From cc63a97920500bf9a429f40b60c9eb8b2ae2aeaf Mon Sep 17 00:00:00 2001
From: amsnyder <asnyder@usgs.gov>
Date: Tue, 9 Apr 2024 16:47:09 -0500
Subject: [PATCH] finalize serap workflows
---
catalog/catalog.json | 17 +-
catalog/serap_slamm/collection.json | 164 ++
catalog/serap_urb/collection.json | 134 ++
...ambi_urb_create_collection_from_zarr.ipynb | 1999 +----------------
...ap_slamm_create_collection_from_zarr.ipynb | 172 +-
...erap_urb_create_collection_from_zarr.ipynb | 168 +-
6 files changed, 631 insertions(+), 2023 deletions(-)
create mode 100644 catalog/serap_slamm/collection.json
create mode 100644 catalog/serap_urb/collection.json
diff --git a/catalog/catalog.json b/catalog/catalog.json
index 12dade73..440e3c02 100644
--- a/catalog/catalog.json
+++ b/catalog/catalog.json
@@ -318,6 +318,21 @@
"rel": "child",
"href": "./cprep/collection.json",
"type": "application/json"
+ },
+ {
+ "rel": "child",
+ "href": "./serap_urb/collection.json",
+ "type": "application/json"
+ },
+ {
+ "rel": "child",
+ "href": "./serap_slamm/collection.json",
+ "type": "application/json"
+ },
+ {
+ "rel": "child",
+ "href": "./sambi_urb/collection.json",
+ "type": "application/json"
}
]
-}
+}
\ No newline at end of file
diff --git a/catalog/serap_slamm/collection.json b/catalog/serap_slamm/collection.json
new file mode 100644
index 00000000..87843be0
--- /dev/null
+++ b/catalog/serap_slamm/collection.json
@@ -0,0 +1,164 @@
+{
+ "type": "Collection",
+ "id": "serap_slamm",
+ "stac_version": "1.0.0",
+ "description": "Sea Level Rise Projections for DSL-SAMBI",
+ "links": [
+ {
+ "rel": "root",
+ "href": "../catalog.json",
+ "type": "application/json"
+ },
+ {
+ "rel": "parent",
+ "href": "../catalog.json",
+ "type": "application/json"
+ }
+ ],
+ "stac_extensions": [
+ "https://stac-extensions.github.io/datacube/v2.2.0/schema.json"
+ ],
+ "cube:dimensions": {
+ "time": {
+ "type": "temporal",
+ "description": null,
+ "extent": [
+ "2000-01-01T00:00:00Z",
+ "2090-01-01T00:00:00Z"
+ ],
+ "step": "P10Y0M0DT0H0M0S"
+ },
+ "x": {
+ "type": "spatial",
+ "axis": "x",
+ "description": "x coordinate of projection",
+ "extent": [
+ 1020833.773,
+ 1838393.773
+ ],
+ "step": 30.0,
+ "reference_system": "{\"$schema\":\"https://proj.org/schemas/v0.5/projjson.schema.json\",\"type\":\"ProjectedCRS\",\"name\":\"undefined\",\"base_crs\":{\"name\":\"undefined\",\"datum\":{\"type\":\"GeodeticReferenceFrame\",\"name\":\"undefined\",\"ellipsoid\":{\"name\":\"undefined\",\"semi_major_axis\":6378137,\"inverse_flattening\":298.257222101},\"prime_meridian\":{\"name\":\"undefined\",\"longitude\":0}},\"coordinate_system\":{\"subtype\":\"ellipsoidal\",\"axis\":[{\"name\":\"Longitude\",\"abbreviation\":\"lon\",\"direction\":\"east\",\"unit\":\"degree\"},{\"name\":\"Latitude\",\"abbreviation\":\"lat\",\"direction\":\"north\",\"unit\":\"degree\"}]}},\"conversion\":{\"name\":\"unknown\",\"method\":{\"name\":\"Albers Equal Area\",\"id\":{\"authority\":\"EPSG\",\"code\":9822}},\"parameters\":[{\"name\":\"Latitude of false origin\",\"value\":23,\"unit\":\"degree\",\"id\":{\"authority\":\"EPSG\",\"code\":8821}},{\"name\":\"Longitude of false origin\",\"value\":-96,\"unit\":\"degree\",\"id\":{\"authority\":\"EPSG\",\"code\":8822}},{\"name\":\"Latitude of 1st standard parallel\",\"value\":29.5,\"unit\":\"degree\",\"id\":{\"authority\":\"EPSG\",\"code\":8823}},{\"name\":\"Latitude of 2nd standard parallel\",\"value\":45.5,\"unit\":\"degree\",\"id\":{\"authority\":\"EPSG\",\"code\":8824}},{\"name\":\"Easting at false origin\",\"value\":0,\"unit\":{\"type\":\"LinearUnit\",\"name\":\"Metre\",\"conversion_factor\":1},\"id\":{\"authority\":\"EPSG\",\"code\":8826}},{\"name\":\"Northing at false origin\",\"value\":0,\"unit\":{\"type\":\"LinearUnit\",\"name\":\"Metre\",\"conversion_factor\":1},\"id\":{\"authority\":\"EPSG\",\"code\":8827}}]},\"coordinate_system\":{\"subtype\":\"Cartesian\",\"axis\":[{\"name\":\"Easting\",\"abbreviation\":\"E\",\"direction\":\"east\",\"unit\":\"metre\"},{\"name\":\"Northing\",\"abbreviation\":\"N\",\"direction\":\"north\",\"unit\":\"metre\"}]}}"
+ },
+ "y": {
+ "type": "spatial",
+ "axis": "y",
+ "description": "y coordinate of projection",
+ "extent": [
+ 762857.078,
+ 1742207.078
+ ],
+ "step": 30.0,
+ "reference_system": "{\"$schema\":\"https://proj.org/schemas/v0.5/projjson.schema.json\",\"type\":\"ProjectedCRS\",\"name\":\"undefined\",\"base_crs\":{\"name\":\"undefined\",\"datum\":{\"type\":\"GeodeticReferenceFrame\",\"name\":\"undefined\",\"ellipsoid\":{\"name\":\"undefined\",\"semi_major_axis\":6378137,\"inverse_flattening\":298.257222101},\"prime_meridian\":{\"name\":\"undefined\",\"longitude\":0}},\"coordinate_system\":{\"subtype\":\"ellipsoidal\",\"axis\":[{\"name\":\"Longitude\",\"abbreviation\":\"lon\",\"direction\":\"east\",\"unit\":\"degree\"},{\"name\":\"Latitude\",\"abbreviation\":\"lat\",\"direction\":\"north\",\"unit\":\"degree\"}]}},\"conversion\":{\"name\":\"unknown\",\"method\":{\"name\":\"Albers Equal Area\",\"id\":{\"authority\":\"EPSG\",\"code\":9822}},\"parameters\":[{\"name\":\"Latitude of false origin\",\"value\":23,\"unit\":\"degree\",\"id\":{\"authority\":\"EPSG\",\"code\":8821}},{\"name\":\"Longitude of false origin\",\"value\":-96,\"unit\":\"degree\",\"id\":{\"authority\":\"EPSG\",\"code\":8822}},{\"name\":\"Latitude of 1st standard parallel\",\"value\":29.5,\"unit\":\"degree\",\"id\":{\"authority\":\"EPSG\",\"code\":8823}},{\"name\":\"Latitude of 2nd standard parallel\",\"value\":45.5,\"unit\":\"degree\",\"id\":{\"authority\":\"EPSG\",\"code\":8824}},{\"name\":\"Easting at false origin\",\"value\":0,\"unit\":{\"type\":\"LinearUnit\",\"name\":\"Metre\",\"conversion_factor\":1},\"id\":{\"authority\":\"EPSG\",\"code\":8826}},{\"name\":\"Northing at false origin\",\"value\":0,\"unit\":{\"type\":\"LinearUnit\",\"name\":\"Metre\",\"conversion_factor\":1},\"id\":{\"authority\":\"EPSG\",\"code\":8827}}]},\"coordinate_system\":{\"subtype\":\"Cartesian\",\"axis\":[{\"name\":\"Easting\",\"abbreviation\":\"E\",\"direction\":\"east\",\"unit\":\"metre\"},{\"name\":\"Northing\",\"abbreviation\":\"N\",\"direction\":\"north\",\"unit\":\"metre\"}]}}"
+ }
+ },
+ "cube:variables": {
+ "a1b_slr": {
+ "dimensions": [
+ "time",
+ "y",
+ "x"
+ ],
+ "type": "data",
+ "description": "A1B Sea Level Rise Projection for South Atlantic Migratory Bird Initiative",
+ "unit": "m"
+ },
+ "a1fi_slr": {
+ "dimensions": [
+ "time",
+ "y",
+ "x"
+ ],
+ "type": "data",
+ "description": "A1FI Sea Level Rise Projection for South Atlantic Migratory Bird Initiative",
+ "unit": "m"
+ },
+ "a2_slr": {
+ "dimensions": [
+ "time",
+ "y",
+ "x"
+ ],
+ "type": "data",
+ "description": "A2 Sea Level Rise Projection for South Atlantic Migratory Bird Initiative",
+ "unit": "m"
+ },
+ "albers_conical_equal_area": {
+ "dimensions": [],
+ "type": "auxiliary",
+ "description": null,
+ "unit": null
+ },
+ "b1_slr": {
+ "dimensions": [
+ "time",
+ "y",
+ "x"
+ ],
+ "type": "data",
+ "description": "B1 Sea Level Rise Projection for South Atlantic Migratory Bird Initiative",
+ "unit": "m"
+ }
+ },
+ "extent": {
+ "spatial": {
+ "bbox": [
+ [
+ -85.45951153138921,
+ 28.29288351506335,
+ -75.00778602615432,
+ 38.14259014718172
+ ]
+ ]
+ },
+ "temporal": {
+ "interval": [
+ [
+ "2000-01-01T00:00:00Z",
+ "2090-01-01T00:00:00Z"
+ ]
+ ]
+ }
+ },
+ "license": "Unlicense",
+ "assets": {
+ "zarr-s3-osn": {
+ "href": "s3://mdmf/gdp/serap_slamm.zarr/",
+ "type": "application/vnd+zarr",
+ "description": "Open Storage Network Pod S3 API access to collection zarr group",
+ "xarray:open_kwargs": {
+ "chunks": {},
+ "engine": "zarr",
+ "consolidated": true
+ },
+ "xarray:storage_options": {
+ "anon": true,
+ "client_kwargs": {
+ "endpoint_url": "https://usgs.osn.mghpcc.org/"
+ }
+ },
+ "roles": [
+ "data",
+ "zarr",
+ "s3"
+ ]
+ },
+ "zarr-s3": {
+ "href": "s3://nhgf-development/workspace/DataConversion/serap_slamm.zarr/",
+ "type": "application/vnd+zarr",
+ "description": "S3 access to collection zarr group",
+ "xarray:open_kwargs": {
+ "chunks": {},
+ "engine": "zarr",
+ "consolidated": true
+ },
+ "xarray:storage_options": {
+ "requester_pays": true
+ },
+ "roles": [
+ "data",
+ "zarr",
+ "s3"
+ ]
+ }
+ }
+}
\ No newline at end of file
diff --git a/catalog/serap_urb/collection.json b/catalog/serap_urb/collection.json
new file mode 100644
index 00000000..6fc459c3
--- /dev/null
+++ b/catalog/serap_urb/collection.json
@@ -0,0 +1,134 @@
+{
+ "type": "Collection",
+ "id": "serap_urb",
+ "stac_version": "1.0.0",
+ "description": "Urban Growth Projection for Southeast Regional Assessment Project",
+ "links": [
+ {
+ "rel": "root",
+ "href": "../catalog.json",
+ "type": "application/json"
+ },
+ {
+ "rel": "parent",
+ "href": "../catalog.json",
+ "type": "application/json"
+ }
+ ],
+ "stac_extensions": [
+ "https://stac-extensions.github.io/datacube/v2.2.0/schema.json"
+ ],
+ "cube:dimensions": {
+ "time": {
+ "type": "temporal",
+ "description": null,
+ "extent": [
+ "2000-01-01T00:00:00Z",
+ "2090-01-01T00:00:00Z"
+ ],
+ "step": "P10Y0M0DT0H0M0S"
+ },
+ "x": {
+ "type": "spatial",
+ "axis": "x",
+ "description": "x coordinate of projection",
+ "extent": [
+ 341918.77300000004,
+ 1838378.773
+ ],
+ "step": 60.0,
+ "reference_system": "{\"$schema\":\"https://proj.org/schemas/v0.5/projjson.schema.json\",\"type\":\"ProjectedCRS\",\"name\":\"undefined\",\"base_crs\":{\"name\":\"undefined\",\"datum\":{\"type\":\"GeodeticReferenceFrame\",\"name\":\"undefined\",\"ellipsoid\":{\"name\":\"undefined\",\"semi_major_axis\":6378137,\"inverse_flattening\":298.257222101},\"prime_meridian\":{\"name\":\"undefined\",\"longitude\":0}},\"coordinate_system\":{\"subtype\":\"ellipsoidal\",\"axis\":[{\"name\":\"Longitude\",\"abbreviation\":\"lon\",\"direction\":\"east\",\"unit\":\"degree\"},{\"name\":\"Latitude\",\"abbreviation\":\"lat\",\"direction\":\"north\",\"unit\":\"degree\"}]}},\"conversion\":{\"name\":\"unknown\",\"method\":{\"name\":\"Albers Equal Area\",\"id\":{\"authority\":\"EPSG\",\"code\":9822}},\"parameters\":[{\"name\":\"Latitude of false origin\",\"value\":23,\"unit\":\"degree\",\"id\":{\"authority\":\"EPSG\",\"code\":8821}},{\"name\":\"Longitude of false origin\",\"value\":-96,\"unit\":\"degree\",\"id\":{\"authority\":\"EPSG\",\"code\":8822}},{\"name\":\"Latitude of 1st standard parallel\",\"value\":29.5,\"unit\":\"degree\",\"id\":{\"authority\":\"EPSG\",\"code\":8823}},{\"name\":\"Latitude of 2nd standard parallel\",\"value\":45.5,\"unit\":\"degree\",\"id\":{\"authority\":\"EPSG\",\"code\":8824}},{\"name\":\"Easting at false origin\",\"value\":0,\"unit\":{\"type\":\"LinearUnit\",\"name\":\"Metre\",\"conversion_factor\":1},\"id\":{\"authority\":\"EPSG\",\"code\":8826}},{\"name\":\"Northing at false origin\",\"value\":0,\"unit\":{\"type\":\"LinearUnit\",\"name\":\"Metre\",\"conversion_factor\":1},\"id\":{\"authority\":\"EPSG\",\"code\":8827}}]},\"coordinate_system\":{\"subtype\":\"Cartesian\",\"axis\":[{\"name\":\"Easting\",\"abbreviation\":\"E\",\"direction\":\"east\",\"unit\":\"metre\"},{\"name\":\"Northing\",\"abbreviation\":\"N\",\"direction\":\"north\",\"unit\":\"metre\"}]}}"
+ },
+ "y": {
+ "type": "spatial",
+ "axis": "y",
+ "description": "y coordinate of projection",
+ "extent": [
+ 261002.07799999998,
+ 1966502.078
+ ],
+ "step": 60.0,
