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{
"metadata": {
"name": "",
"signature": "sha256:0f91dd0485441d3a64000fbcee35260201d5298be30c4df7b0a4ff64d15bae6e"
},
"nbformat": 3,
"nbformat_minor": 0,
"worksheets": [
{
"cells": [
{
"cell_type": "code",
"collapsed": false,
"input": [
"%matplotlib inline"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 1
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"\n",
"np.random.seed(12345) # set seed for reproducibility\n",
"\n",
"N = 10\n",
"data = np.random.random((N, 4))\n",
"labels = ['point{0}'.format(i) for i in range(N)]\n",
"plt.subplots_adjust(bottom = 0.1)\n",
"plt.scatter(\n",
" data[:, 0], data[:, 1], marker = 'o', c = data[:, 2], s = data[:, 3]*1500,\n",
" cmap = plt.get_cmap('Spectral'))\n",
"for label, x, y in zip(labels, data[:, 0], data[:, 1]):\n",
" plt.text(x-.05, y+.05,\n",
" label,\n",
" ha = 'right', va = 'bottom')\n",
" plt.plot([x-.05,x], [y+.05,y], 'k-')"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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F+09LS6NZYAscbTvQyLGDVr4HEKj0DWnmNYTdUQuJiztKkyb/lRrWdLmqTp06975+9dVX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\nTab8jOPri7B7YRx2z/SmTlA36gR3x65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"text": [
"<matplotlib.figure.Figure at 0x2b2ffe9f0390>"
]
}
],
"prompt_number": 2
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"import mpld3\n",
"mpld3.enable_notebook()"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 3
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"\n",
"np.random.seed(12345) # set seed for reproducibility\n",
"\n",
"N = 10\n",
"data = np.random.random((N, 4))\n",
"labels = ['point{0}'.format(i) for i in range(N)]\n",
"plt.subplots_adjust(bottom = 0.1)\n",
"plt.scatter(\n",
" data[:, 0], data[:, 1], marker = 'o', c = data[:, 2], s = data[:, 3]*1500,\n",
" cmap = plt.get_cmap('Spectral'))\n",
"for label, x, y in zip(labels, data[:, 0], data[:, 1]):\n",
" plt.text(x-.05, y+.05,\n",
" label,\n",
" ha = 'right', va = 'bottom')\n",
" plt.plot([x-.05,x], [y+.05,y], 'k-')"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"\n",
"\n",
"<style>\n",
"\n",
"</style>\n",
"\n",
"<div id=\"fig_el31675474853560874409921888964\"></div>\n",
"<script>\n",
"function mpld3_load_lib(url, callback){\n",
" var s = document.createElement('script');\n",
" s.src = url;\n",
" s.async = true;\n",
" s.onreadystatechange = s.onload = callback;\n",
" s.onerror = function(){console.warn(\"failed to load library \" + url);};\n",
" document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
"}\n",
"\n",
"if(typeof(mpld3) !== \"undefined\" && mpld3._mpld3IsLoaded){\n",
" // already loaded: just create the figure\n",
" !function(mpld3){\n",
" \n",
" mpld3.draw_figure(\"fig_el31675474853560874409921888964\", {\"axes\": [{\"xlim\": [-0.20000000000000001, 1.2000000000000002], \"yscale\": \"linear\", \"axesbg\": \"#FFFFFF\", \"texts\": [{\"v_baseline\": \"auto\", \"h_anchor\": \"end\", \"color\": \"#000000\", \"text\": \"point0\", \"coordinates\": \"data\", \"zorder\": 3, \"alpha\": 1, \"fontsize\": 10.0, \"position\": [0.87961609281714781, 0.36637555458178589], \"rotation\": -0.0, \"id\": \"el3167547485357725776\"}, {\"v_baseline\": \"auto\", \"h_anchor\": \"end\", \"color\": \"#000000\", \"text\": \"point1\", \"coordinates\": \"data\", \"zorder\": 3, \"alpha\": 1, \"fontsize\": 10.0, \"position\": [0.51772502908168661, 0.64554470297925159], \"rotation\": -0.0, \"id\": \"el3167547485357727504\"}, {\"v_baseline\": \"auto\", \"h_anchor\": \"end\", \"color\": \"#000000\", \"text\": \"point2\", \"coordinates\": \"data\", \"zorder\": 3, \"alpha\": 1, \"fontsize\": 10.0, \"position\": [0.6989066375339118, 0.70356987085173539], \"rotation\": -0.0, \"id\": \"el3167547485357775440\"}, {\"v_baseline\": \"auto\", \"h_anchor\": \"end\", \"color\": \"#000000\", \"text\": \"point3\", \"coordinates\": \"data\", \"zorder\": 3, \"alpha\": 1, \"fontsize\": 10.0, \"position\": [-0.041611702058446512, 0.15644437669771932], \"rotation\": -0.0, \"id\": \"el3167547485357819152\"}, {\"v_baseline\": \"auto\", \"h_anchor\": \"end\", \"color\": \"#000000\", \"text\": \"point4\", \"coordinates\": \"data\", \"zorder\": 3, \"alpha\": 1, \"fontsize\": 10.0, \"position\": [0.75981255254093472, 0.92217591372428309], \"rotation\": -0.0, \"id\": \"el3167547485357821840\"}, {\"v_baseline\": \"auto\", \"h_anchor\": \"end\", \"color\": \"#000000\", \"text\": \"point5\", \"coordinates\": \"data\", \"zorder\": 3, \"alpha\": 1, \"fontsize\": 10.0, \"position\": [0.59247532789584123, 0.76745362081241375], \"rotation\": -0.0, \"id\": \"el3167547485357869648\"}, {\"v_baseline\": \"auto\", \"h_anchor\": \"end\", \"color\": \"#000000\", \"text\": \"point6\", \"coordinates\": \"data\", \"zorder\": 3, \"alpha\": 1, \"fontsize\": 10.0, \"position\": [0.38964460588480948, 