From 3a53cde749f7cfb799d7aa7e505ce5e0ff4c8e9d Mon Sep 17 00:00:00 2001
From: Abram Claycomb <aclaycomb@usgs.gov>
Date: Mon, 22 Oct 2018 15:23:59 -0600
Subject: [PATCH] flesh out testing, controller integration

---
 docs/algorithms/FilterAlgorithm.ipynb       |  246 +-
 docs/algorithms/Filter_notes.ipynb          | 4274 +------------------
 etc/filter/BOU20180901vmin.min              |   78 +
 etc/filter/BOU20180901vsec.sec              | 3649 ++++++++++++++++
 geomagio/algorithm/FilterAlgorithm.py       |   23 +-
 geomagio/algorithm/__init__.py              |    1 +
 test/algorithm_test/FilterAlgorithm_test.py |   41 +
 7 files changed, 4200 insertions(+), 4112 deletions(-)
 create mode 100644 etc/filter/BOU20180901vmin.min
 create mode 100644 etc/filter/BOU20180901vsec.sec
 create mode 100644 test/algorithm_test/FilterAlgorithm_test.py

diff --git a/docs/algorithms/FilterAlgorithm.ipynb b/docs/algorithms/FilterAlgorithm.ipynb
index 91a351d38..bc1f889bc 100644
--- a/docs/algorithms/FilterAlgorithm.ipynb
+++ b/docs/algorithms/FilterAlgorithm.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -20,7 +20,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 57,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1575,7 +1575,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1584,7 +1584,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 63,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1593,7 +1593,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 64,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [
     {
@@ -1602,7 +1602,7 @@
        "array([  0.  ,  59.88, 119.76, 179.64, 239.52, 299.4 ])"
       ]
      },
-     "execution_count": 64,
+     "execution_count": 5,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1613,7 +1613,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 65,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1622,7 +1622,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 66,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
@@ -1631,7 +1631,7 @@
        "array([  0.,  60., 120., 180., 240., 300.])"
       ]
      },
-     "execution_count": 66,
+     "execution_count": 7,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1649,7 +1649,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 65,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1658,7 +1658,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 66,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
@@ -1671,7 +1671,7 @@
        "NT.BOU.R0.SSF | 2018-10-10T00:59:15.000000Z - 2018-10-10T23:59:45.000000Z | 1.0 Hz, 82831 samples"
       ]
      },
-     "execution_count": 66,
+     "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1682,7 +1682,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 67,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [
     {
@@ -1691,7 +1691,7 @@
        "'SVH'"
       ]
      },
-     "execution_count": 67,
+     "execution_count": 10,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1709,7 +1709,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 68,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1718,7 +1718,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 69,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [
     {
@@ -1755,7 +1755,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 70,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [
     {
@@ -1777,7 +1777,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 71,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [
     {
@@ -1790,7 +1790,7 @@
        "NT.BOU.R0.MSF | 2018-10-10T01:00:00.000000Z - 2018-10-10T23:59:00.000000Z | 60.0 s, 1380 samples"
       ]
      },
-     "execution_count": 71,
+     "execution_count": 14,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1801,7 +1801,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 72,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [
     {
@@ -1823,7 +1823,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 63,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [
     {
@@ -1856,7 +1856,7 @@
        "        station_name: Boulder"
       ]
      },
-     "execution_count": 63,
+     "execution_count": 16,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1867,7 +1867,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 64,
+   "execution_count": 17,
    "metadata": {},
    "outputs": [
     {
@@ -1899,7 +1899,7 @@
        "        station_name: Boulder"
       ]
      },
-     "execution_count": 64,
+     "execution_count": 17,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2089,6 +2089,204 @@
     "np.isnan(bouf[0].data).sum()"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import geomagio.iaga2002 as i2"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "factorytest = i2.IAGA2002Writer()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "fh1=open('/Users/aclaycomb/repos/BOU20181010vsec.sec','wb')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 52,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "fhf=open('/Users/aclaycomb/repos/BOU20181010vmin.min','wb')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "factorytest.write(fh1, bou1, ('SVH', 'SVE', 'SVZ', 'SSF'))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 53,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "factorytest.write(fhf, bouf, ('MVH', 'MVE', 'MVZ', 'MSF'))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 54,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "bou2 = c.get_timeseries(channels=['SVH','SVE','SVZ','SSF'], starttime=UTCDateTime(\"2018-09-01T22:59:15Z\"), endtime=UTCDateTime(\"2018-09-01T23:59:45Z\"), observatory=\"BOU\", type=\"variation\", interval=\"second\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 55,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'SVH': 'MVH', 'SVE': 'MVE', 'SVZ': 'MVZ', 'SSF': 'MSF'}\n",
+      "(3541, 91)\n",
+      "20828.919200138072\n",
+      "20827.77731386921\n",
+      "60\n",
+      "60\n",
+      "(3541, 91)\n",
+      "-52.88243507069091\n",
+      "-44.32389226455428\n",
+      "60\n",
+      "60\n",
+      "(3541, 91)\n",
+      "47043.06023925271\n",
+      "47040.51322540838\n",
+      "60\n",
+      "60\n",
+      "(3541, 91)\n",
+      "51965.67216973773\n",
+      "51962.84290357895\n",
+      "60\n",
+      "60\n"
+     ]
+    }
+   ],
+   "source": [
+    "bou2f = filterer.process(bou2)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 57,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 800x1000 with 4 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "bou2.plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 58,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 800x1000 with 4 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "bou2f.plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 71,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "fh2=open('/Users/aclaycomb/repos/BOU20180901vsec.sec','wb')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 72,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "fh2f=open('/Users/aclaycomb/repos/BOU20180901vmin.min','wb')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 73,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "factorytest.write(fh2, bou2, ('SVH', 'SVE', 'SVZ', 'SSF'))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 74,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "factorytest.write(fh2f, bou2f, ('MVH', 'MVE', 'MVZ', 'MSF'))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 75,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "fh2.close()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 76,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "fh2f.close()"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
diff --git a/docs/algorithms/Filter_notes.ipynb b/docs/algorithms/Filter_notes.ipynb
index 9b35c85b8..37e91d791 100644
--- a/docs/algorithms/Filter_notes.ipynb
+++ b/docs/algorithms/Filter_notes.ipynb
@@ -91,7 +91,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 75,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -107,16 +107,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 76,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "[<matplotlib.lines.Line2D at 0x1c25fa6d68>]"
+       "[<matplotlib.lines.Line2D at 0x1c1a098550>]"
       ]
      },
-     "execution_count": 76,
+     "execution_count": 8,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -139,16 +139,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 77,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "[<matplotlib.lines.Line2D at 0x1c2606d400>]"
+       "[<matplotlib.lines.Line2D at 0x1c1c131780>]"
       ]
      },
-     "execution_count": 77,
+     "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -171,16 +171,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 78,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "[<matplotlib.lines.Line2D at 0x1c260bde10>]"
+       "[<matplotlib.lines.Line2D at 0x1c1c24eb38>]"
       ]
      },
-     "execution_count": 78,
+     "execution_count": 10,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -203,7 +203,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 79,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -212,16 +212,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 80,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "[<matplotlib.lines.Line2D at 0x1c2571b048>]"
+       "[<matplotlib.lines.Line2D at 0x1c1c2a9cc0>]"
       ]
      },
-     "execution_count": 80,
+     "execution_count": 12,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -245,7 +245,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 81,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -254,7 +254,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 82,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [
     {
@@ -344,7 +344,7 @@
        "       891., 892., 893., 894., 895., 896., 897., 898., 899., 900.])"
       ]
      },
-     "execution_count": 82,
+     "execution_count": 14,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -355,7 +355,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 83,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [
     {
@@ -364,7 +364,7 @@
        "901"
       ]
      },
-     "execution_count": 83,
+     "execution_count": 15,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -375,7 +375,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 84,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [
     {
@@ -384,7 +384,7 @@
        "991"
       ]
      },
-     "execution_count": 84,
+     "execution_count": 16,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -395,7 +395,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 85,
+   "execution_count": 17,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -406,7 +406,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 86,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [
     {
@@ -416,7 +416,7 @@
      "traceback": [
       "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
       "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
-      "\u001b[0;32m<ipython-input-86-1f8b0065d365>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0;32mfor\u001b[0m \u001b[0mi\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mt\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mt_filt\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m     \u001b[0mt\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mt\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m     \u001b[0mhf\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mone_minute_gauss_filter\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mh\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0;36m60\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0;36m60\u001b[0m\u001b[0;34m+\u001b[0m\u001b[0;36m91\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m<ipython-input-18-1f8b0065d365>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0;32mfor\u001b[0m \u001b[0mi\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mt\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mt_filt\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m     \u001b[0mt\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mt\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m     \u001b[0mhf\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mone_minute_gauss_filter\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mh\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0;36m60\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0;36m60\u001b[0m\u001b[0;34m+\u001b[0m\u001b[0;36m91\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
       "\u001b[0;31mTypeError\u001b[0m: 'numpy.float64' object is not iterable"
      ]
     }
@@ -429,7 +429,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 87,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [
     {
@@ -519,7 +519,7 @@
        "       891., 892., 893., 894., 895., 896., 897., 898., 899., 900.])"
       ]
      },
-     "execution_count": 87,
+     "execution_count": 19,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -532,7 +532,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 88,
+   "execution_count": 20,
    "metadata": {},
    "outputs": [
     {
@@ -622,7 +622,7 @@
        "       981., 982., 983., 984., 985., 986., 987., 988., 989., 990.])"
       ]
      },
-     "execution_count": 88,
+     "execution_count": 20,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -633,7 +633,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 89,
+   "execution_count": 21,
    "metadata": {},
    "outputs": [
     {
@@ -643,7 +643,7 @@
      "traceback": [
       "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
       "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
-      "\u001b[0;32m<ipython-input-89-6664f3db0770>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0;32mfor\u001b[0m \u001b[0mi\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mhf\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m     \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m<ipython-input-21-6664f3db0770>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0;32mfor\u001b[0m \u001b[0mi\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mhf\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m     \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
       "\u001b[0;31mTypeError\u001b[0m: 'int' object is not iterable"
      ]
     }
@@ -655,7 +655,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 90,
+   "execution_count": 22,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -664,7 +664,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 91,
+   "execution_count": 23,
    "metadata": {},
    "outputs": [
     {
@@ -673,7 +673,7 @@
        "(901, 91)"
       ]
      },
-     "execution_count": 91,
+     "execution_count": 23,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -688,7 +688,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 92,
+   "execution_count": 24,
    "metadata": {},
    "outputs": [
     {
@@ -697,7 +697,7 @@
        "(901, 91)"
       ]
      },
-     "execution_count": 92,
+     "execution_count": 24,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -708,7 +708,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 93,
+   "execution_count": 25,
    "metadata": {},
    "outputs": [
     {
@@ -717,7 +717,7 @@
        "(8, 8)"
       ]
      },
-     "execution_count": 93,
+     "execution_count": 25,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -728,7 +728,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 94,
+   "execution_count": 26,
    "metadata": {},
    "outputs": [
     {
@@ -743,7 +743,7 @@
        "       [9156.089, 9156.107, 9156.129, ..., 9158.807, 9158.818, 9158.832]])"
       ]
      },
-     "execution_count": 94,
+     "execution_count": 26,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -754,7 +754,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 95,
+   "execution_count": 27,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -763,7 +763,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 96,
+   "execution_count": 28,
    "metadata": {},
    "outputs": [
     {
@@ -997,7 +997,7 @@
        "       9158.39531688])"
       ]
      },
-     "execution_count": 96,
+     "execution_count": 28,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1008,7 +1008,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 97,
+   "execution_count": 29,
    "metadata": {},
    "outputs": [
     {
@@ -1017,7 +1017,7 @@
        "(901,)"
       ]
      },
-     "execution_count": 97,
+     "execution_count": 29,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1028,7 +1028,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 98,
+   "execution_count": 30,
    "metadata": {
     "scrolled": true
    },
@@ -1036,11 +1036,11 @@
     {
      "data": {
       "text/plain": [
-       "[<matplotlib.lines.Line2D at 0x1c256f0668>,\n",
-       " <matplotlib.lines.Line2D at 0x1c256f07f0>]"
+       "[<matplotlib.lines.Line2D at 0x1c1c3ffe48>,\n",
+       " <matplotlib.lines.Line2D at 0x1c1c406128>]"
       ]
      },
-     "execution_count": 98,
+     "execution_count": 30,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -1063,7 +1063,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 99,
+   "execution_count": 31,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1072,7 +1072,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 100,
+   "execution_count": 32,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1081,7 +1081,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 121,
+   "execution_count": 33,
    "metadata": {},
    "outputs": [
     {
@@ -1093,7 +1093,7 @@
        "       9156.09298106, 9157.78661802, 9156.74486717, 9158.39531688])"
       ]
      },
-     "execution_count": 121,
+     "execution_count": 33,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1104,7 +1104,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 101,
+   "execution_count": 34,
    "metadata": {},
    "outputs": [
     {
@@ -1131,17 +1131,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 102,
+   "execution_count": 35,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "[<matplotlib.lines.Line2D at 0x1c26399358>,\n",
-       " <matplotlib.lines.Line2D at 0x1c263994e0>]"
+       "[<matplotlib.lines.Line2D at 0x1c1c5c1cc0>,\n",
+       " <matplotlib.lines.Line2D at 0x1c1c5c1e48>]"
       ]
      },
-     "execution_count": 102,
+     "execution_count": 35,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -1165,17 +1165,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 103,
+   "execution_count": 36,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "[<matplotlib.lines.Line2D at 0x1c2645a278>,\n",
-       " <matplotlib.lines.Line2D at 0x1c2645a400>]"
+       "[<matplotlib.lines.Line2D at 0x1c1c621ba8>,\n",
+       " <matplotlib.lines.Line2D at 0x1c1c621d30>]"
       ]
      },
-     "execution_count": 103,
+     "execution_count": 36,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -1199,7 +1199,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 104,
+   "execution_count": 37,
    "metadata": {},
    "outputs": [
     {
@@ -1373,7 +1373,7 @@
        "       9158.832])"
       ]
      },
-     "execution_count": 104,
+     "execution_count": 37,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1384,7 +1384,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 105,
+   "execution_count": 38,
    "metadata": {},
    "outputs": [
     {
@@ -1393,7 +1393,7 @@
        "9156.74486717354"
       ]
      },
-     "execution_count": 105,
+     "execution_count": 38,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1404,7 +1404,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 106,
+   "execution_count": 39,
    "metadata": {},
    "outputs": [
     {
@@ -1413,7 +1413,7 @@
        "655928"
       ]
      },
-     "execution_count": 106,
+     "execution_count": 39,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1424,7 +1424,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 107,
+   "execution_count": 40,
    "metadata": {},
    "outputs": [
     {
@@ -1433,7 +1433,7 @@
        "7928"
       ]
      },
-     "execution_count": 107,
+     "execution_count": 40,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1444,7 +1444,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 108,
+   "execution_count": 41,
    "metadata": {},
    "outputs": [
     {
@@ -1453,7 +1453,7 @@
        "82.73562058526741"
       ]
      },
-     "execution_count": 108,
+     "execution_count": 41,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1464,7 +1464,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 109,
+   "execution_count": 42,
    "metadata": {},
    "outputs": [
     {
@@ -1473,7 +1473,7 @@
        "62969088"
       ]
      },
-     "execution_count": 109,
+     "execution_count": 42,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1484,7 +1484,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 110,
+   "execution_count": 43,
    "metadata": {},
    "outputs": [
     {
@@ -1493,7 +1493,7 @@
        "1952041728"
       ]
      },
-     "execution_count": 110,
+     "execution_count": 43,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1504,7 +1504,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 111,
+   "execution_count": 44,
    "metadata": {},
    "outputs": [
     {
@@ -1513,7 +1513,7 @@
        "1296000"
       ]
      },
-     "execution_count": 111,
+     "execution_count": 44,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1524,7 +1524,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 112,
+   "execution_count": 45,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1533,7 +1533,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 113,
+   "execution_count": 46,
    "metadata": {},
    "outputs": [
     {
@@ -1557,7 +1557,7 @@
        "       9158.832])"
       ]
      },
-     "execution_count": 113,
+     "execution_count": 46,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1568,7 +1568,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 114,
+   "execution_count": 47,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1586,7 +1586,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 115,
+   "execution_count": 48,
    "metadata": {},
    "outputs": [
     {
@@ -1595,7 +1595,7 @@
        "array([9157.58185583,           nan])"
       ]
      },
-     "execution_count": 115,
+     "execution_count": 48,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1606,7 +1606,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 116,
+   "execution_count": 49,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1622,7 +1622,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 117,
+   "execution_count": 50,
    "metadata": {},
    "outputs": [
     {
@@ -1633,7 +1633,7 @@
        "       fill_value=999999)"
       ]
      },
-     "execution_count": 117,
+     "execution_count": 50,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1644,7 +1644,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 118,
+   "execution_count": 51,
    "metadata": {},
    "outputs": [
     {
@@ -1653,7 +1653,7 @@
        "1"
       ]
      },
-     "execution_count": 118,
+     "execution_count": 51,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1664,7 +1664,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 119,
+   "execution_count": 52,
    "metadata": {},
    "outputs": [
     {
@@ -1673,7 +1673,7 @@
        "array([9157.58185583, 9158.39741188])"
       ]
      },
-     "execution_count": 119,
+     "execution_count": 52,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1689,7 +1689,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 120,
+   "execution_count": 53,
    "metadata": {},
    "outputs": [
     {
@@ -1702,7 +1702,7 @@
        "       0, 0, 0])"
       ]
      },
-     "execution_count": 120,
+     "execution_count": 53,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1715,7 +1715,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 50,
+   "execution_count": 54,
    "metadata": {
     "scrolled": true
    },
@@ -1726,7 +1726,7 @@
        "81.9"
       ]
      },
-     "execution_count": 50,
+     "execution_count": 54,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1737,7 +1737,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 51,
+   "execution_count": 55,
    "metadata": {},
    "outputs": [
     {
@@ -1746,7 +1746,7 @@
        "-1"
       ]
      },
-     "execution_count": 51,
+     "execution_count": 55,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1757,7 +1757,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 52,
+   "execution_count": 56,
    "metadata": {
     "scrolled": true
    },
@@ -1768,7 +1768,7 @@
        "1"
       ]
      },
-     "execution_count": 52,
+     "execution_count": 56,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1779,7 +1779,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 53,
+   "execution_count": 57,
    "metadata": {},
    "outputs": [
     {
@@ -1788,7 +1788,7 @@
        "0"
       ]
      },
-     "execution_count": 53,
+     "execution_count": 57,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1799,7 +1799,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 54,
+   "execution_count": 58,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1808,7 +1808,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 55,
+   "execution_count": 59,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1822,7 +1822,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 56,
+   "execution_count": 60,
    "metadata": {},
    "outputs": [
     {
@@ -1831,7 +1831,7 @@
        "2018-09-19T00:00:00.000000Z"
       ]
      },
-     "execution_count": 56,
+     "execution_count": 60,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1842,7 +1842,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 57,
+   "execution_count": 61,
    "metadata": {},
    "outputs": [
     {
@@ -1851,7 +1851,7 @@
        "'second'"
       ]
      },
-     "execution_count": 57,
+     "execution_count": 61,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1862,7 +1862,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 58,
+   "execution_count": 62,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1871,7 +1871,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 59,
+   "execution_count": 63,
    "metadata": {},
    "outputs": [
     {
@@ -1880,7 +1880,7 @@
        "(901,)"
       ]
      },
-     "execution_count": 59,
+     "execution_count": 63,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1891,7 +1891,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 60,
+   "execution_count": 64,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1905,7 +1905,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 61,
+   "execution_count": 65,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1914,7 +1914,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 62,
+   "execution_count": 66,
    "metadata": {},
    "outputs": [
     {
@@ -1923,7 +1923,7 @@
        "(9199,)"
       ]
      },
-     "execution_count": 62,
+     "execution_count": 66,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1934,7 +1934,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 63,
+   "execution_count": 67,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1943,810 +1943,30 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 64,
+   "execution_count": 68,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "application/javascript": [
-       "/* Put everything inside the global mpl namespace */\n",
-       "window.mpl = {};\n",
-       "\n",
-       "\n",
-       "mpl.get_websocket_type = function() {\n",
-       "    if (typeof(WebSocket) !== 'undefined') {\n",
-       "        return WebSocket;\n",
-       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
-       "        return MozWebSocket;\n",
-       "    } else {\n",
-       "        alert('Your browser does not have WebSocket support.' +\n",
-       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
-       "              'Firefox 4 and 5 are also supported but you ' +\n",
-       "              'have to enable WebSockets in about:config.');\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
-       "    this.id = figure_id;\n",
-       "\n",
-       "    this.ws = websocket;\n",
-       "\n",
-       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
-       "\n",
-       "    if (!this.supports_binary) {\n",
-       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
-       "        if (warnings) {\n",
-       "            warnings.style.display = 'block';\n",
-       "            warnings.textContent = (\n",
-       "                \"This browser does not support binary websocket messages. \" +\n",
-       "                    \"Performance may be slow.\");\n",
-       "        }\n",
-       "    }\n",
-       "\n",
-       "    this.imageObj = new Image();\n",
-       "\n",
-       "    this.context = undefined;\n",
-       "    this.message = undefined;\n",
-       "    this.canvas = undefined;\n",
-       "    this.rubberband_canvas = undefined;\n",
-       "    this.rubberband_context = undefined;\n",
-       "    this.format_dropdown = undefined;\n",
-       "\n",
-       "    this.image_mode = 'full';\n",
-       "\n",
-       "    this.root = $('<div/>');\n",
-       "    this._root_extra_style(this.root)\n",
-       "    this.root.attr('style', 'display: inline-block');\n",
-       "\n",
-       "    $(parent_element).append(this.root);\n",
-       "\n",
-       "    this._init_header(this);\n",
-       "    this._init_canvas(this);\n",
-       "    this._init_toolbar(this);\n",
-       "\n",
-       "    var fig = this;\n",
-       "\n",
-       "    this.waiting = false;\n",
-       "\n",
-       "    this.ws.onopen =  function () {\n",
-       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
-       "            fig.send_message(\"send_image_mode\", {});\n",
-       "            if (mpl.ratio != 1) {\n",
-       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
-       "            }\n",
-       "            fig.send_message(\"refresh\", {});\n",
-       "        }\n",
-       "\n",
-       "    this.imageObj.onload = function() {\n",
-       "            if (fig.image_mode == 'full') {\n",
-       "                // Full images could contain transparency (where diff images\n",
-       "                // almost always do), so we need to clear the canvas so that\n",
-       "                // there is no ghosting.\n",
-       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
-       "            }\n",
-       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
-       "        };\n",
-       "\n",
-       "    this.imageObj.onunload = function() {\n",
-       "        fig.ws.close();\n",
-       "    }\n",
-       "\n",
-       "    this.ws.onmessage = this._make_on_message_function(this);\n",
-       "\n",
-       "    this.ondownload = ondownload;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_header = function() {\n",
-       "    var titlebar = $(\n",
-       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
-       "        'ui-helper-clearfix\"/>');\n",
-       "    var titletext = $(\n",
-       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
-       "        'text-align: center; padding: 3px;\"/>');\n",
-       "    titlebar.append(titletext)\n",
-       "    this.root.append(titlebar);\n",
-       "    this.header = titletext[0];\n",
-       "}\n",
-       "\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_canvas = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var canvas_div = $('<div/>');\n",
-       "\n",
-       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
-       "\n",
-       "    function canvas_keyboard_event(event) {\n",
-       "        return fig.key_event(event, event['data']);\n",
-       "    }\n",
-       "\n",
-       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
-       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
-       "    this.canvas_div = canvas_div\n",
-       "    this._canvas_extra_style(canvas_div)\n",
-       "    this.root.append(canvas_div);\n",
-       "\n",
-       "    var canvas = $('<canvas/>');\n",
-       "    canvas.addClass('mpl-canvas');\n",
-       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
-       "\n",
-       "    this.canvas = canvas[0];\n",
-       "    this.context = canvas[0].getContext(\"2d\");\n",
-       "\n",
-       "    var backingStore = this.context.backingStorePixelRatio ||\n",
-       "\tthis.context.webkitBackingStorePixelRatio ||\n",
-       "\tthis.context.mozBackingStorePixelRatio ||\n",
-       "\tthis.context.msBackingStorePixelRatio ||\n",
-       "\tthis.context.oBackingStorePixelRatio ||\n",
-       "\tthis.context.backingStorePixelRatio || 1;\n",
-       "\n",
-       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
-       "\n",
-       "    var rubberband = $('<canvas/>');\n",
-       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
-       "\n",
-       "    var pass_mouse_events = true;\n",
-       "\n",
-       "    canvas_div.resizable({\n",
-       "        start: function(event, ui) {\n",
-       "            pass_mouse_events = false;\n",
-       "        },\n",
-       "        resize: function(event, ui) {\n",
