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diff --git a/Available_area/All_Roof_Info.ipynb b/Available_area/All_Roof_Info.ipynb
index 73f14a2..f9463ad 100644
--- a/Available_area/All_Roof_Info.ipynb
+++ b/Available_area/All_Roof_Info.ipynb
@@ -1,2303 +1,2941 @@
{
"cells": [
{
"cell_type": "code",
- "execution_count": 1,
+ "execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"import xarray as xr\n",
"import numpy as np\n",
"\n",
"import os\n",
"import time\n",
"\n",
"%matplotlib notebook\n",
"import matplotlib.pyplot as plt"
]
},
{
"cell_type": "code",
- "execution_count": 2,
+ "execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"SON_fp = '/work/hyenergy/raw/Sonnendach/Sonnendach_all_roofs/SOLKAT_CH_DACH_LV03.txt'\n",
"roof_repl_fp = '/work/hyenergy/output/solar_potential/geographic_potential/available_area/ROOFS_CH_replaced.csv'\n",
"panel_fitting_fp = '/work/hyenergy/output/solar_potential/geographic_potential/available_area/panel_fitting/panelled_area_stats_CH_best.csv'\n",
"corners_fp = '/work/hyenergy/output/solar_potential/geographic_potential/available_area/CH_n_corners.csv'\n",
"shade_fp = '/work/hyenergy/output/solar_potential/geographic_potential/available_area/shading_stats/CH_shaded_area_replaced.csv'\n",
"\n",
"output_fp = '/work/hyenergy/output/solar_potential/geographic_potential/CH_ROOFS_all_replaced.csv'"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"SON_cols = pd.read_csv( SON_fp, nrows = 0 )\n",
"roof_cols = pd.read_csv( roof_repl_fp, nrows = 0 )\n",
"panel_cols = pd.read_csv( panel_fitting_fp, nrows = 0 )"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Empty DataFrame\n",
"Columns: [Unnamed: 0, OBJECTID, DF_UID, DF_NUMMER, DATUM_ERSTELLUNG, DATUM_AENDERUNG, SB_UUID, SB_OBJEKTART, SB_DATUM_ERSTELLUNG, SB_DATUM_AENDERUNG, KLASSE, FLAECHE, AUSRICHTUNG, NEIGUNG, MSTRAHLUNG, GSTRAHLUNG, STROMERTRAG, WAERMEERTRAG, DUSCHGAENGE, DG_HEIZUNG, DG_WAERMEBEDARF, BEDARF_WARMWASSER, BEDARF_HEIZUNG, FLAECHE_KOLLEKTOREN, VOLUMEN_SPEICHER, GWR_EGID, Shape_Length, Shape_Area, XCOORD, YCOORD, Estim_build_area]\n",
"Index: []\n",
"\n",
"[0 rows x 31 columns]\n",
"Empty DataFrame\n",
"Columns: [Unnamed: 0, DF_UID, FLAECHE, NEIGUNG, AUSRICHTUNG, XCOORD, YCOORD, Shape_Length, Shape_Area, GWR_EGID, GBAUP, GKAT, GAREA, GASTW, GKODX, GKODY, Shape_Ratio, n_neighbors_100, Estim_build_area]\n",
"Index: []\n",
"Empty DataFrame\n",
"Columns: [DF_UID, panel_tilt, best_align, panel_count, panelled_area, panelled_area_ratio]\n",
"Index: []\n"
]
}
],
"source": [
"print(SON_cols)\n",
"print(roof_cols)\n",
"print(panel_cols)\n"
]
},
{
"cell_type": "code",
- "execution_count": 7,
+ "execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"SON_columns = ['DF_UID', 'SB_UUID', 'XCOORD', 'YCOORD', 'FLAECHE', 'NEIGUNG']\n",
"roof_columns = ['DF_UID', 'AUSRICHTUNG', 'GWR_EGID', 'GBAUP', 'GKAT', 'GAREA', 'GASTW', 'GKODX', 'GKODY', 'Shape_Ratio', 'n_neighbors_100']\n",
"panel_columns= ['DF_UID', 'panel_tilt', 'panelled_area_ratio']"
]
},
{
"cell_type": "code",
- "execution_count": 8,
+ "execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"SON_info = pd.read_csv( SON_fp, usecols = SON_columns )"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
"ROOF_info = pd.read_csv( roof_repl_fp, usecols = roof_columns )\n",
"ROOF_info = ROOF_info.drop_duplicates()"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [],
"source": [
"PANEL_info = pd.read_csv( panel_fitting_fp, usecols = panel_columns)"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [],
"source": [
"CORNER_info = pd.read_csv( corners_fp )"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [],
"source": [
"SHADE_info = pd.read_csv( shade_fp )"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"9639231\n",
"9639231\n",
"9639231\n",
"9639231\n",
"9639231\n"
]
}
],
"source": [
"print(len(SON_info))\n",
"print(len(ROOF_info))\n",
"print(len(PANEL_info))\n",
"print(len(CORNER_info))\n",
"print(len(SHADE_info))"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [],
"source": [
"ALL_info = SON_info.merge( ROOF_info, on = 'DF_UID', how = 'outer' )\n",
"ALL_info = ALL_info.merge( CORNER_info, on = 'DF_UID', how = 'outer' )\n",
"\n",
"ALL_info['panel_direction'] = ALL_info['AUSRICHTUNG'] + 180\n",
"\n",
"ALL_info = ALL_info.merge( PANEL_info, on = 'DF_UID', how = 'outer' )\n",
"ALL_info = ALL_info.merge( SHADE_info, on = 'DF_UID', how = 'outer' )\n",
"\n",
"ALL_info.rename(columns = {'panelled_area_ratio' : 'panelled_area_ratio_ftr'}, inplace = True)\n",
"ALL_info.rename(columns = {'fully_shaded_ratio' : 'shaded_area_ratio_ftr'}, inplace = True)"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
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" DF_UID SB_UUID FLAECHE NEIGUNG \\\n",
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" XCOORD YCOORD AUSRICHTUNG GWR_EGID GBAUP GKAT \\\n",
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"4 621692.928934 254250.448974 100.0 245033426.0 8011.0 1060.0 \n",
"\n",
" ... GASTW GKODX GKODY Shape_Ratio \\\n",
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" n_neighbors_100 n_corners panel_direction panel_tilt \\\n",
"0 2.0 4 190.0 37 \n",
"1 2.0 4 10.0 44 \n",
"2 2.0 4 100.0 12 \n",
"3 2.0 4 100.0 33 \n",
"4 2.0 4 280.0 35 \n",
"\n",
" panelled_area_ratio_ftr shaded_area_ratio_ftr \n",
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"[5 rows x 21 columns]"
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ALL_info.head()"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [
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" <td>1.0</td>\n",
" <td>624739.0</td>\n",
" <td>254230.0</td>\n",
" <td>0.109071</td>\n",
" <td>32.0</td>\n",
" <td>4</td>\n",
" <td>180.0</td>\n",
" <td>30</td>\n",
" <td>0.440950</td>\n",
" <td>0.002985</td>\n",
" </tr>\n",
" <tr>\n",
" <th>61</th>\n",
" <td>63</td>\n",
" <td>{F83A82E2-222B-4410-ADDE-93D16325A5FB}</td>\n",
" <td>5.166799</td>\n",
" <td>0</td>\n",
" <td>624863.365921</td>\n",
" <td>254237.320991</td>\n",
" <td>0.0</td>\n",
" <td>3032511.0</td>\n",
" <td>8017.0</td>\n",
" <td>1030.0</td>\n",
" <td>...</td>\n",
" <td>1.0</td>\n",
" <td>624870.0</td>\n",
" <td>254245.0</td>\n",
" <td>1.762661</td>\n",
" <td>21.0</td>\n",
" <td>4</td>\n",
" <td>180.0</td>\n",
" <td>30</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>62</th>\n",
" <td>64</td>\n",
" <td>{5E4F5D5B-6C9E-4A4F-BD83-40FF4F58350A}</td>\n",
" <td>38.989391</td>\n",
" <td>0</td>\n",
" <td>624853.582435</td>\n",
" <td>254244.803252</td>\n",
" <td>0.0</td>\n",
" <td>245054942.0</td>\n",
" <td>8017.0</td>\n",
" <td>1030.0</td>\n",
" <td>...</td>\n",
" <td>1.0</td>\n",
" <td>624854.0</td>\n",
" <td>254246.0</td>\n",
" <td>0.714579</td>\n",
" <td>22.0</td>\n",
" <td>6</td>\n",
" <td>180.0</td>\n",
" <td>30</td>\n",
" <td>0.213233</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>65</th>\n",
" <td>67</td>\n",
" <td>{48C1049B-A8BC-4F4F-B53A-F1B0F8299315}</td>\n",
" <td>1018.456320</td>\n",
" <td>0</td>\n",
" <td>624922.140087</td>\n",
" <td>254162.085863</td>\n",
" <td>0.0</td>\n",
" <td>245038324.0</td>\n",
" <td>8019.0</td>\n",
" <td>1040.0</td>\n",
" <td>...</td>\n",
" <td>2.0</td>\n",
" <td>624919.0</td>\n",
" <td>254163.0</td>\n",
" <td>0.148195</td>\n",
" <td>7.0</td>\n",
" <td>6</td>\n",
" <td>180.0</td>\n",
" <td>30</td>\n",
" <td>0.417683</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>66</th>\n",
" <td>68</td>\n",
" <td>{48C1049B-A8BC-4F4F-B53A-F1B0F8299315}</td>\n",
" <td>350.584181</td>\n",
" <td>0</td>\n",
" <td>624888.562638</td>\n",
" <td>254171.393540</td>\n",
" <td>0.0</td>\n",
" <td>245038324.0</td>\n",
" <td>8019.0</td>\n",
" <td>1040.0</td>\n",
" <td>...</td>\n",
" <td>2.0</td>\n",
" <td>624919.0</td>\n",
" <td>254163.0</td>\n",
" <td>0.227961</td>\n",
" <td>7.0</td>\n",
" <td>6</td>\n",
" <td>180.0</td>\n",
" <td>30</td>\n",
" <td>0.379428</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>67</th>\n",
" <td>69</td>\n",
" <td>{48C1049B-A8BC-4F4F-B53A-F1B0F8299315}</td>\n",
" <td>552.018229</td>\n",
" <td>0</td>\n",
" <td>624902.768127</td>\n",
" <td>254181.500254</td>\n",
" <td>0.0</td>\n",
" <td>245038324.0</td>\n",
" <td>8019.0</td>\n",
" <td>1040.0</td>\n",
" <td>...</td>\n",
" <td>2.0</td>\n",
" <td>624919.0</td>\n",
" <td>254163.0</td>\n",
" <td>0.305340</td>\n",
" <td>7.0</td>\n",
" <td>12</td>\n",
" <td>180.0</td>\n",
" <td>30</td>\n",
" <td>0.389071</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>74</th>\n",
" <td>76</td>\n",
" <td>{0EC9A383-F98C-43B6-BC5D-86F32AC3753B}</td>\n",
" <td>45.863031</td>\n",
" <td>0</td>\n",
" <td>624862.277386</td>\n",
" <td>254058.546342</td>\n",
" <td>0.0</td>\n",
" <td>3032005.0</td>\n",
" <td>8019.0</td>\n",
" <td>1060.0</td>\n",
" <td>...</td>\n",
" <td>1.0</td>\n",
" <td>624859.0</td>\n",
" <td>254062.0</td>\n",
" <td>0.590713</td>\n",
" <td>4.0</td>\n",
" <td>5</td>\n",
" <td>180.0</td>\n",
" <td>30</td>\n",
" <td>0.241701</td>\n",
" <td>0.083333</td>\n",
" </tr>\n",
" <tr>\n",
" <th>76</th>\n",
" <td>78</td>\n",
" <td>{0EC9A383-F98C-43B6-BC5D-86F32AC3753B}</td>\n",
" <td>73.968605</td>\n",
" <td>0</td>\n",
" <td>624855.911866</td>\n",
" <td>254063.758643</td>\n",
" <td>0.0</td>\n",
" <td>3032005.0</td>\n",
" <td>8019.0</td>\n",
" <td>1060.0</td>\n",
" <td>...</td>\n",
" <td>1.0</td>\n",
" <td>624859.0</td>\n",
" <td>254062.0</td>\n",
" <td>0.625616</td>\n",
" <td>4.0</td>\n",
" <td>5</td>\n",
" <td>180.0</td>\n",
" <td>30</td>\n",
" <td>0.280992</td>\n",
" <td>0.631579</td>\n",
" </tr>\n",
" <tr>\n",
" <th>80</th>\n",
" <td>82</td>\n",
" <td>{817D1FC4-6DF1-4F7F-8E46-C215E1B12EBA}</td>\n",
" <td>40.704476</td>\n",
" <td>0</td>\n",
" <td>624992.172735</td>\n",
" <td>254072.793140</td>\n",
" <td>0.0</td>\n",
" <td>245061375.0</td>\n",
" <td>8019.0</td>\n",
" <td>1060.0</td>\n",
" <td>...</td>\n",
" <td>1.0</td>\n",
" <td>624882.0</td>\n",
" <td>254083.0</td>\n",
" <td>0.627283</td>\n",
" <td>5.0</td>\n",
" <td>5</td>\n",
" <td>180.0</td>\n",
" <td>30</td>\n",
" <td>0.204249</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>86</th>\n",
" <td>88</td>\n",
" <td>{E85CC83D-D8CE-42A3-940B-0CAABD8B4D17}</td>\n",
" <td>51.579906</td>\n",
" <td>0</td>\n",
" <td>627780.974184</td>\n",
" <td>254002.644257</td>\n",
" <td>0.0</td>\n",
" <td>245000359.0</td>\n",
" <td>8015.0</td>\n",
" <td>1060.0</td>\n",
" <td>...</td>\n",
" <td>1.0</td>\n",
" <td>627783.0</td>\n",
" <td>254011.0</td>\n",
" <td>0.612906</td>\n",
" <td>3.0</td>\n",
" <td>8</td>\n",
" <td>180.0</td>\n",
" <td>30</td>\n",
" <td>0.402959</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>101</th>\n",
" <td>105</td>\n",
" <td>{572C2E66-8D48-4A99-839A-08723755F8B0}</td>\n",
" <td>23.291964</td>\n",
" <td>0</td>\n",
" <td>628063.176823</td>\n",
" <td>254003.110151</td>\n",
" <td>0.0</td>\n",
" <td>430920.0</td>\n",
" <td>8011.0</td>\n",
" <td>1021.0</td>\n",
" <td>...</td>\n",
" <td>2.0</td>\n",
" <td>628069.0</td>\n",
" <td>254004.0</td>\n",
" <td>0.908534</td>\n",
" <td>23.0</td>\n",
" <td>4</td>\n",
" <td>180.0</td>\n",
" <td>30</td>\n",
" <td>0.237960</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>120</th>\n",
" <td>124</td>\n",
" <td>{F47F8780-D09E-48C1-8386-00D7F98BFEB7}</td>\n",
" <td>29.551728</td>\n",
" <td>0</td>\n",
" <td>628107.812190</td>\n",
" <td>254155.949988</td>\n",
" <td>0.0</td>\n",
" <td>430883.0</td>\n",
" <td>8011.0</td>\n",
" <td>1030.0</td>\n",
" <td>...</td>\n",
" <td>4.0</td>\n",
" <td>628113.0</td>\n",
" <td>254145.0</td>\n",
" <td>0.745832</td>\n",
" <td>33.0</td>\n",
" <td>5</td>\n",
" <td>180.0</td>\n",
" <td>30</td>\n",
" <td>0.140666</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>121</th>\n",
" <td>125</td>\n",
" <td>{45D9BF4B-789E-43F1-B75F-FBB96A0CF33B}</td>\n",
" <td>64.430985</td>\n",
" <td>0</td>\n",
" <td>628065.143850</td>\n",
" <td>254236.140115</td>\n",
" <td>0.0</td>\n",
" <td>430777.0</td>\n",
" <td>8011.0</td>\n",
" <td>1025.0</td>\n",
" <td>...</td>\n",
" <td>3.0</td>\n",
" <td>628075.0</td>\n",
" <td>254230.0</td>\n",
" <td>0.554923</td>\n",
" <td>30.0</td>\n",
" <td>6</td>\n",
" <td>180.0</td>\n",
" <td>30</td>\n",
" <td>0.258070</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>165</th>\n",
" <td>169</td>\n",
" <td>{D8C149BD-4BFE-4E9F-87FC-B84B981B22BD}</td>\n",
" <td>40.901631</td>\n",
" <td>0</td>\n",
" <td>628154.918666</td>\n",
" <td>254198.096885</td>\n",
" <td>0.0</td>\n",
" <td>245048324.0</td>\n",
" <td>8020.0</td>\n",
" <td>1021.0</td>\n",
" <td>...</td>\n",
" <td>2.0</td>\n",
" <td>628154.0</td>\n",
" <td>254203.0</td>\n",
" <td>0.829660</td>\n",
" <td>27.0</td>\n",
" <td>10</td>\n",
" <td>180.0</td>\n",
" <td>30</td>\n",
" <td>0.135510</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>214</th>\n",
" <td>219</td>\n",
" <td>{BBFA2A04-84C2-44E0-891C-22FA14A034AD}</td>\n",
" <td>49.654829</td>\n",
" <td>0</td>\n",
" <td>628062.649378</td>\n",
" <td>254053.465941</td>\n",
" <td>0.0</td>\n",
" <td>430898.0</td>\n",
" <td>8011.0</td>\n",
" <td>1025.0</td>\n",
" <td>...</td>\n",
" <td>4.0</td>\n",
" <td>628058.0</td>\n",
" <td>254043.0</td>\n",
" <td>0.607512</td>\n",
" <td>24.0</td>\n",
" <td>6</td>\n",
" <td>180.0</td>\n",
" <td>30</td>\n",
" <td>0.195338</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>215</th>\n",
" <td>220</td>\n",
" <td>{BBFA2A04-84C2-44E0-891C-22FA14A034AD}</td>\n",
" <td>30.840837</td>\n",
" <td>0</td>\n",
" <td>628062.608542</td>\n",
" <td>254048.045143</td>\n",
" <td>0.0</td>\n",
" <td>430898.0</td>\n",
" <td>8011.0</td>\n",
" <td>1025.0</td>\n",
" <td>...</td>\n",
" <td>4.0</td>\n",
" <td>628058.0</td>\n",
" <td>254043.0</td>\n",
" <td>0.962769</td>\n",
" <td>24.0</td>\n",
" <td>6</td>\n",
" <td>180.0</td>\n",
" <td>30</td>\n",
" <td>0.044929</td>\n",
" <td>0.142857</td>\n",
" </tr>\n",
" <tr>\n",
" <th>219</th>\n",
" <td>224</td>\n",
" <td>{6EB94ACE-BD99-460E-9DA3-387F17A02F88}</td>\n",
" <td>18.906543</td>\n",
" <td>0</td>\n",
" <td>628051.410827</td>\n",
" <td>254049.777477</td>\n",
" <td>0.0</td>\n",
" <td>430898.0</td>\n",
" <td>8011.0</td>\n",
" <td>1025.0</td>\n",
" <td>...</td>\n",
" <td>4.0</td>\n",
" <td>628058.0</td>\n",
" <td>254043.0</td>\n",
" <td>1.658057</td>\n",
" <td>24.0</td>\n",
" <td>4</td>\n",
" <td>180.0</td>\n",
" <td>30</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>220</th>\n",
" <td>225</td>\n",
" <td>{49C3BAA3-2267-469D-B9C4-C1B281C1FB9E}</td>\n",
" <td>7.881839</td>\n",
" <td>0</td>\n",
" <td>628198.521851</td>\n",
" <td>254067.427156</td>\n",
" <td>0.0</td>\n",
" <td>3030172.0</td>\n",
" <td>8019.0</td>\n",
" <td>1021.0</td>\n",
" <td>...</td>\n",
" <td>3.0</td>\n",
" <td>628194.0</td>\n",
" <td>254062.0</td>\n",
" <td>1.436468</td>\n",
" <td>40.0</td>\n",
" <td>4</td>\n",
" <td>180.0</td>\n",
" <td>30</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>227</th>\n",
" <td>233</td>\n",
" <td>{F59652BD-3ACE-45B1-9FBD-F2F98054770D}</td>\n",
" <td>20.499503</td>\n",
" <td>0</td>\n",
" <td>628223.898944</td>\n",
" <td>254051.908896</td>\n",
" <td>0.0</td>\n",
" <td>430925.0</td>\n",
" <td>8011.0</td>\n",
" <td>1025.0</td>\n",
" <td>...</td>\n",
" <td>2.0</td>\n",
" <td>628216.0</td>\n",
" <td>254049.0</td>\n",
" <td>0.901785</td>\n",
" <td>38.0</td>\n",
" <td>4</td>\n",
" <td>180.0</td>\n",
" <td>30</td>\n",
" <td>0.135188</td>\n",
" <td>0.200000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>311</th>\n",
" <td>330</td>\n",
" <td>{1DB7FF99-FB26-4FA6-85AC-E17E8CF77F92}</td>\n",
" <td>33.958161</td>\n",
" <td>0</td>\n",
" <td>628210.343499</td>\n",
" <td>254193.683539</td>\n",
" <td>0.0</td>\n",
" <td>3032289.0</td>\n",
" <td>8019.0</td>\n",
" <td>1021.0</td>\n",
" <td>...</td>\n",
" <td>2.0</td>\n",
" <td>628203.0</td>\n",
" <td>254195.0</td>\n",
" <td>0.697815</td>\n",
" <td>30.0</td>\n",
" <td>4</td>\n",
" <td>180.0</td>\n",
" <td>30</td>\n",
" <td>0.204022</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>322</th>\n",
" <td>341</td>\n",
" <td>{7E26B49D-CE7A-4A50-AF60-05A80718E36F}</td>\n",
" <td>756.108672</td>\n",
" <td>0</td>\n",
" <td>627999.258940</td>\n",
" <td>254034.056541</td>\n",
" <td>0.0</td>\n",
" <td>2360253.0</td>\n",
" <td>8015.0</td>\n",
" <td>1060.0</td>\n",
" <td>...</td>\n",
" <td>1.0</td>\n",
" <td>628025.0</td>\n",
" <td>254034.0</td>\n",
" <td>0.169583</td>\n",
" <td>16.0</td>\n",
" <td>9</td>\n",
" <td>180.0</td>\n",
" <td>30</td>\n",
" <td>0.426995</td>\n",
" <td>0.015789</td>\n",
" </tr>\n",
" <tr>\n",
" <th>353</th>\n",
" <td>372</td>\n",
" <td>{5939F926-C517-4FBC-8BDF-E5FA63394885}</td>\n",
" <td>9.286116</td>\n",
" <td>0</td>\n",
" <td>628191.864031</td>\n",
" <td>254182.508210</td>\n",
" <td>0.0</td>\n",
" <td>245000420.0</td>\n",
" <td>8019.0</td>\n",
" <td>1060.0</td>\n",
" <td>...</td>\n",
" <td>1.0</td>\n",
" <td>628185.0</td>\n",
" <td>254180.0</td>\n",
" <td>1.328678</td>\n",
" <td>32.0</td>\n",
" <td>4</td>\n",
" <td>180.0</td>\n",
" <td>30</td>\n",
" <td>0.298433</td>\n",
" <td>0.500000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>370</th>\n",
" <td>389</td>\n",
" <td>{C028D467-CFD3-4F7C-9C4D-7EDA7ACE2CED}</td>\n",
" <td>47.997201</td>\n",
" <td>0</td>\n",
" <td>628195.891187</td>\n",
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" <td>245058420.0</td>\n",
" <td>8011.0</td>\n",
" <td>1060.0</td>\n",
" <td>...</td>\n",
" <td>1.0</td>\n",
" <td>628196.0</td>\n",
" <td>254146.0</td>\n",
" <td>0.580531</td>\n",
" <td>41.0</td>\n",
" <td>4</td>\n",
" <td>180.0</td>\n",
" <td>30</td>\n",
" <td>0.230954</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>400</th>\n",
" <td>420</td>\n",
" <td>{4E485D48-299E-4328-992B-AF64F98FD330}</td>\n",
" <td>31.183380</td>\n",
" <td>0</td>\n",
" <td>628127.978124</td>\n",
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" <td>430882.0</td>\n",
" <td>8013.0</td>\n",
" <td>1030.0</td>\n",
" <td>...</td>\n",
" <td>4.0</td>\n",
" <td>628125.0</td>\n",
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" </tr>\n",
" <tr>\n",
" <th>9639196</th>\n",
" <td>9889989</td>\n",
" <td>{A3CE165E-3A96-4E34-83BF-68B6CE064E3F}</td>\n",
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" <td>8020.0</td>\n",
" <td>1025.0</td>\n",
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" <td>1.636984</td>\n",
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" <td>180.0</td>\n",
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" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9639197</th>\n",
" <td>9889990</td>\n",
" <td>{0D9CEFCD-902E-41C5-AC42-274C2E3EAE53}</td>\n",
" <td>52.048368</td>\n",
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" <td>0.675452</td>\n",
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" </tr>\n",
" <tr>\n",
" <th>9639198</th>\n",
" <td>9889991</td>\n",
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" </tr>\n",
" <tr>\n",
" <th>9639199</th>\n",
" <td>9889992</td>\n",
" <td>{5EF4AE5E-5A04-43E0-B4E3-D7A6E054CA53}</td>\n",
" <td>80.279603</td>\n",
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" </tr>\n",
" <tr>\n",
" <th>9639200</th>\n",
" <td>9889993</td>\n",
" <td>{8E30AE19-B684-4897-941F-D2B511881621}</td>\n",
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" <tr>\n",
" <th>9639201</th>\n",
" <td>9889994</td>\n",
" <td>{97CD100C-C434-4C03-A3F7-D3F9524AE1E5}</td>\n",
" <td>10.427635</td>\n",
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" </tr>\n",
" <tr>\n",
" <th>9639202</th>\n",
" <td>9889995</td>\n",
" <td>{02024B9E-B05E-4355-BA84-AF3BB85176FB}</td>\n",
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" </tr>\n",
" <tr>\n",
" <th>9639203</th>\n",
" <td>9889996</td>\n",
" <td>{02024B9E-B05E-4355-BA84-AF3BB85176FB}</td>\n",
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" </tr>\n",
" <tr>\n",
" <th>9639209</th>\n",
" <td>9890002</td>\n",
" <td>{C0FD62CF-FA6E-4CB0-AB96-17D725631DDA}</td>\n",
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" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>1154667 rows × 21 columns</p>\n",
"</div>"
],
"text/plain": [
" DF_UID SB_UUID FLAECHE \\\n",
"31 33 {0E182AE6-B2B7-4CF8-AB37-940E0310D6CB} 27.568645 \n",
"48 50 {AF2290C1-3867-4575-B160-54F495756DC7} 681.609660 \n",
"49 51 {AF2290C1-3867-4575-B160-54F495756DC7} 609.169499 \n",
"50 52 {AF2290C1-3867-4575-B160-54F495756DC7} 1523.273993 \n",
"51 53 {AF2290C1-3867-4575-B160-54F495756DC7} 1332.294940 \n",
"52 54 {AF2290C1-3867-4575-B160-54F495756DC7} 1344.947851 \n",
"61 63 {F83A82E2-222B-4410-ADDE-93D16325A5FB} 5.166799 \n",
"62 64 {5E4F5D5B-6C9E-4A4F-BD83-40FF4F58350A} 38.989391 \n",
"65 67 {48C1049B-A8BC-4F4F-B53A-F1B0F8299315} 1018.456320 \n",
"66 68 {48C1049B-A8BC-4F4F-B53A-F1B0F8299315} 350.584181 \n",
"67 69 {48C1049B-A8BC-4F4F-B53A-F1B0F8299315} 552.018229 \n",
"74 76 {0EC9A383-F98C-43B6-BC5D-86F32AC3753B} 45.863031 \n",
"76 78 {0EC9A383-F98C-43B6-BC5D-86F32AC3753B} 73.968605 \n",
"80 82 {817D1FC4-6DF1-4F7F-8E46-C215E1B12EBA} 40.704476 \n",
"86 88 {E85CC83D-D8CE-42A3-940B-0CAABD8B4D17} 51.579906 \n",
"101 105 {572C2E66-8D48-4A99-839A-08723755F8B0} 23.291964 \n",
"120 124 {F47F8780-D09E-48C1-8386-00D7F98BFEB7} 29.551728 \n",
"121 125 {45D9BF4B-789E-43F1-B75F-FBB96A0CF33B} 64.430985 \n",
"165 169 {D8C149BD-4BFE-4E9F-87FC-B84B981B22BD} 40.901631 \n",
"214 219 {BBFA2A04-84C2-44E0-891C-22FA14A034AD} 49.654829 \n",
"215 220 {BBFA2A04-84C2-44E0-891C-22FA14A034AD} 30.840837 \n",
"219 224 {6EB94ACE-BD99-460E-9DA3-387F17A02F88} 18.906543 \n",
"220 225 {49C3BAA3-2267-469D-B9C4-C1B281C1FB9E} 7.881839 \n",
"227 233 {F59652BD-3ACE-45B1-9FBD-F2F98054770D} 20.499503 \n",
"311 330 {1DB7FF99-FB26-4FA6-85AC-E17E8CF77F92} 33.958161 \n",
"322 341 {7E26B49D-CE7A-4A50-AF60-05A80718E36F} 756.108672 \n",
"353 372 {5939F926-C517-4FBC-8BDF-E5FA63394885} 9.286116 \n",
"370 389 {C028D467-CFD3-4F7C-9C4D-7EDA7ACE2CED} 47.997201 \n",
"400 420 {4E485D48-299E-4328-992B-AF64F98FD330} 31.183380 \n",
"407 427 {D6952202-76B8-4ED7-B4A0-1C234C112601} 27.367197 \n",
"... ... ... ... \n",
"9639142 9889935 {4F9E976D-6F54-4A63-BAC0-C74805EB357A} 7.200696 \n",
"9639147 9889940 {7A47B46F-8CF9-47AB-B9F4-AAED05777DDC} 5.602632 \n",
"9639153 9889946 {7A47B46F-8CF9-47AB-B9F4-AAED05777DDC} 12.430050 \n",
"9639154 9889947 {7A47B46F-8CF9-47AB-B9F4-AAED05777DDC} 20.471845 \n",
"9639155 9889948 {7A47B46F-8CF9-47AB-B9F4-AAED05777DDC} 87.567810 \n",
"9639156 9889949 {7A47B46F-8CF9-47AB-B9F4-AAED05777DDC} 18.711647 \n",
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"9639160 9889953 {33218C41-FD05-4129-84BF-35F9AE4B8DEA} 17.937427 \n",
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"9639179 9889972 {AF5709F5-8DEB-4753-83EA-2C3BDD43656D} 27.149089 \n",
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"9639183 9889976 {85E23C32-C62C-4516-803D-6B8B45A9D376} 121.889368 \n",
"9639184 9889977 {85E23C32-C62C-4516-803D-6B8B45A9D376} 100.298458 \n",
"9639190 9889983 {D97438F4-4398-4E10-8542-284DE0BB211E} 192.593823 \n",
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"9639195 9889988 {A3CE165E-3A96-4E34-83BF-68B6CE064E3F} 168.922592 \n",
"9639196 9889989 {A3CE165E-3A96-4E34-83BF-68B6CE064E3F} 5.973544 \n",
"9639197 9889990 {0D9CEFCD-902E-41C5-AC42-274C2E3EAE53} 52.048368 \n",
"9639198 9889991 {0D9CEFCD-902E-41C5-AC42-274C2E3EAE53} 39.066331 \n",
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"9639200 9889993 {8E30AE19-B684-4897-941F-D2B511881621} 31.399356 \n",
"9639201 9889994 {97CD100C-C434-4C03-A3F7-D3F9524AE1E5} 10.427635 \n",
"9639202 9889995 {02024B9E-B05E-4355-BA84-AF3BB85176FB} 7.403436 \n",
"9639203 9889996 {02024B9E-B05E-4355-BA84-AF3BB85176FB} 92.962710 \n",
"9639209 9890002 {C0FD62CF-FA6E-4CB0-AB96-17D725631DDA} 11.937935 \n",
"\n",
" NEIGUNG XCOORD YCOORD AUSRICHTUNG GWR_EGID \\\n",
"31 0 622443.648193 254088.496398 0.0 245049569.0 \n",
"48 0 624744.786885 254213.178640 0.0 2361838.0 \n",
"49 0 624700.866428 254270.417857 0.0 2361838.0 \n",
"50 0 624749.048656 254246.125799 0.0 2361838.0 \n",
"51 0 624768.067357 254198.593359 0.0 2361838.0 \n",
"52 0 624721.337023 254227.820131 0.0 2361838.0 \n",
"61 0 624863.365921 254237.320991 0.0 3032511.0 \n",
"62 0 624853.582435 254244.803252 0.0 245054942.0 \n",
"65 0 624922.140087 254162.085863 0.0 245038324.0 \n",
"66 0 624888.562638 254171.393540 0.0 245038324.0 \n",
"67 0 624902.768127 254181.500254 0.0 245038324.0 \n",
"74 0 624862.277386 254058.546342 0.0 3032005.0 \n",
"76 0 624855.911866 254063.758643 0.0 3032005.0 \n",
"80 0 624992.172735 254072.793140 0.0 245061375.0 \n",
"86 0 627780.974184 254002.644257 0.0 245000359.0 \n",
"101 0 628063.176823 254003.110151 0.0 430920.0 \n",
"120 0 628107.812190 254155.949988 0.0 430883.0 \n",
"121 0 628065.143850 254236.140115 0.0 430777.0 \n",
"165 0 628154.918666 254198.096885 0.0 245048324.0 \n",
"214 0 628062.649378 254053.465941 0.0 430898.0 \n",
"215 0 628062.608542 254048.045143 0.0 430898.0 \n",
"219 0 628051.410827 254049.777477 0.0 430898.0 \n",
"220 0 628198.521851 254067.427156 0.0 3030172.0 \n",
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"311 0 628210.343499 254193.683539 0.0 3032289.0 \n",
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"400 0 628127.978124 254128.071967 0.0 430882.0 \n",
"407 0 628021.042452 254209.020314 0.0 3030625.0 \n",
"... ... ... ... ... ... \n",
"9639142 0 683599.242494 253872.453865 0.0 302019393.0 \n",
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"9639161 0 683578.111644 253809.392928 0.0 302019398.0 \n",
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"9639163 0 683537.915617 253910.151911 0.0 302019389.0 \n",
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"9639183 0 683618.091902 253869.268816 0.0 302024764.0 \n",
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"9639190 0 683489.524819 253849.389781 0.0 302019384.0 \n",
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"9639203 0 683795.366549 253951.987280 0.0 302017881.0 \n",
"9639209 0 684219.249721 253840.300209 0.0 302021503.0 \n",
"\n",
" GBAUP GKAT ... GASTW GKODX GKODY \\\n",
"31 8011.0 1060.0 ... 1.0 622443.0 254084.0 \n",
"48 8018.0 1060.0 ... 1.0 624739.0 254230.0 \n",
"49 8018.0 1060.0 ... 1.0 624739.0 254230.0 \n",
"50 8018.0 1060.0 ... 1.0 624739.0 254230.0 \n",
"51 8018.0 1060.0 ... 1.0 624739.0 254230.0 \n",
"52 8018.0 1060.0 ... 1.0 624739.0 254230.0 \n",
"61 8017.0 1030.0 ... 1.0 624870.0 254245.0 \n",
"62 8017.0 1030.0 ... 1.0 624854.0 254246.0 \n",
"65 8019.0 1040.0 ... 2.0 624919.0 254163.0 \n",
"66 8019.0 1040.0 ... 2.0 624919.0 254163.0 \n",
"67 8019.0 1040.0 ... 2.0 624919.0 254163.0 \n",
"74 8019.0 1060.0 ... 1.0 624859.0 254062.0 \n",
"76 8019.0 1060.0 ... 1.0 624859.0 254062.0 \n",
"80 8019.0 1060.0 ... 1.0 624882.0 254083.0 \n",
"86 8015.0 1060.0 ... 1.0 627783.0 254011.0 \n",
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"120 8011.0 1030.0 ... 4.0 628113.0 254145.0 \n",
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"227 8011.0 1025.0 ... 2.0 628216.0 254049.0 \n",
"311 8019.0 1021.0 ... 2.0 628203.0 254195.0 \n",
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"400 8013.0 1030.0 ... 4.0 628125.0 254120.0 \n",
"407 8019.0 1025.0 ... 3.0 628012.0 254211.0 \n",
"... ... ... ... ... ... ... \n",
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"9639198 8020.0 1060.0 ... 1.0 683551.0 253861.0 \n",
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"9639201 8020.0 1060.0 ... 1.0 683807.0 253950.0 \n",
"9639202 8018.0 1060.0 ... 1.0 683795.0 253952.0 \n",
"9639203 8018.0 1060.0 ... 1.0 683795.0 253952.0 \n",
"9639209 8020.0 1060.0 ... 1.0 684219.0 253841.0 \n",
"\n",
" Shape_Ratio n_neighbors_100 n_corners panel_direction panel_tilt \\\n",
"31 0.762308 2.0 4 180.0 30 \n",
"48 0.162401 32.0 5 180.0 30 \n",
"49 0.188920 32.0 4 180.0 30 \n",
"50 0.115776 32.0 8 180.0 30 \n",
"51 0.109587 32.0 4 180.0 30 \n",
"52 0.109071 32.0 4 180.0 30 \n",
"61 1.762661 21.0 4 180.0 30 \n",
"62 0.714579 22.0 6 180.0 30 \n",
"65 0.148195 7.0 6 180.0 30 \n",
"66 0.227961 7.0 6 180.0 30 \n",
"67 0.305340 7.0 12 180.0 30 \n",
"74 0.590713 4.0 5 180.0 30 \n",
"76 0.625616 4.0 5 180.0 30 \n",
"80 0.627283 5.0 5 180.0 30 \n",
"86 0.612906 3.0 8 180.0 30 \n",
"101 0.908534 23.0 4 180.0 30 \n",
"120 0.745832 33.0 5 180.0 30 \n",
"121 0.554923 30.0 6 180.0 30 \n",
"165 0.829660 27.0 10 180.0 30 \n",
"214 0.607512 24.0 6 180.0 30 \n",
"215 0.962769 24.0 6 180.0 30 \n",
"219 1.658057 24.0 4 180.0 30 \n",
"220 1.436468 40.0 4 180.0 30 \n",
"227 0.901785 38.0 4 180.0 30 \n",
"311 0.697815 30.0 4 180.0 30 \n",
"322 0.169583 16.0 9 180.0 30 \n",
"353 1.328678 32.0 4 180.0 30 \n",
"370 0.580531 41.0 4 180.0 30 \n",
"400 0.716537 37.0 4 180.0 30 \n",
"407 0.879711 22.0 8 180.0 30 \n",
"... ... ... ... ... ... \n",
"9639142 1.491464 31.0 4 180.0 30 \n",
"9639147 1.690676 44.0 4 180.0 30 \n",
"9639153 3.006134 44.0 4 180.0 30 \n",
"9639154 1.868956 44.0 4 180.0 30 \n",
"9639155 0.945541 44.0 20 180.0 30 \n",
"9639156 2.034357 44.0 4 180.0 30 \n",
"9639157 2.487412 44.0 4 180.0 30 \n",
"9639158 1.409381 44.0 5 180.0 30 \n",
"9639159 0.808241 42.0 4 180.0 30 \n",
"9639160 1.080589 42.0 4 180.0 30 \n",
"9639161 0.229966 36.0 10 180.0 30 \n",
"9639162 1.649121 36.0 4 180.0 30 \n",
"9639163 1.623570 45.0 4 180.0 30 \n",
"9639168 1.568140 45.0 32 180.0 30 \n",
"9639179 0.808250 43.0 4 180.0 30 \n",
"9639180 1.080241 43.0 4 180.0 30 \n",
"9639183 0.621486 25.0 4 180.0 30 \n",
"9639184 0.768329 25.0 6 180.0 30 \n",
"9639190 1.438593 39.0 28 180.0 30 \n",
"9639194 1.690676 39.0 4 180.0 30 \n",
"9639195 0.377257 43.0 4 180.0 30 \n",
"9639196 1.636984 43.0 4 180.0 30 \n",
"9639197 0.675452 43.0 4 180.0 30 \n",
"9639198 0.889210 43.0 6 180.0 30 \n",
"9639199 0.746306 24.0 4 180.0 30 \n",
"9639200 0.746209 20.0 6 180.0 30 \n",
"9639201 1.256860 1.0 4 180.0 30 \n",
"9639202 1.470500 1.0 5 180.0 30 \n",
"9639203 0.508800 1.0 8 180.0 30 \n",
"9639209 1.224940 10.0 4 180.0 30 \n",
"\n",
" panelled_area_ratio_ftr shaded_area_ratio_ftr \n",
"31 0.402092 0.000000 \n",
"48 0.412678 0.000000 \n",
"49 0.402611 0.052288 \n",
"50 0.437540 0.005249 \n",
"51 0.440977 0.000000 \n",
"52 0.440950 0.002985 \n",
"61 0.000000 0.000000 \n",
"62 0.213233 0.000000 \n",
"65 0.417683 0.000000 \n",
"66 0.379428 0.000000 \n",
"67 0.389071 0.000000 \n",
"74 0.241701 0.083333 \n",
"76 0.280992 0.631579 \n",
"80 0.204249 0.000000 \n",
"86 0.402959 0.000000 \n",
"101 0.237960 0.000000 \n",
"120 0.140666 0.000000 \n",
"121 0.258070 0.000000 \n",
"165 0.135510 0.000000 \n",
"214 0.195338 0.000000 \n",
"215 0.044929 0.142857 \n",
"219 0.000000 0.000000 \n",
"220 0.000000 0.000000 \n",
"227 0.135188 0.200000 \n",
"311 0.204022 0.000000 \n",
"322 0.426995 0.015789 \n",
"353 0.298433 0.500000 \n",
"370 0.230954 0.000000 \n",
"400 0.177741 0.571429 \n",
"407 0.101263 0.000000 \n",
"... ... ... \n",
"9639142 0.000000 0.000000 \n",
"9639147 0.000000 0.000000 \n",
"9639153 0.000000 0.333333 \n",
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"9639158 0.000000 0.000000 \n",
"9639159 0.102085 0.000000 \n",
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"9639161 0.393961 0.000000 \n",
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"9639163 0.000000 0.000000 \n",
"9639168 0.030630 0.026667 \n",
"9639179 0.102076 0.000000 \n",
"9639180 0.077202 0.000000 \n",
"9639183 0.215992 0.000000 \n",
"9639184 0.124337 0.000000 \n",
"9639190 0.079141 0.042553 \n",
"9639194 0.000000 0.000000 \n",
"9639195 0.328113 0.045455 \n",
"9639196 0.000000 0.000000 \n",
"9639197 0.159733 0.000000 \n",
"9639198 0.106407 0.000000 \n",
"9639199 0.138081 0.050000 \n",
"9639200 0.176518 0.000000 \n",
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"9639203 0.268296 0.041667 \n",
"9639209 0.000000 0.000000 \n",
"\n",
"[1154667 rows x 21 columns]"
]
},
"execution_count": 16,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ALL_info[ALL_info.NEIGUNG == 0]"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"9639231"
]
},
"execution_count": 18,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(ALL_info.dropna())"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [],
"source": [
"ALL_info.to_csv( output_fp, index = False )"
]
},
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Spielwiese"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "ROOFS_FP = '/work/hyenergy/output/solar_potential/geographic_potential/CH_ROOFS_all_replaced.csv'\n",
+ "roofs = pd.read_csv( ROOFS_FP )"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "SON_columns = ['DF_UID', 'Shape_Length']\n",
+ "SON_info = pd.read_csv( SON_fp, usecols = SON_columns )"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 9,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "9639231\n",
+ "9639231\n"
+ ]
+ }
+ ],
+ "source": [
+ "print( len(roofs) )\n",
+ "print( len(SON_info) )"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 10,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "roofs = roofs.set_index('DF_UID')\n",
+ "SON_info = SON_info.set_index('DF_UID')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 13,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "roofs['Shape_Length'] = SON_info.Shape_Length"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 14,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "<div>\n",
+ "<style scoped>\n",
+ " .dataframe tbody tr th:only-of-type {\n",
+ " vertical-align: middle;\n",
+ " }\n",
+ "\n",
+ " .dataframe tbody tr th {\n",
+ " vertical-align: top;\n",
+ " }\n",
+ "\n",
+ " .dataframe thead th {\n",
+ " text-align: right;\n",
+ " }\n",
+ "</style>\n",
+ "<table border=\"1\" class=\"dataframe\">\n",
+ " <thead>\n",
+ " <tr style=\"text-align: right;\">\n",
+ " <th></th>\n",
+ " <th>SB_UUID</th>\n",
+ " <th>FLAECHE</th>\n",
+ " <th>NEIGUNG</th>\n",
+ " <th>XCOORD</th>\n",
+ " <th>YCOORD</th>\n",
+ " <th>AUSRICHTUNG</th>\n",
+ " <th>GWR_EGID</th>\n",
+ " <th>GBAUP</th>\n",
+ " <th>GKAT</th>\n",
+ " <th>GAREA</th>\n",
+ " <th>...</th>\n",
+ " <th>GKODX</th>\n",
+ " <th>GKODY</th>\n",
+ " <th>Shape_Ratio</th>\n",
+ " <th>n_neighbors_100</th>\n",
+ " <th>n_corners</th>\n",
+ " <th>panel_direction</th>\n",
+ " <th>panel_tilt</th>\n",
+ " <th>panelled_area_ratio_ftr</th>\n",
+ " <th>shaded_area_ratio_ftr</th>\n",
+ " <th>Shape_Length</th>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>DF_UID</th>\n",
+ " <th></th>\n",
+ " <th></th>\n",
+ " <th></th>\n",
+ " <th></th>\n",
+ " <th></th>\n",
+ " <th></th>\n",
+ " <th></th>\n",
+ " <th></th>\n",
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+ " <th></th>\n",
+ " <th></th>\n",
+ " <th></th>\n",
+ " <th></th>\n",
+ " <th></th>\n",
+ " <th></th>\n",
+ " <th></th>\n",
+ " <th></th>\n",
+ " <th></th>\n",
+ " <th></th>\n",
+ " <th></th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " <tr>\n",
+ " <th>1</th>\n",
+ " <td>{DEA19230-2728-42BF-8A28-573F5EB6C214}</td>\n",
+ " <td>15.948816</td>\n",
+ " <td>37</td>\n",
+ " <td>621674.951286</td>\n",
+ " <td>254203.972784</td>\n",
+ " <td>10.0</td>\n",
+ " <td>245033426.0</td>\n",
+ " <td>8011.0</td>\n",
+ " <td>1060.0</td>\n",
+ " <td>889.0</td>\n",
+ " <td>...</td>\n",
+ " <td>621682.0</td>\n",
+ " <td>254206.0</td>\n",
+ " <td>1.050710</td>\n",
+ " <td>2.0</td>\n",
+ " <td>4</td>\n",
+ " <td>190.0</td>\n",
+ " <td>37</td>\n",
+ " <td>0.300963</td>\n",
+ " <td>0.000000</td>\n",
+ " <td>16.757573</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>2</th>\n",
+ " <td>{DEA19230-2728-42BF-8A28-573F5EB6C214}</td>\n",
+ " <td>13.730555</td>\n",
+ " <td>44</td>\n",
+ " <td>621675.374179</td>\n",
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+ " <td>245033426.0</td>\n",
+ " <td>8011.0</td>\n",
+ " <td>1060.0</td>\n",
+ " <td>889.0</td>\n",
+ " <td>...</td>\n",
+ " <td>621682.0</td>\n",
+ " <td>254206.0</td>\n",
+ " <td>1.132856</td>\n",
+ " <td>2.0</td>\n",
+ " <td>4</td>\n",
+ " <td>10.0</td>\n",
+ " <td>44</td>\n",
+ " <td>0.000000</td>\n",
+ " <td>0.000000</td>\n",
+ " <td>15.554747</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>3</th>\n",
+ " <td>{62E12FA3-D6C9-482C-A74C-CDCCE3D32EDD}</td>\n",
+ " <td>63.437476</td>\n",
+ " <td>12</td>\n",
+ " <td>621673.977050</td>\n",
+ " <td>254186.956803</td>\n",
+ " <td>-80.0</td>\n",
+ " <td>245033426.0</td>\n",
+ " <td>8011.0</td>\n",
+ " <td>1060.0</td>\n",
+ " <td>889.0</td>\n",
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+ " <td>254206.0</td>\n",
+ " <td>0.497312</td>\n",
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+ " <td>4</td>\n",
+ " <td>100.0</td>\n",
+ " <td>12</td>\n",
+ " <td>0.706207</td>\n",
+ " <td>0.000000</td>\n",
+ " <td>31.548229</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>4</th>\n",
+ " <td>{99786E44-FF96-4250-A0A2-AF44CB189B28}</td>\n",
+ " <td>38.368910</td>\n",
+ " <td>33</td>\n",
+ " <td>621696.695450</td>\n",
+ " <td>254249.767806</td>\n",
+ " <td>-80.0</td>\n",
+ " <td>245033426.0</td>\n",
+ " <td>8011.0</td>\n",
+ " <td>1060.0</td>\n",
+ " <td>889.0</td>\n",
+ " <td>...</td>\n",
+ " <td>621682.0</td>\n",
+ " <td>254206.0</td>\n",
+ " <td>0.629591</td>\n",
+ " <td>2.0</td>\n",
+ " <td>4</td>\n",
+ " <td>100.0</td>\n",
+ " <td>33</td>\n",
+ " <td>0.583806</td>\n",
+ " <td>0.000000</td>\n",
+ " <td>24.156709</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>5</th>\n",
+ " <td>{99786E44-FF96-4250-A0A2-AF44CB189B28}</td>\n",
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+ " <td>35</td>\n",
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+ " <td>2.0</td>\n",
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+ " <td>35</td>\n",
+ " <td>0.615329</td>\n",
+ " <td>0.285714</td>\n",
+ " <td>23.575579</td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ "</table>\n",
+ "<p>5 rows × 21 columns</p>\n",
+ "</div>"
+ ],
+ "text/plain": [
+ " SB_UUID FLAECHE NEIGUNG \\\n",
+ "DF_UID \n",
+ "1 {DEA19230-2728-42BF-8A28-573F5EB6C214} 15.948816 37 \n",
+ "2 {DEA19230-2728-42BF-8A28-573F5EB6C214} 13.730555 44 \n",
+ "3 {62E12FA3-D6C9-482C-A74C-CDCCE3D32EDD} 63.437476 12 \n",
+ "4 {99786E44-FF96-4250-A0A2-AF44CB189B28} 38.368910 33 \n",
+ "5 {99786E44-FF96-4250-A0A2-AF44CB189B28} 36.403273 35 \n",
+ "\n",
+ " XCOORD YCOORD AUSRICHTUNG GWR_EGID GBAUP \\\n",
+ "DF_UID \n",
+ "1 621674.951286 254203.972784 10.0 245033426.0 8011.0 \n",
+ "2 621675.374179 254206.313551 -170.0 245033426.0 8011.0 \n",
+ "3 621673.977050 254186.956803 -80.0 245033426.0 8011.0 \n",
+ "4 621696.695450 254249.767806 -80.0 245033426.0 8011.0 \n",
+ "5 621692.928934 254250.448974 100.0 245033426.0 8011.0 \n",
+ "\n",
+ " GKAT GAREA ... GKODX GKODY Shape_Ratio \\\n",
+ "DF_UID ... \n",
+ "1 1060.0 889.0 ... 621682.0 254206.0 1.050710 \n",
+ "2 1060.0 889.0 ... 621682.0 254206.0 1.132856 \n",
+ "3 1060.0 889.0 ... 621682.0 254206.0 0.497312 \n",
+ "4 1060.0 889.0 ... 621682.0 254206.0 0.629591 \n",
+ "5 1060.0 889.0 ... 621682.0 254206.0 0.647623 \n",
+ "\n",
+ " n_neighbors_100 n_corners panel_direction panel_tilt \\\n",
+ "DF_UID \n",
+ "1 2.0 4 190.0 37 \n",
+ "2 2.0 4 10.0 44 \n",
+ "3 2.0 4 100.0 12 \n",
+ "4 2.0 4 100.0 33 \n",
+ "5 2.0 4 280.0 35 \n",
+ "\n",
+ " panelled_area_ratio_ftr shaded_area_ratio_ftr Shape_Length \n",
+ "DF_UID \n",
+ "1 0.300963 0.000000 16.757573 \n",
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+ "5 0.615329 0.285714 23.575579 \n",
+ "\n",
+ "[5 rows x 21 columns]"
+ ]
+ },
+ "execution_count": 14,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "roofs.head()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 18,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "21"
+ ]
+ },
+ "execution_count": 18,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "len(roofs.columns)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 20,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "new_roofs = roofs[[ 'SB_UUID', 'FLAECHE', 'NEIGUNG', 'AUSRICHTUNG', 'XCOORD', 'YCOORD',\n",
+ " 'GWR_EGID', 'GBAUP', 'GKAT', 'GAREA', 'GASTW', 'GKODX', 'GKODY', \n",
+ " 'Shape_Length', 'Shape_Ratio', 'n_corners', 'n_neighbors_100', \n",
+ " 'panel_direction', 'panel_tilt', 'panelled_area_ratio_ftr', 'shaded_area_ratio_ftr' ]]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 21,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "21"
+ ]
+ },
+ "execution_count": 21,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "len(new_roofs.columns)"
+ ]
+ },
+ {
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+ "execution_count": 22,
+ "metadata": {},
+ "outputs": [
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+ " </tbody>\n",
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+ "<p>5 rows × 21 columns</p>\n",
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+ ],
+ "text/plain": [
+ " SB_UUID FLAECHE NEIGUNG \\\n",
+ "DF_UID \n",
+ "1 {DEA19230-2728-42BF-8A28-573F5EB6C214} 15.948816 37 \n",
+ "2 {DEA19230-2728-42BF-8A28-573F5EB6C214} 13.730555 44 \n",
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+ "4 {99786E44-FF96-4250-A0A2-AF44CB189B28} 38.368910 33 \n",
+ "5 {99786E44-FF96-4250-A0A2-AF44CB189B28} 36.403273 35 \n",
+ "\n",
+ " AUSRICHTUNG XCOORD YCOORD GWR_EGID GBAUP \\\n",
+ "DF_UID \n",
+ "1 10.0 621674.951286 254203.972784 245033426.0 8011.0 \n",
+ "2 -170.0 621675.374179 254206.313551 245033426.0 8011.0 \n",
+ "3 -80.0 621673.977050 254186.956803 245033426.0 8011.0 \n",
+ "4 -80.0 621696.695450 254249.767806 245033426.0 8011.0 \n",
+ "5 100.0 621692.928934 254250.448974 245033426.0 8011.0 \n",
+ "\n",
+ " GKAT GAREA ... GKODX GKODY \\\n",
+ "DF_UID ... \n",
+ "1 1060.0 889.0 ... 621682.0 254206.0 \n",
+ "2 1060.0 889.0 ... 621682.0 254206.0 \n",
+ "3 1060.0 889.0 ... 621682.0 254206.0 \n",
+ "4 1060.0 889.0 ... 621682.0 254206.0 \n",
+ "5 1060.0 889.0 ... 621682.0 254206.0 \n",
+ "\n",
+ " Shape_Length Shape_Ratio n_corners n_neighbors_100 \\\n",
+ "DF_UID \n",
+ "1 16.757573 1.050710 4 2.0 \n",
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+ "4 24.156709 0.629591 4 2.0 \n",
+ "5 23.575579 0.647623 4 2.0 \n",
+ "\n",
+ " panel_direction panel_tilt panelled_area_ratio_ftr \\\n",
+ "DF_UID \n",
+ "1 190.0 37 0.300963 \n",
+ "2 10.0 44 0.000000 \n",
+ "3 100.0 12 0.706207 \n",
+ "4 100.0 33 0.583806 \n",
+ "5 280.0 35 0.615329 \n",
+ "\n",
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+ "1 0.000000 \n",
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+ "3 0.000000 \n",
+ "4 0.000000 \n",
+ "5 0.285714 \n",
+ "\n",
+ "[5 rows x 21 columns]"
+ ]
+ },
+ "execution_count": 22,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "new_roofs.head()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 24,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "new_roofs.to_csv('/work/hyenergy/output/solar_potential/geographic_potential/CH_ROOFS_all_replaced_withLength.csv')"
+ ]
+ },
{
"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"
+ "version": "3.6.1"
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},
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diff --git a/Hourly_PV_public/Geographic_potential/Available_area/Prepare_features/prepare_training_panelling.ipynb b/Hourly_PV_public/Geographic_potential/Available_area/Prepare_features/prepare_training_panelling.ipynb
index b273576..979e5ff 100644
--- a/Hourly_PV_public/Geographic_potential/Available_area/Prepare_features/prepare_training_panelling.ipynb
+++ b/Hourly_PV_public/Geographic_potential/Available_area/Prepare_features/prepare_training_panelling.ipynb
@@ -1,3786 +1,2309 @@
{
"cells": [
{
"cell_type": "code",
- "execution_count": 1,
+ "execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"import pandas as pd\n",
"import xarray as xr\n",
"import os\n",
- "import geopandas as gpd\n",
+ "# import geopandas as gpd\n",
"\n",
"import matplotlib\n",
"%matplotlib notebook\n",
"import matplotlib.pyplot as plt"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Load data"
]
},
{
"cell_type": "code",
- "execution_count": 2,
+ "execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
- "# General roof information\n",
- "GVA_roofs_all = pd.read_csv(\"/Users/alinawalch/Documents/EPFL/data/rooftops/ROOFS_TRN_panels_replaced.csv\")\n",
- "GVA_roof_corners = pd.read_csv(\"/Users/alinawalch/Documents/EPFL/data/rooftops/SOLKAT_DACH_GVA_ncorners.csv\")"
+ "# load rooftop information\n",
+ "ROOFS_FP = '/work/hyenergy/output/solar_potential/geographic_potential/CH_ROOFS_all_replaced.csv'\n",
+ "roofs = pd.read_csv( ROOFS_FP )"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
- "# Roof shape information (to find roofs with superstructures)\n",
- "gva_shp = gpd.read_file('/Users/alinawalch/Documents/EPFL/data/rooftops/SOLKAT_DACH_GVA/SOLKAT_DACH_GVA.shp')\n",
- "gva_shp_noSP = gpd.read_file('/Users/alinawalch/Documents/EPFL/data/rooftops/SOLKAT_DACH_GVA_noSP/SOLKAT_CH_DACH_GVA_noSP.shp')"
+ "# Roof shapes in Geneva (training area), to find those with superstructures\n",
+ "gva_full_roofs_fp = '/Users/alinawalch/Documents/EPFL/data/rooftops/SOLKAT_DACH_GVA/SOLKAT_DACH_GVA.shp'\n",
+ "gva_shp = gpd.read_file( gva_full_roof_fp )\n",
+ "\n",
+ "gva_noSP_roofs_fp = '/Users/alinawalch/Documents/EPFL/data/rooftops/SOLKAT_DACH_GVA_noSP/SOLKAT_CH_DACH_GVA_noSP.shp'\n",
+ "gva_shp_noSP = gpd.read_file( gva_noSP_roofs_fp )"
]
},
{
"cell_type": "code",
- "execution_count": 4,
+ "execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"# panel fitting information\n",
- "GVA_panels_tgt = pd.read_csv('/Users/alinawalch/Documents/EPFL/data/rooftops/panel_stats_final/panelled_area_stats_GVA_best.csv')\n",
- "CH_panels_ftr = pd.read_csv('/Users/alinawalch/Documents/EPFL/data/rooftops/panel_stats_final/panelled_area_stats_CH_best.csv')"
+ "target_fp = '/work/hyenergy/output/solar_potential/geographic_potential/available_area/panel_fitting/panelled_area_stats_GVA_best.csv'\n",
+ "GVA_panels_tgt = pd.read_csv( target_fp )"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Merge roofs with shading info and roofs with panelled area info"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
- "### Step 1: get roofs for training set\n",
- "By merging the roofs_w_panels and the area of the gva_shp, we get a dataframe that contains all rooftops who's footprint overlaps with the SITG roof information for which superstructure information is available (all roofs where area_with_SP == area_without_SP are excluded!!!). To complement the superstructure information, all roof surfaces smaller than 8m^2 in SITG were also categorized as superstructures."
+ "### Step 1: get roofs for training set (roofs with target information available)\n",
+ "The for training, all roofs which have a \"raw\" panelled area ratio (feature, computed from the full roofs) > 0 and which are represented in the target dataset (GVA canton) are considered."
]
},
{
"cell_type": "code",
- "execution_count": 5,
+ "execution_count": 13,
"metadata": {},
- "outputs": [],
- "source": [
- "training_roofs = pd.merge(GVA_roofs_all, GVA_roof_corners, how = 'inner', on = 'DF_UID')"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 6,
- "metadata": {
- "scrolled": false
- },
- "outputs": [
- {
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- " <td>194.813319</td>\n",
- " <td>7</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>3</th>\n",
- " <td>4817427.0</td>\n",
- " <td>36.861447</td>\n",
- " <td>37.0</td>\n",
- " <td>-147.0</td>\n",
- " <td>503510.594159</td>\n",
- " <td>134142.188986</td>\n",
- " <td>28.210273</td>\n",
- " <td>29.341346</td>\n",
- " <td>1004090.0</td>\n",
- " <td>8012.0</td>\n",
- " <td>1021.0</td>\n",
- " <td>152.000000</td>\n",
- " <td>2.0</td>\n",
- " <td>503507.0</td>\n",
- " <td>134137.0</td>\n",
- " <td>0.765306</td>\n",
- " <td>3.0</td>\n",
- " <td>194.813319</td>\n",
- " <td>4</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>4</th>\n",
- " <td>4817428.0</td>\n",
- " <td>81.256555</td>\n",
- " <td>28.0</td>\n",
- " <td>123.0</td>\n",
- " <td>503504.226918</td>\n",
- " <td>134138.960671</td>\n",
- " <td>37.840077</td>\n",
- " <td>71.574129</td>\n",
- " <td>1004090.0</td>\n",
- " <td>8012.0</td>\n",
- " <td>1021.0</td>\n",
- " <td>152.000000</td>\n",
- " <td>2.0</td>\n",
- " <td>503507.0</td>\n",
- " <td>134137.0</td>\n",
- " <td>0.465686</td>\n",
- " <td>3.0</td>\n",
- " <td>194.813319</td>\n",
- " <td>4</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>5</th>\n",
- " <td>4817429.0</td>\n",
- " <td>11.397236</td>\n",
- " <td>27.0</td>\n",
- " <td>-144.0</td>\n",
- " <td>503512.070989</td>\n",
- " <td>134135.795686</td>\n",
- " <td>15.417311</td>\n",
- " <td>10.154872</td>\n",
- " <td>1004090.0</td>\n",
- " <td>8012.0</td>\n",
- " <td>1021.0</td>\n",
- " <td>152.000000</td>\n",
- " <td>2.0</td>\n",
- " <td>503507.0</td>\n",
- " <td>134137.0</td>\n",
- " <td>1.352724</td>\n",
- " <td>3.0</td>\n",
- " <td>194.813319</td>\n",
- " <td>3</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>6</th>\n",
- " <td>4817430.0</td>\n",
- " <td>11.262413</td>\n",
- " <td>27.0</td>\n",
- " <td>31.0</td>\n",
- " <td>503510.350525</td>\n",
- " <td>134133.126967</td>\n",
- " <td>15.346288</td>\n",
- " <td>10.045172</td>\n",
- " <td>1004090.0</td>\n",
- " <td>8012.0</td>\n",
- " <td>1021.0</td>\n",
- " <td>152.000000</td>\n",
- " <td>2.0</td>\n",
- " <td>503507.0</td>\n",
- " <td>134137.0</td>\n",
- " <td>1.362611</td>\n",
- " <td>3.0</td>\n",
- " <td>194.813319</td>\n",
- " <td>3</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>7</th>\n",
- " <td>4817431.0</td>\n",
- " <td>174.501987</td>\n",
- " <td>31.0</td>\n",
- " <td>-147.0</td>\n",
- " <td>503503.978942</td>\n",
- " <td>134181.171146</td>\n",
- " <td>59.815925</td>\n",
- " <td>149.165008</td>\n",
- " <td>1004088.0</td>\n",
- " <td>8011.0</td>\n",
- " <td>1021.0</td>\n",
- " <td>206.000000</td>\n",
- " <td>2.0</td>\n",
- " <td>503503.0</td>\n",
- " <td>134179.0</td>\n",
- " <td>0.342781</td>\n",
- " <td>3.0</td>\n",
- " <td>298.817334</td>\n",
- " <td>4</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>8</th>\n",
- " <td>4817432.0</td>\n",
- " <td>174.108293</td>\n",
- " <td>31.0</td>\n",
- " <td>33.0</td>\n",
- " <td>503500.517066</td>\n",
- " <td>134175.889168</td>\n",
- " <td>59.775896</td>\n",
- " <td>148.702405</td>\n",
- " <td>1004088.0</td>\n",
- " <td>8011.0</td>\n",
- " <td>1021.0</td>\n",
- " <td>206.000000</td>\n",
- " <td>2.0</td>\n",
- " <td>503503.0</td>\n",
- " <td>134179.0</td>\n",
- " <td>0.343326</td>\n",
- " <td>3.0</td>\n",
- " <td>298.817334</td>\n",
- " <td>4</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>9</th>\n",
- " <td>4817433.0</td>\n",
- " <td>69.216255</td>\n",
- " <td>26.0</td>\n",
- " <td>33.0</td>\n",
- " <td>503510.917446</td>\n",
- " <td>134191.713704</td>\n",
- " <td>45.633223</td>\n",
- " <td>61.997846</td>\n",
- " <td>295084893.0</td>\n",
- " <td>8011.0</td>\n",
- " <td>1021.0</td>\n",
- " <td>100.000000</td>\n",
- " <td>2.0</td>\n",
- " <td>503512.0</td>\n",
- " <td>134193.0</td>\n",
- " <td>0.659285</td>\n",
- " <td>3.0</td>\n",
- " <td>107.414054</td>\n",
- " <td>5</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>10</th>\n",
- " <td>4817434.0</td>\n",
- " <td>26.716480</td>\n",
- " <td>31.0</td>\n",
- " <td>-147.0</td>\n",
- " <td>503517.020358</td>\n",
- " <td>134191.118711</td>\n",
- " <td>23.687927</td>\n",
- " <td>22.959133</td>\n",
- " <td>295084893.0</td>\n",
- " <td>8011.0</td>\n",
- " <td>1021.0</td>\n",
- " <td>100.000000</td>\n",
- " <td>2.0</td>\n",
- " <td>503512.0</td>\n",
- " <td>134193.0</td>\n",
- " <td>0.886641</td>\n",
- " <td>3.0</td>\n",
- " <td>107.414054</td>\n",
- " <td>5</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>11</th>\n",
- " <td>4817435.0</td>\n",
- " <td>26.018729</td>\n",
- " <td>31.0</td>\n",
- " <td>-147.0</td>\n",
- " <td>503507.806109</td>\n",
- " <td>134197.114437</td>\n",
- " <td>23.199036</td>\n",
- " <td>22.360589</td>\n",
- " <td>295084893.0</td>\n",
- " <td>8011.0</td>\n",
- " <td>1021.0</td>\n",
- " <td>100.000000</td>\n",
- " <td>2.0</td>\n",
- " <td>503512.0</td>\n",
- " <td>134193.0</td>\n",
- " <td>0.891628</td>\n",
- " <td>3.0</td>\n",
- " <td>107.414054</td>\n",
- " <td>5</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>12</th>\n",
- " <td>4817436.0</td>\n",
- " <td>13.309012</td>\n",
- " <td>33.0</td>\n",
- " <td>123.0</td>\n",
- " <td>503512.471353</td>\n",
- " <td>134196.622116</td>\n",
- " <td>15.096068</td>\n",
- " <td>11.164928</td>\n",
- " <td>295084893.0</td>\n",
- " <td>8011.0</td>\n",
- " <td>1021.0</td>\n",
- " <td>100.000000</td>\n",
- " <td>2.0</td>\n",
- " <td>503512.0</td>\n",
- " <td>134193.0</td>\n",
- " <td>1.134274</td>\n",
- " <td>3.0</td>\n",
- " <td>22.613146</td>\n",
- " <td>6</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>13</th>\n",
- " <td>4817437.0</td>\n",
- " <td>13.503089</td>\n",
- " <td>32.0</td>\n",
- " <td>-57.0</td>\n",
- " <td>503514.586126</td>\n",
- " <td>134195.245953</td>\n",
- " <td>15.198331</td>\n",
- " <td>11.396747</td>\n",
- " <td>295084893.0</td>\n",
- " <td>8011.0</td>\n",
- " <td>1021.0</td>\n",
- " <td>100.000000</td>\n",
- " <td>2.0</td>\n",
- " <td>503512.0</td>\n",
- " <td>134193.0</td>\n",
- " <td>1.125545</td>\n",
- " <td>3.0</td>\n",
- " <td>22.613146</td>\n",
- " <td>5</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>14</th>\n",
- " <td>4817438.0</td>\n",
- " <td>130.038144</td>\n",
- " <td>26.0</td>\n",
- " <td>-144.0</td>\n",
- " <td>503951.193324</td>\n",
- " <td>134195.306644</td>\n",
- " <td>64.584475</td>\n",
- " <td>117.365353</td>\n",
- " <td>295084994.0</td>\n",
- " <td>8014.0</td>\n",
- " <td>1030.0</td>\n",
- " <td>213.000000</td>\n",
- " <td>2.0</td>\n",
- " <td>503949.0</td>\n",
- " <td>134194.0</td>\n",
- " <td>0.496658</td>\n",
- " <td>5.0</td>\n",
- " <td>230.552584</td>\n",
- " <td>4</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>15</th>\n",
- " <td>4817439.0</td>\n",
- " <td>126.475108</td>\n",
- " <td>26.0</td>\n",
- " <td>36.0</td>\n",
- " <td>503948.788882</td>\n",
- " <td>134191.981218</td>\n",
- " <td>64.301850</td>\n",
- " <td>113.406403</td>\n",
- " <td>295084994.0</td>\n",
- " <td>8014.0</td>\n",
- " <td>1030.0</td>\n",
- " <td>213.000000</td>\n",
- " <td>2.0</td>\n",
- " <td>503949.0</td>\n",
- " <td>134194.0</td>\n",
- " <td>0.508415</td>\n",
- " <td>5.0</td>\n",
- " <td>230.552584</td>\n",
- " <td>4</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>16</th>\n",
- " <td>4817440.0</td>\n",
- " <td>47.540096</td>\n",
- " <td>37.0</td>\n",
- " <td>-144.0</td>\n",
- " <td>503996.949571</td>\n",
- " <td>134161.244934</td>\n",
- " <td>27.081498</td>\n",
- " <td>37.981483</td>\n",
- " <td>1004076.0</td>\n",
- " <td>8012.0</td>\n",
- " <td>1021.0</td>\n",
- " <td>66.000000</td>\n",
- " <td>3.0</td>\n",
- " <td>504005.0</td>\n",
- " <td>134153.0</td>\n",
- " <td>0.569656</td>\n",
- " <td>7.0</td>\n",
- " <td>68.070576</td>\n",
- " <td>5</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>17</th>\n",
- " <td>4817441.0</td>\n",
- " <td>35.497241</td>\n",
- " <td>32.0</td>\n",
- " <td>36.0</td>\n",
- " <td>503994.863047</td>\n",
- " <td>134158.375583</td>\n",
- " <td>25.402378</td>\n",
- " <td>29.945648</td>\n",
- " <td>1004076.0</td>\n",
- " <td>8012.0</td>\n",
- " <td>1021.0</td>\n",
- " <td>66.000000</td>\n",
- " <td>3.0</td>\n",
- " <td>504005.0</td>\n",
- " <td>134153.0</td>\n",
- " <td>0.715616</td>\n",
- " <td>7.0</td>\n",
- " <td>68.070576</td>\n",
- " <td>4</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>18</th>\n",
- " <td>4817442.0</td>\n",
- " <td>49.847956</td>\n",
- " <td>38.0</td>\n",
- " <td>36.0</td>\n",
- " <td>504003.468131</td>\n",
- " <td>134152.306087</td>\n",
- " <td>29.835723</td>\n",
- " <td>39.429900</td>\n",
- " <td>1004076.0</td>\n",
- " <td>8012.0</td>\n",
- " <td>1021.0</td>\n",
- " <td>66.000000</td>\n",
- " <td>3.0</td>\n",
- " <td>504005.0</td>\n",
- " <td>134153.0</td>\n",
- " <td>0.598535</td>\n",
- " <td>7.0</td>\n",
- " <td>96.433564</td>\n",
- " <td>4</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>19</th>\n",
- " <td>4817443.0</td>\n",
- " <td>74.607733</td>\n",
- " <td>40.0</td>\n",
- " <td>-144.0</td>\n",
- " <td>504005.947778</td>\n",
- " <td>134155.715627</td>\n",
- " <td>32.967494</td>\n",
- " <td>57.409186</td>\n",
- " <td>1004076.0</td>\n",
- " <td>8012.0</td>\n",
- " <td>1021.0</td>\n",
- " <td>66.000000</td>\n",
- " <td>3.0</td>\n",
- " <td>504005.0</td>\n",
- " <td>134153.0</td>\n",
- " <td>0.441878</td>\n",
- " <td>7.0</td>\n",
- " <td>96.433564</td>\n",
- " <td>4</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>20</th>\n",
- " <td>4817444.0</td>\n",
- " <td>12.607657</td>\n",
- " <td>0.0</td>\n",
- " <td>0.0</td>\n",
- " <td>503991.439805</td>\n",
- " <td>134163.317363</td>\n",
- " <td>17.745074</td>\n",
- " <td>12.607657</td>\n",
- " <td>1004076.0</td>\n",
- " <td>8012.0</td>\n",
- " <td>1021.0</td>\n",
- " <td>66.000000</td>\n",
- " <td>3.0</td>\n",
- " <td>504005.0</td>\n",
- " <td>134153.0</td>\n",
- " <td>1.407484</td>\n",
- " <td>7.0</td>\n",
- " <td>12.607657</td>\n",
- " <td>5</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>21</th>\n",
- " <td>4817445.0</td>\n",
- " <td>9.973655</td>\n",
- " <td>29.0</td>\n",
- " <td>-55.0</td>\n",
- " <td>503926.571766</td>\n",
- " <td>134212.338837</td>\n",
- " <td>14.288661</td>\n",
- " <td>8.760702</td>\n",
- " <td>1004089.0</td>\n",
- " <td>8012.0</td>\n",
- " <td>1021.0</td>\n",
- " <td>57.000000</td>\n",
- " <td>2.0</td>\n",
- " <td>503922.0</td>\n",
- " <td>134215.0</td>\n",
- " <td>1.432640</td>\n",
- " <td>4.0</td>\n",
- " <td>78.634747</td>\n",
- " <td>3</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>22</th>\n",
- " <td>4817446.0</td>\n",
- " <td>34.666521</td>\n",
- " <td>29.0</td>\n",
- " <td>35.0</td>\n",
- " <td>503921.018886</td>\n",
- " <td>134214.298798</td>\n",
- " <td>29.015856</td>\n",
- " <td>30.403885</td>\n",
- " <td>1004089.0</td>\n",
- " <td>8012.0</td>\n",
- " <td>1021.0</td>\n",
- " <td>57.000000</td>\n",
- " <td>2.0</td>\n",
- " <td>503922.0</td>\n",
- " <td>134215.0</td>\n",
- " <td>0.836999</td>\n",
- " <td>4.0</td>\n",
- " <td>78.634747</td>\n",
- " <td>4</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>23</th>\n",
- " <td>4817447.0</td>\n",
- " <td>9.971017</td>\n",
- " <td>29.0</td>\n",
- " <td>125.0</td>\n",
- " <td>503917.347567</td>\n",
- " <td>134218.902400</td>\n",
- " <td>14.287157</td>\n",
- " <td>8.757635</td>\n",
- " <td>1004089.0</td>\n",
- " <td>8012.0</td>\n",
- " <td>1021.0</td>\n",
- " <td>57.000000</td>\n",
- " <td>2.0</td>\n",
- " <td>503922.0</td>\n",
- " <td>134215.0</td>\n",
- " <td>1.432869</td>\n",
- " <td>4.0</td>\n",
- " <td>78.634747</td>\n",
- " <td>4</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>24</th>\n",
- " <td>4817448.0</td>\n",
- " <td>34.963254</td>\n",
- " <td>28.0</td>\n",
- " <td>-145.0</td>\n",
- " <td>503922.898105</td>\n",
- " <td>134216.939359</td>\n",
- " <td>29.062031</td>\n",
- " <td>30.741322</td>\n",
- " <td>1004089.0</td>\n",
- " <td>8012.0</td>\n",
- " <td>1021.0</td>\n",
- " <td>57.000000</td>\n",
- " <td>2.0</td>\n",
- " <td>503922.0</td>\n",
- " <td>134215.0</td>\n",
- " <td>0.831216</td>\n",
- " <td>4.0</td>\n",
- " <td>78.634747</td>\n",
- " <td>4</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>25</th>\n",
- " <td>4817449.0</td>\n",
- " <td>19.979434</td>\n",
- " <td>7.0</td>\n",
- " <td>35.0</td>\n",
- " <td>503916.075512</td>\n",
- " <td>134213.701005</td>\n",
- " <td>17.895750</td>\n",
- " <td>19.831984</td>\n",
- " <td>1004089.0</td>\n",
- " <td>8012.0</td>\n",
- " <td>1021.0</td>\n",
- " <td>57.000000</td>\n",
- " <td>2.0</td>\n",
- " <td>503922.0</td>\n",
- " <td>134215.0</td>\n",
- " <td>0.895709</td>\n",
- " <td>4.0</td>\n",
- " <td>19.830510</td>\n",
- " <td>4</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>26</th>\n",
- " <td>4817450.0</td>\n",
- " <td>21.119847</td>\n",
- " <td>18.0</td>\n",
- " <td>-144.0</td>\n",
- " <td>503936.461763</td>\n",
- " <td>134203.761986</td>\n",
- " <td>18.414721</td>\n",
- " <td>20.066844</td>\n",
- " <td>295084994.0</td>\n",
- " <td>8014.0</td>\n",
- " <td>1030.0</td>\n",
- " <td>213.000000</td>\n",
- " <td>2.0</td>\n",
- " <td>503949.0</td>\n",
- " <td>134194.0</td>\n",
- " <td>0.871915</td>\n",
- " <td>5.0</td>\n",
- " <td>40.296071</td>\n",
- " <td>5</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>27</th>\n",
- " <td>4817451.0</td>\n",
- " <td>21.374411</td>\n",
- " <td>19.0</td>\n",
- " <td>36.0</td>\n",
- " <td>503934.470464</td>\n",
- " <td>134200.829905</td>\n",
- " <td>19.727025</td>\n",
- " <td>20.261942</td>\n",
- " <td>295084994.0</td>\n",
- " <td>8014.0</td>\n",
- " <td>1030.0</td>\n",
- " <td>213.000000</td>\n",
- " <td>2.0</td>\n",
- " <td>503949.0</td>\n",
- " <td>134194.0</td>\n",
- " <td>0.922927</td>\n",
- " <td>5.0</td>\n",
- " <td>40.296071</td>\n",
- " <td>6</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>28</th>\n",
- " <td>4817452.0</td>\n",
- " <td>68.854261</td>\n",
- " <td>35.0</td>\n",
- " <td>-140.0</td>\n",
- " <td>504222.101990</td>\n",
- " <td>134017.187739</td>\n",
- " <td>31.767443</td>\n",
- " <td>56.268749</td>\n",
- " <td>1004049.0</td>\n",
- " <td>8011.0</td>\n",
- " <td>1025.0</td>\n",
- " <td>67.000000</td>\n",
- " <td>3.0</td>\n",
- " <td>504220.0</td>\n",
- " <td>134015.0</td>\n",
- " <td>0.461372</td>\n",
- " <td>25.0</td>\n",
- " <td>99.757951</td>\n",
- " <td>5</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>29</th>\n",
- " <td>4817453.0</td>\n",
- " <td>52.296595</td>\n",
- " <td>34.0</td>\n",
- " <td>40.0</td>\n",
- " <td>504219.058562</td>\n",
- " <td>134013.574920</td>\n",
- " <td>29.327904</td>\n",
- " <td>43.406040</td>\n",
- " <td>1004049.0</td>\n",
- " <td>8011.0</td>\n",
- " <td>1025.0</td>\n",
- " <td>67.000000</td>\n",
- " <td>3.0</td>\n",
- " <td>504220.0</td>\n",
- " <td>134015.0</td>\n",
- " <td>0.560799</td>\n",
- " <td>25.0</td>\n",
- " <td>99.757951</td>\n",
- " <td>5</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",
- " </tr>\n",
- " <tr>\n",
- " <th>206432</th>\n",
- " <td>5124497.0</td>\n",
- " <td>139.413591</td>\n",
- " <td>30.0</td>\n",
- " <td>-60.0</td>\n",
- " <td>512727.853591</td>\n",
- " <td>121799.313992</td>\n",
- " <td>54.005430</td>\n",
- " <td>120.493402</td>\n",
- " <td>1018653.0</td>\n",
- " <td>8012.0</td>\n",
- " <td>1025.0</td>\n",
- " <td>153.000000</td>\n",
- " <td>3.0</td>\n",
- " <td>512725.0</td>\n",
- " <td>121800.0</td>\n",
- " <td>0.387376</td>\n",
- " <td>3.0</td>\n",
- " <td>239.840444</td>\n",
- " <td>9</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>206433</th>\n",
- " <td>5124498.0</td>\n",
- " <td>137.530298</td>\n",
- " <td>30.0</td>\n",
- " <td>120.0</td>\n",
- " <td>512722.012941</td>\n",
- " <td>121802.781737</td>\n",
- " <td>53.905711</td>\n",
- " <td>119.641777</td>\n",
- " <td>1018653.0</td>\n",
- " <td>8012.0</td>\n",
- " <td>1025.0</td>\n",
- " <td>153.000000</td>\n",
- " <td>3.0</td>\n",
- " <td>512725.0</td>\n",
- " <td>121800.0</td>\n",
- " <td>0.391955</td>\n",
- " <td>3.0</td>\n",
- " <td>239.840444</td>\n",
- " <td>9</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>206434</th>\n",
- " <td>5124499.0</td>\n",
- " <td>92.630815</td>\n",
- " <td>7.0</td>\n",
- " <td>-150.0</td>\n",
- " <td>512731.300787</td>\n",
- " <td>121811.881398</td>\n",
- " <td>47.143675</td>\n",
- " <td>91.927158</td>\n",
- " <td>1018653.0</td>\n",
- " <td>8012.0</td>\n",
- " <td>1025.0</td>\n",
- " <td>153.000000</td>\n",
- " <td>3.0</td>\n",
- " <td>512725.0</td>\n",
- " <td>121800.0</td>\n",
- " <td>0.508942</td>\n",
- " <td>3.0</td>\n",
- " <td>91.940359</td>\n",
- " <td>8</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>206435</th>\n",
- " <td>5124500.0</td>\n",
- " <td>44.081253</td>\n",
- " <td>7.0</td>\n",
- " <td>-148.0</td>\n",
- " <td>512734.614676</td>\n",
- " <td>121817.612632</td>\n",
- " <td>28.618486</td>\n",
- " <td>43.718502</td>\n",
- " <td>1018653.0</td>\n",
- " <td>8012.0</td>\n",
- " <td>1025.0</td>\n",
- " <td>153.000000</td>\n",
- " <td>3.0</td>\n",
- " <td>512725.0</td>\n",
- " <td>121800.0</td>\n",
- " <td>0.649221</td>\n",
- " <td>3.0</td>\n",
- " <td>43.752678</td>\n",
- " <td>4</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>206436</th>\n",
- " <td>5124501.0</td>\n",
- " <td>12.602429</td>\n",
- " <td>0.0</td>\n",
- " <td>0.0</td>\n",
- " <td>512727.537367</td>\n",
- " <td>121820.039977</td>\n",
- " <td>14.885065</td>\n",
- " <td>12.602429</td>\n",
- " <td>1018653.0</td>\n",
- " <td>8012.0</td>\n",
- " <td>1025.0</td>\n",
- " <td>153.000000</td>\n",
- " <td>3.0</td>\n",
- " <td>512725.0</td>\n",
- " <td>121800.0</td>\n",
- " <td>1.181127</td>\n",
- " <td>3.0</td>\n",
- " <td>26.462734</td>\n",
- " <td>6</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>206437</th>\n",
- " <td>5124502.0</td>\n",
- " <td>14.119724</td>\n",
- " <td>11.0</td>\n",
- " <td>-147.0</td>\n",
- " <td>512729.165421</td>\n",
- " <td>121822.382400</td>\n",
- " <td>16.789635</td>\n",
- " <td>13.863595</td>\n",
- " <td>1018653.0</td>\n",
- " <td>8012.0</td>\n",
- " <td>1025.0</td>\n",
- " <td>153.000000</td>\n",
- " <td>3.0</td>\n",
- " <td>512725.0</td>\n",
- " <td>121800.0</td>\n",
- " <td>1.189091</td>\n",
- " <td>3.0</td>\n",
- " <td>26.462734</td>\n",
- " <td>6</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>206438</th>\n",
- " <td>5124503.0</td>\n",
- " <td>36.753693</td>\n",
- " <td>21.0</td>\n",
- " <td>122.0</td>\n",
- " <td>512683.971180</td>\n",
- " <td>121769.079140</td>\n",
- " <td>23.556753</td>\n",
- " <td>34.231614</td>\n",
- " <td>2040405.0</td>\n",
- " <td>8012.0</td>\n",
- " <td>1021.0</td>\n",
- " <td>129.000000</td>\n",
- " <td>3.0</td>\n",
- " <td>512678.0</td>\n",
- " <td>121753.0</td>\n",
- " <td>0.640936</td>\n",
- " <td>7.0</td>\n",
- " <td>68.582316</td>\n",
- " <td>5</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>206439</th>\n",
- " <td>5124504.0</td>\n",
- " <td>0.064896</td>\n",
- " <td>19.0</td>\n",
- " <td>-58.0</td>\n",
- " <td>512689.499215</td>\n",
- " <td>121759.357413</td>\n",
- " <td>8.350840</td>\n",
- " <td>0.061348</td>\n",
- " <td>2040405.0</td>\n",
- " <td>8012.0</td>\n",
- " <td>1021.0</td>\n",
- " <td>129.000000</td>\n",
- " <td>3.0</td>\n",
- " <td>512678.0</td>\n",
- " <td>121753.0</td>\n",
- " <td>128.679441</td>\n",
- " <td>7.0</td>\n",
- " <td>68.582316</td>\n",
- " <td>3</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>206440</th>\n",
- " <td>5124505.0</td>\n",
- " <td>36.179539</td>\n",
- " <td>19.0</td>\n",
- " <td>-58.0</td>\n",
- " <td>512689.565868</td>\n",
- " <td>121765.612262</td>\n",
- " <td>23.566963</td>\n",
- " <td>34.201265</td>\n",
- " <td>2040405.0</td>\n",
- " <td>8012.0</td>\n",
- " <td>1021.0</td>\n",
- " <td>129.000000</td>\n",
- " <td>3.0</td>\n",
- " <td>512678.0</td>\n",
- " <td>121753.0</td>\n",
- " <td>0.651389</td>\n",
- " <td>7.0</td>\n",
- " <td>68.582316</td>\n",
- " <td>4</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>206441</th>\n",
- " <td>5124506.0</td>\n",
- " <td>57.609988</td>\n",
- " <td>17.0</td>\n",
- " <td>-57.0</td>\n",
- " <td>512685.874412</td>\n",
- " <td>121760.247993</td>\n",
- " <td>37.797327</td>\n",
- " <td>55.148314</td>\n",
- " <td>2040405.0</td>\n",
- " <td>8012.0</td>\n",
- " <td>1021.0</td>\n",
- " <td>129.000000</td>\n",
- " <td>3.0</td>\n",
- " <td>512678.0</td>\n",
- " <td>121753.0</td>\n",
- " <td>0.656090</td>\n",
- " <td>7.0</td>\n",
- " <td>108.760020</td>\n",
- " <td>8</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>206442</th>\n",
- " <td>5124507.0</td>\n",
- " <td>57.882063</td>\n",
- " <td>22.0</td>\n",
- " <td>122.0</td>\n",
- " <td>512679.975021</td>\n",
- " <td>121763.783138</td>\n",
- " <td>29.386703</td>\n",
- " <td>53.499302</td>\n",
- " <td>2040405.0</td>\n",
- " <td>8012.0</td>\n",
- " <td>1021.0</td>\n",
- " <td>129.000000</td>\n",
- " <td>3.0</td>\n",
- " <td>512678.0</td>\n",
- " <td>121753.0</td>\n",
- " <td>0.507700</td>\n",
- " <td>7.0</td>\n",
- " <td>108.760020</td>\n",
- " <td>5</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>206443</th>\n",
- " <td>5124508.0</td>\n",
- " <td>35.898733</td>\n",
- " <td>22.0</td>\n",
- " <td>-153.0</td>\n",
- " <td>512676.571716</td>\n",
- " <td>121745.126015</td>\n",
- " <td>30.833490</td>\n",
- " <td>33.393443</td>\n",
- " <td>2040405.0</td>\n",
- " <td>8012.0</td>\n",
- " <td>1021.0</td>\n",
- " <td>129.000000</td>\n",
- " <td>3.0</td>\n",
- " <td>512678.0</td>\n",
- " <td>121753.0</td>\n",
- " <td>0.858902</td>\n",
- " <td>7.0</td>\n",
- " <td>116.033907</td>\n",
- " <td>7</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>206444</th>\n",
- " <td>5124509.0</td>\n",
- " <td>88.059840</td>\n",
- " <td>20.0</td>\n",
- " <td>27.0</td>\n",
- " <td>512674.020870</td>\n",
- " <td>121740.921893</td>\n",
- " <td>39.260540</td>\n",
- " <td>82.722458</td>\n",
- " <td>2040405.0</td>\n",
- " <td>8012.0</td>\n",
- " <td>1021.0</td>\n",
- " <td>129.000000</td>\n",
- " <td>3.0</td>\n",
- " <td>512678.0</td>\n",
- " <td>121753.0</td>\n",
- " <td>0.445839</td>\n",
- " <td>7.0</td>\n",
- " <td>116.033907</td>\n",
- " <td>8</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>206445</th>\n",
- " <td>5124510.0</td>\n",
- " <td>234.137426</td>\n",
- " <td>15.0</td>\n",
- " <td>-139.0</td>\n",
- " <td>512576.260995</td>\n",
- " <td>121776.663075</td>\n",
- " <td>66.560300</td>\n",
- " <td>226.093454</td>\n",
- " <td>1018659.0</td>\n",
- " <td>8011.0</td>\n",
- " <td>1030.0</td>\n",
- " <td>449.601882</td>\n",
- " <td>2.0</td>\n",
- " <td>512596.0</td>\n",
- " <td>121754.0</td>\n",
- " <td>0.284279</td>\n",
- " <td>7.0</td>\n",
- " <td>449.601882</td>\n",
- " <td>4</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>206446</th>\n",
- " <td>5124511.0</td>\n",
- " <td>232.447102</td>\n",
- " <td>16.0</td>\n",
- " <td>41.0</td>\n",
- " <td>512570.079754</td>\n",
- " <td>121769.520367</td>\n",
- " <td>66.292584</td>\n",
- " <td>222.913017</td>\n",
- " <td>1018659.0</td>\n",
- " <td>8011.0</td>\n",
- " <td>1030.0</td>\n",
- " <td>449.601882</td>\n",
- " <td>2.0</td>\n",
- " <td>512596.0</td>\n",
- " <td>121754.0</td>\n",
- " <td>0.285194</td>\n",
- " <td>7.0</td>\n",
- " <td>449.601882</td>\n",
- " <td>4</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>206447</th>\n",
- " <td>5124512.0</td>\n",
- " <td>131.925651</td>\n",
- " <td>29.0</td>\n",
- " <td>121.0</td>\n",
- " <td>512861.419320</td>\n",
- " <td>121844.774678</td>\n",
- " <td>55.702429</td>\n",
- " <td>114.847781</td>\n",
- " <td>1018654.0</td>\n",
- " <td>8011.0</td>\n",
- " <td>1025.0</td>\n",
- " <td>304.000000</td>\n",
- " <td>2.0</td>\n",
- " <td>512862.0</td>\n",
- " <td>121841.0</td>\n",
- " <td>0.422226</td>\n",
- " <td>2.0</td>\n",
- " <td>236.648087</td>\n",
- " <td>5</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>206448</th>\n",
- " <td>5124513.0</td>\n",
- " <td>137.339196</td>\n",
- " <td>28.0</td>\n",
- " <td>-59.0</td>\n",
- " <td>512865.854189</td>\n",
- " <td>121842.120366</td>\n",
- " <td>56.243851</td>\n",
- " <td>121.027343</td>\n",
- " <td>1018654.0</td>\n",
- " <td>8011.0</td>\n",
- " <td>1025.0</td>\n",
- " <td>304.000000</td>\n",
- " <td>2.0</td>\n",
- " <td>512862.0</td>\n",
- " <td>121841.0</td>\n",
- " <td>0.409525</td>\n",
- " <td>2.0</td>\n",
- " <td>236.648087</td>\n",
- " <td>4</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>206449</th>\n",
- " <td>5124514.0</td>\n",
- " <td>21.008432</td>\n",
- " <td>23.0</td>\n",
- " <td>-150.0</td>\n",
- " <td>512862.686744</td>\n",
- " <td>121857.263294</td>\n",
- " <td>23.119281</td>\n",
- " <td>19.328343</td>\n",
- " <td>1018654.0</td>\n",
- " <td>8011.0</td>\n",
- " <td>1025.0</td>\n",
- " <td>304.000000</td>\n",
- " <td>2.0</td>\n",
- " <td>512862.0</td>\n",
- " <td>121841.0</td>\n",
- " <td>1.100476</td>\n",
- " <td>2.0</td>\n",
- " <td>39.706122</td>\n",
- " <td>6</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>206450</th>\n",
- " <td>5124515.0</td>\n",
- " <td>21.541363</td>\n",
- " <td>19.0</td>\n",
- " <td>30.0</td>\n",
- " <td>512860.734800</td>\n",
- " <td>121855.152708</td>\n",
- " <td>19.585625</td>\n",
- " <td>20.336518</td>\n",
- " <td>1018654.0</td>\n",
- " <td>8011.0</td>\n",
- " <td>1025.0</td>\n",
- " <td>304.000000</td>\n",
- " <td>2.0</td>\n",
- " <td>512862.0</td>\n",
- " <td>121841.0</td>\n",
- " <td>0.909210</td>\n",
- " <td>2.0</td>\n",
- " <td>39.706122</td>\n",
- " <td>4</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>206451</th>\n",
- " <td>5124516.0</td>\n",
- " <td>33.342276</td>\n",
- " <td>17.0</td>\n",
- " <td>-58.0</td>\n",
- " <td>512857.342542</td>\n",
- " <td>121829.041410</td>\n",
- " <td>24.377198</td>\n",
- " <td>31.954253</td>\n",
- " <td>1018654.0</td>\n",
- " <td>8011.0</td>\n",
- " <td>1025.0</td>\n",
- " <td>304.000000</td>\n",
- " <td>2.0</td>\n",
- " <td>512862.0</td>\n",
- " <td>121841.0</td>\n",
- " <td>0.731120</td>\n",
- " <td>2.0</td>\n",
- " <td>108.900435</td>\n",
- " <td>4</td>\n",
+ "outputs": [],
+ "source": [
+ "# merge panelled area ratio for training (GVA only, excluded superstrucutres)\n",
+ "training_panels = roofs.merge( GVA_panels_tgt.loc[:,['DF_UID', 'panelled_area_ratio']], \n",
+ " how = 'right', on = 'DF_UID')\n",
+ "training_panels.rename( {'panelled_area_ratio' : 'panelled_area_ratio_tgt'}, axis = 1, inplace = True)\n",
+ "training_panels.fillna(0, inplace = True)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 14,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# exclude all roofs that have a feature panel count (before subtracting superstructures) equal to 0\n",
+ "training_panels = training_panels[ training_panels.panelled_area_ratio_ftr != 0 ]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 16,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "<div>\n",
+ "<style scoped>\n",
+ " .dataframe tbody tr th:only-of-type {\n",
+ " vertical-align: middle;\n",
+ " }\n",
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+ "</style>\n",
+ "<table border=\"1\" class=\"dataframe\">\n",
+ " <thead>\n",
+ " <tr style=\"text-align: right;\">\n",
+ " <th></th>\n",
+ " <th>DF_UID</th>\n",
+ " <th>SB_UUID</th>\n",
+ " <th>FLAECHE</th>\n",
+ " <th>NEIGUNG</th>\n",
+ " <th>AUSRICHTUNG</th>\n",
+ " <th>XCOORD</th>\n",
+ " <th>YCOORD</th>\n",
+ " <th>GWR_EGID</th>\n",
+ " <th>GBAUP</th>\n",
+ " <th>GKAT</th>\n",
+ " <th>...</th>\n",
+ " <th>GKODY</th>\n",
+ " <th>Shape_Length</th>\n",
+ " <th>Shape_Ratio</th>\n",
+ " <th>n_corners</th>\n",
+ " <th>n_neighbors_100</th>\n",
+ " <th>panel_direction</th>\n",
+ " <th>panel_tilt</th>\n",
+ " <th>panelled_area_ratio_ftr</th>\n",
+ " <th>shaded_area_ratio_ftr</th>\n",
+ " <th>panelled_area_ratio_tgt</th>\n",
" </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
" <tr>\n",
- " <th>206452</th>\n",
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- " <td>43.358052</td>\n",
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- " <td>26.787103</td>\n",
- " <td>42.321731</td>\n",
- " <td>1018654.0</td>\n",
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+ " <td>{C0837EBA-3FE8-4166-99E4-A009D794F3F7}</td>\n",
+ " <td>71.487047</td>\n",
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- " <td>121841.0</td>\n",
- " <td>0.617811</td>\n",
- " <td>2.0</td>\n",
- " <td>108.900435</td>\n",
+ " <td>1021.0</td>\n",
+ " <td>...</td>\n",
+ " <td>134198.0</td>\n",
+ " <td>33.936595</td>\n",
+ " <td>0.474724</td>\n",
" <td>4</td>\n",
- " </tr>\n",
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- " <td>2.0</td>\n",
- " <td>512862.0</td>\n",
- " <td>121841.0</td>\n",
- " <td>0.836549</td>\n",
- " <td>2.0</td>\n",
- " <td>108.900435</td>\n",
- " <td>6</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>206454</th>\n",
- " <td>5124519.0</td>\n",
- " <td>32.262272</td>\n",
- " <td>7.0</td>\n",
- " <td>-62.0</td>\n",
- " <td>512889.292856</td>\n",
- " <td>121962.982921</td>\n",
- " <td>22.665441</td>\n",
- " <td>32.006156</td>\n",
- " <td>1018655.0</td>\n",
- " <td>8014.0</td>\n",
- " <td>1025.0</td>\n",
- " <td>44.936338</td>\n",
- " <td>3.0</td>\n",
- " <td>512908.0</td>\n",
- " <td>121915.0</td>\n",
- " <td>0.702537</td>\n",
- " <td>1.0</td>\n",
- " <td>44.936338</td>\n",
- " <td>5</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>206455</th>\n",
- " <td>5124520.0</td>\n",
- " <td>14.249623</td>\n",
- " <td>25.0</td>\n",
- " <td>118.0</td>\n",
- " <td>512885.599017</td>\n",
- " <td>121964.977036</td>\n",
- " <td>15.514710</td>\n",
- " <td>12.886922</td>\n",
- " <td>1018655.0</td>\n",
- " <td>8014.0</td>\n",
- " <td>1025.0</td>\n",
- " <td>44.936338</td>\n",
" <td>3.0</td>\n",
- " <td>512908.0</td>\n",
- " <td>121915.0</td>\n",
- " <td>1.088780</td>\n",
- " <td>1.0</td>\n",
- " <td>44.936338</td>\n",
- " <td>5</td>\n",
+ " <td>307.0</td>\n",
+ " <td>10</td>\n",
+ " <td>0.805740</td>\n",
+ " <td>0.117647</td>\n",
+ " <td>0.805740</td>\n",
" </tr>\n",
" <tr>\n",
- " <th>206456</th>\n",
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- " <td>202.860586</td>\n",
- " <td>26.0</td>\n",
- " <td>-65.0</td>\n",
- " <td>512907.355343</td>\n",
- " <td>121907.640275</td>\n",
- " <td>69.264065</td>\n",
- " <td>181.708205</td>\n",
- " <td>1018655.0</td>\n",
- " <td>8014.0</td>\n",
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- " <td>0.341437</td>\n",
- " <td>1.0</td>\n",
- " <td>383.229874</td>\n",
+ " <th>1</th>\n",
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+ " <td>{10B89BB0-60A3-4460-9D73-7C0036224AC5}</td>\n",
+ " <td>36.859836</td>\n",
+ " <td>37</td>\n",
+ " <td>33.0</td>\n",
+ " <td>503503.812619</td>\n",
+ " <td>134131.833522</td>\n",
+ " <td>1004090.0</td>\n",
+ " <td>8012.0</td>\n",
+ " <td>1021.0</td>\n",
+ " <td>...</td>\n",
+ " <td>134137.0</td>\n",
+ " <td>28.208608</td>\n",
+ " <td>0.765294</td>\n",
" <td>4</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>206457</th>\n",
- " <td>5124524.0</td>\n",
- " <td>221.668609</td>\n",
- " <td>25.0</td>\n",
- " <td>115.0</td>\n",
- " <td>512901.324171</td>\n",
- " <td>121910.827716</td>\n",
- " <td>72.136766</td>\n",
- " <td>201.586966</td>\n",
- " <td>1018655.0</td>\n",
- " <td>8014.0</td>\n",
- " <td>1025.0</td>\n",
- " <td>148.000000</td>\n",
" <td>3.0</td>\n",
- " <td>512908.0</td>\n",
- " <td>121915.0</td>\n",
- " <td>0.325426</td>\n",
- " <td>1.0</td>\n",
- " <td>383.229874</td>\n",
- " <td>6</td>\n",
+ " <td>213.0</td>\n",
+ " <td>37</td>\n",
+ " <td>0.390669</td>\n",
+ " <td>0.000000</td>\n",
+ " <td>0.173631</td>\n",
" </tr>\n",
" <tr>\n",
- " <th>206458</th>\n",
- " <td>5124525.0</td>\n",
- " <td>126.405824</td>\n",
- " <td>22.0</td>\n",
- " <td>118.0</td>\n",
- " <td>512801.107921</td>\n",
- " <td>121763.322478</td>\n",
- " <td>43.276794</td>\n",
- " <td>116.796274</td>\n",
- " <td>1018651.0</td>\n",
- " <td>8013.0</td>\n",
- " <td>1030.0</td>\n",
- " <td>181.000000</td>\n",
+ " <th>2</th>\n",
+ " <td>4817426</td>\n",
+ " <td>{10B89BB0-60A3-4460-9D73-7C0036224AC5}</td>\n",
+ " <td>51.333864</td>\n",
+ " <td>31</td>\n",
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+ " <td>503509.783165</td>\n",
+ " <td>134135.282805</td>\n",
+ " <td>1004090.0</td>\n",
+ " <td>8012.0</td>\n",
+ " <td>1021.0</td>\n",
+ " <td>...</td>\n",
+ " <td>134137.0</td>\n",
+ " <td>40.053428</td>\n",
+ " <td>0.780254</td>\n",
+ " <td>7</td>\n",
" <td>3.0</td>\n",
- " <td>512806.0</td>\n",
- " <td>121761.0</td>\n",
- " <td>0.342364</td>\n",
- " <td>2.0</td>\n",
- " <td>234.405582</td>\n",
- " <td>4</td>\n",
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+ " <td>31</td>\n",
+ " <td>0.155843</td>\n",
+ " <td>0.000000</td>\n",
+ " <td>0.155843</td>\n",
" </tr>\n",
" <tr>\n",
- " <th>206459</th>\n",
- " <td>5124526.0</td>\n",
- " <td>126.408740</td>\n",
- " <td>22.0</td>\n",
- " <td>-62.0</td>\n",
- " <td>512810.176759</td>\n",
- " <td>121758.418405</td>\n",
- " <td>43.277184</td>\n",
- " <td>116.797944</td>\n",
- " <td>1018651.0</td>\n",
- " <td>8013.0</td>\n",
- " <td>1030.0</td>\n",
- " <td>181.000000</td>\n",
- " <td>3.0</td>\n",
- " <td>512806.0</td>\n",
- " <td>121761.0</td>\n",
- " <td>0.342359</td>\n",
- " <td>2.0</td>\n",
- " <td>234.405582</td>\n",
+ " <th>3</th>\n",
+ " <td>4817427</td>\n",
+ " <td>{10B89BB0-60A3-4460-9D73-7C0036224AC5}</td>\n",
+ " <td>36.861447</td>\n",
+ " <td>37</td>\n",
+ " <td>-147.0</td>\n",
+ " <td>503510.594159</td>\n",
+ " <td>134142.188986</td>\n",
+ " <td>1004090.0</td>\n",
+ " <td>8012.0</td>\n",
+ " <td>1021.0</td>\n",
+ " <td>...</td>\n",
+ " <td>134137.0</td>\n",
+ " <td>28.210273</td>\n",
+ " <td>0.765306</td>\n",
" <td>4</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>206460</th>\n",
- " <td>5124527.0</td>\n",
- " <td>17.738624</td>\n",
- " <td>32.0</td>\n",
- " <td>-67.0</td>\n",
- " <td>512895.656423</td>\n",
- " <td>121945.700714</td>\n",
- " <td>16.399780</td>\n",
- " <td>14.964642</td>\n",
- " <td>1018655.0</td>\n",
- " <td>8014.0</td>\n",
- " <td>1025.0</td>\n",
- " <td>29.863731</td>\n",
" <td>3.0</td>\n",
- " <td>512908.0</td>\n",
- " <td>121915.0</td>\n",
- " <td>0.924524</td>\n",
- " <td>1.0</td>\n",
- " <td>29.863731</td>\n",
- " <td>4</td>\n",
+ " <td>33.0</td>\n",
+ " <td>37</td>\n",
+ " <td>0.390652</td>\n",
+ " <td>0.166667</td>\n",
+ " <td>0.217029</td>\n",
" </tr>\n",
" <tr>\n",
- " <th>206461</th>\n",
- " <td>5124528.0</td>\n",
- " <td>17.671450</td>\n",
- " <td>33.0</td>\n",
- " <td>113.0</td>\n",
- " <td>512893.143353</td>\n",
- " <td>121946.778198</td>\n",
- " <td>16.370630</td>\n",
- " <td>14.885036</td>\n",
- " <td>1018655.0</td>\n",
- " <td>8014.0</td>\n",
- " <td>1025.0</td>\n",
- " <td>29.863731</td>\n",
- " <td>3.0</td>\n",
- " <td>512908.0</td>\n",
- " <td>121915.0</td>\n",
- " <td>0.926389</td>\n",
- " <td>1.0</td>\n",
- " <td>29.863731</td>\n",
+ " <th>4</th>\n",
+ " <td>4817428</td>\n",
+ " <td>{10B89BB0-60A3-4460-9D73-7C0036224AC5}</td>\n",
+ " <td>81.256555</td>\n",
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+ " <td>503504.226918</td>\n",
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+ " <td>1004090.0</td>\n",
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+ " <td>...</td>\n",
+ " <td>134137.0</td>\n",
+ " <td>37.840077</td>\n",
+ " <td>0.465686</td>\n",
" <td>4</td>\n",
+ " <td>3.0</td>\n",
+ " <td>303.0</td>\n",
+ " <td>28</td>\n",
+ " <td>0.708866</td>\n",
+ " <td>0.333333</td>\n",
+ " <td>0.708866</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
- "<p>206462 rows × 19 columns</p>\n",
+ "<p>5 rows × 23 columns</p>\n",
"</div>"
],
"text/plain": [
- " DF_UID FLAECHE NEIGUNG AUSRICHTUNG XCOORD \\\n",
- "0 4817410.0 71.487047 10.0 127.0 503491.325015 \n",
- "1 4817425.0 36.859836 37.0 33.0 503503.812619 \n",
- "2 4817426.0 51.333864 31.0 -57.0 503509.783165 \n",
- "3 4817427.0 36.861447 37.0 -147.0 503510.594159 \n",
- "4 4817428.0 81.256555 28.0 123.0 503504.226918 \n",
- "5 4817429.0 11.397236 27.0 -144.0 503512.070989 \n",
- "6 4817430.0 11.262413 27.0 31.0 503510.350525 \n",
- "7 4817431.0 174.501987 31.0 -147.0 503503.978942 \n",
- "8 4817432.0 174.108293 31.0 33.0 503500.517066 \n",
- "9 4817433.0 69.216255 26.0 33.0 503510.917446 \n",
- "10 4817434.0 26.716480 31.0 -147.0 503517.020358 \n",
- "11 4817435.0 26.018729 31.0 -147.0 503507.806109 \n",
- "12 4817436.0 13.309012 33.0 123.0 503512.471353 \n",
- "13 4817437.0 13.503089 32.0 -57.0 503514.586126 \n",
- "14 4817438.0 130.038144 26.0 -144.0 503951.193324 \n",
- "15 4817439.0 126.475108 26.0 36.0 503948.788882 \n",
- "16 4817440.0 47.540096 37.0 -144.0 503996.949571 \n",
- "17 4817441.0 35.497241 32.0 36.0 503994.863047 \n",
- "18 4817442.0 49.847956 38.0 36.0 504003.468131 \n",
- "19 4817443.0 74.607733 40.0 -144.0 504005.947778 \n",
- "20 4817444.0 12.607657 0.0 0.0 503991.439805 \n",
- "21 4817445.0 9.973655 29.0 -55.0 503926.571766 \n",
- "22 4817446.0 34.666521 29.0 35.0 503921.018886 \n",
- "23 4817447.0 9.971017 29.0 125.0 503917.347567 \n",
- "24 4817448.0 34.963254 28.0 -145.0 503922.898105 \n",
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- "26 4817450.0 21.119847 18.0 -144.0 503936.461763 \n",
- "27 4817451.0 21.374411 19.0 36.0 503934.470464 \n",
- "28 4817452.0 68.854261 35.0 -140.0 504222.101990 \n",
- "29 4817453.0 52.296595 34.0 40.0 504219.058562 \n",
- "... ... ... ... ... ... \n",
- "206432 5124497.0 139.413591 30.0 -60.0 512727.853591 \n",
- "206433 5124498.0 137.530298 30.0 120.0 512722.012941 \n",
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- "206436 5124501.0 12.602429 0.0 0.0 512727.537367 \n",
- "206437 5124502.0 14.119724 11.0 -147.0 512729.165421 \n",
- "206438 5124503.0 36.753693 21.0 122.0 512683.971180 \n",
- "206439 5124504.0 0.064896 19.0 -58.0 512689.499215 \n",
- "206440 5124505.0 36.179539 19.0 -58.0 512689.565868 \n",
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- "206443 5124508.0 35.898733 22.0 -153.0 512676.571716 \n",
- "206444 5124509.0 88.059840 20.0 27.0 512674.020870 \n",
- "206445 5124510.0 234.137426 15.0 -139.0 512576.260995 \n",
- "206446 5124511.0 232.447102 16.0 41.0 512570.079754 \n",
- "206447 5124512.0 131.925651 29.0 121.0 512861.419320 \n",
- "206448 5124513.0 137.339196 28.0 -59.0 512865.854189 \n",
- "206449 5124514.0 21.008432 23.0 -150.0 512862.686744 \n",
- "206450 5124515.0 21.541363 19.0 30.0 512860.734800 \n",
- "206451 5124516.0 33.342276 17.0 -58.0 512857.342542 \n",
- "206452 5124517.0 43.358052 13.0 122.0 512853.537208 \n",
- "206453 5124518.0 34.768271 0.0 0.0 512851.492252 \n",
- "206454 5124519.0 32.262272 7.0 -62.0 512889.292856 \n",
- "206455 5124520.0 14.249623 25.0 118.0 512885.599017 \n",
- "206456 5124523.0 202.860586 26.0 -65.0 512907.355343 \n",
- "206457 5124524.0 221.668609 25.0 115.0 512901.324171 \n",
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- "206459 5124526.0 126.408740 22.0 -62.0 512810.176759 \n",
- "206460 5124527.0 17.738624 32.0 -67.0 512895.656423 \n",
- "206461 5124528.0 17.671450 33.0 113.0 512893.143353 \n",
+ " DF_UID SB_UUID FLAECHE NEIGUNG \\\n",
+ "0 4817410 {C0837EBA-3FE8-4166-99E4-A009D794F3F7} 71.487047 10 \n",
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+ "3 4817427 {10B89BB0-60A3-4460-9D73-7C0036224AC5} 36.861447 37 \n",