0.77968908274685145], \"rotation\": -0.0, \"id\": \"el3167547485357917456\"}, {\"v_baseline\": \"auto\", \"h_anchor\": \"end\", \"color\": \"#000000\", \"text\": \"point7\", \"coordinates\": \"data\", \"zorder\": 3, \"alpha\": 1, \"fontsize\": 10.0, \"position\": [0.74082251784778852, 0.2209142577924344], \"rotation\": -0.0, \"id\": \"el3167547485357920144\"}, {\"v_baseline\": \"auto\", \"h_anchor\": \"end\", \"color\": \"#000000\", \"text\": \"point8\", \"coordinates\": \"data\", \"zorder\": 3, \"alpha\": 1, \"fontsize\": 10.0, \"position\": [0.85372253821700006, 0.074676210429265269], \"rotation\": -0.0, \"id\": \"el3167547485357973200\"}, {\"v_baseline\": \"auto\", \"h_anchor\": \"end\", \"color\": \"#000000\", \"text\": \"point9\", \"coordinates\": \"data\", \"zorder\": 3, \"alpha\": 1, \"fontsize\": 10.0, \"position\": [0.54636601041938049, 0.10195754510253359], \"rotation\": -0.0, \"id\": \"el3167547485358007632\"}], \"zoomable\": true, \"images\": [], \"xdomain\": [-0.20000000000000001, 1.2000000000000002], \"ylim\": [-0.20000000000000001, 1.0000000000000002], \"paths\": [], \"sharey\": [], \"sharex\": [], \"axesbgalpha\": null, \"axes\": [{\"scale\": \"linear\", \"tickformat\": null, \"grid\": {\"gridOn\": false}, \"fontsize\": 10.0, \"position\": \"bottom\", \"nticks\": 9, \"tickvalues\": null}, {\"scale\": \"linear\", \"tickformat\": null, \"grid\": {\"gridOn\": false}, \"fontsize\": 10.0, \"position\": \"left\", \"nticks\": 8, \"tickvalues\": null}], \"lines\": [{\"color\": \"#000000\", \"yindex\": 1, \"coordinates\": \"data\", \"dasharray\": \"none\", \"zorder\": 2, \"alpha\": 1, \"xindex\": 0, \"linewidth\": 1.0, \"data\": \"data01\", \"id\": \"el3167547485357726864\"}, {\"color\": \"#000000\", \"yindex\": 1, \"coordinates\": \"data\", \"dasharray\": \"none\", \"zorder\": 2, \"alpha\": 1, \"xindex\": 0, \"linewidth\": 1.0, \"data\": \"data02\", \"id\": \"el3167547485357774800\"}, {\"color\": \"#000000\", \"yindex\": 1, \"coordinates\": \"data\", \"dasharray\": \"none\", \"zorder\": 2, \"alpha\": 1, \"xindex\": 0, \"linewidth\": 1.0, \"data\": \"data03\", \"id\": \"el3167547485357818512\"}, {\"color\": \"#000000\", \"yindex\": 1, \"coordinates\": \"data\", \"dasharray\": \"none\", \"zorder\": 2, \"alpha\": 1, \"xindex\": 0, \"linewidth\": 1.0, \"data\": \"data04\", \"id\": \"el3167547485357821200\"}, {\"color\": \"#000000\", \"yindex\": 1, \"coordinates\": \"data\", \"dasharray\": \"none\", \"zorder\": 2, \"alpha\": 1, \"xindex\": 0, \"linewidth\": 1.0, \"data\": \"data05\", \"id\": \"el3167547485357869008\"}, {\"color\": \"#000000\", \"yindex\": 1, \"coordinates\": \"data\", \"dasharray\": \"none\", \"zorder\": 2, \"alpha\": 1, \"xindex\": 0, \"linewidth\": 1.0, \"data\": \"data06\", \"id\": \"el3167547485357916816\"}, {\"color\": \"#000000\", \"yindex\": 1, \"coordinates\": \"data\", \"dasharray\": \"none\", \"zorder\": 2, \"alpha\": 1, \"xindex\": 0, \"linewidth\": 1.0, \"data\": \"data07\", \"id\": \"el3167547485357919504\"}, {\"color\": \"#000000\", \"yindex\": 1, \"coordinates\": \"data\", \"dasharray\": \"none\", \"zorder\": 2, \"alpha\": 1, \"xindex\": 0, \"linewidth\": 1.0, \"data\": \"data08\", \"id\": \"el3167547485357971408\"}, {\"color\": \"#000000\", \"yindex\": 1, \"coordinates\": \"data\", \"dasharray\": \"none\", \"zorder\": 2, \"alpha\": 1, \"xindex\": 0, \"linewidth\": 1.0, \"data\": \"data09\", \"id\": \"el3167547485358006992\"}, {\"color\": \"#000000\", \"yindex\": 1, \"coordinates\": \"data\", \"dasharray\": \"none\", \"zorder\": 2, \"alpha\": 1, \"xindex\": 0, \"linewidth\": 1.0, \"data\": \"data10\", \"id\": \"el3167547485358009616\"}], \"markers\": [], \"id\": \"el3167547485356087184\", \"ydomain\": [-0.20000000000000001, 1.0000000000000002], \"collections\": [{\"paths\": [[[[0.0, -0.5], [0.13260155, -0.5], [0.25978993539242673, -0.44731684579412084], [0.3535533905932738, -0.3535533905932738], [0.44731684579412084, -0.25978993539242673], [0.5, -0.13260155], [0.5, 0.0], [0.5, 0.13260155], [0.44731684579412084, 0.25978993539242673], [0.3535533905932738, 0.3535533905932738], [0.25978993539242673, 0.44731684579412084], [0.13260155, 0.5], [0.0, 0.5], [-0.13260155, 0.5], [-0.25978993539242673, 0.44731684579412084], [-0.3535533905932738, 0.3535533905932738], [-0.44731684579412084, 0.25978993539242673], [-0.5, 0.13260155], [-0.5, 0.0], [-0.5, -0.13260155], [-0.44731684579412084, -0.25978993539242673], [-0.3535533905932738, -0.3535533905932738], [-0.25978993539242673, -0.44731684579412084], [-0.13260155, -0.5], [0.0, -0.5]], [\"M\", \"C\", \"C\", \"C\", \"C\", \"C\", \"C\", \"C\", \"C\", \"Z\"]]], \"edgecolors\": [\"#000000\"], \"edgewidths\": [1.0], \"offsets\": \"data11\", \"yindex\": 1, \"id\": \"el3167547485357723728\", \"pathtransforms\": [[19.463178842465002, 0.0, 0.0, 19.463178842465002, 0.0, 