+ "reference_system": "{\"$schema\":\"https://proj.org/schemas/v0.5/projjson.schema.json\",\"type\":\"ProjectedCRS\",\"name\":\"undefined\",\"base_crs\":{\"name\":\"undefined\",\"datum\":{\"type\":\"GeodeticReferenceFrame\",\"name\":\"undefined\",\"ellipsoid\":{\"name\":\"undefined\",\"semi_major_axis\":6378137,\"inverse_flattening\":298.257222101},\"prime_meridian\":{\"name\":\"undefined\",\"longitude\":0}},\"coordinate_system\":{\"subtype\":\"ellipsoidal\",\"axis\":[{\"name\":\"Longitude\",\"abbreviation\":\"lon\",\"direction\":\"east\",\"unit\":\"degree\"},{\"name\":\"Latitude\",\"abbreviation\":\"lat\",\"direction\":\"north\",\"unit\":\"degree\"}]}},\"conversion\":{\"name\":\"unknown\",\"method\":{\"name\":\"Albers Equal Area\",\"id\":{\"authority\":\"EPSG\",\"code\":9822}},\"parameters\":[{\"name\":\"Latitude of false origin\",\"value\":23,\"unit\":\"degree\",\"id\":{\"authority\":\"EPSG\",\"code\":8821}},{\"name\":\"Longitude of false origin\",\"value\":-96,\"unit\":\"degree\",\"id\":{\"authority\":\"EPSG\",\"code\":8822}},{\"name\":\"Latitude of 1st standard parallel\",\"value\":29.5,\"unit\":\"degree\",\"id\":{\"authority\":\"EPSG\",\"code\":8823}},{\"name\":\"Latitude of 2nd standard parallel\",\"value\":45.5,\"unit\":\"degree\",\"id\":{\"authority\":\"EPSG\",\"code\":8824}},{\"name\":\"Easting at false origin\",\"value\":0,\"unit\":{\"type\":\"LinearUnit\",\"name\":\"Metre\",\"conversion_factor\":1},\"id\":{\"authority\":\"EPSG\",\"code\":8826}},{\"name\":\"Northing at false origin\",\"value\":0,\"unit\":{\"type\":\"LinearUnit\",\"name\":\"Metre\",\"conversion_factor\":1},\"id\":{\"authority\":\"EPSG\",\"code\":8827}}]},\"coordinate_system\":{\"subtype\":\"Cartesian\",\"axis\":[{\"name\":\"Easting\",\"abbreviation\":\"E\",\"direction\":\"east\",\"unit\":\"metre\"},{\"name\":\"Northing\",\"abbreviation\":\"N\",\"direction\":\"north\",\"unit\":\"metre\"}]}}"
+ }
+ },
+ "cube:variables": {
+ "albers_conical_equal_area": {
+ "dimensions": [],
+ "type": "auxiliary",
+ "description": null,
+ "unit": null
+ },
+ "urb_prob": {
+ "dimensions": [
+ "time",
+ "y",
+ "x"
+ ],
+ "type": "data",
+ "description": "Predicted probability of future urbanization",
+ "unit": "Percent * 10"
+ }
+ },
+ "extent": {
+ "spatial": {
+ "bbox": [
+ [
+ -92.64043063971503,
+ 23.80646502478526,
+ -74.43645174636934,
+ 40.64437052079659
+ ]
+ ]
+ },
+ "temporal": {
+ "interval": [
+ [
+ "2000-01-01T00:00:00Z",
+ "2090-01-01T00:00:00Z"
+ ]
+ ]
+ }
+ },
+ "license": "Unlicense",
+ "assets": {
+ "zarr-s3-osn": {
+ "href": "s3://mdmf/gdp/serap_urb.zarr/",
+ "type": "application/vnd+zarr",
+ "description": "Open Storage Network Pod S3 API access to collection zarr group",
+ "xarray:open_kwargs": {
+ "chunks": {},
+ "engine": "zarr",
+ "consolidated": true
+ },
+ "xarray:storage_options": {
+ "anon": true,
+ "client_kwargs": {
+ "endpoint_url": "https://usgs.osn.mghpcc.org/"
+ }
+ },
+ "roles": [
+ "data",
+ "zarr",
+ "s3"
+ ]
+ },
+ "zarr-s3": {
+ "href": "s3://nhgf-development/workspace/DataConversion/serap_urb.zarr/",
+ "type": "application/vnd+zarr",
+ "description": "S3 access to collection zarr group",
+ "xarray:open_kwargs": {
+ "chunks": {},
+ "engine": "zarr",
+ "consolidated": true
+ },
+ "xarray:storage_options": {
+ "requester_pays": true
+ },
+ "roles": [
+ "data",
+ "zarr",
+ "s3"
+ ]
+ }
+ }
+}
\ No newline at end of file
diff --git a/workflows/archive/sambi_urb_create_collection_from_zarr.ipynb b/workflows/archive/sambi_urb_create_collection_from_zarr.ipynb
index 2436a97d..a73e46cf 100644
--- a/workflows/archive/sambi_urb_create_collection_from_zarr.ipynb
+++ b/workflows/archive/sambi_urb_create_collection_from_zarr.ipynb
@@ -17,648 +17,10 @@
},
{
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+ "execution_count": null,
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- " element.href = url;\n",
- " console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n",
- " document.body.appendChild(element);\n",
- " } if (((window['jsPanel'] !== undefined) && (!(window['jsPanel'] instanceof HTMLElement))) || window.requirejs) {\n",
- " var urls = ['https://cdn.holoviz.org/panel/1.3.8/dist/bundled/floatpanel/jspanel4@4.12.0/dist/jspanel.js', 'https://cdn.holoviz.org/panel/1.3.8/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/modal/jspanel.modal.js', 'https://cdn.holoviz.org/panel/1.3.8/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/tooltip/jspanel.tooltip.js', 'https://cdn.holoviz.org/panel/1.3.8/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/hint/jspanel.hint.js', 'https://cdn.holoviz.org/panel/1.3.8/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/layout/jspanel.layout.js', 'https://cdn.holoviz.org/panel/1.3.8/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/contextmenu/jspanel.contextmenu.js', 'https://cdn.holoviz.org/panel/1.3.8/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/dock/jspanel.dock.js'];\n",
- " for (var i = 0; i < urls.length; i++) {\n",
- " skip.push(urls[i])\n",
- " }\n",
- " } if (((window['GridStack'] !== undefined) && (!(window['GridStack'] instanceof HTMLElement))) || window.requirejs) {\n",
- " var urls = ['https://cdn.holoviz.org/panel/1.3.8/dist/bundled/gridstack/gridstack@7.2.3/dist/gridstack-all.js'];\n",
- " for (var i = 0; i < urls.length; i++) {\n",
- " skip.push(urls[i])\n",
- " }\n",
- " } if (((window['Notyf'] !== undefined) && (!(window['Notyf'] instanceof HTMLElement))) || window.requirejs) {\n",
- " var urls = ['https://cdn.holoviz.org/panel/1.3.8/dist/bundled/notificationarea/notyf@3/notyf.min.js'];\n",
- " for (var i = 0; i < urls.length; i++) {\n",
- " skip.push(urls[i])\n",
- " }\n",
- " } var existing_scripts = []\n",
- " var scripts = document.getElementsByTagName('script')\n",
- " for (var i = 0; i < scripts.length; i++) {\n",
- " var script = scripts[i]\n",
- " if (script.src != null) {\n",
- "\texisting_scripts.push(script.src)\n",
- " }\n",
- " }\n",
- " for (var i = 0; i < js_urls.length; i++) {\n",
- " var url = js_urls[i];\n",
- " if (skip.indexOf(url) !== -1 || existing_scripts.indexOf(url) !== -1) {\n",
- "\tif (!window.requirejs) {\n",
- "\t on_load();\n",
- "\t}\n",
- "\tcontinue;\n",
- " }\n",
- " var element = document.createElement('script');\n",
- " element.onload = on_load;\n",
- " element.onerror = on_error;\n",
- " element.async = false;\n",
- " element.src = url;\n",
- " console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
- " document.head.appendChild(element);\n",
- " }\n",
- " for (var i = 0; i < js_modules.length; i++) {\n",
- " var url = js_modules[i];\n",
- " if (skip.indexOf(url) !== -1 || existing_scripts.indexOf(url) !== -1) {\n",
- "\tif (!window.requirejs) {\n",
- "\t on_load();\n",
- "\t}\n",
- "\tcontinue;\n",
- " }\n",
- " var element = document.createElement('script');\n",
- " element.onload = on_load;\n",
- " element.onerror = on_error;\n",
- " element.async = false;\n",
- " element.src = url;\n",
- " element.type = \"module\";\n",
- " console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
- " document.head.appendChild(element);\n",
- " }\n",
- " for (const name in js_exports) {\n",
- " var url = js_exports[name];\n",
- " if (skip.indexOf(url) >= 0 || root[name] != null) {\n",
- "\tif (!window.requirejs) {\n",
- "\t on_load();\n",
- "\t}\n",
- "\tcontinue;\n",
- " }\n",
- " var element = document.createElement('script');\n",
- " element.onerror = on_error;\n",
- " element.async = false;\n",
- " element.type = \"module\";\n",
- " console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
- " element.textContent = `\n",
- " import ${name} from \"${url}\"\n",
- " window.${name} = ${name}\n",
- " window._bokeh_on_load()\n",
- " `\n",
- " document.head.appendChild(element);\n",
- " }\n",
- " if (!js_urls.length && !js_modules.length) {\n",
- " on_load()\n",
- " }\n",
- " };\n",
- "\n",
- " function inject_raw_css(css) {\n",
- " const element = document.createElement(\"style\");\n",
- " element.appendChild(document.createTextNode(css));\n",
- " document.body.appendChild(element);\n",
- " }\n",
- "\n",
- " var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-3.3.4.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-3.3.4.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-3.3.4.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-3.3.4.min.js\", \"https://cdn.holoviz.org/panel/1.3.8/dist/panel.min.js\"];\n",
- " var js_modules = [];\n",
- " var js_exports = {};\n",
- " var css_urls = [];\n",
- " var inline_js = [ function(Bokeh) {\n",
- " Bokeh.set_log_level(\"info\");\n",
- " },\n",
- "function(Bokeh) {} // ensure no trailing comma for IE\n",
- " ];\n",
- "\n",
- " function run_inline_js() {\n",
- " if ((root.Bokeh !== undefined) || (force === true)) {\n",
- " for (var i = 0; i < inline_js.length; i++) {\n",
- "\ttry {\n",
- " inline_js[i].call(root, root.Bokeh);\n",
- "\t} catch(e) {\n",
- "\t if (!reloading) {\n",
- "\t throw e;\n",
- "\t }\n",
- "\t}\n",
- " }\n",
- " // Cache old bokeh versions\n",
- " if (Bokeh != undefined && !reloading) {\n",
- "\tvar NewBokeh = root.Bokeh;\n",
- "\tif (Bokeh.versions === undefined) {\n",
- "\t Bokeh.versions = new Map();\n",
- "\t}\n",
- "\tif (NewBokeh.version !== Bokeh.version) {\n",
- "\t Bokeh.versions.set(NewBokeh.version, NewBokeh)\n",
- "\t}\n",
- "\troot.Bokeh = Bokeh;\n",
- " }} else if (Date.now() < root._bokeh_timeout) {\n",
- " setTimeout(run_inline_js, 100);\n",
- " } else if (!root._bokeh_failed_load) {\n",
- " console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
- " root._bokeh_failed_load = true;\n",
- " }\n",
- " root._bokeh_is_initializing = false\n",
- " }\n",
- "\n",
- " function load_or_wait() {\n",
- " // Implement a backoff loop that tries to ensure we do not load multiple\n",
- " // versions of Bokeh and its dependencies at the same time.\n",
- " // In recent versions we use the root._bokeh_is_initializing flag\n",
- " // to determine whether there is an ongoing attempt to initialize\n",
- " // bokeh, however for backward compatibility we also try to ensure\n",
- " // that we do not start loading a newer (Panel>=1.0 and Bokeh>3) version\n",
- " // before older versions are fully initialized.\n",
- " if (root._bokeh_is_initializing && Date.now() > root._bokeh_timeout) {\n",
- " root._bokeh_is_initializing = false;\n",
- " root._bokeh_onload_callbacks = undefined;\n",
- " console.log(\"Bokeh: BokehJS was loaded multiple times but one version failed to initialize.\");\n",
- " load_or_wait();\n",
- " } else if (root._bokeh_is_initializing || (typeof root._bokeh_is_initializing === \"undefined\" && root._bokeh_onload_callbacks !== undefined)) {\n",
- " setTimeout(load_or_wait, 100);\n",
- " } else {\n",
- " root._bokeh_is_initializing = true\n",
- " root._bokeh_onload_callbacks = []\n",
- " var bokeh_loaded = Bokeh != null && (Bokeh.version === py_version || (Bokeh.versions !== undefined && Bokeh.versions.has(py_version)));\n",
- " if (!reloading && !bokeh_loaded) {\n",
- "\troot.Bokeh = undefined;\n",
- " }\n",
- " load_libs(css_urls, js_urls, js_modules, js_exports, function() {\n",
- "\tconsole.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n",
- "\trun_inline_js();\n",
- " });\n",
- " }\n",
- " }\n",
- " // Give older versions of the autoload script a head-start to ensure\n",
- " // they initialize before we start loading newer version.\n",
- " setTimeout(load_or_wait, 100)\n",
- "}(window));"
- ],
