> <span class="nam">cell_longitudinal_velocity</span> <span class="op">=</span> <span class="nam">row</span><span class="op">[</span><span class="str">'Vmag_mps'</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t435" class="stm run hide_run"> <span class="nam">cell_lateral_velocity</span> <span class="op">=</span> <span class="nam">row</span><span class="op">[</span><span class="str">'Vvert_mps'</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t436" class="stm run hide_run"> <span class="nam">cell_vertical_velocity</span> <span class="op">=</span> <span class="nam">row</span><span class="op">[</span><span class="str">'Vlat_mps'</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t437" class="stm run hide_run"> <span class="nam">cell_shear_velocity</span> <span class="op">=</span> <span class="nam">row</span><span class="op">[</span><span class="str">'Ustar_mps'</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t438" class="stm run hide_run"> <span class="nam">cell_temperature</span> <span class="op">=</span> <span class="nam">row</span><span class="op">[</span><span class="str">'Temp_C'</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t439" class="pln"><span class="strut"> </span></p> -<p id="t440" class="stm run hide_run"> <span class="nam">hydraulic_cell</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t441" class="pln"> <span class="nam">SteadyStateHydraulicCell</span><span class="op">(</span><span class="nam">cell_length</span><span class="op">,</span> <span class="nam">cell_depth</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t442" class="pln"> <span class="nam">cell_discharge</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t443" class="pln"> <span class="nam">cell_longitudinal_velocity</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t444" class="pln"> <span class="nam">cell_lateral_velocity</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t445" class="pln"> <span class="nam">cell_vertical_velocity</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t446" class="pln"> <span class="nam">cell_shear_velocity</span><span class="op">,</span> <span class="nam">cell_temperature</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t447" class="pln"><span class="strut"> </span></p> -<p id="t448" class="stm run hide_run"> <span class="nam">list_of_cells</span><span class="op">.</span><span class="nam">append</span><span class="op">(</span><span class="nam">hydraulic_cell</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t449" class="pln"><span class="strut"> </span></p> -<p id="t450" class="stm run hide_run"> <span class="key">return</span> <span class="nam">list_of_cells</span><span class="strut"> </span></p> -<p id="t451" class="pln"><span class="strut"> </span></p> -<p id="t452" class="stm run hide_run"> <span class="op">@</span><span class="nam">staticmethod</span><span class="strut"> </span></p> -<p id="t453" class="pln"> <span class="key">def</span> <span class="nam">_list_of_unsteady_cells</span><span class="op">(</span><span class="nam">data_frame</span><span class="op">,</span> <span class="op">**</span><span class="nam">kwargs</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t454" class="pln"> <span class="str">"""Returns a list of UnsteadyHydraulicCell instances."""</span><span class="strut"> </span></p> -<p id="t455" class="pln"><span class="strut"> </span></p> -<p id="t456" class="pln"> <span class="com"># unpack the keyword arguments</span><span class="strut"> </span></p> -<p id="t457" class="stm run hide_run"> <span class="nam">start_time</span> <span class="op">=</span> <span class="nam">kwargs</span><span class="op">[</span><span class="str">'start_time'</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t458" class="stm run hide_run"> <span class="nam">simulation_clock</span> <span class="op">=</span> <span class="nam">kwargs</span><span class="op">[</span><span class="str">'simulation_clock'</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t459" class="stm run hide_run"> <span class="nam">simulation</span> <span class="op">=</span> <span class="nam">kwargs</span><span class="op">[</span><span class="str">'simulation'</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t460" class="pln"><span class="strut"> </span></p> -<p id="t461" class="pln"> <span class="com"># get the cell cumulative distance</span><span class="strut"> </span></p> -<p id="t462" class="stm run hide_run"> <span class="nam">grouped_by_time</span> <span class="op">=</span> <span class="nam">data_frame</span><span class="op">.</span><span class="nam">groupby</span><span class="op">(</span><span class="nam">axis</span><span class="op">=</span><span class="num">0</span><span class="op">,</span> <span class="nam">level</span><span class="op">=</span><span class="num">0</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t463" class="stm run hide_run"> <span class="nam">initial_time_step</span> <span class="op">=</span> <span class="nam">list</span><span class="op">(</span><span class="nam">grouped_by_time</span><span class="op">.</span><span class="nam">groups</span><span class="op">.</span><span class="nam">keys</span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t464" class="stm run hide_run"> <span class="nam">initial_group</span> <span class="op">=</span> <span class="nam">grouped_by_time</span><span class="op">.</span><span class="nam">get_group</span><span class="op">(</span><span class="nam">initial_time_step</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t465" class="stm run hide_run"> <span class="nam">initial_group</span><span class="op">.</span><span class="nam">index</span> <span class="op">=</span> <span class="nam">initial_group</span><span class="op">.</span><span class="nam">index</span><span class="op">.</span><span class="nam">droplevel</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t466" class="stm run hide_run"> <span class="nam">cumulative_distance_series</span> <span class="op">=</span> <span class="nam">initial_group</span><span class="op">[</span><span class="str">'CumlDistance_km'</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t467" class="pln"><span class="strut"> </span></p> -<p id="t468" class="stm run hide_run"> <span class="nam">cumulative_distance</span> <span class="op">=</span> <span class="num">0</span><span class="strut"> </span></p> -<p id="t469" class="pln"><span class="strut"> </span></p> -<p id="t470" class="stm run hide_run"> <span class="nam">list_of_cells</span> <span class="op">=</span> <span class="op">[</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t471" class="pln"><span class="strut"> </span></p> -<p id="t472" class="stm run hide_run"> <span class="nam">grouped_by_cell</span> <span class="op">=</span> <span class="nam">data_frame</span><span class="op">.</span><span class="nam">groupby</span><span class="op">(</span><span class="nam">axis</span><span class="op">=</span><span class="num">0</span><span class="op">,</span> <span class="nam">level</span><span class="op">=</span><span class="num">1</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t473" class="stm run hide_run"> <span class="key">for</span> <span class="nam">cell_number</span> <span class="key">in</span> <span class="nam">grouped_by_cell</span><span class="op">.</span><span class="nam">groups</span><span class="op">.</span><span class="nam">keys</span><span class="op">(</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t474" class="pln"><span class="strut"> </span></p> -<p id="t475" class="pln"> <span class="com"># get the cell length and add it to the cumulative distance</span><span class="strut"> </span></p> -<p id="t476" class="stm run hide_run"> <span class="nam">cell_length</span> <span class="op">=</span> <span class="num">1000</span> <span class="op">*</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t477" class="pln"> <span class="op">(</span><span class="nam">cumulative_distance_series</span><span class="op">[</span><span class="nam">cell_number</span><span class="op">]</span> <span class="op">-</span> <span class="nam">cumulative_distance</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t478" class="stm run hide_run"> <span class="nam">cumulative_distance</span> <span class="op">=</span> <span class="nam">cumulative_distance_series</span><span class="op">[</span><span class="nam">cell_number</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t479" class="pln"><span class="strut"> </span></p> -<p id="t480" class="stm run hide_run"> <span class="nam">cell_time_series</span> <span class="op">=</span> <span class="nam">grouped_by_cell</span><span class="op">.</span><span class="nam">get_group</span><span class="op">(</span><span class="nam">cell_number</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t481" class="stm run hide_run"> <span class="nam">cell_time_series</span><span class="op">.</span><span class="nam">index</span> <span class="op">=</span> <span class="nam">cell_time_series</span><span class="op">.</span><span class="nam">index</span><span class="op">.</span><span class="nam">droplevel</span><span class="op">(</span><span class="num">1</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t482" class="stm run hide_run"> <span class="nam">hydraulic_cell</span> <span class="op">=</span> <span class="nam">UnsteadyHydraulicCell</span><span class="op">(</span><span class="nam">cell_length</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t483" class="pln"> <span class="nam">cell_time_series</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t484" class="pln"> <span class="nam">start_time</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t485" class="pln"> <span class="nam">simulation_clock</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t486" class="pln"> <span class="nam">simulation</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t487" class="stm run hide_run"> <span class="nam">list_of_cells</span><span class="op">.</span><span class="nam">append</span><span class="op">(</span><span class="nam">hydraulic_cell</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t488" class="pln"><span class="strut"> </span></p> -<p id="t489" class="stm run hide_run"> <span class="key">return</span> <span class="nam">list_of_cells</span><span class="strut"> </span></p> -<p id="t490" class="pln"><span class="strut"> </span></p> -<p id="t491" class="stm run hide_run"> <span class="op">@</span><span class="nam">classmethod</span><span class="strut"> </span></p> -<p id="t492" class="pln"> <span class="key">def</span> <span class="nam">from_data_frame</span><span class="op">(</span><span class="nam">cls</span><span class="op">,</span> <span class="nam">data_frame</span><span class="op">,</span> <span class="op">**</span><span class="nam">kwargs</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t493" class="pln"> <span class="str">"""Creates an instance of this class from a Pandas DataFrame.</span><span class="strut"> </span></p> -<p id="t494" class="pln"><span class="strut"> </span></p> -<p id="t495" class="pln"><span class="str"> This method handles the creation of a steady or unsteady series of</span><span class="strut"> </span></p> -<p id="t496" class="pln"><span class="str"> cells, depending on the DataFrame passed. For an unsteady model, level</span><span class="strut"> </span></p> -<p id="t497" class="pln"><span class="str"> 0 of the MultiIndex is the time, and level 1 is the cell number.</span><span class="strut"> </span></p> -<p id="t498" class="pln"><span class="strut"> </span></p> -<p id="t499" class="pln"><span class="str"> Parameters</span><span class="strut"> </span></p> -<p id="t500" class="pln"><span class="str"> ----------</span><span class="strut"> </span></p> -<p id="t501" class="pln"><span class="str"> data_frame : pandas.DataFrame</span><span class="strut"> </span></p> -<p id="t502" class="pln"><span class="str"> Pandas DataFrame containing hydraulic information</span><span class="strut"> </span></p> -<p id="t503" class="pln"><span class="str"> **kwargs</span><span class="strut"> </span></p> -<p id="t504" class="pln"><span class="str"> These keyword arguments are required when initializing a series of</span><span class="strut"> </span></p> -<p id="t505" class="pln"><span class="str"> unsteady cells.</span><span class="strut"> </span></p> -<p id="t506" class="pln"><span class="str"> start_time : numpy.datetime64</span><span class="strut"> </span></p> -<p id="t507" class="pln"><span class="str"> Simulation start time.</span><span class="strut"> </span></p> -<p id="t508" class="pln"><span class="str"> simulation_clock : fluegg.simclock.SimulationClock</span><span class="strut"> </span></p> -<p id="t509" class="pln"><span class="str"> simulation : fluegg.simulation.Simulation</span><span class="strut"> </span></p> -<p id="t510" class="pln"><span class="strut"> </span></p> -<p id="t511" class="pln"><span class="strut"> </span></p> -<p id="t512" class="pln"><span class="str"> Returns</span><span class="strut"> </span></p> -<p id="t513" class="pln"><span class="str"> -------</span><span class="strut"> </span></p> -<p id="t514" class="pln"><span class="str"> SeriesOfHydraulicCells</span><span class="strut"> </span></p> -<p id="t515" class="pln"><span class="strut"> </span></p> -<p id="t516" class="pln"><span class="str"> See Also</span><span class="strut"> </span></p> -<p id="t517" class="pln"><span class="str"> --------</span><span class="strut"> </span></p> -<p id="t518" class="pln"><span class="str"> SteadyStateHydraulicCell</span><span class="strut"> </span></p> -<p id="t519" class="pln"><span class="str"> UnsteadyHydraulicCell</span><span class="strut"> </span></p> -<p id="t520" class="pln"><span class="strut"> </span></p> -<p id="t521" class="pln"><span class="str"> Notes</span><span class="strut"> </span></p> -<p id="t522" class="pln"><span class="str"> -----</span><span class="strut"> </span></p> -<p id="t523" class="pln"><span class="str"> The method initializes steady or unsteady cells based on the number of</span><span class="strut"> </span></p> -<p id="t524" class="pln"><span class="str"> levels in the index of `data_frame`. Steady cells are initialized if</span><span class="strut"> </span></p> -<p id="t525" class="pln"><span class="str"> there is one level, and unsteady cells are initialized if there are</span><span class="strut"> </span></p> -<p id="t526" class="pln"><span class="str"> two.</span><span class="strut"> </span></p> -<p id="t527" class="pln"><span class="strut"> </span></p> -<p id="t528" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t529" class="pln"><span class="strut"> </span></p> -<p id="t530" class="stm run hide_run"> <span class="key">if</span> <span class="nam">data_frame</span><span class="op">.</span><span class="nam">index</span><span class="op">.</span><span class="nam">nlevels</span> <span class="op">==</span> <span class="num">1</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t531" class="stm run hide_run"> <span class="nam">list_of_cells</span> <span class="op">=</span> <span class="nam">cls</span><span class="op">.</span><span class="nam">_list_of_steady_cells</span><span class="op">(</span><span class="nam">data_frame</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t532" class="stm run hide_run"> <span class="key">elif</span> <span class="nam">data_frame</span><span class="op">.</span><span class="nam">index</span><span class="op">.</span><span class="nam">nlevels</span> <span class="op">==</span> <span class="num">2</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t533" class="stm run hide_run"> <span class="nam">list_of_cells</span> <span class="op">=</span> <span class="nam">cls</span><span class="op">.</span><span class="nam">_list_of_unsteady_cells</span><span class="op">(</span><span class="nam">data_frame</span><span class="op">,</span> <span class="op">**</span><span class="nam">kwargs</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t534" class="pln"> <span class="key">else</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t535" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="str">"Unrecognized DataFrame format"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t536" class="pln"><span class="strut"> </span></p> -<p id="t537" class="stm run hide_run"> <span class="key">return</span> <span class="nam">cls</span><span class="op">(</span><span class="nam">list_of_cells</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t538" class="pln"><span class="strut"> </span></p> -<p id="t539" class="stm run hide_run"> <span class="key">def</span> <span class="nam">hydraulic_results</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">position</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t540" class="pln"> <span class="str">"""Returns the results of a hydraulic simulation at the given positions</span><span class="strut"> </span></p> -<p id="t541" class="pln"><span class="str"> in space.</span><span class="strut"> </span></p> -<p id="t542" class="pln"><span class="strut"> </span></p> -<p id="t543" class="pln"><span class="str"> Position is an n by 3 numpy array, where n is the number of positions</span><span class="strut"> </span></p> -<p id="t544" class="pln"><span class="str"> requested (along axis=0).</span><span class="strut"> </span></p> -<p id="t545" class="pln"><span class="strut"> </span></p> -<p id="t546" class="pln"><span class="str"> The indices along axis=1 are:</span><span class="strut"> </span></p> -<p id="t547" class="pln"><span class="str"> 0 - The position in the longitudinal, or x, direction in m. The</span><span class="strut"> </span></p> -<p id="t548" class="pln"><span class="str"> positive direction is downstream.</span><span class="strut"> </span></p> -<p id="t549" class="pln"><span class="str"> 1 - The position in the lateral, or y, direction in m. The positive</span><span class="strut"> </span></p> -<p id="t550" class="pln"><span class="str"> direction is from the right bank.</span><span class="strut"> </span></p> -<p id="t551" class="pln"><span class="str"> 2 - The position in the vertical, or z, direction in m. The</span><span class="strut"> </span></p> -<p id="t552" class="pln"><span class="str"> positive direction is away from the bed.</span><span class="strut"> </span></p> -<p id="t553" class="pln"><span class="strut"> </span></p> -<p id="t554" class="pln"><span class="str"> In this coordinate system, the datum (0, 0, 0) is the point at the</span><span class="strut"> </span></p> -<p id="t555" class="pln"><span class="str"> upstream, right bank, water surface of the first cell.</span><span class="strut"> </span></p> -<p id="t556" class="pln"><span class="strut"> </span></p> -<p id="t557" class="pln"><span class="str"> position[:, 0] is the position in the longitudinal, or x, direction,</span><span class="strut"> </span></p> -<p id="t558" class="pln"><span class="str"> position[:, 1] is the position in the lateral, or y, direction, and</span><span class="strut"> </span></p> -<p id="t559" class="pln"><span class="str"> position[:, 2] is the position in the vertical, or z, direction.</span><span class="strut"> </span></p> -<p id="t560" class="pln"><span class="strut"> </span></p> -<p id="t561" class="pln"><span class="str"> :param position: Array containing position of results</span><span class="strut"> </span></p> -<p id="t562" class="pln"><span class="str"> :return: HydraulicResults</span><span class="strut"> </span></p> -<p id="t563" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t564" class="pln"><span class="strut"> </span></p> -<p id="t565" class="stm run hide_run"> <span class="nam">longitudinal_location</span> <span class="op">=</span> <span class="nam">position</span><span class="op">[</span><span class="op">:</span><span class="op">,</span> <span class="num">0</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t566" class="pln"><span class="strut"> </span></p> -<p id="t567" class="stm run hide_run"> <span class="nam">depth</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_cell_property_by_location</span><span class="op">(</span><span class="str">'depth'</span><span class="op">,</span> <span class="nam">longitudinal_location</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t568" class="stm run hide_run"> <span class="nam">discharge</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_cell_property_by_location</span><span class="op">(</span><span class="strut"> </span></p> -<p id="t569" class="pln"> <span class="str">'discharge'</span><span class="op">,</span> <span class="nam">longitudinal_location</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t570" class="stm run hide_run"> <span class="nam">mean_xs_velocity</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_cell_property_by_location</span><span class="op">(</span><span class="strut"> </span></p> -<p id="t571" class="pln"> <span class="str">'mean_xs_velocity'</span><span class="op">,</span> <span class="nam">longitudinal_location</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t572" class="stm run hide_run"> <span class="nam">mean_lat_velocity</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_cell_property_by_location</span><span class="op">(</span><span class="strut"> </span></p> -<p id="t573" class="pln"> <span class="str">'mean_lat_velocity'</span><span class="op">,</span> <span class="nam">longitudinal_location</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t574" class="stm run hide_run"> <span class="nam">mean_long_velocity</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_cell_property_by_location</span><span class="op">(</span><span class="strut"> </span></p> -<p id="t575" class="pln"> <span class="str">'mean_long_velocity'</span><span class="op">,</span> <span class="nam">longitudinal_location</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t576" class="stm run hide_run"> <span class="nam">mean_vert_velocity</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_cell_property_by_location</span><span class="op">(</span><span class="strut"> </span></p> -<p id="t577" class="pln"> <span class="str">'mean_vert_velocity'</span><span class="op">,</span> <span class="nam">longitudinal_location</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t578" class="stm run hide_run"> <span class="nam">shear_velocity</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_cell_property_by_location</span><span class="op">(</span><span class="strut"> </span></p> -<p id="t579" class="pln"> <span class="str">'shear_velocity'</span><span class="op">,</span> <span class="nam">longitudinal_location</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t580" class="stm run hide_run"> <span class="nam">temperature</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_cell_property_by_location</span><span class="op">(</span><span class="strut"> </span></p> -<p id="t581" class="pln"> <span class="str">'temperature'</span><span class="op">,</span> <span class="nam">longitudinal_location</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t582" class="pln"><span class="strut"> </span></p> -<p id="t583" class="stm run hide_run"> <span class="nam">area</span> <span class="op">=</span> <span class="nam">discharge</span> <span class="op">/</span> <span class="nam">mean_xs_velocity</span><span class="strut"> </span></p> -<p id="t584" class="stm run hide_run"> <span class="nam">width</span> <span class="op">=</span> <span class="nam">area</span> <span class="op">/</span> <span class="nam">depth</span><span class="strut"> </span></p> -<p id="t585" class="pln"><span class="strut"> </span></p> -<p id="t586" class="stm run hide_run"> <span class="nam">viscosity</span> <span class="op">=</span> <span class="nam">calc_water_viscosity</span><span class="op">(</span><span class="nam">temperature</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t587" class="stm run hide_run"> <span class="nam">density</span> <span class="op">=</span> <span class="nam">calc_water_density</span><span class="op">(</span><span class="nam">temperature</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t588" class="pln"><span class="strut"> </span></p> -<p id="t589" class="stm run hide_run"> <span class="nam">lateral_location</span> <span class="op">=</span> <span class="nam">position</span><span class="op">[</span><span class="op">:</span><span class="op">,</span> <span class="num">1</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t590" class="stm run hide_run"> <span class="nam">vertical_location</span> <span class="op">=</span> <span class="nam">position</span><span class="op">[</span><span class="op">:</span><span class="op">,</span> <span class="num">2</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t591" class="stm run hide_run"> <span class="nam">streamwise_velocity</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t592" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">_calc_longitudinal_velocity</span><span class="op">(</span><span class="nam">vertical_location</span><span class="op">,</span> <span class="nam">shear_velocity</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t593" class="pln"> <span class="nam">depth</span><span class="op">,</span> <span class="nam">mean_long_velocity</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t594" class="pln"> <span class="nam">viscosity</span><span class="op">,</span> <span class="nam">lateral_location</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t595" class="pln"> <span class="nam">width</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t596" class="pln"><span class="strut"> </span></p> -<p id="t597" class="pln"> <span class="com"># set the streamwise velocities above the water surface to nan</span><span class="strut"> </span></p> -<p id="t598" class="stm run hide_run"> <span class="nam">above_water_surface</span> <span class="op">=</span> <span class="nam">depth</span> <span class="op"><</span> <span class="nam">vertical_location</span><span class="strut"> </span></p> -<p id="t599" class="stm run hide_run"> <span class="nam">streamwise_velocity</span><span class="op">[</span><span class="nam">above_water_surface</span><span class="op">]</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">nan</span><span class="strut"> </span></p> -<p id="t600" class="pln"><span class="strut"> </span></p> -<p id="t601" class="stm run hide_run"> <span class="nam">hydraulic_data</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">stack</span><span class="op">(</span><span class="op">[</span><span class="nam">depth</span><span class="op">,</span> <span class="nam">width</span><span class="op">,</span> <span class="nam">temperature</span><span class="op">,</span> <span class="nam">viscosity</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t602" class="pln"> <span class="nam">density</span><span class="op">,</span> <span class="nam">streamwise_velocity</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t603" class="pln"> <span class="nam">shear_velocity</span><span class="op">,</span> <span class="nam">mean_lat_velocity</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t604" class="pln"> <span class="nam">mean_vert_velocity</span><span class="op">]</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t605" class="pln"> <span class="nam">axis</span><span class="op">=</span><span class="num">1</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t606" class="pln"><span class="strut"> </span></p> -<p id="t607" class="stm run hide_run"> <span class="key">return</span> <span class="nam">HydraulicResults</span><span class="op">(</span><span class="nam">hydraulic_data</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t608" class="pln"><span class="strut"> </span></p> -<p id="t609" class="stm run hide_run"> <span class="key">def</span> <span class="nam">to_data_frame</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t610" class="pln"> <span class="str">"""Create a Pandas DataFrame from information in this instance.</span><span class="strut"> </span></p> -<p id="t611" class="pln"><span class="strut"> </span></p> -<p id="t612" class="pln"><span class="str"> Returns</span><span class="strut"> </span></p> -<p id="t613" class="pln"><span class="str"> -------</span><span class="strut"> </span></p> -<p id="t614" class="pln"><span class="str"> pandas.DataFrame</span><span class="strut"> </span></p> -<p id="t615" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t616" class="pln"><span class="strut"> </span></p> -<p id="t617" class="stm mis"> <span class="key">if</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_cells</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="op">,</span> <span class="nam">SteadyStateHydraulicCell</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t618" class="pln"><span class="strut"> </span></p> -<p id="t619" class="stm mis"> <span class="nam">columns</span> <span class="op">=</span> <span class="op">[</span><span class="str">'CumlDistance_km'</span><span class="op">,</span> <span class="str">'Depth_m'</span><span class="op">,</span> <span class="str">'Q_cms'</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t620" class="pln"> <span class="str">'Vmag_mps'</span><span class="op">,</span> <span class="str">'Vvert_mps'</span><span class="op">,</span> <span class="str">'Vlat_mps'</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t621" class="pln"> <span class="str">'Ustar_mps'</span><span class="op">,</span> <span class="str">'Temp_C'</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t622" class="stm mis"> <span class="nam">data_dict</span> <span class="op">=</span> <span class="nam">dict</span><span class="op">(</span><span class="nam">zip</span><span class="op">(</span><span class="nam">columns</span><span class="op">,</span> <span class="op">[</span><span class="op">[</span><span class="op">]</span> <span class="key">for</span> <span class="nam">_</span> <span class="key">in</span> <span class="nam">range</span><span class="op">(</span><span class="nam">len</span><span class="op">(</span><span class="nam">columns</span><span class="op">)</span><span class="op">)</span><span class="op">]</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t623" class="pln"><span class="strut"> </span></p> -<p id="t624" class="stm mis"> <span class="key">for</span> <span class="nam">cell</span> <span class="key">in</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_cells</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t625" class="pln"><span class="strut"> </span></p> -<p id="t626" class="stm mis"> <span class="nam">data_dict</span><span class="op">[</span><span class="str">'CumlDistance_km'</span><span class="op">]</span><span class="op">.</span><span class="nam">append</span><span class="op">(</span><span class="nam">cell</span><span class="op">.</span><span class="nam">length</span><span class="op">(</span><span class="op">)</span> <span class="op">/</span> <span class="num">1000</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t627" class="stm mis"> <span class="nam">data_dict</span><span class="op">[</span><span class="str">'Depth_m'</span><span class="op">]</span><span class="op">.</span><span class="nam">append</span><span class="op">(</span><span class="nam">cell</span><span class="op">.</span><span class="nam">depth</span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t628" class="stm mis"> <span class="nam">data_dict</span><span class="op">[</span><span class="str">'Q_cms'</span><span class="op">]</span><span class="op">.</span><span class="nam">append</span><span class="op">(</span><span class="nam">cell</span><span class="op">.</span><span class="nam">discharge</span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t629" class="stm mis"> <span class="nam">data_dict</span><span class="op">[</span><span class="str">'Vmag_mps'</span><span class="op">]</span><span class="op">.</span><span class="nam">append</span><span class="op">(</span><span class="nam">cell</span><span class="op">.</span><span class="nam">mean_xs_velocity</span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t630" class="stm mis"> <span class="nam">data_dict</span><span class="op">[</span><span class="str">'Vvert_mps'</span><span class="op">]</span><span class="op">.</span><span class="nam">append</span><span class="op">(</span><span class="nam">cell</span><span class="op">.</span><span class="nam">mean_vert_velocity</span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t631" class="stm mis"> <span class="nam">data_dict</span><span class="op">[</span><span class="str">'Vlat_mps'</span><span class="op">]</span><span class="op">.</span><span class="nam">append</span><span class="op">(</span><span class="nam">cell</span><span class="op">.</span><span class="nam">mean_lat_velocity</span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t632" class="stm mis"> <span class="nam">data_dict</span><span class="op">[</span><span class="str">'Ustar_mps'</span><span class="op">]</span><span class="op">.</span><span class="nam">append</span><span class="op">(</span><span class="nam">cell</span><span class="op">.</span><span class="nam">shear_velocity</span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t633" class="stm mis"> <span class="nam">data_dict</span><span class="op">[</span><span class="str">'Temp_C'</span><span class="op">]</span><span class="op">.</span><span class="nam">append</span><span class="op">(</span><span class="nam">cell</span><span class="op">.</span><span class="nam">temperature</span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t634" class="pln"><span class="strut"> </span></p> -<p id="t635" class="stm mis"> <span class="nam">cell_numbers</span> <span class="op">=</span> <span class="nam">range</span><span class="op">(</span><span class="num">1</span><span class="op">,</span> <span class="nam">len</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_cells</span><span class="op">)</span> <span class="op">+</span> <span class="num">1</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t636" class="stm mis"> <span class="nam">df</span> <span class="op">=</span> <span class="nam">pd</span><span class="op">.</span><span class="nam">DataFrame</span><span class="op">(</span><span class="nam">data</span><span class="op">=</span><span class="nam">data_dict</span><span class="op">,</span> <span class="nam">index</span><span class="op">=</span><span class="nam">cell_numbers</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t637" class="stm mis"> <span class="nam">df</span><span class="op">[</span><span class="str">'CumlDistance_km'</span><span class="op">]</span> <span class="op">=</span> <span class="nam">df</span><span class="op">[</span><span class="str">'CumlDistance_km'</span><span class="op">]</span><span class="op">.</span><span class="nam">cumsum</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t638" class="pln"><span class="strut"> </span></p> -<p id="t639" class="stm mis"> <span class="nam">df</span><span class="op">.</span><span class="nam">index</span><span class="op">.</span><span class="nam">name</span> <span class="op">=</span> <span class="str">'CellNumber'</span><span class="strut"> </span></p> -<p id="t640" class="pln"><span class="strut"> </span></p> -<p id="t641" class="stm mis"> <span class="key">elif</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_cells</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="op">,</span> <span class="nam">UnsteadyHydraulicCell</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t642" class="pln"><span class="strut"> </span></p> -<p id="t643" class="stm mis"> <span class="nam">frames</span> <span class="op">=</span> <span class="op">[</span><span class="nam">cell</span><span class="op">.</span><span class="nam">to_data_frame</span><span class="op">(</span><span class="op">)</span> <span class="key">for</span> <span class="nam">cell</span> <span class="key">in</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_cells</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t644" class="stm mis"> <span class="nam">df</span> <span class="op">=</span> <span class="nam">pd</span><span class="op">.</span><span class="nam">concat</span><span class="op">(</span><span class="nam">frames</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t645" class="pln"> <span class="nam">keys</span><span class="op">=</span><span class="nam">range</span><span class="op">(</span><span class="num">1</span><span class="op">,</span> <span class="nam">len</span><span class="op">(</span><span class="nam">frames</span><span class="op">)</span><span class="op">+</span><span class="num">1</span><span class="op">)</span><span class="op">)</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t646" class="pln"> <span class="op">.</span><span class="nam">swaplevel</span><span class="op">(</span><span class="op">)</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t647" class="pln"> <span class="op">.</span><span class="nam">sort_index</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t648" class="pln"><span class="strut"> </span></p> -<p id="t649" class="pln"> <span class="key">else</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t650" class="stm mis"> <span class="key">raise</span> <span class="nam">RuntimeError</span><span class="op">(</span><span class="str">"Unknown subclass of HydraulicCell"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t651" class="pln"><span class="strut"> </span></p> -<p id="t652" class="stm mis"> <span class="key">return</span> <span class="nam">df</span><span class="strut"> </span></p> -<p id="t653" class="pln"><span class="strut"> </span></p> -<p id="t654" class="stm run hide_run"> <span class="key">def</span> <span class="nam">cell_edges</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t655" class="pln"> <span class="str">"""Returns the edges of each of the cells</span><span class="strut"> </span></p> -<p id="t656" class="pln"><span class="strut"> </span></p> -<p id="t657" class="pln"><span class="str"> :return: Edges of the hydraulic cells</span><span class="strut"> </span></p> -<p id="t658" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t659" class="stm mis"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_cell_edges</span><span class="strut"> </span></p> -<p id="t660" class="pln"><span class="strut"> </span></p> -<p id="t661" class="pln"><span class="strut"> </span></p> -<p id="t662" class="stm run hide_run"><span class="key">class</span> <span class="nam">RoughBottomSeriesOfHydraulicCells</span><span class="op">(</span><span class="nam">SeriesOfHydraulicCells</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t663" class="pln"> <span class="str">"""Series of hydraulic cells with velocity velocity calculated under a</span><span class="strut"> </span></p> -<p id="t664" class="pln"><span class="str"> rough bottom assumption</span><span class="strut"> </span></p> -<p id="t665" class="pln"><span class="strut"> </span></p> -<p id="t666" class="pln"><span class="str"> Parameters</span><span class="strut"> </span></p> -<p id="t667" class="pln"><span class="str"> ----------</span><span class="strut"> </span></p> -<p id="t668" class="pln"><span class="str"> list_of_cells : list</span><span class="strut"> </span></p> -<p id="t669" class="pln"><span class="str"> List containing HydraulicCell elements.</span><span class="strut"> </span></p> -<p id="t670" class="pln"><span class="strut"> </span></p> -<p id="t671" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t672" class="pln"><span class="strut"> </span></p> -<p id="t673" class="pln"><span class="strut"> </span></p> -<p id="t674" class="stm run hide_run"> <span class="op">@</span><span class="nam">staticmethod</span><span class="strut"> </span></p> -<p id="t675" class="pln"> <span class="key">def</span> <span class="nam">_calc_roughness_height</span><span class="op">(</span><span class="nam">depth</span><span class="op">,</span> <span class="nam">mean_xs_velocity</span><span class="op">,</span> <span class="nam">shear_velocity</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t676" class="pln"> <span class="str">"""Calculate roughness height (kc), in meters</span><span class="strut"> </span></p> -<p id="t677" class="pln"><span class="strut"> </span></p> -<p id="t678" class="pln"><span class="str"> :param depth: Depth of water column in m</span><span class="strut"> </span></p> -<p id="t679" class="pln"><span class="str"> :param mean_xs_velocity: Mean cross-section velocity in m/s</span><span class="strut"> </span></p> -<p id="t680" class="pln"><span class="str"> :param shear_velocity: Shear velocity in ms/</span><span class="strut"> </span></p> -<p id="t681" class="pln"><span class="str"> :return: Roughness height in m</span><span class="strut"> </span></p> -<p id="t682" class="pln"><span class="strut"> </span></p> -<p id="t683" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t684" class="stm run hide_run"> <span class="key">return</span> <span class="num">11</span> <span class="op">*</span> <span class="nam">depth</span> <span class="op">/</span> <span class="nam">np</span><span class="op">.</span><span class="nam">exp</span><span class="op">(</span><span class="op">(</span><span class="nam">mean_xs_velocity</span> <span class="op">*</span> <span class="nam">VON_KARMAN_CONSTANT</span><span class="op">)</span> <span class="op">/</span><span class="strut"> </span></p> -<p id="t685" class="pln"> <span class="nam">shear_velocity</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t686" class="pln"><span class="strut"> </span></p> -<p id="t687" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_calc_log_law_velocity</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">vertical_location</span><span class="op">,</span> <span class="nam">shear_velocity</span><span class="op">,</span> <span class="nam">depth</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t688" class="pln"> <span class="nam">mean_xs_velocity</span><span class="op">,</span> <span class="nam">viscosity</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t689" class="pln"><span class="strut"> </span></p> -<p id="t690" class="stm run hide_run"> <span class="nam">roughness_height</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_calc_roughness_height</span><span class="op">(</span><span class="strut"> </span></p> -<p id="t691" class="pln"> <span class="nam">depth</span><span class="op">,</span> <span class="nam">mean_xs_velocity</span><span class="op">,</span> <span class="nam">shear_velocity</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t692" class="pln"><span class="strut"> </span></p> -<p id="t693" class="stm run hide_run"> <span class="nam">log_law_velocity</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t694" class="pln"> <span class="nam">shear_velocity</span> <span class="op">*</span> <span class="op">(</span><span class="op">(</span><span class="num">1</span><span class="op">/</span><span class="nam">VON_KARMAN_CONSTANT</span><span class="op">)</span> <span class="op">*</span><span class="strut"> </span></p> -<p id="t695" class="pln"> <span class="nam">np</span><span class="op">.</span><span class="nam">log</span><span class="op">(</span><span class="nam">vertical_location</span> <span class="op">/</span> <span class="nam">roughness_height</span><span class="op">)</span> <span class="op">+</span><span class="strut"> </span></p> -<p id="t696" class="pln"> <span class="num">8.5</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t697" class="pln"><span class="strut"> </span></p> -<p id="t698" class="stm run hide_run"> <span class="key">return</span> <span class="nam">log_law_velocity</span><span class="strut"> </span></p> -<p id="t699" class="pln"><span class="strut"> </span></p> -<p id="t700" class="pln"><span class="strut"> </span></p> -<p id="t701" class="stm run hide_run"><span class="key">class</span> <span class="nam">SmoothBottomSeriesOfHydraulicCells</span><span class="op">(</span><span class="nam">SeriesOfHydraulicCells</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t702" class="pln"> <span class="str">"""Not implemented. Fails unit tests.</span><span class="strut"> </span></p> -<p id="t703" class="pln"><span class="strut"> </span></p> -<p id="t704" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t705" class="pln"><span class="strut"> </span></p> -<p id="t706" class="stm run hide_run"> <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="op">*</span><span class="nam">args</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t707" class="stm mis"> <span class="key">raise</span> <span class="nam">NotImplementedError</span><span class="op">(</span><span class="str">"This class is not implemented."</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t708" class="pln"><span class="strut"> </span></p> -<p id="t709" class="pln"><span class="strut"> </span></p> -<p id="t710" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_calc_log_law_velocity</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">distance_above_bed</span><span class="op">,</span> <span class="nam">shear_velocity</span><span class="op">,</span> <span class="nam">depth</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t711" class="pln"> <span class="nam">mean_xs_velocity</span><span class="op">,</span> <span class="nam">viscosity</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t712" class="pln"><span class="strut"> </span></p> -<p id="t713" class="stm mis"> <span class="nam">log_law_velocity</span> <span class="op">=</span> <span class="nam">shear_velocity</span> <span class="op">*</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t714" class="pln"> <span class="op">(</span><span class="num">1</span> <span class="op">/</span> <span class="nam">VON_KARMAN_CONSTANT</span> <span class="op">*</span> <span class="nam">np</span><span class="op">.</span><span class="nam">log</span><span class="op">(</span><span class="nam">shear_velocity</span> <span class="op">*</span><span class="strut"> </span></p> -<p id="t715" class="pln"> <span class="nam">distance_above_bed</span> <span class="op">/</span> <span class="nam">viscosity</span><span class="op">)</span> <span class="op">+</span><span class="strut"> </span></p> -<p id="t716" class="pln"> <span class="num">5.5</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t717" class="pln"><span class="strut"> </span></p> -<p id="t718" class="stm mis"> <span class="key">return</span> <span class="nam">log_law_velocity</span><span class="strut"> </span></p> -<p id="t719" class="pln"><span class="strut"> </span></p> -<p id="t720" class="pln"><span class="strut"> </span></p> -<p id="t721" class="stm run hide_run"><span class="key">def</span> <span class="nam">from_csv</span><span class="op">(</span><span class="nam">path</span><span class="op">,</span> <span class="nam">bed_roughness</span><span class="op">=</span><span class="str">'rough'</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t722" class="pln"> <span class="str">"""Construct a SeriesOfHydraulicCells from a CSV file.</span><span class="strut"> </span></p> -<p id="t723" class="pln"><span class="strut"> </span></p> -<p id="t724" class="pln"><span class="str"> The CSV file must contain the following columns</span><span class="strut"> </span></p> -<p id="t725" class="pln"><span class="strut"> </span></p> -<p id="t726" class="pln"><span class="str"> Column name Description</span><span class="strut"> </span></p> -<p id="t727" class="pln"><span class="str"> ----------- -----------</span><span class="strut"> </span></p> -<p id="t728" class="pln"><span class="str"> CellNumber Cell number, integer 1 to inf</span><span class="strut"> </span></p> -<p id="t729" class="pln"><span class="str"> CumlDistance_km Cumulative distance along the channel of the end of the</span><span class="strut"> </span></p> -<p id="t730" class="pln"><span class="str"> cell in km</span><span class="strut"> </span></p> -<p id="t731" class="pln"><span class="str"> Depth_m Depth of the cell in m</span><span class="strut"> </span></p> -<p id="t732" class="pln"><span class="str"> Q_cms Discharge of the cell in m**3/s</span><span class="strut"> </span></p> -<p id="t733" class="pln"><span class="str"> Vmag_mps Cross-section average velocity in m/s</span><span class="strut"> </span></p> -<p id="t734" class="pln"><span class="str"> Vvert_mps Vertical component of velocity in m/s</span><span class="strut"> </span></p> -<p id="t735" class="pln"><span class="str"> Vlat_mps Lateral component of velocity in m/s</span><span class="strut"> </span></p> -<p id="t736" class="pln"><span class="str"> Ustar_mps Shear velocity in m/s</span><span class="strut"> </span></p> -<p id="t737" class="pln"><span class="str"> Temp_C Temperature in degrees Celsius</span><span class="strut"> </span></p> -<p id="t738" class="pln"><span class="strut"> </span></p> -<p id="t739" class="pln"><span class="str"> The contents of a CSV file representing a reach may look like this.</span><span class="strut"> </span></p> -<p id="t740" class="pln"><span class="str"> CellNumber,CumlDistance_km,Depth_m,Q_cms,Vmag_mps,Vvert_mps,Vlat_mps,</span><span class="strut"> </span></p> -<p id="t741" class="pln"><span class="str"> Ustar_mps,Temp_C</span><span class="strut"> </span></p> -<p id="t742" class="pln"><span class="str"> 1,20,1,10,1,0,0,0.08,19</span><span class="strut"> </span></p> -<p id="t743" class="pln"><span class="str"> 2,40,2,20,2,0,0,0.08,20</span><span class="strut"> </span></p> -<p id="t744" class="pln"><span class="str"> 3,60,3,30,3,0,0,0.08,21</span><span class="strut"> </span></p> -<p id="t745" class="pln"><span class="str"> 4,80,4,40,4,0,0,0.08,22</span><span class="strut"> </span></p> -<p id="t746" class="pln"><span class="str"> 5,100,5,50,5,0,0,0.08,23</span><span class="strut"> </span></p> -<p id="t747" class="pln"><span class="strut"> </span></p> -<p id="t748" class="pln"><span class="str"> This 100 km reach has 5 cells and the discharge (Q_cms) increases from 10</span><span class="strut"> </span></p> -<p id="t749" class="pln"><span class="str"> to 50 m**3/s.</span><span class="strut"> </span></p> -<p id="t750" class="pln"><span class="strut"> </span></p> -<p id="t751" class="pln"><span class="str"> :param path: Path to CSV file</span><span class="strut"> </span></p> -<p id="t752" class="pln"><span class="str"> :type path: str</span><span class="strut"> </span></p> -<p id="t753" class="pln"><span class="str"> :param bed_roughness: 'rough' or 'smooth'</span><span class="strut"> </span></p> -<p id="t754" class="pln"><span class="str"> :type bed_roughness: str</span><span class="strut"> </span></p> -<p id="t755" class="pln"><span class="str"> :return: SeriesOfHydraulicCells</span><span class="strut"> </span></p> -<p id="t756" class="pln"><span class="strut"> </span></p> -<p id="t757" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t758" class="pln"><span class="strut"> </span></p> -<p id="t759" class="stm run hide_run"> <span class="nam">input_df</span> <span class="op">=</span> <span class="nam">pd</span><span class="op">.</span><span class="nam">read_csv</span><span class="op">(</span><span class="nam">path</span><span class="op">,</span> <span class="nam">index_col</span><span class="op">=</span><span class="num">0</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t760" class="pln"><span class="strut"> </span></p> -<p id="t761" class="stm run hide_run"> <span class="key">if</span> <span class="nam">bed_roughness</span> <span class="op">==</span> <span class="str">'rough'</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t762" class="stm run hide_run"> <span class="nam">cls</span> <span class="op">=</span> <span class="nam">RoughBottomSeriesOfHydraulicCells</span><span class="strut"> </span></p> -<p id="t763" class="stm mis"> <span class="key">elif</span> <span class="nam">bed_roughness</span> <span class="op">==</span> <span class="str">'smooth'</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t764" class="stm mis"> <span class="nam">cls</span> <span class="op">=</span> <span class="nam">SmoothBottomSeriesOfHydraulicCells</span><span class="strut"> </span></p> -<p id="t765" class="pln"> <span class="key">else</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t766" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="str">"Unknown bed roughness"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t767" class="pln"><span class="strut"> </span></p> -<p id="t768" class="stm run hide_run"> <span class="key">return</span> <span class="nam">cls</span><span class="op">.</span><span class="nam">from_data_frame</span><span class="op">(</span><span class="nam">input_df</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t769" class="pln"><span class="strut"> </span></p> -<p id="t770" class="pln"><span class="strut"> </span></p> -<p id="t771" class="stm run hide_run"><span class="key">class</span> <span class="nam">HydraulicResults</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t772" class="pln"> <span class="str">"""Data structure containing hydraulic results from a hydraulic model</span><span class="strut"> </span></p> -<p id="t773" class="pln"><span class="str"> simulation.</span><span class="strut"> </span></p> -<p id="t774" class="pln"><span class="strut"> </span></p> -<p id="t775" class="pln"><span class="str"> Instantiated from SeriesOfHydraulicCells.hydraulic_results(). Not to be</span><span class="strut"> </span></p> -<p id="t776" class="pln"><span class="str"> instantiated elsewhere.</span><span class="strut"> </span></p> -<p id="t777" class="pln"><span class="strut"> </span></p> -<p id="t778" class="pln"><span class="str"> See Also</span><span class="strut"> </span></p> -<p id="t779" class="pln"><span class="str"> --------</span><span class="strut"> </span></p> -<p id="t780" class="pln"><span class="str"> SeriesOfHydraulicCells.hydraulic_results()</span><span class="strut"> </span></p> -<p id="t781" class="pln"><span class="strut"> </span></p> -<p id="t782" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t783" class="pln"><span class="strut"> </span></p> -<p id="t784" class="stm run hide_run"> <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">hydraulic_data</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t785" class="pln"> <span class="str">"""Initialize self. See help(type(self)) for accurate signature."""</span><span class="strut"> </span></p> -<p id="t786" class="pln"><span class="strut"> </span></p> -<p id="t787" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_hydraulic_data</span> <span class="op">=</span> <span class="nam">hydraulic_data</span><span class="strut"> </span></p> -<p id="t788" class="pln"><span class="strut"> </span></p> -<p id="t789" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_depth_index</span> <span class="op">=</span> <span class="num">0</span><span class="strut"> </span></p> -<p id="t790" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_width_index</span> <span class="op">=</span> <span class="num">1</span><span class="strut"> </span></p> -<p id="t791" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_temperature_index</span> <span class="op">=</span> <span class="num">2</span><span class="strut"> </span></p> -<p id="t792" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_viscosity_index</span> <span class="op">=</span> <span class="num">3</span><span class="strut"> </span></p> -<p id="t793" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_density_index</span> <span class="op">=</span> <span class="num">4</span><span class="strut"> </span></p> -<p id="t794" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_streamwise_velocity_index</span> <span class="op">=</span> <span class="num">5</span><span class="strut"> </span></p> -<p id="t795" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_shear_velocity_index</span> <span class="op">=</span> <span class="num">6</span><span class="strut"> </span></p> -<p id="t796" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_lateral_velocity_index</span> <span class="op">=</span> <span class="num">7</span><span class="strut"> </span></p> -<p id="t797" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_vertical_velocity_index</span> <span class="op">=</span> <span class="num">8</span><span class="strut"> </span></p> -<p id="t798" class="pln"><span class="strut"> </span></p> -<p id="t799" class="stm run hide_run"> <span class="key">def</span> <span class="nam">depth</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t800" class="pln"> <span class="str">"""Returns the depth of the water column at a given position.</span><span class="strut"> </span></p> -<p id="t801" class="pln"><span class="strut"> </span></p> -<p id="t802" class="pln"><span class="str"> Returns a numpy array of length n, where n is the number of positions</span><span class="strut"> </span></p> -<p id="t803" class="pln"><span class="str"> passed to SeriesOfHydraulicCells.hydraulic_results().</span><span class="strut"> </span></p> -<p id="t804" class="pln"><span class="strut"> </span></p> -<p id="t805" class="pln"><span class="str"> :return: Depth of water column in m</span><span class="strut"> </span></p> -<p id="t806" class="pln"><span class="strut"> </span></p> -<p id="t807" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t808" class="pln"><span class="strut"> </span></p> -<p id="t809" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_hydraulic_data</span><span class="op">[</span><span class="op">:</span><span class="op">,</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_depth_index</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t810" class="pln"><span class="strut"> </span></p> -<p id="t811" class="stm run hide_run"> <span class="key">def</span> <span class="nam">lateral_velocity</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t812" class="pln"> <span class="str">"""Returns the lateral (y-direction) velocity for a given position.</span><span class="strut"> </span></p> -<p id="t813" class="pln"><span class="strut"> </span></p> -<p id="t814" class="pln"><span class="str"> Returns a numpy array of length n, where n is the number of positions</span><span class="strut"> </span></p> -<p id="t815" class="pln"><span class="str"> passed to SeriesOfHydraulicCells.hydraulic_results().</span><span class="strut"> </span></p> -<p id="t816" class="pln"><span class="strut"> </span></p> -<p id="t817" class="pln"><span class="str"> :return: Lateral velocity in m/s</span><span class="strut"> </span></p> -<p id="t818" class="pln"><span class="strut"> </span></p> -<p id="t819" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t820" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_hydraulic_data</span><span class="op">[</span><span class="op">:</span><span class="op">,</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_lateral_velocity_index</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t821" class="pln"><span class="strut"> </span></p> -<p id="t822" class="stm run hide_run"> <span class="key">def</span> <span class="nam">shear_velocity</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t823" class="pln"> <span class="str">"""Returns the shear velocity corresponding to a position.</span><span class="strut"> </span></p> -<p id="t824" class="pln"><span class="strut"> </span></p> -<p id="t825" class="pln"><span class="str"> Returns a numpy array of length n, where n is the number of positions</span><span class="strut"> </span></p> -<p id="t826" class="pln"><span class="str"> passed to SeriesOfHydraulicCells.hydraulic_results().</span><span class="strut"> </span></p> -<p id="t827" class="pln"><span class="strut"> </span></p> -<p id="t828" class="pln"><span class="str"> :return: Shear velocity in m/s</span><span class="strut"> </span></p> -<p id="t829" class="pln"><span class="strut"> </span></p> -<p id="t830" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t831" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_hydraulic_data</span><span class="op">[</span><span class="op">:</span><span class="op">,</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_shear_velocity_index</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t832" class="pln"><span class="strut"> </span></p> -<p id="t833" class="stm run hide_run"> <span class="key">def</span> <span class="nam">streamwise_velocity</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t834" class="pln"> <span class="str">"""Returns the streamwise (x-direction) velocity for a given position.</span><span class="strut"> </span></p> -<p id="t835" class="pln"><span class="strut"> </span></p> -<p id="t836" class="pln"><span class="str"> Returns a numpy array of length n, where n is the number of positions</span><span class="strut"> </span></p> -<p id="t837" class="pln"><span class="str"> passed to SeriesOfHydraulicCells.hydraulic_results().</span><span class="strut"> </span></p> -<p id="t838" class="pln"><span class="strut"> </span></p> -<p id="t839" class="pln"><span class="str"> :return: Streamwise velocity in m/s</span><span class="strut"> </span></p> -<p id="t840" class="pln"><span class="strut"> </span></p> -<p id="t841" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t842" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_hydraulic_data</span><span class="op">[</span><span class="op">:</span><span class="op">,</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_streamwise_velocity_index</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t843" class="pln"><span class="strut"> </span></p> -<p id="t844" class="stm run hide_run"> <span class="key">def</span> <span class="nam">temperature</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t845" class="pln"> <span class="str">"""Returns the temperature for a given position.</span><span class="strut"> </span></p> -<p id="t846" class="pln"><span class="strut"> </span></p> -<p id="t847" class="pln"><span class="str"> Returns a numpy array of length n, where n is the number of positions</span><span class="strut"> </span></p> -<p id="t848" class="pln"><span class="str"> passed to SeriesOfHydraulicCells.hydraulic_results().</span><span class="strut"> </span></p> -<p id="t849" class="pln"><span class="strut"> </span></p> -<p id="t850" class="pln"><span class="str"> :return: Temperature in deg C</span><span class="strut"> </span></p> -<p id="t851" class="pln"><span class="strut"> </span></p> -<p id="t852" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t853" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_hydraulic_data</span><span class="op">[</span><span class="op">:</span><span class="op">,</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_temperature_index</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t854" class="pln"><span class="strut"> </span></p> -<p id="t855" class="stm run hide_run"> <span class="key">def</span> <span class="nam">water_density</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t856" class="pln"> <span class="str">"""Returns the density of the water at a given position.</span><span class="strut"> </span></p> -<p id="t857" class="pln"><span class="strut"> </span></p> -<p id="t858" class="pln"><span class="str"> Returns a numpy array of length n, where n is the number of positions</span><span class="strut"> </span></p> -<p id="t859" class="pln"><span class="str"> passed to SeriesOfHydraulicCells.hydraulic_results().</span><span class="strut"> </span></p> -<p id="t860" class="pln"><span class="strut"> </span></p> -<p id="t861" class="pln"><span class="str"> :return: Water density in kg/m**3</span><span class="strut"> </span></p> -<p id="t862" class="pln"><span class="strut"> </span></p> -<p id="t863" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t864" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_hydraulic_data</span><span class="op">[</span><span class="op">:</span><span class="op">,</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_density_index</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t865" class="pln"><span class="strut"> </span></p> -<p id="t866" class="stm run hide_run"> <span class="key">def</span> <span class="nam">water_viscosity</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t867" class="pln"> <span class="str">"""Returns the viscosity of water at a given position.</span><span class="strut"> </span></p> -<p id="t868" class="pln"><span class="strut"> </span></p> -<p id="t869" class="pln"><span class="str"> Returns a numpy array of length n, where n is the number of positions</span><span class="strut"> </span></p> -<p id="t870" class="pln"><span class="str"> passed to SeriesOfHydraulicCells.hydraulic_results().</span><span class="strut"> </span></p> -<p id="t871" class="pln"><span class="strut"> </span></p> -<p id="t872" class="pln"><span class="str"> :return: Viscosity in m**2/s</span><span class="strut"> </span></p> -<p id="t873" class="pln"><span class="strut"> </span></p> -<p id="t874" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t875" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_hydraulic_data</span><span class="op">[</span><span class="op">:</span><span class="op">,</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_viscosity_index</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t876" class="pln"><span class="strut"> </span></p> -<p id="t877" class="stm run hide_run"> <span class="key">def</span> <span class="nam">width</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t878" class="pln"> <span class="str">"""Returns the width of the channel at a given position.</span><span class="strut"> </span></p> -<p id="t879" class="pln"><span class="strut"> </span></p> -<p id="t880" class="pln"><span class="str"> Returns a numpy array of length n, where n is the number of positions</span><span class="strut"> </span></p> -<p id="t881" class="pln"><span class="str"> passed to SeriesOfHydraulicCells.hydraulic_results().</span><span class="strut"> </span></p> -<p id="t882" class="pln"><span class="strut"> </span></p> -<p id="t883" class="pln"><span class="str"> :return: Width in m</span><span class="strut"> </span></p> -<p id="t884" class="pln"><span class="strut"> </span></p> -<p id="t885" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t886" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_hydraulic_data</span><span class="op">[</span><span class="op">:</span><span class="op">,</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_width_index</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t887" class="pln"><span class="strut"> </span></p> -<p id="t888" class="stm run hide_run"> <span class="key">def</span> <span class="nam">vertical_velocity</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t889" class="pln"> <span class="str">"""Returns the vertical (z-direction) velocity for a given position.</span><span class="strut"> </span></p> -<p id="t890" class="pln"><span class="strut"> </span></p> -<p id="t891" class="pln"><span class="str"> Returns a numpy array of length n, where n is the number of positions</span><span class="strut"> </span></p> -<p id="t892" class="pln"><span class="str"> passed to SeriesOfHydraulicCells.hydraulic_results().</span><span class="strut"> </span></p> -<p id="t893" class="pln"><span class="strut"> </span></p> -<p id="t894" class="pln"><span class="str"> :return: Vertical velocity in m/s</span><span class="strut"> </span></p> -<p id="t895" class="pln"><span class="strut"> </span></p> -<p id="t896" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t897" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_hydraulic_data</span><span class="op">[</span><span class="op">:</span><span class="op">,</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_vertical_velocity_index</span><span class="op">]</span><span class="strut"> </span></p> - - </td> - </tr> - </table> -</div> - -<div id="footer"> - <div class="content"> - <p> - <a class="nav" href="index.html">« index</a> <a class="nav" href="https://coverage.readthedocs.io">coverage.py v4.5.3</a>, - created at 2019-07-09 15:15 - </p> - </div> -</div> - -</body> -</html> diff --git a/coverage_report/fluegg_kml_py.html b/coverage_report/fluegg_kml_py.html deleted file mode 100644 index b85f228..0000000 --- a/coverage_report/fluegg_kml_py.html +++ /dev/null @@ -1,907 +0,0 @@ - - - -<!DOCTYPE html> -<html> -<head> - <meta http-equiv="Content-Type" content="text/html; charset=utf-8"> - - - <meta http-equiv="X-UA-Compatible" content="IE=emulateIE7" /> - <title>Coverage for fluegg\kml.py: 13%</title> - <link rel="stylesheet" href="style.css" type="text/css"> - - <script type="text/javascript" src="jquery.min.js"></script> - <script type="text/javascript" src="jquery.hotkeys.js"></script> - <script type="text/javascript" src="jquery.isonscreen.js"></script> - <script type="text/javascript" src="coverage_html.js"></script> - <script type="text/javascript"> - jQuery(document).ready(coverage.pyfile_ready); - </script> -</head> -<body class="pyfile"> - -<div id="header"> - <div class="content"> - <h1>Coverage for <b>fluegg\kml.py</b> : - <span class="pc_cov">13%</span> - </h1> - - <img id="keyboard_icon" src="keybd_closed.png" alt="Show keyboard shortcuts" /> - - <h2 class="stats"> - 130 statements - <span class="run hide_run shortkey_r button_toggle_run">17 run</span> - <span class="mis shortkey_m button_toggle_mis">113 missing</span> - <span class="exc shortkey_x 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href="#n100">100</a></p> -<p id="n101" class="pln"><a href="#n101">101</a></p> -<p id="n102" class="pln"><a href="#n102">102</a></p> -<p id="n103" class="pln"><a href="#n103">103</a></p> -<p id="n104" class="pln"><a href="#n104">104</a></p> -<p id="n105" class="pln"><a href="#n105">105</a></p> -<p id="n106" class="pln"><a href="#n106">106</a></p> -<p id="n107" class="pln"><a href="#n107">107</a></p> -<p id="n108" class="pln"><a href="#n108">108</a></p> -<p id="n109" class="pln"><a href="#n109">109</a></p> -<p id="n110" class="pln"><a href="#n110">110</a></p> -<p id="n111" class="pln"><a href="#n111">111</a></p> -<p id="n112" class="stm run hide_run"><a href="#n112">112</a></p> -<p id="n113" class="pln"><a href="#n113">113</a></p> -<p id="n114" class="pln"><a href="#n114">114</a></p> -<p id="n115" class="pln"><a href="#n115">115</a></p> -<p id="n116" class="pln"><a href="#n116">116</a></p> -<p id="n117" class="stm mis"><a href="#n117">117</a></p> -<p id="n118" class="pln"><a href="#n118">118</a></p> -<p id="n119" class="stm mis"><a href="#n119">119</a></p> -<p id="n120" class="pln"><a href="#n120">120</a></p> -<p id="n121" class="pln"><a href="#n121">121</a></p> -<p id="n122" class="stm mis"><a href="#n122">122</a></p> -<p id="n123" class="pln"><a href="#n123">123</a></p> -<p id="n124" class="stm mis"><a href="#n124">124</a></p> -<p id="n125" class="pln"><a href="#n125">125</a></p> -<p id="n126" class="stm run hide_run"><a href="#n126">126</a></p> -<p id="n127" class="pln"><a href="#n127">127</a></p> -<p id="n128" class="pln"><a href="#n128">128</a></p> -<p id="n129" class="pln"><a href="#n129">129</a></p> -<p id="n130" class="pln"><a href="#n130">130</a></p> -<p id="n131" class="pln"><a href="#n131">131</a></p> -<p id="n132" class="pln"><a href="#n132">132</a></p> -<p id="n133" class="pln"><a href="#n133">133</a></p> -<p id="n134" class="pln"><a href="#n134">134</a></p> -<p id="n135" class="stm mis"><a href="#n135">135</a></p> -<p id="n136" class="stm mis"><a href="#n136">136</a></p> -<p id="n137" class="pln"><a href="#n137">137</a></p> -<p id="n138" class="stm mis"><a href="#n138">138</a></p> -<p id="n139" class="stm mis"><a href="#n139">139</a></p> -<p id="n140" class="pln"><a href="#n140">140</a></p> -<p id="n141" class="stm mis"><a href="#n141">141</a></p> -<p id="n142" class="pln"><a href="#n142">142</a></p> -<p id="n143" class="stm mis"><a href="#n143">143</a></p> -<p id="n144" class="stm mis"><a href="#n144">144</a></p> -<p id="n145" class="pln"><a href="#n145">145</a></p> -<p id="n146" class="stm run hide_run"><a href="#n146">146</a></p> -<p id="n147" class="pln"><a href="#n147">147</a></p> -<p id="n148" class="stm mis"><a href="#n148">148</a></p> -<p id="n149" class="stm mis"><a href="#n149">149</a></p> -<p id="n150" class="pln"><a href="#n150">150</a></p> -<p id="n151" class="stm mis"><a href="#n151">151</a></p> -<p id="n152" class="stm mis"><a href="#n152">152</a></p> -<p id="n153" class="pln"><a href="#n153">153</a></p> -<p id="n154" class="pln"><a href="#n154">154</a></p> -<p id="n155" class="stm mis"><a href="#n155">155</a></p> -<p id="n156" class="pln"><a href="#n156">156</a></p> -<p id="n157" class="pln"><a href="#n157">157</a></p> -<p id="n158" class="stm mis"><a href="#n158">158</a></p> -<p id="n159" class="stm mis"><a href="#n159">159</a></p> -<p id="n160" class="pln"><a href="#n160">160</a></p> -<p id="n161" class="pln"><a href="#n161">161</a></p> -<p id="n162" class="stm mis"><a href="#n162">162</a></p> -<p id="n163" class="stm mis"><a href="#n163">163</a></p> -<p id="n164" class="pln"><a href="#n164">164</a></p> -<p id="n165" class="pln"><a href="#n165">165</a></p> -<p id="n166" class="stm mis"><a href="#n166">166</a></p> -<p id="n167" class="stm mis"><a href="#n167">167</a></p> -<p id="n168" class="pln"><a href="#n168">168</a></p> -<p id="n169" class="pln"><a href="#n169">169</a></p> -<p id="n170" class="stm mis"><a href="#n170">170</a></p> -<p id="n171" class="stm mis"><a href="#n171">171</a></p> -<p id="n172" class="pln"><a href="#n172">172</a></p> -<p id="n173" class="pln"><a href="#n173">173</a></p> -<p id="n174" class="stm mis"><a href="#n174">174</a></p> -<p id="n175" class="stm mis"><a href="#n175">175</a></p> -<p id="n176" class="pln"><a href="#n176">176</a></p> -<p id="n177" class="pln"><a href="#n177">177</a></p> -<p id="n178" class="pln"><a href="#n178">178</a></p> -<p id="n179" class="stm mis"><a href="#n179">179</a></p> -<p id="n180" class="pln"><a href="#n180">180</a></p> -<p id="n181" class="stm mis"><a href="#n181">181</a></p> -<p id="n182" class="stm mis"><a href="#n182">182</a></p> -<p id="n183" class="stm mis"><a href="#n183">183</a></p> -<p id="n184" class="stm mis"><a href="#n184">184</a></p> -<p id="n185" class="pln"><a href="#n185">185</a></p> -<p id="n186" class="pln"><a href="#n186">186</a></p> -<p id="n187" class="stm mis"><a href="#n187">187</a></p> -<p id="n188" class="pln"><a href="#n188">188</a></p> -<p id="n189" class="stm run hide_run"><a href="#n189">189</a></p> -<p id="n190" class="pln"><a href="#n190">190</a></p> -<p id="n191" class="pln"><a href="#n191">191</a></p> -<p id="n192" class="pln"><a href="#n192">192</a></p> -<p id="n193" class="pln"><a href="#n193">193</a></p> -<p id="n194" class="pln"><a href="#n194">194</a></p> -<p id="n195" class="pln"><a href="#n195">195</a></p> -<p id="n196" class="pln"><a href="#n196">196</a></p> -<p id="n197" class="pln"><a href="#n197">197</a></p> -<p id="n198" class="pln"><a href="#n198">198</a></p> -<p id="n199" class="pln"><a href="#n199">199</a></p> -<p id="n200" class="pln"><a href="#n200">200</a></p> -<p id="n201" class="pln"><a href="#n201">201</a></p> -<p id="n202" class="stm mis"><a href="#n202">202</a></p> -<p id="n203" class="pln"><a href="#n203">203</a></p> -<p id="n204" class="pln"><a href="#n204">204</a></p> -<p id="n205" class="stm mis"><a href="#n205">205</a></p> -<p id="n206" class="pln"><a href="#n206">206</a></p> -<p id="n207" class="pln"><a href="#n207">207</a></p> -<p id="n208" class="pln"><a href="#n208">208</a></p> -<p id="n209" class="stm mis"><a href="#n209">209</a></p> -<p id="n210" class="pln"><a href="#n210">210</a></p> -<p id="n211" class="stm run hide_run"><a href="#n211">211</a></p> -<p id="n212" class="pln"><a href="#n212">212</a></p> -<p id="n213" class="pln"><a href="#n213">213</a></p> -<p id="n214" class="pln"><a href="#n214">214</a></p> -<p id="n215" class="pln"><a href="#n215">215</a></p> -<p id="n216" class="pln"><a href="#n216">216</a></p> -<p id="n217" class="pln"><a href="#n217">217</a></p> -<p id="n218" class="pln"><a href="#n218">218</a></p> -<p id="n219" class="pln"><a href="#n219">219</a></p> -<p id="n220" class="pln"><a href="#n220">220</a></p> -<p id="n221" class="pln"><a href="#n221">221</a></p> -<p id="n222" class="pln"><a href="#n222">222</a></p> -<p id="n223" class="pln"><a href="#n223">223</a></p> -<p id="n224" class="pln"><a href="#n224">224</a></p> -<p id="n225" class="pln"><a href="#n225">225</a></p> -<p id="n226" class="pln"><a href="#n226">226</a></p> -<p id="n227" class="pln"><a href="#n227">227</a></p> -<p id="n228" class="pln"><a href="#n228">228</a></p> -<p id="n229" class="pln"><a href="#n229">229</a></p> -<p id="n230" class="pln"><a href="#n230">230</a></p> -<p id="n231" class="pln"><a href="#n231">231</a></p> -<p id="n232" class="pln"><a href="#n232">232</a></p> -<p id="n233" class="pln"><a href="#n233">233</a></p> -<p id="n234" class="pln"><a href="#n234">234</a></p> -<p id="n235" class="pln"><a href="#n235">235</a></p> -<p id="n236" class="pln"><a href="#n236">236</a></p> -<p id="n237" class="stm mis"><a href="#n237">237</a></p> -<p id="n238" class="pln"><a href="#n238">238</a></p> -<p id="n239" class="stm mis"><a href="#n239">239</a></p> -<p id="n240" class="stm mis"><a href="#n240">240</a></p> -<p id="n241" class="pln"><a href="#n241">241</a></p> -<p id="n242" class="stm mis"><a href="#n242">242</a></p> -<p id="n243" class="stm mis"><a href="#n243">243</a></p> -<p id="n244" class="pln"><a href="#n244">244</a></p> -<p id="n245" class="stm mis"><a href="#n245">245</a></p> -<p id="n246" class="stm mis"><a href="#n246">246</a></p> -<p id="n247" class="pln"><a href="#n247">247</a></p> -<p id="n248" class="pln"><a href="#n248">248</a></p> -<p id="n249" class="stm mis"><a href="#n249">249</a></p> -<p id="n250" class="pln"><a href="#n250">250</a></p> -<p id="n251" class="stm mis"><a href="#n251">251</a></p> -<p id="n252" class="pln"><a href="#n252">252</a></p> -<p id="n253" class="stm mis"><a href="#n253">253</a></p> -<p id="n254" class="pln"><a href="#n254">254</a></p> -<p id="n255" class="stm mis"><a href="#n255">255</a></p> -<p id="n256" class="stm mis"><a href="#n256">256</a></p> -<p id="n257" class="stm mis"><a href="#n257">257</a></p> -<p id="n258" class="stm mis"><a href="#n258">258</a></p> -<p id="n259" class="pln"><a href="#n259">259</a></p> -<p id="n260" class="pln"><a href="#n260">260</a></p> -<p id="n261" class="stm mis"><a href="#n261">261</a></p> -<p id="n262" class="pln"><a href="#n262">262</a></p> -<p id="n263" class="stm mis"><a href="#n263">263</a></p> -<p id="n264" class="pln"><a href="#n264">264</a></p> -<p id="n265" class="stm mis"><a href="#n265">265</a></p> -<p id="n266" class="stm mis"><a href="#n266">266</a></p> -<p id="n267" class="pln"><a href="#n267">267</a></p> -<p id="n268" class="pln"><a href="#n268">268</a></p> -<p id="n269" class="stm mis"><a href="#n269">269</a></p> -<p id="n270" class="stm mis"><a href="#n270">270</a></p> -<p id="n271" class="pln"><a href="#n271">271</a></p> -<p id="n272" class="stm mis"><a href="#n272">272</a></p> -<p id="n273" class="stm mis"><a href="#n273">273</a></p> -<p id="n274" class="pln"><a href="#n274">274</a></p> -<p id="n275" class="stm mis"><a href="#n275">275</a></p> -<p id="n276" class="pln"><a href="#n276">276</a></p> -<p id="n277" class="stm mis"><a href="#n277">277</a></p> -<p id="n278" class="pln"><a href="#n278">278</a></p> -<p id="n279" class="stm run hide_run"><a href="#n279">279</a></p> -<p id="n280" class="pln"><a href="#n280">280</a></p> -<p id="n281" class="pln"><a href="#n281">281</a></p> -<p id="n282" class="pln"><a href="#n282">282</a></p> -<p id="n283" class="pln"><a href="#n283">283</a></p> -<p id="n284" class="pln"><a href="#n284">284</a></p> -<p id="n285" class="pln"><a href="#n285">285</a></p> -<p id="n286" class="pln"><a href="#n286">286</a></p> -<p id="n287" class="pln"><a href="#n287">287</a></p> -<p id="n288" class="pln"><a href="#n288">288</a></p> -<p id="n289" class="pln"><a href="#n289">289</a></p> -<p id="n290" class="pln"><a href="#n290">290</a></p> -<p id="n291" class="pln"><a href="#n291">291</a></p> -<p id="n292" class="stm mis"><a href="#n292">292</a></p> -<p id="n293" class="stm mis"><a href="#n293">293</a></p> -<p id="n294" class="pln"><a href="#n294">294</a></p> -<p id="n295" class="stm mis"><a href="#n295">295</a></p> -<p id="n296" class="pln"><a href="#n296">296</a></p> -<p id="n297" class="stm run hide_run"><a href="#n297">297</a></p> -<p id="n298" class="pln"><a href="#n298">298</a></p> -<p id="n299" class="pln"><a href="#n299">299</a></p> -<p id="n300" class="pln"><a href="#n300">300</a></p> -<p id="n301" class="pln"><a href="#n301">301</a></p> -<p id="n302" class="pln"><a href="#n302">302</a></p> -<p id="n303" class="pln"><a href="#n303">303</a></p> -<p id="n304" class="pln"><a href="#n304">304</a></p> -<p id="n305" class="pln"><a href="#n305">305</a></p> -<p id="n306" class="pln"><a href="#n306">306</a></p> -<p id="n307" class="pln"><a href="#n307">307</a></p> -<p id="n308" class="pln"><a href="#n308">308</a></p> -<p id="n309" class="pln"><a href="#n309">309</a></p> -<p id="n310" class="pln"><a href="#n310">310</a></p> -<p id="n311" class="pln"><a href="#n311">311</a></p> -<p id="n312" class="pln"><a href="#n312">312</a></p> -<p id="n313" class="pln"><a href="#n313">313</a></p> -<p id="n314" class="pln"><a href="#n314">314</a></p> -<p id="n315" class="pln"><a href="#n315">315</a></p> -<p id="n316" class="stm mis"><a href="#n316">316</a></p> -<p id="n317" class="pln"><a href="#n317">317</a></p> -<p id="n318" class="stm mis"><a href="#n318">318</a></p> -<p id="n319" class="pln"><a href="#n319">319</a></p> -<p id="n320" class="stm mis"><a href="#n320">320</a></p> -<p id="n321" class="pln"><a href="#n321">321</a></p> -<p id="n322" class="pln"><a href="#n322">322</a></p> -<p id="n323" class="stm mis"><a href="#n323">323</a></p> -<p id="n324" class="pln"><a href="#n324">324</a></p> -<p id="n325" class="stm mis"><a href="#n325">325</a></p> -<p id="n326" class="stm mis"><a href="#n326">326</a></p> -<p id="n327" class="stm mis"><a href="#n327">327</a></p> -<p id="n328" class="stm mis"><a href="#n328">328</a></p> -<p id="n329" class="stm mis"><a href="#n329">329</a></p> -<p id="n330" class="stm mis"><a href="#n330">330</a></p> -<p id="n331" class="stm mis"><a href="#n331">331</a></p> -<p id="n332" class="stm mis"><a href="#n332">332</a></p> -<p id="n333" class="stm mis"><a href="#n333">333</a></p> -<p id="n334" class="pln"><a href="#n334">334</a></p> -<p id="n335" class="stm mis"><a href="#n335">335</a></p> -<p id="n336" class="stm mis"><a href="#n336">336</a></p> -<p id="n337" class="stm mis"><a href="#n337">337</a></p> -<p id="n338" class="stm mis"><a href="#n338">338</a></p> -<p id="n339" class="pln"><a href="#n339">339</a></p> -<p id="n340" class="pln"><a href="#n340">340</a></p> -<p id="n341" class="stm mis"><a href="#n341">341</a></p> -<p id="n342" class="pln"><a href="#n342">342</a></p> -<p id="n343" class="stm mis"><a href="#n343">343</a></p> -<p id="n344" class="pln"><a href="#n344">344</a></p> -<p id="n345" class="stm mis"><a href="#n345">345</a></p> -<p id="n346" class="pln"><a href="#n346">346</a></p> -<p id="n347" class="stm run hide_run"><a href="#n347">347</a></p> -<p id="n348" class="pln"><a href="#n348">348</a></p> -<p id="n349" class="pln"><a href="#n349">349</a></p> -<p id="n350" class="pln"><a href="#n350">350</a></p> -<p id="n351" class="pln"><a href="#n351">351</a></p> -<p id="n352" class="pln"><a href="#n352">352</a></p> -<p id="n353" class="pln"><a href="#n353">353</a></p> -<p id="n354" class="pln"><a href="#n354">354</a></p> -<p id="n355" class="pln"><a href="#n355">355</a></p> -<p id="n356" class="pln"><a href="#n356">356</a></p> -<p id="n357" class="pln"><a href="#n357">357</a></p> -<p id="n358" class="pln"><a href="#n358">358</a></p> -<p id="n359" class="pln"><a href="#n359">359</a></p> -<p id="n360" class="pln"><a href="#n360">360</a></p> -<p id="n361" class="pln"><a href="#n361">361</a></p> -<p id="n362" class="pln"><a href="#n362">362</a></p> -<p id="n363" class="pln"><a href="#n363">363</a></p> -<p id="n364" class="pln"><a href="#n364">364</a></p> -<p id="n365" class="pln"><a href="#n365">365</a></p> -<p id="n366" class="pln"><a href="#n366">366</a></p> -<p id="n367" class="pln"><a href="#n367">367</a></p> -<p id="n368" class="pln"><a href="#n368">368</a></p> -<p id="n369" class="pln"><a href="#n369">369</a></p> -<p id="n370" class="pln"><a href="#n370">370</a></p> -<p id="n371" class="pln"><a href="#n371">371</a></p> -<p id="n372" class="stm mis"><a href="#n372">372</a></p> -<p id="n373" class="pln"><a href="#n373">373</a></p> -<p id="n374" class="stm mis"><a href="#n374">374</a></p> -<p id="n375" class="stm mis"><a href="#n375">375</a></p> -<p id="n376" class="pln"><a href="#n376">376</a></p> -<p id="n377" class="stm run hide_run"><a href="#n377">377</a></p> -<p id="n378" class="pln"><a href="#n378">378</a></p> -<p id="n379" class="pln"><a href="#n379">379</a></p> -<p id="n380" class="pln"><a href="#n380">380</a></p> -<p id="n381" class="pln"><a href="#n381">381</a></p> -<p id="n382" class="pln"><a href="#n382">382</a></p> -<p id="n383" class="pln"><a href="#n383">383</a></p> -<p id="n384" class="pln"><a href="#n384">384</a></p> -<p id="n385" class="pln"><a href="#n385">385</a></p> -<p id="n386" class="stm mis"><a href="#n386">386</a></p> -<p id="n387" class="pln"><a href="#n387">387</a></p> -<p id="n388" class="stm mis"><a href="#n388">388</a></p> -<p id="n389" class="stm mis"><a href="#n389">389</a></p> -<p id="n390" class="pln"><a href="#n390">390</a></p> -<p id="n391" class="stm run hide_run"><a href="#n391">391</a></p> -<p id="n392" class="pln"><a href="#n392">392</a></p> -<p id="n393" class="pln"><a href="#n393">393</a></p> -<p id="n394" class="pln"><a href="#n394">394</a></p> -<p id="n395" class="pln"><a href="#n395">395</a></p> -<p id="n396" class="pln"><a href="#n396">396</a></p> -<p id="n397" class="pln"><a href="#n397">397</a></p> -<p id="n398" class="pln"><a href="#n398">398</a></p> -<p id="n399" class="pln"><a href="#n399">399</a></p> -<p id="n400" class="pln"><a href="#n400">400</a></p> -<p id="n401" class="pln"><a href="#n401">401</a></p> -<p id="n402" class="pln"><a href="#n402">402</a></p> -<p id="n403" class="pln"><a href="#n403">403</a></p> -<p id="n404" class="pln"><a href="#n404">404</a></p> -<p id="n405" class="pln"><a href="#n405">405</a></p> -<p id="n406" class="stm mis"><a href="#n406">406</a></p> -<p id="n407" class="pln"><a href="#n407">407</a></p> -<p id="n408" class="stm mis"><a href="#n408">408</a></p> -<p id="n409" class="stm mis"><a href="#n409">409</a></p> - - </td> - <td class="text"> -<p id="t1" class="stm run hide_run"><span class="key">import</span> <span class="nam">xml</span><span class="op">.</span><span class="nam">etree</span><span class="op">.</span><span class="nam">ElementTree</span> <span class="key">as</span> <span class="nam">ElementTree</span><span class="strut"> </span></p> -<p id="t2" class="pln"><span class="strut"> </span></p> -<p id="t3" class="stm run hide_run"><span class="key">from</span> <span class="nam">matplotlib</span><span class="op">.</span><span class="nam">cm</span> <span class="key">import</span> <span class="nam">jet</span> <span class="key">as</span> <span class="nam">jet_cm</span><span class="strut"> </span></p> -<p id="t4" class="stm run hide_run"><span class="key">import</span> <span class="nam">numpy</span> <span class="key">as</span> <span class="nam">np</span><span class="strut"> </span></p> -<p id="t5" class="stm run hide_run"><span class="key">import</span> <span class="nam">simplekml</span><span class="strut"> </span></p> -<p id="t6" class="pln"><span class="strut"> </span></p> -<p id="t7" class="pln"><span class="strut"> </span></p> -<p id="t8" class="stm run hide_run"><span class="key">def</span> <span class="nam">kml_linestring_coordinates</span><span class="op">(</span><span class="nam">kml_path</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t9" class="pln"> <span class="str">"""Return lat, lon coordinates from a LineString contained in a KML file</span><span class="strut"> </span></p> -<p id="t10" class="pln"><span class="strut"> </span></p> -<p id="t11" class="pln"><span class="str"> This function looks for a LineString under the coordinates tag in the</span><span class="strut"> </span></p> -<p id="t12" class="pln"><span class="str"> following structure.</span><span class="strut"> </span></p> -<p id="t13" class="pln"><span class="strut"> </span></p> -<p id="t14" class="pln"><span class="str"> <kml xmlns="http://www.opengis.net/kml/2.2" ...></span><span class="strut"> </span></p> -<p id="t15" class="pln"><span class="str"> <Document></span><span class="strut"> </span></p> -<p id="t16" class="pln"><span class="str"> <Placemark></span><span class="strut"> </span></p> -<p id="t17" class="pln"><span class="str"> <LineString></span><span class="strut"> </span></p> -<p id="t18" class="pln"><span class="str"> <coordinates></span><span class="strut"> </span></p> -<p id="t19" class="pln"><span class="str"> "lat1,lon1,z1 lat2,lon2,z2 ..."</span><span class="strut"> </span></p> -<p id="t20" class="pln"><span class="str"> </coordinates></span><span class="strut"> </span></p> -<p id="t21" class="pln"><span class="str"> </LineString></span><span class="strut"> </span></p> -<p id="t22" class="pln"><span class="str"> </Placemark></span><span class="strut"> </span></p> -<p id="t23" class="pln"><span class="str"> </Document></span><span class="strut"> </span></p> -<p id="t24" class="pln"><span class="str"> </kml></span><span class="strut"> </span></p> -<p id="t25" class="pln"><span class="strut"> </span></p> -<p id="t26" class="pln"><span class="str"> Parameters</span><span class="strut"> </span></p> -<p id="t27" class="pln"><span class="str"> ----------</span><span class="strut"> </span></p> -<p id="t28" class="pln"><span class="str"> kml_path : str</span><span class="strut"> </span></p> -<p id="t29" class="pln"><span class="str"> Path to KML file containing a LineString</span><span class="strut"> </span></p> -<p id="t30" class="pln"><span class="strut"> </span></p> -<p id="t31" class="pln"><span class="str"> Returns</span><span class="strut"> </span></p> -<p id="t32" class="pln"><span class="str"> -------</span><span class="strut"> </span></p> -<p id="t33" class="pln"><span class="str"> numpy.ndarray</span><span class="strut"> </span></p> -<p id="t34" class="pln"><span class="strut"> </span></p> -<p id="t35" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t36" class="pln"><span class="strut"> </span></p> -<p id="t37" class="stm mis"> <span class="nam">ns</span> <span class="op">=</span> <span class="op">{</span><span class="str">'og'</span><span class="op">:</span> <span class="str">'http://www.opengis.net/kml/2.2'</span><span class="op">}</span><span class="strut"> </span></p> -<p id="t38" class="pln"><span class="strut"> </span></p> -<p id="t39" class="stm mis"> <span class="nam">tree</span> <span class="op">=</span> <span class="nam">ElementTree</span><span class="op">.</span><span class="nam">parse</span><span class="op">(</span><span class="nam">kml_path</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t40" class="stm mis"> <span class="nam">xml_root</span> <span class="op">=</span> <span class="nam">tree</span><span class="op">.</span><span class="nam">getroot</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t41" class="stm mis"> <span class="nam">document</span> <span class="op">=</span> <span class="nam">xml_root</span><span class="op">.</span><span class="nam">find</span><span class="op">(</span><span class="str">'og:Document'</span><span class="op">,</span> <span class="nam">ns</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t42" class="stm mis"> <span class="nam">placemark</span> <span class="op">=</span> <span class="nam">document</span><span class="op">.</span><span class="nam">find</span><span class="op">(</span><span class="str">'og:Placemark'</span><span class="op">,</span> <span class="nam">ns</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t43" class="stm mis"> <span class="nam">linestring</span> <span class="op">=</span> <span class="nam">placemark</span><span class="op">.</span><span class="nam">find</span><span class="op">(</span><span class="str">'og:LineString'</span><span class="op">,</span> <span class="nam">ns</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t44" class="stm mis"> <span class="nam">coordinates</span> <span class="op">=</span> <span class="nam">linestring</span><span class="op">.</span><span class="nam">find</span><span class="op">(</span><span class="str">'og:coordinates'</span><span class="op">,</span> <span class="nam">ns</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t45" class="pln"><span class="strut"> </span></p> -<p id="t46" class="stm mis"> <span class="nam">list_coordinates</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t47" class="pln"> <span class="op">[</span><span class="nam">cset</span><span class="op">.</span><span class="nam">split</span><span class="op">(</span><span class="str">','</span><span class="op">)</span> <span class="key">for</span> <span class="nam">cset</span> <span class="key">in</span> <span class="nam">coordinates</span><span class="op">.</span><span class="nam">text</span><span class="op">.</span><span class="nam">strip</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">split</span><span class="op">(</span><span class="str">' '</span><span class="op">)</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t48" class="stm mis"> <span class="nam">flt_coordinates</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t49" class="pln"> <span class="op">[</span><span class="op">[</span><span class="nam">float</span><span class="op">(</span><span class="nam">cset</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="op">)</span><span class="op">,</span> <span class="nam">float</span><span class="op">(</span><span class="nam">cset</span><span class="op">[</span><span class="num">1</span><span class="op">]</span><span class="op">)</span><span class="op">]</span> <span class="key">for</span> <span class="nam">cset</span> <span class="key">in</span> <span class="nam">list_coordinates</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t50" class="pln"><span class="strut"> </span></p> -<p id="t51" class="stm mis"> <span class="key">return</span> <span class="nam">np</span><span class="op">.</span><span class="nam">array</span><span class="op">(</span><span class="nam">flt_coordinates</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t52" class="pln"><span class="strut"> </span></p> -<p id="t53" class="pln"><span class="strut"> </span></p> -<p id="t54" class="stm run hide_run"><span class="key">def</span> <span class="nam">great_circle_dist</span><span class="op">(</span><span class="nam">coordinates</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t55" class="pln"> <span class="str">"""Computes great circle distance</span><span class="strut"> </span></p> -<p id="t56" class="pln"><span class="strut"> </span></p> -<p id="t57" class="pln"><span class="str"> Parameters</span><span class="strut"> </span></p> -<p id="t58" class="pln"><span class="str"> ----------</span><span class="strut"> </span></p> -<p id="t59" class="pln"><span class="str"> coordinates : np.ndarray</span><span class="strut"> </span></p> -<p id="t60" class="pln"><span class="str"> N x 2 ndarray, with column 0 as longitude and column 1 as latitude</span><span class="strut"> </span></p> -<p id="t61" class="pln"><span class="strut"> </span></p> -<p id="t62" class="pln"><span class="str"> Returns</span><span class="strut"> </span></p> -<p id="t63" class="pln"><span class="str"> -------</span><span class="strut"> </span></p> -<p id="t64" class="pln"><span class="str"> numpy.ndarray</span><span class="strut"> </span></p> -<p id="t65" class="pln"><span class="str"> Cumulative distance of array, in meters</span><span class="strut"> </span></p> -<p id="t66" class="pln"><span class="strut"> </span></p> -<p id="t67" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t68" class="pln"><span class="strut"> </span></p> -<p id="t69" class="stm mis"> <span class="nam">LATT_COLUMN</span> <span class="op">=</span> <span class="num">1</span><span class="strut"> </span></p> -<p id="t70" class="stm mis"> <span class="nam">LONG_COLUMN</span> <span class="op">=</span> <span class="num">0</span><span class="strut"> </span></p> -<p id="t71" class="pln"><span class="strut"> </span></p> -<p id="t72" class="stm mis"> <span class="nam">rads</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">radians</span><span class="op">(</span><span class="nam">coordinates</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t73" class="pln"><span class="strut"> </span></p> -<p id="t74" class="stm mis"> <span class="nam">start_latt</span> <span class="op">=</span> <span class="nam">rads</span><span class="op">[</span><span class="op">:</span><span class="op">-</span><span class="num">1</span><span class="op">,</span> <span class="nam">LATT_COLUMN</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t75" class="stm mis"> <span class="nam">end_latt</span> <span class="op">=</span> <span class="nam">rads</span><span class="op">[</span><span class="num">1</span><span class="op">:</span><span class="op">,</span> <span class="nam">LATT_COLUMN</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t76" class="pln"><span class="strut"> </span></p> -<p id="t77" class="stm mis"> <span class="nam">d_latt</span> <span class="op">=</span> <span class="nam">end_latt</span> <span class="op">-</span> <span class="nam">start_latt</span><span class="strut"> </span></p> -<p id="t78" class="stm mis"> <span class="nam">d_long</span> <span class="op">=</span> <span class="nam">rads</span><span class="op">[</span><span class="num">1</span><span class="op">:</span><span class="op">,</span> <span class="nam">LONG_COLUMN</span><span class="op">]</span> <span class="op">-</span> <span class="nam">rads</span><span class="op">[</span><span class="op">:</span><span class="op">-</span><span class="num">1</span><span class="op">,</span> <span class="nam">LONG_COLUMN</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t79" class="pln"><span class="strut"> </span></p> -<p id="t80" class="stm mis"> <span class="nam">a</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">sin</span><span class="op">(</span><span class="nam">d_latt</span><span class="op">/</span><span class="num">2</span><span class="op">)</span><span class="op">**</span><span class="num">2</span> <span class="op">+</span> <span class="nam">np</span><span class="op">.</span><span class="nam">cos</span><span class="op">(</span><span class="nam">start_latt</span><span class="op">)</span> <span class="op">*</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t81" class="pln"> <span class="nam">np</span><span class="op">.</span><span class="nam">cos</span><span class="op">(</span><span class="nam">end_latt</span><span class="op">)</span> <span class="op">*</span> <span class="nam">np</span><span class="op">.</span><span class="nam">sin</span><span class="op">(</span><span class="nam">d_long</span><span class="op">/</span><span class="num">2</span><span class="op">)</span><span class="op">**</span><span class="num">2</span><span class="strut"> </span></p> -<p id="t82" class="stm mis"> <span class="nam">c</span> <span class="op">=</span> <span class="num">2</span> <span class="op">*</span> <span class="nam">np</span><span class="op">.</span><span class="nam">arcsin</span><span class="op">(</span><span class="nam">np</span><span class="op">.</span><span class="nam">sqrt</span><span class="op">(</span><span class="nam">a</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t83" class="pln"><span class="strut"> </span></p> -<p id="t84" class="stm mis"> <span class="nam">dist</span> <span class="op">=</span> <span class="num">6371e3</span> <span class="op">*</span> <span class="nam">c</span><span class="strut"> </span></p> -<p id="t85" class="stm mis"> <span class="nam">cum_dist</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">insert</span><span class="op">(</span><span class="nam">np</span><span class="op">.</span><span class="nam">cumsum</span><span class="op">(</span><span class="nam">dist</span><span class="op">)</span><span class="op">,</span> <span class="num">0</span><span class="op">,</span> <span class="num">0</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t86" class="pln"><span class="strut"> </span></p> -<p id="t87" class="stm mis"> <span class="key">return</span> <span class="nam">cum_dist</span><span class="strut"> </span></p> -<p id="t88" class="pln"><span class="strut"> </span></p> -<p id="t89" class="pln"><span class="strut"> </span></p> -<p id="t90" class="stm run hide_run"><span class="key">class</span> <span class="nam">FluEggKML</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t91" class="pln"> <span class="str">"""Manages KML file output for FluEgg.</span><span class="strut"> </span></p> -<p id="t92" class="pln"><span class="strut"> </span></p> -<p id="t93" class="pln"><span class="str"> Parameters</span><span class="strut"> </span></p> -<p id="t94" class="pln"><span class="str"> ----------</span><span class="strut"> </span></p> -<p id="t95" class="pln"><span class="str"> centerline_kml_path : str</span><span class="strut"> </span></p> -<p id="t96" class="pln"><span class="str"> Path to stream centerline KML. The centerline KML must have uniform</span><span class="strut"> </span></p> -<p id="t97" class="pln"><span class="str"> spacing between the points.</span><span class="strut"> </span></p> -<p id="t98" class="pln"><span class="str"> spawing_location : float</span><span class="strut"> </span></p> -<p id="t99" class="pln"><span class="str"> Streamwise distance downstream of spawning location.</span><span class="strut"> </span></p> -<p id="t100" class="pln"><span class="strut"> </span></p> -<p id="t101" class="pln"><span class="str"> Notes</span><span class="strut"> </span></p> -<p id="t102" class="pln"><span class="str"> -----</span><span class="strut"> </span></p> -<p id="t103" class="pln"><span class="str"> Particle streamwise distances are mapped to geographic coordinates under</span><span class="strut"> </span></p> -<p id="t104" class="pln"><span class="str"> the assumption the points in the centerline KML are spaced equally along</span><span class="strut"> </span></p> -<p id="t105" class="pln"><span class="str"> the streamline.</span><span class="strut"> </span></p> -<p id="t106" class="pln"><span class="strut"> </span></p> -<p id="t107" class="pln"><span class="str"> The first coordinate in the KML centerline is assumed to be the upstream-</span><span class="strut"> </span></p> -<p id="t108" class="pln"><span class="str"> most point. The streamwise distance at this point is 0.</span><span class="strut"> </span></p> -<p id="t109" class="pln"><span class="strut"> </span></p> -<p id="t110" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t111" class="pln"><span class="strut"> </span></p> -<p id="t112" class="stm run hide_run"> <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">centerline_kml_path</span><span class="op">,</span> <span class="nam">spawning_location</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t113" class="pln"> <span class="str">"""see help(self) for initialization details"""</span><span class="strut"> </span></p> -<p id="t114" class="pln"><span class="strut"> </span></p> -<p id="t115" class="pln"> <span class="com"># coordinates and stream distances corresponding to the centerline</span><span class="strut"> </span></p> -<p id="t116" class="pln"> <span class="com"># points</span><span class="strut"> </span></p> -<p id="t117" class="stm mis"> <span class="nam">coordinates</span> <span class="op">=</span> <span class="nam">kml_linestring_coordinates</span><span class="op">(</span><span class="nam">centerline_kml_path</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t118" class="pln"><span class="strut"> </span></p> -<p id="t119" class="stm mis"> <span class="nam">dist</span> <span class="op">=</span> <span class="nam">great_circle_dist</span><span class="op">(</span><span class="nam">coordinates</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t120" class="pln"><span class="strut"> </span></p> -<p id="t121" class="pln"> <span class="com"># dist, lat, lon</span><span class="strut"> </span></p> -<p id="t122" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">_centerline_coords</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">hstack</span><span class="op">(</span><span class="op">(</span><span class="nam">dist</span><span class="op">[</span><span class="op">:</span><span class="op">,</span> <span class="nam">np</span><span class="op">.</span><span class="nam">newaxis</span><span class="op">]</span><span class="op">,</span> <span class="nam">coordinates</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t123" class="pln"><span class="strut"> </span></p> -<p id="t124" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">_spawning_location</span> <span class="op">=</span> <span class="nam">spawning_location</span><span class="strut"> </span></p> -<p id="t125" class="pln"><span class="strut"> </span></p> -<p id="t126" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_add_spawning_location</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">kml</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t127" class="pln"> <span class="str">"""Add the spawning location to a KML</span><span class="strut"> </span></p> -<p id="t128" class="pln"><span class="strut"> </span></p> -<p id="t129" class="pln"><span class="str"> Parameters</span><span class="strut"> </span></p> -<p id="t130" class="pln"><span class="str"> ----------</span><span class="strut"> </span></p> -<p id="t131" class="pln"><span class="str"> kml : simplekml.Kml</span><span class="strut"> </span></p> -<p id="t132" class="pln"><span class="strut"> </span></p> -<p id="t133" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t134" class="pln"><span class="strut"> </span></p> -<p id="t135" class="stm mis"> <span class="nam">spawning_style</span> <span class="op">=</span> <span class="nam">simplekml</span><span class="op">.</span><span class="nam">Style</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t136" class="stm mis"> <span class="nam">spawning_style</span><span class="op">.</span><span class="nam">iconstyle</span><span class="op">.</span><span class="nam">icon</span><span class="op">.</span><span class="nam">href</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t137" class="pln"> <span class="str">'http://maps.google.com/mapfiles/kml/shapes/fishing.png'</span><span class="strut"> </span></p> -<p id="t138" class="stm mis"> <span class="nam">spawning_style</span><span class="op">.</span><span class="nam">iconstyle</span><span class="op">.</span><span class="nam">color</span> <span class="op">=</span> <span class="str">'ffffff00'</span><span class="strut"> </span></p> -<p id="t139" class="stm mis"> <span class="nam">spawning_style</span><span class="op">.</span><span class="nam">iconstyle</span><span class="op">.</span><span class="nam">scale</span> <span class="op">=</span> <span class="num">1.2</span><span class="strut"> </span></p> -<p id="t140" class="pln"><span class="strut"> </span></p> -<p id="t141" class="stm mis"> <span class="nam">spawning_coords</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_interpolate_points</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_spawning_location</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t142" class="pln"><span class="strut"> </span></p> -<p id="t143" class="stm mis"> <span class="nam">spawning_location</span> <span class="op">=</span> <span class="nam">kml</span><span class="op">.</span><span class="nam">newpoint</span><span class="op">(</span><span class="nam">coords</span><span class="op">=</span><span class="op">[</span><span class="nam">spawning_coords</span><span class="op">]</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t144" class="stm mis"> <span class="nam">spawning_location</span><span class="op">.</span><span class="nam">style</span> <span class="op">=</span> <span class="nam">spawning_style</span><span class="strut"> </span></p> -<p id="t145" class="pln"><span class="strut"> </span></p> -<p id="t146" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_get_point_style</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">shape</span><span class="op">,</span> <span class="nam">color</span><span class="op">,</span> <span class="nam">scale</span><span class="op">,</span> <span class="nam">alphaint</span><span class="op">=</span><span class="num">128</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t147" class="pln"><span class="strut"> </span></p> -<p id="t148" class="stm mis"> <span class="key">if</span> <span class="nam">shape</span> <span class="op">==</span> <span class="str">'dot'</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t149" class="stm mis"> <span class="nam">icon_shape</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t150" class="pln"> <span class="str">'http://maps.google.com/mapfiles/kml/shapes/shaded_dot.png'</span><span class="strut"> </span></p> -<p id="t151" class="stm mis"> <span class="key">elif</span> <span class="nam">shape</span> <span class="op">==</span> <span class="str">'square'</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t152" class="stm mis"> <span class="nam">icon_shape</span> <span class="op">=</span> <span class="str">'http://maps.google.com/mapfiles/kml/shapes/'</span> <span class="op">+</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t153" class="pln"> <span class="str">'placemark_square.png'</span><span class="strut"> </span></p> -<p id="t154" class="pln"> <span class="key">else</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t155" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="str">"Unknown shape: {}"</span><span class="op">.</span><span class="nam">format</span><span class="op">(</span><span class="nam">shape</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t156" class="pln"><span class="strut"> </span></p> -<p id="t157" class="pln"> <span class="com"># blue</span><span class="strut"> </span></p> -<p id="t158" class="stm mis"> <span class="key">if</span> <span class="nam">color</span> <span class="op">==</span> <span class="str">'b'</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t159" class="stm mis"> <span class="nam">icon_color</span> <span class="op">=</span> <span class="nam">simplekml</span><span class="op">.</span><span class="nam">Color</span><span class="op">.</span><span class="nam">blue</span><span class="strut"> </span></p> -<p id="t160" class="pln"><span class="strut"> </span></p> -<p id="t161" class="pln"> <span class="com"># red</span><span class="strut"> </span></p> -<p id="t162" class="stm mis"> <span class="key">elif</span> <span class="nam">color</span> <span class="op">==</span> <span class="str">'r'</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t163" class="stm mis"> <span class="nam">icon_color</span> <span class="op">=</span> <span class="nam">simplekml</span><span class="op">.</span><span class="nam">Color</span><span class="op">.</span><span class="nam">red</span><span class="strut"> </span></p> -<p id="t164" class="pln"><span class="strut"> </span></p> -<p id="t165" class="pln"> <span class="com"># yellow</span><span class="strut"> </span></p> -<p id="t166" class="stm mis"> <span class="key">elif</span> <span class="nam">color</span> <span class="op">==</span> <span class="str">'y'</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t167" class="stm mis"> <span class="nam">icon_color</span> <span class="op">=</span> <span class="nam">simplekml</span><span class="op">.</span><span class="nam">Color</span><span class="op">.</span><span class="nam">yellow</span><span class="strut"> </span></p> -<p id="t168" class="pln"><span class="strut"> </span></p> -<p id="t169" class="pln"> <span class="com"># magenta</span><span class="strut"> </span></p> -<p id="t170" class="stm mis"> <span class="key">elif</span> <span class="nam">color</span> <span class="op">==</span> <span class="str">'m'</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t171" class="stm mis"> <span class="nam">icon_color</span> <span class="op">=</span> <span class="nam">simplekml</span><span class="op">.</span><span class="nam">Color</span><span class="op">.</span><span class="nam">magenta</span><span class="strut"> </span></p> -<p id="t172" class="pln"><span class="strut"> </span></p> -<p id="t173" class="pln"> <span class="com"># black</span><span class="strut"> </span></p> -<p id="t174" class="stm mis"> <span class="key">elif</span> <span class="nam">color</span> <span class="op">==</span> <span class="str">'k'</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t175" class="stm mis"> <span class="nam">icon_color</span> <span class="op">=</span> <span class="nam">simplekml</span><span class="op">.</span><span class="nam">Color</span><span class="op">.</span><span class="nam">black</span><span class="strut"> </span></p> -<p id="t176" class="pln"><span class="strut"> </span></p> -<p id="t177" class="pln"> <span class="com"># assume color is passed as a KML hex value</span><span class="strut"> </span></p> -<p id="t178" class="pln"> <span class="key">else</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t179" class="stm mis"> <span class="nam">icon_color</span> <span class="op">=</span> <span class="nam">color</span><span class="strut"> </span></p> -<p id="t180" class="pln"><span class="strut"> </span></p> -<p id="t181" class="stm mis"> <span class="nam">style</span> <span class="op">=</span> <span class="nam">simplekml</span><span class="op">.</span><span class="nam">Style</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t182" class="stm mis"> <span class="nam">style</span><span class="op">.</span><span class="nam">iconstyle</span><span class="op">.</span><span class="nam">scale</span> <span class="op">=</span> <span class="nam">scale</span><span class="strut"> </span></p> -<p id="t183" class="stm mis"> <span class="nam">style</span><span class="op">.</span><span class="nam">iconstyle</span><span class="op">.</span><span class="nam">icon</span><span class="op">.</span><span class="nam">href</span> <span class="op">=</span> <span class="nam">icon_shape</span><span class="strut"> </span></p> -<p id="t184" class="stm mis"> <span class="nam">style</span><span class="op">.</span><span class="nam">iconstyle</span><span class="op">.</span><span class="nam">color</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t185" class="pln"> <span class="nam">simplekml</span><span class="op">.</span><span class="nam">Color</span><span class="op">.</span><span class="nam">changealphaint</span><span class="op">(</span><span class="nam">alphaint</span><span class="op">,</span> <span class="nam">icon_color</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t186" class="pln"><span class="strut"> </span></p> -<p id="t187" class="stm mis"> <span class="key">return</span> <span class="nam">style</span><span class="strut"> </span></p> -<p id="t188" class="pln"><span class="strut"> </span></p> -<p id="t189" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_interpolate_points</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">point_dist</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t190" class="pln"> <span class="str">"""</span><span class="strut"> </span></p> -<p id="t191" class="pln"><span class="strut"> </span></p> -<p id="t192" class="pln"><span class="str"> Parameters</span><span class="strut"> </span></p> -<p id="t193" class="pln"><span class="str"> ----------</span><span class="strut"> </span></p> -<p id="t194" class="pln"><span class="str"> point_dist : float, numpy.ndarray</span><span class="strut"> </span></p> -<p id="t195" class="pln"><span class="strut"> </span></p> -<p id="t196" class="pln"><span class="str"> Returns</span><span class="strut"> </span></p> -<p id="t197" class="pln"><span class="str"> -------</span><span class="strut"> </span></p> -<p id="t198" class="pln"><span class="str"> latitude, longitude : float, numpy.ndarray</span><span class="strut"> </span></p> -<p id="t199" class="pln"><span class="strut"> </span></p> -<p id="t200" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t201" class="pln"><span class="strut"> </span></p> -<p id="t202" class="stm mis"> <span class="nam">latitude</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">interp</span><span class="op">(</span><span class="nam">point_dist</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t203" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">_centerline_coords</span><span class="op">[</span><span class="op">:</span><span class="op">,</span> <span class="num">0</span><span class="op">]</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t204" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">_centerline_coords</span><span class="op">[</span><span class="op">:</span><span class="op">,</span> <span class="num">1</span><span class="op">]</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t205" class="stm mis"> <span class="nam">longitude</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">interp</span><span class="op">(</span><span class="nam">point_dist</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t206" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">_centerline_coords</span><span class="op">[</span><span class="op">:</span><span class="op">,</span> <span class="num">0</span><span class="op">]</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t207" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">_centerline_coords</span><span class="op">[</span><span class="op">:</span><span class="op">,</span> <span class="num">2</span><span class="op">]</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t208" class="pln"><span class="strut"> </span></p> -<p id="t209" class="stm mis"> <span class="key">return</span> <span class="nam">latitude</span><span class="op">,</span> <span class="nam">longitude</span><span class="strut"> </span></p> -<p id="t210" class="pln"><span class="strut"> </span></p> -<p id="t211" class="stm run hide_run"> <span class="key">def</span> <span class="nam">kml_particle_locations</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">point_dist</span><span class="op">,</span> <span class="nam">depth_fraction</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t212" class="pln"> <span class="str">"""KML text containing georeferenced points</span><span class="strut"> </span></p> -<p id="t213" class="pln"><span class="strut"> </span></p> -<p id="t214" class="pln"><span class="str"> Parameters</span><span class="strut"> </span></p> -<p id="t215" class="pln"><span class="str"> ----------</span><span class="strut"> </span></p> -<p id="t216" class="pln"><span class="str"> point_dist : numpy.ndarray</span><span class="strut"> </span></p> -<p id="t217" class="pln"><span class="str"> Stream distance of points (distance downstream).</span><span class="strut"> </span></p> -<p id="t218" class="pln"><span class="str"> depth_fraction : numpy.ndarray</span><span class="strut"> </span></p> -<p id="t219" class="pln"><span class="str"> Depth fraction of points. Depth fraction is the fractional height</span><span class="strut"> </span></p> -<p id="t220" class="pln"><span class="strut"> </span></p> -<p id="t221" class="pln"><span class="str"> Returns</span><span class="strut"> </span></p> -<p id="t222" class="pln"><span class="str"> -------</span><span class="strut"> </span></p> -<p id="t223" class="pln"><span class="str"> str</span><span class="strut"> </span></p> -<p id="t224" class="pln"><span class="strut"> </span></p> -<p id="t225" class="pln"><span class="str"> Notes</span><span class="strut"> </span></p> -<p id="t226" class="pln"><span class="str"> -----</span><span class="strut"> </span></p> -<p id="t227" class="pln"><span class="str"> Particles with depth fractions greater than or equal to 0.05 are</span><span class="strut"> </span></p> -<p id="t228" class="pln"><span class="str"> shown as suspended particles.</span><span class="strut"> </span></p> -<p id="t229" class="pln"><span class="strut"> </span></p> -<p id="t230" class="pln"><span class="str"> See also</span><span class="strut"> </span></p> -<p id="t231" class="pln"><span class="str"> --------</span><span class="strut"> </span></p> -<p id="t232" class="pln"><span class="str"> write_locations : Write points to a KML file</span><span class="strut"> </span></p> -<p id="t233" class="pln"><span class="strut"> </span></p> -<p id="t234" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t235" class="pln"><span class="strut"> </span></p> -<p id="t236" class="pln"> <span class="com"># eggs greater than suspended_depth_fraction are shown as suspended</span><span class="strut"> </span></p> -<p id="t237" class="stm mis"> <span class="nam">suspended_depth_fraction</span> <span class="op">=</span> <span class="num">0.05</span><span class="strut"> </span></p> -<p id="t238" class="pln"><span class="strut"> </span></p> -<p id="t239" class="stm mis"> <span class="key">if</span> <span class="nam">point_dist</span><span class="op">.</span><span class="nam">ndim</span> <span class="op">!=</span> <span class="num">1</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t240" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="str">"point_dist must be a one-dimensional array"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t241" class="pln"><span class="strut"> </span></p> -<p id="t242" class="stm mis"> <span class="key">if</span> <span class="nam">depth_fraction</span><span class="op">.</span><span class="nam">ndim</span> <span class="op">!=</span> <span class="num">1</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t243" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="str">"depth_fraction must be a one-dimensional array"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t244" class="pln"><span class="strut"> </span></p> -<p id="t245" class="stm mis"> <span class="key">if</span> <span class="key">not</span> <span class="nam">point_dist</span><span class="op">.</span><span class="nam">shape</span> <span class="op">==</span> <span class="nam">depth_fraction</span><span class="op">.</span><span class="nam">shape</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t246" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="str">"point_dist and depth_fraction must have "</span> <span class="op">+</span><span class="strut"> </span></p> -<p id="t247" class="pln"> <span class="str">"the same shape"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t248" class="pln"><span class="strut"> </span></p> -<p id="t249" class="stm mis"> <span class="nam">suspended_index</span> <span class="op">=</span> <span class="nam">suspended_depth_fraction</span> <span class="op"><=</span> <span class="nam">depth_fraction</span><span class="strut"> </span></p> -<p id="t250" class="pln"><span class="strut"> </span></p> -<p id="t251" class="stm mis"> <span class="nam">latitude</span><span class="op">,</span> <span class="nam">longitude</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_interpolate_points</span><span class="op">(</span><span class="nam">point_dist</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t252" class="pln"><span class="strut"> </span></p> -<p id="t253" class="stm mis"> <span class="nam">kml</span> <span class="op">=</span> <span class="nam">simplekml</span><span class="op">.</span><span class="nam">Kml</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t254" class="pln"><span class="strut"> </span></p> -<p id="t255" class="stm mis"> <span class="nam">point_shape</span> <span class="op">=</span> <span class="str">'dot'</span><span class="strut"> </span></p> -<p id="t256" class="stm mis"> <span class="nam">point_scale</span> <span class="op">=</span> <span class="num">0.4</span><span class="strut"> </span></p> -<p id="t257" class="stm mis"> <span class="nam">suspended_color</span> <span class="op">=</span> <span class="str">'y'</span><span class="strut"> </span></p> -<p id="t258" class="stm mis"> <span class="nam">bottom_color</span> <span class="op">=</span> <span class="str">'m'</span><span class="strut"> </span></p> -<p id="t259" class="pln"><span class="strut"> </span></p> -<p id="t260" class="pln"> <span class="com"># add suspended points</span><span class="strut"> </span></p> -<p id="t261" class="stm mis"> <span class="nam">style</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_get_point_style</span><span class="op">(</span><span class="nam">point_shape</span><span class="op">,</span> <span class="nam">suspended_color</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t262" class="pln"> <span class="nam">point_scale</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t263" class="stm mis"> <span class="key">for</span> <span class="nam">lat</span><span class="op">,</span> <span class="nam">lon</span> <span class="key">in</span> <span class="nam">zip</span><span class="op">(</span><span class="nam">latitude</span><span class="op">[</span><span class="nam">suspended_index</span><span class="op">]</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t264" class="pln"> <span class="nam">longitude</span><span class="op">[</span><span class="nam">suspended_index</span><span class="op">]</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t265" class="stm mis"> <span class="nam">pnt</span> <span class="op">=</span> <span class="nam">kml</span><span class="op">.</span><span class="nam">newpoint</span><span class="op">(</span><span class="nam">coords</span><span class="op">=</span><span class="op">[</span><span class="op">(</span><span class="nam">lat</span><span class="op">,</span> <span class="nam">lon</span><span class="op">)</span><span class="op">]</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t266" class="stm mis"> <span class="nam">pnt</span><span class="op">.</span><span class="nam">style</span> <span class="op">=</span> <span class="nam">style</span><span class="strut"> </span></p> -<p id="t267" class="pln"><span class="strut"> </span></p> -<p id="t268" class="pln"> <span class="com"># add non-suspended (bottom) points</span><span class="strut"> </span></p> -<p id="t269" class="stm mis"> <span class="nam">style</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_get_point_style</span><span class="op">(</span><span class="nam">point_shape</span><span class="op">,</span> <span class="nam">bottom_color</span><span class="op">,</span> <span class="nam">point_scale</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t270" class="stm mis"> <span class="key">for</span> <span class="nam">lat</span><span class="op">,</span> <span class="nam">lon</span> <span class="key">in</span> <span class="nam">zip</span><span class="op">(</span><span class="nam">latitude</span><span class="op">[</span><span class="op">~</span><span class="nam">suspended_index</span><span class="op">]</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t271" class="pln"> <span class="nam">longitude</span><span class="op">[</span><span class="op">~</span><span class="nam">suspended_index</span><span class="op">]</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t272" class="stm mis"> <span class="nam">pnt</span> <span class="op">=</span> <span class="nam">kml</span><span class="op">.</span><span class="nam">newpoint</span><span class="op">(</span><span class="nam">coords</span><span class="op">=</span><span class="op">[</span><span class="op">(</span><span class="nam">lat</span><span class="op">,</span> <span class="nam">lon</span><span class="op">)</span><span class="op">]</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t273" class="stm mis"> <span class="nam">pnt</span><span class="op">.</span><span class="nam">style</span> <span class="op">=</span> <span class="nam">style</span><span class="strut"> </span></p> -<p id="t274" class="pln"><span class="strut"> </span></p> -<p id="t275" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">_add_spawning_location</span><span class="op">(</span><span class="nam">kml</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t276" class="pln"><span class="strut"> </span></p> -<p id="t277" class="stm mis"> <span class="key">return</span> <span class="nam">kml</span><span class="op">.</span><span class="nam">kml</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t278" class="pln"><span class="strut"> </span></p> -<p id="t279" class="stm run hide_run"> <span class="key">def</span> <span class="nam">kml_spawning_location</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t280" class="pln"> <span class="str">"""KML text containing georeferenced spawning location</span><span class="strut"> </span></p> -<p id="t281" class="pln"><span class="strut"> </span></p> -<p id="t282" class="pln"><span class="str"> Returns</span><span class="strut"> </span></p> -<p id="t283" class="pln"><span class="str"> -------</span><span class="strut"> </span></p> -<p id="t284" class="pln"><span class="str"> str</span><span class="strut"> </span></p> -<p id="t285" class="pln"><span class="strut"> </span></p> -<p id="t286" class="pln"><span class="str"> See also</span><span class="strut"> </span></p> -<p id="t287" class="pln"><span class="str"> --------</span><span class="strut"> </span></p> -<p id="t288" class="pln"><span class="str"> write_locations : Write points to a KML file</span><span class="strut"> </span></p> -<p id="t289" class="pln"><span class="strut"> </span></p> -<p id="t290" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t291" class="pln"><span class="strut"> </span></p> -<p id="t292" class="stm mis"> <span class="nam">kml</span> <span class="op">=</span> <span class="nam">simplekml</span><span class="op">.</span><span class="nam">Kml</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t293" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">_add_spawning_location</span><span class="op">(</span><span class="nam">kml</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t294" class="pln"><span class="strut"> </span></p> -<p id="t295" class="stm mis"> <span class="key">return</span> <span class="nam">kml</span><span class="op">.</span><span class="nam">kml</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t296" class="pln"><span class="strut"> </span></p> -<p id="t297" class="stm run hide_run"> <span class="key">def</span> <span class="nam">kml_quantiles</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">point_dist</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t298" class="pln"> <span class="str">"""KML text containing georeferenced quantiles of particle locations.</span><span class="strut"> </span></p> -<p id="t299" class="pln"><span class="strut"> </span></p> -<p id="t300" class="pln"><span class="str"> Parameters</span><span class="strut"> </span></p> -<p id="t301" class="pln"><span class="str"> ----------</span><span class="strut"> </span></p> -<p id="t302" class="pln"><span class="str"> point_dist : numpy.ndarray</span><span class="strut"> </span></p> -<p id="t303" class="pln"><span class="str"> Stream distance of points (distance downstream).</span><span class="strut"> </span></p> -<p id="t304" class="pln"><span class="strut"> </span></p> -<p id="t305" class="pln"><span class="str"> Returns</span><span class="strut"> </span></p> -<p id="t306" class="pln"><span class="str"> -------</span><span class="strut"> </span></p> -<p id="t307" class="pln"><span class="str"> str</span><span class="strut"> </span></p> -<p id="t308" class="pln"><span class="strut"> </span></p> -<p id="t309" class="pln"><span class="str"> Notes</span><span class="strut"> </span></p> -<p id="t310" class="pln"><span class="str"> -----</span><span class="strut"> </span></p> -<p id="t311" class="pln"><span class="str"> Locations for the 0, 0.10, 0.25, 0.50, 0.75, 0.90, and 1 quantiles are</span><span class="strut"> </span></p> -<p id="t312" class="pln"><span class="str"> included in the KML string.</span><span class="strut"> </span></p> -<p id="t313" class="pln"><span class="strut"> </span></p> -<p id="t314" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t315" class="pln"><span class="strut"> </span></p> -<p id="t316" class="stm mis"> <span class="nam">kml</span> <span class="op">=</span> <span class="nam">simplekml</span><span class="op">.</span><span class="nam">Kml</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t317" class="pln"><span class="strut"> </span></p> -<p id="t318" class="stm mis"> <span class="nam">quantiles</span> <span class="op">=</span> <span class="op">[</span><span class="num">0</span><span class="op">,</span> <span class="num">0.10</span><span class="op">,</span> <span class="num">0.25</span><span class="op">,</span> <span class="num">0.50</span><span class="op">,</span> <span class="num">0.75</span><span class="op">,</span> <span class="num">0.90</span><span class="op">,</span> <span class="num">1.</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t319" class="pln"><span class="strut"> </span></p> -<p id="t320" class="stm mis"> <span class="nam">computed_quantiles</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">quantile</span><span class="op">(</span><span class="nam">point_dist</span><span class="op">,</span> <span class="nam">quantiles</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t321" class="pln"> <span class="nam">interpolation</span><span class="op">=</span><span class="str">'nearest'</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t322" class="pln"><span class="strut"> </span></p> -<p id="t323" class="stm mis"> <span class="nam">la</span><span class="op">,</span> <span class="nam">lo</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_interpolate_points</span><span class="op">(</span><span class="nam">computed_quantiles</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t324" class="pln"><span class="strut"> </span></p> -<p id="t325" class="stm mis"> <span class="key">for</span> <span class="nam">i</span><span class="op">,</span> <span class="op">(</span><span class="nam">lat</span><span class="op">,</span> <span class="nam">lon</span><span class="op">)</span> <span class="key">in</span> <span class="nam">enumerate</span><span class="op">(</span><span class="nam">zip</span><span class="op">(</span><span class="nam">la</span><span class="op">,</span> <span class="nam">lo</span><span class="op">)</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t326" class="stm mis"> <span class="nam">q</span> <span class="op">=</span> <span class="nam">quantiles</span><span class="op">[</span><span class="nam">i</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t327" class="stm mis"> <span class="nam">pnt</span> <span class="op">=</span> <span class="nam">kml</span><span class="op">.</span><span class="nam">newpoint</span><span class="op">(</span><span class="nam">name</span><span class="op">=</span><span class="nam">str</span><span class="op">(</span><span class="nam">q</span><span class="op">)</span><span class="op">,</span> <span class="nam">coords</span><span class="op">=</span><span class="op">[</span><span class="op">(</span><span class="nam">lat</span><span class="op">,</span> <span class="nam">lon</span><span class="op">)</span><span class="op">]</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t328" class="stm mis"> <span class="nam">X</span> <span class="op">=</span> <span class="num">1</span> <span class="op">-</span> <span class="nam">abs</span><span class="op">(</span><span class="nam">q</span> <span class="op">-</span> <span class="num">0.5</span><span class="op">)</span><span class="op">/</span><span class="num">0.5</span><span class="strut"> </span></p> -<p id="t329" class="stm mis"> <span class="nam">rgba</span> <span class="op">=</span> <span class="nam">jet_cm</span><span class="op">(</span><span class="nam">X</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t330" class="stm mis"> <span class="nam">red_value</span> <span class="op">=</span> <span class="nam">int</span><span class="op">(</span><span class="nam">rgba</span><span class="op">[</span><span class="num">0</span><span class="op">]</span> <span class="op">*</span> <span class="num">255</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t331" class="stm mis"> <span class="nam">green_value</span> <span class="op">=</span> <span class="nam">int</span><span class="op">(</span><span class="nam">rgba</span><span class="op">[</span><span class="num">1</span><span class="op">]</span> <span class="op">*</span> <span class="num">255</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t332" class="stm mis"> <span class="nam">blue_value</span> <span class="op">=</span> <span class="nam">int</span><span class="op">(</span><span class="nam">rgba</span><span class="op">[</span><span class="num">2</span><span class="op">]</span> <span class="op">*</span> <span class="num">255</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t333" class="stm mis"> <span class="nam">color</span> <span class="op">=</span> <span class="nam">simplekml</span><span class="op">.</span><span class="nam">Color</span><span class="op">.</span><span class="nam">rgb</span><span class="op">(</span><span class="strut"> </span></p> -<p id="t334" class="pln"> <span class="nam">red_value</span><span class="op">,</span> <span class="nam">green_value</span><span class="op">,</span> <span class="nam">blue_value</span><span class="op">,</span> <span class="num">255</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t335" class="stm mis"> <span class="nam">style</span> <span class="op">=</span> <span class="nam">simplekml</span><span class="op">.</span><span class="nam">Style</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t336" class="stm mis"> <span class="nam">style</span><span class="op">.</span><span class="nam">iconstyle</span><span class="op">.</span><span class="nam">scale</span> <span class="op">=</span> <span class="num">1.25</span><span class="strut"> </span></p> -<p id="t337" class="stm mis"> <span class="nam">style</span><span class="op">.</span><span class="nam">iconstyle</span><span class="op">.</span><span class="nam">color</span> <span class="op">=</span> <span class="nam">color</span><span class="strut"> </span></p> -<p id="t338" class="stm mis"> <span class="nam">style</span><span class="op">.</span><span class="nam">iconstyle</span><span class="op">.</span><span class="nam">icon</span><span class="op">.</span><span class="nam">href</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t339" class="pln"> <span class="str">'http://maps.google.com/mapfiles/kml/shapes/'</span> <span class="op">+</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t340" class="pln"> <span class="str">'placemark_square.png'</span><span class="strut"> </span></p> -<p id="t341" class="stm mis"> <span class="nam">pnt</span><span class="op">.</span><span class="nam">style</span> <span class="op">=</span> <span class="nam">style</span><span class="strut"> </span></p> -<p id="t342" class="pln"><span class="strut"> </span></p> -<p id="t343" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">_add_spawning_location</span><span class="op">(</span><span class="nam">kml</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t344" class="pln"><span class="strut"> </span></p> -<p id="t345" class="stm mis"> <span class="key">return</span> <span class="nam">kml</span><span class="op">.</span><span class="nam">kml</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t346" class="pln"><span class="strut"> </span></p> -<p id="t347" class="stm run hide_run"> <span class="key">def</span> <span class="nam">write_locations</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">point_dist</span><span class="op">,</span> <span class="nam">depth_fraction</span><span class="op">,</span> <span class="nam">kml_path</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t348" class="pln"> <span class="str">"""Write particle locations to a KML file</span><span class="strut"> </span></p> -<p id="t349" class="pln"><span class="strut"> </span></p> -<p id="t350" class="pln"><span class="str"> Parameters</span><span class="strut"> </span></p> -<p id="t351" class="pln"><span class="str"> ----------</span><span class="strut"> </span></p> -<p id="t352" class="pln"><span class="str"> point_dist : numpy.ndarray</span><span class="strut"> </span></p> -<p id="t353" class="pln"><span class="str"> Stream distance of points (distance downstream).