+ "4 4817428 {10B89BB0-60A3-4460-9D73-7C0036224AC5} 81.256555 28 \n",
+ "\n",
+ " AUSRICHTUNG XCOORD YCOORD GWR_EGID GBAUP GKAT \\\n",
+ "0 127.0 503491.325015 134197.490397 295070969.0 8011.0 1021.0 \n",
+ "1 33.0 503503.812619 134131.833522 1004090.0 8012.0 1021.0 \n",
+ "2 -57.0 503509.783165 134135.282805 1004090.0 8012.0 1021.0 \n",
+ "3 -147.0 503510.594159 134142.188986 1004090.0 8012.0 1021.0 \n",
+ "4 123.0 503504.226918 134138.960671 1004090.0 8012.0 1021.0 \n",
"\n",
- " YCOORD Shape_Length Shape_Area GWR_EGID GBAUP GKAT \\\n",
- "0 134197.490397 33.936595 70.390620 295070969.0 8011.0 1021.0 \n",
- "1 134131.833522 28.208608 29.339500 1004090.0 8012.0 1021.0 \n",
- "2 134135.282805 40.053428 44.043504 1004090.0 8012.0 1021.0 \n",
- "3 134142.188986 28.210273 29.341346 1004090.0 8012.0 1021.0 \n",
- "4 134138.960671 37.840077 71.574129 1004090.0 8012.0 1021.0 \n",
- "5 134135.795686 15.417311 10.154872 1004090.0 8012.0 1021.0 \n",
- "6 134133.126967 15.346288 10.045172 1004090.0 8012.0 1021.0 \n",
- "7 134181.171146 59.815925 149.165008 1004088.0 8011.0 1021.0 \n",
- "8 134175.889168 59.775896 148.702405 1004088.0 8011.0 1021.0 \n",
- "9 134191.713704 45.633223 61.997846 295084893.0 8011.0 1021.0 \n",
- "10 134191.118711 23.687927 22.959133 295084893.0 8011.0 1021.0 \n",
- "11 134197.114437 23.199036 22.360589 295084893.0 8011.0 1021.0 \n",
- "12 134196.622116 15.096068 11.164928 295084893.0 8011.0 1021.0 \n",
- "13 134195.245953 15.198331 11.396747 295084893.0 8011.0 1021.0 \n",
- "14 134195.306644 64.584475 117.365353 295084994.0 8014.0 1030.0 \n",
- "15 134191.981218 64.301850 113.406403 295084994.0 8014.0 1030.0 \n",
- "16 134161.244934 27.081498 37.981483 1004076.0 8012.0 1021.0 \n",
- "17 134158.375583 25.402378 29.945648 1004076.0 8012.0 1021.0 \n",
- "18 134152.306087 29.835723 39.429900 1004076.0 8012.0 1021.0 \n",
- "19 134155.715627 32.967494 57.409186 1004076.0 8012.0 1021.0 \n",
- "20 134163.317363 17.745074 12.607657 1004076.0 8012.0 1021.0 \n",
- "21 134212.338837 14.288661 8.760702 1004089.0 8012.0 1021.0 \n",
- "22 134214.298798 29.015856 30.403885 1004089.0 8012.0 1021.0 \n",
- "23 134218.902400 14.287157 8.757635 1004089.0 8012.0 1021.0 \n",
- "24 134216.939359 29.062031 30.741322 1004089.0 8012.0 1021.0 \n",
- "25 134213.701005 17.895750 19.831984 1004089.0 8012.0 1021.0 \n",
- "26 134203.761986 18.414721 20.066844 295084994.0 8014.0 1030.0 \n",
- "27 134200.829905 19.727025 20.261942 295084994.0 8014.0 1030.0 \n",
- "28 134017.187739 31.767443 56.268749 1004049.0 8011.0 1025.0 \n",
- "29 134013.574920 29.327904 43.406040 1004049.0 8011.0 1025.0 \n",
- "... ... ... ... ... ... ... \n",
- "206432 121799.313992 54.005430 120.493402 1018653.0 8012.0 1025.0 \n",
- "206433 121802.781737 53.905711 119.641777 1018653.0 8012.0 1025.0 \n",
- "206434 121811.881398 47.143675 91.927158 1018653.0 8012.0 1025.0 \n",
- "206435 121817.612632 28.618486 43.718502 1018653.0 8012.0 1025.0 \n",
- "206436 121820.039977 14.885065 12.602429 1018653.0 8012.0 1025.0 \n",
- "206437 121822.382400 16.789635 13.863595 1018653.0 8012.0 1025.0 \n",
- "206438 121769.079140 23.556753 34.231614 2040405.0 8012.0 1021.0 \n",
- "206439 121759.357413 8.350840 0.061348 2040405.0 8012.0 1021.0 \n",
- "206440 121765.612262 23.566963 34.201265 2040405.0 8012.0 1021.0 \n",
- "206441 121760.247993 37.797327 55.148314 2040405.0 8012.0 1021.0 \n",
- "206442 121763.783138 29.386703 53.499302 2040405.0 8012.0 1021.0 \n",
- "206443 121745.126015 30.833490 33.393443 2040405.0 8012.0 1021.0 \n",
- "206444 121740.921893 39.260540 82.722458 2040405.0 8012.0 1021.0 \n",
- "206445 121776.663075 66.560300 226.093454 1018659.0 8011.0 1030.0 \n",
- "206446 121769.520367 66.292584 222.913017 1018659.0 8011.0 1030.0 \n",
- "206447 121844.774678 55.702429 114.847781 1018654.0 8011.0 1025.0 \n",
- "206448 121842.120366 56.243851 121.027343 1018654.0 8011.0 1025.0 \n",
- "206449 121857.263294 23.119281 19.328343 1018654.0 8011.0 1025.0 \n",
- "206450 121855.152708 19.585625 20.336518 1018654.0 8011.0 1025.0 \n",
- "206451 121829.041410 24.377198 31.954253 1018654.0 8011.0 1025.0 \n",
- "206452 121831.368979 26.787103 42.321731 1018654.0 8011.0 1025.0 \n",
- "206453 121838.457750 29.085365 34.768271 1018654.0 8011.0 1025.0 \n",
- "206454 121962.982921 22.665441 32.006156 1018655.0 8014.0 1025.0 \n",
- "206455 121964.977036 15.514710 12.886922 1018655.0 8014.0 1025.0 \n",
- "206456 121907.640275 69.264065 181.708205 1018655.0 8014.0 1025.0 \n",
- "206457 121910.827716 72.136766 201.586966 1018655.0 8014.0 1025.0 \n",
- "206458 121763.322478 43.276794 116.796274 1018651.0 8013.0 1030.0 \n",
- "206459 121758.418405 43.277184 116.797944 1018651.0 8013.0 1030.0 \n",
- "206460 121945.700714 16.399780 14.964642 1018655.0 8014.0 1025.0 \n",
- "206461 121946.778198 16.370630 14.885036 1018655.0 8014.0 1025.0 \n",
+ " ... GKODY Shape_Length Shape_Ratio n_corners \\\n",
+ "0 ... 134198.0 33.936595 0.474724 4 \n",
+ "1 ... 134137.0 28.208608 0.765294 4 \n",
+ "2 ... 134137.0 40.053428 0.780254 7 \n",
+ "3 ... 134137.0 28.210273 0.765306 4 \n",
+ "4 ... 134137.0 37.840077 0.465686 4 \n",
"\n",
- " GAREA GASTW GKODX GKODY Shape_Ratio n_neighbors_100 \\\n",
- "0 44.000000 2.0 503491.0 134198.0 0.474724 3.0 \n",
- "1 152.000000 2.0 503507.0 134137.0 0.765294 3.0 \n",
- "2 152.000000 2.0 503507.0 134137.0 0.780254 3.0 \n",
- "3 152.000000 2.0 503507.0 134137.0 0.765306 3.0 \n",
- "4 152.000000 2.0 503507.0 134137.0 0.465686 3.0 \n",
- "5 152.000000 2.0 503507.0 134137.0 1.352724 3.0 \n",
- "6 152.000000 2.0 503507.0 134137.0 1.362611 3.0 \n",
- "7 206.000000 2.0 503503.0 134179.0 0.342781 3.0 \n",
- "8 206.000000 2.0 503503.0 134179.0 0.343326 3.0 \n",
- "9 100.000000 2.0 503512.0 134193.0 0.659285 3.0 \n",
- "10 100.000000 2.0 503512.0 134193.0 0.886641 3.0 \n",
- "11 100.000000 2.0 503512.0 134193.0 0.891628 3.0 \n",
- "12 100.000000 2.0 503512.0 134193.0 1.134274 3.0 \n",
- "13 100.000000 2.0 503512.0 134193.0 1.125545 3.0 \n",
- "14 213.000000 2.0 503949.0 134194.0 0.496658 5.0 \n",
- "15 213.000000 2.0 503949.0 134194.0 0.508415 5.0 \n",
- "16 66.000000 3.0 504005.0 134153.0 0.569656 7.0 \n",
- "17 66.000000 3.0 504005.0 134153.0 0.715616 7.0 \n",
- "18 66.000000 3.0 504005.0 134153.0 0.598535 7.0 \n",
- "19 66.000000 3.0 504005.0 134153.0 0.441878 7.0 \n",
- "20 66.000000 3.0 504005.0 134153.0 1.407484 7.0 \n",
- "21 57.000000 2.0 503922.0 134215.0 1.432640 4.0 \n",
- "22 57.000000 2.0 503922.0 134215.0 0.836999 4.0 \n",
- "23 57.000000 2.0 503922.0 134215.0 1.432869 4.0 \n",
- "24 57.000000 2.0 503922.0 134215.0 0.831216 4.0 \n",
- "25 57.000000 2.0 503922.0 134215.0 0.895709 4.0 \n",
- "26 213.000000 2.0 503949.0 134194.0 0.871915 5.0 \n",
- "27 213.000000 2.0 503949.0 134194.0 0.922927 5.0 \n",
- "28 67.000000 3.0 504220.0 134015.0 0.461372 25.0 \n",
- "29 67.000000 3.0 504220.0 134015.0 0.560799 25.0 \n",
- "... ... ... ... ... ... ... \n",
- "206432 153.000000 3.0 512725.0 121800.0 0.387376 3.0 \n",
- "206433 153.000000 3.0 512725.0 121800.0 0.391955 3.0 \n",
- "206434 153.000000 3.0 512725.0 121800.0 0.508942 3.0 \n",
- "206435 153.000000 3.0 512725.0 121800.0 0.649221 3.0 \n",
- "206436 153.000000 3.0 512725.0 121800.0 1.181127 3.0 \n",
- "206437 153.000000 3.0 512725.0 121800.0 1.189091 3.0 \n",
- "206438 129.000000 3.0 512678.0 121753.0 0.640936 7.0 \n",
- "206439 129.000000 3.0 512678.0 121753.0 128.679441 7.0 \n",
- "206440 129.000000 3.0 512678.0 121753.0 0.651389 7.0 \n",
- "206441 129.000000 3.0 512678.0 121753.0 0.656090 7.0 \n",
- "206442 129.000000 3.0 512678.0 121753.0 0.507700 7.0 \n",
- "206443 129.000000 3.0 512678.0 121753.0 0.858902 7.0 \n",
- "206444 129.000000 3.0 512678.0 121753.0 0.445839 7.0 \n",
- "206445 449.601882 2.0 512596.0 121754.0 0.284279 7.0 \n",
- "206446 449.601882 2.0 512596.0 121754.0 0.285194 7.0 \n",
- "206447 304.000000 2.0 512862.0 121841.0 0.422226 2.0 \n",
- "206448 304.000000 2.0 512862.0 121841.0 0.409525 2.0 \n",
- "206449 304.000000 2.0 512862.0 121841.0 1.100476 2.0 \n",
- "206450 304.000000 2.0 512862.0 121841.0 0.909210 2.0 \n",
- "206451 304.000000 2.0 512862.0 121841.0 0.731120 2.0 \n",
- "206452 304.000000 2.0 512862.0 121841.0 0.617811 2.0 \n",
- "206453 304.000000 2.0 512862.0 121841.0 0.836549 2.0 \n",
- "206454 44.936338 3.0 512908.0 121915.0 0.702537 1.0 \n",
- "206455 44.936338 3.0 512908.0 121915.0 1.088780 1.0 \n",
- "206456 148.000000 3.0 512908.0 121915.0 0.341437 1.0 \n",
- "206457 148.000000 3.0 512908.0 121915.0 0.325426 1.0 \n",
- "206458 181.000000 3.0 512806.0 121761.0 0.342364 2.0 \n",
- "206459 181.000000 3.0 512806.0 121761.0 0.342359 2.0 \n",
- "206460 29.863731 3.0 512908.0 121915.0 0.924524 1.0 \n",
- "206461 29.863731 3.0 512908.0 121915.0 0.926389 1.0 \n",
+ " n_neighbors_100 panel_direction panel_tilt panelled_area_ratio_ftr \\\n",
+ "0 3.0 307.0 10 0.805740 \n",
+ "1 3.0 213.0 37 0.390669 \n",
+ "2 3.0 123.0 31 0.155843 \n",
+ "3 3.0 33.0 37 0.390652 \n",
+ "4 3.0 303.0 28 0.708866 \n",
"\n",
- " Estim_build_area n_corners \n",
- "0 70.400998 4 \n",
- "1 194.813319 4 \n",
- "2 194.813319 7 \n",
- "3 194.813319 4 \n",
- "4 194.813319 4 \n",
- "5 194.813319 3 \n",
- "6 194.813319 3 \n",
- "7 298.817334 4 \n",
- "8 298.817334 4 \n",
- "9 107.414054 5 \n",
- "10 107.414054 5 \n",
- "11 107.414054 5 \n",
- "12 22.613146 6 \n",
- "13 22.613146 5 \n",
- "14 230.552584 4 \n",
- "15 230.552584 4 \n",
- "16 68.070576 5 \n",
- "17 68.070576 4 \n",
- "18 96.433564 4 \n",
- "19 96.433564 4 \n",
- "20 12.607657 5 \n",
- "21 78.634747 3 \n",
- "22 78.634747 4 \n",
- "23 78.634747 4 \n",
- "24 78.634747 4 \n",
- "25 19.830510 4 \n",
- "26 40.296071 5 \n",
- "27 40.296071 6 \n",
- "28 99.757951 5 \n",
- "29 99.757951 5 \n",
- "... ... ... \n",
- "206432 239.840444 9 \n",
- "206433 239.840444 9 \n",
- "206434 91.940359 8 \n",
- "206435 43.752678 4 \n",
- "206436 26.462734 6 \n",
- "206437 26.462734 6 \n",
- "206438 68.582316 5 \n",
- "206439 68.582316 3 \n",
- "206440 68.582316 4 \n",
- "206441 108.760020 8 \n",
- "206442 108.760020 5 \n",
- "206443 116.033907 7 \n",
- "206444 116.033907 8 \n",
- "206445 449.601882 4 \n",
- "206446 449.601882 4 \n",
- "206447 236.648087 5 \n",
- "206448 236.648087 4 \n",
- "206449 39.706122 6 \n",
- "206450 39.706122 4 \n",
- "206451 108.900435 4 \n",
- "206452 108.900435 4 \n",
- "206453 108.900435 6 \n",
- "206454 44.936338 5 \n",
- "206455 44.936338 5 \n",
- "206456 383.229874 4 \n",
- "206457 383.229874 6 \n",
- "206458 234.405582 4 \n",
- "206459 234.405582 4 \n",
- "206460 29.863731 4 \n",
- "206461 29.863731 4 \n",
+ " shaded_area_ratio_ftr panelled_area_ratio_tgt \n",
+ "0 0.117647 0.805740 \n",
+ "1 0.000000 0.173631 \n",
+ "2 0.000000 0.155843 \n",
+ "3 0.166667 0.217029 \n",
+ "4 0.333333 0.708866 \n",
"\n",
- "[206462 rows x 19 columns]"
+ "[5 rows x 23 columns]"
]
},
- "execution_count": 6,
+ "execution_count": 16,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
- "training_roofs"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Step 2: add panel information\n",
- "Add information of panelled area for Sonnendach roof polygons (ftr) and roof polygons with excluded superstructures (tgt). Note that CH_panels_ftr contains ALL rooftops and their panel_count information. For all roofs where panel_count == 0, we know already that there cannot be any panels fitted (due to geometry/size), neither vertically nor horizontally, so any calculation of available area for these rooftops is obsolete, i.e. the panels are excluded from further analysis."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 7,
- "metadata": {},
- "outputs": [],
- "source": [
- "# merge panelled area ratio for features (no superstructure excluded)\n",
- "training_roofs_panel_ftr = training_roofs.merge( CH_panels_ftr.loc[:,['DF_UID', \n",
- " 'panel_tilt', \n",
- " 'best_align', \n",
- " 'panelled_area_ratio']], \n",
- " how = 'left', on = 'DF_UID')\n",
- "training_roofs_panel_ftr.rename( {'panelled_area_ratio' : 'panelled_area_ratio_ftr'}, axis = 1, inplace = True)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 8,
- "metadata": {},
- "outputs": [],
- "source": [
- "# exclude all roofs that have a feature panel count (before subtracting superstructures) equal to 0\n",
- "training_panels = training_roofs_panel_ftr[training_roofs_panel_ftr.panelled_area_ratio_ftr != 0]"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 9,
- "metadata": {},
- "outputs": [],
- "source": [
- "# merge panelled area ratio for training (GVA only, excluded superstrucutres)\n",
- "training_panels = training_panels.merge( GVA_panels_tgt.loc[:,['DF_UID', 'panelled_area_ratio']], \n",
- " how = 'left', on = 'DF_UID')\n",
- "training_panels.rename( {'panelled_area_ratio' : 'panelled_area_ratio_tgt'}, axis = 1, inplace = True)\n",
- "training_panels.fillna(0, inplace = True)"
+ "training_panels.head()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
- "### Step 3: Exclude roofs without superstructure data\n",
+ "### Step 2: Exclude roofs without superstructure data\n",
"The shapefiles of GVA / GVA_noSP can be use to check if the area was changed when superstructures were subtracted. In the cases where this was not the case, the respective roofs are removed from training - it is assumed that the dataset is incomplete and superstructures were not correctly registered rather than there are no superstructures that can be found on the roof. This may be a conservative estimate in some cases, which however is preferred to an overestimate. Uncertainty is to be quantified to assess the level of confidence"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [],
"source": [
"# extract area information from shapefiles\n",
"gva_all = gva_shp.loc[:,['DF_UID']]\n",
"gva_all['area_full'] = gva_shp.area\n",
"\n",
"gva_noSP = gva_shp_noSP.loc[:,['DF_UID']]\n",
"gva_noSP['area_noSP'] = gva_shp_noSP.area"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [],
"source": [
"# Merge information of areas wih and without superstructures; areas not found in gva_noSP are given area = 0\n",
"gva_data = gva_all.merge(gva_noSP, on = 'DF_UID', how = 'left')\n",
"gva_data.fillna(0, inplace = True)"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [],
"source": [
"unequal_area = gva_data[np.round(gva_data.area_full,2) != np.round(gva_data.area_noSP,2)]"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Number of total roofs in Geneva: 206462\n",
"Number of roofs with some superstructure: 63225\n",
"Percentage of roofs with some superstructure: 30.62 percent\n"
]
}
],
"source": [
"print(\"Number of total roofs in Geneva: %d\" %len(gva_data))\n",
"print(\"Number of roofs with some superstructure: %d\" %len(unequal_area))\n",
"print(\"Percentage of roofs with some superstructure: %.2f percent\" %(100 * len(unequal_area) / len(gva_data)))"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [],
"source": [
"TRN_data = training_panels[training_panels.DF_UID.isin(unequal_area.DF_UID)]"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {
"scrolled": false
},
"outputs": [
{
"data": {
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"\n",
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <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>AUSRICHTUNG</th>\n",
" <th>XCOORD</th>\n",
" <th>YCOORD</th>\n",
" <th>Shape_Length</th>\n",
" <th>Shape_Area</th>\n",
" <th>GWR_EGID</th>\n",
" <th>GBAUP</th>\n",
" <th>...</th>\n",
" <th>GKODX</th>\n",
" <th>GKODY</th>\n",
" <th>Shape_Ratio</th>\n",
" <th>n_neighbors_100</th>\n",
" <th>Estim_build_area</th>\n",
" <th>n_corners</th>\n",
" <th>panel_tilt</th>\n",
" <th>best_align</th>\n",
" <th>panelled_area_ratio_ftr</th>\n",
" <th>panelled_area_ratio_tgt</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>4817425.0</td>\n",
" <td>36.859836</td>\n",
" <td>37.0</td>\n",
" <td>33.0</td>\n",
" <td>503503.812619</td>\n",
" <td>134131.833522</td>\n",
" <td>28.208608</td>\n",
" <td>29.339500</td>\n",
" <td>1004090.0</td>\n",
" <td>8012.0</td>\n",
" <td>...</td>\n",
" <td>503507.0</td>\n",
" <td>134137.0</td>\n",
" <td>0.765294</td>\n",
" <td>3.0</td>\n",
" <td>194.813319</td>\n",
" <td>4</td>\n",
" <td>37</td>\n",
" <td>equal</td>\n",
" <td>0.390669</td>\n",
" <td>0.173631</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>4817427.0</td>\n",
" <td>36.861447</td>\n",
" <td>37.0</td>\n",
" <td>-147.0</td>\n",
" <td>503510.594159</td>\n",
" <td>134142.188986</td>\n",
" <td>28.210273</td>\n",
" <td>29.341346</td>\n",
" <td>1004090.0</td>\n",
" <td>8012.0</td>\n",
" <td>...</td>\n",
" <td>503507.0</td>\n",
" <td>134137.0</td>\n",
" <td>0.765306</td>\n",
" <td>3.0</td>\n",
" <td>194.813319</td>\n",
" <td>4</td>\n",
" <td>37</td>\n",
" <td>horizontal</td>\n",
" <td>0.390652</td>\n",
" <td>0.217029</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>4817433.0</td>\n",
" <td>69.216255</td>\n",
" <td>26.0</td>\n",
" <td>33.0</td>\n",
" <td>503510.917446</td>\n",
" <td>134191.713704</td>\n",
" <td>45.633223</td>\n",
" <td>61.997846</td>\n",
" <td>295084893.0</td>\n",
" <td>8011.0</td>\n",
" <td>...</td>\n",
" <td>503512.0</td>\n",
" <td>134193.0</td>\n",
" <td>0.659285</td>\n",
" <td>3.0</td>\n",
" <td>107.414054</td>\n",
" <td>5</td>\n",
" <td>26</td>\n",
" <td>horizontal</td>\n",
" <td>0.508551</td>\n",
" <td>0.277391</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td>4817445.0</td>\n",
" <td>9.973655</td>\n",
" <td>29.0</td>\n",
" <td>-55.0</td>\n",
" <td>503926.571766</td>\n",
" <td>134212.338837</td>\n",
" <td>14.288661</td>\n",
" <td>8.760702</td>\n",
" <td>1004089.0</td>\n",
" <td>8012.0</td>\n",
" <td>...</td>\n",
" <td>503922.0</td>\n",
" <td>134215.0</td>\n",
" <td>1.432640</td>\n",
" <td>4.0</td>\n",
" <td>78.634747</td>\n",
" <td>3</td>\n",
" <td>29</td>\n",
" <td>horizontal</td>\n",
" <td>0.160423</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>26</th>\n",
" <td>4817452.0</td>\n",
" <td>68.854261</td>\n",
" <td>35.0</td>\n",
" <td>-140.0</td>\n",
" <td>504222.101990</td>\n",
" <td>134017.187739</td>\n",
" <td>31.767443</td>\n",
" <td>56.268749</td>\n",
" <td>1004049.0</td>\n",
" <td>8011.0</td>\n",
" <td>...</td>\n",
" <td>504220.0</td>\n",
" <td>134015.0</td>\n",
" <td>0.461372</td>\n",
" <td>25.0</td>\n",
" <td>99.757951</td>\n",
" <td>5</td>\n",
" <td>35</td>\n",
" <td>horizontal</td>\n",
" <td>0.697125</td>\n",
" <td>0.697125</td>\n",
" </tr>\n",
" <tr>\n",
" <th>27</th>\n",
" <td>4817453.0</td>\n",
" <td>52.296595</td>\n",
" <td>34.0</td>\n",
" <td>40.0</td>\n",
" <td>504219.058562</td>\n",
" <td>134013.574920</td>\n",
" <td>29.327904</td>\n",
" <td>43.406040</td>\n",
" <td>1004049.0</td>\n",
" <td>8011.0</td>\n",
" <td>...</td>\n",
" <td>504220.0</td>\n",
" <td>134015.0</td>\n",
" <td>0.560799</td>\n",
" <td>25.0</td>\n",
" <td>99.757951</td>\n",
" <td>5</td>\n",
" <td>34</td>\n",
" <td>horizontal</td>\n",
" <td>0.734273</td>\n",
" <td>0.673084</td>\n",
" </tr>\n",
" <tr>\n",
" <th>33</th>\n",
" <td>4817464.0</td>\n",
" <td>78.771912</td>\n",
" <td>31.0</td>\n",
" <td>130.0</td>\n",
" <td>504150.396646</td>\n",
" <td>134085.492644</td>\n",
" <td>32.609685</td>\n",
" <td>67.373176</td>\n",
" <td>1004073.0</td>\n",
" <td>8011.0</td>\n",
" <td>...</td>\n",
" <td>504151.0</td>\n",
" <td>134082.0</td>\n",
" <td>0.413976</td>\n",
" <td>17.0</td>\n",
" <td>140.790186</td>\n",
" <td>5</td>\n",
" <td>31</td>\n",
" <td>vertical</td>\n",
" <td>0.710913</td>\n",
" <td>0.406236</td>\n",
" </tr>\n",
" <tr>\n",
" <th>40</th>\n",
" <td>4817471.0</td>\n",
" <td>73.524780</td>\n",
" <td>35.0</td>\n",
" <td>34.0</td>\n",
" <td>504039.884935</td>\n",
" <td>134127.753162</td>\n",
" <td>40.713703</td>\n",
" <td>60.474674</td>\n",
" <td>1004075.0</td>\n",
" <td>8011.0</td>\n",
" <td>...</td>\n",
" <td>504040.0</td>\n",
" <td>134129.0</td>\n",
" <td>0.553741</td>\n",
" <td>7.0</td>\n",
" <td>119.554424</td>\n",
" <td>6</td>\n",
" <td>35</td>\n",
" <td>horizontal</td>\n",
" <td>0.609318</td>\n",
" <td>0.652841</td>\n",
" </tr>\n",
" <tr>\n",
" <th>48</th>\n",
" <td>4817483.0</td>\n",
" <td>100.571828</td>\n",
" <td>27.0</td>\n",
" <td>140.0</td>\n",
" <td>504182.850754</td>\n",
" <td>134128.499894</td>\n",
" <td>41.247227</td>\n",
" <td>89.271304</td>\n",
" <td>1004060.0</td>\n",
" <td>8011.0</td>\n",
" <td>...</td>\n",
" <td>504185.0</td>\n",
" <td>134127.0</td>\n",
" <td>0.410127</td>\n",
" <td>13.0</td>\n",
" <td>170.407907</td>\n",
" <td>4</td>\n",
" <td>27</td>\n",
" <td>horizontal</td>\n",
" <td>0.763633</td>\n",
" <td>0.493180</td>\n",
" </tr>\n",
" <tr>\n",
" <th>52</th>\n",
" <td>4817487.0</td>\n",
" <td>107.363169</td>\n",
" <td>26.0</td>\n",
" <td>-50.0</td>\n",
" <td>504164.499411</td>\n",
" <td>134085.908714</td>\n",
" <td>40.126227</td>\n",
" <td>96.811374</td>\n",
" <td>1004058.0</td>\n",
" <td>8011.0</td>\n",
" <td>...</td>\n",
" <td>504160.0</td>\n",
" <td>134089.0</td>\n",
" <td>0.373743</td>\n",
" <td>17.0</td>\n",
" <td>232.571656</td>\n",
" <td>4</td>\n",
" <td>26</td>\n",
" <td>horizontal</td>\n",
" <td>0.834551</td>\n",
" <td>0.804745</td>\n",
" </tr>\n",
" <tr>\n",
" <th>69</th>\n",
" <td>4817506.0</td>\n",
" <td>338.194772</td>\n",
" <td>32.0</td>\n",
" <td>-57.0</td>\n",
" <td>504118.320342</td>\n",
" <td>134142.125054</td>\n",
" <td>89.124850</td>\n",
" <td>288.352570</td>\n",
" <td>1004078.0</td>\n",
" <td>8014.0</td>\n",
" <td>...</td>\n",
" <td>504101.0</td>\n",
" <td>134121.0</td>\n",
" <td>0.263531</td>\n",
" <td>12.0</td>\n",
" <td>1265.908399</td>\n",
" <td>6</td>\n",
" <td>32</td>\n",
" <td>horizontal</td>\n",
" <td>0.794808</td>\n",
" <td>0.553527</td>\n",
" </tr>\n",
" <tr>\n",
" <th>74</th>\n",
" <td>4817511.0</td>\n",
" <td>20.907218</td>\n",
" <td>47.0</td>\n",
" <td>-147.0</td>\n",
" <td>504132.987332</td>\n",
" <td>134174.806150</td>\n",
" <td>20.892222</td>\n",
" <td>14.380937</td>\n",
" <td>1004078.0</td>\n",
" <td>8014.0</td>\n",
" <td>...</td>\n",
" <td>504101.0</td>\n",
" <td>134121.0</td>\n",
" <td>0.999283</td>\n",
" <td>12.0</td>\n",
" <td>1265.908399</td>\n",
" <td>3</td>\n",
" <td>47</td>\n",
" <td>equal</td>\n",
" <td>0.229586</td>\n",
" <td>0.076529</td>\n",
" </tr>\n",
" <tr>\n",
" <th>76</th>\n",
" <td>4817513.0</td>\n",
" <td>180.037771</td>\n",
" <td>33.0</td>\n",
" <td>-57.0</td>\n",
" <td>504131.757170</td>\n",
" <td>134165.089431</td>\n",
" <td>53.979078</td>\n",
" <td>150.181533</td>\n",
" <td>1004078.0</td>\n",
" <td>8014.0</td>\n",
" <td>...</td>\n",
" <td>504101.0</td>\n",
" <td>134121.0</td>\n",
" <td>0.299821</td>\n",
" <td>12.0</td>\n",
" <td>1265.908399</td>\n",
" <td>7</td>\n",
" <td>33</td>\n",
" <td>horizontal</td>\n",
" <td>0.773171</td>\n",
" <td>0.479899</td>\n",
" </tr>\n",
" <tr>\n",
" <th>86</th>\n",
" <td>4817534.0</td>\n",
" <td>69.050433</td>\n",
" <td>37.0</td>\n",
" <td>-145.0</td>\n",
" <td>504232.555744</td>\n",
" <td>134035.586526</td>\n",
" <td>37.131477</td>\n",
" <td>55.112486</td>\n",
" <td>1004070.0</td>\n",
" <td>8011.0</td>\n",
" <td>...</td>\n",
" <td>504235.0</td>\n",
" <td>134032.0</td>\n",
" <td>0.537744</td>\n",
" <td>29.0</td>\n",
" <td>148.612823</td>\n",
" <td>8</td>\n",
" <td>37</td>\n",
" <td>horizontal</td>\n",
" <td>0.625630</td>\n",
" <td>0.648801</td>\n",
" </tr>\n",
" <tr>\n",
" <th>95</th>\n",
" <td>4817543.0</td>\n",
" <td>136.154298</td>\n",
" <td>26.0</td>\n",
" <td>-58.0</td>\n",
" <td>504216.156462</td>\n",
" <td>134047.845046</td>\n",
" <td>46.060999</td>\n",
" <td>121.923272</td>\n",
" <td>1004071.0</td>\n",
" <td>8011.0</td>\n",
" <td>...</td>\n",
" <td>504213.0</td>\n",
" <td>134050.0</td>\n",
" <td>0.338300</td>\n",
" <td>27.0</td>\n",
" <td>260.007501</td>\n",
" <td>5</td>\n",
" <td>26</td>\n",
" <td>vertical</td>\n",
" <td>0.775591</td>\n",
" <td>0.587569</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104</th>\n",
" <td>4817553.0</td>\n",
" <td>299.453663</td>\n",
" <td>28.0</td>\n",
" <td>-47.0</td>\n",
" <td>504213.418431</td>\n",
" <td>134081.933731</td>\n",
" <td>71.637039</td>\n",
" <td>265.577565</td>\n",
" <td>1004055.0</td>\n",
" <td>8011.0</td>\n",
" <td>...</td>\n",
" <td>504206.0</td>\n",
" <td>134087.0</td>\n",
" <td>0.239226</td>\n",
" <td>21.0</td>\n",
" <td>686.905610</td>\n",
" <td>14</td>\n",
" <td>28</td>\n",
" <td>vertical</td>\n",
" <td>0.774744</td>\n",
" <td>0.593080</td>\n",
" </tr>\n",
" <tr>\n",
" <th>108</th>\n",
" <td>4817558.0</td>\n",
" <td>232.507194</td>\n",
" <td>28.0</td>\n",
" <td>113.0</td>\n",
" <td>504140.745470</td>\n",
" <td>134060.379545</td>\n",
" <td>67.568369</td>\n",
" <td>205.428267</td>\n",
" <td>1004050.0</td>\n",
" <td>8011.0</td>\n",
" <td>...</td>\n",
" <td>504146.0</td>\n",
" <td>134056.0</td>\n",
" <td>0.290608</td>\n",
" <td>16.0</td>\n",
" <td>483.038711</td>\n",
" <td>10</td>\n",
" <td>28</td>\n",
" <td>horizontal</td>\n",
" <td>0.729440</td>\n",
" <td>0.633099</td>\n",
" </tr>\n",
" <tr>\n",
" <th>117</th>\n",
" <td>4817569.0</td>\n",
" <td>46.645324</td>\n",
" <td>59.0</td>\n",
" <td>47.0</td>\n",
" <td>504383.212030</td>\n",
" <td>134038.490596</td>\n",
" <td>29.044821</td>\n",
" <td>23.861811</td>\n",
" <td>1004034.0</td>\n",
" <td>8011.0</td>\n",
" <td>...</td>\n",
" <td>504388.0</td>\n",
" <td>134043.0</td>\n",
" <td>0.622674</td>\n",
" <td>10.0</td>\n",
" <td>221.776847</td>\n",
" <td>3</td>\n",
" <td>59</td>\n",
" <td>equal</td>\n",
" <td>0.343014</td>\n",
" <td>0.171507</td>\n",
" </tr>\n",
" <tr>\n",
" <th>118</th>\n",
" <td>4817570.0</td>\n",
" <td>114.433767</td>\n",
" <td>40.0</td>\n",
" <td>-43.0</td>\n",
" <td>504390.817811</td>\n",
" <td>134040.491507</td>\n",
" <td>40.761920</td>\n",
" <td>87.041610</td>\n",
" <td>1004034.0</td>\n",
" <td>8011.0</td>\n",
" <td>...</td>\n",
" <td>504388.0</td>\n",
" <td>134043.0</td>\n",
" <td>0.356205</td>\n",
" <td>10.0</td>\n",
" <td>221.776847</td>\n",
" <td>4</td>\n",
" <td>40</td>\n",
" <td>vertical</td>\n",
" <td>0.727058</td>\n",
" <td>0.531312</td>\n",
" </tr>\n",
" <tr>\n",
" <th>119</th>\n",
" <td>4817571.0</td>\n",
" <td>46.644194</td>\n",
" <td>59.0</td>\n",
" <td>-133.0</td>\n",
" <td>504393.326128</td>\n",
" <td>134047.945689</td>\n",
" <td>29.044527</td>\n",
" <td>23.859602</td>\n",
" <td>1004034.0</td>\n",
" <td>8011.0</td>\n",
" <td>...</td>\n",
" <td>504388.0</td>\n",
" <td>134043.0</td>\n",
" <td>0.622683</td>\n",
" <td>10.0</td>\n",
" <td>221.776847</td>\n",
" <td>3</td>\n",
" <td>59</td>\n",
" <td>horizontal</td>\n",
" <td>0.343022</td>\n",
" <td>0.102907</td>\n",
" </tr>\n",
" <tr>\n",
" <th>120</th>\n",
" <td>4817572.0</td>\n",
" <td>114.041009</td>\n",
" <td>41.0</td>\n",
" <td>137.0</td>\n",
" <td>504385.717010</td>\n",
" <td>134045.948402</td>\n",
" <td>40.689282</td>\n",
" <td>86.524609</td>\n",
" <td>1004034.0</td>\n",
" <td>8011.0</td>\n",
" <td>...</td>\n",
" <td>504388.0</td>\n",
" <td>134043.0</td>\n",
" <td>0.356795</td>\n",
" <td>10.0</td>\n",
" <td>221.776847</td>\n",
" <td>4</td>\n",
" <td>41</td>\n",
" <td>vertical</td>\n",
" <td>0.729562</td>\n",
" <td>0.505081</td>\n",
" </tr>\n",
" <tr>\n",
" <th>126</th>\n",
" <td>4817579.0</td>\n",
" <td>22.712083</td>\n",
" <td>31.0</td>\n",
" <td>135.0</td>\n",
" <td>504362.580721</td>\n",
" <td>134030.362133</td>\n",
" <td>23.779044</td>\n",
" <td>19.549695</td>\n",
" <td>1004033.0</td>\n",
" <td>8011.0</td>\n",
" <td>...</td>\n",
" <td>504369.0</td>\n",
" <td>134040.0</td>\n",
" <td>1.046978</td>\n",
" <td>16.0</td>\n",
" <td>39.954721</td>\n",
" <td>6</td>\n",
" <td>31</td>\n",
" <td>horizontal</td>\n",
" <td>0.352235</td>\n",
" <td>0.352235</td>\n",
" </tr>\n",
" <tr>\n",
" <th>131</th>\n",
" <td>4817586.0</td>\n",
" <td>15.737103</td>\n",
" <td>52.0</td>\n",
" <td>-142.0</td>\n",
" <td>504292.267286</td>\n",
" <td>134012.035242</td>\n",
" <td>15.698669</td>\n",
" <td>9.582079</td>\n",
" <td>1004062.0</td>\n",
" <td>8011.0</td>\n",
" <td>...</td>\n",
" <td>504291.0</td>\n",
" <td>134005.0</td>\n",
" <td>0.997558</td>\n",
" <td>30.0</td>\n",
" <td>32.402196</td>\n",
" <td>5</td>\n",
" <td>52</td>\n",
" <td>vertical</td>\n",
" <td>0.203341</td>\n",
" <td>0.203341</td>\n",
" </tr>\n",
" <tr>\n",
" <th>133</th>\n",
" <td>4817590.0</td>\n",
" <td>107.805268</td>\n",
" <td>42.0</td>\n",
" <td>128.0</td>\n",
" <td>504291.857602</td>\n",
" <td>134007.238999</td>\n",
" <td>55.805688</td>\n",
" <td>79.525784</td>\n",
" <td>1004062.0</td>\n",
" <td>8011.0</td>\n",
" <td>...</td>\n",
" <td>504291.0</td>\n",
" <td>134005.0</td>\n",
" <td>0.517653</td>\n",
" <td>30.0</td>\n",
" <td>349.441134</td>\n",
" <td>11</td>\n",
" <td>42</td>\n",
" <td>horizontal</td>\n",
" <td>0.400723</td>\n",
" <td>0.281990</td>\n",
" </tr>\n",
" <tr>\n",
" <th>135</th>\n",
" <td>4817592.0</td>\n",
" <td>166.696743</td>\n",
" <td>44.0</td>\n",
" <td>-52.0</td>\n",
" <td>504295.617156</td>\n",
" <td>134002.024478</td>\n",
" <td>56.562275</td>\n",
" <td>119.181308</td>\n",
" <td>1004062.0</td>\n",
" <td>8011.0</td>\n",
" <td>...</td>\n",
" <td>504291.0</td>\n",
" <td>134005.0</td>\n",
" <td>0.339312</td>\n",
" <td>30.0</td>\n",
" <td>349.441134</td>\n",
" <td>6</td>\n",
" <td>44</td>\n",
" <td>horizontal</td>\n",
" <td>0.700674</td>\n",
" <td>0.508708</td>\n",
" </tr>\n",
" <tr>\n",
" <th>137</th>\n",
" <td>4817594.0</td>\n",
" <td>21.341327</td>\n",
" <td>44.0</td>\n",
" <td>-142.0</td>\n",
" <td>504285.546035</td>\n",
" <td>134006.535637</td>\n",
" <td>17.605523</td>\n",
" <td>15.460501</td>\n",
" <td>1004062.0</td>\n",
" <td>8011.0</td>\n",
" <td>...</td>\n",
" <td>504291.0</td>\n",
" <td>134005.0</td>\n",
" <td>0.824950</td>\n",
" <td>30.0</td>\n",
" <td>349.441134</td>\n",
" <td>5</td>\n",
" <td>44</td>\n",
" <td>vertical</td>\n",
" <td>0.449831</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>138</th>\n",
" <td>4817595.0</td>\n",
" <td>7.320491</td>\n",
" <td>24.0</td>\n",
" <td>128.0</td>\n",
" <td>504287.311728</td>\n",
" <td>134009.157566</td>\n",
" <td>10.533612</td>\n",
" <td>6.664126</td>\n",
" <td>1004062.0</td>\n",
" <td>8011.0</td>\n",
" <td>...</td>\n",
" <td>504291.0</td>\n",
" <td>134005.0</td>\n",
" <td>1.438922</td>\n",
" <td>30.0</td>\n",
" <td>17.596906</td>\n",
" <td>4</td>\n",
" <td>24</td>\n",
" <td>vertical</td>\n",
" <td>0.437129</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>139</th>\n",
" <td>4817596.0</td>\n",
" <td>11.941720</td>\n",
" <td>24.0</td>\n",
" <td>128.0</td>\n",
" <td>504292.697300</td>\n",
" <td>134016.015514</td>\n",
" <td>14.222427</td>\n",
" <td>10.871010</td>\n",
" <td>1004062.0</td>\n",
" <td>8011.0</td>\n",
" <td>...</td>\n",
" <td>504291.0</td>\n",
" <td>134005.0</td>\n",
" <td>1.190986</td>\n",
" <td>30.0</td>\n",
" <td>17.596906</td>\n",
" <td>4</td>\n",
" <td>24</td>\n",
" <td>vertical</td>\n",
" <td>0.535936</td>\n",
" <td>0.267968</td>\n",
" </tr>\n",
" <tr>\n",
" <th>144</th>\n",
" <td>4817604.0</td>\n",
" <td>28.995697</td>\n",
" <td>32.0</td>\n",
" <td>49.0</td>\n",
" <td>504248.714875</td>\n",
" <td>134022.816832</td>\n",
" <td>23.386408</td>\n",
" <td>24.560885</td>\n",
" <td>1004069.0</td>\n",
" <td>8012.0</td>\n",
" <td>...</td>\n",
" <td>504254.0</td>\n",
" <td>134015.0</td>\n",
" <td>0.806548</td>\n",
" <td>28.0</td>\n",
" <td>61.764345</td>\n",
" <td>6</td>\n",
" <td>32</td>\n",
" <td>equal</td>\n",
" <td>0.331084</td>\n",
" <td>0.275903</td>\n",
" </tr>\n",
" <tr>\n",
" <th>145</th>\n",
" <td>4817605.0</td>\n",
" <td>26.436872</td>\n",
" <td>34.0</td>\n",
" <td>-131.0</td>\n",
" <td>504251.675595</td>\n",
" <td>134025.521354</td>\n",
" <td>22.737006</td>\n",
" <td>21.871817</td>\n",
" <td>1004069.0</td>\n",
" <td>8012.0</td>\n",
" <td>...</td>\n",
" <td>504254.0</td>\n",
" <td>134015.0</td>\n",
" <td>0.860049</td>\n",
" <td>28.0</td>\n",
" <td>61.764345</td>\n",
" <td>5</td>\n",
" <td>34</td>\n",
" <td>equal</td>\n",
" <td>0.302608</td>\n",
" <td>0.302608</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>156361</th>\n",
" <td>5124081.0</td>\n",
" <td>266.605425</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>505205.617439</td>\n",
" <td>121850.298615</td>\n",
" <td>86.079619</td>\n",
" <td>266.605425</td>\n",
" <td>1007588.0</td>\n",
" <td>8013.0</td>\n",
" <td>...</td>\n",
" <td>505200.0</td>\n",
" <td>121851.0</td>\n",
" <td>0.322873</td>\n",
" <td>11.0</td>\n",
" <td>266.605425</td>\n",
" <td>8</td>\n",
" <td>30</td>\n",
" <td>horizontal</td>\n",
" <td>0.327433</td>\n",
" <td>0.311841</td>\n",
" </tr>\n",
" <tr>\n",
" <th>156363</th>\n",
" <td>5124083.0</td>\n",
" <td>263.545062</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>505144.771970</td>\n",
" <td>121855.495639</td>\n",
" <td>86.673944</td>\n",
" <td>263.545062</td>\n",
" <td>1007482.0</td>\n",
" <td>8013.0</td>\n",
" <td>...</td>\n",
" <td>505140.0</td>\n",
" <td>121857.0</td>\n",
" <td>0.328877</td>\n",
" <td>17.0</td>\n",
" <td>263.545062</td>\n",
" <td>8</td>\n",
" <td>30</td>\n",
" <td>horizontal</td>\n",
" <td>0.325977</td>\n",
" <td>0.304947</td>\n",
" </tr>\n",
" <tr>\n",
" <th>156368</th>\n",
" <td>5124091.0</td>\n",
" <td>75.980910</td>\n",
" <td>37.0</td>\n",
" <td>39.0</td>\n",
" <td>505015.098230</td>\n",
" <td>121962.536676</td>\n",
" <td>31.455957</td>\n",
" <td>60.994226</td>\n",
" <td>1007458.0</td>\n",
" <td>8014.0</td>\n",
" <td>...</td>\n",
" <td>505018.0</td>\n",
" <td>121966.0</td>\n",
" <td>0.413998</td>\n",
" <td>18.0</td>\n",
" <td>135.538642</td>\n",
" <td>6</td>\n",
" <td>37</td>\n",
" <td>vertical</td>\n",
" <td>0.694911</td>\n",
" <td>0.168463</td>\n",
" </tr>\n",
" <tr>\n",
" <th>156369</th>\n",
" <td>5124092.0</td>\n",
" <td>75.983413</td>\n",
" <td>37.0</td>\n",
" <td>-141.0</td>\n",
" <td>505019.265222</td>\n",
" <td>121967.617780</td>\n",
" <td>31.456985</td>\n",
" <td>60.996623</td>\n",
" <td>1007458.0</td>\n",
" <td>8014.0</td>\n",
" <td>...</td>\n",
" <td>505018.0</td>\n",
" <td>121966.0</td>\n",
" <td>0.413998</td>\n",
" <td>18.0</td>\n",
" <td>135.538642</td>\n",
" <td>6</td>\n",
" <td>37</td>\n",
" <td>vertical</td>\n",
" <td>0.694889</td>\n",
" <td>0.189515</td>\n",
" </tr>\n",
" <tr>\n",
" <th>156374</th>\n",
" <td>5124098.0</td>\n",
" <td>10.187720</td>\n",
" <td>23.0</td>\n",
" <td>-134.0</td>\n",
" <td>505136.048480</td>\n",
" <td>121823.092968</td>\n",
" <td>13.694789</td>\n",
" <td>9.378436</td>\n",
" <td>1007538.0</td>\n",
" <td>8014.0</td>\n",
" <td>...</td>\n",
" <td>505140.0</td>\n",
" <td>121816.0</td>\n",
" <td>1.344245</td>\n",
" <td>16.0</td>\n",
" <td>49.931162</td>\n",
" <td>5</td>\n",
" <td>23</td>\n",
" <td>horizontal</td>\n",
" <td>0.157052</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>156388</th>\n",
" <td>5124117.0</td>\n",
" <td>116.551287</td>\n",
" <td>20.0</td>\n",
" <td>37.0</td>\n",
" <td>505212.306673</td>\n",
" <td>121944.341314</td>\n",
" <td>53.663493</td>\n",
" <td>109.837185</td>\n",
" <td>1007518.0</td>\n",
" <td>8014.0</td>\n",
" <td>...</td>\n",
" <td>505222.0</td>\n",
" <td>121943.0</td>\n",
" <td>0.460428</td>\n",
" <td>10.0</td>\n",
" <td>281.042520</td>\n",
" <td>7</td>\n",
" <td>20</td>\n",
" <td>vertical</td>\n",
" <td>0.658937</td>\n",
" <td>0.604026</td>\n",
" </tr>\n",
" <tr>\n",
" <th>156399</th>\n",
" <td>5124132.0</td>\n",
" <td>97.474823</td>\n",
" <td>18.0</td>\n",
" <td>37.0</td>\n",
" <td>505154.911718</td>\n",
" <td>121992.092114</td>\n",
" <td>41.600238</td>\n",
" <td>92.691874</td>\n",
" <td>1007515.0</td>\n",
" <td>8014.0</td>\n",
" <td>...</td>\n",
" <td>505158.0</td>\n",
" <td>121996.0</td>\n",
" <td>0.426779</td>\n",
" <td>19.0</td>\n",
" <td>218.441718</td>\n",
" <td>9</td>\n",
" <td>18</td>\n",
" <td>vertical</td>\n",
" <td>0.689409</td>\n",
" <td>0.689409</td>\n",
" </tr>\n",
" <tr>\n",
" <th>156401</th>\n",
" <td>5124138.0</td>\n",
" <td>30.082116</td>\n",
" <td>18.0</td>\n",
" <td>37.0</td>\n",
" <td>505156.643720</td>\n",
" <td>121986.481617</td>\n",
" <td>21.502608</td>\n",
" <td>28.604706</td>\n",
" <td>1007515.0</td>\n",
" <td>8014.0</td>\n",
" <td>...</td>\n",
" <td>505158.0</td>\n",
" <td>121996.0</td>\n",
" <td>0.714797</td>\n",
" <td>19.0</td>\n",
" <td>36.637903</td>\n",
" <td>5</td>\n",
" <td>18</td>\n",
" <td>vertical</td>\n",
" <td>0.585065</td>\n",
" <td>0.425502</td>\n",
" </tr>\n",
" <tr>\n",
" <th>156407</th>\n",
" <td>5124145.0</td>\n",
" <td>249.308311</td>\n",
" <td>1.0</td>\n",
" <td>37.0</td>\n",
" <td>505199.255195</td>\n",
" <td>121922.503240</td>\n",
" <td>77.354537</td>\n",
" <td>249.294867</td>\n",
" <td>1007519.0</td>\n",
" <td>8015.0</td>\n",
" <td>...</td>\n",
" <td>505199.0</td>\n",
" <td>121921.0</td>\n",
" <td>0.310277</td>\n",
" <td>12.0</td>\n",
" <td>249.270341</td>\n",
" <td>12</td>\n",
" <td>1</td>\n",
" <td>horizontal</td>\n",
" <td>0.770131</td>\n",
" <td>0.718789</td>\n",
" </tr>\n",
" <tr>\n",
" <th>156417</th>\n",
" <td>5124157.0</td>\n",
" <td>61.049862</td>\n",
" <td>35.0</td>\n",
" <td>38.0</td>\n",
" <td>505038.054617</td>\n",
" <td>121900.383583</td>\n",
" <td>31.229961</td>\n",
" <td>49.771623</td>\n",
" <td>3131586.0</td>\n",
" <td>8019.0</td>\n",
" <td>...</td>\n",
" <td>505040.0</td>\n",
" <td>121901.0</td>\n",
" <td>0.511548</td>\n",
" <td>17.0</td>\n",
" <td>119.125599</td>\n",
" <td>8</td>\n",
" <td>35</td>\n",
" <td>vertical</td>\n",
" <td>0.524162</td>\n",
" <td>0.524162</td>\n",
" </tr>\n",
" <tr>\n",
" <th>156442</th>\n",
" <td>5124184.0</td>\n",
" <td>152.955166</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>505138.741055</td>\n",
" <td>121751.371196</td>\n",
" <td>49.572093</td>\n",
" <td>152.955166</td>\n",
" <td>1007533.0</td>\n",
" <td>8014.0</td>\n",
" <td>...</td>\n",
" <td>505119.0</td>\n",
" <td>121780.0</td>\n",
" <td>0.324096</td>\n",
" <td>15.0</td>\n",
" <td>152.955166</td>\n",
" <td>4</td>\n",
" <td>30</td>\n",
" <td>vertical</td>\n",
" <td>0.344247</td>\n",
" <td>0.235537</td>\n",
" </tr>\n",
" <tr>\n",
" <th>156456</th>\n",
" <td>5124225.0</td>\n",
" <td>149.628056</td>\n",
" <td>24.0</td>\n",
" <td>118.0</td>\n",
" <td>507938.483195</td>\n",
" <td>121938.971036</td>\n",
" <td>47.207179</td>\n",
" <td>136.744127</td>\n",
" <td>1020465.0</td>\n",
" <td>8011.0</td>\n",
" <td>...</td>\n",
" <td>507934.0</td>\n",
" <td>121918.0</td>\n",
" <td>0.315497</td>\n",
" <td>8.0</td>\n",
" <td>229.185291</td>\n",
" <td>4</td>\n",
" <td>24</td>\n",
" <td>vertical</td>\n",
" <td>0.769909</td>\n",
" <td>0.727136</td>\n",
" </tr>\n",
" <tr>\n",
" <th>156457</th>\n",
" <td>5124226.0</td>\n",
" <td>100.481013</td>\n",
" <td>23.0</td>\n",
" <td>-62.0</td>\n",
" <td>507945.991866</td>\n",
" <td>121934.251075</td>\n",
" <td>42.236335</td>\n",
" <td>92.428410</td>\n",
" <td>1020465.0</td>\n",
" <td>8011.0</td>\n",
" <td>...</td>\n",
" <td>507934.0</td>\n",
" <td>121918.0</td>\n",
" <td>0.420341</td>\n",
" <td>8.0</td>\n",
" <td>229.185291</td>\n",
" <td>6</td>\n",
" <td>23</td>\n",
" <td>horizontal</td>\n",
" <td>0.684706</td>\n",
" <td>0.636936</td>\n",
" </tr>\n",
" <tr>\n",
" <th>156495</th>\n",
" <td>5124268.0</td>\n",
" <td>69.521653</td>\n",
" <td>26.0</td>\n",
" <td>127.0</td>\n",
" <td>507988.872644</td>\n",
" <td>121923.898204</td>\n",
" <td>41.662072</td>\n",
" <td>62.694983</td>\n",
" <td>1020473.0</td>\n",
" <td>8016.0</td>\n",
" <td>...</td>\n",
" <td>507988.0</td>\n",
" <td>121925.0</td>\n",
" <td>0.599268</td>\n",
" <td>5.0</td>\n",
" <td>138.925812</td>\n",
" <td>9</td>\n",
" <td>26</td>\n",
" <td>horizontal</td>\n",
" <td>0.460288</td>\n",
" <td>0.460288</td>\n",
" </tr>\n",
" <tr>\n",
" <th>156496</th>\n",
" <td>5124269.0</td>\n",
" <td>80.758005</td>\n",
" <td>26.0</td>\n",
" <td>-53.0</td>\n",
" <td>507992.817789</td>\n",
" <td>121921.257256</td>\n",
" <td>38.928120</td>\n",
" <td>72.825494</td>\n",
" <td>1020473.0</td>\n",
" <td>8016.0</td>\n",
" <td>...</td>\n",
" <td>507988.0</td>\n",
" <td>121925.0</td>\n",
" <td>0.482034</td>\n",
" <td>5.0</td>\n",
" <td>138.925812</td>\n",
" <td>6</td>\n",
" <td>26</td>\n",
" <td>horizontal</td>\n",
" <td>0.633993</td>\n",
" <td>0.614181</td>\n",
" </tr>\n",
" <tr>\n",
" <th>156502</th>\n",
" <td>5124275.0</td>\n",
" <td>33.715366</td>\n",
" <td>25.0</td>\n",
" <td>-155.0</td>\n",
" <td>507851.862589</td>\n",
" <td>121897.816540</td>\n",
" <td>27.906534</td>\n",
" <td>30.670579</td>\n",
" <td>1020460.0</td>\n",
" <td>8015.0</td>\n",
" <td>...</td>\n",
" <td>507851.0</td>\n",
" <td>121894.0</td>\n",
" <td>0.827710</td>\n",
" <td>6.0</td>\n",
" <td>256.684990</td>\n",
" <td>5</td>\n",
" <td>25</td>\n",
" <td>horizontal</td>\n",
" <td>0.284737</td>\n",
" <td>0.237281</td>\n",
" </tr>\n",
" <tr>\n",
" <th>156503</th>\n",
" <td>5124276.0</td>\n",
" <td>38.150126</td>\n",
" <td>25.0</td>\n",
" <td>25.0</td>\n",
" <td>507845.816019</td>\n",
" <td>121895.960950</td>\n",
" <td>28.228417</td>\n",
" <td>34.456133</td>\n",
" <td>1020460.0</td>\n",
" <td>8015.0</td>\n",
" <td>...</td>\n",
" <td>507851.0</td>\n",
" <td>121894.0</td>\n",
" <td>0.739930</td>\n",
" <td>6.0</td>\n",
" <td>256.684990</td>\n",
" <td>4</td>\n",
" <td>25</td>\n",
" <td>horizontal</td>\n",
" <td>0.419396</td>\n",
" <td>0.335517</td>\n",
" </tr>\n",
" <tr>\n",
" <th>156507</th>\n",
" <td>5124280.0</td>\n",
" <td>13.260158</td>\n",
" <td>24.0</td>\n",
" <td>-19.0</td>\n",
" <td>507852.909926</td>\n",
" <td>121900.448859</td>\n",
" <td>19.454339</td>\n",
" <td>12.143164</td>\n",
" <td>1020460.0</td>\n",
" <td>8015.0</td>\n",
" <td>...</td>\n",
" <td>507851.0</td>\n",
" <td>121894.0</td>\n",
" <td>1.467127</td>\n",
" <td>6.0</td>\n",
" <td>256.684990</td>\n",
" <td>4</td>\n",
" <td>24</td>\n",
" <td>horizontal</td>\n",
" <td>0.120662</td>\n",
" <td>0.120662</td>\n",
" </tr>\n",
" <tr>\n",
" <th>156508</th>\n",
" <td>5124281.0</td>\n",
" <td>12.849435</td>\n",
" <td>25.0</td>\n",
" <td>160.0</td>\n",
" <td>507852.228616</td>\n",
" <td>121902.124777</td>\n",
" <td>19.208987</td>\n",
" <td>11.620749</td>\n",
" <td>1020460.0</td>\n",
" <td>8015.0</td>\n",
" <td>...</td>\n",
" <td>507851.0</td>\n",
" <td>121894.0</td>\n",
" <td>1.494929</td>\n",
" <td>6.0</td>\n",
" <td>256.684990</td>\n",
" <td>4</td>\n",
" <td>25</td>\n",
" <td>horizontal</td>\n",
" <td>0.124519</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>156510</th>\n",
" <td>5124283.0</td>\n",
" <td>20.322154</td>\n",
" <td>30.0</td>\n",
" <td>-66.0</td>\n",
" <td>507863.633435</td>\n",
" <td>121905.138610</td>\n",
" <td>20.654033</td>\n",
" <td>17.628942</td>\n",
" <td>1020460.0</td>\n",
" <td>8015.0</td>\n",
" <td>...</td>\n",
" <td>507851.0</td>\n",
" <td>121894.0</td>\n",
" <td>1.016331</td>\n",
" <td>6.0</td>\n",
" <td>58.327437</td>\n",
" <td>4</td>\n",
" <td>30</td>\n",
" <td>equal</td>\n",
" <td>0.236195</td>\n",
" <td>0.157464</td>\n",
" </tr>\n",
" <tr>\n",
" <th>156512</th>\n",
" <td>5124285.0</td>\n",
" <td>23.152132</td>\n",
" <td>26.0</td>\n",
" <td>114.0</td>\n",
" <td>507860.241136</td>\n",
" <td>121906.680783</td>\n",
" <td>21.406529</td>\n",
" <td>20.826972</td>\n",
" <td>1020460.0</td>\n",
" <td>8015.0</td>\n",
" <td>...</td>\n",
" <td>507851.0</td>\n",
" <td>121894.0</td>\n",
" <td>0.924603</td>\n",
" <td>6.0</td>\n",
" <td>58.327437</td>\n",
" <td>4</td>\n",
" <td>26</td>\n",
" <td>horizontal</td>\n",
" <td>0.414649</td>\n",
" <td>0.345541</td>\n",
" </tr>\n",
" <tr>\n",
" <th>156516</th>\n",
" <td>5124291.0</td>\n",
" <td>90.925022</td>\n",
" <td>35.0</td>\n",
" <td>44.0</td>\n",
" <td>507943.410921</td>\n",
" <td>121877.913753</td>\n",
" <td>37.434216</td>\n",
" <td>74.778700</td>\n",
" <td>1020458.0</td>\n",
" <td>8011.0</td>\n",
" <td>...</td>\n",
" <td>507945.0</td>\n",
" <td>121879.0</td>\n",
" <td>0.411704</td>\n",
" <td>7.0</td>\n",
" <td>156.302014</td>\n",
" <td>6</td>\n",
" <td>35</td>\n",
" <td>equal</td>\n",
" <td>0.651086</td>\n",
" <td>0.580698</td>\n",
" </tr>\n",
" <tr>\n",
" <th>156549</th>\n",
" <td>5124362.0</td>\n",
" <td>119.658477</td>\n",
" <td>25.0</td>\n",
" <td>132.0</td>\n",
" <td>509833.292224</td>\n",
" <td>121883.708346</td>\n",
" <td>41.864123</td>\n",
" <td>108.376924</td>\n",
" <td>1018455.0</td>\n",
" <td>8011.0</td>\n",
" <td>...</td>\n",
" <td>509835.0</td>\n",
" <td>121889.0</td>\n",
" <td>0.349863</td>\n",
" <td>2.0</td>\n",
" <td>448.199438</td>\n",
" <td>4</td>\n",
" <td>25</td>\n",
" <td>vertical</td>\n",
" <td>0.802283</td>\n",
" <td>0.748798</td>\n",
" </tr>\n",
" <tr>\n",
" <th>156553</th>\n",
" <td>5124372.0</td>\n",
" <td>21.508865</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>509830.542020</td>\n",
" <td>121890.939403</td>\n",
" <td>19.144630</td>\n",
" <td>21.508865</td>\n",
" <td>1018455.0</td>\n",
" <td>8011.0</td>\n",
" <td>...</td>\n",
" <td>509835.0</td>\n",
" <td>121889.0</td>\n",
" <td>0.890081</td>\n",
" <td>2.0</td>\n",
" <td>28.198185</td>\n",
" <td>7</td>\n",
" <td>30</td>\n",
" <td>equal</td>\n",
" <td>0.128844</td>\n",
" <td>0.128844</td>\n",
" </tr>\n",
" <tr>\n",
" <th>156597</th>\n",
" <td>5124422.0</td>\n",
" <td>118.827342</td>\n",
" <td>33.0</td>\n",
" <td>-44.0</td>\n",
" <td>509777.061068</td>\n",
" <td>121984.581143</td>\n",
" <td>39.984208</td>\n",
" <td>99.826972</td>\n",
" <td>1018454.0</td>\n",
" <td>8011.0</td>\n",
" <td>...</td>\n",
" <td>509755.0</td>\n",
" <td>121973.0</td>\n",
" <td>0.336490</td>\n",
" <td>1.0</td>\n",
" <td>732.156993</td>\n",
" <td>5</td>\n",
" <td>33</td>\n",
" <td>vertical</td>\n",
" <td>0.807895</td>\n",
" <td>0.807895</td>\n",
" </tr>\n",
" <tr>\n",
" <th>156601</th>\n",
" <td>5124426.0</td>\n",
" <td>64.747340</td>\n",
" <td>45.0</td>\n",
" <td>-138.0</td>\n",
" <td>509791.644236</td>\n",
" <td>121764.305896</td>\n",
" <td>28.417197</td>\n",
" <td>45.662025</td>\n",
" <td>1018487.0</td>\n",
" <td>8015.0</td>\n",
" <td>...</td>\n",
" <td>509796.0</td>\n",
" <td>121759.0</td>\n",
" <td>0.438894</td>\n",
" <td>3.0</td>\n",
" <td>103.624105</td>\n",
" <td>4</td>\n",
" <td>45</td>\n",
" <td>horizontal</td>\n",
" <td>0.741343</td>\n",
" <td>0.247114</td>\n",
" </tr>\n",
" <tr>\n",
" <th>156619</th>\n",
" <td>5124450.0</td>\n",
" <td>58.985735</td>\n",
" <td>19.0</td>\n",
" <td>141.0</td>\n",
" <td>509914.886217</td>\n",
" <td>121818.670138</td>\n",
" <td>37.958737</td>\n",
" <td>55.913928</td>\n",
" <td>1018456.0</td>\n",
" <td>8014.0</td>\n",
" <td>...</td>\n",
" <td>509954.0</td>\n",
" <td>121782.0</td>\n",
" <td>0.643524</td>\n",
" <td>7.0</td>\n",
" <td>68.927176</td>\n",
" <td>5</td>\n",
" <td>19</td>\n",
" <td>horizontal</td>\n",
" <td>0.379753</td>\n",
" <td>0.352628</td>\n",
" </tr>\n",
" <tr>\n",
" <th>156630</th>\n",
" <td>5124463.0</td>\n",
" <td>17.508327</td>\n",
" <td>34.0</td>\n",
" <td>-22.0</td>\n",
" <td>510037.013096</td>\n",
" <td>121760.096891</td>\n",
" <td>18.884070</td>\n",
" <td>14.575574</td>\n",
" <td>1018458.0</td>\n",
" <td>8011.0</td>\n",
" <td>...</td>\n",
" <td>510019.0</td>\n",
" <td>121774.0</td>\n",
" <td>1.078577</td>\n",
" <td>7.0</td>\n",
" <td>24.601407</td>\n",
" <td>4</td>\n",
" <td>34</td>\n",
" <td>horizontal</td>\n",
" <td>0.365540</td>\n",
" <td>0.182770</td>\n",
" </tr>\n",
" <tr>\n",
" <th>156671</th>\n",
" <td>5124512.0</td>\n",
" <td>131.925651</td>\n",
" <td>29.0</td>\n",
" <td>121.0</td>\n",
" <td>512861.419320</td>\n",
" <td>121844.774678</td>\n",
" <td>55.702429</td>\n",
" <td>114.847781</td>\n",
" <td>1018654.0</td>\n",
" <td>8011.0</td>\n",
" <td>...</td>\n",
" <td>512862.0</td>\n",
" <td>121841.0</td>\n",
" <td>0.422226</td>\n",
" <td>2.0</td>\n",
" <td>236.648087</td>\n",
" <td>5</td>\n",
" <td>29</td>\n",
" <td>vertical</td>\n",
" <td>0.800451</td>\n",
" <td>0.739811</td>\n",
" </tr>\n",
" <tr>\n",
" <th>156677</th>\n",
" <td>5124518.0</td>\n",
" <td>34.768271</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>512851.492252</td>\n",
" <td>121838.457750</td>\n",
" <td>29.085365</td>\n",
" <td>34.768271</td>\n",
" <td>1018654.0</td>\n",
" <td>8011.0</td>\n",
" <td>...</td>\n",
" <td>512862.0</td>\n",
" <td>121841.0</td>\n",
" <td>0.836549</td>\n",
" <td>2.0</td>\n",
" <td>108.900435</td>\n",
" <td>6</td>\n",
" <td>30</td>\n",
" <td>vertical</td>\n",
" <td>0.119561</td>\n",
" <td>0.119561</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>37729 rows × 23 columns</p>\n",
"</div>"
],
"text/plain": [
" DF_UID FLAECHE NEIGUNG AUSRICHTUNG XCOORD \\\n",
"1 4817425.0 36.859836 37.0 33.0 503503.812619 \n",
"3 4817427.0 36.861447 37.0 -147.0 503510.594159 \n",
"8 4817433.0 69.216255 26.0 33.0 503510.917446 \n",
"19 4817445.0 9.973655 29.0 -55.0 503926.571766 \n",
"26 4817452.0 68.854261 35.0 -140.0 504222.101990 \n",
"27 4817453.0 52.296595 34.0 40.0 504219.058562 \n",
"33 4817464.0 78.771912 31.0 130.0 504150.396646 \n",
"40 4817471.0 73.524780 35.0 34.0 504039.884935 \n",
"48 4817483.0 100.571828 27.0 140.0 504182.850754 \n",
"52 4817487.0 107.363169 26.0 -50.0 504164.499411 \n",
"69 4817506.0 338.194772 32.0 -57.0 504118.320342 \n",
"74 4817511.0 20.907218 47.0 -147.0 504132.987332 \n",
"76 4817513.0 180.037771 33.0 -57.0 504131.757170 \n",
"86 4817534.0 69.050433 37.0 -145.0 504232.555744 \n",
"95 4817543.0 136.154298 26.0 -58.0 504216.156462 \n",
"104 4817553.0 299.453663 28.0 -47.0 504213.418431 \n",
"108 4817558.0 232.507194 28.0 113.0 504140.745470 \n",
"117 4817569.0 46.645324 59.0 47.0 504383.212030 \n",
"118 4817570.0 114.433767 40.0 -43.0 504390.817811 \n",
"119 4817571.0 46.644194 59.0 -133.0 504393.326128 \n",
"120 4817572.0 114.041009 41.0 137.0 504385.717010 \n",
"126 4817579.0 22.712083 31.0 135.0 504362.580721 \n",
"131 4817586.0 15.737103 52.0 -142.0 504292.267286 \n",
"133 4817590.0 107.805268 42.0 128.0 504291.857602 \n",
"135 4817592.0 166.696743 44.0 -52.0 504295.617156 \n",
"137 4817594.0 21.341327 44.0 -142.0 504285.546035 \n",
"138 4817595.0 7.320491 24.0 128.0 504287.311728 \n",
"139 4817596.0 11.941720 24.0 128.0 504292.697300 \n",
"144 4817604.0 28.995697 32.0 49.0 504248.714875 \n",
"145 4817605.0 26.436872 34.0 -131.0 504251.675595 \n",
"... ... ... ... ... ... \n",
"156361 5124081.0 266.605425 0.0 0.0 505205.617439 \n",
"156363 5124083.0 263.545062 0.0 0.0 505144.771970 \n",
"156368 5124091.0 75.980910 37.0 39.0 505015.098230 \n",
"156369 5124092.0 75.983413 37.0 -141.0 505019.265222 \n",
"156374 5124098.0 10.187720 23.0 -134.0 505136.048480 \n",
"156388 5124117.0 116.551287 20.0 37.0 505212.306673 \n",
"156399 5124132.0 97.474823 18.0 37.0 505154.911718 \n",
"156401 5124138.0 30.082116 18.0 37.0 505156.643720 \n",
"156407 5124145.0 249.308311 1.0 37.0 505199.255195 \n",
"156417 5124157.0 61.049862 35.0 38.0 505038.054617 \n",
"156442 5124184.0 152.955166 0.0 0.0 505138.741055 \n",
"156456 5124225.0 149.628056 24.0 118.0 507938.483195 \n",
"156457 5124226.0 100.481013 23.0 -62.0 507945.991866 \n",
"156495 5124268.0 69.521653 26.0 127.0 507988.872644 \n",
"156496 5124269.0 80.758005 26.0 -53.0 507992.817789 \n",
"156502 5124275.0 33.715366 25.0 -155.0 507851.862589 \n",
"156503 5124276.0 38.150126 25.0 25.0 507845.816019 \n",
"156507 5124280.0 13.260158 24.0 -19.0 507852.909926 \n",
"156508 5124281.0 12.849435 25.0 160.0 507852.228616 \n",
"156510 5124283.0 20.322154 30.0 -66.0 507863.633435 \n",
"156512 5124285.0 23.152132 26.0 114.0 507860.241136 \n",
"156516 5124291.0 90.925022 35.0 44.0 507943.410921 \n",
"156549 5124362.0 119.658477 25.0 132.0 509833.292224 \n",
"156553 5124372.0 21.508865 0.0 0.0 509830.542020 \n",
"156597 5124422.0 118.827342 33.0 -44.0 509777.061068 \n",
"156601 5124426.0 64.747340 45.0 -138.0 509791.644236 \n",
"156619 5124450.0 58.985735 19.0 141.0 509914.886217 \n",
"156630 5124463.0 17.508327 34.0 -22.0 510037.013096 \n",
"156671 5124512.0 131.925651 29.0 121.0 512861.419320 \n",
"156677 5124518.0 34.768271 0.0 0.0 512851.492252 \n",
"\n",
" YCOORD Shape_Length Shape_Area GWR_EGID GBAUP \\\n",
"1 134131.833522 28.208608 29.339500 1004090.0 8012.0 \n",
"3 134142.188986 28.210273 29.341346 1004090.0 8012.0 \n",
"8 134191.713704 45.633223 61.997846 295084893.0 8011.0 \n",
"19 134212.338837 14.288661 8.760702 1004089.0 8012.0 \n",
"26 134017.187739 31.767443 56.268749 1004049.0 8011.0 \n",
"27 134013.574920 29.327904 43.406040 1004049.0 8011.0 \n",
"33 134085.492644 32.609685 67.373176 1004073.0 8011.0 \n",
"40 134127.753162 40.713703 60.474674 1004075.0 8011.0 \n",
"48 134128.499894 41.247227 89.271304 1004060.0 8011.0 \n",
"52 134085.908714 40.126227 96.811374 1004058.0 8011.0 \n",
"69 134142.125054 89.124850 288.352570 1004078.0 8014.0 \n",
"74 134174.806150 20.892222 14.380937 1004078.0 8014.0 \n",
"76 134165.089431 53.979078 150.181533 1004078.0 8014.0 \n",
"86 134035.586526 37.131477 55.112486 1004070.0 8011.0 \n",
"95 134047.845046 46.060999 121.923272 1004071.0 8011.0 \n",
"104 134081.933731 71.637039 265.577565 1004055.0 8011.0 \n",
"108 134060.379545 67.568369 205.428267 1004050.0 8011.0 \n",
"117 134038.490596 29.044821 23.861811 1004034.0 8011.0 \n",
"118 134040.491507 40.761920 87.041610 1004034.0 8011.0 \n",
"119 134047.945689 29.044527 23.859602 1004034.0 8011.0 \n",
"120 134045.948402 40.689282 86.524609 1004034.0 8011.0 \n",
"126 134030.362133 23.779044 19.549695 1004033.0 8011.0 \n",
"131 134012.035242 15.698669 9.582079 1004062.0 8011.0 \n",
"133 134007.238999 55.805688 79.525784 1004062.0 8011.0 \n",
"135 134002.024478 56.562275 119.181308 1004062.0 8011.0 \n",
"137 134006.535637 17.605523 15.460501 1004062.0 8011.0 \n",
"138 134009.157566 10.533612 6.664126 1004062.0 8011.0 \n",
"139 134016.015514 14.222427 10.871010 1004062.0 8011.0 \n",
"144 134022.816832 23.386408 24.560885 1004069.0 8012.0 \n",
"145 134025.521354 22.737006 21.871817 1004069.0 8012.0 \n",
"... ... ... ... ... ... \n",
"156361 121850.298615 86.079619 266.605425 1007588.0 8013.0 \n",
"156363 121855.495639 86.673944 263.545062 1007482.0 8013.0 \n",
"156368 121962.536676 31.455957 60.994226 1007458.0 8014.0 \n",
"156369 121967.617780 31.456985 60.996623 1007458.0 8014.0 \n",
"156374 121823.092968 13.694789 9.378436 1007538.0 8014.0 \n",
"156388 121944.341314 53.663493 109.837185 1007518.0 8014.0 \n",
"156399 121992.092114 41.600238 92.691874 1007515.0 8014.0 \n",
"156401 121986.481617 21.502608 28.604706 1007515.0 8014.0 \n",
"156407 121922.503240 77.354537 249.294867 1007519.0 8015.0 \n",
"156417 121900.383583 31.229961 49.771623 3131586.0 8019.0 \n",
"156442 121751.371196 49.572093 152.955166 1007533.0 8014.0 \n",
"156456 121938.971036 47.207179 136.744127 1020465.0 8011.0 \n",
"156457 121934.251075 42.236335 92.428410 1020465.0 8011.0 \n",
"156495 121923.898204 41.662072 62.694983 1020473.0 8016.0 \n",
"156496 121921.257256 38.928120 72.825494 1020473.0 8016.0 \n",
"156502 121897.816540 27.906534 30.670579 1020460.0 8015.0 \n",
"156503 121895.960950 28.228417 34.456133 1020460.0 8015.0 \n",
"156507 121900.448859 19.454339 12.143164 1020460.0 8015.0 \n",
"156508 121902.124777 19.208987 11.620749 1020460.0 8015.0 \n",
"156510 121905.138610 20.654033 17.628942 1020460.0 8015.0 \n",
"156512 121906.680783 21.406529 20.826972 1020460.0 8015.0 \n",
"156516 121877.913753 37.434216 74.778700 1020458.0 8011.0 \n",
"156549 121883.708346 41.864123 108.376924 1018455.0 8011.0 \n",
"156553 121890.939403 19.144630 21.508865 1018455.0 8011.0 \n",
"156597 121984.581143 39.984208 99.826972 1018454.0 8011.0 \n",
"156601 121764.305896 28.417197 45.662025 1018487.0 8015.0 \n",
"156619 121818.670138 37.958737 55.913928 1018456.0 8014.0 \n",
"156630 121760.096891 18.884070 14.575574 1018458.0 8011.0 \n",
"156671 121844.774678 55.702429 114.847781 1018654.0 8011.0 \n",
"156677 121838.457750 29.085365 34.768271 1018654.0 8011.0 \n",
"\n",
" ... GKODX GKODY Shape_Ratio \\\n",
"1 ... 503507.0 134137.0 0.765294 \n",
"3 ... 503507.0 134137.0 0.765306 \n",
"8 ... 503512.0 134193.0 0.659285 \n",
"19 ... 503922.0 134215.0 1.432640 \n",
"26 ... 504220.0 134015.0 0.461372 \n",
"27 ... 504220.0 134015.0 0.560799 \n",
"33 ... 504151.0 134082.0 0.413976 \n",
"40 ... 504040.0 134129.0 0.553741 \n",
"48 ... 504185.0 134127.0 0.410127 \n",
"52 ... 504160.0 134089.0 0.373743 \n",
"69 ... 504101.0 134121.0 0.263531 \n",
"74 ... 504101.0 134121.0 0.999283 \n",
"76 ... 504101.0 134121.0 0.299821 \n",
"86 ... 504235.0 134032.0 0.537744 \n",
"95 ... 504213.0 134050.0 0.338300 \n",
"104 ... 504206.0 134087.0 0.239226 \n",
"108 ... 504146.0 134056.0 0.290608 \n",
"117 ... 504388.0 134043.0 0.622674 \n",
"118 ... 504388.0 134043.0 0.356205 \n",
"119 ... 504388.0 134043.0 0.622683 \n",
"120 ... 504388.0 134043.0 0.356795 \n",
"126 ... 504369.0 134040.0 1.046978 \n",
"131 ... 504291.0 134005.0 0.997558 \n",
"133 ... 504291.0 134005.0 0.517653 \n",
"135 ... 504291.0 134005.0 0.339312 \n",
"137 ... 504291.0 134005.0 0.824950 \n",
"138 ... 504291.0 134005.0 1.438922 \n",
"139 ... 504291.0 134005.0 1.190986 \n",
"144 ... 504254.0 134015.0 0.806548 \n",
"145 ... 504254.0 134015.0 0.860049 \n",
"... ... ... ... ... \n",
"156361 ... 505200.0 121851.0 0.322873 \n",
"156363 ... 505140.0 121857.0 0.328877 \n",
"156368 ... 505018.0 121966.0 0.413998 \n",
"156369 ... 505018.0 121966.0 0.413998 \n",
"156374 ... 505140.0 121816.0 1.344245 \n",
"156388 ... 505222.0 121943.0 0.460428 \n",
"156399 ... 505158.0 121996.0 0.426779 \n",
"156401 ... 505158.0 121996.0 0.714797 \n",
"156407 ... 505199.0 121921.0 0.310277 \n",
"156417 ... 505040.0 121901.0 0.511548 \n",
"156442 ... 505119.0 121780.0 0.324096 \n",
"156456 ... 507934.0 121918.0 0.315497 \n",
"156457 ... 507934.0 121918.0 0.420341 \n",
"156495 ... 507988.0 121925.0 0.599268 \n",
"156496 ... 507988.0 121925.0 0.482034 \n",
"156502 ... 507851.0 121894.0 0.827710 \n",
"156503 ... 507851.0 121894.0 0.739930 \n",
"156507 ... 507851.0 121894.0 1.467127 \n",
"156508 ... 507851.0 121894.0 1.494929 \n",
"156510 ... 507851.0 121894.0 1.016331 \n",
"156512 ... 507851.0 121894.0 0.924603 \n",
"156516 ... 507945.0 121879.0 0.411704 \n",
"156549 ... 509835.0 121889.0 0.349863 \n",
"156553 ... 509835.0 121889.0 0.890081 \n",
"156597 ... 509755.0 121973.0 0.336490 \n",
"156601 ... 509796.0 121759.0 0.438894 \n",
"156619 ... 509954.0 121782.0 0.643524 \n",
"156630 ... 510019.0 121774.0 1.078577 \n",
"156671 ... 512862.0 121841.0 0.422226 \n",
"156677 ... 512862.0 121841.0 0.836549 \n",
"\n",
" n_neighbors_100 Estim_build_area n_corners panel_tilt best_align \\\n",
"1 3.0 194.813319 4 37 equal \n",
"3 3.0 194.813319 4 37 horizontal \n",
"8 3.0 107.414054 5 26 horizontal \n",
"19 4.0 78.634747 3 29 horizontal \n",
"26 25.0 99.757951 5 35 horizontal \n",
"27 25.0 99.757951 5 34 horizontal \n",
"33 17.0 140.790186 5 31 vertical \n",
"40 7.0 119.554424 6 35 horizontal \n",
"48 13.0 170.407907 4 27 horizontal \n",
"52 17.0 232.571656 4 26 horizontal \n",
"69 12.0 1265.908399 6 32 horizontal \n",
"74 12.0 1265.908399 3 47 equal \n",
"76 12.0 1265.908399 7 33 horizontal \n",
"86 29.0 148.612823 8 37 horizontal \n",
"95 27.0 260.007501 5 26 vertical \n",
"104 21.0 686.905610 14 28 vertical \n",
"108 16.0 483.038711 10 28 horizontal \n",
"117 10.0 221.776847 3 59 equal \n",
"118 10.0 221.776847 4 40 vertical \n",
"119 10.0 221.776847 3 59 horizontal \n",
"120 10.0 221.776847 4 41 vertical \n",
"126 16.0 39.954721 6 31 horizontal \n",
"131 30.0 32.402196 5 52 vertical \n",
"133 30.0 349.441134 11 42 horizontal \n",
"135 30.0 349.441134 6 44 horizontal \n",
"137 30.0 349.441134 5 44 vertical \n",
"138 30.0 17.596906 4 24 vertical \n",
"139 30.0 17.596906 4 24 vertical \n",
"144 28.0 61.764345 6 32 equal \n",
"145 28.0 61.764345 5 34 equal \n",
"... ... ... ... ... ... \n",
"156361 11.0 266.605425 8 30 horizontal \n",
"156363 17.0 263.545062 8 30 horizontal \n",
"156368 18.0 135.538642 6 37 vertical \n",
"156369 18.0 135.538642 6 37 vertical \n",
"156374 16.0 49.931162 5 23 horizontal \n",
"156388 10.0 281.042520 7 20 vertical \n",
"156399 19.0 218.441718 9 18 vertical \n",
"156401 19.0 36.637903 5 18 vertical \n",
"156407 12.0 249.270341 12 1 horizontal \n",
"156417 17.0 119.125599 8 35 vertical \n",
"156442 15.0 152.955166 4 30 vertical \n",
"156456 8.0 229.185291 4 24 vertical \n",
"156457 8.0 229.185291 6 23 horizontal \n",
"156495 5.0 138.925812 9 26 horizontal \n",
"156496 5.0 138.925812 6 26 horizontal \n",
"156502 6.0 256.684990 5 25 horizontal \n",
"156503 6.0 256.684990 4 25 horizontal \n",
"156507 6.0 256.684990 4 24 horizontal \n",
"156508 6.0 256.684990 4 25 horizontal \n",
"156510 6.0 58.327437 4 30 equal \n",
"156512 6.0 58.327437 4 26 horizontal \n",
"156516 7.0 156.302014 6 35 equal \n",
"156549 2.0 448.199438 4 25 vertical \n",
"156553 2.0 28.198185 7 30 equal \n",
"156597 1.0 732.156993 5 33 vertical \n",
"156601 3.0 103.624105 4 45 horizontal \n",
"156619 7.0 68.927176 5 19 horizontal \n",
"156630 7.0 24.601407 4 34 horizontal \n",
"156671 2.0 236.648087 5 29 vertical \n",
"156677 2.0 108.900435 6 30 vertical \n",
"\n",
" panelled_area_ratio_ftr panelled_area_ratio_tgt \n",
"1 0.390669 0.173631 \n",
"3 0.390652 0.217029 \n",
"8 0.508551 0.277391 \n",
"19 0.160423 0.000000 \n",
"26 0.697125 0.697125 \n",
"27 0.734273 0.673084 \n",
"33 0.710913 0.406236 \n",
"40 0.609318 0.652841 \n",
"48 0.763633 0.493180 \n",
"52 0.834551 0.804745 \n",
"69 0.794808 0.553527 \n",
"74 0.229586 0.076529 \n",
"76 0.773171 0.479899 \n",
"86 0.625630 0.648801 \n",
"95 0.775591 0.587569 \n",
"104 0.774744 0.593080 \n",
"108 0.729440 0.633099 \n",
"117 0.343014 0.171507 \n",
"118 0.727058 0.531312 \n",
"119 0.343022 0.102907 \n",
"120 0.729562 0.505081 \n",
"126 0.352235 0.352235 \n",
"131 0.203341 0.203341 \n",
"133 0.400723 0.281990 \n",
"135 0.700674 0.508708 \n",
"137 0.449831 0.000000 \n",
"138 0.437129 0.000000 \n",
"139 0.535936 0.267968 \n",
"144 0.331084 0.275903 \n",
"145 0.302608 0.302608 \n",
"... ... ... \n",
"156361 0.327433 0.311841 \n",
"156363 0.325977 0.304947 \n",
"156368 0.694911 0.168463 \n",
"156369 0.694889 0.189515 \n",
"156374 0.157052 0.000000 \n",
"156388 0.658937 0.604026 \n",
"156399 0.689409 0.689409 \n",
"156401 0.585065 0.425502 \n",
"156407 0.770131 0.718789 \n",
"156417 0.524162 0.524162 \n",
"156442 0.344247 0.235537 \n",
"156456 0.769909 0.727136 \n",
"156457 0.684706 0.636936 \n",
"156495 0.460288 0.460288 \n",
"156496 0.633993 0.614181 \n",
"156502 0.284737 0.237281 \n",
"156503 0.419396 0.335517 \n",
"156507 0.120662 0.120662 \n",
"156508 0.124519 0.000000 \n",
"156510 0.236195 0.157464 \n",
"156512 0.414649 0.345541 \n",
"156516 0.651086 0.580698 \n",
"156549 0.802283 0.748798 \n",
"156553 0.128844 0.128844 \n",
"156597 0.807895 0.807895 \n",
"156601 0.741343 0.247114 \n",
"156619 0.379753 0.352628 \n",
"156630 0.365540 0.182770 \n",
"156671 0.800451 0.739811 \n",
"156677 0.119561 0.119561 \n",
"\n",
"[37729 rows x 23 columns]"
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
- "TRN_data"
+ "TRN_data.head()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## SAVE AS CSV"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [],
"source": [
"TRN_data.to_csv('/Users/alinawalch/Documents/EPFL/data/rooftops/TRN_panelled_area.csv', index = False)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Get additional info on number of BUILDINGS"
]
},
- {
- "cell_type": "code",
- "execution_count": 16,
- "metadata": {},
- "outputs": [],
- "source": [
- "training_roofs_w_building = TRN_data.merge(gva_shp.loc[:,['DF_UID', 'SB_UUID']], on = 'DF_UID', how = 'left')"
- ]
- },
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Total number of considered buildings in Geneva (by SB_UUID): 19174\n",
"Total number of considered buildings in Geneva (by GWR_EGID): 15919\n"
]
}
],
"source": [
- "print('Total number of considered buildings in Geneva (by SB_UUID): %d' %len(training_roofs_w_building.SB_UUID.unique()) )\n",
- "print('Total number of considered buildings in Geneva (by GWR_EGID): %d' %len(training_roofs_w_building.GWR_EGID.unique()) )"
+ "print('Total number of considered buildings in Geneva (by SB_UUID): %d' %len(TRN_data.SB_UUID.unique()) )\n",
+ "print('Total number of considered buildings in Geneva (by GWR_EGID): %d' %len(TRN_data.GWR_EGID.unique()) )"
]
}
],
"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": "3.7.3"
+ "version": "3.6.1"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
diff --git a/Hourly_PV_public/Physical_potential/Temperature/max_temperature_MMH.ipynb b/Hourly_PV_public/Physical_potential/Temperature/max_temperature_MMH.ipynb
index 5c4a82a..91c7477 100644
--- a/Hourly_PV_public/Physical_potential/Temperature/max_temperature_MMH.ipynb
+++ b/Hourly_PV_public/Physical_potential/Temperature/max_temperature_MMH.ipynb
@@ -1,9020 +1,1004 @@
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"import xarray as xr\n",
"import pandas as pd\n",
"\n",
"from pvlib import pvsystem\n",
"\n",
"import os\n",
"import time\n",
"import util\n",
" \n",
"%matplotlib notebook\n",
"import matplotlib.pyplot as plt"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
- "### Check range of $G_t$"
+ "### Create monthly-mean-hourly temperature data"
]
},
{
"cell_type": "code",
- "execution_count": 2,
+ "execution_count": 64,
"metadata": {},
"outputs": [],
"source": [
- "fp = '/scratch/walch/workspace_tilted_irrad/PV_all_interp.nc'\n",
- "PV_hourly = xr.open_mfdataset( fp, chunks = {'DF_UID' : 100000} )"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 3,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<xarray.Dataset>\n",
- "Dimensions: (DF_UID: 9639231, timestamp: 146)\n",
- "Coordinates:\n",
- " * timestamp (timestamp) datetime64[ns] 2001-01-15T08:00:00 ... 2001-12-15T15:00:00\n",
- " * DF_UID (DF_UID) int64 1 2 3 4 ... 9890021 9890022 9890023\n",
- "Data variables:\n",
- " tilted_irradiance (DF_UID, timestamp) float64 dask.array<shape=(9639231, 146), chunksize=(100000, 146)>\n",
- " panelled_area (DF_UID) float64 dask.array<shape=(9639231,), chunksize=(100000,)>\n",
- " tilted_area (DF_UID) float64 dask.array<shape=(9639231,), chunksize=(100000,)>\n",
- " available_area (DF_UID) float64 dask.array<shape=(9639231,), chunksize=(100000,)>\n",
- " efficiency float64 ...\n",
- " performance_factor float64 ...\n",
- " pv_potential (DF_UID, timestamp) float64 dask.array<shape=(9639231, 146), chunksize=(100000, 146)>\n",
- " yearly_kWh_m2 (DF_UID) float64 dask.array<shape=(9639231,), chunksize=(100000,)>\n",
- " yearly_PV_kWh (DF_UID) float64 dask.array<shape=(9639231,), chunksize=(100000,)>\n",
- " yearly_PV_all_area (DF_UID) float64 dask.array<shape=(9639231,), chunksize=(100000,)>"
- ]
- },
- "execution_count": 3,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "PV_hourly"
+ "max_T = xr.open_mfdataset('/work/hyenergy/raw/MeteoSwiss_satellite/raw_data/temperature_max/TmaxD_ch01r.swisscors_20*.nc').TmaxD.load()\n"
]
},
{
"cell_type": "code",
- "execution_count": 4,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "array(1002.4908246549828)"
- ]
- },
- "execution_count": 4,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "PV_hourly.tilted_irradiance.max().values"
- ]
- },
- {
- "cell_type": "markdown",
+ "execution_count": 120,
"metadata": {},
+ "outputs": [],
"source": [
- "### Check range of temperature"
+ "# get max_T for our range of data (maximum Temperature per month, taking the average across 12 years)\n",
+ "year_sel = max_T.sel(time = slice('2004', '2015')).to_dataset()"
]
},
{
"cell_type": "code",
- "execution_count": 64,
+ "execution_count": 121,
"metadata": {},
"outputs": [],
"source": [
- "max_T = xr.open_mfdataset('/work/hyenergy/raw/MeteoSwiss_satellite/raw_data/temperature_max/TmaxD_ch01r.swisscors_20*.nc').TmaxD.load()\n"
+ "year_sel['month'] = year_sel.time.dt.month"
]
},
{
"cell_type": "code",
- "execution_count": 65,
+ "execution_count": 122,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
- "array(-16.48746605682373)"
+ "<xarray.Dataset>\n",
+ "Dimensions: (chx: 370, chy: 240, time: 4383)\n",
+ "Coordinates:\n",
+ " * chx (chx) float64 4.745e+05 4.755e+05 4.765e+05 ... 8.425e+05 8.435e+05\n",
+ " * chy (chy) float64 6.45e+04 6.55e+04 6.65e+04 ... 3.025e+05 3.035e+05\n",
+ " lon (chy, chx) float32 5.82685 5.83969 5.85253 ... 10.6785 10.6919\n",
+ " lat (chy, chx) float32 45.7206 45.7208 45.721 ... 47.8369 47.8366\n",
+ " * time (time) datetime64[ns] 2004-01-01 2004-01-02 ... 2015-12-31\n",
+ "Data variables:\n",
+ " TmaxD (time, chy, chx) float32 nan nan nan nan nan ... nan nan nan nan\n",
+ " month (time) int64 1 1 1 1 1 1 1 1 1 1 ... 12 12 12 12 12 12 12 12 12 12"
]
},
- "execution_count": 65,
+ "execution_count": 122,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
- "max_T.quantile(0.001).values"
+ "year_sel"
]
},
{
"cell_type": "code",
- "execution_count": 7,
+ "execution_count": 123,
"metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "array(33.862671474456874)"
- ]
- },
- "execution_count": 7,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "outputs": [],
"source": [
- "max_T.quantile(0.999).values"
+ "daily_data = year_sel.groupby('time.dayofyear').median(['time'])"
]
},
{
"cell_type": "code",
- "execution_count": 33,
+ "execution_count": 148,
"metadata": {},
"outputs": [
{
- "name": "stdout",
+ "name": "stderr",
"output_type": "stream",
"text": [
- "-35.1317024230957\n",
- "46.538177490234375\n"
+ "/home/walch/miniconda3/envs/py3/lib/python3.6/site-packages/xarray/core/nanops.py:161: RuntimeWarning: Mean of empty slice\n",
+ " return np.nanmean(a, axis=axis, dtype=dtype)\n"
]
}
],
"source": [
- "print(max_T.min().values)\n",
- "print(max_T.max().values)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 3,
- "metadata": {},
- "outputs": [],
- "source": [
- "min_T = xr.open_mfdataset('/work/hyenergy/raw/MeteoSwiss_satellite/raw_data/temperature_min/TminD_ch01r.swisscors_20*.nc').TminD # .load()\n"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 6,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "array(-23.631393720626832)"
- ]
- },
- "execution_count": 6,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "min_T.quantile(0.001).values"
+ "T_max_avg = daily_data.groupby('month').mean(['dayofyear']).TmaxD\n",
+ "T_max_std = daily_data.groupby('month').std( ['dayofyear']).TmaxD"
]
},
{
"cell_type": "code",
- "execution_count": 4,
+ "execution_count": 152,
"metadata": {},
"outputs": [],
"source": [
- "T_diff = max_T - min_T"
+ "T_max_mmd = T_max_avg.to_dataset()\n",
+ "T_max_mmd['stddev'] = T_max_std"
]
},
{
"cell_type": "code",
- "execution_count": 5,
+ "execution_count": 153,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
- "<xarray.DataArray (time: 6575, chy: 240, chx: 370)>\n",
- "dask.array<shape=(6575, 240, 370), dtype=float32, chunksize=(366, 240, 370)>\n",
+ "<xarray.Dataset>\n",
+ "Dimensions: (chx: 370, chy: 240, month: 12)\n",
"Coordinates:\n",
" * chx (chx) float64 4.745e+05 4.755e+05 4.765e+05 ... 8.425e+05 8.435e+05\n",
" * chy (chy) float64 6.45e+04 6.55e+04 6.65e+04 ... 3.025e+05 3.035e+05\n",
" lon (chy, chx) float32 5.82685 5.83969 5.85253 ... 10.6785 10.6919\n",
" lat (chy, chx) float32 45.7206 45.7208 45.721 ... 47.8369 47.8366\n",
- " * time (time) datetime64[ns] 2000-01-01 2000-01-02 ... 2017-12-31"
- ]
- },
- "execution_count": 5,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "T_diff"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 6,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "array(8.099149703979492, dtype=float32)"
- ]
- },
- "execution_count": 6,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "T_diff.mean().values"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 7,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "array(3.4837684631347656, dtype=float32)"
+ " * month (month) float64 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0\n",
+ "Data variables:\n",
+ " TmaxD (month, chy, chx) float32 nan nan nan nan nan ... nan nan nan nan\n",
+ " stddev (month, chy, chx) float32 nan nan nan nan nan ... nan nan nan nan"
]
},
- "execution_count": 7,
+ "execution_count": 153,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
- "T_diff.std().values"
+ "T_max_mmd"
]
},
{
"cell_type": "code",
- "execution_count": 65,
+ "execution_count": 156,
"metadata": {},
"outputs": [],
"source": [
- "T_values = max_T.values.flatten()\n",
- "T_values = T_values[~np.isnan(T_values)]"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 66,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "array([ 3.47477555, 3.60009646, 3.77452803, ..., 10.73526192,\n",
- " 10.71866512, 10.89078522], dtype=float32)"
- ]
- },
- "execution_count": 66,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "T_values"
+ "T_max_mmd.to_netcdf('/work/hyenergy/output/solar_potential/technical_potential/Tmax_surface_mmd.nc')"
]
},
{
"cell_type": "code",
- "execution_count": 67,
- "metadata": {},
+ "execution_count": 107,
+ "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\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
"\n",
"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
" // object with the appropriate methods. Currently this is a non binary\n",
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
" ws.close = function() {\n",
" comm.close()\n",
" };\n",
" ws.send = function(m) {\n",
" //console.log('sending', m);\n",
" comm.send(m);\n",
" };\n",
" // Register the callback with on_msg.\n",
" comm.on_msg(function(msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
" // Pass the mpl event to the overriden (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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\" 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\" width=\"640\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
- }
- ],
- "source": [
- "plt.figure()\n",
- "hist = plt.hist(T_values, range=(T_range[0], T_range[-1]+1), bins = len(T_range), density = True)\n",
- "plt.xlabel('Max daily temperature')\n",
- "plt.ylabel('Occurences')\n",
- "plt.show()"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Create monthly-mean-hourly temperature data"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 120,
- "metadata": {},
- "outputs": [],
- "source": [
- "# get max_T for our range of data (maximum Temperature per month, taking the average across 12 years)\n",
- "year_sel = max_T.sel(time = slice('2004', '2015')).to_dataset()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 121,
- "metadata": {},
- "outputs": [],
- "source": [
- "year_sel['month'] = year_sel.time.dt.month"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 122,
- "metadata": {},
- "outputs": [
+ },
{
"data": {
"text/plain": [
- "<xarray.Dataset>\n",
- "Dimensions: (chx: 370, chy: 240, time: 4383)\n",
- "Coordinates:\n",
- " * chx (chx) float64 4.745e+05 4.755e+05 4.765e+05 ... 8.425e+05 8.435e+05\n",
- " * chy (chy) float64 6.45e+04 6.55e+04 6.65e+04 ... 3.025e+05 3.035e+05\n",
- " lon (chy, chx) float32 5.82685 5.83969 5.85253 ... 10.6785 10.6919\n",
- " lat (chy, chx) float32 45.7206 45.7208 45.721 ... 47.8369 47.8366\n",
- " * time (time) datetime64[ns] 2004-01-01 2004-01-02 ... 2015-12-31\n",
- "Data variables:\n",
- " TmaxD (time, chy, chx) float32 nan nan nan nan nan ... nan nan nan nan\n",
- " month (time) int64 1 1 1 1 1 1 1 1 1 1 ... 12 12 12 12 12 12 12 12 12 12"
+ "[]"
]
},
- "execution_count": 122,
+ "execution_count": 107,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
- "year_sel"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 123,
- "metadata": {},
- "outputs": [],
- "source": [
- "daily_data = year_sel.groupby('time.dayofyear').median(['time'])"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 148,
- "metadata": {},
- "outputs": [
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "/home/walch/miniconda3/envs/py3/lib/python3.6/site-packages/xarray/core/nanops.py:161: RuntimeWarning: Mean of empty slice\n",
- " return np.nanmean(a, axis=axis, dtype=dtype)\n"
- ]
- }
- ],
- "source": [
- "T_max_avg = daily_data.groupby('month').mean(['dayofyear']).TmaxD\n",
- "T_max_std = daily_data.groupby('month').std( ['dayofyear']).TmaxD"
+ "plt.figure()\n",
+ "T_max_mmd.TmaxD.sel(month = 7).plot()\n",
+ "plt.axis('equal')\n",
+ "plt.plot()"
]
- },
- {
- "cell_type": "code",
- "execution_count": 152,
- "metadata": {},
- "outputs": [],
- "source": [
- "T_max_mmd = T_max_avg.to_dataset()\n",
- "T_max_mmd['stddev'] = T_max_std"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 153,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<xarray.Dataset>\n",
- "Dimensions: (chx: 370, chy: 240, month: 12)\n",
- "Coordinates:\n",
- " * chx (chx) float64 4.745e+05 4.755e+05 4.765e+05 ... 8.425e+05 8.435e+05\n",
- " * chy (chy) float64 6.45e+04 6.55e+04 6.65e+04 ... 3.025e+05 3.035e+05\n",
- " lon (chy, chx) float32 5.82685 5.83969 5.85253 ... 10.6785 10.6919\n",
- " lat (chy, chx) float32 45.7206 45.7208 45.721 ... 47.8369 47.8366\n",
- " * month (month) float64 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0\n",
- "Data variables:\n",
- " TmaxD (month, chy, chx) float32 nan nan nan nan nan ... nan nan nan nan\n",
- " stddev (month, chy, chx) float32 nan nan nan nan nan ... nan nan nan nan"
- ]
- },
- "execution_count": 153,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "T_max_mmd"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 156,
- "metadata": {},
- "outputs": [],
- "source": [
- "T_max_mmd.to_netcdf('/work/hyenergy/output/solar_potential/technical_potential/Tmax_surface_mmd.nc')"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 107,
- "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\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
- "\n",
- "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
- " // Create a \"websocket\"-like object which calls the given IPython comm\n",
- " // object with the appropriate methods. Currently this is a non binary\n",
- " // socket, so there is still some room for performance tuning.\n",
- " var ws = {};\n",
- "\n",
- " ws.close = function() {\n",
- " comm.close()\n",
- " };\n",
- " ws.send = function(m) {\n",
- " //console.log('sending', m);\n",
- " comm.send(m);\n",
- " };\n",
- " // Register the callback with on_msg.\n",
- " comm.on_msg(function(msg) {\n",
- " //console.log('receiving', msg['content']['data'], msg);\n",
- " // Pass the mpl event to the overriden (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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\" 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- },
- "execution_count": 107,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "plt.figure()\n",
- "T_max_mmd.TmaxD.sel(month = 7).plot()\n",
- "plt.axis('equal')\n",
- "plt.plot()"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Find average parameters of suitable models\n",
- "1. Retrieve all models from the CEC module database\n",
- "2. Select all models which are mono-crystalline (>70% of panels in CH use mono, see Buffat et al.)\n",
- "3. Select only \"residential\"-style modules (60 cells)\n",
- "4. Obtain average P_dc0 and gamma_pdc for these panels"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 32,
- "metadata": {},
- "outputs": [],
- "source": [
- "models = pvsystem.retrieve_sam('CECMod').T"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 33,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/html": [
- "<div>\n",
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- " vertical-align: middle;\n",
- " }\n",
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- " .dataframe tbody tr th {\n",
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- " }\n",
- "\n",
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- "<table border=\"1\" class=\"dataframe\">\n",
- " <thead>\n",
- " <tr style=\"text-align: right;\">\n",
- " <th></th>\n",
- " <th>BIPV</th>\n",
- " <th>Date</th>\n",
- " <th>T_NOCT</th>\n",
- " <th>A_c</th>\n",
- " <th>N_s</th>\n",
- " <th>I_sc_ref</th>\n",
- " <th>V_oc_ref</th>\n",
- " <th>I_mp_ref</th>\n",
- " <th>V_mp_ref</th>\n",
- " <th>alpha_sc</th>\n",
- " <th>...</th>\n",
- " <th>a_ref</th>\n",
- " <th>I_L_ref</th>\n",
- " <th>I_o_ref</th>\n",
- " <th>R_s</th>\n",
- " <th>R_sh_ref</th>\n",
- " <th>Adjust</th>\n",
- " <th>gamma_r</th>\n",
- " <th>Version</th>\n",
- " <th>PTC</th>\n",
- " <th>Technology</th>\n",
- " </tr>\n",
- " </thead>\n",
- " <tbody>\n",
- " <tr>\n",
- " <th>1Soltech_1STH_215_P</th>\n",
- " <td>N</td>\n",
- " <td>10/7/2010</td>\n",
- " <td>47.4</td>\n",
- " <td>1.567</td>\n",
- " <td>60</td>\n",
- " <td>7.84</td>\n",
- " <td>36.3</td>\n",
- " <td>7.35</td>\n",
- " <td>29</td>\n",
- " <td>0.007997</td>\n",
- " <td>...</td>\n",
- " <td>1.6413</td>\n",
- " <td>7.843</td>\n",
- " <td>1.936e-09</td>\n",
- " <td>0.359</td>\n",
- " <td>839.4</td>\n",
- " <td>16.5</td>\n",
- " <td>-0.495</td>\n",
- " <td>MM107</td>\n",
- " <td>189.4</td>\n",
- " <td>Multi-c-Si</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>1Soltech_1STH_220_P</th>\n",
- " <td>N</td>\n",
- " <td>10/4/2010</td>\n",
- " <td>47.4</td>\n",
- " <td>1.567</td>\n",
- " <td>60</td>\n",
- " <td>7.97</td>\n",
- " <td>36.6</td>\n",
- " <td>7.47</td>\n",
- " <td>29.3</td>\n",
- " <td>0.008129</td>\n",
- " <td>...</td>\n",
- " <td>1.6572</td>\n",
- " <td>7.974</td>\n",
- " <td>2.03e-09</td>\n",
- " <td>0.346</td>\n",
- " <td>751.03</td>\n",
- " <td>16.8</td>\n",
- " <td>-0.495</td>\n",
- " <td>MM107</td>\n",
- " <td>194</td>\n",
- " <td>Multi-c-Si</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>1Soltech_1STH_225_P</th>\n",
- " <td>N</td>\n",
- " <td>10/4/2010</td>\n",
- " <td>47.4</td>\n",
- " <td>1.567</td>\n",
- " <td>60</td>\n",
- " <td>8.09</td>\n",
- " <td>36.9</td>\n",
- " <td>7.58</td>\n",
- " <td>29.6</td>\n",
- " <td>0.008252</td>\n",
- " <td>...</td>\n",
- " <td>1.6732</td>\n",
- " <td>8.094</td>\n",
- " <td>2.126e-09</td>\n",
- " <td>0.334</td>\n",
- " <td>670.65</td>\n",
- " <td>17.1</td>\n",
- " <td>-0.495</td>\n",
- " <td>MM107</td>\n",
- " <td>198.5</td>\n",
- " <td>Multi-c-Si</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>1Soltech_1STH_230_P</th>\n",
- " <td>N</td>\n",
- " <td>10/4/2010</td>\n",
- " <td>47.4</td>\n",
- " <td>1.567</td>\n",
- " <td>60</td>\n",
- " <td>8.18</td>\n",
- " <td>37.1</td>\n",
- " <td>7.65</td>\n",
- " <td>29.9</td>\n",
- " <td>0.008344</td>\n",
- " <td>...</td>\n",
- " <td>1.6888</td>\n",
- " <td>8.185</td>\n",
- " <td>2.332e-09</td>\n",
- " <td>0.311</td>\n",
- " <td>462.56</td>\n",
- " <td>17.9</td>\n",
- " <td>-0.495</td>\n",
- " <td>MM107</td>\n",
- " <td>203.1</td>\n",
- " <td>Multi-c-Si</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>1Soltech_1STH_235_WH</th>\n",
- " <td>N</td>\n",
- " <td>3/4/2010</td>\n",
- " <td>49.9</td>\n",
- " <td>1.635</td>\n",
- " <td>60</td>\n",
- " <td>8.54</td>\n",
- " <td>37</td>\n",
- " <td>8.02</td>\n",
- " <td>29.3</td>\n",
- " <td>0.00743</td>\n",
- " <td>...</td>\n",
- " <td>1.6292</td>\n",
- " <td>8.543</td>\n",
- " <td>1.166e-09</td>\n",
- " <td>0.383</td>\n",
- " <td>1257.84</td>\n",
- " <td>8.7</td>\n",
- " <td>-0.482</td>\n",
- " <td>MM107</td>\n",
- " <td>205.1</td>\n",
- " <td>Mono-c-Si</td>\n",
- " </tr>\n",
- " </tbody>\n",
- "</table>\n",
- "<p>5 rows × 21 columns</p>\n",
- "</div>"
- ],
- "text/plain": [
- " BIPV Date T_NOCT A_c N_s I_sc_ref V_oc_ref \\\n",
- "1Soltech_1STH_215_P N 10/7/2010 47.4 1.567 60 7.84 36.3 \n",
- "1Soltech_1STH_220_P N 10/4/2010 47.4 1.567 60 7.97 36.6 \n",
- "1Soltech_1STH_225_P N 10/4/2010 47.4 1.567 60 8.09 36.9 \n",
- "1Soltech_1STH_230_P N 10/4/2010 47.4 1.567 60 8.18 37.1 \n",
- "1Soltech_1STH_235_WH N 3/4/2010 49.9 1.635 60 8.54 37 \n",
- "\n",
- " I_mp_ref V_mp_ref alpha_sc ... a_ref I_L_ref \\\n",
- "1Soltech_1STH_215_P 7.35 29 0.007997 ... 1.6413 7.843 \n",
- "1Soltech_1STH_220_P 7.47 29.3 0.008129 ... 1.6572 7.974 \n",
- "1Soltech_1STH_225_P 7.58 29.6 0.008252 ... 1.6732 8.094 \n",
- "1Soltech_1STH_230_P 7.65 29.9 0.008344 ... 1.6888 8.185 \n",
- "1Soltech_1STH_235_WH 8.02 29.3 0.00743 ... 1.6292 8.543 \n",
- "\n",
- " I_o_ref R_s R_sh_ref Adjust gamma_r Version PTC \\\n",
- "1Soltech_1STH_215_P 1.936e-09 0.359 839.4 16.5 -0.495 MM107 189.4 \n",
- "1Soltech_1STH_220_P 2.03e-09 0.346 751.03 16.8 -0.495 MM107 194 \n",
- "1Soltech_1STH_225_P 2.126e-09 0.334 670.65 17.1 -0.495 MM107 198.5 \n",
- "1Soltech_1STH_230_P 2.332e-09 0.311 462.56 17.9 -0.495 MM107 203.1 \n",
- "1Soltech_1STH_235_WH 1.166e-09 0.383 1257.84 8.7 -0.482 MM107 205.1 \n",
- "\n",
- " Technology \n",
- "1Soltech_1STH_215_P Multi-c-Si \n",
- "1Soltech_1STH_220_P Multi-c-Si \n",
- "1Soltech_1STH_225_P Multi-c-Si \n",
- "1Soltech_1STH_230_P Multi-c-Si \n",
- "1Soltech_1STH_235_WH Mono-c-Si \n",
- "\n",
- "[5 rows x 21 columns]"
- ]
- },
- "execution_count": 33,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "models.head()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 34,
- "metadata": {},
- "outputs": [],
- "source": [
- "models['gamma_r'] = models['gamma_r'].astype(float)\n",
- "models['PTC'] = models['PTC'].astype(float)\n",
- "# models['Date'] = pd.to_datetime(models['Date'], format = '%m/%d/%Y')"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 35,
- "metadata": {},
- "outputs": [],
- "source": [
- "suitable_models = models[(models.Technology == 'Mono-c-Si') & (models.N_s == 60)]"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 36,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/html": [
- "<div>\n",
- "<style scoped>\n",
- " .dataframe tbody tr th:only-of-type {\n",
- " vertical-align: middle;\n",
- " }\n",
- "\n",
- " .dataframe tbody tr th {\n",
- " vertical-align: top;\n",
- " }\n",
- "\n",
- " .dataframe thead th {\n",
- " text-align: right;\n",
- " }\n",
- "</style>\n",
- "<table border=\"1\" class=\"dataframe\">\n",
- " <thead>\n",
- " <tr style=\"text-align: right;\">\n",
- " <th></th>\n",
- " <th>BIPV</th>\n",
- " <th>Date</th>\n",
- " <th>T_NOCT</th>\n",
- " <th>A_c</th>\n",
- " <th>N_s</th>\n",
- " <th>I_sc_ref</th>\n",
- " <th>V_oc_ref</th>\n",
- " <th>I_mp_ref</th>\n",
- " <th>V_mp_ref</th>\n",
- " <th>alpha_sc</th>\n",
- " <th>...</th>\n",
- " <th>a_ref</th>\n",
- " <th>I_L_ref</th>\n",
- " <th>I_o_ref</th>\n",
- " <th>R_s</th>\n",
- " <th>R_sh_ref</th>\n",
- " <th>Adjust</th>\n",
- " <th>gamma_r</th>\n",
- " <th>Version</th>\n",
- " <th>PTC</th>\n",
- " <th>Technology</th>\n",
- " </tr>\n",
- " </thead>\n",
- " <tbody>\n",
- " <tr>\n",