- "application/vnd.holoviews_load.v0+json": "(function(root) {\n function now() {\n return new Date();\n }\n\n var force = true;\n var py_version = '3.3.4'.replace('rc', '-rc.').replace('.dev', '-dev.');\n var reloading = false;\n var Bokeh = root.Bokeh;\n\n if (typeof (root._bokeh_timeout) === \"undefined\" || force) {\n root._bokeh_timeout = Date.now() + 5000;\n root._bokeh_failed_load = false;\n }\n\n function run_callbacks() {\n try {\n root._bokeh_onload_callbacks.forEach(function(callback) {\n if (callback != null)\n callback();\n });\n } finally {\n delete root._bokeh_onload_callbacks;\n }\n console.debug(\"Bokeh: all callbacks have finished\");\n }\n\n function load_libs(css_urls, js_urls, js_modules, js_exports, callback) {\n if (css_urls == null) css_urls = [];\n if (js_urls == null) js_urls = [];\n if (js_modules == null) js_modules = [];\n if (js_exports == null) js_exports = {};\n\n root._bokeh_onload_callbacks.push(callback);\n\n if (root._bokeh_is_loading > 0) {\n console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n return null;\n }\n if (js_urls.length === 0 && js_modules.length === 0 && Object.keys(js_exports).length === 0) {\n run_callbacks();\n return null;\n }\n if (!reloading) {\n console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n }\n\n function on_load() {\n root._bokeh_is_loading--;\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n run_callbacks()\n }\n }\n window._bokeh_on_load = on_load\n\n function on_error() {\n console.error(\"failed to load \" + url);\n }\n\n var skip = [];\n if (window.requirejs) {\n window.requirejs.config({'packages': {}, 'paths': {'jspanel': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/jspanel', 'jspanel-modal': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/modal/jspanel.modal', 'jspanel-tooltip': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/tooltip/jspanel.tooltip', 'jspanel-hint': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/hint/jspanel.hint', 'jspanel-layout': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/layout/jspanel.layout', 'jspanel-contextmenu': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/contextmenu/jspanel.contextmenu', 'jspanel-dock': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/dock/jspanel.dock', 'gridstack': 'https://cdn.jsdelivr.net/npm/gridstack@7.2.3/dist/gridstack-all', 'notyf': 'https://cdn.jsdelivr.net/npm/notyf@3/notyf.min'}, 'shim': {'jspanel': {'exports': 'jsPanel'}, 'gridstack': {'exports': 'GridStack'}}});\n require([\"jspanel\"], function(jsPanel) {\n\twindow.jsPanel = jsPanel\n\ton_load()\n })\n require([\"jspanel-modal\"], function() {\n\ton_load()\n })\n require([\"jspanel-tooltip\"], function() {\n\ton_load()\n })\n require([\"jspanel-hint\"], function() {\n\ton_load()\n })\n require([\"jspanel-layout\"], function() {\n\ton_load()\n })\n require([\"jspanel-contextmenu\"], function() {\n\ton_load()\n })\n require([\"jspanel-dock\"], function() {\n\ton_load()\n })\n require([\"gridstack\"], function(GridStack) {\n\twindow.GridStack = GridStack\n\ton_load()\n })\n require([\"notyf\"], function() {\n\ton_load()\n })\n root._bokeh_is_loading = css_urls.length + 9;\n } else {\n root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length + Object.keys(js_exports).length;\n }\n\n var existing_stylesheets = []\n var links = document.getElementsByTagName('link')\n for (var i = 0; i < links.length; i++) {\n var link = links[i]\n if (link.href != null) {\n\texisting_stylesheets.push(link.href)\n }\n }\n for (var i = 0; i < css_urls.length; i++) {\n var url = css_urls[i];\n if (existing_stylesheets.indexOf(url) !== -1) {\n\ton_load()\n\tcontinue;\n }\n const element = document.createElement(\"link\");\n element.onload = on_load;\n element.onerror = on_error;\n element.rel = \"stylesheet\";\n element.type = \"text/css\";\n element.href = url;\n console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n document.body.appendChild(element);\n } if (((window['jsPanel'] !== undefined) && (!(window['jsPanel'] instanceof HTMLElement))) || window.requirejs) {\n var urls = ['https://cdn.holoviz.org/panel/1.3.8/dist/bundled/floatpanel/jspanel4@4.12.0/dist/jspanel.js', 'https://cdn.holoviz.org/panel/1.3.8/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/modal/jspanel.modal.js', 'https://cdn.holoviz.org/panel/1.3.8/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/tooltip/jspanel.tooltip.js', 'https://cdn.holoviz.org/panel/1.3.8/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/hint/jspanel.hint.js', 'https://cdn.holoviz.org/panel/1.3.8/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/layout/jspanel.layout.js', 'https://cdn.holoviz.org/panel/1.3.8/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/contextmenu/jspanel.contextmenu.js', 'https://cdn.holoviz.org/panel/1.3.8/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/dock/jspanel.dock.js'];\n for (var i = 0; i < urls.length; i++) {\n skip.push(urls[i])\n }\n } if (((window['GridStack'] !== undefined) && (!(window['GridStack'] instanceof HTMLElement))) || window.requirejs) {\n var urls = ['https://cdn.holoviz.org/panel/1.3.8/dist/bundled/gridstack/gridstack@7.2.3/dist/gridstack-all.js'];\n for (var i = 0; i < urls.length; i++) {\n skip.push(urls[i])\n }\n } if (((window['Notyf'] !== undefined) && (!(window['Notyf'] instanceof HTMLElement))) || window.requirejs) {\n var urls = ['https://cdn.holoviz.org/panel/1.3.8/dist/bundled/notificationarea/notyf@3/notyf.min.js'];\n for (var i = 0; i < urls.length; i++) {\n skip.push(urls[i])\n }\n } var existing_scripts = []\n var scripts = document.getElementsByTagName('script')\n for (var i = 0; i < scripts.length; i++) {\n var script = scripts[i]\n if (script.src != null) {\n\texisting_scripts.push(script.src)\n }\n }\n for (var i = 0; i < js_urls.length; i++) {\n var url = js_urls[i];\n if (skip.indexOf(url) !== -1 || existing_scripts.indexOf(url) !== -1) {\n\tif (!window.requirejs) {\n\t on_load();\n\t}\n\tcontinue;\n }\n var element = document.createElement('script');\n element.onload = on_load;\n element.onerror = on_error;\n element.async = false;\n element.src = url;\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n document.head.appendChild(element);\n }\n for (var i = 0; i < js_modules.length; i++) {\n var url = js_modules[i];\n if (skip.indexOf(url) !== -1 || existing_scripts.indexOf(url) !== -1) {\n\tif (!window.requirejs) {\n\t on_load();\n\t}\n\tcontinue;\n }\n var element = document.createElement('script');\n element.onload = on_load;\n element.onerror = on_error;\n element.async = false;\n element.src = url;\n element.type = \"module\";\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n document.head.appendChild(element);\n }\n for (const name in js_exports) {\n var url = js_exports[name];\n if (skip.indexOf(url) >= 0 || root[name] != null) {\n\tif (!window.requirejs) {\n\t on_load();\n\t}\n\tcontinue;\n }\n var element = document.createElement('script');\n element.onerror = on_error;\n element.async = false;\n element.type = \"module\";\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n element.textContent = `\n import ${name} from \"${url}\"\n window.${name} = ${name}\n window._bokeh_on_load()\n `\n document.head.appendChild(element);\n }\n if (!js_urls.length && !js_modules.length) {\n on_load()\n }\n };\n\n function inject_raw_css(css) {\n const element = document.createElement(\"style\");\n element.appendChild(document.createTextNode(css));\n document.body.appendChild(element);\n }\n\n var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-3.3.4.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-3.3.4.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-3.3.4.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-3.3.4.min.js\", \"https://cdn.holoviz.org/panel/1.3.8/dist/panel.min.js\"];\n var js_modules = [];\n var js_exports = {};\n var css_urls = [];\n var inline_js = [ function(Bokeh) {\n Bokeh.set_log_level(\"info\");\n },\nfunction(Bokeh) {} // ensure no trailing comma for IE\n ];\n\n function run_inline_js() {\n if ((root.Bokeh !== undefined) || (force === true)) {\n for (var i = 0; i < inline_js.length; i++) {\n\ttry {\n inline_js[i].call(root, root.Bokeh);\n\t} catch(e) {\n\t if (!reloading) {\n\t throw e;\n\t }\n\t}\n }\n // Cache old bokeh versions\n if (Bokeh != undefined && !reloading) {\n\tvar NewBokeh = root.Bokeh;\n\tif (Bokeh.versions === undefined) {\n\t Bokeh.versions = new Map();\n\t}\n\tif (NewBokeh.version !== Bokeh.version) {\n\t Bokeh.versions.set(NewBokeh.version, NewBokeh)\n\t}\n\troot.Bokeh = Bokeh;\n }} else if (Date.now() < root._bokeh_timeout) {\n setTimeout(run_inline_js, 100);\n } else if (!root._bokeh_failed_load) {\n console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n root._bokeh_failed_load = true;\n }\n root._bokeh_is_initializing = false\n }\n\n function load_or_wait() {\n // Implement a backoff loop that tries to ensure we do not load multiple\n // versions of Bokeh and its dependencies at the same time.\n // In recent versions we use the root._bokeh_is_initializing flag\n // to determine whether there is an ongoing attempt to initialize\n // bokeh, however for backward compatibility we also try to ensure\n // that we do not start loading a newer (Panel>=1.0 and Bokeh>3) version\n // before older versions are fully initialized.\n if (root._bokeh_is_initializing && Date.now() > root._bokeh_timeout) {\n root._bokeh_is_initializing = false;\n root._bokeh_onload_callbacks = undefined;\n console.log(\"Bokeh: BokehJS was loaded multiple times but one version failed to initialize.\");\n load_or_wait();\n } else if (root._bokeh_is_initializing || (typeof root._bokeh_is_initializing === \"undefined\" && root._bokeh_onload_callbacks !== undefined)) {\n setTimeout(load_or_wait, 100);\n } else {\n root._bokeh_is_initializing = true\n root._bokeh_onload_callbacks = []\n var bokeh_loaded = Bokeh != null && (Bokeh.version === py_version || (Bokeh.versions !== undefined && Bokeh.versions.has(py_version)));\n if (!reloading && !bokeh_loaded) {\n\troot.Bokeh = undefined;\n }\n load_libs(css_urls, js_urls, js_modules, js_exports, function() {\n\tconsole.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n\trun_inline_js();\n });\n }\n }\n // Give older versions of the autoload script a head-start to ensure\n // they initialize before we start loading newer version.\n setTimeout(load_or_wait, 100)\n}(window));"
- },
- "metadata": {},
- "output_type": "display_data"
- },
- {
- "data": {
- "application/javascript": [
- "\n",
- "if ((window.PyViz === undefined) || (window.PyViz instanceof HTMLElement)) {\n",
- " window.PyViz = {comms: {}, comm_status:{}, kernels:{}, receivers: {}, plot_index: []}\n",
- "}\n",
- "\n",
- "\n",
- " function JupyterCommManager() {\n",
- " }\n",
- "\n",
- " JupyterCommManager.prototype.register_target = function(plot_id, comm_id, msg_handler) {\n",
- " if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n",
- " var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n",
- " comm_manager.register_target(comm_id, function(comm) {\n",
- " comm.on_msg(msg_handler);\n",
- " });\n",
- " } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n",
- " window.PyViz.kernels[plot_id].registerCommTarget(comm_id, function(comm) {\n",
- " comm.onMsg = msg_handler;\n",
- " });\n",
- " } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n",
- " google.colab.kernel.comms.registerTarget(comm_id, (comm) => {\n",
- " var messages = comm.messages[Symbol.asyncIterator]();\n",
- " function processIteratorResult(result) {\n",
- " var message = result.value;\n",
- " console.log(message)\n",
- " var content = {data: message.data, comm_id};\n",
- " var buffers = []\n",
- " for (var buffer of message.buffers || []) {\n",