</span><span class="strut"> </span></p> -<p id="t354" class="pln"><span class="str"> depth_fraction : numpy.ndarray</span><span class="strut"> </span></p> -<p id="t355" class="pln"><span class="str"> Depth fraction of points. Depth fraction is the fractional height</span><span class="strut"> </span></p> -<p id="t356" class="pln"><span class="str"> above the bed.</span><span class="strut"> </span></p> -<p id="t357" class="pln"><span class="str"> kml_path : str</span><span class="strut"> </span></p> -<p id="t358" class="pln"><span class="str"> Path to write KML file to.</span><span class="strut"> </span></p> -<p id="t359" class="pln"><span class="strut"> </span></p> -<p id="t360" class="pln"><span class="str"> Notes</span><span class="strut"> </span></p> -<p id="t361" class="pln"><span class="str"> -----</span><span class="strut"> </span></p> -<p id="t362" class="pln"><span class="str"> Particles with depth fractions greater than or equal to 0.05 are</span><span class="strut"> </span></p> -<p id="t363" class="pln"><span class="str"> shown as suspended particles.</span><span class="strut"> </span></p> -<p id="t364" class="pln"><span class="strut"> </span></p> -<p id="t365" class="pln"><span class="str"> See also</span><span class="strut"> </span></p> -<p id="t366" class="pln"><span class="str"> --------</span><span class="strut"> </span></p> -<p id="t367" class="pln"><span class="str"> kml_particle_locations : KML text containing georeferenced particle</span><span class="strut"> </span></p> -<p id="t368" class="pln"><span class="str"> locations.</span><span class="strut"> </span></p> -<p id="t369" class="pln"><span class="strut"> </span></p> -<p id="t370" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t371" class="pln"><span class="strut"> </span></p> -<p id="t372" class="stm mis"> <span class="nam">kml</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">kml_particle_locations</span><span class="op">(</span><span class="nam">point_dist</span><span class="op">,</span> <span class="nam">depth_fraction</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t373" class="pln"><span class="strut"> </span></p> -<p id="t374" class="stm mis"> <span class="key">with</span> <span class="nam">open</span><span class="op">(</span><span class="nam">kml_path</span><span class="op">,</span> <span class="str">'w'</span><span class="op">)</span> <span class="key">as</span> <span class="nam">f</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t375" class="stm mis"> <span class="nam">f</span><span class="op">.</span><span class="nam">writelines</span><span class="op">(</span><span class="nam">kml</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t376" class="pln"><span class="strut"> </span></p> -<p id="t377" class="stm run hide_run"> <span class="key">def</span> <span class="nam">write_spawning_location</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">kml_path</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t378" class="pln"> <span class="str">"""Write spawning location to a KML file</span><span class="strut"> </span></p> -<p id="t379" class="pln"><span class="strut"> </span></p> -<p id="t380" class="pln"><span class="str"> Parameters</span><span class="strut"> </span></p> -<p id="t381" class="pln"><span class="str"> ----------</span><span class="strut"> </span></p> -<p id="t382" class="pln"><span class="str"> kml_path : str</span><span class="strut"> </span></p> -<p id="t383" class="pln"><span class="strut"> </span></p> -<p id="t384" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t385" class="pln"><span class="strut"> </span></p> -<p id="t386" class="stm mis"> <span class="nam">kml</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">kml_spawning_location</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t387" class="pln"><span class="strut"> </span></p> -<p id="t388" class="stm mis"> <span class="key">with</span> <span class="nam">open</span><span class="op">(</span><span class="nam">kml_path</span><span class="op">,</span> <span class="str">'w'</span><span class="op">)</span> <span class="key">as</span> <span class="nam">f</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t389" class="stm mis"> <span class="nam">f</span><span class="op">.</span><span class="nam">writelines</span><span class="op">(</span><span class="nam">kml</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t390" class="pln"><span class="strut"> </span></p> -<p id="t391" class="stm run hide_run"> <span class="key">def</span> <span class="nam">write_quantiles</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">point_dist</span><span class="op">,</span> <span class="nam">kml_path</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t392" class="pln"> <span class="str">"""</span><span class="strut"> </span></p> -<p id="t393" class="pln"><span class="strut"> </span></p> -<p id="t394" class="pln"><span class="str"> Parameters</span><span class="strut"> </span></p> -<p id="t395" class="pln"><span class="str"> ----------</span><span class="strut"> </span></p> -<p id="t396" class="pln"><span class="str"> point_dist : numpy.ndarray</span><span class="strut"> </span></p> -<p id="t397" class="pln"><span class="str"> kml_path : str</span><span class="strut"> </span></p> -<p id="t398" class="pln"><span class="strut"> </span></p> -<p id="t399" class="pln"><span class="str"> See also</span><span class="strut"> </span></p> -<p id="t400" class="pln"><span class="str"> --------</span><span class="strut"> </span></p> -<p id="t401" class="pln"><span class="str"> kml_quantiles : KML text containing georeferenced quantiles of particle</span><span class="strut"> </span></p> -<p id="t402" class="pln"><span class="str"> locations.</span><span class="strut"> </span></p> -<p id="t403" class="pln"><span class="strut"> </span></p> -<p id="t404" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t405" class="pln"><span class="strut"> </span></p> -<p id="t406" class="stm mis"> <span class="nam">kml</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">kml_quantiles</span><span class="op">(</span><span class="nam">point_dist</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t407" class="pln"><span class="strut"> </span></p> -<p id="t408" class="stm mis"> <span class="key">with</span> <span class="nam">open</span><span class="op">(</span><span class="nam">kml_path</span><span class="op">,</span> <span class="str">'w'</span><span class="op">)</span> <span class="key">as</span> <span class="nam">f</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t409" class="stm mis"> <span class="nam">f</span><span class="op">.</span><span class="nam">writelines</span><span class="op">(</span><span class="nam">kml</span><span class="op">)</span><span class="strut"> </span></p> - - </td> - </tr> - </table> -</div> - -<div id="footer"> - <div class="content"> - <p> - <a class="nav" href="index.html">« index</a> <a class="nav" href="https://coverage.readthedocs.io">coverage.py v4.5.3</a>, - created at 2019-07-09 15:15 - </p> - </div> -</div> - -</body> -</html> diff --git a/coverage_report/fluegg_random_py.html b/coverage_report/fluegg_random_py.html deleted file mode 100644 index 1726c11..0000000 --- a/coverage_report/fluegg_random_py.html +++ /dev/null @@ -1,271 +0,0 @@ - - - -<!DOCTYPE html> -<html> -<head> - <meta http-equiv="Content-Type" content="text/html; charset=utf-8"> - - - <meta http-equiv="X-UA-Compatible" content="IE=emulateIE7" /> - <title>Coverage for fluegg\random.py: 50%</title> - <link rel="stylesheet" href="style.css" type="text/css"> - - <script type="text/javascript" src="jquery.min.js"></script> - <script type="text/javascript" src="jquery.hotkeys.js"></script> - <script type="text/javascript" src="jquery.isonscreen.js"></script> - <script type="text/javascript" src="coverage_html.js"></script> - <script type="text/javascript"> - jQuery(document).ready(coverage.pyfile_ready); - </script> -</head> -<body class="pyfile"> - -<div id="header"> - <div class="content"> - <h1>Coverage for <b>fluegg\random.py</b> : - <span class="pc_cov">50%</span> - </h1> - - <img id="keyboard_icon" src="keybd_closed.png" alt="Show keyboard shortcuts" /> - - <h2 class="stats"> - 36 statements - <span class="run hide_run shortkey_r button_toggle_run">18 run</span> - <span class="mis shortkey_m button_toggle_mis">18 missing</span> - <span class="exc shortkey_x button_toggle_exc">0 excluded</span> - - - </h2> - </div> -</div> - -<div class="help_panel"> - <img id="panel_icon" src="keybd_open.png" alt="Hide keyboard shortcuts" /> - <p class="legend">Hot-keys on this page</p> - <div> - <p class="keyhelp"> - 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href="#n46">46</a></p> -<p id="n47" class="pln"><a href="#n47">47</a></p> -<p id="n48" class="stm run hide_run"><a href="#n48">48</a></p> -<p id="n49" class="pln"><a href="#n49">49</a></p> -<p id="n50" class="pln"><a href="#n50">50</a></p> -<p id="n51" class="pln"><a href="#n51">51</a></p> -<p id="n52" class="pln"><a href="#n52">52</a></p> -<p id="n53" class="pln"><a href="#n53">53</a></p> -<p id="n54" class="pln"><a href="#n54">54</a></p> -<p id="n55" class="pln"><a href="#n55">55</a></p> -<p id="n56" class="pln"><a href="#n56">56</a></p> -<p id="n57" class="pln"><a href="#n57">57</a></p> -<p id="n58" class="pln"><a href="#n58">58</a></p> -<p id="n59" class="pln"><a href="#n59">59</a></p> -<p id="n60" class="stm run hide_run"><a href="#n60">60</a></p> -<p id="n61" class="pln"><a href="#n61">61</a></p> -<p id="n62" class="stm mis"><a href="#n62">62</a></p> -<p id="n63" class="stm mis"><a href="#n63">63</a></p> -<p id="n64" class="pln"><a href="#n64">64</a></p> -<p id="n65" class="stm mis"><a href="#n65">65</a></p> -<p id="n66" class="stm mis"><a href="#n66">66</a></p> -<p id="n67" class="pln"><a href="#n67">67</a></p> -<p id="n68" class="stm run hide_run"><a href="#n68">68</a></p> -<p id="n69" class="pln"><a href="#n69">69</a></p> -<p id="n70" class="stm mis"><a href="#n70">70</a></p> -<p id="n71" class="stm mis"><a href="#n71">71</a></p> -<p id="n72" class="pln"><a href="#n72">72</a></p> -<p id="n73" class="stm mis"><a href="#n73">73</a></p> -<p id="n74" class="pln"><a href="#n74">74</a></p> -<p id="n75" class="stm mis"><a href="#n75">75</a></p> -<p id="n76" class="pln"><a href="#n76">76</a></p> -<p id="n77" class="stm run hide_run"><a href="#n77">77</a></p> -<p id="n78" class="pln"><a href="#n78">78</a></p> -<p id="n79" class="stm mis"><a href="#n79">79</a></p> -<p id="n80" class="stm mis"><a href="#n80">80</a></p> -<p id="n81" class="pln"><a href="#n81">81</a></p> -<p id="n82" class="stm mis"><a href="#n82">82</a></p> -<p id="n83" class="stm mis"><a href="#n83">83</a></p> -<p id="n84" class="pln"><a href="#n84">84</a></p> -<p id="n85" class="pln"><a href="#n85">85</a></p> -<p id="n86" class="stm mis"><a href="#n86">86</a></p> -<p id="n87" class="stm mis"><a href="#n87">87</a></p> -<p id="n88" class="pln"><a href="#n88">88</a></p> -<p id="n89" class="stm mis"><a href="#n89">89</a></p> -<p id="n90" class="pln"><a href="#n90">90</a></p> -<p id="n91" class="stm mis"><a href="#n91">91</a></p> - - </td> - <td class="text"> -<p id="t1" class="stm run hide_run"><span class="key">from</span> <span class="nam">abc</span> <span class="key">import</span> <span class="nam">abstractmethod</span><span class="strut"> </span></p> -<p id="t2" class="pln"><span class="strut"> </span></p> -<p id="t3" class="stm run hide_run"><span class="key">import</span> <span class="nam">h5py</span><span class="strut"> </span></p> -<p id="t4" class="stm run hide_run"><span class="key">import</span> <span class="nam">numpy</span> <span class="key">as</span> <span class="nam">np</span><span class="strut"> </span></p> -<p id="t5" class="pln"><span class="strut"> </span></p> -<p id="t6" class="pln"><span class="strut"> </span></p> -<p id="t7" class="stm run hide_run"><span class="key">class</span> <span class="nam">RandomNumbers</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t8" class="pln"><span class="strut"> </span></p> -<p id="t9" class="stm run hide_run"> <span class="op">@</span><span class="nam">abstractmethod</span><span class="strut"> </span></p> -<p id="t10" class="pln"> <span class="key">def</span> <span class="nam">random</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">mean</span><span class="op">,</span> <span class="nam">std</span><span class="op">,</span> <span class="nam">size</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t11" class="stm mis"> <span class="key">raise</span> <span class="nam">NotImplementedError</span><span class="strut"> </span></p> -<p id="t12" class="pln"><span class="strut"> </span></p> -<p id="t13" class="pln"><span class="strut"> </span></p> -<p id="t14" class="stm run hide_run"><span class="key">class</span> <span class="nam">NormalRandomNumbers</span><span class="op">(</span><span class="nam">RandomNumbers</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t15" class="pln"> <span class="str">"""Returns normally distributed random numbers.</span><span class="strut"> </span></p> -<p id="t16" class="pln"><span class="strut"> </span></p> -<p id="t17" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t18" class="pln"><span class="strut"> </span></p> -<p id="t19" class="stm run hide_run"> <span class="key">def</span> <span class="nam">random</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">mean</span><span class="op">,</span> <span class="nam">std</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t20" class="pln"> <span class="str">"""Returns a normally distributed random number</span><span class="strut"> </span></p> -<p id="t21" class="pln"><span class="strut"> </span></p> -<p id="t22" class="pln"><span class="str"> Notes</span><span class="strut"> </span></p> -<p id="t23" class="pln"><span class="str"> -----</span><span class="strut"> </span></p> -<p id="t24" class="pln"><span class="str"> Calls numpy.random.normal for random numbers</span><span class="strut"> </span></p> -<p id="t25" class="pln"><span class="strut"> </span></p> -<p id="t26" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t27" class="stm run hide_run"> <span class="key">return</span> <span class="nam">np</span><span class="op">.</span><span class="nam">random</span><span class="op">.</span><span class="nam">normal</span><span class="op">(</span><span class="nam">loc</span><span class="op">=</span><span class="nam">mean</span><span class="op">,</span> <span class="nam">scale</span><span class="op">=</span><span class="nam">std</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t28" class="pln"><span class="strut"> </span></p> -<p id="t29" class="stm run hide_run"> <span class="key">def</span> <span class="nam">random_array</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">mean</span><span class="op">,</span> <span class="nam">std</span><span class="op">,</span> <span class="nam">size</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t30" class="pln"> <span class="str">"""Returns an array of normally distributed random numbers</span><span class="strut"> </span></p> -<p id="t31" class="pln"><span class="strut"> </span></p> -<p id="t32" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t33" class="stm mis"> <span class="key">return</span> <span class="nam">np</span><span class="op">.</span><span class="nam">random</span><span class="op">.</span><span class="nam">normal</span><span class="op">(</span><span class="nam">loc</span><span class="op">=</span><span class="nam">mean</span><span class="op">,</span> <span class="nam">scale</span><span class="op">=</span><span class="nam">std</span><span class="op">,</span> <span class="nam">size</span><span class="op">=</span><span class="nam">size</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t34" class="pln"><span class="strut"> </span></p> -<p id="t35" class="pln"><span class="strut"> </span></p> -<p id="t36" class="stm run hide_run"><span class="key">class</span> <span class="nam">NonRandomNumbers</span><span class="op">(</span><span class="nam">RandomNumbers</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t37" class="pln"> <span class="str">"""Returns means instead of random numbers</span><span class="strut"> </span></p> -<p id="t38" class="pln"><span class="strut"> </span></p> -<p id="t39" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t40" class="pln"><span class="strut"> </span></p> -<p id="t41" class="stm run hide_run"> <span class="key">def</span> <span class="nam">random</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">mean</span><span class="op">,</span> <span class="nam">std</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t42" class="stm run hide_run"> <span class="key">return</span> <span class="nam">mean</span><span class="op">.</span><span class="nam">copy</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t43" class="pln"><span class="strut"> </span></p> -<p id="t44" class="stm run hide_run"> <span class="key">def</span> <span class="nam">random_array</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">mean</span><span class="op">,</span> <span class="nam">std</span><span class="op">,</span> <span class="nam">size</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t45" class="stm run hide_run"> <span class="key">return</span> <span class="nam">np</span><span class="op">.</span><span class="nam">tile</span><span class="op">(</span><span class="nam">mean</span><span class="op">,</span> <span class="nam">size</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t46" class="pln"><span class="strut"> </span></p> -<p id="t47" class="pln"><span class="strut"> </span></p> -<p id="t48" class="stm run hide_run"><span class="key">class</span> <span class="nam">HDF5NormalRandomNumbers</span><span class="op">(</span><span class="nam">RandomNumbers</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t49" class="pln"> <span class="str">"""Returns normal random numbers from an HDF5 file.</span><span class="strut"> </span></p> -<p id="t50" class="pln"><span class="strut"> </span></p> -<p id="t51" class="pln"><span class="str"> Parameters</span><span class="strut"> </span></p> -<p id="t52" class="pln"><span class="str"> ----------</span><span class="strut"> </span></p> -<p id="t53" class="pln"><span class="str"> file_path : str</span><span class="strut"> </span></p> -<p id="t54" class="pln"><span class="str"> Path to HDF5 file</span><span class="strut"> </span></p> -<p id="t55" class="pln"><span class="str"> data_set : str</span><span class="strut"> </span></p> -<p id="t56" class="pln"><span class="str"> Data set containing standard normal random numbers</span><span class="strut"> </span></p> -<p id="t57" class="pln"><span class="strut"> </span></p> -<p id="t58" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t59" class="pln"><span class="strut"> </span></p> -<p id="t60" class="stm run hide_run"> <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">file_path</span><span class="op">,</span> <span class="nam">data_set</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t61" class="pln"><span class="strut"> </span></p> -<p id="t62" class="stm mis"> <span class="key">with</span> <span class="nam">h5py</span><span class="op">.</span><span class="nam">File</span><span class="op">(</span><span class="nam">file_path</span><span class="op">,</span> <span class="str">'r'</span><span class="op">)</span> <span class="key">as</span> <span class="nam">f</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t63" class="stm mis"> <span class="nam">dset</span> <span class="op">=</span> <span class="nam">f</span><span class="op">[</span><span class="nam">data_set</span><span class="op">]</span><span class="op">[</span><span class="op">:</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t64" class="pln"><span class="strut"> </span></p> -<p id="t65" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">_dset</span> <span class="op">=</span> <span class="nam">dset</span><span class="strut"> </span></p> -<p id="t66" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">_index</span> <span class="op">=</span> <span class="num">0</span><span class="strut"> </span></p> -<p id="t67" class="pln"><span class="strut"> </span></p> -<p id="t68" class="stm run hide_run"> <span class="key">def</span> <span class="nam">random</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">mean</span><span class="op">,</span> <span class="nam">std</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t69" class="pln"><span class="strut"> </span></p> -<p id="t70" class="stm mis"> <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_index</span> <span class="op">></span> <span class="nam">len</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_dset</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t71" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="str">"No remaining random numbers"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t72" class="pln"><span class="strut"> </span></p> -<p id="t73" class="stm mis"> <span class="nam">size</span> <span class="op">=</span> <span class="nam">mean</span><span class="op">.</span><span class="nam">shape</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t74" class="pln"><span class="strut"> </span></p> -<p id="t75" class="stm mis"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">random_array</span><span class="op">(</span><span class="nam">mean</span><span class="op">,</span> <span class="nam">std</span><span class="op">,</span> <span class="nam">size</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t76" class="pln"><span class="strut"> </span></p> -<p id="t77" class="stm run hide_run"> <span class="key">def</span> <span class="nam">random_array</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">mean</span><span class="op">,</span> <span class="nam">std</span><span class="op">,</span> <span class="nam">size</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t78" class="pln"><span class="strut"> </span></p> -<p id="t79" class="stm mis"> <span class="nam">first_index</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_index</span><span class="strut"> </span></p> -<p id="t80" class="stm mis"> <span class="nam">last_index</span> <span class="op">=</span> <span class="nam">first_index</span> <span class="op">+</span> <span class="nam">size</span><span class="strut"> </span></p> -<p id="t81" class="pln"><span class="strut"> </span></p> -<p id="t82" class="stm mis"> <span class="key">if</span> <span class="nam">last_index</span> <span class="op">></span> <span class="nam">len</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_dset</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t83" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="strut"> </span></p> -<p id="t84" class="pln"> <span class="str">"`size` exceeds the number of remaining random numbers"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t85" class="pln"><span class="strut"> </span></p> -<p id="t86" class="stm mis"> <span class="nam">standard_values</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_dset</span><span class="op">[</span><span class="nam">first_index</span><span class="op">:</span><span class="nam">last_index</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t87" class="stm mis"> <span class="nam">scaled_values</span> <span class="op">=</span> <span class="nam">standard_values</span> <span class="op">*</span> <span class="nam">std</span> <span class="op">+</span> <span class="nam">mean</span><span class="strut"> </span></p> -<p id="t88" class="pln"><span class="strut"> </span></p> -<p id="t89" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">_index</span> <span class="op">=</span> <span class="nam">last_index</span><span class="strut"> </span></p> -<p id="t90" class="pln"><span class="strut"> </span></p> -<p id="t91" class="stm mis"> <span class="key">return</span> <span class="nam">scaled_values</span><span class="strut"> </span></p> - - </td> - </tr> - </table> -</div> - -<div id="footer"> - <div class="content"> - <p> - <a class="nav" href="index.html">« index</a> <a class="nav" href="https://coverage.readthedocs.io">coverage.py v4.5.3</a>, - created at 2019-07-09 15:15 - </p> - </div> -</div> - -</body> -</html> diff --git a/coverage_report/fluegg_ras_py.html b/coverage_report/fluegg_ras_py.html deleted file mode 100644 index c68a2ca..0000000 --- a/coverage_report/fluegg_ras_py.html +++ /dev/null @@ -1,1007 +0,0 @@ - - - -<!DOCTYPE html> -<html> -<head> - <meta http-equiv="Content-Type" content="text/html; charset=utf-8"> - - - <meta http-equiv="X-UA-Compatible" content="IE=emulateIE7" /> - <title>Coverage for fluegg\ras.py: 25%</title> - <link rel="stylesheet" href="style.css" type="text/css"> - - <script type="text/javascript" src="jquery.min.js"></script> - <script type="text/javascript" src="jquery.hotkeys.js"></script> - <script type="text/javascript" src="jquery.isonscreen.js"></script> - <script type="text/javascript" src="coverage_html.js"></script> - <script type="text/javascript"> - jQuery(document).ready(coverage.pyfile_ready); - </script> -</head> -<body class="pyfile"> - -<div id="header"> - <div class="content"> - <h1>Coverage for <b>fluegg\ras.py</b> : - <span class="pc_cov">25%</span> - </h1> - - <img id="keyboard_icon" src="keybd_closed.png" alt="Show keyboard shortcuts" /> - - <h2 class="stats"> - 197 statements - <span class="run hide_run shortkey_r button_toggle_run">49 run</span> - <span class="mis shortkey_m button_toggle_mis">148 missing</span> - <span class="exc 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class="pln"><a href="#n95">95</a></p> -<p id="n96" class="pln"><a href="#n96">96</a></p> -<p id="n97" class="stm mis"><a href="#n97">97</a></p> -<p id="n98" class="stm mis"><a href="#n98">98</a></p> -<p id="n99" class="pln"><a href="#n99">99</a></p> -<p id="n100" class="stm mis"><a href="#n100">100</a></p> -<p id="n101" class="stm mis"><a href="#n101">101</a></p> -<p id="n102" class="pln"><a href="#n102">102</a></p> -<p id="n103" class="stm mis"><a href="#n103">103</a></p> -<p id="n104" class="pln"><a href="#n104">104</a></p> -<p id="n105" class="stm mis"><a href="#n105">105</a></p> -<p id="n106" class="stm mis"><a href="#n106">106</a></p> -<p id="n107" class="stm mis"><a href="#n107">107</a></p> -<p id="n108" class="stm mis"><a href="#n108">108</a></p> -<p id="n109" class="stm mis"><a href="#n109">109</a></p> -<p id="n110" class="stm mis"><a href="#n110">110</a></p> -<p id="n111" class="stm mis"><a href="#n111">111</a></p> -<p id="n112" class="stm mis"><a href="#n112">112</a></p> -<p id="n113" class="pln"><a href="#n113">113</a></p> -<p id="n114" class="stm mis"><a href="#n114">114</a></p> -<p id="n115" class="pln"><a href="#n115">115</a></p> -<p id="n116" class="stm mis"><a href="#n116">116</a></p> -<p id="n117" class="stm mis"><a href="#n117">117</a></p> -<p id="n118" class="pln"><a href="#n118">118</a></p> -<p id="n119" class="stm mis"><a href="#n119">119</a></p> -<p id="n120" class="stm mis"><a href="#n120">120</a></p> -<p id="n121" class="pln"><a href="#n121">121</a></p> -<p id="n122" class="stm run hide_run"><a href="#n122">122</a></p> -<p id="n123" class="stm mis"><a href="#n123">123</a></p> -<p id="n124" class="pln"><a href="#n124">124</a></p> -<p id="n125" class="stm run hide_run"><a href="#n125">125</a></p> -<p id="n126" class="stm mis"><a href="#n126">126</a></p> -<p id="n127" class="pln"><a href="#n127">127</a></p> -<p id="n128" class="stm run hide_run"><a href="#n128">128</a></p> -<p id="n129" class="pln"><a href="#n129">129</a></p> -<p id="n130" class="stm mis"><a href="#n130">130</a></p> -<p id="n131" class="stm mis"><a href="#n131">131</a></p> -<p id="n132" class="stm mis"><a href="#n132">132</a></p> -<p id="n133" class="pln"><a href="#n133">133</a></p> -<p id="n134" class="stm mis"><a href="#n134">134</a></p> -<p id="n135" class="pln"><a href="#n135">135</a></p> -<p id="n136" class="stm mis"><a href="#n136">136</a></p> -<p id="n137" class="pln"><a href="#n137">137</a></p> -<p id="n138" class="pln"><a href="#n138">138</a></p> -<p id="n139" class="stm mis"><a href="#n139">139</a></p> -<p id="n140" class="pln"><a href="#n140">140</a></p> -<p id="n141" class="stm run hide_run"><a href="#n141">141</a></p> -<p id="n142" class="pln"><a href="#n142">142</a></p> -<p id="n143" class="pln"><a href="#n143">143</a></p> -<p id="n144" class="stm mis"><a href="#n144">144</a></p> -<p id="n145" class="stm mis"><a href="#n145">145</a></p> -<p id="n146" class="stm mis"><a href="#n146">146</a></p> -<p id="n147" class="pln"><a href="#n147">147</a></p> -<p id="n148" class="stm mis"><a href="#n148">148</a></p> -<p id="n149" class="stm mis"><a href="#n149">149</a></p> -<p id="n150" class="pln"><a href="#n150">150</a></p> -<p id="n151" class="stm mis"><a href="#n151">151</a></p> -<p id="n152" class="pln"><a href="#n152">152</a></p> -<p id="n153" class="stm run hide_run"><a href="#n153">153</a></p> -<p id="n154" class="pln"><a href="#n154">154</a></p> -<p id="n155" class="stm mis"><a href="#n155">155</a></p> -<p id="n156" class="pln"><a href="#n156">156</a></p> -<p id="n157" class="pln"><a href="#n157">157</a></p> -<p id="n158" class="stm mis"><a href="#n158">158</a></p> -<p id="n159" class="pln"><a href="#n159">159</a></p> -<p id="n160" class="stm mis"><a href="#n160">160</a></p> -<p id="n161" class="pln"><a href="#n161">161</a></p> -<p id="n162" class="stm mis"><a href="#n162">162</a></p> -<p id="n163" class="stm mis"><a href="#n163">163</a></p> -<p id="n164" class="pln"><a href="#n164">164</a></p> -<p id="n165" class="pln"><a href="#n165">165</a></p> -<p id="n166" class="stm mis"><a href="#n166">166</a></p> -<p id="n167" class="pln"><a href="#n167">167</a></p> -<p id="n168" class="stm mis"><a href="#n168">168</a></p> -<p id="n169" class="stm mis"><a href="#n169">169</a></p> -<p id="n170" class="pln"><a href="#n170">170</a></p> -<p id="n171" class="pln"><a href="#n171">171</a></p> -<p id="n172" class="stm mis"><a href="#n172">172</a></p> -<p id="n173" class="pln"><a href="#n173">173</a></p> -<p id="n174" class="stm mis"><a href="#n174">174</a></p> -<p id="n175" class="stm mis"><a href="#n175">175</a></p> -<p id="n176" class="pln"><a href="#n176">176</a></p> -<p id="n177" class="stm mis"><a href="#n177">177</a></p> -<p id="n178" class="pln"><a href="#n178">178</a></p> -<p id="n179" class="stm mis"><a href="#n179">179</a></p> -<p id="n180" class="pln"><a href="#n180">180</a></p> -<p id="n181" class="stm mis"><a href="#n181">181</a></p> -<p id="n182" class="pln"><a href="#n182">182</a></p> -<p id="n183" class="stm run hide_run"><a href="#n183">183</a></p> -<p id="n184" class="pln"><a href="#n184">184</a></p> -<p id="n185" class="stm mis"><a href="#n185">185</a></p> -<p id="n186" class="pln"><a href="#n186">186</a></p> -<p id="n187" class="stm mis"><a href="#n187">187</a></p> -<p id="n188" class="pln"><a href="#n188">188</a></p> -<p id="n189" class="pln"><a href="#n189">189</a></p> -<p id="n190" class="pln"><a href="#n190">190</a></p> -<p id="n191" class="stm mis"><a href="#n191">191</a></p> -<p id="n192" class="pln"><a href="#n192">192</a></p> -<p id="n193" class="pln"><a href="#n193">193</a></p> -<p id="n194" class="pln"><a href="#n194">194</a></p> -<p id="n195" class="stm mis"><a href="#n195">195</a></p> -<p id="n196" class="stm mis"><a href="#n196">196</a></p> -<p id="n197" class="pln"><a href="#n197">197</a></p> -<p id="n198" class="pln"><a href="#n198">198</a></p> -<p id="n199" class="pln"><a href="#n199">199</a></p> -<p id="n200" class="stm mis"><a href="#n200">200</a></p> -<p id="n201" class="pln"><a href="#n201">201</a></p> -<p id="n202" class="stm mis"><a href="#n202">202</a></p> -<p id="n203" class="stm mis"><a href="#n203">203</a></p> -<p id="n204" class="stm mis"><a href="#n204">204</a></p> -<p id="n205" class="stm mis"><a href="#n205">205</a></p> -<p id="n206" class="stm mis"><a href="#n206">206</a></p> -<p id="n207" class="pln"><a href="#n207">207</a></p> -<p id="n208" class="stm mis"><a href="#n208">208</a></p> -<p id="n209" class="pln"><a href="#n209">209</a></p> -<p id="n210" class="stm mis"><a href="#n210">210</a></p> -<p id="n211" class="stm mis"><a href="#n211">211</a></p> -<p id="n212" class="stm mis"><a href="#n212">212</a></p> -<p id="n213" class="stm mis"><a href="#n213">213</a></p> -<p id="n214" class="pln"><a href="#n214">214</a></p> -<p id="n215" class="stm mis"><a href="#n215">215</a></p> -<p id="n216" class="stm mis"><a href="#n216">216</a></p> -<p id="n217" class="pln"><a href="#n217">217</a></p> -<p id="n218" class="stm mis"><a href="#n218">218</a></p> -<p id="n219" class="pln"><a href="#n219">219</a></p> -<p id="n220" class="stm run hide_run"><a href="#n220">220</a></p> -<p id="n221" class="pln"><a href="#n221">221</a></p> -<p id="n222" class="stm mis"><a href="#n222">222</a></p> -<p id="n223" class="pln"><a href="#n223">223</a></p> -<p id="n224" class="stm mis"><a href="#n224">224</a></p> -<p id="n225" class="pln"><a href="#n225">225</a></p> -<p id="n226" class="pln"><a href="#n226">226</a></p> -<p id="n227" class="stm mis"><a href="#n227">227</a></p> -<p id="n228" class="stm mis"><a href="#n228">228</a></p> -<p id="n229" class="stm mis"><a href="#n229">229</a></p> -<p id="n230" class="stm mis"><a href="#n230">230</a></p> -<p id="n231" class="stm mis"><a href="#n231">231</a></p> -<p id="n232" class="stm mis"><a href="#n232">232</a></p> -<p id="n233" class="pln"><a href="#n233">233</a></p> -<p id="n234" class="pln"><a href="#n234">234</a></p> -<p id="n235" class="stm mis"><a href="#n235">235</a></p> -<p id="n236" class="stm mis"><a href="#n236">236</a></p> -<p id="n237" class="pln"><a href="#n237">237</a></p> -<p id="n238" class="pln"><a href="#n238">238</a></p> -<p id="n239" class="stm mis"><a href="#n239">239</a></p> -<p id="n240" class="pln"><a href="#n240">240</a></p> -<p id="n241" class="pln"><a href="#n241">241</a></p> -<p id="n242" class="stm mis"><a href="#n242">242</a></p> -<p id="n243" class="pln"><a href="#n243">243</a></p> -<p id="n244" class="stm mis"><a href="#n244">244</a></p> -<p id="n245" class="stm mis"><a href="#n245">245</a></p> -<p id="n246" class="pln"><a href="#n246">246</a></p> -<p id="n247" class="stm mis"><a href="#n247">247</a></p> -<p id="n248" class="pln"><a href="#n248">248</a></p> -<p id="n249" class="stm run hide_run"><a href="#n249">249</a></p> -<p id="n250" class="pln"><a href="#n250">250</a></p> -<p id="n251" class="stm mis"><a href="#n251">251</a></p> -<p id="n252" class="pln"><a href="#n252">252</a></p> -<p id="n253" class="stm mis"><a href="#n253">253</a></p> -<p id="n254" class="pln"><a href="#n254">254</a></p> -<p id="n255" class="pln"><a href="#n255">255</a></p> -<p id="n256" class="stm mis"><a href="#n256">256</a></p> -<p id="n257" class="stm mis"><a href="#n257">257</a></p> -<p id="n258" class="pln"><a href="#n258">258</a></p> -<p id="n259" class="pln"><a href="#n259">259</a></p> -<p id="n260" class="stm mis"><a href="#n260">260</a></p> -<p id="n261" class="pln"><a href="#n261">261</a></p> -<p id="n262" class="stm mis"><a href="#n262">262</a></p> -<p id="n263" class="pln"><a href="#n263">263</a></p> -<p id="n264" class="stm run hide_run"><a href="#n264">264</a></p> -<p id="n265" class="pln"><a href="#n265">265</a></p> -<p id="n266" class="stm mis"><a href="#n266">266</a></p> -<p id="n267" class="stm mis"><a href="#n267">267</a></p> -<p id="n268" class="pln"><a href="#n268">268</a></p> -<p id="n269" class="stm mis"><a href="#n269">269</a></p> -<p id="n270" class="stm mis"><a href="#n270">270</a></p> -<p id="n271" class="stm mis"><a href="#n271">271</a></p> -<p id="n272" class="pln"><a href="#n272">272</a></p> -<p id="n273" class="stm mis"><a href="#n273">273</a></p> -<p id="n274" class="pln"><a href="#n274">274</a></p> -<p id="n275" class="stm mis"><a href="#n275">275</a></p> -<p id="n276" class="stm mis"><a href="#n276">276</a></p> -<p id="n277" class="stm mis"><a href="#n277">277</a></p> -<p id="n278" class="pln"><a href="#n278">278</a></p> -<p id="n279" class="stm mis"><a href="#n279">279</a></p> -<p id="n280" class="pln"><a href="#n280">280</a></p> -<p id="n281" class="stm run hide_run"><a href="#n281">281</a></p> -<p id="n282" class="pln"><a href="#n282">282</a></p> -<p id="n283" class="pln"><a href="#n283">283</a></p> -<p id="n284" class="pln"><a href="#n284">284</a></p> -<p id="n285" class="pln"><a href="#n285">285</a></p> -<p id="n286" class="stm mis"><a href="#n286">286</a></p> -<p id="n287" class="stm mis"><a href="#n287">287</a></p> -<p id="n288" class="pln"><a href="#n288">288</a></p> -<p id="n289" class="stm mis"><a href="#n289">289</a></p> -<p id="n290" class="stm mis"><a href="#n290">290</a></p> -<p id="n291" class="pln"><a href="#n291">291</a></p> -<p id="n292" class="stm run hide_run"><a href="#n292">292</a></p> -<p id="n293" class="pln"><a href="#n293">293</a></p> -<p id="n294" class="pln"><a href="#n294">294</a></p> -<p id="n295" class="pln"><a href="#n295">295</a></p> -<p id="n296" class="pln"><a href="#n296">296</a></p> -<p id="n297" class="pln"><a href="#n297">297</a></p> -<p id="n298" class="pln"><a href="#n298">298</a></p> -<p id="n299" class="pln"><a href="#n299">299</a></p> -<p id="n300" class="stm mis"><a href="#n300">300</a></p> -<p id="n301" class="pln"><a href="#n301">301</a></p> -<p id="n302" class="stm mis"><a href="#n302">302</a></p> -<p id="n303" class="pln"><a href="#n303">303</a></p> -<p id="n304" class="stm run hide_run"><a href="#n304">304</a></p> -<p id="n305" class="pln"><a href="#n305">305</a></p> -<p id="n306" class="pln"><a href="#n306">306</a></p> -<p id="n307" class="pln"><a href="#n307">307</a></p> -<p id="n308" class="pln"><a href="#n308">308</a></p> -<p id="n309" class="pln"><a href="#n309">309</a></p> -<p id="n310" class="pln"><a href="#n310">310</a></p> -<p id="n311" class="pln"><a href="#n311">311</a></p> -<p id="n312" class="pln"><a href="#n312">312</a></p> -<p id="n313" class="stm mis"><a href="#n313">313</a></p> -<p id="n314" class="pln"><a href="#n314">314</a></p> -<p id="n315" class="stm mis"><a href="#n315">315</a></p> -<p id="n316" class="pln"><a href="#n316">316</a></p> -<p id="n317" class="stm run hide_run"><a href="#n317">317</a></p> -<p id="n318" class="pln"><a href="#n318">318</a></p> -<p id="n319" class="pln"><a href="#n319">319</a></p> -<p id="n320" class="pln"><a href="#n320">320</a></p> -<p id="n321" class="pln"><a href="#n321">321</a></p> -<p id="n322" class="pln"><a href="#n322">322</a></p> -<p id="n323" class="pln"><a href="#n323">323</a></p> -<p id="n324" class="pln"><a href="#n324">324</a></p> -<p id="n325" class="pln"><a href="#n325">325</a></p> -<p id="n326" class="stm mis"><a href="#n326">326</a></p> -<p id="n327" class="pln"><a href="#n327">327</a></p> -<p id="n328" class="stm mis"><a href="#n328">328</a></p> -<p id="n329" class="pln"><a href="#n329">329</a></p> -<p id="n330" class="stm run hide_run"><a href="#n330">330</a></p> -<p id="n331" class="pln"><a href="#n331">331</a></p> -<p id="n332" class="pln"><a href="#n332">332</a></p> -<p id="n333" class="pln"><a href="#n333">333</a></p> -<p id="n334" class="pln"><a href="#n334">334</a></p> -<p id="n335" class="pln"><a href="#n335">335</a></p> -<p id="n336" class="pln"><a href="#n336">336</a></p> -<p id="n337" class="pln"><a href="#n337">337</a></p> -<p id="n338" class="pln"><a href="#n338">338</a></p> -<p id="n339" class="pln"><a href="#n339">339</a></p> -<p id="n340" class="pln"><a href="#n340">340</a></p> -<p id="n341" class="pln"><a href="#n341">341</a></p> -<p id="n342" class="pln"><a href="#n342">342</a></p> -<p id="n343" class="pln"><a href="#n343">343</a></p> -<p id="n344" class="pln"><a href="#n344">344</a></p> -<p id="n345" class="pln"><a href="#n345">345</a></p> -<p id="n346" class="pln"><a href="#n346">346</a></p> -<p id="n347" class="pln"><a href="#n347">347</a></p> -<p id="n348" class="pln"><a href="#n348">348</a></p> -<p id="n349" class="stm mis"><a href="#n349">349</a></p> -<p id="n350" class="pln"><a href="#n350">350</a></p> -<p id="n351" class="stm mis"><a href="#n351">351</a></p> -<p id="n352" class="stm mis"><a href="#n352">352</a></p> -<p id="n353" class="stm mis"><a href="#n353">353</a></p> -<p id="n354" class="stm mis"><a href="#n354">354</a></p> -<p id="n355" class="pln"><a href="#n355">355</a></p> -<p id="n356" class="stm mis"><a href="#n356">356</a></p> -<p id="n357" class="pln"><a href="#n357">357</a></p> -<p id="n358" class="stm mis"><a href="#n358">358</a></p> -<p id="n359" class="pln"><a href="#n359">359</a></p> -<p id="n360" class="stm run hide_run"><a href="#n360">360</a></p> -<p id="n361" class="pln"><a href="#n361">361</a></p> -<p id="n362" class="pln"><a href="#n362">362</a></p> -<p id="n363" class="pln"><a href="#n363">363</a></p> -<p id="n364" class="pln"><a href="#n364">364</a></p> -<p id="n365" class="pln"><a href="#n365">365</a></p> -<p id="n366" class="pln"><a href="#n366">366</a></p> -<p id="n367" class="pln"><a href="#n367">367</a></p> -<p id="n368" class="pln"><a href="#n368">368</a></p> -<p id="n369" class="stm mis"><a href="#n369">369</a></p> -<p id="n370" class="stm mis"><a href="#n370">370</a></p> -<p id="n371" class="pln"><a href="#n371">371</a></p> -<p id="n372" class="stm mis"><a href="#n372">372</a></p> -<p id="n373" class="pln"><a href="#n373">373</a></p> -<p id="n374" class="pln"><a href="#n374">374</a></p> -<p id="n375" class="stm mis"><a href="#n375">375</a></p> -<p id="n376" class="pln"><a href="#n376">376</a></p> -<p id="n377" class="stm run hide_run"><a href="#n377">377</a></p> -<p id="n378" class="pln"><a href="#n378">378</a></p> -<p id="n379" class="pln"><a href="#n379">379</a></p> -<p id="n380" class="pln"><a href="#n380">380</a></p> -<p id="n381" class="pln"><a href="#n381">381</a></p> -<p id="n382" class="pln"><a href="#n382">382</a></p> -<p id="n383" class="pln"><a href="#n383">383</a></p> -<p id="n384" class="pln"><a href="#n384">384</a></p> -<p id="n385" class="pln"><a href="#n385">385</a></p> -<p id="n386" class="stm mis"><a href="#n386">386</a></p> -<p id="n387" class="stm mis"><a href="#n387">387</a></p> -<p id="n388" class="pln"><a href="#n388">388</a></p> -<p id="n389" class="stm mis"><a href="#n389">389</a></p> -<p id="n390" class="pln"><a href="#n390">390</a></p> -<p id="n391" class="stm mis"><a href="#n391">391</a></p> -<p id="n392" class="pln"><a href="#n392">392</a></p> -<p id="n393" class="stm run hide_run"><a href="#n393">393</a></p> -<p id="n394" class="pln"><a href="#n394">394</a></p> -<p id="n395" class="pln"><a href="#n395">395</a></p> -<p id="n396" class="pln"><a href="#n396">396</a></p> -<p id="n397" class="pln"><a href="#n397">397</a></p> -<p id="n398" class="pln"><a href="#n398">398</a></p> -<p id="n399" class="pln"><a href="#n399">399</a></p> -<p id="n400" class="pln"><a href="#n400">400</a></p> -<p id="n401" class="pln"><a href="#n401">401</a></p> -<p id="n402" class="stm mis"><a href="#n402">402</a></p> -<p id="n403" class="pln"><a href="#n403">403</a></p> -<p id="n404" class="stm run hide_run"><a href="#n404">404</a></p> -<p id="n405" class="pln"><a href="#n405">405</a></p> -<p id="n406" class="stm mis"><a href="#n406">406</a></p> -<p id="n407" class="pln"><a href="#n407">407</a></p> -<p id="n408" class="stm run hide_run"><a href="#n408">408</a></p> -<p id="n409" class="pln"><a href="#n409">409</a></p> -<p id="n410" class="pln"><a href="#n410">410</a></p> -<p id="n411" class="pln"><a href="#n411">411</a></p> -<p id="n412" class="pln"><a href="#n412">412</a></p> -<p 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id="n449" class="pln"><a href="#n449">449</a></p> -<p id="n450" class="pln"><a href="#n450">450</a></p> -<p id="n451" class="stm mis"><a href="#n451">451</a></p> -<p id="n452" class="stm mis"><a href="#n452">452</a></p> -<p id="n453" class="pln"><a href="#n453">453</a></p> -<p id="n454" class="stm mis"><a href="#n454">454</a></p> -<p id="n455" class="pln"><a href="#n455">455</a></p> -<p id="n456" class="stm mis"><a href="#n456">456</a></p> -<p id="n457" class="stm mis"><a href="#n457">457</a></p> -<p id="n458" class="pln"><a href="#n458">458</a></p> -<p id="n459" class="stm mis"><a href="#n459">459</a></p> - - </td> - <td class="text"> -<p id="t1" class="stm run hide_run"><span class="key">from</span> <span class="nam">datetime</span> <span class="key">import</span> <span class="nam">timedelta</span><span class="strut"> </span></p> -<p id="t2" class="stm run hide_run"><span class="key">import</span> <span class="nam">glob</span><span class="strut"> </span></p> -<p id="t3" class="stm run hide_run"><span class="key">import</span> <span class="nam">platform</span><span class="strut"> </span></p> -<p id="t4" class="stm run hide_run"><span class="key">import</span> <span class="nam">os</span><span class="strut"> </span></p> -<p id="t5" class="stm run hide_run"><span class="key">import</span> <span class="nam">re</span><span class="strut"> </span></p> -<p id="t6" class="pln"><span class="strut"> </span></p> -<p id="t7" class="stm run hide_run"><span class="key">import</span> <span class="nam">numpy</span> <span class="key">as</span> <span class="nam">np</span><span class="strut"> </span></p> -<p id="t8" class="stm run hide_run"><span class="key">import</span> <span class="nam">pandas</span> <span class="key">as</span> <span class="nam">pd</span><span class="strut"> </span></p> -<p id="t9" class="pln"><span class="strut"> </span></p> -<p id="t10" class="pln"><span class="strut"> </span></p> -<p id="t11" class="stm run hide_run"><span class="key">def</span> <span class="nam">_load_ras_controller</span><span class="op">(</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t12" class="pln"><span class="strut"> </span></p> -<p id="t13" class="stm run hide_run"> <span class="key">if</span> <span class="nam">platform</span><span class="op">.</span><span class="nam">system</span><span class="op">(</span><span class="op">)</span> <span class="op">==</span> <span class="str">'Windows'</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t14" class="stm run hide_run"> <span class="key">import</span> <span class="nam">winreg</span><span class="strut"> </span></p> -<p id="t15" class="stm run hide_run"> <span class="key">import</span> <span class="nam">win32com</span><span class="op">.</span><span class="nam">client</span><span class="strut"> </span></p> -<p id="t16" class="pln"> <span class="key">else</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t17" class="stm mis"> <span class="key">return</span> <span class="key">None</span><span class="strut"> </span></p> -<p id="t18" class="pln"><span class="strut"> </span></p> -<p id="t19" class="pln"> <span class="com"># find the version of RAS that are installed</span><span class="strut"> </span></p> -<p id="t20" class="stm run hide_run"> <span class="nam">ras_controller_pattern</span> <span class="op">=</span> <span class="str">r'^RAS[0-9]{3}.HECRASController$'</span><span class="strut"> </span></p> -<p id="t21" class="pln"><span class="strut"> </span></p> -<p id="t22" class="stm run hide_run"> <span class="key">with</span> <span class="nam">winreg</span><span class="op">.</span><span class="nam">OpenKey</span><span class="op">(</span><span class="nam">winreg</span><span class="op">.</span><span class="nam">HKEY_LOCAL_MACHINE</span><span class="op">,</span> <span class="str">r"SOFTWARE\Classes"</span><span class="op">)</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t23" class="pln"> <span class="key">as</span> <span class="nam">classes_key</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t24" class="pln"><span class="strut"> </span></p> -<p id="t25" class="stm run hide_run"> <span class="nam">ras_controller_prog_ids</span> <span class="op">=</span> <span class="op">[</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t26" class="stm run hide_run"> <span class="nam">n_keys</span><span class="op">,</span> <span class="nam">_</span><span class="op">,</span> <span class="nam">_</span> <span class="op">=</span> <span class="nam">winreg</span><span class="op">.</span><span class="nam">QueryInfoKey</span><span class="op">(</span><span class="nam">classes_key</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t27" class="stm run hide_run"> <span class="key">for</span> <span class="nam">i</span> <span class="key">in</span> <span class="nam">range</span><span class="op">(</span><span class="nam">n_keys</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t28" class="pln"><span class="strut"> </span></p> -<p id="t29" class="stm run hide_run"> <span class="nam">object_name</span> <span class="op">=</span> <span class="nam">winreg</span><span class="op">.</span><span class="nam">EnumKey</span><span class="op">(</span><span class="nam">classes_key</span><span class="op">,</span> <span class="nam">i</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t30" class="stm run hide_run"> <span class="key">if</span> <span class="nam">re</span><span class="op">.</span><span class="nam">match</span><span class="op">(</span><span class="nam">ras_controller_pattern</span><span class="op">,</span> <span class="nam">object_name</span><span class="op">)</span> <span class="key">is</span> <span class="key">not</span> <span class="key">None</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t31" class="stm run hide_run"> <span class="nam">ras_controller_prog_ids</span><span class="op">.</span><span class="nam">append</span><span class="op">(</span><span class="nam">object_name</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t32" class="pln"><span class="strut"> </span></p> -<p id="t33" class="pln"> <span class="com"># use the latest version of RAS installed</span><span class="strut"> </span></p> -<p id="t34" class="stm run hide_run"> <span class="nam">ras_controller_prog_ids</span><span class="op">.</span><span class="nam">sort</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t35" class="pln"><span class="strut"> </span></p> -<p id="t36" class="stm run hide_run"> <span class="key">if</span> <span class="nam">len</span><span class="op">(</span><span class="nam">ras_controller_prog_ids</span><span class="op">)</span> <span class="op">></span> <span class="num">0</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t37" class="stm run hide_run"> <span class="nam">prog_id</span> <span class="op">=</span> <span class="nam">ras_controller_prog_ids</span><span class="op">[</span><span class="op">-</span><span class="num">1</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t38" class="pln"><span class="strut"> </span></p> -<p id="t39" class="pln"> <span class="com"># start the RAS controller</span><span class="strut"> </span></p> -<p id="t40" class="stm run hide_run"> <span class="nam">ras_controller</span> <span class="op">=</span> <span class="nam">win32com</span><span class="op">.</span><span class="nam">client</span><span class="op">.</span><span class="nam">Dispatch</span><span class="op">(</span><span class="nam">prog_id</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t41" class="pln"> <span class="key">else</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t42" class="stm mis"> <span class="nam">ras_controller</span> <span class="op">=</span> <span class="key">None</span><span class="strut"> </span></p> -<p id="t43" class="pln"><span class="strut"> </span></p> -<p id="t44" class="stm run hide_run"> <span class="key">return</span> <span class="nam">ras_controller</span><span class="strut"> </span></p> -<p id="t45" class="pln"><span class="strut"> </span></p> -<p id="t46" class="pln"><span class="strut"> </span></p> -<p id="t47" class="stm run hide_run"><span class="nam">_ras_controller</span> <span class="op">=</span> <span class="nam">_load_ras_controller</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t48" class="pln"><span class="strut"> </span></p> -<p id="t49" class="pln"><span class="strut"> </span></p> -<p id="t50" class="stm run hide_run"><span class="key">def</span> <span class="nam">ras_controller_loaded</span><span class="op">(</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t51" class="stm mis"> <span class="key">return</span> <span class="nam">_ras_controller</span> <span class="key">is</span> <span class="key">not</span> <span class="key">None</span><span class="strut"> </span></p> -<p id="t52" class="pln"><span class="strut"> </span></p> -<p id="t53" class="pln"><span class="strut"> </span></p> -<p id="t54" class="stm run hide_run"><span class="key">class</span> <span class="nam">RASProject</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t55" class="pln"> <span class="str">"""RAS project.</span><span class="strut"> </span></p> -<p id="t56" class="pln"><span class="strut"> </span></p> -<p id="t57" class="pln"><span class="str"> After use, call close() to keep the RAS process from lingering. The</span><span class="strut"> </span></p> -<p id="t58" class="pln"><span class="str"> RASProject interface facilitates the use of the with-statement. See</span><span class="strut"> </span></p> -<p id="t59" class="pln"><span class="str"> below for an example.</span><span class="strut"> </span></p> -<p id="t60" class="pln"><span class="strut"> </span></p> -<p id="t61" class="pln"><span class="str"> ```</span><span class="strut"> </span></p> -<p id="t62" class="pln"><span class="str"> with RASProject(project_file_path) as rp:</span><span class="strut"> </span></p> -<p id="t63" class="pln"><span class="str"> hydrauilc_data = rp.hydraulic_model_data('Unsteady')</span><span class="strut"> </span></p> -<p id="t64" class="pln"><span class="str"> ```</span><span class="strut"> </span></p> -<p id="t65" class="pln"><span class="strut"> </span></p> -<p id="t66" class="pln"><span class="strut"> </span></p> -<p id="t67" class="pln"><span class="str"> Parameters</span><span class="strut"> </span></p> -<p id="t68" class="pln"><span class="str"> ----------</span><span class="strut"> </span></p> -<p id="t69" class="pln"><span class="str"> project_file_path : str</span><span class="strut"> </span></p> -<p id="t70" class="pln"><span class="str"> Path to RAS project file</span><span class="strut"> </span></p> -<p id="t71" class="pln"><span class="strut"> </span></p> -<p id="t72" class="pln"><span class="str"> Notes</span><span class="strut"> </span></p> -<p id="t73" class="pln"><span class="str"> -----</span><span class="strut"> </span></p> -<p id="t74" class="pln"><span class="str"> The values in the output of hydraulic_model_data are in metric units. If</span><span class="strut"> </span></p> -<p id="t75" class="pln"><span class="str"> the quantities in the RAS project are in English units, the output will be</span><span class="strut"> </span></p> -<p id="t76" class="pln"><span class="str"> converted.</span><span class="strut"> </span></p> -<p id="t77" class="pln"><span class="strut"> </span></p> -<p id="t78" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t79" class="pln"><span class="strut"> </span></p> -<p id="t80" class="stm run hide_run"> <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">project_file_path</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t81" class="pln"><span class="strut"> </span></p> -<p id="t82" class="stm mis"> <span class="key">if</span> <span class="nam">_ras_controller</span> <span class="key">is</span> <span class="key">None</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t83" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="str">"RAS controller not found"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t84" class="pln"><span class="strut"> </span></p> -<p id="t85" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">_ras_controller</span> <span class="op">=</span> <span class="nam">_ras_controller</span><span class="strut"> </span></p> -<p id="t86" class="pln"><span class="strut"> </span></p> -<p id="t87" class="pln"> <span class="com"># open the project</span><span class="strut"> </span></p> -<p id="t88" class="stm mis"> <span class="nam">absolute_project_path</span> <span class="op">=</span> <span class="nam">os</span><span class="op">.</span><span class="nam">path</span><span class="op">.</span><span class="nam">abspath</span><span class="op">(</span><span class="nam">project_file_path</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t89" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">_ras_controller</span><span class="op">.</span><span class="nam">Project_Open</span><span class="op">(</span><span class="nam">absolute_project_path</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t90" class="pln"><span class="strut"> </span></p> -<p id="t91" class="pln"> <span class="com"># set the units</span><span class="strut"> </span></p> -<p id="t92" class="stm mis"> <span class="nam">current_project_file_path</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_ras_controller</span><span class="op">.</span><span class="nam">CurrentProjectFile</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t93" class="stm mis"> <span class="key">with</span> <span class="nam">open</span><span class="op">(</span><span class="nam">current_project_file_path</span><span class="op">,</span> <span class="str">'r'</span><span class="op">)</span> <span class="key">as</span> <span class="nam">f</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t94" class="stm mis"> <span class="nam">project_file_contents</span> <span class="op">=</span> <span class="nam">f</span><span class="op">.</span><span class="nam">readlines</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t95" class="pln"><span class="strut"> </span></p> -<p id="t96" class="pln"> <span class="com"># set the current plan number</span><span class="strut"> </span></p> -<p id="t97" class="stm mis"> <span class="nam">current_plan_line</span> <span class="op">=</span> <span class="nam">project_file_contents</span><span class="op">[</span><span class="num">1</span><span class="op">]</span><span class="op">.</span><span class="nam">strip</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t98" class="stm mis"> <span class="nam">current_plan_name</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_get_current_plan_name</span><span class="op">(</span><span class="strut"> </span></p> -<p id="t99" class="pln"> <span class="nam">current_plan_line</span><span class="op">,</span> <span class="nam">current_project_file_path</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t100" class="stm mis"> <span class="nam">plan_names</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">plan_names</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t101" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">_current_plan_number</span> <span class="op">=</span> <span class="nam">plan_names</span><span class="op">.</span><span class="nam">index</span><span class="op">(</span><span class="nam">current_plan_name</span><span class="op">)</span> <span class="op">+</span> <span class="num">1</span><span class="strut"> </span></p> -<p id="t102" class="pln"><span class="strut"> </span></p> -<p id="t103" class="stm mis"> <span class="nam">units</span> <span class="op">=</span> <span class="nam">project_file_contents</span><span class="op">[</span><span class="num">3</span><span class="op">]</span><span class="op">.</span><span class="nam">strip</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t104" class="pln"><span class="strut"> </span></p> -<p id="t105" class="stm mis"> <span class="key">if</span> <span class="nam">units</span> <span class="op">==</span> <span class="str">'English Units'</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t106" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">_ras_units</span> <span class="op">=</span> <span class="str">'English'</span><span class="strut"> </span></p> -<p id="t107" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">_gravity</span> <span class="op">=</span> <span class="num">32.2</span><span class="strut"> </span></p> -<p id="t108" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">_n_conversion</span> <span class="op">=</span> <span class="num">1.4859</span><span class="strut"> </span></p> -<p id="t109" class="stm mis"> <span class="key">elif</span> <span class="nam">units</span> <span class="op">==</span> <span class="str">'SI Units'</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t110" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">_ras_units</span> <span class="op">=</span> <span class="str">'metric'</span><span class="strut"> </span></p> -<p id="t111" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">_gravity</span> <span class="op">=</span> <span class="num">9.81</span><span class="strut"> </span></p> -<p id="t112" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">_n_conversion</span> <span class="op">=</span> <span class="num">1</span><span class="strut"> </span></p> -<p id="t113" class="pln"> <span class="key">else</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t114" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="str">"Unknown units in project file"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t115" class="pln"><span class="strut"> </span></p> -<p id="t116" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">_current_river_number</span> <span class="op">=</span> <span class="num">1</span><span class="strut"> </span></p> -<p id="t117" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">_current_reach_number</span> <span class="op">=</span> <span class="num">1</span><span class="strut"> </span></p> -<p id="t118" class="pln"><span class="strut"> </span></p> -<p id="t119" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">_plan_has_steady_file</span> <span class="op">=</span> <span class="key">False</span><span class="strut"> </span></p> -<p id="t120" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">_plan_has_unsteady_file</span> <span class="op">=</span> <span class="key">False</span><span class="strut"> </span></p> -<p id="t121" class="pln"><span class="strut"> </span></p> -<p id="t122" class="stm run hide_run"> <span class="key">def</span> <span class="nam">__enter__</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t123" class="stm mis"> <span class="key">return</span> <span class="nam">self</span><span class="strut"> </span></p> -<p id="t124" class="pln"><span class="strut"> </span></p> -<p id="t125" class="stm run hide_run"> <span class="key">def</span> <span class="nam">__exit__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="op">*</span><span class="nam">args</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t126" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">close</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t127" class="pln"><span class="strut"> </span></p> -<p id="t128" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_calc_shear_velocity</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">cell_data</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t129" class="pln"><span class="strut"> </span></p> -<p id="t130" class="stm mis"> <span class="nam">manning_values</span> <span class="op">=</span> <span class="nam">cell_data</span><span class="op">[</span><span class="str">'Mann Wtd Chnl'</span><span class="op">]</span><span class="op">.</span><span class="nam">values</span><span class="strut"> </span></p> -<p id="t131" class="stm mis"> <span class="nam">hydraulic_radius</span> <span class="op">=</span> <span class="nam">cell_data</span><span class="op">[</span><span class="str">'Hydr Radius C'</span><span class="op">]</span><span class="op">.</span><span class="nam">values</span><span class="strut"> </span></p> -<p id="t132" class="stm mis"> <span class="nam">channel_velocity</span> <span class="op">=</span> <span class="nam">cell_data</span><span class="op">[</span><span class="str">'Vel Chnl'</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t133" class="pln"><span class="strut"> </span></p> -<p id="t134" class="stm mis"> <span class="nam">ks</span> <span class="op">=</span> <span class="op">(</span><span class="num">8.1</span> <span class="op">*</span> <span class="op">(</span><span class="nam">manning_values</span> <span class="op">/</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_n_conversion</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t135" class="pln"> <span class="op">*</span> <span class="nam">np</span><span class="op">.</span><span class="nam">sqrt</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_gravity</span><span class="op">)</span><span class="op">)</span><span class="op">**</span><span class="num">6</span><span class="strut"> </span></p> -<p id="t136" class="stm mis"> <span class="nam">shear_velocity</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">abs</span><span class="op">(</span><span class="strut"> </span></p> -<p id="t137" class="pln"> <span class="nam">channel_velocity</span> <span class="op">/</span> <span class="op">(</span><span class="num">8.1</span> <span class="op">*</span> <span class="op">(</span><span class="op">(</span><span class="nam">hydraulic_radius</span> <span class="op">/</span> <span class="nam">ks</span><span class="op">)</span> <span class="op">**</span> <span class="op">(</span><span class="num">1</span> <span class="op">/</span> <span class="num">6</span><span class="op">)</span><span class="op">)</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t138" class="pln"><span class="strut"> </span></p> -<p id="t139" class="stm mis"> <span class="key">return</span> <span class="nam">shear_velocity</span><span class="strut"> </span></p> -<p id="t140" class="pln"><span class="strut"> </span></p> -<p id="t141" class="stm run hide_run"> <span class="op">@</span><span class="nam">staticmethod</span><span class="strut"> </span></p> -<p id="t142" class="pln"> <span class="key">def</span> <span class="nam">_get_current_plan_name</span><span class="op">(</span><span class="nam">current_plan_line</span><span class="op">,</span> <span class="nam">current_project_file_path</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t143" class="pln"><span class="strut"> </span></p> -<p id="t144" class="stm mis"> <span class="nam">plan_file_extension</span> <span class="op">=</span> <span class="nam">current_plan_line</span><span class="op">.</span><span class="nam">split</span><span class="op">(</span><span class="str">'='</span><span class="op">)</span><span class="op">[</span><span class="op">-</span><span class="num">1</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t145" class="stm mis"> <span class="nam">path</span><span class="op">,</span> <span class="nam">_</span> <span class="op">=</span> <span class="nam">os</span><span class="op">.</span><span class="nam">path</span><span class="op">.</span><span class="nam">split</span><span class="op">(</span><span class="nam">current_project_file_path</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t146" class="stm mis"> <span class="nam">plan_file_list</span> <span class="op">=</span> <span class="nam">glob</span><span class="op">.</span><span class="nam">glob</span><span class="op">(</span><span class="nam">path</span> <span class="op">+</span> <span class="str">'/*.'</span> <span class="op">+</span> <span class="nam">plan_file_extension</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t147" class="pln"><span class="strut"> </span></p> -<p id="t148" class="stm mis"> <span class="key">with</span> <span class="nam">open</span><span class="op">(</span><span class="nam">plan_file_list</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="op">,</span> <span class="str">'r'</span><span class="op">)</span> <span class="key">as</span> <span class="nam">f</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t149" class="stm mis"> <span class="nam">plan_name_line</span> <span class="op">=</span> <span class="nam">f</span><span class="op">.</span><span class="nam">readline</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">strip</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t150" class="pln"><span class="strut"> </span></p> -<p id="t151" class="stm mis"> <span class="key">return</span> <span class="nam">plan_name_line</span><span class="op">.</span><span class="nam">split</span><span class="op">(</span><span class="str">'='</span><span class="op">)</span><span class="op">[</span><span class="op">-</span><span class="num">1</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t152" class="pln"><span class="strut"> </span></p> -<p id="t153" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_get_data_from_ras</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">profile_number</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t154" class="pln"><span class="strut"> </span></p> -<p id="t155" class="stm mis"> <span class="nam">_</span><span class="op">,</span> <span class="nam">output_var_names</span><span class="op">,</span> <span class="nam">_</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_ras_controller</span><span class="op">.</span><span class="nam">Output_Variables</span><span class="op">(</span><span class="strut"> </span></p> -<p id="t156" class="pln"> <span class="key">None</span><span class="op">,</span> <span class="key">None</span><span class="op">,</span> <span class="key">None</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t157" class="pln"><span class="strut"> </span></p> -<p id="t158" class="stm mis"> <span class="nam">var_name</span> <span class="op">=</span> <span class="op">[</span><span class="str">'Hydr Depth C'</span><span class="op">,</span> <span class="str">'Q Channel'</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t159" class="pln"> <span class="str">'Vel Chnl'</span><span class="op">,</span> <span class="str">'Mann Wtd Chnl'</span><span class="op">,</span> <span class="str">'Hydr Radius C'</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t160" class="stm mis"> <span class="nam">var_values</span> <span class="op">=</span> <span class="op">[</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t161" class="pln"><span class="strut"> </span></p> -<p id="t162" class="stm mis"> <span class="nam">channel_dist</span> <span class="op">=</span> <span class="key">None</span><span class="strut"> </span></p> -<p id="t163" class="stm mis"> <span class="nam">n_river_stations</span> <span class="op">=</span> <span class="num">0</span><span class="strut"> </span></p> -<p id="t164" class="pln"><span class="strut"> </span></p> -<p id="t165" class="pln"> <span class="com"># get the variable for the entire channel length</span><span class="strut"> </span></p> -<p id="t166" class="stm mis"> <span class="key">for</span> <span class="nam">name</span> <span class="key">in</span> <span class="nam">var_name</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t167" class="pln"><span class="strut"> </span></p> -<p id="t168" class="stm mis"> <span class="nam">var_number</span> <span class="op">=</span> <span class="nam">output_var_names</span><span class="op">.</span><span class="nam">index</span><span class="op">(</span><span class="nam">name</span><span class="op">)</span> <span class="op">+</span> <span class="num">1</span><span class="strut"> </span></p> -<p id="t169" class="stm mis"> <span class="nam">_</span><span class="op">,</span> <span class="nam">_</span><span class="op">,</span> <span class="nam">_</span><span class="op">,</span> <span class="nam">_</span><span class="op">,</span> <span class="nam">n_river_stations</span><span class="op">,</span> <span class="nam">_</span><span class="op">,</span> <span class="nam">channel_dist</span><span class="op">,</span> <span class="nam">values</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_ras_controller</span><span class="op">.</span><span class="nam">Output_ReachOutput</span><span class="op">(</span><span class="strut"> </span></p> -<p id="t170" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">_current_river_number</span><span class="op">,</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_current_reach_number</span><span class="op">,</span> <span class="nam">profile_number</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t171" class="pln"> <span class="nam">var_number</span><span class="op">,</span> <span class="key">None</span><span class="op">,</span> <span class="key">None</span><span class="op">,</span> <span class="key">None</span><span class="op">,</span> <span class="key">None</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t172" class="stm mis"> <span class="nam">var_values</span><span class="op">.</span><span class="nam">append</span><span class="op">(</span><span class="nam">values</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t173" class="pln"><span class="strut"> </span></p> -<p id="t174" class="stm mis"> <span class="nam">var_name</span><span class="op">.</span><span class="nam">append</span><span class="op">(</span><span class="str">'ChannelDist'</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t175" class="stm mis"> <span class="nam">var_values</span><span class="op">.</span><span class="nam">append</span><span class="op">(</span><span class="nam">channel_dist</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t176" class="pln"><span class="strut"> </span></p> -<p id="t177" class="stm mis"> <span class="nam">data_dict</span> <span class="op">=</span> <span class="nam">dict</span><span class="op">(</span><span class="nam">zip</span><span class="op">(</span><span class="nam">var_name</span><span class="op">,</span> <span class="nam">var_values</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t178" class="pln"><span class="strut"> </span></p> -<p id="t179" class="stm mis"> <span class="nam">cell_numbers</span> <span class="op">=</span> <span class="nam">range</span><span class="op">(</span><span class="num">1</span><span class="op">,</span> <span class="nam">n_river_stations</span><span class="op">+</span><span class="num">1</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t180" class="pln"><span class="strut"> </span></p> -<p id="t181" class="stm mis"> <span class="key">return</span> <span class="nam">pd</span><span class="op">.</span><span class="nam">DataFrame</span><span class="op">(</span><span class="nam">data_dict</span><span class="op">,</span> <span class="nam">index</span><span class="op">=</span><span class="nam">cell_numbers</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t182" class="pln"><span class="strut"> </span></p> -<p id="t183" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_get_profile_data</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">profile_number</span><span class="op">,</span> <span class="nam">temperature</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t184" class="pln"><span class="strut"> </span></p> -<p id="t185" class="stm mis"> <span class="nam">ras_data</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_get_data_from_ras</span><span class="op">(</span><span class="nam">profile_number</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t186" class="pln"><span class="strut"> </span></p> -<p id="t187" class="stm mis"> <span class="nam">column_map</span> <span class="op">=</span> <span class="op">{</span><span class="str">'Hydr Depth C'</span><span class="op">:</span> <span class="str">'Depth_m'</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t188" class="pln"> <span class="str">'Q Channel'</span><span class="op">:</span> <span class="str">'Q_cms'</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t189" class="pln"> <span class="str">'Vel Chnl'</span><span class="op">:</span> <span class="str">'Vmag_mps'</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t190" class="pln"> <span class="str">'ChannelDist'</span><span class="op">:</span> <span class="str">'CumlDistance_km'</span><span class="op">}</span><span class="strut"> </span></p> -<p id="t191" class="stm mis"> <span class="nam">profile_data</span> <span class="op">=</span> <span class="nam">ras_data</span><span class="op">.</span><span class="nam">rename</span><span class="op">(</span><span class="nam">mapper</span><span class="op">=</span><span class="nam">column_map</span><span class="op">,</span> <span class="nam">axis</span><span class="op">=</span><span class="num">1</span><span class="op">)</span><span class="op">.</span><span class="nam">drop</span><span class="op">(</span><span class="strut"> </span></p> -<p id="t192" class="pln"> <span class="op">[</span><span class="str">'Mann Wtd Chnl'</span><span class="op">,</span> <span class="str">'Hydr Radius C'</span><span class="op">]</span><span class="op">,</span> <span class="nam">axis</span><span class="op">=</span><span class="num">1</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t193" class="pln"><span class="strut"> </span></p> -<p id="t194" class="pln"> <span class="com"># convert from RAS distances to FluEgg distances</span><span class="strut"> </span></p> -<p id="t195" class="stm mis"> <span class="nam">number_of_cells</span> <span class="op">=</span> <span class="nam">profile_data</span><span class="op">.</span><span class="nam">shape</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t196" class="stm mis"> <span class="nam">profile_data</span><span class="op">.</span><span class="nam">loc</span><span class="op">[</span><span class="num">1</span><span class="op">:</span><span class="nam">number_of_cells</span> <span class="op">-</span> <span class="num">1</span><span class="op">,</span> <span class="str">'CumlDistance_km'</span><span class="op">]</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t197" class="pln"> <span class="num">0.5</span> <span class="op">*</span> <span class="op">(</span><span class="nam">profile_data</span><span class="op">.</span><span class="nam">loc</span><span class="op">[</span><span class="num">1</span><span class="op">:</span><span class="nam">number_of_cells</span> <span class="op">-</span> <span class="num">1</span><span class="op">,</span> <span class="str">'CumlDistance_km'</span><span class="op">]</span><span class="op">.</span><span class="nam">values</span><span class="strut"> </span></p> -<p id="t198" class="pln"> <span class="op">+</span> <span class="nam">profile_data</span><span class="op">.</span><span class="nam">loc</span><span class="op">[</span><span class="num">2</span><span class="op">:</span><span class="nam">number_of_cells</span><span class="op">,</span> <span class="str">'CumlDistance_km'</span><span class="op">]</span><span class="op">.</span><span class="nam">values</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t199" class="pln"><span class="strut"> </span></p> -<p id="t200" class="stm mis"> <span class="nam">profile_data</span><span class="op">[</span><span class="str">'CumlDistance_km'</span><span class="op">]</span> <span class="op">=</span> <span class="nam">profile_data</span><span class="op">[</span><span class="str">'CumlDistance_km'</span><span class="op">]</span><span class="op">/</span><span class="num">1000</span><span class="strut"> </span></p> -<p id="t201" class="pln"><span class="strut"> </span></p> -<p id="t202" class="stm mis"> <span class="nam">shear_velocity</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_calc_shear_velocity</span><span class="op">(</span><span class="nam">ras_data</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t203" class="stm mis"> <span class="nam">profile_data</span><span class="op">[</span><span class="str">'Ustar_mps'</span><span class="op">]</span> <span class="op">=</span> <span class="nam">shear_velocity</span><span class="strut"> </span></p> -<p id="t204" class="stm mis"> <span class="nam">profile_data</span><span class="op">[</span><span class="str">'Vvert_mps'</span><span class="op">]</span> <span class="op">=</span> <span class="num">0</span><span class="strut"> </span></p> -<p id="t205" class="stm mis"> <span class="nam">profile_data</span><span class="op">[</span><span class="str">'Vlat_mps'</span><span class="op">]</span> <span class="op">=</span> <span class="num">0</span><span class="strut"> </span></p> -<p id="t206" class="stm mis"> <span class="nam">profile_data</span><span class="op">[</span><span class="str">'Temp_C'</span><span class="op">]</span> <span class="op">=</span> <span class="nam">temperature</span><span class="strut"> </span></p> -<p id="t207" class="pln"><span class="strut"> </span></p> -<p id="t208" class="stm mis"> <span class="nam">feet_to_meters</span> <span class="op">=</span> <span class="op">(</span><span class="num">2.54</span> <span class="op">*</span> <span class="num">12</span><span class="op">)</span> <span class="op">/</span> <span class="num">100</span><span class="strut"> </span></p> -<p id="t209" class="pln"><span class="strut"> </span></p> -<p id="t210" class="stm mis"> <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_ras_units</span> <span class="op">==</span> <span class="str">'English'</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t211" class="stm mis"> <span class="nam">profile_data</span><span class="op">[</span><span class="str">'Depth_m'</span><span class="op">]</span> <span class="op">*=</span> <span class="nam">feet_to_meters</span><span class="strut"> </span></p> -<p id="t212" class="stm mis"> <span class="nam">profile_data</span><span class="op">[</span><span class="str">'Q_cms'</span><span class="op">]</span> <span class="op">*=</span> <span class="nam">feet_to_meters</span><span class="op">**</span><span class="num">3</span><span class="strut"> </span></p> -<p id="t213" class="stm mis"> <span class="nam">profile_data</span><span class="op">[</span><span class="str">'Vmag_mps'</span><span class="op">]</span> <span class="op">*=</span> <span class="nam">feet_to_meters</span><span class="strut"> </span></p> -<p id="t214" class="pln"> <span class="com"># already converted from m to km</span><span class="strut"> </span></p> -<p id="t215" class="stm mis"> <span class="nam">profile_data</span><span class="op">[</span><span class="str">'CumlDistance_km'</span><span class="op">]</span> <span class="op">*=</span> <span class="nam">feet_to_meters</span><span class="strut"> </span></p> -<p id="t216" class="stm mis"> <span class="nam">profile_data</span><span class="op">[</span><span class="str">'Ustar_mps'</span><span class="op">]</span> <span class="op">*=</span> <span class="nam">feet_to_meters</span><span class="strut"> </span></p> -<p id="t217" class="pln"><span class="strut"> </span></p> -<p id="t218" class="stm mis"> <span class="key">return</span> <span class="nam">profile_data</span><span class="strut"> </span></p> -<p id="t219" class="pln"><span class="strut"> </span></p> -<p id="t220" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_get_time_series_index</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t221" class="pln"><span class="strut"> </span></p> -<p id="t222" class="stm mis"> <span class="nam">hydraulic_times</span> <span class="op">=</span> <span class="op">[</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t223" class="pln"><span class="strut"> </span></p> -<p id="t224" class="stm mis"> <span class="key">for</span> <span class="nam">name</span> <span class="key">in</span> <span class="nam">self</span><span class="op">.</span><span class="nam">profile_names</span><span class="op">(</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t225" class="pln"><span class="strut"> </span></p> -<p id="t226" class="pln"> <span class="com"># convert string to Datetime instance</span><span class="strut"> </span></p> -<p id="t227" class="stm mis"> <span class="key">try</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t228" class="stm mis"> <span class="nam">day</span> <span class="op">=</span> <span class="nam">name</span><span class="op">[</span><span class="op">:</span><span class="num">2</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t229" class="stm mis"> <span class="nam">month</span> <span class="op">=</span> <span class="nam">name</span><span class="op">[</span><span class="num">2</span><span class="op">:</span><span class="num">5</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t230" class="stm mis"> <span class="nam">year</span> <span class="op">=</span> <span class="nam">name</span><span class="op">[</span><span class="num">5</span><span class="op">:</span><span class="num">9</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t231" class="stm mis"> <span class="nam">hour</span> <span class="op">=</span> <span class="nam">name</span><span class="op">[</span><span class="num">10</span><span class="op">:</span><span class="num">12</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t232" class="stm mis"> <span class="nam">minute</span> <span class="op">=</span> <span class="nam">name</span><span class="op">[</span><span class="num">12</span><span class="op">:</span><span class="num">14</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t233" class="pln"><span class="strut"> </span></p> -<p id="t234" class="pln"> <span class="com"># if the hour is midnight, convert to midnight at 00</span><span class="strut"> </span></p> -<p id="t235" class="stm mis"> <span class="key">if</span> <span class="nam">int</span><span class="op">(</span><span class="nam">hour</span><span class="op">)</span> <span class="op">==</span> <span class="num">24</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t236" class="stm mis"> <span class="nam">date_time</span> <span class="op">=</span> <span class="nam">pd</span><span class="op">.</span><span class="nam">to_datetime</span><span class="op">(</span><span class="strut"> </span></p> -<p id="t237" class="pln"> <span class="str">''</span><span class="op">.</span><span class="nam">join</span><span class="op">(</span><span class="op">[</span><span class="nam">day</span><span class="op">,</span> <span class="nam">month</span><span class="op">,</span> <span class="nam">year</span><span class="op">,</span> <span class="str">' 00'</span><span class="op">,</span> <span class="nam">minute</span><span class="op">]</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span> <span class="nam">timedelta</span><span class="op">(</span><span class="nam">days</span><span class="op">=</span><span class="num">1</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t238" class="pln"> <span class="key">else</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t239" class="stm mis"> <span class="nam">date_time</span> <span class="op">=</span> <span class="nam">pd</span><span class="op">.</span><span class="nam">to_datetime</span><span class="op">(</span><span class="strut"> </span></p> -<p id="t240" class="pln"> <span class="str">''</span><span class="op">.</span><span class="nam">join</span><span class="op">(</span><span class="op">[</span><span class="nam">day</span><span class="op">,</span> <span class="nam">month</span><span class="op">,</span> <span class="nam">year</span><span class="op">,</span> <span class="str">' '</span><span class="op">,</span> <span class="nam">hour</span><span class="op">,</span> <span class="nam">minute</span><span class="op">]</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t241" class="pln"><span class="strut"> </span></p> -<p id="t242" class="stm mis"> <span class="nam">hydraulic_times</span><span class="op">.</span><span class="nam">append</span><span class="op">(</span><span class="nam">date_time</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t243" class="pln"><span class="strut"> </span></p> -<p id="t244" class="stm mis"> <span class="key">except</span> <span class="nam">ValueError</span><span class="op">:</span> <span class="com"># skip profile name if ValueError is raised</span><span class="strut"> </span></p> -<p id="t245" class="stm mis"> <span class="key">continue</span><span class="strut"> </span></p> -<p id="t246" class="pln"><span class="strut"> </span></p> -<p id="t247" class="stm mis"> <span class="key">return</span> <span class="nam">pd</span><span class="op">.</span><span class="nam">DatetimeIndex</span><span class="op">(</span><span class="nam">hydraulic_times</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t248" class="pln"><span class="strut"> </span></p> -<p id="t249" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_get_unsteady_data</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">temperature</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t250" class="pln"><span class="strut"> </span></p> -<p id="t251" class="stm mis"> <span class="nam">profile_data</span> <span class="op">=</span> <span class="op">[</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t252" class="pln"><span class="strut"> </span></p> -<p id="t253" class="stm mis"> <span class="nam">profile_names</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">profile_names</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t254" class="pln"><span class="strut"> </span></p> -<p id="t255" class="pln"> <span class="com"># the first profile is the maximum water surface elevation, so skip it</span><span class="strut"> </span></p> -<p id="t256" class="stm mis"> <span class="key">for</span> <span class="nam">profile_number</span> <span class="key">in</span> <span class="nam">range</span><span class="op">(</span><span class="num">2</span><span class="op">,</span> <span class="nam">len</span><span class="op">(</span><span class="nam">profile_names</span><span class="op">)</span><span class="op">+</span><span class="num">1</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t257" class="stm mis"> <span class="nam">profile_data</span><span class="op">.</span><span class="nam">append</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_get_profile_data</span><span class="op">(</span><span class="strut"> </span></p> -<p id="t258" class="pln"> <span class="nam">profile_number</span><span class="op">,</span> <span class="nam">temperature</span><span class="op">)</span><span class="op">.</span><span class="nam">transpose</span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t259" class="pln"><span class="strut"> </span></p> -<p id="t260" class="stm mis"> <span class="nam">time_steps</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_get_time_series_index</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t261" class="pln"><span class="strut"> </span></p> -<p id="t262" class="stm mis"> <span class="key">return</span> <span class="nam">pd</span><span class="op">.</span><span class="nam">concat</span><span class="op">(</span><span class="nam">profile_data</span><span class="op">,</span> <span class="nam">keys</span><span class="op">=</span><span class="nam">time_steps</span><span class="op">,</span> <span class="nam">axis</span><span class="op">=</span><span class="num">1</span><span class="op">)</span><span class="op">.</span><span class="nam">transpose</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t263" class="pln"><span class="strut"> </span></p> -<p id="t264" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_ras_set_current_plan</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">plan_name</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t265" class="pln"><span class="strut"> </span></p> -<p id="t266" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">_ras_controller</span><span class="op">.</span><span class="nam">Plan_SetCurrent</span><span class="op">(</span><span class="nam">plan_name</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t267" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">_ras_controller</span><span class="op">.</span><span class="nam">Project_Save</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t268" class="pln"><span class="strut"> </span></p> -<p id="t269" class="stm mis"> <span class="nam">current_steady_file</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_ras_controller</span><span class="op">.</span><span class="nam">CurrentSteadyFile</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t270" class="stm mis"> <span class="key">if</span> <span class="nam">os</span><span class="op">.</span><span class="nam">path</span><span class="op">.</span><span class="nam">isfile</span><span class="op">(</span><span class="nam">current_steady_file</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t271" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">_plan_has_steady_file</span> <span class="op">=</span> <span class="key">True</span><span class="strut"> </span></p> -<p id="t272" class="pln"> <span class="key">else</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t273" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">_plan_has_steady_file</span> <span class="op">=</span> <span class="key">False</span><span class="strut"> </span></p> -<p id="t274" class="pln"><span class="strut"> </span></p> -<p id="t275" class="stm mis"> <span class="nam">current_unsteady_file</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_ras_controller</span><span class="op">.</span><span class="nam">CurrentUnSteadyFile</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t276" class="stm mis"> <span class="key">if</span> <span class="nam">os</span><span class="op">.</span><span class="nam">path</span><span class="op">.</span><span class="nam">isfile</span><span class="op">(</span><span class="nam">current_unsteady_file</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t277" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">_plan_has_unsteady_file</span> <span class="op">=</span> <span class="key">True</span><span class="strut"> </span></p> -<p id="t278" class="pln"> <span class="key">else</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t279" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">_plan_has_unsteady_file</span> <span class="op">=</span> <span class="key">False</span><span class="strut"> </span></p> -<p id="t280" class="pln"><span class="strut"> </span></p> -<p id="t281" class="stm run hide_run"> <span class="key">def</span> <span class="nam">close</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t282" class="pln"> <span class="str">"""Close the RAS controller</span><span class="strut"> </span></p> -<p id="t283" class="pln"><span class="strut"> </span></p> -<p id="t284" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t285" class="pln"><span class="strut"> </span></p> -<p id="t286" class="stm mis"> <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_ras_controller</span> <span class="key">is</span> <span class="key">None</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t287" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="str">"Operation on closed RASProject"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t288" class="pln"><span class="strut"> </span></p> -<p id="t289" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">_ras_controller</span><span class="op">.</span><span class="nam">QuitRas</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t290" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">_ras_controller</span> <span class="op">=</span> <span class="key">None</span><span class="strut"> </span></p> -<p id="t291" class="pln"><span class="strut"> </span></p> -<p id="t292" class="stm run hide_run"> <span class="key">def</span> <span class="nam">current_plan_name</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t293" class="pln"> <span class="str">"""Returns the current plan name</span><span class="strut"> </span></p> -<p id="t294" class="pln"><span class="strut"> </span></p> -<p id="t295" class="pln"><span class="str"> Returns</span><span class="strut"> </span></p> -<p id="t296" class="pln"><span class="str"> -------</span><span class="strut"> </span></p> -<p id="t297" class="pln"><span class="str"> str</span><span class="strut"> </span></p> -<p id="t298" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t299" class="pln"><span class="strut"> </span></p> -<p id="t300" class="stm mis"> <span class="nam">plan_names</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">plan_names</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t301" class="pln"><span class="strut"> </span></p> -<p id="t302" class="stm mis"> <span class="key">return</span> <span class="nam">plan_names</span><span class="op">[</span><span class="nam">self</span><span class="op">.</span><span class="nam">_current_plan_number</span><span class="op">-</span><span class="num">1</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t303" class="pln"><span class="strut"> </span></p> -<p id="t304" class="stm run hide_run"> <span class="key">def</span> <span class="nam">current_reach_name</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t305" class="pln"> <span class="str">"""Returns the current reach name</span><span class="strut"> </span></p> -<p id="t306" class="pln"><span class="strut"> </span></p> -<p id="t307" class="pln"><span class="str"> Returns</span><span class="strut"> </span></p> -<p id="t308" class="pln"><span class="str"> -------</span><span class="strut"> </span></p> -<p id="t309" class="pln"><span class="str"> str</span><span class="strut"> </span></p> -<p id="t310" class="pln"><span class="strut"> </span></p> -<p id="t311" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t312" class="pln"><span class="strut"> </span></p> -<p id="t313" class="stm mis"> <span class="nam">reach_names</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">reach_names</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t314" class="pln"><span class="strut"> </span></p> -<p id="t315" class="stm mis"> <span class="key">return</span> <span class="nam">reach_names</span><span class="op">[</span><span class="nam">self</span><span class="op">.</span><span class="nam">_current_reach_number</span><span class="op">-</span><span class="num">1</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t316" class="pln"><span class="strut"> </span></p> -<p id="t317" class="stm run hide_run"> <span class="key">def</span> <span class="nam">current_river_name</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t318" class="pln"> <span class="str">"""Returns the current river name</span><span class="strut"> </span></p> -<p id="t319" class="pln"><span class="strut"> </span></p> -<p id="t320" class="pln"><span class="str"> Returns</span><span class="strut"> </span></p> -<p id="t321" class="pln"><span class="str"> -------</span><span class="strut"> </span></p> -<p id="t322" class="pln"><span class="str"> str</span><span class="strut"> </span></p> -<p id="t323" class="pln"><span class="strut"> </span></p> -<p id="t324" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t325" class="pln"><span class="strut"> </span></p> -<p id="t326" class="stm mis"> <span class="nam">river_names</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">river_names</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t327" class="pln"><span class="strut"> </span></p> -<p id="t328" class="stm mis"> <span class="key">return</span> <span class="nam">river_names</span><span class="op">[</span><span class="nam">self</span><span class="op">.</span><span class="nam">_current_river_number</span><span class="op">-</span><span class="num">1</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t329" class="pln"><span class="strut"> </span></p> -<p id="t330" class="stm run hide_run"> <span class="key">def</span> <span class="nam">hydraulic_model_data</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">profile_name</span><span class="op">,</span> <span class="nam">temperature</span><span class="op">=</span><span class="num">22</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t331" class="pln"> <span class="str">"""Returns a pandas.DataFrame containing hydraulic data for the specified profile.</span><span class="strut"> </span></p> -<p id="t332" class="pln"><span class="strut"> </span></p> -<p id="t333" class="pln"><span class="str"> If 'Unsteady' is specified for profile_name, the index of the DataFrame will be a pandas.MultiIndex</span><span class="strut"> </span></p> -<p id="t334" class="pln"><span class="strut"> </span></p> -<p id="t335" class="pln"><span class="str"> Parameters</span><span class="strut"> </span></p> -<p id="t336" class="pln"><span class="str"> ----------</span><span class="strut"> </span></p> -<p id="t337" class="pln"><span class="str"> profile_name : str</span><span class="strut"> </span></p> -<p id="t338" class="pln"><span class="str"> Name of profile. The name must be in the list of profiles or 'Unsteady'. If 'Unsteady', the</span><span class="strut"> </span></p> -<p id="t339" class="pln"><span class="str"> RAS profile must have an associated unsteady file.</span><span class="strut"> </span></p> -<p id="t340" class="pln"><span class="str"> temperature : float</span><span class="strut"> </span></p> -<p id="t341" class="pln"><span class="str"> Water temperature</span><span class="strut"> </span></p> -<p id="t342" class="pln"><span class="strut"> </span></p> -<p id="t343" class="pln"><span class="str"> Returns</span><span class="strut"> </span></p> -<p id="t344" class="pln"><span class="str"> -------</span><span class="strut"> </span></p> -<p id="t345" class="pln"><span class="str"> pandas.DataFrame</span><span class="strut"> </span></p> -<p id="t346" class="pln"><span class="strut"> </span></p> -<p id="t347" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t348" class="pln"><span class="strut"> </span></p> -<p id="t349" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">_ras_set_current_plan</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">current_plan_name</span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t350" class="pln"><span class="strut"> </span></p> -<p id="t351" class="stm mis"> <span class="key">if</span> <span class="nam">profile_name</span> <span class="op">==</span> <span class="str">'Unsteady'</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t352" class="stm mis"> <span class="key">if</span> <span class="key">not</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_plan_has_unsteady_file</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t353" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="str">"Current plan does not have an unsteady file"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t354" class="stm mis"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_get_unsteady_data</span><span class="op">(</span><span class="nam">temperature</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t355" class="pln"> <span class="key">else</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t356" class="stm mis"> <span class="nam">profile_number</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">profile_names</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">index</span><span class="op">(</span><span class="strut"> </span></p> -<p id="t357" class="pln"> <span class="nam">profile_name</span><span class="op">)</span> <span class="op">+</span> <span class="num">1</span> <span class="com"># add one to profile_name index for RAS</span><span class="strut"> </span></p> -<p id="t358" class="stm mis"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_get_profile_data</span><span class="op">(</span><span class="nam">profile_number</span><span class="op">,</span> <span class="nam">temperature</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t359" class="pln"><span class="strut"> </span></p> -<p id="t360" class="stm run hide_run"> <span class="key">def</span> <span class="nam">plan_names</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t361" class="pln"> <span class="str">"""Returns a list of plan names in this RAS project.</span><span class="strut"> </span></p> -<p id="t362" class="pln"><span class="strut"> </span></p> -<p id="t363" class="pln"><span class="str"> Returns</span><span class="strut"> </span></p> -<p id="t364" class="pln"><span class="str"> -------</span><span class="strut"> </span></p> -<p id="t365" class="pln"><span class="str"> list</span><span class="strut"> </span></p> -<p id="t366" class="pln"><span class="strut"> </span></p> -<p id="t367" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t368" class="pln"><span class="strut"> </span></p> -<p id="t369" class="stm mis"> <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_ras_controller</span> <span class="key">is</span> <span class="key">None</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t370" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="str">"Operation on closed RASProject"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t371" class="pln"><span class="strut"> </span></p> -<p id="t372" class="stm mis"> <span class="nam">_</span><span class="op">,</span> <span class="nam">plan_names</span><span class="op">,</span> <span class="nam">_</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_ras_controller</span><span class="op">.</span><span class="nam">Plan_Names</span><span class="op">(</span><span class="strut"> </span></p> -<p id="t373" class="pln"> <span class="key">None</span><span class="op">,</span> <span class="key">None</span><span class="op">,</span> <span class="key">False</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t374" class="pln"><span class="strut"> </span></p> -<p id="t375" class="stm mis"> <span class="key">return</span> <span class="nam">list</span><span class="op">(</span><span class="nam">plan_names</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t376" class="pln"><span class="strut"> </span></p> -<p id="t377" class="stm run hide_run"> <span class="key">def</span> <span class="nam">profile_names</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t378" class="pln"> <span class="str">"""Returns a list of profile names in this RAS project.</span><span class="strut"> </span></p> -<p id="t379" class="pln"><span class="strut"> </span></p> -<p id="t380" class="pln"><span class="str"> Returns</span><span class="strut"> </span></p> -<p id="t381" class="pln"><span class="str"> -------</span><span class="strut"> </span></p> -<p id="t382" class="pln"><span class="str"> list</span><span class="strut"> </span></p> -<p id="t383" class="pln"><span class="strut"> </span></p> -<p id="t384" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t385" class="pln"><span class="strut"> </span></p> -<p id="t386" class="stm mis"> <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_ras_controller</span> <span class="key">is</span> <span class="key">None</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t387" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="str">"Operation on closed RASProject"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t388" class="pln"><span class="strut"> </span></p> -<p id="t389" class="stm mis"> <span class="nam">_</span><span class="op">,</span> <span class="nam">profile_names</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_ras_controller</span><span class="op">.</span><span class="nam">Output_GetProfiles</span><span class="op">(</span><span class="key">None</span><span class="op">,</span> <span class="key">None</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t390" class="pln"><span class="strut"> </span></p> -<p id="t391" class="stm mis"> <span class="key">return</span> <span class="nam">list</span><span class="op">(</span><span class="nam">profile_names</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t392" class="pln"><span class="strut"> </span></p> -<p id="t393" class="stm run hide_run"> <span class="key">def</span> <span class="nam">project_units</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t394" class="pln"> <span class="str">"""Returns the RAS project units.</span><span class="strut"> </span></p> -<p id="t395" class="pln"><span class="strut"> </span></p> -<p id="t396" class="pln"><span class="str"> Returns</span><span class="strut"> </span></p> -<p id="t397" class="pln"><span class="str"> -------</span><span class="strut"> </span></p> -<p id="t398" class="pln"><span class="str"> str</span><span class="strut"> </span></p> -<p id="t399" class="pln"><span class="strut"> </span></p> -<p id="t400" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t401" class="pln"><span class="strut"> </span></p> -<p id="t402" class="stm mis"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_ras_units</span><span class="strut"> </span></p> -<p id="t403" class="pln"><span class="strut"> </span></p> -<p id="t404" class="stm run hide_run"> <span class="op">@</span><span class="nam">staticmethod</span><span class="strut"> </span></p> -<p id="t405" class="pln"> <span class="key">def</span> <span class="nam">ras_controller_loaded</span><span class="op">(</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t406" class="stm mis"> <span class="key">return</span> <span class="nam">ras_controller_loaded</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t407" class="pln"><span class="strut"> </span></p> -<p id="t408" class="stm run hide_run"> <span class="key">def</span> <span class="nam">reach_names</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t409" class="pln"> <span class="str">"""Returns a list of reach names in this RAS project.</span><span class="strut"> </span></p> -<p id="t410" class="pln"><span class="strut"> </span></p> -<p id="t411" class="pln"><span class="str"> Returns</span><span class="strut"> </span></p> -<p id="t412" class="pln"><span class="str"> -------</span><span class="strut"> </span></p> -<p id="t413" class="pln"><span class="str"> list</span><span class="strut"> </span></p> -<p id="t414" class="pln"><span class="strut"> </span></p> -<p id="t415" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t416" class="pln"><span class="strut"> </span></p> -<p id="t417" class="stm mis"> <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_ras_controller</span> <span class="key">is</span> <span class="key">None</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t418" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="str">"Operation on closed RASProject"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t419" class="pln"><span class="strut"> </span></p> -<p id="t420" class="stm mis"> <span class="nam">_</span><span class="op">,</span> <span class="nam">_</span><span class="op">,</span> <span class="nam">reach_names</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_ras_controller</span><span class="op">.</span><span class="nam">Geometry_GetReaches</span><span class="op">(</span><span class="strut"> </span></p> -<p id="t421" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">_current_river_number</span><span class="op">,</span> <span class="key">None</span><span class="op">,</span> <span class="key">None</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t422" class="pln"><span class="strut"> </span></p> -<p id="t423" class="stm mis"> <span class="key">return</span> <span class="nam">list</span><span class="op">(</span><span class="nam">reach_names</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t424" class="pln"><span class="strut"> </span></p> -<p id="t425" class="stm run hide_run"> <span class="key">def</span> <span class="nam">river_names</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t426" class="pln"> <span class="str">"""Returns a list of river names in this RAS project.</span><span class="strut"> </span></p> -<p id="t427" class="pln"><span class="strut"> </span></p> -<p id="t428" class="pln"><span class="str"> Returns</span><span class="strut"> </span></p> -<p id="t429" class="pln"><span class="str"> -------</span><span class="strut"> </span></p> -<p id="t430" class="pln"><span class="str"> list</span><span class="strut"> </span></p> -<p id="t431" class="pln"><span class="strut"> </span></p> -<p id="t432" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t433" class="pln"><span class="strut"> </span></p> -<p id="t434" class="stm mis"> <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_ras_controller</span> <span class="key">is</span> <span class="key">None</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t435" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="str">"Operation on closed RASProject"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t436" class="pln"><span class="strut"> </span></p> -<p id="t437" class="stm mis"> <span class="nam">_</span><span class="op">,</span> <span class="nam">river_names</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_ras_controller</span><span class="op">.</span><span class="nam">Geometry_GetRivers</span><span class="op">(</span><span class="key">None</span><span class="op">,</span> <span class="key">None</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t438" class="pln"><span class="strut"> </span></p> -<p id="t439" class="stm mis"> <span class="key">return</span> <span class="nam">list</span><span class="op">(</span><span class="nam">river_names</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t440" class="pln"><span class="strut"> </span></p> -<p id="t441" class="stm run hide_run"> <span class="key">def</span> <span class="nam">set_current_plan</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">plan_name</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t442" class="pln"> <span class="str">"""Sets the current plan name for this RAS project.</span><span class="strut"> </span></p> -<p id="t443" class="pln"><span class="strut"> </span></p> -<p id="t444" class="pln"><span class="str"> Parameters</span><span class="strut"> </span></p> -<p id="t445" class="pln"><span class="str"> ----------</span><span class="strut"> </span></p> -<p id="t446" class="pln"><span class="str"> plan_name : str</span><span class="strut"> </span></p> -<p id="t447" class="pln"><span class="str"> Plan name. The plan name must be in the list of plan names of this project.</span><span class="strut"> </span></p> -<p id="t448" class="pln"><span class="strut"> </span></p> -<p id="t449" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t450" class="pln"><span class="strut"> </span></p> -<p id="t451" class="stm mis"> <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_ras_controller</span> <span class="key">is</span> <span class="key">None</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t452" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="str">"Operation on closed RASProject"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t453" class="pln"><span class="strut"> </span></p> -<p id="t454" class="stm mis"> <span class="nam">plan_names</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">plan_names</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t455" class="pln"><span class="strut"> </span></p> -<p id="t456" class="stm mis"> <span class="key">if</span> <span class="nam">plan_name</span> <span class="key">not</span> <span class="key">in</span> <span class="nam">plan_names</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t457" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="str">"Invalid plan name"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t458" class="pln"><span class="strut"> </span></p> -<p id="t459" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">_current_plan_number</span> <span class="op">=</span> <span class="nam">plan_names</span><span class="op">.</span><span class="nam">index</span><span class="op">(</span><span class="nam">plan_name</span><span class="op">)</span> <span class="op">+</span> <span class="num">1</span><span class="strut"> </span></p> - - </td> - </tr> - </table> -</div> - -<div id="footer"> - <div class="content"> - <p> - <a class="nav" href="index.html">« index</a> <a class="nav" href="https://coverage.readthedocs.io">coverage.py v4.5.3</a>, - created at 2019-07-09 15:15 - </p> - </div> -</div> - -</body> -</html> diff --git a/coverage_report/fluegg_simclock_py.html b/coverage_report/fluegg_simclock_py.html deleted file mode 100644 index 1ad0185..0000000 --- a/coverage_report/fluegg_simclock_py.html +++ /dev/null @@ -1,361 +0,0 @@ - - - -<!DOCTYPE html> -<html> -<head> - <meta http-equiv="Content-Type" content="text/html; charset=utf-8"> - - - <meta http-equiv="X-UA-Compatible" content="IE=emulateIE7" /> - <title>Coverage for fluegg\simclock.py: 89%</title> - <link rel="stylesheet" href="style.css" type="text/css"> - - <script type="text/javascript" src="jquery.min.js"></script> - <script type="text/javascript" src="jquery.hotkeys.js"></script> - <script type="text/javascript" src="jquery.isonscreen.js"></script> - <script type="text/javascript" src="coverage_html.js"></script> - <script type="text/javascript"> - jQuery(document).ready(coverage.pyfile_ready); - </script> -</head> -<body class="pyfile"> - -<div id="header"> - <div class="content"> - <h1>Coverage for <b>fluegg\simclock.py</b> : - <span class="pc_cov">89%</span> - </h1> - - <img id="keyboard_icon" src="keybd_closed.png" alt="Show keyboard shortcuts" /> - - <h2 class="stats"> - 46 statements - <span class="run hide_run shortkey_r button_toggle_run">41 run</span> - <span class="mis shortkey_m button_toggle_mis">5 missing</span> - <span class="exc shortkey_x button_toggle_exc">0 excluded</span> - - - </h2> - </div> -</div> - -<div class="help_panel"> - <img id="panel_icon" src="keybd_open.png" alt="Hide keyboard shortcuts" /> - <p class="legend">Hot-keys on this page</p> - <div> - <p class="keyhelp"> - <span class="key">r</span> - <span class="key">m</span> - <span class="key">x</span> - <span class="key">p</span> toggle line displays - </p> - <p class="keyhelp"> - <span class="key">j</span> - <span class="key">k</span> next/prev highlighted chunk - </p> - <p class="keyhelp"> - <span class="key">0</span> (zero) top of page - </p> - <p class="keyhelp"> - <span class="key">1</span> (one) first highlighted chunk - </p> - </div> -</div> - -<div id="source"> - <table> - <tr> - <td class="linenos"> -<p id="n1" class="stm run hide_run"><a href="#n1">1</a></p> -<p id="n2" class="pln"><a href="#n2">2</a></p> -<p id="n3" class="pln"><a href="#n3">3</a></p> -<p id="n4" class="stm run hide_run"><a href="#n4">4</a></p> -<p id="n5" class="pln"><a href="#n5">5</a></p> -<p id="n6" class="pln"><a href="#n6">6</a></p> -<p id="n7" class="pln"><a href="#n7">7</a></p> -<p id="n8" class="pln"><a href="#n8">8</a></p> -<p id="n9" 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href="#n133">133</a></p> -<p id="n134" class="stm mis"><a href="#n134">134</a></p> -<p id="n135" class="stm mis"><a href="#n135">135</a></p> -<p id="n136" class="pln"><a href="#n136">136</a></p> - - </td> - <td class="text"> -<p id="t1" class="stm run hide_run"><span class="key">import</span> <span class="nam">numpy</span> <span class="key">as</span> <span class="nam">np</span><span class="strut"> </span></p> -<p id="t2" class="pln"><span class="strut"> </span></p> -<p id="t3" class="pln"><span class="strut"> </span></p> -<p id="t4" class="stm run hide_run"><span class="key">class</span> <span class="nam">SimulationClock</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t5" class="pln"> <span class="str">"""Class representing a simulation clock</span><span class="strut"> </span></p> -<p id="t6" class="pln"><span class="strut"> </span></p> -<p id="t7" class="pln"><span class="str"> Parameters</span><span class="strut"> </span></p> -<p id="t8" class="pln"><span class="str"> ----------</span><span class="strut"> </span></p> -<p id="t9" class="pln"><span class="str"> time_step_size : int</span><span class="strut"> </span></p> -<p id="t10" class="pln"><span class="str"> Number of seconds per time step</span><span class="strut"> </span></p> -<p id="t11" class="pln"><span class="strut"> </span></p> -<p id="t12" class="pln"><span class="str"> total_simulation_time : int</span><span class="strut"> </span></p> -<p id="t13" class="pln"><span class="str"> Number of total seconds in the simulation</span><span class="strut"> </span></p> -<p id="t14" class="pln"><span class="strut"> </span></p> -<p id="t15" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t16" class="pln"><span class="strut"> </span></p> -<p id="t17" class="stm run hide_run"> <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">time_step_size</span><span class="op">,</span> <span class="nam">total_simulation_time</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t18" class="pln"><span class="strut"> </span></p> -<p id="t19" class="stm run hide_run"> <span class="key">if</span> <span class="nam">total_simulation_time</span> <span class="op">%</span> <span class="nam">time_step_size</span> <span class="op">==</span> <span class="num">0</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t20" class="stm run hide_run"> <span class="nam">time_array</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">arange</span><span class="op">(</span><span class="num">0</span><span class="op">,</span> <span class="nam">total_simulation_time</span> <span class="op">+</span> <span class="nam">time_step_size</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t21" class="pln"> <span class="nam">time_step_size</span><span class="op">,</span> <span class="nam">dtype</span><span class="op">=</span><span class="nam">float</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t22" class="pln"> <span class="key">else</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t23" class="stm run hide_run"> <span class="nam">time_array</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">arange</span><span class="op">(</span><span class="num">0</span><span class="op">,</span> <span class="nam">total_simulation_time</span><span class="op">,</span> <span class="nam">time_step_size</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t24" class="pln"> <span class="nam">dtype</span><span class="op">=</span><span class="nam">float</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t25" class="pln"><span class="strut"> </span></p> -<p id="t26" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_time_array</span> <span class="op">=</span> <span class="nam">time_array</span><span class="strut"> </span></p> -<p id="t27" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_current_time_index</span> <span class="op">=</span> <span class="num">0</span><span class="strut"> </span></p> -<p id="t28" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_time_step_size</span> <span class="op">=</span> <span class="nam">time_step_size</span><span class="strut"> </span></p> -<p id="t29" class="pln"><span class="strut"> </span></p> -<p id="t30" class="stm run hide_run"> <span class="key">def</span> <span class="nam">current_time</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t31" class="pln"> <span class="str">"""Returns the current simulation time in seconds</span><span class="strut"> </span></p> -<p id="t32" class="pln"><span class="strut"> </span></p> -<p id="t33" class="pln"><span class="str"> :return: sim time (s)</span><span class="strut"> </span></p> -<p id="t34" class="pln"><span class="str"> :rtype: float</span><span class="strut"> </span></p> -<p id="t35" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t36" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_time_array</span><span class="op">[</span><span class="nam">self</span><span class="op">.</span><span class="nam">_current_time_index</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t37" class="pln"><span class="strut"> </span></p> -<p id="t38" class="stm run hide_run"> <span class="key">def</span> <span class="nam">current_time_index</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t39" class="pln"> <span class="str">"""Returns the current simulation time index</span><span class="strut"> </span></p> -<p id="t40" class="pln"><span class="strut"> </span></p> -<p id="t41" class="pln"><span class="str"> :return: sim time index</span><span class="strut"> </span></p> -<p id="t42" class="pln"><span class="str"> :rtype: int</span><span class="strut"> </span></p> -<p id="t43" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t44" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_current_time_index</span><span class="strut"> </span></p> -<p id="t45" class="pln"><span class="strut"> </span></p> -<p id="t46" class="stm run hide_run"> <span class="key">def</span> <span class="nam">number_of_time_steps</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t47" class="pln"> <span class="str">"""Returns the total number of time steps in the simultaion</span><span class="strut"> </span></p> -<p id="t48" class="pln"><span class="strut"> </span></p> -<p id="t49" class="pln"><span class="str"> :return: num time steps</span><span class="strut"> </span></p> -<p id="t50" class="pln"><span class="str"> :rtype: int</span><span class="strut"> </span></p> -<p id="t51" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t52" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_time_array</span><span class="op">.</span><span class="nam">size</span><span class="strut"> </span></p> -<p id="t53" class="pln"><span class="strut"> </span></p> -<p id="t54" class="stm run hide_run"> <span class="key">def</span> <span class="nam">time_array</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t55" class="pln"> <span class="str">"""Returns the array of all time steps in seconds (s)</span><span class="strut"> </span></p> -<p id="t56" class="pln"><span class="strut"> </span></p> -<p id="t57" class="pln"><span class="str"> :return: array of all time steps (s)</span><span class="strut"> </span></p> -<p id="t58" class="pln"><span class="str"> :rtype: np.ndarray</span><span class="strut"> </span></p> -<p id="t59" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t60" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_time_array</span><span class="op">.</span><span class="nam">copy</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t61" class="pln"><span class="strut"> </span></p> -<p id="t62" class="stm run hide_run"> <span class="key">def</span> <span class="nam">time_step_size</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t63" class="pln"> <span class="str">"""Returns the simulation time step size in seconds</span><span class="strut"> </span></p> -<p id="t64" class="pln"><span class="strut"> </span></p> -<p id="t65" class="pln"><span class="str"> :return: time step size (s)</span><span class="strut"> </span></p> -<p id="t66" class="pln"><span class="str"> :rtype: float</span><span class="strut"> </span></p> -<p id="t67" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t68" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_time_step_size</span><span class="strut"> </span></p> -<p id="t69" class="pln"><span class="strut"> </span></p> -<p id="t70" class="stm run hide_run"> <span class="key">def</span> <span class="nam">iter_time_index</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t71" class="pln"><span class="strut"> </span></p> -<p id="t72" class="stm run hide_run"> <span class="key">return</span> <span class="nam">TimeStepIterable</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t73" class="pln"><span class="strut"> </span></p> -<p id="t74" class="stm run hide_run"> <span class="key">def</span> <span class="nam">set_time_index</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">time_index</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t75" class="pln"> <span class="str">"""</span><span class="strut"> </span></p> -<p id="t76" class="pln"><span class="strut"> </span></p> -<p id="t77" class="pln"><span class="str"> :param time_index:</span><span class="strut"> </span></p> -<p id="t78" class="pln"><span class="str"> :type time_index: int</span><span class="strut"> </span></p> -<p id="t79" class="pln"><span class="str"> :return: None</span><span class="strut"> </span></p> -<p id="t80" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t81" class="pln"><span class="strut"> </span></p> -<p id="t82" class="stm run hide_run"> <span class="key">if</span> <span class="op">(</span><span class="num">0</span> <span class="op"><=</span> <span class="nam">time_index</span><span class="op">)</span> <span class="key">and</span> <span class="op">(</span><span class="nam">time_index</span> <span class="op"><</span> <span class="nam">self</span><span class="op">.</span><span class="nam">number_of_time_steps</span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t83" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_current_time_index</span> <span class="op">=</span> <span class="nam">time_index</span><span class="strut"> </span></p> -<p id="t84" class="pln"> <span class="key">else</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t85" class="stm mis"> <span class="key">raise</span> <span class="nam">IndexError</span><span class="op">(</span><span class="str">"Time index out of bounds"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t86" class="pln"><span class="strut"> </span></p> -<p id="t87" class="pln"><span class="strut"> </span></p> -<p id="t88" class="stm run hide_run"><span class="key">class</span> <span class="nam">TimeStepIterable</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t89" class="pln"> <span class="str">"""</span><span class="strut"> </span></p> -<p id="t90" class="pln"><span class="strut"> </span></p> -<p id="t91" class="pln"><span class="str"> Parameters</span><span class="strut"> </span></p> -<p id="t92" class="pln"><span class="str"> ----------</span><span class="strut"> </span></p> -<p id="t93" class="pln"><span class="str"> simulation_clock : SimulationClock</span><span class="strut"> </span></p> -<p id="t94" class="pln"><span class="strut"> </span></p> -<p id="t95" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t96" class="pln"><span class="strut"> </span></p> -<p id="t97" class="stm run hide_run"> <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">simulation_clock</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t98" class="pln"><span class="strut"> </span></p> -<p id="t99" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_simulation_clock</span> <span class="op">=</span> <span class="nam">simulation_clock</span><span class="strut"> </span></p> -<p id="t100" class="pln"><span class="strut"> </span></p> -<p id="t101" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_number_of_time_steps</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t102" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">_simulation_clock</span><span class="op">.</span><span class="nam">number_of_time_steps</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t103" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_current_time_step_index</span> <span class="op">=</span> <span class="num">0</span><span class="strut"> </span></p> -<p id="t104" class="pln"><span class="strut"> </span></p> -<p id="t105" class="stm run hide_run"> <span class="key">def</span> <span class="nam">__iter__</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t106" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="strut"> </span></p> -<p id="t107" class="pln"><span class="strut"> </span></p> -<p id="t108" class="stm run hide_run"> <span class="key">def</span> <span class="nam">__next__</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t109" class="pln"><span class="strut"> </span></p> -<p id="t110" class="stm run hide_run"> <span class="nam">time_step_index</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_current_time_step_index</span><span class="strut"> </span></p> -<p id="t111" class="stm run hide_run"> <span class="key">if</span> <span class="nam">time_step_index</span> <span class="op">==</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_number_of_time_steps</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t112" class="stm run hide_run"> <span class="key">raise</span> <span class="nam">StopIteration</span><span class="strut"> </span></p> -<p id="t113" class="pln"><span class="strut"> </span></p> -<p id="t114" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_current_time_step_index</span> <span class="op">+=</span> <span class="num">1</span><span class="strut"> </span></p> -<p id="t115" class="pln"><span class="strut"> </span></p> -<p id="t116" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_simulation_clock</span><span class="op">.</span><span class="nam">set_time_index</span><span class="op">(</span><span class="nam">time_step_index</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t117" class="pln"><span class="strut"> </span></p> -<p id="t118" class="stm run hide_run"> <span class="key">return</span> <span class="nam">time_step_index</span><span class="strut"> </span></p> -<p id="t119" class="pln"><span class="strut"> </span></p> -<p id="t120" class="pln"><span class="strut"> </span></p> -<p id="t121" class="stm run hide_run"><span class="key">class</span> <span class="nam">ReverseSimulationClock</span><span class="op">(</span><span class="nam">SimulationClock</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t122" class="pln"><span class="strut"> </span></p> -<p id="t123" class="stm run hide_run"> <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">time_step_size</span><span class="op">,</span> <span class="nam">total_simulation_time</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t124" class="stm mis"> <span class="nam">SimulationClock</span><span class="op">.</span><span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">time_step_size</span><span class="op">,</span> <span class="nam">total_simulation_time</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t125" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">_current_time_index</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_time_array</span><span class="op">.</span><span class="nam">shape</span><span class="op">[</span><span class="num">0</span><span class="op">]</span> <span class="op">-</span> <span class="num">1</span><span class="strut"> </span></p> -<p id="t126" class="pln"><span class="strut"> </span></p> -<p id="t127" class="stm run hide_run"> <span class="key">def</span> <span class="nam">increment_time</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t128" class="pln"> <span class="str">"""Increments the simulation time by one time step (s) backwards</span><span class="strut"> </span></p> -<p id="t129" class="pln"><span class="strut"> </span></p> -<p id="t130" class="pln"><span class="str"> :return: time index, time (s)</span><span class="strut"> </span></p> -<p id="t131" class="pln"><span class="str"> :rtype: float, float</span><span class="strut"> </span></p> -<p id="t132" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t133" class="pln"><span class="strut"> </span></p> -<p id="t134" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">_current_time_index</span> <span class="op">-=</span> <span class="num">1</span><span class="strut"> </span></p> -<p id="t135" class="stm mis"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_current_time_index</span><span class="op">,</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t136" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">_time_array</span><span class="op">[</span><span class="nam">self</span><span class="op">.