0.0], [34.77912040907353, 0.0, 0.0, 34.77912040907353, 0.0, 0.0], [42.192388642907076, 0.0, 0.0, 42.192388642907076, 0.0, 0.0], [34.86511530121715, 0.0, 0.0, 34.86511530121715, 0.0, 0.0], [36.60816916825759, 0.0, 0.0, 36.60816916825759, 0.0, 0.0], [24.554726388943635, 0.0, 0.0, 24.554726388943635, 0.0, 0.0], [35.40437595295379, 0.0, 0.0, 35.40437595295379, 0.0, 0.0], [38.49892360028372, 0.0, 0.0, 38.49892360028372, 0.0, 0.0], [31.2177290366138, 0.0, 0.0, 31.2177290366138, 0.0, 0.0], [36.7238488543868, 0.0, 0.0, 36.7238488543868, 0.0, 0.0]], \"pathcoordinates\": \"display\", \"offsetcoordinates\": \"data\", \"zorder\": 1, \"xindex\": 0, \"alphas\": [null], \"facecolors\": [\"#E75A47\", \"#515EA9\", \"#8BD0A4\", \"#FB9F5A\", \"#515EA9\", \"#FEF1A7\", \"#5E4FA2\", \"#9E0142\", \"#FEF9B5\", \"#3389BC\"]}], \"xscale\": \"linear\", \"bbox\": [0.125, 0.099999999999999978, 0.77500000000000002, 0.80000000000000004]}], \"height\": 320.0, \"width\": 480.0, \"plugins\": [{\"type\": \"reset\"}, {\"enabled\": false, \"button\": true, \"type\": \"zoom\"}, {\"enabled\": false, \"button\": true, \"type\": \"boxzoom\"}], \"data\": {\"data11\": [[0.9296160928171479, 0.3163755545817859], [0.5677250290816866, 0.5955447029792516], [0.7489066375339118, 0.6535698708517353], [0.00838829794155349, 0.10644437669771933], [0.8098125525409348, 0.872175913724283], [0.6424753278958413, 0.7174536208124137], [0.43964460588480947, 0.7296890827468514], [0.7908225178477886, 0.1709142577924344], [0.9037225382170001, 0.024676210429265266], [0.5963660104193805, 0.05195754510253359]], \"data10\": [[0.5463660104193805, 0.10195754510253359], [0.5963660104193805, 0.05195754510253359]], \"data08\": [[0.7408225178477885, 0.2209142577924344], [0.7908225178477886, 0.1709142577924344]], \"data09\": [[0.8537225382170001, 0.07467621042926527], [0.9037225382170001, 0.024676210429265266]], \"data06\": [[0.5924753278958412, 0.7674536208124138], [0.6424753278958413, 0.7174536208124137]], \"data07\": [[0.3896446058848095, 0.7796890827468514], [0.43964460588480947, 0.7296890827468514]], \"data04\": [[-0.04161170205844651, 0.15644437669771932], [0.00838829794155349, 0.10644437669771933]], \"data05\": [[0.7598125525409347, 0.9221759137242831], [0.8098125525409348, 0.872175913724283]], \"data02\": [[0.5177250290816866, 0.6455447029792516], [0.5677250290816866, 0.5955447029792516]], \"data03\": [[0.6989066375339118, 0.7035698708517354], [0.7489066375339118, 0.6535698708517353]], \"data01\": [[0.8796160928171478, 0.3663755545817859], [0.9296160928171479, 0.3163755545817859]]}, \"id\": \"el3167547485356087440\"});\n",
" }(mpld3);\n",
"}else if(typeof define === \"function\" && define.amd){\n",
" // require.js is available: use it to load d3/mpld3\n",
" require.config({paths: {d3: \"https://mpld3.github.io/js/d3.v3.min\"}});\n",
" require([\"d3\"], function(d3){\n",
" window.d3 = d3;\n",
" mpld3_load_lib(\"https://mpld3.github.io/js/mpld3.v0.3git.js\", function(){\n",
" \n",
" mpld3.draw_figure(\"fig_el31675474853560874409921888964\", {\"axes\": [{\"xlim\": [-0.20000000000000001, 1.2000000000000002], \"yscale\": \"linear\", \"axesbg\": \"#FFFFFF\", \"texts\": [{\"v_baseline\": \"auto\", \"h_anchor\": \"end\", \"color\": \"#000000\", \"text\": \"point0\", \"coordinates\": \"data\", \"zorder\": 3, \"alpha\": 1, \"fontsize\": 10.0, \"position\": [0.87961609281714781, 0.36637555458178589], \"rotation\": -0.0, \"id\": \"el3167547485357725776\"}, {\"v_baseline\": \"auto\", \"h_anchor\": \"end\", \"color\": \"#000000\", \"text\": \"point1\", \"coordinates\": \"data\", \"zorder\": 3, \"alpha\": 1, \"fontsize\": 10.0, \"position\": [0.51772502908168661, 0.64554470297925159], \"rotation\": -0.0, \"id\": \"el3167547485357727504\"}, {\"v_baseline\": \"auto\", \"h_anchor\": \"end\", \"color\": \"#000000\", \"text\": \"point2\", \"coordinates\": \"data\", \"zorder\": 3, \"alpha\": 1, \"fontsize\": 10.0, \"position\": [0.6989066375339118, 0.70356987085173539], \"rotation\": -0.0, \"id\": \"el3167547485357775440\"}, {\"v_baseline\": \"auto\", \"h_anchor\": \"end\", \"color\": \"#000000\", \"text\": \"point3\", \"coordinates\": \"data\", \"zorder\": 3, \"alpha\": 1, \"fontsize\": 10.0, \"position\": [-0.041611702058446512, 0.15644437669771932], \"rotation\": -0.0, \"id\": \"el3167547485357819152\"}, {\"v_baseline\": \"auto\", \"h_anchor\": \"end\", \"color\": \"#000000\", \"text\": \"point4\", \"coordinates\": \"data\", \"zorder\": 3, \"alpha\": 1, \"fontsize\": 10.0, \"position\": [0.75981255254093472, 0.92217591372428309], \"rotation\": -0.0, \"id\": \"el3167547485357821840\"}, {\"v_baseline\": \"auto\", \"h_anchor\": \"end\", \"color\": \"#000000\", \"text\": \"point5\", \"coordinates\": \"data\", \"zorder\": 3, \"alpha\": 1, \"fontsize\": 10.0, \"position\": [0.59247532789584123, 