-       "            fig.request_resize(ui.size.width, ui.size.height);\n",
-       "        },\n",
-       "        stop: function(event, ui) {\n",
-       "            pass_mouse_events = true;\n",
-       "            fig.request_resize(ui.size.width, ui.size.height);\n",
-       "        },\n",
-       "    });\n",
-       "\n",
-       "    function mouse_event_fn(event) {\n",
-       "        if (pass_mouse_events)\n",
-       "            return fig.mouse_event(event, event['data']);\n",
-       "    }\n",
-       "\n",
-       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
-       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
-       "    // Throttle sequential mouse events to 1 every 20ms.\n",
-       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
-       "\n",
-       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
-       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
-       "\n",
-       "    canvas_div.on(\"wheel\", function (event) {\n",
-       "        event = event.originalEvent;\n",
-       "        event['data'] = 'scroll'\n",
-       "        if (event.deltaY < 0) {\n",
-       "            event.step = 1;\n",
-       "        } else {\n",
-       "            event.step = -1;\n",
-       "        }\n",
-       "        mouse_event_fn(event);\n",
-       "    });\n",
-       "\n",
-       "    canvas_div.append(canvas);\n",
-       "    canvas_div.append(rubberband);\n",
-       "\n",
-       "    this.rubberband = rubberband;\n",
-       "    this.rubberband_canvas = rubberband[0];\n",
-       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
-       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
-       "\n",
-       "    this._resize_canvas = function(width, height) {\n",
-       "        // Keep the size of the canvas, canvas container, and rubber band\n",
-       "        // canvas in synch.\n",
-       "        canvas_div.css('width', width)\n",
-       "        canvas_div.css('height', height)\n",
-       "\n",
-       "        canvas.attr('width', width * mpl.ratio);\n",
-       "        canvas.attr('height', height * mpl.ratio);\n",
-       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
-       "\n",
-       "        rubberband.attr('width', width);\n",
-       "        rubberband.attr('height', height);\n",
-       "    }\n",
-       "\n",
-       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
-       "    // upon first draw.\n",
-       "    this._resize_canvas(600, 600);\n",
-       "\n",
-       "    // Disable right mouse context menu.\n",
-       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
-       "        return false;\n",
-       "    });\n",
-       "\n",
-       "    function set_focus () {\n",
-       "        canvas.focus();\n",
-       "        canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    window.setTimeout(set_focus, 100);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_toolbar = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var nav_element = $('<div/>')\n",
-       "    nav_element.attr('style', 'width: 100%');\n",
-       "    this.root.append(nav_element);\n",
-       "\n",
-       "    // Define a callback function for later on.\n",
-       "    function toolbar_event(event) {\n",
-       "        return fig.toolbar_button_onclick(event['data']);\n",
-       "    }\n",
-       "    function toolbar_mouse_event(event) {\n",
-       "        return fig.toolbar_button_onmouseover(event['data']);\n",
-       "    }\n",
-       "\n",
-       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
-       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
-       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
-       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
-       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
-       "\n",
-       "        if (!name) {\n",
-       "            // put a spacer in here.\n",
-       "            continue;\n",
-       "        }\n",
-       "        var button = $('<button/>');\n",
-       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
-       "                        'ui-button-icon-only');\n",
-       "        button.attr('role', 'button');\n",
-       "        button.attr('aria-disabled', 'false');\n",
-       "        button.click(method_name, toolbar_event);\n",
-       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
-       "\n",
-       "        var icon_img = $('<span/>');\n",
-       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
-       "        icon_img.addClass(image);\n",
-       "        icon_img.addClass('ui-corner-all');\n",
-       "\n",
-       "        var tooltip_span = $('<span/>');\n",
-       "        tooltip_span.addClass('ui-button-text');\n",
-       "        tooltip_span.html(tooltip);\n",
-       "\n",
-       "        button.append(icon_img);\n",
-       "        button.append(tooltip_span);\n",
-       "\n",
-       "        nav_element.append(button);\n",
-       "    }\n",
-       "\n",
-       "    var fmt_picker_span = $('<span/>');\n",
-       "\n",
-       "    var fmt_picker = $('<select/>');\n",
-       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
-       "    fmt_picker_span.append(fmt_picker);\n",
-       "    nav_element.append(fmt_picker_span);\n",
-       "    this.format_dropdown = fmt_picker[0];\n",
-       "\n",
-       "    for (var ind in mpl.extensions) {\n",
-       "        var fmt = mpl.extensions[ind];\n",
-       "        var option = $(\n",
-       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
-       "        fmt_picker.append(option)\n",
-       "    }\n",
-       "\n",
-       "    // Add hover states to the ui-buttons\n",
-       "    $( \".ui-button\" ).hover(\n",
-       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
-       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
-       "    );\n",
-       "\n",
-       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
-       "    nav_element.append(status_bar);\n",
-       "    this.message = status_bar[0];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
-       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
-       "    // which will in turn request a refresh of the image.\n",
-       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.send_message = function(type, properties) {\n",
-       "    properties['type'] = type;\n",
-       "    properties['figure_id'] = this.id;\n",
-       "    this.ws.send(JSON.stringify(properties));\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.send_draw_message = function() {\n",
-       "    if (!this.waiting) {\n",
-       "        this.waiting = true;\n",
-       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
-       "    var format_dropdown = fig.format_dropdown;\n",
-       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
-       "    fig.ondownload(fig, format);\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
-       "    var size = msg['size'];\n",
-       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
-       "        fig._resize_canvas(size[0], size[1]);\n",
-       "        fig.send_message(\"refresh\", {});\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
-       "    var x0 = msg['x0'] / mpl.ratio;\n",
-       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
-       "    var x1 = msg['x1'] / mpl.ratio;\n",
-       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
-       "    x0 = Math.floor(x0) + 0.5;\n",
-       "    y0 = Math.floor(y0) + 0.5;\n",
-       "    x1 = Math.floor(x1) + 0.5;\n",
-       "    y1 = Math.floor(y1) + 0.5;\n",
-       "    var min_x = Math.min(x0, x1);\n",
-       "    var min_y = Math.min(y0, y1);\n",
-       "    var width = Math.abs(x1 - x0);\n",
-       "    var height = Math.abs(y1 - y0);\n",
-       "\n",
-       "    fig.rubberband_context.clearRect(\n",
-       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
-       "\n",
-       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
-       "    // Updates the figure title.\n",
-       "    fig.header.textContent = msg['label'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
-       "    var cursor = msg['cursor'];\n",
-       "    switch(cursor)\n",
-       "    {\n",
-       "    case 0:\n",
-       "        cursor = 'pointer';\n",
-       "        break;\n",
-       "    case 1:\n",
-       "        cursor = 'default';\n",
-       "        break;\n",
-       "    case 2:\n",
-       "        cursor = 'crosshair';\n",
-       "        break;\n",
-       "    case 3:\n",
-       "        cursor = 'move';\n",
-       "        break;\n",
-       "    }\n",
-       "    fig.rubberband_canvas.style.cursor = cursor;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
-       "    fig.message.textContent = msg['message'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
-       "    // Request the server to send over a new figure.\n",
-       "    fig.send_draw_message();\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
-       "    fig.image_mode = msg['mode'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Called whenever the canvas gets updated.\n",
-       "    this.send_message(\"ack\", {});\n",
-       "}\n",
-       "\n",
-       "// A function to construct a web socket function for onmessage handling.\n",
-       "// Called in the figure constructor.\n",
-       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
-       "    return function socket_on_message(evt) {\n",
-       "        if (evt.data instanceof Blob) {\n",
-       "            /* FIXME: We get \"Resource interpreted as Image but\n",
-       "             * transferred with MIME type text/plain:\" errors on\n",
-       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
-       "             * to be part of the websocket stream */\n",
-       "            evt.data.type = \"image/png\";\n",
-       "\n",
-       "            /* Free the memory for the previous frames */\n",
-       "            if (fig.imageObj.src) {\n",
-       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
-       "                    fig.imageObj.src);\n",
-       "            }\n",
-       "\n",
-       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
-       "                evt.data);\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
-       "            fig.imageObj.src = evt.data;\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        var msg = JSON.parse(evt.data);\n",
-       "        var msg_type = msg['type'];\n",
-       "\n",
-       "        // Call the  \"handle_{type}\" callback, which takes\n",
-       "        // the figure and JSON message as its only arguments.\n",
-       "        try {\n",
-       "            var callback = fig[\"handle_\" + msg_type];\n",
-       "        } catch (e) {\n",
-       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        if (callback) {\n",
-       "            try {\n",
-       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
-       "                callback(fig, msg);\n",
-       "            } catch (e) {\n",
-       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
-       "            }\n",
-       "        }\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
-       "mpl.findpos = function(e) {\n",
-       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
-       "    var targ;\n",
-       "    if (!e)\n",
-       "        e = window.event;\n",
-       "    if (e.target)\n",
-       "        targ = e.target;\n",
-       "    else if (e.srcElement)\n",
-       "        targ = e.srcElement;\n",
-       "    if (targ.nodeType == 3) // defeat Safari bug\n",
-       "        targ = targ.parentNode;\n",
-       "\n",
-       "    // jQuery normalizes the pageX and pageY\n",
-       "    // pageX,Y are the mouse positions relative to the document\n",
-       "    // offset() returns the position of the element relative to the document\n",
-       "    var x = e.pageX - $(targ).offset().left;\n",
-       "    var y = e.pageY - $(targ).offset().top;\n",
-       "\n",
-       "    return {\"x\": x, \"y\": y};\n",
-       "};\n",
-       "\n",
-       "/*\n",
-       " * return a copy of an object with only non-object keys\n",
-       " * we need this to avoid circular references\n",
-       " * http://stackoverflow.com/a/24161582/3208463\n",
-       " */\n",
-       "function simpleKeys (original) {\n",
-       "  return Object.keys(original).reduce(function (obj, key) {\n",
-       "    if (typeof original[key] !== 'object')\n",
-       "        obj[key] = original[key]\n",
-       "    return obj;\n",
-       "  }, {});\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
-       "    var canvas_pos = mpl.findpos(event)\n",
-       "\n",
-       "    if (name === 'button_press')\n",
-       "    {\n",
-       "        this.canvas.focus();\n",
-       "        this.canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    var x = canvas_pos.x * mpl.ratio;\n",
-       "    var y = canvas_pos.y * mpl.ratio;\n",
-       "\n",
-       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
-       "                             step: event.step,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "\n",
-       "    /* This prevents the web browser from automatically changing to\n",
-       "     * the text insertion cursor when the button is pressed.  We want\n",
-       "     * to control all of the cursor setting manually through the\n",
-       "     * 'cursor' event from matplotlib */\n",
-       "    event.preventDefault();\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    // Handle any extra behaviour associated with a key event\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.key_event = function(event, name) {\n",
-       "\n",
-       "    // Prevent repeat events\n",
-       "    if (name == 'key_press')\n",
-       "    {\n",
-       "        if (event.which === this._key)\n",
-       "            return;\n",
-       "        else\n",
-       "            this._key = event.which;\n",
-       "    }\n",
-       "    if (name == 'key_release')\n",
-       "        this._key = null;\n",
-       "\n",
-       "    var value = '';\n",
-       "    if (event.ctrlKey && event.which != 17)\n",
-       "        value += \"ctrl+\";\n",
-       "    if (event.altKey && event.which != 18)\n",
-       "        value += \"alt+\";\n",
-       "    if (event.shiftKey && event.which != 16)\n",
-       "        value += \"shift+\";\n",
-       "\n",
-       "    value += 'k';\n",
-       "    value += event.which.toString();\n",
-       "\n",
-       "    this._key_event_extra(event, name);\n",
-       "\n",
-       "    this.send_message(name, {key: value,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
-       "    if (name == 'download') {\n",
-       "        this.handle_save(this, null);\n",
-       "    } else {\n",
-       "        this.send_message(\"toolbar_button\", {name: name});\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
-       "    this.message.textContent = tooltip;\n",
-       "};\n",
-       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
-       "\n",
-       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
-       "\n",
-       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
-       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
-       "    // object with the appropriate methods. Currently this is a non binary\n",
-       "    // socket, so there is still some room for performance tuning.\n",
-       "    var ws = {};\n",
-       "\n",
-       "    ws.close = function() {\n",
-       "        comm.close()\n",
-       "    };\n",
-       "    ws.send = function(m) {\n",
-       "        //console.log('sending', m);\n",
-       "        comm.send(m);\n",
-       "    };\n",
-       "    // Register the callback with on_msg.\n",
-       "    comm.on_msg(function(msg) {\n",
-       "        //console.log('receiving', msg['content']['data'], msg);\n",
-       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
-       "        ws.onmessage(msg['content']['data'])\n",
-       "    });\n",
-       "    return ws;\n",
-       "}\n",
-       "\n",
-       "mpl.mpl_figure_comm = function(comm, msg) {\n",
-       "    // This is the function which gets called when the mpl process\n",
-       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
-       "\n",
-       "    var id = msg.content.data.id;\n",
-       "    // Get hold of the div created by the display call when the Comm\n",
-       "    // socket was opened in Python.\n",
-       "    var element = $(\"#\" + id);\n",
-       "    var ws_proxy = comm_websocket_adapter(comm)\n",
-       "\n",
-       "    function ondownload(figure, format) {\n",
-       "        window.open(figure.imageObj.src);\n",
-       "    }\n",
-       "\n",
-       "    var fig = new mpl.figure(id, ws_proxy,\n",
-       "                           ondownload,\n",
-       "                           element.get(0));\n",
-       "\n",
-       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
-       "    // web socket which is closed, not our websocket->open comm proxy.\n",
-       "    ws_proxy.onopen();\n",
-       "\n",
-       "    fig.parent_element = element.get(0);\n",
-       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
-       "    if (!fig.cell_info) {\n",
-       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
-       "        return;\n",
-       "    }\n",
-       "\n",
-       "    var output_index = fig.cell_info[2]\n",
-       "    var cell = fig.cell_info[0];\n",
-       "\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
-       "    var width = fig.canvas.width/mpl.ratio\n",
-       "    fig.root.unbind('remove')\n",
-       "\n",
-       "    // Update the output cell to use the data from the current canvas.\n",
-       "    fig.push_to_output();\n",
-       "    var dataURL = fig.canvas.toDataURL();\n",
-       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
-       "    // the notebook keyboard shortcuts fail.\n",
-       "    IPython.keyboard_manager.enable()\n",
-       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
-       "    fig.close_ws(fig, msg);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
-       "    fig.send_message('closing', msg);\n",
-       "    // fig.ws.close()\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
-       "    // Turn the data on the canvas into data in the output cell.\n",
-       "    var width = this.canvas.width/mpl.ratio\n",
-       "    var dataURL = this.canvas.toDataURL();\n",
-       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Tell IPython that the notebook contents must change.\n",
-       "    IPython.notebook.set_dirty(true);\n",
-       "    this.send_message(\"ack\", {});\n",
-       "    var fig = this;\n",
-       "    // Wait a second, then push the new image to the DOM so\n",
-       "    // that it is saved nicely (might be nice to debounce this).\n",
-       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_toolbar = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var nav_element = $('<div/>')\n",
-       "    nav_element.attr('style', 'width: 100%');\n",
-       "    this.root.append(nav_element);\n",
-       "\n",
-       "    // Define a callback function for later on.\n",
-       "    function toolbar_event(event) {\n",
-       "        return fig.toolbar_button_onclick(event['data']);\n",
-       "    }\n",
-       "    function toolbar_mouse_event(event) {\n",
-       "        return fig.toolbar_button_onmouseover(event['data']);\n",
-       "    }\n",
-       "\n",
-       "    for(var toolbar_ind in mpl.toolbar_items){\n",
-       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
-       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
-       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
-       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
-       "\n",
-       "        if (!name) { continue; };\n",
-       "\n",
-       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
-       "        button.click(method_name, toolbar_event);\n",
-       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
-       "        nav_element.append(button);\n",
-       "    }\n",
-       "\n",
-       "    // Add the status bar.\n",
-       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
-       "    nav_element.append(status_bar);\n",
-       "    this.message = status_bar[0];\n",
-       "\n",
-       "    // Add the close button to the window.\n",
-       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
-       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
-       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
-       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
-       "    buttongrp.append(button);\n",
-       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
-       "    titlebar.prepend(buttongrp);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(el){\n",
-       "    var fig = this\n",
-       "    el.on(\"remove\", function(){\n",
-       "\tfig.close_ws(fig, {});\n",
-       "    });\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
-       "    // this is important to make the div 'focusable\n",
-       "    el.attr('tabindex', 0)\n",
-       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
-       "    // off when our div gets focus\n",
-       "\n",
-       "    // location in version 3\n",
-       "    if (IPython.notebook.keyboard_manager) {\n",
-       "        IPython.notebook.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "    else {\n",
-       "        // location in version 2\n",
-       "        IPython.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    var manager = IPython.notebook.keyboard_manager;\n",
-       "    if (!manager)\n",
-       "        manager = IPython.keyboard_manager;\n",
-       "\n",
-       "    // Check for shift+enter\n",
-       "    if (event.shiftKey && event.which == 13) {\n",
-       "        this.canvas_div.blur();\n",
-       "        event.shiftKey = false;\n",
-       "        // Send a \"J\" for go to next cell\n",
-       "        event.which = 74;\n",
-       "        event.keyCode = 74;\n",
-       "        manager.command_mode();\n",
-       "        manager.handle_keydown(event);\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
-       "    fig.ondownload(fig, null);\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.find_output_cell = function(html_output) {\n",
-       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
-       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
-       "    // IPython event is triggered only after the cells have been serialised, which for\n",
-       "    // our purposes (turning an active figure into a static one), is too late.\n",
-       "    var cells = IPython.notebook.get_cells();\n",
-       "    var ncells = cells.length;\n",
-       "    for (var i=0; i<ncells; i++) {\n",
-       "        var cell = cells[i];\n",
-       "        if (cell.cell_type === 'code'){\n",
-       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
-       "                var data = cell.output_area.outputs[j];\n",
-       "                if (data.data) {\n",
-       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
-       "                    data = data.data;\n",
-       "                }\n",
-       "                if (data['text/html'] == html_output) {\n",
-       "                    return [cell, data, j];\n",
-       "                }\n",
-       "            }\n",
-       "        }\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "// Register the function which deals with the matplotlib target/channel.\n",
-       "// The kernel may be null if the page has been refreshed.\n",
-       "if (IPython.notebook.kernel != null) {\n",
-       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
-       "}\n"
-      ],
       "text/plain": [
-       "<IPython.core.display.Javascript object>"
+       "[<matplotlib.lines.Line2D at 0x1c1c770c50>]"
       ]
      },
+     "execution_count": 68,
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "execute_result"
     },
     {
      "data": {
-      "text/html": [
-       "<img 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TzW01RQAddrwxfNWIgCkJWCedhMRS8AEgHrEBfkC4Mr+zZGXAFCo33uhsHUJWGcA/ODuamhXWU8HkACQloBDvavIAQylEDmAAgqFR1HfJWCdAsN9AXBFv+bIl0M/B7BsgRyY+lyj8GiQLtyFFQB1CvfwdQDfv7sqbq0c64Liqf8TvjGAOu3451GfHEByAHnaTUQ4gPfXLYoh7SsK1d8rhW8GQH0Cw30BcHm/ZojJkdkrj07oPq1LwDoDoE5uvy8AvndXVdwWrykADmyJ6Kx6pHzieVEQABIA8rQbAkAh1dwvTAB4PQ/g8r7NEBNFAOh+K3T3F60OoM4A+O5dVXE7AaC7jc8jv0YASAAo1FS91oCsu4Dvq1sUQzVxAGln4HUAXNa3GfJrAoDPfrcGvyUngi6TPwemPa/nErBOALjr2Bk0HT0v5b3+zp1V0L5KIaH3vFcKf7NsH/r+cr2v65Tzk+cZeW385qljqDIUAxhKoQiKAbS6At3rFMWwDnosAdPOwOuDwtI+zVAgWg8H0AqAt+TPjunPNxbo7d4qWmvETBxNPhdWp3APAsDrfV2nnJ88vZMAkBxAnnbj2SVgKwDeW6cIhneoJFR/rxT2BUCddwYu6dMUBaOzeOXRCd2nFQBLx2THjBf0BECd3H5fAHy7WxV0qKqnA6hTzk+eFwUBIAEgT7shABRSzf3CBIDXXYHFvZsiNicBoPut0N1ftDqAOgPgW93icUfVOHfFT6Vf810CJgAM/iAIAAkAhbqq1xqQ1QG8p3YRjLhDTwdQ59QQi3o3RSENAbBUTHbM1NQB1Cncw9cBHNM1Hh2r6QmAOiV95xnIvTZ+89QxVBmKAQylUITGAN5duwhe1RQAdU4NsfCVBMTlyirQ6r1T1LoEXDJfNsx6sYl3bl7wTq0OoE7hHr4AOLpLPDpV1xMAdUr6ztNdCADJAeRpNxGxBEwAqGdusAW9ElA4NwGgUMf3QGECwKSH9GaXeHQmAPRAi3X/FgkACQCFWp3XGpB1CfiuWkUwsqOeS8A65wbTFQBL5MuG2Zo6gDqFe/g6gKM6V0aXGoWF3vNeKewbA6jTqT88z8hr4zdPHUOVoSXgUApF6BLwXbUKY2THygK1905R300gOuUG8z0eav7LCSiSRz8HsETebJj9kp5LwDq5/b4A+EbnyuiqKQDqdOoPz2hEAEgOIE+7iYglYJ0AkHKDXd8FPO/lJiiaJ5tQu/dK4We+XYPf1x00b5cAUA+3f+exM2hmSQT9RqfK6FpTDwfw62V70e+XjSndkwAw+JuKAJAAUGgs81oDssYF3VmzMF7rpIcDSAB4HQDnvtQExfLqB4DF82bDHI0cwJojZuJYciJoncI9fAHw9U6V0K1mEaH3vFcK3wSAGh37yPOMvDZ+89QxVBlaAg6lUAQtAVsBsFuNwni9s54AqHNyWAOCDBjS4bI6gMXyZMXclxN0qLZZxxsBUJ9wD18AfK1jJdxZS08A1OnYR56OTQBIDiBPu/HsEjABYNKj0xkAZ7/YGCXyZRdq914pTAB4wXxUOoV7+AKgsdHNcEB1uHwdQAJAWgIO1e7JAQylUIQ6gF1rxOGNzvECtfdOUd8lYJ1PB5j1YmOU1BAAi+bJinmaOoA6hXv4AqCR69TYBKPD5QuAOp37zfN8yQEkBxAffvghRo0ahUOHDqFChQp4++230bBhQ1vtyWsNyOoAdqkeh1Fd9ARAnU8HME7DME7F0OGyOoBFcmfF/F56LgHrFO7hC4Aj7qiIe2oX1aG5wxcAdTr3m+cBe2385qljqDJaO4Dff/89unfvbkJg/fr18cknn2Ds2LHYvHkzihQJPWv0WgMiAEzqDnoDYCOUiskR6r0QEX8nAExaAtYZAId3qIh76xAARkSHllwJr43fkqtvfp3WAFi7dm1Uq1YNH330UYq25cqVQ4cOHTBy5MiQenutAVkBsFax3Pjhsbo31fHn1Qfw48oD+PCeasiVLWNIDbzwAd8l4KHtK+C+usVuuvXBv2/CuYuX8XqnykiTJo0XqhbyHn2Tw854vhFK578RAM9euIzHvlqFlhUKwDg3NlIuKwAaddrzWrubqrbx70QM+WMTXmldFjWK5Y6Uqt+wCaR28dz4/tGb+/pPqw7gf6siq6/7OoC925TFY41L+u3r/128gtc6VYqYvu7rAC7u3RSxPud+n7lwGY9/tQqtKhTQBowDdWqvjd8qXk7aAuDFixeRNWtW/Pjjj7jjjjtStH322Wexdu1azJs37ya9L1y4AOMfu4wGVLhwYSQmJiIqKkrF85H6nVYANL44Pi76pu9fdyDR/G/G8UnGMUqRcPkCoL+6X7xyDVsOnTKrG0nLpL4A6K/u7JkHgiSvtgFfAAzW3iOt7tZdwKH6eiQ5hL4A6K/uFy5fxdbDp81mHUm74n0BUKe+zvOOIgDU2AE8ePAgChUqhEWLFqFevXop7efVV1/FhAkTsG3btptnjYMHY8iQITf9d68CYLBOkz8qE5b1bc7Tr8KujL9BIdhN+nPJwq5SNm/I36AQrKg/l8zmT4Xdx57+dg3+SE4EbefmIqnuvgAYrP6FcmbBot5N7UgU9p/ZcfQMmo+5efIe6MYjaVPUV0v3ov+v1xNBh3pYkdTeQ9XV398JAAkAsXjxYtSte315ZMSIEZg4cSK2bt16U5vxugNoHRTSp02DT++rflMdHxi/0vxvL7a4BU83K83Tr8KujC8AtqtcEJ2qFbrhPq9cBR7+MqnukXReri8AGjFRsTkz31D339cexK9rk07MiKRBwRcAv+hRI2B7j86SAesGtQy7tst7QzWGz8TxM0mrFRnTpcXH3asFrPvLrcrgyYRSvD8VVuV8AbBNxQLoUiMuYF9f+EoC4nJFxtGIvgBoHIOXN/uNYTy/rjmYcjpOJPV1nkZIAKgxAPIsAfs2Mq81IAaARnb8DlULIVP6dDf1m57jlmPOtmOIpCOUGABmSp8WPz1eDxVio/zG/ZTpPwXG8lAkAmDD0nkxqnM8CkTfCH9GA1i3/yTaf7AIkeQEGfViAHhP7SJ4qWUZvzGtH8/bidembEXHaoUwpmsVnnEkLMswADT6cfuqsX77eo9xyzF32zGM6lwZXSLkvFwGgDkyp8fvTzUImPT8lv5TcDHC+joDwOpFc2F0l3i/J/6s2fcv7vhwccT1dZ5O6LXxm6eOocpoGwNoCGNsAqlevbq5C5hd5cuXR/v27SNyEwgDwMnPNET5WP8xiw+MX4HZW49GJACGcnnKD5yKcxevRCQAtqqQH590v9kBM9r9+gMncfv7kQuAg24rj571i/t9F34ybydGRjAATnm2IcoV9N/X2WQvEgEwZ9YMWDswsKNbbsBU/Hcpsvo6A8DWFQrg4+43r+4YHWDt/pPoEIGTvVCg4+/vBIAaO4BGg2BpYD7++GNzGfjTTz/FZ599hk2bNqFo0dC7Ib3WgJwAYCSdockcQLsAOP/lBBTJExnLQmwJ2A4AxkZnxuI+zXjepWFZhjmAtgCwaiGM6RZ5DqAdADSWCrtGmANIAOgfACPV7ed5AXlt/OapY6gyWjuAhjiG+/fGG2+YiaArVqyIt956C40aNQqlm/l3rzUgOwD44PgVmLX1KCLpDE27AFhh4FScvXgF815ugqJ5IuO8XDsAuOFAIm57fyEKRmfGEs0A8NP5O/Hq5K24o2ohvKUZAEai28+WgEMBIHP7I2myZ8cBZAAYaZM9WwO2z4e8Nn7z1DFUGe0BMJRAwf7utQZkBwAfmrACM7ccRSSdoWkXACsOmgYjT9bcl5r4jZ8RaSupVdYOABq58G59byEKRGXG0r56OYCfzd+FEZO3oEOVWLx9Z9XUekzSf5fFAAZzANlkL5LcfrsAGImTPTsAyMI9Im2yx9OBvDZ+89QxVBkCwFAKBfm71xoQAWDwnZ4EgASAAq+DsCpKABg8BlBXAIxUt5+n83lt/OapY6gyBIChFNIOAFdi5pYjiKRD1JkrECoGsNKgaTh94XJEJYdlrkCwGEDmAEZS7kej2z71zWr8uf4QgsUAjl2wC8MnbUH7KrF4RzMHkLn9kRTusePoaTQfMx+hloAjcbI3celeDPh1I4JtAmEAGGluP88wTgCo+SYQnkZjLeO1BsQcwGDLQkYuvBmbjyCSDlG3DYCDp+H0+cuY/WJjlMiXXbR5hEV5O8tCmw4mot27CxGTIxOW94uM5N9WABx8W3n0CLALmAHg7fGxePeuyFsCnvpcQ5Qt4H8X8EMTkiZ7kRTuYRcAI3GyxwDQyH340b3+N4FE6mSP52XrtfGbp46hypADGEqhCHIA7SwLPfLlSkzXFAArD56GUxoC4OaDp9D23QVaAuDnC3dj2J+bEXkAOAPHz1xEMABkkz0tATB5shdJR8ERADobzAkAyQF01mJ8Pu21BuQEAI0TI+6tEzoVjpCALhW2GxjOADASj4cKtizEADBfjkxYoZkDyADwtvhYvBdRDqB9AIyscI+kJeBcWTNgTZA8gJUi0O23A4CR6vbzDCVeG7956hiqDDmAoRTSzAF8dOJKTNt0BMM6VER3zQAwfsh0JP53CTNfaIxSMfosAW85dApt3lmAvNkzYWV/vZaAv1i4G0P/3IxbKxfE+3fffFyawOshVYvWGB4aACPT7bcHgJE42XMCgJE22ePpbASA5ADytJuUMl5rQHYcwMcmrsLUTYe1BMAqQ6fj5Dn9AHDr4VNo/baeADhu0W4M+UNPAGSTvciK97UHgGyyF0luvx0AjFS3n2cg99r4zVPHUGXIAQylkGYOYAoAtq+A7nWLCagTPkXtLgFfB8BGKBWTI3wqIHAndjaBXAfAjFjZv4XAr4VXUbYLONgmEAaA7SoXxAeaOYAMACMr3MMZAEaS228HACPV7ed58xAAkgPI024i2gF8/KtVmLLxMIa2r4D7NAPAqkOn499zlzDj+UYonV8fANx2+DRavT0febJlxKoBegHg+EW7MfiPzWhXqSA+uEevJeDIdPvtAWAkTvacAWBkTfZ4BnICQAJAnnYT0QD4xNerMHmDngBYbdgM/HP2onYAuP3IabR8S08AnLB4Dwb9vklLAGSTvciK97UHgGyyN/OFyHH77QBgpLr9PAM5ASABIE+70QIAh9xeAffXi5QlYHvJYRkATn++EW6JEAfQTnJYBoC5s2XE6ghyAJ/8ZjUmrT+EYEvADADbViqAD+/xnztN6CWRSoXtbAJJAcAICvf468hptHgr9C7gSHT7Jy7ZgwG/bUKwPICR6vbzdDMCQAJAnnbjeQAMlhvsya9XY9KG4IOmkGipUNhuctjqw2bgxNmLmPZcI5QpEBlLwHZcAbuDZio8OqGfZAAYbDLz5ZI9GBhi0BS6iVQqzAAwWFuORLffbluOyMleMgAGm8wwAIy0yR5PNyMAJADkaTceBsDQqSHsuCZCoqVCYbsAaGfQTIXbF/pJOwDI9AmVO03oRlKhsB0AtOOapMKtC/+knckMm+xFUryvXQBk+kSU228DACPV7efpMASABIA87UYLAAx2fqqQaKlQ2C7g2Fk2S4XbF/pJJwAY6vxUoRtJhcJOADBYouxUuHXhn3QCgJEU7sEAMJTDZUcf4Yfg8hewyUwwB9AuILt866nycwSABIBCDc9rDcgO4LDUGQNvLY8HGhQX0idcCtsHwJk4fuYCgp2VHC51snsf9gDwDJqPmYfoLBmwblBLu18d9p+zBYBL92LArxvRqkJ+fNK9RtjXye4N2gGcSHT77QKgnXehXa3D5XN2ANDuaki41EnlfXht/FahBeUBFFDVaw3Izkvv6W/X4I91B6EjANYcMRPHTusHgDuPnUGz0XoCIMuTqCMA2smTKPB6TJWi9gEwabIXLB46VSog8KMEgM7E89r47ax29j5NAGhPJ7+f8loDcgKAA24tjwc1cwAZAE5+piHKx0YJtIzwKWrHAWQAGJU5PdYPbhU+Ny94J3YcQAaALcvnx6f36eUAMgCMpHAPpwAYUW6/jRhAlhQ/0t/Dk/UAACAASURBVNx+nleF18ZvnjqGKkMAGEqhIH/3WgOyA4DPfLsGv687iP7tyuGhhiUE1AmfonaXgGuNmImjpy9g0jMNUCE2OnwqIHAndgBw17EzaDp6HnJkTo8NmgHg18v2ot8vG9GifH58phkARqLbbxcAI3KyZwMAI3Wyx/OK9Nr4zVPHUGUIAEMppBkAPvvdGvy2Vk8ArP3qTBw5pR8A7j5+FglvztUSAL9Ztg99f9mgJQCyyV4khXvYBUA22Ysot58A0NFoTgBIm0AcNRjfD3utAdlxACMRAO3ufGMA+OfTDVCxUIQ4gDaSw6YAYKb02DAkgpaAk3NaBtvlygCwebn8GHu/XkvADAAjKdzDbpqTSHT7WU7LYLuAI9Xt5xnIvTZ+89QxVBlyAEMpFIEOYLDksM99twa/rj2Ifm3L4eFG6peA/z75n+k8RWXOIPAkghe1C4B1Xp2Fw6fOww0AvHr1GtYdOIlyBaOQOUM6ZXW3Exi+5/hZNHlzLrJnSo+NLgDg+UtXYBxKHx+XE2nTplFWdzt57r5dvg99ft6A5uViMPb+msruhX3x6fOXcOr8ZRTKmUXpb9nJc+f2ZM/ohzmzZkS+HJmU1d0uALo52XOrrzMADHautduTvctXrmLPibMomS870qRR19d5GhQBIDmAPO0mpYzXGpCd1BDPf78Wv6z52xUAPJx4HnVGzjL13PNaO6FnEaywXQCsO3IWDiW6A4DsZV2reG788GhdZXW3A4B7T5xF41HuAeDdny3F4p0nlO80twOA3y3fh94uAmCJPpNw9RqwuHdTxCqEQDsnXbDJnhvxvvv/OYeGb8xR3tftAqCbkz123GCdErnx3SPq+no4AuDDX67EjM1H8HqnSuhWs4iy9xzPF3tt/OapY6gy5ACGUiiCHEAnANi3bVk80qikgDqhi07deAiPfbVa+aBgNy6IAeAfTzVApTi1S8Ct356PrYdPK6+7EwDMljEdNg1tHfrBCX6iWO9J5jeUyJcNs19sIvhtgYs7AcBmZWPweQ/1DiCr+7t3VcXt8bHK6h5uADh5wyE88bX6vs4AME+2jFgV5FxrNwGw5VvzsP3IGeV93Q4Auu32s/ZeKiY7Zr7QWFl75/liAkByAHnaTUQ7gC98vxY/r/kbfdqUxaON1QLgtE2H8ejEVcpfjHYBsN7IWTiYeB6/P1UfleNyCrWNUIXbvLPAXAZV7X7aAcB9J86h0ag5yJoxHTa7CIDF82bDnJdSFwC/X7EPr/y0AU3LxuALFwHwnTuroH2VQqGaCfff7QCgm26/W5M9uwAYiZM9OwDI3P5Im+zxdBQCQAJAnnYT2QD4w1r8vNodADSWBowlAtUQZBcA6782G0ZMohsA2O7dBdh0MDwAkC3PuQ2ARfNkxbyXE4T6YLDCdhzAH1bsR6+f1rsOgG91i8cdVeOU1d0OALLJnhvxvm5N9uwCIJvsueH2uzXZswOAbLLnNgCqnuzxdCQCQAJAnnajBQD2blMWjyl2AGdtOYIHJ4QfAP72ZH3EF1brAN723kJs+DtROfzacQAZAGbJkA5bhrm3BFw4dxYs6NVUqA/KAsCEMvkwrmctZffCvpgtiY3uEo9O1cMDAN0I93BrsucUACNpsucEACNtssfTcQkACQB52o0WAPhyqzJ4MqEUlu/+B2v2/YtHGpWQvotrztaj6Dl+hann3JeamLvFmpSJEXom/grbdQBZcthfn6yPKoVz4oeV+2GcjtG6YkHp99T+/YVYdyAJAI1NIMYOXBWnjzgBQObEGrt0xy7YhYSyMUoSYjMIKhidGYNuq4BqRXIiJiqzdI1tOYAr96PX/9aDBegf+Pccflx5APfXK4bc2TJKvydWdyP1ilF/Y+lZxS5wJw7gK63L4vEmJc2+vnb/v3i4ofy+bp3sqezrdgGwxvCko+DYZM9wgqOyZEDrigWkP3PrZO/7R+qYv2Ps/pd92QFA3804bvV1Y9e70earFc2JmBzy+zqPlgSABIA87SaiAZANUEYlH6hfHF8s2m3WV8WS1dxtR9FjXBIAsuvbh+ugbsk8Qs/Ft7BdALTW/dbKBfHn+kPmV/01og0ypEsr9Z7af7AI6/afvOE7d73aVnpaFDsAyJaFjJu5t04RfLV0X8p9qdidbdXZ+CFVzqMdABz8+yaMX7zHrK9x9OHnC5PauwGlPz9RX+ozN77Mt+6G3sM7VJL+O3YAMFBff7tbFXSoKjc+0TrZY5X97pE6qFNCbl+3C4DWurerXBCTkvv6jhFtkF5yX7cCIKv77pFtpU+o7QAgiwFMrb7uVqopOx2KAJAA0E47CfgZrzUgO7uAfQcoVvk7qhbCW92qCOnlW3jOtqPo6QOAxiBszBRlXnZTQwSq++ahrZA1Y3qZt3QTCBhfvm14a2RKLzcnoJ3ksJsPnkLbdxf4rZ8bAGj8sIrfeeLrVZi84TCGtq+A++oW81s/thnA3x9V3JO/Nqbid5wCoLX+navH4c0u8VLbu9UBZF9srCr0bVtO6u9sO3ward6ej1C7gAP19S1DWyNLRrl90N9vqZhUsnQzwfIAbvw7Ebe+tzDi+jpPI/La+M1Tx1BlKA1MKIWC/N1rDchOctjKg6eZiWqN64kmJfHh3J3m/1YRJ+TPFWBLzwKP5aaiTgHQSFlwS/7sJjwY16YhrZAtk3oA3DqstfTlQDuugHVZyIj7/Hhe0jNXBWZuQRADwGHtK6B7AAB8e+Z2vD3zL7OuxjLoR8nt3et1ZwA44/lGKJ0/h9/uVGnQNJy+cHNfV5EXcObmI3goecMXu5lercvgiSalZHZ1OAXA0jHZzSTFUzcl9XW3Jnvbh7dBxvRyVxVSALByQXxwdzW/ulrd/kjq6zyNyGvjN08dQ5UhAAylUAQBoB1XwNwFu/Yg7q5VBNFZM4DtjP3svhrmeakyr9lbj+CB8UmbQNg1rmdNJEiOA7QLgCv3/IPNh06he52iuHD5KsoOmGrelnE6hrF0IfPyB0GpBYBGvX5efcCMeTNiMBmYl8ibDbMVpGnxrXv+qExY1re5THnN77IDgEYMlAHJRixeqZgcGPjbRny5ZK8Z/jDwNrlOtHFPvnXvUa8YBt9eQXrdqw6djn/PXUIwAEzp67WLIDpLBjA39PP7a6BZObl93R8Aju9ZU3rMr10ANPq6kYbp3jpFcf7SVZQbmNTX3ZrsqXD77QCgUcefVh1A3hyZ0PiWfGDOrKqcnL7tvUBUZizt20x6e+f5QgJAWgLmaTcpZbzWgOwAoK8gHT5YhLX7T0I1ABqwsev4WagEwFDLQta6G2CgEwBa685iMysWisKfTzcU6iP+CvsOCsaGG2PjjezLDgD6/ubIKVvwybxdeKhBcfSXHIrgDwANF8bYcS/7sgOAvr/J4lJVA6ABG7uOnYVKAMybPSNW9m9hS1ZrX9cBAK2isMlepULR+OPpBrb0cvIh375etUhO/KIgttbJPbHPem385qljqDLkAIZSKMjfvdaARADw0+7V0bKC3B1yVgewZL5s2HnsLMb1qGnuPpV52Q0MDwSAGwa3RA7JZxX7cwBVxB/ZWQL21ZoBYIXYKEx6Rj0AGil3jN2Ysi8RAFQRi+oPAB9tXAJ92siNgzN+RwQAx95XA80lu/3WNDBGiMWOo2eUTPaYA8gLgF52++06gP4A0OuTPZ53h9fGb546hipDABhKIc0B8I4PF2HNvpP4pHt1tJIMgNZNIGxQ+KJHDTQtK3f5iQcAL1y+gjL9k5aF1g9uiSgXAFBF/BEPAM7bfgz3f7Ec5QtGYfKzLgBgXDR+e0q++8ADgK9N2WrGQLq1BPxooxLoI3kjBC8AqnT7rZtAjPha42g0FZM9UQB0a7KnItyDCwCTN+J5fbLHM4wTANISME+7SSnjtQbE4wB2/HARVisCQPayNgSNj4s28+KFCwBevHwVt/SfogwAR0/fhvdm77ih/YULAM7ffgz3KQRAttEoR6b05iYE49mHCwC+PnWruRFENQAaaWaMfhVOAMgmeyrCPbYePoXWbyftNDeWG40k6OECgNbJngoAfHPaNrw/58a+Hi4AqNrtrzBwKs5evIIcmdPj9PnLZoJ9FW4/z0DutfGbp46hypADGEohzR1ABoAf31tdepJU6+aMwrmymACoIv6IxwG0AuC6QS3NIHmZF3PmjBMo5mw7Zn61ivgjHgeQAaCRrHaKAgeQOXOs7pXjovF7mDiADAB71i9mJqmWfbGlWVZ3FalQeB1ABoAqwj2szlzB6CwmAKqY7PE4gKrdfubMWfu6inAPHgeQAaAqt/+xiavMHdas7qomezz9lACQHECedqOVA9jpo8VYtfdffHxvNeknYtwAgLmzmomRVcQf2d0ZaG0Ml65cRel+SQ7guoEtzR3RMi8GZsbu09lbj5pfrSL+yE5uMN96LfjrGLp/vhxlC+TA1Ocayay2+V0MAFndVQWgP/7VKkzZeBjB0sD4Vu6NqVvN1Eeqd+eyuj/csDj6tZO/25gnBtANt9+IzYvNmQXrFU32mNPoJAZQ9WSP9UFrX1fh9o9ftBuD/9gMI7F1oDQwvu2dhXuomuwxAGR1VzXZ43lJEQASAPK0G88DYLDUEL6CdP5oMVa6AIBFcmc1dxuHCwBevnIVpVwAwGZlYzDLDQB0MCgs/Os47v18mXIAZHVXDoAdKpqpfexco6ZtxQdz1AMgq7tqAJz5QiMzvY2di032VMT7Wp0541gwVW4/DwDeMNlT4PYzALT2dZUAaJxi9H6APIC+7UC1288AkNWdANBOT3TvM7QELKC112YQdpLDBgLAj+6phjaV5J6Ja3UAGQCqiD/icQCtALh2YAvkzCr3XFjmAFoHBRXxRzzLQm4DoKodiCkOYBgDoKp0M8wB5AFAFeEe/gBQxWRPGAAVuP3+AFBFuAdzAHkAUJXb7wuAqiZ7PMO418ZvnjqGKkMAGEqhIH/3WgPiWRbq8vFirNjzLz68pxraKgTAonmymruNVcYfOckDeOXqNZTsO9l8+msGtECubGoAsHm5GMzckrQErGK3MQ8ALtpxHPeMXYYy+XNg2vPqloBZ3VXtQOQBQBawf3/dohjSvqLA28F/UdYHWd1VpZupMnQ6Tp67BCcAqNLtvwEAcyWFe6iY7PEAoOrJHuuD1r6uItyDBwBVh3swAGR1VzXZ4+moXhu/eeoYqgwBYCiFNAfArh8vwfI9/ygHwGJ5spq7IlUCoJO4oKtXr6GEKwCYHzO3HAkrAFy84zjudgUAk+oeTgDIdmerB8CkuocTALLJnop4XysAxuVKCvdQC4CZsLK/vdNlrJM9FW7/dQC83tfDBQBVu/3XATCp7gSAAsChoCgBoICoXptB8DiADACNoGIjuFjmZV0CZgCoOv7I7ukAVgBcPaCFeUyazIstATcvd31QULHbmMcBZABo5Gub/nxjmdU2v4s5c6zuqnYg8jiADADvq1sUQ5U6gEnPXVW6GR4HkAGginAPfwCoYrJ33QHkA0AVbr8/AFQR7sHjADIAVOX2+wKgqskez0vKa+M3Tx1DlSEADKWQ7g7gJ0uwfPc/eP/uqri1cqyAWjcXtcbmFcubLXm3sfx0MzypIa5du4bifZKWgFf1b4482TNJrTsbFFqWz4/pm5McQBW7jbkAcOdx3P3ZMpSOyY4ZL6gDQFZ3VTsQeQBwzPRteHf2DnPTyLAO8peAGZixuqtKN8MDgCrdfuvSbOHcSeEeKiZ7PACoerLHwMza11WEe/AAIAv3UDXZe3TiSkzbdASs7qomezwvZwJA2gXM025SynitAfE4gN0+WYJlLgBg8bzZkncbhwcAGg+ZHdemEgBbVchvviDDCQCX7DyBuz5bqhwAWd3DCgBnbMe7s/5SDoCs7mEFgMmTPRXxvlYwK5I7i7Lk8jwAaJ3sqXD7GZhZ+3q4AKBqt58BIKs7AaAQckgvTA6ggKQ6AeB7d1XFbfHqHMDrACg/3yCPA2gFQCOWKK8iB9A6KKiMP3KSG4wBoHE830yFDiCru6odiFwOYDIA3lunCIZ3qCTwdvBflDlzrO6q8g1yOYDJAKgi3MMfAKrYbSwKgCome/4AUEW4B48DyABQldvvC4CqJns8HdVr4zdPHUOV0RYAR4wYgUmTJmHt2rXImDEjTp48GUqrm/7utQbE4wDe+ekSLN31D969qypuVwiAJfJlM3cbq4g/4tkZaAXAFf2aI18ONUvArSsUMDPlG5eK+COe5LBLd53AnZ8uRcl82TDrxSaO+0WoAgzMWN1VASCLPzKWcu3mAXxrxna8M+sv3FO7CEbcoQ4AWd3DCQBVuv1WMDN2/KtKLr/l0Cm0eWeBOWGzuwlE9WSP9UFrX1cR7jFu0W4M+WMznKSBWZwc7qFqsscAUHVfD/XO8fd3r43fPHUMVUZbABw0aBBy5syJAwcO4PPPP9cKAJ2khrjr06VYsuuEcgAsmS+7uds4nACweJ9JuHYNUAmAbSoWME+rUA2ATgaFZbtOoJsLAMjqrhoAh3eoiHttJoJ+e+Z2vD1TPQCyuqsHwMYwBnc7F5vsqYj3tQKgseFLVXL5cAZAa19XCYDGSo2xYmPnUu32MwBU3dft1NX3MwSAFAOI8ePH47nnniMADNCDGAC+c2cVtK9SiKefBSxj3QTCAFBt/FFG2N0FbNw0A8Dl/ZohJkdmqXVnmzOsg4LK+CMeADRc2dkKHUBWd9U7EHkA8O7aRfCqQgeQ1V1VupnrS8DOAVBFuIc/AFQx2RMFQBWTPeYAWvu6inAP5gDyAKAqt58AUOqwIf3LtHUAmZI6ASBPXNDdny3F4p0noBwAY7Kbu43Vxh85A8ASfSbh6jVged9miIlSA4BtKxXA5A1JDqDK+CMnAGg8h66fLEGJvNkw+yV1S8Cs7qp2ILIlYCcA+M7Mv/DWzO24q1YRjOyobgmY1V1Vupn4IdOR+J+RCNo+AKp0+60AWDxvVmXJ5XkBUOVkjwGgta+rCPfgAUAW7qFqsscAkNVd1WSPh4zIASQH0JEDeOHCBRj/2GU0oMKFCyMxMRFRUVE8bdDVMjwAeM/YpVi0Qz0AGstUxm5jtQDoLC7IOAnESBKrEgDbVSqISRsOhRUArtjzD7p8rB4AWd3DCQCNHcBjZqgHQFb3cAJANtlTEe9rBUBjYqEquTwDQCNm13Dz7F4pkz0Fbn9KHK6lr4cLALJwD9UAyNo7AaDdFunO5yLKARw8eDCGDBkSVLkVK1agRo0aKZ9x4gAG+n4dAPDtblXQoaq6JWAGgKrjj5wEhjMAXNa3GfIrcgCtAKhitzHPzkAGgMbO7DkKHUBWd1U7EHkcwOsAWBgjO1aW/hZmkzBWd1X5BnkcQJVuvz8AVDHZEwZABW6/PwBUEe7B4wCmAKAit585gKonezwdlRzACHMAjx8/DuNfsKtYsWLInPn6cp4TANTRAbx37DIs3HEcb3WLxx1V43j6ma0YwNL5s5u7jVXHHzkBwFJ9J+Py1WtY2qcZCkSrWQI20rNMWp/kAKqMP3KyBLxyzz/o/PESGMH6c19OkPrMjS9jYMbqrmoHIg8AvjfrL4yesR131iyM1zopBMDk564q3QwPAKp0+28AwHzZlCWX5wVAlZM960581tdVhHvwACAL91A12UsBwOT2rmqyx/OSIgCMMADkaQROAND3+73WgHiWgLt/vgwL/jqOMV3j0bGaXAC0pmcpHZPD3G0cTgBYut9kXLpyDUv6NEXB6Cw8zStgGX+DQrgA4Kq9/6DTR0tgpOuYpxAADSj9c/0hc5eqinyDPAD4/uy/8Ob07ehWozBe7ywfABmYsbqHEwCyyZ4Kt98am2dsOFCVXJ4XAFVO9qzpWYz2rirelwcAmduvarL3yJcrzZOOWHsnAJQ6jAh/WUQtATtRY9++ffjnn3/w+++/Y9SoUViwYIFZvFSpUsie3V7aBAJAJ4rf/Fl/AKg6/siJA3hLvym4eOWqUgBkL0ZDHRW7jXmWgI0cbZ0+WqwcAI3din+sO6gs3yAPAH4wZwdGTdumHABZ3VXlG+RxANlkTyUAGrF5RgygAYAqJnu8AMgmeyrcfiuYGe3duFSEe/AAoGq3nwEga++qJns8I5HXxm+eOoYqoy0A9ujRAxMmTLhJnzlz5qBJE3s7H73WgEQcwNFd4tGpujoH8Jb8OZTtNubdGcgAcHHvpojNqcYBNADQ2ARi5BtUsdmEJzksA8AiubNifi91S8BGYvHf1x2E6gB0J7uAGQB2rRGHNzrHh3p/Ov47AzNWd1XpZkQAUEW4hxXMDAdQVXL5zQdPoe27C8zE7U42gah0+/0BoAq3/4uFuzH0z83miU128wAyAFTl9jMAZO1dVboZxx0RgNfGb546hiqjLQCGEsbO373WgHhyg933xXLM334Mb3aJR2eFAFimQA5lu425AbD/FFy8fBWLejdFIYUAOHnDIWXpZnhcgdX7/kXHDxejcO4sWNCrqZ2u4OgzzJlrXyUWv61VD4Aj7qiIe2oXtXWPDAC7VI/DqC7qAJDVXTUAznqxMYwcm3YuleEeVgAslS+7suTyvACocrJn7YN/rj+oLLk8A0ADtoyVFDsXC/dQNdljAMjaOwGgnafi3mcIAAW01gEA7/9iOeZpCoBl+k/BBRcBUMVuYx4AXLPvX9zhJgAq3oHoBAA/nLsDb0zdBrcAUFW+QeYAOgFANtlTEe/rDwBV5BblBsDkyZ4Kt98fAKoI9+ADwKRwD7cAUJXbzzOMe2385qljqDIEgKEUCvJ3rzUgnmUhBoCjOldGlxqFBdQKHgNYtkCUudtYZfyR0/NBGQAufCUBcbmySq27NTbPOArOyDeoOv7I7rIQA8C4XFmw8BV1DmCHKrH4de1BqN6ByAOAhtttuN6yL9YHWd3vqqUm3UzlwdNw6vxl8ACginAPKwAaGwFUJZcXBUAVbr8VACetP6jM7RcBQFVuP3MAWXtXlVyep596bfzmqWOoMgSAoRTSHAB7jFuOuduO4Y3OldFVIQCWKxhl7jZWCYBO44LKDpiC85euYkGvBBTOrQ4Ap248rCzdDI8DuHb/SXT4YJG57G0MiLIvtgR8R9VC+GXN32EFgB/N3YnXp25Fp2pxGN1VHQCyuocTAKp0+60AaCT+VpVcngFgTI5MWO4gEbTKyZ61DxrhHqqSy/MAIAv3UDXZYwDI2jsBoOy3qdj3EQAK6Oe1GQSPA9hz3HLMcREAVQegOwkMLzdgKv67dMU1AFSRboYHANftP4n2LgKgqhQULAeZEwfw43k78doU9wBQVb5BHgeQTfZUxPv6A0AVkz1eAGSTPRVuvz8AVBHuwQOAqt1+XwBU5fbzDONeG7956hiqDAFgKIU0dwBTALBTZXStqW4JmDmAquOPwhEAp206bOYbVB1/ZHcJ2C0A7Fi1EH5e87eydDMiANixWiGM6VpF4O3gvyibhLG6q8o3KAKAKsI9rABoHAemKrm8KACqcPutADhlwyFlbr8IAKpy+xkAsvauarLH01EJACkRNE+7SSmjugFdu3bNPNA9Z9aMQvfJCvM4gA+MX4HZW4/i9U6V0K1mERw5dR7/nL0IA9hEL2sewPKx0eZuYxZ/ZOy+vXTlKrJlSi/6M+DNDVZ+4FScu3gF819OQJE8WWHcb66sGaUcC2eNAZy+6YiZb5DFH50+fwlZMqRD+nRphevO4wCuP3ASt7+/CLHRmbG4TzNcvXoNxlJR+dgoZM0o/jwYmBmQ9fPqv28IQD957iKis2RAmjRphOvOA4CfzNuJkVO2whiwxnSrgv8uXsHGg4moXiQX0qYVv6cUAEyuO0s3I7uv8wCgr9tv9PV/z12EEZ8reln7YNkCOW5ILi+zr/MCoK/bL7OvW/vg1I2Hbkguf+r8JWSV1Nd5ANA33EN2X08BwOT2bk03I7Ov87RP1eM3zz25XYYcQAHFVTUgoxMau0+HTdqMb5btw/ieNdGkTIzAnSYV5QHAYr0nmWWNXWKGM9Dt06Xm/zfOiDXsfJHLejzUmQuXzHg742zUF1rcgts/WIj9//wHGYem8wIgq/uAW8sjV9YMeOGHdWZ197zWTqTaZlkrALLTAX59sj6iMqdH09HzULFQFP58uqHw7/AAIBsUjB//8bG6+GrpXjNdS50SufHdI3WF7ykFAJMdQOML1w1sidnbjuD579fh0cYl0KdNOWm/42QJuN8vG/D1sn3mb//waF0YE6AzFy5j0G3l0bN+ceF7Yn2wYem8JgQZTGmcCzty8lZ8v3I/vnygFhrdkk/4d3gAkLV3o1+/1rFSSl+f+1ITFBPs69Y+mHjukjnhub9uUTzX/Bbc9v5CHPj3P6wd2EJ4sssLgKzuA28tb05AXvxRXl/3lwfw96fqm5PbZqPnoVKhaPzxdAPhZ84DgCznJ+vrE5fsNXNz1i2RB98+Ukf4nnwdQNbXZ209Yr5PH29SEq+0Liv8OzxfoGr85rmX1CpDACigvKoG9Oa0bXh/zo6UO8uUPi22DW8jcKdJRUUA0PfHR3asBCOFhchlzc93/MwFv18l47QA3p2BbFDwvTEZAOjveCgVv8OTHNY4reDpb9f4fR4y6s4AsFqRnFi976Sy32GDjxMADPTMjZuUUXcGZoH6TbaM6bBpaGuRbmWWFQFA3x+XsQHM2gePnfbf1z+8pxraViooVPdNBxPR7t2FcLoJRGVft/ZBdhKIir7++cLdGPbnZjjJA/jrmr/x3PdrlfXBh79ciRmbjyC+cE4YoSX+Lhn9iqfRqBq/ee4ltcoQAAoor6oBsQPprbcmo5Pw5AazvhiNHVy7jp81b0tGrJ4dAJSRKyycAZAdkaTqxcjjChgxiY9OXGXekuEG7U5+5rIgiAGg6kGBAeCrd1SCkXDZzmXsfjYcUOOytveM6dJi+wjxSVgoAJSlMfud2S82RgmbiaAD9XWZfdAAs6MBAPD9u6vi1sqxdh5TwM+ECk99GgAAIABJREFUMwCy0zBU9XUGgEbS5XfutJcI2ohJfPzr1cr6egoAxkVj3YFEAkCh1i2/MAGggKaqAPD8pStmqoB6r802YwCfaFISvSTY5DwAOHvrEYxbtAejOsejQHRmsEHip8froXrRXALqISU2z8jP92yzUnhn1g5zCcw4FaRk38nmdxtLJZXjcgr9Di8AGqdC7Dh6xoxLPHTqPOq/Ntu8Dxkwbl0WMiLLth85jZ+fqIeDJ/9D8zHzpf0ODwBevnIVz363FtWK5sKDDYqDDSyyArgZAPZrWw7frtiH2sVzY2j7ihgzYzuMNCxO0/UEahw8ALj3xFn0/3UjHm9cEvVK5cVt7y3Ehr8T8UzTUnihZRmhdmgUZmBmtKnXpm7Fy63KmPGGNUbMxMlzl/BkQkm83Ep8SYwHAGdtOYIJS/aaoR75o6739V+eqIeqRcT6unVp9smEUnhv9g589VAtlI653tf/eKoBKsVFC2nMC4Dvz/4Lu46dNXM/Hkz8Dw1en6OkD14D8FdyXzeWvVu+Ja+v8wCg0def+W4NahTNjQcaFMfYBbswfNIWc/Iz+yV7R6IGe2AMAK/39TwY2r4C3py+DZ/M2+XYqRVqHD6FVY3fMu9R9XcRAAoorLoBvfDDWjNIvk+bsni0cUmBO00qyrMs5Pujjd6Yg33/nMNPj9dF9aK5he4p2BFtBmz9ffI//PZkfXP5QOTiBUDrbxpgZgC5LCcoUGzevhPn0GjUHHMTyJZh4kuBPADoq/XPqw+Y8TpG3NrEB2uLPAqzbKDNGT+s2I9eP61H07Ix+KJHTeHf4QFA3x99+cd1+HHVARPUDHARvQL1wRe+X2vuiO7btiweaSTe1ysNnobT5y/DiQPoW7eGb8w243CNiUk1iQDom5+v7shZOJR4XspkjxcArXU33jvG+ydj+rTYLiH0JlAfNCYbjUfNhaxlfx4A9H3m/1t1AC/9uM6MQzUm46IXA0BfF/77Ffvwyk8b0KxsDD6X0Nd57lP1+M1zT26XIQAUUFx1A3rxh3X4afUB9G5TFo+FCQA2HjUHe0+cw/8eq4saxdQDoLExoookAHQaF2RtGocS/0PdkbORIV0a/DWirUCrSSoaCAD3/3MODd+Yg8wZ0mLrMPElRxkA+MuaA+bmDOUAuHI/ev1vPRLK5MO4nuKDjwwA7PW/dfhhpQsAKHmyJwMAr0/2xN3+YJsz6o2chYOJ56VM9hgA5o/KhGV9m3P1U9mTvUB9kE32smZMh80S4j5lAOBPqw6YG2Bk9fVAACh7ssfzoFWP3zz35HYZAkABxVU3IGMmZszIwgkAm4yagz0uAGCD12ebOwPDBQAPJ55HnZGztARAFigua1AI5AD+uHI/Xg4zAHzlf+vN3bmqHUA22ZPl9ssAQDbZkxHuEQwAZbr9MgCQTfZkuf2BAJBN9sIJAGW7/QEBMHmyJ8vt5xnGVY/fPPfkdhkCQAHFVTcgBoDGNnlju7zoJWMJmAGgkR6kpkIHkAGg7PgjJ8dDWfVmAJg+bRrseFW9Ayhr57cMB5ABYINSefHVQ+qWgBkANimTD+PDxAFkAPhSy1vwVNPSol0wYBiGbLdfLgCKh3vYAUAZkz2ZACjL7Q8FgLLCPWQ4gG4DoCy3n6djqh6/ee7J7TIEgAKKq25ALP6oV+syeKKJuvgjJxIkvDnX3BVq5EirVVzdErBb8Ud2624kxa396iykS5sGOxUC4IF/z5kB6Krjj+zW2/jcb2v/NjeF1C+VB18/JJ4bLJADyOKPGt+SDxMkxB/JWALu/dN6fLdiP15scQuebqYOAGVP9mQAoEy33w4AypjsyQBA2ZO9UAAoK9xDBgCycA9Zk71ADqDsyZ6T9xn7rOrxm+ee3C5DACiguOoGxOKPwgkAm74510wF8/0jdVC7RB4B9W7cBbyy/43xOiz+SEYAuozA8KOnzqPWq7PMxL27Roongg4UAyg7AJ0nN5jvQ2UAWK9kHnzzsDgABsrPx+KPZAFgoMHHSaPt8/N6fLt8v5mc/BmFAMgme7LcfhkAyCZ7Mtz+YAAo0+3f+Hcibn1vIURiANlkT5bbHwgA2WRPFgCyHbxO0sD49gXm9sua7AXqg2yyJ8vtd9KnCQCvq0UAyNNyksu4BYCy449EdgaqAEB/aT9kBqB7EgAl5Z2T4Qq4DYCydyCKJC13GwBlTfYYAIqc2OM2AMqY7MkEQFlufygAlBXuwQCwQ5VYvG0zD2BqA6CsyR7PMK56/Oa5J7fLEAAKKK66AakKQBcCwNFzzXxZ3z1SB3UEHcBg6VmuB6CLxx9JAcDT51FrxCwYR9TuluAABjqhg+1AlBV/JAMAjaOhnvl2jfTjoXxP6FAVfyQGgBvw7fJ9eL75LXi2ufgSMAOzWS82RklLgmbZu41lACCb7MkI9wjWB1m4h4zNJjIAULbbH8iFl+32ywBA2ZO9hyasxMwtR+CbBoa5/bImezzDuOrxm+ee3C5DACiguOoGxOKPwskBbDZ6LnYeO4tvH66DuiXFloCDASCLP5KRb1AGABrHV9UcMdNsLTISQQdyBWSnm5EBgOxoOFlnAQeKzZOdboYtP4kAYN9fNpjncT/XvLR5bq3oFWhpVvZkTwoAJk/2ZIR7BIvNk+n2SwFAyZO9QH0wJd2MpHyDMgFQ1lnADAB9+yCb7BEAir5RxMoTAAro5xYAytqBKCMuqPmYeebpGG4BoIx8gzIA0DiruMZw9wBQVvyRDAD8c/1BPPXNGugIgP1+2YCvvQiAg6bh9IXLEFkCZpM99wBQ3O33JABKCveQAYCy3f5QACgrtRTPMK56/Oa5J7fLEAAKKK66AbH4I1k7EGUC4DcP10a9knkF1AOCOYAy449k7Ax0CwDZDkRZ8UcyAdA4su37R+sKPXOjcCAHUHa6GRkOIAPAZ5uVxvMt1DmAzO2XNtmTCIAywj2C9UGZyeUZABaIyoylfZtxtVXZbn+gPijb7ZcJgLIme4EAULbbz/OgVY/fPPfkdhkCQAHFVTegPj8nxR+FEwC2GDMPfx09g28eqm2elSpyBQNAFn8kYweiDAA8ceYCqic7gLtHtkUaIxhQ4Aq0BCw73YwMAJy0/hCe/Ga1mfbHiAcTvQIBIIs/kp2CQmQJuP+vG/DV0n3mDmBjJ7DoFWgSxiZ74QSAMt3+YH1QZroZGQAoe7IXqA/KTi4vAwBZuIesyV4gAJSdXJ6nX6oev3nuye0yBIACiqtuQAwAZaWgkOEAtnxrHrYfcQ8AZQagi6SG+OfsRVQbNsNsLW4AoKx0MzIAcPKGQ3jia/cAUHYKChEAHPDrRkxcutc1AJQ22ZPgALLJnoxwDzsAKGOyJwMArZM9GfG+oQBQVriHDABk4R5uAaCsyR7PMK56/Oa5J7fLEAAKKK66AbEAdNk7EEV2ATMA/Pqh2qiv0gF0KQDd7uO3AuCuV9sirUFoAlcgB5DtQJS121gqABbLjR8eU+8Ayso3KGMJOAUAm5bCCy3LCDzxpKKBHcAkt1/aZE8iAMoI9wgGgDKTy8sGQBmTvUB9ULbbLxMAZbn9gRxA2cnleTqm6vGb557cLkMAKKC46gbE4o/CCQBbvTUf246cxlcP1kaD0uqWgGUGoMsIDP/37EVUTXYAjZNAjBg9kSsgAEregSgjOeyUDYfw+NerUbNYLvz4WD2RaptlAy0BswB0WQAYaPBxUoGBv23El0v24ummpfCiQgBkk71wAkCZbn8wAJSZbkYGAMqe7AUCQDbZkxXvKwMAU8I9JE32CACdvG3c/ywBoIDmbgGg7BQUIjsDW789H1sPuweAMgLQZQDgyXMXUWVo0hKwGwBo/I6M5ScZg8LUjYfw2FfyADDQ6QCqdiC+1rES7qxVhKunD/ptIya4CIDSJnvJDuDcl5qgWN5sXHVnkz0Z8b52AFDGbmMZAGid7Mlw+0MBoKxwD9bX76haCG91q8L1zFPCPVwCQFmTPZ7Kqh6/ee7J7TIEgAKKq25ALABd9g5EGQA48cFaaFg6n4B613cBx+TIhOX9bjwKTmYAumwA3DGiDdKnSytU90AOoOwdiDIBsEbRXPjf4+IOYCAAlJ1vkLkPMgDwqYRSeKmVuiVg6elmJAKgjHCPoAAoMbm8bACUMdkLCICK3H4ZACjL7Q/kAMqe7PG8jFWP3zz35HYZAkABxVU3IFUB6DIA8MsHasFI4ilyBcvPl7LbWEK6GRkAmHjuEuKHTjer+9eINsggCICBTgew7kCUEX8kBwAP47GvVqF60VwwTmsQvQIBoKoAdBEAHPz7JoxfvAdPJpTEy63KilYdlZLBzDcOV/pkTwIAynT7g/VBmcnlZQCg1e2XMdkLFIaharInAoAs3EPWZO+hCSswc8tR+G7Ekj3Z4+mYqsdvnntyuwwBoIDiqhsQiz+SloJCQmB4m3cWYMuhU1ANgCnxR+ECgP9dQvwQ+QDoe3C77HQzMgBw2qbDeHSifAD0HRRY/JHsHYjhCIC+kzA22ZPl9lccNA1nLlyGyBKwCgD0l59PhdsvkgfQOtmTCYC+Z/SGIwCycA/ZAOjbB2Unl+cZxlWP3zz35HYZAkABxVU3oBQAlLUDUSIATnigFoyDvEWuYA6gzAB0Ga5AogUAtw9vg4zpxZaAAy0LWQFQRvyRTACsViQnfn6ivsgjN8sG2p0rO9+gjCVg5gA+0aQkerWW5wAGAkBZkz2ZACgj3CNYH2QAKGO3MfudgtGZsaQPXyJo2W5/oD4oO9+gjBhABoCy3H7mAAYCQFmTPZ6Xkurxm+ee3C5DACiguOoGJD0AXQIAtn1nATYfOoXxPWuiSZkYAfWAYADIAtBlxB/JAMBT5y+h8uAkB3Db8NbIlD6dUN0DAaB1B6KM+CMZADh902E8MnEVqhbJiV8UAqCqAHQRB3DIH5swbtEePN6kJF5RCICyJ3syAFCm2x+sD8pMLi8FACVP9gL1QVVuv8gS8NSNSeEesiZ7gQBQ9mSP52WsevzmuSe3yxAACiiuugEx90FaCgoJANju3QXYdFA9ALLlp3ABwNPnL6GSCwAoO92MDACcsfmI6dqpBkAWf1RL8g5EEQAc+sdmfLFot3IAZJO9ZyS5/TIAkE32ZIR7BANAFW6/iANonezJcPsD9UHZyeVlOIAs3EM1AMpOLs8zjKsev3nuye0yBIACiqtuQAwApe1AlAiA43rWRIJCB9Ct+CO7j98KgFuHtUbmDGocQCsAqow/sltv43MMAKsUzolfn1S3BCw736CMJWAGgI81LonebdQtAct2+2UCoIxwDzsAKHOyJwsAZbj9dgBQZriHiAPIAFDWZC+QAyjb7XfyPmOfVT1+89yT22UIAAUUV92AVO1AFNkFfOt7C7Dx71MY16MmEsqqWwJmAKg6/sju4zcC6o1B1bhUAqB1B6KM3cYyHMCZm4/goS9XIr5wTvymEADdCkC3+8yNzw37czOM5fpHG5dAnzblnBT1+1m2C9i3D8qe7MkAQJlufzAAlJlcfsOBRNz2/kKIAKDsyV6gPijb7f9s/i6MmLwFIgDIwj1kTfYCAaDsyR5Px1Q9fvPck9tlCAAFFFfdgFj8kewUFCI7A297byE2/J2oHABZ/FG4AODZC5dRwQUAVBWALjIozNpyBA9OcAMAk+KPZO9AfL1TJXSryZcIevifmzHWwwA47+UmKJqHLxE0m+zJiPcNBoAy3X4ZACh7shcIAGUnl2cA2LFqIYzhTAQt2+0PBICyk8vzDOOqx2+ee3K7DAGggOKqGxADQNk7EGUA4Bc9aqBp2fwC6gXfBOJWALrdClgBcMvQ1siSUc0SsBUAZcYfSQHAuGj89lQDu5IF/Fyg5LAsAF32DkQpANioBPq0Ve8AyprsMQdQBgDKCPewA4AyJnteBUAZ4R4yAVCW2x8KAGVN9nheSqrHb557crsMAaCA4qobkKoAdBEAvP39hVh/IBGf318DzcrJAcD8UZmwrO+NJ4GwAHTV8Ud2H/+5i5dRfmDSEvDmoa2QNWN6u0X9fi7QLmBruhmZ8UciADh76xE8MH4lKsdF43eFAKgqAF0EAEdM2ozPFuzGI41KoK9CAJQ92ZMBgDLdfjsAKGOziQwAlD3ZC+QAynb7ZQBgSriHtMleUiJo341Ysid7PC9j1eM3zz25XYYAUEBx1Q2IxR/JSkEhIy6o/fsLsc4FAGTxR+ECgP9dvIJyA6cqB0DZ6WZk7Aycs/Uoeo5foRwAWfyR7B2IIgD46uQt+HT+LuUAyCZ7stz+CgOn4uzFKxBxANlkT0a8bzAAlOn2ywBA62RPhtsfEAAlJ5eXAYAp4R6KAVB2cnmeYVz1+M1zT26XIQAUUFx1A2IAKGsHokwAHHtfDTQvL+YABjseSkUAukhguBUANw1phWyZxBzAQMdDWQFQxmYTmQBYqVA0/nha3RKw7HyDbPlJBgA+3LA4+rUrL/C2SCrK+qDvJhDZbr9MAJQR7mEHAGVM9hgAxkZnxmLORNCy3X47ACgj3EMmAMpy+x8cvwKztt7sAMp2+3k6purxm+ee3C5DACiguOoGJDsAXQoAfrAI6/afxGf31UCL8vlx6cpVXLl6jSstSjAATNltLCHdjIzksOcvXUHZAUkO4MYhrZA9U3oYS0VZM6ZDmjRpHLeiQIOCqh2IIkvAc7YdRc9xK1CxUBT+fLqhWVej7rwQHCg9i6oAdBEAHDl5Cz6ZvwsPNSiO/reWx7Vr13Du4hXuugfqg7InezIA0Nftl9HX/U3CZCaXlwGA/iZ7Mvq6bx+U7fbLAEAW7mGd7In0dQaAvn1Q9mTP8QsYgOrxm+ee3C5DACiguOoGxOKPWAoKAxq+XrYP3z5cBwWiMzu+cxkA2OGDRVhrAcCmo+fiSOJ5rBrQwjEEBgPAlPijZAB8/KtV5tmmE3rWQtq0zoBLBQAaoFZ35Gw0KZMP43vWcvwsAgGg7w5EAzw7f7wE7SoVxPMtbuH+HREAnLvtKHpYAJBl8e/frhwealjC8T0FAkAWf8RSUCzddQIv/bgOw9pX5Eo5JMMBHDllCz6Zdx0A+/+6AV8t3Yc/nmqASnHRjuseqA+yyR5z+43B/Jvl/H1dCgAmT/aMeN+mZWPQdPQ8GOfXruzfnLuv+wNAX7f/sYmrcPYiX1+XAYDWyZ7h9htxufVem42EMvkwTqCv+/ZB3+TyBngaff22yrF4tnlpx21LBgCycA8GgOzMXt6+HggAfZPLL9l5Ai//bx2GdagonF/WrnCqx2+795GanyMAFFBfdQPq8/N6fLt8P9pWKoAP76mOYr0nmXfre6i43SrIAEB2D0PbV0Dn6nEpGyN+f6o+KsfltHsrSU7a34m49b2F8LcJhN3rR/dUM5eaS/ebYpaZ+UIjlIrJwfU7IkvA1kHBGAAnLN6D92bvMO9jz2vtHN2P8WE7AGjEHxmnUIyatk34d0QAkDmAxk0Yy9LMCeWteygAZN/LIIb/d5IC0EUcwBd+WIufV/+N+LhofP9o3ZS6Nysbg8971HT83AP1wd4/rcd3K/aboP/BPdVS+jpvSg8ZAMj6uqFfp2pxKJXcB/98ugEqFnIGv8EmYeUGTMV/l67g43urI6FsPpTpn+S0z3qxMUrmy+5IY9kAuGFwS3y5ZK+SPujr9hvvhDenb+fu6zIAkDmArM+V6jsZl69e476nUADIfoe1Ad6+7qiRJH9Y9fjNc09ulyEAFFBcdQNiL2DjFssVjMKWQ6fMu+WdicoEQF/ZZAOgte5xubLgwL//mT857blGKFPAGQDKCAy/cPlKysDkW3eZAGjdgSjjd2Qkh2VOtL+uwlP3QAA4ZsZ2vDvrL/NnyheMMs+cZhfP7wQafJx0eWs7tJbjPSkhUB+0/o617kaYhRFu4fSSCYC+vy0bAK11L543G3YfP2v+5IznG6F0fmd9ff2Bk7j9/UUQiQG0TvZk9MFAcbhWt1/G73w6fydenbwVvJMG4x5GTduKD+bsNG8nQ7o0uHQlCf6MS2YftP5Ohdgo83hRkd9x2j+Mz6sev3nuye0yBIACiqtuQIEGH3+OmZ1qyEgNEeieeJbEgjmAgX6HxwH0EgDKHhRkuAIsPk01AA78baPptsj6HQaAb3SqjK41C9vpIjd9JlA7zJE5PTYMbuX4O+0AoPVLC+XMgkW9mzr+HQaA819OQJE8WR2XNwoEqvukZxqgQqw8BzDQ7/A4gF4CQGsMoFQArFYIY7pW4XrmLOZVdh/0deH7/rIB3yzbJ62v81RW9fjNc09ulyEAFFBcdQN6a8Z2vDPrL9ySPzv6tyuP+75Ybt5tyXzZMOvFJo7vXAYAsrQYPz9RD7HRWVBn5CzzPkQGBX9Ay04HeK55aXMZ6Olv15i/M/OFxigVw7csJLIEbAT/t3t3Ifb/cw7zeiWg3y8bMGXjYfOeeGbGgZaAjUB7ttz9affqeOGHdWbsI+/vyADAw4nnUe+1WWbi77e6xaPS4OkpbY+n7oEcwDX7/sUdHy42v9vYEXp/cnvnrbsMAGS7FY0YqDtrFUk5DtBw6SY/m7QhxskVCACZ+1kmfw70a1cupa8b/3/a842c/IT5WRkAyJzf/z1WF3myZ0LCm3PN7576XEOULRDl6J6CLQGzvm4kwS6RNzte/HGd+d08R1bKAECjrxvHyW0/fMZchu7360bM336Muw8GcgCtfd1weZ/9bo25wYi3vac4gAIAeCjxPzR+Yy5qFMuF0V3jzThndvH09UAu/Op9/6KjxL7uqDEmf1j1+M1zT26X0RIA9+zZg2HDhmH27Nk4fPgwYmNjce+996Jfv37ImDGj7WegugEZL6Kdx86YL0Vj44M1/u6+usVs3yf7oAwANL7r4uWryJg+rfm17J54kksHcwCNZZgjp86nHGPFfmdBrwQUzu3M0ZDhABp1NXY7G1e6tGlghRWeF2OwM3qPn7lg/k7e7JnMgYeBP8/vyABA32fOzq2tVSw3fnisruN2GOh0AOOL9p04h5ioTOYmgye+XoXJGw7fsPvYyY/JAEDfurM+ZASrd69T1MntmJ8NBICB+jrv78gAwEB9nSe3YDAADNTXF76SgLhczvq6DAD07etWWOHpg8FSMRl93djSZgD2vO3HUiY9PL8jAwB9n/mg3zZiwpK9qFU8N3541HlfDxaGsffEWeSPymz2dWOTnzGhlpV+xk7HVD1+27mH1P6MlgA4depUfP/997jrrrtQqlQpbNy4EQ8//DC6d++ON9980/YzcbsB9Ry3HHO2HcOozpXRpYbzJS0ZcUG+4rDD7UUAsEBUZizt2yyo7ixIODUB0HqDwfKa2WlAwQDQWt7YcW3svOZdCpQFgNZ7snvvgXQIBoDWMh/P24nXpmw1Nxu92SXejqw3fEYWAFq/1O69B7pZu3G4PcYtx9xtx8x6G/V3epUfONV0k0SWgH1/U2QC6WQnfpn+U3Dh8lWkJgD66+u8Kwh2c3GySWXh3FmwoJfzZX9ZAGitu2gMsd043I/m7sTrU7eiS/U4jOLo6077h/F5t8dvnntUXUZLAPQn6qhRo/DRRx9h165dtjV3uwExAHyjc2V0DTMA5FmucQJRMgBQJDDct1EEcy/tNCC7EBXOANi+SizeubOqnere8Bm7EMUA0NiBaixHOb1UAuDIjpVwV60iTm8poAPo+0UMAHkneyoBUGSyZweiGADyTPaYA8g7YfL3QJ28p/yVdwqAxqa3ha+EFwDyZp5wCoC8kz3HHZEA0JSMADC55fTv3x+GM7hy5UrbbcltAHxg/ArM3noUYQWAg6fh9PnLXPE6Tl6sbEDjGRRkpIbwbRSbDiaaMYG8G3LsAqCRdLt9mDmAgc4xtttx7ALgJ/N2YuSUrWYKkvABwJWYueUIeAGQufChIErU7VcBgCJuv5MwjLIDpuD8pavg6evhCIB2XTQ22QsnALT7ngrU99mYFSoVk6jbb/fdY/2c2+M3zz2qLkMACGDnzp2oVq0aRo8ejYceeiig5hcuXIDxj11GAypcuDASExMRFeUsKJrnwRIAXuEaFMIZAEPl54tkAAw1KEQyAIaKo4tUALTjwkcqAIZKzxLJABhqJz4BIA8RiJeJKAAcPHgwhgwZElSVFStWoEaN63m1Dh48iMaNG5v/xo4dG7RsoO93HQA501ooiQFMdgBnv9gYJRwmbeVxAHlimmQFhlsbB3MAY3JkwvJ+zR33RLvLQgwA7Qyc/m5CRm4w3+9lDuDt8bF49y7+JWC7ANiRc1djyoSJs7/405PtYH71jkq4u7bzJWC7fVA03EOlA8gT7uFkEiYCgKITpmBLwLxuv904XNFwDzZh4u0vwZavecM97PZB0XAPxy9gWgKOvCXg48ePw/gX7CpWrBgyZ046Rs2Av4SEBNSuXRvjx49H2rRJO1sDXantAIrGNMnaGWjVp/LgaTh1/jJUA6DIvasAwM0HT6HtuwugGgBF711FYPgXC3dj6J+boRoARe9d1DH39x54+MuVMI6xUg2AovcuEjIR6P1XSSDcwwkAisT7qgBA0XAPuwAoeu+ijnlqAqCKew8FhbQErHEM4N9//23CX/Xq1fHVV18hXbp0odrLTX93uwERAPLtahSFKH8NgwCQAFClA0gAyBfuIQpR/vo6AeAWqHYACQAd44eUAhG1BGxXEbbsW6RIEXz55Zc3wF+BAgXsfo3r28jt7qgKVAERFy3QdzIHkCdrv5MlYLtLZ/7uUyUA5suRCSsULgGze7eze9Jf3UVdNH/fyRzA2+Jj8Z7CJWDR5WtRiArmAI64oyLuqe08D6Dddmx36SxQv1TpAPK4/TwOIE+4h0oA5HX7I8EB5HX77bZjFcvXoQZytw2cUPeTGn/XEgCN5d6ePXv61dtIyGr3crsBsd2ToWKn3ATA+CHTkfjfJa6D250AoEgOMhUAaJzL3OadBVANgE52T7oFgOMW7caQPzZDNQDaHTgDtXcVAPjIlyu050cjAAAgAElEQVQxffMRqAZAUbdfBQCKhHs4AUCR+EUVACjq9tttx6I7mFW4aKLxvnYBUMVENdQ47vb4Hep+UuPvWgKgLKHdbkCiACjyYg2kGQNAniPaCAC3INQu4EgEQLtOtt2BkwDwZgVE4uhCuf2qHUCR9xQBIH/aJH/PnQBQFi2E5/cQAAo8l9QCwNc6VjLPJXV6ibxYVQKgneVNuycoBFsClpkcljmAxnFtK/ur2wXMANDOaSluO4C3Vi6I9++u5rQZwikAhoLk1ADA4R0q4l6Oo+DsLgHb1ShQ3VUCIE+4B48DGCpVjr+6qwRAXrff7kRGdKVCpQPI6/Y7dgCrFsKYblUcv1N4Crg9fvPco+oyBIACCrvdgFgKinACwCpDp+PkuUsQcQDtAKBIElrRpRV/TWTr4VNo/fYC87xelQDoxCV1CwDHL9qNwX9shmoAtJsqx00AfHTiSkzbdASqAVDU7VcBgCLhHk4A0C4kuwWAouEedgHQiUb+6q4CAEXjfe0CoF2NBIbrm4q6PX7LvHdZ30UAKKCk2w0ovAGwEUrF5HCkppPlzUgDQLunAxAAhl4m9xIAMhc+lLsVaQDoxN2KNAC0u5kpEgEwJZ9liFycBICOhk5pHyYAFJAytQCQ9xgqFUvA1x1AdwCQJwmtimWh6w5gRqzs38JxK7L7whM9c1jF7jrmALarXBAfCCwBhzodQPQYKtFkyv4eKnMAh3WoiO4cS8B2+6Dd4/LcXAIWifd14sLbPS7PX91Fkyn7+07RcA+7GxycTIj93aeKZMrMAeR1++32QbsTYscv2iAF3B6/Zd67rO8iABRQ0u0GxJLQigIgzxmbgWSqOnQ6/jWXgBUDoEASWhUAuO3wabR6ez7yZvcGAPKep+vvuU9YvAeDft8ErwDgqM6V0aVGYYGefr3oYxNXYeqmw1APgElnDvOGe6hYAhYJ93ACgCLxvioAUDTcwy4AssmenZCYYADYuXoc3uwSL6W9sx3/qgFQNNyDp7Juj98896i6DAGggMJuN6BwBsAZzzdC6fwKl4AJALGsr/PNJirigggACQBLxWR39OYkANyKUEe0EQDyh3s4aozJH3Z7/Oa5R9VlCAAFFHa7AYkeQ6UiNxhzAN0CQJ4UFCodwDzZMmLVAPVLwLxJaJUCYKWC+OAe/l3AdpeAeU8hYMtPShzA9hXQvW4xx28P+0vASQ4gr9uv1gF07vbzACBPuIdaB5DP7XfqAPLu+GdLwCocQF633+4SsGi4h+OOSGcBm5IRAPK0nFSaQbAktLznkKoAwGrDZuCfsxehGgBFktCqAMDtR06j5VvzoRoA2TFU4QSAXy7Zg4G/bUI7xQDIcpCFEwA+/tUqTNl4GMMUA6Co268CAEXCPZwAINvwFS4AKBru4WUAFI33JQAUAAwXihIACojstgMoCoAqBgUGgNOfb4RbFC4BEwBmwnKOI+dUOIAEgOEPgGUHTMH5S1cRLvG+BID2l4DDyQEkABQABA8UJQAUeEipBYC8x1BFAgDyJKFV6QDmzpYRqxUuATMHkDcJrUoAbFupAD68p7rjHmQ3N5joKQQqloCZAzi0fQXcp3AJWDTcQyUA8rj9PADIE+7BloDjcmXBwleaOm6b/gowB5DX7XfqAOaPysQV76tiCTgFADndfqcOIK/bz/Og3R6/ee5RdRkCQAGF3W5ALAVFOAFg9WEzcOLsRYg4gLHRmbG4T7OgT0IkCa0KAPzryGm0eGs+VAMgO4c0nABw4pI9GPDbJqgGQJaCgvcgehUA+MTXqzB5w2GoBkBRt18FAIqEezgCwOQNX+ECgKLhHnYBkE32wgkAUzZ8KQZA0XAPnmHc7fGb5x5VlyEAFFDY7QYUzgA47blGKFOAbxcwAWDgo48IADeDAND5sY8EgPIcQAJA/nhfuw4gAaAAiAgUJQAUEC+1AJD3GCoVS8DMAXQLAHmOnFOxM5A5gLmyZsCagS0dtyK7iaAZAPIeOaciOSxzANtULICP7lW3BCx6DFWPccsxd9sxyNwFzBzAIbdXwP311O0CZg4gr9uvEgB53H4eB5An3GPNvn9xx4eLIXMJmAEgr9vv1AHk3fD10dydeH3qVsjcBcwcQF633ykA8k72HL+AaRcw7QLmaTTWMm4DIEtCG04AWGP4DBw/cxE8AOjkeCiRJLQqAHDH0dNoPmY+eAHQ7vFQoqcQqIgLmrh0Lwb8uhGqAZAloeU9iJ4BoJEU1xgUZVxPfr0akzYcAi8AsknY/JcTUCRP1oC3JOr2MwBc+EoC4nIF/h0nmoiEezgJw2AbvsIFAEXDPeyexsMme6IA2KV6HEZJSgTNNnzxAiDrg290royuQZKxi4Z7OGnH7LNuj98896i6DDmAAgq73YDCGQCnPtcQZQtEOVKTADD0zsCIBsAQg0IkA2Co3bkEgJcRaQAY6jSeSAbAUC48AaCjoVPahwkABaRMLQDkPYZKxRIwcwDdA0DnSWhVOoA5s2bAWo4lYLvLQtcBkC8JrUoHsHWFAvi4u8ASsE0A5D2GSqUDOPi28uhRv7jjt4fdPsgAkNftV+kA8rj9PA4gT7iHiiVg0XAPuzvxReN92RKwCgeQ1+23G4YhGu7huCPSEjAtAfM0mtRcAk5JQst5EL3dwceJLjWGz8TxMxcw5dmGKFdQnQMokoRWDQCeQfMx86AaAK+fQxo+APjV0r3o/+tGqAZAloIirADwm9WYtP4QVAOgqNuvAgBFwj2cACDb8R8uACga7mEXANlkj3fHvwoAFI33tQuAom6/kzGLloCvq0UOIE/LSS7jtgMoCoAqAsMJANU6gASAm0EAWNTxW6pM/ym4cPkqZMYAEgDybfgiAAy9EYsA0HEXl1KAAFBAxlQDQM5jqCIBAHmS0KpIDrvjaJIDGJ0lA9YNcr4L2O4SMANA3iS0KpaAmQPYqkJ+fNK9huMelJIIOsQSsOgpBEqWgJMdwEG3lUdPhUvAzAHkDfdQCYA84R58DqDzcA+2BFw4dxYs6CUnETRzAHndfqcAyLvjX6UDyOv2O3UAeSd7jl9CtARMS8A8jSY1l4BZCgrec0hVAGDNETNx7PQFTH6mIcrHqlsCFklCqwIAdx47g2aj1QOg6CkEKgDw62V70e+XjeAFQLupIVKS0FYuiA/urua4u6oAwKe+WY0/1x+CagAUdfvVAGBSuIdqALy+4z9cAFAs3MMuAF53+zNhZf/mjtu7EgBM3vGvGgBFwz0ci0UASADI02gIAG9UTQYAFsqZBYt6B5+tEwBmxCqOI+cIAI9BZhoYAkACQKfjBgFg6CVgAkCnrUrO52kJWEBHt5eARY+hClcH0AkA8iShVbEzkDmAUZnTY/3gVo5bkd0lYOYA8iahVZEcljmALcvnx6f3OV8CduwAch5Ddf8XyzFvuxoAHHhreTzQQN0u4BQHkDPcQ6UDyLPhy8kSMHMAecI9Vu/7Fx0/XAy5S8Bi4R7OAZBvw9eHc3fgjanbIHMXMMv5yev2210CFg33cPwCJgeQHECeRpOaDiBLQst7DqmKnYG1RszE0dMXMOmZBqgQG+1IUienA4gkoVUBgLuOnUHT0fOgGgBFTyFQsSz0zbJ96PvLBqgGQJaEtp0gAI7uEo9OkhJBP/3tGvyx7iBUA6BouAcDQMNZNyZYMi7m9qsGQLbjP1wAUDTcwy4Assle3uxiANi1Rhze6Bwv45FDNN7XLgCKhnvwVNZtA4fnHlWXIQdQQGG3G1CkAaATVyDSANDu6QAEgPznkDIHMJwA0K4LH2kA6CQVU6QBoN3jGCMRAFkfDJUImgBQAEQEihIACoiXWgDIewxVuDmAPADIk4RWpQOYI3N6bOBYArbrCjAA5D1yTqUD2KJ8fnwmsAQcalAQPYZKJQAOuLU8HuRYAnYKgLxuv0oHkGfDl5ONWAwAecI9VCwBi4Z72I3DFd3wxZaAVTiAvG6/3TCMFADkdPt5hnG3x2+ee1RdhgBQQGG3G9CTySkowgkAa786E0dOXcCfTzdAxULOloCdAKBIDjIVALj7+FkkvDkXqgFQ9BQCFQD47fJ96PPzBqgGQJaElvccUhUA+My3a/D7uoNQDYCibr8KAGThHqoBkG34ChcAFA33sAuAbLLHm/JJBQCKxvvaBUDRcA+eYdzt8ZvnHlWXIQAUUNjtBiQKgCoCw70EgDIDwwkACQBVOoCiAHhL/ym4ePmqubteVgwgASDfhi8CwNAbsQgABUBEoCgBoIB4qQWAvMdQRQIA8uQgU5EcNgUAM6XHhiHOdwHbXQJmDiBvElqVDmDzcvkx9n7+XcChloBFj6FS6QD2b1cODzUs4fjtYXcJmAEgr9uvEgB5Nnw5WQJmDiBPuAdbAi6SOyvm90pw/Hz8FWAOIK/b7xQAeXf8q3QAed1+pw4gr9vP86DdHr957lF1GQJAAYXdbkAsB1k4AWCdV2fh8KnzLiwB8yehVQGAe46fRRNjCVgxAIqeQqACAL9bvg+9f94A5QCYnISW9yB6FQD47Hdr8Nvag1AOgILhHioAkLn9qgGQbfgKFwAUdfvtAiCb7IUTALId/6oBUDTcg2cYd3v85rlH1WUIAAUUdrsBEQDyJaFVERjuFQBUkRtMFADtpoZgOch4AfC+L5Zj/vZjkLkLmACQL+WTEwdQBABX7f0XnT5aDJkOoFcA8IM5OzBq2jbI3ARCACgACB4oSgAo8JBSCwB5j6FSERjutgPIk4NMJQBmz5QeGxUuATMHkPfMYRXLQtcBMAZj76/puAc5BUDeY6gYAI7pGo+O1eIc36e/Am4DIK/bzxzAxb2bIlZSHkCReF8eAOQJ91AKgJxuv1MHkHfHPwPAbjUK4/XOlaW0dwaAvG6/3SVg0XAPnsq6PX7z3KPqMgSAAgq73YBYEtpwAsC6I2fhUOJ5/PFUA1SKU7cLWCQJrQoA3HviLBqPmgv1ACh2CoEKAPx+xT688pOxBKwWAFkS2nACwOe+W4NfXVgCFnX7VQCgyGTPCQCyHf/hAoCibr9dAGSTvXACQLbjXzkACoZ78Azjbo/fPPeougwBoIDCbjcgAsALCBcHkAFgtozpsGloa8etyO4mkB1HwxcAm5WNwec91DmA4QyA/dqWw8ON1G0CIQC8iHADQN7JXmQAIN9kz7YDSADoeAyRUYAAUEDF1AJA3mOoVCwB1xs5CwcTz+P3p+qjclxOR2o6OR2AOYA8OchUOID7TpxDo1FzwAuAdk8HYADIe+ScCgfwhxX70eun9XALAHnPIVWxBPx/9s4DSmtiDcMvve/Se++9w9J7VwRRBEFUpKjoVUFAqdJBULEgiqJSBEWaWOi9l6UsS+9l6XXpnXsmu/Mbsv+/ySSZJOx+OYdzrneTP5k3M5ln3vnmm+4zdmDu9lMwC4C8Da7pXRe50qcM2F44AJp1+2U4gNztN5PzUyQXJ3cAzQz2ZEwBW3X7je7HbXXBl4wpYKvhHrwNfta6DF6MZTtGHu9r1u0X6niiT3a6/zbzjLKvIQC0oLDTFYgnoTULgDJWBjoFgFZykHkZANlHkX0cAx1WdyHwMgDqdQo8CW1cBMC1H9VFznSBAdCq21+43wLce/gIdsYA2gGARnJxVhwWteI/rgFg6wo5MSaWts4He2ZTPnkZAPUWYll1+810407332aeUfY1BIAWFHa6AhEA3oUVB9DOlYHcAUyZNBH2mJgCNjot5GUArFc0M362MAX8NANg32ZF0bVWAeGvh9FcnF4GQDPxviKpmLwKgGbdfqOpmLwMgGbdfqMr8QkAhT8ltlxAAGhBRrcA0Ow2VDIcwOqjluPU1duY9051lMklbwqYO4BmcpDJSA578vIt1By9Ak4BoNkktFIcwNCT6D1rJ5wCQLP7kMqYAu4xYwfmbD8FpwDQtNsvwQHkbr9TAGhmsMengPNkSIlVvexJBG013EMUAM2u+JfhAPIFX04BoFm330w37nT/beYZZV9DAGhBYacrEE9BER8B0EoS2qcZAK3uQvA0AyBPQREfAdCy2/8UA6CVeN+nGQC52x8fAdBquIeZbtzp/tvMM8q+hgDQgsJOVyACQHNJaGUEhnMHMEWSRNg7VHwVsNEpYKsAKCM57B/RDmDdIpnwS8fKwi3I6MpAqwDY4adNWHPwIuzMA8gdwD5Ni+LN2vKmgL0MgGYWfIlMAVsDwMt44bsNkOEAmnX7jTqAXgZAs26/0SlgAkDhz6gtFxAAWpDRLQA0uw2VjJWBfAr4z3eqo6zEKWArSWjjBACaTEIrY1poZuhJ9Jq1E04BoNltqDgAjm1TBs+XsycRdI8/dmDOtlNwCgBNu/3RDuCGPvWQLTiFha/cf5fytu4UAJoJ99h63H4AtBruIQqAZlf887betlIujHrBnkTQfMW/UwBo1u03U8Gd7r/NPKPsawgALSjsdAWymoTWqwCYM10KrP2oXqxvwkoS2qcZAH3bUMVDAORJaOMjAFp2+59iALQS7/s0AyB3++MjAFp1+810407332aeUfY1BIAWFHa6AhEA3oGZHGQyATB5koTYN7SpcC0yOgXsZQCsUyQTJkmcAvYyAH7ctCjekjgF7GUANLPgS2QK2KsAaDbcw6gD6GUANOv2G50CJgAU7kJsuYAA0IKMBIBAjU+XI+LKbcztVg3lcqcTUlNkeyivOYARV26hxqcr4BQAmt2FQMYU8KytEeg5MwxOAaDZbahkTAF/+EcYZm+LgFMAaDrcQ6ID6BQAmhvsyZsCdgoAza74lzIFbDHeVxQAzbr9Qh1P9MlO999mnlH2NQSAFhR2ugLxXQisdgp2Jod1CgCtJKGV4QA6BYB8H9L4CID/7UKQBRNfqyjcUp9mALTq9hfqNx/3Hz6GjBhA2QBoLd736QVAn9ufPDHCBzUWru9PMwBadfuFxQLgdP9t5hllX0MAaEFhpyuQ1W2oZOwOYAUARbaH4gBoJgeZjNQQHACTJU6I/cPEp4CNbg/FAdBsElqZDmDtwpkw+Q15q4CtbkMlEwA/alIUb9cRXwXM43D1dgLxMgCaWfAlshuPVwHQrNvPUzHp7QRiV7iHrYtAoh1As24/b4N6O4EQAFoAEQuXxlsAfO6557Bjxw6cP38e6dKlQ4MGDfDpp58ie/bshuV0GgB5Cgqz+5DKAMCao5fj5OXbmNOtGsoLTgGLAKCVJLQyAJAlv2arIq0CoF6nwPch9RIAzt4agQ9nhsEqAOp1CjwJbYNi5jailwGAbOqbTYFbBcB1H9dDjrSBV+dadftlOIB8sGcFAI3sxmMt3CPKAcybISVW2pQI2qrbbzQXJx/spbG44MtOAOQr/q0CoF4qJg6AZsM9DHfaqhOd7r/NPKPsa+ItAI4dOxZVq1ZFtmzZcOrUKfTs2VPRev369YY1d7oCEQDegVccQAJAAkArDiABYODPLAFgYoQP9sYUsFMAaDXcw3CnTQD4hFTxFgC1Feavv/5Cy5YtcffuXSRJksRQfXILAM1uQxUXHEAzOchkpIbgAJg0cUIcsDAFbNQBNJuEVsYUMHcAaxXOhCkWpoCNOoBmt6GS6QD2blIE3eoUNPSdUJ9kdDtGq+EeMh1AMwu+RHbj4QBoZrAXeuwyXvxejgNo1u0XdQDNxvuOW34Qny0+ABkOoFm332gydqvhHsINkWIAFckIAAFcvnwZb7/9tuIErl271nBdchwAo5PQWgVAOwPDa41egROXb2H229VQIY/YKmCRKWArSWhlAODpq7dRbdRyyAZAvg+pVQC0s1OYsy0CPf4Ig1kANLoykCehtQqAX7Ypi5blchhu17Gd2GtmGGZujYBsALTq9nMA3NinPrIGJ7el7DzcQzYAWon3lQGAVt1+owDIwz2sAuDLlXNhZCt7EkHzFf+yAdBquIeZCu50/23mGWVfE68B8KOPPsK4ceNw69YtVKlSBf/88w8yZMgQUHPmDrJ//GAVKFeuXIiMjERQUJDsdwW+C0FcA8Bc6VNgTe/YE0ETACbCniHiW87JWBlIAEgAKJryScQBJABMjF0mpoC5A0gAaKwrJgCMYw7goEGDMHjw4Fjf/pYtW1CxYlRKiYsXLyru3/Hjx5XrgoODFQhMkCCB398I9PtOA6DZbaj4FLDXHEARADSTgkKqA5goIQ4MN78KWG8KmDuAZnOQyQTAmoUyYmqnEGNfW9VZog6g2W2o+PSTDAewV+MieKeuvClg7gCaHezJdADNLPgyA4Bmwj1kOoBm3X5RB9Dsgi+ZAGjW7Tc6BcwdQLNuv/BHiKaA494UMAM69i+2I2/evEiePOaUSEREhOLmsUUgbHGIv8NtB5AnofUSANYeswLHL7Ep4KqokCe9UDsU2R2AO4BeAcAzkbdRdeRyJJUMgHwfUi8B4NztEeg+IwzSATA6BYWXALD3rDD8ERoB6QBoMdxDBgDycA/ZAMhX/HsFAK2GexgFQD7Y8xIAWo33NQqAVsM9hDqe6JPJAYxjDqCZSsCvOXnyJHLnzo0VK1agTp06hn7K6QpkFQBlBIYTAMp1AAkAd4IAUDzfYMG+8/Hg0WPYGQNIAGhuwRcB4EXopYEhADSEHLafFC9jADdv3gz2r0aNGkoOwCNHjmDgwIE4c+YMdu/ejWTJkhkS2i0ANLsNlUwAnPVWVVTMK98BNJODjE8B25kbjDuASRIlwMHhzQzVF/VJRvcH5QBoNgmtjClgpx1As/uQypgCdtoBNOv2ywRAMwu+RKaAuQNoxu3nU8D5MqbCip7GBvJ6jdfnAJp0+0UB0OyCLxlTwNwBNOv2izqAZgd7eu/Q39+d7r/NPKPsa+IlAIaHh+P9999HWFgYbt68qeQCbNKkCfr3748cOYyvFnS6AvEktF4CwDpjVuDYpVswA4AiuwNYSUIrAwDPRt5BlZHLYBYAje4O4EUA/HP7KXwwY4f0KWCeg8xLAPjRrJ2YEXrS/BRw9B69enkArbr9MgDwP7dffMW/yHaMVsI9ZACg1XAPPgh7qWJOjH6xTMA+nbd1LwEgX/AlHQAthnuYASWn+28zzyj7mngJgHaJ6nQFen78Omw/cRUtymbHV23L4dy1O2DZ40PyB165rC6rDAcw78f/KrcY164cni2dHQvCzyB5kkSoWzSzrswiAMjvM61zCKoXzAi2bRILyo5tNwX+ADICwzkAsnscHdlMmW6btvE4qhXMiMJZ0uiW3agrwDsF9oPHRj2Dx48fY2dEJPJnSoU0yfXzVcpwAKduOIYB83YrZWTPdP76HczbfhqtK+ZE2pRJdcvOF4HoTQv9uvE4+v+5y3efew8eIfzUVZTJmRaJEyXUvY8MB7DhF6tw8PwNVM6bHn+8VRXhEZHYEXEVr4TkDrh4TP2gRnNxtvh2HcJOXkXLstnxZdtyuHLzHk5H3kaJ7MG65WYnyABA3ga/a18eTUtlw/zwM0iRNBHqFtFv6yK78fD7TO8corSnIxduIFmSREJt3U4HkAOguq2zusm+Q0bautFcnFbbugwHcPL6Y/jkL1Vbv3YH83YYb+tGc3Fqvymibd1Qo9Cc5HT/beYZZV9DAGhBYacrEP8wskf+pWMldPxli/L0v3etgioGIFAmALLn6FanAMavPKw80/5hTZAscaJY1TUDgOwHv3m5HP7323blt4+MaIaECf2v2pYJgDw3GLsHS7uw7tAlJR8ihyK9amUUAFnnV+/zVcrPjX6xNHZGXMWvG0/AaAcnIzls47Grsf/cdeWZ2LaEw+fvVf53lfzp8XtX/wuo1HoYBcAmX67GvrNR95nUsRL6zAnHmcg7eKduAfRqXFRPYrwycRPWHroIO1cBq9sgW6E7Yv4+5Tm+alsWLcrqzx4YBcBAbd1oDj6ZAMjK+1btAvh+VVRbZ4nQ2WAstsMMALLf+/rlcnhPoK1vOXYZrb/fYLh96FYiAGowaxeSG2sOXlC2vzTa1o0C4MFz19Fw7Grldz9rXQbs+zh90wllsLf8Q/3p7G+WHcTnSw4o3yO78gDW/3wlDl+4GaOtVyuQAdO7VNGVzygA8oEV+8HpXULQf+4uHLl4E+/VK4gejYro3sfMCU7332aeUfY1BIAWFHa6Aqk7BfVjtw/JjeHPl9ItiYyVgYGeaeegRgjScajMAqC6oHuGNEbKpIljLbsMB5Bv3O7vxswV0zuMAuC+s9fQ5Ms1fn/OyH1kuALqTkH7YEaeySgAVhy2BBdv3DNddg6ARuFM752xvweq783LZFcGJnqHGQBU/+arVfNgSIuSerfxOYCb+tZHliB7EkEHKnv4oEa6brRZAFQXdO+QJorjGNshAwAPX7iB+tGDMDP13SgA7j4diWe+9r8RgZF29R8A5sbIVvr9gW4lAsBDfMx+54wCYLkhi3Hl1n3Tbd1IWbTnON1/m3lG2dcQAFpQ2OkKpP4Al8oRjPBTkcrTs9E4iwvUO2QDYOV86bH56GXlMcI+aYTgFLFPUdoBgLsHN0aqZM4D4P6z19H4y6jROuv8/w477ZPfyMfaKACyaUA2HciOYtmCsPfMNaH7yADArlNCsXjPOeU5WpXLgTnbTwk9k9HA8LY/bMDGI1H1qWSOIOw6JVZ22QDYqnwOzNkWVfb36xdC94aF9ZogzACguq2/WSs/+jQrpnsf7gDKAsCKedIh9PgV5TmMDPbsAEAjgz0ZAMjaXNOvogZhz5XJjr8E27pRAORpsdh9imcLwh7Bti4DADtP3oKle89bbutj25TB8+VyBqy3L03Y4Os7CmdJjQPnbgh9U3QbhJ8TnO6/zTyj7GsIAC0o7HQF4gBYNGsaLPygls+N+Om1iqhfLItuSWQCIJuqaVoyKwr1WxAFgAMbITilMQDMnT4lVveuG+vz87KzaVD2ES46YKFyvlsAGHHlFmp8ukJ5BgZ8qw5cwGs/b0a24OTY0Ke+7rswCoBqV4Ddh8VYvj1tG9IkM7ZhvAwA/GLxfny9/JCv7IP+2o1J64/hlSq5MbrqCoAAACAASURBVKylvvNgFAD5tmtc486TQ7F07zm0qZgLn76ov9WVDACsNHwpLly/Cz4Fxnet+P6V8mhSMpvuexcFQAYC89+vKdzWZQIgi/dtVDwr2L7GSls3MNgzA4BsGrRZqawoPnCRch+3AFAbm7dy/3m8/ssWZA9OjvUG2rpRANx1KhLPfhPlALK2zkCTTX8bzQAgAwA/W7Qf41b819YHztuFKRuOo0OVPBjaUt+JNuoAsnJysGZl7zRpC5btO2/rvsbaxul0/637cXDhBAJAC6I7XYHYR5TF3fR/phjyZEilOEPMIZr4akU0KO4OAK4/dFGJVelWpyAePX6MgpIAkG0WvvHIJYxpXQYPHz32ASDbMontnRnbIWMKmN2PBYKnTZlEWfyy9uBFvPLTJnA416tWRgGQLfoYOG83sqdNgbfrFMCKfefRcdIWxRH753819W4DGQB4+95DfLfyEBoWz4pSOYPBO4nXq+XFoOdK6D6TUQC8eOMu+s0NR9vKuZWFBiPn78WE1UfQpWY+9HumuO59ZAAg2691xpaTeKNGPmRMnQwvfrdeccL4wgi9hzIKgGzl+ncrj2DAs9FtfdxahEVEwuhgTwYArjt0EcylYjugsEVPvsGezQD42+YT2HTkkhIHd+/hIx8AGhnsyXAA2TuduvE40qdMimdKZ1NiADv8tFlx5Be8r98GjQIga+sD5u1CznQplVmd5fvO4Y1JoSidMxh/vVtDr2pBBgBq2/rohfuUOO+O1fPik+bG27qeA8gWNHafsQMsxIENpEbM34sfVh9B11r50deA460rjp8TnO6/zTyj7GsIAC0o7HYFavntOuw4eRU/vloRDQ0AoIzAcLV8Dx4+8gHgjoENdVeEiuQGU9/nzv2HPgA0En8kCwDVzyQLALXVc8X+88rinxLZg/Dve/qdjwwA1D6TLADU3mfkgr2YsOoIOtfIh/7PugOA2mdq/f16bDl2BePbl0ezUvY5gNr7iA72CvSdrwyU7JwCVj/T/YePhNx+EQdQfR8GIMUGRrn9RgZ7sgBQ/UwcAI0O9owCYIy2Hj3YYyEAf//PHQDUPhMHQNHBnh4AxmjrgoM9M9242/23mWe2+xoCQAuKul2BeFoYrwAg63BYx8OO7QMaIl2q2FOCmAXAuw8eokj/qE5BBACNrpw1UyWYO9J+4iYUyZIGi7rX0v0Jow6g9of49JOXAPDzxfvxzfJDeK1qHgw2sEDBqAOoLfuoBfsUB9xLAPjS9xuw+dhlfNuuvOIO6R1GHUDt7/DBnlG3XzYAig72zAKgerAnAoD5M6bCcpsSQWvfhehgzzQARg/2vASAYxbtw7crDkM6AEYP9oy6/Xrtzt/f3e6/zTyz3dcQAFpQ1O0KxAHwhw4V0KhEVt2SyHYAHz16jPwOA6CRAHQZyWG1YrOp8HYOAiCPDdN76U44gDwm0CkA7FQjHwZ4xAHkwes8D6be+7AKgEYHe7IBUD3YM+L22wGARgZ73AGUCYB8sCfdAYwGQKPhHjKmgLX12azbL+wACrr9eu2OANC/QgSAZmpO9DVuA2Cr8euw7cRVTOhQAY09BoDbBjREeh0HUGR3APVrYklCRQLQnZgW4gDIVrAt7l5bt1YZ3R1A+0N8sYnR+CMZucG0z8QB0GiKErMO4KcL94FtofdG9XwY2Fx/Crj9xI1KfkY708Boy95mwgZsOnpZSQHDVoPrHXwh1vqP6ylxnUYP0cGekwBoxO3nu/HkyZASq3rFvuBLrYnaATQy2GNZCBiUOwGARt1+sw6gqNv/9bKD+ELJA2hfGphAAGh0sMfjcEUBkLv9Rgd7RtuR+jy3+28zz2z3NQSAFhR1uwK98N16KAtDXqmAJiWNO4Cy4oJYEHO+PlFTwFv7N0CG1LHvqWwWAEXjjxwBwMMX0e7HTSiUOTWW9DAOgEZXtPJquvrABbA8ekbdBydcAdbpsM7H7pWB2qYpGoDuBADyVDVsFTxbna53mE3GLjrY4wC4uW99ZLYpD6C6bGq339hg7zJe+G4DRPfjVod7GFlt7AQAmh3sta2UC6Ne0F+9znXmgz2jbj8HQJaseoSBvLB6ddXf33m4h9HBntlk7KKDPTNlcbv/NvPMdl9DAGhBUbcrkNcAkEnJ07WE9m+grJKM7YhLALjh8CW8/OPGeAmAY5ccwFfxFABf/mEjNhwx7jLGFQBUD/biHQBGD/ZE3f64AICibj8BoAXAcOBSAkALIrsNgDwFhdEcZDJSQ2jlcwIARQPQnXAAOQAWzJwaSyU6gKIrEJ1wADkAiuYBFJ0WEg1Ad8IBbPfjRqw/LB8ARQd7sh1AcbffnAP4RLiHgdyijjiAJt1+UQDkbr/RcA8nHEAOgEbdfrMAKOr2m+nG3e6/zTyz3dcQAFpQ1O0KxFNQGM1B5iQAbunXAJnSyHEARVcbOwGALEdh2x82okCmVFhmYN9Os3FBfAWi0fgjJwDwy6UH8OXSgzC6JaHR5LCB4o+MrkB0AgD5PYzuN2zWARQd7MkGQHG33xwAqsM9jCw2cQIAzQ72RAFQdLDnCABGh3sYHeyZBUDRwZ6Zbtzt/tvMM9t9DQGgBUXdrkA8BYWXADBfn3/x+DGwuV99ZE4T+x6kZlcGiq42dgIAWeLaNg4AoGi6GScA8KulBzF26QHpAMjjj7wEgKJB7mYBkA/2jLr9cQUARd1+JwCQD/ZE3X5RABRNN+MEAIq6/WYBUHS1sZlu3O3+28wz230NAaAFRd2uQBwAjSahlb0ykEnpNAAaiT9yEgDzZ0qF5RIdQA6ARuOPnARAo8HnZh1A0XyDTjiAoiuarQKg0cFe/j7/4hEbiElaBKJ2AI25/eYcQDUAGllt7CQAirr9cQkAjbr9BIAWAMOBSwkALYjsOgBGb6BtNAmtEwAo0vGYdQBF44+cyA0m2vGYnQLmKxCNrjZ2AgBF00+YBUDRAHQnAfDz1mXwQoXAm93zz4xZABQd7Im0Q7OfQLHBnjkAVId7GBns+dqhwYGYmbJzt190sCcKgKJuvxMOIA/3MDrYMwuAooM9M+/R7f7bzDPbfQ0BoAVF3a5APAeZlwBQBDLNAqDafTCSbsYJABS9h2kAFAxAdwIARe9hGgCj44+MpqBwAgBZSh4WrM/2rX1RJgBGD/aMuv1OAKDvHobCPcwBoGi6GScAUPQevK2LAqBocnknAJCHe8gGQNHk8ma6cbf7bzPPbPc1BIAWFHW7AnEANLoLgQicmZWF32Njn/rIGiwnBlA0AF3UnTNTdtFpZqsAaDT+SNSdM1N20WTTVgHQ6ApE0RW6Zsr+2s+bwfK1jXmxNFpXzKX7E6YdQEG331EANDDNzBNBi+YBVAOgkcGeqDun+8L8nCD6PbEKgEbDPUThzEzZ+T2MJps26wCKuv1myuJ2/23mme2+hgDQgqJuVyCehNboLgROBIaLbDdnhwNoJP5I9INtpkrw7eaMdnBmAZCvQDQaf+SEK8C3mzPqcJgFQNEAdA6ARpM0m3nvr/+yGSv3X8DoF0vjJYkAKDrYE3HnzJSbXSMyoDQLgOpwDyO5RZ0AQLODPaPtg7+P9YJuv+hiLDPv/b8BZS6MbKWf1No0AAomlzdTFrf7bzPPbPc1BIAWFHW7AvEktF4CQBGHw+z2UOyV8fgjrwCgaAdnFgBF0804AYCiDodZAOTxR0ZTUDgBgB1/2YwVDABfKI2XKuk7gHyAtKFPPWQLNr4VHB/sGXX7nQBAkbRSogMk9WdZJLeoEwAoure46ACJl100ubwTACjq9oumSeJlF00ub6Ybd7v/NvPMdl9DAGhBUbcrEAdAow6HEw6gyF6ndgCgkXQzTjiAomURhSZeTTkAGg1AdxIAjW5rxwHQaO48XnbRfINOAOAbk7Zg+b7z+PSFUmhTKbfu10TEIVf/mKjb7yQAGgn3EIUmfwBoZLDnJAAadfs5AL5c2ZhrpgVAo+EeTgKgUTfTbByuqNuv2/D8nOB2/23mme2+hgDQgqJuVyDRGCcnALBwvwW49/ARjGx2LwpN6lclEuPkDABeAdutIXf6lFjdW3+ze7MA6OvgMqbC8p51dGuvkwD4UsWcGP1iGd1nMguAojFOTgBgp0lbsGzfeYxqVQptK8sDQNHBnhMAKOL22wGARgZ7TgCg6HfLLACKuv1OACAvi9HBnlkAFB3s6X50CAD9SkQAaKbmRF/jNgCKNi5HALD/ArDtm9Z9XA850sY+xSX6IVW/KpGyOAGA205cQavx8gFQtCxOAOD4lYcweuF+GAVAs3FBomVxAgA7T96CpXvPY2SrUmCB8XqHWQdQtCxOACAf7BmZzrYCgCLpZpwBwKjBXp4MKbGql/5gzywAiiaXdwIARUNXRPso3n6cKIvb/bfet8KJvxMAWlDZ7Qok2rhEXDOzshSOBsC1H9VFznQpY/0Z0bg5fwC4qW99ZAmKfbWxKDSZKTsHwFzpU2BN73q6P2HWAeRlyZcxFVZ4xAHkANi6Qk6Maa3vAFoFQKMrEEWhSfel+Tmh8+RQLN17DiOeLwWWGkPvsAqAX7UtixZlc+jdRighu+6PBThBxO23BQANrDZ2EgCNuv1WAdBouIcT0MS/W0YHe6J9lBYAjaabMVOH3e6/zTyz3dcQAFpQ1O0KJNqROgGARfovwN0HjyAbAEU6UtG8XWaqxPYTV/D8+PXImS4F1n4kDwD5CkSj8UeirpmZsn+38jA+XbhPyYPH8uHpHaL1lv+eaAC6EwDYZUooluw5h+HPl0T7kDx6RYdIvVX/mGhHKuKa6T50IAAUcPutACD/bhkZ7Im6ZmbKLjrYMwuAogNXJwHQ6GBPtN7y9+FE+iq3+28zdc/uawgALSjqdgUSjaVyAgCLDliAO/cfYU3vusiVXp4DyOOPjASgOwGAO05eRctv10kHQNHVlE4A4PerDmPUAvkAKNqROgGAXaeEYvGecxjWsiReqSIPADk0e8kB5IM9I+EeVgBQJN2MEwDIB3tG3X7Resu7JNHk8k4AoKjbbxYARZPLm+nG3e6/zTyz3dcQAFpQ1O0KJJpOIy4CoJH4IyemhTgAsrhH1iHqHWangHlHajT+SHThhN5z+/s7B8AXyufE5y/JcwBF02mILpwwU/Y3p4Zi0e5zGNqyJFiCar3DrAMo6po64QCKuP12AKCRwZ7owgm99+Xv76Juv1UANBru4cTCCQ6ARt1+6wAotnJa5H263X+LPKuscwkALSjrdgUS3YjeicDwYgMW4vb9h1jdqy5yZ5DnAIrEHzkBgGEnr6LFt+uUhS8yAZDHTRqNP3LCFZiw6jBGLtiHVuVz4IuXyuq2KFGY4T8oGoAumidT98H9nPDW1K1YuPsshrYogQ5V8+r+hFkAFB3sieTJ1H3oACeIuP1WAFAkd6ITACg62DMLgKJuv2ieTDPvnYd7GB3smQVA0cGembK43X+beWa7ryEAtKCo2xWI70P6xUtl0Kq8/kb0TgBg8YELceueAwAYHX9kJN2MEwC4M+IqnhvnBACKpZtxAgB/WH0YI+bHTwB8+9etWLDrLIa0KIFX4xkA8sGekXAPKwAokm7GCQAUHeyZBUDRRXJOAKCo228WAM3OkIh052733yLPKutcAkALyrpdgTgAft66DF4wsBG9kwC4qlcd5MmQKlZ1RUe46h/jq42NxB85CYDZg5NjfZ/6urXK7AiXb59nNP7IUQAslwNftJHvABpdgeiEA9ht2lbMDz+Lwc+VwGvV9B1Akb2y1ZVI1O13wgEUAUDR7dPUZRdJLu9FABRdvMTLLpomy0kANOr2i+aqNev2635w/Zzgdv9t5pntvoYA0IKiblcgvhE9W3nJYjL0DicAsMTAhbh57yFW9qyDvBnlAaBI/JETABgeEYnm49YiW3BybBAAQNHdAfgKRKOrjZ0AwB9XH8Hw+XvxfLkcGCsAgEYXNPB6LRqA7gQAvjNtG/4NP4NBzYvj9er59Jqg0P656h8THew5AYAibr/ogoYnBnvRyeWNDPacAEDu9hsd7Jld0MAHe0bDPZwAQF+4h8HBnlUANDrY0214BIB+JSIANFNzoq9xGwD5RvReAsCSnyzCjbsPpAMgjz8ykm7GCQDcdSoSz36zFlmDkmNjX+MOoCgAigagOwGAE9ccwbB/5QMgjz8ymoLCEQCcvg3/7jyDT5oXR0eJAMgHe0bdficAkA/2jMT7WgJAgXQzTgAgH+zJBkDR5PJOAKAv3EMyAIomlzfTjbvdf5t5ZruvIQC0oKjbFYgD4JgXS6N1Rf2N6J1YGVjqk0W4fveBkqSYrV6L7bAyBSwSgB4XAdDoYhMnAbBl2ez4sm053RZlNi5INN+gEwD47vRt+GfnGQx8tjjeqCHPARR1+/N+/K/yHozsn6v7wgKcwAHQSLiHHQBoZLDnJAAadfvNOoCi+QadBECjbr9ZB1DU7TdTh93uv808s93XEABaUNTtCtTxl81Ysf8CRr9YGi95DACXf1gb+TOlNgSARtMcqH9MJP7Iidxg3AHMEpQMm/o20K1VZgPDRVcgOgmALcpmx1cSAVA0AN0JAPzfb9vxd9hpDHi2ODpJBEDRwZ4TACji9lsBQB7uYWSxCQfAgplTY2mP2rrt0MwJom6/WQAUdfudAEAe7mF0sGcWAEUHe2beo9v9t5lntvsaAkALirpdgd6YtAXL9533AeDjx4/x6DGQKGECv6VyxAEctAjX7zwAB8AL1+8iZdJESJUscYxnsrIykMcf8U7h4aPHAcvthCuw+3Qknvl6LTKnSYbN/aIA8OTlW8ieNoXf5zILgP5WIMZWdicA8Ke1RzH0nz14rkx2fP1yOTx69Binrt4OmAjcrAPI44/UKShiK7sTAPj+79sxb8dp9H+mGDrXzI9b9x4oIRCZ0/jfnlAkqbG6wfDBHnf79dq6EwCodftja+tWAFDr9htp604AoHqwF1tbNwuA/pLLx1Z2JwCQh3vwwZ5eWzcLgKLJ5c10427332ae2e5rCAAtKOp2Bao+arnS0b5XvxB6NCwMtiIx7GQkFnWvhdR+gMsJAOQdz7ftyiNHuhTK7hhpkidG+KDGtgIgvw8DzazBydHwi9UonTMY371SIcZ9nARAdnMGpYt2n1Xi4pqXyY5vXo45LWoVANl9jo16BswlYHn1ejYu4jcGzYnksGwbODZiZweLB+v3ZzjWHLyIQOmJzALg54v345vlh3wLbX5ZdxRjFu3HtM4hKJc7XYz33vaHDdh45LKiP3sPMo6QEUtx7tpdVMiTTilv7TErldsESk9kFgCrjlyGM5F38H79QujesDBY+pnwU5FY9EEtv4MrJwCQ3+O79uWRJTg5Wo1fj6DkibHTT1u3AoD8PmxhWeagZGjw+SqUzZ0W49vHbOsbDl/Cyz9uhBMAyNv6wl1nlUVQgRxwqwDI2zqbEu4wcRN6NS7id8HR2CUH8NWyg3ilSm4Ma1lKRnXHyAV7MWHVkRhtfWybMni+XMyFiGYB8LNF+zFuxSHDeVXNFNbt/tvMM9t9DQGgBUXdrkD8w8iKkCAB8PhxVGECdbxOBIarn0ktLYMV7WHFARS5jxMAuHzfObwxKdRvbfJXdrMA+FfYabz323bD93HCFeBurL+H8ld2swAYqL6nSJIIe4c2CQiA49qVw7Ol5QBgoHoYaGcQswAYqOxftimLluVyxCg7Pz+0fwNkTJ3Mwlcu8KUibdAOANQ+ib+65QQA/rPzNN6dbrwNmgXAP7efwgczdhhu6xwA2Y40rP7JOAK9cw6p2nuaBUBtfWcDnw8aFLa1SG7337YWxuSPEQCaFI5d5nYFEu18CABTYdmHdSy88cCXLtlzDl2mRAEgAxK2Gwo/7ATAmaEn0WvWTsOdghMA2OCLVTh0/obyTGy6nyUCj63sdgCgERjgDqBTAMhcdzb9y45AO4PYAYDqso94vhTaheQmAIxWwAkAXBB+Bm9P22a4rZsFwBlbTuCj2eGG27oTAFhx2BJcvHHPcFu3AwDZzT5oQAAoo+MiALSgqtsAyF2k71+poExBVRq+VCnN7LerKf+tPZwAwCF/7wGLh/u1cwgu37yHkBHLlMew2wHk8V1sBeL563fR+vsNAe/jhAN478EjMLApnzsd+jQrBh4rkzZlEuwY2CjGuzDrAEbevo9Kw5YqU1yT36isTMnM2XYKLOzzyMiYLqsTAMjed5fJoejRqIiSj7LR2FU4cO6GsiiCLY7QHmYBcP3hi2j34yZ0rpEPb9Yu4Kvvr1fLi0HPlYhxHycAcPHus/hs8X582aYcimcPAh+UzXyrKirlTR/jmcwCIIeICR0qKHWMt/U53aop/609nHAAP5q1E7tOR4I9A2vrVUcuD9gGrTiAbSZswKajl5XwgtORt9H2h40B7+MEAN65/1AJbamYN50y1cpTo6RPlRTbBjSM8S7MAiBv64WypMakjpUxYv5ezN1+CkkSJcDB4c1i3McJAGQLYNhAt2ejIsrmA/U/X4nDF26iS8186PdMzLZuFgDXH7qIdhP/a+uB4sgtdN+uGzhWnt2uawkALSjpNgCyR7/74CGSJU6klKLW6BU4cfmWqwColvP89TuoPHyZMj191A+cWNkdgAUfP3j0GEkTJ8Tpq7dRbdRyJE2UEAeGN43xRp0AQO1N5+04hfd/34FqBTJgepcqsXQK4puds3fOypogQQLM3hqBD2eGoWahjJjaKSTGfZwAQO1N+8wJx2+bTyhxqSw+1S4A1Nb3XjPDMHNrBHo3KYJudQq6AoDam9b9bCWOXryJP96sisr5YgIgT8a+qW99ZAnyv1Ak0CdJ3dZrjl6Ok5dvK/DlFgCqn/PctTvKYI8tQDs8IiacbD56GS9N2ID8GVNheU8xF5619YePHyNJooSIuHILNT5dobT7A8NitnUnADBQW69eMAOmdY7Z1r9edhBfLDmAlyvnxshWYrF56rY+a2sEes4MQ+3CmZTBn/ZwAgC19/x49k78vuUkPmxYGP/z09b5QF006bu2rVvopgNe6oX+W0a5RH6TAFBELc25XqtAtceswPFLDACrokKemJ2PEw6gWiK2KpA7Ff4cQCsAqL7PmcjbivsQaGTsBgDyWL2q+TPgt66xAaB4p6Au+5xtEejxh7cAsO/ccEzfdALdGxTG+w3sBUB12XvPCsMfoRFKUPw7db0BgPU+W4kjF29iRtcqCMmfIcbXxbcbT9/6yCwIgOof0xvsOeEAPjHYu3YHlUcsC+hE+wAwUyostxCGwRa9scVvgQZ7bgJgoMEeB0A2Vc+m7M0efLBXq3AmTPEIAPaZsxO/bT4ZcLDHAZBlB2BZArx0eK3/dkMbAkALqnutAtUZswLHYgFAJ1YGquW8eOMuKg6LmpaWCYBnI++gyshlngJAlhuO5YiTDYBzt0eg+wxvAWC/ueGY5gAAsinIGSwm0ksA+PlKHLkgHwD/G+z5D/dwHACj3f5AoQh2AaCe2+8GAPLBnmwA5IM9bwFg7G4/AaAFwHDgUgJACyJ7FQBnvVUVFf3EHzkNgJdu3EWFaAA8OrKZMmWpPuxyADkAJk6YAIf8TD85kRxWW404AFbJnx6/d60ao5aZjQvS/hAHwBoFMypxl9rDjSlgDoCBArfNxgVpy+ZlAPy9axVUkegA6rn9bgFgoHAPuwEwkNvPAbBQ5tRYIikRtLYe6rn9djmAem6/G1PAPNwjkNtPAGgBMBy4lADQgsheA0AefxQoAN1pAGSB4eWHLlEUPjKiGRJqElRbCQxXvza9+CM3XAGeKiIkX3rMeFMeAPJUEYHij5zIDaZtQv3/DMevG0/4ctZp/24XAPL4o56NCuPdejGnmvniAZmrgLVl40Hxv3WpgqoF5E0Bc7dfb7AnMw2Muux64R52ASAP9wg02OMLhZwEQL3Bnl0AqOf2szhDdi+ZaWC09Z2HewQa7BEAWgAMBy4lALQgstcAkMcf6QGgU53ClZv3UC4aAA8Nb4rEiRL6dQDNBIarf+h8dPxRoAB0NwDw351n8M70bZANgHyxiR4AOtkpDPhzF6ZuPC4dAHn8kR4AsqTkz5TOZqGlG7+Up8SRDYB8sKcHgFv7N0AGSXkA1arohXvYBYB6br8bAMgHe4HcfrsAkA/2Ai344gD4atU8GNJCTh5AbUvQc/sJAI1/O9w4kwDQgupeBcBAKxCdnhaKvHUfZYYsVhQ+OLypsopPfdjlAHIADBR/5CYAspWg7H1oD7umgPVWG7sxLcQBkO9QI8sB5AAYaAUidwDdAMDpXUJQrUDGGO/drkUgRt3+uAqAgQZ7bgJgoMGe3QAYKNzDTQDkO9RoKzwBoAXAcODSeA+Ad+/eRUhICMLCwrB9+3aULVvWsOyeA0CdAHTHAfD2fZQZHAWALGUDS90gBQB10s24AYDzw8+g27RtqJw3Pf54Sz4ABlps4gYADpy3C1M2HMd79QoquQHlAWDsAehuAGDDL1bh4PkbmN45BNUKygNA7vbrDfacAkC9eF+7HEAe7hFosOcGAHK3P9Bgzy4A1HP73QBAHu4RaLBHAGgYJ1w5Md4D4Pvvv4+DBw9iwYIFTz0A8vijQCkonAbAa3fuo/SgKADcP6yJL18hr+l2OYA8/ihQALobAMh3C5ANgHoB6G4A4CfzdmGyAwDI448C5Rt0AwB5EmzpABg92PMKAKrjff0t+LILAPXcfjcA0DfYC+D2x2UA1HP7CQBd4TrDN43XAMigr0ePHpg9ezZKlCgRZwAw0ApEpwHw+p37KBUNgPuGNkHyJFEJq2UBIPtdt/YH1bY4DoCV8qbDzLeqSZsC5gAYKP7ITQD8X72C+FCiA6iXb9BNAJzWOQTVZTqABt1+pxxAvQVfdgNgoMGeqwAYwO23GwADpZtxwwH0AWAAt58A0DCLuXJivAXAc+fOoUKFCvjzzz+RMWNG5MuXTxcA2XQx+8cPNgWcK1cuREZGIigoyJUXqL6pXgC6CX964AAAIABJREFU0wDI9kUt+cki5RFlAqBeALobDuDCXWfw1q/bUDFPOsx6Wx4A8hWIgeKP3ADAQX/txqT1x/Bu3YLo2VjeFLBeALobANh47GrsP3cdv3YKQY1C8qaAuduvN9hzCgDVC77YTiAsRk992AaA0eEegQZ7bgCg3mDPLgDUc/vdAEAe7hFosEcA6DoWxPoA8RIAHz9+jGbNmqF69ero378/jh07ZggABw0ahMGDB8cQ1CsAyOOPAq1AdBoAb959gBLRALh3SBOkSPqkA2hleyj1S1DHH3nFAVy46yze+nVrQAC0sj2Uuux66WbiMgDy+KNAKSjcAMAmX67GvrOBAZDvxrPZ4k4gfLDnDwDZ9y1fn/lKNXEKAK/euoeyQ6JSPvkDwE1HLqHNDxuR3+JOIHrpZtwAQD7YC+T2f7X0IMYuPQCrO4HoJZd3AwB5uEcgAOT7cdNOIN4EwTgFgIEA7Ylpxy1bsH79esyYMQOrV69GokSJDAOg1x1AXwB6gBWITgPgrXsPUHxglAO4Z0hjpEya2L8rYGJ/0EAA6C/+yI3ksBwAK+RJp+zNrD3scgU4AAYKQHcTAN+pWwC9GheNUXaeB9Bqp6CXb9BNAJzaqTJqFsoUo+w+AOxXH5nTiO0FbNTtdxsA/aV84gBYIFMqLLOwFZxRACycJTUWd6/tSK+r5/ZzAGwfkhvDLWwFp5dv0E0ADOT2cwD85uVyaE5bwTlSH0VuEqcA8OLFi2D/Yjvy5s2Ltm3b4u+//35iZ4qHDx8qMNi+fXtMnjzZkIZeWwWsF4DuNADevvcQxQYuVLTcPbgxUiWTA4B68UduuAKLdp/Fm1O3onzutJjTrbo0APStQAwQf+RGctjBf+/GL+uOoVudAujdJCYA2jUtpBeA/tKEDWAus5NpYLgDyPZqZVt2aQ+7ADC2wZ4bAKiX8skuAFSHe/gb7K0/dBHtJm6CswAY5fYHGuzZBYB6bv8Xi/fj6+WH4GQeQB7uEWiwRwBoCCVcOylOAaBRFU+cOAEGb/w4ffo0GjdujFmzZikpYXLmzGnop7wGgDz+KNAKRA6ATk0L3bn/EEUHRAHgrsGNkToQAFqcFlLHH/nbccQNAFy8+yy6Tt2KcrnTYq5EANRLN+OGKzDk7z34ed1RvF2nAD6SCIC+dDP1Cymb0WsPDoDj25dHs1LOJIJu+tUa7D1zDZPfqIzaEgHQN9jz4/arAXDbgIZInyqpoe+ZlZMidVI+2QWAeulm3ABAvcGeXQCol1yeA+BrVfNgsEOJoDkABhrsEQBaaVXyr42XAKiV1WgMoPY6rwJgoBWIbgJg+KBGSJM8yRMS2hUYrheAHh8AMFD8UbwAwAArEOMFAPrJNxhfANDvYM8FB9BpAAwU7kEAKAZMXuu/xZ7enrMJAFnqEIOLQLwOgHoB6E4D4N0HD1Gkf5QDuHNQIwRJAkB1ALq/+CM3AHDJnnPoMiUUZXOlxZ/vyJsC5isQA602dgMAh/6zBz+tPYq3ahfAx03lTQHrBaC7AYDNvlqDPWeuYVLHSqhTJLO0KWDu9vsb7LkBgHo5P+1yANXhHv4Wm7jhAOq5/XY5gLpuf/QUsJMOIA/3COT2kwNoD6jJ+hUCQAvKem0E4TUAvPfgEQr3X6AoHPZJIwSnkOMAquOPvAKAS/ecQ+cpoSiTKy3mSQRAvQB0NwBw2D97MHHtUbxZOz/6NC0Wo4XZFQPIp58CrUB0AwCf+XoNdp++hl86VkJdiQDI27pXAFAv56ddAKjr9rvgAOoN9uwCQL3k8m44gDzcI9BgjwDQAmA4cCkBoAWRvQqAgVYgOu0A3n/4CIX6RQPgwEYITikfAP3tOeyGA7hs7zl0muwcAAYKQHcDAIf/uwc/rnEOAAOtQHQDAJ/9Zg12nXIOAP3lG3TDAdTL+SkDAP0O9lwAQD7YC+T22w2AAcM9XHAA9dx+AkALgOHApQSAFkT2GgDyAPRAKxCdBsAHDx+hYDQA7hjYEGlTPhmMblcMoF4AuqsAmDMY896tEaOW2ZUGhqebCbTa2FUArJUffZrJdwADrUB0FQBfr4S6ReVNAXMH0N9gLy4DoDrcw+9gz0UADOT22wWAum6/iwAYyO0nALQAGA5cSgBoQWSvASCPP/IHgG6khnj46DEK9I1KSLt9QEOk06xGtAsA1fFHB4Y1RdLECZ94q24A4PJ95/DGpFCUzhmMvyQCoF4AuhsAOGL+Xvyw+gi61sqPvhIBkMcfeQkAm3+zFuGnIvHz6xVRr2gWaTGAfLDnDwAfPXqM/NHtzqlVwHpJ3+1yAPXSzbgRA+hz+wMM9uwDwNiTy7sxBewL9wgw2CMAtAAYDlxKAGhBZK8CoL8UFG4AoF5HZNfuAHoB6BwAncwNtmLfeXSctCUgANq1OwAHwEDpZtwAwJHz92KCgwAYKAWFGw7gc+PWYmdEYADkLvxmi4mgY3P79dqdhU9ewEvVSd/97fqz8cgltP1hI6wmglYDoN/BXrQDWCRLGizqXktGUWP8Jh/slQkAgF8uPYAvlx6E1UTQesnl3QBAX7hHAADkydgpEbQjVVH4JgSAwpL9d4HXAJAHoPtbgegGAOrd0y4A1AtAd8MV4ABYKkcw/v5fzClgu1wBvgIxUPyRG8lhOQB2qZkP/Z4pHnARiNVOQS/f4Evfb8DmY5fhZB5ADoA/vVYR9YvFdAA5AG7p1wCZ0iQz/fXhbr+/wZ7bAOhv1x8OgAUzp8bSHuZ36FCHe+wf1gTJEj+5veS6QxfRfuImuAGAgdx+DoCvVMmNYS1LmX7nem7/54v345vlh+DkKmAOgIHcfg6A49qVw7Ols5suu4wLvdZ/yyij3m8SAOopFMvfvVaBYgtAdyMuiEkX2+4jdgGgXgC6KwC4/zw6/rIFJXME4Z//1YxRi+wCQL4CMVD8kRuuwMgFezFh1RF0rpEP/Z+NCYB2TQvpBaBzAPyufXk0dSgRdItxaxEWEYmJr1ZEg+LyADC2wZ4aAP2FXlj45AW8VG/XH7sAUO327xvaBMmTuA+AeoM9uwBQL90MB8DXq+XFoOdKyHjNMX6Th3sEGuwRADryGkzfhADQtHRQdhMJDg5GZGQkgoKCLPySPZfy+CN/KSjcBkB/joddcUHq+CN/nYIbALhy/3m87gAA6qWbcQMARy3Yh+9XHZYOgDz+KFAKClcA8Nt1CDt5VToA8sGeP7ffDQBU7/rjb9tHuwBQz+13wwFcET3YC+T22wWAfLAXKNzDDQDUc/sJAO3p22X9CgGgBWU9C4B+ViC6BYCx7X0qAwD9xR+5CYAlsgfh3/fkOYA+AAwQf+QmAHaqkQ8DJDqAevkG3QTAH1+tiIYSHcDY3H63AdDfto/xAQADuf12A2CgcA83ATCQ208AaAEwHLiUANCCyF4DwNgC0N0CwPx9/sWjx8DmvvWROSj5E2rbBYDqAHR/8UduAOCqAxfw2s+bUTxbEOa/Lw8A+QrEQPFHbgDgpwv34buVh/FG9XwY2FzeFLBeALobANjy23XYcfIqfuhQAY1KZI3xdbErBtDn9vsZ7LkNgP62fbQLANXhHv4Ge244gNztDzTYswsA9dx+VwAwOtwj0GCPANACYDhwKQGgBZG9BoA8/shfCgq3AJClgWHpYDb1rY8skgBQHX/kFQBcfeACXnUAAPXSzbgBgKMX7sN4BwCQxx+9GWAFohsA+Pz4ddh+Qj4A8sHeLx4BQPW2jzIBUC/djBsAyAd7sgFQL7m8GwDIwz0IAC2AhIuXEgBaEN+rAOhvBaJbAFiw73w8ePQYG/vUR9ZgOQ6gXgC6Gw4gB8Bi2YKwQKIDyAEwUPyRmwDYsXpefNI8ZjC6XYtA9PINugmAEzpUQGOJDmBsbr8bDqDevt92OYBqAPQ32HMTAAO5/XY5gHr5Bt0EwEBuPzmAFgDDgUsJAC2I7DkAjCUA3Y3UEEzaQv3m4/7Dx9jQpx6yBaeQMgWsDkD3F3/kBgCuOXgBHX7ajKJZ02DhBzHzkdm1CpivQAwUf+QGAI5ZtA/frjiMQKsR7QJAvQB0NwCw1fh12HbiKr5/pQKalJQ3Bczdfn+DPb0E7BY+eQEv1dv32y4AVId7+Fts4gYA6g327AJAPbffDQDk4R6BBnsEgDJam32/SQBoQUuvASCPP/KXgsItACzcbwHuPXyE9R/XQ/a07gCgG53C2oMX8cpPm+QDoE66GTcA8LNF+zFuxSH5ABgdfxQoBUXr79djy7ErcDINzAvfrcfW41fkA2D0YM8rAPjEvt+fNEJwiif3/bYLAPXcft7WAw28LHzuA17KB3uB3H67AFAvubwbAMjDPQgAZdQs+b9JAGhBY68BYPVRy3Hq6m1f4tuxSw6AJU79pHlxPH4M3/ZQTuUGY9LyoPd1H9dDUPLEePG7DcoeqR83LQq7dgdQO4As/ihJooT4cGYYahfOhJcq5oKbAMg0ODbqGWw7cQXv/74d/ZoVQ5OS2WDX7gA8BUWihAlweEQzHDp/A2xq9L36hcBWC7qRHJYnaGb6s0TFUzccw8S1R/FrpxDkSp8SdjmAfCu4lmWz48u25cD2Sp297RQ+e7EMglMmAQfA718pr2juxFFx2FJcvHEXn7cugxcq5ES/ueE4f/0uJrxSAQkTJvC1B6uJoHlb52VjbZ3lyBv4bHFl0RXfgtHfHtwydHgCAAc2QuJECZRFUHWKZMK79Qphw+FLePnHjbCaCFoNgMztT5wwAT78I0y5T+uKuaA38JJRdg6AvK3vOhWJ3rN2oneTIqhTJDPYu/lq2UFYTQTNATBJogQ4OJy19esYOX+f0tZZHlC9gZeMsg/6azcmrT+GukUy4ZeOlfFH6ElMYe391UpKyA/fjYcSQctQ3/pvEgBa0NBrAMhhixWpWoEMWH/4klK6RR/UQqHMqV0FQK3MDIrsAkB1/FHKpIlw695D3+3YfdwAwAmrDmPkgn3Kc+RMlwIRV24/8Ux2uQIs3x4LxGZHjYIZsfbQxSfu44YroK6HOdKmUAYl7KiaPwN+61rFB4BWOwX1feoVzYzl+84r92lTMRc+fbG0KwCofqbswclxOvKO8kxzu1VDudzpYk2MLvIpUt+nVuFMYNOQ7FjaoxbyZUztOAA+ePgIBfst8FsE1gY5ALLv0BILO4GoB3vMZWQDXH6w+7gBgONXHsLohfsDtnUOgB2q5MHQliVFXvMT505ccwTD/t2r/H/1i2bGsuj6zv6bld0NAFTXw/yZUuHIhZvK87H2+PPrlXwA+G278nimtDODMKMCe63/Nvrcdp5HAGhBTa9VIHVjVBfrr3ero2T24HgBgNrX6RYA8tgYf9WLPZNdANj/z3D8uvFEwI7XbQBUP1jSRAlxYHhT2BUXFKi+p0uZBNsHNnIdANVln9G1CkLyZ5ACgOr7/PO/GmBTkU47gOq4Q39tUAYA+ruPGwDIY1EDtXW7AJDvfBPoPm4DoPq52EB8z5AmBIAW+MKJSwkALajsNQAsMXAhbt57iCYlsipJaNk0KDuWf1gbeTOkcgUAS36yCCx3F9uxYP/Z6z5XTO0AWp0WUnc+w1qWBFstt2J/lCPiFgDuO3sNTb5cozwDc3/embZNcYPYNPjOQY1tA8D1hy+i3Y+blPt81bYs3v99h69Gs7K7AYDc/WRpMYY/XwosNpUd79YtiJ6Ni9gGgJ/M24XJG44rvz36xdLKtBs7utUpgN5NiroCgDwGsHuDwqhdJJOv7Eu610KhLGlsA8DSgxbh2p0HytQna+8fzwlXyr6iZx3kTp/ScQBUZxmY1jkE245fwedLDvjaoF0AqHYa2XT30r3nfDMdbjmA2rb+xqQtuHLrPjgE2QWAfDGbUt9fKI3es6PqO//OuQGALN8nG+yyFdAs1KjNDxuV53mvXkH0aFSEANACXzhxKQGgBZW9BoBXbt7D/nPXEZIvPRIkSIAi/Rfg7oNHSqeQJ31KVwCQTdmwZ2DTNQwAG3+5GhlSJcXWAQ19U8BWAZC9wsMXbij5BgtnSQMWg/PsN2uRJSgZNvVt4MoUMHumiCu3kDF1MmW/0snrj+GTv3bjmVLZ8G378rYBILtP6LHLyJMhFTKlSQY+TdSibHZ81bacKwDIYODoxZvKoIPFvb01dSsW7j6rTH+xaTC7HEC28nTz0cuomDedonGnSVuUabFRrUqhbeXcrgAge6YzkbeV98GOskMW4+qt+7AbAFlbP3DuOipHt/XC/ReA3XtlzzpKnKXTDiAr69Vb95SUT6zO7z1zDU2/WqP879D+DWybAmb3YXGurI4xoA6PiETzcWuRNSg5Nvat78oUMHumk5dvKe2P1cNf1h3F4L/34NnS2TCuXXlfDKDVKWBW5tDjV5AvYypF1x9XH8Hw+XvxfLkcGNumrCtTwNq23nVKKBbvOQc2EH+lSh4CQAt84cSlBIAWVPYaAGqLUmrQIly/88BVAFQ/E+uwGo1djfSpkmKbzQCovs/u05F45mv3AVD9TCwweuC83WhWKivGt69gKwCq7+MFANTWw7d/3YoFu85iaIsS6FA1r20AqL1P58mhiiPkJgBqn6nckMWKG7S4ey1lcMKnrRkUsU7crqPUJ4tw/e4DVwFQXRbuimVMnRSh/RvaCoDq+/DBntsAqH6mSeuOYtDfe5SYNxb7ZpcDqK0rvK27CYDaZ3pzaigW7T7nG+zxRSAUA2hXS7f3dwgALej5tACgm1PAankPnruOhmNXg8do2ZUaQvsKOQBmTpMMm/u55wCqn4uthB0wbzealsyK716RD4DPlcmOr192xwF0GwBHtiqFl11yALVlLz90CS7fvKcsxCqSVT4AujUFrC230wDI3X43YgC1ZXcaAPkqeDemgAkALQCEBy4lALTwErwOgDxOaFl0DCCfFnIyDYxaXpa2oMEXq5E2ZRLsGNjI1ilg9X32nL6GZl+vUaZkWLoNN1YBa6vV1I3HMeDPXUq81vcd5AHgT2uPggWLNy+THd94BAC7TduK+eFnMaRFCbwq0QHsMiUUS/acw4jnS6FdiDtTwNr3XmHoEly6eQ8LP6iJolmD5DmA0W4/G+yxGEC+ItepNDDacmvDPeyKAdTehzuAfLDnBQDUhnvIdgB5uIcXANAX7hHt9pMDaAEwHLiUANCCyF4HwDKDFytpErwDgDfQ4ItVSjxg2CfyAJDHH3EA9EKn8OvG4+j/5y40LpEFEzpUlDYF/PPaoxiiAkAvdApsAcy/4Wcw+LkSeK2avClgHn/EAfDF79YrMVNO5gHUfk4qDluCizfuKdsBstW5sqaA+WDPKwCoDfeQBYBat19vBx4Ln3vDl2rDPWQBIB/scQDU24HHcAEsnMjDPfhgjwDQgpgOXEoAaEHkpwUAl/aorQQOuxEYrpaXLdSo//kq30pYWVPA2gB0LwDgtE3H0W/uLjQqngU/vCofAHkAuicAcPo2/LvTOQAc/nxJtA/Jg/8A0P+2bBaavuFLeWLo+e/VRPHs8gGQDfbYgi/uAIYNbKQkxXb64OEePN5XNgDywZ4XAJCHe/B4X9kAyMM9OAAG2pXDiTqgdfsJAJ1Q3fw9CADNawevAyBfgehWclittEcu3EC9z1chTfLECB/UWNoUsDb+yAsAOH3TCfSdG66k5/lRIgDyFYg8AN1LADioeXG8Xj2ftEUgPACdr0D0AgBWGr4UF67fxb/v1UCJ7MHSHEDu9rPBXt4M3gFAHu8rCwB5uAdfbewlAOTxvrIAUOv2ewkAudtPAGgBMBy4lADQgsheB0C+ApGloMifyfndAbTSstQgdT9biTTJEiN8cGPbtofSiz/yAgD+tvkE+swJR4NiWTDxtYq2bQ+lLbsvAD063YwXAPDd6dvwz84zSp6wjhIBUJtuxgsAWHn4UmUrOJagmeVFzNdnvvLK7F4F/N9gzxsAqI335fkqre4Eoq3v/7n9UauNPQGAmnjfL5YcwNfLDiopkKzsBKItOx/s8XhfLwAgD/fgg72Xvt+AzccuK6uhaScQC7Ah6VICQAvCEgCKiXfs4k3U+WwlUidLDLaPp137gz4NAPj75hNKst4GxTJj4muVpKWG8CIA/u+37fg77LQPAGW5Al4EwJARS3HuWkwA3Nq/ATLYmAZG7faz/ItuTwGzXH0s3pcv+OIAWDhLaizuXlvswxHL2V4EQB7vyxd8cQB8tWoeDGlhfiu4QADIwz08AYDR4R5aABzfvjyalaKt4Gyr+Db9EAGgBSG9DoA8BQXLQVbAAw7g8Us3UXvMSqRKmgi7hzSRlhtMG4DuBQdwxpYT+Gh2uLKH50+vywNAvgKRxx95wQHkAMh2bnijRj5pyWG1+Qa94ABWGbEMZ6/dwd/v1kDJHP85gHYDoNrtZ/G+XgFAvuBLFgDycA+eXN4LDqB2wZcsANSmm/ESAHK3nzuABIAWQEPipQSAFsT1OgDyFBQsBxnbbcPtRSAnLt1CrTErfFskyYoL0uYb9AIA/rHlpLJ1E98kXVZcEF+ByOOPvACA7/22HX+FncaAZ4ujk0QA1AagewEAq45chjORd8D24y6VI9g3BWw3AKoHe/k9AIDaBV+yAJCnm+GLTbwAgNoFX7IAUJtuxgsAyMM9fIO96ClgAkALoCHxUgJAC+ISAIqJx7ZLqjl6BVIkSYS9Q+U5gJ4EwNCTyl61dYtkwi8dK0ubAvYiAL7/+3bM2xE/AbDayGXKHtDz3qmO0jnjDwDyBV987+v4BIB8wRdf8R+fADCG208AKNZJOnw2AaAFwb0OgDwHGUtCWzBTateTw3IATJ4kIfYNbSptClgbgO4FB3Bm6En0mrUTdYpkwiSJAMhTUPD4Iy84gBwA+z9TDJ1r5pc2BazNN+gFB7D6qOU4dfU2/nynOspIBEC1258/UyoU6rdA+bK5lQZGu+JfFgDycA++2tgLDqB2xb8sANTmG/SCA8gB0Of2EwBaIAz5lxIAWtDY+wC4FBdv3FWS0LLVd27vDhBx5RZqfLoCyRInxP5hMgHwyYTTXugUZm2NQM+ZYahdOBMmvyHPAeQ7jvCE015IDvvB79vx547TkA6AmgD0F75bj61KImj38gByAJzbrRrK5korbQpYPdhj8b5uA6B2xb8sAORuP19ssvrABbz682Yl6Tb77rlxaFf8ywJA7faSoxfuw/iVh+FmHkAe7uFr6wSAblRBw/ckADQsVcwTvQ6APAeZFgDdcgWYE8I6xKSJE+KARADk8Uc8AN0LADh7awQ+nBmGWoUzYYpEANQGoHvBFeg+Ywfmbj8lHQB5/BFfgcgBcEKHCmhcIquFlm7+0hqfLkfElduY060aykkFwKjBHnP7nwDATxopO+84ffAV/zzlkywA1Lr9XgDA/1b8R6V8kgaA0elmeLwvB8A3qufDwObFnX7lyv1iuP0EgK68B6M3JQA0qpSf854WAGS7ELD0C26vDDx99TaqMQBMlBAHhstzALUB6F4AwDnbItDjjzDULJQRUzuFSIsB5ADI44+8BID9mhVDl1rypoC1+Qa9AIA1Ry/Hycu3MfvtaiifW6YD+J/bzxZ8+RxAlwGQp3ySDYB8sOctAIxK+SQbAHm4BwGgWGfu9f5brDTmziYANKebcpXXKxBPQst2ISiSJY3rAHgm8jaqjlyOxAkT4NCIZtJiALXxR14AwLnbI9B9RhhqFMyIXzvLA0C+ApHvOOIFAOwxYwfmbD+Fvs2KomutAtJiALUB6F4AwFqjV+DE5VuY/XZVlM+dTtoUMHf72WCvUBb3AVCb8kkeAEaFe/DFJl4AQG3KJ1kAqHX7vQCAPNzDN9gjB9ACYci/lADQgsZeB0CehNYrAHju2h2EjFiGRAkT4PCIZpC1O4Av/ih6yzkvAOCf20/hgxk7UL1gBkzrXMXnCti9O4A2AN0TAPjHDszZJh8AefwRT0HhBQCsM2YFjl26hVlvRQFg/r5RO4HYnQaGD/a8AoA85RPP+bn+0EW0m7hJmYmwMxG01u33AgDylE885+cXi/fj6+WHYHciaD7Y4/G+XgBAHu7BAbD19+ux5dgVUBoYC6Ah8VICQAviPi0AyLahKprVfQfw/LU7qDxiGRImAI6MfEY+AEZvOecFAJy34xTe/30HqhXIgOld/gNAuzsFDoB8yzkvAWCfpkXxZu0CkJUcVptv0AsAyLY+ZAOSmW9VRQUVAG4b0BAsd51dh9rtL5wljetTwNqcnxwA2UzEou617Co2OADy/cW9BIA85ycHwNeq5sFgG3cC0eYb9BIAcrefA+B37cujKe0EYlu9t+uHCAAtKOl1AOS7EHgGAK/fQeXhy5AgAXBUBYB2uwLaLee8BIBV82fAb13lAeB/KxCj4o+8AIAf/hGG2dsi8HHTonhLIgBqA9C9AID1PluJIxdv4o83q6Jinv8cQLsBUL3lXJGs7gOgNuenLAD0hXtED/Y8AYCanJ+yAFDr9nsBAHm4Bx/sEQBaAAwHLiUAtCCy1wGQ70LgFQC8cP0uWKwSO46N+s8BtBsAefwRD0D3AgCynTCYQ1Ulf3r83rWqtMBw7Z7DXgBAlv6GpcGRDYDadDOeAMDPV+LIhZuY0bUKKuVN75sCthsA1YO9+ASA2nQzXgBAnvOTJ32XBYB8sMfjfT0BgNHhHgSAFsDCwUsJAC2I/bQAINuHtGg2lSswsBGCUzqfGoKlqag4zDkA5PFHXgDAv8NOgy1SCMmXHjPelA+APP7ISwD4UZOieLuOvClgLwJg/c9X4vCFm/i9axVUdggA2RRw4f7RiaBdWgWsTfouywHkAMgHe14CQJ70XTYA8nAPLwEgH+yRA2gBMBy4lADQgsheB0C+DRXbh5QlRnU7OeylG3dRIRoAj45shg1HLqHdj/YHhmvjj7zQKfyz8zTenb4dlfOlV6YDZa0M5CsQefyRF5LD9poZhplbI9C7SRF0q1NQWgygNgC91fh12HbiKtzMA8hWqB46fwO/damiwD9eywNdAAAcoElEQVRfBGK3A8jdfjbYYw6g2wCoTfouCwB5uAcf7K06cAGv/bwZxbMFYb5LiaC1Sd9lAaDW7f904T58t/Iw3MwDyMM9+GCPANACYDhwKQGgBZG9DoB8F4IYAOiSK3D55j2wTevZcWREM2w8KgcAufuQMmki7BnSBF4AwH93nsE707cpLtAfb8kDQL4CUQuAbnYKvWeF4Y9Q+QDI44/4CkQOgD90qIBGLiWCbvjFKhw8fwPTu4SgSr4M0gCQD/a0ALhzUCMEJXfe7edJ3/muP7IAUJtuxgsAyJO+811/ZAEgH+w1KBYV78sBsFONfGBbsblx8HAPAkA31Be/JwGguGa+K54WAGQb0RfPrnIAXQLAKzfvoVw0ALI0MJskA2CKJImwd6g3AHB++Bl0m7YNlfKmw8y3qklzADkA8vgjL0wLcQDs1bgI3qkrzwHU5hv0AgA2GrsKB87dwPTOIaiSXz4AssFe0axBPgfQbQDku/7IBkA+2PMSAPJdf2QDIA/38BIAcrefHEALgOHApQSAFkR+WgCQbURfwgMAePXWPZQdEuUAHhreFJuPXZYyBayNP+IOINsPeUmP2hbeuPlLF4SfwdvTtikrQWe9LREAo1cg8vijkQv2YsKqI67uD/rRrJ2YEXoS0gFQE4De5MvV2Hf2Otx0ABuPXY39565jWucQsBXgsqaAudvPBnss3INPAbsFgNpdf2QBIA/34IM9DoB2LywTafnaXX9kAaDW7R85fy8mrD7i6hQwD/fgbZ0AUKTmOH8uAaAFzb0OgHwfUgaA2dMmV1KwsCPMJQcw8tZ9lBmyWHmGg8ObYoskAOTxR8mTJMS+oU3x8eyd+H3LSeW+bPWxG8fCXWfw1q/bUCFPOmVbMFkxgHwFIgfAvB//qxSX5150o+xcf9kAyOOP+ApEXnaek8yNsnMI/bVTiJID0gkAzBqcXEm4zg63AJDv+sO3fZQFgNp0M9xtdrOt811/+LaP0gAwerDHwz14fec7LblR37VuPwGgG2/B+D0JAI1rFePMpwUA53arhht3H6DDT5vdBcDb91FmcBQAHhjWFGxl7Iczw2wHM20AOv8wutkpLNx1Fm/9ulXZD3ZOt+poMW4twiIifY6ghWr4xKUcAHn8kRfKzgGwZ6PCeLdeIfBn+uKlMmhVPqddRYc23yC/D9fCthsJ/BAHwKmdKisOIN+P2+5FINwBZIM9FmrRcdIWTwBgkkQJcHB4M/B6aXcb1Lr9XqjvWgBs/s1ahJ+K9MX/ClSfWE/9Q5Nv0Atl1wIgf6axbcrg+XL2tXU7NPR6/21HGfV+I94CYN68eXH8+PEn9Pnoo48watQoPc18f/d6BeIb0c/pVg3X7zxQVsexwy0H8Nqd+yg9KAoA9w9rorgUV2/dtx0AeQA6jz/ywodx0e6zeHPqVpTLnRZzu1X3QZDdHSJfgcjjj7xQ9j5zduK3zSfxYcPC+F/9/wCQJ8U23OB0TtQGoPOyczfUrvuI/E7Tr9Zg75lrmPJGZaROnhitxq9XLt8+oCHS2bgTCHf72WDvyq17eGNSqKsAeDbyDqqMXObb97vUoEXKN8ju+s4BkC828UJ959s+8n2/ZT1TILffbo1F6jsP99AO9rgbKvJbss/1ev8tu/zs9+M1AHbq1AldunTx6Zw6dWqwf0YPr1cgvhG9VwDw+p37KBUNgPuGNkGJTxbh4aPHtncKvvijxAkVp1HWB9hoPWHnLd59Fl2nbkXZXGnBXBpZz8RXIHoLAMPBktZqAZDHQ4roGNu5PP6Ir0D0AgA2+2oN9py5hslvVEbyxAnR5oeNUgCQD/YYALLV9p0muwuAfN9vPh0pq7570e3n2z7KBkA+2NOGe7gJgIHcfp7/1K62bsfveL3/tqOMer8RrwHwgw8+APtn9vB6BeIAyGLOGHy9/kvUtJBbDiCbhi75ySLlGRgAFh+4ENH8Z2tsnjYAXVbnI1Jvluw5hy5TQlEmV1qwQH1Zz8QBkI+4Zd1HpOx95kQBYI+GhfGeygHkK6JFfssIAPIViLzsPEbKrvuI/M4zX6/B7tPXMKljJSRLnAgv/ygXANlg7/KNe+g8xRsAmChhArAV/7LqIQdAL7n9HACrF8yAaZ2rSCu7Nt+gLI1F6jsHQO1gj++AJPJbss/1ev8tu/zx3gG8e/cu7t27h1y5cqF169bo1asXkiYNvEE7O5/94werQOzayMhIBAUFOfG+hO5Re8wKHL90C7Pfroprtx+4Hhd08+4DxfVjx94hTVD8k4V4HGUA2gqAPACd/64XPoxL95xTOuXc6VNide+60joFvgJRtvsgUhH5FPA7dQugV+OivrLzpNgivxXbuYHij3iaDLvuI/I79aK3gvtFAcCEyqp3dtg9Bawe7DEHkA022BE+qBHSuJAH8Py1O6gcvRCFLbyS1QZ5uIeX2joHQNnhHt4c7EWFe3zQoBA+aFDY997tDvcQaYOBziUAjMdTwGPHjkX58uWRLl06bN68GX369EGLFi0wceLEgHVr0KBBGDx4cIy/exUA+Ue3SJY0yirgFfsvKM/u1srAW/ceoPjAKABsXia7sgiEH3auzlUDIEuIOvSfPVLuI/IR+mH1YYyYv0+5pFudAhi/8rCUZxq3/CA+W3xA+e2hLUtiwJ+7pNxHpOzqzl9ddrunhYoNWIjb9x/GKDtPlCvyzHadqy47m/7fcfKqFADk9ymaNQ0yByVXkp97BQBfrZoHUzb8F29tZ1tXA+DAZ4tjiAfaOl/1K7utf73soJJN4Glo62wF/PQuVexqVrb8DgFgHAPAQICmri1btmxBxYoVY1Sg2bNn48UXX8TFixeRIUMGvxXsaXMA1Z2PukBuAaDaAdQKbGenwPcH9fcS7byPyFeI7QOsBl71tXY+U50xK3Ds0i2/j2bnfUTKHqge2u0ABroPn4oTeWa7zg30THY7gIHu45YDyBdnyG6DbJs9tt2e7PuI1Idnv1mDXaeuSX8mvvDHS2UPVA/JARSpQc6dG6diABm8sX+xHWz1b/LkyWOccurUKeTMmRMbN25ESEiIoTfg9RGEujGyxKhsRwJ2uAWAd+4/RNEBC5VneKliTmV7MH7YCSfqzqdJiaxYuPuslPsYqiTRJ/FpIfafbFu2n9cdlfJMPPEz+/GmJbNiwS73y863Q9OWnTlDQ1qUFJEx9rYdnfNQW3Y3t8bibTBNssSoWTgj5odHvQ+ZAJg/UyocuXBTuY9bAHjh+l1UGr5UeYbXq+XFpPXHpNR3vhUc+3GvtPUfVx/B8Pl7lfLKbOsj5u/FD6uPKPfxSluvMmIZzl67E6PsrA4Meq6EbW3djh/yev9tRxn1fiNOAaBeYWP7+z///IPmzZsrqWFy585t6Ke8XoFY3BlLtty7SVGwhRE1R69QyuUWALJ7s6mpR48fo06RzOg3NxzTNp1QnslOAGS/xzZFz5AqKV6qlAs9oneIkHEfQxUFwKNHjzFz60mUz50OhbKkkRYTxRbafLZoP54tnQ0V86aXdh+j5WbnsZQgc7ZH4OVKuZXUJxyK7AbAQ+evY/L643i3XkFkCUruu8+btfKjT7NiIo9s27nsmUKPXcFLFXPh4o27vrg4uwFQaevHL+OjxkURceU2ao2JautuASC7Nxv0pE6WGPWLZQFfCCSjDY5feQgZUydTNO4+Ywfmbj8l5ZtitFLcffAQk9cfQ+3CmVEkq/y23rxMNlTI4422zsJvmP7atk4AaLT2OHtevATADRs2KE5f3bp1ERwcDDYt3L17d2VqeN68eYbfgNcBUF0QvlrObQBUP1P/P8Px60Y5AKi+D08QLKPzMVxZNCfKCorXPo9T9xHRgT9Thyp5lDhFWQe/j5sAqC7b+et3fLvx2J0IWn0ftQPuJgCqn6nv3HBMlzTYU9+H7wdNbd2dHY8CfX9eq5oHg210++34ZjxN/bcd5fX3G/ESALdt24Zu3bph3759yqrePHnyoG3btujduzdSpkxpWOunqQKpg6XddADV4rIFClM3RgWH2+0AEgBGKeBlAHylSm4Ma1nKcHsTPZGXvWut/OjrkgOofmb1tOjW/g2QIXUy0SIZOt+LACjT7ScA9H5bt9vtN9QQdE56mvpvO8pLAGizik9TBeK58ZgE8Q0A+Q4RskFTpHo5BWZO3cdM2Z1yALvUzId+zxQXeUQp5xIAynf7vRDuEcgFk/398XJbJwCU8kmx/KPx0gG0rFr0DxAAWlNSZlyQ+sn4DhGyP8Aiajj1sXbqPmbKLjsuiJe9c4186P+s+wDIt0djWoUNbITglElEZDN8rjrcwytTwDxBsOw2SOEeUdVE5oyK4YqomoFgi2EGNne/Daqf/Wnqv0U0FzmXAFBELc25T1MFUncKuwY3VoKz3T74vpGyP1jUKXizU5ANZl6bAlaHYchsg+op4D1DGiNlUvfbulMuPMUAerOteyUMgwDwyV6fANACBT1NAHji0i3fykC2C0eKpIkslNyeSw+cu45GY1crK1bHtStvz4/6+RUvrAzUPtbUDccwYN5ufPpCKbSpZGzVuRmBvOgAvjk1FIt2n8OKnnWQL2MqM8UydA0v+1u1C+DjpkUNXSPzpAcPH6Hc0CVIkighQvs1QMKECaTc7tjFm6jz2Urlt/cPa6JsQef2se/sNTT5cg2eK5MdX79cTtrjvP/7dszbEZVg3isu2JQNxzBw3m6MfqG0kpVA1uHFtt51SigW7zmHlT3rIK/Etm5G06ep/zZTPiPXEAAaUSnAOU9TBVInR/ZKp8BkZcmhUyZNhAQJ5HSG7B5e7BTYc7GULbKdWC92Co8fP8atew+RSrILzcvOt6Cz0NRtu5SlCEmABGB718o6Dl+4gfqfRyVHPjS8KRInkncvkTKw+p5KcltXJ1z3CgBSW5ff1kXqIT/3aeq/zZTPyDUEgEZUigMAGHnrPsoMWayUhG3OzjZpjy/HH6En0XvWTqXMrOzx6ejw0yasOXgRz5fLgbFtysanovtWQP/yeiXULZo53pT96q17KDtkiVLeoyObSR1ceU3UP7acRO/ZO5E4YQIcimdtvf3EjVh36BJalcuBL+JZWzdTDwkA49hWcGYqgZVrnrYKxJJCJ02UEGVypbVS7KfuWpaEefGes0q5swWneOqe38oDX7tzH6v2X0D9Ypk9EQtmpSyi17Kwh/3nroPtBSzTYRZ9LifOZ209WeKEKJ2T2roTenvhHrytNyiWxRMhPl7QJLZneNr6bxl6kgNoQVWqQBbEo0tJAVKAFCAFSAGXFKD+mxxAS1WPKpAl+ehiUoAUIAVIAVLAFQWo/yYAtFTxqAJZko8uJgVIAVKAFCAFXFGA+m8CQEsVjyqQJfnoYlKAFCAFSAFSwBUFqP8mALRU8agCWZKPLiYFSAFSgBQgBVxRgPpvAkBLFY8qkCX56GJSgBQgBUgBUsAVBaj/JgC0VPGoAlmSjy4mBUgBUoAUIAVcUYD6bwJASxWPKpAl+ehiUoAUIAVIAVLAFQWo/yYAtFTxqAJZko8uJgVIAVKAFCAFXFGA+m8CQEsVjyqQJfnoYlKAFCAFSAFSwBUFqP8mALRU8agCWZKPLiYFSAFSgBQgBVxRgPpvAkBLFY8qkCX56GJSgBQgBUgBUsAVBaj/JgC0VPGoAlmSjy4mBUgBUoAUIAVcUYD6bwJASxWPKpAl+ehiUoAUIAVIAVLAFQWo/yYAtFTxIiMjkTZtWpw8eRJBQUGWfosuJgVIAVKAFCAFSAFnFGAAmCtXLly9ehXBwcHO3NRjd0nw+PHjxx57pqfmcSIiIpQKRAcpQAqQAqQAKUAKPH0KMAMnZ86cT9+D2/DEBIAWRHz06BFOnz6NNGnSIEGCBBZ+KealfHRC7qKtsgr/GL0HYcmkXEDvQYqswj9K70FYMikX0HuwLivzvq5fv47s2bMjYcKE1n/wKfwFAkCPvjSKT/DGi6H3QO/BGwp44ymoPdB78IYC9BR2KEAAaIeKEn6DPrQSRDXxk/QeTIgm4RJ6DxJENfGT9B5MiCbhEnoPEkSNhz9JAOjRl04N3Bsvht4DvQdvKOCNp6D2QO/BGwrQU9ihAAGgHSpK+I27d+9i5MiR6NOnD5IlSybhDvSTRhSg92BEJfnn0HuQr7GRO9B7MKKS/HPoPcjXOD7cgQAwPrxlKiMpQAqQAqQAKUAKkAIqBQgAqTqQAqQAKUAKkAKkACkQzxQgAIxnL5yKSwqQAqQAKUAKkAKkAAEg1QFSgBQgBUgBUoAUIAXimQIEgPHshVNxSQFSgBQgBUgBUoAUIAD0YB0YP348xowZgzNnzqBEiRL48ssvUbNmTQ8+6dP3SGxl9Zw5c7Bv3z6kSJEC1apVw6effooiRYr4CsNW2PXs2RO//fYbbt++jfr164O9E/V2QSdOnMA777yD5cuXK7/Trl07fPbZZ0iaNOnTJ4oHnpi9l759++L9999X6js76D0482JOnTqFjz76CAsWLFDqe+HChfHTTz+hQoUKygOwHRMGDx6MH374AVeuXEFISAi+/fZb5dvED/b/v/fee/jrr7+U/+u5557DN998o+yVTocxBR48eIBBgwZh2rRpOHv2LLJly4bXX38d/fv39+1UQe/CmJZ0ljEFCACN6eTYWTNmzECHDh0U4KhevTomTJiAiRMnYs+ePcidO7djzxFXb9SkSRO0bdsWlSpVAvvg9uvXD+Hh4Yq+qVKlUor99ttv4++//8akSZOQIUMGfPjhh7h8+TK2bt2KRIkS4eHDhyhbtiwyZcqEzz//HJcuXcJrr72GVq1aKZ0eHWIKbNmyBS+99BKCgoJQt25dHwDSexDT0czZDNzKlSun6M70zpw5Mw4fPoy8efOiQIECyk+yAdLw4cOV9sDgcNiwYVi9ejX279+vbIPJjqZNm4Ltjc4gkR1du3ZVfoO1IzqMKcA0Hjt2LCZPnqzAdWhoKDp27KjozQZG9C6M6UhnGVeAANC4Vo6cyUbX5cuXx3fffee7X7FixdCyZUslLyAd9ipw4cIFpdNbtWoVatWqhcjISAXspk6dijZt2ig3Y/s958qVC/Pnz0fjxo0Vp+TZZ58F26eZ7SPJjt9//10ZrZ8/f14BGTqMKXDjxg2lvrMBD+voGFgzB5DegzH9rJ718ccfY926dVizZo3fn2KOE6vjH3zwgeISsoM5s1myZFHA8M0338TevXtRvHhxbNy4UXEH2cH+d9WqVRWnXe2uW33euHw9+6YwXZn7yo8XXngBKVOmVL5H9C7i8tt3p2wEgO7o7veu9+7dUxr7zJkz8fzzz/vOYaO/HTt2KJBCh70KHDp0CIUKFVJcwJIlSypTumzKlzl+6dKl892sTJkyCoSzqbCBAwdi3rx5CAsL8/2dOSnp06dXrmduCh3GFGDOKdONOR916tTxASC9B2P6WT2LgRsb1DD3jn1fcuTIgW7duqFLly7KTx85ckRxArdt26Y4hfxo0aKFMr3L3Kqff/4ZPXr0wNWrV594HPZ39l6Zi0WHvgKjRo3C999/j8WLFytOK/u+NGrUSBkQvfzyy/Qu9CWkMwQVIAAUFEzm6cxpYh9gNiJnsWn8GDFihPKhZVMudNinABtRs46MwRt3QKZPn650WMzlUB/sQ5wvXz5lSp5Nbx07dkz5UKsPtmMLmyZjH2s69BVgrimb9mJTwMmTJ38CAOk96OtnxxlMd3YwgGvdujU2b96suH2snr/66qtYv369EorC4gS5283OZ23g+PHjWLRoEdj3idX7AwcOPPFIDGJYW2K7GdGhrwD7HrE4WOas8lAT1j64fvQu9DWkM8QUIAAU00vq2RwAWUNn0yf8YB8BNgXAplPosE8Btojj33//xdq1a30LPAKBR8OGDRUnhI3Q1Z2f+mnYApApU6YoMYZ0xK4Amz6vWLGiAtHMXWWH2gGk9+BMDWJ1lr0H9s3hB1vMwaB8w4YNPgBk3ya2KIEfzCFk73DhwoUKAPoboDJnvVOnTmDTzHToK8AGRL169VIWALIYQDbrw2D8iy++UGKMOQDSu9DXks4wpgABoDGdHDmLpoAdkVm5yf/+9z/8+eefSjA7c/b4QVOPzrwDpj0Lc2BOBz/Y4poECRIoKx6Zs9SgQQOaipf8OvLkyQM2uGELzfjB4o9ZPCZz/WgKWPILUP08izNmsMwGpvxg7+HXX39VBv/0Lpx7F/HlTgSAHnvTLIiapV9gQfH8YHE6bKqSFoFYf1lsmoXB39y5c7Fy5Uol/k998MUH7KPLVqayg6XjYSlgtItAWNwUd0XY6m02SqdFIMbe0fXr15UpRPXBpguLFi2qLDZgnSFbjEPvwZieZs9i6YuYk6deBNK9e3ds2rRJcZz4wgP2//Xu3Vu5DRuosoVT2kUg7JrKlSsr57D/XaVKFVoEIvBiWMYBBnxsNTY/2Df/l19+UabX6V0IiEmnGlKAANCQTM6dxNPAsKlGNg3M0ir8+OOP2L17N9honQ5rCrAAdza9yBZxqFcnBgcHK/n82ME+wP/8848S18QWKLCcgCzVizYNDFuxx6Zr2IIRtgKYLRKhNDDm3496Cpjeg3kdRa5kU70s3pgtbmIDHhYDyKZ32Xenffv2yk8x0OMgwgZMbMqXDZ60aWDY1CSLHWQHC5Ng3ytKA2P8bbBvyNKlSxUN2RTw9u3bFR3feOMN5R3QuzCuJZ1pTAECQGM6OXoWc/9Gjx6tOE9sZSpbScdSlNBhXQE2xejvYKNs9gFmx507d5RYHAaK6kTQzJXiB0sEzWBSmwiaLQShw5wCWgCk92BOR9Gr2GCHLTQ4ePCgEg7BFoTwVcDst3jyYQYm6kTQ7NvEDzYI0iaCHjduHCWCFngZzBUfMGCAMjvBZhLYohu2oIxlHeAJ5uldCAhKp+oqQACoKxGdQAqQAqQAKUAKkAKkQNxSgAAwbr1PKg0pQAqQAqQAKUAKkAK6ChAA6kpEJ5ACpAApQAqQAqQAKRC3FCAAjFvvk0pDCpACpAApQAqQAqSArgIEgLoS0QmkAClACpACpAApQArELQUIAOPW+6TSkAKkAClACpACpAApoKsAAaCuRHQCKUAKkAKkAClACpACcUsBAsC49T6pNKQAKUAKkAKkAClACugqQACoKxGdQAqQAqQAKUAKkAKkQNxSgAAwbr1PKg0pQAqQAqQAKUAKkAK6ChAA6kpEJ5ACpAApQAqQAqQAKRC3FCAAjFvvk0pDCpACpAApQAqQAqSArgIEgLoS0QmkAClACpACpAApQArELQUIAOPW+6TSkAKkAClACpACpAApoKsAAaCuRHQCKUAKkAKkAClACpACcUsBAsC49T6pNKQAKUAKkAKkAClACugqQACoKxGdQAqQAqQAKUAKkAKkQNxSgAAwbr1PKg0pQAqQAqQAKUAKkAK6ChAA6kpEJ5ACpAApQAqQAqQAKRC3FCAAjFvvk0pDCpACpAApQAqQAqSArgIEgLoS0QmkAClACpACpAApQArELQUIAOPW+6TSkAKkAClACpACpAApoKsAAaCuRHQCKUAKkAKkAClACpACcUsBAsC49T6pNKQAKUAKkAKkAClACugqQACoKxGdQAqQAqQAKUAKkAKkQNxSgAAwbr1PKg0pQAqQAqQAKUAKkAK6ChAA6kpEJ5ACpAApQAqQAqQAKRC3FCAAjFvvk0pDCpACpAApQAqQAqSArgIEgLoS0Qn/b7cOiQAAABCI9W9NBPzfPIZhIECAAAECBAi0BBzA1p7aECBAgAABAgSugAN4iQQIECBAgAABAi0BB7C1pzYECBAgQIAAgSswtpYdNnLyDhoAAAAASUVORK5CYII=\" 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+      "image/png": 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\n",
       "text/plain": [
-       "<IPython.core.display.HTML object>"
+       "<Figure size 432x288 with 1 Axes>"
       ]
      },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/plain": [
-       "[<matplotlib.lines.Line2D at 0x1c294f84a8>]"
-      ]
+     "metadata": {
+      "needs_background": "light"
      },
-     "execution_count": 64,
-     "metadata": {},
-     "output_type": "execute_result"
+     "output_type": "display_data"
     }
    ],
    "source": [
@@ -2755,7 +1975,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 65,
+   "execution_count": 69,
    "metadata": {},
    "outputs": [
     {
@@ -2764,7 +1984,7 @@
        "'second'"
       ]
      },
-     "execution_count": 65,
+     "execution_count": 69,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2775,7 +1995,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 66,
+   "execution_count": 70,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2798,7 +2018,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 67,
+   "execution_count": 71,
    "metadata": {},
    "outputs": [
     {
@@ -2831,7 +2051,7 @@
        "       -2.01483397e-04, -1.11619355e-04, -4.52198796e-05])"
       ]
      },
-     "execution_count": 67,
+     "execution_count": 71,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2842,7 +2062,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 68,
+   "execution_count": 72,
    "metadata": {},
    "outputs": [
     {
@@ -2851,7 +2071,7 @@
        "(99,)"
       ]
      },
-     "execution_count": 68,
+     "execution_count": 72,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2862,810 +2082,30 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 69,
+   "execution_count": 73,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "application/javascript": [
-       "/* Put everything inside the global mpl namespace */\n",
-       "window.mpl = {};\n",
-       "\n",
-       "\n",
-       "mpl.get_websocket_type = function() {\n",
-       "    if (typeof(WebSocket) !== 'undefined') {\n",
-       "        return WebSocket;\n",
-       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
-       "        return MozWebSocket;\n",
-       "    } else {\n",
-       "        alert('Your browser does not have WebSocket support.' +\n",
-       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
-       "              'Firefox 4 and 5 are also supported but you ' +\n",
-       "              'have to enable WebSockets in about:config.');\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
-       "    this.id = figure_id;\n",
-       "\n",
-       "    this.ws = websocket;\n",
-       "\n",
-       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
-       "\n",
-       "    if (!this.supports_binary) {\n",
-       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
-       "        if (warnings) {\n",
-       "            warnings.style.display = 'block';\n",
-       "            warnings.textContent = (\n",
-       "                \"This browser does not support binary websocket messages. \" +\n",
-       "                    \"Performance may be slow.\");\n",
-       "        }\n",
-       "    }\n",
-       "\n",
-       "    this.imageObj = new Image();\n",
-       "\n",
-       "    this.context = undefined;\n",
-       "    this.message = undefined;\n",
-       "    this.canvas = undefined;\n",
-       "    this.rubberband_canvas = undefined;\n",
-       "    this.rubberband_context = undefined;\n",
-       "    this.format_dropdown = undefined;\n",
-       "\n",
-       "    this.image_mode = 'full';\n",
-       "\n",
-       "    this.root = $('<div/>');\n",
-       "    this._root_extra_style(this.root)\n",
-       "    this.root.attr('style', 'display: inline-block');\n",
-       "\n",
-       "    $(parent_element).append(this.root);\n",
-       "\n",
-       "    this._init_header(this);\n",
-       "    this._init_canvas(this);\n",
-       "    this._init_toolbar(this);\n",
-       "\n",
-       "    var fig = this;\n",
-       "\n",
-       "    this.waiting = false;\n",
-       "\n",
-       "    this.ws.onopen =  function () {\n",
-       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
-       "            fig.send_message(\"send_image_mode\", {});\n",
-       "            if (mpl.ratio != 1) {\n",
-       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
-       "            }\n",
-       "            fig.send_message(\"refresh\", {});\n",
-       "        }\n",
-       "\n",
-       "    this.imageObj.onload = function() {\n",
-       "            if (fig.image_mode == 'full') {\n",
-       "                // Full images could contain transparency (where diff images\n",
-       "                // almost always do), so we need to clear the canvas so that\n",
-       "                // there is no ghosting.\n",
-       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
-       "            }\n",
-       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
-       "        };\n",
-       "\n",
-       "    this.imageObj.onunload = function() {\n",
-       "        fig.ws.close();\n",
-       "    }\n",
-       "\n",
-       "    this.ws.onmessage = this._make_on_message_function(this);\n",
-       "\n",
-       "    this.ondownload = ondownload;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_header = function() {\n",