</span><span class="nam">_current_time_index</span><span class="op">]</span><span class="strut"> </span></p> - - </td> - </tr> - </table> -</div> - -<div id="footer"> - <div class="content"> - <p> - <a class="nav" href="index.html">« index</a> <a class="nav" href="https://coverage.readthedocs.io">coverage.py v4.5.3</a>, - created at 2019-07-09 15:15 - </p> - </div> -</div> - -</body> -</html> diff --git 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href="#n15">15</a></p> -<p id="n16" class="stm mis"><a href="#n16">16</a></p> -<p id="n17" class="stm mis"><a href="#n17">17</a></p> -<p id="n18" class="pln"><a href="#n18">18</a></p> -<p id="n19" class="pln"><a href="#n19">19</a></p> -<p id="n20" class="stm run hide_run"><a href="#n20">20</a></p> -<p id="n21" class="pln"><a href="#n21">21</a></p> -<p id="n22" class="pln"><a href="#n22">22</a></p> -<p id="n23" class="pln"><a href="#n23">23</a></p> -<p id="n24" class="pln"><a href="#n24">24</a></p> -<p id="n25" class="pln"><a href="#n25">25</a></p> -<p id="n26" class="pln"><a href="#n26">26</a></p> -<p id="n27" class="pln"><a href="#n27">27</a></p> -<p id="n28" class="pln"><a href="#n28">28</a></p> -<p id="n29" class="pln"><a href="#n29">29</a></p> -<p id="n30" class="pln"><a href="#n30">30</a></p> -<p id="n31" class="pln"><a href="#n31">31</a></p> -<p id="n32" class="pln"><a href="#n32">32</a></p> -<p id="n33" class="pln"><a href="#n33">33</a></p> -<p id="n34" class="pln"><a href="#n34">34</a></p> -<p id="n35" class="pln"><a href="#n35">35</a></p> -<p id="n36" class="pln"><a href="#n36">36</a></p> -<p id="n37" class="stm run hide_run"><a href="#n37">37</a></p> -<p id="n38" class="pln"><a href="#n38">38</a></p> -<p id="n39" class="stm run hide_run"><a href="#n39">39</a></p> -<p id="n40" class="stm run hide_run"><a href="#n40">40</a></p> -<p id="n41" class="stm run hide_run"><a href="#n41">41</a></p> -<p id="n42" class="stm run hide_run"><a href="#n42">42</a></p> -<p id="n43" class="pln"><a href="#n43">43</a></p> -<p id="n44" class="stm run hide_run"><a href="#n44">44</a></p> -<p id="n45" class="pln"><a href="#n45">45</a></p> -<p id="n46" class="stm run hide_run"><a href="#n46">46</a></p> -<p id="n47" class="pln"><a href="#n47">47</a></p> -<p id="n48" class="stm run hide_run"><a href="#n48">48</a></p> -<p id="n49" class="stm run hide_run"><a href="#n49">49</a></p> -<p id="n50" class="pln"><a href="#n50">50</a></p> -<p id="n51" class="stm run hide_run"><a href="#n51">51</a></p> -<p id="n52" class="pln"><a href="#n52">52</a></p> -<p id="n53" class="pln"><a href="#n53">53</a></p> -<p id="n54" class="pln"><a href="#n54">54</a></p> -<p id="n55" class="pln"><a href="#n55">55</a></p> -<p id="n56" class="pln"><a href="#n56">56</a></p> -<p id="n57" class="pln"><a href="#n57">57</a></p> -<p id="n58" class="pln"><a href="#n58">58</a></p> -<p id="n59" class="pln"><a href="#n59">59</a></p> -<p id="n60" class="pln"><a href="#n60">60</a></p> -<p id="n61" class="stm run hide_run"><a href="#n61">61</a></p> -<p id="n62" class="pln"><a href="#n62">62</a></p> -<p id="n63" class="stm run hide_run"><a href="#n63">63</a></p> -<p id="n64" class="pln"><a href="#n64">64</a></p> -<p id="n65" class="pln"><a href="#n65">65</a></p> -<p id="n66" class="pln"><a href="#n66">66</a></p> -<p id="n67" class="pln"><a href="#n67">67</a></p> -<p id="n68" class="pln"><a href="#n68">68</a></p> -<p id="n69" class="pln"><a href="#n69">69</a></p> -<p id="n70" class="pln"><a href="#n70">70</a></p> -<p id="n71" class="pln"><a href="#n71">71</a></p> -<p id="n72" class="pln"><a href="#n72">72</a></p> -<p id="n73" class="pln"><a href="#n73">73</a></p> -<p id="n74" class="stm run hide_run"><a href="#n74">74</a></p> -<p id="n75" class="pln"><a href="#n75">75</a></p> -<p id="n76" class="stm run hide_run"><a href="#n76">76</a></p> -<p id="n77" class="pln"><a href="#n77">77</a></p> -<p id="n78" class="pln"><a href="#n78">78</a></p> -<p id="n79" class="pln"><a href="#n79">79</a></p> -<p id="n80" class="pln"><a href="#n80">80</a></p> -<p id="n81" class="pln"><a href="#n81">81</a></p> -<p id="n82" class="pln"><a href="#n82">82</a></p> -<p id="n83" class="pln"><a href="#n83">83</a></p> -<p id="n84" class="pln"><a href="#n84">84</a></p> -<p id="n85" class="pln"><a href="#n85">85</a></p> -<p id="n86" class="pln"><a href="#n86">86</a></p> -<p id="n87" class="stm run hide_run"><a href="#n87">87</a></p> -<p id="n88" class="pln"><a href="#n88">88</a></p> -<p id="n89" class="stm run hide_run"><a href="#n89">89</a></p> -<p id="n90" class="pln"><a href="#n90">90</a></p> -<p id="n91" class="pln"><a href="#n91">91</a></p> -<p id="n92" class="stm run hide_run"><a href="#n92">92</a></p> -<p id="n93" class="pln"><a href="#n93">93</a></p> -<p id="n94" class="stm run hide_run"><a href="#n94">94</a></p> -<p id="n95" class="pln"><a href="#n95">95</a></p> -<p id="n96" class="pln"><a href="#n96">96</a></p> -<p id="n97" class="stm run hide_run"><a href="#n97">97</a></p> -<p id="n98" class="pln"><a href="#n98">98</a></p> -<p id="n99" class="pln"><a href="#n99">99</a></p> -<p id="n100" class="stm run hide_run"><a href="#n100">100</a></p> -<p id="n101" class="pln"><a href="#n101">101</a></p> -<p id="n102" class="stm run hide_run"><a href="#n102">102</a></p> -<p id="n103" class="stm mis"><a href="#n103">103</a></p> -<p id="n104" class="pln"><a href="#n104">104</a></p> -<p id="n105" class="stm run hide_run"><a href="#n105">105</a></p> -<p id="n106" class="pln"><a href="#n106">106</a></p> -<p id="n107" class="pln"><a href="#n107">107</a></p> -<p id="n108" class="stm run hide_run"><a href="#n108">108</a></p> -<p id="n109" class="pln"><a href="#n109">109</a></p> -<p id="n110" class="stm run hide_run"><a href="#n110">110</a></p> -<p id="n111" class="stm mis"><a href="#n111">111</a></p> -<p id="n112" class="stm mis"><a href="#n112">112</a></p> -<p id="n113" class="pln"><a href="#n113">113</a></p> -<p id="n114" class="stm run hide_run"><a href="#n114">114</a></p> -<p id="n115" class="pln"><a href="#n115">115</a></p> -<p id="n116" class="pln"><a href="#n116">116</a></p> -<p id="n117" class="pln"><a href="#n117">117</a></p> -<p id="n118" class="pln"><a href="#n118">118</a></p> -<p id="n119" class="pln"><a href="#n119">119</a></p> -<p id="n120" class="pln"><a href="#n120">120</a></p> -<p id="n121" class="stm run hide_run"><a href="#n121">121</a></p> -<p id="n122" class="pln"><a href="#n122">122</a></p> -<p id="n123" class="stm mis"><a href="#n123">123</a></p> -<p id="n124" class="pln"><a href="#n124">124</a></p> -<p id="n125" class="pln"><a href="#n125">125</a></p> -<p id="n126" class="stm mis"><a href="#n126">126</a></p> -<p id="n127" class="pln"><a href="#n127">127</a></p> -<p id="n128" class="pln"><a href="#n128">128</a></p> -<p id="n129" class="stm mis"><a href="#n129">129</a></p> -<p id="n130" class="pln"><a href="#n130">130</a></p> -<p id="n131" class="stm mis"><a href="#n131">131</a></p> -<p id="n132" class="stm mis"><a href="#n132">132</a></p> -<p id="n133" class="stm mis"><a href="#n133">133</a></p> -<p id="n134" class="stm mis"><a href="#n134">134</a></p> -<p id="n135" class="stm mis"><a href="#n135">135</a></p> -<p id="n136" class="stm mis"><a href="#n136">136</a></p> -<p id="n137" class="pln"><a href="#n137">137</a></p> -<p id="n138" class="pln"><a href="#n138">138</a></p> -<p id="n139" class="stm mis"><a href="#n139">139</a></p> -<p id="n140" class="pln"><a href="#n140">140</a></p> -<p id="n141" class="pln"><a href="#n141">141</a></p> -<p id="n142" class="pln"><a href="#n142">142</a></p> -<p id="n143" class="stm mis"><a href="#n143">143</a></p> -<p id="n144" class="pln"><a href="#n144">144</a></p> -<p id="n145" class="pln"><a href="#n145">145</a></p> -<p id="n146" class="stm mis"><a href="#n146">146</a></p> -<p id="n147" class="pln"><a href="#n147">147</a></p> -<p id="n148" class="stm mis"><a href="#n148">148</a></p> -<p id="n149" class="pln"><a href="#n149">149</a></p> -<p id="n150" class="stm mis"><a href="#n150">150</a></p> -<p id="n151" class="stm mis"><a href="#n151">151</a></p> -<p id="n152" class="stm mis"><a href="#n152">152</a></p> -<p id="n153" class="stm mis"><a href="#n153">153</a></p> -<p id="n154" class="stm mis"><a href="#n154">154</a></p> -<p id="n155" class="stm mis"><a href="#n155">155</a></p> -<p id="n156" class="stm mis"><a href="#n156">156</a></p> -<p id="n157" class="pln"><a href="#n157">157</a></p> -<p id="n158" class="stm mis"><a href="#n158">158</a></p> -<p id="n159" class="pln"><a href="#n159">159</a></p> -<p id="n160" class="pln"><a href="#n160">160</a></p> -<p id="n161" class="pln"><a href="#n161">161</a></p> -<p id="n162" class="pln"><a href="#n162">162</a></p> -<p id="n163" class="pln"><a href="#n163">163</a></p> -<p id="n164" class="pln"><a href="#n164">164</a></p> -<p id="n165" class="pln"><a href="#n165">165</a></p> -<p id="n166" class="stm mis"><a href="#n166">166</a></p> -<p id="n167" class="stm mis"><a href="#n167">167</a></p> -<p id="n168" class="pln"><a href="#n168">168</a></p> -<p id="n169" class="pln"><a href="#n169">169</a></p> -<p id="n170" class="stm mis"><a href="#n170">170</a></p> -<p id="n171" class="pln"><a href="#n171">171</a></p> -<p id="n172" class="pln"><a href="#n172">172</a></p> -<p id="n173" class="stm run hide_run"><a href="#n173">173</a></p> -<p id="n174" class="pln"><a href="#n174">174</a></p> -<p id="n175" class="pln"><a href="#n175">175</a></p> -<p id="n176" class="pln"><a href="#n176">176</a></p> -<p id="n177" class="pln"><a href="#n177">177</a></p> -<p id="n178" class="pln"><a href="#n178">178</a></p> -<p id="n179" class="pln"><a href="#n179">179</a></p> -<p id="n180" class="pln"><a href="#n180">180</a></p> -<p id="n181" class="pln"><a href="#n181">181</a></p> -<p id="n182" class="pln"><a href="#n182">182</a></p> -<p id="n183" class="pln"><a href="#n183">183</a></p> -<p id="n184" class="pln"><a href="#n184">184</a></p> -<p id="n185" class="pln"><a href="#n185">185</a></p> -<p id="n186" class="stm run hide_run"><a href="#n186">186</a></p> -<p id="n187" class="stm run hide_run"><a href="#n187">187</a></p> -<p id="n188" class="stm run hide_run"><a href="#n188">188</a></p> -<p id="n189" class="stm run hide_run"><a href="#n189">189</a></p> -<p id="n190" class="pln"><a href="#n190">190</a></p> -<p id="n191" class="pln"><a href="#n191">191</a></p> -<p id="n192" class="stm run hide_run"><a href="#n192">192</a></p> -<p id="n193" class="pln"><a href="#n193">193</a></p> -<p id="n194" class="stm run hide_run"><a href="#n194">194</a></p> -<p id="n195" class="pln"><a href="#n195">195</a></p> -<p id="n196" class="stm run hide_run"><a href="#n196">196</a></p> -<p id="n197" class="stm run hide_run"><a href="#n197">197</a></p> -<p id="n198" class="pln"><a href="#n198">198</a></p> -<p id="n199" class="stm run hide_run"><a href="#n199">199</a></p> -<p id="n200" class="pln"><a href="#n200">200</a></p> -<p id="n201" class="pln"><a href="#n201">201</a></p> -<p id="n202" class="pln"><a href="#n202">202</a></p> -<p id="n203" class="pln"><a href="#n203">203</a></p> -<p id="n204" class="pln"><a href="#n204">204</a></p> -<p id="n205" class="pln"><a href="#n205">205</a></p> -<p id="n206" class="pln"><a href="#n206">206</a></p> -<p id="n207" class="pln"><a href="#n207">207</a></p> -<p id="n208" class="pln"><a href="#n208">208</a></p> -<p id="n209" class="pln"><a href="#n209">209</a></p> -<p id="n210" class="pln"><a href="#n210">210</a></p> -<p id="n211" class="pln"><a href="#n211">211</a></p> -<p id="n212" class="pln"><a href="#n212">212</a></p> -<p id="n213" class="pln"><a href="#n213">213</a></p> -<p id="n214" class="pln"><a href="#n214">214</a></p> -<p id="n215" class="pln"><a href="#n215">215</a></p> -<p id="n216" class="pln"><a href="#n216">216</a></p> -<p id="n217" class="stm run hide_run"><a href="#n217">217</a></p> -<p id="n218" class="pln"><a href="#n218">218</a></p> -<p id="n219" class="stm run hide_run"><a href="#n219">219</a></p> -<p id="n220" class="pln"><a href="#n220">220</a></p> -<p id="n221" class="pln"><a href="#n221">221</a></p> -<p id="n222" class="pln"><a href="#n222">222</a></p> -<p id="n223" class="pln"><a href="#n223">223</a></p> -<p id="n224" class="pln"><a href="#n224">224</a></p> -<p id="n225" class="pln"><a href="#n225">225</a></p> -<p id="n226" class="pln"><a href="#n226">226</a></p> -<p id="n227" class="pln"><a href="#n227">227</a></p> -<p id="n228" class="stm run hide_run"><a href="#n228">228</a></p> -<p id="n229" class="pln"><a href="#n229">229</a></p> -<p id="n230" class="stm run hide_run"><a href="#n230">230</a></p> -<p id="n231" class="pln"><a href="#n231">231</a></p> -<p id="n232" class="pln"><a href="#n232">232</a></p> -<p id="n233" class="stm mis"><a href="#n233">233</a></p> -<p id="n234" class="pln"><a href="#n234">234</a></p> -<p id="n235" class="pln"><a href="#n235">235</a></p> -<p id="n236" class="stm mis"><a href="#n236">236</a></p> -<p id="n237" class="stm mis"><a href="#n237">237</a></p> -<p id="n238" class="stm mis"><a href="#n238">238</a></p> -<p id="n239" class="stm mis"><a href="#n239">239</a></p> -<p id="n240" class="stm mis"><a href="#n240">240</a></p> -<p id="n241" class="pln"><a href="#n241">241</a></p> -<p id="n242" class="pln"><a href="#n242">242</a></p> -<p id="n243" class="pln"><a href="#n243">243</a></p> -<p id="n244" class="stm mis"><a href="#n244">244</a></p> -<p id="n245" class="stm mis"><a href="#n245">245</a></p> -<p id="n246" class="stm mis"><a href="#n246">246</a></p> -<p id="n247" class="stm mis"><a href="#n247">247</a></p> -<p id="n248" class="pln"><a href="#n248">248</a></p> -<p id="n249" class="pln"><a href="#n249">249</a></p> -<p id="n250" class="stm mis"><a href="#n250">250</a></p> -<p id="n251" class="pln"><a href="#n251">251</a></p> -<p id="n252" class="stm mis"><a href="#n252">252</a></p> -<p id="n253" class="stm mis"><a href="#n253">253</a></p> -<p id="n254" class="stm mis"><a href="#n254">254</a></p> -<p id="n255" class="stm mis"><a href="#n255">255</a></p> -<p id="n256" class="pln"><a href="#n256">256</a></p> -<p id="n257" class="pln"><a href="#n257">257</a></p> -<p id="n258" class="pln"><a href="#n258">258</a></p> -<p id="n259" class="pln"><a href="#n259">259</a></p> -<p id="n260" class="stm mis"><a href="#n260">260</a></p> -<p id="n261" class="stm mis"><a href="#n261">261</a></p> -<p id="n262" class="stm mis"><a href="#n262">262</a></p> -<p id="n263" class="stm mis"><a href="#n263">263</a></p> -<p id="n264" class="pln"><a href="#n264">264</a></p> -<p id="n265" class="pln"><a href="#n265">265</a></p> -<p id="n266" class="stm run hide_run"><a href="#n266">266</a></p> -<p id="n267" class="pln"><a href="#n267">267</a></p> -<p id="n268" class="pln"><a href="#n268">268</a></p> -<p id="n269" class="pln"><a href="#n269">269</a></p> -<p id="n270" class="pln"><a href="#n270">270</a></p> -<p id="n271" class="pln"><a href="#n271">271</a></p> -<p id="n272" class="stm mis"><a href="#n272">272</a></p> -<p id="n273" class="stm mis"><a href="#n273">273</a></p> -<p id="n274" class="pln"><a href="#n274">274</a></p> -<p id="n275" class="stm mis"><a href="#n275">275</a></p> -<p id="n276" class="stm mis"><a href="#n276">276</a></p> -<p id="n277" class="pln"><a href="#n277">277</a></p> -<p id="n278" class="stm mis"><a href="#n278">278</a></p> -<p id="n279" class="stm mis"><a href="#n279">279</a></p> -<p id="n280" class="pln"><a href="#n280">280</a></p> -<p id="n281" class="stm mis"><a href="#n281">281</a></p> -<p id="n282" class="pln"><a href="#n282">282</a></p> -<p id="n283" class="pln"><a href="#n283">283</a></p> -<p id="n284" class="stm mis"><a href="#n284">284</a></p> -<p id="n285" class="pln"><a href="#n285">285</a></p> -<p id="n286" class="pln"><a href="#n286">286</a></p> -<p id="n287" class="stm mis"><a href="#n287">287</a></p> -<p id="n288" class="stm mis"><a href="#n288">288</a></p> -<p id="n289" class="stm mis"><a href="#n289">289</a></p> -<p id="n290" class="stm mis"><a href="#n290">290</a></p> -<p id="n291" class="stm mis"><a href="#n291">291</a></p> -<p id="n292" class="stm mis"><a href="#n292">292</a></p> -<p id="n293" class="pln"><a href="#n293">293</a></p> -<p id="n294" class="stm mis"><a href="#n294">294</a></p> -<p id="n295" class="stm mis"><a href="#n295">295</a></p> -<p id="n296" class="pln"><a href="#n296">296</a></p> -<p id="n297" class="stm mis"><a href="#n297">297</a></p> -<p id="n298" class="pln"><a href="#n298">298</a></p> -<p id="n299" class="pln"><a href="#n299">299</a></p> -<p id="n300" class="stm mis"><a href="#n300">300</a></p> -<p id="n301" class="pln"><a href="#n301">301</a></p> -<p id="n302" class="stm mis"><a href="#n302">302</a></p> -<p id="n303" class="stm mis"><a href="#n303">303</a></p> -<p id="n304" class="pln"><a href="#n304">304</a></p> -<p id="n305" class="stm mis"><a href="#n305">305</a></p> -<p id="n306" class="stm mis"><a href="#n306">306</a></p> -<p id="n307" class="pln"><a href="#n307">307</a></p> -<p id="n308" class="stm mis"><a href="#n308">308</a></p> -<p id="n309" class="pln"><a href="#n309">309</a></p> -<p id="n310" class="stm mis"><a href="#n310">310</a></p> -<p id="n311" class="pln"><a href="#n311">311</a></p> -<p id="n312" class="stm mis"><a href="#n312">312</a></p> -<p id="n313" class="pln"><a href="#n313">313</a></p> -<p id="n314" class="stm mis"><a href="#n314">314</a></p> -<p id="n315" class="pln"><a href="#n315">315</a></p> -<p id="n316" class="stm mis"><a href="#n316">316</a></p> -<p id="n317" class="stm mis"><a href="#n317">317</a></p> - - </td> - <td class="text"> -<p id="t1" class="stm run hide_run"><span class="key">import</span> <span class="nam">numpy</span> <span class="key">as</span> <span class="nam">np</span><span class="strut"> </span></p> -<p id="t2" class="stm run hide_run"><span class="key">from</span> <span class="nam">copy</span> <span class="key">import</span> <span class="nam">deepcopy</span><span class="strut"> </span></p> -<p id="t3" class="stm run hide_run"><span class="key">from</span> <span class="nam">fluegg</span><span class="op">.</span><span class="nam">hydraulics</span> <span class="key">import</span> <span class="nam">from_csv</span><span class="strut"> </span></p> -<p id="t4" class="stm run hide_run"><span class="key">from</span> <span class="nam">fluegg</span><span class="op">.</span><span class="nam">hydraulics</span> <span class="key">import</span> <span class="nam">RoughBottomSeriesOfHydraulicCells</span><span class="strut"> </span></p> -<p id="t5" class="stm run hide_run"><span class="key">from</span> <span class="nam">fluegg</span><span class="op">.</span><span class="nam">simclock</span> <span class="key">import</span> <span class="nam">SimulationClock</span><span class="strut"> </span></p> -<p id="t6" class="stm run hide_run"><span class="key">from</span> <span class="nam">fluegg</span><span class="op">.</span><span class="nam">asiancarpeggs</span> <span class="key">import</span> <span class="nam">BigheadCarpEggs</span><span class="strut"> </span></p> -<p id="t7" class="stm run hide_run"><span class="key">from</span> <span class="nam">fluegg</span><span class="op">.</span><span class="nam">asiancarpeggs</span> <span class="key">import</span> <span class="nam">SilverCarpEggs</span><span class="strut"> </span></p> -<p id="t8" class="stm run hide_run"><span class="key">from</span> <span class="nam">fluegg</span><span class="op">.</span><span class="nam">asiancarpeggs</span> <span class="key">import</span> <span class="nam">GrassCarpEggs</span><span class="strut"> </span></p> -<p id="t9" class="stm run hide_run"><span class="key">from</span> <span class="nam">fluegg</span><span class="op">.</span><span class="nam">transporter</span> <span class="key">import</span> <span class="nam">init_transporter</span><span class="strut"> </span></p> -<p id="t10" class="stm run hide_run"><span class="key">import</span> <span class="nam">h5py</span><span class="strut"> </span></p> -<p id="t11" class="stm run hide_run"><span class="key">import</span> <span class="nam">os</span><span class="strut"> </span></p> -<p id="t12" class="stm run hide_run"><span class="key">import</span> <span class="nam">datetime</span><span class="strut"> </span></p> -<p id="t13" class="pln"><span class="strut"> </span></p> -<p id="t14" class="stm run hide_run"><span class="key">try</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t15" class="stm run hide_run"> <span class="key">from</span> <span class="nam">fluegg</span><span class="op">.</span><span class="nam">ras</span> <span class="key">import</span> <span class="nam">RASProject</span><span class="strut"> </span></p> -<p id="t16" class="stm mis"><span class="key">except</span> <span class="nam">ModuleNotFoundError</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t17" class="stm mis"> <span class="key">pass</span><span class="strut"> </span></p> -<p id="t18" class="pln"><span class="strut"> </span></p> -<p id="t19" class="pln"><span class="strut"> </span></p> -<p id="t20" class="stm run hide_run"><span class="key">class</span> <span class="nam">Simulation</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t21" class="pln"> <span class="str">"""Class that controls the simulation by incrementing time</span><span class="strut"> </span></p> -<p id="t22" class="pln"><span class="str"> steps and calling simulation functions correctly.</span><span class="strut"> </span></p> -<p id="t23" class="pln"><span class="strut"> </span></p> -<p id="t24" class="pln"><span class="str"> Parameters</span><span class="strut"> </span></p> -<p id="t25" class="pln"><span class="str"> ----------</span><span class="strut"> </span></p> -<p id="t26" class="pln"><span class="str"> particles : fluegg.drift.DriftingParticles</span><span class="strut"> </span></p> -<p id="t27" class="pln"><span class="str"> Particles being drifted through the simulation</span><span class="strut"> </span></p> -<p id="t28" class="pln"><span class="strut"> </span></p> -<p id="t29" class="pln"><span class="str"> transporter : fluegg.transporter.Transporter</span><span class="strut"> </span></p> -<p id="t30" class="pln"><span class="str"> Class that physically transports each egg for each time step</span><span class="strut"> </span></p> -<p id="t31" class="pln"><span class="strut"> </span></p> -<p id="t32" class="pln"><span class="str"> simclock : fluegg.simclock.SimulationClock</span><span class="strut"> </span></p> -<p id="t33" class="pln"><span class="str"> Clock that keeps track of the time during the simulation</span><span class="strut"> </span></p> -<p id="t34" class="pln"><span class="strut"> </span></p> -<p id="t35" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t36" class="pln"><span class="strut"> </span></p> -<p id="t37" class="stm run hide_run"> <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">particles</span><span class="op">,</span> <span class="nam">transporter</span><span class="op">,</span> <span class="nam">simclock</span><span class="op">,</span> <span class="nam">hydraulic_cells</span><span class="op">=</span><span class="key">None</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t38" class="pln"><span class="strut"> </span></p> -<p id="t39" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_hydraulic_model</span> <span class="op">=</span> <span class="nam">hydraulic_cells</span><span class="strut"> </span></p> -<p id="t40" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_particles</span> <span class="op">=</span> <span class="nam">particles</span><span class="strut"> </span></p> -<p id="t41" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_transporter</span> <span class="op">=</span> <span class="nam">transporter</span><span class="strut"> </span></p> -<p id="t42" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_simclock</span> <span class="op">=</span> <span class="nam">simclock</span><span class="strut"> </span></p> -<p id="t43" class="pln"><span class="strut"> </span></p> -<p id="t44" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_time_step_function_calls</span> <span class="op">=</span> <span class="op">{</span><span class="op">}</span><span class="strut"> </span></p> -<p id="t45" class="pln"><span class="strut"> </span></p> -<p id="t46" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_call_time_step_functions</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t47" class="pln"><span class="strut"> </span></p> -<p id="t48" class="stm run hide_run"> <span class="key">for</span> <span class="nam">fun</span><span class="op">,</span> <span class="nam">args</span> <span class="key">in</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_time_step_function_calls</span><span class="op">.</span><span class="nam">items</span><span class="op">(</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t49" class="stm run hide_run"> <span class="nam">fun</span><span class="op">(</span><span class="op">*</span><span class="nam">args</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t50" class="pln"><span class="strut"> </span></p> -<p id="t51" class="stm run hide_run"> <span class="key">def</span> <span class="nam">add_time_step_function_call</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">fun</span><span class="op">,</span> <span class="nam">args</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t52" class="pln"> <span class="str">"""Adds a function that will be called at the beginning of a time step.</span><span class="strut"> </span></p> -<p id="t53" class="pln"><span class="strut"> </span></p> -<p id="t54" class="pln"><span class="str"> Parameters</span><span class="strut"> </span></p> -<p id="t55" class="pln"><span class="str"> ----------</span><span class="strut"> </span></p> -<p id="t56" class="pln"><span class="str"> fun : function</span><span class="strut"> </span></p> -<p id="t57" class="pln"><span class="str"> args : list</span><span class="strut"> </span></p> -<p id="t58" class="pln"><span class="strut"> </span></p> -<p id="t59" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t60" class="pln"><span class="strut"> </span></p> -<p id="t61" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_time_step_function_calls</span><span class="op">[</span><span class="nam">fun</span><span class="op">]</span> <span class="op">=</span> <span class="nam">args</span><span class="strut"> </span></p> -<p id="t62" class="pln"><span class="strut"> </span></p> -<p id="t63" class="stm run hide_run"> <span class="key">def</span> <span class="nam">set_hydraulic_model</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">hydraulic_model</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t64" class="pln"> <span class="str">"""Sets the hydraulic model used in this instance.</span><span class="strut"> </span></p> -<p id="t65" class="pln"><span class="strut"> </span></p> -<p id="t66" class="pln"><span class="str"> Required before calling run().</span><span class="strut"> </span></p> -<p id="t67" class="pln"><span class="strut"> </span></p> -<p id="t68" class="pln"><span class="str"> Parameters</span><span class="strut"> </span></p> -<p id="t69" class="pln"><span class="str"> ----------</span><span class="strut"> </span></p> -<p id="t70" class="pln"><span class="str"> hydraulic_model : fluegg.hydraulics.SeriesOfHydraulicCells</span><span class="strut"> </span></p> -<p id="t71" class="pln"><span class="strut"> </span></p> -<p id="t72" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t73" class="pln"><span class="strut"> </span></p> -<p id="t74" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_hydraulic_model</span> <span class="op">=</span> <span class="nam">hydraulic_model</span><span class="strut"> </span></p> -<p id="t75" class="pln"><span class="strut"> </span></p> -<p id="t76" class="stm run hide_run"> <span class="key">def</span> <span class="nam">run</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">configuration</span><span class="op">=</span><span class="op">{</span><span class="op">}</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t77" class="pln"> <span class="str">"""Runs the simulation and returns the time-stamped positions</span><span class="strut"> </span></p> -<p id="t78" class="pln"><span class="str"> of the particles throughout the simulation</span><span class="strut"> </span></p> -<p id="t79" class="pln"><span class="strut"> </span></p> -<p id="t80" class="pln"><span class="str"> Returns</span><span class="strut"> </span></p> -<p id="t81" class="pln"><span class="str"> -------</span><span class="strut"> </span></p> -<p id="t82" class="pln"><span class="str"> SimulationResults</span><span class="strut"> </span></p> -<p id="t83" class="pln"><span class="strut"> </span></p> -<p id="t84" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t85" class="pln"><span class="strut"> </span></p> -<p id="t86" class="pln"> <span class="com"># Initialize simulation results</span><span class="strut"> </span></p> -<p id="t87" class="stm run hide_run"> <span class="nam">simulation_results</span> <span class="op">=</span> <span class="nam">SimulationResults</span><span class="op">(</span><span class="strut"> </span></p> -<p id="t88" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">_simclock</span><span class="op">,</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_particles</span><span class="op">,</span> <span class="nam">configuration</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t89" class="stm run hide_run"> <span class="nam">simulation_results</span><span class="op">.</span><span class="nam">record_result</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t90" class="pln"><span class="strut"> </span></p> -<p id="t91" class="pln"> <span class="com"># Run through all time steps</span><span class="strut"> </span></p> -<p id="t92" class="stm run hide_run"> <span class="key">for</span> <span class="nam">_</span> <span class="key">in</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_simclock</span><span class="op">.</span><span class="nam">iter_time_index</span><span class="op">(</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t93" class="pln"><span class="strut"> </span></p> -<p id="t94" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_call_time_step_functions</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t95" class="pln"><span class="strut"> </span></p> -<p id="t96" class="pln"> <span class="com"># record the result in the current state</span><span class="strut"> </span></p> -<p id="t97" class="stm run hide_run"> <span class="nam">simulation_results</span><span class="op">.</span><span class="nam">record_result</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t98" class="pln"><span class="strut"> </span></p> -<p id="t99" class="pln"> <span class="com"># Get positions and hydraulic results</span><span class="strut"> </span></p> -<p id="t100" class="stm run hide_run"> <span class="nam">positions</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_particles</span><span class="op">.</span><span class="nam">position</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t101" class="pln"><span class="strut"> </span></p> -<p id="t102" class="stm run hide_run"> <span class="key">if</span> <span class="nam">np</span><span class="op">.</span><span class="nam">all</span><span class="op">(</span><span class="nam">np</span><span class="op">.</span><span class="nam">isnan</span><span class="op">(</span><span class="nam">positions</span><span class="op">)</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t103" class="stm mis"> <span class="key">break</span><span class="strut"> </span></p> -<p id="t104" class="pln"><span class="strut"> </span></p> -<p id="t105" class="stm run hide_run"> <span class="nam">hydraulic_results</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t106" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">_hydraulic_model</span><span class="op">.</span><span class="nam">hydraulic_results</span><span class="op">(</span><span class="nam">positions</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t107" class="pln"><span class="strut"> </span></p> -<p id="t108" class="stm run hide_run"> <span class="key">try</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t109" class="pln"> <span class="com"># Increment positions</span><span class="strut"> </span></p> -<p id="t110" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_transporter</span><span class="op">.</span><span class="nam">increment_positions</span><span class="op">(</span><span class="nam">hydraulic_results</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t111" class="stm mis"> <span class="key">except</span> <span class="nam">ValueError</span> <span class="key">as</span> <span class="nam">e</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t112" class="stm mis"> <span class="key">raise</span> <span class="nam">e</span><span class="strut"> </span></p> -<p id="t113" class="pln"><span class="strut"> </span></p> -<p id="t114" class="stm run hide_run"> <span class="key">return</span> <span class="nam">simulation_results</span><span class="strut"> </span></p> -<p id="t115" class="pln"><span class="strut"> </span></p> -<p id="t116" class="pln"> <span class="com"># Raise error if time step is too large</span><span class="strut"> </span></p> -<p id="t117" class="pln"> <span class="com"># if user_step > max_step:</span><span class="strut"> </span></p> -<p id="t118" class="pln"> <span class="com"># raise ValueError('User time step is', user_step, '. Must be at less than', max_step)</span><span class="strut"> </span></p> -<p id="t119" class="pln"><span class="strut"> </span></p> -<p id="t120" class="pln"><span class="strut"> </span></p> -<p id="t121" class="stm run hide_run"><span class="key">def</span> <span class="nam">from_input_dict</span><span class="op">(</span><span class="nam">d</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t122" class="pln"> <span class="str">"""Creates a Simulation object from an input dictionary"""</span><span class="strut"> </span></p> -<p id="t123" class="stm mis"> <span class="nam">input_dict_validator</span><span class="op">(</span><span class="nam">d</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t124" class="pln"><span class="strut"> </span></p> -<p id="t125" class="pln"> <span class="com"># Simulation Clock</span><span class="strut"> </span></p> -<p id="t126" class="stm mis"> <span class="nam">simulation_clock</span> <span class="op">=</span> <span class="nam">SimulationClock</span><span class="op">(</span><span class="nam">d</span><span class="op">[</span><span class="str">'time_step'</span><span class="op">]</span><span class="op">,</span> <span class="nam">d</span><span class="op">[</span><span class="str">'duration'</span><span class="op">]</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t127" class="pln"><span class="strut"> </span></p> -<p id="t128" class="pln"> <span class="com"># Drifting Particles</span><span class="strut"> </span></p> -<p id="t129" class="stm mis"> <span class="nam">initial_position</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">tile</span><span class="op">(</span><span class="strut"> </span></p> -<p id="t130" class="pln"> <span class="nam">np</span><span class="op">.</span><span class="nam">array</span><span class="op">(</span><span class="op">[</span><span class="nam">d</span><span class="op">[</span><span class="str">'x'</span><span class="op">]</span><span class="op">,</span> <span class="nam">d</span><span class="op">[</span><span class="str">'y'</span><span class="op">]</span><span class="op">,</span> <span class="nam">d</span><span class="op">[</span><span class="str">'z'</span><span class="op">]</span><span class="op">]</span><span class="op">)</span><span class="op">,</span> <span class="op">(</span><span class="nam">d</span><span class="op">[</span><span class="str">'num_eggs'</span><span class="op">]</span><span class="op">,</span> <span class="num">1</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t131" class="stm mis"> <span class="key">if</span> <span class="nam">d</span><span class="op">[</span><span class="str">'species'</span><span class="op">]</span> <span class="op">==</span> <span class="str">'grass'</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t132" class="stm mis"> <span class="nam">drift</span> <span class="op">=</span> <span class="nam">GrassCarpEggs</span><span class="op">(</span><span class="nam">initial_position</span><span class="op">,</span> <span class="nam">simulation_clock</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t133" class="stm mis"> <span class="key">elif</span> <span class="nam">d</span><span class="op">[</span><span class="str">'species'</span><span class="op">]</span> <span class="op">==</span> <span class="str">'silver'</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t134" class="stm mis"> <span class="nam">drift</span> <span class="op">=</span> <span class="nam">SilverCarpEggs</span><span class="op">(</span><span class="nam">initial_position</span><span class="op">,</span> <span class="nam">simulation_clock</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t135" class="stm mis"> <span class="key">elif</span> <span class="nam">d</span><span class="op">[</span><span class="str">'species'</span><span class="op">]</span> <span class="op">==</span> <span class="str">'bighead'</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t136" class="stm mis"> <span class="nam">drift</span> <span class="op">=</span> <span class="nam">BigheadCarpEggs</span><span class="op">(</span><span class="nam">initial_position</span><span class="op">,</span> <span class="nam">simulation_clock</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t137" class="pln"><span class="strut"> </span></p> -<p id="t138" class="pln"> <span class="com"># Transporter</span><span class="strut"> </span></p> -<p id="t139" class="stm mis"> <span class="nam">transporter_model</span> <span class="op">=</span> <span class="nam">init_transporter</span><span class="op">(</span><span class="strut"> </span></p> -<p id="t140" class="pln"> <span class="nam">simulation_clock</span><span class="op">,</span> <span class="nam">drift</span><span class="op">,</span> <span class="nam">d</span><span class="op">[</span><span class="str">'diffusivity'</span><span class="op">]</span><span class="op">,</span> <span class="nam">d</span><span class="op">[</span><span class="str">'direction'</span><span class="op">]</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t141" class="pln"><span class="strut"> </span></p> -<p id="t142" class="pln"> <span class="com"># Simulation</span><span class="strut"> </span></p> -<p id="t143" class="stm mis"> <span class="nam">sim</span> <span class="op">=</span> <span class="nam">Simulation</span><span class="op">(</span><span class="nam">drift</span><span class="op">,</span> <span class="nam">transporter_model</span><span class="op">,</span> <span class="nam">simulation_clock</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t144" class="pln"><span class="strut"> </span></p> -<p id="t145" class="pln"> <span class="com"># Hydraulic cells (csv vs. hecras)</span><span class="strut"> </span></p> -<p id="t146" class="stm mis"> <span class="key">if</span> <span class="nam">d</span><span class="op">[</span><span class="str">'hydraulic_mode'</span><span class="op">]</span> <span class="op">==</span> <span class="str">'csv'</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t147" class="pln"> <span class="com"># Hydraulic channel (CSV)</span><span class="strut"> </span></p> -<p id="t148" class="stm mis"> <span class="nam">hydraulic_cells</span> <span class="op">=</span> <span class="nam">from_csv</span><span class="op">(</span><span class="nam">d</span><span class="op">[</span><span class="str">'csv_path'</span><span class="op">]</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t149" class="pln"> <span class="com"># Hecras Mode</span><span class="strut"> </span></p> -<p id="t150" class="stm mis"> <span class="key">if</span> <span class="nam">d</span><span class="op">[</span><span class="str">'hydraulic_mode'</span><span class="op">]</span> <span class="op">==</span> <span class="str">'hecras'</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t151" class="stm mis"> <span class="key">with</span> <span class="nam">RASProject</span><span class="op">(</span><span class="nam">d</span><span class="op">[</span><span class="str">'hecras_path'</span><span class="op">]</span><span class="op">)</span> <span class="key">as</span> <span class="nam">rp</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t152" class="stm mis"> <span class="nam">plan_name</span> <span class="op">=</span> <span class="nam">d</span><span class="op">[</span><span class="str">'hecras_plan'</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t153" class="stm mis"> <span class="nam">rp</span><span class="op">.</span><span class="nam">set_current_plan</span><span class="op">(</span><span class="nam">plan_name</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t154" class="stm mis"> <span class="nam">profile_name</span> <span class="op">=</span> <span class="nam">d</span><span class="op">[</span><span class="str">'hecras_profile'</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t155" class="stm mis"> <span class="nam">temperature</span> <span class="op">=</span> <span class="nam">d</span><span class="op">[</span><span class="str">'hecras_temperature'</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t156" class="stm mis"> <span class="nam">hydraulic_data_frame</span> <span class="op">=</span> <span class="nam">rp</span><span class="op">.</span><span class="nam">hydraulic_model_data</span><span class="op">(</span><span class="strut"> </span></p> -<p id="t157" class="pln"> <span class="nam">profile_name</span><span class="op">,</span> <span class="nam">temperature</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t158" class="stm mis"> <span class="nam">hydraulic_cells</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t159" class="pln"> <span class="nam">RoughBottomSeriesOfHydraulicCells</span><span class="op">.</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t160" class="pln"> <span class="nam">from_data_frame</span><span class="op">(</span><span class="nam">hydraulic_data_frame</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t161" class="pln"> <span class="nam">start_time</span><span class="op">=</span><span class="nam">d</span><span class="op">[</span><span class="str">'hecras_start_time'</span><span class="op">]</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t162" class="pln"> <span class="nam">simulation_clock</span><span class="op">=</span><span class="nam">simulation_clock</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t163" class="pln"> <span class="nam">simulation</span><span class="op">=</span><span class="nam">sim</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t164" class="pln"><span class="strut"> </span></p> -<p id="t165" class="pln"> <span class="com"># Update sim & transporter with hydraulic cells</span><span class="strut"> </span></p> -<p id="t166" class="stm mis"> <span class="nam">sim</span><span class="op">.</span><span class="nam">set_hydraulic_model</span><span class="op">(</span><span class="nam">hydraulic_cells</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t167" class="stm mis"> <span class="nam">transporter_model</span><span class="op">.</span><span class="nam">set_hydraulic_model</span><span class="op">(</span><span class="nam">hydraulic_cells</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t168" class="pln"><span class="strut"> </span></p> -<p id="t169" class="pln"> <span class="com"># Return simulation</span><span class="strut"> </span></p> -<p id="t170" class="stm mis"> <span class="key">return</span> <span class="nam">sim</span><span class="strut"> </span></p> -<p id="t171" class="pln"><span class="strut"> </span></p> -<p id="t172" class="pln"><span class="strut"> </span></p> -<p id="t173" class="stm run hide_run"><span class="key">class</span> <span class="nam">SimulationResults</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t174" class="pln"> <span class="str">"""Data structure containing simulation results during a simulation run</span><span class="strut"> </span></p> -<p id="t175" class="pln"><span class="strut"> </span></p> -<p id="t176" class="pln"><span class="str"> Parameters</span><span class="strut"> </span></p> -<p id="t177" class="pln"><span class="str"> ----------</span><span class="strut"> </span></p> -<p id="t178" class="pln"><span class="str"> simclock : fluegg.simclock.SimulationClock</span><span class="strut"> </span></p> -<p id="t179" class="pln"><span class="str"> Representation of a simulation clock</span><span class="strut"> </span></p> -<p id="t180" class="pln"><span class="strut"> </span></p> -<p id="t181" class="pln"><span class="str"> particles : fluegg.drift.DriftingParticle</span><span class="strut"> </span></p> -<p id="t182" class="pln"><span class="str"> Particles that were are being drifted through the simulation</span><span class="strut"> </span></p> -<p id="t183" class="pln"><span class="strut"> </span></p> -<p id="t184" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t185" class="pln"><span class="strut"> </span></p> -<p id="t186" class="stm run hide_run"> <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">simclock</span><span class="op">,</span> <span class="nam">particles</span><span class="op">,</span> <span class="nam">configuration</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t187" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_simclock</span> <span class="op">=</span> <span class="nam">simclock</span><span class="strut"> </span></p> -<p id="t188" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_particles</span> <span class="op">=</span> <span class="nam">particles</span><span class="strut"> </span></p> -<p id="t189" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_positions</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">tile</span><span class="op">(</span><span class="strut"> </span></p> -<p id="t190" class="pln"> <span class="nam">np</span><span class="op">.</span><span class="nam">nan</span><span class="op">,</span> <span class="op">(</span><span class="nam">simclock</span><span class="op">.</span><span class="nam">number_of_time_steps</span><span class="op">(</span><span class="op">)</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t191" class="pln"> <span class="nam">particles</span><span class="op">.</span><span class="nam">position</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">shape</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="op">,</span> <span class="num">3</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t192" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_configuration</span> <span class="op">=</span> <span class="nam">configuration</span><span class="strut"> </span></p> -<p id="t193" class="pln"><span class="strut"> </span></p> -<p id="t194" class="stm run hide_run"> <span class="key">def</span> <span class="nam">record_result</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t195" class="pln"> <span class="str">"""Records the current particle positions in the positions array."""</span><span class="strut"> </span></p> -<p id="t196" class="stm run hide_run"> <span class="nam">time_index</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_simclock</span><span class="op">.</span><span class="nam">current_time_index</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t197" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_positions</span><span class="op">[</span><span class="nam">time_index</span><span class="op">]</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_particles</span><span class="op">.</span><span class="nam">position</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t198" class="pln"><span class="strut"> </span></p> -<p id="t199" class="stm run hide_run"> <span class="key">def</span> <span class="nam">results</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t200" class="pln"> <span class="str">"""Returns the positions of the particles logged throughout the</span><span class="strut"> </span></p> -<p id="t201" class="pln"><span class="str"> simulation.</span><span class="strut"> </span></p> -<p id="t202" class="pln"><span class="strut"> </span></p> -<p id="t203" class="pln"><span class="str"> The returned array is structured as</span><span class="strut"> </span></p> -<p id="t204" class="pln"><span class="strut"> </span></p> -<p id="t205" class="pln"><span class="str"> Axis Values Size</span><span class="strut"> </span></p> -<p id="t206" class="pln"><span class="str"> 0 Time step Number of time steps (N_t)</span><span class="strut"> </span></p> -<p id="t207" class="pln"><span class="str"> 1 Particle number Number of eggs (N_e)</span><span class="strut"> </span></p> -<p id="t208" class="pln"><span class="str"> 3 Position (x, y, z) 3</span><span class="strut"> </span></p> -<p id="t209" class="pln"><span class="strut"> </span></p> -<p id="t210" class="pln"><span class="str"> The shape of the array is (N_t, N_e, 3).</span><span class="strut"> </span></p> -<p id="t211" class="pln"><span class="strut"> </span></p> -<p id="t212" class="pln"><span class="str"> Returns</span><span class="strut"> </span></p> -<p id="t213" class="pln"><span class="str"> -------</span><span class="strut"> </span></p> -<p id="t214" class="pln"><span class="str"> numpy.ndarray</span><span class="strut"> </span></p> -<p id="t215" class="pln"><span class="strut"> </span></p> -<p id="t216" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t217" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_positions</span><span class="strut"> </span></p> -<p id="t218" class="pln"><span class="strut"> </span></p> -<p id="t219" class="stm run hide_run"> <span class="key">def</span> <span class="nam">time</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t220" class="pln"> <span class="str">"""Returns time array</span><span class="strut"> </span></p> -<p id="t221" class="pln"><span class="strut"> </span></p> -<p id="t222" class="pln"><span class="str"> Returns</span><span class="strut"> </span></p> -<p id="t223" class="pln"><span class="str"> -------</span><span class="strut"> </span></p> -<p id="t224" class="pln"><span class="str"> numpy.ndarray</span><span class="strut"> </span></p> -<p id="t225" class="pln"><span class="strut"> </span></p> -<p id="t226" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t227" class="pln"><span class="strut"> </span></p> -<p id="t228" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_simclock</span><span class="op">.</span><span class="nam">time_array</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t229" class="pln"><span class="strut"> </span></p> -<p id="t230" class="stm run hide_run"> <span class="key">def</span> <span class="nam">save_results</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">file_path</span><span class="op">=</span><span class="key">None</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t231" class="pln"> <span class="str">"""Save the results of a simulation to an hdf time-stamped file"""</span><span class="strut"> </span></p> -<p id="t232" class="pln"><span class="strut"> </span></p> -<p id="t233" class="stm mis"> <span class="key">if</span> <span class="nam">file_path</span> <span class="key">is</span> <span class="key">None</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t234" class="pln"><span class="strut"> </span></p> -<p id="t235" class="pln"> <span class="com"># Create results folder</span><span class="strut"> </span></p> -<p id="t236" class="stm mis"> <span class="nam">absolute_path</span><span class="op">,</span> <span class="nam">_</span> <span class="op">=</span> <span class="nam">os</span><span class="op">.</span><span class="nam">path</span><span class="op">.</span><span class="nam">split</span><span class="op">(</span><span class="nam">os</span><span class="op">.</span><span class="nam">path</span><span class="op">.</span><span class="nam">realpath</span><span class="op">(</span><span class="nam">__file__</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t237" class="stm mis"> <span class="nam">p</span> <span class="op">=</span> <span class="nam">os</span><span class="op">.</span><span class="nam">path</span><span class="op">.</span><span class="nam">abspath</span><span class="op">(</span><span class="nam">os</span><span class="op">.</span><span class="nam">path</span><span class="op">.</span><span class="nam">join</span><span class="op">(</span><span class="nam">absolute_path</span><span class="op">,</span> <span class="nam">os</span><span class="op">.</span><span class="nam">pardir</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t238" class="stm mis"> <span class="nam">p</span> <span class="op">=</span> <span class="nam">os</span><span class="op">.</span><span class="nam">path</span><span class="op">.</span><span class="nam">join</span><span class="op">(</span><span class="nam">p</span><span class="op">,</span> <span class="str">'results'</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t239" class="stm mis"> <span class="key">if</span> <span class="key">not</span> <span class="nam">os</span><span class="op">.</span><span class="nam">path</span><span class="op">.</span><span class="nam">exists</span><span class="op">(</span><span class="nam">p</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t240" class="stm mis"> <span class="nam">os</span><span class="op">.</span><span class="nam">makedirs</span><span class="op">(</span><span class="nam">p</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t241" class="pln"><span class="strut"> </span></p> -<p id="t242" class="pln"> <span class="com"># Check if sim_name exists in configuration, if not use current</span><span class="strut"> </span></p> -<p id="t243" class="pln"> <span class="com"># time</span><span class="strut"> </span></p> -<p id="t244" class="stm mis"> <span class="key">if</span> <span class="key">not</span> <span class="op">(</span><span class="str">'sim_name'</span> <span class="key">in</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_configuration</span><span class="op">.</span><span class="nam">keys</span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t245" class="stm mis"> <span class="nam">now</span> <span class="op">=</span> <span class="nam">datetime</span><span class="op">.</span><span class="nam">datetime</span><span class="op">.</span><span class="nam">now</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t246" class="stm mis"> <span class="nam">date_string</span> <span class="op">=</span> <span class="nam">now</span><span class="op">.</span><span class="nam">strftime</span><span class="op">(</span><span class="str">'%Y-%m-%d-%H-%M-%S'</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t247" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">_configuration</span><span class="op">[</span><span class="str">'sim_name'</span><span class="op">]</span> <span class="op">=</span> <span class="str">'fluegg_'</span> <span class="op">+</span> <span class="nam">date_string</span><span class="strut"> </span></p> -<p id="t248" class="pln"><span class="strut"> </span></p> -<p id="t249" class="pln"> <span class="com"># Check if results file already exists</span><span class="strut"> </span></p> -<p id="t250" class="stm mis"> <span class="nam">file_path</span> <span class="op">=</span> <span class="nam">os</span><span class="op">.</span><span class="nam">path</span><span class="op">.</span><span class="nam">join</span><span class="op">(</span><span class="strut"> </span></p> -<p id="t251" class="pln"> <span class="nam">p</span><span class="op">,</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_configuration</span><span class="op">[</span><span class="str">'sim_name'</span><span class="op">]</span><span class="op">)</span> <span class="op">+</span> <span class="str">'.h5'</span><span class="strut"> </span></p> -<p id="t252" class="stm mis"> <span class="key">if</span> <span class="nam">os</span><span class="op">.</span><span class="nam">path</span><span class="op">.</span><span class="nam">exists</span><span class="op">(</span><span class="nam">file_path</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t253" class="stm mis"> <span class="nam">now</span> <span class="op">=</span> <span class="nam">datetime</span><span class="op">.</span><span class="nam">datetime</span><span class="op">.</span><span class="nam">now</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t254" class="stm mis"> <span class="nam">date_string</span> <span class="op">=</span> <span class="nam">now</span><span class="op">.</span><span class="nam">strftime</span><span class="op">(</span><span class="str">'%Y-%m-%d-%H-%M-%S'</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t255" class="stm mis"> <span class="nam">file_path</span> <span class="op">=</span> <span class="nam">os</span><span class="op">.</span><span class="nam">path</span><span class="op">.</span><span class="nam">join</span><span class="op">(</span><span class="strut"> </span></p> -<p id="t256" class="pln"> <span class="nam">p</span><span class="op">,</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_configuration</span><span class="op">[</span><span class="str">'sim_name'</span><span class="op">]</span><span class="op">)</span> <span class="op">+</span> <span class="nam">str</span><span class="op">(</span><span class="nam">date_string</span><span class="op">)</span> <span class="op">+</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t257" class="pln"> <span class="str">'.h5'</span><span class="strut"> </span></p> -<p id="t258" class="pln"><span class="strut"> </span></p> -<p id="t259" class="pln"> <span class="com"># Save simulation results</span><span class="strut"> </span></p> -<p id="t260" class="stm mis"> <span class="key">with</span> <span class="nam">h5py</span><span class="op">.</span><span class="nam">File</span><span class="op">(</span><span class="nam">file_path</span><span class="op">,</span> <span class="str">'w'</span><span class="op">)</span> <span class="key">as</span> <span class="nam">f</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t261" class="stm mis"> <span class="nam">f</span><span class="op">.</span><span class="nam">create_dataset</span><span class="op">(</span><span class="str">'simclock'</span><span class="op">,</span> <span class="nam">data</span><span class="op">=</span><span class="nam">self</span><span class="op">.</span><span class="nam">_simclock</span><span class="op">.</span><span class="nam">time_array</span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t262" class="stm mis"> <span class="nam">f</span><span class="op">.</span><span class="nam">create_dataset</span><span class="op">(</span><span class="str">'positions'</span><span class="op">,</span> <span class="nam">data</span><span class="op">=</span><span class="nam">self</span><span class="op">.</span><span class="nam">_positions</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t263" class="stm mis"> <span class="nam">f</span><span class="op">.</span><span class="nam">create_dataset</span><span class="op">(</span><span class="str">'configuration'</span><span class="op">,</span> <span class="nam">data</span><span class="op">=</span><span class="nam">str</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_configuration</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t264" class="pln"><span class="strut"> </span></p> -<p id="t265" class="pln"><span class="strut"> </span></p> -<p id="t266" class="stm run hide_run"><span class="key">def</span> <span class="nam">input_dict_validator</span><span class="op">(</span><span class="nam">d</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t267" class="pln"> <span class="str">"""Validates a list of simulation inputs and runs the simlation if inputs</span><span class="strut"> </span></p> -<p id="t268" class="pln"><span class="str"> are valid</span><span class="strut"> </span></p> -<p id="t269" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t270" class="pln"><span class="strut"> </span></p> -<p id="t271" class="pln"> <span class="com"># Hydraulic Input Mode</span><span class="strut"> </span></p> -<p id="t272" class="stm mis"> <span class="key">if</span> <span class="key">not</span> <span class="nam">d</span><span class="op">[</span><span class="str">'hydraulic_mode'</span><span class="op">]</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t273" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="str">'hydraulic_mode must be type str'</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t274" class="pln"> <span class="com"># CSV path</span><span class="strut"> </span></p> -<p id="t275" class="stm mis"> <span class="key">if</span> <span class="key">not</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">d</span><span class="op">[</span><span class="str">'csv_path'</span><span class="op">]</span><span class="op">,</span> <span class="nam">str</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t276" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="str">'csv_path must be type str'</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t277" class="pln"> <span class="com"># Hecras path</span><span class="strut"> </span></p> -<p id="t278" class="stm mis"> <span class="key">if</span> <span class="key">not</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">d</span><span class="op">[</span><span class="str">'hecras_path'</span><span class="op">]</span><span class="op">,</span> <span class="nam">str</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t279" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="str">'hecras_path must be type str'</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t280" class="pln"> <span class="com"># Diffusivity</span><span class="strut"> </span></p> -<p id="t281" class="stm mis"> <span class="key">if</span> <span class="op">(</span><span class="nam">d</span><span class="op">[</span><span class="str">'diffusivity'</span><span class="op">]</span> <span class="op">!=</span> <span class="str">'parabolic'</span><span class="op">)</span> <span class="key">and</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t282" class="pln"> <span class="op">(</span><span class="nam">d</span><span class="op">[</span><span class="str">'diffusivity'</span><span class="op">]</span> <span class="op">!=</span> <span class="str">'constant'</span><span class="op">)</span> <span class="key">and</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t283" class="pln"> <span class="op">(</span><span class="nam">d</span><span class="op">[</span><span class="str">'diffusivity'</span><span class="op">]</span> <span class="op">!=</span> <span class="str">'parabolic-constant'</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t284" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="strut"> </span></p> -<p id="t285" class="pln"> <span class="str">'diffusivity must be parabolic, constant, or parabolic-constant'</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t286" class="pln"> <span class="com"># XYZ Position</span><span class="strut"> </span></p> -<p id="t287" class="stm mis"> <span class="key">if</span> <span class="op">(</span><span class="key">not</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">d</span><span class="op">[</span><span class="str">'x'</span><span class="op">]</span><span class="op">,</span> <span class="nam">float</span><span class="op">)</span><span class="op">)</span> <span class="key">and</span> <span class="op">(</span><span class="key">not</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">d</span><span class="op">[</span><span class="str">'x'</span><span class="op">]</span><span class="op">,</span> <span class="nam">int</span><span class="op">)</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t288" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="str">'x must be type float or int'</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t289" class="stm mis"> <span class="key">if</span> <span class="op">(</span><span class="key">not</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">d</span><span class="op">[</span><span class="str">'y'</span><span class="op">]</span><span class="op">,</span> <span class="nam">float</span><span class="op">)</span><span class="op">)</span> <span class="key">and</span> <span class="op">(</span><span class="key">not</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">d</span><span class="op">[</span><span class="str">'y'</span><span class="op">]</span><span class="op">,</span> <span class="nam">int</span><span class="op">)</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t290" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="str">'y must be type float or int'</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t291" class="stm mis"> <span class="key">if</span> <span class="op">(</span><span class="key">not</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">d</span><span class="op">[</span><span class="str">'z'</span><span class="op">]</span><span class="op">,</span> <span class="nam">float</span><span class="op">)</span><span class="op">)</span> <span class="key">and</span> <span class="op">(</span><span class="key">not</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">d</span><span class="op">[</span><span class="str">'z'</span><span class="op">]</span><span class="op">,</span> <span class="nam">int</span><span class="op">)</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t292" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="str">'z must be type float or int'</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t293" class="pln"> <span class="com"># Number of eggs</span><span class="strut"> </span></p> -<p id="t294" class="stm mis"> <span class="key">if</span> <span class="key">not</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">d</span><span class="op">[</span><span class="str">'num_eggs'</span><span class="op">]</span><span class="op">,</span> <span class="nam">int</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t295" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="str">'num_eggs must be type int'</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t296" class="pln"> <span class="com"># Species</span><span class="strut"> </span></p> -<p id="t297" class="stm mis"> <span class="key">if</span> <span class="op">(</span><span class="nam">d</span><span class="op">[</span><span class="str">'species'</span><span class="op">]</span> <span class="op">!=</span> <span class="str">'grass'</span><span class="op">)</span> <span class="key">and</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t298" class="pln"> <span class="op">(</span><span class="nam">d</span><span class="op">[</span><span class="str">'species'</span><span class="op">]</span> <span class="op">!=</span> <span class="str">'silver'</span><span class="op">)</span> <span class="key">and</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t299" class="pln"> <span class="op">(</span><span class="nam">d</span><span class="op">[</span><span class="str">'species'</span><span class="op">]</span> <span class="op">!=</span> <span class="str">'bighead'</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t300" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="str">'species must be grass, silver, or bighead'</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t301" class="pln"> <span class="com"># Varying density & diameter</span><span class="strut"> </span></p> -<p id="t302" class="stm mis"> <span class="key">if</span> <span class="op">(</span><span class="nam">d</span><span class="op">[</span><span class="str">'varying_dd'</span><span class="op">]</span> <span class="op">!=</span> <span class="str">'constant'</span><span class="op">)</span> <span class="key">and</span> <span class="op">(</span><span class="nam">d</span><span class="op">[</span><span class="str">'varying_dd'</span><span class="op">]</span> <span class="op">!=</span> <span class="str">'varying'</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t303" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="str">'varying_dd must be constant or varying.'</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t304" class="pln"> <span class="com"># Direction of simulation</span><span class="strut"> </span></p> -<p id="t305" class="stm mis"> <span class="key">if</span> <span class="op">(</span><span class="nam">d</span><span class="op">[</span><span class="str">'direction'</span><span class="op">]</span> <span class="op">!=</span> <span class="str">'forward'</span><span class="op">)</span> <span class="key">and</span> <span class="op">(</span><span class="nam">d</span><span class="op">[</span><span class="str">'direction'</span><span class="op">]</span> <span class="op">!=</span> <span class="str">'reverse'</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t306" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="str">'direction must be forward or reverse.'</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t307" class="pln"> <span class="com"># Duration</span><span class="strut"> </span></p> -<p id="t308" class="stm mis"> <span class="key">if</span> <span class="op">(</span><span class="key">not</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">d</span><span class="op">[</span><span class="str">'duration'</span><span class="op">]</span><span class="op">,</span> <span class="nam">float</span><span class="op">)</span><span class="op">)</span> <span class="key">and</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t309" class="pln"> <span class="op">(</span><span class="key">not</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">d</span><span class="op">[</span><span class="str">'duration'</span><span class="op">]</span><span class="op">,</span> <span class="nam">int</span><span class="op">)</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t310" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="str">'duration must be type float or int'</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t311" class="pln"> <span class="com"># Time step</span><span class="strut"> </span></p> -<p id="t312" class="stm mis"> <span class="key">if</span> <span class="op">(</span><span class="key">not</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">d</span><span class="op">[</span><span class="str">'time_step'</span><span class="op">]</span><span class="op">,</span> <span class="nam">float</span><span class="op">)</span><span class="op">)</span> <span class="key">and</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t313" class="pln"> <span class="op">(</span><span class="key">not</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">d</span><span class="op">[</span><span class="str">'time_step'</span><span class="op">]</span><span class="op">,</span> <span class="nam">int</span><span class="op">)</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t314" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="str">'time_step must be type float or int'</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t315" class="pln"> <span class="com"># Simulation name</span><span class="strut"> </span></p> -<p id="t316" class="stm mis"> <span class="key">if</span> <span class="key">not</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">d</span><span class="op">[</span><span class="str">'sim_name'</span><span class="op">]</span><span class="op">,</span> <span class="nam">str</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t317" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="str">'sim_name must be type str'</span><span class="op">)</span><span class="strut"> </span></p> - - </td> - </tr> - </table> -</div> - -<div id="footer"> - <div class="content"> - <p> - <a class="nav" href="index.html">« index</a> <a class="nav" href="https://coverage.readthedocs.io">coverage.py v4.5.3</a>, - created at 2019-07-09 15:15 - </p> - </div> -</div> - -</body> -</html> diff --git a/coverage_report/fluegg_transporter_py.html b/coverage_report/fluegg_transporter_py.html deleted file mode 100644 index 85a1edf..0000000 --- a/coverage_report/fluegg_transporter_py.html +++ /dev/null @@ -1,1809 +0,0 @@ - - - -<!DOCTYPE html> -<html> -<head> - <meta http-equiv="Content-Type" content="text/html; charset=utf-8"> - - - <meta http-equiv="X-UA-Compatible" content="IE=emulateIE7" /> - <title>Coverage for fluegg\transporter.py: 80%</title> - <link rel="stylesheet" href="style.css" type="text/css"> - - <script type="text/javascript" src="jquery.min.js"></script> - <script type="text/javascript" src="jquery.hotkeys.js"></script> - <script type="text/javascript" src="jquery.isonscreen.js"></script> - <script type="text/javascript" src="coverage_html.js"></script> - <script type="text/javascript"> - jQuery(document).ready(coverage.pyfile_ready); - </script> -</head> -<body class="pyfile"> - -<div id="header"> - <div class="content"> - <h1>Coverage for <b>fluegg\transporter.py</b> : - <span class="pc_cov">80%</span> - </h1> - - <img id="keyboard_icon" src="keybd_closed.png" alt="Show keyboard shortcuts" /> - - <h2 class="stats"> - 285 statements - <span class="run hide_run shortkey_r button_toggle_run">229 run</span> - <span class="mis shortkey_m button_toggle_mis">56 missing</span> - <span class="exc shortkey_x button_toggle_exc">0 excluded</span> - - - </h2> - </div> -</div> - -<div class="help_panel"> - <img id="panel_icon" src="keybd_open.png" alt="Hide keyboard shortcuts" /> - <p class="legend">Hot-keys on this page</p> - <div> - <p class="keyhelp"> - <span class="key">r</span> - <span class="key">m</span> - <span class="key">x</span> - 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class="pln"><a href="#n256">256</a></p> -<p id="n257" class="pln"><a href="#n257">257</a></p> -<p id="n258" class="pln"><a href="#n258">258</a></p> -<p id="n259" class="pln"><a href="#n259">259</a></p> -<p id="n260" class="stm mis"><a href="#n260">260</a></p> -<p id="n261" class="stm mis"><a href="#n261">261</a></p> -<p id="n262" class="stm mis"><a href="#n262">262</a></p> -<p id="n263" class="stm mis"><a href="#n263">263</a></p> -<p id="n264" class="stm mis"><a href="#n264">264</a></p> -<p id="n265" class="stm mis"><a href="#n265">265</a></p> -<p id="n266" class="stm mis"><a href="#n266">266</a></p> -<p id="n267" class="stm mis"><a href="#n267">267</a></p> -<p id="n268" class="pln"><a href="#n268">268</a></p> -<p id="n269" class="pln"><a href="#n269">269</a></p> -<p id="n270" class="pln"><a href="#n270">270</a></p> -<p id="n271" class="stm mis"><a href="#n271">271</a></p> -<p id="n272" class="pln"><a href="#n272">272</a></p> -<p id="n273" class="pln"><a href="#n273">273</a></p> -<p id="n274" class="stm mis"><a href="#n274">274</a></p> -<p id="n275" class="pln"><a href="#n275">275</a></p> -<p id="n276" class="pln"><a href="#n276">276</a></p> -<p id="n277" class="pln"><a href="#n277">277</a></p> -<p id="n278" class="stm mis"><a href="#n278">278</a></p> -<p id="n279" class="pln"><a href="#n279">279</a></p> -<p id="n280" class="pln"><a href="#n280">280</a></p> -<p id="n281" class="stm run hide_run"><a href="#n281">281</a></p> -<p id="n282" class="pln"><a href="#n282">282</a></p> -<p id="n283" class="stm run hide_run"><a href="#n283">283</a></p> -<p id="n284" class="pln"><a href="#n284">284</a></p> -<p id="n285" class="pln"><a href="#n285">285</a></p> -<p id="n286" class="pln"><a href="#n286">286</a></p> -<p id="n287" class="pln"><a href="#n287">287</a></p> -<p id="n288" class="pln"><a href="#n288">288</a></p> -<p id="n289" class="pln"><a href="#n289">289</a></p> -<p id="n290" class="pln"><a href="#n290">290</a></p> -<p id="n291" class="pln"><a href="#n291">291</a></p> -<p id="n292" class="pln"><a href="#n292">292</a></p> -<p id="n293" class="pln"><a href="#n293">293</a></p> -<p id="n294" class="pln"><a href="#n294">294</a></p> -<p id="n295" class="pln"><a href="#n295">295</a></p> -<p id="n296" class="pln"><a href="#n296">296</a></p> -<p id="n297" class="pln"><a href="#n297">297</a></p> -<p id="n298" class="pln"><a href="#n298">298</a></p> -<p id="n299" class="stm run hide_run"><a href="#n299">299</a></p> -<p id="n300" class="pln"><a href="#n300">300</a></p> -<p id="n301" class="stm run hide_run"><a href="#n301">301</a></p> -<p id="n302" class="pln"><a href="#n302">302</a></p> -<p id="n303" class="stm run hide_run"><a href="#n303">303</a></p> -<p id="n304" class="pln"><a href="#n304">304</a></p> -<p id="n305" class="stm run hide_run"><a href="#n305">305</a></p> -<p id="n306" class="stm run hide_run"><a href="#n306">306</a></p> -<p id="n307" class="pln"><a href="#n307">307</a></p> -<p id="n308" class="stm run hide_run"><a href="#n308">308</a></p> -<p id="n309" class="stm run hide_run"><a href="#n309">309</a></p> -<p id="n310" class="pln"><a href="#n310">310</a></p> -<p id="n311" class="stm run hide_run"><a href="#n311">311</a></p> -<p id="n312" class="pln"><a href="#n312">312</a></p> -<p id="n313" class="stm run hide_run"><a href="#n313">313</a></p> -<p id="n314" class="pln"><a href="#n314">314</a></p> -<p id="n315" class="stm run hide_run"><a href="#n315">315</a></p> -<p id="n316" class="pln"><a href="#n316">316</a></p> -<p id="n317" class="stm run hide_run"><a href="#n317">317</a></p> -<p id="n318" class="pln"><a href="#n318">318</a></p> -<p id="n319" class="pln"><a href="#n319">319</a></p> -<p id="n320" class="stm run hide_run"><a href="#n320">320</a></p> -<p id="n321" class="stm run hide_run"><a href="#n321">321</a></p> -<p id="n322" class="stm run hide_run"><a href="#n322">322</a></p> -<p id="n323" class="pln"><a href="#n323">323</a></p> -<p id="n324" class="stm run hide_run"><a href="#n324">324</a></p> -<p id="n325" class="pln"><a href="#n325">325</a></p> -<p id="n326" class="stm run hide_run"><a href="#n326">326</a></p> -<p id="n327" class="pln"><a href="#n327">327</a></p> -<p id="n328" class="pln"><a href="#n328">328</a></p> -<p id="n329" class="stm run hide_run"><a href="#n329">329</a></p> -<p id="n330" class="pln"><a href="#n330">330</a></p> -<p id="n331" class="pln"><a href="#n331">331</a></p> -<p id="n332" class="stm run hide_run"><a href="#n332">332</a></p> -<p id="n333" class="pln"><a href="#n333">333</a></p> -<p id="n334" class="stm run hide_run"><a href="#n334">334</a></p> -<p id="n335" class="pln"><a href="#n335">335</a></p> -<p id="n336" class="pln"><a href="#n336">336</a></p> -<p id="n337" class="pln"><a href="#n337">337</a></p> -<p id="n338" class="pln"><a href="#n338">338</a></p> -<p id="n339" class="pln"><a href="#n339">339</a></p> -<p id="n340" class="pln"><a href="#n340">340</a></p> -<p id="n341" class="pln"><a href="#n341">341</a></p> -<p id="n342" class="pln"><a href="#n342">342</a></p> -<p id="n343" class="pln"><a href="#n343">343</a></p> -<p id="n344" class="pln"><a href="#n344">344</a></p> -<p id="n345" class="pln"><a href="#n345">345</a></p> -<p id="n346" class="pln"><a href="#n346">346</a></p> -<p id="n347" class="pln"><a href="#n347">347</a></p> -<p id="n348" class="stm run hide_run"><a href="#n348">348</a></p> -<p id="n349" class="stm run hide_run"><a href="#n349">349</a></p> -<p id="n350" class="pln"><a href="#n350">350</a></p> -<p id="n351" class="pln"><a href="#n351">351</a></p> -<p id="n352" class="stm run hide_run"><a href="#n352">352</a></p> -<p id="n353" class="stm run hide_run"><a href="#n353">353</a></p> -<p id="n354" class="pln"><a href="#n354">354</a></p> -<p id="n355" class="stm run hide_run"><a href="#n355">355</a></p> -<p id="n356" class="pln"><a href="#n356">356</a></p> -<p id="n357" class="stm run hide_run"><a href="#n357">357</a></p> -<p id="n358" class="pln"><a href="#n358">358</a></p> -<p id="n359" class="pln"><a href="#n359">359</a></p> -<p id="n360" class="pln"><a href="#n360">360</a></p> -<p id="n361" class="pln"><a href="#n361">361</a></p> -<p id="n362" class="pln"><a href="#n362">362</a></p> -<p id="n363" class="pln"><a href="#n363">363</a></p> -<p id="n364" class="pln"><a href="#n364">364</a></p> -<p id="n365" class="pln"><a href="#n365">365</a></p> -<p id="n366" class="pln"><a href="#n366">366</a></p> -<p id="n367" class="pln"><a href="#n367">367</a></p> -<p id="n368" class="stm run hide_run"><a href="#n368">368</a></p> -<p id="n369" class="stm run hide_run"><a href="#n369">369</a></p> -<p id="n370" class="stm run hide_run"><a href="#n370">370</a></p> -<p id="n371" class="pln"><a href="#n371">371</a></p> -<p id="n372" class="pln"><a href="#n372">372</a></p> -<p id="n373" class="stm run hide_run"><a href="#n373">373</a></p> -<p id="n374" class="pln"><a href="#n374">374</a></p> -<p id="n375" class="stm run hide_run"><a href="#n375">375</a></p> -<p id="n376" class="pln"><a href="#n376">376</a></p> -<p id="n377" class="pln"><a href="#n377">377</a></p> -<p id="n378" class="pln"><a href="#n378">378</a></p> -<p id="n379" class="pln"><a href="#n379">379</a></p> -<p id="n380" class="pln"><a href="#n380">380</a></p> -<p id="n381" class="pln"><a href="#n381">381</a></p> -<p id="n382" class="stm mis"><a href="#n382">382</a></p> -<p id="n383" class="pln"><a href="#n383">383</a></p> -<p id="n384" class="stm run hide_run"><a href="#n384">384</a></p> -<p id="n385" class="pln"><a href="#n385">385</a></p> -<p id="n386" class="pln"><a href="#n386">386</a></p> -<p id="n387" class="pln"><a href="#n387">387</a></p> -<p id="n388" class="pln"><a href="#n388">388</a></p> -<p id="n389" class="pln"><a href="#n389">389</a></p> -<p id="n390" class="pln"><a href="#n390">390</a></p> -<p id="n391" class="stm mis"><a href="#n391">391</a></p> -<p id="n392" class="pln"><a href="#n392">392</a></p> -<p id="n393" class="stm run hide_run"><a href="#n393">393</a></p> -<p id="n394" class="pln"><a href="#n394">394</a></p> -<p id="n395" class="pln"><a href="#n395">395</a></p> -<p id="n396" class="pln"><a href="#n396">396</a></p> -<p id="n397" class="pln"><a href="#n397">397</a></p> -<p id="n398" class="pln"><a href="#n398">398</a></p> -<p id="n399" class="pln"><a href="#n399">399</a></p> -<p id="n400" class="stm mis"><a href="#n400">400</a></p> -<p id="n401" class="pln"><a href="#n401">401</a></p> -<p id="n402" class="stm run hide_run"><a href="#n402">402</a></p> -<p id="n403" class="pln"><a href="#n403">403</a></p> -<p id="n404" class="pln"><a href="#n404">404</a></p> -<p id="n405" class="pln"><a href="#n405">405</a></p> -<p id="n406" class="pln"><a href="#n406">406</a></p> -<p id="n407" class="pln"><a href="#n407">407</a></p> -<p id="n408" class="pln"><a href="#n408">408</a></p> -<p id="n409" class="pln"><a href="#n409">409</a></p> -<p id="n410" class="pln"><a href="#n410">410</a></p> -<p id="n411" class="pln"><a href="#n411">411</a></p> -<p id="n412" class="pln"><a href="#n412">412</a></p> -<p id="n413" class="pln"><a href="#n413">413</a></p> -<p id="n414" class="stm run hide_run"><a href="#n414">414</a></p> -<p id="n415" class="stm run hide_run"><a href="#n415">415</a></p> -<p id="n416" class="stm run hide_run"><a href="#n416">416</a></p> -<p id="n417" class="stm run hide_run"><a href="#n417">417</a></p> -<p id="n418" class="stm run hide_run"><a href="#n418">418</a></p> -<p id="n419" class="pln"><a href="#n419">419</a></p> -<p id="n420" class="stm run hide_run"><a href="#n420">420</a></p> -<p id="n421" class="pln"><a href="#n421">421</a></p> -<p id="n422" class="stm run hide_run"><a href="#n422">422</a></p> -<p id="n423" class="stm mis"><a href="#n423">423</a></p> -<p id="n424" class="pln"><a href="#n424">424</a></p> -<p id="n425" class="pln"><a href="#n425">425</a></p> -<p id="n426" class="pln"><a href="#n426">426</a></p> -<p id="n427" class="stm run hide_run"><a href="#n427">427</a></p> -<p id="n428" class="pln"><a href="#n428">428</a></p> -<p id="n429" class="stm run hide_run"><a href="#n429">429</a></p> -<p id="n430" class="pln"><a href="#n430">430</a></p> -<p id="n431" class="stm run hide_run"><a href="#n431">431</a></p> -<p id="n432" class="pln"><a href="#n432">432</a></p> -<p id="n433" class="stm run hide_run"><a href="#n433">433</a></p> -<p id="n434" class="pln"><a href="#n434">434</a></p> -<p id="n435" class="pln"><a href="#n435">435</a></p> -<p id="n436" class="stm run hide_run"><a href="#n436">436</a></p> -<p id="n437" class="pln"><a href="#n437">437</a></p> -<p id="n438" class="pln"><a href="#n438">438</a></p> -<p id="n439" class="stm run hide_run"><a href="#n439">439</a></p> -<p id="n440" class="pln"><a href="#n440">440</a></p> -<p id="n441" class="pln"><a href="#n441">441</a></p> -<p id="n442" class="pln"><a href="#n442">442</a></p> -<p id="n443" class="pln"><a href="#n443">443</a></p> -<p id="n444" class="pln"><a href="#n444">444</a></p> -<p id="n445" class="pln"><a href="#n445">445</a></p> -<p id="n446" class="stm run hide_run"><a href="#n446">446</a></p> -<p id="n447" class="pln"><a href="#n447">447</a></p> -<p id="n448" class="stm run hide_run"><a href="#n448">448</a></p> -<p id="n449" class="pln"><a href="#n449">449</a></p> -<p id="n450" class="pln"><a href="#n450">450</a></p> -<p id="n451" class="pln"><a href="#n451">451</a></p> -<p id="n452" class="pln"><a href="#n452">452</a></p> -<p id="n453" class="pln"><a href="#n453">453</a></p> -<p id="n454" class="pln"><a href="#n454">454</a></p> -<p id="n455" class="pln"><a href="#n455">455</a></p> -<p id="n456" class="pln"><a href="#n456">456</a></p> -<p id="n457" class="pln"><a href="#n457">457</a></p> -<p id="n458" class="pln"><a href="#n458">458</a></p> -<p id="n459" class="pln"><a href="#n459">459</a></p> -<p id="n460" class="pln"><a href="#n460">460</a></p> -<p id="n461" class="pln"><a href="#n461">461</a></p> -<p id="n462" class="pln"><a href="#n462">462</a></p> -<p id="n463" class="stm run hide_run"><a href="#n463">463</a></p> -<p id="n464" class="pln"><a href="#n464">464</a></p> -<p id="n465" class="pln"><a href="#n465">465</a></p> -<p id="n466" class="stm run hide_run"><a href="#n466">466</a></p> -<p id="n467" class="pln"><a href="#n467">467</a></p> -<p id="n468" class="pln"><a href="#n468">468</a></p> -<p id="n469" class="pln"><a href="#n469">469</a></p> -<p id="n470" class="stm run hide_run"><a href="#n470">470</a></p> -<p id="n471" class="pln"><a href="#n471">471</a></p> -<p id="n472" class="stm run hide_run"><a href="#n472">472</a></p> -<p id="n473" class="pln"><a href="#n473">473</a></p> -<p id="n474" class="stm run hide_run"><a href="#n474">474</a></p> -<p id="n475" class="pln"><a href="#n475">475</a></p> -<p id="n476" class="stm run hide_run"><a href="#n476">476</a></p> -<p id="n477" class="pln"><a href="#n477">477</a></p> -<p id="n478" class="pln"><a href="#n478">478</a></p> -<p id="n479" class="pln"><a href="#n479">479</a></p> -<p id="n480" class="pln"><a href="#n480">480</a></p> -<p id="n481" class="pln"><a href="#n481">481</a></p> -<p id="n482" class="pln"><a href="#n482">482</a></p> -<p id="n483" class="pln"><a href="#n483">483</a></p> -<p id="n484" class="pln"><a href="#n484">484</a></p> -<p id="n485" class="stm run hide_run"><a href="#n485">485</a></p> -<p id="n486" class="pln"><a href="#n486">486</a></p> -<p id="n487" class="stm run hide_run"><a href="#n487">487</a></p> -<p id="n488" class="pln"><a href="#n488">488</a></p> -<p id="n489" class="stm run hide_run"><a href="#n489">489</a></p> -<p id="n490" class="pln"><a href="#n490">490</a></p> -<p id="n491" class="stm run hide_run"><a href="#n491">491</a></p> -<p id="n492" class="pln"><a href="#n492">492</a></p> -<p id="n493" class="pln"><a href="#n493">493</a></p> -<p id="n494" class="pln"><a href="#n494">494</a></p> -<p id="n495" class="stm run hide_run"><a href="#n495">495</a></p> -<p id="n496" class="stm run hide_run"><a href="#n496">496</a></p> -<p id="n497" class="stm mis"><a href="#n497">497</a></p> -<p id="n498" class="stm mis"><a href="#n498">498</a></p> -<p id="n499" class="stm mis"><a href="#n499">499</a></p> -<p id="n500" class="pln"><a href="#n500">500</a></p> -<p id="n501" class="stm run hide_run"><a href="#n501">501</a></p> -<p id="n502" class="pln"><a href="#n502">502</a></p> -<p id="n503" class="stm run hide_run"><a href="#n503">503</a></p> -<p id="n504" class="pln"><a href="#n504">504</a></p> -<p id="n505" class="pln"><a href="#n505">505</a></p> -<p id="n506" class="stm run hide_run"><a href="#n506">506</a></p> -<p id="n507" class="pln"><a href="#n507">507</a></p> -<p id="n508" class="stm run hide_run"><a href="#n508">508</a></p> -<p id="n509" class="pln"><a href="#n509">509</a></p> -<p id="n510" class="pln"><a href="#n510">510</a></p> -<p id="n511" class="pln"><a href="#n511">511</a></p> -<p id="n512" class="pln"><a href="#n512">512</a></p> -<p id="n513" class="pln"><a href="#n513">513</a></p> -<p id="n514" class="pln"><a href="#n514">514</a></p> -<p id="n515" class="pln"><a href="#n515">515</a></p> -<p id="n516" class="pln"><a href="#n516">516</a></p> -<p id="n517" class="pln"><a href="#n517">517</a></p> -<p id="n518" class="stm run hide_run"><a href="#n518">518</a></p> -<p id="n519" class="stm run hide_run"><a href="#n519">519</a></p> -<p id="n520" class="pln"><a href="#n520">520</a></p> -<p id="n521" class="pln"><a href="#n521">521</a></p> -<p id="n522" class="stm run hide_run"><a href="#n522">522</a></p> -<p id="n523" class="pln"><a href="#n523">523</a></p> -<p id="n524" class="pln"><a href="#n524">524</a></p> -<p id="n525" class="pln"><a href="#n525">525</a></p> -<p id="n526" class="stm run hide_run"><a href="#n526">526</a></p> -<p id="n527" class="stm run hide_run"><a href="#n527">527</a></p> -<p id="n528" class="stm run hide_run"><a href="#n528">528</a></p> -<p id="n529" class="pln"><a href="#n529">529</a></p> -<p id="n530" class="pln"><a href="#n530">530</a></p> -<p id="n531" class="stm run hide_run"><a href="#n531">531</a></p> -<p id="n532" class="pln"><a href="#n532">532</a></p> -<p id="n533" class="stm run hide_run"><a href="#n533">533</a></p> -<p id="n534" class="pln"><a href="#n534">534</a></p> -<p id="n535" class="pln"><a href="#n535">535</a></p> -<p id="n536" class="pln"><a href="#n536">536</a></p> -<p id="n537" class="pln"><a href="#n537">537</a></p> -<p id="n538" class="pln"><a href="#n538">538</a></p> -<p id="n539" class="pln"><a href="#n539">539</a></p> -<p id="n540" class="pln"><a href="#n540">540</a></p> -<p id="n541" class="pln"><a href="#n541">541</a></p> -<p id="n542" class="pln"><a href="#n542">542</a></p> -<p id="n543" class="pln"><a href="#n543">543</a></p> -<p id="n544" class="stm run hide_run"><a href="#n544">544</a></p> -<p id="n545" class="stm run hide_run"><a href="#n545">545</a></p> -<p id="n546" class="pln"><a href="#n546">546</a></p> -<p id="n547" class="stm run hide_run"><a href="#n547">547</a></p> -<p id="n548" class="pln"><a href="#n548">548</a></p> -<p id="n549" class="stm run hide_run"><a href="#n549">549</a></p> -<p id="n550" class="pln"><a href="#n550">550</a></p> -<p id="n551" class="stm run hide_run"><a href="#n551">551</a></p> -<p id="n552" class="pln"><a href="#n552">552</a></p> -<p id="n553" class="pln"><a href="#n553">553</a></p> -<p id="n554" class="pln"><a href="#n554">554</a></p> -<p id="n555" class="pln"><a href="#n555">555</a></p> -<p id="n556" class="pln"><a href="#n556">556</a></p> -<p id="n557" class="pln"><a href="#n557">557</a></p> -<p id="n558" class="pln"><a href="#n558">558</a></p> -<p id="n559" class="pln"><a href="#n559">559</a></p> -<p id="n560" class="pln"><a href="#n560">560</a></p> -<p id="n561" class="pln"><a href="#n561">561</a></p> -<p id="n562" class="pln"><a href="#n562">562</a></p> -<p id="n563" class="stm run hide_run"><a href="#n563">563</a></p> -<p id="n564" class="stm run hide_run"><a href="#n564">564</a></p> -<p id="n565" class="pln"><a href="#n565">565</a></p> -<p id="n566" class="stm run hide_run"><a href="#n566">566</a></p> -<p id="n567" class="pln"><a href="#n567">567</a></p> -<p id="n568" class="stm run hide_run"><a href="#n568">568</a></p> -<p id="n569" class="pln"><a href="#n569">569</a></p> -<p id="n570" class="pln"><a href="#n570">570</a></p> -<p id="n571" class="stm run hide_run"><a href="#n571">571</a></p> -<p id="n572" class="pln"><a href="#n572">572</a></p> -<p id="n573" class="stm run hide_run"><a href="#n573">573</a></p> -<p id="n574" class="pln"><a href="#n574">574</a></p> -<p id="n575" class="pln"><a href="#n575">575</a></p> -<p id="n576" class="pln"><a href="#n576">576</a></p> -<p id="n577" class="pln"><a href="#n577">577</a></p> -<p id="n578" class="pln"><a href="#n578">578</a></p> -<p id="n579" class="pln"><a href="#n579">579</a></p> -<p id="n580" class="pln"><a href="#n580">580</a></p> -<p id="n581" class="pln"><a href="#n581">581</a></p> -<p id="n582" class="pln"><a href="#n582">582</a></p> -<p id="n583" class="stm mis"><a href="#n583">583</a></p> -<p id="n584" class="stm mis"><a href="#n584">584</a></p> -<p id="n585" class="stm mis"><a href="#n585">585</a></p> -<p id="n586" class="stm mis"><a href="#n586">586</a></p> -<p id="n587" class="pln"><a href="#n587">587</a></p> -<p id="n588" class="stm mis"><a href="#n588">588</a></p> -<p id="n589" class="pln"><a href="#n589">589</a></p> -<p id="n590" class="pln"><a href="#n590">590</a></p> -<p id="n591" class="stm mis"><a href="#n591">591</a></p> -<p id="n592" class="stm mis"><a href="#n592">592</a></p> -<p id="n593" class="pln"><a href="#n593">593</a></p> -<p id="n594" class="pln"><a href="#n594">594</a></p> -<p id="n595" class="stm mis"><a href="#n595">595</a></p> -<p id="n596" class="stm mis"><a href="#n596">596</a></p> -<p id="n597" class="stm mis"><a href="#n597">597</a></p> -<p id="n598" class="pln"><a href="#n598">598</a></p> -<p id="n599" class="pln"><a href="#n599">599</a></p> -<p id="n600" class="pln"><a href="#n600">600</a></p> -<p id="n601" class="pln"><a href="#n601">601</a></p> -<p id="n602" class="stm mis"><a href="#n602">602</a></p> -<p id="n603" class="stm mis"><a href="#n603">603</a></p> -<p id="n604" class="stm mis"><a href="#n604">604</a></p> -<p id="n605" class="pln"><a href="#n605">605</a></p> -<p id="n606" class="pln"><a href="#n606">606</a></p> -<p id="n607" class="stm mis"><a href="#n607">607</a></p> -<p id="n608" class="pln"><a href="#n608">608</a></p> -<p id="n609" class="stm run hide_run"><a href="#n609">609</a></p> -<p id="n610" class="pln"><a href="#n610">610</a></p> -<p id="n611" class="pln"><a href="#n611">611</a></p> -<p id="n612" class="pln"><a href="#n612">612</a></p> -<p id="n613" class="pln"><a href="#n613">613</a></p> -<p id="n614" class="pln"><a href="#n614">614</a></p> -<p id="n615" class="pln"><a href="#n615">615</a></p> -<p id="n616" class="pln"><a href="#n616">616</a></p> -<p id="n617" class="pln"><a href="#n617">617</a></p> -<p id="n618" class="pln"><a href="#n618">618</a></p> -<p id="n619" class="pln"><a href="#n619">619</a></p> -<p id="n620" class="stm mis"><a href="#n620">620</a></p> -<p id="n621" class="stm mis"><a href="#n621">621</a></p> -<p id="n622" class="stm mis"><a href="#n622">622</a></p> -<p id="n623" class="stm mis"><a href="#n623">623</a></p> -<p id="n624" class="pln"><a href="#n624">624</a></p> -<p id="n625" class="stm mis"><a href="#n625">625</a></p> -<p id="n626" class="pln"><a href="#n626">626</a></p> -<p id="n627" class="stm mis"><a href="#n627">627</a></p> -<p id="n628" class="pln"><a href="#n628">628</a></p> -<p id="n629" class="pln"><a href="#n629">629</a></p> -<p id="n630" class="stm mis"><a href="#n630">630</a></p> -<p id="n631" class="pln"><a href="#n631">631</a></p> -<p id="n632" class="stm run hide_run"><a href="#n632">632</a></p> -<p id="n633" class="pln"><a href="#n633">633</a></p> -<p id="n634" class="pln"><a href="#n634">634</a></p> -<p id="n635" class="pln"><a href="#n635">635</a></p> -<p id="n636" class="pln"><a href="#n636">636</a></p> -<p id="n637" class="pln"><a href="#n637">637</a></p> -<p id="n638" class="pln"><a href="#n638">638</a></p> -<p id="n639" class="pln"><a href="#n639">639</a></p> -<p id="n640" class="pln"><a href="#n640">640</a></p> -<p id="n641" class="pln"><a href="#n641">641</a></p> -<p id="n642" class="pln"><a href="#n642">642</a></p> -<p id="n643" class="pln"><a href="#n643">643</a></p> -<p id="n644" class="stm mis"><a href="#n644">644</a></p> -<p id="n645" class="stm mis"><a href="#n645">645</a></p> -<p id="n646" class="pln"><a href="#n646">646</a></p> -<p id="n647" class="stm mis"><a href="#n647">647</a></p> -<p id="n648" class="pln"><a href="#n648">648</a></p> -<p id="n649" class="pln"><a href="#n649">649</a></p> -<p id="n650" class="stm mis"><a href="#n650">650</a></p> -<p id="n651" class="pln"><a href="#n651">651</a></p> -<p id="n652" class="pln"><a href="#n652">652</a></p> -<p id="n653" class="stm run hide_run"><a href="#n653">653</a></p> -<p id="n654" class="pln"><a href="#n654">654</a></p> -<p id="n655" class="stm run hide_run"><a href="#n655">655</a></p> -<p id="n656" class="pln"><a href="#n656">656</a></p> -<p id="n657" class="pln"><a href="#n657">657</a></p> -<p id="n658" class="pln"><a href="#n658">658</a></p> -<p id="n659" class="pln"><a href="#n659">659</a></p> -<p id="n660" class="pln"><a href="#n660">660</a></p> -<p id="n661" class="pln"><a href="#n661">661</a></p> -<p id="n662" class="pln"><a href="#n662">662</a></p> -<p id="n663" class="pln"><a href="#n663">663</a></p> -<p id="n664" class="pln"><a href="#n664">664</a></p> -<p id="n665" class="stm run hide_run"><a href="#n665">665</a></p> -<p id="n666" class="stm run hide_run"><a href="#n666">666</a></p> -<p id="n667" class="stm run hide_run"><a href="#n667">667</a></p> -<p id="n668" class="stm run hide_run"><a href="#n668">668</a></p> -<p id="n669" class="stm run hide_run"><a href="#n669">669</a></p> -<p id="n670" class="pln"><a href="#n670">670</a></p> -<p id="n671" class="stm run hide_run"><a href="#n671">671</a></p> -<p id="n672" class="pln"><a href="#n672">672</a></p> -<p id="n673" class="stm run hide_run"><a href="#n673">673</a></p> -<p id="n674" class="pln"><a href="#n674">674</a></p> -<p id="n675" class="pln"><a href="#n675">675</a></p> -<p id="n676" class="stm run hide_run"><a href="#n676">676</a></p> -<p id="n677" class="stm run hide_run"><a href="#n677">677</a></p> -<p id="n678" class="pln"><a href="#n678">678</a></p> -<p id="n679" class="pln"><a href="#n679">679</a></p> -<p id="n680" class="pln"><a href="#n680">680</a></p> -<p id="n681" class="stm run hide_run"><a href="#n681">681</a></p> -<p id="n682" class="stm run hide_run"><a href="#n682">682</a></p> -<p id="n683" class="stm run hide_run"><a href="#n683">683</a></p> -<p id="n684" class="pln"><a href="#n684">684</a></p> -<p id="n685" class="pln"><a href="#n685">685</a></p> -<p id="n686" class="stm run hide_run"><a href="#n686">686</a></p> -<p id="n687" class="stm run hide_run"><a href="#n687">687</a></p> -<p id="n688" class="stm run hide_run"><a href="#n688">688</a></p> -<p id="n689" class="pln"><a href="#n689">689</a></p> -<p id="n690" class="pln"><a href="#n690">690</a></p> -<p id="n691" class="pln"><a href="#n691">691</a></p> -<p id="n692" class="pln"><a href="#n692">692</a></p> -<p id="n693" class="pln"><a href="#n693">693</a></p> -<p id="n694" class="pln"><a href="#n694">694</a></p> -<p id="n695" class="stm run hide_run"><a href="#n695">695</a></p> -<p id="n696" class="stm run hide_run"><a href="#n696">696</a></p> -<p id="n697" class="stm run hide_run"><a href="#n697">697</a></p> -<p id="n698" class="pln"><a href="#n698">698</a></p> -<p id="n699" class="pln"><a href="#n699">699</a></p> -<p id="n700" class="stm run hide_run"><a href="#n700">700</a></p> -<p id="n701" class="pln"><a href="#n701">701</a></p> -<p id="n702" class="stm run hide_run"><a href="#n702">702</a></p> -<p id="n703" class="pln"><a href="#n703">703</a></p> -<p id="n704" class="pln"><a href="#n704">704</a></p> -<p id="n705" class="pln"><a href="#n705">705</a></p> -<p id="n706" class="pln"><a href="#n706">706</a></p> -<p id="n707" class="pln"><a href="#n707">707</a></p> -<p id="n708" class="pln"><a href="#n708">708</a></p> -<p id="n709" class="pln"><a href="#n709">709</a></p> -<p id="n710" class="pln"><a href="#n710">710</a></p> -<p id="n711" class="pln"><a href="#n711">711</a></p> -<p id="n712" class="pln"><a href="#n712">712</a></p> -<p id="n713" class="stm run hide_run"><a href="#n713">713</a></p> -<p id="n714" class="stm run hide_run"><a href="#n714">714</a></p> -<p id="n715" class="stm run hide_run"><a href="#n715">715</a></p> -<p id="n716" class="stm run hide_run"><a href="#n716">716</a></p> -<p id="n717" class="stm run hide_run"><a href="#n717">717</a></p> -<p id="n718" class="pln"><a href="#n718">718</a></p> -<p id="n719" class="stm run hide_run"><a href="#n719">719</a></p> -<p id="n720" class="pln"><a href="#n720">720</a></p> -<p id="n721" class="pln"><a href="#n721">721</a></p> -<p id="n722" class="stm run hide_run"><a href="#n722">722</a></p> -<p id="n723" class="pln"><a href="#n723">723</a></p> -<p id="n724" class="stm run hide_run"><a href="#n724">724</a></p> -<p id="n725" class="stm run hide_run"><a href="#n725">725</a></p> -<p id="n726" class="pln"><a href="#n726">726</a></p> -<p id="n727" class="stm run hide_run"><a href="#n727">727</a></p> -<p id="n728" class="stm run hide_run"><a href="#n728">728</a></p> -<p id="n729" class="pln"><a href="#n729">729</a></p> -<p id="n730" class="pln"><a href="#n730">730</a></p> -<p id="n731" class="pln"><a href="#n731">731</a></p> -<p id="n732" class="stm run hide_run"><a href="#n732">732</a></p> -<p id="n733" class="pln"><a href="#n733">733</a></p> -<p id="n734" class="stm run hide_run"><a href="#n734">734</a></p> -<p id="n735" class="pln"><a href="#n735">735</a></p> -<p id="n736" class="pln"><a href="#n736">736</a></p> -<p id="n737" class="pln"><a href="#n737">737</a></p> -<p id="n738" class="pln"><a href="#n738">738</a></p> -<p id="n739" class="pln"><a href="#n739">739</a></p> -<p id="n740" class="pln"><a href="#n740">740</a></p> -<p id="n741" class="pln"><a href="#n741">741</a></p> -<p id="n742" class="pln"><a href="#n742">742</a></p> -<p id="n743" class="pln"><a href="#n743">743</a></p> -<p id="n744" class="pln"><a href="#n744">744</a></p> -<p id="n745" class="pln"><a href="#n745">745</a></p> -<p id="n746" class="stm run hide_run"><a href="#n746">746</a></p> -<p id="n747" class="stm run hide_run"><a href="#n747">747</a></p> -<p id="n748" class="stm run hide_run"><a href="#n748">748</a></p> -<p id="n749" class="stm run hide_run"><a href="#n749">749</a></p> -<p id="n750" class="stm run hide_run"><a href="#n750">750</a></p> -<p id="n751" class="pln"><a href="#n751">751</a></p> -<p id="n752" class="stm run hide_run"><a href="#n752">752</a></p> -<p id="n753" class="pln"><a href="#n753">753</a></p> -<p id="n754" class="pln"><a href="#n754">754</a></p> -<p id="n755" class="stm run hide_run"><a href="#n755">755</a></p> -<p id="n756" class="pln"><a href="#n756">756</a></p> -<p id="n757" class="stm run hide_run"><a href="#n757">757</a></p> -<p id="n758" class="stm run hide_run"><a href="#n758">758</a></p> -<p id="n759" class="pln"><a href="#n759">759</a></p> -<p id="n760" class="stm run hide_run"><a href="#n760">760</a></p> -<p id="n761" class="stm run hide_run"><a href="#n761">761</a></p> -<p id="n762" class="pln"><a href="#n762">762</a></p> -<p id="n763" class="pln"><a href="#n763">763</a></p> -<p id="n764" class="pln"><a href="#n764">764</a></p> -<p id="n765" class="stm run hide_run"><a href="#n765">765</a></p> -<p id="n766" class="pln"><a href="#n766">766</a></p> -<p id="n767" class="pln"><a href="#n767">767</a></p> -<p id="n768" class="stm run hide_run"><a href="#n768">768</a></p> -<p id="n769" class="pln"><a href="#n769">769</a></p> -<p id="n770" class="pln"><a href="#n770">770</a></p> -<p id="n771" class="pln"><a href="#n771">771</a></p> -<p id="n772" class="pln"><a href="#n772">772</a></p> -<p id="n773" class="pln"><a href="#n773">773</a></p> -<p id="n774" class="pln"><a href="#n774">774</a></p> -<p id="n775" class="pln"><a href="#n775">775</a></p> -<p id="n776" class="pln"><a href="#n776">776</a></p> -<p id="n777" class="stm run hide_run"><a href="#n777">777</a></p> -<p id="n778" class="stm mis"><a href="#n778">778</a></p> -<p id="n779" class="stm run hide_run"><a href="#n779">779</a></p> -<p id="n780" class="stm mis"><a href="#n780">780</a></p> -<p id="n781" class="stm run hide_run"><a href="#n781">781</a></p> -<p id="n782" class="stm run hide_run"><a href="#n782">782</a></p> -<p id="n783" class="pln"><a href="#n783">783</a></p> -<p id="n784" class="stm mis"><a href="#n784">784</a></p> -<p id="n785" class="pln"><a href="#n785">785</a></p> -<p id="n786" class="pln"><a href="#n786">786</a></p> -<p id="n787" class="stm run hide_run"><a href="#n787">787</a></p> -<p id="n788" class="stm run hide_run"><a href="#n788">788</a></p> -<p id="n789" class="stm mis"><a href="#n789">789</a></p> -<p id="n790" class="stm mis"><a href="#n790">790</a></p> -<p id="n791" class="pln"><a href="#n791">791</a></p> -<p id="n792" class="stm mis"><a href="#n792">792</a></p> -<p id="n793" class="pln"><a href="#n793">793</a></p> -<p id="n794" class="pln"><a href="#n794">794</a></p> -<p id="n795" class="stm run hide_run"><a href="#n795">795</a></p> -<p id="n796" class="pln"><a href="#n796">796</a></p> -<p id="n797" class="pln"><a href="#n797">797</a></p> -<p id="n798" class="pln"><a href="#n798">798</a></p> -<p id="n799" class="pln"><a href="#n799">799</a></p> -<p id="n800" class="pln"><a href="#n800">800</a></p> -<p id="n801" class="pln"><a href="#n801">801</a></p> -<p id="n802" class="pln"><a href="#n802">802</a></p> -<p id="n803" class="pln"><a href="#n803">803</a></p> -<p id="n804" class="pln"><a href="#n804">804</a></p> -<p id="n805" class="pln"><a href="#n805">805</a></p> -<p id="n806" class="pln"><a href="#n806">806</a></p> -<p id="n807" class="pln"><a href="#n807">807</a></p> -<p id="n808" class="stm run hide_run"><a href="#n808">808</a></p> -<p id="n809" class="pln"><a href="#n809">809</a></p> -<p id="n810" class="pln"><a href="#n810">810</a></p> -<p id="n811" class="pln"><a href="#n811">811</a></p> -<p id="n812" class="pln"><a href="#n812">812</a></p> -<p id="n813" class="pln"><a href="#n813">813</a></p> -<p id="n814" class="pln"><a href="#n814">814</a></p> -<p id="n815" class="pln"><a href="#n815">815</a></p> -<p id="n816" class="pln"><a href="#n816">816</a></p> -<p id="n817" class="pln"><a href="#n817">817</a></p> -<p id="n818" class="stm run hide_run"><a href="#n818">818</a></p> -<p id="n819" class="pln"><a href="#n819">819</a></p> -<p id="n820" class="pln"><a href="#n820">820</a></p> -<p id="n821" class="stm run hide_run"><a href="#n821">821</a></p> -<p id="n822" class="stm run hide_run"><a href="#n822">822</a></p> -<p id="n823" class="pln"><a href="#n823">823</a></p> -<p id="n824" class="pln"><a href="#n824">824</a></p> -<p id="n825" class="pln"><a href="#n825">825</a></p> -<p id="n826" class="stm run hide_run"><a href="#n826">826</a></p> -<p id="n827" class="pln"><a href="#n827">827</a></p> -<p id="n828" class="stm run hide_run"><a href="#n828">828</a></p> -<p id="n829" class="pln"><a href="#n829">829</a></p> -<p id="n830" class="pln"><a href="#n830">830</a></p> -<p id="n831" class="pln"><a href="#n831">831</a></p> -<p id="n832" class="pln"><a href="#n832">832</a></p> -<p id="n833" class="stm run hide_run"><a href="#n833">833</a></p> -<p id="n834" class="pln"><a href="#n834">834</a></p> -<p id="n835" class="pln"><a href="#n835">835</a></p> -<p id="n836" class="pln"><a href="#n836">836</a></p> -<p id="n837" class="pln"><a href="#n837">837</a></p> -<p id="n838" class="stm run hide_run"><a href="#n838">838</a></p> -<p id="n839" class="pln"><a href="#n839">839</a></p> -<p id="n840" class="stm run hide_run"><a href="#n840">840</a></p> -<p id="n841" class="pln"><a href="#n841">841</a></p> -<p id="n842" class="pln"><a href="#n842">842</a></p> -<p id="n843" class="stm run hide_run"><a href="#n843">843</a></p> -<p id="n844" class="pln"><a href="#n844">844</a></p> -<p id="n845" class="pln"><a href="#n845">845</a></p> -<p id="n846" class="pln"><a href="#n846">846</a></p> -<p id="n847" class="pln"><a href="#n847">847</a></p> -<p id="n848" class="pln"><a href="#n848">848</a></p> -<p id="n849" class="pln"><a href="#n849">849</a></p> -<p id="n850" class="pln"><a href="#n850">850</a></p> -<p id="n851" class="pln"><a href="#n851">851</a></p> -<p id="n852" class="pln"><a href="#n852">852</a></p> -<p id="n853" class="pln"><a href="#n853">853</a></p> -<p id="n854" class="pln"><a href="#n854">854</a></p> -<p id="n855" class="pln"><a href="#n855">855</a></p> -<p id="n856" class="stm mis"><a href="#n856">856</a></p> -<p id="n857" class="pln"><a href="#n857">857</a></p> -<p id="n858" class="pln"><a href="#n858">858</a></p> -<p id="n859" class="pln"><a href="#n859">859</a></p> -<p id="n860" class="stm mis"><a href="#n860">860</a></p> - - </td> - <td class="text"> -<p id="t1" class="stm run hide_run"><span class="key">from</span> <span class="nam">abc</span> <span class="key">import</span> <span class="nam">abstractmethod</span><span class="strut"> </span></p> -<p id="t2" class="pln"><span class="strut"> </span></p> -<p id="t3" class="stm run hide_run"><span class="key">import</span> <span class="nam">numpy</span> <span class="key">as</span> <span class="nam">np</span><span class="strut"> </span></p> -<p id="t4" class="pln"><span class="strut"> </span></p> -<p id="t5" class="stm run hide_run"><span class="key">import</span> <span class="nam">fluegg</span><span class="op">.</span><span class="nam">hydraulics</span> <span class="key">as</span> <span class="nam">hydraulics</span><span class="strut"> </span></p> -<p id="t6" class="pln"><span class="strut"> </span></p> -<p id="t7" class="pln"><span class="strut"> </span></p> -<p id="t8" class="stm run hide_run"><span class="key">class</span> <span class="nam">Transporter</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t9" class="pln"><span class="strut"> </span></p> -<p id="t10" class="stm run hide_run"> <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">simulation_clock</span><span class="op">,</span> <span class="nam">particles</span><span class="op">,</span> <span class="nam">random_numbers</span><span class="op">=</span><span class="key">None</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t11" class="pln"> <span class="str">"""</span><span class="strut"> </span></p> -<p id="t12" class="pln"><span class="strut"> </span></p> -<p id="t13" class="pln"><span class="str"> :param simulation_clock:</span><span class="strut"> </span></p> -<p id="t14" class="pln"><span class="str"> :param particles:</span><span class="strut"> </span></p> -<p id="t15" class="pln"><span class="str"> :param hydraulic_model:</span><span class="strut"> </span></p> -<p id="t16" class="pln"><span class="str"> :param random_numbers:</span><span class="strut"> </span></p> -<p id="t17" class="pln"><span class="str"> :type: fluegg.random.RandomNumbers</span><span class="strut"> </span></p> -<p id="t18" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t19" class="pln"><span class="strut"> </span></p> -<p id="t20" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_simulation_clock</span> <span class="op">=</span> <span class="nam">simulation_clock</span><span class="strut"> </span></p> -<p id="t21" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_particles</span> <span class="op">=</span> <span class="nam">particles</span><span class="strut"> </span></p> -<p id="t22" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_hydraulic_model</span> <span class="op">=</span> <span class="key">None</span><span class="strut"> </span></p> -<p id="t23" class="stm run hide_run"> <span class="key">if</span> <span class="nam">random_numbers</span> <span class="key">is</span> <span class="key">None</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t24" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">_random_func</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">random</span><span class="op">.</span><span class="nam">normal</span><span class="strut"> </span></p> -<p id="t25" class="pln"> <span class="key">else</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t26" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_random_func</span> <span class="op">=</span> <span class="nam">random_numbers</span><span class="op">.</span><span class="nam">random_array</span><span class="strut"> </span></p> -<p id="t27" class="pln"><span class="strut"> </span></p> -<p id="t28" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_random_num</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">size</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t29" class="pln"> <span class="str">"""Returns an array of random numbers pulled from</span><span class="strut"> </span></p> -<p id="t30" class="pln"><span class="str"> a normal distribution (mean=0, std=1)</span><span class="strut"> </span></p> -<p id="t31" class="pln"><span class="strut"> </span></p> -<p id="t32" class="pln"><span class="str"> :param size: Number of random numbers</span><span class="strut"> </span></p> -<p id="t33" class="pln"><span class="str"> :type: int</span><span class="strut"> </span></p> -<p id="t34" class="pln"><span class="str"> :return: random numbers</span><span class="strut"> </span></p> -<p id="t35" class="pln"><span class="str"> :rtype: numpy.ndarray</span><span class="strut"> </span></p> -<p id="t36" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t37" class="pln"><span class="strut"> </span></p> -<p id="t38" class="stm run hide_run"> <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_random_func</span><span class="op">(</span><span class="num">0</span><span class="op">,</span> <span class="num">1</span><span class="op">,</span> <span class="nam">size</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t39" class="pln"><span class="strut"> </span></p> -<p id="t40" class="stm run hide_run"> <span class="op">@</span><span class="nam">staticmethod</span><span class="strut"> </span></p> -<p id="t41" class="pln"> <span class="key">def</span> <span class="nam">_horizontal_turbulent_diffusion</span><span class="op">(</span><span class="nam">depth</span><span class="op">,</span> <span class="nam">shear_velocity</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t42" class="pln"> <span class="str">"""Returns the horizontal turbulent diffusion</span><span class="strut"> </span></p> -<p id="t43" class="pln"><span class="strut"> </span></p> -<p id="t44" class="pln"><span class="str"> :param depth: depth of water (m)</span><span class="strut"> </span></p> -<p id="t45" class="pln"><span class="str"> :type: numpy.ndarray</span><span class="strut"> </span></p> -<p id="t46" class="pln"><span class="str"> :param shear_velocity: shear velocity of water at depth (m/s)</span><span class="strut"> </span></p> -<p id="t47" class="pln"><span class="str"> :type: numpy.ndarray</span><span class="strut"> </span></p> -<p id="t48" class="pln"><span class="str"> :return: horizontal turbulent diffusion at input depth (m**2/s)</span><span class="strut"> </span></p> -<p id="t49" class="pln"><span class="str"> :rtype: numpy.ndarray</span><span class="strut"> </span></p> -<p id="t50" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t51" class="pln"><span class="strut"> </span></p> -<p id="t52" class="stm run hide_run"> <span class="key">return</span> <span class="num">0.6</span> <span class="op">*</span> <span class="nam">depth</span> <span class="op">*</span> <span class="nam">shear_velocity</span><span class="strut"> </span></p> -<p id="t53" class="pln"><span class="strut"> </span></p> -<p id="t54" class="stm run hide_run"> <span class="op">@</span><span class="nam">abstractmethod</span><span class="strut"> </span></p> -<p id="t55" class="pln"> <span class="key">def</span> <span class="nam">increment_positions</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">hydraulic_results</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t56" class="pln"> <span class="str">"""Increments positions of particles according to current time step.</span><span class="strut"> </span></p> -<p id="t57" class="pln"><span class="strut"> </span></p> -<p id="t58" class="pln"><span class="str"> :param hydraulic_results: hydraulic results at current particle</span><span class="strut"> </span></p> -<p id="t59" class="pln"><span class="str"> positions</span><span class="strut"> </span></p> -<p id="t60" class="pln"><span class="str"> :type hydraulic_results: fluegg.hydraulics.HydraulicResults</span><span class="strut"> </span></p> -<p id="t61" class="pln"><span class="strut"> </span></p> -<p id="t62" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t63" class="pln"><span class="strut"> </span></p> -<p id="t64" class="stm mis"> <span class="key">raise</span> <span class="nam">NotImplementedError</span><span class="strut"> </span></p> -<p id="t65" class="pln"><span class="strut"> </span></p> -<p id="t66" class="stm run hide_run"> <span class="key">def</span> <span class="nam">set_hydraulic_model</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">hydraulic_model</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t67" class="pln"> <span class="str">"""</span><span class="strut"> </span></p> -<p id="t68" class="pln"><span class="strut"> </span></p> -<p id="t69" class="pln"><span class="str"> :param hydraulic_model:</span><span class="strut"> </span></p> -<p id="t70" class="pln"><span class="str"> :type hydraulic_model: fluegg.hydraulics.SeriesOfHydraulicCells</span><span class="strut"> </span></p> -<p id="t71" class="pln"><span class="str"> :return: None</span><span class="strut"> </span></p> -<p id="t72" class="pln"><span class="strut"> </span></p> -<p id="t73" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t74" class="pln"><span class="strut"> </span></p> -<p id="t75" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_hydraulic_model</span> <span class="op">=</span> <span class="nam">hydraulic_model</span><span class="strut"> </span></p> -<p id="t76" class="pln"><span class="strut"> </span></p> -<p id="t77" class="stm run hide_run"> <span class="key">def</span> <span class="nam">max_time_step</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t78" class="pln"> <span class="str">"""Finds the maximum time step required for an accurate simulation.</span><span class="strut"> </span></p> -<p id="t79" class="pln"><span class="str"> Default is at infinity (i.e. no maximum time step)</span><span class="strut"> </span></p> -<p id="t80" class="pln"><span class="strut"> </span></p> -<p id="t81" class="pln"><span class="str"> :return: maximum time step criterion given the current time step</span><span class="strut"> </span></p> -<p id="t82" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t83" class="pln"><span class="strut"> </span></p> -<p id="t84" class="stm run hide_run"> <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_hydraulic_model</span> <span class="key">is</span> <span class="key">None</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t85" class="stm mis"> <span class="key">raise</span> <span class="nam">RuntimeError</span><span class="op">(</span><span class="str">"hydraulic_model attribute is set to None"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t86" class="pln"><span class="strut"> </span></p> -<p id="t87" class="stm run hide_run"> <span class="key">return</span> <span class="nam">float</span><span class="op">(</span><span class="str">"inf"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t88" class="pln"><span class="strut"> </span></p> -<p id="t89" class="stm run hide_run"> <span class="key">def</span> <span class="nam">increment_positions</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">hydraulic_results</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t90" class="pln"> <span class="str">"""</span><span class="strut"> </span></p> -<p id="t91" class="pln"><span class="strut"> </span></p> -<p id="t92" class="pln"><span class="str"> Parameters</span><span class="strut"> </span></p> -<p id="t93" class="pln"><span class="str"> ----------</span><span class="strut"> </span></p> -<p id="t94" class="pln"><span class="str"> hydraulic_results : fluegg.hydraulics.HydraulicResults</span><span class="strut"> </span></p> -<p id="t95" class="pln"><span class="strut"> </span></p> -<p id="t96" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t97" class="pln"><span class="strut"> </span></p> -<p id="t98" class="stm mis"> <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_hydraulic_model</span> <span class="key">is</span> <span class="key">None</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t99" class="stm mis"> <span class="key">raise</span> <span class="nam">RuntimeError</span><span class="op">(</span><span class="str">"hydraulic_model attribute is set to None"</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t100" class="pln"><span class="strut"> </span></p> -<p id="t101" class="pln"><span class="strut"> </span></p> -<p id="t102" class="stm run hide_run"><span class="key">class</span> <span class="nam">LateralTransporter</span><span class="op">(</span><span class="nam">Transporter</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t103" class="pln"><span class="strut"> </span></p> -<p id="t104" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_lateral_boundary_checks</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">hydraulic_results</span><span class="op">,</span> <span class="nam">next_position</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t105" class="pln"> <span class="str">"""</span><span class="strut"> </span></p> -<p id="t106" class="pln"><span class="strut"> </span></p> -<p id="t107" class="pln"><span class="str"> :param hydraulic_results:</span><span class="strut"> </span></p> -<p id="t108" class="pln"><span class="str"> :param next_position:</span><span class="strut"> </span></p> -<p id="t109" class="pln"><span class="str"> :return:</span><span class="strut"> </span></p> -<p id="t110" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t111" class="pln"><span class="strut"> </span></p> -<p id="t112" class="pln"> <span class="com"># Check lateral position</span><span class="strut"> </span></p> -<p id="t113" class="stm run hide_run"> <span class="nam">width</span> <span class="op">=</span> <span class="nam">hydraulic_results</span><span class="op">.</span><span class="nam">width</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t114" class="pln"><span class="strut"> </span></p> -<p id="t115" class="stm run hide_run"> <span class="nam">diameter</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_particles</span><span class="op">.</span><span class="nam">diameter</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t116" class="pln"><span class="strut"> </span></p> -<p id="t117" class="stm run hide_run"> <span class="nam">boundary_length</span> <span class="op">=</span> <span class="nam">width</span> <span class="op">-</span> <span class="nam">diameter</span><span class="strut"> </span></p> -<p id="t118" class="pln"><span class="strut"> </span></p> -<p id="t119" class="stm run hide_run"> <span class="nam">shifted_next_lateral_position</span> <span class="op">=</span> <span class="nam">next_position</span> <span class="op">-</span> <span class="nam">diameter</span> <span class="op">/</span> <span class="num">2</span><span class="strut"> </span></p> -<p id="t120" class="stm run hide_run"> <span class="nam">shifted_boundary_location</span> <span class="op">=</span> <span class="nam">boundary_length</span><span class="strut"> </span></p> -<p id="t121" class="pln"><span class="strut"> </span></p> -<p id="t122" class="stm run hide_run"> <span class="nam">right_of_boundary</span> <span class="op">=</span> <span class="nam">shifted_next_lateral_position</span> <span class="op"><</span> <span class="num">0</span><span class="strut"> </span></p> -<p id="t123" class="stm run hide_run"> <span class="nam">left_of_boundary</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t124" class="pln"> <span class="nam">shifted_next_lateral_position</span> <span class="op">></span> <span class="nam">shifted_boundary_location</span><span class="strut"> </span></p> -<p id="t125" class="stm run hide_run"> <span class="nam">out_of_bounds</span> <span class="op">=</span> <span class="nam">right_of_boundary</span> <span class="op">|</span> <span class="nam">left_of_boundary</span><span class="strut"> </span></p> -<p id="t126" class="pln"><span class="strut"> </span></p> -<p id="t127" class="stm run hide_run"> <span class="key">if</span> <span class="nam">np</span><span class="op">.</span><span class="nam">any</span><span class="op">(</span><span class="nam">out_of_bounds</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t128" class="pln"><span class="strut"> </span></p> -<p id="t129" class="stm run hide_run"> <span class="nam">reflections</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">floor_divide</span><span class="op">(</span><span class="nam">shifted_next_lateral_position</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t130" class="pln"> <span class="nam">shifted_boundary_location</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t131" class="stm run hide_run"> <span class="nam">remainder</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">mod</span><span class="op">(</span><span class="nam">shifted_next_lateral_position</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t132" class="pln"> <span class="nam">shifted_boundary_location</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t133" class="pln"><span class="strut"> </span></p> -<p id="t134" class="stm run hide_run"> <span class="nam">reflection_mod_2</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">mod</span><span class="op">(</span><span class="nam">reflections</span><span class="op">,</span> <span class="num">2</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t135" class="stm run hide_run"> <span class="nam">odd_reflections</span> <span class="op">=</span> <span class="op">(</span><span class="nam">reflection_mod_2</span> <span class="op">==</span> <span class="num">1</span><span class="op">)</span> <span class="op">&</span> <span class="nam">out_of_bounds</span><span class="strut"> </span></p> -<p id="t136" class="stm run hide_run"> <span class="nam">even_reflections</span> <span class="op">=</span> <span class="op">(</span><span class="nam">reflection_mod_2</span> <span class="op">==</span> <span class="num">0</span><span class="op">)</span> <span class="op">&</span> <span class="nam">out_of_bounds</span><span class="strut"> </span></p> -<p id="t137" class="pln"><span class="strut"> </span></p> -<p id="t138" class="stm run hide_run"> <span class="nam">shifted_next_lateral_position</span><span class="op">[</span><span class="nam">even_reflections</span><span class="op">]</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t139" class="pln"> <span class="nam">remainder</span><span class="op">[</span><span class="nam">even_reflections</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t140" class="stm run hide_run"> <span class="nam">shifted_next_lateral_position</span><span class="op">[</span><span class="nam">odd_reflections</span><span class="op">]</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t141" class="pln"> <span class="nam">boundary_length</span><span class="op">[</span><span class="nam">odd_reflections</span><span class="op">]</span> <span class="op">-</span> <span class="nam">remainder</span><span class="op">[</span><span class="nam">odd_reflections</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t142" class="pln"><span class="strut"> </span></p> -<p id="t143" class="stm run hide_run"> <span class="nam">next_position</span> <span class="op">=</span> <span class="nam">shifted_next_lateral_position</span> <span class="op">+</span> <span class="nam">diameter</span> <span class="op">/</span> <span class="num">2</span><span class="strut"> </span></p> -<p id="t144" class="pln"><span class="strut"> </span></p> -<p id="t145" class="stm run hide_run"> <span class="key">return</span> <span class="nam">next_position</span><span class="strut"> </span></p> -<p id="t146" class="pln"><span class="strut"> </span></p> -<p id="t147" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_next_lateral_positions</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">hydraulic_results</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t148" class="pln"> <span class="str">"""Returns incremented lateral particle positions</span><span class="strut"> </span></p> -<p id="t149" class="pln"><span class="strut"> </span></p> -<p id="t150" class="pln"><span class="str"> :param hydraulic_results: hydraulic results at current particle</span><span class="strut"> </span></p> -<p id="t151" class="pln"><span class="str"> positions</span><span class="strut"> </span></p> -<p id="t152" class="pln"><span class="str"> :type hydraulic_results: fluegg.hydraulics.HydraulicResults</span><span class="strut"> </span></p> -<p id="t153" class="pln"><span class="str"> :return: next lateral particle positions</span><span class="strut"> </span></p> -<p id="t154" class="pln"><span class="str"> :rtype: numpy.ndarray(num_particles)</span><span class="strut"> </span></p> -<p id="t155" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t156" class="pln"> <span class="com"># Initialize necessary calculations</span><span class="strut"> </span></p> -<p id="t157" class="stm run hide_run"> <span class="nam">lateral_position</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_particles</span><span class="op">.</span><span class="nam">position</span><span class="op">(</span><span class="op">)</span><span class="op">[</span><span class="op">:</span><span class="op">,</span> <span class="num">1</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t158" class="stm run hide_run"> <span class="nam">num_particles</span> <span class="op">=</span> <span class="nam">lateral_position</span><span class="op">.</span><span class="nam">shape</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t159" class="stm run hide_run"> <span class="nam">random_num</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_random_num</span><span class="op">(</span><span class="nam">num_particles</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t160" class="stm run hide_run"> <span class="nam">time_step</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_simulation_clock</span><span class="op">.</span><span class="nam">time_step_size</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t161" class="stm run hide_run"> <span class="nam">lateral_velocity</span> <span class="op">=</span> <span class="nam">hydraulic_results</span><span class="op">.</span><span class="nam">lateral_velocity</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t162" class="pln"><span class="strut"> </span></p> -<p id="t163" class="stm run hide_run"> <span class="nam">depth</span> <span class="op">=</span> <span class="nam">hydraulic_results</span><span class="op">.</span><span class="nam">depth</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t164" class="stm run hide_run"> <span class="nam">shear_velocity</span> <span class="op">=</span> <span class="nam">hydraulic_results</span><span class="op">.</span><span class="nam">shear_velocity</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t165" class="stm run hide_run"> <span class="nam">turbulent_diffusion</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t166" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">_horizontal_turbulent_diffusion</span><span class="op">(</span><span class="nam">depth</span><span class="op">,</span> <span class="nam">shear_velocity</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t167" class="pln"><span class="strut"> </span></p> -<p id="t168" class="pln"> <span class="com"># Calculate incremented lateral positions</span><span class="strut"> </span></p> -<p id="t169" class="stm run hide_run"> <span class="nam">next_lateral_position</span> <span class="op">=</span> <span class="nam">lateral_position</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t170" class="pln"> <span class="op">+</span> <span class="nam">lateral_velocity</span> <span class="op">*</span> <span class="nam">time_step</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t171" class="pln"> <span class="op">+</span> <span class="nam">random_num</span> <span class="op">*</span> <span class="nam">np</span><span class="op">.</span><span class="nam">sqrt</span><span class="op">(</span><span class="num">2</span> <span class="op">*</span> <span class="nam">turbulent_diffusion</span> <span class="op">*</span> <span class="nam">time_step</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t172" class="pln"><span class="strut"> </span></p> -<p id="t173" class="stm run hide_run"> <span class="key">return</span> <span class="nam">next_lateral_position</span><span class="strut"> </span></p> -<p id="t174" class="pln"><span class="strut"> </span></p> -<p id="t175" class="stm run hide_run"> <span class="key">def</span> <span class="nam">increment_positions</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">hydraulic_results</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t176" class="pln"> <span class="str">"""Increments positions of particles according to current time step.</span><span class="strut"> </span></p> -<p id="t177" class="pln"><span class="strut"> </span></p> -<p id="t178" class="pln"><span class="str"> :param hydraulic_results: hydraulic results at current particle</span><span class="strut"> </span></p> -<p id="t179" class="pln"><span class="str"> positions</span><span class="strut"> </span></p> -<p id="t180" class="pln"><span class="str"> :type hydraulic_results: fluegg.hydraulics.HydraulicResults</span><span class="strut"> </span></p> -<p id="t181" class="pln"><span class="strut"> </span></p> -<p id="t182" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t183" class="pln"><span class="strut"> </span></p> -<p id="t184" class="stm run hide_run"> <span class="nam">next_lateral_positions</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t185" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">_next_lateral_positions</span><span class="op">(</span><span class="nam">hydraulic_results</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t186" class="pln"><span class="strut"> </span></p> -<p id="t187" class="stm run hide_run"> <span class="nam">next_lateral_positions</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t188" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">_lateral_boundary_checks</span><span class="op">(</span><span class="nam">hydraulic_results</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t189" class="pln"> <span class="nam">next_lateral_positions</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t190" class="pln"><span class="strut"> </span></p> -<p id="t191" class="stm run hide_run"> <span class="nam">positions</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_particles</span><span class="op">.</span><span class="nam">position</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t192" class="pln"><span class="strut"> </span></p> -<p id="t193" class="stm run hide_run"> <span class="nam">positions</span><span class="op">[</span><span class="op">:</span><span class="op">,</span> <span class="num">1</span><span class="op">]</span> <span class="op">=</span> <span class="nam">next_lateral_positions</span><span class="strut"> </span></p> -<p id="t194" class="pln"><span class="strut"> </span></p> -<p id="t195" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_particles</span><span class="op">.</span><span class="nam">set_position</span><span class="op">(</span><span class="nam">positions</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t196" class="pln"><span class="strut"> </span></p> -<p id="t197" class="pln"><span class="strut"> </span></p> -<p id="t198" class="stm run hide_run"><span class="key">class</span> <span class="nam">LongitudinalTransporter</span><span class="op">(</span><span class="nam">Transporter</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t199" class="pln"><span class="strut"> </span></p> -<p id="t200" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_next_longitudinal_positions</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">hydraulic_results</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t201" class="pln"> <span class="str">"""Returns incremented longitudinal particle positions</span><span class="strut"> </span></p> -<p id="t202" class="pln"><span class="strut"> </span></p> -<p id="t203" class="pln"><span class="str"> :param hydraulic_results: hydraulic results at current particle</span><span class="strut"> </span></p> -<p id="t204" class="pln"><span class="str"> positions</span><span class="strut"> </span></p> -<p id="t205" class="pln"><span class="str"> :type: numpy.ndarray</span><span class="strut"> </span></p> -<p id="t206" class="pln"><span class="str"> :return: next longitudinal particle positions</span><span class="strut"> </span></p> -<p id="t207" class="pln"><span class="str"> :rtype: numpy.ndarray</span><span class="strut"> </span></p> -<p id="t208" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t209" class="pln"><span class="strut"> </span></p> -<p id="t210" class="pln"> <span class="com"># Initialize necessary calculations</span><span class="strut"> </span></p> -<p id="t211" class="stm run hide_run"> <span class="nam">longitudinal_position</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_particles</span><span class="op">.</span><span class="nam">position</span><span class="op">(</span><span class="op">)</span><span class="op">[</span><span class="op">:</span><span class="op">,</span> <span class="num">0</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t212" class="stm run hide_run"> <span class="nam">num_particles</span> <span class="op">=</span> <span class="nam">longitudinal_position</span><span class="op">.</span><span class="nam">shape</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t213" class="stm run hide_run"> <span class="nam">random_num</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_random_num</span><span class="op">(</span><span class="nam">num_particles</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t214" class="stm run hide_run"> <span class="nam">time_step</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_simulation_clock</span><span class="op">.</span><span class="nam">time_step_size</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t215" class="stm run hide_run"> <span class="nam">longitudinal_velocity</span> <span class="op">=</span> <span class="nam">hydraulic_results</span><span class="op">.</span><span class="nam">streamwise_velocity</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t216" class="stm run hide_run"> <span class="nam">depth</span> <span class="op">=</span> <span class="nam">hydraulic_results</span><span class="op">.</span><span class="nam">depth</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t217" class="stm run hide_run"> <span class="nam">shear_velocity</span> <span class="op">=</span> <span class="nam">hydraulic_results</span><span class="op">.</span><span class="nam">shear_velocity</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t218" class="stm run hide_run"> <span class="nam">turbulent_diffusion</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t219" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">_horizontal_turbulent_diffusion</span><span class="op">(</span><span class="nam">depth</span><span class="op">,</span> <span class="nam">shear_velocity</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t220" class="pln"><span class="strut"> </span></p> -<p id="t221" class="pln"> <span class="com"># Calculate incremented longitudinal positions</span><span class="strut"> </span></p> -<p id="t222" class="stm run hide_run"> <span class="nam">next_longitudinal_position</span> <span class="op">=</span> <span class="nam">longitudinal_position</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t223" class="pln"> <span class="op">+</span> <span class="nam">longitudinal_velocity</span> <span class="op">*</span> <span class="nam">time_step</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t224" class="pln"> <span class="op">+</span> <span class="nam">random_num</span> <span class="op">*</span> <span class="nam">np</span><span class="op">.</span><span class="nam">sqrt</span><span class="op">(</span><span class="num">2</span> <span class="op">*</span> <span class="nam">turbulent_diffusion</span> <span class="op">*</span> <span class="nam">time_step</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t225" class="pln"><span class="strut"> </span></p> -<p id="t226" class="stm run hide_run"> <span class="key">return</span> <span class="nam">next_longitudinal_position</span><span class="strut"> </span></p> -<p id="t227" class="pln"><span class="strut"> </span></p> -<p id="t228" class="stm run hide_run"> <span class="key">def</span> <span class="nam">increment_positions</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">hydraulic_results</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t229" class="pln"> <span class="str">"""Increments positions of particles according to current time step.</span><span class="strut"> </span></p> -<p id="t230" class="pln"><span class="strut"> </span></p> -<p id="t231" class="pln"><span class="str"> :param hydraulic_results: hydraulic results at current particle</span><span class="strut"> </span></p> -<p id="t232" class="pln"><span class="str"> positions</span><span class="strut"> </span></p> -<p id="t233" class="pln"><span class="str"> :type hydraulic_results: fluegg.hydraulics.HydraulicResults</span><span class="strut"> </span></p> -<p id="t234" class="pln"><span class="strut"> </span></p> -<p id="t235" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t236" class="pln"><span class="strut"> </span></p> -<p id="t237" class="stm run hide_run"> <span class="nam">next_longitudinal_positions</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t238" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">_next_longitudinal_positions</span><span class="op">(</span><span class="nam">hydraulic_results</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t239" class="pln"><span class="strut"> </span></p> -<p id="t240" class="stm run hide_run"> <span class="nam">positions</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_particles</span><span class="op">.</span><span class="nam">position</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t241" class="pln"><span class="strut"> </span></p> -<p id="t242" class="stm run hide_run"> <span class="nam">positions</span><span class="op">[</span><span class="op">:</span><span class="op">,</span> <span class="num">0</span><span class="op">]</span> <span class="op">=</span> <span class="nam">next_longitudinal_positions</span><span class="strut"> </span></p> -<p id="t243" class="pln"><span class="strut"> </span></p> -<p id="t244" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_particles</span><span class="op">.</span><span class="nam">set_position</span><span class="op">(</span><span class="nam">positions</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t245" class="pln"><span class="strut"> </span></p> -<p id="t246" class="pln"><span class="strut"> </span></p> -<p id="t247" class="stm run hide_run"><span class="key">class</span> <span class="nam">ReverseLongitudinalTransporter</span><span class="op">(</span><span class="nam">LongitudinalTransporter</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t248" class="pln"><span class="strut"> </span></p> -<p id="t249" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_get_next_longitudinal_positions</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">hydraulic_results</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t250" class="pln"> <span class="str">"""Returns incremented longitudinal particle positions</span><span class="strut"> </span></p> -<p id="t251" class="pln"><span class="strut"> </span></p> -<p id="t252" class="pln"><span class="str"> :param hydraulic_results: hydraulic results at current particle</span><span class="strut"> </span></p> -<p id="t253" class="pln"><span class="str"> positions</span><span class="strut"> </span></p> -<p id="t254" class="pln"><span class="str"> :type: numpy.ndarray</span><span class="strut"> </span></p> -<p id="t255" class="pln"><span class="str"> :return: next longitudinal particle positions</span><span class="strut"> </span></p> -<p id="t256" class="pln"><span class="str"> :rtype: numpy.ndarray</span><span class="strut"> </span></p> -<p id="t257" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t258" class="pln"><span class="strut"> </span></p> -<p id="t259" class="pln"> <span class="com"># Initialize necessary calculations</span><span class="strut"> </span></p> -<p id="t260" class="stm mis"> <span class="nam">longitudinal_position</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_particles</span><span class="op">.</span><span class="nam">get_position</span><span class="op">(</span><span class="op">)</span><span class="op">[</span><span class="op">:</span><span class="op">,</span> <span class="num">0</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t261" class="stm mis"> <span class="nam">num_particles</span> <span class="op">=</span> <span class="nam">longitudinal_position</span><span class="op">.</span><span class="nam">shape</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t262" class="stm mis"> <span class="nam">random_num</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_random_num</span><span class="op">(</span><span class="nam">num_particles</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t263" class="stm mis"> <span class="nam">time_step</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_simulation_clock</span><span class="op">.</span><span class="nam">get_time_step_size</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t264" class="stm mis"> <span class="nam">longitudinal_velocity</span> <span class="op">=</span> <span class="nam">hydraulic_results</span><span class="op">.</span><span class="nam">streamwise_velocity</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t265" class="stm mis"> <span class="nam">depth</span> <span class="op">=</span> <span class="nam">hydraulic_results</span><span class="op">.</span><span class="nam">depth</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t266" class="stm mis"> <span class="nam">shear_velocity</span> <span class="op">=</span> <span class="nam">hydraulic_results</span><span class="op">.