0.76745362081241375], \"rotation\": -0.0, \"id\": \"el3167547485357869648\"}, {\"v_baseline\": \"auto\", \"h_anchor\": \"end\", \"color\": \"#000000\", \"text\": \"point6\", \"coordinates\": \"data\", \"zorder\": 3, \"alpha\": 1, \"fontsize\": 10.0, \"position\": [0.38964460588480948, 0.77968908274685145], \"rotation\": -0.0, \"id\": \"el3167547485357917456\"}, {\"v_baseline\": \"auto\", \"h_anchor\": \"end\", \"color\": \"#000000\", \"text\": \"point7\", \"coordinates\": \"data\", \"zorder\": 3, \"alpha\": 1, \"fontsize\": 10.0, \"position\": [0.74082251784778852, 0.2209142577924344], \"rotation\": -0.0, \"id\": \"el3167547485357920144\"}, {\"v_baseline\": \"auto\", \"h_anchor\": \"end\", \"color\": \"#000000\", \"text\": \"point8\", \"coordinates\": \"data\", \"zorder\": 3, \"alpha\": 1, \"fontsize\": 10.0, \"position\": [0.85372253821700006, 0.074676210429265269], \"rotation\": -0.0, \"id\": \"el3167547485357973200\"}, {\"v_baseline\": \"auto\", \"h_anchor\": \"end\", \"color\": \"#000000\", \"text\": \"point9\", \"coordinates\": \"data\", \"zorder\": 3, \"alpha\": 1, \"fontsize\": 10.0, \"position\": [0.54636601041938049, 0.10195754510253359], \"rotation\": -0.0, \"id\": \"el3167547485358007632\"}], \"zoomable\": true, \"images\": [], \"xdomain\": [-0.20000000000000001, 1.2000000000000002], \"ylim\": [-0.20000000000000001, 1.0000000000000002], \"paths\": [], \"sharey\": [], \"sharex\": [], \"axesbgalpha\": null, \"axes\": [{\"scale\": \"linear\", \"tickformat\": null, \"grid\": {\"gridOn\": false}, \"fontsize\": 10.0, \"position\": \"bottom\", \"nticks\": 9, \"tickvalues\": null}, {\"scale\": \"linear\", \"tickformat\": null, \"grid\": {\"gridOn\": false}, \"fontsize\": 10.0, \"position\": \"left\", \"nticks\": 8, \"tickvalues\": null}], \"lines\": [{\"color\": \"#000000\", \"yindex\": 1, \"coordinates\": \"data\", \"dasharray\": \"none\", \"zorder\": 2, \"alpha\": 1, \"xindex\": 0, \"linewidth\": 1.0, \"data\": \"data01\", \"id\": \"el3167547485357726864\"}, {\"color\": \"#000000\", \"yindex\": 1, \"coordinates\": \"data\", \"dasharray\": \"none\", \"zorder\": 2, \"alpha\": 1, \"xindex\": 0, \"linewidth\": 1.0, \"data\": \"data02\", \"id\": \"el3167547485357774800\"}, {\"color\": \"#000000\", \"yindex\": 1, \"coordinates\": \"data\", \"dasharray\": \"none\", \"zorder\": 2, \"alpha\": 1, \"xindex\": 0, \"linewidth\": 1.0, \"data\": \"data03\", \"id\": \"el3167547485357818512\"}, {\"color\": \"#000000\", \"yindex\": 1, \"coordinates\": \"data\", \"dasharray\": \"none\", \"zorder\": 2, \"alpha\": 1, \"xindex\": 0, \"linewidth\": 1.0, \"data\": \"data04\", \"id\": \"el3167547485357821200\"}, {\"color\": \"#000000\", \"yindex\": 1, \"coordinates\": \"data\", \"dasharray\": \"none\", \"zorder\": 2, \"alpha\": 1, \"xindex\": 0, \"linewidth\": 1.0, \"data\": \"data05\", \"id\": \"el3167547485357869008\"}, {\"color\": \"#000000\", \"yindex\": 1, \"coordinates\": \"data\", \"dasharray\": \"none\", \"zorder\": 2, \"alpha\": 1, \"xindex\": 0, \"linewidth\": 1.0, \"data\": \"data06\", \"id\": \"el3167547485357916816\"}, {\"color\": \"#000000\", \"yindex\": 1, \"coordinates\": \"data\", \"dasharray\": \"none\", \"zorder\": 2, \"alpha\": 1, \"xindex\": 0, \"linewidth\": 1.0, \"data\": \"data07\", \"id\": \"el3167547485357919504\"}, {\"color\": \"#000000\", \"yindex\": 1, \"coordinates\": \"data\", \"dasharray\": \"none\", \"zorder\": 2, \"alpha\": 1, \"xindex\": 0, \"linewidth\": 1.0, \"data\": \"data08\", \"id\": \"el3167547485357971408\"}, {\"color\": \"#000000\", \"yindex\": 1, \"coordinates\": \"data\", \"dasharray\": \"none\", \"zorder\": 2, \"alpha\": 1, \"xindex\": 0, \"linewidth\": 1.0, \"data\": \"data09\", \"id\": \"el3167547485358006992\"}, {\"color\": \"#000000\", \"yindex\": 1, \"coordinates\": \"data\", \"dasharray\": \"none\", \"zorder\": 2, \"alpha\": 1, \"xindex\": 0, \"linewidth\": 1.0, \"data\": \"data10\", \"id\": \"el3167547485358009616\"}], \"markers\": [], \"id\": \"el3167547485356087184\", \"ydomain\": [-0.20000000000000001, 1.0000000000000002], \"collections\": [{\"paths\": [[[[0.0, -0.5], [0.13260155, -0.5], [0.25978993539242673, -0.44731684579412084], [0.3535533905932738, -0.3535533905932738], [0.44731684579412084, -0.25978993539242673], [0.5, -0.13260155], [0.5, 0.0], [0.5, 0.13260155], [0.44731684579412084, 0.25978993539242673], [0.3535533905932738, 0.3535533905932738], [0.25978993539242673, 0.44731684579412084], [0.13260155, 0.5], [0.0, 0.5], [-0.13260155, 0.5], [-0.25978993539242673, 0.44731684579412084], [-0.3535533905932738, 0.3535533905932738], [-0.44731684579412084, 0.25978993539242673], [-0.5, 0.13260155], [-0.5, 0.0], [-0.5, -0.13260155], [-0.44731684579412084, -0.25978993539242673], [-0.3535533905932738, -0.3535533905932738], [-0.25978993539242673, -0.44731684579412084], [-0.13260155, -0.5], [0.0, -0.5]], [\"M\", \"C\", \"C\", \"C\", \"C\", \"C\", \"C\", \"C\", \"C\", \"Z\"]]], \"edgecolors\": [\"#000000\"], \"edgewidths\": [1.0], \"offsets\": \"data11\", \"yindex\": 