- " <th>1Soltech_1STH_235_WH</th>\n",
- " <td>N</td>\n",
- " <td>3/4/2010</td>\n",
- " <td>49.9</td>\n",
- " <td>1.635</td>\n",
- " <td>60</td>\n",
- " <td>8.54</td>\n",
- " <td>37</td>\n",
- " <td>8.02</td>\n",
- " <td>29.3</td>\n",
- " <td>0.00743</td>\n",
- " <td>...</td>\n",
- " <td>1.6292</td>\n",
- " <td>8.543</td>\n",
- " <td>1.166e-09</td>\n",
- " <td>0.383</td>\n",
- " <td>1257.84</td>\n",
- " <td>8.7</td>\n",
- " <td>-0.482</td>\n",
- " <td>MM107</td>\n",
- " <td>205.1</td>\n",
- " <td>Mono-c-Si</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>1Soltech_1STH_240_WH</th>\n",
- " <td>N</td>\n",
- " <td>3/4/2010</td>\n",
- " <td>49.9</td>\n",
- " <td>1.635</td>\n",
- " <td>60</td>\n",
- " <td>8.58</td>\n",
- " <td>37.1</td>\n",
- " <td>8.07</td>\n",
- " <td>29.7</td>\n",
- " <td>0.007465</td>\n",
- " <td>...</td>\n",
- " <td>1.6425</td>\n",
- " <td>8.582</td>\n",
- " <td>1.325e-09</td>\n",
- " <td>0.335</td>\n",
- " <td>1463.82</td>\n",
- " <td>9.8</td>\n",
- " <td>-0.482</td>\n",
- " <td>MM107</td>\n",
- " <td>209.6</td>\n",
- " <td>Mono-c-Si</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>1Soltech_1STH_245_WH</th>\n",
- " <td>N</td>\n",
- " <td>3/4/2010</td>\n",
- " <td>49.9</td>\n",
- " <td>1.635</td>\n",
- " <td>60</td>\n",
- " <td>8.62</td>\n",
- " <td>37.2</td>\n",
- " <td>8.1</td>\n",
- " <td>30.2</td>\n",
- " <td>0.007499</td>\n",
- " <td>...</td>\n",
- " <td>1.6617</td>\n",
- " <td>8.623</td>\n",
- " <td>1.623e-09</td>\n",
- " <td>0.272</td>\n",
- " <td>724.06</td>\n",
- " <td>11.6</td>\n",
- " <td>-0.482</td>\n",
- " <td>MM107</td>\n",
- " <td>214.1</td>\n",
- " <td>Mono-c-Si</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>1Soltech_1STH_250_WH</th>\n",
- " <td>N</td>\n",
- " <td>3/4/2010</td>\n",
- " <td>49.9</td>\n",
- " <td>1.635</td>\n",
- " <td>60</td>\n",
- " <td>8.66</td>\n",
- " <td>37.3</td>\n",
- " <td>8.15</td>\n",
- " <td>30.7</td>\n",
- " <td>0.007534</td>\n",
- " <td>...</td>\n",
- " <td>1.6783</td>\n",
- " <td>8.662</td>\n",
- " <td>1.919e-09</td>\n",
- " <td>0.211</td>\n",
- " <td>760.07</td>\n",
- " <td>13.1</td>\n",
- " <td>-0.482</td>\n",
- " <td>MM107</td>\n",
- " <td>218.6</td>\n",
- " <td>Mono-c-Si</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>1Soltech_1STH_FRL_4H_245_M60_BLK</th>\n",
- " <td>N</td>\n",
- " <td>1/14/2013</td>\n",
- " <td>48.3</td>\n",
- " <td>1.668</td>\n",
- " <td>60</td>\n",
- " <td>8.81</td>\n",
- " <td>38.3</td>\n",
- " <td>8.06</td>\n",
- " <td>30.2</td>\n",
- " <td>0.006167</td>\n",
- " <td>...</td>\n",
- " <td>1.6351</td>\n",
- " <td>8.844</td>\n",
- " <td>5.7e-10</td>\n",
- " <td>0.421</td>\n",
- " <td>109.31</td>\n",
- " <td>6.502</td>\n",
- " <td>-0.453</td>\n",
- " <td>NRELv1</td>\n",
- " <td>217.7</td>\n",
- " <td>Mono-c-Si</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>1Soltech_1STH_FRL_4H_250_M60_BLK</th>\n",
- " <td>N</td>\n",
- " <td>1/14/2013</td>\n",
- " <td>48.3</td>\n",
- " <td>1.668</td>\n",
- " <td>60</td>\n",
- " <td>8.85</td>\n",
- " <td>38.4</td>\n",
- " <td>8.11</td>\n",
- " <td>30.7</td>\n",
- " <td>0.006195</td>\n",
- " <td>...</td>\n",
- " <td>1.6517</td>\n",
- " <td>8.878</td>\n",
- " <td>6.83e-10</td>\n",
- " <td>0.358</td>\n",
- " <td>111.51</td>\n",
- " <td>8.03</td>\n",
- " <td>-0.453</td>\n",
- " <td>NRELv1</td>\n",
- " <td>222.3</td>\n",
- " <td>Mono-c-Si</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>1Soltech_1STH_FRL_4H_255_M60_BLK</th>\n",
- " <td>N</td>\n",
- " <td>1/14/2013</td>\n",
- " <td>48.3</td>\n",
- " <td>1.668</td>\n",
- " <td>60</td>\n",
- " <td>8.89</td>\n",
- " <td>38.46</td>\n",
- " <td>8.16</td>\n",
- " <td>31.24</td>\n",
- " <td>0.006223</td>\n",
- " <td>...</td>\n",
- " <td>1.6688</td>\n",
- " <td>8.912</td>\n",
- " <td>8.39e-10</td>\n",
- " <td>0.285</td>\n",
- " <td>113.34</td>\n",
- " <td>9.818</td>\n",
- " <td>-0.453</td>\n",
- " <td>NRELv1</td>\n",
- " <td>226.9</td>\n",
- " <td>Mono-c-Si</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>1Soltech_1STH_FRL_4H_260_M60_BLK</th>\n",
- " <td>N</td>\n",
- " <td>1/14/2013</td>\n",
- " <td>48.3</td>\n",
- " <td>1.668</td>\n",
- " <td>60</td>\n",
- " <td>8.93</td>\n",
- " <td>38.6</td>\n",
- " <td>8.21</td>\n",
- " <td>31.6</td>\n",
- " <td>0.006251</td>\n",
- " <td>...</td>\n",
- " <td>1.6811</td>\n",
- " <td>8.949</td>\n",
- " <td>9.2e-10</td>\n",
- " <td>0.249</td>\n",
- " <td>117.56</td>\n",
- " <td>10.6</td>\n",
- " <td>-0.453</td>\n",
- " <td>NRELv1</td>\n",
- " <td>231.4</td>\n",
- " <td>Mono-c-Si</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>APOS_Energy_AS220</th>\n",
- " <td>N</td>\n",
- " <td>3/29/2010</td>\n",
- " <td>47.8</td>\n",
- " <td>1.659</td>\n",
- " <td>60</td>\n",
- " <td>8.28</td>\n",
- " <td>36.63</td>\n",
- " <td>7.62</td>\n",
- " <td>29.08</td>\n",
- " <td>0.007118</td>\n",
- " <td>...</td>\n",
- " <td>1.5181</td>\n",
- " <td>8.307</td>\n",
- " <td>2.661e-10</td>\n",
- " <td>0.41</td>\n",
- " <td>127.31</td>\n",
- " <td>24.3</td>\n",
- " <td>-0.425</td>\n",
- " <td>MM107</td>\n",
- " <td>197.0</td>\n",
- " <td>Mono-c-Si</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>APOS_Energy_AS225</th>\n",
- " <td>N</td>\n",
- " <td>3/29/2010</td>\n",
- " <td>47.8</td>\n",
- " <td>1.659</td>\n",
- " <td>60</td>\n",
- " <td>8.34</td>\n",
- " <td>36.99</td>\n",
- " <td>7.69</td>\n",
- " <td>29.31</td>\n",
- " <td>0.00717</td>\n",
- " <td>...</td>\n",
- " <td>1.5291</td>\n",
- " <td>8.365</td>\n",
- " <td>2.527e-10</td>\n",
- " <td>0.419</td>\n",
- " <td>138.1</td>\n",
- " <td>23.7</td>\n",
- " <td>-0.425</td>\n",
- " <td>MM107</td>\n",
- " <td>201.6</td>\n",
- " <td>Mono-c-Si</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>APOS_Energy_AS230</th>\n",
- " <td>N</td>\n",
- " <td>3/29/2010</td>\n",
- " <td>47.8</td>\n",
- " <td>1.659</td>\n",
- " <td>60</td>\n",
- " <td>8.46</td>\n",
- " <td>37.11</td>\n",
- " <td>7.82</td>\n",
- " <td>29.42</td>\n",
- " <td>0.007276</td>\n",
- " <td>...</td>\n",
- " <td>1.533</td>\n",
- " <td>8.483</td>\n",
- " <td>2.526e-10</td>\n",
- " <td>0.412</td>\n",
- " <td>151.47</td>\n",
- " <td>23.5</td>\n",
- " <td>-0.425</td>\n",
- " <td>MM107</td>\n",
- " <td>206.1</td>\n",
- " <td>Mono-c-Si</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>APOS_Energy_AS235</th>\n",
- " <td>N</td>\n",
- " <td>3/29/2010</td>\n",
- " <td>47.8</td>\n",
- " <td>1.659</td>\n",
- " <td>60</td>\n",
- " <td>8.55</td>\n",
- " <td>37.34</td>\n",
- " <td>7.86</td>\n",
- " <td>29.76</td>\n",
- " <td>0.007353</td>\n",
- " <td>...</td>\n",
- " <td>1.5517</td>\n",
- " <td>8.578</td>\n",
- " <td>2.927e-10</td>\n",
- " <td>0.387</td>\n",
- " <td>119.65</td>\n",
- " <td>24.9</td>\n",
- " <td>-0.425</td>\n",
- " <td>MM107</td>\n",
- " <td>210.7</td>\n",
- " <td>Mono-c-Si</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>APOS_Energy_AS240</th>\n",
- " <td>N</td>\n",
- " <td>3/29/2010</td>\n",
- " <td>47.8</td>\n",
- " <td>1.659</td>\n",
- " <td>60</td>\n",
- " <td>8.63</td>\n",
- " <td>37.52</td>\n",
- " <td>7.95</td>\n",
- " <td>30.05</td>\n",
- " <td>0.007422</td>\n",
- " <td>...</td>\n",
- " <td>1.5616</td>\n",
- " <td>8.655</td>\n",
- " <td>3.074e-10</td>\n",
- " <td>0.363</td>\n",
- " <td>126.69</td>\n",
- " <td>25.3</td>\n",
- " <td>-0.425</td>\n",
- " <td>MM107</td>\n",
- " <td>215.4</td>\n",
- " <td>Mono-c-Si</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>AU_Optronics_PM060M00_250</th>\n",
- " <td>N</td>\n",
- " <td>11/1/2013</td>\n",
- " <td>47.3</td>\n",
- " <td>1.611</td>\n",
- " <td>60</td>\n",
- " <td>8.66</td>\n",
- " <td>37.86</td>\n",
- " <td>8.22</td>\n",
- " <td>30.82</td>\n",
- " <td>0.005145</td>\n",
- " <td>...</td>\n",
- " <td>1.5635</td>\n",
- " <td>8.753</td>\n",
- " <td>2.64e-10</td>\n",
- " <td>0.293</td>\n",
- " <td>392.21</td>\n",
- " <td>18.48</td>\n",
- " <td>-0.437</td>\n",
- " <td>NRELv1</td>\n",
- " <td>224.6</td>\n",
- " <td>Mono-c-Si</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>AU_Optronics_PM060M00_255</th>\n",
- " <td>N</td>\n",
- " <td>11/1/2013</td>\n",
- " <td>47.3</td>\n",
- " <td>1.611</td>\n",
- " <td>60</td>\n",
- " <td>8.72</td>\n",
- " <td>37.92</td>\n",
- " <td>8.34</td>\n",
- " <td>30.86</td>\n",
- " <td>0.005181</td>\n",
- " <td>...</td>\n",
- " <td>1.5592</td>\n",
- " <td>8.808</td>\n",
- " <td>2.41e-10</td>\n",
- " <td>0.294</td>\n",
- " <td>3072.79</td>\n",
- " <td>17.53</td>\n",
- " <td>-0.437</td>\n",
- " <td>NRELv1</td>\n",
- " <td>229.2</td>\n",
- " <td>Mono-c-Si</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>AU_Optronics_PM060M00_260</th>\n",
- " <td>N</td>\n",
- " <td>11/1/2013</td>\n",
- " <td>47.3</td>\n",
- " <td>1.611</td>\n",
- " <td>60</td>\n",
- " <td>8.78</td>\n",
- " <td>37.98</td>\n",
- " <td>8.46</td>\n",
- " <td>30.91</td>\n",
- " <td>0.005216</td>\n",
- " <td>...</td>\n",
- " <td>1.5631</td>\n",
- " <td>8.959</td>\n",
- " <td>2.5e-10</td>\n",
- " <td>0.289</td>\n",
- " <td>915.51</td>\n",
- " <td>17.74</td>\n",
- " <td>-0.437</td>\n",
- " <td>NRELv1</td>\n",
- " <td>233.8</td>\n",
- " <td>Mono-c-Si</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>AU_Optronics_PM060M00_265</th>\n",
- " <td>N</td>\n",
- " <td>11/1/2013</td>\n",
- " <td>47.3</td>\n",
- " <td>1.611</td>\n",
- " <td>60</td>\n",
- " <td>8.84</td>\n",
- " <td>38.04</td>\n",
- " <td>8.54</td>\n",
- " <td>30.96</td>\n",
- " <td>0.005252</td>\n",
- " <td>...</td>\n",
- " <td>1.5634</td>\n",
- " <td>9.019</td>\n",
- " <td>2.44e-10</td>\n",
- " <td>0.288</td>\n",
- " <td>3154.03</td>\n",
- " <td>17.43</td>\n",
- " <td>-0.437</td>\n",
- " <td>NRELv1</td>\n",
- " <td>238.5</td>\n",
- " <td>Mono-c-Si</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>AU_Optronics_PM060M00_270</th>\n",
- " <td>N</td>\n",
- " <td>7/1/2014</td>\n",
- " <td>46.5</td>\n",
- " <td>1.611</td>\n",
- " <td>60</td>\n",
- " <td>9.01</td>\n",
- " <td>38.5</td>\n",
- " <td>8.5</td>\n",
- " <td>31.8</td>\n",
- " <td>0.005721</td>\n",
- " <td>...</td>\n",
- " <td>1.6407</td>\n",
- " <td>9.013</td>\n",
- " <td>5.77e-10</td>\n",
- " <td>0.216</td>\n",
- " <td>674.93</td>\n",
- " <td>15.7</td>\n",
- " <td>-0.454</td>\n",
- " <td>NRELv1</td>\n",
- " <td>243.1</td>\n",
- " <td>Mono-c-Si</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>AU_Optronics_PM060M00_275</th>\n",
- " <td>N</td>\n",
- " <td>7/1/2014</td>\n",
- " <td>46.5</td>\n",
- " <td>1.611</td>\n",
- " <td>60</td>\n",
- " <td>9.03</td>\n",
- " <td>38.7</td>\n",
- " <td>8.52</td>\n",
- " <td>32.3</td>\n",
- " <td>0.005734</td>\n",
- " <td>...</td>\n",
- " <td>1.6589</td>\n",
- " <td>9.033</td>\n",
- " <td>6.63e-10</td>\n",
- " <td>0.171</td>\n",
- " <td>590.38</td>\n",
- " <td>17</td>\n",
- " <td>-0.454</td>\n",
- " <td>NRELv1</td>\n",
- " <td>247.8</td>\n",
- " <td>Mono-c-Si</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>AU_Optronics_PM060M00_280</th>\n",
- " <td>N</td>\n",
- " <td>7/1/2014</td>\n",
- " <td>46.5</td>\n",
- " <td>1.611</td>\n",
- " <td>60</td>\n",
- " <td>9.06</td>\n",
- " <td>38.9</td>\n",
- " <td>8.57</td>\n",
- " <td>32.7</td>\n",
- " <td>0.005753</td>\n",
- " <td>...</td>\n",
- " <td>1.6718</td>\n",
- " <td>9.061</td>\n",
- " <td>7.08e-10</td>\n",
- " <td>0.14</td>\n",
- " <td>880.22</td>\n",
- " <td>17.58</td>\n",
- " <td>-0.454</td>\n",
- " <td>NRELv1</td>\n",
- " <td>252.4</td>\n",
- " <td>Mono-c-Si</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>AU_Optronics_PM060M00_285</th>\n",
- " <td>N</td>\n",
- " <td>7/1/2014</td>\n",
- " <td>46.5</td>\n",
- " <td>1.611</td>\n",
- " <td>60</td>\n",
- " <td>9.08</td>\n",
- " <td>39.2</td>\n",
- " <td>8.59</td>\n",
- " <td>33.2</td>\n",
- " <td>0.005766</td>\n",
- " <td>...</td>\n",
- " <td>1.6918</td>\n",
- " <td>9.081</td>\n",
- " <td>7.81e-10</td>\n",
- " <td>0.107</td>\n",
- " <td>789.79</td>\n",
- " <td>18.51</td>\n",
- " <td>-0.454</td>\n",
- " <td>NRELv1</td>\n",
- " <td>257.1</td>\n",
- " <td>Mono-c-Si</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>AU_Optronics_PM060M00_290</th>\n",
- " <td>N</td>\n",
- " <td>7/1/2014</td>\n",
- " <td>46.5</td>\n",
- " <td>1.611</td>\n",
- " <td>60</td>\n",
- " <td>9.11</td>\n",
- " <td>39.5</td>\n",
- " <td>8.61</td>\n",
- " <td>33.7</td>\n",
- " <td>0.005785</td>\n",
- " <td>...</td>\n",
- " <td>1.7128</td>\n",
- " <td>9.111</td>\n",
- " <td>8.73e-10</td>\n",
- " <td>0.074</td>\n",
- " <td>591.61</td>\n",
- " <td>19.55</td>\n",
- " <td>-0.454</td>\n",
- " <td>NRELv1</td>\n",
- " <td>261.7</td>\n",
- " <td>Mono-c-Si</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>AU_Optronics_PM060M01_250</th>\n",
- " <td>N</td>\n",
- " <td>6/2/2014</td>\n",
- " <td>47.3</td>\n",
- " <td>1.611</td>\n",
- " <td>60</td>\n",
- " <td>8.66</td>\n",
- " <td>37.86</td>\n",
- " <td>8.22</td>\n",
- " <td>30.8</td>\n",
- " <td>0.005145</td>\n",
- " <td>...</td>\n",
- " <td>1.5635</td>\n",
- " <td>8.753</td>\n",
- " <td>2.64e-10</td>\n",
- " <td>0.293</td>\n",
- " <td>392.21</td>\n",
- " <td>18.48</td>\n",
- " <td>-0.437</td>\n",
- " <td>NRELv1</td>\n",
- " <td>224.6</td>\n",
- " <td>Mono-c-Si</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>AU_Optronics_PM060M01_255</th>\n",
- " <td>N</td>\n",
- " <td>6/2/2014</td>\n",
- " <td>47.3</td>\n",
- " <td>1.611</td>\n",
- " <td>60</td>\n",
- " <td>8.72</td>\n",
- " <td>37.92</td>\n",
- " <td>8.34</td>\n",
- " <td>30.9</td>\n",
- " <td>0.005181</td>\n",
- " <td>...</td>\n",
- " <td>1.5592</td>\n",
- " <td>8.808</td>\n",
- " <td>2.41e-10</td>\n",
- " <td>0.294</td>\n",
- " <td>3072.79</td>\n",
- " <td>17.53</td>\n",
- " <td>-0.437</td>\n",
- " <td>NRELv1</td>\n",
- " <td>229.2</td>\n",
- " <td>Mono-c-Si</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>AU_Optronics_PM060M01_260</th>\n",
- " <td>N</td>\n",
- " <td>6/2/2014</td>\n",
- " <td>47.3</td>\n",
- " <td>1.611</td>\n",
- " <td>60</td>\n",
- " <td>8.78</td>\n",
- " <td>37.98</td>\n",
- " <td>8.46</td>\n",
- " <td>30.9</td>\n",
- " <td>0.005216</td>\n",
- " <td>...</td>\n",
- " <td>1.5631</td>\n",
- " <td>8.959</td>\n",
- " <td>2.5e-10</td>\n",
- " <td>0.289</td>\n",
- " <td>915.51</td>\n",
- " <td>17.74</td>\n",
- " <td>-0.437</td>\n",
- " <td>NRELv1</td>\n",
- " <td>233.8</td>\n",
- " <td>Mono-c-Si</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>AU_Optronics_PM060M01_265</th>\n",
- " <td>N</td>\n",
- " <td>6/2/2014</td>\n",
- " <td>47.3</td>\n",
- " <td>1.611</td>\n",
- " <td>60</td>\n",
- " <td>8.84</td>\n",
- " <td>38.04</td>\n",
- " <td>8.54</td>\n",
- " <td>31</td>\n",
- " <td>0.005252</td>\n",
- " <td>...</td>\n",
- " <td>1.5634</td>\n",
- " <td>9.019</td>\n",
- " <td>2.44e-10</td>\n",
- " <td>0.288</td>\n",
- " <td>3154.03</td>\n",
- " <td>17.43</td>\n",
- " <td>-0.437</td>\n",
- " <td>NRELv1</td>\n",
- " <td>238.5</td>\n",
- " <td>Mono-c-Si</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>AU_Optronics_PM060M01_270</th>\n",
- " <td>N</td>\n",
- " <td>7/1/2014</td>\n",
- " <td>46.5</td>\n",
- " <td>1.611</td>\n",
- " <td>60</td>\n",
- " <td>9.01</td>\n",
- " <td>38.5</td>\n",
- " <td>8.5</td>\n",
- " <td>31.8</td>\n",
- " <td>0.005721</td>\n",
- " <td>...</td>\n",
- " <td>1.6407</td>\n",
- " <td>9.013</td>\n",
- " <td>5.77e-10</td>\n",
- " <td>0.216</td>\n",
- " <td>674.93</td>\n",
- " <td>15.7</td>\n",
- " <td>-0.454</td>\n",
- " <td>NRELv1</td>\n",
- " <td>243.1</td>\n",
- " <td>Mono-c-Si</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>AU_Optronics_PM060M01_275</th>\n",
- " <td>N</td>\n",
- " <td>7/1/2014</td>\n",
- " <td>46.5</td>\n",
- " <td>1.611</td>\n",
- " <td>60</td>\n",
- " <td>9.03</td>\n",
- " <td>38.7</td>\n",
- " <td>8.52</td>\n",
- " <td>32.3</td>\n",
- " <td>0.005734</td>\n",
- " <td>...</td>\n",
- " <td>1.6589</td>\n",
- " <td>9.033</td>\n",
- " <td>6.63e-10</td>\n",
- " <td>0.171</td>\n",
- " <td>590.38</td>\n",
- " <td>17</td>\n",
- " <td>-0.454</td>\n",
- " <td>NRELv1</td>\n",
- " <td>247.8</td>\n",
- " <td>Mono-c-Si</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>AU_Optronics_PM060M01_280</th>\n",
- " <td>N</td>\n",
- " <td>7/1/2014</td>\n",
- " <td>46.5</td>\n",
- " <td>1.611</td>\n",
- " <td>60</td>\n",
- " <td>9.06</td>\n",
- " <td>38.9</td>\n",
- " <td>8.57</td>\n",
- " <td>32.7</td>\n",
- " <td>0.005753</td>\n",
- " <td>...</td>\n",
- " <td>1.6718</td>\n",
- " <td>9.061</td>\n",
- " <td>7.08e-10</td>\n",
- " <td>0.14</td>\n",
- " <td>880.22</td>\n",
- " <td>17.58</td>\n",
- " <td>-0.454</td>\n",
- " <td>NRELv1</td>\n",
- " <td>252.4</td>\n",
- " <td>Mono-c-Si</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>AU_Optronics_PM060M01_285</th>\n",
- " <td>N</td>\n",
- " <td>7/1/2014</td>\n",
- " <td>46.5</td>\n",
- " <td>1.611</td>\n",
- " <td>60</td>\n",
- " <td>9.08</td>\n",
- " <td>39.2</td>\n",
- " <td>8.59</td>\n",
- " <td>33.2</td>\n",
- " <td>0.005766</td>\n",
- " <td>...</td>\n",
- " <td>1.6918</td>\n",
- " <td>9.081</td>\n",
- " <td>7.81e-10</td>\n",
- " <td>0.107</td>\n",
- " <td>789.79</td>\n",
- " <td>18.51</td>\n",
- " <td>-0.454</td>\n",
- " <td>NRELv1</td>\n",
- " <td>257.1</td>\n",
- " <td>Mono-c-Si</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>alfasolar_alfasolar_M6L60_240</th>\n",
- " <td>N</td>\n",
- " <td>4/2/2013</td>\n",
- " <td>44.5</td>\n",
- " <td>1.6</td>\n",
- " <td>60</td>\n",
- " <td>8.61</td>\n",
- " <td>37.41</td>\n",
- " <td>7.9</td>\n",
- " <td>30.43</td>\n",
- " <td>0.002962</td>\n",
- " <td>...</td>\n",
- " <td>1.5697</td>\n",
- " <td>8.634</td>\n",
- " <td>3.7e-10</td>\n",
- " <td>0.294</td>\n",
- " <td>106.59</td>\n",
- " <td>9.256</td>\n",
- " <td>-0.456</td>\n",
- " <td>NRELv1</td>\n",
- " <td>217.5</td>\n",
- " <td>Mono-c-Si</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>alfasolar_alfasolar_M6L60_245</th>\n",
- " <td>N</td>\n",
- " <td>4/2/2013</td>\n",
- " <td>44.5</td>\n",
- " <td>1.6</td>\n",
- " <td>60</td>\n",
- " <td>8.66</td>\n",
- " <td>37.58</td>\n",
- " <td>8.03</td>\n",
- " <td>30.55</td>\n",
- " <td>0.002979</td>\n",
- " <td>...</td>\n",
- " <td>1.5663</td>\n",
- " <td>8.676</td>\n",
- " <td>3.21e-10</td>\n",
- " <td>0.298</td>\n",
- " <td>157.07</td>\n",
- " <td>7.923</td>\n",
- " <td>-0.456</td>\n",
- " <td>NRELv1</td>\n",
- " <td>222.2</td>\n",
- " <td>Mono-c-Si</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>alfasolar_alfasolar_M6L60_250</th>\n",
- " <td>N</td>\n",
- " <td>4/2/2013</td>\n",
- " <td>44.5</td>\n",
- " <td>1.6</td>\n",
- " <td>60</td>\n",
- " <td>8.71</td>\n",
- " <td>37.75</td>\n",
- " <td>8.16</td>\n",
- " <td>30.67</td>\n",
- " <td>0.002996</td>\n",
- " <td>...</td>\n",
- " <td>1.5634</td>\n",
- " <td>8.719</td>\n",
- " <td>2.8e-10</td>\n",
- " <td>0.301</td>\n",
- " <td>295.89</td>\n",
- " <td>6.663</td>\n",
- " <td>-0.456</td>\n",
- " <td>NRELv1</td>\n",
- " <td>226.8</td>\n",
- " <td>Mono-c-Si</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>alfasolar_alfasolar_M6L60_255</th>\n",
- " <td>N</td>\n",
- " <td>4/2/2013</td>\n",
- " <td>44.5</td>\n",
- " <td>1.6</td>\n",
- " <td>60</td>\n",
- " <td>8.76</td>\n",
- " <td>37.92</td>\n",
- " <td>8.29</td>\n",
- " <td>30.79</td>\n",
- " <td>0.003013</td>\n",
- " <td>...</td>\n",
- " <td>1.5609</td>\n",
- " <td>8.761</td>\n",
- " <td>2.46e-10</td>\n",
- " <td>0.304</td>\n",
- " <td>2378.2</td>\n",
- " <td>5.471</td>\n",
- " <td>-0.456</td>\n",
- " <td>NRELv1</td>\n",
- " <td>231.5</td>\n",
- " <td>Mono-c-Si</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>alfasolar_alfasolar_M6L60_260</th>\n",
- " <td>N</td>\n",
- " <td>4/2/2013</td>\n",
- " <td>44.5</td>\n",
- " <td>1.6</td>\n",
- " <td>60</td>\n",
- " <td>8.81</td>\n",
- " <td>38.09</td>\n",
- " <td>8.42</td>\n",
- " <td>30.91</td>\n",
- " <td>0.003031</td>\n",
- " <td>...</td>\n",
- " <td>1.5669</td>\n",
- " <td>8.899</td>\n",
- " <td>2.46e-10</td>\n",
- " <td>0.304</td>\n",
- " <td>2284.52</td>\n",
- " <td>5.348</td>\n",
- " <td>-0.456</td>\n",
- " <td>NRELv1</td>\n",
- " <td>236.2</td>\n",
- " <td>Mono-c-Si</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>alfasolar_alfasolar_M6L60_265</th>\n",
- " <td>N</td>\n",
- " <td>4/2/2013</td>\n",
- " <td>44.5</td>\n",
- " <td>1.6</td>\n",
- " <td>60</td>\n",
- " <td>8.86</td>\n",
- " <td>38.26</td>\n",
- " <td>8.55</td>\n",
- " <td>31.03</td>\n",
- " <td>0.003048</td>\n",
- " <td>...</td>\n",
- " <td>1.5731</td>\n",
- " <td>9.04</td>\n",
- " <td>2.47e-10</td>\n",
- " <td>0.303</td>\n",
- " <td>1932.19</td>\n",
- " <td>5.247</td>\n",
- " <td>-0.456</td>\n",
- " <td>NRELv1</td>\n",
- " <td>240.8</td>\n",
- " <td>Mono-c-Si</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>ecoSolargy_ECO250T156M4_60</th>\n",
- " <td>N</td>\n",
- " <td>42681</td>\n",
- " <td>45.5</td>\n",
- " <td>1.627</td>\n",
- " <td>60</td>\n",
- " <td>8.74</td>\n",
- " <td>37.65</td>\n",
- " <td>8.1</td>\n",
- " <td>30.98</td>\n",
- " <td>0.005993</td>\n",
- " <td>...</td>\n",
- " <td>1.5861</td>\n",
- " <td>8.754</td>\n",
- " <td>4.17e-10</td>\n",
- " <td>0.24</td>\n",
- " <td>148.03</td>\n",
- " <td>18.71</td>\n",
- " <td>-0.432</td>\n",
- " <td>NRELv1</td>\n",
- " <td>226.8</td>\n",
- " <td>Mono-c-Si</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>ecoSolargy_ECO255T156M4_60</th>\n",
- " <td>N</td>\n",
- " <td>42681</td>\n",
- " <td>45.5</td>\n",
- " <td>1.627</td>\n",
- " <td>60</td>\n",
- " <td>8.79</td>\n",
- " <td>37.88</td>\n",
- " <td>8.19</td>\n",
- " <td>31.19</td>\n",
- " <td>0.006027</td>\n",
- " <td>...</td>\n",
- " <td>1.5914</td>\n",
- " <td>8.801</td>\n",
- " <td>3.96e-10</td>\n",
- " <td>0.238</td>\n",
- " <td>190.95</td>\n",
- " <td>18.12</td>\n",
- " <td>-0.432</td>\n",
- " <td>NRELv1</td>\n",
- " <td>231.5</td>\n",
- " <td>Mono-c-Si</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>ecoSolargy_ECO260T156M4_60</th>\n",
- " <td>N</td>\n",
- " <td>42681</td>\n",
- " <td>45.5</td>\n",
- " <td>1.627</td>\n",
- " <td>60</td>\n",
- " <td>8.86</td>\n",
- " <td>38.23</td>\n",
- " <td>8.29</td>\n",
- " <td>31.44</td>\n",
- " <td>0.006075</td>\n",
- " <td>...</td>\n",
- " <td>1.6011</td>\n",
- " <td>8.869</td>\n",
- " <td>3.72e-10</td>\n",
- " <td>0.244</td>\n",
- " <td>250.14</td>\n",
- " <td>17.44</td>\n",
- " <td>-0.432</td>\n",
- " <td>NRELv1</td>\n",
- " <td>236.2</td>\n",
- " <td>Mono-c-Si</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>ecoSolargy_ECO265T156M4_60</th>\n",
- " <td>N</td>\n",
- " <td>42681</td>\n",
- " <td>45.5</td>\n",
- " <td>1.627</td>\n",
- " <td>60</td>\n",
- " <td>8.93</td>\n",
- " <td>38.54</td>\n",
- " <td>8.36</td>\n",
- " <td>31.75</td>\n",
- " <td>0.006123</td>\n",
- " <td>...</td>\n",
- " <td>1.6152</td>\n",
- " <td>8.938</td>\n",
- " <td>3.81e-10</td>\n",
- " <td>0.237</td>\n",
- " <td>257.69</td>\n",
- " <td>17.6</td>\n",
- " <td>-0.432</td>\n",
- " <td>NRELv1</td>\n",
- " <td>240.8</td>\n",
- " <td>Mono-c-Si</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>ecoSolargy_ECO270T156M4_60</th>\n",
- " <td>N</td>\n",
- " <td>42681</td>\n",
- " <td>45.5</td>\n",
- " <td>1.627</td>\n",
- " <td>60</td>\n",
- " <td>9.37</td>\n",
- " <td>38.79</td>\n",
- " <td>8.69</td>\n",
- " <td>31.19</td>\n",
- " <td>0.006425</td>\n",
- " <td>...</td>\n",
- " <td>1.612</td>\n",
- " <td>9.39</td>\n",
- " <td>3.24e-10</td>\n",
- " <td>0.33</td>\n",
- " <td>158.28</td>\n",
- " <td>15.64</td>\n",
- " <td>-0.432</td>\n",
- " <td>NRELv1</td>\n",
- " <td>245.5</td>\n",
- " <td>Mono-c-Si</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>ecoSolargy_ECO275T156M4_60</th>\n",
- " <td>N</td>\n",
- " <td>42681</td>\n",
- " <td>45.5</td>\n",
- " <td>1.627</td>\n",
- " <td>60</td>\n",
- " <td>9.39</td>\n",
- " <td>39.28</td>\n",
- " <td>8.73</td>\n",
- " <td>31.57</td>\n",
- " <td>0.006439</td>\n",
- " <td>...</td>\n",
- " <td>1.6297</td>\n",
- " <td>9.407</td>\n",
- " <td>3.13e-10</td>\n",
- " <td>0.335</td>\n",
- " <td>181.96</td>\n",
- " <td>15.28</td>\n",
- " <td>-0.432</td>\n",
- " <td>NRELv1</td>\n",
- " <td>250.2</td>\n",
- " <td>Mono-c-Si</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>ecoSolargy_ECO280T156M4_60</th>\n",
- " <td>N</td>\n",
- " <td>42681</td>\n",
- " <td>45.5</td>\n",
- " <td>1.627</td>\n",
- " <td>60</td>\n",
- " <td>9.46</td>\n",
- " <td>39.56</td>\n",
- " <td>8.8</td>\n",
- " <td>31.9</td>\n",
- " <td>0.006487</td>\n",
- " <td>...</td>\n",
- " <td>1.6439</td>\n",
- " <td>9.476</td>\n",
- " <td>3.28e-10</td>\n",
- " <td>0.321</td>\n",
- " <td>184.91</td>\n",
- " <td>15.64</td>\n",
- " <td>-0.432</td>\n",
- " <td>NRELv1</td>\n",
- " <td>254.8</td>\n",
- " <td>Mono-c-Si</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>ecoSolargy_ECO285T156M4_60</th>\n",
- " <td>N</td>\n",
- " <td>42681</td>\n",
- " <td>45.5</td>\n",
- " <td>1.627</td>\n",
- " <td>60</td>\n",
- " <td>9.5</td>\n",
- " <td>39.98</td>\n",
- " <td>8.85</td>\n",
- " <td>32.28</td>\n",
- " <td>0.006514</td>\n",
- " <td>...</td>\n",
- " <td>1.6612</td>\n",
- " <td>9.515</td>\n",
- " <td>3.29e-10</td>\n",
- " <td>0.317</td>\n",
- " <td>201.22</td>\n",
- " <td>15.63</td>\n",
- " <td>-0.432</td>\n",
- " <td>NRELv1</td>\n",
- " <td>259.5</td>\n",
- " <td>Mono-c-Si</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>ecoSolargy_ECO290T156M4_60</th>\n",
- " <td>N</td>\n",
- " <td>42681</td>\n",
- " <td>45.5</td>\n",
- " <td>1.627</td>\n",
- " <td>60</td>\n",
- " <td>9.55</td>\n",
- " <td>40.36</td>\n",
- " <td>8.91</td>\n",
- " <td>32.64</td>\n",
- " <td>0.006548</td>\n",
- " <td>...</td>\n",
- " <td>1.6771</td>\n",
- " <td>9.564</td>\n",
- " <td>3.32e-10</td>\n",
- " <td>0.312</td>\n",
- " <td>220.39</td>\n",
- " <td>15.65</td>\n",
- " <td>-0.432</td>\n",
- " <td>NRELv1</td>\n",
- " <td>264.2</td>\n",
- " <td>Mono-c-Si</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>ecoSolargy_ECO295T156M4_60</th>\n",
- " <td>N</td>\n",
- " <td>42681</td>\n",
- " <td>45.5</td>\n",
- " <td>1.627</td>\n",
- " <td>60</td>\n",
- " <td>9.59</td>\n",
- " <td>40.75</td>\n",
- " <td>8.96</td>\n",
- " <td>32.99</td>\n",
- " <td>0.006576</td>\n",
- " <td>...</td>\n",
- " <td>1.693</td>\n",
- " <td>9.602</td>\n",
- " <td>3.32e-10</td>\n",
- " <td>0.309</td>\n",
- " <td>242.88</td>\n",
- " <td>15.62</td>\n",
- " <td>-0.432</td>\n",
- " <td>NRELv1</td>\n",
- " <td>268.9</td>\n",
- " <td>Mono-c-Si</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>iTek_iT_220</th>\n",
- " <td>N</td>\n",
- " <td>10/26/2011</td>\n",
- " <td>48.2</td>\n",
- " <td>1.637</td>\n",
- " <td>60</td>\n",
- " <td>8.3</td>\n",
- " <td>37.4</td>\n",
- " <td>7.7</td>\n",
- " <td>29.6</td>\n",
- " <td>0.00332</td>\n",
- " <td>...</td>\n",
- " <td>1.6118</td>\n",
- " <td>8.316</td>\n",
- " <td>6.81e-10</td>\n",
- " <td>0.412</td>\n",
- " <td>212.87</td>\n",
- " <td>14.02</td>\n",
- " <td>-0.500</td>\n",
- " <td>NRELv1</td>\n",
- " <td>192.5</td>\n",
- " <td>Mono-c-Si</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>iTek_iT_225</th>\n",
- " <td>N</td>\n",
- " <td>10/26/2011</td>\n",
- " <td>48.2</td>\n",
- " <td>1.637</td>\n",
- " <td>60</td>\n",
- " <td>8.4</td>\n",
- " <td>37.6</td>\n",
- " <td>7.8</td>\n",
- " <td>29.7</td>\n",
- " <td>0.00336</td>\n",
- " <td>...</td>\n",
- " <td>1.6176</td>\n",
- " <td>8.416</td>\n",
- " <td>6.63e-10</td>\n",
- " <td>0.419</td>\n",
- " <td>226.85</td>\n",
- " <td>13.66</td>\n",
- " <td>-0.500</td>\n",
- " <td>NRELv1</td>\n",
- " <td>197.0</td>\n",
- " <td>Mono-c-Si</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>iTek_iT_230</th>\n",
- " <td>N</td>\n",
- " <td>10/26/2011</td>\n",
- " <td>48.2</td>\n",
- " <td>1.637</td>\n",
- " <td>60</td>\n",
- " <td>8.5</td>\n",
- " <td>37.7</td>\n",
- " <td>7.9</td>\n",
- " <td>29.8</td>\n",
- " <td>0.0034</td>\n",
- " <td>...</td>\n",
- " <td>1.6217</td>\n",
- " <td>8.515</td>\n",
- " <td>6.7e-10</td>\n",
- " <td>0.412</td>\n",
- " <td>237.91</td>\n",
- " <td>13.64</td>\n",
- " <td>-0.500</td>\n",
- " <td>NRELv1</td>\n",
- " <td>201.5</td>\n",
- " <td>Mono-c-Si</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>iTek_iT_235</th>\n",
- " <td>N</td>\n",
- " <td>10/26/2011</td>\n",
- " <td>48.2</td>\n",
- " <td>1.637</td>\n",
- " <td>60</td>\n",
- " <td>8.6</td>\n",
- " <td>37.9</td>\n",
- " <td>8.1</td>\n",
- " <td>29.9</td>\n",
- " <td>0.00344</td>\n",
- " <td>...</td>\n",
- " <td>1.6161</td>\n",
- " <td>8.601</td>\n",
- " <td>5.61e-10</td>\n",
- " <td>0.418</td>\n",
- " <td>4412.37</td>\n",
- " <td>11.87</td>\n",
- " <td>-0.500</td>\n",
- " <td>NRELv1</td>\n",
- " <td>206.1</td>\n",
- " <td>Mono-c-Si</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>iTek_iT_240</th>\n",
- " <td>N</td>\n",
- " <td>10/26/2011</td>\n",
- " <td>48.2</td>\n",
- " <td>1.637</td>\n",
- " <td>60</td>\n",
- " <td>8.7</td>\n",
- " <td>38</td>\n",
- " <td>8.2</td>\n",
- " <td>30</td>\n",
- " <td>0.00348</td>\n",
- " <td>...</td>\n",
- " <td>1.6204</td>\n",
- " <td>8.7</td>\n",
- " <td>5.68e-10</td>\n",
- " <td>0.411</td>\n",
- " <td>25925.1</td>\n",
- " <td>11.88</td>\n",
- " <td>-0.500</td>\n",
- " <td>NRELv1</td>\n",
- " <td>210.6</td>\n",
- " <td>Mono-c-Si</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>iTek_iT_260_HE</th>\n",
- " <td>N</td>\n",
- " <td>2/2/2015</td>\n",
- " <td>44.5</td>\n",
- " <td>1.634</td>\n",
- " <td>60</td>\n",
- " <td>8.9</td>\n",
- " <td>38.6</td>\n",
- " <td>8.2</td>\n",
- " <td>31.7</td>\n",
- " <td>0.00356</td>\n",
- " <td>...</td>\n",
- " <td>1.527</td>\n",
- " <td>8.923</td>\n",
- " <td>9e-11</td>\n",
- " <td>0.276</td>\n",
- " <td>109.16</td>\n",
- " <td>17.19</td>\n",
- " <td>-0.400</td>\n",
- " <td>NRELv1</td>\n",
- " <td>239.0</td>\n",
- " <td>Mono-c-Si</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>iTek_iT_265_HE</th>\n",
- " <td>N</td>\n",
- " <td>2/2/2015</td>\n",
- " <td>44.5</td>\n",
- " <td>1.634</td>\n",
- " <td>60</td>\n",
- " <td>9</td>\n",
- " <td>38.7</td>\n",
- " <td>8.3</td>\n",
- " <td>31.8</td>\n",
- " <td>0.0036</td>\n",
- " <td>...</td>\n",
- " <td>1.5306</td>\n",
- " <td>9.022</td>\n",
- " <td>9.06e-11</td>\n",
- " <td>0.271</td>\n",
- " <td>111.38</td>\n",
- " <td>17.14</td>\n",
- " <td>-0.400</td>\n",
- " <td>NRELv1</td>\n",
- " <td>243.7</td>\n",
- " <td>Mono-c-Si</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>iTek_iT_270_HE</th>\n",
- " <td>N</td>\n",
- " <td>2/2/2015</td>\n",
- " <td>44.5</td>\n",
- " <td>1.634</td>\n",
- " <td>60</td>\n",
- " <td>9.1</td>\n",
- " <td>38.9</td>\n",
- " <td>8.4</td>\n",
- " <td>32</td>\n",
- " <td>0.00364</td>\n",
- " <td>...</td>\n",
- " <td>1.5386</td>\n",
- " <td>9.121</td>\n",
- " <td>9.19e-11</td>\n",
- " <td>0.265</td>\n",
- " <td>113.85</td>\n",
- " <td>17.17</td>\n",
- " <td>-0.400</td>\n",
- " <td>NRELv1</td>\n",
- " <td>248.4</td>\n",
- " <td>Mono-c-Si</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>iTek_iT_275_HE</th>\n",
- " <td>N</td>\n",
- " <td>2/2/2015</td>\n",
- " <td>44.5</td>\n",
- " <td>1.634</td>\n",
- " <td>60</td>\n",
- " <td>9.2</td>\n",
- " <td>39</td>\n",
- " <td>8.5</td>\n",
- " <td>32.1</td>\n",
- " <td>0.00368</td>\n",
- " <td>...</td>\n",
- " <td>1.5422</td>\n",
- " <td>9.221</td>\n",
- " <td>9.25e-11</td>\n",
- " <td>0.26</td>\n",
- " <td>116.21</td>\n",
- " <td>17.12</td>\n",
- " <td>-0.400</td>\n",
- " <td>NRELv1</td>\n",
- " <td>253.1</td>\n",
- " <td>Mono-c-Si</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>iTek_iT_280_HE</th>\n",
- " <td>N</td>\n",
- " <td>2/2/2015</td>\n",
- " <td>44.5</td>\n",
- " <td>1.634</td>\n",
- " <td>60</td>\n",
- " <td>9.3</td>\n",
- " <td>39.2</td>\n",
- " <td>8.6</td>\n",
- " <td>32.3</td>\n",
- " <td>0.00372</td>\n",
- " <td>...</td>\n",
- " <td>1.5503</td>\n",
- " <td>9.32</td>\n",
- " <td>9.39e-11</td>\n",
- " <td>0.254</td>\n",
- " <td>118.83</td>\n",
- " <td>17.15</td>\n",
- " <td>-0.400</td>\n",
- " <td>NRELv1</td>\n",
- " <td>257.8</td>\n",
- " <td>Mono-c-Si</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>iTek_iT_285_HE</th>\n",
- " <td>N</td>\n",
- " <td>5/29/2015</td>\n",
- " <td>48.8</td>\n",
- " <td>1.62</td>\n",
- " <td>60</td>\n",
- " <td>10.05</td>\n",
- " <td>40.9</td>\n",
- " <td>9.53</td>\n",
- " <td>33.6</td>\n",
- " <td>0.00376</td>\n",
- " <td>...</td>\n",
- " <td>1.5904</td>\n",
- " <td>9.418</td>\n",
- " <td>1.69e-10</td>\n",
- " <td>0.241</td>\n",
- " <td>125.87</td>\n",
- " <td>18.44</td>\n",
- " <td>-0.420</td>\n",
- " <td>NRELv1</td>\n",
- " <td>292.1</td>\n",
- " <td>Mono-c-Si</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>iTek_iT_290_HE</th>\n",
- " <td>N</td>\n",
- " <td>5/29/2015</td>\n",
- " <td>48.8</td>\n",
- " <td>1.62</td>\n",
- " <td>60</td>\n",
- " <td>10.08</td>\n",
- " <td>41.2</td>\n",
- " <td>9.57</td>\n",
- " <td>34</td>\n",
- " <td>0.0038</td>\n",
- " <td>...</td>\n",
- " <td>1.5986</td>\n",
- " <td>9.517</td>\n",
- " <td>1.71e-10</td>\n",
- " <td>0.235</td>\n",
- " <td>128.9</td>\n",
- " <td>18.47</td>\n",
- " <td>-0.420</td>\n",
- " <td>NRELv1</td>\n",
- " <td>296.8</td>\n",
- " <td>Mono-c-Si</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>iTek_iT_295_HE</th>\n",
- " <td>N</td>\n",
- " <td>5/29/2015</td>\n",
- " <td>48.7</td>\n",
- " <td>1.62</td>\n",
- " <td>60</td>\n",
- " <td>9.9</td>\n",
- " <td>41.2</td>\n",
- " <td>9.43</td>\n",
- " <td>34.5</td>\n",
- " <td>0.00384</td>\n",
- " <td>...</td>\n",
- " <td>1.6069</td>\n",
- " <td>9.617</td>\n",
- " <td>1.74e-10</td>\n",
- " <td>0.229</td>\n",
- " <td>132.03</td>\n",
- " <td>18.5</td>\n",
- " <td>-0.420</td>\n",
- " <td>NRELv1</td>\n",
- " <td>296.9</td>\n",
- " <td>Mono-c-Si</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>iTek_iT_300_HE</th>\n",
- " <td>N</td>\n",
- " <td>5/29/2015</td>\n",
- " <td>48.8</td>\n",
- " <td>1.62</td>\n",
- " <td>60</td>\n",
- " <td>10.08</td>\n",
- " <td>41.2</td>\n",
- " <td>9.57</td>\n",
- " <td>34</td>\n",
- " <td>0.00388</td>\n",
- " <td>...</td>\n",
- " <td>1.6107</td>\n",
- " <td>9.716</td>\n",
- " <td>1.75e-10</td>\n",
- " <td>0.225</td>\n",
- " <td>135.1</td>\n",
- " <td>18.47</td>\n",
- " <td>-0.420</td>\n",
- " <td>NRELv1</td>\n",
- " <td>296.8</td>\n",
- " <td>Mono-c-Si</td>\n",
- " </tr>\n",
- " </tbody>\n",
- "</table>\n",
- "<p>3397 rows × 21 columns</p>\n",
- "</div>"
- ],
- "text/plain": [
- " BIPV Date T_NOCT A_c N_s I_sc_ref \\\n",
- "1Soltech_1STH_235_WH N 3/4/2010 49.9 1.635 60 8.54 \n",
- "1Soltech_1STH_240_WH N 3/4/2010 49.9 1.635 60 8.58 \n",
- "1Soltech_1STH_245_WH N 3/4/2010 49.9 1.635 60 8.62 \n",
- "1Soltech_1STH_250_WH N 3/4/2010 49.9 1.635 60 8.66 \n",
- "1Soltech_1STH_FRL_4H_245_M60_BLK N 1/14/2013 48.3 1.668 60 8.81 \n",
- "1Soltech_1STH_FRL_4H_250_M60_BLK N 1/14/2013 48.3 1.668 60 8.85 \n",
- "1Soltech_1STH_FRL_4H_255_M60_BLK N 1/14/2013 48.3 1.668 60 8.89 \n",
- "1Soltech_1STH_FRL_4H_260_M60_BLK N 1/14/2013 48.3 1.668 60 8.93 \n",
- "APOS_Energy_AS220 N 3/29/2010 47.8 1.659 60 8.28 \n",
- "APOS_Energy_AS225 N 3/29/2010 47.8 1.659 60 8.34 \n",
- "APOS_Energy_AS230 N 3/29/2010 47.8 1.659 60 8.46 \n",
- "APOS_Energy_AS235 N 3/29/2010 47.8 1.659 60 8.55 \n",
- "APOS_Energy_AS240 N 3/29/2010 47.8 1.659 60 8.63 \n",
- "AU_Optronics_PM060M00_250 N 11/1/2013 47.3 1.611 60 8.66 \n",
- "AU_Optronics_PM060M00_255 N 11/1/2013 47.3 1.611 60 8.72 \n",
- "AU_Optronics_PM060M00_260 N 11/1/2013 47.3 1.611 60 8.78 \n",
- "AU_Optronics_PM060M00_265 N 11/1/2013 47.3 1.611 60 8.84 \n",
- "AU_Optronics_PM060M00_270 N 7/1/2014 46.5 1.611 60 9.01 \n",
- "AU_Optronics_PM060M00_275 N 7/1/2014 46.5 1.611 60 9.03 \n",
- "AU_Optronics_PM060M00_280 N 7/1/2014 46.5 1.611 60 9.06 \n",
- "AU_Optronics_PM060M00_285 N 7/1/2014 46.5 1.611 60 9.08 \n",
- "AU_Optronics_PM060M00_290 N 7/1/2014 46.5 1.611 60 9.11 \n",
- "AU_Optronics_PM060M01_250 N 6/2/2014 47.3 1.611 60 8.66 \n",
- "AU_Optronics_PM060M01_255 N 6/2/2014 47.3 1.611 60 8.72 \n",
- "AU_Optronics_PM060M01_260 N 6/2/2014 47.3 1.611 60 8.78 \n",
- "AU_Optronics_PM060M01_265 N 6/2/2014 47.3 1.611 60 8.84 \n",
- "AU_Optronics_PM060M01_270 N 7/1/2014 46.5 1.611 60 9.01 \n",
- "AU_Optronics_PM060M01_275 N 7/1/2014 46.5 1.611 60 9.03 \n",
- "AU_Optronics_PM060M01_280 N 7/1/2014 46.5 1.611 60 9.06 \n",
- "AU_Optronics_PM060M01_285 N 7/1/2014 46.5 1.611 60 9.08 \n",
- "... ... ... ... ... .. ... \n",
- "alfasolar_alfasolar_M6L60_240 N 4/2/2013 44.5 1.6 60 8.61 \n",
- "alfasolar_alfasolar_M6L60_245 N 4/2/2013 44.5 1.6 60 8.66 \n",
- "alfasolar_alfasolar_M6L60_250 N 4/2/2013 44.5 1.6 60 8.71 \n",
- "alfasolar_alfasolar_M6L60_255 N 4/2/2013 44.5 1.6 60 8.76 \n",
- "alfasolar_alfasolar_M6L60_260 N 4/2/2013 44.5 1.6 60 8.81 \n",
- "alfasolar_alfasolar_M6L60_265 N 4/2/2013 44.5 1.6 60 8.86 \n",
- "ecoSolargy_ECO250T156M4_60 N 42681 45.5 1.627 60 8.74 \n",
- "ecoSolargy_ECO255T156M4_60 N 42681 45.5 1.627 60 8.79 \n",
- "ecoSolargy_ECO260T156M4_60 N 42681 45.5 1.627 60 8.86 \n",
- "ecoSolargy_ECO265T156M4_60 N 42681 45.5 1.627 60 8.93 \n",
- "ecoSolargy_ECO270T156M4_60 N 42681 45.5 1.627 60 9.37 \n",
- "ecoSolargy_ECO275T156M4_60 N 42681 45.5 1.627 60 9.39 \n",
- "ecoSolargy_ECO280T156M4_60 N 42681 45.5 1.627 60 9.46 \n",
- "ecoSolargy_ECO285T156M4_60 N 42681 45.5 1.627 60 9.5 \n",
- "ecoSolargy_ECO290T156M4_60 N 42681 45.5 1.627 60 9.55 \n",
- "ecoSolargy_ECO295T156M4_60 N 42681 45.5 1.627 60 9.59 \n",
- "iTek_iT_220 N 10/26/2011 48.2 1.637 60 8.3 \n",
- "iTek_iT_225 N 10/26/2011 48.2 1.637 60 8.4 \n",
- "iTek_iT_230 N 10/26/2011 48.2 1.637 60 8.5 \n",
- "iTek_iT_235 N 10/26/2011 48.2 1.637 60 8.6 \n",
- "iTek_iT_240 N 10/26/2011 48.2 1.637 60 8.7 \n",
- "iTek_iT_260_HE N 2/2/2015 44.5 1.634 60 8.9 \n",
- "iTek_iT_265_HE N 2/2/2015 44.5 1.634 60 9 \n",
- "iTek_iT_270_HE N 2/2/2015 44.5 1.634 60 9.1 \n",
- "iTek_iT_275_HE N 2/2/2015 44.5 1.634 60 9.2 \n",
- "iTek_iT_280_HE N 2/2/2015 44.5 1.634 60 9.3 \n",
- "iTek_iT_285_HE N 5/29/2015 48.8 1.62 60 10.05 \n",
- "iTek_iT_290_HE N 5/29/2015 48.8 1.62 60 10.08 \n",
- "iTek_iT_295_HE N 5/29/2015 48.7 1.62 60 9.9 \n",
- "iTek_iT_300_HE N 5/29/2015 48.8 1.62 60 10.08 \n",
- "\n",
- " V_oc_ref I_mp_ref V_mp_ref alpha_sc \\\n",
- "1Soltech_1STH_235_WH 37 8.02 29.3 0.00743 \n",
- "1Soltech_1STH_240_WH 37.1 8.07 29.7 0.007465 \n",
- "1Soltech_1STH_245_WH 37.2 8.1 30.2 0.007499 \n",
- "1Soltech_1STH_250_WH 37.3 8.15 30.7 0.007534 \n",
- "1Soltech_1STH_FRL_4H_245_M60_BLK 38.3 8.06 30.2 0.006167 \n",
- "1Soltech_1STH_FRL_4H_250_M60_BLK 38.4 8.11 30.7 0.006195 \n",
- "1Soltech_1STH_FRL_4H_255_M60_BLK 38.46 8.16 31.24 0.006223 \n",
- "1Soltech_1STH_FRL_4H_260_M60_BLK 38.6 8.21 31.6 0.006251 \n",
- "APOS_Energy_AS220 36.63 7.62 29.08 0.007118 \n",
- "APOS_Energy_AS225 36.99 7.69 29.31 0.00717 \n",
- "APOS_Energy_AS230 37.11 7.82 29.42 0.007276 \n",
- "APOS_Energy_AS235 37.34 7.86 29.76 0.007353 \n",
- "APOS_Energy_AS240 37.52 7.95 30.05 0.007422 \n",
- "AU_Optronics_PM060M00_250 37.86 8.22 30.82 0.005145 \n",
- "AU_Optronics_PM060M00_255 37.92 8.34 30.86 0.005181 \n",
- "AU_Optronics_PM060M00_260 37.98 8.46 30.91 0.005216 \n",
- "AU_Optronics_PM060M00_265 38.04 8.54 30.96 0.005252 \n",
- "AU_Optronics_PM060M00_270 38.5 8.5 31.8 0.005721 \n",
- "AU_Optronics_PM060M00_275 38.7 8.52 32.3 0.005734 \n",
- "AU_Optronics_PM060M00_280 38.9 8.57 32.7 0.005753 \n",
- "AU_Optronics_PM060M00_285 39.2 8.59 33.2 0.005766 \n",
- "AU_Optronics_PM060M00_290 39.5 8.61 33.7 0.005785 \n",
- "AU_Optronics_PM060M01_250 37.86 8.22 30.8 0.005145 \n",
- "AU_Optronics_PM060M01_255 37.92 8.34 30.9 0.005181 \n",
- "AU_Optronics_PM060M01_260 37.98 8.46 30.9 0.005216 \n",
- "AU_Optronics_PM060M01_265 38.04 8.54 31 0.005252 \n",
- "AU_Optronics_PM060M01_270 38.5 8.5 31.8 0.005721 \n",
- "AU_Optronics_PM060M01_275 38.7 8.52 32.3 0.005734 \n",
- "AU_Optronics_PM060M01_280 38.9 8.57 32.7 0.005753 \n",
- "AU_Optronics_PM060M01_285 39.2 8.59 33.2 0.005766 \n",
- "... ... ... ... ... \n",
- "alfasolar_alfasolar_M6L60_240 37.41 7.9 30.43 0.002962 \n",
- "alfasolar_alfasolar_M6L60_245 37.58 8.03 30.55 0.002979 \n",
- "alfasolar_alfasolar_M6L60_250 37.75 8.16 30.67 0.002996 \n",
- "alfasolar_alfasolar_M6L60_255 37.92 8.29 30.79 0.003013 \n",
- "alfasolar_alfasolar_M6L60_260 38.09 8.42 30.91 0.003031 \n",
- "alfasolar_alfasolar_M6L60_265 38.26 8.55 31.03 0.003048 \n",
- "ecoSolargy_ECO250T156M4_60 37.65 8.1 30.98 0.005993 \n",
- "ecoSolargy_ECO255T156M4_60 37.88 8.19 31.19 0.006027 \n",
- "ecoSolargy_ECO260T156M4_60 38.23 8.29 31.44 0.006075 \n",
- "ecoSolargy_ECO265T156M4_60 38.54 8.36 31.75 0.006123 \n",
- "ecoSolargy_ECO270T156M4_60 38.79 8.69 31.19 0.006425 \n",
- "ecoSolargy_ECO275T156M4_60 39.28 8.73 31.57 0.006439 \n",
- "ecoSolargy_ECO280T156M4_60 39.56 8.8 31.9 0.006487 \n",
- "ecoSolargy_ECO285T156M4_60 39.98 8.85 32.28 0.006514 \n",
- "ecoSolargy_ECO290T156M4_60 40.36 8.91 32.64 0.006548 \n",
- "ecoSolargy_ECO295T156M4_60 40.75 8.96 32.99 0.006576 \n",
- "iTek_iT_220 37.4 7.7 29.6 0.00332 \n",
- "iTek_iT_225 37.6 7.8 29.7 0.00336 \n",
- "iTek_iT_230 37.7 7.9 29.8 0.0034 \n",
- "iTek_iT_235 37.9 8.1 29.9 0.00344 \n",
- "iTek_iT_240 38 8.2 30 0.00348 \n",
- "iTek_iT_260_HE 38.6 8.2 31.7 0.00356 \n",
- "iTek_iT_265_HE 38.7 8.3 31.8 0.0036 \n",
- "iTek_iT_270_HE 38.9 8.4 32 0.00364 \n",
- "iTek_iT_275_HE 39 8.5 32.1 0.00368 \n",
- "iTek_iT_280_HE 39.2 8.6 32.3 0.00372 \n",
- "iTek_iT_285_HE 40.9 9.53 33.6 0.00376 \n",
- "iTek_iT_290_HE 41.2 9.57 34 0.0038 \n",
- "iTek_iT_295_HE 41.2 9.43 34.5 0.00384 \n",
- "iTek_iT_300_HE 41.2 9.57 34 0.00388 \n",
- "\n",
- " ... a_ref I_L_ref I_o_ref \\\n",
- "1Soltech_1STH_235_WH ... 1.6292 8.543 1.166e-09 \n",
- "1Soltech_1STH_240_WH ... 1.6425 8.582 1.325e-09 \n",
- "1Soltech_1STH_245_WH ... 1.6617 8.623 1.623e-09 \n",
- "1Soltech_1STH_250_WH ... 1.6783 8.662 1.919e-09 \n",
- "1Soltech_1STH_FRL_4H_245_M60_BLK ... 1.6351 8.844 5.7e-10 \n",
- "1Soltech_1STH_FRL_4H_250_M60_BLK ... 1.6517 8.878 6.83e-10 \n",
- "1Soltech_1STH_FRL_4H_255_M60_BLK ... 1.6688 8.912 8.39e-10 \n",
- "1Soltech_1STH_FRL_4H_260_M60_BLK ... 1.6811 8.949 9.2e-10 \n",
- "APOS_Energy_AS220 ... 1.5181 8.307 2.661e-10 \n",
- "APOS_Energy_AS225 ... 1.5291 8.365 2.527e-10 \n",
- "APOS_Energy_AS230 ... 1.533 8.483 2.526e-10 \n",
- "APOS_Energy_AS235 ... 1.5517 8.578 2.927e-10 \n",
- "APOS_Energy_AS240 ... 1.5616 8.655 3.074e-10 \n",
- "AU_Optronics_PM060M00_250 ... 1.5635 8.753 2.64e-10 \n",
- "AU_Optronics_PM060M00_255 ... 1.5592 8.808 2.41e-10 \n",
- "AU_Optronics_PM060M00_260 ... 1.5631 8.959 2.5e-10 \n",
- "AU_Optronics_PM060M00_265 ... 1.5634 9.019 2.44e-10 \n",
- "AU_Optronics_PM060M00_270 ... 1.6407 9.013 5.77e-10 \n",
- "AU_Optronics_PM060M00_275 ... 1.6589 9.033 6.63e-10 \n",
- "AU_Optronics_PM060M00_280 ... 1.6718 9.061 7.08e-10 \n",
- "AU_Optronics_PM060M00_285 ... 1.6918 9.081 7.81e-10 \n",
- "AU_Optronics_PM060M00_290 ... 1.7128 9.111 8.73e-10 \n",
- "AU_Optronics_PM060M01_250 ... 1.5635 8.753 2.64e-10 \n",
- "AU_Optronics_PM060M01_255 ... 1.5592 8.808 2.41e-10 \n",
- "AU_Optronics_PM060M01_260 ... 1.5631 8.959 2.5e-10 \n",
- "AU_Optronics_PM060M01_265 ... 1.5634 9.019 2.44e-10 \n",
- "AU_Optronics_PM060M01_270 ... 1.6407 9.013 5.77e-10 \n",
- "AU_Optronics_PM060M01_275 ... 1.6589 9.033 6.63e-10 \n",
- "AU_Optronics_PM060M01_280 ... 1.6718 9.061 7.08e-10 \n",
- "AU_Optronics_PM060M01_285 ... 1.6918 9.081 7.81e-10 \n",
- "... ... ... ... ... \n",
- "alfasolar_alfasolar_M6L60_240 ... 1.5697 8.634 3.7e-10 \n",
- "alfasolar_alfasolar_M6L60_245 ... 1.5663 8.676 3.21e-10 \n",
- "alfasolar_alfasolar_M6L60_250 ... 1.5634 8.719 2.8e-10 \n",
- "alfasolar_alfasolar_M6L60_255 ... 1.5609 8.761 2.46e-10 \n",
- "alfasolar_alfasolar_M6L60_260 ... 1.5669 8.899 2.46e-10 \n",
- "alfasolar_alfasolar_M6L60_265 ... 1.5731 9.04 2.47e-10 \n",
- "ecoSolargy_ECO250T156M4_60 ... 1.5861 8.754 4.17e-10 \n",
- "ecoSolargy_ECO255T156M4_60 ... 1.5914 8.801 3.96e-10 \n",
- "ecoSolargy_ECO260T156M4_60 ... 1.6011 8.869 3.72e-10 \n",
- "ecoSolargy_ECO265T156M4_60 ... 1.6152 8.938 3.81e-10 \n",
- "ecoSolargy_ECO270T156M4_60 ... 1.612 9.39 3.24e-10 \n",
- "ecoSolargy_ECO275T156M4_60 ... 1.6297 9.407 3.13e-10 \n",
- "ecoSolargy_ECO280T156M4_60 ... 1.6439 9.476 3.28e-10 \n",
- "ecoSolargy_ECO285T156M4_60 ... 1.6612 9.515 3.29e-10 \n",
- "ecoSolargy_ECO290T156M4_60 ... 1.6771 9.564 3.32e-10 \n",
- "ecoSolargy_ECO295T156M4_60 ... 1.693 9.602 3.32e-10 \n",
- "iTek_iT_220 ... 1.6118 8.316 6.81e-10 \n",
- "iTek_iT_225 ... 1.6176 8.416 6.63e-10 \n",
- "iTek_iT_230 ... 1.6217 8.515 6.7e-10 \n",
- "iTek_iT_235 ... 1.6161 8.601 5.61e-10 \n",
- "iTek_iT_240 ... 1.6204 8.7 5.68e-10 \n",
- "iTek_iT_260_HE ... 1.527 8.923 9e-11 \n",
- "iTek_iT_265_HE ... 1.5306 9.022 9.06e-11 \n",
- "iTek_iT_270_HE ... 1.5386 9.121 9.19e-11 \n",
- "iTek_iT_275_HE ... 1.5422 9.221 9.25e-11 \n",
- "iTek_iT_280_HE ... 1.5503 9.32 9.39e-11 \n",
- "iTek_iT_285_HE ... 1.5904 9.418 1.69e-10 \n",
- "iTek_iT_290_HE ... 1.5986 9.517 1.71e-10 \n",
- "iTek_iT_295_HE ... 1.6069 9.617 1.74e-10 \n",
- "iTek_iT_300_HE ... 1.6107 9.716 1.75e-10 \n",
- "\n",
- " R_s R_sh_ref Adjust gamma_r Version \\\n",
- "1Soltech_1STH_235_WH 0.383 1257.84 8.7 -0.482 MM107 \n",
- "1Soltech_1STH_240_WH 0.335 1463.82 9.8 -0.482 MM107 \n",
- "1Soltech_1STH_245_WH 0.272 724.06 11.6 -0.482 MM107 \n",
- "1Soltech_1STH_250_WH 0.211 760.07 13.1 -0.482 MM107 \n",
- "1Soltech_1STH_FRL_4H_245_M60_BLK 0.421 109.31 6.502 -0.453 NRELv1 \n",
- "1Soltech_1STH_FRL_4H_250_M60_BLK 0.358 111.51 8.03 -0.453 NRELv1 \n",
- "1Soltech_1STH_FRL_4H_255_M60_BLK 0.285 113.34 9.818 -0.453 NRELv1 \n",
- "1Soltech_1STH_FRL_4H_260_M60_BLK 0.249 117.56 10.6 -0.453 NRELv1 \n",
- "APOS_Energy_AS220 0.41 127.31 24.3 -0.425 MM107 \n",
- "APOS_Energy_AS225 0.419 138.1 23.7 -0.425 MM107 \n",
- "APOS_Energy_AS230 0.412 151.47 23.5 -0.425 MM107 \n",
- "APOS_Energy_AS235 0.387 119.65 24.9 -0.425 MM107 \n",
- "APOS_Energy_AS240 0.363 126.69 25.3 -0.425 MM107 \n",
- "AU_Optronics_PM060M00_250 0.293 392.21 18.48 -0.437 NRELv1 \n",
- "AU_Optronics_PM060M00_255 0.294 3072.79 17.53 -0.437 NRELv1 \n",
- "AU_Optronics_PM060M00_260 0.289 915.51 17.74 -0.437 NRELv1 \n",
- "AU_Optronics_PM060M00_265 0.288 3154.03 17.43 -0.437 NRELv1 \n",
- "AU_Optronics_PM060M00_270 0.216 674.93 15.7 -0.454 NRELv1 \n",
- "AU_Optronics_PM060M00_275 0.171 590.38 17 -0.454 NRELv1 \n",
- "AU_Optronics_PM060M00_280 0.14 880.22 17.58 -0.454 NRELv1 \n",
- "AU_Optronics_PM060M00_285 0.107 789.79 18.51 -0.454 NRELv1 \n",
- "AU_Optronics_PM060M00_290 0.074 591.61 19.55 -0.454 NRELv1 \n",
- "AU_Optronics_PM060M01_250 0.293 392.21 18.48 -0.437 NRELv1 \n",
- "AU_Optronics_PM060M01_255 0.294 3072.79 17.53 -0.437 NRELv1 \n",
- "AU_Optronics_PM060M01_260 0.289 915.51 17.74 -0.437 NRELv1 \n",
- "AU_Optronics_PM060M01_265 0.288 3154.03 17.43 -0.437 NRELv1 \n",
- "AU_Optronics_PM060M01_270 0.216 674.93 15.7 -0.454 NRELv1 \n",
- "AU_Optronics_PM060M01_275 0.171 590.38 17 -0.454 NRELv1 \n",
- "AU_Optronics_PM060M01_280 0.14 880.22 17.58 -0.454 NRELv1 \n",
- "AU_Optronics_PM060M01_285 0.107 789.79 18.51 -0.454 NRELv1 \n",
- "... ... ... ... ... ... \n",
- "alfasolar_alfasolar_M6L60_240 0.294 106.59 9.256 -0.456 NRELv1 \n",
- "alfasolar_alfasolar_M6L60_245 0.298 157.07 7.923 -0.456 NRELv1 \n",
- "alfasolar_alfasolar_M6L60_250 0.301 295.89 6.663 -0.456 NRELv1 \n",
- "alfasolar_alfasolar_M6L60_255 0.304 2378.2 5.471 -0.456 NRELv1 \n",
- "alfasolar_alfasolar_M6L60_260 0.304 2284.52 5.348 -0.456 NRELv1 \n",
- "alfasolar_alfasolar_M6L60_265 0.303 1932.19 5.247 -0.456 NRELv1 \n",
- "ecoSolargy_ECO250T156M4_60 0.24 148.03 18.71 -0.432 NRELv1 \n",
- "ecoSolargy_ECO255T156M4_60 0.238 190.95 18.12 -0.432 NRELv1 \n",
- "ecoSolargy_ECO260T156M4_60 0.244 250.14 17.44 -0.432 NRELv1 \n",
- "ecoSolargy_ECO265T156M4_60 0.237 257.69 17.6 -0.432 NRELv1 \n",
- "ecoSolargy_ECO270T156M4_60 0.33 158.28 15.64 -0.432 NRELv1 \n",
- "ecoSolargy_ECO275T156M4_60 0.335 181.96 15.28 -0.432 NRELv1 \n",
- "ecoSolargy_ECO280T156M4_60 0.321 184.91 15.64 -0.432 NRELv1 \n",
- "ecoSolargy_ECO285T156M4_60 0.317 201.22 15.63 -0.432 NRELv1 \n",
- "ecoSolargy_ECO290T156M4_60 0.312 220.39 15.65 -0.432 NRELv1 \n",
- "ecoSolargy_ECO295T156M4_60 0.309 242.88 15.62 -0.432 NRELv1 \n",
- "iTek_iT_220 0.412 212.87 14.02 -0.500 NRELv1 \n",
- "iTek_iT_225 0.419 226.85 13.66 -0.500 NRELv1 \n",
- "iTek_iT_230 0.412 237.91 13.64 -0.500 NRELv1 \n",
- "iTek_iT_235 0.418 4412.37 11.87 -0.500 NRELv1 \n",
- "iTek_iT_240 0.411 25925.1 11.88 -0.500 NRELv1 \n",
- "iTek_iT_260_HE 0.276 109.16 17.19 -0.400 NRELv1 \n",
- "iTek_iT_265_HE 0.271 111.38 17.14 -0.400 NRELv1 \n",
- "iTek_iT_270_HE 0.265 113.85 17.17 -0.400 NRELv1 \n",
- "iTek_iT_275_HE 0.26 116.21 17.12 -0.400 NRELv1 \n",
- "iTek_iT_280_HE 0.254 118.83 17.15 -0.400 NRELv1 \n",
- "iTek_iT_285_HE 0.241 125.87 18.44 -0.420 NRELv1 \n",
- "iTek_iT_290_HE 0.235 128.9 18.47 -0.420 NRELv1 \n",
- "iTek_iT_295_HE 0.229 132.03 18.5 -0.420 NRELv1 \n",
- "iTek_iT_300_HE 0.225 135.1 18.47 -0.420 NRELv1 \n",
- "\n",
- " PTC Technology \n",
- "1Soltech_1STH_235_WH 205.1 Mono-c-Si \n",
- "1Soltech_1STH_240_WH 209.6 Mono-c-Si \n",
- "1Soltech_1STH_245_WH 214.1 Mono-c-Si \n",
- "1Soltech_1STH_250_WH 218.6 Mono-c-Si \n",
- "1Soltech_1STH_FRL_4H_245_M60_BLK 217.7 Mono-c-Si \n",
- "1Soltech_1STH_FRL_4H_250_M60_BLK 222.3 Mono-c-Si \n",
- "1Soltech_1STH_FRL_4H_255_M60_BLK 226.9 Mono-c-Si \n",
- "1Soltech_1STH_FRL_4H_260_M60_BLK 231.4 Mono-c-Si \n",
- "APOS_Energy_AS220 197.0 Mono-c-Si \n",
- "APOS_Energy_AS225 201.6 Mono-c-Si \n",
- "APOS_Energy_AS230 206.1 Mono-c-Si \n",
- "APOS_Energy_AS235 210.7 Mono-c-Si \n",
- "APOS_Energy_AS240 215.4 Mono-c-Si \n",
- "AU_Optronics_PM060M00_250 224.6 Mono-c-Si \n",
- "AU_Optronics_PM060M00_255 229.2 Mono-c-Si \n",
- "AU_Optronics_PM060M00_260 233.8 Mono-c-Si \n",
- "AU_Optronics_PM060M00_265 238.5 Mono-c-Si \n",
- "AU_Optronics_PM060M00_270 243.1 Mono-c-Si \n",
- "AU_Optronics_PM060M00_275 247.8 Mono-c-Si \n",
- "AU_Optronics_PM060M00_280 252.4 Mono-c-Si \n",
- "AU_Optronics_PM060M00_285 257.1 Mono-c-Si \n",
- "AU_Optronics_PM060M00_290 261.7 Mono-c-Si \n",
- "AU_Optronics_PM060M01_250 224.6 Mono-c-Si \n",
- "AU_Optronics_PM060M01_255 229.2 Mono-c-Si \n",
- "AU_Optronics_PM060M01_260 233.8 Mono-c-Si \n",
- "AU_Optronics_PM060M01_265 238.5 Mono-c-Si \n",
- "AU_Optronics_PM060M01_270 243.1 Mono-c-Si \n",
- "AU_Optronics_PM060M01_275 247.8 Mono-c-Si \n",
- "AU_Optronics_PM060M01_280 252.4 Mono-c-Si \n",
- "AU_Optronics_PM060M01_285 257.1 Mono-c-Si \n",
- "... ... ... \n",
- "alfasolar_alfasolar_M6L60_240 217.5 Mono-c-Si \n",
- "alfasolar_alfasolar_M6L60_245 222.2 Mono-c-Si \n",
- "alfasolar_alfasolar_M6L60_250 226.8 Mono-c-Si \n",
- "alfasolar_alfasolar_M6L60_255 231.5 Mono-c-Si \n",
- "alfasolar_alfasolar_M6L60_260 236.2 Mono-c-Si \n",
- "alfasolar_alfasolar_M6L60_265 240.8 Mono-c-Si \n",
- "ecoSolargy_ECO250T156M4_60 226.8 Mono-c-Si \n",
- "ecoSolargy_ECO255T156M4_60 231.5 Mono-c-Si \n",
- "ecoSolargy_ECO260T156M4_60 236.2 Mono-c-Si \n",
- "ecoSolargy_ECO265T156M4_60 240.8 Mono-c-Si \n",
- "ecoSolargy_ECO270T156M4_60 245.5 Mono-c-Si \n",
- "ecoSolargy_ECO275T156M4_60 250.2 Mono-c-Si \n",
- "ecoSolargy_ECO280T156M4_60 254.8 Mono-c-Si \n",
- "ecoSolargy_ECO285T156M4_60 259.5 Mono-c-Si \n",
- "ecoSolargy_ECO290T156M4_60 264.2 Mono-c-Si \n",
- "ecoSolargy_ECO295T156M4_60 268.9 Mono-c-Si \n",
- "iTek_iT_220 192.5 Mono-c-Si \n",
- "iTek_iT_225 197.0 Mono-c-Si \n",
- "iTek_iT_230 201.5 Mono-c-Si \n",
- "iTek_iT_235 206.1 Mono-c-Si \n",
- "iTek_iT_240 210.6 Mono-c-Si \n",
- "iTek_iT_260_HE 239.0 Mono-c-Si \n",
- "iTek_iT_265_HE 243.7 Mono-c-Si \n",
- "iTek_iT_270_HE 248.4 Mono-c-Si \n",
- "iTek_iT_275_HE 253.1 Mono-c-Si \n",
- "iTek_iT_280_HE 257.8 Mono-c-Si \n",
- "iTek_iT_285_HE 292.1 Mono-c-Si \n",
- "iTek_iT_290_HE 296.8 Mono-c-Si \n",
- "iTek_iT_295_HE 296.9 Mono-c-Si \n",
- "iTek_iT_300_HE 296.8 Mono-c-Si \n",
- "\n",
- "[3397 rows x 21 columns]"
- ]
- },
- "execution_count": 36,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "suitable_models"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 37,
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "230.873682661\n",
- "-0.455559022667\n"
- ]
- }
- ],
- "source": [
- "print(suitable_models.mean().PTC)\n",
- "print(suitable_models.mean().gamma_r)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Compute efficiencies for all possible $G_t$ intervals for all temperature cells"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 38,
- "metadata": {},
- "outputs": [],
- "source": [
- "Gt_INTERVAL = 1\n",
- "Gt_range = list(range(1, 1004, Gt_INTERVAL))"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 39,
- "metadata": {},
- "outputs": [],
- "source": [
- "T_INTERVAL = 1\n",
- "T_range = list(range(-24, 35, T_INTERVAL))"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 40,
- "metadata": {},
- "outputs": [],
- "source": [
- "df = xr.DataArray(data = np.ones((len(Gt_range), len(T_range))), \n",
- " dims = ['G_t', 'T_amb'], coords = {'G_t' : Gt_range, 'T_amb' : T_range}, \n",
- " name = 'T_cell').to_dataframe().reset_index()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 41,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/html": [
- "<div>\n",
- "<style scoped>\n",
- " .dataframe tbody tr th:only-of-type {\n",
- " vertical-align: middle;\n",
- " }\n",
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- " .dataframe tbody tr th {\n",
- " vertical-align: top;\n",
- " }\n",
- "\n",
- " .dataframe thead th {\n",
- " text-align: right;\n",
- " }\n",
- "</style>\n",
- "<table border=\"1\" class=\"dataframe\">\n",
- " <thead>\n",
- " <tr style=\"text-align: right;\">\n",
- " <th></th>\n",
- " <th>G_t</th>\n",
- " <th>T_amb</th>\n",
- " <th>T_cell</th>\n",
- " </tr>\n",
- " </thead>\n",
- " <tbody>\n",
- " <tr>\n",
- " <th>0</th>\n",
- " <td>1</td>\n",
- " <td>-24</td>\n",
- " <td>1.0</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>1</th>\n",
- " <td>1</td>\n",
- " <td>-23</td>\n",
- " <td>1.0</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>2</th>\n",
- " <td>1</td>\n",
- " <td>-22</td>\n",
- " <td>1.0</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>3</th>\n",
- " <td>1</td>\n",
- " <td>-21</td>\n",
- " <td>1.0</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>4</th>\n",
- " <td>1</td>\n",
- " <td>-20</td>\n",
- " <td>1.0</td>\n",
- " </tr>\n",
- " </tbody>\n",
- "</table>\n",
- "</div>"
- ],
- "text/plain": [
- " G_t T_amb T_cell\n",
- "0 1 -24 1.0\n",
- "1 1 -23 1.0\n",
- "2 1 -22 1.0\n",
- "3 1 -21 1.0\n",
- "4 1 -20 1.0"
- ]
- },
- "execution_count": 41,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "df.head()"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Get cell temperatures "
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 42,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "59177"
- ]
- },
- "execution_count": 42,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "len(df)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 114,
- "metadata": {
- "scrolled": false
- },
- "outputs": [],
- "source": [
- "df['T_cell'] = pvsystem.pvsyst_celltemp(df.G_t, df.T_amb, model_params = 'insulated')"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 116,
- "metadata": {},
- "outputs": [],
- "source": [
- "A_panel = 1.6 # in m2\n",
- "\n",
- "P_dc0 = 285 / A_panel # , PV output per m2 - 285: AVERAGE FOR 3 LARGEST PRODUCERS\n",
- "gamma = -0.39 / 100 # suitable_models.mean().gamma_r : AVERAGE FOR 3 LARGEST PRODUCERS"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 117,
- "metadata": {},
- "outputs": [],
- "source": [
- "P_dc = pvsystem.pvwatts_dc(df.G_t, df.T_cell, P_dc0, gamma)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 118,
- "metadata": {},
- "outputs": [],
- "source": [
- "df['module_eff'] = (P_dc / df['G_t'])"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 119,
- "metadata": {
- "scrolled": true
- },
- "outputs": [
- {
- "data": {
- "text/html": [
- "<div>\n",
- "<style scoped>\n",
- " .dataframe tbody tr th:only-of-type {\n",
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- "\n",
- " .dataframe thead th {\n",
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- " }\n",
- "</style>\n",
- "<table border=\"1\" class=\"dataframe\">\n",
- " <thead>\n",
- " <tr style=\"text-align: right;\">\n",
- " <th></th>\n",
- " <th>G_t</th>\n",
- " <th>T_amb</th>\n",
- " <th>T_cell</th>\n",
- " <th>module_eff</th>\n",
- " <th>losses</th>\n",
- " <th>inverter_eff</th>\n",
- " <th>PF</th>\n",
- " </tr>\n",
- " </thead>\n",
- " <tbody>\n",
- " <tr>\n",
- " <th>0</th>\n",
- " <td>1</td>\n",
- " <td>-24</td>\n",
- " <td>-23.946</td>\n",
- " <td>0.212127</td>\n",
- " <td>14.075661</td>\n",
- " <td>0.0</td>\n",
- " <td>0.0</td>\n",
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- " <tr>\n",
- " <th>1</th>\n",
- " <td>1</td>\n",
- " <td>-23</td>\n",
- " <td>-22.946</td>\n",
- " <td>0.211432</td>\n",
- " <td>14.075661</td>\n",
- " <td>0.0</td>\n",
- " <td>0.0</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>2</th>\n",
- " <td>1</td>\n",
- " <td>-22</td>\n",
- " <td>-21.946</td>\n",
- " <td>0.210738</td>\n",
- " <td>14.075661</td>\n",
- " <td>0.0</td>\n",
- " <td>0.0</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>3</th>\n",
- " <td>1</td>\n",
- " <td>-21</td>\n",
- " <td>-20.946</td>\n",
- " <td>0.210043</td>\n",
- " <td>14.075661</td>\n",
- " <td>0.0</td>\n",
- " <td>0.0</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>4</th>\n",
- " <td>1</td>\n",
- " <td>-20</td>\n",
- " <td>-19.946</td>\n",
- " <td>0.209348</td>\n",
- " <td>14.075661</td>\n",
- " <td>0.0</td>\n",
- " <td>0.0</td>\n",
- " </tr>\n",
- " </tbody>\n",
- "</table>\n",
- "</div>"
- ],
- "text/plain": [
- " G_t T_amb T_cell module_eff losses inverter_eff PF\n",
- "0 1 -24 -23.946 0.212127 14.075661 0.0 0.0\n",
- "1 1 -23 -22.946 0.211432 14.075661 0.0 0.0\n",
- "2 1 -22 -21.946 0.210738 14.075661 0.0 0.0\n",
- "3 1 -21 -20.946 0.210043 14.075661 0.0 0.0\n",
- "4 1 -20 -19.946 0.209348 14.075661 0.0 0.0"
- ]
- },
- "execution_count": 119,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "df.head()"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Assess performance factor"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Check nominal inverter efficiencies"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 120,
- "metadata": {},
- "outputs": [],
- "source": [
- "inverters = pvsystem.retrieve_sam('CECInverter').T "
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 121,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "0.9593134070067068"
- ]
- },
- "execution_count": 121,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "(inverters.Paco / inverters.Pdco).mean()"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "#### Compute inverter efficiencies and other system losses"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 122,
- "metadata": {},
- "outputs": [],
- "source": [
- "P_ac = pvsystem.pvwatts_ac(P_dc, P_dc0)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 123,
- "metadata": {},
- "outputs": [],
- "source": [
- "df['losses'] = pvsystem.pvwatts_losses()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 124,
- "metadata": {},
- "outputs": [],
- "source": [
- "df['inverter_eff'] = (P_ac / P_dc)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 125,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/html": [
- "<div>\n",
- "<style scoped>\n",
- " .dataframe tbody tr th:only-of-type {\n",
- " vertical-align: middle;\n",
- " }\n",
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- " .dataframe tbody tr th {\n",
- " vertical-align: top;\n",
- " }\n",
- "\n",
- " .dataframe thead th {\n",
- " text-align: right;\n",
- " }\n",
- "</style>\n",
- "<table border=\"1\" class=\"dataframe\">\n",
- " <thead>\n",
- " <tr style=\"text-align: right;\">\n",
- " <th></th>\n",
- " <th>G_t</th>\n",
- " <th>T_amb</th>\n",
- " <th>T_cell</th>\n",
- " <th>module_eff</th>\n",
- " <th>losses</th>\n",
- " <th>inverter_eff</th>\n",
- " <th>PF</th>\n",
- " </tr>\n",
- " </thead>\n",
- " <tbody>\n",
- " <tr>\n",
- " <th>0</th>\n",
- " <td>1</td>\n",
- " <td>-24</td>\n",
- " <td>-23.946</td>\n",
- " <td>0.212127</td>\n",
- " <td>14.075661</td>\n",
- " <td>0.0</td>\n",
- " <td>0.0</td>\n",
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- " <tr>\n",
- " <th>1</th>\n",
- " <td>1</td>\n",
- " <td>-23</td>\n",
- " <td>-22.946</td>\n",
- " <td>0.211432</td>\n",
- " <td>14.075661</td>\n",
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- " <td>0.0</td>\n",
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- " <tr>\n",
- " <th>2</th>\n",
- " <td>1</td>\n",
- " <td>-22</td>\n",
- " <td>-21.946</td>\n",
- " <td>0.210738</td>\n",
- " <td>14.075661</td>\n",
- " <td>0.0</td>\n",
- " <td>0.0</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>3</th>\n",
- " <td>1</td>\n",
- " <td>-21</td>\n",
- " <td>-20.946</td>\n",
- " <td>0.210043</td>\n",
- " <td>14.075661</td>\n",
- " <td>0.0</td>\n",
- " <td>0.0</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>4</th>\n",
- " <td>1</td>\n",
- " <td>-20</td>\n",
- " <td>-19.946</td>\n",
- " <td>0.209348</td>\n",
- " <td>14.075661</td>\n",
- " <td>0.0</td>\n",
- " <td>0.0</td>\n",
- " </tr>\n",
- " </tbody>\n",
- "</table>\n",
- "</div>"
- ],
- "text/plain": [
- " G_t T_amb T_cell module_eff losses inverter_eff PF\n",
- "0 1 -24 -23.946 0.212127 14.075661 0.0 0.0\n",
- "1 1 -23 -22.946 0.211432 14.075661 0.0 0.0\n",
- "2 1 -22 -21.946 0.210738 14.075661 0.0 0.0\n",
- "3 1 -21 -20.946 0.210043 14.075661 0.0 0.0\n",
- "4 1 -20 -19.946 0.209348 14.075661 0.0 0.0"
- ]
- },
- "execution_count": 125,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "df.head()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 126,
- "metadata": {},
- "outputs": [],
- "source": [
- "df['PF'] = df.inverter_eff * (1 - df.losses/100)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Get overall performance\n",
- "We notice that module efficiency, in the simplified model used here, is a linear function of the ambient temperature, and hence it is averaged across G_t\n",
- "At the same time, the inverter efficiency is *almost* a function of $G_t$, except for low temperatures. We create a weighted average for computing module efficiency as a function of $G_t$, using the histogram of ambient temperatures (see above) as weighting"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 136,
- "metadata": {},
- "outputs": [],
- "source": [
- "performance = df.dropna().set_index(['G_t', 'T_amb']).to_xarray()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 137,
- "metadata": {},
- "outputs": [],
- "source": [
- "# performance['T_weight'] = xr.DataArray(data = hist[0], dims = 'T_amb', coords = {'T_amb' : hist[1][:-1]})"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 138,
- "metadata": {},
- "outputs": [],
- "source": [
- "performance['PF_mean'] = performance.PF.mean('T_amb')"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 139,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<xarray.Dataset>\n",
- "Dimensions: (G_t: 1003, T_amb: 59)\n",
- "Coordinates:\n",
- " * G_t (G_t) int64 1 2 3 4 5 6 7 ... 997 998 999 1000 1001 1002 1003\n",
- " * T_amb (T_amb) int64 -24 -23 -22 -21 -20 -19 ... 29 30 31 32 33 34\n",
- "Data variables:\n",
- " T_cell (G_t, T_amb) float64 -23.95 -22.95 -21.95 ... 87.16 88.16\n",
- " module_eff (G_t, T_amb) float64 0.2121 0.2114 0.2107 ... 0.1349 0.1342\n",
- " losses (G_t, T_amb) float64 14.08 14.08 14.08 ... 14.08 14.08 14.08\n",
- " inverter_eff (G_t, T_amb) float64 0.0 0.0 0.0 0.0 ... 0.962 0.962 0.962\n",
- " PF (G_t, T_amb) float64 0.0 0.0 0.0 0.0 ... 0.8266 0.8266 0.8266\n",
- " PF_mean (G_t) float64 0.0 0.0 0.0 0.0 ... 0.8259 0.8259 0.8259 0.8259"
- ]
- },
- "execution_count": 139,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "performance"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 141,
- "metadata": {
- "scrolled": true
- },
- "outputs": [],
- "source": [
- "performance.to_netcdf('/work/hyenergy/output/solar_potential/technical_potential/pv_efficiencies.nc')"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 131,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "application/javascript": [
- "/* Put everything inside the global mpl namespace */\n",
- "window.mpl = {};\n",
- "\n",
- "\n",
- "mpl.get_websocket_type = function() {\n",
- " if (typeof(WebSocket) !== 'undefined') {\n",
- " return WebSocket;\n",
- " } else if (typeof(MozWebSocket) !== 'undefined') {\n",
- " return MozWebSocket;\n",
- " } else {\n",
- " alert('Your browser does not have WebSocket support.' +\n",
- " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
- " 'Firefox 4 and 5 are also supported but you ' +\n",
- " 'have to enable WebSockets in about:config.');\n",
- " };\n",
- "}\n",
- "\n",
- "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
- " this.id = figure_id;\n",
- "\n",
- " this.ws = websocket;\n",
- "\n",
- " this.supports_binary = (this.ws.binaryType != undefined);\n",
- "\n",
- " if (!this.supports_binary) {\n",
- " var warnings = document.getElementById(\"mpl-warnings\");\n",
- " if (warnings) {\n",
- " warnings.style.display = 'block';\n",
- " warnings.textContent = (\n",
- " \"This browser does not support binary websocket messages. \" +\n",
- " \"Performance may be slow.\");\n",
- " }\n",
- " }\n",
- "\n",
- " this.imageObj = new Image();\n",
- "\n",
- " this.context = undefined;\n",
- " this.message = undefined;\n",
- " this.canvas = undefined;\n",
- " this.rubberband_canvas = undefined;\n",
- " this.rubberband_context = undefined;\n",
- " this.format_dropdown = undefined;\n",
- "\n",
- " this.image_mode = 'full';\n",
- "\n",
- " this.root = $('<div/>');\n",
- " this._root_extra_style(this.root)\n",
- " this.root.attr('style', 'display: inline-block');\n",
- "\n",
- " $(parent_element).append(this.root);\n",
- "\n",
- " this._init_header(this);\n",
- " this._init_canvas(this);\n",
- " this._init_toolbar(this);\n",
- "\n",
- " var fig = this;\n",
- "\n",
- " this.waiting = false;\n",
- "\n",
- " this.ws.onopen = function () {\n",
- " fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
- " fig.send_message(\"send_image_mode\", {});\n",
- " if (mpl.ratio != 1) {\n",
- " fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
- " }\n",
- " fig.send_message(\"refresh\", {});\n",
- " }\n",
- "\n",
- " this.imageObj.onload = function() {\n",
- " if (fig.image_mode == 'full') {\n",
- " // Full images could contain transparency (where diff images\n",
- " // almost always do), so we need to clear the canvas so that\n",
- " // there is no ghosting.\n",
- " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
- " }\n",
- " fig.context.drawImage(fig.imageObj, 0, 0);\n",
- " };\n",
- "\n",
- " this.imageObj.onunload = function() {\n",
- " fig.ws.close();\n",
- " }\n",
- "\n",
- " this.ws.onmessage = this._make_on_message_function(this);\n",
- "\n",
- " this.ondownload = ondownload;\n",
- "}\n",
- "\n",
- "mpl.figure.prototype._init_header = function() {\n",
- " var titlebar = $(\n",
- " '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
- " 'ui-helper-clearfix\"/>');\n",
- " var titletext = $(\n",
- " '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
- " 'text-align: center; padding: 3px;\"/>');\n",
- " titlebar.append(titletext)\n",
- " this.root.append(titlebar);\n",
- " this.header = titletext[0];\n",
- "}\n",
- "\n",
- "\n",
- "\n",
- "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
- "\n",
- "}\n",
- "\n",
- "\n",
- "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
- "\n",
- "}\n",
- "\n",
- "mpl.figure.prototype._init_canvas = function() {\n",
- " var fig = this;\n",
- "\n",
- " var canvas_div = $('<div/>');\n",
- "\n",
- " canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
- "\n",
- " function canvas_keyboard_event(event) {\n",
- " return fig.key_event(event, event['data']);\n",
- " }\n",
- "\n",
- " canvas_div.keydown('key_press', canvas_keyboard_event);\n",
- " canvas_div.keyup('key_release', canvas_keyboard_event);\n",
- " this.canvas_div = canvas_div\n",
- " this._canvas_extra_style(canvas_div)\n",
- " this.root.append(canvas_div);\n",
- "\n",
- " var canvas = $('<canvas/>');\n",
- " canvas.addClass('mpl-canvas');\n",
- " canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
- "\n",
- " this.canvas = canvas[0];\n",
- " this.context = canvas[0].getContext(\"2d\");\n",
- "\n",
- " var backingStore = this.context.backingStorePixelRatio ||\n",
- "\tthis.context.webkitBackingStorePixelRatio ||\n",
- "\tthis.context.mozBackingStorePixelRatio ||\n",
- "\tthis.context.msBackingStorePixelRatio ||\n",
- "\tthis.context.oBackingStorePixelRatio ||\n",
- "\tthis.context.backingStorePixelRatio || 1;\n",
- "\n",
- " mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
- "\n",
- " var rubberband = $('<canvas/>');\n",
- " rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
- "\n",
- " var pass_mouse_events = true;\n",
- "\n",
- " canvas_div.resizable({\n",
- " start: function(event, ui) {\n",
- " pass_mouse_events = false;\n",
- " },\n",
- " resize: function(event, ui) {\n",
- " fig.request_resize(ui.size.width, ui.size.height);\n",
- " },\n",
- " stop: function(event, ui) {\n",
- " pass_mouse_events = true;\n",
- " fig.request_resize(ui.size.width, ui.size.height);\n",
- " },\n",
- " });\n",
- "\n",
- " function mouse_event_fn(event) {\n",
- " if (pass_mouse_events)\n",
- " return fig.mouse_event(event, event['data']);\n",
- " }\n",
- "\n",
- " rubberband.mousedown('button_press', mouse_event_fn);\n",
- " rubberband.mouseup('button_release', mouse_event_fn);\n",
- " // Throttle sequential mouse events to 1 every 20ms.\n",
- " rubberband.mousemove('motion_notify', mouse_event_fn);\n",
- "\n",
- " rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
- " rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
- "\n",
- " canvas_div.on(\"wheel\", function (event) {\n",
- " event = event.originalEvent;\n",
- " event['data'] = 'scroll'\n",
- " if (event.deltaY < 0) {\n",
- " event.step = 1;\n",
- " } else {\n",
- " event.step = -1;\n",
- " }\n",
- " mouse_event_fn(event);\n",
- " });\n",
- "\n",
- " canvas_div.append(canvas);\n",
- " canvas_div.append(rubberband);\n",
- "\n",
- " this.rubberband = rubberband;\n",
- " this.rubberband_canvas = rubberband[0];\n",
- " this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
- " this.rubberband_context.strokeStyle = \"#000000\";\n",
- "\n",
- " this._resize_canvas = function(width, height) {\n",
- " // Keep the size of the canvas, canvas container, and rubber band\n",
- " // canvas in synch.\n",
- " canvas_div.css('width', width)\n",
- " canvas_div.css('height', height)\n",
- "\n",
- " canvas.attr('width', width * mpl.ratio);\n",
- " canvas.attr('height', height * mpl.ratio);\n",
- " canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
- "\n",
- " rubberband.attr('width', width);\n",
- " rubberband.attr('height', height);\n",
- " }\n",
- "\n",
- " // Set the figure to an initial 600x600px, this will subsequently be updated\n",
- " // upon first draw.\n",
- " this._resize_canvas(600, 600);\n",
- "\n",
- " // Disable right mouse context menu.\n",
- " $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
- " return false;\n",
- " });\n",
- "\n",
- " function set_focus () {\n",
- " canvas.focus();\n",
- " canvas_div.focus();\n",
- " }\n",
- "\n",
- " window.setTimeout(set_focus, 100);\n",
- "}\n",
- "\n",
- "mpl.figure.prototype._init_toolbar = function() {\n",
- " var fig = this;\n",
- "\n",
- " var nav_element = $('<div/>')\n",
- " nav_element.attr('style', 'width: 100%');\n",
- " this.root.append(nav_element);\n",
- "\n",
- " // Define a callback function for later on.\n",
- " function toolbar_event(event) {\n",
- " return fig.toolbar_button_onclick(event['data']);\n",
- " }\n",
- " function toolbar_mouse_event(event) {\n",
- " return fig.toolbar_button_onmouseover(event['data']);\n",
- " }\n",
- "\n",
- " for(var toolbar_ind in mpl.toolbar_items) {\n",
- " var name = mpl.toolbar_items[toolbar_ind][0];\n",
- " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
- " var image = mpl.toolbar_items[toolbar_ind][2];\n",
- " var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
- "\n",
- " if (!name) {\n",
- " // put a spacer in here.\n",
- " continue;\n",
- " }\n",
- " var button = $('<button/>');\n",
- " button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
- " 'ui-button-icon-only');\n",
- " button.attr('role', 'button');\n",
- " button.attr('aria-disabled', 'false');\n",
- " button.click(method_name, toolbar_event);\n",
- " button.mouseover(tooltip, toolbar_mouse_event);\n",
- "\n",
- " var icon_img = $('<span/>');\n",
- " icon_img.addClass('ui-button-icon-primary ui-icon');\n",
- " icon_img.addClass(image);\n",
- " icon_img.addClass('ui-corner-all');\n",
- "\n",
- " var tooltip_span = $('<span/>');\n",
- " tooltip_span.addClass('ui-button-text');\n",
- " tooltip_span.html(tooltip);\n",
- "\n",
- " button.append(icon_img);\n",
- " button.append(tooltip_span);\n",
- "\n",
- " nav_element.append(button);\n",
- " }\n",
- "\n",
- " var fmt_picker_span = $('<span/>');\n",
- "\n",
- " var fmt_picker = $('<select/>');\n",
- " fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
- " fmt_picker_span.append(fmt_picker);\n",
- " nav_element.append(fmt_picker_span);\n",
- " this.format_dropdown = fmt_picker[0];\n",
- "\n",
- " for (var ind in mpl.extensions) {\n",
- " var fmt = mpl.extensions[ind];\n",
- " var option = $(\n",
- " '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
- " fmt_picker.append(option)\n",
- " }\n",
- "\n",
- " // Add hover states to the ui-buttons\n",
- " $( \".ui-button\" ).hover(\n",
- " function() { $(this).addClass(\"ui-state-hover\");},\n",
- " function() { $(this).removeClass(\"ui-state-hover\");}\n",
- " );\n",
- "\n",
- " var status_bar = $('<span class=\"mpl-message\"/>');\n",
- " nav_element.append(status_bar);\n",
- " this.message = status_bar[0];\n",
- "}\n",
- "\n",
- "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
- " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
- " // which will in turn request a refresh of the image.\n",
- " this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
- "}\n",
- "\n",
- "mpl.figure.prototype.send_message = function(type, properties) {\n",
- " properties['type'] = type;\n",
- " properties['figure_id'] = this.id;\n",
- " this.ws.send(JSON.stringify(properties));\n",
- "}\n",
- "\n",
- "mpl.figure.prototype.send_draw_message = function() {\n",
- " if (!this.waiting) {\n",
- " this.waiting = true;\n",
- " this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
- " }\n",
- "}\n",
- "\n",
- "\n",
- "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
- " var format_dropdown = fig.format_dropdown;\n",
- " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
- " fig.ondownload(fig, format);\n",
- "}\n",
- "\n",
- "\n",
- "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
- " var size = msg['size'];\n",
- " if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
- " fig._resize_canvas(size[0], size[1]);\n",
- " fig.send_message(\"refresh\", {});\n",
- " };\n",
- "}\n",
- "\n",
- "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
- " var x0 = msg['x0'] / mpl.ratio;\n",
- " var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
- " var x1 = msg['x1'] / mpl.ratio;\n",
- " var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
- " x0 = Math.floor(x0) + 0.5;\n",
- " y0 = Math.floor(y0) + 0.5;\n",
- " x1 = Math.floor(x1) + 0.5;\n",
- " y1 = Math.floor(y1) + 0.5;\n",
- " var min_x = Math.min(x0, x1);\n",
- " var min_y = Math.min(y0, y1);\n",
- " var width = Math.abs(x1 - x0);\n",
- " var height = Math.abs(y1 - y0);\n",
- "\n",
- " fig.rubberband_context.clearRect(\n",
- " 0, 0, fig.canvas.width, fig.canvas.height);\n",
- "\n",
- " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
- "}\n",
- "\n",
- "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
- " // Updates the figure title.\n",
- " fig.header.textContent = msg['label'];\n",
- "}\n",
- "\n",
- "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
- " var cursor = msg['cursor'];\n",
- " switch(cursor)\n",
- " {\n",
- " case 0:\n",
- " cursor = 'pointer';\n",
- " break;\n",
- " case 1:\n",
- " cursor = 'default';\n",
- " break;\n",
- " case 2:\n",
- " cursor = 'crosshair';\n",
- " break;\n",
- " case 3:\n",
- " cursor = 'move';\n",
- " break;\n",
- " }\n",
- " fig.rubberband_canvas.style.cursor = cursor;\n",
- "}\n",
- "\n",
- "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
- " fig.message.textContent = msg['message'];\n",
- "}\n",
- "\n",
- "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
- " // Request the server to send over a new figure.\n",
- " fig.send_draw_message();\n",
- "}\n",
- "\n",
- "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
- " fig.image_mode = msg['mode'];\n",
- "}\n",
- "\n",
- "mpl.figure.prototype.updated_canvas_event = function() {\n",
- " // Called whenever the canvas gets updated.\n",
- " this.send_message(\"ack\", {});\n",
- "}\n",
- "\n",
- "// A function to construct a web socket function for onmessage handling.\n",
- "// Called in the figure constructor.\n",
- "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
- " return function socket_on_message(evt) {\n",
- " if (evt.data instanceof Blob) {\n",
- " /* FIXME: We get \"Resource interpreted as Image but\n",
- " * transferred with MIME type text/plain:\" errors on\n",
- " * Chrome. But how to set the MIME type? It doesn't seem\n",
- " * to be part of the websocket stream */\n",
- " evt.data.type = \"image/png\";\n",
- "\n",
- " /* Free the memory for the previous frames */\n",
- " if (fig.imageObj.src) {\n",
- " (window.URL || window.webkitURL).revokeObjectURL(\n",
- " fig.imageObj.src);\n",
- " }\n",
- "\n",
- " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
- " evt.data);\n",
- " fig.updated_canvas_event();\n",
- " fig.waiting = false;\n",
- " return;\n",
- " }\n",
- " else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
- " fig.imageObj.src = evt.data;\n",
- " fig.updated_canvas_event();\n",
- " fig.waiting = false;\n",
- " return;\n",
- " }\n",
- "\n",
- " var msg = JSON.parse(evt.data);\n",
- " var msg_type = msg['type'];\n",
- "\n",
- " // Call the \"handle_{type}\" callback, which takes\n",
- " // the figure and JSON message as its only arguments.\n",
- " try {\n",
- " var callback = fig[\"handle_\" + msg_type];\n",
- " } catch (e) {\n",
- " console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
- " return;\n",
- " }\n",
- "\n",
- " if (callback) {\n",
- " try {\n",
- " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
- " callback(fig, msg);\n",
- " } catch (e) {\n",
- " console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
- " }\n",
- " }\n",
- " };\n",
- "}\n",
- "\n",
- "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
- "mpl.findpos = function(e) {\n",
- " //this section is from http://www.quirksmode.org/js/events_properties.html\n",
- " var targ;\n",
- " if (!e)\n",
- " e = window.event;\n",
- " if (e.target)\n",
- " targ = e.target;\n",
- " else if (e.srcElement)\n",
- " targ = e.srcElement;\n",
- " if (targ.nodeType == 3) // defeat Safari bug\n",
- " targ = targ.parentNode;\n",
- "\n",
- " // jQuery normalizes the pageX and pageY\n",
- " // pageX,Y are the mouse positions relative to the document\n",
- " // offset() returns the position of the element relative to the document\n",
- " var x = e.pageX - $(targ).offset().left;\n",
- " var y = e.pageY - $(targ).offset().top;\n",
- "\n",
- " return {\"x\": x, \"y\": y};\n",
- "};\n",
- "\n",
- "/*\n",
- " * return a copy of an object with only non-object keys\n",
- " * we need this to avoid circular references\n",
- " * http://stackoverflow.com/a/24161582/3208463\n",
- " */\n",
- "function simpleKeys (original) {\n",
- " return Object.keys(original).reduce(function (obj, key) {\n",
- " if (typeof original[key] !== 'object')\n",
- " obj[key] = original[key]\n",
- " return obj;\n",
- " }, {});\n",
- "}\n",
- "\n",
- "mpl.figure.prototype.mouse_event = function(event, name) {\n",
- " var canvas_pos = mpl.findpos(event)\n",
- "\n",
- " if (name === 'button_press')\n",
- " {\n",
- " this.canvas.focus();\n",
- " this.canvas_div.focus();\n",
- " }\n",
- "\n",
- " var x = canvas_pos.x * mpl.ratio;\n",
- " var y = canvas_pos.y * mpl.ratio;\n",
- "\n",
- " this.send_message(name, {x: x, y: y, button: event.button,\n",
- " step: event.step,\n",
- " guiEvent: simpleKeys(event)});\n",
- "\n",
- " /* This prevents the web browser from automatically changing to\n",
- " * the text insertion cursor when the button is pressed. We want\n",
- " * to control all of the cursor setting manually through the\n",
- " * 'cursor' event from matplotlib */\n",
- " event.preventDefault();\n",
- " return false;\n",
- "}\n",
- "\n",
- "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
- " // Handle any extra behaviour associated with a key event\n",
- "}\n",
- "\n",
- "mpl.figure.prototype.key_event = function(event, name) {\n",
- "\n",
- " // Prevent repeat events\n",
- " if (name == 'key_press')\n",
- " {\n",
- " if (event.which === this._key)\n",
- " return;\n",
- " else\n",
- " this._key = event.which;\n",
- " }\n",
- " if (name == 'key_release')\n",
- " this._key = null;\n",
- "\n",
- " var value = '';\n",
- " if (event.ctrlKey && event.which != 17)\n",
- " value += \"ctrl+\";\n",
- " if (event.altKey && event.which != 18)\n",
- " value += \"alt+\";\n",
- " if (event.shiftKey && event.which != 16)\n",
- " value += \"shift+\";\n",
- "\n",
- " value += 'k';\n",
- " value += event.which.toString();\n",
- "\n",
- " this._key_event_extra(event, name);\n",
- "\n",
- " this.send_message(name, {key: value,\n",
- " guiEvent: simpleKeys(event)});\n",
- " return false;\n",
- "}\n",
- "\n",
- "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
- " if (name == 'download') {\n",
- " this.handle_save(this, null);\n",
- " } else {\n",
- " this.send_message(\"toolbar_button\", {name: name});\n",
- " }\n",
- "};\n",
- "\n",
- "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
- " this.message.textContent = tooltip;\n",
- "};\n",
- "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
- "\n",
- "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
- "\n",
- "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
- " // Create a \"websocket\"-like object which calls the given IPython comm\n",
- " // object with the appropriate methods. Currently this is a non binary\n",
- " // socket, so there is still some room for performance tuning.\n",
- " var ws = {};\n",
- "\n",
- " ws.close = function() {\n",
- " comm.close()\n",
- " };\n",
- " ws.send = function(m) {\n",
- " //console.log('sending', m);\n",
- " comm.send(m);\n",
- " };\n",
- " // Register the callback with on_msg.\n",
- " comm.on_msg(function(msg) {\n",
- " //console.log('receiving', msg['content']['data'], msg);\n",
- " // Pass the mpl event to the overriden (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"
- }
- ],
- "source": [
- "plt.figure()\n",
- "performance.module_eff.plot()\n",
- "plt.show()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 140,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "application/javascript": [
- "/* Put everything inside the global mpl namespace */\n",
- "window.mpl = {};\n",
- "\n",
- "\n",
- "mpl.get_websocket_type = function() {\n",
- " if (typeof(WebSocket) !== 'undefined') {\n",
- " return WebSocket;\n",
- " } else if (typeof(MozWebSocket) !== 'undefined') {\n",
- " return MozWebSocket;\n",
- " } else {\n",
- " alert('Your browser does not have WebSocket support.' +\n",
- " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
- " 'Firefox 4 and 5 are also supported but you ' +\n",
- " 'have to enable WebSockets in about:config.');\n",
- " };\n",
- "}\n",
- "\n",
- "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
- " this.id = figure_id;\n",
- "\n",
- " this.ws = websocket;\n",
- "\n",
- " this.supports_binary = (this.ws.binaryType != undefined);\n",
- "\n",
- " if (!this.supports_binary) {\n",
- " var warnings = document.getElementById(\"mpl-warnings\");\n",
- " if (warnings) {\n",
- " warnings.style.display = 'block';\n",
- " warnings.textContent = (\n",
- " \"This browser does not support binary websocket messages. \" +\n",
- " \"Performance may be slow.\");\n",
- " }\n",
- " }\n",
- "\n",
- " this.imageObj = new Image();\n",
- "\n",
- " this.context = undefined;\n",
- " this.message = undefined;\n",
- " this.canvas = undefined;\n",
- " this.rubberband_canvas = undefined;\n",
- " this.rubberband_context = undefined;\n",
- " this.format_dropdown = undefined;\n",
- "\n",
- " this.image_mode = 'full';\n",
- "\n",
- " this.root = $('<div/>');\n",
- " this._root_extra_style(this.root)\n",
- " this.root.attr('style', 'display: inline-block');\n",
- "\n",
- " $(parent_element).append(this.root);\n",
- "\n",
- " this._init_header(this);\n",
- " this._init_canvas(this);\n",
- " this._init_toolbar(this);\n",
- "\n",
- " var fig = this;\n",
- "\n",
- " this.waiting = false;\n",
- "\n",
- " this.ws.onopen = function () {\n",
- " fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
- " fig.send_message(\"send_image_mode\", {});\n",
- " if (mpl.ratio != 1) {\n",
- " fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
- " }\n",
- " fig.send_message(\"refresh\", {});\n",
- " }\n",
- "\n",
- " this.imageObj.onload = function() {\n",
- " if (fig.image_mode == 'full') {\n",
- " // Full images could contain transparency (where diff images\n",
- " // almost always do), so we need to clear the canvas so that\n",
- " // there is no ghosting.\n",
- " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
- " }\n",
- " fig.context.drawImage(fig.imageObj, 0, 0);\n",
- " };\n",
- "\n",
- " this.imageObj.onunload = function() {\n",
- " fig.ws.close();\n",
- " }\n",
- "\n",
- " this.ws.onmessage = this._make_on_message_function(this);\n",
- "\n",
- " this.ondownload = ondownload;\n",
- "}\n",
- "\n",
- "mpl.figure.prototype._init_header = function() {\n",
- " var titlebar = $(\n",
- " '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
- " 'ui-helper-clearfix\"/>');\n",
- " var titletext = $(\n",
- " '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