</span><span class="nam">shear_velocity</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t267" class="stm mis"> <span class="nam">turbulent_diffusion</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t268" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">_horizontal_turbulent_diffusion</span><span class="op">(</span><span class="nam">depth</span><span class="op">,</span> <span class="nam">shear_velocity</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t269" class="pln"><span class="strut"> </span></p> -<p id="t270" class="pln"> <span class="com"># Reverse the advection direction</span><span class="strut"> </span></p> -<p id="t271" class="stm mis"> <span class="nam">reversal</span> <span class="op">=</span> <span class="op">-</span><span class="num">1</span><span class="strut"> </span></p> -<p id="t272" class="pln"><span class="strut"> </span></p> -<p id="t273" class="pln"> <span class="com"># Calculate incremented longitudinal positions</span><span class="strut"> </span></p> -<p id="t274" class="stm mis"> <span class="nam">next_longitudinal_position</span> <span class="op">=</span> <span class="nam">longitudinal_position</span> <span class="op">+</span> <span class="nam">reversal</span> <span class="op">*</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t275" class="pln"> <span class="nam">longitudinal_velocity</span> <span class="op">*</span> <span class="nam">time_step</span> <span class="op">+</span> <span class="nam">random_num</span> <span class="op">*</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t276" class="pln"> <span class="nam">np</span><span class="op">.</span><span class="nam">sqrt</span><span class="op">(</span><span class="num">2</span> <span class="op">*</span> <span class="nam">turbulent_diffusion</span> <span class="op">*</span> <span class="nam">time_step</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t277" class="pln"><span class="strut"> </span></p> -<p id="t278" class="stm mis"> <span class="key">return</span> <span class="nam">next_longitudinal_position</span><span class="strut"> </span></p> -<p id="t279" class="pln"><span class="strut"> </span></p> -<p id="t280" class="pln"><span class="strut"> </span></p> -<p id="t281" class="stm run hide_run"><span class="key">class</span> <span class="nam">VerticalTransporter</span><span class="op">(</span><span class="nam">Transporter</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t282" class="pln"><span class="strut"> </span></p> -<p id="t283" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_vertical_boundary_checks</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">hydraulic_results</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t284" class="pln"> <span class="nam">next_vertical_position</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t285" class="pln"> <span class="str">"""Checks whether positions are within the hydraulic boundary.</span><span class="strut"> </span></p> -<p id="t286" class="pln"><span class="str"> If not, returns the positions reflected on the boundary</span><span class="strut"> </span></p> -<p id="t287" class="pln"><span class="strut"> </span></p> -<p id="t288" class="pln"><span class="str"> :param hydraulic_results: hydraulic results at current particle</span><span class="strut"> </span></p> -<p id="t289" class="pln"><span class="str"> positions</span><span class="strut"> </span></p> -<p id="t290" class="pln"><span class="str"> :type: hydraulics.HydraulicResults</span><span class="strut"> </span></p> -<p id="t291" class="pln"><span class="str"> :param next_vertical_position: incremented vertical positions of</span><span class="strut"> </span></p> -<p id="t292" class="pln"><span class="str"> particles</span><span class="strut"> </span></p> -<p id="t293" class="pln"><span class="str"> :type: numpy.ndarray</span><span class="strut"> </span></p> -<p id="t294" class="pln"><span class="str"> :return: boundary-checked incremented position of a particle</span><span class="strut"> </span></p> -<p id="t295" class="pln"><span class="str"> :type: numpy.ndarray</span><span class="strut"> </span></p> -<p id="t296" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t297" class="pln"><span class="strut"> </span></p> -<p id="t298" class="pln"> <span class="com"># Check vertical position</span><span class="strut"> </span></p> -<p id="t299" class="stm run hide_run"> <span class="nam">depth</span> <span class="op">=</span> <span class="nam">hydraulic_results</span><span class="op">.</span><span class="nam">depth</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t300" class="pln"><span class="strut"> </span></p> -<p id="t301" class="stm run hide_run"> <span class="nam">diameter</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_particles</span><span class="op">.</span><span class="nam">diameter</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t302" class="pln"><span class="strut"> </span></p> -<p id="t303" class="stm run hide_run"> <span class="nam">boundary_length</span> <span class="op">=</span> <span class="nam">depth</span> <span class="op">-</span> <span class="nam">diameter</span><span class="strut"> </span></p> -<p id="t304" class="pln"><span class="strut"> </span></p> -<p id="t305" class="stm run hide_run"> <span class="nam">shifted_next_vertical_position</span> <span class="op">=</span> <span class="nam">next_vertical_position</span> <span class="op">+</span> <span class="nam">diameter</span><span class="op">/</span><span class="num">2</span><span class="strut"> </span></p> -<p id="t306" class="stm run hide_run"> <span class="nam">shifted_bottom_boundary_location</span> <span class="op">=</span> <span class="op">-</span><span class="nam">boundary_length</span><span class="strut"> </span></p> -<p id="t307" class="pln"><span class="strut"> </span></p> -<p id="t308" class="stm run hide_run"> <span class="nam">above_top_boundary</span> <span class="op">=</span> <span class="nam">shifted_next_vertical_position</span> <span class="op">></span> <span class="num">0</span><span class="strut"> </span></p> -<p id="t309" class="stm run hide_run"> <span class="nam">below_bottom_boundary</span> <span class="op">=</span> <span class="nam">shifted_next_vertical_position</span> <span class="op"><</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t310" class="pln"> <span class="nam">shifted_bottom_boundary_location</span><span class="strut"> </span></p> -<p id="t311" class="stm run hide_run"> <span class="nam">out_of_bounds</span> <span class="op">=</span> <span class="nam">above_top_boundary</span> <span class="op">|</span> <span class="nam">below_bottom_boundary</span><span class="strut"> </span></p> -<p id="t312" class="pln"><span class="strut"> </span></p> -<p id="t313" class="stm run hide_run"> <span class="key">if</span> <span class="nam">np</span><span class="op">.</span><span class="nam">any</span><span class="op">(</span><span class="nam">out_of_bounds</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t314" class="pln"><span class="strut"> </span></p> -<p id="t315" class="stm run hide_run"> <span class="nam">reflections</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">floor_divide</span><span class="op">(</span><span class="nam">shifted_next_vertical_position</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t316" class="pln"> <span class="nam">shifted_bottom_boundary_location</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t317" class="stm run hide_run"> <span class="nam">remainder</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">mod</span><span class="op">(</span><span class="nam">shifted_next_vertical_position</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t318" class="pln"> <span class="nam">shifted_bottom_boundary_location</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t319" class="pln"><span class="strut"> </span></p> -<p id="t320" class="stm run hide_run"> <span class="nam">reflection_mod_2</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">mod</span><span class="op">(</span><span class="nam">reflections</span><span class="op">,</span> <span class="num">2</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t321" class="stm run hide_run"> <span class="nam">odd_reflections</span> <span class="op">=</span> <span class="op">(</span><span class="nam">reflection_mod_2</span> <span class="op">==</span> <span class="num">1</span><span class="op">)</span> <span class="op">&</span> <span class="nam">out_of_bounds</span><span class="strut"> </span></p> -<p id="t322" class="stm run hide_run"> <span class="nam">even_reflections</span> <span class="op">=</span> <span class="op">(</span><span class="nam">reflection_mod_2</span> <span class="op">==</span> <span class="num">0</span><span class="op">)</span> <span class="op">&</span> <span class="nam">out_of_bounds</span><span class="strut"> </span></p> -<p id="t323" class="pln"><span class="strut"> </span></p> -<p id="t324" class="stm run hide_run"> <span class="nam">shifted_next_vertical_position</span><span class="op">[</span><span class="nam">even_reflections</span><span class="op">]</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t325" class="pln"> <span class="nam">remainder</span><span class="op">[</span><span class="nam">even_reflections</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t326" class="stm run hide_run"> <span class="nam">shifted_next_vertical_position</span><span class="op">[</span><span class="nam">odd_reflections</span><span class="op">]</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t327" class="pln"> <span class="op">-</span><span class="nam">boundary_length</span><span class="op">[</span><span class="nam">odd_reflections</span><span class="op">]</span> <span class="op">-</span> <span class="nam">remainder</span><span class="op">[</span><span class="nam">odd_reflections</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t328" class="pln"><span class="strut"> </span></p> -<p id="t329" class="stm run hide_run"> <span class="nam">next_vertical_position</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t330" class="pln"> <span class="nam">shifted_next_vertical_position</span> <span class="op">-</span> <span class="nam">diameter</span><span class="op">/</span><span class="num">2</span><span class="strut"> </span></p> -<p id="t331" class="pln"><span class="strut"> </span></p> -<p id="t332" class="stm run hide_run"> <span class="key">return</span> <span class="nam">next_vertical_position</span><span class="strut"> </span></p> -<p id="t333" class="pln"><span class="strut"> </span></p> -<p id="t334" class="stm run hide_run"> <span class="op">@</span><span class="nam">staticmethod</span><span class="strut"> </span></p> -<p id="t335" class="pln"> <span class="key">def</span> <span class="nam">_beta</span><span class="op">(</span><span class="nam">hydraulic_results</span><span class="op">,</span> <span class="nam">fall_velocity</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t336" class="pln"> <span class="str">"""Returns the factor beta used in calculation of the vertical</span><span class="strut"> </span></p> -<p id="t337" class="pln"><span class="str"> eddy diffusivity</span><span class="strut"> </span></p> -<p id="t338" class="pln"><span class="strut"> </span></p> -<p id="t339" class="pln"><span class="str"> :param hydraulic_results: hydraulic results at current particle</span><span class="strut"> </span></p> -<p id="t340" class="pln"><span class="str"> positions</span><span class="strut"> </span></p> -<p id="t341" class="pln"><span class="str"> :type: hydraulics.HydraulicResults</span><span class="strut"> </span></p> -<p id="t342" class="pln"><span class="str"> :param fall_velocity:</span><span class="strut"> </span></p> -<p id="t343" class="pln"><span class="str"> :type: numpy.ndarray</span><span class="strut"> </span></p> -<p id="t344" class="pln"><span class="str"> :return: beta factor for calculating eddy diffusivity</span><span class="strut"> </span></p> -<p id="t345" class="pln"><span class="str"> :rtype: numpy.ndarray</span><span class="strut"> </span></p> -<p id="t346" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t347" class="pln"> <span class="com"># Calculate beta coefficient</span><span class="strut"> </span></p> -<p id="t348" class="stm run hide_run"> <span class="nam">shear_velocity</span> <span class="op">=</span> <span class="nam">hydraulic_results</span><span class="op">.</span><span class="nam">shear_velocity</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t349" class="stm run hide_run"> <span class="nam">beta</span> <span class="op">=</span> <span class="num">1</span> <span class="op">+</span> <span class="num">2</span> <span class="op">*</span> <span class="op">(</span><span class="nam">np</span><span class="op">.</span><span class="nam">abs</span><span class="op">(</span><span class="op">(</span><span class="nam">fall_velocity</span> <span class="op">/</span> <span class="nam">shear_velocity</span><span class="op">)</span><span class="op">)</span> <span class="op">**</span> <span class="num">2</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t350" class="pln"><span class="strut"> </span></p> -<p id="t351" class="pln"> <span class="com"># set the values out of the function range to 3</span><span class="strut"> </span></p> -<p id="t352" class="stm run hide_run"> <span class="nam">out_of_range</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">abs</span><span class="op">(</span><span class="nam">fall_velocity</span><span class="op">)</span><span class="op">/</span><span class="nam">shear_velocity</span> <span class="op">></span> <span class="num">1</span><span class="strut"> </span></p> -<p id="t353" class="stm run hide_run"> <span class="nam">beta</span><span class="op">[</span><span class="nam">out_of_range</span><span class="op">]</span> <span class="op">=</span> <span class="num">3</span><span class="strut"> </span></p> -<p id="t354" class="pln"><span class="strut"> </span></p> -<p id="t355" class="stm run hide_run"> <span class="key">return</span> <span class="nam">beta</span><span class="strut"> </span></p> -<p id="t356" class="pln"><span class="strut"> </span></p> -<p id="t357" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_eddy_diffusivity_second_derivative</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">hydraulic_results</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t358" class="pln"> <span class="str">"""Returns the eddy diffusivity second derivative at the positions in</span><span class="strut"> </span></p> -<p id="t359" class="pln"><span class="str"> hydraulic_results</span><span class="strut"> </span></p> -<p id="t360" class="pln"><span class="strut"> </span></p> -<p id="t361" class="pln"><span class="str"> :param hydraulic_results: hydraulic results at current particle</span><span class="strut"> </span></p> -<p id="t362" class="pln"><span class="str"> positions</span><span class="strut"> </span></p> -<p id="t363" class="pln"><span class="str"> :type: hydraulics.HydraulicResults</span><span class="strut"> </span></p> -<p id="t364" class="pln"><span class="str"> :return: eddy diffusivity second derivative</span><span class="strut"> </span></p> -<p id="t365" class="pln"><span class="str"> :rtype: float</span><span class="strut"> </span></p> -<p id="t366" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t367" class="pln"><span class="strut"> </span></p> -<p id="t368" class="stm run hide_run"> <span class="nam">fall_velocity</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_particles</span><span class="op">.</span><span class="nam">fall_velocity</span><span class="op">(</span><span class="nam">hydraulic_results</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t369" class="stm run hide_run"> <span class="nam">beta</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_beta</span><span class="op">(</span><span class="nam">hydraulic_results</span><span class="op">,</span> <span class="nam">fall_velocity</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t370" class="stm run hide_run"> <span class="nam">second_derivative</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t371" class="pln"> <span class="nam">beta</span> <span class="op">*</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_eddy_viscosity_second_derivative</span><span class="op">(</span><span class="nam">hydraulic_results</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t372" class="pln"><span class="strut"> </span></p> -<p id="t373" class="stm run hide_run"> <span class="key">return</span> <span class="nam">second_derivative</span><span class="strut"> </span></p> -<p id="t374" class="pln"><span class="strut"> </span></p> -<p id="t375" class="stm run hide_run"> <span class="op">@</span><span class="nam">abstractmethod</span><span class="strut"> </span></p> -<p id="t376" class="pln"> <span class="key">def</span> <span class="nam">_eddy_viscosity</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">hydraulic_results</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t377" class="pln"> <span class="str">"""</span><span class="strut"> </span></p> -<p id="t378" class="pln"><span class="strut"> </span></p> -<p id="t379" class="pln"><span class="str"> :param hydraulic_results:</span><span class="strut"> </span></p> -<p id="t380" class="pln"><span class="str"> :return:</span><span class="strut"> </span></p> -<p id="t381" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t382" class="stm mis"> <span class="key">raise</span> <span class="nam">NotImplementedError</span><span class="strut"> </span></p> -<p id="t383" class="pln"><span class="strut"> </span></p> -<p id="t384" class="stm run hide_run"> <span class="op">@</span><span class="nam">abstractmethod</span><span class="strut"> </span></p> -<p id="t385" class="pln"> <span class="key">def</span> <span class="nam">_eddy_viscosity_gradient</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">hydraulic_results</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t386" class="pln"> <span class="str">"""</span><span class="strut"> </span></p> -<p id="t387" class="pln"><span class="strut"> </span></p> -<p id="t388" class="pln"><span class="str"> :param hydraulic_results:</span><span class="strut"> </span></p> -<p id="t389" class="pln"><span class="str"> :return:</span><span class="strut"> </span></p> -<p id="t390" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t391" class="stm mis"> <span class="key">raise</span> <span class="nam">NotImplementedError</span><span class="strut"> </span></p> -<p id="t392" class="pln"><span class="strut"> </span></p> -<p id="t393" class="stm run hide_run"> <span class="op">@</span><span class="nam">abstractmethod</span><span class="strut"> </span></p> -<p id="t394" class="pln"> <span class="key">def</span> <span class="nam">_eddy_viscosity_second_derivative</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">hydraulic_results</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t395" class="pln"> <span class="str">"""</span><span class="strut"> </span></p> -<p id="t396" class="pln"><span class="strut"> </span></p> -<p id="t397" class="pln"><span class="str"> :param hydraulic_results:</span><span class="strut"> </span></p> -<p id="t398" class="pln"><span class="str"> :return:</span><span class="strut"> </span></p> -<p id="t399" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t400" class="stm mis"> <span class="key">raise</span> <span class="nam">NotImplementedError</span><span class="strut"> </span></p> -<p id="t401" class="pln"><span class="strut"> </span></p> -<p id="t402" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_next_vertical_positions</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">hydraulic_results</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t403" class="pln"> <span class="str">"""Returns incremented vertical particle positions</span><span class="strut"> </span></p> -<p id="t404" class="pln"><span class="strut"> </span></p> -<p id="t405" class="pln"><span class="str"> :param hydraulic_results: hydraulic results at current particle</span><span class="strut"> </span></p> -<p id="t406" class="pln"><span class="str"> positions</span><span class="strut"> </span></p> -<p id="t407" class="pln"><span class="str"> :type: numpy.ndarray</span><span class="strut"> </span></p> -<p id="t408" class="pln"><span class="str"> :return: next vertical particle positions</span><span class="strut"> </span></p> -<p id="t409" class="pln"><span class="str"> :rtype: numpy.ndarray</span><span class="strut"> </span></p> -<p id="t410" class="pln"><span class="strut"> </span></p> -<p id="t411" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t412" class="pln"><span class="strut"> </span></p> -<p id="t413" class="pln"> <span class="com"># Initialize necessary variables for equation</span><span class="strut"> </span></p> -<p id="t414" class="stm run hide_run"> <span class="nam">positions</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_particles</span><span class="op">.</span><span class="nam">position</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t415" class="stm run hide_run"> <span class="nam">vertical_position</span> <span class="op">=</span> <span class="nam">positions</span><span class="op">[</span><span class="op">:</span><span class="op">,</span> <span class="num">2</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t416" class="stm run hide_run"> <span class="nam">num_particles</span> <span class="op">=</span> <span class="nam">positions</span><span class="op">.</span><span class="nam">shape</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t417" class="stm run hide_run"> <span class="nam">random_num</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_random_num</span><span class="op">(</span><span class="nam">num_particles</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t418" class="stm run hide_run"> <span class="nam">time_step_size</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_simulation_clock</span><span class="op">.</span><span class="nam">time_step_size</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t419" class="pln"><span class="strut"> </span></p> -<p id="t420" class="stm run hide_run"> <span class="nam">max_time_step</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">max_time_step</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t421" class="pln"><span class="strut"> </span></p> -<p id="t422" class="stm run hide_run"> <span class="key">if</span> <span class="op">(</span><span class="nam">max_time_step</span> <span class="op"><</span> <span class="nam">time_step_size</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t423" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="str">"Time step size is greater than maximum time "</span> <span class="op">+</span><span class="strut"> </span></p> -<p id="t424" class="pln"> <span class="str">"step of {}"</span><span class="op">.</span><span class="nam">format</span><span class="op">(</span><span class="nam">max_time_step</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t425" class="pln"><span class="strut"> </span></p> -<p id="t426" class="pln"> <span class="com"># Calculate fall velocity</span><span class="strut"> </span></p> -<p id="t427" class="stm run hide_run"> <span class="nam">fall_velocity</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_particles</span><span class="op">.</span><span class="nam">fall_velocity</span><span class="op">(</span><span class="nam">hydraulic_results</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t428" class="pln"><span class="strut"> </span></p> -<p id="t429" class="stm run hide_run"> <span class="nam">beta</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_beta</span><span class="op">(</span><span class="nam">hydraulic_results</span><span class="op">,</span> <span class="nam">fall_velocity</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t430" class="pln"><span class="strut"> </span></p> -<p id="t431" class="stm run hide_run"> <span class="nam">vertical_eddy_diffusivity_gradient</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t432" class="pln"> <span class="nam">beta</span> <span class="op">*</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_eddy_viscosity_gradient</span><span class="op">(</span><span class="nam">hydraulic_results</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t433" class="stm run hide_run"> <span class="nam">vertical_eddy_diffusivity</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t434" class="pln"> <span class="nam">beta</span> <span class="op">*</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_eddy_viscosity</span><span class="op">(</span><span class="nam">hydraulic_results</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t435" class="pln"><span class="strut"> </span></p> -<p id="t436" class="stm run hide_run"> <span class="nam">vertical_velocity</span> <span class="op">=</span> <span class="nam">hydraulic_results</span><span class="op">.</span><span class="nam">vertical_velocity</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t437" class="pln"><span class="strut"> </span></p> -<p id="t438" class="pln"> <span class="com"># Calculate the next step's vertical position</span><span class="strut"> </span></p> -<p id="t439" class="stm run hide_run"> <span class="nam">next_vertical_position</span> <span class="op">=</span> <span class="nam">vertical_position</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t440" class="pln"> <span class="op">+</span> <span class="nam">vertical_velocity</span> <span class="op">*</span> <span class="nam">time_step_size</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t441" class="pln"> <span class="op">+</span> <span class="nam">fall_velocity</span> <span class="op">*</span> <span class="nam">time_step_size</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t442" class="pln"> <span class="op">+</span> <span class="nam">vertical_eddy_diffusivity_gradient</span> <span class="op">*</span> <span class="nam">time_step_size</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t443" class="pln"> <span class="op">+</span> <span class="nam">random_num</span> <span class="op">*</span> <span class="nam">np</span><span class="op">.</span><span class="nam">sqrt</span><span class="op">(</span><span class="num">2</span> <span class="op">*</span> <span class="nam">vertical_eddy_diffusivity</span> <span class="op">*</span><span class="strut"> </span></p> -<p id="t444" class="pln"> <span class="nam">time_step_size</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t445" class="pln"><span class="strut"> </span></p> -<p id="t446" class="stm run hide_run"> <span class="key">return</span> <span class="nam">next_vertical_position</span><span class="strut"> </span></p> -<p id="t447" class="pln"><span class="strut"> </span></p> -<p id="t448" class="stm run hide_run"> <span class="key">def</span> <span class="nam">increment_positions</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">hydraulic_results</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t449" class="pln"> <span class="str">"""Increments positions of particles according to current time step.</span><span class="strut"> </span></p> -<p id="t450" class="pln"><span class="strut"> </span></p> -<p id="t451" class="pln"><span class="str"> :param hydraulic_results: hydraulic results at current particle</span><span class="strut"> </span></p> -<p id="t452" class="pln"><span class="str"> positions</span><span class="strut"> </span></p> -<p id="t453" class="pln"><span class="str"> :type hydraulic_results: fluegg.hydraulics.HydraulicResults</span><span class="strut"> </span></p> -<p id="t454" class="pln"><span class="strut"> </span></p> -<p id="t455" class="pln"><span class="str"> Raises</span><span class="strut"> </span></p> -<p id="t456" class="pln"><span class="str"> ------</span><span class="strut"> </span></p> -<p id="t457" class="pln"><span class="str"> ValueError</span><span class="strut"> </span></p> -<p id="t458" class="pln"><span class="str"> If the simulation clock time step is greater than the maximum time</span><span class="strut"> </span></p> -<p id="t459" class="pln"><span class="str"> step defined by self.max_time_step()</span><span class="strut"> </span></p> -<p id="t460" class="pln"><span class="strut"> </span></p> -<p id="t461" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t462" class="pln"><span class="strut"> </span></p> -<p id="t463" class="stm run hide_run"> <span class="nam">next_vertical_positions</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t464" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">_next_vertical_positions</span><span class="op">(</span><span class="nam">hydraulic_results</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t465" class="pln"><span class="strut"> </span></p> -<p id="t466" class="stm run hide_run"> <span class="nam">next_vertical_positions</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t467" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">_vertical_boundary_checks</span><span class="op">(</span><span class="nam">hydraulic_results</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t468" class="pln"> <span class="nam">next_vertical_positions</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t469" class="pln"><span class="strut"> </span></p> -<p id="t470" class="stm run hide_run"> <span class="nam">positions</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_particles</span><span class="op">.</span><span class="nam">position</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t471" class="pln"><span class="strut"> </span></p> -<p id="t472" class="stm run hide_run"> <span class="nam">positions</span><span class="op">[</span><span class="op">:</span><span class="op">,</span> <span class="num">2</span><span class="op">]</span> <span class="op">=</span> <span class="nam">next_vertical_positions</span><span class="strut"> </span></p> -<p id="t473" class="pln"><span class="strut"> </span></p> -<p id="t474" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_particles</span><span class="op">.</span><span class="nam">set_position</span><span class="op">(</span><span class="nam">positions</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t475" class="pln"><span class="strut"> </span></p> -<p id="t476" class="stm run hide_run"> <span class="key">def</span> <span class="nam">max_time_step</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t477" class="pln"> <span class="str">"""Finds the maximum time step required for an accurate simulation.</span><span class="strut"> </span></p> -<p id="t478" class="pln"><span class="strut"> </span></p> -<p id="t479" class="pln"><span class="str"> This is based on the the time step being <= 1/abs(vertical eddy</span><span class="strut"> </span></p> -<p id="t480" class="pln"><span class="str"> diffusivity second derivative)</span><span class="strut"> </span></p> -<p id="t481" class="pln"><span class="strut"> </span></p> -<p id="t482" class="pln"><span class="str"> :return: maximum time step criterion given the current time step</span><span class="strut"> </span></p> -<p id="t483" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t484" class="pln"><span class="strut"> </span></p> -<p id="t485" class="stm run hide_run"> <span class="nam">super</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">max_time_step</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t486" class="pln"><span class="strut"> </span></p> -<p id="t487" class="stm run hide_run"> <span class="nam">particle_positions</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_particles</span><span class="op">.</span><span class="nam">position</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t488" class="pln"><span class="strut"> </span></p> -<p id="t489" class="stm run hide_run"> <span class="nam">hydraulic_results</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t490" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">_hydraulic_model</span><span class="op">.</span><span class="nam">hydraulic_results</span><span class="op">(</span><span class="nam">particle_positions</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t491" class="stm run hide_run"> <span class="nam">criteria</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_eddy_diffusivity_second_derivative</span><span class="op">(</span><span class="nam">hydraulic_results</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t492" class="pln"><span class="strut"> </span></p> -<p id="t493" class="pln"> <span class="com"># Minimum inverse vertical eddy diffusivity second derivative is</span><span class="strut"> </span></p> -<p id="t494" class="pln"> <span class="com"># maximum time step</span><span class="strut"> </span></p> -<p id="t495" class="stm run hide_run"> <span class="nam">criteria</span> <span class="op">=</span> <span class="nam">criteria</span><span class="op">[</span><span class="nam">criteria</span> <span class="op">></span> <span class="num">0</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t496" class="stm run hide_run"> <span class="key">if</span> <span class="nam">len</span><span class="op">(</span><span class="nam">criteria</span> <span class="op">></span> <span class="num">0</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t497" class="stm mis"> <span class="nam">criteria</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">power</span><span class="op">(</span><span class="nam">criteria</span><span class="op">,</span> <span class="op">-</span><span class="num">1</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t498" class="stm mis"> <span class="nam">criteria</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">absolute</span><span class="op">(</span><span class="nam">criteria</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t499" class="stm mis"> <span class="nam">criterion</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">amin</span><span class="op">(</span><span class="nam">criteria</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t500" class="pln"> <span class="key">else</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t501" class="stm run hide_run"> <span class="nam">criterion</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">inf</span><span class="strut"> </span></p> -<p id="t502" class="pln"><span class="strut"> </span></p> -<p id="t503" class="stm run hide_run"> <span class="key">return</span> <span class="nam">criterion</span><span class="strut"> </span></p> -<p id="t504" class="pln"><span class="strut"> </span></p> -<p id="t505" class="pln"><span class="strut"> </span></p> -<p id="t506" class="stm run hide_run"><span class="key">class</span> <span class="nam">ConstantVerticalTransporter</span><span class="op">(</span><span class="nam">VerticalTransporter</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t507" class="pln"><span class="strut"> </span></p> -<p id="t508" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_eddy_viscosity</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">hydraulic_results</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t509" class="pln"> <span class="str">"""Returns the vertical eddy viscosity at the given position</span><span class="strut"> </span></p> -<p id="t510" class="pln"><span class="strut"> </span></p> -<p id="t511" class="pln"><span class="str"> :param hydraulic_results: hydraulic results at given particle positions</span><span class="strut"> </span></p> -<p id="t512" class="pln"><span class="str"> :type: hydraulics.HydraulicResults</span><span class="strut"> </span></p> -<p id="t513" class="pln"><span class="str"> :return: eddy viscosity</span><span class="strut"> </span></p> -<p id="t514" class="pln"><span class="str"> :rtype: float</span><span class="strut"> </span></p> -<p id="t515" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t516" class="pln"><span class="strut"> </span></p> -<p id="t517" class="pln"> <span class="com"># Initialize necessary information for calculation</span><span class="strut"> </span></p> -<p id="t518" class="stm run hide_run"> <span class="nam">depth</span> <span class="op">=</span> <span class="nam">hydraulic_results</span><span class="op">.</span><span class="nam">depth</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t519" class="stm run hide_run"> <span class="nam">shear_velocity</span> <span class="op">=</span> <span class="nam">hydraulic_results</span><span class="op">.</span><span class="nam">shear_velocity</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t520" class="pln"><span class="strut"> </span></p> -<p id="t521" class="pln"> <span class="com"># constant portion of profile</span><span class="strut"> </span></p> -<p id="t522" class="stm run hide_run"> <span class="nam">eddy_viscosity</span> <span class="op">=</span> <span class="num">1</span><span class="op">/</span><span class="num">15</span> <span class="op">*</span> <span class="nam">shear_velocity</span> <span class="op">*</span> <span class="nam">depth</span><span class="strut"> </span></p> -<p id="t523" class="pln"><span class="strut"> </span></p> -<p id="t524" class="pln"> <span class="com"># use fluid viscosity where eddy viscosity is less than the fluid</span><span class="strut"> </span></p> -<p id="t525" class="pln"> <span class="com"># viscosity</span><span class="strut"> </span></p> -<p id="t526" class="stm run hide_run"> <span class="nam">fluid_viscosity</span> <span class="op">=</span> <span class="nam">hydraulic_results</span><span class="op">.</span><span class="nam">water_viscosity</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t527" class="stm run hide_run"> <span class="nam">eddy_viscosity_lt_water_viscosity</span> <span class="op">=</span> <span class="nam">eddy_viscosity</span> <span class="op"><</span> <span class="nam">fluid_viscosity</span><span class="strut"> </span></p> -<p id="t528" class="stm run hide_run"> <span class="nam">eddy_viscosity</span><span class="op">[</span><span class="nam">eddy_viscosity_lt_water_viscosity</span><span class="op">]</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t529" class="pln"> <span class="nam">fluid_viscosity</span><span class="op">[</span><span class="nam">eddy_viscosity_lt_water_viscosity</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t530" class="pln"><span class="strut"> </span></p> -<p id="t531" class="stm run hide_run"> <span class="key">return</span> <span class="nam">eddy_viscosity</span><span class="strut"> </span></p> -<p id="t532" class="pln"><span class="strut"> </span></p> -<p id="t533" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_eddy_viscosity_gradient</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">hydraulic_results</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t534" class="pln"> <span class="str">"""Returns the eddy viscosity gradient with depth at the given position</span><span class="strut"> </span></p> -<p id="t535" class="pln"><span class="strut"> </span></p> -<p id="t536" class="pln"><span class="str"> :param hydraulic_results: hydraulic results at current particle</span><span class="strut"> </span></p> -<p id="t537" class="pln"><span class="str"> positions</span><span class="strut"> </span></p> -<p id="t538" class="pln"><span class="str"> :type: hydraulics.HydraulicResults</span><span class="strut"> </span></p> -<p id="t539" class="pln"><span class="str"> :return: eddy viscosity gradient m/s</span><span class="strut"> </span></p> -<p id="t540" class="pln"><span class="str"> :rtype: float</span><span class="strut"> </span></p> -<p id="t541" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t542" class="pln"><span class="strut"> </span></p> -<p id="t543" class="pln"> <span class="com"># Initialize necessary information for calculation</span><span class="strut"> </span></p> -<p id="t544" class="stm run hide_run"> <span class="nam">positions</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_particles</span><span class="op">.</span><span class="nam">position</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t545" class="stm run hide_run"> <span class="nam">num_particles</span> <span class="op">=</span> <span class="nam">positions</span><span class="op">.</span><span class="nam">shape</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t546" class="pln"> <span class="com"># Depending on profile, fill fluid eddy viscosity gradient array</span><span class="strut"> </span></p> -<p id="t547" class="stm run hide_run"> <span class="nam">eddy_viscosity_gradient</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">zeros</span><span class="op">(</span><span class="nam">num_particles</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t548" class="pln"><span class="strut"> </span></p> -<p id="t549" class="stm run hide_run"> <span class="key">return</span> <span class="nam">eddy_viscosity_gradient</span><span class="strut"> </span></p> -<p id="t550" class="pln"><span class="strut"> </span></p> -<p id="t551" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_eddy_viscosity_second_derivative</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">hydraulic_results</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t552" class="pln"> <span class="str">"""Returns the eddy viscosity second derivative with depth at the given</span><span class="strut"> </span></p> -<p id="t553" class="pln"><span class="str"> position</span><span class="strut"> </span></p> -<p id="t554" class="pln"><span class="strut"> </span></p> -<p id="t555" class="pln"><span class="str"> :param hydraulic_results: hydraulic results at current particle</span><span class="strut"> </span></p> -<p id="t556" class="pln"><span class="str"> positions</span><span class="strut"> </span></p> -<p id="t557" class="pln"><span class="str"> :type: hydraulics.HydraulicResults</span><span class="strut"> </span></p> -<p id="t558" class="pln"><span class="str"> :return: eddy viscosity second derivative m/s**2</span><span class="strut"> </span></p> -<p id="t559" class="pln"><span class="str"> :rtype: float</span><span class="strut"> </span></p> -<p id="t560" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t561" class="pln"><span class="strut"> </span></p> -<p id="t562" class="pln"> <span class="com"># Initialize necessary information for calculation</span><span class="strut"> </span></p> -<p id="t563" class="stm run hide_run"> <span class="nam">positions</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_particles</span><span class="op">.</span><span class="nam">position</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t564" class="stm run hide_run"> <span class="nam">num_particles</span> <span class="op">=</span> <span class="nam">positions</span><span class="op">.</span><span class="nam">shape</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t565" class="pln"> <span class="com"># Depending on profile, fill fluid eddy viscosity gradient array</span><span class="strut"> </span></p> -<p id="t566" class="stm run hide_run"> <span class="nam">eddy_viscosity_second_derivative</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">zeros</span><span class="op">(</span><span class="nam">num_particles</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t567" class="pln"><span class="strut"> </span></p> -<p id="t568" class="stm run hide_run"> <span class="key">return</span> <span class="nam">eddy_viscosity_second_derivative</span><span class="strut"> </span></p> -<p id="t569" class="pln"><span class="strut"> </span></p> -<p id="t570" class="pln"><span class="strut"> </span></p> -<p id="t571" class="stm run hide_run"><span class="key">class</span> <span class="nam">ParabolicVerticalTransporter</span><span class="op">(</span><span class="nam">VerticalTransporter</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t572" class="pln"><span class="strut"> </span></p> -<p id="t573" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_eddy_viscosity</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">hydraulic_results</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t574" class="pln"> <span class="str">"""Returns the vertical eddy viscosity at the given position</span><span class="strut"> </span></p> -<p id="t575" class="pln"><span class="strut"> </span></p> -<p id="t576" class="pln"><span class="str"> :param hydraulic_results: hydraulic results at given particle positions</span><span class="strut"> </span></p> -<p id="t577" class="pln"><span class="str"> :type: hydraulics.HydraulicResults</span><span class="strut"> </span></p> -<p id="t578" class="pln"><span class="str"> :return: eddy viscosity</span><span class="strut"> </span></p> -<p id="t579" class="pln"><span class="str"> :rtype: float</span><span class="strut"> </span></p> -<p id="t580" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t581" class="pln"><span class="strut"> </span></p> -<p id="t582" class="pln"> <span class="com"># Initialize necessary information for calculation</span><span class="strut"> </span></p> -<p id="t583" class="stm mis"> <span class="nam">positions</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_particles</span><span class="op">.</span><span class="nam">position</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t584" class="stm mis"> <span class="nam">vertical_position</span> <span class="op">=</span> <span class="nam">positions</span><span class="op">[</span><span class="op">:</span><span class="op">,</span> <span class="num">2</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t585" class="stm mis"> <span class="nam">depth</span> <span class="op">=</span> <span class="nam">hydraulic_results</span><span class="op">.</span><span class="nam">depth</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t586" class="stm mis"> <span class="nam">shear_velocity</span> <span class="op">=</span> <span class="nam">hydraulic_results</span><span class="op">.</span><span class="nam">shear_velocity</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t587" class="pln"><span class="strut"> </span></p> -<p id="t588" class="stm mis"> <span class="nam">distance_above_bed</span> <span class="op">=</span> <span class="nam">depth</span> <span class="op">+</span> <span class="nam">vertical_position</span><span class="strut"> </span></p> -<p id="t589" class="pln"><span class="strut"> </span></p> -<p id="t590" class="pln"> <span class="com"># parabolic portion of profile</span><span class="strut"> </span></p> -<p id="t591" class="stm mis"> <span class="nam">time_step_size</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_simulation_clock</span><span class="op">.</span><span class="nam">time_step_size</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t592" class="stm mis"> <span class="nam">eddy_viscosity_gradient</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t593" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">_eddy_viscosity_gradient</span><span class="op">(</span><span class="nam">hydraulic_results</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t594" class="pln"><span class="strut"> </span></p> -<p id="t595" class="stm mis"> <span class="nam">offset_distance</span> <span class="op">=</span> <span class="num">0.5</span> <span class="op">*</span> <span class="nam">eddy_viscosity_gradient</span> <span class="op">*</span> <span class="nam">time_step_size</span><span class="strut"> </span></p> -<p id="t596" class="stm mis"> <span class="nam">distance_above_bed_offset</span> <span class="op">=</span> <span class="nam">distance_above_bed</span> <span class="op">+</span> <span class="nam">offset_distance</span><span class="strut"> </span></p> -<p id="t597" class="stm mis"> <span class="nam">eddy_viscosity</span> <span class="op">=</span> <span class="nam">hydraulics</span><span class="op">.</span><span class="nam">VON_KARMAN_CONSTANT</span> <span class="op">*</span> <span class="nam">shear_velocity</span> <span class="op">*</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t598" class="pln"> <span class="nam">distance_above_bed_offset</span> <span class="op">*</span> <span class="op">(</span><span class="num">1</span> <span class="op">-</span> <span class="nam">distance_above_bed_offset</span> <span class="op">/</span> <span class="nam">depth</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t599" class="pln"><span class="strut"> </span></p> -<p id="t600" class="pln"> <span class="com"># use fluid viscosity where eddy viscosity is less than the fluid</span><span class="strut"> </span></p> -<p id="t601" class="pln"> <span class="com"># viscosity</span><span class="strut"> </span></p> -<p id="t602" class="stm mis"> <span class="nam">fluid_viscosity</span> <span class="op">=</span> <span class="nam">hydraulic_results</span><span class="op">.</span><span class="nam">water_viscosity</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t603" class="stm mis"> <span class="nam">eddy_viscosity_lt_water_viscosity</span> <span class="op">=</span> <span class="nam">eddy_viscosity</span> <span class="op"><</span> <span class="nam">fluid_viscosity</span><span class="strut"> </span></p> -<p id="t604" class="stm mis"> <span class="nam">eddy_viscosity</span><span class="op">[</span><span class="nam">eddy_viscosity_lt_water_viscosity</span><span class="op">]</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t605" class="pln"> <span class="nam">fluid_viscosity</span><span class="op">[</span><span class="nam">eddy_viscosity_lt_water_viscosity</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t606" class="pln"><span class="strut"> </span></p> -<p id="t607" class="stm mis"> <span class="key">return</span> <span class="nam">eddy_viscosity</span><span class="strut"> </span></p> -<p id="t608" class="pln"><span class="strut"> </span></p> -<p id="t609" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_eddy_viscosity_gradient</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">hydraulic_results</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t610" class="pln"> <span class="str">"""Returns the eddy viscosity gradient with depth at the given position</span><span class="strut"> </span></p> -<p id="t611" class="pln"><span class="strut"> </span></p> -<p id="t612" class="pln"><span class="str"> :param hydraulic_results: hydraulic results at current particle</span><span class="strut"> </span></p> -<p id="t613" class="pln"><span class="str"> positions</span><span class="strut"> </span></p> -<p id="t614" class="pln"><span class="str"> :type: hydraulics.HydraulicResults</span><span class="strut"> </span></p> -<p id="t615" class="pln"><span class="str"> :return: eddy viscosity gradient m/s</span><span class="strut"> </span></p> -<p id="t616" class="pln"><span class="str"> :rtype: float</span><span class="strut"> </span></p> -<p id="t617" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t618" class="pln"><span class="strut"> </span></p> -<p id="t619" class="pln"> <span class="com"># Initialize necessary information for calculation</span><span class="strut"> </span></p> -<p id="t620" class="stm mis"> <span class="nam">positions</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_particles</span><span class="op">.</span><span class="nam">position</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t621" class="stm mis"> <span class="nam">vertical_position</span> <span class="op">=</span> <span class="nam">positions</span><span class="op">[</span><span class="op">:</span><span class="op">,</span> <span class="num">2</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t622" class="stm mis"> <span class="nam">depth</span> <span class="op">=</span> <span class="nam">hydraulic_results</span><span class="op">.</span><span class="nam">depth</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t623" class="stm mis"> <span class="nam">shear_velocity</span> <span class="op">=</span> <span class="nam">hydraulic_results</span><span class="op">.</span><span class="nam">shear_velocity</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t624" class="pln"><span class="strut"> </span></p> -<p id="t625" class="stm mis"> <span class="nam">distance_above_bed</span> <span class="op">=</span> <span class="nam">vertical_position</span> <span class="op">+</span> <span class="nam">depth</span><span class="strut"> </span></p> -<p id="t626" class="pln"><span class="strut"> </span></p> -<p id="t627" class="stm mis"> <span class="nam">eddy_viscosity_gradient</span> <span class="op">=</span> <span class="nam">hydraulics</span><span class="op">.</span><span class="nam">VON_KARMAN_CONSTANT</span> <span class="op">*</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t628" class="pln"> <span class="nam">shear_velocity</span> <span class="op">*</span> <span class="op">(</span><span class="num">1</span> <span class="op">-</span> <span class="num">2</span><span class="op">*</span><span class="nam">distance_above_bed</span><span class="op">/</span><span class="nam">depth</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t629" class="pln"><span class="strut"> </span></p> -<p id="t630" class="stm mis"> <span class="key">return</span> <span class="nam">eddy_viscosity_gradient</span><span class="strut"> </span></p> -<p id="t631" class="pln"><span class="strut"> </span></p> -<p id="t632" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_eddy_viscosity_second_derivative</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">hydraulic_results</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t633" class="pln"> <span class="str">"""Returns the eddy viscosity second derivative with depth at the given</span><span class="strut"> </span></p> -<p id="t634" class="pln"><span class="str"> position</span><span class="strut"> </span></p> -<p id="t635" class="pln"><span class="strut"> </span></p> -<p id="t636" class="pln"><span class="str"> :param hydraulic_results: hydraulic results at current particle</span><span class="strut"> </span></p> -<p id="t637" class="pln"><span class="str"> positions</span><span class="strut"> </span></p> -<p id="t638" class="pln"><span class="str"> :type: hydraulics.HydraulicResults</span><span class="strut"> </span></p> -<p id="t639" class="pln"><span class="str"> :return: eddy viscosity second derivative m/s**2</span><span class="strut"> </span></p> -<p id="t640" class="pln"><span class="str"> :rtype: float</span><span class="strut"> </span></p> -<p id="t641" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t642" class="pln"><span class="strut"> </span></p> -<p id="t643" class="pln"> <span class="com"># Initialize necessary information for calculation</span><span class="strut"> </span></p> -<p id="t644" class="stm mis"> <span class="nam">depth</span> <span class="op">=</span> <span class="nam">hydraulic_results</span><span class="op">.</span><span class="nam">depth</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t645" class="stm mis"> <span class="nam">shear_velocity</span> <span class="op">=</span> <span class="nam">hydraulic_results</span><span class="op">.</span><span class="nam">shear_velocity</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t646" class="pln"><span class="strut"> </span></p> -<p id="t647" class="stm mis"> <span class="nam">eddy_viscosity_second_derivative</span> <span class="op">=</span> <span class="op">-</span> <span class="nam">hydraulics</span><span class="op">.</span><span class="nam">VON_KARMAN_CONSTANT</span> <span class="op">*</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t648" class="pln"> <span class="nam">shear_velocity</span> <span class="op">*</span> <span class="num">2</span> <span class="op">/</span> <span class="nam">depth</span><span class="strut"> </span></p> -<p id="t649" class="pln"><span class="strut"> </span></p> -<p id="t650" class="stm mis"> <span class="key">return</span> <span class="nam">eddy_viscosity_second_derivative</span><span class="strut"> </span></p> -<p id="t651" class="pln"><span class="strut"> </span></p> -<p id="t652" class="pln"><span class="strut"> </span></p> -<p id="t653" class="stm run hide_run"><span class="key">class</span> <span class="nam">ParabolicConstantVerticalTransporter</span><span class="op">(</span><span class="nam">VerticalTransporter</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t654" class="pln"><span class="strut"> </span></p> -<p id="t655" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_eddy_viscosity</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">hydraulic_results</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t656" class="pln"> <span class="str">"""Returns the vertical eddy viscosity at the given position</span><span class="strut"> </span></p> -<p id="t657" class="pln"><span class="strut"> </span></p> -<p id="t658" class="pln"><span class="str"> :param hydraulic_results: hydraulic results at given particle positions</span><span class="strut"> </span></p> -<p id="t659" class="pln"><span class="str"> :type: hydraulics.HydraulicResults</span><span class="strut"> </span></p> -<p id="t660" class="pln"><span class="str"> :return: eddy viscosity</span><span class="strut"> </span></p> -<p id="t661" class="pln"><span class="str"> :rtype: float</span><span class="strut"> </span></p> -<p id="t662" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t663" class="pln"><span class="strut"> </span></p> -<p id="t664" class="pln"> <span class="com"># Initialize necessary information for calculation</span><span class="strut"> </span></p> -<p id="t665" class="stm run hide_run"> <span class="nam">positions</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_particles</span><span class="op">.</span><span class="nam">position</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t666" class="stm run hide_run"> <span class="nam">vertical_position</span> <span class="op">=</span> <span class="nam">positions</span><span class="op">[</span><span class="op">:</span><span class="op">,</span> <span class="num">2</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t667" class="stm run hide_run"> <span class="nam">num_particles</span> <span class="op">=</span> <span class="nam">positions</span><span class="op">.</span><span class="nam">shape</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t668" class="stm run hide_run"> <span class="nam">depth</span> <span class="op">=</span> <span class="nam">hydraulic_results</span><span class="op">.</span><span class="nam">depth</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t669" class="stm run hide_run"> <span class="nam">shear_velocity</span> <span class="op">=</span> <span class="nam">hydraulic_results</span><span class="op">.</span><span class="nam">shear_velocity</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t670" class="pln"><span class="strut"> </span></p> -<p id="t671" class="stm run hide_run"> <span class="nam">distance_above_bed</span> <span class="op">=</span> <span class="nam">depth</span> <span class="op">+</span> <span class="nam">vertical_position</span><span class="strut"> </span></p> -<p id="t672" class="pln"><span class="strut"> </span></p> -<p id="t673" class="stm run hide_run"> <span class="nam">eddy_viscosity</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">zeros</span><span class="op">(</span><span class="nam">num_particles</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t674" class="pln"><span class="strut"> </span></p> -<p id="t675" class="pln"> <span class="com"># constant portion of profile</span><span class="strut"> </span></p> -<p id="t676" class="stm run hide_run"> <span class="nam">constant</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">where</span><span class="op">(</span><span class="nam">distance_above_bed</span> <span class="op">/</span> <span class="nam">depth</span> <span class="op">>=</span> <span class="num">0.5</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t677" class="stm run hide_run"> <span class="nam">eddy_viscosity</span><span class="op">[</span><span class="nam">constant</span><span class="op">]</span> <span class="op">=</span> <span class="num">0.25</span> <span class="op">*</span> <span class="nam">hydraulics</span><span class="op">.</span><span class="nam">VON_KARMAN_CONSTANT</span> <span class="op">*</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t678" class="pln"> <span class="nam">shear_velocity</span><span class="op">[</span><span class="nam">constant</span><span class="op">]</span> <span class="op">*</span> <span class="nam">depth</span><span class="op">[</span><span class="nam">constant</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t679" class="pln"><span class="strut"> </span></p> -<p id="t680" class="pln"> <span class="com"># parabolic portion of profile</span><span class="strut"> </span></p> -<p id="t681" class="stm run hide_run"> <span class="nam">parabolic</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">where</span><span class="op">(</span><span class="nam">distance_above_bed</span> <span class="op">/</span> <span class="nam">depth</span> <span class="op"><</span> <span class="num">0.5</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t682" class="stm run hide_run"> <span class="nam">time_step_size</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_simulation_clock</span><span class="op">.</span><span class="nam">time_step_size</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t683" class="stm run hide_run"> <span class="nam">eddy_viscosity_gradient</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t684" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">_eddy_viscosity_gradient</span><span class="op">(</span><span class="nam">hydraulic_results</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t685" class="pln"><span class="strut"> </span></p> -<p id="t686" class="stm run hide_run"> <span class="nam">offset_distance</span> <span class="op">=</span> <span class="num">0.5</span> <span class="op">*</span> <span class="nam">eddy_viscosity_gradient</span> <span class="op">*</span> <span class="nam">time_step_size</span><span class="strut"> </span></p> -<p id="t687" class="stm run hide_run"> <span class="nam">distance_above_bed_offset</span> <span class="op">=</span> <span class="nam">distance_above_bed</span> <span class="op">+</span> <span class="nam">offset_distance</span><span class="strut"> </span></p> -<p id="t688" class="stm run hide_run"> <span class="nam">eddy_viscosity</span><span class="op">[</span><span class="nam">parabolic</span><span class="op">]</span> <span class="op">=</span> <span class="nam">hydraulics</span><span class="op">.</span><span class="nam">VON_KARMAN_CONSTANT</span> <span class="op">*</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t689" class="pln"> <span class="nam">shear_velocity</span><span class="op">[</span><span class="nam">parabolic</span><span class="op">]</span> <span class="op">*</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t690" class="pln"> <span class="nam">distance_above_bed_offset</span><span class="op">[</span><span class="nam">parabolic</span><span class="op">]</span> <span class="op">*</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t691" class="pln"> <span class="op">(</span><span class="num">1</span> <span class="op">-</span> <span class="nam">distance_above_bed_offset</span><span class="op">[</span><span class="nam">parabolic</span><span class="op">]</span> <span class="op">/</span> <span class="nam">depth</span><span class="op">[</span><span class="nam">parabolic</span><span class="op">]</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t692" class="pln"><span class="strut"> </span></p> -<p id="t693" class="pln"> <span class="com"># use fluid viscosity where eddy viscosity is less than the fluid</span><span class="strut"> </span></p> -<p id="t694" class="pln"> <span class="com"># viscosity</span><span class="strut"> </span></p> -<p id="t695" class="stm run hide_run"> <span class="nam">fluid_viscosity</span> <span class="op">=</span> <span class="nam">hydraulic_results</span><span class="op">.</span><span class="nam">water_viscosity</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t696" class="stm run hide_run"> <span class="nam">eddy_viscosity_lt_water_viscosity</span> <span class="op">=</span> <span class="nam">eddy_viscosity</span> <span class="op"><</span> <span class="nam">fluid_viscosity</span><span class="strut"> </span></p> -<p id="t697" class="stm run hide_run"> <span class="nam">eddy_viscosity</span><span class="op">[</span><span class="nam">eddy_viscosity_lt_water_viscosity</span><span class="op">]</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t698" class="pln"> <span class="nam">fluid_viscosity</span><span class="op">[</span><span class="nam">eddy_viscosity_lt_water_viscosity</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t699" class="pln"><span class="strut"> </span></p> -<p id="t700" class="stm run hide_run"> <span class="key">return</span> <span class="nam">eddy_viscosity</span><span class="strut"> </span></p> -<p id="t701" class="pln"><span class="strut"> </span></p> -<p id="t702" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_eddy_viscosity_gradient</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">hydraulic_results</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t703" class="pln"> <span class="str">"""Returns the eddy viscosity gradient with depth at the given position</span><span class="strut"> </span></p> -<p id="t704" class="pln"><span class="strut"> </span></p> -<p id="t705" class="pln"><span class="str"> :param hydraulic_results: hydraulic results at current particle</span><span class="strut"> </span></p> -<p id="t706" class="pln"><span class="str"> positions</span><span class="strut"> </span></p> -<p id="t707" class="pln"><span class="str"> :type: hydraulics.HydraulicResults</span><span class="strut"> </span></p> -<p id="t708" class="pln"><span class="str"> :return: eddy viscosity gradient m/s</span><span class="strut"> </span></p> -<p id="t709" class="pln"><span class="str"> :rtype: float</span><span class="strut"> </span></p> -<p id="t710" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t711" class="pln"><span class="strut"> </span></p> -<p id="t712" class="pln"> <span class="com"># Initialize necessary information for calculation</span><span class="strut"> </span></p> -<p id="t713" class="stm run hide_run"> <span class="nam">positions</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_particles</span><span class="op">.</span><span class="nam">position</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t714" class="stm run hide_run"> <span class="nam">vertical_position</span> <span class="op">=</span> <span class="nam">positions</span><span class="op">[</span><span class="op">:</span><span class="op">,</span> <span class="num">2</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t715" class="stm run hide_run"> <span class="nam">num_particles</span> <span class="op">=</span> <span class="nam">positions</span><span class="op">.</span><span class="nam">shape</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t716" class="stm run hide_run"> <span class="nam">depth</span> <span class="op">=</span> <span class="nam">hydraulic_results</span><span class="op">.</span><span class="nam">depth</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t717" class="stm run hide_run"> <span class="nam">shear_velocity</span> <span class="op">=</span> <span class="nam">hydraulic_results</span><span class="op">.</span><span class="nam">shear_velocity</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t718" class="pln"><span class="strut"> </span></p> -<p id="t719" class="stm run hide_run"> <span class="nam">distance_above_bed</span> <span class="op">=</span> <span class="nam">vertical_position</span> <span class="op">+</span> <span class="nam">depth</span><span class="strut"> </span></p> -<p id="t720" class="pln"><span class="strut"> </span></p> -<p id="t721" class="pln"> <span class="com"># Depending on profile, fill fluid eddy viscosity gradient array</span><span class="strut"> </span></p> -<p id="t722" class="stm run hide_run"> <span class="nam">eddy_viscosity_gradient</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">zeros</span><span class="op">(</span><span class="nam">num_particles</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t723" class="pln"><span class="strut"> </span></p> -<p id="t724" class="stm run hide_run"> <span class="nam">constant</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">where</span><span class="op">(</span><span class="nam">distance_above_bed</span><span class="op">/</span><span class="nam">depth</span> <span class="op">>=</span> <span class="num">0.5</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t725" class="stm run hide_run"> <span class="nam">eddy_viscosity_gradient</span><span class="op">[</span><span class="nam">constant</span><span class="op">]</span> <span class="op">=</span> <span class="num">0.0</span><span class="strut"> </span></p> -<p id="t726" class="pln"><span class="strut"> </span></p> -<p id="t727" class="stm run hide_run"> <span class="nam">parabolic</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">where</span><span class="op">(</span><span class="nam">distance_above_bed</span><span class="op">/</span><span class="nam">depth</span> <span class="op"><</span> <span class="num">0.5</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t728" class="stm run hide_run"> <span class="nam">eddy_viscosity_gradient</span><span class="op">[</span><span class="nam">parabolic</span><span class="op">]</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t729" class="pln"> <span class="nam">hydraulics</span><span class="op">.</span><span class="nam">VON_KARMAN_CONSTANT</span> <span class="op">*</span> <span class="nam">shear_velocity</span><span class="op">[</span><span class="nam">parabolic</span><span class="op">]</span> <span class="op">*</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t730" class="pln"> <span class="op">(</span><span class="num">1</span> <span class="op">-</span> <span class="num">2</span><span class="op">*</span><span class="nam">distance_above_bed</span><span class="op">[</span><span class="nam">parabolic</span><span class="op">]</span><span class="op">/</span><span class="nam">depth</span><span class="op">[</span><span class="nam">parabolic</span><span class="op">]</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t731" class="pln"><span class="strut"> </span></p> -<p id="t732" class="stm run hide_run"> <span class="key">return</span> <span class="nam">eddy_viscosity_gradient</span><span class="strut"> </span></p> -<p id="t733" class="pln"><span class="strut"> </span></p> -<p id="t734" class="stm run hide_run"> <span class="key">def</span> <span class="nam">_eddy_viscosity_second_derivative</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">hydraulic_results</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t735" class="pln"> <span class="str">"""Returns the eddy viscosity second derivative with depth at the given</span><span class="strut"> </span></p> -<p id="t736" class="pln"><span class="str"> position</span><span class="strut"> </span></p> -<p id="t737" class="pln"><span class="strut"> </span></p> -<p id="t738" class="pln"><span class="str"> :param hydraulic_results: hydraulic results at current particle</span><span class="strut"> </span></p> -<p id="t739" class="pln"><span class="str"> positions</span><span class="strut"> </span></p> -<p id="t740" class="pln"><span class="str"> :type: hydraulics.HydraulicResults</span><span class="strut"> </span></p> -<p id="t741" class="pln"><span class="str"> :return: eddy viscosity second derivative m/s**2</span><span class="strut"> </span></p> -<p id="t742" class="pln"><span class="str"> :rtype: float</span><span class="strut"> </span></p> -<p id="t743" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t744" class="pln"><span class="strut"> </span></p> -<p id="t745" class="pln"> <span class="com"># Initialize necessary information for calculation</span><span class="strut"> </span></p> -<p id="t746" class="stm run hide_run"> <span class="nam">positions</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_particles</span><span class="op">.</span><span class="nam">position</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t747" class="stm run hide_run"> <span class="nam">vertical_position</span> <span class="op">=</span> <span class="nam">positions</span><span class="op">[</span><span class="op">:</span><span class="op">,</span> <span class="num">2</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t748" class="stm run hide_run"> <span class="nam">num_particles</span> <span class="op">=</span> <span class="nam">positions</span><span class="op">.</span><span class="nam">shape</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t749" class="stm run hide_run"> <span class="nam">depth</span> <span class="op">=</span> <span class="nam">hydraulic_results</span><span class="op">.</span><span class="nam">depth</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t750" class="stm run hide_run"> <span class="nam">shear_velocity</span> <span class="op">=</span> <span class="nam">hydraulic_results</span><span class="op">.</span><span class="nam">shear_velocity</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t751" class="pln"><span class="strut"> </span></p> -<p id="t752" class="stm run hide_run"> <span class="nam">distance_above_bed</span> <span class="op">=</span> <span class="nam">vertical_position</span> <span class="op">+</span> <span class="nam">depth</span><span class="strut"> </span></p> -<p id="t753" class="pln"><span class="strut"> </span></p> -<p id="t754" class="pln"> <span class="com"># Depending on profile, fill fluid eddy viscosity gradient array</span><span class="strut"> </span></p> -<p id="t755" class="stm run hide_run"> <span class="nam">eddy_viscosity_second_derivative</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">zeros</span><span class="op">(</span><span class="nam">num_particles</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t756" class="pln"><span class="strut"> </span></p> -<p id="t757" class="stm run hide_run"> <span class="nam">constant</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">where</span><span class="op">(</span><span class="nam">distance_above_bed</span> <span class="op">/</span> <span class="nam">depth</span> <span class="op">>=</span> <span class="num">0.5</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t758" class="stm run hide_run"> <span class="nam">eddy_viscosity_second_derivative</span><span class="op">[</span><span class="nam">constant</span><span class="op">]</span> <span class="op">=</span> <span class="num">0.0</span><span class="strut"> </span></p> -<p id="t759" class="pln"><span class="strut"> </span></p> -<p id="t760" class="stm run hide_run"> <span class="nam">parabolic</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">where</span><span class="op">(</span><span class="nam">distance_above_bed</span> <span class="op">/</span> <span class="nam">depth</span> <span class="op"><</span> <span class="num">0.5</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t761" class="stm run hide_run"> <span class="nam">eddy_viscosity_second_derivative</span><span class="op">[</span><span class="nam">parabolic</span><span class="op">]</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t762" class="pln"> <span class="op">-</span> <span class="nam">hydraulics</span><span class="op">.</span><span class="nam">VON_KARMAN_CONSTANT</span> <span class="op">*</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t763" class="pln"> <span class="nam">shear_velocity</span><span class="op">[</span><span class="nam">parabolic</span><span class="op">]</span> <span class="op">*</span> <span class="num">2</span> <span class="op">/</span> <span class="nam">depth</span><span class="op">[</span><span class="nam">parabolic</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t764" class="pln"><span class="strut"> </span></p> -<p id="t765" class="stm run hide_run"> <span class="key">return</span> <span class="nam">eddy_viscosity_second_derivative</span><span class="strut"> </span></p> -<p id="t766" class="pln"><span class="strut"> </span></p> -<p id="t767" class="pln"><span class="strut"> </span></p> -<p id="t768" class="stm run hide_run"><span class="key">def</span> <span class="nam">fluegg_transporter_class_factory</span><span class="op">(</span><span class="nam">vertical_turbulence</span><span class="op">=</span><span class="str">'parabolic-constant'</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t769" class="pln"> <span class="nam">advection_direction</span><span class="op">=</span><span class="str">'forward'</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t770" class="pln"> <span class="str">"""</span><span class="strut"> </span></p> -<p id="t771" class="pln"><span class="strut"> </span></p> -<p id="t772" class="pln"><span class="str"> :param vertical_turbulence:</span><span class="strut"> </span></p> -<p id="t773" class="pln"><span class="str"> :param advection_direction:</span><span class="strut"> </span></p> -<p id="t774" class="pln"><span class="str"> :return: class</span><span class="strut"> </span></p> -<p id="t775" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t776" class="pln"><span class="strut"> </span></p> -<p id="t777" class="stm run hide_run"> <span class="key">if</span> <span class="nam">vertical_turbulence</span> <span class="op">==</span> <span class="str">'constant'</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t778" class="stm mis"> <span class="nam">vertical_base_class</span> <span class="op">=</span> <span class="nam">ConstantVerticalTransporter</span><span class="strut"> </span></p> -<p id="t779" class="stm run hide_run"> <span class="key">elif</span> <span class="nam">vertical_turbulence</span> <span class="op">==</span> <span class="str">'parabolic'</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t780" class="stm mis"> <span class="nam">vertical_base_class</span> <span class="op">=</span> <span class="nam">ParabolicVerticalTransporter</span><span class="strut"> </span></p> -<p id="t781" class="stm run hide_run"> <span class="key">elif</span> <span class="nam">vertical_turbulence</span> <span class="op">==</span> <span class="str">'parabolic-constant'</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t782" class="stm run hide_run"> <span class="nam">vertical_base_class</span> <span class="op">=</span> <span class="nam">ParabolicConstantVerticalTransporter</span><span class="strut"> </span></p> -<p id="t783" class="pln"> <span class="key">else</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t784" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="str">"vertical_turbulence must be \'constant\' "</span> <span class="op">+</span><span class="strut"> </span></p> -<p id="t785" class="pln"> <span class="str">"\'parabolic\' or \'parabolic-constant\'."</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t786" class="pln"><span class="strut"> </span></p> -<p id="t787" class="stm run hide_run"> <span class="key">if</span> <span class="nam">advection_direction</span> <span class="op">==</span> <span class="str">'forward'</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t788" class="stm run hide_run"> <span class="nam">longitudinal_base_class</span> <span class="op">=</span> <span class="nam">LongitudinalTransporter</span><span class="strut"> </span></p> -<p id="t789" class="stm mis"> <span class="key">elif</span> <span class="nam">advection_direction</span> <span class="op">==</span> <span class="str">'reverse'</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t790" class="stm mis"> <span class="nam">longitudinal_base_class</span> <span class="op">=</span> <span class="nam">ReverseLongitudinalTransporter</span><span class="strut"> </span></p> -<p id="t791" class="pln"> <span class="key">else</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t792" class="stm mis"> <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="str">"advection_direction must be \'forward\' or "</span> <span class="op">+</span><span class="strut"> </span></p> -<p id="t793" class="pln"> <span class="str">"\'reverse\'."</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t794" class="pln"><span class="strut"> </span></p> -<p id="t795" class="stm run hide_run"> <span class="key">class</span> <span class="nam">FluEggTransporter</span><span class="op">(</span><span class="nam">vertical_base_class</span><span class="op">,</span> <span class="nam">LateralTransporter</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t796" class="pln"> <span class="nam">longitudinal_base_class</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t797" class="pln"> <span class="str">"""This class transports particles through hydraulic cells</span><span class="strut"> </span></p> -<p id="t798" class="pln"><span class="str"> using a parabolic-constant diffusivity profile.</span><span class="strut"> </span></p> -<p id="t799" class="pln"><span class="strut"> </span></p> -<p id="t800" class="pln"><span class="str"> :param LateralTransporter: A lateral transporter model</span><span class="strut"> </span></p> -<p id="t801" class="pln"><span class="str"> :type: transporter.LateralTranslporter</span><span class="strut"> </span></p> -<p id="t802" class="pln"><span class="str"> :param longitudinal_base_class: A longitudinal transporter model</span><span class="strut"> </span></p> -<p id="t803" class="pln"><span class="str"> :type: transporter.Translporter</span><span class="strut"> </span></p> -<p id="t804" class="pln"><span class="str"> :param vertical_base_class: A vertical transporter model</span><span class="strut"> </span></p> -<p id="t805" class="pln"><span class="str"> :type: transporter.Transporter</span><span class="strut"> </span></p> -<p id="t806" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t807" class="pln"><span class="strut"> </span></p> -<p id="t808" class="stm run hide_run"> <span class="key">def</span> <span class="nam">increment_positions</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">hydraulic_results</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t809" class="pln"> <span class="str">"""Increments particle positions to the next time step</span><span class="strut"> </span></p> -<p id="t810" class="pln"><span class="strut"> </span></p> -<p id="t811" class="pln"><span class="str"> :param hydraulic_results: hydraulic results at current particle</span><span class="strut"> </span></p> -<p id="t812" class="pln"><span class="str"> positions</span><span class="strut"> </span></p> -<p id="t813" class="pln"><span class="str"> :type: hydraulics.HydraulicResults</span><span class="strut"> </span></p> -<p id="t814" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t815" class="pln"><span class="strut"> </span></p> -<p id="t816" class="pln"> <span class="com"># Calculate new particle positions</span><span class="strut"> </span></p> -<p id="t817" class="pln"><span class="strut"> </span></p> -<p id="t818" class="stm run hide_run"> <span class="nam">longitudinal_positions</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t819" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">_next_longitudinal_positions</span><span class="op">(</span><span class="nam">hydraulic_results</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t820" class="pln"><span class="strut"> </span></p> -<p id="t821" class="stm run hide_run"> <span class="nam">lateral_positions</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_next_lateral_positions</span><span class="op">(</span><span class="nam">hydraulic_results</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t822" class="stm run hide_run"> <span class="nam">lateral_positions</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t823" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">_lateral_boundary_checks</span><span class="op">(</span><span class="nam">hydraulic_results</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t824" class="pln"> <span class="nam">lateral_positions</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t825" class="pln"><span class="strut"> </span></p> -<p id="t826" class="stm run hide_run"> <span class="nam">vertical_positions</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t827" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">_next_vertical_positions</span><span class="op">(</span><span class="nam">hydraulic_results</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t828" class="stm run hide_run"> <span class="nam">vertical_positions</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t829" class="pln"> <span class="nam">self</span><span class="op">.</span><span class="nam">_vertical_boundary_checks</span><span class="op">(</span><span class="nam">hydraulic_results</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t830" class="pln"> <span class="nam">vertical_positions</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t831" class="pln"><span class="strut"> </span></p> -<p id="t832" class="pln"> <span class="com"># [s, n, z]</span><span class="strut"> </span></p> -<p id="t833" class="stm run hide_run"> <span class="nam">next_positions</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">stack</span><span class="op">(</span><span class="op">(</span><span class="nam">longitudinal_positions</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t834" class="pln"> <span class="nam">lateral_positions</span><span class="op">,</span> <span class="nam">vertical_positions</span><span class="op">)</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t835" class="pln"> <span class="nam">axis</span><span class="op">=</span><span class="num">1</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t836" class="pln"><span class="strut"> </span></p> -<p id="t837" class="pln"> <span class="com"># Increment particle positions</span><span class="strut"> </span></p> -<p id="t838" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">_particles</span><span class="op">.</span><span class="nam">set_position</span><span class="op">(</span><span class="nam">next_positions</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t839" class="pln"><span class="strut"> </span></p> -<p id="t840" class="stm run hide_run"> <span class="key">return</span> <span class="nam">FluEggTransporter</span><span class="strut"> </span></p> -<p id="t841" class="pln"><span class="strut"> </span></p> -<p id="t842" class="pln"><span class="strut"> </span></p> -<p id="t843" class="stm run hide_run"><span class="key">def</span> <span class="nam">init_transporter</span><span class="op">(</span><span class="nam">simulation_clock</span><span class="op">,</span> <span class="nam">particles</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t844" class="pln"> <span class="nam">vertical_turbulence</span><span class="op">=</span><span class="str">'parabolic-constant'</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t845" class="pln"> <span class="nam">advection_direction</span><span class="op">=</span><span class="str">'forward'</span><span class="op">,</span> <span class="nam">random_numbers</span><span class="op">=</span><span class="key">None</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t846" class="pln"> <span class="str">"""</span><span class="strut"> </span></p> -<p id="t847" class="pln"><span class="strut"> </span></p> -<p id="t848" class="pln"><span class="str"> :param simulation_clock:</span><span class="strut"> </span></p> -<p id="t849" class="pln"><span class="str"> :param particles:</span><span class="strut"> </span></p> -<p id="t850" class="pln"><span class="str"> :param vertical_turbulence:</span><span class="strut"> </span></p> -<p id="t851" class="pln"><span class="str"> :param advection_direction:</span><span class="strut"> </span></p> -<p id="t852" class="pln"><span class="str"> :return:</span><span class="strut"> </span></p> -<p id="t853" class="pln"><span class="strut"> </span></p> -<p id="t854" class="pln"><span class="str"> """</span><span class="strut"> </span></p> -<p id="t855" class="pln"><span class="strut"> </span></p> -<p id="t856" class="stm mis"> <span class="nam">FluEggTransporter</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t857" class="pln"> <span class="nam">fluegg_transporter_class_factory</span><span class="op">(</span><span class="nam">vertical_turbulence</span><span class="op">,</span><span class="strut"> </span></p> -<p id="t858" class="pln"> <span class="nam">advection_direction</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t859" class="pln"><span class="strut"> </span></p> -<p id="t860" class="stm mis"> <span class="key">return</span> <span class="nam">FluEggTransporter</span><span class="op">(</span><span class="nam">simulation_clock</span><span class="op">,</span> <span class="nam">particles</span><span class="op">,</span> <span class="nam">random_numbers</span><span class="op">)</span><span class="strut"> </span></p> - - </td> - </tr> - </table> -</div> - -<div id="footer"> - <div class="content"> - <p> - <a class="nav" href="index.html">« index</a> <a class="nav" href="https://coverage.readthedocs.io">coverage.py v4.5.3</a>, - created at 2019-07-09 15:15 - </p> - </div> -</div> - -</body> -</html> diff --git a/coverage_report/index.html b/coverage_report/index.html deleted file mode 100644 index f97afe9..0000000 --- a/coverage_report/index.html +++ /dev/null @@ -1,230 +0,0 @@ - - - -<!DOCTYPE html> -<html> -<head> - <meta http-equiv="Content-Type" content="text/html; charset=utf-8"> - <title>Coverage report</title> - <link rel="stylesheet" href="style.css" type="text/css"> - - <script type="text/javascript" src="jquery.min.js"></script> - <script type="text/javascript" src="jquery.ba-throttle-debounce.min.js"></script> - <script type="text/javascript" src="jquery.tablesorter.min.js"></script> - <script type="text/javascript" src="jquery.hotkeys.js"></script> - <script type="text/javascript" src="coverage_html.js"></script> - <script type="text/javascript"> - jQuery(document).ready(coverage.index_ready); - </script> -</head> -<body class="indexfile"> - -<div id="header"> - <div class="content"> - <h1>Coverage report: - <span class="pc_cov">47%</span> - </h1> - - <img id="keyboard_icon" src="keybd_closed.png" alt="Show keyboard shortcuts" /> - - <form id="filter_container"> - <input id="filter" type="text" value="" placeholder="filter..." /> - </form> - </div> -</div> - -<div class="help_panel"> - <img id="panel_icon" src="keybd_open.png" alt="Hide keyboard shortcuts" /> - <p class="legend">Hot-keys on this page</p> - <div> - <p class="keyhelp"> - <span class="key">n</span> - <span class="key">s</span> - <span class="key">m</span> - <span class="key">x</span> - - <span class="key">c</span> change column sorting - </p> - </div> -</div> - -<div id="index"> - <table class="index"> - <thead> - - <tr class="tablehead" title="Click to sort"> - <th class="name left headerSortDown shortkey_n">Module</th> - <th class="shortkey_s">statements</th> - <th class="shortkey_m">missing</th> - <th class="shortkey_x">excluded</th> - - <th class="right shortkey_c">coverage</th> - </tr> - </thead> - - <tfoot> - <tr class="total"> - <td class="name left">Total</td> - <td>2060</td> - <td>1084</td> - <td>0</td> - - <td class="right" data-ratio="976 2060">47%</td> - </tr> - </tfoot> - <tbody> - - <tr class="file"> - <td class="name left"><a href="fluegg___init___py.html">fluegg\__init__.py</a></td> - <td>0</td> - <td>0</td> - <td>0</td> - - <td class="right" data-ratio="0 0">100%</td> - </tr> - - <tr class="file"> - <td class="name left"><a href="fluegg_asiancarpeggs_py.html">fluegg\asiancarpeggs.py</a></td> - <td>226</td> - <td>17</td> - <td>0</td> - - <td class="right" data-ratio="209 226">92%</td> - </tr> - - <tr class="file"> - <td class="name left"><a href="fluegg_drift_py.html">fluegg\drift.py</a></td> - <td>56</td> - <td>6</td> - <td>0</td> - - <td class="right" data-ratio="50 56">89%</td> - </tr> - - <tr class="file"> - <td class="name left"><a href="fluegg_gui___init___py.html">fluegg\gui\__init__.py</a></td> - <td>0</td> - <td>0</td> - <td>0</td> - - <td class="right" data-ratio="0 0">100%</td> - </tr> - - <tr class="file"> - <td class="name left"><a href="fluegg_gui_gui_py.html">fluegg\gui\gui.py</a></td> - <td>254</td> - <td>225</td> - <td>0</td> - - <td class="right" data-ratio="29 254">11%</td> - </tr> - - <tr class="file"> - <td class="name left"><a href="fluegg_gui_gui_layout_py.html">fluegg\gui\gui_layout.py</a></td> - <td>276</td> - <td>272</td> - <td>0</td> - - <td class="right" data-ratio="4 276">1%</td> - </tr> - - <tr class="file"> - <td class="name left"><a href="fluegg_gui_hecras_dialog_py.html">fluegg\gui\hecras_dialog.py</a></td> - <td>112</td> - <td>108</td> - <td>0</td> - - <td class="right" data-ratio="4 112">4%</td> - </tr> - - <tr class="file"> - <td class="name left"><a href="fluegg_hydraulics_py.html">fluegg\hydraulics.py</a></td> - <td>287</td> - <td>37</td> - <td>0</td> - - <td class="right" data-ratio="250 287">87%</td> - </tr> - - <tr class="file"> - <td class="name left"><a href="fluegg_kml_py.html">fluegg\kml.py</a></td> - <td>130</td> - <td>113</td> - <td>0</td> - - <td class="right" data-ratio="17 130">13%</td> - </tr> - - <tr class="file"> - <td class="name left"><a href="fluegg_random_py.html">fluegg\random.py</a></td> - <td>36</td> - <td>18</td> - <td>0</td> - - <td class="right" data-ratio="18 36">50%</td> - </tr> - - <tr class="file"> - <td class="name left"><a href="fluegg_ras_py.html">fluegg\ras.py</a></td> - <td>197</td> - <td>148</td> - <td>0</td> - - <td class="right" data-ratio="49 197">25%</td> - </tr> - - <tr class="file"> - <td class="name left"><a href="fluegg_simclock_py.html">fluegg\simclock.py</a></td> - <td>46</td> - <td>5</td> - <td>0</td> - - <td class="right" data-ratio="41 46">89%</td> - </tr> - - <tr class="file"> - <td class="name left"><a href="fluegg_simulation_py.html">fluegg\simulation.py</a></td> - <td>132</td> - <td>76</td> - <td>0</td> - - <td class="right" data-ratio="56 132">42%</td> - </tr> - - <tr class="file"> - <td class="name left"><a href="fluegg_transporter_py.html">fluegg\transporter.py</a></td> - <td>285</td> - <td>56</td> - <td>0</td> - - <td class="right" data-ratio="229 285">80%</td> - </tr> - - <tr class="file"> - <td class="name left"><a href="test_fluegg_py.html">test_fluegg.py</a></td> - <td>23</td> - <td>3</td> - <td>0</td> - - <td class="right" data-ratio="20 23">87%</td> - </tr> - - </tbody> - </table> - - <p id="no_rows"> - No items found using the specified filter. - </p> -</div> - -<div id="footer"> - <div class="content"> - <p> - <a class="nav" href="https://coverage.readthedocs.io">coverage.py v4.5.3</a>, - created at 2019-07-09 15:49 - </p> - </div> -</div> - -</body> -</html> diff --git a/coverage_report/jquery.ba-throttle-debounce.min.js b/coverage_report/jquery.ba-throttle-debounce.min.js deleted file mode 100644 index 648fe5d..0000000 --- a/coverage_report/jquery.ba-throttle-debounce.min.js +++ /dev/null @@ -1,9 +0,0 @@ -/* - * jQuery throttle / debounce - v1.1 - 3/7/2010 - * http://benalman.com/projects/jquery-throttle-debounce-plugin/ - * - * Copyright (c) 2010 "Cowboy" Ben Alman - * Dual licensed under the MIT and GPL licenses. - * http://benalman.com/about/license/ - */ -(function(b,c){var $=b.jQuery||b.Cowboy||(b.Cowboy={}),a;$.throttle=a=function(e,f,j,i){var h,d=0;if(typeof f!=="boolean"){i=j;j=f;f=c}function g(){var o=this,m=+new Date()-d,n=arguments;function l(){d=+new Date();j.apply(o,n)}function k(){h=c}if(i&&!h){l()}h&&clearTimeout(h);if(i===c&&m>e){l()}else{if(f!==true){h=setTimeout(i?k:l,i===c?e-m:e)}}}if($.guid){g.guid=j.guid=j.guid||$.guid++}return g};$.debounce=function(d,e,f){return f===c?a(d,e,false):a(d,f,e!==false)}})(this); diff --git a/coverage_report/jquery.hotkeys.js b/coverage_report/jquery.hotkeys.js deleted file mode 100644 index 09b21e0..0000000 --- a/coverage_report/jquery.hotkeys.js +++ /dev/null @@ -1,99 +0,0 @@ -/* - * jQuery Hotkeys Plugin - * Copyright 2010, John Resig - * Dual licensed under the MIT or GPL Version 2 licenses. - * - * Based upon the plugin by Tzury Bar Yochay: - * http://github.com/tzuryby/hotkeys - * - * Original idea by: - * Binny V A, http://www.openjs.com/scripts/events/keyboard_shortcuts/ -*/ - -(function(jQuery){ - - jQuery.hotkeys = { - version: "0.8", - - specialKeys: { - 8: "backspace", 9: "tab", 13: "return", 16: "shift", 17: "ctrl", 18: "alt", 19: "pause", - 20: "capslock", 27: "esc", 32: "space", 33: "pageup", 34: "pagedown", 35: "end", 36: "home", - 37: "left", 38: "up", 39: "right", 40: "down", 45: "insert", 46: "del", - 96: "0", 97: "1", 98: "2", 99: "3", 100: "4", 101: "5", 102: "6", 103: "7", - 104: "8", 105: "9", 106: "*", 107: "+", 109: "-", 110: ".", 111 : "/", - 112: "f1", 113: "f2", 114: "f3", 115: "f4", 116: "f5", 117: "f6", 118: "f7", 119: "f8", - 120: "f9", 121: "f10", 122: "f11", 123: "f12", 144: "numlock", 145: "scroll", 191: "/", 224: "meta" - }, - - shiftNums: { - "`": "~", "1": "!", "2": "@", "3": "#", "4": "$", "5": "%", "6": "^", "7": "&", - "8": "*", "9": "(", "0": ")", "-": "_", "=": "+", ";": ": ", "'": "\"", ",": "<", - ".": ">", "/": "?", "\\": "|" - } - }; - - function keyHandler( handleObj ) { - // Only care when a possible input has been specified - if ( typeof handleObj.data !== "string" ) { - return; - } - - var origHandler = handleObj.handler, - keys = handleObj.data.toLowerCase().split(" "); - - handleObj.handler = function( event ) { - // Don't fire in text-accepting inputs that we didn't directly bind to - if ( this !== event.target && (/textarea|select/i.test( event.target.nodeName ) || - event.target.type === "text") ) { - return; - } - - // Keypress represents 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var i = 0, l = keys.length; i < l; i++ ) { - if ( possible[ keys[i] ] ) { - return origHandler.apply( this, arguments ); - } - } - }; - } - - jQuery.each([ "keydown", "keyup", "keypress" ], function() { - jQuery.event.special[ this ] = { add: keyHandler }; - }); - -})( jQuery ); diff --git a/coverage_report/jquery.isonscreen.js b/coverage_report/jquery.isonscreen.js deleted file mode 100644 index 0182ebd..0000000 --- a/coverage_report/jquery.isonscreen.js +++ /dev/null @@ -1,53 +0,0 @@ -/* Copyright (c) 2010 - * @author Laurence Wheway - * Dual licensed under the MIT (http://www.opensource.org/licenses/mit-license.php) - * and GPL (http://www.opensource.org/licenses/gpl-license.php) licenses. - * - * @version 1.2.0 - */ -(function($) { - jQuery.extend({ - isOnScreen: function(box, container) { - //ensure numbers come in as intgers (not strings) and remove 'px' is it's there - for(var i in box){box[i] = parseFloat(box[i])}; - for(var i in container){container[i] = 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charset=utf-8"> - - - <meta http-equiv="X-UA-Compatible" content="IE=emulateIE7" /> - <title>Coverage for test_fluegg.py: 87%</title> - <link rel="stylesheet" href="style.css" type="text/css"> - - <script type="text/javascript" src="jquery.min.js"></script> - <script type="text/javascript" src="jquery.hotkeys.js"></script> - <script type="text/javascript" src="jquery.isonscreen.js"></script> - <script type="text/javascript" src="coverage_html.js"></script> - <script type="text/javascript"> - jQuery(document).ready(coverage.pyfile_ready); - </script> -</head> -<body class="pyfile"> - -<div id="header"> - <div class="content"> - <h1>Coverage for <b>test_fluegg.py</b> : - <span class="pc_cov">87%</span> - </h1> - - <img id="keyboard_icon" src="keybd_closed.png" alt="Show keyboard shortcuts" /> - - <h2 class="stats"> - 23 statements - <span class="run hide_run shortkey_r button_toggle_run">20 run</span> - <span class="mis shortkey_m button_toggle_mis">3 missing</span> - <span class="exc shortkey_x button_toggle_exc">0 excluded</span> - - - </h2> - </div> -</div> - -<div class="help_panel"> - <img id="panel_icon" src="keybd_open.png" alt="Hide keyboard shortcuts" /> - <p class="legend">Hot-keys on this page</p> - <div> - <p class="keyhelp"> - <span class="key">r</span> - <span class="key">m</span> - <span class="key">x</span> - <span class="key">p</span> toggle line displays - </p> - <p class="keyhelp"> - <span class="key">j</span> - <span class="key">k</span> next/prev highlighted chunk - </p> - <p class="keyhelp"> - <span class="key">0</span> (zero) top of page - </p> - <p class="keyhelp"> - <span class="key">1</span> (one) first highlighted chunk - </p> - </div> -</div> - -<div id="source"> - <table> - <tr> - <td class="linenos"> -<p id="n1" class="stm run hide_run"><a href="#n1">1</a></p> -<p id="n2" class="stm run hide_run"><a href="#n2">2</a></p> -<p id="n3" class="stm run hide_run"><a href="#n3">3</a></p> -<p id="n4" class="stm run hide_run"><a href="#n4">4</a></p> -<p id="n5" class="pln"><a href="#n5">5</a></p> -<p id="n6" class="stm run hide_run"><a href="#n6">6</a></p> -<p id="n7" class="pln"><a href="#n7">7</a></p> -<p id="n8" class="stm run hide_run"><a href="#n8">8</a></p> -<p id="n9" class="pln"><a href="#n9">9</a></p> -<p id="n10" class="stm run hide_run"><a href="#n10">10</a></p> -<p id="n11" class="pln"><a href="#n11">11</a></p> -<p id="n12" class="pln"><a href="#n12">12</a></p> -<p id="n13" class="stm run hide_run"><a href="#n13">13</a></p> -<p id="n14" class="pln"><a href="#n14">14</a></p> -<p id="n15" class="pln"><a href="#n15">15</a></p> -<p id="n16" class="stm run hide_run"><a href="#n16">16</a></p> -<p id="n17" class="pln"><a href="#n17">17</a></p> -<p id="n18" class="stm run hide_run"><a href="#n18">18</a></p> -<p id="n19" class="pln"><a href="#n19">19</a></p> -<p id="n20" class="stm run hide_run"><a href="#n20">20</a></p> -<p id="n21" class="stm run hide_run"><a href="#n21">21</a></p> -<p id="n22" class="stm run hide_run"><a href="#n22">22</a></p> -<p id="n23" class="stm run hide_run"><a href="#n23">23</a></p> -<p id="n24" class="stm run hide_run"><a href="#n24">24</a></p> -<p id="n25" class="stm run hide_run"><a href="#n25">25</a></p> -<p id="n26" class="pln"><a href="#n26">26</a></p> -<p id="n27" class="stm run hide_run"><a href="#n27">27</a></p> -<p id="n28" class="pln"><a href="#n28">28</a></p> -<p id="n29" class="stm run hide_run"><a href="#n29">29</a></p> -<p id="n30" class="pln"><a href="#n30">30</a></p> -<p id="n31" class="stm run hide_run"><a href="#n31">31</a></p> -<p id="n32" class="pln"><a href="#n32">32</a></p> -<p id="n33" class="pln"><a href="#n33">33</a></p> -<p id="n34" class="stm run hide_run"><a href="#n34">34</a></p> -<p id="n35" class="stm mis"><a href="#n35">35</a></p> -<p id="n36" class="stm mis"><a href="#n36">36</a></p> -<p id="n37" class="stm mis"><a href="#n37">37</a></p> -<p id="n38" class="pln"><a href="#n38">38</a></p> - - </td> - <td class="text"> -<p id="t1" class="stm run hide_run"><span class="key">import</span> <span class="nam">os</span><span class="strut"> </span></p> -<p id="t2" class="stm run hide_run"><span class="key">import</span> <span class="nam">glob</span><span class="strut"> </span></p> -<p id="t3" class="stm run hide_run"><span class="key">import</span> <span class="nam">importlib</span><span class="strut"> </span></p> -<p id="t4" class="stm run hide_run"><span class="key">import</span> <span class="nam">unittest</span><span class="strut"> </span></p> -<p id="t5" class="pln"><span class="strut"> </span></p> -<p id="t6" class="stm run hide_run"><span class="nam">absolute_path</span><span class="op">,</span> <span class="nam">_</span> <span class="op">=</span> <span class="nam">os</span><span class="op">.</span><span class="nam">path</span><span class="op">.</span><span class="nam">split</span><span class="op">(</span><span class="nam">os</span><span class="op">.</span><span class="nam">path</span><span class="op">.</span><span class="nam">realpath</span><span class="op">(</span><span class="nam">__file__</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t7" class="pln"><span class="strut"> </span></p> -<p id="t8" class="stm run hide_run"><span class="nam">module_paths</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t9" class="pln"> <span class="op">[</span><span class="nam">path</span> <span class="key">for</span> <span class="nam">path</span> <span class="key">in</span> <span class="nam">glob</span><span class="op">.</span><span class="nam">glob</span><span class="op">(</span><span class="nam">os</span><span class="op">.</span><span class="nam">path</span><span class="op">.</span><span class="nam">join</span><span class="op">(</span><span class="nam">absolute_path</span><span class="op">,</span> <span class="str">'test'</span><span class="op">,</span> <span class="str">'*.py'</span><span class="op">)</span><span class="op">)</span> <span class="key">if</span> <span class="str">'__init__.py'</span> <span class="key">not</span> <span class="key">in</span> <span class="nam">path</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t10" class="stm run hide_run"><span class="nam">nonrandom_test_module_paths</span> <span class="op">=</span> <span class="xx">\</span><span class="strut"> </span></p> -<p id="t11" class="pln"> <span class="op">[</span><span class="nam">path</span> <span class="key">for</span> <span class="nam">path</span> <span class="key">in</span> <span class="nam">glob</span><span class="op">.</span><span class="nam">glob</span><span class="op">(</span><span class="nam">os</span><span class="op">.</span><span class="nam">path</span><span class="op">.</span><span class="nam">join</span><span class="op">(</span><span class="nam">absolute_path</span><span class="op">,</span> <span class="str">'test'</span><span class="op">,</span> <span class="str">'nonrandom'</span><span class="op">,</span> <span class="str">'*.py'</span><span class="op">)</span><span class="op">)</span> <span class="key">if</span> <span class="str">'__init__.py'</span> <span class="key">not</span> <span class="key">in</span> <span class="nam">path</span><span class="op">]</span><span class="strut"> </span></p> -<p id="t12" class="pln"><span class="strut"> </span></p> -<p id="t13" class="stm run hide_run"><span class="nam">module_paths</span><span class="op">.</span><span class="nam">extend</span><span class="op">(</span><span class="nam">nonrandom_test_module_paths</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t14" class="pln"><span class="strut"> </span></p> -<p id="t15" class="pln"><span class="strut"> </span></p> -<p id="t16" class="stm run hide_run"><span class="key">def</span> <span class="nam">load_tests</span><span class="op">(</span><span class="nam">loader</span><span class="op">,</span> <span class="op">*</span><span class="nam">args</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t17" class="pln"><span class="strut"> </span></p> -<p id="t18" class="stm run hide_run"> <span class="nam">suite</span> <span class="op">=</span> <span class="nam">unittest</span><span class="op">.</span><span class="nam">TestSuite</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t19" class="pln"><span class="strut"> </span></p> -<p id="t20" class="stm run hide_run"> <span class="key">for</span> <span class="nam">path</span> <span class="key">in</span> <span class="nam">module_paths</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t21" class="stm run hide_run"> <span class="nam">_</span><span class="op">,</span> <span class="nam">module_file_name</span> <span class="op">=</span> <span class="nam">os</span><span class="op">.</span><span class="nam">path</span><span class="op">.</span><span class="nam">split</span><span class="op">(</span><span class="nam">path</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t22" class="stm run hide_run"> <span class="nam">module_name</span><span class="op">,</span> <span class="nam">_</span> <span class="op">=</span> <span class="nam">os</span><span class="op">.</span><span class="nam">path</span><span class="op">.</span><span class="nam">splitext</span><span class="op">(</span><span class="nam">module_file_name</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t23" class="stm run hide_run"> <span class="nam">spec</span> <span class="op">=</span> <span class="nam">importlib</span><span class="op">.</span><span class="nam">util</span><span class="op">.</span><span class="nam">spec_from_file_location</span><span class="op">(</span><span class="nam">module_name</span><span class="op">,</span> <span class="nam">path</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t24" class="stm run hide_run"> <span class="nam">module</span> <span class="op">=</span> <span class="nam">importlib</span><span class="op">.</span><span class="nam">util</span><span class="op">.</span><span class="nam">module_from_spec</span><span class="op">(</span><span class="nam">spec</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t25" class="stm run hide_run"> <span class="nam">spec</span><span class="op">.</span><span class="nam">loader</span><span class="op">.</span><span class="nam">exec_module</span><span class="op">(</span><span class="nam">module</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t26" class="pln"><span class="strut"> </span></p> -<p id="t27" class="stm run hide_run"> <span class="nam">tests</span> <span class="op">=</span> <span class="nam">loader</span><span class="op">.</span><span class="nam">loadTestsFromModule</span><span class="op">(</span><span class="nam">module</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t28" class="pln"><span class="strut"> </span></p> -<p id="t29" class="stm run hide_run"> <span class="nam">suite</span><span class="op">.</span><span class="nam">addTest</span><span class="op">(</span><span class="nam">tests</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t30" class="pln"><span class="strut"> </span></p> -<p id="t31" class="stm run hide_run"> <span class="key">return</span> <span class="nam">suite</span><span class="strut"> </span></p> -<p id="t32" class="pln"><span class="strut"> </span></p> -<p id="t33" class="pln"><span class="strut"> </span></p> -<p id="t34" class="stm run hide_run"><span class="key">if</span> <span class="nam">__name__</span> <span class="op">==</span> <span class="str">'__main__'</span><span class="op">:</span><span class="strut"> </span></p> -<p id="t35" class="stm mis"> <span class="nam">test_loader</span> <span class="op">=</span> <span class="nam">unittest</span><span class="op">.</span><span class="nam">defaultTestLoader</span><span class="strut"> </span></p> -<p id="t36" class="stm mis"> <span class="nam">test_suite</span> <span class="op">=</span> <span class="nam">load_tests</span><span class="op">(</span><span class="nam">test_loader</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t37" class="stm mis"> <span class="nam">unittest</span><span class="op">.</span><span class="nam">TextTestRunner</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">run</span><span class="op">(</span><span class="nam">test_suite</span><span class="op">)</span><span class="strut"> </span></p> -<p id="t38" class="pln"><span class="strut"> </span></p> - - </td> - </tr> - </table> -</div> - -<div id="footer"> - <div class="content"> - <p> - <a class="nav" href="index.html">« index</a> <a class="nav" href="https://coverage.readthedocs.io">coverage.py v4.5.3</a>, - created at 2019-07-09 15:15 - </p> - </div> -</div> - -</body> -</html> diff --git a/notebooks/asian carp eggs.ipynb b/notebooks/asian carp eggs.ipynb deleted file mode 100644 index 3494173..0000000 --- a/notebooks/asian carp eggs.ipynb +++ /dev/null @@ -1,98 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "import numpy as np\n", - "\n", - "from fluegg.asiancarpeggs import BigheadCarpEggs\n", - "from fluegg.simclock import SimulationClock\n", - "\n", - "hatching_time = BigheadCarpEggs.hatching_time()\n", - "time_step_size = 10 # seconds\n", - "\n", - "initial_position = np.array([[0, 0, 0]])\n", - "\n", - "simulation_clock = SimulationClock(time_step_size, hatching_time)\n", - "\n", - "carp_eggs = BigheadCarpEggs(initial_position, simulation_clock)" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": { - "scrolled": true - }, - "outputs": [], - "source": [ - "number_of_time_steps = simulation_clock.number_of_time_steps()\n", - "\n", - "time = np.tile(np.nan, number_of_time_steps)\n", - "density = np.tile(np.nan, number_of_time_steps)\n", - "diameter = np.tile(np.nan, number_of_time_steps)\n", - "\n", - "for current_time_index in simulation_clock.iter_time_index():\n", - " time[current_time_index] = simulation_clock.current_time()\n", - " density[current_time_index] = carp_eggs.density()\n", - " diameter[current_time_index] = carp_eggs.diameter()" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "<Figure size 720x576 with 2 Axes>" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "%matplotlib inline\n", - "import matplotlib.pyplot as plt\n", - "\n", - "fig = plt.figure(figsize=(10,8))\n", - "\n", - "density_axes = fig.add_subplot(211)\n", - "_ = density_axes.plot(time, density)\n", - "_ = density_axes.set_ylabel('Density, in kg/m^3')\n", - "\n", - "diameter_axes = fig.add_subplot(212, sharex=density_axes)\n", - "_ = diameter_axes.plot(time, diameter)\n", - "_ = diameter_axes.set_ylabel('Diameter, in m')\n", - "_ = diameter_axes.set_xlabel('Time, in s')" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.6.6" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/notebooks/fall velocity discrepancy.ipynb b/notebooks/fall velocity discrepancy.ipynb deleted file mode 100644 index 7c7f5af..0000000 --- a/notebooks/fall velocity discrepancy.ipynb +++ /dev/null @@ -1,292 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "<div>\n", - "<style scoped>\n", - " .dataframe tbody tr th:only-of-type {\n", - " vertical-align: middle;\n", - " }\n", - "\n", - " .dataframe tbody tr th {\n", - " vertical-align: top;\n", - " }\n", - "\n", - " .dataframe thead th {\n", - " text-align: right;\n", - " }\n", - "</style>\n", - "<table border=\"1\" class=\"dataframe\">\n", - " <thead>\n", - " <tr style=\"text-align: right;\">\n", - " <th></th>\n", - " <th>CumlDistance_km</th>\n", - " <th>Depth_m</th>\n", - " <th>Q_cms</th>\n", - " <th>Vmag_mps</th>\n", - " <th>Vvert_mps</th>\n", - " <th>Vlat_mps</th>\n", - " <th>Ustar_mps</th>\n", - " <th>Temp_C</th>\n", - " </tr>\n", - " <tr>\n", - " <th>CellNumber</th>\n", - " <th></th>\n", - " <th></th>\n", - " <th></th>\n", - " <th></th>\n", - " <th></th>\n", - " <th></th>\n", - " <th></th>\n", - " <th></th>\n", - " </tr>\n", - " </thead>\n", - " <tbody>\n", - " <tr>\n", - " <th>1</th>\n", - " <td>100.0</td>\n", - " <td>4.94</td>\n", - " <td>125.0</td>\n", - " <td>0.25</td>\n", - " <td>0.0</td>\n", - " <td>0.0</td>\n", - " <td>0.013555</td>\n", - " <td>23.0</td>\n", - " </tr>\n", - " </tbody>\n", - "</table>\n", - "</div>" - ], - "text/plain": [ - " CumlDistance_km Depth_m Q_cms Vmag_mps Vvert_mps Vlat_mps \\\n", - "CellNumber \n", - "1 100.0 4.94 125.0 0.25 0.0 0.0 \n", - "\n", - " Ustar_mps Temp_C \n", - "CellNumber \n", - "1 0.013555 23.0 " - ] - }, - "execution_count": 1, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "import pandas as pd\n", - "\n", - "hydraulic_csv_path = r'../test/nonrandom/data/highQ_1Cell.csv'\n", - "hydraulic_csv = pd.read_csv(hydraulic_csv_path, index_col='CellNumber')\n", - "hydraulic_csv" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "%matplotlib inline\n", - "import numpy as np\n", - "import scipy.io as sio\n", - "\n", - "import matplotlib.pyplot as plt\n", - "\n", - "mat_file_path = r'../test/nonrandom/data/single_egg.mat'\n", - "results = sio.loadmat(mat_file_path, squeeze_me=False)\n", - "expected_x = np.squeeze(results['ResultsSim']['X'][0][0])\n", - "expected_y = np.squeeze(results['ResultsSim']['Y'][0][0])\n", - "expected_z = np.squeeze(results['ResultsSim']['Z'][0][0])\n", - "expected_time = np.squeeze(results['ResultsSim']['time'][0][0])" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "import os\n", - "import sys\n", - "\n", - "from fluegg.drift import ConstantDriftingParticle\n", - "\n", - "initial_position = np.array([[0, 50.6, 0]])\n", - "egg_density = results['ResultsSim']['Rhoe'][0][0][0]\n", - "egg_diameter = results['ResultsSim']['D'][0][0][0]/1000\n", - "\n", - "drifting_particles = ConstantDriftingParticle(egg_density, egg_diameter, initial_position)" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [], - "source": [ - "import os\n", - "import sys\n", - "\n", - "from fluegg.hydraulics import from_csv\n", - "from fluegg.simclock import SimulationClock\n", - "from fluegg.simulation import Simulation\n", - "\n", - "test_classes_module = os.path.realpath('../test/nonrandom/testclasses.py')\n", - "test_classes_path, _ = os.path.split(test_classes_module)\n", - "\n", - "sys.path.append(test_classes_path)\n", - "\n", - "from testclasses import NonRandomFluEggTransporter\n", - "\n", - "hatching_time = results['ResultsSim']['T2_Hatching'][0][0][0][0]*3600 # seconds\n", - "\n", - "time_step_size = 100 # seconds\n", - "simulation_clock = SimulationClock(time_step_size, hatching_time)\n", - "hydraulic_model = from_csv(hydraulic_csv_path)\n", - "transport_model = NonRandomFluEggTransporter(simulation_clock, drifting_particles)\n", - "simulation = Simulation(drifting_particles, transport_model, simulation_clock)\n", - "transport_model.set_hydraulic_model(hydraulic_model)\n", - "simulation.set_hydraulic_model(hydraulic_model)\n", - "\n", - "simulation_results = simulation.run()\n", - "\n", - "time = simulation_results.time()\n", - "positions = simulation_results.results()" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "<Figure size 720x576 with 3 Axes>" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fig = plt.figure(figsize=(10,8))\n", - "\n", - "x_position_axes = fig.add_subplot(311)\n", - "_ = x_position_axes.plot(expected_time, expected_x, 'x', label='Expected')\n", - "_ = x_position_axes.plot(time, positions[:, 0, 0], '.', label='Calculated')\n", - "_ = x_position_axes.legend()\n", - "_ = x_position_axes.set_ylabel('x')\n", - "\n", - "y_position_axes = fig.add_subplot(312, sharex=x_position_axes)\n", - "_ = y_position_axes.plot(expected_time, expected_y, 'x')\n", - "_ = y_position_axes.plot(time, positions[:, 0, 1], '.')\n", - "_ = y_position_axes.set_ylabel('y')\n", - "\n", - "z_position_axes = fig.add_subplot(313, sharex=x_position_axes)\n", - "_ = z_position_axes.plot(expected_time, expected_z, 'x')\n", - "_ = z_position_axes.plot(time, positions[:, 0, 2], '.')\n", - "_ = z_position_axes.set_ylabel('z')\n", - "_ = z_position_axes.set_xlabel('time')" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "<Figure size 720x576 with 3 Axes>" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fig = plt.figure(figsize=(10,8))\n", - "\n", - "x_position_axes = fig.add_subplot(311)\n", - "_ = x_position_axes.plot(expected_time, positions[:, 0, 0] - expected_x, '.', label='Expected')\n", - "_ = x_position_axes.set_ylabel('calculated x - expected x')\n", - "\n", - "y_position_axes = fig.add_subplot(312, sharex=x_position_axes)\n", - "_ = y_position_axes.plot(expected_time, positions[:, 0, 1] - expected_y, '.')\n", - "_ = y_position_axes.set_ylabel('calculated y - expected y')\n", - "\n", - "z_position_axes = fig.add_subplot(313, sharex=x_position_axes)\n", - "_ = z_position_axes.plot(expected_time, positions[:, 0, 2] - expected_z, 'x')\n", - "_ = z_position_axes.set_ylabel('calculated z - expected z')\n", - "_ = z_position_axes.set_xlabel('time')" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "<Figure size 720x576 with 3 Axes>" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fig = plt.figure(figsize=(10,8))\n", - "\n", - "xy_axes = fig.add_subplot(221)\n", - "_ = xy_axes.plot(expected_x,expected_y, 'x', label='Expected')\n", - "_ = xy_axes.plot(positions[:, 0, 0], positions[:, 0, 1], '.', label='Calculated')\n", - "_ = xy_axes.legend()\n", - "_ = xy_axes.set_ylabel('y')\n", - "\n", - "xz_axes = fig.add_subplot(223, sharex=xy_axes)\n", - "_ = xz_axes.plot(expected_x, expected_z, 'x')\n", - "_ = xz_axes.plot(positions[:, 0, 0], positions[:, 0, 2], '.')\n", - "_ = xz_axes.set_ylabel('z')\n", - "_ = xz_axes.set_xlabel('x')\n", - "\n", - "zy_axes = fig.add_subplot(224, sharey=xz_axes)\n", - "_ = zy_axes.plot(expected_y, expected_z, 'x')\n", - "_ = zy_axes.plot(positions[:, 0, 1], positions[:, 0, 2], '.')\n", - "_ = zy_axes.set_xlabel('y')" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.6.6" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/notebooks/fluegg-tutorial-steady-ras.ipynb b/notebooks/fluegg-tutorial-steady-ras.ipynb deleted file mode 100644 index 2002be8..0000000 --- a/notebooks/fluegg-tutorial-steady-ras.ipynb +++ /dev/null @@ -1,510 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# FluEgg Steady RAS Profile Tutorial " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Step 1: Hydraulic Channel\n", - "\n", - "First, we will import hyraulic channel data. \n", - "\n", - "FluEgg includes a sample unsteady RAS project in the `test/data/ras/steadyflume` directory. Below, we use an instance of the `RASProject` class to show the current plan name and profiles within the plan." - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Current plan name: case1\n", - "Profile names\n", - "----------\n", - " PF 1\n", - " PF 2\n" - ] - } - ], - "source": [ - "from fluegg.ras import RASProject\n", - "\n", - "project_file_path = r'..\\test\\data\\ras\\steadyflume\\rectangular-flume.prj'\n", - "\n", - "with RASProject(project_file_path) as rp:\n", - " plan_name = rp.current_plan_name()\n", - " project_profile_names = rp.profile_names()\n", - "\n", - "print(\"Current plan name: {}\".format(plan_name))\n", - "print(\"Profile names\\n----------\")\n", - "for pn in project_profile_names:\n", - " print(\" {}\".format(pn))" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "In the following cell, a plan name is selected (PF 1), and the necessary data to create a FluEgg hydraulic model is extracted. The `hydraulic_model_data` method returns a Pandas `DataFrame` for use in the initialization of a hydraulic model." - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "<div>\n", - "<style scoped>\n", - " .dataframe tbody tr th:only-of-type {\n", - " vertical-align: middle;\n", - " }\n", - "\n", - " .dataframe tbody tr th {\n", - " vertical-align: top;\n", - " }\n", - "\n", - " .dataframe thead th {\n", - " text-align: right;\n", - " }\n", - "</style>\n", - "<table border=\"1\" class=\"dataframe\">\n", - " <thead>\n", - " <tr style=\"text-align: right;\">\n", - " <th></th>\n", - " <th>Depth_m</th>\n", - " <th>Q_cms</th>\n", - " <th>Vmag_mps</th>\n", - " <th>CumlDistance_km</th>\n", - " <th>Ustar_mps</th>\n", - " <th>Vvert_mps</th>\n", - " <th>Vlat_mps</th>\n", - " <th>Temp_C</th>\n", - " </tr>\n", - " </thead>\n", - " <tbody>\n", - " <tr>\n", - " <th>1</th>\n", - " <td>1.835397</td>\n", - " <td>24.999996</td>\n", - " <td>0.136210</td>\n", - " <td>5.0</td>\n", - " <td>0.013188</td>\n", - " <td>0</td>\n", - " <td>0</td>\n", - " <td>22</td>\n", - " </tr>\n", - " <tr>\n", - " <th>2</th>\n", - " <td>1.835564</td>\n", - " <td>24.999996</td>\n", - " <td>0.136198</td>\n", - " <td>15.0</td>\n", - " <td>0.013187</td>\n", - " <td>0</td>\n", - " <td>0</td>\n", - " <td>22</td>\n", - " </tr>\n", - " <tr>\n", - " <th>3</th>\n", - " <td>1.835687</td>\n", - " <td>24.999996</td>\n", - " <td>0.136189</td>\n", - " <td>20.0</td>\n", - " <td>0.013186</td>\n", - " <td>0</td>\n", - " <td>0</td>\n", - " <td>22</td>\n", - " </tr>\n", - " </tbody>\n", - "</table>\n", - "</div>" - ], - "text/plain": [ - " Depth_m Q_cms Vmag_mps CumlDistance_km Ustar_mps Vvert_mps \\\n", - "1 1.835397 24.999996 0.136210 5.0 0.013188 0 \n", - "2 1.835564 24.999996 0.136198 15.0 0.013187 0 \n", - "3 1.835687 24.999996 0.136189 20.0 0.013186 0 \n", - "\n", - " Vlat_mps Temp_C \n", - "1 0 22 \n", - "2 0 22 \n", - "3 0 22 " - ] - }, - "execution_count": 2, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "profile_name = project_profile_names[0]\n", - "\n", - "with RASProject(project_file_path) as rp:\n", - " hydraulic_data = rp.hydraulic_model_data(profile_name)\n", - "\n", - "hydraulic_data" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Finally, an instance of `RoughBottomSeriesOfHydraulicCells` is created to serve as the hydraulic model for the FluEgg simulation." - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "from fluegg.hydraulics import RoughBottomSeriesOfHydraulicCells\n", - "\n", - "# initialize a hydraulic model as a series of hydraulic cells from the DataFrame\n", - "hydraulic_model = RoughBottomSeriesOfHydraulicCells.from_data_frame(hydraulic_data)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Step 2: Simulation Clock\n", - "\n", - "Next, we need to initialize a simulation clock that will keep track of time throughout the simulation. FluEgg uses discrete time-steps when transporting eggs. The simulation clock needs to know the total simulation time and the length of each discrete time step. Below, these are initialized as 1000 seconds and 1 second respectively.\n", - "\n", - "Alternatively, the total simulation time can be set to the hatching time of the carp eggs. This is seen in the commented out line below." - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [], - "source": [ - "from fluegg.asiancarpeggs import BigheadCarpEggs\n", - "from fluegg.simclock import SimulationClock\n", - "\n", - "# total_simulation_time = BigheadCarpEggs.hatching_time(hydraulic_data['Temp_C'].mean())\n", - "total_simulation_time = 1000 # seconds\n", - "time_step_size = 1 # seconds\n", - "\n", - "simulation_clock = SimulationClock(time_step_size, total_simulation_time)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Step 3: Carp Eggs\n", - "\n", - "Next, we need to initialize the carp eggs that will be transported through the hyrdaulic channel. There are 3 carp species supported by the FluEgg program: Bighead Carp, Silver Carp, and Grass Carp. We will use the Bighead Carp species throughout this tutorial. (As a side-note, FluEgg also supports non-egg particles!)\n", - "\n", - "To initialize the carp eggs, we use the `BigheadCarpEggs(initial_position, simulation_clock)` constructor. It takes in `initial_position`, a numpy array containing the starting positions for each individual egg. In this case, there are 10 eggs starting at (10, y-midpoint, z-midpoint). The y-midpoint is calculated based on the discharge, longitudinal water velocity, and depth of the hydraulic channel. The z-midpoint is calculated based on the depth. Take note of the coordinate system used (don't worry if it's confusing, it should become clearer in the simulation graphs you'll see below).\n", - "\n", - "$Width = \\frac{Area_{yz}}{Depth} = \\frac{Discharge / Longitudinal Velocity}{Depth} = \\frac{Q / V_{mag}}{Depth}$ \n", - "\n", - "$y_{mid} = \\frac{Width}{2}, z_{mid} = \\frac{-Depth}{2}$\n", - "\n", - "The constructor also takes in `simulation_clock` which was initialized earlier. The carp eggs need the simulation clock to keep track of their changing densities and diameters over time." - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Initial Egg XYZ-Positions: \n", - " [[10. 49.99999429 -0.9176985 ]\n", - " [10. 49.99999429 -0.9176985 ]\n", - " [10. 49.99999429 -0.9176985 ]\n", - " [10. 49.99999429 -0.9176985 ]\n", - " [10. 49.99999429 -0.9176985 ]\n", - " [10. 49.99999429 -0.9176985 ]\n", - " [10. 49.99999429 -0.9176985 ]\n", - " [10. 49.99999429 -0.9176985 ]\n", - " [10. 49.99999429 -0.9176985 ]\n", - " [10. 49.99999429 -0.9176985 ]]\n" - ] - } - ], - "source": [ - "import numpy as np\n", - "\n", - "first_cell_x_midpoint = 1000*hydraulic_data.loc[1, 'CumlDistance_km']/2\n", - "\n", - "depth = hydraulic_data.loc[1, 'Depth_m']\n", - "first_cell_z_midpoint = -depth/2\n", - "\n", - "area = hydraulic_data.loc[1, 'Q_cms']/hydraulic_data.loc[1, 'Vmag_mps']\n", - "width = area/depth\n", - "first_cell_y_midpoint = width/2\n", - "\n", - "initial_position = np.array([10, first_cell_y_midpoint, first_cell_z_midpoint])\n", - "\n", - "number_of_eggs = 10\n", - "initial_position = np.tile(initial_position, (number_of_eggs, 1))\n", - "print(\"Initial Egg XYZ-Positions: \\n\", initial_position)\n", - "\n", - "carp_eggs = BigheadCarpEggs(initial_position, simulation_clock)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Step 4: Transporter\n", - "\n", - "Next, we need to initialize a transporter. The transporter in FluEgg is used to physcially move the eggs during each time step. The `init_transporter(simulation_clock, carp_eggs, hydraulic_model, vertical_turbulence)` method is used to initialize this transporter. It takes in the previously initialized simulation clock, carp eggs, hydraulic_model, and the additional parameter of the vertical turbulence profile. This tutorial uses a parabolic vertical turbulence profile, for instance, but FluEgg also supports constant and parabolic-constant profiles." - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [], - "source": [ - "from fluegg.transporter import init_transporter\n", - "\n", - "transport_model = init_transporter(simulation_clock, carp_eggs, 'parabolic')\n", - "transport_model.set_hydraulic_model(hydraulic_model)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Step 5: Simulation\n", - "\n", - "Finally, we can run the simulation! In order to run the simulation, we create a simulation from the following constructor that takes in all of the previously initialized FluEgg objects: `Simulation(hydraulic_model, carp_eggs, transport_model, simulation_clock)`. To run the simulation, we simply call `fluegg_simulation.run()` on this initialized simulation. This function runs through each time step in the clock and transports the eggs through the hyraulic channel based on the transport model. We store the simulation results produced in `simulation_results`.\n", - "\n", - "We can double-check that the simulation ran by checking the current time step from the simulation_clock. Did the simulation make it to the final time step (1000 seconds)? You can also verify the simulation ran by trying to run the code below a second time. It should output an index error at index 1001. Why would this error occur?" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Current Simulation Time: 1000.0 seconds\n" - ] - } - ], - "source": [ - "from fluegg.simulation import Simulation\n", - "\n", - "fluegg_simulation = Simulation(carp_eggs, transport_model, simulation_clock)\n", - "fluegg_simulation.set_hydraulic_model(hydraulic_model)\n", - "\n", - "simulation_results = fluegg_simulation.run()\n", - "\n", - "print(\"Current Simulation Time: \", simulation_clock.current_time(), \" seconds\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Step 6: Data Analysis\n", - "\n", - "Now that we have run the FluEgg simulation, we can retrieve all sorts of data stored in the simulation. We will visualize some of the data below using the matplotlib library. The most interesting data to look at is the egg positions over time. Below, we can see how the eggs move longitudinally (x), laterally (y), and vertically (z) through the channel over time. We additionally plot the xyz-positions against eachother throughout the simulation to see the egg paths throughout the simulation.\n", - "\n", - "We retrieve these positions by using the `simulation_results.get_results()` function which returns the positions of the carp eggs over time." - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "<Figure size 720x576 with 3 Axes>" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "%matplotlib inline\n", - "import matplotlib.pyplot as plt\n", - "\n", - "positions = simulation_results.results()\n", - "\n", - "time = simulation_clock.time_array()\n", - "\n", - "x = positions[:, :, 0]\n", - "y = positions[:, :, 1]\n", - "z = positions[:, :, 2]\n", - "\n", - "fig = plt.figure(figsize=(10,8))\n", - "\n", - "x_position_axes = fig.add_subplot(311)\n", - "_ = x_position_axes.plot(time, x, '.')\n", - "_ = x_position_axes.set_ylabel('x')\n", - "\n", - "y_position_axes = fig.add_subplot(312, sharex=x_position_axes)\n", - "_ = y_position_axes.plot(time, y, '.')\n", - "_ = y_position_axes.set_ylabel('y')\n", - "\n", - "z_position_axes = fig.add_subplot(313, sharex=x_position_axes)\n", - "_ = z_position_axes.plot(time, z, '.')\n", - "_ = z_position_axes.set_ylabel('z')\n", - "_ = z_position_axes.set_xlabel('time')" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": { - "scrolled": false - }, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "<Figure size 720x576 with 3 Axes>" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fig = plt.figure(figsize=(10,8))\n", - "\n", - "xy_axes = fig.add_subplot(221)\n", - "_ = xy_axes.plot(x, y, '.')\n", - "_ = xy_axes.set_ylabel('y')\n", - "\n", - "xz_axes = fig.add_subplot(223, sharex=xy_axes)\n", - "_ = xz_axes.plot(x, z, '.')\n", - "_ = xz_axes.set_ylabel('z')\n", - "_ = xz_axes.set_xlabel('x')\n", - "\n", - "yz_axes = fig.add_subplot(224, sharey=xz_axes)\n", - "_ = yz_axes.plot(y, z, '.')\n", - "_ = yz_axes.set_xlabel('y')" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "<Figure size 432x288 with 1 Axes>" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "from mpl_toolkits.mplot3d import Axes3D\n", - "fig = plt.figure()\n", - "\n", - "# 3-Dimensional plotting!\n", - "ax = fig.add_subplot(111, projection='3d')\n", - "\n", - "# Only look at the 1st egg\n", - "for i in range(1):\n", - " ax.scatter(x.transpose()[i], y.transpose()[i], z.transpose()[i])\n", - " \n", - "# Set view angle\n", - "ax.view_init(20, -70)\n", - "ax.set_xlabel('X')\n", - "ax.set_ylabel('Y')\n", - "ax.set_zlabel('Z')\n", - "plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([[112.87246867, 52.99250149, -1.81554181],\n", - " [129.23256286, 50.34731347, -0.31828964],\n", - " [157.96565746, 49.07607002, -1.48092605],\n", - " [114.32742594, 62.98863475, -1.82608929],\n", - " [101.44406675, 54.21796584, -1.76485366],\n", - " [176.2605702 , 56.11526941, -1.4431294 ],\n", - " [126.78326949, 44.02848669, -1.34415829],\n", - " [156.50789027, 59.28279066, -1.78484798],\n", - " [138.09939604, 48.38843799, -1.34070468],\n", - " [108.51932843, 57.81323762, -1.77115225]])" - ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# final positions\n", - "# rows are eggs, columns are x, y, z\n", - "positions[-1, :, :]" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Other Tutorials\n", - "\n", - "There are plenty of other ways to extract data out of FluEgg. If you are interested in learning more, try out the other jupyter notebooks in this directory to see the capabilities of FluEgg!" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.6.6" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/notebooks/fluegg-tutorial.ipynb b/notebooks/fluegg-tutorial.ipynb deleted file mode 100644 index e9ae0c9..0000000 --- a/notebooks/fluegg-tutorial.ipynb +++ /dev/null @@ -1,485 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# FluEgg Tutorial\n", - "\n", - "Welcome to FluEgg! This tutorial will show you the basics for how to setup and run the FluEgg program, a model that simulates carp eggs being transported through a fluvial channel." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Step 1: Hydraulic Channel\n", - "\n", - "First, we will import hyraulic channel data. The channel data is input by the user and is composed of hydraulic cells representing discrete lengths of a channel. Each cell contains the following data that defines the cell:\n", - "* Cumulative channel distance $(km)$\n", - "* Cell depth $(m)$\n", - "* Discharge $(m^3/s), Q$\n", - "* Longitudinal velocity $(m/s), V_{mag}$\n", - "* Vertical velocity $(m/s), V_{vert}$\n", - "* Lateral velocity $(m/s), V_{lat}$\n", - "* Shear velocity $(m/s), u_{*}$\n", - "* Temperature $(Celsius)$\n", - "\n", - "FluEgg includes a sample 5-cell hydraulic channel in the `test/data/multi-cell input.csv` file. Below, we use the pandas data analysis package to show the sample hydraulic data stored in the csv file.\n", - "\n", - "To initialize this hydraulic model in FluEgg, we use the function `from_csv(csv_path)` from the `fluegg.hydraulics` module." - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "<div>\n", - "<style scoped>\n", - " .dataframe tbody tr th:only-of-type {\n", - " vertical-align: middle;\n", - " }\n", - "\n", - " .dataframe tbody tr th {\n", - " vertical-align: top;\n", - " }\n", - "\n", - " .dataframe thead th {\n", - " text-align: right;\n", - " }\n", - "</style>\n", - "<table border=\"1\" class=\"dataframe\">\n", - " <thead>\n", - " <tr style=\"text-align: right;\">\n", - " <th></th>\n", - " <th>CumlDistance_km</th>\n", - " <th>Depth_m</th>\n", - " <th>Q_cms</th>\n", - " <th>Vmag_mps</th>\n", - " <th>Vvert_mps</th>\n", - " <th>Vlat_mps</th>\n", - " <th>Ustar_mps</th>\n", - " <th>Temp_C</th>\n", - " </tr>\n", - " <tr>\n", - " <th>CellNumber</th>\n", - " <th></th>\n", - " <th></th>\n", - " <th></th>\n", - " <th></th>\n", - " <th></th>\n", - " <th></th>\n", - " <th></th>\n", - " <th></th>\n", - " </tr>\n", - " </thead>\n", - " <tbody>\n", - " <tr>\n", - " <th>1</th>\n", - " <td>20</td>\n", - " <td>1</td>\n", - " <td>10</td>\n", - " <td>1</td>\n", - " <td>0</td>\n", - " <td>0</td>\n", - " <td>0.08</td>\n", - " <td>19</td>\n", - " </tr>\n", - " <tr>\n", - " <th>2</th>\n", - " <td>40</td>\n", - " <td>2</td>\n", - " <td>20</td>\n", - " <td>2</td>\n", - " <td>0</td>\n", - " <td>0</td>\n", - " <td>0.08</td>\n", - " <td>20</td>\n", - " </tr>\n", - " <tr>\n", - " <th>3</th>\n", - " <td>60</td>\n", - " <td>3</td>\n", - " <td>30</td>\n", - " <td>3</td>\n", - " <td>0</td>\n", - " <td>0</td>\n", - " <td>0.08</td>\n", - " <td>21</td>\n", - " </tr>\n", - " <tr>\n", - " <th>4</th>\n", - " <td>80</td>\n", - " <td>4</td>\n", - " <td>40</td>\n", - " <td>4</td>\n", - " <td>0</td>\n", - " <td>0</td>\n", - " <td>0.08</td>\n", - " <td>22</td>\n", - " </tr>\n", - " <tr>\n", - " <th>5</th>\n", - " <td>100</td>\n", - " <td>5</td>\n", - " <td>50</td>\n", - " <td>5</td>\n", - " <td>0</td>\n", - " <td>0</td>\n", - " <td>0.08</td>\n", - " <td>23</td>\n", - " </tr>\n", - " </tbody>\n", - "</table>\n", - "</div>" - ], - "text/plain": [ - " CumlDistance_km Depth_m Q_cms Vmag_mps Vvert_mps Vlat_mps \\\n", - "CellNumber \n", - "1 20 1 10 1 0 0 \n", - "2 40 2 20 2 0 0 \n", - "3 60 3 30 3 0 0 \n", - "4 80 4 40 4 0 0 \n", - "5 100 5 50 5 0 0 \n", - "\n", - " Ustar_mps Temp_C \n", - "CellNumber \n", - "1 0.08 19 \n", - "2 0.08 20 \n", - "3 0.08 21 \n", - "4 0.08 22 \n", - "5 0.08 23 " - ] - }, - "execution_count": 1, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "import os\n", - "import pandas as pd\n", - "\n", - "# show the hydraulic data contained in the CSV file\n", - "hydraulic_csv_path = os.path.join('..', 'test', 'data', 'multi-cell input.csv')\n", - "hydraulic_data = pd.read_csv(hydraulic_csv_path, index_col='CellNumber')\n", - "hydraulic_data" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "from fluegg.hydraulics import from_csv\n", - "\n", - "# initialize a hydraulic model as a series of hydraulic cells from the CSV\n", - "hydraulic_model = from_csv(hydraulic_csv_path)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Step 2: Simulation Clock\n", - "\n", - "Next, we need to initialize a simulation clock that will keep track of time throughout the simulation. FluEgg uses discrete time-steps when transporting eggs. The simulation clock needs to know the total simulation time and the length of each discrete time step. Below, these are initialized as 1000 seconds and 1 second respectively.\n", - "\n", - "Alternatively, the total simulation time can be set to the hatching time of the carp eggs. This is seen in the commented out line below." - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "from fluegg.asiancarpeggs import BigheadCarpEggs\n", - "from fluegg.simclock import SimulationClock\n", - "\n", - "# total_simulation_time = BigheadCarpEggs.hatching_time(hydraulic_data['Temp_C'].mean())\n", - "total_simulation_time = 1000 # seconds\n", - "time_step_size = 1 # seconds\n", - "\n", - "simulation_clock = SimulationClock(time_step_size, total_simulation_time)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Step 3: Carp Eggs\n", - "\n", - "Next, we need to initialize the carp eggs that will be transported through the hyrdaulic channel. There are 3 carp species supported by the FluEgg program: Bighead Carp, Silver Carp, and Grass Carp. We will use the Bighead Carp species throughout this tutorial. (As a side-note, FluEgg also supports non-egg particles!)