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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/Applications/anaconda2/envs/py3/lib/python3.6/site-packages/h5py/__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.\n",
" from ._conv import register_converters as _register_converters\n"
]
}
],
"source": [
"import numpy as np\n",
"import pandas as pd\n",
"import xarray as xr\n",
"import os\n",
"\n",
"from sklearn.ensemble import RandomForestRegressor\n",
"from sklearn.metrics import mean_squared_error as mse\n",
"from sklearn.model_selection import cross_val_predict\n",
"import scipy.spatial as spatial\n",
"\n",
"from pvlib.solarposition import get_solarposition\n",
"\n",
"import util\n",
"import matplotlib\n",
"%matplotlib notebook\n",
"import matplotlib.pyplot as plt"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Load rooftop data and merge with shading data"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"# load rooftop information (SONNENDACH data)\n",
"roof_select = '/Users/alinawalch/Documents/EPFL/data/rooftops/GVA_select_area8_buf30.txt'\n",
"roof_select = pd.read_csv(roof_select, index_col = 0)\n",
"roof_select = roof_select.loc[:,['DF_UID','FLAECHE','NEIGUNG','AUSRICHTUN','BUF30_Perc','XCOORD','YCOORD', 'SHAPE_Leng','GWR_EGID']]\n",
"roof_select.loc[roof_select.NEIGUNG == 0, 'AUSRICHTUN'] = 0"
]
},
{
"cell_type": "code",
"execution_count": 78,
"metadata": {
"scrolled": false
},
"outputs": [
{
"data": {
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" <th>NEIGUNG</th>\n",
" <th>AUSRICHTUN</th>\n",
" <th>BUF30_Perc</th>\n",
" <th>XCOORD</th>\n",
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" <td>46.507495</td>\n",
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" <td>39</td>\n",
" <td>0.245521</td>\n",
" <td>493478.741922</td>\n",
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" <td>31.477187</td>\n",
" <td>1020549</td>\n",
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" <td>65.822671</td>\n",
" <td>28</td>\n",
" <td>-141</td>\n",
" <td>0.182859</td>\n",
" <td>493481.191087</td>\n",
" <td>122047.635869</td>\n",
" <td>35.355795</td>\n",
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" <td>33.159751</td>\n",
" <td>41</td>\n",
" <td>-51</td>\n",
" <td>0.315406</td>\n",
" <td>493484.502179</td>\n",
" <td>122038.094141</td>\n",
" <td>26.367892</td>\n",
" <td>1020549</td>\n",
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" <th>4</th>\n",
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" <td>35.956510</td>\n",
" <td>11</td>\n",
" <td>-51</td>\n",
" <td>0.224638</td>\n",
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" <td>1020549</td>\n",
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" <td>20.596973</td>\n",
" <td>1020549</td>\n",
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" <td>26.304688</td>\n",
" <td>19</td>\n",
" <td>-143</td>\n",
" <td>0.252403</td>\n",
" <td>493463.360632</td>\n",
" <td>122094.162534</td>\n",
" <td>20.943016</td>\n",
" <td>2041392</td>\n",
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" <th>7</th>\n",
" <td>4879568</td>\n",
" <td>25.396184</td>\n",
" <td>20</td>\n",
" <td>37</td>\n",
" <td>0.259015</td>\n",
" <td>493461.198117</td>\n",
" <td>122091.312567</td>\n",
" <td>20.661054</td>\n",
" <td>2041392</td>\n",
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" <td>4879569</td>\n",
" <td>45.485566</td>\n",
" <td>8</td>\n",
" <td>-149</td>\n",
" <td>0.179873</td>\n",
" <td>493496.634242</td>\n",
" <td>122082.025889</td>\n",
" <td>26.983629</td>\n",
" <td>0</td>\n",
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" <td>41.481273</td>\n",
" <td>23</td>\n",
" <td>35</td>\n",
" <td>0.256334</td>\n",
" <td>493511.024937</td>\n",
" <td>122043.228215</td>\n",
" <td>32.570624</td>\n",
" <td>0</td>\n",
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" <td>4879571</td>\n",
" <td>37.316007</td>\n",
" <td>26</td>\n",
" <td>-145</td>\n",
" <td>0.285250</td>\n",
" <td>493512.562465</td>\n",
" <td>122045.403184</td>\n",
" <td>31.889598</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>4879572</td>\n",
" <td>14.442069</td>\n",
" <td>33</td>\n",
" <td>-142</td>\n",
" <td>0.353366</td>\n",
" <td>493519.594076</td>\n",
" <td>122010.886479</td>\n",
" <td>14.335675</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>4879573</td>\n",
" <td>20.230417</td>\n",
" <td>29</td>\n",
" <td>38</td>\n",
" <td>0.284888</td>\n",
" <td>493517.520013</td>\n",
" <td>122008.193580</td>\n",
" <td>16.881133</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>4879576</td>\n",
" <td>56.425414</td>\n",
" <td>37</td>\n",
" <td>-131</td>\n",
" <td>0.188028</td>\n",
" <td>493858.430044</td>\n",
" <td>122063.995365</td>\n",
" <td>28.247269</td>\n",
" <td>1020551</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>4879577</td>\n",
" <td>56.416744</td>\n",
" <td>37</td>\n",
" <td>49</td>\n",
" <td>0.188055</td>\n",
" <td>493854.908406</td>\n",
" <td>122060.966845</td>\n",
" <td>28.245385</td>\n",
" <td>1020551</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>4879578</td>\n",
" <td>21.678637</td>\n",
" <td>17</td>\n",
" <td>-64</td>\n",
" <td>0.263868</td>\n",
" <td>493861.601489</td>\n",
" <td>122073.440568</td>\n",
" <td>18.272307</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>4879579</td>\n",
" <td>27.094867</td>\n",
" <td>13</td>\n",
" <td>116</td>\n",
" <td>0.233973</td>\n",
" <td>493857.253150</td>\n",
" <td>122075.561250</td>\n",
" <td>20.571758</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td>4879581</td>\n",
" <td>27.303228</td>\n",
" <td>10</td>\n",
" <td>48</td>\n",
" <td>0.243404</td>\n",
" <td>494048.490791</td>\n",
" <td>122127.974434</td>\n",
" <td>21.815644</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>4879582</td>\n",
" <td>39.881046</td>\n",
" <td>8</td>\n",
" <td>48</td>\n",
" <td>0.192826</td>\n",
" <td>494052.921911</td>\n",
" <td>122122.292509</td>\n",
" <td>25.390413</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td>4879583</td>\n",
" <td>16.287173</td>\n",
" <td>31</td>\n",
" <td>139</td>\n",
" <td>0.351170</td>\n",
" <td>494031.065266</td>\n",
" <td>122144.711861</td>\n",
" <td>16.347465</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>4879584</td>\n",
" <td>16.594484</td>\n",
" <td>30</td>\n",
" <td>-41</td>\n",
" <td>0.345016</td>\n",
" <td>494032.694450</td>\n",
" <td>122142.863817</td>\n",
" <td>16.471196</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>4879585</td>\n",
" <td>15.423368</td>\n",
" <td>8</td>\n",
" <td>139</td>\n",
" <td>0.346054</td>\n",
" <td>494029.174399</td>\n",
" <td>122146.490457</td>\n",
" <td>17.613588</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td>4879586</td>\n",
" <td>27.906263</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.232186</td>\n",
" <td>494064.425856</td>\n",
" <td>122139.775622</td>\n",
" <td>21.598115</td>\n",
" <td>1020550</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23</th>\n",
" <td>4879587</td>\n",
" <td>87.360724</td>\n",
" <td>30</td>\n",
" <td>-138</td>\n",
" <td>0.154336</td>\n",
" <td>494028.864196</td>\n",
" <td>122210.211756</td>\n",
" <td>38.734764</td>\n",
" <td>2041393</td>\n",
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" <tr>\n",
" <th>24</th>\n",
" <td>4879588</td>\n",
" <td>85.970456</td>\n",
" <td>31</td>\n",
" <td>42</td>\n",
" <td>0.156790</td>\n",
" <td>494025.290758</td>\n",
" <td>122206.261441</td>\n",
" <td>38.502663</td>\n",
" <td>2041393</td>\n",
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" <tr>\n",
" <th>25</th>\n",
" <td>4879589</td>\n",
" <td>63.060851</td>\n",
" <td>6</td>\n",
" <td>-135</td>\n",
" <td>0.239073</td>\n",
" <td>494069.811943</td>\n",
" <td>122166.993289</td>\n",
" <td>49.943631</td>\n",
" <td>1020550</td>\n",
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" <tr>\n",
" <th>26</th>\n",
" <td>4879590</td>\n",
" <td>98.456303</td>\n",
" <td>33</td>\n",
" <td>-45</td>\n",
" <td>0.161719</td>\n",
" <td>494052.448592</td>\n",
" <td>122141.856383</td>\n",
" <td>44.467793</td>\n",
" <td>1020550</td>\n",
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" <tr>\n",
" <th>27</th>\n",
" <td>4879591</td>\n",
" <td>119.977310</td>\n",
" <td>29</td>\n",
" <td>135</td>\n",
" <td>0.151186</td>\n",
" <td>494049.441085</td>\n",
" <td>122146.960720</td>\n",
" <td>52.694179</td>\n",
" <td>1020550</td>\n",
" </tr>\n",
" <tr>\n",
" <th>28</th>\n",
" <td>4879592</td>\n",
" <td>52.899653</td>\n",
" <td>19</td>\n",
" <td>135</td>\n",
" <td>0.187633</td>\n",
" <td>494043.853986</td>\n",
" <td>122145.861717</td>\n",
" <td>31.285857</td>\n",
" <td>1020550</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29</th>\n",
" <td>4879593</td>\n",
" <td>257.117999</td>\n",
" <td>11</td>\n",
" <td>-45</td>\n",
" <td>0.079582</td>\n",
" <td>494066.645138</td>\n",
" <td>122153.737354</td>\n",
" <td>66.901310</td>\n",
" <td>1020550</td>\n",
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" <th>...</th>\n",
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" <td>...</td>\n",
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" <td>...</td>\n",
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" <tr>\n",
" <th>160334</th>\n",
" <td>5124499</td>\n",
" <td>92.630815</td>\n",
" <td>7</td>\n",
" <td>-150</td>\n",
" <td>0.153851</td>\n",
" <td>512730.885097</td>\n",
" <td>121812.056608</td>\n",
" <td>47.143675</td>\n",
" <td>1018653</td>\n",
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" <tr>\n",
" <th>160335</th>\n",
" <td>5124500</td>\n",
" <td>44.081253</td>\n",
" <td>7</td>\n",
" <td>-148</td>\n",
" <td>0.196382</td>\n",
" <td>512734.198663</td>\n",
" <td>121817.788002</td>\n",
" <td>28.618486</td>\n",
" <td>1018653</td>\n",
" </tr>\n",
" <tr>\n",
" <th>160336</th>\n",
" <td>5124501</td>\n",
" <td>12.602429</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.354338</td>\n",
" <td>512727.121243</td>\n",
" <td>121820.215342</td>\n",
" <td>14.885065</td>\n",
" <td>1018653</td>\n",
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" <tr>\n",
" <th>160337</th>\n",
" <td>5124502</td>\n",
" <td>14.119724</td>\n",
" <td>11</td>\n",
" <td>-147</td>\n",
" <td>0.363318</td>\n",
" <td>512728.749164</td>\n",
" <td>121822.557834</td>\n",
" <td>16.789635</td>\n",
" <td>1018653</td>\n",
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" <tr>\n",
" <th>160338</th>\n",
" <td>5124503</td>\n",
" <td>36.753693</td>\n",
" <td>21</td>\n",
" <td>122</td>\n",
" <td>0.206447</td>\n",
" <td>512683.557856</td>\n",
" <td>121769.252969</td>\n",
" <td>23.556753</td>\n",
" <td>2040405</td>\n",
" </tr>\n",
" <tr>\n",
" <th>160339</th>\n",
" <td>5124505</td>\n",
" <td>36.179539</td>\n",
" <td>19</td>\n",
" <td>-58</td>\n",
" <td>0.206720</td>\n",
" <td>512689.152724</td>\n",
" <td>121765.786059</td>\n",
" <td>23.566963</td>\n",
" <td>2040405</td>\n",
" </tr>\n",
" <tr>\n",
" <th>160340</th>\n",
" <td>5124506</td>\n",
" <td>57.609988</td>\n",
" <td>17</td>\n",
" <td>-57</td>\n",
" <td>0.205613</td>\n",
" <td>512685.461550</td>\n",
" <td>121760.421637</td>\n",
" <td>37.797327</td>\n",
" <td>2040405</td>\n",
" </tr>\n",
" <tr>\n",
" <th>160341</th>\n",
" <td>5124507</td>\n",
" <td>57.882063</td>\n",
" <td>22</td>\n",
" <td>122</td>\n",
" <td>0.164787</td>\n",
" <td>512679.561974</td>\n",
" <td>121763.956813</td>\n",
" <td>29.386703</td>\n",
" <td>2040405</td>\n",
" </tr>\n",
" <tr>\n",
" <th>160342</th>\n",
" <td>5124508</td>\n",
" <td>35.898733</td>\n",
" <td>22</td>\n",
" <td>-153</td>\n",
" <td>0.277002</td>\n",
" <td>512676.159641</td>\n",
" <td>121745.299236</td>\n",
" <td>30.833490</td>\n",
" <td>2040405</td>\n",
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" <tr>\n",
" <th>160343</th>\n",
" <td>5124509</td>\n",
" <td>88.059840</td>\n",
" <td>20</td>\n",
" <td>27</td>\n",
" <td>0.142382</td>\n",
" <td>512673.609011</td>\n",
" <td>121741.094997</td>\n",
" <td>39.260540</td>\n",
" <td>2040405</td>\n",
" </tr>\n",
" <tr>\n",
" <th>160344</th>\n",
" <td>5124510</td>\n",
" <td>234.137426</td>\n",
" <td>15</td>\n",
" <td>-139</td>\n",
" <td>0.088318</td>\n",
" <td>512575.847364</td>\n",
" <td>121776.836176</td>\n",
" <td>66.560300</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>160345</th>\n",
" <td>5124511</td>\n",
" <td>232.447102</td>\n",
" <td>16</td>\n",
" <td>41</td>\n",
" <td>0.089218</td>\n",
" <td>512569.666461</td>\n",
" <td>121769.693256</td>\n",
" <td>66.292584</td>\n",
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],
"text/plain": [
" DF_UID FLAECHE NEIGUNG AUSRICHTUN BUF30_Perc XCOORD \\\n",
"FID \n",
"0 4879560 78.139731 9 -143 0.157027 493497.059441 \n",
"1 4879561 46.507495 34 39 0.245521 493478.741922 \n",
"2 4879562 65.822671 28 -141 0.182859 493481.191087 \n",
"3 4879563 33.159751 41 -51 0.315406 493484.502179 \n",
"4 4879564 35.956510 11 -51 0.224638 493486.994637 \n",
"5 4879565 23.465989 36 129 0.325512 493481.402009 \n",
"6 4879567 26.304688 19 -143 0.252403 493463.360632 \n",
"7 4879568 25.396184 20 37 0.259015 493461.198117 \n",
"8 4879569 45.485566 8 -149 0.179873 493496.634242 \n",
"9 4879570 41.481273 23 35 0.256334 493511.024937 \n",
"10 4879571 37.316007 26 -145 0.285250 493512.562465 \n",
"11 4879572 14.442069 33 -142 0.353366 493519.594076 \n",
"12 4879573 20.230417 29 38 0.284888 493517.520013 \n",
"13 4879576 56.425414 37 -131 0.188028 493858.430044 \n",
"14 4879577 56.416744 37 49 0.188055 493854.908406 \n",
"15 4879578 21.678637 17 -64 0.263868 493861.601489 \n",
"16 4879579 27.094867 13 116 0.233973 493857.253150 \n",
"17 4879581 27.303228 10 48 0.243404 494048.490791 \n",
"18 4879582 39.881046 8 48 0.192826 494052.921911 \n",
"19 4879583 16.287173 31 139 0.351170 494031.065266 \n",
"20 4879584 16.594484 30 -41 0.345016 494032.694450 \n",
"21 4879585 15.423368 8 139 0.346054 494029.174399 \n",
"22 4879586 27.906263 0 0 0.232186 494064.425856 \n",
"23 4879587 87.360724 30 -138 0.154336 494028.864196 \n",
"24 4879588 85.970456 31 42 0.156790 494025.290758 \n",
"25 4879589 63.060851 6 -135 0.239073 494069.811943 \n",
"26 4879590 98.456303 33 -45 0.161719 494052.448592 \n",
"27 4879591 119.977310 29 135 0.151186 494049.441085 \n",
"28 4879592 52.899653 19 135 0.187633 494043.853986 \n",
"29 4879593 257.117999 11 -45 0.079582 494066.645138 \n",
"... ... ... ... ... ... ... \n",
"160334 5124499 92.630815 7 -150 0.153851 512730.885097 \n",
"160335 5124500 44.081253 7 -148 0.196382 512734.198663 \n",
"160336 5124501 12.602429 0 0 0.354338 512727.121243 \n",
"160337 5124502 14.119724 11 -147 0.363318 512728.749164 \n",
"160338 5124503 36.753693 21 122 0.206447 512683.557856 \n",
"160339 5124505 36.179539 19 -58 0.206720 512689.152724 \n",
"160340 5124506 57.609988 17 -57 0.205613 512685.461550 \n",
"160341 5124507 57.882063 22 122 0.164787 512679.561974 \n",
"160342 5124508 35.898733 22 -153 0.277002 512676.159641 \n",
"160343 5124509 88.059840 20 27 0.142382 512673.609011 \n",
"160344 5124510 234.137426 15 -139 0.088318 512575.847364 \n",
"160345 5124511 232.447102 16 41 0.089218 512569.666461 \n",
"160346 5124512 131.925651 29 121 0.145503 512861.001267 \n",
"160347 5124513 137.339196 28 -59 0.139416 512865.436278 \n",
"160348 5124514 21.008432 23 -150 0.358840 512862.267927 \n",
"160349 5124515 21.541363 19 30 0.288923 512860.316121 \n",
"160350 5124516 33.342276 17 -58 0.228863 512856.925464 \n",
"160351 5124517 43.358052 13 122 0.189882 512853.120003 \n",
"160352 5124518 34.768271 0 0 0.250965 512851.074627 \n",
"160353 5124519 32.262272 7 -62 0.212448 512888.867335 \n",
"160354 5124520 14.249623 25 118 0.361173 512885.173409 \n",
"160355 5124521 17.491505 2 118 0.359617 512889.571818 \n",
"160356 5124522 73.914707 1 -61 0.147023 512787.375432 \n",
"160357 5124523 202.860586 26 -65 0.114355 512906.933121 \n",
"160358 5124524 221.668609 25 115 0.107353 512900.901794 \n",
"160359 5124525 126.405824 22 118 0.111160 512800.694862 \n",
"160360 5124526 126.408740 22 -62 0.111159 512809.763984 \n",
"160361 5124527 17.738624 32 -67 0.328771 512895.231916 \n",
"160362 5124528 17.671450 33 113 0.329941 512892.718802 \n",
"160363 5124529 116.297209 5 -155 0.132662 512876.098582 \n",
"\n",
" YCOORD SHAPE_Leng GWR_EGID \n",
"FID \n",
"0 122054.961813 40.420060 0 \n",
"1 122044.537267 31.477187 1020549 \n",
"2 122047.635869 35.355795 1020549 \n",
"3 122038.094141 26.367892 1020549 \n",
"4 122036.384922 26.383903 1020549 \n",
"5 122038.122620 20.596973 1020549 \n",
"6 122094.162534 20.943016 2041392 \n",
"7 122091.312567 20.661054 2041392 \n",
"8 122082.025889 26.983629 0 \n",
"9 122043.228215 32.570624 0 \n",
"10 122045.403184 31.889598 0 \n",
"11 122010.886479 14.335675 0 \n",
"12 122008.193580 16.881133 0 \n",
"13 122063.995365 28.247269 1020551 \n",
"14 122060.966845 28.245385 1020551 \n",
"15 122073.440568 18.272307 0 \n",
"16 122075.561250 20.571758 0 \n",
"17 122127.974434 21.815644 0 \n",
"18 122122.292509 25.390413 0 \n",
"19 122144.711861 16.347465 0 \n",
"20 122142.863817 16.471196 0 \n",
"21 122146.490457 17.613588 0 \n",
"22 122139.775622 21.598115 1020550 \n",
"23 122210.211756 38.734764 2041393 \n",
"24 122206.261441 38.502663 2041393 \n",
"25 122166.993289 49.943631 1020550 \n",
"26 122141.856383 44.467793 1020550 \n",
"27 122146.960720 52.694179 1020550 \n",
"28 122145.861717 31.285857 1020550 \n",
"29 122153.737354 66.901310 1020550 \n",
"... ... ... ... \n",
"160334 121812.056608 47.143675 1018653 \n",
"160335 121817.788002 28.618486 1018653 \n",
"160336 121820.215342 14.885065 1018653 \n",
"160337 121822.557834 16.789635 1018653 \n",
"160338 121769.252969 23.556753 2040405 \n",
"160339 121765.786059 23.566963 2040405 \n",
"160340 121760.421637 37.797327 2040405 \n",
"160341 121763.956813 29.386703 2040405 \n",
"160342 121745.299236 30.833490 2040405 \n",
"160343 121741.094997 39.260540 2040405 \n",
"160344 121776.836176 66.560300 0 \n",
"160345 121769.693256 66.292584 0 \n",
"160346 121844.951885 55.702429 1018654 \n",
"160347 121842.297555 56.243851 1018654 \n",
"160348 121857.440814 23.119281 1018654 \n",
"160349 121855.330158 19.585625 1018654 \n",
"160350 121829.218203 24.377198 1018654 \n",
"160351 121831.545790 26.787103 1018654 \n",
"160352 121838.634710 29.085365 1018654 \n",
"160353 121963.163257 22.665441 0 \n",
"160354 121965.157380 15.514710 0 \n",
"160355 121967.004430 20.955387 0 \n",
"160356 121772.037243 36.219623 0 \n",
"160357 121907.819462 69.264065 1018655 \n",
"160358 121911.006917 72.136766 1018655 \n",
"160359 121763.497186 43.276794 1018651 \n",
"160360 121758.593080 43.277184 1018651 \n",
"160361 121945.880702 16.399780 0 \n",
"160362 121946.958185 16.370630 0 \n",
"160363 121937.457745 51.190721 0 \n",
"\n",
"[160364 rows x 9 columns]"
]
},
"execution_count": 78,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"roof_select"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"# load GWR\n",
"GWR = '/Users/alinawalch/Documents/EPFL/data/GWR/EPFL-150701-GEB.txt'\n",
"GWR_column_names = pd.read_csv('/Users/alinawalch/Documents/EPFL/data/GWR/Maske_EINZELD-GEB.csv').columns\n",
"buildings = pd.read_csv(GWR, sep = '\\t', encoding = 'cp1250', header = None, names = GWR_column_names)\n",
"GWR = buildings.loc[:,['EGID', 'GBAUP', 'GKAT', 'GAREA', 'GASTW', 'GKODX', 'GKODY']]"
]
},
{
"cell_type": "code",
"execution_count": 70,
"metadata": {},
"outputs": [],
"source": [
"# merge rooftop information and GWR\n",
"# 146.000 buildings instead of 170.000\n",
"ROOFS = roof_select.merge(GWR, left_on = 'GWR_EGID', right_on = 'EGID', how='inner').drop('EGID', axis = 1)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Compute neighborhood index"
]
},
{
"cell_type": "code",
"execution_count": 71,
"metadata": {},
"outputs": [],
"source": [
"def find_neighbors(input_table, radius, x = 'GKODX', y = 'GKODY', ID_column = 'GWR_EGID'):\n",
"\n",
" # create unique non-NaN rows for correct neighbor count\n",
" reduced_table = input_table.loc[ : , [ ID_column, x, y ] ].dropna().drop_duplicates().reset_index()\n",
"\n",
" # declare a tree structure to store points and count neighbors (based on 2D coordinates)\n",
" tree = spatial.KDTree(reduced_table.loc[:,[x, y]])\n",
"\n",
" # compute all pairs in tree\n",
" tt = util.Timer()\n",
" query_pairs = tree.query_pairs(r = radius)\n",
" print('Finished computing neighboring pairs')\n",
" tt.stop()\n",
"\n",
" # convert output to pandas dataframe\n",
" query_array = list(query_pairs)\n",
" df = pd.DataFrame(np.asarray(query_array), columns = ['index_x', 'index_y'])\n",
"\n",
" # COUNT TOTAL NUMBER OF NEIGHBORS\n",
"\n",
" # group by index, to count number of neighbors per pair (for left-side merging)\n",
" left_groups = df.groupby('index_x').count()\n",
" left_groups = left_groups.rename({'index_y' : 'n_neighbors'}, axis = 1)\n",
"\n",
" # group by index, to count number of neighbors per pair (for right-side merging)\n",
" right_groups = df.groupby('index_y').count()\n",
" right_groups = right_groups.rename({'index_x' : 'n_neighbors'}, axis = 1)\n",
"\n",
" # merge counts together and evaluate total number of neighbors for each building\n",
" neighbors = left_groups.merge(right_groups, left_index = True, right_index = True, how='outer').fillna(0)\n",
" neighbors[('n_neighbors_%d' %radius)] = neighbors.n_neighbors_x + neighbors.n_neighbors_y\n",
"\n",
" all_neighbors = reduced_table.merge(neighbors, left_index = True, right_index = True, how='outer').fillna(0)\n",
"\n",
" # return neighbor count data, merged onto the input table as column n_neighbors_RADIUS\n",
" return input_table.merge(all_neighbors, on = [ ID_column, x, y ], how = 'left').drop(['index', 'n_neighbors_x', 'n_neighbors_y'], axis=1)"
]
},
{
"cell_type": "code",
"execution_count": 73,
"metadata": {
"scrolled": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Finished computing neighboring pairs\n",
"CPU time: 6.08 seconds\n",
"Wall clock time: 6.09 seconds\n"
]
},
{
"data": {
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" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>DF_UID</th>\n",
" <th>FLAECHE</th>\n",
" <th>NEIGUNG</th>\n",
" <th>AUSRICHTUN</th>\n",
" <th>BUF30_Perc</th>\n",
" <th>XCOORD</th>\n",
" <th>YCOORD</th>\n",
" <th>SHAPE_Leng</th>\n",
" <th>GWR_EGID</th>\n",
" <th>GBAUP</th>\n",
" <th>GKAT</th>\n",
" <th>GAREA</th>\n",
" <th>GASTW</th>\n",
" <th>GKODX</th>\n",
" <th>GKODY</th>\n",
" <th>n_neighbors_100</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>4879561</td>\n",
" <td>46.507495</td>\n",
" <td>34</td>\n",
" <td>39</td>\n",
" <td>0.245521</td>\n",
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" <td>1.0</td>\n",
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" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>4879562</td>\n",
" <td>65.822671</td>\n",
" <td>28</td>\n",
" <td>-141</td>\n",
" <td>0.182859</td>\n",
" <td>493481.191087</td>\n",
" <td>122047.635869</td>\n",
" <td>35.355795</td>\n",
" <td>1020549</td>\n",
" <td>8012.0</td>\n",
" <td>1021</td>\n",
" <td>71.0</td>\n",
" <td>1.0</td>\n",
" <td>493481.0</td>\n",
" <td>122046.0</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>4879563</td>\n",
" <td>33.159751</td>\n",
" <td>41</td>\n",
" <td>-51</td>\n",
" <td>0.315406</td>\n",
" <td>493484.502179</td>\n",
" <td>122038.094141</td>\n",
" <td>26.367892</td>\n",
" <td>1020549</td>\n",
" <td>8012.0</td>\n",
" <td>1021</td>\n",
" <td>71.0</td>\n",
" <td>1.0</td>\n",
" <td>493481.0</td>\n",
" <td>122046.0</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>4879564</td>\n",
" <td>35.956510</td>\n",
" <td>11</td>\n",
" <td>-51</td>\n",
" <td>0.224638</td>\n",
" <td>493486.994637</td>\n",
" <td>122036.384922</td>\n",
" <td>26.383903</td>\n",
" <td>1020549</td>\n",
" <td>8012.0</td>\n",
" <td>1021</td>\n",
" <td>71.0</td>\n",
" <td>1.0</td>\n",
" <td>493481.0</td>\n",
" <td>122046.0</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>4879565</td>\n",
" <td>23.465989</td>\n",
" <td>36</td>\n",
" <td>129</td>\n",
" <td>0.325512</td>\n",
" <td>493481.402009</td>\n",
" <td>122038.122620</td>\n",
" <td>20.596973</td>\n",
" <td>1020549</td>\n",
" <td>8012.0</td>\n",
" <td>1021</td>\n",
" <td>71.0</td>\n",
" <td>1.0</td>\n",
" <td>493481.0</td>\n",
" <td>122046.0</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>4879567</td>\n",
" <td>26.304688</td>\n",
" <td>19</td>\n",
" <td>-143</td>\n",
" <td>0.252403</td>\n",
" <td>493463.360632</td>\n",
" <td>122094.162534</td>\n",
" <td>20.943016</td>\n",
" <td>2041392</td>\n",
" <td>8014.0</td>\n",
" <td>1021</td>\n",
" <td>24.0</td>\n",
" <td>1.0</td>\n",
" <td>493463.0</td>\n",
" <td>122091.0</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>4879568</td>\n",
" <td>25.396184</td>\n",
" <td>20</td>\n",
" <td>37</td>\n",
" <td>0.259015</td>\n",
" <td>493461.198117</td>\n",
" <td>122091.312567</td>\n",
" <td>20.661054</td>\n",
" <td>2041392</td>\n",
" <td>8014.0</td>\n",
" <td>1021</td>\n",
" <td>24.0</td>\n",
" <td>1.0</td>\n",
" <td>493463.0</td>\n",
" <td>122091.0</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>4879576</td>\n",
" <td>56.425414</td>\n",
" <td>37</td>\n",
" <td>-131</td>\n",
" <td>0.188028</td>\n",
" <td>493858.430044</td>\n",
" <td>122063.995365</td>\n",
" <td>28.247269</td>\n",
" <td>1020551</td>\n",
" <td>8012.0</td>\n",
" <td>1021</td>\n",
" <td>48.0</td>\n",
" <td>3.0</td>\n",
" <td>493858.0</td>\n",
" <td>122061.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>4879577</td>\n",
" <td>56.416744</td>\n",
" <td>37</td>\n",
" <td>49</td>\n",
" <td>0.188055</td>\n",
" <td>493854.908406</td>\n",
" <td>122060.966845</td>\n",
" <td>28.245385</td>\n",
" <td>1020551</td>\n",
" <td>8012.0</td>\n",
" <td>1021</td>\n",
" <td>48.0</td>\n",
" <td>3.0</td>\n",
" <td>493858.0</td>\n",
" <td>122061.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>4879586</td>\n",
" <td>27.906263</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.232186</td>\n",
" <td>494064.425856</td>\n",
" <td>122139.775622</td>\n",
" <td>21.598115</td>\n",
" <td>1020550</td>\n",
" <td>8012.0</td>\n",
" <td>1021</td>\n",
" <td>166.0</td>\n",
" <td>3.0</td>\n",
" <td>494050.0</td>\n",
" <td>122145.0</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>4879589</td>\n",
" <td>63.060851</td>\n",
" <td>6</td>\n",
" <td>-135</td>\n",
" <td>0.239073</td>\n",
" <td>494069.811943</td>\n",
" <td>122166.993289</td>\n",
" <td>49.943631</td>\n",
" <td>1020550</td>\n",
" <td>8012.0</td>\n",
" <td>1021</td>\n",
" <td>166.0</td>\n",
" <td>3.0</td>\n",
" <td>494050.0</td>\n",
" <td>122145.0</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>4879590</td>\n",
" <td>98.456303</td>\n",
" <td>33</td>\n",
" <td>-45</td>\n",
" <td>0.161719</td>\n",
" <td>494052.448592</td>\n",
" <td>122141.856383</td>\n",
" <td>44.467793</td>\n",
" <td>1020550</td>\n",
" <td>8012.0</td>\n",
" <td>1021</td>\n",
" <td>166.0</td>\n",
" <td>3.0</td>\n",
" <td>494050.0</td>\n",
" <td>122145.0</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>4879591</td>\n",
" <td>119.977310</td>\n",
" <td>29</td>\n",
" <td>135</td>\n",
" <td>0.151186</td>\n",
" <td>494049.441085</td>\n",
" <td>122146.960720</td>\n",
" <td>52.694179</td>\n",
" <td>1020550</td>\n",
" <td>8012.0</td>\n",
" <td>1021</td>\n",
" <td>166.0</td>\n",
" <td>3.0</td>\n",
" <td>494050.0</td>\n",
" <td>122145.0</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>4879592</td>\n",
" <td>52.899653</td>\n",
" <td>19</td>\n",
" <td>135</td>\n",
" <td>0.187633</td>\n",
" <td>494043.853986</td>\n",
" <td>122145.861717</td>\n",
" <td>31.285857</td>\n",
" <td>1020550</td>\n",
" <td>8012.0</td>\n",
" <td>1021</td>\n",
" <td>166.0</td>\n",
" <td>3.0</td>\n",
" <td>494050.0</td>\n",
" <td>122145.0</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>4879593</td>\n",
" <td>257.117999</td>\n",
" <td>11</td>\n",
" <td>-45</td>\n",
" <td>0.079582</td>\n",
" <td>494066.645138</td>\n",
" <td>122153.737354</td>\n",
" <td>66.901310</td>\n",
" <td>1020550</td>\n",
" <td>8012.0</td>\n",
" <td>1021</td>\n",
" <td>166.0</td>\n",
" <td>3.0</td>\n",
" <td>494050.0</td>\n",
" <td>122145.0</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>4879594</td>\n",
" <td>332.516025</td>\n",
" <td>9</td>\n",
" <td>135</td>\n",
" <td>0.067697</td>\n",
" <td>494056.369323</td>\n",
" <td>122163.753664</td>\n",
" <td>74.097563</td>\n",
" <td>1020550</td>\n",
" <td>8012.0</td>\n",
" <td>1021</td>\n",
" <td>166.0</td>\n",
" <td>3.0</td>\n",
" <td>494050.0</td>\n",
" <td>122145.0</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>4879595</td>\n",
" <td>210.472123</td>\n",
" <td>8</td>\n",
" <td>-45</td>\n",
" <td>0.089134</td>\n",
" <td>494047.083075</td>\n",
" <td>122172.564987</td>\n",
" <td>61.977891</td>\n",
" <td>1020550</td>\n",
" <td>8012.0</td>\n",
" <td>1021</td>\n",
" <td>166.0</td>\n",
" <td>3.0</td>\n",
" <td>494050.0</td>\n",
" <td>122145.0</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td>4879596</td>\n",
" <td>28.356617</td>\n",
" <td>16</td>\n",
" <td>135</td>\n",
" <td>0.494003</td>\n",
" <td>494043.105026</td>\n",
" <td>122176.486925</td>\n",
" <td>44.787707</td>\n",
" <td>1020550</td>\n",
" <td>8012.0</td>\n",
" <td>1021</td>\n",
" <td>166.0</td>\n",
" <td>3.0</td>\n",
" <td>494050.0</td>\n",
" <td>122145.0</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>4879597</td>\n",
" <td>146.037528</td>\n",
" <td>5</td>\n",
" <td>-45</td>\n",
" <td>0.107666</td>\n",
" <td>494074.156498</td>\n",
" <td>122146.950960</td>\n",
" <td>52.205428</td>\n",
" <td>1020550</td>\n",
" <td>8012.0</td>\n",
" <td>1021</td>\n",
" <td>166.0</td>\n",
" <td>3.0</td>\n",
" <td>494050.0</td>\n",
" <td>122145.0</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td>4879598</td>\n",
" <td>49.542742</td>\n",
" <td>4</td>\n",
" <td>-45</td>\n",
" <td>0.185587</td>\n",