- " 'text-align: center; padding: 3px;\"/>');\n",
- " titlebar.append(titletext)\n",
- " this.root.append(titlebar);\n",
- " this.header = titletext[0];\n",
- "}\n",
- "\n",
- "\n",
- "\n",
- "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
- "\n",
- "}\n",
- "\n",
- "\n",
- "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
- "\n",
- "}\n",
- "\n",
- "mpl.figure.prototype._init_canvas = function() {\n",
- " var fig = this;\n",
- "\n",
- " var canvas_div = $('<div/>');\n",
- "\n",
- " canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
- "\n",
- " function canvas_keyboard_event(event) {\n",
- " return fig.key_event(event, event['data']);\n",
- " }\n",
- "\n",
- " canvas_div.keydown('key_press', canvas_keyboard_event);\n",
- " canvas_div.keyup('key_release', canvas_keyboard_event);\n",
- " this.canvas_div = canvas_div\n",
- " this._canvas_extra_style(canvas_div)\n",
- " this.root.append(canvas_div);\n",
- "\n",
- " var canvas = $('<canvas/>');\n",
- " canvas.addClass('mpl-canvas');\n",
- " canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
- "\n",
- " this.canvas = canvas[0];\n",
- " this.context = canvas[0].getContext(\"2d\");\n",
- "\n",
- " var backingStore = this.context.backingStorePixelRatio ||\n",
- "\tthis.context.webkitBackingStorePixelRatio ||\n",
- "\tthis.context.mozBackingStorePixelRatio ||\n",
- "\tthis.context.msBackingStorePixelRatio ||\n",
- "\tthis.context.oBackingStorePixelRatio ||\n",
- "\tthis.context.backingStorePixelRatio || 1;\n",
- "\n",
- " mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
- "\n",
- " var rubberband = $('<canvas/>');\n",
- " rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
- "\n",
- " var pass_mouse_events = true;\n",
- "\n",
- " canvas_div.resizable({\n",
- " start: function(event, ui) {\n",
- " pass_mouse_events = false;\n",
- " },\n",
- " resize: function(event, ui) {\n",
- " fig.request_resize(ui.size.width, ui.size.height);\n",
- " },\n",
- " stop: function(event, ui) {\n",
- " pass_mouse_events = true;\n",
- " fig.request_resize(ui.size.width, ui.size.height);\n",
- " },\n",
- " });\n",
- "\n",
- " function mouse_event_fn(event) {\n",
- " if (pass_mouse_events)\n",
- " return fig.mouse_event(event, event['data']);\n",
- " }\n",
- "\n",
- " rubberband.mousedown('button_press', mouse_event_fn);\n",
- " rubberband.mouseup('button_release', mouse_event_fn);\n",
- " // Throttle sequential mouse events to 1 every 20ms.\n",
- " rubberband.mousemove('motion_notify', mouse_event_fn);\n",
- "\n",
- " rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
- " rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
- "\n",
- " canvas_div.on(\"wheel\", function (event) {\n",
- " event = event.originalEvent;\n",
- " event['data'] = 'scroll'\n",
- " if (event.deltaY < 0) {\n",
- " event.step = 1;\n",
- " } else {\n",
- " event.step = -1;\n",
- " }\n",
- " mouse_event_fn(event);\n",
- " });\n",
- "\n",
- " canvas_div.append(canvas);\n",
- " canvas_div.append(rubberband);\n",
- "\n",
- " this.rubberband = rubberband;\n",
- " this.rubberband_canvas = rubberband[0];\n",
- " this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
- " this.rubberband_context.strokeStyle = \"#000000\";\n",
- "\n",
- " this._resize_canvas = function(width, height) {\n",
- " // Keep the size of the canvas, canvas container, and rubber band\n",
- " // canvas in synch.\n",
- " canvas_div.css('width', width)\n",
- " canvas_div.css('height', height)\n",
- "\n",
- " canvas.attr('width', width * mpl.ratio);\n",
- " canvas.attr('height', height * mpl.ratio);\n",
- " canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
- "\n",
- " rubberband.attr('width', width);\n",
- " rubberband.attr('height', height);\n",
- " }\n",
- "\n",
- " // Set the figure to an initial 600x600px, this will subsequently be updated\n",
- " // upon first draw.\n",
- " this._resize_canvas(600, 600);\n",
- "\n",
- " // Disable right mouse context menu.\n",
- " $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
- " return false;\n",
- " });\n",
- "\n",
- " function set_focus () {\n",
- " canvas.focus();\n",
- " canvas_div.focus();\n",
- " }\n",
- "\n",
- " window.setTimeout(set_focus, 100);\n",
- "}\n",
- "\n",
- "mpl.figure.prototype._init_toolbar = function() {\n",
- " var fig = this;\n",
- "\n",
- " var nav_element = $('<div/>')\n",
- " nav_element.attr('style', 'width: 100%');\n",
- " this.root.append(nav_element);\n",
- "\n",
- " // Define a callback function for later on.\n",
- " function toolbar_event(event) {\n",
- " return fig.toolbar_button_onclick(event['data']);\n",
- " }\n",
- " function toolbar_mouse_event(event) {\n",
- " return fig.toolbar_button_onmouseover(event['data']);\n",
- " }\n",
- "\n",
- " for(var toolbar_ind in mpl.toolbar_items) {\n",
- " var name = mpl.toolbar_items[toolbar_ind][0];\n",
- " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
- " var image = mpl.toolbar_items[toolbar_ind][2];\n",
- " var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
- "\n",
- " if (!name) {\n",
- " // put a spacer in here.\n",
- " continue;\n",
- " }\n",
- " var button = $('<button/>');\n",
- " button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
- " 'ui-button-icon-only');\n",
- " button.attr('role', 'button');\n",
- " button.attr('aria-disabled', 'false');\n",
- " button.click(method_name, toolbar_event);\n",
- " button.mouseover(tooltip, toolbar_mouse_event);\n",
- "\n",
- " var icon_img = $('<span/>');\n",
- " icon_img.addClass('ui-button-icon-primary ui-icon');\n",
- " icon_img.addClass(image);\n",
- " icon_img.addClass('ui-corner-all');\n",
- "\n",
- " var tooltip_span = $('<span/>');\n",
- " tooltip_span.addClass('ui-button-text');\n",
- " tooltip_span.html(tooltip);\n",
- "\n",
- " button.append(icon_img);\n",
- " button.append(tooltip_span);\n",
- "\n",
- " nav_element.append(button);\n",
- " }\n",
- "\n",
- " var fmt_picker_span = $('<span/>');\n",
- "\n",
- " var fmt_picker = $('<select/>');\n",
- " fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
- " fmt_picker_span.append(fmt_picker);\n",
- " nav_element.append(fmt_picker_span);\n",
- " this.format_dropdown = fmt_picker[0];\n",
- "\n",
- " for (var ind in mpl.extensions) {\n",
- " var fmt = mpl.extensions[ind];\n",
- " var option = $(\n",
- " '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
- " fmt_picker.append(option)\n",
- " }\n",
- "\n",
- " // Add hover states to the ui-buttons\n",
- " $( \".ui-button\" ).hover(\n",
- " function() { $(this).addClass(\"ui-state-hover\");},\n",
- " function() { $(this).removeClass(\"ui-state-hover\");}\n",
- " );\n",
- "\n",
- " var status_bar = $('<span class=\"mpl-message\"/>');\n",
- " nav_element.append(status_bar);\n",
- " this.message = status_bar[0];\n",
- "}\n",
- "\n",
- "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
- " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
- " // which will in turn request a refresh of the image.\n",
- " this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
- "}\n",
- "\n",
- "mpl.figure.prototype.send_message = function(type, properties) {\n",
- " properties['type'] = type;\n",
- " properties['figure_id'] = this.id;\n",
- " this.ws.send(JSON.stringify(properties));\n",
- "}\n",
- "\n",
- "mpl.figure.prototype.send_draw_message = function() {\n",
- " if (!this.waiting) {\n",
- " this.waiting = true;\n",
- " this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
- " }\n",
- "}\n",
- "\n",
- "\n",
- "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
- " var format_dropdown = fig.format_dropdown;\n",
- " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
- " fig.ondownload(fig, format);\n",
- "}\n",
- "\n",
- "\n",
- "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
- " var size = msg['size'];\n",
- " if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
- " fig._resize_canvas(size[0], size[1]);\n",
- " fig.send_message(\"refresh\", {});\n",
- " };\n",
- "}\n",
- "\n",
- "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
- " var x0 = msg['x0'] / mpl.ratio;\n",
- " var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
- " var x1 = msg['x1'] / mpl.ratio;\n",
- " var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
- " x0 = Math.floor(x0) + 0.5;\n",
- " y0 = Math.floor(y0) + 0.5;\n",
- " x1 = Math.floor(x1) + 0.5;\n",
- " y1 = Math.floor(y1) + 0.5;\n",
- " var min_x = Math.min(x0, x1);\n",
- " var min_y = Math.min(y0, y1);\n",
- " var width = Math.abs(x1 - x0);\n",
- " var height = Math.abs(y1 - y0);\n",
- "\n",
- " fig.rubberband_context.clearRect(\n",
- " 0, 0, fig.canvas.width, fig.canvas.height);\n",
- "\n",
- " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
- "}\n",
- "\n",
- "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
- " // Updates the figure title.\n",
- " fig.header.textContent = msg['label'];\n",
- "}\n",
- "\n",
- "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
- " var cursor = msg['cursor'];\n",
- " switch(cursor)\n",
- " {\n",
- " case 0:\n",
- " cursor = 'pointer';\n",
- " break;\n",
- " case 1:\n",
- " cursor = 'default';\n",
- " break;\n",
- " case 2:\n",
- " cursor = 'crosshair';\n",
- " break;\n",
- " case 3:\n",
- " cursor = 'move';\n",
- " break;\n",
- " }\n",
- " fig.rubberband_canvas.style.cursor = cursor;\n",
- "}\n",
- "\n",
- "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
- " fig.message.textContent = msg['message'];\n",
- "}\n",
- "\n",
- "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
- " // Request the server to send over a new figure.\n",
- " fig.send_draw_message();\n",
- "}\n",
- "\n",
- "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
- " fig.image_mode = msg['mode'];\n",
- "}\n",
- "\n",
- "mpl.figure.prototype.updated_canvas_event = function() {\n",
- " // Called whenever the canvas gets updated.\n",
- " this.send_message(\"ack\", {});\n",
- "}\n",
- "\n",
- "// A function to construct a web socket function for onmessage handling.\n",
- "// Called in the figure constructor.\n",
- "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
- " return function socket_on_message(evt) {\n",
- " if (evt.data instanceof Blob) {\n",
- " /* FIXME: We get \"Resource interpreted as Image but\n",
- " * transferred with MIME type text/plain:\" errors on\n",
- " * Chrome. But how to set the MIME type? It doesn't seem\n",
- " * to be part of the websocket stream */\n",
- " evt.data.type = \"image/png\";\n",
- "\n",
- " /* Free the memory for the previous frames */\n",
- " if (fig.imageObj.src) {\n",
- " (window.URL || window.webkitURL).revokeObjectURL(\n",
- " fig.imageObj.src);\n",
- " }\n",
- "\n",
- " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
- " evt.data);\n",
- " fig.updated_canvas_event();\n",
- " fig.waiting = false;\n",
- " return;\n",
- " }\n",
- " else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
- " fig.imageObj.src = evt.data;\n",
- " fig.updated_canvas_event();\n",
- " fig.waiting = false;\n",
- " return;\n",
- " }\n",
- "\n",
- " var msg = JSON.parse(evt.data);\n",
- " var msg_type = msg['type'];\n",
- "\n",
- " // Call the \"handle_{type}\" callback, which takes\n",
- " // the figure and JSON message as its only arguments.\n",
- " try {\n",
- " var callback = fig[\"handle_\" + msg_type];\n",
- " } catch (e) {\n",
- " console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
- " return;\n",
- " }\n",
- "\n",
- " if (callback) {\n",
- " try {\n",
- " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
- " callback(fig, msg);\n",
- " } catch (e) {\n",
- " console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
- " }\n",
- " }\n",
- " };\n",
- "}\n",
- "\n",
- "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
- "mpl.findpos = function(e) {\n",
- " //this section is from http://www.quirksmode.org/js/events_properties.html\n",
- " var targ;\n",
- " if (!e)\n",
- " e = window.event;\n",
- " if (e.target)\n",
- " targ = e.target;\n",
- " else if (e.srcElement)\n",
- " targ = e.srcElement;\n",
- " if (targ.nodeType == 3) // defeat Safari bug\n",
- " targ = targ.parentNode;\n",
- "\n",
- " // jQuery normalizes the pageX and pageY\n",
- " // pageX,Y are the mouse positions relative to the document\n",
- " // offset() returns the position of the element relative to the document\n",
- " var x = e.pageX - $(targ).offset().left;\n",
- " var y = e.pageY - $(targ).offset().top;\n",
- "\n",
- " return {\"x\": x, \"y\": y};\n",
- "};\n",
- "\n",
- "/*\n",
- " * return a copy of an object with only non-object keys\n",
- " * we need this to avoid circular references\n",
- " * http://stackoverflow.com/a/24161582/3208463\n",
- " */\n",
- "function simpleKeys (original) {\n",
- " return Object.keys(original).reduce(function (obj, key) {\n",
- " if (typeof original[key] !== 'object')\n",
- " obj[key] = original[key]\n",
- " return obj;\n",
- " }, {});\n",
- "}\n",
- "\n",
- "mpl.figure.prototype.mouse_event = function(event, name) {\n",
- " var canvas_pos = mpl.findpos(event)\n",
- "\n",
- " if (name === 'button_press')\n",
- " {\n",
- " this.canvas.focus();\n",
- " this.canvas_div.focus();\n",
- " }\n",
- "\n",
- " var x = canvas_pos.x * mpl.ratio;\n",
- " var y = canvas_pos.y * mpl.ratio;\n",
- "\n",
- " this.send_message(name, {x: x, y: y, button: event.button,\n",
- " step: event.step,\n",
- " guiEvent: simpleKeys(event)});\n",
- "\n",
- " /* This prevents the web browser from automatically changing to\n",
- " * the text insertion cursor when the button is pressed. We want\n",
- " * to control all of the cursor setting manually through the\n",
- " * 'cursor' event from matplotlib */\n",
- " event.preventDefault();\n",
- " return false;\n",
- "}\n",
- "\n",
- "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
- " // Handle any extra behaviour associated with a key event\n",
- "}\n",
- "\n",
- "mpl.figure.prototype.key_event = function(event, name) {\n",
- "\n",
- " // Prevent repeat events\n",
- " if (name == 'key_press')\n",
- " {\n",
- " if (event.which === this._key)\n",
- " return;\n",
- " else\n",
- " this._key = event.which;\n",
- " }\n",
- " if (name == 'key_release')\n",
- " this._key = null;\n",
- "\n",
- " var value = '';\n",
- " if (event.ctrlKey && event.which != 17)\n",
- " value += \"ctrl+\";\n",
- " if (event.altKey && event.which != 18)\n",
- " value += \"alt+\";\n",
- " if (event.shiftKey && event.which != 16)\n",
- " value += \"shift+\";\n",
- "\n",
- " value += 'k';\n",
- " value += event.which.toString();\n",
- "\n",
- " this._key_event_extra(event, name);\n",
- "\n",
- " this.send_message(name, {key: value,\n",
- " guiEvent: simpleKeys(event)});\n",
- " return false;\n",
- "}\n",
- "\n",
- "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
- " if (name == 'download') {\n",
- " this.handle_save(this, null);\n",
- " } else {\n",
- " this.send_message(\"toolbar_button\", {name: name});\n",
- " }\n",
- "};\n",
- "\n",
- "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
- " this.message.textContent = tooltip;\n",
- "};\n",
- "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
- "\n",
- "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
- "\n",
- "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
- " // Create a \"websocket\"-like object which calls the given IPython comm\n",
- " // object with the appropriate methods. Currently this is a non binary\n",
- " // socket, so there is still some room for performance tuning.\n",
- " var ws = {};\n",
- "\n",
- " ws.close = function() {\n",
- " comm.close()\n",
- " };\n",
- " ws.send = function(m) {\n",
- " //console.log('sending', m);\n",
- " comm.send(m);\n",
- " };\n",
- " // Register the callback with on_msg.\n",
- " comm.on_msg(function(msg) {\n",
- " //console.log('receiving', msg['content']['data'], msg);\n",
- " // Pass the mpl event to the overriden (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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\" 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- "<IPython.core.display.HTML object>"
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- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "plt.figure()\n",
- "performance.PF_mean.plot()\n",
- "plt.show()"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# Combine efficiencies with PV potential"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 208,
- "metadata": {},
- "outputs": [],
- "source": [
- "ROOFS='/work/hyenergy/output/solar_potential/geographic_potential/CH_ROOFS_all_replaced.csv'\n",
- "roofs = pd.read_csv(ROOFS, usecols = ['DF_UID', 'XCOORD', 'YCOORD'])"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 209,
- "metadata": {},
- "outputs": [],
- "source": [
- "roofs['chx'] = util.round_to_interval(roofs['XCOORD'] - 500, 1000) + 500\n",
- "roofs['chy'] = util.round_to_interval(roofs['YCOORD'] - 500, 1000) + 500"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 210,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/html": [
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- " vertical-align: middle;\n",
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- "<table border=\"1\" class=\"dataframe\">\n",
- " <thead>\n",
- " <tr style=\"text-align: right;\">\n",
- " <th></th>\n",
- " <th>DF_UID</th>\n",
- " <th>XCOORD</th>\n",
- " <th>YCOORD</th>\n",
- " <th>chx</th>\n",
- " <th>chy</th>\n",
- " </tr>\n",
- " </thead>\n",
- " <tbody>\n",
- " <tr>\n",
- " <th>0</th>\n",
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- " <tr>\n",
- " <th>3</th>\n",
- " <td>4</td>\n",
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- " <th>4</th>\n",
- " <td>5</td>\n",
- " <td>621692.928934</td>\n",
- " <td>254250.448974</td>\n",
- " <td>621500.0</td>\n",
- " <td>254500.0</td>\n",
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- "text/plain": [
- " DF_UID XCOORD YCOORD chx chy\n",
- "0 1 621674.951286 254203.972784 621500.0 254500.0\n",
- "1 2 621675.374179 254206.313551 621500.0 254500.0\n",
- "2 3 621673.977050 254186.956803 621500.0 254500.0\n",
- "3 4 621696.695450 254249.767806 621500.0 254500.0\n",
- "4 5 621692.928934 254250.448974 621500.0 254500.0"
- ]
- },
- "execution_count": 210,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "roofs.head()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 211,
- "metadata": {},
- "outputs": [],
- "source": [
- "performance = xr.open_dataset('/work/hyenergy/output/solar_potential/technical_potential/pv_efficiencies.nc')"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 212,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<xarray.Dataset>\n",
- "Dimensions: (G_t: 1003, T_amb: 59)\n",
- "Coordinates:\n",
- " * G_t (G_t) int64 1 2 3 4 5 6 7 ... 997 998 999 1000 1001 1002 1003\n",
- " * T_amb (T_amb) int64 -24 -23 -22 -21 -20 -19 ... 29 30 31 32 33 34\n",
- "Data variables:\n",
- " T_cell (G_t, T_amb) float64 ...\n",
- " module_eff (G_t, T_amb) float64 ...\n",
- " losses (G_t, T_amb) float64 ...\n",
- " inverter_eff (G_t, T_amb) float64 ...\n",
- " PF (G_t, T_amb) float64 ...\n",
- " PF_mean (G_t) float64 ..."
- ]
- },
- "execution_count": 212,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "performance"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 213,
- "metadata": {},
- "outputs": [],
- "source": [
- "T_max_mmd = xr.open_dataset('/work/hyenergy/output/solar_potential/technical_potential/Tmax_surface_mmd.nc')"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 214,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<xarray.Dataset>\n",
- "Dimensions: (chx: 370, chy: 240, month: 12)\n",
- "Coordinates:\n",
- " * chx (chx) float64 4.745e+05 4.755e+05 4.765e+05 ... 8.425e+05 8.435e+05\n",
- " * chy (chy) float64 6.45e+04 6.55e+04 6.65e+04 ... 3.025e+05 3.035e+05\n",
- " lon (chy, chx) float32 ...\n",
- " lat (chy, chx) float32 ...\n",
- " * month (month) float64 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0\n",
- "Data variables:\n",
- " TmaxD (month, chy, chx) float32 ...\n",
- " stddev (month, chy, chx) float32 ..."
- ]
- },
- "execution_count": 214,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "T_max_mmd"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 215,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<xarray.Dataset>\n",
- "Dimensions: (DF_UID: 9639231, timestamp: 146)\n",
- "Coordinates:\n",
- " * timestamp (timestamp) datetime64[ns] 2001-01-15T08:00:00 ... 2001-12-15T15:00:00\n",
- " * DF_UID (DF_UID) int64 1 2 3 4 ... 9890021 9890022 9890023\n",
- "Data variables:\n",
- " tilted_irradiance (DF_UID, timestamp) float64 dask.array<shape=(9639231, 146), chunksize=(100000, 146)>\n",
- " panelled_area (DF_UID) float64 dask.array<shape=(9639231,), chunksize=(100000,)>\n",
- " tilted_area (DF_UID) float64 dask.array<shape=(9639231,), chunksize=(100000,)>\n",
- " available_area (DF_UID) float64 dask.array<shape=(9639231,), chunksize=(100000,)>\n",
- " efficiency float64 ...\n",
- " performance_factor float64 ...\n",
- " pv_potential (DF_UID, timestamp) float64 dask.array<shape=(9639231, 146), chunksize=(100000, 146)>\n",
- " yearly_kWh_m2 (DF_UID) float64 dask.array<shape=(9639231,), chunksize=(100000,)>\n",
- " yearly_PV_kWh (DF_UID) float64 dask.array<shape=(9639231,), chunksize=(100000,)>\n",
- " yearly_PV_all_area (DF_UID) float64 dask.array<shape=(9639231,), chunksize=(100000,)>"
- ]
- },
- "execution_count": 215,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "PV_hourly"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "##### Treat every timestamp independently"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 217,
- "metadata": {
- "scrolled": true
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Finished iteration 0 in 64.138s\n",
- "Finished iteration 1 in 36.358s\n",
- "Finished iteration 2 in 39.396s\n",
- "Finished iteration 3 in 42.460s\n",
- "Finished iteration 4 in 43.976s\n",
- "Finished iteration 5 in 41.098s\n"
- ]
- },
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "\n",
- "KeyboardInterrupt\n",
- "\n"
- ]
- }
- ],
- "source": [
- "for i, t in enumerate(PV_hourly.timestamp):\n",
- " tt = time.time()\n",
- " \n",
- " # get month for maximum temperature\n",
- " month = int(t.dt.month)\n",
- " \n",
- " # get tilted irradiance for given timestamp\n",
- " Gt = PV_hourly.sel(timestamp = t).tilted_irradiance.to_dataframe().reset_index()\n",
- " Gt['G_t'] = np.round(Gt.tilted_irradiance)\n",
- " \n",
- " # get maximum temperature\n",
- " Tmax = T_max_mmd.TmaxD.sel(month = month).to_dataframe().dropna().reset_index().drop(columns = ['lon', 'lat', 'month'])\n",
- " Tmax['T_amb'] = np.round(Tmax['TmaxD'])\n",
- " \n",
- " # get efficiency dataframe\n",
- " eff = performance.to_dataframe().reset_index().drop(columns = ['T_cell', 'losses', 'inverter_eff', 'PF'])\n",
- " \n",
- " # create dataset with all merged information\n",
- " tmp = roofs.merge(Tmax, on = ['chx', 'chy'], how = 'left')\n",
- " tmp = tmp.merge(Gt, on = 'DF_UID', how = 'left')\n",
- " roofs_w_eff = tmp.merge(eff, on = ['T_amb', 'G_t'], how = 'left')\n",
- " \n",
- " # create xarray dataset from the relevant information and save intermediate file\n",
- " eff_xr = roofs_w_eff.set_index(['DF_UID', 'timestamp'])[['TmaxD', 'module_eff', 'PF_mean']].to_xarray()\n",
- " eff_xr.to_netcdf('/scratch/walch/scratch/tmp/eff_model_%d.nc' %i)\n",
- " \n",
- " print('Finished iteration %d in %.3fs' %(i, time.time()-tt))\n",
- " "
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "scrolled": true
- },
- "outputs": [],
- "source": [
- "eff = []\n",
- "for i in range(10):\n",
- " eff.append(xr.open_mfdataset('/scratch/walch/scratch/tmp/eff_model_%d*' %i, chunks = {'DF_UID': 100000}))\n",
- " \n",
- "eff_xr = xr.concat(eff, dim = 'timestamp').sortby('timestamp')"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "eff_xr.to_netcdf('/scratch/walch/scratch/tmp/efficiencies.nc')"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# Alternative comparison"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 8,
- "metadata": {},
- "outputs": [],
- "source": [
- "fp = '/scratch/walch/workspace_tilted_irrad/tilted_irradiance_SVF_nobias.nc'\n",
- "Gt = xr.open_mfdataset(fp, chunks = {'DF_UID':100000})"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 9,
- "metadata": {},
- "outputs": [],
- "source": [
- "fp = '/scratch/walch/workspace_tilted_irrad/TmaxD_proj_roofs.nc'\n",
- "TmaxD = xr.open_mfdataset(fp, chunks = {'DF_UID':100000})"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 10,
- "metadata": {},
- "outputs": [],
- "source": [
- "efficiency = xr.open_dataset( '/work/hyenergy/output/solar_potential/technical_potential/pv_efficiencies.nc' )"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 11,
- "metadata": {},
- "outputs": [],
- "source": [
- "TmaxD['T_amb'] = TmaxD.TmaxD.astype(int)\n",
- "TmaxD['T_amb'] = TmaxD['T_amb'].where((TmaxD.T_amb >= -100) & (TmaxD.T_amb <= 100))"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 12,
- "metadata": {},
- "outputs": [],
- "source": [
- "Gt['G_t'] = Gt.tilted_irradiance.astype(int)\n",
- "Gt['G_t'] = Gt['G_t'].where((Gt.G_t >= 0) & (Gt.G_t <= 5000))"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 13,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<xarray.Dataset>\n",
- "Dimensions: (DF_UID: 9639231, timestamp: 146)\n",
- "Coordinates:\n",
- " * timestamp (timestamp) datetime64[ns] 2001-01-15T08:00:00 ... 2001-12-15T15:00:00\n",
- " * DF_UID (DF_UID) int64 1 2 3 4 5 ... 9890020 9890021 9890022 9890023\n",
- "Data variables:\n",
- " TmaxD (DF_UID, timestamp) float32 dask.array<shape=(9639231, 146), chunksize=(100000, 146)>\n",
- " T_amb (DF_UID, timestamp) float64 dask.array<shape=(9639231, 146), chunksize=(100000, 146)>"
- ]
- },
- "execution_count": 13,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "TmaxD"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 14,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<xarray.Dataset>\n",
- "Dimensions: (DF_UID: 9639231, timestamp: 146)\n",
- "Coordinates:\n",
- " * timestamp (timestamp) datetime64[ns] 2001-01-15T08:00:00 ... 2001-12-15T15:00:00\n",
- " * DF_UID (DF_UID) int64 1 2 3 4 ... 9890021 9890022 9890023\n",
- "Data variables:\n",
- " tilted_irradiance (DF_UID, timestamp) float32 dask.array<shape=(9639231, 146), chunksize=(100000, 146)>\n",
- " yearly_kWh_m2 (DF_UID) float32 dask.array<shape=(9639231,), chunksize=(100000,)>\n",
- " G_t (DF_UID, timestamp) float64 dask.array<shape=(9639231, 146), chunksize=(100000, 146)>"
- ]
- },
- "execution_count": 14,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "Gt"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 23,
- "metadata": {},
- "outputs": [],
- "source": [
- "eff = efficiency[['module_eff', 'PF_mean']]"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 61,
- "metadata": {},
- "outputs": [],
- "source": [
- "eff_df = eff.to_dataframe().reset_index()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 70,
- "metadata": {},
- "outputs": [],
- "source": [
- "ds = xr.merge([Gt.G_t, TmaxD.T_amb])"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 72,
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "0 100000\n",
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- ]
- }
- ],
- "source": [
- "BATCH_SIZE = 100000\n",
- "N_BATCHES = int(np.ceil(len(Gt.DF_UID)/100000))\n",
- "\n",
- "for i in range(N_BATCHES):\n",
- " tt = time.time()\n",
- " start = i * BATCH_SIZE\n",
- " end = min((i+1) * BATCH_SIZE, len(Gt.DF_UID))\n",
- " print(start, end)\n",
- " \n",
- " curr_ds = ds.isel(DF_UID = range(start, end)).dropna(dim = 'timestamp').compute()\n",
- " df = curr_ds.to_dataframe().reset_index().merge(eff_df, how = 'left', on = ['G_t', 'T_amb'])\n",
- " \n",
- " ds_out = df.set_index(['DF_UID', 'timestamp']).to_xarray()[['module_eff', 'PF_mean']]\n",
- " ds_out.to_netcdf('/scratch/walch/workspace_tilted_irrad/files/eff_v2_%d.nc' %i)\n",
- " print('Finished iteration %d in %.3fs' %(i, time.time()-tt))"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 2,
- "metadata": {},
- "outputs": [],
- "source": [
- "eff_all = xr.open_mfdataset('/scratch/walch/workspace_tilted_irrad/files/eff_v2_*.nc')"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 6,
- "metadata": {},
- "outputs": [],
- "source": [
- "eff_all = eff_all.astype('float32')"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 7,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<xarray.Dataset>\n",
- "Dimensions: (DF_UID: 9639231, timestamp: 143)\n",
- "Coordinates:\n",
- " * timestamp (timestamp) datetime64[ns] 2001-01-15T08:00:00 ... 2001-12-15T15:00:00\n",
- " * DF_UID (DF_UID) int64 1 2 3 4 5 ... 9890020 9890021 9890022 9890023\n",
- "Data variables:\n",
- " module_eff (DF_UID, timestamp) float32 dask.array<shape=(9639231, 143), chunksize=(100000, 143)>\n",
- " PF_mean (DF_UID, timestamp) float32 dask.array<shape=(9639231, 143), chunksize=(100000, 143)>"
- ]
- },
- "execution_count": 7,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "eff_all"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 9,
- "metadata": {},
- "outputs": [],
- "source": [
- "eff_all.to_netcdf('/scratch/walch/workspace_tilted_irrad/eff_new_SVF_nobias.nc')"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": []
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# Spielwiese"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Correct original PV pot by corrected efficiencies"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 2,
- "metadata": {},
- "outputs": [],
- "source": [
- "pv_pot = xr.open_mfdataset('/scratch/walch/workspace_tilted_irrad/pv_potential_w_efficiency_new.nc', \n",
- " chunks = {'DF_UID' : 100000})"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 3,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<xarray.Dataset>\n",
- "Dimensions: (DF_UID: 9639231, timestamp: 146)\n",
- "Coordinates:\n",
- " * DF_UID (DF_UID) int64 1 2 3 4 ... 9890021 9890022 9890023\n",
- " * timestamp (timestamp) datetime64[ns] 2001-01-15T08:00:00 ... 2001-12-15T15:00:00\n",
- "Data variables:\n",
- " TmaxD (DF_UID, timestamp) float32 dask.array<shape=(9639231, 146), chunksize=(100000, 146)>\n",
- " module_eff (DF_UID, timestamp) float64 dask.array<shape=(9639231, 146), chunksize=(100000, 146)>\n",
- " PF_mean (DF_UID, timestamp) float64 dask.array<shape=(9639231, 146), chunksize=(100000, 146)>\n",
- " tilted_irradiance (DF_UID, timestamp) float64 dask.array<shape=(9639231, 146), chunksize=(100000, 146)>\n",
- " pv_potential (DF_UID, timestamp) float64 dask.array<shape=(9639231, 146), chunksize=(100000, 146)>\n",
- " yearly_kWh_m2 (DF_UID) float64 dask.array<shape=(9639231,), chunksize=(100000,)>\n",
- " yearly_PV_kWh (DF_UID) float64 dask.array<shape=(9639231,), chunksize=(100000,)>"
- ]
- },
- "execution_count": 3,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "pv_pot"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 4,
- "metadata": {},
- "outputs": [],
- "source": [
- "eff = xr.open_dataset('/scratch/walch/workspace_tilted_irrad/eff_new_SVF_nobias.nc', \n",
- " chunks = {'DF_UID' : 100000})"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 5,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<xarray.Dataset>\n",
- "Dimensions: (DF_UID: 9639231, timestamp: 143)\n",
- "Coordinates:\n",
- " * timestamp (timestamp) datetime64[ns] 2001-01-15T08:00:00 ... 2001-12-15T15:00:00\n",
- " * DF_UID (DF_UID) int64 1 2 3 4 5 ... 9890020 9890021 9890022 9890023\n",
- "Data variables:\n",
- " module_eff (DF_UID, timestamp) float32 dask.array<shape=(9639231, 143), chunksize=(100000, 143)>\n",
- " PF_mean (DF_UID, timestamp) float32 dask.array<shape=(9639231, 143), chunksize=(100000, 143)>"
- ]
- },
- "execution_count": 5,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "eff"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 7,
- "metadata": {},
- "outputs": [],
- "source": [
- "pv_new = pv_pot.pv_potential / (pv_pot.module_eff * pv_pot.PF_mean) * (eff.module_eff * eff.PF_mean)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 17,
- "metadata": {},
- "outputs": [],
- "source": [
- "pv_cmp = xr.merge([pv_new.rename('EPV_new'), pv_pot.pv_potential.rename('EPV_old')])"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 23,
- "metadata": {},
- "outputs": [],
- "source": [
- "EPV_new_annual = util.get_yearly_sum(pv_cmp, 'EPV_new') / 1000"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 25,
- "metadata": {},
- "outputs": [
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "/home/walch/.local/lib/python3.6/site-packages/dask/core.py:137: RuntimeWarning: invalid value encountered in true_divide\n",
- " return func(*args2)\n"
- ]
- },
- {
- "data": {
- "text/plain": [
- "<xarray.DataArray ()>\n",
- "array(38528060942.136536)"
- ]
- },
- "execution_count": 25,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "EPV_new_annual.sum().compute()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 19,
- "metadata": {},
- "outputs": [],
- "source": [
- "pv_cmp['diff'] = pv_cmp.EPV_new - pv_cmp.EPV_old"
- ]
- },
- {
- "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 overriden (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": [
- "[<matplotlib.lines.Line2D at 0x7f7f20287198>]"
- ]
- },
- "execution_count": 22,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "DF_UID = 123005\n",
- "plt.plot(pv_cmp.isel(DF_UID = DF_UID)['diff'].values)\n",
- "plt.plot(pv_cmp.isel(DF_UID = DF_UID)['EPV_new'].values)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 26,
- "metadata": {},
- "outputs": [],
- "source": [
- "pv_out = xr.merge([pv_new.rename('pv_potential'), EPV_new_annual.rename('yearly_PV_kWh')])"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 28,
- "metadata": {},
- "outputs": [],
- "source": [
- "pv_out = pv_out.astype('float32')"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 29,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<xarray.Dataset>\n",
- "Dimensions: (DF_UID: 9639231, timestamp: 143)\n",
- "Coordinates:\n",
- " * DF_UID (DF_UID) int64 1 2 3 4 5 ... 9890020 9890021 9890022 9890023\n",
- " * timestamp (timestamp) datetime64[ns] 2001-01-15T08:00:00 ... 2001-12-15T15:00:00\n",
- "Data variables:\n",
- " pv_potential (DF_UID, timestamp) float32 dask.array<shape=(9639231, 143), chunksize=(100000, 143)>\n",
- " yearly_PV_kWh (DF_UID) float32 dask.array<shape=(9639231,), chunksize=(100000,)>"
- ]
- },
- "execution_count": 29,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "pv_out"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 30,
- "metadata": {},
- "outputs": [],
- "source": [
- "pv_out.to_netcdf('/scratch/walch/workspace_tilted_irrad/pv_potential_SVF_eff_nobias.nc')"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": []
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": []
- },
- {
- "cell_type": "code",
- "execution_count": 2,
- "metadata": {
- "scrolled": false
- },
- "outputs": [],
- "source": [
- "pv_pot = xr.open_mfdataset('/scratch/walch/workspace_tilted_irrad/pv_potential_SVF_eff_nobias.nc')"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 17,
- "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 overriden (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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- "<IPython.core.display.HTML object>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "plt.figure()\n",
- "plt.plot(pv_pot.isel(DF_UID = 22249).pv_potential.values)\n",
- "plt.show()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": []
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": []
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": []
- },
- {
- "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"
+ "version": "3.6.1"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
diff --git a/Shading/partly_shaded_viz.ipynb b/Shading/partly_shaded_viz.ipynb
deleted file mode 100644
index a743f96..0000000
--- a/Shading/partly_shaded_viz.ipynb
+++ /dev/null
@@ -1,61 +0,0 @@
-{
- "cells": [
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "import numpy as np\n",
- "import pandas as pd\n",
- "import xarray as xr\n",
- "\n",
- "from partly_shading_conversion import combine_partly_shading_from_file\n",
- "\n",
- "%matplotlib notebook\n",
- "import matplotlib.pyplot as plt\n",
- "\n",
- "import sys\n",
- "import os"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "path = '/work/hyenergy/output/solar_potential/geographic_potential/available_area/shading_stats'\n",
- "data = xr.open_mfdataset( os.path.join( path, 'CH_partly_shading_replaced_debiased.nc' ) )"
- ]
- },
- {
- "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": "3.6.1"
- }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
diff --git a/Tilted_irradiance/.ipynb_checkpoints/skyview_factor-checkpoint.ipynb b/Tilted_irradiance/.ipynb_checkpoints/skyview_factor-checkpoint.ipynb
index 0db6b11..18d9da6 100644
--- a/Tilted_irradiance/.ipynb_checkpoints/skyview_factor-checkpoint.ipynb
+++ b/Tilted_irradiance/.ipynb_checkpoints/skyview_factor-checkpoint.ipynb
@@ -1,6699 +1,9762 @@
{
"cells": [
{
"cell_type": "code",
- "execution_count": 23,
+ "execution_count": 1,
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "/home/walch/miniconda3/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 pandas as pd\n",
"import xarray as xr\n",
"import numpy as np\n",
"from pvlib.tools import cosd\n",
"import scipy.stats as stats\n",
"\n",
"%matplotlib notebook\n",
"import matplotlib.pyplot as plt\n",
"\n",
+ "import calendar\n",
+ "\n",
"import os\n",
"import time\n",
"import util"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"path = '/work/hyenergy/output/solar_potential/geographic_potential/tilted_irradiance/'\n",
"skyview_stats = pd.read_csv( os.path.join(path, 'skyview_stats.csv') ) # from 2m DOM\n",
"merged_stats = pd.read_csv( os.path.join(path, 'skyview_merged_stats.csv') )"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
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" <td>0.596541</td>\n",
" <td>0.166124</td>\n",
" <td>0.508238</td>\n",
" <td>0.508238</td>\n",
" <td>0.052079</td>\n",
" <td>0.002712</td>\n",
" <td>10.247045</td>\n",
" <td>4.574139</td>\n",
" <td>4.574139</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" zone label non_null_cells null_cells min max range \\\n",
"0 4879560 NaN 20 0 0.448777 0.579490 0.130713 \n",
"1 4879561 NaN 9 0 0.437539 0.626010 0.188472 \n",
"2 4879562 NaN 15 0 0.525769 0.631051 0.105282 \n",
"3 4879563 NaN 6 0 0.502072 0.614747 0.112675 \n",
"4 4879564 NaN 9 0 0.430417 0.596541 0.166124 \n",
"\n",
" mean mean_of_abs stddev variance coeff_var sum sum_abs \n",
"0 0.537930 0.537930 0.035747 0.001278 6.645317 10.758608 10.758608 \n",
"1 0.543964 0.543964 0.061913 0.003833 11.381847 4.895678 4.895678 \n",
"2 0.601935 0.601935 0.031992 0.001024 5.314931 9.029022 9.029022 \n",
"3 0.568163 0.568163 0.041745 0.001743 7.347364 3.408977 3.408977 \n",
"4 0.508238 0.508238 0.052079 0.002712 10.247045 4.574139 4.574139 "
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"skyview_stats.head()"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"212059"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(skyview_stats)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"text/plain": [
"zone 5.004933e+06\n",
"label NaN\n",
"non_null_cells 1.998777e+01\n",
"null_cells 0.000000e+00\n",
"min 6.067868e-01\n",
"max 8.168479e-01\n",
"range 2.100611e-01\n",
"mean 7.272358e-01\n",
"mean_of_abs 7.272358e-01\n",
"stddev 6.349468e-02\n",
"variance 5.760109e-03\n",
"coeff_var 9.160844e+00\n",
"sum 1.530654e+01\n",
"sum_abs 1.530654e+01\n",
"dtype: float64"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"skyview_stats.mean()"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
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" .dataframe tbody tr th:only-of-type {\n",
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" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>zone</th>\n",
" <th>label</th>\n",
" <th>non_null_cells</th>\n",
" <th>null_cells</th>\n",
" <th>min</th>\n",
" <th>max</th>\n",
" <th>range</th>\n",
" <th>mean</th>\n",
" <th>mean_of_abs</th>\n",
" <th>stddev</th>\n",
" <th>variance</th>\n",
" <th>coeff_var</th>\n",
" <th>sum</th>\n",
" <th>sum_abs</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>4817081</td>\n",
" <td>NaN</td>\n",
" <td>406</td>\n",
" <td>0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
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" <td>0.0</td>\n",
" <td>406.0</td>\n",
" <td>406.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>4817082</td>\n",
" <td>NaN</td>\n",
" <td>432</td>\n",
" <td>0</td>\n",
" <td>1.0</td>\n",
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" <td>0.0</td>\n",
" <td>432.0</td>\n",
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" <tr>\n",
" <th>2</th>\n",
" <td>4817083</td>\n",
" <td>NaN</td>\n",
" <td>423</td>\n",
" <td>0</td>\n",
" <td>1.0</td>\n",
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" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>423.0</td>\n",
" <td>423.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>4817084</td>\n",
" <td>NaN</td>\n",
" <td>419</td>\n",
" <td>0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
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" <td>0.0</td>\n",
" <td>419.0</td>\n",
" <td>419.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>4817085</td>\n",
" <td>NaN</td>\n",
" <td>535</td>\n",
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" <td>1.0</td>\n",
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" <td>1.0</td>\n",
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" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>535.0</td>\n",
" <td>535.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" zone label non_null_cells null_cells min max range mean \\\n",
"0 4817081 NaN 406 0 1.0 1.0 0.0 1.0 \n",
"1 4817082 NaN 432 0 1.0 1.0 0.0 1.0 \n",
"2 4817083 NaN 423 0 1.0 1.0 0.0 1.0 \n",
"3 4817084 NaN 419 0 1.0 1.0 0.0 1.0 \n",
"4 4817085 NaN 535 0 1.0 1.0 0.0 1.0 \n",
"\n",
" mean_of_abs stddev variance coeff_var sum sum_abs \n",
"0 1.0 0.0 0.0 0.0 406.0 406.0 \n",
"1 1.0 0.0 0.0 0.0 432.0 432.0 \n",
"2 1.0 0.0 0.0 0.0 423.0 423.0 \n",
"3 1.0 0.0 0.0 0.0 419.0 419.0 \n",
"4 1.0 0.0 0.0 0.0 535.0 535.0 "
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"merged_stats.head()"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"244075"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(merged_stats)"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"zone 4.998131e+06\n",
"label NaN\n",
"non_null_cells 2.903269e+02\n",
"null_cells 0.000000e+00\n",
"min 3.634644e-01\n",
"max 8.380713e-01\n",
"range 4.746069e-01\n",
"mean 6.776022e-01\n",
"mean_of_abs 6.776022e-01\n",
"stddev 8.572729e-02\n",
"variance 1.065515e-02\n",
"coeff_var 1.509738e+01\n",
"sum 2.070582e+02\n",
"sum_abs 2.070582e+02\n",
"dtype: float64"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"merged_stats.mean()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Convert skyview stats to suitable dataframe"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
"skyview_stats.rename(columns = {'zone' : 'DF_UID', 'mean' : 'SVF_2m', 'stddev' : 'std_2m'}, inplace = True)\n",
"skyview_2m = skyview_stats.set_index('DF_UID')[['SVF_2m', 'std_2m']]"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [],
"source": [
"merged_stats.rename(columns = {'zone' : 'DF_UID', 'mean' : 'SVF_50cm', 'stddev' : 'std_50cm'}, inplace = True)\n",
"skyview_50cm = merged_stats.set_index('DF_UID')[['SVF_50cm', 'std_50cm']]"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [],
"source": [
"skyview = skyview_2m.merge(skyview_50cm, left_index = True, right_index = True, how = 'inner')"
]
},
{
"cell_type": "code",
- "execution_count": 14,
+ "execution_count": 12,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>SVF_2m</th>\n",
" <th>std_2m</th>\n",
" <th>SVF_50cm</th>\n",
" <th>std_50cm</th>\n",
- " <th>bias</th>\n",
" </tr>\n",
" <tr>\n",
" <th>DF_UID</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
- " <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>4879560</th>\n",
" <td>0.537930</td>\n",
" <td>0.035747</td>\n",
" <td>0.497254</td>\n",
" <td>0.051997</td>\n",
- " <td>-0.040677</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4879561</th>\n",
" <td>0.543964</td>\n",
" <td>0.061913</td>\n",
" <td>0.474188</td>\n",
" <td>0.106268</td>\n",
- " <td>-0.069776</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4879562</th>\n",
" <td>0.601935</td>\n",
" <td>0.031992</td>\n",
" <td>0.546454</td>\n",
" <td>0.051656</td>\n",
- " <td>-0.055481</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4879563</th>\n",
" <td>0.568163</td>\n",
" <td>0.041745</td>\n",
" <td>0.509543</td>\n",
" <td>0.042314</td>\n",
- " <td>-0.058620</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4879564</th>\n",
" <td>0.508238</td>\n",
" <td>0.052079</td>\n",
" <td>0.429219</td>\n",
" <td>0.077267</td>\n",
- " <td>-0.079019</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
- " SVF_2m std_2m SVF_50cm std_50cm bias\n",
- "DF_UID \n",
- "4879560 0.537930 0.035747 0.497254 0.051997 -0.040677\n",
- "4879561 0.543964 0.061913 0.474188 0.106268 -0.069776\n",
- "4879562 0.601935 0.031992 0.546454 0.051656 -0.055481\n",
- "4879563 0.568163 0.041745 0.509543 0.042314 -0.058620\n",
- "4879564 0.508238 0.052079 0.429219 0.077267 -0.079019"
+ " SVF_2m std_2m SVF_50cm std_50cm\n",
+ "DF_UID \n",
+ "4879560 0.537930 0.035747 0.497254 0.051997\n",
+ "4879561 0.543964 0.061913 0.474188 0.106268\n",
+ "4879562 0.601935 0.031992 0.546454 0.051656\n",
+ "4879563 0.568163 0.041745 0.509543 0.042314\n",
+ "4879564 0.508238 0.052079 0.429219 0.077267"
]
},
- "execution_count": 14,
+ "execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"skyview.head()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Compute bias"
]
},
{
"cell_type": "code",
- "execution_count": 82,
+ "execution_count": 13,
"metadata": {},
"outputs": [],
"source": [
"skyview['bias'] = skyview.SVF_2m - skyview.SVF_50cm"
]
},
{
"cell_type": "code",
- "execution_count": 83,
+ "execution_count": 14,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Mean bias of SVF: 7.16 percent\n",
"Std deviation of SVF: 12.09 percent\n"
]
}
],
"source": [
"print('Mean bias of SVF: %.2f percent' %(skyview['bias'].mean() * 100))\n",
"print('Std deviation of SVF: %.2f percent' %(skyview['bias'].std() * 100))"
]
},
{
"cell_type": "code",
- "execution_count": 85,
+ "execution_count": 15,
"metadata": {},
"outputs": [
{
"data": {
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"\n",
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"\n",
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"\n",
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" 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 overriden (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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"text/plain": [
"<IPython.core.display.HTML object>"
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},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
- "[<matplotlib.lines.Line2D at 0x7f728bd9ac18>]"
+ "[<matplotlib.lines.Line2D at 0x7f34c51cce48>]"
]
},
- "execution_count": 85,
+ "execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"plt.figure()\n",
"skyview.bias.hist(bins = 100, density = True)\n",
"x = np.linspace(-0.5, 0.5, 100)\n",
"plt.plot(x, stats.norm.pdf(x, skyview['bias'].mean(), skyview['bias'].std()))"
]
},
+ {
+ "cell_type": "code",
+ "execution_count": 16,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# save mean and std deviation of random variable \"SVF bias\"\n",
+ "df=pd.DataFrame(data = [skyview['bias'].mean(), skyview['bias'].std()], columns = ['SVF'], index = ['mean', 'std']).T\n",
+ "df.to_csv('/work/hyenergy/output/solar_potential/uncertainty/SVF_RV_mean_std.csv')"
+ ]
+ },
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Load shading data"
]
},
{
"cell_type": "code",
- "execution_count": 70,
+ "execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"path = '/work/hyenergy/output/solar_potential/geographic_potential/available_area/shading_stats'\n",
"shade_bias = pd.read_csv( os.path.join(path, 'GVA_bias_2m-50cm.csv') )"
]
},
{
"cell_type": "code",
- "execution_count": 71,
+ "execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
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" <th>mean_9_9h</th>\n",
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" <th>mean_4_8h</th>\n",
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"text/plain": [
" DF_UID non_null_cells n_cells fully_shaded_ratio mean_12_13h \\\n",
"0 4817081 -378 -378 0.0 0.0 \n",
"1 4817082 -406 -406 0.0 0.0 \n",
"2 4817083 -398 -398 0.0 0.0 \n",
"3 4817084 -394 -394 0.0 0.0 \n",
"4 4817085 -501 -501 0.0 0.0 \n",
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" mean_1_16h mean_11_10h mean_7_15h mean_6_18h mean_6_10h ... \\\n",
"0 -1.000000 0.0 0.0 0.000000 0.0 ... \n",
"1 -1.000000 0.0 0.0 -0.076923 0.0 ... \n",
"2 -0.960000 0.0 0.0 0.000000 0.0 ... \n",
"3 -1.000000 0.0 0.0 0.000000 0.0 ... \n",
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"3 0.0 0.0 0.000000 0.0 0.0 -0.88 \n",
"4 0.0 0.0 -0.205882 0.0 0.0 0.00 \n",
"\n",
" mean_5_10h mean_4_8h mean_8_12h mean_12_12h \n",
"0 0.0 0.0 0.0 0.0 \n",
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"2 0.0 0.0 0.0 0.0 \n",
"3 0.0 0.0 0.0 0.0 \n",
"4 0.0 0.0 0.0 0.0 \n",
"\n",
"[5 rows x 150 columns]"
]
},
- "execution_count": 71,
+ "execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"shade_bias.head()"
]
},
{
"cell_type": "code",
- "execution_count": 72,
+ "execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"shade_bias_mean = shade_bias.mean()\n",
"shade_bias_std = shade_bias.std()"
]
},
{
"cell_type": "code",
- "execution_count": 73,
+ "execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"rename_dict = {}\n",
"Ssh = pd.DataFrame(data = 0, columns = ['mean', 'std'], index = range(288))\n",
"\n",
"for col in shade_bias_mean.index:\n",
" name = col.split('_')\n",
" if name[0] == 'mean':\n",
" hour_idx = (int(name[1]) - 1) * 24 + int(name[2][:-1])\n",
" Ssh.loc[hour_idx,:] = [shade_bias_mean[col], shade_bias_std[col]]\n",
" rename_dict[col] = hour_idx\n",
"# shade_bias_mean\n",
- "Ssh.sort_index(inplace = True)"
+ "Ssh.sort_index(inplace = True)\n",
+ "Ssh.index.rename('hour_idx', inplace = True)"
]
},
{
"cell_type": "code",
- "execution_count": 104,
+ "execution_count": 6,
"metadata": {
"scrolled": false
},
"outputs": [],
"source": [
"shade_bias_hourly = shade_bias.set_index('DF_UID').rename(columns = rename_dict).iloc[:,4:].sort_index(axis = 1)\n",
"shade_bias_hourly['Csh'] = - shade_bias.fully_shaded_ratio.values # negative value to obtain bias for (1-Csh)"
]
},
{
"cell_type": "code",
- "execution_count": 75,
+ "execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"mean 0.027160\n",
"std 0.247525\n",
"dtype: float64"
]
},
- "execution_count": 75,
+ "execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"Ssh[Ssh['std'] > 0].mean()"
]
},
{
"cell_type": "code",
- "execution_count": 86,
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 8,
"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 overriden (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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\" 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width=\"1200\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
- },
- {
- "data": {
- "text/plain": [
- "<matplotlib.axes._subplots.AxesSubplot at 0x7f728c157eb8>"
- ]
- },
- "execution_count": 86,
- "metadata": {},
- "output_type": "execute_result"
}
],
"source": [
- "plt.figure()\n",
- "Ssh['mean'].plot()\n",
- "Ssh['std'].plot()"
+ "plt_arr = Ssh[Ssh['std'] > 0]['std']\n",
+ "bias_arr = Ssh[Ssh['std'] > 0]['mean']\n",
+ "\n",
+ "# plt_arr[plt_arr == 0] = np.nan\n",
+ "\n",
+ "plt.figure(figsize = (12, 3))\n",
+ "ax = plt.subplot()\n",
+ "\n",
+ "# Ssh['mean'].plot()\n",
+ "plt_arr.plot(marker = 'x', markersize = 3, c = 'darkblue', label = '$\\sigma_{Ssh}$')\n",
+ "bias_arr.plot(marker = 'x', markersize = 3, c = 'orange', label = 'bias$_{Ssh}$')\n",
+ "\n",
+ "ax.set_xticks(list(range(12, 24*12, 24)))\n",
+ "ax.set_xticklabels(calendar.month_abbr[1:])\n",
+ "ax.set_ylabel('Fraction of roof surface')\n",
+ "ax.set_xlabel('')\n",
+ "ax.set_xlim((0, 12*24))\n",
+ "ax.yaxis.grid(linestyle = '--')\n",
+ "\n",
+ "plt.legend()\n",
+ "plt.tight_layout()\n",
+ "plt.show()\n",
+ "# plt.savefig('Ssh_temporal_var.png', dpi = 300)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 48,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# save to file\n",
+ "Ssh.to_csv('/work/hyenergy/output/solar_potential/uncertainty/Ssh_RV_mean_std.csv')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Merge shading data and SVF data to compute correlation"
]
},
{
"cell_type": "code",
- "execution_count": 105,
+ "execution_count": 49,
"metadata": {},
"outputs": [
{
"data": {
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" <th></th>\n",
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]
},
- "execution_count": 105,
+ "execution_count": 49,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"shade_bias_hourly.head()"
]
},
{
"cell_type": "code",
- "execution_count": 106,
+ "execution_count": 50,
"metadata": {},
"outputs": [],
"source": [
"merged_df = shade_bias_hourly.merge(skyview[['bias']], how = 'inner', left_index = True, right_index = True)\n",
"merged_df.rename(columns = {'bias' : 'SVF'}, inplace = True)"
]
},
{
"cell_type": "code",
- "execution_count": 107,
+ "execution_count": 51,
"metadata": {},
"outputs": [
{
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" 8 9 10 11 12 13 14 15 16 31 \\\n",
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},
- "execution_count": 107,
+ "execution_count": 51,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"merged_df.head()"
]
},
{
"cell_type": "code",
- "execution_count": 137,
+ "execution_count": 52,
"metadata": {
"scrolled": false
},
"outputs": [
{
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" 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 overriden (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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{
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\" 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\" width=\"640\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
- "<matplotlib.axes._subplots.AxesSubplot at 0x7f728bc8b048>"
+ "<matplotlib.axes._subplots.AxesSubplot at 0x7f99396da668>"
]
},
- "execution_count": 137,
+ "execution_count": 52,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"merged_df.plot(x=10, y='SVF', style='o', markersize = 1)"
]
},
{
"cell_type": "code",
- "execution_count": 125,
+ "execution_count": 53,
"metadata": {},
"outputs": [],
"source": [
"corr = merged_df.corr()\n",
"cov = merged_df.cov()"
]
},
{
"cell_type": "code",
- "execution_count": 143,
+ "execution_count": 54,
"metadata": {},
"outputs": [],
"source": [
"corr_w_SVF = pd.concat([corr.loc[:, 'SVF'].rename('corr'), cov.loc[:, 'SVF'].rename('cov')], axis = 1)\n",
"corr_w_Csh = pd.concat([corr.loc[:, 'Csh'].rename('corr'), cov.loc[:, 'Csh'].rename('cov')], axis = 1)"
]
},
{
"cell_type": "code",
- "execution_count": 138,
+ "execution_count": 55,
"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 overriden (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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\" 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\" width=\"640\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
- "<matplotlib.axes._subplots.AxesSubplot at 0x7f728bc0b710>"
+ "<matplotlib.axes._subplots.AxesSubplot at 0x7f9939725128>"
]
},
- "execution_count": 138,
+ "execution_count": 55,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"plt.figure()\n",
"corr_w_SVF['corr'][:-2].plot()"
]
},
{
"cell_type": "code",
- "execution_count": 139,
+ "execution_count": 56,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"corr 0.356733\n",
"cov 0.010845\n",
"dtype: float64"
]
},
- "execution_count": 139,
+ "execution_count": 56,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"corr_w_SVF.mean()"
]
},
{
"cell_type": "code",
- "execution_count": 144,
+ "execution_count": 57,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"corr 0.125164\n",
"cov 0.005559\n",
"dtype: float64"
]
},
- "execution_count": 144,
+ "execution_count": 57,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"corr_w_Csh.mean()"
]
},
{
"cell_type": "code",
- "execution_count": 142,
+ "execution_count": 58,
"metadata": {
"scrolled": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"correlation between SVF and C_sh: 0.564\n",
"covariance between SVF and C_sh: 0.014\n"
]
}
],
"source": [
"print('correlation between SVF and C_sh: %.3f' %corr.loc['Csh', 'SVF'])\n",
"print('covariance between SVF and C_sh: %.3f' %cov.loc[ 'Csh', 'SVF'])"
]
},
{
"cell_type": "code",
- "execution_count": 150,
+ "execution_count": 59,
"metadata": {},
"outputs": [],
"source": [
"corr_save = pd.concat([corr_w_SVF.rename(columns = {'corr' : 'corr_SVF', 'cov' : 'cov_SVF'}), \n",
- " corr_w_Csh.rename(columns = {'corr' : 'corr_Csh', 'cov' : 'cov_Csh'})], axis = 1)"
+ " corr_w_Csh.rename(columns = {'corr' : 'corr_Csh', 'cov' : 'cov_Csh'})], axis = 1)\n",
+ "corr_save.index.rename('hour_idx', inplace = True)"
]
},
{
"cell_type": "code",
- "execution_count": 152,
+ "execution_count": 60,
"metadata": {},
"outputs": [],
"source": [
"corr_save.to_csv('/work/hyenergy/output/solar_potential/uncertainty/covariance_DSM.csv')"
]
},
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ },
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Attach rooftop data"
]
},
{
"cell_type": "code",
- "execution_count": 16,
+ "execution_count": 61,
"metadata": {},
"outputs": [],
"source": [
"ROOFS='/work/hyenergy/output/solar_potential/geographic_potential/CH_ROOFS_all_replaced.csv'\n",
"roofs = pd.read_csv(ROOFS, usecols = ['DF_UID', 'NEIGUNG', 'AUSRICHTUNG', 'FLAECHE'])"
]
},
{
"cell_type": "code",
- "execution_count": 17,
+ "execution_count": 62,
"metadata": {},
"outputs": [],
"source": [
"SVF = skyview.merge(roofs, left_index = True, right_on = 'DF_UID', how = 'left')"
]
},
{
"cell_type": "code",
- "execution_count": 33,
+ "execution_count": 63,
"metadata": {},
"outputs": [],
"source": [
"SVF['AREA'] = util.round_to_interval(SVF['FLAECHE'], 10)"
]
},
{
"cell_type": "code",
- "execution_count": 27,
+ "execution_count": 64,
"metadata": {},
"outputs": [],
"source": [
"SVF['bias'] = SVF.SVF_2m - SVF.SVF_50cm"
]
},
{
"cell_type": "code",
- "execution_count": 28,
+ "execution_count": 65,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"SVF_2m 7.272423e-01\n",
"std_2m 6.351421e-02\n",
"SVF_50cm 6.556163e-01\n",
"std_50cm 9.321401e-02\n",
+ "bias 7.162608e-02\n",
"DF_UID 5.004925e+06\n",
"FLAECHE 8.545578e+01\n",
"NEIGUNG 2.264418e+01\n",
"AUSRICHTUNG -2.870675e+00\n",
- "AREA 8.545396e+01\n",
- "bias 7.162608e-02\n",
+ "AREA 8.539042e+01\n",
"dtype: float64"
]
},
- "execution_count": 28,
+ "execution_count": 65,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"SVF.mean()"
]
},
{
"cell_type": "code",
- "execution_count": 22,
+ "execution_count": 66,
"metadata": {},
"outputs": [
{
"data": {
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" <th>SVF_2m</th>\n",
" <th>std_2m</th>\n",
" <th>SVF_50cm</th>\n",
" <th>std_50cm</th>\n",
+ " <th>bias</th>\n",
" <th>DF_UID</th>\n",
" <th>FLAECHE</th>\n",
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"text/plain": [
- " SVF_2m std_2m SVF_50cm std_50cm DF_UID FLAECHE NEIGUNG \\\n",
- "4708076 0.537930 0.035747 0.497254 0.051997 4879560 78.139731 9 \n",
- "4708077 0.543964 0.061913 0.474188 0.106268 4879561 46.507495 34 \n",
- "4708078 0.601935 0.031992 0.546454 0.051656 4879562 65.822671 28 \n",
- "4708079 0.568163 0.041745 0.509543 0.042314 4879563 33.159751 41 \n",
- "4708080 0.508238 0.052079 0.429219 0.077267 4879564 35.956510 11 \n",
- "\n",
- " AUSRICHTUNG AREA \n",
- "4708076 -143.0 78.0 \n",
- "4708077 39.0 47.0 \n",
- "4708078 -141.0 66.0 \n",
- "4708079 -51.0 33.0 \n",
- "4708080 -51.0 36.0 "
+ " SVF_2m std_2m SVF_50cm std_50cm bias DF_UID FLAECHE \\\n",
+ "4708076 0.537930 0.035747 0.497254 0.051997 0.040677 4879560 78.139731 \n",
+ "4708077 0.543964 0.061913 0.474188 0.106268 0.069776 4879561 46.507495 \n",
+ "4708078 0.601935 0.031992 0.546454 0.051656 0.055481 4879562 65.822671 \n",
+ "4708079 0.568163 0.041745 0.509543 0.042314 0.058620 4879563 33.159751 \n",
+ "4708080 0.508238 0.052079 0.429219 0.077267 0.079019 4879564 35.956510 \n",
+ "\n",
+ " NEIGUNG AUSRICHTUNG AREA \n",
+ "4708076 9 -143.0 80.0 \n",
+ "4708077 34 39.0 50.0 \n",
+ "4708078 28 -141.0 70.0 \n",
+ "4708079 41 -51.0 30.0 \n",
+ "4708080 11 -51.0 40.0 "
]
},
- "execution_count": 22,
+ "execution_count": 66,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"SVF.head()"
]
},
{
"cell_type": "code",
- "execution_count": 26,
+ "execution_count": 67,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<xarray.Dataset>\n",
"Dimensions: (AUSRICHTUNG: 361, NEIGUNG: 70)\n",
"Coordinates:\n",
" * NEIGUNG (NEIGUNG) int64 0 1 2 3 4 5 6 7 8 ... 62 63 64 65 66 67 68 69\n",
" * AUSRICHTUNG (AUSRICHTUNG) float64 -180.0 -179.0 -178.0 ... 179.0 180.0\n",
"Data variables:\n",
" SVF_2m (NEIGUNG, AUSRICHTUNG) float64 nan nan nan nan ... nan nan nan\n",
" std_2m (NEIGUNG, AUSRICHTUNG) float64 nan nan nan nan ... nan nan nan\n",
" SVF_50cm (NEIGUNG, AUSRICHTUNG) float64 nan nan nan nan ... nan nan nan\n",
" std_50cm (NEIGUNG, AUSRICHTUNG) float64 nan nan nan nan ... nan nan nan\n",
+ " bias (NEIGUNG, AUSRICHTUNG) float64 nan nan nan nan ... nan nan nan\n",
" DF_UID (NEIGUNG, AUSRICHTUNG) float64 nan nan nan nan ... nan nan nan\n",
" FLAECHE (NEIGUNG, AUSRICHTUNG) float64 nan nan nan nan ... nan nan nan\n",
" AREA (NEIGUNG, AUSRICHTUNG) float64 nan nan nan nan ... nan nan nan"
]
},
- "execution_count": 26,
+ "execution_count": 67,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"svf_aspect_tilt = SVF.groupby(['NEIGUNG', 'AUSRICHTUNG']).mean().to_xarray()\n",
"svf_aspect_tilt"
]
},
{
"cell_type": "code",
- "execution_count": 30,
+ "execution_count": 68,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "<matplotlib.collections.QuadMesh at 0x7f9938d8e2e8>"
+ ]
+ },
+ "execution_count": 68,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "svf_aspect_tilt.SVF_50cm.plot()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 69,
"metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "<xarray.Dataset>\n",
+ "Dimensions: (AREA: 454, AUSRICHTUNG: 361)\n",
+ "Coordinates:\n",
+ " * AUSRICHTUNG (AUSRICHTUNG) float64 -180.0 -179.0 -178.0 ... 179.0 180.0\n",
+ " * AREA (AREA) float64 0.0 10.0 20.0 ... 2.164e+04 2.325e+04 2.351e+04\n",
+ "Data variables:\n",
+ " SVF_2m (AUSRICHTUNG, AREA) float64 0.7526 0.6545 0.6434 ... nan nan\n",
+ " std_2m (AUSRICHTUNG, AREA) float64 0.03314 0.05123 0.04813 ... nan nan\n",
+ " SVF_50cm (AUSRICHTUNG, AREA) float64 0.7312 0.5687 0.6316 ... nan nan\n",
+ " std_50cm (AUSRICHTUNG, AREA) float64 0.0656 0.09705 0.07214 ... nan nan\n",
+ " bias (AUSRICHTUNG, AREA) float64 0.02135 0.08577 0.01173 ... nan nan\n",
+ " DF_UID (AUSRICHTUNG, AREA) float64 4.976e+06 4.975e+06 ... nan nan\n",
+ " FLAECHE (AUSRICHTUNG, AREA) float64 2.913 10.42 20.29 ... nan nan nan\n",
+ " NEIGUNG (AUSRICHTUNG, AREA) float64 24.37 24.93 27.84 ... nan nan nan"
+ ]
+ },
+ "execution_count": 69,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "svf_aspect_area = SVF.groupby(['AUSRICHTUNG', 'AREA']).mean().to_xarray()\n",
+ "svf_aspect_area"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 70,
+ "metadata": {
+ "scrolled": false
+ },
"outputs": [
{
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"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
" var size = msg['size'];\n",
" if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
" fig._resize_canvas(size[0], size[1]);\n",
" fig.send_message(\"refresh\", {});\n",
" };\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
" var x0 = msg['x0'] / mpl.ratio;\n",
" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
" var x1 = msg['x1'] / mpl.ratio;\n",
" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
" x0 = Math.floor(x0) + 0.5;\n",
" y0 = Math.floor(y0) + 0.5;\n",
" x1 = Math.floor(x1) + 0.5;\n",
" y1 = Math.floor(y1) + 0.5;\n",
" var min_x = Math.min(x0, x1);\n",
" var min_y = Math.min(y0, y1);\n",
" var width = Math.abs(x1 - x0);\n",
" var height = Math.abs(y1 - y0);\n",
"\n",
" fig.rubberband_context.clearRect(\n",
" 0, 0, fig.canvas.width, fig.canvas.height);\n",
"\n",
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
" // Updates the figure title.\n",
" fig.header.textContent = msg['label'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
" var cursor = msg['cursor'];\n",
" switch(cursor)\n",
" {\n",
" case 0:\n",
" cursor = 'pointer';\n",
" break;\n",
" case 1:\n",
" cursor = 'default';\n",
" break;\n",
" case 2:\n",
" cursor = 'crosshair';\n",
" break;\n",
" case 3:\n",
" cursor = 'move';\n",
" break;\n",
" }\n",
" fig.rubberband_canvas.style.cursor = cursor;\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
" fig.message.textContent = msg['message'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
" // Request the server to send over a new figure.\n",
" fig.send_draw_message();\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
" fig.image_mode = msg['mode'];\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Called whenever the canvas gets updated.\n",
" this.send_message(\"ack\", {});\n",
"}\n",
"\n",
"// A function to construct a web socket function for onmessage handling.\n",
"// Called in the figure constructor.\n",
"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
" /* FIXME: We get \"Resource interpreted as Image but\n",
" * transferred with MIME type text/plain:\" errors on\n",
" * Chrome. But how to set the MIME type? It doesn't seem\n",
" * to be part of the websocket stream */\n",
" evt.data.type = \"image/png\";\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
" (window.URL || window.webkitURL).revokeObjectURL(\n",
" fig.imageObj.src);\n",
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" evt.data);\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
" fig.imageObj.src = evt.data;\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
"\n",
" var msg = JSON.parse(evt.data);\n",
" var msg_type = msg['type'];\n",
"\n",
" // Call the \"handle_{type}\" callback, which takes\n",
" // the figure and JSON message as its only arguments.\n",
" try {\n",
" var callback = fig[\"handle_\" + msg_type];\n",
" } catch (e) {\n",
" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
" return;\n",
" }\n",
"\n",
" if (callback) {\n",
" try {\n",
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
" callback(fig, msg);\n",
" } catch (e) {\n",
" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
" }\n",
" }\n",
" };\n",
"}\n",
"\n",
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function(e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e)\n",
" e = window.event;\n",
" if (e.target)\n",
" targ = e.target;\n",
" else if (e.srcElement)\n",
" targ = e.srcElement;\n",
" if (targ.nodeType == 3) // defeat Safari bug\n",
" targ = targ.parentNode;\n",
"\n",
" // jQuery normalizes the pageX and pageY\n",
" // pageX,Y are the mouse positions relative to the document\n",
" // offset() returns the position of the element relative to the document\n",
" var x = e.pageX - $(targ).offset().left;\n",
" var y = e.pageY - $(targ).offset().top;\n",
"\n",
" return {\"x\": x, \"y\": y};\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * http://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys (original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object')\n",
" obj[key] = original[key]\n",
" return obj;\n",
" }, {});\n",
"}\n",
"\n",
"mpl.figure.prototype.mouse_event = function(event, name) {\n",
" var canvas_pos = mpl.findpos(event)\n",
"\n",
" if (name === 'button_press')\n",
" {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * mpl.ratio;\n",
" var y = canvas_pos.y * mpl.ratio;\n",
"\n",
" this.send_message(name, {x: x, y: y, button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event)});\n",
"\n",
" /* This prevents the web browser from automatically changing to\n",
" * the text insertion cursor when the button is pressed. We want\n",
" * to control all of the cursor setting manually through the\n",
" * 'cursor' event from matplotlib */\n",
" event.preventDefault();\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" // Handle any extra behaviour associated with a key event\n",
"}\n",
"\n",
"mpl.figure.prototype.key_event = function(event, name) {\n",
"\n",
" // Prevent repeat events\n",
" if (name == 'key_press')\n",
" {\n",
" if (event.which === this._key)\n",
" return;\n",
" else\n",
" this._key = event.which;\n",
" }\n",
" if (name == 'key_release')\n",
" this._key = null;\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which != 17)\n",
" value += \"ctrl+\";\n",
" if (event.altKey && event.which != 18)\n",
" value += \"alt+\";\n",
" if (event.shiftKey && event.which != 16)\n",
" value += \"shift+\";\n",
"\n",
" value += 'k';\n",
" value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, {key: value,\n",
" guiEvent: simpleKeys(event)});\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
" if (name == 'download') {\n",
" this.handle_save(this, null);\n",
" } else {\n",
" this.send_message(\"toolbar_button\", {name: name});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
" this.message.textContent = tooltip;\n",
"};\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
- "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
+ "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 overriden (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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\" 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\" width=\"640\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
- "<matplotlib.collections.QuadMesh at 0x7f3ce75ad208>"
+ "(1, 23640.0)"
]
},
- "execution_count": 30,
+ "execution_count": 70,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
- "svf_aspect_tilt.SVF_50cm.plot()"
+ "plt.figure()\n",
+ "svf_aspect_area.SVF_50cm.T.plot()\n",
+ "plt.yscale('log')\n",
+ "plt.ylim(bottom = 1)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Verify batch computation for CH"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "path = '/scratch/walch/grassgis/scripts/executables/workspace_skyview/files'"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 10,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "files = []\n",
+ "for i in range(64):\n",
+ " try:\n",
+ " files.append( pd.read_csv( os.path.join(path, 'skyview_CH_%d_stats.csv' %i )))\n",
+ " except:\n",
+ " print('Skipping %d' %i)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "**Merging of files**\n",
+ "1. Append all files to one long file (need columns *non_null_cells* and *sum*)\n",
+ "2. Groupby zone and perform sum-operation\n",
+ "3. Compute mean as *sum*/*non_null_cells*\n",
+ "4. Rename \"zone\" to \"DF_UID\" and \"mean\" to \"SVF\"\n",
+ "5. Load roofs to obtain full list of DF_UIDs\n",
+ "6. Refill missing values with the national mean\n",
+ "7. Debias bysubtracting the bias"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 11,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# 1.\n",
+ "df = pd.concat(files, axis = 0)\n",
+ "df_sel = df[['zone', 'sum', 'non_null_cells']].rename(columns = {'zone' : 'DF_UID'})"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 12,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "df_sel['non_null_cells'] = df_sel.non_null_cells.astype(int)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 13,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# 2. to 4.\n",
+ "df_merged = df_sel.groupby('DF_UID').sum()\n",
+ "df_merged['SVF'] = df_merged['sum']/df_merged['non_null_cells']\n",
+ "SVF = df_merged[['SVF']]"
]
},
{
"cell_type": "code",
- "execution_count": 34,
+ "execution_count": 14,
"metadata": {},
"outputs": [
{
- "data": {
- "text/plain": [
- "<xarray.Dataset>\n",
- "Dimensions: (AREA: 454, AUSRICHTUNG: 361)\n",
- "Coordinates:\n",
- " * AUSRICHTUNG (AUSRICHTUNG) float64 -180.0 -179.0 -178.0 ... 179.0 180.0\n",
- " * AREA (AREA) float64 0.0 10.0 20.0 ... 2.164e+04 2.325e+04 2.351e+04\n",
- "Data variables:\n",
- " SVF_2m (AUSRICHTUNG, AREA) float64 0.7526 0.6545 0.6434 ... nan nan\n",
- " std_2m (AUSRICHTUNG, AREA) float64 0.03314 0.05123 0.04813 ... nan nan\n",
- " SVF_50cm (AUSRICHTUNG, AREA) float64 0.7312 0.5687 0.6316 ... nan nan\n",
- " std_50cm (AUSRICHTUNG, AREA) float64 0.0656 0.09705 0.07214 ... nan nan\n",
- " DF_UID (AUSRICHTUNG, AREA) float64 4.976e+06 4.975e+06 ... nan nan\n",
- " FLAECHE (AUSRICHTUNG, AREA) float64 2.913 10.42 20.29 ... nan nan nan\n",
- " NEIGUNG (AUSRICHTUNG, AREA) float64 24.37 24.93 27.84 ... nan nan nan\n",
- " bias (AUSRICHTUNG, AREA) float64 0.02135 0.08577 0.01173 ... nan nan"
- ]
- },
- "execution_count": 34,
- "metadata": {},
- "output_type": "execute_result"
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "/home/walch/miniconda3/envs/py3/lib/python3.6/site-packages/numpy/lib/arraysetops.py:463: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison\n",
+ " mask |= (ar1 == a)\n"
+ ]
}
],
"source": [
- "svf_aspect_area = SVF.groupby(['AUSRICHTUNG', 'AREA']).mean().to_xarray()\n",
- "svf_aspect_area"
+ "# 5.\n",
+ "ROOFS='/work/hyenergy/output/solar_potential/geographic_potential/CH_ROOFS_all_replaced.csv'\n",
+ "roofs = pd.read_csv(ROOFS, usecols = ['DF_UID', 'FLAECHE', 'NEIGUNG', 'AUSRICHTUNG'], index_col = 0)"
]
},
{
"cell_type": "code",
- "execution_count": 42,
- "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",
+ "execution_count": 15,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# 6. \n",
+ "SVF_filled = roofs.merge(SVF, left_index = True, right_index = True, how = 'left').fillna(SVF.SVF.mean())"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 27,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "SVF_filled['SVF_unbiased'] = np.minimum(np.maximum(SVF_filled.SVF - skyview['bias'].mean(), 0), 1)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 29,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "SVF_filled.drop(columns = ['FLAECHE', 'NEIGUNG', 'AUSRICHTUNG'], inplace = True)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 30,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "SVF_filled.to_csv('/work/hyenergy/output/solar_potential/geographic_potential/tilted_irradiance/SVF_CH_replaced.csv')"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Plot SVF against roof characteristics"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 56,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "SVF = pd.read_csv('/work/hyenergy/output/solar_potential/geographic_potential/tilted_irradiance/SVF_CH_replaced.csv')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 33,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "SVF_merged = roofs.merge(SVF, left_index = True, right_on = 'DF_UID', how = 'left')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 50,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# ADJUST FOR FLAT ROOFS\n",
+ "FLAT = -5.1\n",
+ "SVF_merged['tilt'] = SVF_merged.NEIGUNG\n",
+ "SVF_merged.loc[SVF_merged.NEIGUNG == 0, 'tilt'] = FLAT # NEEDED FOR PLOTTING"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 51,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "SVF_merged['area_log'] = np.log10(SVF_merged.FLAECHE)\n",
+ "SVF_merged['area_log_round'] = util.round_to_interval(SVF_merged.area_log, 0.2)\n",
+ "SVF_merged['area_log_round'] = np.minimum(np.maximum(SVF_merged.area_log_round, 0.7), 3.2)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 55,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "ASP_ROUND = 10\n",
+ "TILT_ROUND = 10\n",
+ "SVF_merged['NEIGUNG_round'] = util.round_to_interval(SVF_merged.NEIGUNG, 5)\n",
+ "SVF_merged['tilt_round'] = util.round_to_interval(SVF_merged.tilt, TILT_ROUND)\n",
+ "SVF_merged['aspect_round'] = util.round_to_interval(SVF_merged.AUSRICHTUNG, ASP_ROUND)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 56,
+ "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 overriden (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": [
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+ ]
+ },
+ "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": [
+ "SVF_grouped = SVF_merged.groupby(['tilt_round', 'aspect_round']).mean()\n",
+ "plot_var = SVF_grouped['SVF_unbiased']\n",
+ "plot_array = plot_var.to_xarray()\n",
+ "\n",
+ "plot_array['tilt_round' == FLAT] = plot_array['tilt_round' == FLAT].mean()\n",
+ "\n",
+ "\n",
+ "# prepare data\n",
+ "data = plot_array.values\n",
+ "# theta = np.append(plot_array.aspect_round * np.pi / 180, 2*np.pi) + (0.5 * ASP_ROUND * np.pi / 180)\n",
+ "theta = plot_array.aspect_round * np.pi / 180 - (0.5 * ASP_ROUND * np.pi / 180)\n",
+ "tilts = plot_array.tilt_round\n",
+ "\n",
+ "X, Y = np.meshgrid( theta, tilts )\n",
+ "\n",
+ "# SET PROPERTIES\n",
+ "VMIN = None\n",
+ "VMAX = None\n",
+ " \n",
+ "plt.figure()\n",
+ "ax = plt.subplot(projection='polar')\n",
+ "ax.set_theta_zero_location('S')\n",
+ "ax.set_theta_direction(-1)\n",
+ "\n",
+ "plt.pcolor(X, Y, data, vmin = VMIN, vmax = VMAX)\n",
+ "cb = plt.colorbar() # extend = get_cbar_extent( data, VMIN, VMAX )\n",
+ "# cb.set_label('Uncertainty for (1 - $C_{sh}$)')\n",
+ "\n",
+ "# FORMATTING\n",
+ "xticks = ['S', 'SW', 'W', 'NW', 'N', 'NE', 'E', 'SE']\n",
+ "yticks = [str(int(tilt)) + '°' for tilt in ax.get_yticks()]\n",
+ "ax.set_xticklabels( xticks )\n",
+ "ax.set_yticklabels( yticks )\n",
+ "ax.text(60,80, 'Tilt angle')\n",
+ "ax.set_rlabel_position(200) # get radial labels away from plotted line\n",
+ "\n",
+ "plt.tight_layout()\n",
+ "plt.show()\n",
+ "# plt.savefig('Shade_slope_azimuth_unc.png', dpi = 300)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 53,
+ "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 overriden (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": [
+ "SVF_grouped = SVF_merged.groupby(['area_log_round', 'NEIGUNG_round']).mean()\n",
+ "arr = SVF_grouped['SVF_unbiased'].to_xarray()\n",
+ "arr.coords['area_log_round'] = 10**(arr.area_log_round)\n",
+ "\n",
+ "# PV_array.attrs['long_name'] = 'Uncertainty for $C_{pv}$'\n",
+ "\n",
+ "plt.figure()\n",
+ "ax = plt.subplot()\n",
+ "\n",
+ "arr.plot()\n",
+ "ax.set_yscale('log')\n",
+ "plt.xlabel('Roof tilt (in degree)')\n",
+ "plt.ylabel('Roof area (in $m^2$)')\n",
+ "\n",
+ "plt.tight_layout()\n",
+ "# plt.savefig('panelled_area_unc.png', dpi = 300)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 57,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "DF_UID 1.000000\n",
+ "SVF 0.000057\n",
+ "SVF_unbiased 0.000000\n",
+ "dtype: float64"
+ ]
+ },
+ "execution_count": 57,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "SVF.min()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 58,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "DF_UID 9.890023e+06\n",
+ "SVF 1.000000e+00\n",
+ "SVF_unbiased 9.283739e-01\n",
+ "dtype: float64"
+ ]
+ },
+ "execution_count": 58,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "SVF.max()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 59,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "DF_UID 4.977728e+06\n",
+ "SVF 7.625916e-01\n",
+ "SVF_unbiased 6.909656e-01\n",
+ "dtype: float64"
+ ]
+ },
+ "execution_count": 59,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "SVF.mean()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Spielwiese"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 95,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "roof_SVF = skyview.merge(roofs, left_index = True, right_index = True, how = 'left')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 85,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "<div>\n",
+ "<style scoped>\n",
+ " .dataframe tbody tr th:only-of-type {\n",
+ " vertical-align: middle;\n",
+ " }\n",
+ "\n",
+ " .dataframe tbody tr th {\n",
+ " vertical-align: top;\n",
+ " }\n",
+ "\n",
+ " .dataframe thead th {\n",
+ " text-align: right;\n",
+ " }\n",
+ "</style>\n",
+ "<table border=\"1\" class=\"dataframe\">\n",
+ " <thead>\n",
+ " <tr style=\"text-align: right;\">\n",
+ " <th></th>\n",
+ " <th>SVF_2m</th>\n",
+ " <th>std_2m</th>\n",
+ " <th>SVF_50cm</th>\n",
+ " <th>std_50cm</th>\n",
+ " <th>bias</th>\n",
+ " <th>FLAECHE</th>\n",
+ " <th>NEIGUNG</th>\n",
+ " <th>AUSRICHTUNG</th>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>DF_UID</th>\n",
+ " <th></th>\n",
+ " <th></th>\n",
+ " <th></th>\n",
+ " <th></th>\n",
+ " <th></th>\n",
+ " <th></th>\n",
+ " <th></th>\n",
+ " <th></th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " <tr>\n",
+ " <th>4879560</th>\n",
+ " <td>0.537930</td>\n",
+ " <td>0.035747</td>\n",
+ " <td>0.497254</td>\n",
+ " <td>0.051997</td>\n",
+ " <td>0.040677</td>\n",
+ " <td>78.139731</td>\n",
+ " <td>9</td>\n",
+ " <td>-143.0</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>4879561</th>\n",
+ " <td>0.543964</td>\n",
+ " <td>0.061913</td>\n",
+ " <td>0.474188</td>\n",
+ " <td>0.106268</td>\n",
+ " <td>0.069776</td>\n",
+ " <td>46.507495</td>\n",
+ " <td>34</td>\n",
+ " <td>39.0</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>4879562</th>\n",
+ " <td>0.601935</td>\n",
+ " <td>0.031992</td>\n",
+ " <td>0.546454</td>\n",
+ " <td>0.051656</td>\n",
+ " <td>0.055481</td>\n",
+ " <td>65.822671</td>\n",
+ " <td>28</td>\n",
+ " <td>-141.0</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>4879563</th>\n",
+ " <td>0.568163</td>\n",
+ " <td>0.041745</td>\n",
+ " <td>0.509543</td>\n",
+ " <td>0.042314</td>\n",
+ " <td>0.058620</td>\n",
+ " <td>33.159751</td>\n",
+ " <td>41</td>\n",
+ " <td>-51.0</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>4879564</th>\n",
+ " <td>0.508238</td>\n",
+ " <td>0.052079</td>\n",
+ " <td>0.429219</td>\n",
+ " <td>0.077267</td>\n",
+ " <td>0.079019</td>\n",
+ " <td>35.956510</td>\n",
+ " <td>11</td>\n",
+ " <td>-51.0</td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ "</table>\n",
+ "</div>"
+ ],
+ "text/plain": [
+ " SVF_2m std_2m SVF_50cm std_50cm bias FLAECHE NEIGUNG \\\n",
+ "DF_UID \n",
+ "4879560 0.537930 0.035747 0.497254 0.051997 0.040677 78.139731 9 \n",
+ "4879561 0.543964 0.061913 0.474188 0.106268 0.069776 46.507495 34 \n",
+ "4879562 0.601935 0.031992 0.546454 0.051656 0.055481 65.822671 28 \n",
+ "4879563 0.568163 0.041745 0.509543 0.042314 0.058620 33.159751 41 \n",
+ "4879564 0.508238 0.052079 0.429219 0.077267 0.079019 35.956510 11 \n",
+ "\n",
+ " AUSRICHTUNG \n",
+ "DF_UID \n",
+ "4879560 -143.0 \n",
+ "4879561 39.0 \n",
+ "4879562 -141.0 \n",
+ "4879563 -51.0 \n",
+ "4879564 -51.0 "
+ ]
+ },
+ "execution_count": 85,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "roof_SVF.head()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 94,
+ "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 overriden (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": [