1, \"id\": \"el3167547485357723728\", \"pathtransforms\": [[19.463178842465002, 0.0, 0.0, 19.463178842465002, 0.0, 0.0], [34.77912040907353, 0.0, 0.0, 34.77912040907353, 0.0, 0.0], [42.192388642907076, 0.0, 0.0, 42.192388642907076, 0.0, 0.0], [34.86511530121715, 0.0, 0.0, 34.86511530121715, 0.0, 0.0], [36.60816916825759, 0.0, 0.0, 36.60816916825759, 0.0, 0.0], [24.554726388943635, 0.0, 0.0, 24.554726388943635, 0.0, 0.0], [35.40437595295379, 0.0, 0.0, 35.40437595295379, 0.0, 0.0], [38.49892360028372, 0.0, 0.0, 38.49892360028372, 0.0, 0.0], [31.2177290366138, 0.0, 0.0, 31.2177290366138, 0.0, 0.0], [36.7238488543868, 0.0, 0.0, 36.7238488543868, 0.0, 0.0]], \"pathcoordinates\": \"display\", \"offsetcoordinates\": \"data\", \"zorder\": 1, \"xindex\": 0, \"alphas\": [null], \"facecolors\": [\"#E75A47\", \"#515EA9\", \"#8BD0A4\", \"#FB9F5A\", \"#515EA9\", \"#FEF1A7\", \"#5E4FA2\", \"#9E0142\", \"#FEF9B5\", \"#3389BC\"]}], \"xscale\": \"linear\", \"bbox\": [0.125, 0.099999999999999978, 0.77500000000000002, 0.80000000000000004]}], \"height\": 320.0, \"width\": 480.0, \"plugins\": [{\"type\": \"reset\"}, {\"enabled\": false, \"button\": true, \"type\": \"zoom\"}, {\"enabled\": false, \"button\": true, \"type\": \"boxzoom\"}], \"data\": {\"data11\": [[0.9296160928171479, 0.3163755545817859], [0.5677250290816866, 0.5955447029792516], [0.7489066375339118, 0.6535698708517353], [0.00838829794155349, 0.10644437669771933], [0.8098125525409348, 0.872175913724283], [0.6424753278958413, 0.7174536208124137], [0.43964460588480947, 0.7296890827468514], [0.7908225178477886, 0.1709142577924344], [0.9037225382170001, 0.024676210429265266], [0.5963660104193805, 0.05195754510253359]], \"data10\": [[0.5463660104193805, 0.10195754510253359], [0.5963660104193805, 0.05195754510253359]], \"data08\": [[0.7408225178477885, 0.2209142577924344], [0.7908225178477886, 0.1709142577924344]], \"data09\": [[0.8537225382170001, 0.07467621042926527], [0.9037225382170001, 0.024676210429265266]], \"data06\": [[0.5924753278958412, 0.7674536208124138], [0.6424753278958413, 0.7174536208124137]], \"data07\": [[0.3896446058848095, 0.7796890827468514], [0.43964460588480947, 0.7296890827468514]], \"data04\": [[-0.04161170205844651, 0.15644437669771932], [0.00838829794155349, 0.10644437669771933]], \"data05\": [[0.7598125525409347, 0.9221759137242831], [0.8098125525409348, 0.872175913724283]], \"data02\": [[0.5177250290816866, 0.6455447029792516], [0.5677250290816866, 0.5955447029792516]], \"data03\": [[0.6989066375339118, 0.7035698708517354], [0.7489066375339118, 0.6535698708517353]], \"data01\": [[0.8796160928171478, 0.3663755545817859], [0.9296160928171479, 0.3163755545817859]]}, \"id\": \"el3167547485356087440\"});\n",
" });\n",
" });\n",
"}else{\n",
" // require.js not available: dynamically load d3 & mpld3\n",
" mpld3_load_lib(\"https://mpld3.github.io/js/d3.v3.min.js\", function(){\n",
" mpld3_load_lib(\"https://mpld3.github.io/js/mpld3.v0.3git.js\", function(){\n",
" \n",
" mpld3.draw_figure(\"fig_el31675474853560874409921888964\", {\"axes\": [{\"xlim\": [-0.20000000000000001, 1.2000000000000002], \"yscale\": \"linear\", \"axesbg\": \"#FFFFFF\", \"texts\": [{\"v_baseline\": \"auto\", \"h_anchor\": \"end\", \"color\": \"#000000\", \"text\": \"point0\", \"coordinates\": \"data\", \"zorder\": 3, \"alpha\": 1, \"fontsize\": 10.0, \"position\": [0.87961609281714781, 0.36637555458178589], \"rotation\": -0.0, \"id\": \"el3167547485357725776\"}, {\"v_baseline\": \"auto\", \"h_anchor\": \"end\", \"color\": \"#000000\", \"text\": \"point1\", \"coordinates\": \"data\", \"zorder\": 3, \"alpha\": 1, \"fontsize\": 10.0, \"position\": [0.51772502908168661, 0.64554470297925159], \"rotation\": -0.0, \"id\": \"el3167547485357727504\"}, {\"v_baseline\": \"auto\", \"h_anchor\": \"end\", \"color\": \"#000000\", \"text\": \"point2\", \"coordinates\": \"data\", \"zorder\": 3, \"alpha\": 1, \"fontsize\": 10.0, \"position\": [0.6989066375339118, 0.70356987085173539], 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F+09LS6NZYAscbTvQyLGDVr4HEKj0DWnmNYTdUQuJiztKkyb/lRrWdLmqTp06975+9dVX\nCQsL09K4K463tzdfL/2K/5s7m23btnHg4EH27j1A3D9ruJ2Tg9DTw8TEFE9PT7q82JJmgcMJCQnB\nxMSksocu3UejxK8oiloI8QawGdAHvlYU5bgQYvjd1xcDM4HlQogj3FlaeltRFO1vFZAqTdEEp2uF\nhYX0eKEX6TdzsHHXzgeOAFk517hy/Qw21q6o9EzRw5yYmBgSEhJo2LChxstVFy5coG7dusCdD36b\nNm2qtbFXNEtLS7p370737t0reyhSOWm8rVJRlE3ApvueW1zk66tA1ZveSKXi5OREbGxshcVbtGgR\nqeeu4t24G5v3zCTIdwgN6gZo3G8NcztOJv3F3uilWFnWp33z8WzaM5VOnTphbGys0XLV2rVrmTZt\nGjExMQghcHZ2ZvHixQ/0VVRmZiZr167l7907iIo6zJWr1xAC6terR0BAM9p36Eh4eHixdxySVFri\nSdhpIIRQnoRxSE+2tLQ0PNy9CGk2ESuL+ly9kcCOAwtxdWyLj1v3cq/zZ2ZfYdv+/yO8/cxiz6dc\njObM+V9ISDyt9QS7a9cuzMzMCAgo/kcrMzOT6dPeY9nyZbQJ8uD59p4E+LlQ19YKRYGzKVc4FJ1I\n5MYjnEq4yJi3xjJm7DhUKnlrTHV099jMMr/llrV6pCpj0aIvcajbDCuLOzuGa9dsSJdnpnHxSjzb\nD8wnL1+Dw7pLWK5ysPNDDwsiIyPL3+9D3Lx5k06dOhX77GLPnj34+DThcloMMbs/4tdVb/Haq8/R\nPMAVB/vaNHCoTZtgD8aM7MKODe/w5y8T+POPHwgOas6pU6e0Pkbp6SVn/FKVkJ+fT726DgR5j6am\npX2x1woK1RyM+45LV48T0vwtaljU1VrcpPP7Uati2btP++WKjx49Svfu3QkLC6NDhw4MGfIKXy98\nlbBOpV+6UhSFL5Zu4cPZ69m8+S+8vb0ff5H01CjvjF8mfqlKWL9+PW+8PpmQgIdX5jx9dgfR8WsJ\n8nsVBzs/rcQtKFSzfsd4oqIP6GQ74o0bN+jatSsHDx4gcvU4OnUs37jX/LyXcVN/JDo6ttR3ICuK\nwtmzZzl8+DBxcXFk3MogLz8PIyNj6tS2wc/Pj4CAAGrVKtu9EVLFkUs90lNt167d1LJ49C6eRo4h\ntGvxFv8cWUHsyV9RlEKN4+rrqahbx4O9e/dq3FdJzM3Nyc7K4NmQJrw+dhnRR/47/nDYm19x/OT5\nR14fueEQx0+ep3fPYPq80Jw2rVvh4eGBj48PPXr0ID09vVj7wsJC/vrrL8J7dMe6tjUBLZrxYcSn\n7EmL4ZRygRSjm5zIT+WPY7t4a+oEHJ0dqd/AnhGvv/bAFlup6pIzfqlKaBX8DMZKM+xtfR7bNjvn\nBjsPLsTYqAat/f+HgYFm+8iPndlAy2ds+DxioUb9lOTLRYv4ee1X/LluImvX7Wfk+GUs+HQQfV9s\nVarrB732BWGhAfTs1oKcnDwa+o7hu+9/pH379kyaNAmAWbNmkZuby6JFi1gQsZBCFQS++AxeIf5Y\n2tR8ZP+FhYVcPXuRI5v2c3DdLtzcGvP22Al069atQrfxSiWTSz3SU61GjZo8H/QBJsZWpWpfUJDP\ngbiVXL5+mnbNR2Npblfu2GmXj3IzfxcHD+4rdx9wp4R1aGgogYGBREVF4eXlRfyxWAb3a8aqtXtQ\nFxTS0LkOMbFn6RnenIPRifzfzFfw93XGvN5A3nqtM79vjsLE2JDI1eM5k3iRsN6fUcPSlBqWpvy8\ncgyb/jrCzv03+HHtL6xbt46ff/6Zt956i/6vDMC4jgVtBnfGybdRuZK2Ol/N0W2H2LFkPT4eTVm6\neAl2duX/uUqak0s90lNLURRu3UrHyMiy1Nfo6xsQ5DsED5eO/LF7BqmXjpQ7vrGRJTdvaKe2TtES\n1mq1mgsXLrBg8R/8uOItYvd+iqWFKcMGtSf22Dnijp3jZkYWANnZeQQ1b0TM35/QNtidJSu2EdzC\njfDOAcz+cADRf8/CxdmWl3u3ZtMfm8nMzGTp0qVkZGTQsdNzBL7SgZfnj8bZr3G5Z+oqAxW+z7fk\njVXTyK2jj5d3E1avXq2Vn4tUsWTil554/74bFJQ9YTV2as8zzUcRf2YThYUF5YqvJ/TJV2vnAJei\nJaxdXFwwMtTHxakOrg3vzJwH9m3L4egkNv40CXMzY14eFsGRuLMYGqro8rw/AAG+LiSf++8UsqLv\nli0tTfFwa8CoUaM4dPgwiddTGLVmBv6dg7W2NKMyNCD0zV4MmDeKMZPG8+HMj6pU5VFJHr0oVQF6\nenro6+lTWKhGX7/sN1LZ1nKjY/DEcie+gsI8jI2My3Xt/YqOITHxDDa1LSiaM/9NoCqVPg1dbOnY\nrinPdvuw2G0GenoCdcF/f8Tu/75MjPVZvXo1nm396D1zOPoGuvk1b9CkIcOXTWbxa7PJz89n+vvT\ndBJH0j4545eqhLp17cnIulTu6zWZ7WZkXsLZ2bnc1xdVtIT1sWPHaNTQjuRzV0hIvAjAyjW7CWnj\nea99aAdftvz6Lrm5ar7/8e8H+rMwNyHjVva9x3/8FcOx+LPUqGtN749H6Czp/8vSpiZDF7/NV8uX\n8sWiL3QaS9IemfilKiEgIIDrN5Me31AHbmaepVWrFlrp698S1p6enqjVBTzTyoPlESPoNXAe3sFv\no9LXZ8SQZ4td4+vthJmZEeF3b+wqVhOoZxCfLfidgLaTSUy6xJsTVpCbpyYnM5v5/d7j54+Wa2Xc\nj2JRqwYDF47hnXff5eTJkzqPJ2lO7uqRqoTPPvuMb5duxd+jf4XH3hU9m0WLPyE0NFSjfpKTkwkL\nCyMuLg6A2bNnk5KwnfmfaPcIwrZdZ9DopVA82/pxOSmNOs71tNr/w/z9/WbO7zrJvr/3oq+vXyEx\nqzu5q0d6qnXp0oWUi4coLKzY45qzcq5z9XoyrVqVbl/94xRdcgoICOBAVLJW+v1XQUEhsXFnsfd0\n5ta1dL4cNpPtK36vkA9fg/t2JKMgm/kL5us8lqQZmfilKsHT0xN3dzfOXXjwcBddSkzdSb++/bCw\neOC00DK7v4R1UFAQCUkXOZNwUeO+//XHXzHUsrfBsrYVFrVqMOq76Rz58x++nxRBbvZtrcUpiZ6e\nHl0n9ueTTz8lP187u6Ak3ZCJX6oyxo4bTVLa1nLPXvfGfM3NW48ugXDuwuF7bfLVuZxM2sLWbVvQ\n19cv8UQxTRgbGzN40GAWLP5TK/0pisJnX2yi2Usd7z1nZVeLkcumom+gImLQB1xLvayVWA9Tt5ED\n1g42OqloKmmPTPxSldGjRw+srI1IOLezXNcH+w69V9L5YVIuHCb9VhoAR8/8TNu2bdm4cSNt27Yt\nV8zHGTN2PGvW/cOhqASN+1r9814SUq/j1ymo2PMGxob0mTGcZt3a8vkr0zn9z1GNYz1K4IshzFso\nl3ueZHIfv1RlqFQqVv/wHUFBrbGzaQIo/LVvNrWsnLl+Mxkry/q08h/OleunOXzsBwqVQmpbOdPC\nZxD6eio2/z2TwCb9qGXlxKrfh+HR8HlSL8agr29AuxZjuJV1iZSL0Vy6dpKo+B9RGajZsfcU1tbW\n5RpvTk4OWVlZKIqCqakpZmZmD7Sxs7Pj/+bO5+Xh77Bn83tYW5uXK9bphAu8OfEbBswfh8rwwXsd\nhBC06R9K3UYN+H5yBCEDu9D25U46qbfTpEMgkR9/W+y4SenJImf8UpXi5eXF5MkT2R+7iPz822Rk\nXsTduQPdOszCQGVC/JlN7IleQtvANwhv9xGFSgGnkrbeubhIklMX5GFT05Wwdh9iW8ud08k7qGPd\nCAc7f7xcu6AyUPh25YoyJf0LFy4wZ84cwrv1xN7eiRo1rHBydsXZpRE1a9bCzq4+nTuH8/HHH5Oc\nnHzvur79+hEW/iIdX/iES5fLXhoi/kQqrUOn02FkLxo0eXTpaNfmnry5cjpRG/aw+p1F5OXkljne\n46gMVDg1bcShQ4e03rekHTLxS1XOpEkTCe38DAfjl2NqXBMb60YAuNgHc/FqPBamdbA0twWgoUMb\nLl17cG+5np4KeztfAGpZOZGZc6cEQr76NscSI5n63mS6du1aqvHs2bOH8G49cG3kxuJlf3Dhel08\nAkfRtc83PN/zK57v+RVd+67AJ/htrmY6882q3TRt6kvHjp34888/EULwyaez6da9Hz6t3mHtuv2l\n+hyjoKCQeV9sonn7KXh1aU2LHu1KNV7rerUZueI9FCBi0AdcT7taquvKwtbNnoMy8T+xZOKXqhwh\nBEuWLiakfXNu56VzPf0cAApgaGB696t/lZxA9cR/+8yFECiFhZy/HMvFq7H06tWDMWPeeuw4MjIy\nGDhwCF3DepJyqSYdwhfQtNkwGjRsi6WVPULvv18vIfQwt6yLg0srvAIG0b7bQq5nO9F/wKt07/4i\nV69e5b33p/Fr5AamfbqRgGemsmTFVlJSrxb7I1BYWMipM2nMXvA7jQPGs27jaQoVQbvBpfsj9S9D\nEyP6zXwNv86tWDjgfc4ciC/T9Y9T38OJfQf2a7VPSXvkGr9UJenp6TFz5oesWbOabQc+wd2pI+mZ\nV6hl5cyp5O3cyrqEhZktiSl7sK396ANc1Opcrt48TXZ+Ip06h9K2besS2xVNwHv37qVHz5eoYe1J\nm9BZGBialmn8KpURTo3a4eDcilNHf8Ld3Yvvv/+W0NBQ4uKO8+eff7J0yZdMnTmNwsIC6tpaU1io\nkHL+MlZWNWgX0o5Vq3/B1dUVRxcnTGuU/bMBIQQhAztTz60B30+KoP3QMFr3e14r6/7W9W34J3WL\nxv1IuiETv1RlCSFwc3PD09OTzZs3k5ubj5drKP6evdl58PO7H+664ObUvoRr4WbGeRLP7+B08i4a\nODpw6NBBjh49yrBhw1i4cCFr167lyJEjjBo1iqtXr9KlSxf8/PwYN24cPXq+RJPAYdR1KP35uCXR\nVxni4dsPm7p+9O4zgK8WR9C7d29CQ0MJDQ1FURQuXLjAlStXEEJQr149ateufe/6tLQ0jIyNNBpD\n45ZNeOPb91kxZh6px5Pp/cH/0NPTbDHAwNiQ27dzNOpD0h1ZskGqsu4vgXDs2DEWzP+cVatXYWVh\ni6V5AyxNHTAxskJPT0VBYT6Z2VfIup3K9Yyz5KuzGTH8f4x4bTgODg6lirlr1y66du2OX6vR1Lb1\n0Or3k379LAd3fcKq77+hS5cupbrmwoULePk04d2/FmgcPzf7Nsd2ROHfOVjjvi4lnufniV+RcPKM\nxn1JD1fekg1yxi9VaUWXJby8vFj81SLmzZ9LTEwMhw8fZt/eA1y8GE9uXh7GZsb4NG1AUNArBAQE\n4OXlhYFB6cs