" <td>494058.505654</td>\n",
" <td>122134.230225</td>\n",
" <td>30.581988</td>\n",
" <td>1020550</td>\n",
" <td>8012.0</td>\n",
" <td>1021</td>\n",
" <td>166.0</td>\n",
" <td>3.0</td>\n",
" <td>494050.0</td>\n",
" <td>122145.0</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>4879599</td>\n",
" <td>19.554210</td>\n",
" <td>3</td>\n",
" <td>-45</td>\n",
" <td>0.280526</td>\n",
" <td>494064.725821</td>\n",
" <td>122133.170932</td>\n",
" <td>18.250880</td>\n",
" <td>1020550</td>\n",
" <td>8012.0</td>\n",
" <td>1021</td>\n",
" <td>166.0</td>\n",
" <td>3.0</td>\n",
" <td>494050.0</td>\n",
" <td>122145.0</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>4879600</td>\n",
" <td>24.972216</td>\n",
" <td>9</td>\n",
" <td>135</td>\n",
" <td>0.256793</td>\n",
" <td>494067.799175</td>\n",
" <td>122136.633782</td>\n",
" <td>21.123500</td>\n",
" <td>1020550</td>\n",
" <td>8012.0</td>\n",
" <td>1021</td>\n",
" <td>166.0</td>\n",
" <td>3.0</td>\n",
" <td>494050.0</td>\n",
" <td>122145.0</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td>4879601</td>\n",
" <td>27.299810</td>\n",
" <td>15</td>\n",
" <td>135</td>\n",
" <td>0.244460</td>\n",
" <td>494070.939006</td>\n",
" <td>122134.093766</td>\n",
" <td>21.521896</td>\n",
" <td>1020550</td>\n",
" <td>8012.0</td>\n",
" <td>1021</td>\n",
" <td>166.0</td>\n",
" <td>3.0</td>\n",
" <td>494050.0</td>\n",
" <td>122145.0</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23</th>\n",
" <td>4879587</td>\n",
" <td>87.360724</td>\n",
" <td>30</td>\n",
" <td>-138</td>\n",
" <td>0.154336</td>\n",
" <td>494028.864196</td>\n",
" <td>122210.211756</td>\n",
" <td>38.734764</td>\n",
" <td>2041393</td>\n",
" <td>8011.0</td>\n",
" <td>1021</td>\n",
" <td>91.0</td>\n",
" <td>2.0</td>\n",
" <td>494028.0</td>\n",
" <td>122207.0</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24</th>\n",
" <td>4879588</td>\n",
" <td>85.970456</td>\n",
" <td>31</td>\n",
" <td>42</td>\n",
" <td>0.156790</td>\n",
" <td>494025.290758</td>\n",
" <td>122206.261441</td>\n",
" <td>38.502663</td>\n",
" <td>2041393</td>\n",
" <td>8011.0</td>\n",
" <td>1021</td>\n",
" <td>91.0</td>\n",
" <td>2.0</td>\n",
" <td>494028.0</td>\n",
" <td>122207.0</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25</th>\n",
" <td>4879603</td>\n",
" <td>55.782605</td>\n",
" <td>22</td>\n",
" <td>141</td>\n",
" <td>0.171559</td>\n",
" <td>495600.894977</td>\n",
" <td>122215.511491</td>\n",
" <td>29.601988</td>\n",
" <td>1020569</td>\n",
" <td>8013.0</td>\n",
" <td>1021</td>\n",
" <td>75.0</td>\n",
" <td>1.0</td>\n",
" <td>495603.0</td>\n",
" <td>122213.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>26</th>\n",
" <td>4879604</td>\n",
" <td>72.169621</td>\n",
" <td>24</td>\n",
" <td>-39</td>\n",
" <td>0.150722</td>\n",
" <td>495605.063345</td>\n",
" <td>122210.549004</td>\n",
" <td>33.216251</td>\n",
" <td>1020569</td>\n",
" <td>8013.0</td>\n",
" <td>1021</td>\n",
" <td>75.0</td>\n",
" <td>1.0</td>\n",
" <td>495603.0</td>\n",
" <td>122213.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>27</th>\n",
" <td>4879605</td>\n",
" <td>146.924324</td>\n",
" <td>29</td>\n",
" <td>-21</td>\n",
" <td>0.131341</td>\n",
" <td>495595.680394</td>\n",
" <td>122037.585238</td>\n",
" <td>56.349336</td>\n",
" <td>3131860</td>\n",
" <td>8019.0</td>\n",
" <td>1021</td>\n",
" <td>58.0</td>\n",
" <td>3.0</td>\n",
" <td>495588.0</td>\n",
" <td>122037.0</td>\n",
" <td>12.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>28</th>\n",
" <td>4879606</td>\n",
" <td>149.955503</td>\n",
" <td>28</td>\n",
" <td>159</td>\n",
" <td>0.128607</td>\n",
" <td>495593.606354</td>\n",
" <td>122043.015684</td>\n",
" <td>56.656931</td>\n",
" <td>3131860</td>\n",
" <td>8019.0</td>\n",
" <td>1021</td>\n",
" <td>58.0</td>\n",
" <td>3.0</td>\n",
" <td>495588.0</td>\n",
" <td>122037.0</td>\n",
" <td>12.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29</th>\n",
" <td>4879607</td>\n",
" <td>112.779260</td>\n",
" <td>28</td>\n",
" <td>-21</td>\n",
" <td>0.139096</td>\n",
" <td>495570.308703</td>\n",
" <td>122025.955633</td>\n",
" <td>46.369998</td>\n",
" <td>2041363</td>\n",
" <td>8019.0</td>\n",
" <td>1021</td>\n",
" <td>58.0</td>\n",
" <td>1.0</td>\n",
" <td>495564.0</td>\n",
" <td>122026.0</td>\n",
" <td>14.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>147845</th>\n",
" <td>5124479</td>\n",
" <td>201.344527</td>\n",
" <td>28</td>\n",
" <td>-57</td>\n",
" <td>0.110559</td>\n",
" <td>512580.233215</td>\n",
" <td>121889.136842</td>\n",
" <td>65.261998</td>\n",
" <td>1018649</td>\n",
" <td>8011.0</td>\n",
" <td>1030</td>\n",
" <td>281.0</td>\n",
" <td>3.0</td>\n",
" <td>512578.0</td>\n",
" <td>121893.0</td>\n",
" <td>2.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>147846</th>\n",
" <td>5124480</td>\n",
" <td>222.078136</td>\n",
" <td>28</td>\n",
" <td>123</td>\n",
" <td>0.110206</td>\n",
" <td>512574.241420</td>\n",
" <td>121894.372239</td>\n",
" <td>71.750997</td>\n",
" <td>1018649</td>\n",
" <td>8011.0</td>\n",
" <td>1030</td>\n",
" <td>281.0</td>\n",
" <td>3.0</td>\n",
" <td>512578.0</td>\n",
" <td>121893.0</td>\n",
" <td>2.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>147847</th>\n",
" <td>5124481</td>\n",
" <td>88.795794</td>\n",
" <td>23</td>\n",
" <td>-147</td>\n",
" <td>0.149423</td>\n",
" <td>512584.730873</td>\n",
" <td>121903.726978</td>\n",
" <td>40.629952</td>\n",
" <td>1018649</td>\n",
" <td>8011.0</td>\n",
" <td>1030</td>\n",
" <td>281.0</td>\n",
" <td>3.0</td>\n",
" <td>512578.0</td>\n",
" <td>121893.0</td>\n",
" <td>2.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>147848</th>\n",
" <td>5124483</td>\n",
" <td>75.633549</td>\n",
" <td>30</td>\n",
" <td>-147</td>\n",
" <td>0.169608</td>\n",
" <td>512606.304400</td>\n",
" <td>121901.560650</td>\n",
" <td>37.171831</td>\n",
" <td>1018650</td>\n",
" <td>8015.0</td>\n",
" <td>1025</td>\n",
" <td>95.0</td>\n",
" <td>3.0</td>\n",
" <td>512606.0</td>\n",
" <td>121899.0</td>\n",
" <td>2.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>147849</th>\n",
" <td>5124484</td>\n",
" <td>96.109368</td>\n",
" <td>31</td>\n",
" <td>33</td>\n",
" <td>0.143688</td>\n",
" <td>512603.387815</td>\n",
" <td>121897.055040</td>\n",
" <td>39.628036</td>\n",
" <td>1018650</td>\n",
" <td>8015.0</td>\n",
" <td>1025</td>\n",
" <td>95.0</td>\n",
" <td>3.0</td>\n",
" <td>512606.0</td>\n",
" <td>121899.0</td>\n",
" <td>2.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>147850</th>\n",
" <td>5124488</td>\n",
" <td>165.220451</td>\n",
" <td>20</td>\n",
" <td>-53</td>\n",
" <td>0.101590</td>\n",
" <td>512634.079435</td>\n",
" <td>121751.577376</td>\n",
" <td>52.477312</td>\n",
" <td>1018656</td>\n",
" <td>8011.0</td>\n",
" <td>1021</td>\n",
" <td>313.0</td>\n",
" <td>2.0</td>\n",
" <td>512631.0</td>\n",
" <td>121756.0</td>\n",
" <td>7.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>147851</th>\n",
" <td>5124489</td>\n",
" <td>239.812345</td>\n",
" <td>22</td>\n",
" <td>126</td>\n",
" <td>0.088074</td>\n",
" <td>512628.613532</td>\n",
" <td>121760.935293</td>\n",
" <td>65.063152</td>\n",
" <td>1018656</td>\n",
" <td>8011.0</td>\n",
" <td>1021</td>\n",
" <td>313.0</td>\n",
" <td>2.0</td>\n",
" <td>512631.0</td>\n",
" <td>121756.0</td>\n",
" <td>7.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>147852</th>\n",
" <td>5124490</td>\n",
" <td>46.693778</td>\n",
" <td>24</td>\n",
" <td>-147</td>\n",
" <td>0.197704</td>\n",
" <td>512638.808717</td>\n",
" <td>121762.936532</td>\n",
" <td>28.070510</td>\n",
" <td>1018656</td>\n",
" <td>8011.0</td>\n",
" <td>1021</td>\n",
" <td>313.0</td>\n",
" <td>2.0</td>\n",
" <td>512631.0</td>\n",
" <td>121756.0</td>\n",
" <td>7.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>147853</th>\n",
" <td>5124491</td>\n",
" <td>112.466072</td>\n",
" <td>29</td>\n",
" <td>-64</td>\n",
" <td>0.120936</td>\n",
" <td>512521.577577</td>\n",
" <td>121873.022662</td>\n",
" <td>39.762596</td>\n",
" <td>295081617</td>\n",
" <td>8017.0</td>\n",
" <td>1060</td>\n",
" <td>110.0</td>\n",
" <td>1.0</td>\n",
" <td>512513.0</td>\n",
" <td>121866.0</td>\n",
" <td>2.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>147854</th>\n",
" <td>5124492</td>\n",
" <td>108.203352</td>\n",
" <td>30</td>\n",
" <td>116</td>\n",
" <td>0.124360</td>\n",
" <td>512513.364438</td>\n",
" <td>121877.059813</td>\n",
" <td>38.853185</td>\n",
" <td>295081617</td>\n",
" <td>8017.0</td>\n",
" <td>1060</td>\n",
" <td>110.0</td>\n",
" <td>1.0</td>\n",
" <td>512513.0</td>\n",
" <td>121866.0</td>\n",
" <td>2.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>147855</th>\n",
" <td>5124493</td>\n",
" <td>76.814349</td>\n",
" <td>32</td>\n",
" <td>-64</td>\n",
" <td>0.153423</td>\n",
" <td>512515.570905</td>\n",
" <td>121864.378429</td>\n",
" <td>33.214762</td>\n",
" <td>295081617</td>\n",
" <td>8017.0</td>\n",
" <td>1060</td>\n",
" <td>110.0</td>\n",
" <td>1.0</td>\n",
" <td>512513.0</td>\n",
" <td>121866.0</td>\n",
" <td>2.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>147856</th>\n",
" <td>5124494</td>\n",
" <td>63.680411</td>\n",
" <td>30</td>\n",
" <td>116</td>\n",
" <td>0.169030</td>\n",
" <td>512510.329761</td>\n",
" <td>121867.086155</td>\n",
" <td>31.106354</td>\n",
" <td>295081617</td>\n",
" <td>8017.0</td>\n",
" <td>1060</td>\n",
" <td>110.0</td>\n",
" <td>1.0</td>\n",
" <td>512513.0</td>\n",
" <td>121866.0</td>\n",
" <td>2.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>147857</th>\n",
" <td>5124495</td>\n",
" <td>27.490066</td>\n",
" <td>21</td>\n",
" <td>116</td>\n",
" <td>0.292291</td>\n",
" <td>512506.735714</td>\n",
" <td>121868.942467</td>\n",
" <td>24.997104</td>\n",
" <td>295081617</td>\n",
" <td>8017.0</td>\n",
" <td>1060</td>\n",
" <td>110.0</td>\n",
" <td>1.0</td>\n",
" <td>512513.0</td>\n",
" <td>121866.0</td>\n",
" <td>2.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>147858</th>\n",
" <td>5124497</td>\n",
" <td>139.413591</td>\n",
" <td>30</td>\n",
" <td>-60</td>\n",
" <td>0.134461</td>\n",
" <td>512727.438593</td>\n",
" <td>121799.488883</td>\n",
" <td>54.005430</td>\n",
" <td>1018653</td>\n",
" <td>8012.0</td>\n",
" <td>1025</td>\n",
" <td>153.0</td>\n",
" <td>3.0</td>\n",
" <td>512725.0</td>\n",
" <td>121800.0</td>\n",
" <td>3.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>147859</th>\n",
" <td>5124498</td>\n",
" <td>137.530298</td>\n",
" <td>30</td>\n",
" <td>120</td>\n",
" <td>0.135168</td>\n",
" <td>512721.597769</td>\n",
" <td>121802.956658</td>\n",
" <td>53.905711</td>\n",
" <td>1018653</td>\n",
" <td>8012.0</td>\n",
" <td>1025</td>\n",
" <td>153.0</td>\n",
" <td>3.0</td>\n",
" <td>512725.0</td>\n",
" <td>121800.0</td>\n",
" <td>3.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>147860</th>\n",
" <td>5124499</td>\n",
" <td>92.630815</td>\n",
" <td>7</td>\n",
" <td>-150</td>\n",
" <td>0.153851</td>\n",
" <td>512730.885097</td>\n",
" <td>121812.056608</td>\n",
" <td>47.143675</td>\n",
" <td>1018653</td>\n",
" <td>8012.0</td>\n",
" <td>1025</td>\n",
" <td>153.0</td>\n",
" <td>3.0</td>\n",
" <td>512725.0</td>\n",
" <td>121800.0</td>\n",
" <td>3.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>147861</th>\n",
" <td>5124500</td>\n",
" <td>44.081253</td>\n",
" <td>7</td>\n",
" <td>-148</td>\n",
" <td>0.196382</td>\n",
" <td>512734.198663</td>\n",
" <td>121817.788002</td>\n",
" <td>28.618486</td>\n",
" <td>1018653</td>\n",
" <td>8012.0</td>\n",
" <td>1025</td>\n",
" <td>153.0</td>\n",
" <td>3.0</td>\n",
" <td>512725.0</td>\n",
" <td>121800.0</td>\n",
" <td>3.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>147862</th>\n",
" <td>5124501</td>\n",
" <td>12.602429</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.354338</td>\n",
" <td>512727.121243</td>\n",
" <td>121820.215342</td>\n",
" <td>14.885065</td>\n",
" <td>1018653</td>\n",
" <td>8012.0</td>\n",
" <td>1025</td>\n",
" <td>153.0</td>\n",
" <td>3.0</td>\n",
" <td>512725.0</td>\n",
" <td>121800.0</td>\n",
" <td>3.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>147863</th>\n",
" <td>5124502</td>\n",
" <td>14.119724</td>\n",
" <td>11</td>\n",
" <td>-147</td>\n",
" <td>0.363318</td>\n",
" <td>512728.749164</td>\n",
" <td>121822.557834</td>\n",
" <td>16.789635</td>\n",
" <td>1018653</td>\n",
" <td>8012.0</td>\n",
" <td>1025</td>\n",
" <td>153.0</td>\n",
" <td>3.0</td>\n",
" <td>512725.0</td>\n",
" <td>121800.0</td>\n",
" <td>3.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>147864</th>\n",
" <td>5124512</td>\n",
" <td>131.925651</td>\n",
" <td>29</td>\n",
" <td>121</td>\n",
" <td>0.145503</td>\n",
" <td>512861.001267</td>\n",
" <td>121844.951885</td>\n",
" <td>55.702429</td>\n",
" <td>1018654</td>\n",
" <td>8011.0</td>\n",
" <td>1025</td>\n",
" <td>304.0</td>\n",
" <td>2.0</td>\n",
" <td>512862.0</td>\n",
" <td>121841.0</td>\n",
" <td>2.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>147865</th>\n",
" <td>5124513</td>\n",
" <td>137.339196</td>\n",
" <td>28</td>\n",
" <td>-59</td>\n",
" <td>0.139416</td>\n",
" <td>512865.436278</td>\n",
" <td>121842.297555</td>\n",
" <td>56.243851</td>\n",
" <td>1018654</td>\n",
" <td>8011.0</td>\n",
" <td>1025</td>\n",
" <td>304.0</td>\n",
" <td>2.0</td>\n",
" <td>512862.0</td>\n",
" <td>121841.0</td>\n",
" <td>2.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>147866</th>\n",
" <td>5124514</td>\n",
" <td>21.008432</td>\n",
" <td>23</td>\n",
" <td>-150</td>\n",
" <td>0.358840</td>\n",
" <td>512862.267927</td>\n",
" <td>121857.440814</td>\n",
" <td>23.119281</td>\n",
" <td>1018654</td>\n",
" <td>8011.0</td>\n",
" <td>1025</td>\n",
" <td>304.0</td>\n",
" <td>2.0</td>\n",
" <td>512862.0</td>\n",
" <td>121841.0</td>\n",
" <td>2.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>147867</th>\n",
" <td>5124515</td>\n",
" <td>21.541363</td>\n",
" <td>19</td>\n",
" <td>30</td>\n",
" <td>0.288923</td>\n",
" <td>512860.316121</td>\n",
" <td>121855.330158</td>\n",
" <td>19.585625</td>\n",
" <td>1018654</td>\n",
" <td>8011.0</td>\n",
" <td>1025</td>\n",
" <td>304.0</td>\n",
" <td>2.0</td>\n",
" <td>512862.0</td>\n",
" <td>121841.0</td>\n",
" <td>2.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>147868</th>\n",
" <td>5124516</td>\n",
" <td>33.342276</td>\n",
" <td>17</td>\n",
" <td>-58</td>\n",
" <td>0.228863</td>\n",
" <td>512856.925464</td>\n",
" <td>121829.218203</td>\n",
" <td>24.377198</td>\n",
" <td>1018654</td>\n",
" <td>8011.0</td>\n",
" <td>1025</td>\n",
" <td>304.0</td>\n",
" <td>2.0</td>\n",
" <td>512862.0</td>\n",
" <td>121841.0</td>\n",
" <td>2.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>147869</th>\n",
" <td>5124517</td>\n",
" <td>43.358052</td>\n",
" <td>13</td>\n",
" <td>122</td>\n",
" <td>0.189882</td>\n",
" <td>512853.120003</td>\n",
" <td>121831.545790</td>\n",
" <td>26.787103</td>\n",
" <td>1018654</td>\n",
" <td>8011.0</td>\n",
" <td>1025</td>\n",
" <td>304.0</td>\n",
" <td>2.0</td>\n",
" <td>512862.0</td>\n",
" <td>121841.0</td>\n",
" <td>2.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>147870</th>\n",
" <td>5124518</td>\n",
" <td>34.768271</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.250965</td>\n",
" <td>512851.074627</td>\n",
" <td>121838.634710</td>\n",
" <td>29.085365</td>\n",
" <td>1018654</td>\n",
" <td>8011.0</td>\n",
" <td>1025</td>\n",
" <td>304.0</td>\n",
" <td>2.0</td>\n",
" <td>512862.0</td>\n",
" <td>121841.0</td>\n",
" <td>2.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>147871</th>\n",
" <td>5124523</td>\n",
" <td>202.860586</td>\n",
" <td>26</td>\n",
" <td>-65</td>\n",
" <td>0.114355</td>\n",
" <td>512906.933121</td>\n",
" <td>121907.819462</td>\n",
" <td>69.264065</td>\n",
" <td>1018655</td>\n",
" <td>8014.0</td>\n",
" <td>1025</td>\n",
" <td>148.0</td>\n",
" <td>3.0</td>\n",
" <td>512908.0</td>\n",
" <td>121915.0</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>147872</th>\n",
" <td>5124524</td>\n",
" <td>221.668609</td>\n",
" <td>25</td>\n",
" <td>115</td>\n",
" <td>0.107353</td>\n",
" <td>512900.901794</td>\n",
" <td>121911.006917</td>\n",
" <td>72.136766</td>\n",
" <td>1018655</td>\n",
" <td>8014.0</td>\n",
" <td>1025</td>\n",
" <td>148.0</td>\n",
" <td>3.0</td>\n",
" <td>512908.0</td>\n",
" <td>121915.0</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>147873</th>\n",
" <td>5124525</td>\n",
" <td>126.405824</td>\n",
" <td>22</td>\n",
" <td>118</td>\n",
" <td>0.111160</td>\n",
" <td>512800.694862</td>\n",
" <td>121763.497186</td>\n",
" <td>43.276794</td>\n",
" <td>1018651</td>\n",
" <td>8013.0</td>\n",
" <td>1030</td>\n",
" <td>181.0</td>\n",
" <td>3.0</td>\n",
" <td>512806.0</td>\n",
" <td>121761.0</td>\n",
" <td>2.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>147874</th>\n",
" <td>5124526</td>\n",
" <td>126.408740</td>\n",
" <td>22</td>\n",
" <td>-62</td>\n",
" <td>0.111159</td>\n",
" <td>512809.763984</td>\n",
" <td>121758.593080</td>\n",
" <td>43.277184</td>\n",
" <td>1018651</td>\n",
" <td>8013.0</td>\n",
" <td>1030</td>\n",
" <td>181.0</td>\n",
" <td>3.0</td>\n",
" <td>512806.0</td>\n",
" <td>121761.0</td>\n",
" <td>2.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>147875 rows × 16 columns</p>\n",
"</div>"
],
"text/plain": [
" DF_UID FLAECHE NEIGUNG AUSRICHTUN BUF30_Perc XCOORD \\\n",
"0 4879561 46.507495 34 39 0.245521 493478.741922 \n",
"1 4879562 65.822671 28 -141 0.182859 493481.191087 \n",
"2 4879563 33.159751 41 -51 0.315406 493484.502179 \n",
"3 4879564 35.956510 11 -51 0.224638 493486.994637 \n",
"4 4879565 23.465989 36 129 0.325512 493481.402009 \n",
"5 4879567 26.304688 19 -143 0.252403 493463.360632 \n",
"6 4879568 25.396184 20 37 0.259015 493461.198117 \n",
"7 4879576 56.425414 37 -131 0.188028 493858.430044 \n",
"8 4879577 56.416744 37 49 0.188055 493854.908406 \n",
"9 4879586 27.906263 0 0 0.232186 494064.425856 \n",
"10 4879589 63.060851 6 -135 0.239073 494069.811943 \n",
"11 4879590 98.456303 33 -45 0.161719 494052.448592 \n",
"12 4879591 119.977310 29 135 0.151186 494049.441085 \n",
"13 4879592 52.899653 19 135 0.187633 494043.853986 \n",
"14 4879593 257.117999 11 -45 0.079582 494066.645138 \n",
"15 4879594 332.516025 9 135 0.067697 494056.369323 \n",
"16 4879595 210.472123 8 -45 0.089134 494047.083075 \n",
"17 4879596 28.356617 16 135 0.494003 494043.105026 \n",
"18 4879597 146.037528 5 -45 0.107666 494074.156498 \n",
"19 4879598 49.542742 4 -45 0.185587 494058.505654 \n",
"20 4879599 19.554210 3 -45 0.280526 494064.725821 \n",
"21 4879600 24.972216 9 135 0.256793 494067.799175 \n",
"22 4879601 27.299810 15 135 0.244460 494070.939006 \n",
"23 4879587 87.360724 30 -138 0.154336 494028.864196 \n",
"24 4879588 85.970456 31 42 0.156790 494025.290758 \n",
"25 4879603 55.782605 22 141 0.171559 495600.894977 \n",
"26 4879604 72.169621 24 -39 0.150722 495605.063345 \n",
"27 4879605 146.924324 29 -21 0.131341 495595.680394 \n",
"28 4879606 149.955503 28 159 0.128607 495593.606354 \n",
"29 4879607 112.779260 28 -21 0.139096 495570.308703 \n",
"... ... ... ... ... ... ... \n",
"147845 5124479 201.344527 28 -57 0.110559 512580.233215 \n",
"147846 5124480 222.078136 28 123 0.110206 512574.241420 \n",
"147847 5124481 88.795794 23 -147 0.149423 512584.730873 \n",
"147848 5124483 75.633549 30 -147 0.169608 512606.304400 \n",
"147849 5124484 96.109368 31 33 0.143688 512603.387815 \n",
"147850 5124488 165.220451 20 -53 0.101590 512634.079435 \n",
"147851 5124489 239.812345 22 126 0.088074 512628.613532 \n",
"147852 5124490 46.693778 24 -147 0.197704 512638.808717 \n",
"147853 5124491 112.466072 29 -64 0.120936 512521.577577 \n",
"147854 5124492 108.203352 30 116 0.124360 512513.364438 \n",
"147855 5124493 76.814349 32 -64 0.153423 512515.570905 \n",
"147856 5124494 63.680411 30 116 0.169030 512510.329761 \n",
"147857 5124495 27.490066 21 116 0.292291 512506.735714 \n",
"147858 5124497 139.413591 30 -60 0.134461 512727.438593 \n",
"147859 5124498 137.530298 30 120 0.135168 512721.597769 \n",
"147860 5124499 92.630815 7 -150 0.153851 512730.885097 \n",
"147861 5124500 44.081253 7 -148 0.196382 512734.198663 \n",
"147862 5124501 12.602429 0 0 0.354338 512727.121243 \n",
"147863 5124502 14.119724 11 -147 0.363318 512728.749164 \n",
"147864 5124512 131.925651 29 121 0.145503 512861.001267 \n",
"147865 5124513 137.339196 28 -59 0.139416 512865.436278 \n",
"147866 5124514 21.008432 23 -150 0.358840 512862.267927 \n",
"147867 5124515 21.541363 19 30 0.288923 512860.316121 \n",
"147868 5124516 33.342276 17 -58 0.228863 512856.925464 \n",
"147869 5124517 43.358052 13 122 0.189882 512853.120003 \n",
"147870 5124518 34.768271 0 0 0.250965 512851.074627 \n",
"147871 5124523 202.860586 26 -65 0.114355 512906.933121 \n",
"147872 5124524 221.668609 25 115 0.107353 512900.901794 \n",
"147873 5124525 126.405824 22 118 0.111160 512800.694862 \n",
"147874 5124526 126.408740 22 -62 0.111159 512809.763984 \n",
"\n",
" YCOORD SHAPE_Leng GWR_EGID GBAUP GKAT GAREA GASTW \\\n",
"0 122044.537267 31.477187 1020549 8012.0 1021 71.0 1.0 \n",
"1 122047.635869 35.355795 1020549 8012.0 1021 71.0 1.0 \n",
"2 122038.094141 26.367892 1020549 8012.0 1021 71.0 1.0 \n",
"3 122036.384922 26.383903 1020549 8012.0 1021 71.0 1.0 \n",
"4 122038.122620 20.596973 1020549 8012.0 1021 71.0 1.0 \n",
"5 122094.162534 20.943016 2041392 8014.0 1021 24.0 1.0 \n",
"6 122091.312567 20.661054 2041392 8014.0 1021 24.0 1.0 \n",
"7 122063.995365 28.247269 1020551 8012.0 1021 48.0 3.0 \n",
"8 122060.966845 28.245385 1020551 8012.0 1021 48.0 3.0 \n",
"9 122139.775622 21.598115 1020550 8012.0 1021 166.0 3.0 \n",
"10 122166.993289 49.943631 1020550 8012.0 1021 166.0 3.0 \n",
"11 122141.856383 44.467793 1020550 8012.0 1021 166.0 3.0 \n",
"12 122146.960720 52.694179 1020550 8012.0 1021 166.0 3.0 \n",
"13 122145.861717 31.285857 1020550 8012.0 1021 166.0 3.0 \n",
"14 122153.737354 66.901310 1020550 8012.0 1021 166.0 3.0 \n",
"15 122163.753664 74.097563 1020550 8012.0 1021 166.0 3.0 \n",
"16 122172.564987 61.977891 1020550 8012.0 1021 166.0 3.0 \n",
"17 122176.486925 44.787707 1020550 8012.0 1021 166.0 3.0 \n",
"18 122146.950960 52.205428 1020550 8012.0 1021 166.0 3.0 \n",
"19 122134.230225 30.581988 1020550 8012.0 1021 166.0 3.0 \n",
"20 122133.170932 18.250880 1020550 8012.0 1021 166.0 3.0 \n",
"21 122136.633782 21.123500 1020550 8012.0 1021 166.0 3.0 \n",
"22 122134.093766 21.521896 1020550 8012.0 1021 166.0 3.0 \n",
"23 122210.211756 38.734764 2041393 8011.0 1021 91.0 2.0 \n",
"24 122206.261441 38.502663 2041393 8011.0 1021 91.0 2.0 \n",
"25 122215.511491 29.601988 1020569 8013.0 1021 75.0 1.0 \n",
"26 122210.549004 33.216251 1020569 8013.0 1021 75.0 1.0 \n",
"27 122037.585238 56.349336 3131860 8019.0 1021 58.0 3.0 \n",
"28 122043.015684 56.656931 3131860 8019.0 1021 58.0 3.0 \n",
"29 122025.955633 46.369998 2041363 8019.0 1021 58.0 1.0 \n",
"... ... ... ... ... ... ... ... \n",
"147845 121889.136842 65.261998 1018649 8011.0 1030 281.0 3.0 \n",
"147846 121894.372239 71.750997 1018649 8011.0 1030 281.0 3.0 \n",
"147847 121903.726978 40.629952 1018649 8011.0 1030 281.0 3.0 \n",
"147848 121901.560650 37.171831 1018650 8015.0 1025 95.0 3.0 \n",
"147849 121897.055040 39.628036 1018650 8015.0 1025 95.0 3.0 \n",
"147850 121751.577376 52.477312 1018656 8011.0 1021 313.0 2.0 \n",
"147851 121760.935293 65.063152 1018656 8011.0 1021 313.0 2.0 \n",
"147852 121762.936532 28.070510 1018656 8011.0 1021 313.0 2.0 \n",
"147853 121873.022662 39.762596 295081617 8017.0 1060 110.0 1.0 \n",
"147854 121877.059813 38.853185 295081617 8017.0 1060 110.0 1.0 \n",
"147855 121864.378429 33.214762 295081617 8017.0 1060 110.0 1.0 \n",
"147856 121867.086155 31.106354 295081617 8017.0 1060 110.0 1.0 \n",
"147857 121868.942467 24.997104 295081617 8017.0 1060 110.0 1.0 \n",
"147858 121799.488883 54.005430 1018653 8012.0 1025 153.0 3.0 \n",
"147859 121802.956658 53.905711 1018653 8012.0 1025 153.0 3.0 \n",
"147860 121812.056608 47.143675 1018653 8012.0 1025 153.0 3.0 \n",
"147861 121817.788002 28.618486 1018653 8012.0 1025 153.0 3.0 \n",
"147862 121820.215342 14.885065 1018653 8012.0 1025 153.0 3.0 \n",
"147863 121822.557834 16.789635 1018653 8012.0 1025 153.0 3.0 \n",
"147864 121844.951885 55.702429 1018654 8011.0 1025 304.0 2.0 \n",
"147865 121842.297555 56.243851 1018654 8011.0 1025 304.0 2.0 \n",
"147866 121857.440814 23.119281 1018654 8011.0 1025 304.0 2.0 \n",
"147867 121855.330158 19.585625 1018654 8011.0 1025 304.0 2.0 \n",
"147868 121829.218203 24.377198 1018654 8011.0 1025 304.0 2.0 \n",
"147869 121831.545790 26.787103 1018654 8011.0 1025 304.0 2.0 \n",
"147870 121838.634710 29.085365 1018654 8011.0 1025 304.0 2.0 \n",
"147871 121907.819462 69.264065 1018655 8014.0 1025 148.0 3.0 \n",
"147872 121911.006917 72.136766 1018655 8014.0 1025 148.0 3.0 \n",
"147873 121763.497186 43.276794 1018651 8013.0 1030 181.0 3.0 \n",
"147874 121758.593080 43.277184 1018651 8013.0 1030 181.0 3.0 \n",
"\n",
" GKODX GKODY n_neighbors_100 \n",
"0 493481.0 122046.0 1.0 \n",
"1 493481.0 122046.0 1.0 \n",
"2 493481.0 122046.0 1.0 \n",
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"13 494050.0 122145.0 1.0 \n",
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"15 494050.0 122145.0 1.0 \n",
"16 494050.0 122145.0 1.0 \n",
"17 494050.0 122145.0 1.0 \n",
"18 494050.0 122145.0 1.0 \n",
"19 494050.0 122145.0 1.0 \n",
"20 494050.0 122145.0 1.0 \n",
"21 494050.0 122145.0 1.0 \n",
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"27 495588.0 122037.0 12.0 \n",
"28 495588.0 122037.0 12.0 \n",
"29 495564.0 122026.0 14.0 \n",
"... ... ... ... \n",
"147845 512578.0 121893.0 2.0 \n",
"147846 512578.0 121893.0 2.0 \n",
"147847 512578.0 121893.0 2.0 \n",
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"147851 512631.0 121756.0 7.0 \n",
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"147856 512513.0 121866.0 2.0 \n",
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"147863 512725.0 121800.0 3.0 \n",
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"147874 512806.0 121761.0 2.0 \n",
"\n",
"[147875 rows x 16 columns]"
]
},
"execution_count": 73,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ROOFS = find_neighbors(ROOFS, radius=100)"
]
},
{
"cell_type": "code",
"execution_count": 45,
"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\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\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>"
]
},
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"output_type": "display_data"
},
{
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\" width=\"640\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"(484848.8492159098, 514244.15078409016, 109455.89894775776, 131304.10105224221)"
]
},
"execution_count": 45,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"plt.scatter(building_neighbors.GKODX, building_neighbors.GKODY, c = building_neighbors.n_neighbors, s=0.5, vmax=25)\n",
"plt.colorbar()\n",
"plt.axis('equal')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Load shading data"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [],
"source": [
"# load shading data for 50cm DOM with 40% visibility threshold - FEATURES\n",
"horizon_50cm_vis40 = '/Users/alinawalch/Documents/EPFL/data/rooftops/shading_images/visibility/summary_stats_vis_40_50cm.csv'\n",
"horizon_50cm_vis40 = pd.read_csv(horizon_50cm_vis40, sep='|')\n",
"horizon_50cm_vis40 = horizon_50cm_vis40.loc[:,['zone', 'non_null_cells', 'null_cells']]\n",
"horizon_50cm_vis40['n_cells'] = horizon_50cm_vis40.non_null_cells + horizon_50cm_vis40.null_cells\n",
"horizon_50cm_vis40['fully_shaded_ratio'] = horizon_50cm_vis40.null_cells / horizon_50cm_vis40.n_cells\n",
"\n",
"horizon_50cm = horizon_50cm_vis40.merge(ROOFS, how='inner', right_on='DF_UID', left_on = 'zone')"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
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" <th></th>\n",
" <th>zone</th>\n",
" <th>non_null_cells</th>\n",
" <th>null_cells</th>\n",
" <th>n_cells</th>\n",
" <th>fully_shaded_ratio</th>\n",
" <th>DF_UID</th>\n",
" <th>FLAECHE</th>\n",
" <th>NEIGUNG</th>\n",
" <th>AUSRICHTUN</th>\n",
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" <th>n_neighbors</th>\n",
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" </thead>\n",
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" <th>0</th>\n",
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" <td>5159</td>\n",
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" <td>1019783</td>\n",
" <td>8014.0</td>\n",
" <td>1025</td>\n",
" <td>243.0</td>\n",
" <td>9.0</td>\n",
" <td>497506.0</td>\n",
" <td>116080.0</td>\n",
" <td>5.0</td>\n",
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" <th>1</th>\n",
" <td>4965783</td>\n",
" <td>1487</td>\n",
" <td>34</td>\n",
" <td>1521</td>\n",
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" <td>4965783</td>\n",
" <td>560.036571</td>\n",
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" <td>0.052521</td>\n",
" <td>...</td>\n",
" <td>97.901422</td>\n",
" <td>295009928</td>\n",
" <td>295009928</td>\n",
" <td>8014.0</td>\n",
" <td>1060</td>\n",
" <td>641.0</td>\n",
" <td>1.0</td>\n",
" <td>497498.0</td>\n",
" <td>116020.0</td>\n",
" <td>7.0</td>\n",
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" <th>2</th>\n",
" <td>4965784</td>\n",
" <td>254</td>\n",
" <td>40</td>\n",
" <td>294</td>\n",
" <td>0.136054</td>\n",
" <td>4965784</td>\n",
" <td>73.745743</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.180812</td>\n",
" <td>...</td>\n",
" <td>44.447665</td>\n",
" <td>295009928</td>\n",
" <td>295009928</td>\n",
" <td>8014.0</td>\n",
" <td>1060</td>\n",
" <td>641.0</td>\n",
" <td>1.0</td>\n",
" <td>497498.0</td>\n",
" <td>116020.0</td>\n",
" <td>7.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>4965785</td>\n",
" <td>370</td>\n",
" <td>21</td>\n",
" <td>391</td>\n",
" <td>0.053708</td>\n",
" <td>4965785</td>\n",
" <td>204.889465</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.126366</td>\n",