-       "    var titlebar = $(\n",
-       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
-       "        'ui-helper-clearfix\"/>');\n",
-       "    var titletext = $(\n",
-       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
-       "        'text-align: center; padding: 3px;\"/>');\n",
-       "    titlebar.append(titletext)\n",
-       "    this.root.append(titlebar);\n",
-       "    this.header = titletext[0];\n",
-       "}\n",
-       "\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_canvas = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var canvas_div = $('<div/>');\n",
-       "\n",
-       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
-       "\n",
-       "    function canvas_keyboard_event(event) {\n",
-       "        return fig.key_event(event, event['data']);\n",
-       "    }\n",
-       "\n",
-       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
-       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
-       "    this.canvas_div = canvas_div\n",
-       "    this._canvas_extra_style(canvas_div)\n",
-       "    this.root.append(canvas_div);\n",
-       "\n",
-       "    var canvas = $('<canvas/>');\n",
-       "    canvas.addClass('mpl-canvas');\n",
-       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
-       "\n",
-       "    this.canvas = canvas[0];\n",
-       "    this.context = canvas[0].getContext(\"2d\");\n",
-       "\n",
-       "    var backingStore = this.context.backingStorePixelRatio ||\n",
-       "\tthis.context.webkitBackingStorePixelRatio ||\n",
-       "\tthis.context.mozBackingStorePixelRatio ||\n",
-       "\tthis.context.msBackingStorePixelRatio ||\n",
-       "\tthis.context.oBackingStorePixelRatio ||\n",
-       "\tthis.context.backingStorePixelRatio || 1;\n",
-       "\n",
-       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
-       "\n",
-       "    var rubberband = $('<canvas/>');\n",
-       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
-       "\n",
-       "    var pass_mouse_events = true;\n",
-       "\n",
-       "    canvas_div.resizable({\n",
-       "        start: function(event, ui) {\n",
-       "            pass_mouse_events = false;\n",
-       "        },\n",
-       "        resize: function(event, ui) {\n",
-       "            fig.request_resize(ui.size.width, ui.size.height);\n",
-       "        },\n",
-       "        stop: function(event, ui) {\n",
-       "            pass_mouse_events = true;\n",
-       "            fig.request_resize(ui.size.width, ui.size.height);\n",
-       "        },\n",
-       "    });\n",
-       "\n",
-       "    function mouse_event_fn(event) {\n",
-       "        if (pass_mouse_events)\n",
-       "            return fig.mouse_event(event, event['data']);\n",
-       "    }\n",
-       "\n",
-       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
-       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
-       "    // Throttle sequential mouse events to 1 every 20ms.\n",
-       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
-       "\n",
-       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
-       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
-       "\n",
-       "    canvas_div.on(\"wheel\", function (event) {\n",
-       "        event = event.originalEvent;\n",
-       "        event['data'] = 'scroll'\n",
-       "        if (event.deltaY < 0) {\n",
-       "            event.step = 1;\n",
-       "        } else {\n",
-       "            event.step = -1;\n",
-       "        }\n",
-       "        mouse_event_fn(event);\n",
-       "    });\n",
-       "\n",
-       "    canvas_div.append(canvas);\n",
-       "    canvas_div.append(rubberband);\n",
-       "\n",
-       "    this.rubberband = rubberband;\n",
-       "    this.rubberband_canvas = rubberband[0];\n",
-       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
-       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
-       "\n",
-       "    this._resize_canvas = function(width, height) {\n",
-       "        // Keep the size of the canvas, canvas container, and rubber band\n",
-       "        // canvas in synch.\n",
-       "        canvas_div.css('width', width)\n",
-       "        canvas_div.css('height', height)\n",
-       "\n",
-       "        canvas.attr('width', width * mpl.ratio);\n",
-       "        canvas.attr('height', height * mpl.ratio);\n",
-       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
-       "\n",
-       "        rubberband.attr('width', width);\n",
-       "        rubberband.attr('height', height);\n",
-       "    }\n",
-       "\n",
-       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
-       "    // upon first draw.\n",
-       "    this._resize_canvas(600, 600);\n",
-       "\n",
-       "    // Disable right mouse context menu.\n",
-       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
-       "        return false;\n",
-       "    });\n",
-       "\n",
-       "    function set_focus () {\n",
-       "        canvas.focus();\n",
-       "        canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    window.setTimeout(set_focus, 100);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_toolbar = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var nav_element = $('<div/>')\n",
-       "    nav_element.attr('style', 'width: 100%');\n",
-       "    this.root.append(nav_element);\n",
-       "\n",
-       "    // Define a callback function for later on.\n",
-       "    function toolbar_event(event) {\n",
-       "        return fig.toolbar_button_onclick(event['data']);\n",
-       "    }\n",
-       "    function toolbar_mouse_event(event) {\n",
-       "        return fig.toolbar_button_onmouseover(event['data']);\n",
-       "    }\n",
-       "\n",
-       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
-       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
-       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
-       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
-       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
-       "\n",
-       "        if (!name) {\n",
-       "            // put a spacer in here.\n",
-       "            continue;\n",
-       "        }\n",
-       "        var button = $('<button/>');\n",
-       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
-       "                        'ui-button-icon-only');\n",
-       "        button.attr('role', 'button');\n",
-       "        button.attr('aria-disabled', 'false');\n",
-       "        button.click(method_name, toolbar_event);\n",
-       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
-       "\n",
-       "        var icon_img = $('<span/>');\n",
-       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
-       "        icon_img.addClass(image);\n",
-       "        icon_img.addClass('ui-corner-all');\n",
-       "\n",
-       "        var tooltip_span = $('<span/>');\n",
-       "        tooltip_span.addClass('ui-button-text');\n",
-       "        tooltip_span.html(tooltip);\n",
-       "\n",
-       "        button.append(icon_img);\n",
-       "        button.append(tooltip_span);\n",
-       "\n",
-       "        nav_element.append(button);\n",
-       "    }\n",
-       "\n",
-       "    var fmt_picker_span = $('<span/>');\n",
-       "\n",
-       "    var fmt_picker = $('<select/>');\n",
-       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
-       "    fmt_picker_span.append(fmt_picker);\n",
-       "    nav_element.append(fmt_picker_span);\n",
-       "    this.format_dropdown = fmt_picker[0];\n",
-       "\n",
-       "    for (var ind in mpl.extensions) {\n",
-       "        var fmt = mpl.extensions[ind];\n",
-       "        var option = $(\n",
-       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
-       "        fmt_picker.append(option)\n",
-       "    }\n",
-       "\n",
-       "    // Add hover states to the ui-buttons\n",
-       "    $( \".ui-button\" ).hover(\n",
-       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
-       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
-       "    );\n",
-       "\n",
-       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
-       "    nav_element.append(status_bar);\n",
-       "    this.message = status_bar[0];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
-       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
-       "    // which will in turn request a refresh of the image.\n",
-       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.send_message = function(type, properties) {\n",
-       "    properties['type'] = type;\n",
-       "    properties['figure_id'] = this.id;\n",
-       "    this.ws.send(JSON.stringify(properties));\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.send_draw_message = function() {\n",
-       "    if (!this.waiting) {\n",
-       "        this.waiting = true;\n",
-       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
-       "    var format_dropdown = fig.format_dropdown;\n",
-       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
-       "    fig.ondownload(fig, format);\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
-       "    var size = msg['size'];\n",
-       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
-       "        fig._resize_canvas(size[0], size[1]);\n",
-       "        fig.send_message(\"refresh\", {});\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
-       "    var x0 = msg['x0'] / mpl.ratio;\n",
-       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
-       "    var x1 = msg['x1'] / mpl.ratio;\n",
-       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
-       "    x0 = Math.floor(x0) + 0.5;\n",
-       "    y0 = Math.floor(y0) + 0.5;\n",
-       "    x1 = Math.floor(x1) + 0.5;\n",
-       "    y1 = Math.floor(y1) + 0.5;\n",
-       "    var min_x = Math.min(x0, x1);\n",
-       "    var min_y = Math.min(y0, y1);\n",
-       "    var width = Math.abs(x1 - x0);\n",
-       "    var height = Math.abs(y1 - y0);\n",
-       "\n",
-       "    fig.rubberband_context.clearRect(\n",
-       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
-       "\n",
-       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
-       "    // Updates the figure title.\n",
-       "    fig.header.textContent = msg['label'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
-       "    var cursor = msg['cursor'];\n",
-       "    switch(cursor)\n",
-       "    {\n",
-       "    case 0:\n",
-       "        cursor = 'pointer';\n",
-       "        break;\n",
-       "    case 1:\n",
-       "        cursor = 'default';\n",
-       "        break;\n",
-       "    case 2:\n",
-       "        cursor = 'crosshair';\n",
-       "        break;\n",
-       "    case 3:\n",
-       "        cursor = 'move';\n",
-       "        break;\n",
-       "    }\n",
-       "    fig.rubberband_canvas.style.cursor = cursor;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
-       "    fig.message.textContent = msg['message'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
-       "    // Request the server to send over a new figure.\n",
-       "    fig.send_draw_message();\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
-       "    fig.image_mode = msg['mode'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Called whenever the canvas gets updated.\n",
-       "    this.send_message(\"ack\", {});\n",
-       "}\n",
-       "\n",
-       "// A function to construct a web socket function for onmessage handling.\n",
-       "// Called in the figure constructor.\n",
-       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
-       "    return function socket_on_message(evt) {\n",
-       "        if (evt.data instanceof Blob) {\n",
-       "            /* FIXME: We get \"Resource interpreted as Image but\n",
-       "             * transferred with MIME type text/plain:\" errors on\n",
-       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
-       "             * to be part of the websocket stream */\n",
-       "            evt.data.type = \"image/png\";\n",
-       "\n",
-       "            /* Free the memory for the previous frames */\n",
-       "            if (fig.imageObj.src) {\n",
-       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
-       "                    fig.imageObj.src);\n",
-       "            }\n",
-       "\n",
-       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
-       "                evt.data);\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
-       "            fig.imageObj.src = evt.data;\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        var msg = JSON.parse(evt.data);\n",
-       "        var msg_type = msg['type'];\n",
-       "\n",
-       "        // Call the  \"handle_{type}\" callback, which takes\n",
-       "        // the figure and JSON message as its only arguments.\n",
-       "        try {\n",
-       "            var callback = fig[\"handle_\" + msg_type];\n",
-       "        } catch (e) {\n",
-       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        if (callback) {\n",
-       "            try {\n",
-       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
-       "                callback(fig, msg);\n",
-       "            } catch (e) {\n",
-       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
-       "            }\n",
-       "        }\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
-       "mpl.findpos = function(e) {\n",
-       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
-       "    var targ;\n",
-       "    if (!e)\n",
-       "        e = window.event;\n",
-       "    if (e.target)\n",
-       "        targ = e.target;\n",
-       "    else if (e.srcElement)\n",
-       "        targ = e.srcElement;\n",
-       "    if (targ.nodeType == 3) // defeat Safari bug\n",
-       "        targ = targ.parentNode;\n",
-       "\n",
-       "    // jQuery normalizes the pageX and pageY\n",
-       "    // pageX,Y are the mouse positions relative to the document\n",
-       "    // offset() returns the position of the element relative to the document\n",
-       "    var x = e.pageX - $(targ).offset().left;\n",
-       "    var y = e.pageY - $(targ).offset().top;\n",
-       "\n",
-       "    return {\"x\": x, \"y\": y};\n",
-       "};\n",
-       "\n",
-       "/*\n",
-       " * return a copy of an object with only non-object keys\n",
-       " * we need this to avoid circular references\n",
-       " * http://stackoverflow.com/a/24161582/3208463\n",
-       " */\n",
-       "function simpleKeys (original) {\n",
-       "  return Object.keys(original).reduce(function (obj, key) {\n",
-       "    if (typeof original[key] !== 'object')\n",
-       "        obj[key] = original[key]\n",
-       "    return obj;\n",
-       "  }, {});\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
-       "    var canvas_pos = mpl.findpos(event)\n",
-       "\n",
-       "    if (name === 'button_press')\n",
-       "    {\n",
-       "        this.canvas.focus();\n",
-       "        this.canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    var x = canvas_pos.x * mpl.ratio;\n",
-       "    var y = canvas_pos.y * mpl.ratio;\n",
-       "\n",
-       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
-       "                             step: event.step,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "\n",
-       "    /* This prevents the web browser from automatically changing to\n",
-       "     * the text insertion cursor when the button is pressed.  We want\n",
-       "     * to control all of the cursor setting manually through the\n",
-       "     * 'cursor' event from matplotlib */\n",
-       "    event.preventDefault();\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    // Handle any extra behaviour associated with a key event\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.key_event = function(event, name) {\n",
-       "\n",
-       "    // Prevent repeat events\n",
-       "    if (name == 'key_press')\n",
-       "    {\n",
-       "        if (event.which === this._key)\n",
-       "            return;\n",
-       "        else\n",
-       "            this._key = event.which;\n",
-       "    }\n",
-       "    if (name == 'key_release')\n",
-       "        this._key = null;\n",
-       "\n",
-       "    var value = '';\n",
-       "    if (event.ctrlKey && event.which != 17)\n",
-       "        value += \"ctrl+\";\n",
-       "    if (event.altKey && event.which != 18)\n",
-       "        value += \"alt+\";\n",
-       "    if (event.shiftKey && event.which != 16)\n",
-       "        value += \"shift+\";\n",
-       "\n",
-       "    value += 'k';\n",
-       "    value += event.which.toString();\n",
-       "\n",
-       "    this._key_event_extra(event, name);\n",
-       "\n",
-       "    this.send_message(name, {key: value,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
-       "    if (name == 'download') {\n",
-       "        this.handle_save(this, null);\n",
-       "    } else {\n",
-       "        this.send_message(\"toolbar_button\", {name: name});\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
-       "    this.message.textContent = tooltip;\n",
-       "};\n",
-       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
-       "\n",
-       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
-       "\n",
-       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
-       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
-       "    // object with the appropriate methods. Currently this is a non binary\n",
-       "    // socket, so there is still some room for performance tuning.\n",
-       "    var ws = {};\n",
-       "\n",
-       "    ws.close = function() {\n",
-       "        comm.close()\n",
-       "    };\n",
-       "    ws.send = function(m) {\n",
-       "        //console.log('sending', m);\n",
-       "        comm.send(m);\n",
-       "    };\n",
-       "    // Register the callback with on_msg.\n",
-       "    comm.on_msg(function(msg) {\n",
-       "        //console.log('receiving', msg['content']['data'], msg);\n",
-       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
-       "        ws.onmessage(msg['content']['data'])\n",
-       "    });\n",
-       "    return ws;\n",
-       "}\n",
-       "\n",
-       "mpl.mpl_figure_comm = function(comm, msg) {\n",
-       "    // This is the function which gets called when the mpl process\n",
-       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
-       "\n",
-       "    var id = msg.content.data.id;\n",
-       "    // Get hold of the div created by the display call when the Comm\n",
-       "    // socket was opened in Python.\n",
-       "    var element = $(\"#\" + id);\n",
-       "    var ws_proxy = comm_websocket_adapter(comm)\n",
-       "\n",
-       "    function ondownload(figure, format) {\n",
-       "        window.open(figure.imageObj.src);\n",
-       "    }\n",
-       "\n",
-       "    var fig = new mpl.figure(id, ws_proxy,\n",
-       "                           ondownload,\n",
-       "                           element.get(0));\n",
-       "\n",
-       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
-       "    // web socket which is closed, not our websocket->open comm proxy.\n",
-       "    ws_proxy.onopen();\n",
-       "\n",
-       "    fig.parent_element = element.get(0);\n",
-       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
-       "    if (!fig.cell_info) {\n",
-       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
-       "        return;\n",
-       "    }\n",
-       "\n",
-       "    var output_index = fig.cell_info[2]\n",
-       "    var cell = fig.cell_info[0];\n",
-       "\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
-       "    var width = fig.canvas.width/mpl.ratio\n",
-       "    fig.root.unbind('remove')\n",
-       "\n",
-       "    // Update the output cell to use the data from the current canvas.\n",
-       "    fig.push_to_output();\n",
-       "    var dataURL = fig.canvas.toDataURL();\n",
-       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
-       "    // the notebook keyboard shortcuts fail.\n",
-       "    IPython.keyboard_manager.enable()\n",
-       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
-       "    fig.close_ws(fig, msg);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
-       "    fig.send_message('closing', msg);\n",
-       "    // fig.ws.close()\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
-       "    // Turn the data on the canvas into data in the output cell.\n",
-       "    var width = this.canvas.width/mpl.ratio\n",
-       "    var dataURL = this.canvas.toDataURL();\n",
-       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Tell IPython that the notebook contents must change.\n",
-       "    IPython.notebook.set_dirty(true);\n",
-       "    this.send_message(\"ack\", {});\n",
-       "    var fig = this;\n",
-       "    // Wait a second, then push the new image to the DOM so\n",
-       "    // that it is saved nicely (might be nice to debounce this).\n",
-       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_toolbar = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var nav_element = $('<div/>')\n",
-       "    nav_element.attr('style', 'width: 100%');\n",
-       "    this.root.append(nav_element);\n",
-       "\n",
-       "    // Define a callback function for later on.\n",
-       "    function toolbar_event(event) {\n",
-       "        return fig.toolbar_button_onclick(event['data']);\n",
-       "    }\n",
-       "    function toolbar_mouse_event(event) {\n",
-       "        return fig.toolbar_button_onmouseover(event['data']);\n",
-       "    }\n",
-       "\n",
-       "    for(var toolbar_ind in mpl.toolbar_items){\n",
-       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
-       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
-       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
-       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
-       "\n",
-       "        if (!name) { continue; };\n",
-       "\n",
-       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
-       "        button.click(method_name, toolbar_event);\n",
-       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
-       "        nav_element.append(button);\n",
-       "    }\n",
-       "\n",
-       "    // Add the status bar.\n",
-       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
-       "    nav_element.append(status_bar);\n",
-       "    this.message = status_bar[0];\n",
-       "\n",
-       "    // Add the close button to the window.\n",
-       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
-       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
-       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
-       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
-       "    buttongrp.append(button);\n",
-       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
-       "    titlebar.prepend(buttongrp);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(el){\n",
-       "    var fig = this\n",
-       "    el.on(\"remove\", function(){\n",
-       "\tfig.close_ws(fig, {});\n",
-       "    });\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
-       "    // this is important to make the div 'focusable\n",
-       "    el.attr('tabindex', 0)\n",
-       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
-       "    // off when our div gets focus\n",
-       "\n",
-       "    // location in version 3\n",
-       "    if (IPython.notebook.keyboard_manager) {\n",
-       "        IPython.notebook.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "    else {\n",
-       "        // location in version 2\n",
-       "        IPython.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    var manager = IPython.notebook.keyboard_manager;\n",
-       "    if (!manager)\n",
-       "        manager = IPython.keyboard_manager;\n",
-       "\n",
-       "    // Check for shift+enter\n",
-       "    if (event.shiftKey && event.which == 13) {\n",
-       "        this.canvas_div.blur();\n",
-       "        event.shiftKey = false;\n",
-       "        // Send a \"J\" for go to next cell\n",
-       "        event.which = 74;\n",
-       "        event.keyCode = 74;\n",
-       "        manager.command_mode();\n",
-       "        manager.handle_keydown(event);\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
-       "    fig.ondownload(fig, null);\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.find_output_cell = function(html_output) {\n",
-       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
-       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
-       "    // IPython event is triggered only after the cells have been serialised, which for\n",
-       "    // our purposes (turning an active figure into a static one), is too late.\n",
-       "    var cells = IPython.notebook.get_cells();\n",
-       "    var ncells = cells.length;\n",
-       "    for (var i=0; i<ncells; i++) {\n",
-       "        var cell = cells[i];\n",
-       "        if (cell.cell_type === 'code'){\n",
-       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
-       "                var data = cell.output_area.outputs[j];\n",
-       "                if (data.data) {\n",
-       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
-       "                    data = data.data;\n",
-       "                }\n",
-       "                if (data['text/html'] == html_output) {\n",
-       "                    return [cell, data, j];\n",
-       "                }\n",
-       "            }\n",
-       "        }\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "// Register the function which deals with the matplotlib target/channel.\n",
-       "// The kernel may be null if the page has been refreshed.\n",
-       "if (IPython.notebook.kernel != null) {\n",
-       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
-       "}\n"
-      ],
       "text/plain": [
-       "<IPython.core.display.Javascript object>"
+       "[<matplotlib.lines.Line2D at 0x1c1c7b0780>]"
       ]
      },
+     "execution_count": 73,
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "execute_result"
     },
     {
      "data": {
-      "text/html": [
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\" 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+      "image/png": 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\n",
       "text/plain": [
-       "<IPython.core.display.HTML object>"
+       "<Figure size 432x288 with 1 Axes>"
       ]
      },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/plain": [
-       "[<matplotlib.lines.Line2D at 0x1c28cf46a0>]"
-      ]
+     "metadata": {
+      "needs_background": "light"
      },
-     "execution_count": 69,
-     "metadata": {},
-     "output_type": "execute_result"
+     "output_type": "display_data"
     }
    ],
    "source": [
@@ -3674,7 +2114,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 70,
+   "execution_count": 74,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -3683,7 +2123,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 71,
+   "execution_count": 75,
    "metadata": {},
    "outputs": [
     {
@@ -3692,7 +2132,7 @@
        "(9101, 99)"
       ]
      },
-     "execution_count": 71,
+     "execution_count": 75,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -3707,7 +2147,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 72,
+   "execution_count": 76,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -3716,7 +2156,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 73,
+   "execution_count": 77,
    "metadata": {},
    "outputs": [
     {
@@ -3726,7 +2166,7 @@
        "       9.100e+02])"
       ]
      },
-     "execution_count": 73,
+     "execution_count": 77,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -3737,7 +2177,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 74,
+   "execution_count": 78,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -3746,799 +2186,19 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 75,
+   "execution_count": 79,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "application/javascript": [
-       "/* Put everything inside the global mpl namespace */\n",
-       "window.mpl = {};\n",
-       "\n",
-       "\n",
-       "mpl.get_websocket_type = function() {\n",
-       "    if (typeof(WebSocket) !== 'undefined') {\n",
-       "        return WebSocket;\n",
-       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
-       "        return MozWebSocket;\n",
-       "    } else {\n",
-       "        alert('Your browser does not have WebSocket support.' +\n",
-       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
-       "              'Firefox 4 and 5 are also supported but you ' +\n",
-       "              'have to enable WebSockets in about:config.');\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
-       "    this.id = figure_id;\n",
-       "\n",
-       "    this.ws = websocket;\n",
-       "\n",
-       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
-       "\n",
-       "    if (!this.supports_binary) {\n",
-       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
-       "        if (warnings) {\n",
-       "            warnings.style.display = 'block';\n",
-       "            warnings.textContent = (\n",
-       "                \"This browser does not support binary websocket messages. \" +\n",
-       "                    \"Performance may be slow.\");\n",
-       "        }\n",
-       "    }\n",
-       "\n",
-       "    this.imageObj = new Image();\n",
-       "\n",
-       "    this.context = undefined;\n",
-       "    this.message = undefined;\n",
-       "    this.canvas = undefined;\n",
-       "    this.rubberband_canvas = undefined;\n",
-       "    this.rubberband_context = undefined;\n",
-       "    this.format_dropdown = undefined;\n",
-       "\n",
-       "    this.image_mode = 'full';\n",
-       "\n",
-       "    this.root = $('<div/>');\n",
-       "    this._root_extra_style(this.root)\n",
-       "    this.root.attr('style', 'display: inline-block');\n",
-       "\n",
-       "    $(parent_element).append(this.root);\n",
-       "\n",
-       "    this._init_header(this);\n",
-       "    this._init_canvas(this);\n",
-       "    this._init_toolbar(this);\n",
-       "\n",
-       "    var fig = this;\n",
-       "\n",
-       "    this.waiting = false;\n",
-       "\n",
-       "    this.ws.onopen =  function () {\n",
-       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
-       "            fig.send_message(\"send_image_mode\", {});\n",
-       "            if (mpl.ratio != 1) {\n",
-       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
-       "            }\n",
-       "            fig.send_message(\"refresh\", {});\n",
-       "        }\n",
-       "\n",
-       "    this.imageObj.onload = function() {\n",
-       "            if (fig.image_mode == 'full') {\n",
-       "                // Full images could contain transparency (where diff images\n",
-       "                // almost always do), so we need to clear the canvas so that\n",
-       "                // there is no ghosting.\n",
-       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
-       "            }\n",
-       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
-       "        };\n",
-       "\n",
-       "    this.imageObj.onunload = function() {\n",
-       "        fig.ws.close();\n",
-       "    }\n",
-       "\n",
-       "    this.ws.onmessage = this._make_on_message_function(this);\n",
-       "\n",
-       "    this.ondownload = ondownload;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_header = function() {\n",
-       "    var titlebar = $(\n",
-       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
-       "        'ui-helper-clearfix\"/>');\n",
-       "    var titletext = $(\n",
-       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
-       "        'text-align: center; padding: 3px;\"/>');\n",
-       "    titlebar.append(titletext)\n",
-       "    this.root.append(titlebar);\n",
-       "    this.header = titletext[0];\n",
-       "}\n",
-       "\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_canvas = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var canvas_div = $('<div/>');\n",
-       "\n",
-       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
-       "\n",
-       "    function canvas_keyboard_event(event) {\n",
-       "        return fig.key_event(event, event['data']);\n",
-       "    }\n",
-       "\n",
-       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
-       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
-       "    this.canvas_div = canvas_div\n",
-       "    this._canvas_extra_style(canvas_div)\n",
-       "    this.root.append(canvas_div);\n",
-       "\n",
-       "    var canvas = $('<canvas/>');\n",
-       "    canvas.addClass('mpl-canvas');\n",
-       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
-       "\n",
-       "    this.canvas = canvas[0];\n",