\n", - "\n", - "To initialize the carp eggs, we use the `BigheadCarpEggs(initial_position, simulation_clock)` constructor. It takes in `initial_position`, a numpy array containing the starting positions for each individual egg. In this case, there are 10 eggs starting at (10, y-midpoint, z-midpoint). The y-midpoint is calculated based on the discharge, longitudinal water velocity, and depth of the hydraulic channel. The z-midpoint is calculated based on the depth. Take note of the coordinate system used (don't worry if it's confusing, it should become clearer in the simulation graphs you'll see below).\n", - "\n", - "$Width = \\frac{Area_{yz}}{Depth} = \\frac{Discharge / Longitudinal Velocity}{Depth} = \\frac{Q / V_{mag}}{Depth}$ \n", - "\n", - "$y_{mid} = \\frac{Width}{2}, z_{mid} = \\frac{-Depth}{2}$\n", - "\n", - "The constructor also takes in `simulation_clock` which was initialized earlier. The carp eggs need the simulation clock to keep track of their changing densities and diameters over time." - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Initial Egg XYZ-Positions: \n", - " [[10. 5. -0.5]\n", - " [10. 5. -0.5]\n", - " [10. 5. -0.5]\n", - " [10. 5. -0.5]\n", - " [10. 5. -0.5]\n", - " [10. 5. -0.5]\n", - " [10. 5. -0.5]\n", - " [10. 5. -0.5]\n", - " [10. 5. -0.5]\n", - " [10. 5. -0.5]]\n" - ] - } - ], - "source": [ - "import numpy as np\n", - "\n", - "first_cell_x_midpoint = 1000*hydraulic_data.loc[1, 'CumlDistance_km']/2\n", - "\n", - "depth = hydraulic_data.loc[1, 'Depth_m']\n", - "first_cell_z_midpoint = -depth/2\n", - "\n", - "area = hydraulic_data.loc[1, 'Q_cms']/hydraulic_data.loc[1, 'Vmag_mps']\n", - "width = area/depth\n", - "first_cell_y_midpoint = width/2\n", - "\n", - "initial_position = np.array([10, first_cell_y_midpoint, first_cell_z_midpoint])\n", - "\n", - "number_of_eggs = 10\n", - "initial_position = np.tile(initial_position, (number_of_eggs, 1))\n", - "print(\"Initial Egg XYZ-Positions: \\n\", initial_position)\n", - "\n", - "carp_eggs = BigheadCarpEggs(initial_position, simulation_clock)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Step 4: Transporter\n", - "\n", - "Next, we need to initialize a transporter. The transporter in FluEgg is used to physcially move the eggs during each time step. The `init_transporter(simulation_clock, carp_eggs, hydraulic_model, vertical_turbulence)` method is used to initialize this transporter. It takes in the previously initialized simulation clock, carp eggs, hydraulic_model, and the additional parameter of the vertical turbulence profile. This tutorial uses a parabolic vertical turbulence profile, for instance, but FluEgg also supports constant and parabolic-constant profiles." - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [], - "source": [ - "from fluegg.transporter import init_transporter\n", - "\n", - "transport_model = init_transporter(simulation_clock, carp_eggs, 'parabolic')\n", - "transport_model.set_hydraulic_model(hydraulic_model)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Step 5: Simulation\n", - "\n", - "Finally, we can run the simulation! In order to run the simulation, we create a simulation from the following constructor that takes in all of the previously initialized FluEgg objects: `Simulation(hydraulic_model, carp_eggs, transport_model, simulation_clock)`. To run the simulation, we simply call `fluegg_simulation.run()` on this initialized simulation. This function runs through each time step in the clock and transports the eggs through the hyraulic channel based on the transport model. We store the simulation results produced in `simulation_results`.\n", - "\n", - "We can double-check that the simulation ran by checking the current time step from the simulation_clock. Did the simulation make it to the final time step (1000 seconds)? You can also verify the simulation ran by trying to run the code below a second time. It should output an index error at index 1001. Why would this error occur?" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Current Simulation Time: 1000.0 seconds\n" - ] - } - ], - "source": [ - "from fluegg.simulation import Simulation\n", - "\n", - "fluegg_simulation = Simulation(carp_eggs, transport_model, simulation_clock)\n", - "fluegg_simulation.set_hydraulic_model(hydraulic_model)\n", - "\n", - "simulation_results = fluegg_simulation.run()\n", - "\n", - "print(\"Current Simulation Time: \", simulation_clock.current_time(), \" seconds\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Step 6: Data Analysis\n", - "\n", - "Now that we have run the FluEgg simulation, we can retrieve all sorts of data stored in the simulation. We will visualize some of the data below using the matplotlib library. The most interesting data to look at is the egg positions over time. Below, we can see how the eggs move longitudinally (x), laterally (y), and vertically (z) through the channel over time. We additionally plot the xyz-positions against eachother throughout the simulation to see the egg paths throughout the simulation.\n", - "\n", - "We retrieve these positions by using the `simulation_results.get_results()` function which returns the positions of the carp eggs over time." - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "<Figure size 720x576 with 3 Axes>" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "%matplotlib inline\n", - "import matplotlib.pyplot as plt\n", - "\n", - "positions = simulation_results.results()\n", - "\n", - "time = simulation_clock.time_array()\n", - "\n", - "x = positions[:, :, 0]\n", - "y = positions[:, :, 1]\n", - "z = positions[:, :, 2]\n", - "\n", - "fig = plt.figure(figsize=(10,8))\n", - "\n", - "x_position_axes = fig.add_subplot(311)\n", - "_ = x_position_axes.plot(time, x, '.')\n", - "_ = x_position_axes.set_ylabel('x')\n", - "\n", - "y_position_axes = fig.add_subplot(312, sharex=x_position_axes)\n", - "_ = y_position_axes.plot(time, y, '.')\n", - "_ = y_position_axes.set_ylabel('y')\n", - "\n", - "z_position_axes = fig.add_subplot(313, sharex=x_position_axes)\n", - "_ = z_position_axes.plot(time, z, '.')\n", - "_ = z_position_axes.set_ylabel('z')\n", - "_ = z_position_axes.set_xlabel('time')" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": { - "scrolled": false - }, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "<Figure size 720x576 with 3 Axes>" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fig = plt.figure(figsize=(10,8))\n", - "\n", - "xy_axes = fig.add_subplot(221)\n", - "_ = xy_axes.plot(x, y, '.')\n", - "_ = xy_axes.set_ylabel('y')\n", - "\n", - "xz_axes = fig.add_subplot(223, sharex=xy_axes)\n", - "_ = xz_axes.plot(x, z, '.')\n", - "_ = xz_axes.set_ylabel('z')\n", - "_ = xz_axes.set_xlabel('x')\n", - "\n", - "yz_axes = fig.add_subplot(224, sharey=xz_axes)\n", - "_ = yz_axes.plot(y, z, '.')\n", - "_ = yz_axes.set_xlabel('y')" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "<Figure size 432x288 with 1 Axes>" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "from mpl_toolkits.mplot3d import Axes3D\n", - "fig = plt.figure()\n", - "\n", - "# 3-Dimensional plotting!\n", - "ax = fig.add_subplot(111, projection='3d')\n", - "\n", - "# Only look at the 1st egg\n", - "for i in range(1):\n", - " ax.scatter(x.transpose()[i], y.transpose()[i], z.transpose()[i])\n", - " \n", - "# Set view angle\n", - "ax.view_init(20, -70)\n", - "ax.set_xlabel('X')\n", - "ax.set_ylabel('Y')\n", - "ax.set_zlabel('Z')\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Other Tutorials\n", - "\n", - "There are plenty of other ways to extract data out of FluEgg. If you are interested in learning more, try out the other jupyter notebooks in this directory to see the capabilities of FluEgg!" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.6.6" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/notebooks/hydraulic model.ipynb b/notebooks/hydraulic model.ipynb deleted file mode 100644 index 0f512a3..0000000 --- a/notebooks/hydraulic model.ipynb +++ /dev/null @@ -1,300 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "<div>\n", - "<style scoped>\n", - " .dataframe tbody tr th:only-of-type {\n", - " vertical-align: middle;\n", - " }\n", - "\n", - " .dataframe tbody tr th {\n", - " vertical-align: top;\n", - " }\n", - "\n", - " .dataframe thead th {\n", - " text-align: right;\n", - " }\n", - "</style>\n", - "<table border=\"1\" class=\"dataframe\">\n", - " <thead>\n", - " <tr style=\"text-align: right;\">\n", - " <th></th>\n", - " <th>CumlDistance_km</th>\n", - " <th>Depth_m</th>\n", - " <th>Q_cms</th>\n", - " <th>Vmag_mps</th>\n", - " <th>Vvert_mps</th>\n", - " <th>Vlat_mps</th>\n", - " <th>Ustar_mps</th>\n", - " <th>Temp_C</th>\n", - " </tr>\n", - " <tr>\n", - " <th>CellNumber</th>\n", - " <th></th>\n", - " <th></th>\n", - " <th></th>\n", - " <th></th>\n", - " <th></th>\n", - " <th></th>\n", - " <th></th>\n", - " <th></th>\n", - " </tr>\n", - " </thead>\n", - " <tbody>\n", - " <tr>\n", - " <th>1</th>\n", - " <td>20</td>\n", - " <td>1</td>\n", - " <td>10</td>\n", - " <td>1</td>\n", - " <td>0</td>\n", - " <td>0</td>\n", - " <td>0.08</td>\n", - " <td>19</td>\n", - " </tr>\n", - " <tr>\n", - " <th>2</th>\n", - " <td>40</td>\n", - " <td>2</td>\n", - " <td>20</td>\n", - " <td>2</td>\n", - " <td>0</td>\n", - " <td>0</td>\n", - " <td>0.08</td>\n", - " <td>20</td>\n", - " </tr>\n", - " <tr>\n", - " <th>3</th>\n", - " <td>60</td>\n", - " <td>3</td>\n", - " <td>30</td>\n", - " <td>3</td>\n", - " <td>0</td>\n", - " <td>0</td>\n", - " <td>0.08</td>\n", - " <td>21</td>\n", - " </tr>\n", - " <tr>\n", - " <th>4</th>\n", - " <td>80</td>\n", - " <td>4</td>\n", - " <td>40</td>\n", - " <td>4</td>\n", - " <td>0</td>\n", - " <td>0</td>\n", - " <td>0.08</td>\n", - " <td>22</td>\n", - " </tr>\n", - " <tr>\n", - " <th>5</th>\n", - " <td>100</td>\n", - " <td>5</td>\n", - " <td>50</td>\n", - " <td>5</td>\n", - " <td>0</td>\n", - " <td>0</td>\n", - " <td>0.08</td>\n", - " <td>23</td>\n", - " </tr>\n", - " </tbody>\n", - "</table>\n", - "</div>" - ], - "text/plain": [ - " CumlDistance_km Depth_m Q_cms Vmag_mps Vvert_mps Vlat_mps \\\n", - "CellNumber \n", - "1 20 1 10 1 0 0 \n", - "2 40 2 20 2 0 0 \n", - "3 60 3 30 3 0 0 \n", - "4 80 4 40 4 0 0 \n", - "5 100 5 50 5 0 0 \n", - "\n", - " Ustar_mps Temp_C \n", - "CellNumber \n", - "1 0.08 19 \n", - "2 0.08 20 \n", - "3 0.08 21 \n", - "4 0.08 22 \n", - "5 0.08 23 " - ] - }, - "execution_count": 1, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "import os\n", - "\n", - "import pandas as pd\n", - "\n", - "\n", - "# show the hydraulic data contained in the CSV file\n", - "hydraulic_csv_path = os.path.join('..', 'test', 'data', 'multi-cell input.csv')\n", - "hydraulic_data = pd.read_csv(hydraulic_csv_path, index_col='CellNumber')\n", - "hydraulic_data" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "from fluegg.hydraulics import from_csv\n", - "\n", - "# initialize a hydraulic model as a series of hydraulic cells from the CSV\n", - "hydraulic_model = from_csv(hydraulic_csv_path)" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "<Figure size 432x288 with 1 Axes>" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "%matplotlib inline\n", - "import numpy as np\n", - "import matplotlib.pyplot as plt\n", - "\n", - "cell_distance = hydraulic_data['CumlDistance_km'].diff()\n", - "beginning_of_cells = hydraulic_data['CumlDistance_km'].values - cell_distance.values\n", - "beginning_of_cells[0] = 0\n", - "end_of_cells = hydraulic_data['CumlDistance_km'] - 0.001\n", - "\n", - "x_position = 1000*np.hstack((beginning_of_cells, end_of_cells))\n", - "x_position.sort()\n", - "\n", - "y_position = np.zeros(x_position.shape)\n", - "z_position = np.zeros(y_position.shape)\n", - "\n", - "position = np.stack((x_position, y_position, z_position)).transpose()\n", - "\n", - "hydraulic_results = hydraulic_model.hydraulic_results(position)\n", - "\n", - "depth = hydraulic_results.depth()\n", - "\n", - "water_surface_z = np.zeros(x_position.shape)\n", - "_ = plt.plot(x_position, water_surface_z, label='Water surface')\n", - "_ = plt.plot(x_position, depth, label='Channel bed')\n", - "_ = plt.xlabel('Distance down stream, in m')\n", - "_ = plt.ylabel('Depth, in meters')\n", - "_ = plt.legend()\n", - "plt.gca().invert_yaxis()\n", - "plt.autoscale(axis='x', tight=True)" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "<Figure size 432x288 with 1 Axes>" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "x_midpoint_of_cell = (hydraulic_data.loc[2, 'CumlDistance_km'] + hydraulic_data.loc[3, 'CumlDistance_km'])/2\n", - "\n", - "cell_area = hydraulic_data.loc[3, 'Q_cms']/hydraulic_data.loc[3, 'Vmag_mps']\n", - "cell_width = cell_area/hydraulic_data.loc[3, 'Depth_m']\n", - "y_midpoint_of_cell = cell_width/2\n", - "\n", - "num = 100\n", - "x_position = 1000*np.tile(x_midpoint_of_cell, num)\n", - "y_position = np.tile(y_midpoint_of_cell, num)\n", - "\n", - "eps = 1e-6\n", - "z_position = np.linspace(0, -(1-eps)*hydraulic_data.loc[3, 'Depth_m'], num)\n", - "position = np.stack((x_position, y_position, z_position)).transpose()\n", - "\n", - "hydraulic_results = hydraulic_model.hydraulic_results(position)\n", - "\n", - "velocity = hydraulic_results.streamwise_velocity()\n", - "\n", - "_ = plt.plot(velocity, z_position)\n", - "_ = plt.xlabel('Velocity, in m/s')\n", - "_ = plt.ylabel('Z, in m')" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "<Figure size 432x288 with 1 Axes>" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "y_position = np.linspace(0, cell_width, num)\n", - "z_position = np.tile(-hydraulic_data.loc[3, 'Depth_m']/2, num)\n", - "\n", - "position = np.stack((x_position, y_position, z_position)).transpose()\n", - "\n", - "hydraulic_results = hydraulic_model.hydraulic_results(position)\n", - "\n", - "velocity = hydraulic_results.streamwise_velocity()\n", - "\n", - "_ = plt.plot(y_position, velocity)\n", - "_ = plt.xlabel('Distance across channel, in m')\n", - "_ = plt.ylabel('Velocity, in m/s')\n", - "plt.gca().invert_xaxis()\n", - "plt.autoscale(axis='x', tight=True)" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.6.6" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/notebooks/lateral transporter.ipynb b/notebooks/lateral transporter.ipynb deleted file mode 100644 index edcec08..0000000 --- a/notebooks/lateral transporter.ipynb +++ /dev/null @@ -1,339 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "<div>\n", - "<style scoped>\n", - " .dataframe tbody tr th:only-of-type {\n", - " vertical-align: middle;\n", - " }\n", - "\n", - " .dataframe tbody tr th {\n", - " vertical-align: top;\n", - " }\n", - "\n", - " .dataframe thead th {\n", - " text-align: right;\n", - " }\n", - "</style>\n", - "<table border=\"1\" class=\"dataframe\">\n", - " <thead>\n", - " <tr style=\"text-align: right;\">\n", - " <th></th>\n", - " <th>CumlDistance_km</th>\n", - " <th>Depth_m</th>\n", - " <th>Q_cms</th>\n", - " <th>Vmag_mps</th>\n", - " <th>Vvert_mps</th>\n", - " <th>Vlat_mps</th>\n", - " <th>Ustar_mps</th>\n", - " <th>Temp_C</th>\n", - " </tr>\n", - " <tr>\n", - " <th>CellNumber</th>\n", - " <th></th>\n", - " <th></th>\n", - " <th></th>\n", - " <th></th>\n", - " <th></th>\n", - " <th></th>\n", - " <th></th>\n", - " <th></th>\n", - " </tr>\n", - " </thead>\n", - " <tbody>\n", - " <tr>\n", - " <th>1</th>\n", - " <td>20</td>\n", - " <td>1</td>\n", - " <td>10</td>\n", - " <td>1</td>\n", - " <td>0</td>\n", - " <td>0</td>\n", - " <td>0.08</td>\n", - " <td>19</td>\n", - " </tr>\n", - " <tr>\n", - " <th>2</th>\n", - " <td>40</td>\n", - " <td>2</td>\n", - " <td>20</td>\n", - " <td>2</td>\n", - " <td>0</td>\n", - " <td>0</td>\n", - " <td>0.08</td>\n", - " <td>20</td>\n", - " </tr>\n", - " <tr>\n", - " <th>3</th>\n", - " <td>60</td>\n", - " <td>3</td>\n", - " <td>30</td>\n", - " <td>3</td>\n", - " <td>0</td>\n", - " <td>0</td>\n", - " <td>0.08</td>\n", - " <td>21</td>\n", - " </tr>\n", - " <tr>\n", - " <th>4</th>\n", - " <td>80</td>\n", - " <td>4</td>\n", - " <td>40</td>\n", - " <td>4</td>\n", - " <td>0</td>\n", - " <td>0</td>\n", - " <td>0.08</td>\n", - " <td>22</td>\n", - " </tr>\n", - " <tr>\n", - " <th>5</th>\n", - " <td>100</td>\n", - " <td>5</td>\n", - " <td>50</td>\n", - " <td>5</td>\n", - " <td>0</td>\n", - " <td>0</td>\n", - " <td>0.08</td>\n", - " <td>23</td>\n", - " </tr>\n", - " </tbody>\n", - "</table>\n", - "</div>" - ], - "text/plain": [ - " CumlDistance_km Depth_m Q_cms Vmag_mps Vvert_mps Vlat_mps \\\n", - "CellNumber \n", - "1 20 1 10 1 0 0 \n", - "2 40 2 20 2 0 0 \n", - "3 60 3 30 3 0 0 \n", - "4 80 4 40 4 0 0 \n", - "5 100 5 50 5 0 0 \n", - "\n", - " Ustar_mps Temp_C \n", - "CellNumber \n", - "1 0.08 19 \n", - "2 0.08 20 \n", - "3 0.08 21 \n", - "4 0.08 22 \n", - "5 0.08 23 " - ] - }, - "execution_count": 1, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "import os\n", - "\n", - "import pandas as pd\n", - "\n", - "\n", - "# show the hydraulic data contained in the CSV file\n", - "hydraulic_csv_path = os.path.join('..', 'test', 'data', 'multi-cell input.csv')\n", - "hydraulic_data = pd.read_csv(hydraulic_csv_path, index_col='CellNumber')\n", - "hydraulic_data" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "from fluegg.hydraulics import from_csv\n", - "\n", - "# initialize a hydraulic model as a series of hydraulic cells from the CSV\n", - "hydraulic_model = from_csv(hydraulic_csv_path)" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "from fluegg.asiancarpeggs import BigheadCarpEggs\n", - "from fluegg.simclock import SimulationClock\n", - "\n", - "# total_simulation_time = BigheadCarpEggs.hatching_time(hydraulic_data['Temp_C'].mean())\n", - "total_simulation_time = 1000 # seconds\n", - "time_step_size = 1 # seconds\n", - "\n", - "simulation_clock = SimulationClock(time_step_size, total_simulation_time)" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [], - "source": [ - "import numpy as np\n", - "\n", - "\n", - "first_cell_x_midpoint = 1000*hydraulic_data.loc[1, 'CumlDistance_km']/2\n", - "\n", - "depth = hydraulic_data.loc[1, 'Depth_m']\n", - "first_cell_z_midpoint = -depth/2\n", - "\n", - "area = hydraulic_data.loc[1, 'Q_cms']/hydraulic_data.loc[1, 'Vmag_mps']\n", - "width = area/depth\n", - "first_cell_y_midpoint = width/2\n", - "\n", - "initial_position = np.array([10, first_cell_y_midpoint, first_cell_z_midpoint])\n", - "\n", - "number_of_eggs = 10\n", - "initial_position = np.tile(initial_position, (number_of_eggs, 1))\n", - "\n", - "carp_eggs = BigheadCarpEggs(initial_position, simulation_clock)" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [], - "source": [ - "from fluegg.transporter import LateralTransporter\n", - "\n", - "transport_model = LateralTransporter(simulation_clock, carp_eggs)\n", - "transport_model.set_hydraulic_model(hydraulic_model)" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "1000" - ] - }, - "execution_count": 6, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "from fluegg.simulation import Simulation\n", - "\n", - "fluegg_simulation = Simulation(carp_eggs, transport_model, simulation_clock)\n", - "fluegg_simulation.set_hydraulic_model(hydraulic_model)\n", - "\n", - "simulation_results = fluegg_simulation.run()\n", - "\n", - "simulation_clock.current_time()" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "<Figure size 720x576 with 3 Axes>" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "%matplotlib inline\n", - "import matplotlib.pyplot as plt\n", - "\n", - "positions = simulation_results.results()\n", - "\n", - "time = simulation_clock.time_array()\n", - "\n", - "x = positions[:, :, 0]\n", - "y = positions[:, :, 1]\n", - "z = positions[:, :, 2]\n", - "\n", - "fig = plt.figure(figsize=(10,8))\n", - "\n", - "x_position_axes = fig.add_subplot(311)\n", - "_ = x_position_axes.plot(time, x, '.')\n", - "_ = x_position_axes.set_ylabel('x')\n", - "\n", - "y_position_axes = fig.add_subplot(312, sharex=x_position_axes)\n", - "_ = y_position_axes.plot(time, y, '.')\n", - "_ = y_position_axes.set_ylabel('y')\n", - "\n", - "z_position_axes = fig.add_subplot(313, sharex=x_position_axes)\n", - "_ = z_position_axes.plot(time, z, '.')\n", - "_ = z_position_axes.set_ylabel('z')\n", - "_ = z_position_axes.set_xlabel('time')" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": { - "scrolled": false - }, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "<Figure size 720x576 with 3 Axes>" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fig = plt.figure(figsize=(10,8))\n", - "\n", - "xy_axes = fig.add_subplot(221)\n", - "_ = xy_axes.plot(x, y, '.')\n", - "_ = xy_axes.set_ylabel('y')\n", - "\n", - "xz_axes = fig.add_subplot(223, sharex=xy_axes)\n", - "_ = xz_axes.plot(x, z, '.')\n", - "_ = xz_axes.set_ylabel('z')\n", - "_ = xz_axes.set_xlabel('x')\n", - "\n", - "zy_axes = fig.add_subplot(222, sharey=xy_axes)\n", - "_ = zy_axes.plot(z, y, '.')\n", - "_ = zy_axes.set_xlabel('z')" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.6.6" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/notebooks/longitudinal transporter.ipynb b/notebooks/longitudinal transporter.ipynb deleted file mode 100644 index 89d01ab..0000000 --- a/notebooks/longitudinal transporter.ipynb +++ /dev/null @@ -1,326 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "<div>\n", - "<style scoped>\n", - " .dataframe tbody tr th:only-of-type {\n", - " vertical-align: middle;\n", - " }\n", - "\n", - " .dataframe tbody tr th {\n", - " vertical-align: top;\n", - " }\n", - "\n", - " .dataframe thead th {\n", - " text-align: right;\n", - " }\n", - "</style>\n", - "<table border=\"1\" class=\"dataframe\">\n", - " <thead>\n", - " <tr style=\"text-align: right;\">\n", - " <th></th>\n", - " <th>CumlDistance_km</th>\n", - " <th>Depth_m</th>\n", - " <th>Q_cms</th>\n", - " <th>Vmag_mps</th>\n", - " <th>Vvert_mps</th>\n", - " <th>Vlat_mps</th>\n", - " <th>Ustar_mps</th>\n", - " <th>Temp_C</th>\n", - " </tr>\n", - " <tr>\n", - " <th>CellNumber</th>\n", - " <th></th>\n", - " <th></th>\n", - " <th></th>\n", - " <th></th>\n", - " <th></th>\n", - " <th></th>\n", - " <th></th>\n", - " <th></th>\n", - " </tr>\n", - " </thead>\n", - " <tbody>\n", - " <tr>\n", - " <th>1</th>\n", - " <td>20</td>\n", - " <td>1</td>\n", - " <td>10</td>\n", - " <td>1</td>\n", - " <td>0</td>\n", - " <td>0</td>\n", - " <td>0.08</td>\n", - " <td>19</td>\n", - " </tr>\n", - " <tr>\n", - " <th>2</th>\n", - " <td>40</td>\n", - " <td>2</td>\n", - " <td>20</td>\n", - " <td>2</td>\n", - " <td>0</td>\n", - " <td>0</td>\n", - " <td>0.08</td>\n", - " <td>20</td>\n", - " </tr>\n", - " <tr>\n", - " <th>3</th>\n", - " <td>60</td>\n", - " <td>3</td>\n", - " <td>30</td>\n", - " <td>3</td>\n", - " <td>0</td>\n", - " <td>0</td>\n", - " <td>0.08</td>\n", - " <td>21</td>\n", - " </tr>\n", - " <tr>\n", - " <th>4</th>\n", - " <td>80</td>\n", - " <td>4</td>\n", - " <td>40</td>\n", - " <td>4</td>\n", - " <td>0</td>\n", - " <td>0</td>\n", - " <td>0.08</td>\n", - " <td>22</td>\n", - " </tr>\n", - " <tr>\n", - " <th>5</th>\n", - " <td>100</td>\n", - " <td>5</td>\n", - " <td>50</td>\n", - " <td>5</td>\n", - " <td>0</td>\n", - " <td>0</td>\n", - " <td>0.08</td>\n", - " <td>23</td>\n", - " </tr>\n", - " </tbody>\n", - "</table>\n", - "</div>" - ], - "text/plain": [ - " CumlDistance_km Depth_m Q_cms Vmag_mps Vvert_mps Vlat_mps \\\n", - "CellNumber \n", - "1 20 1 10 1 0 0 \n", - "2 40 2 20 2 0 0 \n", - "3 60 3 30 3 0 0 \n", - "4 80 4 40 4 0 0 \n", - "5 100 5 50 5 0 0 \n", - "\n", - " Ustar_mps Temp_C \n", - "CellNumber \n", - "1 0.08 19 \n", - "2 0.08 20 \n", - "3 0.08 21 \n", - "4 0.08 22 \n", - "5 0.08 23 " - ] - }, - "execution_count": 1, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "import os\n", - "\n", - "import pandas as pd\n", - "\n", - "\n", - "# show the hydraulic data contained in the CSV file\n", - "hydraulic_csv_path = os.path.join('..', 'test', 'data', 'multi-cell input.csv')\n", - "hydraulic_data = pd.read_csv(hydraulic_csv_path, index_col='CellNumber')\n", - "hydraulic_data" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "from fluegg.hydraulics import from_csv\n", - "\n", - "# initialize a hydraulic model as a series of hydraulic cells from the CSV\n", - "hydraulic_model = from_csv(hydraulic_csv_path)" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "from fluegg.asiancarpeggs import BigheadCarpEggs\n", - "from fluegg.simclock import SimulationClock\n", - "\n", - "# total_simulation_time = BigheadCarpEggs.hatching_time(hydraulic_data['Temp_C'].mean())\n", - "total_simulation_time = 1000 # seconds\n", - "time_step_size = 1 # seconds\n", - "\n", - "simulation_clock = SimulationClock(time_step_size, total_simulation_time)" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [], - "source": [ - "import numpy as np\n", - "\n", - "\n", - "first_cell_x_midpoint = 1000*hydraulic_data.loc[1, 'CumlDistance_km']/2\n", - "\n", - "depth = hydraulic_data.loc[1, 'Depth_m']\n", - "first_cell_z_midpoint = -depth/2\n", - "\n", - "area = hydraulic_data.loc[1, 'Q_cms']/hydraulic_data.loc[1, 'Vmag_mps']\n", - "width = area/depth\n", - "first_cell_y_midpoint = width/2\n", - "\n", - "initial_position = np.array([10, first_cell_y_midpoint, first_cell_z_midpoint])\n", - "\n", - "number_of_eggs = 10\n", - "initial_position = np.tile(initial_position, (number_of_eggs, 1))\n", - "\n", - "carp_eggs = BigheadCarpEggs(initial_position, simulation_clock)" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [], - "source": [ - "from fluegg.transporter import LongitudinalTransporter\n", - "\n", - "transport_model = LongitudinalTransporter(simulation_clock, carp_eggs)\n", - "transport_model.set_hydraulic_model(hydraulic_model)" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [], - "source": [ - "from fluegg.simulation import Simulation\n", - "\n", - "fluegg_simulation = Simulation(carp_eggs, transport_model, simulation_clock)\n", - "fluegg_simulation.set_hydraulic_model(hydraulic_model)\n", - "\n", - "simulation_results = fluegg_simulation.run()" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "<Figure size 720x576 with 3 Axes>" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "%matplotlib inline\n", - "import matplotlib.pyplot as plt\n", - "\n", - "positions = simulation_results.results()\n", - "\n", - "time = simulation_clock.time_array()\n", - "\n", - "x = positions[:, :, 0]\n", - "y = positions[:, :, 1]\n", - "z = positions[:, :, 2]\n", - "\n", - "fig = plt.figure(figsize=(10,8))\n", - "\n", - "x_position_axes = fig.add_subplot(311)\n", - "_ = x_position_axes.plot(time, x, '.')\n", - "_ = x_position_axes.set_ylabel('x')\n", - "\n", - "y_position_axes = fig.add_subplot(312, sharex=x_position_axes)\n", - "_ = y_position_axes.plot(time, y, '.')\n", - "_ = y_position_axes.set_ylabel('y')\n", - "\n", - "z_position_axes = fig.add_subplot(313, sharex=x_position_axes)\n", - "_ = z_position_axes.plot(time, z, '.')\n", - "_ = z_position_axes.set_ylabel('z')\n", - "_ = z_position_axes.set_xlabel('time')" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": { - "scrolled": false - }, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "<Figure size 720x576 with 3 Axes>" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fig = plt.figure(figsize=(10,8))\n", - "\n", - "xy_axes = fig.add_subplot(221)\n", - "_ = xy_axes.plot(x, y, '.')\n", - "_ = xy_axes.set_ylabel('y')\n", - "\n", - "xz_axes = fig.add_subplot(223, sharex=xy_axes)\n", - "_ = xz_axes.plot(x, z, '.')\n", - "_ = xz_axes.set_ylabel('z')\n", - "_ = xz_axes.set_xlabel('x')\n", - "\n", - "zy_axes = fig.add_subplot(222, sharey=xy_axes)\n", - "_ = zy_axes.plot(z, y, '.')\n", - "_ = zy_axes.set_xlabel('z')" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.6.6" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/notebooks/mean velocity test.ipynb b/notebooks/mean velocity test.ipynb deleted file mode 100644 index be1153c..0000000 --- a/notebooks/mean velocity test.ipynb +++ /dev/null @@ -1,479 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "<div>\n", - "<style scoped>\n", - " .dataframe tbody tr th:only-of-type {\n", - " vertical-align: middle;\n", - " }\n", - "\n", - " .dataframe tbody tr th {\n", - " vertical-align: top;\n", - " }\n", - "\n", - " .dataframe thead th {\n", - " text-align: right;\n", - " }\n", - "</style>\n", - "<table border=\"1\" class=\"dataframe\">\n", - " <thead>\n", - " <tr style=\"text-align: right;\">\n", - " <th></th>\n", - " <th>CumlDistance_km</th>\n", - " <th>Depth_m</th>\n", - " <th>Q_cms</th>\n", - " <th>Vmag_mps</th>\n", - " <th>Vvert_mps</th>\n", - " <th>Vlat_mps</th>\n", - " <th>Ustar_mps</th>\n", - " <th>Temp_C</th>\n", - " </tr>\n", - " </thead>\n", - " <tbody>\n", - " <tr>\n", - " <th>1</th>\n", - " <td>20.0</td>\n", - " <td>1</td>\n", - " <td>10</td>\n", - " <td>1</td>\n", - " <td>0.0</td>\n", - " <td>0.0</td>\n", - " <td>0.08</td>\n", - " <td>19</td>\n", - " </tr>\n", - " <tr>\n", - " <th>2</th>\n", - " <td>40.0</td>\n", - " <td>2</td>\n", - " <td>20</td>\n", - " <td>2</td>\n", - " <td>0.0</td>\n", - " <td>0.0</td>\n", - " <td>0.08</td>\n", - " <td>20</td>\n", - " </tr>\n", - " <tr>\n", - " <th>3</th>\n", - " <td>60.0</td>\n", - " <td>3</td>\n", - " <td>30</td>\n", - " <td>3</td>\n", - " <td>0.0</td>\n", - " <td>0.0</td>\n", - " <td>0.08</td>\n", - " <td>21</td>\n", - " </tr>\n", - " <tr>\n", - " <th>4</th>\n", - " <td>80.0</td>\n", - " <td>4</td>\n", - " <td>40</td>\n", - " <td>4</td>\n", - " <td>0.0</td>\n", - " <td>0.0</td>\n", - " <td>0.08</td>\n", - " <td>22</td>\n", - " </tr>\n", - " <tr>\n", - " <th>5</th>\n", - " <td>100.0</td>\n", - " <td>5</td>\n", - " <td>50</td>\n", - " <td>5</td>\n", - " <td>0.0</td>\n", - " <td>0.0</td>\n", - " <td>0.08</td>\n", - " <td>23</td>\n", - " </tr>\n", - " </tbody>\n", - "</table>\n", - "</div>" - ], - "text/plain": [ - " CumlDistance_km Depth_m Q_cms Vmag_mps Vvert_mps Vlat_mps Ustar_mps \\\n", - "1 20.0 1 10 1 0.0 0.0 0.08 \n", - "2 40.0 2 20 2 0.0 0.0 0.08 \n", - "3 60.0 3 30 3 0.0 0.0 0.08 \n", - "4 80.0 4 40 4 0.0 0.0 0.08 \n", - "5 100.0 5 50 5 0.0 0.0 0.08 \n", - "\n", - " Temp_C \n", - "1 19 \n", - "2 20 \n", - "3 21 \n", - "4 22 \n", - "5 23 " - ] - }, - "execution_count": 1, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "from fluegg.hydraulics import RoughBottomSeriesOfHydraulicCells, SmoothBottomSeriesOfHydraulicCells\n", - "\n", - "import numpy as np\n", - "import pandas as pd\n", - "\n", - "cell_number = np.arange(1, 6)\n", - "\n", - "length = 20\n", - "cuml_distance = length*cell_number*1000\n", - "depth = np.arange(1, 6)\n", - "discharge = 10*cell_number\n", - "vmag = cell_number.copy()\n", - "vvert = np.zeros(cell_number.shape)\n", - "vlat = np.zeros(cell_number.shape)\n", - "ustar = 0.08*np.ones(cell_number.shape)\n", - "temp = 18 + cell_number\n", - "width = (discharge / vmag) / depth\n", - "\n", - "data_dict = {'CumlDistance_km': cuml_distance/1000,\n", - " 'Depth_m': depth,\n", - " 'Q_cms': discharge,\n", - " 'Vmag_mps': vmag,\n", - " 'Vvert_mps': vvert,\n", - " 'Vlat_mps': vlat,\n", - " 'Ustar_mps': ustar,\n", - " 'Temp_C': temp}\n", - "\n", - "input_data_frame = pd.DataFrame(data_dict, index=cell_number)\n", - "input_data_frame" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "hydraulic_model = RoughBottomSeriesOfHydraulicCells.from_data_frame(input_data_frame)" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": { - "scrolled": true - }, - "outputs": [ - { - "data": { - "text/plain": [ - "30000.0" - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "cell_number = 2\n", - "\n", - "try:\n", - " cell_length = input_data_frame.loc[cell_number, 'CumlDistance_km'] - input_data_frame.loc[cell_number-1, 'CumlDistance_km']\n", - "except KeyError:\n", - " cell_length = input_data_frame.loc[cell_number, 'CumlDistance_km']\n", - "\n", - "x_location = 1000*(input_data_frame.loc[cell_number, 'CumlDistance_km'] - cell_length/2)\n", - "x_location" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "2" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "depth = input_data_frame.loc[cell_number, 'Depth_m']\n", - "depth" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "5.0" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "discharge = input_data_frame.loc[cell_number, 'Q_cms']\n", - "vmag = input_data_frame.loc[cell_number, 'Vmag_mps']\n", - "width = (discharge / vmag) / depth\n", - "width" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [], - "source": [ - "ny = 100 # number of points along width\n", - "\n", - "# eps = 0.00001\n", - "eps = 1e-6\n", - "\n", - "y = np.linspace(eps, width-eps, ny)" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [], - "source": [ - "nz = 100 # number of points along depth\n", - "z = np.linspace(depth-eps, eps, nz) - depth" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [], - "source": [ - "yy, zz = np.meshgrid(y, z)" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [], - "source": [ - "y_position = yy.flatten()\n", - "z_position = zz.flatten()" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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d2rvFYPta20/ZPmp7ZIrjrrT9rO29tm9Oj59v+7Hu8c/YbnIarMXAiG6l+3J0K92Xo1v7uBj2SPqApK9MdoDtEyR9UtJ7JV0k6XrbF3VPf0LSHRHxVkkvS7phHkxvqhYDI7qV7svRrXRfjm7t3WKIiGci4tlpDrtE0t6I2BcRr0m6V9LG7ns9Xybpvu64rRp87+d5rxYDI7qV7svRrXRfjm7t42KYSWdL+l66v7977DRJP4yII+Men/dqMTCiW+m+HN1K9+Xo1oVeDDP6ns+2H5Z05gRP3RoR988vaVLDZkmbJWnNmjWzfn0tBkZ0K92Xo1vpvhzdutCLYUYnhohYP+THOSDp3HT/nO6xw5JOsb28Ww3HHp/IsEXSFkkaGRmZ9a/fscUwl1/4fLYm/sah+3J0K92Xo1vpvhzdOt6Hv8Ywwx6XdGH3FUgrJF0naXtEhKRHJV3THbdJUpMFUouBEd1K9+XoVrovR7f27hqD7att75f0LkkP2H6we/ws2zskqVsDN0l6UNIzkj4bEU917+Kjkj5ie68G1xzuGtY0UXWNgRHdSvfl6Fa6L0e3Iq8xTFVEbJO0bYLHX5C0Id3fIWnHBMft0+CrlppWi4ER3Ur35ehWui9Ht/ZuMfSlWgyM6Fa6L0e30n05urV3/46hL9ViYES30n05upXuy9GttRgaVYuBEd1K9+XoVrovR7fWYmhULQZGdCvdl6Nb6b4c3VqLoVG1GBjRrXRfjm6l+3J0ay2GRtViYES30n05upXuy9GttRgaVYuBEd1K9+XoVrovR7fWYmhULQZGdCvdl6Nb6b4c3VqLoVG1GBjRrXRfjm6l+3J0ay2GRtViYES30n05upXuy9GttRgaVYuBEd1K9+XoVrovR7fWYmhULQZGdCvdl6Nb6b4c3VqLoVG1GBjRrXRfjm6l+3J0ay2GRtViYES30n05upXuy9GttRgaVYuBEd1K9+XoVrovR7fWYmhULQZGdCvdl6Nb6b4c3dqrxWD7WttP2T5qe2SSY861/ajtp7tjP5Se+5jtA7Z3d28bJnof81EtBkZ0K92Xo1vpvhzdutCLYdjv4LZH0gck/fEUxxyR9N8i4hu23yJpl+2HIuLp7vk7IuL3hnRMWy0GRnQr3ZejW+m+HN260IthqBNDRDwjSfbk59mIOCjpYHf772w/I+lsSU9P+qIGHVsMc/mFz2dr4m8cui9Ht9J9ObqV7svRreN9x9U1BttrJb1T0mPp4ZtsP2H7btsrW33sWgyM6Fa6L0e30n05uhV3jcH2w7b3TPC2cTYfyPZPS/qcpA9HxI+6h/9I0s9KWqfBqvj9KV6/2fao7dFDhw7N5kNLqmsMlOhWui9Ht9J9OboVd40hItYP+0Fsn6jBSeGeiPh8et8vpmP+RNIXpnBskbRFkkZGRmZ9Yq/FwIhupftydCvdl6NbcYth2Dy4AHGXpGci4g/GPbc63b1ag4vZTarFwIhupftydCvdl6Nbe/XvGGxfbXu/pHdJesD2g93jZ9ne0R32bkkflHTZBF+W+ru2n7T9hKT3SPr1YTxTVYuBEd1K9+XoVrovR7f27auStknaNsHjL0ja0N3+qjTxiTgiPjjMx59N9VVJjOhWui9Ht9J9Obr1uP6qpMWsFgMjupXuy9GtdF+Obj3urjFQqmsMjOhWui9Ht9J9Obq1V9cY+lQtBkZ0K92Xo1vpvhzdWouhUbUYGNGtdF+ObqX7cnRrLYZG1WJgRLfSfTm6le7L0a21GBpVi4ER3Ur35ehWui9Ht9ZiaFQtBkZ0K92Xo1vpvhzdWouhUbUYGNGtdF+ObqX7cnRrLYZG1WJgRLfSfTm6le7L0a21GBpVi4ER3Ur35ehWui9Ht9ZiaFQtBkZ0K92Xo1vpvhzdWouhUbUYGNGtdF+ObqX7cnRrLYZG1WJgRLfSfTm6le7L0a21GBpVi4ER3Ur35ehWui9Ht9ZiaFQtBkZ0K92Xo1vpvhzdWouhUbUYGNGtdF+ObqX7cnRrrxaD7WttP2X7qO2RKY57vvtObbttj6bHT7X9kO3nuh9XDuOZqloMjOhWui9Ht9J9Obq1b4thj6QPSPrKDI59T0Ssi4h8ArlZ0iMRcaGkR7r7TarFwIhupftydCvdl6Nbe7UYIuKZiHh2iHexUdLW7vZWSVcN45mqWgyM6Fa6L0e30n05urVvi2GmhaQv2d5le3N6/IyIONjd/r6kMyZ7B7Y32x61PXro0KFZA2oxMKJb6b4c3Ur35ejWhV4My6cF2Q9LOnOCp26NiPtn+HF+PiIO2P6nkh6y/a2IGPPpp4gI25OesCNii6QtkjQyMjLrE3stBkZ0K92Xo1vpvhzdutCLYdoTQ0SsH/aDRMSB7seXbG+TdIkG1yVetL06Ig7aXi3ppWE/1mQdWwxz+YXPZ2vibxy6L0e30n05upXuy9Gt433oawwzyfbJtt9y7LakX9TgorUkbZe0qbu9SdJMF8isq8XAiG6l+3J0K92Xo1t7dY3B9tW290t6l6QHbD/YPX6W7R3dYWdI+qrtb0r6uqQHIuIvu+dul3SF7eckre/uN6muMTCiW+m+HN1K9+XoVtw1hqmKiG2Stk3w+AuSNnS390n6V5O8/rCky4cxzLRaDIzoVrovR7fSfTm6tVeLoU/VYmBEt9J9ObqV7svRrb36dwx9qhYDI7qV7svRrXRfjm6txdCoWgyM6Fa6L0e30n05urUWQ6NqMTCiW+m+HN1K9+Xo1loMjarFwIhupftydCvdl6NbazE0qhYDI7qV7svRrXRfjm6txdCoWgyM6Fa6L0e30n05urUWQ6NqMTCiW+m+HN1K9+Xo1loMjarFwIhupftydCvdl6NbazE0qhYDI7qV7svRrXRfjm6txdCoWgyM6Fa6L0e30n05urUWQ6NqMTCiW+m+HN1K9+Xo1loMjarFwIhupftydCvdl6NbazE0qhYDI7qV7svRrXRfjm6txdCoWgyM6Fa6L0e30n05urUWQ6NqMTCiW+m+HN1K9+Xo1l4tBtvX2n7K9lHbI5Mc8zbbu9Pbj2x/uHvuY7YPpOc2DOOZqloMjOhWui9Ht9J9Obp1oRfDUN/BTYPv3fwBSX882QER8aykdZJk+wRJBzT2u77dERG/N6Rj2moxMKJb6b4c3Ur35ejWhV4Mw35rz2ckyZ7xefZySX8dEd8d5uPOpWOLYS6/8PlsTfyNQ/fl6Fa6L0e30n05unW873i7xnCdpE+Pe+wm20/Yvtv2ysleaHuz7VHbo4cOHZr1B67FwIhupftydCvdl6NbcdcYbD9se88Ebxtn84Fsr5D0fkn/Kz38R5J+VoNPNR2U9PuTvT4itkTESESMrFq1ajYfWlJdY6BEt9J9ObqV7svRrbhrDBGxfp4+1nslfSMiXkzv+ye3bf+JpC/M08d6U7UYGNGtdF+ObqX7cnQrbjHMY9dr3KeRbK9Od6/W4GJ2k2oxMKJb6b4c3Ur35ejWXv07BttX294v6V2SHrD9YPf4WbZ3pONOlnSFpM+Pexe/a/tJ209Ieo+kXx/GM1W1GBjRrXRfjm6l+3J0a9++Kmmbxn7p6bHHX5C0Id3/e0mnTXDcB4f5+LOpviqJEd1K9+XoVrovR7ce71+VtGjVYmBEt9J9ObqV7svRrcfzNYZFra4xMKJb6b4c3Ur35ejWXl1j6FO1GBjRrXRfjm6l+3J0ay2GRtViYES30n05upXuy9GttRgaVYuBEd1K9+XoVrovR7fWYmhULQZGdCvdl6Nb6b4c3VqLoVG1GBjRrXRfjm6l+3J0ay2GRtViYES30n05upXuy9GttRgaVYuBEd1K9+XoVrovR7fWYmhULQZGdCvdl6Nb6b4c3VqLoVG1GBjRrXRfjm6l+3J0ay2GRtViYES30n05upXuy9GttRgaVYuBEd1K9+XoVrovR7fWYmhULQZGdCvdl6Nb6b4c3VqLoVG1GBjRrXRfjm6l+3J0a+8Wg+3/Yftbtp+wvc32KZMcd6XtZ23vtX1zevx82491j3+m+97Q814tBkZ0K92Xo1vpvhzd2sfF8JCkd0TEv5T0bUm3jD/A9gmSPqnB932+SNL1ti/qnv6EpDsi4q2SXpZ0wzyY3lQtBkZ0K92Xo1vpvhzd2rvFEBFfiogj3d2dks6Z4LBLJO2NiH0R8ZqkeyVttG1Jl0m6rztuq6SrhjVNVC0GRnQr3ZejW+m+HN3ax8WQ+y+SvjjB42dL+l66v7977DRJP0wnlmOPz3u1GBjRrXRfjm6l+3J0K3Ix2H7Y9p4J3jamY26VdETSPS2gtjfbHrU9eujQoVm//uVXXtOy7nSb/1Ywk9vLPDhbz/X1rW/TfX2y0n19stJ9fbKO9y1z28WwfCYHRcT6qZ63/auS3ifp8oiY6KR7QNK56f453WOHJZ1ie3m3Go49PpFhi6QtkjQyMjLrE/ulF5ymFcuX6fUjR3XCMku23nhjZrdPXL5M733Haj3+/A/m9PrWt+m+Plnpvj5Z6b4+Wcf7Tly+TJdecNps/xiccTM6MUyV7Ssl/ZakfxcRr0xy2OOSLrR9vgZ/8F8n6T9GRNh+VNI1Glx32CTp/mFNE3XxeSt1z42Xaue+wz/5Dzqb2xeft1JvO/Mtc35969t0X5+sdF+frHRfn6zjfReft1Kt8sR/wZ/FO7D3SjpJg7/9S9LOiPivts+SdGdEbOiO2yDpDyWdIOnuiLite/wCDU4Kp0r6K0m/EhGvTvUxR0ZGYnR0dCh3VVXVUsv2rogYme64oRdD92WmEz3+gqQN6f4OSTsmOG6fBl+1VFVVVQFaMv/yuaqqqppZdWKoqqqqxlQnhqqqqmpMdWKoqqqqxlQnhqqqqmpMQ3+56mJk+5Ck787x5adL+pt55PSh+jkvjernvDQa5ud8XkSsmu6gXp4Yhsn26Ey+jvd4qn7OS6P6OS+NFuLnXJ9KqqqqqsZUJ4aqqqpqTEvxxLBlsQGLUP2cl0b1c14aNf85L7lrDFVVVdXULcXFUFVVVU3Rkjox2L7S9rO299q+ebE9rbN9t+2XbO9ZbMtCZPtc24/aftr2U7Y/tNim1tn+Kdtft/3N7uf83xfbtFDZPsH2X9n+wmJbFiLbz9t+0vZu203/76WXzKeSbJ8g6duSrtDgW4g+Lun6iHh6UWENs/0Lkn4s6c8j4h2L7Wmd7dWSVkfEN2y/RdIuSVcd57/GlnRyRPzY9omSvirpQxGxc5FpzbP9EUkjkn4mIt632J7W2X5e0khENP93G0tpMVwiaW9E7IuI1zT4HhAbp3lNr4uIr0j6wWI7FqqIOBgR3+hu/52kZ9Toe4hTikE/7u6e2L0d93/bs32OpP8g6c7FthyPLaUTw9mSvpfu79dx/ofGUs72WknvlPTY4kra131KZbeklyQ9FBHH/c9Zg2/69VuSji42ZAELSV+yvcv25pYfaCmdGKolku2flvQ5SR+OiB8ttqd1EfFGRKzT4HumX2L7uP60oe33SXopInYttmWB+/mI+NeS3ivp17pPFTdpKZ0YDkg6N90/p3usOo7qPs/+OUn3RMTnF9uzkEXEDyU9KunKxbY07t2S3t99zv1eSZfZ/tTiktoXEQe6H1+StE0Nv/PlUjoxPC7pQtvn214h6TpJ2xfZVM1j3YXYuyQ9ExF/sNiehcj2KtundLf/kQZfXPGtxVW1LSJuiYhzImKtBv87/nJE/Mois5pm++TuCypk+2RJvyip2VcbLpkTQ0QckXSTpAc1uCj52Yh4anFVbbP9aUlfk/Q22/tt37DYpsa9W9IHNfgb5O7ubcN0L+p5qyU9avsJDf7y81BELIkv31xinSHpq7a/Kenrkh6IiL9s9cGWzJerVlVVVTNrySyGqqqqambViaGqqqoaU50YqqqqqjHViaGqqqoaU50YqqqqqjHViaGqqqoaU50YqqqqqjHViaGqqqoa0/8HsywYZYxtcFsAAAAASUVORK5CYII=\n", - "text/plain": [ - "<Figure size 432x288 with 1 Axes>" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "%matplotlib inline\n", - "import matplotlib.pyplot as plt\n", - "_ = plt.plot(y_position, z_position, '.')" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(10000, 3)" - ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "x_position = np.tile(x_location, y_position.shape)\n", - "\n", - "position = np.stack([x_position, y_position, z_position], axis=1)\n", - "position.shape" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [], - "source": [ - "hydraulic_results = hydraulic_model.hydraulic_results(position)" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [], - "source": [ - "streamwise_velocity = hydraulic_results.streamwise_velocity()\n", - "streamwise_velocity = streamwise_velocity.reshape(yy.shape)" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "<Figure size 1080x720 with 1 Axes>" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fig, ax = plt.subplots(figsize=(15,10))\n", - "extent = (y.min(), y.max(), z.min(), z.max())\n", - "ax.imshow(streamwise_velocity, extent=extent)\n", - "CS = ax.contour(yy, zz, streamwise_velocity, colors='k')\n", - "_ = ax.clabel(CS, inline=1, fontsize=10)" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": { - "scrolled": true - }, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "<Figure size 432x288 with 1 Axes>" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "depth_averaged_velocity = np.trapz(streamwise_velocity, -z, axis=0)/depth\n", - "_ = plt.plot(y, depth_averaged_velocity)\n", - "_ = plt.xlabel('y position')\n", - "_ = plt.ylabel('Depth averaged velocity')\n", - "plt.autoscale(tight=True)" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "<Figure size 432x288 with 1 Axes>" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "width_averaged_velocity = np.trapz(streamwise_velocity, y, axis=1)/width\n", - "_ = plt.plot(width_averaged_velocity, z)\n", - "_ = plt.xlabel('Width averaged velocity')\n", - "_ = plt.ylabel('z position')\n", - "plt.autoscale(tight=True)" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "2.01214778177025" - ] - }, - "execution_count": 17, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "cross_section_averaged_velocity = np.trapz(width_averaged_velocity, -z)/depth\n", - "cross_section_averaged_velocity" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "0.0" - ] - }, - "execution_count": 18, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "round(cross_section_averaged_velocity - input_data_frame.loc[cell_number, 'Vmag_mps'], 1)" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.6.7" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/notebooks/nonrandom constant particle.ipynb b/notebooks/nonrandom constant particle.ipynb deleted file mode 100644 index ded47bb..0000000 --- a/notebooks/nonrandom constant particle.ipynb +++ /dev/null @@ -1,259 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "<div>\n", - "<style scoped>\n", - " .dataframe tbody tr th:only-of-type {\n", - " vertical-align: middle;\n", - " }\n", - "\n", - " .dataframe tbody tr th {\n", - " vertical-align: top;\n", - " }\n", - "\n", - " .dataframe thead th {\n", - " text-align: right;\n", - " }\n", - "</style>\n", - "<table border=\"1\" class=\"dataframe\">\n", - " <thead>\n", - " <tr style=\"text-align: right;\">\n", - " <th></th>\n", - " <th>CumlDistance_km</th>\n", - " <th>Depth_m</th>\n", - " <th>Q_cms</th>\n", - " <th>Vmag_mps</th>\n", - " <th>Vvert_mps</th>\n", - " <th>Vlat_mps</th>\n", - " <th>Ustar_mps</th>\n", - " <th>Temp_C</th>\n", - " </tr>\n", - " <tr>\n", - " <th>CellNumber</th>\n", - " <th></th>\n", - " <th></th>\n", - " <th></th>\n", - " <th></th>\n", - " <th></th>\n", - " <th></th>\n", - " <th></th>\n", - " <th></th>\n", - " </tr>\n", - " </thead>\n", - " <tbody>\n", - " <tr>\n", - " <th>1</th>\n", - " <td>100.0</td>\n", - " <td>4.94</td>\n", - " <td>125.0</td>\n", - " <td>0.25</td>\n", - " <td>0.0</td>\n", - " <td>0.0</td>\n", - " <td>0.013555</td>\n", - " <td>23.0</td>\n", - " </tr>\n", - " </tbody>\n", - "</table>\n", - "</div>" - ], - "text/plain": [ - " CumlDistance_km Depth_m Q_cms Vmag_mps Vvert_mps Vlat_mps \\\n", - "CellNumber \n", - "1 100.0 4.94 125.0 0.25 0.0 0.0 \n", - "\n", - " Ustar_mps Temp_C \n", - "CellNumber \n", - "1 0.013555 23.0 " - ] - }, - "execution_count": 1, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "import pandas as pd\n", - "hydraulic_csv_path = r'../test/nonrandom/data/highQ_1Cell.csv'\n", - "hydraulic_csv = pd.read_csv(hydraulic_csv_path, index_col='CellNumber')\n", - "hydraulic_csv" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "%matplotlib inline\n", - "import numpy as np\n", - "import scipy.io as sio\n", - "\n", - "import matplotlib.pyplot as plt\n", - "\n", - "mat_file_path = r'../test/nonrandom/data/constant_particle_property.mat'\n", - "results = sio.loadmat(mat_file_path, squeeze_me=False)\n", - "expected_x = np.squeeze(results['ResultsSim']['X'][0][0])\n", - "expected_y = np.squeeze(results['ResultsSim']['Y'][0][0])\n", - "expected_z = np.squeeze(results['ResultsSim']['Z'][0][0])\n", - "expected_time = np.squeeze(results['ResultsSim']['time'][0][0])" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "import os\n", - "import sys\n", - "\n", - "test_classes_module = os.path.realpath('../test/nonrandom/testclasses.py')\n", - "test_classes_path, _ = os.path.split(test_classes_module)\n", - "\n", - "sys.path.append(test_classes_path)\n", - "\n", - "from test_simulation import run_nonrandom_constant_simulation\n", - "\n", - "simulation_results = run_nonrandom_constant_simulation()\n", - "\n", - "time = simulation_results.time()\n", - "positions = simulation_results.results()" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "<Figure size 720x576 with 3 Axes>" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fig = plt.figure(figsize=(10,8))\n", - "\n", - "x_position_axes = fig.add_subplot(311)\n", - "_ = x_position_axes.plot(expected_time, expected_x, 'x', label='Expected')\n", - "_ = x_position_axes.plot(time, positions[:, 0, 0], '.', label='Calculated')\n", - "_ = x_position_axes.legend()\n", - "_ = x_position_axes.set_ylabel('x')\n", - "\n", - "y_position_axes = fig.add_subplot(312, sharex=x_position_axes)\n", - "_ = y_position_axes.plot(expected_time, expected_y, 'x')\n", - "_ = y_position_axes.plot(time, positions[:, 0, 1], '.')\n", - "_ = y_position_axes.set_ylabel('y')\n", - "\n", - "z_position_axes = fig.add_subplot(313, sharex=x_position_axes)\n", - "_ = z_position_axes.plot(expected_time, expected_z, 'x')\n", - "_ = z_position_axes.plot(time, positions[:, 0, 2], '.')\n", - "_ = z_position_axes.set_ylabel('z')\n", - "_ = z_position_axes.set_xlabel('time')" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "<Figure size 720x576 with 3 Axes>" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fig = plt.figure(figsize=(10,8))\n", - "\n", - "x_position_axes = fig.add_subplot(311)\n", - "_ = x_position_axes.plot(expected_time, positions[:, 0, 0] - expected_x, '.', label='Expected')\n", - "_ = x_position_axes.set_ylabel('calculated x - expected x')\n", - "\n", - "y_position_axes = fig.add_subplot(312, sharex=x_position_axes)\n", - "_ = y_position_axes.plot(expected_time, positions[:, 0, 1] - expected_y, '.')\n", - "_ = y_position_axes.set_ylabel('calculated y - expected y')\n", - "\n", - "z_position_axes = fig.add_subplot(313, sharex=x_position_axes)\n", - "_ = z_position_axes.plot(expected_time, positions[:, 0, 2] - expected_z, 'x')\n", - "_ = z_position_axes.set_ylabel('calculated z - expected z')\n", - "_ = z_position_axes.set_xlabel('time')" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "<Figure size 720x576 with 3 Axes>" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fig = plt.figure(figsize=(10,8))\n", - "\n", - "xy_axes = fig.add_subplot(221)\n", - "_ = xy_axes.plot(expected_x,expected_y, 'x', label='Expected')\n", - "_ = xy_axes.plot(positions[:, 0, 0], positions[:, 0, 1], '.', label='Calculated')\n", - "_ = xy_axes.legend()\n", - "_ = xy_axes.set_ylabel('y')\n", - "\n", - "xz_axes = fig.add_subplot(223, sharex=xy_axes)\n", - "_ = xz_axes.plot(expected_x, expected_z, 'x')\n", - "_ = xz_axes.plot(positions[:, 0, 0], positions[:, 0, 2], '.')\n", - "_ = xz_axes.set_ylabel('z')\n", - "_ = xz_axes.set_xlabel('x')\n", - "\n", - "zy_axes = fig.add_subplot(224, sharey=xz_axes)\n", - "_ = zy_axes.plot(expected_y, expected_z, 'x')\n", - "_ = zy_axes.plot(positions[:, 0, 1], positions[:, 0, 2], '.')\n", - "_ = zy_axes.set_xlabel('y')" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.6.7" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/notebooks/nonrandom single egg.ipynb b/notebooks/nonrandom single egg.ipynb deleted file mode 100644 index 490827a..0000000 --- a/notebooks/nonrandom single egg.ipynb +++ /dev/null @@ -1,259 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "<div>\n", - "<style scoped>\n", - " .dataframe tbody tr th:only-of-type {\n", - " vertical-align: middle;\n", - " }\n", - "\n", - " .dataframe tbody tr th {\n", - " vertical-align: top;\n", - " }\n", - "\n", - " .dataframe thead th {\n", - " text-align: right;\n", - " }\n", - "</style>\n", - "<table border=\"1\" class=\"dataframe\">\n", - " <thead>\n", - " <tr style=\"text-align: right;\">\n", - " <th></th>\n", - " <th>CumlDistance_km</th>\n", - " <th>Depth_m</th>\n", - " <th>Q_cms</th>\n", - " <th>Vmag_mps</th>\n", - " <th>Vvert_mps</th>\n", - " <th>Vlat_mps</th>\n", - " <th>Ustar_mps</th>\n", - " <th>Temp_C</th>\n", - " </tr>\n", - " <tr>\n", - " <th>CellNumber</th>\n", - " <th></th>\n", - " <th></th>\n", - " <th></th>\n", - " <th></th>\n", - " <th></th>\n", - " <th></th>\n", - " <th></th>\n", - " <th></th>\n", - " </tr>\n", - " </thead>\n", - " <tbody>\n", - " <tr>\n", - " <th>1</th>\n", - " <td>100.0</td>\n", - " <td>4.94</td>\n", - " <td>125.0</td>\n", - " <td>0.25</td>\n", - " <td>0.0</td>\n", - " <td>0.0</td>\n", - " <td>0.013555</td>\n", - " <td>23.0</td>\n", - " </tr>\n", - " </tbody>\n", - "</table>\n", - "</div>" - ], - "text/plain": [ - " CumlDistance_km Depth_m Q_cms Vmag_mps Vvert_mps Vlat_mps \\\n", - "CellNumber \n", - "1 100.0 4.94 125.0 0.25 0.0 0.0 \n", - "\n", - " Ustar_mps Temp_C \n", - "CellNumber \n", - "1 0.013555 23.0 " - ] - }, - "execution_count": 1, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "import pandas as pd\n", - "hydraulic_csv_path = r'../test/nonrandom/data/highQ_1Cell.csv'\n", - "hydraulic_csv = pd.read_csv(hydraulic_csv_path, index_col='CellNumber')\n", - "hydraulic_csv" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "%matplotlib inline\n", - "import numpy as np\n", - "import scipy.io as sio\n", - "\n", - "import matplotlib.pyplot as plt\n", - "\n", - "mat_file_path = r'../test/nonrandom/data/single_egg.mat'\n", - "results = sio.loadmat(mat_file_path, squeeze_me=False)\n", - "expected_x = np.squeeze(results['ResultsSim']['X'][0][0])\n", - "expected_y = np.squeeze(results['ResultsSim']['Y'][0][0])\n", - "expected_z = np.squeeze(results['ResultsSim']['Z'][0][0])\n", - "expected_time = np.squeeze(results['ResultsSim']['time'][0][0])" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "import os\n", - "import sys\n", - "\n", - "test_classes_module = os.path.realpath('../test/nonrandom/testclasses.py')\n", - "test_classes_path, _ = os.path.split(test_classes_module)\n", - "\n", - "sys.path.append(test_classes_path)\n", - "\n", - "from test_simulation import run_nonrandom_single_egg_simulation\n", - "\n", - "simulation_results = run_nonrandom_single_egg_simulation()\n", - "\n", - "time = simulation_results.time()\n", - "positions = simulation_results.results()" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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HyghKu4+4+w1mNgKYCxwALAb+1t0bzawMeAA4EVgPXOLuK8PvmgZcBjQDX3f3J8P2ccCdQBK4x91v2Ve/qqurvaamZpe2ZcuWcdRRR3X/l5Z2aYxFpEfIdfk0VRFcNsQzKp9Km8xssbvv8wKv+TyHrgEY4+5bzawE+L2ZPQH8E/Ajd59rZtMJgtrd4c+N7n6omU0EbgUuMbOjgYnAMcDHgKfMrOXibD8BxgK1wCtmNt/d38rj7yQiIr1JzUx44d+hfgNgObh4b2mweKHfUC1ekJzKW6DzYOqv5VYGJeHDgTHAF8P2WcD3CALdhPA5wCPAXRZcn2MCMNfdG4D3zGw50PK/L8vd/V0AM5sbbqtAJyIiXdOy+jTdEMy85eLab1p9KgWQ11WuZpYkKKseSjCbtgLY5O4tJ2zVAoeEzw8BVgG4e9rMNhOUZQ8BXsr62uzPrNqt/eR2+jEVmAowfPjwNvvq7rtc301yJ19lfRGRbsl1+VS3zpII5TXQuXszMNrMBgLzgD3P6i8Ad58BzIDgHLrd3y8vL2f9+vUccMABCnU55u6sX7+e8vLyqLsiIr1ddvk0k4H09u59n8qnUkQKch06d99kZs8ApwIDzSwVztJVAqvDzVYDw4BaM0sB+xEsjmhpb5H9mfbaO6WyspLa2lrq6uq68nHZh/LyciorK6Puhoj0Jrm+dVZLeEuWqXwqRSlvgc7MhgBNYZjrQ7B44VbgGeBzBCtdJwGPhR+ZH77+n/D9p93dzWw+MMfMfkiwKOIwYBFgwGHhqtnVBAsnWs7N65SSkhJGjBjRtV9URESi13Lj+m110FQP6W7eW7qlfFoxCE7/psKbFL18ztAdDMwKz6NLAA+7++Nm9hYw18xuAl4F7g23vxf4ebjoYQNBQMPd3zSzhwkWO6SBK8NSLmZ2FfAkwWVL7nP3N/P4+4iISLHILp/m4s4LqXIo6aPyqcRW3q5DV6zaug6diIgUsXyUT5NlunWWxEIxXIdORESk83JdPk1VQCKh8qn0aAp0IiISrZZrv3kzNDV0b/Vpy7lvyRKVT6VXUaATEZHCaZl927E5KJs2fASZ9D4/1q6W8mlJOYy+FMbemLOuisSJAp2IiORPrq/9pvKpSJsU6EREJHdUPhWJhAKdiIh0Ta7Lp6mKoHSaSKp8KpGbfP8iltRuoiyVpKI0ycbtjTQ1O4aTSiTYv28p9Y3N7GhqZtSwgcycEu1KaQU6ERHpmFyXT0v7A67yqURmzO3PUt/U3BrYylJJ1m9rpCmdoU9Jgu1NGaCpjU82s2H7zvbTDj2gYH1ujwKdiIjsadUieOoG+ODN4Jy17pZPEyko6w9lA+CgY3XjeimYyfcvYtWG7a2BraI0yZpN9TQ0Z0gATZnsrXeGtO27vtGu6z99JJefMTKnfe4KBToREcnPtd9UPpUCaa88urUhjQGZ1nso7Drb1tzN/Z5UtX9RhDlQoBMR6Z1UPpWY6Wp5NJ/3w1q0ciM/e2FFUYQ6BToRkZ4uu3zqmeC+p925dZbKp5IH059bwRNL17B1R7o1sG1tSNOQzuAZB7zb5dF8uPnXfwKIPNQp0ImI9DS5Lp+W9g8uHaLyqeRAe+XRbQ3prNIotL0YIVqlqQTlKdtjlesflq9XoBMRkW5ouXH9qhpo2paji/eWQ/l+UPlJzb5Jl3R99Wj0kgkjk3EG9S2hLJVkR1Mz5SXJork8SXsU6ERE4iS7fNrc1P3wliyF0r4qn0qnxLU82iKZMMDpW5osymvKdYUCnYhIMcvH6lPdOks6oCW0rdqwnbJUkoZ0MwZB8ElnYlEebWrOUJIwhg2qaA1s5SVJykuSPH3NWVF3MacU6EREisXu5dPmpmABQ3eofCr70F55NJ3OsHMurfgCG8S3PJoPCnQiIlHJvnVW4zZo3NK970uVQ0kflU9lF90pjxaDZAISGH1KE6QSidbAtn/fUoYNquhVoW1vFOhERAqhZfZtzRvQuDV4dOfSIRCUT1OlMPRoOPdGhbderCeUR5szGUqTCT42sE9reVShreMU6ERE8iG7fNrwUffPfUuWBZcOKe2r8mkvNf25Fcx6cSUADelmylJJANZuacAzrvJoL5e3QGdmw4AHgKEEF2qe4e53mtkg4CGgClgJfMHdN5qZAXcCFwLbgcnu/sfwuyYB3w6/+iZ3nxW2nwjMBPoAvwGudvd8XhRaRKRt+SifJkqC22fp2m+9xt7Ko+ZOQ3P2f+KKL7ipPBqdfM7QpYFvuvsfzaw/sNjMFgKTgd+5+y1mdi1wLfAvwAXAYeHjZOBu4OQwAN4AVBMEw8VmNt/dN4bbXA68TBDoxgFP5PF3EhHJT/m0tH9w4V6VT3u8nlQe3b+itDWwAQptEdpnoDOzo939rd3aznL3Z/f2OXdfA6wJn28xs2XAIcAE4Kxws1nAswSBbgLwQDjD9pKZDTSzg8NtF7r7hnDfC4FxZvYsMMDdXwrbHwA+gwKdiOTa7rfO6vbsW3jpEJVPe6yeUB7FnaEDygFay6PuMOm0Kr76V9Hfu1R21ZEZuofN7OfAD4Dy8Gc1cGpHd2JmVcDxBDNpQ8OwB/ABQUkWgrC3KutjtWHb3tpr22gXEemehTfAqw+CN0NzOnerT/sNhZOv0LXfeojdZ9oqSpOs3dIQrh7NFPXKUVB5tKfpSKA7GbgVeBHoD8wGTuvoDsysH/Ao8A13/yg4VS7g7m5meT/nzcymAlMBhg8fnu/diUic5OPabyqf9hgdL48WX2ADlUd7k44EuiagnmDhQTnwnrt36L4dZlZCEOZmu/uvwuYPzexgd18TllTXhu2rgWFZH68M21azs0Tb0v5s2F7ZxvZ7cPcZwAyA6upqLZoQ6c1UPpXdxL08mjAwYGBFCe603sZK5dHepSOB7hXgMeCTwGBgupn9tbt/fm8fClet3gssc/cfZr01H5gE3BL+fCyr/Sozm0swK7g5DH1PAv9mZvuH250HTHP3DWb2kZmdQlDK/TLwHx34fUSkN8l1+bS0fxDe+gxU+TRGJt+/iFUbtreuHK0oTbJmUz0NzRkSEIvyaFkyQZ/S4Dy2lvLosAMquOATByu0SYcC3WXuXhM+XwNMMLO/7cDnTgP+FnjDzF4L264jCHIPm9llwPvAF8L3fkNwyZLlBJctmQIQBrd/JQiWAN9vWSABfI2dly15Ai2IEOndcl0+TVUElw3xjMqnMZA909ZyGysDtjQ005TOsLM8s2tgay5gH/dG5VHpDuttl22rrq72mpqafW8oIsWvZia88O9QvwGw7s++JUuD2TctXihaHS+PFieVR6WzzGyxu1fvazvdKUJE4qOlfJpuCGbecnHtN5VPi05PKI+mEkZpMsGBA8pbb2Ol8qjkkwKdiBSnljsvbKsLgpvKpz3K5PsXsaR2U2tg27i9kaZmZ3tjmkwGlUdFOkmBTkSKQ3b5NBeXDlH5NHItM21A62xbY7qZjdubKElYeBur4ptha6HyqMSJAp2IRCOX5dOW8JYsU/m0wPZWHsWhuZ3bWO16T9LoJAxKkiqPSvwp0IlI/uW6fJosg2QJVAyC07+p8JZnXS2PFouShOHAgf3LAFrLo/3KUwpt0mMo0IlI7uWyfNoS3pIlKp/m0Zjbn6W+qbk1sJWlkmxtSLN1R5rSpMqjIsVOgU5Euqdl9m3H5mD2rXFr98unybJgAcPoS2HsjTnram/X1dWjKo+KFD8FOhHpnOzyaXfDG6h8mmPtlUe3NqQxaPfeo8WwerQkYWRwDFN5VKSTFOhEZO+yb53V1ADp7V3/LpVPc6Kr5dHimGcDM+hflqRfWUlrYKtvbKa8JMnT15wVdfdEYkmBTkR22r182vARZNJd/z6VT7tM5VER6QwFOpHeLNfl09L+gKt82kEqj4pIrijQifQWqxbBUzfAB29CIpG78mlpX6j8JJx2te680Ia2yqPrtzXSlM7QpyTB9qYMxVoeLU0laEpn6F+u8qhIsVOgE+mpssunjdu6f+P6lltnJZIqn2aZ/twKnli6hq070q2BDWDdlgYy+F7Lo9ubor+VfDJhgNO3NEkqkWgNbDuamhk1bKBuYSUSEwp0Ij1F9rXfMpnuzb6Byqe7aa88uq0hnVUahWItj6bdKUkYwwZVtAa28pKkZtpEeggFOpE4Uvk0L7paHi0GKo+K9G4KdCJxkL14oake0vXd+77S/kGA62Xl07bKo1sb0jSkM3jGAVd5VERiSYFOpNisWgR/uANW1UDTttyVTxNJGHo0nHtjj559awltqzZsby2Prt3SQEM6Q7o5s9fyaDEoTSVoas6oPCoinaJAJxK17PKpZ7q/eCGRgrL+UDYADjq2x5ZP2yuPptMZds6lFV9gg2CmLZNxBvUtoSyVbA1smmkTka5SoBMpNJVPO6Q75dFikLDgjggqj4pIISjQieRTPsqnqXIo369HLF7YvTzakG7GIAg+6XiUR5szGUqTCT42sE9rYNu/bynDBlUotIlIweQt0JnZfcBFwFp3/0TYNgh4CKgCVgJfcPeNZmbAncCFwHZgsrv/MfzMJODb4dfe5O6zwvYTgZlAH+A3wNXuXgzX4pTeLLt82tzU/fCWLA1Wnsa4fDr9uRXMenElQGt51IBN9Wk84yqPiojkQD5n6GYCdwEPZLVdC/zO3W8xs2vD1/8CXAAcFj5OBu4GTg4D4A1ANcGF0xeb2Xx33xhucznwMkGgGwc8kcffR2RXLbNva94IbpuVq/JpaV/oMzBWN67fW3nU3Ivm/qLtSSYggdGnNEEqkWgNbJppE5G4yFugc/fnzaxqt+YJwFnh81nAswSBbgLwQDjD9pKZDTSzg8NtF7r7BgAzWwiMM7NngQHu/lLY/gDwGRToJJ+yy6cNH3U/vEGsyqdxL4+23HtU5VER6YkKfQ7dUHdfEz7/ABgaPj8EWJW1XW3Ytrf22jba22RmU4GpAMOHD+9G96VXyXX5NFUOJX2KunyaXR5tSDe33sZq7ZaG2JRHcWfogHKA1vKoO0w6rUo3ixeRHiuyRRHu7mZWkDqMu88AZgBUV1cXd+1HopGP8mmqAlKlRXftt86VR4svuKk8KiKyp0IHug/N7GB3XxOWVNeG7auBYVnbVYZtq9lZom1pfzZsr2xje5GOyXX5NFUR3IKrSG6dFffyaPbq0f0rSlsDG6DQJiLShkIHuvnAJOCW8OdjWe1XmdlcgkURm8PQ9yTwb2a2f7jdecA0d99gZh+Z2SkEiyK+DPxHIX8RiZmFN8CrD4I3Q3O6+xfvbSmf9hsa2eKFuJdHEwYGKo+KiORAPi9b8guC2bXBZlZLsFr1FuBhM7sMeB/4Qrj5bwguWbKc4LIlUwDC4PavwCvhdt9vWSABfI2dly15Ai2IkBa7l08bPoJMunvfGVH5dPL9i1i1YXtrabSiNMmaTfU0NGdIQFFfWBeC8mhZMkGf0iCotZRHhx1QwQWfOFihTUQkR6y3Xbqturraa2pqou6G5FLMy6d7K482pDMU+RU/VB4VEckjM1vs7tX72k53ipD4iWH5tKeURwdWlOBO622sVB4VESkOCnRS3HJdPk1VQEk5eCbn5VOVR0VEJCoKdFJcambCC/8O9RsAy8HsW1g+rRgEp3+z27Nvk+9fxJLaTa2BbeP2Rpqane2NaTKZ4HYmgV0DW3O39po7Ko+KiPRMCnQSrezyaVND7i7e243y6V7Lo+7hJT+Kb4athcqjIiK9jwKdFE724oWmbcHdF5obuv593Sifxr08mjAoSRqlyQQHDihvvY2VyqMiIr2TAp3kT8Tl055QHrXw3qP9y0tay6P9ylMKbSIisgsFOsmdXJZPEyko6w/JMugzsN3yaXZoaymPNqab2bC9CQOVR0VEpFdQoJOuqZkJL/0UttVBc2PuyqeJJIy+FMbe2PrW5PsXseq57Wx8YsEe5dGUWXjv0ZbQtjO8Fcvl21QeFRGRfFOgk47JLp9mMt1fvJAsDS7cGy5emPzG0TvLo0uSbHxpQQfLo9HHtpKEkcExjAP7lwGoPCoiIgWlQCdtaymfphuCmbfmxq5/V1g+rat3ttCPeWXjmZ0+m7JMkq11abY+kqY0uW63mbbikzBIJYzB/cpaA1t9Y3D/0aevOSvq7omISC+mQCfemN+fAAAgAElEQVQ5LZ86sJ0yGkgBSX5bci7fq/8CTdszpBLh6tEdEAS3neGtoUjub6XyqIiIxJECXW+UXT7tQnjz3Z7voJQdlLIusx/3N4/jF83n7NxgBxDe2GrXS4FEQ+VRERHpiRToeoMulk/bmjPbkUlRTzlbvZy3vIoZzRfxRz88t/3tpoqSBPXpDCUqj4qISC+hQNfTdLF86ns8CdR7ijRJNjGAn6bHMzdzzu4fjUzCoF9ZklQi0RrYdjQ1M2rYQN3CSkREehUFurjbS/k0O5vZbh/zNqbfWsJbEyWs9/24r3lcpAFO5VEREZGOUaCLk5bZtx2bg9m3xq3Q3LhHadR2+wltB7gdnqKREhop4ZfNZ/KD5i/mp997UZpK0JTO0L88Sb+yEpVHRUREukCBrpiFAa5+4xoSzdspJb3r+2FIs92m39oKbxBd+TSZMDIZp3+5yqMiIiL5oEBXJKY/t4LBL93MWfULSAKlNFBBIziUZ223S3gLnxdD+bSlPFqaTPCxgX1aA9v+fUsZNqhCoU1ERCSPFOgKaPpzK5j14koAqpPv8Jntj3AE79EnU88U6im1Pa/rsfvsG0RXPlV5VEREpDgp0OXY5PsXsWpDcFusjdsbW28WX1X/JlMTj/Mre4cBtp0Ky7ojQlZo60j51IEt3gcjk/PyacKCPvQtVXlUREQkLmIf6MxsHHAnkATucfdbouhHS5AzYEXdNiYmfseU5BPs17iNPjQwoGTHHp/p6OxbS/l0O314LXNot6/9lkwEP1UeFRER6RliHejMLAn8BBgL1AKvmNl8d3+r0H057dADuPnXdUxM/I6flzzCQYnNe2zT0QC3zUtp8BIyluxy+bQ0lSDdnGH/ihLKUsnWwAYotImIiPQwsQ50wEnAcnd/F8DM5gITgIIHusvPGMkRqx/ljGX3trZ1JsBlsE6XT1UeFREREYh/oDsEWJX1uhY4efeNzGwqMBVg+PDheevMmU3/g9ver//mQL0H9z7tyOpTrR4VERGRfYl7oOsQd58BzACorq5u5ypt3fd8yamc4U/vcfP6Ld6HDMaffTg/SE/c4/y3RBgChw4ILlCyoylYNeoOk06r0t0QREREZK/iHuhWA8OyXleGbQX3sxdWcPNrxzAxcRlTkk/QN9nI0vTOm9ebQWnS6FeRYpDTWh5VaBMREZHuinugewU4zMxGEAS5iUDh718F/GH5ekYO6cvaAyay/ozrOGLkYJ54YQWbF63iON13VERERPLIvL37RMWEmV0I3EFw2ZL73P3mvW1fXV3tNTU1BembiIiISHeY2WJ3r97XdnGfocPdfwP8Jup+iIiIiEQl9jN0nWVmdcD7ed7NYGBdnvfRm2g8c0vjmVsaz9zSeOaWxjO3ohjP/+PuQ/a1Ua8LdIVgZjUdmR6VjtF45pbGM7c0nrml8cwtjWduFfN4JqLugIiIiIh0jwKdiIiISMwp0OXHjKg70MNoPHNL45lbGs/c0njmlsYzt4p2PHUOnYiIiEjMaYZOREREJOYU6ERERERiToEuh8xsnJn92cyWm9m1UfenmJjZMDN7xszeMrM3zezqsH2QmS00s3fCn/uH7WZmPw7HcomZnZD1XZPC7d8xs0lZ7Sea2RvhZ35sZlb437SwzCxpZq+a2ePh6xFm9nI4Bg+ZWWnYXha+Xh6+X5X1HdPC9j+b2flZ7b3qeDazgWb2iJn9ycyWmdmpOj67zsz+Mfy3vtTMfmFm5To+O8fM7jOztWa2NKst78dke/uIu3bG87bw3/wSM5tnZgOz3uvUsdeV4zun3F2PHDwIbj22Avg4UAq8Dhwddb+K5QEcDJwQPu8PvA0cDfwAuDZsvxa4NXx+IfAEYMApwMth+yDg3fDn/uHz/cP3FoXbWvjZC6L+vQswrv8EzAEeD18/DEwMn08Hrgiffw2YHj6fCDwUPj86PFbLgBHhMZzsjcczMAv4u/B5KTBQx2eXx/IQ4D2gT9ZxOVnHZ6fH8UzgBGBpVlvej8n29hH3RzvjeR6QCp/fmjWenT72Ont85/qhGbrcOQlY7u7vunsjMBeYEHGfioa7r3H3P4bPtwDLCP7oTyD4Dynhz8+EzycAD3jgJWCgmR0MnA8sdPcN7r4RWAiMC98b4O4vefCv5oGs7+qRzKwS+DRwT/jagDHAI+Emu49nyzg/ApwTbj8BmOvuDe7+HrCc4FjuVcezme1H8Mf+XgB3b3T3Tej47I4U0MfMUkAFsAYdn53i7s8DG3ZrLsQx2d4+Yq2t8XT3Be6eDl++BFSGzzt17HXx729OKdDlziHAqqzXtWGb7Cacbj4eeBkY6u5rwrc+AIaGz9sbz72117bR3pPdAXwLyISvDwA2Zf1xyh6D1nEL398cbt/Zce6pRgB1wP0WlLDvMbO+6PjsEndfDdwO/IUgyG0GFqPjMxcKcUy2t4+e7isEM5XQ+fHsyt/fnFKgk4Iys37Ao8A33P2j7PfC/0vUdXQ6wMwuAta6++Ko+9JDpAhKMXe7+/HANoJSUysdnx0XnnM1gSAofwzoC4yLtFM9UCGOyd5y3JvZ9UAamB11X7pKgS53VgPDsl5Xhm0SMrMSgjA3291/FTZ/GE79E/5cG7a3N557a69so72nOg0Yb2YrCab8xwB3EpRZUuE22WPQOm7h+/sB6+n8OPdUtUCtu78cvn6EIODp+Oyac4H33L3O3ZuAXxEcszo+u68Qx2R7++iRzGwycBFwaRhgofPjuZ7OH985pUCXO68Ah4WrXEoJTnycH3GfikZ4vsC9wDJ3/2HWW/OBllVXk4DHstq/HK7cOgXYHJYAngTOM7P9w1mA84Anw/c+MrNTwn19Oeu7ehx3n+bule5eRXCsPe3ulwLPAJ8LN9t9PFvG+XPh9h62TwxXYY0ADiM4UbpXHc/u/gGwysyOCJvOAd5Cx2dX/QU4xcwqwt+3ZTx1fHZfIY7J9vbR45jZOIJTV8a7+/astzp17IXHa2eP79zKx0qL3vogWGX0NsEKmOuj7k8xPYDTCabtlwCvhY8LCc4j+B3wDvAUMCjc3oCfhGP5BlCd9V1fIThBdTkwJau9GlgafuYuwjuh9PQHcBY7V7l+nOCPznLgl0BZ2F4evl4evv/xrM9fH47Zn8laednbjmdgNFATHqP/RbAiUMdn18fzRuBP4e/8c4LVgjo+OzeGvyA4B7GJYBb5skIck+3tI+6PdsZzOcH5bS3/XZre1WOvK8d3Lh+69ZeIiIhIzKnkKiIiIhJzCnQiIiIiMadAJyIiIhJzCnQiIiIiMadAJyIiIhJzCnQiIiIiMadAJyIiIhJzCnQiIiIiMZfa9yY9y+DBg72qqirqboiIiIjs0+LFi9e5+5B9bdfrAl1VVRU1NTVRd0NERERkn8zs/Y5sp5KriIiISMwp0ImIiIjEnAKdiIiISMwp0ImIiIjEXGwWRZjZSmAL0Ayk3b3azP4VmABkgLXAZHf/3+h6KSIiIlJ4cZuhO9vdR7t7dfj6Nncf5e6jgceB70bYNxEREZFIxC3Q7cLdP8p62RfwqPoiIiIiEpXYlFwJwtoCM3PgP919BoCZ3Qx8GdgMnN3WB81sKjAVYPjw4YXprYiIiEiBxGmG7nR3PwG4ALjSzM4EcPfr3X0YMBu4qq0PuvsMd6929+ohQ/Z5sWURERGRWIlNoHP31eHPtcA84KTdNpkN/HWh+yUiIiIStVgEOjPra2b9W54D5wFLzeywrM0mAH+Kon8iIiIiUYrLOXRDgXlmBkGf57j7b83sUTM7guCyJe8DX42wjyIiIiKRiEWgc/d3gePaaFeJVURERHq9WJRcRURERKR9CnQiIiIiMadAJyIiIhJzCnQiIiIiMadAJyIiIhJzCnQiIiIiMadAJyIiIhJzCnQiIiIiMadAJyIiIhJzCnQiIiIiMadAJyIiIhJzCnQiIiIiMadAJyIiIhJzCnQiIiIiMZeKugMdZWYrgS1AM5B292ozuw34v0AjsAKY4u6bouuliIiISOHFbYbubHcf7e7V4euFwCfcfRTwNjAtuq6JiIiIRCNugW4X7r7A3dPhy5eAyij7IyIiIhKFOAU6BxaY2WIzm9rG+18Bnmjrg2Y21cxqzKymrq4ur50UERERKbQ4BbrT3f0E4ALgSjM7s+UNM7seSAOz2/qgu89w92p3rx4yZEhheisiIiJSILEJdO6+Ovy5FpgHnARgZpOBi4BL3d0j66CIiIhIRGIR6Mysr5n1b3kOnAcsNbNxwLeA8e6+Pco+ioiIiEQlLpctGQrMMzMI+jzH3X9rZsuBMmBh+N5L7v7V6LopIiIiUnixCHTu/i5wXBvth0bQHREREZGiEouSq4iIiIi0T4FOREREJOYU6ERERERiToFOREREJOYU6ERERERiToFOREREJOYU6ERERERiToFOREREJOYU6ERERERiToFOREREJOYU6ERERERiToFOREREJOYU6ERERERiToFOREREJOZiE+jMbKWZvWFmr5lZTdj2eTN708wyZlYddR9FREREopCKugOddLa7r8t6vRT4LPCfEfVHREREJHJxC3S7cPdlAGYWdVdEREREIhObkivgwAIzW2xmUzvzQTObamY1ZlZTV1eXp+6JiIiIRCNOge50dz8BuAC40szO7OgH3X2Gu1e7e/WQIUPy10MRERGRCMQm0Ln76vDnWmAecFK0PRIREREpDrEIdGbW18z6tzwHziNYECEiIiLS68Ui0AFDgd+b2evAIuDX7v5bM7vYzGqBU4Ffm9mTkfZSREREJAKxWOXq7u8Cx7XRPo+g/CoiIiLSa8Ui0MXB5PsXsWrDdjZub6QslaSiNMmaTfU0NGcAyGQgkYCMAw6phJF2D9bu2p5ticTeP9Pd97XP4vpO7VP71D61T+0zHvvsW5oklUiwf99S6hub2dHUzKhhA5k5JdpT+xXocuS0Qw/g5l/XMTHxO6Ykn2Dw9s2UWJqmVAm4U5JK00T43NI4CYzM3tv29Znuvq99Ftd3ap/ap/apfWqfxb/PZqckk2bT5gH8ND2euZlzOO3QA6KOIZi7F25nZv8APOjuGwu2091UV1d7TU1NXr77+bk/4IxlN+flu0VERKT4vHDU9Zw58Vt5+34zW+zu+7y9aaFn6IYCr5jZH4H7gCe9kIkyz85s+h/cgtlaERER6dmc4L/9xaCggc7dv21m3yG47MgU4C4zexi4191XFLIv+fB8yamc4U/TYxKqiIiI7NXzJafS4Tsd5FHBz6FzdzezD4APgDSwP/CImS109/zNWebZz15Ywc2vHcPExGXBOXSE59Bl1eM7Xa/vwGe6+772WVzfqX1qn9qn9ql9xmOfmwjPoXvtGK4/ZAWXnzEy0hxS0EBnZlcDXwbWAfcA/+zuTWaWAN4BYhvo/rB8PSOH9GXB9nE8l/q0Vrn24H32lN9D+9Q+tU/tU/vs/D53X+U6qKmZPyxf37sCHTAI+Ky7v5/d6O4ZM7uowH3JqaiXK4uIiEjvVehz6G7Yy3vLCtkXERERkZ4iEXUHRERERKR7FOhEREREYk6BTkRERCTmFOhEREREYk6BTkRERCTmCn5h4a4ys5XAFqAZSLt7tZkNAh4CqoCVwBeivE+siIiISBTiNkN3truPzrpJ7bXA79z9MOB34WsRERGRXiVugW53E4BZ4fNZwGci7IuIiIhIJOIU6BxYYGaLzWxq2DbU3deEzz8Ahrb1QTObamY1ZlZTV1dXiL6KiIiIFExszqEDTnf31WZ2ILDQzP6U/aa7u5l5Wx909xnADIDq6uo2txERERGJq9jM0Ln76vDnWmAecBLwoZkdDBD+XBtdD0VERESiEYtAZ2Z9zax/y3PgPGApMB+YFG42CXgsmh6KiIiIRCcuJdehwDwzg6DPc9z9t2b2CvCwmV0GvA98IcI+ioiIiEQiFoHO3d8FjmujfT1wTuF7JCIiIlI8YlFyFREREZH2KdCJiIiIxJwCnYiIiEjMKdCJiIiIxJwCnYiIiEjMKdCJiIiIxJwCnYiIiEjMKdCJiIiIxJwCnYiIiEjMKdCJiIiIxJwCnYiIiEjMKdCJiIiIxJwCnYiIiEjMKdCJiIiIxFxsAp2ZJc3sVTN7PHw9xsz+aGZLzWyWmaWi7qOIiIhIFGIT6ICrgWUAZpYAZgET3f0TwPvApAj7JiIiIhKZWAQ6M6sEPg3cEzYdADS6+9vh64XAX0fRNxEREZGoxSLQAXcA3wIy4et1QMrMqsPXnwOGtfdhM5tqZjVmVlNXV5ffnoqIiIgUWNEHOjO7CFjr7otb2tzdgYnAj8xsEbAFaG7vO9x9hrtXu3v1kCFD8t5nERERkUKKw0KC04DxZnYhUA4MMLMH3f1LwBkAZnYecHiEfRQRERGJTNHP0Ln7NHevdPcqglm5p939S2Z2IICZlQH/AkyPsJsiIiIikSn6QLcX/2xmy4AlwH+7+9NRd0hEREQkCnEoubZy92eBZ8Pn/wz8c5T9ERERESkGcZ6hExEREREU6ERERERiT4FOREREJOYU6ERERERiToFOREREJOYU6ERERERiToFOREREJOYU6ERERERiToFOREREJOYU6ERERERiToFOREREJOYU6ERERERiToFOREREJOYU6ERERERiLlaBzsySZvaqmT0evj7HzP5oZq+Z2e/N7NCo+ygiIiJSaLEKdMDVwLKs13cDl7r7aGAO8O1IeiUiIiISodgEOjOrBD4N3JPV7MCA8Pl+wP8Wul8iIiIiUUtF3YFOuAP4FtA/q+3vgN+YWT3wEXBKWx80s6nAVIDhw4fnuZsiIiIihRWLGTozuwhY6+6Ld3vrH4EL3b0SuB/4YVufd/cZ7l7t7tVDhgzJc29FRERECisuM3SnAePN7EKgHBhgZr8GjnT3l8NtHgJ+G1UHRURERKISixk6d5/m7pXuXgVMBJ4GJgD7mdnh4WZj2XXBhIiIiEivEJcZuj24e9rMLgceNbMMsBH4yr4+t3jx4nVm9n6euzcYWJfnffQmGs/c0njmlsYztzSeuaXxzK0oxvP/dGQjc/d8d6TXMbMad6+Ouh89hcYztzSeuaXxzC2NZ25pPHOrmMczFiVXEREREWmfAp2IiIhIzCnQ5ceMqDvQw2g8c0vjmVsaz9zSeOaWxjO3inY8dQ6diIiISMxphk5EREQk5hToRERERGJOgS6HzGycmf3ZzJab2bVR96eYmNkwM3vGzN4yszfN7OqwfZCZLTSzd8Kf+4ftZmY/DsdyiZmdkPVdk8Lt3zGzSVntJ5rZG+FnfmxmVvjftLDMLGlmr5rZ4+HrEWb2cjgGD5lZadheFr5eHr5flfUd08L2P5vZ+Vntvep4NrOBZvaImf3JzJaZ2ak6PrvOzP4x/Le+1Mx+YWblOj47x8zuM7O1ZrY0qy3vx2R7+4i7dsbztvDf/BIzm2dmA7Pe69Sx15XjO6fcXY8cPIAksAL4OFAKvA4cHXW/iuUBHAycED7vD7wNHA38ALg2bL8WuDV8fiHwBGDAKcDLYfsg4N3w5/7h8/3D9xaF21r42Qui/r0LMK7/BMwBHg9fPwxMDJ9PB64In38NmB4+nwg8FD4/OjxWy4AR4TGc7I3HMzAL+LvweSkwUMdnl8fyEOA9oE/WcTlZx2enx/FM4ARgaVZb3o/J9vYR90c743kekAqf35o1np0+9jp7fOf6oRm63DkJWO7u77p7IzCX4PZkArj7Gnf/Y/h8C8Ft2g4hGKNZ4WazgM+EzycAD3jgJWCgmR0MnA8sdPcN7r4RWAiMC98b4O4vefCv5oGs7+qRzKwS+DRwT/jagDHAI+Emu49nyzg/ApwTbj8BmOvuDe7+HrCc4FjuVcezme1H8Mf+XgB3b3T3Tej47I4U0MfMUkAFsAYdn53i7s8DG3ZrLsQx2d4+Yq2t8XT3Be6eDl++BFSGzzt17HXx729OKdDlziHAqqzXtWGb7Cacbj4eeBkY6u5rwrc+AIaGz9sbz72117bR3pPdAXwLyISvDwA2Zf1xyh6D1nEL398cbt/Zce6pRgB1wP0WlLDvMbO+6PjsEndfDdwO/IUgyG0GFqPjMxcKcUy2t4+e7isEM5XQ+fHsyt/fnFKgk4Iys37Ao8A33P2j7PfC/0vUdXQ6wMwuAta6++Ko+9JDpAhKMXe7+/HANoJSUysdnx0XnnM1gSAofwzoC4yLtFM9UCGOyd5y3JvZ9UAamB11X7pKgS53VgPDsl5Xhm0SMrMSgjA3291/FTZ/GE79E/5cG7a3N557a69so72nOg0Yb2YrCab8xwB3EpRZUuE22WPQOm7h+/sB6+n8OPdUtUCtu78cvn6EIODp+Oyac4H33L3O3ZuAXxEcszo+u68Qx2R7++iRzGwycBFwaRhgofPjuZ7OH985pUCXO68Ah4WrXEoJTnycH3GfikZ4vsC9wDJ3/2HWW/OBllVXk4DHstq/HK7cOgXYHJYAngTOM7P9w1mA84Anw/c+MrNTwn19Oeu7ehx3n+bule5eRXCsPe3ulwLPAJ8LN9t9PFvG+XPh9h62TwxXYY0ADiM4UbpXHc/u/gGwysyOCJvOAd5Cx2dX/QU4xcwqwt+3ZTx1fHZfIY7J9vbR45jZOIJTV8a7+/astzp17IXHa2eP79zKx0qL3vogWGX0NsEKmOuj7k8xPYDTCabtlwCvhY8LCc4j+B3wDvAUMCjc3oCfhGP5BlCd9V1fIThBdTkwJau9GlgafuYuwjuh9PQHcBY7V7l+nOCPznLgl0BZ2F4evl4evv/xrM9fH47Zn8laednbjmdgNFATHqP/RbAiUMdn18fzRuBP4e/8c4LVgjo+OzeGvyA4B7GJYBb5skIck+3tI+6PdsZzOcH5bS3/XZre1WOvK8d3Lh+69ZeIiIhIzKnkKiIiIhJzCnQiIiIiMadAJyIiIhJzCnQiIiIiMadAJyIiIhJzCnQiIiIiMadAJyIiIhJzCnQiIiIiMadAJyIiIhJzqX1v0rMMHjzYq6qqou6GiIiIyD4tXrx4nbsP2dd2vS7QVVVVUVNTE3U3RERERPbJzN7vyHaxL7ma2Tgz+7OZLTeza6Puj4iIiEihxTrQmVkS+AlwAXA08DdmdnQUfZn+3ApeXLFul7YXV6xj+nMrouiOiIiI9CJxL7meBCx393cBzGwuMAF4q9AdGVW5H1fNeZWZY51RTW+wpORYrlpo3PXF4wvdFREREell4h7oDgFWZb2uBU6OoiOfGjmYmWOdw397KRnSHE6KmeNmM2rk4Ci6IyIiIr1IrEuuHWVmU82sxsxq6urq8rafUU1vUEqaBBlKaWZU0xt525eIiIhIi7gHutXAsKzXlWHbLtx9hrtXu3v1kCH7XPnbZUtKjqWRFBmSNJJkScmxeduXiIiISIu4B7pXgMPMbISZlQITgflRdOTFFeuYvNB4e9xsEudcz9vjZjN5oe2xUEJEREQk12J9Dp27p83sKuBJIAnc5+5vRtGXJbWbueuLx4fnzJ3HKOCuIetYUruZT+k8OhEREckjc/eo+1BQ1dXVrgsLi4iISByY2WJ3r97XdnEvuYqIiIj0egp0IiIiIjGnQCciIiIScwp0IiIiIjGnQCciIiIScwp0IiIiIjGnQCciIiIScwp0IiIiIjGnQCciIiIScwp0IiIiIjGnQCciIiIScwp0IiIiIjGnQCciIiIScwp0IiIiIjGnQCciIiISc7ENdGb2eTN708wyZlYddX9EREREohLbQAcsBT4LPB91R0RERESilIq6A13l7ssAzCzqroiIiIhEKs4zdB1mZlPNrMbMaurq6qLujoiIiEhOFfUMnZk9BRzUxlvXu/tjHf0ed58BzACorq72HHVPREREpCgUdaBz93Oj7oOIiIhIsesVJVcRERGRniy2gc7MLjazWuBU4Ndm9mTUfRIRERGJQlGXXPfG3ecB86Luh4iIiEjUYjtDJyIiIiIBBToRERGRmFOgExEREYk5BToRERGRmFOgExEREYk5BToRERGRmFOgExEREYk5BToRERGRmFOgy5Hpz63gxRXrdml7ccU6pj+3IqIeiYiISG8R2ztFFJtRlftx1ZxXmTnWGdX0BktKjuWqhcZdXzw+6q6JiIhID6dAlyOfGjmYmWOdw397KRnSHE6KmeNmM2rk4Ki7JiIiIj2cSq45NKrpDUpJkyBDKc2Manoj6i6JiIhIL6BAl0NLSo6lkRQZkjSSZEnJsVF3SURERHoBBboceXHFOiYvNN4eN5vEOdfz9rjZTF5oeyyUEPn/7d1/kF1lecDx77ObLJGA+WEw/AhCEhkrAzGRFWnU2goFij+irc4wMBXEmqq1tdZKoZlqHccZlVpbJ61pqhaloFa0RVGKoA6lpkA3ApsooFmJsgiaAAlUMD+f/nFOwjWTzWY3Z++55+73M3PmnvOec8/73HfeLA/vOe85kiRVzXvoKjI4vJWVFywp75k7m0XAyqM2Mzi8laXeRydJkiZQZGbdMYxLRFwBvBrYDgwBb8rMLaN9r7+/PwcGBiY6PEmSpEMWEWszs3+045p8yfUm4JTMXAT8ALi85ngkSZJq0diELjO/kZk7y83bgHl1xiNJklSXxiZ0+7gEuGGknRGxPCIGImJg06ZNbQxLkiRp4nX0pIiIuBk4ej+7VmTmdeUxK4CdwNUjnSczVwOrobiHbgJClSRJqk1HJ3SZedaB9kfExcCrgDOzqbM7JEmSDlFHJ3QHEhHnApcCL8/MJ+uOR5IkqS5NvoduJXAkcFNE3BURq+oOSJIkqQ6NHaHLzOfWHYMkSVInaPIInSRJkjChkyRJajwTOkmSpIYzoZMkSWq4tiR0EfHNiDhvn7LV7ahbkiSp27VrhG4+8BcR8b6Wsv421S1JktTV2pXQbQHOBOZGxFcjYkab6pUkSep67UroIjN3ZubbgS8B/w08u011S5IkdbV2PVh471scMvPKiJgEKmMAAA3lSURBVFgH/FGb6pYkSepqbUnoMvOf9tleC1zSjrolSZK6nY8tkSRJajgTOkmSpIYzoZMkSWo4EzpJkqSGa2xCFxEfiIjBiLgrIr4REcfWHZMkSVIdGpvQAVdk5qLMXAxcD7y37oAkSZLq0NiELjMfb9mcDmRdsUiSJNWpXQ8WnhAR8UHgjcBW4LcOcNxyYDnAc57znPYEJ0mS1CaR2bkDWxFxM3D0fnatyMzrWo67HJiWme8b7Zz9/f05MDBQYZSSJEkTIyLWZmb/aMd19AhdZp51kIdeDXwdGDWhkyRJ6jaNvYcuIk5q2VwG3FtXLJIkSXXq6BG6UXwoIp4H7AZ+DLy15ngkSZJq0diELjN/r+4YJEmSOkFjL7lKkiSp0NgRuk606pYhFs2bwdK+H8HGW+HEl7Fm+wIGh7fy1pcvrDs8SZLUpUzoKrRo3gxWX/15XhwfoHf3Dnb1TGV1/hXLLzy/7tAkSVIXM6Gr0NKFczhu0WPkXduB3eSu5P2LH+OEhXPqDk2SJHUx76Gr2AmnnUP2TGVn9pA9UznhtHPqDkmSJHU5R+gqtmb7AlbzXt58woN8avg4lm9fwNK6g5IkSV3NhK5Ca4Y2845r7mTlheezdOEcevdsX7CEpV52lSRJE8RLrhUaHN76K8nb0oVzWHnBEgaHt9YcmSRJ6maRmXXH0Fb9/f05MDBQdxiSJEmjioi1mdk/2nGO0EmSJDWcCZ0kSVLDmdBJkiQ1nAmdJElSw5nQSZIkNZwJnSRJUsM1PqGLiHdHREaET+6VJEmTUqMTuog4Hjgb+EndsUiSJNWl0Qkd8DHgUmByPR1ZkiSpRWMTuohYBjyYmXcfxLHLI2IgIgY2bdrUhugkSZLaZ0rdARxIRNwMHL2fXSuAv6S43DqqzFwNrIbi1V+VBShJktQBOjqhy8yz9lceEacC84G7IwJgHvDdiDg9Mx9uY4iSJEm16+iEbiSZuQ549p7tiNgI9Gfm5tqCkiRJqklj76GTJElSoZEjdPvKzBPrjkGSJKkujtBNhAfugFs/WnxKkiRNsK4YoesoD9wBn3kN7NoOvX1w0Vfg+NPrjkqSJHUxR+iqtvHWIpnLXcXnxlvrjkiSJHU5E7oKrbpliMGppxYjc9ELvX0MTj2VVbcMPX3Q/i7HDlwJV72u+JQkSRojL7lWaNG8GVx8TXDlb3+WRTvWMfzQw/Cfl/OGefNhwaXws+/D194Fubv4wpRpQA/sfLLYHvoW3PAeOPJoeOm7of/iun6KJElqkMicXC9O6O/vz4GBgQk7/5qhzbzjmjv5xNzrOP2nVwEQ4z1Zbx/0TYcj5sKL32aCJ0nSJBMRazOzf7TjHKGr2NKFc3jPyVvoH7wK4hCSOSjuwXtqOzz1GFz/TrjhUuidWixEOfGiZZ0Acmz7x/Md6+yu32Gd1mmd1mmdY6/z8NkddTXNhK5ia4Y2M3fdanpib1cgqjr5rm3FIkmS6rX9/4rBFuiIpM5JERXac7m1/1nbfiWJ2+9F7b4joe8IeMYsmHkCHH0qTJ9bXGaVJEnNcM91dUcAOEJXqcHhray8YAnPfOySp7N2YMu045mVj8PUaTDvRfCSdx742XQDVxYzYZ96FHbtcFROkqRO9fxldUcA4KSICTNwZZG1P3/ZoQ/F3vQ+uPNfYec2JsV9CU2ps1t+h3Vap3Vap3WOvc423UN3sJMiTOgqtuqWIRbNm8HShXP2lq0Z2szg8Fbe+vKFE1avJEnqPs5yrcmPH/kFV9x4H88+8jC27dxFAI/+Ygc9PcEVN97L7gQSpvQEOzOfnjWxT1lPD+zeXX7u5zuHut86O+uc1mmd1mmd1tmMOqf39TKlp4dZ0/t4avsufrljF4uOn8mVb6r3NZ+O0FXs8i8Pcu3AMDt2T652lSRpslrxyl/jLS+bmKtwBztC19hZrhHx1xHxYETcVS7n1R0TwKtfcCzT+nrpibojkSRJE20ik7mxaGxCV/pYZi4ul6/XHQwUDxb+kzOfiwN0kiR1t9NPnNURyRw0P6HrOGuGNvPxb25whE6SpC53x8bH+Odbh+oOA2h+QveOiBiMiE9HxKy6gwH46t0/5ZfbdzlCJ0nSJPDBr93bEUldRyd0EXFzRKzfz7IM+ASwEFgMPAR89ADnWR4RAxExsGnTpgmPezdwzIxpzJ4+lWdNn0oAvT1Bbw9EFBNopvbE3vX9lfX2tHxOwH7r7KxzWqd1Wqd1Wmcz6nzmtF5mHz6VhUdN59gZ05h9+FS+s+ER6tYVs1wj4kTg+sw8ZbRjfQ6dJElqiq5/Dl1EHJOZD5WbrwPW1xnPHvtL2pYunPMrCZ4kSVKVGpvQAR+JiMUUjwHcCPxhveFIkiTVoysuuY5FRGwCfjzB1cwBNk9wHZOJ7Vkt27Natme1bM9q2Z7VqqM9T8jMo0Y7aNIldO0QEQMHc71bB8f2rJbtWS3bs1q2Z7Vsz2p1cnt29CxXSZIkjc6ETpIkqeFM6CbG6roD6DK2Z7Vsz2rZntWyPatle1arY9vTe+gkSZIazhE6SZKkhjOhkyRJajgTugpFxLkRcV9EbIiIy+qOp5NExPER8e2I+H5EfC8i3lmWz46ImyLih+XnrLI8IuLjZVsORsQLW851UXn8DyPiopby0yJiXfmdj0dEtP+XtldE9EbEnRFxfbk9PyJuL9vgCxHRV5YfVm5vKPef2HKOy8vy+yLinJbySdWfI2JmRFwbEfdGxD0R8ev2z/GLiHeV/9bXR8TnImKa/XNsIuLTEfHziFjfUjbhfXKkOppuhPa8ovw3PxgR/x4RM1v2janvjad/VyozXSpYgF5gCFgA9AF3AyfXHVenLMAxwAvL9SOBHwAnAx8BLivLLwM+XK6fB9xA8T7kM4Dby/LZwI/Kz1nl+qxy3x3lsVF+93fq/t1taNc/A66heJcxwL8B55frq4C3letvB1aV6+cDXyjXTy776mHA/LIP907G/gx8BviDcr0PmGn/HHdbHgfcDzyjpV9ebP8cczv+BvBCYH1L2YT3yZHqaPoyQnueDUwp1z/c0p5j7ntj7d9VL47QVed0YENm/igztwOfB5bVHFPHyMyHMvO75foTwD0Uf/SXUfyHlPLzteX6MuCzWbgNmBkRxwDnADdl5qOZ+RhwE3Buue+ZmXlbFv9qPttyrq4UEfOAVwKfLLcDeAVwbXnIvu25p52vBc4sj18GfD4zt2Xm/cAGir48qfpzRMyg+GP/KYDM3J6ZW7B/HoopwDMiYgpwOPAQ9s8xycz/Ah7dp7gdfXKkOhptf+2Zmd/IzJ3l5m3AvHJ9TH1vnH9/K2VCV53jgAdatofLMu2jHG5eAtwOzM3Mh8pdDwNzy/WR2vNA5cP7Ke9mfwdcCuwut58FbGn549TaBnvbrdy/tTx+rO3creYDm4B/ieIS9icjYjr2z3HJzAeBvwF+QpHIbQXWYv+sQjv65Eh1dLtLKEYqYeztOZ6/v5UyoVNbRcQRwJeAP83Mx1v3lf+X6HN0DkJEvAr4eWaurTuWLjGF4lLMJzJzCfALiktNe9k/D155z9UyikT5WGA6cG6tQXWhdvTJydLvI2IFsBO4uu5YxsuErjoPAse3bM8ry1SKiKkUydzVmfnlsvhn5dA/5efPy/KR2vNA5fP2U96tXgK8JiI2Ugz5vwL4e4rLLFPKY1rbYG+7lftnAI8w9nbuVsPAcGbeXm5fS5Hg2T/H5yzg/szclJk7gC9T9Fn756FrR58cqY6uFBEXA68CLiwTWBh7ez7C2Pt3pUzoqvO/wEnlLJc+ihsfv1JzTB2jvF/gU8A9mfm3Lbu+AuyZdXURcF1L+RvLmVtnAFvLSwA3AmdHxKxyFOBs4MZy3+MRcUZZ1xtbztV1MvPyzJyXmSdS9LVvZeaFwLeB15eH7duee9r59eXxWZafX87Cmg+cRHGj9KTqz5n5MPBARDyvLDoT+D72z/H6CXBGRBxe/t497Wn/PHTt6JMj1dF1IuJciltXXpOZT7bsGlPfK/vrWPt3tSZipsVkXShmGf2AYgbMirrj6aQFeCnFsP0gcFe5nEdxH8E3gR8CNwOzy+MD+IeyLdcB/S3nuoTiBtUNwJtayvuB9eV3VlK+CaXbF+A3eXqW6wKKPzobgC8Ch5Xl08rtDeX+BS3fX1G22X20zLycbP0ZWAwMlH30PyhmBNo/x9+e7wfuLX/zVRSzBe2fY2vDz1Hcg7iDYhT5ze3okyPV0fRlhPbcQHF/257/Lq0ab98bT/+ucvHVX5IkSQ3nJVdJkqSGM6GTJElqOBM6SZKkhjOhkyRJajgTOkmSpIYzoZOkEUTEzIh4e7l+bERcO9p3JKkOPrZEkkZQvnf4+sw8peZQJOmApox+iCRNWh8CFkbEXRQPWX1+Zp5SvirotRTvKD2J4kX0fcDvA9uA8zLz0YhYSPGw16OAJ4G3ZOa97f8Zkrqdl1wlaWSXAUOZuRh4zz77TgF+F3gR8EHgycxcAvwPxWuUAFYDf5yZpwF/DvxjW6KWNOk4QidJ4/PtzHwCeCIitgJfLcvXAYsi4ghgKfDF4lWZQPH6K0mqnAmdJI3Ptpb13S3buyn+tvYAW8rRPUmaUF5ylaSRPQEcOZ4vZubjwP0R8QaAKLygyuAkaQ8TOkkaQWY+AnwnItYDV4zjFBcCb46Iu4HvAcuqjE+S9vCxJZIkSQ3nCJ0kSVLDmdBJkiQ1nAmdJElSw5nQSZIkNZwJnSRJUsOZ0EmSJDWcCZ0kSVLD/T8/37hbOIlqlAAAAABJRU5ErkJggg==\n", - "text/plain": [ - "<Figure size 720x576 with 3 Axes>" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fig = plt.figure(figsize=(10,8))\n", - "\n", - "x_position_axes = fig.add_subplot(311)\n", - "_ = x_position_axes.plot(expected_time, expected_x, 'x', label='Expected')\n", - "_ = x_position_axes.plot(time, positions[:, 0, 0], '.', label='Calculated')\n", - "_ = x_position_axes.legend()\n", - "_ = x_position_axes.set_ylabel('x')\n", - "\n", - "y_position_axes = fig.add_subplot(312, sharex=x_position_axes)\n", - "_ = y_position_axes.plot(expected_time, expected_y, 'x')\n", - "_ = y_position_axes.plot(time, positions[:, 0, 1], '.')\n", - "_ = y_position_axes.set_ylabel('y')\n", - "\n", - "z_position_axes = fig.add_subplot(313, sharex=x_position_axes)\n", - "_ = z_position_axes.plot(expected_time, expected_z, 'x')\n", - "_ = z_position_axes.plot(time, positions[:, 0, 2], '.')\n", - "_ = z_position_axes.set_ylabel('z')\n", - "_ = z_position_axes.set_xlabel('time')" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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RrWv5dMu2dlornLwwvqGOUqnOa7+Z2YiT5x66XwFrgb2AnYCLJf02Iv530cGZ2ehR7fLp+IY6kFw+NbNRIU/J9XsR8Z/p/UuSDiIbrTMzG7DOtd86ImjtCDZvq2zxXpdPzWw0y1Ny/c8u223A2YVFZGYjTtfy6Stb22ivYACusSQaS3V+dJaZWeJ16Mys6sonL9RR+aOzOsunU8c38IlD5nv0zcysCyd0Zlax8vLp1rYOtrZ69qmZ2WByQmdm/VLt8um4hjoaG+ro6MDlUzOzAeoxoZN0P9DjGgERsXchEZnZsOLyqZnZ8NfbCN1R6effpZ+Xp58nFReOmQ21apZP6+tg+zH11NfX+dFZZmYF6jGhi4inACS9KyIWlO1aJOleYFHRwZlZsa5Y8jSX/O5x1m/eRmtb0NbeQUsFi/d2lk9LquP4fWez6MjdqxitmZn1JM89dJL0toj4n7RxEFBXyUElPQlsAtqBtohokjQVuAqYCzwJHB8RGyQJ+DZwJLAFOCUi7k3fczLwxfS1X42ISyuJy2ykq/ajs1w+NTMbHvIkdKcBl0ialLZfAk6twrEPiYjny7YXAbdGxDmSFqXtzwNHAPPTa3/g+8D+KQH8MtBEdq/fUkmLI2JDFWIzGxE6y6ctbR1sa++o6NFZLp+amQ1feRYWXgq8pTOhi4iNBcWyEDg4vb8UuJ0soVsIXBYRAdwlabKkmanvLRHxIoCkW4DDgZ8WFJ/ZsObyqZnZ6JXnWa4zgK8DsyLiCEl7AAdGxMUVHDeAX0oK4AcRcSEwIyLWpf3PADPS+x2BVWWfXZ3aemrv7nc4HTgdYM4cjyjYyFDt8qnXfjMzq115Sq4/Bn4EnJm2HyG7162ShO7PI2KNpD8DbpH0UPnOiIiU7FVFShgvBGhqaqra95oNlqVPbeCcmx7koXUvE0HF5dPGkhjfWGK7sQ3sOXOiH1xvZlbj8iR00yLiaklnQPYsV0kVLUQVEWvSz+ckXQfsBzwraWZErEsl1edS9zXATmUfn53a1vDHEm1n++2VxGU2XJSXT7e2dLCtwtG3xpKoL9V58oKZ2QiVJ6HbLGkH0iLDkg4ABnwfnaTtgLqI2JTeHwacBSwGTgbOST+vTx9ZDHxS0pVkkyI2pqTvZuDrkjqHFQ4DzhhoXGZDqbx8Wum9b+DyqZnZaJMnofscWVI1T9L/ANOB4yo45gzgumw1EuqBKyLivyTdA1wt6TTgKeD41P9GsiVLVpItW/JhgIh4UdLZwD2p31mdEyTMhrPO0beXtrbS2t7Blm3tLp+amVlFlE0e7aWDNIZsvbhdAQEPk42wbSs+vOpramqK5ubmoQ7DRpHy8mmlyRt47Tczs9FE0tKIaOqrX54RujsjYh9gRdmX3wvsU0F8ZiNS54Pr73t6A1ta2isun3be+7ZdY4kFc6Z49M3MzLrVY0In6Q1ky4CMk7SAbHQOYCIwfhBiMxv2ysunr7a0s3lbZQ+ubyyJxlIdjQ0lr/1mZma59TZC927gFLLZo+eVtW8CvlBgTGbDVrXLp9s3lugAl0/NzKwiPSZ06bmol0r6QET8fBBjMhsWytd+K9WJrW0dbG0d+PIhLp+amVlR8jz66+eS3gPsCYwtaz+ryMDMBlu1y6dj6utoqJPLp2ZmVrg8j/66gOyeuUOAi4BjgbsLjsusUF0nL1Tj0VnbN5ZQndj9DRP4/BG7e/TNzMwGTZ5ZrgdFxN6SlkXEP0s6F7ip6MDMqqnro7Neaal88oLLp2ZmNlzkSeheTT+3SJoFvADMLC4ks8pVu3w6YUyJupIoqc7lUzMzG3byJHQ3SJoM/BtwL9kjwC4qNCqzfnD51MzMRrs8kyLOTm9/LukGYGxEDPhZrmaVKqJ86kdnmZlZLettYeFjetlHRFxbTEhmr3fOjQ9ydfMqWto6aO0ItlU4+jZhTIkxjSUmj2v0g+vNzGxE6G2E7r297AvACZ1VXbUfnQUun5qZ2cjX28LCHx7MQGx0Ki+ftrVXfu+by6dmZjYa5VmH7kvdtXthYRsIl0/NzMyqL88s181l78cCRwEPFhOOjSTVLp967TczM7Pu5Znlem75tqRvAjcXFpHVrGqXT8fU1zGuoY5pE8Z69M3MzKwXeUbouhoPzK52IFZbOkffHli7kVda2tja0lFx+XR8Qx2lUp0nL5iZmfVTnnvo7ieb1QpQAqYDvn9ulCkvn27a2lZx8ubyqZmZWfXkGaE7qux9G/BsRLQVFI8NE9V+dJbLp2ZmZsXJk9DNBFZExCYASRMk7RERS4oNzQZL1/Lplm3ttFa49pvLp2ZmZoMnT0L3fWCfsu3N3bRZDal2+XR8Qx1ILp+amZkNkTwJnSLiteGaiOiQNJDJFDZEXD41MzMb2fIkZo9L+jTZqBzAJ4DHiwvJKlFE+dSPzjIzMxve8iR0Hwe+A3yRbLbrrcDpRQZl+ZWv/RYBr7RUNvrm8qmZmVntybOw8HPACYMQi+Xg8qmZmZl11WNCJ+m7/HH9uT8REZ8uJCJ7nSuWPM35tz3Khi2tREflT19w+dTMzGzk6W2ErnnQorDXdD68viOCrW0dbG0deALn8qmZmdno0GNCFxGXDmYgo1VnCXX95m28srWN9goG4CaMKTGmscTkcY0un5qZmY0ieR79NR34PLAHMLazPSIOLTCuEav8HrhXtrZVNALn8qmZmZlBvlmuPwGuAt5DNuP1ZGB9kUH1h6TDgW+TPWf2oog4Z4hDep3yEbhKlhCpr4Ptx9Sz3dgG9pw50eVTMzMze02ehG6HiLhY0mci4jfAbyTdU3RgeUgqAecD7wJWA/dIWhwRDwxVTNUagRvXUEdjQx0l1XH8vrNZdOTuVY7UzMzMRoo8CV1r+rlO0nuAtcDU4kLql/2AlRHxOICkK4GFwJAkdFcseZovXHf/gD7bWBL1pTqmjm/gE4fM9/1vZmZmlluehO6rkiYB/wB8F5gI/H2hUeW3I7CqbHs1sH/XTpJOJy2GPGdOcYnSTcvX9av/9o0lGhtKHoEzMzOziuRZWPiG9HYjcEix4RQjIi4ELgRoamqq7DlYvThir5n896PPd7uvcwTOS4iYmZlZteWZ5Xop8JmIeCltTwHOjYhTiw4uhzXATmXbs1PbkOgsk3beQ9fa3uF74MzMzKxweUque3cmcwARsUHSggJj6o97gPmSdiZL5E4AThzKgE7cf47vfzMzM7NBlSehq5M0JSI2AEiamvNzhYuINkmfBG4mW7bkkohYMcRhmZmZmQ2qPInZucCdkn6Wto8DvlZcSP0TETcCNw51HGZmZmZDRRF9zxGQtAfQ+WSIXw/lOm+VkrQeeKrgw0wDup8dYQPh81ldPp/V5fNZXT6f1eXzWV1DcT7fGBHT++qUK6Gz/pHUHBFNQx3HSOHzWV0+n9Xl81ldPp/V5fNZXcP5fNYNdQBmZmZmVhkndGZmZmY1zgldMS4c6gBGGJ/P6vL5rC6fz+ry+awun8/qGrbn0/fQmZmZmdU4j9CZmZmZ1TgndGZmZmY1zgldlUk6XNLDklZKWjTU8QwXknaSdJukByStkPSZ1D5V0i2SHk0/p6R2SfpOOo/LJO1T9l0np/6PSjq5rH1fSfenz3xHkgb/Nx1ckkqS7pN0Q9reWdKSdA6uktSY2sek7ZVp/9yy7zgjtT8s6d1l7aPqWpY0WdI1kh6S9KCkA319Dpykv09/1pdL+qmksb4++0fSJZKek7S8rK3wa7KnY9S6Hs7nv6U/88skXSdpctm+fl17A7m+qyoi/KrSi+zxY48BuwCNwB+APYY6ruHwAmYC+6T3E4BHgD2AfwUWpfZFwDfS+yOBmwABBwBLUvtU4PH0c0p6PyXtuzv1VfrsEUP9ew/Cef0ccAVwQ9q+Gjghvb8A+Nv0/hPABen9CcBV6f0e6TodA+ycrt/SaLyWgUuBj6T3jcBkX58DPpc7Ak8A48quy1N8ffb7PP4lsA+wvKyt8Guyp2PU+quH83kYUJ/ef6PsfPb72uvv9V3tl0foqms/YGVEPB4RLcCVwMIhjmlYiIh1EXFver8JeJDsL/2FZP+Qkn6+L71fCFwWmbuAyZJmAu8GbomIFyN7vvAtwOFp38SIuCuyPzWXlX3XiCRpNvAe4KK0LbInulyTunQ9n53n+RrgHan/QuDKiNgWEU8AK8mu41F1LUuaRPaX/cUAEdESES/h67MS9cA4SfXAeGAdvj77JSJ+C7zYpXkwrsmejlHTujufEfHLiGhLm3cBs9P7fl17A/z7t6qc0FXXjsCqsu3Vqc3KpOHmBcASYEZErEu7ngFmpPc9ncve2ld30z6S/TvwT0BH2t4BeKnsL6fyc/DaeUv7N6b+/T3PI9XOwHrgR8pK2BdJ2g5fnwMSEWuAbwJPkyVyG4Gl+PqshsG4Jns6xkh3KtlIJfT/fA7k79+qckJng0rS9sDPgc9GxMvl+9L/JXodnRwkHQU8FxFLhzqWEaKerBTz/YhYAGwmKzW9xtdnfumeq4VkifIsYDvg8CENagQajGtytFz3ks4E2oCfDHUsA+WErrrWADuVbc9ObQZIaiBL5n4SEdem5mfT0D/p53Opvadz2Vv77G7aR6q3AUdLepJsyP9Q4NtkZZb61Kf8HLx23tL+ScAL9P88j1SrgdURsSRtX0OW4Pn6HJh3Ak9ExPqIaAWuJbtmfX1WbjCuyZ6OMSJJOgU4CjgpJbDQ//P5Av2/vqvKCV113QPMTzNdGsluflw8xDENC+l+gYuBByPivLJdi4HOWVcnA9eXtX8ozdw6ANiYSgA3A4dJmpJGAQ4Dbk77XpZ0QDrWh8q+a8SJiDMiYnZEzCW7zn4dEScBtwHHpm5dz2fneT429Y/UfkKahbUzMJ/sRulRdS1HxDPAKkm7pqZ3AA/g63OgngYOkDQ+/b6d59PXZ+UG45rs6RgjjqTDyW5dOToitpTt6te1l67X/l7f1VXETIvR/CKbafQI2SyYM4c6nuHyAv6cbNh+GfD79DqS7D6CW4FHgV8BU1N/Aeen83g/0FT2XaeS3aC6EvhwWXsTsDx95nukJ6GM9BdwMH+c5boL2V86K4GfAWNS+9i0vTLt36Xs82emc/YwZTMvR9u1DLwVaE7X6H+SzQj09Tnw8/nPwEPpd76cbLagr8/+ncOfkt2D2Eo2inzaYFyTPR2j1l89nM+VZPe3df67dMFAr72BXN/VfPnRX2ZmZmY1ziVXMzMzsxrnhM7MzMysxjmhMzMzM6txTujMzMzMapwTOjMzM7Ma54TOzMzMrMY5oTMzMzOrcU7ozMzMzGpcfd9dRpZp06bF3LlzhzoMMzMzsz4tXbr0+YiY3le/UZfQzZ07l+bm5qEOw8zMzKxPkp7K088lVzMzM7Malyuhk/QpSVOKDsbMzMzM+i/vCN0M4B5JV0s6XJKKDMrMzMzM8suV0EXEF4H5wMXAKcCjkr4uaV6BsZmZmZlZDrnvoYuIAJ5JrzZgCnCNpH8tKDYzMzMzyyHXLFdJnwE+BDwPXAT8Y0S0SqoDHgX+qbgQzczMzKw3eZctmQocExGvmzobER2Sjqp+WGZmZmaWV66ELiK+3Mu+B6sXjpmZmZn1l9ehMzMzM6txTujMzMzMapwTOjMzM7Ma1+s9dJI2AdHT/oiYWPWIzMzMzKxfek3oImICgKSzgXXA5YCAk4CZhUdnZmZmZn3KW3I9OiL+/4jYFBEvR8T3gYXVCCA9SuxhSSslLepm/xhJV6X9SyTN7bJ/jqRXJP3vasRjZmZmVmvyJnSbJZ0kqSSpTtJJwOZKDy6pBJwPHAHsAfy1pD26dDsN2BARbwK+BXyjy/7zgJsqjcXMzMysVuVN6E4EjgeeTa/jUlul9gNWRsTjEdECXMmfjvwtBC5N768B3iFJAJLeBzwBrKhCLGZmZmY1Ke/Cwk9SpRJrFzsCq8q2VwP799QnItokbQR2kLQV+DzwLqDXcquk04HTAebMmVOdyM3MzMyGiVwjdJLeLOlWScvT9t6SvlhsaH36CvCtiHilr44RcWFENEVE0/Tp04uPzMzMzGwQ5S25/hA4A2gFiIhlwAlVOP4aYKey7dmprds+kuqBScALZCN5/yrpSeCzwBckfbIKMZmZmZnVlFwlV2DnPwBBAAAgAElEQVR8RNydbl3r1FaF498DzJe0M1nidgJ/em/eYuBk4E7gWODXERHAX3R2kPQV4JWI+F4VYjIzMzOrKXkTuuclzSMtMizpWLJ16SqS7on7JHAzUAIuiYgVks4CmiNiMXAxcLmklcCLVGdk0MzMzGzEUDbY1UcnaRfgQuAgYAPZzNKTIuKpYsOrvqampmhubh7qMMzMzMz6JGlpRDT11S/vCF1ExDslbQfURcSmVCY1MzMzsyGWd1LEzwEiYnNEbEpt1xQTkpmZmZn1R68jdJJ2A/YEJkk6pmzXRGBskYGZmZmZWT59lVx3BY4CJgPvLWvfBHy0qKDMzMzMLL9eE7qIuB64XtKBEXHnIMVkZmZmZv2Q9x66j0ua3LkhaYqkSwqKyczMzMz6IW9Ct3dEvNS5EREbgAXFhGRmZmZm/ZE3oauTNKVzQ9JU8i95YmZmZmYFypuUnQvcKelnafs44GvFhGRmZmZm/ZEroYuIyyQ1A4empmMi4oHiwjIzMzOzvPKWXAGmApsj4nvAej8pwszMzGx4yJXQSfoy8HngjNTUAPxHUUGZmZmZWX55R+jeDxwNbAaIiLXAhKKCMjMzM7P88iZ0LRERQABI2q64kMzMzMysP/ImdFdL+gEwWdJHgV8BP6xGAJIOl/SwpJWSFnWzf4ykq9L+JZLmpvZ3SVoq6f7089CunzUzMzMbDfLOcv2mpHcBLwNvBr4UEbdUenBJJeB84F3AauAeSYu7zKA9DdgQEW+SdALwDeCvgOeB90bEWkl7ATcDO1Yak5mZmVmt6c/iwPcD48jKrvdX6fj7ASsj4nEASVcCC4HyhG4h8JX0/hrge5IUEfeV9VkBjJM0JiK2VSk2MzMzs5qQd5brR4C7gWOAY4G7JJ1ahePvCKwq217Nn46yvdYnItqAjcAOXfp8ALi3p2RO0umSmiU1r1+/vgphm5mZmQ0feUfo/hFYEBEvAEjaAbgDuKSowPKStCdZGfawnvpExIXAhQBNTU0xSKGZmZmZDYq8kyJeADaVbW9KbZVaA+xUtj07tXXbR1I9MKnz2JJmA9cBH4qIx6oQj5mZmVnNyTtCtxJYIul6snvoFgLLJH0OICLOG+Dx7wHmp6dOrAFOAE7s0mcxcDJwJ1m599cREZImA78AFkXE/wzw+GZmZmY1L29C91h6dbo+/axoceGIaJP0SbIZqiXgkohYIeksoDkiFgMXA5dLWgm8SJb0AXwSeBPwJUlfSm2HRcRzlcRkZmZmVmuUrRfcRydpbERs7dI2LSKeLyyygjQ1NUVzc/NQh2FmZmbWJ0lLI6Kpr35576G7W9IBZV/+AbJJEWZmZmY2xPKWXE8CLpF0OzCLbNkQP5nBzMzMbBjI+6SI+yV9DbicbIbrX0bE6kIjMzMzM7NcciV0ki4G5gF7kz366wZJ342I84sMzszMzMz6lvceuvuBQyLiiYi4Gdgf2Ke4sMzMzMwsr1wJXUT8OzBW0q5pe2NEnFZoZGZmZmaWS95nub4X+D3wX2n7rZIWFxmYmZmZmeWTt+T6FWA/4CWAiPg9sEtBMZmZmZlZP+RN6FojYmOXto5qB2NmZmZm/Zd3HboVkk4ESpLmA5/GCwubmZmZDQt5R+g+BewJbAOuADYCny0qKDMzMzPLL+/CwluAM9PLzMzMzIaRvCN0ZmZmZjZMOaEzMzMzq3FDntBJOlzSw5JWSlrUzf4xkq5K+5dImlu274zU/rCkdw9m3GZmZmbDRd5Zrq+RdG9EVOWxX5JKwPnAu4DVwD2SFkfEA2XdTgM2RMSbJJ0AfAP4K0l7ACeQTdaYBfxK0psjor0asQ3UFUue5pLfPc5LW1tpbe+gtS1oLIkQtLYFdWTrvZS39bV/IJ/xMX1MH9PH9DGHxzFHyu/hY76+ber4Bj5xyHxO3H8Ow4Eion8fkO6LiAVVObh0IPCViHh32j4DICL+pazPzanPnZLqgWeA6cCi8r7l/Xo7ZlNTUzQ3N1cj/D9xxZKn+cJ19xfy3WZmZjb8fP39/1+hSZ2kpRHR1Fe/gZRcfzGAz/RkR2BV2fbq1NZtn4hoI1syZYecnwVA0umSmiU1r1+/vkqh/6mblq8r7LvNzMxs+Bku//b3O6GLiC8WEUiRIuLCiGiKiKbp06cXdpwj9ppZ2HebmZnZ8DNc/u3v9z10VbYG2Klse3Zq667P6lRynQS8kPOzg6pzyNX30PmYPqaP6WP6mCPt9/Axh/c9dEOd0N0DzJe0M1kydgJwYpc+i4GTgTuBY4FfR0RIWgxcIek8skkR84G7By3yHpy4/5xh8x/XzMzMRodcCZ2k9wK/iIiOah48ItokfRK4GSgBl0TECklnAc0RsRi4GLhc0krgRbKkj9TvauABoA34u6Ge4WpmZmY2FHLNcpX0H8CBwM/Jkq6Hig6sKEXOcjUzMzOrpqrOco2IvwEWAI8BP5Z0Z5o5OqHCOM3MzMysQrlnuUbEy8A1wJXATOD9wL2SPlVQbGZmZmaWQ66ETtLRkq4DbgcagP0i4gjgLcA/FBeemZmZmfUl7yzXDwDfiojfljdGxBZJp1U/LDMzMzPLK1dCFxEn97Lv1uqFY2ZmZmb9NZBHf5mZmZnZMOKEzszMzKzGOaEzMzMzq3G93kMn6X6gx5WHI2LvqkdkZmZmZv3S16SIo9LPv0s/L08/TyomHDMzMzPrr14Tuoh4CkDSuyJiQdmuRZLuBRYVGZyZmZmZ9S3vPXSS9LayjYP68VkzMzMzK1DehYVPAy6RNCltvwScWkxIZmZmZtYfeRcWXgq8pTOhi4iNhUZlZmZmZrnlfZbrDEkXA1dGxEZJe1T6yC9JUyXdIunR9HNKD/1OTn0elXRyahsv6ReSHpK0QtI5lcRiZmZmVsvy3gf3Y+BmYFbafgT4bIXHXgTcGhHzgVvpZoKFpKnAl4H9gf2AL5clft+MiN2ABcDbJB1RYTxmZmZmNSlvQjctIq4GOgAiog1or/DYC4FL0/tLgfd10+fdwC0R8WJEbABuAQ6PiC0RcVuKpQW4F5hdYTxmZmZmNSlvQrdZ0g6kRYYlHQBUeh/djIhYl94/A8zops+OwKqy7dWp7TWSJgPvJRvlMzMzMxt18s5y/RywGJgn6X+A6cBxfX1I0q+AN3Sz68zyjYgIST0+kaKX768Hfgp8JyIe76Xf6cDpAHPmzOnvYczMzMyGtbwJ3Qrg7cCugICHyTG6FxHv7GmfpGclzYyIdZJmAs91020NcHDZ9mzg9rLtC4FHI+Lf+4jjwtSXpqamfieOZmZmZsNZ3pLrnRHRFhErImJ5RLQCd1Z47MXAyen9ycD13fS5GThM0pQ0GeKw1IakrwKTqHxyhpmZmVlN63WETtIbyO5ZGydpAdnoHMBEYHyFxz4HuDotf/IUcHw6ZhPw8Yj4SES8KOls4J70mbNS22yysu1DwL2SAL4XERdVGJOZmZlZzVFEzxXItO7bKUAT0Fy2axPw44i4ttDoCtDU1BTNzc19dzQzMzMbYpKWRkRTX/16HaGLiEuBSyV9ICJ+XrXozMzMzKxq8j766+eS3gPsCYwtaz+rqMDMzMzMLJ+8j/66APgr4FNk99EdB7yxwLjMzMzMLKe8s1wPiogPARsi4p+BA4E3FxeWmZmZmeWVN6F7Nf3cImkW0ArMLCYkMzMzM+uPvAsL35AesfVvZM9NDcBLhJiZmZkNA3knRZyd3v5c0g3A2Iio9FmuZmZmZlYFfS0sfEwv+6jFdejMzMzMRpq+Ruje28u+AJzQmZmZmQ2xvhYW/vBgBWJmZmZmA5PrHjpJX+qu3QsLm5mZmQ29vLNcN5e9HwscBTxY/XDMzMzMrL/yznI9t3xb0jeBmwuJyMzMzMz6Je/Cwl2NB2ZXMxAzMzMzG5i899DdTzarFaAETAd8/5yZmZnZMJD3Hrqjyt63Ac9GRFslB5Y0FbgKmAs8CRwfERu66Xcy8MW0+dWIuLTL/sXALhGxVyXxmJmZmdWqvCXXmcCLEfFURKwBxknav8JjLwJujYj5wK1p+3VS0vdlYH9gP+DLkqaU7T8GeKXCOMzMzMxqWt6E7vu8PnHanNoqsRDoHG27FHhfN33eDdwSES+m0btbgMMBJG0PfA74aoVxmJmZmdW0vAmdIqLzHjoiooP85dqezIiIden9M8CMbvrsCKwq216d2gDOBs4FtvR1IEmnS2qW1Lx+/foKQjYzMzMbfvImdI9L+rSkhvT6DPB4Xx+S9CtJy7t5LSzvl5LF6OFruvvetwLzIuK6PP0j4sKIaIqIpunTp+c9jJmZmVlNyDvK9nHgO2STE4LsnrfT+/pQRLyzp32SnpU0MyLWSZoJPNdNtzXAwWXbs4HbgQOBJklPkv0Ofybp9og4GDMzM7NRJu/Cws8BJ1T52IuBk4Fz0s/ru+lzM/D1sokQhwFnRMSLpHv4JM0FbnAyZ2ZmZqNVrwmdpO/SSyk0Ij5dwbHPAa6WdBrwFHB8OmYT8PGI+EhEvCjpbOCe9JmzUjJnZmZmZklfI3TNRR04Il4A3tFNezPwkbLtS4BLevmeJwGvQWdmZmajVq8JXddFfM3MzMxs+Mn76K/pwOeBPYCxne0RcWhBcZmZmZlZTnmXLfkJ8CCwM/DPZI/quqe3D5iZmZnZ4Mib0O0QERcDrRHxm4g4FfDonJmZmdkwkHcdutb0c52k9wBrganFhGRmZmZm/ZE3ofuqpEnAPwDfBSYCf19YVGZmZmaWW96FhW9IbzcChxQXjpmZmZn1V6576CRdKmly2fYUST2uDWdmZmZmgyfvpIi9I+Klzo2I2AAsKCYkMzMzM+uPvAldXdnzVJE0lfz335mZmZlZgfImZecCd0r6Wdo+DvhaMSGZmZmZWX8oIvJ1lPbgj2vP/ToiHigsqgJJWg88VfBhpgHPF3yM0cTns7p8PqvL57O6fD6ry+ezuobifL4xIqb31Sl3Qmf5SWqOiKahjmOk8PmsLp/P6vL5rC6fz+ry+ayu4Xw+895DZ2ZmZmbDlBM6MzMzsxrnhK4YFw51ACOMz2d1+XxWl89ndfl8VpfPZ3UN2/Ppe+jMzMzMapxH6MzMzMxqnBM6MzMzsxrnhK7KJB0u6WFJKyUtGup4hgtJO0m6TdIDklZI+kxqnyrpFkmPpp9TUrskfSedx2WS9in7rpNT/0clnVzWvq+k+9NnviNJg/+bDi5JJUn3Sbohbe8saUk6B1dJakztY9L2yrR/btl3nJHaH5b07rL2UXUtS5os6RpJD0l6UNKBvj4HTtLfpz/ryyX9VNJYX5/9I+kSSc9JWl7WVvg12dMxal0P5/Pf0p/5ZZKu0+ufW9+va28g13dVRYRfVXoBJeAxYBegEfgDsMdQxzUcXsBMYJ/0fgLwCLAH8K/AotS+CPhGen8kcBMg4ABgSWqfCjyefk5J76ekfXenvkqfPWKof+9BOK+fA64AbkjbVwMnpPcXAH+b3n8CuCC9PwG4Kr3fI12nY4Cd0/VbGo3XMnAp8JH0vhGY7OtzwOdyR+AJYFzZdXmKr89+n8e/BPYBlpe1FX5N9nSMWn/1cD4PA+rT+2+Unc9+X3v9vb6r/fIIXXXtB6yMiMcjogW4Elg4xDENCxGxLiLuTe83AQ+S/aW/kOwfUtLP96X3C4HLInMXMFnSTODdwC0R8WJEbABuAQ5P+yZGxF2R/am5rOy7RiRJs4H3ABelbZE9zeWa1KXr+ew8z9cA70j9FwJXRsS2iHgCWEl2HY+qa1nSJLK/7C8GiIiWiHgJX5+VqAfGSaoHxgPr8PXZLxHxW+DFLs2DcU32dIya1t35jIhfRkRb2rwLmJ3e9+vaG+Dfv1XlhK66dgRWlW2vTm1WJg03LwCWADMiYl3a9QwwI73v6Vz21r66m/aR7N+BfwI60vYOwEtlfzmVn4PXzlvavzH17+95Hql2BtYDP1JWwr5I0nb4+hyQiFgDfBN4miyR2wgsxddnNQzGNdnTMUa6U8lGKqH/53Mgf/9WlRM6G1SStgd+Dnw2Il4u35f+L9Hr6OQg6SjguYhYOtSxjBD1ZKWY70fEAmAzWanpNb4+80v3XC0kS5RnAdsBhw9pUCPQYFyTo+W6l3Qm0Ab8ZKhjGSgndNW1BtipbHt2ajNAUgNZMveTiLg2NT+bhv5JP59L7T2dy97aZ3fTPlK9DTha0pNkQ/6HAt8mK7PUpz7l5+C185b2TwJeoP/neaRaDayOiCVp+xqyBM/X58C8E3giItZHRCtwLdk16+uzcoNxTfZ0jBFJ0inAUcBJKYGF/p/PF+j/9V1VTuiq6x5gfprp0kh28+PiIY5pWEj3C1wMPBgR55XtWgx0zro6Gbi+rP1DaebWAcDGVAK4GThM0pQ0CnAYcHPa97KkA9KxPlT2XSNORJwREbMjYi7ZdfbriDgJuA04NnXrej47z/OxqX+k9hPSLKydgflkN0qPqms5Ip4BVknaNTW9A3gAX58D9TRwgKTx6fftPJ++Pis3GNdkT8cYcSQdTnbrytERsaVsV7+uvXS99vf6rq4iZlqM5hfZTKNHyGbBnDnU8QyXF/DnZMP2y4Dfp9eRZPcR3Ao8CvwKmJr6Czg/ncf7gaay7zqV7AbVlcCHy9qbgOXpM98jPQllpL+Ag/njLNddyP7SWQn8DBiT2sem7ZVp/y5lnz8znbOHKZt5OdquZeCtQHO6Rv+TbEagr8+Bn89/Bh5Kv/PlZLMFfX327xz+lOwexFayUeTTBuOa7OkYtf7q4XyuJLu/rfPfpQsGeu0N5Pqu5suP/jIzMzOrcS65mpmZmdU4J3RmZmZmNc4JnZmZmVmNc0JnZmZmVuOc0JmZmZnVOCd0ZmZmZjXOCZ2ZmZlZjXNCZ2ZmZlbjnNCZmZmZ1bj6vruMLNOmTYu5c+cOdRhmZmZmfVq6dOnzETG9r36jLqGbO3cuzc3NQx2GmZmZWZ8kPZWnn0uuZmZmZjXOCd0gueA3j3HHY8+/rm3h+b/j1B/f/bq2H/73Y5zyo9e3mZmZmfWm8IROUrukcySprO3eoo873Ow9exKn/biZH/73YwDc8djzPPLMJn790Href/7vgCyZ+/ovHmLHyWO54DePDWW4ZmZmVkMG4x66FWSJ4y8l/VVEvAioj8+MOMtWb+SYfWbx9V88xANrX+a/lj/LQfN24NcPree+VRs5/Fu/4eFnX+GtO01i8R/WcdTeM4c6ZDMzM6sRg1FybYuIfwIuAv5b0r5ADMJxh5W9Z0/ipuXP8rY3TeO6+9YybftGbn1oPYfuNp2S4KFnXwHgoWc2AfDet8waynDNzMyshgxGQieAiLgK+CvgR8Aug3DcYeWgedN4606T+N3K55k1aSyrNrzKXrMmcvvD62lP6W0Are3Bp9/xJpat3jik8ZqZmVntGIyE7iOdbyJiOfAXwKcH4bjDyhnXLuPOx16gvk6s3biVads3snzty68lc5016LaO4Js3P0KpDt9HZ2ZmZrkUntBFxNIu2xsj4rI8n5V0uKSHJa2UtKiXfh+QFJKaKo23Grqb0frsy1vZ1tZBW0dQXyde2tLyuv3BH5O6lrYOvnPrSvaePWlwAjYzM7OaNmyXLZFUAs4HjgD2AP5a0h7d9JsAfAZYMrgR9uypFzbzscuXvpbU3fHY89z52AsANJZERwRtHVnf8tkhAew0ZRwAb5q+ncuuZmZmlsuwTeiA/YCVEfF4RLQAVwILu+l3NvANYOtgBtebzgkNH7t8Kef98mE+dvlS2gPOOHI35s/Yno5UZq3rMte3oU6s2vAqe86ayEPPvOIROjMzM8ulsIRO0j69vXJ8xY7AqrLt1antdccAdoqIX/QRy+mSmiU1r1+/vt+/S38dNG8aP/jgvrS2d/CdX6/k1ZZ2/vHdbwZgxdpNryVyHfH66b6tHcGub5jA8rUvc8w+WVLo++jMzMysL0WuQ3du+jkWaAL+QFZh3BtoBg6s5Msl1QHnAaf01TciLgQuBGhqahqUJVP+7x/W0p6G4iQ475eP0NYRHLrbdGZOGstPlqx6Xf86ZQnew89s4s/ftAM/a17Dtfeu4X0Lduzu683MzMxeU9gIXUQcEhGHAOuAfSKiKSL2BRYAa3J8xRpgp7Lt2V0+NwHYC7hd0pPAAcDi4TAx4o7Hnuc/71tDW3vw/gWzGNtQoqWtg9b2oKUtuGLJKmZMGPO6z7wllVfrBM1PbUApwfN6dGZmZtaXwbiHbteIuL9zIy1dsnuOz90DzJe0s6RG4ARgcdn3bIyIaRExNyLmAncBR0dEc3XD77//+4e11Jfq+MJ7duM3jzzPO3efQUfA3B3G87uVz7PnrIk8u2kbAKX0X+C+VRt5x27TaayvY2trB9vaOjh23x09McLMzMz6NBgJ3TJJF0k6OL1+CCzr60MR0QZ8ErgZeBC4OiJWSDpL0tEFx1yRN+6wHT/44L589C/m8Tf7z+G6+9ZkSdzL23j/glksX/syAIfuNp3LT9uf+nRT3W0Pr6e1PZv+Wl8H1yxd4/XozMzMrE+DkdB9mOx5rp9JrwdSW58i4saIeHNEzIuIr6W2L0XE4m76HjwcRucAPv72eRw0bxp3PPY8/7Hkaf78TTu8NtFh1zdMZOaksQAcOG8HDpo3jctO248FO00iAto7YLcZ29PeARHh9ejMzMysT0VOigAgIrZKugC4MSIeLvp4w8UZ1y7jhmXr+MEH92XZ6o28cYfxXLFkFXvMmsi2tg7OfM9upME4Dpo3jd1mTmTFuk28+c+2Z/nal9n1DRN45JlN7DkrW4/uoHnThvYXMjMzs2Gr8BG6VB79PfBfafutkv5khG0k+/jb5/GevWfRUBIr1r7M3+w/h4/+xTw+/vZ5r/V54w7bcdy+O7J87cvsNGUsDz+z6bX16Fx2NTMzs94MRsn1y2SLBL8EEBG/B3YehOMOqX85Zm9+8MF9Oe3Hzfz9VffxscuXMqahxKcPfRM/uuNJzrj29bcR7j17Ejctf5Z37DadVRu2stOUcSxf+zIHzZvK929/3GVXMzMz69FgJHStEdF1quagrAU31A6aN43D95rBdfetZVtbBz/44L4cMG8HAG5Ytu51z3tdtnojf3vwLtzx2IvsNWsiqza8yk5TxnHrQ+s5Yq8Znu1qZmZmPRqMhG6FpBOBkqT5kr4L3DEIxx1yZ1y7jF89+Bx7zppAS1sHP2tezccuX8pRe8987d66Th9/+zzaO+CYfWa9VnZdteFV9po1kWvvXeuyq5mZmfVoMBK6TwF7AtuAK4CNZLNdR7Q7HnueG5atA+DM9+zB+xfsyHX3rWHb/2vv7qOsqs48j39/VUUJEkWEWolaoFIotrHRMiUoxuhg4msi3Zm42hDblzi6TIc2iZ3OaOxlojNxOjHjpA0mROMLHSQmGpOm1YwaXxgjESmDQVGIVahQahQQSwUFinrmj3OqvAVV1Av3nFsvv89ad9179jnnPvvubMon5+y9z9ZtfObwfZlWM7bDGDr44LbrxKqRO9x2vf6hBl5ev7EUP8XMzMz6uTwSutMj4oqIOCp9/QvQr9eRK4ZlTc385O8/xqcn78MFty3ht8++RmW5kMTyV5s7vdrWdtv19Xc2U1GmDrddt7WGnxphZmZmncojobu8h2WDSttadBOqRvLe1lbe39rKxcfX8PWTD+aae1e0PyFi+3O2tcJRB4xmWLnak7qKMnH0hL09js7MzMw6ldk6dJJOBU4D9pN0fcGuPYGWrOL2B3MWNjK5ehTLmpq5s34NleUCiR892khlRRlHjBvF4w3rufC4mh3OnVw9ihseaaClNYh07khLa/DEqjc5pmYMcxY27nCr1szMzIa2LK/QvQrUA+8DTxW8FgAnZxi35CZXj2LW/KWseXMjjWs3IgkiaGkNNm3ZxsrX3+WiT0zo9NxlTc1ccuJEWluj/akRAO9v3cZ1D/zZ4+jMzMxsB5kldBHxp4iYC/w1MC8i5qbb/0EyQWLQmlYzltkza7n7j6/y8Ylj2NzSypZt0X6b9egJe3f55IeLj69h1dqNVFaUUSZY8fq7TPrIHrRGcqVuQtVIz3Y1MzOzDvIYQ/cAMKJgewTwuxziltS0mrFceNyB/L5hPRVlApLntP5t7b48vaa5wxp029t/zEguPelgypSct/Iv71BRJo47aKxnu5qZmdkO8kjohkfEu20b6efdc4hbUosa1zFv8Wo+uu8etLQGlRVlDB9Wxu+ef4MvnTBhpxMcJleP4sePruKw/fZsL2tpDR5vWE9L2wNgzczMzFJ5JHQbJR3ZtiHpY8B7OcQtiTkLG7npsUZmzV/Kl06YwOo332O3ijII+KeTDgbg+ocadvoor7blS1b+5Z0O5ZtbWpFEmeC8W5/M9HeYmZnZwJFHQvdV4E5Jj0n6PfALYFYOcUticvUornvgBb50woT2JUgqK8r451MOZlsr7WvT7ewKXds4uoryMmrHdUz89hoxjPmL11DupM7MzMxSisj+saqShgGT0s2VEbE186BdqKuri/r6+kxjLGpcx6z5Szl76njmLV7N7Jm1XU6C6MqchY2UlyVX8955v+MqL7XjRvH0mmamH1LFtoDbzp/S6XdM//6jvLd1G7tXlrNh0xZ2qyjn3c0tvPt+C2Vl0BpAQEWZaIlInrCrHcvKyqC1lQ7njBhWxojKciJg+LBy3t+6jXFjdufUw/bxsipmZmZFIumpiKjr9risEzpJuwOXAvtHxIWSDgImRcQ9mQbuQh4JHcB1D6zk+ocbuGT6RC49aVL3J3Ti8ruX8Zulr1BRXsamzS1sK/if6sRDqnhoxVomVo2keu9kSOKaNzcBtCdvAl5tfn9Xf0qvlCUrtHSbEPYliSzmfsd0TMd0zKxjDpbf4ZgdY+49chi7VSQXMtouaEwet1eXF1d2VU8TuswWFi5wK8n6c8ek268AdwIlSejy0DYh4pLpE5m3eDVH14zp9RW6NhXlZaj1N9IAABV1SURBVJxx+D7cvnhNh/KHVqwFoGHtRl596z02t7R2SPigNBdBW9M6bG39oDJt8zgK53MU7qcP5+zqfsd0TMd0zKxjDpbf4ZgdY67fuJUP/hubvB87cQyllscYupqI+B7pr46ITSR5brcknSJppaQGSZd1sv9iSc9IelrS7yUdWtyq917b7dbZM2u59KRJzJ5Zy6z5S3e6TElX9h8zkjMO34f5i9dw4iFVXR63aev2yZyZmZnl4YrTD+n0yU95yyOh2yJpBGluK6mGHiwsLKkcuAE4FTgU+HwnCdv8iPjriDgC+B5wXVFr3gfLmpo7jJlrW2S4L89hvfj4Gl55632mH1LFwyvW7jSpMzMzs3xNOWB0v0jmIJ+E7lvA/wXGSbodeAj4Rg/OmwI0RMSqiNgC3AHMKDwgIt4u2BxJ+wXR0rn4+Jodbq9Oqxnb54kCt50/hW0B09Mxc8PKenRx08zMzDL25EsbuOmx/vH0pswTuoh4EPgscB7wc6AuIh7twan7AYUDx5rSsg4kfVlSI8kVuks6+yJJF0mql1S/du3a3v2AfuC286ewbuMWhpWJltbYpSt1lRVlCCgvAym59z2sTO2fOysrL2OHc3Yrd2JpZmb2nXtX9IukLo9JEQDHAx8nuYI2DPh1sb44Im4AbpA0E/gX4NxOjrkRuBGSWa7Fip2nUw/bB4CxIyvbJ0R0pwz4yKjhjKgs570t24o6E2fOwkbmLnoJoH1ZFAFvvddCa2sMmNlKjumYjumYWcUcLL/DMTvG7GyW6+MN60t+6zWPZUt+BEwkuToH8HdAY0R8uZvzjgG+HREnp9uXA0TE/+ri+DJgQ0R0/QgG8lu2JCvn3foky5reYreKcja3bGO3inK2tGzj3c0tVJaXscfwYby/dRujR1byoeEVXhfOzMxsAOtPy5ZMB/4q0sxR0lxgeQ/OWwIcJOlAkqVOzgJmFh4g6aCIeCHdPB14gUEuq3VuzMzMbODKI6FrAMYDL6fb49KynYqIFkmzgPuBcuCWiFgu6WqgPiIWALMkfZJkSZQNdHK71czMzGywyyOh2wN4XtKTJHehpwD1khYARMQZXZ0YEfcB921XdmXB569kUmMzMzOzASSPhO7K7g8xMzMzs77KI6FbGxHPFRZIOqGHS5eYmZmZWTfyWFj4l5K+ocQIST8EOp2pamZmZma9l0dCN5VkUsQikpmrrwLH5hDXzMzMbEjII6HbCrwHjACGAy9GRGsOcc3MzMyGhDwSuiUkCd1RwHHA5yXdmUNcMzMzsyEhj4Tugoi4MiK2RsRrETEDWJBD3JKYs7CRRY3rOpQtalzHnIWlf86bmZmZDU6ZJ3QRUS/p45LOB5A0Fvh91nFLZXL1KGbNX9qe1C1qXMes+UuZXL3TJ5KZmZmZ9Vnmy5ZI+hZQB0wCbgUqgXkM0okR02rGMntmLbPmL+XsqeOZt3g1s2fWMq1mbKmrZmZmZoNUHrdc/xY4A9gIEBGvkjw9YtCaVjOWs6eO5/qHGzh76ngnc2ZmZpapPBK6LRERJI/9QtLIHGKW1KLGdcxbvJpLpk9k3uLVO4ypMzMzMyumvBYW/gmwl6QLgd8BN+UQtyTaxszNnlnLpSdNar/96qTOzMzMspL5GLqI+L6kTwFvk4yjuzIiHsw6bqksa2ruMGaubUzdsqZm33o1MzOzTCi5Gzp01NXVRX19famrYWZmZtYtSU9FRF13x+Vxy9XMzMzMMuSEzszMzGyAyzWhk3RknvHMzMzMhoK8r9D9NOd4ZmZmZoNe3gmdco5nZmZmNujlndBd1dMDJZ0iaaWkBkmXdbL/UknPSVom6SFJ+xe3qmZmZmYDQ64JXUT8pifHSSoHbgBOBQ4FPi/p0O0OWwrURcRk4C7ge8Wsq5mZmdlA0V9nuU4BGiJiVURsAe4AZhQeEBGPRMSmdPMJoDrnOpqZmZn1C/01odsPWFOw3ZSWdeUC4Ldd7ZR0kaR6SfVr164tUhXNzMzM+ofMEzpJN0s6Yruybxfx+88G6oBruzomIm6MiLqIqKuqqipWaDMzM7N+IY8rdCcDcyWdU1B2RjfnvAKMK9iuTss6kPRJ4ArgjIjYvKsVNTMzMxuI8kjo3gA+AZwp6QZJFXS/fMkS4CBJB0qqBM4CFhQeIKkW+AlJMvdGBvU2MzMzGxDySOgUEc0R8RlgLfAoMGpnJ0RECzALuB94HvhlRCyXdLWktqt71wIfAu6U9LSkBV18nZmZmdmgVpFDjPZEKyK+Lekp4GvdnRQR9wH3bVd2ZcHnTxazkmZmZmYDVeZX6CLiW9tt/2dETM86rpmZmdlQ0V+XLTEzMzOzHnJCZ2ZmZjbAOaErojkLG1nUuK5D2aLGdcxZ2FiiGpmZmdlQkFlCJ+kZScu6emUVt5QmV49i1vyl7UndosZ1zJq/lMnVO53Ua2ZmZrZLspzl+un0/cvp+8/S9y9kGLOkptWMZfbMWmbNX8rZU8czb/FqZs+sZVrN2FJXzczMzAaxzBK6iHgZQNKnIqK2YNdlkv4IXJZV7FKaVjOWs6eO5/qHG7hk+kQnc2ZmZpa5XBYWlnRswca0nOKWxKLGdcxbvJpLpk9k3uLVO4ypMzMzMyu2PBYWvgC4RVLbQLK3gC/mEDd3bWPm2m6zHl0zpsO2mZmZWRYyT+gi4ing8LaELiKas45ZKsuamjskb21j6pY1NTuhMzMzs8woIrINIH0YuAbYNyJOlXQocExE3Jxp4C7U1dVFfX19KUKbmZmZ9YqkpyKirrvj8hjLdhtwP7Bvuv1n4Ks5xDUzMzMbEvJI6MZGxC+BVoCIaAG25RDXzMzMbEjII6HbKGkMEACSjgYG7Tg6MzMzs7zlMcv1UmABUCPpcaAKODOHuGZmZmZDQh4J3XLgeGASIGAlg3gdOjMzM7O85ZFY/SEiWiJieUQ8GxFbgT/kENfMzMxsSMjsCp2kjwD7ASMk1ZJcnQPYE9g9q7hmZmZmQ02Wt1xPBs4DqoHrCsrfAb7Z3cmSTgH+DSgHfhoR/7rd/k8APwAmA2dFxF3FqbaZmZnZwJJZQhcRc4G5kv5rRPyqN+dKKgduAD4FNAFLJC2IiOcKDltNkjB+vUhVNjMzMxuQ8nj0168knQ58FBheUH71Tk6bAjRExCoASXcAM4D2hC4iXkr3tWZQbTMzM7MBI/NJEZLmAH8H/CPJOLozgf27OW0/YE3BdlNa1tc6XCSpXlL92rVr+/o1ZmZmZv1SHrNcp0XEOcCGiLgKOAY4OIe47SLixoioi4i6qqqqPEObmZmZZS6PhO699H2TpH2BrcA+3ZzzCjCuYLs6LTMzMzOz7eSR0N0jaS/gWuCPwEvAz7s5ZwlwkKQDJVUCZ5E8bcLMzMzMtpPHpIj/kX78laR7gOERsdNnuUZEi6RZwP0ky5bcEhHLJV0N1EfEAklHAb8GRgOfkXRVRHw0w59iZmZm1i9lubDwZ3eyj4i4e2fnR8R9wH3blV1Z8HkJya1YMzMzsyEtyyt0n9nJvgB2mtANRHMWNjK5ehTTasa2ly1qXMeypmYuPr6mhDUzMzOzwSzLhYXPz+q7+6vJ1aOYNX8ps2fWMq1mLIsa17Vvm5mZmWUl8zF0kq7srLybhYUHpGk1Y5k9s5ZZ85dy9tTxzFu8uj25MzMzM8tKHrNcNxa8tgGnAgfkELckptWM5eyp47n+4QbOnjreyZyZmZllLo9Zrv+7cFvS90lmrw5KixrXMW/xai6ZPpF5i1dzdM0YJ3VmZmaWqTyu0G1vdwbp7NTCMXOXnjSp/fbrosZ1pa6amZmZDWJ5jKF7hmRWKyRrylUBg278HMCypuYOY+baxtQta2r2VTozMzPLjCKi+6N2JYC0f8FmC/B6RLRkGnQn6urqor6+vlThzczMzHpM0lMRUdfdcXncct0HeDMiXo6IV4ARkqbmENfMzMxsSMgjofsx8G7B9sa0zMzMzMyKII+ETlFwXzciWslh7J6ZmZnZUJFHQrdK0iWShqWvrwCrcohrZmZmNiTkkdBdDEwDXgGagKnARTnENTMzMxsS8lhY+A3grKzjmJmZmQ1VmSV0kn7IB+vP7SAiLskqtpmZmdlQkuUVOi/2ZmZmZpaDzBK6iJib1XebmZmZ2QfyePRXFfDfgUOB4W3lETE969hmZmZmQ0Ees1xvB54HDgSuAl4CluQQ18zMzGxIyCOhGxMRNwNbI2JhRHwR6NHVOUmnSFopqUHSZZ3s303SL9L9iyUdUNyq99x5tz7JTY81dii76bFGzrv1yRLVyMzMzIaKPBK6ren7a5JOl1QL7N3dSZLKgRuAU0lu135e0qHbHXYBsCEiJgL/B/hu8ardO8dOHMM1965oT+pueqyRa+5dwbETx5SqSmZmZjZE5PEIrv8paRTwT8APgT2Br/XgvClAQ0SsApB0BzADeK7gmBnAt9PPdwGzJXV41FheLjyuBoBr7l3Bg8tfZ8lLG/jm6Ye0l5uZmZllJY+Fhe9JPzYD/6UXp+4HrCnYbnvKRKfHRESLpGZgDLCu8CBJF5E+nWL8+PG9qELvXHhcDQ8uf50nX9rAlANGO5kzMzOzXGR+y1XSXEl7FWyPlnRL1nELRcSNEVEXEXVVVVWZxbnpsUaWpMnckpc27DCmzszMzCwLedxynRwRb7VtRMSGdBxdd14BxhVsV6dlnR3TJKkCGAWs38X69knbmLm226xt24Cv1JmZmVmm8pgUUSZpdNuGpL3pWSK5BDhI0oGSKkmeB7tgu2MWAOemnz8HPFyK8XMAjzes7zBm7sLjavjm6YfweENJ8kszMzMbQpR1/iPpHOCbwJ1p0ZnAdyLiZz049zTgB0A5cEtEfEfS1UB9RCyQNBz4GVALvAmc1TaJoit1dXVRX++nkpmZmVn/J+mpiKjr9rg8Lmily420rT33cEQ8t7Pjs+SEzszMzAaKfpXQ9SeS1gIvZxxmLNvNtLVd4vYsLrdncbk9i8vtWVxuz+IqRXvuHxHdzugccgldHiTV9ySbtp5xexaX27O43J7F5fYsLrdncfXn9sxjUoSZmZmZZcgJnZmZmdkA54QuGzeWugKDjNuzuNyexeX2LC63Z3G5PYur37anx9CZmZmZDXC+QmdmZmY2wDmhMzMzMxvgnNAVmaRTJK2U1CDpslLXp7+QNE7SI5Kek7Rc0lfS8r0lPSjphfR9dFouSden7bhM0pEF33VuevwLks4tKP+YpGfSc66XpPx/ab4klUtaKumedPtASYvTNvhF+tg8JO2Wbjek+w8o+I7L0/KVkk4uKB9SfVnSXpLukrRC0vOSjnH/7DtJX0v/rT8r6eeShrt/9o6kWyS9IenZgrLM+2RXMQa6Ltrz2vTf/DJJv5a0V8G+XvW9vvTvoooIv4r0InlEWSMwAagE/gQcWup69YcXsA9wZPp5D+DPwKHA94DL0vLLgO+mn08DfgsIOBpYnJbvDaxK30enn0en+55Mj1V67qml/t05tOulwHzgnnT7lySPwAOYA3wp/fwPwJz081nAL9LPh6b9dDfgwLT/lg/FvgzMBf5b+rkS2Mv9s89tuR/wIjCioF+e5/7Z63b8BHAk8GxBWeZ9sqsYA/3VRXueBFSkn79b0J697nu97d/FfvkKXXFNARoiYlVEbAHuAGaUuE79QkS8FhF/TD+/AzxP8kd/Bsl/SEnf/yb9PAP490g8AewlaR/gZODBiHgzIjYADwKnpPv2jIgnIvlX8+8F3zUoSaoGTgd+mm6L5BF7d6WHbN+ebe18F3BievwM4I6I2BwRLwINJP14SPVlSaNI/tjfDBARWyLiLdw/d0UFMEJSBbA78Brun70SEf+P5DnlhfLok13FGNA6a8+IeCAiWtLNJ4Dq9HOv+l4f//4WlRO64toPWFOw3ZSWWYH0cnMtsBj4cES8lu76C/Dh9HNXbbmz8qZOygezHwDfAFrT7THAWwV/nArboL3d0v3N6fG9befB6kBgLXCrklvYP5U0EvfPPomIV4DvA6tJErlm4CncP4shjz7ZVYzB7oskVyqh9+3Zl7+/ReWEznIl6UPAr4CvRsTbhfvS/5fodXR6QNKngTci4qlS12WQqCC5FfPjiKgFNpLcamrn/tlz6ZirGSSJ8r7ASOCUklZqEMqjTw6Vfi/pCqAFuL3UdekrJ3TF9QowrmC7Oi0zQNIwkmTu9oi4Oy1+Pb30T/r+RlreVVvurLy6k/LB6ljgDEkvkVzynw78G8ltlor0mMI2aG+3dP8oYD29b+fBqgloiojF6fZdJAme+2fffBJ4MSLWRsRW4G6SPuv+uevy6JNdxRiUJJ0HfBr4QprAQu/bcz29799F5YSuuJYAB6UzXSpJBj8uKHGd+oV0vMDNwPMRcV3BrgVA26yrc4H/KCg/J525dTTQnN4CuB84SdLo9CrAScD96b63JR2dxjqn4LsGnYi4PCKqI+IAkn72cER8AXgE+Fx62Pbt2dbOn0uPj7T8rHQW1oHAQSQDpYdUX46IvwBrJE1Ki04EnsP9s69WA0dL2j39vW3t6f656/Lok13FGHQknUIydOWMiNhUsKtXfS/tr73t38WVxUyLofwimWn0Z5JZMFeUuj795QV8nOSy/TLg6fR1Gsk4goeAF4DfAXunxwu4IW3HZ4C6gu/6IskA1Qbg/ILyOuDZ9JzZpE9CGewv4AQ+mOU6geSPTgNwJ7BbWj483W5I908oOP+KtM1WUjDzcqj1ZeAIoD7to78hmRHo/tn39rwKWJH+5p+RzBZ0/+xdG/6cZAziVpKryBfk0Se7ijHQX120ZwPJ+La2/y7N6Wvf60v/LubLj/4yMzMzG+B8y9XMzMxsgHNCZ2ZmZjbAOaEzMzMzG+Cc0JmZmZkNcE7ozMzMzAY4J3RmZl2QtJekf0g/7yvpru7OMTMrBS9bYmbWhfS5w/dExGElroqZ2U5VdH+ImdmQ9a9AjaSnSRZZ/auIOCx9VNDfkDyj9CCSB9FXAn8PbAZOi4g3JdWQLPZaBWwCLoyIFfn/DDMb7HzL1cysa5cBjRFxBPDP2+07DPgscBTwHWBTRNQCfyB5jBLAjcA/RsTHgK8DP8ql1mY25PgKnZlZ3zwSEe8A70hqBv4zLX8GmCzpQ8A04M7kUZlA8vgrM7Oic0JnZtY3mws+txZst5L8bS0D3kqv7pmZZcq3XM3MuvYOsEdfToyIt4EXJZ0JoMThxaycmVkbJ3RmZl2IiPXA45KeBa7tw1d8AbhA0p+A5cCMYtbPzKyNly0xMzMzG+B8hc7MzMxsgHNCZ2ZmZjbAOaEzMzMzG+Cc0JmZmZkNcE7ozMzMzAY4J3RmZmZmA5wTOjMzM7MB7v8DmFS585rlEp0AAAAASUVORK5CYII=\n", - "text/plain": [ - "<Figure size 720x576 with 3 Axes>" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fig = plt.figure(figsize=(10,8))\n", - "\n", - "x_position_axes = fig.add_subplot(311)\n", - "_ = x_position_axes.plot(expected_time, positions[:, 0, 0] - expected_x, '.', label='Expected')\n", - "_ = x_position_axes.set_ylabel('calculated x - expected x')\n", - "\n", - "y_position_axes = fig.add_subplot(312, sharex=x_position_axes)\n", - "_ = y_position_axes.plot(expected_time, positions[:, 0, 1] - expected_y, '.')\n", - "_ = y_position_axes.set_ylabel('calculated y - expected y')\n", - "\n", - "z_position_axes = fig.add_subplot(313, sharex=x_position_axes)\n", - "_ = z_position_axes.plot(expected_time, positions[:, 0, 2] - expected_z, 'x')\n", - "_ = z_position_axes.set_ylabel('calculated z - expected z')\n", - "_ = z_position_axes.set_xlabel('time')" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "<Figure size 720x576 with 3 Axes>" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fig = plt.figure(figsize=(10,8))\n", - "\n", - "xy_axes = fig.add_subplot(221)\n", - "_ = xy_axes.plot(expected_x,expected_y, 'x', label='Expected')\n", - "_ = xy_axes.plot(positions[:, 0, 0], positions[:, 0, 1], '.', label='Calculated')\n", - "_ = xy_axes.legend()\n", - "_ = xy_axes.set_ylabel('y')\n", - "\n", - "xz_axes = fig.add_subplot(223, sharex=xy_axes)\n", - "_ = xz_axes.plot(expected_x, expected_z, 'x')\n", - "_ = xz_axes.plot(positions[:, 0, 0], positions[:, 0, 2], '.')\n", - "_ = xz_axes.set_ylabel('z')\n", - "_ = xz_axes.set_xlabel('x')\n", - "\n", - "zy_axes = fig.add_subplot(224, sharey=xz_axes)\n", - "_ = zy_axes.plot(expected_y, expected_z, 'x')\n", - "_ = zy_axes.plot(positions[:, 0, 1], positions[:, 0, 2], '.')\n", - "_ = zy_axes.set_xlabel('y')" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.6.7" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/notebooks/ras.ipynb b/notebooks/ras.ipynb deleted file mode 100644 index e6e5c72..0000000 --- a/notebooks/ras.ipynb +++ /dev/null @@ -1,311 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "from fluegg.ras import RASProject" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": { - "scrolled": false - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Help on class RASProject in module fluegg.ras:\n", - "\n", - "class RASProject(builtins.object)\n", - " | RAS project.\n", - " | \n", - " | After use, call close() to keep the RAS process from lingering. The\n", - " | RASProject interface facilitates the use of the with-statement. See\n", - " | below for an example.\n", - " | \n", - " | ```\n", - " | with RASProject(project_file_path) as rp:\n", - " | hydrauilc_data = rp.hydraulic_model_data('Unsteady')\n", - " | ```\n", - " | \n", - " | \n", - " | Parameters\n", - " | ----------\n", - " | project_file_path : str\n", - " | Path to RAS project file\n", - " | \n", - " | Notes\n", - " | -----\n", - " | The values in the output of hydraulic_model_data are in metric units. If\n", - " | the quantities in the RAS project are in English units, the output will be\n", - " | converted.\n", - " | \n", - " | Methods defined here:\n", - " | \n", - " | __enter__(self)\n", - " | \n", - " | __exit__(self, *args)\n", - " | \n", - " | __init__(self, project_file_path)\n", - " | Initialize self. See help(type(self)) for accurate signature.\n", - " | \n", - " | close(self)\n", - " | Close the RAS controller\n", - " | \n", - " | current_plan_name(self)\n", - " | Returns the current plan name\n", - " | \n", - " | Returns\n", - " | -------\n", - " | str\n", - " | \n", - " | current_reach_name(self)\n", - " | Returns the current reach name\n", - " | \n", - " | Returns\n", - " | -------\n", - " | str\n", - " | \n", - " | current_river_name(self)\n", - " | Returns the current river name\n", - " | \n", - " | Returns\n", - " | -------\n", - " | str\n", - " | \n", - " | hydraulic_model_data(self, profile_name, temperature=22)\n", - " | Returns a pandas.DataFrame containing hydraulic data for the specified profile.\n", - " | \n", - " | If 'Unsteady' is specified for profile_name, the index of the DataFrame will be a pandas.MultiIndex\n", - " | \n", - " | Parameters\n", - " | ----------\n", - " | profile_name : str\n", - " | Name of profile. The name must be in the list of profiles or 'Unsteady'. If 'Unsteady', the\n", - " | RAS profile must have an associated unsteady file.\n", - " | temperature : float\n", - " | Water temperature\n", - " | \n", - " | Returns\n", - " | -------\n", - " | pandas.DataFrame\n", - " | \n", - " | plan_names(self)\n", - " | Returns a list of plan names in this RAS project.\n", - " | \n", - " | Returns\n", - " | -------\n", - " | list\n", - " | \n", - " | profile_names(self)\n", - " | Returns a list of profile names in this RAS project.\n", - " | \n", - " | Returns\n", - " | -------\n", - " | list\n", - " | \n", - " | project_units(self)\n", - " | Returns the RAS project units.\n", - " | \n", - " | Returns\n", - " | -------\n", - " | str\n", - " | \n", - " | reach_names(self)\n", - " | Returns a list of reach names in this RAS project.\n", - " | \n", - " | Returns\n", - " | -------\n", - " | list\n", - " | \n", - " | river_names(self)\n", - " | Returns a list of river names in this RAS project.\n", - " | \n", - " | Returns\n", - " | -------\n", - " | list\n", - " | \n", - " | set_current_plan(self, plan_name)\n", - " | Sets the current plan name for this RAS project.\n", - " | \n", - " | Parameters\n", - " | ----------\n", - " | plan_name : str\n", - " | Plan name. The plan name must be in the list of plan names of this project.\n", - " | \n", - " | ----------------------------------------------------------------------\n", - " | Data descriptors defined here:\n", - " | \n", - " | __dict__\n", - " | dictionary for instance variables (if defined)\n", - " | \n", - " | __weakref__\n", - " | list of weak references to the object (if defined)\n", - "\n" - ] - } - ], - "source": [ - "help(RASProject)" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Current plan name: case1\n", - "Profile names\n", - "----------\n", - " PF 1\n", - " PF 2\n" - ] - } - ], - "source": [ - "project_file_path = r'..\\test\\data\\ras\\steadyflume\\rectangular-flume.prj'\n", - "\n", - "with RASProject(project_file_path) as rp:\n", - " plan_name = rp.current_plan_name()\n", - " project_profile_names = rp.profile_names()\n", - "\n", - "print(\"Current plan name: {}\".format(plan_name))\n", - "print(\"Profile names\\n----------\")\n", - "for pn in project_profile_names:\n", - " print(\" {}\".format(pn))" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "<div>\n", - "<style scoped>\n", - " .dataframe tbody tr th:only-of-type {\n", - " vertical-align: middle;\n", - " }\n", - "\n", - " .dataframe tbody tr th {\n", - " vertical-align: top;\n", - " }\n", - "\n", - " .dataframe thead th {\n", - " text-align: right;\n", - " }\n", - "</style>\n", - "<table border=\"1\" class=\"dataframe\">\n", - " <thead>\n", - " <tr style=\"text-align: right;\">\n", - " <th></th>\n", - " <th>Depth_m</th>\n", - " <th>Q_cms</th>\n", - " <th>Vmag_mps</th>\n", - " <th>CumlDistance_km</th>\n", - " <th>Ustar_mps</th>\n", - " <th>Vvert_mps</th>\n", - " <th>Vlat_mps</th>\n", - " <th>Temp_C</th>\n", - " </tr>\n", - " </thead>\n", - " <tbody>\n", - " <tr>\n", - " <th>1</th>\n", - " <td>1.835397</td>\n", - " <td>24.999996</td>\n", - " <td>0.136210</td>\n", - " <td>5.0</td>\n", - " <td>0.013188</td>\n", - " <td>0</td>\n", - " <td>0</td>\n", - " <td>22</td>\n", - " </tr>\n", - " <tr>\n", - " <th>2</th>\n", - " <td>1.835564</td>\n", - " <td>24.999996</td>\n", - " <td>0.136198</td>\n", - " <td>15.0</td>\n", - " <td>0.013187</td>\n", - " <td>0</td>\n", - " <td>0</td>\n", - " <td>22</td>\n", - " </tr>\n", - " <tr>\n", - " <th>3</th>\n", - " <td>1.835687</td>\n", - " <td>24.999996</td>\n", - " <td>0.136189</td>\n", - " <td>20.0</td>\n", - " <td>0.013186</td>\n", - " <td>0</td>\n", - " <td>0</td>\n", - " <td>22</td>\n", - " </tr>\n", - " </tbody>\n", - "</table>\n", - "</div>" - ], - "text/plain": [ - " Depth_m Q_cms Vmag_mps CumlDistance_km Ustar_mps Vvert_mps \\\n", - "1 1.835397 24.999996 0.136210 5.0 0.013188 0 \n", - "2 1.835564 24.999996 0.136198 15.0 0.013187 0 \n", - "3 1.835687 24.999996 0.136189 20.0 0.013186 0 \n", - "\n", - " Vlat_mps Temp_C \n", - "1 0 22 \n", - "2 0 22 \n", - "3 0 22 " - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "profile_name = project_profile_names[0]\n", - "temperature = 22\n", - "\n", - "with RASProject(project_file_path) as rp:\n", - " hydraulic_data = rp.hydraulic_model_data(profile_name, temperature)\n", - "\n", - "hydraulic_data" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.6.6" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/notebooks/reverse longitudinal transporter.ipynb b/notebooks/reverse longitudinal transporter.ipynb deleted file mode 100644 index d39f80c..0000000 --- a/notebooks/reverse longitudinal transporter.ipynb +++ /dev/null @@ -1,326 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "<div>\n", - "<style scoped>\n", - " .dataframe tbody tr th:only-of-type {\n", - " vertical-align: middle;\n", - " }\n", - "\n", - " .dataframe tbody tr th {\n", - " vertical-align: top;\n", - " }\n", - "\n", - " .dataframe thead th {\n", - " text-align: right;\n", - " }\n", - "</style>\n", - "<table border=\"1\" class=\"dataframe\">\n", - " <thead>\n", - " <tr style=\"text-align: right;\">\n", - " <th></th>\n", - " <th>CumlDistance_km</th>\n", - " <th>Depth_m</th>\n", - " <th>Q_cms</th>\n", - " <th>Vmag_mps</th>\n", - " <th>Vvert_mps</th>\n", - " <th>Vlat_mps</th>\n", - " <th>Ustar_mps</th>\n", - " <th>Temp_C</th>\n", - " </tr>\n", - " <tr>\n", - " <th>CellNumber</th>\n", - " <th></th>\n", - " <th></th>\n", - " <th></th>\n", - " <th></th>\n", - " <th></th>\n", - " <th></th>\n", - " <th></th>\n", - " <th></th>\n", - " </tr>\n", - " </thead>\n", - " <tbody>\n", - " <tr>\n", - " <th>1</th>\n", - " <td>20</td>\n", - " <td>1</td>\n", - " <td>10</td>\n", - " <td>1</td>\n", - " <td>0</td>\n", - " <td>0</td>\n", - " <td>0.08</td>\n", - " <td>19</td>\n", - " </tr>\n", - " <tr>\n", - " <th>2</th>\n", - " <td>40</td>\n", - " <td>2</td>\n", - " <td>20</td>\n", - " <td>2</td>\n", - " <td>0</td>\n", - " <td>0</td>\n", - " <td>0.08</td>\n", - " <td>20</td>\n", - " </tr>\n", - " <tr>\n", - " <th>3</th>\n", - " <td>60</td>\n", - " <td>3</td>\n", - " <td>30</td>\n", - " <td>3</td>\n", - " <td>0</td>\n", - " <td>0</td>\n", - " <td>0.08</td>\n", - " <td>21</td>\n", - " </tr>\n", - " <tr>\n", - " <th>4</th>\n", - " <td>80</td>\n", - " <td>4</td>\n", - " <td>40</td>\n", - " <td>4</td>\n", - " <td>0</td>\n", - " <td>0</td>\n", - " <td>0.08</td>\n", - " <td>22</td>\n", - " </tr>\n", - " <tr>\n", - " <th>5</th>\n", - " <td>100</td>\n", - " <td>5</td>\n", - " <td>50</td>\n", - " <td>5</td>\n", - " <td>0</td>\n", - " <td>0</td>\n", - " <td>0.08</td>\n", - " <td>23</td>\n", - " </tr>\n", - " </tbody>\n", - "</table>\n", - "</div>" - ], - "text/plain": [ - " CumlDistance_km Depth_m Q_cms Vmag_mps Vvert_mps Vlat_mps \\\n", - "CellNumber \n", - "1 20 1 10 1 0 0 \n", - "2 40 2 20 2 0 0 \n", - "3 60 3 30 3 0 0 \n", - "4 80 4 40 4 0 0 \n", - "5 100 5 50 5 0 0 \n", - "\n", - " Ustar_mps Temp_C \n", - "CellNumber \n", - "1 0.08 19 \n", - "2 0.08 20 \n", - "3 0.08 21 \n", - "4 0.08 22 \n", - "5 0.08 23 " - ] - }, - "execution_count": 1, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "import os\n", - "\n", - "import pandas as pd\n", - "\n", - "\n", - "# show the hydraulic data contained in the CSV file\n", - "hydraulic_csv_path = os.path.join('..', 'test', 'data', 'multi-cell input.csv')\n", - "hydraulic_data = pd.read_csv(hydraulic_csv_path, index_col='CellNumber')\n", - "hydraulic_data" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "from fluegg.hydraulics import from_csv\n", - "\n", - "# initialize a hydraulic model as a series of hydraulic cells from the CSV\n", - "hydraulic_model = from_csv(hydraulic_csv_path)" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "from fluegg.asiancarpeggs import BigheadCarpEggs\n", - "from fluegg.simclock import ReverseSimulationClock\n", - "\n", - "# total_simulation_time = BigheadCarpEggs.get_hatching_time(hydraulic_data['Temp_C'].mean())\n", - "total_simulation_time = 1000 # seconds\n", - "time_step_size = 1 # seconds\n", - "\n", - "simulation_clock = ReverseSimulationClock(time_step_size, total_simulation_time)" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [], - "source": [ - "import numpy as np\n", - "\n", - "\n", - "first_cell_x_midpoint = 1000*hydraulic_data.loc[1, 'CumlDistance_km']/2\n", - "\n", - "depth = hydraulic_data.loc[1, 'Depth_m']\n", - "first_cell_z_midpoint = -depth/2\n", - "\n", - "area = hydraulic_data.loc[1, 'Q_cms']/hydraulic_data.loc[1, 'Vmag_mps']\n", - "width = area/depth\n", - "first_cell_y_midpoint = width/2\n", - "\n", - "initial_position = np.array([1500, first_cell_y_midpoint, first_cell_z_midpoint])\n", - "\n", - "number_of_eggs = 10\n", - "initial_position = np.tile(initial_position, (number_of_eggs, 1))\n", - "\n", - "carp_eggs = BigheadCarpEggs(initial_position, simulation_clock)" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [], - "source": [ - "from fluegg.transporter import ReverseLongitudinalTransporter\n", - "\n", - "transport_model = ReverseLongitudinalTransporter(simulation_clock, carp_eggs)\n", - "transport_model.set_hydraulic_model(hydraulic_model)" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [], - "source": [ - "from fluegg.simulation import Simulation\n", - "\n", - "fluegg_simulation = Simulation(carp_eggs, transport_model, simulation_clock)\n", - "fluegg_simulation.set_hydraulic_model(hydraulic_model)\n", - "\n", - "simulation_results = fluegg_simulation.run()" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "<Figure size 720x576 with 3 Axes>" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "%matplotlib inline\n", - "import matplotlib.pyplot as plt\n", - "\n", - "positions = simulation_results.results()\n", - "\n", - "time = simulation_clock.time_array()\n", - "\n", - "x = positions[:, :, 0]\n", - "y = positions[:, :, 1]\n", - "z = positions[:, :, 2]\n", - "\n", - "fig = plt.figure(figsize=(10,8))\n", - "\n", - "x_position_axes = fig.add_subplot(311)\n", - "_ = x_position_axes.plot(time, x, '.')\n", - "_ = x_position_axes.set_ylabel('x')\n", - "\n", - "y_position_axes = fig.add_subplot(312, sharex=x_position_axes)\n", - "_ = y_position_axes.plot(time, y, '.')\n", - "_ = y_position_axes.set_ylabel('y')\n", - "\n", - "z_position_axes = fig.add_subplot(313, sharex=x_position_axes)\n", - "_ = z_position_axes.plot(time, z, '.')\n", - "_ = z_position_axes.set_ylabel('z')\n", - "_ = z_position_axes.set_xlabel('time')" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": { - "scrolled": false - }, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "<Figure size 720x576 with 3 Axes>" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fig = plt.figure(figsize=(10,8))\n", - "\n", - "xy_axes = fig.add_subplot(221)\n", - "_ = xy_axes.plot(x, y, '.')\n", - "_ = xy_axes.set_ylabel('y')\n", - "\n", - "xz_axes = fig.add_subplot(223, sharex=xy_axes)\n", - "_ = xz_axes.plot(x, z, '.')\n", - "_ = xz_axes.set_ylabel('z')\n", - "_ = xz_axes.set_xlabel('x')\n", - "\n", - "zy_axes = fig.add_subplot(222, sharey=xy_axes)\n", - "_ = zy_axes.plot(z, y, '.')\n", - "_ = zy_axes.set_xlabel('z')" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.6.6" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/notebooks/reverse simulation clock.ipynb b/notebooks/reverse simulation clock.ipynb deleted file mode 100644 index 2d5d85a..0000000 --- a/notebooks/reverse simulation clock.ipynb +++ /dev/null @@ -1,7353 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "from fluegg.simclock import ReverseSimulationClock\n", - "\n", - "time_step_size = 5 # seconds\n", - "total_simulation_time = 10*3600 # hours to seconds\n", - "\n", - "simulation_clock = ReverseSimulationClock(time_step_size, total_simulation_time)" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "36000" - ] - }, - "execution_count": 2, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "simulation_clock.current_time()" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "current_time_index, curren_time = simulation_clock.increment_time()" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "35995" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "simulation_clock.current_time()" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "7198\n", - "7197\n", - "7196\n", - "7195\n", - "7194\n", - "7193\n", - "7192\n", - "7191\n", - "7190\n", - "7189\n", - "7188\n", - "7187\n", - "7186\n", - "7185\n", - "7184\n", - "7183\n", - "7182\n", - "7181\n", - "7180\n", - "7179\n", - "7178\n", - "7177\n", - "7176\n", - "7175\n", - "7174\n", - "7173\n", - "7172\n", - "7171\n", - "7170\n", - "7169\n", - "7168\n", - "7167\n", - "7166\n", - "7165\n", - "7164\n", - "7163\n", - "7162\n", - "7161\n", - "7160\n", - "7159\n", 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- "23\n", - "22\n", - "21\n", - "20\n", - "19\n", - "18\n", - "17\n", - "16\n", - "15\n", - "14\n", - "13\n", - "12\n", - "11\n", - "10\n", - "9\n", - "8\n", - "7\n", - "6\n", - "5\n", - "4\n", - "3\n", - "2\n", - "1\n", - "0\n" - ] - } - ], - "source": [ - "import numpy as np\n", - "\n", - "number_of_time_steps = simulation_clock.number_of_time_steps()\n", - "time_indices = np.zeros(number_of_time_steps)\n", - "times = np.zeros(number_of_time_steps)\n", - "\n", - "while True and (current_time_index > 0):\n", - " try:\n", - " current_time_index, current_time = simulation_clock.increment_time()\n", - " time_indices[current_time_index] = current_time_index\n", - " times[current_time_index] = current_time\n", - " print(current_time_index)\n", - " except IndexError:\n", - " break" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "<Figure size 432x288 with 1 Axes>" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "%matplotlib inline\n", - "import matplotlib.pyplot as plt\n", - "\n", - "_ = plt.plot(time_indices, times)\n", - "_ = plt.xlabel('Time index')\n", - "_ = plt.ylabel('Time')" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.6.6" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/notebooks/reverse simulation.ipynb b/notebooks/reverse simulation.ipynb deleted file mode 100644 index 77824fc..0000000 --- a/notebooks/reverse simulation.ipynb +++ /dev/null @@ -1,361 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "<div>\n", - "<style scoped>\n", - " .dataframe tbody tr th:only-of-type {\n", - " vertical-align: middle;\n", - " }\n", - "\n", - " .dataframe tbody tr th {\n", - " vertical-align: top;\n", - " }\n", - "\n", - " .dataframe thead th {\n", - " text-align: right;\n", - " }\n", - "</style>\n", - "<table border=\"1\" class=\"dataframe\">\n", - " <thead>\n", - " <tr style=\"text-align: right;\">\n", - " <th></th>\n", - " <th>CumlDistance_km</th>\n", - " <th>Depth_m</th>\n", - " <th>Q_cms</th>\n", - " <th>Vmag_mps</th>\n", - " <th>Vvert_mps</th>\n", - " <th>Vlat_mps</th>\n", - " <th>Ustar_mps</th>\n", - " <th>Temp_C</th>\n", - " </tr>\n", - " <tr>\n", - " <th>CellNumber</th>\n", - " <th></th>\n", - " <th></th>\n", - " <th></th>\n", - " <th></th>\n", - " <th></th>\n", - " <th></th>\n", - " <th></th>\n", - " <th></th>\n", - " </tr>\n", - " </thead>\n", - " <tbody>\n", - " <tr>\n", - " <th>1</th>\n", - " <td>20</td>\n", - " <td>1</td>\n", - " <td>10</td>\n", - " <td>1</td>\n", - " <td>0</td>\n", - " <td>0</td>\n", - " <td>0.08</td>\n", - " <td>19</td>\n", - " </tr>\n", - " <tr>\n", - " <th>2</th>\n", - " <td>40</td>\n", - " <td>2</td>\n", - " <td>20</td>\n", - " <td>2</td>\n", - " <td>0</td>\n", - " <td>0</td>\n", - " <td>0.08</td>\n", - " <td>20</td>\n", - " </tr>\n", - " <tr>\n", - " <th>3</th>\n", - " <td>60</td>\n", - " <td>3</td>\n", - " <td>30</td>\n", - " <td>3</td>\n", - " <td>0</td>\n", - " <td>0</td>\n", - " <td>0.08</td>\n", - " <td>21</td>\n", - " </tr>\n", - " <tr>\n", - " <th>4</th>\n", - " <td>80</td>\n", - " <td>4</td>\n", - " <td>40</td>\n", - " <td>4</td>\n", - " <td>0</td>\n", - " <td>0</td>\n", - " <td>0.08</td>\n", - " <td>22</td>\n", - " </tr>\n", - " <tr>\n", - " <th>5</th>\n", - " <td>100</td>\n", - " <td>5</td>\n", - " <td>50</td>\n", - " <td>5</td>\n", - " <td>0</td>\n", - " <td>0</td>\n", - " <td>0.08</td>\n", - " <td>23</td>\n", - " </tr>\n", - " </tbody>\n", - "</table>\n", - "</div>" - ], - "text/plain": [ - " CumlDistance_km Depth_m Q_cms Vmag_mps Vvert_mps Vlat_mps \\\n", - "CellNumber \n", - "1 20 1 10 1 0 0 \n", - "2 40 2 20 2 0 0 \n", - "3 60 3 30 3 0 0 \n", - "4 80 4 40 4 0 0 \n", - "5 100 5 50 5 0 0 \n", - "\n", - " Ustar_mps Temp_C \n", - "CellNumber \n", - "1 0.08 19 \n", - "2 0.08 20 \n", - "3 0.08 21 \n", - "4 0.08 22 \n", - "5 0.08 23 " - ] - }, - "execution_count": 1, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "import os\n", - "\n", - "import pandas as pd\n", - "\n", - "\n", - "# show the hydraulic data contained in the CSV file\n", - "hydraulic_csv_path = os.path.join('..', 'test', 'data', 'multi-cell input.csv')\n", - "hydraulic_data = pd.read_csv(hydraulic_csv_path, index_col='CellNumber')\n", - "hydraulic_data" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "from fluegg.hydraulics import from_csv\n", - "\n", - "# initialize a hydraulic model as a series of hydraulic cells from the CSV\n", - "hydraulic_model = from_csv(hydraulic_csv_path)" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "from fluegg.asiancarpeggs import BigheadCarpEggs\n", - "from fluegg.simclock import ReverseSimulationClock\n", - "\n", - "mean_temperature = hydraulic_data['Temp_C'].mean()\n", - "total_simulation_time = BigheadCarpEggs.hatching_time(mean_temperature)\n", - "# total_simulation_time = BigheadCarpEggs.get_gas_bladder_inflation_time(mean_temperature)\n", - "# total_simulation_time = 1000 # seconds\n", - "time_step_size = 10 # seconds\n", - "\n", - "simulation_clock = ReverseSimulationClock(time_step_size, total_simulation_time)" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [], - "source": [ - "import numpy as np\n", - "\n", - "\n", - "first_cell_x_midpoint = 1000*hydraulic_data.loc[1, 'CumlDistance_km']/2\n", - "\n", - "depth = hydraulic_data.loc[1, 'Depth_m']\n", - "first_cell_z_midpoint = -depth/2\n", - "\n", - "area = hydraulic_data.loc[1, 'Q_cms']/hydraulic_data.loc[1, 'Vmag_mps']\n", - "width = area/depth\n", - "first_cell_y_midpoint = width/2\n", - "\n", - "initial_position = np.array([500000, first_cell_y_midpoint, first_cell_z_midpoint])\n", - "\n", - "number_of_eggs = 10\n", - "initial_position = np.tile(initial_position, (number_of_eggs, 1))\n", - "\n", - "carp_eggs = BigheadCarpEggs(initial_position, simulation_clock)" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "False" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "carp_eggs.diameter() == 0" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [], - "source": [ - "from fluegg.transporter import init_transporter\n", - "\n", - "transport_model = init_transporter(simulation_clock, carp_eggs, 'parabolic', 'reverse')\n", - "transport_model.set_hydraulic_model(hydraulic_model)" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "147810.0" - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "from fluegg.simulation import Simulation\n", - "\n", - "fluegg_simulation = Simulation(carp_eggs, transport_model, simulation_clock)\n", - "fluegg_simulation.set_hydraulic_model(hydraulic_model)\n", - "\n", - "simulation_results = fluegg_simulation.run()\n", - "\n", - "simulation_clock.current_time()" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "<Figure size 720x576 with 3 Axes>" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "%matplotlib inline\n", - "import matplotlib.pyplot as plt\n", - "\n", - "positions = simulation_results.results()\n", - "\n", - "time = simulation_clock.time_array()\n", - "\n", - "x = positions[:, :, 0]\n", - "y = positions[:, :, 1]\n", - "z = positions[:, :, 2]\n", - "\n", - "fig = plt.figure(figsize=(10,8))\n", - "\n", - "x_position_axes = fig.add_subplot(311)\n", - "_ = x_position_axes.plot(time, x, '.')\n", - "_ = x_position_axes.set_ylabel('x')\n", - "\n", - "y_position_axes = fig.add_subplot(312, sharex=x_position_axes)\n", - "_ = y_position_axes.plot(time, y, '.')\n", - "_ = y_position_axes.set_ylabel('y')\n", - "\n", - "z_position_axes = fig.add_subplot(313, sharex=x_position_axes)\n", - "_ = z_position_axes.plot(time, z, '.')\n", - "_ = z_position_axes.set_ylabel('z')\n", - "_ = z_position_axes.set_xlabel('time')" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": { - "scrolled": false - }, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "<Figure size 720x576 with 3 Axes>" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fig = plt.figure(figsize=(10,8))\n", - "\n", - "xy_axes = fig.add_subplot(221)\n", - "_ = xy_axes.plot(x, y, '.')\n", - "_ = xy_axes.set_ylabel('y')\n", - "\n", - "xz_axes = fig.add_subplot(223, sharex=xy_axes)\n", - "_ = xz_axes.plot(x, z, '.')\n", - "_ = xz_axes.set_ylabel('z')\n", - "_ = xz_axes.set_xlabel('x')\n", - "\n", - "yz_axes = fig.add_subplot(224, sharey=xz_axes)\n", - "_ = yz_axes.plot(y, z, '.')\n", - "_ = yz_axes.set_xlabel('y')" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.6.6" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/notebooks/simulation clock.ipynb b/notebooks/simulation clock.ipynb deleted file mode 100644 index ea0dee5..0000000 --- a/notebooks/simulation clock.ipynb +++ /dev/null @@ -1,122 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "from fluegg.simclock import SimulationClock\n", - "\n", - "time_step_size = 5 # seconds\n", - "total_simulation_time = 10*3600 # hours to seconds\n", - "\n", - "simulation_clock = SimulationClock(time_step_size, total_simulation_time)" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "0" - ] - }, - "execution_count": 2, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "simulation_clock.current_time()" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "5" - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "simulation_clock.set_time_index(1)\n", - "simulation_clock.current_time()" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [], - "source": [ - "import numpy as np\n", - "\n", - "number_of_time_steps = simulation_clock.number_of_time_steps()\n", - "time_indices = np.zeros(number_of_time_steps)\n", - "times = np.zeros(number_of_time_steps)\n", - "\n", - "for current_time_index in simulation_clock.iter_time_index():\n", - " time_indices[current_time_index] = current_time_index\n", - " times[current_time_index] = simulation_clock.current_time()" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "<Figure size 432x288 with 1 Axes>" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "%matplotlib inline\n", - "import matplotlib.pyplot as plt\n", - "\n", - "_ = plt.plot(time_indices, times)\n", - "_ = plt.xlabel('Time index')\n", - "_ = plt.ylabel('Time')" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.6.6" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/notebooks/simulation.ipynb b/notebooks/simulation.ipynb deleted file mode 100644 index cc03fab..0000000 --- a/notebooks/simulation.ipynb +++ /dev/null @@ -1,361 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "<div>\n", - "<style scoped>\n", - " .dataframe tbody tr th:only-of-type {\n", - " vertical-align: middle;\n", - " }\n", - "\n", - " .dataframe tbody tr th {\n", - " vertical-align: top;\n", - " }\n", - "\n", - " .dataframe thead th {\n", - " text-align: right;\n", - " }\n", - "</style>\n", - "<table border=\"1\" class=\"dataframe\">\n", - " <thead>\n", - " <tr style=\"text-align: right;\">\n", - " <th></th>\n", - " <th>CumlDistance_km</th>\n", - " <th>Depth_m</th>\n", - " <th>Q_cms</th>\n", - " <th>Vmag_mps</th>\n", - " <th>Vvert_mps</th>\n", - " <th>Vlat_mps</th>\n", - " <th>Ustar_mps</th>\n", - " <th>Temp_C</th>\n", - " </tr>\n", - " <tr>\n", - " <th>CellNumber</th>\n", - " <th></th>\n", - " <th></th>\n", - " <th></th>\n", - " <th></th>\n", - " <th></th>\n", - " <th></th>\n", - " <th></th>\n", - " <th></th>\n", - " </tr>\n", - " </thead>\n", - " <tbody>\n", - " <tr>\n", - " <th>1</th>\n", - " <td>20</td>\n", - " <td>1</td>\n", - " <td>10</td>\n", - " <td>1</td>\n", - " <td>0</td>\n", - " <td>0</td>\n", - " <td>0.08</td>\n", - " <td>19</td>\n", - " </tr>\n", - " <tr>\n", - " <th>2</th>\n", - " <td>40</td>\n", - " <td>2</td>\n", - " <td>20</td>\n", - " <td>2</td>\n", - " <td>0</td>\n", - " <td>0</td>\n", - " <td>0.08</td>\n", - " <td>20</td>\n", - " </tr>\n", - " <tr>\n", - " <th>3</th>\n", - " <td>60</td>\n", - " <td>3</td>\n", - " <td>30</td>\n", - " <td>3</td>\n", - " <td>0</td>\n", - " <td>0</td>\n", - " <td>0.08</td>\n", - " <td>21</td>\n", - " </tr>\n", - " <tr>\n", - " <th>4</th>\n", - " <td>80</td>\n", - " <td>4</td>\n", - " <td>40</td>\n", - " <td>4</td>\n", - " <td>0</td>\n", - " <td>0</td>\n", - " <td>0.08</td>\n", - " <td>22</td>\n", - " </tr>\n", - " <tr>\n", - " <th>5</th>\n", - " <td>100</td>\n", - " <td>5</td>\n", - " <td>50</td>\n", - " <td>5</td>\n", - " <td>0</td>\n", - " <td>0</td>\n", - " <td>0.08</td>\n", - " <td>23</td>\n", - " </tr>\n", - " </tbody>\n", - "</table>\n", - "</div>" - ], - "text/plain": [ - " CumlDistance_km Depth_m Q_cms Vmag_mps Vvert_mps Vlat_mps \\\n", - "CellNumber \n", - "1 20 1 10 1 0 0 \n", - "2 40 2 20 2 0 0 \n", - "3 60 3 30 3 0 0 \n", - "4 80 4 40 4 0 0 \n", - "5 100 5 50 5 0 0 \n", - "\n", - " Ustar_mps Temp_C \n", - "CellNumber \n", - "1 0.08 19 \n", - "2 0.08 20 \n", - "3 0.08 21 \n", - "4 0.08 22 \n", - "5 0.08 23 " - ] - }, - "execution_count": 1, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "import os\n", - "\n", - "import pandas as pd\n", - "\n", - "\n", - "# show the hydraulic data contained in the CSV file\n", - "hydraulic_csv_path = os.path.join('..', 'test', 'data', 'multi-cell input.csv')\n", - "hydraulic_data = pd.read_csv(hydraulic_csv_path, index_col='CellNumber')\n", - "hydraulic_data" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "from fluegg.hydraulics import from_csv\n", - "\n", - "# initialize a hydraulic model as a series of hydraulic cells from the CSV\n", - "hydraulic_model = from_csv(hydraulic_csv_path)" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "from fluegg.asiancarpeggs import BigheadCarpEggs\n", - "from fluegg.simclock import SimulationClock\n", - "\n", - "mean_temperature = hydraulic_data['Temp_C'].mean()\n", - "total_simulation_time = BigheadCarpEggs.hatching_time(mean_temperature)\n", - "# total_simulation_time = BigheadCarpEggs.gas_bladder_inflation_time(mean_temperature)\n", - "# total_simulation_time = 1000 # seconds\n", - "time_step_size = 10 # seconds\n", - "\n", - "simulation_clock = SimulationClock(time_step_size, total_simulation_time)" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [], - "source": [ - "import numpy as np\n", - "\n", - "\n", - "first_cell_x_midpoint = 1000*hydraulic_data.loc[1, 'CumlDistance_km']/2\n", - "\n", - "depth = hydraulic_data.loc[1, 'Depth_m']\n", - "first_cell_z_midpoint = -depth/2\n", - "\n", - "area = hydraulic_data.loc[1, 'Q_cms']/hydraulic_data.loc[1, 'Vmag_mps']\n", - "width = area/depth\n", - "first_cell_y_midpoint = width/2\n", - "\n", - "initial_position = np.array([10, first_cell_y_midpoint, first_cell_z_midpoint])\n", - "\n", - "number_of_eggs = 10\n", - "initial_position = np.tile(initial_position, (number_of_eggs, 1))\n", - "\n", - "carp_eggs = BigheadCarpEggs(initial_position, simulation_clock)" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "False" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "carp_eggs.diameter() == 0" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [], - "source": [ - "from fluegg.transporter import init_transporter\n", - "\n", - "transport_model = init_transporter(simulation_clock, carp_eggs, 'parabolic')\n", - "transport_model.set_hydraulic_model(hydraulic_model)" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "147810.0" - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "from fluegg.simulation import Simulation\n", - "\n", - "fluegg_simulation = Simulation(carp_eggs, transport_model, simulation_clock)\n", - "fluegg_simulation.set_hydraulic_model(hydraulic_model)\n", - "\n", - "simulation_results = fluegg_simulation.run()\n", - "\n", - "simulation_clock.current_time()" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "<Figure size 720x576 with 3 Axes>" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "%matplotlib inline\n", - "import matplotlib.pyplot as plt\n", - "\n", - "positions = simulation_results.results()\n", - "\n", - "time = simulation_clock.time_array()\n", - "\n", - "x = positions[:, :, 0]\n", - "y = positions[:, :, 1]\n", - "z = positions[:, :, 2]\n", - "\n", - "fig = plt.figure(figsize=(10,8))\n", - "\n", - "x_position_axes = fig.add_subplot(311)\n", - "_ = x_position_axes.plot(time, x, '.')\n", - "_ = x_position_axes.set_ylabel('x')\n", - "\n", - "y_position_axes = fig.add_subplot(312, sharex=x_position_axes)\n", - "_ = y_position_axes.plot(time, y, '.')\n", - "_ = y_position_axes.set_ylabel('y')\n", - "\n", - "z_position_axes = fig.add_subplot(313, sharex=x_position_axes)\n", - "_ = z_position_axes.plot(time, z, '.')\n", - "_ = z_position_axes.set_ylabel('z')\n", - "_ = z_position_axes.set_xlabel('time')" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": { - "scrolled": false - }, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "<Figure size 720x576 with 3 Axes>" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fig = plt.figure(figsize=(10,8))\n", - "\n", - "xy_axes = fig.add_subplot(221)\n", - "_ = xy_axes.plot(x, y, '.')\n", - "_ = xy_axes.set_ylabel('y')\n", - "\n", - "xz_axes = fig.add_subplot(223, sharex=xy_axes)\n", - "_ = xz_axes.plot(x, z, '.')\n", - "_ = xz_axes.set_ylabel('z')\n", - "_ = xz_axes.set_xlabel('x')\n", - "\n", - "yz_axes = fig.add_subplot(224, sharey=xz_axes)\n", - "_ = yz_axes.plot(y, z, '.')\n", - "_ = yz_axes.set_xlabel('y')" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.6.6" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/notebooks/unsteady hydraulic cell.ipynb b/notebooks/unsteady hydraulic cell.ipynb deleted file mode 100644 index ec008ec..0000000 --- a/notebooks/unsteady hydraulic cell.ipynb +++ /dev/null @@ -1,465 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "<div>\n", - "<style scoped>\n", - " .dataframe tbody tr th:only-of-type {\n", - " vertical-align: middle;\n", - " }\n", - "\n", - " .dataframe tbody tr th {\n", - " vertical-align: top;\n", - " }\n", - "\n", - " .dataframe thead th {\n", - " text-align: right;\n", - " }\n", - "</style>\n", - "<table border=\"1\" class=\"dataframe\">\n", - " <thead>\n", - " <tr style=\"text-align: right;\">\n", - " <th></th>\n", - " <th></th>\n", - " <th>Depth_m</th>\n", - " <th>Q_cms</th>\n", - " <th>Vmag_mps</th>\n", - " <th>CumlDistance_km</th>\n", - " <th>Ustar_mps</th>\n", - " <th>Vvert_mps</th>\n", - " <th>Vlat_mps</th>\n", - " <th>Temp_C</th>\n", - " </tr>\n", - " </thead>\n", - " <tbody>\n", - " <tr>\n", - " <th rowspan=\"3\" valign=\"top\">2017-01-01 00:00:00</th>\n", - " <th>1</th>\n", - " <td>0.055352</td>\n", - " <td>0.001416</td>\n", - " <td>0.119885</td>\n", - " <td>7.62</td>\n", - " <td>0.009489</td>\n", - " <td>0.0</td>\n", - " <td>0.0</td>\n", - " <td>22.0</td>\n", - " </tr>\n", - " <tr>\n", - " <th>2</th>\n", - " <td>0.055076</td>\n", - " <td>0.001416</td>\n", - " <td>0.120487</td>\n", - " <td>22.86</td>\n", - " <td>0.009542</td>\n", - " <td>0.0</td>\n", - " <td>0.0</td>\n", - " <td>22.0</td>\n", - " </tr>\n", - " <tr>\n", - " <th>3</th>\n", - " <td>0.055350</td>\n", - " <td>0.001416</td>\n", - " <td>0.119890</td>\n", - " <td>30.48</td>\n", - " <td>0.009489</td>\n", - " <td>0.0</td>\n", - " <td>0.0</td>\n", - " <td>22.0</td>\n", - " </tr>\n", - " <tr>\n", - " <th rowspan=\"3\" valign=\"top\">2017-01-01 01:00:00</th>\n", - " <th>1</th>\n", - " <td>0.055322</td>\n", - " <td>0.001416</td>\n", - " <td>0.119951</td>\n", - " <td>7.62</td>\n", - " <td>0.009494</td>\n", - " <td>0.0</td>\n", - " <td>0.0</td>\n", - " <td>22.0</td>\n", - " </tr>\n", - " <tr>\n", - " <th>2</th>\n", - " <td>0.055108</td>\n", - " <td>0.001416</td>\n", - " <td>0.120416</td>\n", - " <td>22.86</td>\n", - " <td>0.009535</td>\n", - " <td>0.0</td>\n", - " <td>0.0</td>\n", - " <td>22.0</td>\n", - " </tr>\n", - " <tr>\n", - " <th>3</th>\n", - " <td>0.055320</td>\n", - " <td>0.001416</td>\n", - " <td>0.119956</td>\n", - " <td>30.48</td>\n", - " <td>0.009495</td>\n", - " <td>0.0</td>\n", - " <td>0.0</td>\n", - " <td>22.0</td>\n", - " </tr>\n", - " <tr>\n", - " <th rowspan=\"3\" valign=\"top\">2017-01-01 02:00:00</th>\n", - " <th>1</th>\n", - " <td>0.055322</td>\n", - " <td>0.001416</td>\n", - " <td>0.119951</td>\n", - " <td>7.62</td>\n", - " <td>0.009494</td>\n", - " <td>0.0</td>\n", - " <td>0.0</td>\n", - " <td>22.0</td>\n", - " </tr>\n", - " <tr>\n", - " <th>2</th>\n", - " <td>0.055108</td>\n", - " 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Vvert_mps Vlat_mps Temp_C \n", - "2017-01-01 00:00:00 1 0.009489 0.0 0.0 22.0 \n", - " 2 0.009542 0.0 0.0 22.0 \n", - " 3 0.009489 0.0 0.0 22.0 \n", - "2017-01-01 01:00:00 1 0.009494 0.0 0.0 22.0 \n", - " 2 0.009535 0.0 0.0 22.0 \n", - " 3 0.009495 0.0 0.0 22.0 \n", - "2017-01-01 02:00:00 1 0.009494 0.0 0.0 22.0 \n", - " 2 0.009535 0.0 0.0 22.0 \n", - " 3 0.009495 0.0 0.0 22.0 " - ] - }, - "execution_count": 1, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "import numpy as np\n", - "from fluegg.ras import RASProject\n", - "\n", - "project_file_path = r'..\\test\\data\\ras\\unsteadyflume\\HEC-RASFlumeCase.prj'\n", - "\n", - "with RASProject(project_file_path) as rp:\n", - " data_frame = rp.hydraulic_model_data('Unsteady')\n", - "\n", - "data_frame.head(9)" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": { - "scrolled": true - }, - "outputs": [ - { - "data": { - "text/html": [ - "<div>\n", - "<style scoped>\n", - " .dataframe tbody tr th:only-of-type {\n", - " vertical-align: middle;\n", - " }\n", - "\n", - " .dataframe tbody tr th {\n", - " vertical-align: top;\n", - " }\n", - "\n", - " .dataframe thead th {\n", - " text-align: right;\n", - " }\n", - "</style>\n", - "<table border=\"1\" class=\"dataframe\">\n", - " <thead>\n", - " <tr style=\"text-align: right;\">\n", - " <th></th>\n", - " <th>Depth_m</th>\n", - " <th>Q_cms</th>\n", - " <th>Vmag_mps</th>\n", - " <th>CumlDistance_km</th>\n", - " <th>Ustar_mps</th>\n", - " <th>Vvert_mps</th>\n", - " <th>Vlat_mps</th>\n", - " <th>Temp_C</th>\n", - " </tr>\n", - " </thead>\n", - " <tbody>\n", - " <tr>\n", - " <th>2017-01-01 00:00:00</th>\n", - " <td>0.055352</td>\n", - " <td>0.001416</td>\n", - " <td>0.119885</td>\n", - " <td>7.62</td>\n", - " <td>0.009489</td>\n", - " <td>0.0</td>\n", - " <td>0.0</td>\n", - " <td>22.0</td>\n", - " </tr>\n", - " <tr>\n", - " <th>2017-01-01 01:00:00</th>\n", - " <td>0.055322</td>\n", - " <td>0.001416</td>\n", - " <td>0.119951</td>\n", - " <td>7.62</td>\n", - " <td>0.009494</td>\n", - " <td>0.0</td>\n", - " <td>0.0</td>\n", - " <td>22.0</td>\n", - " </tr>\n", - " <tr>\n", - " <th>2017-01-01 02:00:00</th>\n", - " <td>0.055322</td>\n", - " <td>0.001416</td>\n", - " <td>0.119951</td>\n", - " <td>7.62</td>\n", - " <td>0.009494</td>\n", - " <td>0.0</td>\n", - " <td>0.0</td>\n", - " <td>22.0</td>\n", - " </tr>\n", - " <tr>\n", - " <th>2017-01-01 03:00:00</th>\n", - " <td>0.081595</td>\n", - " <td>0.002447</td>\n", - " <td>0.140534</td>\n", - " <td>7.62</td>\n", - " <td>0.010691</td>\n", - " <td>0.0</td>\n", - " <td>0.0</td>\n", - " <td>22.0</td>\n", - " </tr>\n", - " <tr>\n", - " <th>2017-01-01 04:00:00</th>\n", - " <td>0.073091</td>\n", - " <td>0.002101</td>\n", - " <td>0.134733</td>\n", - " <td>7.62</td>\n", - " <td>0.010359</td>\n", - " <td>0.0</td>\n", - " <td>0.0</td>\n", - " <td>22.0</td>\n", - " </tr>\n", - " </tbody>\n", - "</table>\n", - "</div>" - ], - "text/plain": [ - " Depth_m Q_cms Vmag_mps CumlDistance_km Ustar_mps \\\n", - "2017-01-01 00:00:00 0.055352 0.001416 0.119885 7.62 0.009489 \n", - "2017-01-01 01:00:00 0.055322 0.001416 0.119951 7.62 0.009494 \n", - "2017-01-01 02:00:00 0.055322 0.001416 0.119951 7.62 0.009494 \n", - "2017-01-01 03:00:00 0.081595 0.002447 0.140534 7.62 0.010691 \n", - "2017-01-01 04:00:00 0.073091 0.002101 0.134733 7.62 0.010359 \n", - "\n", - " Vvert_mps Vlat_mps Temp_C \n", - "2017-01-01 00:00:00 0.0 0.0 22.0 \n", - "2017-01-01 01:00:00 0.0 0.0 22.0 \n", - "2017-01-01 02:00:00 0.0 0.0 22.0 \n", - "2017-01-01 03:00:00 0.0 0.0 22.0 \n", - "2017-01-01 04:00:00 0.0 0.0 22.0 " - ] - }, - "execution_count": 2, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "grouped_by_cell = data_frame.groupby(axis=0, level=1)\n", - "cell_1_data = grouped_by_cell.get_group(1)\n", - "cell_1_data.index = cell_1_data.index.droplevel(1)\n", - "cell_1_data.head()" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "cell_length = cell_1_data.loc[cell_1_data.index[0], 'CumlDistance_km']" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [], - "source": [ - "total_ras_time = cell_1_data.index[-1] - cell_1_data.index[0]" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [], - "source": [ - "from fluegg.simclock import SimulationClock\n", - "sim_clock = SimulationClock(2*3600, total_ras_time.total_seconds())" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [], - "source": [ - "class SimpleSim:\n", - " \n", - " def __init__(self, sim_clock):\n", - " self._time_step_function_calls = {}\n", - " self._sim_clock = sim_clock\n", - " \n", - " def add_time_step_function_call(self, fun, args):\n", - " self._time_step_function_calls[fun] = args\n", - " \n", - " def call_time_step_functions(self):\n", - " for fun, args in self._time_step_function_calls.items():\n", - " fun(*args)\n", - " \n", - " def run(self, hydraulic_cell):\n", - " \n", - " discharge = np.zeros(self._sim_clock.number_of_time_steps())\n", - " \n", - " for index in self._sim_clock.iter_time_index():\n", - " self.call_time_step_functions()\n", - " discharge[index] = hydraulic_cell.discharge()\n", - " \n", - " return self._sim_clock.time_array(), discharge\n", - " \n", - "simple_sim = SimpleSim(sim_clock)" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [], - "source": [ - "from fluegg.hydraulics import UnsteadyHydraulicCell\n", - "hydraulic_cell = UnsteadyHydraulicCell(cell_length, cell_1_data, cell_1_data.index[0], sim_clock, simple_sim)" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [], - "source": [ - "time_array, cell_discharge = simple_sim.run(hydraulic_cell)" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "<Figure size 432x288 with 1 Axes>" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "%matplotlib inline\n", - "import matplotlib.pyplot as plt\n", - "_ = plt.plot(time_array, cell_discharge)\n", - "_ = plt.xlabel('Time in seconds')\n", - "_ = plt.ylabel('Discharge in CMS')" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "<Figure size 432x288 with 1 Axes>" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "results_datetime = np.datetime64(cell_1_data.index[0]) + time_array*np.timedelta64(1, 's')\n", - "\n", - "_ = plt.plot(cell_1_data['Q_cms'].index.values, cell_1_data['Q_cms'].values, label='From RAS')\n", - "_ = plt.plot(results_datetime, cell_discharge, '.', label='From simulation')\n", - "_ = plt.legend()\n", - "_ = plt.xlabel('Time')\n", - "_ = plt.ylabel('Discharge in CMS')" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.6.6" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/notebooks/unsteady simulation.ipynb b/notebooks/unsteady simulation.ipynb deleted file mode 100644 index b9bd1a9..0000000 --- a/notebooks/unsteady simulation.ipynb +++ /dev/null @@ -1,599 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": { - "scrolled": true - }, - "outputs": [ - { - "data": { - "text/html": [ - "<div>\n", - "<style scoped>\n", - " .dataframe tbody tr th:only-of-type {\n", - " vertical-align: middle;\n", - " }\n", - "\n", - " .dataframe tbody tr th {\n", - " vertical-align: top;\n", - " }\n", - "\n", - " .dataframe thead th {\n", - " text-align: right;\n", - " }\n", - "</style>\n", - "<table border=\"1\" class=\"dataframe\">\n", - " <thead>\n", - " <tr style=\"text-align: right;\">\n", - " <th></th>\n", - " <th></th>\n", - " <th>Depth_m</th>\n", - " <th>Q_cms</th>\n", - " <th>Vmag_mps</th>\n", - " <th>CumlDistance_km</th>\n", - " <th>Ustar_mps</th>\n", - " <th>Vvert_mps</th>\n", - " <th>Vlat_mps</th>\n", - " <th>Temp_C</th>\n", - " </tr>\n", - " </thead>\n", - " <tbody>\n", - " <tr>\n", - " <th rowspan=\"3\" valign=\"top\">2017-01-01 00:00:00</th>\n", - " <th>1</th>\n", - " <td>0.055352</td>\n", - " <td>0.001416</td>\n", - " <td>0.119885</td>\n", - " <td>7.62</td>\n", - " <td>0.009489</td>\n", - " <td>0.0</td>\n", - " <td>0.0</td>\n", - " <td>22.0</td>\n", - " </tr>\n", - " <tr>\n", - " <th>2</th>\n", - " <td>0.055076</td>\n", - " <td>0.001416</td>\n", - " <td>0.120487</td>\n", - " <td>22.86</td>\n", - " <td>0.009542</td>\n", - " <td>0.0</td>\n", - " <td>0.0</td>\n", - " <td>22.0</td>\n", - " </tr>\n", - " <tr>\n", - " <th>3</th>\n", - " <td>0.055350</td>\n", - " <td>0.001416</td>\n", - " <td>0.119890</td>\n", - " <td>30.48</td>\n", - " <td>0.009489</td>\n", - " <td>0.0</td>\n", - " <td>0.0</td>\n", - " <td>22.0</td>\n", - " </tr>\n", - " <tr>\n", - " <th rowspan=\"3\" valign=\"top\">2017-01-01 01:00:00</th>\n", - " <th>1</th>\n", - " <td>0.055322</td>\n", - " <td>0.001416</td>\n", - " <td>0.119951</td>\n", - " <td>7.62</td>\n", - " <td>0.009494</td>\n", - " <td>0.0</td>\n", - " <td>0.0</td>\n", - " <td>22.0</td>\n", - " </tr>\n", - " <tr>\n", - " <th>2</th>\n", - " <td>0.055108</td>\n", - " <td>0.001416</td>\n", - " <td>0.120416</td>\n", - " <td>22.86</td>\n", - " <td>0.009535</td>\n", - " <td>0.0</td>\n", - " <td>0.0</td>\n", - " <td>22.0</td>\n", - " </tr>\n", - " <tr>\n", - " <th>3</th>\n", - " <td>0.055320</td>\n", - " <td>0.001416</td>\n", - " <td>0.119956</td>\n", - " <td>30.48</td>\n", - " <td>0.009495</td>\n", - " <td>0.0</td>\n", - " <td>0.0</td>\n", - " <td>22.0</td>\n", - " </tr>\n", - " <tr>\n", - " <th rowspan=\"3\" valign=\"top\">2017-01-01 02:00:00</th>\n", - " <th>1</th>\n", - " <td>0.055322</td>\n", - " <td>0.001416</td>\n", - " <td>0.119951</td>\n", - " <td>7.62</td>\n", - " <td>0.009494</td>\n", - " <td>0.0</td>\n", - " <td>0.0</td>\n", - " <td>22.0</td>\n", - " </tr>\n", - " <tr>\n", - " <th>2</th>\n", - " <td>0.055108</td>\n", - " <td>0.001416</td>\n", - " <td>0.120416</td>\n", - " <td>22.86</td>\n", - " <td>0.009535</td>\n", - " <td>0.0</td>\n", - " <td>0.0</td>\n", - " <td>22.0</td>\n", - " </tr>\n", - " <tr>\n", - " <th>3</th>\n", - " <td>0.055320</td>\n", - " <td>0.001416</td>\n", - " <td>0.119956</td>\n", - " <td>30.48</td>\n", - " <td>0.009495</td>\n", - " <td>0.0</td>\n", - " <td>0.0</td>\n", - " <td>22.0</td>\n", - " </tr>\n", - " </tbody>\n", - "</table>\n", - "</div>" - ], - "text/plain": [ - " Depth_m Q_cms Vmag_mps CumlDistance_km \\\n", - "2017-01-01 00:00:00 1 0.055352 0.001416 0.119885 7.62 \n", - " 2 0.055076 0.001416 0.120487 22.86 \n", - " 3 0.055350 0.001416 0.119890 30.48 \n", - "2017-01-01 01:00:00 1 0.055322 0.001416 0.119951 7.62 \n", - " 2 0.055108 0.001416 0.120416 22.86 \n", - " 3 0.055320 0.001416 0.119956 30.48 \n", - "2017-01-01 02:00:00 1 0.055322 0.001416 0.119951 7.62 \n", - " 2 0.055108 0.001416 0.120416 22.86 \n", - " 3 0.055320 0.001416 0.119956 30.48 \n", - "\n", - " Ustar_mps Vvert_mps Vlat_mps Temp_C \n", - "2017-01-01 00:00:00 1 0.009489 0.0 0.0 22.0 \n", - " 2 0.009542 0.0 0.0 22.0 \n", - " 3 0.009489 0.0 0.0 22.0 \n", - "2017-01-01 01:00:00 1 0.009494 0.0 0.0 22.0 \n", - " 2 0.009535 0.0 0.0 22.0 \n", - " 3 0.009495 0.0 0.0 22.0 \n", - "2017-01-01 02:00:00 1 0.009494 0.0 0.0 22.0 \n", - " 2 0.009535 0.0 0.0 22.0 \n", - " 3 0.009495 0.0 0.0 22.0 " - ] - }, - "execution_count": 1, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "import os\n", - "\n", - "from fluegg.ras import RASProject\n", - "\n", - "\n", - "project_file_path = r'..