- " buffers.push(new DataView(buffer))\n",
- " }\n",
- " var metadata = message.metadata || {};\n",
- " var msg = {content, buffers, metadata}\n",
- " msg_handler(msg);\n",
- " return messages.next().then(processIteratorResult);\n",
- " }\n",
- " return messages.next().then(processIteratorResult);\n",
- " })\n",
- " }\n",
- " }\n",
- "\n",
- " JupyterCommManager.prototype.get_client_comm = function(plot_id, comm_id, msg_handler) {\n",
- " if (comm_id in window.PyViz.comms) {\n",
- " return window.PyViz.comms[comm_id];\n",
- " } else if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n",
- " var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n",
- " var comm = comm_manager.new_comm(comm_id, {}, {}, {}, comm_id);\n",
- " if (msg_handler) {\n",
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- " }\n",
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- " return comm;\n",
- " }\n",
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- " \n",
- "\n",
- "\n",
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- "var HTML_MIME_TYPE = 'text/html';\n",
- "var EXEC_MIME_TYPE = 'application/vnd.holoviews_exec.v0+json';\n",
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- " */\n",
- "function render(props, node) {\n",
- " var div = document.createElement(\"div\");\n",
- " var script = document.createElement(\"script\");\n",
- " node.appendChild(div);\n",
- " node.appendChild(script);\n",
- "}\n",
- "\n",
- "/**\n",
- " * Handle when a new output is added\n",
- " */\n",
- "function handle_add_output(event, handle) {\n",
- " var output_area = handle.output_area;\n",
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- " var html_node = toinsert[nchildren-1].children[0];\n",
- " html_node.innerHTML = output.data[HTML_MIME_TYPE];\n",
- " var scripts = [];\n",
- " var nodelist = html_node.querySelectorAll(\"script\");\n",
- " for (var i in nodelist) {\n",
- " if (nodelist.hasOwnProperty(i)) {\n",
- " scripts.push(nodelist[i])\n",
- " }\n",
- " }\n",
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- " newScript.appendChild(document.createTextNode(oldScript.innerHTML));\n",
- " oldScript.parentNode.replaceChild(newScript, oldScript);\n",
- " });\n",
- " if (JS_MIME_TYPE in output.data) {\n",
- " toinsert[nchildren-1].children[1].textContent = output.data[JS_MIME_TYPE];\n",
- " }\n",
- " output_area._hv_plot_id = id;\n",
- " if ((window.Bokeh !== undefined) && (id in Bokeh.index)) {\n",
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- " } else {\n",
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- " } else if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n",
- " var bk_div = document.createElement(\"div\");\n",
- " bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n",
- " var script_attrs = bk_div.children[0].attributes;\n",
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- " toinsert[toinsert.length - 1].childNodes[1].setAttribute(script_attrs[i].name, script_attrs[i].value);\n",
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- "function handle_clear_output(event, handle) {\n",
- " var id = handle.cell.output_area._hv_plot_id;\n",
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- " var doc = window.Bokeh.index[id].model.document\n",
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- " // create a DOM node to render to\n",
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- " CLASS_NAME,\n",
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- " render(props, toinsert[0]);\n",
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- " }\n",
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- " events.on('output_added.OutputArea', handle_add_output);\n",
- " events.on('output_updated.OutputArea', handle_update_output);\n",
- " events.on('clear_output.CodeCell', handle_clear_output);\n",
- " events.on('delete.Cell', handle_clear_output);\n",
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- " if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n",
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- " }\n",
- " } catch(err) {\n",
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window.PyViz.plot_index[id] = Bokeh.index[id];\n } else {\n window.PyViz.plot_index[id] = null;\n }\n } else if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n var bk_div = document.createElement(\"div\");\n bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n var script_attrs = bk_div.children[0].attributes;\n for (var i = 0; i < script_attrs.length; i++) {\n toinsert[toinsert.length - 1].childNodes[1].setAttribute(script_attrs[i].name, script_attrs[i].value);\n }\n // store reference to server id on output_area\n output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n }\n}\n\n/**\n * Handle when an output is cleared or removed\n */\nfunction handle_clear_output(event, handle) {\n var id = handle.cell.output_area._hv_plot_id;\n var server_id = handle.cell.output_area._bokeh_server_id;\n if (((id === undefined) || !(id in PyViz.plot_index)) && (server_id !== undefined)) { return; }\n var comm = 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function append_mime(data, metadata, element) {\n // create a DOM node to render to\n var toinsert = this.create_output_subarea(\n metadata,\n CLASS_NAME,\n EXEC_MIME_TYPE\n );\n this.keyboard_manager.register_events(toinsert);\n // Render to node\n var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n render(props, toinsert[0]);\n element.append(toinsert);\n return toinsert\n }\n\n events.on('output_added.OutputArea', handle_add_output);\n events.on('output_updated.OutputArea', handle_update_output);\n events.on('clear_output.CodeCell', handle_clear_output);\n events.on('delete.Cell', handle_clear_output);\n events.on('kernel_ready.Kernel', handle_kernel_cleanup);\n\n OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n safe: true,\n index: 0\n });\n}\n\nif (window.Jupyter !== undefined) {\n try {\n var events = require('base/js/events');\n var OutputArea = require('notebook/js/outputarea').OutputArea;\n if 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- " }\n",
- " }\n",
- " function get_bokeh(root) {\n",
- " if (root.Bokeh === undefined) {\n",
- " return null\n",
- " } else if (root.Bokeh.version !== py_version) {\n",
- " if (root.Bokeh.versions === undefined || !root.Bokeh.versions.has(py_version)) {\n",
- "\treturn null\n",
- " }\n",
- " return root.Bokeh.versions.get(py_version);\n",
- " } else if (root.Bokeh.version === py_version) {\n",
- " return root.Bokeh\n",
- " }\n",
- " return null\n",
- " }\n",
- " function is_loaded(root) {\n",
- " var Bokeh = get_bokeh(root)\n",
- " return (Bokeh != null && Bokeh.Panel !== undefined)\n",
- " }\n",
- " if (is_loaded(root)) {\n",
- " embed_document(root);\n",
- " } else {\n",
- " var attempts = 0;\n",
- " var timer = setInterval(function(root) {\n",
- " if (is_loaded(root)) {\n",
- " clearInterval(timer);\n",
- " embed_document(root);\n",
- " } else if (document.readyState == \"complete\") {\n",
- " attempts++;\n",
- " if (attempts > 200) {\n",
- " clearInterval(timer);\n",
- "\t var Bokeh = get_bokeh(root)\n",
- "\t if (Bokeh == null || Bokeh.Panel == null) {\n",
- " console.warn(\"Panel: ERROR: Unable to run Panel code because Bokeh or Panel library is missing\");\n",
- "\t } else {\n",
- "\t console.warn(\"Panel: WARNING: Attempting to render but not all required libraries could be resolved.\")\n",
- "\t embed_document(root)\n",
- "\t }\n",
- " }\n",
- " }\n",
- " }, 25, root)\n",
- " }\n",
- "})(window);</script>"
- ]
- },
- "metadata": {
- "application/vnd.holoviews_exec.v0+json": {
- "id": "p1002"
- }
- },
- "output_type": "display_data"
- }
- ],
+ "outputs": [],
"source": [
"import pystac\n",
"from pystac.extensions.datacube import CollectionDatacubeExtension, AssetDatacubeExtension, AdditionalDimension, DatacubeExtension\n",
@@ -691,7 +53,7 @@
},
{
"cell_type": "code",
- "execution_count": 2,
+ "execution_count": null,
"id": "15ee060d-3127-4024-a1ad-6aa0648667e1",
"metadata": {},
"outputs": [],
@@ -710,7 +72,7 @@
},
{
"cell_type": "code",
- "execution_count": 3,
+ "execution_count": null,
"id": "dd6fa323-132a-4794-8c80-576933f547a0",
"metadata": {
"tags": []
@@ -732,7 +94,7 @@
},
{
"cell_type": "code",
- "execution_count": 4,
+ "execution_count": null,
"id": "e1441cd4-e94c-4902-af46-8f1af470eb6b",
"metadata": {
"tags": []
@@ -764,571 +126,10 @@
},
{
"cell_type": "code",
- "execution_count": 5,
+ "execution_count": null,
"id": "708f2cf5-79ab-49af-8067-de31d0d13ee6",
"metadata": {},
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- ".xr-attrs dt,\n",
- ".xr-attrs dd {\n",
- " padding: 0;\n",
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- " width: auto;\n",
- "}\n",
- "\n",
- ".xr-attrs dt {\n",
- " font-weight: normal;\n",
- " grid-column: 1;\n",
- "}\n",
- "\n",
- ".xr-attrs dt:hover span {\n",
- " display: inline-block;\n",
- " background: var(--xr-background-color);\n",
- " padding-right: 10px;\n",
- "}\n",
- "\n",
- ".xr-attrs dd {\n",
- " grid-column: 2;\n",
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- " word-break: break-all;\n",
- "}\n",
- "\n",
- ".xr-icon-database,\n",
- ".xr-icon-file-text2,\n",
- ".xr-no-icon {\n",
- " display: inline-block;\n",
- " vertical-align: middle;\n",
- " width: 1em;\n",
- " height: 1.5em !important;\n",
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- " stroke: currentColor;\n",
- " fill: currentColor;\n",
- "}\n",
- "</style><pre class='xr-text-repr-fallback'><xarray.Dataset> Size: 9GB\n",
- "Dimensions: (time: 10, y: 16389, x: 13693)\n",
- "Coordinates:\n",
- " * time (time) datetime64[ns] 80B 2000-01-01 ... 2090-...\n",
- " * x (x) float64 110kB 1.019e+06 ... 1.84e+06\n",
- " * y (y) float64 131kB 7.609e+05 ... 1.744e+06\n",
- "Data variables:\n",
- " albers_conical_equal_area |S64 64B ...\n",
- " urb (time, y, x) float32 9GB dask.array<chunksize=(1, 3962, 3308), meta=np.ndarray>\n",
- "Attributes: (12/32)\n",
- " Conventions: CF-1.5\n",
- " DODS.strlen: 0\n",
- " GDAL: GDAL 1.10.1, released 2013/08/26\n",
- " Metadata_Conventions: Unidata Dataset Discovery v1.0\n",
- " NCO: 4.3.8\n",
- " acknowledgement: Southeast Regional Assessment Project; Biodive...\n",
- " ... ...\n",
- " publisher_url: https://www.cida.usgs.gov/\n",
- " summary: This dataset represents the extent of urbaniza...\n",
- " time_coverage_end: 2100-01-01T00:00\n",
- " time_coverage_resolution: P10Y\n",
- " time_coverage_start: 2010-01-01T00:00\n",
- " title: Urban Growth Projection for DSL-SAMBI</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-d305a879-d8ca-4153-b40a-a1f553d1fd70' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-d305a879-d8ca-4153-b40a-a1f553d1fd70' class='xr-section-summary' title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 10</li><li><span class='xr-has-index'>y</span>: 16389</li><li><span class='xr-has-index'>x</span>: 13693</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-d4cc599b-ce84-4cc6-b1fb-f91198b43d24' class='xr-section-summary-in' type='checkbox' checked><label for='section-d4cc599b-ce84-4cc6-b1fb-f91198b43d24' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2000-01-01 ... 2090-01-01</div><input id='attrs-0cb49f8b-1c71-4035-9899-942afcf719a3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0cb49f8b-1c71-4035-9899-942afcf719a3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-17704630-2c3d-44fd-bb69-f851ee75ed4b' class='xr-var-data-in' type='checkbox'><label for='data-17704630-2c3d-44fd-bb69-f851ee75ed4b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(['2000-01-01T00:00:00.000000000', '2010-01-01T00:00:00.000000000',\n",