-       "    this.context = canvas[0].getContext(\"2d\");\n",
-       "\n",
-       "    var backingStore = this.context.backingStorePixelRatio ||\n",
-       "\tthis.context.webkitBackingStorePixelRatio ||\n",
-       "\tthis.context.mozBackingStorePixelRatio ||\n",
-       "\tthis.context.msBackingStorePixelRatio ||\n",
-       "\tthis.context.oBackingStorePixelRatio ||\n",
-       "\tthis.context.backingStorePixelRatio || 1;\n",
-       "\n",
-       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
-       "\n",
-       "    var rubberband = $('<canvas/>');\n",
-       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
-       "\n",
-       "    var pass_mouse_events = true;\n",
-       "\n",
-       "    canvas_div.resizable({\n",
-       "        start: function(event, ui) {\n",
-       "            pass_mouse_events = false;\n",
-       "        },\n",
-       "        resize: function(event, ui) {\n",
-       "            fig.request_resize(ui.size.width, ui.size.height);\n",
-       "        },\n",
-       "        stop: function(event, ui) {\n",
-       "            pass_mouse_events = true;\n",
-       "            fig.request_resize(ui.size.width, ui.size.height);\n",
-       "        },\n",
-       "    });\n",
-       "\n",
-       "    function mouse_event_fn(event) {\n",
-       "        if (pass_mouse_events)\n",
-       "            return fig.mouse_event(event, event['data']);\n",
-       "    }\n",
-       "\n",
-       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
-       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
-       "    // Throttle sequential mouse events to 1 every 20ms.\n",
-       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
-       "\n",
-       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
-       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
-       "\n",
-       "    canvas_div.on(\"wheel\", function (event) {\n",
-       "        event = event.originalEvent;\n",
-       "        event['data'] = 'scroll'\n",
-       "        if (event.deltaY < 0) {\n",
-       "            event.step = 1;\n",
-       "        } else {\n",
-       "            event.step = -1;\n",
-       "        }\n",
-       "        mouse_event_fn(event);\n",
-       "    });\n",
-       "\n",
-       "    canvas_div.append(canvas);\n",
-       "    canvas_div.append(rubberband);\n",
-       "\n",
-       "    this.rubberband = rubberband;\n",
-       "    this.rubberband_canvas = rubberband[0];\n",
-       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
-       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
-       "\n",
-       "    this._resize_canvas = function(width, height) {\n",
-       "        // Keep the size of the canvas, canvas container, and rubber band\n",
-       "        // canvas in synch.\n",
-       "        canvas_div.css('width', width)\n",
-       "        canvas_div.css('height', height)\n",
-       "\n",
-       "        canvas.attr('width', width * mpl.ratio);\n",
-       "        canvas.attr('height', height * mpl.ratio);\n",
-       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
-       "\n",
-       "        rubberband.attr('width', width);\n",
-       "        rubberband.attr('height', height);\n",
-       "    }\n",
-       "\n",
-       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
-       "    // upon first draw.\n",
-       "    this._resize_canvas(600, 600);\n",
-       "\n",
-       "    // Disable right mouse context menu.\n",
-       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
-       "        return false;\n",
-       "    });\n",
-       "\n",
-       "    function set_focus () {\n",
-       "        canvas.focus();\n",
-       "        canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    window.setTimeout(set_focus, 100);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_toolbar = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var nav_element = $('<div/>')\n",
-       "    nav_element.attr('style', 'width: 100%');\n",
-       "    this.root.append(nav_element);\n",
-       "\n",
-       "    // Define a callback function for later on.\n",
-       "    function toolbar_event(event) {\n",
-       "        return fig.toolbar_button_onclick(event['data']);\n",
-       "    }\n",
-       "    function toolbar_mouse_event(event) {\n",
-       "        return fig.toolbar_button_onmouseover(event['data']);\n",
-       "    }\n",
-       "\n",
-       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
-       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
-       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
-       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
-       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
-       "\n",
-       "        if (!name) {\n",
-       "            // put a spacer in here.\n",
-       "            continue;\n",
-       "        }\n",
-       "        var button = $('<button/>');\n",
-       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
-       "                        'ui-button-icon-only');\n",
-       "        button.attr('role', 'button');\n",
-       "        button.attr('aria-disabled', 'false');\n",
-       "        button.click(method_name, toolbar_event);\n",
-       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
-       "\n",
-       "        var icon_img = $('<span/>');\n",
-       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
-       "        icon_img.addClass(image);\n",
-       "        icon_img.addClass('ui-corner-all');\n",
-       "\n",
-       "        var tooltip_span = $('<span/>');\n",
-       "        tooltip_span.addClass('ui-button-text');\n",
-       "        tooltip_span.html(tooltip);\n",
-       "\n",
-       "        button.append(icon_img);\n",
-       "        button.append(tooltip_span);\n",
-       "\n",
-       "        nav_element.append(button);\n",
-       "    }\n",
-       "\n",
-       "    var fmt_picker_span = $('<span/>');\n",
-       "\n",
-       "    var fmt_picker = $('<select/>');\n",
-       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
-       "    fmt_picker_span.append(fmt_picker);\n",
-       "    nav_element.append(fmt_picker_span);\n",
-       "    this.format_dropdown = fmt_picker[0];\n",
-       "\n",
-       "    for (var ind in mpl.extensions) {\n",
-       "        var fmt = mpl.extensions[ind];\n",
-       "        var option = $(\n",
-       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
-       "        fmt_picker.append(option)\n",
-       "    }\n",
-       "\n",
-       "    // Add hover states to the ui-buttons\n",
-       "    $( \".ui-button\" ).hover(\n",
-       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
-       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
-       "    );\n",
-       "\n",
-       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
-       "    nav_element.append(status_bar);\n",
-       "    this.message = status_bar[0];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
-       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
-       "    // which will in turn request a refresh of the image.\n",
-       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.send_message = function(type, properties) {\n",
-       "    properties['type'] = type;\n",
-       "    properties['figure_id'] = this.id;\n",
-       "    this.ws.send(JSON.stringify(properties));\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.send_draw_message = function() {\n",
-       "    if (!this.waiting) {\n",
-       "        this.waiting = true;\n",
-       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
-       "    var format_dropdown = fig.format_dropdown;\n",
-       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
-       "    fig.ondownload(fig, format);\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
-       "    var size = msg['size'];\n",
-       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
-       "        fig._resize_canvas(size[0], size[1]);\n",
-       "        fig.send_message(\"refresh\", {});\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
-       "    var x0 = msg['x0'] / mpl.ratio;\n",
-       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
-       "    var x1 = msg['x1'] / mpl.ratio;\n",
-       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
-       "    x0 = Math.floor(x0) + 0.5;\n",
-       "    y0 = Math.floor(y0) + 0.5;\n",
-       "    x1 = Math.floor(x1) + 0.5;\n",
-       "    y1 = Math.floor(y1) + 0.5;\n",
-       "    var min_x = Math.min(x0, x1);\n",
-       "    var min_y = Math.min(y0, y1);\n",
-       "    var width = Math.abs(x1 - x0);\n",
-       "    var height = Math.abs(y1 - y0);\n",
-       "\n",
-       "    fig.rubberband_context.clearRect(\n",
-       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
-       "\n",
-       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
-       "    // Updates the figure title.\n",
-       "    fig.header.textContent = msg['label'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
-       "    var cursor = msg['cursor'];\n",
-       "    switch(cursor)\n",
-       "    {\n",
-       "    case 0:\n",
-       "        cursor = 'pointer';\n",
-       "        break;\n",
-       "    case 1:\n",
-       "        cursor = 'default';\n",
-       "        break;\n",
-       "    case 2:\n",
-       "        cursor = 'crosshair';\n",
-       "        break;\n",
-       "    case 3:\n",
-       "        cursor = 'move';\n",
-       "        break;\n",
-       "    }\n",
-       "    fig.rubberband_canvas.style.cursor = cursor;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
-       "    fig.message.textContent = msg['message'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
-       "    // Request the server to send over a new figure.\n",
-       "    fig.send_draw_message();\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
-       "    fig.image_mode = msg['mode'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Called whenever the canvas gets updated.\n",
-       "    this.send_message(\"ack\", {});\n",
-       "}\n",
-       "\n",
-       "// A function to construct a web socket function for onmessage handling.\n",
-       "// Called in the figure constructor.\n",
-       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
-       "    return function socket_on_message(evt) {\n",
-       "        if (evt.data instanceof Blob) {\n",
-       "            /* FIXME: We get \"Resource interpreted as Image but\n",
-       "             * transferred with MIME type text/plain:\" errors on\n",
-       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
-       "             * to be part of the websocket stream */\n",
-       "            evt.data.type = \"image/png\";\n",
-       "\n",
-       "            /* Free the memory for the previous frames */\n",
-       "            if (fig.imageObj.src) {\n",
-       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
-       "                    fig.imageObj.src);\n",
-       "            }\n",
-       "\n",
-       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
-       "                evt.data);\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
-       "            fig.imageObj.src = evt.data;\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        var msg = JSON.parse(evt.data);\n",
-       "        var msg_type = msg['type'];\n",
-       "\n",
-       "        // Call the  \"handle_{type}\" callback, which takes\n",
-       "        // the figure and JSON message as its only arguments.\n",
-       "        try {\n",
-       "            var callback = fig[\"handle_\" + msg_type];\n",
-       "        } catch (e) {\n",
-       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        if (callback) {\n",
-       "            try {\n",
-       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
-       "                callback(fig, msg);\n",
-       "            } catch (e) {\n",
-       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
-       "            }\n",
-       "        }\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
-       "mpl.findpos = function(e) {\n",
-       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
-       "    var targ;\n",
-       "    if (!e)\n",
-       "        e = window.event;\n",
-       "    if (e.target)\n",
-       "        targ = e.target;\n",
-       "    else if (e.srcElement)\n",
-       "        targ = e.srcElement;\n",
-       "    if (targ.nodeType == 3) // defeat Safari bug\n",
-       "        targ = targ.parentNode;\n",
-       "\n",
-       "    // jQuery normalizes the pageX and pageY\n",
-       "    // pageX,Y are the mouse positions relative to the document\n",
-       "    // offset() returns the position of the element relative to the document\n",
-       "    var x = e.pageX - $(targ).offset().left;\n",
-       "    var y = e.pageY - $(targ).offset().top;\n",
-       "\n",
-       "    return {\"x\": x, \"y\": y};\n",
-       "};\n",
-       "\n",
-       "/*\n",
-       " * return a copy of an object with only non-object keys\n",
-       " * we need this to avoid circular references\n",
-       " * http://stackoverflow.com/a/24161582/3208463\n",
-       " */\n",
-       "function simpleKeys (original) {\n",
-       "  return Object.keys(original).reduce(function (obj, key) {\n",
-       "    if (typeof original[key] !== 'object')\n",
-       "        obj[key] = original[key]\n",
-       "    return obj;\n",
-       "  }, {});\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
-       "    var canvas_pos = mpl.findpos(event)\n",
-       "\n",
-       "    if (name === 'button_press')\n",
-       "    {\n",
-       "        this.canvas.focus();\n",
-       "        this.canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    var x = canvas_pos.x * mpl.ratio;\n",
-       "    var y = canvas_pos.y * mpl.ratio;\n",
-       "\n",
-       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
-       "                             step: event.step,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "\n",
-       "    /* This prevents the web browser from automatically changing to\n",
-       "     * the text insertion cursor when the button is pressed.  We want\n",
-       "     * to control all of the cursor setting manually through the\n",
-       "     * 'cursor' event from matplotlib */\n",
-       "    event.preventDefault();\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    // Handle any extra behaviour associated with a key event\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.key_event = function(event, name) {\n",
-       "\n",
-       "    // Prevent repeat events\n",
-       "    if (name == 'key_press')\n",
-       "    {\n",
-       "        if (event.which === this._key)\n",
-       "            return;\n",
-       "        else\n",
-       "            this._key = event.which;\n",
-       "    }\n",
-       "    if (name == 'key_release')\n",
-       "        this._key = null;\n",
-       "\n",
-       "    var value = '';\n",
-       "    if (event.ctrlKey && event.which != 17)\n",
-       "        value += \"ctrl+\";\n",
-       "    if (event.altKey && event.which != 18)\n",
-       "        value += \"alt+\";\n",
-       "    if (event.shiftKey && event.which != 16)\n",
-       "        value += \"shift+\";\n",
-       "\n",
-       "    value += 'k';\n",
-       "    value += event.which.toString();\n",
-       "\n",
-       "    this._key_event_extra(event, name);\n",
-       "\n",
-       "    this.send_message(name, {key: value,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
-       "    if (name == 'download') {\n",
-       "        this.handle_save(this, null);\n",
-       "    } else {\n",
-       "        this.send_message(\"toolbar_button\", {name: name});\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
-       "    this.message.textContent = tooltip;\n",
-       "};\n",
-       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
-       "\n",
-       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
-       "\n",
-       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
-       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
-       "    // object with the appropriate methods. Currently this is a non binary\n",
-       "    // socket, so there is still some room for performance tuning.\n",
-       "    var ws = {};\n",
-       "\n",
-       "    ws.close = function() {\n",
-       "        comm.close()\n",
-       "    };\n",
-       "    ws.send = function(m) {\n",
-       "        //console.log('sending', m);\n",
-       "        comm.send(m);\n",
-       "    };\n",
-       "    // Register the callback with on_msg.\n",
-       "    comm.on_msg(function(msg) {\n",
-       "        //console.log('receiving', msg['content']['data'], msg);\n",
-       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
-       "        ws.onmessage(msg['content']['data'])\n",
-       "    });\n",
-       "    return ws;\n",
-       "}\n",
-       "\n",
-       "mpl.mpl_figure_comm = function(comm, msg) {\n",
-       "    // This is the function which gets called when the mpl process\n",
-       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
-       "\n",
-       "    var id = msg.content.data.id;\n",
-       "    // Get hold of the div created by the display call when the Comm\n",
-       "    // socket was opened in Python.\n",
-       "    var element = $(\"#\" + id);\n",
-       "    var ws_proxy = comm_websocket_adapter(comm)\n",
-       "\n",
-       "    function ondownload(figure, format) {\n",
-       "        window.open(figure.imageObj.src);\n",
-       "    }\n",
-       "\n",
-       "    var fig = new mpl.figure(id, ws_proxy,\n",
-       "                           ondownload,\n",
-       "                           element.get(0));\n",
-       "\n",
-       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
-       "    // web socket which is closed, not our websocket->open comm proxy.\n",
-       "    ws_proxy.onopen();\n",
-       "\n",
-       "    fig.parent_element = element.get(0);\n",
-       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
-       "    if (!fig.cell_info) {\n",
-       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
-       "        return;\n",
-       "    }\n",
-       "\n",
-       "    var output_index = fig.cell_info[2]\n",
-       "    var cell = fig.cell_info[0];\n",
-       "\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
-       "    var width = fig.canvas.width/mpl.ratio\n",
-       "    fig.root.unbind('remove')\n",
-       "\n",
-       "    // Update the output cell to use the data from the current canvas.\n",
-       "    fig.push_to_output();\n",
-       "    var dataURL = fig.canvas.toDataURL();\n",
-       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
-       "    // the notebook keyboard shortcuts fail.\n",
-       "    IPython.keyboard_manager.enable()\n",
-       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
-       "    fig.close_ws(fig, msg);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
-       "    fig.send_message('closing', msg);\n",
-       "    // fig.ws.close()\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
-       "    // Turn the data on the canvas into data in the output cell.\n",
-       "    var width = this.canvas.width/mpl.ratio\n",
-       "    var dataURL = this.canvas.toDataURL();\n",
-       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Tell IPython that the notebook contents must change.\n",
-       "    IPython.notebook.set_dirty(true);\n",
-       "    this.send_message(\"ack\", {});\n",
-       "    var fig = this;\n",
-       "    // Wait a second, then push the new image to the DOM so\n",
-       "    // that it is saved nicely (might be nice to debounce this).\n",
-       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_toolbar = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var nav_element = $('<div/>')\n",
-       "    nav_element.attr('style', 'width: 100%');\n",
-       "    this.root.append(nav_element);\n",
-       "\n",
-       "    // Define a callback function for later on.\n",
-       "    function toolbar_event(event) {\n",
-       "        return fig.toolbar_button_onclick(event['data']);\n",
-       "    }\n",
-       "    function toolbar_mouse_event(event) {\n",
-       "        return fig.toolbar_button_onmouseover(event['data']);\n",
-       "    }\n",
-       "\n",
-       "    for(var toolbar_ind in mpl.toolbar_items){\n",
-       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
-       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
-       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
-       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
-       "\n",
-       "        if (!name) { continue; };\n",
-       "\n",
-       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
-       "        button.click(method_name, toolbar_event);\n",
-       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
-       "        nav_element.append(button);\n",
-       "    }\n",
-       "\n",
-       "    // Add the status bar.\n",
-       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
-       "    nav_element.append(status_bar);\n",
-       "    this.message = status_bar[0];\n",
-       "\n",
-       "    // Add the close button to the window.\n",
-       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
-       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
-       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
-       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
-       "    buttongrp.append(button);\n",
-       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
-       "    titlebar.prepend(buttongrp);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(el){\n",
-       "    var fig = this\n",
-       "    el.on(\"remove\", function(){\n",
-       "\tfig.close_ws(fig, {});\n",
-       "    });\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
-       "    // this is important to make the div 'focusable\n",
-       "    el.attr('tabindex', 0)\n",
-       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
-       "    // off when our div gets focus\n",
-       "\n",
-       "    // location in version 3\n",
-       "    if (IPython.notebook.keyboard_manager) {\n",
-       "        IPython.notebook.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "    else {\n",
-       "        // location in version 2\n",
-       "        IPython.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    var manager = IPython.notebook.keyboard_manager;\n",
-       "    if (!manager)\n",
-       "        manager = IPython.keyboard_manager;\n",
-       "\n",
-       "    // Check for shift+enter\n",
-       "    if (event.shiftKey && event.which == 13) {\n",
-       "        this.canvas_div.blur();\n",
-       "        event.shiftKey = false;\n",
-       "        // Send a \"J\" for go to next cell\n",
-       "        event.which = 74;\n",
-       "        event.keyCode = 74;\n",
-       "        manager.command_mode();\n",
-       "        manager.handle_keydown(event);\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
-       "    fig.ondownload(fig, null);\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.find_output_cell = function(html_output) {\n",
-       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
-       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
-       "    // IPython event is triggered only after the cells have been serialised, which for\n",
-       "    // our purposes (turning an active figure into a static one), is too late.\n",
-       "    var cells = IPython.notebook.get_cells();\n",
-       "    var ncells = cells.length;\n",
-       "    for (var i=0; i<ncells; i++) {\n",
-       "        var cell = cells[i];\n",
-       "        if (cell.cell_type === 'code'){\n",
-       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
-       "                var data = cell.output_area.outputs[j];\n",
-       "                if (data.data) {\n",
-       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
-       "                    data = data.data;\n",
-       "                }\n",
-       "                if (data['text/html'] == html_output) {\n",
-       "                    return [cell, data, j];\n",
-       "                }\n",
-       "            }\n",
-       "        }\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "// Register the function which deals with the matplotlib target/channel.\n",
-       "// The kernel may be null if the page has been refreshed.\n",
-       "if (IPython.notebook.kernel != null) {\n",
-       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
-       "}\n"
-      ],
+      "image/png": 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\n",
       "text/plain": [
-       "<IPython.core.display.Javascript object>"
+       "<Figure size 432x288 with 1 Axes>"
       ]
      },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
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\" width=\"640\">"
-      ],
-      "text/plain": [
-       "<IPython.core.display.HTML object>"
-      ]
+     "metadata": {
+      "needs_background": "light"
      },
-     "metadata": {},
      "output_type": "display_data"
     }
    ],
@@ -4549,7 +2209,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 76,
+   "execution_count": 80,
    "metadata": {},
    "outputs": [
     {
@@ -4558,7 +2218,7 @@
        "(9199,)"
       ]
      },
-     "execution_count": 76,
+     "execution_count": 80,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -4569,7 +2229,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 77,
+   "execution_count": 81,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -4578,7 +2238,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 78,
+   "execution_count": 82,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -4592,799 +2252,19 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 79,
+   "execution_count": 83,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "application/javascript": [
-       "/* Put everything inside the global mpl namespace */\n",
-       "window.mpl = {};\n",
-       "\n",
-       "\n",
-       "mpl.get_websocket_type = function() {\n",
-       "    if (typeof(WebSocket) !== 'undefined') {\n",
-       "        return WebSocket;\n",
-       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
-       "        return MozWebSocket;\n",
-       "    } else {\n",
-       "        alert('Your browser does not have WebSocket support.' +\n",
-       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
-       "              'Firefox 4 and 5 are also supported but you ' +\n",
-       "              'have to enable WebSockets in about:config.');\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
-       "    this.id = figure_id;\n",
-       "\n",
-       "    this.ws = websocket;\n",
-       "\n",
-       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
-       "\n",
-       "    if (!this.supports_binary) {\n",
-       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
-       "        if (warnings) {\n",
-       "            warnings.style.display = 'block';\n",
-       "            warnings.textContent = (\n",
-       "                \"This browser does not support binary websocket messages. \" +\n",
-       "                    \"Performance may be slow.\");\n",
-       "        }\n",
-       "    }\n",
-       "\n",
-       "    this.imageObj = new Image();\n",
-       "\n",
-       "    this.context = undefined;\n",
-       "    this.message = undefined;\n",
-       "    this.canvas = undefined;\n",
-       "    this.rubberband_canvas = undefined;\n",
-       "    this.rubberband_context = undefined;\n",
-       "    this.format_dropdown = undefined;\n",
-       "\n",
-       "    this.image_mode = 'full';\n",
-       "\n",
-       "    this.root = $('<div/>');\n",
-       "    this._root_extra_style(this.root)\n",
-       "    this.root.attr('style', 'display: inline-block');\n",
-       "\n",
-       "    $(parent_element).append(this.root);\n",
-       "\n",
-       "    this._init_header(this);\n",
-       "    this._init_canvas(this);\n",
-       "    this._init_toolbar(this);\n",
-       "\n",
-       "    var fig = this;\n",
-       "\n",
-       "    this.waiting = false;\n",
-       "\n",
-       "    this.ws.onopen =  function () {\n",
-       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
-       "            fig.send_message(\"send_image_mode\", {});\n",
-       "            if (mpl.ratio != 1) {\n",
-       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
-       "            }\n",
-       "            fig.send_message(\"refresh\", {});\n",
-       "        }\n",
-       "\n",
-       "    this.imageObj.onload = function() {\n",
-       "            if (fig.image_mode == 'full') {\n",
-       "                // Full images could contain transparency (where diff images\n",
-       "                // almost always do), so we need to clear the canvas so that\n",
-       "                // there is no ghosting.\n",
-       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
-       "            }\n",
-       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
-       "        };\n",
-       "\n",
-       "    this.imageObj.onunload = function() {\n",
-       "        fig.ws.close();\n",
-       "    }\n",
-       "\n",
-       "    this.ws.onmessage = this._make_on_message_function(this);\n",
-       "\n",
-       "    this.ondownload = ondownload;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_header = function() {\n",
-       "    var titlebar = $(\n",
-       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
-       "        'ui-helper-clearfix\"/>');\n",
-       "    var titletext = $(\n",
-       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
-       "        'text-align: center; padding: 3px;\"/>');\n",
-       "    titlebar.append(titletext)\n",
-       "    this.root.append(titlebar);\n",
-       "    this.header = titletext[0];\n",
-       "}\n",
-       "\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_canvas = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var canvas_div = $('<div/>');\n",
-       "\n",
-       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
-       "\n",
-       "    function canvas_keyboard_event(event) {\n",
-       "        return fig.key_event(event, event['data']);\n",
-       "    }\n",
-       "\n",
-       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
-       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
-       "    this.canvas_div = canvas_div\n",
-       "    this._canvas_extra_style(canvas_div)\n",
-       "    this.root.append(canvas_div);\n",
-       "\n",
-       "    var canvas = $('<canvas/>');\n",
-       "    canvas.addClass('mpl-canvas');\n",
-       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
-       "\n",
-       "    this.canvas = canvas[0];\n",
-       "    this.context = canvas[0].getContext(\"2d\");\n",
-       "\n",
-       "    var backingStore = this.context.backingStorePixelRatio ||\n",
-       "\tthis.context.webkitBackingStorePixelRatio ||\n",
-       "\tthis.context.mozBackingStorePixelRatio ||\n",
-       "\tthis.context.msBackingStorePixelRatio ||\n",
-       "\tthis.context.oBackingStorePixelRatio ||\n",
-       "\tthis.context.backingStorePixelRatio || 1;\n",
-       "\n",
-       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
-       "\n",
-       "    var rubberband = $('<canvas/>');\n",
-       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
-       "\n",
-       "    var pass_mouse_events = true;\n",
-       "\n",
-       "    canvas_div.resizable({\n",
-       "        start: function(event, ui) {\n",
-       "            pass_mouse_events = false;\n",
-       "        },\n",
-       "        resize: function(event, ui) {\n",
-       "            fig.request_resize(ui.size.width, ui.size.height);\n",
-       "        },\n",
-       "        stop: function(event, ui) {\n",
-       "            pass_mouse_events = true;\n",
-       "            fig.request_resize(ui.size.width, ui.size.height);\n",
-       "        },\n",
-       "    });\n",
-       "\n",
-       "    function mouse_event_fn(event) {\n",
-       "        if (pass_mouse_events)\n",
-       "            return fig.mouse_event(event, event['data']);\n",
-       "    }\n",
-       "\n",
-       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
-       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
-       "    // Throttle sequential mouse events to 1 every 20ms.\n",
-       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
-       "\n",
-       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
-       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
-       "\n",
-       "    canvas_div.on(\"wheel\", function (event) {\n",
-       "        event = event.originalEvent;\n",
-       "        event['data'] = 'scroll'\n",
-       "        if (event.deltaY < 0) {\n",
-       "            event.step = 1;\n",
-       "        } else {\n",
-       "            event.step = -1;\n",
-       "        }\n",
-       "        mouse_event_fn(event);\n",
-       "    });\n",
-       "\n",
-       "    canvas_div.append(canvas);\n",
-       "    canvas_div.append(rubberband);\n",
-       "\n",
-       "    this.rubberband = rubberband;\n",
-       "    this.rubberband_canvas = rubberband[0];\n",
-       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
-       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
-       "\n",
-       "    this._resize_canvas = function(width, height) {\n",
-       "        // Keep the size of the canvas, canvas container, and rubber band\n",
-       "        // canvas in synch.\n",
-       "        canvas_div.css('width', width)\n",
-       "        canvas_div.css('height', height)\n",
-       "\n",
-       "        canvas.attr('width', width * mpl.ratio);\n",
-       "        canvas.attr('height', height * mpl.ratio);\n",
-       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
-       "\n",
-       "        rubberband.attr('width', width);\n",
-       "        rubberband.attr('height', height);\n",
-       "    }\n",
-       "\n",
-       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
-       "    // upon first draw.\n",
-       "    this._resize_canvas(600, 600);\n",
-       "\n",
-       "    // Disable right mouse context menu.\n",
-       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
-       "        return false;\n",
-       "    });\n",
-       "\n",
-       "    function set_focus () {\n",
-       "        canvas.focus();\n",
-       "        canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    window.setTimeout(set_focus, 100);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_toolbar = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var nav_element = $('<div/>')\n",
-       "    nav_element.attr('style', 'width: 100%');\n",
-       "    this.root.append(nav_element);\n",
-       "\n",
-       "    // Define a callback function for later on.\n",
-       "    function toolbar_event(event) {\n",
-       "        return fig.toolbar_button_onclick(event['data']);\n",
-       "    }\n",
-       "    function toolbar_mouse_event(event) {\n",
-       "        return fig.toolbar_button_onmouseover(event['data']);\n",
-       "    }\n",
-       "\n",
-       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
-       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
-       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
-       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
-       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
-       "\n",
-       "        if (!name) {\n",
-       "            // put a spacer in here.\n",
-       "            continue;\n",
-       "        }\n",
-       "        var button = $('<button/>');\n",
-       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
-       "                        'ui-button-icon-only');\n",
-       "        button.attr('role', 'button');\n",
-       "        button.attr('aria-disabled', 'false');\n",
-       "        button.click(method_name, toolbar_event);\n",
-       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
-       "\n",
-       "        var icon_img = $('<span/>');\n",
-       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
-       "        icon_img.addClass(image);\n",
-       "        icon_img.addClass('ui-corner-all');\n",
-       "\n",
-       "        var tooltip_span = $('<span/>');\n",
-       "        tooltip_span.addClass('ui-button-text');\n",
-       "        tooltip_span.html(tooltip);\n",
-       "\n",
-       "        button.append(icon_img);\n",
-       "        button.append(tooltip_span);\n",
-       "\n",
-       "        nav_element.append(button);\n",
-       "    }\n",
-       "\n",
-       "    var fmt_picker_span = $('<span/>');\n",
-       "\n",
-       "    var fmt_picker = $('<select/>');\n",
-       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
-       "    fmt_picker_span.append(fmt_picker);\n",
-       "    nav_element.append(fmt_picker_span);\n",
-       "    this.format_dropdown = fmt_picker[0];\n",
-       "\n",
-       "    for (var ind in mpl.extensions) {\n",
-       "        var fmt = mpl.extensions[ind];\n",
-       "        var option = $(\n",
-       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
-       "        fmt_picker.append(option)\n",
-       "    }\n",
-       "\n",
-       "    // Add hover states to the ui-buttons\n",
-       "    $( \".ui-button\" ).hover(\n",
-       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
-       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
-       "    );\n",
-       "\n",
-       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
-       "    nav_element.append(status_bar);\n",
-       "    this.message = status_bar[0];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
-       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
-       "    // which will in turn request a refresh of the image.\n",
-       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.send_message = function(type, properties) {\n",
-       "    properties['type'] = type;\n",
-       "    properties['figure_id'] = this.id;\n",
-       "    this.ws.send(JSON.stringify(properties));\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.send_draw_message = function() {\n",
-       "    if (!this.waiting) {\n",
-       "        this.waiting = true;\n",
-       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
-       "    var format_dropdown = fig.format_dropdown;\n",
-       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
-       "    fig.ondownload(fig, format);\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
-       "    var size = msg['size'];\n",
-       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
-       "        fig._resize_canvas(size[0], size[1]);\n",
-       "        fig.send_message(\"refresh\", {});\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
-       "    var x0 = msg['x0'] / mpl.ratio;\n",
-       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
-       "    var x1 = msg['x1'] / mpl.ratio;\n",
-       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
-       "    x0 = Math.floor(x0) + 0.5;\n",
-       "    y0 = Math.floor(y0) + 0.5;\n",
-       "    x1 = Math.floor(x1) + 0.5;\n",
-       "    y1 = Math.floor(y1) + 0.5;\n",
-       "    var min_x = Math.min(x0, x1);\n",
-       "    var min_y = Math.min(y0, y1);\n",
-       "    var width = Math.abs(x1 - x0);\n",
-       "    var height = Math.abs(y1 - y0);\n",
-       "\n",
-       "    fig.rubberband_context.clearRect(\n",
-       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
-       "\n",
-       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
-       "    // Updates the figure title.\n",
-       "    fig.header.textContent = msg['label'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
-       "    var cursor = msg['cursor'];\n",
-       "    switch(cursor)\n",
-       "    {\n",
-       "    case 0:\n",
-       "        cursor = 'pointer';\n",
-       "        break;\n",
-       "    case 1:\n",
-       "        cursor = 'default';\n",
-       "        break;\n",
-       "    case 2:\n",
-       "        cursor = 'crosshair';\n",
-       "        break;\n",
-       "    case 3:\n",
-       "        cursor = 'move';\n",
-       "        break;\n",
-       "    }\n",
-       "    fig.rubberband_canvas.style.cursor = cursor;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
-       "    fig.message.textContent = msg['message'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
-       "    // Request the server to send over a new figure.\n",
-       "    fig.send_draw_message();\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
-       "    fig.image_mode = msg['mode'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Called whenever the canvas gets updated.\n",
-       "    this.send_message(\"ack\", {});\n",
-       "}\n",
-       "\n",
-       "// A function to construct a web socket function for onmessage handling.\n",
-       "// Called in the figure constructor.\n",
-       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
-       "    return function socket_on_message(evt) {\n",
-       "        if (evt.data instanceof Blob) {\n",
-       "            /* FIXME: We get \"Resource interpreted as Image but\n",
-       "             * transferred with MIME type text/plain:\" errors on\n",
-       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
-       "             * to be part of the websocket stream */\n",
-       "            evt.data.type = \"image/png\";\n",
-       "\n",
-       "            /* Free the memory for the previous frames */\n",
-       "            if (fig.imageObj.src) {\n",
-       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
-       "                    fig.imageObj.src);\n",
-       "            }\n",
-       "\n",
-       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
-       "                evt.data);\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
-       "            fig.imageObj.src = evt.data;\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        var msg = JSON.parse(evt.data);\n",
-       "        var msg_type = msg['type'];\n",
-       "\n",
-       "        // Call the  \"handle_{type}\" callback, which takes\n",
-       "        // the figure and JSON message as its only arguments.\n",
-       "        try {\n",
-       "            var callback = fig[\"handle_\" + msg_type];\n",
-       "        } catch (e) {\n",
-       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        if (callback) {\n",
-       "            try {\n",
-       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
-       "                callback(fig, msg);\n",
-       "            } catch (e) {\n",
-       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
-       "            }\n",
-       "        }\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
-       "mpl.findpos = function(e) {\n",
-       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
-       "    var targ;\n",
-       "    if (!e)\n",
-       "        e = window.event;\n",
-       "    if (e.target)\n",
-       "        targ = e.target;\n",
-       "    else if (e.srcElement)\n",
-       "        targ = e.srcElement;\n",
-       "    if (targ.nodeType == 3) // defeat Safari bug\n",
-       "        targ = targ.parentNode;\n",
-       "\n",
-       "    // jQuery normalizes the pageX and pageY\n",
-       "    // pageX,Y are the mouse positions relative to the document\n",
-       "    // offset() returns the position of the element relative to the document\n",
-       "    var x = e.pageX - $(targ).offset().left;\n",
-       "    var y = e.pageY - $(targ).offset().top;\n",
-       "\n",
-       "    return {\"x\": x, \"y\": y};\n",
-       "};\n",
-       "\n",
-       "/*\n",
-       " * return a copy of an object with only non-object keys\n",
-       " * we need this to avoid circular references\n",
-       " * http://stackoverflow.com/a/24161582/3208463\n",
-       " */\n",
-       "function simpleKeys (original) {\n",
-       "  return Object.keys(original).reduce(function (obj, key) {\n",
-       "    if (typeof original[key] !== 'object')\n",
-       "        obj[key] = original[key]\n",
-       "    return obj;\n",
-       "  }, {});\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
-       "    var canvas_pos = mpl.findpos(event)\n",
-       "\n",
-       "    if (name === 'button_press')\n",
-       "    {\n",
-       "        this.canvas.focus();\n",
-       "        this.canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    var x = canvas_pos.x * mpl.ratio;\n",
-       "    var y = canvas_pos.y * mpl.ratio;\n",
-       "\n",
-       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
-       "                             step: event.step,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "\n",
-       "    /* This prevents the web browser from automatically changing to\n",
-       "     * the text insertion cursor when the button is pressed.  We want\n",
-       "     * to control all of the cursor setting manually through the\n",
-       "     * 'cursor' event from matplotlib */\n",
-       "    event.preventDefault();\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    // Handle any extra behaviour associated with a key event\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.key_event = function(event, name) {\n",
-       "\n",
-       "    // Prevent repeat events\n",
-       "    if (name == 'key_press')\n",
-       "    {\n",
-       "        if (event.which === this._key)\n",
-       "            return;\n",
-       "        else\n",
-       "            this._key = event.which;\n",
-       "    }\n",
-       "    if (name == 'key_release')\n",
-       "        this._key = null;\n",
-       "\n",
-       "    var value = '';\n",
-       "    if (event.ctrlKey && event.which != 17)\n",
-       "        value += \"ctrl+\";\n",
-       "    if (event.altKey && event.which != 18)\n",
-       "        value += \"alt+\";\n",
-       "    if (event.shiftKey && event.which != 16)\n",
-       "        value += \"shift+\";\n",
-       "\n",
-       "    value += 'k';\n",
-       "    value += event.which.toString();\n",
-       "\n",
-       "    this._key_event_extra(event, name);\n",
-       "\n",
-       "    this.send_message(name, {key: value,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
-       "    if (name == 'download') {\n",
-       "        this.handle_save(this, null);\n",
-       "    } else {\n",
-       "        this.send_message(\"toolbar_button\", {name: name});\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
-       "    this.message.textContent = tooltip;\n",
-       "};\n",
-       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
-       "\n",
-       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
-       "\n",
-       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
-       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
-       "    // object with the appropriate methods. Currently this is a non binary\n",
-       "    // socket, so there is still some room for performance tuning.\n",
-       "    var ws = {};\n",
-       "\n",
-       "    ws.close = function() {\n",
-       "        comm.close()\n",
-       "    };\n",
-       "    ws.send = function(m) {\n",
-       "        //console.log('sending', m);\n",
-       "        comm.send(m);\n",
-       "    };\n",
-       "    // Register the callback with on_msg.\n",
-       "    comm.on_msg(function(msg) {\n",
-       "        //console.log('receiving', msg['content']['data'], msg);\n",
-       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
-       "        ws.onmessage(msg['content']['data'])\n",
-       "    });\n",
-       "    return ws;\n",
-       "}\n",
-       "\n",
-       "mpl.mpl_figure_comm = function(comm, msg) {\n",
-       "    // This is the function which gets called when the mpl process\n",
-       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
-       "\n",
-       "    var id = msg.content.data.id;\n",
-       "    // Get hold of the div created by the display call when the Comm\n",
-       "    // socket was opened in Python.\n",
-       "    var element = $(\"#\" + id);\n",
-       "    var ws_proxy = comm_websocket_adapter(comm)\n",
-       "\n",
-       "    function ondownload(figure, format) {\n",
-       "        window.open(figure.imageObj.src);\n",
-       "    }\n",
-       "\n",
-       "    var fig = new mpl.figure(id, ws_proxy,\n",
-       "                           ondownload,\n",
-       "                           element.get(0));\n",
-       "\n",
-       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
-       "    // web socket which is closed, not our websocket->open comm proxy.\n",
-       "    ws_proxy.onopen();\n",
-       "\n",
-       "    fig.parent_element = element.get(0);\n",
-       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
-       "    if (!fig.cell_info) {\n",
-       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
-       "        return;\n",
-       "    }\n",
-       "\n",
-       "    var output_index = fig.cell_info[2]\n",
-       "    var cell = fig.cell_info[0];\n",
-       "\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
-       "    var width = fig.canvas.width/mpl.ratio\n",
-       "    fig.root.unbind('remove')\n",
-       "\n",
-       "    // Update the output cell to use the data from the current canvas.\n",
-       "    fig.push_to_output();\n",
-       "    var dataURL = fig.canvas.toDataURL();\n",
-       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
-       "    // the notebook keyboard shortcuts fail.\n",
-       "    IPython.keyboard_manager.enable()\n",
-       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
-       "    fig.close_ws(fig, msg);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
-       "    fig.send_message('closing', msg);\n",
-       "    // fig.ws.close()\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
-       "    // Turn the data on the canvas into data in the output cell.\n",
-       "    var width = this.canvas.width/mpl.ratio\n",
-       "    var dataURL = this.canvas.toDataURL();\n",
-       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Tell IPython that the notebook contents must change.\n",
-       "    IPython.notebook.set_dirty(true);\n",
-       "    this.send_message(\"ack\", {});\n",
-       "    var fig = this;\n",
-       "    // Wait a second, then push the new image to the DOM so\n",
-       "    // that it is saved nicely (might be nice to debounce this).\n",
-       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_toolbar = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var nav_element = $('<div/>')\n",
-       "    nav_element.attr('style', 'width: 100%');\n",
-       "    this.root.append(nav_element);\n",
-       "\n",
-       "    // Define a callback function for later on.\n",
-       "    function toolbar_event(event) {\n",
-       "        return fig.toolbar_button_onclick(event['data']);\n",
-       "    }\n",
-       "    function toolbar_mouse_event(event) {\n",
-       "        return fig.toolbar_button_onmouseover(event['data']);\n",
-       "    }\n",
-       "\n",
-       "    for(var toolbar_ind in mpl.toolbar_items){\n",
-       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
-       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
-       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
-       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
-       "\n",
-       "        if (!name) { continue; };\n",
-       "\n",
-       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
-       "        button.click(method_name, toolbar_event);\n",
-       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
-       "        nav_element.append(button);\n",
-       "    }\n",
-       "\n",
-       "    // Add the status bar.\n",
-       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
-       "    nav_element.append(status_bar);\n",
-       "    this.message = status_bar[0];\n",
-       "\n",
-       "    // Add the close button to the window.\n",
-       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
-       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
-       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
-       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
-       "    buttongrp.append(button);\n",
-       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
-       "    titlebar.prepend(buttongrp);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(el){\n",
-       "    var fig = this\n",
-       "    el.on(\"remove\", function(){\n",
-       "\tfig.close_ws(fig, {});\n",
-       "    });\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
-       "    // this is important to make the div 'focusable\n",
-       "    el.attr('tabindex', 0)\n",
-       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
-       "    // off when our div gets focus\n",
-       "\n",
-       "    // location in version 3\n",
-       "    if (IPython.notebook.keyboard_manager) {\n",
-       "        IPython.notebook.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "    else {\n",
-       "        // location in version 2\n",
-       "        IPython.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    var manager = IPython.notebook.keyboard_manager;\n",
-       "    if (!manager)\n",
-       "        manager = IPython.keyboard_manager;\n",
-       "\n",
-       "    // Check for shift+enter\n",
-       "    if (event.shiftKey && event.which == 13) {\n",
-       "        this.canvas_div.blur();\n",
-       "        event.shiftKey = false;\n",
-       "        // Send a \"J\" for go to next cell\n",
-       "        event.which = 74;\n",
-       "        event.keyCode = 74;\n",
-       "        manager.command_mode();\n",
-       "        manager.handle_keydown(event);\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
-       "    fig.ondownload(fig, null);\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.find_output_cell = function(html_output) {\n",
-       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
-       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
-       "    // IPython event is triggered only after the cells have been serialised, which for\n",
-       "    // our purposes (turning an active figure into a static one), is too late.\n",
-       "    var cells = IPython.notebook.get_cells();\n",
-       "    var ncells = cells.length;\n",
-       "    for (var i=0; i<ncells; i++) {\n",
-       "        var cell = cells[i];\n",
-       "        if (cell.cell_type === 'code'){\n",
-       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
-       "                var data = cell.output_area.outputs[j];\n",
-       "                if (data.data) {\n",
-       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
-       "                    data = data.data;\n",
-       "                }\n",
-       "                if (data['text/html'] == html_output) {\n",
-       "                    return [cell, data, j];\n",
-       "                }\n",
-       "            }\n",
-       "        }\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "// Register the function which deals with the matplotlib target/channel.\n",
-       "// The kernel may be null if the page has been refreshed.\n",
-       "if (IPython.notebook.kernel != null) {\n",
-       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
-       "}\n"
-      ],
+      "image/png": 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\n",
       "text/plain": [
-       "<IPython.core.display.Javascript object>"
+       "<Figure size 800x250 with 1 Axes>"
       ]
      },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
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\" width=\"800\">"
-      ],
-      "text/plain": [
-       "<IPython.core.display.HTML object>"
-      ]
+     "metadata": {
+      "needs_background": "light"
      },
-     "metadata": {},
      "output_type": "display_data"
     }
    ],
@@ -5394,7 +2274,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 80,
+   "execution_count": 84,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -5403,7 +2283,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 81,
+   "execution_count": 85,
    "metadata": {},
    "outputs": [
     {
@@ -5412,7 +2292,7 @@
        "91"
       ]
      },
-     "execution_count": 81,
+     "execution_count": 85,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -5423,7 +2303,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 82,
+   "execution_count": 86,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -5433,7 +2313,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 83,
+   "execution_count": 87,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -5442,7 +2322,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 84,
+   "execution_count": 88,
    "metadata": {},
    "outputs": [
     {
@@ -5473,7 +2353,7 @@
        "       -1.25421237e+15, -1.07988457e+15, -9.25626065e+14])"
       ]
      },
-     "execution_count": 84,
+     "execution_count": 88,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -5484,810 +2364,30 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 85,
+   "execution_count": 89,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "application/javascript": [
-       "/* Put everything inside the global mpl namespace */\n",
-       "window.mpl = {};\n",
-       "\n",
-       "\n",
-       "mpl.get_websocket_type = function() {\n",
-       "    if (typeof(WebSocket) !== 'undefined') {\n",
-       "        return WebSocket;\n",
-       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
-       "        return MozWebSocket;\n",
-       "    } else {\n",
-       "        alert('Your browser does not have WebSocket support.' +\n",
-       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
-       "              'Firefox 4 and 5 are also supported but you ' +\n",
-       "              'have to enable WebSockets in about:config.');\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
-       "    this.id = figure_id;\n",
-       "\n",
-       "    this.ws = websocket;\n",
-       "\n",
-       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
-       "\n",
-       "    if (!this.supports_binary) {\n",
-       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
-       "        if (warnings) {\n",
-       "            warnings.style.display = 'block';\n",
-       "            warnings.textContent = (\n",
-       "                \"This browser does not support binary websocket messages. \" +\n",
-       "                    \"Performance may be slow.\");\n",
-       "        }\n",
-       "    }\n",
-       "\n",
-       "    this.imageObj = new Image();\n",
-       "\n",
-       "    this.context = undefined;\n",
-       "    this.message = undefined;\n",
-       "    this.canvas = undefined;\n",
-       "    this.rubberband_canvas = undefined;\n",
-       "    this.rubberband_context = undefined;\n",
-       "    this.format_dropdown = undefined;\n",
-       "\n",
-       "    this.image_mode = 'full';\n",
-       "\n",
-       "    this.root = $('<div/>');\n",
-       "    this._root_extra_style(this.root)\n",
-       "    this.root.attr('style', 'display: inline-block');\n",
-       "\n",
-       "    $(parent_element).append(this.root);\n",
-       "\n",
-       "    this._init_header(this);\n",
-       "    this._init_canvas(this);\n",
-       "    this._init_toolbar(this);\n",
-       "\n",
-       "    var fig = this;\n",
-       "\n",
-       "    this.waiting = false;\n",
-       "\n",
-       "    this.ws.onopen =  function () {\n",
-       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
-       "            fig.send_message(\"send_image_mode\", {});\n",
-       "            if (mpl.ratio != 1) {\n",
-       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
-       "            }\n",
-       "            fig.send_message(\"refresh\", {});\n",
-       "        }\n",
-       "\n",
-       "    this.imageObj.onload = function() {\n",
-       "            if (fig.image_mode == 'full') {\n",
-       "                // Full images could contain transparency (where diff images\n",
-       "                // almost always do), so we need to clear the canvas so that\n",
-       "                // there is no ghosting.\n",
-       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
-       "            }\n",
-       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
-       "        };\n",
-       "\n",
-       "    this.imageObj.onunload = function() {\n",
-       "        fig.ws.close();\n",
-       "    }\n",
-       "\n",
-       "    this.ws.onmessage = this._make_on_message_function(this);\n",
-       "\n",
-       "    this.ondownload = ondownload;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_header = function() {\n",
-       "    var titlebar = $(\n",
-       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
-       "        'ui-helper-clearfix\"/>');\n",
-       "    var titletext = $(\n",
-       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
-       "        'text-align: center; padding: 3px;\"/>');\n",
-       "    titlebar.append(titletext)\n",
-       "    this.root.append(titlebar);\n",
-       "    this.header = titletext[0];\n",
-       "}\n",
-       "\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_canvas = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var canvas_div = $('<div/>');\n",
-       "\n",
-       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
-       "\n",
-       "    function canvas_keyboard_event(event) {\n",
-       "        return fig.key_event(event, event['data']);\n",
-       "    }\n",
-       "\n",
-       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
-       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
-       "    this.canvas_div = canvas_div\n",
-       "    this._canvas_extra_style(canvas_div)\n",
-       "    this.root.append(canvas_div);\n",
-       "\n",
-       "    var canvas = $('<canvas/>');\n",
-       "    canvas.addClass('mpl-canvas');\n",
-       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
-       "\n",
-       "    this.canvas = canvas[0];\n",
-       "    this.context = canvas[0].getContext(\"2d\");\n",
-       "\n",
-       "    var backingStore = this.context.backingStorePixelRatio ||\n",
-       "\tthis.context.webkitBackingStorePixelRatio ||\n",
-       "\tthis.context.mozBackingStorePixelRatio ||\n",
-       "\tthis.context.msBackingStorePixelRatio ||\n",
-       "\tthis.context.oBackingStorePixelRatio ||\n",
-       "\tthis.context.backingStorePixelRatio || 1;\n",
-       "\n",
-       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
-       "\n",
-       "    var rubberband = $('<canvas/>');\n",
-       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
-       "\n",
-       "    var pass_mouse_events = true;\n",
-       "\n",
-       "    canvas_div.resizable({\n",
-       "        start: function(event, ui) {\n",
-       "            pass_mouse_events = false;\n",
-       "        },\n",
-       "        resize: function(event, ui) {\n",
-       "            fig.request_resize(ui.size.width, ui.size.height);\n",
-       "        },\n",
-       "        stop: function(event, ui) {\n",
-       "            pass_mouse_events = true;\n",
-       "            fig.request_resize(ui.size.width, ui.size.height);\n",
-       "        },\n",
-       "    });\n",
-       "\n",
-       "    function mouse_event_fn(event) {\n",
-       "        if (pass_mouse_events)\n",
-       "            return fig.mouse_event(event, event['data']);\n",
-       "    }\n",
-       "\n",
-       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
-       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
-       "    // Throttle sequential mouse events to 1 every 20ms.\n",
-       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
-       "\n",
-       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
-       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
-       "\n",
-       "    canvas_div.on(\"wheel\", function (event) {\n",
-       "        event = event.originalEvent;\n",
-       "        event['data'] = 'scroll'\n",
-       "        if (event.deltaY < 0) {\n",
-       "            event.step = 1;\n",
-       "        } else {\n",
-       "            event.step = -1;\n",
-       "        }\n",
-       "        mouse_event_fn(event);\n",
-       "    });\n",
-       "\n",
-       "    canvas_div.append(canvas);\n",
-       "    canvas_div.append(rubberband);\n",
-       "\n",
-       "    this.rubberband = rubberband;\n",
-       "    this.rubberband_canvas = rubberband[0];\n",
-       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
-       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
-       "\n",
-       "    this._resize_canvas = function(width, height) {\n",
-       "        // Keep the size of the canvas, canvas container, and rubber band\n",
-       "        // canvas in synch.\n",
-       "        canvas_div.css('width', width)\n",
-       "        canvas_div.css('height', height)\n",
-       "\n",
-       "        canvas.attr('width', width * mpl.ratio);\n",
-       "        canvas.attr('height', height * mpl.ratio);\n",
-       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
-       "\n",
-       "        rubberband.attr('width', width);\n",
-       "        rubberband.attr('height', height);\n",
-       "    }\n",
-       "\n",
-       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
-       "    // upon first draw.\n",
-       "    this._resize_canvas(600, 600);\n",
-       "\n",
-       "    // Disable right mouse context menu.\n",
-       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
-       "        return false;\n",
-       "    });\n",
-       "\n",
-       "    function set_focus () {\n",
-       "        canvas.focus();\n",
-       "        canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    window.setTimeout(set_focus, 100);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_toolbar = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var nav_element = $('<div/>')\n",