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CBAgMCgBAeCgytHbYASAvdHPvmMB4OyXAAACBAgQIECAAAECBAgQ6FpAANi18DjaFwCOo05THKUAcIpVNScCBAgQIECAAAECBAgQGJSAAHBQ5ehtMALA3uhn37EAcPZLAAABAgQIECBAgAABAgQIdC0gAOxaeBztCwDHUacpjlIAOMWqmhMBAgQIECBAgAABAgQIDEpAADiocvQ2GAFgb/Sz71gAOPslAIAAAQIECBAgQIAAAQIEuhYQAHYtPI72BYDjqNMURykAnGJVzYkAAQIECBAgQIAAAQIEBiUgABxUOXobjACwN/rZdywAnP0SAECAAAECBAgQIECAAAECXQsIALsWHkf7AsBx1GmKoxQATrGq5kSAAAECBAgQIECAAAECgxIQAA6qHL0NRgDYG/3sOxYAzn4JACBAgAABAgQIECBAgACBrgUEgF0Lj6N9AeA46jTFUQoAp1hVcyJAgAABAgQIECBAgACBQQkIAAdVjt4GIwDsjX72HQsAZ78EABAgQIAAAQIECBAgQIBA1wICwK6Fx9G+AHAcdZriKAWAU6yqOREgQIAAAQIECBAgQIDAoAQEgIMqR2+DEQD2Rj/7jgWAs18CAAgQIECAAAECBAgQIECgawEBYNfC42hfADiOOk1xlALAKVbVnAgQIECAAAECBAgQIEBgUAICwEGVo7fBCAB7o599xwLA2S8BAAQIECBAgAABAgQIECDQtYAAsGvhcbQvABxHnaY4SgHgFKtqTgQ2CNz15b+OW++6N07ad3jsO+KRrAgQIECAAAECBAgQ2IKAAHALyCPoQgA4giJNdIgCwIkW1rQIZAn85kc/GxdfvT/uf/BAPGzvnrjkpSfHOacdD4sAAQIECBAgQIAAgY4FBIAdA4+keQHgSAo1wWEKACdYVFMikCWQdv6dfvk1O+Hf8ieFgNdfcLadgJYMAQIECBAgQIAAgY4FBIAdA4+keQHgSAo1wWEKACdYVFMikCVw/W1fjFdedeOuX73t3GfE6SceDY0AAQIECBAgQIAAgQ4FBIAd4o6oaQHgiIo1saEKACdWUNMhkCdgB6C1QYAAAQIECBAgQKA/AQFgf/ZD6lkAOKRqzGssAsB51dtsZy7gHYAzXwCmT4AAAQIECBAg0JuAALA3+kF1LAAcVDlmNRgB4KzKbbIEIpwCbBUQIECAAAECBAgQ2L6AAHD75kPsUQA4xKrMY0wCwHnU2SwJECBAgAABAgQIECBAoEcBAWCP+APqWgA4oGLMbCgCwJkV3HQJECBAgAABAgQIECBAYPsCAsDtmw+xRwHgEKsyjzEJAOdRZ7MkQIAAAQIECBAgQIAAgR4FBIA94g+oawHggIoxs6EIAGdWcNMlQIAAAQIECBAgQIAAge0LCAC3bz7EHgWAQ6zKPMYkAJxHnc2SAAECBAgQIECAAAECBHoUEAD2iD+grgWAAyrGzIYiAJxZwU2XAAECBAgQIECAAAECBLYvIADcvvkQexQADrEq8xiTAHAedTZLAgQIECBAgAABAgQIEOhRQADYI/6AuhYADqgYMxuKAHBmBTddAgQIECBAgAABAgQIENi+gABw++ZD7FEAOMSqzGNMAsB51NksCRAgQIAAAQIECBAgQKBHAQFgj/gD6loAOKBizGwoAsCZFdx0CRAgQIAAAQIECBAgQGD7AgLA7ZsPsUcB4BCrMo8xCQDnUWezJECAAAECBAgQIECAAIEeBQSAPeIPqGsB4ICKMbOhCABnVnDTJUCAAAECBAgQIECAAIHtCwgAt28+xB4FgEOsykNjelxEnB8RL4yI4yLiqxFxW0T8h4j4pYi4r4WhnxARPx4R3xMRJ0bEN0TElyPiUxHxgYj4dxFxVwv9ZDUhAOwIVrMECBAgQIAAAQIECBAgQGApIAC0FpKAAHCY6+DFEfGWiHhMzvD+aBEM3tpg+P8kIn45Ih61oY0vRcQ5EfG7DfrJu1UA2AGqJgkQIECAAAECBAgQIECAwKqAANB6EAAOcw2cGhHXLYK5eyPi8oj40OKfUxh37mLYKQR8+mLHXtWZnBER10bE3oh4MCJ+PSL+U0R8LiKOj4j/LSJSCJl+/ioiTo6IP67aScH1AsCWQTVHgAABAgQIECBAgAABAgTWBQSA1oQAcJhr4Pci4qyIuH/xnzesDfOnIuKNiz/7uYj42RrTeM9iB2G69Sci4k0ZbfzriPjJxZ+nR47/aY1+Nt0iAGwZVHMECBAgQIAAAQIECBAgQEAAaA1kCXgEeFjr4rSIuHExpPR47o9lDC/t2tsfEU+OiLsjYl9EfK3iNNKjvd8YEX8REUfn3Hvkov306/8eEd9ZsY+iywWARUJ+T4AAAQIECBAgQIAAAQIEGgrYAdgQcCK3CwCHVcjLIuKCxZCeuRIGro/y9YtHg9OfPzcifqfiNNKjxenAj49FxHdtuPfPFwFhChyfVrGPossFgEVCfk+AAAECBAgQIECAAAECBBoKCAAbAk7kdgHgsAqZ3sv37Ij4SkQctXgMOGuEz4qI6xe/+PmI+JmK0/hvEfF3C3YApgNI7lm0+x8j4h9V7KPocgFgkZDfEyBAgAABAgQIECBAgACBhgICwIaAE7ldADisQi533P1hRJyyYWjp8d30GG/6+a2I+McVp5EOEvmVxT0/HhH/LuP+fxkR/2zx538/Iv5LxT6KLhcAFgn5PQECBAgQIECAAAECBAgQaCggAGwIOJHbBYDDKeQjFyfuphG9NyJeVDC05WO8vx8RaUdglZ/DIuLNEfEDi1OA0///7oj4/OIU4O+PiJctGrw0Ii6u0vji2hTwbfr5toj4g3TBHXfcEY99bNHlNUbgFgIECBAgQIAAAQIECBAgMHMBAeDMF8Bi+gLA4ayDb4mIuxbDeUdEnFMwtC8sDgBp8n6+fxgRF0XEqRl9fSgi0jsJ6+78O1CWVgBYVsp1BAgQIECAAAECBAgQIECgmoAAsJrXVK8WAA6nssdFxGcXw/mNxe68TaNL16Z7bouIk2pMI50i/IaIeH5EPCzj/r+OiKsXjwHfWaN9AWANNLcQIECAAAECBAgQIECAAIE2BQSAbWqOty0B4HBqt80dgOmgkd+OiCMj4k8Wj/j+7uK9gt8aES+JiEsiIr1r8HMR8Q8i4uMVqYqe6fUIcEVQlxMgQIAAAQIECBAgQIAAgaoCAsCqYtO8XgA4nLpu6x2Aj1jsGjw2Iv5s8fhv+s/1n6dGxMciIo0rnRr89JapHALSMqjmCBAgQIAAAQIECBAgQIDAuoAA0JpIAgLAYa2DbZwC/L2LR3vTzNP7/9J7/vJ+roqIH1n8Mp1KnE4nbutHANiWpHYIECBAgAABAgQIECBAgECOgADQ0hAADm8NXBsR6fHcr0TEURFxf84Q06m/1y9+9/MR8TMVpvL6iLh8cX16/98HNtz7YxHxbxe/T4eSpMNJ2voRALYlqR0CBAgQIECAAAECBAgQICAAtAY2CNgBOKzlkXbjXbAY0jMj4sac4a2GeM+NiN+pMI1/FhH/cnH9iyPiPRvuPS8irlj8/h9FxH+s0E/RpQLAIiG/J0CAAAECBAgQIECAAAECDQXsAGwIOJHbBYDDKuRpK6HfL0dE2oG3/rM3IvZHRDrF9+6I2BcRX6swjX8YEf/v4vo3RsTrNtybrkvXp5/vjIj/XqGfoksFgEVCfk+AAAECBAgQIECAAAECBBoKCAAbAk7kdgHg8Aq5fAw4Pf57VkTcsDbEn4qIFNyln5+LiJ9d+/13R8SHFn/26xHxg2u/T48W3xkRj46IL0fEGRFxSwZDejw47Q5MgWO6/viIeLBFLgFgi5iaIkCAAAECBAgQIECAAAECWQICQOsiCQgAh7cOTo2I6yLiURFx7+KQjhTopX9O7+H70cWQ/2hxMm8K8VZ/igLAdO0/j4j07sD0k/q4MiJ+NyL+MiK+NSLSQSHnRsTDFtf8k4h4S8tUAsCWQTVHgAABAgQIECBAgAABAgTWBQSA1oQAcLhrIL2bLwVuj8kZYgr/XhgRt2b8vkwAmILfX4iI1xaEwOnR4gsj4l91QCUA7ABVkwQIECBAgAABAgQIECBAYFVAAGg9CACHvQYetwjoUtCXwrK/WQR+vxURvxgR9+UMv0wAuLw1vdfvRyLizIhI/aXHgtOOwBQs/l5EpPcQprCxix8BYBeq2iRAgAABAgQIECBAgAABAisCAkDLQQBoDfQpIADsU1/fBAgQIECAAAECBAgQIDALAQHgLMpcOEnvACwkckFHAgLAjmA1S4AAAQIECBAgQIAAAQIElgICQGshCQgArYO+BASAfcnrlwABAgQIECBAgAABAgRmIyAAnE2pN05UAGgd9CUgAOxLXr8ECBAgQIAAAQIECBAgMBsBAeBsSi0AVOpBCggAB1kWgyJAgAABAgQIECBAgACBKQkIAKdUzfpzsQOwvp07mwkIAJv5uZsAAQIECBAgQIAAAQIECBQKCAALiWZxgQBwFmUe5CQFgIMsi0ERIECAAAECBAgQIECAwJQEBIBTqmb9uQgA69u5s5mAALCZn7sJECBAgAABAgQIECBAgEChgACwkGgWFwgAZ1HmQU5SADjIshgUAQIECBAgQIAAAQIECExJQAA4pWrWn4sAsL6dO5sJCACb+bmbAAECBAgQIECAAAECBAgUCggAC4lmcYEAcBZlHuQkBYCDLItBESBAgAABAgQIECBAgMCUBASAU6pm/bkIAOvbubOZgACwmZ+7CRAgQIAAAQIECBAgQIBAoYAAsJBoFhcIAGdR5kFOUgA4yLIYFAECBAgQIECAAAECBAhMSUAAOKVq1p+LALC+nTubCQgAm/m5mwABAgQIECBAgAABAgQIFAoIAAuJZnGBAHAWZR7kJAWAgyyLQREgQIAAAQIECBAgQIDAlAQEgFOqZv25CADr27mzmYAAsJmfuwkQIECAAAECBAgQIECAQKGAALCQaBYXCABnUeZBTlIAOMiyGBQBAgQIECBAgAABAgQITElAADilatafiwCwvp07mwkIAJv5uZsAAQIECBAgQIAAAQIECBQKCAALiWZxgQBwFmUe5CQFgIMsi0ERIECAAAECBAgQIECAwJQEBIBTqmb9uQgA69u5s5mAALCZn7sJECBAgAABAgQIECBAgEChgACwkGgWFwgAZ1HmQU5SADjIshgUAQIECBAgQIAAAQIECExJQAA4pWrWn4sAsL6dO5sJCACb+bmbAAECBAgQIECAAAECBAgUCggAC4lmcYEAcBZlHuQkBYCDLItBESBAgAABAgQIECBAgMCUBASAU6pm/bkIAOvbubOZgACwmZ+7CRAgQIAAAQIECBAgQIBAoYAAsJBoFhcIAGdR5kFOUgA4yLIYFAECBAgQIECAAAECBAhMSUAAOKVq1p+LALC+nTubCQgAm/m5mwABAgQIECBAgAABAgQIFAoIAAuJZnGBAHAWZR7kJAWAgyyLQREgQIAAAQIECBAgQIDAlAQEgFOqZv25CADr27mzmYAAsJmfuwkQIECAAAECBAgQIECAQKGAALCQaBYXCABnUeZBTlIAOMiyGBQBAgQIECBAgAABAgQITElAADilatafiwCwvp07mwkIAJv5uZsAAQIECBAgQIAAAQIECBQKCAALiWZxgQBwFmUe5CQFgIMsi0ERIECAAAECBAgQIECAwJQEBIBTqmb9uQgA69u5s5mAALCZn7sJECBAgAABAgQIECBAgEChgACwkGgWFwgAZ1HmQU5SADjIshgUAQIECBAgQIAAAQIECExJQAA4pWrWn4sAsL6dO5sJCACb+bmbAAECBAgQIECAAAECBAgUCggAC4lmcYEAcBZlHuQkBYCDLItBESBAgAABAgQIECBAgMCUBASAU6pm/bkIAOvbubOZgACwmZ+7CRAgQIAAAQIECBAgQIBAoYAAsJBoFhcIAGdR5kFOUgA4yLIYFAECBAgQIECAAAECBAhMSUAAOKVq1p+LALC+nTubCQgAm/m5mwABAgQIECBAgGUv7OsAACAASURBVAABAgQIFAoIAAuJZnGBAHAWZR7kJAWAgyyLQREgQIAAAQIECBAgQIDAlAQEgFOqZv25CADr27mzmYAAsJmfuwkQIECAAAECBAgQIECAQKGAALCQaBYXCABnUeZBTlIAOMiyGBQBAgSGIXDXl/86br3r3jhp3+Gx74hHDmNQRkGAAAECBAgQGKGAAHCERetgyALADlA1WUpAAFiKyUUECBCYn8BvfvSzcfHV++P+Bw/Ew/buiUteenKcc9rx84MwYwIECBAgQIBACwICwBYQJ9CEAHACRRzpFASAIy2cYRMgQKBLgbTz7/TLr9kJ/5Y/KQS8/oKz7QTsEl7bBAgQIECAwGQFBICTLW2liQkAK3G5uEUBAWCLmJoiQIDAVASuv+2L8cqrbtw1nbed+4w4/cSjpzJN8yBAgAABAgQIbE1AALg16kF3JAAcdHkmPTgB4KTLa3IECBCoJ2AHYD03dxEgQIAAAQIE8gQEgNZGEhAAWgd9CQgA+5LXLwECBAYu4B2AAy+Q4REgQIAAAQKjEhAAjqpcnQ1WANgZrYYLBASAlggBAgQI5Ao4BdjiIECAAAECBAi0IyAAbMdx7K0IAMdewfGOXwA43toZOQECBAgQIECAAAECBAiMREAAOJJCdTxMAWDHwJrPFRAAWhwECBAgQIAAAQIECBAgQKBjAQFgx8AjaV4AOJJCTXCYAsAJFtWUCBAgQIAAAQIECBAgQGBYAgLAYdWjr9EIAPuS168A0BogQIAAAQIECBAgQIAAAQIdCwgAOwYeSfMCwJEUaoLDFABOsKimRIAAAQIECBAgQIAAAQLDEhAADqsefY1GANiXvH4FgNYAAQIECBAgQIAAAQIECBDoWEAA2DHwSJoXAI6kUBMcpgBwgkU1JQIECBAgQIAAAQIECBAYloAAcFj16Gs0AsC+5PUrALQGCBAgQIAAAQIECBAgQIBAxwICwI6BR9K8AHAkhZrgMAWAEyyqKREgQIAAAQIECBAgQIDAsAQEgMOqR1+jEQD2Ja9fAaA1QIAAAQIECBAgQIAAAQIEOhYQAHYMPJLmBYAjKdQEhykAnGBRTYkAAQIEDhW468t/HbfedW+ctO/w2HfEI/EQIECAAAECBLYuIADcOvkgOxQADrIssxiUAHAWZTZJAgQIzFfgNz/62bj46v1x/4MH4mF798QlLz05zjnt+PmCmDkBAgQIECDQi4AAsBf2wXUqABxcSWYzIAHgbEptogSGK2B31nBrM/aRpbV1+uXX7IR/y58UAl5/wdl2Ao69uMZPgAABAgRGJiAAHFnBOhquALAjWM0WCggAC4lcQIBAlwJ2Z3Wpq+3rb/tivPKqG3dBvO3cZ8TpJx4NiAABAgQIECCwNQEB4NaoB92RAHDQ5Zn04ASAky6vyREYtoDdWcOuzxRGZ41NoYrmQIAAAQIEpiEgAJxGHZvOQgDYVND9dQUEgHXl3DcpAY+g9lNOu7P6cZ9br3aZzq3i5kuAAAECBIYpIAAcZl22PSoB4LbF9bcUEABaC7MXEA70twTszurPfm49C/nnVnHzJUCAAAECwxMQAA6vJn2MSADYh7o+k4AA0DqYtYAAqv/yC2D7r4ERECBAgAABAgQIdC8gAOzeeAw9CADHUKVpjlEAOM26mlVJAY+gloTq+DK7szoG1jwBAgQIECBAgEDvAgLA3kswiAEIAAdRhlkOQgA4y7Kb9FLADkBrgQABAgQIECBAgACBbQgIALehPPw+BIDDr9FURygAnGplzau0gEdQS1O5kAABAgQIECBAgACBmgICwJpwE7tNADjcgj4uIs6PiBdGxHER8dWIuC0i/kNE/FJE3Nfi0L87In4gIp4dEcdExIMR8YWIuCUi/ktE/D8RcW+L/aWmBIAtg2punAIeQR1n3YyaAAECBAgQIECAwFgEBIBjqVS34xQAdutbt/UXR8RbIuIxOQ380SIYvLVuB4v7joiIX42If1zQzqkRcXPDvtZvFwC2DKo5AgQIECBAgAABAgQIECCwLiAAtCaSgABweOsghW3XRcSjFrvuLo+IDy3++ZyIOHcx5BQCPj0ivlxzCt8QEf85Is5Y3P+BiHh7RKR290ZE2oH4XRHxv0ZECiQFgDWh3UaAAAECBAgQIECAAAECBPoSEAD2JT+sfgWAw6pHGs3vRcRZEXH/4j9vWBviT0XEGxd/9nMR8bM1p/CmiPjxxeO+PxwR/z6nnbRGDluMp2ZXmbfZAdimprYIECBAgAABAgQIECBAgECGgADQskgCAsBhrYPTIuLGxZB+OSJ+LGN4aXfe/oh4ckTcHRH7IuJrFadxSkT890X9/1VEpFBx2z8CwG2L648AAQIECBAgQIAAAQIEZicgAJxdyTMnLAAc1jq4LCIuWAzpmSth4PooXx8R6dHg9PPciPiditNI4eKPLg4WOTYi/qLi/W1cLgBsQ1EbBAgQIECAAAECBAgQIEBgg4AA0PJIAgLAYa2Daxcn8X4lIo7a8NjtsyLi+sXQfz4ifqbCNFLNvxgR3xQR74+IFyzufVhEpDAw/fzZIhys0GzlSwWAlcncQIAAAQIECBAgQIAAAQIEqgkIAKt5TfVqAeCwKvvnEXF0RPxhRKTHdPN+vjEivrT45W+VOMV3tZ3/ZXHQR/qzfxER/zYiLo2IV0bE4YsLvxoR/3Xx5x/uiEgA2BGsZgkQIECAAAECBAgQIECAwFJAAGgtJAEB4HDWwSMj4q8Ww3lvRLyoYGj3RkQ6yff3IyLtCCz7870RcfXi4rRzML1n8Jicmw9ExE9HRHpPYNWfFPBt+vm2iPiDdMEdd9wRj31s0eVVu3c9AQIECBAgQIAAAQIECBAgIAC0BpKAAHA46+BbIuKuxXDeERHnFAztC4sDQNKBIE+rMI0fiog3L65PO/0eEREfWOwG/B8R8ZiI+IcR8X9FxJGL614cEe+p0Ee6NIWHpX4EgKWYXESAAAECBAgQIECAAAECBCoLCAArk03yBgHgcMp6XER8djGc34iIHygYWro23XNbRJxUYRr/NCKuXLn+dyPi+RHxwFobZ0bE70VEOnX444uQsXSoJwCsUBGXEiBAgAABAgQIECBAgACBjgQEgB3BjqxZAeBwCratHYA/EhFXrUz770bETTkM6f2C/2jxu78TEbdU4Cp6ptcjwBUwXUqAAAECBAgQIECAAAECBOoICADrqE3vHgHgcGq6rXcAfl9E/OZi2uk04BQ85v2shoU/vPLocBtqDgFpQ1EbBAgQIECAAAECBAgQIEBgg4AA0PJIAgLAYa2DbZwCfHpEXLeYdtr5l3YA5v08d/F+wPT710fEG1rkEgC2iKkpAgQIECBAgAABAgQIECCQJSAAtC4EgMNbA9dGxLMj4isRcVRE3J8zxHTq7/WL3/18RKTTfMv+pHb/cnFxOvTjOzbc+IKISCcSp5+fqnkacF7zAsCyFXMdAQIECBAgQIAAAQIECBCoKSAArAk3sdvsABxWQS+LiAsWQ3pmRNyYM7y0G+/yxe/SLr3fqTiNFPylk4P/5yJozDvc47yIuGLR9isj4u0V+9l0uQCwRUxNESBAgAABAgQIECBAgACBLAEBoHWRBASAw1oHp62Efr8cET+WMbx0Ku/+iHhyRNwdEfsi4msVp/GzK7sG/35E/Jec+z8UEd+9+N3xEXFHxX4EgC2CaYoAAQJLgbu+/Ndx6133xkn7Do99R6RXyPohQIAAAQIECBAgkC0gALQyBIDDXAPLx4DT479nRcQNa8NMj+K+cfFnPxcRKcxb/UmBXQru0s+vR8QPZkwzHfxxW0QcsTjZ98zFbsDVS78/In5j8QfpMeAXtcxlB2DLoJojQGAeAr/50c/GxVfvj/sfPBAP27snLnnpyXHOaenf0fghQIAAAQIECBAgsFtAAGhVJAE7AIe3Dk5dHNLxqIi4NyLSY8Ep0Ev/fE5E/OhiyH8UEU+PiC+vTaFMAJhueU1E/NLi3k8vDvhIjwY/JiJeHhE/HhGHLYLB1M//1zKVALBlUM0RIDB9gbTz7/TLr9kJ/5Y/KQS8/oKz7QScfvnNkAABAgQIECBQS0AAWIttcjcJAIdZ0hdHxFsWYVzWCFP498KIuDXjl2UDwHTrxYsdhCnoy/pJpxK/dOXAkTa1BIBtamqLAIFZCFx/2xfjlVftfj3s2859Rpx+4tGzMDBJAgQIECBAgACBagICwGpeU71aADjcyj4uIl67CPpSWPY3i8DvtyLiFyPivpyhVwkAUxNpd1/aDfj3IuKYiPjqYrffuxcHgKT3DHbxIwDsQlWbBAhMWsAOwEmX1+QIECBAgAABAp0ICAA7YR1dowLA0ZVsMgMWAE6mlCZCgMA2BbwDcJva+iJAgAABAgQIjF9AADj+GrYxAwFgG4raqCMgAKyj5h4CBAhExDZPAd5mX4pLgAABAgQIECDQvoAAsH3TMbYoABxj1aYxZgHgNOpoFgQITFhgLrsNhZwTXsSmRoAAAQIECIQA0CJIAgJA66AvAQFgX/L6JUCAQAmBubxvsGnIKTwssZhcQoAAAQIECPQqIADslX8wnQsAB1OK2Q1EADi7kpswAQJjEpjDicNlQ868kK9peDim9WCsBAgQIECAwHgFBIDjrV2bIxcAtqmprSoCAsAqWq4lQIDAlgXKhmNbHlar3ZUJOfNCvjn4tIqtMQIECBAgQKA3AQFgb/SD6lgAOKhyzGowAsBZldtkCRAYo8AUd7it7uZLNTn98mvi/gcPHCzPw/buiesvODv2HfHIncNW8n5/6133xiuvunFXWd927jPi9BOPHmO5jZkAAQIECBCYqIAAcKKFrTgtAWBFMJe3JiAAbI1SQwQIEOhOoMk77prc28WMsgLN1M/FV+/fCQFT+HfJS0+Oc047fqf7TTsET9p3+MbwsIvxa5MAAQIECBAgUEdAAFhHbXr3CACnV9OxzEgAOJZKGScBAgRqCAxt9+Cm3XxpemlHXwr10s6/5U/RY75Dm2ONMrmFAAECBAgQmIGAAHAGRS4xRQFgCSSXdCIgAOyEVaMECBDoX6AoOOtjhGXe95c1rqKQb2i7HPuw1ScBAgQIECAwbAEB4LDrs63RCQC3Ja2fdQEBoDVBgACBiQrUDdu65GgSSgr5uqyMtgkQIECAAIGuBQSAXQuPo30B4DjqNMVRCgCnWFVzIkCAQMTGwzNWH7HdNlbRbr5tj0d/BAgQIECAAIFtCAgAt6E8/D4EgMOv0VRHKACcamXNiwABAhEx1LDNbj7LkwABAgQIEJibgABwbhXPnq8A0DroS0AA2Je8fgkQILAlAWHblqBH3o11MvICGj4BAgQIDF5AADj4Em1lgALArTDrJENAAGhZECBAgACBDIE5BWJD3SlqYRIgQIAAgSkJCACnVM36cxEA1rdzZzMBAWAzP3cTIDBCgTkEO3OYY5dLb06BWJODWbqsgbYJECBAgMDUBASAU6tovfkIAOu5uau5gACwuaEWCBAYkcBUg53VwO+aT94VF1+9P+5/8EA8bO+euOSlJ8c5px0/oir1O9S5BWJDPC263xWgdwIECBAg0I2AALAb17G1KgAcW8WmM14B4HRqaSYECBQIjCnYqbKDbzXUPGzvnjhw4EA8eODrGCkEvP6Cs6PPk3/HtDjnFoiN6XMxpnVkrAQIECBAYF1AAGhNJAEBoHXQl4AAsC95/RIgsHWBsQQ7VXYpZoU3WbBvO/cZcfqJR2/dfIwdzjEQq7LmxlhTYyZAgAABAkMQEAAOoQr9j0EA2H8N5joCAeBcK2/egxaosvtr0BMZ2ODGEOxUHWNeqLlKbwdg9YU4x0DM3zvV14k7CBAgQIBAFQEBYBWt6V4rAJxubYc+MwHg0CtkfLMTmGPwsM0ib/IdQgBSdZdiVmC4d89DjxY8cCC8A7DB4hrCemgwfLcSIECAAAECAxMQAA6sID0NRwDYE7xuQwBoERAYkEDV3V8DGvqohpIV7AwleK2zBrLGfvaT98Wtd90bJ+073Lv/RrU6DZYAAQIECBCYqoAAcKqVrTYvAWA1L1e3JyAAbM9SSwQaC1Td/dW4Qw3sCNQJ3bqkqxNG2q3WZUW0TYAAAQIECBBoLiAAbG44hRYEgFOo4jjnIAAcZ92MeqACTUOYoQVRA2VufVhDDF6brqXWkTRIgAABAgQIECDQSEAA2IhvMjcLACdTytFNRAA4upIZ8FAF6uzayppLW+0M1WmI4xK8DrEqxkSAAAECBAgQmJaAAHBa9aw7GwFgXTn3NRUQADYVdD+BDh4htftr+8tK8Lp9cz0SIECAAAECBOYkIACcU7Xz5yoAtA76EhAA9iWv30kJDPER0kkBb2kygtctQeuGAAECBAgQIDBDAQHgDIueMWUBoHXQl4AAsC95/U5KoOtHSAVTk1ouJrMiYG1bDgQIECBAgMBcBASAc6n05nkKAK2DvgQEgH3J63dyAl09QtpVu5MrgAmNTsDaHl3JDJgAAQIECBBoICAAbIA3oVsFgBMq5simIgAcWcEMd9gCbe9m6npn4bA1hze6JvVtcu/wJOqNaNUgtXD65dfE/Q8eONjYw/buiesvODv2HfHIg3/GrZ61uwgQIECAAIHhCQgAh1eTPkYkAOxDXZ9JQABoHRAYsIB3Cw6nOE12qzW5dzgCzUaybvBDZ5wQV334M7safdu5z4jTTzx658+5NTN3NwECBAgQIDAsAQHgsOrR12gEgH3J61cAaA0QGLCAHYDDKE6TOjS5dxizbz6KLIPD9u6JOHAgHvj6BsBY3QHIrbm7FggQIECAAIFhCQgAh1WPvkYjAOxLXr8CQGuAwMAF7ILqv0BNdmI2ubf/mbczgjyDc5/9+Pi1627feQw4hX+XvPTkOOe043c65daOvVYIECBAgACB4QgIAIdTiz5HIgDsU3/efQsA511/sx+JgPeg9VuoJrvRmtzb76zb632TQerl1rvujZP2Hb7r3X9l3hHY3ii1RIAAAQIECBDoVkAA2K3vWFoXAI6lUtMbpwBwejU1IwIEOhBoshOzyb0dTKVxk3UC6ToGde5pPDkNECBAgAABAgQ6EhAAdgQ7smYFgCMr2ISGKwCcUDFNhQCBbgXqBF/LETW5t9tZVWu9SShXx6DOPdVm5GoCBAgQIECAwHYEBIDbcR56LwLAoVdouuMTAE63tmZGgACBVgU8ztwqp8YIECBAgACBmQkIAGdW8JzpCgCtg74EBIB9yeuXAAECIxMY88EcdhKObLEZLgECBAgQmKCAAHCCRa0xJQFgDTS3tCIgAGyFUSMECBCYvsBYdwA2eWx5+lU1QwIECBAgQGBbAgLAbUkPux8B4LDrM+XRCQCnXF1zI0CAQMsCYwvTmoSWdg22vHg0R4AAAQIEZi4gAJz5AlhMXwBoHfQlIADsS16/BAgQGKnAmIKxuo8tjy3oHOlSMmwCBAgQIDArAQHgrMqdO1kBoHXQl4AAsC95/RIgQIBA5wJ1dgDWuafzieiAAAECBAgQGL2AAHD0JWxlAgLAVhg1UkNAAFgDzS0ECBAgMB6Bqrv56u4aHI+IkRIgQIAAAQJ9CAgA+1AfXp8CwOHVZC4jEgDOpdLmSWDkAmN67HRM1HNxrTJPOwDHtIL7G2uVNdXfKPVMgAABAkMSEAAOqRr9jUUA2J/93HsWAM59BZg/gREIVN3BNYIpDWKIXPPLwGYQS3Swg7A+BlsaAyNAgMCgBQSAgy7P1gYnANwatY7WBASAlgQBAoMWsBurm/JwLXa1w6vYaI5X+OzMsermTIAAgXYEBIDtOI69FQHg2Cs43vELAMdbOyMnMAsB72Prpsxcu3HV6vQFfHamX2MzJECAQFcCAsCuZMfVrgBwXPWa0mgFgFOqprkQmKCA3TbdFJVrN65ZrdpJuD3rbfTks7MNZX0QIEBgmgICwGnWteqsBIBVxVzfloAAsC1J7RAg0JmA9219nbbNMIlrZ0v2YMOMuzfuowd17UNdnwQIEBi/gABw/DVsYwYCwDYUtVFHQABYR809BAhsXaDN4Gvrg2+pwy5ChyquVa5tacqjbsZOsVGXr3DwPg+FRC4gQIAAgTUBAaAlkQQEgNZBXwICwL7k9UuAAIEKAn2HSV2EjxWmP8pLvStulGUzaAIECBAg0JmAALAz2lE1LAAcVbkmNVgB4KTKaTIEqgnYwVLNq8+r+wyT+g4f+3Rv0je3JnruJUCAAAEC0xMQAE6vpnVmJACso+aeNgQEgG0oaoPACAXs6BpX0foMk/oMH8dVpd2j9TkbewWNnwABAgQItCcgAGzPcswtCQDHXL1xj10AOO76GT2BWgJ9hkm1BuymHYG+wiTrpdkCtNO2mZ+7CRAgQIDAVAQEgFOpZLN5CACb+bm7voAAsL6dOwmMVsCOrvGVbhkiHfXoh8fd930tTtp3eOw74pFbm8hq+HjYnohXn/n4OPesJ2x1DFubrI4IECBAgAABAh0ICAA7QB1hkwLAERZtIkMWAE6kkKZBoIqAHV1VtJpf23QHWF87/9ZnnuZx1bV/HG++7vZ44MED8bC9e+KSl54c55x2fHMkLRAgQIAAAQIEJi4gAJx4gUtOTwBYEsplrQsIAFsn1SCBcQgMJVQah1b9UW5yLhMMDimsHdJY6ldkGHeWqf0wRmoUBAgQIECAQFsCAsC2JMfdjgBw3PUb8+gFgGOunrETaCgghKgGWNVrU2B2zSfviouv3h/3F+ykG9Lj2kMaS7XKDetq4fuw6mE0BAgQIEBgWwICwG1JD7sfAeCw6zPl0QkAp1xdcyMwU4GqQV0ZpjqhTV5g9qZXnRrnv/3mnfBv+ZMep73+grN3vVNvSLvuhjSWMjUb4jUMh1gVYyJAgAABAtsREABux3novQgAh16h6Y5PADjd2poZgVkK1AnqiqDqhjZ5913xilPiNW+9aVe3bzv3GXH6iUfv+vMu5lQ057zfD2ksWWPsIvyta5V1n12UxZpDr2HxDFxBgAABAgSyBQSAVkYSEABaB30JCAD7ktcvAQKtC3zi8/fEi6+4Lh44ULyzrkrnTUKbrMDs7Cfvi9Mvv6bUDsDlOLsMRaq2XfX6KtZNrh16OJnmVjdMbuIypnvHUMMxeRorAQIECAxLQAA4rHr0NRoBYF/y+hUAWgMECExCIAUHF77rllh5qvbgvPJ21pWdeNPQJiswG0rQMZRxlK1F3nVNa9S0/yr3T8W8ypzLXDumGpaZj2sIECBAgMC6gADQmkgCAkDroC8BAWBf8volQKA1gazgYNl43rv1qnbeRWjT9066KQUuTXZpVl0LbVzfd+3bmEPbbYythm3PX3sECBAgMH0BAeD0a1xmhgLAMkqu6UJAANiFqjYJENiqQF5wcNiePXHpy06Oc047vpXxTC20mVLgMqUws5XFOsJG1HCERTNkAgQIEKgkIACsxDXZiwWAky3t4CcmABx8iQyQAIEigazgYO+eiPecf2Y85Zgji24v/fv1AHDsgeDUApcudmmWXhwubEVADVth1AgBAgQIDFRAADjQwmx5WALALYPr7qDAaAPAsX/xtgYJEGhXoOvgYL39l3zHt8e7//BzOwd5pMeML3lpezsN25XZ3FrXbtucS+rLfzdsW7z9/tSwfVMtEiBAgMAwBASAw6hD36MQAPZdgfn2P8oAcGpfWOe7/MycQLsCXQUHm94xuJxBW+8azBPpam5TDM2qWFW5dopW7X4CtUaAAAECBAhsEhAAWh9JQAA43HXwuIg4PyJeGBHHRcRXI+K2iPgPEfFLEXFfB0N/dETsj4jHL9r+k4g4oYN+UpOjCwCn9shaR3XVLAECLQrkvStvvYumpw3nDdm/9ChfzCpWVa5NI6h6/eqoqwaN5We8nSvHPv7tKOmFAAECBAhsFhAAWiECwOGugRdHxFsi4jE5Q/yjRTB4a8tT+FcR8X+utCkAXMGY0kvrW143miMwGYGhhQ197gD0Lz3KL+sqVlWuTSOoev3qqJsEh+Vn392VReMf2ue1OwktEyBAgACBZgICwGZ+U7nbDsDhVfLUiLguIh4VEfdGxOUR8aHFP58TEecuhpxCwKdHxJdbmkLq9w8i4muL/zsiIgSAK7hNvoS1VCPNECDQoUBR2NBh1xub7usdgP6lR/mKV7Gqcm0aQdXrl6Me+39nFY1/qJ/X8qvGlQQIECBAYHsCAsDtWQ+5JwHg8KrzexFxVkTcv/jPG9aG+FMR8cbFn/1cRPxsC1M4LCJujIjvjIh/ERE/HBHpEWQB4BquLxwtrDZNEBigwEdu/fP4J7/60TiwMrau361XhaGPU4CLApgq4x/CtV3uFqtiVeXa5Fb1+qV13eBwCLUqCj5P2nd4nH75NTsH4Sx/hvR5HYqhcRAgQIAAgaWAANBaSAICwGGtg9MWQVwa1S9HxI9lDG/v4j19T46IuyNi32LHXpOZ/GRE/OuI+HRE/J2ISLsLBYA5ol1+iWxSRPcSIFBP4CffcXO886Y7M2/u6t169Ua6/bum8i89tjGPKn1UuTZVver1TYLD7a+y7B43BZ+33nVvvPKq9O8tD/2Z++d1KLUzDgIECBAYnoAAcHg16WNEAsA+1PP7vCwiLlj8+pkrYeD6Ha9fPBqc/vy5EfE7DaaRgr6PR8Q3RMTZi8eNbxcANhB1KwECoxH4xOfviRf8m49kjnfsO4ra+pcVbbXT16Kou4OuznirWFW5dhnopeAr7X7bd8QjSw2vTnBYquEtXZQ3/m3WdEtT1Q0BAgQIEOhUQADYKe9oGhcADqtU10bEsyPiKxFx1OIx4KwRPiu9Fmjxi5+PiJ9pMI33RsQLIuI3IuIHFu0IABuAupUAgfEIXPXh2+LS935q14DTfzle/vKnxTmnHd/JZKqGP1UH0WXw0/XYq8616PqiR2HHNp+i+a7/fuzzyxt/l2u8qrHrCRAgQIDA0AUEgEOv0HbGJwDcjnPZXv48sYEHEwAAIABJREFUIo6OiD+MiFM23PSNEfGlxe9/KyL+cdkO1q5Lh4q8PSL+MiKelF41JACsKek2AgRGKZC3A/AtP3JanHnSt3Qyp66Diy53R62O/bC9e+LVZ5wQ5571hNI70joBLWh0k8c1n7wrLr56/8675NKOz0teenJnoW8fc596n2MPN6deH/MjQIAAgeEICACHU4s+RyIA7FP/0L7T8zx/tfijtCvvRQVDSycEp8d2fz8i0o7Aqj8pRPxkRHxrRPzvEfErKw20sQPwsQUD+rbFqcNxxx13xGMfW3R51em5ngABAuUE1t8B+PJTj41f+L5N/w6mXLtZV3UZzi37K9rxVnf0WWNPbR22J+LSl9XbLbmtACcrdD37yfscJFF3MbiPAAECBAgQGJWAAHBU5epssALAzmgrN5y2mix34L0jItLuvE0/X1gcALI/Ip5WubeIX12c9ptOGT4j4pDDL9sIAFcP09w4PAFgjeq5hQCBVgXSTsDrbv1inHHS0fGUY45ste3VxroK51b76CpkzBt76rvO+xI3vd+t6rvuyhRsPWzcRi3KjMs1BAgQIECAAIGuBQSAXQuPo30B4HDqdFxEfHYxnNX38eWNMF2b7rktIk6qOI2zIuK/RsQDEfGdEfE/1u4XAFYEdTkBAgTKCHQVzq333cVjxnk7AJd9VzmBNc/hp5/3xHjjBz69lUdyt1WLMuuii2u2tbuyi7FrkwABAgQIEGhXQADYrudYWxMADqdy29oB+IjFOwafGBH/OiL+WQZBGwFg0TO9HgEeztozEgIENgi0HaR0Ec5lDb/tcac+0tgvunp/PPDgoZu8q+4AzNt9d9iePfHAga+3XbXdqgt5W7UoGlfbtRrKvIrm7fcECBAgQIDAdgQEgNtxHnovAsDhVGhb7wBMpwb/84i4IyKeEhHpXYLrP20EgEWyKSBMY/AOwCIpvydAoDeBQw692BPx6jMf38qhF20HPm0BlRlXuuaqa/843vyRz8QDBx56/Lfq4RlZu+/27olYyxV3plVlZ2EdhzJzrtNu2XvaDuumvrOxrKvrCBAgQIAAga8LCACthiQgABzWOtjGKcBfjYi/FRG/FhG/kzP9KxenEX8xIs5bXJPeT3hNi1wCwBYxNUWAQPsCuYde7N0Tl07wtNiqQVTT4Gy9v9c974nxhsXjv8tqdr0DsP1VU67Fpd1Rj354vOTK63YeeW5rzt5tWK4GRVc1Xd9F7fs9AQIECBDYpoAAcJvaw+1LADis2lwbEc+OiK9ExFERcX/O8NKpv9cvfpd29P1MhWmUPpxjrc3fi4jvrtBP0aUCwCIhvydAoFeBTYdepJNvr3zlqfH0E74p9h2RNnCP+2dbu8bWQ5X1f64aQnap3kYAlNXGobtKD33keTmfJrset1XLLu37bntI67BvC/0TIECAwDQEBIDTqGPTWQgAmwq2e/9lEXHBoslnRsSNOc2/PiIuX/zuuRt28mXdLgBst2ZaI0BgogJFh16kadd5/HWIXNvYNVY2VGkjeGtqXHasm/rJauPsJ++L0y+/5pAdf+tttLHrsY3xNzVs+/5trQsBatuV0x4BAgQIDEFAADiEKvQ/BgFg/zVYHcFpK6HfL0fEj2UMb29E7I+IJ0fE3RGxLyK+1vI0vAOwZVDNESAwToGdQy/edcvOu+7yftoIbNrQaRKQdB16dNl+k3lnuaf2nnXZBw+pedUa5833ilecEq956027ul2+/7DNQPkTn78nrrv1i3HGSUfHU445so0lVruNpjU6ZNfk3j3x6jNOaOVdnFkT2kYYXhvSjQQIECBAoKaAALAm3MRuEwAOr6DLx4DT479nRcQNa0P8qYh44+LPfi4ifnbt9+kx3Q8t/uzXI+IHa0xRAFgDzS0ECExT4OChF9fdvuv02+WMmzyy2Ybaph1fq++bu/u+r8VJ+w7PfGy5y11jXYUqXYz50vd+Iq768Gd2lSWvxlnhVt583/SqU+P8t9+8651/7z7vjNhUm6prpAuXqmNYXt90LLnv4twTcenLnhbnnHZ83aFl3tdlWN3qQDVGgAABAgQqCAgAK2BN+FIB4PCKe2pEXBcRj1qc0JseC06BXvrncyLiRxdD/qOIeHpEfFkAOLwiGhGBPgSa7rLpY8xj6jP5fuz2L8V5b7/5kCCw6u6wtue8KbC45pN3xcVX798VOOWd2tvVGuoiVKnaZpm57ez+u/yaXUFveufjDRc+Z1dwmhdula1Jmzv+luuqqkvb63G1vTbGsuldnF199pqGll2aapsAAQIECNQREADWUZvePQLAYdb0xRHxloh4TM7wUvj3woi4NeP3dgAOs6ZGRaBTAV9YO+U9pPGhWVfZbbacSFfByaYqtO1WZVdh2b7z2jz32Y+Pi174lEOmVxRuldmVmbcbs8lqruLSpJ8y97YxlqJ3cXa1+7YoMC76fRkf1xAgQIAAgW0JCAC3JT3sfgSAw63P4yLitYugL52Y+zeLwO+3IuIXI+K+nKELAIdbUyMj0IlAURDRSaczb3RIX/6rvm9uWbqugpNNS6NNt7Lrvux1adxZ1x62d0/ccMHZu3b/lQm32pxv2Y9clfmWbbPudW2NZeddnFfv37Uzs48gO1mUDZTrurmPAAECBAi0LSAAbFt0nO0JAMdZtymMOoWad6SJ3HHHHfHYx6Z/9EOAQB2BMkFEnXbdMx6BvBNnn3nZB+PBjANM+gpOmohmhWllgpiqn48ybeaFhUNxLTuHJvUoe29bYzn4Ls6PfGbngJYuHp/eNKfVd2m+5Mrrdj1Wf31GSFzWyHUECBAgQKBrAQFg18LjaF8AOI46TXGUAsApVtWcehFoa5dNL4PvqdOyO7PKXtfTNA7pdnWs6RfpfYU/8dabYj3/S++z6+LwhC4MlnPaf+c98cYPfHondFkPfopqlPVev6KgrqjN5VzbCre6tOviMeOq4y3rWabdNtsq01+6ZrXOyxOb1+/tY0dt2fG7jgABAgQICACtgSQgALQO+hIQAPYlr99JCgw5iBgaeFmrstcNeX5ZY0sn0b7gad+eGx7uO+KRg5jSqv/6gIoCvNXrUzsXvuuWgzshU4BzWYunx5YNpLKuK3vvIAoy00EUvYMwsVRZjzNlNG0CBAgQ6FlAANhzAQbSvQBwIIWY4TAEgDMsuil3KyBMKPYtu1uy7HXFPW73iqKwIiuoGGLQWTSPpFpmx1XmO/1yTvTtslJZxqm/5QnN236ctcu5Tq3tvEfID9uzJx44sHtH6tTmbz4ECBAgMA0BAeA06th0FgLApoLurysgAKwr5z4CBGoLlH0fXNnrag+koxvzxp26ywqZhhp0bprHci5l3rm26YTk9V2QeSVpGqznHSwSBw7svMtu+WMXWUcfiobN5n1G3n3eGXH3fV+LITxi3XCKbidAgACBGQgIAGdQ5BJTFACWQHJJJwICwE5YNUqAwCaBsoFX2euGpp0XNl35ilPi6Sd8U62TbPuY46YdgFV2y+W1U/Y9iG3sjiwKM1d9y+xq7KMec++z6jpoGhrP3dv8CRAgQKB9AQFg+6ZjbFEAOMaqTWPMAsBp1NEsCIxOoOyX+bLX1QHoMiCoMu4ug86mc1yfx+ue98R46rFHVt5xldq56Or98cDacchFO+7asvnE5++JF13xkUNOYz4svYhwizsAm9aizhqf2j1lDat8/qZmZD4ECBAgMFwBAeBwa7PNkQkAt6mtr1UBAaD1QIBAbwJlv8yXva7KRLYREFQZd93xbOqjbpvrjlXmsakG77vlc/Gat96065JNO+7aeAw86yCT5Q7GNJhtvAOwrVpUWeNzvbat0HiufuZNgAABAt0JCAC7sx1TywLAMVVrWmMVAE6rnmZDYJQCVQKmKtfmYQw1IKg6t02h0hDnWGdM2QeI7InfPv+MeMoxR+au96XlUY9+eLzkyuvi/pWdh+ngiNX7q7pX/ZCVnXfX46g67rFe30ZoPNa5GzcBAgQIDFtAADjs+mxrdALAbUnrZ11AAGhNECDQq0DZnVEpHLnq2j+ON193+85jpFXeQbc+wSkEBEWh0lDnWLbeqWbLQGz/nffEGz/w6UNCvE31X+0jPeW79tTxznLYtOuw7SCuTC2quPT6gR1B50WfjRFMwRAJECBAYKICAsCJFrbitASAFcFc3pqAALA1Sg2NRaDtL/djmfcQx1n2i/rO++Pedcshp7Wm+RS9Py5vzmX7HaLZckxFoVL2zrmIK195auZBJNuca5nP4Hog9hN/78S48ppbDwnzsuqfNe/1uW1aN10EcXm1uOHC5+wcCDPW9VimjttcV6t9dVHHvuay7X6HXNdtW+iPAAECbQsIANsWHWd7AsBx1m0KoxYATqGK5lBawJfC0lRbubAoxEqDKAp06p7YOva1UCY0Wt8JlzzTbrg6uyerhAJVrs1aaFlzK7uTL29Npcd+HziweedoGdO6H4xUiwvfdcvBADPN57KXPS3OOe34KPM5qNtvV/eN4fPTdB12ZTfkdsdQ1yH7GRsBAgSKBASARULz+L0AcB51HuIsBYBDrIoxdSLQ5Zf7TgY8g0bL1CQvHEk8dXcALmnHHhCsB3wXPP9Jce5ZJx6yctIcP3b7l+K8t998yAm8m+zWXaqEAlWuzVviRSHe8r6yOwDTde8+74y4+76vbTy9uMsgLpk+6/JrDqnB8l2ERx/+iDj98mt2PeJ8/QVn7+wQHNrPps9tGuutd91b+ZToIc1x7H8v1LUs8/dx3bbdR4AAAQIPCQgArYQkIAC0DvoSEAD2Ja/frQt0+eV+65OZUIdFgVHeDsDD9u6JS1968s4Oqjn//Mq1t8Ub3v/pjbvbqqz99Xr89POemPn+vaxwqq0AIa+d1bFs2sX4k++4Od55050Hl8XLTz02fuH7Ttm1TNaDnjbGnxce5dVguRMwDW4bpxG38VnJm8u5z358/Np1t+8EmXV2mbYxtqZtFP191LT9Id9f5e+JIc/D2AgQIDBkAQHgkKuzvbEJALdnradDBQSAVsRsBNr4cj8brC1PtGjHzeqX8sP2RLz6zMfHuWc9YZC7o9qkK3L5xOfviRdfcd1O+Lf8qbIrbj3Ey35X3UOPzq7/ZD163WaAkBfEFJlk7bTLMslrv0kAVPVU5vWapX8ew+65zHWSkswDBw55T2fTHbptfpbKtDX3/46Y+/zLrBHXECBAoKmAALCp4DTuFwBOo45jnIUAcIxVM+baAk2+3Nfu1I2tCBQFP610MqBGitbq+jvlVoe+Gs4t3VZP0s3bnbVpl9rqSbop63nP+WfGU4458hCxtgOEOjW/9L2fiKs+/JmNgWXROOv0W9RmGtBDh9nsLx2oDmg57hrK+vr8oTNOKHQf8nzS2NoMsIc+17zxFf29M9Z5GTcBAgSGIiAAHEol+h2HALBf/zn3LgCcc/VnOvc6X+5nSmXaPQkUhUl5j0Wn4a7uulr/Mv+65z0xnnrskbnvZ8vrN933hg98etc76i7JeAS7ywCh6LO7s/vvsg/uOi06PS5+w8r79LoIevLavOiFT4rvPeXYg7tV067NF13xkcLTjHtaepW6Xa1HunFM7zHMmmjR564SzogvLvqcjXhqhk6AAIHeBQSAvZdgEAMQAA6iDLMchABwlmU3aQLNBXxJbG6YF0L8p5vvjEvf+6ldv17u7Nt0SMalL3vovYh1w4y8AK/s48Zp0KnvdPBI+nn6Cd/UyqPaZYLFTe+mu+iFT9kZV3rE9qhHPzxecuV1rR66URTKroalZebSzerqttWxzSvr77CxzaHbimqdAAECBNoWEAC2LTrO9gSA46zbFEYtAJxCFc2BwJYFxvIluYuQsos2l+VbdV0v6erOvqywaf2x3Ca73LLmmNfem151ahz16L91yK7CttdH2TAz8910eyJuuPA5cc0n7zrkkI1/8NRvjf+8/wsbD0+p+rEqW79lSDqG9/1VNejy81F1LJuuL3pf4xRr06aftggQIECgnoAAsJ7b1O4SAE6touOZjwBwPLUyUgKDECgbxvQ92LqHSNQJDdoIParsIEtjLArZyoSEVWqU1176HzAPHHjo0eO0y+3sJ+9r/VHQpuFj1piWc0/B6XlnnxTPeMI35z4avby2TJ3TNUU7OKu4r15bpv+6bW/zvr7nMZa/w4pq0rdj0fj8ngABAgR2CwgArYokIAC0DvoSEAD2Ja9fAiMVaLKzbFtTzvuC/9PPe2K8cfEuu7yDMPLG2EWbq32VfYdclUAoa0da1Xmv9rfp4JF0XWr7ilecEq956027GLNODS67HnLDxz174oEHDxwMH9Ojz+lnPRjJs13vf9VmvY2iwHW9Luvvwztsz5747fPP2HVwSlmDKv2XbbOP64YwjzH8HVZUmyE4Fo3R7wkQIEBAAGgNZAsIAK2MvgQEgH3J65fASAXGsHtm0zvyHjhw4KD86mO1ReXoos2i0KjK+PLGX+XdfUUGqfZZh2ys3pceCT7/7Te3+n691P5q4HHYnohUxdWTiTdZbdpdmRUCrh56ktrNOwTl3eedEXff97XMnYNthq9j+MwVrZ1lMDuEg0LG7jn28ZdZK64hQIDAVAXsAJxqZavNSwBYzcvV7QkIANuz1BKB2QgMffdJ3o6x1cBoWayyO9O6aHN9wXTh2uZup6KddMsQbv19e8tHg+u8V211J17ySm3cfd/fVN5luOn9fOt1SI8Fr66V9X9eXr/887xdlW2d+NtmDddD57I1aeNx067mUecv3i4+a3XGUeeePh3bWAd15uweAgQITEVAADiVSjabhwCwmZ+76wsIAOvbuZPArAXSF8G2T3ptE3T9C37eLq7rLzi79Cm1XbS5PudNX7DrfPluc7dQ1m7C5fjXQ7DVsWYFgsvHdfNqnu6/6to/jjd/5DOHvGNwecLxMy/74K6Q7j3nn5m7Iy/1k8Z/3a1fjC//9f3xpg/ddsguxeU40qO6q7tEi/58df7ra6mNoGb5OTvvbTftOGzqb/m7MuukSgC2em0KPV9x2nHx2u/526U/N6vjGsIOwCpObf6d1FZbbX6mq4ypypqp0q5rCRAgMCcBAeCcqp0/VwGgddCXgACwL3n9Ehi5wBi+DG56j1t6jPTVZz4+zj3rCaWDjKzQc1sOWeHjU489svDgirTM2hhj3iOtKVjdNI46YUXeuwaXOwzTnNYDwPQ/pPbuzX4nYJbBctz777znkPdCrr4ncjVsW/3zvJBwfTdpnbmv/rWwHryl36WdiZve4/gr194Wb3j/pzeeblxlXHmPTyfvy1/+tCgKctf/mmtjLY78r85Whr9txyprppUJaoQAAQITFRAATrSwFaclAKwI5vLWBASArVFqiMB8BIbwZTBvl9Nyl9cZJx2deeDCwZ1l192eeYBEXhU3feEus+OqzOrIa2fTO+zKHuqxbPuoRz/8kF1yZcaerll/91/aCZZ23D3lmCM3Tq3qLrjU13q4t9pBCtnSzyuvunFjv6vvBCxar+s2H7/znnhDxmExq9e95MrrSr3nsG5QkzXmw/buiStfcUo8/YRvygytr7r2trj0fZ86xCXr3YhVarLpse80nhsq7KBdDqzMmivzeZnrNXmf5S49qqyZLsehbQIECIxdQAA49gq2M34BYDuOWqkuIACsbuYOArMX6PvLYF6o8pPvuDneedOdB+vz8lOPjV/4vlMOqVdRGJRV3Dr3VF0km4Kisu/e23fEIzd2u97HS77j2+Pdf/i5nSArL0hMc//Zd3883nfLn+1q+6IXPim+95RjN+6gzAuy8oKj993yucz3+6XOV3cArj9KmjXx5Y68Mut13Sbt+Dt5ww7LKsFeUeCV9fsyY16d86bgtMnOxIfC32syH4tO/Zd9h2bVz4PrswWqrLs2Dbfxd2Cb451jW0V/z8zRxJwJDFFAADjEqmx/TALA7Zvr8SEBAaCVQIBAZYEmXwabfknJ6/vfv/q74vt/9aO75vK+1x66S61qsJIazLunTABWBrfIc9MOwGX7RUFMmTbWd4ulsOGid91yyLvn1udTZgfi+iO9affgZS/Lfnw0LwDcGxGXrTxyun4qcHo0duUVeZH6+P0Ln7MTTtbxLXMCc9O1nCzzAp2iMa/XYdMp1TdcuPs9l1WCpPRY8WVrOwtT/0U7ANvwKfP5mcs1VddE2y5V1kzbfWtvs4DaWCEExiMgABxPrbocqQCwS11tbxIQAFofBAjUEqjzhaPOPWWDjlc947h464137JpLCunOffaJB/+8zpfoTeFZmQCsCLhMKJn1Dr5lu2XCqqJdhOtBYpnAMK//9eDnoV1kHyx1iEXWTrY9eyLeu3jceLXt1H86xTY91vyiKz6y61CQZQCYF7Sd/eR9pU4V7irIKlqLVT4vefW68AVPih896+vrf3UtVplXerw4hYDLkHVTiLsp2Cz6LPh9vkCZvye69quyZroey7bbH+rci/4e2baT/ggQ2CwgALRCkoAA0DroS0AA2Je8fglMQKDKF6K2vqQ03QG4DCcuunr/zjsA0y6mS196cuFhBpt2w5UJ4DaVu6zN0nv94IpLVsafV5Mygd7qPMoGhuvBYVZodfw3PzrznX15uxZ3rDPqkxeIlQ1GVm1WTyZOB8KkYCvtIlwPNeucYFz2o11m3FU+Yymku/z9n9qZRwroLnj+k+LcnPAvb4yb+ku/K3Pyd9n1XNbJdQ8JcO1vJVQJ47c9yjJ/j2x7TPojQCBfQABodQgArYE+BQSAferrm0ADgSrBQINuWru1zS8pZd8BmAaf9R7A1TAvhT+X5jyOujr51VAqC6XoEdwiyKpfMLPqX9RGlXcAZu3EW84h/VvL1cdtN72bL/3u3eedEWUPzVj2sR42pT9ff+9fUb/XrxxQsb5zcL2tFJjt2XPoKcJph2Ben0XvWyyqd91AJy+EO/SR6D3xuuc/8eDOv7J/VxStnzJzStfkfdbf9KpT46hH/61SJ1eX7avsdWUNlnVJO0tP2nd46RPCy46j6XVt1ajpOOZ0f53gtcp6a2pZZ3xN+3Q/AQL1BQSA9e2mdKcdgFOq5rjmIgAcV72MlsCOwBi/BLb9JSXrC1Y6AfgF/+Yju1bJ6nsA033Puvyand1/y5+iHXxFu+eK7l8NtTYFC02+NJb1Xe9jU59Zp8qmwPR1z39SvDHjlNxNIe9n/+K+uPjq/RsPHFkt3Poa/6EzToirPvyZXbVdBq+bPhNl21oPqNoMrfP+6lp/l+Grz3x8nHvWEzKDp7x3KW4KKsvuYCy7fsr8FZzV1k7AGrHzGHgbj82XGcfymip/X1a5tsoY2ry2yd8TbY5jLm1V/XugjzXUR59zqb95EmhbQADYtug42xMAjrNuUxi1AHAKVTSHWQm0+UU9C67LL5ddf0m56sO3xaXv/dSuaa2+B/DS935iY5CUZbLpcdiyYUbVuacw8z/v/7P4tiMfGc958rcW7kSq+iW17IfmF3730/GLH7w1Hlycwrt83DhrnRStzbJrK6ud9Kj2gw8eyD3oI82n7JhSiBmL3X6bQuCi+ZQ1LLou9XPVtX8cb77u9p1gOmtNZQXXqd10OMqlLz85Lnjn/l3dpEDz/LffvBO6Ln/yDu4oWj9la5cVuqU+Dxw4kPmIdRs7KTf5VqlhlWuLaur30xGosi6qXNu2UNXPaNv9a48AgXICAsByTlO/SgA49QoPd34CwOHWxsgIZAoUfVFvwnbIbqS9e+LVZ5yQuxupbj9dfkkp2gG4E6KsHUaR5pEXiizHmg6ZWH+ENd1z5StOiaef8E2F4VzVL4U/+Y6b45033XmQOP2PhMtXTsDNsq/aR1FoknYqfvzOe+INi51+h+059LHSvPvTibFveP+n44EDD71fscwaWl8TeWt8/dHj1ZN+88aT19a5z358/Np1txfuSMx7H2HTdbx6fxp71iPJ71kcfJJ+vymETg7pZ/0dhle84pR4zVtv2kWT5n7RC59yyJ9vWj9ldxGud7Sc4933/U3mOJo+Nl/m76Aqf19WubZM366ZjkDZf4FjDU2n5mZCoCsBAWBXsuNqVwA4rnpNabQCwClV01xmIdBm0LMKltXuTjhW8h15Q8FfD89W3wG4KQxaD0SqvC+vaO5VvhTmhZh5IeVq32W/pG4a72ob69dtetR5fRfb8n/YpL1nm3ZJZo0565HWFECmUHH9J+3u/N5Tjs0NYTd9XlJbRe96y3pfZLpv+ThzncM2yj6SnOZ86cseOqAmbwfg0iPrEdvkuP64+/IzfcOFz9llVrYWZR95X44tb0dn2QC96PO16fdV/r6scm2TMbl3nAJlQn9raJy1NWoC2xQQAG5Te7h9CQCHW5upj0wAOPUKm98kBdoIetZhih5zXT1QYeioKUS77tYvxhknHR1POebIg8PNDCL2RKyHIXlf4tJhFnff97XKhwNU+VKY9xhzmkSZHVNlvqSuBjOrAVheCLxa76wxrIZkeWtj9cCOZZ/p2rxDNtZ3nf3085548L2D630U7TSs+3nJC67iwIGdd9mt/lz4gicdPHSjaiCV9Ujyso3VnabJ5MJ33XLITr/VvrIO2aj6yHvZ3Zhl1uLq2FZrsLpjsewj9E3+zqlS/yrXVh1Tlc9m1bbHdv2ULbpcQ2Ors/ESILBbQABoVSQBAaB10JeAALAvef0SaCjQ9heoovCn6hf+htPr7PYyX86q7NgrO9Ay/aa2muwALDuWdF3WeI7/5kfHK6+6MbeZrJ1fRetmtbH1x26LDvZYX+Obdiemfpa7VdPOt/Wdfettlfn8bArF15HSbr0bLjy78HHwTbtQ/++PfCY33FsGZX/nuCPjnf/tT3feF7j+yG9WSL+zc3DtsfcqO/iqhNd5C2dpnR6lv/2LX4nz3nbTIQFqlfFUWeOr15ap9/L6KteWHU/Zz3/Z9sZ83RwsulhDY665sRMg8HUBAaDVIAC0BvoUEAD2qa9vAgMTWH3f2erQtvEz4g3pAAAgAElEQVQFfZsURV/O2gg9suZT1O/ynjrvAKzit2mH4/q7Dpftru7UWp1HCto2hYbL+9NOtvWdc+vv9EvXpn427bRMff+nm+/MPOwl3b/zKOzigI+83WVl33WZtwNw/TCS5RxTSH7SvsM3Pla8aW198d6vxouvuC7zUeeDc1ucpLta7zTny172tJ1HhbN+mgYuh3jtidh0UvF6/2Ufd57Kv2DI+9zn7XTt+hCUKn8v1L227N9rqf2u/m6tO3b3ESBAYNsCAsBtiw+zPzsAh1mXOYxKADiHKpsjgQoC6QvazomkH/nMzi6dbTyiV2F4By+t8qWzTvtlQ6I6bZe5p+opwGXaXF6zaYfjZ//ivoPvt0u72n7i7BPjmU/45oOPPa8HOq973hMPHhSyPoZlwJfWUN5uv/V7nnHCN8bH/uQvc9deqvsHP/mFzFNvswzWw+u8HYt577rMehfk1TffuWunXupn9THlqu89XIZ3Rbscs+aYxp71Tr/Va5t+Xg7+vbDhpOL1seUFqAcePLBzqvTyZ2r/gmHdoYsdxVU+711eWzVcnrJFl87aJkBgOgICwOnUsslMBIBN9NzbREAA2ETPvQQmLNA0MOiSpuqXzrpjGUsYWnV+Rbtwrrr2trj8/Z/aCbnWd/5l7WRKwdcb3v+pXe/FS//j5pdederOScnp55mXfTD3Ede8OayGQ3XCsdTu6u6yOu+6XH2ENWuHZArgXv/8J+0KQosOTck7gCT197Hbv7TrUdlNde5iB93q3wGp76q72Mqc5ly0e7HM2u7r76qy/RZ93srMcYjX1JlXnXuGOHdjIkCAQF0BAWBduWndJwCcVj3HNBsB4JiqZawECGz1EbI6X1bLhgJFpWyrnbx+8kLUTXPOe9w3hU9/8hdfydyVlw6meMHTvn2nbs+49IOx+xzfIomHArz0aO16ALV+5970B3ti47vx8nYALtvaFKTlBVrLwzeyHoUuOqV40+zXd6EeOHAgM0DtYgddG4/uFlmnueedbl12/W/rXwas16lqv1WvL/5U9H9F3d18U7TovxpGQIDAWAQEgGOpVLfjFAB266v1fAEBoNVBgMCoBOp+6awzyap9tfXFtmk7ZcOTrOs2zTkrhFuGT2nH2mveetMu5mUAmHcabVFdlu1vetfg6inA66cHX/LSk3e9G6/uuy7rvr+vyWP0qzVandvSrUnbefZ5j+6uv8OxTPB46PsD92S+33AZui7n+vE77zm4mzJvfgd3Sb795nhg5TSUMmMqWnNFv6/zLwZSm2U/l0X9D+X3dR2maDGUmhgHAQLDFxAADr9G2xihAHAbyvrIEhAAWhcECIxKoMmXztWJrj7Wefd9Xzv4jrv1a8o+9tjmuMr2mVW4ovAwL4TY9Jhr3mO4648Hrz/iu3wE+ISjvyFefOV1hwQ1ZRbd6nv58naTvfIZx8X/8T1/+5DTd7PmuP5n6Z/LvOty/b4s3zSXi6/eH/evHsu7NsG2gqky67aM7aZrNp1U/GvX3b4zzyrBY5m1lRVuroac6YTj9JOC4NWAMGseXTwOvdpP1X8x0LQeQ76/6O+b9bFPLQQdcm2MjQCBYQoIAIdZl22PSgC4bXH9LQUEgNYCAQKjE6j6pXN9glnvkitzYuym0KPo8dCjHv3wyAsa2woXikLIPLesgy7e/Yefyw168r7Ep3YufOctBw94SO93S5nY8j83LbT0P4T2rFz/itOOi9euBXvp3YSXvu9ThzRTJljbtF42BRKbHpNevr8vDWY9sM063ThdVzWYajssKdteum49zE01/P0Ln3MwhEu7QVdPsC3bdpbp2U/eV/h497nPfnwsw8dN66juexer/CVY9Dmr0tYUrm1S+7yTq6fgYg4ECBDIEhAAWhdJQABoHfQlIADsS16/BAg0Eij7pXO9k7ydZOm6vPCgTF9Z7abQJP0XfDpNeflTtHOqSbhQ5/Hdd593RqwfbJHGmP68TGC56pv3aG2ZQqfdfv/07JPiymtu3XX4yPL+vMeINwVrRZ6bdkRu2om5vO/u+/4m89HndILyAwe+Xvis04jzDgFJ820acq+bV2lvUwC4Gvot+6jSdrpn3XzTwSzp+rQ2Ujq8+qhv1pqqe/Lysq0yn/O6cy7zGRjTNVWsljVvsrO5ik3VseW13VY7VcbuWgIEpi8gAJx+jcvMUABYRsk1XQgIALtQ1eZsBXxhGH7pi8KGqru01gOw5aOg6b10ZQ5tyFozVQOV5Rg+8fl74gX/5iO7ivC+1565E+blHVJx6XsP3VWXGqjqsClYLbsq1ncKroZmqf1nXfbB3ScN74l47/lnxtGHP2Ln8dD1nWmbQtHP/sV9Bx/dXQ+Pyt6XVefUVjoZ+Y0f+PQhuyjTTrc0xv133pP7uzT+9FMnLKkSZuYdvpH6rvKIa1HAWqb2RaH8D51xQlz14c/kNpUCwitf+dBp01kBZZkx1vnMzfXv+zpWVdZUmTWTd02dsWW11VY7TebiXgIEpikgAJxmXavOSgBYVcz1bQkIANuS1M6sBNoMbWYFN4DJFoUN6V1jWSFC2aEX7QxbtpMOx/iff3V/bgBVJ1yougMw7VL79R/+rvjBN//BIe+vK/NY7bpHUbBa5Ff02Oym9lcfH14P8rLqnQKj3z7/zI07H9Mj23k7I9f/fHWnZzJ93fOfGD961omH7HTb9I671fvT+PMCr02h7KbAYtM7/S564VN2laZMYLa8qUywU2Ytr48/BagnH3vkTqCbFYgu+09er3veE+Opi2uzPrtFY6wy36J1PNTfl6lBmbHXtap7X5kxLa9pq4+22qkydtcSIDAfAQHgfGq9aaYCQOugLwEBYF/y+h2tQNl3WNUJUUaLMrKBV3kHYN2pPbRj7ZrMU09Tm3k7x5oEkEVfXPPm/ZLv+PbY9M6/MgZ5uw935rr2OGxee+shYArG3nP+mfGUY47cCdPW30uX1876Z2/n3YTvumXn0eL0k9r94TMfn7mrbLkLMbWR5XL8Nz86cyflq55xXLz9o3dkPr5cdXdk1iOvRe+2K3pc+VmXX7PrEdrUzw0XPicz8M77e259l2WVNVfm8fe8x6LzAsKs3ZTr75Xb+SyuzX/VsyggLLP+h3xNm7vZmli1OY4s7yZjW22vrXaGvCaMjQCB/gQEgP3ZD6lnAeCQqjGvsQgA51Vvs20okPdl94pXnJL5HrCqj1E2HJ7bKwgsd8SUPZyjQtMHL/2Va2+Ly9YOrShqp+maWf+Svbo7KvX9wU9+IS561/6DYVj6s9V3/lXxWN1VlIKbvEeMn3zMY+L7f/WjRVPfeV/i8iCQ5cWrodFF7/of8dYb7yhsJ12w6pgVAJU5mCTrXYhZbaUwNw4c2PWux2WYW2d35OqhF0XB2ftu+Vzh3z9135+4DORWdzCuj2fTYSl1HmXOK/D6Lrai8HHZTlYAfNnLnhbLoLBsO6UW3pYvKtrZ1/bcmrZXNN4mfE3Htuy7rXaazMW9BAhMV0AAON3aVpmZALCKlmvbFBAAtqmprckLbDrp9fy339z4McrJAw58gmW+nJa5ZnWa6eTay9//qUMCtzyGtnaNLse4ujsqZVTpZ7kLbn0MKTDb9E689euzdmQt33m3Gt6lECwvHMxyyHoUeOly9U13lgpUl9en9lPfeQd1lFmOF73wSfG9pxx7cJdcld2EyxAy7Y580RUfybRPgefKWSE7Q1od/8du/9LOn+W9327n4JV33bLr3Yjr4WVqY/0dimXXW5lAJOtz0fVOqjLtZ409a+dj17vTyqy1qteUGXMZoy76rdpmW9eXMSnTV1vtlOnLNQQIzEtAADiveufNVgBoHfQlIADsS16/oxTY9EV40w6ZridbNZTqejx12+9zHmW+8JW5JmvuaV4pyDnv7Tcf8hjmetj18lOPjV/4vlPq8h1yX9XHTl/7nJPilz50264QO+s04LzPQdpt+Ia1gy/SLqusXXNVJ5nembgesme1sTcifvjZj49vOeIRBw/a2HQgS5lxLHe8pUM81ne0pWD10pedHBe/a3/mDsCsd/8t31t37Dc+ateaSOO56AVPinPPOjHSDtI3vP/TO4+RZ+0CzKtxmu9zn/qt8YH9f3bII8mp7eUhNUW7Cldd6oZIZYLDMv5515Rpv8rY+/z7p6pDmbmnNstet6n/LJdNVn07ttV/W+1Ura3rCRCYtoAAcNr1LTs7AWBZKde1LSAAbFtUe5MX2BQC9fGFoW4oNbRC1ZlHnnfZOiyvyzvwYfV9fG18kV6dYxfvACwT2uTVPe+R2GVIuRoYFR02svoet6Xxx++8Z+NOyE3vCUxWV+Y8Zr86nzTWvXv37HrXXbom75CRsp+DNP+8R/1TG6s7LDcGhhHxntc+9F7DTY7J69K1x8fXd+zl3f/yU7893nnT5w6Z2nJH4O1f/Erc81dfiyMf9fDcXYXrJk3Wfp3PddmapOuK2m8y9v+fvTeP0qo608XfsmOcRQUFGQSkIqUWSvWNgDJ0C51EyjjAb62rYH7pRMTunwr2tVdHBnv1cC3QrNV2A5p1O6gZWqDtey/gQGGGwm6pEsGkC61CiwQEAoXQgoIDxhjht55T3/7c3/72eM75xnrPP0p9e3j3s/c5Z+/nPO/7hthR7LIhxKYLI5vtoXVDyxcbN+6PEWAEGIFSI8AEYKlnoDz6ZwKwPOahN1rBBGBvnHUec2IEfAmmxB05GqiWw22ccZgOmr4HULmcifyS48iFHLht0ybWjsktNWkMQPSdVRyubM9zDbXZ5krWIQioQx9+QjcsbctJcKJzJ1Xn4q5rR9ChD39LKzfvyzED+P941pi8bMSiEH6/Z3ItPbphh9GFWRc/MO37DyrEe1a2G20QRKVw13Vl3zWte6guTS7DamxDVZEI91bkOtG5eqvzG6IC9L2vdJgX+nnpaj+J7WmvobTaC31mujAyzVtIDMdQm9LCopTtxMG1lPaG9l3t4wvFg8szAmkgwARgGihWfhtMAFb+HFbqCJgArNSZY7sZASLyCf5fCUCFkms24uSGZW05CjAdMaWrr+Kk1gs93MrqwiPHPqXaC87MybYa2p7vPKrEJuqBDHLFAMR4vwMX3vVdVtJQTk4hbDK5p+oyz5rGocYg9B2vKOdS+NnUgb59zZ1iJyHRTl7ykUUteXiCKNw0f3K0HnTklCnTMObwFSVr731Pb6XV7d3ZIUz8Uj/a+OtDvkPKxhuELa4rDTIgjTZcdprILFOG4TjtlUOdQhOboc/l0PICw1KtiaRzWGj8k9qXtH61jy8pPlyfEYiLABOAcZGrrnpMAFbXfFbSaJgArKTZYlsZAQmBKPj/2s48d0ffwP7lBGYoGWY6aF4/agCt6ziQNzRVVWeqLxRSJmWU74FILmcjyXzb850rHY6yKu37/7GTHm/drW1uQWMd3TlphJFUFpVUtST+/fzcHpdW+Vqw5nVa6ZmxV16zGMMzW7upaV2X77Cz5WwkIH6bM6WWvqfEOQzpBPEFj1sq6LAwZd+Vk4uoBIgpezTGsHj6KEIsQpBZOtd1zPfx4yciFaDvlYbq1NUXxrj8pbfoydZdESEaoj50tR3390olnuTxFnIMoc/l0PIYR9rPwLhrIbRenLGG9lHK8tU+vlJiy30zAkwA8hoAAkwA8jooFQJMAJYKee6XEUiAgEnBBve/pmmjCIkXKu0KOQiaiC4d8SGrrQQmNgWhTq0XcuC2qQt1qkJXlteQebQpcJ56ZQ81a8hR0b4ggXzUkapNKoGEzMdq/DrTOECaLVLWbBwb0P5tY4fQ06/uy0lkIveLvq4deT692PVODpGnIw5dikLTeISSsn5Qn0j1icukhAxJ7CH6wxhqanriHJpc10PWDEjNR29r8I4H6Nu2TEwhEUq5fawIed74jrkay4XiFFK+kkmmuGrHSlkj1T6+SpkHtrM6EWACsDrnNXRUTACGIsbl00KACcC0kOR2GIEiImDanCNGWeOogVZLQhQjIWXTGH5IfyCZFq/vymY5veWqwbRCozgDKdQ07Yo880IOqq6xyXZDmTVz+WZjFUGWuTK8uvrE7ypepgP1D2+/ir7x+BZrk0IBiEI6BaOtMjII/4+vjIyKwIZxi1qMcfLkdkzqwTg2oA7m+rZxQwmJLuZ4xj/EBmzR9PpIUfeD1t0RMQhiDvEKl7bs8JkGYxldRmK1sG9ij0SGWCrXIGZgyoq8nGQ3lpiEMKsY6kN5+FifUUZuZX24lNMhz6akc1XMvnxsDbXHt3wlk0yVTF76znlI/EefNrkMI8AI9CDABCCvBCDABCCvg1IhwARgqZDnfhmBBAjEPXyEkF4hZRMMxbuqqih6YG1npPSC2+79U0fS4HNPo7tWtOe1ZyNFfQ+qNiNVnO5HHL0XtmtVaIJkeKa925nhVdenCQNZSaabtw8++dTpUqtTJ7a8eZAWru7MVctlCCPVPhCINzcM8nbf1Sn/1DYFWfOzNw7SGiWrrWlOoPhsurk++nnBmg4vIhJlZeUeXGvbdhxyYoZ6Pio82DTvupHRbk/n2ow1es7pX8wqBtWDt+smsSVv8bFPtO8iwVx24PcQ9abq+l3oGH0y6a4bi4mMLOazsJh9meYzjedi3LWSxhr06TtpGWAUubS37Y7UuOXg0p50TGr9cliLaY+J22MEygEBJgDLYRZKbwMTgKWfg95qAROAvXXmedwVj0Do5jyENAwpawMyrYOkS1GEw5cuc6ouaYKwNw3bTDghmcZ3NSQgEjTMb6wzZngVceFgo0qGuDAACfTc3PFRLD51bG+8fZQal7Q617xMgJjiGH57/DBavnFXXltQkkHxhvhurguKQSj1XIknQpWIol8Qbs/NGU+r/3MfPb5RH/NQZyPWkY3AleuI2IrD+p1BNy5rM7ody+SaTlUou/QKEgF1BMHtwlKsfZ3qUfwGt/Z1r+/XKmTV9pMq8kyqLt04hOo09FnmwkT3u8st3UQ8pfUs9LG5mH2Z7CnGXMh9F7s/n3mQy+jeE+qz+PYJw2n2pIudz7PQvsuhfBrvyXIYB9vACJQTAkwAltNslM4WJgBLh31v75kJwN6+Anj8FY1AyOY8xN0qpGzoQTLEZrTtqygSWWRFrDEQNCBzRCw2mWxK69BpwwkqshuWttFn8K+ULp9EEiiOzL2CEELSBx9VmKyqU3FWs8WqMe5UAlHtT7jr9jvzFG8XX93akEkpESNPp/xyzTvsAbIKvInvZx/FnDwvsL2z+6iW8FWNEe628t/VeRBEFMqYkqGYktXkEhM9ylgkdhH30dimFmdyENmdW9QLUebp5s0UTxH3LNZAoV0NXW7pNvVWGs9C30VZzL50NpWKgAx9J/jimbSc7j2hexZXimoxKR5cnxFgBNJBgAnAdHCs9FaYAKz0Gaxc+5kArNy5Y8sZgSAEQg53ugOzTU2nGuKjjPN1mfJRFMm2icPktu6jWVdcua8QHMS4RJsg9eQkIaa2oEb8SecBWpIwhhz6h+1LZ4zWujebCDZZxSaPHUpAuLaOr+1Hr+89mqcyE2Uv6nu6No6hUIe51FTCLigaQdAJNSTav/HKgfTsa/sjxRzmDZdMdooENr7zjvY9RIde94rNlRYNwN6mafU05dL+JCe2ANl8z7U9RJtpzn2IRRm3m0YPiv6pI8ewvkzJatTYmA/eXB8lBXKRYDJAoco8eV1BgaoSJ1DEPry+K0cdKkgTU8xMlxIxhDQyrSXMyaMz7QlQ4jwvvBabplAx+0L3KoalJiDj4qYbS5K2RHu6e8/0LHat16T2cH1GgBGoHgSYAKyeuUwyEiYAk6DHdZMgwARgEvS4LiNQYQj4Kt+SEoCmg6RKsPgoJ1xKMEHMvLJgStYFy3aQthEOUCPZXG/FdMukmprMAwTX2q3dzthzghDyyTaLGHFzV23NcTOVyTN1Gapkk3BX/fKw86KiYoyHPvwkzx1ZKPRUt1aVLJHHjfZPnDiRM2ZdfDcQqDZ3WbWOj+oRma//eOT51NL1TqK7UcQA1Lluyw2Lcg9lEtConZrmc+zw82jzrne9bdS5A7tI8zjrXmeQUIOqc6W7X1Vl6fSGQfTILaPzyCXTsycO6eX7HBNjMz1D5MQ3tokJ7c97kjUFi9VXNanbCoGZLdGW+iz2eY8lWRNclxFgBKoLASYAq2s+446GCcC4yHG9pAgwAZgUQa7PCFQYAj7KmaRKEN2B26SA8lFOyAc8WzuCwDty7HdaxZzN5VCnmrO53qrx4mDXnMm19OiGHc44eCCtnps7IVJxHT9xwpqhV5AxsmJPEEFXDOmTR+C5EkJguQrFnSmen3Cn1iXRUNWUIBNB7C1u7qKNvz6UvRsEESTfHj6qPjkhRqSyW9PhxBN17l7RHlsJ2Fjfn+6Z8qUofqJK6H7rmqH0ROvunLZD1Hxi/C51oe4xIrsDm9yk5b/b7ludqy3WIdSTWA/qBfWmLmGJfL+27nhHu3YXT+9RSaoxHk3PnhACJw5hiLGpz5D5U+todsY92ucRrqocferELWNSHPu253rG2zDEPSfiT7oIZ197Clku7npw2VRNGLnGyr8zAoxAcRFgArC4eJdrb0wAluvMVL9dTABW/xzzCBmBHARch0MUTuNQ5ZMdN0Q5IR+Kdeo0kG+PvbizJzOwQ5Gmc1FUlV8+rrcqEeRLDMmx+nxIMTXmHMgcQa74jMV0CwAn+OjKiTtk0unqRS1a8k2eN/SvI+l0c+tSc0aJRGpqoqyaIpsvSFg526ZuLLeNHUJ7Dh2j1p2HY9/tgOLm0YNy3JOvqx9AP+k8mBfHMXYnmoouYjAkMy2wGreoJYfQwwZz3b0TInJTmyH6t5/mZaQGFvOmwm13e878gzBclnGZBVE0b3WHEYpQ8sj1XBK/28j9a0b0s06Nqw9T5RCCMq21YYvnaOvDZSswMMWWFGstLk5pjT2knaQfq+JiWUkYheDJZRkBRqDwCDABWHiMK6EHJgArYZaq00YmAKtzXnlUjECEgHpIcR0OZdhCyprgTtK/rk3Rnhzfz9R3lF01k5VWR0bItpncgqEsu2dlu9OdV7ZBl+RDzvQqygqCbMUre7Rx43TJIUyx31ScVbdM2+0wc+wQ+tfNe+k4EYHgaZo2KooZ5yImTWpKuS8dedVDGHZqSTV1zCK24zPt3bSouStY4efjXl3KR0XWnbi5K8Jfdwk3VXmOUc4UG/DrS1vz1qs8rzriQlY9yjYAP5CyUAjKLuc25aBcP4Tg9yViXOR+2vOZxseQUJtMRPnCRrtq0WWrLat2WnMVOtak5V1jTqP9kCQ4Sfvj+owAI1D9CDABWP1z7DNCJgB9UOIyhUCACcBCoMptMgJlgICszMKBfd7UumxSDJWEUl31xO+FUDnEbVMlJO+6dkTkbqtzXxT2y+6ktjH+Yve7NGdle54SDoSbjlAxTa/IPCzHhwNxMmvCcFq+cVdeNbhKggyzjUGuZMr+KpcBvqoKzGSv2HwID1ChTISSLMJk1dZIjadergQOKG9zX4U7pYqriayb3jCQVrfvL4M7Kh0TBEEsSLktu96l1e3dxsaxpuYhicYL2yN1K3A1uW6b3Hbl+TDdB9GcLGnNIyLR/4M3X04PrN2mXQsuVFwu/q7ngY7gUcl9uO9fPqhPlFHYND6XnabfC6kwC+0Ta+fR28xJS0JdwOX3gEgWExenUtZL42NVKe2vtr5d93S1jZfHwwiEIsAEYChi1VmeCcDqnNdKGBUTgJUwS2wjIxCIgI4EMhEsrgN6YNcFKa4jAVzqLvy+eeHniUF0hqlxwVBGzkhryoZrGuTsicNp4fWXRcpLEGi4ROINXUIL1xhsYJoUO80d+40ZgzMev1YlnUyuyAowHVlgUioJ913U0cUTA9n02IYdtL7zQFZddvNoPdHn61atwyoJvgVZyFDUUU/cPZE52CdTdF5Sl8zEyOQsyvx41hj61pOv5iSLkcdhu9dtis8pdfGSrMCm5+f2uB+77j8RU1Ml8mzJGM45/YvU2X00J8t02kRWoRVmOlzQ59WLNhhdz03u1TZbTSpnkMbIOJ02cVqo+8fULpNOxUZc3x+TseUxD2xFeSPABGB5z0+xrGMCsFhIh/czlIjmEtH1RDSEiD4hop1E9G9E9BgRHQtvMlvjdCK6joi+gjMiEdUS0ZlE9D4R/YqIfkJE/4uIDiTow1WVCUAXQvw7I1CBCJhIIJVIqBS3L5c7qmmKmjOxz0yHbJWUk7Pl4kDccxDXx8FT24Sia5OUiVj9PVJkru0MUlGJ+QpJoGKae5A4f/m1kXTDsrYgGzAOuAl/Y9zQKGkJVFa4hFucnDQAdk6tH0B3T66lfmeeonVT/aNL+mkz9gI/kK+y3rDUBN6Xzj+Tfv3Oh7GfAA1DzqHX9h0xKjx9xmeae8znv29/J0+1+tXL+1NzR/62QbhTC6JHJUxMa93HRhtAJmLPRB6jLTXRjM7d+eX5k6NuTb+lSWiVgtSAWzbc3k2X6dmdZrbl2AufK/ZKBEpBlvdKoHnQFY8AE4AVP4WpDIAJwFRgTL2RG4joKSI629AySDoQgzti9HwFEbVlCD9bdZCBszOEY4xunFWYAHRC1FOAvy57AsXFygIBEwmEZAlPv7ov60qYtlomjcHr7jUbWWDrE+qW2RNHaIv4uvY1rXtD676L2Gh4ecuKQcTOM10Ygynen4nkeXTmaDrvjFOiLLsqcWciAEwuwCKBw10r2oOnSSSSAAEox1+Uk5NEiTpad0WElM1N1da5SjaNHX4e/WLPe8GEZfAADRV08RxD2gbmWCWfndCk2fVoCNXnN9ZlFW5qlUzzyOOSvUxrCWUXT++J72jKiIu/6zI/e5jqVUQm9lykvppoRqck9b2HvYxzFCrFHmD5Sztp8fouI4FsUnSabC0FkZkG9mobpZiLQoyj2tos5v1YbdjxeHoXAkwA9q75No2WCcDyWwcNGYLuNCLC5//FRPQiEdCOKFYAACAASURBVOHft2ZIOVgNEhDqvQ8ChzCBiDZm6oAIfJ6IfkFESGF4PhFNJ6I74CWEGPZEBDJyfWAfPsWZAPRAqVo2zR5D5SJVgoCOBBIKIAyxXIOa2+61nKyYmiy/uqkLVQDKLotwU23bcYguvfBs+tMnX80hoUQ5qNx8sHQF37/xygu1ce5ETD6MTSZm5CzCunGbSMsFjSNpcfP24GQaPTRWrjpP9Iu4hD+adVWe62lEfmUy+ia9rXzcgKfW96dL+p+lTaii9q/GPkxin49tcduHInXT/MkElWWIetQ0VyDVENdSzaIN++ZOqaX7vjIy+tjV8uZB79iUmP8oY3AmRqFLMYjyz80dr1WIqjjJBJfvhwEbMe5zr5YbuSTCCajxOOOqt4sxvkL2wfuxuE+TwtdjBWDhMeYeqgMBJgCrYx6TjoIJwKQIpl//P4hoEhH9PvPfTUoXf0VE38387e+I6G8DTbiGiO4lItR9w1D3JiJakzl3we34S4bzV2DXOcWZAHSgxxuaJMuL65YSAdnlVMRksynUSmkr+va51+SDpex6isPwqEF9qH3vkewwpjcMokduGZ03LFMboqCuLbhydnQfjaWcdLk6fieT4EGXbAM26Yg0l7txiOtyGvNuUsrJZBAUkzGFcEbyUdgOEm7+1DpC8hUoEIt1Ya38t6Hn0OZd7xWsSxFX0hbbUe1cF7tRlLElChEZh13qPLk/mTgEwQa1qo5glOvAvjsmDqcLzjolLzGRfB/CzVe44qvknbiPfWIA5nw8qKmh+6eOpDsn9SiDbc+UuArpNAmwkHEWbBFaGlbHGkLQheLk844oBQbc5+cIhMw/48YI9FYEmADsrTOfO24mAMtrHYxB7PiMSf9MRH+uMQ/nnU4iupSIcOK8gIg+LcAw/g8R/T+Zdv8bEf1nyn0wAegAlF0a0ltxoZv99HruvS2VEvPQvuPca2ofQrU3vrafNvGA7nByxZA+dMPSNqeb5lN3jKGTamqCM42axiWC75uC87tWrSt5i5wF2tVWufxuU4+ZfgP5hwzX380o0IoxFrjSY40d/fhTWri6My9zbpo2iGQ2aNM3HiXK6rIng7D84e1X0Tce36I1Eeq8TQv0sfVMY9Kp9GQ3cRsWmDskfznti39Aq7bszbq6ygpX3T2LNoVLMGy+e/IIGndxX+29aSLgFzbW0Vmnnvx5OxpVcRyVXZoEiNqWmu049Bkr5kLUA1kr4nrGiZmos08oQUVfobEKbeslzjsizXuxXNqKO+/Fsr/c7SsWDtwPI2BCgAlAXhtAgAnA8loHixB2J2PSOIkMVK2cl3ENxt+/RkQ/LcAw7iaiRzPt/nci+t8p98EEoANQ/uKczopL81CUjkWV0UqlbqTjzHeh7zVT+0tnjDZmzZVXiS2eoG01od9xi1py4njJCRlcaj2Tuk7n3qyulxDVWDncEbYsxWOHnUubd+cr7aBuvX38MG2cxgm151Hrjp5szGld6G9eRrX5ewSALML1vdsaomzSiLP4+MZdThduk/s1SK/dhz+iFZv3Gq0WxPTa9m5rEgo0YIvTB2Vr/aA+UZbeh5q7gkhS4fqMPvIS9RhcyzG22RlVnzy4VVv20PzV+F6be+G+qjmpxhlf0kW0y63anmEo5+OCLNpzPQ/jPGPRti4cgSmrsOu5ps6Nb7Ii3dhcqmbY4sKkCLdiQbvwed/HnfeCGs6NMwKMQBACTAAGwVW1hZkALK+pfYmIJhLRR0R0TsYNWGfh1UT0cuaHvyeivynAMO4jon/ItAsl4OqU+2AC0ANQ3nB5gGQpUk6bdp8NdrLRple7Utdd6HwXwgVPNwsm9QjUXDZCRLRliyfoOijbCEBd4gVxkMbB/JarBmvtAynUOGpgtmvdepl86QV5BEp6K7R4LWGTBExM7r0gjI4fP5FHjKUdny8NteEdE4bRD17e4ySeZHTl5D3i78Bk8Lmn0t73fps3EdMaBtKa9v15f0c7stLONIM+SVxklZ7tng+NXyhsAvGGa+Zy4ZBhX29qlmOUvmvFL7UZkX1XriA4Ud6HvDM9Y+DG/YO23UEhBGxqN2TijpP92KSGxPhC1Y4m+6DIlJPe6Nq14bTw+sus01Op70XXmvMZV+i71dWn671lcrvH+oujGE1iD9dlBKoJASYAq2k244+FCcD42BWi5jtE1I+IXiOi/ABSn/d4LhEJaQGUeVDopX09Q0Q3ZhrFrujNlDtgAtAT0EoijjyHVLRi5eK247PBLhoojo6KudFPe8wh820irXwO28Ju33sT7sGNS1rzhqsjiUYNPJs69iMJe88l4gn69iV3YnMBRoKRbz6xJS/L55S682nWxIsjl8Zf7H5Xq1C8d0ot3TZuaDZGmokQkGMlpj3XcntJYvylYZcr+UTSPrBOfjxrDL359vvUtK5L2xxUTNAE2oSBmLczT/kCPfTCdi8SEP1ibCGxDU1YhGDk06+I/2dSmoKknrtqa0R8hVw2BaCN1BXqRZATj/xsOy1t2RHSbUQyC6yFKg4N6DIQ6xo2KdvUZDg+ZJvtHWAKG+BSK7piO7rqy2M22Qflp3DHF+rc2ZMuziGMTKpnMe8ucinOczhoIRS5sO/7PuTdmmQILrf7OIrRJPZwXUag2hBgArDaZjTeeJgAjIdbIWqdSkQfZxpeR0Rfd3SCDMFnENErCM+TskFXEtEvM5mAO4joihjtg+CzXQOI6FUU2Lt3Lw0e7CoewwKu0usR8N3cFhKocrAhZHzF2ugX4iDli7VvORtuIaSu6/Ar94ODMOJjIQuwiCcox9TDS3vG2CH0F39yiVMJYVPd2MYmYg7Cjq8vbdWSSuIgdlHf07VKKXGgF/N8/MQJLeFos8NHRRdCLIXcB2mV9RmDq6/GUQPop9sOasksEBfLZoyO3HQjxduaDithZ3N1Vu0oJbajBp1Nb+x/3zoWkNX/vv0dbRlfda06ZpH4BH9X7/FvG9y9RRu4JxArb3Gg2zHqg9D8xrihWbUf/mZT2umen772+pBtpudb3GdnmgpA3dyIpCnoB+7qT7buitaFjjAyZSr3wcV1r1ba777v+7jzHoJHmiR2SL9clhHoTQgwAdibZts8ViYAy2cdnI8wIxlzniaiWx2mHcwkAEGAmVEpDuMUIoJU5cuZNqECfC5G+96f3ZkAjIEuV/FGIISo8W40oKDvBjugyYIWLcZGP805UQ/CPm0nmRP0B2XcnFVbc1RUNgWJLxGnU+egrurGiwUgu0HaFoQu7pZrAYnYf+jjkv5nUtcBfG/Kv6A6e3BaPT2wdlsOFvI4xPwcOfY7r3iHopeIqEL6ecObBL+jwHHJLLGh8X75uIBI+DvwuXtyLT3asiMoDp3oFuOZM6WWvvfiTi35J5MbwPmh5jdpzdb9sTMeJxxu6tUxxzPG+LkOq51jDUNSFyIAlGPBiXUrJ6tAkyopl9evpU/M5+S686mlC84euRfUmWMv7huR/0iOYbpfQFL95vAxozJQfh7q7PVRAArLTImNfJ6xog3ZHp0iOImiS0eC+ry/IhXg4g3GZ1bqC7mMG/TBS5gfMu9xhhz6oeyaEXCY4osRYARCEGACMASt6i3LBGD5zO0QIvpNxpx/IaJvOkxDWdTZSUS1KQ5jORHdkWnvR0T0rZhte5/BmACMiTBX80agEGoz385DNti+bRa6nM9GPy6maeJhU6nYXHnj2uAi064fNYD+5sbLtco8V10QFrMmDifVZc2WTCPEbW3FK3toSaBbYpx1ZsqiaoqVp+sDWWTXbt1vJG9syTfi2FzIOnFVdKj3L3eY3X5ll9PlL+2kpma9a3AaY4s7BtF3kvogiL562QXU3IlvnoW7QP41TRtFt465iIDn4vVd0foTa23aHw6KiLlX3jpMj27YEf1mSpKjxqKD1WOHn0vLZv4hHfrwE204APTzmcRW6ly6gcWzc8bTjcvacghhG6l339NbaXV7dxY4EVIAf7A9w13vAJ/nvy3MQkgWYJ++xAB9P+7ItpnchX1WW4htantJ6vrY5lvGNddyO4W0mRWAvjPG5RiB+AgwARgfu2qqyQRg+cxmOSgAkYEYmYhxwT332kxCkjgouXx62QU4Dqpcp2AIFHJjG7LBLtgAAxtOcji0deUKMO8bg89E4uGAjIO6KVi4GNe27qP08AvbjcHx1fH7qvhwmGy6uT4iEnQHvkg9uLI9z21RTr4h3NlQ35VNV3VbM82bq53A5WEsLlRUKOBSSyXp86ph59Krmsy8Sdosl7pYQzddOZCefW2/MYbd3CkjqG7A2dR14IPgeHOh49QRWqFtJClfjBiPSF7yj7c00Pdf2unMQIyxAJM/HtkvT82Hubv1qsH0r6/uiwg9kIT3TKml+74yMguBSsqZsIniAiKxxfETWVdWl8u93JbtQ4esxlNVeHE/kPj27YqzJ7cT+u6EavGGpW3OZCDoA+N0uQvb1m2obUnGleT+8albyP2PT/+iDMcADEGLyzIC4QgwARiOWTXWYAKwfGa11DEA/4yI/lcGDkgJkI34UAHh4SQgBQSXmw5DIMlG3renctlg+9prKpf0cGiqLwdw93ELMxGJJiIN41HnGX3WD+qTRxbmqENqauj+qT3lfLOCutzsXGpA1YVW5wIckRBS/Dccqm3rGLib2hFznUSpJa8XkJKhLr9J12W11IdSbM6ULwXHSyz0+NNaG2mvNd9xCxIRxN1xOqF1k4Yb7qMbduaQR77tZ8cF13UoB2uIbp+Qr+gV5ZAoRCgJbX0gmck5p38x+4yyEVxoR/6AYnpG6hKkyM8cXxWdze402gh91+ieq7Z3SWj78nhLVTd0PVZied1eqVr2T5U4H2xzdSHABGB1zWfc0TABGBe5wtQrVRbgGUT0FMJKEdEeIppARPsKM8Rsq0wAFhhgbt4PgSQbeb8eqqtUGge7KKnF2s5I2QISa951I7NqPIGWi0TzUeSpRJotqL7o19QuyIHHDLHYdDPsCiivO8irJBpUjDjQd3YfpYcyLokygQJSA16DGKdMoJowBO7z13RkyQ85Zh6I0z8eeT5t0MQn043PlNxC2PLw+i7v7LFIcvGlC84siotyud+NmNMaJbZhudscYl/DkD702r6jQbH5Qto3rVURLxLE3DW1/Wjjr/O/b6ZNcpqeYT7PLoxDra8juEBo4gPF2aeenBcXcPKlF2gTiSydMVobj1NO3OPzrLTNSxrv1ZB3ja4/PKOenzuBLruwj9bUkPbVBkpVN+m9wPUZAUagdyPABGDvnn/5DMFIlA8CL2WUdx8R0TlE9HuDacj6+3Lmt78nor9JMAQk+fi/2GsS0duZ/hFXsNAXE4CFRpjb90IgyUbeq4MqK5TGwU7OaiuUMss37spDykWiyUSiiZASbZjmWY6lBgNsysLr6gdQc8cB54y6yEtbP+Lgj2yisosy/j3o3NPo6MefRv0/sKYzh2BzjR91MHdq8HtdMg3XAG2Eo2y3qx3xO2xomlZP81cjp1X8K20CJ74llVuz0O62aWRFljewPsGG1XWhxtuTZyvt8eueYT7JDnzccoXdGM+JEydySFXxDNK5+pqIwZfnT87GL01DFZ+0jZB3TZz3eEj76h1dqrqlerKwAq9wyDO2hcOWW85HgAlAXhVAgBWA5bUOEH8PcfhwjSOizQbz5hHR4sxvXyOin8YcxhQiWkdEyPx7mIj+iIi2xWwrtBoTgKGIcfmCIJBkI18Qg4rQaJINZ9K4STq8QQJSJtaVGL4PiYZg/Yuau6Jssbqsny4FoNyXiLsXkWSLNmjdAE2x0GD+SZkg/kKRc+ekEdaZNKmAgMX9U+vou5n4hLKNiG+4+9BHtP3AB95quQWNdSRs8SEeVKMxNrQhyEjYd+uYITS+th8N63dGFG9RDugPxaKvq7Tc14LGkbSoeXsRVj93YUNgbkbpKiekSAuxNMk1rMupo9yEfKFI4Sg5yeX9rR8EQHY+OrOBvjzsvJzEQLZnDLDWPUPi3Luyok+Nreoi52Aj4pXiUu23rQe1Hsr6xnXVteuyU9SJ+x73bT+JbbKNAgtbDMa07re02kmCUVo2VGs7jG21zmz5josJwPKdm2JaxgRgMdF29zVGIv3+mYj+XFMF51zIJC4loiNEdAER9UhCwq5rMsThGUT0PhFNJqJfhjWRqDQTgIng48ppItCbNmFJxppG5kTTQXb2xOH0g7bdxqQc6nzrgvXrgubLyThssfdkstA3EYBs021jh9CqLXuzLrlyIg+5nEy+4hC4YE1HVrkjyLbLDfEG45AZ8rjgdty4pDXo1lnYWEezJ43IBsx/onVX1l4546/tIB7UYQqFYdecybW0LJOt1dQk8Ly5YSCtad+fQq/V0QTiw7XtOEQrNu9NfUCzJgyjH7TupuMptexSE2Lt6xSpcZOaiPsP/c6fWkem+1Qdni4OnesZo34A8XUbFn37fEAxfQiK+46IQgys7og+yODSPR/iTL3JTvXvcd9PST+I+RCctozIpoRVcbBKu05cYjVtO6qxPca2Gme1/MfEBGD5z1ExLGQCsBgoh/Uh3IDh/juJiDYp1f+KiL6b+dvfEdHfKr//MRG9mPnbj4joW5ruR2fKwM0Y7sZQEbaFmZm4NBOAiSHkBtJEIMkhIE07CtlWkg2nVrl3Ug1tktzGfGy32YD6Pocpm4JGDZqv2oS6z2ztpqZ1yHWUe8mKmYea36TVnsSQr4JRF/tQKBiFJSJu1Y3L2owZYH1wlssAk8ZRA43uzab2oNhaPG1UlNFY5z6MeiLrr8jsCZLxH36yPS87aqjNScsvnl5PC1d3OskmxB9c33lAmxQiqQ22+iCMC0GyJbVZjguZtC21fhwCO64NwPe2cUOj+G9q1l3M+U86D3jHqNTZAIINilzf+1RHyEHBvFiJ7Sn3pYYncCUPwr34WSYmqOkDhAtP3fPZFUsPbaLe2KaWLPkn+oF7cug7wmUjfjeRlEkV6j59h5QRisg5q7ZGMW/F5UPQhvRTqLJxXKsLZUu1tcvYVtuMVsZ4mACsjHkqtJVMABYa4fD2GzJk3GlE9CERwS0YhB7+fSsR3Zlp8lfwzCCiD5QuXAQg/NIQPxDKQVz/g4h+7jDzv7C/Cx+KtQYTgCkDys0xAi4Ekmw4TXUn1vajf7ljrKvrnN/jKkxEI7Y4fa8smJLjbqczzEZCyq5ZuroqiYGD3LfHDyNXDEP06crCK/oDYff+x7/PBvW3KZ0m1Pal1h2I4GC+QAw0TRtFiP1lswH9IIOpHFdNHFRtrr2COFWJlqBFkWLhKJEG9SRIKccLOP941hj6xuNbytG8xDYVk+izGWuKVRnFvUxhfeA+bf/NEXpi4y4n0Yz+cJ+IxD5C9ZUliFa2awlJXSxA3Ivbuo9mwx8IDEBsfmPc0Lys5iETanq2QjWJOJ2yolput7ljvzaxiBj3NSP6RSShzwce0S4+JkCNinADciIP10ekpAlMQvCylXURtq4Yt0nsCMXa1FeSj4ZJ7O8NdRnb3jDL5TdGJgDLb05KYRETgKVA3d3nDZmsvGcbioL8ux5iGc3vLgIQisAfuE3IKaFTGgY2kVecCcCkCHJ9RiAQAZ2Ky1eJYFKAwYTme82ZFm0Hi5DDoNyOyR1OuKv6wKIjIa8Y0oduWNqmjf8n2oSiZdmM0dn4dzjI43IdOm0HZNVeodgTh7g9hz8yJshATAgfl0qhWLK5AJuIGyiRcAi/YVlbjooFdqP/5+9F4ngKdi/2madSlBkz/Fz6xa73vHCNY18U8tJz3uK0X4l1Rg/uQ68jO3DKxrvchON2B5IZax+KO/Rx+cCzqaMb0VT0l0pGqsTeIz/bTktbdFu6HpXtMiWWoMmdP86z2OfZijK2d4Xp+QZs8FEmNOad+jFhesMgeuQWOK+YEzWBUMOli0GaJtnmQ665XLZ937tx1mfSD2xqn2m3F2dM1VqHsa3WmS3fcTEBWL5zU0zLmAAsJtphfQ0lonszRB/Ist9lCL//TUSPEtExQ3NMAIbhzKUZgV6DADabcsy50BhNd634pTboPQii2RPtSS/SBjkn3lNNDd0/dWQ22YVvX/JBTo3HZ2tDd5h0beR9CUBxYBYutbAjcq9b1JLYTXVK3flO11xTfDQcWG+8ciCt3dqdp6zDb/3POoW6j/7WF/q8cr5EZuwOAipiY4RkGEsMhIyuKTkRTEBXXLRMEXC5QoeoHEHgzZv6eSIdMWSZBFq+cac2LIEMj0wamsqn8SxW3xOyDSYizaRwxn1UN+AsmqMoHG0EWOuOd7TqWEFuFkMBaCL5XM95gZUtaYsuJmRat0GhVGU+pGdaY+ht7TC2vW3GSzteJgBLi3+59M4EYLnMRO+zgxWAvW/OecQFRMC1idTG8Ksh2uThMivMLpTqJC4srjH7tutSa6iH8JcNcQ9t9vi6AIusvWpbaoB92HRvJmPr7z18XUFCoJjLKxaJGn748p48pR/6EyrC1/YeoYVrOr1dbHWuxTKmmSTQUXtQVsFIl52+cxu33B0Th9HjG3d7V8cY4Qr+RKt/He/GC1Bw7LBzafPu9wrQcvk36VIFYgnOb6yjmxsGEZJ1hKwDMXpZ5Yn+Zk0Ybg0T4JugRxBnhz78RKu4BeF231dGJp4E2KOqoV3x/OQYpxjzdfUD6KfbDhpjmZo+pMiJROSByOSmjYjzJel0IGVjCLbtjp6BMlkXQq6Zkrz4xFNMMnlJwnwk6ZfrMgKMQGUgwARgZcxToa1kArDQCHP7JgSYAOS1wQikhIDPgSetg4HNNSul4SRqxkUK6n63qTVU8s8nu6+s3pPrRwfkNR3W5AMg6m4aPYiefW1/XkZk2P5PP/8Vrdq8NyLIdGWh0hN1Rd84xF49oi9t/PUhJ7Yg4BAH0HTZ3OxsjbtIF7kuxvXgtHp6YE1nokQNzsFaCswcO5j+7dXuoEQsIaqwJLalUXfulBG0tGVnGk1VXBsgyb734k7r3ArF6zOv7c8jw3VJf3xAAIEmJ4KA2vZHs66ik2pqorh9f/vsNq3CWm1bEGezfrglT9GLNbh5oTsOqo+9cRTj4vl6zuknWxOk6BSAIB2/vrTV+GFBdW9GX7/Y/W40lC8POy8n9qvrPaAbv+n57IqDqhKZrg9KcdyR5fHAdlP4jBCS0mcNcBlGgBGoLgSYAKyu+Yw7GiYA4yLH9ZIiwARgUgS5flUj4HuA8d3w+5bzAdUUnN2nbkgZXwxEmy4i1JY5Uo3hJxI14HCOw+yRY58ag+u7+pXHLMa07vX93llgQRQ8N3c89TvzlLwkHsLON99+PxssXz6Ew27Yr4vfFzIXKCurj2wHddFuEkIMah9dpuZQm+OWRxbhGqrJJmKJ20651ksyN+U6Jl+7oJxFhmCRTOOh9V3eRLNIqIO+XGS+as/Y4efSL/cc0RKPuLduuWqw85kg7kFbyAJkQG6adkW2+9DnqKiIelcvasnBxjd2XagLbA/5BsJf//VBR2yGPHdda8OHtANJ64r1in5cYzcpyE02yuOUE9iYXInTxMWFW7n/Hnftl/u42D5GIC4CTADGRa666jEBWF3zWUmjYQKwkmaLbS0qAiEb+BBlX0i7RR2wprNQW10Ep+t39ZA1f2odzZ6UH9dQPVC42jXhqDtc2zDHwW/GmCFagkDEzzMdCH0Vjrb+RRZQlHlgbWeQMi50LWEcP7z9KvrmE1u0aqBiJNF46o4xkTLrn372K9rSS11lQ+etUspD5Yr7e/C5p0Umn33ayca1po5p5tghtChDrgl30Sdad3m5w+M+/fEdY7z7UvsW9yCyeatElFxWjiOaEyv1pBq6ffwwmj3pYmemdBuR5aNgi55vizfkKh4zCZR0aj3beMTY5H7jPndNa9SXtPN5L5nIREEemzIp62xzEZMmQpaJLyKfuaqUZxbbyQikhQATgGkhWdntMAFY2fNXydYzAVjJs8e2FwyB0INNnPJxs+8WbNBKw3GUJ6YDHJRcH37yezrzlC9oM+lCaQaXW7jtIm7Tw+u3RyoUHZmmO1Bc1Pd0bdZJuV1VkQclCfqzBdvXYe3jRqseCNH3kp//yqksspKPmUy/UCD6HNTRFtwd4UuMLKmhV+Moe+ww0Z7AAwfrOP2E2sXlqxMBl9u7iVzD33F/tbx5kBau7vTKYBxX2SrHjvMh9JFJHESb7n4VSUkuH9THqGoWY/NRvOlWhfpsw2HjjonDteSjz3jU51rIhy+fVWsi2kT8Rpk09SHXkhCvsr0+2PgQsj4YVFOZ0H1RNY2dx8II2BBgApDXBxBgApDXQakQYAKwVMhzv2WNQJyDTbV96W5a94Y1YL5uAnUbftXN0eT2iMPld64bSd99YXuOsk0+dJoOFM/OGW+MdSXiiKkx+UCOCSUOYljdtaI9b0gmW31cN8WBUA7KH3fRoz8kJoEa0ucwKsi/ppvroy4Xru3UJhSJa49Kxjw6s4foWP7SW9o1o/Yju9D5YJmGndxGegg0DOkTNda+92h6jQa2NHvicFp4/WU5CiMfch5lcN8/HpgoRs3WjmfRuEUtVtUhSL7bDYlH5OG6MtLGebfYVGu6/kzP7pMyMRN96/i6J5umO4e0q0FcwXPp1d3vRTi7cDK9k5J+bIurAAxc0lVXPM4+qupA4AEVBQGfDwJFMcSzEyYAPYGq8mJMAFb5BJfx8JgALOPJYdNKh0DcL9eVtgkxIaxzHYtIJSVjsW68OW68RFpFjhqIX9gh3GhVuwSZZjtQ/ObwsVhusRjTtwyZY2EPxHOhAjqBE8ahxu+Ku6rF4Reuh1cv2mCM02VSy4Cce7J1V6TS8yFKQuyE0umc078YxTn8+pJWpwprSt359JdfG0mr/3NfrOyuIbZx2epEQLjyfuvJVwvqCi/QwzPruTnjs3FI8XcXASiemUirLSce0c2IizgLfbe4PhTo+tMRjXje2Ai0OOSka0WKsb7y1mFa2rIjp7gLJ1fbcX/3l51P6QAAIABJREFUjQEYOk9x7amEenH3UZUwNraxfBAoxDOo0KNjArDQCFdG+0wAVsY8VaOVTABW46zymFJBoBI3FakM3BJAXahu0I8NH3EI2vzWYVqiHOBQFwkAzjz1C14JJnwUgCKgO/pd8coebZ9xsQFZhpe0zr3VpF4TOJlUlHFtEVisbe+mRc1d2mbU5ANyIREvTRCBce1Q6wlCN+NxHEyYpmUHt9O7EEibyHahJ/rDffjt8cO81K5oE8+Dx1t3WTN7o1yabqQu1ZqpvxACyxRWwYWjz+82hWWaOPnYIsrI2OBvKjHam/cMJhwZk5AVxmVDEahUkpkJwNCZrs7yTABW57xWwqiYAKyEWWIbS4ZAyGGoZEYWoGPT4RFuqHdOGhHF3PKJS4VMxY1LWvMsbL53gjabrloQL8fF00eRrEJB5k2RAEN1CUvD3VYHJxRu3Uc+9iIsRfB/tKMG4Bdt+7oG6mwRcQ2femVPnjoG5UHGbZo/OaqqHlAxHz6Zg0W/7J5bgJuLm6wKBELujblTaumxF3daVYCC3Nfdt3EBk8kXtY2kSjofYifJ+9OkYEQSlk0LJnslUImLW5x6vu/EOG2nXSfJvMSxpdj9xbGR61QmApXqZs4EYGWut7StZgIwbUS5PV8EmAD0RYrLMQK9DIHlL+2kJkVlJg6NIJZmLt+ch4hOmXHf01tpdXt3tuz0hkH0yC2jIxLR5UIHMg2ZQh/OxAWU3WBVcstEWsJV8Lr6AfTTNw7GdhVc2FhH47/Uj25Y2mZ0vZVJs3X3TohcBXUYoRyymH5j3NAgMk4GW+DQ0X1Em1gEiqMftO2OxivKov7CNZ1O+9VJDUnOUOpbJISUKbWt3H/vQcCkVBQhD0RmWiBi+rgRFy1BvnR2H83GV40TS0/uX/esxRiWZWKBiuRKScbi+ggVF49C1asUIsKHuC0URtwuI5A2ApVEvMtjZwIw7ZVQme0xAViZ81YNVjMBWA2zyGNgBAqAgO1Agwy6qgJQKM9w+FMvKM/adhyi8bX96LILexIIuGJUiTbUw7NJuWJrTyQYGXzuadpkHy74bG7AurooP29qXV5CE7ks8Pry0HNo8673rN2bCDiMCclPbljWlqMs0mX+xeHcJw6ZCweVYEO7iI+IAP3lcM2dMoKWtuwsB1PYhgQIFNq1V2y6i7lsoVxDZnP5uYb/x72De/bua0fQoxt25NxLNpWer6rK5bYq7PFtz/Xs9knm5Ls01Lh7+BiEREiFvkKwgC0oj0RSc1ZtzXkWJ1VZpj3OSiVL0saB26suBCqR1GYCsLrWYNzRMAEYFzmulxQBJgCTIsj1qx6BkMNASNlyAc5ks+uwgE3XgjUd2QMrXmTzMy7CPmPziVFlakenNHS1Jw5jz7R35ykbfewNLYP+7r9uJD20frtRdedSrIFge27uBHpsww5a13EgzwTgICc/CY1NFjomlBfkDP6LOGgn1dTQk227o4Ovazxx+uM6jEDaCKSxTkNJysZR/emFzoNZwu/48RNesTJ1zzr1wIvs6fWD+hA+zIgPMGq8T1MWXyipt3UfzVNZ3zrmIiPsrmetSnaKhuLE7iv2OzWUTPBNDpL2Go7TXqWoFOOMjev0bgSK/ZxIijYTgEkRrI76TABWxzxW4iiYAKzEWWObi4aAz2FAbDxCD1G6QRR7EyOPT8Slmz3p4uwh0pXoQ5fhFu6yviqN3P5zFTICH18FIMrbYl7hdxE/D0k0Hs4Qc0KxggP08RMn6NVd79IyRYkTd8HhwBtlxl3a6qWSywj1orLC/fmmhkHaTMKy4lJV+ehcq0MJi5Axw5Vx1sTh9NZ/fUgt298JqcplGYGKRABu9oL4LuQARNxV0YeNfMtx91/bmRdzUFak2Z6VIPCemzs+q9bWje/7L+00JiJC+ZDndiHxC2nb9dFLbcvHFTqk/7TLqvuJ0PGlbQ+3xwgwAj0IMAHIKwEIMAHI66BUCDABWCrkud+yR8Bns5xmkHUfsjEOaCEKP7QPYqnp5noSChBTfZOaQCTB0LkC6+wX7YMou3FZW06cPqGiU2MAutQpOncs0bfsDoy/fXnYeRHhqSo54K0X4iKoqorUw/a81R3W6RNuwyj0UHMXHcdc1BDdPmG4NtuonJFZJgcw9rtWtMdZKlyHEWAEPBCQE3bM/7+vU0tX4Uhvleh/Zmu3NRmRLgSAPCR8lNCFcFCHjefRommjsu8B+Xc8s13Z1huluKtJYw56TEmiIuIddOTY77TPTpNysZwVdab9RKH2GYkmgCszAr0MASYAe9mEG4bLBCCvg1IhwARgqZDnfq0IFFsJpzPGtbl3uUGhTV+XJx+yMc6SsW32XTHzXp6vz7QoE3ampBi+41bHZEsYoib9cOHhUgOivpxURI1paHIT1P1djXuFQ/itVw2OYh6CYMRlyggsj0MXmwwxAKGw+0xiI0EMblowJScTZpQBeU1HTjkXRvw7I8AIhCEg1K5CKY3n4ZimlrBGAkurrv6B1XOKIwO7LUGRXBgk4PNzJ+QoAX2eq+LZihil6Et2TU5ieyHqqip4NaapKw6j+t4oh7h/rv2ELiZvIbDlNhkBRkCPABOAvDKAABOAvA5KhQATgKVCnvs1IlAuX6hdm2hXEouQg4CLbPRZLjIxh0OXSVEniD0XgekTe+qrl/enZiU2ne+4de5JquuqS02INqB4wyWUfDJW+N2lmIG9S2eM9lLNCde4tl8fosXru3JcdeH2jIOVGq8PY5hlUPH5zCvK3DZ2CD396r5sVt9vXTOUPv70M7p6RF8674xTgtyMffvkcowAI2BGQA4dgPAPasb0McPOpSsG96HHW3cnghHPj6Zp9fRAlMHbrylbjEMRlqBxSatXY3jm3T+1J8ag7p1ia8T0IagcPvDBbt07ENiddFJN5D7to1xMa7+SJia2/YQaM/ZBSe3vtSC4ECPACCRGgAnAxBBWRQNMAFbFNFbkIJgArMhpq16jXaRbsUfuioGni7UGG30ODipRlURJoFNl+ARiN6nGdCSeaW7ukrJX+o5bh+vZp31BS8J977YGahw1MG/q0YbsVmtyWXMRnWh48fR6+uu123Lcj9UO1bEhBpaIIwhF3jUj+lHbzkPaWH/yoTLOGgYGIDihgvz757ZR14EP4zTDdRiBqkAAKrx7ptTS4Q8/oVWb90bu8qW84mbDntYwkNa077eaHidhCZ6FuNTs3OK5HjdMAHAPwVqNXwibXIRZmkSYa02YiDJ8cLn+ioHeykWdzSHjcO0zQtXvpnc1FJm6MBsmtb8LP/6dEWAE4iHABGA83KqtFhOA1TajlTMeJgArZ656haVpKOHSBsoWQ0+nWHt0Zg9Z4xsDT9jrOhiZxuVDcIm6JmJv+UtvZQPam0g829zAxcv3kGI6nPzPmy+n+as784apIwBNbnc611g0+MjPttPSlh3GpQGX3ZuuHEhrt3ZrCTyRPETOsKkStq51N3b4ubR513vZYvj3oHNOo9UeBMC6e3vc8Basfp1Wbtnr6op/ZwSqHgE5YU6lDjYOuec7Vjw3239zhJ5s3RUpB0VSISiVmzv2eymeffsylVPfN64PfPIHKTzLmwwxCEV/wpX10gvPjrKRh7oawx5dIis57mIcDELe5TZMNrz5X/TA2s6s8jtEraez4aK+p9PM5ZvzhhQ3ZEccbLgOI8AIcBIQXgM9CDAByCuhVAgwAVgq5LlfLQKuA0I5wVYIsjJENSCwcLkii2yMLnWeq++05sZkLw6s96xszyHgTC7Aq7bs0ZKFwEQ9zOAgtGBNhzMLL/D54e1X0Z8+8Sp9hgwgmUtHmrow161TXVZMX9dj2PDVy/pTc+eB2LdAIbMAxzYqoCI2Sk3TLqcFa7YF1OKijEDvQ0AmsGSlshzzVKdeR7xR6dHnBVx0gLHUk5/HJuJRJCYJCQGhxouFGa53nG5AC9e8Tis2539UiUuKhb4nbe/Duau25iXFClHr6cJsJPE08FoQXIgRYAScCLAC0AlRryjABGCvmOayHCQTgGU5Lb3bqJCv56VEKnSjn8RWGzlnUwAKUuvNt9+nuCoJ2e405saleBCJLGwKkH/82XZaYlD0Icg91HK4QtSRgjz0iZGEdk3u3yHzrCM9Q+qHlF3QOJIeat4e5MIX0n4xyhZSMVUM+7kPRiAJAr7rHy6sTdOu0D7/xAcNqMsWru2MYt3h48CcybV07HefZZXgIXbaPi6I57Er3ITJLVmnAIfyzxTD0DcGLcYX2ZTBQB6vTrloU7jL72eUC1HZmd6Hpo9DcYlJMb403uEha4PLMgKMQD4CTADyqgACTADyOigVAkwAlgp57teKgEuNVi7wqZvp71zXEyw91BXJNh6fDbsuBiAOMTdeOZCefW1/noogxJVItS2NudGNafKlF0RuxAg078ocaTsAygckm1JPd2idO6WWxl3c12lDGgQg5gcxma5f0kqesf0TLXuogq4Z0Zc2/vpQona4MiPACBQfAXwQua5+AK1Tki7pLBGkmUulLp7lnd1H6bsvbI/eE3ImcsT8u7bufPr37e84E5CYyEmh7tOFTMAzeN7UOrrT4pasIwCXb9xJTeu6jJPgQ5KZPg6pH55c71/dHkBgKQwUz3rTe830PiyUWi+Nd3jx7wDuEQjw3FXHOmACsDrmMekomABMiiDXj4sAE4BxkeN6VYlAnM2VqINMkA9nDlFxXJF0gIaoDIUdgkCzZWwMUUmkMdE6VyQ5e2+cWEd3rfhlXgZiHCifnzuB+p15SpZMvGFZW6RykS+RRMAUF9A0f2IcR479LlEMLdH+znc+pOUbd6UBsVcbvgoir8a4ECNQpQjU9T+Dug5+VDajg2su7l01qYfOQDlsAj6UqB8Y1LAKPirpGWMG0/sf/57Wdx7Q2tATQ/XCvHim4j1jUsXBfptbsikERBoKQJM7skw4ut6/pt/vv25kzl5A/hDnerfIHw9d5GPZLNCYhsTZb8XsqiqqVft6qIpJ8hwEE4CeQFV5MSYAq3yCy3h4TACW8eSwacVFIMnmynVQiDsSl4LD1q4rTp2PSiKu3XI9FVf1MATVpE4x4RPrCK7AIPFkek/OgInD1tUG1RsSe9hUJCpJKo8jbtZPEI9N0+upz2kn09mnnUzffGKL16E+zjyoSUfitMF1GAFGoDgImDL3hvY+vWEQzWusIzmxk9yGSqq53hNqXZWElJOxoG3EEMTzWCa6XCSjzi0ZpGLTzfV065iLtBDoYgCizu3jh9HsSRdbk3BFcWFXd+SFQ1CVei53Xp/EWLoPcSEf4MqRJEvDpiT7rdB7ohrKF2qPWQ3YVOIYmACsxFlL32YmANPHlFv0Q4AJQD+cuFSVI5B0c5WEqLNBm8QuV2xAH4LNZZsrLhJUfnNWtlvdx/6gpiYn6YboU7iOufpoefMgLVzdaYxtp3P1FQe9G5e15bhHq+MVJKkOyzgH9om1/WjTW4etfQobQBYej3HfTak7n/7yayMjFWQacQpjmMBVGAFGIACB6Q0D6U8u60/bD3xgjG2qNoeDw7SGgfTM1v05z9fouXTC/uyQP/64yLmAYURFQcItmzGavjzsvOjf4vktq7x1bYpM63IdZF23kU1yFuD/2P4OPbFxV/TMtMWPtYVvaBhyDnV0H81m3XV9nPJ5PxdqbxA6L2mVT4O488EtLXurpZ1qW0fVMi9xx8EEYFzkqqseE4DVNZ+VNBomACtpttjWgiGQdHNVyA1tkg338pd20uL1XTkqszTck1026WIShkwebJQPXzqbk/SxoLEn7pStDRwiH5zWo9bDddeK9rwhLJ5eTw+s2aYlMNXCPgdzHJ7vvnYEPbZhp1ebOkxnjh1CE2r70bB+Z8SKLxgnE2jI3HJZRoARyEVAfAQxJdMwue7HyeyNDwuP3tYQEXQg2HDJz8E4barzCYJRl0wJcV7xUeieFe3ajxvqc972npGJQfSvfuwAZuukhFDCRpPrr25Nwh7VnVeNn+t6F5rcleVkVeg7DVVdkvvKp/+09jlJ91tJxllOdX0wF/amhX05jb8328IEYG+e/c/HzgQgr4NSIcAEYKmQ537LCoE0Nleug0CSAes2ikL9ML62XzbrrdxHrstqDd09eUSU4MKUoMR3M+rCKg1Fyb1TaumxF3fmJS8RqkWM/YalbbFJMlkBI3B8Zedhaul6RztNOrWfzm3NNsd1A86krgMfGougj3sm1yYi/5KsMRCey2Y2RMTh4y+9lRfPK0nbXJcRqAQE0oyROazvabT78MepDBuq3he3v5NquACVbBPP/z2HP6L5qztj221SV8vPywVrOoxjwXPwx7PG0Psff0pzVm3Nid8qt/HA2s6sUu9GTfxBDADzuXj6qMiNOO74EBNQXDJpKgNke3eayC451mAh9w4+E+nbf1rEnWsP4WNzpZfxxdy0p0vjQ26lY1jJ9jMBWMmzl57tTACmhyW3FIYAE4BheHHpKkYgzoZMhcOXRAuFUW1XjX+EuE+P3DI622zoBluNb3f7hOHGOEquuEfPbO22xtbzGTsIwCUtO/KK4tDU/psjWVcvXVsyWQdF3YkTJ3IOmyJRCOo+tmGHMbC92jZe1Kj72YncwPVLfv4rWrl5rzWTr4+qbuaYwbRqy76iZATW4TZ74nC64KxT8hSjPvPFZRiBakBAvsfLbTxQ7iG2XpoZwwWhhrHCVRfZgJHISk2aZMMC7x6RaV6QEhf1PZ1mLt+sfX7PXbXVKwSCqU+8A0LaUNXk+NCBOIY+OOJ5X4MQFcdP5MQ0DFkbpg9iIsYhVJGFyvbrY2fIXiGkrKvvNPZbrj6K9Xvovi8JjqF9FQsD7icMASYAw/Cq1tJMAFbrzJb/uJgALP85YguLiEA5bq7UjfJd146IEl+oF9xRp1zaP3LrCvlS7zqgqEHYTZtXXbykOFMnH7rk+qa/q32g3IwxQwjKSCg2dLGn4ip95k6ppbNO/ULU9ut7j9L81R3Og2RSlzocFO+/7hL66JPP6Krh52mVMXFw5jqMACOQjwDi8a1u399roAHx/4O23U5SzvQcgyuryLou1OWmd8TSGaMTZU/Hs/Cea0d4x0kUk6jGmdW9S0AUygmqdImeQpJ3yAsI7/CFazryYuGiPRMmxUrSFbJXwJjSJO7Kcb8VeuPHwSMU81CbuHz5I8AEYPnPUTEsZAKwGChzHzoEmADkdcEIlDECuoOUjVASCgxfVQHatyn2TAeeu1b8kpo7DmSRa6wfQD9946D2EIlD2/HjJ5xEGRozJb7A3+HPpWagtE0dcFo0rcf9K6nLsNpPNKYTJ6KMl64rLtkY4VFDdPPoXIXNt8cPo+Ubd7m65d8ZAUYgBgJJCfsYXWqr3DZ2CK3YvDeouZBnrXi+iKy9QR1JhZG8Y/bEEXnVdSp1ZCdW1W5y5mDX8xy/h7wDxBh1daAkPOf0LxKy9B459mkUGgMXYhSKSxf3NS4xZ4o9qFM0xiUa48xhHDVaNRB3IViZxhsHO/Qbt16IzVy2vBFgArC856dY1jEBWCykuR8VASYAeU0wAmWMgOlLsc1kEctt33sf03df2J6Nk6QGL//+Szvp4fXbnXH05FhF6BeJRZqau3JMMB2acTiEWu7rS1utBzccXG+9ajCt3LJXS6qZXIJdUwe7XlkwJXJv07mkueqX+vdZE4bSD1/+TY5LHuaXMm5ppbaP+2cEGIH0ERBx9G5Y1hbkjotnw5eHnUubd73nZVTIxwk8o3WuwbLyXHRqIzhkRbb4YHXFkD7GmK4Y0/1T62hxc5fXR6To8ZjJoK4m8RD2CXwF8QfVvKrk0inaxbvVFAvQBnooJqry3mtCYxaKo2KL2VXFVbNhk0TJx5hX3FJI1WAmAFOFs2IbYwKwYqeu4g1nArDip5AHkBYC5fZVG/ZAjaALhP7Vy/pTc+fnCjwdBuLwc/mgPnmJP3QknglHEatIBFJXsy2KeqqblVAxmMg3OS5ehtPSkoQ4dD03dwKZDsMuxQ4ITBzYVOVJWuumFO1M/FI/2vjrQ6XomvtkBBiBAiMgYrqqSmufbvG8RJzSNC7xjMaz/Vvjh9ITrbu1zaoJCWyJL1TVnchEbHon1Q88m958+wPthyrds79x1AD62xsvjz76CJdklWyRXX3VGIEySfjVy/vnKN0FYRo3AYNvVmOBSRpz6NtGue1/fO0uZDmXUs/1u8s2xtyFUPX+zgRg9c5tyMiYAAxBi8umiQATgGmiyW1VLALl9jVWtkcmx+SDB9xaf9J5gJa17KDjBuR1rkTYdJpIPNMEusg8HBDvnzpSqzjUbZJ18ZVMfV8/agD9zY2X0/KX3orl+gqFyowxQ+mRn23Xxk6U+zWpXMptYYcod8rNdraHEWAE7AiI5+2hDz+hxiWtwXDhmblOCtEQ3ECmAtyQV23eG71fXM8ckVzpsgv7aF0co7h71ENO4vmvJpoKVbubPvzgXbRpweQoFi4uQbIIV1/898ZlbTnhKtSPVwIv09/xe1w33aSkT9L6cddCGvXStj3t9tQx+ij8ym3vmMY8cRuFR4AJwMJjXAk9MAFYCbNUnTYyAVid88qjCkAg6VfcgK68ipqScswcO4T+4k8uyR5sRGPyBlTXgRqzKPSgJdpEO1BU6JR0Cxrr6M5JI7KHLaG80NmIg1NoHDvUuTuT/CRU3AJS74pBfah975E8eHqyftZE6hIcKC/pfyZ1Hfgwr5wuNiHUMYum1Udl+5x2cqQyXNve7eVW7bUQuBAjwAj0WgRE6IUblm2kju73vXEQRFyo+7DaQXQwqSGvOKeiLp6Ti6b3xF3NySyvycaOOqq6/OpFG5whKVAPY5wPt+D1XVrVuHjn6cgZU4ZilVB0KcthR9x4gN6TqRSsZLIpbdvTbk83J757w0ITkXHXC9crXwSYACzfuSmmZUwAFhNt7ktGgAlAXg+9HgGfr7zFBMlkj6pskG2yuQu/PP9zNQTqIPbfIiWGn2t8stpB3niLg9jsSflB4NGmvDHGv4VbFv5fFwwefw8N8u6yPenvOKQ+N2c8rfnPbnqidVdkn0mVKY9ZKE42v3U4OGtlUpu5PiPACBQXAZdCLtQaqOTmTa2jhzzitMptI17q2Iv70itvHaZHN+yI/TyVQzSE2C4ISMTXE8/Azu4jtKh5u7YZ+d3i4/KM9+Bzc8cTlIY6t2FZPXnD0rYcQlHYpioA1ViB4t8PvbDdGIMxrgIwBEv1Ha++M4ttQ7nY7kvMxbVXrhey34nbH7w52nYciuIlY13zVf0IMAFY/XPsM0ImAH1Q4jKFQIAJwEKgym1WFALF3Ez6AGNz0bUpDlAPbrJPtu2ODi0itlG9FAPQpC68Y8Iw+uHLe7RZfHXxjny+eONwJhQacnZiQQLqgsEje3HLmwfp1V3v0ur2/T5wFbwM4u39y6yxUT9ZonVle06cLfnQKTby/c48JWc+dIbiQHpdPeJMHSz4OLgDRoARqH4EfJRrQAEE49fqB9BPOg9GJFloBmEbknKsvFEG9bVc36YuR0y/n27ryTCvexfJyazE72h7/uoObdIQPM+vH3UhPbC2M69N+b2G99OCNR1ZAlX+6KNzYS70yiq3D5Uh403b9rTbc41Ft8bSStKiy5b9yC2jXSbx7xWOABOAFT6BKZnPBGBKQHIzwQgwARgMGVeoRgSK4U6iw81EpNmUDboA4TnuVpn4ShecdQo9rGQBNrk/4QD2m8PHcg5FyIIok4eueZfHAldYVWUYxYDKZK9VCUGhFNnWfZQeWt+VWhB71yEVKheX4hAH402SirK5Yz/dtaI9r+k4iTlmTxxOr+874p210zUH/DsjwAgwAi4EpjcMpHmNl0bFkGhKXLrnmqutpL+74ssKclBO6qH2qSrNXTFum++dQPhAY2rTFLcWyaigBJc/sj14c33k8lzoq9w+VIaMN23b027PNpZC9gXlny7GJ9YnKwFDVljllWUCsPLmrBAWMwFYCFS5TR8EmABU3BRLkX3NZ6K4TBgCauBvNSZdCBkX1rN/aRfp6PvVWXtYAdt24kSeSu3ZOePzAqDLbkQ+yj7dCFU3mRMnSKu+kOuKfqG0WLi20+hq5Y/o5yVVsvHSC8/KiaMFsu4f/vuVhL7nre5wdiHHlNLZGtf9b1rDQFoTQ+noq/JxDowLMAKMQK9DAM9eNROuT2b5tIGSFX1pES2mDzSy7Quvr6PZE/VhK1DOlsV47qqtOUr5Yrnh6hT+xSIf05h3134ntI+02zP1X0i14fKNO6lpXVde1671GYpVtZePu28tJS5MAJYS/fLpmwnA8pmL3mZJrycAi7WJ6G0Lq5Tj1SXF0LkOldJG38OOz8YmJKmHTunne4gw2WJyK/bBF4Hu71nZblXh6ci1RriuvXFQSxpC1bd42iiCOzHULXDJ/ddX90VlEaT+nim1dN9XRkbm+cRDFAc8lNclQPEZZ2iZIeedRvuP/NZIis4cM5hWbtkX2iyXZwQYAUag5AjgA8ajMxuixEnyR9eQ/ZjpfeRDALoUVqb389IZo7Xq70IlAxFjhDJeqPlL4X6c1oLx2c+E9JV2e7q+ffdqIXaLsqwAjINabp2QZ0by3tJrgQnA9LCs5JaYAKzk2ats23s1AVjIF3tlL4vKtd5GRhXrS70Peml+VQ5RAIqEIKEbZ90mCwQbXKiOHPud9lDkwgGutQ/efDnNX93pKpr3Ow5ccBvWuc/gcDlncm1UB0HwP1PSBsuEnivrJGy8ffwwmj3p4misM5dvDrY1ToXF0+tpyqX9I4Ly8Y2785rA7wtXd9LxOI1zHUaAEWAESogADj2LM9mCVTNsH5ps8WOFGy7q21yApzcMIp8Ya6Z33tWLN+R8mEm6rzCNF/2blPFJ+yzh1Fdk14UkmTgGYPwlUclnOCYA4897NdVkArCaZrOyxtKrCcA0SZjKmvbqtdalhivUl/pQRNPeuPjGAIwTq0hnq+xiC5LsxIm4EwdyAAAgAElEQVQTRhWfKZvkbWOHRFnvXHGnVAWgK2aUz1xgHeAyEXrIpHnsd5/Rk627IgIRff7pNUPpidZ8Ms6nv5AyGO/mhVMi9+SFazryCEyReRkxFhVuM6SbKJNxkvpBnXFhRoARqHgE7pg4jE7/4hdoacuOxGPBc+yVBVNyFICmRtX3G55bcuxWNU6rTJ7ht7uvHUFnnfqF4CyrKjmHduXEIBjDommjYscANBFLLhITOKl7mdCPeqHlE094hTdQyEy9hWy7wmG3ml/JZzgmAKt5ZfqPjQlAf6y4ZLoI9GoCMG0SJt2p4dbiIJCWArAYm2Pb5l8EZlddpGyY6GIE+STycCkufBR+OAjhUhNq4O8/njWGvvnElrzfcDCbd91IamrOj4EjjxNNn3RSTTazsXBZNrnPuNYNyDzEQtx96COas2prnpvt3Cm19I1xQ/PcfYtBmKGP+Y11dHPDIK27MTC7/7qRUaIUXfISmZh14cC/MwKMACMQgoCcCTeknqksQkDgHadLxiHeS1B637isTZuhXm4XCZUWXn9Z9k9pv8O1Svsaok0GEtPVP36/elGLNps83v+2D2OqAjBUoRZaPo25ruQ2GK/ynL1KPsMxAViea6rYVjEBWGzEuT+BQK8mAAECv9ir72ZIGgOwmGsiTYVBnM1QpJTIqMwQW6gpo2bIUVw4FH5iBUE1d+jDT+hft+zNquZA1sFV2OSShZh8Pm6sOCiec/oXI7ffI8c+jf6L2H66ANquFd04agD9dNvB6EApE5d/UFND908dSXdOGmEMAu9qO43fRYyn5Rt35TUHHHDpDodCjQK8/+nnv6KVm/emYQ63wQgwAoxAEAINQ/pQ46gLs3HrTJWRjXjt1v3Rxww5Tm+u4q+GPkNWKceF56aJjHPV9fk9RG3ks4doWvcG6Z7xUPbZPrqpiVNAFs5Z2Z5DJOJd9tzc8dpMsnH2CT74VGuZ3oqXi8Aul/n2udfKxVbZDiYAy3FWim8TE4DFx5x77EGg1xOAAKFSXnS8aP0RkNUDIIx8sgCLtaAmeihWvJ1IEaDEF4JN8sFGXqv4TVZOhBxQxFhVYg4k0vNzJ+QpLiJlGVF0yIA9qguWmBlgpaoOXW7ZPrO6sLGOzjr1ZHpgbadTCeJqD4cj+UCJ8SxTAtLblKSu9kf0O4N2HvrIWgx4XjmoD7XvO6otB6WfKYvzTzoP0BKNCx7iAs4YMzRqD/b/2Y9+Se37jrjM5d8ZAUaAEUiEAJ5XVww6m9r3fv48wyNs3tQ6qh/UJ/pg8/WlrTmqZZ2iWqizXYo/kxq7kCE+dG65OjdmH8LI9a7HZKjvZoTSeEx6T+k+dMqTaHJPDt0nJFoYVVC5N+JVaaRaJZ7hmACsgodDCkNgAjAFELmJWAgwARgLNq5UrQikvdkL2ZjYiDI1e6+sXBOKACi/QshLU7ZEKPl0BJNQ4YFMRXw6ExmnEqa2eEa+CsC0Xc/U9as7ON614pfU3HFAu9Qb6/vTqSf/Aa1p358TR0+8zN16FfcdBJe2H7TtjghPYHrjlQPp2df2awlQ+XAYxQ5c22nMIOzumUswAowAI0A0a8JQerJ1T94zDs8bXQgCFTMQg8/NGR+ptpHJ9qEXtvdkY+/5vqGNQYrYsCs06mXUQZ/4gHP35BH0mJLgqdAf6nwJQJ89hKmM7MZsUufDjkj1pwlfoeKvw8SHoOS1/zkCvQ2v3jbeUq11JgBLhXx59csEYHnNR2+yhgnA3jTbZTbWEHKsWKYn3fzIY5JJMtltxzQWmyrgOY0qT25HbPQfau6i1e3d2Z9sGQ9NBCCUZH+9dlse0YTYeOMu7ptVU8LeZ7Z2a91wZULNRABCeQeFSNJkFhjslLrzqaXrnVjLRHdIWv7STmdswlideVaSMxVD5WmLgyWTozZ1pmfXBSlWjPiJBTGcG2UEejECUbbxNZ05ZB+IuKZp9d7Z24Xi2kb6uSDG8xCJPJZt2JF1Fx4FBfXezxXO6rsu7f2FD7GHcfjsIXRl1EQmoi1Z5e9S/elw1H3cqjSFl2t96H5Pc/57A14CQ991HmdOuM7nCDAByKsBCDAByOugVAgwAVgq5Ht5v+W8oYprmytuno9CwZRl8KK+pxsz1oqlBIXe3FVbc4g7XSwg2T1adcsSLk3PtHcbCTBZcaiLP6SO07ShFIpCUyZe31sEahS8RH0UKWqbOjcpm2LR16Yk5XRkcRpu1Els4rqMACPQuxDAs/HRmQ3aeKO6d02h0BFhJb77wnZr+Af5XRf3HW4bgw+xJ+r79O9TRrbHFZZCDW0h6jbfO8EYC1CXfKVQ81jMdkOx9bEtTULRp79SlQlZ56WysRr6ZQKwGmYx+RiYAEyOIbcQDwEmAD1w6y0vfg8ogoqYcKuEDUbonLs25wI4nxhFwsUHdUQWYFf7OCQtnTHamhzi1jEX5SS9wYHha/X96SfbDkZuWVAgNN1cTyjnIpzkbLM6d2S0IS7bfKOM6raMv4UoxkLKqgtYp7pwjT3oJggoDNe3668YqI1X6Zr/gG64KCPACDACTgSgqJvXWJf3fMZ740ezrqL1HW/Tqi17Y314cXaeKYBwFCMHnBX9y5YVV7SHd9H8qXV5yUd8Pr752BRCLPnsIXzKCLts7yWM79vjhxmTilwzop/P8KqiTJz9Zcg8VAVIjkGErPPegEchxsgEYCFQrbw2mQCsvDmrFouZAOQXYUHWsm0DUY0uBj6kUdJDiKoOlCduQWMd3dwwSEumoZwtuDoOWWMv7pvNsIsYf7h0xJxpsYBIWzZjdJawVMvZ1sP3X9oZuQHLF16Ki6bX087/+pAeb91dkDUqGhWkrE0ZWVADMo0/dccY2vvuMTpw9Lf0tfoBeaoNYDh/dYc2blYx7OM+GAFGoPcgIKvBF6/vikX04b2Aj0txLjm0AWLF4quQT1MiVqDap8/HNx87S0UWmUKEAJvn751A/c48JSgGsM9Yi10mDWxD95dMdulnOY25KPb6qaT+mACspNkqnK1MABYOW27ZjgATgBZ84nxJ5AXnjoFTjbjqSCw5c65PDEDX2okIwNUddFxTUBxuegKHd+ZkuRXFF15fp43XJ7I1Chcr4XL1zgef0JNtu70PcHALaxw10DiMN94+Sm07DtH42n455JYpFiHaG9bvDLp+SWti0guHpKbp9fTA2m054xEZgLvf+zirGsHfcND0Obai3VkTh9O0PxxEuw99RHevaPeq55pr/K6LaaVmhtS1A5doBNjnixFgBBiBJAhAlfz0q/tiZ16XExnJSvEkNvnUVd1hk358E33GIUV0deK0Axua1r1hVfkVisyKa6/PXIkyadkesr8MKRsylnItW4x5lMde7P7KFXedXUwAVtJsFc5WJgALhy23zARg7DUQ+iUxdkdVVtEHt7Q2e+UAHYgtNZYe7FrYWEc3NQwikcQBmRChrrvgrFODzba5gMqHG5RrefNgXuB2oQC8YWmblhw0qSZAht0+YThdcNYpOQQZ+CVVjYGyTdNGRS7E6mWbbxMBqDt8oo+bRg/KZsOFwuTEiRNOZQjmYvakETku0EkOpOj39vHDaPaki3Pm03RAC57wTAURvwnzakq4IrctyNyH12/XznNcO7geI8AI9D4ETO8FXySEMl3EmkM9/H9n9xFa1LzdtxlrOTUEhBozUP34FpeUcO1ZdO3q6mAwD6ztzGZ3fzATdsMHjEgFuKiFPpM+8KjkZtzxmfp3jdvHbleZtIk4X5t99qou2yvld19M0hpPsftLy+5itcMEYLGQLu9+mAAs7/mpZutYAWiZ3bQ3JdW8kOSx+eKW9ka1FPjaFHeyKi/uhl+MyUSSQemAjIxqfD81Lt93rhtJ9YP60CtvHaalLTuCoFIz0oLERIbjhWs789SBOqWFaz3gd1XZhpfiSYr7mIg9dVJNTY67spxtGQThNbX96OWdh3viGtbU0P1TR9Kdk0Zkx4z+ouQlq7Z6qxtVwKBORHxGNYi6yU0rCHCpMFSbZ51yshZrXZtQ3ICUXPHKHloSOM9xbeR6jAAjUP4IiOfn+x9/Sq073qGVm/cV3GiT8s70Pgs1CO3ff93I7McpmezzJeQmX3pB3nNctcP1DtORHWhXDaOBD0eQZ9sIPF3fpkzAaXgW2DDXjVuo5kV84tA505UvBBHns790zWsaYyuHNoo9zmL3Vw4Yh9rABGAoYtVZngnA6pzXShgVE4COWeKvWPGWcW/AzUeVB/TUQ0CoO1IPydiRc2hAuzhLPD+3J8Ofzha4p86ZUhtN4GMv7swqDr56WX96YdsBp2pOnnk1fpLNHVlk9xVqR5/NfTTGDKEo1HXLN+7KW3xCkaJTdSx/6a2syzLGfuvYIfQXf3KJVnHpcwC1qV/GDj+XfrHnSF7yFBicZqy+OyYMi8bkE/sKuM2TDsPx7lyuxQgwAtWKgBzvNCTGqw0PHGCg9EOMvqZ1ubFcUU8Xew8E5P/7+JbE4RKEsluQPeecfjKZlPY6pb6czMpGptneYXjP6Yg+xMT1SVwiYyQ+TuFvINjkj1sucrMQa9aVeCREvRhKNIbuk0ztu4jA3rBX9dmDpbl+it1fmrYXqy0mAIuFdHn3wwRgec9PNVvHBKDH7Lo2EB5N9Moi1Y6baZODQ8WijCts0o2QiWSUM/ZicfkkIRGLULgDIx6f7sCmLladi5Hp8Kg7UJmUEJvmT84h5+QYgbqA5ja7dK5RKC8OiHJdE6Gqti8yUHYd+MCpmhRkLA6fOITqXMLjPARCMhzPmjCMfuBBFprabBhyNrXvfV9rJghPXJt3vRdnGFyHEWAECoAAnjtQgC9Y3ekk09Tn+H1Pb6XV7d1BVonDCjxQ0feMMUPo3sxHFtO7akrd+fTEt8Zk+4nTr8lImVxEHF4R+kCQZULdt637KD3kERYBKsnn5o7PS8BkUzRBnTdz+eY8E7UhLCwKQJB9C9Z0ZD/2IJYr8JY//qRFivlOuu0jJ9pIao+8R3youStnPaoxcH1tVt/1Pt4X1b5XLbYir9j9xVkbpa7DBGCpZ6A8+mcCsDzmoTdawQRgb5x1HnMQAqbNod49JvcAkXQjZCL21IQbro26OmAcnHTKBZxP5kyupUdf3KlVt6Edk01y1kbRnzggqIcbmSRFWVesJDWou2hf4GCKvScyWYq4i6E4gWj92uX9qbnjgHPNQHWIBC1x4mbB1ffMU75A81d3OvsxFbCRheI32HbtyPOppeudoH62LJwSkbUgaR/bsIPWeeAR1AEXZgQYgVgITKztRxt3HHLWldVySUIg2DK+P/Kz7dqPJXOn1NI3xg2N4tO6nnG+Hz1k8mn5SzupSZNJXg0j4QQp8/wWH/BEebw3IoV5665Iia+q8a5evCEvnARcZe+fWkdyci0o5nCppNQVQ/p4fzRKK5uxDxbqu1lXJ6498jtfF8s3DXIxqfeFL0aVUK7YSsdi91cJcyDbyARgpc1YYexlArAwuHKrbgSYAHRjxCV6KQK2Tb+AxGeT41PGBHEIgSj3Y5syOYaPzsUIdYXLsS6xh4n4fHDa5drDHQ4Ind1HaZFyQJNjC5o26rBFJFG5cVlbXjZK2Ddvah099MJ2Yzw/2e3NJ5FGsZc7cPinW6+M3L1Wt+8vSPdCrfOvr+6LFfdQEK2Ye59MxAUZBDfKCDACsRHAc/A3h49lyafYDSluvfIHMtvzVXwgsfWLw1DjqAHODwxoa9H0noRTcZ9JaAMSO114BZl8UomqkORPwByKcKjtx9f2yyoLZczUj2M2fJKSYnHnHAQr3t9qcnkbGWzry/dDXFxyEX0n9b6Ii1U51yu20rHY/ZUz9qptTABW0mwVzlYmAAuHLbdsR4AJwCKuEH4ZFhHshF3JMenkpkxJLtRkEGr3SebeRSDKbaNfm7pDTQ4CRYIcBB31dWTcs3PG58RW0tkEFUPjktY85J+6Ywz96ROvarPSYoOPS+dCpaocTXNiU9zJCkShujAtDdm9LeHy0VYXdqpzcGGfU2nvex8XosucNuMoE0UDIukJJxcp+DRxB4xAQRDoeQ5vyYslG9qZrKqW3wP4O8ixx1t3hzaZLQ9CCcmbXJesIPeJ56q2J0I2vL73KM1f3aF1nzap5GGjGr5CF4LClY0YNrmIsCgZVg3lqQ5d+KT5u8lG3V4ChKzpkvcpJrdp114rZFymj6fqXiakTS7LCKSFABOAaSFZ2e0wAVjZ81fJ1jMBWKTZc5E4RTKDu/FAwLUpT/JV2qN7bRETgZijTsABbEJPFlhV2YcswIPPPS0v8y0OKT+8/Sp68+33I4UCYtjpyDhd8g3VJtMXd8TS02WkFQdJDFgXU1CNc4hytmzIn53IPTiK4PQ3NQzSto/2YAMUhDps4s6Vrp6IuygC1KMMiFqf+IJp2hGnLYGRcGWL0wbXYQQYgdIicL2Hss7HQjxXNy+cEhXVPbdrzz+DdrzzkU9TicqIDMA29bepA0Egbtn1rjYOohzTVfc+RLb1hddfltO8usdDdmLVNpU8tMXuFTb6ZClOBKSjsi3kh/zGtakTVWywH1HfJ1H8YEqX7FT7vfHKgfTsa/uzCdHSSmKiQpjkg28h55LbLh8EmAAsn7kopSVMAJYS/d7dNxOARZj/EDfOIphTtC4qZRMk7BQZBI8c+50xe1+pXHB0k2YiKgVxph4cfBKFwP3qp9sO5rnayv2bMNDZI6sE1DHICTpMiTl8EpCoSotMnPVI1YHfvj1+GOkyCsMeuBBvWjAlIuN8Mzb63ECymlCXXdLXXdunr0KXmVDbl17ecTiKb8gXI8AIlA8CUUzPS86nlu32mJ5J1L+60YpM7zpyDOXTemaAtBw95BxavL5L66qbZFwul2QbwYi6z987QZssBO8SXK07DtHKzXvz4JPJQ+07k4iaptfTlEv7azPYF3v1mUJ+qB/cYJfu46hp/wuC9OEXtueQcWmRnapXhCmMSCH2c73hY3+l7O2Lfa+E9McEYAha1VuWCcDqndtyHxkTgEWYod4Yi6RSNkE6IgakEMgj1RNJjjtUhGXj7MLm+iSILTQi3JPx/6bsvXJnd0xwu3GZNvpyoHQjjhnV3Z2TRuSM0TQetS/T2sKmNHJ/Xtme4+YGO6jG7FqGA5mJIHROgqMAkpfcP3UkyWN1KUxNTfY942Q6/NGn2Z8nfqkfbfy1O/h/0jFUWn1M902jL6S1W9+uNNPZXkYgFQTkhEy+STVCOgYBOKzfGdqQD2gH78of3zGGlrX8OlHmcKE2PPThJ3TD0racMBKmxFDIWP7LPUciYslF8rnGDILolqsG0woNkacmskJbPh92xLsZSZXwLjAlF3HZlubvLkJHjYN461WDSY0nayLTbPtfJCJzhU8JHadpf1CMfXhv+NhfKXv70HVT7PJMABYb8fLsjwnA8pyX3mAVE4BFmOXesCmQYayU8dqImMgdRSGNdC6pGLfuazM2tiLzbCGWmEkxJ/cFgmjTzsM5X9g/+O2nedkSVfumNwy0JqNQM+uqBx/ghFhQDRedo1XVqbH9RP8h68Z0YDGRiCD5nmzbrc3UCMcjnZohrXlTD0ZxYlbBFvUgj8ya33txp1WtmdYYKq0dYDXi/NNpxzvHKs10trcCEZjwpb60aee7XvHrijm8UPLPR1EnQiu4XG992vLBAu+xf5k1Ni9T/F3XjqBlLTu0iSmey8SshapflzzKp19RBu8rkzpcfraHfNhRE7KIdybCdxRy36Abty+ho5KVvjEAQ97rIfMi7xtsHzl9ko2lhXkxSMY4GKVVp9BzmZadldAOE4CVMEuFt5EJwMJjzD3oEWACsEgrw3eTVSRzCtpNpWyCXC6xi6fX0wNrtuWQQyqZowZBB7BQDurcPtMCPeSgIfcJm5bOGO10dV3QiPg8vzISSyoBaNoUIrbgNx7fkjfsZo3rlCiU5D5xJW5BH3/59Gu0ccfnqrmJtf1y/h06R76HXMRBHDngLOp+72NjxuL6gWfRG29/oHV1M9k1pe58+vdfHSo74iEUR1E+lLCI2w/XYwTSRADPgflT6+i/PviEHt+4S5tUIs3+itHWkHORnOi3OV3V1BDNmVxLj27YEfScMtkrf2izJQBBApOTamqijLqIo7qt+2jWfVTXtqwa91HlmezDOxNE49KWHUbIRV+u/YRoQMSDVYnJQrijutZJCKGjdwUmWjazgb487LyoK5OaL8l73TYGtV1TuA8xR/c9vTUn5uP0hkH0yC2joy5cKkgXlqINXRK1l+dPLjqx62NvaJlK2duHjqsU5ZkALAXq5dcnE4DlNye9xSImAIs402lsMIpobuyuQjaVsTtJoaKNSLORZWIz6SLiCrWh9z1o6CCCmmHuqq1Gck+4XMlJRFwHLJM9C6+vo6Z1XXnVXUlU4twnprnAAXNWJjEKDFE355F7cAIFoCnBSZzl6XPYDG0XKsG6AWflJX8JbUctn4GNlLwriZoVyiIRFypRY1yZESgyAnBJ/aOR/WhDlz0eX5HNSrW7NO97NcmFLfauGISIy+d6RsgfmURoiKMff0oLVnfmkLPqB4eGIedQR/fRrGoecepM8Qdhk/wxzLUfQHnxYfCivqdrk22Z3o3qOzHOO1K3EGzv7ptGD8ohrWzkz28OH6OFazujD1E+nhJpKO60hGQmAPBnUnYSHwUg9jsL13REoUOwJ2iaNopsGY1tN1WhyM5Ub+SYjVXK3j7m8IpajQnAosJdtp0xAVi2U1P1hjEBWPVTXJoBVsomSKcOEJt0BKS2fc31IeJcZJdudlybe5+Dhq5dsRHGZnfBmg5njENxcJqzamuOwkwlNt94+2h+fKaTauj+6y6hRc3bc0wpNikqYkDZkoHoYgCee/rJ9N6xz+PtmfB8ds74PBcznfu4711oIk1966vlxPr7/ks7aVFzPhkbt90FjXV0c8MgWtu+L2+O88hCxNTMTdCcU0QcwsXBET+Kw2Rc+7geI1BOCCSNRVeosUDRh/tPjXdbqP7kdhFq4pFbGrJ/wvtmbFOLUz3po7oWzz35/Y6x6p5Doj1d8iwo2kyJTmD4bWOH0L1/ckmWKMuJlVdDdOuYITS+tl8UL1FkgBex/65e1JITq9b0bixkJlvXR1A5S66J/ME78OtLW3PWkC5MSNpryrT/wvv8B2278zL9msrjo+g9K9tTtd9nD5d27MO08TW1Vyl7+2LhEbcfJgDjIldd9ZgArK75rKTRMAFYSbNVYba6NkHlMhxhp3AvEvH71Jg3qluvi4iLQ3b5bq58YgDK+Mpf5WG3evjAhv35uflZDdGGzSYdgSpn4ZVt0AVNT2sNRGNavMHqCqtLSgKbfjxrDP3pE1vyDmNwYX5117u0TOPuJqsEdPgg1iIINwvvlTd0k2sYyAOc0uMc0rcsnBIdTpvWvZFaohNx6EXwel93R59DO4Yp7plvPr6Zug5+mNbysLYzvN/ptOsQxwosCti9tJOp9f3phc6DQc8DAZWcUbwQ8OFZ9tXL+9P6zoOFaN7Y5qwJw+ivv355zu//+LPttMTibisKmxKA4HdBPuH/fZJeyQao72zbO14803T7giixRybmrCkLvPwRzvRudO0x5GemS1Vn2o/ZXKRtIU/EuM4+7QtBsX7TWmQ2NRr6UAk2U/n/efPlNH91Z55ZpljFSe333eMl7aeQ9Stlb19IDJK2zQRgUgSroz4TgNUxj5U4CiYAK3HW2OaCI6BmvUNSC12AbjnunOpOJMeX8TE4zoZWPmjYSBZ5Mxsnjotuw+dzOJHHDRJyk0csHN/NpVxOVTWa1B66GHOmwyRUJLh0ChDEh5wxZmh2eFBBtu04FKk9+p15SqyDJ9zNLh/UJye+lYgtdtapJ8dSxS1srKObGgY5yVGf9SnK4OD+QxxuQ9jNjFrm1JP/gJ5o3W3tDtjqDmQhNnJZRoARKG8ERLiJnGy4mkRN6ijwTLyufgA1dxzQDlC061LvmdCxZZ1H3zePHkjPvPa2URXvcpM0ua7q3o0+XgYYh8vTwEU6waZntnZ7hexQ38+mpFaFItDkeXONS51jXfliEpiutVHedyxblyYCTACmiWbltsUEYOXOXaVbzgRgpc9gTPt9SZaYzadWrRR2hmzSbEq8UAWgabPfMKQPvbbvqDG5iKxgvGFZmzbT7aYFPUowXKFEo2kyfQ8ncn3XQQWuqg+v3x4lXrElUlFdrcBFyQq5yA2XKJikErbKcYN0ykKbAtAUiBxty2oetDFval1E+nV2H6XvvrA967YERc5POg/m4ACXdBxqn9q0m5o91TrA4dGZ5iyWcW7UuIk6UG+Rg9wD7ndfO8JLBWSz/fpRA2jCl/oxkRhngrlOr0eg0KpDATBIovc//n02/poMvElJ7pP9HO8ZKPltCkBdqAbTO1veh5iIRVcyEIR3QFw9V30ZA9+PbLbEWr77Gd9y6s2BeuMWteS9f+FRILs9F+qmCt0jquVN9r8i7ZnSsj3Ox9e0+uZ2ygsBJgDLaz5KZQ0TgKVCnvtlArAXroHQr6algijEztBNoG1Mvps0n825i/CKs9m3EYvAzMe1SIctbHlgbWde7BwTVj7jVw90tk318pd2UpMSp043Vt9+5VhAPi6ogtiSiUcVT3k8JpfdKLFITU0OEYs/zW+so8HnnkZnn3Yyvfn2+5Fa8LIL+2gJWRVzGQeM3ydWlnzIVhO/QI35rWuGOtV4ad/7iPu1un2/tlmB++DzTtNmj/a1BWN7bs54em3vESYAfUHjcoyAggCeYw9Oq6c+p51MSKDhq8odO+w82rz7XS88ofb967XbjEmp5Eag1L5/6kiqH9THGpcPdosPXjb3Vij0xww/T/vO05FEwqUUNtliA9veT3g2zbtuZF4GY9c7XbyXTe8x2z7Ddz+DcYXsueS5kT+EAn8Qnc++tt97L+G1WApUCPMFT4onWndFJKYpiUka3cclWdPom9soLwSYACyv+SiVNUwAlrIe2CgAACAASURBVAp57pcJwF62Boq9AYlLzIXYGXfTGkJs6TboLgVcqAJQ3YDblqZtww/sfpE5gH152Hk5mfzkNuW5cR1qTLbILtCuW8kWA1D3FV60J9Qc4gDm69ol3F9R/viJE05SCQfMr9X3p5ljL6KTamoIMSFvXNZmPZyaknaogchvvHJg9kAkxiVUhKaMkCqe8pwD9/mrO5wxxeTEL+IQiQPONSP6UuuOQ7Gy+LrI1LoBZ1LXAf/4fdgAPXZbA4m1anIpc60v8fuE2r70ylvvepEKvm1yOUagNyJgy3ivi00qwjw89coeWuqI5ReiTpZj1Lo+AOG5P3vSiGi6ULblzYNa8lLYinJyvDh1P/HVy/rTC9sO5CjwUcf2scxGPGIsUH7Lim852YZunckqf/Wd5NpnhOylBGY+CSpMJKnuvemysVT3lm+olzTtS3u/mqZt3FbxEGACsHhYl3NPTACW7+wgyNNcIrqeiIYQ0SdEtJOI/g1nFiJKK3L4VCK6k4iuIqLziegdInqViL5PROsLCA8TgAUEtxybDvkanNT+JBsdXztDN7emMambWZvtIt7bpReeTd968lUt0WBzX3XhCluW/PxXtGLzXm1REFWbFkz2IvZcgcFFBy68bUSu+IL+ZOuuyOUWY0c8uzNP/QItXNOZ4xpkOgiY+sdY5039XDEh2n444y5rw1Io9OCGdOTY77SBym31Xa6usO1Hs67SrgGRJRcHKRuRKA621y9ptZJ5uuD0rqQnpuD0T2zcRcddi9DyO8hNEeA+QTPZqmrGyKQEYBo2FaoNkA6fxcnmkjEIWOFK0EShhsbtVhkCPgkgkOxo8foubXgKKLrFbyo0csZd13NM1FU/gCxY3aF9jonYczYSTtcm/uYiF1FGDg9hI8rQ1opX9mjDGcBGfPDwIdpU7OLsq+LUsS1nW3uuvYTAOc7Y07zF0to7xrEp7ofxOH1xnfJEgAnA8pyXYlvFBGCxEffr7wYieoqIzjYU/1WGGNzh15y2FD6iguSbZWnjcSL6M+z5E/RjqsoEYAFALecm09j0+GxekvbjW99ns+maD9NmVjfO+57eSqvbu7NNNgw5h17fdyQivqDountyLZ116hey7p2uvk2/g2RsXNKq/Rnk0p0ZhUMahwO0gf5uWNoWxZwTl049ZiM2Vbx850YoFuesbM+L2aeL9wQbvpNxo3KRKXjA4sGZJJOubQ4x51cM7kPte4/mFJMPzy6l6ILGkbSoeXteN4Is0hF5poDtaEQoa1T1J3D2PWybxiwC7OP3yG0qIZko+pEP9zY1aNz7qVzquUhlnZ1Yu3AfH3TuaZErprh8XTLLZexsR+UggCRKi6eNolvHXJRjtPyMR+Il2TX1nsm1dN9XRkYkmiB3oES/a0V73sBlkk4OWYH74+aGgfRM+/6cDa/uw9GqLXuM2Vvx7HNlANYlpXI9q03PKxOZVagEGa4Pcjp7fPZtPivUtTdz/Z42Geljs66M7/4kbvtcjxGwIcAEIK8PIMAEYPmtgwYiaiOi04gIvkyLiejFzL9vJaLZGZNBAn6ZiD6IOQS0Oy9TF7uk72YUhvBf+A4RwQ5cKLcgZh+2akwAFgDUcm9SdtsMjXfiu3lLY3Pl05drs+mai5D6JlJOHOpldU4SBaCwWSUbxd8n1vajf7jlyjwFoI7gUWPH6Q4GOqWEsB+JJ2zxjmR8dS5BuuDgchxAuW8ZP5H9FgkydFl4QRiFqvoyofmKpp4SpJaOXJVxM8XFu3dKLY29uG8UzF4oOV2qFtv93LTuDVq+cZfrloh+H1/blzbtPKzFSs5unYZaT7dGkRTloYyyyMvgCizkQwaizLp7J9Dre4/mxPaswOGyyRWEgKrKVU03KeUa6wfQT984mI39hg81wtVVtCGU2bsPfUTqRx+s95MUlaz8LpXfMWjP9H7xCRMBJfPC6y/LGVr0Dl3UYk0eJWPj2qPoPma4sPVZJiYyz2WPT9uuMj57O9tHVd/9hMuOpL+H7P2S9sX1GQEVASYAeU0AASYAy28d/AcRTSKi32f+u0kx8a8yZB3+/HdE9LcxhnAJEW2DRwER/SLTz8dSO6cTEewAwQg7sFP5dYx+bFWYAEwZ0EpoTg3Y3KT50q8bR8iGKaSsDTOfr9ZJNr0+m1lh3/KNO6lpXZf3FMeNeyOPecuuw3TPyq15fcpEjyi/7vX9WrdhEFG/OXzMGOxc3ZDL8ZZ88dHNAchDGwGoWyMY17IZo7Px4GzrCKC4VB4qcD6ki/cEWwrq1JO64sD6x7PGaOMTqpkdTYdu0W7t+WfQyjvHaV3DfQ62sn2uOH9P3TGGJtSeH6l9xjW1xJanm7Ip4+9wc/1cjxpvVoo13/Gsc9cCSTF70sVOUsLdEpcoRwTKeX0KlZ4ON1+lnBqyAf/WxUM1zY38LpJdigUpiHoL13RkFfhiL+N6VsqJQuS+bUmfRDkRY9B3jxN3v2XCRPcBF+9aqC3nrNqaE2Ig7h7EtSfzIfF0ezff/USSe9VnzyjaT7J3TGIj12UEmADkNQAEmAAsr3Uwhog2Z0z6ZyL6c4158MrpJKJLiegIEV1ARJ/75viN53tE9P9lil5NRK9oqo0jIkE+ovzdfk17l2IC0Buq6ijou2kN2fSbElKoCjZZOZQ2miGbPrnvEDxsbrmm8YRkAUYbeQHIL+9PzR0HtM0LV1hVYSEXFhlRTYHDTUoJW/B3XTw63YFg6YzRWvcv0bbvYcB2gHIp4tJeZz7t4eWwaPoo0qknI4ULMgSfOJGTbdDnXvE5dKukobDXp67P2EQZMUb8e/6ajljJRFBXkAyhBKWPrVBQjhxwFu1772NapGSX9qlfDmVANphUsOVgH9uQDAEX0Y44o3hWiFAGyXoLqw3b4NY7LqNCRm05E+7VizbkhIwwtY5ESch4jlisPomV1HbwvoAiWL2HZSUh6sghD/A8QYgCEZdWpy6XE4WIRFHffGJLjuoZ9fDM7gnx0ZOFWITfMKmfde/8uPsTFQudorDnndJjo+4K3YP4rJK4xFnIfsvHDrVMHLvSmps49nKd3osAE4C9d+7lkTMBWF7rYBHONBmTQMAJMlC1Eq67cM3F9TUi+mnAMDDn+4hoIBFBUgQi0XTh95FEhMBjSESSVBQh98MEYMCkVUNRX9JFN9aQzVtI2VLjGrJpVIkam4Ij9Ou7SRFni3MnDogmDKEgurbuAqMbLdxLXV/zXfiY1hTInbmrtuYkSfn/2Xv3cKmqK190bDpPE4NGoigaUUlA3UTojqAB7Y6kE4H4gNud+OicTjTkfNdEvEnf2wrkfH26v2zQnNueBhJP32BMJ6fReE9f8QWadCBfC4hgusGABhIQlGyiiRqJUWNM5H6/tWuWs2aNOeeYa62qWlV71D/KXvMxxm+MtWrNX42Hm+4Z2xt6xVLWgRsX/eBiwqWXmTE4QKH8YRkP1yVz++nSKSdSCJcjDntTQ2ov5DDNZXBYPu3YkU0mjUW1YAIO2/POGeqAaX+4g2PR+w5RNASCImdHCtsXUtKTJXLb6d5lRRNK9i17DDD6pyvOpE/cvKUU3yxbviqsN/aow2jfs2X1Y4tr1C4yDrb/7AdPoeXrdnvLFqB+6A337QqmrNoa4Qehi844ju565EDSfcuVt/jVb14VE+uGPOv3lHSAjLhP8fy1HyeG5HPr0xqdzPefnSZsf19B3yumjc2iaO/cOljD6lDWyAOdd/ExdQx9lsf3mPu8tr+T7HnSBiFxL+NHpJZcSH0HSZErL3EWe59IkcH9jpO8T+RdX+cpAmUioARgmWh271pKAFbLdg8Q0TlE9CIRHVFLv+UkRNTeg7ULf0dEf5Ogxsm1Wn+Y4osyNMvhOjoE44N5siJOMmGUAJTh1DOjihJz0pe3IkRjJ8BOeZm1iRrU5jIHCJcMTI149GGGmn/rdz/TBEssegQH1XuvmU6j3v5mNlX28qkn0DUfei9dv2ZnQ2MTTu4QPiGfsgvFc3URYw1YuIgRcyhERImvPh4Ofqcdezg9duCFhmg7gLjozh1Nh18fkQtCDadS1KPzRVjYhrHrOxW917j7IBbxCPJxxqnHNKUBb9j9CzbNuBP3GvY0qb++1LVOyVXFfdtFOFVR9yrKZEilw970B2yHV8hsbIZn1cQxaBKERBH5B/fHtTMnNNXPc1dwyzv4dsBz6crpQ+nkqCfqRshhvz8Z/y5au/MXIiENsXTX1sF6p19JOjOicr/6/T0NPwphQ/NdxH1fvOOtbxB1cDffC1y0+91XTyP377AjfvUJPdc5As33Y4p5pkEf805gUqARxWt/V4lAZgalEIBl1CHOK2dsXsr7Vmwtcz0lIlO6ZrvGtQKPdsmu++RDQAnAfLj12iwlAKtlUbwBjSKiR4hoUkC0I4noudr1/0VEH0tQ46NEdE9t/OeJ6B8Cc3H9xtr12US0JmGf2FAlAGMI9eB1KYnnU13yssK9JJdR/LqK5qhHoDldbFN/fQ8RRs/8+hX6yrrd9J1Hn87IK7e2kg8XcwjwRWvYkR1mjVS5MS+UwhrzF/e62xiECzAz5Kd7yMFaf3X7Iw2Eqds0ZdGqH7K1EjkMkVILkpcjDd3xdj07cy10r3G4xLDCumbMP296gtbsaE4PdzG5auW/e9PIi9xPXEQl7PL+E4+kLft+GVzaRCLd/ciBJjKgiEw6VxFoBwKmVinX4dbUbbQbLuFHo/m3bqXdv8DvyvGPiTrjGiBxz2nzHfS5W7c2RQsacs00ErJ3rxOBG/clRQRiDbtMxNLv/Vj0TDVpxcvW7m4AwY0MN9iBEDQ1/uKoDUVAc3V6gcHKzfslS9THQNbFTH1kH9FkfnzxdVoPEXKS57559rt1dbnvoeWXTW5IiU5SvAsHxyIyOd+vippF38eroofKkYaAEoBpePXqaCUAq2PZtxCRacSxmohA1IU+6BD8tlr9PkQESj+oK/g/aoP/nIj+JTDxz4gIBCM+mIeIQOkHBF/oM5qIHsaA/fv30/HHx4ZLt9VxVUdA+sKZV49eIABTMCor4jH2MujK5BJv5014F/3brmcaajPh4OGrx+ezr3244zoH2/NixOXG3c9kNaC4tFZ3f0maqzvHPjz66jSa2nhY33dA47DAoW7Rqh3RzsF2sXpOJxdDzs6YZ0eOIEXtkinv9t6CIV0MJv/80BPkHrbz3tPuPNOp+Yb7d9W7fkJmRPVNGVhb1ja6zjBDwLwQ50nHn3rSkfShU4+pR6UBur5aen/ZMIJUuv3hnzYQ2CAGNy04j+3QLm1YZKeRhsge04zC1ssmQnB/XjdzQr1mHad/6vPQrOESdtJ6gJjvI+ncWnW+7wJDIt7ERBLOnzGOuL9zuociAJFafM/8aex3lo8ABGm79cnng53WuR/XYt/5ruxuTdyLJo0h80NKlaP+JPdfyjuXWc/nJ9wPchIZ2jmmFVkC7ZRf98qPgBKA+bHrpZlKAFbHmu9CgEVNnNuJ6JKIaE/XGoCgIcjEBDXsLsIziej+wFxcN1F//ycR/X3CPuJ3aCUAE1DVoVEEyiLEohu1aEDqS3mZhKfvJdj9O/fy6KsJyNXj80FnDimx9F0zX5q6LEmJ9q1l9PLpZw6Pvk7NSD37/J+O99bl47DIoiMPkbjDrbTYOms3Jh0tFokZa+wBm39u5Vax/KFbaVb/MbRmB77uGj9ctJOkk2aLbltdtkcQkKSTsvcsfo1dNCO7hLqg+Iwd9bam9E8zN+8+mG/SdG+olQewCQf3WR26V7NGE7Vami6Bg863A54GNrj3Fs0+rR4RjBRTW2+7KYbPLT5x82a2vISLC1cD0Pw4EXsO2XsDo3vmT2+yh/usA353bRtko/lM4yAOG6zz1+ePj6ZOm+g+yOZGGMZINN93/b3zp9MFyzZES0XY3xN5CSDuXSD2Q13VHw2p71yx949QF+uqYNHt78lVwbEb5VACsButVr7MSgCWj2neFdFk48na5P9JRP8pshDGYs4eIhqXsOl/ISLUDcQHb6vrAnPPIyITToF5X0rYRwnABLB0aHkI5H2xdSXI84twUS3yyJ6HADRpW5A3dljjXo7ffdRhbHMPtzagTehxqax2p0Nz+OE62NqRKfZhw0docc0hfF1qjc2yiJTFaxsOUXbNP19NwAdrUTe+CEBEewxc3E8v/OZV74EaMpjaXVxqdMivYmSdPTflwBwiFUPRknipWDBrPC1es6vo7ZB1mPT1+QBehnCBT+Tp8llYQGuBySccQdsHD2pacZmgdtla3D3jSxEsqhpIuFtq6bN4xlx3/nj6+Quv1LvPhp6n2Ns8l/C85QgcyL3gju1sAxiQaYjwMxG4IZKO0zP0rLzn6mn1rr2m1irW4GRMido2pGWI7AnVObWfs6GabyBDfQRihnsf0aaFMyhLMa7VhHXrJIZ8g+tM7/s+ttdxvyeqRgDF3rdi1/PeT3neuex3hm5t/lFE77xY67xqIKAEYDXs0GkplADstAVe37/XIgBjOb2aAlwd3+s5SfL+omuAKDo/L6B5XspT57hRUr56Q9DB95LIFTZ3awNyNfJWPPA4e0C1D3c+fXCA+8bGfQ0pn4gEcW314dOPYevO+brU2ja3D7wmzXTMkW/NhoAotSMTzfV5577e+dZNizZrx4q+2zXtYg1W3ENdLF3X2NGQZBcs3xituSUhFWNNQXz3AIi762ZNoOOPfCshRTu1Ppa9ru0TKbjlvT9D8wxZDJ24WmCt2DNlzYsnHUt3bftZxzv6Fol8g40vnXIC3bplf9Y5u90f+C55SGlDSNs1vwxp8cSzL9KCO5CsUc5H2gXb+OSq/xisP3cx94paUw5Ik5dYCzWIiT0/fNHSsyaOppsu/6MkkGxCDDJ9jknFddOjuR/AYmTiwllDKc32fu6z2PwYFFsr1qU+BoAkIt/+TuEiC6tEAMXet2LXY3iFrqe+P7lrtVK2InpJ5naz7BL9dAyPgBKA6hm1VxkFoiII9FoNwBis2gQkhpBeL4RA3l+MO/linGfvlDlclBtA9tWPCr0cP/nsS2zduBjukuvur+rcgddXvB1NS2Yt3dDkO//86Sk0oq+P7YjIRVFiAZtUMkQpmprccN+ueoffK6aNrXe4xJyvPbCHFntS5ziHxkENtcJ8kW7ZFzVS9WhoDOS4+rxxNPXko0TdHd2X/LNPOYrW/6S5s7NJcY6lodk6IBVuyX07o3UK7TmobdhHfXXfyXuT47DfN6IvSmbmXT/PPESAIQLIjSTNs1avzYEPL57TX4gIS42OLRPDocjWCfSLF15ha63h+pK5E+u1M+37Ds9XLipZKt/k40fSIz89mKXU4/781LSxwXpv9rr1EgYj+sh+VoUO/ymRwj4d8IMLasRxTRB8EYB4Rk8fh9/C5R87wtJENWJ2qKZpSlS7kcTc21w9RbOvXTc1RBT66uJKSzlw6HA6+aI7zfwqEECx95fYdbmn8CPLWD/2TlNUxlbO72bZW4lLL6+tBGAvW1eum0YAyrFqx0jtAtwOlHUPRSCAQNFfhIuCm+elXDondLDjDh+xl+M8L4+SOa4+vgOv78DkRuLZ6Zl2apyJfkHNLq6rpmtLH+lkanBhPNc5kosABJkxMKefRr71jdG9UXQfAU+GeIyRdAZjLi0Wshx67VBDfT471RkElqRzYSzKxXcf4JD/yVseLpwqe857RrFEZtH7D/Mh41/e8nAyaWPSzAdWP+YlaKaOfSdtrtWIK0PWbljDkOfbB59PivjEfQW/D5HjrdZ/wui3066nfp3Jgfvksx88hZY6nWSNDHapAmnjDan8uG8NgYc5KQ2FJPK5P6iUIb/vOYVnx1/9v4803b8mqvr0MSNFP25wzyA8o++9ZjqNevubxdGN5vl34fKN7HPJYIPvC647sq/mG+TLot5rqdr2dw9XbsJEEEp9wh0n+W5154CMNc2yfJjllUcyz/dOYghkH+YpzcJickjfn2Lr6HVFoBsQUAKwG6zUehmVAGw9xik7PEBE5xDRi0R0BBH9zjMZXX8frF1DPb+/Sdjk5FrdQExBV1909/V9cP0ztYuYtzdhn9hQjQCMIVTh63leNCusToNoMdKrHXrkwVcyJzUCELqW+XKcspatD+RIrbVjDjanHvuOJsLJLX7/sTOPp1s37y9kWl+ar4kO2bL3Obpj62B9D9OYxBcNYwvDdf30pdk1RB6hwD+TK+lLp5b4kJErb5QQmqL4CJQUA8TSqlPWcscCH3xWrG/+ygt1drUPpaEuqkVkK3Mul45bJEXXJ5upGZcaLTrlpCNpy95flqly4bViqebwAXw4oqjo5vY9v2jVD4Nkqs+OIfnsH1TcZ/XHzzw+ibw1urrPKWnUcOxHDqzvewbhHl0y5/VoTBv3UP0+O6rdlt+UWcj7buA+V1PKcBT1Gd98l5xMreNYllyhH5LgA1xjFeNT0mZhEllTvvsk6+kYRaCqCCgBWFXLtFcuJQDbi3dst8XIMqkNOouINnsmXIdsk9q1jxDRd2MLW9dh858S0XFEtJOITg3M/RERTSAinFrRcKTMqjtKACYYrUpDU0icKsmdIksv65jn8OGScXm6/uU9PBm7SW3ivshLiCpppFGetFNEh6Ab6OxlGxrqluHA9dDCGVmUSowsCB3mP3DKqLprS6LyfA1VYvi6uEr24u45XzfllPvTjLUbIeSZ75sD26Cz5keXbWCjz3wkkKlhBmyWfu/HuQgTn0xSYg743jN/Gn1nx1O0bO3u5C/tT58zlm5ev08M58z+Y+g+pkuzu4BU/iLz7KZCnALw/T9+zyhauwvJFvk/Ph9uZQSgkRYp9L9+5XfZs8RXagA/GFx+1onejrdYS/KDSuxHGJDwr712KOpjhlhMLY8QqyXo+0EL+nFlLex0Ydv6XDkJRE+bJiR2RHTsOenzqlhU9qZaMykzv5WElC892YdJ/jtFNjNUT9ZXWzjULEwSwS6TrHOjWmn/zmmlO1cBASUAq2CFzsugBGDnbWBLMMUi/XzReTiDopo0iLvniehoIno1UY2biOh/r81BNOFDzHwQkJtqf8f4zybuERuuBGAMoQpeL0riVFAlr0i9/AIG3ZD2ik+sC7ANUN7DD9YoI7U6ZhNOvvedMJKtCegaHofmbz/80yztE0TC+aePpvsffapOAJk0RszjOhpzEWk4vPzlB06kWzbsYw/JIAeBvyTdziUduMOxD2NDWIVS8kKEgM/uvqYnRe5zfMFdMvUEum3z/iCxYA6G19+3s6Fzc5G97bkgLVb/8ABL4uHF6YMTRtG6nc21FBHh+NXv78lSCfOSXpwOs/pH03cefSrT1deAwaSim1pk5n75lx/spzu2HhBBM6v/GFojIPSw2NSTjqQf7PulGP8y8eCUgZ9fPGlM1oUVOOFj9jTRRPCXIinFphGJeVYYOdx7K0Rq2LJjvc+ddwotX7snSqRJ8Js/Yxx94U/HZ1s0RgMPNf+Y84djMmJrx+BB+vL9u+pNlRBp1R9JvXXvd0QxTznpnfV6e9wPKTYpevbidWxEcsgxY3XxQun29lzfDxbuPSO5SWLfQ+4ath18Px6Eoi8ljZ4kcmNMyg83Meyle0rGQS5f92RTf1HSLCyvzKk2leiUd0yR96y8e+q84YOAEoDDx9YhTZUArJ4fmDRgpP+ea5FwRtL/i4i+XPvH3xLRf3VU+BMi+n7tb98kok8yKr6XiB5FSRsi+kFtn5etcWh7CTneX0tDPo2IflIyVEoAlgxoO5Yrg8Rph5y6R/kIFCV/i86PaeRb31dw3V0PBN5HTj+GvrPj6eyQagiDw9/yBnrq4G/oI/2j6bRjR2bT6ulTG/ZmRIM5/OOaKT6Pg957jn477Xr6117RTe0ot2GAG1VjZLnh/l0ZQckVnfcd7iT1/UJpcVxTCxyavzSnn764aoeX/AGhmqfD72VTT6DFc96XYQyS+uDLr9IX73y0qR4fiI6bakRbzDdSr5uU1TzkooSkseXJUu8OUUNNRk5eE5UI8sbXVRbRYZdOObFpui/N3CUjpLJgg1i0XQxz8/JZZlpBXS6kvlssn93RW1Lr05YdtSZRI80lDU03XUOocbUzDalgk20+XDhiyO7k6mskYn4YMDraXckbnlW1OnRmf0Ogo97eo4MHCc8WkNYpPxKYaFO7dpwvLVMSie1iE4sAxHikFA8wTZfcCEDf/r76fTH/lV6XEG6x+osSHKTySO1Q5p5S2VLeEVLGxvavEuFWpl4xvfX68ERACcDhaXdXayUAq+cHk4loIxGBhMPJEWnBIPTw70usmnw/rhF0LzgqSAhATEEKMVKJ8dmK+vK12oCnENG1RAQ5zLiFLYBJCcAWgNrqJfXlpNUIV3f9Msjf1Bdt36/y3N9DB7z5t21rKO4uJTpskoM7YHNy3Pivu+gr63ZHo4xMCjDSldyITPcQfe354+nnL7xCX1+/NyOKQlErUoxtcsIQi7b3mQMgithztfBCnorD9z1XT2tKQZR4t3sgDxWJH1iNKhbhT6xmW9NLUR/RgpkT6tFRsfXLuI7U4e8++nS0MYqJbvHVf/ORGT4M7RRqE9kmJW19BO/cycfRn73/BG/0pMHLdNU1UWggk0477nDaPvirMiBtWsOu+yndAPfZPfOn0wXLN7INYXB908IZWdOcWAQRSNiPLt0QJXpd2WDTIw57E21+/Fm2diYiTk1HcMx1yzOECCjz44Db/CI1unixU2+PwwJ/89XFhA7jRx9OP/3lyw1RibHIt5BuJmLbjoaVpD1LfUM6TkK4mXqwWLOM79mQbD7MOlUD0JVV+v2FeSljfZhU7Z221faX+q2O610ElADsXdumaKYEYApa7Rt7ARoREtE7PFuC/JuNdz3mupQARBbRCiK6IqDW12uEI86cZX+UACwb0TatV8ZLV5tE1W1KRKCsF+XYQdmI7PMz399D8tmEGoiGa2eOp+OPfGu0+y4H38JZE+gz3q8DywAAIABJREFU5+J3kuaPLxrFHYmH7+K5Q0XqQ/rgMP/Q48+yhKKvlh/2imEcS080BCPqLE1dvLahdqHEpUAszTv35KwDpiEtJfNsUtSM99n1biHBmBKRh5TWv7nw9CziS0Iucjq5hKOkviR88ptXnkk/+tmvCE1rVj70BFtXD12G8eFqE0LPzYuGyCj3E8IQeyHd2hDLkq67IGxQY47rRGt3YY11qgW5NfjLl8k0B7FJCIm/tHKMIZDefdRhwRqd8PVT3vX2euSviaBD6QHTXRWRwxIiyNXHJhh9UZym87TvORLbF91WOV93UylD9fuk0WLc89GdG3t22RjFdHPXLuPdJUU+8yyOlXgwcj7z61ey2p3LnR+QpPhK7wcuNRzPa3zy1PeV7isdl4Jxylhu/6oRbmW9Z0mx1nHDDwElAIefzTmNlQCsrh8gj+eaGtEHsuy3NcLvfxHRV4joJY/oUgLQTJ9VI/nOJCJUk0dRo4drHYLvayE8SgC2ENxWL130pavV8un6rUGgjAOURLIU0sc+HIXks7tPuoXFJTKZMSA4vlKr3WeTLaEIF3t9REhdN+vUetRQKColRij6uvmG9JGkpJlIMl9qcGh9kBbXWhF0iAb8wClH0YN7nh1KX+57vRbZqv8YpK9v2JtFS+aJavQV9U+xpz22aFqru68hg174zatsmqI9XtIcBfY2eLl7ISJvYM77vKrbWMEmF51xHN31yIGmyDa8FKKLaqxO3vVzJ9KeX/yajQ415Bn0DnX+/fT0sfSNB59go+vy2BD7ojmGNK3YFx1q0q1B3MXuFy6y0CWdkUa8YNYEbyShT1ess6T2QwHGcDX4bvz4JFZG+wcCHwEljQCMYQDZpLXXQCTecN+uepkFO8rPFznIRTXib2jU4UYvuli6chV5d3G/XyR1EyGPpAYgfGT9T16vKWrXroxFQua5V6Q4SMflkaEKc6pIuLXrPasK+KsM7UdACcD2Y17FHZUArKJVhodMSgAODzurlj2GACJR7MiWVqiXmvbpFnuXpMGZunp2IfwLzziO7n7kQJaKGetwadfKwiHCV8DcxgeNHG76iz+q/ykUfYCaYr6UOSzAdSR2a0lx0RwpUTMSAhBkEV4kQBj5iFX8/Z+uOJMe3vscjR75Fppx6jH1SDXpAZMb5xIiKdF+rfBbl9BDN9680V+ufFyTmcb9iAacVExzHdghGvPm9XszcixG8uH6lJOOpM17fxmECdFnFyzbwNaBtImx1DTsvLYBifyR00fTmh1PRZcIyQSfXjhzAqE+Hu5DO4I4urBnADCd7pA8krXcGp6IEnOfv7EoJl/0nolm9kWEmR84Up4ZPp3s+xdj3GcTR3pgnKmpytVZxd/sZ7a7d5mRcyES1MiGiGlfBJ3RnyMtfb6Imp72s5LDVvr8lPiaO2a4EFFV1LOVds3jCzqndxBQArB3bFlEEyUAi6Cnc4sgoARgEfR0riLQAQTcF2XUpjOHZC71MK+IKRGAJuXQNOjg9owRbfahzX7x/q93P0prtvvJBJdE5Pa+cvrYjPSaNm5UvYmITcz4IgAh02UrNnshnD1xNK1mZAMZ+uSzLzUdnO1aWD5i0Y04ikU1mkgv++CLxh1cowWbnHPrc+XxE19K5PRxR9GG3c/mWbL0OYaYDpEHEnIMfvapaWOjtRg5wqPsKEkbJESK/url39GirBmMNO6udJgbFhyKbjyW7tx2ICOlQebhY4uHMZeceXy963dIIpvcgW9/7tatDdGRIB2xid10xLdeRpY7DV/qDXWYRjdmHRMdav/oYO8Ri2Lydcq1/RO6gVg03Y3tvXz3GmTwyWTLFyNYOPk5wpvD2iZIJc1M8npfjAS1Ce8YJi4eaD7FPcuRnj3vHL7cBPSI4ZpXV8yL+VSRtas4Vwm3KlpFZWoFAkoAtgLV7ltTCcDus1mvSKwEYK9YUvUYFghIIiAMyVQGIL7DDdJiF6/Z2ZDmh8PXldOH6s6l1EB7cMF57HjfAYjTy5e66evK6a6RUtOwTgiM6KNvXnEm/aevb3HIiKFacp+85eGGhhJ2LTGsgUYly9ZyJWSJFs2aQHYnUci3cNX2ppRQO03SyJWRTau2ezsD27q7MqX6zIr1e9jaZahP59bQSl27jPHA51tXTqERfX3eKDKQ15+aPpa++eATbAMQkCDLL51E7x/7zkykWC0xjHGjYSVz8uprUsWzBhfLNkTThmP7ZCm8DlkXm+O7Dv+6ZMoJ9O0t+xv80SbhpDUHYyQTZDCRar5uvUZOlAAw5KRNFEmJWl9UW+g5cvbitU33pOmSG4puNHv5fozAjxComRn68QffG+7+rg4xci3mA7EI8Nh8yXVJGrS9Tiz60CacENU5a+mGJjFMfUdOvlYTdLGoUglmOkYRUASqh4ASgNWzSSckUgKwE6jrnkBACUD1A0WghQiU/Yt27JAWO/DkUdXVIXZIzlNHzidXTF/M80VvIXLjokljggdje1+frbhmHbG0Nx8hifpxi2afVt/24//4IG3e15zi6WvEkTX0qNXrM7rb3T99B+RQhJuva63EV0JNEe7f8ZSX4JSsHbKtPV+acmyIHjSG4IgyrgswF0Vk17EEgXPo0KEG0q1sYiWElesnbhqppJmIWR/37fLLJmdE54+ffoE+cfMWcR2/mIyxWoZSf7Cj8Ljab/Y9fP2anXTH1kF2aXM/mGZEdkMhrPFXtz9C63e/XguOW8RXb497joQ6QOMHkxhBjL2QBh0iEUMEYCz6EPoVjQAM/ZAjta9kXKx5kruGtC4i5vnqO6Z+P6XsGdK51QSjBG8dUxyBst8Di0ukK3QaASUAO22BauyvBGA17DAcpVACcDhaXXVuCwKtSA2SRECUdfjgQJLsj3l21JR7MI29DLt1qtzDsZvmhRToG+7f1RC9VTYRateOev6lV7PC9xcs3yhKObRxdCP2QKDNXraB7fDL2TEWyeMjGlDH6oue9MYQYev6AGc77tB83awJonqMoRsRUYQf6R/d1GDAbhLiq3foWxeEz5fmnE4L7tjRNATXUC/Q2Bf/Beli+28jwTbUyXrnz15oIJrmTh5DaAphPtJ7BuNTG2i4kaKGyDHp9IgsW3TnjiY/xT5XnzeOvvr9PUO1NmtNYUBG3bl1sN4gwuiAiL0i2cWS5iqpD2XJPb5h9y/oL27eElzaXUdiL8ne9qYsudZHtGnhjKxeXajMgL2XhMjj7lmuEzQX/Zu3BmBqg4zYd0DMF0wN3Bd+8zu6yfJhl/BOtRP2Tamv2w6CrhXvETF89Xp5CKj9ysOyl1ZSArCXrJlfFyUA82OnM4shoARgMfx0tiLAItDKg0EoAiLPgSfFhJKIPHu9WB0md287fdV0sv3FC6/QLRv3ZSSGr9C79CW76MHTyOs7iEuwBBkyMKc/G2pSFt15PjvGUsJCfgcyiEsjxt4Sv2kgv0b00RXTxtbTve1D8w/3H/TqJcEHY+zINs62bqF/SYdPszdSfrMUV0aYUDSkNELKTlU1BKIvhZvDw43WDJGCdpSrz7fxd0SO3rJhb5aCat+T9Wu1+4uLpjTE6MafPBPsouxL98V+iNYzjX64qMmYX0iifEMRvIYE9a1j2913j8VqAMZ0cDvvmtqtrx061FRGwKzlPj9DEbem/qqLQyj60I5GNntyOEr/FsMA16XPat9aoRq4dip16nePRHZujOT5lHftkE2KrqnzW49AK98DWy+97tBKBJQAbCW63bO2EoDdY6tek1QJwF6zqOrTMQTsQ5IvqiNvdJ57ADP/3jF4sH6wbseBRxIdIyWz3HFY29cYw45Q8qW6xci9ogdP+zDGpeKlOF6om2zIjqFIIoNLSE/MX/nQE7SUqT0Y8k2f3UGmLbDqFZZRh45rThIit0y0G/DH/4NQiaWv+tKGQ9GQKeS3SxaBsMzrM5Dps+eN86ZTu+noPv/xkTix9FPganwji1hduqGJPL186gl0zYfem0VLhurg2ZGJPvLb3Efwg+tmTqDjj3wrHXz5VX8E64g++sApR9GDu59pIjhdAoXr/ooxtt19h/a7rx6KDnWjQiX3vUtQn98/mr776NNszUkT1co1dor9AOAjo1wbm9qDZTaNkuBQlBCRzI99D0jkTB1j79kJEjJVXh3fHgRi92t7pNBdqoiAEoBVtEr7ZVICsP2Y645DCCgBqJ6gCJSAABeVUFZaaoy4aveBx40EQydPRFPd7hT6t2GVEJ9rth9gO9eadSRRaj5TSg6O3FwO2xQiKNW1kPZ6+VknBusWutFkKYQZ5MmDRUznhbMm0Dve8kZvJ9rp7zmKNvyksSswyMPXGICkNQm5dFzIECOWzJZTTzqSNu9trr/o8zPg5pJ4ISLX9ttll04K+nbMT4DJZ1duFdfks3UwPgzyyyWwYnaFXLDTVy4fqg0Iwuiqlf/e1JUbBNo986fTvmdezMg6fEa+9Y31xikg/tz9QSZesGxjU+divBBfViMUbTJF2iwEe4eeFb4apvac2DM3Zi/7esqPJiba0tdNPXTvYk9fN/N2kVKx76KihEjR+Sl2yzM2z7M1zz46pzsQUH/oDjt1QkolADuBevX2VAKwejYZLhIpAThcLK16FkYgFIXEHbzstLe80XnteoGMHdxc8DD+B/uey/5siAHzt6tv3drQ7ZIjI7gomhgBiL0kRCJnaN/aofVCkUy+qCl8mc+fMY6NsJM4IAilgYv7KdTJOSOilqxrqOuWSo6mEhwxEgMkUd+IPrYmIpfCCnk/fPoxTUSSVA9vRGIfibrgwk6oa+drTsH5hY94hV1N12VfZCEIvPm3bWMjvmy/8GGVh0CEDk8++1JTDUD7WYSGJgNrdgZd06TNmlTe6+/byeLm6o5/z5k8hu5+5ECD3qYzNyLcuNp3hgDmbGxelrn0bVeJEJF825Yn2DqQrehkKyFZbdljzziO+EYTkxg5lvqMlzyv7DGSZ0rR77Oi81N1Sh0fs0Hqejq++xGQ3Bfdr6VqkIqAEoCpiPXmeCUAe9Ou3aCVEoDdYKVhJGOrDyl5oQy9xIVe+kF0mbS3POlW7ThQ5HlBDc3xXYvtEyMjpOQQbOymZBmCxrZ/aL3YQdOuVegSOPfOn97UuCLF72J6luUTqfcadF6wantSMwgfIfbp6WPpnx58ookQ45pacNilkiruGqGmFohm+9Kc/noEG+5bzh9MGqXdaMNX385ESIaiEw3RZke62TUvJam6Rk9Th5BL18UYc/3C5RubbBDGpq8pYi/Ft+2xIMpNAwdbbtNNtqiNbTK96PPAp6PkHoqR59Jnkj2uoRN1rYHLnD8c0/TccZ8lEnlD9kz9EYzrDBz7Hoj5U9H5sfWLXI99bxRZu8jconYvsrfObXwfyfMeqBj2HgJKAPaeTfNopARgHtR0ThkIKAFYBoq6RikIVPXFPvZSH7teBJxWrg258qwvmeMeOGJzfIdkQyBxEZS+Q41dbN9HyMQi7SQkWyiqELUZfZFSEn9IrccXIw1jexos7TRNzLHJay7yMLSur+EC5viIwVj0k9kPsvjqRYZkikX+gfxCnq2JMMM/l8ydSO8+6jBvtJob2cfpZuzzzK9foY8u2xCNUuS6aLt15NCVl4uEM/Xstg8+Tys37/fCgQYiA6ubo/9Qz+/WLfu9RG/IrjE/s68j3fW6ma938Hbv8RTizLevqadnyjHkfR5w66d8X7mdsiefcARtHzzY1Lmc66YreZZCPuh20RnH1SMuXTxT5E3VV/K8tNcsSkgVnZ/ip6lji+Kcul9sfNXkicmr1xWB4YCAEoDDwcpxHZUAjGOkI1qDgBKArcFVV01EIEYQJS5X6nDJ4aaVL9mtXFuimwtmK+b41kQa3xGHvamp8L6LCdKt+8eMpIcef9bbLMHWw04P5A6TN/7rLnadNddMJ7vbplsTziUc8jii3QHXNz+UnhyLOHX1tdcy+3FRaD4SLI+OmOPWAEwlMRet+iFLcIUIKtRY5BqgQJ5Z/cfQ/Y8+3UTO4QVt9TXNUZ2QNyU1F+QmPlzaK4chR4batkMK/lUrtzZNXTK3n2acekyQIAX59s0rz6RP3vJwAwkF8hC50ei4zX2Mf4PcRkfhoh/oiChpt5yAWZfzzdQ9JYSltO6k2dsXEbr80kn1kgihsSYCEzUZudqMnP6G0Avdh/a6dpmFot+vsfmx6xKbVZnUk8hvj6mKLmXYJVV3Ha8IKAJxBJQAjGM0HEYoATgcrFxNHZUArKZdhp1UeUildoEkfYlu5Us/FwUSI3ok+IR0w3xuDyke7oHIV6Del2IZasaQkg7p4mAX2ncbmlwxbSwhlY5rToB1DCkDDFY88DjdvH5vPQrLdC398v27orXeQraREIDY3yVNJEQxR5xK5A2ljEr8TDJm7uQxdOPHJ0mGZmOAwdSBtQ1RcHiZ+p+fnkK/evlV4mpRopOrz7a+piTYCwTRr17+Xb3BSCg1lyPRjC9jLbd+I6ewpEtrKGoWTTRC0X/YEzJd6ESMfWraWFqxfi9rAxMNifqUxv9v2bgvIwu52oUxQxpMYg0qsNdd2wbZaEU72pKL7jTdmEOywF6bFs4INt5x54fSk+3Iu5DssWhX33MWPsylbhsZuXWLfr9K5kuePz47FJkb87PhfF1it+GMj+quCHQKASUAO4V8tfZVArBa9hhO0igBOJysXWFd85BK7VSnSgeUsmXh1gO2pl4Zl36bR4bYHI6Mm3fuyU0H89TaYEjrBLljRyyFIvV8RJAh5uyab7YPmrRNLior1Vd95IBLvISIKK7+l0ucSggSm1hAUwlpl91Unbm019gaWS3GO3c0RKxBp2tnjqedP3uB7tg6WF/CEIxIEV8caXzh7ououkunnNhQW9LUcvLdP0YuN918YPVjXpLN7Mt1duawyKOLvY4bMYZrPoKSIyXtHyYwd+n3fhwlHjEuxW8xXpIODPmuO78xpdhuxGRja6dPS7E28w35/rlbt3pTuaEft7dZQxLtGiJvsuYuq7Y3RWGm/GgikcHWOfQDjj0u9Yepqn/3x55BVb6u2FbZOirbcEZACcDhbP3XdVcCUP2gUwgoAdgp5HXfJgRiBFGnIWtlhJ9Ut1a90LsH+VYe9kIHxDrBtWFvdrjlyMdU0gMNGKa/Z1RT7TVJaqBtFzSouGjyGApFH3LdXmNpla7tfQdzX+ORUCqqTST6CAUJDrZMxlceHTxISzwdYW2doP/yyybTT3/5soh442weuj8e+9lBNqrP1csmGO/aOliXXaJ/LEXUfTbYtjI1+UxnZy5ykdMvROaYewj/laYU+zB0yeZQs5dYWjL2WPnQE2yatd3916SnxiKUDK5Ik131H4N0S+254LOZSSm2nzFc1CtqAtppzlIyLCUl2UeuS/079qz3/Rjg6yBe9Pu16Hyf/8V8QPrdqON4BFplN8VbEVAE8iOgBGB+7HppphKAvWTN7tJFCcDuslfPS1sFkq3KILfjsNSOPXx2DqW9mXpZofQ323aGcJh37inkJb+I6DWPwc0B3kSUfSawDpYIpTTiuhs5hy/+S6eeQCcd9TYyTQp85EAsAoojHl1Sg+uyjDEfP/P4YNSWjaMLlYmG2vXUC17SZ/GciQRSwtc0hYM/JS0zNSLUjj4DUQRyKeRTkpRsW4cYcYOx//1fd3lrEdprceScHZmLKLMbCtTj8xFfIFXdZiXcWJtcsOtGcjb9509Poenj3tVwicMK66CT9g/3H2yKcgOJa9L0OZv5ukjbzxsfaZonJdf3XeEjKNF45aJJY8TpxhLyJuU70x2bMhe6po6XfJdK7hfJOjrGj0Ar7KZ4KwKKQH4ElADMj10vzVQCsJes2V26KAHYXfZSaYc5AmUdlkIHgrL28JkqdKiNRalJorXQ6GHqyUc1NA6JEWiurG5qpEn39K3DRXm5kY4gVWYv3dBQs86QS9g/FBkZqzn24ILzyFdLzZB0V9+2ram5g4mOnLV0A2sukw4di1ricLFrLRryIKVz77xzTqJFs0+L3vEcsRmb5JJZtk+6XXxn9Y+mm/7ij5qW9N1DPlu55M/H/p8HacveX3pFlaRwm1R2SSSmu1Eo9RW6IZ33ti37szRXzv6p95SPYOOi6nA/YV+uz4jB5c6tg00RpZJIvrzPNynRDP+ZP2McffX7e5pqgeJ+ww8JKZ9WkTcScjFFziJjqyRLET10riKgCCgCEgSUAJSg1PtjlADsfRtXVUMlAKtqGZVLEfAgUPSwFJufmlqWYqjY4TuVVOD29hENX7h9W0NNOHsu6gT2HRqKBoyRXe4657xnFP39x86IRvX4IuAQvff+se8MEoBe4nFEHw1c3J9F2BmSzZf+6MMKf5ekkcbIlZhfYR+MWXjHdm/UpS1jrOacr3mMWQMvViNG+Dvaun5SJ0pv3dpUW80lbkK6hnzY9i2M8xGinA+GInNNJ92DL79KOwYP1om70L0Jku2e+dMJkbV2x9jMRqu21+vbAUfoj0ha+yMlxDAn5jscOR6SHffM4PMvs41BbLti3Y27n6Fp40bVu3cbP7QjKa89fzydPmZkU7dxW4aUZxP0/fBpx9CaHU81qBHDIeVZWmRs7DlcZO28c1tFdOaVR+cpAoqAItAqBJQAbBWy3bWuEoDdZa9eklYJwF6ypurS0wjYByQomlps3RBEofp+DY04+oiumH4ScY048gItSS9uSCv0pOiG6mshGs5E7Bk5JYd3kApHHPamZBJAeqj3EYCXTz2Bbn/4p1m0UIh8TLVNTGcjNzA6e/E6+j06I0Q+kjRJn18a/63Xc6t1kAXR94GTj6L1u59p2t3ejyPd3n3UYV7y0qSSoiad2xHXZzOff8LfNi0c8isJeeKSaLZi9t5cPUsj92nHjqxP80Vx2mul1KczC7tp7hdPHsM2AeFSsmP+ZfZwU65tstGM+cTXN9P6nzTbn3NH4NPXxxO7Nh4uUe92mTb+CMLUdMKOkf+uD3749GPoOzueZu8dX7RyrJ5k7B4s47rkOVzGPrqGIqAIKAKKQDMCSgCqVwABJQDVDzqFgBKAnUJe91UEEhCQRFdJlotFEbnkIEdG2PukRm1IyBOsD2Lkhvt2sQdrHNKv+uAp9JV1uxu6cLrdVm05Y9FKUhKvyMHZF/EFuaUNCWJ429dDDSJcokPSWIXDKCYPbFCPKLUauyDiasyRb81MhOhHfNzus/Z+Pr+5++ppwfp9XG1E7OVLxQxF5RkyMnYPmbqCFyzf2JRybXwytpZNEvnq7LnRhKHmNJJnA8aAjHbJUldme60b/3UXLVu7u2l505HXRNX50tMxEVF6vhR0Tm43RduMsfHwrYluzjNOPab+A4H0eRR65mGNu7YNstGI3A8VbrkAqW3KHJdH7zL317UUAUVAERjOCCgBOJyt/7ruSgCqH3QKASUAO4W87qsICBEIkR9u+l5sydDBz0cY4RA7MOf1NFOzR15SMjYvlkIJ8sg0zbD1Rb26xXOHGk64n9R0Sx+ORQ/OWXfYO3d4iaEQ2RKzrYsrh5PpyAvSzY2SRC09Xy05LjIqZkfIG9PXXjcUsRUi3Z589iUWU6y97NJJdNXKrU3QhZoxcKSWXc/Q5wNoyGEiyUztRM5mMWITcwyZfd6pRzd1neZsGCO4XTl8JJrv79DnoUUzGnwmFOVoE5ixe2bF+j0seTZxzDvosZ+9EL1XoBvsiTRf8zz0EXIYa0ck+sbFIl255wsXWZ01aXE6DhsZuEjl2D1e5nXJ/VvmfrqWIqAIKAKKwBACSgCqJwABJQDVDzqFgBKAnUJe91UEhAjEGmPE0tbcbXwHvxjxZh9YY4d6s6cvQiwUOeZLlTWkTSyyzZcC7NZbwxfvV2v191wyLGSaogfnWMSTnZorTfOWkFKcn7h2gGwXLNvYEHkJ8uubV55JI/r66unREvunpIhykXwxosy9vuKBx+kWK8rwSxf3E0egGdvGSE3XB+zxErKV8yEu+isjSVdtb6o7GCIwufqF0ghAY8+//PrDorRv6IHIwIE576urlPKsiDVFeebXr7ARgGuumU5c+jZnF5vsNhHCXGSimStNIxY+orNhvueC73mWSjKmyCIda1LLMZ77UUC6TtXHSSKVq66DyqcIKAK9g4ASgL1jyyKaKAFYBD2dWwQBJQCLoKdzFYE2IBCKXrPJjJSIEt+BKBTVYx9YJamweYgypKJef9/OhtRe6GjXIIsRS9zBWiJviilDB8rYYXPRqh960ywNyQRZ7CYFILO4yEYjsyQt1a29llJTz6QyGvl8tfckPsLhDHJ3YPXOpkuxGoAuJhz2odp4MZKRI5vMfWbv9YN9z7GRhmY+IvqumDbWW0/zti1P0II7djTpz6UwuwQxaioi8s2uZWc/FyaOGUlb9z9fX9vUwuPSvnGfoRIkOvDaH7ykXjb1BLrmQ+/NogBDtRLdaOEYWQjf3rL3uYYGPZDxulkT2HqEtlzAFeSfiby09eaacMTu8dQfU9z1uKYjErI8JleZ143f1mtxOqR56DlTphztWivP91C7ZNN9FAFFYHgioATg8LS7q7USgOoHnUJACcBOIa/7KgJCBCQEIJYqK6KEiwJz679xh9oYSRers4cU1IE1zSQQdMOX5KfPeb0hiS+11LdHuw7hscNmyJbXzBhHl591YuYVoUYtnNuk6ucbH6uph72BcSxiD+NiRK1N1kjWM2vaUZExstXsgXF/e/ejtHp7Y1dW+76RptG695kvgs/szaUb23KjPp4vAhBkI1c/71e/ebWpRibsYrrZGlIQ/71w+caswYyNtyExr1r577TGwmTWxNF0/46nmghAMxf34ZK5E9nIylC9UAkJi0hAu2OvxB6mcQ/XxRp2gv7f2fEULV+7O9p5OpQWLnlUh+792HNBsn4ZY2KNYmLP6DJkaOcaqc/FsmWTPp/K3lfXUwQUgWojoARgte3TLumUAGwX0rqPi4ASgOoTikDFEZAchMslSnWqAAAgAElEQVQ+uEkOrG60IAiAxXOGavClRtzhoDR1YG0WfRT6mEiqOX84hvY982JGGHx7y/4sfTIWvWPrFIvIcmWQHOQkh00fLngJ2FyrsZaKnZFVYjMzNlZTz0QfhjqZbn3y+aaUWzd6iMP8XYe/me26miI/sHZTflFvrX/MSLaLM8afvXhtU5ot/GBTrWu0b4ztCxIi3B4P/K4+bxx9pH80ma6+LiaHDh1qjrjrI1pSu5ewnu1/d20d9BLlrnyxyFCXaPZ117Z1MkR/qLEHdw9Dh5SaezEC2Y6EjBHmDZgzUY5Fn5+Se1/yDGnlV1EMT7N3WT8kFdWlDLzyPkuLyo75Kc+zMvbTNRQBRaB7EFACsHts1UpJlQBsJbq6dggBJQDVPxSBiiPAHdyyGlZEIuIrr3qxA1hGmCxZx3awxZ6xQ7ktl69OVkx2HNxDxA9H5HG14kJpb9KDnOSw6TuETx37Tlp++eQsvVJCJvhwidnMzIvtYdZ57dAh+oubtzRtZ5pcwA9n9o+mz543rk5wcZi7tQx9ctp/xzpIrcVn7Ki31Rs8ZBFzgUYqHBHss828c06iRbNPq3cq/vqGvd7oN67LdIicdxtqmLRWSa0+4PrQwsamG8AhFEHKETghO/tqafoagdh2NSSR1N+kfuf6jn3vARN8EMzo2lhyj7pRl1yKfao+Rl7JvR97lrX6eid+SMqrk8SekrVjzznJGnnGdGrfPLLqHEVAEWg/AkoAth/zKu6oBGAVrTI8ZFICcHjYWbXscgS4AxEaHEibRLRC/dihN+UQl5cAhF4p0TuhgxnW4ogql7BxUx0NaRBLtzQ24Gqv4ZpNMNlppVzjiDLsGbKP0en5l34brG1n5ODIMVfGFHLFV4vSV6PO3UsSqWdHsi1ctd1L/GFtvKQtnDWB5p17SsNWnD9h3WtnjqfFa3Y1mWnJ3H621h9nz5RalmY+dy/4Il8xh/Nt1Cq8ecM+r4vZqf55/DDluYD1XVLY98xL8S93XRDvqXLZuncD4ROLAIRdr5s5gU73RNHmsXWeOWVjWcSueeTHnNh3Y951dZ4ioAj0BgJKAPaGHYtqoQRgUQR1fl4ElADMi5zOUwQ8CKQeRKVAtmpd9yArJRUlBzWpzBg3ZWCtFIqmcdK0Nd/BDF1Ov73lp1lXVDu6yEdMIlUSzQ7wsSOJLjzjOLr7kQNZzTVfSnIoEscQOHaUW9nkWszesXRJn5FCRGzKIZyLLM3jGFytPmMr2A8k3cWTx5DbHTpVP063F155lW1qMn3cUbRh97NRdVJqWZrFQinwwJSLfLX9117nw6cfQ9/Z8XRTl2A7zT+qRGCA9LlQZI+UuZJnWWy9FB+PrdWq61wNQFMOwZea3ypZfOu2gjxrt7+V4U/txl33UwQUgfYhoARg+7Cu8k5KAFbZOr0tmxKAvW1f1S4nAnkPDN1wCPRBkkf2PHN8+w+sfoxWrN+bbLGiEYBcyqNpqLD4vp10yFOYEBEz1NfXlAKNhhboyup23TWKxSJxQp1fEankfsq0ASdblm5e0xNkAVezzsgE2WdNPK5BxJTDMMb66sSlOIbPJ9BoZkmtyzTGfOzM4+nWzfvFS/uIZvd5gUY6s5ZuEK9rDzTkMtLSuedQQ1osEX2k/xh67zGHN9QZdDcO2QDNNy5YtrGB7DONXuDHiGxFvU183j/2ndl/uR8J8j4zJSC1cm3sXxbp1Go5JVjFxtgRy+Y5hTkpJRtiexS5zkbVjuij5ZdOyvyPewYW2a9Vc8t8LrdKRl1XEVAEOoOAEoCdwb1quyoBWDWLDB95lAAcPrZWTYUI5Hlxx6EF9cquvnVrQ6OBFHJKKF5LhqWQNBy5II0aDAkPGXzRWHMnH0dHvf3N9aYTZp1Y4w9uPzcl8vdWh1R7vKlzlwq4JBrRTvG114c+yy6dxKbdcusWsRunl48IMd1WQWr6utZiPS5dWbKmm4IZwhwvTCNGDBGvJnrp6MPfTDfcvysYecmSm6gpJzQwdFt+2WQxCfGF27fRHVsHhasPDYNuq6+ZntVTdJ9DpsMvbIAPIvrsmoWh6LwQwYW1fF10P3DKqAb5fc/GPM9MKTC+FOYyiaCy7yOpblUZVxYBWpY+0tqPZe3XqnW6gRBule66riKgCPgRUAJQvcO88ykSikAnEFACsBOo656VRSDPQZBLq7IVdImbKh4KqnIAvGrlv9Oa7U81+Iddc4yLXslDBJh1Vv/wAK1kIsB83W9twXwRgA/WusrGnLyelrlxX0ZmGTITtR2l0Thl203q/67stq6S+nvAF5GVCK4E0XrdrAkZgecjY+31zS+mmGsTjrH7KtSBOdZ9uhbs2dSAgtvT9tENP/kF7fzZCzTh2MPZmoCujyyq1RkMRYmaxjfX1yIZXZ/c5Gke4vMpzOeIdyOLWd/nG4h4vXD5xox8NZ+iP3zYGLprY48Uu8fuQ3O9lSSmjWEZP5ZIdZKOk9730vXKGFf1H9Viz5syMNA1FAFFoDcRUAKwN+2aqpVGAKYipuPLQkAJwLKQ1HV6AoFUQiV0UAcg7kG4HYfMPIaowgHQh6VLRHD65TmMYY7bxdisPX/GOPrqut0N0Zz2voasw9+4bqL22JhsHKmJKLvYutijFXZL8VFfjcRw/b2h7tWSzzUzxtHokW+hL975qJcclJJNPqwQWbd4zc6MjOQ+dsShuW5SxN2oQ9sf7LVs0pLbAyToJVNPoP/jQ+/NUhxjHVtDBLUvAtVnV+AydWBtk/6Irtxkkdmh+pkciW5HjaaQ9G70lydAN3u2wnahyM/YvefaIjY+dj3k0yn3leTeiI1JlbXd8sXkx/XU72PJmmWMqSJWZeilaygCikB7EFACsD04V30XJQCrbqHelU8JwN61rWqWA4FUQiXW0OFLF/cTannhk7p2DvELTcl7qEk9aPqEzHvYyyt3iNAYmPO+LAXT7g4L0gVdMvudLpkh/aWyceOkXZ6LzPXZQmpTzqdBHHH1usyaOwafF0XDGQIKEVNciqotu7Q2nw8rHxEMkulT08aytSldEo6LCJXckLMnjqb7H306GgUqWQsvk5sXzfDWSePsGnqG2bim1DW060aaiEX3vuH0yUj5xWvFBLFrA5sMlt57Elwxpsh60me/9L6LyZw3bbqs/WPySa9LcZOuV8a4Ksok1atq9pXKreMUgV5DQAnAXrNoPn2UAMyHm84qjoASgMUx1BV6DIGUgx53GMChFB1iZ5x6TMNBPFQLzW2c0E5I7UMB9k1JUUvBKqQTZMhqKN62rampRiiltshhzEde2VFPRi7InlqAXiqbdFwMP2M3afRgWT6WWq/rv//rLlq6dnd0+3nnnESLZp+WEec+gg6L+CIAQxFvto/77stFsyfQRZPGZHK66bNo1IGO0amfJtKwlgttR0TanaBNFKh0H0RMfv5Px0eHu/d8kQhAdzNEM6KYIRe5F6vZ6WsE1FdLGbf34pr34DpIS9RJlKbRR8Eq4ccbyY8bZT5LXd2hI1efU6J7p8fkwaWVRJfElp3GjNs/D45V1ENlUgR6AQElAHvBisV1UAKwOIa6Qj4ElADMh5vO6nEEUg4QXA1A7qDLET3ZwWxEHw1YkYLthLbIoaAM4gq6phJINj5FD2NSksjsmeIXUtmk4yR+kdcmnF4putYJXEETHEkkmV33EXr7iCG7Y66NTwoOkrGun/z1+ePpy7WmI2bfWAQgrl87c0J9Xii60ETevR41ebBpP84fYgSbe7+ZNFrTGdlec+GsCfSZc0+p/8n3/HLliNXP9BG2MaKX2wcvzxx56osalTTo4XAteo/GfCx2XXLvmzGxqHRpjdKUPVs9NuVZVOQ7TaJHmbaS7FfGmG6UuQy9dQ1FoKoIKAFYVcu0Vy4lANuLt+72OgJKAKo3KAIlIABS46PLNjREvXAHXRxOFq3a3pTiJq1jVoKowQN9ihxFD8UQhI3CS+i2WsbBxj1c+g6QHAkUSmv0yYamCc+/9GoWpYTaaCk6xA7CeWzC6QvbSGoQ2v4o7faLOaEOuXgh+vQ5J9G8c0+uR9Bm5JCTGgqi6VtXTqERfX11LGMkSGp9PFs/iZ9g/KI7dzTVK7Q79LrRd9JINUOyfu7WrWx0nZE1dA9zvuYj7Dis3LT4vM8jbu1Y3UNuL0SJfmPjvnr3ZxCzuCePOOyNTY1JUrs4u7aX2smHSYiYitXSjN33MVnt63lJ0Ly2bue8lGdpEblaTTIWkY2bm+d7oWwZdD1FQBF4HQElANUbgIASgOoHnUJACcBOIa/7ihFIOfyIFy15YMoLduywV7Jo3uVSZOYWKeOwVVQGyNVQ76qP6IrpjeRRCp4h0o7rRoq1Q1FX7kHxwjOOo7sfOVAnLEyNSMmBUjIm1SY+ApaQ4prY1dVHLvXV1nJx2rD7F/SJm7c0NJ+wG264413ScPIJR9D2wYMZloiivWLa2DppmIoD7JjnOcORgobgN409po8bFUwfl9jV9mFfNKSE5PHdb25Kc4hExI8dFyzbmCsF2twvXBSaNMLQ1hMNgi6aPCYrW7D58Wdp+brd9U7N9r0GkhMfuLQkSpJ7ZqTayffMdEssZD8KMaQxlwoulT22ZkpTlpTnZ6fHlvF9ItUhz/NCunbZ4/I8D8uWQddTBBSB1xFQAlC9AQgoAah+0CkElADsFPK6rwiBMg5doo0KDkp5wU4ZW1Cs4PQy5ChqnzJkMOTNigcep1s27mtopmAasEhxDNWDG1i907tMLOoKh34uKsmeFzpQpuCUYpOUqCtJ5JBLxoJwsSvlhbpiI0ILY+3acWY8gOfqmrkGseucfe2BPXTDfbsyokpKnEj9xEfucFFiiPjc98yL2RRfHckUMoGLhrTlsdOn3XV9fmSnNIMMvHbm+Ib0X1dfN20f5RAlFRFjdkiNMDT+cefWwayTs/3BNYN9am1Rnx+k2EniSz7S0/gxGgH5fMqOIvb5Y/ZM3LA3iziPYS+Rt+pjUp6TVdelbPlSvhfK3lvXUwQUgUYElABUjwACSgCqH3QKASUAO4W87htFoNte5lNesLmx0q6vUeASBqTI3KpDcV4ZYqmUeVL+8kQAGlxiBFmR6JTUuVKiwkdAhLqrxtzL7L36hwdo5eb9TcNdnDAeDWB2PfUC2xwE4/GJdQI2G5mus6ZGH3RZMPP1SDGTeh3TI+U6dLhr2yBxJLHdwMJOBU5ZH2Ntm9qNXmp9ROoEnNkDc7g0bt/9tuKBPWRqAdpkkc+XvPKAxGWUQ7fjv7nw9IbGSMb2GG7IUUQYzl66oYFQNI2VFtyxo2nlmy6fTFffuo2NSAz5Tux+TbVPnvGxxlC+6+b+lJB60mdBHvmrOCfv90kVdSnbdmWvV0XMVCZFoBsQUAKwG6zUehmVAGw9xroDj4ASgOoZlUUglfSogiIpL9i+A7TkUBfSNUUGl1joVGpYqszuIe9T08bSivV7WVhS8ZTUAHQ3ktRO5CK3JPOMjYrWIPP5DIifASd6CgSDL3VXcp9lui5Z11QLz23ugbVsvH244u+SCEAz301pzauPxC9D8nNYcRjEMA39YIDI0guWb2zAmmtIwkWbYi4iyXzRqXZkYOw+sglEid5utJ9NjtoprKZJki8abtmlk+iqlVubtsR6Dy2ckf09770jsX/Mdr7rhvwMRSf6CHp7TekzJK+c3TivlXZrFx69RGS2CzPdRxHoFgSUAOwWS7VWTiUAW4uvru5HQAlA9Y7KItBtEYB5gSyqZ6uIxLz6tHoehxfqrSGW3k4fLXJIjkU9PTp4kG6odYGNESNGjhDhIcGsFQfCUOQaIquOOOxNTQ02JLL6yHs0bVg0+7T6EiGCw0TymUYrdtQbrqHG212PHGAbbvj8wGwsIU0keIfkD3XDTYk+iz0f8qZxN6Zr97ERdNLagBKiCthDb0RgIuLTJb5wHffxvddMp9OOHcnWZPQRoRw5jPqA82pdjCW2dP06dU4K6eSmUGNvX31CiZ1S/Ely/+qYziIQu+c7K53urggoAkURUAKwKIK9MV8JwN6wYzdqoQRgN1ptGMmceghrJzQpB76QXEUiHd2aa74aau2O7EMa38bdz9C0caOyw3yZHx9eSLXEl6mP/Fk0ewJdNGlMQwpiXrm41MXQWtyBDpFNmxaclyRPWT4HWSWRd3n9RqpvqOYickBdktVNk8c+bp2za88fX58XskmINJEewH3yXzNjHI0e+Rb64p2PiqIgQ3LGmgaxWDP1FE1EnOk8zUVo2nL4CEyOGJaQkG5qtk9nkI4Dc/rJV7+TuwdckoyrYZhy70jtb3RI+Z7y2Wv5ZZOjNSJjdUTzPs+6dV6KTVupY9lyFHknaKWeunb3IVC2b3YfAtWUWAnAatql3VIpAdhuxHU/g4ASgOoLlUegii8wKQe+GMCph02zXkrUzQdOGRUTo7TrbrfWuZPH0I0fn5Rrfc72sagrkAcc8QIBpNF6IWHz2L7oga7seyAWeWe6E8dITbejqe2bkqYsPt9H8wa367Kk0Yqp71eUGJfai41GrRHRaLzgq88nbU6TpcKu2p41cbA/oWYqhmi7/r6dDWS4TQBKOgmDxPzq9/dkXZbNJ0ulJmpqKhF7FiEl+bqZE0TErLlPuU7Bef0x9eEjtT/WTX1+p6zNyS19/pT9zEjFsNXjpTh0oxypPtVqHXX97kSgKvdId6LXWqmVAGwtvt2yuhKA3WKp3pNTCcDes2klNOrlw0crXs7zvKhJo25SD9JFHAiRf7OWbmhaYk0trU+ytvGdHYMHyTRycIm7LJ32ju1sswFEKP3q5d/VGyC4e0rSP31y5rV93nmQI49vxHAORd5JoiRdgu2K6SfRvHNPzqIZ3WuXTDkhiwT1dcDl9Hv3UYexTT+4BiI2CWk/d4CBueamD8cIzhR7Neg7oo8OHTrUQLyB/PrSnH4a+dY3NmEQek76SDVTE88lEe21oDfXNMWk4J69eG0Tqej6DMY++exL9fsI+7q62fcSF1GKOX/y3lH0odOOyfTnavX5fLXdaa2u70jrBqYSeim+FXoO+cj3Vj0zYs+Udl4vA8My5G2lHK147pehs67RHQi00je7A4FqS6kEYLXt0y7plABsF9K6j4uAEoAV8YleIsx6/cU19cAndbFUH/BGH/X1ZWmHZUS7SWU341as38N2QkX67bxzTqkv59M1JS31ti1PENcVdMncfrp0yolZZI6vM2tecqGI7WP3hTTasQiBaQxQ5HAQIqauC6TfhvzR1V0in4snagLe/ciBLGKN2yv1/pKkldp4gpB5/qXfsiSX7W9GjlgdyViH2NC9+bUH9tBip7ELxi+cNYFQUzHWUdltGBLr0mwijI1uSFVd9R+DdPP6vfVuvnjRdQIZCeQo0nWvv29XA2ma6uOptnWx4+5NjOG6KLtzJb7q+knM9qnPXXt8ijxF9unk3CLP4TLlbrUcRf26TF11re5CoNW+2V1oVE9aJQCrZ5NOSKQEYCdQ1z2BgBKAFfCDGDFQARHFIgyHw0eVdOR8x62TJjZeCQMlEYA+f/cRS7ZYNpHi28vuJlq2rYquJyE+bfKqlS/xeZ87ocjTUOML2DGl7mFIPomvpJBIHAEJQm/z48/S8nW7vQ0aUsmgGMGN1Gd05UUqMz5ccwuQeJ+pNbfgbtkQNsCES6/GS+iIEfwPBzGZuQhjyCCJMjSNOlJ90bZXanRnis0wNhRpZ9aSyO+OQYdl0+Amb61Nzv6tfGaU8BVRyhJFn8OlCJEj/busfXUdRSCGQFXukZicw/W6EoDD1fKNeisBqH7QKQSUAOwU8rV9e+1LejgcPmA6yYGvXa5VdpRA0fVCNQBD/u5LWzQ4uoROiIiyx5ZZk7AVtg9hwpFAKcRWzAfz2DpGvrmdY10Z3E7AIRlt+WwyJuYrZk1fpGeIQLIjCV3ZJNgXIbgNdoYEfuDHv6A1O55qECMmQ6w0gJvaa/YyPxwgei9GQkKgUERnTAbOPlJfLFLfkdujrO+skPzt/J5v517Se7dMgjOFdI09/8q4XqV3gTL00TV6BwH1zeraUgnA6tqmnZIpAdhOtHUvGwElADvsD2UdPjqsRn37qhw+2oGH9MDaDlnK2qOsF0ZfF+CQvyPq6azFa9kuvr6UTi5CyiYXsKa0llcKhsb2NlmScsi1fSdUrw2plWUTmCl6+sbCT7jmFBg/a+Jo+u6jTzc0j7DXQdrnpoUzkrofu34p6fTrI8piBFIMH9SYnDXxuOCwFKLJt1BWc++1Q2ydy9QOxmYPN7XXjW5zcf7UtLG0Yv3eJhFNR21c4CLkoP/UgbVNKb/2QpwssfspRj7b977b+CiFmI3hFPMR93q7v+fLeo6n6mnGt2v/qnwHV0WOvPbSeb2LgPpmNW2rBGA17dJuqZQAbDfiup9BQAnADvtCLxJmoYOWJJ2qwyZpyfbtfgnLs187fDEW7eYSgEgp/cplk70NJHy1zkyqaYxcSzV2GamHXCqgaXbiEjX4dysIzFS9ufHAYun3fkwrN+9vuGzSTBFFtvqHB5quY3BKDUafzyCF0sXNFsSkl9p/kxJIIXxAYA7MmUjSTr5mrdDeXH08nwyIEty08DyWQDX+adeYM+vgXlowcwLN86QPc/LhPqJDhxoahhhyDKm3i+7ckdUb5RqTrHhgDw0wdQghj03ocynGWO+KaWPrjWWMDpLIQo74jT3bfN9ZRYgsN3q13fdxnu+Asp4LKbp2Ss4ydNU1FAFFQBHIg4ASgHlQ6705SgD2nk27RSMlACtgqSKHjAqIz4rgvtT3oo5S7Fulu+/glHe/dkWp+OTLs79vjkkzjR38pTbEuFjkWCw1E2v45LEj2lpVA7AVB+2YzRAJOnvphoZIMAlOtl1iUaMpjV4kBJLEJ3wkU+wHjkYf6qM/Hj+K/m3XM/T7Q257DCIfKeirAeirMffQ48/SV9ftyfZw030RIWsiV0P30jc27mtoroJ0YY6sf8iJ7ARBf/2anVkU41DDj6EmJGbfGCHrkq2x8bDdNTPG0ef/dHzdjJgj8RGMQ7MTfNCxGp8UIsv2G+4Zh+uSpiIS/6vymNgzIYZTKrFeZSxUNkVAEVAEOASUAFS/AAJKAKofdAoBJQA7hbyzbysO5xVRzUt6cMXjqyJzWXKUSUBJDk5F9isyNxUvzt/z7M/NGUFE914znU47dmQmVl5C1NZJQjxgfCyyLUZmuQRSHkw4W+TFwGcnI2eIJLGbMxiZ8nSmjmEQux6zo9sAw+0mfOEZx9IdWw80wWrbOkuJDkTD2ZMRGbfkvp1sqrsZ1zcUeNf0mT9jHH3BIrfMAB8GXMMPBPVB598fAinXl3XhRVORUAOfUW9/c0Oq75rtB9hux1x6dOi7TULIumQrFzFoA2V0AtFok58umKF1cc2X/hy7x0P+CBnse9xg40t9ruJ7QUwm6f0oHZf63dKN42OYdqNOKrMioAj4EVACUL0DCCgBqH7QKQSUAOwU8sNo35SIgF6DpRW6hw5ORVNe8xJFZdktz/4cIeASTUUPWHmICg6TPIfePJjESC9fFJ6NE9ddFeu6UUzc3xAh5kZPgZi5Z/60OjHr4hOyUQyD2HV7L4xduGp7nYADIXYdE5mGewmptNffvytLc7U/bo04STQc5kuIZESwmc7DLkY+8snnn6jVN7B6Z/T2RLr06WNG0mUrNjeN5fa8bcsTtOCOHU1jl8ztp0unnBjdz2DxD9/7Md3qpJBzk10ZTLTe1bdta7KNZHP3+QDy84JlGxsiMRF9SH1DnZHNRxK9Kn3mx55bKT4d09m+tzA2FqnqW08qk2ScFKeYbt1+XYJVt+uo8isCikAjAkoAqkcAASUA1Q86hYASgJ1Cfhjtm4f06BV4WqF7LIosb9qawbwoWVbUdnn25w7wksO6VNYYcZMS2ZbnwJcHEzPn+Zd+y0ZruaRKLMU5VA/OJRVSD/cSTGIYxK7b/n32knVRYsdnczctNSUaLkYkg4y8dMoJbN1EXHNTbG2duPseEYAfXbYhGG2INbD2vfOn04XLNzY0b3FJW4PxE8++yBKAkgYp2M+OmJTcg2usiF57PNZZcMf2YLMRd328cCON2tRCdAlhezxKCbjpz7EUVWAUI4RDzxNTQ9O1Rd7nmX1vwc74gNNMeWZhTup3Wex+TF1P4ifdNkYx6DaLqbyKQDkIKAFYDo7dvooSgN1uwe6VXwnA7rVdV0kuOeB3lUIJwpate+zQUPZ+CaqWNjR2eHQ3SiWc8gjqIy0MeWJSjiVrp+onWdMlRkykHggrxDDZQWwcsRPqqBzan4sQi/movV7K2FQcuPFSX/GNc0mulGi4GJFcCzpjCTuuqYnP5natP19nbRcb2PHJZ1+qR3ia61gLNSp//sIrdMuGvbXU4SF/suMiQwRlzN4xu/oiH1OJRFsnlKDAx+f3hojb98yL2TjUBZR0+pYQgDEi2Be5aeMgeYbE/C2FVJTeNzFbxnw2RrCmrF/1sa3AtOo6q3yKgCJApASgegEQUAJQ/aBTCCgB2Cnkh+G+kgNLr8JStu4xkq/s/dppl5hunCztIpF80V6xumDtxC926LdJkC9d3E9I1/U1SbDlDkUAcsSI1I4hou2Iw95UbxhRFoZSX5GOS4kAhA4ZabVqe0Nn3Zhul089gQbmvC82LIvSstM7Y0QTR4it/dHTtOiOHVnjjtAnqyVYS5H1de3l5odkSvExqZ/7dMA9iw+X9gyC/KJJx9HdjxxoaH4iIackpE7RCMCi95aNifTZJb0fok7qDOjm76pUXd3xrcK0qFztnj+cfaDdWOt+1UBACcBq2KHTUigB2GkLDN/9lQAcvrZXzbscgTJfmstcqwisRQ5EX7h9G92xdbC+/dzJY+jGj08qIk7T3CLylSpIYDEp6YMlbBLHXdK+ZiLKMMbXyZTzoZBfmWtogOCmO3J7S8gXKcZSX5EQLVzEF+TwdevFNR9piAY2fSMa6yauiA0AACAASURBVM4hgnOT011Xqifnr1gP5NadWw9kJB9nW+n6iIbc+uTz9chASVqpj/wyqdWuj/31+ePrnYNxzRCcvnqnIEu/vWV/kGA1kW9Yz40AhO9968op9MlbHm5Ih5ZGy0mfEXlrAErXh24xkjRFJ1MT84b7dyWTolJ/6sVxse9WyTOmF3ExOg13/XvZtqqbHwElANU7gIASgOoHnUJACcBOIa/7KgIVQaBKL+DStEsXOknaXQju2CHNnlslvDidYod+idvZKaRcZ2L3b6mYuOPtzrtcyrKUqPDh4XZeTamTKfENdPYdWNPYbCMks89G6PL78m9/T7ds3JfVKJQQajF7+mrAmXqD13zovdkSqSngvlp1kpT4hnqTI/roimljad65J9dTbFHT8zs7nqL9z71Ed207kJF5bv26D592DK3Z8VSD+gbzH+x7jq17icEuppzvvvuow8QNUTj8pfeDTYI//9KrTdGunO9JIgx9z6s8NQBdXWxCVpoSnbfpSMy3q3491Q/GHf12UZp51fWWypdCZkvX1HGKQDcgoARgN1ip9TIqAdh6jHUHHgElANUzFIFhjEDVXsBj0UG+KLDUNMwYoYe02NChVUIKtcKtpPty0UVSeVB/7KJJY8QH0VQf8o1HwwqQIL6mJdIGEzHbFiV3zPq2LfJ0325sutJHH+k/hr776NNZdBVI0Cumn9RAimFf1/5Sf8A4kGJc19xQB2Cfz5hoPR+WSKEdmNNPoahNn+yhphwxH0b0X4jQNB2fP3PuKdlSPgIu1adduQze+Lu0dmBMN9vvUghs12/wbykhVxQHEONL7tuZq+mIFI+qjiuKXVX1KlOuVDK7zL11LUWgkwgoAdhJ9KuztxKA1bHFcJNECcDhZnHVVxGwEKjiC7ivsH8ooiovAYhD2tmL1zakC2bpp0TZ38qIwCrL4aTRJC5B9ejgQTJpe9DtkNO8wZYvT6Rdqg/FxsdI4Bg5GyNKQDQ2dbsd0UebFpwnJj1dW6BJhsHY7C/BEpFuG3c/Q6ce+45gyikwWfHA4w2RgXbUpMRPfbjD15dfNok+d+u2JlddMrefXvjN7+jLtbRPt9ZfKNpUoj9HnLn3Y+r9Ax+/cvpJdPThb6br79vZlAps5Fr3o59709mxZ+r9ZuTMOy9Fz3bsAXli92pI5q89sIcWJ0TFpujfDWOLYNcN+pUho5KkZaCoa3QjAkoAdqPVypdZCcDyMdUVZQgoASjDSUcpAskISKNzkhcucUJVX8BTm23kTQEeWP0YrVi/N4hoHiKjRBNlSxW1kx3pdMHyjVl6qfuRkEicXqmyScaHOi6bxhOhNOUYeYFutwtXba9328VLGGr2nT5mZLTpiE9+pEb6iDIONzcC8PdgZp2P6cwraRoS81MuTdlsB9KMcQkyDSJCz7JQxF5qNGlK/crYPQay8pIzj6eVm/c3DUU06fzbtkVr/KU+w7kfFGJ2ienhu54qW559JPeq75lw9uJ15PPpD5wyKo84XTUnL3ZdpWQJwraLzC5BVF1CESgNASUAS4OyqxdSArCrzdfVwisB2NXmU+GrikA3vdSWJWuZB1LJ4cndzyaNcPgfuDiegnj2knUsGeb6VSqRUbZflhVN4lsnr37GBnaUYYxIrEezbdgbjLL0kcA2tqFozZAPYY2pA2upmXIjinW0DdkCNbyySL2IbqHIOaOfr8ZeyLd8HV0l+7nrphBXiGS8YNlGlvCJ+YO9b0bkD6yNdiDGnHPeM4o27Xm2gcRzdfB1FV526SS2RqC0I67PBr4fFIquW/bzJGW9PN8PvnsE9+tDORvapMhclbF5sKuK7O2Uo8x3h3bKrXspAnkRUAIwL3K9NU8JwN6yZzdpowRgN1lLZe0KBCTkVdUUKfoC3oqDTmhN37UUPUIpkRwxlEJk+OybIp9LjKTW/eJkKNM38zQHiDV/iOkcu29c0srnJ7dteYIW3LEjuJypc+fWsQtFeWFBiZ1CBAki8Yyv+WrscYKHCDtpZJ2JBLR9XeqzobqTtmx5owltnU1nZPxt5UNP0NK1u722nHfOSfSNjfuGaivWGo7M+cMxTWngKYSnuxl08tVYLNLF2XcPS2v4xe4X6XWpD5j1fIQz6k3Oq9VflO7d7eNSset2fVV+RUARiCOgBGAco+EwQgnA4WDlauqoBGA17aJSdTECZUVrdQsEZZJK0Nk+MOHfXBdaCckSw4+TGwTBdUw9N7NWEZKgKEladL7RoYx18tg8z5zGNFnKIva4VFXb1m60FRcpuuCO7Wz0n+sznL0hkzt/7uQxdOPHJ4lrpvmwMI1QTDdQH5ECP73ojOPo7kcOZMQW5Ax1Z5VEAJqIQ7sbbSrRjn3u2jZIA6sbOyIDV5PO/MU7d9Rl/pIVpRuSMdS9NosaXLzW6xcgnS6aPKYpMjO1hqLveRJruAMCctHs02KPI9H1Mu5d0UYlDHJT3K+dOZ5M85USltclFAFFQBHoWgSUAOxa05UquBKApcKpiyUgoARgAlg6VBGQIJCH6JCsW9UxZRKekgNuO/aLERmpNazK8gnTNGLauFF02rEjc7tE0aiUPDbIM8clhO3GDVxDkxhBm0XvCdO+Dbg2ochF/2EcCDk0EcFHSk5LfB3ruSSo3R3Y2FGSgu12ZI0RYD6ftRuecFGxIXLTbb5i28vnH+jse/lZJ9JzL/6W7tv+M5o58ViaPu5dDb6fpf+v2t7U8AODDLHp1r7kCE/X344+/C3BeyxGrBq/iK0juZHLeoZI9iprTNHnTFly6DqKgCKgCFQJASUAq2SNzsmiBGDnsB/uOysBONw9QPVvCQLSw71k8yofouqpb7dubTh8x4gYTm/pAVc6TootUvfwef/YdzZ0gQ3tg/EpaXh5yS9bhzJ9SoJNaEweG+SZ4/MTuyOuGSNJ0Q6lwuJFzE39dmuWheYbojDFTtJ7O0T8SnD1RWOF9o+lKdu4P+h0UOYw8KUz241GXPLU7OHaxkRc2v4RIu1nTxxNq7c/1eRObrRoiu2wWMgfJP6Ych+W8QxJ2U/HKgKKgCKgCLQGASUAW4Nrt62qBGC3Wax35FUCsHdsqZpUDAHp4T4kduqBtJ0Q2LKFUvSkMqUccMvAJbSGsd2OwYP1zq7mQA99fGmMPl0lJE3ZhJsU95DMIZIzjw3yzDHyGZsccdgbm+q3/UFfH90zf1oWFRm673wRgCOI6FufnkKf+PoWspvxugRgLALQRHqVFakJ3WOYxe4byPLRZRsaUmQlBD3mzVq6QeRGXJML1w6SeyCWTmsLs+aa6U1RsNweiMI79NqhpsYibnSeRD4XDHa/PqLll01u+kFBBGRgUB75iu6p8xUBRUARUATKR0AJwPIx7cYVlQDsRqv1hsxKAPaGHVWLHkSgygc+30F7+aWTch98U/UtQrCG9rLTTEGUIOXx9DEjCXXZ8JGmeLouGSNyQi4c6zybEo0ouVWksuaxAUcMxeR3yWauDmCsxpzRG2stXLW9ToiB5Fs8ZyLFItRi802zkNS6eUWJ35gvL1q1g+3OG+oYDHs8/9Jv2U65plGIkduQifh3yI4gFL+6bjfdt/2pjIzzRciFIvlsrNC5et45pzTB5+L/qWljacX6vU3j3Np8MSLVZyfpvSK572Jj2rlXTBa9rggoAoqAIpAPASUA8+HWa7OUAKymRQ8jos8R0Z8TEd4y30xE+4loNREtI6InCoqNoIPpRHQ+zpRENIGI3klEvyGiJ4noASL6RyL6YcF9QtOVAGwhuLq0IiBFgCNS8h5IpXsWGdcq2dp1wPXJf9Plk2n+bduyJgXmA8Lj3vlD0UZF9c5DmEEOH8kTq8cmsXGeSC3JupIxEntzurtrm3puoRpz9hys6aZ+pxDQ3PyQndCg48v372KbX4Rwkvobh+N5px7dRFabvXwRgG69QbfpiiHEb3B0wbqhqNgv3L6N7tg6WFf1nPeMor//2BkNKfeufXzpwGYcFwFortk+jb+5a+Gle7UTQeizv9uYhbOXHZ1qN1FxdYoR3ZJ7Ju8zRLK2jlEEFAFFQBFoPQJKALYe427YQQnA6llpHBGtIaL3eET7FRFdTkT3FhAdJN8Jkfn4ofz/JqLrmPJEBbauT1UCsAwUdQ1FoAACoYihvNFmBcQRTU0hS0ILcofZdhxwQ6l7V63c2iQyUkwH5vQTR6pI0ilFoEYGuX5ik0pmaqoseWq1laEL1pD6kI8Eg01+f2ioAy66yUoj+ELySwlJH5ETkzXVTlKMDJ62XKEafoh4NBGLRiZuL1/tvRjBZqfX+lKJYwQe6jx+fcPeLFIzVgMw9szgUou5CETX/rFGKbYvhXxH4ldl3VdlrhPDtcy9dC05AmoXOVY6UhGoIgJKAFbRKu2XSQnA9mMe2vFwIvoBEb23NmgFyvAQ0ctE9EEiWkBEyAV7iYimEdG2nOL/Ds0DkTVDRP8fEW0kogNE9NbaPp8noiNray8hooU59wlNUwKwBaDqkoqAFIHYAb/KB8eishWdL8XYN45LBb1u5oR6pJY7z5BrboowyCeXTCkqmz3fJVsMyYP/XrZic9NWvtROd2Ao4kkaSVdET2l0mzQyK3YvSWX14Y36fjGf5WRwU2aNHFI7ud17pf4G4u2CZRsb0n/tWokuHqGGFmYsRzD75iHFdt65J9PS7/2YVm5G8kTjR5LCa2b8QR/RZ88bR4e/5Q3kdsCO2cSsweHB6WNH80nvg5DvYf+q/pATuiekuErvKx1XDgJql3Jw1FUUgU4ioARgJ9Gvzt5KAFbHFpDk74jov9RE+msi+m+OeGfX0nPfQET/RkR/klP8B4nob4nou57oPqQdbyKidxERyMLxRPR4zr1805QALBlQXU4RSEFAQoJU+df+vLKVRdakYO2OhQxnL1lHv7fSfU2K45L7djY0TTBz7Y6ledP5UjALHfaKYhjyvSeffcmb0pkif8g+KfJLD71uqumsiaPppsv/KJeb5I24bJKhfzR997GnG9LKpZGakGHRnTsyHwWRCIL6M+c2171zFZRGvNnzOHtwwLnEJXcfYR5ebEeM6Gu4v+z1pE08zBwfWScl1yTPWlu+lPGhsVizCFGfy3kLTkq5NwtupdMTEFC7JIClQxWBCiOgBGCFjdNG0ZQAbCPYka3eSES/IKKRRPQjIuonamoehyVQm+8/19aaQkQPt0gF1CBcXlv7r4joxpL3UQKwZEB1OUUgBYHh+kKfcrhOwdM3liOtQjKg06wbPSUlbULySoksrCHxjZT1XLli63OYFdmPwyVlPTsyi6uz5iOwFs4aIs1SiMuM1Fq8ln7/eilIMinHrh42IebDNE8NQKx11uK1DUS025WYw9QXhWjqWIZwkNQAfHDBeU21+wZWP8Y22vDdC3Mnj6EbPz6p6fKa7QfYxiNmoEs+hmp5HnHYm7LGPYjchM6o+Xj1rVsbbBq6p2P3hy18r0UAtvv5XMYzfjisoXYZDlZWHYcDAkoADgcrx3VUAjCOUbtGfJiIvlPbDHX3bvBsfFYtOg+XW5Wei7VPJ6IdNRluIqLPlgyEEoAlA6rLKQKpCKSQIKlrt3p8CqkiPTDjwG4IsLxRdvZeX3tgD91w366GenFI2Y0d8Mu2S2w/11bSw15eG2C/FB1T5Y/5XozQ4+aH5A3V37tu5nhyG1eE0rZ9hJavA67x2TK7NfvIMDSqmTXxOC+8eSM7zYLGLjsGD9L1ViSs6ZbM4caRlZyAl089gS4/68SsoY77yaIdV21vIOjsMdIIQMjZh/qQrw3Vh7Tr+OEaPgj69XUhtvdMuT+6rQZg6LlR9r0eexbodRkCahcZTjpKEag6AkoAVt1C7ZFPCcD24CzZxU7/RarvQ55JSP99nojeVksH/mPJ4jnG/CER/XttHiIB5+dYIzRFCcCSAdXlFIE8CEhIHMmYPHvnnZNyOOb2aMeBGfXTBtbsbNjeJhJiOpSJuZTQM8K267An1TFV/pBfxXDn5sbwCJFQMeLO3g+14j66bENTCjjq0CEFN0QkxmRMudfyEoA+GdDNVlLTrh4td9u2hvRd6L9p4YxMBZeYd+tp4qW2r2+IaDOf1Gg7GyuXrLN99q6tg2RS9iGj27nYxRwNSpZfOoneP/ad3i7E9hzp/YE5MVKtjB80UnzIN1Zy/0nGlCGLrpGGgG0X3GfzZ4yjz/8pKgTpRxFQBLoFASUAu8VSrZVTCcDW4puy+r8Q0f9Wm4AGHCD5fJ9HiOh9tZTho1M2SRiLRiAm7fcqIvofCXMlQ5UAlKCkYxSBDiNQtcNYWUQHd2Auc203hdKY0U4lBOGzcfczTc0FyjZ5Hr1aYfcUQsPGII/8HIZ515EQkBzhK0ndNXK6RJYtP5paLJp9mpfkMbg+OnjQSxL6/J0jhjhCU5ICDJk5v5F0SeZqB7oYfGPjvqyeoSHluM7YIOKutRrqYCzSoPvHjKyn5drr+my7ZG4/nXjU2xrm2DLaEX2w88enHE+3Mg1HXD+UNmAp+xlQhfVS7r+8z4oq6NnLMly18t9pzfan6ir6Uup7GQPVTRHoZgSUAOxm65UnuxKA5WFZdCVE/E0lohdrnX5D691LRLNrA5Cz9krRzZ35h9XqEL67tvbJtS7BKduA4At9Rpv6hfv376fjj48NT9laxyoCikAZCKQc2Hz7lX2Qk5AxeXUva+1QSuimhUN1zFpBsHF6S8ihdtiuqL5F50PHvPaV3gduyrddf89gLE0nNeMRNXbP1dOIqz2IMVzDEJfs4rDD3C/euaOBULNTbO20WJBqA3MmijtOu/d8DD/uuu2TGdl2qLEoMnBcdukktm4fSDbU4AO5GSJFsUdMNiNHVEZEHgYaj2Ad2/ZlPxfzPvPaOS/v/ddOGXUvPwL4wWrW0g1NA7imOoqjIqAIVBMBJQCraZd2S6UEYLsR9+/3KBGdRkRPExHIsdDndiL6WG3AKCJ6tmQ1kPKLJiD4IAoQTUBSP1YCTniqEoCp0Op4RaA9CBQ9sJVB2riaSg/seRAqa20fWWA3hZB2EM2jh5kjIYeKrC+dWyauRVIZ88iRSqC6xI7kHggRxhdNOo7ufuQAS9RJ9OHGgFSkQ4eiTSnKJKny1FCM+RdqEs6/bZu3y7EEH+xRxEa2jHb6MTD+wClH0YN7nq3XBPzSxf0Zierbr0y8Y9h14rrUHj7ZUvBJGdsJLLpxzxXr99DA6sayFtBj0ewJNO+ceIfwbtRZZVYEeg0BJQB7zaL59FECMB9urZi1h4gQabefiBB5F/p8i4g+URtwAhH9tESBLieif66th27Ef0REL+dYXwnAHKDpFEWgSggUObCxxENfH90zfxpbiD9Fb8mBPWU9e6y9NlL7rp05PrmTq0sqgG9ZMHMCzTt36JBUlFiV6FbEdpL1U8a0Q1+pPCm+UxaBGiMjOFvBZ7515RT65C0PewkuCa6+MRxerU5P9eHA6g8BnVp+tswmmm7dj37ujWSU4GPWzGMjDkNES14y5QT69pb9GcGKf18x/SSad+7J9a7AHPmfp1uz1Oc7OS4PIc7JW+S+NcRrJ3Hohb01ArAXrKg6DHcElAAc7h4wpL8SgOl+ICa2Akt/ioj+yblehQjAPyGi+4nozUT0HBFNr6UCp6NEFMvp1RTgPKjqHEWgzQikHLxs0XyH71BHzxTVYgf2lLXcsajnZor7u908JR08faSCkfmIw94oaopQRIcU8qPIPpK5rSYjU31BMr7VMru4pdTOQ8TNRZPGZEu4ZBIIp+WXTaaxo96WpQ1zviaNAJTYtqwxrv6fmjaWVqzf611+1sTR9BdnnZil+uLjq2VYZqStWwPw0KGhxh/ux238YmyC5h+Q87IVm5vmuPUiQ41LysK81euUFemYci+mjG21/r24/hdu30Z3bB2sq6Y1AHvRyqpTLyOgBGAvW1eumxKAcqzMyFYRgJ2uAfh+IlpHRIfX6hCi5V7zW2o6Xr4Z2gSkPCx1JUWgpQhICBNXAF8aLMZV+XAbktvomEd+9zB84Rn+1M4yjFmlgzBkWfHA43TLxn1N6ZBFdc1LUMf2jRGoee6J2J7umrF7CJFN+JhafnZjCttXOV+z56WQ2jEdily39cc6LnnHrc3Jbq8TihDEeql2tMc/8+tXaPbSDQ0kYK1cIQuDaUjy5ft3NUR1uoShmdzqiMwitorNLfP5E7sXbVlSxsZ00Os8Au1qXqX4KwKKQPkIKAFYPqbduKISgOlWm5A+pWnGz4jooPPXTnYBPp2I/o2Ijqo1/fgoEX2vBD1DSygB2GKAdfnhhUDqQbYd6Aw1EthBv0eojPOp6uFWmjKZIr/vMHx3oLlDGfZpFTmW4muNKdWN6ZBFdSyTZHBlCa0dI5WK6mXPD3XHRWTZpoX4rY7oB/ueo6tv25YRrO4HxBPnayl2LFMn6Vp2I5LQHJuQ53we3YLdCMEySGms4Xb7BpmHF2uk/3IfyHrt+eMbujXb/zZz8vzIIMW1HePKJOJS7vOUse3AQfdQBBQBRaBKCCgBWCVrdE4WJQA7h727898R0X+p/fFsIkJEIPv+SETPE9HbiOgBIvrjgiqgKNV6IjqWiH5HRH9GRHcVXFMyXQlACUo6piUIVP3gm6p0q4ieVDm48YgW+OiyDWTzElU+3LYiArDMw3CqTcr29RRfa/VhPBXXVCx8ZFIZaaUpsmDsXdsG2QL8l089gWa/7zh6/qXfsh1xjb+kENapPiYZn6ovCLsdgwczoowjNd09Tedfn20w3pCAIHAXrdreRNKlPpd8/jfvnJPoGxv3NUT52fLaXYqRwlxmV/AUnCV2yzum7Hs/5bmTMjavfjpPEVAEFIFuREAJwG60WvkyKwFYPqZ5V/wwEX2nNvk6IrrBs9BZRLSpdm0JES3MuyEN1enbQEQnEtFrtcYitxZYL2WqEoApaOnY0hDotcNB2Qet0oC2FuoE5kUOwmWn60KWs5esayAyYmRDEflbYUOsKfE1W25fvbOyyCiJPAaLvD7o2iGVdORskUcWyDF1YC1bcw57oK7fa68d8take2jhjIxo6sQnRd9QxKNPdnMv+fzNJuSA06FDhxp+kHDJuQ+cMkoEU8j/sAAXlRm674ve8yk4ixQsOKhseVLwSRlbUE2drggoAopA1yCgBGDXmKqlgioB2FJ4kxZ/E85XRDSy1ngDablcEsk/EtF/rq08hYgeTtrl9cFH1yIIx9f+9BkiWpFzrTzTlADMg5rOKYRACmFQaKM2Ti6DkGiHuL4DWSsOamUcPF25isgJeRau2l4nHWKNUBrSZkf00RXTxta7iLbDVr49Yr7m4t6O1EaJrcu874uulXd+jACEzXz15xbNer0Ddbv9J0VfSfQtGqCgooCpo2fXAOTmcw1PYkRiClHq+h+6+faPGZk1Jykzsi9mtxScY2uVeb3Ic7NMOXQtRUARUAQUASIlANULzPuiIlEdBOw04L8mov/miIbUYKT9vqFWsw9de7mPIQ6fIKKxzIAjiOj7RDSpdu3zRPQPbYZBCcA2A67bEcUIjG7EqKoHPwmWEvJGso49pmp4sKRErXYbRzT4SBDUexuYM5EumfLuVEiy8WUcxGMRT1z6JQgRjqzJpYQzyeiETrfoeGtIF3ftsu97jug83SJ9Qrr5ZLnp8sl0xGFvStbB3Qspwd/e8tOs7iY6y147czx95lxU+ujMJwX7WP1NO3rO58+ubWLdhA0qIAoHLu7PdX8ZWR6tpSz/7rVDWaMjNGnB/Vrk3pPOTcG5M56guyoCioAioAh0GgElADttgWrsrxGA1bCDkQIdeH9ARO+t/eFrRPRtInqZiD5YS/d9e+3fHyCibR7xQwTgm2vdfjEfn5VEdH0EhheJaG/JUCkBWDKgulwcgaqRQ3GJZSNaQaTJds4/qlW26ORBmDusp8oTIkFiacM+a5TpH761QnqCmHObMOT3nKGZKTq1wteMrVGnziY43QgwV09OFrtxhI+0+9oDe2jxmp1B2Ix/YFAMb9tXJePz2stHgC+/bDK9f+w7G9KSQxGAKZ2KXd3cRh2uLngRXn3NdDrtWCRg5Pu0wsc67eP5kNBZioAioAgoAlVFQAnAqlqmvXIpAdhevCW7jSOiNUT0Hs/gXxHR5UR0b2CxEAGIiMBUMg8dgn3RhhKduDFKAOZFTucVQiDlUFVoozZPlkaKtFks73apxJhU7lYcxCV7+/wqVZ5YGmRq/bzU/SW6cr7Win18skj3suVsRefevISVm+LN1aSz03ZjPmFwWjhrgijaz94f5CM+aNKTQrJJ/MSMSdkvb3SlzydRh+9zt2711vwzMqbeV67+sedZ6vNZ6uO2HN3y3ZaKRYqv6VhFQBFQBBQBPwJKAKp3AAElAKvpB+jw+1ki+nMiAiGI+oD7a8TgUiJCam/oowRgNe2qUlUEAT2AdN4QqQfcFJvlPQin7GEjGNMlVR6MX3Tnjqbup3kiAGPERJmekKpn3r0lOnGynHfq0WxkXF67p6SsurqaPX3de0HM3Tt/epbaHOvwm0JixcjEPD4msSP2lTbFSLUHZ2vI9MU7d3g78doyI/1304Lzgk1SYjKxkY4j+mj5pZNo8JcvZ92M3dTgEG4SH+fmx+SU2KqVY9r1jGilDp1Yu+p27QQmuqcioAikI6AEYDpmvThDCcBetGp36KQRgN1hJ5VSEWgZAtLDoHScS8rF0iDt8Xn2MPMlh/XUAxzGr3jgcbplw176fYHorBg5WbZxU/XMs39Mp9j1suweI9OwDyLLQinQWOPsxeuymn3uxzT1GIELfUNRer6PlLiLkZZGZmkn3BT7Se4T6XrGz1D/8cLlGxuIvpTGH9gPXYLnnXuyN21aSib7Ih1dnSS2euxnB+mCZRsb/EIyT4pfJ8ZJ78t2PEM6oX9oz5DORb6bqqanyqMIKAKdRUAJwM7iX5XdlQCsiiWGnxxKAA4/m6vGikATArHDnvTQWATaonvgsD5r6YYmvQFZLAAAIABJREFUEdYUrCuGBWP4SPTuxQNkSCcp0VTU7sDeloMjeiRNUCT1/fCyNmJEXxYVCiLowjOOo7sfOZAUVWb8yW3WYsvdSpKpDLxdzFEzkSNPJfcFxqC5zrUzJ3gb1XAy2zUb3bTpeqTjrVsz4t73QdOXWROPYy9zPtWq9GwpTmWMk9yXvfisimEX0rmseyYmg15XBBSB4YGAEoDDw84xLZUAjCGk11uFgBKArUJW11UEegiBdjSXkBxMQ5AWnd8Oc5VBJLZDTm4Pn+yGbMEcu6GE9NBclt2MHN977Gm6c+sBeo2G6ulde/74euqn0ctHsK14YA8tuW9nFuWHiD+s4X6WzO2nE496W71TcF6b+gjHdnSajhE8IZ3q5Npt25rS422suAhA6IbGI246bsxGkohJ16aSOb6uwz7CEengRZqUdOretfeN3Zex61XQoWwZYjqX9YwqW25dr7sQyPtd0V1aqrQSBJQAlKDU+2OUAOx9G1dVQyUAq2oZlUsRKAmBMl46fQck++CeGh3jyhU7hMXgKDrfXb8M3GIyS4m2Tsli5AsRRtJrIFuumDY2S/M8+vC31FUvy26QY+Gq7fUU3b4+ogUzJ1D/mJF02YrNTVD7Gk4YrJ949kVacMeOpnmhqLEUe/tIBW59qf1TiD3IyqXnS+3J6YqoPLuRCcaYGoBclJ7ZH/8N2YjzEW5/26bSOYhevGf+tAZib832A3TVyq1in0mxexXGlhG5WwU9ypIhRvCV9YwqS15dp/sQiD2bu08jlbgIAkoAFkGvd+YqAdg7tuw2TZQA7DaLqbyKQAICZb50umvZaZVGJGnqok+uovIWnS8hvBLgTx4aa6SQSrImC8BMCB1+MdxNZXV9APNjdRSL2g17nL14bVO6J0jHe66e1lSfTuKnqSnlUpLOQCwlFaTYxNaTrBOqecfZ2nWXa2aMo6knH1WPjsR1CS5cNKRrI1t+2NXt2szZ1NX5Y2ceT7duRi+3xg+Iy8VzJtIlU96dpZMvWrW9yZckPlPG/dauNUIRvbF7ul0ytmuf2L0DOST3T7vkzbuP5F7Mu7bO8yMg8S/Fb3ghoATg8LK3T1slANUPOoWAEoCdQl73VQRajECMuElpzmGTFtKoHZ96sZfhooeUMuZ34gDM4YKUSUJ9NavzRLuJiFB0DGwci67j9DLdde10yiJ2C6V7IirsyWdfaohEA3mNyEA0BrGjEW2fjUUF2WM5cjy2voRUiN0rEnkXzZ5A08aNipKgbgSlvTYw9NnaHpfHN32ReotmTaB5557S8BixfWTdj37ujS60J9lz8Hdf7UXIfjdDFmOOL1W4xY/wji3fC2RXKngSnYs8o1LlKXu8RL+y99T1hhBI+S5RzIYHAkoADg87x7RUAjCGkF5vFQJKALYKWV1XEegwAr6XTnTb/MbGfcmNC1x1UsgJCVHhS8lsN4ydelmX1CwzWLQTqxiRzBEqC2dNoM/UyBufXki9HJjTn0VdFf2gdt/Amp1Ny4C42bTgvIzkM4f3RwcP1msChiIqpf4dSjUFgXvF9KHutj6iMUQqpPhiWA6+SYfxo9BcQ+qFyDMb+FTflNQXRZfh5196tYmwzUPIfOH2bXTH1kHW5UCWDqxu9qOy0r6L+nk75+fBtp3ytWKvvDrnndcKHbg1pc+ydskz3PZR/IebxeP6KgEYx2g4jFACcDhYuZo6KgFYTbuoVMMcgTIOFGxEGUKvDh1qSG/LE7VjzJMnqqDqL8Odkq+qEYCwdcjOHPlm+5SEXPKRY5LHgG99O63TrJNqW4l/S4jbvBFkvnt4+aWTGhqucPdjDDvbRlKSNk8aro+QMJHEHLEYat7ypYvzk8bA86zFa+t1Im3ZfBGARZ6PMRvo9e5HQPKM6LSWKT8kdFrWXt2/G/ykV7Gvol5KAFbRKu2XSQnA9mOuOw4hoASgeoIiUDEEynxRdNf61LSxtGL93iaNU6N27AXykJVl6tgK87VDPg63KtYAtMkzLm1cEsGFqDvTXde1VxHfw1opzTTyHIRj/u3r5uvqCULyoYUz2EjA0B62T2ANfOxGG24EJda6a9sgG8lmOhtzDTncSE4uTRt727LetXWwbldpfUqJj3P1RQ2eRQg5X3MPwLpk7us1AH2NS1rxrNE1uxeB1B8UOqVpt8jZKXzatW/su6Rdcug+nUdACcDO26AKEigBWAUrDE8ZlAAcnnZXrSuKQCte1O2XTqjdifp2HNxlvQyXtY4rY6vWxT4hgpHbt5WypN4Kriw+n7VJHJA2V33wFPrquj30+0OH6lsWIXNsYlLq00XuL59dfDXlOFy5VNIY2Yx9f7DvOTr48qv0xVU7vNG7sfsc8oDUu9KTkhyTw9WnIRqwr4+unTm+nvbt86kQ/pgTqy9q1k0ljQ02vs7OS+b206VTTqyLXaX7LfX+bNd4xai7arul3t/t8iPdRxEYjggoATgcrd6ssxKA6gedQkAJwE4hr/v2NAJ5D0d5IpRSgeylg0AjCRGvt5aKVSvGFyGhWiFPypo+33H/fu354+t19sz6blqnJGJMeh+l+HTKWCO7r8nH8y/9lq5auVUMIQjA9499Z53owsQQeemSbDZ5apNhbpMTpMnis+jOHQ0NZPC3EOkawjtGMErIXOnzjbtHbD96sFbXUQK8+4xA9OTrFPQQKeqLzJSsPxzH5LmHehGnbnuWS5+nvWgr1UkRqBICSgBWyRqdk0UJwM5hP9x3VgJwuHuA6l86AkUOR+06UPTCQcBHEuStt1a6IzgLGsx9pFFqVFOr5XXX5/BGI4975k8jdPO1fQqRXL7uwOi8K+lAnXofmf19DSNsfVL8P0RGockHyCSrSXNGsP3TFWfSJ27e0kQ0LZg5oaEBSSglHzjFogtjdesQOcgRlKm+VlYpgZTnm72nTf6l1ADk9gPh11frrF3VZ0W77+2U/VJsmLJut45NfU51q54qtyKgCJSHgBKA5WHZzSspAdjN1utu2ZUA7G77qfQVQ6CMw5EeKGRGDTVfkEQjyXYpZ1RZzRPKkSa+CkeQ+fAuo9mGhGyU2LTovZOit5HZJpTsqEbIsmjV9ixlF0ThtTMn0Jfv35V13zYf/J1qZJS93r3zp2ddbzkSFfvZNQDf8dY3eEk+jkRMjQBkid8CzYTcLrxzJ4+hGz8+iXXKFFKXWyBUH/KIw97U1FU4fmfoCGkU53BCKuUHheGEi+qqCCgCPAJKAKpnAAElANUPOoWAEoCdQl737UkEyjoc6YEi7h6hyCzMTo1yiu+YbwTkPHvJuoZUzIw0IsrIIUkqbL6d883ykWipaZlFyLiU+8gmiS5cvrGBYJOQhgalPHqbuUjt5QglSVTkOe8ZRet/8kyDsUJdcO++elpGDoLcW/ejn0fTfKV28I3z2WLeOSfRNzbuy/CW+nAZP5CkeHW790uRrVvHKqbdajmVWxFQBKqCgBKAVbFEZ+VQArCz+A/n3ZUAHM7WV91LR0APR6VDGlzQjrKyB6YQP62WeGD1Y2znZR9p1Gp5Quv//+3dDdRdVX3n8V8CKiIUpWlGBREEBRRaaGmAgFRxahXUgVpbhL7JampHK850tShRp9URUnTGUeg41rjUqQrYNxgXonZKWtGAIB2wAcUKGk0Ri2jBF9AKZNZ+ODfc3Oeee/bbOXufvb93ra4Kz9lvn/8+PLm/nJeu/fuQt3kRxfRT1B7qcV7g6htkd81jXmg3uTJudn1dQbAZy9wq+6qLb9wppJ3eQ7NXrfnsNdsr6SZ9m/FnX6Qyfftr6y3wK6RzT33ojbaTT1cdFnmbPmZvRTa3zl5zzolL3dvczj0Zv+3299edfIj+wxH7zH1Dcuj5YBuAho4zr32X+2wb1+P7mLNNnylNbebHMQgggEDOAgSAOVdnuLkRAA5nzUg7CxAAsiMQiCzAl6PIoB3dmS/NG6/6st67eetSgGN7NdIQs1y6+u+8K3d6c6sZdxKgrN5ztyGmYT2GzZV3n7/jHr3ggk8ve+6dy4sZbIKprvOo6wpQM0ZXEDzvOXPTWCY8XPQsPte9ZvssvckcJuPPC9kW3d560uFPtK65cfw/N96ucz96y7I2k/DUzHv9pVt21Hzebd9tA3bd/j5p52ppvUBpx/MpbZ4P6dLvomO79u9sW9fjY83Tt5+xhJW+66MdAggg0JcAAWBfsuPqlwBwXPUqabYEgCVVk7VkI8CXo3ilsLW0Pc5nZr59L7p98nUnP91nKr228bnyzje4sQk8Frm32ZoXk5grFLvm1RUgTsLDthea+F61ZgLUzbfepUOf8GP6zn0/0qsuumFZQGwTXtrWqiukmjyncPa46fB0XpDdFa6a/ubNcfr290Vjxt7oNvst1piutXE9PtY86QcBBBBAYHgBAsDhzXMckQAwx6rUMScCwDrqzCoRGKXAkF/a24BC5jD3ts8V0jXrn9PL7Y4ximy7Xt9QtC0YsgmUptfXFppMPyNv0RWWXS+RMbffHrbPXjJXjc1e8WhCrM941HDeFYemL/OZfZOwzdtubWs1b18Yv2POu3KncSfHzYani64MXfRW50VXKd5+930LrzqMsZcnfQwdsNlcSTu9PtfjY9rQFwIIIIDAsAIEgMN65zoaAWCulSl/XgSA5deYFSIwSoGhv7S3hSSzzz9zDapCQppUhbMN92yPm11HrMAjxLYtnL3w9CN1+7/ep/ObN/aaN/WacG76qYc+AeCiKw7NLeEXvvQI7b/qMTte8GF7e7hvDa7Y8vW5bw9+9XMO0hnHPHmngLrtXFz0jMKuoNf8PPTcsj0/Yu032/Fc/9vlerztPDgOAQQQQCA/AQLA/GqSYkYEgCnUGdMIEACyDxAYoYDvl/4+lxp7TkN/aZ9nE2sOsW36rKNt37HDN9dgdTLPLttFP5+3hhMPXb0smJpn0vVyEdvQc3Lcov661mhbs+nj2gJA83Kaec8QnLV6zfMO3hGSTvqdV8PZZwCeedz+WnfCU5YCxpA95LLmFAGb7domtb359nt2eHbdvu6ydo5FAAEEEMhLgAAwr3qkmg0BYCp5xiUAZA8gMDIB2y+WQy6rjzml+NI+a5bDHIaso+1YMVym3+BsrrKbfXPtornYBmI2+3K2r0W3Bi8KurrsFl0BuCj8tFlD19jzfj7vFuCuKxunrdqejdj2NuilF/V8+itLzzucDrhsazm9Bp82IfvNx9e06ZrnbG0nt52b26ptrwD1nRvtEEAAAQTSCBAApnHPbVQCwNwqUs98CADrqTUrLUAgRvASm6HPOfUVfrgY5DAHl/kOcWyMKyOXApnLblp6c7O5BfbcUw7TaWv265y+bT189+W8dksvrjAvFwl8y/S8ZwAuutrLdw2diM0BXTVYFGC5zK3r2K6gbHo9tvWfNehaq61ZrOO6TGKNk2M/LvWenX9I2xwtmBMCCNQnQABYX83nrZgAkH2QSoAAMJU84yLgIRAjePEYdmGTvueU4gvf7Ji+c/BtF7tGsfsLDS9827u0C9mXbbcGm6veQq/OmuwJ83KRu+/90cL+QtZgW/O2PWoTtNkcY+axaB1f+9a9ev1lN+l+i3DVpf7T6/dtZ2voc9wQtfWZV99tbPfMvHmEtO17XfSPAAII2AoQANpKlX0cAWDZ9c15dQSAOVeHuSEwI5DjF9kc5xSycWJ9yYzVT8haYredDos2feFO6+Bmdh6+4YdLOzPXYzdsWrpqb/KZd6ttWwCWQ3gb69xyXYvLuDZ9t/Vn3tj8ogs3L4V/i2o0+ZlL/af3nG+72OdP7qFkn+s1fbvsq9m5hLTte130jwACCLgIEAC6aJV7LAFgubXNfWUEgLlXqKD52XxRLGi5vS0lx2Apxzn5FCDWl0zXfsZwbvhcFde2rs/fcY9Oesenl5Xoilcfr1V7PEptV9othXrnXbn0HLmuwMjMd/2lW5be4Gs+5jbe8049fKfbjH32baxa2fbjM8dpWJ/2fQRmG6+6TRs+dstSPSa3Pe/347vr9I3XLtsHbS9EcT2vJh37tvP5b4hLG5/auPQ/1LG2ezlkX4W0HcqBcRBAAAEbAQJAG6XyjyEALL/Gua6QADDXyhQ2r1K+6ORSFtsvXEPOd4g59T1GrC+ZLv2M4dzwCVAWravNZ90zD9D7Nm9tvR3UJtQze37efM2LRq5Z/5wdL1eIvSaXc8215r773meNbX6LXlTSNb/p9e6yYoVe8/yD9dsnHOh1RZir3aQus+3MW4yfsc9ewbd0u9R93rFddqH9993epR6++9FnT/a9bvpHAAEEfAUIAH3lympHAFhWPce0GgLAMVVrpHMN+UP/SJfMtHsQcPmi6Tt8rL1q24/tcb7ridXOJdC0+bLeFtCpedHGZN7TodPcNitX6JpzTlz2xlSb+docM+0Xq1ax+pmd27yrJl3XON2n7fk2e9wrnn2g9txtVx130Co9/Ql7dYZ8tuPYrLdrv0/Ctptuv0dv+fgXO587OPZwrssj9Oc+e9mn3pN5hrQNXSvtEUAAgVgCBICxJMfdDwHguOs35tkTAI65eiOZe8iX0JEskWn2LODzRdN3SrG+ZNr0M5Zzw9XfZl2zPi87bn9t/NRXlpVtcjuoTZ+TxjbztTlmejIu4y/ae7H6sQlFXNc4O++uAGxe/9N9/OKR++iXjtq38zbfrnF8z+Xp/TAJSM2/W7thU+dzB23O39B5jb29714OqXdI27F7M38EEChDgACwjDqGroIAMFSQ9r4CBIC+crSzFgj9Emo9EAcWK+D7RdMXJNaXzK5+xnRumEDkdZduWXr+nrmd9tyZ5+lNW5vnvZ17xS078Xe9gKMrmHG1sglwbI5xCRVt9pvrOhb1adOXyxpt5j99TNt5OX3MB39rjX7zvZ/tDNxsx+46p2b7cQ2aTXsbV9v5lnwcTiVXl7UhgEBfAgSAfcmOq18CwHHVq6TZEgCWVM2M19Lnl9CMl83UIgmU/EVzLOfGUgB42U1Lb9XdZeUKnXvKYTu9UGNRUGZ+tv6kQ5ae+7bo02XR9fPZvm3CIptjJv26jt+21lj92AbjLmt0OWW7rgA0fb3u5EO056Me4f3G6On52LhN1vrY3R+hrXd9X6+66IadXhpjwutFt5qb8WxdXaxKPdamJqWunXUhgAACPgIEgD5q5bUhACyvpmNZEQHgWCpVwDz7+hJaAA1LsBAo+Ytm7ueGSwAbGp50WXT93GIrBR0Sa/wY/bjUJWjRCxpPn5fzDjNvdp48C7Dt7c42c7NZa9dcJuN0vWzGZiybOY/1GNe96Xr8WF2YNwIIIBBDgAAwhuL4+yAAHH8Nx7oCAsCxVo55IzCgQKoveLPjpprHNHUOc3ApfYz5uoR6tYcnLrUJPdZYb7zqy3rv5q1LV2aa26zf3HJlZuhYi9pP9tgHr/mqrrjpGzsONc8AfNuvHBFl6K49aHM1opnI5FZ0878XBZIl/4XDooLUuu4om5ROEEAAAQsBAkALpAoOIQCsoMiZLpEAMNPCMC0EchFI9YUw1bg5fTkODe9iGbqGer/34Rv11zfc3ksQNMR5Eeo+xByna2tuaz3z+AO07oSnLHsj8hBzmR7j83fco8233rXjLcA+48/z79qDNs8jdA1Ix7APfHzb2nQZxxyLvhBAAIFaBQgAa638zusmAGQfpBIgAEwlz7gIZCbg86W7ryXk+EU09py6woXQ8M4EMS+8YLMe2L59R5nmvYjDtoa284ntNG9+XXa2a5p3nO06Q8YIbRvTuE9Ln3Uu8l/0s64rAFeukC4/66HbkfnMF+i6yhI3BBBAAIFwAQLAcMMSeiAALKGK41wDAeA468asEYgmsOg2wlRfCFONuwg15py6QqbQgMf0v/7SLXrw4exvx9IuWne01h64ymv/2IRFMZ3mjddl57WwplGoe8jYLm1jGfdp6bKeybE2/ov2YNczAEP2vs96xtbGxn9sa2K+CCCAQG4CBIC5VSTNfAgA07gzqkQAyC5AoGKBpTe7Xrplp7dkGo7p52St3bBJ908lSSFXkdlS5/hFNNacbPpxDXimQxFjPFuzibtt7WyCvrZazlufeWvwhS89Qkftv7f1LarzwqkTD129bG22a7LZe67uNn32cYzNHuoaN0YfXWO4/rzN/51nHKnH7v5IHbR6j879Y9Z1/dZv61UX37j0XETXve8659KOzy0ULs2X9SCAAAIEgOwBI0AAyD5IJUAAmEqecRFILNB1y9zkaplUXwhTjbuoLG1zcgnMbEImc/vuSe/49LKpTN6oOv2D2Tm97Lj9tfFTX1nWdpcVK3TuqYfptDX7Ldx5Mdyn+zC3XpqPyWJsn8HWFk5d8NIj9IoP3bBs/mavmnDI5i2zi2oVGoq57IPQ0z+0Tjb7MHSOru3n+Zv9s2LFCueXnIT6uM69pOOH3MclubEWBBBAwEaAANBGqfxjCADLr3GuKyQAzLUyzAuBngUWPTR/9qqqVF8IU427iH52Tq5Bg03IZBPOtF3pZF4IoSYwmazD9vlnNnOz3ZY75nfRDTtdYWpzxd6iK8HOuvjGZVeknv28g/WWj39x6d8vChltamVzzDwD33a2nvOOCzk/XGodMo7r+mZfbmKu4Zu+ld1m/0zGHHLeruvkeAQQQACBOgUIAOus++yqCQDZB6kECABTyTMuAokF2q4ANLdrnntK95ViMac/74v6GL68u4Qo015dYVFXv13POlv3zAP0vs1bOwOx2RraBI8udfftb9H6N33hTr3+spt2rO01zztYf/yxWzpDxi7T6XW5vsnWpW8Xv76P7dqHZnybY2LPc3Lu333vv7Ve8en7HEvCwdjVoj8EEEAAARcBAkAXrXKPJQAst7a5r4wAMPcKMT8EehSYvdrmzOMP0LoTnrLjOVtDhHDzAgaz5OmQ581NIDnEfFy4fQMuM0bXWhbdbtz2jD/T7/TzG21uiZ1eb+wgK6S/rje+Tta28aovz73lefa5cba18gm8bPt22VtDHdvnLdGhawjZP4vG9qlx6FpojwACCCCAgBEgAGQfGAECQPZBKgECwFTyjItAJgJtAcAQX5LnfcE3VyBq+/ZlV3SZK73Ot7jNc0jWvgKKyRrm1abr1u1JWOrrELvuIf11haTm58du2LTTyx4mf6gy2+iBqecO2rxAxLeevu18azRUuxyCzZD9M8+p1FoNtScYBwEEEEAgTIAAMMyvlNYEgKVUcnzrIAAcX82YMQK9Cwz1JXlRmDW7SBPo+D4LrE+w2AFF11znhqYrpAtPP9LpLbuLxukK3rrmOPvz2P1N+m/bP+YPVQ+///XhqyJnbx+eDUtDAq+h94FrDXyOH+q/A11zi7l/QmrcNU9+jgACCCCAQJcAAWCXUB0/JwCso845rpIAMMeqMCcEEgsM9SXZ9gpA8wbbB7ZPRzoPAU3eVJyYq/N23tjzmxc2mSvcXG/5jT2vWP3ZBj7z9s9sUDyZ02Sv9HnLq+28YzkN0U9pwWYuoeYQtWMMBBBAAIH8BAgA86tJihkRAKZQZ0wjQADIPkAAgWUCQ35JtnkG4PRbXieTdXkbaIklng6buq5sG9P6XQOn2eND94rr+GOy9Z1racEmNfbdCbRDAAEEEAgVIAAMFSyjPQFgGXUc4yoIAMdYNeaMwAACQ35JnhcwzP67IeczAG+0IYYMa6NNuqUj37XE3isxA6+YffXtP9b+fYxt2tgcM1Yz5o0AAgggkEaAADCNe26jEgDmVpF65kMAWE+tWSkCzgK5fQHObT7OoD00GOp27R6mvqzLmGvJYa8QWve/a/oy7qvf/kUYAQEEEEAgZwECwJyrM9zcCACHs2aknQUIANkRCCCAwIgFfK+ay3HJtmuZDfdyCPtmPW3XkmMdxjKnvoz76ncsrswTAQQQQKA/AQLA/mzH1DMB4JiqVdZcCQDLqierQaBogRyDnhzAx3q10rx6dq1l9ucv+qkn6iOf+7ruf3C7zHMhZ9/s61uf0L0W82pG3zX02c74XL/120tDHLX/3lq95259Dje3776M++p3cCAGRAABBBDIToAAMLuSJJkQAWASdgblJSDsAQQQGItAVzA0lnX0Nc/QwKqvebX1u6iebWuZd2XWbP8xXg7jM7fZebheRTam+hmf9Zdu0YPNi7nNm5fPO/VwnbZmv4XbKPYaXY1t93hf/dqOz3EIIIAAAuUKEACWW1uXlREAumhxbEwBrgCMqUlfCCDQiwBfyLtZY4cr3SP6H2Fbz9k1tV2ZNTuTi9YdrbUHrvKa4KK5ub5t2Ta0nj5ul5UrdOZx+2vdCU8Z7Ko6l71jjj12wyY9MEn/GuVdVkjXrH9O65xtLVyLNrZ+XdfH8eMXcDm/xr9aVoAAAl0CBIBdQnX8nACwjjrnuEoCwByrwpwQQGAnAW7JW7wh+gpBpkeN+SXWpp7z1nTioau1dsOmpdt92z6hVwC2ze2dZxypsy6+caexbcbqcmu7qtEEaudaXFUX+p8K172zKIRtC15tA1/ftXQZ59av73xoNz4B1/NrfCtkxggg4CpAAOgqVubxBIBl1nUMqyIAHEOVmCMClQv0HSCMmXcIm9hfYrvm7HIVXuxnALYFcmcc/SR96Npty7bKdOjlE0QtCtRsAsaQvdtVh3l9+1wBaBP4hqyDtmUL+JxXOYj4nF85zJs5IIBAvwIEgP36jqV3AsCxVKq8eRIAlldTVoRAkQKxQ6hSkPoOV/r6Eruonl1rmg0EYgcE777qNp13xS07bRFza662b9cDUxcfTgd0vvuz67mGIbczd+3xLue29q7PAOxrD3Wtj5+PX8D3vMph5b7nVw5zZw4IINCfAAFgf7Zj6pkAcEzVKmuuBIBl1ZPVIFC0QOygpwSsvsOVPr/EttWz7zV11b1tzeueeYDet3nrsjcOh87XhByvu+ymZc/Vy/EKwImdWbPLW4DHHOR07Rd+3o9A6HnVz6zsex37/O1XypEIIOAiQADoolXusQQuhy2jAAAgAElEQVSA5dY295URAOZeIeaHAAIIdAi0PS/v1ju/p4NW7xH0MolUX2JTBkaL1mxKMesaIyQ1Y2686st676e/snSVoQn/3nzKYZ1v1g09OYZ0JsAPrVZd7WOcV6nFhjy/Uq+V8RFAwE6AANDOqfSjCABLr3C+6yMAzLc2zAwBBBCwFpgOV1zfVts1yE5vqV0hnXn8AYO8pTZlYOTyxT1mSJpizSnG7Npz/ByBmOdVSk3Or5T6jI1AfgIEgPnVJMWMCABTqDOmESAAZB8gUJkAX0bKLrjLl2aXvbDjCrXNW5duVR3qCrWU1XK5zbXPqzBtDFxqadMfxyCQg4BLEJ/DfJkDAggg0CVAANglVMfPCQDrqHOOqyQAzLEqzAmBngT4MtUTbEbd2t4257oXXILFjDiCpuJjNLk92OcqTN8Qz3WeQSg0RmBgAd/zYuBpMhwCCCBgJUAAaMVU/EEEgMWXONsFEgBmWxomhkBcgRoDnLiC4+jNps6uz7gzK7cNFseh1D1LG8e2Xnza+oZ4PmN1r54jEEAAAQQQQKAPAQLAPlTH1ycB4PhqVsqMCQBLqSTrQKBDoLYAp+YN0RUmub7l1lh+/o579MILNuuB7dt30Pb9ltqUNQw5X1zbhoR4rmOlNGVsBBBAAAEEahcgAKx9Bzy0fgJA9kEqAQLAVPKMi8DAAiEhg81UuU3LRmm4YxbVY95e2MX8SWTFiqXn+00+k4Bv+nbW6Z8N8Zba4cR2HinkfDFtjz3vyqW3+c5art5zt2VLCgnxQuaZytZ2XP6bYivFcQgggAACYxEgABxLpfqdJwFgv7703i5AAMjuQKAiga4rw3wp+urXdz606xaYrdnLjttfGz/1lWUN33nGkTrr4ht1/1QwuHKFdPlZx+vpT9ire6CER4QGSL772rRbf+kWTciM13mnHq7T1uw3VyM0xPOdZ8LSdA5d4po6F80BCCCAAALFCxAAFl9iqwUSAFoxcVAPAgSAPaDSJQI5C4SGIrNrCw0vcrYqfW7Te8Gsde2GTTsFfeYKwAteeoRe8aEbllFctO5orT1w1bJ/H3t/+dYgVoDkup65V1euXKFrzjlR867+m6xver4mMDzn+Ydo3QkHWi/fdZ7WHSc4kP+mJEBnSAQQQACBQQQIAAdhzn4QAsDsS1TsBAkAiy0tC0NgGAGb2xdLCieGUU0zynQIZW4JPvP4A3TqT++jF124eVkwePWcQCtW6Ba6+j4DpK69bHM+tK3v3VfdpvM/9sWl5yya8LXkW6wX1TjEMHTv0B4BBBBAAIE+BQgA+9QdT98EgOOpVWkzJQAsraKsB4GBBbrCltlQ6DXPO1jP2GcvHbR6j4VXRA28DIZrBEw9N171Zb1389al5wGaIOpFP/VEfeRzX18KAaeDKZsrCOcFhX1j2wRIXUHevDnaBJxd50Pb2n3b9W2Zov/SLHz2Wgp3xkQAAQQQ6F+AALB/4zGMQAA4hiqVOUcCwDLrWv2q+MI17BZoC0bmfZGfzCzFFU7si+590Ra+fORVx+nue3+0I7i1fYZg263C3TPxP6IrQFq0X2+983tzw+muPqdnaxMUzq7OJrT0FxlfSx/DHFdZyjpytGVOCCCAwBgFCADHWLX4cyYAjG9Kj3YCBIB2Thw1IgG+cKUp1rxwrS3UmA4Bh7pCjH1hty9sgqi5z7lb8BbhRc++s5uV+1EuobQJo82Vqed//IvLrnKcjGzjMj1L17DZJWB01xhnC1fD3FZJTXOrCPNBAAEE0gsQAKavQQ4zIADMoQrL57C7pN+V9BJJ5kncj5K0TdJHJV0g6as9TvvPm3EnQxwgaWsP4xEA9oBKl+kE+MIl5fSledEVgJNdMsQVYuwL+3PSxqotDFv3zAP0vs1bW0M0+1nEOdIllDYv3ph60fHSrc7T4bSNS+isCalDBfNq7xoa5zV7ZoMAAggg0IcAAWAfquPrkwAwv5odJOkKSU9tmdp3JJ0h6fIepn7ynH4JAHuApsvyBGr/wpVjgDA9p9kdNxuy9LUja98Xrq5d+2hRGGbGaruN1nUefRw//+rFFUsv3pj9zIbTXS6h8zVzu37rt5e6OWr/vXlGZiho4vZDhMaJl8jwCCCAAAKOAgSAjmCFHk4AmFdh95R0vaSnNdPaKOkSSfdJerakcyTtIeleScdJujHi9E2/N0vaT9KdklY3fRMARkSmq3IFav7ClfPaJ1di3XT7PXrLgtss+9qZOdv0tebQfruuJO07DPOdf9e8Tb+zcz/7eQfv2JeTcdvCaZv+feaeq6fPWmjzsEBoXfvab9QIAQQQQCCNAAFgGvfcRiUAzKsib5L0hmZKZ0t668z0jpV0laRdJX1S0rMiTv/tkl4t6UpJ/yzpNwgAI+rSVRUCoV+4xoo0lqvc+vpC29Vvrfuiz/3cZd7n2PP6dqnx7Nxd2sZeFwF1bNG8+vM9T1LuybwEmQ0CCCBQjgABYDm1DFkJAWCIXty2j5D0TUl7SfqCpMMkPThniHdJennz79dI+myEaRwl6TOS7pf0k5LWEwBGUKWLKgV8v3CNGavmEMH2i3KN+2LMe3oyd5u6xdj/NuP04TmW8L6PtdPnfIEY+xlbBBBAAIH8BAgA86tJihkRAKZQnz/mcyV9ovnRayWd3zK1YyRd0/xsQxPWhazCXE1oQsQjJL1R0h9Jej8BYAgpbRGoT8A2CCtJhi/KJVVz+Vps9/TQIVrMsJA9XPYe9lnd0PvZZ460QQABBBBwFyAAdDcrsQUBYD5Vnb7919zqa67Im/cxgd3dkh7T3A78c4FLMLcam7DxS5IOl/RDAsBAUZojUKlAzGBiDIR8UR5Dlfzm6BKMdR0b87ywDSVdVt1Hny7jc2xeAl37Oa/ZMhsEEEAAAVsBAkBbqbKPIwDMp75/KenFzXQe14R8bbP7XHOrrrllePKyDp+VmBd83CRpd0k/L+lvm064AtBHkzYIZC4QM4jIfKmDTG/eF2Uz8OtOOkTrTjgw6hyoXVTOzs5cw922EC1muNZnMMP+6twSVR0Qc99WBcdiEUAAgYwFCAAzLs6AUyMAHBC7Yyhzxd/Rkr7fvOl30eGXSzq5OWC35qo9n5WYW47NrccXSzp9qoMYAeC+HRN6/OT5hdu2bdO++3Yd7rM82iCAwESAL3T97IV3X3Wbzrvilp06b3uLq+8MqJ2vnH87n7BtNkTz6WPRjF1DSf/V0zIXgZTBbMqxc/FnHggggEBJAgSAJVXTfy0EgP52sVveLOnpkv5FkgnHFn0+LOmXmwNWSfqWx2R+VdIHJN0j6RBJ34gcAG63nRMBoK0UxyHgJxA7iPCbRZmt+g5lqF26fRMavMbeG117oZbAppZ1hu6/dGcOIyOAAAII5ChAAJhjVYafEwHg8OZtI94m6SmStknar2Nafybp15pjniTpnx2Xsbckc8nKT0h6paR3zrSPcQUgAaBjUTgcgb4EYgcRfc1zjP12hTKha6J2oYJh7UPCpj72xhC3GoeJ9du6llCsj73Tb2XoHQEEEEAgdwECwNwrNMz8CADdna2DrQVdv6x50cb0IUNeATgJ+Mzbf81bhR/sIQDsuqeXW4Dd9x4tEPAS4MukF5t1oz5DCWpnXYYsD+xjb8S+1Tgk5BwSvaZzgeB/yJ3FWAgggEAdAgSAddS5a5UEgF1Cy3/eVwA41DMAT5R0paQHJP2spBvmEMS4ArBL1gSE5mpHcQtwFxU/RyBcoI8gInxW5fTQZ4hC7ca9T2LujXl9hYRFY9pbIeuMvYNi1nTe3GoKO2PXhv4QQAABBOYLEACyM4wAAaD7PjDPywv93NE8e2+6n6HeAjx58ce1kt7espD/KOmE5mdnSTJvGzafS0IXPtWeADAiJl0hYCPQ95dWmzlwjJ8AtfNzK6lVW1jnGxb5tktlmst8hwpNhxonVT0ZFwEEEEBgWAECwGG9cx2NADCfyrxJ0hua6RwryVwROO+zq6S7JT1G0lWSfs5xCX/v0WYyRMz9QgDoWDgORwABBGIKECrG1LTry9e8K/z6vQ/fqL++4fYdk/jFI/fR237liIWTyumKOjs9KXUo1lUH23XYHue7X2z75zgEEEAAgXoECADrqfWilcYMdBANE3iuJHN1nvm8VtL5Ld2ZZ/Zd0/xsg6T1jsMSADqCcTgCCCBQmkDqIKXNs+TAI8R8UVh30Oo9tHbDJt3/4MNPKNl15Qpdfc6JWr3nbq1bd+gwK9Y5lHKPjDE0jeVOPwgggAAC4xYgABx3/WLNngAwlmR4P4+UdKekvSR9QdIzJM173uC7JL28GW6NJPMij9gfngEYW5T+EEAAgUwEcg1+QgKyTGh7C9sW1ezWO7+n0zeap3rs/Llo3dFae+CqhTQlm/exJ3I9d/pYK30igAACCJQlQABYVj19V0MA6CvXT7vp24DPlvTWmWHMrcHmtl9zG/AnJT2rZRqT4PCrkvb3mCoBoAcaTRBAAIExCFyx5et6xYeWv//JJjDqa32lBysxrhyL/QzASS1dr6hzPb6vPZOqX0LTVPKMiwACCCAQIkAAGKJXTlsCwLxquaek6yU9rZnWu5sXb9wn6dnN7b57SDL/vFbSjQSAeRWQ2SCAAAI5C5jw4nWXbtEDM9eX29wy2ue6YgRkfc4vpG8TmF2/9dt61cU36gHH23Rnx20L34YKpYYaJ8R7iLa1h6BDGOc+Bnsg9woxPwQQmBUgAGRPGAECwPz2wUGSrpD01JapfUfSGZIuXzB1rgDMr67MCAEEEEgqMO8qOzOhXVau0LmnHKbT1uyXbH6lXgE4HZitbP7EZTJAE7i+ObJ534FEiTXq2yzZCcXAvQoQhPfKS+cIINCTAAFgT7Aj65YAMM+CmTf8vlLSSySZQNA8H3BbEwy+Q5K5tXfRhwAwz7oyKwQQQCCZQNtVdu8840iddPgTk81rMnBpX6rnBWa7rJAuPP1IHbX/3gtf0JG8GHMmUNpVmqXttxz3TIlzKjEIL7FOrAkBBJYLEACyK4wAASD7IJXAvk2oqW3btmnffc0/8kEAAQQQ6EtgDF9cXa7Icjm2L9NF/ZYWmOW6f3z2Qeq1+Mw5xR5mzOUCpZ3X1BgBBOoRIACsp9aLVkoAyD5IJUAAmEqecRFAIBuBoYOAUq56GsM6UodMfWzy3Nx955MyxPGdcx/1pE93gRLPa3cFWiCAwBgFCADHWLX4cyYAjG9Kj3YCBIB2ThyFQLYCQ4dXQ0P0vb5UQUDf63Ktk+t8xvQFPFWNXWvgcrxrvVz6djk2ZB+EtHWZ4+yxqcYNmTNtlwuUeF5TZwQQKF+AALD8GtuskADQRolj+hAgAOxDlT4RGEig9C9Afa+PIOChjerjnPLqLZ/TK5fAzGfuObcJ3Qc+ey/UI3TOoePTPp4A53U8S3pCAIFhBAgAh3HOfRQCwNwrVO78CADLrS0rK1yg9PBqiPURBEi+zr7tCj8tq1tejH0wdIgTY87VFZoFI4AAAghEESAAjMI4+k4IAEdfwtEugABwtKVj4rULlB5eDbE+ggApxDnF1Vu1n/c5rn+M+2CMc86x9swJAQQQQMBNgADQzavUowkAS61s/usiAMy/RswQgbkCpYdXQ62v9iAg1Hnoq7f4z0E/AqF1DG3fz6oW9zrGOadwYkwEEEAAgXgCBIDxLMfcEwHgmKs37rkTAI67fsy+coHSw6uh1ld7EDCUc+Wna7bLp/7ZloaJIYAAAggUJkAAWFhBPZdDAOgJR7NgAQLAYEI6QCCtQOnhVenr8909sV1i9+e7LtoNKxB6Beiws2U0BBBAAAEExi1AADju+sWaPQFgLEn6cRUgAHQV43gEEEAgsQBXbCUuQEHDhzwDsiAGloIAAggggMAgAgSAgzBnPwgBYPYlKnaCBIDFlpaFIYBAiQJcsVViVdOtyWc/cbVounoxMgIIIIDAuAUIAMddv1izJwCMJUk/rgIEgK5iHI8AAggkFOCKrYT4hQ7tckWpy7GFcrEsBBBAAAEEvAUIAL3pimpIAFhUOUe1GALAUZWLySKAQEkCPldS+VyxVZJZCWvxqfu8dcfqx/Rt0xd7r4TdxxoQQAABBFIKEACm1M9nbALAfGpR20wIAGurOOtFAIFBBLoClZArqULaDrJ4BmkViFW7WP24lIqrT120OBYBBBBAAIHlAgSA7AojQADIPkglQACYSp5xEUCgWIGucCbGlVRdAWOxuCNeWIy6m+XH6seVMtW4rvPkeAQQQAABBHIVIADMtTLDzosAcFhvRntYgACQ3YAAAghEFLAJSbiSKiL4iLqKVfdY/fjQdYXbPn3SBgEEEEAAgVoECABrqfTidRIAsg9SCRAAppJnXAQQKFLAJpyxCQmLxKl8UbHqHqsf33Jw9amvHO0QQAABBGoXIACsfQc8tH4CQPZBKgECwFTyjIsAAkUK2IYzXElVZPk7FxWr7rH66ZwwByCAAAIIIIBANAECwGiUo+6IAHDU5Rv15AkAR10+Jo8AAjkK2IYzXEmVY/X6n1Osusfqp/8VMwICCCCAAAIIGAECQPaBESAAZB+kEiAATCXPuAggULQA4UzR5WVxCCCAAAIIIICAswABoDNZkQ0IAIss6ygWRQA4ijIxSQQQQAABBBBAAAEEEEAAgTELEACOuXrx5k4AGM+SntwECADdvDgaAQQQQAABBBBAAAEEEEAAAWcBAkBnsiIbEAAWWdZRLIoAcBRlYpIIIIAAAgjkLcBt73nXh9khgAACCKQXIABMX4McZkAAmEMV6pwDAWCddWfVCCCAAAIIRBOwffFNtAHpCAEEEEAAgREKEACOsGg9TJkAsAdUurQSIAC0YuIgBBBAAAEEEJgnYK78W7thk+5/cPuOH++6coWuPudErd5zN9AQQAABBBBAoBEgAGQrGAECQPZBKgECwFTyjIsAAggggEABAlffdpdO33jtspVctO5orT1wVQErZAkIIIAAAgjEESAAjOM49l4IAMdewfHOnwBwvLVj5ggggAACcwTMFWnXb/320k+O2n9vrkLreZdwBWDPwHSPAAIIIFCMAAFgMaUMWggBYBAfjQMECAAD8GiKAALlCPACgzJqaZ5Ft/7SLZrcjbpyhXTeqYfrtDX7lbHATFfBMwAzLQzTQgABBBDISoAAMKtyJJsMAWAy+uoHJgCsfgsAgAAChBdl7AET4h67YZMemHoWnVnZLiuka9Y/hysBey4zIXrPwHSPAAIIIDB6AQLA0ZcwygIIAKMw0omHAAGgBxpNEECgHAFuXyynlm3PojMr7Pt5dIRf5ewjVoIAAggggEBfAgSAfcmOq18CwHHVq6TZEgCWVE3WggACzgK8wMCZLNsGqa4A5ArSbLcEE0MAAQQQQCArAQLArMqRbDIEgMnoqx+YALD6LQAAAnULcAVgGfWfXIF38+33aMPHbhnsGYDsnzL2D6tAAAEEEEBgCAECwCGU8x+DADD/GpU6QwLAUivLuhBAwFqAK7isqbwP7PMW2dn6nf28g7Xv4x69NNe+3wLMFaTeW4KGCCCAAAIIVCdAAFhdyecumACQfZBKgAAwlTzjIoBAVgJ9BlRZLTTBZPoMWFNfgZd6/ATlZEgEEEAAAQQQ8BQgAPSEK6wZAWBhBR3RcggAR1QspooAAgiMTaDvgCyHK/D6DDjHVu+h50twP7Q44yGAAAIIhAgQAIboldOWALCcWo5tJQSAY6sY80VgRoAvwGwJV4Eh90zfAV3fAaOt7ZCmtnMq/TiC19IrzPoQQACB8gQIAMurqc+KCAB91GgTQ4AAMIYifSCQSIAvwIngRzzs0HtmiIBu6DWNuPzFTH2IfVUMFgtBAAEEEMhGgAAwm1IknQgBYFL+qgcnAKy6/Cx+zAJ8AR5z9dLMPdWeGSKgy+UKvFzmkWaHDTdq31eWDrcSRkIAAQQQqEmAALCmarevlQCQfZBKgAAwlTzjIhAowBfgQMAKm6fcMzUEY0MEnRVu27lLThVm448AAggggECIAAFgiF45bQkAy6nl2FZCADi2ijFfBBoBvgCzFVwF2DOuYvbHY2tvFetIAtdYkvSDAAIIIDCUAAHgUNJ5j0MAmHd9Sp4dAWDJ1WVtxQvwBbj4EkdfIHsmOulShymvruxnRePotYYrS8dRCWaJAAIIIGAjQABoo1T+MQSA5dc41xUSAOZaGeaFgKUAX4AtoThshwB7Jv5m4ArA+Kb0iAACCCCAQGkCBIClVdRvPQSAfm60ChcgAAw3pAcEEEAAAQTE1ZVsAgQQQAABBBBYJEAAyP4wAgSA7INUAgSAqeQZFwEEEECgOAGuriyupCwIAQQQQACBaAIEgNEoR90RAeCoyzfqyRMAjrp8TB4BBBBAAAEEEEAAAQQQQGAMAgSAY6hS/3MkAOzfmBHmCxAAsjMQQAABBBCoQICrEysoMktEAAEEEMhagAAw6/IMNjkCwMGoGWhGgACQLYEAAggg0JsAoVNvtE4d83xCJy4ORgABBBBAoBcBAsBeWEfXKQHg6EpWzIQJAIspJQtBAAEE8hIgdMqjHryhOI86MAsEEEAAAQQIANkDRoAAkH2QSoAAMJU84yKAAAIFCxA65VPcq2+7S6dvvHbZhC5ad7TWHrgqn4kyEwQQQAABBAoXIAAsvMCWyyMAtITisOgCBIDRSekQAQQQQIDQKZ89QBibTy2YCQIIIIBA3QIEgHXXf7J6AkD2QSoBAsBU8oyLAAIIFCxA6JRXcbkdO696MBsEEEAAgToFCADrrPvsqgkA2QepBAgAU8kzLgKJBXg5Q+ICVDA8oVNeReacz6sezAYBBBBAoD4BAsD6aj5vxQSA7INUAgSAqeQZF4GEAgQzCfErG5rQqbKCR1ou+yYSJN0ggAACCGQlQACYVTmSTYYAMBl99QMTAFa/BQCoTYBbM2urOOtFYFwC/AXFuOrFbBFAAAEE7AUIAO2tSj6SALDk6ua9NgLAvOvD7BCILsDLGaKT0iECCEQS4C8oIkHSDQIIIIBAlgIEgFmWZfBJEQAOTs6AjQABIFsBgcoE+IJdWcFZLgIjEuAvKEZULKaKAAIIIOAsQADoTFZkAwLAIss6ikURAI6iTEwSgbgC3GIX15PeEEAgjgB/QRHHkV4QQAABBPIUIADMsy5Dz4oAcGhxxpsIEACyFxCoVICH7FdaeJaNQOYC/AVF5gVieggggAAC3gIEgN50RTUkACyqnKNaDAHgqMrFZBFAIBcBAtRcKsE8ShTg/CqxqqwJAQQQQIAAkD1gBAgA2QepBAgAU8kzLgIIjFaAK5RGWzomjgACCCCAAAIIJBMgAExGn9XABIBZlaOqyRAAVlVuFosAAqECPKMsVJD2CCCAAAIIIIBAnQIEgHXWfXbVBIDsg1QCBICp5BkXAQRGKcBbSkdZtsEnzS2sg5MzIAIIIIAAAtkLEABmX6JBJkgAOAgzg8wRIABkWyCAAAIOAlwB6IBV6aHcIl5p4Vk2AggggAACHQIEgGwRI0AAyD5IJUAAmEqecRFAYLQCfQQ8XDE22u2w08RLDYjZn2XsT1aBAAIIIJBWgAAwrX8uoxMA5lKJ+uZBAFhfzVkxAghEEIgZiPQRKEZYIl14COR8i7jvnmV/emwEmiCAAAIIIDBHgACQbWEECADZB6kECABTyTMuAgggIKnUK8ZqLW6u9fQN8XJdT637i3UjgAACCIxbgABw3PWLNXsCwFiS9OMqQADoKsbxCCCAQESBnK8Yi7jMqrryDdv6QgoJ8diffVWFfhFAAAEEahQgAKyx6svXTADIPkglQACYSp5xEUAAAa4ALHYP+N5u2wdISIgXEh72sRb6RAABBBBAYMwCBIBjrl68uRMAxrOM2dPukn5X0kskHSjpUZK2SfqopAskfTXmYJKeJulMSc+X9CRJj5b0L5Juk7RJ0ockbY08JgFgZFC6QwABBFwFcrtizHX+HJ+3QGiIx/7Mu77MDgEEEEBgPAIEgOOpVZ8zJQDsU9ev74MkXSHpqS3NvyPpDEmX+3W/rNUbJL1e0iMX9PefJb090niTbggAI4PSHQIIIOAjkNMVYz7zp03eAqEhHvsz7/oyOwQQQACBcQgQAI6jTn3PkgCwb2G3/veUdH1zRZ5puVHSJZLuk/RsSedI2kPSvZKOk3SjW/fLjjah3qubf3uzpPdI+n/NeOZKwEMl/ZKk90t6R+BYs80JACOD0h0CCCCAAAI5ChDi5VgV5oQAAgggUJMAAWBN1W5fKwFgXvvgTZLMFXnmc7akt85M71hJV0naVdInJT0rYPq/LOnDTft3S3qlpPtb+nuEpB8FjDWvKQFgZFC6QwABBBBAAAEEEEAAAQQQQGBWgACQPWEECADz2QcmZPumpL0kfUHSYZIenDO9d0l6efPv10j6rMcSzDMFzTP9Hi/pOkkmWJw3lkfX1k0IAK2pOBABBBBAAAEEEEAAAQQQQAABPwECQD+30loRAOZT0edK+kQznddKOr9lasdIuqb52QZJ6z2W8FJJFzXtXtC8XMSjm6AmBIBBfDRGAAEEEEAAAQQQQAABBBBAoFuAALDbqIYjCADzqfL07b/mirzPtEzN3P57t6THNLcD/5zHEv5a0qmSvivpcZIeaK4GXS3JPIfQvAHY/KzPDwFgn7r0jQACCCCAAAIIIIAAAggggIAkAkC2gREgAMxnH/ylpBc30zGhnAn52j6fk/STzS3DJrRz/dwu6YmSNkn6BUl/IOkVkkwoZz7bJd0g6QJJf9b8s+sYXccTAHYJ8XMEEEAAAQQQQAABBBBAAAEEAgUIAAMBC2lOAJhPIc0Vf0dL+n7zpt9FM7tc0snNAbtJ+qHDMswzBifh4oea0G/RVYR/JcncMuz6EpBJmNg2NfP8waXnF27btk377tt1uMMKORQBBBBAAAEEEEAAAQQQQAABBJYECADZCEaAADCffXCzpKc3t9+acGzRx7y917zF13xWSfqWw++Pq2EAACAASURBVDIOkPTl5ngTHJoXgvyTpN+X9PfN1X4mEPxvkg5pjjP/21wl6PIxVxFafQgArZg4CAEEEEAAAQQQQAABBBBAAAFnAQJAZ7IiGxAA5lPW2yQ9xVwQJ2m/jmmZ23J/rTnmSSbQd1iGebvwlqnjvzF1O/F0NyZYNLcam1uFzdV/Jjg0tw7bfggAbaU4DgEEEEAAAQQQQAABBBBAAIGeBAgAe4IdWbcEgO4Fsw62FnT9Mknvn/n5UFcAHiTpS1Nj/56k/9Ey11dK+pPmZ2dJutCBq+ueXm4BdsDkUAQQQAABBBBAAAEEEEAAAQR8BAgAfdTKa0MA6F7TvgLAoZ4B+O8kmav+Jh9zRaAJH+d9psPCD0j6dXeu1ha8BCQiJl0hgAACCCCAAAIIIIAAAgggME+AAJB9YQQIAN33weS5eO4tH25xh6R7ZjoY6i3AK5sXjZiXh5iPeSnId1oWY54P+IPmZx+X9PyQRc+0JQCMiElXCCCAAAIIIIAAAggggAACCBAAsgfaBAgA89kbb5L0hmY6x0oyVwTO++zavMX3MZKukrToDb5tq7tR0k81P9xb0r+2HLh7ExaaH39U0gsichEARsSkKwQQQAABBBBAAAEEEEAAAQQIANkDBID574HnSvpEM83XSjq/ZcrHSLqm+dkGSes9lnaBpFc17Y6S9A8tfRwu6R+bn71b0ss9xmprQgAYEZOuEEAAAQQQQAABBBBAAAEEECAAZA8QAOa/Bx4p6c7mltwvSHqGpHnPG3zXVBC3RtJnPZb2LEl/17Q7V9LrW/r4Q0l/1PzMvHX4gx5jEQBGRKMrBBBAAAEEEEAAAQQQQAABBFwEeAagi1a5x3ILcF61nb4N+GxJb52Znrk12Nz2a24D/qQkE+TN+0yCw69K2r/lmOmXjhw950Ugh0q6TtIekr7Z9HNvRC6uAIyISVcIIIAAAggggAACCCCAAAIIzBMgAGRfGAECwLz2wZ6Srpf0tGZa5rbbSyTdJ+nZze2+JpAz/7xWknmWn28A+DOSPiXp0c0zBd8ydVXgCZLMbciPazo/TdKHI1MRAEYGpTsEEEAAAQQQQAABBBBAAAEEZgUIANkTBIB57oGDJF0h6akt0zNv7D1D0uULpm9zBaBpfpKkD0l6bEtf90s6S9L/6oGKALAHVLpEAAEEEEAAAQQQQAABBBBAYFqAAJD9QACY7x4wb/h9paSXSDKBoHk+4LYmGHyHJHNr76KPbQBo+nhiE/KZN/w+WdIuzVh/K+ntkr7UExMBYE+wdIsAAggggAACCCCAAAIIIIDARIAAkL1AAMgeSClAAJhSn7ERQACBgQXu/O4PdOud39NBq/fQ6j13G3h0hkMAAQQQQAABBOoVIACst/bTK+cZgOyDVAIEgKnkGRcBBBAYWOCS676m1192k+5/cLt2XblCbz7lMJ22Zr+BZ8FwCCCAAAIIIIBAnQIEgHXWfXbVBIDsg1QCBICp5BkXAQQQGFDAXPm3dsOmpfBv8jEh4NXnnMiVgAPWgaEQQAABBBBAoF4BAsB6az+9cgJA9kEqAQLAVPKMiwACCAwocPVtd+n0jdcuG/GidUdr7YGrBpwJQyGAAAIIIIAAAnUKEADWWffZVRMAsg9SCRAAppJnXAQQQGBAAa4AHBCboRBAAAEEEEAAgTkCBIBsCyNAAMg+SCVAAJhKnnERQACBgQV4BuDA4AyHAAIIIIAAAghMCRAAsh0IANkDKQUIAFPqMzYCCCAwsABvAR4YnOEQQAABBBBAAIFGgACQrUAAyB5IKUAAmFKfsRFAAAEEEEAAAQQQQAABBKoQIACsosydi+QW4E4iDuhJgACwJ1i6RQABBBBAAAEEEEAAAQQQQGAiQADIXjACBIDsg1QCBICp5BkXAQQQQAABBBBAAAEEEECgGgECwGpKvXChBIDsg1QCBICp5BkXAQQQQAABBBBAAAEEEECgGgECwGpKTQBIqbMUIADMsixMCgEEEEAAAQQQQAABBBBAoCQBAsCSqum/Fq4A9LejZZgAAWCYH60RQAABBBBAYGAB3mY9MDjDIYAAAghEESAAjMI4+k4IAEdfwtEugABwtKVj4ggggAACCNQncMl1X9PrL7tJ9z+4XbuuXKE3n3KYTluzX30QrBgBBBBAYHQCBICjK1kvEyYA7IWVTi0ECAAtkDgEAQQQQAABBNILmCv/1m7YtBT+TT4mBLz6nBO1es/d0k+QGSCAAAIIILBAgACQ7WEECADZB6kECABTyTMuAggggAACCDgJXH3bXTp947XL2ly07mitPXCVU18cjAACCCCAwNACBIBDi+c5HgFgnnWpYVYEgDVUmTUigAACCCBQgABXABZQRJaAAAIIVCxAAFhx8aeWTgDIPkglQACYSp5xEUAAAQQQQMBZgGcAOpPRAAEEEEAgEwECwEwKkXgaBICJC1Dx8ASAFRefpSOAAAIIIDBGAd4CPMaqMWcEEEAAAQJA9oARIABkH6QSIABMJc+4CCCAAAIIIIAAAggggAAC1QgQAFZT6oULJQBkH6QSIABMJc+4CCCAAAIIIIAAAggggAAC1QgQAFZTagJASp2lAAFglmVhUggggAACCCCAAAIIIIAAAiUJEACWVE3/tXAFoL8dLcMECADD/GiNAAIIIIAAAggggAACCCCAQKcAAWAnURUHEABWUeYsF0kAmGVZmBQCCCCAAAIIIIAAAggggEBJAgSAJVXTfy0EgP52tAwTIAAM86M1AggggAACCCCAAAIIIIAAAp0CBICdRFUcQABYRZmzXCQBYJZlYVIIIIAAAggggAACCCCAAAIlCRAAllRN/7UQAPrb0TJMgAAwzI/WCCCAAAIIIIAAAggggAACCHQKEAB2ElVxAAFgFWXOcpEEgFmWhUkhgAACCCCAAAIIIIAAAgiUJEAAWFI1/ddCAOhvR8swAQLAMD9aI4AAAggggAACCCCAAAIIINApQADYSVTFAQSAVZQ5y0USAGZZFiaFAAIIIIAAAggggAACCCBQkgABYEnV9F8LAaC/HS3DBAgAw/xojQACCCCAAAIIIIAAAggggECnAAFgJ1EVBxAAVlHmLBdJAJhlWZgUAggggAACCCCAAAIIIIBASQIEgCVV038tBID+drQMEyAADPOjNQIIIIAAAggggAACCCCAAAKdAgSAnURVHEAAWEWZs1wkAWCWZWFSCCCAAAIIIIAAAggggAACJQkQAJZUTf+1EAD629EyTIAAMMyP1ggggAACCCCAAAIIIIAAAgh0ChAAdhJVcQABYBVlznKRBIBZloVJIYAAAggggAACCCCAAAIIlCRAAFhSNf3XQgDob0fLMAECwDA/WiOAAAIIIIAAAggggAACCCDQKUAA2ElUxQEEgFWUOctFEgBmWRYmhQACCCCAAAIIIIAAAgggUJIAAWBJ1fRfCwGgvx0twwQIAMP8aI0AAggggAACCCCAAAIIIIBApwABYCdRFQcQAFZR5iwXSQCYZVmYFAIIIIAAAggggAACCCCAQEkCBIAlVdN/LQSA/na0DBMgAAzzozUCCCCAAAIIIIAAAggggAACnQIEgJ1EVRxAAFhFmbNcJAFglmVhUggggAACCCCAAAIIIIAAAiUJEACWVE3/tRAA+tvRMkyAADDMj9YIIIAAAggggAACCCCAAAIIdAoQAHYSVXEAAWAVZc5ykQSAWZaFSSGAAAIIIIAAAggggAACCJQkQABYUjX910IA6G9HyzABAsAwP1ojgAACCCCAAAIIIIAAAggg0ClAANhJVMUBBIBVlDnLRRIAZlkWJoUAAggggAACCCCAAAIIIFCSAAFgSdX0XwsBoL8dLcMECADD/GiNAAIIIIAAAggggAACCCCAQKcAAWAnURUHEABWUeYsF/lkSVvNzK677jo94QlPyHKSTAoBBBBAAAEEEEAAAQQQQACBMQvccccdWrNmzWQJ+0v66pjXw9z9BAgA/dxoFS5wlKTPhndDDwgggAACCCCAAAIIIIAAAgggYCnws5KutzyWwwoSIAAsqJgjWwoB4MgKxnQRQAABBBBAAAEEEEAAAQRGL0AAOPoS+i2AANDPjVbhAo+SdHjTzTclPRDeZe89XNmM8JzeR1o8QN/ziNl/SF8+bV3b2B6/6LjHT13Nan6ZfiPx/uh7eFuzsc8j5jpD+vJp69LG9tiu42o6D7os+t77k/77nkfM/kP78mnv0sb22K7jOA+G2v0Pj9NVk9AZxew/pC+fti5tbI/tOo5zIHTHubfvqol7j8tbxBojtB+f9i5tbI/tOi7X82AXST/RlHeLpB/G2Bz0MS4BAsBx1YvZphW4uRn+GWmnob7nEbP/kL582rq2sT1+0XE7Xmgj6UmS/jnx/uh7eFuzsc8j5jpD+vJp69LG9tiu42o6D7os+t77k/77nkfM/kP78mnv0sb22K7jOA+G2v0Pj9NVk9AZxew/pC+fti5tbI/tOo5zIHTHubfvqol7j8tbxBojtB+f9i5tbI/tOq6m8yDG/qKPAQUIAAfEZqjRC3T9x36oBfY9j5j9h/Tl09a1je3xi46r7Ze8rVnf50Pf84jZf0hfPm1d2tge23VcTedBl0Xfe58A0E7YpU62x3Ydx3lgV5uYR3XVJHSsmP2H9OXT1qWN7bFdx3EOhO449/ZdNXHvkQCw62KPLvOazoMY+4s+BhQgABwQm6FGL9D1H/uhFtj3PGL2H9KXT1vXNrbHEwAOd7WF7XlkWzvb/maPi9l/SF8+bV3a2B7bdVxNf9jtsvDdc67t+p5HzP5D+/Jp79LG9tiu4zgPXHdx+PFdNQkdIWb/IX35tHVpY3ts13GcA6E7zr19V03ceyQAJACMsWvoI0sBAsAsy8KkMhUY4heszdL7nkfM/kP68mnr2sb2eAJAAkCbc7PtGNt9Nq+9T1uXNrbHdh3Hl76QHeLXtqsmfr32c66HztWnvUsb22O7juM8CN117u27auLe484tYvYf0pdPW5c2tsd2Hcc5ELrj3Nt31cS9RwJAAsAYu4Y+shQgAMyyLEwKAQRGJFDTH3ZHVBamOrAA58HA4AyXpQDnQZZlYVIDCnAODIjNUNkKcB5kWxomRgDIHkAAAQTCBPglH+ZH6zIEOA/KqCOrCBPgPAjzo/X4BTgHxl9DVhAuwHkQbkgPPQkQAPYES7cIIFCNAL/kqyk1C10gwHnA9kBA4jxgF9QuwDlQ+w5g/UaA84B9kK0AAWC2pWFiCCAwEgF+yY+kUEyzVwHOg1556XwkApwHIykU0+xNgHOgN1o6HpEA58GIilXbVAkAa6s460UAAQQQQAABBBBAAAEEEEAAAQQQqEqAALCqcrNYBBBAAAEEEEAAAQQQQAABBBBAAIHaBAgAa6s460UAAQQQQAABBBBAAAEEEEAAAQQQqEqAALCqcrNYBBBAAAEEEEAAAQQQQAABBBBAAIHaBAgAa6s460UAAQQQQAABBBBAAAEEEEAAAQQQqEqAALCqcrNYBBBAAAEEEEAAAQQQQAABBBBAAIHaBAgAa6s460UAAQQQQAABBBBAAAEEEEAAAQQQqEqAALCqcrNYBBBAAAEEEEAAAQQQQAABBBBAAIHaBAgAa6s460UAgRwFflbSGyWtlfQISVskvU3Sn+c4WeaEQA8CvyrpmZJ+RtLhkh4p6WWS3t/DWHSJQI4C+0h6iaSTJB0i6fGSvi1ps6S3SLo2x0kzJwQiCuwm6TxJR0k6SNLeku6WdJuk90j6oKQfRRyPrhAYg8BrJP1xM9FjJX1mDJNmjvkKEADmWxtmhgACdQg8W9InJP1A0iWSvivpxZKeLOn3Jf33OhhYZeUCW5s9f5ek7zf/mwCw8k1R2fLNFzzzRc+EHZ+UdKekp0o6RZL58/rpkj5cmQnLrUtglaRtkq6T9E+SvinpcZKe3/xO+Jvmfz9YFwurrVjgGZL+QdL9kh4jiQCw4s0Qa+kEgLEk6QcBBBBwF9hV0i2S9pV0jKQbmy72av4AvL+kp0n6qnvXtEBgVAL/XtKXmr3+WkkbuAJwVPVjsuECvyjpW034N92buTL2Sknfk/QEST8MH4oeEMhSYKUk8+eif5uZnfl3/1fSsyS9QNJHs5w9k0IgroDZ9+bKb3PVq/nzkblTggAwrnGVvREAVll2Fo0AApkIPLe5+u99ks6cmdNvNLc//qGkN2UyX6aBwBACBIBDKDPGmATMVeLm94V5XMT1Y5o4c0UgksBZkt4h6T81/z9St3SDQLYCfyTJ/HnopyWdLcl8LyAAzLZc45kYAeB4asVMEUAgrsBqSWua/zNfqsz//XgzxP+W9JsOw5nbdc0fTk+W9KTmCg1zG5d5ht//lHRvS1/mWTfnSHppc/vv9GHm+U93SNok6TkOc+FQBFwEcjgPZudLAOhSQY6NIZDjeTC9rsub3y9HTl0pHmPd9IHARCDnc8BcGWjOAXMrsLla3FwRyweB2AI5nQMm9DNX//2X5o4I8zxkAsDYFa+0PwLASgvPshFAQNsXGLgEgC9sHkz9Yy39mefYmGDw1jk//wtJv9Q88No842P2Y54H+K+S9qNeCPQkkMN5QADYU3Hp1logx/NgMnnz33/ze8T8LjCPi3jAelUciIC9QE7ngHkJ1Prm2ZfmL2bNX4KaF+OYEMQ8G5YPAn0I5HIOPKp57p95NvjRzX/zCQD7qHilfRIAVlp4lo0AAjsFgOah019obrEyNLYBoLkaw7yh8dHN85nMc8v+rvnn0ySta5zNlzfzVjsT6E1/zAOtf7550Pu8gPB2SXtIMs8E5INAHwLTf+BNdR7MrosrAPuoNH0uEsjxPDDzNW+F/1tJJ0j6dUkfoIwI9CSQ0zlg/twz/eclMzfzQjRzx4R5GQIfBPoQyOUcMG99f3XzvWFLs1ACwD4qXmmfBICVFp5lI4CA3ijps83//Ysk88KNrzQutgGgeVOj+WJm/kBq/v81M65/IMn8IjcfM555nsf0hwCQjZhaIIfzYNaAADD1rqhv/BzPA3Pbown8zNt/N0r67frKwooHFMj1HHiiJHOnhXlkys2STpL0nQFdGKoegRzOAfOMv0833xf+6xQ9AWA9+7D3lRIA9k7MAAggMBIB1wDQPD/QPJ/DfP5U0u/MWaf5AneTpEMl3S3JPF/EvM1r8uEW4JFsjoqmmeI8IACsaIONZKmpzwPzu+O9zTOfPtj8/wdHYsc0yxBIfQ7MKr6kea6y+UvV15RBzCoyFxj6HDBv/f28pO83zyef/r5AAJj5ZhnT9AgAx1Qt5ooAAn0KuP6in7zAw8zpmKkwsC3MMP/+FySZq/4mH14C0mdF6dtHIMV5QADoUyna9CmQ8jww4Z95M7y55fdiSb/Gc//6LDV9twikPAfmTck8CsX8Rep1zXPRKBwCfQsMfQ48tnnWq826TpV0mc2BHIPArAABIHsCAQQQeEjA9Rf9VZKe2fxNnfml3fZcGnM5/9UN8psk/eEUuAkEP9582TtzphDmbV/mb/zM8aYdHwSGEEhxHhAADlFZxnARSHUeTId/H5Z0BuGfS9k4NqJAqnOgbQnmTgpzdZR57vLxEddJVwi0CQx9DpjniV/YMhnzmKGnSvqIpG9K+hPeCM/G9RUgAPSVox0CCJQm4PqL3vwCXiXpc5KOWIDxOEnfbn5ubvn95aljzeX+X5S0T3MV4Y3Nz8zfdJu/5TZzOljS1tKwWU+2AinOAwLAbLdDtRNLcR5M3/ZrfleYZ//xwoNqt2Dyhac4Bw6TdIekb82sfndJfyXpeZJe1zwPMDkQEyheIMU50IbKLcDFb7fhFkgAOJw1IyGAQN4CLr/od5N0X7Ocj0p6QcfSvifpMZI+I8lcETj9ebakT0j6gaRLmjffvVjSkyX9fvPmu7zlmF1JAqnOg9+auqrjcEk/3VzpMXk7tnko9ntKgmYtWQukOA/MS6LMFd/m98U7WsI/c8vX5C+KsgZkcqMXSHUOmOf7/X3zUjbzsg/zF6TPl/Tjkj7VPEpl8uev0SOzgKwFUpwDBIBZb4kyJkcAWEYdWQUCCIQLuPyi/wlJdzZDmtu0TusY3rxl2LwAxLwQxIQbsx/zQhHz9rG1kh4haYukt0kyffNBYEiBVOfB5G+329Zq+2buIa0Yq1yBFOdB1zlgtF/WPBqiXHlWlotAinPgqOZt1+bPQib420PSPZL+sfkLUvNiHK6KzWWHlD+PFOcAAWD5+yr5CgkAk5eACSCAQCYCLr/onyTpa828P9A8rH3RMsyxps1tkg7KZL1MA4F5ApwH7AsE3J4Jy+8DdkyJAvwuKLGqrMlFgHPARYtjRyNAADiaUjFRBBDoWcDlF33sKwB7XhrdI2AtwHlgTcWBBQtwHhRcXJZmJcA5YMXEQQULcA4UXNyal0YAWHP1WTsCCEwLuPyij/kMQKqAQE4CnAc5VYO5pBLgPEglz7i5CHAO5FIJ5pFKgHMglTzj9ipAANgrL50jgMCIBFx+0ZtlxXgL8Ih4mGolApwHlRSaZS4U4Dxgg9QuwDlQ+w5g/ZwD7IEiBQgAiywri0IAAQ8B11/0V0l6pqTvS3rsggdTm7f+Xt3M503NWx49pkcTBAYR4DwYhJlBMhfgPMi8QEyvdwHOgd6JGSBzAc6BzAvE9PwECAD93GiFAALlCbj+oj9P0jkNwzGSrm0hea2kDc3PfkHS35RHx4oKEuA8KKiYLMVbgPPAm46GhQhwDhRSSJbhLcA54E1Hw5wFCABzrg5zQwCBIQVcf9GvmQr9/lTS78yZ7EpJN0k6VNLdklZL+tGQi2IsBBwFOA8cwTi8SAHOgyLLyqIcBDgHHLA4tEgBzoEiy8qiCADZAwgggMBDAq6/6E2byW3A90s6QdI1M5h/IOktzb97o6Q/AhuBzAU4DzIvENMbRIDzYBBmBslYgHMg4+IwtUEEOAcGYWaQoQUIAIcWZzwEEMhF4HhJB01NZpWktzb/vFnSe2Ym+v45Ez9Skjn20ZK+J8ncFvx3zT+fJum3mzb/JOkoSd/NZfHMA4FGgPOArYCAxHnALqhdgHOg9h3A+jkH2ANVCBAAVlFmFokAAnMETKD3Gw4ybf+9fKGkD0r6sZa+TPh3sqRbHcbiUASGEuA8GEqacXIW4DzIuTrMbQgBzoEhlBkjZwHOgZyrw9yiCRAARqOkIwQQGJlArF/0ZtlPlvTqJujbV9K/NYHfX0j6E0n3jsyG6dYjwHlQT61ZabsA5wG7o3YBzoHadwDr5xxgD1QhQABYRZlZJAIIIIAAAggggAACCCCAAAIIIIBArQIEgLVWnnUjgAACCCCAAAIIIIAAAggggAACCFQhQABYRZlZJAIIIIAAAggggAACCCCAAAIIIIBArQIEgLVWnnUjgAACCCCAAAIIIIAAAggggAACCFQhQABYRZlZJAIIIIAAAggggAACCCCAAAIIIIBArQIEgLVWnnUjgAACCCCAAAIIIIAAAggggAACCFQhQABYRZlZJAIIIIAAAggggAACCCCAAAIIIIBArQIEgLVWnnUjgAACCCCAAAIIIIAAAggggAACCFQhQABYRZlZJAIIIIAAAggggAACCCCAAAIIIIBArQIEgLVWnnUjgAACCCCAAAIIIIAAAggggAACCFQhQABYRZlZJAIIIIAAAggggAACCCCAAAIIIIBArQIEgLVWnnUjgAACCCCAAAIIIIAAAggggAACCFQhQABYRZlZJAIIIIAAAggggAACCCCAAAIIIIBArQIEgLVWnnUjgAACCCCAAAIIIIAAAggggAACCFQhQABYRZlZJAIIIIAAAggggAACCCCAAAIIIIBArQIEgLVWnnUjgAACCCCAAAIIIIAAAggggAACCFQhQABYRZlZJAIIIIAAAggggAACCCCAAAIIIIBArQIEgLVWnnUjgAACCCCAAAIIIIAAAggggAACCFQhQABYRZlZJAIIIIAAAggggAACCCCAAAIIIIBArQIEgLVWnnUjgAACCCCAAAIIIIAAAggggAACCFQhQABYRZlZJAIIIIAAAggggAACCCCAAAIIIIBArQIEgLVWnnUjgAACCCCAAAIIIIAAAggggAACCFQhQABYRZlZJAIIIIAAAggggAACCCCAAAIIIIBArQIEgLVWnnUjgAACCCCAAAIIIIAAAggggAACCFQhQABYRZlZJAIIIIAAAggggAACCCCAAAIIIIBArQIEgLVWnnUjgAACCCCAAAIIIIAAAggggAACCFQhQABYRZlZJAIIIIAAAggggAACCCCAAAIIIIBArQIEgLVWnnUjgAACCCCAAAIIIIAAAggggAACCFQhQABYRZlZJAIIIIAAAggggAACCCCAAAIIIIBArQIEgLVWnnUjgAACCCCAAAIIIIAAAggggAACCFQhQABYRZlZJAIIIIAAAggggAACCCCAAAIIIIBArQIEgLVWnnUjgAACCCCAAAIIIIAAAggggAACCFQhQABYRZlZJAIIIIAAAggggAACCCCAAAIIIIBArQIEgLVWnnUjgAACCCCAAAIIIIAAAggggAACCFQhQABYRZlZJAIIIIAAAggggAACCCCAAAIIIIBArQIEgLVWnnUjgAACCCCAAAIIIIAAAggggAACCFQhQABYRZlZJAIIIIAAAggggAACCCCAAAIIIIBArQIEgLVWnnUjgAACCCCAAAIIIIAAAggggAACCFQhQABYRZlZJAIIIIAAAggggAACCCCAAAIIIIBArQIEgLVWnnUjgAACCCCAAAIIIIAAAggggAACCFQhQABYRZlZJAIIIIAAAggggAACCCCAAAIIIIBArQIEgLVWnnUjgAACCCCAAAIIIIAAAggggAACCFQhQABYRZlZJAIIIIAAAggggAACCCCAAAIIIIBArQIEgLVWnnUjgAACCCCAAAIIIIAAAggggAACCFQhQABYRZlZJAIIIIAAAggggAACCCCAzdtdyQAAAg9JREFUAAIIIIBArQIEgLVWnnUjgAACCCCAAAIIIIAAAggggAACCFQhQABYRZlZJAIIIIAAAggggAACCCCAAAIIIIBArQIEgLVWnnUjgAACCCCAAAIIIIAAAggggAACCFQhQABYRZlZJAIIIIAAAggggAACCCCAAAIIIIBArQIEgLVWnnUjgAACCCCAAAIIIIAAAggggAACCFQhQABYRZlZJAIIIIAAAggggAACCCCAAAIIIIBArQIEgLVWnnUjgAACCCCAAAIIIIAAAggggAACCFQhQABYRZlZJAIIIIAAAggggAACCCCAAAIIIIBArQIEgLVWnnUjgAACCCCAAAIIIIAAAggggAACCFQhQABYRZlZJAIIIIAAAggggAACCCCAAAIIIIBArQIEgLVWnnUjgAACCCCAAAIIIIAAAggggAACCFQhQABYRZlZJAIIIIAAAggggAACCCCAAAIIIIBArQIEgLVWnnUjgAACCCCAAAIIIIAAAggggAACCFQhQABYRZlZJAIIIIAAAggggAACCCCAAAIIIIBArQIEgLVWnnUjgAACCCCAAAIIIIAAAggggAACCFQhQABYRZlZJAIIIIAAAggggAACCCCAAAIIIIBArQIEgLVWnnUjgAACCCCAAAIIIIAAAggggAACCFQhQABYRZlZJAIIIIAAAggggAACCCCAAAIIIIBArQL/H7XyL9qEDJdSAAAAAElFTkSuQmCC\" width=\"640\">"
+ ],
+ "text/plain": [
+ "<IPython.core.display.HTML object>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "sample = roof_SVF.sample(10000)\n",
+ "\n",
+ "plt.figure()\n",
+ "plt.scatter(sample.FLAECHE.values, sample.bias.values, s = 1)\n",
+ "plt.xscale('log')\n",
+ "plt.show()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 98,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "roof_shade = shade_bias[['DF_UID','fully_shaded_ratio']].merge(roofs, left_on = 'DF_UID', \n",
+ " right_index = True, how = 'left')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 99,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "<div>\n",
+ "<style scoped>\n",
+ " .dataframe tbody tr th:only-of-type {\n",
+ " vertical-align: middle;\n",
+ " }\n",
+ "\n",
+ " .dataframe tbody tr th {\n",
+ " vertical-align: top;\n",
+ " }\n",
+ "\n",
+ " .dataframe thead th {\n",
+ " text-align: right;\n",
+ " }\n",
+ "</style>\n",
+ "<table border=\"1\" class=\"dataframe\">\n",
+ " <thead>\n",
+ " <tr style=\"text-align: right;\">\n",
+ " <th></th>\n",
+ " <th>DF_UID</th>\n",
+ " <th>fully_shaded_ratio</th>\n",
+ " <th>FLAECHE</th>\n",
+ " <th>NEIGUNG</th>\n",
+ " <th>AUSRICHTUNG</th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " <tr>\n",
+ " <th>0</th>\n",
+ " <td>4817081</td>\n",
+ " <td>0.0</td>\n",
+ " <td>111.982302</td>\n",
+ " <td>26</td>\n",
+ " <td>-79.0</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>1</th>\n",
+ " <td>4817082</td>\n",
+ " <td>0.0</td>\n",
+ " <td>121.121191</td>\n",
+ " <td>27</td>\n",
+ " <td>101.0</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>2</th>\n",
+ " <td>4817083</td>\n",
+ " <td>0.0</td>\n",
+ " <td>117.993684</td>\n",
+ " <td>26</td>\n",
+ " <td>-79.0</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>3</th>\n",
+ " <td>4817084</td>\n",
+ " <td>0.0</td>\n",
+ " <td>117.579904</td>\n",
+ " <td>27</td>\n",
+ " <td>101.0</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>4</th>\n",
+ " <td>4817085</td>\n",
+ " <td>0.0</td>\n",
+ " <td>155.862755</td>\n",
+ " <td>30</td>\n",
+ " <td>101.0</td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ "</table>\n",
+ "</div>"
+ ],
+ "text/plain": [
+ " DF_UID fully_shaded_ratio FLAECHE NEIGUNG AUSRICHTUNG\n",
+ "0 4817081 0.0 111.982302 26 -79.0\n",
+ "1 4817082 0.0 121.121191 27 101.0\n",
+ "2 4817083 0.0 117.993684 26 -79.0\n",
+ "3 4817084 0.0 117.579904 27 101.0\n",
+ "4 4817085 0.0 155.862755 30 101.0"
+ ]
+ },
+ "execution_count": 99,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "roof_shade.head()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 104,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "application/javascript": [
+ "/* Put everything inside the global mpl namespace */\n",
+ "window.mpl = {};\n",
+ "\n",
+ "\n",
+ "mpl.get_websocket_type = function() {\n",
+ " if (typeof(WebSocket) !== 'undefined') {\n",
+ " return WebSocket;\n",
+ " } else if (typeof(MozWebSocket) !== 'undefined') {\n",
+ " return MozWebSocket;\n",
+ " } else {\n",
+ " alert('Your browser does not have WebSocket support.' +\n",
+ " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
+ " 'Firefox 4 and 5 are also supported but you ' +\n",
+ " 'have to enable WebSockets in about:config.');\n",
+ " };\n",
+ "}\n",
+ "\n",
+ "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
+ " this.id = figure_id;\n",
+ "\n",
+ " this.ws = websocket;\n",
+ "\n",
+ " this.supports_binary = (this.ws.binaryType != undefined);\n",
+ "\n",
+ " if (!this.supports_binary) {\n",
+ " var warnings = document.getElementById(\"mpl-warnings\");\n",
+ " if (warnings) {\n",
+ " warnings.style.display = 'block';\n",
+ " warnings.textContent = (\n",
" \"This browser does not support binary websocket messages. \" +\n",
" \"Performance may be slow.\");\n",
" }\n",
" }\n",
"\n",
" this.imageObj = new Image();\n",
"\n",
" this.context = undefined;\n",
" this.message = undefined;\n",
" this.canvas = undefined;\n",
" this.rubberband_canvas = undefined;\n",
" this.rubberband_context = undefined;\n",
" this.format_dropdown = undefined;\n",
"\n",
" this.image_mode = 'full';\n",
"\n",
" this.root = $('<div/>');\n",
" this._root_extra_style(this.root)\n",
" this.root.attr('style', 'display: inline-block');\n",
"\n",
" $(parent_element).append(this.root);\n",
"\n",
" this._init_header(this);\n",
" this._init_canvas(this);\n",
" this._init_toolbar(this);\n",
"\n",
" var fig = this;\n",
"\n",
" this.waiting = false;\n",
"\n",
" this.ws.onopen = function () {\n",
" fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
" fig.send_message(\"send_image_mode\", {});\n",
" if (mpl.ratio != 1) {\n",
" fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
" }\n",
" fig.send_message(\"refresh\", {});\n",
" }\n",
"\n",
" this.imageObj.onload = function() {\n",
" if (fig.image_mode == 'full') {\n",
" // Full images could contain transparency (where diff images\n",
" // almost always do), so we need to clear the canvas so that\n",
" // there is no ghosting.\n",
" fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
" }\n",
" fig.context.drawImage(fig.imageObj, 0, 0);\n",
" };\n",
"\n",
" this.imageObj.onunload = function() {\n",
" fig.ws.close();\n",
" }\n",
"\n",
" this.ws.onmessage = this._make_on_message_function(this);\n",
"\n",
" this.ondownload = ondownload;\n",
"}\n",
"\n",
"mpl.figure.prototype._init_header = function() {\n",
" var titlebar = $(\n",
" '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
" 'ui-helper-clearfix\"/>');\n",
" var titletext = $(\n",
" '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
" 'text-align: center; padding: 3px;\"/>');\n",
" titlebar.append(titletext)\n",
" this.root.append(titlebar);\n",
" this.header = titletext[0];\n",
"}\n",
"\n",
"\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._init_canvas = function() {\n",
" var fig = this;\n",
"\n",
" var canvas_div = $('<div/>');\n",
"\n",
" canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
"\n",
" function canvas_keyboard_event(event) {\n",
" return fig.key_event(event, event['data']);\n",
" }\n",
"\n",
" canvas_div.keydown('key_press', canvas_keyboard_event);\n",
" canvas_div.keyup('key_release', canvas_keyboard_event);\n",
" this.canvas_div = canvas_div\n",
" this._canvas_extra_style(canvas_div)\n",
" this.root.append(canvas_div);\n",
"\n",
" var canvas = $('<canvas/>');\n",
" canvas.addClass('mpl-canvas');\n",
" canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
"\n",
" this.canvas = canvas[0];\n",
" this.context = canvas[0].getContext(\"2d\");\n",
"\n",
" var backingStore = this.context.backingStorePixelRatio ||\n",
"\tthis.context.webkitBackingStorePixelRatio ||\n",
"\tthis.context.mozBackingStorePixelRatio ||\n",
"\tthis.context.msBackingStorePixelRatio ||\n",
"\tthis.context.oBackingStorePixelRatio ||\n",
"\tthis.context.backingStorePixelRatio || 1;\n",
"\n",
" mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
"\n",
" var rubberband = $('<canvas/>');\n",
" rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
"\n",
" var pass_mouse_events = true;\n",
"\n",
" canvas_div.resizable({\n",
" start: function(event, ui) {\n",
" pass_mouse_events = false;\n",
" },\n",
" resize: function(event, ui) {\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" stop: function(event, ui) {\n",
" pass_mouse_events = true;\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" });\n",
"\n",
" function mouse_event_fn(event) {\n",
" if (pass_mouse_events)\n",
" return fig.mouse_event(event, event['data']);\n",
" }\n",
"\n",
" rubberband.mousedown('button_press', mouse_event_fn);\n",
" rubberband.mouseup('button_release', mouse_event_fn);\n",
" // Throttle sequential mouse events to 1 every 20ms.\n",
" rubberband.mousemove('motion_notify', mouse_event_fn);\n",
"\n",
" rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
" rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
"\n",
" canvas_div.on(\"wheel\", function (event) {\n",
" event = event.originalEvent;\n",
" event['data'] = 'scroll'\n",
" if (event.deltaY < 0) {\n",
" event.step = 1;\n",
" } else {\n",
" event.step = -1;\n",
" }\n",
" mouse_event_fn(event);\n",
" });\n",
"\n",
" canvas_div.append(canvas);\n",
" canvas_div.append(rubberband);\n",
"\n",
" this.rubberband = rubberband;\n",
" this.rubberband_canvas = rubberband[0];\n",
" this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
" this.rubberband_context.strokeStyle = \"#000000\";\n",
"\n",
" this._resize_canvas = function(width, height) {\n",
" // Keep the size of the canvas, canvas container, and rubber band\n",
" // canvas in synch.\n",
" canvas_div.css('width', width)\n",
" canvas_div.css('height', height)\n",
"\n",
" canvas.attr('width', width * mpl.ratio);\n",
" canvas.attr('height', height * mpl.ratio);\n",
" canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
"\n",
" rubberband.attr('width', width);\n",
" rubberband.attr('height', height);\n",
" }\n",
"\n",
" // Set the figure to an initial 600x600px, this will subsequently be updated\n",
" // upon first draw.\n",
" this._resize_canvas(600, 600);\n",
"\n",
" // Disable right mouse context menu.\n",
" $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
" return false;\n",
" });\n",
"\n",
" function set_focus () {\n",
" canvas.focus();\n",
" canvas_div.focus();\n",
" }\n",
"\n",
" window.setTimeout(set_focus, 100);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items) {\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) {\n",
" // put a spacer in here.\n",
" continue;\n",
" }\n",
" var button = $('<button/>');\n",
" button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
" 'ui-button-icon-only');\n",
" button.attr('role', 'button');\n",
" button.attr('aria-disabled', 'false');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
"\n",
" var icon_img = $('<span/>');\n",
" icon_img.addClass('ui-button-icon-primary ui-icon');\n",
" icon_img.addClass(image);\n",
" icon_img.addClass('ui-corner-all');\n",
"\n",
" var tooltip_span = $('<span/>');\n",
" tooltip_span.addClass('ui-button-text');\n",
" tooltip_span.html(tooltip);\n",
"\n",
" button.append(icon_img);\n",
" button.append(tooltip_span);\n",
"\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" var fmt_picker_span = $('<span/>');\n",
"\n",
" var fmt_picker = $('<select/>');\n",
" fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
" fmt_picker_span.append(fmt_picker);\n",
" nav_element.append(fmt_picker_span);\n",
" this.format_dropdown = fmt_picker[0];\n",
"\n",
" for (var ind in mpl.extensions) {\n",
" var fmt = mpl.extensions[ind];\n",
" var option = $(\n",
" '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
" fmt_picker.append(option)\n",
" }\n",
"\n",
" // Add hover states to the ui-buttons\n",
" $( \".ui-button\" ).hover(\n",
" function() { $(this).addClass(\"ui-state-hover\");},\n",
" function() { $(this).removeClass(\"ui-state-hover\");}\n",
" );\n",
"\n",
" var status_bar = $('<span class=\"mpl-message\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"}\n",
"\n",
"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
" // which will in turn request a refresh of the image.\n",
" this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
"}\n",
"\n",
"mpl.figure.prototype.send_message = function(type, properties) {\n",
" properties['type'] = type;\n",
" properties['figure_id'] = this.id;\n",
" this.ws.send(JSON.stringify(properties));\n",
"}\n",
"\n",
"mpl.figure.prototype.send_draw_message = function() {\n",
" if (!this.waiting) {\n",
" this.waiting = true;\n",
" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
" }\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" var format_dropdown = fig.format_dropdown;\n",
" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
" fig.ondownload(fig, format);\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
" var size = msg['size'];\n",
" if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
" fig._resize_canvas(size[0], size[1]);\n",
" fig.send_message(\"refresh\", {});\n",
" };\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
" var x0 = msg['x0'] / mpl.ratio;\n",
" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
" var x1 = msg['x1'] / mpl.ratio;\n",
" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
" x0 = Math.floor(x0) + 0.5;\n",
" y0 = Math.floor(y0) + 0.5;\n",
" x1 = Math.floor(x1) + 0.5;\n",
" y1 = Math.floor(y1) + 0.5;\n",
" var min_x = Math.min(x0, x1);\n",
" var min_y = Math.min(y0, y1);\n",
" var width = Math.abs(x1 - x0);\n",
" var height = Math.abs(y1 - y0);\n",
"\n",
" fig.rubberband_context.clearRect(\n",
" 0, 0, fig.canvas.width, fig.canvas.height);\n",
"\n",
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
" // Updates the figure title.\n",
" fig.header.textContent = msg['label'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
" var cursor = msg['cursor'];\n",
" switch(cursor)\n",
" {\n",
" case 0:\n",
" cursor = 'pointer';\n",
" break;\n",
" case 1:\n",
" cursor = 'default';\n",
" break;\n",
" case 2:\n",
" cursor = 'crosshair';\n",
" break;\n",
" case 3:\n",
" cursor = 'move';\n",
" break;\n",
" }\n",
" fig.rubberband_canvas.style.cursor = cursor;\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
" fig.message.textContent = msg['message'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
" // Request the server to send over a new figure.\n",
" fig.send_draw_message();\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
" fig.image_mode = msg['mode'];\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Called whenever the canvas gets updated.\n",
" this.send_message(\"ack\", {});\n",
"}\n",
"\n",
"// A function to construct a web socket function for onmessage handling.\n",
"// Called in the figure constructor.\n",
"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
" /* FIXME: We get \"Resource interpreted as Image but\n",
" * transferred with MIME type text/plain:\" errors on\n",
" * Chrome. But how to set the MIME type? It doesn't seem\n",
" * to be part of the websocket stream */\n",
" evt.data.type = \"image/png\";\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
" (window.URL || window.webkitURL).revokeObjectURL(\n",
" fig.imageObj.src);\n",
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" evt.data);\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
" fig.imageObj.src = evt.data;\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
"\n",
" var msg = JSON.parse(evt.data);\n",
" var msg_type = msg['type'];\n",
"\n",
" // Call the \"handle_{type}\" callback, which takes\n",
" // the figure and JSON message as its only arguments.\n",
" try {\n",
" var callback = fig[\"handle_\" + msg_type];\n",
" } catch (e) {\n",
" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
" return;\n",
" }\n",
"\n",
" if (callback) {\n",
" try {\n",
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
" callback(fig, msg);\n",
" } catch (e) {\n",
" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
" }\n",
" }\n",
" };\n",
"}\n",
"\n",
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function(e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e)\n",
" e = window.event;\n",
" if (e.target)\n",
" targ = e.target;\n",
" else if (e.srcElement)\n",
" targ = e.srcElement;\n",
" if (targ.nodeType == 3) // defeat Safari bug\n",
" targ = targ.parentNode;\n",
"\n",
" // jQuery normalizes the pageX and pageY\n",
" // pageX,Y are the mouse positions relative to the document\n",
" // offset() returns the position of the element relative to the document\n",
" var x = e.pageX - $(targ).offset().left;\n",
" var y = e.pageY - $(targ).offset().top;\n",
"\n",
" return {\"x\": x, \"y\": y};\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * http://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys (original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object')\n",
" obj[key] = original[key]\n",
" return obj;\n",
" }, {});\n",
"}\n",
"\n",
"mpl.figure.prototype.mouse_event = function(event, name) {\n",
" var canvas_pos = mpl.findpos(event)\n",
"\n",
" if (name === 'button_press')\n",
" {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * mpl.ratio;\n",
" var y = canvas_pos.y * mpl.ratio;\n",
"\n",
" this.send_message(name, {x: x, y: y, button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event)});\n",
"\n",
" /* This prevents the web browser from automatically changing to\n",
" * the text insertion cursor when the button is pressed. We want\n",
" * to control all of the cursor setting manually through the\n",
" * 'cursor' event from matplotlib */\n",
" event.preventDefault();\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" // Handle any extra behaviour associated with a key event\n",
"}\n",
"\n",
"mpl.figure.prototype.key_event = function(event, name) {\n",
"\n",
" // Prevent repeat events\n",
" if (name == 'key_press')\n",
" {\n",
" if (event.which === this._key)\n",
" return;\n",
" else\n",
" this._key = event.which;\n",
" }\n",
" if (name == 'key_release')\n",
" this._key = null;\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which != 17)\n",
" value += \"ctrl+\";\n",
" if (event.altKey && event.which != 18)\n",
" value += \"alt+\";\n",
" if (event.shiftKey && event.which != 16)\n",
" value += \"shift+\";\n",
"\n",
" value += 'k';\n",
" value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, {key: value,\n",
" guiEvent: simpleKeys(event)});\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
" if (name == 'download') {\n",
" this.handle_save(this, null);\n",
" } else {\n",
" this.send_message(\"toolbar_button\", {name: name});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
" this.message.textContent = tooltip;\n",
"};\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
- "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