- " '2020-01-01T00:00:00.000000000', '2030-01-01T00:00:00.000000000',\n",
- " '2040-01-01T00:00:00.000000000', '2050-01-01T00:00:00.000000000',\n",
- " '2060-01-01T00:00:00.000000000', '2070-01-01T00:00:00.000000000',\n",
- " '2080-01-01T00:00:00.000000000', '2090-01-01T00:00:00.000000000'],\n",
- " dtype='datetime64[ns]')</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.019e+06 1.019e+06 ... 1.84e+06</div><input id='attrs-3161abe2-e6ab-49bf-a4e9-9fad095a84de' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3161abe2-e6ab-49bf-a4e9-9fad095a84de' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ded99f85-067b-430b-ad22-db8310cfafc1' class='xr-var-data-in' type='checkbox'><label for='data-ded99f85-067b-430b-ad22-db8310cfafc1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>_CoordinateAxisType :</span></dt><dd>GeoX</dd><dt><span>long_name :</span></dt><dd>x coordinate of projection</dd><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([1018838.773, 1018898.773, 1018958.773, ..., 1840238.773, 1840298.773,\n",
- " 1840358.773])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>7.609e+05 7.61e+05 ... 1.744e+06</div><input id='attrs-7cfe9655-6859-40d8-a0c3-f5382633137e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7cfe9655-6859-40d8-a0c3-f5382633137e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2948c3a4-6010-4189-9daa-fde99c3478a3' class='xr-var-data-in' type='checkbox'><label for='data-2948c3a4-6010-4189-9daa-fde99c3478a3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>_CoordinateAxisType :</span></dt><dd>GeoY</dd><dt><span>long_name :</span></dt><dd>y coordinate of projection</dd><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([ 760892.078, 760952.078, 761012.078, ..., 1744052.078, 1744112.078,\n",
- " 1744172.078])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6ef25e84-f8f4-47eb-8049-e71f6495007a' class='xr-section-summary-in' type='checkbox' checked><label for='section-6ef25e84-f8f4-47eb-8049-e71f6495007a' class='xr-section-summary' >Data variables: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>albers_conical_equal_area</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>|S64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-5d2c312e-3779-423c-9bed-2026169ce61d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5d2c312e-3779-423c-9bed-2026169ce61d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-55ebdc42-7c8c-4db1-a036-763dbd0a2036' class='xr-var-data-in' type='checkbox'><label for='data-55ebdc42-7c8c-4db1-a036-763dbd0a2036' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>GeoTransform :</span></dt><dd>1018808.773 60 0 1744202.078000002 0 -60 </dd><dt><span>false_easting :</span></dt><dd>0.0</dd><dt><span>false_northing :</span></dt><dd>0.0</dd><dt><span>grid_mapping_name :</span></dt><dd>albers_conical_equal_area</dd><dt><span>inverse_flattening :</span></dt><dd>298.2572221010002</dd><dt><span>latitude_of_projection_origin :</span></dt><dd>23.0</dd><dt><span>longitude_of_central_meridian :</span></dt><dd>-96.0</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>semi_major_axis :</span></dt><dd>6378137.0</dd><dt><span>standard_parallel :</span></dt><dd>[29.5, 45.5]</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=|S64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>urb</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 3962, 3308), meta=np.ndarray></div><input id='attrs-3eacb115-6994-437e-88c0-3dc592fceb17' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3eacb115-6994-437e-88c0-3dc592fceb17' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9266eb99-efd5-4cb0-8cc2-684ee811cc1e' class='xr-var-data-in' type='checkbox'><label for='data-9266eb99-efd5-4cb0-8cc2-684ee811cc1e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>grid_mapping :</span></dt><dd>albers_conical_equal_area</dd><dt><span>long_name :</span></dt><dd>Urban Growth SAMBI-DSL</dd><dt><span>name :</span></dt><dd>urb</dd><dt><span>units :</span></dt><dd>percent</dd></dl></div><div class='xr-var-data'><table>\n",
- " <tr>\n",
- " <td>\n",
- " <table style=\"border-collapse: collapse;\">\n",
- " <thead>\n",
- " <tr>\n",
- " <td> </td>\n",
- " <th> Array </th>\n",
- " <th> Chunk </th>\n",
- " </tr>\n",
- " </thead>\n",
- " <tbody>\n",
- " \n",
- " <tr>\n",
- " <th> Bytes </th>\n",
- " <td> 8.36 GiB </td>\n",
- " <td> 50.00 MiB </td>\n",
- " </tr>\n",
- " \n",
- " <tr>\n",
- " <th> Shape </th>\n",
- " <td> (10, 16389, 13693) </td>\n",
- " <td> (1, 3962, 3308) </td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th> Dask graph </th>\n",
- " <td colspan=\"2\"> 250 chunks in 2 graph layers </td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th> Data type </th>\n",
- " <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
- " </tr>\n",
- " </tbody>\n",
- " </table>\n",
- " </td>\n",
- " <td>\n",
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- " <!-- Vertical lines -->\n",
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- "\n",
- " <!-- Horizontal lines -->\n",
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- "\n",
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- " <text x=\"145.208528\" y=\"74.948598\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,145.208528,74.948598)\">16389</text>\n",
- " <text x=\"7.474299\" y=\"147.474299\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,7.474299,147.474299)\">10</text>\n",
- "</svg>\n",
- " </td>\n",
- " </tr>\n",
- "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-946acdfd-e63c-4162-8c43-d0f5a4ceaef1' class='xr-section-summary-in' type='checkbox' ><label for='section-946acdfd-e63c-4162-8c43-d0f5a4ceaef1' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-14279840-f629-4dee-a9c5-1e0f3d52d2db' class='xr-index-data-in' type='checkbox'/><label for='index-14279840-f629-4dee-a9c5-1e0f3d52d2db' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex(['2000-01-01', '2010-01-01', '2020-01-01', '2030-01-01',\n",
- " '2040-01-01', '2050-01-01', '2060-01-01', '2070-01-01',\n",
- " '2080-01-01', '2090-01-01'],\n",
- " dtype='datetime64[ns]', name='time', freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>x</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-bb3bf31b-2fcc-476a-9966-eaa84c37b5aa' class='xr-index-data-in' type='checkbox'/><label for='index-bb3bf31b-2fcc-476a-9966-eaa84c37b5aa' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([1018838.7729999996, 1018898.7729999996, 1018958.7729999996,\n",
- " 1019018.7729999996, 1019078.7729999996, 1019138.7729999996,\n",
- " 1019198.7729999996, 1019258.7729999996, 1019318.7729999996,\n",
- " 1019378.7729999996,\n",
- " ...\n",
- " 1839818.7729999996, 1839878.7729999996, 1839938.7729999996,\n",
- " 1839998.7729999996, 1840058.7729999996, 1840118.7729999996,\n",
- " 1840178.7729999996, 1840238.7729999996, 1840298.7729999996,\n",
- " 1840358.7729999996],\n",
- " dtype='float64', name='x', length=13693))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>y</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-4ef04c40-71db-4c51-a904-8a5f0b7fc01e' class='xr-index-data-in' type='checkbox'/><label for='index-4ef04c40-71db-4c51-a904-8a5f0b7fc01e' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([ 760892.0780000016, 760952.0780000016, 761012.0780000016,\n",
- " 761072.0780000016, 761132.0780000016, 761192.0780000016,\n",
- " 761252.0780000016, 761312.0780000016, 761372.0780000016,\n",
- " 761432.0780000016,\n",
- " ...\n",
- " 1743632.0780000016, 1743692.0780000016, 1743752.0780000016,\n",
- " 1743812.0780000016, 1743872.0780000016, 1743932.0780000016,\n",
- " 1743992.0780000016, 1744052.0780000016, 1744112.0780000016,\n",
- " 1744172.0780000016],\n",
- " dtype='float64', name='y', length=16389))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-4d0a186b-0637-4eff-bc3d-6a49c9faa481' class='xr-section-summary-in' type='checkbox' ><label for='section-4d0a186b-0637-4eff-bc3d-6a49c9faa481' class='xr-section-summary' >Attributes: <span>(32)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.5</dd><dt><span>DODS.strlen :</span></dt><dd>0</dd><dt><span>GDAL :</span></dt><dd>GDAL 1.10.1, released 2013/08/26</dd><dt><span>Metadata_Conventions :</span></dt><dd>Unidata Dataset Discovery v1.0</dd><dt><span>NCO :</span></dt><dd>4.3.8</dd><dt><span>acknowledgement :</span></dt><dd>Southeast Regional Assessment Project; Biodiversity and Spatial Information Center, North Carolina State University, Raleigh, North Carolina 27695, Curtis M. Belyea. Designing Sustainable Landscapes Project; Biodiversity and Spatial Information Center, North Carolina State University, Raleigh, North Carolina 27695, Curtis M. Belyea.</dd><dt><span>cdm_data_type :</span></dt><dd>Grid</dd><dt><span>creator_email :</span></dt><dd>cbelyea@ncsu.edu</dd><dt><span>creator_name :</span></dt><dd>Curtis M. Belyea</dd><dt><span>creator_url :</span></dt><dd>http://www.basic.ncsu.edu/</dd><dt><span>date_created :</span></dt><dd>2012-03-01</dd><dt><span>date_issued :</span></dt><dd>2012-03-01</dd><dt><span>geospatial_lat_max :</span></dt><dd>38.162486</dd><dt><span>geospatial_lat_min :</span></dt><dd>28.271632</dd><dt><span>geospatial_lon_max :</span></dt><dd>-74.980784</dd><dt><span>geospatial_lon_min :</span></dt><dd>-85.48252</dd><dt><span>history :</span></dt><dd>Original ArcGIS grids were converted to NetCDF with gdaltranslate. The data were then changed to make them appropriate for aerial summary statistics calculation; that is, noData was set to zero in the domain of the dataset, a noData mask was applied outside the modeled domain, and the original urbanization extent (which was represented as 1) was set to 100%. For information preceding this modification, see the metadata in the original ArcGIS formatted data here: https://cida.usgs.gov/thredds/catalog.html</dd><dt><span>id :</span></dt><dd>sambi_urb</dd><dt><span>institution :</span></dt><dd>ncsu</dd><dt><span>keywords :</span></dt><dd>SLEUTH, Urbanization, Prediction, Development, Growth, Model, Project Gigalopolis</dd><dt><span>license :</span></dt><dd>Freely available</dd><dt><span>naming_authority :</span></dt><dd>cida.usgs.gov</dd><dt><span>processing_level :</span></dt><dd>Model Result</dd><dt><span>project :</span></dt><dd>Southeast Regional Assessment Project</dd><dt><span>publisher_email :</span></dt><dd>cida@usgs.gov</dd><dt><span>publisher_name :</span></dt><dd>Center for Integrated Data Analytics</dd><dt><span>publisher_url :</span></dt><dd>https://www.cida.usgs.gov/</dd><dt><span>summary :</span></dt><dd>This dataset represents the extent of urbanization (for the year indicated) predicted by the model SLEUTH, developed by Dr. Keith C. Clarke, at the University of California, Santa Barbara, Department of Geography and modified by David I. Donato of the United States Geological Survey (USGS) Eastern Geographic Science Center (EGSC). Further model modification and implementation was performed at the Biodiversity and Spatial Information Center at North Carolina State University. Urban growth probability extents throughout the 21st century for the DSL-SAMBI, which encompasses the Atlantic Coastal Plain in the states of Alabama, Florida, Georgia, North Carolina, South Carolina and Virginia. This data set is not intended for site-specific analyses. Interpretations derived from its use are suited for regional and planning purposes only. These data are not intended to be used at scales larger than 1:100,000. Acknowledgment of Biodiversity and Spatial Analysis Center at North Carolina State University is appreciated.</dd><dt><span>time_coverage_end :</span></dt><dd>2100-01-01T00:00</dd><dt><span>time_coverage_resolution :</span></dt><dd>P10Y</dd><dt><span>time_coverage_start :</span></dt><dd>2010-01-01T00:00</dd><dt><span>title :</span></dt><dd>Urban Growth Projection for DSL-SAMBI</dd></dl></div></li></ul></div></div>"