" <td>...</td>\n",
" <td>86.303247</td>\n",
" <td>1019785</td>\n",
" <td>1019785</td>\n",
" <td>8014.0</td>\n",
" <td>1025</td>\n",
" <td>241.0</td>\n",
" <td>9.0</td>\n",
" <td>497519.0</td>\n",
" <td>116052.0</td>\n",
" <td>5.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>4965875</td>\n",
" <td>139</td>\n",
" <td>29</td>\n",
" <td>168</td>\n",
" <td>0.172619</td>\n",
" <td>4965875</td>\n",
" <td>41.788788</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.208260</td>\n",
" <td>...</td>\n",
" <td>29.008722</td>\n",
" <td>1019776</td>\n",
" <td>1019776</td>\n",
" <td>8015.0</td>\n",
" <td>1025</td>\n",
" <td>389.0</td>\n",
" <td>23.0</td>\n",
" <td>497446.0</td>\n",
" <td>116074.0</td>\n",
" <td>6.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>4965876</td>\n",
" <td>2125</td>\n",
" <td>641</td>\n",
" <td>2766</td>\n",
" <td>0.231743</td>\n",
" <td>4965876</td>\n",
" <td>2635.931059</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.028215</td>\n",
" <td>...</td>\n",
" <td>247.909594</td>\n",
" <td>1019776</td>\n",
" <td>1019776</td>\n",
" <td>8015.0</td>\n",
" <td>1025</td>\n",
" <td>389.0</td>\n",
" <td>23.0</td>\n",
" <td>497446.0</td>\n",
" <td>116074.0</td>\n",
" <td>6.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>4965878</td>\n",
" <td>966</td>\n",
" <td>34</td>\n",
" <td>1000</td>\n",
" <td>0.034000</td>\n",
" <td>4965878</td>\n",
" <td>1938.065681</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.040140</td>\n",
" <td>...</td>\n",
" <td>259.313613</td>\n",
" <td>1019776</td>\n",
" <td>1019776</td>\n",
" <td>8015.0</td>\n",
" <td>1025</td>\n",
" <td>389.0</td>\n",
" <td>23.0</td>\n",
" <td>497446.0</td>\n",
" <td>116074.0</td>\n",
" <td>6.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>4965879</td>\n",
" <td>456</td>\n",
" <td>272</td>\n",
" <td>728</td>\n",
" <td>0.373626</td>\n",
" <td>4965879</td>\n",
" <td>182.631292</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.096756</td>\n",
" <td>...</td>\n",
" <td>58.902105</td>\n",
" <td>1019776</td>\n",
" <td>1019776</td>\n",
" <td>8015.0</td>\n",
" <td>1025</td>\n",
" <td>389.0</td>\n",
" <td>23.0</td>\n",
" <td>497446.0</td>\n",
" <td>116074.0</td>\n",
" <td>6.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>4965884</td>\n",
" <td>567</td>\n",
" <td>187</td>\n",
" <td>754</td>\n",
" <td>0.248011</td>\n",
" <td>4965884</td>\n",
" <td>636.709326</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.121819</td>\n",
" <td>...</td>\n",
" <td>258.545440</td>\n",
" <td>1019776</td>\n",
" <td>1019776</td>\n",
" <td>8015.0</td>\n",
" <td>1025</td>\n",
" <td>389.0</td>\n",
" <td>23.0</td>\n",
" <td>497446.0</td>\n",
" <td>116074.0</td>\n",
" <td>6.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>4965886</td>\n",
" <td>1069</td>\n",
" <td>105</td>\n",
" <td>1174</td>\n",
" <td>0.089438</td>\n",
" <td>4965886</td>\n",
" <td>293.774672</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.102103</td>\n",
" <td>...</td>\n",
" <td>99.982577</td>\n",
" <td>1019787</td>\n",
" <td>1019787</td>\n",
" <td>8014.0</td>\n",
" <td>1025</td>\n",
" <td>315.0</td>\n",
" <td>9.0</td>\n",
" <td>497533.0</td>\n",
" <td>116021.0</td>\n",
" <td>3.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>4966558</td>\n",
" <td>158</td>\n",
" <td>5</td>\n",
" <td>163</td>\n",
" <td>0.030675</td>\n",
" <td>4966558</td>\n",
" <td>3107.350962</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.035727</td>\n",
" <td>...</td>\n",
" <td>370.049530</td>\n",
" <td>1019798</td>\n",
" <td>1019798</td>\n",
" <td>8014.0</td>\n",
" <td>1025</td>\n",
" <td>344.0</td>\n",
" <td>8.0</td>\n",
" <td>497483.0</td>\n",
" <td>116306.0</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>4972728</td>\n",
" <td>14</td>\n",
" <td>11</td>\n",
" <td>25</td>\n",
" <td>0.440000</td>\n",
" <td>4972728</td>\n",
" <td>125.197892</td>\n",
" <td>24</td>\n",
" <td>-95</td>\n",
" <td>0.134290</td>\n",
" <td>...</td>\n",
" <td>51.322510</td>\n",
" <td>1016396</td>\n",
" <td>1016396</td>\n",
" <td>8013.0</td>\n",
" <td>1025</td>\n",
" <td>179.0</td>\n",
" <td>3.0</td>\n",
" <td>497486.0</td>\n",
" <td>117967.0</td>\n",
" <td>3.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>4972729</td>\n",
" <td>391</td>\n",
" <td>11</td>\n",
" <td>402</td>\n",
" <td>0.027363</td>\n",
" <td>4972729</td>\n",
" <td>124.174089</td>\n",
" <td>23</td>\n",
" <td>102</td>\n",
" <td>0.135529</td>\n",
" <td>...</td>\n",
" <td>51.558776</td>\n",
" <td>1016395</td>\n",
" <td>1016395</td>\n",
" <td>8013.0</td>\n",
" <td>1025</td>\n",
" <td>179.0</td>\n",
" <td>3.0</td>\n",
" <td>497496.0</td>\n",
" <td>117997.0</td>\n",
" <td>3.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>4972730</td>\n",
" <td>435</td>\n",
" <td>3</td>\n",
" <td>438</td>\n",
" <td>0.006849</td>\n",
" <td>4972730</td>\n",
" <td>119.978332</td>\n",
" <td>24</td>\n",
" <td>-78</td>\n",
" <td>0.139948</td>\n",
" <td>...</td>\n",
" <td>51.104449</td>\n",
" <td>1016395</td>\n",
" <td>1016395</td>\n",
" <td>8013.0</td>\n",
" <td>1025</td>\n",
" <td>179.0</td>\n",
" <td>3.0</td>\n",
" <td>497496.0</td>\n",
" <td>117997.0</td>\n",
" <td>3.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>4976075</td>\n",
" <td>5</td>\n",
" <td>0</td>\n",
" <td>5</td>\n",
" <td>0.000000</td>\n",
" <td>4976075</td>\n",
" <td>394.834081</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.194787</td>\n",
" <td>...</td>\n",
" <td>256.361342</td>\n",
" <td>1028525</td>\n",
" <td>1028525</td>\n",
" <td>8015.0</td>\n",
" <td>1030</td>\n",
" <td>418.0</td>\n",
" <td>4.0</td>\n",
" <td>497466.0</td>\n",
" <td>118420.0</td>\n",
" <td>5.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>4977601</td>\n",
" <td>1185</td>\n",
" <td>1</td>\n",
" <td>1186</td>\n",
" <td>0.000843</td>\n",
" <td>4977601</td>\n",
" <td>661.683103</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.061522</td>\n",
" <td>...</td>\n",
" <td>135.693397</td>\n",
" <td>2043187</td>\n",
" <td>2043187</td>\n",
" <td>8013.0</td>\n",
" <td>1060</td>\n",
" <td>653.0</td>\n",
" <td>4.0</td>\n",
" <td>497488.0</td>\n",
" <td>118636.0</td>\n",
" <td>3.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>4981768</td>\n",
" <td>31</td>\n",
" <td>128</td>\n",
" <td>159</td>\n",
" <td>0.805031</td>\n",
" <td>4981768</td>\n",
" <td>167.410586</td>\n",
" <td>7</td>\n",
" <td>21</td>\n",
" <td>0.126249</td>\n",
" <td>...</td>\n",
" <td>69.973945</td>\n",
" <td>295101875</td>\n",
" <td>295101875</td>\n",
" <td>8014.0</td>\n",
" <td>1060</td>\n",
" <td>142.0</td>\n",
" <td>1.0</td>\n",
" <td>497485.0</td>\n",
" <td>118807.0</td>\n",
" <td>10.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td>5031245</td>\n",
" <td>2535</td>\n",
" <td>181</td>\n",
" <td>2716</td>\n",
" <td>0.066642</td>\n",
" <td>5031245</td>\n",
" <td>939.826579</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.071570</td>\n",
" <td>...</td>\n",
" <td>224.210407</td>\n",
" <td>2040612</td>\n",
" <td>2040612</td>\n",
" <td>8018.0</td>\n",
" <td>1060</td>\n",
" <td>1244.0</td>\n",
" <td>5.0</td>\n",
" <td>497672.0</td>\n",
" <td>115975.0</td>\n",
" <td>5.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>5031246</td>\n",
" <td>457</td>\n",
" <td>2</td>\n",
" <td>459</td>\n",
" <td>0.004357</td>\n",
" <td>5031246</td>\n",
" <td>1186.279210</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.069947</td>\n",
" <td>...</td>\n",
" <td>276.588492</td>\n",
" <td>2040612</td>\n",
" <td>2040612</td>\n",
" <td>8018.0</td>\n",
" <td>1060</td>\n",
" <td>1244.0</td>\n",
" <td>5.0</td>\n",
" <td>497672.0</td>\n",
" <td>115975.0</td>\n",
" <td>5.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td>5031249</td>\n",
" <td>2155</td>\n",
" <td>140</td>\n",
" <td>2295</td>\n",
" <td>0.061002</td>\n",
" <td>5031249</td>\n",
" <td>818.552360</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.076566</td>\n",
" <td>...</td>\n",
" <td>208.911747</td>\n",
" <td>2040612</td>\n",
" <td>2040612</td>\n",
" <td>8018.0</td>\n",
" <td>1060</td>\n",
" <td>1244.0</td>\n",
" <td>5.0</td>\n",
" <td>497672.0</td>\n",
" <td>115975.0</td>\n",
" <td>5.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>5031254</td>\n",
" <td>160</td>\n",
" <td>2</td>\n",
" <td>162</td>\n",
" <td>0.012346</td>\n",
" <td>5031254</td>\n",
" <td>40.755698</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.214383</td>\n",
" <td>...</td>\n",
" <td>29.124265</td>\n",
" <td>2040612</td>\n",
" <td>2040612</td>\n",
" <td>8018.0</td>\n",
" <td>1060</td>\n",
" <td>1244.0</td>\n",
" <td>5.0</td>\n",
" <td>497672.0</td>\n",
" <td>115975.0</td>\n",
" <td>5.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>5031260</td>\n",
" <td>102</td>\n",
" <td>27</td>\n",
" <td>129</td>\n",
" <td>0.209302</td>\n",
" <td>5031260</td>\n",
" <td>32.506871</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.263408</td>\n",
" <td>...</td>\n",
" <td>28.542027</td>\n",
" <td>2040612</td>\n",
" <td>2040612</td>\n",
" <td>8018.0</td>\n",
" <td>1060</td>\n",
" <td>1244.0</td>\n",
" <td>5.0</td>\n",
" <td>497672.0</td>\n",
" <td>115975.0</td>\n",
" <td>5.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td>5031269</td>\n",
" <td>138</td>\n",
" <td>14</td>\n",
" <td>152</td>\n",
" <td>0.092105</td>\n",
" <td>5031269</td>\n",
" <td>38.084736</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.218424</td>\n",
" <td>...</td>\n",
" <td>27.728889</td>\n",
" <td>2040612</td>\n",
" <td>2040612</td>\n",
" <td>8018.0</td>\n",
" <td>1060</td>\n",
" <td>1244.0</td>\n",
" <td>5.0</td>\n",
" <td>497672.0</td>\n",
" <td>115975.0</td>\n",
" <td>5.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23</th>\n",
" <td>5031275</td>\n",
" <td>106</td>\n",
" <td>26</td>\n",
" <td>132</td>\n",
" <td>0.196970</td>\n",
" <td>5031275</td>\n",
" <td>33.370309</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.258869</td>\n",
" <td>...</td>\n",
" <td>28.795176</td>\n",
" <td>2040612</td>\n",
" <td>2040612</td>\n",
" <td>8018.0</td>\n",
" <td>1060</td>\n",
" <td>1244.0</td>\n",
" <td>5.0</td>\n",
" <td>497672.0</td>\n",
" <td>115975.0</td>\n",
" <td>5.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24</th>\n",
" <td>5031603</td>\n",
" <td>13</td>\n",
" <td>7</td>\n",
" <td>20</td>\n",
" <td>0.350000</td>\n",
" <td>5031603</td>\n",
" <td>211.987975</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.215162</td>\n",
" <td>...</td>\n",
" <td>152.039389</td>\n",
" <td>2034928</td>\n",
" <td>2034928</td>\n",
" <td>8015.0</td>\n",
" <td>1060</td>\n",
" <td>1744.0</td>\n",
" <td>7.0</td>\n",
" <td>498874.0</td>\n",
" <td>115929.0</td>\n",
" <td>5.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25</th>\n",
" <td>5031660</td>\n",
" <td>82</td>\n",
" <td>8</td>\n",
" <td>90</td>\n",
" <td>0.088889</td>\n",
" <td>5031660</td>\n",
" <td>21.434018</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.260876</td>\n",
" <td>...</td>\n",
" <td>18.638709</td>\n",
" <td>1002959</td>\n",
" <td>1002959</td>\n",
" <td>8016.0</td>\n",
" <td>1030</td>\n",
" <td>229.0</td>\n",
" <td>5.0</td>\n",
" <td>499221.0</td>\n",
" <td>116005.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>26</th>\n",
" <td>5031667</td>\n",
" <td>215</td>\n",
" <td>11</td>\n",
" <td>226</td>\n",
" <td>0.048673</td>\n",
" <td>5031667</td>\n",
" <td>86.622891</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.216379</td>\n",
" <td>...</td>\n",
" <td>62.476428</td>\n",
" <td>1002959</td>\n",
" <td>1002959</td>\n",
" <td>8016.0</td>\n",
" <td>1030</td>\n",
" <td>229.0</td>\n",
" <td>5.0</td>\n",
" <td>499221.0</td>\n",
" <td>116005.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>27</th>\n",
" <td>5031668</td>\n",
" <td>149</td>\n",
" <td>191</td>\n",
" <td>340</td>\n",
" <td>0.561765</td>\n",
" <td>5031668</td>\n",
" <td>94.583084</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.280869</td>\n",
" <td>...</td>\n",
" <td>88.551837</td>\n",
" <td>1002959</td>\n",
" <td>1002959</td>\n",
" <td>8016.0</td>\n",
" <td>1030</td>\n",
" <td>229.0</td>\n",
" <td>5.0</td>\n",
" <td>499221.0</td>\n",
" <td>116005.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>28</th>\n",
" <td>5031695</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" <td>3</td>\n",
" <td>0.000000</td>\n",
" <td>5031695</td>\n",
" <td>568.139425</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.462961</td>\n",
" <td>...</td>\n",
" <td>876.753854</td>\n",
" <td>2034930</td>\n",
" <td>2034930</td>\n",
" <td>8018.0</td>\n",
" <td>1060</td>\n",
" <td>3622.0</td>\n",
" <td>6.0</td>\n",
" <td>499102.0</td>\n",
" <td>115935.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>30</th>\n",
" <td>5031703</td>\n",
" <td>165</td>\n",
" <td>33</td>\n",
" <td>198</td>\n",
" <td>0.166667</td>\n",
" <td>5031703</td>\n",
" <td>1749.853582</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.151529</td>\n",
" <td>...</td>\n",
" <td>883.846590</td>\n",
" <td>2034930</td>\n",
" <td>2034930</td>\n",
" <td>8018.0</td>\n",
" <td>1060</td>\n",
" <td>3622.0</td>\n",
" <td>6.0</td>\n",
" <td>499102.0</td>\n",
" <td>115935.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>30701</th>\n",
" <td>5097073</td>\n",
" <td>2</td>\n",
" <td>209</td>\n",
" <td>211</td>\n",
" <td>0.990521</td>\n",
" <td>5097073</td>\n",
" <td>53.010729</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.169895</td>\n",
" <td>...</td>\n",
" <td>30.020978</td>\n",
" <td>1014767</td>\n",
" <td>1014767</td>\n",
" <td>8012.0</td>\n",
" <td>1030</td>\n",
" <td>179.0</td>\n",
" <td>8.0</td>\n",
" <td>500356.0</td>\n",
" <td>118988.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>30702</th>\n",
" <td>5097074</td>\n",
" <td>18</td>\n",
" <td>459</td>\n",
" <td>477</td>\n",
" <td>0.962264</td>\n",
" <td>5097074</td>\n",
" <td>120.454191</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.145204</td>\n",
" <td>...</td>\n",
" <td>58.301827</td>\n",
" <td>1014767</td>\n",
" <td>1014767</td>\n",
" <td>8012.0</td>\n",
" <td>1030</td>\n",
" <td>179.0</td>\n",
" <td>8.0</td>\n",
" <td>500356.0</td>\n",
" <td>118988.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>30703</th>\n",
" <td>5097075</td>\n",
" <td>2</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>0.000000</td>\n",
" <td>5097075</td>\n",
" <td>72.264869</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.216449</td>\n",
" <td>...</td>\n",
" <td>52.140600</td>\n",
" <td>1014767</td>\n",
" <td>1014767</td>\n",
" <td>8012.0</td>\n",
" <td>1030</td>\n",
" <td>179.0</td>\n",
" <td>8.0</td>\n",
" <td>500356.0</td>\n",
" <td>118988.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>30704</th>\n",
" <td>5097076</td>\n",
" <td>183</td>\n",
" <td>20</td>\n",
" <td>203</td>\n",
" <td>0.098522</td>\n",
" <td>5097076</td>\n",
" <td>160.133540</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.242999</td>\n",
" <td>...</td>\n",
" <td>129.706367</td>\n",
" <td>1014767</td>\n",
" <td>1014767</td>\n",
" <td>8012.0</td>\n",
" <td>1030</td>\n",
" <td>179.0</td>\n",
" <td>8.0</td>\n",
" <td>500356.0</td>\n",
" <td>118988.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>30705</th>\n",
" <td>5097080</td>\n",
" <td>71</td>\n",
" <td>22</td>\n",
" <td>93</td>\n",
" <td>0.236559</td>\n",
" <td>5097080</td>\n",
" <td>23.292598</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.309961</td>\n",
" <td>...</td>\n",
" <td>24.066004</td>\n",
" <td>1014767</td>\n",
" <td>1014767</td>\n",
" <td>8012.0</td>\n",
" <td>1030</td>\n",
" <td>179.0</td>\n",
" <td>8.0</td>\n",
" <td>500356.0</td>\n",
" <td>118988.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>30706</th>\n",
" <td>5097081</td>\n",
" <td>1</td>\n",
" <td>72</td>\n",
" <td>73</td>\n",
" <td>0.986301</td>\n",
" <td>5097081</td>\n",
" <td>18.616667</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.358486</td>\n",
" <td>...</td>\n",
" <td>22.245987</td>\n",
" <td>1014767</td>\n",
" <td>1014767</td>\n",
" <td>8012.0</td>\n",
" <td>1030</td>\n",
" <td>179.0</td>\n",
" <td>8.0</td>\n",
" <td>500356.0</td>\n",
" <td>118988.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>30707</th>\n",
" <td>5097086</td>\n",
" <td>358</td>\n",
" <td>99</td>\n",
" <td>457</td>\n",
" <td>0.216630</td>\n",
" <td>5097086</td>\n",
" <td>132.388355</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.258959</td>\n",
" <td>...</td>\n",
" <td>114.277534</td>\n",
" <td>1014795</td>\n",
" <td>1014795</td>\n",
" <td>8017.0</td>\n",
" <td>1040</td>\n",
" <td>818.0</td>\n",
" <td>7.0</td>\n",
" <td>500509.0</td>\n",
" <td>118993.0</td>\n",
" <td>2.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>30708</th>\n",
" <td>5097087</td>\n",
" <td>44</td>\n",
" <td>730</td>\n",
" <td>774</td>\n",
" <td>0.943152</td>\n",
" <td>5097087</td>\n",
" <td>483.483078</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.066900</td>\n",
" <td>...</td>\n",
" <td>107.815944</td>\n",
" <td>1014795</td>\n",
" <td>1014795</td>\n",
" <td>8017.0</td>\n",
" <td>1040</td>\n",
" <td>818.0</td>\n",
" <td>7.0</td>\n",
" <td>500509.0</td>\n",
" <td>118993.0</td>\n",
" <td>2.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>30709</th>\n",
" <td>5097090</td>\n",
" <td>502</td>\n",
" <td>112</td>\n",
" <td>614</td>\n",
" <td>0.182410</td>\n",
" <td>5097090</td>\n",
" <td>161.785347</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.142907</td>\n",
" <td>...</td>\n",
" <td>77.067440</td>\n",
" <td>1014795</td>\n",
" <td>1014795</td>\n",
" <td>8017.0</td>\n",
" <td>1040</td>\n",
" <td>818.0</td>\n",
" <td>7.0</td>\n",
" <td>500509.0</td>\n",
" <td>118993.0</td>\n",
" <td>2.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>30710</th>\n",
" <td>5097092</td>\n",
" <td>46</td>\n",
" <td>10</td>\n",
" <td>56</td>\n",
" <td>0.178571</td>\n",
" <td>5097092</td>\n",
" <td>14.134757</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.319757</td>\n",
" <td>...</td>\n",
" <td>15.065601</td>\n",
" <td>1014795</td>\n",
" <td>1014795</td>\n",
" <td>8017.0</td>\n",
" <td>1040</td>\n",
" <td>818.0</td>\n",
" <td>7.0</td>\n",
" <td>500509.0</td>\n",
" <td>118993.0</td>\n",
" <td>2.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>30711</th>\n",
" <td>5097093</td>\n",
" <td>67</td>\n",
" <td>6</td>\n",
" <td>73</td>\n",
" <td>0.082192</td>\n",
" <td>5097093</td>\n",
" <td>18.313333</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.298996</td>\n",
" <td>...</td>\n",
" <td>18.252096</td>\n",
" <td>1014795</td>\n",
" <td>1014795</td>\n",
" <td>8017.0</td>\n",
" <td>1040</td>\n",
" <td>818.0</td>\n",
" <td>7.0</td>\n",
" <td>500509.0</td>\n",
" <td>118993.0</td>\n",
" <td>2.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>30712</th>\n",
" <td>5097094</td>\n",
" <td>216</td>\n",
" <td>15</td>\n",
" <td>231</td>\n",
" <td>0.064935</td>\n",
" <td>5097094</td>\n",
" <td>201.961897</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.109645</td>\n",
" <td>...</td>\n",
" <td>73.813516</td>\n",
" <td>1014795</td>\n",
" <td>1014795</td>\n",
" <td>8017.0</td>\n",
" <td>1040</td>\n",
" <td>818.0</td>\n",
" <td>7.0</td>\n",
" <td>500509.0</td>\n",
" <td>118993.0</td>\n",
" <td>2.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>30713</th>\n",
" <td>5097097</td>\n",
" <td>12</td>\n",
" <td>204</td>\n",
" <td>216</td>\n",
" <td>0.944444</td>\n",
" <td>5097097</td>\n",
" <td>54.362110</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.300839</td>\n",
" <td>...</td>\n",
" <td>54.514112</td>\n",
" <td>1014795</td>\n",
" <td>1014795</td>\n",
" <td>8017.0</td>\n",
" <td>1040</td>\n",
" <td>818.0</td>\n",
" <td>7.0</td>\n",
" <td>500509.0</td>\n",
" <td>118993.0</td>\n",
" <td>2.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>30714</th>\n",
" <td>5097098</td>\n",
" <td>237</td>\n",
" <td>4</td>\n",
" <td>241</td>\n",
" <td>0.016598</td>\n",
" <td>5097098</td>\n",
" <td>103.289530</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.195073</td>\n",
" <td>...</td>\n",
" <td>67.163530</td>\n",
" <td>1014795</td>\n",
" <td>1014795</td>\n",
" <td>8017.0</td>\n",
" <td>1040</td>\n",
" <td>818.0</td>\n",
" <td>7.0</td>\n",
" <td>500509.0</td>\n",
" <td>118993.0</td>\n",
" <td>2.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>30715</th>\n",
" <td>5097105</td>\n",
" <td>387</td>\n",
" <td>192</td>\n",
" <td>579</td>\n",
" <td>0.331606</td>\n",
" <td>5097105</td>\n",
" <td>204.892636</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.204908</td>\n",
" <td>...</td>\n",
" <td>139.946860</td>\n",
" <td>1014819</td>\n",
" <td>1014819</td>\n",
" <td>8014.0</td>\n",
" <td>1025</td>\n",
" <td>362.0</td>\n",
" <td>5.0</td>\n",
" <td>500247.0</td>\n",
" <td>119026.0</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>30716</th>\n",
" <td>5097106</td>\n",
" <td>583</td>\n",
" <td>39</td>\n",
" <td>622</td>\n",
" <td>0.062701</td>\n",
" <td>5097106</td>\n",
" <td>155.017225</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.104813</td>\n",
" <td>...</td>\n",
" <td>54.159230</td>\n",
" <td>1014819</td>\n",
" <td>1014819</td>\n",
" <td>8014.0</td>\n",
" <td>1025</td>\n",
" <td>362.0</td>\n",
" <td>5.0</td>\n",
" <td>500247.0</td>\n",
" <td>119026.0</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>30717</th>\n",
" <td>5097107</td>\n",
" <td>213</td>\n",
" <td>133</td>\n",
" <td>346</td>\n",
" <td>0.384393</td>\n",
" <td>5097107</td>\n",
" <td>88.500825</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.141080</td>\n",
" <td>...</td>\n",
" <td>41.618960</td>\n",
" <td>1014819</td>\n",
" <td>1014819</td>\n",
" <td>8014.0</td>\n",
" <td>1025</td>\n",
" <td>362.0</td>\n",
" <td>5.0</td>\n",
" <td>500247.0</td>\n",
" <td>119026.0</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>30718</th>\n",
" <td>5097108</td>\n",
" <td>70</td>\n",
" <td>44</td>\n",
" <td>114</td>\n",
" <td>0.385965</td>\n",
" <td>5097108</td>\n",
" <td>28.174149</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.318815</td>\n",
" <td>...</td>\n",
" <td>29.941170</td>\n",
" <td>1014819</td>\n",
" <td>1014819</td>\n",
" <td>8014.0</td>\n",
" <td>1025</td>\n",
" <td>362.0</td>\n",
" <td>5.0</td>\n",
" <td>500247.0</td>\n",
" <td>119026.0</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>30719</th>\n",
" <td>5097109</td>\n",
" <td>1</td>\n",
" <td>3</td>\n",
" <td>4</td>\n",
" <td>0.750000</td>\n",
" <td>5097109</td>\n",
" <td>151.999779</td>\n",
" <td>33</td>\n",
" <td>-63</td>\n",
" <td>0.127348</td>\n",
" <td>...</td>\n",
" <td>54.240235</td>\n",
" <td>1014819</td>\n",
" <td>1014819</td>\n",
" <td>8014.0</td>\n",
" <td>1025</td>\n",
" <td>362.0</td>\n",
" <td>5.0</td>\n",
" <td>500247.0</td>\n",
" <td>119026.0</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>30720</th>\n",
" <td>5097129</td>\n",
" <td>110</td>\n",
" <td>29</td>\n",
" <td>139</td>\n",
" <td>0.208633</td>\n",
" <td>5097129</td>\n",
" <td>109.583732</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.130893</td>\n",
" <td>...</td>\n",
" <td>47.813799</td>\n",
" <td>1014811</td>\n",
" <td>1014811</td>\n",
" <td>8011.0</td>\n",
" <td>1025</td>\n",
" <td>277.0</td>\n",
" <td>8.0</td>\n",
" <td>500261.0</td>\n",
" <td>118955.0</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>30721</th>\n",
" <td>5097130</td>\n",
" <td>196</td>\n",
" <td>5</td>\n",
" <td>201</td>\n",
" <td>0.024876</td>\n",
" <td>5097130</td>\n",
" <td>116.886388</td>\n",
" <td>31</td>\n",
" <td>-62</td>\n",
" <td>0.138579</td>\n",
" <td>...</td>\n",
" <td>46.443726</td>\n",
" <td>1014811</td>\n",
" <td>1014811</td>\n",
" <td>8011.0</td>\n",
" <td>1025</td>\n",
" <td>277.0</td>\n",
" <td>8.0</td>\n",
" <td>500261.0</td>\n",
" <td>118955.0</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>30722</th>\n",
" <td>5097138</td>\n",
" <td>294</td>\n",
" <td>38</td>\n",
" <td>332</td>\n",
" <td>0.114458</td>\n",
" <td>5097138</td>\n",
" <td>98.189777</td>\n",
" <td>33</td>\n",
" <td>-61</td>\n",
" <td>0.145255</td>\n",
" <td>...</td>\n",
" <td>40.062807</td>\n",
" <td>1014811</td>\n",
" <td>1014811</td>\n",
" <td>8011.0</td>\n",
" <td>1025</td>\n",
" <td>277.0</td>\n",
" <td>8.0</td>\n",
" <td>500261.0</td>\n",
" <td>118955.0</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>30723</th>\n",
" <td>5097141</td>\n",
" <td>57</td>\n",
" <td>23</td>\n",
" <td>80</td>\n",
" <td>0.287500</td>\n",
" <td>5097141</td>\n",
" <td>35.341745</td>\n",
" <td>55</td>\n",
" <td>133</td>\n",
" <td>0.362257</td>\n",
" <td>...</td>\n",
" <td>24.241518</td>\n",
" <td>1014811</td>\n",
" <td>1014811</td>\n",
" <td>8011.0</td>\n",
" <td>1025</td>\n",
" <td>277.0</td>\n",
" <td>8.0</td>\n",
" <td>500261.0</td>\n",
" <td>118955.0</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>30724</th>\n",
" <td>5097142</td>\n",
" <td>35</td>\n",
" <td>54</td>\n",
" <td>89</td>\n",
" <td>0.606742</td>\n",
" <td>5097142</td>\n",
" <td>33.443353</td>\n",
" <td>48</td>\n",
" <td>-133</td>\n",
" <td>0.501408</td>\n",
" <td>...</td>\n",
" <td>37.638591</td>\n",
" <td>1014811</td>\n",
" <td>1014811</td>\n",
" <td>8011.0</td>\n",
" <td>1025</td>\n",
" <td>277.0</td>\n",
" <td>8.0</td>\n",
" <td>500261.0</td>\n",
" <td>118955.0</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>30725</th>\n",
" <td>5097143</td>\n",
" <td>332</td>\n",
" <td>16</td>\n",
" <td>348</td>\n",
" <td>0.045977</td>\n",
" <td>5097143</td>\n",
" <td>109.884484</td>\n",
" <td>37</td>\n",
" <td>48</td>\n",
" <td>0.142206</td>\n",
" <td>...</td>\n",
" <td>41.534111</td>\n",
" <td>1014811</td>\n",
" <td>1014811</td>\n",
" <td>8011.0</td>\n",
" <td>1025</td>\n",
" <td>277.0</td>\n",
" <td>8.0</td>\n",
" <td>500261.0</td>\n",
" <td>118955.0</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>30726</th>\n",
" <td>5097144</td>\n",
" <td>1321</td>\n",
" <td>371</td>\n",
" <td>1692</td>\n",
" <td>0.219267</td>\n",
" <td>5097144</td>\n",
" <td>468.788104</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.075506</td>\n",
" <td>...</td>\n",
" <td>117.987055</td>\n",
" <td>1014811</td>\n",
" <td>1014811</td>\n",
" <td>8011.0</td>\n",
" <td>1025</td>\n",
" <td>277.0</td>\n",
" <td>8.0</td>\n",
" <td>500261.0</td>\n",
" <td>118955.0</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>30727</th>\n",
" <td>5097145</td>\n",
" <td>53</td>\n",
" <td>283</td>\n",
" <td>336</td>\n",
" <td>0.842262</td>\n",
" <td>5097145</td>\n",
" <td>90.048705</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.173667</td>\n",
" <td>...</td>\n",
" <td>52.128374</td>\n",
" <td>1014811</td>\n",
" <td>1014811</td>\n",
" <td>8011.0</td>\n",
" <td>1025</td>\n",
" <td>277.0</td>\n",
" <td>8.0</td>\n",
" <td>500261.0</td>\n",
" <td>118955.0</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>30728</th>\n",
" <td>5097147</td>\n",
" <td>705</td>\n",
" <td>24</td>\n",
" <td>729</td>\n",
" <td>0.032922</td>\n",
" <td>5097147</td>\n",
" <td>223.258083</td>\n",
" <td>35</td>\n",
" <td>-62</td>\n",
" <td>0.131254</td>\n",
" <td>...</td>\n",
" <td>79.895403</td>\n",
" <td>1014811</td>\n",
" <td>1014811</td>\n",
" <td>8011.0</td>\n",
" <td>1025</td>\n",
" <td>277.0</td>\n",
" <td>8.0</td>\n",
" <td>500261.0</td>\n",
" <td>118955.0</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>30729</th>\n",
" <td>5097148</td>\n",
" <td>682</td>\n",
" <td>177</td>\n",
" <td>859</td>\n",
" <td>0.206054</td>\n",
" <td>5097148</td>\n",
" <td>214.516672</td>\n",
" <td>1</td>\n",
" <td>118</td>\n",
" <td>0.114318</td>\n",
" <td>...</td>\n",
" <td>81.732726</td>\n",
" <td>1014811</td>\n",
" <td>1014811</td>\n",
" <td>8011.0</td>\n",
" <td>1025</td>\n",
" <td>277.0</td>\n",
" <td>8.0</td>\n",
" <td>500261.0</td>\n",
" <td>118955.0</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>30730</th>\n",
" <td>5097149</td>\n",
" <td>116</td>\n",
" <td>59</td>\n",
" <td>175</td>\n",
" <td>0.337143</td>\n",
" <td>5097149</td>\n",
" <td>42.854700</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.291349</td>\n",
" <td>...</td>\n",
" <td>41.618186</td>\n",
" <td>1014811</td>\n",
" <td>1014811</td>\n",
" <td>8011.0</td>\n",
" <td>1025</td>\n",
" <td>277.0</td>\n",
" <td>8.0</td>\n",
" <td>500261.0</td>\n",
" <td>118955.0</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>24396 rows × 22 columns</p>\n",
"</div>"
],
"text/plain": [
" zone non_null_cells null_cells n_cells fully_shaded_ratio \\\n",
"0 4965782 5013 146 5159 0.028300 \n",
"1 4965783 1487 34 1521 0.022354 \n",
"2 4965784 254 40 294 0.136054 \n",
"3 4965785 370 21 391 0.053708 \n",
"4 4965875 139 29 168 0.172619 \n",
"5 4965876 2125 641 2766 0.231743 \n",
"6 4965878 966 34 1000 0.034000 \n",
"7 4965879 456 272 728 0.373626 \n",
"8 4965884 567 187 754 0.248011 \n",
"9 4965886 1069 105 1174 0.089438 \n",
"10 4966558 158 5 163 0.030675 \n",
"11 4972728 14 11 25 0.440000 \n",
"12 4972729 391 11 402 0.027363 \n",
"13 4972730 435 3 438 0.006849 \n",
"14 4976075 5 0 5 0.000000 \n",
"15 4977601 1185 1 1186 0.000843 \n",
"16 4981768 31 128 159 0.805031 \n",
"17 5031245 2535 181 2716 0.066642 \n",
"18 5031246 457 2 459 0.004357 \n",
"19 5031249 2155 140 2295 0.061002 \n",
"20 5031254 160 2 162 0.012346 \n",
"21 5031260 102 27 129 0.209302 \n",
"22 5031269 138 14 152 0.092105 \n",
"23 5031275 106 26 132 0.196970 \n",
"24 5031603 13 7 20 0.350000 \n",
"25 5031660 82 8 90 0.088889 \n",
"26 5031667 215 11 226 0.048673 \n",
"27 5031668 149 191 340 0.561765 \n",
"28 5031695 3 0 3 0.000000 \n",
"30 5031703 165 33 198 0.166667 \n",
"... ... ... ... ... ... \n",
"30701 5097073 2 209 211 0.990521 \n",
"30702 5097074 18 459 477 0.962264 \n",
"30703 5097075 2 0 2 0.000000 \n",
"30704 5097076 183 20 203 0.098522 \n",
"30705 5097080 71 22 93 0.236559 \n",
"30706 5097081 1 72 73 0.986301 \n",
"30707 5097086 358 99 457 0.216630 \n",
"30708 5097087 44 730 774 0.943152 \n",
"30709 5097090 502 112 614 0.182410 \n",
"30710 5097092 46 10 56 0.178571 \n",