\\test\\data\\ras\\unsteadyflume\\HEC-RASFlumeCase.prj'\n", - "\n", - "with RASProject(project_file_path) as rp:\n", - " data_frame = rp.hydraulic_model_data('Unsteady')\n", - "\n", - "data_frame.head(9)" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": { - "scrolled": true - }, - "outputs": [ - { - "data": { - "text/html": [ - "<div>\n", - "<style scoped>\n", - " .dataframe tbody tr th:only-of-type {\n", - " vertical-align: middle;\n", - " }\n", - "\n", - " .dataframe tbody tr th {\n", - " vertical-align: top;\n", - " }\n", - "\n", - " .dataframe thead th {\n", - " text-align: right;\n", - " }\n", - "</style>\n", - "<table border=\"1\" class=\"dataframe\">\n", - " <thead>\n", - " <tr style=\"text-align: right;\">\n", - " <th></th>\n", - " <th>Depth_m</th>\n", - " <th>Q_cms</th>\n", - " <th>Vmag_mps</th>\n", - " <th>CumlDistance_km</th>\n", - " <th>Ustar_mps</th>\n", - " <th>Vvert_mps</th>\n", - " <th>Vlat_mps</th>\n", - " <th>Temp_C</th>\n", - " </tr>\n", - " </thead>\n", - " <tbody>\n", - " <tr>\n", - " <th>1</th>\n", - " <td>0.055352</td>\n", - " <td>0.001416</td>\n", - " <td>0.119885</td>\n", - " <td>7.62</td>\n", - " <td>0.009489</td>\n", - " <td>0.0</td>\n", - " <td>0.0</td>\n", - " <td>22.0</td>\n", - " </tr>\n", - " <tr>\n", - " <th>2</th>\n", - " <td>0.055076</td>\n", - " <td>0.001416</td>\n", - " <td>0.120487</td>\n", - " <td>22.86</td>\n", - " <td>0.009542</td>\n", - " <td>0.0</td>\n", - " <td>0.0</td>\n", - " <td>22.0</td>\n", - " </tr>\n", - " <tr>\n", - " <th>3</th>\n", - " <td>0.055350</td>\n", - " <td>0.001416</td>\n", - " <td>0.119890</td>\n", - " <td>30.48</td>\n", - " <td>0.009489</td>\n", - " <td>0.0</td>\n", - " <td>0.0</td>\n", - " <td>22.0</td>\n", - " </tr>\n", - " </tbody>\n", - "</table>\n", - "</div>" - ], - "text/plain": [ - " Depth_m Q_cms Vmag_mps CumlDistance_km Ustar_mps Vvert_mps \\\n", - "1 0.055352 0.001416 0.119885 7.62 0.009489 0.0 \n", - "2 0.055076 0.001416 0.120487 22.86 0.009542 0.0 \n", - "3 0.055350 0.001416 0.119890 30.48 0.009489 0.0 \n", - "\n", - " Vlat_mps Temp_C \n", - "1 0.0 22.0 \n", - "2 0.0 22.0 \n", - "3 0.0 22.0 " - ] - }, - "execution_count": 2, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "grouped_by_time = data_frame.groupby(axis=0, level=0)\n", - "hydraulic_data = grouped_by_time.get_group(data_frame.index[0][0])\n", - "hydraulic_data.index = hydraulic_data.index.droplevel(0)\n", - "hydraulic_data" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "212400.0" - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "total_simulation_time = (data_frame.index.get_level_values(0)[-1] - data_frame.index.get_level_values(0)[0]).total_seconds()\n", - "total_simulation_time" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [], - "source": [ - "from fluegg.asiancarpeggs import BigheadCarpEggs\n", - "from fluegg.simclock import SimulationClock\n", - "\n", - "time_step_size = 10 # seconds\n", - "\n", - "simulation_clock = SimulationClock(time_step_size, total_simulation_time)" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([[10. , 0.10668 , -0.02767622],\n", - " [10. , 0.10668 , -0.02767622],\n", - " [10. , 0.10668 , -0.02767622],\n", - " [10. , 0.10668 , -0.02767622],\n", - " [10. , 0.10668 , -0.02767622],\n", - " [10. , 0.10668 , -0.02767622],\n", - " [10. , 0.10668 , -0.02767622],\n", - " [10. , 0.10668 , -0.02767622],\n", - " [10. , 0.10668 , -0.02767622],\n", - " [10. , 0.10668 , -0.02767622]])" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "import numpy as np\n", - "\n", - "\n", - "first_cell_x_midpoint = 1000*hydraulic_data.loc[1, 'CumlDistance_km']/2\n", - "\n", - "depth = hydraulic_data.loc[1, 'Depth_m']\n", - "first_cell_z_midpoint = -depth/2\n", - "\n", - "area = hydraulic_data.loc[1, 'Q_cms']/hydraulic_data.loc[1, 'Vmag_mps']\n", - "width = area/depth\n", - "first_cell_y_midpoint = width/2\n", - "\n", - "initial_position = np.array([10, first_cell_y_midpoint, first_cell_z_midpoint])\n", - "\n", - "number_of_eggs = 10\n", - "initial_position = np.tile(initial_position, (number_of_eggs, 1))\n", - "\n", - "carp_eggs = BigheadCarpEggs(initial_position, simulation_clock)\n", - "carp_eggs.position()" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [], - "source": [ - "from fluegg.transporter import init_transporter\n", - "\n", - "transport_model = init_transporter(simulation_clock, carp_eggs, 'parabolic')" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [], - "source": [ - "from fluegg.simulation import Simulation\n", - "\n", - "fluegg_simulation = Simulation(carp_eggs, transport_model, simulation_clock)" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": { - "scrolled": true - }, - "outputs": [], - "source": [ - "from fluegg.hydraulics import RoughBottomSeriesOfHydraulicCells\n", - "\n", - "start_time = data_frame.index.get_level_values(0)[0]\n", - "\n", - "# initialize a hydraulic model as a series of hydraulic cells from the CSV\n", - "hydraulic_model = RoughBottomSeriesOfHydraulicCells.from_data_frame(data_frame,\n", - " start_time=start_time, \n", - " simulation_clock=simulation_clock, \n", - " simulation=fluegg_simulation)" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [], - "source": [ - "fluegg_simulation.set_hydraulic_model(hydraulic_model)\n", - "transport_model.set_hydraulic_model(hydraulic_model)" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": { - "scrolled": true - }, - "outputs": [ - { - "data": { - "text/plain": [ - "212400.0" - ] - }, - "execution_count": 10, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "simulation_results = fluegg_simulation.run()\n", - "\n", - "simulation_clock.current_time()" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "False" - ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "carp_eggs.diameter() == 0" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "<Figure size 720x576 with 3 Axes>" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "%matplotlib inline\n", - "import matplotlib.pyplot as plt\n", - "\n", - "positions = simulation_results.results()\n", - "\n", - "time = simulation_clock.time_array()\n", - "\n", - "x = positions[:, :, 0]\n", - "y = positions[:, :, 1]\n", - "z = positions[:, :, 2]\n", - "\n", - "fig = plt.figure(figsize=(10,8))\n", - "\n", - "x_position_axes = fig.add_subplot(311)\n", - "_ = x_position_axes.plot(time, x, '.', alpha=0.1)\n", - "_ = x_position_axes.set_ylabel('x')\n", - "\n", - "y_position_axes = fig.add_subplot(312, sharex=x_position_axes)\n", - "_ = y_position_axes.plot(time, y, '.', alpha=0.1)\n", - "_ = y_position_axes.set_ylabel('y')\n", - "\n", - "z_position_axes = fig.add_subplot(313, sharex=x_position_axes)\n", - "_ = z_position_axes.plot(time, z, '.', alpha=0.1)\n", - "_ = z_position_axes.set_ylabel('z')\n", - "_ = z_position_axes.set_xlabel('time')" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": { - "scrolled": false - }, - "outputs": [ - { - "data": { - "image/png": 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Td5Co8amAYkaVI14ZJmM4qy0BQyZxFTqUnjhIw8vNGy5iJDbPCU4TlELE8pCviVJSkzm7HafGUaqINSOzijxVV+iYeO1+mYKeydSYEGjiwlX/wPvmNU+q4WR3DCjqcqa78Ez7htfFO9zbK2o/E43lfrtwUiUmjCiVOFvLtTrwsfoWs3F0csN+eGIunzHPjkkci3b4L390hKyxOdLKmcEWmLggugRRdLLFkFnEgFjEnfBuy7h4Yoxf78FitVqtfk6sYe5HjHGGnSLeKmIo8KpiomRWW06F5dq84Xn8BI9jUAVFCqgUueaR+6Q5mD06BYIYdvGOLieyCCOG1Bi2wYMyFGlAQiTnDcmMVCpgQuBqvsc3GcVCbw1TEj7nJZ2qMHlAU1KwoLJgk+DFMOgCj+LEHpGMAsrUMxUlTmZitmTJoBJCxOSZiEKnyCV3mDwzi2ahJiTYhxP75YzyjpM4nto9Go+oRMMtIhmy5kjDQXZEBJMHCpkpix7JkV5aRlsxSKJXL9nQY3Liuf2IVDzSLJqJzLG/YTF7QjGiiWzCmSiQUsU+PuGbipQswRTcpxtK7SnMzHf958ymYDcP5HaPzQeCKdmmjknvaGSgjJpJB5KaqWykcwoTPYPWpOVtj857xRFXHDE2gko82g1vrjwjgTdFzed1hZfI4iJCpI4daom0eSTlRG0mbtlzsDuGpSIK3Kste+no4o6dX8hLRgUDIyRzTWevCXnDQkTiSKcdN+nEIDuC1ozKEErL8/gamwOD+dOMuaQzNUjiQXZ8q/8QScLvmed8WH2be3eDkYUkJTDjteKgGp4uHXrWmDhjcyCYyFmu8WKxJtJRcZ09AcP7+UPe8a9JseGYGnyueHF6ZEgXzLuF/2PzD4MRTFxQCDt1hJyp7IkQDSkXeGVANAmFYyEr8Bmy1kxLQRTHbjoyFgVOJSYxzNFRp5mLaaZzBVoFRtNwpsbnkkbOLBTUcSGKYQwjucrYwn6tx4rVarX6ebGGuR8RlpnHpxOTKQgYxqxZVMXZb3FuwESwBLyGiMYrS50FguGdcEeVIy4vnGzLte9pzcBZNdRqos87ajPSxAmvNUkJOkNOml6EPTM36Q2TyWgWTrzkjXpOxjBjCdmSlVDmiYIZSZmoHH3eELEoiSQFSy4g1yiEOkU6cbgQeJk+51Y9AxRROVSaeX9+zWw0o2rxYphcy6gCk9KosaDVMOaAk4VEojc1noRfHGe9Aa9JKtC5PU0cAIMRYaCgl4qHqgKEMVrqNPP9zbeJUdirjke9Z9xv6HWNI6OyYVINOWeGYqAKM++Gj+m65yQ0d9UVRiZO5goJD9xwYhbLZbwnc8lZGTSKTVjYzJ5P7DW90UxSU8mJXtXYuPCgX9LqDq9LormjM4axyAgzj+YKHYW5bGnHniCeHDJDXdPOMxszsxtONClwMFs2Rc8htZQ+YJKgOo/bLXwQf0BX7nnSe1AF/rww7it+WL3ic1eTfaKQM1sZaJaRpIWn+YaxVPSlI9kExZ5fWH6TF6nh0VwSlaJKC2WcKeKMzjMfNt/mMV8xWEsShc0TkjLaB4roGQtFQLFIxeIdOS8EFAFLiJmoDBITtZqo1YyxwhwmdK3YesFWETfM9LrmYK4ISiMqUSZPzgblNSYpjr5lKEuSgUEpeuVYcoUmIFlzdjXKZ0gRLZpKBrwYmjTjs2Wm4cPiHQwLl+kNxIwyniwFEcMgJbulY1oKNvOEq8AU6+FrtVqt4GsOcyLyK8B/Bmjgv8w5/8c/8vq/BfzrQADugH815/zRl6/9K8C/++Wi/2HO+b/6mRSVDTe2RC8TLgWiElKeWayhUBmxE7uU2KcjOY/01LRpYt95tv5IVWWyFFTpid3ScS4MyWkG1aByxJHZDScG3WLzwF0laBbAsFEn7i5qOilIuiZnReUDEOjVhmgSBQsFI21+4qRvONuGg7IoStp4xJIxeWIrB2a2POqWlDVWe3woWGxFzEBW3MwBvSiKEPm0uiaJEDG8WA5U3jP5hmJSnNqETTODKRlyyyCGRRqIwiyWZCM6ekoCMZWkHCnTwKQh0BLF0Ou3IdGrjn16YLIFQ9ijYkUqIKiSMi5kbdksBxZdo0dFy4FyeuC2eE5KgoqBg9nw2r5AtLDzb+htQykByR16SczJoBC0HNnpxGfqFYfcICRqTujsKeOIMRlXvmF0NSA8yYbBGm53JYsomAcWEbwr8coRlOYLc0VX7WjpIAvoSBRBksKbkiyKjT+wqIYmjigV3w5cKYSnfEGpPGXMLMYTjbDQMAXLJBlnLI+uJBhNmQbmtGGa93xr/oioCn7r6h/B5RlByLHgbC55THu8McTkqJl4N34OMTHlmqkoIGc26UA1eM5SMSphMTt8Urhsueg6tA200nPSDWfTMtQtpeqpTGJWjsd6Q6dqvHI4ZmxMtPNIRnOWFqUilZopE8QoDLRMUlGkAdC8M32Izo7dNPDgLinUhJp7bssbBt4GeZM8XiokK4a0Y7+ccFhuTcmCJknNF+4dSuPBf8L52KHyOvfcarVawdcY5kREA/858E8DnwJ/U0T+Ws75t76y2G8A38s5DyLybwD/CfAvisgl8O8D3wMy8Otftn36o9blxLE8VFxw5pKertQ06cSluqdOHXXusURcyiQz0GRFG3uyC+zTkefhjs/lBVYsmoWdGdB5ZpCCQs+U4chTUzPnhig1ioRLE7NpWaTgPu/Z5CNFmFHqkoWWlBw2RmxKBCtkMYDDUxNQJGoyiZO+oKanjQs+Oap0IhRbEkJOjqO+QUJmcFsyCsRwEd+wFMJGHZhSSyDRS4nOnnqZmWVLM0QoNGWcKPHcySWxMEhIjMpSLcKgaiRVXNDxneUT3rQtR0q8rklkSFDEAR0j57xH+TPiDSYJWntKSfBlL81RbUEFjJm57I+8mVssA65omKRChUw37xjMiEsK151weqTME+SC96cTxxLOaovPFU3uiFmhAuRU0gwDU2pRWvis/BZFHnme3uCzoZeF3tdgI1FHxAtX4czonjNyyZQbClmY2VKmnqYP1OUMIpQyo/WZZ/4WrRSCYtaZLJGcMxOCThmVPVYWyjTSqoEiRkbR1MvMYmeO5QYlC6UfyT4h2fDMvOEYPoUkSA6U0TNVwmQ2jNpQxIW9PyE+cy42FMFTxYlyOmIoqbzHuJmkGy7lERJI1FgfmW3FmCO38hwrnoCjVRbLgU0eSbGnihOzUpjsKZkhaU5mw0TFJAUfyEdULExGg2hy0uQEMWdsGAjUKNtzwT3BwYf2AxKROTkaOkZTg46UqX/bkx1mulyjSUQET8PJQmgmtqGisBUppD/q7r5arVb/QPg6e+b+MeB3c84/ABCR/xb454HfD3M55//5K8v/78Bf+vLvfxb4Gznnxy/b/g3gV4D/5o9alMpQmYbd4wOvUuScSmYUw0bRqQ1LNmw58VJ9hMkRZscUWrIERqe59m/YFhaWPYXqeBMvOektOiW8KjjJBYuyvPCfc2ZHGQYKH/hwXxPRjKrE+plRWnI2+Oy48B11GuiNpTMbYlL00iI5QLBElzCSiGhCrrBqICVFNJZN7PnU7BBRzGKQnDB5IefMwbT87fq7CMJVuMVkz366Y5syZnAEBVf+DjcKPYqDrVA+U9qZSYTZWU62IYaFmYomPRKjorMVZUjoIlGlATLoBZyHwk7oRTHGHcVYkmzi3flzlPF8VLykzzWzMbg0U+qFN7xLKjQvzSc0/sRRbdDZ8tDW4C8pVM+decGj3lDPCaUCv4shWnk7cW1aaFOkp+Um3OHiQuXP/K3yz+Imz5viOWVaOOQdPmlCECaj0DpyqCsaejSJ6+XEJgzMGOZsmY3B5p6zKcg5MqodPhqilPjYUpDYDU+YdqQwHZWdeeUjzezYTi3W3XF2e5KbqaeS3XSkCELVRy7zAzlqGo704ZqzV/TWEYMwOYfOhg8372KYUXlEpxYVFb3ZEUVjU8DhES90dkOIjksbuExvuOjvuZNnzNlylj2q9CitaOLImBpsyjgfKYnoLJiY8U6zzyf6ZCnzwjv9LZ/pK+6LPR5hzhUn1dLkkZAFkQWbA0XK5NGg8ts7QUxiOeoNgzbM4rB64iwblqTQObOJR0bVkLXGZP92UEQY6HSJY0ayosoLSRUU2uC+cteS1Wq1+pPs6wxz7wKffOXxp8A//ocs/68B/+Mf0vbdn9RIRP4y8JcB3n///Z9alFiLEc3ze81+vGWUib/dvM9DfsFERcOZOZdc5hMDLVEbOttw4Rc+1s85UjKbDUPcEc2IUxM6eS5Vx4kdO/XA6/wOn/Iund5QyUTFwGY6UahEpwqCWHxsKLQHMdRx4nV6j946BhRBHFp5dExcpXtCskyqBBQpK2I2lDHiraJjSxT19pSxgIgnaYuKESWZbewZdU0RIxlomTF1ZHGJMRumcQshI3Gipme7jJSx47a+JqoaJZlFQOVInQZKGXCqo5g0kq6o8BASO3+mDR0uZVzSSK65ngMvpjPR3PNgDJ8nh8uKB92yiYpIT19ZcJkYa8p0IttAJzsiBadB+JBL8lzhjYYZfMoYJxTLmVRkFr+h8JlCR57Nj1yVd/is+DSOHPxzRtlQcSS6kWjBRIWKERFPRYdxI3pMXA0zS7bsZMCoQBsDz/2BRTskzWzTFxz0hikblliiY2Z0C5swsdUn7By4jh1v5D2GUmNcw356ZBcOqOMV0bwNfZ0ueTceSLEgaMttumJqKo7WQXS4mKiXkVEVzKZk0A2zWErJaO/waJyPzKXDpYEyJ8RPMLWEesuFPKDnOxQLS9ry6Coe8wVaFmxcKKKnXhTX4W1vp4kZpTxPdoNXBTE7PqsUJGjiTKcEnTxKeSZr8FqhWcgJiAkq6KIw2QI77TnZFhUnZqXpYks2CqcCAQs5k3MmS+LOXqN1xMcMEoGIkUCOM1fpxIvmfbTWP3V/Xq1Wqz8Jvs4wJz/huZ94OwoR+Uu8PaX6F/6/ts05/1Xgr8LbO0D8tKLatuLZi3e4/+2BRTJP0wuW1hFFGFVJyAaTG2yK9LJhQXPiitfFDRZILlPngKoS5IZX/jMuizM2DEiKeG3ZxANP+RkuBlJw9Nqxy08QBKUdGsWTLb+8MLzki+o5S/ZEHBMtizZs0om9HLnmlsaf+Nx+wKwKYtJAQkvAECAnmpjxyjLqijpOxJgxEtF5YdYlKmlS2mJVj7ORJ9vgTYFKEcMDi5Tsx4VdmHi+dAg9b+prcjbklFECQqIzlnrJxCj0MaOBJp6YbEEbjsS65G7ZorXhhoFxNyLhidJXmKEkbkqCMqisWHCMUlLITOtPHKod+yXjjSJGRZsPbOozoyoY2syRLU9W0foBQ0+eNqQioX1kM48UUdgycK3vOc57NrrjSS5xaeJ1u8XiSAoK8YhOJKVIIli1oGKi9Qtn23AhPW2YicVMQCEyI6HhkSt6bwipJOeCuUyk7Hnd7Cmlp1WBi/HMnb1ABGZj2ekD23zm3JY8mgsmfUXOUKSZbU4kiTSbngfZcCgumFKDUguTbihVTx0XqvCGzhYQK2I2zMmhBC5noR0yJ1OSdGQpFBIT22UCp4mxIkjJi3ik1gOdLdiHATdnbs4ZUy68ri6wIVOnmV4iMe9ZtEJiZCsDu3BgKa9ow8yiKlJWb6/nI6NVoI6PLKpiMgVHW2FwLKpgO4+0agQZedKKhbfftTY9cpYXLCIIgs+aWRcYWcgp0sSeUgeUB8mOZVn+nvcOXq1Wqz9Jvs4j4afAe195/Ar4/EcXEpG/CPw7wF/IOc9faftP/kjb/+VnUZT1I9fzF/T1e3y+E+7KhlvreNIXIOBSwgVPSpZJGTp1xZLfDnC4WM4EXTEljZGeoByv9XO28YkXcuJK7rlP71KMQi4NZ92SNFQhsD0OTNUGI56z2TDKBtKZMh9plzPROp70JR5BUiBJBhVYoiVIjcmJOVjKNGPTgpOJWVUoCW9Hv8YRRcAnx2Tc2xuh+w5i5NXxQFYFoTa81tdU+YQRj1YG0ZFNGFlMQx1nanug81vaZSbaiS2afezJGRajebI7Dn7Lc27ZzScu1YGnVFFLokOomOilxuRH5jpxmgMxVnyc3sOHgtE6mmWkjmds9oRsCUrTS8nJvgKBUhZ2PKJ0oA1Mlo4OAAAgAElEQVQz2SbUkghFyU16xKqAkUDoDR+X3+azKqMTXNyPGFm4LV5QBk8TIvvwMb9Xv89GBgYsFs+L9EOWWHIldzybHym1YlJ7RrYciz0DI1d8wjE9Y1KaWSyN70A39LqEHEm64GguuS02tHSMy8ysLJ0t0Mqz5C3MJQ9qyxf6int3gWXG6Mh9uMSoh7cjiCWzyJ4iChISdsq4PHPBE1NjEDwv8y3zectdueMgLcEqttMTqvaUeeaULnEaglzxUWyp8x2X3YRU6m1PmtZMuqZIAZdgrjXH5oJeLI0d2HAg6IrBWgapmUxBM860eWYIIzrmt6f1rSXlTMGISYFBb/HicGqgyZFKeh7lmrNrKFnYTyc0wmQqMhqVSq7DEyfVsLiCGcNEScPbQSbROtIIvWt4CsPPYndfrVarfyB8nWHubwJ/SkS+DXwG/EvAv/zVBUTkHwX+C+BXcs5vvvLS/wT8RyJy8eXjfwb4t38WRcXhwFEfuH81cy4db4qKo9sRkqZICxfpDc/TIyZlMplIRUUgJov1FpGII6DCBM4ymgLUhs3QYIvIRM2pacgJdPZkDJOU/LD+LhvfkfXEsdiRBW7tcyo/05ktL8InbOSRKFcEiegcsbljpqbMZ1xqySgMCZsi1kR0HliUZqFBEVgomMSSVMUSA5Ua2YUDWgWeTEGg4KG4RHNFFsVleORKHbmMB6Cnzp5eSg5NSZ1mZir2caSOC702EDVF8uiQKZdANpqQNRdFj/KaR3EoL7jFU0mPjR5h5JAu+KjcEENkqSeqOCFlYN/36BzRAbb+xBv7Ck2mF8d+vkPVmUOx46x36ARWJYz3EDT14gkhYSVhoiJoxd3mmt/cv08GBtOw6QcOcgVkzmzIOdKEQLkIF+nERp0w2SGLYrAbgouUqePSP2Gtpwg9VjSq2zFySUpCpTwND7w2LxgLYRTHqC5Z3IBOA+3yRK0C5MhN+oIfxHe539Tcmz2axMV8z0karAkkrYgYmuWekksOS4lRmQvVIxYsC5fhkX3sCPbMrBKSIloiT2VBqxae+3sKpVA+06aeU1MypYbPth/Q2RpMoC8yvalIVlEbTxk9WjyDs9gwoWPGxUQRPdp0FES0mslLReHBW0URF9QCkyoQr6mSUMSFMj8xm8ykrplVQSclkjRt7siF5iY9UIeejpomz7TBY5IGOdHkRLBvr1GMWM6xwJkjnYm8SY8os45mXa1WK/gaw1zOOYjIv8nbYKaBX805/6aI/BXg13LOfw34T4EW+O9EBODjnPM/l3N+FJH/gLeBEOCv/J3BEH9UizHcL0+cG8WT2/FgLklKsZMzOi1sY4fzAXTmRl7jaTjnDe080YTEhX9AS+KoM5/xLiKWnBU/LD+gkZ7ONwR5Owt+EoPKgvGBgOZYtCyuImKo0kgShUsLoiJiFPt8ZE41szIIcC+v0ErwSqFDYpM7xAsXY89NfceD3TOyh5SZqdHBo43Fh0AmM6aSo77A5icKZha/YaprLkLH0RbMytDphlstbJYRrw2daTmbkkk5FhNRBIiJIszUi2e2jhQsySiqNNLIQHHyHNwFh7wl1BZrAvOsacMDIUNKnllB0IYsiSJNNGEiC8xKY0JJXhYWJ6ioCclyX9xwyQMBRREHHIE5tXxmnlNnz13zDOkTD21NzgZUZBdbEgYxnl4VSJWIi6CS4BhQMfGt/jMKfWY3nrkoTqRYUemBEFrCmHlj9/xAt7TmgYkalwLeNOyHRzb1mZOrObhLRoRJO4q8IDli00KjO5RSECN5tiyxxlOAT5TSEa3BF9Drt6dNn8wNehZirrk4ZF6GM1pnTKkxJAp1QJmFSVke7I4kiSCKbT5Q+ZlGFkZxpOyZK0fHMwIZPQV8kfEuMGNZlMJnzS522LzgtUMrRRZNJSe08iRdokiYCG06s1lOPOiSEBPJOc5SYlxC5wDKkUOHiR6PJ+WCNj0ChqANixQc5JKcoR492RhOdg/6hLPwZw/f5zfML5G0YpfPLLngJIZFLL12b38sKU+SdTTrarVawdc8z1zO+a8Df/1Hnvv3vvL3X/xD2v4q8Ks/65qWbPB0tPpIkEiXhTue8SQXb6e4SJbFlLi4cLKXNMsIytAuHQaFkyMNCxN7tnHkbBpGSkQiKp0x1gOCwaLywpktqpiJQBtHtAiTZAatiSjOqsGpQJl6bNQE9y6zKsjqbc9HFWaygYTGxjNH85KNzhy44mK846nactAXxCygIGYha8WSDA5FZGByJZtloOFEZs9ZNczZoRbHpX+iF0VXX7NoR0DjmBl0jWUhkdmkM318e8cG4zPbMKLzGRkUppp4chfMRUWFx8iIyQuUitHv6GJJ0BmjRrq6xeuKyU3ccEupIIompgJBqOeRHA3B1pzNBYtqSURSfDuP3okdShuehRMqavb5SJs7vDZv72BRdxzMC5TVLFmhZSGZClEJSdCkmTpa0rDhs+IFt+FMoTV7TsSiZvTCLAqvE2/UDa0e2I5nqmWgdid0PjPFHcY7lCvpdYtOmcv8xEZman2iyxu+KC4Z65a7paGeOnKVKfNARPMs3r69ZpIrDnpLoyKVWojaY4oZNyeOpqaSRC8bSgXWjpwpsSzoMLLpH9nmyE6/4U37Do3vOKTnuN6zWOG13jErR2dLghg0C0oiGcVMS1JCnY+0y8KsGk7Z0I4D3+ITvNXsw8AUNTqPxKJFxyPJtOSc6HRNikJQETWP6AqEQKduSEExGIcTzyIWnWcKNaASROXw2vAD/Q5qP6DChBGNySUDiiQORJjFQQQX9DrP3Gq1Wn1pvXr4R/RP95xvB+wOlAk4FSjSjMuKS+6/PG0HOdREXaNjxitBV5GQhEfXwJRJWiimib6pKRjJWnPIl8yqwPmZbNT/w9597ciSZWl+/6+tTLoIeU7Kquqa5gDkAE3y/R9i2ENwpjHdpTLziFDu4W5yS1548iab99UX/nuDAAw7lput/X3YHGhk5Ta8sOqGioGJjjot9Ckj+UTWDh0DMz0ZRZUCqVhmqVilBpUpRYHOfJEf0BmOpmEpt/yt+ZFJGQZVo7IiSyRLRc+ZSbXYlIjZoVeHmQKtTXTr8mszhSKI5aQbKBGbI6HUhKqiCzNbfWQbBl7lnlzUJS+vGvnd8hOp1oziWNmwqAqyJ0viVLUIsHVHlMxksaxSE4OjTQWbBmJc2JQzt/NESVu+uh0ihpAbCMLUtsSiMTlR5ZW2nEnZkJRm1Bt80Xxyt7RpZKh6FmMp6hKMnCSzCQN9mdjnMxqFSpFCwpqRnT9TtyNvfGARRwu8WMebe+R2LURJ1GEhVjW+1ATlmXSNrxweg3c31PqVsa6JWdPkiELjsiWmilW2/M38wKxqvFhO1YYHDjRpoltfWauKzniOZkOTR26iwhTDamo2zZm3qmFpFjKZRz9iZWU2XAKZqTmrDdkYXvtH7PIZ7Tp0mYmq5lW15LYmp8Qklx21Ng0UKSidCL5Gh8iWI1XOzE6x0OClYVENXld0+cQmXJ6Pxd4zVhu8thi5DPkFiy+KpFpOSshKuJMvWLn0A5uccWmlYUGbhiSGY72HVTGw4SSXzDzjPLVOiFKUIqAECOiisCXRBU2X+kvO3DWd5Orq6uo6zP3WvM5I1NyvT+zsgVAEbxSjLrzLlobI/fILU9iz2hqjMmPuUcayz2dGVTGoxJu6YZUGFQQRQWSloDEE3s0GI5kqRW7yGxsmWhlpeeeUbslaQQGXf/3HScWr6hGtWMSSpNAxs0nvSEoEaVAm8ip7sjI8VR23QVgEdMlYCl7BjjMzGVdWUnGYMlPZiY/pKy4pggUXFe9Vg6DxvgKENs68bW+pwgglUocVKQWdFN/6JyQpWpNIleZfqx/RUbHgUKNC65nKjXRq4b/k/xsdV4wJGIkczA43GerkaWVhLBZT4KN/4ZvpiJBBGea0Z9aFtUokNWJw1H7GFNjNK0qdeXVbnIo4f2bOLU1a0KZQLwdCfenwPJhbcqmZpMWozMMwMMgNmHegodKfucsjVjkO9oa/qN8x1DVaAm/1xIflFzbBk+IOh6eP70yqxdSGxQpiIh/XlX1+w6eOXAKSDRsyKY9s44ld84pXH0k0ZFHMumYzTyS7YRuPdMXTrE/UsjKoD6RkmDDcpDfO5nsyYFIixpYKsHHmqX7gIA+UomjTmXPeUioQk1noiMpAKvQMtHJpNpmtYRHHaiukCBt1AhEm3eFCgFRwOdEsntdqSyMeo1dc5ZlVQ5tOHNSGUiAriynh8kxgSSqgpOCyZ6G93DPPBsmBXR7p5cg7W7I2TOIQq6jLO2du6MvCohwn6SlSWJQjU0homjzRpzO79Q3y49/vkLi6urr6D+Y6zP1G199i1opS1xxyS9ANAxti0tRE9uuBh/yV42J5l1uKKhSjQCsKwja+I6XBlJlT16MInGxNooGisT5QlEGVgNc1Nh0ZTQelMOgGVQSVFgywn8982n5gpefFbDFSCBSqFFAEcnHc8gtvfAdJiMYChaiFuRSyMhgKlncoPRRByJSsuMuv3OQDH5cXPsqBQ/2BpWtIJhNsgRyJbSafNPfriAywywOgaRnw0WFsYKIjOOHdbFGy4nXFpHukCKCoYuD7+DeiCNs0Xcrqy0RzjqxNQMWCmgudGtmvE9kq/rj8mfZUyF3F9/6Fc1k5FlCh4U3fsOIBgZQZzZaeN358/StbPfKaHzCVYJsFrEJKZpveyKHlbBvqMDPaDvm1X9fKgE2Ru/TGYrY8i2bsIaqFNkVGXRFxnES4r4RdeqX2M3GsMLJQKsvkKnLWKJV5do+IUvzof+Jv6XfkkjBjhd8UlrJnEydU+SvB/CMla1JpqecJpxeS3XCgR5RQ8RNu8USdCPT8Un3LSIPNJ3LONLIQpDDYG7zvcSYy0HCQe5z1nKRnyxmXPbs0oEJAHChmasCsBqFlmw6IGLIWnEpQEkY0VVh5Nve8uTuyyXRl4Mnec88Tk1SoLJdeBjmTi6FERSmGbfDMdUJLpioLvT8iYkliidphSqDKng/6K2upyRiWsuFjeCbmlqAUR3PHpky/7oYWDELDzI068fv8V27TgLNcQ4Ovrq6ufnUd5n6jUZq+Ujy9jaz9FiWRVRqCMuQsvMk9s7T0NnCoKrx1rNpyk0ZKybSrx2dFUQ1RKaoiSMl0ORMl4UWjk+WWN4RMk1dyKkymIaJRRLSuMCwkoxESmoEseyp1wommzp4+n2jDwmy32AISI9s8MpmWCo9FaOKZG145ly2xjGRl2OaJSVq2cmJRjkO3w+uKevU0yvMh/cQk3+NVgxfhvXNMxVCXyC5MjGnPwd0wm44+HXjVH9Bm5lXdsEkj76pj1HscCZ0z3gWO4ZamTFRmZOMXzq7hX5o/sJaOguZ3+WfOqibYlpgth/UWZ06cdaEw08mZu+nEL9VHfIkUdcuaKwZd06U3vjQf+TFGlK+4HWaqbFkrqNLKVg7kDDEZVunIKiIUqhIZbIPLKyZnjrJD9MhGXvmQT4xxi4+aQ7Un/9rpKlGTqdEBfKqwZiE4cGokasUP62c+yoG3+Z6Ya7YhovVIWyZu5oEH/4QJE1OqcLsOHeFd77mJC5YJLxWNfmdMltltwMKL6YlRMDGgTSH6llQqFq/RecIyg3IYSXRroThPm995dfektBAwdMtAU5+oZWDNFTGtvLhbnBpZdEefTvjcsVlnlE6cTcuiKvrwzuQqohhyglF21MxQMjZktpx4U3dkLkHVlohTnmaNeNOgsuacvmExBq8dKiVciRidUUF+vcDgmRHOqmeSDiSySMUuv2OyMElFFkFEkbJjVA3fhWc+NJtrxtzV1dXVr66n4W94hN5atlYxSM+kKqLSKApFNCoWSqqJyKX0Pq7UzLRxYtUVaobUghFPVyZWbcgKZlWxCSN1styNb7Qq4rNHSuS17jiYPVIilXhu4pFkDJ/qBw7qhlnXrBhEdWzySC9v7JaZgmUtLfs4cpSWOicGsSQRtNF8Hw/clwM7BsbQ8rn6jpIF7xxrNgxqRyyGpTGoJvNd/omezG1yTGqLKgWvNIO1fL9+piqeN7PnpTzwygNO33Kueu7T10tOGTNtCpAnTNT4ZEFnhvLAaBLNlOiaT8RQczQtzD3e1HzpRmT1SIx0pbDsLZ9lx2wsOkT2caHxhsdf4OeHDmMMQRS+U5wqR8kaOyfGqqBbwVbpMvzYQBTDye6IuqFf3kmlplHvZGUYTMXevxNVhpjpc2BUt5z1LVnDrBwUKFkRlGOTB3Ktedbf4OcWtURKI+xkoBTh5hSorGVRe95kx6obbIbRJ5rlRJQaQ6YNhTt/JvmO3E5s6je2y8I8f0PohWhqVrG8dzVD6S+DUE6sqkdswM3w0hiwjrHaYOLCqFqKg9lVqNiSBapyeTb/GP8GQ+TYtbyYB3SJrLrlu/SJNwLbeWUuhdk2VD5hSsG7imPbY3MkaYXXFlcWZjrqvHDUHVoCQSyFhIiBIpxtR1tmKMLKBm8rbFrZ+hNrMJyaG9bS8IEvLKXFi+NdbjClMEvFTfYMOI7llr6MtMyczI61GJLdktP36G3FYV2IMV4Huqurqyuuw9y/Y+tLC4HOLXu/MLia5MylWzU7jI+EVDEpx+gqGjWTsjCbllASf7r5EZ0DXjrqNLHLgXodGZqe2keSWP6wfMVlw3uVePk1jsSVia5MQGTUd5AziNCnM6LhphwJommYKWKIFUj0ODMheJpc2MYFu3oG01KJxybFO7eEbDjqFikFi2eTEoaIJpJRl5gRabgvzxgij/mJr0p4sY8UbfC0jKbnj4efea4/EHKHBGExPSTNnG9pveeb9EbUjkEHJBiKBRc9TkWO6lIH9Sf7IyVoRt0QO00VR3yBDoihoY4jjQiVgqiFZC7L8cpkTIAmFEYdUS7Q58TH9IlF1XzafGCsWlSXcRL5bn5lCB3v9Z6SLvd2T/aWzZLxdaaKC1lVzJVhFQUidP7MKA2V9zyubyT3PY/xmWQ1Gc1oNphpwUWDIePrijYV9rNHk6heZo7VA7p6xJtb6uKp8AStGfKOL/qP3OdnGr1Qp5XJGZxJrFXi1A58eP+vhGhZ4+85VxVP8ojJnoJwshtKqii1IxePw7GLb7xWd9TyThCDk0SdAxmDUQuTc2gWnsQylTv+an9kkh5lhCzQxxWRyFA2LHTUrIy1Y1Y1UiwZRZ8mTA44vWDKwrvco1bDwdwSlCaKIogi4VDq0m28ZphUS9YarzV16OiyQusJV2aKMkw0zGUDJJI4qngmGcWJDnLGpnBp4LCJfTnwKo+oCCnVjO6yl5pSug5zV1dXV1yHuX/H6ET7eEtb/iu31cK/2TuCsqy/Fph7XdjKkTd7T1SGdg0UY8mpEG3Fm7plUyY8iqxaGs6IKFQSJnqKipwbTTUL3lTc5iNvsiHoniH1tPlElUf2ceDN3iF6AS75axRo0ogjIUBtFkzOCIWb6RVfaVa55NTpkslaWJXGY0jFoUtGCWzSiC6ZnrdLaLFq8KomGIOKhZswMOQdz8ZSqxnHSl0WOruwSyeSc5Q2oFTkYzgipdCycB/fSKGiciu5sgzS4IujkhN7WenKxDFXPMgzKq781fyAyZmz3XC3/IyPhUf1CWM9Q9OwlpqUhKYEyjby2hvETfTrzPu2p00zubTs1jMnZanLiBhFn84onVm54Vy2jLqjxMQOT51OrOmWJbQEKxz0DTafESk8ccugdjiVWdWMOimWneCxbNYDRRfebMex3aBKoEpbHtcXxryhO2W+5g2DVSjl2ZgveKshTWiTyWfL2HWwKh7nmXo5sGkCTp8JKrPoLb0JZCf4FCA7mrCgxLMWweKoWJjE8cATKVcczY6TaliKZaYiaI0QUAImRZQIizQs0hJyjc8tXiqMZFye8UpxNxw51Xd4NJO5oZkWUl1Rz5E2J0wS+jJSKU8xmUV7XFopki+ND3Ip8GrKSikKlYUqXTICo1XYojAqEDO4DJ1ZGbXmnQYvhj6tGO0xOrLLR5QIkhoQwYsmS4Uio1gpv/6dUWu2dX/tZr26urr61XWY+w1jFVoX1myJ1hDEYEpgxSJSeKvvWZmxPrFIw4u5I+uMJRCLoIvHoylZ0aSFLswImc1yZqw9xWiOW81je2QtewY6ujLSpScO/EBQNUe1ZWThPr7wv+b/xhoj/1z/E+9yx1fzPU0cqIjseGcoPTfpgFZH9nohXhLVaAlkAg7PWR5IogBBSsDIwm4akRgxKpGLMOYWh8dkASxdntmkiZQKBUWOBkPgXl7owkQTOsa6Y1tO9FOgj2eysrzXPce+p4hizi37+IJVM5bEuAFfhC/yQCmwSROPy8jX6p6ZLUvfEPwLsbS06wGVM0e95dXsmVzLmmuUXTk3PerSjMq76UkFchLOZkdBqGTEuwYThCYv5KIwsmJiJhhNFQIEx5I8YlairpGSWbVGlOLDeWBNDrOCGhpWC9HcEZkwKVOllTs5kyVhEbwyvFQbjJ55r2q8uWXeT9zHN5RMSFK87jfMKDoMb6bi+6lg3g3ZQTCKpoz4yrJIjWSFmg1tivhKyLSsypElU4qwC2e8VrxKSxMiSQof/BtKKTbjzMlagstgLzlsx7JjMC1BK1YxSArMpeWzqniuH7BqJlYVuUBj4fZ9IsWafspsPdzoyKHdMnZCCQKDRm7+v33Oy4+cfT4xyfbSy2pWhIoMLDQ4ChsZ2aiROzkR8uUt5yRbUmm58wce/SuvVc+LecSIZ1AtSkdA6MoZmzQpa2xM3K6Rvrq9vpW7urq6+tX1NPyNqt5Q7XbEz5YcNNolCokkhqhX3qodqWiKtaxSUZkVlMIwovSeB/9ELi3VKdOaM6ty7OLAqep4so8ogYGOWnnaOINkPqyf+Ml9T9AVoQhFJ4rOkIT79YVSFQ7hMzcy8JXvQOLl81aGs2y4USfe3AO1GXkvPauuISc2JLaMBCpSnlmzxUgiKsepUfTzzC5cOk6teFwJ2FSY1ztGdUdlPFEr+jhidGB0hm/kXzhww3v3I7fljJLMh+Erh+qBT+YbznVFEoWRwEG3uKI5m2/YhSN1idwPAwd7R8mJ5CyHtIVQeC9blmL4yj2tWelTIYYNZ9XgYqHYiHYLm3Qmm0IIlnO5wa6JqQbHmX2ZafxCJ4F5rpCUmJueXCwNA7fzG73UNOnMmm6wxaLMiVfXUrmFiMOUjGios2DJ3C2e+hiYGqFJgYO6J5mMFY9VE2/6A1ksi9py61953W9IOrDYlp16RmuhXwbO5gbnV5Ssl3xBfSC7lt1xIuA47Sr+1n9AUWjywPecOY53FBVYveMl3qFMxZvq+dz+SAmggrD1C3Nf+GZ6wgj40FJm4d1ayk7YaM/GL4hVVOdndCf4aDk2Gxwrc73FRU9BU5WIlpqSI3X2NCmxiStns+dAT5VmPAZbJ1QJII4k0MlAzRnHwkZGdE4McuLWn/gf5h+RnNE6kkkEMlEM73pz2c1TCjGJYAQARcIl4V1ZEEsWQxRNFosjY8pKyoZfvr4xTRNt2/6dT4yrq6urv7/rMPcbPkSOB8s8PvDzruZd7VEIu3SkTQOj7knRclYtdZ7JNqEKCEKVPTsWwprYMfK13aCU8DXfEbMiYRG1MkjDX8sf6FnRBB7nF1wBaQuL6vHK0KbMSW/4b/5/5z/5/0m2lkF3KL0iCQKav8kPzGaDCoXanLgrgXd7x0FtUXmHS/9GkxZMPDCJQ5sWdARlGEtPXXlu/SuzvuyN5WIIGJRkSnQULJqIITDYjj+7H8hSqNJCzUSfZ17yR07Vlp/sd8xiLzcfo6CJeNvwpH5HlkKv3vEKDn3NymVoLFkx1JYEnPZbbM78P9V/5kN4oZPCR3/CxQqVIYsnZ5itJYpmmyZ86WlCJFSB1VV0ZLKuuF1O/OTumLPFpBWJmWAMa93z+/NnaikcfUUvHR4htRWeQlA1P5x/4duzR5JithvOfYVKmlYvkCM36Zn9MJDrzKocnzff0+iZSRybKRNEKLoiGMuX8g01Izlr2jwh6YaoDblOjLYmmYolN5RV8VxaPrtHehloXMc/pX9mMQ2+aIrTdGUmpMJGIu0aWKgYlSHWUKsR7IpmobTQpXdCusWukVqEVGlqZqZ2i5oEpRWmRCKKgsOWhUlXWCK+LvxcN2xSJOWa3fIL3t/hO4WgLx3F6kyVK8ZUX9628YpVkSSXN8ElK5TOzLGiSxN1GVFV4iae+KB+gSIc9C05K1CgwyV8WS3CXg+sWThVPVAYEXy5dA4rCVAXzMlTRc88z9dh7urq6orrMPfvnE8nlvOMVAlJBVsit/nAqmrqOKGTsGpH1DBJR8QiORG1oqKwkuj1QKdOCBtM8Ly4j2gVmaWmTsJMTZSaoGZ63pm1Y7ItLid2DCzFUEUoUnG097yuZ75f/sY2nnjve35Sv78k71OwJILSuOIwOeHySKValBQW6XnR9wRdsxaHF8VottgSaNRMJ++82z2sma6akGx4lx2TtEwbi+RLnttB9liJpABHs2OnM0VgMBU6e3QVUDkwVTukFDKGKni66DGMZK1JWqNToi9HanH8ZH4gRkFJZjA177anYyBkhfEjOffEUrMfNPiFTfnCZBzPbofH0skTYgKJlr7MxGL54N9osr9kkqUndt7R5js+uw/sToJqHSlYol0ZtaPYmalyuOJ5iF+ZVMvv+Qu3JILt2KuJHAVWzckYTrInqBpVnanUinWZpkw4H1i1JkqhLROD7HFxJRWFSgqdDJPZUnnPh+XAp67nz/X3WFlxdmK3nNFOiBRCEQZu+Uv7PU2E7TrybXlBhch/b/433k3LJ7fDypmH+RcyitZPDK5lkIpERSORnMCWhRM39FLzYXxCxDCzZbYGIxGVIyZGdCmYHECpX5s5NLfqlbdyT0DoloUl1iTj2eqRfZ4IaeKJB6YivPLAH/gzVV4ZZANGaJcFuyY+8pmv23usFIIdUEsiF4c2GUFIBU66w+uGpnN8GbEAACAASURBVPHc+DfuykROsMSK6O4oXMqbbZm4i0e+G39C0j1N0/ydT4urq6ur/xiuw9xv6JCJ5RNBf+G1+T+ZzBaF56Y88w0vvMR7juqeD9GzaAO6UJWZQIXKkbeyJzno84nFWA76jlVXfPTPhGSI2VKphMqRg94zlJZDe0OXJrwSTInc+IFCi0TFaDf8XL7lW+1plsiZRFUmZqkRChmFZEGT2aTAi4KSC0UFZuOQFbR4JNdYA308EaRlKh1f9Dco9YWeIy88MMgNkgNFVfRx4t00mDBQdI8Onnd7S+MjlfUEanKx+FRzxFDlyy7XTTgRQ0eWTFYzoY20+cROXrGycjAP9OlMXSaq5PnsPvDudixK4+kxovnaP/DDfETzhKsDaoFE5DBvmZsdZ9ny3+uOXTrSaMUQG7ayoBd36YWthdoETsaRzokinmiE4CxLI3ype34xPXNlkBTJkjGyIYpjiFuS0XQE3tWGL92Gob40JWzLSFaakA1Bb5GUcXm97EcWzy6MqDxijcelyKgdvlhO+hYbC6qs5FhwKYJElImopFiMxbsaL5pF3SA5cbYdjbyymkA7gSkJLRN3c+GL/sDSOF6rR6LOePMdi3LYkrElcC+ZJq6YXGjnAdkUvupH3s2Wo6rIRrHhwGP6xN08cMh3TJ1htpZKn4hoFqWp4sCd/oXQ3dD6HrVGNuqF2md0ZbgfEsadSVUmFsdSNkyhRxToqHhMn/GVw+rIpowU4AvfsTpHJyO+tKxiGHXHrbzxWJ5o7MijPLErn/mf6h85siFx6Sm2ZG7SG9YUqq67XoC4urq6+tV1mPuNvqvRXc+nsqEPEyE8EbJlUyZ+GL5yl8/8bAMnt2PSN6iQidIQimFFs8rl9ui/un/E5hVdzmguvaZ9OCGpoLRjUYr46yeuUXUUpXAl0pQTH88HvrTfM2VLVgWrKl7iPe9qx1R+7UqNHimeUCpULsRUEUbLfffKohpcGjnYB165wasGVS4VWwFFESH9+l7vJSfsBKFxmLWAU5yNpSsr2ltcjtR+pvOZyUT6SXPY3bHUjn05U8XAz/o70ImgGrp8xmtDyoaQK8iFJguT2SDsGfOWMe+oQmbJFSVqGlnJxhK1YhPP1AzMLvCzfbzswKWFOi3QXPpCdUmX+42q52P+G8ndsB8PzI3ma77BOs/DEWar+VY/0+SZ5+4j3hbe2oYX07FgmHKHNitVnJhzh0qJP7W/5zYPdCJ8qvacpcYXTY4GrzT1olBWo8SzVQea6cSzucVLg9eGfRn5Lh0Z1BafK3TJJKOp9UDnT2izsD3XvFc7lrrFMfCgnnEpwKJ4ru4QHRh1z8/KcZNPiBnw1Z45tZzzjqUy7NOIFU+TMiEXdmph1g5yoCkrOiQoitUKJ9nhm46cLEE5tEQqZj7mF/5B/sz/mP+JbZU5m5p9euVDeeMxf2HMO0a1RxtNKBEbYO0Ujczs9Qs+3DJXNS4N9NETkvCmGs56Q6o1Si30cSCWiufSY2Tlh/KZ2zRw5I6oHa5ERjRf5SOpKJwJIJYTDSIRQ2KVFo9mJnM0N3xtFbMk5nmmqqq/95FxdXV19Xd3HeZ+w9UO0xrmwx1SCVPuKCrzxj3/uoXtHPjj8SsHoHeeoarxteJ7dWAuNSfZs4kjiyge0jM5GV5Mg1jFY/mCQmFn+IUPDH2LZ8MqBoNHpBCU463vgZmlunx+WsQxp56pdnitaTlzn5+RotmVhVQ0q2n4t90fqRgoctmxeifjtGcpLY/xiVPoeLUPrGLJxrCmwEyHmgZ6FGPWvOcNQSsWE9iUE21ZCElYnAaB2WjObo8pkX+1/3DJvMsNTT7TrgNWAtv0lTFuMB50DtzqA0PjWHVLtwon1eDmM0+uYVIbQtbYuNLFRBUTJTa04Uw0mUPd8It+4HF1PKyvfDBbzjTkolmV5sk9khBeyx1VOeNKYWBDdsKSIgvCRINOK1lXfFE7ZmkgZlRKEA0+1wymQdeZQ1GsYeDDdMS4SyzM1LfUPtKqM7s04ZWhlMRz/pZYZYa6pWRNlgYze36ML/Rmxolnig2f3OMlhNlmsovEbDibijpEpBj2wTBLhVQNRVUEpTDpkhc3loJZHXr2dNNCcg6vQZRwdhskFDBCVpqIsOiGJbb4HlzJBDRJDFksYKkXT6oDtR5ZnTDoCgkJ8TW3auTBfCWJQkfFk9lxki3UgpiF0noOasvRbtjP72j1iuSKbOAge0bTMdKTQ0VVFsLQsDjFLIYoFV2aCcpgQ2Yvx8s2pjHUBUpZsURIhc985F21DOryST2Uy73ZZCwv5R7lVr5MbxQpf9/D4urq6uo/iOsw9//j0XzD7jRS9IBTQm3PnPSeF9kzGmHZtEh2eNNQJ0+kpvcz2QiVLMSk2ZcTXfK81C3BGKI2fM7fcutf+T7/G1UZWYPlqzHYUl32lTLoELA5YCicc6DlTMIylYqkNZaAVoqP8wGlEwd9w0H2dPlMkIpdHAmqRnIkF81StqxlwxAmntsHznZLlozNhS6P3KUD39tfGPOWz6ZiaTxmKXhtKUERTE2bZm71GRMSRme8ashFkXOhWgPaClPV4K2mW0du4jtz5UCvrLnCp5Z+mqhrj82FzA1ZAqO7QadC0IpmKmxioJkj9/mFup55crcMoSf6mlPZYXRhE47YFECEpYKQGx7yE7NrWStBx8ggDb8EjU6FhsDUaEyJlLxB8kRlJ0a1p/EBHywKwDhCKjRloTYT1i7YHFhTjfVvfEwvfLO+clNOfE3f4YviUCsKhUltfq38ijjxjMrCanDFI1rY+xeStQSjWcXSvUU21YSKhrWu+Ev1EZcK21i4e37n00Y4uYbgINCTzMhjeqdxE06N5PGW2FlWpenLiMmBRTlUyIy2I+CYdEfMhdnUuLLQ5IjJiofhcsnnpjrytfqOZ/nIe/fIdk10ccCEAuHS/PHUPTDplqasWFk4655ZXz57nmRLs64sxjHohkF6tvmFm/DMbDaUZMgbzVFaQuipVMAthtv5iA6QG+jKxL/s/hdsWpEMyheOcoc3DVWamdXlB4SmkAmUlFElX/qLXcZU1+Pr6urqCq7D3L9TslA/rZghEu8vUQgvbs9R3VFEsysrBmHnT+AcKWS0rDyVHUpnfvCfmHXD796e+bq7u+wSSU8SIevAobrlNRw4c0ufFqKc2U0zpeWyhK5h0DtUmCkm4sXi0STRKDQmRXbxlT+sf+JGv/HP5v9gqHpG1bDQokrApZkNCzfxjZaVkiqm+oaIQ0tCk2ll5gOf+S/Tv3Fbv2FSxbkkQvYYVRii59jc4PLE3Bm+DW+82Y8klfgq37IaQ9CWvnhM8bg80cqZ2VU851t01uyWkSYfeAzPbOyBUSt8brkNT/yp/5HZaiIVFGEfX3jwJ3bnxMf2xBzgLWXmuqdo+EV/4EX2iAhVnNkysZMDTgVuphE9O3xOVG6gMTW2ukSbtCkhcaIZNL7LPG/uyAjeWH7//pWD65izpp1GTrbClhWSRp0dP7qfcHXCI4y2YRLPRgaGXBinjl/CR5IrhGRJArpE/uJ+T50GqjrQ5QklmaAqSoFEulxS6c4UpYm24j68YkwhxI6xTRSTULags8FOBQkV7RL5vvoJXwqawFxVFBEkaBZleHc7oihWbSii8ErwqqYqM8KKIGgSW3njP5cvnOeKIMJbc0eisOotPmXwlloVxJ0hJ1TSWBHanLlNz/xV/Y6QNV5XdMzgwCSPqAZlZobS8W1+ok4LNgkbd+RZ3TJKSw5gimc1FVSJz/aRoWqYxGEpSBYa6bgLrxzUPSbPiNrRlzOdWniXjogQsqZfB7p4iyrq731cXF1dXf2HcB3mfqNkeImagkFHRa8njrlB0IiCGcNBtZhqYbWK1bSYsnKsHlAUouoxJfG1s/is2ecTf64fETS2vOOL4Wz3LKrmbn6hSiuf7I+UrFm0xQlUTGCEj+kLjkgsiqPcE0XwYlG+8JRvscpj1UKbFxax5JKZzQZNYo17dBGCckDBi5CcIGQAHvwzD+GNXAl/kR/5U/M7JtmQKGzDis/CWlpaNRFFMxgHJVyGylRoycTs2fl3tvGdomGoO1YRTu6Gj/6V2GrMrJhUh7fQyQGnJtZOI7lgJEHx2JzpGanDxE33hbI9E21HS8PWT+iy8Cz3eOMoGEbdUK+BlAx1WRmkY1EW3wqL2ZPQ1AycpaZOhW5daMiclpbnfosuEW8MT5sGUkCKohoLnffcDDN3EtjPM/Vpz41x/PmhJrvELC2nUFPHiEqFSsEojpKErDUlVRg8WRyL1ISqZr8cSKpBB89NOHEfDpQCKEOoDENlQQuv7pZcMrYKfMMTO6l5z1t83pMb4aXckxSYMhCN5racSbkhmgaVhJ4JIxUqZpR4hrTSZc9Ga27Lge/5wtZ7/iDP/F/V7/ha35CyIuAoAskY/GgIcUNshJGOJIm79UyfRzY+8jCdaWvhxWjqoqhzIGqw+ZJTF7NlcB03/kQVEosY3tXleWzKwHfpZ7q0EI0CJSRlseLp4oTNnj+Ev7D3Z37JEz939zRqRESQkMEoLEKgIeWaR9uSY/67nhVXV1dX/1Fch7nfEGs5kljjiKdldg2gQTKTdCiVyQgqBXzWeOUIdJRyCZU965Y9Z5yf+WI+Muj9pe4onVE5oqUQtfBuOmz0mLPmziyoYnnbCLOtWI0j20xXoE9nFiomqSkRrFrZyYFzt+Hn1fA3+YHP8h1JaYoC8sokFV/1HVUZ0CSsObDoWxQFE0Zqgbv0you6w+TCkLe8yOVNh8orD+sT3Rz55Cxvtw6VErOpoAS8sgzaoUQoSsgm8zC/csotX6pvSMVyMjtK7qA4pDzz1d1S6ZmeIyrnX4veG7o8kdHo7DHujCsnjLwzq5pFhFe9IaeMEkvDyJO+BzKBmhMdR9nwGJ+ws+Kj+0xIiaQNKp1ZXIvkjK8U+3XmWPe8Vy2TdrgsbMqISGSjA3Yd2ebIYdmTlOGoe5Sq2Z5fUK3QxkDygdHWiN2h7cLUBGp9hNiSXI0piaQdKw6vNLt0xgJP5hvwBikanycGvWNTztykBVneWZzFRY9tblA5EQ005UjiDs3lBu572hGyY8ML3y6f0LOh15GmvHKzwp/rf2BUDRRFEya29kRfZvo0cj880bqIMwt6teR0wJmeTVEc6MloFJ4mz8yd4zVUzBvH3XxAoamXjEkthQldKbbhnRKhDxOmGuhDQBNYXQMIJgdOqmfTn4kYNurMJg68q46prpmLIxdNVUZMNmAcs2lwyRPEgS18Y35GZCEiPMsHVuH/Ze/OdWzfsj2vf8fs/t3qotl7nybz5j03CxBIFHh4eEhY2Jg8BA+BCQYej4CFyyNgoSouKq6qbmaeZnfRrO7fzW5gxFGplIlZUl6J9fFCKxTrH2HMGGvOOX6Ds9whVaniiKXh8/QV4247czc3NzdwK+b+wlINpSrtRrBdpjMzffWstYCbsL9GrX7yD0xmiwiYktnojKtHwGCZWILiWHDW0RRHY69UE9jokaO5o8sLLkFD5OILH7sDYhKLKN2vCfxGlFU7knEM9chZ9iy244/+7xj0yL058+TuiGKo1iBSuZqWnBtqNSiZq/eMv3az7uoV0bfduS/yPW2Z2ejMFx4501BNoAeuEjj4V367POPmlqG88vNuy6t7hAqiSihvI7zu0oXNMnFxPXVjUWOwFPb5/BaA3E88de8ZtOEX94jPiY1MnKSnZE9XzjiptHXB2Er2MNlAtgWJhW+mjxgd2Puf+T/Nf4aSOZo9tVoubsA6xfcZqTMiSpCIFSWWhpp6RmupWIpVNnJioy1FPN3ydtRZiuViB9r6QudnnJa3cWwY/vjwgA0Lx96ByXT1hNDgs6Wxwn0680SHrW8j0YypPMRXxtAwmAtkx1Hu8WrIGmjKC9skRL1ntTtWYJuODCXR2kIRxdRIomF0DYs6JtORKpgsCBue4yPWGbq0stfCUzhwvzxxpw39OnP2PZMbmG3A2cQqG363/CtkjNhSuG48n/tvuMqOJB3bciWUzFAWinEMJvORPcUpO/vEB7tQrSGslbB85dx1+Lii2lJWS2otd+PINSlfmy1Hc4e1labOIMqFHVSYQocDnK7sz1d+V/5Is/uAlUxXI9/pM51ZGczEUzm8dStLQysLg1n5XCHR0K6V7bIwvPsb5NepETc3Nzf/f3cr5v7MdV7I6wvd3Secf6QzBqGjlZHIlmQdFZjYYlQQrXQlEjQSpNDmifvwwqQ92VUaEzlZg2hPqxFVqKay0StLaLFl5aBf+eQGltpyNQ2mXsli8Fbo5cLFHghxZfUtu3wEBCOWz/07znZPtC2Gwr6cqSrMeBZaVnE0mrAUrCTaMqJ1wOuCNZViDVPylKp0rERVkEr2lS/djpoy1SgX19PqhNMZFfNW0JBpZCI3hZdhYCoHduuV7C3WFvp6pVkzqaksWIwGpAhOIhHB6ApRqOqZGseSNyTbk5PhRXa8uC2zG+ibhZIMBzU8Li84vbL0Pcl6irPE4rCsGDKdZtq4UpeOWQwpZCaj2PVtJuvX9kCylvt0pKmFqTiaOtOVKx/0CzkHTnXP0hVyK2iAB7myAX5x33CVhqvd8535wqE8cWbHIT6R2eFlZQkDQ7nSrtD5K2veMNSvxHVgYYtbhc0UaKzS+zNfzQa/BDrr2ZfEuR0IsuDzjs4Xfg53jNZjENwcOSyG5Aairzy7Hfu6oKL4AN3lQo73DJK4eAVXeLEPFBsYw8DfvPyJ62bLivBRvsPLWxd0S0ZdZnaWipBN8xYALS3Cltco+Ea5dB5pZ3IpRNvyUg8Yn9nJV07djrF0FGMxmml1wdmVI3tyVU50WAqqguYWz4U7e+S6bFm9Z5Q9zwx8VyLXumXyA+/qj5z1wIkDMw6kUjIs1lINfBge8Mb/lVeLm5ubm38absXcnzGuMtlEqJWM4Uf7LRd6gi78tvwDRzlwkQcuVnmbdaC4unKXX9iUFxY2jNJzlQ1RHKYYnIFaHcZEZukJktjMJz6HjsnecWaLilBtxYpiVRnSBYDV9EQNZLFk9Yzc4WXFl4XkGrJ5y4xzZFBwxdKlwiqFOTRgIeM5lDNteZsLGp0jSSVpYGZADGzThdW2FBVWF7iyZ+sX9vUVkytH4yimY6YhE5A6k8SxWy6U2pPEUC0MeuX3l3/k7+I/8g/+n/GP3XcUA0fb4HnLPgsiOElEb9lOJ+a8g7NQOk+sA8lvsdFjLW+dpiWxOs+deUJs4vfpHziaPT/bb5m1IejKdl2xwCW/Y5gjU98z2w0ThlYL3yw/MtSJz+GRUDIfw3comT/Iju/jVz7LgcdyhJjAC7E6TtstRkaSa9iYEz5HTHV81g88iWNeB5ysxBQ45DPvTmcasyB+YUgnJi18co8UhKEcqUZYdyurExpVvp2uaLRIM1D7QFAhmZaFyEW3lGTYmCthBW8yyTteNo8ELZx9yydjadbCVhdyo+zHBnWWLq1k8awGWpnBZCY/cDaOjZmAgih0XGn0RLQdWi1BM64oVE9fZ7Z6ZGtHRAxlDYzOMUuLpdKx4PNECPGtw9q27PVEFUuXFkbteTUfWI1nbTxeKzMz9zwzGs8v3TvOZkejM6UE1Diew5bFfIvVxIsJXM2Wgudo7qlFcEC1wuf7byEL3t6KuZubmxu4FXN/wcWVu7Twb/r3/Gi/5cXck9WgxrKwsqkzgU8ArKVhWxe26UyzJl7CB1Rh1YGMI6rDidLlC9F0RPUcuPCgX8itshJYbE9SRwIiHgQm03BwCSmwaMdOr2QafJ6IGkCVqoKrhbZkolW6uhDqimciuT0mWWyJtGVicp6gC1Yq7+yPfJFvqAS+uDsmtjiN9DphZGFhz0f3PYs07PQKsfD7+CewHc9xYrWBoAlRIWiiqUJ0DU1uaeeED5Fv23+Na07EoKTS4FIleSHogrczA2eGPPEsD0TTsWTDT4ff0K+ZL8Hiy4SziWAWshZ6v9LrSF9mJBUmPxGoTGVDpyNaDee6RbXlZA8c+4SSuK9XivfUzpOdo7dnBtcxlh05W1qdKN2G1TS8BM935ydcCnQK0UcaqVizsqrj5LZvx5vrTEuiFuE4dEjxpGL5sDq+SV/pdWZqG3LNHOoL+tLyaixra7nqjkd7wjtlQbkOPaUaTAnMHl4bYfEbLtbyvnxmrIHFtTTZYRRCMr9muRVsXd7uH1JwWonSof2CdjOP8sphMfzYfMuqDRfZId6wDJ4xbyjG86IHeiZGtyPIQhDIWKwmSI7ZDfi6YppCpCe2nqWxOBJaA2Yub39btVQjLNIgxaII7xfD1G6ILrAYj4rhLr/S1yMkx3N4IPr3WI2Mcs/it/hSaGWiq5FQZ57te1ZatvpCwaDytiPXTzM+rvxpjPwXOePcbQm7ubm5ua2EfyafJsLawZqJu0CStwiOXXnhUJ5ppPIj31GrwZFxuhJNA6GBKmx1YtYWa8BkpRTH1e7JHpwsSCnc6xNVYJKekQ2UggO2MpLUEmpB1dDVC14qU2xx1hGL5eJbUhUW09LrglXY5TOdjDiJFAYgY1zhIBOzdDh9i35YCVzMBlsL+d/GWDRYLTRl5ZCPvIgy2h0qwmo8UWBwz/xU/yNW+zYFQdQw2QGXC5P1rMYxmQ02jLzPRz75D/xL/jmvbstoW5bUUi1UAV9WmpLYr89YV3ly79jkiYtpOMwXXnyD+kI3joTeggaO9m2qwN+Yf823vPB9/Nd8CI/Y1VKNkmPAlpWj2zLoxJoPLJ2SquJ14Tu9sl9nfI509isnibzudkymJxDZlTOTbLn4Ab8sbLMj4rBqcB3sOROjwVJBPEWVq3tgCoauKrt8JBWl+oVk4L3+wif3HomRczcwpZZoPb298jo47vyR+/yEXRLP/gNXt/DcHpicZ8cFqZWZDlsEvyYCM3PY8Uk2+Euk9SPJdOTiKbrQ1WfmvlDCkcYnDvkTOOVx/sykB06yY5CVTTyTakujP3LWBzZmxJTIqRt4ZSBKxwMnqnFgV9oYOZs71hAo1bOfrnSaqNrSpRO5Fq6dg2oIUvEpkcTiipAIBC1MdFQDMRgOOdLoyJN94IVHgo3EYinGkq1ltY45F4p4JBWsFH7233PiAdEVxONLpI8RezwyzzPb7favvWTc3Nzc/NXdirk/44YB8ZnWnxh0z51m1trymM/sFtilE7HtOHGPGJhkC0bY6gzioUSsGmqFYntWEWbncVJwxXBxe34sPxCkMNee1QQQoWGhzStCQ69XUnWMekByxVnhw/jMT80HJEcmP2Al4jTT6YVBJhzKzryyVAh1ZpIHBp0RMUSNJNcQNRDFgxqSWrSat7t0v4bCBrOiVsnOoyosGli04ysPfLKPjG7LxJbAQsiZJrasxWKZMVQm0xNrx5kDi2v4UL8y1gOSZlqdufgNs7Ts04U6Njx3D5z9DmMge8PHd1sSnrvxmd4n7DpSjQdriQpXvSeWI2f7gT4v/L78kc/mjpf0gSe/5WQ+kBpDv8xYFh7TmRIUryuj73hwE0ktZmr44fKFq7RcvMUtwvv1K4/xwmY8sUyR178VtiwkDNe1Y2k6DuVCsspWrxizEtlRaHFmpXhDnkE75aVtmJ2wTZ7GjqgKV93w4F+w7oUXtyGa95z6e3SsdP7MbknE/h1eJ7769yzq0OppdcKqpZlGYvAEUwi58lB/4f6ycjkY5tBTbOUlDDyWn7i4HTUpc93Sl5nGruRsqKbB5srCniVvUA87U4ixI7kNUeHU9JhJyDZAW6nBskkT1QYkAtZgZSaHzMn2nF3PNe9ZXIu1lWgMXzcFBB7TVxq50tQLd/XM+/SRf/T/jFf7jsk0ZBG8ZGbTU4shmISayFl72jKzyy+82C3WVKoP+DSxmRd+8/M/EN7/J5RS/trLxc3Nzc0/Cbdi7s9sHu5xv/uOu5//d74zEdVvQC1QSSXwo/s9cRZ6Isk7VrG0kjBGsWXC17fj0avdglai91SBkx8414G2rjRVceXIwEyoSgwWi4AxtLpgNJONI1pPVUfFsTUjSSrnbqASgEDGsOPtTlxTV0xOTOwJ0pEkIOKwRIaqXItHq3B1WyKeIOvbP0w5sslXrHs79g0lstUnqnnEu4QNmbG2qBiaMoPvWVxPtBWjFwaZKW1LxLCq4avd8e18JQ6Bz/V7vGaaCpCgGgzCkUdy0yAWtvbKHFraa0Qbh6kFZ3l7z9ozmj0nO3CQI2NeuOqGr+57+pTY1sjvxiPolkvT07EwmQ1+EaQzbNPIWgU0UaNl1QM+BY6dJ/lCMpUP85GcHfjKF7PlKplp2JF95NpvOaRPZN/gUibi6XOkrSvP3R2HciKayD1PXMIdn3d3bOXI0Rw4uQP/avuOWjzdqZAMNOWCFEOyUFTJkpl9x3PzDSKJPo1IFqw4or7DV8OoHtvPRG+pQB+v7E+J2HWU3jB6yMGSTeWL/Y5n2dPlmQc5wioYveKvsHY9x3WPzyt6afiN/ULxGWNW5mEg5InsGhZtaNuMjZbVbQh1xojlPj+xryOL9Eg7czZbKEpTlVgLRSEwU+nxUjAqdGamIiiWz+49szSMpmdXj4huULGgQlcninpsyWQJICspeL6rL3yWb5mkUGjw1mDczNJuONmCb2535m5ubm7gVsz9BUtmv5uYXrZ4XbG24lJijRvcmNFaYWtxLFRtechXHs0RLYKzCacQzfDWVep3byO4bCQD0bRkCRx1S8iV7XrhbAWDoc1XihPu5xeyN4z0ZGOxVIoIz/6ek99QqyKm/tvmi04nknhGc8fVDrgMQScchSwNbV3Y88KKZ5QdV92ANUTTcsgn7vRIx0IphqCVjSwc8hXrgGzf4iX8loXAiz2QTcM2X/FaUAFsBLVksSgNR7vHGMOH6WfEFfox8TX+DfNW6CQjEshOWe2Ec4WFlo1cEO+YrWWVwFPj2aYzmzhxH79SQsGnzFf7nrlumPzAh/LMUgyb2bBpV6iByBjeywAAIABJREFUbU4Umfi+/MJx7TjXgbE1FGvYxpUTB1JtuThDFEGqgRVewh6hsjYND/6VRS1DKCTgtbl7m+DgLbkIDV/p8iv74ujzzGomOs0YcyJI4lUecRk6KaypoEthGQ6YEvnZPnIoz8Tq+WgeaLrEu/KRXBVdGl79ltnucdUhVdmuZ/ImUzXRlwnVQttcSfeGpMJkDdn2TOp5MndEPIZERVncd9wtC9bDQ1zo8xWTO15Mh24LLwwsbcOH8hFxilaHIASN9HXE1RYS3MmJloXWXFHxZBe4mJ5Xt8H4yiaPb/cto/m1gacifuUujWyniXHYcJE9R7Ml1YFROu71lY29YMkUhFQ6FJjswCgBrw1NqfRyZSNHrhqogCPi2sS8abDbt7F0Nzc3Nze3Yu4vlci0ZE5ly2g3XOQecZlVB9rNK/t8YpQAZGJe6ePKb5fP5G1hl174o/07og5kW2nzhUe58MoOr55gZrqccLryYfnKIU18txz5E+9wolAXmpL40n/HYgLJODZlpi0jXhJieqwZKAiI4HJitj2JFlXFFUFSZHZb9ulM56+8Syde7BZXPUEKzimqBQGasnA2d0ylMIWBIV64r6/4NWMGwRNRMXQy8T5+pBrhpDuqt0h9i6Co1gCZ1bZodthquNqOxm3xSSlmBpsYYiArJN+wn1/ofOZd+cSzfMPj+okn/zvaMnI0K1EaOh15GbaUNrDahiqFoUYOcWEZ73muf0dbT+y3nwj5yl3+CHmgjYbH+hn0kdOuJYbAmA0mCG1UfDgxhQ9kAVsrl67hJDuCi0yhx7sFkmVxOxop5OpR5+jLQpdXvGYW15Bty1PZsElXtnLBNQ2rNWSjmFy41hYtFSWQtfIurlzCwNkIzTyRQkOfFs7mgMuRGAInu+NpeEfWjkYLXc18u3xmDMLYBBoZSeJJzjHJwE6foTZYC6rQagRjKK7ipbBZn1FrMNG/HZF6S2krrs5c+p7kKgst++XprcEmCIMd6SVzmD/hpg2d+4RuZhbx5F44igOB7/NHsjj6MbNZXvhT+A8Zu4IxK6ZUcJFr1xCtI2tgNhs2ZgRRtrwg2dHpyCf/iDWJWh3bfMRTaGXGakXrlkM88hoe8HrCF2GjE6lvOS5HSr4ds97c3NzArZj7C0upfBrhS/qG57xldZZ9vdKYla09E2ri6APnsMNQCSXRmsRBf+LqWqxbqRViFYKNBJ3I8hbNkOtbc0ObEiFmXpodYt86BzGRnXlLiAsS2eXXtxmVuuIwZPV0RQnlmZPdvd2FkkTVgjAzyYZZDOIrG73Qyoxq4Kt84MVsqcYChaaeKdJSs7BKS6mBvi74ZWWTruzNEQ2Gb/hEKY6T3fIkD5zCnmh69nXE5pXHdESN4+T3bMoLFMtc7llrB8VgBaRW+nnk1R7w9DQpoTi2KaPRUH3DN/WV4AyP6xPR9kzNliiJsRlI1qEiWElUZzGxMDWB1UBSZcXwf21+ICQhOeH7fORDPHLvnpElQ79jlveIy28hugV+5gPPsqORC8bydizuVlyd8YtnYxLf5Y8sa4NNC3PXUvLAp2FHLQUTHKsIm/xCKY6uVAZzZq0HPrkfiNpRjeWb1ye28plNVD6HB6QxWGnoL4lzv2M1gZfNDluVJveQOpLraUql+bVodDoy2YGTb9+y+crMfXkhh55atkwyMJQVY4RNvVKk0tUrd+XEk3vkj5vvaHPirvuJdy8GK79gkue1OeBipWdi1oD6yiaOmKIYCn0s/G55xl6e+fpgWWPHl807SnYsZiBEAZexkvigX2iq8AdXCAhUT1bBaqHGhp5CKFdGGmoxGKnU3LORI8kFfBW29pUijmg8qQxcZYOXxB/MO0azpRBAIFehLZVuXtmbd1hn/9rLxc3Nzc0/Cbdi7s8sWmF7oPmXf89m8Byd4WwO7OTCxrwyuT0Xc+DierZlxjULNUZybfgkHzjpjklasniMRmZzh6uVXZ0wKdNNC85l1MMoA9H0nN0GMYlaPYO+Qo1c/IEZT0grLk7ksGWTz5zdwL6MbJgxmrFECoZQMxTBC9hckepxqxKN5ep2LMZSteAlEiTha8QruFyZfIfLBTHCHLa8i0+MumWuPbU2UMF6sFUBR8+MrY7ZOowWZrOjrQtNemG0e6xmDuZEtpa+vdLOiepnxDeggVE/8O68sNiG2ETy2nA5VBp3pLUXvDXE2nIxLbZYXI2YWjnIFZzS2xOlKTzJe0xw3JsrFqizZ5YtV3/ivAlka0CUXToTEPoIV9ezLAvOJVw1/EZ/Qd17YhNodGbJjpN0dMvCgxl5moS58xzqE6fuQJMjn+wHtvKKWENTJ2y19DmzNSvb+ciP5jesTU8KnnNquI9fmUpL55WxD4yuYUiRlZ5NvoII+3zmGgILDWqVSmRrj/hq0bJhl69cmw1WDLU29GviIY/UCp1NTNozNx5TC1/cB052T1HPPWfmznHdFtbs2a0LP7m3bt2LbkmuJTBy8g84HXFWWJoJ039426E0jmzq2weC0GIrdPnCt+MvXNoG51fG8R2FwLoGrj7w6n7Pj3xPMJVvy0d6rfww/SPRW5I0zM7yxN/h80r0DaUo95w4pBOjDMxuT5b4ljknFSGj6mm0UNYNh9OJ397f0fr2r71c3Nzc3PyTcCvm/ow1lpKeaNqEz8pd/kS2LZ1M/Bh+y6QbSrY0OWM1Ykrh8+aen+wHXthw1T2LbinGEMrIYgdWeZtHeW+ObN3C1W1YjVL8ykjH5C1tzRSBaxsQo2QVgmaqBK6+I1ZhsCc2CgblLp1ZTE9rL0TxZAmM3lMxdBhicdzFMz81d4gkghSSgmAoClk6xK5YzYRSafOECFxkoHcTvVxIuUH8xC/+e6oIEY+rhk2OzFZZTKCtIxfdUNiw9D22Fgzl7X6ZZpIM2E1k9YHZDbQpEr3h3FhcaVFrWRvDZOHMe5o0UayyL8e3poq6AzEYUSbTMnnP1QeMZkKZ8WnlKHvaVLiGzOKgmA0v9vDWuKLKiQPfrFdOdcPVdCQcq+7otPBz+1uqCC5CYCXRc2mUguV+fOV5/8AcHA0RQ+bqeqJxOAWTC12NHPMHiiS0OkYGcvJEGhwVGxJVMy6soAnjhAZhl0eOTSHbQvaGOXRsypluyQzpSpXMXfrI2dyxhHti3VKk4uPEGDpMbbh/qUzDmZMHGxwP68gld3zZfkPEU4LBpcwv7QMyTxjZ0erp7eg8zoybA5bEbHYktfjq+e3rV+7cSJ62jM6z2rddtlQCIoFgF2JoOJqe1/rA2W0pQ4Mtr1zbb8lJiI3HqjCaQr9Efjd/JPsLf2//YyZ6qnhMSSTbgsAiDTYu9OVKsJmOkWwNZ1ocQsUiKN9ORzbzyrtp4vd2cwsNvrm5ufnVrZj7M0Yr+0lwds9z+8CzvQNTeUhfOYY7pFhO7oAhY6XgRN+6SedKbVpQy1aPqFSCSYhAp5FJOi52AKdvd4JKIQbH6CwFZdVAlYQx31CNImKhKqYoTRkxzrC4HlczVSutrOzlldVYFtljzITInqGMWJPo85U7feJZWlrtmIwlqLDQ0pfECmiprOIwKpya3Vu2ma5MtmOXjkxuYMgXquftfcWQjGO0A0hHqJmzDdQsVBsoBKxdGNLCHTNGFWM9j3EmcuUXb1HrSL5j7ZU6GxbpULtQxHAOG0L1wNtszyyBvsyQDffTgg7gmoXVHMgqVHF8KCce5pHvli9c7cClG/jZ/YZXO9BWZVcvmOq4X7/wxS9U55EKThzb5cS6sTiNnNuBWgMiiokrWTf82HwPcWWwM7MzZNNzqXuKCaTqQTrOGH4Kf8sjX/Bj4bv8E7+RP/JT9zc4LZzMhhf3DrWZU9hyyCeCVh6nI9/xJyQHXpuBPzQ/0OaIusTD/EJuPUlaenfmbnliowtHt2H1La2ujI3j39wL3+vIIc/MtmEpDTUMWAqdJC66RxSidvTlzJIMJYL1ytp7jFZWaTmzpTERWwvX1qPaQetIJZCyZbAzhzFy3g6AQQBq4Wm4Y9UPTO3AZr1yDA0rDattsXVE1HNxAx+DskvK9/UXvC4c7YFcW86mxRqlFfil+S0H9wK8faiZaVEcwkonMws7Lu3Al43h70ik6+mvuUzc3Nzc/JNyK+b+TD4txE8KG5AALZGkUBGkKm2dGO3APp15lCd8yTyFd+QQGM0GVyKNXbirLzQsvNYPTASohrZkauqgXTAh09dIWzNeL9Ri8Sbja+S1uaPRSKORbRzpJLLmt+MzZxJZLDUKo9lwpeFi7ljFskqHt4WtPPNef8EOkW/KVzZ64hPvyCWQ3VvobXQdVd6CcAedUa3s9YlSHWoFV8CaFS8re30BEUQPBE0MOjHaBmGmpzDSIUDHilLBGPIyAKDZ8Tp0VBK75crsembxRBWuhwFJkRzu2KQjjSpbvVBroTGZhpVGIRtPdRYpFZuEoIVGMoVAyS1GZpauZWksJkWktvg1UWyDRlgN/Ozv+eofqNlSPazWc+gUCRWfMm1ZibEhGJjtlia+kgtU0xIjaHV8W34iNluupXKRRzZ55Ev9LaPs2bBQmshgO3xVejmDZt6vR2x1tGtkCh3Feto60+jK3eXI0R24hPckDZy8QfCYECEUhnxm8Q4tymx72jQzy0BgwoiQwkTViUEn7s1XqrW05YyRiUveYVX52/nfYGpLHnt2q2H7miH8xOdmw0N95lICOfxAMxfUWj6kLzzYJ4Iqs+n5Ut8hVujyjM2enXlhNcJaWoo6bIbYGEbXUY0jlBW00JaFoV74ED+z2D1XGTjbAV8zO52ZdeFiWiqQxVCKoxLY6kQuJ3yBc/CM7FnZYmSm+oT6K8em4ZNM/Lak2+7czc3NDbdi7i8VQxcDa91wZkcWy0hgdZ5oW45W8FXZpQvVWb42jzitoIVtGbmPL9RG+WH+A3mAT/WJIu/JdBhV8IYuJk5mz9x2XMwWr5lDmmnthY1eKRLY6JUhT7zLn6naE1ul1IBQWGn4FB45hntMTcymYdCJnoW78sw39Ss/pD9QfKUUz5rv8NbQ1ESuiQXLUBcKhcW0hBoJmjFVaDQS8gjWMMiIzYV9PPMUvqHRkcUMpKzM4oi25y6/4KyjW1cClft65rv1xKHM/N/8B3zsOpZVSb1SXUMSzxpaBheZXcd7SbRp5n18pi+JyTioFjHKXjNaYZsjP1xeeQktOQvjsOEUtjSlYMTg2on3/BHsPYvZYFcY6bEpkYzizZljOzCGBskOXxdMKvT5zLz2ZCwbnYhGeZ+OvNY921lZ1x1cPA/9M62MxGDxtQCKNSszj8zaM/YNT8uB1Gf65Uog4ZsrV7tjiCNP+sghJkodCCsQlbgcGI1BiiPGDdtTQrvKkBOtqZQYePUH8JF39gs1NkhWNnWEVhGUppv5wiMbfaZWQ58i91RCTpz1wlh3hGIIacZLRuoV1Sc+vAiL7xCuOHdHrV+Y2GBi5rG8cNBnvpoPfAn3fDaPdDKzkQubekV+nWyi8hafkpwhi6MaQ0QYTGWXn3mMLww6ocWy5Jb3+SODvzD7lp9lw9G/B1HUQMEy2oFFOnyOCMqkDYmOirCQUXZk13Pa7hkeR37Kkf80Lbdi7ubm5oZbMfcXwhBwpuGbS2E/LRy7htntMVawJmPVMOSZ1p3p5MKT/DMUZZWBh3Linbmw1kzUnmPesJiOrRzf7k+twtK0vPKeZIUuXbA+M9HRyMSQRu7LlSSBfX1m0h0nu2XRA7YUvtUnTvR4v1AVpCq5Oiazo2Kwavg2/cygEzUoKoqUCDazXRdW59npK2J2ZBRVS9LEhgtKZWee+d38C1135kf5W9ycOdpH7vOFOWz5TfyFj+4DFz9wz5EzO6rxGFXu6leybAjMTP2AK0K/vjJoBNcyytv4rFw9RipCwohjMUKKLaEIm1zJvaClcAoPbNNMNZ536xGODd22MlThffp/+Bfb37FKx2xbTux4kge8wnY98rVsCRpoNXFud5xlhzEZWyOeCZctXT2hfuVDfWawV575gOIYaw/ZwcXRzYmxbbisO5wK+/nMpEBzxLUBR8/Bj/TLjOeKTRMHOfGT/xZnW9oKW/OZGh27s0HrZ5RAtA2r3bKYFj/3iHZEt2VbT+zKwrHtuPoNKShhmTiUkZPZIR5cSTTpQi9n7nnls3zLbLdM7HhplFAiqoajvWdbLyzec798JXqlbRPp3rPpv/BNSGhIFOl5qAG/GkK5MJhnOlt4V165pDu2fnybDCLCLhZcuhA08WJ6Piy/8FP3G+7SCVFLqjDkiQ/1Iz/kP+DIvMg7jm7HL+472jIB4G2mszNtBauRrswocDEHKh5JSjYGimJMBrEUVUQqlszsPB+X11s0yc3Nzc2v/qrFnIj818D/BFjgf1HV/+HPXv8vgf8R+OfAf6uq/+u/81oB/sWvX/5JVf+bfx/PZCzwzjBcM4/pxNrscCYx2kBky2CubFxi0gGtlrXuyJIQLTxOX9nVC2ML52ZLKh1Wy9tYLWfxFpoZisDFW0Z7TxVhWyb25YW7cuIuL5RoGPxIVseX5o5aNyz0NHXLzr9wsXtG3ZAwuFrp6siuzGR567z9af49q9nQ1ROxG7CSceuVWe7omPA54teRsd8Q6kA2Di+JnAOaDYd5xJbPqCgjd285b78Om+/iiHUVMcKogtfMmhwv4ZHV9Bxtz7t5Ykr6ltnXH1icQUolO8jWYLQSrWO3nnm/XtmPr7xrjqzmyuweKCbz5B9warEmM9U9BzmzmA2za8B0fHe98qntIRY2dqX3E+/kSFgtdfoBsY5lo3gKjbkwmY5OVrb5zL1eKaVjyYFGG7o0s21ntmbij+0PmGg4bQbEZqIPNFpgPlMtxNQwu46UFVym4wWfrtzpz1zCwMV19PbKTo+spmdOW0J27DlRjMPowhh3BK1cm56FjjaDzBnnK7PvOLmOSkufXshmQ79cqTqjovzcf0MMj1hgpWUtPbUe6C4r57Ahl4iYzLwZsLZgpPDqd7gWZI64S2AZKk/tjskNzLZjuyQ+yBdkqVS3Y7w4SpMx4vCuoNVQjOWQP1MaRVbDcbshKUx0IG9zig/5xG/TT/T+ROsWjuk9sQZEhWUZeD4c3p7H7HCScEQO5RWS8Ny+Z3YtoBiByfVEDOBBE+CJarkaQ/QdvjG30OCbm5ubX/3VijkRscD/DPxXwE/A/yEi/5uq/v2/821/Av474L////gRs6r+5/++nys76JpC2l4ZXCSYQK8rtkQm7XhXvjLLnhda1uAAyyQe7wqnvsXJmUFeOflvmaqj1kqMgft1pghUWxhlYKcJ0ki2nm25soaBT2Ug1itXuSdpx4vdc5Ge1bV0acVIZaMLXc0M5oKUSqmepJaCUNVRNPDaPrArJz6abwgyIyjVeQJXdlw4ux3WFTomNvnC1/CO1bQsfsNP7m/Y1QvXPDC5hsW0IMJv0h/p7BEj8Freca7vOSwLq30kVsfSVPb5wmo9x8ZzbHbs0pVsLEOZWY3HVcXy9nv0zNzpicNl5b2O7PPM59az4pitJ0rH1Rnu8ys1ZE6DcGlaNnkmt4Z+TXRpZa5bru0D1/HKJnuO8bekMmClUrRikyPSI1V4Zz7zUE90ZuST/C39WqnSYLShXRJ/2n7H7Bve8cqqb3fuhmuldpURj/MGnwasd6gzbMePmG2mzAtsDbn8v+zdyW7tWZbf9+/a3b87HbvbRERGZKarJBcMCzBQ7qBnMDw1/AAa+RkM2CNDb2ANPPbMhgcCPDE8MDyRZrKqVKXKVEVGxL2Xl83p/u1uPTiBQiFThlSArEgb5zMhD8n/IUGQm4v7v9dvtRQLjY/ok+F99cxqGNnESDGZbh5RKvKr5iuW1aXTM1QjcbpD60SuoQqeloUXU6FLg/WRqs/szY6D7XjUd9Rlpkiiixu+GD7xVL7ixd6RoiaYikom6jJcst40l6LcrXl1LcYFWuvoyhltJ6qU8ZXGUdh0A+vYk3TLLvf4eKZtzgSrgcKgNC9mRcaQJTLLGhcCjpHBrKnzhJOZMlec5IbRXBogXu2WYh0+a1Z5wqhAx4Ev4mc28cA875hlgy6ZgMMXqEpEF2FSFkfCs1Alz8qP3J0PdPkdWl9z5q6urq7gp92Z+4+Avyil/BpARP5H4D8H/qqYK6X85Y/v+7f2L7irWtJDRTzteWNnZjOjckEv6TKyKghLl8lKeDF3uBSBzKbsKcnynf0ZK7PmSW6ZzC3H3GFM4d+ZH9nGV1zInFXHh+oBKYWUwcyJKhQMAZMTK7/H2MjazRjxvHKHiYVYHCd96SjMZG7znpNs8ekSrtsysFMnTmXDR/2OILBjRgkYFdGxXDocJdGWhVe9Bu2py8Sg1+zZ8NLcMUwNXXcG4K3/yGJXzNbi9Q1WQVUWdkuPjInv7YbbNPO5s0gMkIVmGohOXTp6tWcdB4qKrMrASAsI9/lAXQpOWd7HPSbOSHriNBk+2HtqNZHEcHQbpDvxsurwYtmXhjYMmBDZycBYVVR54pxvLmfy8hZjPU1c6OaImTLn3cKrqencjJqFVZhYl4nFbPjBfcnh/J5iPCosRKf44N7S+JlKZ/q1JpYGcxqxZ/hh95YXa6hLYjGWrj/TRs+4GI5qzXYeGFWHUolmSaSwYZ4z3eqRYGcOqqXEhMmBKlpU9nzcGfTiKTZg9Q885Ew79hg0c9hydO+4KQO7MPGYL6PHrA04WZjsBjsUGp24GU7s25aEw8jIun1Fl0ssjachZIcuDXtV4UXhcbR6YJuO1HFhsY6D2jBbwzwbINHkwP048OvVe/7Z9m8xKYei8I3/C5RETPSsw8DODnzpH1m6y21kzz29bDilDSwaAYaqIooQReiCZWDF0T5QeYdPLavlTJEjU9Gc7I6oBKQgJQEVogQjhSya84ePqKL+bS0LV1dXV7/Xfspi7kvgu7/2+HvgP/4bXF+LyD8GIvDflVL+53/ZB4nI3wP+HsDXX3/9r3xSKUKP51ftA7mGJIWf5z9nTA9MpWOfO/rSMSsHBdZlIKfL7cOP+oZZN9wow6RaJgyORMiOk6pJ7pYbOaHxTLomZk1GOIrCVImpslQEWu95E1452wqHZyMHKvHYUIhjoTIRSmav14xNi1WZKILEgis9HYmCJpWWs9rhmPmyfCZlzSIZL8JZt6x5RhAqJoa05SwrFl0xrxzr5UzSiiE/UbSDIlAiSWmMLLREtOrJ4tEx0I6Ke39Efpx68W37BY+8JSrDYhRvyjOUnlFOUDS34YweGhrJ/KbeEN2O0Rb8YrFB2IVE0TO2BCqzMKmatowsueFNOGFVQMKJrlLUMvN5teW53JFsh8Xx/nRml55JKzBZczN6Fr8iFljlI5WNTFKgHclJGJWhk5kkmqAyO32iFk+KLU0ZqOKIr2CpI5bMVBpKXHGyK+pqYKwNSgvVaPFhhSyFz6Nj3jasTI9v36E587m7YYodRgfWMvBUvSVkgzjFV+ET2+pAE2esb1GywYujb2t6NHdx5Av/Ae8U6/hCt3hMhjUjh7jm8faeKa8wQVHh6XzEMBJKQxaLVxpVTVhZqNRME0c2+UBfdixVg5WFECwpGfqmUJVIShVHWxhVyyyOXTwyuJZe3VGlkU2c6FRibV6545EP+j2ncMvBtVQxUtsTno4oFU2Z2eWeWRXEJl65Y1BbbpdE7QM7BpwbUBKQpXA2G44m4lhYCKzCzGY5082ePGaGeWDdrP8GS8bV1dXV/z/9lMWc/EveVv4G139dSvkgIr8E/jcR+SellF/9zhOW8g+AfwDwx3/8x//K5w9h4uWwJ3EJ4P1cbjlzQ9JrKJdzSUUXUAWTM6pA0IoUFaO5QaVMKjVIYrItSmkQkOSRfOa5bkgIRRLFChnLvuqoSsKWhaA02vQs2jMZh5TLrM9V7Aml41w/8KIrKiZC0pAVugQGs2KbP5GS5U184ST3ZDsjOaEl84m3RGto/YgqI0kctzwTVMM8r1gay1E3zNJwlpa92VGlBYrQjQFLYuzWRJ2oMHRxz0PaE6hAKd5RMCoTRDjqNbZkKjXR5UCtL0WSKwv35cz99Bmh4dF8zffVPZO5p0ihSGSsV9RLopsNOcPzzRbMyGJrXOpJCCkUgmhKC6bqeZUdQ+mIyjK3hrt4JrQT4ic288hkVpzTDZ/NA6IjWQlfhleSK5xVxak2JISTGAbVUTEwuYZuPCOhkJqJ6VZRosGUA3aqeDEFZQdcI6zYo9hQTzDriu0x4HLNXK1YcsM2t/RaGFzLrDTJgVnyJbw5WHRO7KsVlbqjTiO2eF6qW6b5nr7d8hAGlFlo8pn/dPwnHAvMdWHf3HKIN5RsWaVXHtJCn27p5Q3Bb5nlxFKtqEqiG3tqPIuz2JBYq56eDY/1G+aw5XZ+ZTBbZomodma7eGKbsWNCE7hJZz5sM73eUqeRh+WJXZg4jO8wDbTGc1YbzqYhy8LgHkgsIIVqGdmoI4Nd0cVXkA5VCjMrohieO8M6L7TzQGXOnFljdKZoR8vAQkXNiJFETgYbBaUUKV0bIK6urq7gpy3mvgd+9tcefwV8+Ne9uJTy4ceXvxaR/x34D4DfKeb+plTyyGTopztmm3g1t5gS0bnGmIGoHW1ecKWQ04zJE6JqtMqMCgKaQTVYZh7iK7swE0S4zZ+ZTcVZNz/umpw5mB2JgreWSVXY4nAsKLXjWNaMqibgQMklKNatyQom3VFKxuZEt5w5uY4Fw7N7yzF5XuWWNgYCQpSWQQpeV8xUtM1MpSZWHAipostHns0tCU0WixRBl4KOAZ0UZWnxobAgnAvovNCVnhIEnT135QUvlpIFpRZ2+syju2PRW87SUWePY8Hk/GO34pkj3/DL8w9M2SFamFaOfdVSlzMqRXyluRs9x1WF+Ey2QhMH3sgjdfxM1C0f1HvmytKUiaNuyDnj0kjG0Q09k7I8NXd84h2Ls+Sg6GOHrgIfyheUOqOmzE08sDcPNFPkWF9mgk7SYEtgcY4tfHUmAAAgAElEQVS16lEmc3IddQ5MDm7lA5u5w5uWKBWv9gZdInNdE3NF2SqaH4QdnmPX8FivmUrixXT0qqGoQsPC1/k3JK04ueYS2SKGf+5+jjc1+gSgWcRgjLBSmYSmVTU59qTzmqG+55C3FF1oqleKvnQJr8YDLJHF1MRZGFTNsVlRqZEqeXwjTOUtZ71DlwRieXUFG2HLiRfuCbGhsgv39sCT3fHBvOd2esGrLQ/xmSgN35p7jqsbbDNzgydox1gMioSTAWtmtA5opfgy/iWHdMuKE7WMBAw9O2wSqhy5CUcywqva8KTec8bSS8dODkzlEkZs5JJj2IYF295j1TWW5Orq6gp+2mLuHwF/KCK/AH4A/gvgv/zXuVBEboCxlLKIyD3wd4G//2/ii9JFYyVh+onn7utLMacSKz2zTYktr/RqBdlQyIhODFqz6AafG2zymLhwu+yp6ogVjWFmtJakISrDOh/YccQGz0f7DtGZAhQyloxhZJENs9TsdUOXZpIYujyAUmTxRNEk0cy2Y1I1l5tRgkjhpCxjnahS4KRqvFQE5ZCSKUkTs6KREz1bmjSQtCEUQxYwEi/zYItQ5QWlEsZNzKYDDaNeU7IiujPVHMFYduqVKdQ0jOzZMUvHbXnEqpGgOwyJMFfoYGgpSBTGYghZM1SGLgRymhlVxdnWGJU4bntyytRkejRGJ0zMlOL46O456g2jc+xlQ50WhtyxHnu0Foq5FMBHs4VSWJRidi2jXWMI2FJwccbohjRlKp1ZDQuLvkyfEKfYcWKVZwRBh4JtoEShSoGdOvJV/I7vzTfYkHg0b0nZcDA7Nmkk4rGrhduXmW574IduTSsj5/KG2zSwzSeYFW+mV3Y+8O3mHTpGdAX7UCNJiAihqYhFcVRrJlvzfhj5F7Gj8s88bzec1IalNJgYGGRLx4IzE7b0SLLEqDi5llG1pKzJRRhLjSZxGTCiqWTBlsBO78nx0mwgKfMmP9Grms/2ln+x+pKeDVEst3Hks33LgkK8oiTFFHcEpUASDWeKKGyOVLJQRLHiDAhfnT+CjZxV4VC2ODVe4nPEE6rEPBTOsubIGo/CU/HKDbNYwCBWo+qBfFvxxde/RJtrA8TV1dUV/ITFXCklish/BfyvXKJJ/odSyj8Vkf8W+MellP9FRP5D4H8CboD/TET+m1LKvwf8EfDf/9gYobicmfuT/4dP9TeilKXeB3bjgdtpy6QrrAlUsvBl+sS2P/PrzdcMUnjWa4qqyKXgpcalgIggJIa24b58y0oW3ocnvtVf84F7SBpyRUyOJieUzZcwYaUpOuHCQqMjEs+oywgCVkwEVVGXE+sy8lpu0XgWqQliiGJIgMehyTRlwpaFoqFi+av3oxQ5w4JhLDe8FAvFkLOlwxNSxdb33MYnuqknm5agDL4yKAaMaqF4OiZu5YCrJj7oNww6ca7v2aQ9SRQUqGNhw0dEIJWGsXQc5YYX6ZBW2Luabu+J2dOdNZ078rR9z9lWGF2o6VEpsQRDUZpVeUF0Ys0LnXlgyBGfLUkpmjySlKbTCzIKrirc5Ge+27xlb1cEaUgZ8AFcYVLC0W5ZTYmsAik4lHjqGDH5yLZktC8MsmOTB2rVwzyxb7e0YaY1E3eSeBLLyb4llDUuT3gqjsagtOfd/Ey4ObORj/TlLdnN3CTDUHZMquF+ObPOEx+rG5QsDNLQlpn1NJO0oZfLUPtWBqyOSFGc6oazWNRS0fiBjQws9ZoZeHQP3OSe27LnU/ee1vX4ZcNuOHFoGpRoZpeZTUVNQJdAKYoCZJup45HoWuo50oSaoFqKt7zKA6OsyAhBHCedaRlQTJTKkRFKKQx5B2RkEjb1Ezv5DcUYXvOOqnjm3BHUilNVsbdbQnGoXLjxz4gqWDWhmwxEREW8WVEzkUvCSsKzJVDhdSBqz/ZuTVd3/yZ+5a+urq7+P+8nzZkrpfxD4B/+1tv+67/2+j/icvv1t6/7P4F///+tr+u2q2ijZ24dVAldImt/oLbzZUfMGlT2oKAguFyQ2KPLJex0tGuceWGMLVs5UE8DzkyMpkPryCmueODELWdeZItTiRlHKdByRpfENk+cpbAqjk06c8Mlw+5Q1tzzTMiWoB29WZFRCInb5YkswtlsQNXYHJAfp1PYnHDa05WBpkw4WchGM5Wak2qxJXGfXrgJZ37hv2VSLYMkoqmY7R1ZhCDCKs00TBRlWGyDFs9J3dDHNRnNbT/QqhOdeSVo4VW/gaQ5yFvUrOnXl3mh3zlLJyem3LIrE+NqBRpW4ulLzd7u2HAEHdAhEfSaH3TLZI8kNNSZh3BgpCHkFrGKsWr4YrpMkmhy4e30hG/gZCyTbqHJuDwjSvBR81K1CB31oFDF8JX/hLiZMSj2vEFFQXLPJvSM5g3B10hRhFjT2D2/yI+8LIJYy+eqQ3Im50RbZoKt+UzH0b3lqGvQjlUZeO9fmXPDvX9lnQde7Mxb7zmNW+7TmWrJnOqKF7UGRvrVClSkI+LdQlMGXEyc3ApdIm05kl3NSMezrtlNPb6tuNN7euvIqUEnfYlro6Irno0/oVRkHU+s6Vm0o1DTmxXJJR7CZ76YT3ys70g6kURREHbpRCGRMHilqdJMLQW1eLQpLNGgNbgAdcxs3Ee8rrAefkg/o5bIXGCKDaI0vVhmV1Mx0IrhB7Vmr28REgHLppwIohlLg0chotA5sY2JtXUYdc08v7q6uoLrBIjfUXRBrRJvT2fexleIgZNsmDvLITZsykRMlslUaMkghWQEVQqrMiLJoyVTF09UhkG1+FXhLn5knb6i7Qe+c+9ZikO04SYcGMVSlZaoDLt8RpH5Zf8rHvV7vncgRiglM4slilAEjPKsOOGjpShLysKqBGYqzghFHI2e/qqQQyk25USbJ27kFdDMpUHEUeeMymc25ZWKQqHhg/2Sx+aGQWmCNDyEE7oUvjx9oNOeXX4ld4WSFafqPascCVKzUFOHzHPVMotwKitu4xlPi3eWSS7nAmfpGKqaINWPzSYCSWE8lwkE+RmrBk5qw6hrUjLs5p6cHTv9QpVG7ueez+mO527LbXjmqHfs9In3y4lb/cSYInN0iBFsCQRlMCohaIpJ5OIvu1RVZhBBwoqmTwxdgyTQzjMpzbNdMyeDkURBWHRHpMb7jsMWgp2oVWbdDzy2Nwyy5jurqZuOxq/xVnHHI73uUALuDE4SZ9dyqHb0tLhJI6fC0g2c7ZbcCSp5/iD8BSR4kw6EVmG0J1Yas3iaOONX9wy6YpeO+GzIOpJKYjAVhYWUE9JOiNZUJfB22dNmTx40KzOwqIqihY88QFEUekqzgmQYUsONDOz6P+elu+FuOnDWHU05MbcNN+qIRDAGFmdZkiKwosk9jQ40IXK/9Bzzluhrjm1hMYredhhZyMWxFMNBr2niyEnfkNBoAl0Z2MkLU24u0yBwODxN8UgfmPYHUkoYc13Crq6urq4r4W8pRnDv3hE+/CmDdYy6o6dlEUumpa+OtPpEW2a+5+eIwCYP6BLIYtASKVJIuVCAJp95jffE6MBYnusVJs58NXzL+nbPLj3xQ/mKQ35DXzpMzixLw6u8YdQNjQmX26RaoUyhIvCaLaokTJmpdaCOEzp78IlYdTTMTLRQCkaENUdMzrwtT2w48bP0gXqBf1b9ATEZsDV3+ZlGe25DRFmPNZE6FyiRs8nMWpOy5YP9mi6PaCK1n1H58kNk0kKzFP7wsCfnwHerHabMeBr2BlQeoGwwgcsODYaaSEkarwzWBNb+hWYR9KRgO7J3KwogWTNKzcHc89EM3MQD79IjfbIc1I5D2XEwG0wJRJtQfmHJhY/lZ5A0jkxhoZOBTXmhcDk7NrFlSBu8i5g88uIq9jd/yCiGSM1Xyw8478mLJrdCEM1dOGK9sFctB+cwceY+z5xqy3Fzh2GiniNV9KSsWOKGWcGYF1Qq6GAYS8WBW9rc83584nvzDTl3fH7jqKiZ6oo1rxzaLXYKbNPIF+HX7MoRXyyP3PEb+xVFOhadUbKAJBCDicJX6ZEujxy1p+gVkjNWAaqgNWyWgRVnbvjEP7d/wBw7evOAiwmvG54M1FtPiDVdOGOV56v+IxTNrGvO9YaBDUPpaCrPm/SZu/zIY/3AHsdL/oY7eab4zFqfma1hY5951TvKj808szhSMmib0SnR6xULGsGS0ahyps2XWBWlC64EujRdRtVlz5/86T/lb/+d/4Sqqn7aBePq6urq98C1mPstJUPOmZO5IXvIVqFVImsFNmDDjJpgaTpEFYwqBBRBKu7CKylW3PJC0JpW7flW/gBtE0pbboYJrWpO0vEXm79Ny4G7eMeXfEtTMr/Wv6CXLS0DB71jpOZJ36NVYkoOGz7SmBmlClkpStrQpZ4uT7i4YFmYVIMUQwFWZSKgySiUZKZcUeWaIXRoPfHzw6/5uP6KuBhmC1+mV9Yp86vq5wzpnklvIS2IWCQldFHE4vjQrBmKYZtObOKRIa45OcGqxLv5SEbxnX6DIhKT5ia+QKqYXeQuvtL5E0PVEEXRqwqtoPUDqzyyyzOdJLrpe/6yes9ZtvQYUtDkXEhS40vDOa5xYUJJoXKe0VRsyolshed6zffNHxFLSyFyMz2yGEdxEZM16/hCSe9p1DOYQqTiud5CzvTS0JQJZEa7QC0nelMhIYNoNtNIhcJkwQsEZYkCZ9sBC9sSKUqjYmbqNqQ2IirTpZ4C1MvC5/hzTDzzZAqxzvSxwa80WqAvO0IVWAvcxQMP+hOSOhbjUASWac2frf+IT8s9S9fgykyVBlaMvPNP7NKZoCxVDoxSE1iIrkGywhXPi9owN5a6bDkVS10GnHhyf4uvEnvtmHNLoCGI8OCfcXZhIwO92vJ2fOW52hGKJ5iKk9e8tH+Lb8qvedLv0LGQxTCUDd+5lk6d8MmRtcalBU/FNp3pkuJV7ZipKbrCl0SkQqTQFM8385/zhf1AMpaRhojnPj/xfn7E+IVDeOa5f+Zue/cTrxhXV1dXP71rMfdbSlYcfcdZWSoiEUPEYGJiyh038kxoFJNSNGVgLjUzHaUUImey0uzZUZeZHGsW3XEf95ddCevRyqO95VxviEro2xUh16xiT86GTZ7IRZGrjCRNwlGFM6s80C2BmYYXd4+iIAq+mj9wH16hCMUlHtIjB3XD1/5bNnngqLaokhml/jHHzvFt9Qs25UBzN7DOT+zCnpd8R/YNJ9VgfeFn8gH8jC2CHntSSZwbx7mrERWJUViyZW9vOTvHpoxoCfRrOKp7Sk7kAjd8plYjR9Oic8bmma05si17YrHE6PA4nptbzmVDnj+T00QpN7R+Rilh1C3BRuoyEUSRF82YOqrseFntKCpCzBQFT7zl3BT2aoOb4cnteJsSqzKyC2fGaFGLIRrL0W5Z1IrbtOezrYlKOOgNp9LQloD3ihf1wFg2xMrQzJFZN7Q58BS/4FjfkvLMXDtSFqwqJEncyYEaz+cgaAUqB1QClRPHdMc6Lqy9MGnFWVYYW5iMogkjHZ4SJu79HlUlPlVvmKuOLtWEojm7Hee4YmHNUVfUKJrSo0pgw0gyBbMEJCSeb3eoAktas44nonOcTcNZWxwLvgxsZMIFMDrTlIGhwKJW+FwjRjg2LTu14IaIdgFjMzvfk2l4VFuOZkVC+FYLJia6MjJJTQG6cqYUxSrPPNmGJnp6VVjSpaN2G2YSliCZolsUAVU0joWzu+VjFh7lC2Y0ikyJsB2OqFAYMpe2qaurq6urazH327QxeB9ojKKNhTVHXA4kVShieFE3zHrFrC2+VKQMKyasRJJEUm44u5ZZVZfZmMkiBcagKaFGGXhxW2blkLxQi8fHihJ6ci2YMjPbGskRrxwqJxIWSQIqcefPbF3PIhVnaj5VtxjbE7Kh1zuS0ohAl2d0KmzkyFQaojgmaVEqowmsMtgyUklCVKQqgRv9iWe5ZbLgpaYtPat5YDtZCBN9MnzSW1ILXrX0bsWSHb3ZEJNjLT1DtujsqbJnoUaUUGZN52b0nAhNhfMLWWnIkW3sWZRhKRW6lMv3te6ph2cOvGOkpQ4ja32gip7ZdpTS4kpGaY+TkTpNTKVjo84YlWmXnh82O3ptiDqjnuFAx5QNVc50S+IuLTTxxOf2Lap4xEQEyyodAYMrM7VEyGD0RMorchbmaU0XXzi3l9FSvb/FB4NtB1b6wGJa7sYzpbas7YgiMxfFWRpWZUF1C3X6xIvZMSXDUFsewhNH65iSwZWFrZzAeJa6MOYV79RHfGo5hDeIB1sajGRa57E6kaipY2Z9PvKpvkfpwlh3kDIlW0hCyBVDZTmriqRb6uxZ5TPrvPCN/4Ele3w29PIznlxhVpp1XljHM7fxBZMSPxsfqX3i3LZYCqdqzSIBlwPFGCpm2nlkpWdcgKXa8Fw63qVnBEMphYdlQOfAIB2D0oymIaFIgEIBCSWJUBwv8sBASygWi+fMjsf8FRv5c7rKsHXbn3i1uLq6uvr9cC3mfodmFx27ufDt5u7H/DcNJIoUjnYHRTFJg8cSlSFIS11GRITanJnLmrFUpB9z4yKKojSiPUULYhKKBS+W2zxjfEKZjE6BdTjRqJG92RC1oS4eU/xlV6O+xacZRKjSRJHMXXimYWZvviDL5ZD+Kve0ebj8aUw1k15jyoJXNTELz/YBiiZp+Lvj/4Epim+DsDcb5qxAJ850eDRdFUjLwF0+8e/On/iL9iue84rX6S3aZaK+42HpMQS+PrxSVQuv1iIponLg3LSc6h1SIqYqNMtELRk7jySpsPMjv2p/wUSDlnzpss2Z39TfMI8rDt2ORh0Zqg3v5Fe4/ISdLCGv+Mv2HY14rARW6ZmmTHhj2dc73HQmmi3bcsZrxaKFQMfZFkyaEZ0wq8w79QGlIiIjj3yNU5oUDHUp3M49o+nIueAnRSKx1IbP0y2pnIlJk0WhVM364GmNoa1mXLE8qu3lLGMCJS2f6i3a9pc4Dj4zlIZsClFnhlTjysiN6unygNNnjs0arWfOeY0qgcltuSmvOAz35yfwDr0s7G9a2jyAshzqDZ6aJJYpWU765scg4cQqnbBe0LrDU2Oyp2NARSFky7wkXto1k4NteiVrwZaZoBzrELjhgPMZrxpshuwUP5+/5U+7P6DLJyyRv3P8E/bpG9q6JyJoP1KK4sGfWfuFp3V3yTsUKCS8/BiNgiBczphWJaBzYUg3ZJeYMQRxRAxrMzHWHYNp+Xl3gzXX0OCrq6sruBZzv2MaPf7VsjsnvqqfuFuO/Ka+ZdQdOiWe81uGUjOp5nI4H4VH0aDIKCbVcdQVs7RYZhZV8YH3NGrBcabXLZOqqNWASYkv/beUUPHKG0bd8rG2uDxyKNtLB6ZYkoLQgJVE1LBJT/RqR5UXRtkiKjHJmkpmYrFQIjplFipsELKyxKxIWO7iEwnDaprwquXl8BVv8hHnBvquYtaaRWvW+eUys1MbTKUx5TNtOvPl8BmXJt7myAtbTqtbpCRUypgM9CtqteAbRbaFqAxkqFOgmz1V9Pi6YpUibvR4apraQyhEp3F5IdWaJWlm1bDomlQEkxZKMlQy46rMIBrvDFoKY2rYqhOtLGyXgb27BDQH27CLrygjrFlIyvLabplqzY0/cBv3NKXn190vsWQowib3xDLTpREVhK/6HygOzktLX694WJ5BOgyFQe0ICtqhZxPPND7xobpjqht6a3nne7b6wHN4Q0PHIpq2zMy14PLE3rwhozipLdu0Z5MOJAenqmMRRyeB2/ICKLx3fFv9ks4nNm7iZ58fQRca1XPa1oylYZF7QDM7hwKaONDnNY4FSuFtfMKFFVE74lJhE6xYOEfH/3X7R4yiWFxFW850eeBh2WNj5Il3xNThpeKt/YwzBw7uS/p6iyJQx4W3pxe0EuoyEpPjxXTopeE+7GkHxUolmvzM0FoOrmbfaYoUKiYUDYYBheLN9ELUFVWa2Jc1joxihqIxJFIFkjOYjLPuJ10rrq6urn5fXIu537L0I+PzJ/QA1TZTNj2bH8cJFTSuzCgKJcOg1khJuBTR4ikIIpq7uOdFQRIHqjDpBpXhpA1ZMlXpqXJgnQcQmFXLZCoG1XCQDR0Nr3Z3icLImjZGFlrInmQFR6BWZyQJIx1HuQd16TxdlVfu8ytdHDhVN+icSSKUopnpOAaF15q9u8Eqz2/u3pFj5FG/QcvEmTX7csmV86x4Vz5TVOLUdDyxYZ6FxVSUUbgfjyQNi26ZaBiVQ6EJvmBVYdGGiTWj2eDUyFf5M42MvKgbVBSmpmOmweuabAylXHYuydCiqP3AYDcQa7xoPukH9vmWOznSS4PFY1PELA1fz3v6lQedwWhuwis5VFTR0/jArBVP1Q5fDGZOnOQGMfBZ39OXDZVM1MzUceTMDmUznze30Gu2ywmlFVZF9m7Hogy10rw4g2jDQotdPLt5pFeC6IqaiXWMBNmSpUb7RNEF6yM9b9kva07djk4GimgWteJgE9qM7OJnVrIQxGG9pyqBk0tEHMkulBBJWhFsJDYaJZkazwd3j6RIMI7tdAIRlBGSUdg5UM2RVl0K4cG2LKXhKJnZvONot4hcwok9NTUjmpmoNUutiVEzGeFjuiXJjqPZkJShxrOJe4LVHHzHsbL0WhFsQMrCTf7MW7Xw6jYc3D2nyrJUmvv0SjArpmQIWlOFjC2eNSNSeu7KgZy/xOVAtoaBS+EWcGhTKPuZOcysm/VPvGJcXV1d/fSuxdxvyzPRveKaE1t9JMnMIB0lFxZqcnJksazLQpU967gQ0RiJbOMr0RlsjsRScVJC+XHsVtIKFRasHog06JIhC4/6C47tlpPZENHM1ESpGHWDzhmlCm2aOKstOR2pWZh1hVeOqXS44jElo7LnJDfEYoja8exu8dTcSE+OGoWizj0VCyk5kjE0ZbyMK9OJF7lhUF9y0msombfxESkVKRn2dsdqmnhU9/Rdh8kwdBVv/Z610iAF7ReSbZhsIhX4efyB76pvGMjczEesTKTZoIqQMES/4dSuKLHGV45CoVaeKo1kJ7gxUULFXTyDMjzHGiWGVBx1/UhIPb3RtPOEyQuDF07SQR3wpYEKbqcnnDLcy0f2ueOFDi+Wz+6GTRxxI/jWXjqDF4sWQ5MypT7TZU8vHZMz7FKC2TLXDcd6w2wtrgSCXAptReJsN5yNIdmMKx50YsbSJnBJkVyFGgsqKJpeM1eFrk7YqDFk1sFzo/cYmVnUisGsWE2RdfB4myGC1gEJMyk2fL9uiDcJ3IKRyEE1LEaoi7CmRzTU9CQjmJIwzhOzJSZHpycywracSJUi+kwGjrICYFWEUa85Nfe06UgrgbNvcSbwtn9m1g02RjozsFcbPrsHNuZIlg5nzyTV4rVBNZoXWdNMmk/6jiSWvlQkCiIWKyM3xWNjoSbQMPFN+TW1jyza0JQtJ91yyiuKskxkqirgVcVpGDicDjxsHn7a9eLq6urq98C1mPstdlPhusIST3hjOeuWJ33PWa9ZYsOagXf5E1EspvjLUHfbXua0WqHNJ1SOJNGQDVN2mLSgJHLUNcq0mBRY5Z6vlh/wlaFXl47AjCJLYRJHlRZImdmsOHBD5QvrMtEunsNqh2NgtPdYEqfSsugGpTK+3HBmg1GFm3jGxB5lFUFZknJ4G0jaYGWhqMtor1A0QmIsLSrCohwv6oFGAjZmXFhw3jNWHa9uQxWF2bS0wdMcIk+rloAhtAUXZpRWzGlFOw2sUk0QSxMW1vqEwZO1oneGg3S0TjApsclHunJEe01HQMcAU2bJiawNZzE0buSTeUOQLwjiqNJMVIWH+JnGLviww+mJJBpbBm7iRC8bllLjaXAqkcvMJGumpHhxEXSiKxOLbvmyf2XrT/xZ9QXPekUSzSr3pFAw3UStBVmEz+qGuaxYnCHohi0jehEWBZOKBBSr5UTnFzbjin2rMR5MLISlhWSZTYNOmWgKiomsJg5mh5EBnQspWuoQURQ2fsLYb5mXmpVZKLHjN5u3OLPwam9o2QOebfZMek1OhTUDAUd0Azk66jxQp8D37RcslbsUS3nm3fwdlSwsfYv7cczWVLUkJSTxGFpsHhANVTnw2T3QziNGJbb5SGVHVCg0TBxky2RXaCJoR/CKF33L4WbDyWx5SjuemluMDtg0ch9P1ASO2hBEsDmxqJZ3+S855i13Yc+jeU+rRmbW1GnGLBlFZlQRKfJTLxdXV1dXvxeuxdxvcVWD1y2v6obvmi0fWRGLI8eMlHI5rB0yv/Q/8Av/ZwRxPPIWUYnZKFzs6eWB5f9m776ZLUuyND2/y9lmh10SLDOLTPeMTcMAgzJmEPH/ZQiDBhrdU12VGRnkksM2c7ZGuCVVQ88SzqOHcixsxRe+3b8l8Gk+8r3fYE0hA1dzj0URC2vpeNYf+VbuWKxhkY5WF6zzmBq5+gEtBqqQQoupM39uP/KtbliNZY8HVajCpoxg3k5gXsw9gtLLzCier7InYbApghiidyzGURRcTmxq5NU8MJrAZHuCZpLxbMuVO31FnTBry5M7sKAkbcBW2nylKkxuIBRDl1e++w2NjKgRxChqPX9If+HqG+7jC/jAhQ1DmlkYaFallcidrmzyhaUx1Fx5tVtcFuziiLahtSNGEi9uh9GKqUqokX9c/sJrtyd7efsNjeFz+wMlG8TvWePMl/b924lYF8kGnAqGyn45Y7aFTk5s69snu/2SyaHlU3xiDoaJgU2JpLrBTSPy1/taQSNGLS5lzLpwP46U2mPtBSOZxs5k9bzWDWH19M2VMTiOuw17UUKc6YJhyE9cjUEpNO0VsmF0AV0ds7/j3CX2peOf5gu/W7/wr/U/c7UNU9sz7yxIw4vZ4tLEog2dHXEkNnphy8Jr3qHqcLXSLuBswyYn9nKl80feySu/1/+PIo62vWJW5V/q/8K/u9+x2p5Cj9oL99MLwSSaFaAQZsFZpbhA9J4ldHyWd5Adj/nhtCoAACAASURBVPELd3aiauLcPCKLEJsBPxfW3iNGsFpQ68nV0taZLkd6Jnqd2KVXdvmVtWlp3Io3mYASKSiGNk34ZWZ0GdrfeFjc3Nzc/J24hbm/oUkRvyeLR3Il0nCmY3J7fF3QatmkC+/TV97xRDSGX7p3vNoDIx1bAou+3T8yJmA1Y01hkgGRRDWOUXtaE7nkDKby4/SNZ7cjhQZXK4bCWjPFNviaWERYGke2UO2AJbHW7u1+k3aIKEUtEx1KwVHwsrLQseVKUzKdnLHSUERxUqjFQoauZHp3ZqNCdp5kGoJWWhasLsxyIBBZJODmmcCRMRwQMzC1BpeVTkcurceqUMTTJEMztqSu0tpEpxfaYSInw/8IP9HGSC6Bx/MJ7TvaBF43+GelkHl+t2fuPLTCLo7MpiGbwos8MrCQy4ZQZ2azZaHD2IanpsGnQj8nHtYTY9sTV8fietR6XFwxdcSYSrUG12Z8XqnWE1FW56hNIc6B1e9BVgaXGVj51r6nrTtg4cF8Z88z3/mEUGlV2OsV5kQdIl+XltQKV9PT22/MhzNdO+G8YK1l8g2noaXYSvEbqiSKhreXncbQMWIQdClMbkObMp/DD0iOLKEht4YlWIJdaOLKOexpysLqAj/oF4Y0UxZP1J6n7hFLothMXxfWOSCbymw75tLwECe+ux/YpJGNOdO6lQ/1M9/NHUYzkUDIlWN6TxsWnAihrizSoTGQTEJXj4rh1L5nq2dWt0PLypU7JumJWlFroE84H1FJLLYh1IqJlVn2dCUzNx1GCj+Hn0jOQRWcrtyVJ6IIuSrv5y+0rxnNQo4Lp3T6rcfFzc3Nzd+FW5j7Dwyb0JEnz2XzyLk+4DE0urAtEwbFCiyNZVlbnF1ouRLYcMHwKu/JdLia2eqFrUQW04BAL4k2XVi1ockLo91wDm+PK5p65dP6lQs9J7ejMZGEAVvpyghi8ChFAk1JKG8nckNZGfOG1mYciaogFQIrokJnRs46IBqwUijiEX17eSpGmG1LsspWz29L6EWwCpt8panKKoW1Op43j4Qu0+lItI7ur8veO7NydR3BrnR5RihIVs7hjmNvKKJ05kgtlbHZvXXe2Y7sHH5bGVbB5BZdYUgj89ZgmpUYWmYrXOqGTZnYlDPHesciHeD543LhvkRK3ZHqhpGe+3rmpW4wKkSUY7/l2G6p1dIWy77MbOYIMmHMW5HykCd6PWKsR31gr994Khu2ceQqDa/1jpL3TEWhO+NJ3OVXfm491SpZKocy8Z/+/J2YO9btlpIqLzbQrIljM7DPBROU1q7MvWdVxyZOzNVTHQxroXSGaixdShzZsbiBsjYgllwqF+0wfuFqHogSKHgMb52BR3lEq3CUe8acca2Q10B24GtF1aIlMA49mgRxmc0yEXSh+ID1L2xlJdjEe37mYN7z2fxIRWmIaAtNWZBQWRfPNhXMNXM83PPaDVyGhiQe9TtqEbYyU73gTOI6HLgvX/GSMBqZpSGqp68RR+FaDzQ5MTcdLZGTuePZP7CpI5N0pFp59vesZse/7Tfcmxd25wufzIzT2/i6ubm5gVuY+w9C23C/3WJ1QtOCKZaQlRQsFctGL3QspOJ4LTtSc+DZvOdqei5siLon1ETUSnGWSQcu0jIQ8THTyZVr3XLxPVNoMGpo6krPlQ0TPs8YWXjIwiQdKPxUfuXF35Nr4SzvaetEV2ekNkhRZoSmRppaeLFbgmYqnl7PXHVHVWGokSAnFgmcOAAWK4YmzTT2wqYe6e3ACztMNeR8wCyvxG7DZAMFw31+2zTx4h5YQuVqWt7pd6rLRAzOF2p0EODcNUSr3K2AN4zmke/pgdX1rMZhbaL6hW0cSd7w7AOzv9KZCzbcs5o7JtezSVemMCCaEWCXXrFZmNqOP/n3XMueuQysagiyMoxHDvmZOYIO8JpGzn7LrJ6htDh3pYSWJ7ejqwsvemBjTlRbmaziNWJKos9XTmZgqZ5vZkvTZN7VM0UMJz+gRBoigyz4ZsEcZuZuR2KLZIOfHJeyJTf6dipqC36JxLyQXc9iO9o1UtZAWyNzDdy5K4d5JbUzfU28hD0n33KV37GIo1bLqD1BClmV4Bd2y8SrPxBKhup4tvc0NjN3PaYa+jwTykgoFzqXcTbypd5zaff8ebWEsbLaPT4fae2Vo9tjLGy4MKOoqUQJnNOWYzcQamU6rLTHysVsIWeSeNr6tkpuV09UgciATUonmU/plW/NDjVvQc+UEVdhiIUxKIu1JOeZCSQjoJCNYWRgdIELd4gIYMnOo0EIzR0fNx9/22Fxc3Nz83fiFub+RsmVy7XCFOi9gZ3gFN7Pz3ysv3KnTxhbOXHH/2j/M9nCkQM+RYJLaMls5ZWZgdV7Wj1TsvJBv+NWy8Pywr8Mwsl3rK7FopiSiMVQiRy40uhMW2aswl5f+aF8Zaw9x/zIxJ940ndc+i2YlY1M/Dh/5t/DT1zUon/tmTuaLY6M0YI3M0ULJ3OPYulqxGVYXYsRQywdl9ix2D2FlqoWx4XVb7mLFwIe+spLewAKEUeOhXO3IzmLNRB0YRLlwRxZxDAbz2Idf2o/8bsZduuCd57oDdJkUuO4Gse/2g94rlRTmXzHtgjbPNO6TK0LvSxslgsHecF5xTvAZuw6YXPBzUpvJ/pSMWtBxfNsDkwbz9R2qFUOesZqoa0JyUofJkShMRNJPdUk3plvLLrBe+VufCG4lXZZ8XYlyxOuBvZ1wmmlqmA6YZEOK5Cr8HJvuPjE5Az7mtjWSlUHR+F1/4BZCj0rRZX3J6XWPU0yZKfc2SPRNmzqK9fBQcigSq+vtMxoMRifEAtBIgaIdPxZfqD4FisF9ZWXuqeqB7GIJO7TFauFpmYuoeOl31EFznbD/XJmcgG/zlxzg2v2LKbn7HeIZrxZiBowAkPOlFbIEmjMzCV4lsNbxx8h0yRlIxPBJu7iibkLBF3YykSqPaPdEEtD1YBYxVZlt555rEfGNBCdp1ufsTKDVTAw2S1XBkY6KgYQCgaTMiYW/uv+kb7pf9thcXNzc/N34hbm/kaaFkqOJN/zMuzZzwuTNNy7E61GVtdBVY5mz0kOpBreTsYkcZgvLAXOw45VOibb0ZQZQfFrxGfDN3vP0T+SJeDIQOFiW7IVVlo+6FfepSceeaLJkcGNJC+0cqZPG0q0/Gn3X1nE4iXTx18wdub98p0QAqO7YzLbtx6ybMAarmw4y4GeM52uVPEUEUyq2GK4cICayDXgqhJdZcEzNQNtPFMt+Fxp3EzNicVuGJuWVmc63taG9aw4KdzFmW92Q7SeirCK4UJLDDtMarBqqEAWwdlItRUlczR73pcJJ4U2Lvy0/MqlG3A6Y9VgRXgXj+zyTLaJ0ex4tZ7jzrLNsFsmthJppsoahNF0NCWCFzbxwlxafC44zexJUAuvrmfLK1EaxtKz6BY7T2z1xHa9cg4bXvstQSeKJnJWcm5Qa/FzwYeFxl0pQbmke47dnqtrKNWwMStWhXXYkZ0QZOV9+sLR/pHoOzQZiguEUli6htatHNKRF/cRI5nVACrE2vIcHphsiysVg+K0kMW8PTQBNnolEajWYDWRijCUQkiRtXjW3BPC23q1UBIiMNHx2j3wq1ZqC4d65q6eSFnxThhKotYVVwOyWoJbQCrHbktSUGNoakWcw6bIXT2itvBgvnO0e97pK1SDn46cwo7aOLQaQi1s85XDciWUyIf4xLftHrGRHWe2cuZYd6CwGmGxb/uJUZAYeTyfeBi/Y22PUfPbDoubm5ubvxO3MPc3PBNtvOKvQugzRjOXXcPoLLX2eBPZxwtxa1nEkjHk6mDOFAKDnYhVWFxLlYpIASxJB66deSuyrYWSCwMjUjI4pTcjk9wx1gt/rCM+F5pmRlH+b/O/s5SO1e0Y7cBcGzCGaBy/tu9ZS8NH85lZPEEjMw2uZubq0eBpdGW2DTnvWcl0dQUD2TacrWP2b/tUqxj6JdJIprhKJ6+IBZMyjRMO8cx3eaTJF4KdycUhpkJS7uTESuDsd7BmvF1xBhyZ1/ZAIyuxKMkrooqRwtUGnDX4uGJtIVbPXHoexm90feTBfGGpLW6pXNOGy2HLkBP39pmf5u8kMn/iH2mwqFPex4nlsuN5t2fC0NuVro70esbWxD7P6Cq0dgXJbHvYsLDUDVWuZHGU1qBqWOeeD/qNtl6YdAti+DEf+conQjrR2YkxWNQ4vFSehnsKQqcJnxOuVFoCOWVaLTSseDq21eLlxBxWUgGXEvZ64fjYM/lHfunuSKYFBGNWfli/sBLQohQaVCyTcTit2Fpo64rXgrMZyIgWtnnhQ/nGte45+3t+3T4S6oHiDb9f/kLQldFtiWqYNgesLICwn4/0ecGtQgrQ54zTgTpnXHvmIiB2h+bIS/tAqsKmZt6lZ/5x+jNOE/M9XGnpdGXQkas9cDJbinpMtdzNR7wufO0fMHJPydCVCb9GTCh8qH9htv+AykCyHsHiiDSa6TWRnYXwVlxtrf1th8XNzc3N34lbmPsboXX88JAJplK3ysk0REmo6Xi291Sr3NsjpVq8H2ko9FZo7YJZV06y52QOXE1HVkusnk4iSAErbMwZ3IytHbUanEaO+lbwO2uH13v+vf4X/lD+zJQ3fJWP/Gw/ocZRZMtaLau2zHh8fat0OPoNQx0wC3yoXxFvqW3F54XR9aTimfyWgRGrSq0WxaFiic789YVig0jk2A88lm8sxpHpWYPHOsWthVYDnZl4qCdeOCBVaVh4XE9ssuHf2p84ho7VG7IK1TiaGonGspfvXOQTjV7J8tbmH70n1JHkAx+Xz7wrr+zimXfhhW+8p6oFERbfYqPBzAGbK00UWvzbztzg8HGmJo/MwuQCpiihrKTyVuZcjUWd4TK0HNs979KFwRx5mBbUWSbXcCmPnDkQ18g7faX6jG0WPtlX5toylXtO64HFeUzZoMZgiSiQxdLUiXU60FpHVy50LlGblcHMhPT294RakV6ZjSepJ5Qrr/2W5LdIXfEmEHNg8hs25QLesMQd0TaIESYbaGrBlYrXwmo9oRaKmelkZDE9WTzvOTKFll/lI2c7sEhDNIZFepbQMYwrvjokBBb/VoAtJFxN3OWMvXZ88T05eNYKuzKyn77gvWMVOLd7DIpQydVQWxjp6FPiZ/mBBc/JPPAP4/+LaiIFxUlCi2c0PdYEFteyjSdGv6EYx71MiKuU2mFVuddXkIaNTrzaAyIGbyPJC4uxbLYPVKm/7bC4ubm5+TtxC3N/K2z487Tw5z84XneWS9dxlA2YRCiCpfJk33HgOyoOWxeCVhBl9FsudQNaeSjPqFZW0yEKZ3fPQb/Ty5W1bqiyQbAUKWQVyAYRxzAXJN5zyP8P1SaaMLEtKyc2mFRBenbjiGwb9vnM1hwpeF7shuQaRAWrClnYx2fWpqGqIGR8TUxmwApUL3R1JZuWhYYkDdZA0YYqFlsTgQmho6qlcTPddKUER009IcFQrryfn7mrE1e7pRrz1iEmhr6sbPJ3bIWncM9iA6qK+etr24ZIa0c+6TemsuX3y6+0zBQCX+WBc9Pja3r71Lg0TGFDNI4vm/doVg7jyJ+2H/lud9RBuBuvfNm/49QeWBpDMAvWFD7kXxFRbAZjEgcD79MLVxuIOGwsiDRM2rFhZG09E4FRG5Z2h7EWo5GH6cRi9m8vhmkpxpIl810eaU1HkIbGCFO11DZgysql67i7rFhVHr7/wtS/I5gGIxnTXzHtSHEPeLuwmIaskU5nVu1A3jaTzc7RMXM/fcV3H/EaWXSLrxOten5aP7O4Fkwh50g2PSd/TzUZqmIwLASS62lKJBlPbiMGYTOOpGC50yfu7Vf+oH+h0HORnvNujy0z2IrRM3PjiaXhx/JnKv8J/9feNzWGbRqZ7RalMvmBocx8NQP/HP43BOVqG7a6Yu2FXkdOZmC1hrV9QBVMWXg1B7b1ibl6tuZM0nuGcsK6BmHlogc8M8Yqo7nj+TijWcH/1gPj5ubm5rd3C3P/P/48XqhOsVYpTmjrTDUGI9CXiVoDWjqqU7woyRpW7VDriNWBwlI7NvWFxW0Y0itVHJvljPVK62asKyRxzHqHz5XH9YVvTYOKIfnIVFra0SAmQAmocwx6pRoltp5eCz5cQRJVMlftme2OooF+XZlNy7H5gKohSKUpGaNKl2e26UQOLdUqm3JGVTiaB3wtFFZQh1BZy55oLZPpGKwjdIWNnJmxjGXgIltyOzDbb8TqGYPhtbRvu0JzZrUtmxS50xN9PaLGo1XxKH05USUwpS13caTVle/DA7NvsLUSJ8/R3JFyS9JA0y44eTvly1n4vw7/hVe/pVTLLI7UtEQbuLotVQytcTyu32mKMkpHaVqKWJJ2XIPHSuIufWMKLcN84pLuOA87arbcmZnVVC5uIGhh1i2dZPq6Mg09yMr38MhqGibbkqolOIuqYZOWt9VpqTD7QhMmXMyo3WOsYspEMIqdZxqbmNIJaeHU9IgRjFEe0gVfMv28EoIyV+Xc39HriGI4TCesCs9uw2Rbsgg2W6wIWTwmTUQfiDRUDPf1zFhaFnWoNRhTaLTyzp756fiNe/uZP4R/JvuBX0PHV9lztD2NFZJA2lg29UK0jmsNqIA3iaUGvCYaNxF9Q7OuvMh7voslInhXMMJf/5xHLWAii+3o64zVyioB5yKj9myxVOMYZIRqUY6kJPwafqBIR3WO1i6EkjlfT4zzyNANv/W4uLm5ufnN3cLc3yoRY4WTb/nu77mYgDGWgx6RUvmx/oVUWo71Ho0dWRqitTgbidbT6cx9emLNAQmViynMbsfIQMXS2Ehbrqgx+JrwkvGaCCZzKEc+pM8QlNBfMbFSa2a1gpgr56ahKxeu9j3Gvu3TfLE7qrRM0lLFkOhZ/Ns/uKF6bBWq8nZxPoIxFW9gy3dGDYzmjpGeicB9XdiWGSvQ5UJfLrzIhmg8vUx0/syK4ck/cKkHQo10srKpnqXp+EP9C7u4vpXx1sD37sBkPV4ytXZYKts4IuGVVhYeljN6bjjkii0dsetZS0sUx+Ra5K+dftiMmZTrfqAY5bj9A2vuqQZe3QEj9e23zCCawTck9WTpyUvADcImTRzylasW2pQRmbgzF0oO5E5ZjCcbR19nkhRWF95+F/WMtGxqYTAzixhauxKYSdXREKkKxWWysyzrBmdnktsRJRDjTPRbhi6yBNBoaOyEWy7YJjE0B8rc8gMX3se/8PPwkcN0QU1Dmyqz33B2jtm0QCXVDhmEvk74OnO1G3brMyY7urKQ7J7Vb5jxtLLS1pWmAPMzX9t7FvFE36C1MHvD78dnPuoTsxt4Me+5yobOPyHuwCgBq5B05dVtocCweobieB06rranY+JiO1YzcLFbqim0dWS2e2a3wVhweWFfnljslj1Hogbu9IzRlc/2d2jxBJfp80IyDZEWxdObE5/5gZE7VCxJGy72QNxckXUlm/zbzoqbm5ubvxO3MPc3cqqYMnAxiU5nUhQaXXjkiUGv7NKVF2NQo6zWI2VAqrDnyqoCWslSOIUdiMVqBZPwavEkJgbm0uF0fvtEVWbepTOihmqf6eyVKiARfuF3vLJn9i2urIzeU2zLaCxIoLJjcpZDPXKUDdYYTM0EXUjiqCaQVTGaaZdCTQ19PSG+Uopj9T1n17KalmoDy+p4L088zmeO7Y6ltJgqdKwghlVaXK0MupBJOFaMzRzCN9QdMKr09YUiHZelJftAIzPVZrq8cLUbFt+xXyJ9VpgHWLZQFr51njN7TrLB2sjavN0TK95BVaQ6pChdXQh65tV1XGqLofIuv2A1Mywzvs/EdabPykO6UiSwaODVD1xNwy4ubOqVc+f55nbUUgll5qF+pcyGdddwtlvaPOPr+rbiLFWyehq+8rFcMAYOxVJCS8LRmRVfhHtz5cpHaszgK6txPA0/YDG03UwzZfwiPMgzY1uRacfdNTKcV14+OtZmIBSltyvtGrlbI0/GcuoEqT2r6UnG06fMbAcGveCKMJk7TBJqVbqlokOmNg2+VjZ1xidDVuUxvzISiC6wqSNtmWncE5/9D6zikZh5aXbEtkGY6TWiq8f7idW2iCqLBGp2TDJQRajW8ZofCFowFYoNJC0YVTZ6ZdYOqQZbhbauhKwc3JG2rIhTdvpKS+SzfuQv7vc0ZqTRlYRjKz0TWyBTVejKxF0+052vuB97huZ2Kndzc3MDtzD3H+RUOHc9Ma7YahADiuGSt7z499y7b1xtj68LO61UDbhs6FEe5QuDfeaYHsjNkdHcQTb0cmFYE6u0FPMWjpK0RG1Z3J4qgXfphY/yM4vxvMqB/979E7M2BF2IxpJcQ1SLEhCFLJVFDRnPydxhKHSMrGZDNkIRwzZ9Q5NQ1JFNZQkdu3zFloXSWHyOTH5LMQ6DEqTgc8QVYTaBQWYshp/mr8x9y0GPXM0WaxaEmX2+8JiPPNoTpoIhMpVEKRPfd48Uo6ym4a5MaHa85zvRerZuxODpzEJpzpQ4M24ONOWItIH78pVoe5I6irNIEXK2uATJVqJ4qJkDZ1YdGGqkX2d+n37BXiKf298j4lnUoM6hVbBRcdGxloYne8eQnxCB+3LmKb6j1RWphc1yJuFpfKEkg80TuziTTaYn8qP+mVd7x1U2vFsmxHjey6+kPNBWGOTML25PahznsOGuvlDSlrPu+JQWZhv5tWwYmwd8TRTpWZuMk8wJR7uMbOeZVLb8W/eJabC8hA4hItWhWAzCIgbxDY0msgQ+Li8czT3CgmaDDYWigalU7mNiHxec7zgeOhZtyNIwNgmRwqs+MNSJIvBqeoK5cjUdqh25bzmgGDIf7BOX5o6r7zi5FkHI6nAloXYlmQbHSrATIgkrb481PsWf2a8LIxsuZs8mv7ArMyYvHEPPV/fA6FpKMVzpGPRKlgb0yIELqRpycezign1q8aXhn/7x/8C724W5m5ubG7iFuf9ATYX5C2L2RDVQLMM4sxHlxXom0zPZDWIV99c602EccUBvIh+6F67ugPL2wtHUwgeeWbTlzB12dUSzYVXL0d3hTGLxButmKh+xmjmXO1Jt3i7uI3ySX/A18ov5kdkMiCimQgwdm/xKMg2P+QRYjDF4SbxIYLYBA4RSsIwUqzT1wtltubotRpUgM1FaRB2rcbyEO169YbQDg/uVIS0ELTTzyN6feXbvCDrTc+WP4594pyfWriPiKCbg/Axe2MsrB55o1spORo5my1O4x1ZhmxOGigmJ6iPrMbD4ntF1JGM5lx1NTThVGlnYpDPf2h8o2bI2nvtlJPmVXR6JkrjLF/64fqZ3F1bv+Vi+Ykrgef3E6gdQpZPEYT3S1JHrpiE1wpzveVwvb3cJzRWtCcnCsd3hmXlXrtxJR1GLDQuBK6s1iCjeJNpS+bl+ZLI77vTINkcuZXgLzhZma/jaNogx6BU+7yvJWDYpcGx2UBNYyyt7HtIL06BgNqROiWXDs3uPGoOJkXf6laVMvJr3VGdpNCEIQx65ug3VCVWV6CyTC0QJdPHEqT6QUuYvLbRxwaXCvbySLPic8RpRU7iajtH1nEwLsuVq9zipDHmk50quDdF6xCiH+kIWS8Lia2WoK0NZeA2efbm+3W0kM7OhqOMiDwgrQ1wp0tFjiGEDvQOU2fQstIx2B1TEQFcX5vp2arxqz8ltWWtE+pnfA05avLmFuZubmxu4hbn/yMG2c7hporMFW6EPE0EKG05EHFoLh/rM+3rkmN7RmgXxkXv5zKP9wotsmUsgLZaiA8f6HhrwybNj5qs2GCsYSQRdEYWJwIv9A03JfPfvMVpwKJ/qz9zJEzMdnU70dUHsgaKeKQeKehKByWxoasSSSGLBZFZtsFrYMOFypVbhyo5VDI6E2voWmOoZS2VXT9gMXVWSNpzZs5sL7/hCayd+aQ6MNDQYBCEFz+fyiUvteao7WnPFSeFHfuGhHrG5YEvDXZo5mJGDP7HUhmg84hLf9YDvzhTeuu40Vz7Wr0TT0MkFjY7GzYxdj+dClw1dgvc8I6VSnWFfj9zJiZPZc5IdUYWL7+ndTCMvPMSZSKUJhbZNjOLJOKDlKlv+tfkd4JG8cj3suR+/M8jIsF7oykKIieKFUx/QFiYb8GWlRMvn8nuKtCylZfEO2y/EeuHC7xitwxRFMvT5BMbzZQOTGzjURFJlcju2ZSarxVbDbC3bfEaDIZlKy/pWKE1LqZ4hrrj8zMt+S1Mj2YN3I70aIp5gDKUoUxswC7yYPVE71m5m7Tzv3ZHy1922LmcW0/AkD4hWtFaURDR3VClvn/pLIdnAkgcO+sSuTrxqy2odXZ3pVZFSqEaZ0oahFHac6exIxPPZthgSyQXOrUGdcoo73udvtGVhWS3aeooXKgEjBa/x7RWuZAY5MZsNQkJQMMIyCOPG8fO//HfKf/s/8fYW6G5ubm5uYe5vvPWGvdBvLVf/kRVDK5X7ZaRJhl+6R8QI392PpNiyhp6zGQhuotMHPBNGwRRhCnuu0pNth6OCh/v5V/rgMMWC3aGSSeqYabhwoCcRJXBfLjQyc7++cum2zKVjcltCfSXZgAhE07LWHsVQ8IBjX59Y6kAIibPtESt08cq2rFRpGcOGq/GIgpW316kZDxiusqdxlQuWhZ5Ftjh34Uv9EWuvPJeG0Q9Ezajx/Go/YWNLKsK17Ym0DHmmync+jp+5hA80pfLi92QK02q5+h2dS3T2iraF1Vgmu0NLxVdwa6FU6KtytYGdfmGvR1ZpuZo7Ju74ziekXGlzZsiZxXpG6bnPR6rvEVGcrqi3fODf6FziTic+20dO9iPPzQZTW8DTLQUJkQsPTLTs7cR++c6dvjLohWnZ8+pavnU/YU0mEvj9+sLvphOX8Hu8mcmt4Wo6HBG6wnY9MucHBp7JpqVYeO09xYOxlaQtbZmJNG8hqmRcNviauXYNezsRimXOmbU2iBqu8cDOvlKbEm2NoQAAIABJREFUzOIcLiVMjW8nnfWMF2FMmcuwYbEO30dIBszMDCzOc5EDNie6MuFyJtotwaxkY4nWgXEUUWy1+AR7HenSiYdyZLNeeekeqAm8KWz1V7woi7ac7HvaMrGPE9FbXuojq/VvZcwAalikoWPGm4WaA8Ee0QQ00OVIdCsuRwKFvsx0dmKjE3PdsJiOjMMYATezOseX6zdexhd+CD/8dsPi5ubm5u/ELcz9LRHCYNDZUrAUCzEIgTN+ifyiD+TSMLLF2cokHY1Eih2wNVMRRD1YmE3HVfaIWLq6sl9PHFIh6fJWPrt+ZwmexShZOpI6XsSTsax4nCZ+6R65ugMSYKotXnreVo4X2jwR6SlYEIshc6jPrDJR8yPZOSqO7/YD2jxxshscwmoC+/VCoyvGRFbp2XAkaOE+nvhSP3Jxis2euXFcsqNzhp/yV7Qqo2yRmjClMpSFr+6eRIPVhCcRx4Gv6z1Feq7OQSqMIVNdpVpLifDFfQS3cnQHmvC2BeAfxl+owNe+5ZUDMy3vgFQH9uUbPgqfXi9c3IaO77xu9hQLL3pHrC2/hk8ESVi/crc+sSnf2MsTd3UiucAcAro0zHFPNh6Dso8V4xcW14DCq7lnV14ZmpnLuuVb/xNT2/DZ/siGiVU7fBnw4vFLwJrCKSgH85ViO1LpCGmlX2f6NFNs4ePyhVfzyFN5BFeJOHwSfEhUFYopuHBkp5VXs8UrNCXSTN9JbUOpLZPbIhW8Ru7ihb6MGDtRzABu5cIBVcfsB1btEMkEm9jFE7NsURxgsGJo88yujGDhoRw5l442CLP2NFJpykKoif81/TPWTUTbkGzLWHt6MlNpmXXgLr3gTGGII0kbXjWQ7cogMxs94XXiIndE01DN27q6h/EZjW//kfjAhWe/J+MxVVAMTmY+8JVZAyfZESQhmgh1ZpdX7s/PdOPC5aNnZf1tZ8XNzc3N34lbmPsbRhxmFLZy5pUdC55oAs+mx7QDRR2jGzCmIEVxKF4LVzY8mQ/4Cj4XfDZIcPRkLDNdnXkXv1Nz4WWz4Ww2JLFM4lmsB6NkdZhicJpYnWGrC6NsWGgoYogEGkYEJYknAK6OrLVjryeKWJ7tD7R1RKrFVsWQqNZRqxJ9Q0SowOgDBcXjWWiw2jOpI9j1bWOChYsVQNhGT8hwNHtybQi8ddZNviUjuDLybrwgBjCJJ3mgt56rDJyanr1eWaRwf3lm0yfObgAq9+PIceOoUllcYHItfY08rs+c8z0P8iu9Vi4Wot2x0FFs4aiPlNSyXC19OBF9S5WObAPv5yNOR0JZ2KWXt26+Fi5l4DTvOJUHNFhcLViNfN3esSmFRXd8mJ+Blm4VvtY/8mTf8Xx3IBrLxIGSO7ZpJacDbThxpz9TquDWwGHMnAgMMfGgv7AdT6wby5IKF3ngYRzxc0uQK60pXNlS1RCjBQcn+0DyFqmZWBrO2uN85SI9jX37zFhtJWNIeI6uZZcsbY70foGY2Vwz4t469KpVNunEh/zE1Sw8T0LyASMXYv8/2XuXmNu27L7rN+ZjzfXYr+91nvfeuq5y2SFISAgDHYToENIAIdGK6AQ6aSFagIQUgggI0QQJOlGwRAOBUCSkNCJZ7tCigcGNoNgidpXrcc859zvne+zXes7HoPGVRaliiMGXXCf6fq291txjrbUba2rsOcf4/x3N+YA1LZMTWulpOKFq8NFQ9QnnRoJCyZ6hWZG0YvrZFr0tCWMiiqOYiB0jU10hFCIVsSQiO17MH6mtYcJyrDaMBL5a3/CZ+UjyO6p8JDqDGkuTBrCCSwUngSYmig9QEtl7dpywonTlgOTE1fqS1rbf5lTxzDPPPPOnhudk7heQbNkcPuNl/j/Il3cM9YZWerJ3tOnIq/hjRv0uFKhkIOjAZFcoQtLAQOCV+Yj14LQjW0MXj9Rxgbzwo/Ylxkw05smj9K76koQjCXRxZqUDlUSyGvwCSwNYKAjZCAMNl/qRVVE25cCsLdmCl8hZOpIEHIUmPWJlzckEFgInt8Ywk2mwJDBClyeiOoLrucx7TJ65Tg/UeSY3mUFeULMwdkqbDEFHXuSP1H4AlFt5Q5UKUQLYgiSlpyMp7MOOxpwJOdPOj1htEFPhdCBEQZJy63ecaVjrSBMLq2nmbBpybSiawCqTBFyKOEnYqKyqmWW5B2OppeBV8FnpKyEG+Bi2XC9PvrFJPHfTBSd9w55rPtiXxLzihR6INjC7zFBqUmmoUkUzG9oYKaZjagvJFZI4Imva5ck9A22R5kCdC0mFLi2slp7jtEbDljxmtGp48Thxj6fViVl2NItyebxj2lSIGWh8pB0bhhK4Dyt0cex1xSiWH/u3rMrAVbmnMQOGhWZW3vYfmaqWak4cyorr9hODd8w4qnKm/MyqK9aJXMO1vaOOkevhlqvBc3dZEcKeYjPzKrDmQDfPWBufVhHbRwwQwwqbF7ItnELNKB51ATOPlBDIKMU4Wj2zOI/UI9k6VsvA75vPGLVmw4HP8o8ZZMUH+xopBqcPnMyOzvaMyXHfbunlqflhdDUrnajsCS2Gi2lisRUfqycdRHGGDSfm2nMx3vGZ/z4rv/qWZ4tnnnnmmT8dfCPJnIj8W8B/q6qP38T1vk10WXg4fKJyme18YO2PVMz0pgUc2SlOM6FMBLPw3eUH/KR8D1dFFlOxaEcsjmQjG/NAFEeygcFWGL/mwW9wslCMhZJpy5OAcF9qrD55fcby5Ck6uhbJislCJxNX+khgYscD27Lna/MZZ9lRMVLrCas1j27NUXcEnVmXexZTIWVgko6uDEQz0+YRxVKM0NMRTUA1sNYTWzOwDxcsEsjWIgnu/QUzLY3p6fLItnj8sjDUDX1wzBpYj0e2ZeQU16RQM1mHWEeVElosVYZujmSTkUrAZjqZkeUT3gk2F465487f0JsW9cor/Qo1nsX5p47LVcP9ckHfdPgceZnueJseWOfI366/i9fCYi3IQrGZ2/yKr7evkFzTuzVjaTmHLasMriRa7hlrz4EOu3heTYa6euAQV9xKxye5IVnFSsAvC6QVWUf64FnFwkoPvInvOISWueowuedD+AwThPW1cGou6LOnU6UvhU19hx8n8jQx7zZIJdTZ0y2RuQgH2ZJVyOZppZb6kk16oJWRlgU1C5skdO6EqWYmrZipyKeai2pP9okv8o/5x04zX8835MowzBegIyv/ngd5SVRLFiEay2RaxrShkZ4iyibvaXTiaLaMseU2veAYGsbccfIt1j0Z3l/EA6s0smFBOHNl7vhB+T6jqwlEnIxEPB/rl3xWbrmZ/g5/1/9ZehsYTcu+WjG6mmIXigR2+pHBfIFbMrMEqknJoxBrT9IAOM5as+OBq/RAqZVUwFr7Lc8WzzzzzDN/OvimVuZeAb8lIr8N/DrwG6qq39C1/4HyBz/6Abc5UnnPVLZUswMD6io0Fe78S5IRGh1JOH7P/hkGv2YSB6oUqfhh/SXJVngWmnxmW04Yo8zIkzm4JIId2PGAYhlyg2K5me/Y5EKjC8ZNPPhLurLnzt4wUjES2MhPWaUBgITBycyM58H+MoJylA4nBUdCUwW2sCpPyWOYFkzwtAwoT/VSFzwylDWiSjAz59wQk6fYCicRy0yxLVEzg7wksadkx8ofUQqYhCDMZsVh2jJXNcUUdu7AC95RmYSt4VSuOduWNSNX5Y4SLaNUpLAm5ImMZ/SB6J9q25DIXja8SPeoZC77SMfClDcUjUS7YhAl+Z4X80+oeYlSE5MjWs8gNZUketuy5BV7rjG5QnQmucRKPjK3lrqcMQKXS89iofeZVDesdCTPPYM4ilYkfXI7GAIMZoOYhRAHPrUXaBGOU8uDv2FqHYmGx1AzTg1t1bMte5bGgj6iY825bdjXW45Vi7cza+nZaOIjaxZtKGIwqoCytgOrNFBrYg4NOQtIjTUjWWsqN9Ova7JmiheEidAeSMtrDq5jbFq6dI+1R74/f+DWv+KDvOUkK2x0LHhUr/H1G7bugYaJ9TyRjONrd0MSz2AqFhOeGlRsQUS5mB/YpIk4GNCWt/mB+7BmXy7I1lE08pV/ix8KNZ6KAjLi7MJYWnqp6e0bzq4l5Iomj0yV58FeQxB2qzOTWkZpCRwZZctSKh7rC94sH0h5JpZITf2tzhfPPPPMM38a+EaSOVX9yyLyHwB/Dvg3gf9SRP4H4L9W1R98E/f4B8Xd3R0xF/o6MAZP0IWQZmYaEgGrhVQcR3a0ZcTMjrUZ8FXDXhpmG7B2waKcaUnWYopS60xY4GV4x8luqVKk05l/qv9fONc77uUKax0ns+JgL+nymRlHnQJilVYnpOhTrZ31WHqOcoErE1kdPidqObOvNhiX6KXFl8xSPCMdZKHRgcvUcymPVCQ8A73uGNIFxU240jPaGjWKk0QrBSsL23jAamRygSSOR3fNOa6I4jAlM7nAhT2yNIbL+YGqGsFMLMZjJHG0a+Sc8V3PYjK+mllNE9dm4ANvOLonyZNZKs40nEyLaiaJR9QgskA4ULLh0TfkEmjzQs2ZrAsP1Svq2JMCeDJXPNCWMzkHKsmIPG1fH11N9pDEoDZzsZxR19PTsG83FJ85+GuytqjCGFdYcXx/uuNQCV/7K9QJq7zwgjvECHNqaFiY2zUnWaHGMpWaVEHDgJgZlyYkFM4uMDtDPlhKSWAzSw2RitYsrHVgT4UvkaokQi5MZkUpNU5PuN6RKk9yM/t1y8DTym2eDUtwiI2o8uTSYGDSmjt/SbAzpijbsIBRbCpPDQ3SMLkVKIhVttMeHzJVONMtwnoZkWkgu0uyGbCA10SJlqPeIKZnI3eQLC+mR/w8c2pXfFy3iBiiNdy1l/gps0jHZj8gFw6JQvQ1RYWQI23uSeo420uevOcKR9egWZiLhbIGB6k0TKkhauD+3d/lNJxY1+tve8p45plnnvnW+cZq5lRVReRr4GsgARfA3xCR31TVf++bus//31xdvSLWnnddw4NtmGzDZjmxTT3RKY9mQ6vHp45BU5gaQ583NGWhMxNjNgyyxpsFz8zr9I7X5RPkgoqnz4G9dSSUvdlwEz5Ql56fhs+ItqYUaMvA6/yeT+6CC7cHTfR5TbKGmRa1FSotUjKRFb5MjNIRzRZPocsDsz4p6nvNWFfY8sDGHmnKQGUzPkI2LZIFq5nB1Hxwl5yNQ9Rysxz4XvkRW7mjT2u+bl6ypBWCAy0IgqogEqk1U/uRxSq13fM2/5CRGtGCKYZharFuRn2kSyfaaWIVE45CnzOnRmnmzFQCYhIVE0UFyeDzwloO1P7Ax+o11TIyGIuUQtTA322/i9HMVFXUORLiwmfDHWJmDqyZS0cxgZ0OtFoYh8Kniwu+Nq+pZeZN/kDIkSErveuY3Zq6LKhAbQujC3xtKrwpXA97Tq4iT8K76i0rGSFk/JKY8ppsA97MtLkni1CZgc6ceZHfc6gaSq6eBHHrMwfbcahrbEh0aUBt4s8Mv8sh7JhoGV2DWxzOCC+HPaZYznXLVLU4O9LkmVkEMQs2JLbxE14VA2iCFB2zrykWZuPYbzu2+h5jDNs4YIowlC2LzSQfaHSmdyte8hWbcqLJcK+ZnA2reYBVRcFiTEGpGF3Nsryk4MjW8Ogneu9IxkN2qDpsTHwyr1mXA75KsBvZ2Dsqa9mLJ2pN0JGYK8REIBO9sNBhKViZcSWziMdpARGiBiQH4uHMMR15w7M0yTPPPPPMN1Uz928DfxG4A/468O+qahQRA/we8EcmcyLy54H/ArDAX1fV/+wXxv954D8H/gngL6jq3/i5sb8I/OWfHf4nqvrffBO/5bO3L1nFiToLrybl2Pa8KLdYs9A7/+RtaSoWgVQsb9JXlNGwSgt39SU7N3NfCp0eSdagxjCYGs/CpT5yzy/TlAlblFFWnPIlg28xLBgxYIWiMFSerT6wKo+ImZidIdFQtOJsKlC4KreUmKjjDFiknrjmI4N0Tz6oTYeo0ulArQsr09PqiZGGvdtANvgsJGq0KLOxTyKtBfZe+eUxcd0PvAh75mHD2r7jp+EVqkrKlmDOeDsyS8eDuWCbTxSniD7JX4xmxTGv6V2DVoVkLWNVsU0Tupy4cZ+44JY7WvriSanCitCYDKZiEydM5aEormSC7/HBEFPFbBzbamHWHV6e/GhXKeHtzFA1HOwLZg2c2dDXDTY9eYP2XSAZQ6uFKoObam7cLUYMyRjmssYwsdCyjmcu+jPWRGq3x9nMlC5w6mGuWOceKcIn9xr+0G2jjFzJJ1L2XC5PHcYnveTebHBVBpPYju/5UkaqODFI99RkIRVTpRgLJhmsRroUIQmb3nLv15g6UmvPhXx80m8DDDP3yxWHcEPMFbVELvoj3RJZ1zOmgFXBusIqC9kf6FMmOsO63FLqLdlG6nLmig80y8JgdnwIL2jSAbKyYyLGFrsoH+0lR/uanDNzB4N5TVMmTq5lUUPRwCqN7P0VZ4VsPV0lODPQlkfeLInZ1Bi9BDEcuKC1ZxZnafJEyDObPFCReHQX2DIzugpb5GnrvEx044lxZfA8CwY/88wzz8A3tzJ3Dfxrqvrjnz+pqkVE/uU/KkBELPBfAf8i8BVPNXd/U1V/5+e+9hPg3wD+nV+IvQT+Q+DXeNL5/d9+FvsnbsBYxjMrL2ynnn0HoSSCDpQCa0Z2cs+te0XNmd6u6KlpvHJ9/gjZ09gD2la4kshmQUrh1l7hjLDwZMw+0T15n5YexDJLRSiZVo4IynW6wxV4MdxzbjuMGTC851Eu6WVizoZUnuqrol1xNIZGRupcuOSeW2O5Sg+c5ALRjJWf2TaJMpSOxTdUaaGXhn24IWXPvQv0ZkOyDp8XluI5Tpd8jJaQjnxav8ZpYZCa7XKirxpwDrENr9M7TrLhUo/MtsXMMDQth3xBjsLsa1QrJM882huOqjyGyCSWt9MHXJUp1uNMoVuOFAwnduymyGp5xNQLJhdGuyKliRUHrLFUZaC1FarKYiv8mLEmkX1hcZ5FLDaBpyAlsMkDeRbEnBhcR8GSUotkj8+FK3vEx8w6HRkqQZxBJIMqe7ngXFecdYuxmRgaHtOayzFxPUWCO/BY1ez4xI1+os4L1ip35oalNOi5gThQGs/t9VtsFvbVDmcyZ7vizXBCqkjrRl7F9zyaS5qUUAc0kbFraG1PNpatPPA2vud33Pe4Na/obYto5sg1TU7cdW95nT9yER8R3WKJzLblTq8xJbKOZ2Qq9NtfYqNHREG10JsVPw0dTZp4LBsyLWqEjTziVBDfY3wmcCZYQxJDNEKSwGi3JHlaTR39FT4WvAhhGQga6cxEsg2jhKc/N6YnGMhimHEUYzEou3Kily1ZoWjGSyQZhyUimrmJD8xbx9uL73DRXfxJX/dnnnnmmX8k+KZq5v7K/8PY7/7fDP0zwO+r6g8BROS/B/5V4Hd+LvZHPxsrvxD7LwG/qaoPPxv/TeDPA//d/8ef8H89b70i5YowD9T+yYWhzQPiJgZtGcqKnJ9q6VodudJPBE2s3Z4YPUYzIfVk6+jlgiBnjFhsWTjpmlg8vblATeTONlgtBB255CNg8WXkIvcc0g19s2KgplsO3PtL9nbFSIehUOuBC074ec9P6s+ZpKI3N08rbLImmopoDc2yUKeJU16RvKGYiqCJ3TJjwkDSCWdmPBZfZmJxRHkSn/20uiIFSxs9B19xrhpGaSm1xTOy1gMug1ElqedD/pxUPJPraOKRxVtwyuyfkgKMYSoNXheSKYj5nMfVjoWGLs4UWVgax2AaxsrwdQysyxsuH+7Ytj2/ev49puCZy4poKlIJfD7fEWQkpIl2Vm7DmnPdYsgMbs2SA5ItIWVchEuz5+xbTPF8Pn3k9dBz4fa8jrfoUvHj8+eczIobOyHVQrFCWu+RxZFpOJs1U93g8pM0zJvxkd43jEYgHNiUO5bK4saCTQ2cV8zmEqcWkYLXA14zuQZXDJvjmXO3fnpWu6POM9bu6XMD7YKxkUdqDqahJ+DNiW2+I8RIlQp99VSnd9ArRrMCHRFn6OuGVTpyWW5hqRjmmpNcYauFkj1zqzTmhJXAttxz0B2FiruyAjF084AwMfiGfdnhq8jajNzETywc+Kr6DkUFg0NYqOaE8QoIZwLOKksMFCcMS89Y3tJwwpqEKQvZGRDIkvHuaWs9YalKotEnP14XIvd2jSfjRfFknGRc9vjinr1Zn3nmmWd+xrepM/cW+OnPHX8F/LN/gti3f9QXReQvAX8J4Isvvvj7Xtiud+yvvuTDeOTW1cx1otNHcrakIkymoctHduwRDF+WH/HT8qt8xCPZo+PCYXdJ72qOtqHTGimZde6pYyIZTzaWoDOjDRyrjpAcr+IHfiX9Dp+qG8RayLBZzqhAcJlNPjGL59a2DNJhrXAonk0Y6eSIFqFYz6qMFO9pdU9MgsEw2sBjtaPRCZ8jr/MtlZwYTMOShUe/xRSoTaLkM9E01Hng6GvO1TUuX6BGCWbE24gmwUkm0uD0zCwWvyjJOjR69uaSkgpBBw5uQ7cMgGCJWFeIztNLTc6XpAyjbXG10uhC5UZsUbQoBcu9CzSVo6RLruQOmxLFWDbzSLfMfCYPtDlyig0pVVzkRLYFYwXPA1MvGDKbOHKzLOzJdNIzlIkRz+/JF1z3HVf5jsv7hcYpc52YKkMTBpJaTEmU0HBwVww2MJiWNkd6bcl6QN2CNzNzcfyk+oJVnNibS16nA33XcGcDQwxsOWObFXd5xcGtoQT29Q2MkOqJMI8YY9lzQTFC5fZMNCxrwZaZyQayBr5ON+yrG35gvsdBL5il4mI+YDUzho5kKnR1SRlGXkyPfO2vmILjbGsu5gOHboO1C6FMtNORtizcu5ZD2KFGaMqJypzpZc1oGxbr2ciZ6zlCHckYPD1GlIJhKhXOTqi1FAm0ZUZVaFIkjBOv0gP7ZoWK5ba6ZsGS1WJ1Zut7XCm81lvmVONy4iOvmVyL5IXWzliEXAp1nAmHSBUdr+yWXPIfc7p45plnnvlHm28zmZM/4twfV87kjx2rqn8N+GsAv/Zrv/b3vb71BhMsHyTwELYUyUjK9NKyOIuRgsuZt+NHXi3vMcHRSM+azPt0g9SRmALZGYwIs/E0EUq2aIxYBeMWThJQfaovy6Zi77bMONbpiDUwdg1TcUxzzUpPkIX7cEFPTRaL04Gt3nMpPZYVD+YGn2ayMZgc0Z95yi4ioIrVTNCFIpZ4DhzsFWW2iDGEXACl0pFGoSfhzUxPwGHwNuOJGMCXiCjsygPb6UTnj2ArHq3l4LYcqoCg9HrNm+UWI4WOGURoObItD5zSljt5xWQb9uUafx54U26xtiBG+WgqetMwNx6i5bHuWJsZoyvuwjVShPvieXUqfGeqYXWgLhN2Udow8Cm9YqLCDJGTc+Qm0GOppvdcLXv6ccuDMzxWr2hz4VC9xH2q8fHE7CO0I76r6MzMWNX0dkV0libPuEnZh0K7TISc+Kp7wbEOVG7B60idI5t05JhX3JdCnJW12dMFR1MStpyoZcLNhVeHiZ9UL3GzQWkYmpa1nqnmHirlEFaoGAqWYgwNEScD76ovMTFzJ29xKaEmcT0/UpWJ9+Y1yQXURqQ0HG3iWHkcGeoCOXNdHp4aJIJ7SsaSRSWTi7AYzxWRHUeCXTjIlsnX5LJG6hd8Z36PFM+FO/DRv6ChR01ArZLEoiYTlp6z3VJcZjCBP/CvoTEUlIhh1ppoLBWWF/HHXOc9V3xiyms+ljeEOLDvLml0IeqCZmVRR1UWvnLf5/X4t2kqS+2fZUmeeeaZZ+DbTea+Aj7/uePPgPf/L2L/hV+I/Z++iYey1rJcbzi/4ymhEOgrz6r0zNZjVDF2wTpoSyFlR8kt8wiujVyYBw6lfVL9zxNBIlVZaMpEJYBX1vMtp0pIahn8mgXPx/KK/9n9c/iiXMiRiolrPlFCoc49e/MrFDxRLIowlDVr7dFl4SL31GEBoIs9D3bLh+otCeFgN4gtQMZlR71EwOGZiMUxV4Gkhh2PBI3UeuC+XIMmTu6SpowsrqIpJ67yJzrtOaUbRAwfqs9ZuQOzeFQKqjNqNpiyMNmWBcGZTLIegyDFkEqHdxGjmSpDnSdqP3KzfA2pJsSFRSoezJpon8SFj75DxkywEyqCGyNnrlmqkd9evWbnHJVMrNUxoczTFakWzr4iVoV1PmNNojJHnN9TRU/DwiJnxDruqob8asWyHHlsOtZypq8sq95TfEXBoCi5VlacSChbHeiOlmFlseJZJODjSDtnTsMX9EYxZWGs05M2m0lgBk6ugVKIyZMFQgUXHMlJ6BfozMjkPZvlgGpk5U/Y5HlXXzOXwJoRk4Wv6xccpCb4iTfjO17599g58eg2JDJeRlozMVQ13mSSt6zTES8DTV5gzCS7o7GJu7AhVp6GAScVN/IeYxInXxPFkaVioaB6wybNWHHsxgfOeaKhpw8dHQNJHWSh4kmKx7mJKBULnkbPRFqKMQCs8sxihFk6FjtRsiEw4WSk6YRBBioz45gYTE2tFWt74nF1wamxXIqlrp6TuWeeeeYZ+HaTud8Cvi8ivwS8A/4C8K//MWN/A/hPReQPK6D/HPDvfxMPJQgvKk9nTyQFq5bKTGAXrIWEJ5SJh3LD9XgGHLM0nFuHdSMP1YZX8R113zObllxFtHiakrHFQJlYa4+UiiwLJUGRiiSBW3mLkcytfcGNfs1ZGi7LPUfWRIELDuQSKKLUZeIgW+6aNzT5zGv3jjadWLkjd/GSjgnF07mJXXwkuuqpiNwrc2PZS0s3z7yMD+jk2ISPGApTZXjNLcEs3OUjSVoOecs6nxllQ583nN0ln823eLew0QdmCUxYFMMoE9ZAVXqCzfgSMVJxljUNHetpppoeOddbilqCRq7Pd1zJHeprEoZOZ76bf8wP7S89bcdJZB0PnNqGGcscKsIyspI9w8pSdGCpCl/Xhck6zHQDbxMrAAAgAElEQVSiMgVZNjQSuWtWBBt5kR1Xw5E+Bj6Yz8jG0zeBWntW+Z6lUZwdWS8fsWKZnWfMLVPIzN5jSPhc+OLwkTpEnHOM+Zo4B3J0FGnpxpGreCJkz51c09k7LjnwxfkDqY38jv5ZTAKVRy645dVUeHTXfOouiNTEybLYChsTefbYpuJoLlgtM5WPvMk/4dHcEDWw0jOLsTQlIgaK1FzonskFXE74sGCMY8c9H+QaMTNtPhLywjxvuVu9YqwdD+6CIAs+FVbpxHHekQJMpmaynkyheMecWm7dl1Q5stiOyQtnKnoT8DlgTcRlxZqZxW4YXaCo4HLiJC1qhaaMUBI2j2zKwmU84lV557+HaObgt1SyAJ7JFGoGOjnyKK842jXOJpIqX08Dv5oSzj07Ej7zzDPPfGszoaqmn9mA/QZP0iS/rqp/R0T+KvC/qurfFJF/GvgfedKs+1dE5D9S1X9cVR9E5D/mKSEE+Kt/2AzxJ8WUhNk/8Or8AVNlnPMUC1ktDQM2GV6kW4IpaKv0xlOXA2cuiFWHqkPqju8ff8DgtnTLPYNucKKEoeG+DdzX10Sj9K6iygOTWJI6Tq7Dl8RiaqoykkrgJt4SYw3OMuKfatd0JhlhMCtsMWSp2ZeOW/Oa4M+MdsXNMCD2ycBeTUGlcDEf6aWhGEubTnR2xuoClWW0FapCjgVjCzOGC3o0jVRS2JiRr6oLXi2fODrLPVtG1/DADVGElfQ0eeKST2iuaHXi2j5gk2GSQi/XSAwUM3Pvr8AoRpXV1HNtP7H1jwiOe7mElHl0N/iiVCXRTj3GwboMdDFTjGF2Kz7VDSvzyOhGZrumZGFJgaO9IJSeikh3OvJot3gZ+al+hy/TI3bM1HZgnT+hoaMyI95+4lBt6M2KVL9mSlt2feTBtIjvWeuBlYx4A5fdiSV5DBVf3v2QsLvm2G7p3IjPick1/CS8ZL927LKj05EyG4o6SjYcq5Ypd5zrM125I4Qzm5wxsubsHWdajHvBLBuW8WvcCrbpxMl7NDW8zF9zu36NLpapsXzOD8E5humaF+ETJSuLq3Fy4pO55NG8YJSWRTvO9TWbeKSqM1MlRFdhXEEouLKw4USrCzOO3fzAobkgEkgmo1hmD94WVCcam0jFEYjsloEbfc8pv+IUHAcTaXTmIDtEBJOEdeqpyoz4yA13oBBT4IfNl2RraVxPyUInZ67jBw6ywUmmp6ZiIgu0OpIl8c6cOE9ndqvdN/HaP/PMM8/8Q823+rdWVf8W8Ld+4dxf+bnPv8XTFuofFfvrPFmHfaPYUniZznwx/4B1uuX3619mVMtid3Tao+I5lTWTQpIGTZHUwr5siN5zPT5wNhtu8xdszZE2VWzkA33bUZqI4ZKwRCoyySiBiGfPIC0r/ZnXZBYEw54rfrv+Jwm+QFZCjqzKCWsnjtKRrWBNISewFDbm8clmTCpac2C2F7zlHSkqrQ7EuWVpLrA5c6o6Xi0/5drcMY9rHrhkiZ7fX30PrwMIfHf+IXt3RZ2e9Mrwntm0rPORdZy5iXecnafzCe9nBlnzRj+wzT27vKfTmb6seGe/YNv3nNlgzZOqf9BMIUJKWPEc5ZrBV+zlCq/Kbuh5nY84Sbh5Qs1CxDI4Q9CF7TJS6sQX048ZqoYP7Zaz6VjLQF1OFOPQueVkHTY7pmbNVAV+N32XL+9/ymCeHCeaPGDMgqBc6T2v568ZjOcex3nVQElMOGa54kym8ZEslqAJU82E7YKrFbyQvSXUyqoceFkMOW3o68B7rphsoDZnPpkrjmzYpTMHaVmVmrIYRheYjcH7iE2ZRWqqqVAlS4/jwX0OZkaqwm4SXk/vmNIaiMjUUUYhWce0rLGiWEYG+7SFH01gXQaieGYbONodubYUUyEKVjN1mVjnmXZeaE+J2VfEYlmXI75kzrQs6jn7Glsivbtkp5+odKbViZd6x4U5EXXLoWywqoy5xRqlLQNFA1Eq1Aiv8i1tLJyrhlg1ZDyLerJYKoksscYyk0tNY+651xuCzDS6sHUHZOOJ3jPr/E2//s8888wz/1DyvEfxC1jnCAaC23CobnBJOdoXLGoZy2d0qecknhI8xRqyQqsn6mVmoeHHzRcIiruAVXrgMVWsTMVmPuD0kWQNUS0HFyjAYhxdGQjpkS37Jw9W2aLqyOopZY3TMwJEMo/uBaGc6H1LlwesFEJM1FPmbnPNnqdu0Y/1wsHuuDIfGfyWNo5MdkOeVmg9s5eKH/nvcmCHNo5e1pxsSy7CxTKwD5f80H2f3m5Yc6AzRy7ye67sAaaGJVY8NjsmI9hS2JWPvJCv8TLyttyzljPdPPOVBERhqg2TRMCSEaIJ7PIRF4Q7dw0JHuqWU94yy5a4eNYS2eQ7ilduw0uKU5Lx1MvMtFuz1hMf0wXr0rPpj0Rn0ZLBKiEV7KI8hprFVEy6YpUHBtty3F3R6cgPqs9QD9ZnrCqiBV8KCY/EwrlaYUrBlQo0M/gaI5EhCK0c2cmZIe2oGGlwOKuY0LOODxhqDs0rBut5NGtuzcDWDOzGM+fWItnQV2tMvOVVes/JOEYr5BIwrpAqyFE5aI1lpPcdoSQ+uisG27ErJ3bLmdacGfyGPnji2dKx0MaZ3nse9JqahLWRqTQkMXQSafWE5MJLZuY+QEg4LTRzouApbcXF8MhkK97IJz55WMUTx7JmNCOVjRRANVPp+JTY2sw0ralsZswbJBmWqiboQiQQdKIdAK0ozY6TmYjqoThwFlUQlBfpPe0UOduOya74qG+YtMYqLFgCjzif0MazDs9WXs8888wz8JzM/T2IUbS2/MHuNZP3nFhBhpAzowSOsmW2DcU6HCPZQDQVi52o0kjRQJcXel/zTl7S2YGpwJwavJtIFkI8c5FHvpP37N2Wbf7Ij+2vIGUGdbzglslUzFTMUnO2gdaMrEtGKBSpWUxNV2YiHhHLfXXDwpOWmdGCGDi5FU5PTNQkKhYbmG3HYho6u+doO0b1OIQLfWAonlo9D/UNizjWMtHqgNOFB3NNrQNnLmllJvvAUFocC9YM3HNNSUeO4QsO9Ymr5chF2XNnLzi5hqN1WJkZpUExJLWMZn6qq2Pmg3yOXwbW88xD3RJ9zegzU8kk1zGnFoxjyp7FL9SmJ6SJjOfRXPNYXdE3Fdu8p7V7hrLioW7wZeb18shjs+FiHmmYOFUd0a4I2eDJNPnMwbxkUUudJ5p05vP5PbWpEBX25S1HPAepyMZTlYkmLlQ6MZB5qLfMwWLU4uw7tmPPZ/wBD5Pntrrm4Dc8uh2jrCi+piknjMl4Fia35pjB5gJBuK1fEEXYlRN1mCipwp8qQlRO6zVKYqhr3LIwhR3XpUUcVGVCVTjmlgf3Gh8X7ppXrOREXc6s9J7tdKAsDu8X9m6HEbiOJ747/AEf0hs+rl7wQV5hHVxrIbmadToT3Igridr3vDNf0FNRE1nriU4L63gmas1calIKTF1HKUqkemqqIBMkYa3FLAvNNNDIxKd2y96tmcURWEgIkwucw47FGYqJHOyGJJZae5wWruZP1HNkZ9Z4+6wz98wzzzwDz8nc30MpkWwNOnWcmpqT2zDYliaOzDbQ6IAxE4vtSKUBo6zKI61OWFnIkohigczsA1t9JGWH0RHLGaOe3AYOrmHFgZU8MpuOGY/kimQso2T25ZrBVriUwVsGaZmlJtqKLo24ErElIwWSVBzdjpojQSeMZCoZ6MoRzQ5rMw92R8JiY6QqlqKGQbZ0euRsOnKs8Kp8vrzntt4hOTPZ6klE2Hdg4FIfOeYL9mFLDI6DWVGnxNWYwCkjWzQ7qiyU2PHeX3CiJarS5QHvBoImRDJOI04i6mBWi5thKRXZw+yh5Eg2nsSO0VSUyjxtCYrSpIViGk5uRlF2/YmtHLDNCqPCIoab5QM2LNRzxhrLxbFn/ZCo/MTR7HDZU1kl2Yq9XpGs0kzKmBoW6aCuWUfPVTzQDgMhdJjtQufuWTGwjT1tTuxtoC4nzrxg0Zr/vfk+ca6plx4TLSEseEl4Em2JiMysObBzZ8TOkBySK5aqI9GwLkeyGnBwXG/IYeK2bFmMIdtCNIIVWIzFZ1jNC0VrKhvZuQekZOZsiK56WklMBU3Q6QNtGRBxuJg5OEOdCmo8JVUUKlQ9tUwUY9hzgdFMi6PO0KUJNYmjfGRvrgl5ImvHMhmOpcNE5aN7iQ8To1VElFwMo+lYx49gMpOvSdZzsm9wTERxrPIJZyc2PHCQHej/yd59LMmSZVea/g9XZszZvTciMhNIFGvpev8X6ZYqQQMoJIvL3N3ciPJDdg08ehLoeaRI2/cCNlE5skz17LU1k/P0ZoMCKmYyFhFFlybupwt+FC4vf+U4HPmw/fBbHxk3Nzc3v7lbmPuVUhRDSowVzAaMiezSFU9ERPBmZrYHtuWETpmiDNZkRGd2csRk4ZWPCBlD4lju8Dmz54VsWybV8Wr2LNLwTUHNhZw9o+1YVCBrzTYL0WqS9qzK4fJK0PG9wytfqWNGi6PkmsVoKllJXjGrCifCtnzhvhwpWSNojBIm6VgRTDToSXPeahDDZFpMShzUic00YLQmiUNri6awj0fa0vNd/8RR3fNi7lmMA2PxcUKbwlS79+K/2TG0G0K2YGc2vBLmma92x/34TNcdKdnwV/c7dNZYHVFKU/BgCzpqQln5MFy52g2Dcu99eXmlJE2JFdYmnFa004UhdMRc87n5ES8rWRRjaHHMvFQf2OaeTg0EFfnd8hf82PKsN8y25to26KVwSGcmq0kZcuqYVY0yFWPTMC89fp7Z9COT7fkue1LW9DS88MRatiglJDpyVu9bClbhWB6J1ZYwDRzUyF1/5HnzgCkCAlVKiBEmX2PsFTVPNEvNkCoG51iUw6n3FWaiNMqt7OKEkYmL3qJQFAxSFLpo2nLiw/oXwrpA1PxsHjjGJ2qn8WrhWm35rh95dQ8cxiufxhMuGPyqGZXhs/6Bv9Q/8N080QeHL4VNHNnoC0k8JhcSnoSmLoog30gE6jxjtCWtDXlqmJoGFlg7y6oDXs14VrQGqxIm9qCFTMGZzMm1iEmsqiJm9/78K8NVbxCBVVc4Aw0LG67sck+1Gvyl59q/0C89H7iFuZubm5tbmPuVa1T8j+UB4kBR7/tTkzO4tNLoAirSMOPzQpZAE698VM94M+BLpE6aatac7YZgI04nnpZvPOYzA56x9oy6YqFCs2L1iBKhVmesbBiTJ5qKYjVBT4yiWMQRi6UgWLOw+oRWUOcZXd6b9DvJ1Ezs05FHXtnmCyjFSs1n9YmLuqPjhFSRUjRGtTRxYBWDnyGLJa577t9mnj6NLEGxaMNEIJqAzisFzSGdSMHzovdYXajKFS8rzRqZbYctC7V65Q/rZ4qq+Gx+wkVBzTWfxgs+CHduRC+R42bDqg2v5gdSMWQL3Xyicho/99TXLblVUByLDZj5grVCRY9xQo6G1XkupqPOE0kMUTyqrBQc1mReueOwKM7Xe4osnEzAN6/QBRrpscmA37CNBUkjTgylXYlFuHrLX6qWfZhxasWrlVlX9GWPyR3K1DzFL+icYdUUEnNseUktxc48NK84G+l8T80bZe1wUtilgbvqb1xzS5Ujc7rnaO+YoyMXw0N5pnUDP9ufGK2FknBMoFZ0SXSlJ0mgTYlRebKy1P6OUC1U18xP6c9cg2WjJ777A5OpKAoqmelDw2nI9KklZ4+XxPOyIzeKB/WVqlQ8cOQhX1mModdbZm2xizCwAZPIVY2VSFKeVODod5zClsUFgrYoMm0ZsOr9LmIWi5cZCYLJKzjQkqiZeEgnnvQzm3ykVQNDanj191QS2eQTVT7ilPCBb9zpgawMc71lDQGjzW99XNzc3Nz8XbiFuV/pRTjjiLZmJeAlYtKK/PI+JOkKhRCNx+VMyhVrduzdykxgtZpLVTOZCjcLebLMEf5ns2N2DpUy25Lo/ULFSlMScwlYLSSTCWXFqEhfarQS9mkgZ4VoiEaRMTRqIaVA0paQRw72K6U4ogok1XAsmV7vGXVDLIredDhZKMZQcaUuCSkWH8379K585TGfyNnRJtjNKz+HO1YFs+9YVEuwC3qK6FqwsrDNFzblQlI1nYq8+UdGZd+3BpgtV/1X/mH4K4MEuqz4Ej7xP8x/ZzdeqWRB54wdLY0eOdcJ0R6lI33YIVLQWnGXL0xrRV2OzLkhOkfMlqxbXJ55qR9YjCcBgsaphUnXrMoiWlMvGS0GlitFwfFOM/vM0m1YkkVrR68bMpY6rXh/YTsf+Vnf00vD2XbsG2H6aKmnijHVvPmOxVWMbc0mLox8ALPwMF65mC1tHhGB4hKxGObsiNqhsqY3dxyWgT52PPKNShe25g3BsdMWrR7JJbGqPS4KlRlRSjOpmmIKD/mNw9CjDIylA+WZlEerzHXZsYaJq2hcWGnVhSBXVBnpZcPAFqsKJi8s7ftzk+j4YfnKv9194Htzh1GJkGesipzrlqnUzK4iWvXLAIJikxZkXXlwz6wS+Fv4Izk6BMMdbyQUXmaqNJK0pWKhkRFjhDZPVEtCmYFVBebsqNTIiXvaeaE4S9IVYY0kLNWSsLWl0Wdm3TCQ8fXCcl9zv/kBpf6/FsHc3Nzc/P/PLcz9SuUMoes4Xioi72uWOploSuYkhknXzEUTaTjQMwTHEBv+Vf2RJq+4NBLs+L73siwMdsPXsKP4OwwzTZlBa6oyUefERq7sypmKmX8L/8ib39PlASTTpoG6RNZSMStLLZBUQSkhmvfdpUpqRrVntxyp3Uw1ZJ7dB15NjS2RIgYxHk9PBrxZaLgylkAXHeHcs+4sb3HP1veE3TeMf6LozFo6lNIk41m1Rwfhfj7jfOZj/AutOvM380cqmd5XjsWGUPUYvRDMGVU/w/rAN/8TZxWIuQCKYxHa5oLxK818olEtRM/kLSuOisxWBqSeOVc/UXi/n3g/feYtPHExgcE+Ihl8ThgleCKVnlEIlRoJa6YzV0JSlAY+06H9lZwDk7EUpTEloouwyQPZFzwr/03+le34mf9r9w8sWHSApB3JJa6lZlINNhau1YaNPiFhBW2ZWgtToJ0vdOqVOGuSU8hsUUoTJDGpjI8ekubN/pGn81dM3VDNhnnXci4bFg1KRYpAlQpr0HQMNDJyKXv2eWZUjiquxOzJxnE1DZ+7RyoZyDvHU/yGo6DVihaDZM1kKlRJZLfnrC1KFHbW/Kn5yOgDVV4ZvONQRlzO+GUiK81b3THZmsU4lBRWMWgSR/aMuqPXAeMLCUVB2K8XjJlp1xknmTovnMOWCw0ZT0ivJGl45olVLIMUcnK8orBqxZgZrQqSNYsOfLpeMNvMG/cMdkOwX0iVEFxNTf1bHxc3Nzc3fxduYe5XDs7xo3eYoqlSZLWWVTUonUnZI9qgi0GcJSvNogK2ZN7CjlkXit0TciRrxaq3jNphEKxS2FzhU89umXjMP3Px2/ceMbXhWu+p1YSRhKHgxLBfVhSFejlTmgOWFcmKT+kzF9PiTOJs7rGshPx+Of7kdpxd+0t3l6GSBacWDDMbBv6z/N8M6olRdxzbR6Q9kK2GWvhhfGayNcpCU1YikVm1OInMOEYXqHTgLp9p0sK1OlCU4pv5wHYZ8WpmVRVOzbyqew72hHJXrFyosiUujkHVKG05lFeW6PB+4ZP+M+f6nkE/YkxkKZpBG3LZsyqPmIk5G97CjhwjmvdPxY1dUKmQggPRLKUDVdjKBSMQJLKNA9sycFqeiLVlEs3IliZNgOJhudKmK07N6Hogd2c6M1DLE5aZSSq2ZeEP4zdiaigSwM5EU6FU4Wpb6gXQK9bPLBqsc4Q4c7++8LJ+4Nk/ccoHkm7Q48pSrYxpx6COuFLz5/ojTZwwLBzmCeUyohSP6W9c9IFFVeRiiFTMSkja0lcBsQazOLZLRrsLrb7wjQOjr3lIJ1zR/DCeSHXF4keyDqwqUnQgKc2PvKJ+Wa/ldMFkRb1oxrznxXiu1CxUlCw4mxDJzOr9T4LJgkXo5oXBb/lweWMbvqN8QauE0o79fAGdCXrC5cgknrd2w6u5IytDwoIMrMryvfkDRiI5ewZXs5MJbOFS7xicf/9kWzKvqqUben6wG7qq+03Pipubm5u/F7cw9yu6FH5MZw5LT5obSp3RNuMk0klGF9jJmWMRmrQwVxWv7YFJtdTziVQcdTpTHDhJRP3IoGpaWTEMtOpEbXq+6k8s1lPiCirR2w2zeBKewkJTFiquDL5hMAdGU9OK4sP4lcfYszYVvWlRulASnOodIc14P+L1hhQTsw1IVoQ0smHmk/orxdTMJXBRG17sjtm2VLz32JVK05X3S/sRzWYccSVzaneY4shOI6qwmApZC+tSsZcTF7/nv0z/xqtr6ccNwY8kWxPF4E3kU/kZrRXkQJU0i2zI1pCV5kTLV/sTV3EM6p6fli+IVByWVzCeaBreaCEKMXqKUlxDS7IGvWaaceUpv7GTgWNzRzMcsSKokqndBUfiIX/mYh+YlopYPKoXRtdQrKF2L7SqZ3M5s7Gv3JkjNreUyhNkZtCONr+ymJpmKUg+syqDi6+0JXEm0OSRS+nw64yTFRMilRZaZchlIqYVlhNHY7hIxudIpQYWCydzoDeBKqv3GhGZ8O7KuTzQuZmn+V95sY8MuiPOLSezY7UaS6bVZzQOF1YGu2fVoEnk6Hg2H/jj9MarqZm4AwUpB5INHPKJpFoUhSYu2DAxqIrRtMSyp7gJm0cew8BJb8gqsqiKqzqQteG9FM6giiZah1CwPjG7GqMLAxWpClx9x138zndzTwAkKVxMJOUwLlGAUoTZbJgxaOuxObEaz5JXnE4c1mcm8yNRKgZRtGNP1185GI0xtztzNzc3N3ALc/9BXhPN68qnNJNk5o0aL4kg6X3f6arZpivBC42acWXG5/T+5oCVgKFTC+fs35v2BSpW9st3vMtksYy15zK/Lwl/cxtcWVCS2OSZRWl+yD+zmgobEjVXZmOwWqNL4dxu6dKVrAxFMkhClGFUmt7dkRTMqqKzI0p7cIIRGExNkoBXE1FZRt0yqsCsNRMbHBqchmzZDSPYxE5OJLtDm4qCIeuMSpFVDMk5Bmmok6GLPQuaqap4MzsMW0pKjNaz50TCsmSP6I7GDIQ8s5SKNWf+0vzEoGqyqYhF81zdoTNU/kDSDpevGAJNnKFYYtZs/IxEi5WFg56BRKJFskaLY5lbli6ylwuTbnnO90xFkaJHaQjNTCsXMI5dPtMtFxr/hSf7BV00U9OhRWhyYi4K4obharmn5z9dv/LnzYEVy1Q8tk+o84y4HZeuYzCWxtT8fv3ORTZc2FAQsLCNK3+YP7OakYM7Iiy0snIyLV/9HUuqeCiv7NTCR/03gj0TYmIbr/gkNER+do+sriZqyxsP7M2Vqpz5r8NfeasOkArKerIKvPrCt7Clx7IqRV16pHQsZcNuvfCQv1Gsx2ZhkgP38Uj0DSYX1hDYcaQXj2CxecHoRGBitBuMRHwUggiPc88c7HslTsx8rnZUJZEAVSWyslwlsOLfg6CGvRxp08ghv/LP+v9AyZ433aCl8NCfcKXQujeO4ZEFjyjFx+XELmYk1BynRM75Nz0rbm5ubv5e3MLcr+iUyCkhU8DWE3vXE9SZz/ZHornHlshTyfxx/GeK2lCFhS/hniAzgmWzXNFKcDazkGlLBCxFe3IeOPmObDbExpKp8C6h8CgsqkAricfpympHUhC+2Z+4mC0KgTwwlA1f7A+8qQ0bGdCSGaQlmIWL3aIkI9kiTFiTQIRJAgnHF/mBuhwIZWHWDtAYKSgBz4iTDBSyKxzSG6NyHJsdk6lBQVaWYjVFNGdVs+KZdcX9/MK3+o5v7omVGqXAl8RFNETL6hxWF4ZNoFITo254Uw0SCmfTYnREK4FiuIrCa0FHwRB5ki8YMl4Lp9QRJCDFc7Y1kg0RQ5sGvO/ZLAMLhRQUo9ry+ZeKmJd2zxQ2jKvhEy9UOfNm7rAl8eyfaCbHmoQlCqew4U/8xCXfseCwJRGLRofEUBwqP5BxuFUQ5dn3A0mvzLXC6EjygUVbIp6mTPyu/Iz1iWcqWBakunLIz3zI3zBq5qXasilvvOgDzkWuErjoH+jKHSuWruqhKNJkcUk4uw2TNIh6LwruuLKI46t9JBXPd/3EYVkJopjcHa4Y/kv8K9/9DrMapjSzasfkPaeypV4nlMpkJqwTEjPWzXRx4lgdsBS0WvgxHflfzrGWGqsSdVn4WF6ZfYdRiUgHohmUw0viU/rM1TQMtFQslJRIxmNHhxhDyQ5LJjrFbCsoQlcGduNCa66IVnTLhT/ZP/BmtqzKM4UNOvwZ10ba3d0tzN3c3Nz84hbmfsWaQnaW3tV4MyJaiCVQ5L3hPynNd3tPlYUP6UpIgZ3M1OvAa3gimIUv/gEjkZEKW4SQZiTBsX4kK0NVJgILq9bMusaX6X0ZuRKsTCxiiEbTs0Gpwi4d6TmQ8EzWvF+Mtx7SSKUWRqlYSg1JsZWJNTtEFWyc8HphtR1ROV7kHs/Kh/KNQzkjVMzZoZWilhkRTcmao7nj2Xxg0ZpkLBlLxcC2XPhRPnOSllf7BMWiVCHaQDYOo4SCJolHq5UF4bv+QBLHx/WF2TuezT1vYc/Z1ygRtI38lL6RlEcj+LLwaj7y1d5T28g+nmn0yg/yzAcc17gljYq38AHJ/pc7eI6NWrmalje7Zck1S7KsZkWrhSZFuvGZ5+YeXxacWWlswM+FtDbUo2HYfOBLsHwPO9bkqGViUR6TBCXCXMn7ovlU8+J2kAJiItIKlYnUtkdbw7VURGNJznFWO7I2HMqJx/Kdje6pXc9entF6pvSGuzRybC907vI+dZo6rCrMWnNRDd/MDxgSwSf2akIwBLWgSwRx2GRYcsUlBLwToqpJktikKylDMnu+2wNhuTDOe5I3JHmfAB7sllN7eC+QThukJLRWlGxQOAEqU14AACAASURBVOa5RtnMZDxOVg75lbFscHZmVB4xmTaf0NpAihzGC0tp+N5NdP78PvCzDnzzDb2tGXD0Dx+py8y5HPAyo7Ph9+pvrKVC8R5Cveo52QcGvePInoGGrCxiLS+bHc35fYjIe/9bHxc3Nzc3fxduYe5XVKjo6XlUr/RxpY8rUcBJpveaWVkm71jUhr+kzP1wwfuF3u6YTcBJT8FgmVFGoSUTdQ02Mkv93mivLF6fgMKbfsAXh88R72aasnLs7hhSjVaFWCqsRFxZsWQMMOuWRiZ8Gd974EqFQVBKsRbHZAL7tWcJASdnNC0FISmDksBFb3Al87B+Z9Q7XMo0JTJ5ocmZ7CJLgVVvsSUhqtCVK2HNBDfxUQYGHUh0LOLIFrC87xXVK21ZyUYxSGDLiAK0inxIX+j1jsno97cxaDwDLml+Kn9hzR1Xt6HKK/UqfBqP7E3P1beM9kAsik/TwKCEaBrSUjHbCoMlpj0lFO7jkWvZcraPpEnjqsKoK5pN4X44saXnmHdoZ9Fnw+z2fOscUwN7PP/un+jFMavAY3+mkoU788oaa85mSyweHcGWFV9mstZsUsSQcHICWzjJjmgMXhaUWSlGyCljwoheEs/mQIwfQVke+u/86L5y0QeMF1wSlGhe7BO9t4ymo2KGvJKKoGPD4t5/f5ev+KTINjI2B2YRFg274YWtTMRoqNbIq94gbkG6zCqGsTQ4bzijMGWki4r99czPjzuqNLEqT7gIqjUEs7x/kh2P9FXNpbrjkt+HMpKr6Oj5Ub5B0vRmh1HCD9M3LrGmNQuTqtDqfeJ4U04sbNmkmcUG1rTlWFaMyqjVoD0oFnrToFbFECombVl0ACVYa8BFkoagZkIIv+lZcXNzc/P34hbmfmWRiG4GnHqlciM+z/yp+cP758siaASxmslo0JE6XQnlwvf4EacS57BDS2ErZ2Lx+Lww6j0pW7JytOUVIaESDNWeWbXMJmP1SBLNyT5R5P1t1115YVEBVRQGQYrFKAi5IHqhqPfeuWAim/nKWe/wcWYMNS/+I9HCLA1GRZRSZBwqZ3wuNPMbbdKM88qiG7ar8Jd9xaAbZpVxprAqy6JrqjyxHy78t/7fKK2izYnP7QdOxlPFTODMvryxUjFSQXaMaK7qwCGfUTmzXa74ZYDG0KaV6GZcFh75zo/TmX+QNz4rR84VG/UNTebqO2xakFxxNyxcFkuxkcEFvvoDs6mQ5GmuJ4wfaUpksDXDWuHqxP38XpPxh/GFSg/IYvlcP2C1ZZlrdLrSqTesvrCGPX3x+Ak2amT1FcYIm2VhKxe+uoZohGupCINmrQwTLYEVbQ0P5jt7ufDj9JW/Nk+86ANZDMVYtmuPi5n9+sxLfuK5emR2NUElilVsTc+n/IYsjioWxryhqy8oFbBiqGREtGIKnu16xU2JfT9TuSNXc2D4ZSCiYiIp4dx1zKlGRc9+vdL6gWygy680JGa1EqaF17phVh3KJJaNox4SuzTRl4qY3ouCxVnqGJndPVIKKbesOGbX8h3HkTtMLtyVkXa94q6epp74unvgpX5kJKBVopIFrAUpREAQdIwMVcvH9JWz3+Gl8D3csTiNszBIh5fMQkQEDBF8YquO/Pvrn7hOVzb15rc+Mm5ubm5+c7cw9ytv85kveuHlYJAmcNE7RtUQyorXE6iahCUa2ORIxZUmr7Ss9DESVEbLzCf1BV1nrnaHVpGQR4ysfChfiMZTisYW4cf8yqQs7bLSqpFzvUMbWPD0pf1lW0NkIdDYEc/CTq4c84HFBqKyzFaxGMeCw+MYjSFbhwWSpPfJTq7MaksjKyVbRjZU68r92nOsDZcugNN8iM+cxNCpC44tF3XPQb8x2y1v/hGXhB/133D5T2ziwGWteW4eOSlLXWbu52f+Ev4zRs24MpIXWCXwYp5o6kIuCluEu3TBk/kwntnPDdV8D5Vl7SyTrknGcpeeGdQGNTu+rj8ShpncDpzqA1YvJLNDskNweHMEmalEkZQQcs2kOrpFqBl54MKLecDrld99v3KVDa0dufgJukzOic++oiewqA0+F8bg2EvCSGSbz3R54m9ikFKxH2Z2OYJVGK3ZmoF7e2FoDA/2hX06IYsipYDRFlGai9lzVA2XuGVhh6SBb9aySk9YE/iW/Zwp3YLNC94HDCt3qaeNA3N6wpaCl4g1M4NzfA53hNSjimBzYpNXSrEgiSl5FvMBW3qihyBXOnVCr8Jz9cSgLNoUfn96xeqZZd1g/QllPRt6SuzozldGu2XUhkUZSBq0RQkoZfB5ZCwbirPEzhBc4jI88ZY/khbNUjvEaZQUmtzzYf5M0wt9qKiJrOKRpJld4Gg3RAksYqlIJKWpzcCEJlNRyYgToVoXhjjwNr7dwtzNzc0NtzD3H8zrynn6RkgLOWYmf8diPCsByZpKr2Qmoqp4kM+E5kiKijVGxtZzV464shAW4Wn9zmw3tKWntRP7+I379cjga+bc8EVpslnQoqh0j1+F1q54IlYr2jTwNbR4eR8Q2OczGtivI2/hgGBQWthxREvB4rjae1AajRDSQlEaXxK7MoEKqJI5qT3J1xQ18a3a4bNClCDRszrLPvU8uK/4MpGVRxOZveel3JNKS6Jjb//KRba8Ne8rnUQSV9WQ0czF06UFXxxdf+WlOrBWLas2NKVnR8+nyzeCKszlgVN2fHUfUfNMZ86stZBt4tk9MNiJ388XtEs0RvPm77mme/qmIWphk68MTzPPqkPKhm28MLcVu/HM9+4RvXb8i/k/+WLe2KueJTSY+xk/vGIijGXLSKJkYTJbZDVk7bkfe8Ra9nFC6S3Jdpx0S6KhTSNRLDAz1pZKZ0YC4nue8sjJVowqgLHM04Y5NNyXb7zpA7NtiAUGZxAbyMXTrRkRgaXDLTPLnUURWY1lUy5UZSE7xSyZJmvc20zwM1EJtT8hQUNRlGTRqXCtd0xUdDZRp4WP+UheZmwpRGkZlSZqoUs9k/UMweKMofInstXs1iuVW7mawJGG0TiO9Q4EMoaHfORsZpQYdnKmiiPRtVyKwtWZ3/38la2e+fzQoVH4lBGtEDGc3IFTV8jGcNQGpTPRbBmL56I6RtsRlSLkzLaMtDKR0PQ4rBZO+o6r3BPXEatvx9fNzc0N3MLcf+Ak4oHB1mQNRRmaeeDk7rClsGjHTr6z0yc+qr+xSmDVLffhhSMdOi+IznzjiSQGLZlar7RLzyMv7NKFYgylVBzWVzI1h3wl2oA3E03sKd4gCnq7oWCZVE3UioH3W2YuTGiTsVJweeYf5V94lY/05hPowrZcWQFNQGUhZc+b3VEQrmZPUg1FHFkrCMImjmAVOQEi7NaR/zT+C2/bHY0aWcXzph8RB806UsrCiZq+eK7S8sIP1GqC1fLQn3jb3jHnBiUOLZaz7OmtZTaOvRgel1ee1UfEaUpqaCSyYthkw9Hec9WZq95CybyoB7K5sqkiXhrWdmTRCV1majKH8syx6VApcfJbMIVZPNo8MKsNNZEXa1htpLVvVHOPXmr2a+HZbElUvKotozGMUrPPA5MD0SNuFqo543Xgn9yf+NfmJ5IRvCpkH3CqJ6iKTbnQxy2f1Y9s3JF/V/9ELpZBdtR5ZVSW3lW4MmAolOLRWniKZ8y6oV4yXZ5I+srcNrgUeK4OvOkNnbpiSuRi3/eVPpuAJ5OomGtIyrBmS5UTY65ZQsusPI6Vf+q/8tJ95Hv8CG7gMJ1RWjNWBjGZk+uwJTJXmUM6sVNXnv0dn/0PaMm4nDFpYXSBRVnqHNnlVw5p5F48q9M8LUcupuZVt+SgWYuhPGZ+nP7E9mz5/PAjUlZmXVMzosXhy0qVZyZdofTMVR+YTWDUNWdTYzAUnenWAS8Tm5RItqJOMzZnzHRl7zsa1/y2h8XNzc3N34lbmPsVYxydBD4eR46bTOsrnt1HVHQUNJ4Fj6ZlJuOI+v2z4JICohTJOqqYiXSM0UPM1Coyqi0/S8M3n0k504cdLq3MQePUhcl6OjmyXU9cpzu0h1ezwcnKqD1ZNJO6A9FoA5/Sz2zzipUzf+TP/ExidYFr1RG1R4nDlAUlHpsjZ72laEMRi1ELVmWWYLBkVm9QZSa5me1wROvMSf0e/VbY1xM6nEnaE03NojKNKK5lx2u4Z8bgJPKwXHhTW8bWYXVGKYWPK0qE2ChqRlY6dFkwkllchcT3dVUn48gYrCy4qPmYj0QCpmSUBqffBw2GZFjyHlmvGL/wZP+KMsJOLfi0gFakaLjPJ47+ntF6lDZEE6mi4bnc8dbtebCJF7tnKJbVFNYYUEDymhzgcTnyx8vfcCfNbhB8XUHziX9cV0xz4YU7dAEjA9a8B6pGBuxUeC4f6V3HVbVc6i3WZrblTMkWIwYbFQ/rmaOxKCX4cOSOC3fnif9Z/8g3XfPVHjCyIli+6h94sQ8kHdjbnpQ0i1bc5ytdHNjpyDf7R7IUvod/wJOo1IAFVq84xCObdaQ3mqk0DKFmMuG991eERnqKjzyHjue0Y5EOpTM2C20e6F14f15cYMMbTlYmGxCn6PTIzp7QKfLGnkG3JNEswdP6CWxNl66cbY3OhVf1SFCR2ilMSu9Tv2rHJB1v+kDUBtAoCloEsYpSFN5ENCsZxaG8cG9OKLknlvgbnxY3Nzc3fx9uYe5XjDtQ1h2zLazqvXcsqUh2iUggi2ZXVjouCHBfXmnXxGIC/zCPTGbLiS2n/IBzC2Iy1iWaPOFSZBi3GBXRJtHFkWf/xLPdU3Dk/ELOmskaDDNWB66mwelExBMl0MjIJIEOjY8DT+kVXRRjtwepyMlQmQmnJt7sI2tpMAQ0hYRhNhUOQ51nQkkYs7Bow2DuMWj+n+6PfFqeSTHwsbzR04LMbGMicqaIwabIN35Pnj292mBNYqFCq0LRwuw8kw5or6nmjF0jUimULmQUr7ZCFQONJamM1QuayPOuoks9XVyo40DMNTHUvKqK4jU2wqocOoClwqkz0QaMnji3e+wqrKbiu/+BrEAnoZmunDvHaAOj32OzUPsj13WLkxnLgqaizkI3vrG3LzQpojcRpR3LdqG9/Pw+TTlm7nxFtoXF1egqsy+vhKkwx5op3TMmWL1mDNUvAzMJkzVL3NINV9TacW4PSBFGtWe/fkHyyueN8O/dhjfzxNF2OBJhnWntgikrqwiLNjRl4lq1zBKofUO9zPgl8q15YFXvfywmHI1ELqbFx8LX+pG1suTKIMqhSkLbBW8yq3JQFBUD0XgGNuhcsfrAKnCQ7zzOwln1HNKVLg8sxlGy4yotgZkhVBhWotrQ6pXRd6wqcKWmV5Yre5LSlOJRuuchz2xloh5XRr9l1Aolgi0ZrQRdClZmvEwkAk1+Y2t7PuQv/N78jFIKa26TrDc3Nzf/r1uY+xVDxbn6PX+qLWMQel2BFoJayFii8rzyQNGRvbpw5I5P04l6SBTXYKLBVYI1keTe+9s8PQlLby2Xbc0mRgYT6OtAMUKvd+zVG4MLhKXQ6w3RWPbxxGBbjAiDBBIGciYr/36nyiva5cKYDsxT/b4D02kskUhAS+YhP1OKRQq8hRrzy9TjH/L/IukaJFHEEs0DjUz0Zkt2C2O29KpCRUtSFfvpzEu9Z7YVSTck7QkrqOBZnOXNFjqObJaRiMOVxKIqVmURqxFJHPKVNo2MqqNmZjUFwSE6k/As1mKjg1jz0+mZrDpedMtaKxYVyEHTpoFteiN7WI1jNYG7dGXJjnpNDKFlKgFfEtkIS5t5kBfu9BsjNc/2J/7Ztqy15dP4jDYrfq6Z65qgCyIOrVbedEvTFGIxXPeOu2WA6Y68tCilGEvHJr/ykHp2eeCcd6R5oXcPtPPMZCLeLoy+JZmZoleaMpFMwqc9P55fGOoN1XLmy2HDlCqe/T1ramiXSMlQLwJ2ZfWGRnqyd1QyIQjiCiKK4jSjr0nKU0tkKYWkApTMSXVUemYIDUVnLmZPrWbcYvBlIkhk0A1X6QisKECwDLqlkhnRQlsm7sobu2zxAqYIf6s/UcnCIo60OoLKPNoTYgKNWTibimIdgzpw0Q2jqrBKMDaTVMDnyOoMo+lYacjKYAVcylSxZ5N7rIkom7nolqM5AIrGjFzWmc6/UPmKTXUbfri5ubmBW5j7D0QXVL7S2RPFBtAzu3ziVT5iTX5/M8XEoLfcyRvf1RNiA6VRbNYJGyY2EpGoOPotSmm8ymzkjfvywvPyO3BwURuSMVT05FLR5Jlh2XCSGsp7Qa0Sxba8MekNWz1iZMayUtETbc23tSG1jhwt/17/4X2BfBnoyguYhYtVJKNxkqjpmXOgtYIqiaIdWhUW2eLlhDYwUTPamrG0YCIqP/MpvhGVgLL4uUA94SVTSUcVhY2dMHmklQWlVq5+x6Raeqvxa+HSOGxcEGXwcUYwOCZCmd9rN5YjX+qPZCXMWLyteJNCIFIJKIRF11xVR6hG2jygZSYpx0XXZFtR5AGlhVwKeapY2vduMlsW/DxiTeKb+ZFFC4sIrUQaZqyd8Wrgo7P82f/IoFqiGAoKrzKvwdJKIpaKaN/3dJRkmPDMHl7Njnbu8bFGnWt6OpStaefE7BYoEW8zH5fvWEkkZ6ncSF82fJs7VNz/b/bupMXeLNvv+3ft5mlPGxH/+HeZWZVV10hIYAvrYr8Cg2caynOD8IvwwEN7aLAnwiOPPPDA+C14YjBIYLDk21TdysrMfxfN6Z9md8uDyMGlSgYNrsgSnM8ogmcT8cTg7Pixm7X41N9R2Zm7/IGtbngqDU0sFAs35UBA0TkQKsekLckrFUIwFZJrVtMzr8uBU32LrUFViMby5G45LJdsxyO1DGRrCL7mJj1hXKJLE6PU3OuRnF+2N2fb0OeB5Bo8M9ZbxrDik1tTpUK0NclZztpwzhV1HvigX9PIQJszW7ejyjO/bX5NoOZMQ1sGRCoynrqMiEns7AJRQ5eESpWN7BGbSOqIxmBNJhpP4GWFN9KAZC5mSTKPnE3Lzat7mqr5uaeLq6urqz8J1zD3B6wtNLJDsmUoa3KacAK/2P2Ov9n+gkEW7P0SrEH5Fs1Q8cjZr7D+gM2RHW/YVT2zrRAt1GEGFSoTmPqaUTtAqEpkdjVCosoDU1oyO0twjjZNrMPEJp148BbxFwbb4gg8mddQBGcTk63J4mhCQlKkdUqsamYDNioHs+aNPLIsZ3KuaRkYtGGZTzRqmTWRiuWr8gNHu2ShAzd6pC2Jpdux0IGohr25oZaZuakYSseb8IHKQBtP7OsljpE2j6zDwC/yJ77zX1FNmc/NHVJ5jI7cxU/0IXO2nmN1R1Uys/TUaUJsT7KFLA7nRoZ5ReufEG9wotRiWOqRSma8nbjRj4z215hypM6wno5o7DlqSxUCaEPPwK09srUP7Jj5PN4ytR2j9tyYZ07S8KqcKcaQ1VCbGSmZ8FIbhlg7tFRYm0kFijHUs8cEz3vdkZvCOgRKrHEUoqtIzrNiwEyF2VfMtmVfrVEp3CRBi7BIe6a6Yn3+xF4WtEU59u+4SXu244A7bRm98lV84qNvqPOZB17TzydibfFhhtpQsiNpR7Gw5ECWnpI7lJfyOH25UMmMiYpzMy6PzNQsy8z7+Xd86d5jNTC4BTfzjidzy5xXoMLsepbpGW8So/RUU2a2HRd56YISjWViw3oYyXRgBr5yv+UkK9QKbb7wLAtq9SzKhUoTC/Ys08B9eGZixZDXPLcL6nxgyYnZVQStSEbIwCyOWToEyDiOLAizgyw0i9ufeaa4urq6+tNxDXN/oMPxNq74ns+QZw6uwo6KtfB6/sKFkWzuqcuZoC//aD7YdzgDs+yx4hhKw+A7VAwRj7GZmok6RVou+JwYTM0oLXUc6Dhio7Dyz2i9JpmelAqPfsV9+oLYQAIiLYUKLYJJwtn1WCLFVFSaYVQShtnWPNsVwbQ/3arsWcVnajdiFEwuDHnDg11SUWjyyCKNHJYGo8qRFZU+cyxbSrY89lsupafMNZImuunMXfWJWFesxzObLyduzZk+Hvi0fMeP+oqL6Tj4hkOzZKUDPYmoDXvnwRRqHfn2+JHJG76kNVoPHOlopkCXJ1b1zLvwIz7fMCXHZ6csuKCiXExLk2eiVjgpXKxgvdCnGWtHtiXT5YeX28C5IqnnoVrzpX3HrB6XCus48Gbe827e8ZftBl8rs6nZ5IF7fcBLYByXDNYyac2oSsFBnQjS03gFIuoLn02PNY7TeUGVC84YtmnAxz034YKxI6m0dObI6CsUQ9SaIifUOSyZUVr6fGFTPdHlM3/Zv+L7ZsNzX7OYhX3V46cKP0a8Cot8xqeX7fRD60nOsMxHijomcUzSI9rSlBEjmVheasctdOT1tKcLlt6PBByXeskDFtLMKhx4PZ44rixddeKoNY/Vlu98T60DMTdIgaQOUyDUPbFSfHWmlyOzWi6ywLiAqqWOEXFCGyPOOVbpwkVWjHPNZ/8ep2curqVhxJcAWjiaFcVZLJkCJCyCATHs2zV3coHhTMwRb/3PO2FcXV1d/Qm4hrk/UCZgWJJOt+zXFUdnOTYr2jQw25ZNeqLjjAr0OtCOiUYCzk9UDOTscBIJpqIUi7GBKVc0jHzRV6g1rDmSsuGB1zQa2VX3JHNmzZGLbTAI1hdmW/HFveIYOyoXuBt3RGmIHpJkDIZGXy47vMsfCaZnr2um0jNLRRCLEWUQx+fuNQtzIKulJSDZMceeyWUuVUUfn1nmibv0yN5usMBTdYO4iZIdtZs5NAuMFKa68GRvOcU1t/7AQ33PPC147eFd/A2n3pNmxzHcYurIQgaMGRCnOBlets2McKpWdPnMjV744l7RaKCKhnsdaNyFXid6f2EdweQKycq5sjyZVyBKk0buzRcuaU0Wy8U3VDpQKSz0zGaKLPWArQvb6cLJXehwGC28nQ7cHANpfo+Zhc16pGiiNWeaoESpKcFRFcOmPbDNOx66V2TJ3OiObdhzU54JzvLQrvBieeo8i2mmLTPv50AgkcOa6CIdS27nji99zewGRlfzua+YS8Vo1hgG5ioweWHoYVTHvGjIwFAt8GNh4IYuHZj9SF0M+96yr1cYEYoKVRK6MsBUKDpREFblyETNiTWGgsUT8oVzWnJMW2YvjHT07oKaClGLL0e+ySd8uvC9f4doZBZPMEuMmai1UM+JnDswSpcjdQk88pZiXsqJxFRT20BjEgVHpYW7eOaX+om/1m94am6ZnSIIg6woySFGqPLIQs6U8tK2rtczF+kRFZZ6YsHAtjzhxolYrmHu6urqCq5h7o+cxonDPBMcXCrLZD2T69j7DShE51ikPRfXEng53D+wopgbOjYszQOP9p4TDeo8EPngvkISGKcs4olnt+YkLcEIF9kiCEez4WCWnNyCrkx4rTCx8Ow3JGcQIwwm0ulMXSZqO4IUgqmo8kCVIsYOWPUc6nuKAUWwvLT92tslR7fBauamHGlMwJiEuEC2hYv1GBlpzIGorzhULWozHT0mBzR7bPC4S0ZrS3EOJxNz7dGsdP5MssLZLqlyBA8mRRZzoU4JW0dMzBRbUznlXfods/dUJrLXOxqUT+4VfTOxM2f+IX+Bz540FkZWLMzAR/eGJ7PiQgMqvBu/4MRzqnrObkWwjjfhibs0sohnft/fcs5fUZzSjgdELVFrXqdH7i6RTi/sO4/RBqxQFMa64we7RDQjYUlX7Ui+JZUTk/iXRvS2ZTV9Apl4qr5mX22hOJ67JcY8ApZFyGzSM1/nkXBO9PbEqVuSmhZouLEDFQMuwaArlECwNQXDaVnjTOJihKUMROeo9YyfBFcKZ79knCuiVVwRFmVgpKIZC0EqgltQpZnUWfaypQg0Or7cYM4zTXWh1yMDXxOSYTAtsTRs5hO34w4rgWXe8ewWHMyGg9xw0falLVcBNFGh9POAs5nRVQxS0ai+/N35zEUMzhacyVhNbMserRq+5Pf84H/FhOXgO07F02ugjTN5rlhVI1U889RtGEzPKBWRCiNwYM2fyV/SyonPn3/AqPl5J4urq6urPxHXMPcHZilMTonZMtY9o3MMUmHEsIknZutYl0TtIpu041BtSapkEkfnuMg9o62oS4JQWGgAHM/5hif7is6OiCts2LFmxxfe4gpQhESDBMvsGopGvFwIeASwJdOaM2/CI2dvycZQE0jJ88v4Hety5pJXOOlxJdHIjDUZr4UVJybTUekIRdhMAyftKG1GjFJM4VnucBo56gZfLuA8gkDKvC8/YEfhQYRzafhY3dDpCa0L5+iIpuL75hWvySQN5Krgh0BvzlhmTosNhhq1hmV8oJVEPSrP/YpJEw/1lmKFYGFhZg625a/1z6jrmX1aM+cllYtEY1AjNCTUODqd8W6gVBavGVcyfoTlAJtk+OyFNi7ZG0fSluUAmQCV54fmBmccReHJW7KLzL5jVo8VJeBITcPKGRZckCbT6sDGPXNwW2pGfq9vOaWekjKpcVhm6snxYfOek028mda81ifqNOGWiUO9ATeSgYUdmItlV2+45DWbsOe9/577/Jnfup6SRubKsU57JDnsIHyq1gy5JpmCkUyXJibfgxZWQ2JzipTiudy8lL7ZxgNbPTDYhlIMRjPGZbAvHRjUK1jPkglHxmlmbDxVUqbSkeeOLIazXxCtBWNxJaFAHSNnu2BpH1nLmeoyY4pnnt+zaQtddaAwU4plloZ9u2WZZwINbb6Q7RqbI4hSl5FDtQTjgcLKRG51R1eOnMzfJ0v6aVVxZl2eaaaE/emC0NXV1dXVNcz9EeuVsJ6IFwUTmG3PLA7F42xipQcoBSmFVZnJds9ZtmSt+WLeUiowFBozImqwcSYVz5EbslRkIpXMJDwJS0WgiZln2ZBMRRHBZMHEhE1CVyLJCbVMWA2MdYsxA0lrVF4uDHzmHav0l6QmUGtgUU4ks0GItDLTmCN1Gci6oEmJbhZcdULiic/tDQ7o5EJdAlLgLl64pBWPLToSggAAIABJREFUzZJ99UvG3LPoJ7pxxlYLrBSakmjjkclWVGnHyS5on098Wr3jzJKLX7+EArfBamJwKzIDS/F8HX9D44SnsmA2DWMxhKqnqOOjfUWnF8503M57ZluzKhOK4nPAuITLgabMTOZli9JKImBowszmNLN5LsS6ZlhtONbKqXM0k+JNwseR4mBQi9YLfCxkX7MxO2zY86m955lXaHFkC6PtGbRFSkZSoEszq3Rh7Y7MtmFSz+watBSyN3zeVkRreLYth+YNP463dM2BrjpzqHs6PSNRcZzJtiF5QwyGfFlQtGdOC7xJbNIz/XliU860ORFySzsFPi5f86g1qV5w/3wg+UgXIvO85mGxonGBtX2kKiNYpc9nXsePrM4Hnqotw7oBgb1ZUqVAoxmJytIe8JrZuzWdBE7SEIwj24qeiVig8HI20ySwk0PqRGtneh1pzYVBtizaHbYIGhLn4og+oKbgRFnkPTYXGg3MBG5IOCYomcmtEJs50nLkHQs5MrmOSVoCNTWZQsVpuuFcXbi5f4u19ueeLq6urq7+JFzD3B/ovPLaGf6FOi7SM5kaQ8KX4aftpRmKQ4uhFHinnzmVid/Zr9AsiC0oL/XQ3o0fuAsnjmbD75v3YAoXup/qd+14xRnSM0O6YW/AmJdzcrN4goXGeBbjQKMTb9OPNN3ERbcULBRPNBX304HgLINryZWnTgGrBVMEARoJfFv+hl/rb4lhyXj+BeXU87v7jsGsMEDBMJQFg1iyP2LLhSCOkoWT2VATGc1A6woki1flXPeM6riYimwqknjCoqFNBxZmYLIdqh3FesQlohG8UbJYTuM93fSRqRL2vqMUh08DPUdicSxSYG+3OKPMOHCGJJ5t2tEPJ0ZpmBrP0XWohc00sTAz/T7y9odMbxJfZMnrhyd+uN3iJkvJDcUesTZgJeLNwGduKJUlWYtqYa2JV+cDIW5Iaji1lpINwdR8rt5gy0ztCnflkdEsCKXncfGGCYe1jnY+UWyNDYlnu8K6iUtXscjCNlZUYSI6y77dMhbHXm7R0pBzxWxhjgtyVfNV+EQKygfza3ay4ug6JAhn0yEaeH8OjJXhVb3nPFV8v3nPrrpBS+Gd+cw2HXhrPnKcWpb+TD9fCF3DR/8NZ1oWnGnNhY27oNFTSWaVHknq+OBeY2clmoa+zLQhotWF7AC9sJoHdrqlLF4K/LY6I1p4aNYksSxSoNfI6ynwwbRoHjjYhkf7hpPxbPTC+/13vHeWfbvk6BZcbEWnFw5mSfALDJkznokFRRyoUulEl2YCHUO54av3fx/nrtPX1dXVFVzD3B/x3uM0ICVQSaBOI8H91MpLCmRDO8HquGdwSyoUKRVptUCzJetLW6qawJ17ZPZb/C6R+pqmJLKDu/KBO3nirX7mwbym0HOTnjm7lrPZoJIotmYoBbFKbeFitsTxxOAXRHUUK1ShUOpEFrA2MejmpV8r0JaCkrE2g1SoceAKT3VNdBArRQjclTMmZ7IBGzz3eaRKkdBVBG6YTMtn3mJNoP6p/leTAqt0oJ8DU9dQrPI2/4ixBRHHKDXR1byZD1RS0cfPfGrfsuJEkJpRa3brBZeqw5CxNlHHmawVg2xhmphcg7GWKDXJtAy2IlLz1fFHFv6Zi/csy8wHc0Mohik1HLobwt878+55T+0eCPWFukoIa5oY6MwT317+NcVVzFIxl5qj3eJHUGo2YUfwK27lRNBIPUFr4MHzUwCfcCGBrzBTj5Uabyy1LzzXDUuTWMwXSphZ1DUDFZEGozOlGLJaHv1rgjYMbAgi1EkI0tG5CeZCF5SYlzy0LR9lw+wajmWN3SaaE+AC79InJFluwmf2i19xrhcYSczOsZeeYhNdrgi+Zlse+Li+ZywrsgVvMkEte77iVUjsbcu7/D0kw7GuGV1FRNjogfvpAV9fYDKM6lGnKBUtA3fxyMHesGJP8BWVUZLYl7Ok4lmWE6NtuNg7RjFIGVHxFGt42tzxH+7+X7blxAe3Ja5eoWJwphBKodeBo3kpubPQMyfWSMn4kvGlILEwhfHnniqurq6u/mRcw9wfso6YVgxWMFpwJqI5Y4qjLRM+RQ6+5dK+ZhhXjPOBhgkz25ebgt5SqZJSw6QbLrbmdLNlcBYDNHZiFc54k6lj5pfle8byxA/tV/yV/RbrZiZWoJFKC6USTnaF1URxS26HA42ZiWKwLqD55XwcKoDFSWRZLlzsCoqFIszi+a38mqNdk1vPSE81BUwLc2pwJbI2e5Jr+LFu8bnFpkRdX1hnJYlhlopWEk1WlnGm0Zf+rot44mI32OLp40Sbj0w2ocXxNhyYVWntmZAXtHbiUjYc3JaTafliXrPlC4ihC5Fj1QKFqakQU5CSyMZxsitKgSfvWNQDd+Ez3kAh0etASRW/6+8xHibb0ocjN35gaGu8D5j8yDrCan/mtj0jRfld9yuiOk7aIUHJvfA3HvoYuJ8/MkvDURfUZqYda576BcU0zN2SOE3kYnm29+zsW3YsmNXgtLDNB7YckShUviOWnkWceXVMZFE++47RtogITQ68Ou9w8syb4UBNAttRyYULPcYWghqGqqI2jroudOeJlHuW8UyoOtp5xjWRs++ZpKNmZMbye/MtVYpEZxEy2VgKLefSoUaYjOe5qymlptNEsjWjndhODwTXUs2ReV5Q58zDesUi74mm5tXhI1Pj6O1AZw4sp4mDWeJSzeh6Og7cpGemylITWaVHdtpwckt2pmNnas5h5l+2/wAjhWQMJXtu4one7XnwX1GM4jRgpGPSBq8jN2nHulyYXENu4HL44WeeKK6urq7+dFzD3B/wxhMrgwwZl4VMQysZVBilpZjCbdnTzIEkgR+bW/o0ER2IifTMLMqZoer4Pr1DskApeJcpAlNpuMQ1rZuJybEpF27nC70dCY3hJnf83v6SqBUVASuCkgDBmkzVzNiU+Ox+yeQMxgpVujDpAh0rju6Gs7OcnSWpB31FshavI8k2HMyKSM3GHHmtP9C7gbU+U5vEHBou+hXRZaxmOjkw2BZfJqJWoJYoFtEJcmTnNjgT+SZ9z6/TB5gLf1N/SzANaoVUR1Zhok8jC0n0RUmpZ3AVJwezbTjohoqZXFmCrXEoisGiuDwz+gUX22CNMuWKg+v4R+Mnwjgzuh5/yXxn/wGzWWDMTDaGS9uwLbD1j3w9feRZNuSyxswLnupf4fyROVfcz0+cfUcSS7ItKoZdtaBPFy61Aol9btk8Bb6eP9I0A2PjOfuO3/hvOMiau9Mzx03LanyGGsQWmnzhq8Fi4pEYV9xOkX6c+L9Xr5FkAaFzL2cgTXehCxf68BmmhmlpeVzfsWvWaMmoCj5HpAjPTYPNZ9rR4vXCF3fDoe4RhSZkcj1jirA396CFe/+RJ7ZseUYk82o6UOiIpmK0Hck6KqBQePIdk+k5dSsUEKBLe7RtGOjxqhgNNDpT2ZGilp1bcsj3HOwKNJCTJwbL0a3AQtCa2dTk5KkkUGkgUnP2PSfZMFeeLs1YueBLJJmG+/gjz+4VLieiG8lSY0thcEv6NKLGIGPkfNj9nNPE1dXV1Z+Ua5j7A9567rcFMx9Rt8ZbhQQRsOIwVcNTdctUFmi0mAR1TrgUsQ5IhaQ1lIJFqLgw2wpUiFhcyaTSEnYbfrBbznlEXeI+fsfG7ZjE0+tAkhE1FVktyRjO2rLlifW047nZcDINajwZZbQNt3EG81I1P4kw2xaDoqoUhILhLC2aDRWJIpajbHGaObkVZ1UeuzcMuqApE0ZHbspnotSs2POBb7kZ9/houSkfeO46jk2PyxERz7eXiXPdcZEFR7+kDyeyRD7aDa1pOc8NN3JgU44MyfOpvkPSxE5e8aZ8YualLEcygBYqEtYKmzRQiiE6jycQrfKduyd6jyT41L/lqAucZlQVPwdW45mjuaHiQGocIx7jIuebnof6nspuOduG0hjaY6EAWTOaHKUyZG85+RZSTbGZbB29qZkqz6WzbNIjdYqc7JZjX5PJjHXFKp45ugVdCfRN5H44IQOk7PiL7YqnVQUpsTEj63AgNjUuFUxV6PtntosLf1H/R/yue82x9FgTWZ1PhGoBKpgm4ZoL595wLm8ZbI3JLyVgKm04V4aTWby0SgNOsqCSwmo6MZYbxtgiBpJVsiQEg5LZuZZVDJTsKeLxJZPVsWsWFKcYAg++x9LRVUdGt8CVzEf7mo0fidGwq9/g85ld+zU2z4h5ubDQEvAx4VKgcWdEMlqU6P3L58IUBvOWswwk43lTPnE2LcVaiqnJCBh5KW5sF3RpwmbDQ56ZwnRt6XV1dXXFNcz9kVICrT+y4sxelnjNeCJFHdYEEOE2PfNYLJia6CyzNXRm5G38BDYyh5ogPbkoSkd3Hhi6iHoBhCgVF7PFFIuYA1/qNd+XLbNvmdWiWFwBNRnF8qZ8JNIgVvmr1a+ZUs/ebhBjcDpgjfCgdwx1Q6sjAUtQhxGlyE9BUAYqDYzS0mYoRVAKYhOf7BtyNpQszLQkPNE1tOWEE7BZuClPfD0/UrwheMfH9h0Ht6RUnks+8i/Wv2QdjhztgsE68C2SEilaglsSjeFL2OCjQchUUnDtzFzXBGqirRHJ9CS2Zcd22pNKQ/IO52446YZeR4Jp+K57h4rFZ+E4bwj1gvoSKZK4Hfc8VyscETtbujKRXE2uGkbb4jVRm5EQI9FbttWOKk2s0ooshomWSgZ21XukEhZppl18potKokeD51P9iruwZytPHGTBN+PEoXYEaqw1BNNRmkS/y5Qmco4VX8yCCzV4uNELr+MXJt8SnCUYQ2hakjnzvb3jqVozF0+tsEqCWBA/UzNSrOCJeHthX31FKRUHaVmGxP28IzlHRsEqokKlE8d6jZkVb0809Uu5msne82Y8YipDl0eKeo7aIghOhcF21GkmOseohiI1MRY++a/R/LLFP9KSjWHnb8EYvLEohdGumNVRjOM+P5O8Y2t2iFtR65EvzT25OEbXoDGj1oIWRtPwKFtm25IlM2JRPEpDZmZVBDFQXKYgXKbLNcxdXV1dcQ1zfySlga6t2NgLO454LVhNLMKJY7shSM0X8+ply4fCMs8seeSWzzRh4tw1dO7MowijW9LNI7t6yygNWRxWA646Ep0llIYP+h4jcMeRZ3NHx44g9UstsjKCRIJ0NGWmnkd+8Pdk4WWtLUd8CiwlgirZQiiWIkpdXooFL3Sm1xM4yy3PaPa0JXIXn5kbhWzJOFKu2Nk7VJW+zHx9/sBKZ6ZFYIoNZ7dhX0fGpqYtJ5J4XMmoKVgKFzziW2yaWKczUTtyNgx9y7muKWJYhQGOntXxwh2OB9vhXSaUBnGJ+/iIOMeb857azQzZQhnxaWaXJtRkns2W2VRE0yJiUQGfJqTOmJToZGZX37IuR8RUvEqPfDKrlxZoZqIQOVeO2lwQqdgvlqymjlWasNHyOenLLVkUkzN1GdhyxLueYD2Bnpwzh1KxTAOqLdl6XuUv/NC8JmjNJ1lwlz/RErgUwbjIWFeoGNQUslgG35LEUJLjNZ9o8sTcVNR5xuRMKCuyWHZL6GTPZCwqFRfb0tozY7pFirKcI8V4XDRUkl5apcWAtIlsGrJ6Zm2xyZKbwmQEoxU9I8Zb+jCw0RMTnmWqsSUSpUKtQA29HinSYZg41rc8li1VmajJeJnwJrNKB3wOL+3TBAqZIjWT1Dz4W5DCmRZEuYtfWNkLy3LiUW6IpvCyhq04zdhS8KqIgdooak8kupeC3baiKhH1lnOY8eba/eHq6uoKfuYwJyL/OfDfAxb4n1T1v/2D5zXwPwP/GHgC/qmq/k5Efgn8a+Avfhr6f6rqf/V381aKUDOPN1BaRAuRlkYnfImswxMX01CSEttC8cI2ZFZpz++XX3OyPTHXSMokZ9jrhqPd4Cg0eqFiYqUDOVhW1YFiEhcWnExDtMLZrNAErih9nHk3/0jWwsfNLQM9glJnpZWXPpaVZCIWrBLNy23aYBqqfCHJ8qVQrAhkh8+FG92xnhJfh498dGuSOnwpZC14In2aKCo8m5dgh8LCBQIjr8yOB1YYfVnx85rIxXEbH7ixZ6rxwgO/IGdLkoo610i+UPuRbC3WZRo/8Y0+8Wp+4F/ZXzEFx3N9yyIc6VKgKxeaHMl4PMqj37DkTO/PSA7sy4rRrYhiWFc72iHx3N4TncFYy1kaki+UmDm7FY28JkXlliOj6Shq6aYRbGZKDbWLZDEcqo57PWEay8m0NGQamWgJOInkAmLBSWKZLxyanmPesDorXBK+KqyJdOnAWZfcpBMpK3MDNs7cxh37coM2BmegT5n19AlnEtv6M7H3/D5/TS4NZa5Zc+JOvzAZh/WJJLcUUSTGl5pzJTDgOZUa1HCXvqNxATsFdnLLUFoKjp4ntvLMc3uHEDAqNBLweEazZLSeZvAcqxUzHYPtMCVTM7O3C7bMjKZhZINIwkoCmzEKr8pnVuPEj9XXeD3T5jPv42/4f+r/mFGg1kBbEkEMghKNYbKO2TRkNSR11DIBI8E6+nhAxOBIrMuZc4lMpmJixiKEUrNzN7xyO6yv6Zru7+Yjf3V1dfXvuZ8tzImIBf5H4D8DfgD+LxH531X1X/2tYf8lsFPVPxOR/wL474B/+tOz36jqP/q7fq9Cy988wkE7TnnBU7ulzZEYDuzNkme/Yqx6bsweJxNv5h/p88hH+QUf9A0jLcEJa3OEbMjGMXqPiCAqdFhGqTg2G7Y849NE6wydTNTlOw7ljionbBGcQm3CS+/MdKGRkbUeSMXj9DUJi7EKRbloTTaFaBoiDlN6eNlIxaiiRdmzwelLMWTvBm5U8XlkNL9itjXFGo6mZtaO0Y88mw4xwq0+M+cF07ikyhZUeROeaexElQK3+siKZ072hlfuB6a4IWrCJcNcG16FBw7NClVDxhJ6WOhHVnnJqf4KkyNtzPhkCKnnyd0wqWclTyQ8tc7YOPNBbsAoWYR1PnCbjyzcjNGGY6mJYhh8y1JOVDZyZ55ZxIlia2YjTKXhrX5glSdSflnNTLPni7ynErDTiksTKCq0eabXwDqOGOuxNvPVuOOv25aTXbBrOm6PA1Mt3J0HpC10ZuJiW/rDSHWJzH2GJpBbw419oE4XDtywDk/gA0v7xNf6hbN4Ptp3nPSO9qis3IxvAs4qlQkkK1gmek0kcZxdT58OJHGMXYUphofmLe8OH7nVPaNf08wXhsqjUvOYbnmq78hacZSahUw0jDgEK8LRrzj7mq4MjOJRKyzSwFFbHtx7MopSWLPHamGpI4swYK0yVQ2rsENQlnKgmBXrcsQ4pU0OCsS6Q1SwORNLzyYcCK5lloKKhQKoxanQ6ogvF9SA6kyf9zzYN4golkSXBwrKqt9c68xdXV1d/eTnnA3/E+CvVfW3ACLyvwD/BPjbYe6fAP/NT1//r8D/ICL/Tnv4ZHU8D46j7cmVJwp4C4duRXRCVwKC4iUSnUeL52AqcnQczA0X8QRT46NiCjQMdPlM8TUmZ6oM7UOD6U6szJnlCrKc2dMx65qoDZGGNmWSiYzWcbQGFeXRrrktz3xTfsdtOPLRvObsespPh82dKnMWGon0eSCJozITqo6mnLjVPSZ4GgJJW/wIg99isNzIjlU48dG9o5BQsRgbEQo+J0SPzICZLnyovmHnbrAm0ecj76cvtHXiZDJJWo71GpsCzg60QRFT8X7/iLOGky4IXYWdtmgxpOxo4kzCkUqgzmf2tTDWhqPZQDY82IbB9EympUsXotT0dsBZYcoGUyai9hgdqfTlYL8vwio/M9qe0XcE4xAVdmVLxYlquLC2J77Lf49sKwYc00bRZqJmolilGSMNgadqS2TD7GCRnuhj5FC9RuwFSdDFHfiJb6YTn9ySNhhKB5+7G6yH5BWfErd6pA8Z2pFWL8w4fkivMbz0xi0ox7XHD4lfnn4Lq5mztnzW1xSpmbE0eaDGMosli6PTES8jjQ5s3BPb6USaG8ZVSzSKmEJOHo3CTEWuG6IU2nJGBC6uYRUH0twRCzgNeB+pdHxZ6WSFLwnjMpv4jAB9TlAcQ/GkVJG1JlUOyZkH94pWJtbxzN14YjGd+avVL5hM9bL6Z1taSagKThLRWC40VAgXNURreTXv6dNIdmuyCh1nrBZ6nbEasPNEQ/53OQ1cXV1d/Xvl5wxz74Hv/9b3PwD/6f/fGFVNInIAbn969q2I/EvgCPzXqvp//Jt+iYj8M+CfAXzzzTf/Fq+V0XSgLiPH3BPblkuGIAav5eVwP4LJZ7oyszrNZKk40uA0siwzWQbu8iNSysutzvaXBKApmRwcH9u3VDpyG4648UQwNbG6Y5aKyTRcpOPSCFELtW64uIqA5cndMqeOQ33P7fhMa844nTlqT68J1Qgodcm0OuPyHrxQtGYyLY+lwteBDo+bE8++Z/QVF1tTTMtkezAKJROp0JxQI3yS1zRSOJJZRCWxYKWRLJZoe763/wHPZfsSVsPErX5mMAsywn26UETIqSJbJXlhyJZj+xqJnk4idZpJztLJhYd2RWgcdRmoUuKryycOq5YzK2Zp8JJpzxNLM7IYBj7V77jQIRSSbTDzgcE0vJp2qAqDrTAZBrNmU45YVcgTY9fgdUBLxhZh72pKBa/SEeOEdZx4OxwJGIo4erMnlwUnaZl8zd5vONuOu2bHt+EDO/eenBqyE9JNwmpm9g1UBSRxdj1ZB6wFn5WdecVnuwUa7sOPjGlDjhXbcCKUjufFDclELtIScoeTjEuJdRiZfcNka4TIJIZkPNs0cOO+Z8lEL3seywrNb8jJwmB5Mi1Dv6SQyfBSPkYncnF8qbZYlDwH3s1PrOwRXKbYzMnckNRjVDmVWxbmTJnhs3+LT4nZtixPM0WUySxIpnlpuxYTXZmR2aPiyGJIAnUuADid8GqRVDCuxeWIQVnNe7blmSYl9mbF2ax56cQ6s8kPvI8fWF32THIm5oi313NzV1dXVz9nmPs3rbDpv+WYj8A3qvokIv8Y+N9E5B+q6vGPBqv+c+CfA/z5n//5H/78PzLFiUoFYzLWDWzUYHXmk3+NJaEU3k2/p58zTpTneoEvhX56oqPFlwsjKwoVjWZWqTCnPeH/Y+/OeWRd0zWv/+9neseYclgr19p713S6qguBkGgJl08BEsLBxeAzYPT3AAe7nTZawsHFoNvrbnRO1alh195rr5VjDG+8wzNixG6pVQXC4KBCED8rMhUpvVIqMy49w3UXR8qWkj1BV0zK8ImveZf/RCUjjQyMaUMumrokshYqHViMoy0jVRIGtaKSwJRr8Iq1Pl9qKOwtJwqnsqGVhXv/iNYJUyKvcoNhJhWFKgtaFbzA42rLKIZXdYuSjEgEInUeaVJGodCxcDQ36AKUzL5pOeuKOQniNFkcG55xac/e1LSLZ2HNoeowpaCqwFszQsnszidiaJlVxaFaM4cV63RgPZ9x9UytFt6Hz9g0MYw93sFSOxZVCEbjKLRlwktN5yIxW36z+Tl4QenAu/DCng5nElkci9Q0s2dtJ/b0vLgdJ+lozYQ3BV0iqxjBelRZuF0CgzREVTEXiw2J7/UtT+aOJAoria2fmBz8UN8y4bDG8qoK328+8JP5E+I1zbliX26ozUKXThAyJRmK1XhVEUtDoyFnTZtOPC09B/klIgmnBK1HTkphtSYqx2gaqhSw0VCiEGNFpQPkSFQaFxJiPYrCa33PyYAO44/bqoa3fIOrE/Uy02aHDWd6OdLoCVMSX0rH0a5p0pnYaH4dn1DVGWUyP5dXlrwmFU2X95fRb+I4uQqlI2u/5+AE7WZW4omlx6VMypouLNQxs08fmf2GpAFjCBLJ2bJdvmOsHii6oMpCU0YKDkuiJMtSBIqioHB4IrConoPcMb1vUE1HyNcwd3V1dQV/3TD3HfDNv/f118Cn/5P3fCciBtgAr6WUAiwApZR/JSJ/D/wK+Jf/dx8qRdDa8s2wp64Hfs9POakG4TK/s4ihFsEpaLOnmAIygxXelc9kEj/1T6xGMKGHULNvCu08cRDFpFsGV3N2G86x4RQt6zLgk6GQWZczPjsW6djkE1UM3JRHvuOeRdc85ncYgZBeSF6oJKEU7MpETSSZzNa8oSSgS+ZLfsCry2HztszU+UCiZsRwlh2Tqlikps5ngm65yW9kJXwz/5FXvsIWOOkenT2r8sqdvHKj9qS0JpSeUGv+UP2SYgK76Xsms2KwayQXdv6FV7cDnRnXDdZHiAt3HPjiNCmDni8teIvTfC5fU4eFXt54lDtUCUxmRZ1mDkaoM5SsqfJAFxeeEJR4Ql0xF8ONvKKDgaw4tw4aiwuFWGDtD5egpld8W3VUcqZfVlQEmnikcYKJE0LhbDqGvMKQYNA4kzhXFk1AfEKcIpuaIJ5GPBWQqTnSc9CO13bDqBxMhVaNeNNQlKGeRoiWalScbcfJb1jM6jJD14zUaqBfEqGKDNJy1C2LWPhxDBpGWLRGbOE+POFLRY6KxVUcVY+ViTt1BBRNiNyWb9Em42lRFkyeUDpzG14wKXFSLQfXElShBUqCVAnFKLzSFBG+nr5ggvCDvudQNZQU0CJUJRCkRXyiWxaQQGP3aHViUj2D1nyxP+HYrghGY0omFk1VCrYsOFG4FKnkTBFFWxZUXrgLb7Qx0oSFl7Rjbm6R5MgapjIy2p6xbYjJXG+zXl1dXf3orxnm/lfglyLyc+B74L8E/qs/e88/B/5r4H8B/nPgfy6lFBG55xLqkoj8Avgl8Lt/iIfqbc3dXONKTQoVK97Idk1KhoLCqMBWnhiaDadskShU2bDYQuPPPNkHumXPqaxoUmFaDZdtUuNYqBnl8uGZtCKmQrAVNr2QlKBVpgt79FJIpaYynp3e89P4B6IDPITsqJeFtR/5obtnLg1LsKgcofbs9Q0eRcgV2kRmauo80aRMITLoHTVHztxyFkfWBlUSVYEQM64spCK8lntRPbQPAAAgAElEQVTOVU0ETBlpSBz1mrnu6NJAkybeH88cdMtRJaI2PG6/xukzlRrYmxtO5QMrGVlzZs4tN/4NFTMntyIqTaf3PG7egy5sy4jB8zA98Wgr6uDxynBWDasS+Hj+go0Ngxw5mYonsyVrg06FO//INh7o7Gee5Ge4XC43M03PJIlFWdQkBFtREBwRFTPYSFtGdsvCrGucVBzUig/hle/lG44WjrWhTQmnAoMYou7oZyCdEBPZpgP14pl8xcm+I6SJNhwxtnBwKxZdscoz3XxGUWjSC1jNu2PmVd5BvKw85uiIdY0zz2zSG54OnRxKObIIQVusRGKy9GWPCYGqOvOi7lmKpRSNptDEzFYmJAjHcENjIpYR3ytsBB0iIRlsOxFVy6aceCk1p9Ky5YSLkbosNHbkTa9I4rGpIcuGnCK6WHpmvpm+I3rhUK8Ym4qX7pa+THgtCImX9R0DFR6HQqjDDFpBSRxVBWqHzokp99RlpsoDIa7wWrFYx7GrKCmQJF/Kr4FFO6KFugRkf/iH+HO/urq6+v+Ev1qY+/EM3H8L/E9cqkn+h1LKvxGRfwr8y1LKPwf+e+B/FJHfAq9cAh/Afwb8U7nsDSbgvymlvP5DPJdJ8PG8ph00w03PIhZBsQkn0JlGZmqZsSVC0kyqQUwgiuVQbvFSk8Vgx8zdfOLYjJxDxQ9NiytnVCn4DFJgpU8UJZxVxyQ1W94wJEzOuHEkNQlnznzha0TBYjpS1igxyNuMzgvv0wvfm3vemh2YyGwqmnLAlxpXJlxKFCVkEWKucGHhyB0qJWpXCGSCVKiccDqiysxJvUPZGZcTpmQq5anLyJO9JeBZdI8qiiIDb+GBVDSkjNUDkoVg9OUGZrxMohgEHB4rmWoaMTkxWcXB3rLPO8Rl0lihlzfGoFjJyGPZ0KojdSnclx+QeQdpQEtPmDsm07M1R5JV9Bx5btf8vf4bYjRE5VilE6OqcDkgKdPkzP35mUG1FCpizaXmhZlZaU6mZZUv0xaUZIqc2c0TLhp68ZicGeoWjdAF4afzkX564UH9EVk0f6v/A0ZjOdoaLYlUNNbMXK5qCjoVzKIxIXE2PU5FYuVpSiLZCiOJ2/TMrvqeOTjG/J5XfUuVRxJCFnB5QUyhKjOqzryLr+RYcao79JywrnB3PnPn3lj5bxnili9qx5hadmHGLgr0pfcuJU9WmoRjFoNB44vn1e/YrWdEWwqa38sHDusbBmmQHy8dtMvEojp6n5mqjJJMl0ZuwyuL1rzpLWflmEsFaJIIvcnUaqbLRzw7EoounrmJEyoLr2bLwW4oZBpmyJakBCOAZCo8dV7o8sAqDHSlv26zXl1dXf3or3q3v5TyL4B/8Wff++/+vdcz8F/8H/zcPwP+2f8TzzQdj5z3R/LUUZaazKVb7JZXbuNnqjyjiHxSP2FKHdYlbvwBZyumqFEB9mVLqTz3Zk+lJ6gqDuYBkxxtnnk3v4Ek1pyw0fN1/sRvyz/iu+YrsJrRVqybiSAaHxVdnogFluToOSFZcdwaSqU40GMIrNQLIzWeFSfZ4VVNTJosglCh8sJe31CUwWMI1rALA0YlbJ6pCNjk6WWm8EKlgKSoZUYyDKpjLg6jNCOCBu54Y7GBuFjOrWEDWCK5gCkZQWO90InnJ+ETbTgx9hvmAJ+6r1GpECpNwqJqTTN/T9+dqTkSU+E1rDGzsO8euJMTpVLkZWaxD0xlw6IU63Ri0iuW3IEICqGIZrUMnHSDyord8obVifvpgGvf4aOjSU8UG+k4MOoNJk6s7J4cE91hJvUVTs8E29LzTCg1fSp08ZUzOxpeaM2I9xVjvGWSHpMnstTs4hMBh8szki+hJUeDp2G0iseqYV8Kp87R+Yi1b9SLv/xuY8Wbe6CSDIvDqYlZLFW9UDEzlppBdZxlzSKGQoNKsKg1qQTemi23+QtGZz65W76r3zGzY+dfsCkzieOLes+omktxTYq0JGzOBK353N9Rpz2hGLJWiAlQFqLucTFQq8hWvdDaE/f6mUXe88W8pyiNR6jyTJaMK5mTEpTKNHgq3iDdEKRFSaHWM1CRc8bkGVsyJiUW1V5CnzqycEOfzkSl2PDCtpz4avgeeYL6P/1PrtusV1dXVz+6FjX9mTDOnMaBT7XiranxSjBqYfY1s+445htmHFOpOdsdrRqYykjNRHCFkApLqNhObwydJUjiRfV4VeHRGBK7dMD5CTGGkjJ9go0sHPMJsuakWva6I0nFoFcoAgWI2hCK4oY3klJ8HD4jTUKHkX+7+o8J1JetvDxQlUSJiqQyLirqsjCmliKarsyMyqJUokoZiRVGRc6uYpIGIwryQqsDP4t/YMgrrNqyxIrBVNTqUlD8+/obKI5WzaxU5nYe0OIZF8vYFEQyJnucnRiamkPVMvuac90ya4MVoWbElsQ2veKbheeg8fVPSIulDTP3ybOPLUGvWEzhRd+zmArvBXRk7R/JORKk581sIGlU0oxmQzd4nIyU3FDnEwdtUXlA6wohs0kHviqf2Y+KR11xyi2dGnjIP1AmOKxrUCteZUdbRvS8IBKp9Ei3eE5VR86Fg3KY6kw0GotQB83ae6giW/U9N3Lg6La8hY98bz+wr27QNtLnN1ZqwhuF8/ZS2Ctngko02aNI6Ay35chmODA7S60SszEs3mFMQYeFmsAbjtF2/GDesajAr9XCvlrjS4ePhkV3tGZEQmapak5mQxBNjpqMJksC5XixO3T5mn4Z6NWJQTqCcXgRrAaKZzAVK3/gN91PafWEdRP38TPfmZ+S0BzZUoWFVdG0bsSp5TKlJD5hw8h31dcUFEGXyzxh44gJssp4qTimW+rwTMfE1j7yZB9YlT2lVOzHd1Sd5+H+19dVuaurq6sfXcPcn7HOMlsh1kIfJ0ar0GWiDSN/0H+D5MKiK96FF8ScuEl7dtUzNoEZW4LZYYrmuV0TVppgEo/6IwnBqYQNiVf1wC6+ouaIK5bD8g2V0ViteZMNs2rROgKX8loVFMkKlIVR9YhVLGZGB89an7idJz6G70hK8yd5oCTBxBmFZpcuQ+dLFrbziaVqiebHZ4kzVjxVETKC5Aormd6/IjqxkYmD3PKpvmPJNTbMbH7s2StGCLR4hKgtRTKLdQiaOVvaGLBJ0ZSFnpmmijzpFS/NFq8sWl0OwusS6dOZ0dYEs2Hf9FQp0jhNHgRxR+axBe3Z+APFFEqKVPpMXc707hVXZprBUznFULbspoVKe27jgdFpSrn09CkXCKpBpYSWiZXaE5MmWMd9fOJF7WiWEU9LsyTOZGaxZGnxueMhPNHmgb4ceLNrTrrmRW8oFVjxZO240U9M2nIsFT2RfbXjPK3Z2x0n2ZKV4uv5SCCAXUAHGhPYKU8VElV0uF7xIjcoO6NDZLEOMyvuw4lFZv6oHjiYFX16Y7QdcSkkU0AKUYS92vJb/Y/5Tj3gU8/ZdEgS2jHxsupZVE1BYXOkItCe3ohtRJUMkhjoyMbiYkS7SJsOpKLYhhNreWHDGWsj+1jh8GSJvNhbPumvyEkxqYZNPrMyI3fhM8lUpGSYdEewa5oyIgme6luEHQ0Lm/QDc3EUKRQKrTqw5Jpn88BEiy73dHGkMRMAh3jtmbu6urr6d65h7s802xXm/Q3p6XtMCCxNS5UrjnbFpDpulj2Trgg5s8ozu+HIfTlykB2f2ntiNugYiDahQ8HJjLWeiZoRjTE1t+qVJdYsuoWsKNWJogIP82eC5tIdJoZFt5iSWJxhUi1BhEaOaElE0ezlhsm3TMuKQ7Xi1a0oReHKRCUzJilu4wFtFVNqWPszWr6QUuYoLaPd0udIrSYOZkVSms/qPRtVcRuPZDPx9/YbFIVJWoyL3M2PYDR6DnypKjKZPmWqPLDLT3R55lg2PMktRmVKybzZLacc+eJucdET0ZAzXZl5l58wEvmiH7DecrIrXDqQS6YqCr0obpaFY3VZHRrahlE3qBS4W574evnEq2s4Vz+jn/NlLuik+by94dU0GOBePfNaOo7qnsV2OOe5Q7ib95xzg54S+tzTrBVVBBrDejnzfbxlci1zqXCS6CSwlZmoDFVJpHTmtaqpU+adP3GSwh3f8hgfOLkWFQsv+Y7cZPb6nkCLS5kaT5MT23Dk1r9gsmeUnkadcdawwTMhJHODLSMHs6LOZ1J0nPOOdoi8bhPZGkbjMCZCimQu00CKURQRGmY+zs8caGjTQl4ltNJY7VCiicpg4sC9+cyEYdBrjmwwSbif9yit6dJIVoZjURzsDTk6ziyM/hWfHXO1JoliKpYgCq9rioZGRu6Xz9i4MDSGg7kjo1hUw9fhj3js5cyi8nglzKkCXVDZM6qWF1lTkrr07GnDq9qQsuWlmWjawNPzJ2KM1ykQV1dXV1zD3F9QdcXm/gPLcORJt0xKsGrByJmGgamxmFLodODr4U80OTHmmt/WP+OTuxzsdiXwYXxFkjDnCpcCW3klS0WfT7TMl8JdBVonfqc/0MeRhzjwcfkEutCbE0uo+Hn8I0O4Y7AVv6l/gpLEomrqPJO0wfrIbGsKgVk1qBKxItgMvRw5mB6Fok6Zwa5wGpycyMphJdKYhTUHjrrBkXjLHRWJl+jI6jIPE+Eyi5WAKxHjAzYISxqoVWE7FUJJvG1ueUIIoiAXJGgSNcsMlVto44KTiQXNqGpO9AiKrw6P2K7ggufV3DKmTMGzi6+X1ZuSiSJUQcjZUYWFSk901QBGc6ruCbNg00S3CMemRWdPKoW3bs2QHLNo2rIgP86ijWnFlNeUYMjzGoUihMCzuWVWLcvW8cylCDlicDmgqszd8Mih3hKK402tyCmQcPh5xT1HKhPxyvBqN7yyo5SMzEKyFb1fWGfLNgzMJtINE6MxaBQpak66ZyhbJq0oOWHLgiiP0TO5iuQMIWiSgLhE1BalBB0zOi3UMgKGUgouKBqgzoGeI0NdE5wlYLmTL9zlgsmBQEdsNEVZfhF/x2f5QJ46bElUIVBnx2vbUIunioHbfIKSyWJAR4qFbTkyyY4+TsyqUOWJj+b3tPbEJ/+RNx440NMzg0SKyZTsQRSjaDIRo9acpUFpqNPMrCzB1ryqDYJCJLEqZ2o50CRFnEdSStcwd3V1dcU1zP2FOWc+d4W5MUStqdJMKyMrOVNL4KTWKAoSE29yy6Q9k6mJVl+2qFyHCRV1teFvXr+lOQ/YbWCse866xhE52A2unPFGQITFFJRWPDb36DTRlIlYDNt0ZB0OeNlQnKXVA1kpJEcomrlUeHlPpSeSjSTRl1UObtDpjUUsqVgUjqlp6dOZm/LCbDVdOZOLJwE5abSGs7YUFDkp9m1PykJCYfAoBCFyqLdIyrQsrNOeVTwRfYteRWpd2KuesXTUZMakOHYtLnsWbXgvf+KsWpQILl06+yZV8dSv0DExljXd4nmIe1yaqarAcalAKnyMHJsOTyFXl9XPlAxf0kfOZUPtBWVm9vWKRVUMpkNiQXKmjmd81V1WkGxFDGDVxDx2PPEeLS1NnNiVP7IUGGTFQffs1YZQClYSt+GFNpzxrWU2Qiiek3R080AVPB8PLzzMz7y2GVcf6GeNzy0rP+FDz8G0LLpjshOzvue1UbyYNc2858afWS0DvnK0PpFTjzcLdfGcu5ZZOX7b/oSVHwnKMGWDCxGdFaIXCpqzacgKJBrenwfGssGlEZ8tNSPbeCIbOKmeRVkohlQCRWk26UAQzZvukGK4SV+odKGOI0PjiFKhU2GSNc+5otEn3qUnSpNYRPHKGi/dZaRYeuVj+o5OXvnCR6aqQ+WEFU8dzjRqJsea0fVoAiorhIDTgYhikhWakVhqTE4YIlkKSWqOdssfur/hV/w9S5oo8n/ZAX51dXX1/wvXMPdnAplDPPHctByqDmxNE0ccgUYGJt3ii2Z2hkjDMbW8mZZH+5FJ90RgJRMn2/Nd9w1fT59YxQUdFLkobIoolej0mdlUjGVDKQqlCnVcsGZiHQ4McceLuuG5v8P5iFJHPuY/okQYZE0QS1USfZpJpfCtfMVZt2TAloXJ1Ei2JGru/B4tGYVnMZouLezkxETLoBsavafHEaLlqGBRlqgUoHBEPqRPrJl41BtO+g4tMz+Ye/p4oBTNRh3QSTPFjtk1l23UEgmNRqlEnc4sYunika16o1EDL+odizQUrzmpFbfLRFUyq/mZvn4jS42RiUoH9ukdowmcTcIy4NLCx+kHmjrzSd9zkhWNHVnbhXf5iaFMxPIe5YWSHUZlKr2gSdgUuJ0n7pcXXuVrvtQ7rIbqXHMgMTaWvbslY1EpYfLlkP4ctugyshqPzKYhOaEzB5pm4MaOrPmCyhN+/pql6gj0bGRkF4/ocuDjyyNH88DYw4ttGJVmcj2dONzzI6Nt8L7B1wZvFSs18mv/G/64fMQ2DYP0PLo19+UVqxpMWqiWlqYciYvly8qy1iOT7glLy7K0xHKHMyOzrWkZWcdnGjszpppJKmzRuJypisfkwCwrFrG8rH/CHV/4u/ITRGVC6unKSO/33M+vnE2DJaP8wuC2JGO5LW/o4qlyps4nfl//mr307PUtXTxzJ5/5qB7ZjQc+8VOwhSAZUwI5CqootAjWBEyZ8LqnTkfaslByIpvInXpmo/fU8UQuI1nyX/m/xdXV1dX/O1zD3J8xOTDlhaIL7+OelApfjV9Y6ZnP6x2TaLysaMO3HO1lVSyYlq5M2JQZ8opUoEqe2/IZ42acm0AXntUtoIixQWtoZMHJEzYK0dSUojmHHh3hB3fPkRtSNji74FTDurzSMfMufcbnhigVjZuo/YnP4QZjI5PSeDZgFCZGXCw86pvLOKo4k5NjCQZHRLKlUYHQrAlU3OQnDIk5rxh1RdSXfrMx9PT+jJWIVRNGMkEC9zyzBIdeILkKk/aY4rDJQ6hogwcLx2ZDJvHJfLic3VoEpRPux1XNREt2HV0MbMIRlQoqz2AVMcFSLwRlEOPROrHJRzoJmFmw1rA9TpSS+dnwid+vvuaxu2UoKyqVuA0D78sbqMs2NLqwiSN9OBNTz40beKta3qqexlc4Bjb+zBwaUjEolVipSBMilRekGIxMlLRCUkRrmK1iXyteTY83ia0PaDegdKShMDqLyhCrI3NuCPoy11YXjcoZlzzKGCiJwdTMVjCqphDBKJbckEVTCrzaHTk27OaBd+dCd3C87C6lwgdZgRgWbRmqmqFyGKnZpIp6/5m1h7x75V93v+LotigFdQh0fgSp8VWLthFvLAdWvKg1IBgMNkW6WSElkU3hSMuqBO7OB2J74Hfmpyy2xcWFU2kI2fIuvxJp+JA/seLATX5mrNaUmDiVilPasM4HOk7szgde6neM1GguF3LaORHUjNIDe26ZpMURafKROJ+v1SRXV1dXP7qGuT+jSZTlRC2FIkLOmdn1/KArvuQ7AkJBsbcfcWkmGkssl8oQCqxkjy2B2/xMjScDs1b47NC6YDAkJeRieLc8MlYVdcg0/pndfGQ0iRAyv3G/4kmvmaoGRaIvPVUa+Zj+xPv0RM3CEG8wB2GuapqlYMyCNT2ip8tQW5VRZByBIprJdVAKo6z5am5ZcsbXhigCpbDJL2zCxMm2fM4fLlMa8kQS4a3akSOcTX8JOSUx0aKyxuTI6gRpmxlSIGtFrSbaVJiqO7xAKhXPvMMqzUqdoIAdE1MrKCmgQeeRJh15P/6AVIU81hzje+6WR8aV4EvB50KbzhRtec4doiNdnliZV9Zh4Bv/Jx7Ve1Y+sncbbsMbXQns/A+cU42Xhs0hokaN7GYWV1Hw9ATayXJqe0z0uJJZlS8kNNFqNlOA2PK3yz9hiQNLtKzUyFf6idwIY+N4KXeMZkdBcXceUO3MV2nPd+WOb91HFps5S48NI11euDudiFKRraGWCW8yo1lRbCYqKAK/Gv+Ov+XXHN2as7WMumK2huwcrnhG4/nS3GDiQHHCw/iFlcxUaSbILWfTQjHUjeYrf6IdZ3SvMDHT5YCOE4aCSZFRr1DiicVyYkcuFh0LJivuBqjxDI1jMpqzXjFONdt5ZGO+p1ELTZlYZMUYtgw04C2bNPIz+S2v9p6/rX7Nvtwx2Y4mnqmzp5UzqzLQ12fC/Mbc37HOZ0QyfZ5wxgOBgnCfn9mVAyoI7/r7azXJ1dXV1Y+uYe7PLAVulx/4J89nDn3DuZvJ4giSOVOTMCgSWYRSNIpEW87UKTOXNRUzu3zgLr/xMXzHb+wvOfKBk66h1Khy6Sh74DOb/MJahGhaJtXxnBuaPGCMhlBoyMQYMCZhJXNSO/y8wcRXMArRiWOzY8gb7o8nXupbopoQ7TAsKAXBKFwBUmGQjhgNg7qhksjSwK48M9OjS+BZvWdb3njTt5QijLS4XGhKxJSEzxV1HJhkzdpP1N5Qh4TRI7NtiGJYyUgGtNUoyZgSaUtgUIaQG7JS1MZfJhroBZSmkCk2s0onXDdSTpbX1KHmhpg8aeUxAlt/JIlBouHVf+CpbRAJbEykK4WD3nHyK1ydGFeJqAJRjRxnw1S+YqGjkSOlOyJKs5nBnSaG0uIbh+QONXU0seBrTyMHclZMquNoK9YE9tUGvTQspcZNZ45OWNWvzALOnWnnkUFu0GPCxxVTsrT1gX7VYBRELazyAUtmcSvaybOWEbtMzOsCWUPJbOORdZiwJrLKI7O0nHPEaEWV9WWb3X6POM+52aELzKpClGIoO0iCKgUliWzg6CyPa8tP/Asfp098Lj8laUVSjjF3vOobzBQxzrNShUG3rOJCKUKfz9TsMW7g4GqGqmMsPVpHBhaWFAnBkYziLDUP6o31fMSVyP3xmY1L/G/qKx71jkW1FCW4UjGJRfSaMXWgCiKaWCxnNjRhQiehSRN725CzJeSaOE7kSbgcaLi6urq6gmuY+0thYaMU6/iZiR05JX6wG2YtiGQymlQEQZAwkbRj459JVrPoxMFs0ZJxy4QxD+zlA8l7zs2apiy80fOL+D1IA7FizJZgKl7VGhrN7eDY+UfqauQsNUrsjzdUZ3LRfGu/4dW9IyTDSAWNIYYaqSJNHuizh7gwqTWWwKR7iAXDTBU8bZhY6pZiFhzCbhxZVg17dU/SwozD54qNnNAkKhXIuXDMW7zRLNIQiuMoFm00XnnEaNLgSFLQeNZlQcXCUe9IYvDpciPWlUAF2CLotNClgS5NdPmEN5YbeeTNrflh+4F1mTmFNW11JDmFNYWbYcH6M5/1B740HXNrWMUzuMTsaz6rNc/ullzASuADn8hVwoswnXtUEbomsG/WSF8oB8vduOdO7Vlizfj2wF1XOLueTMVjf08m0XMiNZab9JloGxblUMXwVfTchMiKgb/r7vAqszjNJn1hi+eYL5GjWRS9wPPuhlkqxAoflxdqRkQZjESsSrTi+TDvmbTjJp/RKjMnRc2JXxwm/s32HzFmRxSDlomDrbkNE7fhhWAMJINRhSU5ZlfR+0gCSon0aSG1QiTyof7E7nDmxT5wiD1T01FlT5UTB99RqUwR6EPB2CPvwiek9XjlSGoFJVFyZpAG39ZI8LQyUOUZqyJVnjEmkovi2dzwrTwwSMMiNTErQDOoilgcE4WZzGJ+TlUlRmlBEo0cQQWOtuJgNjRyJiRBE9Fp4TRdZ7NeXV1d/TvXMPdnalFUwxEnB0K64cXd4RFKUWzjkTFHJlVfqiq0pYoj2UJRil4GgjhKyQx6w6pAyo5RN8RUsZueQCdaGSgm8X11z5vacqJB0HR54fvekcfCKgZqf2CX9xSraBlIVORYczaKWnkW3WAipAJtCazzCx5FU44scmZKPWBp88iNP9LGMyTLOgVGrTCyoCpPJ0fOUqNTzSIVWTS+GFwqbMYDlcqYGHmqbomqoslnvHYEEXJs2Lsdeg3On+kYKGWhZ2KID+iS6MzIrT+SVIWTGa9aTJlJGozMrDlQqYlOn/jX9j9kzj1LmIkbyLQ45ykB9puOzR7qtFwuCmjHkTv6+CdKskRtKEnT6YFOIq6MPLNjr+942dxjS+RGVXwTvrDKRzw1L8s32BT5sB95Z/e82cy567mfCraaOWgNWnGsWl7Dju38iF4yY+zZhjNVMEzrNUpNl5ua2tKZA7Nb43ygYsE3miIj1dRS64lkFMUoWk7U1UIdZ5ow8D3/EVEE5wMqFr7s3jEry1H3dCFxOxy40QeezHtu5Qu1TLh8RsoWiQGRxF6vsaeWxVS0+YBRC1U9scnPoD2phU3ec2zeM2M49YZRGu7CK25ecMrhQmJfr9nUe27Y85A+MRbHKzt0ihRp0EmoTcSUgqiC5IKnZl0OzLal5OpyceTHyzRFDFIKRQlNnmkIzKUgISMUbMkkZakoNHFioqfoilQCsRhmDHURSlYc11sOShHSdTbr1dXVFVzD3F8Q1RKzQ6zlsbnlQItTmXo6MTRrkjIIQinCJA5RkV16xJXCo31HVproO0w6sisDgR/4Q/mAlsRTc4PLgbYszKomaujSxFFVvKkdo5kworjhhFaaoIWH8EY7Dgwrx2fVM7qeiKHLEzkqJoHFacDTAHd8Zp2f+FP8JbE4Zio6P3HvX1DKQ2VwIdAXRUlCwiLpUv2QtMKXnvfhEyjFhicqnXBzJkeNNYHajnTqjI4eAyxSM8jPEDHEdsM34Q+MZUezeHx2LHbLAmgpiE9YB9Z7rJrZxAO78sZaXmnCwgu3FA0qKx7tDTt5oYsTj3qLzuCy4zfNPZUbQMHD/IhXjrvxRJ1mPrd3pATHao2dzsx1RYgVk2lxPqMJGALODfgsnBrLydzAAtm+8o+H3/FVHAnekOqFOg5UxvCkNwiasWrZsOfBP6MBaxSC41N64KiESTJr90YfjgytMLctM4G3ssZnzTnfoJKiXx4pBhoixng+jk+8qJ4/uQcwhlIUd2GPnk6ooLEGzAJtBeSZVzfRLSODrjlbx4wGK+ziGyNb6rAwtR2JFl0CXZho8nJZ6SsVRW55Mx0vZm/98FcAACAASURBVINloqFwE59ZnzO0jqAK1izUy4jJC8YO9KL5Vh44y5p81jRlopKFsWkoqmCyZ6krVmmgFKDAbFpOakUBTEys1Bld9hTlKBSUulwMESBicXm5zIzVPYqE+DMntWFSwsKG1k3Uq5HSFqxrCfka5q6urq7gGub+QpJCUTWfNzeEJrE3G5q0UBtBxUKbA4toqpzIRrASmXRLlw+89680KdIx4jKXsl4zsUsn+rQwiRDF8FzfEqOBklF55NXdELQmmw6XAt/1H2h9oZoEU2pa9YbzgcgBb06cpWVXXi7Nb8UxOMdX/AmD5xflNzzJPUFZ6uTJ6UwbR0ZncKWwUXtiUZzcilO5x9kJzcjH/D0mLHynf0olmhmIsaGJAwfds7iKs3TEpJlY8RCf6P2RN7OlDQF84lQblDKYeOa5vSVIoFQjqyXTuIlGBiR5TtwySsep7jEL9H7mlk+cG4eRjC8BEwq7+UDRgkmBpdSQBZoFRURnTxBD6xdO0rPSZ27yG63PvKielCuU9ziVKG2BakFJRDI4OTNyy2hbvGg6M6CaN3T/iI6GnVqYlUYF8LrmRd1h1YgzrzypFk1DoGJ7nqgFDr2waMOSM0E0T/o9uTLYKTJbh0n+f2fvvnYmy5I0Pb+21FaufxERKaqqq5rDITkAD3j/10CCBMhBdfeUyMzIiF+62HJJHngeZV9A5oE/F+CAbwfMDWvbso9IhZ0SWoRNELYms7In+qrms3vgRW84NzVt8Ixi+CnuMKkDV6AUPth/8lJletuhbWCgQiIkZ5lLy0Wv+ZDfSalg9cTdIKhmZpVPGDtTy8DudGFZw1ceeLMbzqVBVEOTB5LVWNuz1UeChoEVzg285R2b5ZFy0bw+PDIrR2gsXemhRLb5yH14pU0nntxHpmlFi8fmRKM973qHLoGgHVXxZDQzFZaISYnt8kqrZmZWNAR0MQgzMddMqWPIjpIC0ShCsRzNHZv6wtt0htuauZubmxvg1sz9J6YqlN2a8bJnKWsmGpJUhGzBFkbdISSCCG2ZWLRjyXcoJaxTZj0uaKPYTu9ErRCzYPTM0VSQhUUZdAmIKqzLK1k7WjzkmYWaTek5yImNr1lPhTpf6LvEIo5LrQnFsuCoY+Et7+nrGq8UX9RH/pj+HSUCCdal5y2vsEQkR6a6pk8di66pckTlwtmsQNWIrNjmE1Y0GYMPNWfTUfKZJs681A/klJn0GpMDUYPOiUM+su9fudByKXv63DIWRyczbXphJWcmU1FFMAE2xyOuirR1IGVFr1uKTYSieR8+cU6P7NwJqQrbMFLZgcnU3A8nvjjLe1ijtKXGs00n7vzIYXnnWW9QzOTcEhrNUlX41KJCxDLR5R5bPFs1sJYjpghV6kGvGaTgTcXDWTirFrENRzE4MoOsiRju5nf+2X7DZ/MdqiQG2+HSwinBXToy54ZLbjhqx0TFLGsOvLIpbwyuZY7XU9jD4HHzROcGpCT+n91/I2hDaITD+YmSYbYVKiaaamEbZrb5R17MI75VjK1mUgZXZiZjWc89l3pPBiZjuJSW0dW0mwFJM0oyvdxzH/6Oi0IVNOViyG7FJkxU+plJDI2aoAj/dN+SDNy5N2o5U8kFNSvybHnZbYjGMeiWuVgymS69sYoDtpnwpcKoGSqFTRNVyMx5SylQ54lEoSJTcSQVhZIE0nKut3RhxsUFxUIRGF1HXzoyiSSaWVek0lHLkaU02BLZKns90ru5ubm5uTVzv2ZtxWrvYFBUZWGbe2zMLFazKIfXii5GbMoghllZ0IWQa95UJhnHymf+uflEVy4UE/mYfyaWQFYKpVbEXKFV5BDORIEhrzmZNaoUtuWJh3TCyh2hKrxUjmP3Le/sSRqqOGGJRKWJWHQubMoZmyfW+UzRwlkOzFQoAlkJY7VhEUtdEu+zY65qonZM4qhLZJUntETa1IMO/FTdEXHMYgmhIYhhr97xpYGiUR7OsuVb+wOHfOQhvTBUG3bLmbmtuYSR3t1RqUAlF7QubMOJre3ZxiNP4RvOriPlhmne87e44YULr/WBe3nClEgQSyOOng1DJZi0IGZFlSeKTnwKP+FMYckw1ZrzWEPSLMaivCU5QeVIN3u25Yx3CpMWfNXxXhTROdr+wp3TSA742vBOS7vArDOzCCYPDOWRTZ54nF6p3UKSwpveQG44VzUntUGXgFUD9ZLY5QuVh0LLZbFkk6ilcBEBVSh2ZqPOzCtFURESvNoDYwd34YXBrlDKUSdD1hsUhgfzlYN6IpeFv/OvUIQUFVKE9TRgc2SRFrBI0VgRpGTu8wmk5p4X1mHkzex4qj7xRstsGzbHEbGaXHb8vDlQGmEyikUJOitKEbahsOgOqwLbcmbJhqIjTVoo4uj0V3b5hZ/SH3hXOxZbs5U1m3zhE3/jM/d4DF6v0emNohydD3hj0WUgiWO1DDx1B+LSEbOlShOVZAYxzMqhS2RShjZdOPgTm9cL9k8PqKJ+63Jxc3Nz87twa+Z+JY+R7otmdZrpxODzCa8Mi97i0cymw6iMz8KH5YTNirPaMJYOlSIOWOWRV9mwyy/MxXHJNRt1pmFizB2fyydcimQRVjLyKf/A4P8n7ssLd3niw/TKSde8Nlt+cI9MyjCoFlGBSdV06sJ7bpmyZTEVOddYNnzkiVN54It8YpSOSE1CMCaTdcdKTnRqQBFY5wkDhKxYyQVtErHUxOJIGJoYqXIgF4MLmYmWNnhW6dqcdXZioMFsBrIkKnVhpmVULY2ekRwIVrj3zwxqh8sJqYWBLWqBqVoRimKoLOdqz9fwyGQ65uTYlxd8VXHEEYDaLMRksSPUScgdjE3Fvnym9pH18grjBq886B5dF1ZBsWSoi2cMNdthINkVzivWeSLnC1NpUaqnSYGLbjibHb03VHKBBF/sI73qCLSsYo+LicUUZLKYxdNmofOBQsY3mY5Csi3JLnTHwnrILE3gqd5z0mv8fk27WB78Z1p5oZgDr3aNzYmSFJYLmwyTXfO+rvkwDxgKK/0GKvOJZ0ow9GXH4jvUNdOCLsEqLOioWDqFyIKqLCwJGxcW05GU5XP9iS/xW5ZOoX3AFsOfXs4MdcV/rB3eVGSuMWSH8oLPhiQaIytMPPLAM5e6RieDJVBz4sBPLNryb81fOMqaSMPH8kysDCoF6jhT6fm68DfNxLJiXQaOOEoqFBsprjBLjZEMOoJSOEZSqREiWRS6FOq88KH/zGby5GhIKf3G1eLm5ubm9+HWzP3KOE48YZiXim0c2EzvlCbx3/X/ymgqRq43MrXyZJtRMdOUEVQhWeFd1bT6glEeL5pXNmRj0SXSyohNC0YVmrwQjMH7lhf3QDGGY34kSM1oVwRXkZImKM2CxgOFCmMKq3JhzZlWFo7hjhgrolL8aP6FgYagHXOpUUbh0WzymVQULkXWamIQS841jZy5nwJ3/o2wghc5YEokac1oDJ7MWgfqaWCvz3zbHxF35GgPVObMpap4UX/hmT1P6gPFQEJzNh0u/7IHTGukZJR4BtcQsqZVns57tE8EU13TL1SmSpGgK1QQGjJPds9kV8xhwqTrgNTFdYgzvPCBXCyH/IY219lBLZZdXygMDMqy4sykWuayIaXD9XVv8rwphapGVuM7X7ffM0R4dwfsnDBGeCg/0sXExWxpzEJKDU4vbP1ICI62/MCcOuKSmRtFM2U+9a9sSs/nzYGc4aXrcFOkBGGoNySt8TFSq4VT4/jeDPwf5/+L/3PzvxNDg5WFJDMBMNnilWXlF1SJTGXD6ByoROMTOSSqJZC1gc2Ec5r7eaQpkdVFo1WmCjNvrsFog7FbjM70psbXiaA0jckUHRldRVM8IRyYlMELzKnmPe0JylI1gbZE7n2hKgsflx95tt9fs4VlRS87nuWBGUvMNUE53vSeVbkQjaaSkSAKiuLZPrINnq6v6K2iOIXExEV1xFIRjEEHTxc9W3WmSol3MRzZsOiKLo80KmJs5JjzLc7r5ubm5he3Zu5XSlXxHiPPq5Zoa95XKz6UJ4pAm0de2TBKzUY8izicAkkCuVBp0Ax4FP8y/Y19OqIr6NkRjGIoK7I+XBejmh0P+UwdX5EabA5cZMuYLcpcl6W+mT1ZMuu0ULIiKstKBmwJNHm+XmxQK7yyoOAoW7x21z/WX5rOUgRD4qG88DH8k9omDvmNiGZgTSueU33HYf7CsqqIRqGZUCIcwok9PUvdcedfWdsZxcxbgqVYfuT762UQCVR5wWNo0jUMXpNwJSA58BCfqPWAU4mJBlcKRV9n1RTQqJHFWCq/YAmY4jk7x0VvQAQxFbv8hBTNJa9JFC6sQQqVjdSDcF+OfKWjJbKZR+6sRzPy1+YvlJLIamEKlv3Y4+sKfa5R6o7utNDXLbEofnbf8jG+MPg9UgJLrlmKxsuWtRiKrjksb9Q6YEPirBsyislaYu9ACUFXlAJ9WZFTzxhbMookmakzNLlQlsQqnnCusE9H3nONKppVHPi66ch5BGVBntHVwGg6Jqk45gdS3qN9odZvzCvhtdpQR0UVCy4nvg9HSnemiZmzdTzxBxZd8WrvWTEQlWBYoBoR9c7LVuN9Q6kmoqyJUnEuFopl0QqvPTORZ3PAFI/XFRnBFo9hIkkDKGKpSFRUMWBzpJGJbZqoCbzpHft8oWdNzIHPXcXZtdfoN5mQkjjEI+9yh0bR5YnH5Z0uQ41DV7BY4ZDP6JIJtibrgdrWv3W5uLm5uflduDVzv+Iay1e38NVvyKXQ65rvk8fIwqIsLQsVC6loUJpVPnFSW+qSmfT1ksBrucOrjj7s0D4QnGNUhowwUxHFMLPCkTiYM6ZkklYIC1ZFzrLCS6Hmwid/YSpbHvzI4BzGjZgyUMuECZG9/cLdL+kHr2pPFqGRhQlhU86YkriLb+z8kbtyZneaeV2vURreSoNVikkaFrXGpUCnB3blnaU4VnrCyYkRy5O0/GQ+UCRy1DsG3dCriiIGJzONzLiyYAhI9EjRoECR6cqZB//OIb3zUu8xJWPLwrjscaUw5hVZMtF6Qq1YmZ5JGRrdU+eZmY7aT2xYeMw/8Vf5nwlAT0NQkFvLD92GhGKcrhm5KWu8brnolqVUHE1NrCreN8DieCgj1dCgXEYvlp0eKSQaZkLueG0cYIilQUXPaigsonh2a0xOjFtHCQXBILFwdh3jUvMP9RFlIRfNyYy8moYpG3yuWOWej3zhIC9UIoS45qGc+G6ZGCvDqnzlLW0IxqFyINnCsez4B3+hNzVD7tgrz665cFQrRqMYU81oLN/xysVYtAosrsapJxbzwJAqKIZZdRz8iY/2iQ/zZ16bNSd9YFGWouV6UQbQOeOlYdaJqMBQiAizsrismcRRZU/JBjMlclNRlGNfegodVfLU2tPHPT8YwyafOMv+emKrGpxcMBKpJBFYMdFwyXvWvqcuE76qOJk1i3XspoHP9oGkJnq1wopHK9gMZ3a5u60lubm5ufnFrZn7lRwWdH7CVmuCJCZ9xz/iH/G5xZYRrfM1BYEEtJgsmAyP5xd+2n/DXBxZWXISnsuWx/zGXXzFWMur/sAijpINXb5w4IJkRZVn9rzjpCWp6w4vykKQjtk6YjC0ydOe3yhtQopnySveTIPJC9oGDvIzSRKXskUoJBSmJKx4aj2SKstzfOQomhgjugSOds3X+oBNBpvG63Z9PBnFIR1pfc9b+wAx8VU/YoohmILmmvl6/e4jGUUlA60s9GpFmxbS7JAqUTFTnMaaSMyKtvQsUpFsYjKO6D2VPXF/+cJr2zKoPRMtuShcXghSX2PPqgub0DM7R0dPXXq+qg+8tAdsihSp2U89L+sVdozs5oWxSTRpguKYXMMqv6F0ZKr2+LDGNif+t+Gf/LDteJ1ajtWamGGx1XXFjAnIAj/X98AGyTP/1f/fbMvC53LgKW05Nx3rcqGRETGZ7TyhJkf2niXsUMmDgsVajEp81TuSjnxanmmIIMLgNNn16Lonm+tr6ZAbXtQebSDmQh1Ger1iqgUvG0J0JDODKoSieDVbquLZ8kYJge/ST3yzPJGU41k9orC8mTs6f+GiDoRU4Y2jZaSXNbksWJmp4sJYClVINOKpmZi0ZtY1UTxeVXzwn1mXwKN/g6GQNh1OaR7STHCRx/hKbytScVz8nlBZsliMRFaqZ116PvPILAVDpKYnOEefNyQntPlCxkNMxGRpmLiIxoVINQVUETar+9+6VNzc3Nz8btyauV/JCjZMdCZwdAfa0tOqHo9DsJgUyBKxOFJJ9NryYToiyWHjgnGahYpnuWOtPLX6zGg13y6vpKrCSKQv15mykOAnt2XCEYygsseQoRQu9oGYFYOs2XpPCYFNOXFXvvLuGi5lw4u+o9EDH+UnUInvyz94kkcueU3WsJM3TIq4HPGhIxjDUK946R6ZxAGFunj2fiRZg0oLh/TGkDd0/cRcd4w4vOm4qBZDZFE1LSMBxVk5lK6vi3hp2aU3NgW6cuai70ilovKevtrxsiw4O9HGgR/0H6nVTLVMjGpNUT1/X33HLAqzwGgcm3ziL+Wv/KT/wCpNqOKIomjUQC1nFlUTi2LBsPU9vVsRtKWgSCshOs+l3rMEyyANOUX6ukYElI7UpsfrxJIyVRk5pBOb5ZmH9MrFPPBUf+DkOpZcEYqQbcQysxhLij1jU+GDIknCyUQ3zJxdS5HMpWtYmUKykeCEEQ0ZJt0ympa5rdEovivPyCx86XYc1MQ/5I8EuS6lXrTiyT2QvOLr+iN1XtAE6rEnWEulZoIWpuJQEpisMEjL3+UbtumdP+e/UV3ge/PEP7o/U1ThXd9hy8JZ7VjNZ+ZgGPSWAnRxYZU9ozRkEUxQdNHTmQFTNSzM1EyQLvxB/UwOmk563nkgFEsyCmeO1DlSfORo71hlQzCGwjW1QxQ85ie0WnBsCMXgxSA8UozBJ8MijqAFL47oBs6mI5hEbze88AnfnFipM/X68BtXipubm5vfj1sz9yu1a2h2hmVuyOIoVjPFjllV2JJYl56IYtYBkRkSmHpkQBFVgyqWTRq486/XQf/kWXJFVoa2jDThgpUD9/kdJ56XfE+wK3wWqpJ4zD9TsCTfUJRlRPNWrUi7zJFvGXXmXd1zji2zNFgmYnHcp59Zc8HpiR/lj+zKiaW0dHmilQUxliNr3uyBoTREZYCELQUsCInkHVUJ6DCinCZS0YbEgkFbRV0yUmba8saoDtQlktC0ZcThOcsdWgpKb1kvPeJHBlMT3ZqzBCYKu3zhMx/QgHGBtR846J+5mJrFHujyGT2vMB6ezfcEt+JrPGBMobgDO/2KQuHKQpaad1Xz7j7yIb2g1cieN362D7yK5bN6IFvFYhzr6UgumTotBO1o1cBFbRBX865W3Pufea/u0XMm6pqNP2F9pjcDF90x62tM2Dq/MTlLRJN05jD1HMzAXX1kG8/sjjNfRVjZ8ZqkUI9obRi15p/qzwCc2fBvtuU9fcBkyxGLiomLrQCFySBJMZgVWVmKQD3P6NoTXEUUOPgzKgYuquO12THrBl0iataM6cCP4V/pVMAlQ1UCScL1s7SCLFzsjhQNQ9pQp5mjdtQMmDTzOF/IaY2hoJXG6ECrJsDT5QmdZ8gNTRn5qTFUzLSLoap6lAjWDmj9gF0mjm5PVSKjaWjTBSFRgkYryNpiiBSd0TGgtCEKuJzQaSYYTaMujFJRJNMbB90a3zT4y0iMEWNuJezm5ubmVgl/JYfMaXkgEknKEDAs0tJmT50iyQpNORHVA0jG4bnXXzhW31FJpEoLXe75WJ54NVue9B6fErvxiU53VMojqmddJk52jTeWRLnmrIZMDB0fpnfG9o7FRLIYRlXjrQEyLk+QFd602DmD0ehSqPTCVt4ZpEXpwkyDQfg4faXOGYUj5ZG3ek8WRRBDUBW2ACzo5HkzH9A64lzhm+lv171taSIWS7MshKoCMpNsiaJwZeZsd8ypw5TMNn1mzUgqFcFYDukN0QsmRyyZFx4J1IyypU0zUjJVnnlTa5IW6rxgSsF5TVQtJi+s84leb0hRUZnANgwYnZilZl1G7pcLvqz5l+EFcYlaR7QpeBFeqgMuTdeIKBdAC9v0AzYm3DTzdfWA12ue1CNKRSiCaE0TB6IW3qsD57LhYlrqtNDQkFWiNhN16hG9ZdhaBmCYFNWsMKlQ2Z5kAzYHdv6JVmveZcMrFzw1GY2jR6lIzIY4O87pgRITH9M7S6pYWsMkHaLBMZOqa/NTMbBaIqtlZGuPuBx4knu8WJJqmFOL9YbRL7ysLKvyRm4CSETIZNFY1dOWiSA1J1XzuV5TlKVKG8w8oTtDEzJF4G4ZKcvA2lyYtb4+pyTomHgy12zhhpnYFBoVEUkcwgvvy5rB7kAZSs50MfBH/5m9PfJVvuWs90BClYLOnkWtkJIoKhC43lauas+6nEiqQlEQUVQyY5pA7t9JKd2auZubmxtuzdx/Mo0jbVpRL69cOktdAk6dcTljcKQS+cQr38d/8m7uyFl41Q9McQVFo/PMoFr+h/qOIDV1NWLVxCQrbJy49y+Ig8peCMXQypl/U/8L5ESWTI7CoBsep3fe3QpjPFYrgir4UvEuB1ye0anggC4tfBN/5r+Yv5J1JmnHKx84YnB54Zjvcc7jqcj6OkfXZk8dPGISu/BONJYf+DOZQhtHmmWgNSMbf2aeKxgCyUZeLDgWer1GletlDp0TGz+QtWKIW2a94TF+5i49cZdPnPKGyTckqXkMR5SHY1cwXpGtw+eKadFUKw9ZmKS9XhCRDToZgp9p9EivHcEYptixje9s85ml7Kl8ZtTC6KDzjn2ZWNLCD24PSUjFoVPBsnA39OzUhJ4vaAFTJibVIAS8smzjmWgKX/UnJPlfTsCe0BwwKSOm8ObvaaJnsCuM98xuhfWa5+Yb/ux/xo4LRfekMCHWs7dfqcRiUmQqHTOOFAx7P1LlSEwJpgxLxVbPGNeydBWRjkE7PC07/8I2nGmmgVBX1ySS1LD37yy6RSWNi4HZWIJ3GEkcTcspdgQT2UwXanN9Bo/5le/CTyy64e/ujmiEogy5KILS5KZCi5BzwpTClBWmVFTjSGuuN5//3WxInWWVzlxMh4oJlQObeOTiVvS5Zc2ZWBp0ycRfFlg3TLzyiWf9QMg1WmfaONDJkZaFLDDzESmwK2ekFKwsbPNA1D0mCvv8wjY809YGrfVvXS5ubm5ufhduzdyvaCUcPHwcJs61J2RN1tddb0o8OlS88R1b/8q+PRGLo4iDMKIRvIWkEloSoRgWbUEyL+ZAUy24piblwCQtS2xpSs+9f0G7HaqAV2t6bVgthawKlkgmEaViVc60+ci6zJyTBmWgKCq9oLOQDPS55lw6htLyLN+w7i50jMy5IWuoQqDJXwm5haypgVEEpwdGWXFhha0zp2nDV/lEbxp8t2U/jVRLJBqFJYAktNKscqAoQZFp1EgsjiW09Ghmu6ZhQMXCOl7QUaNT4bkMWEmcSsPZrOmdQQrU2QMgbKiisATN+6ZlpS2jbfgm/YNZFIcQCX7Np/SVUXWs1ZmzuWcOATd/hLxHxNC4jGIGOXOf36iIsGRsWCjBohT0ZUeVR5JoYqoYZMOkLbtwYVE1r/LAm90TXUVLz/DL5QidA1XJ6JwY1IYzNfsyU1mPqRaEyEVt+Dl9y2g7zDJiHeynZ6oS+X54QsWKZ33PP8snjq5mbrbUukFcpBLFKkUWZu6WC52MYCOD2tLMI4PqCNLgJNBKz+BWdPlC1VzQi6JvFEfT8mL+jC6Rgz8hWkE2XGTHH6a/86L2bGkYXUOSTJbraplVnnjTe0KBZduy6nuyW1HpAS+WuswEpdlyZNQNShZO8om5NGSBTXZUeUFQqKgoKtOmM5O1BG24L2+oZHiWLUoKCx1RGYI4vDLoUuhZsZnf8JXDK01C48rAx/ELesnsPny6ncrd3Nzc/OJWDX+lXXXUWpC5YFLitd2wkYjxibpMqOKJUmjMiZAEj2PRDY0eGdUGkwOBmiKF+MtMW82EGMHgeVEPVBIwApvlxItb07PGF02hQhg4uwc+G0fWke3ywrq8oNSGhgFRii5eOMkGdEGVwM/hA29mi6gZrxxJHJZA0gpy4ciBqPM1Y9Y62jJzlwY2y8DzqqaohBfLXCwlFd7ymlH/maQ3EA0LLZsyEVWFVQOUCSmOjkjJEAsoFO9yR53G66vG5HlrDoTsuJgdKZywZSE1kLRwLqvr8HuJeFbkXFDqjMkJp6HkwqlZkfCcZMugHa16QEpC68y+XFAYQim82x0+ttgmUccFY2caah76E7MIm3xhM0eoM0oM5/rAqTmQTcLKQBHNKC3BOGZd4XGcqw2P01d2ckSFzHt1oBQY1ZouvLFZhCCW0bUsrAnW0DdP2O6FL/Y7Eomn/MifJs2c1uz8hZ1dOOSeXBSrEkhzi60stU5s6xNL17DLFyKWCw0qCzZnLtUaifk6v6gUg/tAUYondWIlE7v4TjEQQsuP7Xd0drlmnwbBpxq7JN5xrBaPxIpFHG/qE+1i2IbMRXmSykTAloiWkTUWEzJBtbgIWRU0AUxNikKxhktpKGSWYskCKV1Xl5RO44vB5AwRiobBNJzkOjNoSZgESVtiiSCG+/yGL45AhUszFMMmj7/s63NEAYrli/yJqv4Hi3O/ZZm4ubm5+V25NXO/4rPwd/uAuBc2aaCPKzbqwqxq5mKZzQqtAp/5BisTz+YTkjOjumZlKlFM1NxNb3w3vlDpI8kZemfwqmJW1TVHMwjaGoiRnfqC1WsWGozLdCExZksqMNsVSYSL7Qg4NqWnSQMbzmRl8Vnx/7b/lYJGbOZD+JELLbG0+GJ40o+4lAio6x+sgnU4kkvk5/pAVomohTr2iO6YVcORPWIU3bzw4E80XGhcj0Jh0sjF1kCmxjOyRhDaMFGXkSbOZGUJ0hBKw6lyXGLH1GnW/p1oLU0+Ew1oLWgi9Us+RwAAIABJREFUnbxRZkOrIkkbVurIsWrpUcyuI2uFzoEjewwDXn3ia/uImhp83pLQZBUwMhNMZHb2Gn9VfsaFM2ShMoGj7CA6TJ3YlROewkVavLLUMaFIZLHcxXcG3fHN8JWjeuBiHdotJKlIWTHrmoN+QYfCftb4qkZU4cd1x0VvYQ4cwpFz3uOXDadmjWRHjImmmpHF8aVour5Dz1uqbwPeWVALfRGSEtbLKy53zCXhzIgyCV9qTDJEsdgSiDhMPnFX3jjaDceqwYrwyAlK4l3uCFIjNtJNZ1Zp5N1tsBaOaU+rFwLgYqCvawpAiTxOr7TlZ171R05obD2jVWIXj3xRln06Y+MX1vYEknjRj3ipEKNYVI2WQsgar4WqBESEi1oTtKPJMzYFVnFA5ZEoloBB5cCgdgyqoy8dUoTrGrmE0oWsHOieSdfMoSX+cop7c3Nzc3Nr5v6TOSQaqzklx9kYEtDnFVVc0EukKI1oj7cOUzw6J77LP3MuHaFU1GVBiuYwe+yieVvfYWVkyB292pNQ2Jx5XJ7J2ZONMLeWAjTMSFTMIiRTKEWRRKEkoNMvw+Il4mOHIeCBo+wZZIsjMmPYyiubdOKkDFV2+OyockQJeCNko3jR98RyxusGx/WU70MZqPPIIB2a61C6rxSVvHOXj/yl/Ds/8q+81yvEBIKsSKUQMnwaf6LUCqN7iq7p/IWhrFnFiaNrCMYyKUtRkWqJDLahp0HrBVUJBbmuj9WeKJZDfuFivmcvLww0xGTp8oVoKiyQs8XmiGPAophLRSgJZzzFJryu6PSZ2WRSZZniCu9rprKjS5ElJ6xO2DjRqYBNPSe9QUVYxQvaRlZygarwcfwbzTLz35s/MRmNLZHH+cgfpn9AExi7f6XXFhM9Iw21qTiv9qgQaN5OyCVTiWMXBgZjsUpjiuDZol3DQ3jnm+VHohfGcOb/s/+NrxwIZYsOGapC0IasrukKasmklcJLxVpbSvZ401KXhXXxFNGc2NLKkXUasSTqMHOXLxjJSIpYyUx1R68VjfcEFmLmejtZR5JuGIzhLj3xOD5TDUKywlBVVCkRQktWjuYE+l5jS8ZKoM4BmzLnWjO7hoi+/q7RkxB0jqhcSEaxVApNZJtOiA7c88RcajbpyMAKATwONwcqO4DzVHnGqBm3PMP7z79pnbi5ubn5Pbk1c79SW42ZF7pUkf0ZJzPKeIrULM2KRapf5ucyVRopxTKllqAMixLe1CdUcsza87SvCVVEUeNLRaCBKJio0ecTx/WOwQoeSxBYy4TRkYfwFYpDy0Qftzw3B9o8E1HYPHI2FS/6E4t2XKRBRJhx5KzwxbHPPa9SEYvhovbocmFU5pfopIwlYfPCoNeYaMha4ZVj1g0xCwsO0bAqA+s88pCPfFInSn4hkmmjcDYtpigWMTy3n3DZU6marbzxXfwf/MP9F+ylMCdLKS9c6j2zWxED7JaJtfGMrtCWiURBqYU5OZbU8JkHbMgUnVAyYkvi4/zEaFqiTtf0CVZEGmJnMGlB60izvLN2b8SoWKg4mQqxCdGOVAxxcqzyF5oktPl0jQdzlhe3IcWa2k98DE9YPYNVRCOc63tc9DRe0/qB2VpCaRnLFh1nHocXTBVRcs0YrVMkhRGdIx/T31nut4ziWLaeaoy0dmIxDU1ZkMMZld7YyJGUNV/shme75dUdyK7CuojBUxehCzP344UXGmRKXDqNLolX80AumUGtqcNEUhqthC5EWFasWLDulaqaMCVglz3eCcl5hITIQp0Tddng9XUnXLaJXja4AJYZEcWmj+Ss2frEHDvKasA0gUG66+Lf5Nn5I/f+yH/YjwySyAJZhJU+UqKiKI3nerqZSqHOgTbMKDw5WQazYswrRtWggYpIsQWnZ6LWhFJTOFObGbm8/dal4ubm5uZ349bM/YrRBW0nSp5QKpCoqOk5sqeQ6FIgAhIL+3PmkL+ydBGpCnUKFBq2y+WXGTVwaebNHHAqUKeFrBT3y4WtTPT9nlHXRFMYVU0VA0UptJ1xfmHRNQ/hjIuJOCfeuzWSNUezZ1HVtTGTSJUCvWlZ5YWaRBs8h/zOKQuznmnT+EtKwYBPDiuFpszEqaHVI7OqCaoBr/gmfCaaiimsaO2EahZiSAzZ0rxdmNs/csYxyI4uT1Qxg/bcq2cajoyy5tk90s4L3VQxTYnPhw+c6TBG2LQDZY78y+uJ/7Atyi1EFIsRerVDvKIvHX/uX8mSoAo8xp9Y2YniM89qj9LXV7xRL1xCh9c1bTlRlKMf73g1DwgKsscx4LFErYkVDNYSXMOoLdU8o21AqYwxI8k5Xsue3CgMC2Pd0pREWy0YIBVNWTT17Fl0RbLCa7OlTSPWz6RScXR7XtwH0qx4a7/nQ3gms2LICzuZ2Mwjr7blVfZEnThjuYs1Kgd+zH9gKBsmWlayUKmJA0d0yqgipLjCoKiLZyqWiRYvHQ/lKwVoc08pisN4otORz3YNCsZqx0W36LwgamAbFuo8ITYwSk0jI6th4NzWjLHlaA9cZE1fbfgmPdFJZpMyPq2JCqJoQuk46448K/b6mQw0eeJYrZHr3msMIOI5lDdm1eEBSmYqLb1ZY33gGLYEa5hszYUNQqRNI4s0eKORYgiyJglkKQQceQzo7f43rBI3Nzc3vy+3Zu5XQg7otWClsPYDR1dTCnTyQpAGJKNEaPBcmg4t0OKZEc62pZeOKJGOI4sWLnZNiIXH+IKPFqxmE3qqMoG1+FIzKkMSQdAkEb7yLZUJOBX4NvxAEc/f2u+ZVcOsV1SMBDQZTRFFl9/RKWGVx4uhthN1mZnVjMsRRWCXJ/4Q/0oSR4g1I3ekPBAlElEkVgSxaJ1RMSM2kgVOcYuJhso3PK8+4YOCquBSxFOx9QtLI0xs6EtDR08oFqs8GYuThE0JZct1obAUgvG87xQVkWbxfFQvxLni780GN1gWNphe8f+zd+exlmT3Yd+/v3NO7Xd7W79eZoYzpLiIWiKTDMXAgWzYjkQJAZgACswEiIREgYBEyvJHgEgwECgCAkQBYiOBlQhOpFiSY1OKbEP8I4IsW04CwxJFUpFEDtdZODM9Pd1vvWutZ8kf747Umo0zVPe8bvF8gMKrW3Wqzu+eqlv396pO3VpPhLTfcJQrenfEfvYij/RL9iVjPlzhmeQdBAVOFINkOG85T8eEJkOFjDazOJPQ6oJNmqMQFvpxct0x6hvIS6bmlN1wzlkyZVAppQiBQOEtjQdvEuamxDeKynWAoRtm3KpKJvYO6dAzCSty12KHHcRa8tQxXQmb1DOkCq8cqXMYq1lxhdoZXiwn1DqhRVH4wO5mTmfgmrmDE5gMC/JB2LWntKbkXKYsJhMaX+GUxRJI+8CQFfS+ovQDubf0Q8LcTOjdhiS0lMPAUZHilKFTY8rMMulqSrchpA0Yx5qSpZkSQsBLzlyNCR4QYdHu0lcWPSxYpYqh6GmSnsK3pDSMxeB1BhjypCY44dpwGy/XEPFk1IBnkYwYXIINCQiAwuuE86Ri8CkLGVOFDU5lJNIziKXwGxqT0yvDwIgqbEj8QB3GrPPJZR4moiiKHigxmXsF4zWFE4INhCHFesWgDIVuOHBnnISrBJ9hjCO3DSUrNnpELxUSNGO7xEoJAa74l7ADNJKB9vQmZ+JPORpPGHdr9oYjCltx2xX0BFJ6Et9e/IaazFgx5vdHB/jQU5sCURaHQlnHjjvGSUZlV2RsOEoyBpWwVCOm3SlX+znP6G+hGyokD2R9zQ41Y/sSz7j3YVRg7FvqVOglo1HltgN8YNfOmQ3nJEpRMCBBMKbBqZouG7NWJXgY+SUjabjSb6h8TZfAepixTndxTjN2F4+dmvUOLx1DJiR05EmDCT037IbSNiSmpvOOaqjZjCYou+FUFGlbUaeGuS7pjGPuU67nL4LWlH7Nvl1ydViwYoqRNaN6g5OEM0ZUTjNqW3LdszAgGqZuwTP5dTyGLsvY6+4gAfbtEdpZQl8wDXNOkz2MV2hXkEmHEUeaLqi6AWyP1gOn2ZQ+CCM5YVCaeXrIIELtSlDCWbhIsKq2wxpPuh5YMsZ1BmegNQcstaEdgbUb1HhEkl7chVqFJXlwjFRLnxlwnnHS0PiEzHWc+QkOzaastj+4axif94gINldIGBgSzbX2Dq0rqP0eVgU6yajkGKc9Nrm4O9snjsGOGCTDdwU9JZnAII4ER58bTHCclwV9afFKcEYx9Am1r9BYbBLoxfB89ji66xnYpfcVE06Z6CUoj5GWczWjk4KEgemwpnQbrORYrwhJoA8JCR1Z6OlFsVElVgKDZPRoCgzGWbwZsThaxCdARFEUbcUj4SsYDKO+RKWBs7CH1RcPI6/dhJlbMVY1ZlgzpJqR39AXwloyMj8QXMpgPINYegJ9GCGi6MUQEPLQsetrTsMMqzUEzdSdQlcwUyc0Giq3ZK32WEkK3uNMggoK8ZAGSx42TJoVPghDAof6HO9g41fkWHqV4BJYMGIRSoY8YcSKTV5x4qfMwx6n7FP4npvVlCapsJJcPIHBdmhlcVrRUqC942p7wrFc50Tt0uuUrFsyzwvAI8oy5J5cLQiDIvUOrwUTPIkXpnJKrhpkMzAOObqpydOeK3JMLWNOkxnHehevDhn1A3urOdVkINWB9biiU+CagtAGOjNik5bk/uInN66oOxz6O/hg2LFrVDGnyGtuq0cY2VNSN2O8PuEk32edGpZSMiSKylpmXWCeKnaHgXHXUSYDXRdAQatLpp2w7y15v0KrAXTgTj4icx0+VNyeVgzaowEJYENK4gITv8IxYtbdJu17CmXZ0ysSm9OEKY4Zy3SDNUIyWBJ9caMLWtNh6MQwEUunK4y3WDfhTE0IGfSJkDiHpoPQU/qOjc4orCfDceDOaXPDIrtCQHA+oe0se8OcG3XFXAzzSl1c3vSQJ0umtkYFR0bLlXZO26VIMpDQc5anaD9QmA3Tbkk7yukzw1qmeDTeaK7XDVZpLAlKHCaAEUevLn7/zktGOkCme1bBMSQZla9R4plwxjW5SRYsSk9pfILm4vFwhEDpB8CxSKb0pDhSumBZhykhCLrv4xMgoiiKti71SCgiHwX+R0AD/1sI4b97xfwM+CXgg8Ap8NdDCF/bzvtJ4EcAB/xnIYTfvCcxaUG3A7PBY5VwvDHMy/3tTzDsoX1CbjuK0JLoHhcKMqu41t+hNkuWFFhpMENHqnrS3nNajXEo1nrGxo9JLIhP2elatBoYLRuytGfm7qBVy9L3qLRkLmPmegdEKE3PfjhiJGsybcFqjsMVzmUXgidzFz8DMaJmcBUbxlhfIDoQ8BAEKyXeeBbJBNWeY8JAbltmSrit9xAveIRZt2a3XVG0mpkaKJMzZskRp8M+SyWceHAJF53ZVcU1ewpBeOTsDqgRy6TC+ZLUDewPLY/YlwhDTTAta5szjDVD6Ml7wQZNGzI6GUilo1ANuYeagiqcs1YJ036FI6VyG0woCS5jx56QNDkmv0WuN6T9gvNul0wdkRLYuOvcygPL1KOk54nV0+y5hjoZk/YFZVtRbSo8KRvVMQ8VB6FjNd4hZIEhHGJCxkF3xGw4JetXzIaBNLQ8PXoH2kGX5CS140Z7yu3iOqkXxmbJgZ9T+oFeEnZCjeGMhfZMuppicorTKdYp+jbhhaGgDxlK97SqoHIddQh4n9BJReIVu/6MRlmuDicUcsbCXqcVxYv+KkZbMj+QuoxRu+QkcxwnU3Ld4tzFo+GknuOzHQp/zFAaKt8w+PTiMWxOcbVbsurHlE7Iw4Y01AgKg6VOCjrJmLg106HnhaRAXI/Uhr1uiU8UTatozBSjhKXs0KiUkatRSnOtP6XMNzibcWxqtPcoH8g7TxE0FY4NsOcWlDQEe3EXq9UttaqobI2XhF57JCiyvkcE8tEsPgEiiqJo69KSORHRwM8C/wZwE/i0iHwyhPCFu4r9CHAeQvgWEfk48DPAXxeR9wMfB74NuA78UxF5TwjB/ZnjMgpdrtl1z7NkD81jrNodKr9G3A5X6zOMVUy1x2WOsu5ZFJ5lm3HAkmtyxCYt6IYCNhpSTWUTRnKO9mfsHzfsdksWeYmiprOKw/OAPewompZ8es7Y9xzKGc/xHZyTkzCQ6lOuqC8ypAaP4Ti9wsytyMOKWd3RSMKQWMq0BqsIDsa2w+olI71glrQkOpAE2G0bZsMKJwNzvYdSLYd+4JHNLVySMFtYDlhxZRXYtXCepKh8RpFC1jbcMg0kgTSrMUXP1K7QLmG0cby7/xrLMqe1e+yvQBvFKAloP2U+T5mMe0LXMtUOyaqL36TTU9KhZ9q07MvznOcFu1aT94pJrxj7gaYp0cZQDQeUeJJ6nzSxjKyjRDHkBTPtsSpDB0MZciahw3crjkzF2LY8sloxOQ6kWUIWao4qxyYI52aKlgxvA4kxVMOAV2PKEBitSvYcHFqHSXpColjYNRpL3STsrwZCPeGKrdkNipk6oTXXsMOGdVKQbXI8lqL3LCtLVuRUTlEOtxhcwpWznpPZNdLW81w/RUzKjmuZ2RrfGVZFhU0nJHLOrl1wzZ/grGWlYWYbOpMybgamyyuMilNqdRtbeWbNkqwtyReG9w5L8mLgnIplDyZzzNYriiBoG5jON5zJCuOFkAaWowxrO8qhpe/mVP0ZO8mcjR6zsvuU3YDdFOjOoArLoTuiN2OC5Ex8QpfUpN5S9o7HVglku7jSQnietSoY21Om7ZpCOdKhIU9OWG12WGeCHRImtkWygamsmI8mFEFYpzm7i47xasN0t+TRb/2OeFYuiqJo6zKPhh8GngohPAMgIp8APgbcncx9DPip7fivAX9bRGQ7/RMhhA54VkSe2q7vd+5FYKb07KxeRNaGdjjm2Aw4nSMmZdauGQ8De4NjubfLIEI+9Bx2KQehwLqBJlnS94qxDzRuxMpfXGKadDBVE2bZGDe6wSln3G4V9WjDaJ6Sr49Jmz2qUcFuNeU7PJxOBux0D20OSY9OuW0stWso+zmanHVdMM6uMnOa0eYOVixLs8+Z7JKrjke6Iw4md9itPK6YYJc9VbIi8ymymrCfJUzUQONa8tbQupJ3ScYsXCHPWrQoMmrqoUIJZGVBUml8NUbPBzKEA3tAqjPK7ICmyqgmhrlNGe+U7OoRu/XzhCQwHdUMu48h7S2MCBOTcVTsY23JLHc8Nn0PZfntzJsnua0EVeWclk/wuHdwNGenm7OnEg7KGcdZwjr0SDtCQkoIHTLZ5Vp1QJV3DOcbfndwEGBSON5hFU+YRzFhF8mmBBQucxRuSeIG9uoFelwyd55AwjIRZld3eay9zqOLA7AN7SiQhJwh0QQdKI3mvSNDr1KmV/eptCKfH+FVytkLT4PWuLFGm4yRqqgTgy/vAD2m2aWxB9ywgfrqPvM25UadoNY9vnNURnFQrglhw4tHDS49JUtW7IwU2gSsMXxHB7eCEJoppXJc7Uoe6z0z29DKjCwbM5pV3LA137ajWIbAaUhYlgaXFWgZ6JcJyUhhOSPVFj0r2JXHyTcnrJyjoueRxvNYqen7hEfLDskr2l7YTfawZmAWCr47qXhe7/FSW7DCQt/wLpfzruGdMJwzDoobaslJmlI1ljWP4tsFqsi4EoT35RnrWph2DVLXtNpjnacOt7ldlKzTikZSrlUpf+kv/5u847H33YuPehRF0Z8Ll5nM3QBeuOv1TeC7X69MCMGKyALY207/3Vcse+O1KhGRHwV+FOCxxx57U4Ht3ngPYRQYNy9w0KdMyysk4wnvUh1PTD/A1UcOuHHjUVqjWHdLRlnF7niffj1nfnIbcR5dJKgkR0uKLws6leO6NWndkJmKYlyiMs2isZwuWmxzSmn/EkUWSKoRhS7IMPhySp8XqCCw+VdYbW5j84JEKdxqg01nJOWUCkuuDO1gafuWDYpmsCAtVSVMqwKtM+quYb1a0XYVSTojrQylgKvXrMWTpTkjKyQWSFOcD6yXCwbrMIVhVCaYPMWnGbZ3hL5FhYHEg0kK+sTQB4cjoMVQSYZbL2g2c6q9fbLZPqv5KXRLTD5h4zRtt2FajsiyCusDiXwPjV2w8poy3yUNlmF+QtZ5iipHZwWPOGGwFjsM+LZDEkO2MybNChg6bDPnHY3jpOvJc8tuUZHqgtBp2tYSUsV35gV1t4ZmSZFX6DRnsd5wUi+hLNmb7rOnDWnXgRFCbljVLR/sAjpPmORQKoPoBC+eRCW4rqZrVvBtfxk71KAgzUcYZXDeUXcLfOgRVZKSk6QGnxW0AXzbYawDrVDOkdGTpQntcsX5+ZwuF6qRpiTg9AgxCW0rLJcrEiz7RUmeJXwPhnNnkBCYFSOmhUb3G4YghBDoXKA1IDgyn7Bxhn5YYUxPlk0QXdDXluP1Bi2Oq1WC8ZZeBlReQEgutr0OFHlBZQxiLVYyzp1l3axIJDDSBWln6etj3hccZBUqN+iQgBuoQ4cEqPKKcjQhDIJvOjLtCf3AYtNTN0vq869wqgJJdcA73vE+ru0fklw8HiKKoigCJIRwORWL/DvA94UQ/qPt638f+HAI4T+9q8yT2zI3t6+f5uIM3E8DvxNC+Hvb6T8P/F8hhH/4RnV+6EMfCp/5zGe+bmy99fz+536X5cmz6OQ61554P0UCV4qMsiqR+FzIKHr72B5cDzoF89Y+eyLy2RDCh+5TZFEURQ+EyzwzdxN49K7XjwC3XqfMTRExwBQ4e5PLfsNSo/jAd3yEwX2YRCtSo+7VqqMoeqvMW0/ioiiKvplcZpbyaeDdIvKEiKRc3NDwyVeU+STww9vxHwR+O1ycSvwk8HERyUTkCeDdwO/dy+BSo6gyExO5KIqiKIoeaJd2Zm7bB+7Hgd/k4qdJfiGE8KSI/DTwmRDCJ4GfB355e4PDGRcJH9tyv8rFzRIW+LF7cSdrFEVRFEXRw+bS+sxdhjfbZy6Koj8fYp+5KIq+GcRriFEURVEURQ+xmMxFURRFURQ9xGIyF0VRFEVR9BD7puozJyLHwHNvsvg+cHIfw3krHpRYYhyv9qDEEuN4tX2gCiEcXHYgURRF99M3VTL3VojIZx6UjtMPSiwxjld7UGKJcbzagxRLFEXR/RQvs0ZRFEVRFD3EYjIXRVEURVH0EIvJ3Ov7O5cdwF0elFhiHK/2oMQS43i1BymWKIqi+yb2mYuiKIqiKHqIxTNzURRFURRFD7GYzL0GEfmoiHxZRJ4SkZ+4T3V8TUQ+JyJ/ICKf2U7bFZHfEpGvbv/ubKeLiPxP23j+SEQ+cNd6fnhb/qsi8sNvot5fEJEjEfn8XdPuWb0i8sHt+3pqu6y8xVh+SkRe3LbLH4jID9w17ye36/2yiHzfXdNfc3uJyBMi8qltjL8iIunrxPGoiPxzEfmiiDwpIv/5ZbTLG8RxGW2Si8jvicgfbmP5b95oeRHJtq+f2s5//BuN8U3G8XdF5Nm72uS77ue2iaIoeqCFEOJw1wBo4GngnUAK/CHw/vtQz9eA/VdM+++Bn9iO/wTwM9vxHwB+AxDgI8CnttN3gWe2f3e24ztfp97vAT4AfP5+1Av8HvCvbZf5DeD732IsPwX8l69R9v3bbZEBT2y3kX6j7QX8KvDx7fjPAf/x68RxDfjAdnwMfGVb39vaLm8Qx2W0iQCj7XgCfGr7Xl9zeeA/AX5uO/5x4Fe+0RjfZBx/F/jB1yh/X/fZOMQhDnF4EId4Zu7VPgw8FUJ4JoTQA58APvY21f0x4Be3478I/Ft3Tf+lcOF3gZmIXAO+D/itEMJZCOEc+C3go29UQQjh/wXO7ke923mTEMLvhBAC8Et3revNxvJ6PgZ8IoTQhRCeBZ7iYlu95vbanl35K8Cvvcb7emUcL4UQfn87vgK+CNx4u9vlDeK4jDYJIYT19mWyHcIbLH93W/0a8Fe39b2lGN9CHG/UJvdtn42iKHoQxWTu1W4AL9z1+iZv/IX6jQrAPxGRz4rIj26nHYYQXoKLL3bgyteJ6V7Feq/qvbEd/7PG8+PbS2S/8PKlzW8glj1gHkKwbyWW7eXBv8DFGaBLa5dXxAGX0CYiokXkD4AjLpKfp99g+T+uczt/sa3vz7zvvjKOEMLLbfLfbtvkb4lI9g22yb3aZ6Moii5NTOZe7bX6y9yPW37/YgjhA8D3Az8mIt/zDcR0v2N9q/Xei3j+F+BdwHcBLwH/w9sVi4iMgH8I/BchhOUbFb2fsbxGHJfSJiEEF0L4LuARLs6kfesbLH/fYnllHCLy7cBPAu8D/lUuLp3+V/c7jiiKogdVTOZe7Sbw6F2vHwFu3etKQgi3tn+PgH/MxZflne1lH7Z/j75OTPcq1ntV783t+DccTwjhzvbL2wP/Kxft8o3EcsLFJTbzZmIRkYSLBOr/CCH8o+3kt71dXiuOy2qTl4UQ5sD/zUUftNdb/o/r3M6fcnEJ/Z7tu3fF8dHtJekQQuiA/51vvE3+zPtsFEXRZYvJ3Kt9Gnj39q69lIvO3J+8lxWISCUi45fHge8FPr+t5+W77H4Y+PXt+CeBH9reqfcRYLG97PebwPeKyM720tv3bqe9Vfek3u28lYh8ZNtf6ofuWteb8nLytPVvc9EuL8fy8e1dk08A7+ai4/prbq9t/6d/Dvzga7yvV9YpwM8DXwwh/M3LapfXi+OS2uRARGbb8QL4a1z04Xu95e9uqx8Efntb31uK8U3G8aW7kmzhoo/b3W3ytu6zURRFl+7r3SHxzThwcUfcV7joI/Q37sP638nF3Xt/CDz5ch1c9DH6Z8BXt393t9MF+NltPJ8DPnTXuv5DLjqVPwX8B2+i7n/AxaW6gYuzEj9yL+sFPsTFF+vTwN9m+8PUbyGWX97W9UdcfDFfu6v839iu98vcdcfh622vbTv/3jbG/xPIXieOf52LS2t/BPzBdviBt7td3iCOy2iT7wT+v22dnwf+6zdaHsi3r5/azn/nNxrjm4zjt7dt8nn7iq4BAAAgAElEQVTg7/End7ze1302DnGIQxwexCE+ASKKoiiKoughFi+zRlEURVEUPcRiMhdFURRFUfQQi8lcFEVRFEXRQywmc1EURVEURQ+xmMxFURRFURQ9xGIyF0VRFEVR9BCLyVwURVEURdFDLCZzURRFURRFD7GYzEVRFEVRFD3EYjIXRVEURVH0EIvJXBRFURRF0UMsJnNRFEVRFEUPsZjMRVEURVEUPcRiMhdFURRFUfQQi8lcFEVRFEXRQywmc1EURVEURQ+xmMxFURRFURQ9xGIyF0VRFEVR9BCLyVwURVEURdFDLCZzURRFURRFD7GYzEVRFEVRFD3EYjIXRVEURVH0EIvJXBRFURRF0UPMXHYAb6f9/f3w+OOPX3YYURS9TT772c+ehBAOLjuOeyEev6Lom8+bPYZ9UyVzjz/+OJ/5zGcuO4woit4mIvLcZcdwr8TjVxR983mzx7B4mTWKoiiKoughFpO5KIqiKIqih1hM5qIoiqIoih5il5rMichHReTLIvKUiPzEa8zPRORXtvM/JSKP3zXvJ7fTvywi3/d2xh1FUQTxGBZF0YPh0pI5EdHAzwLfD7wf+HdF5P2vKPYjwHkI4VuAvwX8zHbZ9wMfB74N+CjwP2/XF0VR9LaIx7Aoih4Ul3lm7sPAUyGEZ0IIPfAJ4GOvKPMx4Be3478G/FURke30T4QQuhDCs8BT2/XdE731nL10kxc+9U955lP/hDsvPkdv/b1afRRFfz48sMewVxrcQD3UDG64X1W8PttDt774+4AKfY/fbAj95cbYNS2r8yVd075xwa/Tpt73WLvB+zf/fu5uA2stXddhrX0r4X9dznr61uLewvdpbz3LTcN6vcG1mwd+X7osl/nTJDeAF+56fRP47tcrE0KwIrIA9rbTf/cVy964F0H11vPFL3ye3/nNn+OOssxdjg6/QRlKZtWUYiS84+oe76keoTcat3PAdHYVv9jQtw3pZMze/pTCBNzgUaIxeY5TPf36lKEGshloGDYL+sEjWiB4JE0pRlOC0iCOEoUeHKHvOV+uOestaa4pMnBGo0LA1muCZOxM90i6mqZfs9Epfe/RXc/Qb+iGnszMGO/vUo41udYEUzIog/GBJAhucDSDxytQIRD6FWkykFVTbMjoNh2JMaz6Dct6w7jK2Z1WQAAEpRKUSv9UW4a+p1vX2CCkuSE1AXQK5k/K+X6NtzXKlKh0dPEhdT0hGIIk+BDwgDYKjaWvV/TWk1Zj0iy/F5v89W1jeWXML7+3MAxIkiBp+joruPfear3WWpxzaK0x5k9/3HvvGXwgUUKq/vT/dc4OOGvRxtB4obaO0mgKpXDWX2wP83X+F3x5W3ohePACtR3oXU+qNLkOoD2b3tI0gcpUFElBCBbxFu8Vx3eWvPTlr3B2do4aFey9/xrXH7vB/nhGopO33H732AN5DLtb6Hv6tuGF+dM0XYNkJU8cvp/MBbrzBUPXYYqUvMpohsD5piEIzCZjijxluVwwny/AFBSFYZK02K5jYxVlViLGcFoHdEjZG+VU2cU+2Q5z2mFOqnLS1Sl91xEyRXr4XtApm/Ud6BoUGXUAk4zIQ8bQbDCFIplMmK8tw7ohzw3FKEH5AW83BKeRpEKMYAaHsi1gaEPGehjAb/DWssGQFwX7VYLtLbV1jLKMUikGD14Z7NCzPj7H37nDeGdMOalIrlwFnbBsB5aLNWqoqUY5iU7ZrDesfYNJA3kyJhHQocOkJUkxwnphPj+jPj2iKFImh4/i0xTXdPjlir5eY5KEdDwiK3Mab2icMMo0uXhufv5puvU56+Uxk3c+zt6Nd+KtwrYDo0xIE8+qWdMujqmylFlVoCd7uHpB5yx9PqF3iq67idYeozTj/J3k+YjB9Qx9iyLgnMMjaAOrdk17dkR2umBS7RJUSl1VYAwqSZjt7zMMDevzU+hb8kTjzYhgCsQNDMFj8wqTalTbwGCxAbyxlFlFluT4dk2/WbI48zTDAEpzeGOXVCt0GghZxaZesT67QxgSqskeGMWm6Tg9OsHNT0GnXM0bdg9GeCXMs302tiOzS8pM4/Ue3ucYUWRJQug3JM6RZRWbrudOu2RIhN1cs19NMGZC7wQk0NcN6+UKnRbs7O+gJXB8eou6WzDO9xhXU3qxdOsG1a4REXoEyTKKJGewnuA9WjuC8TgvpPkEk5Q0bY+1jlFuSBP1msfie+Eykzl5jWnhTZZ5M8terEDkR4EfBXjssce+blDz9Zp/9i/+AZ97fJenkxscJYfgoXQtI7cmEct4fZuDO19iofYwjSatc3JRdJSMhsChPWYcliwyRWMTRqpDj84geMyQMO+v04mwLnPS9UAvgbbo8B60LpjZhp2hZsdv6EzGsBCKhdCGjOcnBSfXE7xvGRWBw8UJixTucI2QjPDS0RQlXa9BFDq0ONVzEBbMGovUFV47BkkokoRd1zFranSiuZ0VrChxSc+73Itc7c5xrqKx19kbpcyV54tesSEwC2vepwaSsSMpD8nHE6zOcTYQ3BRcgTt+ntOuI0jKRHV8S2UYFxV3RJj3NXkPWXZEkQlFXpJk7wFZU7uO9LQHU/LCkLGeluSJZ3/+IuGsxpUF3WhCsXudbDIhbTZkizMO93YZ3XiC1WqOamvK2QhrNIkLJPkEZ3Lq1YZ1u8ZryyyfosgYnCXVDqUbatE4W5D5Fj3cIQxCu27pzIhMl0x3r5BXGetbL9IhqCQhm+3Q1jWJNpR5im02LPuajQjSG9zgWMiAp2c/M+xlJVhH6DuyJMcWCWs6/CqQ9EKZJQQcTajRRUEwmro7xZ/O4eY5awN1njCd3mCWKJpuQdN3KOVRrkXSklG1A6HnZDPgfUo+eFRuubVeMJ+P0GlKXwjjasx52zDqjzkY79Aay2k7p7cDRjTDIvBSn2AXZyS951Em5HlOE+ZMRwlZkeFHgVZn6DKjaB3p1455abHiRB/hhxNCbdiYfYZKUyYdqg90oadVPXOtWJuEqhlYdSMy5Zn6JanTPFfO+NJkyovZPs0MJgr2PvtZHvn1X+eHfuDDfPS7/tplJ3T3/Rj2Vo9fd7P1hltPPsmTz36Br955mjkK5Rp2a+j7grWkJKGjHRvqyR47DLh+oPMas1gzMnPaHtZuSpOnjCY1K63oxTNxKQWOzBu8tay9kAZBdEU+eII6og1C2QtZZwjjNWlm6FVJ15+h+g1VXuG1opMxK1+i24odtcaZjufynL7TZF2gPB2QxJNMjilHHf2QIVZj9B4b05F0HemRYj15B+tpwLGkTXI6N0Ybz36/YNKe0rqCIVh2fM5IptiwIRlOkE3D4BVdXtClsBqP6JOUaRfArriTjMEmFEmFyT0iC4Y0YdasyaSn8BvqLqHhCt7sIvYmp5lgh4ZNeh2tMsS37C/n7PTCwWJJMS6waG5mY/pkhFaa97pbuNWSc2pO9C7dl/6AdZhR2J7KNYwKy6JMeN5cIXc1eQL7izWpDazGHYMCweC9cEPdJA0tfrRHOlyDPrDeLBiyKUEsmoFEWc5VzlLVzDbnZHOhVddROkUpSzqC1ihIUnK3pgpzxLfIkJAoz6bb52vZVZZ5Qa8s03CEbzxtN8IycI01Pg+YROiGQN5Bv/boUqO0ovCaqqpJJecomXBqenprKSyU6xxnKlLOKNsTdjYNoa9QV1sW2YRnVclpMaW0a2zwTJYNO5mhanN6U+HsgPYKV3QcNi9yO015YfQoSMrIwXV7xKRpCNbRURLKQGgTdFCYwdKZhHp0gh4GUmMR9SiLJEWv7xC8phjOMapCJ3t0+T6u7kjdGpOfMUueZ0XJeZjR+DFmqChCgpQjPvK+9/AXvv07mc1m9zyhu8xk7ibw6F2vHwFuvU6ZmyJigClw9iaXBSCE8HeAvwPwoQ996DUTvrudrRY8px1PpY/zorlOLWPQirm2gCDBEySgSotBSKUhDBpB4yShtC27VqP1lHOziw0KEwaMchS+xwVQQeM1ODEMwFJKrM5ROFTwjFzPjrtNIgNBBYaQY4aODXscZ1NqXaAI6NASDgKDKoAR4AEFsv2uePkrI8CX8YDbDoImUIYFhW3ZD7cJynDLXGWgAuBz7PHe/ivst6cE9RJPhil30glfSt6Hdg2KwJf757kq56zrFlMvcJIgXuiHCWs/pSlT+lFBolqutgPPLp/FzRXPT64wGMUyHbHXw6jvGZ+fUG2eZ5Mr9v05ySAMKuWr1eMcLWYUruHRxR12hhXLxRXW1QJ7eguNZjofyFeWK25DONhBO08wHY/r58l3NGtlOAtPYNoxJ71GL27i8oIqG6H0Dmbw2O42xahnFTpy2aHZrLgx1pz1FrMCs6zIJxOq0Qh2djnPhXqUkRNov/hF0kVLJnDQb1D2Dje7BUfZDlZ2OA45vd6wLluu24bHW8febYsPFskzzM4GZ3La+YJivk9wGj1e0eqGJms5K1P6zjDMGyYvzlnfyDDpFFMN7C8D1DdZqIygPHpkSUJBXg6YMOOO1tTzikYluEnDPN2nCWP8fIofBvL2nPZqSmKWeNVR6JZVyNiQce4PyBuwKqXMHDbP2LEbpK1Jkjn+fODK8nnmJwXduKCmYL+bM6mFRWXwowGrKlpVMO+nrPSEaliSTiy1Ee5kh7RUeCxKHG0ocGgUNQMZngnwJ8naUmCZX2M+OeQf/6P/h+ujK3zwvR/8eh/p++m+H8Pe6vHrZc4OPPuVL/H3P/0v+KpOeO7gWxlSRcGCwrWs1A6EwEanWJViVYIPniv9OTooysOSxI1x2tFJwaBSNiZlo0Z4NDIEdu2KkbQchudYmxGn7LJRE3qnqeQKme3RAcrQgLpKo2BqlyRcZ9ad0mUFA4rnknfSSooXzcjPGbNmoWfgAzUVk2sryDw2vYGhYeRqGhnhcZynVxj5DbzTYV2OKMUiuUExtIj3GAbSsANqSkeJChc59E7dcm044z39TXzp+EL2Hu6YK5zoA1bJGBWEPLRUYcFaZnTB4Ekpw4DXNyjtkv2ZYezPGeSQOVM2dhfRgYxrtGbERjIWeoJCsAQyHIfdCbtuzePz2wxac2JGWEnxmecpNyZRmlbt8IJ6lFanrGRC4WrysMCowEl6iEWhgclwRrmfs2CHVuUMKkHjOfR3OAyGg3Cbk3DI2pfs9+fUO9doSDhNZ0zskkaVbJISL4HU16RdoAlTujQlpSbRLRtdYYKjCA2P98+R6Z4NJX0wvKAeZcUYrwy5NOwNHSfJDbwTUIbD4TbeDLR6SqNSnNMUvkGHASOBihphH+cCC7NHHhqcKLLB0s5GFEPPgV6xlyjOe4fSc76avJuF3uVFdRWCxQWFaIU5GMiC49AeI1ZYmylrXaDUwEQqShacqF1syAhWOHCOneGYIcvoJWHDiLWvSK1lY8YUsqY37yR3azpJSMQjBIrDjOBgbb4VsYaGksK1aHq+vXmOUbHkeb3Dc/IEt/Qj5LZhwoq91QZvE5759O+TppqPfPAjf66SuU8D7xaRJ4AXuegM/O+9oswngR8Gfgf4QeC3QwhBRD4J/H0R+ZvAdeDdwO/di6Bs2zN4zbmZXiRyvHwp66KptscCvEBPoCcH40hwOAxOF5xnCk8BItvlehSCpsFSkDAgeLLQUDPGSgJowIMEBtWxSh7FBk+QAo/CJQoQEAOYi7RMKv70P/iaiwxue/nr5VnCdpraxiM4PCvZY5VaztknYUPNFBCEwII9vpY+ylm6S+5rjsMVFjJjrTKCzrAhZZ7s8BVpmRZLcukxtmHjp0y6DZ0KrLISpTyolI0yPKv3gMBRMcaiOTN7zClJrKcKS3bTDUop6pAysYZFotkkilS1oAfmVYnrLYPW2CSADTSS0BcFrnCctgXOw2PLBj/pqOQ2I+Z83ryLk+GYehjIFoaiVRS2Zb7RNMFyddXT2JrCWTANgztGJxNObnasM08Rdsn6Aa2E59ennCw7jnNNkismyQrfe65bz7pxKHuHsvB0bLhjr2DTlhcRiqQDvWDpe07COUfuOmfljBTHlc1L7HMLJxteqAYaUaxLT5o1CJY7+oDdzjGYAjuGBEF3AzI+5yw1LEdXmHczrPIwDhSDpSs1085yK9nDXXHcSffQyhIkI+9bjg8hDCmi9zjUL1HIOfN0hA6BUz/lljyKDRlZDplvWSXCWpe8FHrCRLPjPIae2/oJNnqEVp6WnJfSXaQKONFMkiWd03Q6R1JhQcZZfg3BIgJL2aXBEZhs9+2XP2uzu/bpV5/AOs8ruskB//Jz//Kyk7kH8hgG4KzlCy9+lduypplNaHNFa4RV2Mei8cpQhg3nTFACAwmOhI0ZkYaWPNRYNCIaoWOQgiEkdHLRtUGUsM4ryrDmRAqMH1hLxUqm9MGAwCQsIBhUsCg8KM+akh13zqbc41xdoZOEEw5RMtCHkgUZRdjFoljLDAec5LsEFBfHNk+RdIQAiMdSsNEjOpUyJB4t0JNjMksICZnU2yV7LBUOAMNJXvOs2+dZNyXohCN1jVbltMGAGDJaBlVSoxjCiCAeFzKUDHgMNh2zCiWKGyigIcdmKU7Ahyuk0hPQtOQIjoChB3xuOAktXyv28WLoQ04VWgKewB7IgJGBI66iJNCRsk5Shpef5iQajUUFCKmjJWMRpgRJ8WgCnpSWVSh4gasgwsaPOEqneElQ2rOmovGalZrQSoHBEcIMkzq0Cwwqx0qGFkcfMnKpmYcxrd7uM+qARlLqMAJREBydCFY9wkZGpMZC8ByrCUEJXi6SHmtSakqSMJBTE0TTB0WdlgxBI5LjglAYS5+lZC5lrR7lmXAVckFJy5m6gsPQyIiXT1iI9ExCTU9OSAO5XXMqEzZ6ghbHSdijlCWOEotQmIY6aI7l3fShoJEci9CFkotOPQYtOxAUkuzhgqGQmgSLCTPQgV5Sggr0pGRiGIKhy76LiRzRS8G5HLBhQq43rEPF8W5gt10gquL3v/SH/MUP3vvusZeWzG37j/w48JtcZCG/EEJ4UkR+GvhMCOGTwM8DvywiT3Hx3+zHt8s+KSK/CnwBsMCPhRDcvYgr61cs/YwmZK99IeRPESC5SMACIIqeAGQX03n55rQcj8ejAU2/XXGH2SZnyXZdF+V7oCe9+KC8fGZCLK/eXPIa468X9PYU3R/Pfzm5CwxoBrI/Xn8A5jiQA5ZhhtcwD7v0aJCMi6TTbJPZBKMsm1CQmZwFY87SGQHBEwhiyEKHSno2OiEEw2myRwgWJLChIiRQ+4T1qCKl40V2OfCnnMmIjexgUSgD1+U5TqprpH1HJzlOZaxlig055dCzLwvaVDF0gT2dkuFZ+Ipjf4XaVzxfHrLXdhSDYdSvGduaRToiSaasyym7uiGhg3qDWM+JW+P6gNUdaxcYb5ascDQm0IeBs/yQhdeY3pHUC8Q1FH1D0mua0YLToiMJLYt0jNWCpiB3jg2Kr16d0ZSQkJD2A3ljOc32eKkcc5yN6XOP0g6CZh2m3NFQDA3rwpIlltwO5FJxXNygraAfJlhZ05WGLhQo01OlljUjHMKAodA956aiNzv4IOyEBZ1WHKU7tCFgFYz8irUp6EnwPqFXiuBbnBEGHQgBghNWUiD8/+y9ya4sSZKm94kONvhwhjtFZFRHZqIa6C4CveOGAPkAXDfALQHuueKWAHf9Sv0YBBfcVbEqq6JjvMMZfLBBB+FC1dz9nLj3ZnZ2FLqQHQpcnHOPm5nboCbyyy+/iHqSrBhsgxiDqiKmw6EcaXgrr8FFZu0AwUhCJRJYM+NB2zL/nyQdl18+R0I1JIT3d+8/s80///iXasMAQkr84Q9/x/1Nyw9+w0/uBbNYFIuVQMYSxDHrYqcsYIjMRFlxEAf09WgGNIMURweCSmbGE7klYlFjOGqLsqqmJvMgLxBJoGCkBKM7veFgewwQcKhYjtoCq2pTLAMziCXigUSipQSZCa1hMZIYta02cgmchUT5ngggEOmY1YBs67WUgPdBFOyKg/vvECIzHUkXe6wEcaCZVhomfMmaAJP6CsxMCcIVsrj6aTlfMMw4DAJV+1tsbeRAh0iDssKLQaUAwaBgBDKuTgdPeQdK9gZZju1IZJCZSRsCjiCetDxDNfwkb2hlJmgm04JYcIqXGUtEMRyMZWZNeZcUZGYmgF3mgyeSQDzDQg6YzI41R92W65XFN0HQlnvxIG3xhWQO1mC0AUz1fZlESxBHwrPXSJaWSW0FhWWujTJhDSgDe3tF1o65zp/ybyElUsVzjgc29DLwyIq9W7GjB2kreDeMNBgSkBFafuSvEFUQig/ClPtUjVGir3NLQYQjHrTcJ7RmwOo7M2sCsXxrPW/1ZbGddT4MNHQcWcnExu1wq0S8/wH98Hfw+t/+TIv9XzL+q67Nqqr/EfiPz/72f138PgL/yyf2/Q/Af/ilzynOEw/GMUnLGYxdjgUUnc6EExDTCpCEp/uq1ImxpDpt+SmO8wR9djg11UAt42NATi9+/9z4mERnOY+PaY7KZw96yyABR8aK0jIyUQ2T1pdZM56RiGOkxWAQJibWNU5MJEk8mCswDpMyNg1EaTBEojR4TSQjPHDNLXfMqSNHg7GWWz6gJpGTpWVmZMWtf0eeDxz1JX1ouDcNbQKH8Hp64Gt5oN/tmLuZXXrFO3PLY3PDQ9qwMRazhUDDFDMfzBXzMTOtLdlNfDFl7jtDOza8j1/yorvn3jZIsjwGi2Zh2ghTVsz0AZsPtDJxdzNxO45Mr8A+WCS+xB9g9rCeZ27MI00/spp3hGzZNS3eDuzoedA10bV8v77ie/eGO7ehz4/M0hJNj4/Kvmv5jY6kreF9vGGdEnv/msms2fs1e/MSdMAQmMXTpz2TnQsjkgMHs2EGrvJ7bA4cuSI1imRLzMpsDEYDY25QW+aemswm7vg6/xOH5DnICx7pAMOkMJmewa9QEbIKK/Y0BKIYZhoiDaCogKOIohMdSXyZdx+NP5a5+rk5LQTzL6OLx79EG5Zi5u7dgWE38mL7ge9kiyVgUSKCoqiaAlIkkrWIwFGPSgOaqqNeMgtc2KRMsXUOxJJJ7NnS6UgjiYm5fC7FPjVEJmlJ9Xkm8ezZEtVhyBWEcHKUjowlgSpRLKgHKS5ZKxOTpBRDnZytnr+vONnqbFVBElaUpItdrjaznv+4OGXNVZ6S6zaxuGqNODEYjVimKlKJOIGRHpXFhurZZtd7icQahCsnm68FCCM957riEqhnMicSQG3dN5d/lSwo31PSxyMtToSkEbAIR8ChQCKTpbt4FsXmBRyGSGZVn2XiHNjXeydSvh9TP1eQTKBh0HU9D1f92nK/TA3008Wr25EFPCOqvjxfdThmvAQG6VESIlLBVAnsMk0lP3qS2gqyXP2e5R8XzzoiCIEWVYORsd4zqc+Den8FVEmSiVJ4zEk9KnJ+7rrYpef2ZzmOoZA1oT7nVO+vJdMxSvt0DpKZpUWAR3fNV+N3bHXHPO/xaf7LAXP/EsfRtGQaGiYiK2CJCJbxMcZgAV5L5PpsCJz1aqlus7ws8pFtbTVgnxJ3fwxQnnb+xPbP9jsZZvPz7bR8v4plwjIz4dHKsFDOTUpkJBIwmrEUFkhpsAKqJRKFhqSOzB7PxGC3GBw+R67DDkeJ8JNxBAOtGchY7t2WWTuMJK71Aw2ZwXYcpCPGN2ybB9p8jwi44wo/JTbHA1fNnnXzgVYTR/OG/cNfsQoNk1mzwqFq2Hdrbo8T0VsijruNw/rId6uOucm8RLC25eiuOUjPIPCbsCf2ievDHa9S5sHccL/O7FhxHQNfSqJnyxjh+5RIoSW0Lfd9wwffM8dXbOaJh3yN14mhMQXY6kwOwnf5Je/0hvt0zWBbfJrQaOgIbOPMXScEUd51W+Lccz39RAhb3m1ekCwMRK6YCAh732FSJGTPVXxgaFpUAsk4MoATfDww5GIsU75iZAsuc5QdKXds2JFxeJvo5Mij+5JG7xG+xOeJRIPkTKex8DnS4FPgaNZkFYJ4FCmpOhyOfTX5uTqtOs+fD6U61edz9+mYfPur9frESDFjMtiYebd6yUNzgxUtYAhDrkBaERQHlSdDLEKikcB0kmzAKViVBCewtsg+yudJXM1OLDZEMaJ0HMiqBGnrsxWObIvtUcVpppWJmbY+9sw23/NgXrCAiAXMWImsZCCorwFBPT8JoN0Z7JyCgcyMqw53+ftil4QTUCHV8yl646JwUxKWIB1oJgskVhVcCJZScf/z5IicjucJldXLFUhcAs6FhH0miXlyLE73DAmn/XoJFBgt5SjSIqroAqa0LYGUmPPxOYOufMoELedQIOopQIcKoCKGREMgYQh0F9cYK5jRen7Ly2jPx6tzKGhHy4iqoihZDAMNMxX4qJzn0mleBZJdfGpzQYik+vsyN8tPrWBeJaL4CtYX/7bcd6WVkYaJkQ0tj8wUGYFqU5/b8nyeEy3L3PIX28QLgHe+3vMczPXOWyyK1cjrdMcmBoyzpUvCLzh+NYfPxijQDXBkQ3k4H3vLlok0c0bhzUe2fbafZgxKloUV4xP7LBPhY6lVeMq0fYwl/Nz2cAaVly/7s68/vfCKYpl1qh8WgLYMrwGjFAEuFsXgNeEZSvSnuURfCAEPacSKIxnDY3PFi/mOgRUqEIxj0B6JgYxwxQNBPVs58vX0B/7Q/jXoyL3cksSXwol5x3a44cW9QNdzM3yP9DD3hp/cV7yVLwmxYxsCyR7pJEMwjH7FXd8yOksw8CoeeGH20ChHPDu7phkSvZ0wfs2VT6x9SVEYn2hkYMVIaFfsxXFE+X4z44NnHV4ghwO223Nz7JhuBbWGI4aJLa8PDTYpSRuieL7Nv2dKFqbEcdMQ8ezyFV/sP7CaJthabsOENBNNNuzdim+3LxmcQ82MyQZLwtgJwdFxLEyMGfB25CgeMYboYZc3GJN4o28Z8oad2aJiUMk0YWY2PZPpsZq4SXcYESyJWQRYM0tLUphN0RUliYzaAZjKHK4AACAASURBVIloir5mZFMZoBaqY5y1qU5NSR+Nfisr8if2zVWJ9E3/xzf8b3BYZxDfMa47RuOJ0pKIiLZncERlR08MQrn/Fi1pN5UTI3ayeZpoJDIr9TkZYAJ1JKkpysqGIUJGOOqqSDgWZ6wLALSUNGgsrlMDIhkQDuaKcLKncnEKhU1UgXCyzZ5ik5RijxcGhwpMtPw8MSgVyC1Mni5ZEsHKQMJVBtCBFCazkchMBl1VACMkLubwiaGKT4DjXJnELCXJ6GQCfHkfKmt99jFLkL0wW/XeS6r3FNBMIxOiiSieeMoIKa1MRByekUGW+7IcJ9XD2zPoWhhDzZwYS1nA7pkB63TAMzOyZmG4TmCqSmWeApkKik9AvwCeiaL1LmHDQnosz2fxdcs51/PQmlqWcAZ5LEBu8XupgtASmBdmL5zvoZo6jxXR8s0HVkQ8s2zRmlY/Fw0u96Ey0GRO4PXki+V0jcJcnqmEem/yeW6Ra1ADoopj5GZ6QLnB3f7NL8rKwa9g7mdDp7lEeWGEZv2Jrc5Ivzy8cDGxV5ydVMnRn6hzcWRVYIKarvr08T/XQ+1jQO5z43n4uDCJz4HfxxgRAVy9tiXiWpiVjBA5SsODbqs2JCOqrPJINIphJmlD0kTOFoyyN+tSqauw0h3JNGg0HLQna0N2lp223KvwMr2nyYkNR1Yp8F63zHaLVSHbCXUOxdDYCC7SrHZYPzLjWM8zbr5nb9Z09wf2a0+2kX275o4XjHaFN7sS37oRNwVudeB1CvzoQFuLSSPbwTObzOvpDvnwgJGZ7faW++YGXSnGNzSjZxsVOY7Mccc27lnHK+7pCI2BLIzGk9Xj/YRnZB2KjtKKsDaZFCOrmAlxAm1g6rjWR1w+0A6R769uaMfMC/OeyTpiNNz1V6z1iJjIKu8IvKC3E9fpyMG1BGnZmSsG5zFYruU9JOUdX3Bvb8gYNNqSbsNCFDomRA3ZNIjJvOdVgfY64WzCE2jEcRPesgqP/Gh/w2Q6RuvJNBy1O0XKxSBGEq60Q5CEEMnM5Fpwc34PLoFc4qPM3fKp8f8svZr+EoZ1hvWtR9uGJhf+JumqJg6XFOTiFBfGpjIc5JqqWlJ/Y5mLKFYCaHFe57RUpKmAbDwxdosOMhRG7sRGceH8YQkyA5QgCUNDZJA1Z2da9i1p1VpkVoHBiVU72SV3cdwFbF4GCRUgnSQsC5C5YHvU4CQTL9K28+l6uDju4uQXLWE6bWO0FMhpZXEcBkNx9lmVVmayJrL4wthVsOCZqlbPc2LVqj7LMNFKotUjCMzagLQFfFA0a4Vru2C5yg2vj/aSzaKCjFQBbLFLTwATgFqyCAdd17mzALiFlcpYzaTK4nFiJZf7X5/TCcCb6jns0++pNqIA2SVzpT+/htP5L2CvMqqn7ZZuDhdzQRJLGraRhChkiTRoZQafBZQnP3dJtizzd5kEEUSqejGTTyThOS3uKnPaSEJq6jphufevkPeQcJ/Mu/2541dr+Gx0rcW0AeO7mg56DrgWBA+IIBJpGFnlkdF4hlN+H86GchkN52h3iSKfP4JPALSTMZGL/yzR5eVnf2wsG3+MxTvn+cu4vPbK1Gm4MMhKI4rRXFM4y/UKwTYoEOlJIggN0TpEYyGrdcaRMKIE7xhTx6gtMRvWOuEIROmI2fM4X/FP+d8Qk6exAw0Ne9ngbYs5em6zMmx69ivBT29YjSMbEmN4SUieK7PjFYl5nvhw5cEeGQg0U0I65ToOfB3f8TrdMbuOb1Fs+IntrOACD23iaDLfOMtXx8D1e8ObNJFeJf4/c81VOvCYrlm9ncA94poRN3/grw933Oc7mk3H6HoOzjLPHZNuyRLZGYvDkX3id9OP3Ox2PG569nbLTMZ5z72/RvuWtd1jzMh+1RNDV9g2ikx5lJaknu/tb+g0ERAUoUkBl4UuBTo9kJxB0sjevcLnAqxCNgRnuY0Ddg50MpJNS88AduK3+e+4l1dMseFet/RypNeBYHpW7Bm1Y7AbVBTB4fWIkaXYR86RsZhS9ECLpQjwy1RZ5tjzufh5hs7l9MlX5dcBMc347S2HODGpY5YlnbromjIQzsxUfaW9RqIsgMlgSIWrk0iiIUlNeZ3AVM+8pF51aYu0ONjKrpwKJxY2aGFjypdqFe9nhbGye04ycdGLIQhC1PbC2cOZzVp0YYsGjPodpjJs8CRNdwIF1Z1WsJEohTrxZAeXOVn1XMtYtGxqSiCPYmvA0nGoqdkCKgQhkzEqeBlI0uJIWLr6TYXN8TJintzDxLnopOzvOJavJ5BkjUOxMgFKT2DLOx61NLwd2HICubJkYRbwsqRbC2mQVUEqmKTnDNaFUZfikjOwXHhRo6kAOZV6TxafZC6uY0lFLp9dpmDz032Wz/WcUqYSBOVeRvQixeol0jIwakOkK89I7MXxzt+rRBTBiGJw9QqWObQUN8CZgTMXn18CugX4C5G+zK8n22VWBLxOHKUl4ch4GvZ0ZqRhD21LiN/T5K9/1mj/v2T8CuaejZuuwfo9jrEg95Nw9nIsD95RkgkOZxNWqS/gMmED5+jyGdN1cnSXx81nI3QacjHRLv62nMflf//oeMa8/SxI/hgzt4wSATsmonblGlU4YnFc45nJ6msFV0akpU17jnZV4y5LrHo6Q2nCvM13vAlvycC9+YIujezsmkdWTLbjKuxLl3bxPLBlSg09E5nIhj2rONCTuZaBsW/Y2B3jyjKPDn905DnjjNKlzE/uFVf+BzZM/JB77tYtMWd8gjeHB97sDtzmkR/bnnV3YG6Ul3HPXm5oxwYV+OHFLWNveNUExuSZuSKFFc0YMCLcru4xc1lmZ9IGmWau5wN3tx2HlWd0LUYznonODDyaK5p0YBVm/vq4I/oDv5v/E+/zKx7chv2mIcuG3DSMGN6E94jskXHgsf+aGBuSM3hVLBOT2SBZEY1swg+887c8ND0zLRuOoJ7B3KK5OE5VIQkkUY6+4UXa0aUJSSOpjxz9lh/4DapKn/Y4WbHOO7KxNGmHaGLvb7AmMNHj9UgWg9OZKFtODIHa+muuPMmiB/0UM/3H5/HV8YDN/9VXgPgXOfZz5P+9m5BeCcEz0RVN0KlaD1CDEVuLkEwFdeB0DyR8BXQBg4qBCnSACpIWkA5FdpFA5vKT9vTMz2ndy7TewmQ1nFizRd9U04FRK7tTMwhPAZbjslDhaWpeT/ZSNKGnbRYNVP0OqQHrwu6UCzsf/3SeDWc2LtTzrgykZBpm5osCjLDo6uq5KIAKpSQo1DzNzEiDr0dEJlRtAVciFSxXEKwFBEeUo6wxaopcpQIL1eKFojge9U0VzywZoeV6q37sdN0lm2QpOkoruRSILNW4p+rby8KSjIhida6BeCm6iChBeuJyT06axHOAsLC0BTRJeRYXQPXkIyVjmFAp2uZyXmfGsMzcWLIyIogqMw4rEJUzu3r60vTkfII6hAgyYrQhnXTpi89e2Dcuzstw9r9LMciF3ZF43k/KHjOGREtSh60a0pmOPdc8dNdgIyllcg6/grl/zrFtHJv8rmo2/njon1G8TkSxROkv9ilR688d1sX/n+Cl+gKeRJsXer2PgrUlNXIJEj/Gtl2OZZv6uzz76BQ5LcdeIsVypWipaC3VRgrSkCml5Ss54PIDncAqPvCheUEwvjJ2dX8SXgKrvOc6vWWtA6qWVhNrPTBJR5dHGpQ7sTQyY/NcAJ5cYyXxV/F7Xk8fmEwLNFwPyu/MH/jRbPlgN3xrXzDR8T5NxI3lOgbmtCPmAf8oaCtcmQe+jjPz7Ahhxcv7Iy+PhnbTs9IjTUo8ptfstYdjx9FtGLcQTGDTb5ivhZvYsnVrxtxj8bx43PO748T96pZ/co9MaaLRATsaDmmNzo6d3JTzVsN1HBlsaVswuA1/b4Sj27HLDY92TSsDs/fVkQq9HrGMPHBD5goZhF4CooEgHRlDqxEjGTWJb5oveGCNIBgyI1dcpTs6d+Qoq+IKonJwLwnS8JYe62YsGecmZtvSyJF72XKQLVYjO3PDLI7ROIx1tOlItA3rPDAZBRVEMmuOjNRKOqgOagEFBtUlin4+dz82Xz8+ZucJF/WAv47zOMbEpDMp75iaF1X+sLzTlxWMmSRFx9TJwKgdQRucKI5D0RXpqrbMWGQllYWRC7BwSt0uACydHPDZES6B5+JySqrKkwhLxeIpTTmD1KIB4AT8hTPTthxySevW4xsCFsEzoWILGFVPWqpwn4CVhQlSloKuAigyKlJ72cWLbZd5ep6rqYSvgGIloZRed4nlXEs7lUYyGcdBNxhSgaIaaBmZJVdmSc73j8r+nZgmS1IhncT3gCqC0MnIRItIJOKJurTVqCBVnr9HZf+scnonjSQcM5EiW3nqHxYGVaGCqI3syVh2XGHJxCdZI4NI6W8AtgYLrtY5XB5bn56TRlrJpGrTUtVVntkyAbEkVQy56nj7es+WgOGiCleVUtizsL0zhomgm4sApl4ThWlsZMeg24uABZb0OyeW8/K2XOKEIgMwGJCxZieUXOfja/meV/lbYnPFNE1cXf+yweivYO7ZaNsVPrpTGf/PmTM5vxxaQFeWzF43VR+yRCf5+aHr+AjgUupLu+g6lqqxBHxMt3epHXj+tz8G6D43FqB5WeW1GC/FyshBtxeRsNSCjhINN2RWeSBLh2aLiqHTAZcDCuztDa0GvEngIYSeb8zvkaTMqUOdZbYtagKNBGzOdAwk6ZEYGU1PjA2TyczeEI3hdfyJ9fif2Pd/w86UCss+TOzaBmMmDnZCh5f0nmJ47u5pVh+IuefBb8itsF/N3HUP/C4rL80KJZJjYjS3mIPHdC3iDXPXcmcC6zW8djfsRdkcwIfIC+fJLxrk+pq74QYz/MTgHXH7kn274T0bUrQYUcRYdr4le4/NQnLKh+aKR7NiEmFoemJydPbAjBCNQY8OHddMbouNHnpHy56bNCAh8+CuGF1PoMFoZMYSfEMUgwE2+R4nEzuu2OtVSVNGIXmHmEyWhrtmw2xXbPWOWTrWes8784qJFcnDkTWuJIAxpLLsD5nW7GqJi/LADUrEaqiVdjWdIqXiuTAAcC6i+RSg+9wcjkSBv3rziy9l+hcxVs6Sw8gUDLMpbEhJW1bWCigFCgUEqRqOUlJw3iQ6HZjoSpPUU3Wnx2pARAgVpACV2SppKS9TdflFISbVbpRvvGTUKpOhispleqvMlbwwfacU6aKDWhZ9X7RJi+TFnM7HUoIJlyN72dZWOVJ7yNXzUOWUhVgAVGWKDEpWh5FYWoicqv7rtVbnv1yDwWBlItKST3O7biNF4RdFCdqylj038p5SHlaCGpGEan9h/+EEuE9M05IGXILtJQUJUR07NpQGUd1FZqeye5ds5glwFUbMkog1/ZyxDAv5cPJxBfw7RlQFESXSkGWFUVixw0nRuq0EjrpGJFNUgplEQ1ZPKwNGApGGwPnelce3yI3KdyY1eEkYPRKlJ+pU50DxRQbFSCwFKKdrUxxKXNo0yjJPlFNbE5Ea+tWWN1Dnba5/zfSU1SkyEzO2zM2l88QJfC7nnc627UkVq1LCgbpuuWa8zHgCh7RFhy1ugNa9+kVZOfgVzP1szKFlfW9Kw8Sf3Z5nLJsAeA7c8KTQAT6DqZ5wz2W/J2nVi9LuTx7jWZr1k3/7c0c1FqfUQpn0ifbiJS+GJanFyUxD5jrd49PEO/8VTmYe5YYGg7UTjQZu8h3elu7ghsQkK0a7oo2BbA2d7Nim0m445IjTIlgd8cS2IdBwr9e8jgNY2MYHDs7xKCv6+ci6acjBELNl8EIbRqYm452wmgPHrmMjni1C1AeCtegErgnY6Ek5sjYfGOl4137BgQ34SMbwkh1pcKz2R4K95WHa4VctX2bH9TEgCO9c5G/bR965ls3WsDLCTX5PP8986BpC15Cc4OOMyUo7G3Jao80eVjtCb3n0G0Rnoli2MXIdE/e+I9ATzcwqzMxiMCnQpompc9gmczVOfDn9wI/9K4K2HGSLsRFsWbg+5pZ13mN1RKwy2Z7QWDCZmZ4IBNsSNBC1RXKk11Dclc1ksagqiYZS7+jJKJYHTEhseGBwW7wOBDxOElkMejLe1PTT4swvG6N+CtDpRdwiJyDy4njPX4Xv+J/+3b//Beb6X97YNI7//svX/H275sv9A4/9hge9ZumB1hGZKDrXprJRVufS70sNe9mWghWZETUkAdVMFkFr+s4y0RAI2BL0qiWLpdcDESXLmkaL++z0yETHUVac7dtESdMtDEhNuaoFCRiELBMnEHKqGB0Lg3RqdrxkDsrcySr0HGjyxM5uQQTVTCdHJgynpsZcZkBSWdlBDVksSG36WsFGYQ8zDUo8FS0oVkvDDl2axFYdoFGtoni3dKsjSuRRbyht5S1ZHE4i9rKQAkfRMcJJhK+V5Tz5gQWoLPfEXRQVLAwjPE0XPn/HIo0mVrJjZEOojYMdobY0ebq/UUNGyzerYiQTSxkUqhEjHUnLsbWyXYkK+CUTtMFTir6UGlRUonNZHvNkI2rlcaKtjeWX1C+gpVdcXgLBi4yRZaaXPYFVCSbUVT0inIsayjobS/Xr6SSI9BxwRDxKkomsHSIH5oWlQ8r9pgYOuvQQvNRWLsz3Mq9KS5uslkkcd7xkmv9ALxmX/lyJyafHr2Du2RhDpF0/csWRR674mRD7Z+BKKIUNgfKinfPn53H54C6LIhbQtEyqZSwl/p+iYT/Hvv25rNzHjrNEHImGsWo1tL6wBpjwJFqNSFbu5RYxyogj167kg3SsiUQSBo9TxamiGfayAhxNAJJFbU9yDdv4npU6erOnt0eiCil39DFwNQ3supvSoqAV+nxH1sRMy2qaCHNm1A2rZDm0G67ye6a+48G2XDeJ1XHAhiv6KfCCyDuz5tBaNEzs7A4DPNoWSRMbMu/8FRIFSUemac27boO6BpN/RKRD1XEvjqtw5Da9ZXPs+f0apjbwQu4YaXlvXiPNWOJSzfSpVKNdDQF0R9MdWPEAOfKN+6rAnwRf779nzUzC4lR5NFuwkckoyZVVM7ZhT6TlMb7im/VvaHVPTA2+z2wYmHPkZXxLH2bayobcW4MgNDazCTtG7xBtOcqa5CNzFLqsNEFpTYY8c/RXdd2FTBtGjMk4Ike74q031alvQCg6FqU6fs9Sru8YyWIxhGLQTyz2p+Y4ICPEDOM9tzrz+2//gf8xHflf/7f/nd9++dtfaK7/5Y1X2xv+3eYV//fbv2OY/kBqfl96NNIzslRBloo7K5EgPUZnREwVxCvhVLykLDo3pQPJJO0ZsQhaAeEeVY8jgHiU0hPO6EBZC2EmaEOQRGk5sRR/CU9Sb5oLkHsiQC+sjNVIxxGnZRmrSRYZy7m6XsWX/pQ20tdlExMW1YSeuvrXQJmljYQln3Rui46qAF9HCSpbjVgJzLRELbZtKx+wWtiYvdyQtMGS8TrQ5AOT3aKiDLqlJTKJZ82epKUEoiz0uKTpKmu6pCKf6EyXTAkVQGa8BJJ4pictsS5t/xI4LfvaizhpxjIWeRANjsh06rRgOK82VPZVSbQMRN0AhoiQxRK1pxFhqvb+KagRygovAUPRwt3qngfZMlAYr0RgzcREroUCgiFgxJA10snEQT3nFPwCepfnVJjTFXs6RlCDMtV6Z8+BdfGhGjCEUmGsC1hNUPljKvM44Yi0jDTPGlZXO3bKUu2w0tDpngPXLJIDQ23AzcL8ZpwWuUCZSZFDd820m9Bw/GOv8H/2+BXMPRvGzuy7RWz5rD3CEwx1OXEXdB4rYhfOFVbLfku1zyXzsIiCLwW6cK4E+hxg+xwD96eAvT9l/7qNSlnK66TjWyIjR2BAksXmgdmt6dhhjTBnaMyRqC2z9Bjx3Obv6dPEdbrHaUBTX0pIkiFJg86GnokVI+pKasiZmc4+MqsyOcdP7hWrOGM1YObEq+OOK2bupgOatxy1QbLw6m7HP7664r79DTQW3xi6w3uOxtD5Ozare96tviK3BjNSUsVxhZ0zshbwM/Nkuc4/sA0PrIzy2iRIG2Y98Ogcud2ymb5jdLds4zd0MrDKMxpbrszAF/qWnV3zPl3xehaS3DCuHG565OBf8mAtIobfxbe8664Zm1K6/yLvYfCY+2uCJMb1iq2JjG2m8QcmtyJHeNQNmjzeZVI3MdgOiT2jb7Ap8DK+5eh7vtIfeZSrUpnb3CImYXUg5YYkHQ6LVAPudcQYQ5v3jLYnGodmxZG4jY8EaVjNE+oSycDObonc1GpHi9cJxJJOQK0CAW2JsgZV8tI9fWHnTq0Lfj53LfAy3fM//O3/w//89Uv+/f/xf35m3v46lqHzTHd/xzbes+dviOKqlqowByKlOCCpRU4FDJZZLVa0pJuq/VIcpea0pNe1AiQniayQ1OOl1AtGLEHL4uV7PIYVLQNJBDSxJjNLwqKllcmTylRDSfkt4CbXtG3JDDgJxSmqI0tZJuok9K/pxUxmkDVeA0gkaEvEIOKLXV1sa21afMo+1P5xTwvWCsPUSCrr12qPIeGkrI3aAr0cIYNX5V6umDBYMeztDQZXdWNawyBDpKmtTkytZQ2sZWTQLVlmSp+/BRyUxcsMA1EtnonmlAoWSnlGYD61BlnepeXdol6jgkxn1k4dMyvGGlJZGVlXgLZfGK2TPxMCHSoeS6CVI+DRGqCVvpEN59Tz8u4WXaVDQQKqHbOUgkAvuSyxRgcyYEkFxqkn0yIyl04GdJxTmQsJYi+uKeE5nkrzPKnO3cRIX5nmGRC26S0He0M6tcopbJ7VXLV0JQNUeiwshTnnNO65bQq0OLxOvJR7rMJIWWjAokxwBp1aFvSapOGoK7I1TOLYcyD7P62f5n/O+BXMPRuHu+8ItqEjsmPiskHuU3y0vPCXacelpHoRZNpn+y0TcjEil7qNi4OfIofPPZ7PAbo/h527ZAwXKnpxxpFOpxrLWJ6IQDEEA2p6nCQG2xWu0Uh9Sad6l5TB9Bg1fDANzszMzoNO3PkbDIZGAxIDKXas7J7b/BOd29GaWyw/MaQ1M1d4syUprDF8MSZ6AZk6vr3+gjT33NsrjteOQ9MxtoZGZnIwhDBxFb9n072Fbk/rb1iJpZENs9wQpiOjwvvG4+eBFYY3jx/opiNZbhivEz/6DXiP5HssgX1reT1G+hxpmj1fuAc0NhyD46f1inHasPeeH/MVe9lwSC1j0zP6nps0ELyDubQv2M4DrUkMdMzq+ccemqRMDYiLZFfA00G3ZAeza5ncDCZjNRKt42ihmSesUw7tNWjkQM/ObHjnbzFktumePu8ZWXPIPUE8B9thKY4CiSQrJBFGU/QminCUhk088NfHf8B1M3/b/WsMcJSmOhjDILXq8RSM1IpAocznk3B++fl8ul7+p8SzXRxpRsVdb/6Mef3f5tAQ+GmM/MPV73i0txik9oOLRNraGa4Am7g0cT4BgYFSKZmw4qslUnrdE6RjUl8cuXoyuaz1qnXJNnFESno9oiTxRWOHlhSWZrJ4AloD3sUeLhqxRaeWaCozFTSQ8WQckzacOvCrYGRCELJEVEtj20Bpi4RCxF0sH7ekwaqtOznrwvwYyTgm5ot1uVVNWQeaRBJTdYcWK7DXHstMIzOzeoqCriXJjKD03INaNjxSev0ZBumZpcVTQEbLI6KutAJCmLWrfdsMMGPrShqGGS912SrtiGhpN6NnFu8UOC3slSqNTBfr7xbAJRIxmomyYkmcl5a7M4ZNYc61dGrQUzWxgLQYnQkYGgm1bUk6fzfAqSipPKNIAm1xDKgYrE5E3RQ9Ig17fQEIDXs2aU+kI7mlhZXDyUjGlUb7utiLWtygliArUCHJRKOxrDYhO8Zl9SYRrB4J7qaAw5MMKtUAJXHUbb2GpZfe5VwpkgArlKwHK3o5ksVypy8p+Q5TubuMEVdZ5QI2jVYNqBiCtuxWntgbcrusFfzLjV/B3LPx/v233NjHOj/tM0fzfFyyCIay4PNls8rLsUSRStFFLOmFC53dk+MuejXlCaD87PgcI/d8LGBwyfGbi91r1+3TsTIjG4ozvoxWSqRUOrIblsWFLdDLPSlbHEqWtlLzphpZYZv37LIhWXA2ouKwIXBoW64082g3vMl/T7LFBe15QWgN0TkeUk87W17NB9LoGPyavd/y3t+wCuAlcSt79NjxT33HbCwv5QPX4T27tCaHjHEGbMDYgWDW0DRcP/T87bbhMQtTp1zFe2y74qUEbBPZemGYf0J1y3SYWMvAsVmD7nDtI2l9TyMtKQk7/5oPGA5Nj4SZJD3qO0QtmjtscngpiwaZlDk6y715TUiWTkesz8ya2TWOlSZSBEOPEy1xo1p8yHQceOx6BttjdSytQWwiaIMZDRhLlI6paRlMh0hmFXds88Awb7nv35Cy4KzShTtaHwgYjE1oNuQsZNvj5IGj3dAz8O3NF3y9/4bb/JaQhWC+ojQ/nsja4mtlmSWTicx6exG5LwU+GZblfD45Mm0e6WJJvdwd3v2Jc/vXId7z42R4322YxDNJiyrYPDFLSwE3lX05ZemKljGpx5NpJCOMDBRGNeGwesTJhpl4Ah2+piBH2po8BLSAH9RTVKcBy0AUS6sDWQxWDsy0GHLROMnSXL0cwhGwGvFiOagtK0mc7E8BohmL0dI7LJFomErVp1pElnQXFBsaT1mSUneh5EVvJ0omlyULKzhpSETJJHWoVPumCmIxVVPcMBPFM7E66ekm2hrAZiItvRxI6lnLwETLTFclK1JXzRF69mRtiVhanUCUVjN71lWPJ4wa6ZhxMmHUca7svejZ9qTqcuklZ0EDVgJJm+qBGoRUlZOOpIlODhRetKyv3clA1MKALoDVScLpwEve8R1fFVB+eq8jN9yBKkEaDrVnnUi52qgWS8KScAjhVOlsmLVHbIPXI0kbehk46oqo0MuIY+AoDYmquzy1kylaxagOJzMwc+SKXK5wmQAAIABJREFUs0/LqDQcVWtj9AIxy3lAXAAxy32EZcWIk9yJjsxAh+L4AFXpuGNNliJVyGop64QsgLq8BwfZVhyREYHJNEjf4pvPLQrw541fwdyzMXw48KF5Wapufra00MfYsEv92+KwLrddhN4LU5dpOJLwpGV5mCfjsqO5PAOUnwNqn0ubPt/m8jgXzOISYZ2W8jk3+lwC9/M409CLJNVzxEpg0A0Hrkhi6BlxOmHEcdQtYsvyODcpk1zmyDXBwKQt2EBWYW4aFIemlm46kB00ZuJOX/FFvOORzKsw82WcaFzgJ/+CwRT9iOlKp/qUI17v+O1wx1274nb/gXaYyUSSeeRDuiGOnuw2xMOKLhzYe4eNHtkadrZn9j1WN6SrG16MHxizp/txIGvEaaS7HVhh6fieORhSTEQRgggxwdE03PmGzkz0SRnV42iIjSI50kTPy+knXnLHKs38wA2xabEhc5CO0AvBGKaUOIrDJaEZYTtFVvmeH/oVQycYM2OLSA2bMq/itxzaDZPZMmtTvteNdEYxMROz8I4vOLQtM4arPDDpxI084HLAR3B25E5fEjLMCEYENUq2hvf2BXZ9ZPJronRcySMH7TGaCbSUBJ4laimWOLNxNV2BlLklz83Ps/mtltF09PlIkwf24ZdPTfylDjEw+C2HvicZRYk4mUvKjEypIqwO6+SQAcqSfFq3XRaoL+tpCo4rIhlBsNU2JDEoHlFDIwM9gSiOkRWxFgUIhokVopGOiaP2tBLxemQjOwZaHtkSqP0J1dYitNKSQ08Bcjo5xyUQzRfKkVk9ZaGrXKonVXGSiLUC1kriBT+Rscz4co606EkvVpjClkTWhJVMliX1uGjsMhEpSkDtq62zF8vUKQ1D4UGlgNAFRIRTdawFtUVzRWlbYqU0BilMmGOmrNJwWktVigJw0oZwWuVgeW5LhasijBSoWthMqevuLu9gJ4eSelaPIWHEkGqlastA6VQnNDoAmYk1o3pEDB0H7nnNe31BxJNOgZnS6sSGOwTDo25B1tW1OFSPNdgvbJ/RmQKwzenaJnWI8WRVnEbeyPfMWvr2jVzVoorzdZzAa2Vqg7an9jDls/IiFC1g1WFq8cKeUGfUUtFaM2tPetWFk+3ywFqPHOkI2uIkIhJKocbCcOMRlZqCXmRVyw85FSR3SfD2z8mefX78CuZ+Njo0Gw5sebIW2yk9+rFRe9ycXmbK/6kP9FQunhBGkrZFQwL8nJmwF8ZqmViLdu9zgO1PmRyfuo5n4O40B4uqRTWXUvA60UVT7U9UtBWq4GSH1RItJRTVBiupRs7CihEjI2sGfI40ORTNjRMylkYnbtM7HuxLjA2oZmZruZff8I5XzNpjTOZKJtow0wye6+mRTfvIXq7prLJyj6g3/KvhG74cEv/QfIFY5VUc+J18w5ert7wdbnlnX3F8vAIvGIn07LlJ7zD+GlYOR4czYMQSfYP6kd2+I8WJftzTzIZghdRZjq5DOiGuPCs1bLsGSQ3oSEvkhc7E0NBJ4ibPPObI7XzkzfgDt4PyRv6R9Ytv+JEv+M7dMtATfSIYzzqOCDPXusfnRNKGnBscM1f5Ld1BGGNi13m+Wf0epxlPJPgVMXuyiVwd91y7e+bUcMh9SbHZlgcagngGt2LWlo4BybkC9lxaiSGs7MBomwLosDxIiXoHWxzYRh9RlImvCLm0OQHBISBFYH3WnwqNhLK25xPT84l5KRBwDK3DGOgjv44/ZcSZ+f0faHrDF4/f0nUr7uSGJHAQj9a0YkmElmawemphW97xiRVloxJUFqDiSjNfKY6uMC0ZJeAoc6cAeCGSCuux2D+UtT7wKC8YRMl4hD2NJDo94AjsdMMpSBQ9gUOBWkntSdpyToctuuTLdh2FJXkwL4qej7KMHFjKiqqRrJ5XfE/PzA/6FfdyzSj1ehdOTQNNgVNArCsjnCtDi/Kt2P0ZwTMTxaE1kMm4yv0II6X/aKdH1swEDQyyKTrdU9qvvF9RHSIBp6GmrDsuly4zZGZslTUsOi7h3Bi4cHFGIEpZaspJAZKlQXCiIWNwwEiUlqCCE8dOy/NymrB1PdbShzDhNWJUa+FGqSh2HCnr1Y4VKmX2coPXEggs52E0csUjAyuStPUYiZnxXJCw+JaqjRR1DLrFScDgMacqXrn4V6+/sqVLpb1FyRrJ1ee2RHrZM7DBSqAhkHClDYpGnDwy6qroDxEaTSQMUfq6zFlJ1z9wjZdAy0xSg2U+s8mUSl4rqVT2as2oVW2mlZGX3PHb+SdWV1/+su97Hb+CuWfDv7jmp/GmVhl9ggn4WTZTOK3ReooWlm2XiphC+5aYbxGHX2ro5MnhztGyfPz7TifyyZP6xLiIak4/nxV6AGBwKC0zQSDVxdSdJq70jg/cgvQsy+es84HOTLXSFcb6wpVq17EYezJZDC/5lg0HPshLegayrtjGAxs9EOIKdYaI4R/97+njgZ1csQkH1makPyS6uOe3jxuku0dlQNsVa7Pn3+4njs7xKn+gmw3/JnzHnb/mNh1oFbroeH300M3Y4chuc0uTe8RF/hDfcL2aeKUf0PA123wguETKlncqpKuWNrW8PhzJByEI3L/0GBMRb1gHIeUNsmtZy4pXUZFZwd6xy2tM2nE0ESctWCW2hqN9ZJcM6nqIZSklm2CUFY2MbMOAtwe6NLOJI/fuhmPumGRg8pF/Fb/jzq6J5pp1GhACMbcIA94LJgd2fYfXllu9QwXuzIqM4a39ApNnJMM6HVmbA5BI2WPkQMoGFeFgr0oPLQxX3DGwwejE6HqyGo7SV8BfU+7VqGXJnNcprq1IFo2UWND22Xz8+FAMo2sJFvyvPYL/tJFmQki80YHX5idyvmV2hnf6qhYOlObOV/rATM9Ei17aGxJ6YpCq45SSqmtkQLVBKytnJZK1JcmEEDEiOB2ZWHOSbtRts1gcmVZnVAINkayZA1cc5Qo5pbsiFkFkYVMcpibtS3BbJ8Kp/9uSdi2sWUnkLaL8wh05jVgpacqMZZAN6BEo1bOXWqqSEjNEPP8/e+/SK92S5nf9nrisW1723u/1XKqqq9ttt9oSLYPKAuQJIzAD5BkTy2KC/BWwBBITBgjxCTxBZoIYMGEEMkiWGDBwYwuEaGi3y+7qqjrnve1bZq5rRDwMIlbu/V7qVNmcplulE2dw9ps7M/fKtVZGPPF//pekq99YftekUDHRSDbYnST78SmWWHh3OZmz5j3lpZhciErWE2d/gLb8XojiSUxUTPncI0VVnDgnCRVOoV0/1eNAd5lZOV6GnC/eSI+gVJpQlJEWIzOzOioGGgkcdC1aAlBTccKK0oWR2XUkHEGzgXtSodeWJJ4hdQTbsKjHkoiacJKti7Ihbz4nmYAT6NI9venKWczitoaFXDbma2cIjNpRs1DLDZPWiGbkd9YazsjcI+6jBoxkvm7m9gI6k617EzWBxMKiFQGLSiLgECyV9FQEah3Lsw1GPI4Br47AHb1cAlowyFR6bDln1ZeZcSrXMBeUawdu5qHrlu+IbTjR9QOxilj7nQDiT320u5dMwx/wUBh9okB6r+1ZkLOzgvWxweBK+H58mtfQ+jIBPUbh1lHg4U//vU+Mj+q4X7Q4Pl44Hz/nUzeWZVEB2eQ9nQhX3LFoVg3lfXxR40pkpGGmwUmGqjuOJHXs5cgL+SkxLtybz5hpuDVP8RrzESSwomziwDxv2NhjjpiyFUfZM/oNd/KEUHe48IZL/oTny8SWO+b6SAweE2CgJlpDpT2NLuAM3buE+sRub7CponVH/OYttzyj8hWtduxDoNU7FgnEsWHvAmJ+wmvr0cMEbsPVPHJta8Qm7l90PDmN+Hkm8gQzZZsQa0Z2egnLgfumIh3veDJkc9BdrGl21/y82nApgXc85UhDkMCxrvlMFg6yJ0WDBLBtRASG1vA0DDRxQUQZbUOykWNdsehT7ucNsckO56KBmY4kilqwZmHLkTf2dwhhwzu+5Pn8GlcFrs0FkYDB0qWJJi3YNNKbJwRnOHHBfr5hqQwDHUlKQqdaKj2BCEErjEQW9UBApUEl4xjp3KJ//P9cRMyrcvKTG5JPjax0Tibgvl2PzV/boeqI9wtd/4bfmn/Mq/RXQXP2qJ4LDJjY4pjQNa/1EUJay5ClS9qe5zNDFicYmbPIQTNC1Mip8KRaDIGJmuURAZ2ico44WrmmIXLQC0Y089p0JuDZc+AGh9NYzGiz2rOVIyM191zy2M7GMpLUlGJrRWse8cfOJySnEARs5ufJhpmuCAEicS0OdKXFGBYcOQsh5qgoyZhPLRNSMkqDGHq6Uv5WuaDjoSA9G/DiQBZmcdSalbGd3jCutiKSBVAeg2Ug0hSz78fihoSRiVZHTkhJUdHz51vRSS9jPjeaDZyzPWOkkpFBGzKgEM9t3Cgeo4oW4+eZFjTh7QiqSDE+jios1GgRTRhr8EREZipmTuTEhky6eeju5ISMhq/Nl2Q7koTX3LFKOKKYfJxEPNlcF3EMtMxU+HRAUsC7E7NseEBh12tek3RmdY5QbOlqKk6FVk5cplfcm6d4WejpmBEchqA5oaiw3khii+feBSA0nFiVw5M4co5tT+YzHkkmmzmb0oHKh7Re7wLCICA5hWRmy9PT13j5TZz79kuv74q5D8b28gIrD/Ewj6H3Ty88K3cB3ufYrZPJqs5aH3/8nHWnuYoQHr/0U0jbr8KLI++gecvMFchjouUve/1jtM6A1CVNMGvfeu3yxI2Q434MqnkSGGlIWBpmLBP7eGBjbtgQ6OTEP7O/wz1bRMDZyDtRNvGOQbds4pGX/Vt+Yn6IJsfgHV28ZzINR3E4Frbxhm24ZaN3LOq52y9gZ0Yx3FpDP9Uc5ktqP/JyPBFUuXCeLhwwp8h2qFjqHQdf8ZofkLYzzTwg9Uw87HDLgWDuOIaa1L7DThs2szItnnp+htsHOnOkxuMFrtsOlQqpD2wX5bPlDuuvuK2UMbWEiwPb+4GtNkwEKnvCecdbv0MNHEdP0j2naAnJMibPyVUsTrn3NW0UDBX1GPCysJlPDKZmdA0n06E2cnBdNmnVhllaBluxpedkNtQpoKI4ElfccscFs7W4FHES2S8Dk9ZsY8/L6RVDUzOI0EtNoObU1aSomVtDxCm5NSaZ0xkAUSlqQceksexu4WFaKZ5iq/pQVgNqfYRW/7IhLDiitbTVt2+0+es45gQ3lWOpPbUqTiNacli10CVEMuKRtMaqEs5u9+t8NVNpzXw2Rs2FlWXOLh54ajkS1ZelcDXTlYJfrPy2fEwbOZFU2HFi0hYvM0LkRE0ljqCGW66ABZGE18zpW2hyC3FFYs5txcSGExFbjqq4CLBSU/Tc3s0jd0Gigkp2bhvZZEPg9T4UxWhBmYW8cRVyTB73LNR4XcjWsguhGNSCUjHTykTU3IA8W01JEU3gWNRSyYiolmtQar2CJEYVRmpqWQqqlb8n6yrgSl7pC97wTp8xsMuf+YwACQstOX0hocXQ3Upk0B0LjgWPIat2EyC6YCWVJuaq+k1Etew44HUo0XwQxJKwufRVl/mQCrYUfI5svOxKGz0VtFdlIVLhyCY3RrIrZSqNalWLSmDSikoChoU7LkAMk2mxZsgziq6cxXWdMo/uB83pEyoEWhwBkZ6UlBRroqmz8ToVObwr5HxXLEFrjmxKfNuK0OVrluuxvB5mX79sbRKlyob5LDgmIpaRBscabfZgdAxKJTOiiTfuN7gelWmcqJu1O/HtjO+KuQ+GrTp+9/bH/J9f/vAh3uQbi6CV0/apXxWY/JOA2rqYPYL4P/n7D/7Up95LPnyC8pvDj/lx+6+UjNlvWgR/UZG6+srl9lnSmVSIurfSFCL1ghFwmkNaPBGT7XzJrZyKmiNHvSzTyEy2x90xU9HajlkqvFn4ky3ccsHFcuLe7glqkEXZmGPeHRnPPc/5525CO8tVuuam/ZyZ3AqMg+fZcMMonnGjtPPCvBvQdzVV2DDt7nnnn/AT84Kfb55xFQ68qRu25oATQ3vv+I27I0/8HYMXDr7Di8AiPB0D2yoQDJgKdvWBEDf8xukdd9bxYuqQZcNd6xhraNzIyRtwn1HrAaOW4Ec+N3e8tr8Ly8J19znHKU8aYQ5s9A1UDZVMbKJQs7DnHq0UM89cceBGt4QqZuTFCCEJN+5zks2cDsXnODMb+TL+MSpwl+6KijFyEU9cmHeIfMnBtkS94ml4zVU60hx6Dvs9ziQq6WnSyMl1511roycanbkxl4x0eOkxGrLRpnZl8QkIimpAxCEq5Y45EbjgITextI7e45j+ovt7odaB6jSz3T7/hvv4u7GOIIGogp0t2BpFOIUWYxM5gcBjUKxmX3/HRNBdWRhLm1FXjq9HNXcevExEGozOGEls9J6RFs9CL9tc2GtDzaEsemtxlRjwVGTV6lFyYTGTc4oXibRywuvEXk4MuqFhZpGMFM0YRNce+5r6kBjUsdeh+JFR5tvAGs3VcZ9nZ2mJVEWDqCXjNP9tkQnU4iRhyRYo2Z8uZxq3HPJjWvSr4kq6QEv2NhuIJZnAYvAEWr1lYFeQJB4KEIFIyywZGTMieeVYfRYFRBXPlPWWWp/tSIIaKo65W8KGuRRYD9m3q8gus+pWoUCWYqwbqFzGJDGECGLzHK9abGMIILl9OLMl0WPFIJoY2Gb0idXTTqnomaVlVqgk0JHburMaTvKENdUikk3SYcaVSK5JczqGlxw9mEUrFl2LxCJTyIhoxOqU1ahaWpgYcmoIUCLAFjWF/5kTIBbZIZJ47TYEVSapgAWjLvPeyIpnk6G8IvdbtyQLVie2MjOSYxIThlmrgkhm27JFBaOOSk4g7lHKTUZckRGoiQqDq5liyxxbhn78rpj70x6xH3i+eUPNxLBGqfzCsRZBBU4/O2eXIY+4aJ9shSr5xrR8fClWa5JHKRDf2G599Ackk9sDE7D/huN//BnWnx+ZMz76w7ZEM93rhgdFkSUpzJLhZsdI0hZlIcolM46aAz01p6LoSpo5E3eyZ0gdtQx05shQbTlqzWgqenEkNkRj2UbPRbrmOe+o4kJvaq7tM34uT7mprqjSnOF/LyympZtOnKhIxjDVntNnNfswoq4mLAaXEqNseWO29G5mM5yo5hOJloYNXVh4lbYk3TA3jqej40X1hr4PvGos95VnkudMPtE1PYtruG2UGF/y0uwZ5Y7YGG7NiVAH7s0FuwFGrngrYJLFGo8VpYpZ45c04GKCEFmaTKi9l5Z6Ub7GsjEnrrs9J7PjZfopvdRYEtvlxNdqkaTMpuHeWsbUsplO3IenDH6PCdDKkYtwTetmetfiZGEyz3Bp4Wv/GXEwDO0lqpEmzGy5IVQVE5ZaFtpwwpmRe65YqPKuWh2qBiMOSySQQKW0a0BVsJI5LeHcxlsX2kJmlg8R6Q82Fpq/B/UyZ78s9+3L+X8dR1XV6EYYtGfcWvbcsti/lI2/xdPoHaPuiwo0i4+EyBqwnrWMDhFTGCEBq2QjV3WIWLzOnNhmorzUHLXDSmlL4jknF5RkgEm3LAyM8pSFJiO4Z7Noy6BboGNgixPBcc2g2ZNtxXzDIwECmjX0hjsaDEF7RHyJlXI5JoqKRFZZTiJULJhyT85k7mYmvWeeacSRNNGQrVRyA86TxODjBKZhUYMRi5CRQ4OwYLA6oMbh5wVMg1qHZ2RZMzoL023GYktRZDRxjr1Cz+cjahZU1DIDcNItUiK0Zu1I0uesWWxZn1Y/tLW9vLb8tGCxE16USIuWc7eYllkl45oSCGvofOGoOQKjdAQqZnFZCACgC+hMjjxrcar4ggzO2tDJCaMGoyGniQAtQ0bEJNBrhxOoGYliMrdSDIu2OYkEishFzq3TnCSRxV2GmZmKXBIuiELNRJMG7uQJugIJhfeZxHNPBVSsdmCWSCUDPkVmKqJ4ckZDof6o4ot40Wos/nFD1nlLKEzAKh+HZE5mg8XpTFs2OmPpcOTCNfM1W71jvIhc3xrurkd2+x3WfXvdhu+KuQ9GGK95V18iWDKp9FORWg/ckjxW+Ne9V1M9PC88KgrX15WJSeE9X5vCwMiPz+U1Hx7Dh5XhBy1hjaTUkm/bx8fxDW+BPiy079mh5IkoFlYDj9sxrGqyjD46eqQ02mZjGbhk1JaGiZhy5p51WeM1UlGZ/OU5cEFDDlSexRNMRUoRsUKtA15mTFp4554wq2U0GybrmUwN9oI6zGzSkd14oJ4i77rPWDaW7TAxKai9JZqWqe6IU8c018QQSFYZ2ojbBvYnxQwDr6oXXJsrqqUGUV5sZ2ozMCahdgFbR4bJkhrh3jQc5DmjKkdfE4xwmJVn/inT8prKTdynip82T3DzNT/b1HTxmgMdixhiU1GnyNXNPU/NVzRmQ9SGydbcmAu+F9+SSPSNJUnNSapHZHUhRMueE5NxvKmeYFJgEydscLz2X1ARqauBdhlo3Fw6PwavE5UsiDWcaBEnVMsE1lHpwGfyNXU48VP5PqPZ4dPCPh6wKTL6zI0ZbUMntxzkCRHhQehDvt9xWIRKehLCXG6oJGug+mNbhQ9vSn34+iAstmJwe0z8Ts76qwxvPS8uvyDWE2/9Ba/tc5DMaApaI+Ly94qZmZqRDUZmlNySrUskEmqKx5xBJJX2U84ijVJx0Gw0XRd+ltGElWwrEQtOf2boyaorzIrPc5j7uaDLyFGkI5K40SfkKKgZpaKSnkCO/8vvl8vPO3kOGjFS0XGTOWBpRsQVvaljEYPoKvFYSGtGbFFQWgY8kVl9Rn8SGJtySg05r3a2rgh78rG2qmzkSFQFWibZ5Lahz/50loBRw3LmU+fP55SC8/T0MnKnV2jB9ZTEhiP2bGe1+iRkNDLPv2SETB64g6zPPLchV8P3fA0zlmXLLK506UgwNSfZZLW55sKzYWKgptU+q1DJYqZzMD0RS6KRITugKgU5hIhnkZk7nhTubASNWSVfRAcT7fk7XRNpdGaWHUqxKdFsup9Yc08f2vWWobhA1FlwooKnLxIEyyQNFT2oEqTBE5mk4cg2n4vzOmtQgVF3GLmn44SqJRZEz6BYFowojgmrhkruSAWZ9RKJ6jhSFUeKPI/d0rEhc/cSFZ6QW+eUdroaJtmy+IrLbuR+6JmnhdZ9e+jcd8XcB+Pu6z8ioUw0vFdEvVf8rIXRUgqfx+jCis7p+0XRmdbwyKGbBc6qWXl43iqi0Ozetn4BHr3JB2/K+49L4On4lvvmgmu7trc+eN57zuuFsLlGp5ztUNb8u3XCXdHC8ryzaWX+/CM1NSM5hNkVn6WaoUjdKzeQMHk3isHogtfIk/SGRT1OniApEE1ETHYrG7TCJ0/PhmDhqBdMYphMhw8LENkOR7pRSMNnJDuhy4SXEywti3GcGKkiEA3hVLNNPRujHJLw0rzDS+DL9h18tiUMQj1OSPKEdE3QN3B1IjkPxnJnNrzbXdKlCgmRsQakod1e8U6UQzBIL/T1BffeYFLglGr2/Y40NYi9JTUONXlnzpKw/RaRZyRj2bqBrTlldolbuOUZixja6cRQb3ijLzDA8+lrTLKowh92P2RwLTblhTxSIUY5GSXIhtlZKl1wEvAlkWNOVd7DpwUxgbGq8GZEVLiK74je8cJeY/U1NiUGs6E1PUvsOIWOqprwLhJ1YCEycoljLgtPXqgnKowqDQu1jAzn1tuj6LqPxoe7jCo7rccOjodf8JrvxuOxxIXr5Yal9vSx4ra+YmSTr40YRm2wzATdZM7W6lqvgpWeSk+MXBCoyNcqF2uooWJhoCZJtidaCRZOB2pyIXfJLQMtAw0ndgSVEs5e6GNn3lN8NK2tC2PmMwU8aIUUxaqqw8vEsi5Zmr2/koCKISr0ssutY6kyOiirHCHhZcToQkpCNIqXiC1JCBWJqqT3GBaMWVMsciswiCfSsKolLQtKzmvtpQGFJLk4nGlR0Ud+cuQPKHnmazhwwVtmWgYu8RKZcRhVnCzF3snSSs+JXfEsWwu3zBUM73mtFcsfclJCLtcewIZGBto4MMgGIwfAkYzN90JB7+Kq+1RBxBKkBrX5tdwxsc+fr7zrSXbksLGcFQuKyMJMk9uMBakzBUowGjGFNwdCxJVz0ZfwxmxGH9kQNeZrrgXJl9xe71LPSbJtl5GcnIFmQ3ohZkscCYhW5zZ7raesWmZhbckaVbZywJDYxh5jFk6yI2jmOS5qMQK9OlRyjN2OEzs9MGm29Rmlyi1yzd+dfFY8iYDTmaPsUa1ZxJM0n4cgOeFoMTmvnJB44Dp+O+O7Yu7D0d/SzQueAXgUufHh2qOcb5D3h+NsUyIBVph9dVtfW6vl5nloWX7i78hjRO7DduhjIujjxyNXesuLRWlufsw/ftrQn4my1QevL5PBe+atH6CA5Qv/ENi8PiZ81CbThklANNPms1VFZJQKsb7wa3LIc0ug0YE2TjxL17xJL2lsoNWRWg3bdMfJ7Yki3LgXDOEik/0R1OZIn0s5Iinx2XHAzML3+iNUM/2u4m5smFygu4PgLnEJqjhi44mdBaeOnQSepneEWCP2xNvuOUkbbrTC9weeLHfcLhN919DsJ4Ioe25hitT2GdfmJUt0xMpRne5IAj4Jg7VUIRJsQxVnfm5qRpMwy4FjVRVX+8DGzNh6oG6PVKeZl6nn875HtpEX49cMVx6JCzdckIxjo0faNCJqsMliZsOh3lKlyC4dSNZhmWk4sJcDX+kzGh15Fq7xKRGcMjtPq8NZUG1UoQlc8lWeyJeaf2p/B8uSo3JiYGMPWI3s7MxO32D8FUZDyZM8FmPZkYqRIy05yC1lJEAypgueijmr5dZW0C8cjws6JRnQynDs77/hNd+NdSxpYT7cM99ecahgbFucDAR2QCJJ9ipUVRLFAV8yyj7phoQlSFWKAgHNma21zLi4sIt3JCfcSyapL1TURCp62tRTa8/WHosJsAFqgioVyiQPiBiCF45NAAAgAElEQVSFlyZxIeFQu6aCPASc59ZaZMuBXjfEcmflrNaBwIakKasudaSTBc9IjI4ghkE2RFa/tgVrEjULSR21jNTFDiQiOHUs4lESAUvFiOLwTMUPTQrfzmajZNWSdwuratuW9rKIO+eXZhqO0jDwBT9ly4Gfyw6j2Zy5Brxkjhb5k3HP/mHZUC3nK+E5kqjXMgk0rymNDOeM0NwqBESZtGayNdlbsKGmWBCRs1MrFpJYap0ZTIXRrHd1MrKmxzq1zGXzn87CgNxZsrqceWpxTTUq9IiM0KWMqGlB7SUjdk5mglZETayiC8jCHKuhBN2vYpyQPerwVDKR1HHBLQnHrO1549gSqOWAUcGkwEhDLT2KZ9Y5c68lMWqHY+TaXiAIM77c74BYUsnlqHVilIZ73RHJSvwkhklazgpoHgz+B2qM7AlUuZtEQAR88V/VaNAJ3o4nJpkw37Jx8HfF3IfDDDgcczEi/IVDHv//kZ8QeVdwhrzPO1HIp3vhQWVVPXqjX2F8Eh1cf85/c8OR3z39U55fL/y17gf85a//Eb9/ueMff/lXPv57KiCP/b4+fN9im1ImE9GIkUCUqbTV1nDnojITZadHRloyW1BLSzAWrZviZWATJyQNCJYxdfyMH0By7OUeiOz1jqfpFa+W73Gv2Y4gSjYMnV2NoNgUMDHy8vgWH1ucTrzbW3ahJlQz+zhzsp4mTqSTg1Ax7wO1mXhib+gOnrH3mNrTB8dRf4N5vuQqCLu+5yK8pXN33D1pOZqOr+NTbquOTTUyxJb9EqhT4kk8kmpY+hPeKWFpmFzDF2PPqbujT4423RFdBD3QdxWqgcEavJ95Mky4+p5xqnHmROoSk/X88dUXKBa1npfha97qCwbdcBOfEI3QjAPeOIyOGNlS6cIchTrdMqeGFCx1Dds4cdBnBAN1GrhLGybjGU2Dl0BlJ+oU2DEwJYfnxK1eMqaWlBaCqWiSIXnPJIFJO05kgrpnoNE7buQZAIEKQ8IzMbAhqiDSMTMVm5v1PntMK/hlN7xm+wgbSfLtEoZ/XYeMgcMf/BNubie+fv6bDLIl8rjVlEv+B4rE+5uyhbyQ+hV5K/OYaG6RPwuvuTaXGKtF4BLYygCA0ZmEYxtfc7BbDI5WZgbdYBnouGdhUxC2nN5Q20QOkVqYNWZFYNE+znhqZjapJ9o1hCk346xmwnqSLFAYxBEZ6FSpzAw4HBEjkUBWnC5aF1Xvgk35d6KQaLCa+ctr2oNlZlGHEInSwHlNEGb2hbuWxRlKokk9yeRUiPP5PCcKTFTcUzNz4hnZHDcXJmvSQ+aj5nl01lw4eJ3O64dIpNUJ1ZmZTea0MmFJWJ2pJKOJ6fw3E1rABZGcvDDTIQieBdH5zI9MRalqmJi0JcmYN3qSiiQAzutXuQJeF7amJ+A5FYsWPXd28rGMdHh6KoVRFgxKJUeC5utrBZbHNFmlXOO1q5VVyr3UoG25b4RKToy6IYljKOuakiPDFMEr1BLxOjORkxoQxRVUcBMOBNsQxTNLZkmua2BueEdm8WQLYsPRbDAxi4aMpBLHRv7+nLtzjlNB6oxmzXMiYsr1q/XIs3iH5wj1t1vIrVfnu/FoiKuYxRQi93sVG59saz5Kd8ijqF/F8pFaDzh7b8nDzfON43EB9xEXb30ggQ58Pr/mX7v+f/j+ceav/Xt/i3/z+3+JtnL8h//lfwFffurDwspver+F+3FBVxEJxAxj52DDh89TJnuTdUdU9Fjy9GXJjuXZgy4i6qnklkVqDmbHLA1TckidybgGMKnnT8xfYGDLvWypUsCkgJ9OXDSJYCwqwjYcWWzFYdPhhxZbzQSbCKZmGwNGAr039M86dkPPuN3z/eEVwSg7/47GWJaxJdYN6bTnyEsUQ9u8oh0CURqSGsax467b0eOQCK95ymIXWrGwLDy/P1D5O9zkiIeWWCu7oebet9ykCya/sItvaKp7ElfYMDKamnaZMTHyzlyy8xO19dx3zxlSxSvznB0Di1R4eupp4VY9g69RoPcNrTvxbL6nPpwYbYXfHujMxI/db9JLTTuN1NFwZIfRhdum4UTLte8wKDOe2cJBdnymP8Npy4JlFM+NuSKK5CJRBmwK/JH5i4BhEUNS2JBTKawkWiaEAdgylTYNEtC8bGaU+RySvn4PPhAMffIGFaa6IwTD1eaXiXm+GwAyL+zbp/RXA5UPhbfYsGBLofRYcGV5UESuEUQZOV10QUQQzQiNSqQyE7OzBFvhZcmohjp6aRFdaKWCNPLOvOTAjjX0XgRqHRh1Q8Dx4MGZF89GDqhaKnEksvGvMJVmHhxMhynh6EmyB+aCx6IsCk4y+2/RvPgeSjeilb6oT7PAI7dkHQ0HokBPgxpHUkdnevIsljJxnZZc7nqsxpItvYow4lnXKbnSxcmCKz5yszR5K3I2NK456jNeYWjlSE9HUo9hoUuJK/OWa54wS0bRjCgRLdYlD/y4XHAtGImgDYtkmyijK2q42mA92izJaiGV58RYuISK0MQD6pYiGDGFm5jFA1GERXNBk5eF0goXBQ3seIvTVDJTi7myWh444Pk9ZzpamdjIhBJxCVQcKvka5vfL57BNI5ICi8u84gcFfEH9yvr6ii+JNExrbrnE3CFA8n9GspgCQy/7fFxk4+skysFeokYyS06leMXl9w+qWCwmRZxZCGIYtQUbsZqLas+UOYXEoixez7snByAm9lwzULOwQ0gYAy4mKpOo7fitGwd/V8x9MPb736b/2f9dbpIPi60PC531KRMPGXGPsg4/QvYKLCueT5/6D/lCq63Jp4jij/8vtBL57duf8K/uPuPf/et/g+9//gWVya+rC9Pj08OALjy0dB9/vgU00zjzRJC9kCwjUXNMTEJwzHRypEs9s9aczI6lcDeK3zdI8STDMaaOk24JyaM2+1IZnag1q6qO8pSollYnoslkXmsEsVU2EE0bKjPwXN9ytBeImVk2MPoa38+M6YLZLmB6xOUYnSpGerVMDq7dJTN77qual+M9pyX7tJ1CpAozT8YDWltc0xPdBWPrOLLlbbXjrVPquLA73TDFGt0YBhZ26Z5u7JmXF9w2DbfMRGaecGLyG+7aPTEpLig9G6bYEIPnZCw3zY7v68/xzZbe1AR1nOSKqDWV9vgwc7ItB7spyjLL2/YJV+IRrXiy3PNkfMNt03LUC5xJmBg52I57l20ZVBvunM2RS7SZw8jCF+EV23gipobNEnhdX2XjTgRJGVN9Z19SMRLJfJJUuEGeRDQm2yyQhTMiAYMnCgipcKTKvXdu16+JEO7jr9h7D2RkzsUR3MLzq5e/4B7+bjwerm2wVUM938OuJamgYvAyUOmMkYqAkLQuGzMBnRHJpVMjkaCJNk0gB2ZzwaKCakdiZDQ7FuriM5nDqwYqHBWvTM3ObMrar3QcGHRHLSdqIo4TThInNud2aRSDV8NG7hGERWtGOmLh8gWtMRj26ZbOHLAkkgiTtjiZGPV5mX8zfT1IjRYHsIzTRF7yFXdcZnNtqUlqSeU+zYIOoVJLSpFg2mIbUlHpQBTBl7l7oi6tw1y8VDIAimokGpuNaCWbEwddi49clARJzDi6mMsQjLDjwI254prnDFQIkYRgNGIxDxYkha6QP5fNnMLVakQrFrIdkME8JEecuYjrOpKLZFQIkhmBs61JWhXG4olNGEEmRrMpdBmL4YQjcZAt2XUy+7MpHmTAaCrRWatgYe1U5Ta6kew/JxpwJJqySQ1qEQyVTERxiC4EqRHr8JKpIPPqUXlev/ImMaktIXJSCjVlEZsV9gjKwFKa9Ou9uHI0k1YEyepTkSWrtlkQPJ6BShQXe2ozcKP7UnAKjmzkg0JFjut0AkZ6Rt0XACcj3RtOtPHItX0BJBY6Rq2ZGs+L5ZbPtt23bhz8Z1LMicgT4L8Ffgj8c+DfV9WbTzzvPwD+k/LP/0xV/155/B8AnwND+d2/raqvv41ju3zxA67/4Dk1MPIrZKKWi5cXrPV0Pr751rEiESvxdEXzys4N8s/nVgh8shWlM6zqnzMHTnAkbFXx9NlL/sKX33vvJa1fW1sfHjtkbt8IevGoDbZy44of2HJi9ntE1y+DwzFnRpzWiAijbolSoybblSiuJAQ0ZJVQ9t12jCQDc/JFeQZ1GFALvTh6v8eFhWhqYjjhUfbpwDaeONkLrE50oeeZ+ZpWJkYzoaZl0g5V4VQJfhHaZeKL9DXH1BCsEiphm3raFNkssAVujWWxyug3uEXY6EirJ6r9O05aUzUXvF2+x1gJLgoXacanE0d7wfWmxpojz5ef4Nt7/LuZt3LFu82e3m14fvEVxgonL5z8Je28YKqeXd/jHdzMFxyrPSlZjFEqP9FUFSko1/6SpLBoTaDiNs6MUlFNgcYqIUW8WzJ/rxKmRXh6MLxobrh2G3rbMRuLjxOtBI72EklKjkVK7OIdSsSKZdGWI/CMdwSrRBZG0xRzYM8m3nAyHVYTziZG9SRyuNIcPYsIQWp8nBCTStZjC6KoepycigqxbFTOoiD5xGYHPv6uJYwobRiI6c9Pntef5znMdRsuf+svIv/rP+T59BU327x4eRQrEHUhrXxgdSBZ/WmKM39Qm/EPlcz9QnGrpYc4gq2IuFIHBoxm/zSVLIBZNDv7j7rFyYgiGJ2AnM86U+dNATnPUwiogNds5aGai6RBixJRMoo8mhqrIRc4JXuz1z2OgJcZx0SW+FREckLFLFCLMmhW0q5KXS8LkcCRPZAI1PS0YFabEAhiEDxWEw1HjCiVnjCijDR5ltfAXIx6rQpW5ozsyMxG5mzZUpJcnS7EJJA8npnebLnjsigoj1Rsiz3GQk1PFWbeumdMsgHNbdCThIxwl3m6ymcGU7hqlRxxOHxaqJi4MTtSSYuwKKITqxuBiLJom70uMYgKR7vBp0hKkTYFPLeIsYymZaDKJs4YrIwsWqEMGImPWqMRUZOvu1bn/FlhwpOPKUlNR18iuk54QjmfCZEJk2CjB4Q7bvSSXloyRWgGha0cCZgCuKyGz5lzF4ogYiQLIWoZyjGvo3jfSUDUsmhx55NsXWIEVBOikYGOWWpWZDCQN58OpaHPV0A9KpFJ5sKRtKCGURpqu8t2QMUWZZEGMwsVLdNhIIYF6z7llvEv+b3/1t7pX2z8HeB/VtX/XET+Tvn3f/T4CWWy/E+BH5Fn+P9NRP77RxPm31TV3/+2D2zxNXfiGc/Ku180StEjsRR0j9qmukZ2rWMNAy6PSXh47qoMPd+U5bEPQbr8xnhGfufN7/N/Pf8rJJ6cf5MAlwZEhg9fRJWgivfMbvPxRwCg5iMxA0XAoQ2z91CmHE9uvXgWRrInWibTauZ/aJfXaYU2DZh0YLBXZxSmZ0OtMxd6YIkWwdKFmV4rpmrPgsXLlDlxBLzARE3vaoJWtAiNHQha4eSeq3QC4/DxPmeJSoczM9FYTtNFDgO/H7HtxG8P/4Rkdny9e8Gr9oJZhCr0fHk748zCUA/Uks11+3mDY6Hb9Qy+Yekiszg+m255FideDH9CdHsq02LmI8d6x61c0JsKYeJUK8/l51i/5863tMeKUSvmWRi3llPXcfAVLiaaGDgaj0s1L/ufc7raYtMRZyZGbXPeo/HsphmCsB1uMe3Ivd3TuJ7ZX1E9g2001G4gGqE1RxYM1Txz0g4jga1kO5YonjYdCbQEY1hkz4/ltzA2cTQ7PAt1SIwEFmnxKaBGcLrQxZnetPSy42QFxdDFO0a7wTMjK82gbIQSzaPvxRq7o/me+/C79Ml7PnARb6jmidf9m4/u7T/D8ed2DgNw1rHH4aNhG47cVlcEhEFbahnwGugYGLDYaMAkWk6YONHbrAoVYzGaQ98TOZoraGSSFmEiaZUVouQFL5IV2iqGWmcCM15nIgLiCarM2uClx6sg0hBVidISmDhwRQJm2eQ2qyyZ84VgFAY6MFlBWWukSgPqpLDcAi2BWQIT3ZmrFtVzoOUkW5xO1LLQ6EidJmbj6NmwlNsvicWSE0dqetAalYTTGRBEI0pT7nIt7eocaVazFCQwFouPDR1jiccacHQ4BjapZzCexdZYFiJKoCGwx6C0DKCaU0+wJCoq7QniSbq2pyUXwGqxuuAlUacRYxSnCZcOKJmjesHIKBlRzMh6g9Wc6hHK+5e7lSDZAa82Cy5M2DTirAVZOMhVUarmNnwocfWjbgtKqFCUrZaZTgeUhV6bnDeLwcaAs7EYQCs+juCyf16eO5RITbSJWWteyE/ptWbUHFOYFcwTHX1JswgEAFlFPIol0KYBxFDpyERFxy0qnlEtWrhzeib1QPbMI79elTotaIlqO5dIuvIWU0FNs6FMLffMdEUssbaDLSfdMhVED3Ib12jk2GyoxoUkEEP4tSjm/gbwb5Wf/x7wD/hgIgT+HeDvq+o1gIj8feCvA//Nn+aBXU8z95uczfbN4xHH7CyCeLxLSI+eu/rmrN5aAozld8V+5MPxyT+fJ+CX3R1/yMJ8flzZckNbT7juYwTue5uaH4y3/NFmD6sr+fkP+EdIYflcWh6XNVsRKKToHDQTgJaIz8RabI53WT+7GuwaF2M7VpK1FJ3QYjwGqCTvpFMQrt1V0RBVzBLZc+Dz9BW9eg7mKSNdaTkkkihv9SW1Rto4YhkxThhxOJ3ZmhNz1RADdP2CTZYL9wpnJq79HlVhMo7tMeAng50mahuRJtFN75i6wHw8YqXFdUodhb2/pdaBVC/s4owNlt18YCvvoJ44uj31MnOsO6owcKWvuIq3uNByt4zcuQ4b7mm5offP2MaB2kaWZGnCQDfk3ebb5ood91QpsYiwmUd2YcRqxdXxwE5PtNMtP6su+Lq65LX/jDYFZlPz/eUrFl8RjOMq3WNjZB+OSLC8ar8gitDIgVZv2cZb7u0zKkbuzJ5Rsr9UtjioCCY7/EdTYewa/ZSTF4PkBIGKngN7RntJ1kXmRYayG1+jcfI9P+dJl8cmp/bhnlt3AB+MikCTAtpZjmn86Pd/huPP7RwGUDUVT33NfljowozziUmygMCVa6EqNCScyeHzQqS1C1W64WQu8ZywEoF7Ei2qgZldUS9vyNdxw1lIgVLLiGggy7smak3MJoe053Jr/e4HYMZLytwxySkDFSNeRqJu2TIQNDf9teA6BiEKBFPhyccdsQR1WKaS9ZnFZ4ZYorE0L72iBBUqErUeWbjM9AFtz9xOq7mMamVEELwuVCkQRIp3WWTQbS6W1GLlhNWYW3YstPQ0MoIaOhlZOLBIhdUTXoupslQEPTuasUhDIlBpYMEU3Ntx67aFb1qVQgkofEbRnKHxnNfZG0AMqomA8IX8HEv+rKNuuJUn9BqJYrEai1ApENQwCawOdBSl7izk4lgPzKkGWxF18wA0kM5fWcPC6s+WJNtYiSSSOqws1KXRPWtHtDVLOT+OyOJcMZNvcCzUumD1wGwzuPCa75FwZcWcUHFsOIHmCDFLJOJQDdQy0jES1eLjieAaAjlF3JEQDbQS6anPx+9lxKHFMkmAgBUlWEtSXyxgVopIvr8VIeCxBc2Nagu6vHrD5qxqxJA0F6lJWxqGPJf1PaRIZQ3216HNCrxU1a8AVPUrEXnxied8CfzJo3//lPdp/P+V5F7Qf0duX3yyFyoifxv42wA/+MEPfumB3bz9ivq9TD/54Gd4H0UoTtxnub1ydrg/I10m7xwwIBNQF6h8NXf8VV2gPSMb4ujQzSPUUJVZOjbxgJymj171b/zl3+Prf/Q/UP/wLX9Y/x4LHQ8cOcNHheOZQCs85MrqubCLajHSwxourYat3BK1Yipt1yaNuDCTvGeQ7Felhbtxxw5nhH26IRmH90cm9wXgclB8CtSMnHzHG3tFoEaSRTSyWI9q9i66XTa0y8Lz5Y6Ewdc19yJYZnYasEtNk4TTNvCqesKA4527Ykg1KXiqEDgtW6qkRB3pxiPdkrgfW2w/EkfL5+krzHZL4y11eouxic/0lqhCd7pgcs9JcSZUT9nLRDtPVP0dmzhgd8J1V+FTz8wFex+wKBfTgbmxTEtHWGo280yIO8apIjYVl8tb9u4du3AipRrB8cY1bMw9TpVjs2GqWjyOoBUX4Q3vumf8M/clixdO0vLKvuCSWzb2xLPwhhuzQ21DNA0+Hmlk4V5nBulyWgYNt+kCVUubDngUSUKwFU6z79eBHU7GEm2TGLkkT7Mxx2zHCWfr0u4qkybZlsGJEDTkkkEo7dbHFIPHsNz7AhyxgrkN7KpvlzD8/3H8/zKH/YvOX+uo24Yvv99i/vCEpSOqZl6TCPd6Sc1IKxM+ZX+wKgxEb5moaDiiJBShlgm0QjSH3SOUDVu5frpGL2XOZBKDILRpQGWiSz23clW86QyVNYhONGRlY1YvClYTC9mkOGGxErAEmnRiMB2TgCmG2VmNOZDwjOqpJDdKIxZRpZb150xUTyVlRwFXkMNRNvTs2GjPIg1Ojkzakl3Xcgi7lQmja9amMEhLT4tSnRd3i1LpzE5vUByVTLg0sYhnUstCzag1KpaAkpwUkEeImkpSj0epWGRg0I5aAgsVQau84dWCHGGyPEPhSt9lnq9csIhhKVy+RSveymd4DbR6n+1KVLESmdQX4URGl/K65QoBZ7VRUYJaJlNz454XYUMkkVvKCY+TGUcu0EfJmaaNjIRipKtIFqDo+u2OiEBAibplUUdrhrz9U4+XpXAlDdF0LNoySIdTza17XUUQSk/FTIPRTL+oGfO9ooolZkRVYMIySwuSiuGvzcrs4v9XM+J0LgkU61qXM3szG3RmwhALApd7EOBZSCKE5HLSA1sCkGQ10s/XKSeUKA7FykSjE8+Wr3jJPRebls2VQ8w30Lf+JcafWjEnIv8T8NknfvUf/6pv8YnH1k//N1X1ZyKyI0+Efwv4rz/1Jqr6d4G/C/CjH/3ol549nQO7MFBxYqb71Bvmi/+eQ7WQzQ3XgmddxFZRxEpADZyDx38Z8PfJkTAE5pTzEJcV3RDDoB0TUPcfu+T/3o/+de7++Kd88Q//d/6P7/8v/I8/+KuM8oRPp1usn1NyC1mGjxdekRxTUwrYSkZS8Ywq+2QMhWN15v3l8yRlsoSUVWQI0Vr29ESNDGwR4xmlpYkHtjpyFM9sHHUa6JaZZHJz950+J7SeLo28rV5QpYHF1FzbwPPQs68qmmHgRrYEcSzGc80zqtHTU2Fj4itjeCknpAuM1QBNZFqE6sUEc8W9s0gvqNbQBWwMxGmDO0Xat46wb+BiwoRIExe+9/+y9yY/tmXZed9v7eZ0t4vmdZkvqxGLRZGmSFMSZYE2BNkQRRigIEAg7IEnHliw/S94agOWZh4bBjTwwAPPbMGACHhswC1gChQll1VkVVZm1muiu/eedjfLg33iZVYxi1BVZYk0lBsIBOLGje7GadZe6/t+39wyJccwbvmuv2SyV6UD0g04XTA28Xy84eXdx9xV1+Sl4ajXnOKGZA0YISbPjX1Knlr2MnA4RbR6oIo9/abmHFuO5oBNCe8yx3rLSIvIzK1cF8K5VFSaedU8Yx/OBGmI0ZONkHNi1IZL7TnaRK8dijCbmi6cmaQl5YjKAcvMSTaUZF3DYK5QoMkP1GYhkhnkKYsqye5WLcmjm62MW43YAvmkY8NEBHrZwufmBv/gKZpRuv6Icy2NPfyY58tPt/4sXMN+3OvXuxUX6m1e/98VRouwvtbz2v8Oq6uz6JAiRUoxUZGMfzcNL4mlNfoIgQYaHZkw77RurKDVTLm5ihRw7CE9cKF33NsDso4TjZbA8VZvsLJBRUgamWkxTMUao56GEUPRxSXqd/orr4X9VpIiFMQRyBipyToXfR8DFcpeTjwL32XQsumY3JYkwpkDyXqiepKUAsnrQseMYKgZmKUlK+vHI56ZW56UTNdHfRgBWbtCvWxRVQINjfQc9I4lVxzdvrzaWpzhVvKqCSwjwKjNGnRvaEsQIahZO16ORR8RMrFcb9UUxZuUpNlZyoYuUtHIgCNS54Eq9yyy4UEvwRhUDbJiSrxEKp0LloXV5aqK05kCfYHaJFSkQG+1OHA9mYUes46ZE46NDkxU5HU6s0j1ThfrELweCXRlarPGcj0CjLKu7mAtA1+Aec3tBYii2JUzVzScihHByQJkotY4oNKA5IgaA8Zyttv1DsS73FwnJRrTSOnmOok4jbCmf8xasZUHtvFMaxfObAqGhAUnAdVIoF3j3xxRKhYBUY8jMug6yeLTfOOKGaepvDo5kdixmT9kzgeCWHIOGPN5rNqfbP3MijlV/c0f9TkReSUi76072veAzxP+fo9PxxgAH1BGGajqR+v7k4j8d8C/wY8o5n7ctb+4YPtPJr52+ZrvNr5EkJTBAKVYg+JehUeeDu9y8j7b0Qt8qqN7LGbyDz32wzq1z1uffU6mYWYbJmpNDO+ikQq00U2eq69e/LHvUG+3/LXf+R1+/lu/wbf/p39I+0FkMkXg/sd/llLaxI/8OLBSLrKB9jPPe3QiFhbUQkPDA0E8SQVjEnUqgFsjirKgmqhZWCgt8CN7tnqPmMx7+UNOskHwtNKjArNsWKSm5YjVDU+Xj3mit7yuXpC14s62SN6hGHptUTHYPOA0FdJ7vXDTNbQz3Mslt9sLTrLDNdAMEcmQRZD9G8x24Hp5oOZEkzpCI4guDO4Fy3DB/pgI1vCkfkONskmZh+j4zubAqXqfjTW4wSK5Jdia82bDq9YjtCzdjLULxESsoAsDh3ymdSO3POOj6gmvdUe2EWs31HEkB0PIiTeyYTAZqsTJ78lV5qPdU456gRjD8+kj5qamk57ZOUbnsaoEU3PUHXPyzP6GOp/YqOIZyEY5mwMSYRbLIg0lzlvW5qtFJbKIxaSWhGE2NWWw43ACZ3NY4QblAtatupjyUQkQKgOjhaQbohQvo65i64IpyT90/H1OraKG0e/IIZKmP951/lmu/79ewwBIC3pqIXgAACAASURBVMF09I0niKPTSNAiiXAsWC1mFZ8jIc6M9qLc/KR0vRt6vGScRlTKNUbW8d5j1m6lCSGQKfDZiYYcPVihyoFkPd+Tr67dj3LVaKRfU2KKiSJRYWRENaM077ReRkvfK1EitIwmWo0cwj2ja5hlg6xjQ7dua6OWIjRrQ8Rwh2VxFU/CHVjLlhP3coXTgjwpgfaOTZjIZLLPjHQ8cMBqpJGebZ5KfFXyYB+v3eubJgzKLt/zxjxnpyeMQJsGrMJiOoyurE4Kn87niWA8BadbCmLL6rCkBhYcJRv0PfkON/o+M03pAUqhByiRXi8wxSOJUpAkI21R9JnIYC6556rwHlH8yt4ryQsTkFdo9MIkDZ6BTiaaPHCW/fpz/Bpp7/CaisbNNmu/irVzVbR9VhOdjMzrWBUcUQ3CBkNao97K/8qsWwSD0pGxaWEWR5CG5d29zgOBtGJhSldyLoIN7bAS8BLIallMjTfKQstEKfg8qXRZtfyfkxrknWSoOKStCk4iaI+RRBUzdi1qxXRsmUohmBd8npEVkG5MB2KYdYeVkuHbaFijz0rcl5eEWXV2VZx4kV7zNBy5tieaec9wHrg4fHF6OfjTG7P+j8B/CPz99f3/8DnP+V3gvxSRy/Xj3wL+MxFxwIWqvhURD/wt4H/+on6xqxc12yHylbtbrq6+z2v7kpPteGCHUlPlmX064nThTfW0xH5J5F2BU/YKfLopf3SS/rDh4bF7IZ/53GfX43j3MTVC2TDyy+Ef87XlFX803NFvWhYxeBIHjjyfTnzl67/yuX9Xvd1SP3uPQcqY9NP16N5KWJlXkevq4JHSOUnqUZmKE3U9KdK7330tdEWY2MLq7lmw1KbC5xHR3aq9iWzoaZg5s8fgEVNcbz+n/w+L+YCGft3tK10+YRRmW4MkBjnwGotGg5OZzntcTgxssZowORN1Cyz0Jb8LX2W2R6H3DVENT0JixrKNI5s4oO2ZjpEn3HChPbMdsfWGpero2z1LrLhN12zSAy4mwitHuh7Jacv9BxtmL6QIbr7nNOz451bJUvGqOzC4mYM945aFC3NPEy1xmbgMRzITUsGcPdJMdMsdrfT4WWm0Z6ZGoiHYmqwL++XE1AQG3TBJ+btFE8F5kjVoXoi2Y5N7kCLsnk3FYDtC9iypwhFozYLatWNjLHV6QFNEjEeJuKwYmajNQlLPLMJsWjJCFopAmIVZPJWeqZkZ2SOSOKkny5O1+5zJqmRJ69ijgxVa6hiYH01An2t6KGrQisBejmymAWrH1vxw8fenuv7MXsMAsBWtzuzuI/Fqj8+Z57wiGsHmTLC+bGbUUpFIMqJZyKJs9chOzmzkxD2XNDoQpKLWkVoHIg2tCJUkojqyBIwKVR7pUrmGqHWMlBxMs2qbjELFwsgWx0KSCtFElG51Cuo6zjIsUpfunGaqWEa+LQNeEkcpgzDIq6HhgZ7LUuxIuY2XotUy6I6TiwiZKgut9DSUFABByatpI1nPwGOgPTQ6M2mDqDBhyFIRS5vq3bSliTNqPYPZo3g6XQhq8Tmz1REhEaxd9W62YGG0RMQbVbq1qBp1ByTiaqDYSJGN2OxopXQi36Gy1KAYohTl26QbFKh0ZGFHRY/FEEnMUtAcWYU2n2l1BJPYSL+OdpVMhWqmkpmN9lzzlhd8wh/JN7jVAwuOWgo2Khu3tg0SozQk9fRiUc0sNKX0VkNNT5WXohUkouXVLwVcVjo9sTEjS3bFUZoN0e+LG1Qfpz8rHmmdaimJSoWt9lgWRlqCVoVdirJoS8aWLqpEgno2lOd6EotYZm1Wjp+sv2vC5kg0Hp/LKHTHCX18jdXhJYDALvfs9cSNuaDWhZmmFME6A5bL5S33fo9RYZGaWhe8jIBjdhVveIKPjof7a5ruKRv/3hfalYM/vWLu7wP/vYj8R8B3gX8PQER+HfhPVfXvquqtiPwXwP++fs1/vj62AX53vQhaykXwv/mifrFnly/4pQ8c7bcyZrwlmzeozqR+y6BXbKqWF+3M9/TI//L+wkf+Axa2sApiP398+og3KfbpP9kl+7g+7VLU2vOMW16GT/i1/tt0bx2/Pjywfx642xyoU+Qv9B/zF7/xV3n65Od/5Hd8fXdPpwMZz6eg0Iyj5xl3PJ++w+/Xv8rCZw8yBxLINEUDIANWM0l0bZunH3puRpiIWnMCjIWkGaGiXu3q+9wTTVVa2HkBEicOpJVdloEqBXb5gVC1JDpGOrLzjNphsrLnAdTQ5oGYDS+XMxexJwQ4+g3Bb5hTxexmrJ94Zt4wyvssXjiJB024+kwXR3bmFVfuI5xz3Ov7hPSSmGoOi6UaBD/OXMc7luaeizoxVzXfk5fMrSHSYkhMydEkgMQcAq5JXI8zbBZsnNiaI1UoANZzdwGMJRPVw2A8x7Yi5sSTfMOL4yvedldk02DNgs8TvbSMVYMxE8n6kopgDORUbpbGYjVyofdlJykBVced2TNIRzKljzY7xxqgwyE/MNMRbImnWXCcqYnWs6XHSMbJo+S3otIjMxuS6jp26/ASafS07sU3LCrv9ETl+HrUznkgrSMUj9NEFMenzu7HcyJQ6YlLLTmSm3lm+zDzMr7hz/3C3/4XOG/+pa0/s9cwAFxF7i746mg4jq/4pNqyoKVDmyb+UL5GJUuRSdiFo71kpMWxcMkDz8Nreluz0Z7oaiQXkbdgCQKKK5mbwIGHorXTmSANJRCpdCdm9bSMbKXnMUsgiiXSEtTQMdNpz1F2TBxY1GApnlFHwQb7HICFVkZm8WWkJ4LTzAU3XKY3vBVDMo6TWgKlQzdrtSqtDDFXJQtUGlRhpqHJA4u0JGNKLqoUDbDB4HLACHShZ3J7DAkrq6xG17xQJnwuKa6VHRFd+GB5RUOm5cQsL3H6CJXNqKnY55FZKmZtaJiociKZSBIh45i15oYrLvQMMSIm4+yyagUTQYpfNhf1Fo0stDogahjEU2tiyRWT60ja4KU0DrbpTCcLo1gSDieRXZ4QAUdm1oJmeZ+ZRX2JPzTF7pa1QtKMl5lKyhSk4GUSEU+9woANGWTGryaSjd6zSFv+H7pQ51Cc8mZBE0TxTLIlOcssDa0eqZkAJWg5jozmFRaxdvM0sU/3iDNMUFJmSNRkrASMFg1jRzFjLFQ4KZFiBsFpCebyucSK1SmyzVM5JrNwY5/RcaRmJOLweaTKS8Fg5Q2ejEsLIsLBHdmlB0ZTs5ETR9kTqEAMQR1ojVDkR1EcWx5wOJrdM3YXl59/3v40p/wX/h3/BZaq3gB/43Me/z+Av/uZj/8B8A9+6Dk98Jd/Vr/bxf4F//7f+Y/53/7X/5M333vDYSd88xsf8Owrv8Tm4gWVKzuH/+q//a+Z847wblb+GGPyo8Rwj/iFtD7v81qsjyy6x85epubMV+ZP+LX7f8JXenj6Cg5/5df561/5q3z84fc59fdsOs/P/cJv8s1f+hWa+nN0fuvSPINLODMBLY/FZaPK1+d/xss3d/zRy59jkd0PfeUjbqL4aaOUUOrHYvCdAJpHy7zDSWG/LwAiiGacRBRL8RAVQGkUS8ieXh9FrQnF0pqiWzEEmjxxa65JtsbnoSgVc/n6loWE43oeaYeJWs+Mo0GuMvdccnaZj9qWSzfj00SjMyoVz85HrvMrlu0ezIaTvo8bHb17yl19TXQ9fjY8twsdEeMWGiO0i2UJgrGJdlFGIzyZlBdvO6yreGhr6votSKCVG25sy73fcM6XNDnhRyA5spxxS0+mYpcHRG6QlHGa+Xj7AUNrcEvEKvSNZ3QtwWQOKXCtb3AzGDdzcEdiNtzLJT4HMkoTF66HW4auY3SWwW4Kc4sKiRlr0yoGhmRrlIyKI2pNqIqYOuYRn5TaTDhbU7CXgSYdiVKRTNHXPLrjnAQ2PLDwCHAtXWXRIn4u/Y4iCEANtUy4dUST0JI3q5lDPPHN+3/K+3dHwtyynxK/cmn4a3/zt7j+5l/5kcf2v+z1Z/kaBrDkzNvqQHwv0Ziep2HkSEXvPLN4GiJ1GtY4o5ZNPuPtXJAkqZzVhzzwXfOEUTdkEVo94wjs0pkkwrW85kauQEuCAkkwGR7qHYtUBYESC9q1ywM7uQcCYl7y2rRUslDnCXIGV1FIXkKTz1hjMCnRaBnbW1nQCIsrZgLB4hmxGSY5MJuGJILNkVp6Ko2c2NAyYlFMSnjNqC0dK68gRsqGRmsCBqsApXCyee1BSUVUwWGpNHHQE8YEJBsqXWjjxGRb9vrApR55T7/PnDpmVxNygTXXZkElY3NBpbR5JuHpwpmjv8LnhcFcFC0qCZsCtfbUOhOpaGPgaDblWmgMI4XjZ7VcV20S1Cii0LNlMh1NOlOZuYwoRfA2YlLEJcVpYrYOjTWhKikKgYqGiTMbZmmYpRRYab1OqAnF1DIJsYJgylQmaYVBCaJELWd0kwL7eE/NxNntObsdEzWj1OR85sie1vR0OuHjRKw6kgqjbDEsXKQHkjHYKMxaE7E4F+jMxJ43JRJNEztO2FggJaMprmoFTMq0LKCJTnpqO3I2F1zkwIMcEBU2ccKmYnA52kvOtmNyDdZEelo2esKvQ+OM55y2NGbkvXSDZ+Bj+YAchaQOm2ExbdF/YrBaxuQuL2ApGkObOUtHiAPmssE1X3w04ZcJEJ+zLvYv+K2/+dt/4nPqxvAyf8iEcMtz/njH7YcdsJ99/HM6cxppeACUiXYdcRbgoGC5fL3jN/61v8izv/6clz//F9h1e/7yX/rx/q5tbfGXtzgT13DkMgKuZeR5uGNvRzYauGPisZPyg6Ng+5m3R5ZYBp0LC02bNTrI0mpgoCatOAqVzKIbNuGBJs3UdkG8QDYELD3XuDCSxSI2s5gKEysW9SziqZixaWZhi5FQYJcxs6QNi/FEbmj9RL3cUTVPiVNk6DraMHLaKlVSJpkZTI1iuNnXZD2QckfFDpOU5Cpe2ZbBZZ7JPQeF/Rjwb29ptoqxZwb19A8dw6ZmMS1GDFehoq0swdWoXegWx2U8kg8TQ4K+dviUmGTPsfEcqw03/qt0NlCnmYxFxFLpjLMLx2nPjduTnMHHmUvObK0yGstg66LbkIhoQ7u8ZnI1+MKEG9gTZMPGn7mUW570N3zSvUeYa95udigVJvUgnpBrZmvwZCYtmh5VyqhJLeo8TQ5s0oRnwsvIWS5Ja6dtxpOlZEsmLXR4Kz1GaoSJRctrzapNyetYPogjqmfHPeBo4kw9JGQMfOPtd/lVX/FrX/vXef+bv8JXXr6ktWDrFtts/tgx/eX6/BWyorVHu57ceIZqyyQNQ9oRdcGnhbO5QGyk14aAJyWDNbBh4kEuyMlw56/I6y1Nk2ExjkoTT+UV7/EJXgMx18hgmcyOwRSp7aIlym+bj+zzLddyS81Ab/bYGDGVsA1nEMMmjCAnRqlJYugYsDFjU2S0O452g2rDwZwxuSRTzJJpCezCiNXArYPoKoRAQ2Cbe5LxtHFBKeaDCx74JL9ETZFpuFzwHMYUAMZVessh3nOvzwhSYWQh2YI7qllo81KC4V2FyYGjuSTkwOw6NtrzcXqJsTMn+4RsEm/tM46swes5YHUi4VbHr+LMQiULuzSRtC48O00kU3E011hTxoNX6ZZNslznV7yxz1B3JtDgKAXqhd4RYmGaWU04iYympWGg05kqTgQ1DH7LSTaYHBEVagZSAisZx4ST0tXbcKLRkcW2aDZUduQiP9DkmZBrnJYhtteFTb6jyjP37oqEISL0ZktnRmqd2aQzIhnMjp4dD+YaRUnGIckw+SLlsaulxpLIRtkwsM0ner0iUrEkh9FAw8KsjibP663VsuGOSMWQO6LzVJJZtGOjdwVXgmVJNVsdqM3MY0ZEomE2FfOq57VauKZCJGqFkQKoNibhbCZo4HvuPSqdGWRfaA3G43Vhx4lR1wzk1aLTsJRmD0odFy6ngScBfNf8iefuT7q+LOZ+0jXfkpuWOmWwjw5SWZ1Hj8VO5NMQ3kdg8GczXB9XZBMf+Dff/mP6Q+Cfdb/IHZcoFVtOiArN4cBv/PbfwtufXDTZbg27AFfpntl1nPC0BFxWYmrIoS9y3HedlceCdDV68MjP+wwjTIu5I68dykhpZ1ecCcoqq1dgokmZq3iL1o6zbJmoSaZMmqo8cpCFbToya4vxMJlLXO7Z0CNSMhlt6mlkJhoBa+lzw2g2fKv7BjfziUt3xeJqRrPB50yk5Xaz43a4ILiKaB27ZWIyW5qjw1eON7Hmbc5UqthpIG0bJINNBZiKe0KqB3qz5WggjQvPN39Ib3c8cUecfA2qmp06vtvuGcKRLXChM6O95JV8QKqEaiiRY2dXc9tcktKRQTxXOnA93TBLy5Qb7ncNvWzIBlp1zH5mm86oWL4nXymvRdOyW4482KcIgZBbFEcrI8YkoqsJpsH7UpAvrsImZbKZyR1wJJbsaNJCJ0e87Fj0yChFv2PUojlRpUiySpfu6aurNda74pBveTAXBT8gNY6BOkfEJCIj50e36ooqMBxxSiGzr2kpkYpn5zu++c//gBea+Op7z/iV3/5N/tIv/Dob/8XvXP9VWt4IKU4kNVRT4L6+4IEtakoHrRQ4E4t6gpTwedRS64Qh8CBXVLIQqKnzxGhqJtOQTXHpX+ePeJo/5tLe8M/zLyLGsuSaJFtyMqWI0Ilr8wm37j2yWDRWfCP+PgnPFLdEWyM5EaRjF3t2cmI0FdfpE5I47njGvSldNwX6HGjiTKszjZ3YxJmrOfKRvyKow2TFScJkqHShYQQLLiUu4y1elK15YNQWtVDHhSSWbApEImlNTi37OBNs5sF3TMZjYmS2HY1M5FxTMTKYDjUJYy11HnA6MXPBiUvuzBXBGHqKUN5qokkjT+I9TsGaiSiG6/wWmw2djEy5TFSSdUSNpXiSibdygcmZSgKj2dFK4DK8ZWJLQqhXWUprBqwmFldzZEtDRDRzGW/W9sHCOV8SjF31Zq7IbbJZAcYLMTckNZzcJTkbtnJaFYwlWN4zMduKKC0ViSt9QHOBqVsNZDGYnFCTqFjIpuJyfoWKIUpV0oBEint3HYeXtp/SMJOp2KaJLQNX+TWOQDaGpB1VNmvhDbPbcsi3BK3JJjGw42T3aBJyMmTJ7DjiJXBItyWVJo+0mum1JEMkFayObGRCVdGsBFcxq6NaMTaVJpbHNBtbIzQEqdmnB45cYFy5tzkC2zjygk94ZkcGrhjY4TRRx54gG7wuPDQXnK8WrP/iR6zwZTH3E6/Y12jl8UlxdgGBqJ9Gf7x7k8Aj26bEkXR8CugtZPGWgZfpjm9+/45/Wm9YWkOWT1Mgdnlgmwwhh5+qmNsfLvhac8GvDr+H2QXe8oJOJp4tbzj0J0QrCII0Zd/yqXnj0VH7KFjPoJmdnIrTSgKBS0BIdIgMJdcxw8mWm3+kY7Q999UlzqSV4m0IWpWLgPOE6Gk5FxZ4LHwf1LPYhjaPzNoRJbGYFpsXnCYwgiHiTWSqhO91z/AxsyRHFTJRPSYnWk046ZlyS/SKBos2wjhB33WMwYHdcBWOXIYjkiu6YUGWC9R7Ji98r+vw2jM1nl3zQOUMix3J+Y5FW/6odnxiatpqS+JAE0/szYln/S1DWzNLS2xANFHrhDXFHt8NM4vp0Fjgp0mEyZrC4NMZkwL1ckTiFd5HcjYMWiNclDSH0BNsTW+Ktgeb2HFmzz0bP9PGE9+XTOCauDLiLIHFV1ylO94PHzPIhtk6+nTgLNsCmbGOo9lykW6I0nDMDYPZFmaUOVAxEWSDaEbweFOwIwUj4NbjvGxsFjbAAI+ATrHk3DDJhs5N/M5v/bv88i//23jjf6pj/MtVVmUMX0+O31sScj3i6ZnNE4KWaKmLdMLbQK8dThJeMrMp3kRB6WXP7JbiWpSKOo00ORCNJxnDDS94k9/SrMLxBUtvW3ZyYq9HvrJ8Qh0GTs2G3o6IUwaxfMf8ebph4iA9t1pTSyjHeRipJdCaex7sc3rTkZOHVELns0CtiSf5ASvKJo04SRzMA/2c+L67ZjSOCketgZgNRnLR4GpmIwNeZ57lwJ3sGENLk0YmU3PPc2ZX41PmaIQdQ5EDSCTj8F6LCSKDsTNbblAVWo4k4/HqibYEHN7rJYUmWcZzFUVachFOvD99yG3zggdzAM08N5+wN7c4zTzNHxfhSTQ8mAtm54mUfGrRhKjSmInZ1JicaXRk9C1zcszmwGW8LekKqedglEO64zvVz/HaPqXVgVqFJEIUh0jCaMWEp9YZHycaempdOLtdAf6qsklnmjgRssPnhBFlcI4mj2hWtvEBHwOv6ycs0jBLVSYoCHf2gi0jRuHp8paUKpoYuasuERK93+LzBK6liQOzCDYJmzxhbWYwWyaz4Y25JFFj0oyh4I3RjNcCWbZ24a22ODXUOoEq0dmCfDWWOe9IxrJhZJ/u+a75ajFiiaF+jJpU8JLY5++z0PAkf8TJvMBopDaJRR0qwkTDQsvimoJyiTObnPBm5jLf8UH8NmThI3nJR/Z9QhEzFEOFCrPZcpsnbP2zKbu+LOZ+wrXQcWLLYoTISkN/J+b+FEWy4cyl3q2jxI7zo+ZZDUigRtnqiSYGjqNHVXHiqAkkmTjoDX8+/R6+ff655IYfZ+22B/6tf+c/4PyP/h7fyP+I71Xv0+uW6pXHv01snjs2ckL16Wc6jKsFXwKOkSweJSBUsHpaw7vIpvI3C5mjdIy2IVDo6iWfr+LkLBt6NtpjUGoNpJRpmfEpszEzXl9zY96jGNIrfBrYmBNJCnE7Y7BSWtmb2GNsImbAGURLRmFrMrIMzKZmvzwgrlzMrKnKzjEpMmUGc8E9nrGp8FkQ2fHkfIJlQx8EUc95E7nZv6CvLDaN2Lqnbe9xmnAaae0DjEpdN4htSB7O+cDT+Akfm2teNZe88u/hq8TSWFQC2IjEpezAtYewoTEnXvtrWp05hJHZOTCJrRzZcYeeHEO35011jaojZmWWmrftFU4WVOEyvWGpKhbjeCXPuMo3uOzY2JFpmbFeuaMuFyTJzLali8WC/9p8g8WWKLuMx8pjFNPE0T4rN3ha2rUQR7aIZhoZyw0UYeTAQhF0l2P8s3zCLZ+moCjRGOp5Blq83dL5H633/HL9+Oti+xIf3uPjVPGq+oDJtpAUqxVNmnnCx1gZeWXeK50tEm08Y3NgI6fSkUkNQQwbXchiWahpZGLRjlf6Hi0DU2658xcMbFCdcFGYlkuMUWbrGW3FJFusWBoWps6z5UivDVPe0BDYzyd2fuBD94Kz2TGbhkomzBoIr5QYv108sk9l8xOMcGs2vO0u1yD1YjAyEvFMZAwOZbAdOQeGvKEKkUU35Fxztp4dD3TmjNcSWWdz4CC36Jwx9kDmfdRANo4784SMZaLBF9AOW848ia+412sG3XHvL6nyQpVHWnqimrJpk1LAjOrJqdwjjvmSe3fAGAMmlQgsB1t6SInJVLzIr1Asb7kCBZ9mKi3JpCM7vM0QE7OxRGpaM2ASjPGiJCbknuAsSWq8zvi8kLVGNZOMYZQaJ0pmwmRKB00akhVGWqwUp2ubI0YXVC1N7rEaaTkympZAQ51nTFZazhiT2NozLiyc/CUvwhueyB1X6Za7sOWNf04TelQNJg/s80PZIGpFk2e2+URyhrPbk6Vh0BbrGuo8MKaWHQVgbbRojJMRLnlFoOUQjujK0jtLy2I8HWdu3RMG85RoHJVOIC0CbMKZIJ5GRi54YNEzdQafXmMUsn1gzDX35orRtytP0WLyXMwhJHzKLGHPXf0ckxd635HFEkzLTAFUB1pGIq+Nkobzz+R8/7KY+wnXvllowpm+3gOBUqA9subKKNVrpFki29gz1huOFt695JLfhT4XzYBi6ivuLSzqmMUDDQN77us9E7eELyBo/M994xf523/n7/EH/9c/5Kuv/5AUazYffBX9escffed3ye9Aro/dwwQS2HFfLoIiJArIcmC73rT9WsgWyphoGTer1mshV7p6oxT7etDVHh5L5A5Z6DjxHt8HMpXJTHrLaPcc6UA7bIpYXTBOkZwZ6KjyCdRxPd8XIXJn8UnBCSkbhk3LkGvUea7SPS/lhqgdqPJK3yNUni70nP2BSSyxjugUuK9aqpTJXaI3HXMdGVxNnW648wcazdyF93lwe2ar7GxibxeMZFojVDrQcMJKzcU4Y+wnvKpfoHUmSMWekZ0WXt3P999hGPac26f02fDGXGEIRAyaI8bC4Fr61vNhfM5buWbQDU+ne5xb2Jp7XrsDKg0TFaO0HPQWtYUJV2vk4G54KkdyMuhokPqS0Sxc2nsSwllaXtnn3MkekVw4STpTE7Ci3NsXq9tYV/6UwUhFx0NhkGmCrATTkiQRWc+Jd0koK6PxcXNQTgBiKuDWOszsu09zhr9cX8wanOXBv6SS71NpLEHvqYQPPdgNi/k6F/ktL+JrDImzbotDXROVZiYxiM1UJKqU2S63dLllMcXFHPKWZD0ns+fOHBAyD+zBKO0SuK8cRymSgSSG1kR2HLkIJ17LUxpduLdXmJi4q59ST6+wPuM1MRlB1XIRT2yWeyZX83X9Ns5EbswzTuwxpozobv0lGCnXUKP4vNCsfZRRN+U4TsJBHri3+5IzLCNnt2UbYVGPSRExDiPK5B03/gXRFMZdE2cwC86UDaQhsrd3JFou8i1RWm7tM5KUFAafiruyiyfu3QGXEg/2koGOXjrUFNi66FPObgNiCWq4CrdUJmEkcRFv1uJSGaxjE3tGdqRcdItKSxDLRIuVwKg13hQdYSMjVcpUTrnx16hR9npHWjFTOdvSO5SMEfBa2HaikcUc1ug+JSfFCKTsOGvNk9xTpSODrVlczYfm54jJkvE0eUFXgH3KUq7PyWLEsLhilhtdVaYqMTE0OyQrIobJBEquh8UGQfsBZwWlIlYFSC2qZSIrJULsxj5biQbQ6MRFuqPngLcjo92yULNdI+beOwAAIABJREFUJu7tBdYFGmaey3eZU8NJdogUQ553AWLCy4IKLKYm5JoDJ1omuqXnlgOTLxrhhVjcvaI0eQF1mJRJTvnEviCLoadskA98xFtzvRpULHs9s3GRqX/4mZzvXxZzP+HqqkDDyOAvVw3QZ3VmEaPCdXzDxTDy8jTy6mnijX0E+hb3Z6QpcSQ6sw0DViJLbpje8eoMo2x45Z7z8u2HDGHg0Pz0FPz333+f99//T37gsf/3//49vvW938WbM46lcJ9WjARabOTCTNRmNWcIiQQaYXUqopkLOePXzNXw2KWURzt/aZMbiTQxskhVHKwa2eQRa2aOckEwcG+ui5s1ldf0bC8KSNQo5BmRDXVamEQ45ImtPxHSnkO8h1ixxJZQt3S+x0rmcj7jbeat3yKqHOstMlmWrqVZArZVqnxmF45ku0D1htEbXH3Dc9fzLftNHnxLnGuOvmGSjns5YFIqHDcz8GJ5Q+PvOIwjshhwkbFpmOoOnwN1nhloiGo55itctnzLWJbdhnqaWTYbqhTwcSFaD3XhJp3MDjXvcbY71Bg8gdkLrR1BE9kYhITVGcPCmFusUciGkx6YXcdVvOegR4KpccvMm/oJmg0LFR+ar/HGPmGUzUpLz2tnQ7BEJvz6//ZYig7FmLRKzWsqZnyeOYshiUPVlHPiMUXk3fEhnyn6A/t45ulwSz0I8zT+1Mf1l+sH1ziMyJLJuUFygfEGqTBm4cQFLhc+2xw9DT3JVhgRRjbUORBpkJyoiASU63DHC97wiblmI5GgNSYaLtOJWFUEhAfZ0ejCWBeNnTGR1s40nJnZENWuQfOCpPUmOxwxojRhJOc9k2/IGjEa2emZJ/aGWSwHc8+DlgSSNo8s2ZOMYhAgICjbfOYZn6Di121DSZO4s5dIuifgsSqgQqWZwW1ZrMWvvuqWAZdKtmy3GFwVsClhbeZkDvRiqAi0HFGE0W5YqEnZs4iQjCPZCUmJvdwza8UgNZOpQSoW11DrQpvHwuDMWyZbkcWSbM1F+oSejqiGVmfafOTBbTGS6G2L1YUgO4xmutQTzYTJRXoiKkStaZYTT+MRta855o5BhGgdo9tgNWDJ7NKRs9+ghmJUife8TB/ybfl5FldzZovYYnzZ6MKWW7zM3OqOxdSIgVE8yTvIiktFTFPLQsAwmA3RW3qzYUqePfeo1oymLqgWVayCS4FgK4I4RAwYQ18duAxvsDrjdEFXo8cmjWxDz7U509s9UTtUS87tDTUP7kCrA5aAZofVIhkY8gZrIg9yVbptRt+BpidqGlmQnHEkXFI0V/TmwDYPzNoxm5ZFtzRhQr0lMZCloiVgUmS/BNTX3OeOaEvhao1CzMzSEI0lmhqjR2KtjD+A8/ri1pfF3E+4fNXQLLc0BH4wpaEYA4wo1ghmEXbpyO/7X2JgT3nJCwl7q2cu05FNjGwmIXghVA0NCz1FAJ5w3OpTUjr/aOrJF7AknQliWcyBSsJ6+111c5IZqNcujOdTp6t993nU4GVGNTKwpeTxKaoLTgUrA2hVIJiq5WcJJKlRVxMzDFrRcqS3TxlomGkRo4XUnQMHvcXkhhNbrCwlXsgEjs0WjZk5NJjFEa1Bq4Wzr9BkmNVw8iPIjjHvECI2LfRNzRIb1CX26YSJPd70qFpCVbNNgcpkclb280S/j1iXeMjXyLwnVlsCEWegiyP1eOZpnjnoTM6GV7yg15pZHc+mO7wJ2FjG0W/9BXWKnM1LfFB2boE40fiAlZnWCJN2aBB6syeo5W11QTYOI4Fness3wx9wtgd28cSJHdk4xFhMiiUBI3uSWKoYiQZqn/FpIMqOJp255wKniSBlTF5Qoy3mnTtZGbRhYEsmldErwmIch9zTxjOz3fGefsxROs6yJSgEWbE3Iuux8hjMPa8FndBoYJ8euF5uERbGpf/ZHdz/ii4zvKHpv82TRjjKjsqdOckFnsRZ9oyy5Z4D2VQ4HVETqTWyuIoxR5zOJNcQM7RxJhmHG4RpsyGrIi5QqfI8vsLEyNFu8aKo8UwIyUacDczaYHLHNp1QLA/5gt51VCZSyYhKQqLi6qL1HPSOW7lmqlskCbt8yyEdOcoVSdZwdQyT6ciaaDlicsaZyEv9EMnKpA2bdGYwpat/NDt63XOudrRpwGnA5MAkLdnVCCOWQJvPnGVPNBWLrcmSqG2JgYpZqFkwLPR5j5dErwe89uz8LXBgRPF5pmNEc+lsRluMXi7EMkbUgY5TSUNY0aNdPNPKgMuRS7kvbM488JH/ChMVp+qSgcdiTNmknoqZy3jHwI5FDSM1beq5jrcFCWyUTubiIc8TPmecLgy5o00jNSPbeCQagycySkeyjioFnI20DGQMXmeu81v6fFUQRlRMWnTdWRMiDisTTZ7I2TDjmGz9TmZ9by0jHcc843VikA6bDbOxZLEYE0liQTMZJYrw4A+MpmObzizisVk55DvECKOUxKWkFVkbUp6xJjFKzSQNrc5UUhh6Y6qpTaEm3OWn9NohWjh7FqXLR3YycNIrlpxJVLgMk214K1dEV3G0e6KpEVnYc0eVIr3ZgVqSg9kkJjru7QXJmnLnSieiOowKolDpRJsnrIJK+yeetz/p+rKY+wnXVFe8cZcc2VCiiXS9YT0G1QTqFGjnmQOBVk/AmsW9JjBs5pFn0y2bceHFFHh2OHDV3xGahk9sCbXe6gNP+3sOV084VD+7bErfJWovPJtuaNt7/lC+tpobShdOH+Gvj6GN5Q9Z35eCzpHX/ItT+Ro1TDQUuliFZ6bWAbIhGkirw8kSsRIZpWWUljsuSXgMkSgOHxeMySzSYSRiDaRsmJ2jyTDjGM011hg+kud008xuOZOamtad+f/Ye5cfS9fsTutZ7+W77WtcM/Nk5qmq47LbZbq629ht9cgYaCEhJAa0YNYSjJkw4f9BQvwDCIkJA5oBLSwhdSNa2O1y1alTJ09mRmZE7Ot3ey+LwRunGrdpBFVlV1F91jgUitD+9t7rXe9vPU8ORRKtrmElmaPzmLFsvzXzyFDXzA687/A68MlhTzQeoxPbMGDsSGfestPnTNnizUhDRkzkMn4kqufK9UgjTEDoHf3C8qcXzwmtMuP5Vv8FbZhZjQNnWXDuNuTJc/INtckknVkSeD19ybFrcDJS5cid2zLYBVYsUUrIN4onO9jPW760r8gi2DSw4cxLfQuS0SiczA0jntFWuNSxjocn+0Ogt9dMUjOJweaRgEW1ENe9zBR6U0fNBKLYbBEpOjYoardWBqKp+KDPEUJ5bU1D4sRMy79YoEn8VGMngmFCUMIThNXEiWz+ak6r/zqXtT359Mjp5iWNHHCSsNkQjUFS2SdObGkZ8ClxUkUcOAlkC1XInLPHxRmnEwe7wPiGB/8MyFzmR1b9TAwtCxkZfUuoFGuOdLknS0nXnumYsxDzJZVEopUCj84nnoUv2cZAyAsOfstgyhWWGnCSn5K4lov8yDvzinvznCCes6tYpj17c4kls8l7XqY31DryVl4zS8dRNySxNPLISk4gQsyWhZ4IqWGRzwxVhcmJYDxVnMpBI828mN7wpn3FKA2TtVgpailNM3t/QZcGVumIIxHsikk9a72nMzU1CcmZTTzQmBGMckgrkvE0MmHMiMaESlWuOok4Em0+sx13rJsdZ1mRonAwjpkFk2tL8ycJybCdjoy2xWKYTc0mHxkIvEjv8GSG2tHkkcF6tnHgJn/kc8r1rgE26YFsLJd8LNJ4lCFsqGVmyZ7RVnytHKt1JKlnVsfJlvFFwmHzRDBdyVY+LbBNpkWtoCoEEqKRVhJZYZaWKhfm4Ha+40N1iZBRW75dbDKsxj1WBK0T2QouFRaCf4rjmGS5zgfqOjLR4YLyVfWcmUTMDW3qUVVaBpoYsQ7S3JbNezKz9ZzMAsdMy4DIJZGWjGcTd0j2BdKcHZ3peZAKIdGmM8kYKhNAKhodeJE+QLJEUxG9oZWeSSpSNpxZcWl2bDjwYK+wGohWkXhm2fy/kQb8f69vmrmfsYbTCWkrKpnpv2auCayewJpVDFz0R17fv2GxPeGYcJKIBJDM9fyBb737wO+MR373b/9Nvv+d38ZVDZ//t/81F4c/Y9PcU5uJxQlWg/BHf/Qf0FV/dQHxy+ff5bP1mj/t75koXLZ9teTL+iVRyjXbv9CVyU8nLHwNEFYtypnUYU3G5UhlE5ay6GAwWBmZdUGnPWcqTqwoDlghiqdmpKbHPO2C8ZSkyD4z0tHksbwJ44liEZjp5ESlkQMbIHFIl8R55Fit0Se1TvawigMfzIo6J9aT4KcdZxr6ZAnqWemZzhxJ1LzbXBFp2MmS3WNHj+HUtpzqlqALNtMD4kea+RFvDa/mI1fzPZ/Hl+x8RWprQpOJviblyAd7i5fAi3RHIweCgyYfC+jSKKEWmpS5SHtu5SNXp5ofta9QnTHOUeVAFI+RsqVVshrC581vcDYtomVhpssTVUrM1uEkYxhxKuWK1yjrOND7isHWjLYmP32kVXEk434aNEchaZnEKlJgqk8WkOlr6brJHFizCicqGenkIzv3m/S6LA2bhqLywv+lRYisC1QGoneENeT3E1l//jzoN/UXKzYtd/WCfJ6ploYqRFa8IQVbrtidxeXEsVoze0OXj2QiN+nIo1yQxOJyYLY1Y+yItqaOJUOXkNJwVJ6xqdmEPV4zKSfaNDFi6X2HiqW3HSYZgi3WUZsjjY54CdQ2cKxX9HlF5UayVXw6UpsFZIM1Jed3TGXpJxtHy8CcPE4yjRkRTSVnmh2TXBGke0Jk1HQcytSHQLAdo6mZxZXMVCpu2GU4ISpcxj1kSMZR+4EVj1g6RmmRpDQ6scgzk01Ukji6LSGfuOKOqKuyGZqhSzOeiU5OTOaiQHxzIJJ4Fb5i7xZMUrOXDb1dYFJkMpYhO+7bS6IKZ5ZUOlJppjVHJury/oygyXHkCjsHuvNIv5zxPhQfs12yo0atoZ4CxgYqGbEu8mp4y1zVfBVW7KpbZiyDdDTpyGQXRNuS1NFoz4vwlgd/UXAcNExzJMqS2baIZOo8lwaeRMASTIO1xb6QskdFsUxYY4ptIQtVmtj0Z0Zdo6alTsrCnHiQroB2VelyYBvu2bFFrGA0s8yBi/ORsWuZvXBgSaWRWTK2mtjm99Qp4vNElTKiM9HXRDuU6WLw+NoQxNPlgd601DnQ5ZlWD/SyJtLwxne8mN+xsgcmuWBnV5x1QW87FIvXRJPPPI9fouq5nHeM1vNgLgtRQTMhCtkIzkQe9RKnmaglq9jrhsdmoO5+zk3Gf0V908z9jKWHA82iRfWWnxodNCJR+fb+Hd9++MBnOvA3fuO3+Z/v/qxcvmoEcUUzbzONge9fvuQf/Lv/0U9/73/xH/5D/sn/8t+jH37EsVthXvwOf+uz3+Xv/Ma/WtP1i6jl9gX/9t//L1n+8f/An/zgx3x2fMf/8arhWG8YqTjzNejw66vVsuxQGrWxgCCpibbGckZs2XWdaPCaKXJlsASyFaDCoyTKllyXTyzlTBBHrcVpR1bQiSz+afIXi4NQWtCISUIrI55Abxe0Gjh6ZZtHqj7S1Bmthaoa+HR4x6KZGPMlXfDEdGaplgee0eqeg+lKboeR0bS0aphMw7Ce+UqumMThZWAZd9zIR2qZaPyIxeOXEzKOTH4mTR2n1FGnMy6PTM6WLFvKvK+uWVqL4NkMPU0bsDrz2G5w48gpbejDggsG2jxSoxx44GguyLlmFc6oRDCWs2xQ1adNXodziWW6x9gBaDASgBZMYB33zNbzpn1Obz1BSw7RklBJGFtjMSx1opeM0aLXNhiIhqU5YAwcJKNag85MLBDjCJVFgzJIxciCLMX7YQR48kL+dCqHASYQgyKc7ZJRK4KH8+nhr/T5/texxlyzuBipVhZcuTl4Nf+YvdsQ65oYMuu8Zzg2TH7J8/lzfnDxOyQxBCpMhlojvXPlpkEGUtPg80yl0Nsaax33csO+WhMpP/coFQ9uW3w2UmOSIlK07U3u8SYjEUxWZGyYa8toLGRDEmGSDe0TdHqjO1w23Mklm2EkSs3KHGjciSkXB3FHz9Fe4zMsGYjZErTCkrgKB2ZbsYgHTlKu1Y5+XdhnroZoWecRksNMlsvQs9a3nFcNTmbu5BmTVtQ64VKmtQMdHm8DOScwmaNckhCqHNCcngSJS5Z5YB0OfMJP2KQj9/6CC/lYOH52RZ/XxRgAiCkKq/e2YYw1S444K1wNj4ytp82BKI5unhmnpkDVn0gKXSie6dgJoyzo3aLM+hroTE/EEkP5HD7OLYemI4mUSEY+k/OKA5vyWsnMrEuu41uyMcxMxFyTUosHWjszOyFSc8YgmrhMO7J1jFKxt1sSHomhZJl1z9IOxNjiQqaeDdb0SFJqL2zznj57rBlpTGTpH6k08nx4ALGs0oF7f4OzmSE7uhjYNRc4GanNwKAOZwIxe4wWDJLXxFL3VAQsE73dcpV7HmWL00CnAyvpSdkysybiyeXrjKNb4ugJ2XByK6JxaBaWnGjCRDQNfdjwKrylTiMpW27NRx7zljYPHGSBiudi2jOZGrEj0TnC11D4MHLsZ3SekerXw836//tq/UyblGi/DrIlGpl4lh75u19+4D/5w3+H7/zt7/Pm7Z5/9D99ztlcYOTr5YiJVTyxUCXO41/4vZ+9+ozPXv3nf+3/Dzw1dP/eP+T3fm/gv/tv/ivu4z/jOj7j4BYELLP8y/wvR9YnJx8l9J5VgQqjJ6wK1gys9MyEo9WRTkZizgSBbAxZaryWRm/CI1rE3KSITTCaBarKRnuMFpTLjf45INzl54y0GE000jO5GpmV2VnaEGjNgFODjROtz7yY7nlnHb1fcvId6/hIjhm0otHISvc0eearxbcxyeAl4uLAQiZQGPOCTiM2JMLcURlLPWUkOg6jhesI1jAoXMYzvzV85G26Lqyo2RE3EePK5Kxqd+S44lZ70ExXncjW8kP7KcQKzEzt9izZEXKhfy1mpbcV4iLZGJxmqjxgtKeSnkTFznhmlkQt8ufaZ7IoR7NhEENwDUYDAYNhxqsn2XKKzqJkDCIWxbPOBxbpERTem09IdGSZSdoBhiwlD3WUDclaIo5MJFE9wYTj/+Va/mlJCAeaaeSMT4qNQpwTyX4zmftFVxWPNGZATIvTmTMLvrCvmVzLWh55U7+mcmeG5pKLcE+/XLOYd8y+pSjVFZcMjU04yfR2wzo8YoGX0x0/6W5RKwysGdQDhe12ci1RLD7NZANNmp4StmVJoU4nqlzYXqemo7cLUJjSAu8GVnJCc+aA4rLSmyJ1X/jEOp6oZKIyDoPFm/npuq/l0Vyz10ydE6+GLwm1p0kTQWv84Dkv1qx5wKiBmJl9jajyKBds45lJGybbM9iGle6pOeN0ptJbJqmp7cgqTbTpzKlZ0+nAZDpsmjHWM+oKCVIYabbhY3fLintUKqYcWc0DaiGJL7w3lHXYYTWDJAI1mFx4ffnEZj6yMR/odVnczHScZMWx2xLwZLVUVWbJA05HFrniXq7IYujSCeci2/TITMtoa1w489hellfWlhxyFF8uVoJnrh2NTRxkxeV8xyINWIFZhEUauLcLNnHPmYpaExlBJLPWM1fzA+/8LaJKxqHZ0jHRkNmmA4v4njx5QlwwtY6Ui91owhKeMpCnasFKDmzNR/xQsxgDd+mWtSozivGZqSoZ6l5qRAWRWKDWLKg0MZmK2RQQc1LDMXYc/CWVjljJrPKeKbWsQk8WwzY88L57zk4WIMU6ImJY2jMTHU0aSW7NMa7o3ZrlfGaeK3IqGeZ7f8uFfmSpZ7oxs64OvJdnGBcxqeZgbgipKcinGDnkLfHYoyF808z9ypQzhZcmM2cmoC7bM5K5+NDznU9/k8XqgouHj5xjy4NZPfHYypbnaDtSMyDhV1FRpAx5jaaKZ/kdMy9ZyIBhZNT66Qv66UtawDGhasvsTSAUtTJJSopuMhMK3MuWHTOVVV7PP6E3Db1esWAHKRFcxeBWBPGM0hJdeaP7rLhpR/QdgyR27jfZpHeIU1Koua8rVIsSazUcmfwCdCBUNQt6JvV8Od+U0Xw2SD0TTU3fNMQc8enE9pQwLUzzlo0ZqPPEOp94OX/klFecUoNJmVfnB7ZyQtWyr1se+xfMix3tdqDlETPVzFlY2cx2fizomdox+hUZZTALUjZ0eWY5DdTVyCKdSanB5RPv3AvOTU00DY0KyRjaPBE0kUSoZC5wEJmppLCaKh0wZNRYdu6SmC1kaF1iPT9Qh0BTB9655wwp4mJmdhbrhGJinRENRAVnEkmKx7U2jlt6bB75yDWCx2KBkVkWFBiEJ9sjE23BzapHJGD5uun7ejKXgYDhXK7aUvli9vvMpJnN9uUv8Xn/9awmBZxN4IUv/Lc4sMGaicb2jDnTm5YqzQWTUSk9Nb1ZcdQiDDcm08qBF/GeY7VkNhSH5zzi6sBNeuTObOmNEKSm0sxkLZIj2RqiGCRn6tiDZC7sI7OpicaiClWc8MBZoM3FiqBZ2dtt4bTJjJUJ83RoHLRiKWUKNZsGa8/k7J4YecWHCYLVnthYJBoYG1qntDFjk6EZlRfdW3ycudcb4jlw7DpG71nmQNAKkwWDZ9IFDQOv9Uf8c/s7jHQMZkmXTmUBQQfupWamw8aCzzAqBdGjjsEV24DLGSuZrT5Qq/AqveFaHXfynJQNIVWoUwa7pJLCcjNZmE1ZvNjkDyRzwxRbVCydHgjiOcgF4ouSbPKOvdkw48nRlkwfZ5wKD37JiY5du2UWWzh1ObFJj1ylAw/phsrO7K1H8aipsQ5e5LdkrVD11OrAeDZhzwezZjQNZzrqnNBUcTmNrOyf8c/M73Aya0wOXEwfeOV+TCORpR75yn5G8sqb7hnOzBiNRAw1PVaFKQeSFnzJhTuXxnFl6FkQWXKR3nF25XC/1YhlYpRCFghqSKJ4ncFkcoaUS/5xtgPWzMUYkVsWOmA0c5E+kl3ZhC6UG2XSDtKRNk14E0k4RKHLA5Lganqk8lMBT/uW2VQ86HOuxh2npmEwDYLFpYSZegZfY0zJCtpoef3+QF6tyMb8BQfUL6K+aeZ+xpJYkXPCaWYpkVnhRt/x6fQFUnlSVzZW2jBxpT2FhZ+IGJb0VGkip4p68aunLeqPE31vOHZrNnnPHVegmSjrp83VrycupQL1k3czYZhAPQktK+IYTmzwcuRIQbOIChfmzDZ/4FrPzNS8k2ecXYXiEU2oyUy0OCzKRBCLM5lsHIPx5HxdgrHOcJSWdToymxpdeNxsiZPwKCt29RLE8mV9TRvHctr0gat5R5492MxjtaS3iRvZQZ3Z5jNhtlzmBz4bfowVSzheEmbIY82ue4F2gZO5ge3EGDeIHTGTR5vETjvOdcOVg+v0huQ9OT7y6CqiKn/uP+VeL6kEbsM7nvfvOcqGWCln0xCNsHNrulwxWaElFYK4d1xPD9isnKWmksyQG5KZOeglnT4y5gqbFZ+Vc2x5dop4N5FiySSOpmIwxQ9pNFAZi9PEUs/EbHk0vsBfSdgcCTSMYpmoiVpWe2pJJVkANIyI+rKVxonEqnytisHpRCtj2XClI4sBagyJbAp2xfmZhWbq1c1f+3P+614hOvzcsZgSuRKsUUQ8vS4RyUym4862QAK9IFOTY2KwdYHF6sxzvuJ5fsvb/IzeLDjaNbOZuT6fmapFQVPgELE4e6LJJ0RDYW+pKWgTUY62Y9BArRHNcLQXDG5Jk3tElVk8kYpvpx9w1IE2HhGXkVkY2pbJVgy+YTMcOflbHu2W2Tq6dGbJmZQMQRp8Ls3fgzyjcRPX9ktOtubedlTzgcaeWZxPXIUPaOh4223wOXBwHbXZMwYlzXCQJX2q2buOpRzLND3OzKZjEx7RYBldyyoMRC0opphbTE5ILlukk9ZM2jFYeZpURiZqPB1eZ67yPScWJJOpYs8exccC3PY6ManhxAWalHfmGUezZTANY65J0hKyZ/Addp4wGhGNrMIZSYZn6cCz6S20Sj87et/RS0M2FvLEJgReD+/p5MzglwxRSE2xM0y2Yh823MQHKtszzEvmquE2fODWvUfNcx5Y82i2nJxHI/xQPuU2vOMF95zNEZ9HluZMI4n1uWdiy+RqRleet6v8gZE1isHmsiHf6b44g2XFqbrhIj3ypXvJyTZMLLAyc5U+MuO51Hf0uuFkDQOLYpiQiS7vuEo91THy2K1Lw2VrvFFsnjn5jjpPhMqwnA84Jr6UT56YggtcPGJj4sbtqePM3ra42JK1YbANySiYxFh17MyG6/RIwtPlgJkEbSxOzgTjCF1LEkc05bNQK2F3vcUtVyRjfuHN1zfN3M9Yl/6WV8c/5n31jM6cGGXB6+kj7WRor7RwZgAjsDrMbPRYhOoIjsA6DVwPj6w3v3rU+xyhSg4/ZYIKEWHPkkxNySRktvOu4EV8xYxBxYHakpkSeVJ1OSwTKo4zG1CHl5kolkdZ03KmCgMHW0CjlkwgMFDI2UrFjIKpeKxXZFc2akWUlRV6WdKGM9HWOO5RNVzNO8y85W55zegKuV1UGP2a2TlkjlzpiZozR7tCW0OrPck5mtOJnVzj08gNE6/Hn2BjxaSWBSMXyx0P3QZxlr1sGLyiDVQoq5gYndBLxxga/DgxdAtCKmFbteVKaHOOfFwM5JAwajjZDUeN7GmwYcS5iNiRYK6ZcmTW4kTcaAmYb9ORLgzsTUd0cDZdAYEihNyxyGcskZRrsjq+rGsqK9iQ+WS+4/r8gYf1BWdaBttQayH9N/nM3lxiNGGJRVxtGt5Wz55eBUPDwFk6otZlM1IzVgNJDGV37WvDQwFhZ2BSWxKXcmakYtYOJ2UT7d4+o11nbt47doePv8xH/tezcoMLC17OB/65Js5auIHreGIlJxpN9NKyyDtajRzNko/2BSMLDJkunxGr2BBxKFfxHQNbgnb8oP0us3FEicXfa2CcX9Q7AAAgAElEQVRSD9pRmRlvMjZAeOINOsmkXJ6TYDa0aWSV9wXU+pSmjS5z0A1JDQd7iZeZxp+4jXfsFc50pAZsFi7mAw/VlnU+sDUPRFp2MZc8rY1UOqPZ8lBtSBhGVxFmyw/rz+iGyE+age3jDig4jNE23LsbVnrgcjxxzBeoK894Sp6lnJjykskYdv6SLvUYmVjEEx/8c0gwuhZvJ5xOrPURyUNZ/gAgMpgGL4423aOOsuRlLD5E7u0LYi4H1204sBwsB7/gwYCfM+/ci6K1InORDkTtcdHRmhPHquKduyboAlNbbuf3zFJziBvC6Dm2NwiW2RSYbaJme35gsCtMLoD1hRtodabRgVk8IdVUITBONR+aK5KxGBGuUsTmSGcGLvWeo66wJrHzK0b1hW+QIyQwpqfLA++7ZzBbRm2YjWE2hrfykkbPbDhT03NmyRTX9JMwhA7fwL6qOZklmVz8t4y8jG8JpuImvOeDBn7cfMooLeoNi+mIDwVO/3Z9STNHLHCZH1AT6OTMUS4QDKOxxZMtlwTjwSguJ1oyq0lJ2VOpYjoY2GBIdGNgFc5Ubsbrgd7U2CmwkhOX4wfe2k851BfUckSNcsE92WQCDmMDrVqMF2bvsfYXv9H6TTP3M9Z3v/d3+cn/+E+J7kc8NB2zVFzuB14MD/z+9/8Q58pbWHPiuXF8+/AVz9o7Ripup3tefTiyev/Aiz/4N3/J/8lfrvV1S+thZQ1/are8l0/INIDDEOnmkd//8y9496Li8+0tg1xQ4MCZhKUui+JPTlaLUpE5A5mEPIFOZjo5kiUxmo5JHJPWOCkr446akZmEYiIYhJozMx6nGaeKI1PbQsSr84DVBJUhz5FUZT49vucnm1ecZIWWAxViJy7Tl7zMD3yhv8VX1tCEkb2tGMyC63SHc5kmRL5yL7lzQt91bMMDN2Zg6D2Tc+ykJluhtVPxkc4zs+1IqeLUNpySZ6s9nSSGnJiqyEdzy6Z9YDQ1k/PMZkEdR5zpSOJY60DrDyz1yJDWiEZ8rlnkIxv2XMmOi7Cnmgekec6onkfZkjXjiUxSYdQStCVahxr40GxYmJ42TTzkJWluGKSmYcdV2nGTHvjgbljkMxNrVEei9TgTC55EWs6MBUXChNeA4Ol0hqSIBpJzJKaSleNJKIxiCCQcA4unjdiISC5XeBiczPg4gGmR0+Mv6Wn/Na7acq0n1vOJ755+gnaWpMVrqpUhmJpF6lnqxPW4J9QVlkDNSLKOWcrV3Y08YrJijKXmzKFaY0MkYTGhIZkIRljrEfvE9/KamKUCiYzFL4AkuB4euEwPvF19ymhraj2XjJU1WMkcTEcdIsHUXJ4/Uvue0bb0tkEk4GUuh5WmoI4GOqocMAg3+sAb+ynpKeKxzD1eAss5kN0FB1NQJSt3T29qTLVm1y7p3RN8OGeyWB6XS7yMGErwPSfHyk74mLEmUTOw5kxQxSYheF+uV8VSk9nqka3s+Cx9zlf6kpBrJhFW8YS3gWWeGLJjLxvOssZYsClzuz/S2Ij6iKCQHXVSJmOLaSBnJqm4DBOrdGTSDcdmzegFKwYfT4S4QHPmwW0xFAB5xx6jI3NyPJ/vmEPNRdijduBZ+orglY/mAm9GcrYQBQIMcU22FjWW0TaM1mKql+RkOJolmpRaB2brMGLKGa53dG4EY5il4avxUw6ygVRzt1yVv8lEVmlkzQPP9Qs+pteo7Znsgmw9s1pyMhgTGNWxd4WhWeeZNkZMpdjR8qPlCw62sDfRSI6esy0Z4L1d8yx8JNctCz2yTQ+s0o43VgnaYnFEKQ5YZxKokDTSxR1WjvSsmdSiAaqcqN3Epe5YSE8Kgk/KNu/ZsqNJkWO3wU8TV6ePXFfvOdRrrCgdAz7eM1nHeoZlHll2TXl9f8H1TTP3M9b3fv/vEOJ/xup//cfs3z+SiVx0nr/xm/8Wn373D3Bdmbj57Q3fXXS8vtvzsG6xacfr3TsuH3f8G9/7Nt/93t/7Jf8nf7naZcXVd25Zf/wnhLxm1O6naAlBaccjJp/pplA4QV+bIoiguWyeKnhORCoCGYsnc6DWhGemlhMfzC1T3ZQrPSPUDFRMTNQkAoa5ZLAMJClTzZYjVc5UOTJLxyKMNJXSMnEWx1lqajeCVJz8mvV8YhNnTmaJdT1SZaIRfli9Znt6oE2vERxdGKh1wtiRySxxnZKninFqiP2KPsGhiVAllvM9hGtWzYnr+chCj9STJdeKHCAsPjDiWc473q0/QcLAqb5Bsyc7x2fzn9KHNe+aazoi2StxtnyUawapEaCWE8kayMKr/CWzrZiM435xye30liMLoijCiBNDInMw13SpZ8bT6oCKJXs40XGUFSRYVROesZyy8wOd9rRphFzhiVykR5JUGI082o5IjRWP6ozEzDaPZFEERSVhpTCnClfua5WdATXFWSzxKVoZ8RgyA4kWR6a3LXPn8fnE82r5S3zif03LJhZuwVkbOsl8b/4z3sgNkg32EGm693gTqc1ELSOt9jifMSSqlLhIOy7METFCkycuxj3BVsxVw2xWnLVl5U6s4iM72bBNJx7tlibvwDhaGSBR4N46cZMPXOqRMSxZTCf6asGc1kyuwWgs1+/iqWTk0V7y+eI7XKU7NMyohYrAQs5cyAdOXFFroJmLfeTB35Ktx6phOz/Q25Zn/Tu27p538pxTbImzYaLlQS5p84m5SwWFIpFRFz+V0CeBF+MjJ7dgGw8c4yX11DOaKzp3wlQZKFGTaKSw3LMStEy0kvZ0MtGGmavqnkEcTezBGUwUDn7F2SwKTJmAT5EoG3Z+S2smrsOOaGZqPdHNE0O3RYMQvEU10OiZm/TAD+strfb0usUkT29bFmkAk1nOJxod6Gmx0aCxYlPvWOUDTsLTNq7j3t4Soi+WHLvnyII2K9twJqmlmXqG7hmntKIyI7M2WKNchQ+cp0va+Su+uvyUiOdsG5YyU58N+Im5akim4mgXrOyJCk+TJ8601DoSUsODec7RtRzNujSSJJwXunHgTMUiD0RpwAyQhXaeadJAFCFboTY9kRoQsjge3AJVy4Pb0G86Fml6+oxWbjiw8g98kOfsueDEEpMKE9airFNp4L1NZC2xoI9ck3H0NDQhUkUgj9x11wxUnHzHgglNyrle0WvDzjUs5MRNOnLBjmqIBO9pj8rrqeXT9QUpRqz7lxcKf776ppn7Oepv/b3f47d/928yjj2aEtYYrHNUTfvTF6q6+YQ/+I//Uxb/9B/zo7svMQlufvs7vP72p9x+6/s061+9rFCKmdvbNc19Rzdn2qaE7mdVLscHXvQf2JjMF37FIKsnNMuT1kuEDE8bkcKsrnDksLQS8JSQ8M5cUKdIFkPDiH/CjiigapAsCDNRFTEZI5Ft2PFt/pxVDgy5YWcuixw6ZsiRs1tx9h2T77jIB1zzyDoe6XLG5kwm0viJs1zSq2dhEi/P7zmwoTWBJkPwS+6Wt5gYMbblcpxQ8Uy54hg2eDOz8xtqPREDEDNNnVmYyDkvObRLhIizjrrJjM5D5TjZjk4Gem1ZScLUGcGRFDQI1TjxsHxGlUdmV2FyRgSMBOanDdDJNDxWDf2F4+gbgrSMuqTVnlU6cLRrJlMV3p8GKlFaHRikxTHjVTmZFhWhFcdD3nA0a47cIBQeXTcEVmZkmR+Yq0+YbfFfWizOJKyZmU1LxBBoCSSUBgskmZ8MIV9DgqEcAEoAPDORtcMgRCmzOycDbpmoNutfzsP+a1ymqfmiWfGVCHfWM6hlloYLPTN7hwSDiBJSx9BZjBFexR9zZ25IWoN1TCw45wmmTHYtWYRrvaOZP3Bv17yQO5KB2XwHnwMrPfFp/AmDdMzSUM2RSRqSwO20I6mQm4CrMsEIVgWJilYWlwJGIE6GbMoBpTcdWRes5j1DtcKqYyETN/oDvtLXfOU/YTALgi5o9ITVmd51RGPIlRQ+Xl4QdUEyCy4PJ5wvsYXdsiZaYcHIoBVN3rOSA95kYiN0nHh+eiCkNefqiiQVzpSFIWOERJlwV7GAk70KyziyyJEujaAOKxmpLK3JRJQuzox01ObA6EZ2uQWb2aQPWAsuGYwbuG/WiCQ+uhqpI40cERqMwK6+ZrRbRu2oJKJiac0Olz2v+nc82CtCMpxYIyaxzDuMHVnNR8grcGNpXAN81dwwVg0RcJpZMdIkpTJCZWY+md8xnh1fecAojR85yoLBX5QMs/VchEdmWzEmzyrtWaTAx8UlwTmqPFHNiewNR7NioGHWiirN9HbJQZec2JKSKeZTa1GnTNGxyT2r2NNXC7IakmQel0u6JAQqfA5c6D2DLunyxCeHO368eclQLbFEFAWbWceeWmaiCmNc4cXwbP5I375m767oqahy4tn8kcpEklru6lsGqTlXDavQM0nLrl5gZGZ0G6ItSs6dXPNeKoI3OE2owkZnXI5IqFjGETev+M7DATkHPjGeeg5Y94tvvb5p5n7Oquqaqv5/XmKobj7hd//+P+B3/5r+pp+3rDM8f/GMb/3JC3YfP+fRvOXol6Tk+O7jPVf5zDZf0X7NmdNypWpRRAo5SUgYjXi+Vjh5glZF0fU0YrZ2LgBShVYnPAMHvQYsk62YxZOpKO2hRVRxUvBz0RZn7Ad/UyZU5hmzcQgJRfFpApc4pw2znTDzxOW441QJb/wnOCL3IlSjcOxWHFrHwY+ICThNrELE6T11HVmcFZ0Nl8MO2/ZMbaJZTKgoreu5Oh6owprx7kRfnWiMJV4Ix8ozuyUY4ZzXPJ/uiRVcTI/cuysWeSKLJQbPYgp8bBuqYHgwHc6cAIePgXFcQGWYvWWyNUMDR3sLlO0/1DBoTcSh6nA6Y1RZ2CN1GvASGFmQECIRMRWD9Rzzd1jFM8F0eCI+R7p54pX7gi4GUOhtx4PbEG3Gi+JTJkjEiTJIhz5BgUUCXgPhaw5hae+AMpVLahBpyFiczAg1RiK5boh5xf78DZrkF13qF9yZ5+zljtY8spQz/bzmbLcc5Zou7iAJrQba+cDHZsvkPDWB5fxI5w90nPGSEcn4yTD6Fc+mHXWueZ4fqRd7PvgNV/ktIS9ppwETarRqMFaIpmXZz2xygXtPLvPn1SvOdOzlgtZMpOxY5Uc24YGEYXAdxhgqsdjkSF45csFAQZg0aSYNB2bfoNZCFm54i1I4Yyk7MsrZdHxoniGTZxECo89UOZcohxkJ0eBtJCos7Jm1OeFypMkDmkGz50v5Hu+aa+7dhuTLtrcQWOuZmSXJXCMaWYY9q7RnO++YupY3+RNO3ZJF2OMkMFlhL1s+bzecZI2osuWRSgtWY6gWNMyYmLivrvGSmE1hwVUa6VkgCgs9cjRrkpupwkwTA1M0vHDveeQGb+F5fmDVD8yt0KcFB3/JoB5jDTf1PdEq07ym92uCcVQ5FSaaRi7TAyGsyzt3qrmfX7O2ZxbT53zR3DKLR6WitWe+Nb3nXjeE0NLGnkFuqVW4b2/xscdKQAFjYcgNEgrdMs81U1rhrQHv8apYjXhNpLDkOr6nk5lqnmiCY3bvGX3FUh4w0aJquGs21DJwk98RTc06jgzNJVfjji+qJeoEFaEXx12sONprmtSxmEeohIaebDzdNNI3LQHD2+olN+MbVhbUGBot9pvJ1VQpEUzNu+Z5OSiIIRuPIeFTwGqZaJ9lRdSakQVt3PHJeeCDWfLRdrRNQEKiXXW/8KkcfNPMfVP/N2Wd4ZPvPuePun+f7/zvf8xvvPmchzxRVys++c1P+Oz1H/In/+h/48fDD+l0KA48Mh0nzromSpF6DUXSwtPeNyL56cpN8ExMdCgDSEWdR2btCFoxSI26ilYnJslUBByJ5Dw/0N+i1gGfI1FqBm8LkDhnllJE8jAwxbJhu3F7dm6Bz7D338LPRx7sJdvwwB23vHT3VCnhJ0ewHSYGVDJ7iVzmE1fDjk1SBj+R5xlbj1T1AHZkpTMLc0KqCT3XwCOjwHC5Yd0O1LpniplF3mFSS6OB49jRs+GQb3ApcmKBzwlpBtbuHcs0cpRrvEbeyS0VE71fchXecfJXzMbhaalyT9KWnC0aHCY5NvnAvlmj4kkGqnTPMp+ozIjiUKM4DH05s5KM4dFuEYGVCbTxQL/w+Bi5a55Rj4HW7GnqI71f8NE9Y3IU/AGWrK70bVII/AUFPDE/ceYQiqpIAkFrysTOEmlKKF4D9RjR2KD9N83cL7pULfvK8sF0jLZhObRgEufaYuKZ5/KG83lBXLUc0wpJhpWeWOiJ7AtSJotn1My+3mLVYp1ydXxHa4808wj2xGQhRcsbrnGT4Z1tqKcR8cqSnivteX36kt5t+KJecXQbMIVzdpUe6PIJJ4HZeFyG6/OJRhUqqHXicj7zUW/xIWJNgztvSZMhrJeIMfRVh8mRVRhxEciZx9U10bblKjMZ1EH0Bh8HhtzyRfcpaKTRyCQWay1ntkwyM+aaWWfOsqJrIkPynKqWbMFLZlLL/8nem/zatmX5Wd+Y1ap2dYp7zrv3vvfiRTgcKRuQkBxCIIFkig4SkoWEQAIhGkjmT8ASHZpGNGiC3KNnekCLBhY0aCFEjWRnEZkvXnGLU+xyVbOksU5kpiDTOMh8jgznG51z9tpnbS1przXPmGP8xu8LolFFuM0PDLnDSgRTWOsDxow821suusabgiszSmb63C3EBWaMFHblmW068M7eM+aMjtCrmkl1eMnMWZOBq7ynYmLLAYmFXq9QPqOHgNM9r/UFZzPb8kxbLmzNnrJVuCqT4g2VyTDV2CkxqBVK54WYLELKNbMNC3MnGyZZUUsgG4MKnqfNhpO9x2fD1+0bOhlQBWoZyTrwqjxgp8Ap31Arobtk3t80iFVMpqYJnvvhPbPaoHSkRItNkZqZYgQjIzmB0pEmLJzzYITe1xgUsxY+nfd8NFdsOPO+uicirDmhJNCUxJyhFEeoanb+IyrBQ9iREbwojB45q4qz2jCVget4ofQTjQ7MOi2GzAgwc9ZbdvmEksxgLa5EkjIIM5N0jNKQgTr3uBhwMVJUIlpD9UINlgiIhlB41DUfzIq5KKwYrnNPar/HeX0f/xBDG8Wrz1/z6s2/zE+TB+3ALCaH4xT5mftfwCVsylxMxFKYaMiYFx1dxpJZ9issrv9FqKTHlw75fZG8Iopjr18xc2YqNSPtAg1TI6pARnNh8fCxZQHC36WPZAqzVGQ0SnvqdKGOE2tmEgaVDRHDpGu6ODJnWCnPpD06w5AreqXoa8FnTSoalRy7cyBuZro48O52xzehofNHXo0fqfUjn8YPDLbDRMEGiwkD+MTYr+lfXbPfrhh0y3WY8crS+9dMpmM7DlhX0NEClo0f0HnGuBlZKbb6kUF3rDji0syXyuJ1S9RQtFDnE9ZohMhMTRMupKFC1YFUVRRl0CXTcMEkjyqeQuRZ3vCkr9E5sc17otJEKgKCUoLN+YUOafAvwvhiPDccOacVPq2ZbEehsCkTQ85QCrUMnPUywarJWCaSvNBbX5xrFmQY8JLg/8JAWCQu3nQ5Y8dA+g52qn/eo641m7TnWY9oHSlrT5UTViK9q3kwO278mevLhYNr+NA6ntSGjjO7dKArJ7IIe3Z80Pe4ZqnIDpUFFaFYBv8ZqUqYtKC2vKmYjCHoBqNH7oeZ+/SAyovP5G/zY3rWuDwzqkUmMOuKq/xEJ4vOM1hNqy7k4jBMSDZEo4kJ5tjxTGQliYtqMSRqRm7yM9t0Zu/uGH1NLoYSM1aPrJInizDPhkvteHA3FCkkEdpwQUyhJKHOgbpcmHLHWCxROSpGLAemVIPMzGaBvIeyYpV6Sm7Zhp6uHAgKKJqP5p6TWhMx6DJRciaKcNAbomo5i2GXnjCx8EG95kN5TcSw0hNdiqhpRruRKlsSGZXM4os2XLjoDa1K1HGg1zs28ZlY1XTlyCszcKvf05YT77hnb14zYCAIJliaIdLISNs9c6k7tjJi0xqfLV4MUYReWlb5Axe54mN5zbPe0vgjU1st/pNFE8VRZcdBdmz7gaO9Qg2asa752r7Gi+I6H2ij5iqcqcYaVS+s1FPucLNnU44008RV+8wohq/sF2SXeFY3vJlnpGSS83xrXyNaYUKgN9f45DjqLVlAlLAuZwY6tHIUBS73YBOV9AzSYnPhWW0AR5sjc+kYYqRhkQA0xVPj6W2NFc/gHO/MDZN0nHVLHQNSIjoU+rpGVCa9aIJLWf7L3c/PIDNVCjzZiVoK6zShXOB97Pj5uuNxqGnSzOYp8vHpkevP//Sf9++Tue/j7x/mD5K4X0RTG8y2UB8uVDKSuWaGl3/YLK03MoHES+nm5UxFxKGYaFiYnr40ZBRRNIoGIXNVTrjsGUUziCFIjS8KcKzK9NKadGzSE7OtUBpmDBs5QVLUZWBmQ9LLjsuUyI39yODvaCOcfKEkg8mKpq+YVE+vVzRl5KzXKJuxolCyZVeeSd6w9oVe3wEzdZ64OX3EaoObeyTV7L3w4bZj2FlW+pmkK2pm6l7xXG6BiNeGc92wLzv2ZoU/aj7Wd2zlmeICDReyLkTRhNCiM3iJeNVwKS1N7qnCSKCmZmTSLbnVRNNiSwHJNDnQm4osFSUIQ2kWzqbWTMohZeHmduXw++7vq3JkUCt6V9OrhqwVooXQGk55y6wNl9Iuk6kSXqxgJjSFFTMZv+zUEU6lXnalv5jWevne/kBD5/kFEs5LQ0qO0oLY/N3dw39Oo20MujWkaIgCo2o4ilCVyG15z3oaqCfBm8ShbrB4bBKiMszFsCYTleGorplosDKg8kTfOGRMPKzumFNDiEBQZKOYirCvNqyiR+uKixr5srlBaeGj3fGxXRBWg2ppysB9fCKKoi5LpX2IHVXM1ObMSj4wGkNsHE0a6bNGF+FYGfbtLdlG1l64U490caK2CYVn42YUkWjBlYnUaiLC6cVU1yvHq/iBZ7lhtDWOTECxlx1rL8xphZEjhkI39GidmLMmWkuRlh2PhGLZpJ5Px0eiKjxWVzzp7YK1Ko6qLKa4s6oRk/i5+QvEYhcyQ1Z8lr7mmmcUYMd3RFMhOaGyIePw84qb8MzUWIKylKIx2bEpnk4+MmIJMtFdDOdKONs1zidKFi5uzZP5hIt0eKXIClLliXPiOW6YjOf37A85645UObowLtpcqTirLX3XshpPbHTEmZFUWmYMuRSe7dViOZTfcDBX7MwJ0NzlM/f8jMpPvPKFqVtRPKzTTC4ZZwpSDLVccHmmyZFUVfTccqwMReCkN3gqRtOg0sQTV/SmISpD1Aq4wkhCirBjj0RZbKpioKTEk1uzNxvu4ju28sBFrTixYtAbVBSKeErUnMuGqanoqVFJuJ0eGNwbJllqa14ZvBKKzviiGGlpZESZyCqOzErRELmNJ+ayoYtCSBrUuJjEK0VAONgVTi1m1qIUalwq2Mf98J08798nc9/H/69Yh4ivayYqEA+4F23cwv1syvGF2lpDWbzHlpRu0TJMZU3HkcXVzL6QQg0Wz0qOCJ5BbogsnEElEVXS4hJfEkNdc90L63SmKz1nvWITLjylV4xqRcGykv2CnckTg7as9Uc2c8+DtBQVSKoQJXEVLwSjIRWOZssl19yGI15GTLKIyvhwS28Mre85GqG6OKopU0Jhnjb8zs2OL9fX7N2OtT7TxcAUd5zDa57WDbNUjLKiVg9cDXu2RfNR3WH0SD1kvNVkqdilCw8YsliqfOFUvSaJ0EvH2/kbtrknFI/HMJprLkZjTSTFBVTtQqIHRGkurLHilkobELGkrNAoervC5fnFrHVLbzaMaaZojy3QMPGsd5yNo5cds9ZQEkG2aMn4F9pDVXoQy7nsSKIpkli0co6F/lBY6A+/SO4KSEK/mEqLAURo1XfTevhzHdpxX/Yc855DabHeUWzBl4o1Pa/CmXert+Aij2aDlMCDul6IIC843RnHoBpSWVBxuxh5kGu+XjV4adjOEz5DnSeG4oi1IYhCVGAqFd/aG9aSmM2KyvvFdBrPJBrJhffmE1of+XR/5l3VUsTiOBOUoUjGS8WkWvQccRKYjWZoHE0KGD3TyZEqDQxVi2IiCVQy8rqc0CVg08TX5jWDvCKKoMkkBU/6loyQcUxKocriM6Ynwyt/wDaRlTzQ2jOdH2j1SDUFflP/gCSGooUVZ6TpqaMnpzWTapAIg+mo84xR6cWeZ1kn6zLSyxpN5PfU5+zDFqcKyVZsYg8R1hy5iT192iHF4auGJDVJJ75qPqVNZ+o4M9mK0Vh+6/VrKJpaNfTKkpPHzgMf7CsOecde31BPE65AqE6klaFv7piVBZGXoZWBkCyiPTY+EcQRadjra17Nj0jUYCoQeFQ3iHiCrjkVRyqGG//EWLFoppXQy5ounNhy4fXc0xTHb1crmhyYjGMMK2LyL/ZGlioWBrVsdiGztzuCnFHCsp6IwQRPX9Yk8Uy6puaMZIspnjxYctaYUiiiSbnixrxnlJper5ep46pQxTO6ctA7BtvQ01KbmWQ71v1I5S6kqImdYNWSwJdSqHJgnQYq7enySFUG7BiZ7YapGB7dFZMuZHXLRE1XFlThKS8MWeUjU3Hs5oCdFab5bib3v0/mvo9fOlLMdEnz9nnPz149cdEbApEsBssIZRlBT6rFMTGLQooQccSi0RiyLB5RFQFdQInHFs9VOdCwp5ftiwKhIAVMhDZ7tCwO9V4qTtWWXfnILh0QHRikIStFwWDTzFHdkSUTjEU03FZnrP2KWdW0eC66XsT8oWAIZK24Gx6pkmV9vvBW7Xk1zvhUk85rlGsR+wmsRlADQ71j0okvm4YP6wZFwPiAmwuf+IFORprua0bzFpNmchZaPNEZhtoyiKWvK4qyNNMJp+FYNwSp+DS+J6qGXu2oxKO1p1UDPw5/l99WP+GDveGiFINeUTESjWIbenpxDKxRkklO0aWF30pRLyYyii57Zp+4L+95Zz8hIxQ0pQiXvKNSmSpnTkazl81ykSkAACAASURBVGugeqm6BqYXeHVhRWGhggjhRR+XCfyiXZpYkjh5SfKXYx0XKJoqJ3bhzJvLMzvTUHXXv6K7+R/dmIczp6SIF4evHWNpaNKEHoVtVIz+Ne/XP6DSTzzoe7blI3UprOKZTo+0xXM2W3QpVGogB8WsOz6gUWWmKYmg4bnaYF3HybbkZR6dk2pANKOKuLLBB4O3i/3NNvf0yvCiqCSHzGAgas1sHUOsMBIw4iEXNJ6x6aj8iagzUSzBCLsYuSl71vORr+xbnMzUauI6HSmSIXue9R1R1csIVRGqMtLOE3Xqycaxrzac9ArJebEOKpZOHVjHnit/RlUXmhw5uZZzuCIH4aw7jrphMg3fylvW7kBMjlyg0p678siKE2rOXGzLoFegFSYvlibr+cCBG3Qy/CB8i1YeZyZcCoy55ZKuibJCivDJsfDzleJg1qRKsU4N9zzSsWe0jl5XVCmy19c8yCt+Xn7IxvQMaWmLnlljXeEiilV6plMDY64Y9JpJVZRcKEq4n/cYZUhZkUwFBQ5uRVGZnT9RFU9MirUaeTZLIt/mgSyW6/LINUdWw8ST2TLpju0lU5WKad8R6h5HIMSGQRp625BY8aEx3M1nVCy8ys/0rqJIRSiO23DAELjYjpmGOkwYX9HIQLQXfjR+CcZw5z8wpRse3Cue4gYlUPvEZ2XPtN7y7AIJRVSaOiZSSQQHOiukSuQAURmCXfR9m3DBmhOjazDKE3JNPRW0grfT77JOI1u/57e7fwyKoFRcEIWloSZh5xFNZg4V6+ypbMGjqNLEJJl4Zbh684Pv5Hn/Ppn7Pn7pSDGzWd9w/97xxfkZoyPnsuPg1jRloik9WcETBhFFXQKOGRAGVsxUaBKhVCgpOBK6eBpmbtJHRtVSy4RjJuIQP/JJOFPlkUO9ZlKaoAzPXFHlHpFEScIH9YaamYkGj2PCvjAmwRA5l4b39gpUIuWMNzWpyzzImqQKuVjWac82Rq7GwFjXfCtbKqDJGjdOzBRyWTG0FZdUoVXgQd3ysawIdSKZNd08kscasZl9YxjKiqCEuszs+gsJRy0DKW8gXjDAhpFZw6BXTOJ4V7/C5iMbdqiSIMNEw+/qLxhUA1mxUiO+ONb5TF/WtDkQg2ZSI6UAybGNZyq5ELUjYylFaMqFLhu0isRS4XNhoCaolwpqDExiScpiSER5qayJAIaEBhRIJpSCQnAlUgQqJiQFZrXByjIpuCC/Fgrsbp5pUuAq7Pl0eOLVxzOvvvgB3fX9r+6G/kc0+v077PgtRrVEL0x1uwwENJnjUHFpOuaimfQVRSlcSkiYqEpEyDSqZ4ulJEVMljrMzLpmMCuibMnpgAsTOubF1qYayQImDiQsaswYEbISrvORzp9o4xmjPMiOJ32PyopSgQ0Db+czH80rTEpUYeJGnijaMolAAV9Z7uYPKJOxMdDOkVf5iVwtE7kKTZsnqrJYls+p5pLXxNKiRHMdj6zKwHqacDLyUd8wJkMSULmwzheu1QM/jn8PnZfqzEE5vqzvudQN++YGKZ5Hd81oKnrZchc+0CaDnQKfxm9o8oQtQlX1nNItJQeyirxJH0AUZ4RHc49XFSrBRXXcTQdsKJgAg63xTiipYH2N2D3BmMWL0xR0jiSTmeqGqAUjkbNquUi3VLslowVMiZQiFGVIyRFE4VODbTJBHC6PSIlM6WVKNhau5m8IseNjN3NhjUt5+e5Li8+OWVlenU40XY+PFzoGolg+uZwwZiC5Be1WK8/F1AxiqOoTtop0IXIsDcZrXIHtPNJHWMcJm2ZMdeKNt5yqHWdXKCoya0UrB1TpuQkntnPA6MBebdAKYtHkfcfGLVo5ZxRWIi6duagbVlNiJ0cm7XgyN/ye/QwbE+0An/n3JLPCmxqyxuXE7WlkEwNXac9XtYLmwOA3vJqfaVLmk/BAVzJTuKajUNHTryuCg73ZYApQZTbzgFbTQkHxcNMcaMPEsVvxcyKzTN/J8/4rSeZE5Br4L4AvgN8D/vVSyv/LAl5E/hvgnwb+h1LKv/KHjv8Q+NvANfA/A/92KcV/91f+fcAyHHH9+V/mL/+f/wf9Vz1qPBJWR75tbxAVGUyNQrFiwpelVL3hTBFLoRARUlEoSdgSWUtP7U+spEcVmJQjUuNZUTHT5YkfnX+HoW6JZQGCywvsq8lnDuaWQuFoNsQ4UoqQRGELJCnkpNAm0XLmKh3QXvBOsUpHRmPZmw2rMrDKB5pq4LbsaYPmf9/+BkUsdQ58xje4B8W06iBFem2YqkysDbYfucoTx7yimU7cjwemqmMjS7v0Tt7js2X2O75sv8DqxaUtZUXjF8vdsbYImVU6s3efk0rFhgs/Ov4W87qhlMzFtHyTPl2waCVThQOjblFZk7VmpMHXBisToLCMiEps0wGKYy0nLlRsy4QMhZ+tPkfFhJaaau4xSi9DE9qRSkKVhJNAXMZRFkPoxZFqaZ8WjcXTph5RkYTDEjAS0ChsiNRpYsOFVGpGVXF9ONKdhH/y/SN39cznf+nHfPHP/bPsut2v9qb+JePXYg0LgSKGoemgUgtWKCuigi/NhpxrZmPRcZlEL8WiI6yZWIUT23TitN6xDjO1FNQceVoJNRknI9ty4E4+8kCgdyuu4jMBjY2RojQ2F2Yq2jByfT6QO+HNfCS7jI2aubtCokbHhS0aqsVcONDQhhnPmugsH9w9qQhaPJt0QSaDygLF8VBeQRK6PKOD4HzGOUOdT4t5eZeoSqZJE/fnA+t8IU8rlDqz83ve1A1P1TXeV9io6ObEsX6L44wzI03qSVaQnNEmcjQrgnJUyROzIeDIwXGdnzA+cOs+cJMfOKkr6snhpisKhspOpBXcTx/4mf0BKV2oJLNOPZu8J8c1x3RHTQWh5bFdcdUckXLidoqExvCkO6xxVGGiDQOIolKKNvd4rUiqYRZHCAtWy5TClgPr5FFx5ov8LWacObPBVoaTViCBIpp9vYXo+Svj/4UNr/mWisEqJutwwTMpTR1Hagl8ev6GXCt6a7ElsuueyVScjGGcW+ZcEQ1chZmTbfm6eg1zYWhrbi8DJ7didAce3C3iD6Az61w4mltMzGANEh1eW1QpNAUqqenSwLPpUHPEm4ab/kTkDi8aZTI32VPnPXu14qAUQQybMWGriE5PBN0iJ+HgGr5y19iY2UbPWWsOruXr1ZbP54Efz08gMx/kmkN2FCOs0gXbV1w6QyxCUX6x68mBtT/jqbjtjxzqG3b5gpeFfCNJ8LngqxpbZjr3zDfnd/wlfvKn+qjDr64y9zeAv1NK+Zsi8jdeXv/7f8Tf/cdAC/x7/4/j/xHwn5RS/raI/GfAvwv8p9/lBX8ffxDaKG5+4wf8dP1v8ZMv/y6/tf+G/+13fs5184G/d3WHmEyUiqqMBFYI8CR3i+cc8JZvuciGjEbL4lNndaJkteBZRLMYYIys6ZlNw9Nuh8meTh35NF0WvYvUKJM56C1DqZmp6crMJj1RdEVTei5yReuPNGHmOhzRM7RxpkSDdp6sNZITo9SLQHke8bPhXNX02iG55thV2Ls9XXdhDFfMG01ltxQR6DMHt6YojysKXY3slabOPdX8REk3PLZb9vma6aam8pEtJ17Nz4SyiGwfmy1ZaaIyZCClxWh3oKU0Qpd7knLE3DCVioKgVeIqJz7rv0X7mtR0WBFmp1lxZi8rKkkYmVirgVHSglQSRVv2+LZjVS6c1Y5BKZQoMkKVIylrbuSJKdYUBga5MBtLwjJSL+q3srRQq9ijSyRIRUHh0dz4Mz+c3hO1ZXeeFjxUgNkqVsrxk8/f8q/+i/8Gr9/eIE2FdR1W/9pNs/6ZX8NcdUU3yzLQkgvZZmoGBnaMrqbOCRcju3IkUlA6gio4n5iomGloxolVhuIXbVysMyfZEIsQkiOYhi9O71F2ZpzXnKvNMlQwjnjf4ivBjiM/2/6IXXmkiTPVPLByMy4GutLTholXw7eE1lLHFbNa8cn+hFnP6PiOD2azjE3JUmGyMXEot+TK4uKATsJWTox+he01wTdkVRATuZpOnK0jmcKpc3ipaWPCc8Pr/DVX4ZnfOP0O5/kNs1sxaMtIS1SRvnTcjZq+2TCpmiQWq2aa3GNUxITMF9OXS7WZjPEZk4RH95ZhWjPIPV0OZAzRbwjjjB6Em+ZAzpooll084Z0jFY1RHusTyUBjYJu/oTInVtLxyns2vuOVPxDrvFRSxXOTe6rYo0ph0DVT7tiNZ6wozKxZucB2vlAY6Ncdg7pahjPSTC5rrI1IKlyHPbfjM8l31FL4of4Z79yOU9ySqsKkNZs0otPEzWHk7vDEfmO5GMOh2lL7wp4dj+2WSZY2bT0+IRR6V/N6vKCiwqYt3WQwpqILGaOEXmnU/ApMhSojSiJ9pTGSmEqDVy24E5erNV5rnPZ8HK9A1ayiw0VHbc406kzhPXvzCad6jZfFnmodjpztaw5s6dsKLZlqHKlIzMpSpIAqqCYyW4XfC1MxfNm8RYpQcs2r6chGR2aEyWY+P3/Dx82O+/nn9O6KWTverz9B50hRM7M4YqpZpxmbM8UWap8o+YYy/OmjvOBXl8z9NeCvvvz+nwP/PX/EQlhK+Tsi8lf/8DEREeBfAP7NP3T+f8j3ydw/1NBG0X3+Gd3nn/EauPqf/le+/B//S2ZnycpQUEiaQBdGqTnLFk3ClRlLoi4RkfEF41M4yTWzuAVsLTBS4WkIVGgjPJYrcMJanhBJbDlDutCkgCuBIDWUwKQct8y4MlGnRJETkhSjafhat8i6oLLCMFOyxvkzsVoqgZ2/MHAFaaAUYdaaqTYUlXhnb2g2G6bxhiEr7jO0nGnxVGGiMpGV3zPnxErNZKUILhBw+NiiJVGpBUr+1Gw4uYa1P+LmEVsqAgabI0SPEc3ZrUBFahmo80AvilgEJQWdEmu1ZzdfOLgNT2xABC0DSdUkBUk5cvYc9Q3f5EAjEzZ7ikTeqbdkSRzlGkqikkCdJoJ2bNlzUmsCjmAM6zDRpTO6FCZVsdcbRlrIioiwKRekBCbVvNBYaw52SxcC2yHwZj/j5B0//vwtP/kn/nmubj/l9fqGXd39qm/hP2n8mV/DJLc0ac1NvKCS4cQVLiasFJxKRAGxiZwTSQkuRI76mj7fYBkJRqGN8PZ8pA9XRJPYxh5tZiiKtvQ8yDWmfuZNOnCRew7+LRM13nk2+pnZOvaseWhXpBBRKrK9GH40n9lVF3Z5wARhkjUf6utlotBWuBFy/4qpzVzCLZWZqfqedT9zVC2+tUhOnHTLjdnjwoV9dYX4DVWJrNUDr9TvcpYVH+PAUa1wqTDWFW39zDm9xeMYzJZQG6qS+Mg1AxUn33KrYa4dhyqzTRO7ceLdaoO18Gb+LUQim/7Cuh6xpaBK4GBv+Kj/IqOu+XT+QKBQnCFGzV040EyP9NKzygfObKjUTKdPzFKjysQsa657wa0ybw9fMtaRJ7vFhsgkHVUJ7JuGJ3vF2/KBFFvadGCbRy7lGeUzY1lRzwpVVlxUTbYzyvQ0akSpAGww5QJeLQZHvufUrnBpgrqw14GhzWxDj7Ud13PPQewyzCYrGu1ppVDTUqcDtUz8ZvmLfKwaDuWeubSEpMgknnJH74SULO/cjm1KuDKwqiOSZy4OmDNWg8uWnCyjztRpRopZWvZ4IHGxFX02zNJglaVv1rTjA0/Xa5rG09qZNcLn8YSpV2xy4IkbilKQQavAtX8iuB02vwzvecN1HwkdaJlpykRfWb7c3XNWHX1ZUeMZVcVX7VtmRm6rR3xWZFWTsgFqxDuu/ECpIkEMk1SU5HDjTK/XtNPMD9JXKPGszRU35buh3fyqkrn7Uso7gFLKOxG5+yXOvQEOpZT48vpr4O2f9gV+H//g4WPm50PESEaTibmiVw6rND2r3zcPTgheBJ9GigRiaSjIoo9XQq9WFAyaSCMTFUdKAVsUSmBQNWuEZ+6I1NR65FLWSIGkwORMJZ43+QOjahdhazEcqltEIGuoysSmjMwqLw4ZeQ1J0UaNnVacUscDSytDD47SCthCEcFmz0E5ptqSo2Uoa6ocuPI9cxaicpgwYlWg6EyfLFfxI1PQUDtO3KDLhMoNLi/WImfXLexB0Wx9j/KaQUO2lgnL3twwpjVGelLWrDgRxKJEeFK3zFhqOVCpM7MtVHogJSETGVVLAXJ1T8dAT83Ijqr0hNJQlTOVErwYUIUqXrgqe+7jt5xljVErKjUy5ZogQq/XCELNjEgkSMesHBqFArwsbdbr+MgnHx94m3bcvb7nx//4T/nJpz/iB1c//HWswP1x8Wd+DVNK6OKaakzYKvPaP2FjplbL9zV0irXfU0ngzFL1rfsRPRdKB+sMKnhOtCQFe71GJ0HCIir/qHcUgVx17A4TNZY6CybPXHJhHSdO1ZZQNThZEsCEQVtHLJabMvJ62vOz6o7fbX/I2Ciuyp6NvKO9Thzne+K0ph4LlZuoYmakI/UtUmdcPBOcZq/WHOw1c3Z8okce3ZqSrlmHI93c09kLF1khqqCyR6fEyh4YqHi2N4zuwsadmeeB2vf0IbJXLUTBzPesfMTEwN4Iomb25prN9MhU1wTXMDu7WP7EzN50hFLzZf6crs8MjedxDVNyNOUKNSpmXROC4zpO5GxRSqPdzKQz5+sjU1xTsscXoSSQlKjqie10IaXCc9ktTGRXaPuRV/qR1dDTWY8MDe/lRzymNe+2jl05o0QopZBEMWhLz1tuykAuIFm48x/Q4glFLbQIXUGEVTmRtGcIG97qL3FF4ULg6fIZp3ZPv7LMRvjILZ6akmouqmPQjiZd6G2NZuJm/oAuis/mkVWeeMi3fGNv0Dmj80LrGZ1GmxmvC1FZyKBiYu9uiMqRgEqPRImoolhx4X4OfNVA0Wd25SOiet6pN5xzy0mtwYPTmWPa8uRuUBS8sfhc4/B0MREEol34sYnMSp3IdaQtFwwzA0uFb0qJo635bP6Gr1Z/gUlZHvWKbpg5uRWFGTGaVMKyEZLMcbVm1XtMcUx+zap42lBztfpu0q7vLJkTkf8W+OSPeOs/+JN+9B9x7I+tW4rIXwf+OsDnn38HTn3fB4fB8+U3H3mKLT4aZqdJogi0CBGhQkrCSIaSICcuqmFWHVkiqlgSM1lqKAmRmlLAoGjKUr0rBBItY2oYdcdGzhx4EW6HgaRfYctAIfOeT6hzz6RaHtU1F92hiEhUQGTCsE1HXBRGZ6iKYEsmakN2hffVGp0bUBO16IU6qwwX0zCJoLMnZbiaD9yrJ7TTfJ3umbwjqjV6bbkr7xZxrQ5YFfgkXfjseEbHyLt4RcTQG4uTzOvLA0d3hY6OKp/JVeE+e2ZpKFGjiJSimV1FeDFClpwRB0IhmxotA0YKb+JXPKhbbEmUBEkbPI5V6ZlkTS5QxKBTIKoak2YapWnTGUqiTgOfl9/lwd3zu+ULHvQtnopKPAlhx5GBhiYPBB3QJCYcipFSagRIGLb5I//Ub3zKX/ln/hpd4+iM+7VL5P4srGF/kvVre32NbTfk4UK5GE7tFetscHPgE/mawXhm6fBY2nmmJMEpwVSZqDQ34ZlsIiezw8SEsol1vLA8Q5aLW9OmGas8ZEWXj1Rli/FhkVXmzN38yBQbStUtwvsUmFhzCjNzXfjSrdjXNXXI9Koml7I42ug9fWMWW5TgUOeGXBqeTcNlvSalQiorbucPqBooMw/2DfFaKEWx8wOPaYOaWoayIh0dnXtCjKNKA6s5cdxtccpzNDVBCwe9prM9w+yYZUMtkcdVx6enI2/mD1z5ibEY5qqwKgFvas5SkRVUKZAshNSyiRMaz2WreLKvCKLR2rCdLjTmgjcNSgpnXbHOzxiz53fUj/nN6g3T6odIgDbM3I8nvBau8wPKBA71lkr1SIaHskPOgZ/nT3E5YnTmWgJzXpMrz9X5kd9rW86VRfSKtzyx4oIrF96ZT6nNQNRbhlhTYubcdNRqxqqeu/KRrTsw0rFPKxSa6qJpfCCyYpCGWo80lwv92qFzBr3oahWFNs2k7JhYEU1HkIaNPzOknkFrjq4jSYONPb013KiRSo9MVYWiImi9cG2LQaXEipGLNDRxYqcj1+HAUd/zvuvwUqiI7FVFtDWzaZlFMSjLLu2hZEqpaaeRyTqCMmgC1Yu2etKWu/HAOpxIlWel9/RmRciWNT374qjjorm04rnohqgTITfE2BKzpTl5WM+s84FeG+7TI4f4CjUFXoUB0SNv8gdupsQaRdv8miVzpZR/6Y97T0Q+iMjrlx3ta+DjL/HRj8BORMzLzvZT4Nu/z3X8LeBvAfz0pz/9bprVf84jpIyIZdtPrOOFc2qY9JqExUpkFc/oorBp5GJ2zNJyUStAARWJBHRQNIhBykxXLrSpp5EBXQJndYvFE2gxzFxKx5EtRRVq7aFMdGXAF81RLZDqMdes04gmMsqKtvTcxI/cjhdsGcnKYZJQhQtVnBjKhlgcWk0kozmrmpIs9+GJbh6ITrAUTuxIUqjszN30kWf9A9JKM7NBD5GeHacy0qaJ+/xIKB1VGhmqNVOrSRbOqkXFiPbCNiWsv6DE0YaJj14gGc7NFq1gkpaEMOcaVTJeLApACpbASs5oCWidoWS6ckFNcKquiUlI2pFQmOyJxXJRmyVpzlAVz4ylsCMqTWKNiolA4Um9YqRGtGCyZ6TBSqQuI6/VNzyWT15aRJkue3bqW0woXPfPNA97zI/OdFbYVb+eLdU/C2vYn2T9ctsN5+sv8P2ADp4mebohke2FKl+YisIbzUl1ZBxRLWbOd/MDSOGcW9Tk+aheo2wkILTTHlll6qR5tjfMpUZ7zTC/4Sa951P1Jde8hz7yUF0zzC1jWmOz51LWPLsd3mao7rgJjwwkunjgyVxDylzFJz7NP6fSGWsSQxnZjB31oJkqxzfVFUe74cofUFmYc0UfFu1XCpreWIpp+Jn6AZILTQkcqvVicWI2NHrkUjV088gQGpRL+OS4DgdWfkCCwkniojKRGpMFOwruVFHbpS1tYqQqGdNnzl2FxhNTxU1+QDJoUbhQc1SLGW6lR4rMxCoyS2ECNvrEhMNHxyQVWQsowauKWVUEM9AxsgpHctSs8siM4i6cKOeaXCU+Sd8ymZaV9FjvGKqOYCvOuuZwvaYXg5YaLWohNDQr6rBMWZrZca0GVkNk1Bmvr6inmb5pCdFiM2guDCFwL08krbF64Fwq9toSzTUrk5jCsj6NYqhLjyuFWFaM2mEoXM3POAo2Zh7sHWdXcZCWUTeM2lFJZBM8c9GkEqlKz5xWFFGIzlzMClsilMhtfKJRnlrP3J3O9PmalRSOtgWvkTnhrWXQa1AZG04Un1FyodRXeK2xFCrlSdbStO+RuabkEZcabJ644swgFXWZaKWn8Z6JDiOBdngiKIvMFpsajPWYNFBrj0oDbe7pKg+SqfSZvr7mQEcThSG/4m4+UIcr1KWlxIwY9f/1CP9S8atqs/7XwL8D/M2Xn//VP+iJpZQiIv8d8K+xTIP9Uud/H3/6sW0cW+tIXeBcNwRtQQINha5c2MxHfvjNN6S642fXgX1dcaF7sbqAF7IXIgEQaplxRIJ29LJCk0hortMzJSukKLypcYz83+y9ua5tXZqm9Yx2tqvfe58u/siIjMyilCklICEkDISBg4PJFVQZWFwFBjeBX+IOMMrCwQAhlBJSZmV0f3v22c3qZj+aD2OdQFVSYSAi4q+sOK+3pvZaWkt7jDG/Ocb7vU/HFqxGYVAx0qSJUo3M2hJsic6JNt6aDooUwRomU+HVLXvN60gbJzah51MqeWk8S1lSILyL33PmQGknJEMbe7QYstG8X545pDPROVL0qKyYrCa3BlUo1LKizx6TNc/1htncE3FUBD7Mn6jTRDv3nPWeXjuKHKk6RWontnpipYWghGAaRlWQ0ZR6YNA1GUWfGrwErCQylpArTB7pc01JJhNoYk+joJw6VvaFSInRiXM6oLAoBSYvOBURpVAorGTOdsOMR0tClGahIOlIwnHlhikKyrAKjwT1gVaPPJoHRKqbL3ISUnKYoqF05Y85NP+Q+nd+DXt8fuL7148kDcsGjGSkFbJYpnlDyhNtWphFE5YWsRNz4fmufEuwGpsisxSomNmFC40EjEnUZmSUhl+MvyFPq1v8kA8wWkx5voWIO1hzJmlL+drRbQpymUkGHJGja7DuxJhbJgNaR+rcU0+RHAuM6whFiWTNylzw2nHxW6IXxGb6VIMWtlPPlRobzygniFHMBqxSBO3JjUXbSMnEqDSrfKZEGBpLSAan8i0SMSmczPRhzXrImLLjtK8pcmZZ95y0xiHolKlHDaamVBeSheQMna7IVtPICDqgVYnPKwq6mwUDjeHKYFt26shsPVYWPlY7iMJ35g1naT/jCTUKxeIdZRbeho/4AR75KRe1ISqNicKzvYeUWYxQMDJFzwXPsmiCudlIvFtufrDqiiGw0VeGWGNzzTpb6jkTyhKbAoiwmXsO+oiLgRd7YKIiGHXjRxeWGJab121oaSSwT6809sIPW4UxmbMxTFpolhljIhaLS1fKV6GmYyi3+FohMZHMjeAwao1NCSuBs94R0KhouOtODGvHKvUsGTbTC4ta491McoriOjLqhlwU2HhlsjXB3Hb2mnxlKTzJFARl0UvC+YyWDk2mDAuHeCKFNWWceXvsGcuArATZClF7zqaiNDM/G3/JEHfEbBiMZz3MHF3mzfSI04nD+MzJNYi9Rd8388BdPHOMkY57lFv4Xt5gbcH7zVtKVyJJfgdM+r3pxyrm/gfgf1JK/TPga+C/AVBK/SfAfysi//zz6/8F+KdAq5T6FvhnIvI/czMa/wul1H8P/B/A//gj/IYv+qy2tHxVH/k79wmr37FRVwJ3tHLiPj7zi/Ff8de0fPPs+Yd7SzYWr2ZEZsAQiChVoSXj1cxaLizK3goKlfEEOmn5aN5j3esbGAAAIABJREFUDKziiZQMXoRkFbfyZsHp5ZZzphWezCH8GpsM+Vyx8mcG3RABNQmnaoMjI6LY+Ude1I4pe9QkqFqxSy94t3A/DWyHgUksTe7Y6gs1G+7UmRNbRmV4cnfkYNDKYO1IuUzs4omTbVnMjhSFZARN4qxWqGKhCCOvxQFRBqtHbLjysdnxUn6gVCOF7snZoXTCS+CQnwm5olMtogxXWuo8oQmovGBVYlANvVpR5Yk6TeznI6d2Q3S3mJc2jChbkWUi6IIy94iJtARS0pydZxZHyCWJgiwOLYkyT6zzwOQnnAhrdeaUdoxuxYk9RkW0QBEvlCnjUqbf7PnpV/+U0v97W8z9O7+G9c9PiLlSN5/IJpOo6Z2jzBNGzgzFgT7tGUyFF0VSFTonsrntpMymZJQCKTTOJtplwrlP1Hniog4MvqRQM0iBma88rrck7zibCq8W3p+PDC4xlRHtE/Uy0dlAEgjK0oYTUe+pwww5MrHiqA/oLORkKRjZMHApNtTzhUpbmuA/x5YU5GRBLBpzQ/PlxLIIvpgp0kLLwIxlUGsUMwuOi9pA0VGoAbRhUCUZxdlteDNecSjWSYFceUobDqEDo0mNp48rkjNYpahiZs5COXaYIKzdK0155mgOqKy4SE3IGz7MX/Op3FOqK4upOds17+R7ZrWizAsXveU+nLkPZ1y2jKVhMBXbeOLdcuT+cqJUM8m3rLhwpqLtHIuvmWtLIz29biinSC8F16IkuIArJnS5ELRDp0QGxrxhyHsucc3u2KIXCL7j7ePAm3Jm8kIdEqtVxiwlqqpIuSWrTB1fkWJirg74eIU5ITEy5oZCeu7kBT8HRqsIuqJSI36OfHU94k1HSjWiKurlSBkKOtuyrB0+Tgzeks2ABEEZqOJMshWp0mgTUHpBBc9cNAyqYrccOcuaqpwQ73Fq5FO5JivDOh5Z6yfu5wtX3/Jo3rIox1yWOBl4mBeMG9jPF3yeeLVbhtjyq3XFNn0i5RqZoNcVTXHGp0w9J87ZMgdNdBXt2bPTPSt1xFUXjBkYw8JETXCGyRbUKlBPHd/zM862wmvBqMAPpwtzCrTm3+a0+P+nH6WYE5EX4L/8t1z/34B//q+9/s//X97/K+A//YN9wS/6/6zGBWqJrFJPqQfQmZ/F33A/HnnPiZ/9x/8ZX/+vVzwdBYpOCgDk81GrYcKpyDp3JKUYpGRStwaJSarP4J2Ak4TVEVHmlrhOQHMDxVsCPgW+ir8h6JazrCEY2phZyYh1mV57urbhZA5kpQmSmZWnyYnerxjSGpMHUjxTF2ecfWW9BOK0ZaMmXI7s1ZmgDT/odzy5NVMseT9fsEHAdJxXnlPZELOmzROJmhfWOH27oemgsbHCGseKC5qB5IWjL+m1Y0maDRMkIWuoQ8fiG9byitXTzRtofs5kK8iKmHbUcuGsdlR5pkiJUgVWxZFGrszKU6se4zMZhV5uXqm36hs+6R1NPjNxIEVPUB6t17/bLKWOMxUzykWuNIzUBFFoLTdGo/KIlDhmlDIoHdkU041t66ofcUT+YfWPYQ1rmhJthCieyRiyigyuYZpKcI52CjRmJIRAExK/0Q1H0xCsQsQyaodF8DJxJ0+8TS8oA3H2bOwzZS8EdSBpzWg1Ro8kZTjmB8QmsvW0uSOELavQURgohk9MfktIV872gFKJaDSjXePNgssjY1VynbaUuucw9+RcsHFnrtXAya2QKVMOiZwU11XNqAqS2bCZzxgZ0Z8tBFaFm+0gdwyuBK0xolmlCwULg1kz6pJCLVxUy9LWqNkTwoxqwaqRS6FYjxfmZsUknpPd0ZwV2s5sXc/W9ARlGKznWa3pdIMhU4UJWV4p1oEmDwym4SXWXP2aXToTVMVdeLqhymJmy8Sqf6QTTzKR0gecZMQqlt6S4i0fkNKANXRFTUmPFY8ePWMynG2LjImlKVmlKz+TGbsItTrzIE98rf6MztZc1I65KPhKP1HokXUzUHY7zp1mz0wvB6gEi+NNfOGoPVEnsjKUcSJXA5PWrOcjdjBsugtnKTiuapKU7OdXiJZN7Fn7F0qZsaqjlZEnu0K7xCk+kKcSpwZ+WW3pTEvSiiAFb1VPXhSiM0oiIxXBe679hl6teUyRUW3x8wtjscKExOwrtJsYskYbx5RaMobZWTQTOmtKFVn3E6v+lcNp4Lk6YJyh0BO/3myJ0hKV40P4lglH0yWqMWKTYfaWa7FhpmJqJ1qZWUqHMTv2KfKD+Qkvfk82lhWvEL5ntp7e3zzLqzwxpcRLeOYUXrmzX/3e5/sXAsQX/V7001/8NR/+r3/JL16f6QrLg4z8+fxEPVv+5q//Q7L/S8z8v+PSAiiMEhIVjomM5ndkgYvSOGYWKkS4HfMpjZJbzplVmVIN+NgRcsFKncFA1rctdiuKVeiZssZG4ZgOHI1Dyg2NPlJYjTDynEHbiBjLVVqiunnCZlNzmCZmUxCnhnUITBiqpkNH4exrvD7ztf3Ab80GyQ6ZHau0UPWG3fWCpoRa0AidbajyzPvp1jXoJsNFbfFxYrK3xaoyHUvgZiHUirNaUYaFf9L9A8EpAiWXpeaDfaW3nllbXhkZTInVmVF7Ut6QRbNoR5Nn9suJNhz5YfOOzq8RFFUeUKKwGlw68Vb/ll7XRNVw1hs0QlCGyZYc5o69XPH5AkYIyVFZD+qKkRkF9KxQgFEDRVpocqAg8CY+IlEYri8/5pD8k1fdPvCheEfqv+M6e7J3uDndsh2JXP2KIi6QPUfj6EuDlYkmjlRTR1AVjR6YWLNfJoKpMXnk5A+08ZWP9Z8j4mhkZt+/0pWZj+pnROVoxpE+RwoCw85jFsjzGlW1lFNBw0QqAq0cmXJDaRe8XrialtFqSh1vaDnRRA/fuRXP5g6/JNoR2usLySte0gathMEWOJM4zD3N8MwYal5Xe8alplALg2oxOmOiY+TANn5P5QInLCFbgoFgDWIchoVLc6CaOwZb8M4rJGoWZ/F5Yq49j0XFRb2n5ch6ufm8TrJhQ8+ZFW+ur9R+hBDZ8wqsscFRxlfqtCC2oxqEn+evWclAERJT2HEaKorySsgFT2ZPksA3q58yNyVBFQw0rJjILrDpRq6rNU/xjsoNfKfeo40jlwurYaTMM3NumPKa6/SBU7uhXgI7zhzrN7xIiZk31OPfk3PksHll0p5UDZzS6tbpWWse9RY3FRi1cK9OdFi8eWZvHgl6S+MHyqMmTzN3dye0TlxNzXZ65lyUjMsad79AmGnVK629cDedCMpwto534cJAgV0ik264WwZibDmWjiIviGjqvDCPdyxS8EkbMhZT9jyXG1o3MqkKJRqCRpOZLHzoPnJqNmhZ2IWed+EZnRxOd4z1Cmcz2kaGEsQnzLIQVYmbPQ8hQXJ4IxzLDSoYvA2EWbEUiUl7rIZigEJBpYTGLhh6jNKc9Jqx2JKUxthAUjOr8BGWiXG5/kHm+5di7ot+L7r7+V/xX/3X/x3/5F/9n7yeBnIwFIf/gPbnG+5/+md8+02i7ixNuPKYP5t9MWTlyKKAGxEiKwsyE7ldQwyCApVoGCjSQK89o74jWIsm4ySgRDNR0nJl1iXDtGFRFUkcvoqUaSEUlqgsPkeUgYGSQdXM4hE7cLe8MBCppplcaFK+sqQFpQuqECmU4TvdcirecEx7gnUUy8xQWM6sidGxlA8oPXEIr0za0aqRJj3znfkLkjiYN5icqMyEDhfu5ZX19DW/XP0UbYSSiVU88376xEo6ptGRdCIYz7O5YxKHiQHjbzdlSyKQCNp+DrhMNPrInTwy2RW78YrLQqlGRuVu/WaSWSh5Uu8QhAc+8cqOQbX/j5n5h6KgzAM1hpKBoDQDFYID5SlkppCRjLpxd3VBJuFkppIL68sZ0pd+ox9TohzHYs/H81u+L7aY5cJQNdwNF4xJTEpxrlpsVPgwo2JFcBUmZXb5kd3yDVW5oGdFGQPP+o7sI4MveHEP9GFLnQKTMSgsd/LEHC3P9g1Ja1IBxbCgfUCrzKAtarYcK4fRhoaJip7oFJZMqXuC0WQsIgYVAkpF2jwSvEVJZLGeszfclT2ba2C0LYsXYl6YU4WfzhSxJHhHkyYKrVFh5kVtuOg9SUdiLGgWGHKB0rc8MxcjZtYcXck37RtGU5DsAy5ndICV6lAmklDkLJS5o0w9XbHCKs0oDdf0liq8oFCsVA85MuaCkFdYDGpW5KLirN6jYkTylUYWtLI8co9H38K5rUVlS8mMqIKzectF346VE5mCCRsiV7dmSgkbSq7mwOwMOivWoUelzJE7JBUELSRzy0ObMDTmSpWeWaVnvq/e8cvmgSlsaFWFnmsuq0QMBq0TX8Vv2WfhnjPfxPcka3BJKNKVzjiO7Hh096S2JrlImS6onFhLx1ueuOYt1vcs2vLL+iuSDuzziV/It6xk4iX/OXUQRgpMyNypM3f5wiIXmsnwmO6ZlYVYU/aG9dIxIIyVv/nYJk/NCdGW3hYMRUk59xyXmj4VuKmn4co2DVSADQFtM2l0bNuJNg2MISI6cXUtbl7oU8l6mInVgpVA7ywuCRMCXjMUG2YLvTO8CyemqaWaM12qSKUnq0QZLwSXKVSkjRc0C4XtmNaK5Q/U1P+lmPui35vufv5X3P38r/6NayEFQg6UDzN/W2oOw8yvWhi1B+WIooBIwYiRTMTgJVGrgQlPVrfjWIMgMjPpgpmSSVf8rgAUNA0jkg1Ew0V2zL4mR6FwHYUETqqmMzuUSniVMbln0SV8hsxHZTnpHZvU09iFOpyIVcvfmS3lsrCn49Vbfl3+hLMuEGuBzOxatCQWMosCIzUMOzq/puAKGl5MRV84mlHjxdHGAXETh3DmYXnk5LdUIfGgP/LIe6o4cTYNzk4kZfnEe67SYkyEEChzIKuKmg7DAlpY8LcmElFMqebZvKNLG+ppYlEVvWvotGWyDQUBlxaSaAbVkLPQ5AlNJliPzz0TLW2e0CRG1bCIYqRCiSCqJQMP+QWjQVBcWdP56nNhHjDZEJX54w7AL/o3lGSgu/6ApIibhHWE1RAwGmgmKtvREHnlgTQXBF0hmltHZVlSJGEdRyQW9Nowe83R7rnKjlnDp/KOh+7MKidW88BiCyrdsZ0t2yWBX4jO3jywqSSYzJJgUo5G9Vx1iUrvuNDi0ohhz26+UDJwtTUXvealzmzmjI2J0Vj0mPBxBjUg9xPb+YmL0Yz2jsEVFGHFX/avOAXFDKOPdHKPDg4tlsMw08yKTdZQCG0eMbqnN55B1UQLWSlECUkp0IZTvUenzFfXT/xQ7MnaM6mSLSeUeKap4JO6Z6RiUgWNvlD4V0L0rMOVRaDNJ57Y00lF51es9JVnc6DqMy1HTDsRYskklnKpeT99ZCoKXs2GUMHsHLOrkBhZq56YIVnNWHpemzXkAMlQxsw5bXm0D/SyRpVCNkLA8BCO3PdHdjrwjfuK78uf8OxXIDO4kqtonEm82i0qQCw9IWm0QBOu1HHA0+GdJlthFMPO/5ZX9ZaTtHgtKNOg1MSoaxbtWVTNWo2czJoOT8srzxy4H1952X3gLAdImcPrBUmR4/2OCxumUrMNF3TQfNX1rD4lQnScVjNdW5PThIkXqiUzVBUijt24kKyFWeGCcLQrDmFitpa748A6KeK44XovxCrzYmtqNRF0yWGYmIuK3Xzipd7hTc/sSxIKYyOFOxOoOS4tl7qhYaCzK+7rR74vV7TzyIf0CX283V9eViWIUDJTp5EqDezyhWT3BMl/kPn+pZj7oj+onHE44zjnyOwDfbmmyPI5kSh97mi9ddgVXCgEinwL3c1o4ufAYORKogKEoDw3krwiC2ix+BAp9UxhRl7VgZBKlM28774jOcN3zT1iFZ2s2csJSRrwkIVF1/w8/Ib1MvJ+/MRZtsy15pvqp5CFTmeacSTYAj0mQt2SRLFLzxSxo1BCr7YsquFuvmBkhqAJpUO5iYtt2MUzOa2J5oqdZzoasu4xTUuOlpwtvamZtePoNohoOirWsUOnBaKGySFOEHXDMvk0oPXCCRjxBFvgFTxXB+pxQpvIUDiCAkEwClacb344vfDRvGGUgt7U1LnHxoxVkUUgOM0oFZM4vAkIkURGKAFNVHs+GY3CcsgnrIoYMqVMnJsN+3rm48tHQgr/6PLl/n3R0n0C9RFffkQcxAjltWCNIAaCDviiR2XDKmV+eP2KU+OIjeGqD/zabSjMleQTk7J8WH6JKSrW+cxIwbOKLLZgWXo+rjfUukNl4e38LU2G13ggYkgCr8WKuYRJC4sJPIwnznZF1B7RiU5v0Fbx7N/xfvyIDokiwlhUJDyN7vDdQBETRiKvHOjTwsIdlghKaOXMqW1u/OF8oYoXxEdGtULUGpMUF+t5CN/zJj6hl5qLtFQ6UCjN4hPrfOJqW5RyQMYz4wS0UTzZA9kZNsOJ17xljC06ZAYsF9dQzZlTucV3iUf9lo/FWxp386zeyytWZVo1cTYGkkHEoJNhzDWXtONs95wLR5kWkvfsu4j3lsIvtCmgMIiUoCoG6yhkJidYNFQ5YyTRykKYITQ1iKY3jiKPFCGRYuK74oEuZ55MccOAWcPVrXEiDHFFMWWgYHYGSRElkU04smle+Ivnv+O1OfAr+UswiZQMa/vK1TvGAKOvIUOdNSbCAvgceBc+EV3ioh8YaLEEXsstKnrsEnl1a1o10ZYzY9FR65GTWnGQV87aorSgtGLXvfK4eYuVyFg0rHOPykIzBLKPPJctOjpmX7PSZ0ZX8JTf4NLA90Gw8RmloHjWvKlOxKaktR1PrJA48tGu+WTvOFUbtJlQWLLPMJcslTAvFqktWmCxhkXVPNcbllCy1z0tiVWvSDkSqWlkpMoLFT1oxSf3ntUsVPYPsx5+Kea+6I+ihIBUuHBEceOEInwu5goSNy/dJnZMxmEQDBMajXwuIiK3Y0UtgpYZkyeKNKO1psoTWRQ6gbILlep5dQc+7e44pzUXs6aQQFIazIxJGkNkkweueUUzTKzMwFU2dHZPbxQLnoIrsylvrEfgXK/IYkBl7qZXcq2RYFExYOeJc3D01R6URarMNj0Rs3C1DSvTUejM6PaMJCb3jhMHqEp6l3lmRZSCiMWZhV4aklVEXXHxNSZkStHcyzM/0b/lSW941nds5UJQlk4sq3xl0BWxukW5kDWjOnCxW3pVsI4nCt0zmYrObZmxZAyv7gFnFnSKuCSUpqcgECXgBJIC+/k/JzeSJwmHAQIKKyNKGSyZYBzJKbo4MYSBjdn8qGPvT1ZhQOXr51ifI140Dk+aFW4wPLhHLAun2SJKMWw0fbHiWhf0qaVmplIVa/XMpax54yo2cmRKK65pxZqJu3QhWEU/N7RhwBfCfewJUtIVFUe947XcQs6s9IRBU0rAu5ki324/vVqxuJIqLCgj5KxJJvNabDEyY2WknGeKzjN6CzYhSpFdibNXLsU9V99yVg3VsiBKOPkVsymZaViUJ2jHbp5Z5YE/vwy8ySfK8pm5LzgXO5YqIsoy6z02RVbpwjqfmV1JrTLv5iOLWM5UVJ+jinK2WDPx3LxnMCWSoEwTjQhBNoymvu1uG089CV4Fep7pixu+L4glJ02ca8xqIbqMs5EqCAJo03MwFwq/o9PNrWidFlxSBJ9x6spD+cJVb7A5IalABbhUBxbrWbKniAuH8IqTjqf6jmkpOQKnsqYVj9IRQ8JkRRZLlROH84VPdY3zM2ItrZ3ZhCuVmygY6UxFqUY6X1BSsJJnihiY1AYJnrPfMNNS6okmTVQhcZBPaLsQC00dBh7ixG/tmm/X70haM5knCmYmt+MiFWhhVJ7RK/w00x0SySa061mlzDlVtGEkVhEvMxZNiOCD41u75VO5BRLWRNZM9HXJ36efYGd3OwL2v0L0itEqYoI5NMyNw0ShkZ5SLajk2E1XhrRnEs2YWqxRVDHcGhu04km/IaNow8Ss4Gq3zCbRl55Wa/RsqdKCDzAud7x3V/b3uz/IdP9SzH3RH0W+URTtC89+jSiFYUFUJnNL+9ZK0UuLGCHqFvW5YKjomCjoqQEHKlNJx0/HrwluheTbEaMyEaMSk9FE5Xi1O2apmaVgoWbSnkGVeBJJNJW/UqiWgKFNPUpZ6mHkkn9CToJNESMTg27Rongu9qzigASDj4ANaAren34LS8UjD9ghMda3gnGxlotpiHrHfn5h7Y+8TWfepSf+Qf6Grtxy8SVtnGinCYcl25KoDKMrb99BG+7SIywzoClCokgLe3NBRY1yN/TNJCVZLAHDxa4I2dGEC4d84mpaFqvIZCKOq1kTcLdOVCwzLQlFkW7+t2A9SguIRucOqytcXvAKdrzSm5ZBSm6RMhVK3czHm/ARcTWreMUm0MpQ7dsfdcz9qSubEuJCcBahoG8MOwms1Ex+qTm4R5zpqL3ibN9QqcA0z0yFR0KJCZmj2RNNJKEZY8VKz+znnmu1MJiJS1Wym56YnONFdrgcGfLAY/GBb6t3HPUbrA4UekarI4268mH5HjfDt+UDyWrexpmrXtO7GsfA5GFyLRIyvWwpZ8Woa8rDjDGQF81qGZiXLaac8XqmlSOves9i4WN9x918gRQY6oIid3S6RvmAThP9quc3FBAMwoFhgOfdlqFwlOpKOY0EU9JK4G4cqRW0YWFsJoo8MpgCFRRBPJ+KDRGNI3KuG8bF8UsHs3/L4CvO85qDfmHPM15bck7shpHZaXQwPKkd53LPooS4CLP1aLNgzYi1F7LKbPJADD1JIioIi3Lczy+s6kfuwzd0esMkDbOqGNkQkqHMI7iAjxETCj75DxS6J6wtxMCkDM1i0AlWXPCppgoXrNUYHXhvOyQsLMZjp8RQ7hBrGFzFlGtS8nwqd4y6xahMy0AzLrTdTLdt8THiTGYVexZfIkvFQ3dBLwutmrHWUuaBqAx16DkXO+7nJ/4m/S2P8oASwQEfTUlZLZxWnj0njlVNyAWDL3lRG0qXcGqm4UowMOs190tPFwucXNAqsx1Hsi0YkkethOw9sfqKOgDFgvSBV3mPWhyLdpTTgMJgGTjbNXG2t3BtWxBsg+4jVWmp5UrCYpeROTcEDa9+iylHRAsbBpIv6VKBmRyrYsTeryjaP8zD7Zdi7ov+KGrKwPq+590iuDAxG0vSjoVMzw34HrFkfUNCWRWIYj8fxwq3oZqBm8k3F54sCXGWwZQkWjb5RJUKDumFyV54Vm/pTUtKlioNGIS9esLJzIqOQn7L9+pnJBzfVH/GQIsLjkl75pQp4m1Sb+Ir53LPSMPFbGiWQIlQqYlru8eMjpAM++p7vIGLqxntDhWF0Vac/ZZGTbzqgnf+Iz7Pt/DjJbMYw4vdMlCixbBfXqjkis+JYD0JT19sSWKJXtFOJwKRi625mpoiXbion5DEoeJto9OR6EzDEM8MqqRnTa9ufrZKMhlHZzwZQxMvBCCoFmz4vPuZ6VXJoCt8ukW/6AROwUZ3lGomCkxqjY4QDcxui5VMLyt+cnlhEwLvD++pXf1jDrs/aWVbkl2JEGk+B/26JTKaQNdk1soyygM2z8R5jXIW4zLrZcLGiAmwCwuViZTmiNeRi9qhUGymmSo+0bNmm0fi5OnSjlUY+a3/OZOtqdPAxQ5YpanSwm65slEdZdacXcN+7JidJbqMjwljInV65dG9IdgVCyusTjcTuQS0HrjnwtfFzxAjtGPk/fDMYDwvZkfC4qKiS3t2S+BU7+ikwPmBt+MjrRuxC7yUBZ2s0S5i2sAlF5yVIflEUpa5rch9yWQci3WUcUTmmjv9Dft85ttizSgtDQMn43EqYZYJ8Gz7VygzS1lTqIlYWfRgWdKGZVEEH4nO8Kp2KKs5NjsWcShtIAvNPLKmR5tMwFGNgbbs0Qqe846H85Vrqvhp/XdY2yEmY3SmzANP3GH9jC4GIBEpqWK4fbYqyCKM1CwmUi0dZR652g2jrCkN9LZklU/UaqZdAkYLTJGNnXCzMJstcrHYtWJ2nvS5ge2k1yQ/oOeeWBquucIrx1ndbCHeTgS3cCfCh+FILBSDdbz6zY3x7AwOTU/DhGekRs+GMN2CdWevMWQwJffjFXoQ23Nde6r5fLMQOPhq/o7vnKNMkaLbszdn7mQg5sDfrt7zsl0TnfDQP5GjYfQDLjQMDk6upRkDk1V8SC80NuHDwLO0JBc4J8+wKrFLolrP2Nwz64qBzDYtBG1J2X1+gMpoHXAR7sYz17Slp7otzmYD+R8ZzuuLvuhflzOGDx/uKf/hE3XK3C1natPRScX33qARrqomCkRVsMiNSNBwoy78rpCD2+LVU7PgiGiE22SfVIEohUsRpTN3+oU+jYy5AiySYdIlkylYVMGcb8G4hWQGarQ+cJCB9nplb49oMs/6QG92XGRPqQMpQVaWIsBsLVkM2XrGynOVCpt63k+/JhQardZkAgZFrUZsOaEmuHMvJBwnXRBCwRg0u+EVUkXpFdZ0aBuxOFT0lDLSSoeVGwLmyb4jKeHRPkCCzrS0sScpgyhHLQM9Nb2vEKVoOSOiEBSz0kyqBAIJRdKKJo1UqafghW/NL4iqwpKxSajSglKaoCwbdULngFIbekqi0ojSuJwI4jFEsgSWpcLGTBF+1CH3Jy9fVOxjzes8kY3C1MLKf0LpBXfu0PmC0neMeYuWkp+/XPh1G5j9gvYZZwPrpSeYRDdt+GXxHhOFUFl285mtfiG4ltOypzBCowJKboSVTmrSDKuUaPKVw3Tknf2Ik4AVTVYeJ5nBLEzZ4kJkIfHi3zKqFY4IJMo5sOeFyp8YK8OJmpwFHRSiMp0qeDs+84O5ozYDhY54PbObB5IxBL9i0ppQF2zkkbncErKAjFylRBu4mgZlICvHLl0o85WrekdIFbUIQ665Vo6qjhyXDU56KjuSjOYwd2zChY6WiYFYJo7lhkGXOAlUceIhPLPRL/SmZipukPedOtGGmSwF37oCtXiMgoeu4G9GAAAgAElEQVQhUtQLRi84s1DSs+KVxlyo45U/Mx85XR4wemBub9D4wW2RWeG04MyA0pHeNAQtXJsaPU+gMnVYmNCsl2dG5YnJoZSh1TP7cEX0TLVMzFXJtV5RTBMPU8/VbvnoGwwDnV8RZk8RRrR4Up4pnLBeei52CzoiPlP0HclUqBzxOjCYhiEonpJBxTOjtxz1Bom3+Kk34zNbfeQ6vsGZzMd8QHnDrBQpKPb5xMWXyFBjbYP4BTGKoErEakzK4CKb+IRPwu70iEsOU5V8WjmCtxzkiU43NDZgFsOjuiPlBq96tIls9MSazP01MbeKrDOxFqYc6aodkzQ4L9Rq4qvliUF7HuVA0IZePF4yOk4UasJVC02euNRr5KKxs+YwCXqlyeH3i/H6nb4Uc1/0R5G1Nf/R3/wXzJd/yd9/+8xlgTKf+O3OwVYx2ZKLWZFVQZBMy4Rg6WmRHGk5M+gtloAAgqEgMVORuLXxV3nhYXjlL/SvGWbL18XPsRIRFIUsxGwAQyk9o6nxcSLLjEqg9QIzXExDqx1xNsQ0cN4cCNnf/j4NaJVZzSNrvXC1Da9uTW0nbAzUuWNyFRUjzRJwKmCC4WoLptyyThcMidK8UHvDnPY0cWLwntGtUCqi84xLgaAqsoKdfCJJyYvbMyiNlgSiUZJJKEQrAoaj2ZJJKHGs5UjvKz7lLeBZxNLKkVWcebQ7Jl2glaaUhVpGROvPT9meHSeuNAypIaHJKCblbhEJekeTeqrcg1IosagsWBlAObIIOTqWzqKWwDIPhPylAeLHkjO3GJu3+RuO3nM/RbJssXMg2q/4Og3MRc2bLjHJLRx1HS63EO5siN4jVlGpmdEUdK6iVAuSAFmI0ZDRdF6zqJvdIV1bskk89C9sxpldc2Q0npxnrmPLxkRUnvFSUqsztVqYYuYHW1EEQ2EyvTHE7EhiaZcryQgrdeI+Djfm8rLnB/eeIDv2vHCXPvEmP2HGTMJydz2zfur4+qsDU9KYGKnlQgJmGxh0gyihVIF9fCJbRT1PvJo967FnKGpCskQKpiwYs9DmgTfDwCKe/bywcp94sRavIx+uA5OpuaqGy2pmt3zi0b9hlJpViuzTBRGPGNAp8VHfQXCkPOEDtBLReeFiSq5V5Kk9cDcdOec99SAEu2YsHFkbYuW4uxzxuue6WJ78A3OoCcpRqJ5gSrqyYcoVtRqp54lySey7xKlY4ZEbykstoANtCFztlhgqGjMQjaGKPfV4xCwGPwr9riTlzCoHxkmzyoFDnqjDK4WeGESxmIqp9lR2IOmKrBNqUcy+JHihloV2fOa52TAWNZeqIomgc8bNEyoo+rrhVZesYk+7nLEKVEwciw2SDZI823nhZP9v9t5c57YtTdN6Rj+71f3tbs4+EXFOZJGVCYVICkollRCNwMBC2BhIJWFwA9hcAA4mN8AFIOEhIYQEQggEpAqKrIg47W7+ZrWzHS3Gf1QqAyMRGZykYj/mWsYaxhhzfXN87/e+maBgMyQ+bDfYZSYKwaBrduXEjGCuKqqoEaYllplYNMnUVEHSTQEtXzJXj2uHypbaF75aHhDCoG1hQpGU5UzHpW65mA5VXmywunThVfjAXtxxiZFnu0WGiImZe38kKoWdMzquITiqAVzREDva72fy4Qw313/l5/1zMfeZ/0+Q0rLd/Q3+1X/zNX/nNHHee/6H//q/4XH+LU0ujEVQkdiVPUc2qJ8arJFCEQpJpGLEFU/FhMH/pPxKDLFDFIHNAQWQNPepJ5qHl3F39bdfbvKkw4ojl/KWFCXbfOLX42+QtnBc1ghtmNOOTcnooXBZW1aLpy0JbV88jlJOXPuFnTzQq8AkamYhkVScwxYVJLZktt4ymYjrI3VzxtiFpCU/yF9ynw+8y99QrODH8oqndocaBaJMHPQGxIsQ+sZ/QkpJCQmdE0Z4ihD0skMnj8iFLHgJMxMWw0IRhVEaEhIhr6lyZO1PbMeXQY5aL4x5ZtQdBUgSVIIrnojR4OQMaKqf8nCrPHNUHaZcCEITBRgCTkwgBUlIqugx5cyJW7IeOa83PF0kvzv9hj8tf+9n3Xd/yPiQCPVrxv5ENhKbjny/alChZhIOvbxk+k5ZIqqF565hrx2lGCp15l15zyQkRUEVMrG646QNK0ZeiW/BaIoODGrFQoMgosyEkSCixGmJy4mPZsPZzgTW+GVgJWZulgtBvLyktblQnERkAbKh1hGSZQw1r/mGZADj8aXB+YmULBe5BmUYtORqSVyHC9d9ZHAVW34g7Sbu5V/Qi6+ZTYXCIkJHEpZRNrTLGWcn1vnISdzQqw1xtMzzhnzJXMlIoz9iY2aXZw7WcVYKciKIkSYecLFgskXPW+6qiTadQSmmqqGJM52dSbnj2/Ur+mlLJc60fkaKxFU6srfXNEvA+EI9Fy5NYsURmSpuUk89a57EL0klIcSMU4VjWVH0NTf9Ry7JsbQrrvOFECpK5/lO3NDGBaQlSYWSC1/m7/nypHgQ7zheBx478yLjmB2jaOjSQB0Dr/pHUgcn1bFxJ0oQzO4GYmSWK54nsD5yGwesy3wV3rNSBxZa3pfrF9/LNJFFxZ0/MAeFlAIpZq7mHp0lwVZs0hPPZQVZIKLACEFQFciOqiRyTKh44cH+6uWlViduL2dmpfl+vcaWyFwJ7uePvC0Skz1ZZhahCAg+da8ouqE9FyoyVd7zpf/fGVXL1mfehsS+ctjFEuqKdumxgDAa4Q2zTDzoFmsjl6pGy0hVAjpKmly4TRfeLkcWLCLdEYWhirBZFq7iI6Nc8cQN/2dzhUmJlRt4fRl40w/c1Ct0/9k0+DP/P0dKS91cUzfQ7SLqf+xwE9xNJ06yQUtPEYp1OaF/Um9dZI0R5cX2gh4QNLkHKV58mXRF1I6cCwMtz3rHKt6w17fM0TDTkpNmrY6cRIMWhUUIRIY5Ww71ljflB2phCVHSRQjKcbyumJqJvd1gSJgy0OQTXRm4HidOreWg18xaEr1lM/XYXlGM4tJtgESnFlLVUHTiSW750b3htfjAJXV8vYzU0ww648oEViECzH6FlTMX0dKWiS6cUSVg08xoG7axpxUj23jhIzd81PdI9ZKhkTBICiMdBYVEIcSCKUfQgqgFqrxEoVVlYJD1SzyXdkw06BSp5YSKUJcBIQRRaaIy5KyYs0PliBUtqkSSeFEzztLihcXjWETkuJUsj5rBPzGGkcZ+1s39HGSgP8+keWHsGj7INR7HfR85d4bRGXIF7x3MboWPa462QfczSRjOUTDbGpkST/UNle+pS8KFnlHe4CfJfrMCXvzJbFiYrCIE95KZOc0E1RGEw6WJMSl+NPe0aeS3u4br/kCtOt6p3/E6/MjGPfMx3rOkDo/hvbjFN4JRNoysWZ9GcOVlctTAqOBKTNhlxvqRB/2as+h4aP8WVXNBixEpQXqByIpZrFlSxSwr1vnEOhzYLhNqec8n9Qsm7fhmc09UBS9b2jyxHQO74c/5OvyW79xb5qL4YFbc95l3/XuqKRB0IlQzoa1oREtdImdRobznobrioHYcbWS1PPCmPyFK5JAsp6ZGpcil6sAUijIswrBXV+ASXqzYlAsyp5cUhegxUlM2hiF8yb6sMTFilGetJkxeqHLkLCRtObIKJ74c9mzKwl7dE5moBk8Ud4yNYVo7lIc3R4/xBp2u2ZZPqDiyqI7TpmMMO7wp1OlCXcNX+Tu6U03dHUlFc7BrtmPhJA2D8Uid+OX8PVdTzwepSVJDnll7j0ordHCE2lBlyOFlyE1FxWg6ZOio04QpEzb2ZDPg5hMn5VDZI9VMURUpS5bsOOk1jh7VJHKCLh1YcoeNE0VC2kSSX1B+pB0VRMvrcCZN9xS3x1QzCOj1mjELvreeSKRTmvfmjk4aetXQFE8be7pR8vY8ctUMqFC4zRNPcibPI00J3HKiXcCIxFQmUJl2icy7TFIzwp6Zp8Ao3e/lvH8u5j7zs6C0xI1nisocTEsRgm04kFF04kInRi6iAhkwFEbsTwHdNc/yDk3ESI8iAQUjI1NuOLHmL+xXNGpgxUDlR+rYM2nNoNcvbcmkAYU2C5OsICdmKSkz2ByRdsTJwJUcUWLiLDe040hOEhEF8cqjVKATidWc+CTfIaRmNB0VZwQFK3ruljPv0zXHas1eb+jNlhgdU77QLSOTdpxYQwSZA5tlAKXxI5RWEYqkoHm0t4QkyUlSRMKycNEryk/FW50CVUkMokGSyFKjRKIAY1Y8ySsO9pqXHwpsxIWYM4Pc8JLRUMhojJoQCBBwKSsWbcjixboklwJSknTFSKFJHlEKisRFVFQ/tW2yFCSb8OsN1jSE/Fk493NRlcKqavhmvCMGTy81UQa+v8kIfQQtydHQuw2FwpwUR9NQrzNaFM5YPND7a+TCiwyAwKgtJzS5arFIdBipxELxhllkdPEMJvMP6jtu1DMPqiLFGw7VK1QuTKImZ4EgkZUjSU8lZj5tthRpEEFx7T+x1pqJipQFR25An7i+RKTRNAzM1mDLiEkzXZo4pYKoNEVrrIqYnFjKhCqCQTWUJaMXiQiSFGpibvFiZi93nKXDI0lK4IXGF6iQRJv4Ru2wpzM6enSx9FXFpXZ81De0ZiLHHalMPOYVi1DIlHDmwoJmUgUtCkk1BHNPsjVSDcjak4RA1QMbceSLsqdJay5ujciRXtWIeuFSBNdxpAmJXm4ZVE0wGuUlQWlWvaAuPYuwhHTL3cVj04FcAkaNrOTI9bznx27HIDVea4oqLx2OMOK14alrqMeC6Hfo1NPZM0fzikG0HGyD14IqWJg8n7RCtZlt+kAskll2TCZTy5E/HifMsPAEOB9YuQe6lPAps5sGPsk7yBGE4Yv8CScij9wSjCUKgaJwyi25LKSw4eSuwSRYIrlY1ulCrRbOboURhaEYMo679B4bF5YAz2iM2nJwHaIEYpZIuSGViDQzKcz0amEa1nS+8EX5kSxefD3rWbE3LfuVg6w4ix3bpecuHxEhUcoOrQuD3LLkZ9ah5xf6N9h8IaNZ+56NkNipZWpHJqk5dA6TZ1CBnsJcwSQ/a+Y+808RSkuM1eifNvqoNYNoScIgSuE2PXCTPnEQWy40DOoV6SfnuUyLIKFkZM2JjKSUhFSRWVWc3Jo2jJzEmXv9iVFVZCRt7pElMIgNs2hZ5YE5W35b/ogkoIszRUhIgqmxDMUxSkcRhbnRuGXi4BoOsUXKSBQFq0aQmZ18xilJsZpq2fNY3dHFQK0O6LLCCc+Sl5f2Z9RUMXCYd9ja06hHurLwVf/E/yEL79c77PyIqSOVGJEiciVmygK1nmm48BfmNZNyRCle/Kdyps6gyKQESEOdA3UMVGFBqUIxgURizTOPXFOIgCEjSUAqgiwqtvlIlhU6B/ZqRUailKWKE1osJBwhR7xwyJjxun4xeMaRMbRqQhqo2rds3GePuZ+LRguq8kRsDUUsPKsdVTjx1O7Yxh5vQGpBK06MpUaJkXaqWeUjoTE8c4sgMNOy8hN1gugEt+mRWe2I0iIPiqd6xzodqebAxj7T0zF2NUIkXOy59zOf4hs2MXJsKuYsyVLxqa6INrPKZ76vGz7qGzp6FmeJKRGL4yBvqcuREhUhOmbZom3PRV8hY0KLQtQWkXtMUXyqN1xkw7GT/In/37gC3o877OgYbIPJhd1l4vU8swJsHbFVYpMPXHKFkgGVQclCRJKQLFnzoLdkkXl2K7y0yJI4ssM5j68Ev1iOKCSn6g1kyUluqAdP62YIEoV+8bmreqbO0+gDORi0G4i5cNgoYplp1ZnMjr1dsypnAppZQJMjOhZEM/MgXlMVgc2erBxmctynE73TTKplex4pEmILB3YoaViio0ojQhqUiVykoyPR5QtC1bQEgt2Q9reobeGpfcW+tjzZFTp7pC0MJXIQlpQS0e7YzifmpeMpvAMV0GhwjiIjmB7RDsTpp/zrWjNXid3yyKQMq4vANANR1wQP38iv6PzMkjVVmZhqjUsR7TMXu2IqZ4SMXI9HFtEwKouOhkE1XPKBTjwjSmQ1JzbDidVqwCnPkGuW0iKWAZ0T57RhqiEuCXRmJSZKUVy0pdSBTswUnzFZc1AtxvToMrORZ5Kf6bLnvGz4Tn2B0SM6DGy5YIjY1LCOE537h6yjZBcMj+mKZDLJZow7sVwMlRK/l/P+uZj7zM+GNx2P6RW+VAyyw1OByEx0XMqO+/nItfmWB3XLzJZeORa2SBRWLOiS2fpHlM2sQ08UmiQqcgkIXZhTw+/U18RicCIisifIllwUNi9oXkxMMyByJirJanlmqDYgM4LE1h+46BWLqHg0jnU/UMnAQ3WNkhN1sdRhYKpq2nQgGngwdxzVhn23oc1HSkkIEdnGEy6/RCTt1R0+Gaq8ILzGJIsaa3brPSPQS0tG88HcMOmWRTgmW3MVH9nLG0TJaJmxaUaUIyUKDvqWQiHJGpsWQjE0xTOrhl5XUDJGJUp5omSLC4GExOC5S49cs2fC0ZSFB+6Q0iAQGOLLbWNZQBZUXl7sYLIhCM31fEbLBPrMKk90fqTprvnjmz/93GL9GQmV4XT9hvl5eJnilgqbNTZPGLkwl4a96HiVn2j9wFt/5pgyfRNxZUSITOUjH/IVCUlqLXXMCF1hJklTjRiRmcs9mzAza0m1zEzsWM0Dxa4IOKzIrMTImRYUFKEgZ6xM2PTyUnChY6ImSIdImcdyz65MrOYRx8x35i1qkzGpIKKkZMUmjuzjDbkYktTIKLhdjvxqeWSWI00saGZOKdD0AWkD1ykw60QlMpUa8U2klhe+FL9jO535Md5y1Dv80lFcYD14pEoc04p6nqjHmUYu+EbybLe87h94EluKicgoGKWlSzMmB67EkevTmShaUrE09BycY5YSi4MiOYktg66wdkR7jyVw7fcEJXmXvmOk5W7Ys/iW582amoCWkSv/hMiKJnm+GL+nt45DuaPkQFoaklK0YeCoW47CEU1krDpEtLQFVsOempE38UeO9i1UmtFYqmVm3StWYmJUBScVdfQYseC15lFsWeSJcH7N3O84qwpvZg51hxcVxWiqNDO7L9ioJ7pqQbEQnGDCslQSY2YkJ7TyhNnw49WWUgInZ+mTYQi3zLZidYlsZU8UL3q1aBTOeV7lT+zVNXJSdC7wehkwofCs1gTWFFWx8oU+Op5X1ySbmWrL6/wdk6wYpGJKWxYVcbJwv3zEJoeIjjUzZ7MCdebX4cC1f48KklrNPFeGBUkpnnCoSW7F2HQvWcai51w5KJFQS6o8cDErbFwok2bzOLM69lQF8jyRYkbpv9obus/F3Gd+NubYoMeWzk2onDByIaPQeaGbB77+/gdCvaHa7Pl+vaCkQwkQLFAyihGvOgSFKAVjqUlSE+KL+/kqnbi4FQpJKQursLCLz0ipqdOCKQlbJkZZcdIbkp8xdmQRsFkiSXhEHommEMlMesVzu0VECRlckowCbvy3rOWeu/DIY7tjzHeMpiFkQ+9arsIHajIrH6gTfLn8yLfunklrFll4E/ZUwvHjfcelFmjRY0RHFUcWVaPSARsTj9JgguJka0yZWQrMwqIwjMoghEQpjyo9O3FiLh11fploE+oaZRdSkRzMPVZEdInUKZCKYhErjj6hLZhloDEjY3aYJkARFJmwJIQoZKlIouE+PDOIit3lkSRrZAdNLlwVxZ+8fcW7u1/83FvsD5ohK6qu5e7jI79THVUqJGmJQTOVhFgsQhsWWgyZG/8Bl07k1JF9IleRVQhcj9+RLg2i2xNVQTNxm4+8Ovb8IF/xRObMluQVv7r8yEZ9z6IkLh2o5IUydfRcI53kepnYzoEf1h0mZuZiCVGBDMiUmYrjanjmyk/UIhFM4GLW9HLFVlyYpOM+njBJMEhHEGsohrN8xboaOakrUIHkPBcjWWeJmDRCdlgyU+2p/ciuv7AzI7q+cKYBY9kFwSE7Yg7U88L28pESFMcC6ELNiHSW4i0uZE4mcWFLyg1JrajEM715h0ozqlS4dKaOiV5DG094Cb/kG2YdOJgtWSnOeUssFUloGjFyIz+gvWIz9OSkGSvHnh1SNOymnvWiwE20MaN72MSFya95WreMWr1k46aRS94QxctQiQgZYTQtA9kUXJhwfUI2C9USaVXPvlzRxSOFE4REEgmRoMsT69CzymdmtcKnlqNdkV1hurUMteah2jHiaHyiWzKHakcREZtrgqi4TQeqMvGprkhZU+ee1Twj9cIq9bjYsM0DT2pNQ2EVC9FlShUYo8RaT54VWnvUBE0aaZkQxtIsM22cOLuKYiV2yZQC22mg5JbX8sQkBL1smOqGO57wonBJLVXqkSXxqb6C6NiUkS6eWEyhCEP2mqAL58ryvX6LV4o2FURMoBqW3KD8Qh0jj7RIk1lxYBIdJ+soRbHNZ6ohYGmR7i2DvmE8Xz4Xc5/5p4sbmdk9K2ahuDUXkg4EHL9Ov+GrwyfK6iv+6FLxEB/4VH7gH27f0huHp0IiURQWYZloOeotC5YqR1QuZOGZZU3JClUCJmWu+p42ZWatcYAsmXO35SJakpLcVHs28ZnvTIuXLaJYrtOZqDSDWBOFpRKe0UJFIqfMIiuOtiOrAJtAVTyuREoWZClJUrA3V6TiQA8cXQNknk3HJj8zyw1eCsRQeHYNZ1njlcLlhSw0MnlcUohZQKXp5RaKwKQFFz1OLMSiqZKiiP5FUFwSQi2IUtOrlrmq8UkjhEakDFLhOHISryliJImKUhbG9p516nE2sLr0SKFYy56TXVOKZTEGS6QtPT5bdE7c9Ae+fvoL3qyu+Zu//LuY1nG/WvPH775i3a1/7i32B02jDJINqqy46iNXx0eO24kSE2O9wuBppMWkRKUCvoKnYvlUrWgTuLDwZf9AShWDdpyRUCTtyaDjyFELLrUk20T2gs7P1BR25ogaF5okCcOaT7binf2eQuFcO3yt0HheTR9YssX6C2etWeWFugR2pVDNAqELi9EkYJI1smSSFKyqQk4JKQvNlJDZELXiVG9RKeGx2GPDd9U/i5aeoCtcibx6PjCvI6pIknQM5Z67MPBaXjimmmexZpKS0Tp8KjRLwxePz0QLfWs4qC2tWpjk+mVAKEuiiqznEx921wz2C6JyKDXwenzk7XHBqICsNO0U+E52HPQVUsz0dUebRs5uRY6ZodS04kw9BKokufFH+rym7h+YpSReNGYTKVpzK0Yq4dlx4MG95tJsWZyiywt7vQM106gBM2uSUnzv3qDqjFATb9KPjLrDty8a2FAq7qdvMbpHJGhNws2KL84PqGVLuiS205nNtOfD23tG49mrDpTHl8JAh44TjYEsJCdTEXOiEZlettQlcApXBOUJyeGSZygNuVKMqkbXC05O7MSexMKPzWu+7TYUadlOe3QJ6JxwZuJmfKLyltkItmpPk8BXlqO/45QVg7LMtsZR+GK5vJij54pJCtrSI3PmU3nNpTiiSmipCKLBRlBRogX05grEwq/jdzxV16S54OLCwVRkpemFJVeaepaYPGHP6cXY2Cla0fPsGj6ZO9CghOQqzC//Vl6/SAV0RdSrv/JCDj4Xc5/5Gbm9W/GL//4Dq8mzmfaE6wuzcrxZjrhxxx/92b/Iu/mK5//pPycKwUWsCVQEDI4TIzUneUVBoEWgFIUXGqsXyDVzVtTZ04UBNRWiaBmriW1+YjuOfO/eUILEu4pVOrBYS1KaXb4Qs8TKgdG0QCFLgMLFOpKQ5JJYlyPb+cjN8ETuMge7YcVClw9s5oaoL5ALWWY8GaHhgkPbHWNxlCpR+xFhEhe54clcEZRAsPBFeuSRV7RhQsbM1XkhdYVLZUgZhFSsU2SSjkiNROGWkTaf+Dr/OWf3ijk/MHLFJDSzu2amfclQJTKpjllaHJIZw87PIBIexUd1S96If2zJ3OUJnTzSZVJRyFD4cvqBX/ZPXKfI3/j6mn/5b/7b/NE/88+jfk8h0p/5f862kny9fOR0+QYXFWxG1NqwKReiCuhesxiHyhU5G45CM5YbdICUNXOR/GjuuLiaOkoWEo2eSGh8cvioaYthIzxmirgl8Wn1Dmd6lpx5vXxgaVvOyjLWa1o/oKeeqyVTmy21vGB9wMWZnCqOvsLLQpULd/qRoATJzOAlS3HcxJ71PKGbC3PeMirNJDcE41mUohRHJRPIQqYiCkE2mtDCQSXO1TU3w3eQI4WBWFpOD1+x2+65iHumHSSTWIsTpkh29UfUauLLZeEyrRkJdJPjk1FctltSI5hEgw4TIw2qGEzJFNFikqfOgkZ8xwMVh02hJ5NDBV6DhiZOXMkHNvNE8orrtMcRecq3bOPMpCwxtygCG5mp+z0nZbjRI0/+NUNdsW8cq1h4UDdoJlAg5RkbwI0RVhJNIItMMuAxrPuBQsCIiXOlSaMjTx6BxdcJ6Szf7HYMdFRyYjUdSSFxmW54smtiFswycJefyGrP2dzgygUfam7LI7PTqPzi23cTDwTpuF0eOIpfEmJHUpCCwp4Sm/qMXUa69kSjj+SiMEUwxo5gK1xK7MYjToGSkVwyIwYzBpCKvmo5+5kfqzcMFbjsmYrnt6XBDhWIxLzcoPQMS6EJM6VETroBIjlqTClc1BoTJwRgfOLMLV6sECqxt7cUKoYMbkk4ItjEUEn8eqadZ+7imSp7PsZritZczZbJeuqYueE9P+y+wpYv0asvWX1x//MVc0KI/wr4T0op/+U/8dl/Vkr5D/7KV/SZPxhu/+TXXP93/yvy+SPdkJk+GdzqAlnT3Vu+fPuO8J3gKbwl1JkoDIJAEhWnsgUUUsxk3IuZrshYEjpHbPbs2GNKZJNGilbEopm0Q/uWXCtOeoVWM1Z66tijeAnDFrLnIhvO4ppFCSTQ5oUxSxZlMWIhFYOSgbXYI2Rmb7YomXnkDWs50E4nZBE0/sxZ1Xx07xilI5QWw4GWjIgvD59oFNF5TFwQGSozMrX3CNUAACAASURBVCmHlTMmjSTZIoxCJYGOLzeLE5Y2JYICkwfaBERLERWf9FcYP/Mk37Jkw7O85SX/IYOsqEtPSAojA5aJgR1nU6OEBBFJOASZKDSrPCLLS9ySILEb91zPF157z7/1Z3+X+/u3vN69Yd1dfS7k/poRwkR//IDw0AoYWoENkIuiiIqFjnoOtH4iS8uxdZxkgaIYc4tTkU+6IwqFYGZxmoO4ojhB91R46z9xdoalRLRdIA9MrXrRfFZrptHSLZJ1HPG5YqX2fLR3zGXixvzIbXqkmMTRtDTl+SWPORW6AlIJ7PSS8TsWTScHmnygyTOhZCQLNgWEkLgQkCIxaEglMyqFjpaLssicUSUjOTEKybFsqbqJ6RxY156VGllsxJs9zgiqohEqsRYR0QS4jixBYT8VJgQ+ahYrGaygkTNGZHAzUnRQ1izFsQ4KPUg+qpq3sWUdI0NR1NWFnBwpZnKVWIkLVVjI0lG85Fldc1lqMjW700y+Egg9onOmERdKrKlHRVoHqHqE1ojs2I0DPnlCqmCYeXA3VGVC2UQyHbJYAuDyHiSIeiIshmQarAykVGHlTBPO7Nc3/Pn6K35o7sEnVnNmkJpNK7j3nhhnXBrI0rAdzqx8g1YTS63QpbASF9qwEIQiikIXjgy6xeozr/UnRHJwEWzVhVjXPJgrFiEYqQipMIgVFZ46P6FzpMnLi544ZIZ8T1VOPHNNKpLQamSOnLUmLzNWZ+oyshcdi7xFd5ZUHK73eFuhfWFWKw5knuprTMkkq4iXkVpY1sGTtEPLAREtMiuy6FA5cjv/QBKKOdaENjJpTVUCFQvbckZXE3ux4cG+ZpZbtDdc+R+5808gIpX8yEZbdLejWdvfy3n/y97M/Qr4j4QQ/1Ip5T/+6bO//XtZ0Wf+YLj/5Wv+zt//d3n+9j2lCHKIjMszbqu5+/prtus3/C/f/M8sNjKVGi8Mnpd2S6YAAo0klsh12SNT5io+kiQEOgqZJATeRnqxYlAr6jyxmI6qd4y5gVRhpsJsV3TyyJGORsykUr20QYXhKHboElnlA4KMJTBIiRKJjplVOZFiwfmF91XLfTgitCRPgtYukAyIj+iceZKvqLJGeoG0A7UKTLni1K45iwonZ5pyRqEIGD7Ub1ARkj3wSReCMpQiseXFYkXlROc9k7asvAdfMTa3CDkjSAihQUWS0OTiMCngyoyXLQnDgEawUKXAKl/womKvLF5WFATGB764fMft0wWnK7ZyZO00/87f+9f44z/5V0D/fh5Mn/l/z+k88PxxfoltEyNJVkgUyTrcHEiqp5QXmw2VK/KlYVsSIgtsmHBG8t12C3bhQRSkUqQgsCVQKo8ZTlz1R94QCY3kk+h4Nnc82mu26RmcJAvJkFfIpHlUV/ilooiEiBPf6C8pTcRHzbV/5hfhz3nsbqAoinW8HQ7s5sxv5Tu8kVzUFq1OuEuPkDVSZKSMiBJQQuMpGO+p1YU6RFRcY4XnrBuiqFBa8nBzzZvwxL7b8e78G4TMBF8zrhpQLzfbv5q/pUqOOWpCqTistlSzZZUDm/5MnZ+I5S1BCpQpvOY9bY5MQXEKO65PFp0mfH0hmx/pTGKTBKN4zbO4YrLQjgeC3lGXmVlq2tMj1Hes5plLXejvNV4n7uIDz3nHt+srPJrquLCTNTE77JKxShBtYRuOxKliqRI6KXbjSAottRJ4m19Mx1NEJkvlCyE1PLc3mJRp9MBd/IZLU/HRvuYsDYvUJGcpMtMvt2AWRtXSixZDwooZYSqu/Z5FakYsqBXeW67yI7QgFJxXFbt+z+2hZ9MGzmzJ1Gif8MrwtLxlMDVqGfmi/CPu4gOLdBS1xpSMTDVy2FLJE6K7EEPNYjuIkVAU66kn+/hi/2Ezwbzoex+7G2RpWITh1o8kHUlY3ORJ1Kx8RGnPnCRGXyhl5lwJun7BZsPgdkyyQQho4oyeG27KkVX/xHnUPN0YhBQUWWjkTDdNLOaa27CQ7ANBSnbxE71WDOKKnh2NNrzbralIv5fz/pct5o7AvwH8p0KI/wL4934vq/nMHxz3v3zN/S9f/99+949FotVE7TJ38iMfeUtBAJGFFs2MQdKUniAqLCN9umWWDYNqWHPC6YH79IEHCk05c5Q3HFc3hFCD8WzymdlWlLRizitu4z8iqZ6VfGQWjlnUVMWTsMh4JghJnSObcKToTOg0KoNRmY3ck61HZIVEcmCD9zWzrri+FLbVi0WBtJmr8Rs+ra94YocqhawVbR5BCgoFlwemZJl1wwdzzwx0+cQkVizSUHIkC4FyB5KUXFpJKRKNJCM5iGuKLCgBNo0swmLI5OLoYo/LIyfZsehrZv1SPG7jnjrVGBEJwqJFwIrAr0j863/2t6hX17y5u+P+9t3nQu6vOX5JTM5w8IbYdjzrNZvpgSBqbpdAqAeOOiNjoBUHevuKXQjoGOlYSDZiS6bzAwfRUpmRZ3lFkhqnMrK2NJxREqIp4KBJR3TqEAFCWVP5HkeiCmeeuo6m3nOSKx7lKxYKberJIjM1cEwNN/FInTQ+rci55aIzxSa8dUgiz3bD/SnT2kRuFx5dy1Bp3NzjjCXhObsVqRRctry+RK7sBy7cUOzMpdqw8Y/QBbwNiKB40jUyBGJxNEA8v6PxE6dVzcf2nj5KrJIE9Z7QXXBiZlVW9KxfJhnzwsZ/4Fnu2MWBkmu0Gblb/YArA3u9JS8OpRaq9okpbclI9mrN7QyzWKMu04sVUe05bRwRyYBhkZ4nVXMqW6I3XPOBapII6zB94c00cxPO2CHwuDGciubVEGirAc+GlfUstNzOI2M1sy49WRtiqriaR1o1IcTCRk/8zt6z5IrFOVyeWVLF1XJBFkBaNsORRWZMmpCN4KO55yS2mDKjBsONfkJNFU1WYASb+Qd+rG5p5IFTXdjJR1zoaXSgiIr3qiNayUG2yFLB5Uuufc9aDZy3ikqPjGrHIBzq0rIuC4oR3U7IWRKkxugFSsHFPZUH6QvSdSy2ISWHlQHhTiRdmHUkk3FzhRkNY2vIReLtyDoMrOQeU2lOZcc5rZEszCZzUz6yqT+yPQqCr9mKAXUqzMKhjOIunZkvG4TV+FVGqcgmn1ilH/hkdyRdMdMxxZpuWHDi99PB+MsWc6KUEoH/UAjx7wP/LbD7vazoM5/5CaUlr67hvvqWD7zijXhPQuGLpWTDnAKyFKJQ7NVrVF74Xn2NyuCVISvJhAOuqVNPlJlB1wQ0Jg4UCotQPNs1SVmylNRxxuYFUyaESJDgVnwi0XApjlpOdCUya8toOzZhhGTpfrLt+Lr8A6S0iKA4jq/47eoXUCVCVgiV2Y4jxUaSHfheviYT6E1NEIZerlmVgZQFm9TDYlAWglAIMrNxhKKIUtOEhJANMge86KhCosjCIhU5ZCo505UDUbRkXoYxVnlClcJV2jOhCXqFVIL8k0FLSoYmn9FZcVYVWiQMnqwVJ5Gx7T3/3J/+C2j9WWr7150YI0voWbkevQykWPEQXzG5VxTds3PfsbhMIVCbiBULO/mEmTM0nnTRTO7FjkbpBakrmjgw6A49WV6FyHWy1NIyBrgyZ/aba1CCt3lC54LPhr3q8EKytDumYinGk8pLvvFQr+inBu1mOn9kTI5iG6KHrA111aNUhW8kk64gF6o0gqrIMoEIiCLQcsEUycbPnNUKSwAjuM4PXJkJnQ88oDlSgXJ8b76ky088p8y+3rIoQ3IT12lPLUaiMIzxmh/G15xTRdaZRYzEdg3BM1RbUhYvutqgONgbXscfiElADETZcGMfWItn3jdvWYSgbxzNxdMYeB9/xVltEUVw3RdqqanijvYwU1zHphZs9JGiCj5bXIi0omcwK2bXMklJnSdmu2N7almVI8jAzfKEUhWVGIm6vOh9/QVftRx1w5Jv8fLMdlpYl8BB3GCEYuUFampZCUFd9sisCctIQXI/7QnSMhdBlzK78wj2zKU0OKHRwH2cQF0YlCK5wPNyjdIeoRxBtJzyW76zG9oyceUD2+YDVYF945ikREqPPQWyqFEyInSPTZkoBSfVsk0eLFTJ83+x9y4v1217ftdn3OdtXZ/be9l7n1uRihJE4QTsiEFtCoqoXYMJMWDXkBLBhiAU+A9oOsaGDcWOthQsEFSQqFCWCYlV1rnss/d+3/e5rdu8jquNZwuHcIJJ1dnZu8z76ax5GWuusVhr/hjzN8bv+23NO1I5MZkK6y2KjEgBWRu2ZWIsLXaOPFcZVUZuxTNtfWaRhRQsc7OiTSMhKmQsWPnMrXhHTeA6Dji/cCCiXebRVEQNuSRU1eNXDSHUjMsd1fh/wbXCJ8l7tWFZrUglINNAM020nCgy4lVFWbY0ZUMX1lTzGlm+XdHg//j/3Sil/HUhxP8J/NvfSI8+8pFfogwPNOVALVoey2+SMTgRsOLASihOXJMEDNLRqMRcLDotzKp5sbQSgS73DHJDBgINPmui1mRRXrTXRMAWT+0n2qVHT7BpDzzoHQHJyJZuPuMIJKkYRYNmwUvDUW7oxMQqe5asEaliCh0xGw5qw6AaRI4kVRNc4rFRWEZu5Ih3FaJUjLLBhELNQJ0nZA7YAXoaojQMuiFoiUTQpiOlGJrs8aLGzQuD03hR0coLrXjkYq8xOZNFjSsDUnhEFugc8WXNbpmIakU2iqJAkQhodAqYAD8Kf4sDLUEZ6jyzE2fGrHm6fDOegh/59ZNSQvoBqz6wNFvOTtK7QucD06Kx8ojOmqbxHPKeSMWn4xc8irecVcvTquHYtkRvyXrA5iMoR50KqxxoU6RXiqd6j5AzfVvTliOIin28IOOa5AMf9BorRwa1okk9vTQEYSlxRofCZunRQuDZsY3PWJl5qF4TsXxQK6KAmBStOiEXWPsebSQhdwQlmUXFKnkIAitGSl7hZELFhk0ZsfECekZyJlvF6/PnbJjYykdUJbDVCTM7QsqoAj5IjnLDRUmkSLwVZyY6rIUwrriYwBmHDoUnu+ZJVnTDmjI2TLpwaRtKFMiy4LJnyY6DXXFiRWgcTZkoYuH15UReDHqSrFJEIOm1IVnDnAoH+wlzkeymQJESLQUrH7heLmzLSOcth/E1g4yU9Uwg0YURWRIXV1Enh3cKXSJOPHJor6jmE0fZ0sjA98dH2pCxMtAMHodFHG/xnaeWibfTM6lYLD0jHUIv5LZw2yfUIXJ2O466BZHZlp7rdCInxSQNpepwl4QxF6JUxFhRtECriNwM/Fy/pTOFWWqu0oE6enpbofCcO0MtW7Ty7Jb3BCFRQnLWLdfqgQ0P5NgwjStWuUJNhVE4Tq6ln3cY4GqMqHLP0dRs2vcEJMVofJaUUJCi56dXn1LpGW/esunPONWz7ntqFi7yhkWnl2l0OSFz5KG6o4tn1P7McNQUcU2pJSIbPlR7sq8ps2ZoNDfLAwd9R1wc5IygR+CZQ2BQO3LJ38g9//c1mCul/Cd/1/7/Dvyb30iPPvKRX+L8vNDHhpwUnb4wiZaRhrNYkVRhEWtknogYSnlRbRfyxXSeLKizB6EYUsdgWjwtQnl25RGXFqK0hNIgY0AkxWYICCxjkTxxgxKwJJD5inUaOeuGs9lCTqzEgSaNpFwxZkUvGq7iEylLxmGFnFtqk5iFJNQgNMwq45WGuAb5Mp1lS0LIwtYvmBSZZMWDXTGJBps9MkmCdqiSyEJjcqBbek5K4Y3jLCuSlCxKY8SajKLkiMkjCknKGZ9bTJ6o0oDKC5V0uJIYaKg4EXJNkpb39hOyeZk+02Kil1tcXHCV5ZROLGH5mJn7E4BSiriMRJ/YLQkTRzZNjzALrZs5B8u9ecVBb5jpcClCp9GXCV0SY1khF8XOz5hY08oDlRhZizMOAzYj9YWQr7Cl4HPF2/SATo8YDxfe8LP6M2b9UhU9Sk3SGygZGSK1HzG6YMXEpswEIaAIfDFMWhNwXGjJIpC0JsuC15l9mtnogJX3nH1HKYlzWdPba4RY6GtH7c8UkZhjQWSLEOBGhQgtF7mmmhdGoVjLkcFYoisEnfGp5qvqR0hdkVpDHQKv1IHXw8R1/54/aH9IDpZoQc/3YCMlZUYcJ7Xl1HT0tSCJmhgN+fILTtLwoPcYEdFyZH8+spQGkxO16Hmrv8CZike3YmbN5FsqMVKSpEsLz+5T9tMzMl+4Oh0w0TPtDO+4RTtJjA4TtwzrA0/tLSFZJtGxnxNn5RBF0qQTj96x6EAIFl8a7s01vtHEEHhQr7gbjzAnRCqsppGOCD7RVGfaOdKuv2CwNe06EWjoBsE6CwbX8aT2PLeOWWYUhSAFUGEnyTpkTrqmrQvJr1lkJs8V6hLwt5JAQZaApEFUMBhLneBtf8YdVvhGMeHp6nv24QNOB3bLwKy22FPHiRW3cmJ3nqkG+Jnd8eW6cCHi7ESTZh7sFW4ZiUGyiY94uUZJz86PPKiOTIsOnoP8IVE/Y4Jipw5Uw8T91nGSOzwTZ7Wl1hl9LRFpxdkajmXLYhS2CLKEk1zhi4OYuR1f3CHW5QOVhMq+YjaWWY60/Pplmz5G5Y98p8mlZrnsUF4RtGNUFQFLRoFIJCSuFDQjpsxosRDFi2fpIFtOvGTSDMuL/ygTNTO2eKxIGBIyLVRpYokrHtUti6tZh3uKk/S5JQpNnZ9YeJFjyEISi6ZnixwfqeVMyYI6zkxyxVU6sfUVP50K6/YZ7QwqGUgVSSp0XGhzIOeA0oF1uCBTYbf0ZAWpiuALQ6x4tluCkrg0v3xudlQhYkqiSzNHo0EKajy5FEwZ2ZWBodSILLkuD1jp+YX4DCc8Z9NxkZpBWVbigZITfaq5qBaAIBwTNUJEWjJkkEXTeE/tLFl8M0+VH/n1orWmbm5R8x1N0RASd9NIlRPIE5UZuOHDS4V1NGyXQhUrxAVmkRDOUHkLSbGRgkomrBOctGSsMr2IJOX5kAU5rVn8mpU8c5cHooZBFors2eYe6eH78zsW1ZEXQbSO66RR8QRMrNUFHw234cJiFH9HbZipGeMGE3tkCGh5oWRYxBYvR7q00CyCEcnBWVycSVXC+oTJitVlwouKN+ORh9IyLoY6e44GogRRapw/8aqfeWgKX3Q/IlBxL6+4zUeyFazGE7qc+N480uiF5z4zlITqE42auMwji4XJWGyaiDR40YIUHPSGo/KIYcbJQl0uTMbylG9Ya09eZW4u9+R9xE09urQUF2n6jFeSxdYo+VJBfqPONCqyaWfCww3uaJhMxokTP6lvOVaSuG1BRdZz4HO946IzTUr4JNmqC1pNmFwoYuYqHtDdB6SVrO2Zk48M0ZLbEaEtOnq8C1TnCpk0wcAUGha1QoiB4+oVYm6QOEQqTKZCxIyzRyQzdZyRi2byW+ol0JWZG/EVqkCRNb+IW56ahugjbfTocmYxjgToMtGVnqZ4KlEjFolzmjafSWnF4B0xbHku30dPimAdc29ZnU4kp3C3J2zOVG5hoCaEDYNeU8+OIVdsTw/Y5RnVfMpB14iScGFiKi2zaLkXhk9ifJmlmQvHwXKOLcWcqcOCFWd8qUihIhg42xqTIglNVWY2lxFfBEUrjp1jpb+iCyeyDAxB8GwrFuZv5p7/Rq76kY/8mti9eUX3P9+yOva88Y+YKnFULc/u+sVTVAgGtcaIkYhB5oiX7msbqkSXerTMtKlnLo4iICswcWZVeta5cEjXxAQTjrmuSEqQRKKdL8y2QpXCY3vDOvRMylHlQJCKQMWH9o5r/4zyml18T+UmXJ6Yqx4tT8ziFhkkuzwgZE9Mkt5prOqBzL480qc97/SnDLqjUOjKhUU1JOVAFFTJeOEQJNZlYhN7NupInQaO0jLrDYIX9fFtPiIwmBRp84kVR0CzLiMuDbyrr3jQeybV0ERBm09cVIuQkSheJAwoO0Iy9Oy5je9Js8A6w35lqEz17f4hPvL3jbR7nLxl9/wlQsB1e0bIRMmZ1FeItUUtAqsVUlhW4SUL7EXi1fLMOpzRRXJL4HkbWM9nfL1Gi5lSS3QpbPOEihmeRpyVGFtYGomQAz7fIIolCEEVFubsECViYmHVL8R2JopMNgkTHJUJXOSarR95EhW1T9hx5rQzqKzZxDOfyRkpAKWpywBqz2ZMPDeKRSpMDjiZacOCaiJTbbkLAycMP3UNuZt5LywslvrSUc1nWr1QiqIuA1JvmCtNFgptIzlK5pIxQaPEM1ZZ1vIZEwaGcCKLC496TyMuGLlG50AQBpEkaVJIrticTqA12zJSrOQmjbw3NW07kuLCIBPqeaChZY6Kp+0OVRIHsaUOB7xS2FGg8pGge1JZM68CRRpmO3PWDTJFFrNF14/oFBBIiolQMlfHCzZm2kPhXq1oxJG23HPJHWcF2fXMc8XkKoReQEt2ORFtwzu1IWdPYcKKE4JEXgr1dEFJQSTi48wiLNbA1fRMzpIP9jVT3mDyBlUEl/mOp/oKmwpTrhiS4Lp/YugqRBixwfOsGlohkMKxvqz4vLnl/25vuWjBNR/4Qey48ifO/pY5KtbNSG8lsbV8uf4UKTN9NSLbSM1EJY8swmApmCSZ5A63HZlVxV34Au0NmzzQlMCXTYeIKy6uw84DYn7ElMh+mSHsKXNFtg7Vz5iNpDiYqw1NfFkes42B6/mB5/GaR+soQhN0zeBvuS8WaS8E7zCHgbjEb+R+/1YGc0KIPfBfAN8Hfgb866WUw69o998C/zTwP5VS/sVfOv7XgX8WOH196M+XUn73m+31R74N7n70Q/7Mb/xjuK/+Jm61cKUeObUnfne3YtQVVo4IoXAl49HUeEwJxKIpUrCohsJClhrHzKJqFip6eUVJlhIjVZlJ3tKrhHHLyxSQ8FS+cMeRrOAottz6I4O7cNA7iqwxKeFTh748s2B5V93QqZH33S1uSUQl6cSFqOCsrrieBpyXsJmRbUIAV+lASFu2eUQli3eRlZiJBLoy8Ch3OGZirpH5JUiPcoWVw0vFnph5E79EyshdesfKDxzTHW0MjPbFpqwtE1J4zrYmKsUzVxQhcGLmJh4QSfJev2YWgaAMKr9UsBagaKCWXPnEq/YKoz5qycGfjBgmak3dbonvjgQb2DwseNmzyB1W7lmbB9owUWXJkl6xOmdmv8M1A1GEF/P1lCi2EOYWUT8jYyYoxVIsudREUdPLFdYkcnnmTfE8yFuezBX9ssUNkUk7rM9IM9LkmUWtWZxCqUwXjmzjkeQDs3CEpeMuH1Ayc/IWEyxyCWi/cK16wrihtTP4DCYzWU2TZ8awZVsGHDMye7IKaFWYVcWn8cC+RJ7UmkVY7k1HnxSXyqB9ptI9dekZZUcXR1alp1pG1pyo04TQM3nZoLWlFAi20BbBKxk4lRVmHLGl8KP+9/G+ZpSOaFfsyszAmuYoGHcNTZScXUNMe0qeGPWK5/QabT1i1eEeHN4YqpRRcubsDCklTq7QlgW1gJctwbxYZ9Es3O9vmWRLnRuauSf7BqUUQnhC0SQRuYgtUUmU73kljqzySOeOFDNxKQ0384VT9T1maWhzYDsJBnnNu+4Vi+pZB49B0k93ZBcZW81GnWl8YPN0RLgjp02NZeTt9ICXhiVuqHpB6K4gLtR5oSBxWbBIgxKFRVcIn0nLmk08k1Ok1j1GFnwdGJrEWh7Q0mAXwxS2DJcdiynI+ozXF6gLk1ekGlyIrJqBk6zQGLr5TOt69mnkQ7PG5R6TA8/2ilVMOD+yziea3HN0r6iSYKHCjh8wSnF2HTFp+rpGEbnOF6SJ3PQDxSQW01LCESECt+GBH07vmJeZ/9W84RfV9/A6UEqNSRPbfCbXF4ZpQ4rfzLDr28rM/RbwO6WU3xZC/NbX+3/1V7T7j4AG+Ld+xbm/Ukr5r77BPn7kO4Dbbvmn/tV/hR/87J/g1J/4kE78L3/nb/C3xcyjWjF8vfZgJLwYwosWSaBCIpJHFrjO94BA5IIXiqI0XjbUcSanxJvhge2S+KnxnIvBiJlO9byZH/lgb+iD4axbBm2o5chq/AW/3/0GKStORvP56jW2h15e8yp+ztBWrNSJsTWMvkMoQfAtXTwyaDAqEhEc9TUqRA7lLYPeUhw0eeD7w3tmbfm5vuZkrpH5xdLmNp4wamKSlotqqfSMEQsgGan4ik9RNhOTJllLQaFkQGeo8oIqif3yyNFdo4mMcsUHeY2kcFXeMcqWc2lB1hzFml16pkkjLieGZs3TofDJsuCc+1b/E98RvvMxbLNbEa4V91++Z9KOc7GE9IZTu0LPniqIFzHaAt0lUz1bUpPoSw25osgjbekRYeDNYjBpYKdbkonEEujlhllKJtPRrI4QYEBjpsDdcmaZNb50nGpDzoqlDjAHqhgwy4IYM5O8xi8rVFyj1ImlagnJU02KUAZ+erVny4FkDXU/YVKFTomjXdErzVHvmNtMLBWvxoUoJ1x/ZlgLJlfhjeYP/Vtu1AnhRrQSdOJCpS8M0vGpz1Qh8Gf93+Kpvn7RODMakQJOLLghouSFg6q47yJmkTzvOsrFU+xCfdEYJ7hYxSQ2vJlm7oiEpZDmN5zcmribWKpMM/W4/sI+aEycyM7hs0WFgvQZawR1HkhOc69bqGbqQdGca4JQfJn3/PzmNTE7RlcYVoVeVSzaMcVCiYbdMNFROK8LZ6EoJtDX4NJE6iTtU6Da3nPJa46yRU6Cx7znZDuKlgymYymJo3jFxTQEo4jzjEwagUZVApUUss68mb/E1zU1CyXUFK85upYWT2U9MtUgDthLwGuIrnDWDZfGYnmklMyn/gk9wbHOTCiMWjhKgTBwzolDXSPJbNSMngqP3Z5gE6YYXFpomTmpNYuuMWYBAbs80yyWWe8pTEQh0DmRraZPOwa9Yh0fOWvDjpm+rEFYonxRSXinOmoXeXQrTBgRYuR6eeIqLmSZyUFjg+NWnVFpRi6JT5cJN92QRU1HxuqXwrKD6ViJFSEa2vJELSdq9+1Kk/y6+ZeAP/f19n8G/A/8tDnAGwAAIABJREFUikBYSvkdIcSf+7uPf+QfLdx2y90/+WPugDfnR/7G5/8HoTg0BcSLeHAulogEUaiiQumFbbgwCEekQskJITOCiIiJTOFsNkhR+MPyhn168Si9Ds9ot9AsE1HVdP0Rr67YcCbqFyHdjgs2ekZR0cuW0FjaMtK3Nbm8YhGOrKEUidEzW3/mkjL3VUUomqxAYIhFk1KF8fB2fqZmRsqFqj7hUmGlDUNQ2JhQObLmyFlsWIyjiAbPRC0GliwZ2KABLyts9pxVjckLqtQoWRBJosvCngNLrBBZ04uWpbQoNfIqfclQOgbzpxDFk0RBlML7+jV7eSANGwap8d5/HMy98J2PYUkKHm4afvrpFX001POESbCaZvRSeF5fMakVE4KVjNB6ooZGC6SHobXkpUHUA7I84mNFcRe2DJyWG5LsELqmE5JOGLIqHMI1gj29WVGbhE8VbZgpJrLPPTc800nBiogcJQ8YdCroNiLFntfpPSehiHpmiQZU4VCtQa4QSnIzT7QlsSTH2Rk6+YSnQaUjZRmYVGZ0HUOj+GDf8ln8gsk3zKPgT6cv+cP6FbVYUHNB+YWLachyj4875FJIVYMYIzhBihGUZ7GFtIApIIQlzI5BBYQ9kXaKJCNP6YZa91xMy4/GA/q4I48n5C7RO89gKn7KDathpPJHplwResd5s+EiM42OuNQTVmCEoJawXx7o1Zpz1VCCoJZrikuMEp7FiqxmHJ6cJVVZqJdILzq8qViyRS2SQQremzUb+cyy67m2F96bT6gyPOeGVo68t3csypFsRcmAiXivKGomKLjinqty4KmqSCWhxUQ0ibPWWBRxtXCpEtYm7t0n7C8jlp51nriezqiiiJc7tqcPLOtrLtJSi0cu5Y5qkRQFIVRk0/L5ZsdmOXPsDNf9ez4tR5pF8r3wJQx3/O39DeSKbBQpHeipuYgVTnj24R1CC85pxU/qO8QoqOUDTX7iKj/wqNcoIutwpj1NHNWOyW6YVcd2mBCzoZUBqx0Kz2IijolaDkwu8wvbIcOat2HBqonPThdGXxEPllRHLkLzcG04mTUX42i8RBVBO3m0ljQ+8EnV0onwjdzv39Zg7q6U8g6glPJOCHH7R7jGfyiE+PeB3wF+q5Sy/KpGQoi/BPwlgM8+++yP2t+PfEeomprviR1d6nmkAwQAQmQkIDEodUHniEwL2VaM2aCEZhse+Uz8hGf2DLIjZMeCA5eYzDVXvifTsQ0L1+WJJ7nmnX3Fz+xnHNyaOnmU2nOyaxYMTRwhJ7CQatAENvnAQk0jJmwKjLqiKQNaJaQv7P2R92WHCiDFHpJBGs9yNmjnKd3C0WgO6YoYFE56MBmtZ2y6cJCfkiS4MpMzpCR54DUns0ZSSAg2IoLIZGkIRZCFwwaHEz31OKOcptctnopRtXQicq/fYtKIEJGcJQVNRqBLQZZCkj1L9lj7USj4a/6hxLA/Tvw6js+czn9I8hcoN2hpab1jMHCpCr6e0GomLY6vmop53ZCDJOvMn1m+gGQx7XvCauISKlJacU5vCb4nNAqVEmcpkLlHlJFrZro4IcwHkJ6dfOTnZoZxQ19L9LiiW57Yi8CuF/z+Zs9ZrxH5wtv4iOYlq9wIw1EKUKBVYpQVrRgo0vC+WyHTQr2MGDHiSqCYCyZIllVD9IHZ6K+n9cDHK1JYiDPk1HLnJzrRE5LlEq4Zc4XKe2bRUExB6wLJ0y5n1see86bmQe6IlUWJmWVR+J3m2Uq82rEae85uQ5onyJpwcFyExDrwJjA0IxHBWj2wSiNN5Tkqy7O+5mAcctRs/RNmmmjTmS4UwgyLK5QMOQtKkjyxA73i86qlJEeJitUycJEZlKReBjYpcj0kvlrXZGHphWQqCl0CWSSiEJxdy2XdsF0mgnR8Xu5Ycs2xrVCy0KUJ8sRUbUgiY0gYG/CipUkjX1SvyKlmk86MUrHSI+fGMZkakARtmdsFpw0hFuYPChsteYLVVaZvBg5O8yTWbOZHGvEl5CuabcIR6OWKW97zZNcc3ZpGJ2SciVJS10eapeeJHTFvKaWH0XBdJlzJGFFR5QtOjORlpPEwLI6LfgXWkqNiF3uEPFCFhS5bmhCZW0VzSdjRM6rIuVkxqhXPUhFMYafvuZmfkCj68xXhokiVolfXeJHpKwe5JnZnHp0lu4wSM1rNLKLl9za/yS72eNb86HwkHE9w/UeIFv8ffGODOSHEfw+8+hWn/r1fw+X/XeA9YIG/xssT8X/wqxqWUv7a12348Y9/XH4Nn/2RbxGRFa9qyZ+9/B7JBD6YmZE1EY2kYIisy4TkRe5DyQRGENA8mlfkLBlFR1HghWWmRucVKz8TXI31C4PQaDKLM5zNCsh46UBCJyI35RHhE2PcoEyBUkBCkyZUlOzTI4urGWnJSXDMkiZf8NpyoUN6zUr02HIPWlCXEVlnYlBUYcSqmVqNuDhThxljPUOxnE2NB0pRqOBQ2XNUe06uIwhDISMQzNKRi0IXjy0Zk89krSkh4W2NEolVXhhlS0+Hzh5vVkixZ6JGCb5eyF2h48ycLKvlyK7L/0hl5b4LMeyPE7+mwwPL/edYazlpyzg52n5Flw/kKjLNkaWRaOlZqopFJO7UOx7VNYdtpnAhNwKv1zzpG6qsGHyDGTpuTiPrUTF0hpWY6YRnV84McY2xZ6TsWZSkMg9cy8DdMeOWhSaNVKrwUH+PXlt8EngL0cB++UBSC4f4Kb1q6M2azTThWDDyJSt2vTyR3MxkKxAF4WEj3iOFYhI7bpPgJ7srelm44p67wfDpg6OZDfPK0SRPo6H3BiUGKie5X19xrDpKiDSc6RiAzKR3LAHqPPHsKtZzJJiRzSHxvFV4Z0hNYuWfueQdz2JDcoVJS4ow1L7nYjK9ssjcEUNLwy+waqDhwJK25NjyZG7oYuYLAit9JiZLNwXqMZPKSGVnpEgIAtcPE8XUnHVFLBqtBFfqgs6ZKg9MVSAXhx4rlq5iypZuPtGLlpILQglSMWQxkYzEECgebM7UKbNPPdsQaMIHYnFU8kinAiIqGgYqOWHjTCsDwRT+4GrHc7VnUh2mvBTDxNSy94/gB7KRCGBZDVjpiUlT+yd8KegwYvFQegZ9y5w6Rrni3twQhGZxLT0z0QxUQ+CpUtwTeRCFLntuo2ZSFZHMIgon4TmYNUkqngtMThCjZjP13MgzS2VZqgrrF2ozMlUN780bBuW4ST2jmCDMSCLJb7gVAzf6A5U90LVnprwhbwRzjEQh0aHCyAlRNZxKpujAs11xsRVKJ46uxoRAKA0ziokt792GccnfiOPCNzaYK6X8C3+vc0KID0KI118/0b4G7v8Br/3u681FCPGfAv/OH6OrH/kThCiGcS7oeOY2P5CKhvyBTI3LI7NYs84nYrFs8zNDWjHJhiwgKomXbyhIiihIErJkTMkvHo5ihZOWHBw/qR1XywcO9ZpnuSFLSQZkjlxkTRsGSqhBSZbkMGRulgfaErAlvohFukKMhWe3oxA4yx15eib4FW/CE9flieQy780nBDRf1bc4NzLoH7AvT9RqZqsf2MkHvhCf8WX5BF0EmplazLRl4AEHKFJ5capt44V1mikKYpEkYV6yFCIiReYgVhz0hpQNlEhVBmKxLEWjCi9OE7LF5szMFpOeUFnQpSPE87f98/9D5U96DJPDwm/MhgcfuVYnVK8ZleMnqy2jjox1pF0OSDmzpMRDu+GSFK7U1Pw+WsEcBCJnSq3xXlJkhyiWPu6ZaknQE1U+EMtCMQMuSFLK6LQw1DU6eqScWPeCWATncsW7dcNiVoxCcm4kNxJKBj05GCrmGgIaFz0n03F3OiC1py0nFqsYkyNnSatnitNMsqUUy6okoqvZhyO7CMJkXgvFtS483Al63/C42SN9Ida8FAbVM0MdsNxztBU6T6ziiE8BqQtGwUkYfEzUw8xDZxlKRUbT5hGTI33ZouaFECWrYeR+tSJVmnWlqUJiNY1s1MyOibty5D5dcXYNi2gIVYemZ7WMjJtMiAqhNWUWKASNWBil4Z14xaYseGqC1y+Z92zoUkbWHp0913HiRpyY5oa+EthgiNmQXY30E9080pAwVpCpMEmyZMdZX0HKNMszV/7C1eHCuLnmXjXopWIQt0yNfplyzjUtF5JQLLQc5RUizhAVoSi6+cRxW1NhSLrBpplHXkFzwbjEQUYu2jIaQxon1krg5oHr+BXv9fe5HQ5kobkbvuIkNyQsXihOYosuA2LRCB2YteJYFbr8zD5fkL1mqBwBSWg9iyq0csZNjmoSfDBvSbPC2Qv7aUIuNXf5mbkOoK7IOuNzYZMWRE6oEklTRWwtJmdqkSAGeiFQ1YxKPVItfJA3DNkiRODKR9QcyNZy4488uQ6hMgOOY3K8Dieczdj9N5CW49ubZv1vgH8D+O2vX//rf5A3/1IQFcC/DPzNX38XP/JdJPmFh0Ph9/Y/5ll0HMWKK/nAXf4SmwOT6KFk3qm3HPQP6OWKXCRVGtBCUBQkDBLPTMc2XYBMlc+c9YakIxfn6K0iGoGMnq2YEPlIKyeuwgNWBaTJHOsNLntMbpBZMHCFL4HG9pSi8TSMS4tMkaAtg92wSgtzXFMNFZ2+cNSKWViyUSih2PiRZ3VNWSp63dIsMw/6e2g8tcgIJoIWNGpkxZmvzBsUCZczkoL+2inGlUC3eC6me7GjSYl16kl2i8qZIDJGJDbxSFIOFTUXvcKkBVFmrsOFg1RslgU7ChZfo3T3rf723zG+8zGs665YuQ0+3ZPFwmN3zcG33Ls1g5iJOiNSQklBt0yY8R1OBmxSdGPk0X6Pn69aJmNZkkFnRStfqjnXg8QLcLrnfdNxlRaqvOfcNJA3HNOet8sXBAzGjugbwRINT80tJ2qEEISlUJWZfTiStSYoQQqC89LQdxJTCnf5mTfhmTknopBkEit9QSfFSEMucLI3hA6mObGZIzfmTKcUdRh5GwJBrxGmUPIVfdNg1YVLZWjkQFALtdbk8OIKk5bARWgMBe09SUq0gDpJBlkRysgb8Y6TumE1ebLUFLEQEjRmYbxqGUwD3pGF5JoeLWeaouh8oomWVyky+CN3Q8Wpk8h6YGw6ege5CIqo8bklnQOvpy8QTvJJuKcthmG0DFpQjT/jabNhQRNFhc4LVZjY+oE/Vb7g5+YWnwJCBVRe2PNMMTVTckgfMNqTUqGdM1FGfjB8QKrAJ+ILbF1T0gfKUDGaiifToSZF4kLjPCrCVb4QhWI0ikFuqL3HBI8SDkJmtSzUpUdX4L1nQyBGy06ekH3E7Q2dnV50QSUc0iccSoeUHo1iFjtSXZGEQFBICobwmrnSUASiZHKyGJlQFbzKj/xBc8u5dAxixVIMZZkRWTHriiIX6hTIoSMVhQ2BUdWMynJpFWoUWJ2wIiJD5s4/E+kw3SPGe/pqxRw7vqhfs14+MGnH98dImxV7debsBJkOM9TshYE2cjsdECVT0pGQ12znCe22KPX/r2rW3wb+SyHEXwA+B/41ACHEj4G/XEr5i1/v/4/AnwY6IcQXwF8opfx3wH8uhLjhZcHU7wJ/+Vv4Dh/5FsghEswWHxKpVWgKVkQ2+YwlYHPhZ+pTznJFkQpKZMNIRNOlMzE5Rlmo48KkC7fzkWgCKz8j0iMDNZd6jSJzFg2IhSReJE6aONGWM0JIBrFiVB1BKkyBOi64kDEIznJNIWPDhIuOCYXIiiYOrJcZEyV9eoWJDel8Zt42LNmxWMuQK+bieFQ7dM7caU9UNXNeMU0bFqu5yfc0ZebCBrJinQeEKCShacrCNg3s5wOTsjRlImtB8eJlEOsNY9tQpMALKF6g9YJkYSkSmQtFagbVYGJGL4kQOsTSkKZMjPGjA8QL3/kYdvPqDddvf5PjT06s5oovqoDQJ3qzYrAVOWdM3uOyJAmJC4Lq/KLTdgqfMMkN1WAIokWrAanBlMTZrSlrRdET0Uq0TZAih9Ry9lve9M/0q8SZHUjFehzJVPS2JejCaAyahUYPdOHMpBw6SB6zRMWaTSyE9TMmJbIoTEoxJ02bMjkqxrzCpILTlkPtuAjLLjxRaDBecOUzbgmsYiaJhZgjKSxMWJLKBO2Zmz3nWSFyTaawFEUVJ354+kOiXXOUeyZnSSvP3eVLpFxxLtcYJxjkll1+os0FkVeMYoUomY06Y/SRe7OnlBrRC37z6QkXnqk2Fl0sxUoqoPFgguAkA1UZOaqa4goX85rkC91UMPZM3mt0mVnrM6eHTxARrJrJtWUzJvbTPf64YW0/sPYDdR2Jcsenl0Twnto+ky2sTU8W0Moz4VwT6gqkBK/IsuUctmgzEoLGZ03G4cyIkQNBSpK64hIbbqcznT/RycJ759jHgVrAVfjAqVT8vHlFaAKVvuXTxVOdDUVKFnHFHDomm0ghYpeZqdRMWdGkmiAE5/WKxYBNmU/mnrUfESKxSxNkyywNuMQ6TIQSGFWhlp5ZOSZ1yxwdiyksxYGAr6pPWGePSs90fkKWjHus2BfBUjRaaFRvaWwhlxbnF0SSzNLxoTOUAJ/MCyOWMxsO+fplGUEzAyNHNRMXR9AFoaEuF94Kw+wTZwMuj5RQXlR0gmclMs18YTk9we3rX/ft/u0M5kopT8A//yuO/2/AX/yl/X/m7/H+f+6b691HvsuoyvKP79+werjnoTNo4bElYsuMEoVfqFe813d4KpIA0OzKCU2gYiAz4sWeIjReWQZraMvMigErM7J0yJhZ6RMP4havWygFIwQSSLFipOHJ7DDMNGnCJYkLCZs7AiAoGAKYzFY/cpUiJkhuygeKFix15FQVvgzfQ4kTcsnY/4e99+aVNNvS9J6tPxnqiMysrOqrWkwLdJPE0CAJggCtGZq0aPIfEvRpkMYA49OYnp7bfVVVZh4VJ8Qnt6Rx2qTBIbpwUUA+vyCAFWvHG2vv9b7VgpKSq90Q0JSgOFUVx3yDEYkZRxMWAjVKF0bVcLI7mgAegWXE6MiunJGlYOXAS33LVVbYUvhQvsde9whTsE1B5YXFaIrVaHFlLhvaHFiKpU9XbMl0ceQ2zrhlpF0j4bqQUvoq5viJnGHSUvTPkOY/UcQTRkZEqOnEgBoV0WWaErm7rjAJag/NmnElILNgjSvTZsNSVzT5wmIrRAnInGinZz7ZPdFpoogUXWjExKQcr77DLDP3rw/Eg8DEjlgXnF7YFc+jqkAEmnzC6ERKiuIdJ19hysi2/y132qOUwAtN0C3BNkQvIVfUVtPPkhVFCheiaskoqlzY5IUl95R5RXqYyw0kTz1HdnokNmeucg8ykGxhpGU/DNzPI6O2uNoy5RpZBCk0mDXwWH5B1XiUkNznZ65FI1zkxX7Alx3XtMeqK0Iu1OXMtoxUa0Bnxa0rGJP50s+UuUbohtvo2dkXih35UGpsnlhrS0oztijG1CJQvLiWIjw2KjY5YLSknydMM9GGJzbZ8k/VgZwbjvyMzj8Q9RndZFTybGJNHV7ZiAeCyQzc8GDuSVkRqeiWBTcmPuZXkB4fJZ/thgMjUSjydSHUjjYGQj6R/AafDWd7Sw6CWVmcO9KKCx/KD0zqlyidMaGQaJjEhnpTMFGTTOHVVKQgGefIfp7RwiOFxocDZ7uligERoaBIVOgykLThuTgGtcc7gyojdQIVPKOpGURFkyNGTNR+4ZJvkUpjyZgE+6QpxkFI1PmBXk14Wv7RfSC4yFxJ3vPIXhVkHfmy3BCKJePJTvLa3nKVMAvLpVSokCg0bJZMm2ZIZ9pyYsyCpCqu9cpT3YLXnMwdjV9ozZFv9PcoLXmKLWuaf5R2/3oqf+UnhW4q/ua/+S/4X//3/4P/7csT3l3o9BM36sKl2iLNP4/lESSgYiVT8NRkIxhLDRJWIVAiI1VEhkiVF749f2GWNc/yjpe+I0nBoFoyEktkpuZcbvFesJoanw3P5oZeD7R2ZRPO5GjRJdHFiVPbcd1Y9uECA8hJ81xtGJXlNsBSaex6YCqCSUyQBJKELhGtA0ZKIgaRBbNqKE2hyyMiZLoIV63IZFbRcLe+QFxQKeC1wgvJTXiic4qL2LJUjhUo64ilIRRJFWdu1hOdOfKIJYrIJO8QUlKHmb040Q6Zm+uFSb55Iyml/qj1/8r/d07nkcfhe2bxxJS+oP0HfNLcLs/MsSWJRO8jh2HmqN8TreHVLbTrzG6a0NPMO/nEUma8y+hp5YbIVXxgtDWmzGzXKwOC1bSkEJHCoFKNy2eyaunOR455/5a72ktmKpo0YllJWqBLoPKJF/kRmzU6QlpbFt3TuCuL6uimiIsJ7QOieU/xiZxafJog99QFjKx5fw3sr3sedcfVP/L99iPd9UplJT+ff2AfRzblE895QnjPGLb42vLKDVpeuI8DrZyZimHQhuBaBJobceUmvPAS/5xJdyxKEGfBzA1JaUZj0MIwyppGeTZpeJsYiTuuMpHtgSDONO5IbDzHjUaUgl8jZsrkEtGiRlKxD55v4onLsOfcaZCZqTJUy8QQzmzdEaTFmsJQLDMKRskkE2X7jKgWzuqGf6r2DLJlSZa7omiWhTa9ctQ1alJYlRlM/SbUqivJZLCZhYpH2YPPNJuJjXilLyP6VPGy3jM2El8sqVvYyZEgIjv5SFMfsfoeGVYyNWuqCDkhwsxsNIuLhGpGrLzFjL0K2lgY2j3sNVIVvIGUw1uWtq9ZQsvNfKVbBy4bT640UfZM2tD5CZUUcVQEIZgHeKlvmBtJUhErC+0aaSbPpnqg5UJjPjHrHoSnyDvu1pnnuqYqGscAeWXta67Jspiaj/ERM46EzRbrLdJobsOEySsf1PfoMoPoCEGz6J4sMyUXVMpYNeBF4iBnksws0dHkhDMT/kdSXV/F3Fd+cjTf3vM//i//lj/7+3/kH7/8E36ueTn+A//x0NGpmdt05FlmEpa+XInFUoTkIhpGcYMUK0Ym6rIwiYaoDJ9dYSxbPpQv7MKV35c7ooSKmRVHSJILG5qQmWXHmgVBghAJJ2ZMWlmVpgkzJ9cRjECXCBFKFEQ6JqOYpWCsNb+2e6ol0IuZOTeoEhFSkErGElAlcJMnbvMzEy2H8kywDSFmjMmYEGl9RxYCMrxfLlyrRGwKKgV+Z96TMDRcqf/ZdHhykllLujxxlQ1tnkBZRlGxlLdN2S7Nb67oKXC3nthGyGScFRxubr9O5X5CLPGIjr/GeM9EixUjqcD7NXFNA806Yccbiu7IITCZBakyo0pEo4kZxOHMO3niXLWMRQKCd/kHXIx423I2HSoutOlEG8DbjNHgiiTpBj9MVFUgFk8RQKzZjAGlPJUd2fiRXCyBzM18BqnQomLDQB0ip9BTSkEnQ4OgTXDNK5OsmNXb91pmRT8LtqOgXgeCXPnc7vlUN3yQC6+6wew78C29WDmWPSIXjIM6v1AFRS2hCytCdxQl0DKxGU605ZleZaQw7OSFL+KWV2l4dHskFdu0oLIgSU1cLTlUbOoLFRdUu5DoCMaQxY6QIkmcWWSHLhOxUXTpGV8bbpdMlIp6OCFCRfSepBRL7MnawOkVtQfvDzgFozXEqeWH9h1GKgojOWYexJZFBtbKs4kDSlY0wlOWhkHXjOUDZlOwExzWSBNndDzzKDt8LCyyovEaYTNfVI8Sgr+cPsMCIlXkLKhjxseGUGoq9YmC5kF8RAdBtyyMlaOWy5tPIUe0jVgyc9lw1De07QKx53XMwMpWfOH2qklFgtfE1tOz8tq3pKMh9hZnA6SBJGtUEFQ5M1mB0lfcemSze8XExBwaHktN5TRdPqNrw36WqGzJVcUgK17UlrHApPY0Z0/fjxzCAzLv+I0yaJtwgNUjGkWRhcFYYinUKbI9z0Sn8KWjjRBjoX0SvNw7BiWQecGVEYpDYjiUEy1nZJQEe481/Y/S719P5q/8JLE3e3713/1rfsW/5jf/7v/k3//f/xe+c9gmIGJAmkIQkovoyaKQcRQEEk9XrpgMXX4lCvfmDq4yp6pHhsSjveUqdwyqJ2Co0sI2DlQpM1eWPl6hOIQUeNnwyoGrDOicaeXIiT26ZKKQJKdoped+XSEXlmIpySNE5C480y0JISSLT8xNpm3O3OQLSq/IUZJcxaIqBrkhkzibA00cadTCbjnSqpnP8p7XSuOtJeeEVIkkNXOpKFlxFZJOXllER8S+rdWLwibOiLKwiB4hPFk0tPHEz/337OeJ28cT4WmPryo+frtjd/gxFuq/8mPRmogQF2KRlARyUYS5o2YgVhqhIj8cenxRPNU9RSZ24pW7/MDmMuAS/G7zHQMKXOFfnX9DvNzSiETILbWYecrvaKaFJ3vHi4g8i57GCOrYchsutHZkagPB1jzqHVe9Y5GwnUY+xB+o5lee+/dkrpw+ZHJypNjhw467+EoUPSV6fDqwrp7sanQSmBLYpIFjuiUpz5WKq12IsePUVAThWF3DZ5Npo6L3kR+qW36oN0QUW/lEkwKqRKxJ1LPH6CtT7HgfnpjzHpUFlSoc1hFSZghPJP0t1dLRlDf/s14MhDxwag+MVcPYvePn80KdNU/1DuV3JKv50/ELiEy7zsy2JynJOtbMr2BLpFosgy2Uq6OqFtp9ISh4tTsogn/45q84pBNjHaiXhbhWhDUjq4BME1qdSW1C2wtbcabJO2ZTECXjfKEJEXA477keBKFeCMIxBdCtJClJ0YoQDTasnERH1JaoJy5O8k6O7M4WcbMymBa0RC4V9RW+3/0S5IQrmUbNbL3kJmYmDSLP3CyPkDW1W1lNRbvMXPMdbRkx2mO1RnMhi5UuzbyyQRjHzmQ2NycWLCKpt6ctCWRxDKKwZM1ad9Ri5EF/wIyS1QpC02DDkRez4ePpicl4bs3vySrS68wxb2nWK6VUVMbwIj5wdRYdHUoqGulp48RBjqTsIChCFKikyQF+fXPHriiKlPzd8/foJbMWMENhUwPTwp39ghUrngrzWlGvB3x1y7sP37E9e7LSAAAgAElEQVTZ3fwo/f5VzH3lJ4/zM2L9hjRt2VQzD9UBVQoZzYp7+5ftT0idCcKyizM2rtzmLzy7D2QpeOKWqgRaeeVL9Q4vBaYkNDN1LigV2KYzq2zQUtKsmiQDTbmQjaNmYJIb1mxZSk2XFyxv+atdntnKE7kprHZHFVYO+UK9HDlWd0wpgl45yAutOGGCRFiPlz2X0lHHiFdvWamWQFdWZBI0cuB+faEIxbXs2S4Dz1VLkBCwnMwBVQSFgl4lRQoW4ViRFGF5VLe0pSUnSEohKJAk/ei5nS7c939HOdTcfPuOm2/ecdjf/bFL/ZX/DDrb8bH7FbP5gR/iA2f1LdNG8SBu2EwLRyvwOjML98+xbyt38Qs38hXnItdU0zCw9yNn2zConqa9MgnBs+7IThCKx6mAuVoOa6AuZzZ5JiHZesG+CuzFmauqGOeO3UUyOkO3eu7QoA98jjuycxwrWGNN7QeGcMd22aKFhjURXEM3JwqRoEY+jAtLvdL6iasvTKkFPCl5mnXHYjQHHznEFQkMqsdLR0qStcBn95Gf58/s1xW3JPSrwemKpRUEVVFaRV5WFr0DTqyNJvjMqCo8hqB7NlzYzp7beOY/NIVefeFqavb+9yxiQ5VHbF5Zljvcc0PUDU4Ztr3hoe/QMRBdRiyKoBLIiKsC19phiqBCcpcu9Dnwe9Nxf/7MVf+cedGcuIfqwtRY7tSJSWoerwf6nOhl5Dv9iOVCEwXN1FMLyWe75XkD0UhWKTBqods9EatClwN1Cjykj4gSibnDzIHZCV51g7rzfAyP5LPhsj1Ql5FXpbDzHeLaUUVJEC2KlVplribRyGfeT/+RFslUbnhiQ14aLmvLaePIdWarCu+HkVv3heBvKMIhJWzzkTa2jOwJWWGk5z6d6cfMb7XmqC1VHomyIEQkGYXRlsXe4IJhuxiOZIZqzylrorbkJfLSCv5e/wxTNFV4izuDhjpasgq0y8q8CUQpSFISguXmGaSDEBJNMFwrTz8HnivHU95zJ1Z26sjgKkrdkpJiiAeKKAhlSaoiy0Jv3tPt/oKm2vwo/f5VzH3lJ89md8DqwLFzfGpuWKXDo0lFgCgkClEL9nmizg/8ovzAIjWdvBKz4yI25CKYqfm9/ZYrhigsOWmsKrTpEaMyRr5lFG5zQsYZbxoupmOmJhTF242npi0zVfacdU8REKSki1eatFCnlUUJ5BxBSmSemNot0bakAo18RbqBRdYQEoNtUeXN4JgUWJXji2jo1IWtEDy7lhAzY8nMecuQJaW4t+tdLYmiIMrbhHKbRjZlwSuByBMSwYYTJQkGGjZ+5nB95RBf+fO//h/4L//mf6Jve2KOOFtRueaPXeqv/GeQ5QZr/oKydZjZsFZbnoVkcDVTvdJevtAUw1RVWDVRzVdcXujjiVs/8GU88Gzfc1QVUzK4BEeTeRTvsFITteR+9LRlorgHLBMqtVSDJRpYKpjqClmBSQUjFUehkSXQhlecWrnODarN7MuJJSkGUShK82hbRIIht+zSRBQwbldErbBVZMDR5BWzSnKUDE3Dqx/fNriVoGdCFUG3XNmGwC6cmFvB42aHt4ImL+yXZ+a8YZAB9olBSGyaCauhkYb9OXPedDzqGR1m8jTzQX1miGeW/mfM0vKH6iMlFFblUAKiUgRZUYJgGTdoEwmy8P3OkUtNsx7YLxc2wlC/nBH9gloCokrIaAFD6FayKSiViGXD/KrRubBQUdJKM0W8TNR2JKaEEAuz23LKd6zy7bN20SPVAVdeyGNGGs03Q0W4fWHUK1+M5aIrBicx2TPKnlFsWGtHs5yxYqBUGasXunzGigmBwLYrshmZZEFMnjBO1LNCaolQgW4eMU1LcFf25QWRPZI7Tvpbkn9PUg2DE+j0lpDTqSOqHXDe0y0nHCudlFRVjQ4LDzazUvFQepbc08lXbnhmCTVZJc5qx7PKXMSG2yIQU8HohauEtWRqlViQDFoQLAhRqP0VqMlJIawnGsmiF1YcH0vgEK9YBnr/yGf9gSf7ESENi6uwVeLaVqzuBhUCoVuJeuWxrsjCMFrY+CujVYzC0JwhaMOd8CAG1scrflyofgTz9a9i7is/eWalmW9HWnfC0RKLwpAIOeOY8EqRZMVCRIjCXCrG0nCfP9OUgVe5p48Dn/Q9CkuR+u2KVCciPUcnOMQHluIYRc9JtQg7AwFbytthIXq2DIioufUXNvOJW/fMRr9QpKJSK0HW9NOF0TR8c3kkIPlyf89cWaKyqBB54p5DOZKTItWOVCTb+YJTMypIGvmI14ZdfKG3M0UmVqkhJ2ZpWXVHEG+bfjrPLKJHF08UYOKKDYLKBapcQEq2q6dMifd+5ls9UFUrf/3Lv+ObP/lbdrsbKlv9scv7lf+fhJT5p1z4LATOPlOsYlDvsF5yVhW1bXi3fk9XSxo/QYD6y0xlPNlqupL55suFsdLkukZoz6gtr7VGSkdbIl9ayZr2uLzSSc938ZG1dPwQ3vNSd/z65obartyGie14ZXfJ5CWyFRFT1zhZsZ8KVwlV9kjr+cKeEB1kQTQtU2/RaaBeEyavHNZXxNKyESPFW2yjYZw5xpqiLYLI5nQhuwlvPcEucDqxe0nsSmFqG4zKxFDj0ahR8NTW/JYtldX0IlJkTai3HG3DWa2MTrIzz+h1S1lrTLK08ojXNWuW7MYZ3Z4xMTPgaOXKzpxwRaGniigyCcfUwFpbLAvXW+hVpJaZqpoRa+CqNhzFDV4Y7v0jPys/YMOObz99ZrpMJJM4N3ccTaZtEr04vU3Vi0Clwku554YHnLowqpohNSC3zGaiqv6JTjhOeYf00KULRizsyshtuMLqeIqeWAqtP7PLZ76YPYNpibqmdoowgjAdgxG8i1e0v2LMBbsYGgIlrYx2plUnTrZnVX/GRdwzxy2LOXA1kIm0XLk0FlSFv2yx0wBJMduOadmglkK7kdytirN+898M6UibzjyYDU8q8mpv2V5GbtNACJoYalZZ0cSZu+QxaSbXhixARc+j3bDkhsfuPc0w0lcDvzz/mpPueW16ZKl4LJqfT2eqakIIwT4PuPI9cn7Hsy0YBGGU/KHfUUn4vbllUwrRrmzyE1f9kQf1DbM3mLxSpYEgI8+01NIic+I6TWwO23/xfv8q5r7yk+dleWbdzqAFRi5EuWGXz9i84nFUEmox0XHF0xDK27uxSznQTQM3zQs5CqJxRASlgCkZLSSZgGJlpaMIR5COUAzRKFT2zLqh9jOz7OjD+hYnFka6GFnK21p8NIqyZEZb4dxMrUb66ol/1H/JQMsoOyiFSlYsuWUSK7tloeQLvvwJR6WRKrGPr8jcoxdLtI6Qaq7WvS1m6AuX3PNqt1AyoRi6NFAY2aYJmzOjqtF+5k+mT/zJ8AVhHeXaQpD8zYdv+Mv/6r+nP3S4ZkfTfhVyP3WWshDDgJiPrGZGpiey27EGyaQbNFdkPfLny++Z2DF7y/fNRw7rhuoq2fJAsxu52gPSBS6NZhEGazxD6slzw4EjdlnYyWcGXfEydgy2Y15bojGEXMBbUokIDfs2wAKV8UyHjFQLQsPtsNDIzJMrnPUetOSz1WiuqDyyCsnSFSrzxCgyIkTqsyCvGa9nTvXKg62oo+AiNaIuzFKgguVh5xBq4RwrIpY+zLh8xaaJJFY+Hd7xqrYwKapxwpSCHTJBZzquXLoNL9nw6+0vOFwGfF3RpMCx3FGJwj5dqEPN2dQsMrCICPZIFDUmBWLMFGZmJelKIKdMP79ykYHRVQzWYPQt7XnlsW6ohwvTvsXnSFMglbepGKWhPq4YubzljhrJfX5BVGcGwLQBe9kSkuOTuwdr8dZQUo/yPYmeD/OVW3+hlD1DUWRbs8knkq6Yk6bOE21ckCGyVAU7zfQqoH3FqnrmdESkmaxbzrLHVB03aqKsAvILRWUinthlMCuNuaLDHrO29PXCnyQIZcbnRNEzdXhhrB1DbN7SHZYNOzlTt2cWIXgXThj7DWmwXGxiJ89oN6E50CTLOWtCbvF6S21WZqWoFlBhZKcHNv7KSb1Hy4WNkPThzIvccLe+YkWmWs40LjEG2PrAZHpe519yX/6Bfj2xUYlPKTOKG4qOpFJRREW/rjRTYN4YXiqNFRMmVaRVsmNkuyZWA0ZMNKKgTcElUFYj3Y9zrn4Vc1/5yTOpgrTgyLzLDyw05FwISjHjSMKwlBsWWVGHiadyQJfIVezYqhN38Qtf1EeaMmJL5CR6QtIkFFIqgjAYmRExsghN1IWmLPTimcItTVrRBewssSaiVsVqNColKHCYX7mPZ6Tw+Mqx5YVlV2FCoNWJFCaiLMgE2fdofWXOgiIsMntWlZnlltUV9FRoy0qKFZ91xVIUOhdEykgSudJIElEpbpcnUnGgCjlbgtREBaPf4j6d+TCAEFdu/vov+G//zf9M/+5f3sjyK388jDSU+ZFq/U9kceI78coyK8ayw6oOsSk8sUeFlY1cuLoNn9V7xnbiJpzoPUhxgbDjW/2Fs2iphKf1CZ8nstyj4sLi9hwXaOSEkwsjW15tzZPpiCawkTM+LoTY0dhMuhPk4sgmUIrmQVqcyWziRBoNVT3RrwtJJ7RumJu33lPzjJ0WLv17hEhcK8M2/J6126K4UFeO7nVBjxm7RupWICVcBIzZMitFjA3beaXtT+yCx1SBeT1g8wsn9ozWMesNHZk6B14ryWADxngUkba8GRX96WlAqYFN9ZldHJhihUwbtmni5Cyv7Cl+j/VHVIDWvFLUjHQLs215bgyzcsjs8I3DLo61OWOTopkrLrbDZkGWheQrRI4EO+LshSRnFlVBLJS1pdEjh7yS7MKN+Q98CJ5ldtRzxUt1x9XcIEti0Jar6KjHhbJuubteyXcXGl0o+cKkLTUrwdUkDOWyJ0nLayfI0rC3ETfdkNaWD+cJ0ydEf+RWDZzbHem1Qasn7tQzIUfGpWcVGsGRb1PBDe/fzJfliqkGjAiY4kEZtrUEu0VEyynsuJr3GO+RfsUtCyff45fIo+kpQGUcUimMhCF7NuUTQtfcpIVNCjzVO6xzlNlwF79g4sqz+nMGtgg0VTY4DdZKbk/PnMeKbO4oco89rQzultsSaJVhX3tCN+OKxwZwYSXKe2ILdVGI3GDlylAlNvqMzzucDOzi9zRuosqaV7lhzh2UmtraH6Xfv4q5r/zkOdR7tFb0ZUTkQpNHfqd/TpAGT0VdRnIOQMYUj//nR7axwFh3VHnkIF655pZFO7bhQpEGHSeS0egUsCRWaalYiEUzywpLj02BrThyE17Yh4nFt5zMHSenmURDk2dqk3jy3zM2jp18JgnBGDuW4phFg4yGJo98iIlGnOiWkVForlJz7nqC1BQhcLPEpUxdFoT2hLIjl5oUM1dxi5QaFwNZZaoMWVr6csHFmbPYs4otq3Q8mBu+7F75i1/c8zd/+1/zzV/9Fa7/cR7lfuWPh/QLefjEORdkLUiisCkTRMNUKoRMNGSkFzzLA38o96x1zUh5W4bxP2c+KK5yyyg79usrfya+54v8QAmFUCbaU+TcQTVFKl1YhvcUXdEwcztK5BjoU6BzBi0dipFP+wMax6kpbNcVF1c6Bq7KM0rLZBZK0tynZ0xWqGrFY6nlSBZHimzZlIXHUpP3DVDo5AsxW1wdOSTPYfM9z+U9R2vw+Y6zUiAE9+sAyiC95FI6nimcs8OuV3bTI2NzQ24TWSr24ZWYNMHENxNdU3jZOEoM0DzzUbzQMdC4jJXPGLdwTFuqkJBxwoVIlII+H7ld/8A+G656Qz1rrnLDxVSEfOAiFXcl0OcVqxTSOHZzy11MnLrCQ68IsUYPNa2zbLPj2kqsh9+5e2qredUdJkmcLqA0ODithpPYcDLt2yR2PaPzmS4KggKtDGY1WAq4lVqsoAJf2CHXwp29IGjIWWDGiC4FLRrCvBBFoGdlW0mKvGEVDVxhVoJeRfpwYqufCAKYJmYlSGWDEZmkNWexIZoVXxTv5BFZFHN9w3kUzEODWyP79JmT25Kz56I6el9IeuWD+D2hq4npCzHfEPyVP6iKY9riZeK11MTUsPMnwuoww4LyO0QQdG4lr4k+StoYWdMtA/BhOhHimU8bzed7ScwHkrd8TGd+W3/Ds3XMuaUVDV1Y+OV54LI9YspKjcRFzew3vE+/Zakyjk/08oViNHHZsZES23V81zhUTj9Kv38Vc1/5yWOFoR56TvodP+gND9ywZgsFvHKUIhAKPIlFNdykE68cGETLQR+Zyx1N8aw0XGVLJTIJw24908RXZt0QpGAWGyoW+nJmKhUtM14orrJnlR3P9VtEj68UV1UThEVHSbueGKuOhGAsW0RWdOnK++HM4va4eQS38m15QiiPyJlr1XKu35zqAxZVCl7X6GbGl8hQ9QylJQmJyJlsCo1fcGolFcF9OfIx/UC/LpiQoFbMpsGmN0G73m/403/7b/jFuz/7Y5fvKz8SIZwpyUJoseqFlQ2tT+zECy5FpA1UUZCXjqf6V5zbnqM5oJcXohZMB0UqkKjJS0UaNajIfqnZK8OTNfx2v+PiPJX1fBcWjL+yXTO/PxyYFURh2XwKrPme2G04t4FH61lSz5ILc3DchmdOpSYphZeaQ4ycZcveFoQJ2PzClBzby4BZCkNuOLWKS2+wecciDU2G98sRtyY6l6GN1FNiEj3KFxagC2d01kTlKMHz3LT4quDCRM5gWXhtQRbPi+mwQiOBOybO3PKn8wMy9RSulP1ISC9U+REzO1q/UA9H6uLwuuZx/oZjuqHETEkD2iqMDhy1ZhA7bBQgNZ0ITGi8cJzbhvfzkZIEWVT8wR5Y4kxkopYjqu4xosFOClkM1QgntlyfGsouMoqatdswhUSXA3nWTLT0ekCIAeWuHIUhZ41NgeY8sJ0mQrCoyjPlntkZQnJIa1hKYhHN201BK9BekC4ZqRRedxyFAnlhjQWdEmCZe4ekJgC344DQK69yx+d6w+xrXIYlCrRb2YRXiiy8Xy7s6z0XMRBFg1CFMFYc0z0lNNgwcuk0wSkqsQFvUGFmlRH8ke/FHTF79vkBESQxdQxrRTGGUTX8wRhGveFiJG4eEW5Fe8NWWGbzDVNXGL1me05szAkJ+ByYVc+kE143TFXFEhRSCHalcNu9UrhQyj3BVOgksSKTJkl7esHpH9BSI1qFjRoTDXYd2FQSW32dzH3lK/+vxMtMlBmrB2oUcEuSGjLUaSSmwuwOKDETiqNWHovHsHJfvvAP/CsCNTFbVM4IldBJMsodfbzi8kqxDicHrrolRQlFEvJKLoKj3JGUQ4uMkRKvDIu0FCEYJEjRU4cFzcKl2pO9Imf7z+/ddvQ5U8Ujtb5AUqwqc3YdV7YYEl0eIQtU8kymoYmRal3pyiNj6TFpedvYdYZGDBQB78MDLsBQGoRSdOtKlxeaJXKzHLk5VGzb2z926b7yI6LdBoyihA1rtUGKxNykNzf6deW76RkXFcfyHY9py/0CFx2olMABsgi8rAjaIv3C7llwM99iy4rY7BhrQ6sMmk9clWOmxauKOloO84ofXnm8u2FwhnPj+FUuLLYQNaxtREZNXzLv85XiLmQ58Fv9S6JoSAaWcGDjXxH2PXcqsWx7muuJX738lqstmLynVJknpZmk4iozWp/53AqqShGMoviCSZLVVKiyYGXEyZFKVjx7y5hrOkacL8iuYag3aFUweeLb9BsG3ZFIiHVkaTeEoDDOU6UT0SWGRUGcUaNGzAKiRklDsziSTez8RLCKKd2QybC+R9sDPljktLJaTUOhDzMjNX+Q9zjleWwOFJNJa0O/SPp8JpJ57Q1fmorHZFmCZI0jyRi8kCQN25hxSlC0IVeK1XhWF+jSiV5fOeeatvGUVVHMK09RIUyFiRVbsdB5iS5XhuSQSlOZjJkzc3Ycwpl2e+RT/pagBacAIii00ijRMDc1Ol/pfGYqlofpnkqPjLbC5MTSXHl1LUXNXM2eFFtKEYwpME6WixlYLi0o+OA9997x2jqOtWBjZu7WK5nERfbkWJiFoy1nOnll8i1hlahYsSkzRTaU2FPHhCg7tIA+J5Q0zDkR28Bv7IaoN4gVpkmQxIXVKoyZyXZl0hVn9jzYLcF7DCAZ8W5hUTCUDpEHUkmseuZ9SqwWdk8R3URE1aGHHuvfodsbul98x+0v3qHMjyO7voq5r/zkkUojhj1Tu+NB33PWW6q8MhfHrgwMomIlYop/i8cqmS69IITkS74nKc0kDVEqAoaxCMiCWlaU/I5oHbNWrFJTsDTiyCa/0pWVEBUP7p4kYVWWRq1s0gilh/yWU1inkVUqVrcny0QwDWtIFK1Q4cTQ1DRh5LWq6MPKJNxbbJdMxFKhvKdOmUbOHHXFKByxdLybvtDLF7r6xKBblCgc4gsxG5yPXPUOo2ce7D0344nKe5pSeL9O/Ey9xwn5xy7dV35EzOaA+uZviY9/zzpKdv6RfYlouZJyoYk1IhhEcsxOcpEOGaHEhBYLt/IVH2qmcofMK893mtvLBPGWz/sNMYycRX5bChIap4a3JaIqoKRk3b/H64agI68W+ulM5QWbkAhFccEyqcQcDVlsKLZFSotXDuyOB/ENo3niu/WJpCNrUNBp+uFMvs6oreEzjkdzoB3PPNktNIlVdTCfmYUmiYhyE6ZYrPJkVWBdudgdzerpfcIZAM1K5t0yc7WRKiQYr2yiYO4aRBZUU0aGmaEThErzEjuyLIxL5n6ciSWhrCTKQhug6jyNqbnYluh+ziIlA4klSaLOmKgQ6yt+v2UWGa8MevGkemJyhW0eGUVFSpoSIhtR6EXNc0zshx+QVrBRE3W3MhTDnGrW3HGSDb0XSAT9esKVmV0+0+SR6KC2M7PSnN7BMjp+sB/ZBnDtwjufiUS0KlgyFkVTMpVsMFVhlTUxRJ7tjqk2XKjp48j9PBFR7MwDReS3/OtLh8+SyQx45UiVwJkXtvnEXhrqGIn+hsnfMJuClwud/IHqWrObF17u3vOpjgShaOLAqBXRTkh54DA/vCWMqJqg3uNSAdtRlxNVXFCDol4CT5sN17ZldYI2P2Nz4Oy2nKRg0YZtnDA5MFWJrApNc8Lklb5cOIdErhbufQIRkH6mqSR9ecW2B/bnLYkvRBaeOsnvvMa6jjJZti+31OEGhyG3CfIndGhR0ZOWBd11/+L9/lXMfeWnj9myigoTZz7Ez5xkRyOntx8IMhux4JkoyLd/4WnBl45KDGSp2ecjQ96ixErEMoqGV33DpARX27ApR7yUJDQgCBiS0DS8sBpLw8IoWxwzfZl4Hz+j+JYiNQmJqT0CT1aOJnlmWVF0IZnCWDUoEpelxSiPzInHeoePilg0OgtksmgmpApEFKOqyGjGTYVloSVjWFilpRiJXaEIg7Dp/2HvTXYl27I1rW/WcxVWbdu+t7uf4p6IuHkzkwYJEi2QeARoINHjcXgGngCJlOgj8QSIxpUSkQjI4EbEieN+3HdpxSpnScOjA0g0UASR98i/rlljScPWsn+NOcb/04oZIRNCZqLqGEXhU7Ph31kFJpe/duW+8hck1koxG4rrmVMmuY6sXvCpso6aQd8wh4IwnuPymcXefzkuq1cWFyhxRFb4/vrKvl6ZRM+1Tyz6hdEoXB14dxqp4oFLuyOKhp/ckbf1EypPqLCjF5Jr35NkYCkr3XJiJzTSWGbbsdGJ4Xjgfv49e/OZDSOf5fc06ZlYzhQqT95Qas99nrk0N/zo37D4gvCOE5KySoKbMWliI09c9A0f3B0ldOznRyiCPo/4kglGUa2nqZlugsOroZqWoDIvNwlrF5LpKOnMy2bHb84/cY/gY33DJDck1bBbVvo4MHrLsm4ZpUZuBN4+oarAckJi6eNbRDD8frPlog3RaB6NgJRxItEvFzodqWLCSoEOC8VEoGKoLMqwqp5dDUTzBiEin/TIICXzvkNGSZGaql6I0uJF5p+WHwnLDYc685z2XLVHCk9WAVcKhyIZcbR6QOoATrKIwm1IWFs4lEdqHnmRb1mU5ZwNOWxJtvDotggFkYGNuNJPkpOzBKO4yITViT6ecWdPqzNDHbhst1hdaOszt7GCGQheYotjVxOn1HJxJ6pOOBGwQnMzZIbdnj/0ntgHNnHhEK5AZTO98pg2XELPrnpaG9Ey8tJqgs3kVrCZMzfhxKQc92TK+MSz0ficmcwehMWYibNbCelKFoX9OJCiwqwaQSJ1ilwVn12LCJWtHDmWCzd5ZZM9c9JkrViqJYjAoC1agsLTGsGde09JWxYtGMWK44X1539FbzM3QP3h14g/8yLEVzH3lX/0RNvzebjn0giynBFakXBs5YThQhQt+wRQacLCqh2LkOhoMaJgxIJnQpZMrZIqJVUJihTMaFT1rFgUGVkrc27ZlQEZCogvb7pVarya+Cb9jqM8kYMhVse53SPTSqMmQlHMWlOKpkiDFJGeV4wQ4DIP5S3SVibZsxdPdHIkZ8diOq5iy0n2DMKjKfRloWFkkD0X1THJHdv4hAiC714eeVV3fO42TLKlUhik5cG9oVsX1kbzaVyo6S8ziPuVfztIa+KUM0u3QT4vBPEGvSRWaXm8FcylY9wo7JxoJPhlpPMtQTeoHFHLilgq0nlWWWn0hEwQqdQ0chETnonjWDGLQrSV2Lwg7IIuGjtldkGyisCb6YFtesbngb0FO77hJGZiLGASLAupKHY1YP0rf+gkUiokmk2eOQvHCUExEGPPLCyDtExUtjyiCDTMlC7jwkpLJI8FU1a2jMyiIQiLrAmB4Pa0MtOyioKKr0x7x2I1yUjcJPg2PpGUZ8w75qDJpkGkQjaJPl5JZUMoEpMNL8ax3hqc0xzSidv8GVcGWp4YhcbnLYNqeHYdo55pyoVKoWhDVRVfI0JHjuvK7vSEbhf6TeAsHec48f04UY4dwlUSipotSs44Rn7uDmTA1UStglO6QSZLEQuGM3RwhIoAACAASURBVLui6ddIWA2TuaPOis5MqGbmXBuemzsWseFpSXx7WnDhRBENeiNYcib1cDWOS27p5IhLM2NfENmStKZJ4cvvaXP7pdbhngOJQe2xG0VjC4cgiUUiKsQa6Vi5rS9k0RFtx3M9smpFt4wICtkoxH5EuoUqHYsU6BSoqRKkoVPPbMqEOhmaxrP0ntF6JucxpfDsE2MbUXZl0TNWXjHVsBcvFCRddoxJ0sjA2zAyLYLj+MDJvofcsOieNk6oqNiYCbeuGFlRc8Nju+dz2lBfj4QUMcCNekFYz6s8EkXH2RyYzROXrLluGp76DU24chsXlk+/4/7bv8XH+FXMfeUr/w86Q3VXkvaMraVIgZErQkQm0RFlBwJUTQTticKyCs2Lu8WlyKFe2YYzQRmqEszSftnnK5UsBRFNqhpRNUIUssxc2PO/+P5LbJioGFZEqjzI94zywLW5Ia8an2caJg7ygS6dONUDS2hBamxcKNqgy8AxXFEpgHCgBUoJ+nohpC0KqCRmHPsamVTDKr9EFLX5wiwcl7xhJ1/YsKK0o02Fb+Izi9Zs/zTbdxUj2kRKFMyuklL8a1fuK39BpCjcqxcezQuj+wk59eziwI+H9wxGMiyeS6s5lAtJJWYnSLIyipZUEp/VgRtx5fb0hMgtt+1HFp+JzRYfn1EoXNKQHdl4pkYSdOQldzRxQpfPWLlwl1u8jDhtULGSVMFkiRKFxSikinzDiJBg0sSL0Hw3XxhkSy0dyUjers8wFWJwDGbHuYGcF4I3jMnhaPnh+lusyqxUPsoj0bb4tKFfI4c1EcUZy4XX/Yan7YEUHWpq2NZXlE8U1dDmick2XEtLpWW2C8l3qHoiui/isgsLZ/kGXa/MwuFUIVoFjeQpHxDRYLaOT9VirldmseUVR6ySWjWrtrRx5O/iP4BSiGogLuzzyE0PMv4dZklMIfFHO2O8YvRnPirNqjKltazsceuX0Ht0w9k4znnL6kZCX7nGSl41u8kh3cImVOS4INMOmTrWXcu1m5n0kb4sOFd5P/4RIUaycES98Mm+5UPbgkgMwuGqwKfKgWfexTOf5Tck4dmHK0kH7rRCr+/5Q2OJFapX7PKVLD1hqcg6YazAsdCmzDUYhtxBhpd+x0n2zATq7TPJwWw0UmTe1s/csPIUvmNRmhoL6MwqV8JZ45cr3jiW4wp2YaKSOs9uWRidoRTJwp6XORNVy3EKvN3NXMMjVXuUFKy5Yf8YMaalKo3c3WNlYDPPXHVL0RWlJD55Ziy7p8JVRU79r/DJotdEKxompYl65afuSI2WQXgCC1IJiIV5mLguM2+M+bPf71/F3Ff+0SOGz2z9MzTvmVSPoLIKhy6Vq94h/zQDJ6pFyMSgt4j6xX7BELBioBdnXu0tTV3wYoEsqEUSlMfXhBUZXROGjJaFmCVZeFoWqlS05cymTJzouaodc3UsvuE4P7GvV76PP3ExW1yO/M79CpkSaoUunLhVF9pYSbFjxeBUYtWOm/LKpn7mc7njo9/zqg5frkFkvgsf2JcnTmXPq7llFS0PvKOfPnLMj+hqmFIhCoGviawzt+mZGcNmzfRKEFX9a5fuK39BtCp477kV65+WFO643BuiTUiluDaWFBW5SIS29HLERYHSAnuOZGPY51eOmxV9vcU7w492j6RhVpZfx08Ym1A28aI0i/YcxzPkwvYUEJeB2AeCbXkUHmUhbHZsxIlZL+yGF2pqoCb+9fKGwxjw9sJiWu7VE8H0UEaGeGB/zbiLwueFY/3IsTgedMMZyf10oRNXcnlHEiNJgU8RNUeuvufZgSgRny/k2CNfAmI60xJITkJzRngN8lv62nAYC+3oaaXjIO75KezIs6ARAzEolr7D+sI318RVRV6U4wHNXlZMgewCobaMOPTgeXt+ZNkGWG5obWQ3zLwfXrjpB17zDdZVruqGqN/yusLdeUXqVwyCTlREVKyxEIQlmIJsHH64ociVN+qFmmCsAlUCMRXOYo/PC6GzdOUzsgS+j5qLKJxKy0dnCS5x1p5zYyhCs3qoi0YqUCXg1SNGbvBx+ycj4JnD/BkvJvbqDHJLVwam4knKIrRhSCuTn3mxB3Yp87Sx6GtBxJZmeEW4maYsrLayVkmsiasoFKnwKSEJ7PUZ40aycbznlSlq3CB4un7PLA84fcKWM8obhI6kl4QXgvv5Qpg2TMkTRMNZwdgXhtqxkxPn6vF1zyFqvD4h54WDXbjMmlYkUszUtqCkQtTIzSdHvYG+XBHSI1Vl9EfasrBXA9MePiVHLZpp2VLdwmt/YFYF0StyWVg2hqQVajXEOHO5SjZyRjn4S4wrfxVzX/lHz/r0wOgyWmZWZShVMWWHB1bhKUhm5WlqpBEDisgqDBLJ2fRE5BcLBmEpOBbVUnNFUejzFSUqsmQaMdOXM0HAydxxElsuYkubThhh2KcLL+INs/JfsmEFrNqzFodPK0+lRQiFkzO36yskSRsnGjnzUN+SfEfKjqs27OKZ1VoO+f/AN2cOupDRfzoK1gRlWXXDVDwBz4YLokisnknNhAgPqPgOkcCqgFcTb+YrF9Fy87ph+u6eIax/7dJ95S+IEgrrMif1yKWVfPIeqwWr3NKFmcYE2jVg2ohVgXvxyoN7yyJ2CBKxGqroiSIh7MIsdiAMrbgymANBSDySaAIfmw1/MD259txeXziWgdYFPriW577jVDpqVihREYPl+eaWJRoWb9lOMOJYXeRvdCXnnkexMq6O3XliUyo1J7bhSp8rUQ5sxpmj0vwDd6jokNWjJpjNhkuzIfUrU6M5tTv86ujWSPfyM7PQBDVy3Rg8hc5ELCvflBPVGNbxBvuskLJnsZqfXKKJP6PqhVkaBu2p9YCZF2r0TERCKrTmismV7bRSZc81vMExUtorCwtg0IsjV4FPBakFF+eI6suz6Wd3QxBfIsaO6iPf5YmTrVQzInaV2XYgB57le0wVvDN/5DY9cTM/cFYbPiH5pO+IeAbf0QQH0rJVJ3q7EvWCWis6a6b+jsUKHs2eqzNsciToLxu0+/CKMRAnTdw3CAKLNpSSmV2HmsHElWAMctZslkq+GYiqskjHajoerYYqGFXLxSmupXKzERT5Smt7KhoXK7kYYuy5uo5nfcRyAV35TTyjUJToiWy5BGhMwKoToYm4UGhXT2obJveRab2iZGQzKXJWODmwqB1XtWPVFld6kvMotTAtkjdpRS4tPlbWvQMh0G8c7ZLQoyaJhFAJPzyxu3tlFoqn5o7FFrSK/NPlZ+6qpsYbRtVxcR6XW3bTStw0zEaT+oVjvJB1g60zSs18myV3h7dYLSAH0F+PWb/ylf8LYn9gEyTHaeJ/az1BGLJQRBS5GqgBJEiRCHgUkYaKIlJRtHXGykxf/sgn8T2OhalukCIjS6ErI/16Zu+f2TLwR76lqxMhe6KRFO2YypZP6p52HvF2ZRA7kkzYEqizZF07ws4yaY+XmT4v7KeBJ7njw+ZbVu0pReLqlYVbGisoyjJLDyJ/mZVBMskGlwNZKIbSIlHIXAnVI9eAdCtjciQcTZlJ1bCIhhI1uzzTzZCr5OeS+e3DT3x7fPc1tusXSkHy4fHEcK2EuIO2cpcv4CymLnxfzwxC0cqBKFq0rBzrK7t1QFwL+U2D3EEQN7R5QJYLITX8g39Dqo7WTvj8wiQtq7BoIrVkQu2QJiLMwoSkkpAxsiRHlpnStAQM718nPtwktFjomoln6/hgD9ia6HNDSpqfmy2lOuKrQauO2zGRmmfi0tGrzP0syCJixJU/bvd82u+IpiIxVJFQaWSQI8+yQ9eOUgf6duTaKZIIhDSRxAC5otdIDJKfNw17vdLKJxozczsNxCwYpadbYVePjPGFU7vjQc2sWrHnI9v1yps0olbNOPXUdkZmzaQbShG08QUpNighGbeWWWxxeuAkO1K2dGXhIhJFKHQxtPmM0ZIpeS5ixyIcNffYZUHmQIqOblH09UpXHDq98Lnz1FpRSJo6IqTACMtYMiG2XHTgbAUJiWMgJ4MOAm9XhKwUWmpdGPYtUTpuLwItBlS6oG1lFR0Dv2YXXinZ0YiVsCh8iZy1wlRDS2YwCVEiRUxMOrKxF4bkmdOBUBsWs2KrQKHo6kqKZ34t/wFM4p38QF6+4WG5J6t3xPglY3djztgsOJRHSmj4rCXJ9Jzp6PVAF14Y6i1jbAjVIZPGZMXgbqlScDEenROPXcOxnhFJsFsj0mXOGNZmJq/PvLi3jNYg9cqbNLBjpuQrffsjkzO49jPNCFvTMJgv5txrMDz292RZkTXj0kqQkjb/hEDg1cKLbDmS8b4B9ef3mvsq5r7yj577X/0tbfMDh+kT9/MZZxJJQZKChCVJh0DgSqQIgc0BZAapyIAQgoilFI2XIzFbBipNWpCpEI3mqm9ISA68ssvPGJkYRUeuDbKALYkm5C++cNMnHnziojqylHgVIW5Y5y01GBq70OSVpiYUHhFaXsWOU9OjCKyiI2aNywtj6ZBmwZXErj7xs/wbZIpMwqOiYM+VXgeyrBzTC60f+YP+ltVrprKjroZRdnwbXnjNbynFsstXdo1HacUSl69i7hfKGFbGMcIlkZUi25Z1/YHbMiDXgYMeOesNOo/UWngfRlLJLEtHkJp5AdusxNKydhGxSPRsyLJyskC9Z/QbtvHMNQueTUcfZwwzIm94bRpemo6r2UOC2wVuTg/YbeS3QjEeBAc5swkT3q9I0RPkgVEoxiQ5TAMn2bMpJ1SEF9HzgZFtreyF5CIbKIrejlybSm0LZj2zqyuLsFi/IMNMkp6qCtcby1X29PaWVAxv85WyWNbg0Tcjsmb27sx5POCYiTVhxIQwnwi7jmU98rr9hme55dE3OHXlqsCXFxbZMa+JOEbCxzuqm4lekpXFuQkzbFmERkWHn1eMqcy6pVSDKZI+BsYsqOtEKiNLKFzbBmJE1sQ+PPFg336xOTKWnCVOzqTcYhZLUzbopmI6g1aGUlpcHDEyMzrLI4YX/RZ5itRacDGii8aHwNS21GB4snv+5vxCNWe0cjTiivA9u2hwIjOz4dlv0U1DWE5sr6/4EIlkfpTfcLaW6A1388DsJLlkopvoGdmtD6hYSKUjuwZRDZ91y9JoainomknVsVkr/SxQ5TPzWVFNQc6aaWu5COjXwkPaM5WOp/AGYwNSRc7W4MfKIU20UyZvLbJqpAioHLF5YVKZY3rBLYF2Loi153WzYXGFWiR5XWlLw0UeOJkrqJb9ucWoC6XzXBGoVCgrTLmjIXNYAnV+5sPmPf200jMjTcXqjKkDUglknehqQWw3vPmbf0Fz/8/+7F05+CrmvvILYLfZ8R/9x/8J6r/+bzlz4ffbymgl1Y4UlSlK8cKBOX9pqUMlS4NiQVDRzKATl9QRhYFUkRqETkSr2cWJqDSptnyS73E5cJNOzHLDVGcSDiky+ESXL8QiSIIvqQ3Vo0dDmHu8gtl/iYWZ0y3HPHK1O2RaKJ1imwaKEFQRqRWiNDzXd2zimZB7pCpIldElkaSnyydUEbRpomQIRvO7+BvOdoOSlVIdVlVUNqy6owDGB8YK3fSM5zd481XI/VJZYuTy8ox4nomu5bvriW275/36mWsdCHLmZj6To2AUlrU0iOI5DpFZT0TVcla3VK2YQuHa3PCMZQmG4AyqXkBUSu759jJBC2ZJeBVIdkOeM8f5Ca8UKSkOQ4GtZPJbrBSEbaGNn2n6M1JWvGoBCdEzVsVGFFoRWbGMbYPMGd9KyIqNmqkZ0o1lyIJBL/j1ieJueTB7urzQ5SsyRBZ3JbUDo+t4VjtGoTBhZSgbdteEnUfEaUuWdwgtUAr6LBEu8526skpHGyvNvLD0CVgp1mHXQFINMhekSVQEL/WIrIVnt6NqRXIdfbU0a0ToE6pY5M4xuAbFBRs978cTk1m4NoK9vPJJt8T4DZ9UR9IRkVdMvWJLT1wzVVu61wbJAZJDxkojBd+YAQzItBBMy2re8KO0TOLAlYUHu+eontimgV1cKGpHSBKFoJ9nOimYbWVbMzZ15K3Aaomrgb8dT4QE3iVO+sDoeqw48WYeqVPLKia+nRZ+bI7o7AmycpjP5Abuw8RtWHg2NzyXjlDefun21UhrBq7V8EY+8v36E2/lgrOBdZZsyoWgJNOmI0tHlxJVNPwoexa/odiWFcH3wytdeqEvV6z8ssDBqjh1ElMLkQajz4hqcWpgDnc0/plkJM20ootCUijLBC7ysH9LETdEdaCbEz9MC2+GB3KulN5wVu/5UfyGLi9cVGXXPtLKGcsrcimkdYtIV8YkkUmyDZIgJDuRideRcS00f4H7/auY+8ovgh/++d+i/7P/lM1//9/xw+UDYXxhuFn5+/vf8LP8Finqlz+e6qjVIGplw8oiNJe8oyiF1AlNpakr7+tPbPPIg7pj0B2z8PRxpi2Wb9ZP7PJKT+C3m18RaiAqw4Al6S1kTRQNb+crk2gpSnBxG6a1hyzZLIlSBFEIRNVsB8mdujKawlN7Q5EaETxCRN6PmYxjkRZRzuzkwKIgC8FmGTnbjtk3RAyr0qzV0ckzF9mzyC2NDHT5hSAKsgreD4FNzNyXhn9y+/WI9ZdMKYWw2bFu7tCl53YI1LVwrjecbwpSfDFK7a4Z99qzWscsHWUtDPcnrPxEn15YteWaPLEa1txwlh15qizthv0Ci51IMpF0ZTENgoY/aI8/jTzrQFAClwsPQtJqw2oLjRhxuSJDy8nssNeRJDrYjDTMeGbq2GBaDSGSG48PE9xbllq5XxL2tWMeZ1K6oDqDjJHjeKFdJ3ZlYtz3jH1PIfFo3mHLSgEOKXGTMnp26NHx0Vg2ymCkYhdXNq+vSLHSyYHuTYtcbxDbM52beFRnSgjEfKSSuCsLh/zCFG+Q4cDUCezdKw/7LVI5DILjONKKK8f6gJE9iplhOuLbzzyvN6wlIYuhVRWTV16qQHd7ZNZk4TltWm7ijFlf6KmoxVK0I9VATAJkwHQnlC7sc2FUR3RN7FTGCcHgCzoKhFTEneCK5c35jMgL1Vlisyc6xWktbF82CHvCjyNvvebN3GDLikt73OrR7UoZHznWwJZP1G5hyN8xGlhjj1vP7MrMGPY0KaBj5G698mJvuaob1nXEqU/cLZHFKX4WXxYQvBTMHHkohVQWNumEEDMNgtpIqmh4ch1mNNSsKEkjSkWJDr9EtsvMQT5S9MjqI4SOm7UiqiUV8LIS2aL4MgbTxytj3FBF4tpoIHPoruxSYWfuqYvmSfRc/ZbH9CvuzSOtnBhEh8xHRO24uQTUNqCSYSMGag0oWRHLCyuOq7nHkdhVwc0ouSXjguDzZWR72GL1n3cL4quY+8ovhm///X/O4fs7Xj78nh//1d/z20//A3+4v/BURqo6ULRirYaYM6ZK5upISlAVTGzQfNlWdbVixIxWkYaRNl/RosfIRFaGgQaxKCbTEatCi0ipcNJHkpQYWfClsqiVTXphsw5sRGGjFp5zT8mK2e5o5YAWzxzMM26SxLWibiIU+8UsuIkEvfJsduTQELVlLZqh6Qi54X+8+Rcc0zMNgaQkrbwSiuVUj8TisExosRCVYKcnVBFI+UyMnrLMKPU1AeKXjDKGfHBw1HwQnqlV9DXx7mJ5Fn8SYkHQBMG4LWQUF60pCZ7qEacSEcUhXSlEXvCoouhy4of1gtSVt3ViKg3nJpJ1pMiCnSFqxUEo1Lpw3iS0c8ybhmbQXGulxMTqNN6s6JyQeLZ1xZ8v9DEgRaC4lpkGqSQvZYNuNXsiPluStSy7CS0bStwymh1r3nPpR2o1LOYNjA0yJq4OHro9phZ0qfisyPpC71fCm4VYGsrSc8wbQizY7QL+jAoJqNj6xHqN2BeJvFuoomG/jBzGxMF+pIjC6jRGBWYfiXqH6DrWvKXmkY0bed/8r1g1kGi/jG5ozSoNTRhoJvDbmZPYUlqLmwUqJ0oTCEqyyYE35QS5Y3Yt+/nKanrWJBj7masKNLpgCfiy8nfxxKu+Z1UNQnW080TOFicCxWqUWPj5uGeQWy7qlpot2/IKqYJ+w6nu2CWBL4qzzbRhxrczH7vIazGccBhzxSTY+kotme/WM2chmKOE2rO7GHzq2E1PCCV5ansm43jZd9yUwqOeeL8MvKSATwPRSq5JY4pirBuKaggbR3CaVTW03mCrRCRBTILfW0vRBZMSSUNRhaQWSolEE6j+gEmZx7KjURdEmVD2M0164LW9ZSo7tJ3ZlwkVYS8z3j9TaqUXP/Mi7rGhcr9anNyi5ZWtrgTZM5gR5AvP71amfENRAumutOuMuWhS6LiaFiMSN/HL1KiLiRbYbS3aO2IuX8XcV77y/0Z3PNIdjxQ8//r8W3bzxLftEy/yhkHsvszMaYnOgd165dncEIQmaYfIoGWlLSM3PJCzJQvNLFpWBUlpBhoKlbv6zDZFtIBZNAyqgVwZ5B4lClUM2DywTRfkJvG57NjXK++nD/iQOF/eIeyA8IVNHbitAydxS10Kg9qzFycOlxElNVU0tPLEyQsWdQdC0bEQ0LRxobVXrqInZ02bV448ErRlkT2qFmbR05UHSvXUxdAvL0zW8+H6R/aHbzHqz+959JW/Pt5b7u5+4A+TIpxmMq98kg2hMZziHQMN9+JE5z2TUIiLYuwNwTYYOXE/X8le0E3QEfggJ3YJrG1xpWW7thzKj6xdBhZclTzbPZ+Tw62VtL7QNJGl15i6kqVF25nm2bPqhFpWtJZ0MbLWHb154VZe6Hwks5BWiRKWLD3fpMzR3aC14HSo/GEYyW5ClJaqA4NuWPqGx/aG2/GVIg3HOfHSNCSp0EnQjStYyWF8ZrecOVvH1DUUWpTWpLRFpRHtFVq09PnK314SZjxBE9BdZbsE0jwwd4mUM9dmSxVb1qzIasc2nknqS9JMDeCWgX15JhlFKBvEaqjXlbNPDH2HcaCtx06GJrc8NJprbvCq8k3+mawCc9kgRItMMzIbdPGsBFLMwIlZ9sTkeCMXMondWLHyI1FYNl3GyYXfinuMcJykY69fGVVLrhUvLkTVYpTkGh1BLaS9ZZ8K3+XIqVjs644kI0PnqWXD/TDRNYrN6pF6JSKZcRg3IpVF5BnWM90y0EXIew1rg1IZITz9+oTUESsEx5NnwhJk5bNyvGZBLIJfj5Bdy7GdeGotwYOfJOeS0UnwTn2myESlw9kFWQXWGqaomXRlwJNqIjaJbgrMxWHzyKD3TNJRtCW5hBE7Jp2Za+FOOqzRfD//RA4tdxmMrtwUx01x9E6R0zObnHlfnxmN5qRnfqfesUrN2d/wzfozx+mZEjSDF7ARfNAHvMycE/xmEfymSMxf4EX6q5j7yi+OGgJ1POOrxqya6gS9XMliQSuBSzNaCDblhZe6Aww6R0weMVkiUmJkz6IMqlYWrUlSU5kZOVCUYrA7flX+gBAJVyJTdUShqBV0CmQlCdZx0j1v5hO2LlRT6JoVYxLt+SdGND+7PS/pnpl3yD7Q1plDfeXu8sxkNjzalmcv+aN6j2NFJkMyllkrqoAITNHzLn4giAZRK1PcYvKCMQOdGPhZWRbrmNlzKwPPzvAmaWotxBK/irlfKHmpvD6MDKumaEEvYMqVzIrIG3IyyLJhnzJLL0jHxHaYmHRCZsGj2tFFQ6wLNTve6gFnR06bI+0EGk3JheN4ZjQT2xoxy0o3ZNS8x6XM1EK0hqgKuyGxF4VVWUYJXp5QQRItkFeEyJhiEM2ZWgQpFZr0yJWW9ipIMfHcdfyuFi7ScWscubS0OjDKBjNPQCYr0MLjE/zz1zMft4VBOnz16GVkXm+5CMvJ73hTr0TjmYxkWDQ67/m+DCwestP8Tk8czM+ospApLPqG2RmysZSwcMkS0ezYxZmzuiMXwWurSLoifWUXXzhZy+TfokThoCvNa0EGT/u6ENwtv3N3nJpETYJz6nHGsJozbbXcXF6R4sI6w1BvmO3C1TZ4+QnZKj6qDbFKWCyCM34S6EUx7jxuNoyrhuhpTeI3/pn/Wf4dKbdEsUEkkLLg4wV9fqUNliwriEhNDVOJpHxCqJWrufBk3nLuKiJuuBcCgyHU71BjJAuNj2dybfDmmUY3bO0f8POXCLVjFaixpQDbVWE7Q1kL31yeeDUrbXTY9kA/Q8iJ3keuKrKoCqlAXDmVnsde0boRpQMuFoJdYM2o1SFyzxoNk23QFLLw3CyJb04PxF6gw4Vht0OJicEfudQOHMilIpA8j28x8RWfZ/r1ynv5mVh3vOsSN2ugzJWpNAg3U9xEIxK/t54PbsNSDnTlSiM2dHJhMxTa8gFZBSH3pDURfct5OLMVf/6uHHwVc1/5BVJjxLZb+s2v+P7pf0KnR270zL8xP/DQ32BEoFS42i1SJKQqaCYwDp2uDG5DKAuLbFG1orJAlIATlUUlBLAIzyd1i04aJ2Z6MbHWhli/bJ+pJKgh88m+QypFN0e8XqkpE4QgW8/HesMnt0WawMfmjqIV23qlTxN34cRH847ZQBCGEgS38onP+sA2STQZIwOtWHAuIDK4PNPFmZItb9IDISmUCojccJMic17Z5Veihv3uDu+PGPlVyP1SuUwr+ZJwGfK18rMw2DKz5JZAQ9UDg5I8uVds6ZhThJjYtytdkvzkLCopXmxHF6+stmetHUV6eh6QbYOPHj21BLElOcOcvtgwCKcZO4tn4tvnkeQjzEe86TjIL7NV0Sh0fQUinhFlNkTdUW1mbhx5WAnXA80lYdaJtXacuwZbK0HPfPIdJoyoMRBKx2IiFImtC+9eLtwXRdrM7JTjyAeaZNkPCyYrFuG4SkNVFg/UIjBlZcTxnHvMNXFTKilHpqajVM9js6HOijmtX/zctEHFDboWitiRXcaXTBcyojpSLTy6twQhSRRueSYvG5wJyKHl3Ec+dN9SVEOcQJfAFB1BV0azoeoLITcc1oky9+St41hfGdeZ26woaD6KxCIRzgAAIABJREFUno0eSHXFrAuH/oHYWYTb4F57pOvJciUYmKTnGJ45rBeU/cyApAqJGj2bU+KKw7hEnyZ6MeJVi7pUkqmUtedQLG/zzLDRZLNhSJXL5ci7+QVXNMKA3K9MKrOZHtnYnxG6pdQ9mzxhZstxPpGsIfuGuJ0ZNq9o5enXB4bSgBnYrhInV7bqDDjuiTznymcruE0RnQsXm1mdx8qEkI59mWmaN9gx0wiDnb4k4/R1JEiDKivlVdK1giffsmRF0oYX2YCSfL+8sIxHcjkyloEkCsEkTBlQauAaesbs+an+mudsKP7EVl0R1bANZ/zSYcXIoT7x/sZj8u/5N2pPzA1rq5j6idwaip6p/GWSd/4qYk4IcQP8S+AH4PfAf15rff2/feffA/4rYAtk4L+stf7LP332K+C/AW6Avwf+i1pr+P/r+r/ybzfCGLZ9x998+8+Iryfy+Wf23TOHcebxuuW025OJPLV7+hJYVY+WlUImGcnKliZbVM4swqBqRFfQOWHtipAFsoSiqEGha6LajDCCN+mZUB2mriy01KCZxx05SoJpUUpxoz6h2gkpPBd1z8XdE7TAyoVZeJTI/M58z4M4UExhsBbp4GM88qpusCVi5Ionogi0nJnpeNG39DlRleC4/O98ku+ocYE0shkX2qTZqD2b4zf8B//uf8gPt//ka1fu/yP/GJ5hsmbEKBhLi6sBXw3beKW7rHyWmZdNhyie2Ikvnotl4ao2fFtHJqnxNdGmhaXs6fG8SQ5hR15N4NxLbP4jh2Vlsj2Jd+xSYmkETY7c8oqvLTUqHpdKSTvapWGHJvQeUx9JQ6KtD/zRfs91/z2zbHlSM3ueqOvKzfSJMDsW0zC3ilYElBzRtqETK3lS3OYTRW9pWam5ktaVLFqil6xF8+PmyEoCmdjVM9+uhdNuT8wdh6hwVRKBLAWzzrThiffDIzlZentg9lcubUt0MydtOYSE9IKNuHIQKzFVhv+TvTf5tW3J87s+0a5+N2efc8+57758TWZluUzZYKxSDZBpZJAYegIMGGBLtiz/B1iCAQMGxYgpssQA8MCCAQKJAZKRkZgwsEWBUNnl7PPlu83pdrP6aBncBypKWRam8jkzK+9nsrqIpVBsxW9/VzTfMCWjTESdkVMLOFYBTmWcbDD5QEgwy8wuCloz8NGa6NeGTiay9AzakG2NlZ7FFIRcEeaRL+OG5ylgipUnW3DtBFYKKumI4oLqWpzX+BxoYyQFwzmV+NDRig1xMpyTRq+RWXdIVXAJW27GM7fxHRSwak9qEwUDbT5i+wpRP5HcjkCmXyQUM7ksKKoaCsm7zZa5nzmVkWJYaJ2hFZEsCrQsUfX7IcwcE1ZpxlShc0krJRdTE9s9WzNwXGv84rgSPdXpgUomtspR2QpDJgwlTsHYlARjmRpJVwTq9N5e5eQ1+JbXc+CTy8S6Opb2JdF9hJWSyl8jsqUO75jrkVpPXOuO70ZYtWTjJvwqQTqC0NxOI5N06NjT6YnCaGQxsN6M/FD+Jj/JW9xkKS+GrRlAe+pqwQVDmVdeoLg1FSdVsBMzYrmwFJZJveCzqw23+z3F5utZdPbz6pn7m8D/lHP+HSHE3/zq+t//Q2km4N/LOX9HCPER8A+EEP9jzvkE/CfAf5pz/jtCiP8M+Ku8D5of+ADCWppvvOI3b665+/Vv8eb73+N4/jHDw5l/9P0nvmtXHrYdCU2WgkxEkFAAOaHFSp0mpIDDeqFVz6yyQMuZIl4x5A1ONPhcYNJCxOJ1x1F3lHImZMXOz0QNpl/pU0OqCj6aZxZRYURkCjtiram5cG+uyDJxkju2ceA2PbEUklUpvFYQJDqPDGqDDZFWrGg8t/qJiygY1IZBbKnSSHcJ5Kw45WtyVFy5FV8qzGHLX3z5Z/j45tfY3H1Mu9+h9YeO+T8Gv/Ax7MoWvGgCX84zuzBgBISlZcHhqxWhYKsmjkKhfMVtmliUQYeCzRLxRclDXVAj6SV0saavLYvskXmkiV8yzR1F16LiBqyjUxdyqXBaIlzDnx0E+3f3JGYuncYXNZ2b0ItknmHdtNgIMvWspWGhZtRbzDzTW8FDtUVkgdEtnyC5kwpky014Yo4TQo6cgkIUmmBKCLD3F2oPyb4gyJonFZlyZNQDfTtwjUfkLa2bEGvPFBds1SGUpUiBxp+4DpJkJPeq5d68IooLl9lQxZHKXyj1iJIrUn2EXgJWa4bqhMmSetKM6QVRpfe2LMZSrxcOueeqHDDa4m5KlrUi58xo7Xtj2ei5bhX9zqKDIo4dJ1Xgi4EiZVxa0YukKBZIgFXsxQVSZphmmtVgUbSuJYnIXhsuQjKmjsUECgHWOdxQYHNPWXuMKciixvhEUoLQBmQwjPUt1/OGqn6LF6BUBPUTsjtQ2YQeVlScuRkcL4YTNy5DW+Jvvkmx3CPnH9G4jkcsX3T/Ais3OJ14uXwXlR1P88APPIzNAZ0Cs1LYRbHoCspIKDbcXd5QDzVrltSF4tB+yRsBO+Hws+Cp+ojH2LFRNYkzV7NgKiVr35PVC0IpWdqSKGr27padF2xzyU0O6GVkcpY6ZLyUHJZMOczY2tEnRSEF77obWntmKAqmbPkuhpNfyYBeEmEouapHPnYLWyW5Hizd7lNkU3EcZya5I5lAuv6MeldSbRuubz+lbdqfZTP/f/h5RfO/BPxrX53/F8D/zB8KhDnnf/wHzl8LIe6BGyHEGfiLwL/7B/L/R3wQcx/4AwhrKa3l1abj1ScvAfg//pf/nb//7u/hq5lJK4o8ooJmn2C1hoDCighkVmMpVk+RPVkaVlmxy2cuOVHnFYPAFwqnJIGaNvRA5FQ0SJFZRUVSmqKKNGbBZcmJLSSJ4oarPFDmwC4LrsMztTxzFBtu85F29czrhit1oZcFk6wxXrIkSZdHhEkEKnQQrKalW07s8oR3BT4VtOPErUv0+4Js/jl+7fNv8Be+/Rv8uZd/9kNP3M+OX/gYZmzm2zGxXC68DitzsZCZuF3vSallyAWvd3swCSscl1WRVoGaE7no2CyJKAMf+QnfXbMRmRADbTgRlaPICmUFYRq4K7+Hy4qb8UxatrRhYTrd8+BGBmXeW22oAaVnCv+ApGcmEIcrqrJlKgWKgPWZmAT7STJOLUrU5LrF6JahrtDr4/s2Eo584QNYT50zNzHxLC29rvFrRMsRtKZMgaATu7AiUslRWUoz0K5v8FLgTMQaTSsGNheBkQ5bnclZUdJRiC1tjPTJIHWG5siheub6dGQxHWl9zan+FNfV5Oa931pEs1/OULRIoyhjSeEfcGPBs0hEt2MpNBuZ6HzPD4qS9pJx14ZDsdLKkpAtdVEg/Eywjhg0S67wdsTGgDELNisGF1jSSGEiJkWkVBS0jGgGWZAHyZUQPCG42A6hE1k2yPXAvBqGscBXW4ydKHPCrBnWmb6sGPQG6x4hGsboedTXZF8iBk0zRrK+5lxJViuZtpZWnFnSzFpd4Yua+e2GKcHz5YbP6pkn5bBqIvaanVl4Vgc2LhK9QCxbotREWSFyohwd87FErII4OmRdc99cMdZQ6ZF9umDPkXtrqZLApYZ+iszaY93I22oiy0hneq640OQSPbYs/iMub+4paPnEzkyrYrILh7XHViuzFdSLpsyZ1xwgJiaucMYiBZRlxIaJzfQFd+pERlBZiVaJT65rbPcZX16+Q5SWxp9Y6hd8vL+lFgV4iV0k8mvaEvvnJeZuc85vAHLOb4QQL/5JiYUQvw1Y4HvAATjlnMNXj38CvPon5P3rwF8H+OSTT34GRf/ALyurzcgX72jKldXeIUKBkxqQCCALSZfPmJzYxBGVBDpAJUeGomaRhlVUqBwoGVlERSdGBtEw0bFIBTESVIWTAi0yXRzohGSUM5N579d1X/0p7i5HmtFxFU/0zUi2mVYGDvOMlpGON5zjNeIIrq3Jq0UVmmbRNPrCWjQ4rVlzxSGdmENBO3jseGYjHR9/+m0+v/s2+nDN3aefcr3ZfxByP1v+mcSwP078EmQm+8gL8UBaTninGKLHZUlbj3zmZrKvqYMirzPx0bIbJ2p9xUpgIx6YUse5sKTZ0PEWk1e8iLickc8dSIcrKsp0ojs1HOzEfdRMER43llkkXt+WWOnwsuFjN2HmHVfzhDQWFRV7l7jyr3kxCbJMZNfQnTqEidj6yLta4qVjO26YVzi5AZMdyZdsXSTJTPIwWM+LwlMWI6ZcWWpHreB2CmznE8/akmLge9WWV4Vgpz3GO9QSeWw8JkIRFxpXkYsdZIlZO6xsGNuA0CPedxwrRTscqcsRWTRYawn7hlgHUlhZF0sZM9UqUGmgECPf0SXGwhvZcJ0VpqjodCZIzQs/cBtGvqtf8ZqWxq2YvqdSkZcuc29LQtKUKqOTReT8flcL6RHTmaYY2DqHFDXjUpFiw1wKnKkYS8FhKaiZqJPEqoFRQhSSp2pL7joIe7YBPj46jt1Mb2eGRdE4jXe/xtJIJjPwtNmxc2f8YtidL1Bu8KVA72/IRiGePebtiU4JnnAsk+VFmfiJlFzQmOyo5JmsIMYWuWxIayAliR1PFEjKWhOKE2L0aPnAuBYE31Oumn5aeGkjyidylmzFE1drg7wsUGWGtsCZwFBJTHzGuoArDvS2piTg2pZU7ziGa/binjpOtPMbbFyRtmJOE2lWLLrElQpfes5as2gBItPmI6wCnRs6Fi62Zq0r2loypg29bKnWCTV5sDVOBZTKnF8/0a+BTdPyw9P3eHl4wfbq7p+qLf9/4WsTc0KIvwv8tBL/B/+U73kJ/FfAX845JyGE+CnJ/kitm3P+W8DfAvit3/qtr0kTf+CXgXobuLaCMcJVeKTLM/3Scq/vqJIHkwm5oFAXZt57vTXVTBlH9umRipUtIyUDay4p5cwuH4nZIFymKAM6Bo5iT50CJvj3K5vyiFUFFktjF5LaUBcTZhXcxQvX/SOP3YajuEKLhEfR5YGYB3JWPDnNYhVSRVyRaIVjKmoULdWauD56xPpI289oMaA/+YQ/96/+m3x2/QlKa5T+IOL+//CLEMP+WPErJ65SRuieYI9cyKRUkXxkc0oMpuJCQc6ZLhtM1iASgz/SW01jBfWwIkqNROJnw0fRMaeebBQXXeKuWtakoF4o+55lMJhR4aWkkEdWlQi7AikyLlsSE8ZMZBXZhpZKlQy2orUTIox09kiRFvyVxkVDpR1mnjm2mt4WyChowkStz5ScGacNSwg0jeRWTdysz5zKjmw3iDjxPE7Uo6NVZxbZsdWeY1S8YkDLlwxGUaYTRbxQrglvJiKWslrRWXDIA9XcIM3EVM3025IpS8L2jhsjyeuBQEPykZ/4mSf1hJKBmAMh30FomApLlAmTNW/rhiUHatXyTS58ZARQs9Qd9Rq5WVYKAjoO2PKIy57SbRgW2FOzUY5Ns8OvmucpsMYnqKCJPUZ5CmlZZaAQNYXXSLNQRU3HkctmJSuNaiJvFsNqNEJlrlOP9CUZQdsv+E3GSk9ZBGaZqHVGUaC/2mfXliN7uRDSgCgyS6UofGJXGQY6ntdnogpE4GlVfOSOXLOg/USpOkJoOcuG22hZoqU7Rr4ZFx7KiNQ1rUjcBcnFrEz1idVY9oXB9hpnVkRYqANsHxMvFDBrhOrQ4kw79tgs8AzY5NEywujBtiyyZZ+e6XWHjB4lLLaUdFZyiS2rFdSpphQXLilQqROjbmjJyNHi04YmSiodOZSCoy4ROXEVPDF7grmgmi15HAhJk6Ll82qPGFd877kaNOqS6X/z+Msl5nLO/8Yf9UwI8U4I8fKrL9qXwP0fkW4D/A/Af5hz/l+/uv0I7IQQ+qsv24+B1z/j4n/gTyB3Nx/zG1eW+viamYoxtIhFU5Uza2nIUZKy5Da+RaApcuSZG77Ut1zYseWRLCJVmtnmkTr05GyYfceWIysGnWdS0OgIWmS0mLhJ74hzwVJEhqLDiy2nosVs4G4R6Lli70ZSUdKrgme5R5CQgFaOnXrmi/ZAlSPeCErvuV5PVNnT+Ec+jSfMm46gG/xuyzc/+/O8OnyMLb+OTWN+dfhlj2FGSOyLLUlLvNB4v1BuDLU+EL1GusB2dqhCUuuSZyXxUqIU3NqRsulZveLEgXI1mFzgWbHZ4nMNQM4NxmVCWXBWhosBKRSRnlhogrVUhYC4YsWZMc3o4Gn0O4psmEyJajdst9f4OWOUQy43SGvo8kJWJ66KZ9b0ESoYsvS05SP1cuGgA6MwZF9Rpwe8KRGlAqWYpeWca8p1otQRLQMv00hpE8otpJS4zAsmO0Ss6aYfUM0Vb+2Wi2yYmoZrt6NXNcYL6vaaWCz0cqBJA9fFP0/tBNl+CXpmiEeIK9oGlD/xuLmhjpk4BBoT6LJHVY6ct8QMIU8IYK88+6VkSZofPyX6ynBOjps8sjlu8PaZvTLE0mMay7HYQimRvmV0r9kJgcuQd4ZoNvSv9/go8VMmypm0LMjJExtBt0pe1weCPROzpMyRk7jhyU7s2p4pTlj9xLWuCWYmTBVSC6TKFKZhl0GKK7Zp5C6tvHGJqyoQ5MxePLGugd1pIuSFKGqSMayyRorMwxgwbsI0LYe4QU4Nn6wFQ4YiHol6IZiSNhaULMjiGZE1ud2TvSPFwM4tzF8KbHtP7SKGgrt8wQlFcIG5XGCnuFmOmH4inVuyMzijKEzkrAruOSFKwSWtyDVSTgPDkFnMkaAqxmDIqWIuG5q4EgpJlR1zVoRk0S4xRsfsNIVM0MNz7kjGg7pwqiZSc0dfNISl5Gxabl1P6Y+sxRmdE6X/emTXz2uY9b8H/jLwO18d/7s/nEAIYYH/Fvgvc87/zf99P+echRB/D/i3eL8a7Kfm/8AH/jCHwx2/9S/9DX7t7T/mTz9feMwVP377wD94PPKTXWRpNKVa6FNLlQK92PIgrxAiI7NHZME+HVnDhkN4oImCTXpgaEue5Q0zlmsin7sfssgdh+HCF90Lvh8+odIz3wjfRYyZm0qwihYVPb6aMThMF+nXj/iyuOY5HXBFgfGJu9zT6CMlNVVaUbzvPWzEQLM6yjgxv7zht3/zX0ZpQ/3RC159/DFN1fy8q/tPOr/wMcyWLY0oKcaeG2kobCK4V/RNRxgl0dyzjwElPEP9EpFOhE2gnBdME1HOUmvH7CXmrmS7tujnR3LcE9sthR6YNjVxCegwM06apzTQVxsOl8RGaLZa8enseAo1Jj2RlOA6CdRVZpSZk0joTclj8YpqARlLgi74sdlR52fiUhPEI6Kuubo2LM4T08rlpBhXR6ETVdFQ68A+OY5BsPMTZdnxxdoyjBv6usJkz3VXsVW/x8HdMykQy5m4eEbxEUX6BGkzQkGzGxBVDVtNdWn4uLhlm79kCj9A6xqfNW/WSDf/BKHeQHzJWcAaJSoqDA7FRPSRlK/Z5RoZFGdb0MVE1AWZiVlsieEt1TxSmJLPBs3iMsF5TPtEzJ4ROPsVrQNifE3OhlNpkHmPq1tsNshUMm0CYm2IraQcA16WrDZhk6UuoDIfURQPOLni5545H9A8cm1P3MW3HIoFe/DUWYC+5rMiosOJmRkWwX3c49WWLBVBCF7qii6t4Hp0eKbeSmJUMM7IfkbYSMof8SxLnA88zpqXQ+IYWmrZovM1q1IctWcnwas9RhhqXVB9/hew6xcUjz9iDgVIzXG4QTTP5CkQfUV1HBHljtnuGGrBsq+58hM+RDZxplKSeKXJxvMYLElkruKFjX4gpQeeyw0mBebtN2gU7FSiMSs4z5Azc5KUybGukbroUJMlBEOKnlos3PaadrwwzQ1DFoRWIK4WnguBUhXTkuh8xpwdTmaUKqnKiptNSdV+PbH55yXmfgf4r4UQfxX4MfBvAwghfgv4Gznnvwb8O8C/AhyEEH/lq3x/Jef8u7yfaPx3hBD/MfC/Af/5P+Pyf+CXlMPhjsPhjm99df1//u7v8737v8uPTElQBTM1SbwAziy5ZKJGkLDSckoC8gWUofIjU2MxQeFEQcWAxbKLJ6IruNQNx7JjyZranyjNhDM1x3DNvbhh0SXb9pGDMBRpovIDp6Ili0xQAJ6oIZmJwbRk8d4nyiDY+2dS9hAST1Jy3hfs/vy3+Nb+059fxf7q8Qsfw4JRDJVhTi3H7FF+QeaVPHRUPnApFacMG1tRVZZObRmWhVIa2sIyx0DK9+zUW6Y1IHYtub6mr7csqeJUdFSdwZwfyOcjwgZcLJikpdqUbFKCzoN9YqME9pwwcoMuH/m+esFbt2MuNvzpdSH4irSULKkg2wvrnKnTM0hJFVZu0pk8XtgkzygkprnmSSY2rmSOgZ0cqfIF5pXe7FnPcJMmDnFgnhT7rkPXBXLewmAQ+h098FTuaWLBtWuoRaK5upCbht62xGSZ9ZatbZC9wMjA1jnIHjGMPOZMpuFeC57rjjBIaiGx8YSVDUYJcrDIMHNWcKEkioYmLHwjnlDhzNsMTXqiTg1RrgQlCebEJDPoks5rYhu4as68KUqcbHlcMq/cG6rLSpkdu2pllXvKYLgUkiQSvcmIeKZXFZs0Us2GFBuEFcRcsCsuTMmwzxVSQNwkxFyTMhSiJ6QepwwunZBY3gjL5VJTRxiLzJfW0slImxNKrZRqQ9ALJ7lA9qgwI7RmEgpCz6IbLuolkyh47SOKBzYINnJB255Zj9Bc8dZsqMU10/UtTXGF/+ING3XkwsrFtBQyMylPYy1n2fHQSdayp9+N3Pl32IeEjQWFXclqRtmKzXpN73tiSEwWnnVDLyOlLgmqxdszs/FsZcCqgnJSpKWmVxXoCuMiDkEQARFXXsQLr8KI94LFva+vzi2oOSOy40ymj+CjQJUOvZNQwEFrNu0WWXY/66YO/JzEXM75CfjXf8r9vw/8ta/O/zbwt/+I/N8HfvvrLOMHfjXQleYgTyBryrySsKg00OWBkQ1ZZlKyOFYUmkN8ZhQtD/IaQqCXFU5piuxZReKSG87mmpATi2nIUvHj5lvc+J6wPjCrCjlJRC0galZVAB4nJIXuUWriyIFYasKiCEkScsXBX7iILWBJUvIsb1mMJsvMFs3Ffz1GlB/46fwyxLA1TDgbOJsrjvwQJSTd9CPmYmUs99gwsxcjyt9xzAtt6am0pw3XjOs9KVx4jCuRDPKeZZl5+eJfBGNwfuaSF8Lcs8srOWjWCDLAHoOYJkabqVWmaGtwC140ZC+47F8y0lBEzVRU/KPY8kIZtLji7uTI88ggZ2ysSEJhY2SjAiJ5moPnS68oLgfqaYN1BskbfLrgwgAzNPXK4ge2pscXllOuWc4FRcpYMq5wKJ9p/JFoBdexA3UDVWRnelZTItPItbgm2Robz+ThiRQCvfIgLO+EpRIV0RgecoeeLbYHnQfsahFk0n5DI0vCsqIbxdZHVJqZVMWRz7kXnkZ6Yu251SuHfE8relqOrP6KJW7QiyKkiuNcEkKmWV7zaDe4JFljB3HluegY5pZSa+p84UVZ45KlcpmiXpCuh2xIY0UxCTCeKk+0csN11izqiljfsgrJMVZEb/HTd1j9yC5MRBEII6A1j9YyFi2rP2MEfBYc1zjScE9YMs+mpH5RY7OgMw1X1YHjg+BmiDQqYGxgUwmGsiGlJ0gaV5focGK3HplyS/XlG97Zmpd47JJJqaWIFWr1eFZiqCnpUKlFCYmQJTELLhzYiLfYPHJKmUndUEsHeqJYM9IbXBKY2lHbkpUtVjTsQ0RR0Jl7tHXopmK5eGSwNGnFZUN2kY9UJofIy2VHkTtigCgce+VwOXHtMosRrPNMcC2JE4OquZkb2nqLvT5g2m+QsF9Le/9gNPWBX2lsOHPIj2zZvA+0NHR5IiFpORGSwFHghMGlknt5g8garS4ssmNVmZzez7Wr80yXjvRmT0yGXu+4mk9Y4bl2j1TKM+XMue5QrHibOcz3pFwQLiVRFThRsMlHXvkv+UL+Gr3suKgakxJJSpQT/LDYsIoCKTMpQyk3dHb/867KD/yCoUVmzoJ73eC8ZRQ1ggceqxUdn5CxQnmP7S0pAe0VRbwg44iMF4KZeUKirebSbFAhUL17YiklwRiUGBh7iBk+TZbaJBap6Z3EiQKrax7VM3NoaNYRHS04zaW/oy+2PJsGGTSFVNhYc5EzD2biEGa2i6fcKE5S0Ks9XmU69Y60HknxFRch0HXB1ZpI0nN2mkSJyAu1dzQikEXGyI5PE4RqpW3gNFb0zuD6O2ormKNkUDXJJKwWnGLFbQjMquRSXuPiPcXyJa54JpstbbIIqRn8BGvJ4iaWrKnyCYeFdUA5xVSXVGvm2V7RxYjIjjFVTKakWQNaGDwLa5TMObPD4buCc1pR6ky+ZGTWxHjLNgpUegZtUH7m47xQj4an4iXnzS3vrEYFz6o1fkp8VERqGyitwweHlolnMWKrERc9tvQocYVQNaM6M6lM5SZU3LKGkkufyHllLCIpVwihgMA+nohjjZGZXXgmlQcu+QqXb9iZEcRI8CtTKHgSC67U6HHik6tX1G3g7fqOPij+oZqxYUJIuFnfkdMzUp8wacekSi6nimkqWYrE4XIhFjUEx1FXDEoQQ2ZOG0QWyBQQOvJZema7nlA58/qqw2M4C8PtRaN9SU49nntSnOjna6p8oIqGznuUrJFo/OZzLikT04LVJ+LpkaQtyRmubI0SgaErcUXJu+NAXQgmJupuB01DpTOEC3GsKbVlv1zIVxV9+/63uXGa2tSYQn097f1reesHPvBLghkdGzlgxAq5QUvHq/x9drnHScWb/Blv5R0qB2bZco5bujRSxRWXMqvc4VMimg0vwj2j2lHSE6nRYgHp3wu7sMUnRbecuJLvqMNAsvBj/U02bqLUiTItFHlloOVZXNGLlmqeUVGyy2eEXdjPnklFhroi5BIlFZ+aA4d68/Ouyg/8gqEwSBcRSqFSiRAj3ixoH7jhyNHeMoVM0a+MSlCmTDCefplRKuDz3YSjAAAgAElEQVSVoqwMxVwyL3s2KSLLxKGfqdKRurwnxRKZr2l8SdYrv2EMb7JnHS2lKOhcIGiohiNh6ZjmRNQ9n4eFrvwW1yny7rCnLxXFZYOwCzKWdDpAgKJ9QdVseZvOjLJEx3dcjSuNXyiXR6QqOO0KHhbDznWoKKlXg29bghrQ3oMQaCXok+V1eYeKDofj1RS5220ZDztwNaWEy6KQ6pF9CLj4uww+c04nnJgZomYRBr0IikLS+5U1Cyo/sVsv2FTyyezQaUNbXrH4zJfbmdss6bLnm+4nuNjQxEDf7MmqYloNQw64IFDBUYkTKjdIuWEbHZOxbOYa53qEO8N44dW2wlUf88PmmlNZ8lYr2nVhezkiQ2ASmhfiRJEcPl9IRcEaFlzSuELgm5YmSCoFQWQqs+EkM6flmoWV79tIFt+ANCDXkc5u6IRHGMtdXHkw32BEEpUl5ExrE33cIOfAUjmEUMTY0Plb3Owp0jv0bsPeRNIsmfOJbg2koiDHiJUaZAV6pvbfI66C7LZc8paUN9g5o3FUaeK8jQxlyXdLx95eE0rNnGbMExTughy2POwtS75jyDtWJTi4FRtek0RAixIloKoU23zLXfCUOeCjYggeIc5MaiQmyWb1tKshOw+vEnMcmdsdRbGhlx2/rp/ZpoxvE2V14O3wJXqeuc4Dvd4w1QXXquVa/YDtbkOnJm5uP8eWf7IWQHzgA78QqK7DoDjER4Rc6ak42hsIgieuGUILZFTyRCVxsqTPisk/89Tt8dnidckqDFZmStnzwh1RGqr4BQZP52ZuloG+PFCZHq07hCgo00zDxAv9jmf9gphqmtFTFpldv3BUjknWFCJw5+8JyZKkxouSggWVMzJIynDAyJ/mdvGBX2Wcj6RcstOCh0ug1BM2TKAHpizhslCsAW8dsi+Zc8DZmsIubPSEzT02b4hVg5Ua50rcRePTayp7ZhtAMhCNRzWCo4JorzBaYniFSi3RvUDylrRm1iWRYsJkKObMlR+oui3b9cwYFTfTylOWTBqy3HOIJ4RqWWzkMSqufWBdWyofcMuKyoa4qxmuPudpVKR+pbGaHYKiWPHaI6uVFFr63Y4ljJyz47PV8VAlTstM6WbGNMKacFNGkUgx0mvolxOPg+MkPZscSGPiZXFkFFc0KXM7eU6rwLkBUyZqHbnWlnmU3PSBx6qmWha2XAgYbhdHtoKyTrRdzzo+kF3LNAdehhpz6gjFQq8m4mrRqaNjg2/eT9koVeQqlhRB8qObO1K3JxeGzTJipGL36HgpSuw8oFvBrCsmUxNywdkX3JkfgXk/5nAVFD4IpumBTpdMVxvM+EACqhwpXGAsNNPmc/QaMcpgQsNejpQyYvVKEXrmosGoliGttPX7VbuzLlmDYXQT1Vfm7TeHO344TSzzE+sI0Um6NECYEXJAmhVtNWK1uFJihWdoLCmWBCF5Ec+MfmbVBlLFyawkO3AXE0YOqFizJgkm8qX9mNXsKLzFrxekWjBCIaVkXS0xvDeDftgmhP6CLXAVBN7sWXNLTBfOAWYKvCjZcaRxEb9qmijx00jvW34/vIadYLeR7OSRez3jrGLYNGyloy033L5UpOCQzjGqH7JMvwfhBeif/VDrBzH3gV9pzLYgphcUc8abgpKVc9zyKK94lK9QJAqxUuQJmz06JZxU/KS9QxOQJGQKKDQqR7q88sn4BU/VFcRIttDoCVto9OwpvOLjdP9+5ZRcSVLypG84c4XLFi8rlBPkUrCVz2ixEoV5P7fOW5R27NKAyZmzatmPwNvv0J//DO3hZ+9d9IFfXnyO+GmgPf+YH5cTZMEkt3x7uGCFQYoLroqsYcDpDc/ylpQ9DVuq+X3Pjqp2SJUo3cSTtezbjvNlw5ZAFc4kC6toEG1AOk/VrAjf0swGLRuSsbwxCacqRh6pg2MzZ0rt2auRx9DzoneMjaJaG6LSNDgWLFKViMbg8dTNNeasGLJnHgTXvSdvFnpm1vFM0/wGLk/slokyZAoC30+RsK5sikAhGw55x0/8yNt1RrsHzOXI0W4JXyzYwy2bTlOVjl5G+nXlSMTE5f2cO++QZkObE7XfgHpCJsFqCpxp0eYGJTPCSW6qjI0X8jLyZDSXEqTyZBHYuAvt1cqmMawohhXUkijTBbFodBOIqeFctaxhi65WcjOzzgshQyNKKr0h2WteWMtiC276I9Vy4ZvnE0ZXpCwxRclDLBizYU010UaGsKXrV3ywLGjUuGJyyaUs0H3B7l3iUWnGm5K5jqwq04UBhWepGlyMXFxNszquzEJdXXiQJ7S8Q46BrX0iiJq2nYl8jhkMtbJ4nli4cGM6VPiC0vcsWqDTgmo79lVLHwIhzxS1ZFOPbIobvixahreBJZ1YU6DSBaUaQSjWJCm9JZQTs1qoTU8eIazX1INluylJqkBtz8giMuuGu75mXzpK00CzQHQ0IZKMIcgjRT+xbwVWXWBTIo8ND6IEu0H6Z2QOmHyFk5o2H6nyG5hgPA38eOoQYuUqXNDqimiO/MP2wHMULGLLp/4nFDJwMx+5dSPmg5j7wAd+tji94andYFKP8ZB0YGWDo0BGjcyZnDMi9xRp4ckcEDIyS0PDiMdisiOnhMRRhJUxdvRyz4WaSl9YYsVOrtRrz13ytKtCeU2SC5U888PuG1Te0ThHES1X02umbc9VfuR+f8WjqPkBL9n3M5skUGpl30/UNnB9GSkOHW54Bx/E3Af+AEoIiqpH7hNO15RZ8pgqtmmiHgIpK5QvqXOEusctklBIlrwlLiVBNWQ/U/iBY9jj4si+qskY8rFDTpryWiKqzJpmvK4pckGeSppcUFcRa64ZuKcsHvhxahmaDo9ikILCes5SMssN7bCgnn8I5TVDKdhUJcWsmE8nDleOt26kp0ASWU1AXN0z55IZy8Vb1OWeg+956R0XVpz3PKqMFgWDTxQPjzShpUkOQ8SqzGnbMBiDuZx4LltydUURS0zcYM5viXJHHwNBFLy4XFCmxNpAo89EEkGWVEIg5YZb2/EDbflCzaj+SDeN6H7hKmWO2VKFhS9kw6FytG2Hajbk6PGNhLnmQfRsbE+pemKC1UExDYzWUkbFvtyxTIGkLPNS4b1kM/Tc+J5P4wDjW6695IuyJaJB1kQxgywJEjbhHW3j2G9W7Dph12/RzStf2hI3wOwto0pMPrJ7mNmoyGUjMXXBxRSIoNk/n3lotszLG97phXZdqNIFLQNtUFStQ9WRpsxUZeDLsuYkSlKzpbWZ4rygmYhdRHtN2AiyuhCEwgSN8CV1Ckhj+XadaW5v+E7ZopYOPSjuUs98vvBm9LRp5LP4lkbX5FhBlgzVR2R1xVBmKkYGs7J3Jw7OsiTP1ay4dp5zkXjwC0JVDDoj/IXCTQxaI+aRMC1cUubh0OFz5D6+tyW5WitezLBMJ+K8kvYLai6YzRMXNugxEKIhZ8mPXhx4jhYzw6I+ojQFn4oVpRq8EHwdNu4fxNwHfqWJumUKrxDq9ygZ+FLfkJJmzDXeGdAKIzJRXGPTjCCjs6eXW2KCKq8UaSZgWalwQvL7h1+HJDirmtt1QoiIl+6rP7oCpzVaCjSZJ9NyDjckqaizZh8ibdBUzvNUCGYKXLY4YThWBSyZl2ngT/nvE5cND4NltAOF/rC5yQf+31gtuNm+wp/OVMUDtVAgNpRDzxR7bHKshQNTEUzDk70hVlD2HiFXjPQgPSMTqYzEWPBDd+TuumN2FVVVM+eKdj5TBEW7TMSHiPYCHSPpOLJYhdq9ghpal1jXhIiOvt1AXmnWN3hV0vZnSnumrRxn4egcaPGS12allS0kj5ELZTGybjImRjo/oZYTN8nixIxN9zzPFULNjLnj/2LvvnZ1S7Pzvv/fNPP88go71K7Y7CabgkhJJGDI9k37AnTiM9uQLcoUQ1d3hR1X+sLMb/RBwQcCDJgWWOg2e/3uYA5gAA8wxxjvsWlAwhxrvh4G5pRYu5myhGUDYnLMZJybmosUtPOR2RrWRUn0Ozblhp12+MOaX/xpwXjnaN1b8vCBIU9ICTsruE+BJ06M2Y5SWT6KhSQXFgXH9Y5EJOhIv16BVtylSHUa+eg3TKWkqhLWtQSRkUTBTt/jHLxX1+SZAeGQnFBJ0/YZRfLc2h8Zcax95Lp5zeW0Im4sXgaqS8+gNE/tmjlfOBrNZurJppyVy5FmTb3ZgJ/IApRTx3EaOfuZ0gUuzRq73tLmgV1SzNIyu8gkEkqfaKYHBvMCF3I+xZbysqBdya0M7E0ii4Iu5PzQ5bikqJYNj/K3lMMDQVvqrEBMGf16i7WSH63BZgG/eF4vJ0ymON0/YaYfQBrK6QPSFMwT5HpH1jpK0ZGWmQ09wlgusWBe33BwN3wlIrIbGPuewThmJorZkHUr+nLhvtQEFnZ2oZGC8eGeZRd58DkqeWLU1G5mdAuN0nzKW45VxBcZMmjWleLp7PE1xNkwKzjhaUXJ2By4vTi2fUdPxZNqKFxBljYIA/nqNSb7l3Vn7tmzPwhxnJChx+UJrTw2leRxJsezdffIqNE+4KTAJYXRM2OWY5EEVeNCjpMZGYlZKR5FxShaTEwMouKd/gKdHCc98JkbyFeWp6akFpbJlhzLik5IRpXzVTzxOX9L5vZY6+l0gYwQUSAlWRzZMlI8DRSLJPWWHZDakoXnmbln/zVjSur1Nb7+kb19T7CGXA5Efc+sF2YfsW5L1q+ZDzsIAjWBHC2ekcVMtClxiQvt0JPpDY8msSTLJy0QLoeTYs5WrMcVO/ctUc6ci+9hmonxljlbUWc1Wt6wcye+U4nHZYVVkX5eOPhrTAyUYyK0x582CfPIqrXo7MLq4lgNF2RWMMkcYzyjC8zKUjNjsjU6GIQItPPMaC7cly0DgU9VRR4kU9S48oLzj0g9Yyk5hhy7alncwqOsqf3Ik1mzOp8xp3vGHsQBVk1JsTfsr3do+w8cL09shpnkJ5RsELliFz6R7JaHADEtzHmHFTPRJdZqYQAmVf4UbNLEPJbMwpPbgPeS6A/EMBNN4IPac5oNsy1pkyCbFvaupMpfcC0DzbpiHP+G2jpIPbPW/EhilgvCBMLkKfKAbzM2qucoL7S0hDpjF2fK1Y57ObF0P5A1iWA1c5FwpycIFXO5oswT10ZwXeck2dBd7jgsnyA8cfEeJwpSSMSL5L1+SSYyYqsYw0fi44U0n7gsv+GS/RrSmZBGKvUWZSQegV1aLvoKengQC9ovKCsIQ8HHULEfE3eN4LfrnG9VYjDX3EjBOmzogwY1UYwzptZYAdX2Ndkp8UZVNGHg3sLSP9A4RRAF0gr08cjke3pVYWdNazJUnpG6DjKHqAy5zzBh4mwkZYjUeiaV14xlg0xr5kphQuTlkhjCyEm/ZioFtrQInaNiwBkgQe4M+UWSL4HbfObrfc4vr9e8LA4/2xvZz2Hu2R81P13Yp3dc/MAIoBKzKlliTq0sWXCMrJm0pIxHrv0Dn/QtKAlJo5MlBM2C58lc06uaQMZaDLTuQhYCWzeQiGRmwYuBPB/wSnAqN5znNUsS5PKEWN1xST1DUaKSoadmNS30zAgVaWKPMxbWivtuTXVWJLHAkuOs/H2X8tkfGCkzotyx+MS1G+nmSOYvhGViFgMuFEgKRrnD6xVKBxYJBQuDtxyVQa9gjA32dOTj5jWjKlFGcdM4HmxBaQLTPBE/RoSZWUyNSAaHRVaKj+dHdH9i2Sj+upHkOfz2GMD1fDfPYD25HwhNh84tXSMRuuY76XDzHbM6cFkkewVJBOaxJiXLEcOSNawI6E2NlJrTWXGRJ4ZoSC5nVUbW0nMiMpJQbiATkbOomKRhwuDUQjKKlzN4EVhPHc5opDyDyVFXAW0C7z79Z/7OtnghWbcNX4UOMc1Y2xBEhzMJU1xwPkdJjyoKHnXGMhnyPNG6niq3qMJSeg9hZnn46TSLKQKiXujRVMki5gxZTWQusOiWD2rHi5j4zfgdN8sTxIBUE6J54nH9FceiYXNTs+kd6u5EayWb4T1/vzpwbA7I2TP4ilGUhGlHN7/FP16Ysws5BauYEZl4W0fOOqJWgpgJXtz8kr3acxwHLqpiDCOFnxilItiKnkCUgkkEUGusvWUKDZ+EQriALc4wa/Awh4G8KkmhpeQlxdUV9JKndsbFM/exo2g7ZOowQ6BfGqbLiTaL9HHDY4KHQhMXxcnUbP1LorjQRkMyBbnsGf0j751lcAvLbLjke8zsKKVm2TgeIpxEQkUPsYDQs/Ejl6gwsyUVHlPvKLuKJjkKWSFv/g2LGeiGDhM9xk50taEfIhSv0H7Et4HM9bjVRJkENr+mXmZehIU35w79smLv7indLW5SeL9B6+afvd+fw9yzP2opevRoaEXHPWu0d8yqIvOWMSsYUyJLR3IpWKd7WnlmlobIAUeJipBHj5IBHyxl+ulKeOsHXs33eFOgtGWYS5K2FGZCyoDUOZV/TykEP3CF8p6Lqvgb9WuWVtP6GRcrjEjcjE+o3INITJR0KRCEZlNZpBdU+YG2Pvy+S/nsD5A2GWmuUI81tfmADB5v4k8bgakm6DVHmVOkE5dsg1p6SuFIuWCZW3RyeL1GlHtMJtklmELNlBY2acYuiojGBthktwTlCJlgiBOh/46JDZ084KbAP8qMNyqwKgomEVgbqM+BUniCDCj30zyqT4kxSGYWXpcf+TC1ZIOlSBLtBEpEViIQdCDKhSRGqhIGYcieFNkcWfKFbebZWsU6c+QhsPgHgnhJ1xXo4IgqozIG8kiRFYQg8NWGKYuETFCMT+i7H2gvhneFZzK/Qs8DF0rOy47GGmJR8OgFi8pxsyOXC3U8I2UNKrAWF8SysJufmKsSV47kqeR6+IR/1/OxekNjJ4ZSkqzCccGpyCoo1sKjRIOanlBGMuRHzpVGjE+4ZJmj4EG2yLpmUSsaPfFGdFRqBXMgEbmfLDpZtN3TTSuYHD49MWAofAQZ0cVMWhmY4SVPdEVJEAe+7QVmC6s8MA4DIp/QdsekJdFPZGXPTub0WQ5hw1O9Ro+R1WzYIWn0hI+K1dyTlowf1zf4KKlkwasxx+mSBlDa0qt3vJTf0Y6OKpsYloLJKj4ag68axAX6VCKUoAoj9dyTDRNWSeKk0HJmlWYqWdIsFz76iDYjefBM7QZdbQCHOnXUuUYGj+TMIAxP2YF6jmSqYCsNt28yLmdFWX5F39UsQWFDxIXIS/07jDnRHEb6+g2/O63J5UfW4sTeRiazZdhUMBgKaxBJopQnngJ63RCfjvjNGd08h7lnz/5Z6aCxU8aTPHBODSJGLroBGUhJYRIUWqGjAxGwaF6kD4gYsGFF5j1GRUiBORlGanJnuZ4+8qvpLWMqmYvAUa4ps46QHK/jb8lmxagrzBJ5lIYkA73aoINHoHjwK/K0YOIjttoQyVhnj2gEttLERXKqV4Qlstve4LP8913KZ3+AjIscLobHrsKXmk/6CiEG7rMSO58pl5kqzGzqQLO9BfuRgoGZnFGtGREoH7hZG86hQOqIDIKdsGQ6x2cCrzK8kNzbnFEKoulJi2c3WZR5YBaJfHL8kB/okuJQByrT8VUIBDEzPiSkiqAGlqHmhGKpJmxMfBgEl7kiT5FIIhSPnHVNn3bs40QpHHb5xIfkcEtOjJLaG4okeDVZVuUVQ24ZA5yGHBEtuvBIq1m5jg1PbMsHrjefMQ+Sk1qTz/f0RU4VFsqmZQwt47ljNJDCDRU92kfSNHGeHVPjmcuCT3GNoEGGEpfOTCrQiIheLLWWkDKK6KmvPmcrWkI2kDKNjBei8WwIHELHbHdsXWLMHbvFcidX6HpGyoQUgfEYEWNJ8AW6kOy2htVmxyt/5qa6YlYPjMbRiYFi2TOmll41FGVJJw278xs897jZIlYbptstQg6Mi6UM77Fi4e9KqKXkh+7MX45vEd4SdEuIt1zijAkji5G0NpGXiTJFnph4WSWWzY6m2LOKBUkIxOYFy3nLx+2ebXfhY5Hx2dhxU6/IrODeOFplENWaBwTr5YEinvjzuWcVtxyF5BI3+OXMU67w7kwpJhwOFzL8pSNfPHb+gFYti7cU64FKzKiqAaMofeJ87vCDYjyPmDxH7S2+/OlViXlosX3BaYD9/gq1KZE+I9pHXmBRJ8dRTVQcibNFy4STj3ixoyIQQ8AqRx8sV1mPTw3JTzxmliAUZ1Vh+5E/FRW7RcM/f5Z7DnPP/riZLCcNEm9yeremK7b4oFhkBVKRC4tInlxciEkRpaAk0ODoxcCKkSo5zn6NMJJymTDKsg2f8G1kc/nISZXAhrPZMs2w7o4U2lGIhJKKw7xwyteMznA2FTosXNsnGn3Bp5JJFOggObFniGsy2WOahWQipZjpS829HXnF7vddzmd/QOyy8P53vyPNI07NfChKHrIKnTWUfo+LM2ZYaIRCYmE+YpLD5BnFMrGWJ07pilwJNlLyJmgu80hajpA6ln3NeHQcxYFqMswqYAZL5s8EccSaDjWWxKbC6hLTweDO6GakuBo4ZBkcJgI5i71iPEeiLjk2msl1aNuzDsB4QeYdQyVROrALlkEGatezHmqG0wPHQ4WeO6IQrLICIQJSGKQJVIuFUBKzF4hworQOMsuq8gizUNcbwqB5qmo6c4ObCiQL0xD4YclY5Iaz3lNcArs5USKJ+sCnqWdoA1OssLYmqIzaei56zw5J7Rzr2JP3iTYTfFxnzGrFky1Yc4UwjiDOeNOTyQOlj+heshUJlWlcviHjivX0LXp2XKURnWbEsWPpN2QXKFbgngZm+zuGp0fuZE9ddoj8CpYz6/6eQQ6ocCZnxJV7smKk6iOpH7BBsCweUzv2pqM+nWmWA3YLtyvH47TwXgaujaAn8ijhrspxdU0RH7j1gd3QUx07KBxznkhlQV0q3mQNMgu8y18wjSs6LFVYmNqCSUbU/I5zP3G/UbzXn3ORmrI6caevOCwluRm54YHtBX4rCyq5sDKewr3jUu/pJ8l2aOH+E4ufCUaSTxX7wxXWPsAg0PJIniZWouWpUGTphk6BUBGXZkIE0pF5LqiFY9QWfffIRazJioJ+Vgy9xc8LsviIqC+E6o5J5DAVaOsY0sISM455yyVecy8VX+oL6/xCb1aEucYoxTyUpOIzVPbzHHh/DnPP/qhVhzX1mzXiMpEfId4YipCIJqHTTJlGRAzMsuJjyvFkaBxBZAgZmE3LOj5imGnSmTYuTKLgbfYFpzhQVx17e8EUgagUIRU82jd0fsLnApKgYGFKOXrKuYoTqfLUNmFMJFsSS7EQo0F4wyYOHMRH7sWKc9EwkXCpY7HT77uUz/7AdGPH4/QB5098YuEYDwwYJn3Nl67ilg9s3SO1+0CaD2gs9y6j9pFefclTkwhawMqQ/CPZpxM7MXMOmlhDpqBXgdxZtB9xesIKwewHQgoU2UiKnqtM4HSFspFx05ByhRYFuA/kXvPe5pzcxKwWtmri4DX9mDEFQeokxig6VUOcCTLSFTWT84jhwKIjs3Ocxi1XU4cxCa0VJnl6/QKv1lxUJJdPGLlQiQK1vEKnE3nZ4TNFVQu6ZDnPGcJbLrVGjwupesGDKrmeJSIGFD3tMhBaxb3POVYZxnhk1qPsEVPsMNQYCbnzTN4yCE9VJTJfsx0STm7p+4V3dz1LVCxiIGsTv9gVLGYkqYpJOC4mQ5iFj+6BfOkoHJRmwzhdkO6AzA2Fd7y8fESnjqIMSOEYyoBPFywLp6CYLGxCwGrJtAk0heDNqiaer3DecT5FzkA0L9jrDZtcIPOWu2B5fHiLU4I8LFihueQrYr5B1+AF4Awml6jHER0GWgKNTOy05KXWdD7nnO7J4plSJsp2zUjGXi3c0HG/9HQxZ1g0ZBkP4TVfuhJVDsj1Ql62VPKa9dSQiEzTiYfZccrXCFmhwoKaBNMUUB10ZmFDoHI15eaJtVmwgO16HkSOzjwVE2dZI4uWxpwZkTQx4cRAmBynVDPXgmQLnJG8zyOn3KA11EFzH26pveDJ1nTsUKEi95AxcycbDvHCRayoJ4ueT+QIHlRithX6MeNcLAQRfpZ+fw5zz/6oNU3Jm7/6d3z/v/0H3HDkPK4RTvLQBjK5kIuBKEEFT582WCUYKRBINBHNmZkKLyxBGO7Kn24edVnNtX9ksgktPSGBiwX1RXHOVyiuSdIRJBibkbQBofhUVGzFCa8TYCiUxSwatShSV+JNwOsanSQ3+gmZIpJIYZ4XIJ7915JIWKF53N5yco90MicbOk5a8Am4urnhIM+sbcaUfpoVLVVF4Y8sKWBEy8EowmRQy0DhTgw5lPpIJp/ofUatb5BIvLmwaEHJiBeWw3ChCR6Rt7w4tMzb13T3kUdhkWnhB19ziddMMTAVij4TxMrgk6RiAanIZkNxfKDIDWQLpRfYZYdurlBCEHKBCxKjNUk2jM2WG3VHG2eSWdEVJW/tE3e5pi5fUVnLV8WCKjPKsEK6AP2OYBVCSi6TwuvE2a9oVOBFZimyjD45tF/Y2A6tPVJsCGIhr3fIOGFkxRfuPcPljPU9Zv+SSb/GtpZlemBWE6Lv0XpP8pp2CqhJEJBkuUbKR5axxEfPWZU4IbjMglt95EF7yiJjcjnZRRDdjnVRoWeHMJbAjBgeUZVmDpJsMRDeQL2lthLlZ/z8gZxHdBb4Yr3mxed7Hj9ILr+9w597tlETxwe26x35sEGEif9OvCNsb7H+RFltuUwFjoJBzURTsK0NpaxQl5mr25LTJRHDwoOYKIGnvKecZ6x9Rxp7JrHmK3tCxsQ6lwijUAl0dEwuY7UoJqNQTpA1OXrl+E35mn5ukdsdr7uJr+qR7+aPVM4TRY6IFUJIGpUQuWOJiqptMcVInwRPumF0K4S58Lru8bpgvKqp44FUNkjrUWOHf2qg0SQGZKEQcmIJM5elYE4VOkRyGzhVmlCULPI1JSM6eXK/UOVrgohM/kAbF/IgORSOJfWsrco8TgAAACAASURBVCAukZuXN2yaa6rWELz9Wfr9Ocw9+6OWaclf/vmfI9cNxx++5evThThEvv/xLTH7hMgH3rd7HsUt3hiilyQtiUngkRQpI6SAkmDiiBdrStcx5xVWGEolKe2F1k2cXOKpec1QbEiN48rfk1vA5ayWHpk8oTIIGXjSFUbl7MIDV5PjTjboJcc7R1FUbOKF6C1WlNxcb3nZ7H/fpXz2B6apWqrdFU/TPWu14+wkyxSokTRpZCstPoegS0S24RMNzm0Y3AGxWGa9oUoDJwNeGu7jFav4O3QAnReEpUaEniz2iDLQTiUrPfKYDGa1o7265uv1N8jUEos1/HLP98nxg23IwsjuTnHGcI+F5NHyiW2q0MagbIadPTkTNA5lFEXuefXiJe/rL3n7lEHeMwXPdVbypQgIO7P3GdqMnKaCUQROooJCYdIFVwk6+4J0XiAItpllvVpYJk26HLmeb7jPnyhLgS88D3bhm+mBvc3QSXJBIa7gLjPoyVHXJYSMulCo4R1xOBPWBz4vE//gJJP1CO1xoWKVRV5NOcdUEOfAKCW1lOhmZFzdol+84vjo+bhM5PrCSeZoJNZGVvQEp5jTmqLQzFphyp7txVLLgI8j1BVLVpGpQOhr5LRDZluq7IS1OV+WiVxPfP7V16xefM5u39Ca39GvfkRpDXc/UJUHdLng5IBenkjykbATiPaG9x8Ec2/x9oKfDXUWQfRsswFnMlJqSbFCNCtieYsbO6K/wxI55ANLqmmY2a4aXq+h6SW7QvNfTuefQqGbuL0P5KFjSp6728/odIteBHRHTk8L7Si4LV/SyEi82mLlA437R2x2B1KAW/FAYisgqi+oGEAIRrEmrbe8juBevGLja7olUu1vKNWK797mLDk8HO9QZY92C6/o+F9Z8RQtXZNxbXuCyCiqr/DdyDr1jK6klTk7s6J0GcmX1EKRzwXr9swkV7Q7BYuhSoLMOcoyJyuKn6Xfn8Pcsz96Tab5qy+/wn3+Jf+Dd/h+4P3f/B3/y9//Jx7Gb3ExspLvMFVg1jlzKkkp4IWmDI4kFSk5cmWJcmDKSwKaThTkUbEIjZdbpkYyTwmtR2IKpKCpg+PWX5hzwyIEdeqxc06fl1xfnvCioOx76uKBTdcx7K741S9/xV9c32DtCOsNX774hqt68/su47M/MEYqDrLkB+dJwnFIUKaRWS5MpmHZfMZGNHh/w7e956yvmaKDdGLvJoR9ZAo3mFXOyhsevGSTJ6LMUWqhqGpWoWAZFN4cCSYi04orteYb6TDxiJw6ZLZjsglTgrIXdOrQNvFYGdZzyZ9tCjq1oos75Owx88AVgrsUubp+iQ2PxEyybyvaRvHjMFIOiVbnNMrQVJJaClJMFM2OIlfYdxO/mCWYjBOGoG4xSqJMIFx6Cr3Fe1APJcWUUduZz9yZORnQM9daYIzkRkvWeLRMBBOwZkDpmkpEXrcSFQtcmPh+c8VDK1jymkZr9lXONBrUPJF8RLUrsmlFlb+gzAfQGzIuhK/29J2mTSOXbIUyDeGYaJ2l0RGrB0JWE8hZC41pr4jUbP2enXhLuXjcyiLkjlO+I9rIEPf4mEMmaF5vuDwpsqZmU2fk9Z+B26OD4LAPlM7h+jP5qqTdVcQgaL75V5zPgrlZqNfXXPIbvh0+0NqFSSW24Q6xlNxkipc33/D98Y7HessQwCTJJASPNqdVNd7PnI8f2FcTVWn4LPPo7ojKryjefEa/v+HKTzx8fKK9PJDpFqRFiYXUd4y2RHWBUTo+ZJpNXnB1OpPnE756IjSGCw1WavL6S85TxbSZsP5MKte05UteZiVv2jNyOvJ/xsRT1EgtaRdBMIF827ARBW1haLcZuhtxi+VwHNj2H3gvJK/8BVFpyqHF5Huu9DVptKxLw13+gqyXfHZaeJVrRLmm+SwQp4mgPS/sDV/f/CVt3rL9/EBWVD9Lvz+HuWfPgExKMgloBUXB7t//Fa/+9Bue+p6H0ycezx/4x7//B96XE/2suS8bFlshYoYWJ85lgwiecpmwRmNEwAuFFJoQChadkYLkZFaMlaaRHYd4z5pPpLHldRj4wAtKLpypELODyTJoiQqOKl6RHfbUtwf+7LMv+fXXv/7Zjk8++5fBzhPu8chh6hAyUnsBesdGlZjyllf7Ay1rHj5+TxFHYj+xyEQSI7FsEOM9QfZ02Yp/LK8QZiaqa+QoyEaFnWs6GZnrHJ+9Qs2KGx9ZryXbvMJVXxJ1QzIHFjfhpgvCLdzUinUWyMuWP9m85rgEjlnGt2NB5RceVcXYCArvKIoNj7JkvhaMOdTzgudIayJerahC4s9qKIs9c/ye0U/o45F6LlGl4gvfMrWKw/YLZLzg375HdYk1DrFpKXTOXGT0Y+DSBYztsUJiwxEpDaKoCdmBpDzoB7ogMOlMs7mm3rfcVmt+eDoTzzO1sxA1c75iLQNrORNiRRM8K1kjy4z6dsVnLz4HO9H4yLL+kbeNZykC+eENr9tPfEKxGQfMdKSMD6hgKBpPGh0nOSN0IvviF7QfwFwMxeGK0Ow5TR2+LHFSYTPLkFdsdi+Z9he6Zk22vvnpVzqCMDkaUVHcfsU4/AYfGy7phN4q6rpkt/kfsU3HknryALfXFedxRPSCrS5pNi/R9ol+OWG04leHA11KhM7x+Tpjs66Y8hvC4/dcDld88/KXBP89Wkemx4I5v+I0ZoR5pBCWIi8w2wIjDUFkrJtXFNPIpZxoHwd0ntA+4ywL2LV8sdkjVM84/BZlZrTOoM7JsgPN9TWLuvDFm5fsd59RKcnw+J5P339H3wsKG0A7JDPC9Vxv98hOsF0VrI2lrw2fLk+MsyavV9woyy/MnpdffYbvc+TkflqcKCSivMYPgWL1mrCcGRoHHsq556a+wpQV1+rXHF69JpKjzM93deA5zD179v9AZBm72xt23PANX+PszHW+4T/+7f/MMk98+WQ5d3C8CoyFIS0TRRoRemCUBb3c4ITmPlOspkg2B3LtURKkSuR+IIsz7dyjQ04+CII4cSk0KQhKGfBLpKozzGHNf5//gmb3iqYu+NWrb56D3LN/GgGl0tw2OeKqpSpvqKs3tNNEnC9452jyHY1NxMs9L6rILn7AK8ugDH1xzcZZKAu+fnRciy3We4b1C7IypzcFW2+JXrGsNAUF1XKirhtMbpitZRovjKdHNrefEe/ukLljJU/cvnzD6lqRTS9oM8n4MaNlIvY/sFGR7aYhe/Oa0F1RVSPn+QFtjhQIdjKR2ci/Xbe0mwtzqgiHLwl9RywkjW54KSa+KgtOL26RhxU8jaTtK2YsJgjkJjIHx4c4MYQdx8Yz9RnBOD7qDV9UM++o+GK7oZgfue1/JM0FgQcK3SLJEEGxMxVkVwxmoRcZnzcrboVE9Sdipshw7Hdb0nrFsV7TXe7Y1JK6kbSHP2UjHZek0fd3GA+hUJjhQqZmZJmj1ZpG14ypoqm2aDFyP14w7Z61ymlelRRVwX488hAK4mWkXdWcho5Pl/+EXTRP+sx7Z7mzOddZwe05kU+B6I/YduFh1TDoArmvWbKaL6+v0NMDp6d/QOUr3lSG7NWa3w0jDJ5GNhxMxU4GJqVxbiRXGzJZcOvXTG4gThNWbfBh5K2TvDQvKcvIYh6py4Czmpf1LU4daQrPC7kiL7d8mEeq1QGe3tMEy7Ld8UOrCcuGTBpq+8iUdRyyKzIBl7Jg0oas/hOigqUw5NtrXr/8kkoqxm7ATgtuHpEqR4kLtt6gcoF4sjy+/R1iLODzGyrVkAKsdzdsLx+YVmva+EApLXnQrKst5U3F6XGgG3soc5JfoGrJiBT5wmZaCK6mf5Tc3Na4OLIsFpPnCPXzvdTzHOaePfsnMFnBX/z1v2ezveHx00ey0xP3wxN/M1/4NlXMKCI5SxJEDFI4ksoRISCMpV48cVhR5YqwBIxQjKrlUuTkZmB0MJ4NYamoUkQLj67gy1+9ojgY/tX1X7EzW7IiIyueb8o9+3+XFSWr3YE4z7i0wa+21NdvUONCHd5j6oL+NHPKV1z7DaGZeKEncvVLej6gphypEiUdVbWifn1NeQ7EKOn6iWy+x+crHuoKO00Ek1GMls1mRWyvWW8SmZ0wKFyyNKuccdqgKs14dyQ+eR4uv0G1oKsrmqJAGsXW3PB106KCI9utqKYNx/ORfsw4iJqbskXvPN9kt1zffMU0nqnmHDY1a/0D5XTGLp6svSL/8pfYreFpmvg0v+VgNau2oCiu8GvL/aXHTQvoB0az5d1qhSkS3vXINFIIUKUlGonxgpVSTF1gPlomfWZ6c8X25Zq/KHKGZeY9iq+DJ2pH+XLDLjW46cLq5jOWq5fsQ2A8P5ClAT8tcPeAHiua4CgImGbHm1oxV5EsZMjiiVxsaWXN8VNHl0YmfSGJBX3ImHlBe7ilbEuyAFvv+PvjD5zyBi2+Ry8zhVrh+5FjGyAvuI8TH4aZL1KBTIFaa0IM5Mah84LoIt1vvqU/fuTc/SOxKbifJlT1Bd+sX7G6yjAhQ4dAFRfmMpHmM3muSVJyny0swTNmLTfbHTd3dwRnuJKKTCbu4yceXYZaaf5idYPnChEXYiOwJNbTI5/LiP2mBZtB+4LW5ywfJ4bpA1kfiTqibr9gOzuqvKF7UVDfviDTJcNwpDaS6eGe6ewJ0fPphx+xywNNVpDJjL2sKWXCZmuaTQt3HQ8Pd/wf0ZLqkmYlubnS7GtHSLd8tt9QC83m5SvmfmCxAjJNoGS3wLYxbPIVUR3xaeCTWtOQSMbwalMx50fy9Rqhf75Ftecw9+zZP5HJCn7x6z/nF7/+c/CW7vJA/x/+Jz70jyxB8qHc4mWOk4YyLogk2KQzJjpC5jhmNb1UJAmrcWBjnggy4EPOIhWNXWgSVJUhq2raz7ccXl5RFiWH9YEq+3lmLZ79yyRjYi015eGW2Ue63QvqpqKbR1wKZEkRTIbf7NiZHGpFPr1FhoJwPpJFz15YimZD4sTx8cyQPNvqlu2qJpQvMZOgVw8kbclSIncGVSS8dyAr9rsKFyOVCHRGoaRFDSPDODHl7yj8wgbJVRj5d198iV1qHq2kXEuWywe224Y/WWXc5S/xcs2VfIdzFzaqwYbAtz+csUEgVMntSmFEzpg+p+MDQ5mxyJmpf+Lt20i3GHrT8vXNnrrdczf+Rx7Ht3y7rFBljc8kzbkjWxQXBU6U1ASa2SK2JdpdY56eKNOaqdqxzTO6+yfoIr1dUFjqdo1sMnzeE58+cer/lnV5y2odeFCSwUYoA1nl0T4nsCBKTRFzvpyfkH4iCcO5XGHmAcGKdX3DOFkSkVUaWW8lLBNRCmx4QLS/wJRbvFsoKsnVaYCw0FLSm4gWM5OVtD6g/ZnT8QhDIB8cbZHjixaZN6TZIpdIfvrPeHLGy4QLDT8en3BFR5UilXbU2Z9Q1wcuxyMf7j9xd/+eq8yh1D3GZ/S3t1QhYArN0J9J3Yl6XXF//4my3NE1Z7bNDSZzXDUVWb7CGsGjfaJRhs4+MruBvG64qWrUegtqz8Pjd9yNkqRL1GrE+w5XFnzMb3nIRrJ04sqfeOUnWlXSH3uIa1RTY6oMqR+4Go5oVbLGMLZXWH/hHAV5vaXrOk5FTVw8H0LBbn3NpYhcxZJ9fsCNHfNjR361Yisb1sA4OlRWIzPN3gYOmy1n9Z78eEGKC3bJEGqFyhRJ/jwnSf5vz2Hu2bP/FjqjWt1SNF8yDgOPWclFFbwI78i8RccZQsbr5T1ONNhCEcVEPoGwsPULrfOM5Y535RpPxtXc8/kc+df/+q+5/cWfsT7sWNJCpavnIPfs/7PkHBJJ1q6x3ZlxGbnvz2R+YlUVyExxtxS87WbcYpnOv+XKRNT9GRFvedXWrDcj21dXnFTOe9nivOVxgS8EpELwgxDcsSIWnrUf0KWjyxVLOFPkJdX1DY1QiMOe9+/+d8YVzE8di9pRXi6gakTbsLh3VJ2hKRuybMdlOCMSJJHxdZ24FjmXkNNdPIKFPJQc8cQUqJsS5wPRGVYmMeUeXh+gzHlnNSc3cZcSu7ZB5DmsS0yhEZ8Cu3zNcZrJvUDLEr9b4YuCm9MdLy+BVSmp5oypTJw2b0jnHisSavwv2LwjXL2kKq+5rQsEips2Z72tieORsi3po2a9XZEIVGmmCxpZ3nBcPrLflEjbkY6eGdBXX/CL7YpwcQzzNZenT1TXe/pzh/v4DxTHC9J3rMqcMc/4zhmUN1x++MCv1pEwLmxfHSj2G3zoUM2e4hHemBWVfMmdrPhuHJiEIXtzRX//AVYlOpPUueIm25OvGjIcdjHIxw4TFwqlqNo9c7YCJYki43RyjIOiMzVB5ciqYQqOt87Rx4WQPL/evuRlppmsoyhyHrv3iNGhhaApBOnpiHNPaN+h2oakJ1wF++qa/P6B/OEdy/TEan/G1q8w+5KdbjndPyGmn541JDNc4j2ZqmizhmAv2OSxaFSuGXrL48eBfjyhrCcuknwTOU5HVL/lar2nIuDqjGOIaBVIi8Unw1b15PWazUUwPN7zqfueqmrxp8D1+hVZscXnAmMj411HuVicy1jpjGG3h/Y1ZvlImyeQMAdPLtzPNiLzHOaePftvNPWWrmvxPkfHCWfWPMkdax74LL4lzDVOFnSyYZKaSTZkJpF7QWklOhUU+YxOAuUFg1mTloEXX/4prz77HICW9vf8lc/+f0so7LHncbjDKs37/Uw2jpiixgnFXSh5lIaym1FdRzZOlO0NruhwwdBVLdm25fbqBWG6kLQkj4rRB/T1DqkNt68OKHvh7jxgl0SYBCK+JyTF48MZ9zTyf7V35zGyJPlh378RmZF3nd3V53tv3szOLrm7vDUkbNOmJVkAKcoyBVgSBEMQadMgrAOWLcjQEjQEmTZhWoJhwrAhgjZ4yZZ4WYIXMASbWlK2AZrHLrlL7nK5u7NzvLtfH3XmnRnhP6pmpufNO7rf1d1v4wMUOuvIyl9EZGf9KiKycnfrZVJSWtdla7TF/tFd1GxCU9fgNuR3buN2XVRZ4JgUzZQbe1+ldVsOZte4Ovo4w80Pczc9oNWKvb0Sz8kw2YwiHJPmMUIoNvofx+mFeHc9ZmlJWlTo5haXHc28dvDEOpGr2HQ2aK/fZPxWyWShWIiAOlzH7XS5OhQEUYhwW9Y6fWrhUJSHHB3tUaYzYg/q3gDVztEqJAkEiJTpfEopCkSQ4EyhM7lOU85xhOJgMaFY+GSBoC4CRoHHtBkSyh6jlz6C2NVcm6TUgDces9XW3L7zOdLMoSn2WPPX8ZWLHnZpphKTbyGVgHlAEkXszw2p0ujDjHH6JjLRhIOSjeFl9khwnCFSh3zELNjuerw53kOIglnfR/nQzivGzRzJAdvOFo6vCJM+3TSj7ayTzm7AQBIpRTcYcJQ1NGLBLWNIopBFJ2YyH2OMwQsDNtw587LALQWjaINF3yMralJnSNl2yFpBXnpEpoepYPaHf0AwWCP2Pcw3fD29ZJ0ic5CTa5TaYXKQIpuCvGwo70wxZYPjNIgwgXad0JmzkBFZU7OlfEZdB4WgEAF/1EimeUnVBgyNQAqNKDQLJ0c6ktqJ6aeHjLTBTAxe0KVoY/ZEj5vlAmfa0BZz+tWU8WKOW4y5u3dA7fwRJurjbodEm5dJixSHhKrwCN2anqhp5xWDzhphssNePQE9RjBhJ9l5JgmdTeYs6zEZbQi0Iq0jDjsdJC2l9NBGMRPr+BqCOsORLXgJuYkonYCoatEiQtYSVeQ0ekDtKtxAM9Yd9g4O2H356lkXz7rojAG/AqkRtaQ+mhLqgnmliVQNcYMvDIu9LxHNu2inoRZjlO+wNtgm63WJ45Lp4U02m5oj0aEIIhQ5a5tbFFlGpWKmxmMe+ESOR+fWNfJ0itsGMIRWzGjlPnPf57Buqfa/QjI5Ikxz+pvbLMY1ahYTbK/R6oxFfoj2u6An9MxHyZqcauoxj0tc12HQ7fKVvYQ3FxXdMqVjbuHWV3B7Etw5IowJdz7EYLpPTIAe38B1AnadKQElnvAQiwwX6FSD5eXMfJ9gtI4ZKHYvBax1uuRrXczBEXWZsj8HxDpFYTiqBL7wSOKEYZCyPRrhOR6zboRQCUq56HKB7F0izPcJhSJrE2SwBU1NUyzIZJ/9wEdJj7pVRBKu39knLDPy7AjZcZgWOX5vk0MzZr0Tkkx7FAeHUHcJ422IQ0zTcL3rURxmXM8qwjhE+C2BXsD0gKKt8NQufXdAkeVUi1sMei7hSz3E8CqtgZtvXqdqFkymN8kDxZGneemlb2QYJwwGCuH2cPd61H5A7fjk0oXa4DYpsVuy4adEGxEs7hD6MTcAbST9wQDPCai0obv9EuVezXCwwWx2l3U1hKMcUy+YHU6p8iOS3SvslRX+pKSODdXRHeLJAaJsGYqCeOsKhdullDFBsEk+nxJSEzsHbHUUIvBokh6+F+BLRVNVXLuxx3w8p51MyQqI1at0ZE4tQtz1Ha7EEdl0nyidMqsMUduyUxoIE+Is46g4ohoMuFNdI/UEY5VyZ9GS1IbN0OfITBFpzt0bEeUc2lbhzA8Zrdesr0laYYh8Q9sKMA6RisjqjFo/m945m8xZ1mNyPQdPtxgTk7oSYxowmlZ4jFUPt6tJMjCtwqNmt97DyWMax2esYkzj8aFZDdJQxBqZpygvJO6sn3XRrBeAoEZ5PrrpMB3PaJQDKkJNJySBYVZkhImLtyZIBiF++800dUocVrTqNlrnhLohrWLqqc9W61IOuoyrlvl0RuQrrnZjdF5z1GoO52PKpiXpRDjjCjerCZRaXf9SciXY4EZ9C0yXbHaTLCuR0RZDGVPf6SCHKWQuItKYLGcRHYHs0lYCU1ZMZ1PuFjnjVOHnNakzwOtrPFngBDGOm1DnObNbb9PUNSaHbXOXuq1pbt9hMnMo5S5vezED5VPnNY4oaWtFeXAdkpyjRYc7ucdG/PX4/RE9f4M330y5O7nBWEqczjqO6lJHXVQ3Ie5uIiZvsKhvc5BPaYMRPb1GXU1RMmAtCbhVReSzI5jMuKTWkfmEfjyk77oUTYMoG6hqRJPBokDmBRKoiorSgF6Pib5uxNrVlvHeFO0EyLxm3QRUTcXWMAYXIqeLV4/Zm8/pJAnRQhLECUVjEKGDH67hdRKEWODUhzh1SCsNt5oFbtMSk6D9iLcbQ+GGBM2CtWqG4yhUd4u3s5ZFk3LQ7rM1+TJrnkfc1NTODmHgAYZXTct4keLqmqzWHC0cNjohfifCLw1Oowi7LpW5Rh0ahBTMHMP4+k0OSFhPZtzdv0YiDun0M3z9EqbtUEU7uG2I19/DczSqE7L28hUSP0VFfdoq5e3yiHEbcr3R1E3CopVMlcIJAgKjaIIhuVBMt/qovOGLN49IioZmljOZVwzCPiwqelJTrA2ZuCmeW9AIH9267HQEWhvKA5jcnKI7hs2ddRampe3FxM2QOh+T1xkHewVqtEk3FQinQrQtGSnCkShph1kt61xp6hLtTenrKaNcMA4ici/klthCmZZBPcGTKYM2RWsPx22pPUHkTvEKQdJKxCTisik4aEtStcDtjEi69tJc1pMTfoDq+ISLlsSHV9wQ4RgS36CSNdT8q7R5zqC3Rtj4eHVAEMQYNyOVRzi1x9G0YT4b000FdeRStgq1sY3uuQy7AVq2kM1ItKY0DmthQlTGSL3AqA6eIyjzBZnbcLQ4Ik1ronJBvL1OUUfIsIPrunh+h650qL0JSgkuXflmcC8RqT6iqfHdgq1wRqsl1VoXWfRpJgvGc0UdBbj6EpdMgtcAdcBCCOpsD93cpefFFIuaomzww4pMZPjhGgw8ho1HC+hhQbues2jWyPIF4fhNvGgEjeLKlW+kE8dcmx+x6G6gkxihEpJ8QjkeU8wXDLySdcdlXOUIYmLpksuAvJPgpC1xK6lnOYOddSLgIA6YVCWiNSRINnRDm7d0wz7rCbTDEQd7DUG+YDFuKNWMNS+m8QOqu0dkTYMfgWx8hi9tYdyWgJB2bjDpLbqtw2JiGHUCRNMSBw7Scam9lrvzPZyqwXEHDOMYMdxB+5LMLCirnMRx6QYhqbPFeHqERpPeHFN5ikDOSbhF4B3woc4mJp3R97pkruBwURFGEWtBlzsqQXU63GwEcV5ijCJIfLRXcav8Ko6cEIoWWeY0A0FdGhatx507+zSM6ScaJWA9qlgbbeKPhsQqQnkfp61yIi+kv5ngLG5QFQWHVcnb0ifA5Y2jCT0Hkipj2wE/SojXXQ6lhlJQFjXt3QN0XWOUy/rmJar6Gql3iFxUuMWC3s2Kq6MuWgla0ZBGAThDJkWJ3ylJk4C4Y2gGfZx5gPI38BaGIPLojHZRk1sY01JhcMKYXhOhPIkXBi/WnDkhxBD4ReAq8BbwF40x43te8y3APwS6QAv8mDHmF1fP/SzwbwLT1ct/wBjz2ecRu2W9o6kr0BCakH65j5YNnbYlC2Ia6VGLkII+XnuduGhw3YqgXqCNxPMUqumj11LqNiXuHdJtBL7cJ8/fBq6cdfGsh7gQxzDXQ/cv4xRjQqWRWUvgC0LfJb9zxHRhWIQt+W7Mq7sbRP42zG7RHFUoKrZ8zTRcY25K8lYydjwSX3B5d0BGw53qEFEVFOMDesEartMyuLqGmVWopMNod5tsMiXtOKRRyI0bNbqrKauKSjkEDIiSTWQyRElBk2ocv09bl+T1Op3Ny+TpDH34JbJFSW1y+vHXUaNp/S5RokjWN+i2iiYYoOZ3kGFLsziiNg1+adBtSzE9IBZQti3M5+i8JVgbMk5fJ/cF0gtZ332JmxQ0+REBPnXpYPoBvlPj1jnGBDhOQuK2jCJJt/Jp5JBCalp/gihuILyIjnZpSpdZ7NGUc6LMw1QuWVpSTFtutTO2k4CROCSvXHxP4HZ2+PBHL1PfuIZyJF4r2IzWqMJDCm1QWlNkOXfrIzqeTy728fobDPsJVTMnFhmR4xGkE2dKPwAAIABJREFUKVmWsnY0I0h80gqMnpM1CkFI4HZwmxxjNC45eX5I2/kQg3oN14/ZK+5Q7qwz8XKOihzRCmIvwhlo8voIYoes0IThgKi+hT/9Cp7bQQce7jf8MZybtzFlzuFszsRU1HtHECXsm5Lhzi6N01L2G8rcIVIebl3jFArHVBi9x0i2SLaInRLpaRzWlwloVeDWt/Hil+nvDmkbjeNKHFdSiUvc3D/gbiu5NZuz2RFI06LcBXUCPQUf6Vxmlt/i+t5dFnXFuOoTtzUbqsWfTsm9Ee3aVfTsFoiWtq0waUEn6NDtRWi9gahaxt0BIrjDoudxSMXEPaJJIZIxSZ3RiQZEIkXXLkW4Tp7E3HV6eFlFa1pe6fee6e+DnlXP3CeATxljflwI8YnV/b9zz2sy4K8YY74ihNgBPiOE+D+NMZPV8/+ZMeZXnmPMlvU+RriYecnlo9sE6gB3O+JGNEJLgaQhblNMGTAzA1JH03emREYSakPUTBE13E0iFuEW0lOspxO61Yy6as66aNajXYxjmOuSlg3VPCNfaOKtPq3TZSLGfFm46LmDvp0SRS6bcY6n+uieT9z5GFHow6Tk9q096sZBNwWiLpmXFbnbElYlSQ1u2+LrjEbfRvkD3B2fQdVFCc00hNRopuMjdLbHQRgSbV/FkzFX/S6JO6LWLagD5ofXcY/mOGGArwYkTkk2/SNk/gau5zEtZtDEjIIhO2EPfzPmKAio9saIIiXLFxD0CdY28Ks5rTRk+Rpl60PdstELaXRA6dWUQZdoMGNj9wrTfB+/12OUb0Lh45qQkJINp0KbW5giZ1a1dMJNbuiKJGtoiiMyJ8SrXRq5y8B8GZoG08K6gSY7IE+nSK/BP/CpKkVP9iiagEmuaL6aQSApqxRn6HDpG68Qf/QjNEVB67gcjSumrWF+54BWtXRCgdONcKsAU7YUiwmTFgaXNlmLtlikFel4TH3tADMX1IsM3885eP13KaNNSrlNr92n23UQekzmKVJpcHzNcGuNAI2cONROg2inzPcNl/1t0smMmbkFVYWYuaSqg+e03AzX2dEl0eijdDRU/Q5xZ8D0i58niAzNJGPhBbiBRJY5odRkVHi1wyjYIl0opJ/RG8YUWYZoW7pOC3WD8V8FOUE1c2hTFkdTKMY4OsLv7yKlxpQlRiuKqiEtDqgqjShS5q3LIIrYlAVOlDDyKyq9YG+WoktJmVUMJ4eI4og4qOlGDqPNLRQj9Bv75JM7lLMaoeYwbnBkh+EoAd0SV3OqSLA/bsC0eI1LWPXxtGZ/cUS91SNsFP24wxu1oTaKWZGxo+Zoz+V6nvOqt/ti9cwB3wf88dXyzwH/knsOhMaYLx9bviWEuAuMgAmWdQ7UpUAWEWqmEf0EHEPqdmmExGiJR0vHLPhwfYv9YIDjC7TwEVVFYAwpHtc7PQrp0IQOXlMzbEDU9keBL4ALcQwzaMKOIjAJ0i/BNRwtUuYiZTK/Tej7LIqaw8ND/KZla2MLPYe6UggkXici6LsUXs7GPKU797l7c4Ec9Dm8u8eOownnM1QzZs0vSJSGbgcv2sbkoLUicRVyfJdmuIMip1NPCRtJNxih6oZG3CEt52hvStv4JIMuWTqmuP6HqOIu2hwwrwMOZzN8WZHqirWuu7xKxHzG/o0xju8yT/fxQ/DCmN3tl7nxpU/TZJA3Nb3BDnpS0TEdQqdCNwmRErjVAT1/QRAFdGWIH21Ta4fEFzjhgqN5TpVXBG2Jms8YJj5RUWCmFVlZIvwOqQtt+xLhYISpMtrZgv7RAV6W4+iSda0w3gZF5lKWJeGohxmnpM0Bqpii5zmzaw2iO0SoiLKA1oXRwODtz3FlSzw7onR3mBcTJnVFTIepcemvD0mly5Ex9JuG66XBjxOaPKejCkohyPUdFl85pFbQDjv0tgJmwnAgekyKjBv5W+yYAW9nNZO6JIo8OpVGmZrWCNy6JexXHFQz4sRHqT5V6XGbisAJWaRTqCrapgU/pG00sZ6TyIZuvo9yfKrJTRw1xMVBS+iFG7zc28LJ7zDObhF1pzRxj28M+7jrl8gRzPbexs3fZjF7g8UcooVi7ZKL3xYICUYDyqed55is4oq4S+DAuomJQx9ExsHdmyzqPn80PiLXFYusZquSXPJcelqxsaFIeg5vHjY0Xh/Ry9AHb1PN91HNHF30cNodDtfWwHGI+iO0rgiEYD6/SW5KWtHiSEVftqSF4K2jloM8xZcuE7cl1A6bO+u4on5mJz/A2SVzm8aY2wDGmNtCiI2HvVgI8R2AB3z12MM/JoT4u8CngE8YY8oHrPtDwA8BXLlih66sp8gYRG5whY8OKnLhoqXEp6WQ0C1SwkrQuBItDcZIJnIdJe/gaVh09ml0n6kakmuJJ0MuVfuEfnzWJbMe7bkcw570+OU4DspzqWSN1oZrZUXrSqpLl3Bnh+i8wk1T3PkYHUXk8xShNXMmiEJQaY0TgrOAttEcyIzrRYvYW6Bajw3l0W+mmPyASmoOpgWOiEmNZD0MwM1wlGTTCwm9iJkTo3TClhiwOdhAz+5AoyirATlH6KZEODDwXfrdGL+/QXVwB9N4iMTjwNvgaNFAllGsDyGHKvap2oqyFpR3cgaXNug7HkIl+PEud9MjqAM6uovnJTihQEQS4V/C80FJRScekOoGsopAxAhXsD8ryA4KzKTBuA7SjUmMQqcTPE8xLSsKcuJ0QZ7PaXTFKKhxjSKvC/Ba8qpBNXfZSHLMMGIm1pGeC50+blPjSUmRNCzSt1BOSTBIcBghjCRvGoSoEYuSpijwWwdBRC8ISXoxh/6EujqkrwuE6JJ11nDDnG2/S6r3qZOKdlGQZQZVuaxvDxHzCm9jEyUrnPlNekHLUTtjrmAwCnBzQVYZ8qJmVszpJAFedsj+0TUaFZCGAaHapde9jEtFIV0Ih3hKUQqBPxhC2CH0+9CJGTJnfbRO02Q4RrARb1C1NaOtdZJ+RD3rEKoh4+oNmlZxpKasxVeYaZ9Zsk4+24OypU52EKZmPh3zcuAR9ru00zmObBl2MppyH62nRN5VYuXSDdY4mF+nqDRVdURVShxKci9h6msGjmQUugRhi+MIRhsDcrfiqPkS5mgP3WpEI9D+OhMglQXdsKWUiu1gk1jU5GXMhlKoMmWhSqq8olYjgihClTm1MYyUw6YjGegST7rP7OQHeIbJnBDiXwBb93nqR075PtvAPwK+3xijVw//MHCH5cHxp1h+I/7R+61vjPmp1Wt47bXXzGm2bVkPk3QDomFIcyAwSlKaHjSCxigcBK32CcoJSZHiJB5RA4Uw9IsKqgA/bIjRLEzBWp2ypkvCMKLfG5x10SzOxzHsSY9fruvSXxvQdjr4paatSkQ2Y1w6XB2t4eU3yIqGiAmO2SRZ69FmLUU9JXADcjUnWldsDvocXVuQyRxfJpSuwWk8xKIgLwqijqSdS0Q3pNPZpRQKHIcw6XFtsUDXmrWoz0echnDzwwSzOZ4uKVy1vJyWMEi1RjOKWHhdnMRhqxvjiQjj1PSCHvH+AeMC+q6iv9GjkC5+t4M/nrA4mBMnAwYbfaJOF7cxuL5C7Izoy4Dd9Us0Rw2udHEFpJ6Dlj6F65KIHNMWJMMO7nAASK7PbnLn8BBTajqOz1XVI9m4ilFwc9LgeT5uUdBoTUe4FIMe2q2BHKV8krJGhSGV6hKMFE3nCq3O6HRCOv0h0jXsjUuKW19ElcsEVpa7VEWF72leWu9TdF9hUl6juHMH1dlAqAg3jBmngmk9xwsdoqhLjWaj6zLo91DKoSlb5KBPm71FcXCA5zgEhaEUiiCMCAcfQR9cw53eZpqVyEjSD0IOkHT8LokSvLIVYQ4LEt/F6e7QuA0dRzH3HFpP0lEab3iZwIlZ3LlBNdtHCPB2P0S3NoyUy6xp6ed3mGUZVdMyF4JLG0OCpsIPPZrDu+hGUy0qmngHL/TY9/bIigPmtUtfSPLuJlV2C8+JUcbQ+j61FPhZCo5EKpfYWWdnrcfh5HW8ekaZR1RaMK1c5rkiTQ8ZxiMWxsV3BgRRTmX6hF1Fd9PHrH2EIJU0UuOmV+gf3GI+vYOzkISxi9laRwQKE42IipJhFFBlBeGm4u5iRjcM0d6ANR925AZHpUPrB9StYasTsT3oI7oKz/Mv5pw5Y8yfetBzQog9IcT26hvtNnD3Aa/rAv8H8J8bY37z2HvfXi2WQoifAf72Uwzdsk4kiBXDr1unc9flUp6STSExcyZmSNA0RIeSoAKjI3aHW1Rxl8Ekw3cniPiIYU/wxx3Dp4XALBw8b0gcJGjx7C7GbJ3ci3IMc10X13URgWZaSJrQZVDV7DoOxe2KytF0Bg5BP8GPIogl01lK4TQo4YGBNtBEr+ygypqhdpjlNRuqR7cuaVSL8eeIPMUkuxQmQQoIfBfWQzqiIsSnDEKSpqQfhIhOF1PX0A4ZjAOEC3lZUPiSOOxQmgodrSOlS7D2Cp4UfGO/JpzljAuDdjxCR6JUgHn5EpEn6XoKxw/wvIAwcenLDlma4wVDouEWhC1BIKmB0oFg3pCWBWEyIupcwvFjpPTI6oxy3i5PHKi3EdphO9lhOOhiHIGIrtKYhrWBwLSacv8mSI+u18WIisjv0dQhevAKKgzxnDfRjkDrLvHWJbxweTUXN7jE3K+RM0Hj3sWhRYYRnUGC8lw8t4d69Ts5EF9EIcHxWPvwh9nQgrwsUP4U14cGSSdMCFyffjiiqFtE3TC+3rKfS5wgwJ1WDAc7dLZGqFAReQFfP/BJszmeB92hpGsCnGBElRUoKWA9IgxDgnRAXpRoU9OLL7PRvQpi2aOpmhK336N1Qpw2R3sOjlLUBiKlUP5lUrEg9D1m4zl5UxIqF0eCNgbVSejrhspvqAKBrH2GQZdpMWehDb3RDoXMSV2FCDtE/RFJ6KPaBqEUGk2bZsi4pqteJvK3aHFpRIBSHjs76xzsNQy6a8xNRtco+q5HKwZ0Rx1UJwHXY9fTZJWD1+zA3asomaDzGG80QsqAMAkwqmW9dehHXaY4mNjl7Tqn5xky3eKHIYP1IVHrMLrURWIIXBfXc5/pNVnf/T9/5lu4v08C3w/8+Orv/37vC4QQHvDPgJ83xvzyPc+9cxAVwJ8DPv/sQ7as93NcyeUPb3Lt2i5674j12tA5SBk7If00o+v6XN0a8fGP/QnWt14lb1vu3rpGw6tUZsyrl1/B93vIL3yaW/tTonKGrASlfnbf3qyn5sIdwzwpuRR41FqhEoHoRsySlPRoH8dTqKiL47o4rmJneGk5v2c1LFTrGpUsl3eailYLPCS+hOndiKbOSAaCzmgHnHB5VqYrQYIf+eQLgSxzlHIQSiE8D+F5uE2Nm8ZgDIHn0QYNtaNxUCgvBkchAQn0XfimsEtat6ANsVp+fNVthNzuQ9MAEi/waeqKrHDQ2kcol3AY4DsC0TQo5TLNNYW3i1vXdDa6qDB4t56UVEhXYuIWGSqEHOC8tI7qRAhHMCKkbVscx1luf9SjKm7guBK5gMDpYzohbf9lHN9H6E10kyHdCOkl77WHGy171uoSabbw1Qh/MMDxAtpGMz8sMMQku99AGIGfRLhhSAAMAK3X0LpGSoWUHgCh5xJ6Lk3jUA56JIczaDWd7RGDVy+hkhB0g3EkoT8g9jdg1MFPtuiqHlJ6NMF75XNdF6JX2a22qYVAefH7e5eMwXUcXCpwHFA+l6RLrc0yIdQwyQ2FgU6nx6DrE3gujtZUQqCzFN/zuLJxiVzUeLkC07AbKjxcAkAOr+IM+jjKJ3I9PCmB5bxiB4jcy9R1TtX2QKrlY0GEKnbQbs3G5UtsdSOEa0jyksY4eK5HNwlAylVbSDw3JNr6MOmrLebOPkgH1jaIXnoJGQfUukbONMIIWkdQCYNUilnYQRlNsLaJCAICIOD5H8OFMc9/5FEIsQb8EsvfX7gG/AVjzJEQ4jXgPzLG/IdCiL8M/AzwhWOr/oAx5rNCiF9jOZFYAJ9drbN41HZfe+018+lPf/ppF8f6GjebzDi89TZVOaN0fNA+vgNh7NHrDkn6fSQOpjWUTU6lK3wvIPAj5vMFn/md32D/S7+DozQ9Z5dv/u4/y/rO6KyL9UIQQnzGGPPaM3jf534MexbHL60r6jrDtBLlhTju6T+E2qambZp3E8F7VVpTlRVu0+D7yyTuQetrwbtJ5IOGpLSuPpDE3Gs+nrH3xnXifod0Mmfj8hZ+Nl9eFUMI2Nyike57Sec90rLky3cOOJhWKDdgZxhzdT2572vfF5M2SAM4Hrj3j+3e9dq6RGgXR/nv9uBURUM6LfF8l6psiHs+XnC6vpemaagWGdQtXhziRu8lrG2xIF9cA+UglUcQ7D6wLh+9oQra6oFlrhpN3eoP1LWpKkxdv5vcA9Rt/W77S8P79qtHtXvTNO9LQu+33UrrdxNNT96/LU1VobMMABlF79tfTaMxrVn2CKKptKE2hsB1iLzHrL9HOOkx7EySubNikznrvJmlFV/49OdI3/pVKsdlGLl8/Dv/Ip3NS2cd2gvhWSVzZ+FpHL8e9MH6IO98eAlHPJehokfRuqIobr6bkz0oCSnzghtffANjDEIIdl7aQs6myChGZylqYwMZP/xEo3FacWuS04sUVaPZ7AbE/vMZzHqvZ84gEHTWApynXP8nSYrPi5O2+4vopMcwewUIyzpDwkCloXZjTOkRX3JRsZ0zZz19VaO5Oc4wLLsDdwfRez0W90nyTKNpxsW767uD4MwTOq1rjAHXjWiabJWMfPBD3Q8DLn30Faqiwgs8PEdSzWfoLAUhEOrRPZCx7xJ5DlWjEYBy3l/2+/UsPS2OK+msBe/7gdyTOmkCLqX3vro7Sa/Vo9z3y8Ijeu5O4qTt/rXMJnOWdYbquqUwDYdmjvFq2qMuu7kgSB69rmWdRt1qDMskJS0b6lbjufKBSZ5pl6M20nfQZbtMEM74E0NKhRDQNBlCLO8/iB8G+Mfmwnk7O6dKvjxXsjuIHjhEWN269e6wrbezc+KE7lE9Ysef94LTJSz3JuCyJzGyfWTvW6U1N4rq3Z6vS8Fybtppeu/uux/RwOTaey/qX3mshO54u9NqqCUGfeZfLs4Tm8xZ1hnSokbnb4MzJ3Qrai2ZTw4ZjnbOOjTrBaMciQDSsnlfT9ODkjzhLHuIddkCvHv/cTyt4Vopl/O7Hmd48J2TLk5jOTH+g/GaugZj3h22NXV9ovd+1HDhkw4nHk/Am7ygTA8Qnnzke9XaYAzErkPatNTaLH9H7hSx3Hc/olo+6cVQpcseusdK5pbt3tYleqExpaGheGRv8WmnFVxkNpmzrDMUh4KkYzictORlgJItQtrLeVlP34N6mh6U5AlXInuStqlwXO+xk7B7e4tEx0GjH3jCxKPcOzx4FoRSsDob86TDtvDg4cKq0RRlA20KRuMHyWMNJx5PwI2pQZ5saNKhoW0z5trFcTyUFKce2rz/frR6fZWuNnT6djveO+gQgSxP1Fv8sGkFLyKbzFnWGZLGEDo5/fBtWiMIRB/hBY9e0bIew/16mh6U5GldUTa3MWb5qx+B+3iTzo/3FtVZSbp3hFAChKA3Gj1WQnc/957N+CwJzzv1sC3cf5i4ajTX9xekkwpMxSAo6K2Bq+RDh5HvG5crcQcBpjVIIdHN/JFD0lpX6OoWI2FogI63uxxi5eRD2vCg/chbDq0+5py5e3sqfXd7+fgJeosf1OP8orLJnGWdId0ahFqn1K8ihEtmPAwv7gHHOp/ul+Qd75mpqil1PUWtfovsNI73FummBQleEFAVxeqnJ548mWuahsnkvUve9vv955LQnXbY9n7DxHXd0LaG0HOoCZDOJspV+EH4WMmzcOWqt8ohcB89JP1OO0deTNNkuDSA/1hD2u/sR5XWpE27PJnCPV0Sd3xoVPL+3kEjW9xBeKIh+wf1OL+obDJnWWdIC8W08bnrKoSQxJ0E14/OOizLercXqaqmVNUeYGjbxanncR3vLRLGoRjnVEUBQuA8pYSrbZc9NZ7nUVUVbds+82Tucd07TKwcieMI0qpFYPCCEM+PkI95RunDtnX/1zy4B+5xhrQfdDLFida9Z2h0u+d+IDYh5YlOxHnYCSwvovO5t1vW1wrHo7f9ETZVg2k0cRITJPZUVuvsvdMzU9dTwOB5/cf+WYh3eoskDr3R6KE/Mvw43rkaQ1VV77t/EXiu5PIooeg2OCwvg/a0f1PuYZ7kpJL7ud/JFN4Ji3Pv0GhrXMIniO1BJ7C8iGwyZ1lnSDmSJOyR9HfR2rDRjYg82zNnnQ9SeijVo20XJ5479SiOq55aEvcO13Xp9/vPbc7c07ZMOs7upI6neVKJkgIhIG1ahFjeP/G69xkaldI98xNeLoKLtcdb1gvGcyUvr/dZ7/gY0ZB4AYHrn3VYlvWup91z86y4rnvhkrgX0XvXAD79DxB/rQ2NPk12z7esM+a5kjX34ZcWsqyzdB5+DsS6ODwpTzy0+oF1v4aGRp8mW2OWZVmWZVkXmE3mLMuyLMuyLjCbzFmWZVmWZV1gNpmzLMuyLMu6wGwyZ1mWZVmWdYEJY8xZx/DcCCH2gbdP+PJ14OAZhnMa5yUWG8cHnZdYbBwftA7ExpjRWQfyNFzg49fT9KKWC17csr2o5YLnU7aXTnIM+5pK5k5DCPFpY8xrZx0HnJ9YbBwfdF5isXF80HmK5Xl7Ucv+opYLXtyyvajlgvNVNjvMalmWZVmWdYHZZM6yLMuyLOsCs8ncg/3UWQdwzHmJxcbxQeclFhvHB52nWJ63F7XsL2q54MUt24taLjhHZbNz5izLsizLsi4w2zNnWZZlWZZ1gdlkzrIsy7Is6wKzydx9CCG+RwjxJSHE60KITzyjbbwlhPgDIcRnhRCfXj02FEL8qhDiK6u/g9XjQgjx36/i+X0hxLcde5/vX73+K0KI7z/Bdn9aCHFXCPH5Y489te0KIf7Yqlyvr9YVp4zl7wkhbq7q5bNCiO899twPr973S0KI7z72+H3bSwjxshDit1Yx/qIQwntAHJeFEL8uhPiiEOILQoi/eRb18pA4zqJOAiHEbwshPreK5b942PpCCH91//XV81cfN8YTxvGzQog3j9XJtzzLtjkvHlVnj9MO58Xjlk0IcVUIkR/bF37yecf+MCco13cJIX5XCNEIIf78Pc+d6vj+vD1h2dpjbfbJ5xf1o52gXH9LCPGHq2PMp4QQLx177mzazBhjb8dugAN8FXgF8IDPAR97Btt5C1i/57G/D3xitfwJ4L9ZLX8v8M8BAfwrwG+tHh8Cb6z+DlbLg0ds97uAbwM+/yy2C/w28K+u1vnnwJ8+ZSx/D/jb93ntx1Zt4QMvr9rIeVh7Ab8E/KXV8k8Cf/UBcWwD37Za7gBfXm3vudbLQ+I4izoRQLJaVsBvrcp63/WBvwb85Gr5LwG/+LgxnjCOnwX+/H1e/0z32bO8naTOTtsOZ12mp1S2qxw7hpyn2wnLdRX4JuDnj+/TD9tnz8PtScq2em5x1mV4gnL9CSBaLf/VY/vimbWZ7Zn7oO8AXjfGvGGMqYBfAL7vOW37+4CfWy3/HPDnjj3+82bpN4G+EGIb+G7gV40xR8aYMfCrwPc8bAPGmP8HOHoW21091zXG/H9muWf//LH3OmksD/J9wC8YY0pjzJvA6yzb6r7ttepd+ZPAr9ynXPfGcdsY87ur5TnwRWD3edfLQ+I4izoxxpjF6q5a3cxD1j9eV78C/Fur7Z0qxlPE8bA6eWb77Bk7SZ2dth3Oiycp23n2yHIZY94yxvw+oO9Z99TH9+fsScp2np2kXL9ujMlWd38TuLRaPrM2s8ncB+0C14/dv8HDP1AflwH+LyHEZ4QQP7R6bNMYcxuWH+zAxiNielqxPq3t7q6WnzSev7Hqvv5psRrafIxY1oCJMaY5TSyroZtvZdkDdGb1ck8ccAZ1IoRwhBCfBe6yPCh99SHrv7vN1fPT1faeeN+9Nw5jzDt18mOrOvnvhBD+Y9bJ09pnn4eT1Nlp2+G8eJKyAbwshPg9IcT/LYT4N551sKfwJPX+IrTZwwRCiE8LIX5TCHGevkCdtlw/yLJH/3HWfWpsMvdB9/um9yx+v+U7jTHfBvxp4K8LIb7rMWJ61rGedrtPI55/CHwI+BbgNvDfPq9YhBAJ8L8B/4kxZvawlz7LWO4Tx5nUiTGmNcZ8C8tvnd8BfPQh6z+zWO6NQwjxDcAPA18PfDvLIY2/86zjOAdOEutFLeeTlO02cMUY863A3wL+sRCi+5Tje1xPUu8vQps9zBWzvBTWvwf8hBDiQ08nrCd24nIJIf4y8BrwD0677tNmk7kPugFcPnb/EnDraW/EGHNr9fcu8M9YfljurYZ9WP29+4iYnlasT2u7N3ivu/mx4jHG7K0+vDXwP/HeUNBpYzlgOcTmniQWIYRimUD9r8aYf7p6+LnXy/3iOKs6eYcxZgL8S5Zz0B60/rvbXD3fYzmE/tT23WNxfM9qSNoYY0rgZ3j8OnniffY5OkmdnbYdzovHLttq6PgQwBjzGZY9yB955hGfzJPU+4vQZg907DPwDZb/19/6NIN7AicqlxDiTwE/Avw7q+PQidd9Jsw5mHB4nm6Ay3LS4su8N/nx4095GzHQObb8GyzH1f8B759w//dXy3+G90/q/m3z3mTLN1lOtByslocn2P5V3n/SwVPbLvA7q9e+M5n8e08Zy/ax5f+U5TwfgI/z/gncb7CcqPrA9gJ+mfdP1v9rD4hBsJwr9RP3PP5c6+UhcZxFnYyA/mo5BP5f4N9+0PrAX+f9k9N/6XFjPGEc28fq7CeAH39e++xZ3U5SZ6dth7Mu01Mq2+idsrCctH6TExwHz0u5jr32Z/ngCRCnPr5fkLINAH+1vA58hWdwouEz3Be/leWXhg/f8/iZtdmZV9x5vLE8I+7Lq8b6kWfw/q+sdpDPAV94Zxtha56MAAACsUlEQVQs5398arVjf+rYh40A/sdVPH8AvHbsvf4DlpOZXwf+/RNs+5+wHJaoWX6L+MGnuV2WXc6fX63zP7C6ysgpYvlHq239PvBJ3p/I/Mjqfb/EsTMOH9Req3r+7VWMv/zOweM+cfzrLLvCfx/47Or2vc+7Xh4Sx1nUyTcBv7fa5ueBv/uw9YFgdf/11fOvPG6MJ4zj11Z18nngf+G9M16f6T571rf71Rnwoyx7Bx6rHc7L7XHLBvy7LI+jnwN+F/izZ12WU5br21ke/1LgEPjCo/bZ83J73LIB/9rq//Nzq78/eNZlOWW5/gWwx3vH6U+edZvZy3lZlmVZlmVdYHbOnGVZlmVZ1gVmkznLsizLsqwLzCZzlmVZlmVZF5hN5izLsizLsi4wm8xZlmVZlmVdYDaZsyzLsizLusBsMmdZlmVZlnWB2WTOemEJIb59dSH2QAgRCyG+sLqup2VZ1rkmhPgvhRB/89j9HxNC/MdnGZN1ftkfDbZeaEKI/4rlL8eHwA1jzH99xiFZlmU9khDiKvBPjTHfJoSQLK9E8x1mdR1ayzrOffRLLOtC+1GW194sAPut1rKsC8EY85YQ4lAI8a3AJvB7NpGzHsQmc9aLbggkgGLZQ5eebTiWZVkn9j8DPwBsAT99tqFY55kdZrVeaEKITwK/ALzM8gL1f+OMQ7IsyzoRIYTH8kL0CviwMaY945Csc8r2zFkvLCHEXwEaY8w/FkI4wG8IIf6kMebXzjo2y7KsRzHGVEKIXwcmNpGzHsb2zFmWZVnWObQ68eF3gb9gjPnKWcdjnV/2p0ksy7Is65wRQnwMeB34lE3krEexPXOWZVmWZVkXmO2ZsyzLsizLusBsMmdZlmVZlnWB2WTOsizLsizrArPJnGVZlmVZ1gVmkznLsizLsqwL7P8HQfET7G1unqIAAAAASUVORK5CYII=\n", - "text/plain": [ - "<Figure size 720x576 with 3 Axes>" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fig = plt.figure(figsize=(10,8))\n", - "\n", - "xy_axes = fig.add_subplot(221)\n", - "_ = xy_axes.plot(x, y, '.', alpha=0.1)\n", - "_ = xy_axes.set_ylabel('y')\n", - "\n", - "xz_axes = fig.add_subplot(223, sharex=xy_axes)\n", - "_ = xz_axes.plot(x, z, '.', alpha=0.1)\n", - "_ = xz_axes.set_ylabel('z')\n", - "_ = xz_axes.set_xlabel('x')\n", - "\n", - "yz_axes = fig.add_subplot(224, sharey=xz_axes)\n", - "_ = yz_axes.plot(y, z, '.', alpha=0.1)\n", - "_ = yz_axes.set_xlabel('y')" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([[ 3.33175985e+04, 4.36499587e-02, -1.09440256e-02],\n", - " [ 3.34805171e+04, 1.01941873e-01, -9.53601654e-03],\n", - " [ 3.35582698e+04, 2.99759824e-02, -7.85268329e-03],\n", - " [ 3.34803588e+04, 2.01669276e-02, -1.65330493e-02],\n", - " [ 3.33652227e+04, 1.51568465e-01, -1.58727924e-02],\n", - " [ 3.34439659e+04, 1.37990083e-01, -8.42117631e-03],\n", - " [ 3.32467122e+04, 1.58005628e-01, -7.74457162e-03],\n", - " [ 3.35431499e+04, 5.43510481e-02, -1.01035844e-02],\n", - " [ 3.33190099e+04, 6.23305926e-02, -1.68905342e-02],\n", - " [ 3.33803179e+04, 2.95667412e-02, -6.43673916e-03]])" - ] - }, - "execution_count": 14, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "positions[-1, :, :]" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.6.6" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/notebooks/vertical transporter - Copy.ipynb b/notebooks/vertical transporter - Copy.ipynb deleted file mode 100644 index 95df8cf..0000000 --- a/notebooks/vertical transporter - Copy.ipynb +++ /dev/null @@ -1,326 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "<div>\n", - "<style scoped>\n", - " .dataframe tbody tr th:only-of-type {\n", - " vertical-align: middle;\n", - " }\n", - "\n", - " .dataframe tbody tr th {\n", - " vertical-align: top;\n", - " }\n", - "\n", - " .dataframe thead th {\n", - " text-align: right;\n", - " }\n", - "</style>\n", - "<table border=\"1\" class=\"dataframe\">\n", - " <thead>\n", - " <tr style=\"text-align: right;\">\n", - " <th></th>\n", - " <th>CumlDistance_km</th>\n", - " <th>Depth_m</th>\n", - " <th>Q_cms</th>\n", - " <th>Vmag_mps</th>\n", - " <th>Vvert_mps</th>\n", - " <th>Vlat_mps</th>\n", - " <th>Ustar_mps</th>\n", - " <th>Temp_C</th>\n", - " </tr>\n", - " <tr>\n", - " <th>CellNumber</th>\n", - " <th></th>\n", - " <th></th>\n", - " <th></th>\n", - " <th></th>\n", - " <th></th>\n", - " <th></th>\n", - " <th></th>\n", - " <th></th>\n", - " </tr>\n", - " </thead>\n", - " <tbody>\n", - " <tr>\n", - " <th>1</th>\n", - " <td>20</td>\n", - " <td>1</td>\n", - " <td>10</td>\n", - " <td>1</td>\n", - " <td>0</td>\n", - " <td>0</td>\n", - " <td>0.08</td>\n", - " <td>19</td>\n", - " </tr>\n", - " <tr>\n", - " <th>2</th>\n", - " <td>40</td>\n", - " <td>2</td>\n", - " <td>20</td>\n", - " <td>2</td>\n", - " <td>0</td>\n", - " <td>0</td>\n", - " <td>0.08</td>\n", - " <td>20</td>\n", - " </tr>\n", - " <tr>\n", - " <th>3</th>\n", - " <td>60</td>\n", - " <td>3</td>\n", - " <td>30</td>\n", - " <td>3</td>\n", - " <td>0</td>\n", - " <td>0</td>\n", - " <td>0.08</td>\n", - " <td>21</td>\n", - " </tr>\n", - " <tr>\n", - " <th>4</th>\n", - " <td>80</td>\n", - " <td>4</td>\n", - " <td>40</td>\n", - " <td>4</td>\n", - " <td>0</td>\n", - " <td>0</td>\n", - " <td>0.08</td>\n", - " <td>22</td>\n", - " </tr>\n", - " <tr>\n", - " <th>5</th>\n", - " <td>100</td>\n", - " <td>5</td>\n", - " <td>50</td>\n", - " <td>5</td>\n", - " <td>0</td>\n", - " <td>0</td>\n", - " <td>0.08</td>\n", - " <td>23</td>\n", - " </tr>\n", - " </tbody>\n", - "</table>\n", - "</div>" - ], - "text/plain": [ - " CumlDistance_km Depth_m Q_cms Vmag_mps Vvert_mps Vlat_mps \\\n", - "CellNumber \n", - "1 20 1 10 1 0 0 \n", - "2 40 2 20 2 0 0 \n", - "3 60 3 30 3 0 0 \n", - "4 80 4 40 4 0 0 \n", - "5 100 5 50 5 0 0 \n", - "\n", - " Ustar_mps Temp_C \n", - "CellNumber \n", - "1 0.08 19 \n", - "2 0.08 20 \n", - "3 0.08 21 \n", - "4 0.08 22 \n", - "5 0.08 23 " - ] - }, - "execution_count": 1, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "import os\n", - "\n", - "import pandas as pd\n", - "\n", - "\n", - "# show the hydraulic data contained in the CSV file\n", - "hydraulic_csv_path = os.path.join('..', 'test', 'data', 'multi-cell input.csv')\n", - "hydraulic_data = pd.read_csv(hydraulic_csv_path, index_col='CellNumber')\n", - "hydraulic_data" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "from fluegg.hydraulics import from_csv\n", - "\n", - "# initialize a hydraulic model as a series of hydraulic cells from the CSV\n", - "hydraulic_model = from_csv(hydraulic_csv_path)" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "from fluegg.asiancarpeggs import BigheadCarpEggs\n", - "from fluegg.simclock import SimulationClock\n", - "\n", - "# total_simulation_time = BigheadCarpEggs.hatching_time(hydraulic_data['Temp_C'].mean())\n", - "total_simulation_time = 1000 # seconds\n", - "time_step_size = 1 # seconds\n", - "\n", - "simulation_clock = SimulationClock(time_step_size, total_simulation_time)" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [], - "source": [ - "import numpy as np\n", - "\n", - "\n", - "first_cell_x_midpoint = 1000*hydraulic_data.loc[1, 'CumlDistance_km']/2\n", - "\n", - "depth = hydraulic_data.loc[1, 'Depth_m']\n", - "first_cell_z_midpoint = -depth/2\n", - "\n", - "area = hydraulic_data.loc[1, 'Q_cms']/hydraulic_data.loc[1, 'Vmag_mps']\n", - "width = area/depth\n", - "first_cell_y_midpoint = width/2\n", - "\n", - "initial_position = np.array([10, first_cell_y_midpoint, first_cell_z_midpoint])\n", - "\n", - "number_of_eggs = 10\n", - "initial_position = np.tile(initial_position, (number_of_eggs, 1))\n", - "\n", - "carp_eggs = BigheadCarpEggs(initial_position, simulation_clock)" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [], - "source": [ - "from fluegg.transporter import ParabolicConstantVerticalTransporter\n", - "\n", - "transport_model = ParabolicConstantVerticalTransporter(simulation_clock, carp_eggs)\n", - "transport_model.set_hydraulic_model(hydraulic_model)" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [], - "source": [ - "from fluegg.simulation import Simulation\n", - "\n", - "fluegg_simulation = Simulation(carp_eggs, transport_model, simulation_clock)\n", - "fluegg_simulation.set_hydraulic_model(hydraulic_model)\n", - "\n", - "simulation_results = fluegg_simulation.run()" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "<Figure size 720x576 with 3 Axes>" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "%matplotlib inline\n", - "import matplotlib.pyplot as plt\n", - "\n", - "positions = simulation_results.results()\n", - "\n", - "time = simulation_clock.time_array()\n", - "\n", - "x = positions[:, :, 0]\n", - "y = positions[:, :, 1]\n", - "z = positions[:, :, 2]\n", - "\n", - "fig = plt.figure(figsize=(10,8))\n", - "\n", - "x_position_axes = fig.add_subplot(311)\n", - "_ = x_position_axes.plot(time, x, '.')\n", - "_ = x_position_axes.set_ylabel('x')\n", - "\n", - "y_position_axes = fig.add_subplot(312, sharex=x_position_axes)\n", - "_ = y_position_axes.plot(time, y, '.')\n", - "_ = y_position_axes.set_ylabel('y')\n", - "\n", - "z_position_axes = fig.add_subplot(313, sharex=x_position_axes)\n", - "_ = z_position_axes.plot(time, z, '.')\n", - "_ = z_position_axes.set_ylabel('z')\n", - "_ = z_position_axes.set_xlabel('time')" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": { - "scrolled": false - }, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "<Figure size 720x576 with 3 Axes>" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fig = plt.figure(figsize=(10,8))\n", - "\n", - "xy_axes = fig.add_subplot(221)\n", - "_ = xy_axes.plot(x, y, '.')\n", - "_ = xy_axes.set_ylabel('y')\n", - "\n", - "xz_axes = fig.add_subplot(223, sharex=xy_axes)\n", - "_ = xz_axes.plot(x, z, '.')\n", - "_ = xz_axes.set_ylabel('z')\n", - "_ = xz_axes.set_xlabel('x')\n", - "\n", - "zy_axes = fig.add_subplot(222, sharey=xy_axes)\n", - "_ = zy_axes.plot(z, y, '.')\n", - "_ = zy_axes.set_xlabel('z')" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.6.6" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/notebooks/vertical transporter.ipynb b/notebooks/vertical transporter.ipynb deleted file mode 100644 index 95df8cf..0000000 --- a/notebooks/vertical transporter.ipynb +++ /dev/null @@ -1,326 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "<div>\n", - "<style scoped>\n", - " .dataframe tbody tr th:only-of-type {\n", - " vertical-align: middle;\n", - " }\n", - "\n", - " .dataframe tbody tr th {\n", - " vertical-align: top;\n", - " }\n", - "\n", - " .dataframe thead th {\n", - " text-align: right;\n", - " }\n", - "</style>\n", - "<table border=\"1\" class=\"dataframe\">\n", - " <thead>\n", - " <tr style=\"text-align: right;\">\n", - " <th></th>\n", - " <th>CumlDistance_km</th>\n", - " <th>Depth_m</th>\n", - " <th>Q_cms</th>\n", - " <th>Vmag_mps</th>\n", - " <th>Vvert_mps</th>\n", - " <th>Vlat_mps</th>\n", - " <th>Ustar_mps</th>\n", - " <th>Temp_C</th>\n", - " </tr>\n", - " <tr>\n", - " <th>CellNumber</th>\n", - " <th></th>\n", - " <th></th>\n", - " <th></th>\n", - " <th></th>\n", - " <th></th>\n", - " <th></th>\n", - " <th></th>\n", - " <th></th>\n", - " </tr>\n", - " </thead>\n", - " <tbody>\n", - " <tr>\n", - " <th>1</th>\n", - " <td>20</td>\n", - " <td>1</td>\n", - " <td>10</td>\n", - " <td>1</td>\n", - " <td>0</td>\n", - " <td>0</td>\n", - " <td>0.08</td>\n", - " <td>19</td>\n", - " </tr>\n", - " <tr>\n", - " <th>2</th>\n", - " <td>40</td>\n", - " <td>2</td>\n", - " <td>20</td>\n", - " <td>2</td>\n", - " <td>0</td>\n", - " <td>0</td>\n", - " <td>0.08</td>\n", - " <td>20</td>\n", - " </tr>\n", - " <tr>\n", - " <th>3</th>\n", - " <td>60</td>\n", - " <td>3</td>\n", - " <td>30</td>\n", - " <td>3</td>\n", - " <td>0</td>\n", - " <td>0</td>\n", - " <td>0.08</td>\n", - " <td>21</td>\n", - " </tr>\n", - " <tr>\n", - " <th>4</th>\n", - " <td>80</td>\n", - " <td>4</td>\n", - " <td>40</td>\n", - " <td>4</td>\n", - " <td>0</td>\n", - " <td>0</td>\n", - " <td>0.08</td>\n", - " <td>22</td>\n", - " </tr>\n", - " <tr>\n", - " <th>5</th>\n", - " <td>100</td>\n", - " <td>5</td>\n", - " <td>50</td>\n", - " <td>5</td>\n", - " <td>0</td>\n", - " <td>0</td>\n", - " <td>0.08</td>\n", - " <td>23</td>\n", - " </tr>\n", - " </tbody>\n", - "</table>\n", - "</div>" - ], - "text/plain": [ - " CumlDistance_km Depth_m Q_cms Vmag_mps Vvert_mps Vlat_mps \\\n", - "CellNumber \n", - "1 20 1 10 1 0 0 \n", - "2 40 2 20 2 0 0 \n", - "3 60 3 30 3 0 0 \n", - "4 80 4 40 4 0 0 \n", - "5 100 5 50 5 0 0 \n", - "\n", - " Ustar_mps Temp_C \n", - "CellNumber \n", - "1 0.08 19 \n", - "2 0.08 20 \n", - "3 0.08 21 \n", - "4 0.08 22 \n", - "5 0.08 23 " - ] - }, - "execution_count": 1, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "import os\n", - "\n", - "import pandas as pd\n", - "\n", - "\n", - "# show the hydraulic data contained in the CSV file\n", - "hydraulic_csv_path = os.path.join('..', 'test', 'data', 'multi-cell input.csv')\n", - "hydraulic_data = pd.read_csv(hydraulic_csv_path, index_col='CellNumber')\n", - "hydraulic_data" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "from fluegg.hydraulics import from_csv\n", - "\n", - "# initialize a hydraulic model as a series of hydraulic cells from the CSV\n", - "hydraulic_model = from_csv(hydraulic_csv_path)" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "from fluegg.asiancarpeggs import BigheadCarpEggs\n", - "from fluegg.simclock import SimulationClock\n", - "\n", - "# total_simulation_time = BigheadCarpEggs.hatching_time(hydraulic_data['Temp_C'].mean())\n", - "total_simulation_time = 1000 # seconds\n", - "time_step_size = 1 # seconds\n", - "\n", - "simulation_clock = SimulationClock(time_step_size, total_simulation_time)" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [], - "source": [ - "import numpy as np\n", - "\n", - "\n", - "first_cell_x_midpoint = 1000*hydraulic_data.loc[1, 'CumlDistance_km']/2\n", - "\n", - "depth = hydraulic_data.loc[1, 'Depth_m']\n", - "first_cell_z_midpoint = -depth/2\n", - "\n", - "area = hydraulic_data.loc[1, 'Q_cms']/hydraulic_data.loc[1, 'Vmag_mps']\n", - "width = area/depth\n", - "first_cell_y_midpoint = width/2\n", - "\n", - "initial_position = np.array([10, first_cell_y_midpoint, first_cell_z_midpoint])\n", - "\n", - "number_of_eggs = 10\n", - "initial_position = np.tile(initial_position, (number_of_eggs, 1))\n", - "\n", - "carp_eggs = BigheadCarpEggs(initial_position, simulation_clock)" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [], - "source": [ - "from fluegg.transporter import ParabolicConstantVerticalTransporter\n", - "\n", - "transport_model = ParabolicConstantVerticalTransporter(simulation_clock, carp_eggs)\n", - "transport_model.set_hydraulic_model(hydraulic_model)" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [], - "source": [ - "from fluegg.simulation import Simulation\n", - "\n", - "fluegg_simulation = Simulation(carp_eggs, transport_model, simulation_clock)\n", - "fluegg_simulation.set_hydraulic_model(hydraulic_model)\n", - "\n", - "simulation_results = fluegg_simulation.run()" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "<Figure size 720x576 with 3 Axes>" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "%matplotlib inline\n", - "import matplotlib.pyplot as plt\n", - "\n", - "positions = simulation_results.results()\n", - "\n", - "time = simulation_clock.time_array()\n", - "\n", - "x = positions[:, :, 0]\n", - "y = positions[:, :, 1]\n", - "z = positions[:, :, 2]\n", - "\n", - "fig = plt.figure(figsize=(10,8))\n", - "\n", - "x_position_axes = fig.add_subplot(311)\n", - "_ = x_position_axes.plot(time, x, '.')\n", - "_ = x_position_axes.set_ylabel('x')\n", - "\n", - "y_position_axes = fig.add_subplot(312, sharex=x_position_axes)\n", - "_ = y_position_axes.plot(time, y, '.')\n", - "_ = y_position_axes.set_ylabel('y')\n", - "\n", - "z_position_axes = fig.add_subplot(313, sharex=x_position_axes)\n", - "_ = z_position_axes.plot(time, z, '.')\n", - "_ = z_position_axes.set_ylabel('z')\n", - "_ = z_position_axes.set_xlabel('time')" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": { - "scrolled": false - }, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "<Figure size 720x576 with 3 Axes>" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fig = plt.figure(figsize=(10,8))\n", - "\n", - "xy_axes = fig.add_subplot(221)\n", - "_ = xy_axes.plot(x, y, '.')\n", - "_ = xy_axes.set_ylabel('y')\n", - "\n", - "xz_axes = fig.add_subplot(223, sharex=xy_axes)\n", - "_ = xz_axes.plot(x, z, '.')\n", - "_ = xz_axes.set_ylabel('z')\n", - "_ = xz_axes.set_xlabel('x')\n", - "\n", - "zy_axes = fig.add_subplot(222, sharey=xy_axes)\n", - "_ = zy_axes.plot(z, y, '.')\n", - "_ = zy_axes.set_xlabel('z')" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.6.6" - } - }, - "nbformat": 4, - 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Information - 1 Initial Profile - 3.1E+38 1 -Flow and Seasonal Roughness Flag (plan) - F F - 2 0 0 - 3 01.14E-04 - 1 1 0 0 - 0 0 - F -Project Title, Plan Title and Plan ShortID -HEC-RAS Flume Case -Flume Unsteady Example -Unsteady -Job Control Information - Computation Interval = 1MIN - Warmup Interval = 0 - Instantaneous Profile = 1HOUR - Hydrograph Interval = 1HOUR - Theta Simulation = 1 - Theta Warmup = 1 - Friction Slope Method = 2 - Maximum Iterations = 20 - Max Iter WOImprovement= 0 - Number Warmup Steps = 0 - Abort DZ Tolerance = 30 - DZ Tolerance = .006 - DZSA Tolerance = .006 - DQ Tolerance = 3.1E+38 - Weir Flow Stability = 2 - Spillway Stability = 1 - Write Restart File = F F - Echo Input TS = F - Echo Parameters = F - Echo Output TS = F - DSS Message Level = 4 - Write HDF5 File = T - Write DSS File = T -D:\py\FluEgg\test\data\ras\HEC-RAS Flume\HEC-RASFlumeCase.dss -Computational Time Window - Start Date/Time = 31Dec2016 2400 - End Date/Time = 03Jan2017 1100 -Initial 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b/test/data/ras/unsteadyflume/HEC-RASFlumeCase.f02 deleted file mode 100644 index fb7f220..0000000 --- a/test/data/ras/unsteadyflume/HEC-RASFlumeCase.f02 +++ /dev/null @@ -1,22 +0,0 @@ -Flow Title=BaseCase02Data -Program Version=5.03 -Number of Profiles= 2 -Profile Names=PF 1,PF 2 -River Rch & RM=Flume,1 ,10000 - .1296 .1296 -Boundary for River Rch & Prof#=Flume,1 , 1 -Up Type= 0 -Dn Type= 3 -Dn Slope=6.84117E-05 -Boundary for River Rch & Prof#=Flume,1 , 2 -Up Type= 0 -Dn Type= 3 -Dn Slope=6.84117E-05 -DSS Import StartDate= -DSS Import StartTime= -DSS Import EndDate= -DSS Import EndTime= -DSS Import GetInterval= 0 -DSS Import Interval= -DSS Import GetPeak= 0 -DSS Import FillOption= 0 diff --git a/test/data/ras/unsteadyflume/HEC-RASFlumeCase.f03 b/test/data/ras/unsteadyflume/HEC-RASFlumeCase.f03 deleted file mode 100644 index bd9970f..0000000 --- a/test/data/ras/unsteadyflume/HEC-RASFlumeCase.f03 +++ /dev/null @@ -1,22 +0,0 @@ -Flow Title=BaseCase03Data -Program Version=5.03 -Number of Profiles= 2 -Profile Names=PF 1,PF 2 -River Rch & RM=Flume,1 ,10000 - .108 .108 -Boundary for River Rch & Prof#=Flume,1 , 1 -Up Type= 0 -Dn Type= 3 -Dn Slope=4.89227E-05 -Boundary for River Rch & Prof#=Flume,1 , 2 -Up Type= 0 -Dn Type= 3 -Dn Slope=4.89227E-05 -DSS Import StartDate= -DSS Import StartTime= -DSS Import EndDate= -DSS Import EndTime= -DSS Import GetInterval= 0 -DSS Import Interval= -DSS Import GetPeak= 0 -DSS Import FillOption= 0 diff --git a/test/data/ras/unsteadyflume/HEC-RASFlumeCase.f04 b/test/data/ras/unsteadyflume/HEC-RASFlumeCase.f04 deleted file mode 100644 index c599515..0000000 --- a/test/data/ras/unsteadyflume/HEC-RASFlumeCase.f04 +++ /dev/null @@ -1,22 +0,0 @@ -Flow Title=BaseCase04Data -Program Version=5.03 -Number of Profiles= 2 -Profile Names=PF 1,PF 2 -River Rch & RM=Flume,1 ,10000 - .0864 .0864 -Boundary for River Rch & Prof#=Flume,1 , 1 -Up Type= 0 -Dn Type= 3 -Dn Slope=3.23062E-05 -Boundary for River Rch & Prof#=Flume,1 , 2 -Up Type= 0 -Dn Type= 3 -Dn 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0.006 -Split Flow Ratio= 0.02 -Log Output Level= 0 -Friction Slope Method= 1 -Unsteady Friction Slope Method= 2 -Unsteady Bridges Friction Slope Method= 1 -Parabolic Critical Depth -Global Vel Dist= 0 , 0 , 0 -Global Log Level= 0 -CheckData=True -Encroach Param=-1 ,0,0, 0 -Computation Interval=1MIN -Output Interval=1HOUR -Instantaneous Interval=1HOUR -Mapping Interval=1HOUR -Run HTab= 0 -Run UNet= 0 -Run Sediment= 0 -Run PostProcess= 0 -Run WQNet= 0 -Run RASMapper= 0 -UNET Theta= 1 -UNET Theta Warmup= 1 -UNET ZTol= 0.006 -UNET ZSATol= 0.006 -UNET QTol= -UNET MxIter= 20 -UNET Max Iter WO Improvement= 0 -UNET MaxInSteps= 0 -UNET DtIC= 0 -UNET DtMin= 0 -UNET MaxCRTS= 20 -UNET WFStab= 2 -UNET SFStab= 1 -UNET WFX= 1 -UNET SFX= 1 -UNET DSS MLevel= 4 -UNET Pardiso=0 -UNET DZMax Abort= 30 -UNET Use Existing IB Tables=-1 -UNET Froude Reduction=False -UNET Froude Limit= 0.8 -UNET Froude Power= 4 -UNET Time Slicing=0,0, 5 -UNET D1 Cores= 0 -UNET D2 Coriolis=0 -UNET D2 Cores= 0 -UNET D2 Theta= 1 -UNET D2 Theta Warmup= 1 -UNET D2 Z Tol= 0.003 -UNET D2 Volume Tol= 0.003 -UNET D2 Max Iterations= 20 -UNET D2 Equation= 0 -UNET D2 TotalICTime= -UNET D2 RampUpFraction=0.1 -UNET D2 TimeSlices= 1 -UNET D2 Eddy Viscosity= -UNET D2 BCVolumeCheck=0 -UNET D2 Latitude= -UNET D1D2 MaxIter= 0 -UNET D1D2 ZTol=0.003 -UNET D1D2 QTol=0.1 -UNET D1D2 MinQTol=0.03 -DSS File=dss -Write IC File= 0 -Write IC File at Fixed DateTime=0 -IC Time=,, -Write IC File Reoccurance= -Write IC File at Sim End=0 -Echo Input=False -Echo Parameters=False -Echo Output=False -Write Detailed= 0 -HDF Write Warmup=0 -HDF Write Time Slices=0 -HDF Flush=0 -HDF Face Node Velocities=0 -HDF Compression= 1 -HDF Chunk Size= 1 -HDF Spatial Parts= 1 -HDF Use Max Rows=0 -HDF Fixed Rows= 1 -Calibration Method= 0 -Calibration Iterations= 20 -Calibration Max Change=0.05 -Calibration Tolerance=0.2 -Calibration Maximum=1.5 -Calibration Minimum=0.5 -Calibration Optimization Method= 1 -Calibration Window=,,, -WQ AD Non Conservative -WQ ULTIMATE=-1 -WQ Max Comp Step=1HOUR -WQ Output Interval=15MIN -WQ Output Selected Increments= 0 -WQ Output face flow=0 -WQ Output face velocity=0 -WQ Output face area=0 -WQ Output face dispersion=0 -WQ Output cell volume=0 -WQ Output cell surface area=0 -WQ Output cell continuity=0 -WQ Output cumulative cell continuity=0 -WQ Output face conc=0 -WQ Output face dconc_dx=0 -WQ Output face courant=0 -WQ Output face peclet=0 -WQ Output face adv mass=0 -WQ Output face disp mass=0 -WQ Output cell mass=0 -WQ Output cell source sink temp=0 -WQ Output nsm pathways=0 -WQ Output nsm derived pathways=0 -WQ Output MaxMinRange=-1 -WQ Daily Max Min Mean=-1 -WQ Daily Range=0 -WQ Daily Time=0 -WQ Create Restart=0 -WQ Fixed Restart=0 -WQ Restart Simtime= -WQ Restart Date= -WQ Restart Hour= -WQ System Summary=0 -WQ Write To DSS=0 -WQ Use Fixed Temperature=0 -WQ Fixed Temperature= -Sorting and Armoring Iterations= 10 -XS Update Threshold= 0.02 -Bed Roughness Predictor= 0 -Hydraulics Update Threshold= 0.02 -Energy Slope Method= 1 -Volume Change Method= 1 -Sediment Retention Method= 0 -XS Weighting Method= 0 -Number of US Weighted Cross Sections= 1 -Number of DS Weighted Cross Sections= 1 -Upstream XS Weight=0 -Main XS Weight=1 -Downstream XS Weight=0 -Number of DS XS's Weighted with US Boundary= 1 -Upstream Boundary Weight= 1 -Weight of XSs Associated with US Boundary= 0 -Number of US XS's Weighted with DS Boundary= 1 -Downstream Boundary Weight= 0.5 -Weight of XSs Associated with DS Boundary= 0.5 -Percentile Method= 0 -Sediment Output Level= 4 -Mass or Volume Output= 0 -Output Increment Type= 1 -Profile and TS Output Increment= 1 -XS Output Flag= 0 -XS Output Increment= 10 -Write Gradation File= 0 -Read Gradation Hotstart= 0 -Gradation File Name= -Write HDF5 File= 1 -Write DSS Sediment File= 0 -SV Curve= 0 -Specific Gage Flag= 0 diff --git a/test/data/ras/unsteadyflume/HEC-RASFlumeCase.p01.hdf b/test/data/ras/unsteadyflume/HEC-RASFlumeCase.p01.hdf deleted file mode 100644 index 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-Critical Tol= 0.003 -Num of Std Step Trials= 20 -Max Error Tol= 0.1 -Flow Tol Ratio= 0.001 -Split Flow NTrial= 30 -Split Flow Tol= 0.006 -Split Flow Ratio= 0.02 -Log Output Level= 0 -Friction Slope Method= 1 -Unsteady Friction Slope Method= 2 -Unsteady Bridges Friction Slope Method= 1 -Parabolic Critical Depth -Global Vel Dist= 0 , 0 , 0 -Global Log Level= 0 -CheckData=True -Encroach Param=-1 ,0,0, 0 -Computation Interval=1MIN -Output Interval=1HOUR -Instantaneous Interval=1HOUR -Mapping Interval=1HOUR -Run HTab= 0 -Run UNet= 0 -Run Sediment= 0 -Run PostProcess= 0 -Run WQNet= 0 -Run RASMapper= 0 -UNET Theta= 1 -UNET Theta Warmup= 1 -UNET ZTol= 0.006 -UNET ZSATol= 0.006 -UNET QTol= -UNET MxIter= 20 -UNET Max Iter WO Improvement= 0 -UNET MaxInSteps= 0 -UNET DtIC= 0 -UNET DtMin= 0 -UNET MaxCRTS= 20 -UNET WFStab= 2 -UNET SFStab= 1 -UNET WFX= 1 -UNET SFX= 1 -UNET DSS MLevel= 4 -UNET Pardiso=0 -UNET DZMax Abort= 30 -UNET Use Existing IB Tables=-1 -UNET Froude Reduction=False -UNET Froude Limit= 0.8 -UNET Froude Power= 4 -UNET Time Slicing=0,0, 5 -UNET D1 Cores= 0 -UNET D2 Coriolis=0 -UNET D2 Cores= 0 -UNET D2 Theta= 1 -UNET D2 Theta Warmup= 1 -UNET D2 Z Tol= 0.003 -UNET D2 Volume Tol= 0.003 -UNET D2 Max Iterations= 20 -UNET D2 Equation= 0 -UNET D2 TotalICTime= -UNET D2 RampUpFraction=0.1 -UNET D2 TimeSlices= 1 -UNET D2 Eddy Viscosity= -UNET D2 BCVolumeCheck=0 -UNET D2 Latitude= -UNET D1D2 MaxIter= 0 -UNET D1D2 ZTol=0.003 -UNET D1D2 QTol=0.1 -UNET D1D2 MinQTol=0.03 -Write IC File= 0 -Write IC File at Fixed DateTime=0 -IC Time=,, -Write IC File Reoccurance= -Write IC File at Sim End=0 -Echo Input=False -Echo Parameters=False -Echo Output=False -Write Detailed= 0 -HDF Write Warmup=0 -HDF Write Time Slices=0 -HDF Flush=0 -HDF Face Node Velocities=0 -HDF Compression= 1 -HDF Chunk Size= 1 -HDF Spatial Parts= 1 -HDF Use Max Rows=0 -HDF Fixed Rows= 1 -Calibration Method= 0 -Calibration Iterations= 20 -Calibration Max Change=0.05 -Calibration Tolerance=0.2 -Calibration Maximum=1.5 -Calibration Minimum=0.5 -Calibration Optimization Method= 1 -Calibration Window=,,, -WQ AD Non Conservative -WQ ULTIMATE=-1 -WQ Max Comp Step=1HOUR -WQ Output Interval=15MIN -WQ Output Selected Increments= 0 -WQ Output face flow=0 -WQ Output face velocity=0 -WQ Output face area=0 -WQ Output face dispersion=0 -WQ Output cell volume=0 -WQ Output cell surface area=0 -WQ Output cell continuity=0 -WQ Output cumulative cell continuity=0 -WQ Output face conc=0 -WQ Output face dconc_dx=0 -WQ Output face courant=0 -WQ Output face peclet=0 -WQ Output face adv mass=0 -WQ Output face disp mass=0 -WQ Output cell mass=0 -WQ Output cell source sink temp=0 -WQ Output nsm pathways=0 -WQ Output nsm derived pathways=0 -WQ Output MaxMinRange=-1 -WQ Daily Max Min Mean=-1 -WQ Daily Range=0 -WQ Daily Time=0 -WQ Create Restart=0 -WQ Fixed Restart=0 -WQ Restart Simtime= -WQ Restart Date= -WQ Restart Hour= -WQ System Summary=0 -WQ Write To DSS=0 -WQ Use Fixed Temperature=0 -WQ Fixed Temperature= -Sorting and Armoring Iterations= 10 -XS Update Threshold= 0.02 -Bed Roughness Predictor= 0 -Hydraulics Update Threshold= 0.02 -Energy Slope Method= 1 -Volume Change Method= 1 -Sediment Retention Method= 0 -XS Weighting Method= 0 -Number of US Weighted Cross Sections= 1 -Number of DS Weighted Cross Sections= 1 -Upstream XS Weight=0 -Main XS Weight=1 -Downstream XS Weight=0 -Number of DS XS's Weighted with US Boundary= 1 -Upstream Boundary Weight= 1 -Weight of XSs Associated with US Boundary= 0 -Number of US XS's Weighted with DS Boundary= 1 -Downstream Boundary Weight= 0.5 -Weight of XSs Associated with DS Boundary= 0.5 -Percentile Method= 0 -Sediment Output Level= 4 -Mass or Volume Output= 0 -Output Increment Type= 1 -Profile and TS Output Increment= 1 -XS Output Flag= 0 -XS Output Increment= 10 -Write Gradation File= 0 -Read Gradation Hotstart= 0 -Gradation File Name= -Write HDF5 File= 1 -Write DSS Sediment File= 0 -SV Curve= 0 -Specific Gage Flag= 0 diff --git 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b/test/data/ras/unsteadyflume/HEC-RASFlumeCase.p03 deleted file mode 100644 index 14b6682..0000000 --- a/test/data/ras/unsteadyflume/HEC-RASFlumeCase.p03 +++ /dev/null @@ -1,172 +0,0 @@ -Plan Title=Flume Base Case 03 -Program Version=5.03 -Short Identifier=BaseCase03 -Simulation Date=,,, -Geom File=g01 -Flow File=f03 -Subcritical Flow -K Sum by GR= 0 -Std Step Tol= 0.003 -Critical Tol= 0.003 -Num of Std Step Trials= 20 -Max Error Tol= 0.1 -Flow Tol Ratio= 0.001 -Split Flow NTrial= 30 -Split Flow Tol= 0.006 -Split Flow Ratio= 0.02 -Log Output Level= 0 -Friction Slope Method= 1 -Unsteady Friction Slope Method= 2 -Unsteady Bridges Friction Slope Method= 1 -Parabolic Critical Depth -Global Vel Dist= 0 , 0 , 0 -Global Log Level= 0 -CheckData=True -Encroach Param=-1 ,0,0, 0 -Computation Interval=1MIN -Output Interval=1HOUR -Instantaneous Interval=1HOUR -Mapping Interval=1HOUR -Run HTab= 0 -Run UNet= 0 -Run Sediment= 0 -Run PostProcess= 0 -Run WQNet= 0 -Run RASMapper= 0 -UNET Theta= 1 -UNET Theta Warmup= 1 -UNET ZTol= 0.006 -UNET ZSATol= 0.006 -UNET QTol= -UNET MxIter= 20 -UNET Max Iter WO Improvement= 0 -UNET MaxInSteps= 0 -UNET DtIC= 0 -UNET DtMin= 0 -UNET MaxCRTS= 20 -UNET WFStab= 2 -UNET SFStab= 1 -UNET WFX= 1 -UNET SFX= 1 -UNET DSS MLevel= 4 -UNET Pardiso=0 -UNET DZMax Abort= 30 -UNET Use Existing IB Tables=-1 -UNET Froude Reduction=False -UNET Froude Limit= 0.8 -UNET Froude Power= 4 -UNET Time Slicing=0,0, 5 -UNET D1 Cores= 0 -UNET D2 Coriolis=0 -UNET D2 Cores= 0 -UNET D2 Theta= 1 -UNET D2 Theta Warmup= 1 -UNET D2 Z Tol= 0.003 -UNET D2 Volume Tol= 0.003 -UNET D2 Max Iterations= 20 -UNET D2 Equation= 0 -UNET D2 TotalICTime= -UNET D2 RampUpFraction=0.1 -UNET D2 TimeSlices= 1 -UNET D2 Eddy Viscosity= -UNET D2 BCVolumeCheck=0 -UNET D2 Latitude= -UNET D1D2 MaxIter= 0 -UNET D1D2 ZTol=0.003 -UNET D1D2 QTol=0.1 -UNET D1D2 MinQTol=0.03 -Write IC File= 0 -Write IC File at Fixed DateTime=0 -IC Time=,, -Write IC File Reoccurance= -Write IC File at Sim End=0 -Echo Input=False -Echo Parameters=False -Echo Output=False -Write Detailed= 0 -HDF Write Warmup=0 -HDF Write Time Slices=0 -HDF Flush=0 -HDF Face Node Velocities=0 -HDF Compression= 1 -HDF Chunk Size= 1 -HDF Spatial Parts= 1 -HDF Use Max Rows=0 -HDF Fixed Rows= 1 -Calibration Method= 0 -Calibration Iterations= 20 -Calibration Max Change=0.05 -Calibration Tolerance=0.2 -Calibration Maximum=1.5 -Calibration Minimum=0.5 -Calibration Optimization Method= 1 -Calibration Window=,,, -WQ AD Non Conservative -WQ ULTIMATE=-1 -WQ Max Comp Step=1HOUR -WQ Output Interval=15MIN -WQ Output Selected Increments= 0 -WQ Output face flow=0 -WQ Output face velocity=0 -WQ Output face area=0 -WQ Output face dispersion=0 -WQ Output cell volume=0 -WQ Output cell surface area=0 -WQ Output cell continuity=0 -WQ Output cumulative cell continuity=0 -WQ Output face conc=0 -WQ Output face dconc_dx=0 -WQ Output face courant=0 -WQ Output face peclet=0 -WQ Output face adv mass=0 -WQ Output face disp mass=0 -WQ Output cell mass=0 -WQ Output cell source sink temp=0 -WQ Output nsm pathways=0 -WQ Output nsm derived pathways=0 -WQ Output MaxMinRange=-1 -WQ Daily Max Min Mean=-1 -WQ Daily Range=0 -WQ Daily Time=0 -WQ Create Restart=0 -WQ Fixed Restart=0 -WQ Restart Simtime= -WQ Restart Date= -WQ Restart Hour= -WQ System Summary=0 -WQ Write To DSS=0 -WQ Use Fixed Temperature=0 -WQ Fixed Temperature= -Sorting and Armoring Iterations= 10 -XS Update Threshold= 0.02 -Bed Roughness Predictor= 0 -Hydraulics Update Threshold= 0.02 -Energy Slope Method= 1 -Volume Change Method= 1 -Sediment Retention Method= 0 -XS Weighting Method= 0 -Number of US Weighted Cross Sections= 1 -Number of DS Weighted Cross Sections= 1 -Upstream XS Weight=0 -Main XS Weight=1 -Downstream XS Weight=0 -Number of DS XS's Weighted with US Boundary= 1 -Upstream Boundary Weight= 1 -Weight of XSs Associated with US Boundary= 0 -Number of US XS's Weighted with DS Boundary= 1 -Downstream Boundary Weight= 0.5 -Weight of XSs Associated with DS Boundary= 0.5 -Percentile Method= 0 -Sediment Output Level= 4 -Mass or Volume Output= 0 -Output Increment Type= 1 -Profile and TS Output Increment= 1 -XS Output Flag= 0 -XS Output Increment= 10 -Write Gradation File= 0 -Read Gradation Hotstart= 0 -Gradation File Name= -Write HDF5 File= 1 -Write DSS Sediment File= 0 -SV Curve= 0 -Specific Gage Flag= 0 diff --git a/test/data/ras/unsteadyflume/HEC-RASFlumeCase.p03.hdf b/test/data/ras/unsteadyflume/HEC-RASFlumeCase.p03.hdf deleted file mode 100644 index b0a7f93a7a33e6055807dbf47fd6e55c164e5c41..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 180952 zcmeI52|!fE|G;Ot#6(?>l+^O&QJ7|nSdnIe2!bbp2cEIQ!mcj6xVz|*N0h((k!4wS z*r{p#qMse~vpiEt{iXfPBI}=;7nUiNn%SXw{%79IcaO(DRuB*H`;?tG^S(20<}>r= zeP`Yrk0tg^Xn0+#>j*nSLrD<P%BS#iUK~5t2gpufhwJI$L?g^XVHR<5q9MWbkC1TT zt`*@MS8*R@!hL8;d_19&5I&gVGLcqt`556~wDOa3VK04&pCpQi7&mZxp|Br2E(Arq zgbj^aLLf0dHkm~=O~f}*n41;(+0S6jF*t1b;xb7#>n&1Wy+bb?;wKv{4k^xR$uv1k 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Interval=1HOUR -Mapping Interval=1HOUR -Run HTab= 0 -Run UNet= 0 -Run Sediment= 0 -Run PostProcess= 0 -Run WQNet= 0 -Run RASMapper= 0 -UNET Theta= 1 -UNET Theta Warmup= 1 -UNET ZTol= 0.006 -UNET ZSATol= 0.006 -UNET QTol= -UNET MxIter= 20 -UNET Max Iter WO Improvement= 0 -UNET MaxInSteps= 0 -UNET DtIC= 0 -UNET DtMin= 0 -UNET MaxCRTS= 20 -UNET WFStab= 2 -UNET SFStab= 1 -UNET WFX= 1 -UNET SFX= 1 -UNET DSS MLevel= 4 -UNET Pardiso=0 -UNET DZMax Abort= 30 -UNET Use Existing IB Tables=-1 -UNET Froude Reduction=False -UNET Froude Limit= 0.8 -UNET Froude Power= 4 -UNET Time Slicing=0,0, 5 -UNET D1 Cores= 0 -UNET D2 Coriolis=0 -UNET D2 Cores= 0 -UNET D2 Theta= 1 -UNET D2 Theta Warmup= 1 -UNET D2 Z Tol= 0.003 -UNET D2 Volume Tol= 0.003 -UNET D2 Max Iterations= 20 -UNET D2 Equation= 0 -UNET D2 TotalICTime= -UNET D2 RampUpFraction=0.1 -UNET D2 TimeSlices= 1 -UNET D2 Eddy Viscosity= -UNET D2 BCVolumeCheck=0 -UNET D2 Latitude= -UNET D1D2 MaxIter= 0 -UNET D1D2 ZTol=0.003 -UNET D1D2 QTol=0.1 -UNET D1D2 MinQTol=0.03 -Write IC File= 0 -Write IC File at Fixed DateTime=0 -IC Time=,, -Write IC File Reoccurance= -Write IC File at Sim End=0 -Echo Input=False -Echo Parameters=False -Echo Output=False -Write Detailed= 0 -HDF Write Warmup=0 -HDF Write Time Slices=0 -HDF Flush=0 -HDF Face Node Velocities=0 -HDF Compression= 1 -HDF Chunk Size= 1 -HDF Spatial Parts= 1 -HDF Use Max Rows=0 -HDF Fixed Rows= 1 -Calibration Method= 0 -Calibration Iterations= 20 -Calibration Max Change=0.05 -Calibration Tolerance=0.2 -Calibration Maximum=1.5 -Calibration Minimum=0.5 -Calibration Optimization Method= 1 -Calibration Window=,,, -WQ AD Non Conservative -WQ ULTIMATE=-1 -WQ Max Comp Step=1HOUR -WQ Output Interval=15MIN -WQ Output Selected Increments= 0 -WQ Output face flow=0 -WQ Output face velocity=0 -WQ Output face area=0 -WQ Output face dispersion=0 -WQ Output cell volume=0 -WQ Output cell surface area=0 -WQ Output cell continuity=0 -WQ Output cumulative cell continuity=0 -WQ Output face conc=0 -WQ Output face dconc_dx=0 -WQ Output face courant=0 -WQ Output face peclet=0 -WQ Output face adv mass=0 -WQ Output face disp mass=0 -WQ Output cell mass=0 -WQ Output cell source sink temp=0 -WQ Output nsm pathways=0 -WQ Output nsm derived pathways=0 -WQ Output MaxMinRange=-1 -WQ Daily Max Min Mean=-1 -WQ Daily Range=0 -WQ Daily Time=0 -WQ Create Restart=0 -WQ Fixed Restart=0 -WQ Restart Simtime= -WQ Restart Date= -WQ Restart Hour= -WQ System Summary=0 -WQ Write To DSS=0 -WQ Use Fixed Temperature=0 -WQ Fixed Temperature= -Sorting and Armoring Iterations= 10 -XS Update Threshold= 0.02 -Bed Roughness Predictor= 0 -Hydraulics Update Threshold= 0.02 -Energy Slope Method= 1 -Volume Change Method= 1 -Sediment Retention Method= 0 -XS Weighting Method= 0 -Number of US Weighted Cross Sections= 1 -Number of DS Weighted Cross Sections= 1 -Upstream XS Weight=0 -Main XS Weight=1 -Downstream XS Weight=0 -Number of DS XS's Weighted with US Boundary= 1 -Upstream Boundary Weight= 1 -Weight of XSs Associated with 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b/test/data/ras/unsteadyflume/HEC-RASFlumeCase.p05 deleted file mode 100644 index b5f1dfe..0000000 --- a/test/data/ras/unsteadyflume/HEC-RASFlumeCase.p05 +++ /dev/null @@ -1,183 +0,0 @@ -Plan Title=Flume Unsteady Example -Program Version=5.05 -Short Identifier=Unsteady -Simulation Date=01JAN2017,0000,03JAN2017,1100 -Geom File=g05 -Flow File=u01 -Subcritical Flow -K Sum by GR= 0 -Std Step Tol= 0.003 -Critical Tol= 0.003 -Num of Std Step Trials= 20 -Max Error Tol= 0.1 -Flow Tol Ratio= 0.001 -Split Flow NTrial= 30 -Split Flow Tol= 0.006 -Split Flow Ratio= 0.02 -Log Output Level= 0 -Friction Slope Method= 1 -Unsteady Friction Slope Method= 2 -Unsteady Bridges Friction Slope Method= 1 -Parabolic Critical Depth -Global Vel Dist= 0 , 0 , 0 -Global Log Level= 0 -CheckData=True -Encroach Param=-1 ,0,0, 0 -Computation Interval=1MIN -Output Interval=1HOUR -Instantaneous Interval=1HOUR -Mapping Interval=1HOUR -Computation Time Step Use Courant= 0 -Computation Time Step Use Time Series= 0 -Computation Time Step Max Courant= -Computation Time Step Min Courant= -Computation Time Step Count To Double=0 -Computation Time Step Max Doubling=0 -Computation Time Step Max Halving=0 -Computation Time Step Residence Courant=0 -Run HTab= 1 -Run UNet= 1 -Run Sediment= 0 -Run PostProcess= 1 -Run WQNet= 0 -Run RASMapper= 0 -UNET Theta= 1 -UNET Theta Warmup= 1 -UNET ZTol= 0.006 -UNET ZSATol= 0.006 -UNET QTol= -UNET MxIter= 20 -UNET Max Iter WO Improvement= 0 -UNET MaxInSteps= 0 -UNET DtIC= 0 -UNET DtMin= 0 -UNET MaxCRTS= 20 -UNET WFStab= 2 -UNET SFStab= 1 -UNET WFX= 1 -UNET SFX= 1 -UNET 1D Methodology=Finite Difference -UNET DSS MLevel= 4 -UNET Pardiso=0 -UNET DZMax Abort= 30 -UNET Use Existing IB Tables=-1 -UNET Froude Reduction=False -UNET Froude Limit= 0.8 -UNET Froude Power= 4 -UNET D1 Cores= 0 -UNET D2 Coriolis=0 -UNET D2 Cores= 0 -UNET D2 Theta= 1 -UNET D2 Theta Warmup= 1 -UNET D2 Z Tol= 0.003 -UNET D2 Volume Tol= 0.003 -UNET D2 Max Iterations= 20 -UNET D2 Equation= 0 -UNET D2 TotalICTime= -UNET D2 RampUpFraction=0.1 -UNET D2 TimeSlices= 1 -UNET D2 Eddy Viscosity= -UNET D2 BCVolumeCheck=0 -UNET D2 Latitude= -UNET D1D2 MaxIter= 0 -UNET D1D2 ZTol=0.003 -UNET D1D2 QTol=0.1 -UNET D1D2 MinQTol=0.03 -DSS File=dss -Write IC File= 0 -Write IC File at Fixed DateTime=0 -IC Time=,, -Write IC File Reoccurance= -Write IC File at Sim End=0 -Echo Input=False -Echo Parameters=False -Echo Output=False -Write Detailed= 0 -Computation Level Output=True -HDF Write Warmup=0 -HDF Write Time Slices=0 -HDF Flush=0 -HDF Face Node Velocities=0 -HDF Compression= 1 -HDF Chunk Size= 1 -HDF Spatial Parts= 1 -HDF Use Max Rows=0 -HDF Fixed Rows= 1 -Calibration Method= 0 -Calibration Iterations= 20 -Calibration Max Change=0.05 -Calibration Tolerance=0.2 -Calibration Maximum=1.5 -Calibration Minimum=0.5 -Calibration Optimization Method= 1 -Calibration Window=,,, -WQ AD Non Conservative -WQ ULTIMATE=-1 -WQ Max Comp Step=1HOUR -WQ Output Interval=15MIN -WQ Output Selected Increments= 0 -WQ Output face flow=0 -WQ Output face velocity=0 -WQ Output face area=0 -WQ Output face dispersion=0 -WQ Output cell volume=0 -WQ Output cell surface area=0 -WQ Output cell continuity=0 -WQ Output cumulative cell continuity=0 -WQ Output face conc=0 -WQ Output face dconc_dx=0 -WQ Output face courant=0 -WQ Output face peclet=0 -WQ Output face adv mass=0 -WQ Output face disp mass=0 -WQ Output cell mass=0 -WQ Output cell source sink temp=0 -WQ Output nsm pathways=0 -WQ Output nsm derived pathways=0 -WQ Output MaxMinRange=-1 -WQ Daily Max Min Mean=-1 -WQ Daily Range=0 -WQ Daily Time=0 -WQ Create Restart=0 -WQ Fixed Restart=0 -WQ Restart Simtime= -WQ Restart Date= -WQ Restart Hour= -WQ System Summary=0 -WQ Write To DSS=0 -WQ Use Fixed Temperature=0 -WQ Fixed Temperature= -Sorting and Armoring Iterations= 10 -XS Update Threshold= 0.02 -Bed Roughness Predictor= 0 -Hydraulics Update Threshold= 0.02 -Energy Slope Method= 1 -Volume Change Method= 1 -Sediment Retention Method= 0 -XS Weighting Method= 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Rating Curves= 0 -DSS Export Rating Curve Sorted= 0 -DSS Export Volume Flow Curves= 0 -DXF Filename= -DXF OffsetX= 0 -DXF OffsetY= 0 -DXF ScaleX= 1 -DXF ScaleY= 10 -GIS Export Profiles= 0 diff --git a/test/data/ras/unsteadyflume/HEC-RASFlumeCase.r01 b/test/data/ras/unsteadyflume/HEC-RASFlumeCase.r01 deleted file mode 100644 index 0e14bbe..0000000 --- a/test/data/ras/unsteadyflume/HEC-RASFlumeCase.r01 +++ /dev/null @@ -1,69 +0,0 @@ -HEC-RAS 5.0.3 September 2016 -Section - Arrays Sizes -Flume Base Case 01 - 1 1 0 9 12 F - 2 1 0 0 - 3 3 0 0 0 0 0 0 - 0 0 0 F F 0 0 0 0 0 0 0 - 0 0 F T 0 0 0 F 0 0 F - 0 - 0 0 - 1 1 0 F T F 0 3 30 F F F 0 - 2 - 0 .01 F .0098 20 .3281 .0098 F 5 T F -Section - Expansion and Contraction Coefficients - .1 .3 1 -Section - Job Control - 1 1 1 F F 1 -Section - Flow Data - 1 0PF 1 -6.102375 1 - 1 0PF 2 -6.102375 1 -Section - Flow and Seasonal Roughness Flag (plan) - F F -Section - Junction Information -Section - Reach Boundaries - T T 1 3 Flume F F - 0 0 - 0 0 - 3 01.14E-04 - 3 01.14E-04 -Section - Encroachment Data -Section - Observed Water Surface Data -Section - Roughness Change Factors -Section - Breach Data -Section - Storage Area Data -Section - Storage Area Connection Data -Section - Pump Station Data -Section - River Reach Data -NODE 11 10000 16404.2 16404.2 16404.2 0 0.107 2.574 - 1 F - 4 - 0 335.131 0 331.85 2.297 331.85 2.297 335.131 -Section - XS Manning's/Roughness Data - 2 F F 0 - 09.79E-03 2.2979.79E-03 - F F 0 2.297 F F - 0 0 F - 0 F -NODE 11 5000 16404.2 16404.2 16404.2 0 1.573 1.576 - 1 F - 4 - 0 333.249 0 329.968 2.297 329.968 2.297 333.249 -Section - XS Manning's/Roughness Data - 2 F F 0 - 09.79E-03 2.2979.79E-03 - F F 0 2.297 F F - 0 0 F - 0 F -NODE 11 0 0 0 0 0 3.039 0.578 - 1 F - 4 - 0 331.365 0 328.084 2.297 328.084 2.297 331.365 -Section - XS Manning's/Roughness Data - 2 F F 0 - 09.79E-03 2.2979.79E-03 - F F 0 2.297 F F - 0 0 F - 0 F diff --git a/test/data/ras/unsteadyflume/HEC-RASFlumeCase.r02 b/test/data/ras/unsteadyflume/HEC-RASFlumeCase.r02 deleted file mode 100644 index 07a8514..0000000 --- a/test/data/ras/unsteadyflume/HEC-RASFlumeCase.r02 +++ /dev/null @@ -1,69 +0,0 @@ -HEC-RAS 5.0.3 September 2016 -Section - Arrays Sizes -BaseCase02 - 1 1 0 9 12 F - 2 1 0 0 - 3 3 0 0 0 0 0 0 - 0 0 0 F F 0 0 0 0 0 0 0 - 0 0 F T 0 0 0 F 0 0 F - 0 - 0 0 - 1 1 0 F T F 0 3 30 F F F 0 - 2 - 0 .01 F .0098 20 .3281 .0098 F 5 T F -Section - Expansion and Contraction Coefficients - .1 .3 1 -Section - Job Control - 1 1 1 F F 1 -Section - Flow Data - 1 0PF 1 -4.576781 1 - 1 0PF 2 -4.576781 1 -Section - Flow and Seasonal Roughness Flag (plan) - F F -Section - Junction Information -Section - Reach Boundaries - T T 1 3 Flume F F - 0 0 - 0 0 - 3 06.84E-05 - 3 06.84E-05 -Section - Encroachment Data -Section - Observed Water Surface Data -Section - Roughness Change Factors -Section - Breach Data -Section - Storage Area Data -Section - Storage Area Connection Data -Section - Pump Station Data -Section - River Reach Data -NODE 11 10000 16404.2 16404.2 16404.2 0 0.107 2.574 - 1 F - 4 - 0 333.609 0 330.328 2.297 330.328 2.297 333.609 -Section - XS Manning's/Roughness Data - 2 F F 0 - 01.00E-02 2.2971.00E-02 - F F 0 2.297 F F - 0 0 F - 0 F -NODE 11 5000.00* 16404.2 16404.2 16404.2 0 1.573 1.576 - 1 F - 4 - 0 332.487 0 329.206 2.297 329.206 2.297 332.487 -Section - XS Manning's/Roughness Data - 2 F F 0 - 01.00E-02 2.2971.00E-02 - F F 0 2.297 F F - 0 0 F - 0 F -NODE 11 0 0 0 0 0 3.039 0.578 - 1 F - 4 - 0 331.365 0 328.084 2.297 328.084 2.297 331.365 -Section - XS Manning's/Roughness Data - 2 F F 0 - 01.00E-02 2.2971.00E-02 - F F 0 2.297 F F - 0 0 F - 0 F diff --git a/test/data/ras/unsteadyflume/HEC-RASFlumeCase.r03 b/test/data/ras/unsteadyflume/HEC-RASFlumeCase.r03 deleted file mode 100644 index 716483f..0000000 --- a/test/data/ras/unsteadyflume/HEC-RASFlumeCase.r03 +++ /dev/null @@ -1,69 +0,0 @@ -HEC-RAS 5.0.3 September 2016 -Section - Arrays Sizes -BaseCase03 - 1 1 0 9 12 F - 2 1 0 0 - 3 3 0 0 0 0 0 0 - 0 0 0 F F 0 0 0 0 0 0 0 - 0 0 F T 0 0 0 F 0 0 F - 0 - 0 0 - 1 1 0 F T F 0 3 30 F F F 0 - 2 - 0 .01 F .0098 20 .3281 .0098 F 5 T F -Section - Expansion and Contraction Coefficients - .1 .3 1 -Section - Job Control - 1 1 1 F F 1 -Section - Flow Data - 1 0PF 1 -3.813984 1 - 1 0PF 2 -3.813984 1 -Section - Flow and Seasonal Roughness Flag (plan) - F F -Section - Junction Information -Section - Reach Boundaries - T T 1 3 Flume F F - 0 0 - 0 0 - 3 04.89E-05 - 3 04.89E-05 -Section - Encroachment Data -Section - Observed Water Surface Data -Section - Roughness Change Factors -Section - Breach Data -Section - Storage Area Data -Section - Storage Area Connection Data -Section - Pump Station Data -Section - River Reach Data -NODE 11 10000 16404.2 16404.2 16404.2 0 0.107 2.574 - 1 F - 4 - 0 332.969 0 329.688 2.297 329.688 2.297 332.969 -Section - XS Manning's/Roughness Data - 2 F F 0 - 01.02E-02 2.2971.02E-02 - F F 0 2.297 F F - 0 0 F - 0 F -NODE 11 5000.00* 16404.2 16404.2 16404.2 0 1.573 1.576 - 1 F - 4 - 0 332.169 0 328.888 2.297 328.888 2.297 332.169 -Section - XS Manning's/Roughness Data - 2 F F 0 - 01.02E-02 2.2971.02E-02 - F F 0 2.297 F F - 0 0 F - 0 F -NODE 11 0 0 0 0 0 3.039 0.578 - 1 F - 4 - 0 331.365 0 328.084 2.297 328.084 2.297 331.365 -Section - XS Manning's/Roughness Data - 2 F F 0 - 01.02E-02 2.2971.02E-02 - F F 0 2.297 F F - 0 0 F - 0 F diff --git a/test/data/ras/unsteadyflume/HEC-RASFlumeCase.r04 b/test/data/ras/unsteadyflume/HEC-RASFlumeCase.r04 deleted file mode 100644 index 252e40a..0000000 --- a/test/data/ras/unsteadyflume/HEC-RASFlumeCase.r04 +++ /dev/null @@ -1,69 +0,0 @@ -HEC-RAS 5.0.3 September 2016 -Section - Arrays Sizes -BaseCase04 - 1 1 0 9 12 F - 2 1 0 0 - 3 3 0 0 0 0 0 0 - 0 0 0 F F 0 0 0 0 0 0 0 - 0 0 F T 0 0 0 F 0 0 F - 0 - 0 0 - 1 1 0 F T F 0 3 30 F F F 0 - 2 - 0 .01 F .0098 20 .3281 .0098 F 5 T F -Section - Expansion and Contraction Coefficients - .1 .3 1 -Section - Job Control - 1 1 1 F F 1 -Section - Flow Data - 1 0PF 1 -3.051187 1 - 1 0PF 2 -3.051187 1 -Section - Flow and Seasonal Roughness Flag (plan) - F F -Section - Junction Information -Section - Reach Boundaries - T T 1 3 Flume F F - 0 0 - 0 0 - 3 03.23E-05 - 3 03.23E-05 -Section - Encroachment Data -Section - Observed Water Surface Data -Section - Roughness Change Factors -Section - Breach Data -Section - Storage Area Data -Section - Storage Area Connection Data -Section - Pump Station Data -Section - River Reach Data -NODE 11 10000 16404.2 16404.2 16404.2 0 0.107 2.574 - 1 F - 4 - 0 332.425 0 329.144 2.297 329.144 2.297 332.425 -Section - XS Manning's/Roughness Data - 2 F F 0 - 01.03E-02 2.2971.03E-02 - F F 0 2.297 F F - 0 0 F - 0 F -NODE 11 5000.00* 16404.2 16404.2 16404.2 0 1.573 1.576 - 1 F - 4 - 0 331.895 0 328.614 2.297 328.614 2.297 331.895 -Section - XS Manning's/Roughness Data - 2 F F 0 - 01.03E-02 2.2971.03E-02 - F F 0 2.297 F F - 0 0 F - 0 F -NODE 11 0 0 0 0 0 3.039 0.578 - 1 F - 4 - 0 331.365 0 328.084 2.297 328.084 2.297 331.365 -Section - XS Manning's/Roughness Data - 2 F F 0 - 01.03E-02 2.2971.03E-02 - F F 0 2.297 F F - 0 0 F - 0 F diff --git a/test/data/ras/unsteadyflume/HEC-RASFlumeCase.r05 b/test/data/ras/unsteadyflume/HEC-RASFlumeCase.r05 deleted file mode 100644 index 5b9849d..0000000 --- a/test/data/ras/unsteadyflume/HEC-RASFlumeCase.r05 +++ /dev/null @@ -1,349 +0,0 @@ -HEC-RAS 5.0.5 June 2018 -Section - Arrays Sizes -Unsteady - 1 1 0 9 12 F - 61 3 0 3 - 3 3 0 0 0 0 0 0 - 0 0 0 F F 0 0 0 0 0 0 0 - 0 0 T F 0 0 0 F 0 0 F - 0 - 0 0 - 1 1 0 F T F 0 3 30 F F F 0 - 61 - 0 .01 F .003 20 .1 .003 F 5 T F -Section - Expansion and Contraction Coefficients - .1 .3 1 -Section - Job Control - 1 1 1 F F 1 -Section - Flow Data - 3 0Max WS - .5 1.4477215 2 .403181 3 - 3 001JAN2017 0000 - .05 1 .05 2 .05 3 - 3 001JAN2017 0100 - .05 15.00E-02 25.00E-02 3 - 3 001JAN2017 0200 - .05 15.00E-02 25.00E-02 3 - 3 001JAN2017 0300 - .1 11.63E-02 28.64E-02 3 - 3 001JAN2017 0400 - .1 12.09E-02 27.42E-02 3 - 3 001JAN2017 0500 - .1 12.58E-02 2.0642757 3 - 3 001JAN2017 0600 - .15 17.37E-03 28.77E-02 3 - 3 001JAN2017 0700 - .15 11.30E-02 27.04E-02 3 - 3 001JAN2017 0800 - .15 11.99E-02 25.64E-02 3 - 3 001JAN2017 0900 - .2 17.34E-03 27.28E-02 3 - 3 001JAN2017 1000 - .2 11.52E-02 25.42E-02 3 - 3 001JAN2017 1100 - .2 12.51E-02 23.97E-02 3 - 3 001JAN2017 1200 - .25 11.35E-02 2.0521406 3 - 3 001JAN2017 1300 - .25 12.63E-02 23.56E-02 3 - 3 001JAN2017 1400 - .25 14.01E-02 22.64E-02 3 - 3 001JAN2017 1500 - .3 12.90E-02 23.39E-02 3 - 3 001JAN2017 1600 - .3 14.67E-02 22.30E-02 3 - 3 001JAN2017 1700 - .3 1.0644845 21.47E-02 3 - 3 001JAN2017 1800 - .35 15.42E-02 22.24E-02 3 - 3 001JAN2017 1900 - .35 17.64E-02 21.27E-02 3 - 3 001JAN2017 2000 - .35 19.74E-02 26.29E-03 3 - 3 001JAN2017 2100 - .4 18.81E-02 21.46E-02 3 - 3 001JAN2017 2200 - .4 1.1135756 26.90E-03 3 - 3 001JAN2017 2300 - .4 1.1371284 22.56E-03 3 - 3 002JAN2017 0000 - .45 1.1285696 21.18E-02 3 - 3 002JAN2017 0100 - .45 1.1562583 26.15E-03 3 - 3 002JAN2017 0200 - .45 1.1815034 23.64E-03 3 - 3 002JAN2017 0300 - .5 1 .17367 21.45E-02 3 - 3 002JAN2017 0400 - .5 1.2027799 21.08E-02 3 - 3 002JAN2017 0500 - .5 1.2291546 21.01E-02 3 - 3 002JAN2017 0600 - .45 1.2875505 21.70E-03 3 - 3 002JAN2017 0700 - .45 1.3029256 29.10E-03 3 - 3 002JAN2017 0800 - .45 1.3175578 21.75E-02 3 - 3 002JAN2017 0900 - .4 1.3679012 21.46E-02 3 - 3 002JAN2017 1000 - .4 1 .371589 22.99E-02 3 - 3 002JAN2017 1100 - .4 1.3754609 24.79E-02 3 - 3 002JAN2017 1200 - .35 1.4180924 24.98E-02 3 - 3 002JAN2017 1300 - .35 1.4119918 28.13E-02 3 - 3 002JAN2017 1400 - .35 1 .406457 2.1114301 3 - 3 002JAN2017 1500 - .3 1.4428244 2.1147146 3 - 3 002JAN2017 1600 - .3 1.4284927 2.1515737 3 - 3 002JAN2017 1700 - .3 1.4154813 2 .18403 3 - 3 002JAN2017 1800 - .25 1.4477215 2.1842001 3 - 3 002JAN2017 1900 - .25 1.4269008 2.2213254 3 - 3 002JAN2017 2000 - .25 1.4081997 2.2523037 3 - 3 002JAN2017 2100 - .2 1.4382429 2.2466414 3 - 3 002JAN2017 2200 - .2 1.4124274 2 .281561 3 - 3 002JAN2017 2300 - .2 1.3894127 2 .309322 3 - 3 003JAN2017 0000 - .15 1.4191277 2.2963563 3 - 3 003JAN2017 0100 - .15 1.3893773 2.3283369 3 - 3 003JAN2017 0200 - .15 1.3630884 2.3525086 3 - 3 003JAN2017 0300 - .1 1.3946227 2 .331126 3 - 3 003JAN2017 0400 - .1 1.3615198 2 .360618 3 - 3 003JAN2017 0500 - .1 1.3325785 2.3816974 3 - 3 003JAN2017 0600 - .05 1.3700845 2.3495327 3 - 3 003JAN2017 0700 - .05 1.3334168 2.3782524 3 - 3 003JAN2017 0800 - .05 1.3016858 2.3977329 3 - 3 003JAN2017 0900 - .01 1.3420733 2.3577345 3 - 3 003JAN2017 1000 - .01 1.3031967 2.3854274 3 - 3 003JAN2017 1100 - .01 1 .270029 2 .403181 3 -Section - Flow and Seasonal Roughness Flag (plan) - F F -Section - Post Process Set WS Elevations - 1 - 3112.5458 3111.6644 3111.6643 3111.6643 3111.7678 - 3111.7692 3111.7708 3111.8609 3111.8641 3111.8675 - 3111.9511 3111.9563 3111.9614 3112.0419 3 112.048 - 3112.0549 3112.1347 3112.1418 3112.1506 3112.2292 - 3112.2376 3112.2479 3112.3255 3 112.335 3112.3466 - 3112.4229 3112.4337 3112.4462 3112.5209 3112.5327 - 3112.5458 3112.4946 3112.5006 3112.5036 3112.4406 - 3112.4382 3112.4325 3112.3607 3112.3508 3112.3409 - 3112.2627 3112.2501 3112.2387 3112.1554 3112.1424 - 3112.1312 3112.0433 3112.0314 3112.0216 3111.9285 - 3111.9183 3111.9103 3111.8099 3111.8019 3 111.796 - 3111.6817 3111.6764 3111.6727 3111.5504 3111.5486 - 3111.5474 - 2 - 3106.6544 3105.9221 3105.9222 3105.9222 3105.8279 - 3105.8432 3105.8573 3105.7922 3105.8153 3105.8394 - 3105.7917 3105.8228 3105.8547 3105.8168 3 105.858 - 3105.8957 3105.8656 3105.9124 3105.9538 3105.9301 - 3105.9802 3106.0239 3106.0048 3106.0566 3106.1015 - 3106.0856 3106.1379 3106.1831 3 106.17 3106.2221 - 3106.2674 3106.3628 3106.3886 3106.4143 3106.4939 - 3106.5025 3106.5136 3106.5806 3106.5772 3106.5749 - 3106.6323 3106.6172 3106.6035 3106.6544 3106.6289 - 3106.6056 3106.6526 3106.6182 3106.5868 3106.6326 - 3106.5905 3 106.552 3106.6002 3 106.551 3106.5062 - 3106.5636 3 106.507 3106.4558 3106.5184 3106.4561 - 3106.4005 - 3 - 3100.8923 3100.1816 3100.1815 3100.1815 3100.2677 - 3100.2398 3100.2163 3100.2708 3100.2311 3100.1974 - 3100.2366 3100.1921 3100.1548 3100.1869 3100.1416 - 3100.1078 3100.1357 3100.0951 3100.0646 3100.0931 - 3100.0573 3100.0333 3100.0643 3100.0355 3100.0195 - 3100.0539 3100.0328 3100.0235 3 100.064 3100.0501 - 3100.0476 3100.0166 3100.0437 3 100.075 3100.0643 - 3100.1209 3 100.176 3100.1809 3100.2561 3100.3226 - 3100.3297 3100.4068 3100.4726 3 100.473 3100.5464 - 3100.6067 3100.5957 3100.6629 3100.7159 3100.6912 - 3100.7519 3100.7974 3100.7571 3100.8127 3100.8521 - 3100.7919 3100.8457 3100.8821 3100.8073 3100.8591 - 3100.8923 -Section - Junction Information -Section - Reach Boundaries - T T 1 3 Flume F F - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 1100.8923 0 - 1100.1816 0 - 1100.1815 0 - 1100.1815 0 - 1100.2677 0 - 1100.2398 0 - 1100.2163 0 - 1100.2708 0 - 1100.2311 0 - 1100.1974 0 - 1100.2366 0 - 1100.1921 0 - 1100.1548 0 - 1100.1869 0 - 1100.1416 0 - 1100.1078 0 - 1100.1357 0 - 1100.0951 0 - 1100.0646 0 - 1100.0931 0 - 1100.0573 0 - 1100.0333 0 - 1100.0643 0 - 1100.0355 0 - 1100.0195 0 - 1100.0539 0 - 1100.0328 0 - 1100.0235 0 - 1 100.064 0 - 1100.0501 0 - 1100.0476 0 - 1100.0166 0 - 1100.0437 0 - 1 100.075 0 - 1100.0643 0 - 1100.1209 0 - 1 100.176 0 - 1100.1809 0 - 1100.2561 0 - 1100.3226 0 - 1100.3297 0 - 1100.4068 0 - 1100.4726 0 - 1 100.473 0 - 1100.5464 0 - 1100.6067 0 - 1100.5957 0 - 1100.6629 0 - 1100.7159 0 - 1100.6912 0 - 1100.7519 0 - 1100.7974 0 - 1100.7571 0 - 1100.8127 0 - 1100.8521 0 - 1100.7919 0 - 1100.8457 0 - 1100.8821 0 - 1100.8073 0 - 1100.8591 0 - 1100.8923 0 -Section - Encroachment Data -Section - Observed Water Surface Data -Section - Roughness Change Factors -Section - Breach Data - 0 -Section - Storage Area Data -Section - Storage Area Connection Data -Section - Pump Station Data -Section - River Reach Data -NODE 11 10000 50000 50000 50000 0 0.033 0.785 - 1 F - 4 - 0115.4828 0111.4828 .7111.4828 .7115.4828 -Section - XS Manning's/Roughness Data - 2 F F 0 - 0 .00979 .7 .00979 - F F 0 .7 F F - 0 0 F - 0 F -NODE 11 5000 50000 50000 50000 0 0.48 0.48 - 1 F - 4 - 0109.7414 0105.7414 .7105.7414 .7109.7414 -Section - XS Manning's/Roughness Data - 2 F F 0 - 0 .00979 .7 .00979 - F F 0 .7 F F - 0 0 F - 0 F -NODE 11 0 0 0 0 0 0.926 0.176 - 1 F - 4 - 0 104 0 100 .7 100 .7 104 -Section - XS Manning's/Roughness Data - 2 F F 0 - 0 .00979 .7 .00979 - F F 0 .7 F F - 0 0 F - 0 F diff --git a/test/data/ras/unsteadyflume/HEC-RASFlumeCase.r06 b/test/data/ras/unsteadyflume/HEC-RASFlumeCase.r06 deleted file mode 100644 index 9676c00..0000000 --- a/test/data/ras/unsteadyflume/HEC-RASFlumeCase.r06 +++ /dev/null @@ -1,349 +0,0 @@ -HEC-RAS 5.0.3 September 2016 -Section - Arrays Sizes -Plan 06 - 1 1 0 9 12 F - 61 3 0 3 - 3 3 0 0 0 0 0 0 - 0 0 0 F F 0 0 0 0 0 0 0 - 0 0 T T 0 0 0 F 0 0 F - 0 - 0 0 - 1 1 0 F T F 0 3 30 F F F 0 - 61 - 0 .01 F .0098 20 .3281 .0098 F 5 T F -Section - Expansion and Contraction Coefficients - .1 .3 1 -Section - Job Control - 1 1 1 F F 1 -Section - Flow Data - 3 0Max WS -17.65733 1 16.6825 216.07345 3 - 3 031DEC2016 2400 -1.765733 11.765733 21.765733 3 - 3 001JAN2017 0100 -1.765733 11.771711 21.768767 3 - 3 001JAN2017 0200 -1.765733 11.769161 21.770519 3 - 3 001JAN2017 0300 -3.531467 11.389794 21.802249 3 - 3 001JAN2017 0400 -3.531467 1 2.28216 21.432712 3 - 3 001JAN2017 0500 -3.531467 12.801502 21.659112 3 - 3 001JAN2017 0600 - 5.2972 12.841915 22.025836 3 - 3 001JAN2017 0700 - 5.2972 1 3.92496 22.196783 3 - 3 001JAN2017 0800 - 5.2972 14.498059 22.811183 3 - 3 001JAN2017 0900 -7.062933 14.632547 23.391718 3 - 3 001JAN2017 1000 -7.062933 15.734402 23.804687 3 - 3 001JAN2017 1100 -7.062933 16.254492 24.538166 3 - 3 001JAN2017 1200 -8.828667 16.431442 25.131091 3 - 3 001JAN2017 1300 -8.828667 17.528893 25.616398 3 - 3 001JAN2017 1400 -8.828667 18.000274 2 6.35645 3 - 3 001JAN2017 1500 - 10.5944 18.222512 26.916453 3 - 3 001JAN2017 1600 - 10.5944 19.311354 27.436736 3 - 3 001JAN2017 1700 - 10.5944 19.742496 28.164446 3 - 3 001JAN2017 1800 -12.36013 1 10.0084 28.694324 3 - 3 001JAN2017 1900 -12.36013 111.08103 29.238958 3 - 3 001JAN2017 2000 -12.36013 1 11.4791 29.950885 3 - 3 001JAN2017 2100 -14.12587 111.79085 210.45885 3 - 3 001JAN2017 2200 -14.12587 112.84504 211.02375 3 - 3 001JAN2017 2300 -14.12587 113.21672 211.71972 3 - 3 001JAN2017 2400 - 15.8916 1 13.5722 212.21221 3 - 3 002JAN2017 0100 - 15.8916 114.60528 212.79508 3 - 3 002JAN2017 0200 - 15.8916 114.95488 213.47847 3 - 3 002JAN2017 0300 -17.65733 1 15.3525 213.96195 3 - 3 002JAN2017 0400 -17.65733 116.36305 214.56144 3 - 3 002JAN2017 0500 -17.65733 116.69472 215.23433 3 - 3 002JAN2017 0600 - 15.8916 1 16.6825 215.82604 3 - 3 002JAN2017 0700 - 15.8916 116.02056 216.04506 3 - 3 002JAN2017 0800 - 15.8916 115.95254 216.02785 3 - 3 002JAN2017 0900 -14.12587 1 15.7227 216.05589 3 - 3 002JAN2017 1000 -14.12587 114.89893 215.84371 3 - 3 002JAN2017 1100 -14.12587 114.69582 215.49485 3 - 3 002JAN2017 1200 -12.36013 114.38449 215.26355 3 - 3 002JAN2017 1300 -12.36013 113.46265 214.85821 3 - 3 002JAN2017 1400 -12.36013 1 13.1817 214.34584 3 - 3 002JAN2017 1500 - 10.5944 112.85581 213.98532 3 - 3 002JAN2017 1600 - 10.5944 1 11.8671 213.49557 3 - 3 002JAN2017 1700 - 10.5944 111.53575 212.89658 3 - 3 002JAN2017 1800 -8.828667 111.23403 212.46656 3 - 3 002JAN2017 1900 -8.828667 110.19258 211.94846 3 - 3 002JAN2017 2000 -8.828667 19.821993 211.29984 3 - 3 002JAN2017 2100 -7.062933 19.570595 210.82656 3 - 3 002JAN2017 2200 -7.062933 1 8.48115 210.31356 3 - 3 002JAN2017 2300 -7.062933 18.073236 29.633651 3 - 3 002JAN2017 2400 - 5.2972 17.899219 29.126683 3 - 3 003JAN2017 0100 - 5.2972 16.761486 28.648818 3 - 3 003JAN2017 0200 - 5.2972 16.314324 27.953119 3 - 3 003JAN2017 0300 -3.531467 16.254657 27.409228 3 - 3 003JAN2017 0400 -3.531467 15.060842 27.002091 3 - 3 003JAN2017 0500 -3.531467 14.563483 26.299874 3 - 3 003JAN2017 0600 -1.765733 14.693266 25.690785 3 - 3 003JAN2017 0700 -1.765733 13.404716 25.420096 3 - 3 003JAN2017 0800 -1.765733 12.834469 24.724866 3 - 3 003JAN2017 0900 -.3531467 13.267956 2 3.94956 3 - 3 003JAN2017 1000 -.3531467 11.959105 23.932511 3 - 3 003JAN2017 1100 -.3531467 11.371168 23.319759 3 -Section - Flow and Seasonal Roughness Flag (plan) - F F -Section - Post Process Set WS Elevations - 1 - 3 336.588 3 332.639 3 332.636 3 332.636 3 332.963 - 3 333.087 3 333.146 3 333.435 3 333.569 3 333.62 - 3 333.873 3 334.002 3 334.049 3 334.288 3 334.418 - 3 334.468 3 334.7 3 334.832 3 334.886 3 335.115 - 3 335.249 3 335.308 3 335.534 3 335.669 3 335.732 - 3 335.956 3 336.091 3 336.159 3 336.381 3 336.517 - 3 336.588 3 336.475 3 336.422 3 336.413 3 336.241 - 3 336.14 3 336.093 3 335.885 3 335.757 3 335.691 - 3 335.461 3 335.319 3 335.244 3 335 3 334.849 - 3 334.772 3 334.515 3 334.36 3 334.285 3 334.012 - 3 333.853 3 333.781 3 333.485 3 333.322 3 333.254 - 3 332.912 3 332.743 3 332.684 3 332.295 3 332.151 - 3 332.121 - 2 - 3 334.557 3 330.752 3 330.753 3 330.752 3 330.658 - 3 330.848 3 330.972 3 331.01 3 331.228 3 331.378 - 3 331.456 3 331.67 3 331.82 3 331.913 3 332.117 - 3 332.264 3 332.364 3 332.561 3 332.705 3 332.809 - 3 333.001 3 333.143 3 333.252 3 333.439 3 333.58 - 3 333.693 3 333.878 3 334.019 3 334.136 3 334.318 - 3 334.458 3 334.557 3 334.546 3 334.538 3 334.522 - 3 334.421 3 334.343 3 334.273 3 334.128 3 334.013 - 3 333.919 3 333.749 3 333.615 3 333.511 3 333.326 - 3 333.182 3 333.076 3 332.88 3 332.728 3 332.627 - 3 332.421 3 332.261 3 332.172 3 331.951 3 331.78 - 3 331.718 3 331.47 3 331.278 3 331.273 3 330.997 - 3 330.785 - 3 - 3 332.675 3 328.872 3 328.872 3 328.873 3 328.883 - 3 328.762 3 328.837 3 328.953 3 329.006 3 329.19 - 3 329.359 3 329.476 3 329.679 3 329.841 3 329.972 - 3 330.17 3 330.318 3 330.454 3 330.644 3 330.782 - 3 330.922 3 331.105 3 331.235 3 331.38 3 331.559 - 3 331.685 3 331.834 3 332.01 3 332.134 3 332.287 - 3 332.46 3 332.611 3 332.668 3 332.663 3 332.67 - 3 332.616 3 332.527 3 332.467 3 332.363 3 332.232 - 3 332.14 3 332.014 3 331.86 3 331.75 3 331.617 - 3 331.451 3 331.33 3 331.198 3 331.024 3 330.893 - 3 330.77 3 330.589 3 330.447 3 330.34 3 330.155 - 3 329.992 3 329.919 3 329.731 3 329.516 3 329.512 - 3 329.338 -Section - Junction Information -Section - Reach Boundaries - T T 1 3 Flume F F - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0 - 1 332.675 0 - 1 328.872 0 - 1 328.872 0 - 1 328.873 0 - 1 328.883 0 - 1 328.762 0 - 1 328.837 0 - 1 328.953 0 - 1 329.006 0 - 1 329.19 0 - 1 329.359 0 - 1 329.476 0 - 1 329.679 0 - 1 329.841 0 - 1 329.972 0 - 1 330.17 0 - 1 330.318 0 - 1 330.454 0 - 1 330.644 0 - 1 330.782 0 - 1 330.922 0 - 1 331.105 0 - 1 331.235 0 - 1 331.38 0 - 1 331.559 0 - 1 331.685 0 - 1 331.834 0 - 1 332.01 0 - 1 332.134 0 - 1 332.287 0 - 1 332.46 0 - 1 332.611 0 - 1 332.668 0 - 1 332.663 0 - 1 332.67 0 - 1 332.616 0 - 1 332.527 0 - 1 332.467 0 - 1 332.363 0 - 1 332.232 0 - 1 332.14 0 - 1 332.014 0 - 1 331.86 0 - 1 331.75 0 - 1 331.617 0 - 1 331.451 0 - 1 331.33 0 - 1 331.198 0 - 1 331.024 0 - 1 330.893 0 - 1 330.77 0 - 1 330.589 0 - 1 330.447 0 - 1 330.34 0 - 1 330.155 0 - 1 329.992 0 - 1 329.919 0 - 1 329.731 0 - 1 329.516 0 - 1 329.512 0 - 1 329.338 0 -Section - Encroachment Data -Section - Observed Water Surface Data -Section - Roughness Change Factors -Section - Breach Data - 0 -Section - Storage Area Data -Section - Storage Area Connection Data -Section - Pump Station Data -Section - River Reach Data -NODE 11 10000 16404.2 16404.2 16404.2 0 0.107 2.574 - 1 F - 4 - 0 335.131 0 331.85 2.297 331.85 2.297 335.131 -Section - XS Manning's/Roughness Data - 2 F F 0 - 0 .00979 2.297 .00979 - F F 0 2.297 F F - 0 0 F - 0 F -NODE 11 5000 16404.2 16404.2 16404.2 0 1.573 1.576 - 1 F - 4 - 0 333.248 0 329.967 2.297 329.967 2.297 333.248 -Section - XS Manning's/Roughness Data - 2 F F 0 - 0 .00979 2.297 .00979 - F F 0 2.297 F F - 0 0 F - 0 F -NODE 11 0 0 0 0 0 3.039 0.578 - 1 F - 4 - 0 331.365 0 328.084 2.297 328.084 2.297 331.365 -Section - XS Manning's/Roughness Data - 2 F F 0 - 0 .00979 2.297 .00979 - F F 0 2.297 F F - 0 0 F - 0 F diff --git a/test/data/ras/unsteadyflume/HEC-RASFlumeCase.rasmap 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Type="RASMoreLayers" /> - </Layer> - <Layer Name="depth" Type="RASResultsMap"> - <SurfaceFill Alpha="255" Colors="-16711681,-16777077" Values="0,15" Stretched="True" /> - <Contour On="False" Interval="5" Color="-16777216" /> - <MapParameters MapType="depth" OutputMode="Dynamic Surface" ContourPolygonValue="0" ProfileIndex="2147483647" ProfileName="Max" ArrivalStartMode="0" Hours="True" /> - </Layer> - <Layer Name="velocity" Type="RASResultsMap"> - <SurfaceFill Alpha="255" Colors="-16777077,-16776961,-7278960,-256,-23296,-47872,-7667712" Values="0,2,4,6,8,10,15" Stretched="True" /> - <Contour On="False" Interval="5" Color="-16777216" /> - <MapParameters MapType="velocity" OutputMode="Dynamic Surface" ContourPolygonValue="0" ProfileIndex="2147483647" ProfileName="Max" ArrivalStartMode="0" Hours="True" /> - </Layer> - <Layer Name="elevation" Type="RASResultsMap"> - <SurfaceFill Alpha="255" Colors="-8388864,-16744448,-256,-23296,-65536,-16181,-65281" Values="0,16.6666666666667,33.3333333333333,50,66.6666666666667,83.3333333333333,100" Stretched="True" /> - <Contour On="False" Interval="5" Color="-16777216" /> - <MapParameters MapType="elevation" OutputMode="Dynamic Surface" ContourPolygonValue="0" ProfileIndex="2147483647" ProfileName="Max" ArrivalStartMode="0" Hours="True" /> - </Layer> - </Layer> - <Layer Name="BaseCase02" Type="RASResults" Filename=".\HEC-RASFlumeCase.p02.hdf"> - <Layer Name="Geometry" Type="RASGeometry" Filename=".\HEC-RASFlumeCase.p02.hdf"> - <Layer Name="Rivers" Type="RASRiver" /> - <Layer Name="XS" Type="RASXS" /> - <Layer Name="Storage Areas" Type="RASStorageArea" /> - <Layer Name="2D Flow Areas" Type="RASD2FlowArea" /> - <Layer Name="..." Type="RASMoreLayers" /> - </Layer> - <Layer Name="depth" Type="RASResultsMap"> - <SurfaceFill Alpha="255" Colors="-16711681,-16777077" Values="0,15" Stretched="True" /> - <Contour On="False" Interval="5" Color="-16777216" /> - <MapParameters MapType="depth" OutputMode="Dynamic Surface" ContourPolygonValue="0" ProfileIndex="2147483647" ProfileName="Max" ArrivalStartMode="0" Hours="True" /> - </Layer> - <Layer Name="velocity" Type="RASResultsMap"> - <SurfaceFill Alpha="255" Colors="-16777077,-16776961,-7278960,-256,-23296,-47872,-7667712" Values="0,2,4,6,8,10,15" Stretched="True" /> - <Contour On="False" Interval="5" Color="-16777216" /> - <MapParameters MapType="velocity" OutputMode="Dynamic Surface" ContourPolygonValue="0" ProfileIndex="2147483647" ProfileName="Max" ArrivalStartMode="0" Hours="True" /> - </Layer> - <Layer Name="elevation" Type="RASResultsMap"> - <SurfaceFill Alpha="255" Colors="-8388864,-16744448,-256,-23296,-65536,-16181,-65281" Values="0,16.6666666666667,33.3333333333333,50,66.6666666666667,83.3333333333333,100" Stretched="True" /> - <Contour On="False" Interval="5" Color="-16777216" /> - <MapParameters MapType="elevation" OutputMode="Dynamic Surface" ContourPolygonValue="0" ProfileIndex="2147483647" ProfileName="Max" ArrivalStartMode="0" Hours="True" /> - </Layer> - </Layer> - <Layer Name="BaseCase03" Type="RASResults" Filename=".\HEC-RASFlumeCase.p03.hdf"> - <Layer Name="Geometry" Type="RASGeometry" Filename=".\HEC-RASFlumeCase.p03.hdf"> - <Layer Name="Rivers" Type="RASRiver" /> - <Layer Name="XS" Type="RASXS" /> - <Layer Name="Storage Areas" Type="RASStorageArea" /> - <Layer Name="2D Flow Areas" Type="RASD2FlowArea" /> - <Layer Name="..." Type="RASMoreLayers" /> - </Layer> - <Layer Name="depth" Type="RASResultsMap"> - <SurfaceFill Alpha="255" Colors="-16711681,-16777077" Values="0,15" Stretched="True" /> - <Contour On="False" Interval="5" Color="-16777216" /> - <MapParameters MapType="depth" OutputMode="Dynamic Surface" ContourPolygonValue="0" ProfileIndex="2147483647" ProfileName="Max" ArrivalStartMode="0" Hours="True" /> - </Layer> - <Layer Name="velocity" Type="RASResultsMap"> - <SurfaceFill Alpha="255" Colors="-16777077,-16776961,-7278960,-256,-23296,-47872,-7667712" Values="0,2,4,6,8,10,15" Stretched="True" /> - <Contour On="False" Interval="5" Color="-16777216" /> - <MapParameters MapType="velocity" OutputMode="Dynamic Surface" ContourPolygonValue="0" ProfileIndex="2147483647" ProfileName="Max" ArrivalStartMode="0" Hours="True" /> - </Layer> - <Layer Name="elevation" Type="RASResultsMap"> - <SurfaceFill Alpha="255" Colors="-8388864,-16744448,-256,-23296,-65536,-16181,-65281" Values="0,16.6666666666667,33.3333333333333,50,66.6666666666667,83.3333333333333,100" Stretched="True" /> - <Contour On="False" Interval="5" Color="-16777216" /> - <MapParameters MapType="elevation" OutputMode="Dynamic Surface" ContourPolygonValue="0" ProfileIndex="2147483647" ProfileName="Max" ArrivalStartMode="0" Hours="True" /> - </Layer> - </Layer> - <Layer Name="BaseCase04" Type="RASResults" Filename=".\HEC-RASFlumeCase.p04.hdf"> - <Layer Name="Geometry" Type="RASGeometry" Filename=".\HEC-RASFlumeCase.p04.hdf"> - <Layer Name="Rivers" Type="RASRiver" /> - <Layer Name="XS" Type="RASXS" /> - <Layer Name="Storage Areas" Type="RASStorageArea" /> - <Layer Name="2D Flow Areas" Type="RASD2FlowArea" /> - <Layer Name="..." Type="RASMoreLayers" /> - </Layer> - <Layer Name="depth" Type="RASResultsMap"> - <SurfaceFill Alpha="255" Colors="-16711681,-16777077" Values="0,15" Stretched="True" /> - <Contour On="False" Interval="5" Color="-16777216" /> - <MapParameters MapType="depth" OutputMode="Dynamic Surface" ContourPolygonValue="0" ProfileIndex="2147483647" ProfileName="Max" ArrivalStartMode="0" Hours="True" /> - </Layer> - <Layer Name="velocity" Type="RASResultsMap"> - <SurfaceFill Alpha="255" Colors="-16777077,-16776961,-7278960,-256,-23296,-47872,-7667712" Values="0,2,4,6,8,10,15" Stretched="True" /> - <Contour On="False" Interval="5" Color="-16777216" /> - <MapParameters MapType="velocity" OutputMode="Dynamic Surface" ContourPolygonValue="0" ProfileIndex="2147483647" ProfileName="Max" ArrivalStartMode="0" Hours="True" /> - </Layer> - <Layer Name="elevation" Type="RASResultsMap"> - <SurfaceFill Alpha="255" Colors="-8388864,-16744448,-256,-23296,-65536,-16181,-65281" Values="0,16.6666666666667,33.3333333333333,50,66.6666666666667,83.3333333333333,100" Stretched="True" /> - <Contour On="False" Interval="5" Color="-16777216" /> - <MapParameters MapType="elevation" OutputMode="Dynamic Surface" ContourPolygonValue="0" ProfileIndex="2147483647" ProfileName="Max" ArrivalStartMode="0" Hours="True" /> - </Layer> - </Layer> - <Layer Name="Unsteady" Type="RASResults" Expanded="True" Selected="True" Filename=".\HEC-RASFlumeCase.p05.hdf"> - <Layer Name="Geometry" Type="RASGeometry" Filename=".\HEC-RASFlumeCase.p05.hdf"> - <Layer Name="Rivers" Type="RASRiver" /> - <Layer Name="XS" Type="RASXS" /> - <Layer Name="Storage Areas" Type="RASStorageArea" /> - <Layer Name="2D Flow Areas" Type="RASD2FlowArea" /> - <Layer Name="..." Type="RASMoreLayers" /> - </Layer> - <Layer Name="depth" Type="RASResultsMap"> - <SurfaceFill Alpha="255" Colors="-16711681,-16777077" Values="0,15" Stretched="True" /> - <Contour On="False" Interval="5" Color="-16777216" /> - <MapParameters MapType="depth" OutputMode="Dynamic Surface" ContourPolygonValue="0" ProfileIndex="2147483647" ProfileName="Max" ArrivalStartMode="0" Hours="True" /> - </Layer> - <Layer Name="velocity" Type="RASResultsMap"> - <SurfaceFill Alpha="255" Colors="-16777077,-16776961,-7278960,-256,-23296,-47872,-7667712" Values="0,2,4,6,8,10,15" Stretched="True" /> - <Contour On="False" Interval="5" Color="-16777216" /> - <MapParameters MapType="velocity" OutputMode="Dynamic Surface" ContourPolygonValue="0" ProfileIndex="2147483647" ProfileName="Max" ArrivalStartMode="0" Hours="True" /> - </Layer> - <Layer Name="elevation" Type="RASResultsMap"> - <SurfaceFill Alpha="255" Colors="-8388864,-16744448,-256,-23296,-65536,-16181,-65281" Values="100.0166015625,102.104797363281,104.192993164063,106.281188964844,108.369384765625,110.457580566406,112.545776367188" Stretched="True" /> - <Contour On="False" Interval="5" Color="-16777216" /> - <MapParameters MapType="elevation" OutputMode="Dynamic Surface" ContourPolygonValue="0" ProfileIndex="2147483647" ProfileName="Max" ArrivalStartMode="0" Hours="True" /> - </Layer> - </Layer> - </Results> - <MapLayers /> - <Terrains /> - <CurrentView> - <MaxX>1.06769596199525</MaxX> - <MinX>0.0676959619952494</MinX> - <MaxY>0.989311163895487</MaxY> - <MinY>-0.010688836104513</MinY> - </CurrentView> - <VelocitySettings> - <Density>1.5</Density> - <Lifetime>100</Lifetime> - <Radius>0.75</Radius> - <Method>2</Method> - <Timestep>1</Timestep> - <StaticColor>Black</StaticColor> - </VelocitySettings> - <AnimationSettings> - <DelayTimer>0</DelayTimer> - </AnimationSettings> - <ProjectSettings> - <Units>US Customary</Units> - </ProjectSettings> - <CurrentSettings> - <Folders /> - </CurrentSettings> -</RASMapper> \ No newline at end of file diff --git a/test/data/ras/unsteadyflume/HEC-RASFlumeCase.u01 b/test/data/ras/unsteadyflume/HEC-RASFlumeCase.u01 deleted file mode 100644 index b4ff53e..0000000 --- a/test/data/ras/unsteadyflume/HEC-RASFlumeCase.u01 +++ /dev/null @@ -1,20 +0,0 @@ -Flow Title=UnsteadyExampleData -Program Version=5.03 -Use Restart= 0 -Boundary Location=Flume ,1 ,10000 , , , , , -Interval=1HOUR -Flow Hydrograph= 60 - .05 .05 .05 .1 .1 .1 .15 .15 .15 .2 - .2 .2 .25 .25 .25 .3 .3 .3 .35 .35 - .35 .4 .4 .4 .45 .45 .45 .5 .5 .5 - .45 .45 .45 .4 .4 .4 .35 .35 .35 .3 - .3 .3 .25 .25 .25 .2 .2 .2 .15 .15 - .15 .1 .1 .1 .05 .05 .05 .01 .01 .01 -DSS Path= -Use DSS=False -Use Fixed Start Time=True -Fixed Start Date/Time=01JAN2017,0000 -Is Critical Boundary=False -Critical Boundary Flow= -Boundary Location=Flume ,1 ,0 , , , , , -Friction Slope=1.14828E-04 diff --git a/test/data/ras/unsteadyflume/HEC-RASFlumeCase.x05 b/test/data/ras/unsteadyflume/HEC-RASFlumeCase.x05 deleted file mode 100644 index b410e89..0000000 --- a/test/data/ras/unsteadyflume/HEC-RASFlumeCase.x05 +++ /dev/null @@ -1,58 +0,0 @@ -HEC-RAS 5.0.5 June 2018 -Section - Arrays Sizes -Unsteady - 1 1 0 9 12 F - 3 3 0 0 0 0 0 0 - 0 0 0 F T 0 0 0 0 0 0 0 - 0 0 F F 0 0 0 F 0 0 F - 0 - 1 1 0 F T F 0 3 30 F F F 0 - 0 .01 F .003 20 .1 .003 T 5 T F -Section - Expansion and Contraction Coefficients - .1 .3 1 -Section - Job Control - 1 1 1 F F 1 -Section - Junction Information -Section - Reach Boundaries - T T 1 3 Flume F F -Section - Encroachment Data -Section - Observed Water Surface Data -Section - Roughness Change Factors -Section - Breach Data -Section - Storage Area Data -Section - Storage Area Connection Data -Section - Pump Station Data -Section - River Reach Data -NODE 11 10000 50000 50000 50000 0 0.033 0.785 - 1 F - 4 - 0115.4828 0111.4828 .7111.4828 .7115.4828 -Section - XS Manning's/Roughness Data - 2 F F 0 - 0 .00979 .7 .00979 - F F 0 .7 F F - 0 0 F - 0 F -111.4828 .04 21 -NODE 11 5000 50000 50000 50000 0 0.48 0.48 - 1 F - 4 - 0109.7414 0105.7414 .7105.7414 .7109.7414 -Section - XS Manning's/Roughness Data - 2 F F 0 - 0 .00979 .7 .00979 - F F 0 .7 F F - 0 0 F - 0 F -105.7414 .04 21 -NODE 11 0 0 0 0 0 0.926 0.176 - 1 F - 4 - 0 104 0 100 .7 100 .7 104 -Section - XS Manning's/Roughness Data - 2 F F 0 - 0 .00979 .7 .00979 - F F 0 .7 F F - 0 0 F - 0 F - 100.15 .04 21 -- GitLab From 48b887699e2790468d36ceb08976940a2594681a Mon Sep 17 00:00:00 2001 From: Berutti <mberutti@contractor.usgs.gov> Date: Wed, 7 Aug 2019 13:22:19 -0500 Subject: [PATCH 6/7] Removed other files. --- test/test_transporter.py | 9 --------- 1 file changed, 9 deletions(-) delete mode 100644 test/test_transporter.py diff --git a/test/test_transporter.py b/test/test_transporter.py deleted file mode 100644 index ef37a92..0000000 --- a/test/test_transporter.py +++ /dev/null @@ -1,9 +0,0 @@ -import unittest - -from fluegg.transporter import * - -class TestMaxTimeStep(unittest.TestCase): - - def test_time_step(self): - - \ No newline at end of file -- GitLab From 970bd067c894d2482522d815c1f8e607bbbee819 Mon Sep 17 00:00:00 2001 From: Berutti <mberutti@contractor.usgs.gov> Date: Wed, 7 Aug 2019 13:27:58 -0500 Subject: [PATCH 7/7] Removed other files. --- test/test_random.py | 67 +++++++++++++++++++++++++++++++++++++++------ 1 file changed, 58 insertions(+), 9 deletions(-) diff --git a/test/test_random.py b/test/test_random.py index f721f5d..4185dd5 100644 --- a/test/test_random.py +++ b/test/test_random.py @@ -76,7 +76,25 @@ class TestNormalRandomNumbers(unittest.TestCase): class TestNonRandomNumbers(unittest.TestCase): - pass + def test_non_random_numbers(self): + + self.assertEqual(NonRandomNumbers().random([5], 1), [5]) + + with self.assertRaises(TypeError): + NonRandomNumbers().random(5) + + with self.assertRaises(TypeError): + NonRandomNumbers().random(5, 1, 5) + + with self.assertRaises(TypeError): + NonRandomNumbers().random_array(5) + + with self.assertRaises(TypeError): + NonRandomNumbers().random_array(5, 1) + + with self.assertRaises(TypeError): + NonRandomNumbers().random_array(5, 1, 5, 1) + class TestHDF5NormalRandomNumbers(unittest.TestCase): @@ -84,11 +102,21 @@ class TestHDF5NormalRandomNumbers(unittest.TestCase): def setUp(self): self._remove_test_saves() + + def _average(self, numbers): + + sum = 0 + for number in numbers: + sum += number + return float(sum) / len(numbers) + def _create_HDF5_file(self): with h5py.File('UNIT TEST HDF5 TEST FILE.hdf', 'w') as f: - f.create_dataset('TEST DATA SET', (100,)) + arr = np.random.normal(0, 1, 1000) + f.create_dataset('TEST DATA SET', data=arr) + def _get_file_path(self): @@ -104,8 +132,7 @@ class TestHDF5NormalRandomNumbers(unittest.TestCase): os.remove(r'.\results\{}'.format(file)) def test_HDF5_input(self): - ''' Needs way to validate the results - ''' + self._create_HDF5_file() file_path = self._get_file_path() arr = np.random.normal(25, 50, 100) @@ -131,16 +158,38 @@ class TestHDF5NormalRandomNumbers(unittest.TestCase): numbers = HDF5NormalRandomNumbers( file_path, 'TEST DATA SET').random( arr, 70) + + def test_HDF5_array_output_dimensions(self): - def test_HDF5_array(self): - ''' Needs way to validate the results - ''' self._create_HDF5_file() file_path = self._get_file_path() - arr = np.random.normal(25, 50, 100) numbers = HDF5NormalRandomNumbers( file_path, 'TEST DATA SET').random_array( - arr, 70, 100) + 0, 70, 100) + + self.assertEqual(len(numbers), 100) + + def test_HDF5_array_output_value(self): + + self._create_HDF5_file() + file_path = self._get_file_path() + numbers = HDF5NormalRandomNumbers( + file_path, 'TEST DATA SET').random_array( + 0, 1, 100) + avg = self._average(numbers) + + self.assertTrue(-1 < avg < 1) + + def test_HDF5_array_size(self): + + self._create_HDF5_file() + file_path = self._get_file_path() + + with self.assertRaises(ValueError): + numbers = HDF5NormalRandomNumbers( + file_path, 'TEST DATA SET').random_array( + 0, 70, 2500) + def tearDown(self): -- GitLab