- ],
- "text/plain": [
- "<xarray.Dataset> Size: 9GB\n",
- "Dimensions: (time: 10, y: 16389, x: 13693)\n",
- "Coordinates:\n",
- " * time (time) datetime64[ns] 80B 2000-01-01 ... 2090-...\n",
- " * x (x) float64 110kB 1.019e+06 ... 1.84e+06\n",
- " * y (y) float64 131kB 7.609e+05 ... 1.744e+06\n",
- "Data variables:\n",
- " albers_conical_equal_area |S64 64B ...\n",
- " urb (time, y, x) float32 9GB dask.array<chunksize=(1, 3962, 3308), meta=np.ndarray>\n",
- "Attributes: (12/32)\n",
- " Conventions: CF-1.5\n",
- " DODS.strlen: 0\n",
- " GDAL: GDAL 1.10.1, released 2013/08/26\n",
- " Metadata_Conventions: Unidata Dataset Discovery v1.0\n",
- " NCO: 4.3.8\n",
- " acknowledgement: Southeast Regional Assessment Project; Biodive...\n",
- " ... ...\n",
- " publisher_url: https://www.cida.usgs.gov/\n",
- " summary: This dataset represents the extent of urbaniza...\n",
- " time_coverage_end: 2100-01-01T00:00\n",
- " time_coverage_resolution: P10Y\n",
- " time_coverage_start: 2010-01-01T00:00\n",
- " title: Urban Growth Projection for DSL-SAMBI"
- ]
- },
- "execution_count": 5,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "outputs": [],
"source": [
"# open and view zarr dataset\n",
"fs2 = fsspec.filesystem('s3', anon=True, endpoint_url='https://usgs.osn.mghpcc.org/')\n",
@@ -1347,18 +148,10 @@
},
{
"cell_type": "code",
- "execution_count": 6,
+ "execution_count": null,
"id": "482d204d-b5b6-40e5-ac42-55b459be1097",
"metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "collection description: Urban Growth Projection for DSL-SAMBI\n"
- ]
- }
- ],
+ "outputs": [],
"source": [
"# description of STAC collection\n",
"collection_description = ds.attrs['title']\n",
@@ -1367,25 +160,12 @@
},
{
"cell_type": "code",
- "execution_count": 7,
+ "execution_count": null,
"id": "91129d65-a614-4fe4-86b6-105b1f121f55",
"metadata": {
"tags": []
},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "license in dataset attrs: \"Freely available\"\n",
- "\n",
- "For USGS data, we can use \"\u001b[1mCC0-1.0\u001b[0m\" as the license. For all other data we can use \"\u001b[1mUnlicense\u001b[0m\".\n",
- "Ref: https://spdx.org/licenses/\n",
- "\n",
- "license automatically chosen: \u001b[1mUnlicense\n"
- ]
- }
- ],
+ "outputs": [],
"source": [
"# license for dataset\n",
"collection_license = stac_helpers.license_picker(ds.attrs['license'])"
@@ -1402,18 +182,10 @@
},
{
"cell_type": "code",
- "execution_count": 9,
+ "execution_count": null,
"id": "ab91268f-7200-4cb1-979a-c7d75531d2c0",
"metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Dimension dictionary: {'X': 'x', 'Y': 'y', 'T': 'time'}\n"
- ]
- }
- ],
+ "outputs": [],
"source": [
"# dims_auto_extract = ['X', 'Y', 'T']\n",
"# dim_names_dict = {}\n",
@@ -1434,7 +206,7 @@
},
{
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- "execution_count": 10,
+ "execution_count": null,
"id": "239d3b00-77f9-4178-954b-ba81a2b34512",
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"outputs": [],
@@ -1444,7 +216,7 @@
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- "execution_count": 11,
+ "execution_count": null,
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@@ -1468,440 +240,20 @@
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- "data": {
- "text/plain": [
- "'+proj=aea +lat_0=23 +lon_0=-96 +lat_1=29.5 +lat_2=45.5 +x_0=0 +y_0=0 +ellps=GRS80 +units=m +no_defs +type=crs'"
- ]
- },
- "execution_count": 13,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "outputs": [],
"source": [
"crs.to_proj4()"
]
@@ -1925,20 +277,10 @@
},
{
"cell_type": "code",
- "execution_count": 14,
+ "execution_count": null,
"id": "d46805e0-8e94-4ebe-aa01-d9a2d7051459",
"metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "[1018838.7729999996, 760892.0780000016, 1840358.7729999996, 1744172.0780000016]\n",
- "\n",
- "spatial_bounds data type: <class 'float'>\n"
- ]
- }
- ],
+ "outputs": [],
"source": [
"# pull out lat/lon bbox for data\n",
"# coordinates must be from WGS 84 datum\n",
@@ -1954,7 +296,7 @@
},
{
"cell_type": "code",
- "execution_count": 15,
+ "execution_count": null,
"id": "f16fdb9e-7ed8-40fb-a4f1-9ecabdebc0a1",
"metadata": {},
"outputs": [],
@@ -1964,7 +306,7 @@
},
{
"cell_type": "code",
- "execution_count": 16,
+ "execution_count": null,
"id": "074fc23c-f4d9-4427-80d3-fbf691e6d411",
"metadata": {},
"outputs": [],
@@ -1975,19 +317,10 @@
},
{
"cell_type": "code",
- "execution_count": 17,
+ "execution_count": null,
"id": "5345c975-9fe3-48e1-a663-0275cdf275dc",
"metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "lower left coordinates (WGS84): -85.48217902360058, 28.271951434906544\n",
- "upper right coordinates (WGS84): -74.98118991571037, 38.16218753090247\n"
- ]
- }
- ],
+ "outputs": [],
"source": [
"print(f'lower left coordinates (WGS84): {min(lon)}, {min(lat)}')\n",
"print(f'upper right coordinates (WGS84): {max(lon)}, {max(lat)}')"
@@ -1995,7 +328,7 @@
},
{
"cell_type": "code",
- "execution_count": 18,
+ "execution_count": null,
"id": "e0a5a222-743d-403a-9411-2406374803cf",
"metadata": {},
"outputs": [],
@@ -2014,19 +347,10 @@
},
{
"cell_type": "code",
- "execution_count": 19,
+ "execution_count": null,
"id": "41a84995-867c-4152-8c57-85e3758bbb77",
"metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "min: 2000-01-01 00:00:00 \n",
- "max: 2090-01-01 00:00:00\n"
- ]
- }
- ],
+ "outputs": [],
"source": [
"# pull out first and last timestamps\n",
"temporal_extent_lower = pd.Timestamp(ds[dim_names_dict['T']].data.min())\n",
@@ -2044,7 +368,7 @@
},
{
"cell_type": "code",
- "execution_count": 20,
+ "execution_count": null,
"id": "1b1e37c4-5348-46ad-abc9-e005b5d6c02b",
"metadata": {},
"outputs": [],
@@ -2062,7 +386,7 @@
},
{
"cell_type": "code",
- "execution_count": 21,
+ "execution_count": null,
"id": "adf6c59d-58cd-48b1-a5fd-3bb205a3ef56",
"metadata": {},
"outputs": [],
@@ -2075,18 +399,10 @@
},
{
"cell_type": "code",
- "execution_count": 22,
+ "execution_count": null,
"id": "7e96811b-95ae-406a-9728-55fc429d4e1f",
"metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "new collection created\n"
- ]
- }
- ],
+ "outputs": [],
"source": [
"if catalog.get_child(collection_id):\n",
" collection = catalog.get_child(collection_id)\n",
@@ -2112,7 +428,7 @@
},
{
"cell_type": "code",
- "execution_count": 23,
+ "execution_count": null,
"id": "094832af-d22b-4359-b0f6-cf687acce5cc",
"metadata": {},
"outputs": [],
@@ -2128,7 +444,7 @@
},
{
"cell_type": "code",
- "execution_count": 24,
+ "execution_count": null,
"id": "0c298d07-f234-4a08-986d-87f4a39e9ae6",
"metadata": {
"tags": []
@@ -2154,7 +470,7 @@
},
{
"cell_type": "code",
- "execution_count": 25,
+ "execution_count": null,
"id": "fc00946d-2880-491d-9b3b-3aeeb4414d6c",
"metadata": {},
"outputs": [],
@@ -2182,33 +498,10 @@
},
{
"cell_type": "code",
- "execution_count": 26,
+ "execution_count": null,
"id": "ea452f62-5644-49b6-8a4e-7dc4f649fd1a",
"metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<Projected CRS: {\"$schema\": \"https://proj.org/schemas/v0.2/projjso ...>\n",
- "Name: undefined\n",
- "Axis Info [cartesian]:\n",
- "- E[east]: Easting (metre)\n",
- "- N[north]: Northing (metre)\n",
- "Area of Use:\n",
- "- undefined\n",
- "Coordinate Operation:\n",
- "- name: unknown\n",
- "- method: Albers Equal Area\n",
- "Datum: undefined\n",
- "- Ellipsoid: undefined\n",
- "- Prime Meridian: undefined"
- ]
- },
- "execution_count": 26,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "outputs": [],
"source": [
"# print out crs information in dataset\n",
"crs"
@@ -2216,146 +509,10 @@
},
{
"cell_type": "code",
- "execution_count": 27,
+ "execution_count": null,
"id": "1b1d05ff-8e43-44a7-8343-178b112c4ad6",
"metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "{\n",
- " \"$schema\": \"https://proj.org/schemas/v0.5/projjson.schema.json\",\n",
- " \"type\": \"ProjectedCRS\",\n",
- " \"name\": \"undefined\",\n",
- " \"base_crs\": {\n",
- " \"name\": \"undefined\",\n",
- " \"datum\": {\n",
- " \"type\": \"GeodeticReferenceFrame\",\n",
- " \"name\": \"undefined\",\n",
- " \"ellipsoid\": {\n",
- " \"name\": \"undefined\",\n",
- " \"semi_major_axis\": 6378137,\n",
- " \"inverse_flattening\": 298.257222101\n",
- " },\n",
- " \"prime_meridian\": {\n",
- " \"name\": \"undefined\",\n",
- " \"longitude\": 0\n",
- " }\n",
- " },\n",
- " \"coordinate_system\": {\n",
- " \"subtype\": \"ellipsoidal\",\n",
- " \"axis\": [\n",
- " {\n",
- " \"name\": \"Longitude\",\n",
- " \"abbreviation\": \"lon\",\n",
- " \"direction\": \"east\",\n",
- " \"unit\": \"degree\"\n",
- " },\n",
- " {\n",
- " \"name\": \"Latitude\",\n",
- " \"abbreviation\": \"lat\",\n",
- " \"direction\": \"north\",\n",
- " \"unit\": \"degree\"\n",
- " }\n",
- " ]\n",
- " }\n",
- " },\n",
- " \"conversion\": {\n",
- " \"name\": \"unknown\",\n",
- " \"method\": {\n",
- " \"name\": \"Albers Equal Area\",\n",
- " \"id\": {\n",
- " \"authority\": \"EPSG\",\n",
- " \"code\": 9822\n",
- " }\n",
- " },\n",
- " \"parameters\": [\n",
- " {\n",
- " \"name\": \"Latitude of false origin\",\n",
- " \"value\": 23,\n",
- " \"unit\": \"degree\",\n",
- " \"id\": {\n",
- " \"authority\": \"EPSG\",\n",
- " \"code\": 8821\n",
- " }\n",
- " },\n",
- " {\n",
- " \"name\": \"Longitude of false origin\",\n",
- " \"value\": -96,\n",
- " \"unit\": \"degree\",\n",
- " \"id\": {\n",
- " \"authority\": \"EPSG\",\n",
- " \"code\": 8822\n",
- " }\n",
- " },\n",
- " {\n",
- " \"name\": \"Latitude of 1st standard parallel\",\n",
- " \"value\": 29.5,\n",
- " \"unit\": \"degree\",\n",
- " \"id\": {\n",
- " \"authority\": \"EPSG\",\n",
- " \"code\": 8823\n",
- " }\n",
- " },\n",
- " {\n",
- " \"name\": \"Latitude of 2nd standard parallel\",\n",
- " \"value\": 45.5,\n",
- " \"unit\": \"degree\",\n",
- " \"id\": {\n",
- " \"authority\": \"EPSG\",\n",
- " \"code\": 8824\n",
- " }\n",
- " },\n",
- " {\n",
- " \"name\": \"Easting at false origin\",\n",
- " \"value\": 0,\n",
- " \"unit\": {\n",
- " \"type\": \"LinearUnit\",\n",
- " \"name\": \"Metre\",\n",
- " \"conversion_factor\": 1\n",
- " },\n",
- " \"id\": {\n",
- " \"authority\": \"EPSG\",\n",
- " \"code\": 8826\n",
- " }\n",
- " },\n",
- " {\n",
- " \"name\": \"Northing at false origin\",\n",
- " \"value\": 0,\n",
- " \"unit\": {\n",
- " \"type\": \"LinearUnit\",\n",
- " \"name\": \"Metre\",\n",
- " \"conversion_factor\": 1\n",
- " },\n",
- " \"id\": {\n",
- " \"authority\": \"EPSG\",\n",
- " \"code\": 8827\n",
- " }\n",
- " }\n",
- " ]\n",
- " },\n",
- " \"coordinate_system\": {\n",
- " \"subtype\": \"Cartesian\",\n",
- " \"axis\": [\n",
- " {\n",
- " \"name\": \"Easting\",\n",
- " \"abbreviation\": \"E\",\n",
- " \"direction\": \"east\",\n",
- " \"unit\": \"metre\"\n",
- " },\n",
- " {\n",
- " \"name\": \"Northing\",\n",
- " \"abbreviation\": \"N\",\n",
- " \"direction\": \"north\",\n",
- " \"unit\": \"metre\"\n",
- " }\n",
- " ]\n",
- " }\n",
- "}\n"
- ]
- }
- ],
+ "outputs": [],
"source": [
"# # the datacube extension can accept reference_system information as a numerical EPSG code, \n",