"30711 5097093 67 6 73 0.082192 \n",
"30712 5097094 216 15 231 0.064935 \n",
"30713 5097097 12 204 216 0.944444 \n",
"30714 5097098 237 4 241 0.016598 \n",
"30715 5097105 387 192 579 0.331606 \n",
"30716 5097106 583 39 622 0.062701 \n",
"30717 5097107 213 133 346 0.384393 \n",
"30718 5097108 70 44 114 0.385965 \n",
"30719 5097109 1 3 4 0.750000 \n",
"30720 5097129 110 29 139 0.208633 \n",
"30721 5097130 196 5 201 0.024876 \n",
"30722 5097138 294 38 332 0.114458 \n",
"30723 5097141 57 23 80 0.287500 \n",
"30724 5097142 35 54 89 0.606742 \n",
"30725 5097143 332 16 348 0.045977 \n",
"30726 5097144 1321 371 1692 0.219267 \n",
"30727 5097145 53 283 336 0.842262 \n",
"30728 5097147 705 24 729 0.032922 \n",
"30729 5097148 682 177 859 0.206054 \n",
"30730 5097149 116 59 175 0.337143 \n",
"\n",
" DF_UID FLAECHE NEIGUNG AUSRICHTUN BUF30_Perc ... \\\n",
"0 4965782 1289.608452 0 0 0.045802 ... \n",
"1 4965783 560.036571 3 -24 0.052521 ... \n",
"2 4965784 73.745743 0 0 0.180812 ... \n",
"3 4965785 204.889465 0 0 0.126366 ... \n",
"4 4965875 41.788788 0 0 0.208260 ... \n",
"5 4965876 2635.931059 0 0 0.028215 ... \n",
"6 4965878 1938.065681 0 0 0.040140 ... \n",
"7 4965879 182.631292 0 0 0.096756 ... \n",
"8 4965884 636.709326 0 0 0.121819 ... \n",
"9 4965886 293.774672 0 0 0.102103 ... \n",
"10 4966558 3107.350962 0 0 0.035727 ... \n",
"11 4972728 125.197892 24 -95 0.134290 ... \n",
"12 4972729 124.174089 23 102 0.135529 ... \n",
"13 4972730 119.978332 24 -78 0.139948 ... \n",
"14 4976075 394.834081 0 0 0.194787 ... \n",
"15 4977601 661.683103 0 0 0.061522 ... \n",
"16 4981768 167.410586 7 21 0.126249 ... \n",
"17 5031245 939.826579 0 0 0.071570 ... \n",
"18 5031246 1186.279210 0 0 0.069947 ... \n",
"19 5031249 818.552360 0 0 0.076566 ... \n",
"20 5031254 40.755698 0 0 0.214383 ... \n",
"21 5031260 32.506871 0 0 0.263408 ... \n",
"22 5031269 38.084736 0 0 0.218424 ... \n",
"23 5031275 33.370309 0 0 0.258869 ... \n",
"24 5031603 211.987975 0 0 0.215162 ... \n",
"25 5031660 21.434018 0 0 0.260876 ... \n",
"26 5031667 86.622891 0 0 0.216379 ... \n",
"27 5031668 94.583084 0 0 0.280869 ... \n",
"28 5031695 568.139425 0 0 0.462961 ... \n",
"30 5031703 1749.853582 0 0 0.151529 ... \n",
"... ... ... ... ... ... ... \n",
"30701 5097073 53.010729 0 0 0.169895 ... \n",
"30702 5097074 120.454191 0 0 0.145204 ... \n",
"30703 5097075 72.264869 0 0 0.216449 ... \n",
"30704 5097076 160.133540 0 0 0.242999 ... \n",
"30705 5097080 23.292598 0 0 0.309961 ... \n",
"30706 5097081 18.616667 0 0 0.358486 ... \n",
"30707 5097086 132.388355 0 0 0.258959 ... \n",
"30708 5097087 483.483078 0 0 0.066900 ... \n",
"30709 5097090 161.785347 0 0 0.142907 ... \n",
"30710 5097092 14.134757 0 0 0.319757 ... \n",
"30711 5097093 18.313333 0 0 0.298996 ... \n",
"30712 5097094 201.961897 0 0 0.109645 ... \n",
"30713 5097097 54.362110 0 0 0.300839 ... \n",
"30714 5097098 103.289530 0 0 0.195073 ... \n",
"30715 5097105 204.892636 0 0 0.204908 ... \n",
"30716 5097106 155.017225 0 0 0.104813 ... \n",
"30717 5097107 88.500825 0 0 0.141080 ... \n",
"30718 5097108 28.174149 0 0 0.318815 ... \n",
"30719 5097109 151.999779 33 -63 0.127348 ... \n",
"30720 5097129 109.583732 0 0 0.130893 ... \n",
"30721 5097130 116.886388 31 -62 0.138579 ... \n",
"30722 5097138 98.189777 33 -61 0.145255 ... \n",
"30723 5097141 35.341745 55 133 0.362257 ... \n",
"30724 5097142 33.443353 48 -133 0.501408 ... \n",
"30725 5097143 109.884484 37 48 0.142206 ... \n",
"30726 5097144 468.788104 0 0 0.075506 ... \n",
"30727 5097145 90.048705 0 0 0.173667 ... \n",
"30728 5097147 223.258083 35 -62 0.131254 ... \n",
"30729 5097148 214.516672 1 118 0.114318 ... \n",
"30730 5097149 42.854700 0 0 0.291349 ... \n",
"\n",
" SHAPE_Leng GWR_EGID EGID GBAUP GKAT GAREA GASTW \\\n",
"0 196.890521 1019783 1019783 8014.0 1025 243.0 9.0 \n",
"1 97.901422 295009928 295009928 8014.0 1060 641.0 1.0 \n",
"2 44.447665 295009928 295009928 8014.0 1060 641.0 1.0 \n",
"3 86.303247 1019785 1019785 8014.0 1025 241.0 9.0 \n",
"4 29.008722 1019776 1019776 8015.0 1025 389.0 23.0 \n",
"5 247.909594 1019776 1019776 8015.0 1025 389.0 23.0 \n",
"6 259.313613 1019776 1019776 8015.0 1025 389.0 23.0 \n",
"7 58.902105 1019776 1019776 8015.0 1025 389.0 23.0 \n",
"8 258.545440 1019776 1019776 8015.0 1025 389.0 23.0 \n",
"9 99.982577 1019787 1019787 8014.0 1025 315.0 9.0 \n",
"10 370.049530 1019798 1019798 8014.0 1025 344.0 8.0 \n",
"11 51.322510 1016396 1016396 8013.0 1025 179.0 3.0 \n",
"12 51.558776 1016395 1016395 8013.0 1025 179.0 3.0 \n",
"13 51.104449 1016395 1016395 8013.0 1025 179.0 3.0 \n",
"14 256.361342 1028525 1028525 8015.0 1030 418.0 4.0 \n",
"15 135.693397 2043187 2043187 8013.0 1060 653.0 4.0 \n",
"16 69.973945 295101875 295101875 8014.0 1060 142.0 1.0 \n",
"17 224.210407 2040612 2040612 8018.0 1060 1244.0 5.0 \n",
"18 276.588492 2040612 2040612 8018.0 1060 1244.0 5.0 \n",
"19 208.911747 2040612 2040612 8018.0 1060 1244.0 5.0 \n",
"20 29.124265 2040612 2040612 8018.0 1060 1244.0 5.0 \n",
"21 28.542027 2040612 2040612 8018.0 1060 1244.0 5.0 \n",
"22 27.728889 2040612 2040612 8018.0 1060 1244.0 5.0 \n",
"23 28.795176 2040612 2040612 8018.0 1060 1244.0 5.0 \n",
"24 152.039389 2034928 2034928 8015.0 1060 1744.0 7.0 \n",
"25 18.638709 1002959 1002959 8016.0 1030 229.0 5.0 \n",
"26 62.476428 1002959 1002959 8016.0 1030 229.0 5.0 \n",
"27 88.551837 1002959 1002959 8016.0 1030 229.0 5.0 \n",
"28 876.753854 2034930 2034930 8018.0 1060 3622.0 6.0 \n",
"30 883.846590 2034930 2034930 8018.0 1060 3622.0 6.0 \n",
"... ... ... ... ... ... ... ... \n",
"30701 30.020978 1014767 1014767 8012.0 1030 179.0 8.0 \n",
"30702 58.301827 1014767 1014767 8012.0 1030 179.0 8.0 \n",
"30703 52.140600 1014767 1014767 8012.0 1030 179.0 8.0 \n",
"30704 129.706367 1014767 1014767 8012.0 1030 179.0 8.0 \n",
"30705 24.066004 1014767 1014767 8012.0 1030 179.0 8.0 \n",
"30706 22.245987 1014767 1014767 8012.0 1030 179.0 8.0 \n",
"30707 114.277534 1014795 1014795 8017.0 1040 818.0 7.0 \n",
"30708 107.815944 1014795 1014795 8017.0 1040 818.0 7.0 \n",
"30709 77.067440 1014795 1014795 8017.0 1040 818.0 7.0 \n",
"30710 15.065601 1014795 1014795 8017.0 1040 818.0 7.0 \n",
"30711 18.252096 1014795 1014795 8017.0 1040 818.0 7.0 \n",
"30712 73.813516 1014795 1014795 8017.0 1040 818.0 7.0 \n",
"30713 54.514112 1014795 1014795 8017.0 1040 818.0 7.0 \n",
"30714 67.163530 1014795 1014795 8017.0 1040 818.0 7.0 \n",
"30715 139.946860 1014819 1014819 8014.0 1025 362.0 5.0 \n",
"30716 54.159230 1014819 1014819 8014.0 1025 362.0 5.0 \n",
"30717 41.618960 1014819 1014819 8014.0 1025 362.0 5.0 \n",
"30718 29.941170 1014819 1014819 8014.0 1025 362.0 5.0 \n",
"30719 54.240235 1014819 1014819 8014.0 1025 362.0 5.0 \n",
"30720 47.813799 1014811 1014811 8011.0 1025 277.0 8.0 \n",
"30721 46.443726 1014811 1014811 8011.0 1025 277.0 8.0 \n",
"30722 40.062807 1014811 1014811 8011.0 1025 277.0 8.0 \n",
"30723 24.241518 1014811 1014811 8011.0 1025 277.0 8.0 \n",
"30724 37.638591 1014811 1014811 8011.0 1025 277.0 8.0 \n",
"30725 41.534111 1014811 1014811 8011.0 1025 277.0 8.0 \n",
"30726 117.987055 1014811 1014811 8011.0 1025 277.0 8.0 \n",
"30727 52.128374 1014811 1014811 8011.0 1025 277.0 8.0 \n",
"30728 79.895403 1014811 1014811 8011.0 1025 277.0 8.0 \n",
"30729 81.732726 1014811 1014811 8011.0 1025 277.0 8.0 \n",
"30730 41.618186 1014811 1014811 8011.0 1025 277.0 8.0 \n",
"\n",
" GKODX GKODY n_neighbors \n",
"0 497506.0 116080.0 5.0 \n",
"1 497498.0 116020.0 7.0 \n",
"2 497498.0 116020.0 7.0 \n",
"3 497519.0 116052.0 5.0 \n",
"4 497446.0 116074.0 6.0 \n",
"5 497446.0 116074.0 6.0 \n",
"6 497446.0 116074.0 6.0 \n",
"7 497446.0 116074.0 6.0 \n",
"8 497446.0 116074.0 6.0 \n",
"9 497533.0 116021.0 3.0 \n",
"10 497483.0 116306.0 1.0 \n",
"11 497486.0 117967.0 3.0 \n",
"12 497496.0 117997.0 3.0 \n",
"13 497496.0 117997.0 3.0 \n",
"14 497466.0 118420.0 5.0 \n",
"15 497488.0 118636.0 3.0 \n",
"16 497485.0 118807.0 10.0 \n",
"17 497672.0 115975.0 5.0 \n",
"18 497672.0 115975.0 5.0 \n",
"19 497672.0 115975.0 5.0 \n",
"20 497672.0 115975.0 5.0 \n",
"21 497672.0 115975.0 5.0 \n",
"22 497672.0 115975.0 5.0 \n",
"23 497672.0 115975.0 5.0 \n",
"24 498874.0 115929.0 5.0 \n",
"25 499221.0 116005.0 0.0 \n",
"26 499221.0 116005.0 0.0 \n",
"27 499221.0 116005.0 0.0 \n",
"28 499102.0 115935.0 0.0 \n",
"30 499102.0 115935.0 0.0 \n",
"... ... ... ... \n",
"30701 500356.0 118988.0 0.0 \n",
"30702 500356.0 118988.0 0.0 \n",
"30703 500356.0 118988.0 0.0 \n",
"30704 500356.0 118988.0 0.0 \n",
"30705 500356.0 118988.0 0.0 \n",
"30706 500356.0 118988.0 0.0 \n",
"30707 500509.0 118993.0 2.0 \n",
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"30709 500509.0 118993.0 2.0 \n",
"30710 500509.0 118993.0 2.0 \n",
"30711 500509.0 118993.0 2.0 \n",
"30712 500509.0 118993.0 2.0 \n",
"30713 500509.0 118993.0 2.0 \n",
"30714 500509.0 118993.0 2.0 \n",
"30715 500247.0 119026.0 1.0 \n",
"30716 500247.0 119026.0 1.0 \n",
"30717 500247.0 119026.0 1.0 \n",
"30718 500247.0 119026.0 1.0 \n",
"30719 500247.0 119026.0 1.0 \n",
"30720 500261.0 118955.0 1.0 \n",
"30721 500261.0 118955.0 1.0 \n",
"30722 500261.0 118955.0 1.0 \n",
"30723 500261.0 118955.0 1.0 \n",
"30724 500261.0 118955.0 1.0 \n",
"30725 500261.0 118955.0 1.0 \n",
"30726 500261.0 118955.0 1.0 \n",
"30727 500261.0 118955.0 1.0 \n",
"30728 500261.0 118955.0 1.0 \n",
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"30730 500261.0 118955.0 1.0 \n",
"\n",
"[24396 rows x 22 columns]"
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"horizon_50cm.drop_duplicates()"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [],
"source": [
"# load shading data for 2m DOM with 40% visibility threshold - LABELS\n",
"horizon_2m_vis40 = '/Users/alinawalch/Documents/EPFL/data/rooftops/shading_images/visibility/summary_stats_vis_40_2m.csv'\n",
"horizon_2m_vis40 = pd.read_csv(horizon_2m_vis40, sep='|')\n",
"horizon_2m_vis40 = horizon_2m_vis40.loc[:,['zone', 'non_null_cells', 'null_cells']]\n",
"horizon_2m_vis40['n_cells'] = horizon_2m_vis40.non_null_cells + horizon_2m_vis40.null_cells\n",
"horizon_2m_vis40['fully_shaded_ratio'] = horizon_2m_vis40.null_cells / horizon_2m_vis40.n_cells\n",
"\n",
"horizon_2m = horizon_2m_vis40.merge(ROOFS, how='inner', right_on='DF_UID', left_on = 'zone')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Create table with features and labels\n",
"Fully shaded cells only, features are:\n",
"- Total number of cells (2m DOM - n_cells)\n",
"- Number of fully shaded cells (2m DOM - null_cells)\n",
"- Slope (NEIGUNG)\n",
"- Aspect (AUSRICHTUN)\n",
"- Roof area (FLAECHE)\n",
"- Roof perimeter (SHAPE_Leng)\n",
"- Number of floors (GASTW)\n",
"- Period of construction (GBAUP)\n",
"- Building area (GAREA)\n",
"- (Building typology (GKAT) ?)"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [],
"source": [
"# select features and labels, and merge index (zone)\n",
"features = horizon_2m.loc[:, ['zone', 'fully_shaded_ratio', 'n_cells', 'null_cells','non_null_cells', 'NEIGUNG', 'AUSRICHTUN', 'FLAECHE', 'SHAPE_Leng', 'GASTW', 'GBAUP', 'GKAT', 'GAREA', 'n_neighbors']].drop_duplicates()\n",
"features['perim_ratio'] = features.SHAPE_Leng/features.FLAECHE\n",
"features.rename( {'fully_shaded_ratio' : 'fully_shaded_ratio_2m'}, axis = 1, inplace = True)\n",
"\n",
"labels = horizon_50cm.loc[:,['zone','fully_shaded_ratio']].drop_duplicates()"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [],
"source": [
"learning_table = features.merge( labels, on='zone', how='inner' ).dropna().reset_index().drop( ['index'], axis = 1 )"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"24114\n",
"24396\n",
"23970\n"
]
}
],
"source": [
"print(len(features))\n",
"print(len(labels))\n",
"print(len(learning_table))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Machine Learning"
]
},
{
"cell_type": "code",
"execution_count": 49,
"metadata": {},
"outputs": [],
"source": [
"label_name = 'fully_shaded_ratio'\n",
"identifier = 'zone'\n",
"# choose from: \n",
"# -'fully_shaded_ratio_2m', 'null_cells', 'non_null_cells', 'n_cells' (shading analysis)\n",
"# -'NEIGUNG', 'AUSRICHTUN', 'FLAECHE', 'SHAPE_Leng', 'perim_ratio' (rooftop info)\n",
"# -'GASTW', 'GBAUP', 'GKAT' (GWR info)\n",
"all_features = ['fully_shaded_ratio_2m', 'null_cells', 'non_null_cells', 'n_cells', 'NEIGUNG', 'AUSRICHTUN', 'FLAECHE', 'SHAPE_Leng', 'perim_ratio', 'GASTW', 'GBAUP', 'GKAT', 'GAREA', 'n_neighbors']\n",
"feature_names = all_features # ['n_cells', 'NEIGUNG', 'AUSRICHTUN', 'FLAECHE', 'SHAPE_Leng', 'perim_ratio', 'GASTW', 'GBAUP', 'GAREA']"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Baseline MSE: 0.047743\n"
]
}
],
"source": [
"# Baseline mse:\n",
"ref_2m = horizon_2m.loc[:, [ identifier, 'fully_shaded_ratio' ]].drop_duplicates()\n",
"ref = ref_2m.merge(labels, on= identifier ).dropna()\n",
"print( 'Baseline MSE: %f' %mse(ref.fully_shaded_ratio_x, ref.fully_shaded_ratio_y))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Tests:\n",
"- 12 features in total\n",
"- Total options of combinations: 12 CHOOSE K"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"n_features = len(feature_names)\n",
"max_trials = 20\n",
"#. for i in range(len(feature_names)):\n",
"i=0\n",
"n_permutations = comb(n_features, i) "
]
},
{
"cell_type": "code",
"execution_count": 34,
"metadata": {},
"outputs": [],
"source": [
"tr_ratio = 0.8\n",
"ind = np.random.permutation(len(learning_table))\n",
"tr_ind = int( tr_ratio * len(learning_table) )\n",
"\n",
"training = learning_table.loc[ ind[ : tr_ind ] , :]\n",
"validation = learning_table.loc[ ind[ tr_ind : ] , :]"
]
},
{
"cell_type": "code",
"execution_count": 35,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
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"<table border=\"1\" class=\"dataframe\">\n",
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" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>zone</th>\n",
" <th>fully_shaded_ratio_2m</th>\n",
" <th>n_cells</th>\n",
" <th>null_cells</th>\n",
" <th>non_null_cells</th>\n",
" <th>NEIGUNG</th>\n",
" <th>AUSRICHTUN</th>\n",
" <th>FLAECHE</th>\n",
" <th>SHAPE_Leng</th>\n",
" <th>GASTW</th>\n",
" <th>GBAUP</th>\n",
" <th>GKAT</th>\n",
" <th>GAREA</th>\n",
" <th>n_neighbors</th>\n",
" <th>perim_ratio</th>\n",
" <th>fully_shaded_ratio</th>\n",
" </tr>\n",
" </thead>\n",
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" <tr>\n",
" <th>0</th>\n",
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" <td>4965783</td>\n",
" <td>0.000000</td>\n",
" <td>55</td>\n",
" <td>0</td>\n",
" <td>55</td>\n",
" <td>3</td>\n",
" <td>-24</td>\n",
" <td>560.036571</td>\n",
" <td>97.901422</td>\n",
" <td>1.0</td>\n",
" <td>8014.0</td>\n",
" <td>1060</td>\n",
" <td>641.0</td>\n",
" <td>7.0</td>\n",
" <td>0.174813</td>\n",
" <td>0.022354</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>4965784</td>\n",
" <td>0.000000</td>\n",
" <td>18</td>\n",
" <td>0</td>\n",
" <td>18</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>73.745743</td>\n",
" <td>44.447665</td>\n",
" <td>1.0</td>\n",
" <td>8014.0</td>\n",
" <td>1060</td>\n",
" <td>641.0</td>\n",
" <td>7.0</td>\n",
" <td>0.602715</td>\n",
" <td>0.136054</td>\n",
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" <tr>\n",
" <th>3</th>\n",
" <td>4965785</td>\n",
" <td>0.000000</td>\n",
" <td>12</td>\n",
" <td>0</td>\n",
" <td>12</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>204.889465</td>\n",
" <td>86.303247</td>\n",
" <td>9.0</td>\n",
" <td>8014.0</td>\n",
" <td>1025</td>\n",
" <td>241.0</td>\n",
" <td>5.0</td>\n",
" <td>0.421219</td>\n",
" <td>0.053708</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>4965875</td>\n",
" <td>0.000000</td>\n",
" <td>6</td>\n",
" <td>0</td>\n",
" <td>6</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>41.788788</td>\n",
" <td>29.008722</td>\n",
" <td>23.0</td>\n",
" <td>8015.0</td>\n",
" <td>1025</td>\n",
" <td>389.0</td>\n",
" <td>6.0</td>\n",
" <td>0.694175</td>\n",
" <td>0.172619</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>4965876</td>\n",
" <td>0.146667</td>\n",
" <td>75</td>\n",
" <td>11</td>\n",
" <td>64</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>2635.931059</td>\n",
" <td>247.909594</td>\n",
" <td>23.0</td>\n",
" <td>8015.0</td>\n",
" <td>1025</td>\n",
" <td>389.0</td>\n",
" <td>6.0</td>\n",
" <td>0.094050</td>\n",
" <td>0.231743</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>4965878</td>\n",
" <td>0.000000</td>\n",
" <td>9</td>\n",
" <td>0</td>\n",
" <td>9</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1938.065681</td>\n",
" <td>259.313613</td>\n",
" <td>23.0</td>\n",
" <td>8015.0</td>\n",
" <td>1025</td>\n",
" <td>389.0</td>\n",
" <td>6.0</td>\n",
" <td>0.133800</td>\n",
" <td>0.034000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>4965879</td>\n",
" <td>0.400000</td>\n",
" <td>45</td>\n",
" <td>18</td>\n",
" <td>27</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>182.631292</td>\n",
" <td>58.902105</td>\n",
" <td>23.0</td>\n",
" <td>8015.0</td>\n",
" <td>1025</td>\n",
" <td>389.0</td>\n",
" <td>6.0</td>\n",
" <td>0.322519</td>\n",
" <td>0.373626</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>4965884</td>\n",
" <td>0.093750</td>\n",
" <td>32</td>\n",
" <td>3</td>\n",
" <td>29</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>636.709326</td>\n",
" <td>258.545440</td>\n",
" <td>23.0</td>\n",
" <td>8015.0</td>\n",
" <td>1025</td>\n",
" <td>389.0</td>\n",
" <td>6.0</td>\n",
" <td>0.406065</td>\n",
" <td>0.248011</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>4965886</td>\n",
" <td>0.000000</td>\n",
" <td>75</td>\n",
" <td>0</td>\n",
" <td>75</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>293.774672</td>\n",
" <td>99.982577</td>\n",
" <td>9.0</td>\n",
" <td>8014.0</td>\n",
" <td>1025</td>\n",
" <td>315.0</td>\n",
" <td>3.0</td>\n",
" <td>0.340338</td>\n",
" <td>0.089438</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>4972730</td>\n",
" <td>0.000000</td>\n",
" <td>15</td>\n",
" <td>0</td>\n",
" <td>15</td>\n",
" <td>24</td>\n",
" <td>-78</td>\n",
" <td>119.978332</td>\n",
" <td>51.104449</td>\n",
" <td>3.0</td>\n",
" <td>8013.0</td>\n",
" <td>1025</td>\n",
" <td>179.0</td>\n",
" <td>3.0</td>\n",
" <td>0.425947</td>\n",
" <td>0.006849</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>4977601</td>\n",
" <td>0.021277</td>\n",
" <td>47</td>\n",
" <td>1</td>\n",
" <td>46</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>661.683103</td>\n",
" <td>135.693397</td>\n",
" <td>4.0</td>\n",
" <td>8013.0</td>\n",
" <td>1060</td>\n",
" <td>653.0</td>\n",
" <td>3.0</td>\n",
" <td>0.205073</td>\n",
" <td>0.000843</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>5031245</td>\n",
" <td>0.056497</td>\n",
" <td>177</td>\n",
" <td>10</td>\n",
" <td>167</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>939.826579</td>\n",
" <td>224.210407</td>\n",
" <td>5.0</td>\n",
" <td>8018.0</td>\n",
" <td>1060</td>\n",
" <td>1244.0</td>\n",
" <td>5.0</td>\n",
" <td>0.238566</td>\n",
" <td>0.066642</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>5031246</td>\n",
" <td>0.031250</td>\n",
" <td>32</td>\n",
" <td>1</td>\n",
" <td>31</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1186.279210</td>\n",
" <td>276.588492</td>\n",
" <td>5.0</td>\n",
" <td>8018.0</td>\n",
" <td>1060</td>\n",
" <td>1244.0</td>\n",
" <td>5.0</td>\n",
" <td>0.233156</td>\n",
" <td>0.004357</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>5031249</td>\n",
" <td>0.068027</td>\n",
" <td>147</td>\n",
" <td>10</td>\n",
" <td>137</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>818.552360</td>\n",
" <td>208.911747</td>\n",
" <td>5.0</td>\n",
" <td>8018.0</td>\n",
" <td>1060</td>\n",
" <td>1244.0</td>\n",
" <td>5.0</td>\n",
" <td>0.255221</td>\n",
" <td>0.061002</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>5031254</td>\n",
" <td>0.000000</td>\n",
" <td>11</td>\n",
" <td>0</td>\n",
" <td>11</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>40.755698</td>\n",
" <td>29.124265</td>\n",
" <td>5.0</td>\n",
" <td>8018.0</td>\n",
" <td>1060</td>\n",
" <td>1244.0</td>\n",
" <td>5.0</td>\n",
" <td>0.714606</td>\n",
" <td>0.012346</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>5031260</td>\n",
" <td>0.000000</td>\n",
" <td>7</td>\n",
" <td>0</td>\n",
" <td>7</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>32.506871</td>\n",
" <td>28.542027</td>\n",
" <td>5.0</td>\n",
" <td>8018.0</td>\n",
" <td>1060</td>\n",
" <td>1244.0</td>\n",
" <td>5.0</td>\n",
" <td>0.878031</td>\n",
" <td>0.209302</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td>5031269</td>\n",
" <td>0.000000</td>\n",
" <td>8</td>\n",
" <td>0</td>\n",
" <td>8</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>38.084736</td>\n",
" <td>27.728889</td>\n",
" <td>5.0</td>\n",
" <td>8018.0</td>\n",
" <td>1060</td>\n",
" <td>1244.0</td>\n",
" <td>5.0</td>\n",
" <td>0.728084</td>\n",
" <td>0.092105</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>5031275</td>\n",
" <td>0.000000</td>\n",
" <td>8</td>\n",
" <td>0</td>\n",
" <td>8</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>33.370309</td>\n",
" <td>28.795176</td>\n",
" <td>5.0</td>\n",
" <td>8018.0</td>\n",
" <td>1060</td>\n",
" <td>1244.0</td>\n",
" <td>5.0</td>\n",
" <td>0.862898</td>\n",
" <td>0.196970</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td>5031603</td>\n",
" <td>0.000000</td>\n",
" <td>2</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>211.987975</td>\n",
" <td>152.039389</td>\n",
" <td>7.0</td>\n",
" <td>8015.0</td>\n",
" <td>1060</td>\n",
" <td>1744.0</td>\n",
" <td>5.0</td>\n",
" <td>0.717208</td>\n",
" <td>0.350000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>5031660</td>\n",
" <td>0.000000</td>\n",
" <td>6</td>\n",
" <td>0</td>\n",
" <td>6</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>21.434018</td>\n",
" <td>18.638709</td>\n",
" <td>5.0</td>\n",
" <td>8016.0</td>\n",
" <td>1030</td>\n",
" <td>229.0</td>\n",
" <td>0.0</td>\n",
" <td>0.869585</td>\n",
" <td>0.088889</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>5031667</td>\n",
" <td>0.000000</td>\n",
" <td>20</td>\n",
" <td>0</td>\n",
" <td>20</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>86.622891</td>\n",
" <td>62.476428</td>\n",
" <td>5.0</td>\n",
" <td>8016.0</td>\n",
" <td>1030</td>\n",
" <td>229.0</td>\n",
" <td>0.0</td>\n",
" <td>0.721246</td>\n",
" <td>0.048673</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td>5031668</td>\n",
" <td>0.086957</td>\n",
" <td>23</td>\n",
" <td>2</td>\n",
" <td>21</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>94.583084</td>\n",
" <td>88.551837</td>\n",
" <td>5.0</td>\n",
" <td>8016.0</td>\n",
" <td>1030</td>\n",
" <td>229.0</td>\n",
" <td>0.0</td>\n",
" <td>0.936233</td>\n",
" <td>0.561765</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23</th>\n",
" <td>5031703</td>\n",
" <td>0.200000</td>\n",
" <td>15</td>\n",
" <td>3</td>\n",
" <td>12</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1749.853582</td>\n",
" <td>883.846590</td>\n",
" <td>6.0</td>\n",
" <td>8018.0</td>\n",
" <td>1060</td>\n",
" <td>3622.0</td>\n",
" <td>0.0</td>\n",
" <td>0.505097</td>\n",
" <td>0.166667</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24</th>\n",
" <td>5031849</td>\n",
" <td>0.000000</td>\n",
" <td>35</td>\n",
" <td>0</td>\n",
" <td>35</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>590.026405</td>\n",
" <td>116.975482</td>\n",
" <td>7.0</td>\n",
" <td>8021.0</td>\n",
" <td>1025</td>\n",
" <td>264.0</td>\n",
" <td>3.0</td>\n",
" <td>0.198255</td>\n",
" <td>0.059829</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25</th>\n",
" <td>5031857</td>\n",
" <td>0.000000</td>\n",
" <td>19</td>\n",
" <td>0</td>\n",
" <td>19</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>409.432946</td>\n",
" <td>262.015433</td>\n",
" <td>7.0</td>\n",
" <td>8021.0</td>\n",
" <td>1025</td>\n",
" <td>264.0</td>\n",
" <td>3.0</td>\n",
" <td>0.639947</td>\n",
" <td>0.363636</td>\n",
" </tr>\n",
" <tr>\n",
" <th>26</th>\n",
" <td>5031866</td>\n",
" <td>0.416667</td>\n",
" <td>12</td>\n",
" <td>5</td>\n",
" <td>7</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>48.068482</td>\n",
" <td>30.739744</td>\n",
" <td>5.0</td>\n",
" <td>8016.0</td>\n",
" <td>1040</td>\n",
" <td>718.0</td>\n",
" <td>3.0</td>\n",
" <td>0.639499</td>\n",
" <td>0.238095</td>\n",
" </tr>\n",
" <tr>\n",
" <th>27</th>\n",
" <td>5031872</td>\n",
" <td>0.000000</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>129</td>\n",
" <td>57.948718</td>\n",
" <td>29.802854</td>\n",
" <td>5.0</td>\n",
" <td>8016.0</td>\n",
" <td>1040</td>\n",
" <td>718.0</td>\n",
" <td>3.0</td>\n",
" <td>0.514297</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>28</th>\n",
" <td>5031875</td>\n",
" <td>0.000000</td>\n",
" <td>5</td>\n",
" <td>0</td>\n",
" <td>5</td>\n",
" <td>38</td>\n",
" <td>125</td>\n",
" <td>29.295900</td>\n",
" <td>20.849144</td>\n",
" <td>5.0</td>\n",
" <td>8016.0</td>\n",
" <td>1040</td>\n",
" <td>718.0</td>\n",
" <td>3.0</td>\n",
" <td>0.711674</td>\n",
" <td>0.289855</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29</th>\n",
" <td>5032059</td>\n",
" <td>0.500000</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>335.198181</td>\n",
" <td>100.261822</td>\n",
" <td>7.0</td>\n",
" <td>8013.0</td>\n",
" <td>1025</td>\n",
" <td>321.0</td>\n",
" <td>1.0</td>\n",
" <td>0.299112</td>\n",
" <td>0.350000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23940</th>\n",
" <td>5097068</td>\n",
" <td>0.000000</td>\n",
" <td>66</td>\n",
" <td>0</td>\n",
" <td>66</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>261.888561</td>\n",
" <td>65.514620</td>\n",
" <td>8.0</td>\n",
" <td>8012.0</td>\n",
" <td>1030</td>\n",
" <td>179.0</td>\n",
" <td>0.0</td>\n",
" <td>0.250162</td>\n",
" <td>0.078319</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23941</th>\n",
" <td>5097069</td>\n",
" <td>0.071429</td>\n",
" <td>14</td>\n",
" <td>1</td>\n",
" <td>13</td>\n",
" <td>38</td>\n",
" <td>123</td>\n",
" <td>69.189981</td>\n",
" <td>32.547997</td>\n",
" <td>8.0</td>\n",
" <td>8012.0</td>\n",
" <td>1030</td>\n",
" <td>179.0</td>\n",
" <td>0.0</td>\n",
" <td>0.470415</td>\n",
" <td>0.362385</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23942</th>\n",
" <td>5097070</td>\n",
" <td>0.000000</td>\n",
" <td>13</td>\n",
" <td>0</td>\n",
" <td>13</td>\n",
" <td>38</td>\n",
" <td>-57</td>\n",
" <td>66.355573</td>\n",
" <td>30.614168</td>\n",
" <td>8.0</td>\n",
" <td>8012.0</td>\n",
" <td>1030</td>\n",
" <td>179.0</td>\n",
" <td>0.0</td>\n",
" <td>0.461365</td>\n",
" <td>0.196172</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23943</th>\n",
" <td>5097071</td>\n",
" <td>0.047619</td>\n",
" <td>21</td>\n",
" <td>1</td>\n",
" <td>20</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>86.315952</td>\n",
" <td>50.196239</td>\n",
" <td>8.0</td>\n",
" <td>8012.0</td>\n",
" <td>1030</td>\n",
" <td>179.0</td>\n",
" <td>0.0</td>\n",
" <td>0.581541</td>\n",
" <td>0.228986</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23944</th>\n",
" <td>5097076</td>\n",
" <td>0.000000</td>\n",
" <td>12</td>\n",
" <td>0</td>\n",
" <td>12</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>160.133540</td>\n",
" <td>129.706367</td>\n",
" <td>8.0</td>\n",
" <td>8012.0</td>\n",
" <td>1030</td>\n",
" <td>179.0</td>\n",
" <td>0.0</td>\n",
" <td>0.809989</td>\n",
" <td>0.098522</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23945</th>\n",
" <td>5097080</td>\n",
" <td>0.000000</td>\n",
" <td>6</td>\n",
" <td>0</td>\n",
" <td>6</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>23.292598</td>\n",
" <td>24.066004</td>\n",
" <td>8.0</td>\n",
" <td>8012.0</td>\n",
" <td>1030</td>\n",
" <td>179.0</td>\n",
" <td>0.0</td>\n",
" <td>1.033204</td>\n",
" <td>0.236559</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23946</th>\n",
" <td>5097081</td>\n",
" <td>0.750000</td>\n",
" <td>4</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>18.616667</td>\n",
" <td>22.245987</td>\n",
" <td>8.0</td>\n",
" <td>8012.0</td>\n",
" <td>1030</td>\n",
" <td>179.0</td>\n",
" <td>0.0</td>\n",
" <td>1.194950</td>\n",
" <td>0.986301</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23947</th>\n",
" <td>5097086</td>\n",
" <td>0.000000</td>\n",
" <td>26</td>\n",
" <td>0</td>\n",
" <td>26</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>132.388355</td>\n",
" <td>114.277534</td>\n",
" <td>7.0</td>\n",
" <td>8017.0</td>\n",
" <td>1040</td>\n",
" <td>818.0</td>\n",
" <td>2.0</td>\n",
" <td>0.863199</td>\n",
" <td>0.216630</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23948</th>\n",
" <td>5097087</td>\n",
" <td>0.844444</td>\n",
" <td>45</td>\n",
" <td>38</td>\n",
" <td>7</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>483.483078</td>\n",
" <td>107.815944</td>\n",
" <td>7.0</td>\n",
" <td>8017.0</td>\n",
" <td>1040</td>\n",
" <td>818.0</td>\n",
" <td>2.0</td>\n",
" <td>0.222998</td>\n",
" <td>0.943152</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23949</th>\n",
" <td>5097090</td>\n",
" <td>0.000000</td>\n",
" <td>39</td>\n",
" <td>0</td>\n",
" <td>39</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>161.785347</td>\n",
" <td>77.067440</td>\n",
" <td>7.0</td>\n",
" <td>8017.0</td>\n",
" <td>1040</td>\n",
" <td>818.0</td>\n",
" <td>2.0</td>\n",
" <td>0.476356</td>\n",
" <td>0.182410</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23950</th>\n",
" <td>5097092</td>\n",
" <td>0.000000</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>14.134757</td>\n",
" <td>15.065601</td>\n",
" <td>7.0</td>\n",
" <td>8017.0</td>\n",
" <td>1040</td>\n",
" <td>818.0</td>\n",
" <td>2.0</td>\n",
" <td>1.065855</td>\n",
" <td>0.178571</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23951</th>\n",