+ "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 overriden (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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yVaWAIbxxmQCaG1x2QbQGm7cKgIQCPc4gE3/fNa9iqv7vxgBK8pTtAsBJwngpDWJygTwmiYpTADtWvwg7IcJoNqisARQDT9uHYYIcBzAMFxUB6Y0eVszcZWr66A5d3gWJoDhua6hOismgGorxwRQDT9uHYYIvLqxn5jVk/WnheHseEqMgHUEnCSAE9fUg5IKXsBZJ87DoCabrUgAUUMm7e7XuKJwYDQOo4LpV5/EsKEAUAMAtgDA4wAwwzrK3NIsAkwAzSJlXI8JoBp+3DoMEeg8G+/9APN6YMx1LoxAeCFw53LkKgCft0RfQ/+KkwTwp9X1lQng4KYb/SWAMvLG3S5nS4y8MQjDpQHAAQO0XgeAmwHgDgBAttkHAN5xZfAKX1Gwf9smYLWZAKpBywRQDT9uHYYI1Bs9Rsxq8+iRYTg7nlKkIxAqBPCH1Q2VCeCNTdf7SwAx9u4yV/QNbIuxcjMA4AMPsXf3AMDLAKANGTAJALJdxDDSt1tA588E0Bq87ARiDTduFQEIJD9HBHDTC0wAI2C5eYp+IOCkBDAfCKCV7FuHAQAjxn+pgfE7AOgIALF+QMtVLSDABNACaJomLAFUw49bhyECty+nEJxjW34dhrPjKTEC1hFwkgB+u6qRsgRwSLN1ONmaAHBCM+vTAIB/+lIdAHa71LeLNCcxNVAXAGhj0OYHAGgCAFcCAEad7oHp5wEAU5gUs440tzSDABNAMyh5rsMEUA0/bh2GCHAcwDBcVJ6SLQg4SQC/XtVEmQDe0gx9OC4pzwPAaD8IIBoDdwKAtgZtKgPAFwAwAAAuukjg3wAwHABK2gI6d+IRASaAapuDCaAaftw6DBGYm54oZtUlVsQQ48II5AsCb21CfwKAUckz8+X6RhcNUQJoVgJoRQUsYSoOABUBAG0CMV/p5QDQIGgWLkwHwgRQbWGZAKrhx63DEIEfUknTc2NdtAfnwggwAhIBJwngVyubKUsAb20uHHGjAOC4yVXEHz2GfLnfVR+dQHYCwIcenED03WJYmE0A8DMAUFJxLgFDgAmgGrRMANXw49ZhiEC3OY+IWf3T/e0wnB1PKT8RuH4RRhcBmNDu0/wchuVrO0kAv1jZQpkA3tF8hb8EUIaBudNFBDEMzHUAUA8A9gPANy47QYz9hwXfFjH+32rXJ6qW4wCgOQActQw0NzSFABNAUzBdUom9gK3hxq0iAAGVMBkRAA9PMYIRiAACiKt7nyYQNBK7B1wxAfHcvwCQDgDkKUbOIZ8AQDwAnAQAjB7/hEsVHME7xZmpMwFUw5klgGr4ceswRGBaWkMxq35xIoYYF0aAEXAh4CQB/GxlCyhRurBl7LNPnoO7/JcAWr4eN3QeASaAapgzAVTDj1uHIQKcCi4MF5WnZAsCThLAT1a2UiaA9zTHmM5+2QDaghN34gwCTADVcGYCqIYftw5DBCakthKzur6ueHhwYQQYgXyQADIB5G3nCwEmgL4Q8n6eCaAaftw6DBG4rMmzYlYz1rwYhrPjKTEC1hFwUgL44Yo2yhLA+1oIT35/vICtg8MtHUeACaAa5EwAveA3bOlt4uz41tosP2qAc+vgRyD+h1fEILffyFEcgn+1eIROIuAkAXx/RVtlAvhAi8VMAJ3cIA5fiwmgGuAhTQDvXjFEzP7TFt+qoeChNRPAgMAa9J2O2dRbjHFk8l9BP1YeICPgJAJOEsAxy9srE8CRLRcyAXRygzh8LSaA1gDnMDDWcONWEYBA33kPillO7/xeBMyWp8gImEeACaB5rLhm4BFgAqiGcUhLANWmzq0ZAWMEpmxvKk4MjMcQYFwYAUZAIuAkAXxreUdlCeColgtYAhjG25cJoNriMgFUw49bhyECcd+9KmaVdrMM9h+Gk+QpMQIWEHCSAL6xrJMyAXys1XwmgBbWOVSaMAFUWykmgGr4ceswRIBtAMNwUXlKtiDABNAWGLkTmxBgAqgGJBNANfy4dRgi8O3WtmJWQxKEByEXRoARcCHgJAF8bVkXKK6QCSTn5Dl4otVclgCG8e5lAqi2uGFBAN/b3FOg8GC9v9XQ4NaMAADUf3qMwGHjyyMZjwAhEPv5m6Ln9DsfDdAVuNtAIOAkAXxlaTdlAvhU63+YAAZiIwRJn0wA1RYiLAigGgTcmhHIi8DYlE7iwO2Jwn6ICyPACLgQYALIWyGYEGACqLYaIUkAB8y/X8x6aqcP1GbPrQOGQOy4N0jCM/yxgF0jUB1/vKWb6HpEkpAecLERgYEL7hO9Ten4oY29cldOIeAkAXxxaXdlCeCzrecgNJwJxKkN4vB1mABaAzxo4gCOXj/QPYPRDadYmw23chyBidtaiGsOqrPC67U3ZtQQ5+vH7HZ8jFYvGOgA41bHxe2CH4Fwf3lwkgA+v6SnMgH8XxthFsQEMPh/OpZGyATQEmzuRiEpAVSbMrcOBgTWZdQUw2gUsysYhpNnDK9u7Cf+f7L+tKAbGw8oPBDYklFdTCQpZk9ITYgJYEgtV9gPlgmg2hIzAVTDj1uHIQI3LL5TzOrHtp+H4ex4SoyAdQScJIDPCQlgEcuDzTl5Fl5gCaBl/EKhIRNAtVViAqiGH7cOQwSGLxsuZjWu1bgwnB1PiRGwjoCTBPCZxb2VCeBLbUU+b1YBW1/yoG7JBFBteZgAquHHrcMQgcnbmolZXV1nVUjPLmN3NTH+mBp7Q3oePPjgQcBJAvjkosuUCeCr7WYwAQye7WP7SJgAqkHKBFANP24dhgg8uOoGMav3mv0YhrPjKYUqAr06viyGPmvB0/k2BSaA+QY9X9gAASaAatuCCaAaftw6DBG4f+VNYlYfNP8+DGeXf1NatjNWXLxVrfT8GwRfWQkBJwngE4v6QjEFG8DTJ8/Ca+2mswRQacWDuzETQLX1YQKohh+3DkMELuxLFLMqGJ0ShrPjKTEC1hFwkgA+urC/MgF8s/2fTACtL3fQt2QCqLZEQU0AWRWntrj52Tr2o7fF5dPvfSQ/h2Hp2p9t6SLa3ZUk8ohyYQSUEfghtY3o48a6S9x9dZ09Snz/t8dbyv071QETQKeQ5uuYQYAJoBmUPNcJagKoNrXwbB3M8fPCBfG3NvURUxmVPDNcpuRzHn3nPSjqTO/8ns+6XMEeBJgAesRRPJce+e9yZQng2x3+wIuwF7A9WzboemECaG1JgiYTiLXhcytGIHAIJEx8SXS+ddAzgbsI98wIhCACTkoAH/rvCmUC+G6H35kAhuA+MztkJoBmkTKuxxJANfy4dYgjMD+9rphBp9hU90zq/zZafN94JX1yYQQYAUKACSDvhGBCgAmg2mqEDQEM1dRK7W4gW7lFP4aerZza1guO1kYE8MPN3cXg7qsnEslzYQRsRSCU8wU7SQAfWDBQWQL4fkeRX55VwLbu4ODpjAmg2lqEDQFUg4FbhxMC47e2F9MZlrDQ0rTY+cgSbNzIJAJMAH0CJZ5L9y24SpkAftjxVyaAPuEO3QpMANXWzlECODOtvhhtn7iNaqPm1oxAABFoM/Qd0fuSbx4O4FW4a0Yg9BBwUgLIBDD09ofTI2YCqIa4owRQbajcmhFwBoHWM54SF1p62SvOXJCvElEIxH33qphv2s1Phty8nSSA98y/WlkC+EmnySwBDLldZn7ATADNY2VUkwmgGn6mWnOIDVMwBU2lEStvFmP5uPl3QTMmHkhwIbByZy0xoOa1dto+sB7/kOR5djeSRAdTcZIA3jXvGmUC+FnnSUwAg2kD2TwWJoBqgIYlARyy5HaByrdtxqqhw60jEoEJqa3EvK+vuywi58+TDk8Enl57tZjYy42FVMxScZIA3jl3EBRVSAV35uRZ+LzLRCaAllY6NBoxAVRbp7AkgGqQcGstAl+ldBT/3pq4IGKAqfszxQFMvY7jAEbMogfRRBMnvShGk3LNs0E0KhoKE8CgW5KIHhATQLXlZwKohl/It566vbGYw4D4tSE/F7smMHFbC9HVoDor7OqS+wkxBO5feZMY8QfNvzc9cittTHceJBWdJIC3zb1OWQL4ZZefETkOAxMk+8fuYTABVEOUCaAafiHfOr8JYDBKGGPHvy7WNX3Y4yG/vjwBcwhcs3CEqDip/cfmGkRoLScJ4PB/kQAWtYz0mZNnYFxXJoCWAQyBhkwA1RYpIglgMKtY1JaTW9uBQKAkORxg2o7V4T7yEwEmgPmJPl9bjwATQLU9EZEEUA0ybh3uCNT+6g0xxR23PmbrVJkA2gpnWHcWrC+pThLAYf8MVpYAju/2E+4TVgGH6a+FCaDawoY0AXxi7bVi9q81/sU0CqGaMs70BIOo4p7d1cVoqtfYE0Sj8j2UGxbfKSr92PZz35WDsIYd3p5BOK2wGFKHWWRW8F8vMjMIteIkARzyzw3KBPDbbj9aIYD3AsCjABANAGsA4H4MC+plrR4CgHsAAGMDHQIAfCBhkMecUFvfUBsvE0C1FQt7Anj9orsFQhPafSo+mQCqbZhIaP3suqvENF9sJNJIhVxhAhi8S8YE0NTaiOdSPhHA6wHgGwDAB8cSAEByNwgAkgDggMHobwSArzBQAgBg7slEAPgaAFD0yKmETC239UpMAK1hh284+FcQN/axY8egbFn8zXFhBOxDINglaZ7iRQZzIF77VufSnkKd+Bph88bGvuLwY/WnBxK6iOnbSQngjXNuVJYA/tD9B1wbf1TASPowAOh9rkXFZ2QGOoSjsslgoT8EgGQA6KE59zYAtAEAiqHFJWAIMAFUgzakJYBqU+fW3hCYk44vvADdY7dcUu3BVTeIY+81E+qVkC3vbe4pxv5gvb/zzKHPXHzpB5jZ5d2QnZuVgYcjAbSCQ362kb+tPdnlxDAmtv8kP4dzybWdJICDZ9+sTAB/6iGy+dQEgBOayZwGAPzTF3Q5zgIAtC36TXNyPADgggw0aIMSQHQd7+1SE8cDwJ+YhwAAOJdkgHcvE0A1gCOOAH62pYtA7K6kuWrIhXlrLQEctvQ2Mdvxrb/0Oetvt7YVdYYkLPZZN1gr3L78FjG0sS1Rk8OFEbAfgWU7Y0WnrWql2995AHt0kgBeN3sIFC2lEAbm1Bn4uQfysEvK8wAw2uA4Gi3vBoD2ALBIcx69wvDBgVI9o/IAALwFAMhHCgMA2huhTSCXACPABFAN4JAigNLpA6fsj+OHFiImgGobJhJa37TkDjHN79t8ERLTDcZYiiEBnMODDId1ClECaFYC6IkAvgkAnQCA3m7zlq4uez9MG4Tq47qoHAEAvHlQShcuAUOACaAatCFFANWmyq31COgdZOxCaPxWfIEGSDtdGUY3nHJJt9t3VRPH4mvuteuStvYT+zne7wHS70RHQC6MgD0IhDIBlPeKLxq8AVFRaFLnl12dvwCK59Kg2UOhiIIE8OypMzCxB/pzmB6rFRXwfABAdYf2ZnEzAGAIgdIAcMHfyXN98wgwATSPlVHNsCeAoapqUVtW49Yd/6a4dgt6Upw7WVrPeEp8XXqZusnKlO1NRV8D41cHYgqO9Pnqxn7iOk/Wn+bI9drOxIgRAIv7vOrI9bbuovA8WBJqhlaIHkcA4ot4RMBJCeA1fw9TJoCTeqL5nmkCiHVRiochXzD0CxZ0AtkJAOjsYeQEgvki0YhYmzYIjaTRMxgJ4HneToFDgAmgGrZMANXw49YmEHCaUJkYktcqnoiyar/B0n7lTgxXRqV5LXy2UXGaiAYLHp7Gke6SVMfaLKmevK2ZuOTVdVYFOwSXjC8CCKAMA4PBQJEIokfYdQBQDwD2u0LEoJ0gvbWRLSGGe8H6UgWMnjtIDLEvLgFEgAmgGrhBQwA9heRQm55x67EpaM4BcHsiSu+5MAJ5EQiUatwsznevGCKq7s0WqjZRpnREAURgCxPAwOIbDr07SQCvmjVcWQL4a69xCLs/YWCwPoaAkYGgUZWBTh5I7rD8i9YhAECeYuT08TT6vQFADQA4CABTXceOhsOaB/McmACqrU7QEEC1afhuHSqG/eEQt2zESjSBAfi4uQjBEHLFThKE9/IAACAASURBVJW4P5NPmPiSqL51ENqTcwk3BCZuayGmNKgOCoeCu3gaq5MEcOBftyoTwCm9URPrNwEM7sXh0bkRYAKothlsIYD95+ELEsCfnd9XG00AW4/ZhGGaAEYm/xXAq6h3HeoE8IX1V8C+MxRUPFQJYKjsFfXdBmAlnaI/152VhjFyAXrFbfKnWb7UtSODSufZ5Aswrwc5EjlVEn8hh9OUa581fcnR6ymsnZGjFhNA0zByxXxEgAmgGvhMANXwc6S13aFrpIrx0xaGMbJsm9PI1YNFX2OaioTsIVMCqQLO2E0e0FhiagSnF3TILJQDA43/gRyjtt9IjlKRXpyUAA746zZlCeDU3iJ2qb8q4Ehf5pCZPxNAtaWyhQCqDSE8Ws9NxxSQAF1iU5QnpM9XbDcBVB6giQ7WZWDoLYBGMbu81g6Uob2JIXqs0m3OI+LcP90xo5O9RYbAwV6DNQyOvTMOXG+eMrnYeUW7CGD8jy4iecNTEIq/Z4mpkwSw/8zblQngn33GMgG08wcRZH0xAVRbkLAggPHvviNQ2P4Q595W2w55Wzd+eIw4sPadkZa6DZaMGvevvEmM/4Pm35uah7/1TXXKlRiBACBQeyypmnfc7kzMSiaAAVhE7tIyAkwALUMnGoYkARy0kLLsBFueTLWluLS1HTZJ+l6thqCwYpto9Vp24+hvf1f9d69o8muHj/xtyvUjCAGrjmWeJIAz0+oL9PrEbQxaFJ0kgH1n3KEsAZx+mcjmwyrgoN1RagNjAqiGX1ARQDvVqGqwcGs7EJi6vbHoZkD8Wju6c6yPxlOfE9daO+AFx67JFwpOBDg0Tt51cZIA9pl+pzIBnNkXE3IwAQzOX5f6qJgAqmHIBFANP0dbo4ctluca/m77dUetoZilbzWZoNS3TAM3LGEh2CVJS5pMRGzL1UTMAl2ccpIJ9DzCpf87lw8TU/m8pcjq4GixiwAaSf3qufb1ZsV9Xfsryuyz41bK9BPI4iQB7DXtLmUCOKvfZwgHSwADuSnysW8mgGrgBxUBtDqVCamtRNPr6y7z2MXHW7qJcyOS/rF6mYC2a/pnbviG1f2DM4d43TfIJjD1MWs2gVYBdJoAdphFWZ2aVyQHFrO2g1bnF8h21ywcIbqf1P5jw8uoEv/YcUQ+0ocHhnzIoO0bsmoExJu8xz+5dsOzu5EtcagVJoDGK4a5gJkAhtpu9m+8TAD9w0tfOywIoDcIZByyrWeig5oAShu7rAuYj9w4NpfaUhu3lnZ6Uw43FxXGtxZhEwyLVQL41qY+or9RyTMDMQXb+3xszSA4fq64u99Ahsu5YTFmkAL4sa1QVTlS5qQnua/TPXaL0jXli4vqS0vc95QHOe0mmWErd1iBDCfkiwD6K8X+dmtbMfD5x3Ix9ldyOS2toeijX9x6pbUJRGMnJYA9p90FhUsVszyNc6dOw98sAbSMXyg0ZAKotkq2EEB8YGJ5o8lEtdEYtFaVUHga0A+pbcSpG+vKDD/ehx772VuiQvpdo2yfI3b47Lqr3P2+2OhX9/fWw0gqce76TPG5sh9li7C79JmLKS8BZnZ5V6lrGUT527TWAR2v0iB9NJYSwP96vR7IyzjSt5GaUUsAV2bHinFIcv5VSkfx/62JC0yNL9ASwGFLbxPj8PZiYmqgflaSKtvf9zcRLf0Nci/V1thWTwA9YZz8LEnYN73orITdH2icJIDd/7xbmQDO6f8pTo9VwP4scgjVjXQCWA4A/nblI8SchO8BgHB7MllsIYDyWrW/dNmi3GafOkgSwKNnS8DYll8bTmtjBqZgBNh9jjJQaLMOLNkRJ461qZ1mEpLgqiYJ4NLxzoW4qf8b5jcH2HglfepLgyl0fMPAS89LArjzdAVRB4NAS6nIkITF4pjfJOPb10S79CFPiM9AS0jsJvvepFtabDteQy8ZCyblfcmQ+7t+DOag968k//q8aLDpqv+Zapif9namBmhzpa6X5ZL8f2eQ6h+LKgHUD9PfF05f05SajXcyKMPR9M546w98YQIYeIz5CuYRiHQCWAgAUEaeBQClAAB1Bi0B4LBJCG0lgEbXlIFvnQh6G8i0U4EgtybXyLZqMi5fg1J7Ap4SL5Bqu0ATQLvVsmYJoL8LPWTJ7aLJt21EsFvDgvaTLzWZIs7JHLQy3AgeC+aQI/7gYTV9nycCaPbaF/ZRAPiC0eoB4M1e01s9rROWHf3JPqSqf16nRyEqCgVqAZWqiedS1z/uUZYA/nv5J4Eeq50wc19+IhDpBFALF4pcVroI4CGTOAacAJoch1I1fwP3WnEICQcCiCBbfVBi217/kmpqVldSVckSbl6zAxfcJ6Y2peOHSvtSNo5/zxWo/EHnpLj6B7fWRi9cCOCrG/uJaT5Zf5rSvjZa5Drv0Jpte9j7mnkigPPT67q77RSbass+8taJp9y9dl/YSQlg56kjlAngvAHC+YlVwHZvhCDpL9QJYGcAwBDuLQAAk4SiIdhvOmwxKi3WQS+GNQBwPwAs1dRBNfBcAEhw1fMnem3QEEAz0gxPe85fAuipH2+ppeK+cxmp33ypkXogfgta28dQSx0l1V2Z51AoDRBVKAuk+tcurAIZY7DzbMqqMK8HZVlQLbE6FbZqf/60bzWdctgu60upyPwtvmxwY78hFWr60Fz1Kf7fpxWpnmcuM6d6NhrXlO1NxeGB8asNh60lgP7OK9zqMwG8dEXRCYQJYLjt9LzzCXUC2BcAOrgkd5MMCCAGZ/sGAO4GAPRWQEt99LhAF7MDuqWtCgCTAeBqANhvctnDggDiXH2FuzCJB1fzgIA3VdcTa68VrRqU2HUJ0dPb/2G9hTviRf32tbfnuVqg1Ff+LmqL6U+LJiv6vuxvU8P6RjaTKpJYs4NC8teq6k5R/ePm37mbyVzHeECb77j5XSTZXflZrhOCLwJodixO1luzM8Z9uSa1Mpy8tNdrIUl7dM5gUSf9DmdSt9k9eSclgB1/v1dZArjgCiEPYQmg3RshSPoLdQKohfGiAQFE0ofB7UgnBVAQAPCO9gEAkGV83oIGD7MB4BeT6xM0BFCO14w60YhUMAE0ueIG1ewgXkZr8vKGy8XVnm7wR56reiKA1mdgb0sZGsSuuHDenGbMjnzEyptFVS2RM9O29QySAC697BVDNWnHv8lha0HPN8CIAJq5RrDVCVUC6K9zVH7g7iQB7DDlPmUC+N9AYcbBBDA/NosD1wxnAogB4dC5A8UrWrUwhsNHte9Al1r4FACccG3y/wDgBgBY5wF7dBjRBlYqAwC7jh07BmXLkgdtoIqV0BryRu7rLX7lzlpi2M1rkbTDqKzLqCkON4qh4L7+ekcGCpdg6NcMAdQSCbNj9kQAsb2V3MJmr6taL9ChTbTj82RXqToHbK/1gP9wc3c4exEDBUDAHYB8jd1uj1hf11M5X+cnUp1vG0xE2lsx8/KK7Y1elvB4xm60AgKIqbHX16UsnW9+j0vC+4n1MDNMAC1Bz40ChEA4E8DqGNkENWUAsEiDH8Za6YKRTQAAg61hBFnEAf9Q3i1y33goGLfjEqMcKwQw9htXaI6hFJpDW5o8lOsksOZd6zcbM3sGPSxfaE1ejmhn5slDVE8AzfStrRP3wdvi37T7H/G3qXJ9MwRX+SI+OtATQK1qUBssF+MJNilH4Uo6lNkqPo1suIKZAPoKg2MV63Z/0W9lUW8j4b3VXj23C9YQSP4QwGCX7Gv3sVkC+PRatNIBeLkxWuw4V0KNALabcr+yBHDRQFSWsQTQuV3m7JUikQCiZXonAKCQ8/4V2ySA3pwimvyRm9ZszeWBSWumjY2mJUhOpkXyD/rQru3NK9LfbAn5gYQ/AYXtdgKR83WaAHp6cUjfRZImLLE1AyNtyo81NntNu4KeSyKL2XtuT5xv9vKX1PO0HnpJdPy7Lm/yh5z3JpeDdlIC2Oa3B5QJ4JIr32cCaHlnBn/DcCaAZlTAqitkyQZw2U7KHtCqVrrh9aW0CE+i7ZG+DF82XBwa12qc5fFLAth/ysNwT3eMhQ3wWP3pl/RnRr1pZhCxn7oygdxtfyYQX9Iws6pwM/PAOvFjXA+Skb4fJDJrxB2T7xLda8NiSO9rPI75cqVzgdaxQI5pz24UaFOpXmOP2aEa1rPi8egPAQyUx7cTRFkfNFq+jBWYSYG5V38wErZk5K5FUsweGLTwHnFuYnsRMy1oSiAzDKlOUv4utp+pIrpCAhg73uURPSyvR7T2WvpoB3PTE6F2YbTgoeKNkAeCAPq79k4SwNa/PqhMAJdeJQJksw2g6oYP0vbhTAARcnQCwZAvGPoFCzqBoKEbWrbaoUeyRAB97QU9AbQ7u8D1i9ApGmBCO5Hmx2sxIoD+tHffmPOBAJox/JfSjENZFHLFjOeqJIBxTXeBL0cH+aA7e7HQJUGD9QRQvxBSArUwi2Ki3Vdvjq/lMnXeCgHUdyznZZQLt+tsIvn/9iDSb1fxRQDrjSbTic2jPZtN+Os9bEQAPc3HyaDtKpg+uArNnAHea/ajSjd+tTWr3vXVqSSA3cpvNp1uz1efTp5nAugk2nwtXwiEOgEsDQAyYugqAECRzD8AgIlfkejJMDCYMR6JIIaBuQ4A6vkR6sUIQ4wtiH9IKJOs2AD6WhhP582q1/zNJBH/I0kat9/g21gb6zV6mB62694xZ6NolFPVKgZm25khgGb70tfz5umql7zIwMH+ZI1AQ/eP07qKy95Ui8JWSgKoqoLzNh4p3ULJlrfijQD2n/eAaOpv/ld5PSedSHytv8zgoA0EfdOSO9zNvm/jT+ZIX1dz5rwvAihtH3E0dqWAtIsA4phCwdvX00o6SQBbTn5IWQK4/GqR25wlgM78NB2/SqgTQHxCIuHTF/T0vcV1EEPAyEDQGBEVn04oGbSjWJYA+mPPpA3aa5YA+jM56ZAwrAI6Qed6+vrTR7DU1ZOb/AgCLQng0idawd72RWDLs3lJsrdUaTId375zIl0U9ChJntlata9ZSZN8CShZ8IzoQxrNT97WTPx/dR18Z8pbzBJAb+st4wDWLUcZFc1ImmV/gVIfW9mfGJ9xRkayaPpt43HCA77Jg/Tis+Y9cy8+Vq5rdxuZVQMzakgJWvOytK9GJv8lPlGViqVLbIrb+xn/RwLYdiYFb1/ch4K521m0YzPTr/bFQ6+JkKYeb+y9THSVH+Tc13ycJIAtJo1UJoArrhH7nQmgmc0ZgnVCnQDmN+S2EsBGv5OD8borKAtAIMtl5SkP6owjl+ZB1d5kzZINb2MNZNYJXxjlBwHEMclQFfhdm8VDGzfOaOySAFYshNGJKDQPzqF4wbPu6v8dw6Q1AJ+3xPccAAxRgsWTiljvNemPF6kvfI3OyxBBiZUPitN2pYSzMhaVNpgpY/PJajCq2kzRTSAIoBNp7oxIiV4Vriq19RfnQOQANrL1lfm7x7b82t8hBqQ+E8CAwMqdWkSACaBF4FzNLBNAM5e1ojo06hdtCu+t8684NSxhofjUE0BtuAhv6j0z49bXyU8CaGW8qm1QmrLtTBUoUuCc6GrO0eQ8Djt1JlCGjG3XU8YMfZHk8cudHcUpX7Z0vgigvn8tAdy6K9ehIaGmmnOJvE7iLy9CcnRuMh0nCaA/pgZOvnCp7ikn28v9gde8sa5dyhIAeR/AfvuXzBFTKhid4vfU5AtNtaJHfcZmDBYCKPfl0p4PQVSUkO4HUqomnkvNf3kYCpXShq31D+rzp07DymuFw1sgx+rfoLi2rQgwAbQGp+M2gNLuyIpaw4gAaqeNzgh7ckjl+EoMxcz2ZQOmMh5vkPsy9Le2XPa0kqrTVVnkxf1io199dqyXdPgTI++tTX1E/6OSSQIli5GkA0kXlpRrnwUpZcT/MUMFFk/Bc31OwM8KeO0yRU+LVtM7Cw9CUczYpEovUDhVSLRJH+G/x7gVAnj6DAV4RuzMFJmZBOtuGIihQT2X2I8o/mX6vc7HvzQzF6M6gSCA+piKKnmItQQQx6+VjmvDyeg9ho3MbrS/Mbsk47GfUw7s9DsvTVfnpASwGRLAkgoEMOs0rGICaPVnFBLtmACqLVNAJYDaoQWCcMkb6fFzJcSlMBSJGRswb2phf0Kk+IJeej9jPanu9NSm49W5HqcLJucSB6O0aTIIt7hJGwTi9jWuZ9ddJapoCWDyc2QbtumFkW57qqFzSM2+41ZKF4ZFEsCsfaUh3UdIHOkljOuidTx4rNoM0Zc2w4tdBDD2Y1e4HgvkS84xcZKLjF6TS6gkASxU4CK81WSCIcSSANaptd+nd7VRB1Zt1bTY7XOF24musSePal1Kr/afi4Ixm3q4Ly8JoFSp/v4gnfvnLwpl4osA1v35JVEv9bpnfG27fDlv9oVFhmI6dLY0vNFkonusfec9SHu13G54rTFl2Ex8iX4rKc+MdP8eNl45GuJ/cDmi3ejZEQ2l6xUKYYIngGu/fgRa9t4ovhu9GJshgFpQ7SKAsk+j6A1MAPNlG/NFPSDABFBtazhGAP0ZZos76Aa74gv/DdU9ZQKJ/daVuWTIE2CGAF4sfFE564c/BNATPs2nPQO3xpPa21cYFStx0+TDbPTgn8Q1pMpM7yWMDgVYftncFM5lFhffjQigNmOKNhCxVMtjO33oFX9i9Pmzj6zWlarVU9tIqrzdRLxEq9fStrNKALV9SAI47VQ8YOgeLHclzQWZCWdJdpw49tKsK2kNXZI9f8PL2DFflT6SJr8A/eKJPI1pSnvXzmLGphBj6G04UFVcdkS9eeJT/xvVvsChFLtWkUyYeoycmKb+TrH8f7nlbXeKSvmi1KQMpaw0im0q5/nC+ivE1+ca/i4+Pd37rOIi71/limS5SbGTBLDJL48oSwDXXCsk2KwCtroJgrwdE0C1BRIE8IuVLaBkmUIe7WVGr8e0wwCjG1LKNTuLUSw5IwI4YD6FQpzaSaT2AU+xBY0kZnK8vjzcsF6dt9+BC0Uviib5kfZNjy0SQCwr+5GkxVsxIoD6rCx6FbUvVVbtL9+AtvW3w33VKNj23WtuFp9a1aE2n61WVeYrhR06jEw43AbOXiCiMr71l76m6D6vD3isbZj0Ir1A6L2XzXaOBFCSP2yjSgDjPiQ1anQiOZXYnQpOS1YwhuHQmMXiOrcmLnBPWTrn9IrbZBYGUc+Xk4cvpyC/LmZT5VbTcyVwy/q+AjJEVPlyp3zGyfSm/vQ2PK0dq/Z3qL0fIWHblVNedFOwwAX4tMW3bmIuc5QHQlOiAqv+nuIkAWw8cZQyAVw7SGgEmACqbIIgbssEUG1xAi4BNBMd398p4MNs4mFMgwzw18b64jN9KKms9G/BH2/pJo6PSDKKtkNX7jArN3L/f70omr++SLspXzZT/s4l0PV9peUzSwBxnBgORet4IFXwSzNri2n0qrJZSCykurS9KxfwtMzG4rw+84snUiIDMWMbTw4kdhNAKeFENZ8/pNvM+kkCmHafNTs6X6TEjLTK1zg9qc59EUBf/RqdDzTJ0RNAHIMM7eMrULovrOV8tBoFPBb7hctu7o68dnNaAiVDYNUvt090U7HIqTz5gLVrYBR3MBAhtPxdPyaA/iLG9QOJABNAa+jmcQKRORelwb0n431flzJSI9lJAGWqsafiphHhiNsEsd+40i+5CKA+SGyoEEA57u0nK4m5HcqmzB7+Sov8Te2kXVNvgaclydh9gtSiGFhYEkD8P6pwtjhes2gmLDtJasbMMzQHlHZgeTh6lviU0g5P+8wMAfS1F/G8t3iFeD5hIklVtw56BowIYI0yx8R5KXW2OySPdIbZfCZaXOf6usvyTKt32xfE/ym3ko2rkVE+Hn95w+Xi/NMN/jADi2EdST7KxhwX59cOoGsHothFAJOfddmtvui/qYjqvPQEUN+fJHBlC5O3MNoV4r2oafEd4v8/jzUVnzK2JX6XaxBXby8kRR0Q51FKKEukEcCGPz+qLAFcf50g5iwBVN3wQdqeCaDawggJYCAJoHZ4qF7Fsu0R3zlo9dPyFf1f1pf17qs8VxxamVNDfGofrkZOEGowmvMS9XYNOW6s42SKKz1unq4tCWBMqSOXPJi0eEqj+8+afifqYfBeo4LZQHpVIXXkgTO4DekhqS3espWYWS9fBNBTH1piaOY6KnVU9yKaRrStkCaGIAmgN4mgDJvjKWRO46nPib4CSQBV8DJqq98n8qUP63qT/KuOw59YgBjJ4Ja4ReKSH27qIj7RcURf5Etuz6pb8qyprCel0/i/GbMQ1Tnq2zspAWwwQZ0AbrieCaDdeyCY+mMCqLYaggDGvPkSFCxRXDnUQ6NHXOnV3qY38vj3yfYJKlFYjQJ7yXnAHwIoPduWnIgXbbUExSjrglQ/jqhERtlYVOPDeQtBIsdwZcM14lr+GKRLtfLFZVFQvguphbB4UkPjubEpnUQdbbgI/F8+jG5Kp/RrCzdShkGtBy/+78meU0+why8bLtrr1baS4OVkFxXnZeq99zb3FP9/tpli/0kCeMfKodArlh5m6A0sxraD1rJ97e3i05PziswpvfQy8q7E4ktl7a6o8EWVeOovXfdNevFJfTTvi4/R/MwMGyVFN3Ukx6C1x+gFR0opPXnlTkhtJeq9/PGN1M5kCkQz4/FWR3W9vNkfW8kxPmU7Sd4GxmNSpdyilQBrj0vC9XryJHH4lbR+4vOf7q57m6uyDNFSpeRJcUQfO1K71jJz0V87k/IQbf19xiiPua/1sDOKgdG1nCSA9X96TFkCuHGwCCPFEkBfGydEzzMBVFs4SzaAvtSMUsWzaAmmLAbY/kCu7ZOZPLDSG7JpJfKEQzWItEWqlHRIHENSYEQApQ3g+YuY5pjKgPi1oBJQ1QwBTLuZ0k35U6wQQE/9SwJ45672gFkDan9F8fPMEsA+rSh7y8xllM1FSwCx77cy64jj320jInHyJJF5JIComioI5DiDNnvyIVumYDaMWHkTlClBajA0yMciCeCEzDbi/+nTyJ4z5em8qjwrBFCG7dDG8PNnTbCuVXtPT/lik15wOaU8F3hVpZ4ASjV7TBFMLw7w2yHyQP2x7efiU/u7sFvFjf1rQ9RoU58Z5Sg2Wic7HdC8Bc72RAC1Y5LSOTyGZihfH6CXHQzhonWEkmQbtQ7a2H3agPJS0ppzuojp+I14LV/mEZ4IoF0vNUwA/b2bcP1AIsAEUA3dgBJAeXOUQ8SbXrWyZGM0s4tI0m1YJAEcGENStSfrTxOEZOkkcibAsuG1Sx+mWhvEQGSIUIM68K3lw7xoQcrg8XFzUsNqixWpgvbBczSH7NHQBlAGln43naR/N9VcCn8frg83R5Oq69NdpOq6pTpJq/Q2bnJciS+74qrpCKA3xDxJuuwggGYdBuxeUTuCiHsigB8uoDWaeRlhPTsrSXyuPEEOPE6kGtPnvpUvg2JcXu4HduOs7U/eM/CYzCts5nrSgemuKXeI6pXq5b6Yagmgti99RiFP4Y8k0dRLGbW/Q/zuLcOOlZBQZubtJAFM/vFxZQngphuEjThLAM0sbgjWYQJobdHyOIEMmj0UipQqGvDk40b2RTK8C05DqrHwO4aCOdyaiEz6HY/6JIAovci6QFHj8UauJYDTTtaHAaU3iHPxNfdaQ8yPVkYPcjs8NY2GICUstSuRhGdW1zHgzZnDGwHEILVYusRSeit8YN9YlUKKSJWZVnIjCSCev7rOKpHzFwkglontPwFJxvQEUK+G80fiJoM0XzhPP/1ABCCWBLBKKVLnqUgTzWwbGUC4Se3dovqvHT4SnumZJ0u6m2+6iiSzeikjOkIUaU12mWi3Jz3apRmBJB33zx7i/i1pbeT2nikHrUttE+dQUu5P+SqFJGDacDOyvZF0Hs9ppYxmCKAdhN4oNaS0vaxQmHJWY3l3YU8ocrgIpD5GL5cH95B6fetZuq9IkwX8LvfwyN+HinMVXZoJKeX2hCOGVcKy47bHwAoBNLs+ngigmUD53q7hJAFM+uEJZQK45UYR/9VfAojPR3TnRu8slEJgDLKlHnDBHKX0ppu3oKdif7PrxfWsIcAE0BpuspUlCaD+klLyNO+vJnCmci5p82dodd4iO6lBvUlaNOuDDuLzVN8T4vP1ppPhwb9vcneJHpEyFMjC7HiQKl8MeqstE7e1gD1nKfbW6hMxl9i0+TPGYKxrRAC148SAubJsuZoM/H0VfYBZrC/zOj+89jrRvEtMqlvCiKTsXEYpGNV3qjj37vru4rNnHNn+7c8hJ49V6TXF53ZdpoTkX0n9LEmOr/EF8jxKX/YdKwuxFYlQY1ElgFZy9uoJ4A0JK8RYVhytlce+DAlgdp0z4lz6LY+7Y96hah5frm6oRs8tTzlxkQhJArgii7y3zcb7VCGA723qlscJAkkamgtg2Xz1c26b1v4pfW1ZA097RjoK4fll85JFNT0BvPwJMmFZ8o1n5zX50hBd6gR0rJQKY9cSOX6g6RzxmXWhKNQskgnPzLta/F+gyEWoUS0Tss8WEf+Pqf+z+Byxhmw0/Q03ZdbhSRLA3jOJ5O64/VEwY5Yj8YsAAng9AHyD71q45ADwED6WMLso+qsZ7KMKAEAG0VQqukgjplH62tO+4+P2IMAEUA1HUwTQW3BlvLyWAOL/KU95tnXypB6RBHDa9ZTKS+bylblRP2j2I9y7gm6O4hpe8p5qUyhJp4k+pcgbNaZGYCSAnuZlZXmuWThCNJvU/mO/msd9/6qon3aTsT2iN49TM4GC0SHnxXX9oFvtreI6UsUsCSAe+2zgF+LcA6sHi8+W1TPEZ7fym91zQYmRP1kv5ANqc2p10QdKT/TF7AMQ23nLPIIEMOccPZSNQvCYyQns16IBgD5OIDoJZGTRSwvGXpRl4IL7xFe9g4Gn6+mDp8t6krjh/7gWMpyPNiSJv3MwW18GZZbOQ7KdngDajbMnCbyWAEq7SP1c2gyll1MtAdSmfcPf/phtpGKXShJE0QAAIABJREFUZivHzuVKb6MKU+o3JID/++M6uLr7Elh0gPJxD6+9EBKK7ndfMtAE0Gj/BysBTPxeXQKYcpPfEkAkfRiPiX5sAGhMjjcxzEBA6aS8FySM+NZdDeUXvirzeTUEmACq4ScI4HNLesLzrSlGGxZtDlf83xcB9JZGSqvuQ4LyWpvJ4hpPrbgS7mpEmQq06Y7kG+qIVCIQs7vRzVcaaf+aSnaAKM1qdSudW/YVvZnLB2TZIuR08G2bsYASwEfnDIb5/aiuJIB2q2StEkCjUBKSAKYcqgznL9AWb1GNHGJwTp6KWQI474l2MPfPx4SECMuZC4VgVK2Z4rvMFCE9FX9Z0lIcR4krEsCXN5BEpuB8ige47q2RoI31iHUOnisDzYuni/MHz5cRn0fPU0xALFoC+FODr+Hp3RTHzigfauy4NyApfo84ryWAMner3DtWCODyvTGiX720RQbPXnM55QTWFn+ICdZdtJ+kaov7EDnXF8yksXszpROTgaIl9vqcwzLAcdniOe7fhZTWTtxOzh1Y1l1BElVZJOk6n11YHPpfR0odhuXY+ZKA+W+x5CcB1OOixdko/h3uCyyDW5CEU+bp1fcj7xvrjtLLQ9oMWo+Nr9BLqrw/4fcHZ1CWm96t14nPQRWp7+e3DRCf7StTuB0sv2wgvFGajb/9D9K7Qe0ypIrHfSwzg+D/mB5Ob3pR5ydyiHqy+XTxOTszGbqW3wJbcygm5IZ+VcTnobH0+7myFqnn9bEetU4y0iRjy+lqwm5a3uOwXcEC5KSFZjYqqRedlAAmfIcEkJzNrJTzWTmw9WbB2VD1QKokKhiWgkJT5C0oyUO2jnkvf9OcGg8A5fARY2IcuHnQCPpOE3W5iiICTADVABQEEANurhtEN1QsegJo9hKeouHL9lqCUmfCy4YEUNY147XmiQBqJSRIALGknqaH7PoTNZRsHVveTkQSy/Kx/sczNIulvp4+MbyVfuQDAu31tEVKAGq7Yvx93nI8GBFAbIP2emfOFIbiS4jQVemfARWKURBotPuTYXte/WQwtLthNaw+VAM6RFO4FxkiR9qB9SlFtoa+CCDW+aE7ScKkHZaeAOrx8CVhrP/MGCjQigI996y1JU94IbtV0lIN70kFr30J6Jv4OPw571cxroLRhI+2ePpdSDUz1o0tn5nHnlZPAF/qRC9hWIYkkI2n3UVr6+ZP30YvZkaSaytqdaNxeCOA6zJRiAPQPToFFh4i4ijj803b00D8L20tcb9lLifSpvdm9zR/reewvk7fGvRyNn03pb70FOxbH6FAG3bHEwH0Zz30dUOUAOqngW9IlwZhBMC3BDTEbe8icbIdPhzRzo/CFnguGM4AJYhYz5PNoAr83FaHABNAtS1hSACtdumLAHrrFx98WC6UJS/Tmcvp9+kpa4DWo07rmCCdBFKueVa0l5K5t1N7QUJ5ysVqJGkyO2e7CKCWwGBWgYunKR8uFrTLkQUfLHt3kTrQSPWpHbc25IZ8y08slateSi5OTgZ6AiiJ4YwjJF1NLrWX7CVrzYdem0g6JyWxMkhy2dLZUK44Eb/teyqLzxdaT4EX1/SHYotIonT7HX+Kzwfr/e1eB/z/6HlSj+ntNaWEy5chvehz1Q2iD0+Bq30RQImb7GfeWApFs+qjkbangvNEAKUq9s0NvcS10QZS/g6mp7wO9Z4nj10sm/83ErQPe09SHK3aN/ZrV5acWx53S3uxLykNwu96dbJd5NcXAfQUH9CXZF4SoZ9cL3Z6aacbMM0XKS1MH36p6YC8P7z+JpmXrPws13xFhnDZuwPNugDuaJ9rXzx1VyNx7OA62vtVGpN5mN5sALUSo2rOEOfeyOgLFy4WgMEuu0wk39K2tk/cRqOhB90xJwlg3W+fVJYApg4RknezEkBPBBCjSWMA1rY+FuQzF3mkzcEl4AgwAVSDWBDAH1Y3hBuakNrDjOQN1Q6rjpL6TD5AxENuA6krCjU6Jgy89eTNm52ZGQIovVvxGn3LkUoEPReNCGCbmpRyaVQ1Um1+cKCH+KxWjKQ+LzYiKYs/Kj1PUMuwDW0q0TUXHKBAxzK1nlE7SQAzz5WCn9a0VCaAKFEtVIhSrl28WADa1yZ1lZYASvWRNsbfkh1xsPscajcAVpwiKUelIuT9+se+huLzhhrL3IGntQQQz3WM3g5/bKH73egWvwsCiKVc6WwYnUSqxrfTe8OdMfPdMORcJBu7dVm0h6Sq0x8C6Gkt8Li2nwZPEIkyChuEx6V06Y9PO4t6SADlHAu41Gbe7E29jUMbW85obpIAVi58HN7fSfsTvbilTd6kXynoNxZPBHD1gerQJnqnqIOSW6lq/OT5a2Ffz7PiODqHSGLYqWIq/JBGan0sGM5HW+wigNin/mVMex1vAaK1ak2pKt02+CnRXBLAn9NIBWukptdep/5TYyArwYXD8MfATKYT/T1QvthWqHFMZN/Al4t9++g3U+gg7eW2nSirDYZgSjlaxS0Z9EYA5xxNhsGVUGAEgARQqvNn7iVnFG8B4fG8kQTRKN6pLxOePBvAxz9OEsA6NhDAbUQAzXoBq6iA8a0WDczR0+49fzDlutYRYAJoDbs8YWA+XNEGSpQuLGyzzBLA/w4RycEHFhYkgBc3EgFMeeZSJxCjByASwofXkVcpFl9v81oCaBTjTguFVJniMa3dnNnUW/7kK7VCADFzBobgwOLJfsnK0vpKY6bPzYwEEEub2mmG4WOkE83i43Ug5VhluCWGYvy9vamnUJ3KMmVJC0i/exQs2xkL924kaUrXauQs8vNKCh4tJTBWYxGaxcNorxkFL8cHaIdKpJ7Wer5iLL2CBclmSuxnLw5HZsYU+/mbUDmG7MMwtMyfnd93S0QxNqI+Ppw3p4ykF11BpZ/N/Y3hfCc0Guceyo1PkAR58Xd5TRSQPBUpcB6+TSVpJ5ZKpU9ektXCzJz0dWSGGG16M0kAa5Q/KqobxbUzupZW3amValsa11OEl7T589SHNvaekT2pdk1a3vYOlB9Czk3y/ofEOb7iYTh6mjQYRuQNX9KwDGtApO+5hrm2mNpxaUP52Jn/18rLrj7bSpgTQFwGXBxU35IOnpxA8A3rQx9OILdg6FMAwNhBh63sVW7jPwJMAP3HTNtCSAC1BFClO5mtY/uDeR88qGZbuI+Ihla954sASnXQ+tSaUDizMFRrmpsuTStdi/2GnLPShz4hPlGtsu0M2fyJ4zmVLskz62meMu5YhWLkuadXF0tHk04VidyMSiYJo79Fpk5D9ai3on0AmCWv3vqTBDApdm+e4LtohzZkB4WzwjlL1dT7GeTdWK3kcUEA9x0tC0UKnxfHpCrxxB4i/pIA3jbmQah25Q5oXYEkosfPFfeoqvUWs1A7Dytpv7TtPRFArCMf4vIa8zPo5SZ7H9k5pt8zyt/lzVMfCSCWBvWINGgJ4PrsmlCyENmjo+E+FpSObT5J9mfjW3+Zpy9JAGM7E7YYQFlPAD3FusS91LfaBvhrH0mYZHkhfgr8dYKkuFIyrp+wjNVYrzKpOvUe6kYEUPYhyZU372rt9SQBHDetOxSMI0dKPQlHCfovO0kKqE0V6GmhfGUvkmNM21HV/aKCfeHv4oVDyXD2Aplo/LylOUTNKOkmgM3K7xL3FkkA5frKcciYi5iTWJolPJlAjh8YWzP2M4p6kH7XKLcEEImhxGCma63m9aA9pC/+OHSYJYBaqav8TWSfLyJepJ0kgPHfPKWsAt4+VDjbmJUAYl0ZBgadOJAIolcvSikwrRXa02CIGLSl0YdaQBUHHifvRS6OIMAEUA3mS8LA+PvGjQGbsaz4YiQkvuLK6KALAyPtrGKLH4aepcnWZeD8EdAlgUgU5ps1Uj1ZIYAoXYouTBKHWccbQUEgtSjepMXnRvJiRe9RI/LhK/CsngC2KbENOsVSiBl/PFGxPqoIk0uQh+t3u3Pti5GQSMeMbFdIEnwA+CKAGLi5eKGzcCCnNBgRWFyH1BOV4ZwrTd6WtGpQpgIR3TWtf4Rt50j1O2TDMHg+cYr4fv8KsrV7qNEcmHWoPqzfQ8SkaY3dsP0YhsCi0rnaNuhadjM8t3EAdKhO6ueEEgcgPYfsp6StHqr3tp4iY/mYEkcEOcTSpgxJ4rAMS6BYkNoiH0Q7Op6DmTmUU9hX0cYz9GRwH/sN2cnd1HQJHDxDRHbezjqQsz83jIdZAig9P9Hr00yR6+kPART4LL0N9mXTWFOX1YKLNcjrHQ5SwGJMvai3kUTnnJWnKPTI1hNkt4Zl7Y4a8E2HL/MQQNxHa/fROsvYjL4IoOxP2s3h/9IeThKPxa7QJ/K4VPViXa0EVv6Ols2nVJKVm1xqX2eVAC7bShikDyObY1lwf2xNozmXWV8ESvQ6COVLZMH0pGmCAGL5fhNJsrFs6fQNPLG/ifhestAZmLWXxoqSP224HkkAf8hoBefOE4lMrrAPyhamNZuylJzUtAQQfx/1StPLLpptaElknkH7CGmkr2v2f0kALxwqJjzTtQ5ojhLA8TYQwGF+E0CECUPAyEDQmDT6AZdkEM9h4GcMcYASP1kwgj6qQ3rjY8cszlxPHQEmgGoY+iSAZt8acRixn7jeZnUSE3wQlylENzzM0oE5Xg9lloarG1CqtwFRq+CldLIdk9IY7bRQrTkwcR388WuuDW7FDvvcahYtkbus0dPwwO9EXh5cTi9jWwc9I8IybMmqBjHFKcCvNvSMNwg9vWHLh1T5olmGKdd8LQtKhXo3Xw9nXWQMSbC2SAIYV5q0CZgPuclDRLDXvGscZ1ESQKyjlxzhMcwTev9lM+DzzRRkO/tYcTcBHJawGFKziJjhtQRGawbBa1XXwN272kFGFqmrMSiykZkA7hMkgFhk1hDEqHABIuBG4Wukqva+unhPzS37z0aZXh/ZSrsHpLNE2mmaz/Q99fMY58t8qphKSxLA9KGPu6UuXyztDCXLEzHGUrjQBWgRnQHztiWI/6U9Wp5BW/xHn3YO171cUfqtaGMAarvX7klpzzl3EdlrYtETQH2uZpmpZrUrMPfsLu+Ldp9ndjBtjoBe4r+sai7aoY0hFiR0M/fkShcl0fNEjD0RQAyNg2X3JpLiRyeR85bWwUIltzf2ZSRR1sbDw3sUEsAdhytAclVypEoqs9+ND0rI75o3DHo2INu/7uXo862UXhBTll5AjeI1YvzAUqVJ4uvN5EXu5x0nK0D/qmSf/f1OUt1r1csYsmhIHXI41WsjJEZ4Tqb6M8qvjeel6Qh+x/ulNjal9hngKAH8+mkoqBAG5kJWDmy/Rajd/ZEACiy5hAYCTADV1slNAJdn0ttt99hcuy78X4UAoppzw0lKp1SuCD1QURInb0Inc4rCJ01/cM9ApiCTB9A7FkuR4pRdBG9MWKSNTNliOe4sDXEfvC3Ovd8fQzYBPLwi17ZQSwDx3AfNPUuQ5MNHqpi9qVjMqi/FvDWSR/xfqgUxvp6RkbZ8aK4/RfhJUuZtufV2i9qHZOOHx8DJmIt5CKC3zBto0zmwDj14cM1kCrJT50jKlHaCpH+IE+Kw5VgVOH8BzWVyc5TieA7lkBrVKNerDNHz2KJrIe1m0qj4Cu/iaf5GBPDsxcLwRTplZPi0Hq15k1oZIAlg96oUZkXaYsn0WZM2NxXHq5Sn0GGnThe1nQDK9R2X1k5c4+w5kg5hrmxJAFOPVoQVfcluDIuUrkkihM5PzapQfEjtC4RWio2hl2Ki6aXHSI0o7dIGJVNoIE/2qPrfhScC+N3GXCmZTNPnr2RUzlf+ptPup0wcWGqPJVWo1lPefdLDF9yHC5eShA77wuDynWtR+jt0nJFFEsDoErTue7Iogw2GOYorRbl+JT56712p3j3jkvJFFc922zxqzTi8EUDt71XaHK4+WtMtzd9+nKTpJYtQ5pcqJU7C+oPRASGAEhPUwiSWJQkshnFiAuhrt/F5JxFgAqiGtiCAby3vCM0q0o/89R19/U7MrvfUk0PyRABloGNUnex/sJaoHvUOZejAWHKySAKYPuQJ0NoY4YOhXhPyfJRpurQPC5lVZNso/+P06R903gzym097BmpHkXE/5m/1VjwRG7T36lKKJGfaXKPyoTl1P4VmMSJQ3q6HD7mOtUitejCnNKRNriO+V+hPoWC0ieT1mUdQ5bN0N63Lh81+FJ/3rboBLmwpA227U05lIwKIx/GhJDMqeCKA+LCUHrb7DlBA6cqV6KFrxp7LK9Cuk/o0ZWt2kscxEkAsKAGqWZzWDgkgElyplsMgv1UrHXdfpkJxenlB2z1vxZfBPkrIb+00j9ahMKnbpbpYeqfmnCGv0jIlSQpYtxxJgFEa6A5LklpJHCtXmzza9Z68kgAeP10c9hwgya1RdhiMD/hSK5KWnzhPqvgPv7hSBPfWF/m7uKI6vRR8sqozXOmS4Mv4jv7kdPYKpOuk0YuRJID1E4n4mknTZ0QAsW1C5YN54iXiMdwXpy9QwOydJwk7mWZSEmh98Ha891RNJIK4N6MCxMeT+rZKiVPweI1p8NBWNCvLJeBaL3wtDpIAXl+RnERkUHZtHWnKQP3THmpYZrfbftQMrkYp/NDxSRZtfm1phrP1QGVhh+kkAYwbpy4BTBvOEkAzeyJU6zABVFs5NwH8cvLVENM717Dcn271BLDhY7nxy9a/kfswQdXhjoMkOeoanwqnzxf2SgDxRovqRywLdrki+F85GiTZ69FunVu1kfgyXbNA8gk4t53i0CEBlAGNj54tAXhjfWtnH3HOE6HSepBisOCrrqPwJUZZErQE8MoqJEExsl/D456Ca8twGDP31hftdx4gfMqUoRh70WWIGGnHK6WHeBwliPLmjTduKbFcsqu2aJdUJTd9ZbUSx2DzUVKrdai8HSalkqSrQTQ9sKRhv7T5qVUiE7qWIdWWJID4/ap+ZKM3pAJ5BA+c/DC0aLUVChck55Csc0UBr9U5iiRsO86Q5AKdHOamJ8LjW65xE8BKJcjIf/8psmmLiyJpFRIe6aH898kGkHWe0m1azVYR+6nLPOFucujQqwCRAB45Q9LKVbtrQFLVXNwwe8LWXZRJIqEm2Wxi0b8sGBFArXeplgBi+105FN+xUxRJ3T9N7wIHj9PefbPZJPhhf67Jg1YdHPsxzSWu3l44fKoUJFUkFal8eZKe2+N2YDxbgJxzhSEztQL0akehkw7Lee6oCQVdoYNKFD8LMI8IjxEBRGlj2+h0iC9BRAcJIBYtsZQE8Nx5kgRj4OsmD7jMFt6/lFRKL2GsK+N2usF1fZEvTkuOxon9KbO0VC9LBN0bAZQvkB0SSdp3/ExxOHmW9lFplxQN1xaLNGuoU4YIN0oG5dodySZ70Ktrk8nKM5XohU3em2Ytope0Gsn7ISOd7CvbNqBrIgHEMmZvb7ddX2oW1Tl5tjigCYmUQia+RFh9dNPn4vPD3T1gzdZa8EyHqSK7DhbpKCSuv2II1C5B49UeFwe8FH8IIHajtQt3kgDGfvWMsgo4/VZBbFkF7GtThOh5JoBqCycIYIMJj0KhksXg5EkKYaC1cTIbDqX99W9Dxfso/Ze8qXoamjRq/nI7PaD61STHEPRA1NpEIQFM+JdsbSuWo7fdxU1/EZ937qK2GHfrjOuNHe1c0Ngd7XCwYMwuFQJoNH6ZmxjPYdJ6bfEWnBjJIpbDe6KgeTLhpJUaSrWkngD6inOG/RgRQHQSkI4g+hyn2iDJaDco1VtLDhFpxHAdWsmn1pkCMzA81+APUW/srtw4dSm7qkKNqkdg72GS6JUrS1IzqdpcOwDTY1JBr+0hzZZA37L0QEXJpyTe8eVyCSCeQ0xLu7xkvZE/LdEyWjctAfRkB4Xt0BbqbHZhSI7NzRltRDKQ0K/KJPW8NBcwerB2vIbI2oJJo0AbkLj2V29A00SSYm/+h6Sz6NmLKsTokkT6PeWm1c4PJYd6AijP41oVLULmE1pVstb2btxSsgct5XIGkmFcGj5KZGT9m0TcJAHE7zM2UBYM6XWP3/UvgZIMx5Wh9USbVG28TjwmPXPxu1byr50fkkqt57G3NH2ynfSUPh1LtnaoQcCCex2LJNPaOI143FMKPqMsPCjFK+Kyb0UCh+rjzCwiivUq0MvDukPV4MSW8tCt81rYnRUFHSsSKdx4shqUKkRqXCyzttQTRHp+el3xv3Qqw+9yz8TVJjtEs6F0tBjqv2vDMOlfjLzFZ8R+mAB6Q5bPOY0AE0BriOeJAygJoBHZsEIA168mT7vGzcgbNLYUvaX+MacVvHYl2WINqrNCvMFWLkrEDouWAJ7MLgadXCrM8xcLQIeoVLi1bG5Wi2u29RIECm2/JAGcvSUJXm5DKRxvrEtqFGkviOmcsBw9W9KrDaAnOKWadMM+ytWJxRMBnL+XHuhIQLVFqq+MCKDsf8eX9BDo/gBJ1yYsa+3T3kkG+UXpRrcq5Fn93+F4NwFM/Zzsn2TOZGnPV7rwGcjIIikUPhT1JAoJ+EuHqC0WVJXKFFzoNILl03WdoHv8VvEQw1I7+rBQL0siPzxukfAexoJG8eKBVuiCIIBYvptLNnpVE0iy1LQSqfakzaMk1fElDoqMIvqYefLhvOsUEU9vD0iJf9WapPrVq5uRGB8+XgrOnyMJ1tX1iaDqc/LiMbPpEo0I4PMdf4Pn5l/pJoBpRyoI2z8sRpJprfe3fJGQewtJ1MlzJNXSE9Wul5GH878zHhehZX7c1hIGxpIKV4Z7QdJToiCRkcWHY91OWHoCKCp4KZ4IYKfKRHqQvFslgKcyiVjF1iJilb6HVOCS2KFzE5aenWi95k4nyTaWLc+OhLjvKA9z6zqk4Viyqi6kjxjlzi/+1y7auzLvNt4HpUSwVukjcM4VAkY6MuHv4rYMIs77sslOEDN8tKuY5vZw33CI7hNIAIscKwBFW9Kea1SFXiy6ld8Mpy4Ug3dXUADwyhVPQJlipPavH7Xf7R0/d0OSOCYJ4Oj4qe65/eKy2/Zk09w3iYgvlulbyJ4aiySAO05Xgq8WkCS3Zl3Ctn/19eLTk0TRUQL45bPqEsDbRKBzlgC6Vz+8vjABVFtPIQEcPPtmKFq6qKHnqJXupYrWFwHU962VoMj0WffX/1fYSeENeVsGeXU2q0N2XM2iMqBmUZIwYBBrNHh/oiWlXdqWQ3Vn70EPfby5F4RO1cgmDm+YvpxbkPi2LEsPDPRc1tvJ6ceulS7oH9JY15tzA5IYqeKUBHD5lw97NHiXpLZDFZoPOmkg4UKnmH3HykJ9l9di86id8Nvb3d1DlQRQZDJIrQTXdiTvQSOCg8e1BPCHFMoegeGRm1ffBa2j0uGjdfTwQAKIBeMEYpH2hWgDWgguuAngoexSsHtXRZjTawx8d5ScBcb9S7EHJQFc3OdVt6QGjyMx1cZM9EQAsS4+oPUkVnq84suCJIBY18iJAHE5kFkGLpwpBNc2XenGDfFRsSvV7hX58MVjL6+hkETFi1GmCq2UVOKPn/87SBK37AtFYc5u8kQuVvic8IrVE0CUCKLHsliHFNr7KF3yRgCxzpojpOKWeZ09eSBjHS2mqG5+eWk/uo7LkUc7X21d7XH8Lsk9fjdK6Ye2jJs2xUBcwl6R3UYWXwRQ69iBbSQBxPFJ9TkSQCzyt4rfixYiE4bChc5DsUIkOUUCiGXD4Woi1BGWN6qSuQfmapb2lnJsRV1mEB0qUN2OpbbA6xn9APc+lpqlj0GvimRHiwSwXrE98OyWK8X/1Uofh1ol6XoyPNKmzKrQpsoOSD9FpiGjYnLjjvpDALM/pvnI36aU6n+3uZUIel6pbO6LuLcMRk4SwNpj1QngjtuZALp/OGH4hQmg2qIKApj48CtQqFhxn9HyzV5KPoQLvEqEIG0YZVW4ogHZIF1whT7Rv7lKAvjVzvaQEHUQWpQhAoYEEKUgqady45eVKnwGahXPdBPAj966BhJvJXu1VTOS4YqrcmPJIUGS0oen602DD9K7Q4uK9JCUBuzaueFDtWihc24CODalPWwYSLmJpWoLv2u9KvXqJT1WWgKoTXWF9bQqJilJqVuN3si1EiEZX0w+TLQEECWhy/aT4wYG25aBZMf+080dy6tJ2QxIKLYffjtMAXRxHWS4GKyfcorsA/GY1kYOnQ+OnCQpjEw3V7H0KWhWgaR1WJYciHVL75bury2knyglm7u7DsREHXVnSEAPRhnbsGrJk1BQUEpSAaLaee2xGlCyMBEiLAeySwmpni/VlKyvJYC45nEulXLKIdo7ch3164P/o7qxSpkTkLa7MoxslRugGyWPdhFALWHYdoAkWa81myw+ZY5m6WSgHSOSDZTW/b0rEUoUIXz2upxBLmtDki+UmmoJoNYz2Eg9Le1FKxejhz8SXV/7GOuZJYD4Iti0Ob2kGDlJ+UMAsQ/cB9JTW8b1bHrfGCh7Fdllyt+jlHBLTLQ4IrY9Ng4Qh7A/6VhzRU26N/25h8LpzGtImoSGH9wDpTuRjaUkgPh96aFa0LZSOlQpehyWHImHnPOFBYFsWY7MOwq59rUkgHhsRI058NW+ztC2HGGy8EgdOJRTEooXJnK27SDth2cbUw7tD7bRy5uWAK5NIWcmLJgbfMwmDD1HL6na7+5Kri/a0Ed4SN4Ps7KLCgLYpFqubevyhfTisO2RXCc6vH9hCsHzWadh/XXCEzuQUjXxXIoQAogc5loUCqNfjyvziHb5rtavJf+fiwATQLXdcEkcQKPu2gwlFcuSb7x71eIDfMbuZCGJkqVwwQuwM7M8vNB4Kiw8QepNIwJY9813oNaMM3DmSZLoIQHEon2ISSNzPN6uRjqsHNsESlyzDxLLHYC1X5Ah9hOPfwfPfnszjB+e67E5dMVwEdKkVWmXBDC9OxTrRTfqY9NIoqJVB0rbpKii2bBoN6mzfRFAPW76B5X2vJ4Aygfx/EUNoEBVl/enFwJoFF9MH5IG1cLr19B8krOeAAAgAElEQVTYZTBXSQDx2ORDFIAWg0JvP1YRLq+x3isBxLrosVu81BloWHUf7M8mZ4U6ZQ/BpkxSd3WOToW/d5PKCtVpseVImrF+STzENs8li6ji2pNDKlsjAojH0Y5US+Z8EcAu/d4Q/c2dRjHksMiHXMW3S8K+B8kezBsBRK/YoY2WwPjV5HyhlWhp7SD1a+3pfyldquPy5EWSqyWAm3cSbm+3+1l86gmgDECM575eRc5QAxuugc3Hq8L+k2Xg6A7CcHBHUsdjiBIpLf0urXWerDtTtpNaFGM0SueLdjH0GyhVmLDpU269O4ajpzlJT9V5MygIchHy4YENr17q5CE1AV3brs/zOzaLn560YDsVAogerVMTZ+QhgHIsmJHjlR4ULH7qoSbwfSzFpkTijS8yU5c0g1s6kUNYnWL74YudndwEEI/9uitX7VyuWDZcE50rQd6YXUMQd1mqlTkOkvwPSiRporRvnZDaCla4AnZLkqvFq/aXtM+xNEzYBT0rk0MKSuPvbUQe5j9nNM8TM1Gf/lHrhYx7Hsv2GyjXspjf23S/z3cC+IUNEsA7gl4CiHmD78L3EVemkdwclLQcw7Xrz9/zIsAEUG1HXEIAjSQdvgggSiampDSC65JWCgKIJbrUCdi0KxpaxJKkDR9+Ca+SYfnWJy99WCABPBd1HspEkzSiU81t7gDL23dRhP5vjubmMNVmDtCqXDG23NOrSaWCnoVSlSxj2pUvckrYt8iHU+UEsk+UBBBVvznniwjvPCwygKoRzBszyAmgfsxu94Nd2mF5I4BGfck0euKaAz8T4XiweAv/0v46in248GeKk4bZVFBljmX6gYawaS9J9NA7WEogJ2fQg6p2WSJn6LmLBBCLjC82u9s7gA+JtmWJML++kjynr62/Cv5II3Vks2q7hQMOlkIFLsKgiqROfnDVYChY8IJIF4cEEMkflkcuJ9ulNxZdBgMar4Whlf4T/7+08/JLAubKEDhZFyjmIAbttkIAsW2P7mT/dfopmq9Ub2EaQiz6UBvrMmrCgH8wEUBeJwf83yhbjajooegJ4Jq91aHcVFIFYln69cN5nCfQzODoMzFQ+oXdsGs82ZEe6ZYNhXaWgLM1iKQ1iqUwPtv/IFzvvfV3t4q9a0XyJkbyhyXzOF1r2/VPgySAsYUPw6BlmOWKyvWJRFRaliJ73ZFTh4I+lSMeRxODI0dKQfdEsqWVBNAo77e7c3x6LaPnlz7QubaOp+9GBNBMO20dGcYEQ/jI71VKnBDj0ZoWyIDg7Vwew2v2kUq86Owo6DR8eR4CmFicvOafmnmd24wCHYJkqjs9AXx1zWWifs2KRyBtazVITs6AozklhDoYi3SAwZeDW6ovdBPAzLO0fp7uQXI+eL0lO8iBq7LLWU4bNNtfAugJY3wBRwnglhuFPWHAJYC1Pn9O2QZw553C+SyQY/V3S+rro8TjZgAgd3EufiHABNAvuC6pLAhg/5m3Q5FSRYWaxogA+oq6Lwkg9l6twjEoU4QeVkgARTlYHC4UuwBFjlCwWySA+pRz2v+lNGvr8cpCXfhNPcpM4YsAZi+qCJtezEsuZXDXSsVPiXhZWOb1oJAy0/d+JLIXYJGEUhJAPIZhJ5KfI9K66YVLSas3Aoht5LXxe5XiRGyNMmLgcenJ27vuZri2wrJLCKBRPEJvBPBrV4DhllXI0xTT8GH551Ai7Mgkx48r4sngu1axw7DkWDxIR4pbai6EOUeT3QQwtuhBkfWgS3KK8GzEIqVamHpOOuGgauuzTeTUUbL4GegQTaQC46ptO0Eks3sVIhDoCXnyLBG8XSeioEVlkhCiM8kjLXKzKenTqkkV5XJXXD8kN1ikR+e0HeRwgvZ00s5z+nY6pnXakQTwq/2dYOcJwmPf4Sj4rcPHcPVi8hbFdHcrlpPUusDZAlA0nrxze8eS1CXTFU7F05riPp62iNTt6fc+IiRvWgJYauhu2HmAcEHPe0kAt98GcHnyevhzM5FtJIBYbhkwW3zuPl0O1h+hdRhcc7kg1SPb5mL2+bj+UKt/OqTsJTvYilEkpjt8rBRMbvcpXLXgHvG/6LMxSQ8xDd6f80kqfEcvUn9rHQEkAcTj2298yqPHrHSOwXrSxMMonp97AJovRtIotN9r7CK9Wsm3PoOKUX9o79egIe3/NhXSYWdOBUCHMizpJyrAldVJdY4qfkkABzddJo5h7lssc78iMl16IDlv7D1UDs6dKgwtk9MhM4fWBVXJSN5QKluowAW4qw5JCr/LaANHsktAyaJnobjLrGHv0SgYnLgC1hyrKepoVePYR2IZMv1ALUn2BRqDlgDOSScJ+xObrxGfdsXN1OKH5iBfzO0KA9qSdFKuIxNAo12mfAxvkvi2TzcVLn4hwATQL7guqXwJAZQhWqYMJgP/maueB08EUCvlwjh80W3JjuTUGfJKxHIkhR5wSACxpN9N3neTU0iFdEXCemF7VG80Ea2ybQ/C8azikHOyGCTU2ue2FztyqiTUrUieoljwYSBtffBmOX8KSbaQAOKNCiWIWLadqAQja8+C7w+QCu37Nl9A32roBG1MAN0XcH3xRgBlvLUPt3YVwXiRVDy0loK+PpL8N0zYS44TWPwhgFi/mEu6Jm0UvQWk1o459os3oUuTzbBkGtkydb9ihft02klaC0kAz6REwcMDfxfHkABiQW/G3hWIGE473BhuqbqAvh+l9Zq1IwmaRO+BLZlVoEFFkoRIAnjoqdpwJKk4nOt/RKRPwyIDZe87VUaopTCQbb2yB6BnOTKE35JTDSbsaJ6HAF5Rn+yxsJy9WChPqj0rBHBGWrKwc8IiVcDYT0FXGA8tASxU5DycySoCrVweo1oCiO1RLSZt14wIIJK+jFPlYUrCTLhvT2v4axaRqtTHc8Op4P+YZgxL/2qEtUzjhZkisET/Vgz2XE62fgWOERGQGTGkyQDGacSy8kgM7DpO6mDMwzx3QgtBAGVWihOnKcgzEkAsdaPJvGJgNBGgrdlV4daKC2BlDtmQ7jlL8QC1BNBsNAB/CGDCa7nxQrc+MRLMEEA0bUBsW60aJMaoDW8jDmiK1uEDVfhIAD+vSbbBaAd4bCKRsJWf0Nq0Hkaqz8z+tDa/tvsUXttDkvgrKq6Gp5ZfJb4jAby5FRHnnzbR+mLWmL37ykOZclnQuOoe2H2S1gNLTOmjsGBpMhSrQUQcCeAkl0o+O6cIFNxK69Ku13oYVoV+b/qMTDLN5ld9vxDnzRBAeS/H+iOS/gGpZZASXhl8XO985IkAYj9OOoEICWAJ2rtWyoXsHAgBCeAwAEAR8a343mFlnpHchgmg2uoLAhjz0fPQo1WaUItI1WjiV66wFKueF1eQ9lT4XWYekATwz3SSVMiHq3w7x2OVSp4C9IzDmzYWDCuSdYEI4rmLJBGclUH2McUKkxde40p7YNk+MnbGkAzo/JB6mAykq0cdg6PZJcRb9vITZOOGZOnfcfSmvub9vARwxuKm0KHlZqhfmt7glx6JhYIFiAzITxkAGY9hPLq2Vcn5xFvKOAm7NrSFngBiHUxFtu9gFIxuTSpQo0DRaLw9ZQ/ZMM5pQISs83pSY9coResgvTK1wYZlPLv9u+mBjUbhWIw8nCdvI0lU6ulo+HhBd+jUZAssmkvr1rvnCtifU1Yktcey97F4qPw62Yet2kMPydebkqPCq1v7itRo/WM3gFSFTT/USJzbdTIK9qZXhGYNqC2SvkYV9sK6TJJWHV5OKukW3TdB5umS0KMyqSz1eZnl/mnjWoePm38n6smC8+5VnV6YX6yyXthpeSqoTv5oU5dLCKC0pZKYadtjnMJn2pIhPpZf2iTB9i9IxXbuLO1Zrc2Utq2WAOLxEbvbwOJ9tE/xdyMz2uD/MuYefpc2hsfPl4BfVraAa5sTcceXI6kKTXTZxcpMFUfPlICM4+WE96gkgL1iUqB9acJj0iF6AcGQJEfTywGUIZX9dU2Wi8/ftzUSL1raY/ib+C2V9qJWYuqJAEqSgQTDTEEv6OeXXy6qFtpBEjQsSABlWjpUY6I3OMbcrFGe8uqiFz96sEoCiMeM1l1PIqUHcNlyWXAqqxgULkwvJhgf8aGkOeI7RhDA+ILFJpIkeOn4h915zet9dhwajt8CrUqROcTXe9rDZVXo5UU4B02gVH1S9dqvxgZ3JpEj50oC5vLdkF4dLp4rCA+1I8nqjAMkkcaXrbQDFd0EEI/VaEeS8LJFT+cxjZAEMLkBmdRgQXMTby+G/hBA+VKB/WrziOttX50kgDGf/U+ZAGbcJZ5fwawCxh/Br/juhvIRfOd1LzB9oYTbXAwRYAKotjEEAbxxzo0iDAwSwPpPj4EK3fa6yZH0rDMigPLS+hRQ8qaL5xNjKHaftGXT3lBQ7VmqJKmLscg4hHqJo/R+zTpHkhBJAPH77YmkbtHauWgN3jFbw571pIp+fcD38N3edtC6PBGUlf9n7zvA2y7P7Y+XZFvTe287tmMnIXsR9t6bP7S0UHqh7e29LRR6u2/3oFBu56W9baGlpaVAKVB2CCQhey873ntbXrIky5bs/3O+V5+sGCckJISk+H0eiC3LsvSb5zvvec8ZFMbjeABg6OYP9YbjxffxpqXqxwSArOniuPh46PReqGaKQCc0GYPPfa8AkL+rdXR/rFqKZZmyDWIi5HpDkKVf2zFsQkT4OL5UKqBdeyryaz2x3DQsN0t9fGgTXWqhyu0dSDY48c+2cuhUiMFdkxPcBIDqtVKEjbksT1gwXXrKtNgix87h8mmnRnId8iKBbw6XQ5v7mHjkNd7+X+/4NZo037VUBPXrz5Rjp/6+Mlxw6Q68UiU378MBQP1iegq7ZSTuPQHA+bNkEcIW4VQAqG1OeF40DcYhKtyPdMtkdN2+ZtGvsVXL4rlLAPjzS/+ALzxxB5ZeKABmZ2cm/rNEgNvdxWuDbfTptvdUyYb+nMcDAKfbhqEm5dp0PdUmny00vnC6fc3HDgcAv7l0cgHGIa8qRxK8YxL5phJL/vl1JJtFpvH6OQ+r6WDbF2WhOvzgiGq1v9gtCx1WqOeilnrU7shGcrm0cOcH/CwJAFm1vYm4oXA31vcUoKkxCXcs3YCXWmUBxmIrV59bQ2PCeoW2vJmgw/phszCS+j0cbWcg+EuH+eKUBICPnAAA+KlTHgByAowTwEw44AVv6hCIMDAzNe0WmAGAx3dgvCsAHPXJRZJxUrqmZo+GAkAyIC9XTF7YNADkapfxS/TuY7V7bVhdV/wOAMiLoPbg0tqXIwFAHXfV1i4X2libBz+YKxYOf+tZjCZn3LsCQA0s+Tu9LtO0DODhbnShHmNHAwAfr5EJ09uKNiumrttrCdrN/HTbeTi3VFgxgvFjBYD2FNGonZcpvnyhFjdMuPhEmQCuYwWAj7auCBoETwWA1DyxFiYIc/FeAaAe1vnvuS/iqS5hrjQA3NGXpdrGrFBW9nAAkLrOZxuFxfq3Qhk2CdUScuHhc8ti4ngB4C2bZaBiamrH0QDAZIsADgKbqQygBoCdv8yH8U5hrzUD2OK2q/ORLNGRAGCk0Q9fWyysBQPvCgA5cNM1JqbGBwaFsdWxadS4nQgAyM+YY+wNMoBF6ZNxe40OOX/jTNIFOyetJshEagBI2yDWkTwKQwEgF5JvHBTN3JEAYLRBFkEaAJIFZY7ykQBgScCUvtGVAH39OB4AGBXhR75VdLqhAFAnn/ys/En1s8MBQO9E1CF+nqF2PoezMAodagoFgOu2zlbOASx9XF5h3Y0F2c0ntQWc9eEAgNQFcMpOev8zdUxbYAYAHtPmeseT32EErXU5pjl9mJgAYgJRUmzJTFcqrm0tZQxAWFOsaieydNuOVh60gmHp/E2yGlq/1+aW9iWL1h8EGDUDwhbdkrMN/+yUVfc5STX4w0Fh1Fi+ZhMuOXsn9jhkEtczFqUGEw50pyDGOBaMY/pYsgCArx2UlqrJMIpCm2gJ9zvkRqf1WPw6NUbYhtCpRQKK5Ch5/JHqyfgzamdCAWDZl0TTdNft0j78XY3E1c1PaVNAtLE1Cd9ZQbYf+Nra63Hdoh0KALI2VMnUJ8vYZFSxYKwjTQHryd5tA7no8ZiU4JwV9WwcaCTNIpvFMlikvWs1e3Bueq36us1jQ36sbIthvxH7B2R7jI1HgBFeZeZ2vN4tKQn05vONh6NlUPZXknlYtbBCizfNj+Zuw9bBXJWekB4zgH/smo/z5gjjp7cpJ23HAl6QvKlwn29tEzaWAJD1q8azlVdjxaAwcBoAWiM975oHHAoAnTXCVNbe8oj6l21DPXDz7QUvBNlNzaQ83zgHzoFY5GVOghMCIJ02EZYuAOUT5ZLUst8pbNtUABgKTrXX3LyEtmDCCQF5Rry0NwkACYDJEL3VVYQfz3oKt2+/AwnPiPdi5+Wy78ggc1ihNLc9uCBjTu2ilBaUmSZ93DYPiJ5zV3uGAoCR6W58tGQb/tEsoHhO4mTM3dUJMgXcNJqk9lvDYAKSAkDrSAAwlMnn9v5LtWjhyKYdrvg7eUbZrludBah2TrLCGgDy90Mj2nTnoThedIssAi4dNzldTJt+nu4kvFk765B4S/6cf6N31ByUmujf0dnbNbuzkVgs58ZlmQfwZM0CLMmQgRJWvEH0fASAzUP24PVm05YShCV7kRQni7EUkxNXJovW8s+tS1Bu78Q8czO+v+NSzMuWobRut1gq6Vzsm1NlEIXMe2j0Had+78oUZpp1344bMN4ci2svkFQdZqtre6XIwMIs2ejES2tk3+Qvagku5Ph9KADUAH+sU445DQC5qL0jUbosJx8AfvP4W8CfUv6tp3ILmFqWmzi3FtyxM18c9RaYAYBHvakOeeIhUXD5f/gKImKjlfjd0GpEVNmgsvEgAGQdKY9W3+gKnr4bEW6J0MpbIhfKmpp05BV0orknHhmJA0iKkYvm3rVFOP8iufGEAsDmQTsiAmL92/K2KpG+BoBdTgsuyhZ2jJpB3thXrqhAu9uqAMud2QL0tjjzsbpBVv2jPTFYNf8grkjYgwdrJB+Ywwn2aA+iA07/Uw1qp9pW8KY1DjnM2L7pGZaLtfocV357WpsLbS8xHQDk7zV+/L8OSfmgrqkncBPo3yqTm9MBwLn3CMA0XiQ3wxtzZEqPGjoNMsaelN8nAGRiSGuLDH7k50o7lSC8qkueU5Tcg8b+eOTHO5Bv7g0CQFpUsBjHl2iRfcabEwFgdVeyApG0BLmpXPah1qQ1u+PVcxbaZf9v6pNpaz0Aw1SDnpoEPH/Nw/h01a3qZ7Rl4U2c2cUstt/YtmeV2LvxdrOAGR6PVwVizP60dfkR4/EO8TkLxIRpADhny63w+8PxjQDQ1O3tQwBgl+zj7HwBKyW2bry+eS5iMp1Ki8b6WLHY3vx+vwwX6WlkPcSh26/qh0BwwcOhJFb9jiycuUpasds7slSrnACQpbWpj78tcWOsm1ZswTlWAdI9PmHqqCclQHI6Y4KAQ723XBlQeKY9MIG8U3Sc0YVDcLfIdmb9z2WP42v7r8a3yp7H/61YhrLX+vB8rQwP0UJJL9J0LF/wF0OYoSfrFuDGgl1HBIChGcjsFoyORuKSgsrgcZNilMWVjqdjog+L0+DPdshwV9M20QSXLhct3nQAkDGF52TK4oZMMaeqdzfLZ1+RV48traLj5GcjAFzbWRi0PuLjZFRZQ6NGNOyV30sp7cbF6ZUKAHq6ZVjj6iWyyGV6CdvJs8xd2N6fjarGNNgTh5FkGkZd4Pf5vJvO2aSG3gj4VyQ24LU2WVSZjfL3/IHF0A8Ln8HnK/+feuyMxLbgdUd3QkItbaiTHQpkt9fc+LVgNKEGgJS16I7EmpYipZ1mcSE3nY+oBoBq+9zwdfVc1tTIw5OqAfzfEwAAP33KA8DLuZl5iQhoAIPbfuaLd98CMwDw3bfRkZ6hGMDMn38LEVbRu0R2GWCcJRfkI5nmHulFOenJIgBEtB/xCcNwtIsOztAjreTkRTJB2tYpDI3JOqIimPxrpRW09wv/q/5l5u/Xs17A7Xtux8iotO0+WrwNj71+DuYtkUnfPU3CAvKmqy1kXtoqN47Fc+sUY6BF8gSzWuuWFiur9K11cmNgTY2z0kzHa50lwdY0ffJCs0L5e2S3tA4uMsyP1wOGyJxS5I1UgyQ+T08PW8LF9PlPHcuCQzL8fsEOmSSe2mqfCgD5HKZ+kGXVHmSXpleo32UW8PCoERemTboLNLgT1fDFvnq5ucVWGeBf5IS3OxZzypqCwONgdzLKU2X/7OtIQ1FSjzKM5lQps0j/q0osKMICwzRdDgEk83NaFQDcXZ2NxM1RSP2o2MCcmViLZ5tlfxAAsi5dKeCVTDFb3VlWYcNoK7PzRdHZeTJ9KC1pxfJ4eZ3f71yBiVEZwpguyk39gAuQn4s/op6aJdsWvcmE8bPlJsjisc19+8xvzkXc1W3ofkOOoUfv/hluWv1p5OROMk4aAPLn+WXC2vAYYOlYvg0XiqZQA8DxQJ6wyTYCrzcS450CqgvmSqucrHhlU5o67vX74b86ctDhESZmZZIAHk5DawC43yNgyI8wZRfyamcpWiomM6qvP0vA6d8r5uFPK36rvr6/+kYMuGMQZ3IjIVqmXDXD1zFohXfEgHF/GIwx0g7VAyBakzfgkvc/Nf+agG5JepPyzmS1BTKZ+bXWh04FgPrzrrhZ9hPL/bEBDDgEeCe/EYWPffmf6uvP2GV7/WpAjlnWVGugxXfIvhi5dvAdALCyWxY7C9NaDwGA2vYlLDCtPiuzC1UNwoBrtjzVPgRT1ChaB+wY22XHeVdOTtTzuOU14OykWrzZXRSMqmsfsKmFNIblOnf1sh149bkl+PJHnsIfW0X+cXGKAPk9zkx0ui2oOygsMuuixZLVzNILz42tMkTEoSF9fDEa7/pyWTAwC/oiu+hotZk4v9bXI379dme+YiNZoQDwcA4Pep9dOU/YSy29mAGAwd1zor6gQSlPdh4wPDGnDoHIDXGmpt0CMwDw+A4MBQBzv/c9hEdHo3BhM+q2Siuu9v4jp34c6c/qpIEL8qrw0n5p4TZ+7FCxvdao5MSK7iXDKEa9q3tKcUGSXCDfcgiTp1k6WpywkrP60XswwKR8/l5o/Qqn1zQTxudpM1TqtDZVS4uV70MnTCQHGMkjAUCdCqLNWvXn1gBQAwE+HnrBPVy+Lp83FQDeXLjtEM9A+omxpgJAPrbwLmEBd/xm0pdwav4tf66F6SsTBEAccKZjrrVVDWZokPiN8ucV+8Yc4jyTA8/sF5BmiBlDun1QMROdAwLuyJpwGIFsK1voe3rkpsX3yJsIfdPYbnL5jHh1TxlKCttxWcr+4MS3thThfq8fkGsawWvodusYCWjQegXMWKNHlIXGjjYBPBHbZLtMlzqh9wv/PRwA5M/2/WRyu4UCQP7srpz1+Mqma4EAeGu8YzJVhEblrPEMAWxTGT7997UkYGJcLk0aAPp6RdivfekIAHdXybkWOomsJ6CvzNqvtrWu19tLEB2IgLsiYB1DAOgYs+Dp3QuQkS6WMCwm47h9RtQOCNjubbchJUMANuPM1nVMyg2GR2ThFzqRHLot3w0Ahj5Xvf4b9wcfCo1KnPo8fp/7uDIUhj1eWOZQAMjvOY2rOwxHAwA/+aXn1OtwoGVqUW/b6pbFJs9lfZ3QA1opiUMqyYbV5bViW3sWFqeLXplSiMaRBLxeJ8wdi6xbKAAk8CtJFsa44e8FcC0RqcC4Lwwl2Z3Kh/DRLSsR7o7AFSuFOX9xnbRmV60QJpgVEzEKa+SIStSZlySLjS1tskANBYD8Xh+DXGAeDQDk70yV8pzSAPBXJ4AB/MwpzwCKfurw9Yd3+fmH+sczAPD4dv9hAWB4vlyUeeNn6bbc9Rmy6vxcXCOK139Mfc2LIS1hOkZsSsulg9sPBwB5MW73iJbsaABgx7BV6ZL2HZQbZigA9Jv9OGeusFwVjpSg/xy/Z7LFqqQ6VA2nBAHgleV7sX9AAMaxAMAdjVm4d8HqYOqCZk+OFgDm/ULYjrB4L76y6GX1tWYAaS0RqqfTAPDThaL3eWjfBUiNE1bW9aQAr1vueUX9S/84DQC11pJt1KMBgLQc6RqxHBUAnJPWAbJSUwHg+BvxWHLrnvcEANnuT4hxodQm7eljAYDaAmc6I9x3A4D5P3sIhkwXbp21PcgA8u9PBYBlBa1gagRr/VuykNEAMHZXDPb/WMDkRctU2oCqms8KE3YsADAiRuxZeEP/oADgaJUw9NqvkAufbXU5SE0W1nQqAzi1NahtdUKZ07Zeu2qNsyUfCmL0tno3AIhberH5DA5HHsoAPrj1Ytw2X9rcZNbf/B9pw2sA+PaAxDuytEl3KAAkm02LItZ7BYC5SQ51zmoG8IMAgJkp/YplnQ4AEogvSZzULJIBZJkM3iB7rbbZ9tvV47rNTGB8fdYu/GLz+epxzQDuCxiPP7/4G7DZ1LHyfurqgvZkx+sD2PLv//1+v9fgsTbzxcnfAjMA8Pi2uTrRCr78fcSfJTe6gZ1JWHx+Bba1CthiXiiZtSMBwDFPJG6atyMIAE3RIlpXrzcgrSy9WqWomVOqz26T1e/nzpQEg0drl8ES7YXDaVItR1avx4SuXiuSE5wCABukTVecI+3JJfFN+OOWFVhQ2hhs8fLxnqZ4FBSLKJ4AkLWmaxbmxcljzD4lWGXxs2nR+fquApVjrEPZNfjVbZdQAMjfbXqyALt/fmhCyOHMVUMBYFS03PC1YJ4JAAdbJlt4E/5wZKT14WPZcpMLBYC84D9YKdFsrJ9vlAt1mGEcRQHLHep8ViXUKID54+cl6SSuvBf9zlh8as56/O/es3DFrP2ICh9HXKQLb/UUKWsd1uKUZtWWZRu/x2VGnr1PtQq1Poog8LyUavylZiGi1gtj5ztrUJlDD41GwzVmQEtvnPJFuzpL2kd/rV+Ij92WGJ0AACAASURBVOSL99yf6xdhdmIXdqwuRfzibgUAeUNmceCFN6TqwcnhgK5BuVFHbLfAt0CmQEddBiSnCDCZCgCn80DUjPR1RXuUpYwGgPx9a+wIht9Owm23ynH4271nwu+JBMEfSwPAtRsDFiBJIyD4Y00HALu+Jh2c4Wphm267aK3SjrL0EFRDf7waDNK1vlZ+boj2wdMvTCGNhs2Rk5nar3WWKv3WGfZW9Xq8uT/9tnhfFsxug8M9GTG3JKUZrx2QNvpFZRV4uzUPWXEDaFyXgxWXiNb8d1kbkPfiJ9XXfzz/t7jzSUkH+dRVsrDY0p+vACArIdGpDJdDo9k0AHwtkEwxEnjf6VnCRHb3y37LSuxHntURBIA58f3KQkVFP6ZMdrtCOwR6SCfeKq3qwa1JCBOLUIwUyLUlFADy+7/tkclxRrnpAQh+X9GXorSs1P5SB6f3QYLRhexoea+vdpQq1pQ1NBYTnOrl9t7VmInw1hiMxfuQnCFdii3zn8bFBy9HkyMe89LaMeKPVFpa6lQTYl3qvEkxy/WUVWDpxZtNRcFF3uyULpwVX6Omrp+vF80l2T2C7u07C3HmYumAbGnJwagjBpctlkX3ur8uxLzrReLRMiwLaLao2wZtKm2EpfWff22V7RHKwoZ2LTSzOudh2e8j84WxTI4fUgCQpc3JOeTD4STWDAAM7tYT9cVlSs0BiOfWZF3Eyx4dh07UH/pXfJ0ZAHh8ezUIACOio1H1jXsw6/sPKwDI0hfSTyavxTcbrlKPNfdK+85gEBAz5ovAqEtYD6NZLs6VKyaNewvXyArT745Sui091TY3SSYRtQ8dvz7QLyCIdgjrqwuRljKgAOD4gLSpVi6UIRBWOCbQ6zUFp3b7vCakxQxiY7sMHtxZJJYn/2ifp26czkDsGBNFaGKsAaDbZ0CBWQDnVADo94UHxf06/WFXn2iRhv4R0O1c0ndIq3Y6AKjbYj1DonGqvFatSoNFNuuR2bLNrnv5P4EYudvVX/Q7zFonLOsFBfLZ33hdfEFVcsLPHoLfJM8tzO9UU4Ba30Xz7QMvzUL0Cmmxs/yvSksw7qo2JASSKDh409MSh0i7F4yhU689lAT3mAE3Ze3AK91lClx8JFd0ZY9UroLR4MOwy4h5mQKoaUa8IKkFr9eWIC1hEJaAmP6sRLGjmQoAfzPnT/hsxS3qZ4aA+Xe2pR872zORZBWQ1z1gQXrcILqGLDgjrQ17npfsXnexHGMLi2RKOtTDkfq57Fi5qWsLHN7oztj2/3BZjhzTtkgBFWxJ6ynqSpccd5xc3tycizFquAItXD5uSXDB1SALhrCUEUQE3nOoWF79kO3Xp78Df7MJETnCoNNihBPT1NmdmdmAzR0CqooCqTZJRgEKbzXJDXbUGwnTthi4l3hwYZEAAdZr6+bjvFV7sdjSgF/VSEoPNbG5CX3oDYC/yzIrMOSLRueITYES/kdrEr9xAh9ZtQEVzjQFQp4tfE39/uXVlyrN5v8V/hXnvHQvotsj8cmbBQC+2FGOT2RtwP/UygJjYChWgTn1Xs9/MPi+tH2PXsxoaUe3RwCp7gbwd7jQYdkNHmxbX4L4OZPJPldkioaNsgQNAM/JrwX1b/69su15faLx8tzMduxtTYfWWVqsAl7KkmRhuLtDFoosRhJqAMjvqVfc2ZWJ/LgAUA0MXxkifGg8IOd0zuwOZJgHla5RazHnxHUEJ2wTDK7gfrTHetA9aFELCUOkTx377UNWjOyU6+SiiyvAawyvpZzU71mdgfzL6pXmd+muG4Jt/v4OKxqukJQP3VlhdjCLU+is8i8+HASAwVjL3qLgNZDxdjdmSHuZUZB6cUQNLIudGha3b/VZfwxuI35R9JZcp1lXlcgiQZ9DHD7hwo51MgFg5i++ddxTwK2fPeUZQG7sL02TBcx0EAqLJYJppqbdAjMA8PgODAUAz3rhM4g0GVVroORbojE7+N/3KMuJCIMfjy37vXpsVa5oZHSxzdjQK6DCOyCJAlOTFXiT/eXG8+RnnxR9EG8EheZevNogmhoybVqTQ90eW5pnJ9eiLKYVT3QuU+we9WCpgaEN/k5a9BBeay6GuzJOWc/QcJXTk85RI+7MFksleu3x88y/uBKVDkmhCP+nXJjHLhVNVEmirPy1xk8nNXi9Amr1dKcGgJz80xWaAqIf0+ycXj3z8aMBgLx5sHz+CAx5ZFvuX/YEVu27FqkB8TbBjrbpIQDURXaW3omcUF2VXIfVHcUqaJ4A0NIso9ybHngkGJ81GjDAjTGMoafXotp8HV32YLvPYhxBcowAsQ17Z8GSMozPFr+Fx5qWq1YgY9WMUT4F/ll8HRpWV/SkqBis+sEEOLalIH6RzjUNQ1Hc5FDF4zlrMeuPn8bvbpJBn9GJCDCTlwCQpdunBICs+QmtiA0fVakffx2OwwNVF+GuQtnHoQkUeoAiFBRqAMjn3lIgLCSLADDUwy/UToRJIPUXyTHPmrdVwKo52ovuPmE9md07XR0JAPL5WmvHxBlvwFtTR3HpY+y5vWdgfqG076h/5WDTKwdnIy7OpSbY6VVZntSJzRtKRbfblYhbSmVAISVqEM91zkPnkFWlXfCYoFE099GYP+IQU3INyMjIkd3jucPXZxEoEgCyeB7pxAt9Pkz74QFoAMifT+fXp7e5JdKL1Rvk3kZQ/fFyYbsJAHV7vziuW02Ha2kD3yffR35Kb5DxjHg6Ht5r5VzW21Hbm/AxHQGYbHGi22kJAkD+jANhC14SUDQ0HK0WQC/unIdL5wsAWveMLLbIPHNinvXiWT8LLmJ5Ht1SJNv9a4kHkffSJ3FOeZUCjts3inHz7CUN4CLLM2KALeBxeEf+Jvy2Tia8OU0/7pGBkeh4D6wxI5iXJAurtQ2SQ62BG78ODhn1G7FqUaWyo5kd2w7neDSebT0DV2TsCw5cHQkAMuaONSer9RArK17zr50rDGAoANSf/WQOgXA48XhbwK3/ccoDQJ5wXN2KM/9kcfKH4tBJan/KE2a+RcCf49TYEkQWk0rsU+M9vdu7OCwA9GT4VFvxcABw1ncfRt6qpncAwMh+uZjV3SdDJKEAkDYx2WUdiIkaOywAHPJEgxfrEwEAf/i7m+GPwVEBwCuSpF35owNk3oFQAMh26GybsAt7+9PVipyga9grQK0gTli25XHSbmYdCQDypsEbnWYLo6N8ij1gHS0A/PJ1z+Dhg+djZUY99venfegBIAeBhn2yP44GAG7uy0dspLCJWxtzlU0Iq6o/Gd3d1ncFgAn2YfT2mxEZJQysZgPfDQCajKNq+CUUAJLJuzjvYDCbOBQAslVpCPe9rwCwqi0F2cl9Rw0A9WJtw1yJByTwYTV94ouHAEAO+1yTvRePviQLQA6WvZ8AkMke8WZ3UK/Iv3kkAOjdHo/YJQHz5aMEgOwmVPfJANrJAoApcUPKLomL0xG3MHHjRwEAtZ8jrZtYNxULO/jkwQUq55gVCgDDIiYwPhZxCADkwojOASxDhB9jrlG8eLGaLH/fNYAfEgDIGws9sSSXcLIuAPAEu/JTHp/5NmQLnAoMIBEDr4BXkgw5zfaOAoALnr4XO66XNgNTN3YflDZVSZHolELNiPXE7abXRLvy9ZvFof6JVbJarr5PVq2fvGw1fvPG+ch8Yxyx97ShZo9MchIA5liktbE54MvFtt/n8t7A1/dcjYiIcdUy+2r+i3igiSw4FHNhjPSh0ym6ovE1wuKV31SJ7S3ZWJIt7cDGoXil5en2WND4krSCz75pBzZ25CHDMojv5EpCyHVrP4OCzG4kRrsVa3Vfqei/WN/eITml1MLoMgdammyXsTJNg2hwxgctbBbky7SgBoC/2nU2EuKEQdOTrjrWioMHrFAAONxggyVfWAwa0d6bLS26pxxL0OaW9hfZD6ZLvNwxG5/Ilva2BoD8en1rAVZmNGBXTwZ6uuV3lhfXISfQEt3Sm6PSDf69QCYkf7BHtq3FNKKYvKSfyqGb88Mq1SLT7UVaybA9lmvpU5YjvBn0jcSq7RwVMJt9JFNMkb/eXY5/NMxVvoIsskh1vYkYGTZgTp4cS21OGxwdVsSlOpVeikMl1LNt7slR4Nc9GhW0lylJ6FETw3zOjbnCStDyhEVtUyiDxeOSPoMsZkmzKGznAMKOziwMtQtz13j3faDFxbyiZhRZhNV5tnIePjFnI2rdSTjgSEN3YzwScuQYZTl6LYg0CkAnoLCbhSWbDgBSkL+upQBM+bAZRcNHLWtbXRKScmR9yGNCSyE8XrmhEwBu6xHdretVueYvvVUWJXrC+tkNi3Hf+S8iPaofu9y5qqXLqu1LQPIPRTsY/+MW9I7Ewm4cgbZA8QTyfuPiXejrlnNoeUldkBUfGpJ9/6Mlz+CR5rMx29aFF/bNxdeWixUL4xZ1wkZOiiNoOTQdAAxNlOBQVigAvPT8HZM5uaOx2FohgwmsGxfLecHpeeYO7+tOw2CPGTcv3IbNvWKDcn/eq/hjpzBntD6hjc7KWXXYUCnXHKPVqwAgZSPB6opG0QJhU6v3ZSkbHx6Xt2dtwg/+fCPSzhKtJ/35/tksCUaDbQHLqgQPytI6VQeCUoX0QC43/zbPJZZr1KD0fjTkJuA6cCAbBSXtiqVlZVoHUdmWiji7C319ZkS0G5G+oAMdfTaMOaLVcabtrVxD0SjLaceBRmlhx28wIPZGkcowkWnqxLZOYFqVWQeP36AWELu6M/HVkpfU7zzWJtuKnREeg+cFMrPXdhcGr8Fa6+0L2Cvx+SvzZTG0oT5ffZ0bcGrYP5R+cgHgz759/Azgfypj8vcTrE4ea+/tq1/zdARwLXmTwEvwgH6Gl4oAtnhvr/wh+K0PCgASId0R+I9qXAo1ucOeOs22+TsAIN+/NtJtD4CP6QAghyfYAq5qEv1U48e+pCYYqfm5MVdWmhoA+j7jCLa7dl72XZV64B0StiYzU8ACAWB02BhaxhLwhkNu8k/lS3j64l03qn+pQ2LdViZ6tG+WP4eCh36C8RQvVhTVo3fEpPR++qLHf+ljd1XhfjS4Avo3gxurK0twdnENmoft6By04qOzxHmf9ft9kt5hsXgUU8liW/r31Weqr9/sn7SCWF8lNx5+dhZvXBsqihBu9L0DAPLnFHnrgQe29jgFmZvei8ZmueFr25FXG2Yr8Mdy+QQgMGlCA0B+T0aA7c07W1Zia7sAdnrbkVli2on26PMEtDu6rVyc1IP+gNFzQ2MyTAlunJVVhx6vBdYoATZr9pVibpGAWnooLoxvwd92i6g8wuhHlMGHgsReZMRKi5agsyS+G9kxfdjalwO7YQScmrbaPArk8Yar98uBqixYU50Y2ReHqy7fjLXtBao9yRvcFwpfwxc33YB/X/iWet3eMQErHNygbumucmlJ0viaFQoA+X2ogTS/DwWA1GqxCBxpGJz08xi475P3T2sMtlkHx2KwsSYf4yPCYlOyoCdVG2/7kloctTptavs21wrYJKAMLQ6c6G1P0ED/uKyzm1HXkYQ75wpw/2rZP5V+E0leoCsa1towDCwRNjI1ZQA9+5OwZKXoMbnf2Z7lcdNWmYK6G38NmlmfnVWLroBtTuNgXFB3Sc1kZtwA6ndmwW+SBJ7l86qVlU74fjMizhhUbXr13ofiVcuXetHGgTi1+Jhl6QGNg1nZcQKCufgIBYB8bHGCgKoH5h16yeO21bXvqkNjTDk4srErF+enV+PpN5dj3uKAj2dzBgrSBIxzgp1at9JrqtX3TPZh/SjANqrtd+AaFAQWGTyPNKuYFdOPp9Yvw4IF8rq7tsj5WX/PvaCdTVdNIhILHChP7MCb+0sR0yAyj8pv34O7tn8c1qgRdTxyAWWJE62oLdajrmkdvTYszpXPTIBdbOtWkZfhXUbV5u1yWdA3FKu00SlWp1oksg72JSv5CtvYH03fjN81nxkE0J6xSDX4RsNztb2j+1REJtONBt5OgW3lpISCP+9qk8EPLbOhti/O4oYt2qMGUlh6cC24E0K+0NuJAyR6Ea4BILO/dVGjrPd3aUYn7EYPMqIH8FzdHPjdI6i7TRl1v5+gSqaAf3r8ALDlc6c8AOR2pPCWF1hZjQDUwjB+5Tre9qbblzOPyRY4mQCQd2LuELJ9XFoRnTCZm3b7k+6dp9eeCQJAx3CySqhgTQWA+ubNi61e4VPnMjAaHQSAGWn9Kp7q3QAgb44UZZ8IAPhE1SL4G03vOwD8TN5bGJsQUHA4AHjthn9XLcWpADDXJjfRbQfysbisPggAd+/Mx4R97B0AkKv6n8z92zsAIG/gHy/ZohhA1r15r+Mak+sQAOjqMiEpq/9fDgBWDqXiQHtqEAC+0VOsWGkNAM9NrAYf00J1fUM9XgBIUX7+659Q25tm5jSrngoA66/+DX7aLwzVr567FGFFwycUAI6OR6pBhA8SABLA17TLIoUMIEsDwLgoGXbRPo9TAaBuIUZH+pAePXjCASDtXHKtwqy+VwAYv6oTZXGdpw0A1JPWvYPmdwDAb84T1vahmgsQ9WdZ9PZIIExwUfFuAPDy/AplIs76QAHg/5wAAPj5Ux4AahzDqCpudK5UKUKdzPw7vTDFSX23JwsA/izQp+dYI8c1/8rOUMC1mztNRgxPv5KVViByRwNA/TH0xbwwMLFIAEibjV1fXoCUb9TjL3kiW2C+KhMR+temwl0wBu1rFh5w2c9O7EO2uR/r6opgt8kNI9k0rNomMVGBnNOaNGQWdONns7hpgRs33Y0bS3dhY09e0D5hXbm0cFl/dsbjO3svR4xxFMPDMbiieB/WtMwC2yEsDoWwDjRkKCuM1W/Pw3icMHraNLd3UyrilsoqmyxQ6CAKH+Mq2Bg9hq+Uv4zmUdH9kL3RFTo4QADI4jbSFgs318sEJYsAkHX78rfxhzdlipNJFWS2TLESCUVROgFgSZK8p76RGPDGSWDd1i+rf+MmM771aZnge6pnMYbHjNhbLe31MH8Y5pQKS0FGYlFys9IHsnqdJpQmd2MPpyc7YmEt7Md1OXvwz9ZyDLqlnaVPJt2Gb+6Ox01lO3GpdS/ueP5uFM0TVvDKlL1KxP7xfMkgPeBKR4tL3h8zXfMT2SaMxJlJ9Wh0JyhvyBSbTLvOj29VLSlbpAftI3ZcGb8LX3+YZDqUpQ5ZNhbTCr6+71o8vmMZ5hXK302JdqLJJfYqBIBkku8skfYzAaB+fKq32bKPPITuK2Qb19/yFSV6Zzv04/kyePC5ktVB7VpNfyL6Wm2ov0omMln5z9yN+DwB8mSw9fDPzoUifwgFgIkLutRATbRpFN52aQNGZwyjMLEX9X1yQyZTS0nAx0vk7/96+1nIzhBgRe3rn/YswYUlB+EYndR/UwfY7TGjZWMWbr5qHTY7cpEY7ULdQKJqPdasF8kDK7YTiLisFy6PEZaYEfT2WZCV2oeIHyWi6zMeuJ2yv7PTHYp5JYNU3ZKCCV84ohsNuOpaYSrJ7mk/SR3np2Pq2AFg/aCCLhaTAFBbKvExMrehAFAz+p9pk0zvV/aKtY7B6lUtcBYTJ8ikk83XA2aLM5ux+1lZ+LDcGePIL29Tk+osbfj+97r5qB9Nxj/aBLysSJIEGX4ODmLRAUCbaZ+ZVq8Gi7S9Sd+wdBdogP7VvBfxnfor0NSVgJjYUXgCujsNfrkgJjPeG4iFZJQe674tNyK8LRrzVtYGr1mc/t3TkY5Plm7Epv58VHalBG2uKjfnIeWMLjhHpBuyJK0ZMeFjSDAM44+rz0bcATkjnReLnIQ601CjewLfjQcKkZg+iMXJzVhdVwzmW7OmA4B1XzjU3J/XHk5SX1m6D8/tk23G4acvdgliZDueEYlMoWE9uW0Jxj0jaH3/26pyX/rwAMDgsT3zxbFtgZMFACkA4kg2resnDZ4ktuVfCgDy5piU6IRj0ITYGAFn7wYAaVWSEuc8rQHgj4qfwZeqSfACvBnYYkeUxutwAJD5vbSzYNFs9kQAQHp5cQjmwwoAwy91BCPh9uzPxW0rNxwzAEyPHUREIKJOm9u+GwA0hXvxukP0XycDALqbLTBmuE55AHihdT8ebBbPyakAcO3BIpxdUoMSs2jUKpzp6jwIBYDMv12a1aR0o1zIvF8AkOdMpn0Ad2eunRYAvtVRpIDf6Q4AR/ujkZYzaet0rACwZLEMmnKSOf/hnyA8w31EANjkilc5xx8YAHz4O8etAWy5RwUZvJ/t6mNDLIc+m6wCWwzUAFJLRcsGuuJzBfYYydvjefEPw++eLADIKR3SFNxRL/KeH+jbEwGc9gDw+b0FMFkicF5ulWJHNADkATTeEw1DurB2l+UL0bnDIYwTM1JZa+qLELVf2IrZl9Qo9ie0WgbtarCDNTeuXf1+hmkQnf9dgK5PC4gi4NKi8pK3b8PCzBZlLFzVmYyy9E7l8dfmFpaJ7TCKsDt6bMhO6VOZmc0tiYiMHUNYmEy7Pd8o7IJ/PAxRa2y48M7N2OHIVL9HDReLJqqsL2VPem3etfOjwffDL7o7bcjO6kWeRdpMG96U4ZfSFfWwGkTkn2gYxsCYMAisJKN81oSoybXC1v485QM2294VHOyobBX9JD0S07MnL+yesSj0d1pw3cKdKjFFR9WRtfKuFxaJi/LIpf3K5qM8uRO7O8TDbFlmk0pE6e6wo7xQJCW84P+66mz19UP7OVwG5beXHDuMPc0ZiDT4MVEjHoVLzq3Ahh3FgNkPg2kUB1c+jpV7r8OSpCassNSiyNCF++tuAJMPZgUMu4stXcpDkVnBmZZBpSkjU7S9OQsT7TEwFQwiPKAxmhXfi6GAJyMNcwdq4zBvYT3q+hKUWW9frxlwTx4/enCCsXQ06WYNjMQo70VOoo9mT5qOn1sqLBL90Fic1qYmcmQsSukMWXExbtXO/I8z3sJz7XPVYx/N2oLvvM0ZLiAy1gefKxJGmzCGLDIvvGGyLEX9GD4Yhy9e+Rye7liAV0teVMMvujb05Ad98qiJ5Xtu6kxQ1jZn5LWCrX9dqcU98P85GQNFYRiNl2nimDQXjGusyLixAYOjwtSR+abxsHp/4eOo7kjGmXn1eGt/MS6eewCb2nOVCTFrZWoDhv3CjNEbk0A6Is6rvPMcP8qF404XXP0B0+9Zjcgz9aJtxI4Ne2YhNTCkwkzulsYk/Pb83+MLP79LvVbSlcLCsurbkzDhD1MAcO2eEqyaKx6VWwJDXdShcRqatTy7Ee1uGcqgCXPzkF15eLL0eai9HvnY/u40/OGMR3HD25/CuCsKMYmixaOukVVk7cGraxZgPE32T6xZ/iUAZJGBpvcii8cTB5xCp+x7h8wY6YlFUXGb8s1ktXTGKyuWFeU12Fybh/wMue9y6pVFJnLEZYBtuzB1ExfI4EZpSldwkIga44aBeHX8XlJ2QHlishJsLpW+wc/oHorBvPwW5c9IzR51tNzHnTuFpTfN7gOHgjiQwYUna3Q0EmdktSm/xj2VOVg5V7SRG7eVAPZRlOe0I8vUj/VPLIRv5ZDy6KR2efhV0U4uvWUP3nxrLi47bwfqh+XaoQFgSplcv5mYNDQix5pjwIwLimR/9o/GovMBOV5H7u6HPcYDn8uLt65Q9k3vJ6gSBvAnJwAA3nvKAsDFAfNnHuCUkxH4Ec9Qa8HWEW8oXH1NelepPTFToVvgZAFA/Tcp9iEQpGsmdxDvNDcDkLyi06/Uifb5DVfh4RWSo6nzdhv/7X7QD41liB3D5YWTeZV/37EANy/aFgQ9O3oyMeiMUfo/XqxYtOJgC29nf5YaANi5uQiXnbMDL+yRVkNC6qDSAiY+IcCp7Qo/rHsNcGVM4IrztmH/QJry7frybDGmfbWvHDoxgTfTJQVNKqGCE6ntzQkIM8jF+rOL30T3qFUZ4rI6PDbkmhzY2pODsviAlUuvgCX63fUE2jj0EKNIem9XOlzdJjWowFqW1oT1LXIRjDGOYWifXETnnFmrXpelY9xcfqOaWOVwScuODMxZIe1oWnk4vCZU9ybhmjzxGPve3L8HPb0IALNyA+knQ2ZEG8cUAGT9x4o31L+/eu1i2Iv6MLY6Af5JrAnbWV3KJ3CRvQl/ql6s3kvUJguM54nJLhMcWPRPu7ioEi9vmI+LV+xGxUAqBj3RWJnegIr+VHQ7zZifJvuObUW+jstrwMQE4B6IQW5Wj5p4dBxMREJJL+Jj3cFUBU6bEoiyKCaPNvgQaxhVbCaBP/0btzTJoAoNaFfsuR5j4+G4I28T/q92pZq6DLeOYmleI6r6ktXgiC4Cnjm2duzqF49AgkbW1JxkGpiPF7rUYiHfLJ+dPmYEgKyB4VjkJ8vjX8v5J+546jNYflYFmobjUGCVx1sDbeyagxlAhIAUFs+FIwFAPocyiNCkDD7GcyncPIbLiw/gp+kyaHRplbRM+TmSTMOoakhTg1BsxXpGo3BGShsOOFIRETaOZSky3f7yGwsxLvMKuPysHRgYi8H6ilkIH4zE/CW1Kq2C6SUso92rklKYJEMvyF1tGYrJ5yACi0bhNFFmxeyIReLFbWoBxdKpKzR15mdJMw2h1CznzNoeGagg8Ke5svrMmFALLtPDNjRcEwFDsizmphtEoHTk7Y58DLpjUJzcrcAVJ8JZemhmONAKDQJAbyQumbsPr1bORmGmgBUCwF+kb0X+8/+mvl81T8AK2Ue25n1r4+EOpFrwcS5uylI7sWt/HuyZg1iR1oDXakuUdo6JHgVviPwg+VUjBq+RhRtNnQna+tyxMAaA9RmJbVhdLTKDvLRetPTFwddqwkSCV723mqZUmOwexJncoOG7NsDOS3SohREZ0G6XGX0Os5IfOF3RWJbdiN1dGbg4RxYuq1tnqeexegdlQe0biUJS0qDabvx7tTeLfcstDeehw21RVlQEfHqIY1lio2rV0sEhyySguLJfwOCGC9nEmixKKHz1ZvgTfDBYJhc8YyORSExwoqfXqlJgvQpsswAAIABJREFUNGDn9PrJ9AH8FweA1H9wzP9TAeYvdNfwhOSO5gpVcg5natotcLIBoH4T/LtE56RvGZHBOwhNsf7zNNlPFKzxP961iwkAn91/JqITPRhxCDsQ0xwJT5FcFN4LANxRnYPbFm4+bQAgDVizzAMnDQDS1Dg0JeX9AoDUWrLIGv0rAcCR7fGIXtSn7H1YNW/nvW8A8L5VL+MnL4s90HQMIB9/ZDADf2uVeMM1AU1Y/gv/dloCQO+wAbkZvccNAKkfY/15wwpcu3z7DAD8gAGgvjdpWyuypccCADkdTQ1gy6e/yZd6/xnAh04AA/iFU5YB5GqJYktB/+8sUsj0vjrdrOVOKgT6oABg6IckC8i8Li4lT7fYlkPEtgSA3jYTFi2sxf6Xxcm+8jv3gHYD2icq7XlpL2188gvqXy0C//WWcxDVGQVTOzCwUBiCC8orUTeUgIFnMnHmndsRGe7HKw2lqk1B7zG7zY1LM6WtvL0/W/n8udzSZkm0uXBZxgG80FKuWLWBdmtQ/5JtGQCjpkrtXXijcZZqH5M1oqHtx+ZswZ8rFwdZhVF3FIxNRsw6px7mKC/aXDbVzt3Xm6YYSK52M1ImPd/IkFR1J2N8PAzzM9oQZ3DhtepS5KX2oqknHpkJsqrW7WO2U3Tp6elHFz8q9iEBEumC2QeVxcNjb5yjnlr/uXvVoMgdzatUu7YwrlfFReniAMThKvc3P8Z3zqXjEPCn9mXBp3UNW+AJpJdQyE4fOLbbNABknFuaeUgNIjhbrEgr6kFHZxyWFjUgwTis4t+0z2FDazIio8fUZ23en475i2sx4I1GXXMKFhc1qhbWvoPZiAy0SRkRVmTtRdeIBQc2FuDmS9bj4HCqsuG4YNUelUV7fYF42lFP9EqL2PyQ7WAWcENfvPIAvKZwL8YRjgOD0hqnlIC5wukJgyrNguX4exZu/NQbePzp8w8BgPxZWuwQVleUIClJPBy1ByO/pj8f65GFj6tBG0+TBZEZbiXIH/DKNZYMJ4uxXBEuEb7fe7EM/Ty49jJcvWQH3v5fsee58j/fwvPNczAwGIv7Fkz6SP65eQnWz3lWPWfBjptRFNeLbbU5KM3tQP1amRau+rqk7MRaPRitsuH+a/6BX1afDWejTWkDedgwW9eWLODd7TGAsWjbOrOQaHLBGfCgY5udTFXT9kxceaFYI73WVILZSV2qzc796aKPY6QPzXXJsGcMYcBhxkWz5Zzb15cGyg3IIHW0xyH3yTDM+s4BvFZRqppRzKz2dQb8IWeL1o+M+fKMRnVeayN0MlxMusj8tdCUa14XW6RQAKgeMPsQETUOtEerqDx7IBlDD2bo3NpV10rUXO6XDqJ7xBycQOYAD03Z2wdt+GiRfF49fcyv837+ECj//Nh5MkD5x31LkZY4iAF3jGLIyMqxVa6Z17L8tmBEJD+Le8SAZJsTF6RU4dE3z4a5MRzmi7vUtolPdsK9Tdj/xZccUG1tng+5mT3gsBTbpsywbmhIQUK6dDdYfL0Ohw1G4xjcHWacu+gA1uwtxeyiNlS1piAn1YHBgC0T29V8f2QHyYpyGItpLizaxbR2xOPqcjmPntsvt5qb5u7AsN+ozt9lCQGNX0tZ0H6Jz+H1k+fPiE/2jwaA2t6Lgz4P5ksT69pNn8KY0wCDVa7hOoWEcXAcqDupAPDBEwAA7ztlASAnlOiZdGgmn9rqqogpvs3TYPKhma+mboFTAQCeznvlXQFg+aXV2N2W8Q4A6CgLh2EIuPUTcvP7MANARtfVN6TgvLmS3XpZ/F7cv/HG9wwAtUExp/CoI2PiAG8G7t3xGE3yzQDAYwCAWtJwyQJpvTt90djdmfGBAsBlF+/H2oOz/mUBYM9cAT9XfZxWZsIACvJ4dwDISd6H7/uIevpUABjeEoO8Jc2HAMCNjgLUvh7QqSWNzwBAavyOEgC2DtjhGoxGcU7nYQFgWrww7JYo7wwAPLF3enbgmL5AI2jqfKgBZLFfTw0gxbdkWX51Yv/sv9arnSwAyCUznYB11Bt3Cg2GdJo5hZtcfoWos06LDa0AYP4fv4JvLHsTT7QLu8GVIVkSMgks5uQW/ERE8Ky6e+9F8bcfVgCw5LpqZfrLnNL+mniV9PGFPEmy+K+91ynrETIRLY8XKFf77gGLYhcuza/Ac9sW4HOrBEA+3Tof12buxp/qlyj926eWv4UnahfDVWcDxcrRkWPKNoaVZ+9D02AcfP5wJJhcSmNIITQNVJmv2tdiR0yy6MhSbUNo2puBzDkdSmfFfFGmmJgXONQqm/q5jmERqet2Yo/bHNTUaN3M+W+KhQLzklk6sL72pq+p7GICQNaD54g1yO/bxDiaJros2lDMixMDXlpdsBbe9TBu+PzryjA7ZZYcSmel1ioWTL3WNAAwsmxQ6a50kdlIsTiVZo/6rDuKN+PVrlLF/FDDV54szM2m6gJkZ/QqwXtSghNeXwRuK9iKX2w7V+0Pi80TFNIr/d+YAe3ddtSe95gKpx/3hysLH07Y0jaGonydzVzdl6QSDyiC9/vD1cQl9VyL0ltUmgC6o4Ek0aCZLSNIsw6p16dGkNFoPQNmWM0jGByKRXayA83dwrRcX7pLsRuvVM1GcrxTaamYCFNo61UMDHVYqXZh+xzDopkig5IT8F4kk6oBYFiMT5mFszavFwbSnzKqrFBYmn2iIfRLO+bBljaZBEN7Hp0v6/NFwO8LR1QgGSRsrwWfuEmOd9ZvXrgIEzkehDfG4O6rX8HjdUvUwMCq7HplmF2eIJq6FOMQ/rZnIQzNRhSd1YCa7iSMDhsQbvQjrD0attI+3JonukEaYv9181KYayIRe36PYnLpixi1z4Sbb34Lf61eiJEO+fz/ds6bYmYeNoHspD41NNKwJRvWOQ6MjEbis6Vr8fBesSeKfyEWIzf1BzOdqfW89oxd2NQlljKd3TaYrLLfqItlhZtkOGHcG4nkNGHDmTlLE26e27Qp0jW20qk6CjmzO1Bil2sJGVjaS/G81YwrB5ZYjJIjALx3nWQvI3JcLaLChqLAGEkWc79Zu3oz4RgyoTilOwgAL7p2qxow0ybHfJ5vPAJNQ3HoPpikrI8Ges2IqTNgrNyl7Jc4KMJyNMcpjSCZMh7Luw7kwloZibDz+5TelZYvF2SL3vDZvfNx35JX8bO/X6mGd9Lye9U54eqLRUr6gPr6kjxZDPL90OaFDDf1tDRdX/f3BaB94lDBOKx5A8EkEKaY8Lx5cM5TuHvdxzHhC1OJOWWJndj8dilyF7QGc5Hjje5gRJuOqVzXUSB/89LvIe8XDyG9WHST9Dhc1yw/O3id8sWTx5/7pgKA4dzOgeL5OSe5AzERY1hdUaquGayujemYe361SgJ5TnKy3/8W8I+/e/xTwPerrOf3870Gt917+ILzAwx1p3ZEWg4AWx08yHmj+dt7eM0P1a+cLADIM4R9KTmjAN4dzmA3L/A97/6808pV6vSpaQFgVWOaEjQfDgAuWl6N3a8XfygA4LDXgMEmOwpmy4AEQQdr3C+Hnn8sArlpvYcFgJxYJSg1G71BAPjC/rlIS+3H6NMpRwSAz728DNZ5vYcwgDMA8P0DgL+tXoWdwzkzAPAYAaBzQxISzpbF3bsBQC7SCHKmA4AEvw8t+9sMADxOAEhpRXtV8rQAkAtiph+x2FU4lQFg9gPHDwCbv3hKA0CNFNibF6NZIZVklTVT77oFPigAyBFRijBCASDpHY3i3/WNnyJPUABw5XOfxdzMfuztS0drm7AvNIXWhrecuKS+hhU+FgYNAM2Le+HotKEgV1gNbavQ2i42HNfO3Y0XX1yKqPJBYKMNEWf2Y3RnHEaLPLDb3Xi0/A+4Ycvd6rmWNSbEXt+BDNMQtjVk47qyPXi7M18Fu/urLZi1oiE4NcgL3MZ5z4B2McxldXqMasVN/RPtIGjbQO0Ni6kQ/okwbGmTrFlzjBcDA7GYl9OmtGys61Mluu7n1aLRI8NGJkt93vBxBQCje+T78Tmiy2KNdsYizB6YiIwcx4IssV1hNBdLswsEgJyKvTVrG55pn4+6lhQFAFk0saVeUDMt+rU/XbwOP/3HlZh9Zp1a9XOohlmnvkYzvnmlLAx/+HsuIIGIFf2YeCsOt975Ov5St0jZXtxf9Cp+UHUpvGPyGWknwVB5DrowVYTbhz+jRQpvxpwEbemQ/UatVNhAFGhTQvuXamcyKhvTUZrbDmoJyXDQRuaiVNEvb+rLQ113InIS+9DcF6empcnS0g6HFkHUCGr9EW/+5mgv+odjcVZ2HTa05akM480dOUpHlmgbDk5Q0iScN6sz0tpQ3Z+k/pajx4K8TJmY5msSRLMSP9KkmGDq4ipflCiziu/dg9zHfqSMyZPj5Hjg9tbsrc8dhdQAi0UjcALAnx48D852C4pLdSqTMOK5v3wIhhSxJNEgx7VQpl6j6iZ12t4kP5afIVYdyUYnXq6brfKWfz77L/hW41WoahLLD+r/suIGUNWciqTEIaXV5JQojz1mvlpjvEE7JaUj3FeAs+dXKtaH0+/UaYaFjyPW4lWaPG3EvTKhXu2PhjW58BaNKHaH8WTU3TqHo9V2IDPMGnKYYK4wIP7idqXnuy1vK17pnq3YWerWkuxyrHPb6Giw8dEIfGKhRPKt6ZqlzvmB9bIPJubLNg5lmXhsp6UMKNDH/a73wZJXvoICu7BLB3pE8+kcisGivGZER8j9b3NzLnxeuaTGbZCpfud5LpydV6u+3tiaq45rVuQBE3wB3+zaL5JUgTKnH1iTimtuWY+/181TxxWPe5qi71/2BPJe/CQwIbeQucXN2NeQgSgeK3YnRn0R+GT+BjzeslQxivqc4XPpJ3hpTgVebCyDq9WChPw+MPGnrj9BHX+0nhoalG4F2XYyf70OCyY8kZhTwr+TiQijD6nxQ0qPV1UhE+6p+Q5l6k0T956aBMQX9qkJXO4vsoM2w4jKJWalW4dU3jCPG5pSM/Lx5mxhR9lNYemElPpBuabTZuu8A1cFAaDeTzm/fwCJadLqZfXVxmP2vCZU7hT5Wf3npftB/eXJtIH5AAEg27P3B0gfii7/g0R3cAO98wtS2LRb4NQTL/504/88AAllnqn3bQvMAMDj27SHBYD0+YpLCaQ3JLfirc3idTYDAE8sAOxoSARifTMA8CQBQILxoWEBE6EAsLsyCV+57NlpAWDjuhx448dnACAXQEcBAEdHImHeJqB4aIH3HQCQ4J9WKzMA8IMFgP4qC0xz+9DfZTkiAPRbfIiJG0FWfP/JBYA/OgEM4H8dMwPIVTUHM2jPwqgjAjmG0dMDSHcAQ++6XE1xRcSffZ+OZkxMDGT4ysTO9EXZWOjrsaPIlQv9lthN5CSghKLP1GG3wMkCgOzLc5mqnbmJjOjRI1lDItw8bRnAnB99F7bZIxh0mGE+YICzRFbgy0rrsWVfAc6dX6EYNHXT9EXAuNkMZ7EP80rFpywpehjrX56HsHGg9IJaVKwRzzBqRrZV5SEj06HaQ1azR62U93emqhUtmaSRQMyS1eZBmmUIzS/nYmzhMPy+CCTHD2GWvQdv7StWFyAyRqzXq0pgsXrUdCT9vKgNs8WMwBjhU/5qcxI7UNUv2aVMNKHWb3F2s2Ia+DsT4+HwuSNxxqxm7KnIQbhlknFn9mX1xjz4sz0Y9wn7YIsfRqrFGQxc58o591cPIqYjAjnPiyw04TedyriaRWaxsScBn5sjUXmcILWmD8HliobBOKaYCEZ0XZ51AI9tWCVHULRMuWp25U9Vi5V5cILVheUpcpjt7stAQ6swYY0f+5LSpZFto7Yrwz6IziErhnpNSNgWheELhtU2JqOg31NtWzIKM7qVfx81lJw6dHaZsbCsASnRQ9jQLtovMjH828y/7auLR35ZG1r77epvcWK0u9+iWD1O6LLirS4YIv3KmDs6dhQR4RP4RNEmPNm8EJ1ddmV+Ozou25Is3Y7abDWp29NlQ162XAPpC5dj6lcTw3zfaltkb8TjrUuRHONCVV9SMCWkZciOe2a9gR/su0TdlFgDHgEcnPy9b48wo9RQUntJxkdtYoNMVBIAUv/F/UD95ML4FvxtzQqYCwYUG9pQlxrUAF6YVY0Xnl+GsDInPAPRCIscV6J5FsEkJ0AtFmECqR1rHpBtkm3vV9PF1Gg21ycDnH4l2zQiTPIlS/ZgW3c2HN1WJCQPoX/AhLDwCfHzCwOunLMXq5tkEn9uagcqelJgi/UgJnIMHsaQDZkVS52Z0I+GtiTEWkSrxxofD4fXEwVjzFhw0pbnQElcF96sLEF4lBxr42PhiE8cVlFwNGjnhD4ZrASLCw6nCSOtoudjZCEzwHf9tRxjq0QbOTYWgYnWWOQvEIPo+s4kLMltxJZ6YY00ANz78D3I+d0DuHBehWIpaYDMoga4IjDtXbc5BzGlAzLo5DEgI34ADTVpOHfBAbxVPQt15z+qvCPVe54IQ4/DorSkbrcRfmcUYByHyeaBe1iGTxo+8mX174KXvqamtGmqfFHuQbzaINpPnnvcd2SctQfhXWVv4y+Ni5Sf5bDLqBYHCSlDaprXGOXD8HA0rFbZz3QcaN6cBcPsQdA0e3RrPFLPaVXHEw2feY3kecvq6rXCECPMtGcgBnk5XaCpOdl2nl/UMbv3yTaJLJFtS9NpDBgQnuhFRJQflxccwMvPLsVI/ijsiXI+a5/QtMx+5anJ85Ka2kuyK5Upu453rLjmmyj+zsPqd6yL5PbFc2TeP7+u/i4BIIuuDKoCzgVpScIIdlSkwG8WAEh/Ur/bi/03/Zg/ej91dYqYyP5gACBBH8W3kkkpsi4e5D8PJIEFHg7+Q6BItpC2LcfSuuVJyHYAL4CckiLYYwIImUaCwXMDwyAzmcBTt3jI9ycLAFIDuJ/4J/C3Cf7Y/9IxBOxDMEvqtGwBzwDAGQA4AwBnAOAMAJwBgKcSAOR9KTxaFtXvpcZHRtB0bAwg2TyuPm8AMBk8D/wBANu8V0/zPtjmJYrm7/HnRNlPBKJjZaU1fYXOFXCKjCDzzpCn/g/zBgIg8L18/A/F75wsAEi/nqOpbx3Nk06h56iV1gwAPDYASHZlYjBqhgE8xRnApzctRnZR1wwDGEjbeK8MIL0Jl2Y2vScGMOqiXvS2204qA0gQ0/DRL88wgKSkDtoQHri8aQawtzZBTR+f6gzgCQSAFFlO5nICFKNORp9M3pAZkcMWLhm5TSH36QcAMEtz6TT3bhJBpL1p7UB3EAqQfwmA9g/08TsaAMjuIfWDTAfRRUKJrKC0fGZq2i1wsgDgv+rmlyngx74Kc4JsyrFN8XCXeGE0jWKkLwaRgxEqd3Y8IUB2+sMQbvBj3GlQovSdnZnKrLS3za7izNq64mC1SQuPQmVrlBexkV50eqyo3J+FSFc4zLP7VftqQeqk0J4xb7SSYUvkF+V/wR1bb0dE5Di8Q0bYEodhNo6irU1aJVGmMYwOGZRFAosalohon2rBsGUSxf8CEU5s8bDVw0zSdTWFyniVecD8OwXxDmWW7GgVGwrabCy7aQ/eqCpGfnoPOgatqkWdGC9tF9pd5P35B+rriVEhexvv+KKKzQqmP7x6J1JTxR6D4nlW7qMPICzKj7m5bSLw3p+E/IUtcI8ZVGucrb8Yo2zfZPOwGrTo67Xgp2f+BV/eew3KkrtgiPApSwvGP7FoW8J4svQ5nejotcNmdaucWwrD2crn9uBQSu+IiNHPTq7F+p4CZWbNuDTaiOQlO1TbmK03trXYnmWxzXagMR1G8yiYkFIS3436oQTMsnfj7cYC1TajMTjbcKy8uD6V/8vhl54eGyx2txrGiY7wKYsd2mDQyJbFiKuUOKd6jHYwHBq5PL8Cm3ty0NKUCGuSC/eUSPzdz2rOVbYdGA9DbJwb7jYLjGkujLabUFjeiuSY4aCJ84EqyadmbJuu3EcexJfPfQE/rTxXbcNttdKe5AAGB4KY5doYaNnS6oV148ZPY9uuQhT9h1yL7W/LcB6tkGjeXJbbpoT4g30mGExjyEmQFtrr5zyMlTfKoFTi5xqwZ18u5s9tUJ9/YGMyRnLHYEtyBqPFVqbW47l1ixGd7YQhyg+nU1pw474wdZxYo0bUucXKjutHXU8i/r1sLX5XswKxBrb7jCpbNiFpSNmIsBXJohSCgz1sk2al9qHdYVOm6n3Dsapd3v1CFjzLpD0Zb3Wr+DnnYAxy03vVsMOm5lzYAgbN7lFDcBhqfnorhseMqlVfYu7EP5vLMFwl7e66L9yrbEcmIieQWTgpa2K7us8Tq2IiC78/iqb/lnPGd9CKsUwvIgNWOjT6pj2Rev92tzKDn5Uir8Ptx3MhIhD16B8wIDrZrTSEcxPbVcxZZ59MtTIfeV21yE8IAGlgP+o0qOtVavIg2lviEWYYx4Q3AnFpQxgdi1DbnjU4EIsJXzgijH5EGXzKViezuEttN5cjFsnK3kX2EY+bVqdNtYs5WEOTZw70MDquryIRE2kjKi6OlR47pMysD9ZkwBow9lY2SwMxSk6QkjgUHMphS5tygnlJ7djUkqtM6ln6mnZBTjXoIMCyJwyrtm9XRTJM+YNwdliQV9SBUX+kat+zODzHopOAa0sirMukBcwBkzMW1Ktc6llzW1BVnYH4DGn5+l+RgZHMGxrwwqxXUPTnT8FcLDILt8eIcfcI6m9X8ZLvews454ffO34G8EtfVe99SpGoUXEmU+pwAJA9b2p1Jp33J3+RE1+kKamf0Ywfp2Z4IZKJr+mLDCDBInfKbs4iBpI/9LPp20Pz0sBo0xFe6UP8o1MFAPIAoGZALOxPn5oBgMcAAHnDIThkaQBYlNeBMX/EtACQ/nYsZv2eaADYXJWCcG/4DAAMpHhoAGiIH1GgrMtpwVCb9agBIM22U6xOJMW4pgWAWyvzEBY1cVgAyJv6yK8y1P7+sAHAJSsPYvP24lMKABLQtjriZgDg6QwAf3ACAOCXFQA8WgbwvbSA1wa0fxeE3PYvDUwAU5SqZWJTUQEBoA4cJ46hHcb/hTyJEbNcUYqlwUxNuwVOJgAkFUsKmDuUFAXRPv17PsNEooD+73SjaxUAXPjMPShKH8b+7jQVRr9+V4kSVrOMLVHwpor0sfGu+8FIIBazV23ze9BXmQifzYeEtCEM707AqG0cYTY55qNNo5iV1INaR6IaOKDRLTwRyJvVoYxV8+MdioliMbCepsA0d6XYWA8ikIn0DkYr8fzSM8T+gQMB3tFIJaqOiBXWikML/I+sR3NbAsIpuucKPGlAiaPJmjASi4xHT6ddsTFkytLSJmPguNpfkN6KzbV5MMaOYXmWDF9wAOayvEoMjMUgng6utK4YTEN1VzJykxwosPRiZ48wULTwcPXKoi3SItthokt0LGR7GFtHI2P1XJ8RmTHCFr7aQA0xwOg6VoxZTGoXpdFRANjVnYkvF7+Cv3Ytwa49MqzBWnxGHXwT4djTlIH05AG0dcaJjYonAlFxXmUBwkq20Eg5Upk7M/quq19YE5oaa3E7I7JYde1JGCcbYhhXjARtLLitGAPX4rSr7djWa4fZJAzgORm1yu6E4n2yqxTOcyjE2RcLU5xHmQibAsbcZAbJ+jEGTE+DFsX1KHuTysY0RDJ+zCvMx9LCRtT0JypbjZXpDdjcmYvPFa3BbxpXKWamMLEXGbGy/dY0zFIsL5kTDQAjX4rDojt3o8zcppizhakysLCnJ0NZ4NCah/YcywobsLsjQwHAxppUdVmOTJDPdnPJTlQ407DzYA6iAvuT5t+MltsYGJpJMst2I9uz47kyXHbzZjy9ZRFgGFfWPRwicFfGIX1huwyEAGC+cIU7HW1uO/btyMd4rF9ZhLQPW3Fmaj08foOyxmHx9ck2MdIrOXYYe/h8m+xXsluRUX5l88IiOzvUaYEhbkQxy77RSOSm9CpWmRF3sQluGTLg8Wn0Y25GO3ZU5SKcDLrDiAmrT7FtZ+bXBdk0PpcDCzR65zH8kaLt+O2ac5E1uxMZJmGOOOSwvS1LzlUyVMlODNbbcdbSCqw9IIsmLpY4rMPz77PL3sCj1ZJz724Wc/hrztyGh1J34vq6C3GwW7aTZ9iIObltqOqS70e7YlFc3oKWfju8jD6cCMPcrDbsqs9CuMOAsNQRZSbO4nnQ2JaotsPEWIT6jGEd0fAnjWJ5UT12tGapY5ZF9o7spuNgosp7JkM84jEgNtarrKA44NPpEkaN5vEc9GroTFRDO1nZvWjvsSPS4FfXOLLv3Cesr8x5Bb+sOwfdnTZ1feLPWCazF86BGMU6RpnlOsGBNg7JkUnnIJXl2ya03e9T1xOyhaX57WrgjVVXnY6w0TCVfMIyZLrg84UjJ6kP2eZ+bG7NVccz645szhZAPC5r2VkEYqJHleHztpZsREb64a2V68G4cQIrloi9U9VvZGimd8k4bluxAa+2lcLv8mLnDcoM//1nAE8cADyW98ohEA5i0PqFxSEQXoQ5lfvDwGOh/3Dy91YAjKPRjtqfYw4CLwnTPF8/xJZyaHHyV/yjpPgaPFHVxM1MTb8FThYAZKwDQ0F5lvCU2x7I/qVQlGc0A2EpFJUxsdOnZgDgDACcAYAzAHAGAM4AQHXXOqUA4PdPAAP4FcUAHgsA1DYwjGIjEKQNzE2BKV/G2dAihjpBGTUHuPJnUthjgUlhMnaMSiEmUL3yE1SMx3meoTwn6PX+JV7mZAFAijEp1CTa/3ggo6+Geef03TyNt+QxAcDY5kjkXSSs2AwDOMMAflgZQDI1C5NbZhjAGQZwhgF8f25+6r6U+73jB4CNXz1mAMhPRDmXNoKmPo9tLzKDLGIBxr7eHvLRSWXTa4f2LQSHvzuKKeBj3XJT08eO9ff/JZ9/sgAgewoUgRLpUwnMng+ndp47zbeqOtH+d+di/HD/dSqRoDyxA29WlCBxXRQc53mVSJnCfcNeaWt6yz2oOeceBb+dAAAgAElEQVQxFP71U5hI8mLCHakExEzX4HMptC7MF580DiQsT2vEpo5c1UKk/1hpZicOHMxChG0Un5yzAZv7JMidovnl86tR1ZesMnk7hy3obotD5FAE7KUOOF3RCA+Xfgf/H2fyqKSEgXYrIixj8I9EoCCnS+XhssWVniKtHbZECzK7UVufihVltah0pGCgx4z4ZCdSzE71HhnTpt7vsBnDzVaYs4dQmNCrWtdsP9I/jt5x4+2xyJsngytsF1UGUh0oMGdqRbfTooYm4qNlCMZunCSEtzbnYMwRjXDbqGpD1dz6CArX3I4Y06hq8TXWBdIUIicQYx9RXmWpZif2HcyGnR6CAWH8YMBr8O0LHlADKRxWOTupFk/Vzw+20DnUMdZgxoLlNdi2WzJAYfar9BFmKjd1JcDvjsQ1C3ZhdXMxvN5I1TrSMXcX5x3EiwfLVMuKn42tNG4H5XM3ZMfAUCwSbC6VJ6z2x0SY+ttsyzJpxdFrQXF2J7qGLTAZRuEZiwpuYw4o0AC4YTBBDUf4y10Y80Qh2uxV3nVL8ptQPyADAUzF6Gq3q3YiW/j0H5zoiIF9Vh/mJbVhf29aUEBP70AOkdiSh5XcgINJMVE+9BxIQuqcLpTGdWFNtfjqhUVMYHZ6J1Yl1MLpj0atKwnbmrNhNnnVYIC704zY1EnDb98BG26+ah0e37UMYYORSCx0oKc+QfleTtjHgGFpWd+wYhue2XcGbp27DU/VzEdxcjcOdqYgO7EPbf12jDaZkVAi7X9ul1aHXbXoPS0WxGY71aAMUx/YcuTxNTAsAzxp8YPoGTKrXGurwYvdVdkIj/arIRzPSJR6DUoLWN19VvjHwgFnJGDxqUGLyMhxxJnd6GhMQGlJq0ptYfF84rnEiyhb8vSOo6wisjcSplKRRig5Ab3pvFHwN5uQMa9DDZnk2fqwszUTo4NGJKQPwjUiaRUdTTJEcPvyt/F88xzxmmy3INw6qtqeo3vs8OZ6YWwwwpsl8g3qY6OifViZU6+kDuPjYWpbtDYlqqENuCOC+4N5u2y5UtYxuj0OI2l+3HfOS3iha24wZSUmMJzk6Y1FWo5DyUrYBva6DEhOGkJ3SxyMCR54hw1q0EltY9uQunaMtcdiwuZT+zk8eQQZiQNYltiI5+rmKLkEi3IVDjAdrEvH7MI2leDC/cVtz2EsDlTVd8k2pt8ktwGLx3dRRiAb3RGnEkc4DKWzve3RHjhHjfB4o+Bxiach+gwwZLjUMByH38boE0l/kLw27KvIwbyyRuypF/lJWMS4kncoGch4OFID10DPy8lwpwJnX7AH27uylDcl29jqc8cOYfW+2UrmwTInyABXZNi4+lyOqkScd+ZerN5ZhqJZ7SfVCPoDBICyMU6tmpo+dmq9uw/o3ZwsADg1C5g7g2hfnIlP35oBgDMAcAYAzgDAGQA4AwBPPQD43RPAAH7tPTGAp+IdfQYATrNXTiYAPC9g+Mi3QVUtdQGTPiby5ji2fTqVOK4/8F0Y80S/annNDMdysawYdomg++KiSrxeJ0MK4/5wlGe2K8ZuwjiuxMmZ6X2K5XHRNd8wpgTMrP66OOSWtaO5O0Elb1gTXcrpn8Jtpnww55esBivdNIQNe2ap4RPaqJB1NBp9cDuNKn4q2j6C/8/ee4BZdlV3vv+Tbk4Vu6tzpCUkkEEGCWFE8nsenAA/ksfPBnvGGJtgzDgM2GAwYONsD55xeDgAM7ZxxAkzzyRjkkhCKLekzt3VlatuPPeeNN9/7XNLjdxC1XVa6tvN2t/XX3fV3fvcfdbe5+xfr732f4WB+Z80ZReY7YBSEMz0MfQM8vAIg/sLuQDtlum7ZPOILCC04Nb7IoHCLBgs/J82A/Qpg8EyOdEyP/t57KqvYtkviaehtVTGNftP4eRaA8/daeJ0DzenJWcqvQYMvKd3gJ4YBo/vn1rEZL6Dzx43siOUpZHva+fRGO+Ih4PSHexno9TDiXu2orrT2IHeu1rBx1K7LJ/xdCllHay7KhiMxZjcvyR9Ygn6rgSe8zprCxXkqgPcuOsYPnX/ftx88H45WHH7MXMylR4WeiPo7aSHoFIzHiN6kMKVAvYcOIszKybPqOSNPVPFtz/1K/jQHddK7l3mI+afVb+I7sATaR0Gj0s/AlcOw9CDOOi74m2ZmVgTWyy3SlKPMiwsp9p18TRNV9uSRaNR74p3kdeLj1Rw6MajuH/ReE+YAYPSLTu2LZkg+weKGOzqi8dtz6Gz4kFj4aGM77vlh+FHHr7yuQOoX7WMleUyvBMFxAc6qFV88fbee8p4WS0bKNxaxDNe8mXcsTKDU4en4Uz0wfSHcmKbnj3XzGHaNDpdQsTDEYUQuUIoh0yYw5f5m8OvGpvd++afkGwZLJ/6t2vg7O7g5j0PyKnxPTOLkn2FEkCv3W+yw3xs9Wp8eW4HWvePobi3aQ5JnS2htmsNb7/m7/Ens09fn6f0rvN72aNd4ysi3dNuFsSTOTnWxvxsA9NpTmMe0KEnlrZn5pCVVklkYCgbw0MNuXwoc0rmmh1Lft6l1QoqFV+eg2q9h+ZyGQm9iHaCA3uNN//ImSn5HT3ny4sVOQXf2Grm7FDChnOROaJZhpJNr7nhY/ifR54qmSZ4sKhwJI8feck/4z3vex76TzLhTPFsCTOPn5P8u4sPTMgcX1yuIum4sPq2eOQO7jL9OL1ax3Vbz8jcnm3W0DpWl4MmXzizU/ICU9qGB7FY6BWlx3upU0ZztSSHRJ7+tLvk8NWtt+9FkovhlsyhDDcXot/Owz2bQ+WaZePRO1uX9xsPkPAAywOz5ozf//24u/Hp0/ukv7QkM6esdIpyaIunyenB7TbNM0pZGd43s4Hwc44By9RYS95/pcIA7a7x9vE9wfddrhTIuy7qu5iaWsPCQg3T002stosYr5rdBba9buYM7l6cFi8t31Fbt61IVhemLtxz83HJic5C2Zo7P7sP4ZYBamNdxJ8cQ+Vb50U26ujH9yC4qivvBhnLZhGNTxfQeU4bU/U2ztwzDce3EG4dYPtWkwru8y+kxN0FxdXJtS+gmC3gt18EAHyzAuAF2P2yq/pYAuBwt+ThjMTPL8tMIAqACoAKgAqACoAKgAqAI8tA6gE8z9A8VgBo9Bi+fqFGANPFPZaFwR/vp8pHehqZarZ/eQEdUA+gegDVA6geQPUAqgdw5DyAe38huwfw6FvUA3gBPHDZVX2sAPDhDEPo4/Fs7v188yXwAFJpnPtaPKlEQb0vAWCk+0aPiisAKgBe9gDIzCJ7asuXdAt46mmz2F8z+nO6BaxbwLoFnIklZF3a+7ZfzJwJ5OjPv+nR3q7OdKMX0JjOJQpMGzFTLWKBSwWANwP4oTRpNOVh/gbAXwP4wiUel9sAfOcFTBJ50F7/6e/GP33sWdJ155qmxKUsHR9DbrKHQScHZ9HD+OPN6cWlw5OwZ7qSpu25ew7jn758HbwVB85+E/vDuKLunMmAceiqU2jkfDnVOVnu4PDstJygK+YCTJXakuaJ8XMsPAF3bH5C4vu6q0Xs2bmAhXZFxHoX5uoo1n30fSOSHDdzQDFcH32eVGVcWRg6cgKS8W4UImZheiWWb3vcXfj48YMSh2eterAm++L1aK6U5XQyS6E4kDiinZMrErdo2bHEIfa6OVy36zTmuxWUPHNq8PADM9ixy8TjPW5yQQR8zx6eQmF7G9HdNSQHO+sn63ZMrOLosWlJc9Y6WQOq5vRjfZwxkXkRoz12ysQXPe3QA1gdFHH3PTtESJh2YGweY4IYe/SRjzwZ4biJW5I+T/RMarbQESHZxcMTcLd3sa2xhrlmVeKOWCi6PYgdrPRKUp9ZShgbNntyXFJUbauvyWcsUWJhstQRcdwosbE8V0Ox0UMxH8hpT8YcVUs+7FTInqdCGVfWbedhO4mI505WGOM3ISK9R1fH0U3jspiib6zMuD9bbMd/nzo9Aa8UiDgtT38yBlPmz8QCjjfH0OrlZew554YnYp++8yg+/XfXYfxmExvGU7LP2n0//v8vPUFSYr1g2234zY//BzhjA8xMruLUqQkRpZY5cbIKe8oXIWtJMXhsUmLNOHa8t8GJCjBtYiT5s+3GiHzXxINFTBdm7M+TxBQo5mlOllOz4yKiXK34cmqb98Nt1W/edwK3zW6T9ISdNDaMsaCMnWvUO1haqEn6vIIXYLlZljhQlkoal8UYsUErL1p9FOZmnNmAp3IHNsYn2yK8zdR8LPFaDuO7ViUWlic7GSvLmFMKFB/aO4vDJ7eIyDlLcKQC7PBhOzGeufd+fOSuq5HnSV2Kka/kEJcjOYE9tAOFg3mKnmkUeX3GoLI/t37zB/CkL75UTmpfM27G45PHzelzxsOe+NAe9LYkqBxYRe+OMQTbBxLTd9/daXzqpI9tf5LDsRdaeOKhE7jz1j0iOM3T0Uk1RG2isx7Tmyznse3QvOR35vc7x4qwD7UQPVBB7AL3f+/v4apPfb989/U7TiJObIk7PX1kyjxPu+ZxcmFcTuseHFtcP3HOWEnOL8bTDkWgo6aH6V0raHYLYkPGtrLwRG7+RA7x1TzB7kqMLE/WS3vGJyeW1Je6voc4cOAVA0zW2/CcCGdXaohCB/nCQJ6D4SLG9y7jbP3AFfvyexpTbZlLjKPttfKoNswc5uc8uc0Y6OKXSghubMk74tn778MnPnYdxp6wgOU18x5maruB78p7s3jagffUFflevrdu/co+HLzmFI4tmHhBxrtOXrUo8YFPaMzibz5+A665/ihOt+oSX8gYwE99N1PdPvoxgHvfehEA8K0jC4DkB+YPPl9OYhkLLY9sgccSAOltowYgvX0Ep78A8CoA16XyMI/c239fgyBJvaHr07yBLwRAcelzy6vP0SQi4FGhnAKVDy28BsWor72AjigAKgAqACoAKgAqACoAXsDCeRGq0utAphgmz6Yj6aZUY/AiXP4b4xKPFQBSgZupW/4ppfYPp6ng+F/pLABIl+7TmaUn9SA+FACHquQETQpRUpX8xXSOnDNxONIUTvs3AD+cnlDe6OgrACoAKgAqACoAKgCOHADu+/nsHsAjbxtZD+D5pOXIEkc2unhrvcduC3iY7u13mQTjHMNnBcBzx5D7Cw8FQEIft5WpTM5CJVLGALz7nLyE3C/7lzSRNA+EfL3CuqnCqFRjDOOpPe94J1DLA2PmqP/8GrcOI9kurY91Je9uFBkRVMoQnD0yAXtgI24Ekkt3bqmGOLBxcNccDtYW8KE7niB1a2Md2Wpg237Xk/y80cDBxGRLxIS51XX1ViMPcsfpGdmaFOmXdh7VWk/kXShAS2mRfCFY70O17IuMCkVh4cQi5kp5GorScpuMW8Kzc0YihPIL3I6JAge1ehdrixWRoWEOYX6/SMukuXp3P/E0jn91u2yBUHKhTnHcTtHImtSbsiWNzxjZD//JXYzXTKglZRqu23dK7oG5QZ9+9f0406nh5KKRm4nmiiIYvGNmGbOLDXBrKTfhS5+4XUo5iR1jRriagtWT29bEPrwWt765NbSyUhbZj6jP7SSzBRn4rmzf0Vbbak0cWxqXrWDeL0WcmeO3nQrKhmt5Eb/lFhdtN+h5ItzN7VaOT7nYF+kLFubopbQFpX0oQULZlK0TayJ1sX9iSaRluM3++Bmz3ffV49vFRtxCH0pvtPt52X7mNShxQqFolvn5Oiammii4Ro6EW9EMC8i7oUiWhJwnedOPLRNNEUbeUm3h+NI4BssFuQduy07XjYju2ooRKEdsoXRvDuH1bQzmiyjNmPy5DFP40Oe+CbsOzcGzzXX7zIl8+1bc8LR7JP91p53HdbtPS38OVefwl5+8EflFM9+nbz6Dk2fH4ZwqwNrXkfuk5M8Td5zBV09tW5cgYt1vP3An/uGTTxGl8nh8AGc+J1us3Oqj3Q4vTIlQOEuj2MOaX5Tc1LKFH9kiOE5JnHpap+kbKREWyqhQwoXbyCwizBzaMv7cemQuXrk3hkkkgOPFMg8oTcTfDfNkz61V5VlhYbgE/11rdI2UyHIJbikQKRX2i5JNFPxmWVypyPhS8qdU7GNtoYrSWFfGeG2+Am/ZRViJUZw1W9GNb5nD7NkG9u+cF7H11gNjmHjcIl6+93P4tVu+TepYTSNqXNu7Ktucoe9KLmiGEXD+cW7Uqz0snm5gy46hMLWxx+L9E0gqEZ7/TbdKHmpuBxfvLGD6uadx7B46ViDSSrwnCigzdIDbxjkvErtwTsr7JQ0rCdseCmO+5E4ebpnyGnxGZmfHUB3r4olb6KQB7luZkq3XeKEgkjWUjuI85zNKsWuOZW/BhFMUJnvorRYkJ/TuyWX0Qg+LzYrMNT7XFB4fim3zb46vbLH73nqKRspCnZwdl9zNfOZZhvmRGSbA7eDOShFW28Vzb7wdnzy2X+bp4LR5Nihc3vziFMJygsL+Jux/q8N+1rJs3f/03JPwDw9cI/fAwjHn+4r70rZvoTRrYdfzj4p4v+3biH0fx3/m51j1QtKrmUHbeBHHxL63XAQA/AUFwI2b/fKr+Vh5AJnqhXv21P5jpmyC1gfS9HBZPIDnWvyhAEjBKIo+vegh28Lc5iXdPD+NgfxTypABeOsGho91fv6h9RQAzUKrAKgAqACoAKgAqAC4gbU0axW+bHlwcyG9EEU1yRIm16qWDVngsQLAYWf437qXpTD41PTU7xvS5M8mWnrz5aEAuC3NK8i4gM+ec9lfSbejbwDwLYy3fogANSOgb3+YbqgHUD2A6gFUD6C8HtQDqB7AkfYAvvkX4RQe9IJf6NIa+T6OvH2kPYBraWZT3hqdOoRAcwLswWLyYmo5rwUeawA8txOMw+OBEAIXB4/bsN+dYZw2CoC/muYlvjHDdw2bGsV13QIWe6gHUD2A6gFUD6B6AEfEA/hzFwEA3zGyAMgDpRsp3PHT8jAWuJQAOOwSg16+K/UKXkwA3MgWcNaJYWIt3vsmRHFN4n9YQt+D7UYSczaMIXrKnhPy2S2H92J6C//jAswv1CTeiNIErdUSpqfXRLJjGC9IGQzG9vAalKPwl4qwK4EkPx+vt9djZ3itZrsoshWMAypUBtg+torjC+MIOzlUJzomVVbfxL+4XoT+agGF8Z5IVohUB2MBi4HEwIm0TDozKGNDaQvGSDHF2epSWeKMGDclkh+MOXPNf7rGGh0szdVEeoFxQkyJVZ9oY2u1hbm/2o29L7tfUkixlLa2RabC2dKTWD6mrXLaDrC9JymcnnLgGNqhSft0ZHECY+Ue5peq2L11CYvtClqnqyJRkjDtWGJJrCILY3EYAzRZ7YhchEhy+I7EEtGuvM9ywcTTHRqfx+eP70bYysEaWEAxxo6di5hdqktaKb/N7zeGcAsBDm5dwPbSGj5yx9UircF4I8YDMi6N6d34bxZe37Fiie9iyinakzF8jNHjddkPylJwTFmCgYtc3qS6Yj1K/DDt2eJyxaSgKwyw1jLZVii9wnZMl8V5wJgjxgDOVJu458RWiUejDAcLx4zfTdkT9pV/OA+Y5i/2HYkVZLynzJ9eQezGmM5CIZD40Fy1L33l/AvuryI2wwFvZ1tivdjnIHBkvpdqPUnTxTmwIlI6JvZtMFdCbsVGf2soMjBOIcJEo4250w24qy6mrl1AkNpB0oetVBEt5VHa1pZ4OcbYMXaO8jas1+oajwbHdc+2RTT7BbEN04WVKn1MVdrYWVnFl2Z3SHuWx22Zx53Htsm83TrelLR4nAecN8O4WUoVscR9B4WaUZbgZ343J2MgKQ6ZUq5s5o7UjSyEPQ+WE6NU7YvcEe9/+Cy6bixp71juvWsHnPG+PHscF8rQMC707FJd0jrOLdYkVpQxqix8btbO1FDe0pFx2VJv4cR9W1Dd1jL9GngPStcs55Hb0jXSKUfLqFy7bFLHreaAciipJs/cwd0ywNtl5Kbiw1UE1RhO34K9s4ugnROpot5sGbU0rWJzpSTTn/Fyd56ckfdZcqaI/J6W9J/FSWMq+a5aWzbvBr5z4MY4uHMOYWxjdrUuc5weUxbGSVN2iPYbFplj6XhRGsbJPejIcfjMUAomF0rcMaWAGKPJ9HOUzRo+R3wmGLfKcd3aaGK1W5QUdpStYrwj+F4zXZD3bk1kpHJIKPUTWUi6Ll52wy3480/fiK37ljDH9zPjGKeaODvbkLSGg2YeVi7C9i0r8sy0H2ispzlcnxcDB1bLlRRw3/qcW/HhW66D0zNfzBjAY49+fl2zLl3ZAMgHxfyPW8umLTAKALjpzj+k4cMdAqHkC6VfWPgUksR+55xDIJv5fkrL8A+vd0gBUAFQAVABUAFQAVAgb1QA8GcvggfwnSPrAZxNZdv+iLKym1nEtc1jdwr40bI1lToPpBe/FQDjCT8OgP/tJugNZWBemWr/UQaGB1GuAmCOz2Yr6gFUD6B6ANUDqB5A9QCurySjAoD735QdAB/4xZEFwDenusLcUvoMgPekaVx58FPLBi1wuXsAmX6DwPfQwn3/V6S/pAQMxaK5B8KUb69LNQE3aKKvW00BUAFQAVABUAFQAVAB8GKsqBd+DTLADwL4nvQACBNMEAYpAaflESxwuQPgpR5gkwv4D96C/Bj1vQZo3j+GeCyQ9GhMYWSveJL67Wm7j0lfb5vfhidtOY3bF2ew1iwhDi0UK32J52LatrVuEYOOia9hLB/jtnKMP+oUJLaF2mWsy/Rc1Iqr5E28EmNfmM6t1zHpxBgPyDg9iQHr5HBw91mcWDa6eowp8wdMdWWGnymScuVA0jIxlonp3BijxsJYH14rYYxM4CBX64smGlM2sbROVQHG1/C69Z60ZZzOMN6uv1REaaqDbqsARJbo8rFQQ6x3pIaoHsJdceHubUs8D2PPLDeRmLJh2d5YE823pdWKSUt23zRQjiQuj/Fn1MVbPGP0BbftXMbZhbrE8xw8eAZzrarEATHFGLUWq/WepBdjSagnuKVn4ogYB2klpl+dHGr1Hsq5AU6fMime4CTrab5ypUD0AHv9nMSGUXuO98dYMRZqplEvjnZeXqxIyjrqDC51y5IKzw890QQUDcU0JpMjwTgpps9jH2jDYQwatdGG6c2YEo7fzdglxsdRr4xac4wnZVxbrmD0AaXLdryua8e6h3adxWyzJm3DvoupyaakqmNhbCDvg3FYuyaXEcQOTpyaxNatq1hqlhGs5oG82ernODv/Wkfrel/mAm3Luca4K+rfrdwxiXDazA/G/VE/0qFdZS5Z8BmXeltetNSumljALffsk7qMVW2fqEmqstNnx+TeaNPxSlc07RibyHti4XOxtdzCvWen5bv7rTzcYiBpCBkXWPQClNO0g0cXJyTmi3OW98m21H6jlfZOLkmM6TDlHz9j/JzMj9iClw+lHzI3l0qoT7fX06oxJo5jxfi5AlMtdj2pK3qTzRysUrgeH8uxpCbf6loZUctD4iSwGBNnJShNd+SZ5ne07zf6m3wuLC+WWDfGziWBjS3bViVGmKV/siIpC1kGi0Xsf9wZ3H90KyoTtHWM5ok6nEkfyVwBuR0d9JbNPVHnk++b7koJudMe+tsCeJUBQo5vIYa15sKeMu8USbM3VwN6DqrbW2itFuWdxPdR80xNzlvWd5oY0sdPzuG2s9tQKQywePckcrvbokU4u1gX/cWt9SbOrJpnlHF0TjEEY/tk/jixzAmOEZ8tpnBjn6S/TiLxeYzxjDsecmO+vFv4M2OP+UwPS6Xmi74jdU75vqTNoxNlVB63YmKo+x7CNMaSsZ6Vya4869QHTLMyyrtyanoNi8vV9TSbO7asiI4g338WYzhd835NFvOwQgtxMV4/e5pbdRAVEnh72vBny0DFxL7yfeQ1+oi7Po684p3s8qOuA3iFewDXxz39B3cDqTBCxw+VP+4G8IcAfuOhFfXnBy2gALi52fA1MYAKgAqACoAKgAqACoAjBYBvvAhbwL80slvAX2/l/g4A70vVRcz/srWc1wIKgNkmhnoA1QOoHkD1AKoHUD2AspKMEgAe+K/ZAfD+d102AEiNYcb3czuY+r4PpPrC78q2xF/ZrRUAs42vAqACoAKgAqACoAKgAmC2tXSzrbndyyxjL2Y0DYC/Srd+meBByyNYQAEw2xRZPwRiF4smvmQ1h7gQA4xfqgzwlF0nsOiXJYcli2vFOLXUkBgsdFzkpnqol3pYODKB4rY2uitFyXvJMoyNKZQH6LUKcPJGB4tacoxXY8wWdftYmNOy3ctLTBp13vbMLOLsWm09jyljqcLBg95wN2fyYjK2j4fBGU/HuJr1uKY0Z+YwZk60/hJIfl2vanIHM26JWlzD/JqSi7MQSiwh/2ZsUnFLR7TiqOPFa0SMNWKO2N3LWDw8geLuluThfNLBE7j1/l0Sx8W4n8FCEc6YsQO179qdAqoVE//TXChj7555PGFsFh/62PVItvvrMTyM52EMJWMaZTwW84gdILe1K/E97pyHYMLE6jE2p1TzJT6NcYHDGDrqJVJ7jnGVw5izWrEvmn5DDT/GQfX8nMTx0YbML8z8z8PCthLjl8bj1Wtd1As9iU9jHBjjnyrFdJytWPIhNyY6ktuUYzrM18zrMa5SNN5SW+TdSHL8ikYf40OZ57YYSMzh6loJUdfo3zGWUvTklssmNynt33NF/298vI2lxarEmLFQY42xg/21PKZnViUWlf8uj3dFC49tRd+NWot12iyWXNeMuxpqTDJejpqIS/dOwt5m4tMktiwfw8lHksea80zmthtL/ub5VlXmMQu1Htv9nPSX9VmoizezdRX90EUt7+PYqSn5fbHmS1zZ8bkJGSvmAW538+v6ivmc0VVkWVktS2wex4mxncxp3PbzqYahyZ87vLfaZFvmAuMa5RmVTljyTPJ6nMu8Fku/nRO9Osbx8jmh7iVj+oqMo+17opE3fOb4bBRKA/k97ylXGcgzwbZTky0s3D8Ba7yPePidVkmwRacAACAASURBVGJiECsDBNSpzMVGz85LTE5Z/lwztuT7gWPEfj3n4GF84sgB0QOVQe86cBoDMFevzAnGFXIsAhvWmoebnnIPPv+xxyOsxpLLHCs5eFvN2El848Bdbzu9fQUxLCwx3pQ6lqEtMYFii156fTuRvOPd5SLsQiQ2pz1ou27XPPuc+4NWTjQhqWfKsWVMpp/m/GWsJp8fls5aQZ4hvhdEU7XviZaivLuYszvVMGVd/rve6MozRI1Rb6YrObuTgS1znu829pmlVPUlDtLOh4hX8kAuhtN0MP74RbR6Bck/XJs0WpaMc7b4XTW+Nzj2lsTqJi0PE3tW5HlmTCBLvJwHaoHEMg6oI9pzYNepV2qJxmTc83HqNZJN9FGPARQPYD5DJpC+jxH2AP506u17HIAvpt6+P0uzgZjB0PKIFlAAfEQTfd0KCoAKgAqAqci4AqACICFUAXBEAPBnLgIA/vLIbgEzB/D7U/C7I9sy/o3bWgFwc2P/74Sg1QNo/geuHkAzodQDqB5A9QCqB/CSegCvbAC8GQAdMP94zhL+AwDeRqECAB9ME0CYbRYt57WAAmC2iaEeQPUAqgdQPYC6BaxbwCO3BXzwp7N7AO/7lZH1AP4zgE8A+OV0CX8CgC8D+JNUAobav78P4K3Zlvgru7UCYLbxVQBUAFQAVABUAFQAHD0A/KmLAIC/OrIAyFRw35XG/9H2FFd8ZnoCmD/zUAi9gY/PtsRf2a0VALONrwDgzv/+NtheEVYxRBLZ8EqBBO2L8CtFiL0YpTTgf+14A950D0HHk4ThSdUcSGCgM8VkxypdEd5l4SECiqiWqLLfKkrg/GCuCKseIOm4mN61gsUV6l9C4m6Gos2Mw+F3M7iehycYiC2CsmkAdLncR4uJ3gc2UIhk25YB1iLCnIqzDrMEMhhegtbLA+kPrx2y7xT4HetKoDiD6ll4cIAHLyiAzaBtijQzaJoHJHhoJGp662LCIpTNwHQeAEiAq685icOz0yL2Wy30cXaujnIqGk2xVgmOp/CuG6HR6MqBFwaS1yY6aJ6uYft+hoQAnUEOqwsVydKcr/Qx6HpI0vtmIH9/sbieADGhaK/HoH1fDsvwgES+TlHuRILWpyptnFlJxWvbObglHixxpc+NyTZWl8tycIS25eGcMP0e2pIHObglPjwwwL7xcAwD0TmmfjsnAtEszbUSeCinWBjIgYpiPhAhWxbOIwkgT6/N78sXAxEzHi91cWJ+HNPjLTmgwjI8wMJ/U0C55efR6eYR9jwRuF04NYb8RA/ByQq8nW0E6aEDzhH2bdvUKk6dmTDizl6EneMrWKUI96mGCHqz9P2cCXpPA98pPs3AfR4MCSMb7cNjaFy9JHUXZ+sSTN9cLMPuOKjsbsohJQkVOFNCXH7w4AzHh4HzVtuFNdGXvlAQenyijclSB2dbVRHfHtqShx84buwH7TM93cTCUhVTE8YeFBCWZyMfmgMfgYNGvSs27nG8BzyYlKyLb8t108MFPES0LlK8UJLnRB5T2okHongUgGLO6eESXoclWs3BqgYiIM2DPEsLVVOXc82mqLER72afk9hGY6KN1aUKcqUBIopxr5j7QzmU50ZEoBM+v5E8axRo50GIeL4gB0JYKkccdJ7ow1rIw9vdRnCqjLgRIF8ZyMEgHo4ZHtSqNbpYO1ODNbAh8582GhvAWs6hsncN7aP14bklJPUQSWCJYHJ7ke+GGGh55kBV15NDbDxgYu4vRtDMI9/wMejycIyx1/CQGOf3RM3Mn8W1ihyOEVumdrFsIPIdsa2IQbfNgRGvaN6l7BS/I2TmofSAEA9ViMhyeoho+KyNjXewfLoOsL9dB3bDHMLge8BO+1Wt9bB2oi6C8tIPvguLEZLQMvfZdeE2zaG5qBQjLkVy6A38voEth3JYxxv35V5KFbPTyANt/A6Kt7dOV0UomsLafPcVJnuIuj7u//5fYtVH/RDIwSsbAJlR4CCAk+aBwacA0CsoKtsA9gC4nfry6c/613ksoACYbVooACoAKgAqAApICiwoACoAjggAPu4ns3sAD//ayHoAjwP4fgCUe+H/mlZTj+BH0yWdW8L/yv8HZ1vir+zWCoDZxlcBUAFQAVABUAFQPYAj5wF83H+5CAD46yMLgL8L4DoAPwPgBQBezkyg3ARJl/TvA/B6AE/JtsRf2a0VADc3vl9zCli3gHULWLeAdQtYPYC6BTxKW8BXOABOAvibNOavnQLg356znNMT+DkAP7u5Jf4bo5UCYLZxVg+gegDVA6geQPUAqgdw9DyAb7gIHsDfGFkP4HDlZiwlAfDBYGLzCbd++fuhRzDbSn+FtlYAzDawCoAKgAqACoAKgAqAIweAh34iOwDe+5sjD4DZVvBv8NYKgNkmgAKgAqACoAKgAqAC4OgB4OsvAgD+lgJgNkQY7dYKgNnGRwBw1x+8BbUtQHO+YiQEBjbcVQdhPYLNXJB9C+F06oke2HDqA0RrOSQ2pF40FUgOUeaCpWQH5UBYmqdqKG7toLdalNzCRoLCSKGILErfljyTLJQCmV+ughIvw5ybw1ujHAalTSSfL+VlmBO3bNpRCiMJHDilAFHfFdkHyixQeoKFsiMi0TCwJW+u38uZ/MGUqxgfSE7ZYaE0i8isFCORiLAqAWyPuVJtJKs5I+Pim1ycmPZhnyoirERAKTISK8sFkWjZdWAOJ+7ZitwWk02C8XXMexudKCOaDCS/5t6Dszh6eAaF6S78uZL5TkrDT3TkXkXigSczi5HIiKyslCV3J7+LkjYszBksX8gDnMyZOt6XcWHuWrE3pSHSJ4Q5WYuFQPLEgjIlVcqE2OuyEczFK9IY7C/zinrpjkQCkYmgLATHhfIpzNVLGYlyjUoGJtev54WSk1jy8fZdsRnzGnPstk2s4cySkaOpVXysNUsolfoiZ0LpGUrTcGyZI5VlKIch8hgWjDQPx2DgoDjekzynlLuR76bNKZUy0UP/bAmg8kUElLe3RTqFEhySm3m+CHfC9JfyPpTkYN7r3LYOCrkA/YEndSUn9VcmgENmXrAPlL+h5M3q2ZqMf0IpHEohnSmZ/k6YvrCPvI+Yz4aXoDTRRa+VF7mVyfEWBpGDVsvI3cxMrqHZK6C1VIZdCI3MR2DLPBrmqWaeWZaF+brIElHGg3I1lKER26TSIiJ1xLzN0mHI8wDK+1DqI81HzPkg+YE7HtySkW7i2MTMe13rizwJZUbGZppoNouYHGsj54Y4dXpi/bp8N4gkEfP8Mu+2m8A9m5NnIOGcAzAx05S/V+8fEzmWuBibdwrzbhcC2PeVER/sIGAe4mLaD87ZyEJh0Ya/dyDX5zPAPM18dlaXyus5qTl35Xv2LYu0D7/D6ttw+hbiXIK4GMnzbgbaAgILSSE274SBIzJRfKYpDcVOUTZFxjDgSwJyH9JfSrSUQpE3CkQjMPma/M7yXmBucsvINTEPsLRLYGRgVs285O9E6qXrIjfmiwwOc1Dz1DXzV/trBXl3mXHivZlczMxFbPkOUAmlj3wPS67ldJwlHzJlqQoxLCeWd5rkhObzUE5zha+m+Y05zsxn3bVROrhm3gHMT5zmFaeEjJc+G8FSQd4d5S0dkdW6ev9p3H33TvmdyBX1fJx8/VvY3UddBuaQAmA6kfWvh7OAAmC2uaEAqAAoi5QCoAKgAqAC4EgB4I9fBA/gb6sHMBsijHZrBcBs46MAqACoAKgeQPUAqgdQVpJRAsCrXpcdAO/5bwqA2RBhtFsrAG5ufL5GBka3gI0RdQtYt4B1C1i3gHULeDS2gBUAN7e4fyO1UgDMNtrqAVQPoHoA1QOoHkD1AI6eB/C1F8ED+O5NeQDpIPkpAFsB3AbgtQA+/zBL7SsA/PFDPmNQsAkC1fKoWkABMJt5FQAVABUAFQAVABUARw4Ar35NdgC8+3cuGABfCuB9AF4F4JY0G8eLARwCMH+e5ZYA+Nvp58OPeSxvLtvSrK03YgEFwI1Y6eHrKAAqACoAKgAqACoAKgCadZLQ9wUAr0mXTZ4pPwng3QDe9TAA+FsAGtmWYm29GQsoAG7Gag+2EQA88P43wjoxhcFEhO37FnD6yJTUKJ5y0NtGbQQAnkkWLxIjvg1KB7htG1E+AWwgsRNYk0amYHyyJVWXlypGFqPtAXkjrUJZE542pPSFSJSklxXpCitBrjLAYKEIuzEQqQtKgkQ9VyQnhoVyFizRSk7qUR5DfqYsAy8ZPDgt3EqAOLBF8mQo5SByCzFQHuuJ9IfI1PBT3kouku/1iiGiwDbSHks5dg3unjb6S2ldOxEpkvB0GVE1BNjXvo38TAeD02U4PRvhFiPXQpkGSqLwXpLDFYQ7fUxOtND+zBT8q3wkHRfemJESCboerKaLpBGI7UQehHaj/Wmf6gDxkbKpOxHCojwEbUWZGso/DGxYZSNfQQkNf8FIlaAQyb1xfIw8zNDwFgrjPalC+RGpmg/Q8z2RZ3F4QjgfpFIvEQa+K/IXlCuhrAxLu1mQe9s7s4ijs5OpjImRCnEKkYyfSO/QFrlI5Co4HpToCVbysKsBHDdGo9LFwqkxNLYZKZG11RLylKfhdwYObC8SiRWRu+m7qDa66HTypu8yx2LkSgMEvrsu80MJGOdIEYMdfVhrJsYxqUSw8yG8B4ooPnkZq/NVkSSi7A+Ld6KA/hbzb6ftorx3Da3VopE+4dyvB3I/IivCuUhJFt5b20VSD+DO5kVCCblY5lS+1seglcc1+0/hjsM7pS7lVlbP1ERqxMuHCE+WEY8HMka0S7iah532h7ImYqueK8+MzCPOdYfSK5ZIqNQmjWRMc7ksMkOUC6LcEtuGXSOdQtmVuOXBqZl7i1MJFLFJ4CAn/TRyR5QycewYvTMVM39qAbxCuD5eyVIeVmhJn+Uh7rhGQiV99Kx2+izmY9gdB/HEAOi5sLu2yLW4Uz2RghG7UVqpFMnc5b1QQofT0+7ZiAuxyLlQykXqplIrlDHxZnMIahHcSV+uRbkVFnfOXDcsJSjM2+jtCmBxjPheqIQAZYx47+k7Ru6fz3nXMTIyhEE+HuyT2NvI2AzfVaK8lD4rlLahhA5tJu+3UmTeP0M7DGzsODCPMwsNRB1P7onzL+El2Sc3kX/LvfEaqXST3LubyFyjJA7mC8jvbmFwtGrGbroPazGPiDJUVgKn48Db0UG/nUOuHKC/lhe7y73RnpTD4XtK5IBihG1PbOmdoYxPLO+bYbFWPRlLkZ4JgIjvGc5Lvsu7Po790DtY9VGXgbn61RfBA/jfxQO4A4BZlEzhy9a8cL+2cOJQu+tFAD54zkfvTQHv+edpQw/gewCcpuoYgC8D4JfeeZ66+quLbAEFwGwGVQBUAFQAVABUAFQAHD0A/LGLAID/QwDwoeVtAN56nt9vS0HuJgCfPefzXwHwTAA3nKfN0wAcBPDVFIp/EsDNAK5NPYfZVmht/XUtoACYbYIoACoAKgAqACoAKgBeyQC4UQ/gwwHgrwJ4BoAbN7DccpvhbgB/BuDNG6ivVTJYQAEwg/G4saNbwLoFrFvAugWsW8C6BTxcSkZlC/jxF8EDeJfxAG50u3ozW8DnW4H/khEIAL432/KsrR/JAgqAj2Sh83/+NTqAGgOoMYCcJhoDqDGAGgOoMYAjA4A/mn0L+K7fvSAA5GuQh0Ao+ULpFxbG9Z0A8DsPcwjkoSssAy/vAPDPAN6wueVZW23UAgqAG7XU+eupB1C3gHULWLeAdQtYt4BHbgv4mldlB8A7f++CAXAoA/PKFARfD+AlAK5KpV0oEcMDH29MDcbEyJ8DcH96UIT6gS8AcD2Au7Itz9r6kSygAPhIFvr6nysAKgAqACoAKgAqACoAPrhWUgJmKAT9FQCvSz2DrPEJAMcA8PQvy28C+J5UNHoFwJcA/ByAW7Mtzdp6IxZQANyIlR6+jgKgAqACoAKgAqAC4OgB4I9cBA/g71+wBzDbiqqtH1MLKABmM7cCoAKgAqACoAKgAuBoAmBu8xnVooGPOxUAsxHCiLdWAMw2QAKAO3/7F2DniiKO7HRtuD0L/V0DJKEl4qjUIU2MRjCKZ210Z2IRMEUxFNHV2AXswEI4nYo3D0WbU51aESrNxYj8VJiUgrpOIuKiFDpmyZcH6M+VjKBqLgYCW0RyY98xItBd01ZKORIxahFk5XW8WASLKW5qOvvgtLBiwPZt6T/FTZ2Wg7DxoHCzfN4fqrZCRGopaM1+2WfziAoJWIdtKVI7FIN1fBvRZCAiz7kjBQS1BJjyYc0WRARYBF9rPAgGOIUQEcWJu866KKv8noLGiwVzvwUjbk2RZiu05eccbbL64AvQ4vdTQDYV8OXP8ViAQrWP6HBVhKFdilMvFI0dKWTbMiLAIlAbWXIvuQkfUWgjbOVg8bt5XYr/lo1wtetE6HXyRuyW9slHcL0Itp3Ab+ZlbJzaYF14W4SJ1zw0dq+JeHMswt1sCFhrLuKSESSWa5cHCHgNCodzjCnUzfoU3qWAbkLRX2MLCtGyrcxB3msthLPkItnmm/HxYkTLRgia81bGjvdiJ4jrIdA2916atdHZF4iAMgvnS0Ih3EqAXDGAv1KAt+QhrESwagHcUwVgf0fqBvNFI7RN2/E+OcfYv8SCu+DB3tdGMGvEtpMcbR6KcHjM+VKMRJSZ1+Q98ibF3uyDdY5Q9loONgW+U3HhJLDhlgOUS0artrlaMiK8qdA5708Ek/nsUB+cIuGp0DZFk0GxZE7pVMQ49l3zrAXmpKvMZRbWdYDEjc3vOUZWAjudX3E1gt1M508MxBQwthMZFz4zCfXU02fda9kIZgbrYszWUk6eu7BqxJTzCw6CihGNp23sgSWfG8MBxQWgdSAytqWQNe+N85ci6rN5JOn3RKX03UNx6FwMd8VFnE/k/UOxY4oay9znnGgMEC0bUWiOlzzH/Kwcwea8pLh0agsRX68HZs4M3x+clKVIxMwdN8IgFa7mPdgrngjAizA14bFFQ1rm+mMDI97OOdxx4OzoIuh4sFquzBFrYOrZg1Toejgv+7Z8TrtwrlMU2unYsCKY+6K5zKMh81zefem4O74lwtcyVwMbOQo8l40daO/ckoPBZAS7NkDu3iIGYwncjoXBOA+9WIj5TuV1OV/5VVN9JLOFdb14a0cX7t1lRL6P+9/1qHvVZF26hh5ABUAz4FrOawEFwGwTQwFQAVABUAFQAVABcOQA8NpXZgfAO/7gUYfVbCuwts5kAQXATOYzOoDqAVQPoHoA1QOoHkD1AI6SB/DaH74IAPj/KQBmQ4TRbq0AmG18FADVA6geQPUAqgdQPYCj5wFUAMy2un8DtFYAzDbICoAKgAqACoAKgAqAIweAT/jP2T2At79HPYDZEGG0WysAbm58viYTiG4B6xawbgHrFrBuAesW8ChtAT/hP10EAPxDBcDNIcLl0UoBMNs4qQdQPYDqAVQPoHoA1QM4eh5ABcBsq/s3QGsFwGyDrACoAKgAqACoAKgAOHIA+MQfyu4B/OofqQcwGyKMdmsFwGzjowCoAKgAqACoAKgAOHoA+IMXAQD/WAEwGyKMdmsFwGzjowCoAKgAqACoAKgAOHoA+IqLAIB/ogCYDRFGu7UCYLbxUQBUAFQAVABUAFQAVADMtpZq60tgAQXAbEZXAFQAVABUAFQAVAAcOQC87uXZPYC3vVc9gNkQYbRbKwBmGx8FQAVABUAFQAVABcDRA8AfuAgA+D4FwGyIMNqtFQCzjY8A4J63vxNWuYCYiciZGLwYS7J3SYpuJXCbNoJ6msQ+tCCJxysx3LaNqJQAUz7co0UMdvXhFUIEvkmEngxsSZbOZO5xIUHMxOlFJk+3JOm7mw8RNPPmxROY5O6SXJ0J2Zn8nT8zgXqa9Hw9iT1HXZLFh5KUXforyewTSTzPeg6Ts7MPbiK3weTzCfO1M1k7f/Yt6VPiJfBWTF0mpbdDoL9rAHfekyTzTNzOelZoSVL1YfJ1+Y7aAMnZojTlveWXHFhsPxmbpO5dk+w+t7uN/ukyrIk+kuU8kmoIZ9EDE9sPE9pHZWNfXtcKbLirDqIdPqzFPNwWOwwM6rHch9tLp30MSebONrkFD9RxM2MIhFsGsN0Y8YqxL7wYVjmEZSWImzmxHe0syekDC/ktXfgrhdQOFpxSgLjtwe45SCb70i7qubByZnzY7+KYL/X9hRIS1/SbeoIcW46PveYipmmtBKiEUtf2YkRdFxbHlNfJx3KvtHXsJTKnwtQWMi+idD727PV553Rsqc++o2iui8jYGl1H6kmi+7FYxo3J7SPOO/5hCS3kJ3qI7qsinBkAbUfsi8jUza3a6G8ZXtcyfarx/iyZL8P5yjkUTQewmma+x8VI5pbl0w5mrjldG8nEAI4Xma9eM+Ph1vuI5osy5zhuVmOApOPKvytTHXSWS0Df3FPCsaNdAxtONUCSAPFKDnZoydymDe1qYMzQ8QA7AfXc5Bni/XPKix0jWH3bPAOcEmuOPL98btjPYCKU50aeGSdBbsURe8h1CwnC6QD2sifXY7/5O9ra6AcCcSkyzzZ/rAcyd60AiCocAGNb2s9dc+T9UT5h7q9zTR/OQk6uKTYaC+EUQ9ininC7QFhKxw+QfvJz27dROGujN8Pnjvdk+iN9LZq/aZfCGTM2QTmRfg+fEekv7ZFOGwSW6Vd6jzKehdjM26aHpBjBXTXXCmuR2Cmqh2bOc2g5hoG5d94j553YIbWfXI/PZs9etx/HJJgMzNiyLiE0l8Bp82LmetJmwB8Ap4/1ecn3nYwz38c9S94DnKd8LmibaLuPpOmZ60YW3Jb5zIxljKQQI3/WQ+wCwXi4/g6093Vg316Bvz2Et+RK//vToXkfNHOIez5OvuHNvEwdQNOM2EUvsi5dpwB40Q17pV1QATDbiCoAKgAqACoAKgAqAMpKMkoA+E3f/044ufQ/pZtY56KBj6+8/2cfbVjdRM+0ycWygAJgNksqACoAKgAqACoAKgCOHgD+vxcBAP+nAmA2RBjt1gqA2cZHAVABUAFQAVABUAFQATDbWqqtL4EFFACzGV0BUAFQAVABUAFQAXDkAPBJ35fdA3jr/1IPYDZEGO3WCoDZxkcBUAFQAVABUAFQAXD0APA/XgQA/FMFwGyIMNqtFQCzjY8CoAKgAqACoAKgAqACYLa1VFtfAgsoAG7O6K8GwD8UQTikMjAqA6MyMCoDozIwKgMzSqeAn/y92T2AX/4z9QBuDhEuj1YKgNnGST2A6gFUD6B6ANUDqB7AkfMAPvllFwEA/1wBMBsijHZrBcBs46MAqACoAKgAqACoADhyAHj9S7MD4Jc+oACYDRFGu7UCYLbxUQBUAFQAVABUAFQAVADMtpZq60tgAQXAbEZXAFQAVABUAFQAVAAcPQB8yUXwAP6FegCzIcJot1YAzDY+CoAKgAqACoAKgAqAIwmArrf5VHBh4ONLCoDZCGHEWysAZhsgBUAFQAVABUAFQAVABcBsa6m2vgQWUADMZnQFQAVABUAFQAVABcDRA8AXvwOZPYB/+XO8rzqAZralUluPogUUALONigKgAqACoAKgAqAC4MgB4De/KDsAfvGvFACzIcJot1YAzDY+CoAKgAqACoAKgAqACoDZ1lJtfQksoACYzegKgAqACoAKgAqACoCjB4D/z0XwAP61egCzIcJot1YAzDY+AoC73/VOYIZZ4QBrzYM9sOB2LVgh4E/H8nt3qid/R/NFAYaoGsHpOIjzMRADbsdGOB3AncshKpo2VmjJ5874AMlsAYmbwOnZCLcMgK6DxEtgJeYGnNoASWwhbnmwBjYSJ4FVC+R36LpIvBhOITR96Lmwew6QAHE5MvVzMZw1F3EuAcqhXF+Kx0qWtLecBPKFbReOb8Pe2UUU2kgW8+tWtFjXSZBUQ6mXFCPYHQd234K1q4twzdRN0pmXq/cRnS4h9hI4kz7i+YIspnExRtwIpG5jooNB4KDbLAL83moAa7aAeLqPhPdLOw1t5sZIQht2IUSuFCAcuLCOFxHv7CFu5WDz2pMDY99VD45vid3hO0jcGJbvwIoBa7IvtuS9yPiVQzhuhEHXkzFO8rGxcS6Wm3HyIcK2t143jix4+RCDxSJQjOAWAwTtHCw7Afgnss3fLHYifRGb8fs4NhZg9W0k5QgIrAcNFlqmTj6G5UWIB465ZseVoUnq5l7k/kohksCGnY8Q+y4KdR9+Oy9jyznKcY3HjY1tN0LU9WD7tsyL6p41rC1UYLkJ7FVX7FuYMHPY7+RQOJKHvzUCiiGchRyiyQDo27C7DgrzFrpX9U0fnAS5YoDwWAVRJYLTdMTmg+kQKEQo1Xx058umDx0HUS2UayQc+9CGO+8h3NYX+4hNIjNx4kIMpz5AvJBHUuAzxPsBUIqQ0EZ8JkrpfO94Mh84VzjPaY8koI0TeT4sL5a5ajoBIG0P/p730DfPtlzTtxAVzLhxDjgtB1E5BiJL5o3Ml1IEOxchWcojSZvyfRB7EBvYPTO/eV2Og9e2pF5Qi5Hw+QOw68AcTt69FUktNM9c00PxrI3e9kjsVh3vorVSMp1qu7BDC+72DsKTZXmG2U+WqBIDpVDmrNxLZCGqhMifNT/zO/k79jsuRcgteIjyw5cK56m5L/5xOxYGYwkSzle+FvIJrLKZP0nPhcW5QxP2+X6LAT4brJjOZ46f6RSvZ37ge8COzD9ivmPYl3xs3k/SX8h7j/2QdxOvz7mbjgX7MCysy7HhNewg7R/ftaXYzGtOkbqZE/aaKz/Lu4p9CIwN5H1QjmH3bXlHs7iVwMwzNwFTPg5Ol+Xd63RsefdY+zrybLPkZj2ExcQ8V3yHsqupDeW95vs4+tY3seqjGVcn69JTXpgdAL/wtwqA6xPsCvyHAmC2QVUAVABUAFQAVABUAFQAzLaWautLYAEFwGxGVwBUAFQAVABUAFQAHD0AfMFF8AB+rBmtDwAAIABJREFUUD2A2RBhtFsrAGYbHwVABUAFQAVABUAFwJEDwKc+PzsAfv7vNgWArwbwUwC2ArgNwGsBfH4DS+3LAPwZgL8D8IIN1NcqGS2gAJjNgAqACoAKgAqACoAKgKMHgN/99sw6gJ//+zdfaLziSwG8D8CrANwC4PUAXgzgEID5r7Pc7gbwaQBHACwrAGYDk422VgDcqKXOX08BUAFQAVABUAFQAVAB0KyRhL4vAHhNumTyZNBJAO8G8K6HWW554udfAfwxgGfw3J8CYDYw2WhrBcCNWkoBUE8B6ylgeQr0FLCeAtZTwKN/CviG78ruAbzlH8QDuANA65wlkEf8zTH/ry08Ct0F8CIAHzzno/emUPf8h1lu3wbgiQBeCOBPFACzQcmFtFYAvBBr/fu66gFUD6B6ANUDqB5A9QCOnAfwhu+8CAD4jwKADy0Etree5/fbAJwGcBOAz57z+a8AeCaAG87T5ukAPgDgmwAsKgBmA5ILba0ACPwtgGcB+Gj6P5cLsaECoAKgAqACoAKgAuCVDIAb9QA+HAD+arq1e+NDFtcqgK8C+DEA/5x+ph7ACyGQjHUVAIFnA6gAeLkCoApBqxC0CkGrELQKQV8JQtA3fkd2D+Dn/umCDoFc6BYwvX63Gmnw9TJUXacKOw+OPJCRcbT517GAAqAxDj2ADFpl7MKFFPUAqgdQPYDqAVQPoHoAR84DeOO3/0LmU8Cf+9BbeF8XkrWEh0Ao+ULpFxYC3QkAv3OeQyAFAAcesuC+AwA9gz8O4DAAk7ZJy6NigcsdAG9O9YauBzCTBpGeG3xKo21Ek0gBUFPBaSo4TQWnqeA0FdwVkwruEgHgUAbmlSkIUgbmJQCuAjCXSsQwTvCND0M0ugX8qKDe+S96uQPg8wAwiPTLAP76PAC4UU0iBUAFQAVABUAFQAXAKwYAn/a87B7Az/7zBXsASRrcTRsKQX8FwOtSeRh+9gkAxwC8QgHwMSS9h/mqyx0Az70tBq7wGPm5HsCNahIpACoAKgAqACoAKgBeOQD4Hy4CAH54UwB46clGe7AhC1zJAHghAakbBcA8AP4ZFsYqnNr9rncCMyZ21VrzYA8suF0LVgj404xlBdypnvwdzRdhBRaiagSn4yDOx0AMuB0b4XQAdy6HqGjaWKElnzvjAySzBSRuAqdnI9wyALoOEi8B9bhYnNoASWwhbnmwBjYSJ4FVC+R36LpIvBhOITR96Lmwew6QAHE5MvUVABUAFQAVABUAFQDT1S0MfHxWAXBDIHW5VrqSAXCjmkQfAXAdgHKagoZpa87VMDp3bKl99PMPHWwFwAeZ2Iotgc+kGgJtF0kxgt1xYPctWLu6CNdM3SSdebl6H9HpEmIvgTPpI54vwOnaiIsx4kYgdRsTHQwCB91mEfBt2NUA1mwB8XQfCYGXoDyEZjdGEtqwCyFypQDhwIV1vIh4Zw9xKweb1540ccXWqgfHtwS84TsKgAqACoAKgFcMAN70bdk9gJ/53+oBvFzhbiP9/kYEwIfTJNqIvdQDSJdj24VDENvZRaSngPUUsJ4C1lPAegpY1o/crIewmCAeD2SXBlxhIwtWDPMfW9/H0be+iVUv5GTtRtamc+uIOsVN/9fbMp8C/sy/iL/j0ezrhd6b1r+IFriSAfBCtoA3a1KVgVEAVABUAFQAVAAcPQD81osAgB9RANwsHFwO7a5kAKT9L0STaDPjpQCoAKgAqACoAKgAqAC4mRVU21xSC1zuAMgMHkMhSSqKvwHAx9NYPopPPpIm0WaNT21B/uHJj0MaA6gxgE4+RNj2ZD655RBxZMHLhxgsFoFiBLcYIGjnYNkJwD+Rbf5msROJR5S4SScBeEDHAqy+jaQcAYH1YNBkaJk6+RiWFyEeOOaaHVcOBCV1E88oMY6lEElgw85HiH0XhboPv52XrSkeVAIPDXGril1wI0QaA6gxgBoDeMXEAD6dHkCXWsubK2Ho49PqAdyc8S6TVpc7APL0LoHvoeW95+gMfT1NoqzDpB5A9QCqB1A9gOoBVA/gyHkAn/7ct2YHwI/y3KPGAGYFhVFtf7kD4KW2qwKgAqACoAKgAqACoALgpV6N9fsv2AIKgBdssq9poACoAKgAqACoAKgAOHIA+C3Pye4B/NTH1AOYDRFGu7UC4ObGR2MAVQbGiG3nYgVABUAFQAXA0QPAZ18EAPy4AuDmEOHyaKUAmG2c1AOoHkAFQAVABUAFQAXAbGuptr4EFlAAzGZ0BUAFQAVABUAFQAXAkQPAZzzr5zMfAvm3T7xND4FkY4SRbq0AmG14FAAVABUAFQAVABUARw8Ab74IAPhJBcBsiDDarRUAs42PAqACoAKgAqACoAKgAmC2tVRbXwILKABuzuh6CEQPgeghkK0RUAzhKAAqACoAjhwA3vyMt2TeAv7kv/2CbgFvjhEui1YKgNmGST2A6gFUD6ACoAKgAuDoAeC3XAQA/JQCYDZEGO3WCoDZxkcBUAFQAVABUAFQAXD0APDpb87uAfz029UDmI0RRrq1AmC24VEAVABUAFQAVABUAFQAzLaWautLYAEFwGxGVwBUAFQAVABUAFQAHDkAfOZN2T2A//oZ9QBmQ4TRbq0AuLnx0UMgeghED4HoIRA4LQdROVYAVAAcPQB82s9l3gL+18++Q7eAN8cIl0UrBcBsw6QeQPUAqgdQPYAKgAqACoDZ1lJtfQksoACYzegKgAqACoAKgAqACoAjB4DPuiG7B/ATt6gHMBsijHZrBcBs46MAqACoAKgAqACoADh6APjUn828BfyJz79Tt4CzMcJIt1YAzDY8CoAKgAqACoAKgAqACoDZ1lJtfQksoACYzegKgAqACoAKgAqACoCjB4BPuQgewC+oBzAbIox2awXAbOOjAKgAqACoAKgAqAA4cgD47G9+U+Yt4I9/8Rd1CzgbI4x0awXAzQ2PysCoDIzKwKgMjMrAlAN5gyYKgAqAm1tLtdUltIACYDbjiwfweR/+Ydw1ux+NqTZumjmKWxd3oO3n8cQtZ3Dr7HZEsY1n7Doi37TUL+P42hhqeR/HTk/Cmc/B29eGbcfIeRHKuQFafl7q2naCmWoT850KlpcrwHIOsABvpgvXiXBwchG33bdL6rrlAYqFAP3ARRJb8LwQYehg+/gqlrsl+AMPk9WO1PVDF+1eHv12HrnSAEHfxdhYBysrZVRrPZTzA6y0S+uWYd9cJ0ZzpYTtMyvSfrLUgW0lsJHgrhMzUrdU7aPfd7FjYhUH6otyr41cF4PYxT3L03CsBIfG5qXuF07vwu6JZTRyPsLERhjbKDgh7pjfiulqCzknwmK3bGx2to69u+ewrdzE547twczEGjw7QrNfQNELsNQqo17ype7+xiKOt8aw0KzgRQe+go/OHsJat4B8LkS3l0Ol1MehcdOHE60x5JwQa34Rvb6HHWOrODI3CceN0Sj3MIgc+R6WRrGH40vj2Dm+gpNLYzI2YWijXu2h6+cQJxbiyJa65VJfrtefK8Gd8OX3Y40OWp0CqmVfPuNYnFmqm8UzsdCodbG0UEOx6mPPxDJWeiUZ41OnJ9CYbGN1ydjCdmP5EwUODmyfx5m1OqLIxkQ6tu1+DnFs+uE4MYLQweOn5nDn/BZ4boSbtx3B7SszOHZqCuVGT2xt5oSHghtgqVPGddNnZMxOtBpYbpdw086juHV+B2oFY+O8E2K+XUGvn8PVW+ZwdGVc5pdlJeg384Dv4LueeqvU/ce7r0Wt3sVYsYdjp6dwcNdZnFym/WKEkYO9k0vr8+zE8hh2ja+gH7poDfJotouIYwvVio+DY4toBnmcbVVNH9wInX4OndMVoBqKF7Y21kGnU8CBmXkcXZiAZSdSl3PX7+UwPd7E7FwDuWIAz4vM/E3nNucRy0qnhE6zgFwpQDhw4OVDBL4rY5Qvmjq91YL8XWj4CAcuosBGqerL95RygczxT953APZsHuPXLErd5bsn8eybv4rZbg1HlibQ73nYvXUJZ9dqGK905Xn5zPG9OLBlwVzbCfGVYztw7a4z0s/5bgUlbyC2GywVkJ/sYazck7qc39ViHzk3xJmFBmwnljncny+huKWDq6bncefZrVK3v5rHVQfOyDthtV1CFNpSn/N4vNhFxRvgRLNh7rPvoZgP5O/ubAWILVzzhOOYbdewulpCsTyQdwVLq5dHr52XOk4hRBzYmJpsoe3n0PdzqFR66Pk5qRudKCPZ6sM6U0A0FcByY7g585wFXU/aR2umrpTQLFPORB8xdxwCG3ASOLlInkPan4XvPY65Vwj5msTWehMrvaLMlcV7JxE3AnglM4aDVg5jW1rrz30QOxiELhZWqnDcCP3VAipT5n1ZK/rYU1vGl07txHSjhZPHJ2HFFuAmgG9j674lRPwZEJvyHuoTbTh2grVWUd5XnOsLqxXEXR/HfuhRP1kr69Kzr39jdg/gl36Jt8UXVfPBAdF/XSkWUADMNpIKgAqACoAKgAqACoCjB4BPfiNcx/xnZTMljHx8/MsKgJux3eXSRgEw20gpACoAKgAqACoAKgCOHAA+50n/NTMAfuzWd6kHMBsjjHRrBcBsw6MAqACoAKgAqACoAKgAmG0t1daXwAIKgNmMrgCoAKgAqACoAKgAOHoA+E30AJp48s2UMOrjY19RD+BmbHe5tFEAzDZSCoAKgAqACoAKgAqAoweA1/1MdgC87Zd1CzgbI4x0awXAbMOjAKgAqACoAKgAqACoAJhtLdXWl8ACCoCbM/rX6ACqDIzKwKgMjMrAqAyMysCMkgzMc55wETyAt6sHcHOIcHm0UgDMNk7qAVQPoHoA1QOoHkD1AI6cB/C51/505i3gj97xK5vZAqaD5KcoxQjgNgCvBfD5h1lqvwfAmwAcAOABuA/ArwN4f7alWVtvxAIKgBux0sPXUQBUAFQAVABUAFQAVAA06+RLAbwPwKsA3ALg9QBeDOAQAKPA/7XlWQDGANxDfW4A35kC4HcA+N/Zlmdt/UgWUAB8JAt9/c8VABUAFQAVABUAFQBHDwCv+ansHsA7f/VCPYCEvi8AeE26dDJNy0kA7wYgR4o3UL4M4J8AvHkDdbVKBgsoAGYwHrMEaSo4TQWnqeA0FZymgtNUcFxKRikG8LmP/8nsAHjXr10IADJ/XxfAiwB88Jyl9b3Mpgng+Y+w3JJHngPg7wG8AMC/ZFuetfUjWUAB8JEspB7A9XypmgtYcwHzcdBcwJoLWHMBj34u4Ode/V+yA+DdDMfDDqZ7Pmcp7DOt9HmWxm0ATgO4CcBnz/mcgYTPBHDDwyynzDXMdhQtZFLoHwPwR9mWZm29EQsoAG7ESg9fRz2AugWsW8C6BaxbwLoFPHpbwBcPAB+6Ar4NwFsvAAC5j/wMADc+zFLKbeJ9ACoAnptu/dID+Ilsy7O2fiQLKAA+koXUA6geQO5fFHs4vqQeQPUAAr1V9QCqB/Ay8AAeuggewHsvyAOYdQt4uNq+B8BOAN+WbXnW1o9kAQXAR7KQAqACoAIgbp3fgVrBl6dBt4AVABUARx8Av/Vxb8i8BfyRw7/BR55btM0NLpU8BELJF0q/sNC7dwLA71zAIRBu/9IjyBPCWh5FCygAZjOubgHrFrBuAesWsG4B6xbwyG0BXyIAHMrAvDIFQcrAvATAVQDmUokYxvu9MV16+fcXATyQxgB+ewqKPwqAnkAtj6IFFACzGVcBUAFQAVABUAFQAXD0APDgT2T3AN73mxfqAWR9SsAMhaC/AuB1qSYgP2Nc3zEAr0iX3nek2oE8aNJL9QB/G8AHsi3N2nojFlAA3IiV/n0dTQVX6sC2EtgKgAqACoAKgAqAoweA+1+fHQAf+K3NAODmVlVt9ZhbQAEwm8nVA6gAqACoAKgAqACoAJhtLdXWl8ACCoDZjK4AqACoAKgAqACoADh6ALjvx7N7AI9wN/aCDoFkW1G19WNqAQXAbOZWAFQAVABUAFQAVAAcQQB8HVyb2sqbK2Hcx0eO/DcFwM2Z77JopQCYbZgUABUAFQAVABUAFQAVALOtpdr6ElhAATCb0RUAFQAVABUAFQAVAEcPAPe+NrsH8Oi71QOYjRFGurUCYLbhUQBUAFQAVABUAFQAHD0A3P2a7AB4nPrNGgOYDRNGt7UCYLaxUQBUAFQAVABUAFQAHD0A3PVj2QHwxP9QAMzGCCPdWgEw2/AoACoAKgAqACoAKgAqAGZbS7X1JbCAAmA2oysAKgAqACoAKgAqAI4eAO780ewewJO/qx7AbIww0q0VALMNjwKgAqACoAKgAqAC4OgB4PZXZQfA07+nAJiNEUa6tQJgtuFRAFQAVABUAFQAVABUAMy2lmrrS2ABBcBsRlcAVABUAFQAVABUABw9ANz2I9k9gGd+Xz2A2RhhpFsrAGYbHgVABUAFQAVABUAFwNEDwBkCYG7TK1wYD/CRWQXATRvwMmioAJhtkBQAFQAVABUAFQAVABUAs62l2voSWEABcHNGfzUA/rEBHHreh38Yd83uR2OqjZtmjuLWxR1o+3k8ccsZ3Dq7HVFs4xm7jsg3LfXLOL42hlrex7HTk3Dmc/D2tWHbMXJehHJugJZv8jfadoKZahPznQqWlyvAcg6wAG+mC9eJcHByEbfdt0vquuUBioUA/cBFElvwvBBh6GD7+CqWuyX4Aw+T1Y7U9UMX7V4e/XYeudIAQd/F2FgHKytlVGs9lPMDrLRL65Zh31wnRnOlhO0zK9J+stSBbSWwFQAVABUAFQAVAEcPALe+MrsH8Owf6Bbw5hjhsmilAJhtmNQDqACoAKgAqACoADh6ADj9n7MD4Px7FACzMcJIt1YAzDY8CoAKgAqACoAKgAqACoDZ1lJtfQksoACYzegKgAqACoAKgAqACoCjB4BT/ym7B3DhD9UDmI0RRrq1AmC24VEAVABUAFQAVABUABw9AJz8oewAuPhHCoDZGGGkWysAZhseBUAFQAVABUAFQAXA0QPA8R/MDoDLf6wAmI0RRrq1AmC24VEAVABUAFQAVABUAFQAzLaWautLYAEFwGxGVwBUAFQAVABUAFQAHDkAfO7YyzN7AD+68l71AGZjhJFurQCYbXgUABUAFQAVABUAFQBHDwAbPwDXypAJJBngo6vvUwDMxggj3VoBMNvwKAAqACoAKgAqACoAKgBmW0u19SWwgAJgNqMrACoAKgAqACoAKgCOHgDWvz+7B3Dt/eoBzMYII91aATDb8CgAKgAqACoAKgAqAI4eAFa/LzsAtv6XAmA2Rhjp1gqA2YZHAVABUAFQAVABUAFQATDbWqqtL4EFFACzGV0BUAFQAVABUAFQAXD0ALDyH7N7ANt/qh7AbIww0q0VALMNjwKgAqACoAKgAqAC4MgB4HNKL8sMgB/r/rkCYDZGGOnWCoDZhkcBUAFQAVABUAFQAVABMNtaqq0vgQUUALMZXQFQAVABUAFQAVABcPQAsPjS7B7A3gfUA5iNEUa6tQJgtuFRAFQAVABUAFQAVAAcPQDMvyQ7APb/QgEwGyOMdGsFwGzDowCoAKgAqACoAKgAOHoAmHsxXMvb9AoXJgE+NvhLBcBNW3D0GyoAAt8J4NcB2AB+GcB7LmDYFAAVABUAFQAVABUAFQAvYOHUqqNhgW90AHQB3AXg2QDWAHwJwNMALG9weBQAFQAVABUAFQAVAEcOAJ/tviizB/Dj4V+pB3CDMHA5VvtGB8CbAPwUgBemg/dbAG4B8GcbHEwFQAVABUAFQAVABcDRA0Dne7IDYPQ3CoAbhIHLsdrlDoA3pwB3PYCZFOQ++JCBeHVaZyuA2wC8FsDn0zovAvAsAK9JfyYMJgB+bYODqQCoAKgAqACoAKgAqAC4wUVTq42OBS53AHwegKcD+DKAvz4PAL4UwPsAvCr17L0ewIsBHAIwn/77mQ8BwDiNCdzIKCkAKgAqACoAKgAqAI4cAD7LemFmD+Ankr9VD+BGSOAyrXO5A+C5Zqfnjlu553oAuZ37hXMAjwc9TgJ4N4B3ATjfFjC9g5L/5jwlD4B/hqUK4NS3/vXLce/cXtQnO7hhy3HctrQNnX4e107P4raz2xDFFm7acUzaLA/KONlsoJrzcWJ2As5CDu6eNmw7Qc6LUPIGaPfNV/B3WytNLHQrWFkuAys5wALcrV24Toz9E0u444EdUtctDVAohOgHDhBbcL0IYWhj29gaVnol+AMXE5Wu1O1HLtq9HAadPLziAGHfRWOsi9WVEio1H6XcAKud4vpNsh/8vtZqETNbVqX9RLED20rYHdx7aovULVYGGPQdbBtfw77aktxr3esiSFwcXpmCgwQHxhak7pfP7MCu8RXUc32EiY0wtlFwQty1sAVTlRZyToSlXtnYbK6G3TvnMVNu4QvHd2HLeBOeHaE1KKDgBlhul1Ar9qXuvsYSTrQaWGyV8YJ9t+MTZw+i2csjn4vQ7XmolAY4mPbhZKuBnBOi2S+i13exvbGGY/MTsN0YjZKPQezI98gbsNDDieUx7BhbxanlhoxNFNqoVX10fQ9xYiGJOL2AUmkg1xvMl+CO+4gjG41GF61OHtVyH72+h4lKB2eX+f8HIEks1Gs9LC9WUaj42D2+ImPmOhHOzI6jPtHB2nLJzAknlv5FgYN92xYw26wjiiyMp2PbGeQQx6YfjhMjCB1cNTmPuxem4bkRnr71GO5c3YITZyZRqvtiaxY/9Iwtu2VcOzWLIHZxslXHSqeIG7Yfx1cXt6Oa96Vu3gmx0KnIfRyaXsDx1TGZX5aVYNDKA76D513/Van74XuvRrXeQ4P2m53E/h1zOLVi7BdGNvZMPBhue3KlgZ1jq+iHLtpBHq12AXFsoVLpY39jCa0gh7k2Hzn2IQLvtXumDFRDILFQbXTR7eSxb+sCji2Ow7L5SgD+T3tnAmRHVYXhn9kyYRJCSAgiIBoVQRYFFxBEyw3FHS3csBS0QIUSSrRccN9QwL1wwV1QS0FFUVFBXEFxX9hcQGWJJIaE7DOZLdb35lxsm/fmzUzeTHe/998qisxMv+57vnu739/n3HNuT/c2bR3s1dLFG7Vq9SL19o+ot3e8Nn+7usZrcxvbaeu27KgtG7kvRjQ23K2eeaMaHeqpjVHf/Iljhtb3T/Rh0ZDGhntq82D+gq2188zvHdH9d16tX9y0XF2r5mnxfmtqx9751yU68vBrtXJwJ/1r7WIND/Zqr93WatWGhVo8MFi7X359695avuyOu+y75uZ7ar+9Vtb6uXrLQO3ZALuRtf3qWzJYm6M05vfC/mH19oxq5R2L7pojw6t3VP+yzdpn1zt0w6pltWOH18/TPstvr82v9Zvm1/rOnGIeL+7fooHeEd22cVHtWMZ3/ryR2v8HVw7Univ77n+rVm1eqPXr5qt/YEQDfcO1YzcO9Wlo87zaMd3zRjU+2qWlu2zSpq19Gh7q1cCCIQ0OTWSkjt82oG3LhrTDyn6NLR3RDt3j6umbuM9GBntrnx/b0Ff7udZGJ76munfZWjvvttEuqXubunvHJu7DkYn5zhgxB3v6R2vPpd122qh1Q/Nrc2XNjUs0vmikNq41Dpv6tPOyTXfd9yPj3Roe7dGadQvU1TOm4fX9Glg68bxc2D+kvXe6U39YsYd2XbRJK25doh3GeRBvk4a6tOzea2v3Pw2m2LDTLpvV3bVNGzb2155Xo2PdWrN+QOODW3XLKedwKJA3/M/Ilv6r5ph4pJ6sHm1HFrBGdKUune2+ttRwn2x6BNpZAPIE4Q4mzJsVhV+QtLOkZ/DdIOmGCAOnJBBE4cRT++7tbZLeOj3EPtoETMAETMAE/o8Ab+4rZokJbyj/lMSyp+1tKyXdh/ee7T2RP18+Au0sAO8ZNxiC7pcZ9GdLIux7aPzu6bHmj9dI/vbJSYYp7wHk0F2mkTU8WzOg5omUxENlwqXTHq1d7WJ0bFs156jHzeO2vQSYQ/+O9ebbe65Gn0cEZtyoM74MLl6LvxnjK/cHO1EA4n8/UtJh5R6aafWu5vKf5bDCtDrUooPb1S7w2LYWTZI5Po3HbY6Bt+hy7TxuLULk03QagXYWgFMJAbfLeLfrw61d7bIArO6d5zlZzbFr53Gr5oi414UTaGcBCFySQEjqoPQLjTDvLZLOjSSQwgegRR1o14dbu9plAdiiiV/AaTwnC4Degku287i1AI9P0YkEqi4AF0i6XwzcHySdLunHsSYPoZfKwJwUQpAyMM+RtK+kVW004KxNfIOk95Dka7sqQaBdxwz4tq0SU/BunfS4VXPc3GsTmBGBqgtAijgj+PKNTN/j45cUeabAMxlRf5R0angGZwTMHzIBEzABEzABEzCBqhOougCsOn/33wRMwARMwARMwATmnIAF4Jwj9wVNwARMwARMwARMoFgCFoDF8vfVTcAETMAETMAETGDOCVgAzjlyX9AETMAETMAETMAEiiVgAVgs/+le/Y2SniLpwWxnGVva5c8xsQHq/7fnS/pK5lckz3xA0v6xN/K7JH1+up1p8fFTse1ekj4u6TGSNkki2Yfs59GS25ZHxcbQe+d+iR3sT53aQZI+KulhkthAmf2r2ammCu2UTOLVn6IME+WYqtTqbfv416gggB3stPB+Sc+LrOcfSDq5pNUFHhXj8RBJu9fZM53vgbdLOjGeKVdJeoWkv2cGjB2PmINPYztfSV+XdFrch0WOazPbeK69ONdBxupJFbCtSK6+dgcQsACs1iDzkF4XW769dBIBeIKk72dM4zNpOx/2dbxW0ickfVrS4yR9KIQlD8aiWjPbuiOLm70pyermi+x8SZ+SdEZ0uqy21ROAn4m+p7+xhd/m+IGaZX+T9MMo7XOgpM9KoozRZFsVFjV22eum0ksvj2x7+nyspAdI+k8ZOjjFPiAA2Uf88ZnjedG4I37mRYSXMaoNsAsPtUURRkdM8fxzedjR0a/fh3A7Jrc/+uviRQpb/iHpnZLgFsR4AAAMs0lEQVSYcw/MPDe+F/fcyyT1SvqcpN9IesFcGlLnWs1sQwDuJolnYmqUyroz83NZbSsYrS/f7gQsAKs5wjyoEW071+k+HsD8Az572FnxxXVA5pd4BzlX9q24KDKNbONB/x1J7PGcajgiMrBn1/CIlt22xBQPIOPHf/Ua3pd3R+kiPL00vIPPzHigihqfZtel+DrCgPJLNIqv3xreo6yHs9l5iv47AhDeeNvzbVF4ZRE/X4s/Ulv0BkmPkHR10Z2f5Pr55wPfAexLizfzffE57OMe417k2bCfpOvDG/3bOIZnxaXxMsrny9DqPfsQgDzbGMt6rSq2lYGv+9BmBCwAqzmgzQQgD2SKuvI2j6ePt/UUGv6ZJDwBeGZS4+0YMcKDv+jWyLZ3SHp67gsZjx82HiKJQuBlty2xRQASQsSTQsHyL0v6YCaUjWcTL2D2S4uw948kEYrLei+KHq/s9dtp+0UEIJ5mvHt4z38ZXjLG67GSrpC0ODzyicHNcR8xlmVteZG0XNJNkg4OD3vq90/jZ8K8LwmBiL2p9QQXvLsXl8TYRgKQ+4gXKe4b7qE3SVoTfa6KbSVB7G60EwELwGqO5mQC8M3xkNsi6ahY2/NaSR8JUwktIgjZNSS1J0v6rqQdJQ0WjKSRbYQ+WTf3xEz/6C9hU/pPGKfstqWus2MNInytpMNjLBgTfk+7TNI/JRFuS41w3HURlsPTVMaGd3ZF2IRgSo21i4+WdGgZO92gT3ic2WmIdX8sN3irpD0k4TlnHRzjxUtWtrHOkcL0hFTL2vIiifnHmj/G7vZMpy+Ml0ZC+iyxYB0dYfxsI6QPF8LhZWj1BCBrNHkWcj/dV9KZsW4RT+1YhWwrA1/3oc0IWAAWP6CExZp9YRCm+Eumq5MJwLxFeM7w8O0Vf6gnkljLRHh1fmbNTyvItNK2yQQgX9aseZxL2/J8ZmJrOgdeiPNCcLA+qZ4AJGGHtZv5udCKcWrVORoJwHMkHSnpsFZdqIDzEEbEw4dI5yWpngAk9I1n8PUF9G+ql5yqALwoBBICqpEAJDmJF06iDGVozZa/0Mfk8WRtJ2NVFdvKwNd9aDMCFoDFDyjr15Y06QZhzrQWjEOnIwDz4m4uw6SttK3sIeCZ2JqGPYk71pHhcXIIuPj7sl4PEHgk5lzuELCqEgKuN44IV8LAvHQ5BFzOe829mgMCFoBzAHkWLjEdAUh5lVfH2jG6QqIEIVOy/FJjDRpry6qQBEI4LmWTniQJ79IySXjOym5bo6lwXIi+pbFOKSWBkL04Eh8idPWsiiSBEAp9ZfSbJBDWzZElW6UkkPxYEQ7GDtYGUn4IEUF5Jcqh0PYJ8V7VJBASQEgEobH+lHssnwTyUEm/i2NYXoLXfc9IIpmFx9y0TzkVDyD9ZRxZF3hJJsGl7LZNG4Y/YALNCFgANiNUrr9TBw+hRjIEC9QJq9FujHUtrE1CDJGFiCB6QmT28XBnrQ6NxAnWkvGFTGkRFrSzPhBPYZFlYJrZlsrAkODCmsZ7SLogStlky8CU0bbsLEIgsBaOtWKUfuFnkgZYw5jqlZGMgyeQUDCilnVnjNWrKlQGBnGOECTZ6DkhXFP2drnuqvq94Z75doR9CW1TpoiMYNZiIv5Y98aLFCJpQ2Q5cybW1JWtIV7vF50iWYowNvOPNaiIIZagELZm/rFWjjIw1KHMl4HhhYTM+1QGhozgosvATGYb9vHcQ6RTPoo1gKxHXRgvwDwjadx7ZbStbPPI/WkzAhaA1RrQekVNsYAM0Z+EB4/kDh72jC3CkC8qauVRoyw1jqcQNA/42+KBX3Qh6Ga20XeSQLCHQtYkf+CJ4YsrWwi6jLZlZxkZyx8LQUQSAV+4CFnGI30hcfyDQqRTCJracxThRQxWoVEChhcURPofJZ0aNQGr0PfUR8qfUGSY5RkIvisl4U0nY5aWCkHjBWQcUyFohEbZGvcLgi/fuH8QsKkQNKKdtY7YSlFr1tSmxosnL43ZQtCMKwXZi2yT2YYn/ZuR4YxdvDzyUsW6xezLSFltK5Krr90BBCwAO2CQbaIJmIAJmIAJmIAJZAlYAHo+mIAJmIAJmIAJmECHEbAA7LABt7kmYAImYAImYAImYAHoOWACJmACJmACJmACHUbAArDDBtzmmoAJmIAJmIAJmIAFoOeACZiACZiACZiACXQYAQvADhtwm2sCJmACJmACJmACFoCeAyZgAiZgAiZgAibQYQQsADtswG2uCZiACZiACZiACVgAeg6YQHkJsK3Yz2Orqqdmupl2P1gsaV2u+/+S9KH4jz89OrbDYhszdq9YIekXkk6UNBy7qmR3iWDXkd/E9mDXZM7NTi3spsAeqqmx0we7Y7CN4B6xfyw7f3D9K+KgfH/SZ9lTl3PRL45hl5dGjR0rOJ5dUw6O3UWyx7ILDtdl2zlaOl9+X176xfXglxr73rJrCfssL5e0RdI/JF0UO+jcWd7p4Z6ZgAmYwMwJWADOnJ0/aQKzTeDTsdXWS2PrOMQbbaoCkK3+fhfbyJ0vaVDS/SU9O7Zn4+d0rgfEnrbse3tOHMeWgohEWl4A3lvSVSFA2W/1z7FH7BMlsaXYvhkxlhWkiVlWAO4qib2eaYhe9m5N/eF39BOxOx0ByN6u7EWMAE4tLwDZAoxtzxCBbA8GK+yFEXvc8rePzvYg+/wmYAImUAQBC8AiqPuaJtCcwICk2yWxF/DbQ2CdOU0BiEfsNEn3meRy9cQk+71eEvsRI+zqCcBLJR0UQo19mbMNT2HyTE7FA5j9bCNxi+CcjgBkD1j2gj1GEn2l5QXgJyS9MGxI4jrbF56P25oPlY8wARMwgeoRsACs3pi5x51B4CUhYBCAhH8RL3imECRT9QA+Lzx3R0n6WQNs+XMtkvSx8IDtJ+kvdQQgnjNCxYR/39NkOIoSgPBC+GIfYePxnADskrRG0lclvbwzppStNAETMIH/EbAA9GwwgXISILx6oaQPS+oJb+CxkljvNlUBSFiVMPLxklZKujrW5hEO3hBmp3MlLx6eRxoewGdk0GRDwA+X9KtYN3fxFATg7pJGcsf1Sbo+1uRl/9QqDyAC8EuSbpJ0iqQLcgKQEDFMTpf0wUwHCAMTfqZ9W9Lzyzk93CsTMAET2D4CFoDbx8+fNoHZIIAAuVbSnpJWxQXOjbVqL5qGAEx9I0HjsZIODdE2JgkRR4g5Ca5DIgHiMElnxO/5e2pZAch5EJOEVwm1TtbwAH4xPJHZ406V9KhZFoCIwLdIOiFE3dmZJJAkAF+VSZihf/eShDg9K9YlZpNeZmOsfU4TMAETKISABWAh2H1RE5iUAEKFzFSEWmrcq1sl4U27byQssC7u5tyZWHuHqPlcgyuQTPG3CPOSvFHP48a1WQeIQKsnAIsIAdPvtdHfn+ZsIwP4W5HtzJ+yYecFkm6U9F5J8EpZwM1CwPWynj1tTcAETKBtCFgAts1Q2pA2IUC49zZJiMDLcjbhbXtfhDYReoSEv5E5hjImhDwfGRm6jZCQ2MG5X9NAAO4YfSD7OIV484Loe5IOnMMkEGxZHWsOP5AxjAzef0t6WXDJC0B+JgRM1jEhXRilMjDnSTquQRKIBWCb3FA2wwRMoD4BC0DPDBMoFwFCjiQmLJO0Ptc1wpKEckkMQbyQ3EGWL/X69oqwJR+hlArJIogiPF6IOIQhdQAJISP8OA+etEZr7rjW0ZEJzLnygogEC+oJ4pUjzIqoRLw+IZJXSCCpJ8aSSdkyMFkzJ1vf+AZJrw6bCUEvifItB0ii5A3lYupds1fSDVGrkLWLSQDyeWxg3SM2/FYSayHJbsZjSBiekjluJmACJtB2BCwA225IbVDFCeClIjxJceV8S8kXD4ow7uslPTeKKJPQcHlk5pKhSyP7lSSHIyRR32+TpOvCi8h1aI0EF4KSgsh4yEhGqecRIxxNJjBZyvwbDx1JFCRVkKxST4wlm2YiAElqOTmKWBMGR3ySLAMHwr6p1cs8JpnjyxnRm44l6/l1sZ4RUUu28N8jpMwaQq7hZgImYAJtR8ACsO2G1AaZgAmYgAmYgAmYwOQELAA9Q0zABEzABEzABEygwwhYAHbYgNtcEzABEzABEzABE7AA9BwwARMwARMwARMwgQ4jYAHYYQNuc03ABEzABEzABEzAAtBzwARMwARMwARMwAQ6jIAFYIcNuM01ARMwARMwARMwAQtAzwETMAETMAETMAET6DACFoAdNuA21wRMwARMwARMwAQsAD0HTMAETMAETMAETKDDCFgAdtiA21wTMAETMAETMAETsAD0HDABEzABEzABEzCBDiNgAdhhA25zTcAETMAETMAETOC/HF5C8ytd9tIAAAAASUVORK5CYII=\" 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\" width=\"640\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