"# # WKT2 (ISO 19162) string or PROJJSON object.\n",
@@ -2392,18 +549,10 @@
},
{
"cell_type": "code",
- "execution_count": 31,
+ "execution_count": null,
"id": "82f1e9bd-52ee-46f5-9e95-c2359d95fcf3",
"metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "time step: P10Y0M0DT0H0M0S\n"
- ]
- }
- ],
+ "outputs": [],
"source": [
"#time_step = pd.Timedelta(stac_helpers.get_step(ds, dim_names_dict['T'], time_dim=True)).isoformat()\n",
"# if time is yearly or monthly, you will need to manually construct it:\n",
@@ -2413,7 +562,7 @@
},
{
"cell_type": "code",
- "execution_count": 32,
+ "execution_count": null,
"id": "64be65b2-de20-447a-a9c2-bd8eca3e440e",
"metadata": {},
"outputs": [],
@@ -2426,7 +575,7 @@
},
{
"cell_type": "code",
- "execution_count": 33,
+ "execution_count": null,
"id": "bc8dff39-2a2e-44a0-9b30-987107c2d1e2",
"metadata": {},
"outputs": [],
@@ -2448,18 +597,10 @@
},
{
"cell_type": "code",
- "execution_count": 36,
+ "execution_count": null,
"id": "a8ba7695-ca45-4db2-bd46-c465f4e37eff",
"metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "x step: 60.0\n"
- ]
- }
- ],
+ "outputs": [],
"source": [
"x_step = stac_helpers.get_step(ds, dim_names_dict['X'])\n",
"# a common issue that causes the spatial step not to be identified comes from rounding errors in the step calculation\n",
@@ -2470,7 +611,7 @@
},
{
"cell_type": "code",
- "execution_count": 37,
+ "execution_count": null,
"id": "fac4c9f2-a952-4c7f-aa32-862957372d6f",
"metadata": {},
"outputs": [],
@@ -2507,18 +648,10 @@
},
{
"cell_type": "code",
- "execution_count": 39,
+ "execution_count": null,
"id": "7405583b-ecb9-44b0-8815-048e42e55a42",
"metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "y step: 60.0\n"
- ]
- }
- ],
+ "outputs": [],
"source": [
"y_step = stac_helpers.get_step(ds, dim_names_dict['Y'])\n",
"# a common issue that causes the spatial step not to be identified comes from rounding errors in the step calculation\n",
@@ -2529,7 +662,7 @@
},
{
"cell_type": "code",
- "execution_count": 40,
+ "execution_count": null,
"id": "ece0fe37-b54c-4721-aa9b-33d2998d191b",
"metadata": {},
"outputs": [],
@@ -2544,7 +677,7 @@
},
{
"cell_type": "code",
- "execution_count": 41,
+ "execution_count": null,
"id": "abdafb8f-5217-4b82-91b6-eec8183c9128",
"metadata": {},
"outputs": [],
@@ -2579,18 +712,10 @@
},
{
"cell_type": "code",
- "execution_count": 42,
+ "execution_count": null,
"id": "acd45d3c-7845-47e6-9b7d-e35627a7ca9a",
"metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "['time', 'y', 'x']\n"
- ]
- }
- ],
+ "outputs": [],
"source": [
"dims = list(ds.dims)\n",
"print(dims)"
@@ -2598,7 +723,7 @@
},
{
"cell_type": "code",
- "execution_count": 43,
+ "execution_count": null,
"id": "5a443497-67a9-4dce-a8e9-b08d31a88223",
"metadata": {},
"outputs": [],
@@ -2619,7 +744,7 @@
},
{
"cell_type": "code",
- "execution_count": 44,
+ "execution_count": null,
"id": "8ab85b09-eb38-404c-910c-13349d5e2234",
"metadata": {},
"outputs": [],
@@ -2638,7 +763,7 @@
},
{
"cell_type": "code",
- "execution_count": 45,
+ "execution_count": null,
"id": "e9272931-fc0b-4f2a-9546-283033e9cde8",
"metadata": {},
"outputs": [],
@@ -2678,7 +803,7 @@
},
{
"cell_type": "code",
- "execution_count": 46,
+ "execution_count": null,
"id": "10141fd4-91d6-491d-878b-02653720891d",
"metadata": {},
"outputs": [],
@@ -2697,7 +822,7 @@
},
{
"cell_type": "code",
- "execution_count": 47,
+ "execution_count": null,
"id": "e2120a55-3d04-4122-a93f-29afcdb8cb1b",
"metadata": {
"tags": []
@@ -2711,7 +836,7 @@
},
{
"cell_type": "code",
- "execution_count": 48,
+ "execution_count": null,
"id": "4b75791b-6b2d-40be-b7c6-330a60888fb5",
"metadata": {},
"outputs": [],
@@ -2730,6 +855,14 @@
"metadata": {},
"outputs": [],
"source": []
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "6b112519-8b06-4e22-9dd1-d280cee88d13",
+ "metadata": {},
+ "outputs": [],
+ "source": []
}
],
"metadata": {
diff --git a/workflows/archive/serap_slamm_create_collection_from_zarr.ipynb b/workflows/archive/serap_slamm_create_collection_from_zarr.ipynb
index ebfa82d9..ef6ef4c3 100644
--- a/workflows/archive/serap_slamm_create_collection_from_zarr.ipynb
+++ b/workflows/archive/serap_slamm_create_collection_from_zarr.ipynb
@@ -19,7 +19,9 @@
"cell_type": "code",
"execution_count": null,
"id": "201e0945-de55-45ff-b095-c2af009a4e62",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"import pystac\n",
@@ -59,7 +61,9 @@
"cell_type": "code",
"execution_count": null,
"id": "15ee060d-3127-4024-a1ad-6aa0648667e1",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# name for STAC collection - should match name of zarr dataset\n",
@@ -132,7 +136,9 @@
"cell_type": "code",
"execution_count": null,
"id": "708f2cf5-79ab-49af-8067-de31d0d13ee6",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# open and view zarr dataset\n",
@@ -154,7 +160,9 @@
"cell_type": "code",
"execution_count": null,
"id": "482d204d-b5b6-40e5-ac42-55b459be1097",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# description of STAC collection\n",
@@ -188,7 +196,9 @@
"cell_type": "code",
"execution_count": null,
"id": "ab91268f-7200-4cb1-979a-c7d75531d2c0",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# dims_auto_extract = ['X', 'Y', 'T']\n",
@@ -212,7 +222,9 @@
"cell_type": "code",
"execution_count": null,
"id": "239d3b00-77f9-4178-954b-ba81a2b34512",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"crs_var = 'albers_conical_equal_area'"
@@ -222,7 +234,9 @@
"cell_type": "code",
"execution_count": null,
"id": "b03d52f3-1367-4255-a561-52ee4fc9e92d",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# use pyproj to automatically extract crs info\n",
@@ -246,7 +260,9 @@
"cell_type": "code",
"execution_count": null,
"id": "4cee13ba-487d-483e-a013-b65685137502",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"ds[crs_var]"
@@ -256,7 +272,9 @@
"cell_type": "code",
"execution_count": null,
"id": "f7bc73db-7717-450e-9679-525f7be0c910",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"crs.to_proj4()"
@@ -283,7 +301,9 @@
"cell_type": "code",
"execution_count": null,
"id": "d46805e0-8e94-4ebe-aa01-d9a2d7051459",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# pull out lat/lon bbox for data\n",
@@ -302,7 +322,9 @@
"cell_type": "code",
"execution_count": null,
"id": "f16fdb9e-7ed8-40fb-a4f1-9ecabdebc0a1",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# # uncomment if you wish to use dask\n",
@@ -313,7 +335,9 @@
"cell_type": "code",
"execution_count": null,
"id": "3020e62b",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# # choose a size for the chunks - these are square chunks that are chunk_len x chunk_len\n",
@@ -329,7 +353,9 @@
"cell_type": "code",
"execution_count": null,
"id": "917e1e92",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"transformer = Transformer.from_crs(crs, \"EPSG:4326\", always_xy=True)"
@@ -339,7 +365,9 @@
"cell_type": "code",
"execution_count": null,
"id": "074fc23c-f4d9-4427-80d3-fbf691e6d411",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# # uncomment if you wish to use dask\n",
@@ -352,7 +380,9 @@
"cell_type": "code",
"execution_count": null,
"id": "76f60290",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# #lon, lat = transformer.transform(XX.ravel(), YY.ravel())\n",
@@ -370,7 +400,9 @@
"cell_type": "code",
"execution_count": null,
"id": "668d1cbb",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# commented out because this will crash on nebari, but results from local computer are copied in the cell below\n",
@@ -389,7 +421,9 @@
"cell_type": "code",
"execution_count": null,
"id": "5345c975-9fe3-48e1-a663-0275cdf275dc",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"print(f'lower left coordinates (WGS84): {min_lon}, {min_lat}')\n",
@@ -400,11 +434,13 @@
"cell_type": "code",
"execution_count": null,
"id": "e0a5a222-743d-403a-9411-2406374803cf",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# create a spatial extent object \n",
- "spatial_extent = pystac.SpatialExtent(bboxes=[[min(lon).item(), min(lat).item(), max(lon).item(), max(lat).item()]])"
+ "spatial_extent = pystac.SpatialExtent(bboxes=[[min_lon, min_lat, max_lon, max_lat]])"
]
},
{
@@ -419,7 +455,9 @@
"cell_type": "code",
"execution_count": null,
"id": "41a84995-867c-4152-8c57-85e3758bbb77",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# pull out first and last timestamps\n",
@@ -440,7 +478,9 @@
"cell_type": "code",
"execution_count": null,
"id": "1b1e37c4-5348-46ad-abc9-e005b5d6c02b",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"collection_extent = pystac.Extent(spatial=spatial_extent, temporal=temporal_extent)"
@@ -458,7 +498,9 @@
"cell_type": "code",
"execution_count": null,
"id": "adf6c59d-58cd-48b1-a5fd-3bb205a3ef56",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# define folder location where your STAC catalog json file is\n",
@@ -471,7 +513,9 @@
"cell_type": "code",
"execution_count": null,
"id": "7e96811b-95ae-406a-9728-55fc429d4e1f",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"if catalog.get_child(collection_id):\n",
@@ -500,7 +544,9 @@
"cell_type": "code",
"execution_count": null,
"id": "094832af-d22b-4359-b0f6-cf687acce5cc",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"asset_id = \"zarr-s3-osn\"\n",
@@ -542,7 +588,9 @@
"cell_type": "code",
"execution_count": null,
"id": "fc00946d-2880-491d-9b3b-3aeeb4414d6c",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# instantiate extention on collection\n",
@@ -570,7 +618,9 @@
"cell_type": "code",
"execution_count": null,
"id": "ea452f62-5644-49b6-8a4e-7dc4f649fd1a",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# print out crs information in dataset\n",
@@ -581,7 +631,9 @@
"cell_type": "code",
"execution_count": null,
"id": "1b1d05ff-8e43-44a7-8343-178b112c4ad6",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# # the datacube extension can accept reference_system information as a numerical EPSG code, \n",
@@ -621,7 +673,9 @@
"cell_type": "code",
"execution_count": null,
"id": "82f1e9bd-52ee-46f5-9e95-c2359d95fcf3",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"#time_step = pd.Timedelta(stac_helpers.get_step(ds, dim_names_dict['T'], time_dim=True)).isoformat()\n",
@@ -634,7 +688,9 @@
"cell_type": "code",
"execution_count": null,
"id": "64be65b2-de20-447a-a9c2-bd8eca3e440e",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# # optional debugging for time steps:\n",
@@ -647,7 +703,9 @@
"cell_type": "code",
"execution_count": null,
"id": "bc8dff39-2a2e-44a0-9b30-987107c2d1e2",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# # debugging for time steps, cont:\n",
@@ -669,7 +727,9 @@
"cell_type": "code",
"execution_count": null,
"id": "a8ba7695-ca45-4db2-bd46-c465f4e37eff",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"x_step = stac_helpers.get_step(ds, dim_names_dict['X'])\n",
@@ -683,7 +743,9 @@
"cell_type": "code",
"execution_count": null,
"id": "fac4c9f2-a952-4c7f-aa32-862957372d6f",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# # optional debugging for spatial steps:\n",
@@ -698,7 +760,9 @@
"cell_type": "code",
"execution_count": null,
"id": "8d0b5a2d-dc58-4ad6-b890-859ce6bb08de",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# # debugging for spatial steps, cont:\n",
@@ -720,7 +784,9 @@
"cell_type": "code",
"execution_count": null,
"id": "7405583b-ecb9-44b0-8815-048e42e55a42",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"y_step = stac_helpers.get_step(ds, dim_names_dict['Y'])\n",
@@ -734,7 +800,9 @@
"cell_type": "code",