" <td>5097093</td>\n",
" <td>0.000000</td>\n",
" <td>4</td>\n",
" <td>0</td>\n",
" <td>4</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>18.313333</td>\n",
" <td>18.252096</td>\n",
" <td>7.0</td>\n",
" <td>8017.0</td>\n",
" <td>1040</td>\n",
" <td>818.0</td>\n",
" <td>2.0</td>\n",
" <td>0.996656</td>\n",
" <td>0.082192</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23952</th>\n",
" <td>5097094</td>\n",
" <td>0.000000</td>\n",
" <td>12</td>\n",
" <td>0</td>\n",
" <td>12</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>201.961897</td>\n",
" <td>73.813516</td>\n",
" <td>7.0</td>\n",
" <td>8017.0</td>\n",
" <td>1040</td>\n",
" <td>818.0</td>\n",
" <td>2.0</td>\n",
" <td>0.365482</td>\n",
" <td>0.064935</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23953</th>\n",
" <td>5097097</td>\n",
" <td>0.857143</td>\n",
" <td>14</td>\n",
" <td>12</td>\n",
" <td>2</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>54.362110</td>\n",
" <td>54.514112</td>\n",
" <td>7.0</td>\n",
" <td>8017.0</td>\n",
" <td>1040</td>\n",
" <td>818.0</td>\n",
" <td>2.0</td>\n",
" <td>1.002796</td>\n",
" <td>0.944444</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23954</th>\n",
" <td>5097098</td>\n",
" <td>0.000000</td>\n",
" <td>14</td>\n",
" <td>0</td>\n",
" <td>14</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>103.289530</td>\n",
" <td>67.163530</td>\n",
" <td>7.0</td>\n",
" <td>8017.0</td>\n",
" <td>1040</td>\n",
" <td>818.0</td>\n",
" <td>2.0</td>\n",
" <td>0.650245</td>\n",
" <td>0.016598</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23955</th>\n",
" <td>5097105</td>\n",
" <td>0.000000</td>\n",
" <td>33</td>\n",
" <td>0</td>\n",
" <td>33</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>204.892636</td>\n",
" <td>139.946860</td>\n",
" <td>5.0</td>\n",
" <td>8014.0</td>\n",
" <td>1025</td>\n",
" <td>362.0</td>\n",
" <td>1.0</td>\n",
" <td>0.683025</td>\n",
" <td>0.331606</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23956</th>\n",
" <td>5097106</td>\n",
" <td>0.000000</td>\n",
" <td>40</td>\n",
" <td>0</td>\n",
" <td>40</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>155.017225</td>\n",
" <td>54.159230</td>\n",
" <td>5.0</td>\n",
" <td>8014.0</td>\n",
" <td>1025</td>\n",
" <td>362.0</td>\n",
" <td>1.0</td>\n",
" <td>0.349376</td>\n",
" <td>0.062701</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23957</th>\n",
" <td>5097107</td>\n",
" <td>0.142857</td>\n",
" <td>21</td>\n",
" <td>3</td>\n",
" <td>18</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>88.500825</td>\n",
" <td>41.618960</td>\n",
" <td>5.0</td>\n",
" <td>8014.0</td>\n",
" <td>1025</td>\n",
" <td>362.0</td>\n",
" <td>1.0</td>\n",
" <td>0.470266</td>\n",
" <td>0.384393</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23958</th>\n",
" <td>5097108</td>\n",
" <td>0.000000</td>\n",
" <td>5</td>\n",
" <td>0</td>\n",
" <td>5</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>28.174149</td>\n",
" <td>29.941170</td>\n",
" <td>5.0</td>\n",
" <td>8014.0</td>\n",
" <td>1025</td>\n",
" <td>362.0</td>\n",
" <td>1.0</td>\n",
" <td>1.062718</td>\n",
" <td>0.385965</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23959</th>\n",
" <td>5097129</td>\n",
" <td>0.000000</td>\n",
" <td>7</td>\n",
" <td>0</td>\n",
" <td>7</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>109.583732</td>\n",
" <td>47.813799</td>\n",
" <td>8.0</td>\n",
" <td>8011.0</td>\n",
" <td>1025</td>\n",
" <td>277.0</td>\n",
" <td>1.0</td>\n",
" <td>0.436322</td>\n",
" <td>0.208633</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23960</th>\n",
" <td>5097130</td>\n",
" <td>0.000000</td>\n",
" <td>13</td>\n",
" <td>0</td>\n",
" <td>13</td>\n",
" <td>31</td>\n",
" <td>-62</td>\n",
" <td>116.886388</td>\n",
" <td>46.443726</td>\n",
" <td>8.0</td>\n",
" <td>8011.0</td>\n",
" <td>1025</td>\n",
" <td>277.0</td>\n",
" <td>1.0</td>\n",
" <td>0.397341</td>\n",
" <td>0.024876</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23961</th>\n",
" <td>5097138</td>\n",
" <td>0.000000</td>\n",
" <td>23</td>\n",
" <td>0</td>\n",
" <td>23</td>\n",
" <td>33</td>\n",
" <td>-61</td>\n",
" <td>98.189777</td>\n",
" <td>40.062807</td>\n",
" <td>8.0</td>\n",
" <td>8011.0</td>\n",
" <td>1025</td>\n",
" <td>277.0</td>\n",
" <td>1.0</td>\n",
" <td>0.408014</td>\n",
" <td>0.114458</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23962</th>\n",
" <td>5097141</td>\n",
" <td>0.000000</td>\n",
" <td>6</td>\n",
" <td>0</td>\n",
" <td>6</td>\n",
" <td>55</td>\n",
" <td>133</td>\n",
" <td>35.341745</td>\n",
" <td>24.241518</td>\n",
" <td>8.0</td>\n",
" <td>8011.0</td>\n",
" <td>1025</td>\n",
" <td>277.0</td>\n",
" <td>1.0</td>\n",
" <td>0.685917</td>\n",
" <td>0.287500</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23963</th>\n",
" <td>5097142</td>\n",
" <td>0.333333</td>\n",
" <td>6</td>\n",
" <td>2</td>\n",
" <td>4</td>\n",
" <td>48</td>\n",
" <td>-133</td>\n",
" <td>33.443353</td>\n",
" <td>37.638591</td>\n",
" <td>8.0</td>\n",
" <td>8011.0</td>\n",
" <td>1025</td>\n",
" <td>277.0</td>\n",
" <td>1.0</td>\n",
" <td>1.125443</td>\n",
" <td>0.606742</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23964</th>\n",
" <td>5097143</td>\n",
" <td>0.000000</td>\n",
" <td>23</td>\n",
" <td>0</td>\n",
" <td>23</td>\n",
" <td>37</td>\n",
" <td>48</td>\n",
" <td>109.884484</td>\n",
" <td>41.534111</td>\n",
" <td>8.0</td>\n",
" <td>8011.0</td>\n",
" <td>1025</td>\n",
" <td>277.0</td>\n",
" <td>1.0</td>\n",
" <td>0.377980</td>\n",
" <td>0.045977</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23965</th>\n",
" <td>5097144</td>\n",
" <td>0.205882</td>\n",
" <td>102</td>\n",
" <td>21</td>\n",
" <td>81</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>468.788104</td>\n",
" <td>117.987055</td>\n",
" <td>8.0</td>\n",
" <td>8011.0</td>\n",
" <td>1025</td>\n",
" <td>277.0</td>\n",
" <td>1.0</td>\n",
" <td>0.251685</td>\n",
" <td>0.219267</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23966</th>\n",
" <td>5097145</td>\n",
" <td>0.904762</td>\n",
" <td>21</td>\n",
" <td>19</td>\n",
" <td>2</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>90.048705</td>\n",
" <td>52.128374</td>\n",
" <td>8.0</td>\n",
" <td>8011.0</td>\n",
" <td>1025</td>\n",
" <td>277.0</td>\n",
" <td>1.0</td>\n",
" <td>0.578891</td>\n",
" <td>0.842262</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23967</th>\n",
" <td>5097147</td>\n",
" <td>0.000000</td>\n",
" <td>45</td>\n",
" <td>0</td>\n",
" <td>45</td>\n",
" <td>35</td>\n",
" <td>-62</td>\n",
" <td>223.258083</td>\n",
" <td>79.895403</td>\n",
" <td>8.0</td>\n",
" <td>8011.0</td>\n",
" <td>1025</td>\n",
" <td>277.0</td>\n",
" <td>1.0</td>\n",
" <td>0.357861</td>\n",
" <td>0.032922</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23968</th>\n",
" <td>5097148</td>\n",
" <td>0.000000</td>\n",
" <td>53</td>\n",
" <td>0</td>\n",
" <td>53</td>\n",
" <td>1</td>\n",
" <td>118</td>\n",
" <td>214.516672</td>\n",
" <td>81.732726</td>\n",
" <td>8.0</td>\n",
" <td>8011.0</td>\n",
" <td>1025</td>\n",
" <td>277.0</td>\n",
" <td>1.0</td>\n",
" <td>0.381009</td>\n",
" <td>0.206054</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23969</th>\n",
" <td>5097149</td>\n",
" <td>0.000000</td>\n",
" <td>9</td>\n",
" <td>0</td>\n",
" <td>9</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>42.854700</td>\n",
" <td>41.618186</td>\n",
" <td>8.0</td>\n",
" <td>8011.0</td>\n",
" <td>1025</td>\n",
" <td>277.0</td>\n",
" <td>1.0</td>\n",
" <td>0.971146</td>\n",
" <td>0.337143</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>23970 rows × 16 columns</p>\n",
"</div>"
],
"text/plain": [
" zone fully_shaded_ratio_2m n_cells null_cells non_null_cells \\\n",
"0 4965782 0.031056 322 10 312 \n",
"1 4965783 0.000000 55 0 55 \n",
"2 4965784 0.000000 18 0 18 \n",
"3 4965785 0.000000 12 0 12 \n",
"4 4965875 0.000000 6 0 6 \n",
"5 4965876 0.146667 75 11 64 \n",
"6 4965878 0.000000 9 0 9 \n",
"7 4965879 0.400000 45 18 27 \n",
"8 4965884 0.093750 32 3 29 \n",
"9 4965886 0.000000 75 0 75 \n",
"10 4972730 0.000000 15 0 15 \n",
"11 4977601 0.021277 47 1 46 \n",
"12 5031245 0.056497 177 10 167 \n",
"13 5031246 0.031250 32 1 31 \n",
"14 5031249 0.068027 147 10 137 \n",
"15 5031254 0.000000 11 0 11 \n",
"16 5031260 0.000000 7 0 7 \n",
"17 5031269 0.000000 8 0 8 \n",
"18 5031275 0.000000 8 0 8 \n",
"19 5031603 0.000000 2 0 2 \n",
"20 5031660 0.000000 6 0 6 \n",
"21 5031667 0.000000 20 0 20 \n",
"22 5031668 0.086957 23 2 21 \n",
"23 5031703 0.200000 15 3 12 \n",
"24 5031849 0.000000 35 0 35 \n",
"25 5031857 0.000000 19 0 19 \n",
"26 5031866 0.416667 12 5 7 \n",
"27 5031872 0.000000 1 0 1 \n",
"28 5031875 0.000000 5 0 5 \n",
"29 5032059 0.500000 2 1 1 \n",
"... ... ... ... ... ... \n",
"23940 5097068 0.000000 66 0 66 \n",
"23941 5097069 0.071429 14 1 13 \n",
"23942 5097070 0.000000 13 0 13 \n",
"23943 5097071 0.047619 21 1 20 \n",
"23944 5097076 0.000000 12 0 12 \n",
"23945 5097080 0.000000 6 0 6 \n",
"23946 5097081 0.750000 4 3 1 \n",
"23947 5097086 0.000000 26 0 26 \n",
"23948 5097087 0.844444 45 38 7 \n",
"23949 5097090 0.000000 39 0 39 \n",
"23950 5097092 0.000000 3 0 3 \n",
"23951 5097093 0.000000 4 0 4 \n",
"23952 5097094 0.000000 12 0 12 \n",
"23953 5097097 0.857143 14 12 2 \n",
"23954 5097098 0.000000 14 0 14 \n",
"23955 5097105 0.000000 33 0 33 \n",
"23956 5097106 0.000000 40 0 40 \n",
"23957 5097107 0.142857 21 3 18 \n",
"23958 5097108 0.000000 5 0 5 \n",
"23959 5097129 0.000000 7 0 7 \n",
"23960 5097130 0.000000 13 0 13 \n",
"23961 5097138 0.000000 23 0 23 \n",
"23962 5097141 0.000000 6 0 6 \n",
"23963 5097142 0.333333 6 2 4 \n",
"23964 5097143 0.000000 23 0 23 \n",
"23965 5097144 0.205882 102 21 81 \n",
"23966 5097145 0.904762 21 19 2 \n",
"23967 5097147 0.000000 45 0 45 \n",
"23968 5097148 0.000000 53 0 53 \n",
"23969 5097149 0.000000 9 0 9 \n",
"\n",
" NEIGUNG AUSRICHTUN FLAECHE SHAPE_Leng GASTW GBAUP GKAT \\\n",
"0 0 0 1289.608452 196.890521 9.0 8014.0 1025 \n",
"1 3 -24 560.036571 97.901422 1.0 8014.0 1060 \n",
"2 0 0 73.745743 44.447665 1.0 8014.0 1060 \n",
"3 0 0 204.889465 86.303247 9.0 8014.0 1025 \n",
"4 0 0 41.788788 29.008722 23.0 8015.0 1025 \n",
"5 0 0 2635.931059 247.909594 23.0 8015.0 1025 \n",
"6 0 0 1938.065681 259.313613 23.0 8015.0 1025 \n",
"7 0 0 182.631292 58.902105 23.0 8015.0 1025 \n",
"8 0 0 636.709326 258.545440 23.0 8015.0 1025 \n",
"9 0 0 293.774672 99.982577 9.0 8014.0 1025 \n",
"10 24 -78 119.978332 51.104449 3.0 8013.0 1025 \n",
"11 0 0 661.683103 135.693397 4.0 8013.0 1060 \n",
"12 0 0 939.826579 224.210407 5.0 8018.0 1060 \n",
"13 0 0 1186.279210 276.588492 5.0 8018.0 1060 \n",
"14 0 0 818.552360 208.911747 5.0 8018.0 1060 \n",
"15 0 0 40.755698 29.124265 5.0 8018.0 1060 \n",
"16 0 0 32.506871 28.542027 5.0 8018.0 1060 \n",
"17 0 0 38.084736 27.728889 5.0 8018.0 1060 \n",
"18 0 0 33.370309 28.795176 5.0 8018.0 1060 \n",
"19 0 0 211.987975 152.039389 7.0 8015.0 1060 \n",
"20 0 0 21.434018 18.638709 5.0 8016.0 1030 \n",
"21 0 0 86.622891 62.476428 5.0 8016.0 1030 \n",
"22 0 0 94.583084 88.551837 5.0 8016.0 1030 \n",
"23 0 0 1749.853582 883.846590 6.0 8018.0 1060 \n",
"24 0 0 590.026405 116.975482 7.0 8021.0 1025 \n",
"25 0 0 409.432946 262.015433 7.0 8021.0 1025 \n",
"26 0 0 48.068482 30.739744 5.0 8016.0 1040 \n",
"27 1 129 57.948718 29.802854 5.0 8016.0 1040 \n",
"28 38 125 29.295900 20.849144 5.0 8016.0 1040 \n",
"29 0 0 335.198181 100.261822 7.0 8013.0 1025 \n",
"... ... ... ... ... ... ... ... \n",
"23940 0 0 261.888561 65.514620 8.0 8012.0 1030 \n",
"23941 38 123 69.189981 32.547997 8.0 8012.0 1030 \n",
"23942 38 -57 66.355573 30.614168 8.0 8012.0 1030 \n",
"23943 0 0 86.315952 50.196239 8.0 8012.0 1030 \n",
"23944 0 0 160.133540 129.706367 8.0 8012.0 1030 \n",
"23945 0 0 23.292598 24.066004 8.0 8012.0 1030 \n",
"23946 0 0 18.616667 22.245987 8.0 8012.0 1030 \n",
"23947 0 0 132.388355 114.277534 7.0 8017.0 1040 \n",
"23948 0 0 483.483078 107.815944 7.0 8017.0 1040 \n",
"23949 0 0 161.785347 77.067440 7.0 8017.0 1040 \n",
"23950 0 0 14.134757 15.065601 7.0 8017.0 1040 \n",
"23951 0 0 18.313333 18.252096 7.0 8017.0 1040 \n",
"23952 0 0 201.961897 73.813516 7.0 8017.0 1040 \n",
"23953 0 0 54.362110 54.514112 7.0 8017.0 1040 \n",
"23954 0 0 103.289530 67.163530 7.0 8017.0 1040 \n",
"23955 0 0 204.892636 139.946860 5.0 8014.0 1025 \n",
"23956 0 0 155.017225 54.159230 5.0 8014.0 1025 \n",
"23957 0 0 88.500825 41.618960 5.0 8014.0 1025 \n",
"23958 0 0 28.174149 29.941170 5.0 8014.0 1025 \n",
"23959 0 0 109.583732 47.813799 8.0 8011.0 1025 \n",
"23960 31 -62 116.886388 46.443726 8.0 8011.0 1025 \n",
"23961 33 -61 98.189777 40.062807 8.0 8011.0 1025 \n",
"23962 55 133 35.341745 24.241518 8.0 8011.0 1025 \n",
"23963 48 -133 33.443353 37.638591 8.0 8011.0 1025 \n",
"23964 37 48 109.884484 41.534111 8.0 8011.0 1025 \n",
"23965 0 0 468.788104 117.987055 8.0 8011.0 1025 \n",
"23966 0 0 90.048705 52.128374 8.0 8011.0 1025 \n",
"23967 35 -62 223.258083 79.895403 8.0 8011.0 1025 \n",
"23968 1 118 214.516672 81.732726 8.0 8011.0 1025 \n",
"23969 0 0 42.854700 41.618186 8.0 8011.0 1025 \n",
"\n",
" GAREA n_neighbors perim_ratio fully_shaded_ratio \n",
"0 243.0 5.0 0.152675 0.028300 \n",
"1 641.0 7.0 0.174813 0.022354 \n",
"2 641.0 7.0 0.602715 0.136054 \n",
"3 241.0 5.0 0.421219 0.053708 \n",
"4 389.0 6.0 0.694175 0.172619 \n",
"5 389.0 6.0 0.094050 0.231743 \n",
"6 389.0 6.0 0.133800 0.034000 \n",
"7 389.0 6.0 0.322519 0.373626 \n",
"8 389.0 6.0 0.406065 0.248011 \n",
"9 315.0 3.0 0.340338 0.089438 \n",
"10 179.0 3.0 0.425947 0.006849 \n",
"11 653.0 3.0 0.205073 0.000843 \n",
"12 1244.0 5.0 0.238566 0.066642 \n",
"13 1244.0 5.0 0.233156 0.004357 \n",
"14 1244.0 5.0 0.255221 0.061002 \n",
"15 1244.0 5.0 0.714606 0.012346 \n",
"16 1244.0 5.0 0.878031 0.209302 \n",
"17 1244.0 5.0 0.728084 0.092105 \n",
"18 1244.0 5.0 0.862898 0.196970 \n",
"19 1744.0 5.0 0.717208 0.350000 \n",
"20 229.0 0.0 0.869585 0.088889 \n",
"21 229.0 0.0 0.721246 0.048673 \n",
"22 229.0 0.0 0.936233 0.561765 \n",
"23 3622.0 0.0 0.505097 0.166667 \n",
"24 264.0 3.0 0.198255 0.059829 \n",
"25 264.0 3.0 0.639947 0.363636 \n",
"26 718.0 3.0 0.639499 0.238095 \n",
"27 718.0 3.0 0.514297 0.000000 \n",
"28 718.0 3.0 0.711674 0.289855 \n",
"29 321.0 1.0 0.299112 0.350000 \n",
"... ... ... ... ... \n",
"23940 179.0 0.0 0.250162 0.078319 \n",
"23941 179.0 0.0 0.470415 0.362385 \n",
"23942 179.0 0.0 0.461365 0.196172 \n",
"23943 179.0 0.0 0.581541 0.228986 \n",
"23944 179.0 0.0 0.809989 0.098522 \n",
"23945 179.0 0.0 1.033204 0.236559 \n",
"23946 179.0 0.0 1.194950 0.986301 \n",
"23947 818.0 2.0 0.863199 0.216630 \n",
"23948 818.0 2.0 0.222998 0.943152 \n",
"23949 818.0 2.0 0.476356 0.182410 \n",
"23950 818.0 2.0 1.065855 0.178571 \n",
"23951 818.0 2.0 0.996656 0.082192 \n",
"23952 818.0 2.0 0.365482 0.064935 \n",
"23953 818.0 2.0 1.002796 0.944444 \n",
"23954 818.0 2.0 0.650245 0.016598 \n",
"23955 362.0 1.0 0.683025 0.331606 \n",
"23956 362.0 1.0 0.349376 0.062701 \n",
"23957 362.0 1.0 0.470266 0.384393 \n",
"23958 362.0 1.0 1.062718 0.385965 \n",
"23959 277.0 1.0 0.436322 0.208633 \n",
"23960 277.0 1.0 0.397341 0.024876 \n",
"23961 277.0 1.0 0.408014 0.114458 \n",
"23962 277.0 1.0 0.685917 0.287500 \n",
"23963 277.0 1.0 1.125443 0.606742 \n",
"23964 277.0 1.0 0.377980 0.045977 \n",
"23965 277.0 1.0 0.251685 0.219267 \n",
"23966 277.0 1.0 0.578891 0.842262 \n",
"23967 277.0 1.0 0.357861 0.032922 \n",
"23968 277.0 1.0 0.381009 0.206054 \n",
"23969 277.0 1.0 0.971146 0.337143 \n",
"\n",
"[23970 rows x 16 columns]"
]
},
"execution_count": 35,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"learning_table"
]
},
{
"cell_type": "code",
"execution_count": 36,
"metadata": {},
"outputs": [],
"source": [
"n_est = 500\n",
"tree_depth = 100\n",
"\n",
"x = training.loc[ : , feature_names ]\n",
"t = training.loc[ : , label_name ]"
]
},
{
"cell_type": "code",
"execution_count": 37,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"CPU time: 97.86 seconds\n",
"Wall clock time: 26.24 seconds\n"
]
}
],
"source": [
"RF = RandomForestRegressor(n_estimators = n_est, max_depth = tree_depth, n_jobs = -1)\n",
"\n",
"tt = util.Timer()\n",
"RF.fit(x,t)\n",
"tt.stop()"
]
},
{
"cell_type": "code",
"execution_count": 83,
"metadata": {
"scrolled": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Training MSE: 0.003210\n"
]
}
],
"source": [
"y = RF.predict(x)\n",
"print( 'Training MSE: %f' %mse(y,t))"
]
},
{
"cell_type": "code",
"execution_count": 51,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Validation MSE: 0.023637\n"
]
}
],
"source": [
"x_val = validation.loc[ : , feature_names ]\n",
"t_val = validation.loc[ : , [label_name]]\n",
"\n",
"y_val = RF.predict(x_val)\n",
"print( 'Validation MSE: %f' %mse(y_val,t_val))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Cross-validation (alternative to fitting and prediction):"
]
},
{
"cell_type": "code",
"execution_count": 38,
"metadata": {},
"outputs": [],
"source": [
"x_crossval = learning_table.loc[ ind , feature_names ]\n",
"t_crossval = learning_table.loc[ ind , label_name ]"
]
},
{
"cell_type": "code",
"execution_count": 39,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"CPU time: 0.28 seconds\n",
"Wall clock time: 141.63 seconds\n"
]
}
],
"source": [
"tt = util.Timer()\n",
"RF_crossval = RandomForestRegressor(n_estimators = n_est, max_depth = tree_depth, n_jobs = -1)\n",
" \n",
"y_crossval = cross_val_predict(RF_crossval, x_crossval, t_crossval, cv=5, n_jobs=-1)\n",
"mse_crossval = mse(y_crossval, t_crossval)\n",
"\n",
"tt.stop()"
]
},
{
"cell_type": "code",
"execution_count": 40,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0.023551977851100376"
]
},
"execution_count": 40,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"mse_crossval"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Feature importance (all features)"
]
},
{
"cell_type": "code",
"execution_count": 41,
"metadata": {},
"outputs": [],
"source": [
"n_features = len(x.columns)\n",
"importance = np.mean([tree.feature_importances_ for tree in RF.estimators_],axis=0)\n",
"std = np.std([tree.feature_importances_ for tree in RF.estimators_],axis=0)\n",
"ind = np.argsort(importance)[-n_features:]"
]
},
{
"cell_type": "code",
"execution_count": 42,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[0.53780334 0.00457695 0.01224597 0.01168331 0.07929629 0.06632603\n",
" 0.03254912 0.04311914 0.0686765 0.02630833 0.02814861 0.01265385\n",
" 0.04958951 0.02702305]\n",
"[0.00777786 0.00121 0.00227352 0.00183785 0.00501323 0.00434619\n",
" 0.00351067 0.00405146 0.00510745 0.00249126 0.00276495 0.00172806\n",
" 0.00367226 0.00241346]\n",
"[ 1 3 2 11 9 13 10 6 7 12 5 8 4 0]\n"
]
}
],
"source": [
"print(importance)\n",
"print(std)\n",
"print(ind)"
]
},
{
"cell_type": "code",
"execution_count": 53,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Index(['fully_shaded_ratio_2m', 'null_cells', 'non_null_cells', 'n_cells',\n",
" 'NEIGUNG', 'AUSRICHTUN', 'FLAECHE', 'SHAPE_Leng', 'perim_ratio',\n",
" 'GASTW', 'GBAUP', 'GKAT', 'GAREA', 'n_neighbors'],\n",
" dtype='object')\n"
]
}
],
"source": [
"# rename features for plotting:\n",
"print(x.columns)\n",
"feature_names = np.asarray(['ratio_2m', 'n_shaded', 'n_unshaded', 'n_cells', 'roof_tilt', 'roof_orientation', 'roof_area', 'roof_perim', 'roof_shape_idx', 'building_levels', 'building_period', 'building_category', 'building_area', 'neighbor_count'])"
]
},
{
"cell_type": "code",
"execution_count": 54,
"metadata": {
"scrolled": false
},
"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\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\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"
],
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YDSulMkXKCI03LwnBw8L4givFMcimsKNGyieEcJZeHjC1yWGe4o4J5YAxFtJ6JMxgpsPuyOM+YlcYxmZIOT77NdsEqpFxOFFymuBtvd2xBoTfz43J/oID8LpeKzwQCFW8DjmZdHGgnVKPKRww8fbEm7UAQO/rsoLL4RaXmG+8PN9fXi/WfOJZw4xhFBi7vNQ5DMxE7k2fDsIQ4aLEj+nfOY8XlJu9AiOcOPGj5fGC0A/bxD9jFO44QXjOoATIiiv74O82sTaOoQSDxWxLJ41gHiUKC/yu8aPIW3FY+i5IwwJd4YbDwoss8jLWI7AmGOELBEufH8wPlwLzAkeVLBEBWA8nrfwdjE/+F4MT9gojhAwbYhHAEZeBz7JKtY4s3aT6y2Z4+Dri/ZQHXPSBfBDCcAADlqQmxyPAMTrxU0OD1W0rQX4Gze8L774woU2KTN80bZ/cgwPScUSgCx4x6vFjTTc8GJceeWV+QoUbsSIGm5seSV84HUI95pEjmFRCcBkeAAJD3Gz8QIwUpTGEoCEpAl9Mxbh6yAJFyHWEUmJCkD/xRzLA+i9hqz7jAxZefZ43fCAhBuikJAxC93xjiKW87JkeQAjhVci9XGsF8Th45LItRGvAEzEA8j1gPcwLw+g9zamUgDm5wH0nui8Hrpgj4BiHjEG0YwkjcjkJTykCBeuB7xeeAtZspKoAOShjOgAYjieEKVfWuOvZ9qL15V1tnhkw43oCd/DPNzSfv+QGx5V8cfjySX8nVcSSLwCMPI6wPtL2bSDJQ/RDI8133HJHAdfj2fgl54E+b6bV9slADNxVNO4T/EIwHi31yC0yZevD1P4buOdQvCFC0CEAOuWfMggHBFfMrj4w0NBJBwQGvSZahwfq+08xfMFxtN9pKiIZziKSgDmtQaQmwGhPUKRPtzGmhq/+Jw2s+gab0HkGsBoAtCPReR2EKyfYR1VZPYgwoDy4+Eb6QFEiOK1JByIZzWacVPEO8j6JZ/EEs84+GPwADIP8UokIsjw7HAzxKNHqM1vD8RNH881Hlk8TFhewiuR+jgWjxxhZ9Z64a3zoj/eayNeAZjIGkDWj9EW1gH6PfdgQzIP7YxcAxjp9S0ODyDzhzWARBPCRRoJNXibI9cARm6/A3uiFSzvIAEp1hrfaGPKUhISyHxiBbsK4C3Pb7mIL8uHleNdQkDIlFAva1P9mmB+5+/hoV08mowTnnD+7o3lFzzscr4POXtR6ZeJ5DV3WfbAQwFreSPXb8e6Dgj/c81Ehukj60nmOPiyWWJDaJ/v9cJu85XId09xHisBWJy0VVdMERWOB48TIRg8aiy+5gmXJzFunnj/WG/HjY/1H3xhITBYL8iXKCFPnqrDBaAXEZSL6CBk4J8eeXonTEO4iq08EImslSEDjC/o/DxUtJtz8BjxZUXbEHR86eGNpE3hGazRpkFRCcDwLGCekmFKeDQ8y9FnAbM2j5AV3gi+cBHN9MV7cWJ5ALkxED5EQBLW4ubhvR8w5QZJnfSThfRsIcO2G4Sg8+MbKQDh57OA2fzWZwEzBoSa/JY/9JWxJmzHcWR70ldumPzLTQsPJdnTiAEeBBBPiBHmA16HaBsJ+/HLyzPk10sR3ma+4e1ENFNvtCzgwnoAaQ/ihKxZH3ZN5NqIVwAi4GBFKNG/eSS/LGDmA8kQPBQhxPESRcsCToUA9FnAXBfMJ74/fJZ8+BrOWB5AvpNIeEHk8oDJdwohca4VhBzeNtanIVA4hrA39fHwxXcWIpkkFB4Y+D8PCXznsB6VyESsyAGeOx42ItcDM/8QLmTScy2TdMP8YD0kIW+fmcy8YW6y5pUHNb8RNOPEd1bkRtBw4EGXBAxEIw9HeMp5wMtvI2jq4tqnT6ytgzXfF/wtlgBEiJN4xHcIbScTm+xmPJY8YNEvLJnj4K9vHqD4PmftcqaaBGCmjmya9iseD6BvOl9UfLkhHrj5ICj4AuWL1m8hwxcBC3V5EmVND4v4ycDjizHy1VR4uljDxJcv5fk1ZWzlwA2fGxMCgkxYFnwjTqLtA5jXJtZ86XMDJvzIlyMZmXyBIAQI18SyohKAvPKK7VlgwY0GhvALz6ykXXhkCLXQdm4G3IhY88W2Ij6TNZYApAxuMIgvPCoIEM+f8BFjhAhGkDKGeGi5QcXDN5oApD48IH4fQMYe1vQt/E0khNq4mbOoHUGOCMS7wTGIQm6ALKYnnEz/aDdzh4XveCtivdUjljDAuxNtH0A8Y96S5QH05RHq5sEHIcFNOd5rI14BSD0IZuYEAoPrhrFkDBDPkdeb3wcQwcj1hteJ6wAPm7dUhoBpA98tfC/4fQB5oGQ+hM+hWONMGXxncN0jmlj/yEMEwo0EEq4pHl7xVNNXHlLwgCJ+eGDkoZMHWm987/DD9cgDWX5v1uHhmPrCPWR8F1IuSV2//PKLe9glIYXvAR5I/PXs6+RBN/xVcFwf9CfaHpg8XCOW8QL6V8HxcJPfq+Coi4cfojMw4LqL3AcwrwchljPwkM44wI6lNHi8eeChP96SOQ58hxFlQPzlFX5O01tsQs2SAEwIlw4WgeAQiHcz2OD0SC0VAREIJ+DfWEHyUqa/t7Y4R95vso8QTObbXoqzD/HUJQEYDyUdIwIBJCABGMBBU5NFIAEC7O+IV5mICMtWZIUnQMicCAiebbLAM9kkADN5dNW3rCYgAZjVw6/OZwkBwtg+cz0yvJslCJLaTTbOZ/0ja1czNfnDA5MATOrUUWEiIAIiIAIiIAIikP4EJADTf4zUQhEQAREQAREQARFIKgEJwKTiVGEikJkE/DuI/euxovWStxywd1aimXNkLLIFRfgbFciQZMuIyLeTRNbrN/2O9uaN/EaC0Bmb7/Iu1PD3uHIeG1STTUn5xWkw8K+h4xVd0d6I47fAoV1sBcI2IxjrwchkZxsPtjhhL0SyTckAJWOSfmLhdUTrW171xsOBjFIyPdkCha2BeOUY2wKxfUw8Bm9Cb2TokznMFitkmYa/y5qscvpIVinHk7lNBjgbT5PpGv5aNPa2ZEE/+1SSZUpGLlu1sAclW/9EGmUx19ktgKx5tm4h45RXH7IPHkbCBVntZKfSX5IE2EcUbrQhvH7GhvZGM9qS3xtN4mGmY0SgoAQkAAtKTueJQBYRYDsJsgzZqJZXYkUzFqNzQ+aGF8+7dH0Z0QQgW0Ww/ibyfdHJFIBsW8Megv6dyOFlk/3HtjFsiVGc5sUZW3sg6NiyKPwtD4githhhoTrb9YQLQIQTWyCxNQZb7LAXI1vbsP0OQoNNj8MFIO+7ZcuTSGNLDxbBJ2rs60gyApteswUOe9uxkJ4NpGkDoj6WIabgzXlsJ8TegbzpAqHOPnOIPIxX9iHAeLcucw4BxjYo7C/H1kW8KcYbIhGRT91sgQQH9odkDkduTg57tqhh2xreesK2OvSFunndGK/fw9hehW2M2JuOzcbZDuf11193ohT27P3njfVkbHkSbmzTg/jkIYMHF5kIpIqABGCqyKteEQgYAQQDN1/ekBD5WjveFoJYYwNbbo6JWDQBGO/5hfEAxhKA8daf7OO8AOS1gogUNqvGq+WNfRrZGNd76bwARKiwuS6igk22Iw3h6BMEfB2IqDFjxiStCwgwygx/VzYeNfa5Y76waXQsY39BRBRj6r2aPiOTPvtNudkLDnEb+ZCB9w3xxwMImy3HskaNGrkNhXlTiTfmLRsbs2dk+Lu+4wXEayMRgoxFrK1D8EjiFWVfO0SkTARSRUACMFXkVa8IBIwAb3Fo3bq187QMGDAgV+v9e2LxjhAyw3gjARvZ4sHhRk5WMq9YQ/CFb7AcbwjYbyiNCCLMxgbbhPLYjDg8BIwAwROGJwevEu985Rg8Pj7US2iVtzNEmi8nWggYDxebJj///PNOBOMpoz/czNl42RviBYFBOJyNjxHH9B1xEf7O6mjDHy7OeLsB9eCh9IYIp09+k2EvAPEUInqoj/bEsqISgIR5CbMy3uHGpsKErWkjY5GX4dkkXI2ICjfELmKYTahjZblOnjzZCeNwAZpXXfBD/LFxtjfmBuFhNjsuiCFACR0jAPNqJ0Kct3MQWg6vuyD16RwRKCwBCcDCEtT5IpAlBLh5ERrknaeEtrzxxgJCYdzY8J5447VyCCNCdwg+hBBr/Xi/Z/iL4+MRgH49GW9Y4a0ArLlCKLD9BW9NCBeACDTegkE4Ea8YQoo90ljTxd9pP0KFt8zgjeFfXvuEsfs/6+YiBSB9R/zyGjveHIGg5G0ICEIEL94t/w5oBCACgHefIvoQitTB2zM4LvxtIJFTJ1ycIXCpE6EAQzxWhDFZa4kY5i0T4SFgxoZQPW3iXDhH28bC18FbUxDKkYa49ud5D2s86wIJ3fKqMIR/uPl33hKO9WHUyDoJzRL2pk+EfcPNrz8lLB8rNM2Y8WowBDJv4Qk3xo8fGDI/eBMOY0K/MP8aNkLiRxxxhHtwgSVvOOHhBo9spBGiZ+4TiuehhLIIwzPv8zLW0DI2XAeUKxOBVBKQAEwlfdUtAgEj4F8bxns4WeCPIcR4PyjChDVY0czfLHnlVsuWLd06Ku8pjEcAIuDwOrLWixuoNxIbuFnHSgJB8PB+VoQYYT7eY4rFCgFHCkDqZX0YyQDhr9Hz7/3F++RDtQhAwpQIN/92BryHeOgoN9aGveECkLrwirFeDO8lnlcEK4KW/0cKQJJWSPZAFGIIUEKMeA0pw4u6/JJASCThVXgYoguvGOIGwRTLEI68Ozqyf3gweWUZXjzeyxzNEPE8QJDwgYgKN8aW9X6xPHsknTA+nMur/yKNeelD4wg8+OGh9cZr61jnBzP/GkkEKSFlhHv4+Ppz8LQyHhiCn3ns30OdFydeP4ggZoyqV68esKtfzc00AhKAmTai6o8IFCEBMiDxwiCiWOCPsfYJDwjChJumN7xH3CBJAMDjhgj0xsJ8zsPiEYAcSzkIq3AjSxivU7gAJHkDLww3btqLl8YbIWPf7kQEIGsbEWR4kPAgesOrRJIG7SO5AEMAItzCQ7f8nXVl3PR5Z2xeFhmeJXSKcEEgkWBBJipCDA9SpACkTNbcwYS6SV7gX8Rvu3btDkkCIQGGdXeRhnc1vI/xTicEYPi88Od5AYh3DgEUzbwARKDDOty8AMzrHdz8nffWkilM370nNrwM5gFzEA8yAowlANTlxTwPJohlxGH4GkTGlwcdws8k1IQb8x1PLHMC7+bo0aPthhtucP9GM+rngYAHGNbSykQg1QQkAFM9AqpfBAJG4JJLLjG212B9GmKLmxoeJjxx3giL4TlisT5hUMKRrHviJooXKFywxSMAmzdv7kJ7hHDDjfVmJBmEl8cNlhs64gnRhFcH7xfhVNbs+a1VEhGA3bt3dx5DxFSksb6PBBjCe5hfAxh5k49na5tIAUhoEkF29913u9Au6xrPPvvsPAVgZNu2bt3qXmaPCEOkM3ZFtQYwFSFgRC4PAH7tXvgDSKzLivWfrNdDxJGggke6Xr16dtZZZ7m5HW6DBw92nklCwiwpyMtYmsBcZnsY5mSk8QCBuOUBAG+lTARSTUACMNUjoPpFIGAEWENFiNAnQ+BFidxKBe8bXjFCa6yX88aWIGR0JioA4/UAcpNmDR/hORIivBGCxVNHyLggAjA/DyCeLb+lRzIFIO0nZE7GKCLTJ1jk5QGMNpXYl5H2sd4Pj19RCUDW9+HlYs+9cPOh0vySQPAskwQS6SElfMtci0wCQajh+UMg44ELT8TJ75Lye1YiIHlIwHPKgwLLEiIFIPsa4i3E+xy5tjC8HpJHENjh3u3wz+kbyVB4O8P3CsyvrfpcBIqKgARgUZFVuSKQoQTY1wyvH5mueFDwirHxcLix5xyep8iwHR44PGOJCsB41wByk8ZLE7mWzCcShCcz+DaSkIIXKdwi1wCyxoy99SIzoL0XEe8nXkIs2QIQ0czecqzlI2yLRQpA9qIjkSKah8oLML+2r6gEIKF1Eku8qKKd1OW3geFhIJYhsh9//HG37pd6kvMAACAASURBVNCvnUT0IQx5aPAhdspApDFmeF8Rf4mGrPFYsyaRkLBnxvpJkopIFiKpCSMETDIRfEliimUkB7FWk+Sg8I2rOYf1mWxqzTF4CmUikA4EJADTYRTUBhEIGAH2e+OGz7q+aBmNeIII+7IWjvAlHg9EH9nD3GATFYBsrcGNGA8fgoZsXTxF0bKA8TiSgDFq1Ci3oJ+3SkydOtUJJMLP3gNIO2gj3kWyP3nzCGLD76cX/iYQ+ol3h9AyYT5u5itXrnR9wzMXmQWMOE5GCDivaREpAPGukSlM//AYImDoL+smEa30EzFOGN4LwLw2gvaeMOpOJAnEbwRNxnb4RtCExiM3giakD9/wkDohfoQT6yQJd/uNoPEohm8EzTIAwumE9adPn36I6PWZ3LQfwc94sv6SLWiYlwg/1iNGZhwzZwivk2nNuBJOZr0l8wwvKg8vGJ5lHjRoA0KV/9NH5hVMI7OgOYeQM2s5WV9YkE22A/b1oOYGhIAEYEAGSs0UgXQiwDonbtYIOzIao228iygiK5NjWQtIIgI3Qm7GiQpA+k49CDW/DyBr+hCi3IjDy/PHIfwQO3xO+BOPEfu/hb9ejXVZCFnOIVkk1j6ACBu/DyCeT9a8IQrw6ETbB7A4BSBeWfqBN4z1bHi2yExFgPP2FtaxeS9ZflnAJEMQcsYS2QaG4xGi1EXWdPir4CK3f2FMEIDhr//jfES5fxUc44GYJ6s3/I0see3h6K+P8LnAsaz1w3tH+JV5SFnMw2ivgkNssj0L3krCwiSAIPjDM88ZVzzShONJAOHBgdAxW8VEvgqONvHwwvXBvGd8ZCKQLgQkANNlJNQOERABERABERABESgmAhKAxQRa1YiACIiACIiACIhAuhCQAEyXkVA7REAEREAEREAERKCYCEgAFhNoVSMCIiACIiACIiAC6UJAAjBdRkLtEAEREAEREAEREIFiIiABWEygVY0IiIAIiIAIiIAIpAsBCcB0GQm1QwREQAREQAREQASKiYAEYDGBVjUiIAIiIAIiIAIikC4EJADTZSQC3g5emfTjjz+63fPZoV8mAiIgAiIgAtlAgDcF7dy5071Fhg3Yg2ISgEEZqTRv5w8//BB6f2aaN1XNEwEREAEREIGkE+CNQrwLPCgmARiUkUrzdvLS9kqVKrlXavEuUZkIiIAIiIAIZAOB//mf/3EOEF43GP5ayHTvuwRguo9QQNrHBcDERwhKAAZk0NRMERABERCBQhMI6v1PArDQQ68CIBDUC0CjJwIiIAIiIAKFIRDU+58EYGFGXeeGCAT1AtAQioAIiIAIiEBhCAT1/icBWJhR17kSgJoDIiACIiACWU1AAjCrh1+dD+oFoJETAREQAREQgcIQCOr9Tx7Awoy6zpUHUHNABERABEQgqwlIAGb18KvzQb0ANHIiIAIiIAIiUBgCQb3/yQNYmFHXufIAag6IgAiIgAhkNQEJwKwefnU+qBeARk4EREAEREAECkMgqPc/eQALM+o6Vx5AzQEREAEREIGsJiABmNXDr84H9QLQyImACIiACIhAYQgE9f4nD2BhRl3nygOoOSACIiACIpDVBCQAs3r41fnQBTBmjFUoU0ZAREAEREAERCC1BPr0KZb6JQCLBbMqSVcCEoDpOjJqlwiIgAhkKQEJwJgDrxBwll4Xye62BGCyiao8ERABERCBQhGQAJQALNQE0slxEZAAjAuTDhIBERABESguAhKAEoDFNdeyuR4JwGweffVdBERABNKQgASgBGAaTstQk2rVqmUDBw50P0E2CcAgj57aLgIiIAIZSEACUAIwHab11KlTncjbvn17ruZs2bLFypYta0cddVShm/n3v//dJk6caCtWrLCcnByrW7euDRs2zFq3bl3osvMrQAIwP0L6XAREQAREoFgJSABKABb1hNu7d6+VLl06ZjV5CcBktg2Bedxxx1mLFi2sUqVKNmXKFHv44Yft008/tQYNGiSzqkPKkgAsUrwqXAREQAREIFECEoASgInOmfyOb968udWrV8+JvunTpztP2+WXX+4E15o1a6xKlSp22WWX2YMPPmjlypWzRYsWOVEWbnfffbfzzkWGgDds2GADBgywhQsXWsmSJa1NmzY2fvx4q1atWn7Nivo5bevUqZMNHTrUfU7bzzjjDCtVqpRNmzbN9eHee++1Ll262F/+8hd76aWX7Nhjj7XHHnvM2rZtG3edEoBxo9KBIiACIiACSSSwOycnemk9e0b9O1G3ZJr2AUwmzTQvCxG1bNky69evn/Xq1csOHjxo8+bNszPPPNMJurVr11r//v3toosusgkTJhgeQkKziLB//etfrncIQ37CBSDlNGzY0IWEx4wZY/v27XPllC9f3onIRO3AgQOu/MGDBztx5wXg559/7v6GMHz++ecNMUqYuH379k4gjh492l544QVDjOYVmibEzI83LoAaNWrYDm0Enegw6XgREAEREIFCECjRt29CZ3OvTaZJACaTZpqXhUjasWOHLV++PM+Wvvjii04gbt261R2TVwg4XADOnz/fed0QkIgpbPXq1c7DuGTJEmvcuHFCZB566CF74IEH7KuvvnJePS8A9+/fbx988IH7nf9XrFjRrrjiCufNxDZt2mS/+93v7OOPP7YmTZpErRPv5fDhww/5TAIwoSHSwSIgAiIgAoUkIAFYMIDaCLoA3BCAderUsUmTJoXOfvfdd+3+++93go2nAbx3v/32m+3atct59OIRgOPGjXPeNwRguFWuXNnGjh1rXbt2jbu1zz33nPXu3dteeeUVa9WqVeg82o6gfPzxx0N/q1mzpvMQ3nrrre5vPB0RfubcP//5z1HrlAcw7qHQgSIgAiIgAkVIQCHggsGVACwAN0RU/fr1XZgWW79+vZ166ql2/fXXu7AqawA//PBDFx7etm2bS8iIRwAi8vhhHWG4cT7rAK+99tq4WktYt0ePHoYX8tJLL811TmTb+TDaVjQlSpSw2bNnW7t27eKqU2sA48Kkg0RABERABIqLgJJAYpKWACzARIwUUS+//LJ17tzZrYnDc4aNGDHC7rrrrpAAfPbZZ61v3762c+fOXDXGGwJeunSpNWrUKN/W4vnr2bOn8W808SYBmC9CHSACIiACIpAJBCQAJQCTPY8jRRT77rHNCh5Bsn8/+ugju/32223jxo0hAbh48WI7//zzbcGCBS5ZhOQKfqIlgZAcEp4E4jOJ8+sHoo8wMV5E1vR5K1OmjFvnh0kA5kdRn4uACIiACGQEAQlACcBkT+RoIoq1eyRdsNFzs2bN3LYqiDEfAqYNJIUQlv3ll19c5m2yt4GhXe+9994h3e3WrZsLQUsAJnsmqDwREAEREIG0JSABKAGYtpMzgxqmNYAZNJjqigiIgAhkAgEJQAnATJjH6d4HCcB0HyG1TwREQASyjIAEoARgpkx5tm8h4ziaPfnkky7snCqTAEwVedUrAiIgAiIQlYAEoARgplwaiL///Oc/UbvDq+J4Y0iqTAIwVeRVrwiIgAiIgARg4nNA28AkzkxnRCEQ1FfhaDBFQAREQAREoDAEgnr/kwAszKjr3BCBoF4AGkIREAEREAERKAyBoN7/JAALM+o6VwJQc0AEREAERCCrCUgAZvXwq/NBvQA0ciIgAiIgAiJQGAJBvf/JA1iYUde58gBqDoiACIiACGQ1AQnArB5+dT6rs4CLaasBzTIREAEREIH0IyABmH5johYVIwEJwGKErapEQAREQATShoAEYNoMhRqSCgISgKmgrjpFQAREQARSTUACMNUjoPpTSkACMKX4VbkIiIAIiECKCEgApgi8qk0PAhKA6TEOaoUIiIAIiEDxEpAALF7eWVnbpk2b7Nprr7XFixfb4Ycfbtu3b0+Yw7Bhw2zOnDm2YsUKd2737t1dOfytMCYBWBh6OlcEREAERCCoBCQAgzpyAWr3kCFDbO7cuTZ79myrWLGiHXvssTFbX6JECXdsu3btQsft2rXLcnJyrGrVqlEFYPPmza1+/fo2ZsyYhMhIACaESweLgAiIgAhkCAEJwAwZyKLoxt69e6106dKFLrpDhw5WtmxZmzZtWlxlRROAkSdGegAlAONCm/sgbQNTAGg6RQREQAQyg4AEYGaMY1J6gYiqV6+eE33Tp0+3unXr2owZM2zAgAG2cOFCK1mypLVp08bGjx9v1apVC9U5ceJEe/jhh+3777+32rVr25133ulCvlitWrVs/fr1oWO7detmU6dOzbO9kcfXrFnT1q1bZ7FCwIjBSHG5du1aV3d+lk0ewN05Oblx9OyZ63dEukwEREAERCA7CEgAZsc4x9VLBOCyZcusX79+1qtXLztw4IB16dLFee8Ire7bt8/69+9v5cuXt0WLFrkyCdV26tTJfd6qVSt7/fXXbfDgwTZ//nxr0aKFbdmyxbp27WoVKlSwsWPHWpkyZVwYOC/jeELEU6ZMcWKzVKlSdswxx8QUgDt27LC2bds68XrPPfe4ojmHcyONMDI/3rgAatSoYTvGjLEKZcrExSmoB5Xo2zdm0w8ePBjUrqndIiACIiACCRKQAEwQWCYfjgBETC1fvtx1ExGHsMKbhkjCVq9e7TyDS5YsscaNG9v555/vfn/qqadCaDp27Gi7d+926/4w1vJVqlQppucvnGu0EHB+SSDxhoApZ/jw4YcMowSgmQRgJl/d6psIiIAI5CYgAagZESKAiKpTp45NmjTJ/W3cuHE2evRoJwDDrXLlys6bh2evSpUq7hhCu974jJ81a9aknQDMZg+gQsC62EVABERABDwBCUDNhVwCMDyTNlLI+QPx5rEOkHV+CEDCv4hBb/zO5999913aCcDI4c6mNYCHTHUlgejqFwEREIGsJSABmLVDf2jHI8OosULAS5cutUaNGuUZAt6zZ49bD4glGgImCeW5556zK6+8MtTI/ELAl1xyiZ1yyilOeCZiEoCJ0NKxIiACIiACmUJAAjBTRjIJ/YgUgKwJa9iwoZUrVy5XEgi/+yQQNmJmzR/h4pYtW9prr73mkkAWLFhglFcQAXjyySe7hJKhQ4faEUccYYSc8xOAffr0cZtEv/DCC669eCbJWs7PJADzI6TPRUAEREAEMpGABGAmjmoB+xQtkWLDhg2F2gamIAIQETlo0CC3/cvxxx+f7zYw1PH111+7dYgrV660X3/91a1b1DYw+UwEhYALeKXoNBEQAREIPgEJwOCPoXpQCALyABYCnk4VAREQAREILAEJwMAOnRqeDAISgMmgqDJEQAREQASCRkACMGgjFvD2zpw50/rmsSExb/348ssvi7WHEoDFiluViYAIiIAIpAkBCcA0GYhsacbOnTtt8+bNUbt7+OGHGyKwOE0CsDhpqy4REAEREIF0ISABmC4joXakhEBQL4CUwFKlIiACIiACGUMgqPe/Egf13qqMmYSp7EhQL4BUMlPdIiACIiACwScQ1PufBGDw515a9CCoF0BawFMjREAEREAEAksgqPc/CcDATrn0anhQL4D0oqjWiIAIiIAIBI1AUO9/EoBBm2lp2t6gXgBpilPNEgEREAERCAiBoN7/JAADMsHSvZkZnQWsN32k+/RT+0RABEQgZQQkAFOGXhWnAwEJwHQYBbVBBERABESguAlIABY3cdWXVgQkANNqONQYERABERCBYiIgAVhMoFVNehKQAEzPcVGrREAEREAEipaABGDR8i1w6Zs2bbJrr73WFi9ebLwhY/v27QUuq1atWjZw4ED3k662bt06q127ti1fvtzq168ftZmLFi2yFi1a2LZt26xSpUpJ6YoEYFIwqhAREAEREIGAEZAATNMBGzJkiM2dO9dmz55tFStWtGOPPbbALQ2CANy/f79t2bLFjj76aDvssMMkAAs82mEnKgkkGRRVhgiIgAhkJAEJwCQP6969e6106dKFLrVDhw5WtmxZmzZtWqHLCoIAjKeT8gDGQ0kCMEFKOlwEREAEspKABGAhh7158+ZWr149J/qmT59udevWtRkzZtiAAQNs4cKFVrJkSWvTpo2NHz/eqlWrFqpt4sSJ9vDDD9v333/vQp933nmnC/liCLb169eHju3WrZtNnTo1ZkuHDRtmkydPts2bN1vVqlUNATlu3LhQeX369LFvv/3WXnzxRatcubKrj795w+OIt/GHH36w6tWrW5cuXWzo0KEu/IxR/pw5c6xfv342YsQI++WXX+zSSy+1SZMm5QrHTpkyxR588EFbu3at68eNN95o/fv3z5dytBDwG2+84cLWMGrSpInBoUePHqEQcM+ePe2zzz6zpUuX2hFHHGH/+c9/3HGnnnqqzZw5M986OUAh4Lgw6SAREAEREIEMIyABWMgBRQAuW7bMCaNevXrZgQMHnHjCezdmzBjbt2+fE0Dly5c3PFgYQqtTp07u81atWtnrr79ugwcPtvnz57s1boRCu3btahUqVLCxY8damTJlXBg4L3vppZdc3bNmzXIClPWDK1eutOuuuy4kAHfu3Gn33nuvXXLJJcbxf/3rX+3LL790YglD1F100UV23HHH2apVq9y5gwYNcu3yAhDBes4559gjjzzihBN1nn322SGxhRi8++677bHHHrMGDRq49XyU8+ijjzrxFssiBSCir06dOnb99dc7tgi9W265xQlcvwZw165dduaZZ9qf//xnGz16tN1222323HPP2RdffBGTV3g7MkkA7s7JyY24Z89cvzMnZSIgAiIgAiKQywGyY4fTG0GxtNkIGgG4Y8cOJ3YwRFzbtm2dB6xGjRrub6tXr3bCbMmSJda4cWM7//zz3e9PPfVUiHfHjh1t9+7dbt0f1q5dO+dZy8/zx7EIrCeffNL+8Y9/hDx24QOJJ+6CCy5wnkns4MGDzss3fPhwJ7Ci2UMPPWTPP/+8E15eACISEWonnHCC+9u8efOcF3Djxo2uvBNPPNFGjRplV199dahIzsGTRzJLLIsUgHfccYfzOCJSS5Qo4U5F4FF+eBLIxx9/bBdeeKH7bOTIkc7r2qxZszyrysnJMX68IQAZpx1jxliFMmWCMv+jtrNE374x28+4y0RABERABEQAAvIAFnIeIADxVOH9wgi74o1CAIYbYVe8eXj2qlSp4o4J94rxGT9r1qxxpyUiAPGWISq5wRNu/tOf/mSXXXZZKJkCAXjDDTfYrbfeGmoSnrMrr7zShXkxvIJ4JAkT41nDc8kTwc8//+w+JwRMiNu3j78hfBGpeDZPP/10l6iCt5KwtzfKwXuJ5y6WRQrA9u3bu1A1YW1vr7zyiuMSmQWMWET8EcZ+4IEHYtZDPxC+kSYBWMgLQaeLgAiIgAgEioAEYCGHCwHItiWIJyxSyPniEUqsA2SdHwKQ4xGD3vidz7/77ruEBSAn/Prrr877uGDBArfOj3WF7733nvMIRksCoc2IKQTRJ598Yk2bNnXCqHXr1k6wEU4m1Ou3n4kmAP3koZ5TTjnFeQGfeeYZFyYOt1KlSrn2JCIAaRuc8hOAhNwJm3/00Ud2+eWX28svvxyznkz2ACoEXMiLWaeLgAiIQBYRkAAs5GBHCsBYIWCSFRo1apRnCHjPnj1uPSCWiAcwsgv/+te/3No+1iaeddZZ+QpAhN6ECRNC4pPyevfu7byC4QKQcO6GDRvcOkHsrbfect5GHwImNNy3b1+76667EqaaVwiY8Lm322+/3Xn4wj2AhIRpP+sqEa+IaBJF4rVMWgN4SJ+1DUy800DHiYAIiEDWEZAALOSQRwpAwrANGza0cuXK5UoC4XefBMLaNtb8ES5u2bKlvfbaay7ZAu8d5SUqAFknyD56eN6OOuoo5zVjXSChYTKC8/MAElola5g1gqxRZB0i3kDKDBeAJIGce+65LnuZiYNIRGCSeIE9/fTTLuuXcCzrIPG2sYYQwUZCSSyLFIAITULrhK4RlYhZkkBIcPECcMWKFa7PCFVC3n/729/s5ptvNv5+0kknxTWyEoBxYdJBIiACIiACGUZAArCQAxopACkO8VKYbWASFYAISjxjX331lRNtZ5xxhsvqRVxi+QlAjkGAIhwRbSR2sJ0KYd9wAUg9iDHK/ve//+28f4g+1up5e/bZZ40EEjx3ZJ3SFrZyYU1fIgKQY/GGIugQsmQb49lj6xcE4JFHHumENqFrEmC8XXHFFW694fvvv2+EnvMzCcD8COlzERABERCBTCQgAZiJo1oEffL7AOJdyySTAMyk0VRfREAEREAE4iUgARgvqSw/TgIwgBNAawADOGhqsgiIgAgUDwEJwOLhXKhaeKsFoddoVrNmTbdXXlFbYQXg/fffb/xEM/YofPPNN4u6C1HLlwcwJdhVqQiIgAiIQIoJSACmeADiqZ63eOS1jx7bvCAC091YM8hPNGPvwOOPPz4lXZAATAl2VSoCIiACIpBiAhKAKR4AVZ9aAkG9AFJLTbWLgAiIgAgEnUBQ739p8yq4oE+AbG9/UC+AbB839V8EREAERKBwBIJ6/5MALNy46+z/n0BQLwANoAiIgAiIgAgUhkBQ738SgIUZdZ0bIhDUC0BDKAIiIAIiIAKFIRDU+58EYGFGXedKAGoOiIAIiIAIZDUBCcCsHn51PiOzgLX/nya2CIiACIhAPgQkADVFspqABGBWD786LwIiIAJZS0ACMGuHXh2HgASg5oEIiIAIiEA2EpAAzMZRV59DBCQANRlEQAREQASykYAEYDaOuvosAag5IAIiIAIikNUEJABTPPybNm2ya6+91hYvXmy81m379u1F0qLmzZtb/fr1bcyYMUVSfjIKLVGihM2ePdvatWuXjOLiKkMewLgw6SAREAEREIEMIyABmOIBHTJkiM2dO9cJn4oVK9qxxx5bJC3iPbwIzPLlyyet/O7duzvBOmfOnITKHDZsmDtnxYoVuc5DDFeuXNmOOOKIhMorzMESgIWhp3NFQAREQASCSkACsIAjt3fvXitdunQBz/6/0zp06GBly5a1adOmFbqsaAX85z//ccKvKCzZArAo2phfmRKA+RHS5yIgAiIgAplIQAIwzlElhFqvXj0n+qZPn25169a1GTNm2IABA2zhwoVWsmRJa9OmjY0fP96qVasWKnXixIn28MMP2/fff2+1a9e2O++804V8sVq1atn69etDx3br1s2mTp0as0UbNmyIWaf3rt144402YsQIW7dune3fv99atGiRKwSMgKUtM2fOdF48+jZq1CijnxjtGDhwoD3//PPuX9rftGlTmzJliv3ud78z6hk+fHiutr777rvufLyaeDR/+OEHq169unXp0sWGDh3qhCjl9ujRI9d5lImYjAwBr1q1ym666Sb7+OOP7aijjrIrr7zSHn30UStXrpw73wtQ2vXII48YfercubMLc8crejNFAO7Oyfk/pj17hv7Pw4VMBERABERABCIJSADGOScQNsuWLbN+/fpZr1697MCBA07YcINFcOzbt8/69+/vQqyLFi1ypSKCOnXq5D5v1aqVvf766zZ48GCbP3++E2Rbtmyxrl27WoUKFWzs2LFWpkwZFwbOyw4ePGgNGzaMWSfCDMGJKBo5cqSVKlXKzjjjjEMEIG1HHD7wwAN23HHHubYiCBFdderUcUKtT58+duGFF7pyELj/9V//ZQ0aNHCicdeuXY4DEwgBh1WpUsUJZITnRRdd5MqlvOuuu84GDRrk+v7rr7/aXXfdZfPmzbMFCxa48+gzfQ8XgHv27HHtaNKkiROaP//8s/Xu3duaNWsWEskIQNp9zTXXOKH47bffhnhTZzTLyckxfrzR/ho1atiOMWOsQpkycc6G9DusRN++URvFnJGJgAiIgAiIgARgAecAAnDHjh22fPlyVwIirm3btrZ27VonILDVq1c7z+CSJUuscePGdv7557vfn3rqqVCtHTt2tN27d7t1fxgJD5UqVcrX8xdvnQjA+++/3zZu3GjHHHNMqN7wJJDvvvvOiSs8dIg0b4jUs88+253vPXWIqt///vfukAkTJtg999xjrNXD4g0BP/TQQ86T+Nlnn7nz8loDGC4AJ02a5DyJeB69F+uNN96wyy67zH788UfnZaV+xDb9Qehi8EWszpo1K+pIR/NccqAEYAEvDJ0mAiIgAiIQSALyAMY5bAgoRBPCBBs3bpyNHj3aCcBwI4kBbx6ePTxiHENo1xuf8bNmzZqEBWA8dSJw8NB98803udoVLgBffPFFJ5Qiw4N4xq644gon1hCAN9xwgxOr3vC2EYbF+xlLAL700kvO64l4xFOIdxQvJ168eAUgHkPENmFlbwhwxPJ7773nPIEIQLyoXkxzHJ5AvI7vvPNO1JHNVA+gQsBxXsg6TAREQAREwBGQAIxzIkRuoxIp5HwxCBTWAbLODwGIEEIMeuN3PsdrhSXiAYynzry8a+HtR+ARAv7yyy9DnjPfPtbXsW7PrwEM35aGzN327dubDytG8wB+8sknLvxM2LZ169YuvIs3jjV6vqx4PIA333yzrVy5MpeQ8wLw/ffftwsuuCCqB5L1imQX+zB8fsObKWsAc/VT7wLOb9j1uQiIgAhkPQEJwDinQKQAjBUCXrp0qTVq1CjPEDDr21gPmKgAjKfOeATg119/baeccop5IRUNQTwCkDWCP/30k7322muhIhB6hIq9wOUD1u7hFfQCkBDzc8895zx14VaQEHDkNjQSgGYmARjnVa3DREAERCB7CUgAxjn2kQLQJ2TgMQtPAuF3733CY0aoldBty5YtnVAiEYLkB59tm4gHMJ464xGAdJmEjo8++sh55kjs2Lp1q/O2kTDypz/9KS4PIELuySeftLffftuqVq3qvH2s02NrGzKkWQdJeBZvIJnIXgA+++yzLsHkww8/tBNOOMElzrD3X2QSyB/+8Ac777zz3JpBQr0ISTx/PlM6mgdSAlACMM5LWoeJgAiIQFYTkACMc/ijvUkjvy1ZKDrWNjCJKbbNRgAAIABJREFUegA5Pr864xWA7A9Iti5b2pAwgoA799xznVhDBMbjAUSUEUpmmxbW+vltYBC5kydPdtm2l156qcvkpV1eAPJ3zmP7HP5W2G1gwjeilgCUAIzzktZhIiACIpDVBCQAs3r41XmtAdQcEAEREAERyEYCEoDZOOrqc4iABKAmgwiIgAiIQDYSkABMo1Fn+5a+eWzoW7NmTZe1K0suAQnA5PJUaSIgAiIgAsEgIAGYRuO0c+dO27x5c9QW8WozRKAsuQQkAJPLU6WJgAiIgAgEg4AEYDDGSa0sIgJBvQCKCIeKFQEREAERyBICQb3/lTiol5xmyRQt2m4G9QIoWioqXQREQAREINMJBPX+JwGY6TOzmPoX1AugmPCoGhEQAREQgQwlENT7nwRghk7I4u5WUC+A4uak+kRABERABDKLQFDvfxKAmTUPU9aboF4AKQOmikVABERABDKCQFDvfxKAGTH9Ut+JtM8C1nt9Uz9J1AIREAERyEACEoAZOKjqUvwEJADjZ6UjRUAEREAEMoeABGDmjKV6UgACEoAFgKZTREAEREAEAk9AAjDwQ6gOFIaABGBh6OlcERABERCBoBKQACymkWvevLnVr1/fxowZU6Aa161bZ7Vr17bly5e7chYtWmQtWrSwbdu2WaVKlaKWOXXqVBs4cKBt377dfT5s2DCbM2eOrVixokBtyMSTJAAzcVTVJxEQAREQgfwISADmRyhJnxdWAO7fv9+2bNliRx99tB122GEFEoC7du2ynJwcq1q1apJ6FfxiJACDP4bqgQiIgAiIQOIEJAATZ1agMworACMrLYgHsEANL+aTELolSpSwkiVLFkvNEoDFglmViIAIiIAIpBkBCcBiGhAEYL169VxtzzzzjJUqVcr69etn9957rxM8/MyePdvatWsXahGhXULG3bt3t3hCwIR8hw4dalu3brXWrVtb06ZNXfl5hYApl8847pFHHrG9e/da586dXZ2HH364a8dPP/1kvXv3tnfeeceqV69u9913n91xxx0utMxPfvboo4/alClTbM2aNValShW77LLL7MEHH7Ry5cq5U32YGiaDBw+2r7/+2r755hsX7uY8jl27dq3VqlXLbrzxRuvfv3+oyiFDhjhmP/zwg2tbly5dXP992/NrG59LAMZDSceIgAiIgAhkGgEJwGIaUQTgsmXLrFevXk74ffbZZ9anTx8ntq677rpCC8BPP/3Uzj33XLv//vvtiiuusHnz5tndd99tvDI5lgBEQF1zzTV200032bfffmudOnUKtQk0F198sROUTzzxhBNWgwYNsiVLlrh64hGA9O/MM890Ag4hh4C76KKLbMKECSEBCIfGjRvbQw895MLTJ5xwgj377LOu/Y899pg1aNDArX2EE4KyW7du7twRI0a4so477jhbtWqV+5z2ISTjtXQUgLtzcv6v+T17hv5ftmzZeLul40RABERABEQgJgEJwGKaIAjAn3/+2b788ksn9rDbbrvNXn31VVu9enWhBSAijoSQN998M9QjvHkIwVgCkFDyd9995zySWMeOHV34ddasWfbPf/7TTjvtNFu6dKk1atTIfY5IrFOnjo0ePTouARiJ98UXX3QCGFGJ4QHs0aOHS0xBKHo78cQTbdSoUXb11VeH/obge+ONN2zx4sVRRw0B+fzzzztxnZexBpIfb1wANWrUsB1jxliFMmWKaTbErqZE375RD0DMy0RABERABEQgGQQkAJNBMY4yEIAnnXSSTZ48OXT0K6+8Yh06dLDffvvNJXYUJgSMl6x9+/YuBOpt7NixzosWSwCSWDJ37tzQOXgC8aYR8vXtQzCFr8kjlEs98XgA3333XectROQy2fbt2+f6S0IKHi0EYN++fd3fvDCmTccee6yVKVMmV72cW7FiRdu8ebNr70svveS8lYhSyuPzChUqOKGdl5EJPXz48EM+lgCMYxLrEBEQAREQgYwhIAFYTEOZnwAkvPryyy87EecNgfT444/HtQaQrWEI/SYqABGHbA3jDVGHNw7PIH+/6qqrnMcsXABWrlzZCcv8BOD69evt1FNPteuvv96FlhGOH374oQuD++1rIreqoR0IPNb0sS7wnHPOyTVCeCpZH/jJJ5+4tYuIOdY7IgzxWrKW0QveaEMbBA+gQsDFdFGqGhEQARHIYgISgMU0+D4EjCfM2+233+68bPytWrVqTlT5JAcSIU4++WSXCBFPEgghYIQPIVJvhE8JCeeXBJKXAPQhYEKqDRs2dMUmEgJG0BKGDheQhHHvuuuumAKQelgHiGeQY6MZQo91hISvvZGsglcwlgCMLCsd1wDmaqPeBVxMV6iqEQEREIHsIiABWEzj7ZNASFRA2Hz++ecuaQEhw++ItZUrVzqv14EDB4wM1w8++MCeeuqpuAQgHrHzzjvPHnjgAZdJ/PbbbzvxlF8SSCwPIGhIAvn3v/9tEydOdEkgt9xyi/O+jRw50iWOxDI8iYSmCdOS/fvRRx8Zonfjxo35CsCnn37aZf1ST9u2bZ2IRIjiOSTRw4enZ8yY4RJICGPjDWQbGQnAYprUqkYEREAERCCwBCQAi2noEIB169Z14o4MV0KZCD/Wx7H27ccff3TJEIgkslpZv4coTGQbGNYX4kX85ZdfrFWrVnbhhRfGtQ1MXh5A0LANDCFbvw0MgozQ7z333OPan5+RLEJyBqKsWbNmbquWrl275isAKRdOnIuHlHD4GWec4er2YXKyfekz4vDSSy+1Jk2auLedSADmNyr6XAREQAREINsJSABm+wxIsP/suUfW7IIFC6xly5YJnp1+hysEnH5johaJgAiIgAgUPQEJwKJnHOga8PyRYYv3DW8gXjdCuGzYnMiGy+kKQQIwXUdG7RIBERABEShKAhKARUk3A8p+66233Lo/3uRRvnx5t86QsHTNmjVt5syZeYaB+Zw9D9PdJADTfYTUPhEQAREQgaIgIAFYFFSzpMydO3eG9uSL7DLeQURgupsEYLqPkNonAiIgAiJQFAQkAIuCqsoMDAEJwMAMlRoqAiIgAiKQRAISgEmEqaKCRyCoF0DwSKvFIiACIiAC6UQgqPe/Egf1YtR0mkeBbUtQL4DAAlfDRUAEREAE0oJAUO9/EoBpMX2C34igXgDBJ68eiIAIiIAIpJJAUO9/EoCpnDUZVHdQL4AMGgJ1RQREQAREIAUEgnr/kwBMwWTJxCqDegFk4lioTyIgAiIgAsVHIKj3PwnA4psjGV1TWmUB9+mT0azVOREQAREQgfQhIAGYPmOhlqSAgARgCqCrShEQAREQgZQTkABM+RCoAakkIAGYSvqqWwREQAREIFUEJABTRV71pgUBCcC0GAY1QgREQAREoJgJSAAWM/B0rm7Tpk127bXX2uLFi41XuW3fvj1lza1Vq5YNHDjQ/RSlSQAWJV2VLQIiIAIikK4EJADTdWRS0K4hQ4bY3Llzbfbs2VaxYkU79thjU9CK/61yy5YtVrZsWTvqqKOKtA0SgEWKV4WLgAiIgAikKQEJwDQdmESatXfvXitdunQip0Q9tkOHDk50TZs2rdBlFbSAZPUl3volAOMlpeNEQAREQAQyiYAEYABHs3nz5lavXj0n+qZPn25169a1GTNm2IABA2zhwoVWsmRJa9OmjY0fP96qVasW6uHEiRPt4Ycftu+//95q165td955pwv5YoRc169fHzq2W7duNnXq1Jh0SpQoYRMmTLBXX33VFi1aZNWrV7cHH3zQrrrqqtB5GzdutEGDBtnbb7/t2tW0aVMbO3asqw/r3r27CzWfc845rr30ad26de7z8BAwdT3xxBP22muv2TvvvGM1a9a0yZMn2zHHHGO9e/e2pUuX2h//+Ed75pln7Pe//33co5pqAbg7J+f/2tqzZ+j/CHGZCIiACIiACBQVAQnAoiJbhOUiAJctW2b9+vWzXr162YEDB6xLly7OezdmzBjbt2+f9e/f38qXL++EGUZYt1OnTu7zVq1a2euvv26DBw+2+fPnW4sWLVzItWvXrlahQgUn0MqUKePCwLEMUVa1alV74IEHrFmzZk6Ejhw50latWmWnnXaa7dmzx+rXr28XXHCBE3OHHXaYjRgxwrX9iy++cGIPAfjyyy9b+/btjRA0r3hG3EYTgMcff7w9+uijrkyOXbFihZ100kmuHyeeeKL17NnTKlWqZG+++Waezc7JyTF+vHEB1KhRw3aMGWMVypQpwlGLXnSJvn2jfqBXXRf7UKhCERABEcgqAhKAARxuBOCOHTts+fLlrvWIuLZt29ratWudmMFWr17tPINLliyxxo0b2/nnn+9+f+qpp0I97tixo+3evdut+8PatWvnBFR+nj9fAALw+uuvNzyL3po0aWJnnXWW8wziocMj+NVXXxnHYoR4qWPOnDl2ySWXOAE4b94827BhQ64wdjQBiMfy3nvvdeV88skndu6559rf/vY3J/ywWbNmWY8ePezXX3/Nc1SHDRtmw4cPP+RzCcAAXghqsgiIgAiIQIEJSAAWGF3qTkQA1qlTxyZNmuQaMW7cOBs9erQTgOFWuXJl583Ds1elShV3DKFdb3zGz5o1awosAFkvSPnebr75ZueZe/fdd+2GG26wJ5980o488shc7cIz+PjjjzsPJgKQMDEiNtyiCcAXXnghFF6mr3j/vMDlXOq86KKLnDjGkxnN0s0DqBBw6q4j1SwCIiAC2UxAAjCAo48AJAxKOBeLFHK+S3jaWFfHOj8EIMeHizV+5/PvvvsuqQJw5cqVbp0eAu/zzz+3mTNnHkKZtXuEmP0aQDyC+QlAwth4KTHWCbKOES8oLDDC3YSzt23b5ryM8Viq1wDmaqNeBRfPkOkYERABERCBJBCQAEwCxOIuIlIAxgoBkxzRqFGjPEPAeONYD4gVJASMyCPc642wbIMGDdzf8FCyVg+xlpdHTgIwbPZIABb3paT6REAERCBrCUgABnDoIwUgCQMNGza0cuXK5UoC4XefBIKHjTV/hItbtmzpsmlJnliwYIFRXkEF4NFHH22jRo1y2b14+kjyIAnk9NNPDyWBkLxxzz332AknnODW+v3973+3W2+91f0uASgBGMBLUE0WAREQgcATkAAM4BBGCkC6gLAqzDYwBRWArOVDXL7//vtuGxgygjt37hyiyttF8AK+8cYbtnPnTkMMIkDZjgavoASgBGAAL0E1WQREQAQCT0ACMPBDmLoOkNkbvi4vdS0peM1aA1hwdjpTBERABEQguAQkAIM7dilvuQRgkodAawCTDFTFiYAIiIAI5EVAAlBzIyoB1vP1zWOTYt7C8eWXX7q9/eQBTOIEkgBMIkwVJQIiIAIiEIuABKDmR1QCrNfbvHlz1M8OP/xw9yq2TDCFgDNhFNUHERABERCBRAlIACZKTMdnFIGgXgAZNQjqjAiIgAiIQLETCOr9r8RBvSy12CdLJlYY1AsgE8dCfRIBERABESg+AkG9/0kAFt8cyeiagnoBZPSgqHMiIAIiIAJFTiCo9z8JwCKfGtlRQVAvgOwYHfVSBERABESgqAgE9f4nAVhUMyLLyg3qBZBlw6TuioAIiIAIJJlAUO9/EoBJngjZWlyxZgFrm5dsnWbqtwiIgAikHQEJwLQbEjWoOAlIABYnbdUlAiIgAiKQLgQkANNlJNSOlBCQAEwJdlUqAiIgAiKQYgISgCkeAFWfWgISgKnlr9pFQAREQARSQ0ACMDXcVWuaEJAATJOBUDNEQAREQASKlYAEYLHiDn5lmzZtsmuvvdYWL15svBJu+/btge6UBGCgh0+NFwEREAERKCABCcACgsvW04YMGWJz58612bNnW8WKFe3YY48NNAoJwEAPnxovAiIgAiJQQAISgAUEF7TT9u7da6VLly50szt06GBly5a1adOmFbqsaAXs37/fSpQoYSVLliyS8iMLlQAsFsyqRAREQAREIM0ISACm2YAkqznNmze3evXqOdE3ffp0q1u3rs2YMcMGDBhgCxcudAKrTZs2Nn78eKtWrVqo2okTJ9rDDz9s33//vdWuXdvuvPNOF/LFatWqZevXrw8d261bN5s6dWrMJj/66KM2ZcoUW7NmjVWpUsUuu+wye/DBB61cuXLuPM4fOHCgPfPMMzZ48GD7+uuv7ZtvvnF1cx7Hrl271tV94403Wv/+/UP14Y3EE/nDDz9Y9erVrUuXLjZ06FAXmo7XiloA7s7J+b+m9Ozp/o+AlomACIiACIhAKglIAKaSfhHWjQBctmyZ9evXz3r16mUHDhxwAgnxMWbMGNu3b58TU+XLl7dFixa5liCmOnXq5D5v1aqVvf76606UzZ8/31q0aGFbtmyxrl27WoUKFWzs2LFWpkwZFwaOZZR15plnOgGHkKPOiy66yCZMmBASgH369LHGjRvbQw89ZFWrVrUTTjjBnn32Wbv77rvtscceswYNGtjy5cvtuuuuMwQlwhMbMWKEK+u4446zVatWuc8HDRrk2pyX5eTkGD/euABq1KhhO8aMsQplyiR9REr07XtImQcPHkx6PSpQBERABERABBIhIAGYCK0AHYsA3LFjhxNOGCKubdu2ToQheLDVq1c7z+CSJUucADv//PPd70899VSopx07drTdu3e7dX9Yu3btrFKlSvl6/vJC9eKLLzpRunXr1pAA7NGjh61YscIJRW8nnniijRo1yq6++urQ3xB8b7zxhktAiWYIyOeff94+++yzPEdq2LBhNnz48EM+lwAM0ORWU0VABERABApNQAKw0AjTswAEYJ06dWzSpEmugePGjbPRo0c7ARhulStXdt48PHuEaDnGe9g4js/4IYRbEAH47rvv2v333+/EJpMNz+Nvv/1mu3btct5IQsB9+/Z1f2PtH4ankeQSPIzhawE5F4/j5s2b3XEvvfSS81Z+++23rjw+xzv5888/5zkoxe0BVAg4Pa8PtUoEREAEsp2ABGCGzgAEYP369Z1AiibkfLfx5rEOkHV+CECORwx643c+/+677xIWgKwXPPXUU+366693oWXK//DDD11Ietu2bSFPImsAw7eTQeCxpo91geecc06uESpVqpRbH/jJJ59Y06ZNnTevdevWThjOmjXLHnnkkYS2pinqNYC5Gq93AWfo1aZuiYAIiEDwCEgABm/M4mpxpACMFQJeunSpNWrUKM8Q8J49e9x6wEQ9gC+//LJ17tzZrbnznjzCuHfddVdMAUg9rAPEM8ix0QyhxzpCL0w5pnfv3s4rmMjehBKAcU0nHSQCIiACIpBhBCQAM2xAfXciBSCJBw0bNnTZt+FJIPzuk0DmzJljrPkjXNyyZUt77bXXXELFggULjPISFYCs6yOBg/rI/v3oo4/s9ttvt40bN+YrAJ9++mmX9Tty5Ei3dhERydo+PIckerzyyivGljRkNrN+kTWKeAPZRkYCMEMntbolAiIgAiKQNAISgElDmV4FRQpAWrdhw4ZCbQOTqADkeNYUkpyBKGvWrJnLRCbEHCsE7EmSCcy5rB9kveAZZ5zhtoxp3769OwRxOnnyZCcOL730UmvSpImR5CEBmF5zUa0RAREQARFIPwISgOk3JmpRMRJQCLgYYasqERABERCBtCEgAZg2Q6GGpIKABGAqqKtOERABERCBVBOQAEz1CAS4/pkzZ7pEjWhWs2ZN+/LLL9O+dxKAaT9EaqAIiIAIiEAREJAALAKo2VLkzp07Q3vyRfaZ17EhAtPdJADTfYTUPhEQAREQgaIgIAFYFFRVZmAIBPUCCAxgNVQEREAERCAtCQT1/lfioF6ompYTKmiNCuoFEDTOaq8IiIAIiEB6EQjq/U8CML3mUWBbE9QLILDA1XAREAEREIG0IBDU+58EYFpMn+A3IqgXQPDJqwciIAIiIAKpJBDU+58EYCpnTQbVHdQLIIOGQF0RAREQARFIAYGg3v8kAFMwWTKxyiLNAu7TJxORqU8iIAIiIAIZQEACMAMGUV0oOAEJwIKz05kiIAIiIALBJSABGNyxU8uTQEACMAkQVYQIiIAIiEDgCEgABm7I1OBkEpAATCZNlSUCIiACIhAUAhKABRyp5s2bW/369W3MmDEFKmHdunVWu3ZtW758uStn0aJF1qJFC9u2bZtVqlQpaplTp061gQMH2vbt293nw4YNszlz5tiKFSsK1IZ0O6lWrVquf/wU1BJlIgFYUNI6TwREQAREIMgEJAALOHqFFYD79++3LVu22NFHH22HHXZYgQTgrl27LCcnx6pWrVrAXqTXafAoW7asHXXUUQVumARggdHpRBEQAREQgSwiIAFYwMEurACMrLYgHsACNj3tTtu7d6+VLl06Ke2SAEwKRhUiAiIgAiKQ4QQkAAs4wAjAevXqubOfeeYZK1WqlPXr18/uvfdeK1GihPuZPXu2tWvXLlQDoV1Cxt27d7d4QsCEfIcOHWpbt2611q1bW9OmTV35eYWAKZfPOO6RRx4xhFXnzp1dnYcffrhrx08//WS9e/e2d955x6pXr2733Xef3XHHHXGHXunXhAkT7NVXX3VeS8p48MEH7aqrrgr1c+PGjTZo0CB7++23rWTJkq49Y8eONUK8mG/nOeecY+PHj3fiDx6RIeANGzbYgAEDbOHCha6cNm3auOOrVasWquuBBx6w0aNH2549e6xjx452zDHH2Lx58+IOiysEXMALQKeJgAiIgAgEmoAEYAGHDwG4bNky69WrlxN+n332mfXp08eJreuuu67QAvDTTz+1c8891+6//3674oornKi5++67jVcgxxKAiM5rrrnGbrrpJvv222+tU6dOoTbR1YsvvtgJyieeeMKJQoTakiVLXD3xrL1DABJyRng1a9bMZsyYYSNHjrRVq1bZaaed5oQYaxovuOACVx7h7REjRjhWX3zxhRN7CMCXX37Z2rdvb0OGDHF9QkyHC0D+1rBhQxcShum+ffusf//+Vr58eSc8sRdeeMGuvfZae/zxx119tGXcuHF20kknpVQA7s7J+d9Z1bOn+4c+yERABERABEQgnQhIABZwNBCAP//8s3355ZdO7GG33Xab84ytXr260AIQEUdCyJtvvhlqId48hGAsAYg4+u6775xHEsMrhvds1qxZ9s9//tOJtKVLl1qjRo3c54jEOnXqOC9avALw+uuvt4kTJ4ba1aRJEzvrrLOcZ3Dy5MnOI/jVV1+FuOCJxPtJwsoll1ziBCD9wMMXHvoNF4Dz58+3tm3b2tq1a61GjRquLrjWrVvXCdbGjRvbeeedZ2eeeeYhbfntt9/yFICsmeTHGxcA5e8YM8YqlClTwNmQ+7QSffvm+gNiViYCIiACIiAC6URAArCAo4EAxNOE4PH2yiuvWIcOHQwBguerMCHgBg0aOA8ZIWBvhFHxAsYSgCRSzJ07N3QOnkC8c4R8ffsQQIhCb1WqVHH1xCsAp02bZl27dg2df/PNNzvB9e6779oNN9xgTz75pB155JG5yOIZxFOHtxQBSJgYkRdu4QIQTx6iFAEYbpUrV3bhZOoP/78/hrbQjrwyo1kjOHz48ENGXQKwgBeCThMBERABEQgkAQnAAg5bfgKQ8KoPc/oqCAUiguJZA0gYldBvogIQcYinzRuiDjGEZ5C/s1YvUgAipBCWhRGAK1eudCITgff555/bzJkzDyHL+ryKFSuG1gCGt5ODwwUgIo+fNWvW5CoHTyLrAAn9FkQAFocHUCHgAl5UOk0EREAERKDYCEgAFhC1DwETlvR2++23Oy8bfyNRAVHFujXsm2++sZNPPtmmTJkSlwAkBIyYe+ONN0LlX3311S4knF8SSF4C0IeAWa/I+jqsICFgRB7hXm+sVcRjyd8mTZrk1vWR1FGhQoWodH0SSCwBGCsE7EPYhIARypFt+fXXX1O6BjDUab0LuIBXl04TAREQAREoagISgAUk7JNASPjo27ev83rxf7Jv+R2xhleMDOEDBw44UfTBBx/YU089FZcA/OSTT9waN5ItyCQmo/auu+7KNwkklgeQrpIE8u9//9utm8NLecsttxh1kchBuDg/Y70jexeOGjXKZffi6SPJgzDz6aefHkoCOf744+2ee+6xE044wa31+/vf/2633nqr+z0eAeiTQMqVK5crCYTffRLI888/b926dXMC0LeFsHGqk0AkAPObRfpcBERABEQg1QQkAAs4AghAEhIQd88++6xLukD4kU2LSPrxxx+tR48e9tFHH9lxxx3nwpmIwkS2gWF9IV7EX375xVq1amUXXnhhXNvA5OUBpKtsA0Pmst8GBuFH6BexRvvzM/pGGJs63n//fbcNDCKVBBVvmzZtcoIX7+XOnTsNMdiyZUt7+OGHnVcwHgFIWfFsAwNvRB/rLq+88krneX3rrbfkAcxvIPW5CIiACIhAVhOQAMzq4Tf74YcfXBbsggULnEjLz6Ltb5jfOen8ufYBTOfRUdtEQAREQASKioAEYFGRTdNy8fzxCrkzzjjDeQMHDx7sMnK//vrr0GbRsZouAZjAwGoNYAKwdKgIiIAIiEBxEpAALE7aaVAX4VHW/ZFdy6bKrDMkLF2zZk23ni+vMDCf+z0PI7e3SYNuFbgJ8gAWGJ1OFAEREAERCDABCcAAD16ym856vc2bN0ctloQRRGCmmQRgpo2o+iMCIiACIhAPAQnAeCjpmIwlIAGYsUOrjomACIiACMQgIAGo6ZHVBIJ6AWT1oKnzIiACIiAChSYQ1PtfiYN6wWqhB18FmAX1AtDYiYAIiIAIiEBhCAT1/icBWJhR17khAkG9ADSEIiACIiACIlAYAkG9/0kAFmbUda4EoOaACIiACIhAVhOQAMzq4Vfng3oBaOREQAREQAREoDAEgnr/kwewMKOucw/1AI4ZYxXKlEkeGW0CnTyWKkkEREAERCDpBCQAk45UBQaJQJFtAyMBGKRpoLaKgAiIQNYRkADMuiFXh8MJSABqPoiACIgdeMfaAAAgAElEQVSACGQjAQnAbBx19VkhYM0BERABERCBrCYgAZiC4R82bJjNmTPHVqxYEXftzZs3t/r167v39uZlJUqUsEx6T2/ccApxoDyAhYCnU0VABERABAJLQAIwBUO3a9cuy8nJsapVq8ZduwRgbFSLFi2yFi1a2LZt26xSpUpxc5UAjBuVDhQBERABEcggAhKAARnMVAnAvXv3WunSpdOekgRg2g+RGigCIiACIpBGBCQACzAYiLE//vGPduSRR9rTTz/tBNL1119vhHaxHTt22K233urCvL/99ps1atTIRo8ebWeeeab7PDIEvG/fPhs0aJBNnz7dSpUqZb1797ZNmza5cigDy69OjiEEPGHCBHv11VcNQVS9enV78MEH7aqrrgr1ctWqVXbTTTfZxx9/bEcddZRdeeWV9uijj1q5cuXcMd27d7ft27fbOeecY+PHj3d9W7duXUxKeDPvuusue+655+znn3+2E0880W677Tbr1auXO++9995zPFauXGlVqlSxbt262YgRI+ywww5zn9eqVcsGDhzofrwR7m7Xrl2IKX2bNGmSzZ0719566y07/vjj7ZFHHrE///nPrn21a9fO1UbqmDp1ar6jm2wP4O6cnP+ts2dP90/ZsmXzbYMOEAEREAEREIHiJiABWADiiLHly5c70XbNNdc4MYVwQpi0atXKLrjgAid0hg4dahUrVrQnn3zSiZGvv/7a/T1SAN53331OhCEmTzvtNBs7dqw9++yzLqQZLgDzqvPiiy92vUAkEVZ+4IEHrFmzZjZjxgwbOXKkIfood8+ePVanTh1r0qSJDR8+3Ik1xCbHerFEP15++WVr3769DRkyxHjlcr169WJS6tSpk2NAuxG5a9euta1btxp/37hxo5188smOz4ABA+yf//ynXXfddXbDDTeExF28AvCEE05wgrZx48ZOnE6ePNnWr1/vGL/yyitOzP7rX/+yChUqWJkyZdzfIw2xyo83LoAaNWrYjiTtA1iib99cVeqV1QW4wHSKCIiACIhAkROQACwAYgTg/v377YMPPgidffbZZ9tFF11kl1xyiRNPiKsjjjgi9Pkf/vAHGzx4sPXp0+cQAYin7r//+7/dD0bZJ510kjVo0CCXAMyrTgSfF4B4IidOnBiqF7F31llnOc8gHjRE3ffffx/yTL3xxht22WWX2Y8//mjVqlVzQm3evHm2YcOGuEK/iNpTTjnF5s+f78RvpP31r391gvKrr75yAhWjLbQDD2fJkiXj9gDeeeeddu+997oydu/ebeXLlzfa36ZNG+fxjGcNIOIb8RtpEoAFuBB0igiIgAiIQGAJSAAWYOgQgHXr1rXHH388dPbll1/uvG942gh/4oEKt19//dUJvFGjRuUSgIggkhYIk+KJ83bFFVfYgQMHcgnAvOrEE+YF4LRp06xr166hcm6++WaXbfzuu+86jyVeRP7vLbJ+BCBeOwRdPPbCCy84Lyj9O/zwww85hX7giZsyZUroM0LBhHjx3hEujtcDSF3h4WzKxRNIf+MVgEXtAVQIOJ5Zo2NEQAREQARSTUACsAAjEC0hg/VqCDkEIKIEQRJpfH700UdHFYDvv/++Cx17w4tI+DA8BBy5DYyv04dv8bBFE4AIrnfeeccQg/7/kQLQ1+/XAPp688Pz2muvOY9nXgKQzypXruzCtd4QpHg38TISfsXbSXiY9nlD7CL2/LrKaFvcwJNtcWhzvAIwsj/JXgMYKl9vAslv6uhzERABERCBFBKQACwA/FgCsEuXLta2bVv79ttvnWcrmkWuASQETJLELbfc4g4n1Pv73//eeckSFYD9+vVzIVZv5557rhNbiYSASQKJVwCSgIGAe/vttxMKAeMlpR5CwCScXHjhhW59H8akhAkh83gF4OLFi+388893aw8T2V5HArAAF4BOEQEREAERCDwBCcACDGEsAUiok1Duzp07XbiX9XGsr2OtGh47MoKjJYGQJfy3v/3NTj31VOdBJIGDNYVs7IzFqjPcA4iHkXqbNm1qM2fOdNm2JIGcfvrpLgmEtYjnnXeea8OWLVtcEgiex/AkkEQEIG3r0aOHLVy40MaNG+eSQAjtsgayY8eOoSQQjvnLX/7ikjSoMzwJ5Pbbb3f1E+LFW0hG8YIFC5wgjlcAErbGmwj/P/3pTy4E7zObYw2xBGABLgCdIgIiIAIiEHgCEoAFGML8xBjizyc/ILLwZiEKychFpETbBobwp98GhkSRNWvWuC1h2FolEQHIukS8d4R0qZcEkc6dO4d6Ge82MPF6ACmYrW7uuOMOmzVrlv3yyy9uXR+/I/qw/LaBYRKSGUzyCev6SPRAEEduAxP5lpPwEDD1cB6ezs2bN7t1ganYBiYEWiHgAlxZOkUEREAERKC4CEgAFhfpBOoh+YO1hHjQfNZrAqfr0AQIyAOYACwdKgIiIAIikDEEJADTYCgJmbKGjnVwZKk+9thjLpRJwgZCUFZ0BCQAi46tShYBERABEUhfAhKAaTA27MtHmPYf//hHaONlv5lzqpvHXockteRlvNc4yCYBGOTRU9tFQAREQAQKSkACsKDksuQ8tnchwSIvI6kkyCYBGOTRU9tFQAREQAQKSkACsKDkdF5GEAjqBZAR8NUJERABERCBlBEI6v2vxEG9ZDVlkyaTKg7qBZBJY6C+iIAIiIAIFD+BoN7/JACLf65kZI1BvQAycjDUKREQAREQgWIjENT7nwRgsU2RzK4oqBdAZo+KeicCIiACIlDUBIJ6/5MALOqZkSXlB/UCyJLhUTdFQAREQASKiEBQ738SgEU0IbKtWGUBZ9uIq78iIAIiIAIQkADUPMhqAhKAWT386rwIiIAIZC0BCcCsHXp1PNcT0JgxVqFMmeRB0buAk8dSJYmACIiACCSdgARg0pGqwCARkAcwSKOltoqACIiACCSLgARgskiqnEASkAAM5LCp0SIgAiIgAoUkIAFYSID+9ObNm1v9+vVtzJgxBSpx3bp1Vrt2bVu+fLkrZ9GiRdaiRQvbtm2bVapUKWqZU6dOtYEDB9r27dvd58OGDbM5c+bYihUrCtSGgpxUokQJmz17trVr164gpxfonFq1arl+81NYkwAsLEGdLwIiIAIiEEQCEoBJGrXCCsD9+/fbli1b7Oijj7bDDjusQAJw165dlpOTY1WrVk1Sr/IvRgIwD0ZaA5j/5NERIiACIiACKSMgAZgk9IUVgJHNKIgHMEldSagYCUAJwIQmjA4WAREQARFICwISgEkaBgRgvXr1XGnPPPOMlSpVyvr162f33nuvIZKiCSVCu4SMu3fvbvGEgAn5Dh061LZu3WqtW7e2pk2buvLzCgFTLp9x3COPPGJ79+61zp07uzoPP/xw19affvrJevfube+8845Vr17d7rvvPrvjjjviDrFG9mvjxo02aNAge/vtt61kyZKu7rFjxxph27feessuv/xy27RpU66w9o033mgrV6609957z7Vp8eLFdtttt9nSpUudR7R9+/Y2cuRIK1u2rPs8MgRM6Hvy5Mm2efNm5/3s0KGDjRs3Lq6RTXYIeHdOzv/W27On+8e3Oa7G6CAREAEREAERKCYCEoBJAo0AXLZsmfXq1csJv88++8z69OnjxNZ1111XaAH46aef2rnnnmv333+/XXHFFTZv3jy7++677eDBgzEFIOvzrrnmGrvpppvs22+/tU6dOoXaRNcvvvhiJyifeOIJJwoRb0uWLHH1xLPGLlwA7tmzx61fvOCCC9y5hLJHjBjhuHzxxRdOFB9//PFOZMIJI/TN3+655x7Ha9WqVXbeeec5YXvppZe6sPhf/vIXO/PMM23KlCmHCMCXXnrJlTVr1iyrW7euE5eISZhHM0Lk/HjjAvj/2jsTMB3L9o1fiAw19iXZRcm+bxXZspWt5UNZY0RHlkISESHEILvQQpZkKSRL+SS+ZN+zhJEsFQ6JUfgf5/V9z/ufYd5593m28z6OOWrmvZ97+V334znf67qv+8mXL59cCtMxMKliYhJ1C/uwkAAJkAAJkIDVCFAAhskiEIDnzp2Tffv2qdhDgRdr+fLlsn///pAFIEQcEkJWrVrlGTG8eRCCyXkAEUo+evSoii+UZ599Vj1zEEwHDx6U4sWLq6etYsWK+jlEYtGiRWXcuHEBC0B44UaNGiUHDhzwMIDXEZ5OJKfUr19fhejevXtl3bp12h88hU8++aQKtyxZskjbtm0lKipKpk2b5pnnd999JzVr1pQrV65I+vTpE3kAx44dq3XRpuHVTM6k8BYOGTLkjioUgGG6EdgMCZAACZCALQhQAIbJTBCAhQsX1lCkUZYtW6bhyGvXrqk37PZs2UBCwOXKldNQKELARkFoFV7A5AQgPGgrVqzwXAMBBi8bQr7G+OARgyg0StasWbWfQD2A3bt3VzEGkZawwDM4adIk9YzCuwhPZlxcnOTJk0fatWunr6MBGxR48SBCE4o5eNHQBoQ0BGvCEDDaqVGjhnpCGzRoII0aNVJBCd5JlUh7ABkCDtMNxWZIgARIgAQiSoACMEx4fQlACJrFixeriDMK9odBGPmzBxChVYR+AxWAEIfwvhkFog7HxMAziL8/88wzGhJNKADhiYOwDFQAQuBt375d5s6dewfVHDlySKZMmfTvxYoVk65du6ogzJUrl4Z2W7ZsqZ9B4CEsjX2Bt5f8+fNLunTp7tgDePXqVVmzZo2sXbtWFi1apMfpYD+hPx7BcO8B9IyZWcBhurPYDAmQAAmQQCQIUACGiaoRAoaXyij9+/dXLxv+BqEDUdWtWzf9+PDhwyqEIH78EYAIAUPMrVy50tN+q1atNCTsKwnEmwA0QsDYr1ihQgVtN5QQ8IwZM6Rfv36a0BIdHe2VLMKwX3zxhdbFvj+Efw2vYZs2bfR3I0ScVCPJnQN46NAheeihh3TfYfny5X1alwLQJyJWIAESIAEScCABCsAwGdVIAkHyQUxMjHrC8P/IvsXvEGtITkCG8M2bN1X8bNy4UaZPn+6XANyyZYsmR4wcOVIPXcbeuYEDB/pMAknOA4ipw9v2xx9/yJQpU9Rj9uqrrwr6QtYtwsW+SlJJIEZSR968eeXkyZPy+eefS58+fQS/JxS/pUuXlkqVKsnMmTM93SBZpGrVqtKhQwflBy8p9hTCwzdx4kStl1AAIjMaiSRVqlSRDBkyaAge+wIRGvbnPEQKQF8W5uckQAIkQAJOJEABGCarQgBi/xrE3bx58zTpAsIP2bQQSadPn1ZRs2nTJt37hv17EIWBHAMDcQMv4u+//y5169bVxAh/joHx5gHE1HEMDLJojWNgIPwQ+kVWLsbvq9x+DAy8dxC38FRevnxZM3zr1KkjY8aMSeQVrFy5siafoF+88SRhwd8HDBggmzdvVoFbpEgRzV7G8TS3C0DMDaIYIhFCsFSpUpp5jD79KRSA/lBiHRIgARIgAacRoAB0mkVDnM+pU6f0WBTsp/NXRIXYpamXUwCaip+dkwAJkAAJmESAAtAk8FbpFh44vEIOnjN4A/v27Ss4zPmnn37yK4nCKvMIdhwUgMGS43UkQAIkQAJ2JkABaGfrhWHseDsH9v0dO3ZM7r33Xt1niLB0gQIFNJvXWxgYn+PMQ7sXCkC7W5DjJwESIAESCIYABWAw1FxyDfbw4fVqSRUkjEAE2r1QANrdghw/CZAACZBAMAQoAIOhxmscQ8CuN4BjDMCJkAAJkAAJmELArs+/VLf4klVTFozTOrXrDeA0O3A+JEACJEACKUvArs8/CsCUXSeO7c2uN4BjDcKJkQAJkAAJpAgBuz7/KABTZHk4vxO73gDOtwxnSAIkQAIkEEkCdn3+UQBGclW4qG273gAuMhGnSgIkQAIkEAECdn3+UQBGYDG4scmAsoC7dHEjIs6ZBEiABEjAgQQoAB1oVE7JfwIUgP6zYk0SIAESIAHnEKAAdI4tOZMgCFAABgGNl5AACZAACdieAAWg7U3ICYRCgAIwFHq8lgRIgARIwK4EXCcAa9WqJWXLltXXnQVTjh8/LoUKFZIdO3ZoO99++608/vjjcuHCBcmcOXOSTc6ZM0d69uwpFy9e1M8HDx4sS5culZ07dwYzBF4TRgIUgGGEyaZIgARIgARsQ4ACMEBT3bhxQ86fPy/Zs2eXu+66KygB+Oeff0p8fLxky5YtwN7Nqx6qcDZv5Mn3TAFoVctwXCRAAiRAApEkQAEYIt1gPIAhdmnK5VYSgBDhqVKlktSpU4fMggIwZIRsgARIgARIwIYEXCkAS5Ysqab65JNPJE2aNPLSSy/J0KFDVVTgZ8mSJdKsWTOPORHaRci4ffv24k8IGCHfQYMGyW+//SZPPPGEPPLII9q+txAw2sVnqPfee+/J9evX5V//+pf2mTZtWh3Hr7/+Ki+++KKsX79ecufOLe+884688cYbGlrGj6+C9vv27SvLli2TS5cuyQMPPCAjR46UJk2ayO+//y4vv/yybNy4Uf744w8pUqSItt2qVSttFuP78MMPE3Xx888/S8GCBWX//v3y2muvyb///W/JmDGj1K9fX8aNG6ceUpTLly9L165dNeQdHR3tGUPCMDzC5z169JAvvvhCPaM1a9aUCRMmSNGiRbUNI4QOe2EOP/30k6xbt07q1q0rcXFxysMor776qmzdulXH40+hAPSHEuuQAAmQAAk4jYArBeC2bdukU6dOKvx+/PFH6dKli4qtzp07hywA//Of/0i1atVk+PDh0qJFC/nqq6/krbfeEry6ODkBCNHZunVrFUJHjhyR5557zjMmLLp69eqpoJw6daqKwt69e8sPP/yg/fgSgDdv3pQaNWqoGIM4g8CDcIP4bdiwofzyyy/y6aefqqCCSFuxYoX06tVLNm3aJFWqVFHBiHoQzm+//bbeAzly5JBz585J6dKllVvbtm3l6tWr0q9fP/nnn39UqKLgszVr1sgHH3wguXLlUmG8du1a6dixo2cfZtOmTeXw4cMybdo07R9tHD16VMeIuUIAwkaVKlWS0aNHa+g8b968Ur58eRXFffr00b7Q7/3336/CtkOHDn7dq/4KwCvx8SIdO6rIZSEBEiABEiABuxNwpQCEcNm3b5+KPZTXX39dli9froIjVA8gRBw8WqtWrfKsDXjzIASTE4AIJUP0QJShPPvssxrinD9/vhw8eFCKFy+unq2KFSvq5xCJ8JBB0PkSgF9//bUKuAMHDkixYsX8WrONGzfWPseMGaP1kwoBQ8xB8K5evdrT5qlTpyRfvnxy6NAhue+++1SszZs3T55++mmtAzGZJ08eFYYQ3RB+GBPEZvXq1bUOPJJoA17HZ555RgUgBB2SZsqUKePpa9SoUfoZ7IYC7+bzzz8vZ86c8SrU4GHEj1FwA6CvS7GxEh0V5ZVNqpgY/QxCnoUESIAESIAE7E7AlQKwcOHCMmvWLI/tIBwgUK5du6aJHaGEgMuVKyfNmzdXT5dRxo8fr17A5AQgEkvgeTMKPIF79uxRT5oxPgiXhPvesmbNqv34EoAQSpMmTZITJ04kuV6xpw5eswULFqg30BBJmMfChQu9CkCIRHj30qVLl6jdK1euyMqVK1XoIdSLfvPnz++pA8/dY489pgIQwrtly5bK3hC/qJiQI0ReTEyM1jFEO+pAyMMTiHBv1apVBZ5EhJ7hbfRWkIE9ZMiQOz6mALT7P2UcPwmQAAmQQCAEKAD/5zkyBCBCjosXL1YRZxSE/SCg/NkDCMGD0G+gAhDiEPvkjAJRB48XPIP4OzxhtwvALFmyqLD0JQAnTpyonjxvAhACET8QZKVKlVLvGdqEGDbGlJQHEF7FDBkyyLvvvnvHmoP3D949CLmTJ0+ql80o+Bv2+aG/hOI7oQAERwjDgQMHevYAGgI6YWeoA9GHPZYI/4IXwt3eSrAeQIaAA/lnhXVJgARIgASsTsCVAhCeIyNsCAP1799fhQj+hn1qEFXdunVT2xkhytmzZ/slABEChlCBB8woSKZASNhXEog3AWiEgLFfsUKFCtpsICHgDRs2SO3atb2GgJ988knJmTOnx3OGPYMI/+LHGBOSOx588EGBmDTKgAEDVCzv3btXxeLtBXsOEQLG/kIINRQsOHgGsXfPVwj4o48+Us/s7ecoJuwHXBFiRyLK3LlzNVweSPF3D6C2yXcBB4KWdUmABEiABCxMwJUCEEkg2IOGsOL27dv1/5F9i98h1nbt2qUZwhBCSEhAduz06dP9EoBbtmzRvWwIqSKTGPvv4MXylQSSnAcQ6wdJIMjQnTJliiZGINsVfY0YMUITR3wVHFaNJJKxY8dqBjCEEsKpDRo00IQPCDnsN4RXEXUQ+sU1hgBEEgY8kvj7PffcIwg/Y68dPHXw5iERA544CFO0M2PGDA3pgi0ydhGWhciEuAYTJOFg/yIKOBlJIPfee6/uyUQ7CZNAEh6knXCusBGykc+ePasJKrBXIIUCMBBarEsCJEACJOAUAq4UgCVKlFBxh+QEiBQIP2TTQhCdPn1aEw6QlABPFfbvQRQGcgwM9hdC6CCZAZm1EEj+HAPjzQOIxYZjYCCajGNgIPwgiiB6MH5fBeIRXjLsucMePeMYGOzjw2fIyoVQQ0gXYg9hWyRsGGPC0Svt2rVTcYxsX+MYGAg3iK5vvvlGQ9QFChRQUQkRCZ5JHQMDgQiPJOaAYhwDg7HhCBzsD4Sn8fZjYJIKAeN6hNthPxwJg9BzIIUCMBBarEsCJEACJOAUAq4TgE4xnJFtiyNV6tSpY5tpQXxirx48rhC04SjwMsIDCAEZaKEADJQY65MACZAACTiBAAWgTawIzx9eIYckDXgDcSAyMnbhmTMOi7biVPDOZISbK1eurB5FeCyRqIEQr3FYdLDjRns4Guepp57SPZwIkwdaKAADJcb6JEACJEACTiBAAWgTK+KsPez7O3bsmGCfHPYZIiyNkCuSH7yFgfE5zjw0q0AAIuED5wLiuBgksSA8DCEbakFmMg7DxtyN/YSBtkkBGCgx1icBEiABEnACAQpAB1gR++wQAk2qwDsIEciSNAEKQK4MEiABEiABNxKgAHSj1TlnDwG73gA0IQmQAAmQAAmEQsCuz79Ut/hOrlDszmv/R8CuNwANSAIkQAIkQAKhELDr848CMBSr81p6ALkGSIAESIAEXE2AAtDV5ufk7XoD0HIkQAIkQAIkEAoBuz7/6AEMxeq8lh5ArgESIAESIAFXE6AAdLX5OXlmAXMNkAAJkAAJuJEABaAbrc453+kBjI2V6Kio5Ml06UJyJEACJEACJOAIAhSAjjAjJxEsAXoAgyXH60iABEiABOxMgALQztbj2EMmQAEYMkI2QAIkQAIkYEMCFIA2NBqHHD4CFIDhY8mWSIAESIAE7EOAAtA+trLESOfMmSM9e/aUixcvhn08qVKlkiVLlkizZs2Cbrt9+/Y6tqVLl/rVBgWgX5hYiQRIgARIwGEEKAAdZtBIT4cCMNKE2T4JkAAJkAAJRJ4ABWDkGTuqBwpAR5mTkyEBEiABEnApAQpACxq+Vq1aUrp0aUmfPr3MnDlT0qVLJ127dpXBgwcnO9rjx49LoUKFZMeOHVK2bFmti3BolixZ5JtvvhG0++2338rjjz8ua9eulX79+sn+/fu17uzZs+XBBx/Ua3bt2qVh3h9//FEQli1atKhMmzZNKlasKIYAXLBggdaJi4uTRx55RK+/77779PqtW7fKG2+8oeP4+++/tf1x48ZJ+fLlPeM/fPiwdOrUSX744QcpXLiwjB8/XurXr58oBPzLL79I79695euvv5bUqVNrP6hXsGBBbefGjRvSp08fmTVrlqRJk0bbO3v2rFy6dCmsIeAr8fH/HXfHjvqfjBkzWnDVcEgkQAIkQAIk4D8BCkD/WaVYTQg1iCeIn9atW8vmzZsFe9tWr14t9erV8zqOQARglSpV5N1335UcOXKouISY2rRpk7ZdsmRJKVeunAwYMECF1c6dO6VYsWJSpkwZFYBdunSRmjVryogRI1SYPf/881p/7ty5ev369evl9OnTUqFCBf39vffeky+//FIg+u699165efOmtpU9e3YVhliEEJOYs7EH8K+//lLh+Oijj+pnd911lwwbNky2bdsmu3fvVlE8atQoGT58uHzwwQfy8MMPaz8LFy6U2rVrexWA8fHxgh+joO98+fLJpWTOAUwVE5OI+a1bt1JsLbAjEiABEiABEogEAQrASFANsU0IQAiyjRs3elqqXLmyCpuRI0eGRQDCA1inTh1ta+XKldK4cWO5evWqeh2jo6Nl4sSJ0q5duzv6ggDs0KGDHDlyRIoUKaKfT548Wd5++205c+ZMkmPDXOCFnDdvnjRp0kQ9eo0aNRII1rx58+o1X331lTRs2NAjAOHVg8A7cOCAeiFRrl+/LpkzZ1ZxB29hnjx5pEePHurJRPnnn3/UAwrh6S0JBF7UIUOG3DFOCsAQFy0vJwESIAESsBUBCkALmgsCsESJEjJp0iTP6Jo2bSrZsmXTcKe3EogH8Ny5c+r9Q4HnDeHZEydOSP78+TXU/M4776iXr27duvLMM894xB4EYPfu3eXKlSueYcBr17JlS/XsoaDtQYMGqScQIVkIQHj03n//fenWrZuGcfFz7NgxTxsI20LcGR5A9IGwMwRpwoJ2wAWeUdTfsGGDPPbYY54qzZs3F3jovAnAYDyADAFb8CbhkEiABEiABEIiQAEYEr7IXAwBiPBnbGyspwMcjQLBAwHmrZw8eVIKFCgg27dv15Asyvnz5yVnzpx37AG8cOGCtoeCEC/q//zzz579dT/99JOsWLFCVq1apSJr/vz5AnGVVBIIxJYhvNAevHvoF542jOfuu++WatWqaUgZ4VzMa8KECYkEoLEQDQH40ksv6TyMsHLCORvCNRgBeDs7HgMTmTXMVkmABEiABKxNgALQgvYJVgAihJshQ6BDgFwAABmHSURBVAYVbhBhKGvWrNFw6e1JIL4EYEIsrVq1Uo/f8uXL/RKA2OeHsPALL7ygzSBRBJ5F7PeDADRCwBCsCOOiYH9jgwYNPB7AGTNmaGgXXk2EpJMquBbt9e3bVz9GCBgJJfBm8hxACy5sDokESIAESMAyBCgALWOK/x9IsAIQLcDTljZtWpk6dar89ttvmiWLTFt/BWCuXLn0mqefflr30506dUr3AiLEi6QRfzyA8CbCS4cwLxYY2kNGMRI2INgQKi5VqpRmDSNxA3V69eqlCR63J4Hcf//9ur8QewUhGD///HNtD79jPPhBEkjx4sVl7Nix6qlMLgmEHkALLngOiQRIgARIIMUJUACmOHLfHYYiAJE00bFjRz3KBce6IJEiEA8gvGoQfMgIxv49ZOq2aNFCRo8erfvx/BGA2FOITOE9e/ao5w/C77XXXlPxhx8UhJiNY2BwrAtCwgk9gKiDpBJ4AZGkcvnyZYEYROLKmDFj1CsIjx/axRE0yEbGvCF6w30MjMdiXbr4Nh5rkAAJkAAJkIANCFAA2sBIHGLkCHAPYOTYsmUSIAESIAHrEqAAtK5tOLIUIEABmAKQ2QUJkAAJkIDlCFAAWs4k3geEjNiY2w4lNmoj23bfvn02mo01hkoBaA07cBQkQAIkQAIpS4ACMGV5h9Qb9sFhX15SBYkfEIEsgRGgAAyMF2uTAAmQAAk4gwAFoDPsyFkEScCuN0CQ0+VlJEACJEACJKAE7Pr8S3WLL2TlEg4DAbveAGGYOpsgARIgARJwMQG7Pv8oAF28aMM5dbveAOFkwLZIgARIgATcR8Cuzz8KQPet1YjM2K43QERgsFESIAESIAHXELDr848C0DVLNLITtesNEFkqbJ0ESIAESMDpBOz6/KMAdPrKTKH5+Z0FzLeApJBF2A0JkAAJkEBKEKAATAnK7MOyBCgALWsaDowESIAESCCCBCgAIwiXTVufAAWg9W3EEZIACZAACYSfAAVg+JmyRRsRoAC0kbE4VBIgARIggbARoAAMG0o2ZEcCFIB2tBrHTAIkQAIkECoBCsBQCfL6iBMoWLCg9OzZU39QUqVKJUuWLJFmzZqF3DcFYMgI2QAJkAAJkIANCVAA2tBobhsyBaDbLM75kgAJkAAJRJoABWCkCbP9kAlQAIaMkA2QAAmQAAmQQCICFIBcEH4RqFWrlpQuXVrSp08vM2fOlHTp0knXrl1l8ODBPq+/ePGi9O3bV5YtWyaXLl2SBx54QEaOHClNmjTRa7///nt5/fXXZevWrZI9e3Zp3ry5jBgxQjJmzKifJycAr1+/Lr1795bFixfLhQsXJHfu3BITEyP9+/f3OS5U8CcEfCU+XqRjR23PGJNfjbMSCZAACZAACViUAAWgRQ1jtWFBAO7YsUPFVuvWrWXz5s3Svn17Wb16tdSrV8/rcG/evCk1atSQy5cvy7hx46RIkSKyf/9+SZMmjTRs2FD27Nkj1atXl6FDh0rjxo3l/Pnz8vLLL0uZMmVk9uzZPgXgmDFjZMKECTJ37lzJnz+/xMXF6U+rVq2SHFN8fLzgxyi4AfLlyyeXYmMlOioqyWtSxcR4/n7r1i2rmYbjIQESIAESIIGACVAABozMnRdAAN64cUM2btzoAVC5cmWpXbu2evO8la+//lqF3oEDB6RYsWJ3VGvbtq1ERUXJtGnTPJ999913UrNmTbly5Yp6HJPzAL7yyiuyb98+Wbt2rSaH+CrwWA4ZMuSOahSAvsjxcxIgARIgAScRoAB0kjUjOBcIwBIlSsikSZM8vTRt2lSyZcsms2bN8trzqFGj9JoTJ04kWQdtHjlyRNKmTZvIy/bXX3+pp7B48eLJCsDt27erBxLjaNCggYaV69ev73U8wXgAGQKO4MJi0yRAAiRAAqYQoAA0Bbv9OoUALFu2rMTGxnoGj2NYMmfOLHPmzPE6oYkTJwrCtN4EIAQeBBw8ebcXhHSx19BXEggW8apVq9QLuGjRIqlbt6589tlnfkH2Zw+gNsR3AfvFk5VIgARIgATsQYAC0B52Mn2UwQrADRs2aJjYWwi4TZs2cubMGVm3bp3XOfoSgAkvxJ5EeAJ///13yZo1q09uFIA+EbECCZAACZCAAwlQADrQqJGYUrACEGN5/PHH5bfffpOxY8dqBvDBgwd1vx6E2u7du6Vq1arSoUMH6dy5s2bZQiyuWbNG4D1ESU4AIrHkvvvuU+9k6tSpBSHnFStWyC+//KK/+yoUgL4I8XMSIAESIAEnEqAAdKJVIzCnUATgH3/8Ia+99posX75cEzuMY2CQ9YuC418GDBigmcXIskWm8HPPPSdvvPGGTwE4Y8YMmTx5shw+fFgziytVqiSjR4+WcuXK+UWBAtAvTKxEAiRAAiTgMAIUgA4zKKcTGAEKwMB4sTYJkAAJkIAzCFAAOsOOnEWQBCgAgwTHy0iABEiABGxNgALQ1uYzf/A4gBlv3kiqFChQQM/os3KhALSydTg2EiABEiCBSBGgAIwUWZe0izd8nD17NsnZ4mw/iEArFwpAK1uHYyMBEiABEogUAQrASJFlu7YgYNcbwBZwOUgSIAESIAHLErDr8y/VLb6U1bKLyk4Ds+sNYCfGHCsJkAAJkID1CNj1+UcBaL21ZMsR2fUGsCVsDpoESIAESMAyBOz6/KMAtMwSsvdA7HoD2Js6R08CJEACJGA2Abs+/ygAzV45DunfrjeAQ/BzGiRAAiRAAiYRsOvzjwLQpAXjtG6TzALu0sVp0+R8SIAESIAESCARAQpALghXE6AAdLX5OXkSIAEScC0BCkDXmp4TBwEKQK4DEiABEiABNxKgAHSj1TlnDwEKQC4GEiABEiABNxKgAHSj1UOYc8GCBaVnz576E84yePBgWbp0qezcuTPoZo8fPy6FChWSHTt2SNmyZf1qhwLQL0ysRAIkQAIk4DACFIAOM2ikp0MBGGnCbJ8ESIAESIAEIk+AAjDyjB3VAwWgo8zJyZAACZAACbiUAAWgQw1fq1YtKV26tKRPn15mzpwp6dKlk65duwpCrb4K6syaNUvOnj0r2bJlk6efflomTJigl0EAdunSRY4cOSKLFi2SLFmyyJtvvql/M0q/fv1kyZIlcurUKcmdO7e0adNGBg0aJGnTpvXUGTlypIwbN07++usvefbZZyVHjhzy1VdfJQoBz549W0aNGiU///yz9vvKK69It27dPG388MMPEhMTIwcOHJCSJUvKgAEDpEWLFgwB+zIwPycBEiABEnA9AQpAhy4BCEDshevdu7e0bt1aNm/eLO3bt5fVq1dLvXr1vM76s88+k06dOsn8+fOlRIkScubMGdm1a5d07tzZIwAvX74sQ4cOlfr16wvqQ3jt27dPHnroIa0zbNgwqV27tuTJk0f27Nmj12Icffv21c8XLlwoL7zwgkyaNEkeffRR+fjjj1VgFi5c2CMAZ8yYIW+99Za8//77Uq5cOZ0L2hk7dqy0a9dOrly5ovv90M/AgQNVJPbo0UOOHTsWkgC8Eh8v0rGjZMyY0aErg9MiARIgARIggQSnYFy6JNHR0bZBwoOgfZgKAvDGjRuyceNGT83KlSurYIL3zVuBwJo2bZrs3bs3kcfOqA9PnCHa8Ldbt26pl2/IkCHqYUyqjB49WhYsWCA//vijfly9enUpU6aMTJkyxVO9atWqcu3aNY8AzJ8/v7z77rvSqlUrTx0Iy5UrV8r3338v06dPl/79+0tcXJxkyJBB60ydOlVeeumlZAVgfHy84Mco+AaUL18+uRQbK9FRUZIqJkY/wrxYSIAESIAESMCpBOgBdKhlIQDhwYOXzShNmzbVkC7Cu94KBFWNGjVUADVo0EAaNWokTz75pNx11116CQRg9+7dpU+fPp4mIOZatmypYV4UeAVjY2M1TPznn3/KP//8o98uzp07p58jbDx+/Hhp27atp41evXrJN998owLw/PnzkjNnTomKipLUqVN76qCdTJkyaWga9eGZXL9+vedz/I7s3+SygBHehli9vVAAOvRG4LRIgARIgASSJEAB6NCFAQEIMQQhZpRmzZpJ5syZZc6cOcnO+urVq7JmzRpZu3at7vNDqHXDhg3qEUwqCQT9oG2Iqy1btsgjjzyiIuuJJ55QwYZw8nvvvScXL170SwBC4MGr+Mknn0iVKlUSjTVNmjQ6HhxDs3v37oAFoC8PIEPADr0hOC0SIAESIIFEBCgAHbogQhGACZEcOnRI9/Zt27ZNypcv71MAQuhNnjxZjh496mnmxRdfVK+gIQARAoZoRD2jVKtWTSA8jXMA8+bNqwke2N+XVDFCwEg0gacQBaFrhKF5DqBDFzWnRQIkQAIkEDYCFIBhQ2mthoIVgPAOYu8gPG/YW4dwMfYFIjSM8LEvD+CyZcs0axiJHZUqVZIVK1aoNxBtGgIQ+wGRyAEBCG/h3LlzNSM4YRIIMpeR9TtixAhp2LCh7tvDHsILFy5oQglCy/AEIqEFWcg4BBpJIAg7UwBaay1yNCRAAiRAAtYjQAFoPZuEZUTBCkC8jQNJIjhaBaKtVKlSmtVbp04dHZcvAYg6yPaFcIRoa9y4sSDBA+FhQwCizvDhw1X0IfED+wdz5cqlGcoJ3wQyb948QQLJ/v37NSsXY0Hot3nz5joWhJvh8cNYH374YfUWoi0KwLAsITZCAiRAAiTgYAIUgA42LqfmmwBfBeebEWuQAAmQAAk4jwAFoPNsyhkFQIACMABYrEoCJEACJOAYAhSAjjGlfxPBfjskVyRVChQooAc6u6lQALrJ2pwrCZAACZCAQYAC0GVrAW/xwDErSRUc8wIR6KZCAegma3OuJEACJEACFIBcAyQg9n0VDo1HAiRAAiRAAqEQoAcwFHq81vYE7HoD2B48J0ACJEACJGAqAbs+//guYFOXjXM6t+sN4BwLcCYkQAIkQAJmELDr848C0IzV4sA+7XoDONAUnBIJkAAJkEAKErDr848CMAUXiZO7susN4GSbcG4kQAIkQAKRJ2DX5x8FYOTXhit6sOsN4ArjcJIkQAIkQAIRI2DX5x8FYMSWhLsatusN4C4rcbYkQAIkQALhJmDX5x8FYLhXgkvbs+sN4FJzcdokQAIkQAJhImDX5x8FYJgWgNubsesN4Ha7cf4kQAIkQAKhEbDr848CMDS78+r/EbDrDUADkgAJkAAJkEAoBOz6/KMADMXqvNZDwK43AE1IAiRAAiRAAqEQsOvzjwIwFKvzWgpArgESIAESIAFXE6AAdLX5OXm73gC0HAmQAAmQAAmEQsCuzz96AEOxOq+lB5BrgARIgARIwNUEKABdbX5O/tKlS5I5c2aJi4uT6OhoAiEBEiABEiABVxCAAMyXL59cvHhRMmXKZJs50wNoG1NZe6DHjh2TIkWKWHuQHB0JkAAJkAAJRIgAHCB58+aNUOvhb5YCMPxMXdkivvlkyZJFTp48aatvQGYby/jmSM9p4JYgu8CZ4QpyI7fgCAR3lRvW261bt+Ty5cuSJ08eSZ06dXCgTLiKAtAE6E7s0q57IMy2BbkFbwGyC44duZFbcASCu4rrLThuKXEVBWBKUHZBH7zJgzMyuQXHzfBkYb8N9p9y36n/HLnm/GeVsCa5kVtwBKx7FQWgdW1jq5HxH8fgzEVuwXGjACS34AkEdyXvVXILjoB1r6IAtK5tbDWy+Ph4GTFihPTv31/uvvtuW43dzMGSW/D0yS44duRGbsERCO4qrrfguKXEVRSAKUGZfZAACZAACZAACZCAhQhQAFrIGBwKCZAACZAACZAACaQEAQrAlKDMPkiABEiABEiABEjAQgQoAC1kDA6FBEiABEiABEiABFKCAAVgSlBmHyRAAiRAAiRAAiRgIQIUgBYyhtWHMnnyZBk9erT8+uuvUqJECYmNjZVHH33U67AXL14sAwcOlKNHj+pr4t555x1p3ry51acZ9vEFwm3fvn0yaNAg2bZtm5w4cULGjRsnPXv2DPuY7NJgIOxmzJghH330kezdu1enV6FCBRk+fLhUrlzZLtMN2zgD4fb5558rpyNHjsjff/8tRYsWlVdffVVeeOGFsI3HLg0Fwi3hnObPny+tWrWSpk2bytKlS+0y3bCNMxBuc+bMkQ4dOtzR99WrVyV9+vRhGxMb8k2AAtA3I9YQkQULFugDATd6jRo1ZNq0aTJz5kzZv3+/5M+f/w5GmzdvVnE4dOhQFX1LlixRYfPdd99JlSpVXMM0UG5bt26VhQsXqnjp1auX9OvXz7UCMFB2bdq00bVZvXp1fZCMGjVKIG4gqu+//36uOS/36rfffisXLlyQhx56SNKlSydffvmlCsAVK1bIE088QW5euBlg8EUN665w4cKSNWtW1wnAQO9TCMAePXrIoUOHEq2t3Llzu2atWWWiFIBWsYTFxwHRVr58eZkyZYpnpMWLF5dmzZrp+X+3l+eee07fObpq1SrPRw0aNND3BX/66acWn234hhcot4Q9FyxYUMWfWz2AobADxxs3buh6e//996Vt27bhM6rFWwqVG6aHe71x48b6Bc4tJRhuWGM1a9ZUj9bGjRsF70R3mwcwUG4QgPg3DaxYzCVAAWguf1v0fv36dcmQIYMsWrQoUQgX3+J27twpGzZsuGMe8ArCg4UfoyCcibAxvjG7oQTDjQLwvwRCZYc28HL2nDlz6rpt0qSJG5ZcyNzwUvv169fLU089pUKmXr165Obl3ziAeeutt2T37t0a4Wjfvr3rBGAw9ykE4IsvvqheeQjosmXL6heNcuXKuWKtWWmSFIBWsoZFx3L69Gm9WTdt2qThNaNg39CHH354hysfnyOUhBu9devWnvrz5s3Tb8o4Gd4NJRhuFID/JRAqO7TRvXt3Wb16te4JdMveomC54X3KuMdxb6ZJk0a3enTs2NENt2nQ6w3/HiLSgS/B2bNnd6UADGa9bdmyRfeblipVSqNE48ePl5UrV8quXbt0/ylLyhGgAEw51rbtybjJv//+e6lWrZpnHkjq+Pjjj+XgwYN3zA0CEOIQG6ONMnfuXOnUqZNcu3bNtiwCGXgw3CgAEwvAQNZcQnbY/zdy5EjB/rbSpUsHYjZb1w12zd28eVOOHTsmf/75p6xbt049MvAA1qpVy9Y8/B18oNzgXca6glBu2LChduNGD2Cg3JKyB9Yethw89thjMmHCBH9NxnphIEABGAaITm8iGDc/Q8ChhzHdvAcwmDVn3IdjxoyRYcOGydq1a6VixYpOvz0TzS8UbgkbQoguLi5OPahuKIFyg9cPIUt4S40CIYOSOnVqjYrg5AOnl0C5eePRuXNnOXXqVKI9405nZ4X5UQBawQo2GAM2+iIzFd94jfLwww/rsQfekkDwLRmufaPgm3LmzJldlwQSCLeES8HNAhAcAl1zuAbHFEH8QbhUrVrVBndW+IcYDLfbRwFPPY5vggfVLSUQbohiIIyZsLz55pu67xQhzWLFiuk2GDeUQLglxQP7TnFUE0LCs2bNcgMyy8yRAtAyprD2QIxU/6lTp2oYePr06YJz13DERoECBTTLEnuIDDGI0B1c+ggTQyQuW7ZM8A+kW4+B8ZcbvlHjaB2URo0aCY42wc8999wjDzzwgLUXSZhHF+iaQ9gX505irymO5TAK2OHHLSVQbrhn4SmFxwrrD1/acPwQMv7hCXRLCZTb7VzcGAIGg0C5DRkyRL+cYb8f9gAi7IutRNhT6cYzO828vygAzaRvs77h/cNDFgdBlyxZUg8phshDwV4heKyQ+GGUzz77TEUf9hYZB0G3aNHCZrMOfbiBcDt+/LgUKlTojk5x1ISbvDEGgEDYYf0llWGOTM3BgweHbkgbtRAIN9yjeIgjBBcVFaXnASLDHwkObiuBcKMA/H8CgXDDyRA4n/PMmTOSKVMmDaXj/ky4v9xt686s+VIAmkWe/ZIACZAACZAACZCASQQoAE0Cz25JgARIgARIgARIwCwCFIBmkWe/JEACJEACJEACJGASAQpAk8CzWxIgARIgARIgARIwiwAFoFnk2S8JkAAJkAAJkAAJmESAAtAk8OyWBEiABEiABEiABMwiQAFoFnn2SwIkQAIkQAIkQAImEaAANAk8uyUBEiABEiABEiABswhQAJpFnv2SAAmQAAmQAAmQgEkEKABNAs9uSYAESIAESIAESMAsAhSAZpFnvyRAAiRAAiRAAiRgEgEKQJPAs1sSIAESIAESIAESMIsABaBZ5NkvCZAACZAACZAACZhEgALQJPDslgRIgARIgARIgATMIkABaBZ59ksCJEACJEACJEACJhGgADQJPLslARIgARIgARIgAbMIUACaRZ79kgAJkAAJkAAJkIBJBCgATQLPbkmABEiABEiABEjALAIUgGaRZ78kQAIkQAIkQAIkYBIBCkCTwLNbEiABEiABEiABEjCLAAWgWeTZLwmQAAmQAAmQAAmYRIAC0CTw7JYESIAESIAESIAEzCJAAWgWefZLAiRAAiRAAiRAAiYRoAA0CTy7JQESIAESIAESIAGzCFAAmkWe/ZIACZAACZAACZCASQQoAE0Cz25JgARIgARIgARIwCwCFIBmkWe/JEACJEACJEACJGASAQpAk8CzWxIgARIgARIgARIwiwAFoFnk2S8JkAAJkAAJkAAJmESAAtAk8OyWBEiABEiABEiABMwiQAFoFnn2SwIkQAIkQAIkQAImEaAANAk8uyUBEiABEiABEiABswj8H05YHT1RFHtqAAAAAElFTkSuQmCC\" width=\"640\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.figure()\n",
"ax = plt.axes()\n",
"plt.title(\"Feature Importances for Random Forest (%d trees)\\n Validation MSE: %f\" %(n_est, mse(y_val,t_val)))\n",
"plt.barh(range(n_features),importance[ind],\n",
" color=\"r\", xerr=std[ind], alpha=0.4, align=\"center\")\n",
"plt.yticks(range(n_features), feature_names[ind])\n",
"plt.ylim([-1, len(ind)])\n",
"plt.show()\n",
"\n",
"# pos : [left, bottom, width, height]\n",
"ax.set_position( [0.23, 0.11, 0.7, 0.77] )\n",
"plt.savefig('Feature_importances_all_fully.png', dpi=300)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Validation with leaving features out"
]
},
{
"cell_type": "code",
"execution_count": 71,
"metadata": {},
"outputs": [],
"source": [
"shuffle = np.random.permutation(len(learning_table))\n",
"shuffled_table = learning_table.loc[ shuffle , :]"
]
},
{
"cell_type": "code",
"execution_count": 79,
"metadata": {},
"outputs": [],
"source": [
"fixed_features = ['fully_shaded_ratio_2m', 'NEIGUNG', 'perim_ratio', 'AUSRICHTUN']\n",
"maybe_features = ['GAREA', 'SHAPE_Leng','GBAUP', 'GASTW'] # TAKEN OUT FLAECHE (lowest marginal improvement)\n",
"test_features = np.hstack([fixed_features, maybe_features])\n",
"\n",
"T = shuffled_table.loc[ : , label_name ]"
]
},
{
"cell_type": "code",
"execution_count": 80,
"metadata": {
"scrolled": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Leaving out GAREA: 0.026506\n",
"Leaving out SHAPE_Leng: 0.026597\n",
"Leaving out GBAUP: 0.026666\n",
"Leaving out GASTW: 0.026386\n"
]
}
],
"source": [
"MSE_leaveout = np.zeros(len(maybe_features))\n",
"n_est = 500\n",
"tree_depth = 100\n",
"\n",
"for drop_feature in maybe_features:\n",
" # leave one test feature out\n",
" X = shuffled_table.loc[ : , test_features ].drop(drop_feature, axis=1)\n",
" \n",
" RF_test = RandomForestRegressor(n_jobs = -1) # n_estimators = n_est, max_depth = tree_depth, \n",
" Y = cross_val_predict(RF_test, X, T, cv=5, n_jobs=-1)\n",
" \n",
" print(\"Leaving out %s: %f\" %(drop_feature, mse(Y, T)))\n",
" "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Cross-validation and feature selection"
]
},
{
"cell_type": "code",
"execution_count": 94,
"metadata": {},
"outputs": [],
"source": [
"n_crossval = 10\n",
"all_features_sorted = np.asarray(all_features)[ind]\n",
"MSE = np.zeros(n_features)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"RF_test = RandomForestRegressor(n_estimators = n_est, max_depth = tree_depth, n_jobs = -1)\n",
"Y = cross_val_predict(RF_test, X1, T, cv=5, n_jobs=-1)\n",
"print(mse(Y, T))"
]
},
{
"cell_type": "code",
"execution_count": 95,
"metadata": {
"scrolled": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Iteration 1 out of 14\n",
"CPU time: 0.37 seconds\n",
"Wall clock time: 134.33 seconds\n",
"Iteration 2 out of 14\n",
"CPU time: 0.43 seconds\n",
"Wall clock time: 142.81 seconds\n",
"Iteration 3 out of 14\n",
"CPU time: 0.42 seconds\n",
"Wall clock time: 128.43 seconds\n",
"Iteration 4 out of 14\n",
"CPU time: 0.36 seconds\n",
"Wall clock time: 115.09 seconds\n",
"Iteration 5 out of 14\n",
"CPU time: 0.34 seconds\n",
"Wall clock time: 110.06 seconds\n",
"Iteration 6 out of 14\n",
"CPU time: 0.25 seconds\n",
"Wall clock time: 104.81 seconds\n",
"Iteration 7 out of 14\n",
"CPU time: 0.42 seconds\n",
"Wall clock time: 95.86 seconds\n",
"Iteration 8 out of 14\n",
"CPU time: 0.23 seconds\n",
"Wall clock time: 88.49 seconds\n",
"Iteration 9 out of 14\n",
"CPU time: 0.20 seconds\n",
"Wall clock time: 72.49 seconds\n",
"Iteration 10 out of 14\n",
"CPU time: 0.19 seconds\n",
"Wall clock time: 56.79 seconds\n",
"Iteration 11 out of 14\n",
"CPU time: 0.18 seconds\n",
"Wall clock time: 42.77 seconds\n",
"Iteration 12 out of 14\n",
"CPU time: 0.17 seconds\n",
"Wall clock time: 36.34 seconds\n",
"Iteration 13 out of 14\n",
"CPU time: 0.15 seconds\n",
"Wall clock time: 10.90 seconds\n",
"Iteration 14 out of 14\n",
"CPU time: 0.15 seconds\n",
"Wall clock time: 5.84 seconds\n"
]
}
],
"source": [
"shuffle = np.random.permutation(len(learning_table))\n",
"shuffled_table = learning_table.loc[ shuffle , :]\n",
"\n",
"tt = util.Timer()\n",
"for i in range(n_features):\n",
" \n",
" print('Iteration %d out of %d' %(i+1, n_features))\n",
"\n",
" X = shuffled_table.loc[ : , all_features_sorted[ i : ] ]\n",
" t_cv = shuffled_table.loc[ : , label_name ]\n",
"\n",
" RF_CV = RandomForestRegressor(n_estimators = n_est, max_depth = tree_depth, n_jobs = -1)\n",
" y_CV = cross_val_predict(RF_CV, X, t_cv, cv=5, n_jobs=-1)\n",
"\n",
" MSE[i] = mse(y_CV, t_cv)\n",
" \n",
" tt.restart()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Visualisation"
]
},
{
"cell_type": "code",
"execution_count": 96,
"metadata": {
"scrolled": false
},
"outputs": [
{
"data": {
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" return MozWebSocket;\n",
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" if (warnings) {\n",
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" warnings.textContent = (\n",
" \"This browser does not support binary websocket messages. \" +\n",
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" }\n",
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"\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\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\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>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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AAHxAVgGbSFriZehxOcm/ABJiiDhgL5E5hA+iD/EgAB883qu8N+jV4AAGL2mKjUmZiTwlo63QmQtEJgwbJMsECBg4fe8yn/913+ZYTk8QPCgBgjhYY1MEubd4S0UmcP4oam8HmyJ84KCN/qg7fisF97yYT8m4WN1Jh4OmCOCAIKCuUEYykS2L74gGCLbkw4A4qEESEDWslOnTiZ7ggwMHo6Ye5g4nykx8wI7wuqJIQ/MnUQ2JxFu0S6yYfkBYNh2YBMgB/rFD9sGmgHukl0HhiQRKAAkiQXDmuhjAAlKXnXk5VPJ/AOLl5A1xrzIxJLY1/ldT+K5yCJgARSGLhFE4sull15q/DkqAAwWhuR3g2N6Al6sgnshEXiDRSf51RG8zCXLQuK8AIji74F0ADB+WDWwJzELlCoAJtYZZF2RtUTWPyjJwBvPC8wNRVYyvgTZdLy4AZqjujcKegYl66NU/NgWAIOFIXn5Cl6mA9BDxhTPcTxzMLKDqQy4b/FyhL/gWRMlACaOHsBOPDvwkptXwbxX2IiCmIJnDDLhyKLDbjw3g5GH/O4R/haNAgTAaHRUryUxGOBBGaTY44dsEgMBgAoQBXBKVpB9AfhhSAtZDTyYg4nwOD7IeqQDgIBSZESCgje8xL2nAH/IZGDuGTIbGLrDXJJUMoCYo4W5L4nZjEQtALKYcxRMOg7swts0gnuyCe3BvKPg2LB62mYAw7YDu4JFE0uXLs3VxcHE/MTrQAZw2bJlJtuSLAOIIUD0CUpedeTl9OlkADH8GfRffteT2GYmM4BB5g3b2wAukxVk44sWLRoDwPghPRyPewL+ipes+CkZ8XXhfsR96QMAInsEUAoWrwR2Yu4ihqULumdSBcAwGcCo7o3gWvJ6BiXr34IygPF+bAuAwTQNQFuwkCPRJkxPwJxKTFPBfFr8xV8XstF4voUBwLDP0byy5mgXGWTcA4hJyQqmGASLl4LfMRKDlx7Yjow5soV5Xa96oM2yBgiAhaTDkwUDBGm8HQM2cOOhJEJPkLWIHy5KdskYisFbJCbsxgc3ZMvwAEoHAFORFjc+hjkQVJCxSmUOILJpyFRifklQgiEHZIWCDBCyfzgmfo4iVqxhSA4Z0IKCGeoOqydW4mKuS7pzAMO2ky4AYs4dVpEjK4qh7qBgaBJz9PDSgCxhVAAYDPlhPiQ0CUqQkUAmANmVgq4n0acwhwgBJRNzAOEjyO4BQILFFnn5eLI5XcGxyK7D55JlbOPrSwUAMc0A2exgDmJB915eUJ+YAcQ0AGTmsTkxpgagYKI/Ms7IHhd0z6QKgGHmAEZ1byRqlPgMSqZhKn5sC4DQLliZjTmfeRW8xGG+Ml7YgrmbOBbPUoB6/MhL8JzHyx/umfgS9jmaHwBiyBp1Y356/NzpgvwRvwfzRXFfIGvJoq8AAVBf40hayCsYJFaeCIAYIsBbKQIDhk+wYARpegxNYggJWT8AwN69e83DBllFvInhGDxoMSkdQzJRAiAmxqN9rJjEnBFM5Md8EgzjYdEHggvALMimxK8CxpsiYC9++CsICJgsDcjDimLMx8KDEcE2AEBcA7aUwHHBalHMm8FQCq6xoGAGrcPqiWMxNAnbAFSAKTwUAVgAiYJWAafSTjoZQEwQR5YVE+uxSAET8aE/5mlhCCZxFXCy4cK8HDtZ4AtWT2J+KYACYB6sAobfJa4Chh8ny2gmaxNDSvARzCfFCwv8AwBW0Cpg1JXKHEAcjyFnBFS0Ax/CKlpk+QAP+N9grlV+AAjfRfBFph1aYYoAtuTBSwMyYJinipIKAKIezKHEMDsWDmDoO7/Nt8MCIPwDGUn0F/wYfoOpGxjqxm8F3TOpAmCwCjiYhgKYwLMB92wA3VHcG2GeQcl8LRU/tgVAtA+og63wbQAaoArz/jBsiuxesMAIvgTtgl0bANJYOIN5zXjGBxlA9Bn8A/M8sfE5/ARTbbBLQNjnaH4AGOxEgXnOmB8I34HPwA/Ql9ixAs98gCKOgV8heYHnPa4V9uFZnGy1dCSBlJXkUIAAWEgcIl0AxOVhTgYeoph4iyEoZApwE+KhgXk5wV5cCMJ4KCCY4eGCBweycZjUGyUAAi7wdgoAQNDEHnAYysBDH5vyBgUBEdCK7UkwHxHQhCxlsJVGsM8fHsoAKzxckKkAPAAAg4dj/Gfx8IDEcXhQ4UGI7SgAozi2oGAW2BVWT2RKsBUCdAeMIsOJ/Rsx6TnMPoBh20kHAHEtgA7AWLAPIEAEcyPxAhC/l2MUQ8BoD4EAYARQQT9hSgACEaAz2T6AYQEQ/YZ+BSAgOGIoC0NQ8IkA8vC/tquAg/7HSwj8C/cLpjgAAtG3CPjBSuL8ABD1wPdhI3wTWUwEYGSMsUdksL9nKgCIlx6slg1sCrsPYOLUgGQrQTHMDj/GswPBGvcM7tsw90yqAIgtY/BswHMJC8CwuAlboKCt+BXTtvdG2GdQsvAQ1o+jAEC0j/sTz2+8jGO4GnOIMV8Ow/PBtkOYEoRnJV6wgi1u4P/YmSHxWYO6gk8cAqaDZ3vY52h+AAh70Yd4sUa2Ec9WTGcAZAJg8YxHbMEiQvg3FjzB//EswLMfi6lcfDWokGBA5GYSACOXlBVqKpBsArxme6ybClABKkAFqMDxqAAB8Hjs1eP4mgiAx3Hn8tKoABWgAlQgYwoQADMmNRuKQgECYBQqsg4qQAWoABXIdgUIgNnuAbx+KkAFqAAVoAJUIOsUIABmXZfzgqkAFaACVIAKUIFsV4AAmO0ewOunAlSAClABKkAFsk4BAmDWdTkvmApQASpABagAFch2BQiA2e4BvH4qQAWoABWgAlQg6xQgAFp0OT5gjQ1tsdFl/PdULarkqVSAClABKkAFqICyAtj4Ghu541OS+BpUNhYCoEWvY5dzfBuUhQpQASpABagAFSh8CuDTkfgyVjYWAqBFr+/fv998wgoOVKJECYuaeCoVoAJUgApQASqQKQXweU4kcPAt+pIlS2aqWa/aIQBadAccCI4DECQAWgjJU6kAFaACVIAKZFABxm8RAqCFw9GBLMTjqVSAClABKkAFHCnA+E0AtHI9OpCVfDyZClABKkAFqIATBRi/CYBWjkcHspKPJ1MBKkAFqAAVcKIA4zcB0Mrx6EBW8vFkKkAFqAAVoAJOFGD8JgBaOR4dyEo+nkwFqAAVoAJUwIkCjN8EQCvHowNZyceTqQAVoAJUgAo4UYDxmwBo5Xh0ICv5eDIVoAJUgApQAScKMH4TAK0cjw5kJR9PpgJUgApQASrgRAHGbwKglePRgazk48lUgApQASpABZwowPhNALRyPDqQlXw8mQpQASpABaiAEwUYvwmAVo5HB7KSjydTASpABagAFXCiAOM3AdDK8ehAVvLxZCpABagAFaACThRg/CYAWjkeHchKPp5MBagAFaACVMCJAozfBEArx6MDWcnHk6kAFaACVIAKOFGA8ZsAaOV4dCAr+UKdXPXRv4Q6zvag7SOuta2C51MBKkAFqEAhUYDx2yMAHD9+vIwaNUr27NkjderUkTFjxkizZs3ydKWFCxdK//79ZevWrVK9enUZOnSotG3bNnb8wIEDZe7cubJr1y4pWrSoNGjQwBzTqFGj2DFVq1aVHTt25GjjkUcekREjRoRyYTpQKJmsDiIAWsnHk6kAFaACVCCJAozfngDgvHnzpHPnzgIIbNq0qUyaNEmmTp0qmzZtksqVK+fqurVr1xo4HDx4sIG+xYsXy4ABA2TVqlUxwJs9e7aUL19eqlWrJt9//72MHj1a5s+fL59++qmUK1fO1AkA7Natm3Tv3j3Wxumnny74C1PoQGFUsjuGAGinH8+mAlSAClCB3AowfnsCgMjK1a9fXyZMmBDrpVq1akmbNm1k+PDhuXquffv2gs5bvnx57LeWLVtK6dKlZc6cOUl9PejsV199Va644ooYAPbq1Uvwl06hA6WjWmrnEABT04tHUwEqQAWoQMEKMH57AICHDx+WYsWKmexc/BBuz549ZcOGDbJy5cpcPYmsYO/evc1fUJDhw7Bx4pAufkcbY8eOlSFDhpgM4BlnnBEDwEOHDpnfK1WqJDfffLM89NBDZsg4WcGx+AsKHAjn7d+/X0qUKFGwx/GIlBUgAKYsGU+gAlSAClCBAhQgAHoAgLt375YKFSrI6tWrpUmTJrEuGzZsmMyYMUO2bNmSqxsBaNOnT5dOnTrFfsOQb9euXXMA2tKlS6VDhw7y3XffyVlnnSXPP/+8XHzxxTmgEZlHZA7feecd6du3r7Ru3doMPycrmFc4aNCgXD8RAPWeNQRAPW1ZMxWgAlQgWxUgAHoEgGvWrJHGjRvHfBELNmbOnCmbN29OCoCAw44dO8Z+mzVrlpnPd/Dgwdi/ffvtt2ZRyZdffilTpkyR119/Xd5++20zNzBZwcKSm266yRxftmzZXIdkWwbQB/jywYZsfUDyuqkAFaACx6sCBEAPADATQ8CBA5933nly5513mkxfsvL5559LxYoV5a233sqxWjivG+B4dyAf4MsHG47XByCviwpQASqQrQoc7/E7TL8WOXr06NEwB2oeg0Ug2KYFq4CDUrt2bTMcm9cikAMHDsiyZctix7dq1UpKlSqV5yIQHHjuuefKbbfdJhjKTVYwZHz99debeYTJVh8nnnO8O5AP8OWDDZq+z7qpABWgAlQg8woc7/E7jKJeAGCwDczEiRPNMPDkyZPNkO3GjRulSpUq0qVLFzNPMIBBDBc3b97c7OsHSFyyZIn069cvtg0Mhn7x2w033GDm/u3du9fA5XPPPSfr1q0z+wxiKxlk+i6//HIpWbKkvPvuu2ZRScOGDU19Ycrx7kA+wJcPNoTxBR5DBagAFaAChUeB4z1+h+kJLwAQhgLQRo4caebs1a1b1+zbB8hDadGihdmzDws/grJgwQIDfdu2bYttBN2uXTvzM+YBYoEI5vsF8/mw+APHB4tA1q9fL/fee6+ZY4i5fQBNLBh5+OGHzarkMOV4dyAf4MsHG8L4Ao+hAlSAClCBwqPA8R6/w/SENwAYxljfjtF2INfw47p99LcPNvjmd7SHClABKkAF7BTQjt921mXmbAKghc7aDuQafly3TwC0cE6eSgWoABWgAnkqoB2/C4P0BECLXtJ2INcA5rp9AqCFc/JUKkAFqAAVIADm4wMEQIsbhABoIV7cqdtHXJtnRT5AaDRXyVqoABWgAlTAFwW047cv15mfHQRAi17SdiDX8OO6fWYALZyTp1IBKkAFqAAzgMwA6twFBMBodGUGMBodWQsVoAJUgAqEU0A7foezwu1RzABa6K/tQK4zcK7bZwbQwjl5KhWgAlSACjADyAygzl1AAIxGV2YAo9GRtVABKkAFqEA4BbTjdzgr3B7FDKCF/toO5DoD57p9ZgAtnJOnUgEqQAWoADOAzADq3AUEwGh0ZQYwGh1ZCxWgAlSACoRTQDt+h7PC7VHMAFror+1ArjNwrttnBtDCOXkqFaACVIAKMAPIDKDOXUAAjEZXZgCj0ZG1UAEqQAWoQDgFtON3OCvcHsUMoIX+2g7kOgPnun1mAC2ck6dSASpABagAM4DMAOrcBQTAaHRlBjAaHVkLFaACVIAKhFNAO36Hs8LtUcwAWuiv7UCuM3Cu22cG0MI5eSoVoAJUgAowA8gMoM5dQACMRldmAKPRkbVQASpABahAOAW043c4K9wexQyghf7aDuQ6A+e6fWYALZyTp1IBKkAFqAAzgMwA6twFBMBodGUGMBodWQsVoAJUgAqEU0A7foezwu1RzABa6K/tQK4zcK7bZwbQwjl5KhWgAlSACjADyAygzl1AAIxGV2YAo9GRtVABKkAFqEA4BbTjdzgr3B7FDKCF/toO5DoD57p9ZgAtnJOnUgEqQAWoADOAzADq3AUEwGh0ZQYwGh1ZCxWgAlSACoRTQDt+h7PC7VHMAFror+1ArjNwrttnBtDCOXkqFaACVIAKMAPIDKDOXUAAjEZXZgCj0ZG1UAEqQAWoQAR8rPUAACAASURBVDgFtON3OCvcHsUMoIX+2g7kOgPnun1mAC2ck6dSASpABagAM4DMAOrcBQTAaHRlBjAaHVkLFaACVIAKhFNAO36Hs8LtUcwAWuiv7UCuM3Cu22cG0MI5eSoVoAJUgAowA8gMoM5dQACMRldmAKPRkbVQASpABahAOAW043c4K9wexQyghf7aDuQ6A+e6fWYALZyTp1IBKkAFqAAzgMwA6twFBMBodGUGMBodWQsVoAJUgAqEU0A7foezwu1RzABa6K/tQK4zcK7bZwbQwjl5KhWgAlSACjADyAygzl1AAIxGV2YAo9GRtVABKkAFqEA4BbTjdzgr3B7FDKCF/toO5DoD57p9ZgAtnJOnUgEqQAWoADOAzADq3AUEwGh0ZQYwGh1ZCxWgAlSACoRTQDt+h7PC7VHMAFror+1ArjNwrttnBtDCOXkqFaACVIAKMAPIDKDOXUAAjEZXZgCj0ZG1UAEqQAWoQDgFtON3OCvcHsUMoIX+2g7kOgPnun1mAC2ck6dSASpABagAM4DMAOrcBQTAaHRlBjAaHVkLFaACVIAKhFNAO36Hs8LtUcwAWuiv7UCuM3Cu22cG0MI5eSoVoAJUgAowA1gYMoDjx4+XUaNGyZ49e6ROnToyZswYadasWZ6mL1y4UPr37y9bt26V6tWry9ChQ6Vt27ax4wcOHChz586VXbt2SdGiRaVBgwbmmEaNGsWO+eqrr+SBBx6QF154wfzbDTfcIE8++aSUKlUq1G1DAAwlU4EHMQNYoEQ8gApQASpABSJUQDt+R2iqWlVeZADnzZsnnTt3FkBg06ZNZdKkSTJ16lTZtGmTVK5cOdfFr1271sDh4MGDDfQtXrxYBgwYIKtWrYoB3uzZs6V8+fJSrVo1+f7772X06NEyf/58+fTTT6VcuXKmzlatWslnn30mkydPNv//7rvvlqpVq8qLL74YSnBtB3KdgXPdPjOAodyQB1EBKkAFqECKCmjH7xTNcXK4FwCIrFz9+vVlwoQJMRFq1aolbdq0keHDh+cSpn379oLOW758eey3li1bSunSpWXOnDlJhQw6+9VXX5UrrrhCPvroI6ldu7a89dZbMWjEfzdu3Fg2b94sNWvWLLBDtB3INYC5bp8AWKAL8gAqQAWoABVIQwHt+J2GSRk/xTkAHj58WIoVK2ayc/FDuD179pQNGzbIypUrc4mCrGDv3r3NX1CQ4cOw8Y4dO3IdjzbGjh0rQ4YMMRnAM844Q5555hnp06ePfP311zmOx/Av6uratWuBnaHtQK4BzHX7BMACXZAHUAEqQAWoQBoKaMfvNEzK+CnOAXD37t1SoUIFWb16tTRp0iQmwLBhw2TGjBmyZcuWXKJgTt/06dOlU6dOsd8w5AtoO3ToUOzfli5dKh06dJDvvvtOzjrrLHn++efl4osvNr+jftTx8ccf56i/Ro0app6+ffvmahd1x9cPB6pUqZLs379fSpQoEXnnuQYw1+0TACN3KVZIBagAFaACImYUsWTJkmrxuzCI7A0Arlmzxgy/BgULNmbOnGmGYxMLABBw2LFjx9hPs2bNkm7dusnBgwdj//btt9+aRSVffvmlTJkyRV5//XV5++23zdzAvADzvPPOM/U8+uijudrFwpJBgwbl+ncCoJ2rcxGInX48mwpQASpABVJTgAAo4hwAMzEEHLgF4O7OO+802b10hoCZAUztBgt7NAEwrFI8jgpQASpABaJQgADoAQCiI7EIBNu0YBVwULBAo3Xr1nkuAjlw4IAsW7YsdjxW9GL+Xl6LQHDgueeeK7fddpsgkxcsAkFG8JJLLjH14L8vvfRSLgL5P1U5BBzFY4Z1UAEqQAWogG8KEAA9AcBgG5iJEyeaYWBsy4Ih240bN0qVKlWkS5cuZp5gsCIYw8XNmzc3+/oBEpcsWSL9+vWLbQODoV/8hn39MPdv7969Bi6fe+45WbdundlnEAXQiDmI2HYGBdvAoD1uA3PsViUA+vbIoj1UgApQASoQhQIEQE8AEJ0JQBs5cqSZs1e3bl2zEheQh9KiRQuzPx8WbQRlwYIFBvq2bdsW2wi6Xbt25mfMA8QCEWT0MP+vbNmyZvEHjg8WgeC4ffv25doIety4cdwImhnAKJ4vrIMKUAEqQAU8VYAA6BEAeuoj+Zql7UCuM3Cu2/clC1kYfZM2UwEqQAWoQN4KaMfvwqC980UghUGkvGzUdiDXAOa6fQJgYb47aDsVoAJUwF8FtOO3v1f+s2UEQIte0nYg1wDmun0CoIVz8lQqQAWoABXIUwHt+F0YpCcAWvSStgO5BjDX7RMALZyTp1IBKkAFqAABMB8fIABa3CAEQAvx4k7lPoDR6MhaqAAVoAJUIJwC2vE7nBVujyIAWuiv7UCuM3Cu22cG0MI5eSoVoAJUgAowA8gMoM5dQACMRldmAKPRkbVQASpABahAOAW043c4K9wexQyghf7aDuQ6A+e6fWYALZyTp1IBKkAFqAAzgMwA6twFBMBodPU9A+gDCEejNGuhAlSAClABKKAdvwuDyswAWvSStgO5Bg/X7fuSAfRBBws35alUgApQASqQoIB2/C4MghMALXpJ24Fcg4fr9gmAFs7JU6kAFaACVIBDwBwC1rkLCIDR6Moh4GM65qdDNEqzFipABagAFYAC2vG7MKjMDKBFL2k7kOsMnOv2mQG0cE6eSgWoABWgAswAMgOocxcQAKPRlRlAZgCj8STWQgWoABUIp4B2/A5nhdujmAG00F/bgVxn4Fy3zwyghXPyVCpABagAFWAGkBlAnbuAABiNrswAMgMYjSexFipABahAOAW043c4K9wexQyghf7aDuQ6A+e6fWYALZyTp1IBKkAFqAAzgMwA6twFBMBodGUGkBnAaDyJtVABKkAFwimgHb/DWeH2KGYALfTXdiDXGTjX7TMDaOGcPJUKUAEqQAWYAWQGUOcuIABGoyszgMwARuNJrIUKUAEqEE4B7fgdzgq3RzEDaKG/tgO5zsC5bp8ZQAvn5KlUgApQASrADCAzgDp3AQEwGl2ZAWQGMBpPYi1UgApQgXAKaMfvcFa4PYoZQAv9tR3IdQbOdfvMAFo4J0+lAlSAClABZgCZAdS5CwiA0ejKDCAzgNF4EmuhAlSACoRTQDt+h7PC7VHMAFror+1ArjNwrttnBtDCOXkqFaACVIAKMAPIDKDOXUAAjEZXZgCZAYzGk1gLFaACVCCcAtrxO5wVbo9iBtBCf20Hcp2Bc90+M4AWzslTqQAVoAJUgBlAZgB17gICYDS6MgPIDGA0nsRaqAAVoALhFNCO3+GscHsUM4AW+ms7kOsMnOv2mQG0cE6eSgWoABWgAswAMgOocxcQAKPRlRlAZgCj8STWQgWoABUIp4B2/A5nhdujmAG00F/bgVxn4Fy3zwyghXPyVCpABagAFWAGkBlAnbuAABiNrswAMgMYjSexFipABahAOAW043c4K9wexQyghf7aDuQ6A+e6fWYALZyTp1IBKkAFqAAzgMwA6twFBMBodGUGkBnAaDyJtVABKkAFwimgHb/DWeH2KGYALfTXdiDXGTjX7TMDaOGcPJUKUAEqQAWYAWQGUOcuIABGoyszgPlnAH0A8Wh6mrVQASpABfxQQDt++3GV+VvBDKBFL2k7kOvA77p9ZgCPOacP/WBxm/BUKkAFqIB3CmjHb+8uOIlBBECLXtJ2INeB33X7vsCPax1ct29xi/BUKkAFqICXCmjHby8vOsEoAqBFL2k7kOvA77p9AiAzgBa3J0+lAlSACuSpgHb8LgzSpwyAP/zwg9SsWVOWLl0qtWvXLgzXqGajtgO5BjDX7RMACYBqNy8rpgJUIKsV0I7fhUHclAEQF1WhQgV59dVXpVatWpFd4/jx42XUqFGyZ88eqVOnjowZM0aaNWuWZ/0LFy6U/v37y9atW6V69eoydOhQadu2rTkekNqvXz9ZtmyZbNu2TUqWLClXXnmljBgxQs4+++xYnVWrVpUdO3bkaOORRx4xx4Up2g7kGsBct08AJACGuQ95DBWgAlQgVQW043eq9rg4Pi0ABCBt3rxZpk6dKieddJK13fPmzZPOnTsLILBp06YyadIkU/emTZukcuXKuepfu3atgcPBgwcb6Fu8eLEMGDBAVq1aJY0aNZL9+/fLTTfdJN27d5d69erJV199Jb169ZIff/xR3nvvvRwA2K1bN3NcUE4//XTBX5ii7UCuAcx1+wRAAmCY+5DHUAEqQAVSVUA7fqdqj4vj0wJAQNdrr71mQOmCCy6Q0047LYftixYtSulaAG3169eXCRMmxM5DdrFNmzYyfPjwXHW1b99e0HnLly+P/dayZUspXbq0zJkzJ2nb7777rlxyySUm4xdAJTKAAEP8pVO0Hcg1gLlunwBIAEznvuQ5VIAKUIGCFNCO3wW178PvaQFg165d87V92rRpoa/t8OHDUqxYMZk/f35sCBcn9+zZUzZs2CArV67MVRcArnfv3uYvKKNHjzbDxolDusHvGLK++uqr5euvv5YSJUqYfwYAHjp0SGBDpUqV5Oabb5aHHnpIihYtmtR+HIu/oMCBcB4yjkGdoS88xIGuAcx1+wRAfwCQvhDihuUhVIAKFBoFCIAiaQFglD28e/duM6dw9erV0qRJk1jVw4YNkxkzZsiWLVtyNQdAmz59unTq1Cn22+zZswVgGg9owY8HDx6Uyy67TM4//3x57rnnckAjMo/IHL7zzjvSt29fad26tRl+TlYGDhwogwYNyvUTAdDOI7gR9DH98tKB8OUPCNt5Os+mAlTAFwUIgJYA+MUXXxhAK1KkiNSoUUPKlSuXct8GALhmzRpp3Lhx7Hws6pg5c6aZa5hYAICAw44dO8Z+mjVrlmA+H2AvvmBBCDJ7O3fulBUrVuSbqcPCEswd/PLLL6Vs2bK52mUGMOXuDXUCAZAAGDiK774QyqF5EBWgAt4rQABMEwC//fZb+e1vfyvPPvusHDlyxHT0iSeeKF26dJEnn3zSDOmGLZpDwIC/W265xawEfv3115NCXbydn3/+uVSsWFHeeusts5ikoKLtQK4zP67bh/60gRoE96EPvlDQM4G/UwEqUDgU0I7fhUGFtIaAe/ToYbaBGTdunFm1i4IVuA888IBcddVVORZzhBEBsNWgQQOzCjgo2GMQw7F5LQI5cOCA2eYlKK1atZJSpUrFFoEE8PfJJ5/IG2+8ESo7ib0Nr7/++hwLRfKzX9uBXAc81+0TAI95H/vBHx3CPM94DBWgAv4roB2//VcgzQzgGWecIQsWLJAWLVrkuEaAFjJuGBpOpQTbwEycONEMA0+ePFmmTJkiGzdulCpVqpjMIuYJBjCI4eLmzZubvf8AiUuWLDH7/gXbwGC7lxtvvFHWr19vNqw+88wzY+aUKVPGLPLAVjLI9F1++eVmn0CsEsaikoYNG5r6whRtB3Id+F23T/jxB3zoC2GeCDyGClCBwqKAdvwuDDqklQHEEO+6detybQQNYMNWKxgiTrUg+zdy5EizEXTdunUFq3oBeSgATazYxcKPoABAAX0Y3g02gm7Xrp35efv27XLOOeckNQGQivoAh/fee6+ZY4i5fQDNDh06yMMPPxx6CFvbgVwHXdftEwAJgPE3sQ/+mOpzjcdTASrgpwLa8dvPq85pVVoAeMUVV5j5dJgDeMopp5gav//+e7n99ttl3759Zng4G4q2A7kOeK7bJwASAAmA2fAk5TVSgcwroB2/M39FqbeYFgB++OGHgjl3WHGLL21gFTD27AMMvvzyy+ZTbtlQtB3INYC5bp8ASAD0CQB9uB+y4bnKa6QCmVBAO35n4hps20gLAIOMH/bUwxDq0aNHBYs2br31Vjn11FNtbSo052s7kOuA47p9AiABkABYaB6HNJQKFCoFtON3YRAjZQDE6tq7775b+vfvL9WqVSsM16hmo7YDuQYw1+0TAAmABEC1xxcrpgJZrYB2/C4M4qYMgLgobLeCRRQEwP81K4j5JRA7V/d981/XIOy6fYK4PyBud6fxbCpABQIFCIBpbgODT65dcMEF0qdPn6z2Jm0Hch34XbdP8PAHPOgLfuzHmNUPXF48FYhQAe34HaGpalWllQHE/nt//OMfBauBsYHzaaedlsNAbAidDUXbgVwHXdftEwAJgBwCzoYnKa+RCmReAe34nfkrSr3FtAAwrz320DxWBGNvvmwo2g7kGsBct08AJAASAHM+SX24J7Ph2c5rPP4V0I7fhUHBtACwMFxYJmzUdiDXD3vX7RMACYAEQP8A0PVzwXX7mYgtbENfAe34rX8F9i2kDIBYBVyzZk3ziTVs/ZLNRduBXD/oXLdPACQAEgAJgIkxhs8lP54LPvSDDX9ox28b2zJ1bsoACMPwXV587aNWrVqZstPLdrQdyPUN5rp9AqAfD3r2A/uBIE4Q9xHEbcBAO37b2Japc9MCwBEjRpgNoKdOnSonnXRSpmz1rh1tB3INYK7bJ3gQPAgeBA8fwYPPxsK/Kl47fnsHLEkMSgsA27ZtK6+99pqcfvrpZjuYxFXAixYtKgzXbm2jtgO5fsi4bp8ASAAkABIACYDJQ5Xr57Pr9m0DuHb8trUvE+enBYDYBzC/Mm3atEzY7rwNbQdyfYO5bp8ASAAkABIACYAEQI1grx2/NWyOus60ADBqIwprfdoO5BrAXLdPACQAEgAJgARAAqAGI2jHbw2bo64zbQD88ccfZcWKFbJ161bp1KmTFC9eXHbv3i0lSpQwQ8PZULQdyDWAuW6fAEgAJAASAAmABEANntCO3xo2R11nWgC4Y8cOadmypezcuVMOHTokH3/8sfkucK9eveTgwYMyceLEqO30sj5tB3INYK7bJwASAAmABEACIAFQAwC047eGzVHXmRYAtmnTxmT8nn76aSlbtqx88MEHBgBXrlwpd911l3zyySdR2+llfdoO5BrAXLdPACQAEgAJgARAAqAGAGjHbw2bo64zLQA844wzZPXq1WZDaIBgAIDbt283m0N/9913UdvpZX3aDuQawFy3TwAkABIACYAEQAKgBgBox28Nm6OuMy0ALFOmjKxatcrAXjwA4t9uvPFG+fe//x21nV7Wp+1ArgHMdfsEQAIgAZAASAAkAGoAgHb81rA56jrTAsD27dtLyZIlZfLkyQYA//73v0u5cuWkdevWUrlyZeE2MNF0k2sAc90+AZAASAAkABIACYDRRNSctRAARdICQKz2vfzyy+XEE0808/0aNmxo/hdDw2+++aaUL19eo7+8q1PbgVwDmOv2CYAEQAIgAZAASADUCP7a8VvD5qjrTAsAYcT3338vc+fOlXXr1smRI0ekfv36cuutt8qpp54atY3e1qftQK4BzHX7BEACIAGQAEgAJABqQIB2/NawOeo60wbAqA0pjPVpO5BrAHPdPgGQAEgAJAASAAmAGnygHb81bI66TgKghaLaDuQawFy3TwAkABIACYAEQAKgRZjO81Tt+K1hc9R1EgAtFNV2INcA5rp9AiABkABIACQAEgAtwjQBMB/xCIAWnkUAtBAv7tTtI67NsyJCqAg18AOE2Q/sh+BBRV/w47lkE4G047eNbZk6lwBoobS2A7l+yLhunxlAPwIu+4H9wEwsM7E+ZmItwrdox28b2zJ1LgHQQmltB3INYK7bJ3gQPAgeBA8fwYPPRmYALdDBm1NDA2Dp0qWlSJEioQzft29fqOMK+0EEwGh6kEPAx3TMSwcGGz9AmP3AfuAQ8M/PfB/uB5sIpB2/bWzL1LmhAXDGjBkxm/bu3StDhgyRa665Rho3bmz+fe3atfLyyy9L//79pXfv3pmy32k72g7k+gZz3T4zgH4EXPYD+4GZWGZifczE2gCAdvy2sS1T54YGwHiD8L1ffAnk/vvvz2HnuHHj5NVXX5Xnn38+U/Y7bUfbgVwDmOv2CR4ED4IHwcNH8OCzkUPATuEjosbTAsDTTz9dNmzYIOeee24OM/A5uIsuuki++eabiMzzuxoCYDT9wyHgYzpyCDhvDXx4GWDQ9+OFhP3Afogi8mjH7yhs1K4jLQCsUqWKyf499NBDOewbNWqUIAu4Y8cObbu9qF/bgVw/6Fy370PQ98EG9gMDXvDAoy/4kXliP/jRDzYgoB2/bWzL1LlpAeD06dOlW7du0rJly9gcwLfeekteeuklmTp1qtxxxx2Zst9pO9oO5Poh47p9H+DLBxvYDwRAAuDPj3reD7wfogj82vE7Chu160gLAGHU22+/LWPHjpWPPvpIjh49KrVr15YHHnhAGjVqpG2zN/VrO5DrB53r9n2ALx9sYD8w4BEACYCJgc/1c8F1+7YgoB2/be3LxPlpA2AmjPO9DW0Hcn2DuW7fB/jywQb2AwGQAEgAJABGSwTa8Ttaa3VqSxsAt27dKtOmTZNt27bJmDFjpHz58mYIuFKlSlKnTh0daz2rVduBXAd+1+37AF8+2MB+IAASAAmABMBoAUA7fkdrrU5taQHgypUrpVWrVtK0aVN58803zTBwtWrVZOTIkfLOO+/IggULdKz1rFZtB3Id+F237wN8+WAD+4EASAAkABIAowUA7fgdrbU6taUFgNj8+eabb5Y+ffpI8eLF5YMPPjAA+O6770qbNm3k888/T9na8ePHC1YR79mzx2QQkVVs1qxZnvUsXLjQbDqNTGT16tVl6NCh0rZtW3P8Dz/8IP369ZNly5aZDGXJkiXlyiuvlBEjRsjZZ58dq/Orr74y8xZfeOEF82833HCDPPnkk1KqVKlQ9ms7kOvA77p9H+DLBxvYDwRAAiABkAAYKiyHPkg7foc2xOGBaQEg9gH88MMP5ZxzzskBgNu3b5fzzz9fDh48mNIlzZs3Tzp37iyAQGQVJ02aZFYTb9q0SSpXrpyrLnx1BHA4ePBgA32LFy+WAQMGyKpVq8wilP3798tNN90k3bt3l3r16glAr1evXvLjjz/Ke++9F6sPWczPPvtMJk+ebP7t7rvvlqpVq8qLL74Yyn5tB3Id+F237wN8+WAD+4EASAAkABIAQ4Xl0Adpx+/Qhjg8MC0ArFixovz5z3+WJk2a5ABAgNiDDz5osnKpFEBb/fr1ZcKECbHTatWqZbKJw4cPz1VV+/btBZ23fPny2G/YkgbfK54zZ07SppGdvOSSS8wehYBKDFtj5TK2rwlWLuO/kd3cvHmz1KxZs8BL0HYg14Hfdfs+wJcPNrAfCIAEQAIgAbDAkJzSAdrxOyVjHB2cFgA+/PDD5tu/8+fPlxo1asj69evl3//+t3Tp0sX8Pf7446Ev5/Dhw1KsWDFTVzCEi5N79uxpvjaC+YaJBQCH7w3Hf3N49OjRZtg4r02o8Ym6q6++Wr7++mspUaKEPPPMM2YIG/8/vmD4F3V17dq1wGvQdiDXgd91+z7Alw82sB8IgARAAiABsMCQnNIB2vE7JWMcHZwWAGKOHTZ7njt3rtkD8KSTTpKffvpJOnXqJNgk+sQTTwx9Obt375YKFSrI6tWrTUYxKMOGDZMZM2bIli1bctVVtGhR0w7aC8rs2bMNtB06dCjX8RiSvuyyy8zw9HPPPWd+R/2o4+OPP85xPIAW9fTt2zdXPag7vn44EFY9Y8gZUBl1cR34XbfvA3z5YAP7gQBIACQAEgCjjbAEQJG0ADDoBiywQPbvyJEj5hvA5513Xso9FADgmjVrYl8VQSVY1DFz5kwzHJtYAICAw44dO8Z+mjVrlvk6SeL8Q8AqFqzs3LlTVqxYEQO1vAAT14B6Hn300VztDhw4UAYNGpTr3wmAKXd7jhP4LeBjcvBbwPwWcH5+4MPLiA828IWIL0R2EefY2QTANAAQQIX5cUuXLjVz6GyL5hAwbL3lllvMSuDXX39dypYtGzM3nSFgZgBtezv5+QRAAmDgGT77AsGD4BH4KX2B3wLWiYaZrTWtDCCGbDGnDgs1oihYhNGgQQOzCjgogMvWrVvnuQjkwIEDZpuXoGBFL+bvBYtAAvj75JNP5I033pBy5crlMDVYBIJP2mFxCAr++9JLL+UikP9Tig85BjwGvJ8fG7wfeD/wfvDrfrDhD2YA08gAQnDsp4ehWWzVgvl/tiXYBmbixIlmGBjbskyZMkU2btwoVapUMQtLAJ3BimAMFzdv3twMEwMSlyxZYvb9C7aBwXYvN954oxmeRqbyzDPPjJlYpkwZwRAyCqARQ9DYdgYF28CgPW4D48eDHlYw6FIDX4IufdGP5wL7gf1gyxw4nwCYJgBite5rr70m2A/wggsukNNOOy1HfyxatCjl/kH2D18SwUbQdevWNStxAXkoLVq0MPvzYdFGUPC1EUAfhneDjaDbtWtnfsZ+hNijMFlBNhD1oezbty/XRtDjxo3jRtD/JxwftHzQ+gJfPrwM8H7g/cD74eeo6sP9kDJoxJ1AAEwTAAvaIgXfCM6Gou1Arm8w1+37EPR9sIH9QPAgePgFHrwn/RiZsOEM7fhtY1umzk1rDmCmjPO9HW0Hcv2Qcd2+D/Dlgw3sBwIgAZAAmBgPXT8XXLdvywfa8dvWvkycTwC0UFnbgVzfYK7b9wG+fLCB/UAAJAASAAmAFsE6yana8Ttaa3VqSxsAMQcPn4PD/nrYyiW+YPFFNhRtB3Id+F237wN8+WAD+4EASAAkABIAo6UK7fgdrbU6taUFgGPHjpXHHntMbr/9drNaF3MC8f1ffG/3vvvuM6tzs6FoO5DrwO+6fR/gywcb2A8EQAIgAZAAGC1VaMfvaK3VqS0tAMQn1fC9X3yJo3jx4vLBBx9ItWrVZMCAAWZlLVbSZkPRdiDXgd91+z7Alw82sB8IgARAAiABMFqq0I7f0VqrU1taAFisWDHBRsrYM698+fLy17/+VerVqyfYdBkbKe/du1fHWs9q1XYg14Hfdfs+wJcPNrAfCIAEQAIgATBaANCO39Faq1NbWgCIbB/mANavU7B5uwAAIABJREFUX18uvvhiueuuu6RHjx7yyiuvSIcOHUwWMBuKtgO5Dvyu2/cBvnywgf1AACQAEgAJgNFShXb8jtZandrSAkAAX6VKlcwwML7e0adPH2natKm89957gs2Yn376aR1rPatV24FcB37X7fsAXz7YwH4gABIACYAEwGgBQDt+R2utTm1pAeCRI0cEf8Fn4LAaGJ9hO/fcc+U3v/lN7FNrOib7U6u2A7kO/K7b9wG+fLCB/UAAJAASAAmA0cZ+7fgdrbU6taUFgDqmFL5atR3IdeB33b4P8OWDDewHAiABkABIAIyWEbTjd7TW6tSWFgC++eab+VoTfMNXx2R/atV2INeB33X7PsCXDzawHwiABEACIAEw2tivHb+jtVantrQA8IQTTshlTZEiRWL/9tNPP+lY61mt2g7kOvC7bt8H+PLBBvYDAZAASAAkAEYLANrxO1prdWpLCwD379+fw5offvhB3n//fenfv7/ZBPqKK67QsdazWrUdyHXgd92+D/Dlgw3sBwIgAZAASACMFgC043e01urUlhYA5mUKhoZ79+4t69at07HWs1q1Hch14Hfdvg/w5YMN7AcCIAGQAEgAjBYAtON3tNbq1BYpAGJzaOwL+M033+hY61mt2g7kOvC7bt8H+PLBBvYDAZAASAAkAEYLANrxO1prdWpLCwD//ve/57Dm6NGjsmfPHhkxYoRgOHj16tU61npWq7YDuQ78rtv3Ab58sIH9QAAkABIACYDRAoB2/I7WWp3a0gJALALBog+AX3zBZ+CeeeYZwbeCs6FoO5DrwO+6fR/gywcb2A8EQAIgAZAAGC1VaMfvaK3VqS0tANyxY0cOawCE5cqVk1NOOUXHSk9r1XYg14Hfdfs+wJcPNrAfCIAEQAIgATBaENCO39Faq1NbWgCoY0rhq1XbgVwHftft+wBfPtjAfiAAEgAJgATAaBlBO35Ha61ObWkB4NixY0Nb88ADD4Q+trAdqO1ArgO/6/Z9gC8fbGA/EAAJgARAAmC0hKAdv6O1Vqe2tADwnHPOkS+++EK+++47KVWqlLHs66+/lmLFipmh4KBgnuC2bdt0LPegVm0Hch34XbfvA3z5YAP7gQBIACQAEgCjDfra8Ttaa3VqSwsAZ8+eLePHj5enn35aatasaSzbsmWLdO/eXXr06CG33nqrjrWe1artQK4Dv+v2fYAvH2xgPxAACYAEQAJgtACgHb+jtVantrQAsHr16rJgwQK56KKLcliFDaBvuukm+ec//6ljrWe1ajuQ68Dvun0f4MsHG9gPBEACIAGQABgtAGjH72it1aktLQDEUO+KFSvkkksuyWHVO++8Iy1atDBDw9lQtB3IdeB33b4P8OWDDewHAiABkABIAIyWKrTjd7TW6tSWFgBef/31snPnTjME3KBBA7Mn4HvvvWeGgCtVqiQvvPCCjrWe1artQK4Dv+v2fYAvH2xgPxAACYAEQAJgtACgHb+jtVantrQAEAtAbr/9dnnppZfkF7/4hbHsxx9/lGuuuUamT58u5cuX17HWs1q1Hch14Hfdvg/w5YMN7AcCIAGQAEgAjBYAtON3tNbq1JYWAAamfPLJJ4Lv/+KLILVq1ZIaNWroWOlprdoO5Drwu27fB/jywQb2AwGQAEgAJABGCwLa8Ttaa3VqswLAwKSffvpJPvzwQ6lSpYqULl1ax1IPa9V2INeB33X7PsCXDzawHwiABEACIAEwWgjQjt/RWqtTW1oA2KtXL7ngggukW7duAvj71a9+JWvWrDH7AC5dutQsBMmGou1ArgO/6/Z9gC8fbGA/EAAJgARAAmC0VKEdv6O1Vqe2tACwYsWK8vzzz0vDhg3N/957771mVfCzzz4rb7zxhqxevVrHWs9q1XYg14Hfdfs+wJcPNrAfCIAEQAIgATBaANCO39Faq1NbWgB4yimnyKeffioAwbvvvttk/saMGWP2/6tXr55A2Gwo2g7kOvC7bt8H+PLBBvYDAZAASAAkAEZLFdrxO1prdWpLCwAx12/KlClyxRVXCD4Lh6+CXHfddbJx40a57LLL5KuvvtKx1rNatR3IdeB33b4P8OWDDewHAiABkABIAIwWALTjd7TW6tSWFgAOHDjQZPzOOusss+nzxx9/LCeffLI888wzBgzXrl2rY61ntWo7kOvA77p9H+DLBxvYDwRAAiABkAAYLQBox+9ordWpLS0AhCn4FNyuXbvk5ptvNkPBKDNmzJBSpUpJ69atdaz1rFZtB3Id+F237wN8+WAD+4EASAAkABIAowUA7fgdrbU6taUNgIE5n332mZx99tlywgkn6Fjoca3aDuQ68Ltu3wf48sEG9gMBkABIACQARgsD2vE7Wmt1arMGwBIlSsiGDRukWrVqOhZ6XKu2A7kO/K7b9wG+fLCB/UAAJAASAAmA0cKAdvyO1lqd2qwBsHjx4vLBBx8QAEuUiLyHXAd+1+37AF8+2MB+IAASAAmABMBoQywBUIQAaOFT2g7kOvC7bt8H+PLBBvYDAZAASAAkAFoE6ySnasfvaK3Vqc0aAIcPHy733HOPWfyRbUXbgVwHftft+wBfPtjAfiAAEgAJgATAaAlDO35Ha61ObdYAGJVZ2Etw1KhRsmfPHqlTp47ZZqZZs2Z5Vr9w4ULp37+/bN26VapXry5Dhw6Vtm3bxo5ftGiRTJo0SdatWyd79+6V999/Xy688MIc9eGTdStXrszxb+3bt5e5c+eGuixtB3Id+F237wN8+WAD+4EASAAkABIAQ4Xl0Adpx+/Qhjg8MC0AxPd/p0+fLq+99pr85z//kSNHjuS4hNdffz2lS5o3b5507tzZbCjdtGlTA25Tp06VTZs2SeXKlXPVhX0GAYeDBw820Ld48WIZMGCArFq1Sho1amSOnzlzpvkyCVYod+/ePU8ArFGjhvzhD3+ItXHqqadKyZIlQ9mv7UCuA7/r9n2ALx9sYD8QAAmABEACYKiwHPog7fgd2hCHB6YFgPfff78BwGuvvdZsBl2kSJEclzB69OiULgnQVr9+fZkwYULsvFq1akmbNm0EQ8yJBVk6dN7y5ctjP7Vs2VJKly4tc+bMyXH49u3bzddK8soAIiuIbGM6RduBXAd+1+37AF8+2MB+IAASAAmABMB0onTe52jH72it1aktLQA844wz5Nlnn5Vf//rX1lYdPnzYfEt4/vz5OYZwe/bsabaXSRyiRYPICvbu3dv8BQXQCZDbsWNHSgCIz9cdPXpUzjzzTGnVqpU8/vjjgpXNycqhQ4cEf0GBA1WqVEn2798v2A4n6uI68Ltu3wf48sEG9gMBkABIACQARhthCYBprgLGsOqKFSsEw6e2Zffu3VKhQgVZvXq1NGnSJFbdsGHDzJdFtmzZkquJokWLmgxkp06dYr/Nnj1bunbtmgPQ8GN+GUB8tg7ZwV/+8pfyj3/8Q/r27Svnnnuu/PWvf016WfgE3qBBg3L9RgC084LtI67NswLCjwg1IAASAAmABEC7OJN4NgEwTQD805/+JNu2bZNx48blGv5NtYsCAFyzZo00btw4djoWdWAe3+bNm5MCIOCwY8eOsd9mzZol3bp1k4MHD+Y4Pj8ATKwYC0YaNmxoFo5gSDqxMAOYau+GO54AeEynvHQgABIACYAEQAJguHgS9igCYJoAiIUXb7zxhpQpU8as2P3FL36RQ3OswA1bXA4BJ9qIoeCTTz7ZgCfmGRZUtB3IdeB33T70pw3UwBf4oS8SxH3xRR+ejT7cDwXF6Px+147fNrZl6ty05gBiqDW/Mm3atJTsxyKQBg0amFXAQaldu7a0bt06z0UgBw4ckGXLlsWOx/w97EWYyiKQRCMxDHzBBReYeYfNmzcv8Bq0Hcj1Dea6fR8ecj7YwH4geBA8mAFkBrDAkJzSAdrxOyVjHB2cFgBGbWuwDczEiRPNMPDkyZMF8/OwQKNKlSrSpUsXM08wWBGM4WIAGoaJAYlLliyRfv365dgGZt++fbJz507BEDNWK2Nvv5o1a5r5fvjD/oEYNsZCFixqwZYzv/vd7wTbwLz77rty4oknFniZ2g7kOvC7bt8H+PLBBvYDAZAASAAkABYYklM6QDt+p2SMo4O9AEBcO7J/I0eONBtB161bV7CqN8jCYcPmqlWrmoUfQVmwYIGBPsxFDDaCbteuXex3HJssU4lVvljMsWvXLrntttvM4o9vvvnGrOYFKOJ3DG2HKdoO5Drwu27fB/jywQb2AwGQAEgAJACGicrhj9GO3+EtcXdk2gAIAPvzn/9ssmyYxxdf1q9f7+6KMtiytgO5Dvyu2/cBvnywgf1AACQAEgAJgNEGd+34Ha21OrWlBYBjx46Vxx57TG6//XYzVItMG4ZUMXR63333maHZbCjaDuQ68Ltu3wf48sEG9gMBkABIACQARksV2vE7Wmt1aksLAM8//3wzVIptWLBp8gcffCDVqlUzn2PD3DtsD5MNRduBXAd+1+37AF8+2MB+IAASAAmABMBoqUI7fkdrrU5taQEgvtzx0UcfmQUa5cuXNxsn16tXTz755BO59NJLZe/evTrWelartgO5Dvyu2/cBvnywgf1AACQAEgAJgNECgHb8jtZandrSAkBk+zAHEJslX3zxxXLXXXdJjx495JVXXpEOHTqYLGA2FG0Hch34XbfvA3z5YAP7gQBIACQAEgCjpQrt+B2ttTq1pQWAAD6smsUwMLZu6dOnjzRt2lTee+89wUrcp59+Wsdaz2rVdiDXgd91+z7Alw82sB8IgARAAiABMFoA0I7f0VqrU1taAHjkyBHB30knnWSswmrgVatWme/o/uY3vxF8qzcbirYDuQ78rtv3Ab58sIH9QAAkABIACYDRUoV2/I7WWp3a0gJAHVMKX63aDuQ68Ltu3wf48sEG9gMBkABIACQARssI2vE7Wmt1aksbAP/2t7/JpEmTzPYvmA+IL3XgG7rnnHOOXHbZZTrWelartgO5Dvyu2/cBvnywgf1AACQAEgAJgNECgHb8jtZandrSAsCFCxdK586d5dZbbzXQh8+oYWEIvuaxdOnSHN/o1THbj1q1Hch14Hfdvg/w5YMN7AcCIAGQAEgAjDbua8fvaK3VqS0tALzoooukd+/e5hu98fsAbtiwQVq2bCn/+te/dKz1rFZtB3Id+F237wN8+WAD+4EASAAkABIAowUA7fgdrbU6taUFgNgHEFk/fJ83HgDxXd7atWvLwYMHdaz1rFZtB3Id+F237wN8+WAD+4EASAAkABIAowUA7fgdrbU6taUFgNWrVzfz/6688socAPjss8/KiBEjDBxmQ9F2INeB33X7PsCXDzawHwiABEACIAEwWqrQjt/RWqtTW1oAOHLkSJkxY4Y888wzctVVV5k5fzt27DDDwvgc3P33369jrWe1ajuQ68Dvun0f4MsHG9gPBEACIAGQABgtAGjH72it1aktLQCEKY899piMHj06Ntx78skny4MPPiiDBw/WsdTDWrUdyHXgd92+D/Dlgw3sBwIgAZAASACMFgK043e01urUljYAwpzvvvvODPdiU2jM/Tv99NN1rPS0Vm0Hch34XbfvA3z5YAP7gQBIACQAEgCjBQHt+B2ttTq1WQGgjkmFp1ZtB3Id+F237wN8+WAD+4EASAAkABIAo2UD7fgdrbU6taUEgHfeeWcoKzA3MBuKtgO5Dvyu2/cBvnywgf1AACQAEgAJgNFShXb8jtZandpSAsATTjhBqlSpItgH8OjRo3latHjxYh1rPatV24FcB37X7fsAXz7YwH4gABIACYAEwGgBQDt+R2utTm0pAeC9994rc+fOlcqVKwuygbfddpuUKVNGx7JCUKu2A7kO/K7b9wG+fLCB/UAAJAASAAmA0UKBdvyO1lqd2lICQJhw6NAhWbRokdkCZs2aNXLttddKt27d5Oqrr5YiRYroWOlprdoO5Drwu27fB/jywQb2AwGQAEgAJABGCwLa8Ttaa3VqSxkA483A3n/Tp08XbAD9ww8/mBXB2bQSWNuBXAd+1+37AF8+2MB+IAASAAmABMBoIUg7fkdrrU5tVgC4c+dOA4D4O3z4sGzevJkAGGE/uQ78rtv3Ab58sIH9QAAkABIACYARBlcRIQCKpAyA8UPAq1atkuuuu066du0qLVu2FCwSyaai7UCuA7/r9n2ALx9sYD8QAAmABEACYLR0oR2/o7VWp7aUADB+EQigD4tAypYtq2NZIahV24FcB37X7fsAXz7YwH4gABIACYAEwGihQDt+R2utTm0pASAyfFgBjG1g8lvwgUUi2VC0Hch14Hfdvg/w5YMN7AcCIAGQAEgAjJYqtON3tNbq1JYSAN5xxx2hVvpOmzZNx1rPatV2INeB33X7PsCXDzawHwiABEACIAEwWgDQjt/RWqtTW0oAqGNC4a1V24FcB37X7fsAXz7YwH4gABIACYAEwGhZQTt+R2utTm0EQAtdtR3IdeB33b4P8OWDDewHAiABkABIALQI1klO1Y7f0VqrUxsB0EJXbQdyHfhdt+8DfPlgA/uBAEgAJAASAC2CNQEwqXgEQAufIgBaiBd36vYR1+ZZEeFHhBoQAAmABEACYDTxJqhFO35Ha61ObQRAC121Hch14Hfdvg/ZNx9sYD8QAAmABEACoEWwZgaQGcBo3Ud/J3HXgd91+z7Alw82sB8IgARAAiABMNoIrp3AidZandqYAbTQVduBXAd+1+37AF8+2MB+IAASAAmABECLYM0MIDOA0boPM4BR6ck5gMeUzEsHAiABkABIACQARhVxjtWjncCJ1lqd2pgBtNBV24FcB37X7fuQffPBBvYDAZAASAAkAFoEa2YAmQGM1n303yBcB37X7fsAXz7YwH4gABIACYAEwGgjuHYCJ1prdWpjBtBCV20Hch34XbfvA3z5YAP7gQBIACQAEgAtgjUzgMwARus+zABGpSfnAB5TknMA89aAIO4HBLMf2A8+vYzYxCDtBI6NbZk6lxlAC6W1Hch15sd1+z4EGx9sYD/4EXTZD+wHn+DHtT+6bt8idJtTteO3rX2ZON8bABw/fryMGjVK9uzZI3Xq1JExY8ZIs2bN8tRg4cKF0r9/f9m6datUr15dhg4dKm3bto0dv2jRIpk0aZKsW7dO9u7dK++//75ceOGFOeo7dOiQPPjggzJnzhz5/vvv5YorrhDYUbFixVDaazuQ6xvMdfs+wJcPNrAfCB4Ej58fybwfeD+ECtAFHKQdv6OwUbsOLwBw3rx50rlzZwNfTZs2NeA2depU2bRpk1SuXDmXBmvXrjVwOHjwYAN9ixcvlgEDBsiqVaukUaNG5viZM2fKP//5Tzn77LOle/fuSQHwnnvukRdffFGmT58uZcuWld/97neyb98+A40nnnhigdprO5DrB53r9n2ALx9sYD8w4BEACYCJAcn1c8F1+wUGaAJggRJ5AYCAtvr168uECRNiBteqVUvatGkjw4cPz3UR7du3N+nb5cuXx35r2bKllC5d2mTz4sv27dvlnHPOyQWA+/fvl3LlyhlQRH0ou3fvlkqVKsmyZcvkmmuuKVA8AmCBEoU6gHMAj8nEOYCcA5ifH/jwMuKDDT6AB23w4xvloQJMHgdpx28b2zJ1rnMAPHz4sBQrVkzmz5+fYwi3Z8+esmHDBlm5cmUuLZAV7N27t/kLyujRo82w8Y4dO0IB4Ouvv26GfJHxAzgGpV69egY8Bw0alKtdDBnjLyhwIAAjYLJEiRKR95nrh4zr9n0INj7YwH44dmu51sF1+z5o4IMN7AfeD1EEWwKgiHMARNatQoUKsnr1amnSpEmsX4cNGyYzZsyQLVu25OrrokWLmmHbTp06xX6bPXu2dO3aNQegmbfpPDKAeR1/9dVXm4whhqETy8CBA5OCIQHQ7nZkBvCYfswAMgOYnx/4AF8+2EAAJADaRZxjZxMAPQLANWvWSOPGjWP9ikUdGJ7dvHlzUgAEHHbs2DH226xZs6Rbt25y8ODBHMenCoBXXXWVWVQyceLEXO0yAxjFbZe7DgIgATDwCp99geBB8Aj8lL7gPiNvG40IgB4AYGEaAk50OG0Hcv2Qcd2+D9kGH2xgPxA8CB4/P315P/B+sIU/ZgCPKeh8CBhGYBFIgwYNzCrgoNSuXVtat26d5yKQAwcOmMUaQWnVqpWUKlUq5UUgzz33nNxyyy2mGmxBgy1guAjEjweMD/Dlgw0MeH74I/uB/UAQ9wvEbUBQO4FjY1umzvUCAINtYDDsimHgyZMny5QpU2Tjxo1SpUoV6dKli5knGKwIxnBx8+bNzd5/gMQlS5ZIv379cmwDg8UdO3fuNCt7r732Wpk7d67UrFlTfvnLX5o/FGwDs3TpUjOfsEyZMmZPQOwZyG1g/HjQ+wBfPthA8PDDH9kP7AcCIAEwU3CWiXa8AEBcKLJ/I0eONFm4unXrClb1AvJQWrRoIVWrVjWgFpQFCxYY6Nu2bVtsI+h27drFfsexWBSSWB5//HHBYg4UzBd86KGHBAtC4jeCxsreMEX7DcJ1wHHdvg/w5YMN7AeCB8HDL/DgPck5gGEYwfdjvAFA34VKZh8BMJpe83niPwHQD/hiP7AfCME5n7euIdR1+7bRRzt+29qXifMJgBYqazuQ6xvMdfs+BH0fbGA/+AE/7Af2AyHUr0ysRfjmNjC+LAKx6USX5xIAo1GfGcBjOnIfQO4DmJ8f+PAy4oMNBHGCeBSRRzt+R2Gjdh3MAFoorO1Arh90rtv3Idj4YAP7gQGPmSe/Mk+8JzkH0AIdvDmVAGjRFQRAC/HiTmUGkBnAwB189gUGfYI4QdwvELeJQNrx28a2TJ1LALRQWtuBXAcc1+37kH3zwQb2A8GD4OEXePCeZAbQAh28OZUAaNEVBEAL8ZgBzCUe5wByDiCcwucsKF+I/HgZYT/Yxx7t+G1voX4NBEALjbUdyPVbpuv2fXjI+WAD+8GPoMt+YD8wE+tXJtYifHMVMFcB27iPqDuQ64Djun0f4MsHG9gPBA+Ch1/gwXuSQ8B29ODH2cwAWvQDM4AW4nEImEPASdzH5+FPBn2COEHcLxC3iUDa8dvGtkydSwC0UFrbgVwHHNft+5B988EG9gPBg+DhF3jwnmQG0AIdvDmVAGjRFQRAC/GYAWQGkBnApDeQz1lQvhD58TLCfrCPPdrx295C/RoIgBYaazuQ67dM1+378JDzwQb2gx9Bl/3AfmAm1q9MrEX4Vp/Db2Nbps4lAFooTQC0EI8ZQGYAmQFkBjCfRwi3RfJ7SyAfXohsIpB2/LaxLVPnEgAtlNZ2INc3mOv2fci++WAD+4GZJ2ae/Mo88Z7kHEALdPDmVAKgRVcQAC3EYwaQGUBmAJkBZAYw34eoz/NBfYBgmwikHb9tbMvUuQRAC6W1Hcj1Dea6fR+ybz7YwH5gBpAZQGYAE0OV6+eC6/YtQrc5VTt+29qXifMJgBYqazuQ6xvMdfs+wJcPNrAfCIAEQAIgAdAiWCc5VTt+R2utTm0EQAtdtR3IdeB33b4P8OWDDewHAiABkABIALQI1gTApOIRAC18igBoIV7cqT7PcyEA+gFf7Af2AyE45/PW9Yuh6/Zto492/La1LxPnEwAtVNZ2INc3mOv2fQj6PtjAfvADftgP7AdCqF+ZWIvwzTmAIkIAtPAgAqCFeMwA5hKP+55x3zM4BTPix24N3g9++4IPL0Q2EUg7ftvYlqlzCYAWSms7kOsbzHX7PmTffLCB/cDMEzNPfmWeeE9yH0ALdPDmVAKgRVcQAC3EYwaQGcAk7uNz9otBnyBOEPcLxG0ikHb8trEtU+cSAC2U1nYg1wHHdfs+ZN98sIH9QPAgePgFHrwnmQG0QAdvTiUAWnQFAdBCPGYAmQFkBjDpDeRzFpQvRH68jLAf7GOPdvy2t1C/BgKghcbaDuT6LdN1+z485Hywgf3gR9BlP7AfmIn1KxNrEb65CpirgG3cR/9TMq4Djuv2fYAvH2xgPxA8CB5+gQfvSQ4B29GDH2czA2jRD8wAWojHIWAOAXMImEPA+TxCuA0Mt4GBe+Q3JcImAmnHbxvbMnUuAdBCaW0Hcv2W6bp9H7JvPtjAfmAGkBlAZgATQ5Xr54Lr9i1CtzlVO37b2peJ8wmAFiprO5DrG8x1+z7Alw82sB8IgARAAiAB0CJYJzlVO35Ha61ObQRAC121Hch14Hfdvg/w5YMN7AcCIAGQAEgAtAjWBMCk4hEALXyKAGghXtyp3PbimBic88Q5T/n5gQ8vIz7YwBcivhBFEXm043cUNmrXQQC0UFjbgVw/6Fy370Ow8cEG9gMDHjOAzAAyA2gRrJkBZAYwWvfRn0TqOvC7bt8H+PLBBvYDAZAASAAkAEYbwbUTONFaq1MbM4AWumo7kOvA77p9H+DLBxvYDwRAAiABkABoEayZAWQGMFr3YQYwKj05B/CYkpwDyDmA+fmBDy8jPtjAFyK+EEURe7QTOFHYqF0HM4AWCms7kOsHnev2fQg2PtjAfmDAYwaQGUBmAC2CNTOAzABG6z7MAEalJzOAzAAGvuSzLxDECeIEcb9A3CYGaSdwbGzL1LneZADHjx8vo0aNkj179kidOnVkzJgx0qxZszx1WLhwofTv31+2bt0q1atXl6FDh0rbtm1jxx89elQGDRokkydPlq+++koaNWokTz31lKk7dhNXrSo7duzI0cYjjzwiI0aMCKW/tgO5Djiu2/ch++aDDewHggfBwy/w4D3JbwGHggTPD/ICAOfNmyedO3cWQGDTpk1l0qRJMnXqVNm0aZNUrlw5l4Rr1641cDh48GADfYsXL5YBAwbIqlWrDOihPPHEEwYKp0+fLjVq1JAhQ4bIm2++KVu2bJHixYubY6pWrSrdunWT7t27x9o4/fTTBX9hCgEwjEoFH+Nz1ocA6Ad8sR/YD4TgnM9S1xDquv2CI0v+R2jHb1u08BXZAAAfr0lEQVT7MnG+FwAIaKtfv75MmDAhds21atWSNm3ayPDhw3Pp0L59e/Mdv+XLl8d+a9mypZQuXVrmzJkjyP6dffbZ0qtXL0FGD+XQoUNy5plnGjDs0aNHDABxDP7SKdoO5PoGc92+D0HfBxvYD37AD/uB/UAI/TlS+nA/pBO3g3O047eNbZk61zkAHj58WIoVKybz58/PMYTbs2dP2bBhg6xcuTKXFsgK9u7d2/wFZfTo0WbYGEO627ZtM8PC69evl4suuih2TOvWraVUqVIyY8aMGAACDGFDpUqV5Oabb5aHHnpIihYtGkp/bQdyfYO5bt8H+PLBBvYDwYPg4Rd48J7kEHAoSPD8IOcAuHv3bqlQoYKsXr1amjRpEpNr2LBhBtQwZJtYAGgY2u3UqVPsp9mzZ0vXrl1Npm/NmjVmKPnzzz83mcCg3H333QYQX375ZfNPgEZkHpE5fOedd6Rv374CSMTwc7KCuvEX/wYBcNy/f7+UKFEi8q52/ZBx3b4P8OWDDewHAiABkACYGGBcPxdct28bcLUTOLb2ZeJ8bwAQ0Na4cePYNWP+3syZM2Xz5s1JARBw2LFjx9hvs2bNMvP5Dh48GANAwOVZZ50VOwZz/Xbt2iUvvfRSUm2xsOSmm26SL7/8UsqWLZvrmIEDB5qFJYmFAGjnqpwDeEw/7gPIfQDz8wMfXkZ8sMEH8KANzADaRT0/znYOgC6HgBO7ABnDihUryltvvRVbTBJ/DDOAOk5LACQABp7lsy8w6DMTy0ysX5lYm4jEDKCIcwBEB2IRSIMGDcwq4KDUrl3bDMfmtQjkwIEDsmzZstjxrVq1MvP74heBYI7gww8/bI4BaJYvXz7HIpBE51m6dKlcf/31Zpg42erjxOO1Hch1wHHdvg/ZBh9sYD8QPAgefoEH70lmAG3g05dzvQDAYBuYiRMnmmFg7N03ZcoU2bhxo1SpUkW6dOli5gkGMIjh4ubNm5ttXgCJS5YskX79+uXaBgbHT5s2Tc477zzBnMIVK1bEtoHBVjLI9F1++eVSsmRJeffdd82ikoYNG5r6whQCYBiVCj7G56wPAdAP+GI/sB8IwTmfpa4h1HX7BUeW/I/Qjt+29mXifC8AEBeK7N/IkSPNRtB169Y1CzQAeSgtWrQwe/Zh4UdQFixYYKAvWPELGGzXrl3s92AjaOwpGL8RNOpGwQrhe++918wxxNAuQLNDhw4mY4hVyWGKtgO5vsFct+9D0PfBBvaDH/DDfmA/EEL9ysSGidN5HaMdv21sy9S53gBgpi44yna0Hch1wHHdvg/w5YMN7AeCB8HDL/DgPckh4ChZwlVdBEAL5QmAFuLFncoh4GNicBUwVwHn5wc+vIz4YAPhiy9EUUQe7fgdhY3adRAALRTWdiDXDzrX7fsQbHywgf3AgMcMIDOAiaHK9XPBdfsWoducqh2/be3LxPkEQAuVtR3I9Q3mun0f4MsHG9gPBEACIAGQAGgRrJOcqh2/o7VWpzYCoIWu2g7kOvC7bt8H+PLBBvYDAZAASAAkAFoEawJgUvEIgBY+RQC0EC/uVM4BPCYG5wByDmB+fuDDy4gPNvCFiC9EUUQe7fgdhY3adRAALRTWdiDXDzrX7fsQbHywgf3AgMcMIDOAzABaBGtmAJkBjNZ99CeRug78rtv3Ab58sIH9QAAkABIACYDRRnDtBE601urUxgygha7aDuQ68Ltu3wf48sEG9gMBkABIACQAWgRrZgCZAYzWfZgBjEpPzgE8piTnAHIOYH5+4MPLiA828IWIL0RRxB7tBE4UNmrXwQyghcLaDuT6Qee6fR+CjQ82sB8Y8JgBZAaQGUCLYM0MIDOA0boPM4BR6ckMIDOAgS/57AsEcYI4QdwvELeJQdoJHBvbMnUuM4AWSms7kOuA47p9H7JvPtjAfiB4EDz8Ag/ek/wWsAU6eHMqAdCiKwiAFuLFnepz1ocA6Ad8sR/YD4TgnM9b1xDqun3b6KMdv23ty8T5BEALlbUdyPUN5rp9H4K+DzawH/yAH/YD+4EQ6lcm1iJ881vAIkIAtPAgAqCFeMwA5hKPq4C5ChhOwYz4sVuD94PfvuDDC5FNBNKO3za2ZepcAqCF0toO5PoGc92+D9k3H2xgPzDzxMyTX5kn3pOcA2iBDt6cSgC06AoCoIV4zAAyA5jEfXzOfjHoE8QJ4n6BuE0E0o7fNrZl6lwCoIXS2g7kOuC4bt+H7JsPNrAfCB4ED7/Ag/ckM4AW6ODNqQRAi64gAFqIxwwgM4DMACa9gXzOgvKFyI+XEfaDfezRjt/2FurXQAC00FjbgVy/Zbpu34eHnA82sB/8CLrsB/YDM7F+ZWItwjdXAXMVsI378Esgdur9fDYzHse04KpHrnrMzw98eBnxwQaCOEE8itijncCJwkbtOpgBtFBY24FcP+hct+9DsPHBBvYDAx4zT35lnnhPcg6gBTp4cyoB0KIrCIAW4sWdygwgM4CBO/jsCwz6BHGCuF8gbhOBtOO3jW2ZOpcAaKG0tgO5Djiu2/ch++aDDewHggfBwy/w4D3JDKAFOnhzKgHQoisIgBbiMQOYSzzOAeQcQDiFz1lQvhD58TLCfrCPPdrx295C/RoIgBYaazuQ67dM1+378JDzwQb2gx9Bl/3AfmAm1q9MrEX45ipgrgK2cR+uArZT7+ezmfE4pgUzgH5nvwiABEACIAEwqrjnQz3MAFr0AjOAFuJxCJhDwEncx+eXAQIgAZAASACMJur5UQsB0KIfCIAW4hEACYAEwKQ3kM8QDINdg7Dr9n3QwAcbfOgHmwikHb9tbMvUuQRAC6W1Hcj1Dea6fR8ecj7YwH5g5omZJ78yT7wn3b8IWIRuc6p2/La1LxPnEwAtVNZ2INcPGdft+wBfPtjAfiAAEgAJgImhyvVzwXX7FqGbAPh/4hEALbyIAGghXtypHPI6JgYXgXARSH5+4MPLiA82+AAetIEZwGiin9taCIAW+hMALcQjAOYSjwBIACQA/nxb8H7g/VDQ/WATgbTjt41tmTqXAGihtLYDuX7LdN2+D9kGH2xgP3AImEPAHALmELBFsE5yqnb8jtZandoIgBa6ajuQ68Dvun0f4MsHG9gPBEACIAGQAGgRrAmAScUjAFr4FAHQQjwOAXMIOIn7+DwflCBOECeI+wXiNhFIO37b2JapcwmAFkprO5DrgOO6fR+ybz7YwH4geBA8/AIP3pNcBGKBDt6cSgC06AoCoIV4zAAyA8gMYNIbyOcsKF+I/HgZYT/Yxx7t+G1voX4NBEALjbUdyPVbpuv2fXjI+WAD+8GPoMt+YD8wE+tXJtYifHMjaBHxBgDHjx8vo0aNkj179kidOnVkzJgx0qxZszz7d+HChdK/f3/ZunWrVK9eXYYOHSpt27aNHX/06FEZNGiQTJ48Wb766itp1KiRPPXUU6buoODfH3jgAXnhhRfMP91www3y5JNPSqlSpUL5FQEwlEwFHsSMxzGJuO0Ft73Izw98eBnxwQaCOEG8wKAS4gDt+B3CBOeHeAGA8+bNk86dOwsgsGnTpjJp0iSZOnWqbNq0SSpXrpxLpLVr1xo4HDx4sIG+xYsXy4ABA2TVqlUG9FCeeOIJA4XTp0+XGjVqyJAhQ+TNN9+ULVu2SPHixc0xrVq1ks8++8xAIsrdd98tVatWlRdffDFUx2g7kOsHnev2fQg2PtjAfmDACx5I9AU/5p6xH/zoh1CBOo+DtOO3jW2ZOtcLAAS01a9fXyZMmBC77lq1akmbNm1k+PDhubRo3769Sd8uX7489lvLli2ldOnSMmfOHEH27+yzz5ZevXrJI488Yo45dOiQnHnmmQYMe/ToIR999JHUrl1b3nrrrRg04r8bN24smzdvlpo1axbYB9oO5Poh47p9H+DLBxvYDwRAAuDPj2PeD7wfCgzOIQ7Qjt8hTHB+iHMAPHz4sBQrVkzmz5+fYwi3Z8+esmHDBlm5cmUukZAV7N27t/kLyujRo82w8Y4dO2Tbtm1mWHj9+vVy0UUXxY5p3bq1Gd6dMWOGPPPMM9KnTx/5+uuvc9SP31FX165dc7ULiMRfUPbv328ylLt27ZISJUpE3pl1H3858jqTVfiPQdckbcd1+zCKNlCDwDld+4Lr9nk/HPME9oMfOvjQDzYBEgBYqVIlwwAlS5a0qarQnuscAHfv3i0VKlSQ1atXS5MmTWJCDhs2zIAahmwTS9GiRc3QbqdOnWI/zZ4920AbAG3NmjVmKPnzzz83mcCgYIgXgPjyyy8L6kcdH3/8cY7qMVyMevr27Zur3YEDB5p5hSxUgApQASpABahA4VcACZyKFSsW/gtJ4wq8AUBAG4Zfg4L5ezNnzjTDsckAEHDYsWPH2E+zZs2Sbt26ycGDB2MACLg866yzYsd0797dZOteeuklA4DJAPO8884z9Tz66KO52k3MAB45ckT27dsnZcuWlQMHDpi3Ca1sYBp9m/FTgjeqbNYAolMHakA/+Pnxw/uB94OP9wOmiiFuI0l0wgknZDxe+tCgcwAsTEPA+XUY5xMce8ghlY6hcY0hcR9umDA2UAf6QhDweD/QF+gLx56afC6GiR6ZPcY5AOJysQikQYMGZhVwULBAA3P28loEAnJftmxZ7His6MX8vfhFIJgj+PDDD5tjAJrly5fPtQjk7bfflksuucQcg/++9NJLQy8Cie8qOjdv8MAf6Av0BQa8nBnAbAdhPhP4TMgs2oVrzQsADLaBmThxohkGxrYsU6ZMkY0bN0qVKlWkS5cuZp5gAIMYLm7evLnZ5gWQuGTJEunXr1+ubWBw/LRp0wTDuhjyXbFiRa5tYDBMjG1nUDBHEO2F3QaGAJjTyfiQ45suIZjgkxh6+Fwg/PCFKByQZfooLwAQF43s38iRI81G0HXr1jUrcQF5KC1atDD782HRRlAWLFhgoC9Y8QsYbNeuXez3YCNowF38RtCoOyiYv5e4EfS4ceNCbwQd31mYHwjgxOKRk08+OdP96EV71OBYN1AHakA/+PmRxPuB9wPvBy9CdC4jvAFAP+WhVVSAClABKkAFqAAVOP4UIAAef33KK6ICVIAKUAEqQAWoQL4KEADpIFSAClABKkAFqAAVyDIFCIBZ1uG8XCpABagAFaACVIAKEADpA1SAClABKkAFqAAVyDIFCIARdDhWMI8aNcqsYK5Tp475JnGzZs0iqLlwVIHVz4sWLTL7J5566qnmk35PPPGE1KxZs3BcgIKV0OT3v/+94JvW8IdsKvgE4yOPPCLLly+X77//XvB5xaefftrs9ZkN5ccffxR8NhJfJ/rXv/5lvkZ0xx13mF0LjtcvDrz55pvmGbhu3TrzHFy8eLG0adMm1t3BrgzY4it+VwY8L4+nkp8OP/zwg/EB7F+L3SuwN+KVV14pI0aMyPHJ0sKuR0G+EH99PXr0MNu+YdePXr16FfZLL3T2EwAtuyzYwxAQiO8PY9uZqVOnyqZNm6Ry5cqWtReO01u2bCkdOnSQiy++WBD8HnvsMfnwww+NBqeddlrhuIgIrXz33XfllltuMV9Dufzyy7MKABHcL7roInPd99xzj9l8fevWrWYbp+rVq0eosr9VYUsqBDR8ahKA895775nviw8ZMsS8EByPBbCP77nXr19fbrzxxlwAiBdC6IKtvPBCAC0ACvjWe/HixY8bSfLTAV9IuummmwSfJK1Xr54BYUAPnpnwkeOlFOQLwXU+//zz5kXpiy++kIceeogA6MABCICWouMrJnjoTZgwIVZTrVq1zNtvsq+YWDZXKE7HDY3Av3LlythejoXC8AiM/Oabb4w/4IUAQe7CCy/MKgDEN7QBAn/7298iULNwVnHdddfJmWeeabKeQQEUFStWzHzf/HgvRYoUyQGAyP7he6uAHWSGUbA3IDQCGCILdDyWRB2SXSNeFvElqh07dhyXCYO8NMAoAWLnyy+/LNdee63xDWYAM38XEAAtNE/nO8YWzRWaUz/99FPz9RVkAeM33i40F2Bh6O233y5lypQxGSBsYJ5tAIhPOF5zzTXy2WefmRcAfMHn3nvvNVmPbCkY0sNXjV555RWT7frggw/k6quvNi8CHTt2PO5lSAz6wWb969evN9nhoOArTvh8JzKlx2MJA4Cvvvqq8Y2vv/76uPx+ejINjhw5Yoa+0f/IiGN0gADo5g4gAFrojs/IIcAh44F5b0HBZ+fwUMPwRrYVvO3jxsbwRrZlgebOnWuGufBWf8opp2QlAOK6Ufr06SM333yzvPPOO+bhjqkR+KRjNhTcA5j/iezWiSeeKD/99JPxC3wlKBtKYtDHpzsxPQZZH2QCg4JPbyLzhSzQ8VgKAsCDBw/KZZddJueff74899xzx6MEkkwDjIy98cYbpt/xOwHQXdcTAC20DwAQDzh8wzgoeNhjqAeLIrKt3HffffKXv/zFfJe5YsWKWXP5u3btkoYNG5qsD+b3oGRjBrBo0aJGB9wTQcHnFgHFa9eu/f/tnQmMjecXxk9KUWprEY2dICXWtFTSkEhRoQmxEwS1V0ssFVpSEaGWUHttsYutFfuakKjY9wrd1Ba0pGjpnn9+559vcuea4cbcjs93n5NMWjPffN/7/t47M899zjnvmxKvB94IUNNEUwQ1gCdOnHARPGXKFMMhjnpkJgD5fUlDTBC4wvzcbNu2LZJIHiUAaQjhDdKlS5f8jHrqhaMY8QxoEiLlixscvBmQAHx6Ky8BmAX2SgGnhzdgwACjsJfi7nLlymWB7LP3rcy7ZcuW7vgEgfPDL0A6P6l5iv3aszfDxEZcpkwZa9SokTdCBUF9LPWQOECpEKVKlTJqIXkzFATzx+VJhTeFSgH/f9UzE4CIP5rESI3v2bPHXn755cj+WMQzoAyC7EBsNzy/J/k3PzcXL16MLIswTkwCMIurQiEr21tQ9B8EdVCkQVOlCYSUF+KPrR94N0v9X6rFvXv3PJ0VG3R+kt6h8D1VaiE7duzork5s+n/QoEF28ODBdK5glF8f/EFH8NEFHQS/CxYtWmQXLlyI8tQzFD5BEwivg2HDhvk1vHmmUSzVmkAC8ffNN994GrRo0aKRfj3EC8Bbt275NkGxQc1w586dvVM+lbcOexovBAnALFIPtoGh6Js0MHsazZs3z86ePWu4IakQFPmvWLHCNmzYkO4HmH2u2BcwVSMVU8CkeqmH/eSTT9zloAaQVB8/F506dUqJlwJ7/lHcT90jKeDjx48b9W7du3d3wRPFoPud5i+CRg/S3WwFREMU22Ex70AE8waROmneLEZtG5hHcSDlSTc46c9NmzZ5F3QQcKJ8IgrxuNdC/ByVAn56qy4BmAT2uH+ffvqpv7PB6aEDtH79+km487NxC97lZRQ4HvwxTNVIRQHIWvPHjYYHXA5KAUj5pFIXMG7wxx9/7I74zZs3vdaJ7t9Ro0ZF5o98/M80Yg7BFx/UPLL3X7ARNKI4diPoqDnjj+LAnneZlcbgBvL7IgrxuNeCBGB4VlkCMDxroZGIgAiIgAiIgAiIQLYQkADMFsx6iAiIgAiIgAiIgAiEh4AEYHjWQiMRAREQAREQAREQgWwhIAGYLZj1EBEQAREQAREQAREIDwEJwPCshUYiAiIgAiIgAiIgAtlCQAIwWzDrISIgAiIgAiIgAiIQHgISgOFZC41EBERABERABERABLKFgARgtmDWQ0RABERABERABEQgPAQkAMOzFhqJCIiAmZ8Hyoa5nKBRs2bNUDDhDF82NT9x4oQf78d/44PNjnv37m1r1671zY7DNP5QQNQgREAEQkVAAjBUy6HBiMDTJ4DQWbx4sR/dNXz48LQBffnll9ayZUs/1eG/jDAKwHbt2tnPP/9sCxcutBdffNE47zc+tm7d6meAcxJC+fLlrUiRIpYzZ84so2I9fvnlF4O/QgREQASSRUACMFkkdR8RiAgBBAdnXOfJk8e+//57K1y4sM/sWReAf/755xMfxfbaa69Zs2bN/IzjzGLGjBk2ceJE+/HHH5P6SkiWAPznn3+MYxufe+65pI5PNxMBEXg2CUgAPpvrplGLwH9GAMFx69Yt+/bbb+2dd97xc64zEoCcbYoojE2HTp061fjAxSMC8VKnTh2bNm2a/fHHHzZo0CAbOXKknxe8YMECy5s3r40ZM8a6d+/u3xM4gCtXrrTPPvvMjh07ZhUqVLCZM2emOy/166+/tiFDhti+ffssX7581rhxYz+HG+eN4GxVzprNlSuXLVmyxKpWrWp79+59iNu///5rY8eOtc8//9x++ukne/XVV238+PH29ttv+7XxZ12PHj3amHtsBK5p8LkyZcr4PHBLEYVz5szxs8IrVark5wS3bt3aL0WU9erVy/bs2WPXr1+30qVLW79+/eyDDz7wr/OceNHJubEEZ++Sai5UqJD/m3WoVauW/fDDD1a2bFk/g3fgwIG2bNkyGzZsmF24cCHtfGbO6WZdg2vff/99fy6BUOb85nXr1vn9ixcv7qlt1kshAiIQHQISgNFZS81EBJJCIBBtXbt2tY4dO7poKFmy5EMOYKICcP369dalSxcbMGCA7d+/33r06GFNmjSx+vXrW5s2bdxtRAB+9913VqpUqTQByDMRk1WqVLEpU6b4dQgW0q+IqerVq1vPnj393g8ePLAPP/zQ/v77bxdTgQA8evSo9e3b15+JGKN+Lz4Qjcxl7ty5LqBI8/K5s2fPWsWKFV2YvfXWWy4IEZykgPmIjTt37rhYRUQePnzYcuTIYUWLFnWhy/yZB/dCrPbp08e2b99uDRo0sL/++svFZ/PmzV24fvXVVy4IEWht27a1X3/91cd+9+5d/xzx0ksv+XWJCEDu9frrr7sIhRtMV6xYYYhYHEvmS60iHGHMmk+aNMnnsnz5chekly9f9o8OHTok5fWlm4iACISDgARgONZBoxCB0BCITTnWq1fPBRhOXXwKOFEBSE0cqeQg9YgIK1asmIshAhesYMGCNn/+fGvfvn2aAMSFQ9QRCDsaQxCRuFmjRo2ygwcPupAK4sqVKy4gz58/704bDiDCDIHzqChRooT179/fRowYkXYZjiXCCdeRoBmlRYsWDzl/sfeNdz9/++03F3UIUjgG8e6779r9+/ddiGUUjOXGjRveTEJklAKGaSICsFu3bu4M1qhRI+1RiLoJEyakE3SI0C1btriwxA1E/O7atesh9zM0L1INRAREIMsEJACzjFA3EIFoEYgVHIi0hg0b2qlTpzyFGNsEkqgAJK26efPmNEg4X6RmA3HFF0iZDh482MVHkAImXYtLGATPJt2JE0Y93s6dOx+q6UN0IWSaNm3qAhDXbd68eZkuEM4a4hNBxbiCIE198uTJNDfxSQQgTiBCkvR0bJBixXlDwBKkhxG/1A7iZPJ1nnfo0KEsC0BSt7///nuakGMtEN8vvPBCulpABDYcEJ6k3Bs1auSOIa4n7iTpdYUIiEC0CEgARms9NRsRyDKBeMcJsfX888+7ExUrAEnbUieGUAqCVCPCLr4GMLaDFWGGwMExC4KaNerV+HiUAKQhhRQtAo/aQZys+HjllVdcdGX0nPhrAwEYLzYZx+nTp2337t3+LU8iABF4b7zxhotLXMbYyJ07t7uVq1ev9rTr5MmT3SXMnz+/p2v53qC2MiMHEGGOYL19+3Zak04gOONrAOkgDgKBR00fdYF169ZNNybS1risBFzoasYFXLNmjafAA0cyyy8w3UAERCAUBCQAQ7EMGoQIhIdAvOBACCGAcOgQJ8E2MLNnz/aUKDVyQaNEp06dvM4vGQIQcUe6l8ChYmuV9957zz9HbR3i88yZM5lutZKIAOTemaWAce+ok3tSAXjv3j2vA8SB7Ny5c4YLTEqbZpZAaHIRYostZwIBSB0fNY8bN25Mu8e5c+c8NU+qlv8SPIdrHyUAuY46QJxBmlESCdLsOIE0BlF/qBABEYgGAQnAaKyjZiECSSOQkeNEowVOEOnEQAAiQuisZb9Aulq3bdvmoqJAgQJJEYDUquES0pVLUwY1c4gb6uquXbvmohQXbOjQof45upZXrVrlQgg3K1EByDNoiqCBg3uSYqYhImgCeVIByPd99NFHnuLF4XvzzTfdWaPOjiYSnD86o6lnxAnEfVu6dKk3YPD/gQAcN26cN6js2LHD07Kkagk6o3EYqd+jUQeBTv3j4wQg6WZS7awbTiqd2UeOHPGOX7p/YY2LCgvqNukWJoV/9epVbSGTtJ8y3UgEnj4BCcCnvwYagQiEikBGApD6tMqVK7tYiN0IGnGDQCEV2apVK78GIZUMBxDBh0CiiQOxgxtHPWIQiB6aRNgWhXFRR4hThXjDkUxUAMZuA3Pz5k131GK3gcmKAITV9OnTbdasWd4IQw1j7dq1veGE+kbGTVfwF1984WOm0xaBR/o1EIDU7eGsHjhwwLuCmS9zw2mlwxkONKwg6uiqfpwAZD6wxc3FfSRdXq1aNU+/k+JHQDNe7ouQDrqIqVtUiIAIRIeABGB01lIzEQEREAEREAEREIGECEgAJoRJF4mACIiACIiACIhAdAhIAEZnLTUTERABERABERABEUiIgARgQph0kQiIgAiIgAiIgAhEh4AEYHTWUjMRAREQAREQAREQgYQISAAmhEkXiYAIiIAIiIAIiEB0CEgARmctNRMREAEREAEREAERSIiABGBCmHSRCIiACIiACIiACESHgARgdNZSMxEBERABERABERCBhAhIACaESReJgAiIgAiIgAiIQHQISABGZy01ExEQAREQAREQARFIiIAEYEKYdJEIiIAIiIAIiIAIRIeABGB01lIzEQEREAEREAEREIGECPwPiRU907qM+RAAAAAASUVORK5CYII=\" width=\"640\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.figure()\n",
"plt.bar(range(n_features,0,-1), MSE)\n",
"plt.title('Mean-squared error for different numbers of features')\n",
"plt.xlabel('Number of features')\n",
"plt.ylabel('Mean-squared error')\n",
"plt.show()\n",
"plt.savefig('MSE_varying_features.png', dpi=300)"
]
},
{
"cell_type": "code",
"execution_count": 97,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[0.02356106 0.02355203 0.02354303 0.0235818 0.02361018 0.02373792\n",
" 0.02427768 0.02517083 0.02510396 0.02596514 0.02861912 0.03549382\n",
" 0.03489173 0.03438738]\n"
]
}
],
"source": [
"print(MSE)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"print(min(MSE)) # --> 10 features minimum, nearly the same error with 8 features"
]
},
{
"cell_type": "code",
"execution_count": 123,
"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\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\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>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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\" width=\"640\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# raw data\n",
"plt.figure()\n",
"bins=25\n",
"horizon_2m_hist = plt.hist(horizon_2m.fully_shaded_ratio, range=(0,1), bins=bins, facecolor='w',edgecolor='r', alpha=0.5, density=True, label = '2m DOM res.')\n",
"horizon_50cm_hist = plt.hist(horizon_50cm.fully_shaded_ratio, range=(0,1), bins=bins, density=True, facecolor='g', alpha=0.2, edgecolor='g', label = '50cm DOM res.')\n",
"prediction_hist = plt.hist(y_val, bins=bins, range=(0,1), density=True, facecolor='b', alpha=0.2, edgecolor='b', label = 'RF - validation')\n",
"plt.legend()\n",
"plt.title('Distribution of shaded area ratio')\n",
"plt.show()\n",
"plt.savefig('/Users/alinawalch/Documents/EPFL/data/rooftops/shading_images/visibility/shaded_area_hist_with_val.png', dpi=300)"
]
},
{
"cell_type": "code",
"execution_count": 122,
"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\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\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>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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\" width=\"640\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.figure()\n",
"bins=20\n",
"plt.hist(horizon_50cm.fully_shaded_ratio,bins=bins, range=(0,1), density=True, facecolor='r', alpha=0.2, edgecolor='r', label = '50cm horizon')\n",
"plt.hist(y, bins=bins, range=(0,1), density=True, facecolor='b', alpha=0.2, edgecolor='b', label = 'training')\n",
"plt.hist(y_val, bins=bins, range=(0,1), density=True, facecolor='g', alpha=0.2, edgecolor='g', label = 'RF - validation')\n",
"plt.legend()\n",
"plt.title('Distribution of predicted data')\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Plot random sample\n",
"Plot original value and corrected value for different roof IDs (random)"
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {},
"outputs": [],
"source": [
"validation['prediction'] = y_val\n",
"validation_sample = validation.sample(30)"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Index(['zone', 'fully_shaded_ratio_2m', 'n_cells', 'null_cells',\n",
" 'non_null_cells', 'NEIGUNG', 'AUSRICHTUN', 'FLAECHE', 'SHAPE_Leng',\n",
" 'GASTW', 'GBAUP', 'GKAT', 'GAREA', 'perim_ratio', 'fully_shaded_ratio',\n",
" 'prediction'],\n",
" dtype='object')"
]
},
"execution_count": 26,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"validation_sample.columns"
]
},
{
"cell_type": "code",
"execution_count": 27,
"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\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\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>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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\" width=\"640\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.figure()\n",
"plt.scatter(range(len(validation_sample)), validation_sample.fully_shaded_ratio_2m, facecolor='w',edgecolor='r', alpha=0.7, label = 'Raw ratio (2m DOM)')\n",
"plt.scatter(range(len(validation_sample)), validation_sample.fully_shaded_ratio,facecolor='g', alpha=0.5, edgecolor='g', label = 'Target ratio (50cm DOM)')\n",
"plt.scatter(range(len(validation_sample)), validation_sample.prediction,facecolor='b', alpha=0.5, edgecolor='b', label = 'Corrected ratio')\n",
"plt.legend()\n",
"plt.xlabel('Rooftop sample (random)')\n",
"plt.ylabel('Shaded area ratio')\n",
"plt.title('Performance of shaded area ratio estimation')\n",
"# plt.savefig('random_sample_shaded_area_2', dpi=300)"
]
},
{
"cell_type": "code",
"execution_count": 32,
"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\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\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>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"<div id='d61e12df-2c70-4f85-8686-5501feddc104'></div>"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"Text(0,0.5,'orientation')"
]
},
"execution_count": 32,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"plt.figure(figsize=(10,3))\n",
"\n",
"plt.subplot(131)\n",
"var = horizon_50cm\n",
"plt.scatter(var.NEIGUNG, var.AUSRICHTUN, c=(var.fully_shaded_ratio), s=2)\n",
"plt.xlabel('tilt')\n",
"plt.ylabel('orientation')\n",
"\n",
"plt.subplot(132)\n",
"var = x_crossval\n",
"plt.scatter(var.NEIGUNG, var.AUSRICHTUN, c=(y_crossval), s=3)\n",
"plt.xlabel('tilt')\n",
"plt.ylabel('orientation')\n",
"\n",
"plt.subplot(133)\n",
"var = horizon_2m\n",
"plt.scatter(var.NEIGUNG, var.AUSRICHTUN, c=(var.fully_shaded_ratio), s=2)\n",
"# plt.colorbar()\n",
"plt.xlabel('tilt')\n",
"plt.ylabel('orientation')"
]
},
{
"cell_type": "code",
"execution_count": 23,
"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\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\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"
],
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\" width=\"640\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"Text(0,0.5,'orientation')"
]
},
"execution_count": 23,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"var = horizon_2m\n",
"plt.figure()\n",
"plt.scatter(var.NEIGUNG, var.AUSRICHTUN, c=(var.fully_shaded_ratio), s=3)\n",
"#var.mean_06_15h.hist(bins=100, range=(0,1))\n",
"plt.colorbar()\n",
"plt.xlabel('tilt')\n",
"plt.ylabel('orientation')"
]
},
{
"cell_type": "code",
"execution_count": 22,
"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\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\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>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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\" width=\"640\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"Text(0,0.5,'orientation')"
]
},
"execution_count": 22,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"var = x_crossval\n",
"plt.figure()\n",
"plt.scatter(var.NEIGUNG, var.AUSRICHTUN, c=(y_crossval), s=3)\n",
"#var.mean_06_15h.hist(bins=100, range=(0,1))\n",
"plt.colorbar()\n",
"plt.xlabel('tilt')\n",
"plt.ylabel('orientation')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.4"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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