-       "    nav_element.attr('style', 'width: 100%');\n",
-       "    this.root.append(nav_element);\n",
-       "\n",
-       "    // Define a callback function for later on.\n",
-       "    function toolbar_event(event) {\n",
-       "        return fig.toolbar_button_onclick(event['data']);\n",
-       "    }\n",
-       "    function toolbar_mouse_event(event) {\n",
-       "        return fig.toolbar_button_onmouseover(event['data']);\n",
-       "    }\n",
-       "\n",
-       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
-       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
-       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
-       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
-       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
-       "\n",
-       "        if (!name) {\n",
-       "            // put a spacer in here.\n",
-       "            continue;\n",
-       "        }\n",
-       "        var button = $('<button/>');\n",
-       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
-       "                        'ui-button-icon-only');\n",
-       "        button.attr('role', 'button');\n",
-       "        button.attr('aria-disabled', 'false');\n",
-       "        button.click(method_name, toolbar_event);\n",
-       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
-       "\n",
-       "        var icon_img = $('<span/>');\n",
-       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
-       "        icon_img.addClass(image);\n",
-       "        icon_img.addClass('ui-corner-all');\n",
-       "\n",
-       "        var tooltip_span = $('<span/>');\n",
-       "        tooltip_span.addClass('ui-button-text');\n",
-       "        tooltip_span.html(tooltip);\n",
-       "\n",
-       "        button.append(icon_img);\n",
-       "        button.append(tooltip_span);\n",
-       "\n",
-       "        nav_element.append(button);\n",
-       "    }\n",
-       "\n",
-       "    var fmt_picker_span = $('<span/>');\n",
-       "\n",
-       "    var fmt_picker = $('<select/>');\n",
-       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
-       "    fmt_picker_span.append(fmt_picker);\n",
-       "    nav_element.append(fmt_picker_span);\n",
-       "    this.format_dropdown = fmt_picker[0];\n",
-       "\n",
-       "    for (var ind in mpl.extensions) {\n",
-       "        var fmt = mpl.extensions[ind];\n",
-       "        var option = $(\n",
-       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
-       "        fmt_picker.append(option)\n",
-       "    }\n",
-       "\n",
-       "    // Add hover states to the ui-buttons\n",
-       "    $( \".ui-button\" ).hover(\n",
-       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
-       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
-       "    );\n",
-       "\n",
-       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
-       "    nav_element.append(status_bar);\n",
-       "    this.message = status_bar[0];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
-       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
-       "    // which will in turn request a refresh of the image.\n",
-       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.send_message = function(type, properties) {\n",
-       "    properties['type'] = type;\n",
-       "    properties['figure_id'] = this.id;\n",
-       "    this.ws.send(JSON.stringify(properties));\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.send_draw_message = function() {\n",
-       "    if (!this.waiting) {\n",
-       "        this.waiting = true;\n",
-       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
-       "    var format_dropdown = fig.format_dropdown;\n",
-       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
-       "    fig.ondownload(fig, format);\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
-       "    var size = msg['size'];\n",
-       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
-       "        fig._resize_canvas(size[0], size[1]);\n",
-       "        fig.send_message(\"refresh\", {});\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
-       "    var x0 = msg['x0'] / mpl.ratio;\n",
-       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
-       "    var x1 = msg['x1'] / mpl.ratio;\n",
-       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
-       "    x0 = Math.floor(x0) + 0.5;\n",
-       "    y0 = Math.floor(y0) + 0.5;\n",
-       "    x1 = Math.floor(x1) + 0.5;\n",
-       "    y1 = Math.floor(y1) + 0.5;\n",
-       "    var min_x = Math.min(x0, x1);\n",
-       "    var min_y = Math.min(y0, y1);\n",
-       "    var width = Math.abs(x1 - x0);\n",
-       "    var height = Math.abs(y1 - y0);\n",
-       "\n",
-       "    fig.rubberband_context.clearRect(\n",
-       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
-       "\n",
-       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
-       "    // Updates the figure title.\n",
-       "    fig.header.textContent = msg['label'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
-       "    var cursor = msg['cursor'];\n",
-       "    switch(cursor)\n",
-       "    {\n",
-       "    case 0:\n",
-       "        cursor = 'pointer';\n",
-       "        break;\n",
-       "    case 1:\n",
-       "        cursor = 'default';\n",
-       "        break;\n",
-       "    case 2:\n",
-       "        cursor = 'crosshair';\n",
-       "        break;\n",
-       "    case 3:\n",
-       "        cursor = 'move';\n",
-       "        break;\n",
-       "    }\n",
-       "    fig.rubberband_canvas.style.cursor = cursor;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
-       "    fig.message.textContent = msg['message'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
-       "    // Request the server to send over a new figure.\n",
-       "    fig.send_draw_message();\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
-       "    fig.image_mode = msg['mode'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Called whenever the canvas gets updated.\n",
-       "    this.send_message(\"ack\", {});\n",
-       "}\n",
-       "\n",
-       "// A function to construct a web socket function for onmessage handling.\n",
-       "// Called in the figure constructor.\n",
-       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
-       "    return function socket_on_message(evt) {\n",
-       "        if (evt.data instanceof Blob) {\n",
-       "            /* FIXME: We get \"Resource interpreted as Image but\n",
-       "             * transferred with MIME type text/plain:\" errors on\n",
-       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
-       "             * to be part of the websocket stream */\n",
-       "            evt.data.type = \"image/png\";\n",
-       "\n",
-       "            /* Free the memory for the previous frames */\n",
-       "            if (fig.imageObj.src) {\n",
-       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
-       "                    fig.imageObj.src);\n",
-       "            }\n",
-       "\n",
-       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
-       "                evt.data);\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
-       "            fig.imageObj.src = evt.data;\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        var msg = JSON.parse(evt.data);\n",
-       "        var msg_type = msg['type'];\n",
-       "\n",
-       "        // Call the  \"handle_{type}\" callback, which takes\n",
-       "        // the figure and JSON message as its only arguments.\n",
-       "        try {\n",
-       "            var callback = fig[\"handle_\" + msg_type];\n",
-       "        } catch (e) {\n",
-       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        if (callback) {\n",
-       "            try {\n",
-       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
-       "                callback(fig, msg);\n",
-       "            } catch (e) {\n",
-       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
-       "            }\n",
-       "        }\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
-       "mpl.findpos = function(e) {\n",
-       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
-       "    var targ;\n",
-       "    if (!e)\n",
-       "        e = window.event;\n",
-       "    if (e.target)\n",
-       "        targ = e.target;\n",
-       "    else if (e.srcElement)\n",
-       "        targ = e.srcElement;\n",
-       "    if (targ.nodeType == 3) // defeat Safari bug\n",
-       "        targ = targ.parentNode;\n",
-       "\n",
-       "    // jQuery normalizes the pageX and pageY\n",
-       "    // pageX,Y are the mouse positions relative to the document\n",
-       "    // offset() returns the position of the element relative to the document\n",
-       "    var x = e.pageX - $(targ).offset().left;\n",
-       "    var y = e.pageY - $(targ).offset().top;\n",
-       "\n",
-       "    return {\"x\": x, \"y\": y};\n",
-       "};\n",
-       "\n",
-       "/*\n",
-       " * return a copy of an object with only non-object keys\n",
-       " * we need this to avoid circular references\n",
-       " * http://stackoverflow.com/a/24161582/3208463\n",
-       " */\n",
-       "function simpleKeys (original) {\n",
-       "  return Object.keys(original).reduce(function (obj, key) {\n",
-       "    if (typeof original[key] !== 'object')\n",
-       "        obj[key] = original[key]\n",
-       "    return obj;\n",
-       "  }, {});\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
-       "    var canvas_pos = mpl.findpos(event)\n",
-       "\n",
-       "    if (name === 'button_press')\n",
-       "    {\n",
-       "        this.canvas.focus();\n",
-       "        this.canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    var x = canvas_pos.x * mpl.ratio;\n",
-       "    var y = canvas_pos.y * mpl.ratio;\n",
-       "\n",
-       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
-       "                             step: event.step,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "\n",
-       "    /* This prevents the web browser from automatically changing to\n",
-       "     * the text insertion cursor when the button is pressed.  We want\n",
-       "     * to control all of the cursor setting manually through the\n",
-       "     * 'cursor' event from matplotlib */\n",
-       "    event.preventDefault();\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    // Handle any extra behaviour associated with a key event\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.key_event = function(event, name) {\n",
-       "\n",
-       "    // Prevent repeat events\n",
-       "    if (name == 'key_press')\n",
-       "    {\n",
-       "        if (event.which === this._key)\n",
-       "            return;\n",
-       "        else\n",
-       "            this._key = event.which;\n",
-       "    }\n",
-       "    if (name == 'key_release')\n",
-       "        this._key = null;\n",
-       "\n",
-       "    var value = '';\n",
-       "    if (event.ctrlKey && event.which != 17)\n",
-       "        value += \"ctrl+\";\n",
-       "    if (event.altKey && event.which != 18)\n",
-       "        value += \"alt+\";\n",
-       "    if (event.shiftKey && event.which != 16)\n",
-       "        value += \"shift+\";\n",
-       "\n",
-       "    value += 'k';\n",
-       "    value += event.which.toString();\n",
-       "\n",
-       "    this._key_event_extra(event, name);\n",
-       "\n",
-       "    this.send_message(name, {key: value,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
-       "    if (name == 'download') {\n",
-       "        this.handle_save(this, null);\n",
-       "    } else {\n",
-       "        this.send_message(\"toolbar_button\", {name: name});\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
-       "    this.message.textContent = tooltip;\n",
-       "};\n",
-       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
-       "\n",
-       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
-       "\n",
-       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
-       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
-       "    // object with the appropriate methods. Currently this is a non binary\n",
-       "    // socket, so there is still some room for performance tuning.\n",
-       "    var ws = {};\n",
-       "\n",
-       "    ws.close = function() {\n",
-       "        comm.close()\n",
-       "    };\n",
-       "    ws.send = function(m) {\n",
-       "        //console.log('sending', m);\n",
-       "        comm.send(m);\n",
-       "    };\n",
-       "    // Register the callback with on_msg.\n",
-       "    comm.on_msg(function(msg) {\n",
-       "        //console.log('receiving', msg['content']['data'], msg);\n",
-       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
-       "        ws.onmessage(msg['content']['data'])\n",
-       "    });\n",
-       "    return ws;\n",
-       "}\n",
-       "\n",
-       "mpl.mpl_figure_comm = function(comm, msg) {\n",
-       "    // This is the function which gets called when the mpl process\n",
-       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
-       "\n",
-       "    var id = msg.content.data.id;\n",
-       "    // Get hold of the div created by the display call when the Comm\n",
-       "    // socket was opened in Python.\n",
-       "    var element = $(\"#\" + id);\n",
-       "    var ws_proxy = comm_websocket_adapter(comm)\n",
-       "\n",
-       "    function ondownload(figure, format) {\n",
-       "        window.open(figure.imageObj.src);\n",
-       "    }\n",
-       "\n",
-       "    var fig = new mpl.figure(id, ws_proxy,\n",
-       "                           ondownload,\n",
-       "                           element.get(0));\n",
-       "\n",
-       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
-       "    // web socket which is closed, not our websocket->open comm proxy.\n",
-       "    ws_proxy.onopen();\n",
-       "\n",
-       "    fig.parent_element = element.get(0);\n",
-       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
-       "    if (!fig.cell_info) {\n",
-       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
-       "        return;\n",
-       "    }\n",
-       "\n",
-       "    var output_index = fig.cell_info[2]\n",
-       "    var cell = fig.cell_info[0];\n",
-       "\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
-       "    var width = fig.canvas.width/mpl.ratio\n",
-       "    fig.root.unbind('remove')\n",
-       "\n",
-       "    // Update the output cell to use the data from the current canvas.\n",
-       "    fig.push_to_output();\n",
-       "    var dataURL = fig.canvas.toDataURL();\n",
-       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
-       "    // the notebook keyboard shortcuts fail.\n",
-       "    IPython.keyboard_manager.enable()\n",
-       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
-       "    fig.close_ws(fig, msg);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
-       "    fig.send_message('closing', msg);\n",
-       "    // fig.ws.close()\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
-       "    // Turn the data on the canvas into data in the output cell.\n",
-       "    var width = this.canvas.width/mpl.ratio\n",
-       "    var dataURL = this.canvas.toDataURL();\n",
-       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Tell IPython that the notebook contents must change.\n",
-       "    IPython.notebook.set_dirty(true);\n",
-       "    this.send_message(\"ack\", {});\n",
-       "    var fig = this;\n",
-       "    // Wait a second, then push the new image to the DOM so\n",
-       "    // that it is saved nicely (might be nice to debounce this).\n",
-       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_toolbar = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var nav_element = $('<div/>')\n",
-       "    nav_element.attr('style', 'width: 100%');\n",
-       "    this.root.append(nav_element);\n",
-       "\n",
-       "    // Define a callback function for later on.\n",
-       "    function toolbar_event(event) {\n",
-       "        return fig.toolbar_button_onclick(event['data']);\n",
-       "    }\n",
-       "    function toolbar_mouse_event(event) {\n",
-       "        return fig.toolbar_button_onmouseover(event['data']);\n",
-       "    }\n",
-       "\n",
-       "    for(var toolbar_ind in mpl.toolbar_items){\n",
-       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
-       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
-       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
-       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
-       "\n",
-       "        if (!name) { continue; };\n",
-       "\n",
-       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
-       "        button.click(method_name, toolbar_event);\n",
-       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
-       "        nav_element.append(button);\n",
-       "    }\n",
-       "\n",
-       "    // Add the status bar.\n",
-       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
-       "    nav_element.append(status_bar);\n",
-       "    this.message = status_bar[0];\n",
-       "\n",
-       "    // Add the close button to the window.\n",
-       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
-       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
-       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
-       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
-       "    buttongrp.append(button);\n",
-       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
-       "    titlebar.prepend(buttongrp);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(el){\n",
-       "    var fig = this\n",
-       "    el.on(\"remove\", function(){\n",
-       "\tfig.close_ws(fig, {});\n",
-       "    });\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
-       "    // this is important to make the div 'focusable\n",
-       "    el.attr('tabindex', 0)\n",
-       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
-       "    // off when our div gets focus\n",
-       "\n",
-       "    // location in version 3\n",
-       "    if (IPython.notebook.keyboard_manager) {\n",
-       "        IPython.notebook.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "    else {\n",
-       "        // location in version 2\n",
-       "        IPython.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    var manager = IPython.notebook.keyboard_manager;\n",
-       "    if (!manager)\n",
-       "        manager = IPython.keyboard_manager;\n",
-       "\n",
-       "    // Check for shift+enter\n",
-       "    if (event.shiftKey && event.which == 13) {\n",
-       "        this.canvas_div.blur();\n",
-       "        event.shiftKey = false;\n",
-       "        // Send a \"J\" for go to next cell\n",
-       "        event.which = 74;\n",
-       "        event.keyCode = 74;\n",
-       "        manager.command_mode();\n",
-       "        manager.handle_keydown(event);\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
-       "    fig.ondownload(fig, null);\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.find_output_cell = function(html_output) {\n",
-       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
-       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
-       "    // IPython event is triggered only after the cells have been serialised, which for\n",
-       "    // our purposes (turning an active figure into a static one), is too late.\n",
-       "    var cells = IPython.notebook.get_cells();\n",
-       "    var ncells = cells.length;\n",
-       "    for (var i=0; i<ncells; i++) {\n",
-       "        var cell = cells[i];\n",
-       "        if (cell.cell_type === 'code'){\n",
-       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
-       "                var data = cell.output_area.outputs[j];\n",
-       "                if (data.data) {\n",
-       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
-       "                    data = data.data;\n",
-       "                }\n",
-       "                if (data['text/html'] == html_output) {\n",
-       "                    return [cell, data, j];\n",
-       "                }\n",
-       "            }\n",
-       "        }\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "// Register the function which deals with the matplotlib target/channel.\n",
-       "// The kernel may be null if the page has been refreshed.\n",
-       "if (IPython.notebook.kernel != null) {\n",
-       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
-       "}\n"
-      ],
       "text/plain": [
-       "<IPython.core.display.Javascript object>"
+       "[<matplotlib.lines.Line2D at 0x1c1c4e3c50>]"
       ]
      },
+     "execution_count": 89,
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "execute_result"
     },
     {
      "data": {
-      "text/html": [
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\" 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+      "image/png": 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\n",
       "text/plain": [
-       "<IPython.core.display.HTML object>"
+       "<Figure size 432x288 with 1 Axes>"
       ]
      },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/plain": [
-       "[<matplotlib.lines.Line2D at 0x1c2a3f2940>]"
-      ]
+     "metadata": {
+      "needs_background": "light"
      },
-     "execution_count": 85,
-     "metadata": {},
-     "output_type": "execute_result"
+     "output_type": "display_data"
     }
    ],
    "source": [
@@ -6296,7 +2396,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 41,
+   "execution_count": 90,
    "metadata": {},
    "outputs": [
     {
@@ -6313,7 +2413,7 @@
        "        43.,  44.,  45.])"
       ]
      },
-     "execution_count": 41,
+     "execution_count": 90,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -6324,7 +2424,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 86,
+   "execution_count": 91,
    "metadata": {},
    "outputs": [
     {
@@ -6334,7 +2434,7 @@
      "traceback": [
       "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
       "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
-      "\u001b[0;32m<ipython-input-86-7f9d267afe6b>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mhfdiff\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mgb\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mas_s\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;36m60\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mT\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
+      "\u001b[0;32m<ipython-input-91-7f9d267afe6b>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mhfdiff\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mgb\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mas_s\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;36m60\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mT\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
       "\u001b[0;31mValueError\u001b[0m: shapes (91,) and (99,152) not aligned: 91 (dim 0) != 99 (dim 0)"
      ]
     }
@@ -6345,7 +2445,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 87,
+   "execution_count": 92,
    "metadata": {},
    "outputs": [
     {
@@ -6355,7 +2455,7 @@
      "traceback": [
       "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
       "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
-      "\u001b[0;32m<ipython-input-87-ef665695f428>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mpl\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mt_filt_dec\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mhfdiff\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m':'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0mpl\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mxlabel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'time (s)'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0mpl\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mylabel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'field (nT)'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[0mpl\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshow\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m<ipython-input-92-ef665695f428>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mpl\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mt_filt_dec\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mhfdiff\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m':'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0mpl\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mxlabel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'time (s)'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0mpl\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mylabel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'field (nT)'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[0mpl\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshow\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
       "\u001b[0;31mNameError\u001b[0m: name 'hfdiff' is not defined"
      ]
     }
@@ -6369,7 +2469,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 96,
+   "execution_count": 93,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -6379,7 +2479,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 97,
+   "execution_count": 94,
    "metadata": {},
    "outputs": [
     {
@@ -6388,7 +2488,7 @@
        "15955.0"
       ]
      },
-     "execution_count": 97,
+     "execution_count": 94,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -6403,7 +2503,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 99,
+   "execution_count": 95,
    "metadata": {},
    "outputs": [
     {
@@ -6412,7 +2512,7 @@
        "40"
       ]
      },
-     "execution_count": 99,
+     "execution_count": 95,
      "metadata": {},
      "output_type": "execute_result"
     }
diff --git a/etc/filter/BOU20180901vmin.min b/etc/filter/BOU20180901vmin.min
new file mode 100644
index 000000000..b7b604b86
--- /dev/null
+++ b/etc/filter/BOU20180901vmin.min
@@ -0,0 +1,78 @@
+ Format                 IAGA-2002                                    |
+ Source of Data         United States Geological Survey (USGS)       |
+ Station Name           Boulder                                      |
+ IAGA CODE              BOU                                          |
+ Geodetic Latitude      40.137                                       |
+ Geodetic Longitude     254.763                                      |
+ Elevation              1682                                         |
+ Reported               MVHMVEMVZMSF                                 |
+ Sensor Orientation     HDZF                                         |
+ Digital Sampling       0.01 second                                  |
+ Data Interval Type     Average 1-Second                             |
+ Data Type              variation                                    |
+ # DECBAS               5527    (Baseline declination value in       |
+ # tenths of minutes East (0-216,000)).                              |
+ # CONDITIONS OF USE: The Conditions of Use for data provided        |
+ # through INTERMAGNET and acknowledgement templates can be found at |
+ # www.intermagnet.org                                               |
+DATE       TIME         DOY     BOUMVH    BOUMVE    BOUMVZ    BOUMSF |
+2018-09-01 23:00:00.000 244     20828.92    -52.88  47043.06  51965.67
+2018-09-01 23:01:00.000 244     20828.76    -52.59  47042.96  51965.49
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+2018-09-01 23:59:00.000 244     20827.78    -44.32  47040.51  51962.84
diff --git a/etc/filter/BOU20180901vsec.sec b/etc/filter/BOU20180901vsec.sec
new file mode 100644
index 000000000..fd0527621
--- /dev/null
+++ b/etc/filter/BOU20180901vsec.sec
@@ -0,0 +1,3649 @@
+ Format                 IAGA-2002                                    |
+ Source of Data         United States Geological Survey (USGS)       |
+ Station Name           Boulder                                      |
+ IAGA CODE              BOU                                          |
+ Geodetic Latitude      40.137                                       |
+ Geodetic Longitude     254.763                                      |
+ Elevation              1682                                         |
+ Reported               SVHSVESVZSSF                                 |
+ Sensor Orientation     HDZF                                         |
+ Digital Sampling       0.01 second                                  |
+ Data Interval Type     Average 1-Second                             |
+ Data Type              variation                                    |
+ # DECBAS               5527    (Baseline declination value in       |
+ # tenths of minutes East (0-216,000)).                              |
+ # CONDITIONS OF USE: The Conditions of Use for data provided        |
+ # through INTERMAGNET and acknowledgement templates can be found at |
+ # www.intermagnet.org                                               |
+DATE       TIME         DOY     BOUSVH    BOUSVE    BOUSVZ    BOUSSF |
+2018-09-01 22:59:15.000 244     20828.90    -52.97  47043.12  51965.71
+2018-09-01 22:59:16.000 244     20828.89    -52.97  47043.13  51965.71
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diff --git a/geomagio/algorithm/FilterAlgorithm.py b/geomagio/algorithm/FilterAlgorithm.py
index 37a0af2c6..d45c062f6 100644
--- a/geomagio/algorithm/FilterAlgorithm.py
+++ b/geomagio/algorithm/FilterAlgorithm.py
@@ -126,7 +126,6 @@ class FilterAlgorithm(Algorithm):
             stream containing filtered output
         """
         numtaps = len(window)
-        half = numtaps // 2
 
         # build view into data, with numtaps  chunks separated into 
         # overlapping 'rows'
@@ -181,3 +180,25 @@ def get_input_interval(self, start, end, observatory=None, channels=None):
         end = end + half*self.interval
 
         return (start, end)
+
+@classmethod
+    def add_arguments(cls, parser):
+        """Add command line arguments to argparse parser.
+        Parameters
+        ----------
+        parser: ArgumentParser
+            command line argument parser
+        """
+
+        parser.add_argument('--filter-oneminute',
+                default=None,
+                help='Select one minute filter')
+
+    def configure(self, arguments):
+        """Configure algorithm using comand line arguments.
+        Parameters
+        ----------
+        arguments: Namespace
+            parsed command line arguments
+        """
+        pass
diff --git a/geomagio/algorithm/__init__.py b/geomagio/algorithm/__init__.py
index f803adc7e..1b1423034 100644
--- a/geomagio/algorithm/__init__.py
+++ b/geomagio/algorithm/__init__.py
@@ -10,6 +10,7 @@ from .AlgorithmException import AlgorithmException
 from .AdjustedAlgorithm import AdjustedAlgorithm
 from .AverageAlgorithm import AverageAlgorithm
 from .DeltaFAlgorithm import DeltaFAlgorithm
+from .FilterAlgorithm import FilterAlgorithm
 from .SqDistAlgorithm import SqDistAlgorithm
 from .XYZAlgorithm import XYZAlgorithm
 
diff --git a/test/algorithm_test/FilterAlgorithm_test.py b/test/algorithm_test/FilterAlgorithm_test.py
new file mode 100644
index 000000000..98b39f14e
--- /dev/null
+++ b/test/algorithm_test/FilterAlgorithm_test.py
@@ -0,0 +1,41 @@
+from geomagio.algorithm import FilterAlgorithm as filt
+import geomagio.iaga2002 as i2
+from nose.tools import assert_equals
+from nose.tools import assert_almost_equals
+
+def test_process():
+    """
+    Check one minute filter data processing versus files generated from
+    original script
+    """
+    
+
+    # load boulder Jan 16 files from /etc/ directory
+    min_iaga2002_file = open('etc/filter/BOU20180901vmin.min')
+    min_iaga2002_string = min_iaga2002_file.read()
+    sec_iaga2002_file = open('etc/filter/BOU20180901vsec.sec')
+    sec_iaga2002_string = sec_iaga2002_file.read()
+    factory = i2.IAGA2002Factory()
+    min = factory.parse_string(min_iaga2002_string)
+    sec = factory.parse_string(sec_iaga2002_string)
+
+    # process hezf (raw) channels with loaded transform
+    filt_bou = a.process(sec, inchannels=('SVH','SVE','SVZ','SSF'), 
+                         outchannels=('MVH','MVE','MVZ','MSF'))
+
+    # unpack channels from loaded adjusted data file
+    u = min.select(channel='MVH')[0]
+    v = min.select(channel='MVE')[0]
+    w = min.select(channel='MVZ')[0]
+    f = min.select(channel='MSF')[0]
+    # unpack channels from adjusted processing of raw data
+    u_filt = filt_bou.select(channel='MVH')[0]
+    v_filt = filt_bou.select(channel='MVE')[0]
+    w_filt = filt_bou.select(channel='MVZ')[0]
+    f_filt = filt_bou.select(channel='MSF')[0]
+
+    for r in range(min[0].data.size):
+        assert_almost_equals(u.data[r], u_filt.data[r], 2)
+        assert_almost_equals(v.data[r], v_filt.data[r], 2)
+        assert_almost_equals(w.data[r], w_filt.data[r], 2)
+        assert_almost_equals(f.data[r], f_filt.data[r], 2)
-- 
GitLab