"execution_count": null,
"id": "ece0fe37-b54c-4721-aa9b-33d2998d191b",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# # optional debugging for spatial steps:\n",
@@ -749,7 +817,9 @@
"cell_type": "code",
"execution_count": null,
"id": "abdafb8f-5217-4b82-91b6-eec8183c9128",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# # debugging for spatial steps, cont:\n",
@@ -784,7 +854,9 @@
"cell_type": "code",
"execution_count": null,
"id": "acd45d3c-7845-47e6-9b7d-e35627a7ca9a",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"dims = list(ds.dims)\n",
@@ -795,7 +867,9 @@
"cell_type": "code",
"execution_count": null,
"id": "5a443497-67a9-4dce-a8e9-b08d31a88223",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# create a dictionary of datacube dimensions you would like to assign to this dataset\n",
@@ -816,7 +890,9 @@
"cell_type": "code",
"execution_count": null,
"id": "8ab85b09-eb38-404c-910c-13349d5e2234",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# make sure you added all the right dims\n",
@@ -835,7 +911,9 @@
"cell_type": "code",
"execution_count": null,
"id": "e9272931-fc0b-4f2a-9546-283033e9cde8",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# drop metpy_crs coordinate we have added\n",
@@ -875,7 +953,9 @@
"cell_type": "code",
"execution_count": null,
"id": "10141fd4-91d6-491d-878b-02653720891d",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# add dimesions and variables to collection extension\n",
@@ -908,7 +988,9 @@
"cell_type": "code",
"execution_count": null,
"id": "4b75791b-6b2d-40be-b7c6-330a60888fb5",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"if catalog.get_child(collection_id):\n",
@@ -929,9 +1011,9 @@
],
"metadata": {
"kernelspec": {
- "display_name": "geo",
+ "display_name": "global-global-pangeo",
"language": "python",
- "name": "python3"
+ "name": "conda-env-global-global-pangeo-py"
},
"language_info": {
"codemirror_mode": {
@@ -943,7 +1025,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.10.0"
+ "version": "3.11.6"
}
},
"nbformat": 4,
diff --git a/workflows/archive/serap_urb_create_collection_from_zarr.ipynb b/workflows/archive/serap_urb_create_collection_from_zarr.ipynb
index f527e082..15074424 100644
--- a/workflows/archive/serap_urb_create_collection_from_zarr.ipynb
+++ b/workflows/archive/serap_urb_create_collection_from_zarr.ipynb
@@ -19,7 +19,9 @@
"cell_type": "code",
"execution_count": null,
"id": "201e0945-de55-45ff-b095-c2af009a4e62",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"import pystac\n",
@@ -59,7 +61,9 @@
"cell_type": "code",
"execution_count": null,
"id": "15ee060d-3127-4024-a1ad-6aa0648667e1",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# name for STAC collection - should match name of zarr dataset\n",
@@ -132,7 +136,9 @@
"cell_type": "code",
"execution_count": null,
"id": "708f2cf5-79ab-49af-8067-de31d0d13ee6",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# open and view zarr dataset\n",
@@ -154,7 +160,9 @@
"cell_type": "code",
"execution_count": null,
"id": "482d204d-b5b6-40e5-ac42-55b459be1097",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# description of STAC collection\n",
@@ -188,7 +196,9 @@
"cell_type": "code",
"execution_count": null,
"id": "ab91268f-7200-4cb1-979a-c7d75531d2c0",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# dims_auto_extract = ['X', 'Y', 'T']\n",
@@ -212,7 +222,9 @@
"cell_type": "code",
"execution_count": null,
"id": "239d3b00-77f9-4178-954b-ba81a2b34512",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"crs_var = 'albers_conical_equal_area'"
@@ -222,7 +234,9 @@
"cell_type": "code",
"execution_count": null,
"id": "b03d52f3-1367-4255-a561-52ee4fc9e92d",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# use pyproj to automatically extract crs info\n",
@@ -246,7 +260,9 @@
"cell_type": "code",
"execution_count": null,
"id": "4cee13ba-487d-483e-a013-b65685137502",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"ds[crs_var]"
@@ -256,7 +272,9 @@
"cell_type": "code",
"execution_count": null,
"id": "f7bc73db-7717-450e-9679-525f7be0c910",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"crs.to_proj4()"
@@ -283,7 +301,9 @@
"cell_type": "code",
"execution_count": null,
"id": "d46805e0-8e94-4ebe-aa01-d9a2d7051459",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# pull out lat/lon bbox for data\n",
@@ -302,7 +322,9 @@
"cell_type": "code",
"execution_count": null,
"id": "f16fdb9e-7ed8-40fb-a4f1-9ecabdebc0a1",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# # uncomment if you wish to use dask\n",
@@ -313,7 +335,9 @@
"cell_type": "code",
"execution_count": null,
"id": "798eb059",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# # choose a size for the chunks - these are square chunks that are chunk_len x chunk_len\n",
@@ -329,7 +353,9 @@
"cell_type": "code",
"execution_count": null,
"id": "074fc23c-f4d9-4427-80d3-fbf691e6d411",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"transformer = Transformer.from_crs(crs, \"EPSG:4326\", always_xy=True)"
@@ -339,7 +365,9 @@
"cell_type": "code",
"execution_count": null,
"id": "11860480",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# # uncomment if you wish to use dask\n",
@@ -352,7 +380,9 @@
"cell_type": "code",
"execution_count": null,
"id": "54a31963",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# #lon, lat = transformer.transform(XX.ravel(), YY.ravel())\n",
@@ -370,7 +400,9 @@
"cell_type": "code",
"execution_count": null,
"id": "7aaa3402",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# commented out because this will crash on nebari, but results from local computer are copied in the cell below\n",
@@ -389,7 +421,9 @@
"cell_type": "code",
"execution_count": null,
"id": "5345c975-9fe3-48e1-a663-0275cdf275dc",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"print(f'lower left coordinates (WGS84): {min_lon}, {min_lat}')\n",
@@ -400,11 +434,13 @@
"cell_type": "code",
"execution_count": null,
"id": "e0a5a222-743d-403a-9411-2406374803cf",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# create a spatial extent object \n",
- "spatial_extent = pystac.SpatialExtent(bboxes=[[min(lon).item(), min(lat).item(), max(lon).item(), max(lat).item()]])"
+ "spatial_extent = pystac.SpatialExtent(bboxes=[[min_lon, min_lat, max_lon, max_lat]])"
]
},
{
@@ -419,7 +455,9 @@
"cell_type": "code",
"execution_count": null,
"id": "41a84995-867c-4152-8c57-85e3758bbb77",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# pull out first and last timestamps\n",
@@ -440,7 +478,9 @@
"cell_type": "code",
"execution_count": null,
"id": "1b1e37c4-5348-46ad-abc9-e005b5d6c02b",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"collection_extent = pystac.Extent(spatial=spatial_extent, temporal=temporal_extent)"
@@ -458,7 +498,9 @@
"cell_type": "code",
"execution_count": null,
"id": "adf6c59d-58cd-48b1-a5fd-3bb205a3ef56",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# define folder location where your STAC catalog json file is\n",
@@ -471,7 +513,9 @@
"cell_type": "code",
"execution_count": null,
"id": "7e96811b-95ae-406a-9728-55fc429d4e1f",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"if catalog.get_child(collection_id):\n",
@@ -500,7 +544,9 @@
"cell_type": "code",
"execution_count": null,
"id": "094832af-d22b-4359-b0f6-cf687acce5cc",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"asset_id = \"zarr-s3-osn\"\n",
@@ -542,7 +588,9 @@
"cell_type": "code",
"execution_count": null,
"id": "fc00946d-2880-491d-9b3b-3aeeb4414d6c",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# instantiate extention on collection\n",
@@ -570,7 +618,9 @@
"cell_type": "code",
"execution_count": null,
"id": "ea452f62-5644-49b6-8a4e-7dc4f649fd1a",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# print out crs information in dataset\n",
@@ -581,7 +631,9 @@
"cell_type": "code",
"execution_count": null,
"id": "1b1d05ff-8e43-44a7-8343-178b112c4ad6",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# # the datacube extension can accept reference_system information as a numerical EPSG code, \n",
@@ -621,7 +673,9 @@
"cell_type": "code",
"execution_count": null,
"id": "82f1e9bd-52ee-46f5-9e95-c2359d95fcf3",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"#time_step = pd.Timedelta(stac_helpers.get_step(ds, dim_names_dict['T'], time_dim=True)).isoformat()\n",
@@ -634,7 +688,9 @@
"cell_type": "code",
"execution_count": null,
"id": "64be65b2-de20-447a-a9c2-bd8eca3e440e",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# # optional debugging for time steps:\n",
@@ -669,7 +725,9 @@
"cell_type": "code",
"execution_count": null,
"id": "a8ba7695-ca45-4db2-bd46-c465f4e37eff",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"x_step = stac_helpers.get_step(ds, dim_names_dict['X'])\n",
@@ -683,7 +741,9 @@
"cell_type": "code",
"execution_count": null,
"id": "fac4c9f2-a952-4c7f-aa32-862957372d6f",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# # optional debugging for spatial steps:\n",
@@ -698,7 +758,9 @@
"cell_type": "code",
"execution_count": null,
"id": "8d0b5a2d-dc58-4ad6-b890-859ce6bb08de",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# # debugging for spatial steps, cont:\n",
@@ -720,7 +782,9 @@
"cell_type": "code",
"execution_count": null,
"id": "7405583b-ecb9-44b0-8815-048e42e55a42",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"y_step = stac_helpers.get_step(ds, dim_names_dict['Y'])\n",
@@ -734,7 +798,9 @@
"cell_type": "code",
"execution_count": null,
"id": "ece0fe37-b54c-4721-aa9b-33d2998d191b",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# # optional debugging for spatial steps:\n",
@@ -749,7 +815,9 @@
"cell_type": "code",
"execution_count": null,
"id": "abdafb8f-5217-4b82-91b6-eec8183c9128",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# # debugging for spatial steps, cont:\n",
@@ -784,7 +852,9 @@
"cell_type": "code",
"execution_count": null,
"id": "acd45d3c-7845-47e6-9b7d-e35627a7ca9a",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"dims = list(ds.dims)\n",
@@ -795,7 +865,9 @@
"cell_type": "code",
"execution_count": null,
"id": "5a443497-67a9-4dce-a8e9-b08d31a88223",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# create a dictionary of datacube dimensions you would like to assign to this dataset\n",
@@ -816,7 +888,9 @@
"cell_type": "code",
"execution_count": null,
"id": "8ab85b09-eb38-404c-910c-13349d5e2234",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# make sure you added all the right dims\n",
@@ -835,7 +909,9 @@
"cell_type": "code",
"execution_count": null,
"id": "e9272931-fc0b-4f2a-9546-283033e9cde8",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# drop metpy_crs coordinate we have added\n",
@@ -875,7 +951,9 @@
"cell_type": "code",
"execution_count": null,
"id": "10141fd4-91d6-491d-878b-02653720891d",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# add dimesions and variables to collection extension\n",
@@ -908,7 +986,9 @@
"cell_type": "code",
"execution_count": null,
"id": "4b75791b-6b2d-40be-b7c6-330a60888fb5",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"if catalog.get_child(collection_id):\n",
@@ -929,9 +1009,9 @@
],
"metadata": {
"kernelspec": {
- "display_name": "geo",
+ "display_name": "global-global-pangeo",
"language": "python",
- "name": "python3"
+ "name": "conda-env-global-global-pangeo-py"
},
"language_info": {
"codemirror_mode": {
@@ -943,7 +1023,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.10.0"
+ "version": "3.11.6"
}
},
"nbformat": 4,
--
GitLab