8p6enExbenQJFhYmp9g8gr2HtiF/wW/Qf8ArH44+WaiukiYkJt7V0R66RqbFWkj5A\n/u08jI01O/JS0h0545ekUho0aCh7D5zD1MKeE7HraNbmDerU89Z6nJOxa7Gvk82mTb8/dr1dURSs\na1vz5poZ1Kjz6PNzK1LUhj1kHkwj8pdfK3soTzVZpE2SdOjvv//mt/UbcfftT0OPTjR/ZjQH/47g\n9LH1Wi+A1sjrBaKPnGDdunWPbSuEwMfPl9T4yilZ/TBpx8/Sspl2SllL2icTvySVwiefzsGpcZd7\nu3ds7Lxo1/lDziX+zaHdC1GrtXcjlJ6+Cmf37syaNbtU7Vs2a8H548lai68Nl06k0KxZs8oehvQQ\nMvFL0mOkpaWxfds27J2Lb/M0NbchpNMMEHrs3PQe2ZlXHtJD2dV1CODU6TMcPfr4ujrBQcGcO3xa\na7E1dTsrh5STSQQEaLbjSdIdjRO/ECJUCHFCCHFaCDHxIW1ChBDRQoijQogdmsaUpIq0atUq6ju2\nKHGvvr7KkMDWI2ng0pbtG6dw5YJ2CqDp6amo79SWr79+/AlaoaGhXD13kUuJj648WlGiNuyhfYcO\n1Kz55HzmIBWnUeIXQugDnwOhgCfQVwjhcV8bKyACCFMUpQnwoiYxJami7dy1B8tabg99XQhBI68u\nNGvzBgd2LeBM/EatrPvXtHHn77/3PbadoaEhw14dxoG12zWOqSlFUTi0diej3xhV2UORHkHTGX9z\n4IyiKMmDhgjrAAAgAElEQVSKouQDPwDd7mvTD/hZUZRUAEVRtF8YRJJ0KOpwFDVruTy2XZ26TQnp\n/CFnz+zg8J4vKFDnaRS3Zi0XjsXHUlhY+Ni2rw0fQfTGfeRkZGkUU1NnDsSjUvRo1650dYOkyqFp\n4q8PpBR5nHr3uaIaAdZCiO1CiENCiJc1jClJFSYrK4srVy5hblm68sJmFnV4ptMHFBbks/OP98nO\nKv88x9DIHGNjc86ePfvYtg4ODvTp04eNc38odzxN5d/OY/2s7/hk5iydlHuWtEfTG7hK837WAPAH\nOgCmwD4hxH5FUYp9GjVt2rR7X4eEhBASEqLh0CRJc5mZmRgbmyJE6edIKgNjmrUdzelj69mxYQrN\n246itp1nueIbGZmRmZlZqrZzPpuNh5cnx3fH4NHGt1zxNLFl0Tqa+wXy4otyNVdXduzYwY4dOzTu\nR9PEfx4oeq+7A3dm/UWlAFcVRckBcoQQuwAf4KGJX5KeFIqiFKvjX1pCCBo3CadGTUdyc2+VfwBC\nlGqpB8Dc3Jxvlq+g94C+NFjdELOamp8TXFqJUSc4snEfx49qt8qnVNz9k+Lp06eXqx9Nl3oOAY2E\nEE5CCEOgN/DbfW0igdZCCH0hhCnQApD/O6QqwczMjNzc7HJ/WGtb34f6juW/kSkvN7vEk7sepn37\n9rw6aAgr3pjL7czscsctiwunU1g14Qu++2YlNjY2FRJT0oxGiV9RFDXwBrCZO8l8jaIox4UQw4UQ\nw++2OQH8AcQC/wBLFEWRiV+qEiwsLKhhWZPsTN0eUl6S/LxssjJv4uTkVKbrZn40k46t27P89Tlk\np5dumai8zh9PZtlrs/liweeEhobqNJakPbJWjyQ9xnPPdyE9tzH2TkGPb6xFVy7Gk37xd47ElP0k\nK0VRGDd+PGt+XcuLM1597JGM5ek/asMeNs1dw9LFS+jZs6dW+5dKR1bnlCQdadMmiO/X7KvwxH/j\n6klaB5VvmUgIwZzZs2kWGMgbo9/Ev1trnh3evcSD2Msq48oNImeuJPfSLbb++Rf+/v4a9ylVLFmy\nQZIeo1/fvpw/u1fjfflloSiFpCXvYtCgV8rdhxCCvn37Eh93DOMrhSzs/R771m4lt5xlnG9eusaf\nX/zCwj7v0yW4I0eiYmTSr6LkUo8klUJIu45kqhvj2PCZCol38XwMN9I2cOxojFb2xCuKwrZt25j3\n+QJ27diJb+cg3Nr4YO/phJlVybt/FEXhRtpVUuKTOPbHAc4ciqdfv/6MfnMU7u6PPs5SqhjlXeqR\niV+SSmHjxo0MHPwarZ77CH19Q53GUpRCDmz/kA8/GM+gQYO03n9qaipLli7hz61/EXckFrMa5tRv\n7IiRuQn6Bvqo89RkXc/gXHwiRoZG+Pr78UJYN15++WXMzct+tq+kOzLxS5IOKYpC167dSE5T4e7T\nR6exEk9swkA5yf59f2t89u3jFBYWcubMGeLi4sjMzCQvLw9jY2Osra3x9/cv1SlgUuWRiV+SdOzS\npUu4u3vhEzSaWnUeXrRNExk3U/ln2wyiog7i6uqqkxjS00OewCVJOmZra8vKlSuI3jOPjBspj7+g\njLIzr3J492fMmzdHJn1Jp2Til6Qy6Nq1KxERCziw82OuXzmjtX5vpZ/nn+0zmDplIkOGDNFav5JU\nErnUI0nlEBkZycCBQ3Bo+CyuXt3Q0yvfLTGKUkjSyc0kxP/K/PlzGTx4sJZHKj3N5Bq/JFWw8+fP\n88orgzl2PAln9+7Y2fujp6dfqmsVpZDLaXEknYyknp0Fq77/lkaNGul4xNLTRiZ+SaoEiqKwdu1a\nPp41m+Tks9RzegZrG3esajljaFi8uJo6/zY3rydx/copLpzbRe1aVrw9YQyDBg3S+e4d6ekkE78k\nVbKYmBi+XraCPXv2cfz4UUxNLTE0MkMgyMvLIfPWdRo1dicoqAWDB71Cy5Yt5YElkkZk4pekJ0hB\nQQHJycncunULRVEwMzPD2dkZAwPNa+VI0r9k4pckSapm5D5+SZIkqVRk4pckSapmZOKXJEmqZmTi\nlyRJqmZk4pckSapmZOKXJEmqZmTilyRJqmZk4pckSapmZOKXJEmqZmTilyRJqmZk4pckSapmZOKX\nJEmqZmTilyRJqmZk4pckSapmZOKXJEmqZjRO/EKIUCHECSHEaSHExEe0ayaEUAshemgaU5IkSSo/\njRK/EEIf+BwIBTyBvkIIj4e0+wT4A5BnzUmSJFUiTWf8zYEziqIkK4qSD/wAdCuh3ZvAT8AVDeNJ\nkvQEGjZsGMePH39km8jIyGJtrl+/TseOHWncuDHPPfccN2/e1PUwpbs0Tfz1gZQij1PvPnePEKI+\nd/4YLLr7lDxjUZKeMkuWLMHD44E3+8WsW7eO+Pj4e49nzZpFx44dOXXqFB06dGDWrFm6HqZ0l6aJ\nvzRJfB4w6e6hugK51CNJT7zk5GTc3d0ZMGAAnp6e9OrVi5ycHLZu3Yq/vz/e3t4MHTqUvLw8AEJC\nQoiKigLA3NycKVOm4OvrS1BQEJcvX2bv3r2sX7+eCRMm4O/vT2JiIr/99hsDBw4EYODAgfz666+V\n9v1WNyoNrz8POBR57MCdWX9RAcAPQgiA2kAnIUS+oii/FW00bdq0e1+HhIQQEhKi4dAkSdLEqVOn\nWL58OUFBQQwdOpQ5c+bw1VdfsW3bNlxdXRk4cCCLFi1i9OjR3P39BiA7O5ugoCA+/PBDJk6cyJIl\nS3j33XcJDw8nLCyMHj3u7O+4dOkStra2ANja2nLp0qVK+T6rkh07drBjxw6N+9E08R8CGgkhnIA0\noDfQt2gDRVFc/v1aCLEcWH9/0ofiiV+SpMrn4OBAUFAQAAMGDGDGjBm4uLjg6uoK3JmlR0REMHr0\n6GLXGRoa0qVLFwACAgLYsmXLvdfuvPF/kBCi2B8PqWT3T4qnT59ern40WupRFEUNvAFsBuKBNYqi\nHBdCDBdCDNekb0mSKlfRRKwoClZWVsUS98OSuIGBwb2v9fT0UKvVJfZpa2vLxYsXAbhw4QJ16tTR\n2tilR9N4H7+iKJsURXFTFMVVUZSP7z63WFGUxSW0Hawoyi+axpQkSffOnTvH/v37AVi1ahWBgYEk\nJyeTkJAAwMqVK8u0JGthYUFGRsa9x+Hh4XzzzTcAfPPNN3Tv3l17g5ceSd65K0lSidzc3IiIiMDT\n05P09HTGjh3L8uXL6dWrF97e3qhUKkaMGPHAdUVn9UWXcPr06cNnn31GQEAASUlJTJo0iS1bttC4\ncWO2bdvGpEmTKux7q+7Ew96uVegghFCehHFIknRHcnIyYWFhxMXFVVjM5cuX07NnTywtLSssZlUn\nhEBRlDJ/OKLph7uSJD2lKvLD1sLCQg4cOMCnn35KZGQkjRs3LrFddnY2a9eu5VhcHBk3rmNmYYmz\nqyt9+/alVq1aFTbeqk7O+CVJemL8u/Vz+fLl93YGASQkJPD5vHms/PYb/Gtb0czCGHMDFdnqAo5n\n57H1/GXCw8N5c+w4AgMDK/E7qFjlnfHLxC9J0hNl79699OrVi9dee4133nmH9evXM/SVl+nnZMcA\n57o4mps+cM2123n8kJTGkoQ0xk6ezPi3J1aL7aEy8UuS9NRIS0ujZ8+eACTEH2NlcBN8a9V47HXn\ns3Lov/cY/Ue+wZT33tf1MCudTPySJD1VYmNjaR4YiK2RijXtA3G2MCvVdZdybtN1ewwR33xLWFiY\njkdZuWTilyTpqTLi1aFYHPobG0MVn8aeYWFwU9rXsynVtZtSLrEkE/YcjtLxKCuXTPySJD010tPT\ncbavz47nmmFrYsz+y9cZ/vcRXnVz5A1P58eu36sLC2mx6R827NiJj49PBY264pU38csbuCRJeuJ8\n9913tKlrg62JMQAt61izKTSIDSmXGP73EbKKlIEoiUpPj/7Odnwxf15FDLfKkYlfkqQnTuyhQwRb\nFd+9U8/UmF87NsdEpU/Xzfs5eyv7kX20qm1FbHS0LodZZcnEL0nSE+fm9WtYGjx4f6mxvj7zWjZh\ngKsDXf/cz5Wc3If2YWmoIj09XZfDrLLknbuSJD1xTM3NuX2psMTXhBAMdXPk2Xo22JgYPbSPHHUB\npiYmuhpilSZn/JIkPXEcnF04lXX7kW0cLR68kauo0xlZ2Ds00Oawnhoy8UuS9MR5eeBAfjp7kdsF\nBeXu47uUqwwqoXqoJBO/JElPoEaNGuHn58fv58p3HOPR6xlcyCuga9euWh7Z00EmfkmSnkijJrzN\n/NPnycjLL9N1BYUKs46fY8Sbb6BSyY8xSyJv4JIk6YmkKApvjBhO7B+/801LL8xK2OVzv4JChYnR\np0irXY9NW7dhaGhYASOtPPIGLkmSnipCCBZ8sQi3dh15YdcRDl258dBzfgHOZGQyZP8xUq3t+OX3\nDU990teEnPFLkvREUxSFLxctYvbHMzEryGdgAxua2dTE0kBFllrN8ZuZrEy5yvH0TIaPeI2p06ZV\nm6Qva/VIkvRUKywsZMuWLXw5fx7xx46RkZWFmYkJjg0aMHTkG/Ts2RMjo4fv638aycQvSdXQsGHD\nGDt2LB4eHg9t8+9Rhv+26dOnDydPngTg5s2bWFlZEV2K0gYFBQUkJCRw48YN8vPzMTIyws7ODnt7\n+2px6MmTSCZ+SZJKNGjQIMLCwu4dbFLU+PHjsbKyYsqUKQ+8pigKBw8eZNW3K9m3aw9HTx3HUmWC\npcoYfQRqCrmWl4WiL/Bt4k3rZ0MYNHgwLi4uFfFtScjEL0lPheTkZEJDQwkMDCQqKgovLy++/fZb\n9u7dy4QJE1Cr1TRr1oxFixZhaGhISEgIc+fOxd/fH3Nzc9566y1+//13TExMiIyM5MyZM4SFhVGj\nRg1q1KjBzz//fC8xK4qCo6Mj27dvp2HDhvfGkJeXx3fffcf8T2Zz5fxFWt62xqXAAkcsMBcGxcar\nKAo3ySOZDE4ZZrJf7zLNmjXjrYnj6dy5s3wnoGNyV48kPSVOnTrFyJEjiY+Px9LSkjlz5jB48GB+\n/PFHYmNjUavVLFq0CKBYYs3OziYoKIiYmBjatm3LkiVLCA4OJjw8nNmzZxMdHV1sNr57925sbW2L\nJf2oqCh8PZowf9RU2p8yYEaWL2GFjngJ6weS/r/xawoj/IQNvfOd+eR2IA12X2Jk70F0at+R8+fP\n6/AnJZWXTPyS9IRxcHAgKCgIgAEDBrBt2zZcXFxwdXUFYODAgezateuB6wwNDenSpQsAAQEBJCcn\n33utpHfUq1evpl+/fsCd9ft3J03m2dbP0CrJgNFZbniL2uiVccZuKPRpLeryblYTTPacxdvdk5Ur\nV5apD0n35G1tkvSEKTqLVxQFKysrrl27Vuy5khgY/Dcj19PTQ13ksJL7l1zUajXr1q0jKiqK3Nxc\ner/wIgk7DzElx4eawgg0XKFRCT3C1Q3wza/JpBGjSTx9hvemT5NLP08IOeOXpCfMuXPn2L9/PwCr\nVq0iMDCQ5ORkEhISAFi5ciUhISGl7s/CwoKMjIxiz/311194eHhQp04dXuz2Amk7Y3gz2/1O0tei\nBsKCCdmeLJ8bwQfvT9Nq31L5ycQvSU8YNzc3IiIi8PT0JD09nbFjx7J8+XJ69eqFt7c3KpWKESVU\nnSw6mxZC3Hvcp08fPvvsMwICAkhKSgJgzZo19O3bl7FvjiZ19xGGZbtiIHSTDmoII97KcuerOQv5\n7rvvdBJDKhu5q0eSniDJycmEhYURFxen81g7d+7kxU7hvJPTlL+5wPM00FnyBzir3GKh+UniTh6n\nXr16OotTnVTarh4hRKgQ4oQQ4rQQYmIJr/cXQhwRQsQKIfYIIbw1jSlJT7OKWAfPyspiYJ/+9Mtx\nwgQVZ7nFJ0RxQ3n4UYaachQWtMmtw9ABAx9Zc0fSPY0SvxBCH/gcCAU8gb5CiPtvIUwE2iqK4g3M\nAL7SJKYkPc2cnJyIjY3VeZw5n82mfroevqI2RkKf12mCD7WZwUHOKLo7p7ZLvj3xB6LZvHmzzmJI\nj6fRUo8QIgh4X1GU0LuPJwEoijLrIe1rAnGKotjf97xc6pGkCqJWq7GvU5fXbjjTQFgUe+2IcpVl\nHOcFXAgR9XUSf5eSxsV29mzatkUn/VcnlbXUUx9IKfI49e5zDzMU2KhhzMcaNmwYx48ff2SbyMjI\nYm2mTp2Kj48Pvr6+dOjQgZSUlEdcLUlV1/r167FWGzyQ9AF8RG0mE8AWUvhWOYFaKfnAc020wJa9\n+/YWu89Aqliazvh7AqGKogy7+3gA0EJRlDdLaNsOiABaKYpy477XlPfff//e45CQkDJtVyuP++uX\n3Lp1CwuLO78ICxcu5MiRIyxdulSnY5CkytC5fUfqbz9PsKj70DY5ipqlxHOLfF6nCVZa3ub5g0ES\nrd8ZxNT339Nqv0+7HTt2sGPHjnuPp0+fXvG1eoQQLYFpRZZ6JgOFiqJ8cl87b+AX7vyROFNCP49c\n6qnI+iUAH3/8Menp6cyaVeKKVTGKopCUlMT169dRq9UYGRnh4uJCjRo1SvlTlKSKoygKNjWsmXzL\nE2th/Mi2hYrC7ySzkzRepwkNhfb+Tx9WLnO6rQ2bd27TWp/VUWUt9RwCGgkhnIQQhkBv4Lf7BtaA\nO0l/QElJv7Qqon7Ju+++S4MGDfjmm2+YNGnSQ8eSnJzM1Cnv0r51S2rWsOCZoECG9+vOqMEvMbBn\nF+rXtaWRkwN9enZn9erV5ObqbqeEJJXF+fPnKchXU5PHz+D1hCBcODOAxiwgll1KmtbG4YgF0Udi\ntNafVDYaJX5FUdTAG8BmIB5YoyjKcSHEcCHE8LvN3gNqAouEENFCiAPliVUR9Us++ugjzp07x6BB\ngxgzZswDfe3evZuw0I4E+jYl/fBvjGthyvGPQkn6tDP/vBvC3kltiXq/PdcievDT/3x4tuYlln7y\nDo72dXln8kRu3LjxQJ+SVJGioqJwMaxZpi2jfsKGSfjzB+dYqZzUyrp/LYzJz80jLU17f0yk0tN4\nH7+iKJsURXFTFMVVUZSP7z63WFGUxXe/flVRlFqKovjd/de8PHFKql9SNHFro37Jv/r168fBgwfv\nPc7MzOT1Ef+jb89wwurdIvHTLszt48Pz3vWwsXzw7bK+nh5e9a0Y1KYhm8e04q+xrbj0z2809XBj\nw4YNpf+mJUnLLl++TA112Ut01RVmTCGQ69zmM6JJV/I0GocQAmtDM65cuaJRP1L5VJmSDbquX3L6\n9Ol7X0dGRuLn5wdAXFwc3p7uZJ3YTfS0ZxnyjCumRmX7xXGvV4PFAwNYMcibN4e9wv+GDi72B0iS\nKkpubi765ZywmwoVb+KNOzWZTTSFGm7BVgl9bt++rVEfUvlUmcSvy/oliYmJTJ48maZNm+Lr68uO\nHTuYM2cOhw4d4tl2bfmgixNfDw6gpplmOxtCPOyIev9ZUqJ30OuFcPLz8zXqT5LKysDAgEINfuv1\nhOAF4cIE/Mpcsvl+BRRWm0PRnzRVolZPRdYv+deJEydoE9yCr17xI8zP/vEXlEGeuoCXFv2DlWsg\nK1evkaVqpQqzdu1aZr86nhG3XCt7KEw0OcyBYzE4OTlV9lCqrKf+BK6KTI5qtZpePbpxOzubnDzt\nL8kYqvRZPbw5cQd3s2LFcq33L0kP4+vry9mCjMc31LEMJY9cRY2jo2NlD6VaqhKJv6Lql/zrk1kf\nY2eYy7Z3OvLu2hgm/xhNQaF272A0MVTx9UA/3h43Rh5PJ1WYhg0bklWQR4aGH85qKplb+Hg1le92\nK0mVSPwVKTU1lbmzP2XxK374OVqz7/1QDiddI2zuDq5nanc/vq+jNSNCXJgwZpRW+5XKrjxlPo4c\nOUJQUBDe3t6Eh4dz69YtXQ9TY3p6evg1aUoCuivEVhoJ+rdo2bZVpY6hOqsSa/wVaeqUd7lxKJJ5\nfX3vPacuKGTyj9Gsj05l7ZttaepQU2vx0rPzcJ24kfiTp6lb9+G30EuV7/4yH82aNWPu3Lm0adOG\n5cuXk5SUxAcffPDQ62/fvk1sbCyHDx8m/sRJMrOy0dMT1LCwwNfHm4CAANzd3dHX19fp9/H111/z\n5VvTeT2rkU7jPEyBUshk0yj+2rsLHx+fShnD06K8a/wy8ReRl5eHo31dNr8VjGf9B29PX7U3iXGr\nD/P5K83p2ayB1uK+vjIa+za9eE8eTac1uizzYWVlxU8//YS/vz83b94EICUlhdDQUI4dO1ZsHAUF\nBWzcuJHZ8xayb89uatg1wKiuK1jbo2doDIpC4e0suHaWrNRT3M64Tni37owd/SbNmzfXyVJIdnY2\n9WxseTe7KbWFidb7f5zDyhUOeqv450hUhcd+2jz1H+5WhG3btuFsY15i0gfoF+zMhnHtmfhDFFN/\nitHauv+Q1g1Y9e0KrfQl/UdXZT6ioqJwcXHBy8uLyMhI4M5umaIVXRVF4etly6jn4MjQMe9wrrYf\nTab8jOPri7B7YRx2z/SmTlA36gR3x65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"text": [
"<matplotlib.figure.Figure at 0x2b300bc81890>"
]
}
],
"prompt_number": 4
}
],
"metadata": {}
}
]
}
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