- },
- {
- "data": {
- "text/plain": [
- "(1, 23640.0)"
- ]
- },
- "execution_count": 42,
- "metadata": {},
- "output_type": "execute_result"
}
],
"source": [
+ "sample = roof_shade.sample(10000)\n",
+ "\n",
"plt.figure()\n",
- "svf_aspect_area.SVF_50cm.T.plot()\n",
- "plt.yscale('log')\n",
- "plt.ylim(bottom = 1)"
+ "plt.scatter(sample.NEIGUNG.values, sample.fully_shaded_ratio.values, s = 1)\n",
+ "# plt.xscale('log')\n",
+ "plt.show()"
]
},
{
"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": "3.6.1"
}
},
"nbformat": 4,
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diff --git a/Tilted_irradiance/Ssh_sigma_zenith.pdf b/Tilted_irradiance/Ssh_sigma_zenith.pdf
new file mode 100644
index 0000000..4c0a11b
Binary files /dev/null and b/Tilted_irradiance/Ssh_sigma_zenith.pdf differ
diff --git a/Tilted_irradiance/skyview_compare.ipynb b/Tilted_irradiance/skyview_compare.ipynb
index 273ca7c..a4d9aea 100644
--- a/Tilted_irradiance/skyview_compare.ipynb
+++ b/Tilted_irradiance/skyview_compare.ipynb
@@ -1,4982 +1,4984 @@
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/walch/miniconda3/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 pandas as pd\n",
"import xarray as xr\n",
"import numpy as np\n",
"from pvlib.tools import cosd\n",
"import scipy.stats as stats\n",
"\n",
"%matplotlib notebook\n",
"import matplotlib.pyplot as plt\n",
"\n",
"import calendar\n",
"\n",
"import os\n",
"import time\n",
"import util"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Compare 50cm vs 2m DOM"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"path = '/work/hyenergy/output/solar_potential/geographic_potential/tilted_irradiance/'\n",
"skyview_stats_2m = pd.read_csv( os.path.join(path, 'skyview_stats_GVA_2m.csv') ) # from 2m DOM\n",
"skyview_stats_50cm = pd.read_csv( os.path.join(path, 'skyview_stats_GVA_50cm.csv') )"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"fp = '/work/hyenergy/output/solar_potential/geographic_potential/available_area/PRED_available_area_unc_filled.csv'\n",
"ROOFS = pd.read_csv( fp, usecols = ['DF_UID', 'available_area'] )"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"suitable_roofs = ROOFS[ROOFS.available_area > 8].set_index('DF_UID')"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"skyview_CH = pd.read_csv( os.path.join(path, 'SVF_CH_replaced.csv') )"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"# take out those roofs which are not represented in the discretization of the roof surfaces\n",
"path = '/work/hyenergy/output/solar_potential/geographic_potential/available_area/shading_stats/CH_LV03'\n",
"roof_mask = pd.read_csv( os.path.join(path, 'CH_shading_all.csv'), usecols = ['DF_UID', 'non_null_cells'] )"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"skyview_CH = skyview_CH.merge( roof_mask, how = 'inner', on = 'DF_UID' ).set_index('DF_UID')"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>SVF</th>\n",
" <th>SVF_unbiased</th>\n",
" <th>non_null_cells</th>\n",
" </tr>\n",
" <tr>\n",
" <th>DF_UID</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>0.780161</td>\n",
" <td>0.708535</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>0.751102</td>\n",
" <td>0.679476</td>\n",
" <td>4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>0.656382</td>\n",
" <td>0.584756</td>\n",
" <td>15</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>0.790284</td>\n",
" <td>0.718658</td>\n",
" <td>9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>0.672486</td>\n",
" <td>0.600860</td>\n",
" <td>5</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" SVF SVF_unbiased non_null_cells\n",
"DF_UID \n",
"1 0.780161 0.708535 2\n",
"2 0.751102 0.679476 4\n",
"3 0.656382 0.584756 15\n",
"4 0.790284 0.718658 9\n",
"5 0.672486 0.600860 5"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"skyview_CH.head()"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"8589502"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(skyview_CH)"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [],
"source": [
"skyview_2m = skyview_stats_2m[['zone', 'mean', 'non_null_cells']].rename( {'zone' : 'DF_UID', \n",
" 'mean' : 'SVF_2m',\n",
" 'non_null_cells' : 'cells_2m'}, axis = 1)"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [],
"source": [
"skyview_50cm = skyview_stats_50cm[['zone', 'mean', 'non_null_cells']].rename( {'zone' : 'DF_UID', \n",
" 'mean' : 'SVF_50cm',\n",
" 'non_null_cells' : 'cells_50cm'}, \n",
" axis = 1)"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [],
"source": [
"skyview_GVA = skyview_2m.merge( skyview_50cm, on = 'DF_UID', how = 'inner' ).set_index('DF_UID')"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [],
"source": [
"skyview_GVA['bias'] = skyview_GVA.SVF_2m - skyview_GVA.SVF_50cm\n",
"skyview_GVA['corrected'] = skyview_GVA.SVF_2m - skyview_GVA['bias'].mean()\n",
"skyview_GVA['uncertainty'] = skyview_GVA['bias'].std()\n",
"\n",
"skyview_GVA['vmax'] = skyview_GVA['corrected'] + skyview_GVA['uncertainty']\n",
"skyview_GVA['vmin'] = skyview_GVA['corrected'] - skyview_GVA['uncertainty']"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [],
"source": [
"skyview_GVA = skyview_GVA.merge( skyview_CH, left_index = True, right_index = True, how = 'inner')"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"SVF_2m 0.735122\n",
"cells_2m 20.379479\n",
"SVF_50cm 0.661445\n",
"cells_50cm 325.516613\n",
"bias 0.073677\n",
"corrected 0.663496\n",
"uncertainty 0.120941\n",
"vmax 0.784437\n",
"vmin 0.542555\n",
"SVF 0.735153\n",
"SVF_unbiased 0.663527\n",
"non_null_cells 18.980333\n",
"dtype: float64"
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"skyview_GVA.mean()"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"206433"
]
},
"execution_count": 16,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(skyview_GVA)"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [],
"source": [
"skyview_GVA = skyview_GVA.merge(suitable_roofs, left_index = True, right_index = True, how = 'inner')"
]
},
+ {
+ "cell_type": "code",
+ "execution_count": 20,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "skyview_GVA.to_csv('/scratch/walch/svf_biases.csv')"
+ ]
+ },
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [],
"source": [
"skyview_CH = skyview_CH.merge(suitable_roofs, left_index = True, right_index = True, how = 'inner')"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [
{
"data": {
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" 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",
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" 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",
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" 'ui-button-icon-only');\n",
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" 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 overriden (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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\" width=\"640\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"Text(0.5,0,'Bias')"
]
},
"execution_count": 19,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"NBINS = 100\n",
"RANGE = (-0.5, 0.5)\n",
"\n",
"x = np.linspace(RANGE[0], RANGE[1], NBINS)\n",
"\n",
"plt.figure()\n",
"hist_bias = plt.hist( skyview_GVA.bias, density = True, bins = NBINS, range = RANGE, alpha = 0.7, edgecolor = 'C0' )\n",
"plt.plot(x, stats.norm.pdf(x, skyview_GVA.bias.mean(), skyview_GVA.bias.std()), c = 'C1')\n",
"\n",
"plt.xlabel('Bias')"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [],
"source": [
"hist_2m, bins, patches = plt.hist( skyview_GVA.SVF_2m, bins = 50, range = (0, 1), density = True)\n",
"hist_50cm, bins, patches = plt.hist( skyview_GVA.SVF_50cm, bins = 50, range = (0, 1), density = True)\n",
"hist_corr, bins, patches = plt.hist( skyview_GVA.corrected, bins = 50, range = (0, 1), density = True)\n",
"hist_max, bins, patches = plt.hist( skyview_GVA.vmax, bins = 50, range = (0, 1), density = True)\n",
"hist_min, bins, patches = plt.hist( skyview_GVA.vmin, bins = 50, range = (0, 1), density = True)\n",
"\n",
"hist_CH, bins, patches = plt.hist( skyview_CH.SVF, bins = 50, range = (0, 1), density = True)\n"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"50.0"
]
},
"execution_count": 21,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"hist_CH.sum()"
]
},
{
"cell_type": "code",
"execution_count": 22,
"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 overriden (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"
},
{
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\" width=\"640\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"x_vals = (bins[1:] + bins[:-1]) / 2\n",
"\n",
"plt.figure()\n",
"plt.hist(skyview_GVA.SVF_50cm, bins = 50, range = (0, 1), edgecolor = 'C0', facecolor = 'C0', alpha = 0.5, \n",
" label = '50cm resolution (GVA)', density = True)\n",
"plt.plot(x_vals, hist_2m, color = 'C0', lw = 1.5, marker = '.',\n",
" label = '2m resolution (GVA)')\n",
"plt.plot(x_vals, hist_CH, color = 'C1', lw = 1.5, marker = '.',\n",
" label = '2m resolution (CH)')\n",
"plt.hist(skyview_CH.SVF_unbiased, bins = 50, range = (0, 1), alpha = 0.4, edgecolor = 'C1', facecolor = 'C1', \n",
" label = 'Bias-corrected (CH)', density = True)\n",
"\n",
"\n",
"plt.xlabel('Sky view factor (SVF)')\n",
"plt.ylabel('Relative frequency')\n",
"plt.title('Histograms for bias correction of SVF ($A_{PV} > 8m^2$)')\n",
"plt.legend()\n",
"plt.tight_layout()\n",
"plt.show()\n",
"plt.savefig('SVF_bias_corr_avail.pdf')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Compute errors for SVF correction"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>SVF_2m</th>\n",
" <th>cells_2m</th>\n",
" <th>SVF_50cm</th>\n",
" <th>cells_50cm</th>\n",
" <th>bias</th>\n",
" <th>corrected</th>\n",
" <th>uncertainty</th>\n",
" <th>vmax</th>\n",
" <th>vmin</th>\n",
" <th>SVF</th>\n",
" <th>SVF_unbiased</th>\n",
" <th>non_null_cells</th>\n",
" </tr>\n",
" <tr>\n",
" <th>DF_UID</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>4879560</th>\n",
" <td>0.537930</td>\n",
" <td>20</td>\n",
" <td>0.497254</td>\n",
" <td>305</td>\n",
" <td>0.040677</td>\n",
" <td>0.466304</td>\n",
" <td>0.120941</td>\n",
" <td>0.587245</td>\n",
" <td>0.345363</td>\n",
" <td>0.537930</td>\n",
" <td>0.466304</td>\n",
" <td>20</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4879561</th>\n",
" <td>0.543964</td>\n",
" <td>9</td>\n",
" <td>0.474188</td>\n",
" <td>154</td>\n",
" <td>0.069776</td>\n",
" <td>0.472338</td>\n",
" <td>0.120941</td>\n",
" <td>0.593279</td>\n",
" <td>0.351397</td>\n",
" <td>0.543964</td>\n",
" <td>0.472338</td>\n",
" <td>5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4879562</th>\n",
" <td>0.601935</td>\n",
" <td>15</td>\n",
" <td>0.546454</td>\n",
" <td>232</td>\n",
" <td>0.055481</td>\n",
" <td>0.530309</td>\n",
" <td>0.120941</td>\n",
" <td>0.651250</td>\n",
" <td>0.409368</td>\n",
" <td>0.601935</td>\n",
" <td>0.530309</td>\n",
" <td>14</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4879563</th>\n",
" <td>0.568163</td>\n",
" <td>6</td>\n",
" <td>0.509543</td>\n",
" <td>100</td>\n",
" <td>0.058620</td>\n",
" <td>0.496537</td>\n",
" <td>0.120941</td>\n",
" <td>0.617478</td>\n",
" <td>0.375596</td>\n",
" <td>0.568163</td>\n",
" <td>0.496537</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4879564</th>\n",
" <td>0.508238</td>\n",
" <td>9</td>\n",
" <td>0.429219</td>\n",
" <td>142</td>\n",
" <td>0.079019</td>\n",
" <td>0.436612</td>\n",
" <td>0.120941</td>\n",
" <td>0.557553</td>\n",
" <td>0.315671</td>\n",
" <td>0.508238</td>\n",
" <td>0.436612</td>\n",
" <td>5</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" SVF_2m cells_2m SVF_50cm cells_50cm bias corrected \\\n",
"DF_UID \n",
"4879560 0.537930 20 0.497254 305 0.040677 0.466304 \n",
"4879561 0.543964 9 0.474188 154 0.069776 0.472338 \n",
"4879562 0.601935 15 0.546454 232 0.055481 0.530309 \n",
"4879563 0.568163 6 0.509543 100 0.058620 0.496537 \n",
"4879564 0.508238 9 0.429219 142 0.079019 0.436612 \n",
"\n",
" uncertainty vmax vmin SVF SVF_unbiased \\\n",
"DF_UID \n",
"4879560 0.120941 0.587245 0.345363 0.537930 0.466304 \n",
"4879561 0.120941 0.593279 0.351397 0.543964 0.472338 \n",
"4879562 0.120941 0.651250 0.409368 0.601935 0.530309 \n",
"4879563 0.120941 0.617478 0.375596 0.568163 0.496537 \n",
"4879564 0.120941 0.557553 0.315671 0.508238 0.436612 \n",
"\n",
" non_null_cells \n",
"DF_UID \n",
"4879560 20 \n",
"4879561 5 \n",
"4879562 14 \n",
"4879563 3 \n",
"4879564 5 "
]
},
"execution_count": 16,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"skyview_GVA.head()"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [],
"source": [
"from sklearn.metrics import mean_squared_error as mse\n",
"from sklearn.metrics import mean_absolute_error as mae\n",
"from sklearn.metrics import r2_score as r2"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [],
"source": [
"# ERROR MEASUREMENTS\n",
"error = {\n",
" 'MSE' : lambda y, t: mse(t,y),\n",
" 'RMSE': lambda y, t: np.sqrt(mse(t,y)),\n",
" 'MAE' : lambda y, t: mae(t,y),\n",
" 'MBE' : lambda y, t: np.mean(t - y),\n",
" 'R2' : lambda y, t: r2(t,y)\n",
"}\n",
"\n",
"def get_errors(true, pred, label = ''):\n",
" # create a pandas series with errors and print them\n",
" err_series = pd.Series(data = np.zeros(len(error)), index = error.keys())\n",
" for key, val in error.items():\n",
" print('%s %s: %f' %(label, key, val(pred, true)))\n",
" err_series[ key ] = val(pred, true)\n",
" \n",
" return err_series"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Baseline MSE: 0.019558\n",
"Baseline RMSE: 0.139848\n",
"Baseline MAE: 0.111971\n",
"Baseline MBE: -0.073677\n",
"Baseline R2: 0.245192\n"
]
}
],
"source": [
"_=get_errors(skyview_GVA.SVF_50cm, skyview_GVA.SVF_2m, 'Baseline')"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"MBE+ MSE: 0.014133\n",
"MBE+ RMSE: 0.118884\n",
"MBE+ MAE: 0.080840\n",
"MBE+ MBE: -0.002051\n",
"MBE+ R2: 0.454532\n"
]
}
],
"source": [
"_=get_errors(skyview_GVA.SVF_50cm, skyview_GVA.corrected, 'MBE+')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Compare different number of azimuth bins"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [],
"source": [
"path = '/scratch/walch/grassgis/scripts/executables/workspace_skyview'\n",
"skyview_stats_8 = pd.read_csv( os.path.join(path, 'skyview_8_stats.csv') )\n",
"skyview_stats_16 = pd.read_csv( os.path.join(path, 'skyview_16_stats.csv') )\n",
"skyview_stats_64 = pd.read_csv( os.path.join(path, 'skyview_64_stats.csv') )\n",
"skyview_stats_128 = pd.read_csv( os.path.join(path, 'skyview_128_stats.csv') )"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [],
"source": [
"skyview_8 = skyview_stats_8[['zone', 'mean']].rename( {'zone' : 'DF_UID', 'mean' : '8'}, \n",
" axis = 1)\n",
"skyview_16 = skyview_stats_16[['zone', 'mean']].rename( {'zone' : 'DF_UID', 'mean' : '16'}, \n",
" axis = 1)\n",
"\n",
"skyview_64 = skyview_stats_64[['zone', 'mean']].rename( {'zone' : 'DF_UID', 'mean' : '64'}, \n",
" axis = 1)\n",
"skyview_128 = skyview_stats_128[['zone', 'mean']].rename( {'zone' : 'DF_UID', 'mean' : '128'}, \n",
" axis = 1)"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [],
"source": [
"skyview_32 = skyview_stats_2m[['zone', 'mean']].rename( {'zone' : 'DF_UID', 'mean' : '32'}, \n",
" axis = 1)"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {},
"outputs": [],
"source": [
"SVF_dirs = skyview_8.merge( skyview_16, on = 'DF_UID', how = 'inner' )\n",
"SVF_dirs = SVF_dirs.merge( skyview_32, on = 'DF_UID', how = 'inner' ).set_index('DF_UID')\n",
"SVF_dirs = SVF_dirs.merge( skyview_64, on = 'DF_UID', how = 'inner' ).set_index('DF_UID')\n",
"SVF_dirs = SVF_dirs.merge( skyview_128, on = 'DF_UID', how = 'inner' ).set_index('DF_UID')"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"8 0.733922\n",
"16 0.725343\n",
"32 0.726699\n",
"64 0.724732\n",
"128 0.725023\n",
"dtype: float64"
]
},
"execution_count": 22,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"SVF_dirs.mean()"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"8 0.130039\n",
"16 0.131159\n",
"32 0.131273\n",
"64 0.131644\n",
"128 0.131637\n",
"dtype: float64"
]
},
"execution_count": 23,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"SVF_dirs.std()"
]
},
{
"cell_type": "code",
"execution_count": 24,
"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 overriden (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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\" width=\"640\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.figure()\n",
"plt.hist(SVF_dirs['8'], bins = 50, range = (0, 1), alpha = 0.3, \n",
" label = '8 bins', density = True)\n",
"plt.hist(SVF_dirs['16'], bins = 50, range = (0, 1), alpha = 0.3, \n",
" label = '16 bins', density = True)\n",
"plt.hist(SVF_dirs['32'], bins = 50, range = (0, 1), alpha = 0.3,\n",
" label = '32 bins', density = True)\n",
"plt.hist(SVF_dirs['64'], bins = 50, range = (0, 1), alpha = 0.3,\n",
" label = '64 bins', density = True)\n",
"plt.hist(SVF_dirs['128'], bins = 50, range = (0, 1), alpha = 0.3,\n",
" label = '128 bins', density = True)\n",
"\n",
"plt.xlabel('Sky view factor (SVF)')\n",
"plt.ylabel('Relative frequency')\n",
"\n",
"plt.legend()\n",
"plt.tight_layout()\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {},
"outputs": [],
"source": [
"SVF_delta = SVF_dirs.sub(SVF_dirs['32'], axis=0)"
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"8 0.007223\n",
"16 -0.001357\n",
"32 0.000000\n",
"64 -0.001967\n",
"128 -0.001676\n",
"dtype: float64"
]
},
"execution_count": 28,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"SVF_delta.mean()"
]
},
{
"cell_type": "code",
"execution_count": 29,
"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 overriden (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"
}
],
"source": [
"plt.figure()\n",
"plt.hist(SVF_delta['8'], bins = 100, range = (-0.1, 0.1), alpha = 0.3, \n",
" label = '8 bins', density = True)\n",
"plt.hist(SVF_delta['16'], bins = 100, range = (-0.1, 0.1), alpha = 0.3, \n",
" label = '16 bins', density = True)\n",
"#plt.hist(SVF_dirs['32'], bins = 50, range = (0, 1), alpha = 0.3,\n",
"# label = '32 bins', density = True)\n",
"plt.hist(SVF_delta['64'], bins = 100, range = (-0.1, 0.1), alpha = 0.3, \n",
" label = '64 bins', density = True)\n",
"plt.hist(SVF_delta['128'], bins = 100, range = (-0.1, 0.1), alpha = 0.3, \n",
" label = '128 bins', density = True)\n",
"\n",
"plt.xlabel('$\\Delta$ SVF')\n",
"plt.ylabel('Relative frequency')\n",
"\n",
"plt.legend()\n",
"plt.tight_layout()\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 31,
"metadata": {},
"outputs": [],
"source": [
"SVF_dirs_summary = pd.DataFrame(SVF_dirs.mean()).rename({0 : 'SVF_mean'}, axis = 1)\n",
"SVF_dirs_summary['SVF_std'] = SVF_dirs.std()\n",
"\n",
"# SVF_dirs_summary.index = SVF_dirs_summary.index.astype(int)"
]
},
{
"cell_type": "code",
"execution_count": 32,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>SVF_mean</th>\n",
" <th>SVF_std</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>0.733922</td>\n",
" <td>0.130039</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>0.725343</td>\n",
" <td>0.131159</td>\n",
" </tr>\n",
" <tr>\n",
" <th>32</th>\n",
" <td>0.726699</td>\n",
" <td>0.131273</td>\n",
" </tr>\n",
" <tr>\n",
" <th>64</th>\n",
" <td>0.724732</td>\n",
" <td>0.131644</td>\n",
" </tr>\n",
" <tr>\n",
" <th>128</th>\n",
" <td>0.725023</td>\n",
" <td>0.131637</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" SVF_mean SVF_std\n",
"8 0.733922 0.130039\n",
"16 0.725343 0.131159\n",
"32 0.726699 0.131273\n",
"64 0.724732 0.131644\n",
"128 0.725023 0.131637"
]
},
"execution_count": 32,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"SVF_dirs_summary"
]
},
{
"cell_type": "code",
"execution_count": 33,
"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 overriden (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",
"SVF_dirs.boxplot()\n",
"plt.xlabel('Number of aspect bins')\n",
"plt.ylabel('Sky view factor (SVF)')\n",
"plt.title('Distribution of SVF per number of aspect bins')\n",
"\n",
"plt.tight_layout()\n",
"plt.show()\n",
"plt.savefig('SVF_boxplot_bins.pdf')"
]
- },
- {
- "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": "3.6.1"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
diff --git a/Tilted_irradiance/skyview_factor.ipynb b/Tilted_irradiance/skyview_factor.ipynb
index 8d28612..22b11ca 100644
--- a/Tilted_irradiance/skyview_factor.ipynb
+++ b/Tilted_irradiance/skyview_factor.ipynb
@@ -1,9746 +1,12576 @@
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "/home/walch/miniconda3/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 pandas as pd\n",
"import xarray as xr\n",
"import numpy as np\n",
"from pvlib.tools import cosd\n",
"import scipy.stats as stats\n",
"\n",
+ "import pvlib.solarposition as pvlib\n",
+ "\n",
"%matplotlib notebook\n",
"import matplotlib.pyplot as plt\n",
"\n",
"import calendar\n",
"\n",
"import os\n",
"import time\n",
"import util"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"path = '/work/hyenergy/output/solar_potential/geographic_potential/tilted_irradiance/'\n",
"skyview_stats = pd.read_csv( os.path.join(path, 'skyview_stats.csv') ) # from 2m DOM\n",
"merged_stats = pd.read_csv( os.path.join(path, 'skyview_merged_stats.csv') )"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>zone</th>\n",
" <th>label</th>\n",
" <th>non_null_cells</th>\n",
" <th>null_cells</th>\n",
" <th>min</th>\n",
" <th>max</th>\n",
" <th>range</th>\n",
" <th>mean</th>\n",
" <th>mean_of_abs</th>\n",
" <th>stddev</th>\n",
" <th>variance</th>\n",
" <th>coeff_var</th>\n",
" <th>sum</th>\n",
" <th>sum_abs</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>4879560</td>\n",
" <td>NaN</td>\n",
" <td>20</td>\n",
" <td>0</td>\n",
" <td>0.448777</td>\n",
" <td>0.579490</td>\n",
" <td>0.130713</td>\n",
" <td>0.537930</td>\n",
" <td>0.537930</td>\n",
" <td>0.035747</td>\n",
" <td>0.001278</td>\n",
" <td>6.645317</td>\n",
" <td>10.758608</td>\n",
" <td>10.758608</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>4879561</td>\n",
" <td>NaN</td>\n",
" <td>9</td>\n",
" <td>0</td>\n",
" <td>0.437539</td>\n",
" <td>0.626010</td>\n",
" <td>0.188472</td>\n",
" <td>0.543964</td>\n",
" <td>0.543964</td>\n",
" <td>0.061913</td>\n",
" <td>0.003833</td>\n",
" <td>11.381847</td>\n",
" <td>4.895678</td>\n",
" <td>4.895678</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>4879562</td>\n",
" <td>NaN</td>\n",
" <td>15</td>\n",
" <td>0</td>\n",
" <td>0.525769</td>\n",
" <td>0.631051</td>\n",
" <td>0.105282</td>\n",
" <td>0.601935</td>\n",
" <td>0.601935</td>\n",
" <td>0.031992</td>\n",
" <td>0.001024</td>\n",
" <td>5.314931</td>\n",
" <td>9.029022</td>\n",
" <td>9.029022</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>4879563</td>\n",
" <td>NaN</td>\n",
" <td>6</td>\n",
" <td>0</td>\n",
" <td>0.502072</td>\n",
" <td>0.614747</td>\n",
" <td>0.112675</td>\n",
" <td>0.568163</td>\n",
" <td>0.568163</td>\n",
" <td>0.041745</td>\n",
" <td>0.001743</td>\n",
" <td>7.347364</td>\n",
" <td>3.408977</td>\n",
" <td>3.408977</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>4879564</td>\n",
" <td>NaN</td>\n",
" <td>9</td>\n",
" <td>0</td>\n",
" <td>0.430417</td>\n",
" <td>0.596541</td>\n",
" <td>0.166124</td>\n",
" <td>0.508238</td>\n",
" <td>0.508238</td>\n",
" <td>0.052079</td>\n",
" <td>0.002712</td>\n",
" <td>10.247045</td>\n",
" <td>4.574139</td>\n",
" <td>4.574139</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" zone label non_null_cells null_cells min max range \\\n",
"0 4879560 NaN 20 0 0.448777 0.579490 0.130713 \n",
"1 4879561 NaN 9 0 0.437539 0.626010 0.188472 \n",
"2 4879562 NaN 15 0 0.525769 0.631051 0.105282 \n",
"3 4879563 NaN 6 0 0.502072 0.614747 0.112675 \n",
"4 4879564 NaN 9 0 0.430417 0.596541 0.166124 \n",
"\n",
" mean mean_of_abs stddev variance coeff_var sum sum_abs \n",
"0 0.537930 0.537930 0.035747 0.001278 6.645317 10.758608 10.758608 \n",
"1 0.543964 0.543964 0.061913 0.003833 11.381847 4.895678 4.895678 \n",
"2 0.601935 0.601935 0.031992 0.001024 5.314931 9.029022 9.029022 \n",
"3 0.568163 0.568163 0.041745 0.001743 7.347364 3.408977 3.408977 \n",
"4 0.508238 0.508238 0.052079 0.002712 10.247045 4.574139 4.574139 "
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"skyview_stats.head()"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"212059"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(skyview_stats)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"text/plain": [
"zone 5.004933e+06\n",
"label NaN\n",
"non_null_cells 1.998777e+01\n",
"null_cells 0.000000e+00\n",
"min 6.067868e-01\n",
"max 8.168479e-01\n",
"range 2.100611e-01\n",
"mean 7.272358e-01\n",
"mean_of_abs 7.272358e-01\n",
"stddev 6.349468e-02\n",
"variance 5.760109e-03\n",
"coeff_var 9.160844e+00\n",
"sum 1.530654e+01\n",
"sum_abs 1.530654e+01\n",
"dtype: float64"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"skyview_stats.mean()"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
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"\n",
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" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>zone</th>\n",
" <th>label</th>\n",
" <th>non_null_cells</th>\n",
" <th>null_cells</th>\n",
" <th>min</th>\n",
" <th>max</th>\n",
" <th>range</th>\n",
" <th>mean</th>\n",
" <th>mean_of_abs</th>\n",
" <th>stddev</th>\n",
" <th>variance</th>\n",
" <th>coeff_var</th>\n",
" <th>sum</th>\n",
" <th>sum_abs</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>4817081</td>\n",
" <td>NaN</td>\n",
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" <td>0.0</td>\n",
" <td>406.0</td>\n",
" <td>406.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>4817082</td>\n",
" <td>NaN</td>\n",
" <td>432</td>\n",
" <td>0</td>\n",
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" <td>0.0</td>\n",
" <td>432.0</td>\n",
" <td>432.0</td>\n",
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" <tr>\n",
" <th>2</th>\n",
" <td>4817083</td>\n",
" <td>NaN</td>\n",
" <td>423</td>\n",
" <td>0</td>\n",
" <td>1.0</td>\n",
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" <td>1.0</td>\n",
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" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>423.0</td>\n",
" <td>423.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>4817084</td>\n",
" <td>NaN</td>\n",
" <td>419</td>\n",
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" <td>1.0</td>\n",
" <td>1.0</td>\n",
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" <td>419.0</td>\n",
" <td>419.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>4817085</td>\n",
" <td>NaN</td>\n",
" <td>535</td>\n",
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" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>535.0</td>\n",
" <td>535.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" zone label non_null_cells null_cells min max range mean \\\n",
"0 4817081 NaN 406 0 1.0 1.0 0.0 1.0 \n",
"1 4817082 NaN 432 0 1.0 1.0 0.0 1.0 \n",
"2 4817083 NaN 423 0 1.0 1.0 0.0 1.0 \n",
"3 4817084 NaN 419 0 1.0 1.0 0.0 1.0 \n",
"4 4817085 NaN 535 0 1.0 1.0 0.0 1.0 \n",
"\n",
" mean_of_abs stddev variance coeff_var sum sum_abs \n",
"0 1.0 0.0 0.0 0.0 406.0 406.0 \n",
"1 1.0 0.0 0.0 0.0 432.0 432.0 \n",
"2 1.0 0.0 0.0 0.0 423.0 423.0 \n",
"3 1.0 0.0 0.0 0.0 419.0 419.0 \n",
"4 1.0 0.0 0.0 0.0 535.0 535.0 "
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"merged_stats.head()"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"244075"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(merged_stats)"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"zone 4.998131e+06\n",
"label NaN\n",
"non_null_cells 2.903269e+02\n",
"null_cells 0.000000e+00\n",
"min 3.634644e-01\n",
"max 8.380713e-01\n",
"range 4.746069e-01\n",
"mean 6.776022e-01\n",
"mean_of_abs 6.776022e-01\n",
"stddev 8.572729e-02\n",
"variance 1.065515e-02\n",
"coeff_var 1.509738e+01\n",
"sum 2.070582e+02\n",
"sum_abs 2.070582e+02\n",
"dtype: float64"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"merged_stats.mean()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Convert skyview stats to suitable dataframe"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
"skyview_stats.rename(columns = {'zone' : 'DF_UID', 'mean' : 'SVF_2m', 'stddev' : 'std_2m'}, inplace = True)\n",
"skyview_2m = skyview_stats.set_index('DF_UID')[['SVF_2m', 'std_2m']]"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [],
"source": [
"merged_stats.rename(columns = {'zone' : 'DF_UID', 'mean' : 'SVF_50cm', 'stddev' : 'std_50cm'}, inplace = True)\n",
"skyview_50cm = merged_stats.set_index('DF_UID')[['SVF_50cm', 'std_50cm']]"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [],
"source": [
"skyview = skyview_2m.merge(skyview_50cm, left_index = True, right_index = True, how = 'inner')"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>SVF_2m</th>\n",
" <th>std_2m</th>\n",
" <th>SVF_50cm</th>\n",
" <th>std_50cm</th>\n",
" </tr>\n",
" <tr>\n",
" <th>DF_UID</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>4879560</th>\n",
" <td>0.537930</td>\n",
" <td>0.035747</td>\n",
" <td>0.497254</td>\n",
" <td>0.051997</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4879561</th>\n",
" <td>0.543964</td>\n",
" <td>0.061913</td>\n",
" <td>0.474188</td>\n",
" <td>0.106268</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4879562</th>\n",
" <td>0.601935</td>\n",
" <td>0.031992</td>\n",
" <td>0.546454</td>\n",
" <td>0.051656</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4879563</th>\n",
" <td>0.568163</td>\n",
" <td>0.041745</td>\n",
" <td>0.509543</td>\n",
" <td>0.042314</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4879564</th>\n",
" <td>0.508238</td>\n",
" <td>0.052079</td>\n",
" <td>0.429219</td>\n",
" <td>0.077267</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" SVF_2m std_2m SVF_50cm std_50cm\n",
"DF_UID \n",
"4879560 0.537930 0.035747 0.497254 0.051997\n",
"4879561 0.543964 0.061913 0.474188 0.106268\n",
"4879562 0.601935 0.031992 0.546454 0.051656\n",
"4879563 0.568163 0.041745 0.509543 0.042314\n",
"4879564 0.508238 0.052079 0.429219 0.077267"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"skyview.head()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Compute bias"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [],
"source": [
"skyview['bias'] = skyview.SVF_2m - skyview.SVF_50cm"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Mean bias of SVF: 7.16 percent\n",
"Std deviation of SVF: 12.09 percent\n"
]
}
],
"source": [
"print('Mean bias of SVF: %.2f percent' %(skyview['bias'].mean() * 100))\n",
"print('Std deviation of SVF: %.2f percent' %(skyview['bias'].std() * 100))"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"data": {
"application/javascript": [
"/* Put everything inside the global mpl namespace */\n",
"window.mpl = {};\n",
"\n",
"\n",
"mpl.get_websocket_type = function() {\n",
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" 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",
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" if (warnings) {\n",
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" 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",
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" this.message = undefined;\n",
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" this.rubberband_context = undefined;\n",
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"\n",
" this.image_mode = 'full';\n",
"\n",
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" 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",
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" this._init_toolbar(this);\n",
"\n",
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"\n",
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"\n",
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"\n",
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" // Full images could contain transparency (where diff images\n",
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" };\n",
"\n",
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"\n",
" this.ws.onmessage = this._make_on_message_function(this);\n",
"\n",
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"}\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",
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"\n",
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"\n",
"mpl.figure.prototype._init_canvas = function() {\n",
" var fig = this;\n",
"\n",
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"\n",
" canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
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"\n",
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" 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",
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"\n",
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"\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",
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" },\n",
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" },\n",
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"\n",
" rubberband.mousedown('button_press', mouse_event_fn);\n",
" rubberband.mouseup('button_release', mouse_event_fn);\n",
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"\n",
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"\n",
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" } else {\n",
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"\n",
" canvas_div.append(canvas);\n",
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"\n",
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"\n",
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" // 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",
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"\n",
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" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
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"\n",
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" var name = mpl.toolbar_items[toolbar_ind][0];\n",
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" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
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" // 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",
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"\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 overriden (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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"output_type": "display_data"
},
{
"data": {
"text/plain": [
"[<matplotlib.lines.Line2D at 0x7f34c51cce48>]"
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},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"plt.figure()\n",
"skyview.bias.hist(bins = 100, density = True)\n",
"x = np.linspace(-0.5, 0.5, 100)\n",
"plt.plot(x, stats.norm.pdf(x, skyview['bias'].mean(), skyview['bias'].std()))"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [],
"source": [
"# save mean and std deviation of random variable \"SVF bias\"\n",
"df=pd.DataFrame(data = [skyview['bias'].mean(), skyview['bias'].std()], columns = ['SVF'], index = ['mean', 'std']).T\n",
"df.to_csv('/work/hyenergy/output/solar_potential/uncertainty/SVF_RV_mean_std.csv')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Load shading data"
]
},
{
"cell_type": "code",
- "execution_count": 17,
+ "execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"path = '/work/hyenergy/output/solar_potential/geographic_potential/available_area/shading_stats'\n",
"shade_bias = pd.read_csv( os.path.join(path, 'GVA_bias_2m-50cm.csv') )"
]
},
{
"cell_type": "code",
- "execution_count": 18,
- "metadata": {},
+ "execution_count": 3,
+ "metadata": {
+ "scrolled": true
+ },
"outputs": [
{
"data": {
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" <th>mean_4_8h</th>\n",
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" DF_UID non_null_cells n_cells fully_shaded_ratio mean_12_13h \\\n",
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"[5 rows x 150 columns]"
]
},
- "execution_count": 18,
+ "execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"shade_bias.head()"
]
},
{
"cell_type": "code",
- "execution_count": 19,
+ "execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"shade_bias_mean = shade_bias.mean()\n",
"shade_bias_std = shade_bias.std()"
]
},
{
"cell_type": "code",
- "execution_count": 20,
+ "execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"rename_dict = {}\n",
"Ssh = pd.DataFrame(data = 0, columns = ['mean', 'std'], index = range(288))\n",
"\n",
"for col in shade_bias_mean.index:\n",
" name = col.split('_')\n",
" if name[0] == 'mean':\n",
" hour_idx = (int(name[1]) - 1) * 24 + int(name[2][:-1])\n",
" Ssh.loc[hour_idx,:] = [shade_bias_mean[col], shade_bias_std[col]]\n",
" rename_dict[col] = hour_idx\n",
"# shade_bias_mean\n",
"Ssh.sort_index(inplace = True)\n",
"Ssh.index.rename('hour_idx', inplace = True)"
]
},
{
"cell_type": "code",
- "execution_count": 21,
+ "execution_count": 6,
"metadata": {
"scrolled": false
},
"outputs": [],
"source": [
"shade_bias_hourly = shade_bias.set_index('DF_UID').rename(columns = rename_dict).iloc[:,4:].sort_index(axis = 1)\n",
"shade_bias_hourly['Csh'] = - shade_bias.fully_shaded_ratio.values # negative value to obtain bias for (1-Csh)"
]
},
{
"cell_type": "code",
- "execution_count": 22,
+ "execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"mean 0.027160\n",
"std 0.247525\n",
"dtype: float64"
]
},
- "execution_count": 22,
+ "execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"Ssh[Ssh['std'] > 0].mean()"
]
},
{
"cell_type": "code",
- "execution_count": 27,
+ "execution_count": 8,
"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 overriden (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=\"1200\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt_arr = Ssh[Ssh['std'] > 0]['std']\n",
"bias_arr = Ssh[Ssh['std'] > 0]['mean']\n",
"\n",
"# plt_arr[plt_arr == 0] = np.nan\n",
"\n",
"plt.figure(figsize = (12, 3))\n",
"ax = plt.subplot()\n",
"\n",
"# Ssh['mean'].plot()\n",
"plt_arr.plot(marker = 'x', markersize = 3, c = 'darkblue', label = '$\\sigma_{Ssh}$')\n",
"bias_arr.plot(marker = 'x', markersize = 3, c = 'orange', label = 'bias$_{Ssh}$')\n",
"\n",
"ax.set_xticks(list(range(12, 24*12, 24)))\n",
"ax.set_xticklabels(calendar.month_abbr[1:])\n",
"ax.set_ylabel('Fraction of roof surface')\n",
"ax.set_xlabel('')\n",
"ax.set_xlim((0, 12*24))\n",
"ax.yaxis.grid(linestyle = '--')\n",
"\n",
"plt.legend()\n",
"plt.tight_layout()\n",
"plt.show()\n",
- "plt.savefig('Ssh_temporal_var.png', dpi = 300)"
+ "# plt.savefig('Ssh_temporal_var.png', dpi = 300)"
]
},
{
"cell_type": "code",
"execution_count": 48,
"metadata": {},
"outputs": [],
"source": [
"# save to file\n",
"Ssh.to_csv('/work/hyenergy/output/solar_potential/uncertainty/Ssh_RV_mean_std.csv')"
]
},
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# COMPARE WITH SUN ZENITH"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 18,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "timestamps = pd.to_datetime( [('2001-%02d-15 %02d:00' %(np.floor(idx/24)+1, idx%24)) for idx in plt_arr.index] )"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 21,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "solpos = pvlib.get_solarposition( timestamps, latitude = 46.948, longitude = 7.447 )"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 25,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "solpos_plot = pd.Series(solpos.apparent_zenith.values, index = plt_arr.index)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 48,
+ "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 overriden (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=\"1200\">"
+ ],
+ "text/plain": [
+ "<IPython.core.display.HTML object>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "plt.figure(figsize = (12, 3))\n",
+ "ax = plt.subplot()\n",
+ "\n",
+ "# Ssh['mean'].plot()\n",
+ "plt_arr.plot(ax = ax, marker = 'x', markersize = 3, c = 'darkblue', label = '$\\sigma_{Ssh}$')\n",
+ "ax.plot([0, 287], [-1, -1], marker = 'x', markersize = 3, c = 'orange', label = 'Solar zenith' ) # dummy for legend\n",
+ "# bias_arr.plot(marker = 'x', markersize = 3, c = 'orange', label = 'bias$_{Ssh}$')\n",
+ "\n",
+ "ax.set_xticks(list(range(12, 24*12, 24)))\n",
+ "ax.set_xticklabels(calendar.month_abbr[1:])\n",
+ "ax.set_ylabel('$\\sigma_{Ssh}$ (fraction of roof surface)')\n",
+ "ax.set_xlabel('')\n",
+ "ax.set_xlim((0, 12*24))\n",
+ "ax.set_ylim((0, 0.4))\n",
+ "ax.yaxis.grid(linestyle = '--')\n",
+ "ax.legend()\n",
+ "\n",
+ "ax2 = ax.twinx()\n",
+ "ax.set_zorder(10)\n",
+ "ax.patch.set_visible(False)\n",
+ "\n",
+ "solpos_plot.plot(ax = ax2, marker = 'x', markersize = 3, c = 'orange', label = 'Solar zenith')\n",
+ "ax2.set_ylabel('Solar zenith angle (degrees)')\n",
+ "\n",
+ "plt.tight_layout()\n",
+ "plt.show()\n",
+ "plt.savefig('Ssh_sigma_zenith.pdf')"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# COMPARE WITH MEAN Ssh"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 50,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "path = '/work/hyenergy/output/solar_potential/geographic_potential/available_area/shading_stats'\n",
+ "shade = pd.read_csv( os.path.join(path, 'GVA_shading.csv') )"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 51,
+ "metadata": {
+ "scrolled": true
+ },
+ "outputs": [
+ {
+ "data": {
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+ "<p>5 rows × 150 columns</p>\n",
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+ ],
+ "text/plain": [
+ " DF_UID non_null_cells n_cells fully_shaded_ratio mean_12_13h \\\n",
+ "0 4817081 406 406 0.0 1.0 \n",
+ "1 4817082 432 432 0.0 1.0 \n",
+ "2 4817083 423 423 0.0 1.0 \n",
+ "3 4817084 419 419 0.0 1.0 \n",
+ "4 4817085 535 535 0.0 1.0 \n",
+ "\n",
+ " mean_1_16h mean_11_10h mean_7_15h mean_6_18h mean_6_10h ... \\\n",
+ "0 1.0 1.0 1.0 1.0 1.0 ... \n",
+ "1 1.0 1.0 1.0 1.0 1.0 ... \n",
+ "2 1.0 1.0 1.0 1.0 1.0 ... \n",
+ "3 1.0 1.0 1.0 1.0 1.0 ... \n",
+ "4 1.0 1.0 1.0 1.0 1.0 ... \n",
+ "\n",
+ " mean_11_12h mean_9_11h mean_5_6h mean_8_16h mean_9_9h mean_2_16h \\\n",
+ "0 1.0 1.0 1.0 1.0 1.0 1.0 \n",
+ "1 1.0 1.0 1.0 1.0 1.0 1.0 \n",
+ "2 1.0 1.0 1.0 1.0 1.0 1.0 \n",
+ "3 1.0 1.0 1.0 1.0 1.0 1.0 \n",
+ "4 1.0 1.0 1.0 1.0 1.0 1.0 \n",
+ "\n",
+ " mean_5_10h mean_4_8h mean_8_12h mean_12_12h \n",
+ "0 1.0 1.0 1.0 1.0 \n",
+ "1 1.0 1.0 1.0 1.0 \n",
+ "2 1.0 1.0 1.0 1.0 \n",
+ "3 1.0 1.0 1.0 1.0 \n",
+ "4 1.0 1.0 1.0 1.0 \n",
+ "\n",
+ "[5 rows x 150 columns]"
+ ]
+ },
+ "execution_count": 51,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "shade.head()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 52,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "shade_mean = shade.mean()\n",
+ "shade_std = shade.std()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 60,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "rename_dict = {}\n",
+ "Ssh_50cm = pd.DataFrame(data = 0, columns = ['mean', 'std'], index = range(288))\n",
+ "\n",
+ "for col in shade_mean.index:\n",
+ " name = col.split('_')\n",
+ " if name[0] == 'mean':\n",
+ " hour_idx = (int(name[1]) - 1) * 24 + int(name[2][:-1])\n",
+ " Ssh_50cm.loc[hour_idx,:] = [shade_mean[col], shade_std[col]]\n",
+ " rename_dict[col] = hour_idx\n",
+ "# shade_bias_mean\n",
+ "Ssh_50cm.sort_index(inplace = True)\n",
+ "Ssh_50cm.index.rename('hour_idx', inplace = True)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 61,
+ "metadata": {
+ "scrolled": false
+ },
+ "outputs": [],
+ "source": [
+ "shade_hourly = shade.set_index('DF_UID').rename(columns = rename_dict).iloc[:,4:].sort_index(axis = 1)\n",
+ "shade_hourly['Csh'] = - shade.fully_shaded_ratio.values # negative value to obtain bias for (1-Csh)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 63,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "mean 0.693302\n",
+ "std 0.288245\n",
+ "dtype: float64"
+ ]
+ },
+ "execution_count": 63,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "Ssh_50cm[Ssh_50cm['std'] > 0].mean()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 74,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "application/javascript": [
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+ " 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 overriden (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": [
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61JYuvSSfRWD5jVNHe1oBM4Mkarl/N2Ba/OlojOeEN+OhlJdTyHgLAQUgWUd8nGFwLKul+af/WEQWIuTy8l1kytAirzmoxT5DIZJPNoLXJkB3FxqmLhzscrdZaqysjUEPGywQLC+taqGeIJAZCXFkCHeGDyYiUtVsQcCPj774Of3GMOHV8Hy5f4RF1IvrxiFBu4Bwo2yqiZKC2TVhQZm+wTg/9uqXPoXOPY1kLMlUG2ZrWp1eD1cpL54EYyaNXPh6NF7cHd3U6oVO92F6tUXYe/e2xFqz5o1Of78swY6diwiPNTMKlQl87vHsfiYNpy6ktoLKNgLyNMJSJjy/SpP/wL4/gYU7A2UG2fWJV314EeP3qBEidm4f98oPBJAlizJ0bt3afTsWRLp0iV11ea7ZLv69NmJMWMYSCBL/fqemDWrHjJlUpYNltwwjRAcMKAipk8/G3cIQaqZ9zQF7q43dFuFHlsyBNQ5CgGnIqAILOvgN3OGZt3F4tDZ8Z/ACg0GFtO7HkDLx6b5zJhzA9+9AG4skaos+mxpJXFGqcgimWW8C21O3epYhUAkBDw8RiFMl54hR46U6NKlGLp29ULevGkUVjZGoHr1hdi715Dx9+tumTDhm3OSuDIOk+J1UxU2qKwyeAPudlJfXF8IHOgAZK4J1N5h4x47rjqNjNWuWKFCFkyeXBelS2d2XCM+gCudO/dIECzcc1m5simWLbuEDRuu4unTINF7b+9sGD++NsqUMQH3V1cB/ynA1ekGlSFDYEmmMkwwY9WYQ+nP/w2c/BHI0xHwnhfn0Q8PD0ezZquwZo1UYydK5I7g4DCkSpVIkLMsyZIlQLduxdGnT1n1jjbxjk+adAq9etHe1VAY/koi69NPi6JJk/xIksRO71cT2xiXDuvZcwumTDmjb3LXrsUwfXo984lrR3b60UG5UWOUTAluCYD2Rh6SjmyPupbdEFCRBXaD1mUqVgSWdbdCEVhR4xf/Cay3j4AVmWTv272z38KS9T+/IIkshhm+vW9AnH4f+bpJz6xE8Yto4MeHO/jcbZ448VTc2d2z7n3ilLMHDdqH4cONFA9Grfjoo5zo1s0LLVsWRLJkZvoqOaU3rn3RW7deoGCBKXgbFPHT0briaQxqvhVeuR4DTOighQampAWhA8rdzcCuekDaUkB9Q6ZUB1zZppd48iQQ6dNPfK/OsmUzo0eP4sJPKFUq3caDTa/84VRGL6Zq1RbiwIG7YFjbypXNROeDgkLwzz/HMWLEQbx5EyLsG7/4oiRGjKiCDBmSRQSIKgiGxVJtdW+TwQMyWU6gQE8gb3cgqQnkF2u9MhM43E2qE2tuiPM3YvLkU/jqq21CPUil1cSJdYRJfnBwKAoXTodRo47h1KmHop88pkWLAvjxx/KoWFHZDMR080uUmIWzZwP0nm3Zs6fAnTuv9KekTp0YbdoUwmefFUWVKtldm4hxgVE+dOgBDBlitLkKoFix9Pjmm9Lo1KkoUqRwoUgBztdP/QRcnSGRc08ChL01oOgCCqzBg+l59wJ9+pTDypX+yvPOyjHet+9OjB59XLwj+c3iPPbvvz9CmjRJrKxZnc712b59d/Dxx3nw+HEgkiZN4BSluyKwrBuLisCKGr/4T2C98AfWFQQSpATavLBuFJl6dliInOwzxJBqDS28yCMJkKOFJLOooHBjosm4XSIrKWrWzImxY2vByyuDmlja+NZ27LgOCxZcAJVX/Mj7+QXg5ct32LLlulBYsHD3v127wmLXn6oWs8ODbNzmuFpdt26bMHPmOdH8hB4heBcacce/VQtPDBpSHcWLZ3RsFwOOAFsqAslyAc1uOPbaNrxaly4bMXu2r75Gvi8uXXoqFv8sVK5wkfr55yVQuXI2NY7NxJ4T1xMnHmLt2itCGdSrVymMHh0xgcnt2y/Rv/9uLFwoTdfTpk0iwmW//LIkEoQEyO8XPateG42zrJ9ItRVD5c1VGd5eDexpBqSvCHwSNRFvZjedcjixffLkLaZNO4vAwBB8XDkEm6e8A4r7AGeH6316qNDaseMm/v77GDZuvKZvK0mXH38sh8aN84nskKoYECBmqVOPE9+1nTvbCAUss2bymzZ3rp/4oWG+Vjw9UwtVFn/y57dhqHY8uil58/6Ha9ee6wnBhAnd8e6dlHFzvtCli5d4PxQqZEIWXHvhQqL8yn/A6Z8NWb8ZvZAoPXB3A/DCD8jWCEhX1ukeWK1brxFKVq0UKZIOPXuWQo0aOcR8gESMKqYj0K/fLkH2Ry58tkuXzoRSpTLp/0syW81pTceWZOuwYQf1J9glgYsJzVEElgkgxXCIvd8oRQE0BUDzdM7KzwJ4al2THXJ2/CewHh8FNlcAuGPc7KZDQI1wkbcPgWvz5I4SMzBpJXluGV6YtwvAf8fRwgVn4sSj32t9vnxp0Lx5frRoUVDsOMeJjzoNQ0kqFu4LXBjtcoahX3+9Df/+e0osMBlupZWbN19gzhxfzJhxTkxUtVK0aHpBdHGXNXNmJ/iHnB4EvLkJ5OkABBx2OTyje+QYdlWy5ByxG/h5zUOY2mM5hq/8GHfT90XA46AIk9eWLQtg0CBvlCjhICLr5WVgbQGZBbWNYSEX114fdeoswfbtNwVJRfKKi1QqArhA/e+/Mzh//kmEcUxVFhep7ymE4lrHHdTen37ag5Ejj5g0cd2z5xZ6996BM2eYBwYokS8Q4zvORfVC/vL8ROnkpkv+LwFrlIYP9wLbqgPMxNnYsAB0ECQ2u0zkTZuhvd5hUJWfKRcBEAZ4DQFKDI5wPb5TqHqbN89PTx4UKJAWffuWxWefFVOqWR1a1649Q96800CS5fnz3kiaNKKamO/k3btvie8dSYRXrwwhZQyHJZZ8p5CMVQViQyB58jEICQmHn19Xgdnr18HImjWFUMz7+xuWKVRp8B3coIGnY4lVztGP9gKe6EiMNCWB8v8CGXX+noc/B65MA0oMB7wGOv22VqmyQKhaoyocd9Wr5wAV8SS0OC9QJHXMtyxXrimClNYUWFRYPn8uQ9wjlwwZkuoJLY3cKlgwrcI4GoiXLr2INm2Y240h7h4ICurjlOdHEVjWwW5vAovZAScB4PZxcd1PagD5rGu23c+O/wTWva3Azo+BNMWBBgYfALsjG/kClMjwA81d7RsLAHpnieIGZK4lFwg5mgMJ4pbha69eWzFp0ml9bwsVSovr118gKEgqKVhoGNy0aX40b15AfNj5InXJcqi7QbrOBrqAXF3DiTvTnp7/4caNF1i7tjkaNXr/1cLJPRejJLI4UaU6gCVBAnc0apRXqLLoI8L/t1sR4/w4cH2+nHSGGEI/XAnPmPrfqNEKrF9/FS2r3sWyr0YDTM7A7Ee68XD27CMRKsQMWVpheNCgQZVRsqQuXNleADPD4fIMsvZ2wQA9iOJgadVqtTDG//PP6ujXr0KEHnCsHzx4VyhcFi++IMLcWPjeIClOVRbN3+MEKe6kezN/vh86dZJherFOXN+9QsjleZg6fjsGzimOp69lGGG7Gjfx16+lkKNie9t8l575Ahu8gMTpgZYBTkLGNpd1cxslKiLREvy0NbA6l6HiJJmB3B2AvJ8BXIwbmeTfu/cKEyacFN/Mp09laBQXZVTAMOveh25UTmKqc+eNQnV5gF5/MRQSMatXXxFk1tatN8SGgzbeGzfOK8isevU8XXe+YZuhGGMtfI96ey8QY+zhw14R1CvEa9u2G2I8rlt3Ra/izpMnlRiPnC+kT2/H+Si/ZVRcXWY23XAgYSqgxAiZvdRY3XmyP3D+L7mxWOZvB6AW/SV8fQPg5TVLN86k512dOrmFuo2hWq9fR/ToSpMmMapVMxBaVBMpQsuA79u3IUiefKx4di9f7oEFC86Lzaxvvy2D06cf4eTJh+KHodjnzz9GaKgu1MDoFjEsjkShsVqrePEM75HfTh04Trp44cLTcfHiU736UimwnHQjrLysvQksBphHTgfGVbphFW9lB+x0erwksCjxp0SaPipzJ6zAwV0nUafCO/jMniYWnnxBDhlSxU6QmlBtSCBwe6Uksx5sN5yQMLVUq1CZla5czIa4JlzGEYc0brwC69ZdFR9x7jwRW/p8MGSC/gAkAjRDW7aHuysMneBC9JNP8iB5chfwX3hzGzjZD7ixyACZixmGahMnmtc+fvx1rDv23MHi4p9k1uHD9/T9YnYsKlmozCpcOL3thggNnpnm+sZ84MXF9+t1MTyj6jjfG9wJJGZcc37d8BLGt/8PKD5EqisipfCmqoKeZNzl0kI4SdKSyOJE1S6FoRaLdOGMLR4ASex0Hbs03lCpp+dUQXTv2NFGkFHRFY7jhQvPCzLr+PEH+sPy5k2N7t2Li/CXbNlS2Ka1QoHp8V4omG0qd2wttWotxs6dt/S72lFOXJ/7Af6TgKuzgRCp5gt4nQ4DN/TE1NVpxZhmKOfAgZWFUihxYiuNswPvASuzSZUr/SjjaAj9e2EZXzyBT43fo77B3Djz/EwSWsmy6Y959SpYhCjT+0VTzSZO7IHOnYuhb99yzg3ncuxQjXC1Hj02i0x5//tfBfzxR3WTW3L37iux+CWZRf8srZC4ad++sPjmlSv34YXUjxx5GD/9tFf4ry1fziCRqAuVbyRViT3DY1k41yB2VGWZlOTB1LsVHibnvqd/MiSDyPMpUPpPIGmW92vx/QM4PUBGK1SaaepV7HLc99/vwNixJ8CwQT+/bhHWE+/ehYqwbSoEd+26JQitly9lMgetcP5btWp2vUKLSUvsuqFoFxRsV+mBA3dQpcpCZM6cDPfufRVjeGBg4Dv4+j7WkVoPcOrUI5w+/VC/wWXcKm5u0YcwcgiiXQlZ28Fik5qYITdz5n/Fd1xTXzpr7asUWNbdUnsRWNwOoPykEICrAKZb10yHnx0vCazIE0wh64e7WJTyYaah7eDB3mCIldPVQK+uA1dnAddmRfQaYUpyqrKYkjyJg8KTLBh+X3yxRYT8/PRTBfz++/sTThoGcyFFMmv16st48OCN/ircOaFsnWQWSS2HpxsPDQIujgHODQdCIqZBF410IQWWNhGlgmrDhpZm3SmSX1wscXL/6FGg/lzucpPIYsiFRYbZNFy9uUSqrQIMcfag11v2JhBZg6g21IoL4RkVgMOGHcDgwQaz22Hd78Cn1higzBig8HfRYh4VkaW9Y+xCZC1NA7x7DjS6AKTipydulYCAN8iY8V/R6GfPegtS25Ry8uQDQWQxDEsjxbnz3bBhXqHKotrCqsXAiX7AhVGAW0IgnJ5GwySZFQdLyZKzcOZMAH7/vZrYzNFPXJmV9/YqwP9f4OFuQ88Y1kdvq7ydgURpQawZVrh/v8zCyZDwMWNqRqn8NBme0LfAYp2io9XTOJvQRAvlTpEiIfr1K4+wGysxpPYogN9sZmQUBH4oQM+vMN0ClmRdlrqSzMrRDEggVW4hIWHi2zhq1FEcOWJI/NKkST788EM5od74kDxfChWaLrzw1q1rjoYNLQtg4KKW37r5889HmG9wQUtVVseORZArVyqTh21cPrBhw+XYsOGaeHa/+65srF0hSbBo0QWMH39SEAVa4VyBRFarVgWtmzM/OSHDBR8fllXzmSk/USZEia4w8+nRnkCOpkD1VbH2wV4HUC2UPftkQfBt2NAC9evnjfFSfLb5Ht29+7YgtPbuvR1hM5cnp0yZyIjQygkmMbHqG2avztup3r/+OoL+/feI6IwVK6InWKO7PL9rly8/06u0pGLrQYR5rvG5OXOmfI/Uyp07Vbx8x44ffwLffrsD5cplxtGjn9rpDppWrSKwTMMpuqPsRWDxiSth9MPYnKM6Dyz6YK2zrtl2PzteElibNl1D/frLYwWP8v9ixTKIF5rG1JcsmdGyxXysV4vlAO5KPdgpd6ZuLQfCdDHgJAFyNJGqrKz1zDfOtbZdsZxfuvQcIe9dvryJ8LuKqfBjQ0k7J+wrV16O4NfEhSjDC/kh4+I/e/aU9m353U3A8e+Al7owsAzecjL19G9q/igAACAASURBVIQM9cxUU06qSlB94/xSvfoiMQGaOLE2evUqbVGDuEPIyeyMGWeFMk6TY1Nl0bp1IUFmxbpgItF3ew1wfR5wb4shQQEXaJlrA3k6Ajmby3AAKlpuLnUpA9aYgLtz5yVy5JgiDqHxddCmLcC9zXLXl7u/sRQShVR4LlliUGQxdHbw4MrgTqvNyuq8wOtrQN0DQMbKNqvWURVt3nwN9eotBz2ALl3qbvZl37x5J1RvJLO4y60VGrx27eolxrGnp5nZXp+eAnY1AgJ19bknAtpF7cNhdoOdcALDhviuXbq0MVoVXAiEMQOvh/T208J6+cxmbwoU7CXD2CMpohjKSRKARu/37kmCn/44Y8bUEvfOorI4ORD6BmhyBUgR8wLQovodcNKaNZfRtOkqMWc4ceIz+Y7b10Z+L+oYkYLBT+XfmJX40X5Dy+hfl6u1JLN4jps7iDXJQpoZs35N0Vm+fBZh+M5va3xf2D548BpZskwSG41PnnxjdRYyEghbt14Xvnqcb5CAYGH9nGuQzGLWXpII8bFwvpUu3QRBmpw48alZ3yCOx0OH7onwQr5rNdN3KmW4WUAfTiaTMbnwWTg9UCo+GS7IpEolhgIFv4k9DD6658vki9vmQCr8OnZcj1y5UuLq1c/NDgXk/eBcmWQWSa09e26/5/VEUpwKrRo1cooxSkIrYUIXtdywAazNm6/CqlWX8ddfNUTkhi0Kxy6/VySyqNLS/nvlCi2q3y/0LStVKmMEs3iS3XEd9woV5uHo0fsiqRZDMp1ZFIFlHfr2IrAit4rbi146QoteWN9b12y7nx0vCaxKleaLsCnNFLBKwavYfykvEiRwE2aWnp6p8PRpEJ49i3qBkj9/mveMAml66bDCjz3D2Zh2/An5UF1JkkXukJPMcgHlBXfrUqUaL3aRb9z4wqxdTX5kaBpMMmvFCv8Isn/2lhn0SGZR+l6woA2z47y6BpzoI3fHWehXUvovqXTjzPbUAMDvD6DQd0DZMQ675TFd6MmTQKFYoU/A9eufI3du2utZV+7ff425c6Xx+4ULBsNsjn2SAJzc6yeozKp5f7skrRj6aqxWY1Ygkla52wFJo0gPf7gHcGW69Lbw+sW6Rtv57B49NmH6dJl5kGXYp77wqTcLqLYSyNnM5KszOyRDCxnCqS1EbUpkbSonfcZqrAeyNzC5Xa5y4G+/HcIvv+wT4SkLFjSyqln0xWDYCzMaBgRIdSEfY4Y00/iduMca+nZnPbC/rdG45nQhPE4rsDJlmih2oU+e/AylPKYAZwcZcCaBQj+Z/J8DyXLEij/DYEaMOCjC3biQ5cYPw9wGDqyEFCnMXPyvygkwZPuTo0D6crFe2xUP+Pvvo/jxx91Cubp4cWPAFIUIky8wmQvJLJLPWmE2Uc9OkszSfdMvXnwisOaY1kgX+hJ9/31ZETZrNuauCGIUbVq27CJat14LbiKeOtXZpq1+8UIm36Ayi+SBVqgC5xyDIYbSy8iO/pA27VHslXHhXqbMXJFpkISgpX0jsUiV/eTJp3HnjvS05IYj52dUZdE6IlqVIDdmOebpYxUkk0Qgd3ug9KgIIbUx9ub+NmBHXbnB2JC6AOeUmjUXC/JpyBBvEcFhbSGhxTmwMaGl+eJpdSdPnhDMWkpDeBJaDIN1etSItR3Xnc81AEPc+J2i3x1VfvYstCMg3ppKi+QWNx01ctb42gznpo+WcQZE+mzFlXfvhQuPUaTITPGc3r3b0+neiorAsm5k25vAWgjgSwB05m4CgDERS61rskPOjncEFl+K3HUiObVqVTOc2TgT23c/Qe1a2eEzcaA+Zp0fIBpic0fE2CjQOEWz8R3gzlPkeGqmbba7kfCzs5LIuj4XCDIyvqViiGa4aUoAJUdESN/tkJED4NChu6hceQEyZUqG+/djjl+PrU3cHZHKLH+hHNAW/jyPoZ6cLDHUkF4MFoVUhLwB/EbKH6rb6HVDksprEJDIiBDi30/9JBcUlWfH1myH/J0eQB06rEexYulx7lxXm15T22mlKouhA1pWJ47rT2qlRdfal9DEcy4Shxpl3UnuKUkr/qQuHHN7TvwIXPgbKPKjJApduGi7gbVq5RKTxdDz4zGk0UKg9g4gc02zW05yhYos4qqNZ4YG8d1jlacIJ/Oc1FeeKxe/cay0aLFaFzZVAz/8YJtdV4YqM0SZqiwaOmuFHjiffVYUPXqUQJEiUXi+XRwPnPge4EIrIUMznwEp8svnP5LnWVyBmRP1NGnGi+a+ePGtVJgs4MI8XL732gbGrnqIorMkVugBs2kTc9ZAeI9x55xEpMnv5A0lgWdngJqbgawfxxVII7Tzq6+2isX8L79UwogRVQHf36UZNTeWKs2IuU98EVCNxUU9w68ZCqyV9BV0flntxLedHibMOksVjEbO0hS6Z8+S6N27jO2831zkLnz33Q6MG3dCkCLjx9e2W6uuX38ulIUksxiuqBUmm2F4ITdvihd3XdsGU4EZO/Y4vv9+p0jcYq7tQFTXoIKb71iOR2MSkPMS3jNmO46wwH96Gjj2tUF9mKqIDBc091vKzRpu2iTNDjQ3kI+m4mCL4y5deoJChWaI+T43EXPmtH0IKjcomSBGI7TopaX5kWl9IOFqTGhRoRnrBo0tALBDHZcvP0WBAtMFIffiRW+n9INZOv386Kv1QBeG+EisCSN7l7H73Bij8tg4Yof/dsXEG7/8she//XZY2CusW9fCDnfPvCoVgWUeXpGPtjeBxfR2DCUsCmAJAOrIabzU27pm2/3seEdgcdFYtOhM8VKk2XWKM92kR09pLqL7xgoo/VnIzBuIrQcii4OW4ca4Asp9mXWM8lOGCPFlxo+5XT4o9C65u16GGN7bIBdc+qJL3+1gz5YJE04InxSGlaxfb54vU0w3gpmaOFGi7H/HjptC4aUVyrclmVVASK1j3VXkgoGeL1RdvdYtbBkuU3YckKbY+824PBU48iWQvTFQY02s48URB3TqtF5MuM01tjW3bczqtGzuPsyYdhR7jhtk6+lSvEan6ufRrUNWlPy4NZChsukJBs6NAM74APl6ABWZbch1C8mmQYP2ixC06dPrScNpGk/XOwGksyxsk73lO2nEiEOCyNLeI/R8Y2hh2bJRmNbGBtG+tnLxW3YsUOjb2I52ub9rabN37WorQiVsXWhITGUhf2jurBW+L6jKYrhssiTu8p1wSRI9yNcdKNgb2FgKSJQOaPXY1s1yWH0nTjxA2bJzxcbCgwe95OaGsQLLiu8ECW8m7SCRdfWqJF+IKwkHk/zettUEHu4CvBcCedo5DBNbXqhOnSXYvv0mZs6sJ5IIiAQg50cBhX8AysjshCYVJnO5s1aSWfc2ScKUhZlFszWUZFa2BggMdhdhcH//fUxPuFAFR7KFPlleXnGfbGG3y5SZIxaRixc3Qps2sWyMmARwzAdxLNN3jErkhQsvRCALqAIjkcVEQEx8EhdLy5arhbqdPng//VTRpl0g0TJx4imBnZYllkovqrd79ciHgm//AfwnyHlqguSA12C5YehhpmKTraZqfk1ewCMZ0DYKr1Kb9uz9ypjcZdu2myLEt2DBtIKwd0QSKM4VqBCShJYMO9SIbK2VNNr39s6mV2hVqJBVmO/HhaJlHGX79++POeOoI/tD3JlYwzgEke8lLYw+cltIfEtSK7N+Lejpmdr+4oZoQGH7mSTn5s2XDnuXxnZ/FIEVG0Ix/93eBNZxANTD/wngFID5APi72F0TreuXtWfHOwKLZqj9+u0W5uCbN7eSviYkfipOl6boFhR6rjCzjfELjQa5mrzfuEr6VFAxFFmtZapRsUnN46L62lzg6gxDxjcnZHnr3HkD5szxEwtxe33Qnz17K/yaqMxiZkNtskScqK6gooUhALVr537/w/38AnD8W+D+VglrspxAmX+k0a5RavMImGt+CxmrAXX3mHQ77HnQoEH7hC9KYGAIunf3EmF9Nsf67UPgxmJJ9OrMVf3vZ8CsvZUwa19l3A0wTDqpHCLBw4k9vQNiLRcnAMd7AzlbAdVcW5TardsmYXY/fHgVkXkNi5MBoYE28+uhrJtEFhdLGpHVqFFeochiaIDJ5UhP4PIUmR2x+GCTT3OFAx8+fI3MmaXPDQ3cLUoeYGJHSHzTD5HhL8aeb1xodfzoGj6vuASl89wFSv0BFOkP8DlYyfvgBrQPibNZ8pYsuYC2bdeJhY1YGNCL7uJYqS7L9zmQNJvV3n789v3zzzH8+ush8U6mMuHLL0tg+PCqiDHT096WwK0VQLmJ0nsrDpbcuaeIxcG+fe2FGgKHustvcclfgWI/W9ajwAfAjYWSzHp60lAHyVSGZ3t+hrC05bFu/VXxPaAfolaYzZf+MbVr5zJdCWdZK+12FlWDadOOF0pVhrw41LIBAJUYGzZcFfOZdeuu6MOKhBL5kzwixJDhyMmSJbQbBras2Dg8a//+9vD25lTf9oXzM4a6kszy9zeo2T4ufhHffLwfDRoXh0f5v00KVY62dcHPgGU6z722bwEP05J+2Kq37yV3GVYFPj6O957knIGbYRqhxf8aJ+Vhfxn6xlA8LeSwUqVsphNaDs7C++WXWzB16hmRCOPPP2vY6nbZrR6G0lLYoIkbKHSgMs84WkS7OFXP3NCR4gZJbjkiaRjJ1ps3X2DmTF8xFrjB8euv1eyGiakVKwLLVKSiPs7eBFYPAF8DoHMsPbC4TXABgP23kazDxaEEFh8uKmb4UHE30R4pPbX04Xrjuq1VpYS52nIgp+2klFwc8eVlHH7If0eW/Gq3h4y8ManFfzMEw+TQi6ju89lhwFmjBawVO+uWDKNixWYK+e3atc2ty05l4sXpubVlyw1BZq1deyUC1lTDNWiQVyizGtTNiFQ3R0rD4vAQgIbMRfoBxQbI3cCYiov4LWhN/OKLzfjvP4PvwzBbTZ7oY3VrlSSt7tOMXbf7L8zY6+jN2EPdk2PLluuC2KHZpuYXwI8jsSaZxZC7aJVw1+YDBzsBWeoAtXREoon329GHaR4Xc+c2QKf2+YHFuolyy8dAYtv5sDEUi0QWTWE1IotSbxLB5ctH4SMWGYhTPwN+vwMFvwXKjXU0TFZdb+PGq2jQYIVIcX3+vGUbCpY0gEqsWbPOYdp/J3HtumEXv4xXInz+dXW0b18EqVO42e2eW9JmS8/5/ffD+PnnvSJ0cvZsnUeaPnPlRSBVzMk2zLnurVsvxIbR4sXMvAekS5dEhNV98UWJqN8Jhz8HrkwDSgwHvAaacymXOJbEXbJkY8Si5cGDr2T4yJ4W0huw/CSgQE/r2/nsnNygoudgoFHodsqCUpXl2QlHfBOJORR9nbR3CFVDJLLati0U5wyItfcCPRj9/Tmddl55/DhQJOKgQoRG5lrhorR164JCmcVkJ3a3j7ACAs0Dh2qc58972903KezJGWydMhQTlqbG+lOFER4uvcTo3darVyl061Y8ZmI7pr5SxbWQqqJwoPk9IKkZmz1WYKidqiUX4P8zsiMoqI8NarW+CpKU9C81JrSMs3zzCpynVayYVVgiUO1cuXJWJE0aiYR99xIIOAT4/qrLTOsYD8jixWfh3LkArFzZFM2aFbAeECfU8OpVsF7cwPUfyS2KHYKCdPNpozZpScO0iB0KIph4ZsSIanprG2s3p7UwbO2yNlsvWImtIrCsA9DeBBZbR/KKaU4Ys5AfAGdnsaeusq5f1p7tUAJLC9Gx18PFXbwMGSaKkLPLl3uI1N9Y7wU89wVqbQey1LIWrxjP5wfl9u2X75Fa9NqKqmTMmDSCSSBJLcZYxxoWp1XGHROqiwIOABmqSJLAQVnzGCOeOvU4MZG/d+8rh8vseY+ZxUXzzdLMRcUkI0EI6nj5o3m5c2jSIDsy1fkTSMlH0oTy+BiwubxT/RaMW0mD6h49NotfWT15EmbsWyVpxbDKCGbs5aSRfe620U4QGV67YMEFYZpNM0ytMKyToTRduhR7P/sbDbJ3NwLSlQPqGSUkMOFWOPoQyq6vX38hlRVlEwErMskmtGMGN9vL8kmAk8hieKi2CGU4LhVZDAWItvj9BZzqD5+tP+Ls0yr47beqWL7c3y4bAra+B9o3gOFP8+Y1tHX1Mdf35ATCdjbGzuPJ8N+e6lh5tCiCg8PFOczEyXdv+fSbMLXbIow4vxahCdLaXu3ogB53775JhE8OHeqNQYO8AT73i3SLlhaPgCQZbN4Khrj07r1dn4yDu8/jx9dC1aqRTOJP/g84/ycG7xoEv6dl0b9/eeGpZY/NLJt3EgATNBQrNkv4ipEYEBtQ2z6SC78qi4HcbWx32bBQ4MEOqcqiao3ZG7WS6SNBZl0LrYsxEy+Jd/Lr1+/EX1OmTChUGEuWNBGeUq6OLTc2aRWwd+8dsclHVbW1Czlb3QS+o+fN8xMhnPw2aCV37lRClcUfmyaZsVHDp049jS+/3IqaNXNix462Nqo1imrevQDODpUKT26CeSTFtTQ+mLS1IqbN8INmSk4ijaF39MqyyP9xWXog+AnQ0BdITacWx5VevbZi0qTT+gu6CikQGQGuP+jpRkJLI7Uih71xDlmhXDp8VDYYNQpfRuWsO5H87fFIliQUIXtIFbKdCpV79Crm+oH+uZkzx80w3ajgoVccNykjixuiSxpGo3VmBLd2XNE6oF69ZXpVnsikHRS7bY6dbnGEahWBZR3KtiKwaJrD1HWXrWuOy5ztUAKLvfbw+Fu/WHv4sBcyZkxmMzC0LDaFCqXDhQu63f2VOWRq9HrHgXTOSSXKLHKnT2vZLyRLTykwX1qRCxdSzHZhHFNNQ9Fo49qd5DG0Z88t1KixWIS03brF/AXOK1z8H9uxFyunzcfKPalx8Z6OeKCdiLubCPOgATwVQ3nyxJLB7+UVYG1+p/ktREaxWrWF2Lfvjj6jptkfOc4QHh+RpBUzW2qZgHghprEnaZWng1lZLTlR4seZxu8kX4w/zJwwc7eVYZ0i3ILqR6ogaYzdxN95gySWK5MQTZJktHgmb9/+EtlTPQDWFgCYsa3NS7u2m6EXzPI2b56ByKLxLoks7p6+V65MR/ihHig/zAfHL6US4Xi8zWaPDbv2KurKmzZdiTVrrmD06Joiq5rDyu21wP52kgTgAqjGegS8zSQWpgwxPH/ekIlT7PTDTajEtm5tLdSHrk4CGONYo8YiQe7Pn99QhPri7SO7k7G8Pp+hyZNPwcdnv/6dQKJy5MjqyJ49pWyi30gEH/sF5YcPxpnLTNosS1wYu2wnvRmbNVslFuHHj38qG7+hBMBkK1SYchPJHoUqCZJYJLMe7JRqFBaPpECO5niatiOmrE6LceNPvefV4urY2ntj0xa3g3OMfftuixDDpUsv4sWLYH21VFFwvrZsWRP8+edRp78rSAhyY482F1J5k8P2hCA/OJxPnPxB+kSy5GguMzcnzyX+l9Yb9H2k6TvnC1ohuUoiq1WrgqYrw9bkB15dAeruAzJWscUtNbmODh3WibB/PvPNmuV3+v01teGcp/lfeoLdm09g1/bz2H3wNe48iqi+SugRgvJ5b+OjkgG4+Tgd8qS+iuGtN2P4yjoIzVALQyYNMPVyZh3H0P769ZcLkQHFBvG98F4wtE9TaWn/ZSi6eI17uCEk5AeLYNDCBpct89ebz5O8Cg4Oc5nvqiKwLLq1+pNsRWBRCuELwJjW5DYyHej4hmY8h0zREzeKQwksbaKiLbjy5k2NS5e6m644igXTrl03YtYsX/TpUxb//KPLGrYkhVSaNLkiF+wuUhgOR/ks46i1DBhUtRh7PGlN5cuNGbSMU7pShpouXVLASR5DWipxkkIrVjR1HqrBT4EzgwD/f+UukkdSnE86ECvPVMeKVddw/PiDCG3jRFPLaFisWIb3QziDngDLddnK2gZZZjpqQzSKFp0hFtdjxtQUk2aTF9Iv/CVpxZ9XRnx74gzSU4UZBNNXNN2MPZo+MaSGoYUks7Ztu6H3A6DPEBUtZYsnwuQ67TBibROEFu5v+4m0jbBmZipPz//EhDow8Hu4Pz0ulXjJcgDNbtnoKjFXQyKLnkLc8dfI7Xr18ggii14W+nJrJf7oNx4DFuvCw4Q6z3V222LqZY4ck0Uq9r17272vzrEHylxoXRwnDdu56M9SF6i6NELmUU4umfmURBbDDIUHVqTi6iSAcXOzZ58szOsPH+4olXz0AlxfRGZZbG3wqbEH3KyTSs1fftkn8CT8TAXv41NJEJZv/WagxafHscPXEDLC0IrgYNfYKY4NE+27xzC9RYsay8MdvUn2+qZ8r5PMekGnCl1JmhVBWTtg4fHa6NbbV2DPudbbt31MJwpiA8BOf3dzk+b3cWEscO5GEp4hhps3Uz0oyURulpHocva7wu6E4HM/4Ng3OiKVG2H5gHLjgWz1oxwdWqZjElkk/zQbAmb2/vzzEvjyy5JiIzTGsqkC8OQohhybgTsvswkPKnpvmTwfsmLcTplyGj17bgUTr6xZ09yKmhxwKtW2T08Bj/YCj/bJH3o78usXDlx5kB67L+TDrstlscs3F24/fF9Z7uYWjvBwNwzrFQSfib/YpdE+PvuE+jxCmLtdruS6lUZ+Ttu0KYjFi5uY3eC+fXdi9GhabstSvXoO7N7dzmZhiWY3KIoTFIFlHYq2IrDuA2C6tf265hQBQG0p3xA0TOGXrBQAI+MC6xpu57MdSmBpHlhUZ5QuPUd8yAYMqIjffrPeZI4Th6xZJ+HhwzfYtq21MPVG2Dtgkc6A2sY+Nva4L/wYcxFrzNLz35Ezj2jXTp06EbJmCMWnZdfhpXshJC7U0WEEQbt2a4Xvya+/VsXPP1eyBxwx10myihkZTw8AggLksblaA6VH6XcA+SvuepBg4Y4kVQnG2STpt8GxSEKLCz3hacGwjUXyoz7EbzM8EqcUkyV+bBwxWYrc6ZIlZ4twvfXrWwiPrxgLjYBvLgauzROTPX1h9p4czSRplbWuzHJlh3LjxnMxqaRixTjcwg3hCIcb/te/PP4Y6ZpmnTt33kStWksE6UZSHfe3AzvqAKmLAQ1JajiuML00iSyqg7TFEY2ESWRx93rxlBVo1/Pqew1y9sIpNoSYXTRbtsliUf3ixbcRU67HdrIlf+dk/vj3gP9EeXb+L4ByE6Id/9qEMqFHKN6FGrJwWrM7akmzrTmHqofkyaUvGrPwik2ORweArVXkBg43chxUGNLAsMIDB+R0iP5Y/F75XnoHd/cwhIVJnxwWVx+7Wju5kOWC9pdfKgmvL1H0yR6uAik8HYSubkX65JgksmgAHyQzZ1I9MWjZJ/p21PMOwcb9PzmuXWZeifPCoUMPxrmxwAbTH4lG1Mxey2J1mL+Z2EV1eFBQCJIkGaNrjw03Nt69As4NBy78I71FPZIARX8GivaT/zah3L//WhDbkyef1meI5fuVczCqsrj4jtIXdscnwquz4X9jsWFXsENVx4MH78ewYQcF0TZ5cl0TeunAQ7g5T/8qElUP9wKPD0W0hmBT3BMD6SsAmaoBGavKLNKJ0oDEIrPtMfxbCzvUFEFcyjJz5dChVWxOfvN5p5KR1yYpWKZMJoetWxx4Z2K9FHHgmoNrViZB4Lxo+/Y2IuLCnLXGgAF78McfR1zm/RNVxxWBFetwiPEAWxFYgQAKcV2su9rvAEjJM7SQq951zJoOIK7kNncogWV8hxYuPI8OHdaLX61a1Uws0s15aI3r4ouAH8YpU86Ily19NZgNCW8DgBW6FNN28rGxbljGfjY/MtxNjxxPzZd/5ELviJUrmznEXDR//mm4cuUZtmxphbp188TeEVseEXBE7gBqJA1DgsqOj9Xj7NGjN8L8nWTW1q03IhgtMhUuQwGYKeTv6t3QZ+ZH2HOjKm7efivkvbaIUTcXAt77FCnGClXexYvdovba4KSSflY0/KUBvd6M3UOqTUhakbxKmMLcy1t8PElCTorow0M1kVb4gWZ475w59V3O92bmzLPo1m2zIXvpzeXAvlYyXIFhC04ofL5IZHGnXyOyPD1TifdBUFAYsqd7iVyFCgn1UNmymcGMhq7iHRMVXFooBp+xdu0KW/y+N+lW0JtlXzvg3kapqCr9J1D4hxgVh2KD5fZS+NQai9rjR2HHIUOId1whWM6de4TixWcjTZrEePq0t4Tqzjpgd2On+NDxHcZ3QK9e2/DqlfRoYimX/xHSepYT72GGalLR5MpjV2t37dpLhF/TrFn10LmzFxASCCzR2SC0ehZB2WfSOLXVQaHBwL1NwLXZGDLmFTzcw5At7XP0+K8NEiUMx81bvVzWZ6ZPnx0YM+aEUF8NHFhJbDLFhbGg3TpXyVKntadPn50YM8agyLD63UXpzq1lwPE+0o6DJXsTGS5oIWFLnyCG41KVtXu3IaNmsWLpBZHVqVPRiBsc+9phyZLzaDfhU73K21GqY3qQ0mPOahxt8axTTUVbBpJVJK2enjDM+bT6qbQlUZWpqvwv/UdNyNyobeC4u4UhTGfCnyVLcrF5ysyctnouhw49gCFDDujRcAlcbXFvLKyD694SJWbBz89gY2BqZndmT6WXGP0PEyRwF2H8roinIrAsHBy602xFYNHEpROAw7p6SXsyrNBH9/90Cf83DmQf1NB0GoHFBlSuPD9ClhdLH7xoJdMvL+t8bFICbaI2UrduWDnvbJog0lerdu3FCDVKeEEShlkB1627arcFIj290qeXqgb9Lr8joODH+/TPwJXp8moJUgIlhgIFvzFbVUQTesbhk8xav/5qBE+LqLriqMmS8bU1xQp3aRjWlujCcGmuWewn4FA3KRV/dTWiuS932kha5aIZe2ZH3JVor6E9lwncQxESZlC0GCb+zklHHVWDBw3ah+HDDxl2WanuO9wdyNYA+EgS7c4qV69KIovKNuOUzUNabUO5zhPRqPFKMBz7ypXPndVEk66rLf7tHmrz+hawu6H0CKN9vQAAIABJREFUJaJHkPc80zPQHvkKuDwZQ/b+itvvymD69HPCsLtv37JxYlG9apU/mjdfjXLlMuPoUZ1H09XZwKEuQNZPgJqbTLpXtj6I79u0accLIjaRRwiClozF0ZwnUKHCfEG2BQR8bTMrAVu33bi+3LmngCqF/fvbw9s7O/DmLrAqu3wvc5OMLL2ziwiDzygWnBUH98axq/Ql9ML06fWc3bIor3/48D1UqjQfTAZy44Zz/TQtAYjEN4lYKg2LF88gVN3OJOC6dNkolNBUmDNjoqUbwwKLFxeBY71l8heW5J5AuXFA9kaWQBXlOWfPPhIKlLlzffUWGrQg6NrVS2QwpEn+9ol9Uf+7THgXGjHkzdI1gzmNb9BgOTZuvIZp0z5B9+7FzTnVumP5sef8zjgckPcjckmWE8hYTUdYVZMej8wmbWYRGziv/eFTuivaT/0Gy/Z7CkJEK0w6VaFCFsyZ00DcL0vHFS1TypSZK6p1BcWimTDZ5XDj7La8QPr0SfDJJ56YN6+BCLWMDmvN95lZ2J88+UYosSIcy0Rfbx8AhXoDNxbLzTwHJfoyBkoRWNYNG1vNKiZRCQ+AaT1yA6Aen2ZLe3XN4+8oOYgrKRWcSmBxFyZx4tH6RRlNMFu2ND/FNzM+FC48Q9yCBAnc8O6dzgxPyyjHF3wzTTRn3UBypbM1goBZ94JDEuiVQlob7fVx//TT9cJwmgaMnTtbOUEyBVCGAvlPAs74AO90yjPPzkCpP2ySUpmSe+6qr1x5WcjbZQlH6WJJcdL3rb6F9sIzOgg0o3w9OXF2OHB20PuH0yCdpBV/UrlOOmItZNinaBMMX1QKd1J0x5RZcrfVGYRgTEPts882iJC933+vJqTzOP+PNKjN3QGoMt+UUWr3Y65de4b8+aeLhSmf+aDZA/Cy3mOkyzxLTDSvXfs89iQFdm9l9Bf46qutInTErhPXJ8el2ojGwkmyADXWAOnLm97r078Avr8BBXvjVeFRSJXKeZlWTW+04chRo46iX7/dQuG2cKFukXlhNHCiL5C7PVBlgSXVWn2O/lulmcu23oYB89cjfYaJYvOAhugWZSezumWmV2C8yHjw4CtkypQceHYO2FAcoLdgS0NmVtNrtcORRt+Jg/654T3kG3GRI0c6upzyle1aseISWrZcI8KjDxygnWzcK4cO3UXlygvAhSSTEyVNap8wfVOQoeLx0083oFatXCIkyaLC0LRzvwIXRkkrDoahFf0JKPo/IIEh+YJFdUdzEjdlSbyRHKGVhlby5UuNh/ef4eVrN2RIE4ocebII71ia09Ok3t5koWbjsHFjS9SrZ8cQYdpXPDtt8K6iwkozyDfGLLWXTmGlCwnUmebb5F4YhZvfr3AG9FM0tt3gNdzdgbAwy8O+GzdeITbY41LyGZtgG0Ml+s3eBDRzNyi/Y9vsq1t3qfCejRDSbnydyGuG4sOA4prext69MtSvCCzrsLYVgUXC5ySAVwAY9M2MhDSm0UZcBQBrAThX+mA6Vk4lsPSSVd0Lkc1u2NAT69a1NNlziJ4fNF9mHPF7L0SGVO2oC6QpDjTQiAnTwXH1IwVBEPYSPoXrY/iqj/Es50/45x8pHbenGar20ozt5WoT/B7ukeGCVFOwpC0tfWwyetukeuNKDIRgGIJD3PFRpUS4HZAMly8/E6m9aQBv78mScXtojN69u1FYG/+4gEom3a5Ywd4yiyAX6K6w8x/dHVlTQBjJDz+zEINGGsIFHE0IxjRgtGyPixY1Qtu2hYEzg4Fzw4ACXwHlKap1fjGQAB6gdHxYq83wmTUDVT7eK3b/Hb5DbCYkWkICbjJwkmbz+397NbC/gy7ToJdUzpk7uT//N3DyR0kGe89DsWIz4ef3GOvWNUfDhvnM7LHjD9c8mhiKJcLoWU77AL4jgAJfA+UnOL5R9BPkt8rDHT4DSmB4+2YIDXPDkMUr0bj5ZrGYGTWqBn74wQyi0Qm98PUNgJfXLFAd8uxZb+nVw+/TthpAyoJA4yjUEU5oJ7jrzsyzDJ9N7YVSfTvh9CUPl10wTphwAr1770DLlgWwbJkTE8JYca8YKpsnz1Shzlu5simaNXPeRtLvvx/Gzz/vFZuLs2ZFbawebVep+qElAb0D3+g2fbPWl6qrlPmtQMj0U0mYbN16XYQX8t1gXAZ1vY+sFTrhq6+2oW7d3NiypbXpFVt4ZMaME4UP7enTnUWGcJuVkDfyOdXCAQMOAiGRMh7TrzRdeSP/Km8gMTUUdirPzwPriwKJ0mL4+fXC240qKc43qlXLgb17tQ1IDwQFMTGK+aVkyVkiQ+agQZVF2JulSi7zr+y6Z+i/jz6V8csve4UFx/790jsyurUcLSZo5cLP0NWrMWxeLtDRH+6JgHakLBxfFIFlHea2IrDYCqqs6HGVBgBngyS0tEKnTGYltN6V3Lr+mnq2Uwks7aH9+eeKYvfq6FF65MuUoqZ6DnXvvkl47TDTkb9/d0ybdtbwQry5DNjXWspr6+4xFZO4dRw9kJbKDC7D/Xdj0BBp5sdi8wWirt7OnTcIE0YWu0mA39wBTvaT5rTiQumAkr8B+XoA7u+Ho9nipuk/Ih+NwvBxLxCapSHeJC2Nv/46iq+/LoUJE+yUIj2axmvmjPpru8huitlYG2UQWrYF8PV9LCaf3t7ZHEoIxtTunDmn4Pbtlzh0qCMqVswKHPsOuDQOKDoAKPWb2V22xwnGkxxBAgS/wZBpf2HQ6Jci/LF9+8JYsMB2oR227kOuXFNw69ZLLF3aWGTWtNnElYsuqoxIPHEviaFyVZcACVOZ34Wrs4BDXYGs9YCaG6G964YM8RYm+q5e6tRZgu3bjTya2OCjvaSC1WuQDLl2ZuG9WpwECAsGmt7EP1Me4IcfdqFhw7xYt66FM1sW67Xp2dOs2SrhN3fsmC48k6TpnmZA+krAJwYj8lgrs/cBRuP4bqGlQknBYs+NLUu7pH3nvv22DMaOpQtH3Cw//LBTbCA6+z2sKV0jkNimQErLjWPf6nwDGUeSGyg7VvpdOWmDjKrjAgWmy9Bjqo637sXJ1DNECBqJZPr8ieQ7dirGhvgMc06f3gr1GZMsaJkBH9K/6rhUtxkXfrMyVDHyrypvN8VblJAF3gdWZhWhZkMu7oFHAg99EiNGKdDsXSuWri8KFpwuFHYbNrRA/fqukxneTkPIomoj2+IMHeqNQYMizj9++mkPRo48Amaq3rixVdTXOT0I8B1u+JtSYFl0P5x9kv3ecBF7NgcAJTAyDZDrF6cSWMbwcAeLD+3gwdLcLzZihIs5Gr8z7Ivf1k8/LYrZsw1p5UUll6cBRz4HsjeWoSTxsXBBsCihMHIc4rsRJ88FihTPuXOnQpcuxexCEOTIMRl37ryyj2kgzWgvjpbZbihjZ8x2/i+BkiOAxOkdcwcPdQeuzgBKjMC8U82FHJ+7T3v2tHPM9XVXad16DZYtu4TRo2uKFPRiZ/3KNGmkytC2lAWcEs9uNgg7PpYeGpXn4o/FBTBgwF5h2qxPQ292hbY9gZPUpEnHiFBmfWjQwS7CEFmEqTJswtXKuqLAi/NA7Z0iLfZHHy0G05Lfu/dV1FmcXKD9BQpME2pGPkd8nmxSGF5MheblKbK6/D1lSnf399ODm3S922uAPU1l1qZPDmPcuBP47rsdwiB/7VrXJljYP0/PqSID6N697VC1qg5jmtkzO2mZMUDh70yCwa4HrcgKvL0P1D+FE9eyoGzZucJnjB4e3JF31RJleOaVmcDhbi7hlRcBNyNibfiRf/RZ8niMpQtPe90XjST+449q+N//KsrvHD3FGOrCTRsmJnGCb4u5/XWVMMJGjVYIX8+pUz/G55+XiL0bTETg9zvgN1ISy1RqFOkHFPsZSKBLUBB7LXY5wqA6BoKDgWGf+WHA9GkitDswMAR+fl1RpIj95oXXrz8XER6JE3sIH9IoMyRG1XNOJl5fNyKs9srvdeSSNJvcYBem6/Sv8rLbBq1JNyg0SG4wsLR6KrIVaoVrLs5HuQFZs2ZOkTHS3IiEgIA3yJhRKtod6p9rUudd5yBizeRNVCFynEcmxamI46YrI49WrGgqsnhGWZh44eIY+UwX+wVg9nYnvEuVAsu6seUoAsu6Vjr+bJchsOTE6oCewIptovX99zswduwJPWJRTsrOj5IqnjyfAt7kFuNpWZYeCH4CNPTFxftZhB8YP7jPn/dG4sQWLuSigYpEY5IkoxEcHAZf3y5YvtzfdkqKu5uB498CLy/JqzPdL8MF05Vx7I078SNw4W+gyI8449Ef9EBInZpZvb4xfQJjgxaXKjVbGPVHCF9aWxB46Q/U2SMnPHGh7GsD3FwqMkVuvt4Q9eotR8GCaXHxYneXaD13A7krmCxZArx69Z28x1RVcBFYfjJQwAWNhbdUAQIOANWWIyhTE6RNO0FMdM6e7QwvLxuGOdjwDqVOPU74HV240E1ko7S6iEyDbYB7zKPCTIOjgMJ9rFMLcGd8WzWAvnJN/HHgwB1UqbIQzMZEctCVC4nYZMnGCs8StpVtFsWIQIYnc9A4uawvBjz3A2rvQGiGGsiQYSKePQvC4cMdUaECd/9ds3z55RZMnXpGZMrTh2fqQ047Ad7SmNglyoPdwPaPgFSFMOTYdLHRxw2/2rVzoWrV7GYvPO3ZJ001OHduA5F9TpBW9HokiUXyykmqAXP77CphhGZ5Nt1eK+dcJFtYmLmYc65U5nvRmouXKcfrVcdfBGP4NyMQmjAjhixYAC3kf+bMeujSxcuUqiw6Zv/+O6hadSE8PVOLMK1oC/2rnp+ThJUWEqhlbDQ+KVURQzggSavkeaz7XlnUq1hOWpwMCA0Emlx9L8vklCmnwTB1+o/t2mX+hu769VfQqNFK8f3nPECVmBHo33+3iAChfQl9Ijk35TNBBfuSJReF5x43t/Xfo8jV0RN0UzmARGlzXQZRJ4CuCCzrQFcEVtT4uRSBxQeT4Q/79t2JNbV2v367MGrUMdGraNVapwcCvr8KQ14Rwx9fy5p8MltJ3f0Iz1AZWbJMEsx8hF14G/X9zp2XyJFjigjzfP36O9sQZK+uSZNhei+wJMkMlPoTYrFlQTYVq7tK89IzA4F83RFcegqSJx8rTLJv3PgCuXJZEJZkQYM4GU6ZcpxIjxthwb88IxAUADQ4C6Sx38TNgiZHf8rhL4Ar/wElhuNhpj7InJm5MIAXL74VygtnF/ptfPzxMhQtmh6+vl1lc7bVBB7uArwXAnnMn6jZvU+7GgN31wEV/gPy98AnnyzDli3XMWZMTXz3XVm7X97cC9AAmyo3FhLBadLodnnNrUg7/vUNYFcjuWjwSAZ4zwdyNrO0NsN5Rh4gaPUE9Fjkc0hS6M6dnsiWLYX117BTDVoyE4bTv3z5rYFs31hWpluvsR7IHkmlbKe2xFjt1mpyoVd1GZCrpQjLY3ieXoHjjDaZcE0ti+bs2fVFdjdR9Kb/3wLlXEh4//Q0sLGU/Ja2uA/NF6ljxyKYN48uF65TNG88Go7TeFyQmyQ5tZK5FpCng8wkmiit6zQ8ipa4QhhhunQT8PTpW5w71wXFimWIGi/OuRguyG8IS7IcUqFJjJ0ULhjjjX16BthYEkiSCWjxANr8v2fPkpg0qa7dxsTSpRfRps1aQfru3dteXocKQYaqZ6kDnBsKvLoBBD0yJBjSWuOWAEhXzhAOyNDAJNHcD7v1wIKKV2YHAu8C9Y6/t3msbfZxzcXveLJk5iUrGDhwn8iozOiQmTPN9GezoCtx/RQq1qgAfPXqHZYvb4IWLQqiZ88tmDLF4Okco6KWooBd9YA0JYAGMoGOM4oisKxDXRFYUePnUgSW+DaceSQUL3xB3r//FdKmfX+hQzKBKbn5UDPkgP8f5UN89BvAfyLg5QOUGGbdCHLlsyMtUFq2XI0VK/zx22/VMGBARZu2fPv2G6hTZykKFEiLS5esVNAI6fpI4PxIIPSt3HEt9J30akmU2qbtNquyS/8Cx76Wk7lqy1GixCycPRuAtWubo1Ejxxg537v3CtmyTRb+DpSu83kQMW6LEgHhIUCz20AyPr5xoJzsD5z/Cyj8A1BmFLQQVHsQrJagMXXqaXz55daIPjwbSwNPTwEfbQSyuWD6+QOfAdfnSqK3aD/8+ecR/O9/e9C4cT6sWdPcEhjses7Nmy+QO/dUMY7fvjUjFCOqVj0+KjMNMj00Mw1+tA5IZyPSLvABsDKLVHS1Y/YtD/3zv3p1MzRp4hgjY0tuhra7XbJkRpw61dlQxWpPqbD4+CCQoZIlVdv2nN1NgDtrgQpTgfyfY+zY4/j++5345JM82LQpGi8P27bAoto0DzdmymPGPFGOfAVcngx4DXZKaEa0HXl9E1idW2aPa/dWEIQkCrmTf+LEZxb1314nvafMPNgVuDbr/csxDCZbA0lmZWvkWG8gEzvfo8dmTJ9+Vigj+vQpK77f5oZZmXipKA979SpYEO4sVOCnSpU44nGcZ/n9KUMGxZwrAVDkB6DYQCCh65LzeH0LWJ0LoKl52yAsW34JrVuvtft4HjPmOPr02Yk2bQph8eLGEsujvQH/KJJhJEgBZPA2hAMyDN3JIZgWjaX1XsBzX6DWNiBL7QhVcGOV33F6WW7Z0gp16+Yx6xKa2nLy5Lr48suSZp37oR7s47MPI0YcQsaMSdGyZUF9JmfiEWs272vzgYOdgMy1gdrbnAahIrCsg14RWFHj53IEFptZvPgsnDsXEG0M/+bN10QYUtKkCUQ2IBrZRWkIfKATcH0+UJrhYH2tG0GufPb22sCDHVKFkKeDfkFQv74nNmxoadOWT5x4Et98s11k5Vu92sKFspbphqorTbrOXday44A0RjuvNm25GZVdXwAc6AhkrinCXDp1Wo/588/j11+r4uefHbMAZLaX6tUXRZSuGxn2o83ruDM58v1NKhXydgMqTYeWRnncuFro3dvB4aFRDANmbKJCIYJR/+q8wOtrQN0DQMbKZgweBx3KLFEXx8rU5qV+xxdfbMZ//50VxrZ9+5YDJ5qOXDjF1uujR++hQoX5yJEjJW7dsiIk89YKgO91hjhwV7HGOiB5ztgub/rf6cG3WLfoa/lYZHzq2nUjZs3yhY9PJQwbpsvsZ3qNDjtSI4JatCiA5cuNsrktSSWzWzW6BKRyXnY0PRCR/OW0TSsqx7irnzChfZJ0WHMjAgPfifBMlocPeyFjRp030L62wM0l0uy6EHP7uEhheO1S3SZQmze4dDUQhQrNEHMmhknb0/jaHASMCRe9IndvG+DWUiBjFSBdBeDZaeDtQ6m21ArJghzNJZnFRTaJDRco5thg2KO5588/RtGiM4XlAefGomieYunLyXlN8FP5e865GC6Yuog9mmLbOumHukRHsLV+iVv3w5Ar11QRCcBxY64SyNTGaSFcJCP/+aemPI0JMZgYQxR3oOxoSVrxe2Sp96KpDXLEcXqF7FIg1/sbCl26bMTs2b746acK+P336ia3iGu0NGmk8MDmGR1NbkXcO/DZs7fImnUS3r4NjdB4kle0colRgXVhLHDieyBXW6DqIqd1XhFY1kGvCKyo8XNJAuuPPw4Lo+fo4qw1QiHWzHAMMbm7Hqg4HcgXj+Ot97YEuLArNxEo2AsnTjwQxrhczNIYl+nLbVW++WYbJk48hf79y2PkyBrmV/viopSu398iz02WEyjzD5CzpetI1+9uBHY1ANKWBuqfwF9/HUH//nscajw+Y8ZZdO++GR9/nAebN+smEZF2IV1S6h/ViIikaBs0aJ/Imte1qxdmzHC+uql9+3VYtOgCRo2qgR9+KC97sCydnOg39HPNCf7ZocDZITLBQYXJGDr0AIYMkQkwWFzNqFlTB5Upk1l4OZhdSHrT0/AUDfWZabA+UHUxkFBmYLVpiUT4aKR9gwaeWL/ethsCtmx3797bhelrhHczs1xRtcnSMsBxiTBi6tjxvjJRR5H+QOmRIjwzRYqxwsNt//72wkbAZhkqbQRwr15bMWnSaUEM9O1bVrRZEMQ76gL3t4kEFS7hL6b1l2a9IrlLGND8LkISZhah8DT/vXq1Bzw9DebMNoLIomouXXoiiDWGkpOIEOXKdOBwD6my+mitod5nZ4HrC4EbCwCGEGslcUYgV2tJZtE30xm2A0a99/D4W4wPkishIT9YhIulJzGMnOHkXl4ZcPZsF1lN5ExkCVICFf8DcrVxnTlXbB0W2UsTy6x9TW8iPFkOkVnz3r3Xtk0KEqkdHTuux4IF5/HXXzXw44+6ucH2OsCD7ZK8Qlic8WiLDWL93yMpZCOfN2eOLzp33ogKFbLg8GHTPRXPnn2EEiVmC3UiyVVbrktM7lscPfDvv4/ixx93i9a7u0N8e3x8KovEZzF+K0/7AL4jgAJfA+WjUA06CA9FYFkHtD0ILGor+ZNJ9yYzbmFcYUtcksDSwk0I6M2bXyBnToPv0MuXwcic+V8x2Y3V9HVrVeDRfhEGJsLB4mvRsuaV/A0oNkC80GjqTKxOnPgUpUtntlnPNQmw2eaZ717KzILMiMFJiD7TzQAggc5s2GattLKigEPAlsrSYLPpNWiKvyJF0sHPzzGPtqYK6tWrFCZOrCM7FMkHwspeOu50vaKtFlB7O1at8kfz5qtRqlQmnDzp/HCWypXn49Che1i2rImQaMtQzQRy8dfsDpBMFy7kOMRiv9LF8dJ8lwu3qkvE8R4eoxAWxv86fuEUW4M1QtYiVSjfF0e/lj5qLJyMlWVmHdsmqND3YXUeuUD++BCQoSIOH76HSpXmI1OmZCKs3eRMVLGBYsO/0z+SCy1//2dCHctQMUGwULmygu9/Q0ikDS9rWVXnRgBnfIB8PeRCGkCxYjPg5/dEjN3Q0HCXI2A7dFiHhQsviD0Dvh70BLGr+YsZ3xF9chdJwmuh8BGSglh2B2121s6dN1Gr1hLheXr+vO7bGpsxPm9AwEGA3xWq3+g/pJXkuYHc7SWZlaa4zdppakVa1jzteEdvJDB8kWGMEd6zdzcBu3R+Q7RpYHY5exD/poJk6XErssiw8fqngLQl0bz5KqxadTkiuWRp3dGcV7PmYuzadQsLFjRE+/Y6pdrmysDjQzJTI8nAOJIl02RoDnYGrs0BSo0EivZ/77Tbt1+KDHhUcTKToKl+lppVA33u6HeniukIGLJxeohNCJPfKy4S4q4ILNPvdVRH2prAGgxgEAC6iN+TW8IRioWxVdZ10oKzHUtgUcrMuPvcbWVoH2Xg0aT0rFFjEfbsuY2RI6ujf/8K+q7NmnUOXbtuElkszp/vGvNiQh/LvR3IUssCeOLIKSd+AC78o9/RZqvr1VuGzZuvY+zYWvj2W9uFaWn+RQcPdkClSiYs7DnZvLEQOPkjEMhHBXJnlbLrlC7qJ0OV2LrCQMLUQOtnMPajevXqWyRNav9whdat14iUxaNH1xRZRkQxyiyFRhfiyOAEcGcDsLshkLYMUP84btx4jjx5/hP+dcTT1pkyzQUmS5Z/8eDBG6EMokIIJFuX6khzVw3V1LwNaCRba6vYiRs0aL++6yZPcMwFy8LjNVVt587FMGuWGeatwc+Bfa2B+1slCVNmtAzVsqfR8MYywNOTwEcbgGz1wfAx+sqQWIm8oWIhHDY/Ldr7H8mU3uYXtqTCSIpMVqGND/472qQsllzLRueMG3cC3323Q9QWoX2u5i9m3F+j5C7I6I22bdeKzFV//lkd/foZ5lQ2gsiiaub/n72zgK7i+rr4jwR3d3cP7u7u2uK0FCuUlrZQSiktpaWlLRQpUIoUdye4S4Agwd09OIQgSfjWmXnzJMlLXl7mGf/vrMVqmszce+4du/ecffaed5pOndYr5O3GTa2GGsjfH8pMiLrdsBC4u1VFZQkKPeSF6fgURdRAlgS0kuayy7+YniSB5IMH7+Lre4UiRdLQpk1+p5Zyjxixlx9+2K/wCwnPkGK728CNZer7U7YqHqLqGGHu1xaCZ2eh9nbIUMP4zpA5XrKkWUwvlU3HizqxEJfv2NGe6tUNperhSqBtasiTDgpHTxCZ6wUK/Mv584+JCS9kjx4bmDnzJMOGVWDUKPctxXfHS2VU47QFdWU+gN1t4cZSRQGcAv1dNrT/D2DFbur1DmDJTlxC026km2zXBDk3gKXJI2uuRvEh1XhyihdPpywCNJhkrVqL2L79hvIClBdhlLYiK4iUbSRqGnbNlruepM1r3l5Qbqri5ejRfgwbtkeZO70+7s+evSZFCnVBaZOSmCCG/PtD4G515pLmUZETWZq460yqfhmJnIEOIbyL40X69JN58CAYf/9OlC4tJM+OtZIl/+PYsfuWxPE3VsLulpCmAtTf71gH9Gw9cD9srgRJc0OzSwo/U5o0kxSlJGPQSM/+YtCWObeNZBNTp04EL2/CymwqwW2HN44NlsTAV4tDwwUFZYEjpcNr1lymQIFUdOhQ0Kkbp+iGIUS4Qogbo9LjF1fVwKeokonSYOUFkNUxGxUL/yMpCytRYjYBAYGsWNGcFi3cgEcq3ITLM+Xl9bvyWwtiV0EgCxJZ3r3NLkZ3mZzz96sLYV9HSF8D6mxX+mzXbjVLlpyPiHByjkfR9lKjxkJ27rypoA6kPMwYIF6SUlUfa3IOkuePth2nHhAOHaaVGbtL6bbMhSY+0blzYf77z6CQ6f8pnJ+oEov7/Gj7lIkojFBGCDJL/hv2xnSufDMlmCVlc4n0Q6RH5tyKFRdo1WpVjEusbB+o9SO1IIHF+nh7Q7izAbK1UXmaPBUxtKmSiryruhyytWTHjuvUrLmYbNmScf16LHgVrUynuRL0hQs9yZvXoIAZTYmdHtfRpW2EoyeIzJc+fTYrZOIDB5Zi3DjbwAGFCs3g7NlHThVDcuk8ukPnW2rA/Z0uV9P+/wBW7G4GvQNYDwFJYV2KnVsuP9u5ASwZ7gIpzQlVFec6hlidgG++2cXPPx+C7BIeAAAgAElEQVQ0/l0WjJK9FwUMsatXPyZHjmiU6oT0Ucgfm11SN8/vqxnLidqpvDCSdDOQgOtZ9qIRMWfMmIQ7d/pYn03hDjr+HVyYrJZheSeCot9Cwc/BO6KqpNtdFnMi5zaPFOluTUJ9xoz6dO/u2NIE84XT2bM9FLShYpdmwoEeKv9PzfVuN21WHTKiQFJDG3l1YpzP6dPr07OnY+czqonSSG+FL054GZTysCcnYX0xSJAWWpuVp7jTjIcrcxXXNmy4QsOGopqZTiFJdSfTuEQseMaicvDBAdjVTC2BS5QZqq+JIOntsPFFQsytqYu5a/Z42LDdjB59wOJ7KRwZ3FyjzqMoYtU3/d1hc2dLw3c2wfb6FtLePXtuYMaMk2TPnoyPPirudhxYZcrM4fDhe4wYUVHhblESat+VV3mmxFoFQsK0tozeecdoXD0V50KuD1my5Bzt2q2hfPlM+Pl96Dw/oujps8+2MX78Eb7+uhy//GIghN7XGa7OhZJjVYU8e+zNExWRJcGs+9vVdYiY8GNlqAM5O6ok8A5QO9Y4SDNkkJJjjezbnkHE/Jy6dZewZcs1Zs9uSJcuBkEcLcGZ52Mor66fPdKMnLbTIU9PRABAEqoSUL59uzeZMumrovj06WuFdFwsKGigiSheoyapshSyuy8not3X+NxfcHigGuw17CfCt7V06TlFBdKCay2KDiVZmTq1ysEUGNiXtGkNIhh2O/n/J9o0A1EoStp0vk4HxSKA1Q/4EhDUQAAgyhSmwIClf8IT9A0gpT3yYb4ASFbP04FGCnZWTxsDCFY5BukhPbvXrS3nBrBigMCSEWpkmPJzjhzJFVLyEycekDNnciWYFaXKlgV5raom9d7a5f/ArytkrAe1NirDfPUqRPm4S730uXM9yJ8/9uOfM+cUXbr4UqNGNrZvbx9xOmWReGkGBAyF1w/UvwtHjyxEk2T3rOlflARCXxqDnxqCRMr5pKzPkXb3bpCiOiLZ/uDgz5SSFcXO/AFHv4AcH0DleY50Qd+2pXR0RWZ189AhREE0ffnlDsaO9bdU/tO3V5ta8/W9TKNGyy2DPu6IWgk/mnBlrsrtYVCgkvfk06dupIgGaNx5c+Y0olOnwlFfm+tLYX9ntdw8pQ/UWAuJs9p0PXU5KBLeiCZNlrFu3RXq189J5cpZ3C7AMmDAViZMOErixHEZMqS8yb/Ls8CvO2RqADV9dZmeWDfy0B82llWvaYsbSnO3b79QSJmFA+vVq0FKebE7WZs2q1i27AITJ9amX7+SqmuvHsDydOrPHYTX0UGcbPZOhFY6Jkpz+ftx6tQDihadpRCmP31qCNbb27ZO52ml8haKtOECFbHuSr4/1xarZYYPzfY+XglUNLggszI30i259vBhMGnTTlLclu93woTOuy+00q5t29pRs6ZhzRVONCHW8+mqBoyBzd+g0GAEdSzCCvfvv6Rjx4Lkz59KV9Tx6dMPKFJkFilTJuDxY4Oio4w9XCmjq6bDYf1emQP7u4CBniCyfr76age//SYMOiioalE3jWo/piXX8uZNyYULHznMdY9pWPZKUiota2JBmcre2BHIyHC8ca6aHzsDWLLJ/A/oDUj27TOgLVBAxIAjGUsNQGCSwq8i8Fsp9ZEAVmNA3Rh7qOkdwBI9ZWEfPm749zbcvHzuIfPk3ACWcGCJFLLU4yfJDbk6W+XA0jg9NMh++PmMluPF3ReXet4gN1fDruYRsuw5ckzl+vXnCMpFNgixVXbSiMV79/bh778N/AqaRHOm+rC7lVqyKZaisFp37ancY8byU39IXZqZM0/Qo8dGS64OPa+hWVsaei5XrhRcvvyx6S9uoigS42FLacdiQ8at7TOFQFYIpwWVU6lSZvbu/SDGTep1wuTJR+nXbyvNm+dl5coWarO31sHOJsp1p4G6SHM7exUIy0U/RC1zxcuboKA3JE36l/Irm0p8nTgojUBaFDVFWTNSE76802PUALhY5sZQeSHE0zezHu2wA76FUz+BGQdP796bmDpVPveqRfv9ibYTfQ/w87tNxYrzlUTP1au9TI27Y9D7xWUQfiYpC20fpPgqKIpEicYpCReb0NX6Tl+0rWmcnIsWNaFdu4Lq8c/Ow9oCEC85tH0abRtOP0CU/ETRr/goKDpMmdvEiccpXG43b35CliwOUPCM4SArV57Pvn23TQIacr4jES7PL8K1hSoHq/ApaSbXUIR+JDmUoWasgpHmCOrz53uSL5+h9CyGcxPTw6VfUZoUgaOLFz8iTx6D0qQEsCWQ7fMzFBkS02bd53hRrz4/AQoPhRKjHc77KEg2QbQVLpyGU6e6m+ZBRDEEGdwwAFIVd5/50cuTW2thZ9Mo1z8x4dyUQKOUXwsZvo9POlq0yKtroDHWw5Z1h5Qbhwab/sma1fz/lZ9fRfP3YIj0vEh+b17eLFQV70L056ZTxIhEiTYUWtyExLLdd43ZGcCSoNUhQCPvkqyWZLwEFvmLjSM5AqwDhtt4vFsepncASyVuiNyE0N22omDXT5VzA1gy3jubYXs9VSGmkWlDEH4qzEnrBg/egSzQ9+69rRxmwfFhbQ5lobImn6oS0u6Z62fakR7c3wVbqkOy/ND0nLEnbdEdgbfDTl+E10H4HSyI4cOj6kRdsMQv6ubPy/Fk53YOJfrTjNDbzUom6vDhu5QpM5c0aRIpEGhHKpFpwbK6dXOwaZMkHAxmLzdI9KN17BGKBHZCdZHQ/DokyWZECwliROTTXSGpLO8YWaTKe6VixczUq5dDXViFU0107OTY2boFwvQBJEijNJQ+/SQCA4MVdUdReXQXE+VYyZQfO9YFH59I/FKUBvuoG26x/AOg1B9KYM7pFknQ5+XLt8rm0Obvj5OdXrPmEs2araB06Qz4+3c29W4Mxn0KZdTgpstNyruWGjb17YONyJd8+aZz8eITS8JklzurOlC48AzOnHmkEI0L4bhikZTxuom7qhtHv4QzY6HgF1BqrPKrggVncO7cIzZtakPdulYCyU4cRM6c07h27RkWojDOKHuRb9KTALi6QBWZeakiARVLmAGyt1fLDNOUt4sDUbtfNm9uS506OZwyo+bIr1evPjOJo+xqATdXQdkpkE9/riinDE46kWTpyZGQtzeU+1vpNm7c35WArJcXhIYO1tWV2bNP0q3bBizWYUpQIL4acBD0qDORwbqOLorGAvfB5spGzlJrR5rmXpRjrZf69u+/hUmTjhmbiZD80ZLgxYarSCRZC4j6YfgAkq3BIe08OT7slfWgkhyntRlBh81Zk23oR/ZNHV7r26mV76y+ndjWmh0BrPjAS6ANsNKsl9mAROabR9OzxHwkDrMakMy0qAB5rOkdwPLYiQjnuPMDWI8DwLeEukhoddfmeYyxjKixTCEbtLhucz8eeaCQpfv6QML00OqecQjbtl1XuIbE9FB20kgYI6Ao5muPlxe0vAWJHE9y7vDrtLkqBO6BKksgextFiUzQLY7iWzAfj4Z069u3BJMm1TH9aV8nNXMcG24Qh0+clQ60rKUErVMWU9CAyZP/xcuXIYqaaMGCagDGmWY1ixiJSpoz/bK5r8XJIeQ5NDkPyVVi8bJl5+Dvf09BkwmqzB1MrnX8+H8qz45w5wmHnoXJQmt3a7i3TYXUlxoHBcxKNpw9iEjK7mKScXa2u9LfjBkn6NlzIw0a5MTXV9Z8BnMTGW2LOZHyCSUzHAYtb0OiTMqfI+XvccVkRtJnunSTFBGP48e7UqyYoWwwnJCCm7hqcuPkT3D8W4UviPLTld9rSahx42oycKBB3dZFjgtiKEGCP3n7NsxS3TMc+tnh7sl9KGXjkri4sQReqzyNigl3qqgYSpmhoMpttIYNl7Jhw1UF/e4sjkcRfRHxF+E9vXfPjHtLkpuS5BQ0qyiAe6qdHQ9HPlODi1UWOhyB9fPPB5C1WLduRZg506Cc+/YZLDFw77Z7CXETeepsWvfbBuXa8N/DYcPKM2pU1QhtLl58VlGNl3WeWKTgg0P9VL5ct7A4KmevXFf5b2T/5G9eCa0fY+3c8L8Xgavrsj9zkDqoEcSRFNo9d+nsmgWwBL5skKNXXJKoXWSRO5G4l3KeSoC5YtWvQHWgvJUBycMp5yUAQgF5Ec5w6eB16Pz/A1iRT6LzA1gWfDhv1Q2LDRZjGdG7W0DUpKJBetnQtfsfEnQdVuUA4XTo8Mror8zZyJGmZz82ZS9v30r5wXhCQsItNmPIa+b+k2nwMBKlmbRpJ/Lw4Ss2bGitSGXHtiQzsrmQa7Z06XlOnXqobEaFcNfILbCjMdxeD+X/hTw9PGYqFUfXFIDn56HOTkhfTeGv+PffE9y8+UJRyhTJ8Sg57Rw0Wi+vsUhSVTh33r41VH6fGg0BwyB3d6jgxt++VTkh6BrUOwBpRVMENE4Zd9igapfs/v0gMmT4W1GYe/Pmc0t+oxdXQO7rZ2cgbhKovAiyCGWBC00jPk9dFhqonDlyv06bdpw7d4L48MNCCJeHK+5Xa7MSqZqbHBwJIb0LZ9bU9bK0aqCg0UlIqZJNa0T5I0dW4rvvZN3qHibv+Xjx/lDeExYB2CtzVa62KLhiXDqC85NUFeBsraHqUsUVjey/V6/iTJ1az6XuBQa+VNR95b3w+vUg4sUzoC1dKb4j6A+pEhC+rJsrVREgzUTBTwJZOTpAkqhRVb17b2bq1AC++64iI0dWdso8r159kebNV1KmTAYOHTJDYa73gSfHoeZGyOTaax6riTByM9WFWpuUd3JQUAhjxx5S7qFvvok8iGJvnxpySNr96SdDcEaUcVfnUlGjgh59Hy34LqyQpEIcVWgrkj2azL1Udsyff1ZBdLZsmZflyw0UDMB33+1R1OL37DFQihiCV2/ehEUsvz/xA5wYEflMCjLJPIhka3BIO0c73lrAKXx70p/cTM6wA5/ApWmQMCPk66s/B5am/p0kJzS/4owRWe3DLIAV/piRsryK5ERrAazfAHkYK1jpTAIKotgmvBO1DaWDcmPucOkExLJzR9yRAmPrCRQCBX94BpD6BzckQ7A6e84PYJmXvjhSuUeIgPe0hXRVoe6uWN4+bn66eVbIrCRDPjIrV15U5N8tSqTsGI58pKT8IEmSeErJl3y8FDs+Ak6KlsE7KPSlymtSPLL3kR2duvKU/V3hyn9QYowKZwaKFp2pBJaEaFhg67EJCFobWpRIj3Ay0q6cnhj3vbG8SqBbbRVkbebw7Kkt/lmd66Nfw5lfocAgKP2HLU255hjfkvD4GNTwhcwNFB+k3Pr33/0ZNKg0f/zhWLEBWwd98mQgxYrNJm1aKb8VURlDOYgkM26ugNeBaqm3vKdTlbC1WccdZ4XEv2XLlcr7dNKk2vTtayDydpwXMWpZE0X4/PPS/P672XUPp0QXo0YdefCa/PD8AtTZBenVzaH2PPboUZR//1XvZ3cwLdAivrx5YxZosUGty6X+R1IKPW/eaTp1Wk/VqlnZtauDS93TEEMWan3uJL4jwSsJZkuJ4R1ftbRJs3RV1GBWtjaQ0IDIM5vN0aP9GDZsjyI2NGuWAb3j4NmeNOko/ftvpWXLfCxfblZhszK7WiJZ/yCkKetgLxzYvJGbqQw0EGocEBRfqlQTEcVAC3SkDm5oaEWL9/2jw7ChjKqMK9UG76OFvlYpH8TaPIb4Bi61SMY6YsRefvhhP02b5mH16pbGIxo1WoavryloUrNmNrZta6+84yMkfjdWgIcH1ECZoCELD1FVyyXo5AoKAWddU/NAYYc3seLdi9TlSBJxzhpa+H7sQGDFtoRQc0Ggx9mA+naOXWC38jJ9ApwCTgjFrJ1t2X2a3gGsMgZWewnBS4pW2pffCZ5UUhxCHOYJ5vwAlszK0jTw5hE0PhUjWHaMJvTidDj4MWRpCtWlDPY9NouSjDsWJXzCWSUfYlFuFEJwe7mbVq68QMuWqyhVKgOHD5tl9948haWGD5xZ8MzjZ9t/IJz/S/2YlvhZGc6oUfsZPnyv8rMeJZnW5ihOHJWvJF48LwWxYjRPVr/ZVh/uboIKsyG36F+Y81dEzaHgqHtJAryjRx9QSlgGDiylqA0pqJqDn8DFaVDseyhmJTPoKKdi0u7W2mrZXaV56mZK2C0nHGHAgG20apWPZcuiowmISWf2H7t16zXq1AlHhhseuVlwMJSS5JobmJUSCk3pb8iQcvz8czU3cNTkQrduvsyefYqff66qqBAazbcUPD4KNdZDZudspG2aGG3TUm0lZFXvU03ltnbt7GzZ0s6mZpxxkKZGlipVQh490vhkI+fkcYY/NvcRSYnj0aP3KFVqDqlTJ+TBg352rwds9iGKA9evv0zjxsspWTI9R46o3wS3VXZ8/UgVH5Kg4P2dhpy1rPy9IUkuSOUDlearIhTvQpl3op0SKLSq2KzHBIZrY8iQXYwZc5ABA0opPKVGW5wMQl5A0wuQzD3Kyu0avjGxkFtVhzZYpUrz2b//NhYCC3Z1YHlS+fJzFaT9ihXNadFCLdG3lcNXh+5d28SixCoHVbPLkDSXVV80ZVNZD9+714eUKRPy7NlrcueejnCyiUW7Vl5XTBX3Es7Lty/0RyK5diat9x4WCosSOI5k/dJMONADMjWEmutdOgt2cGCJv0LiLvEVjU9C0FXCBzQxBiTuUkIhiCxRKLTHrgJCuCfliMUM/6RMMY89jdl7jt4BrN3ARUAkwtTiXhCtXIn2yWTZu7qV9PSXgJAIBRgunJnub4ThS+TgJ6E2MMhHysUVqUlb71bXBLCcsREX8lIhMc3ZGSqJEud7bktTw5vH0PgMpDCoJIGiTJY27WRevQqJFbHzL78cYOjQ3Ur5zNy5ZiU+7yukOhLCUE1KXRDGUk7iCARWlGWfbiKJa9eTtKcDXF8EpcdDgQFugcB68eINyZKpxNaCKhR5ecU0X4WLqeBAu4brlJN2t1E3VWUmQn4V2aSReUcINDvFocg70RQntSys8SiNO0/EHiQD6S4mClPC2SZ5qQ5vjVlgKVX58sudfPBBIebNc3GZY7i5atx4GevXX+Gff+rx0UdmyljGMlM/SGuNNsIFE7+9kYpqKT8D8qgKX7t23aB69UWKepqoqLmLaX7lz5+Kc+cEdG8wLclR5BvwkWWYm1kkZMwiRpA06Xjl+yUbzvTpw/HROXEI//xznF69NtGkSW7WrJElLOAJ4jsvb8G1RWqZoSByNJNglih+FfuBPU+7U7XqQiIoCTtwfkXVV961v/1WncGDDUgrZ1U8OHBcxqatJBZ69tzAjBknGTGioq5l3dmyTeXmzeccPPghZcuqPH3Kdd/bAdJXhzoeXZUU9RVbkQWCb0ODw5C6VJTHapUJs2Y1oGvXomioLDlJgleifhrlWllLblb8T1Wm/18yje/PEejI07/Bsa/cYg9sZwBLCPtk8y6yyhIHkdiGZLZkgytkz/I3gUEaZKuV/4psuES3hQOrkSHQ1ccQm7Hnztpn4OEyP1dq3SWg5TTTO4AloWWpITDT4VXGInAzmUCDZnyMxqddrN6GyKNcLJEgKwDcj6Ql2W0JHET+NtpwIaUwX6BuEvyyxVwTwDKSSi6CHA7KtLqj+pItV8TeY1blhqArUG8/pLUsD27RYiWrVl2M1Qdey/D/+GNlvv22osnLR0dhQymViFcIed8XC0cYKsPq3t2XWbNOKfw3XboUcQgH1hdfbOePPw4rZYrCnyHE1woqyELJ7xokMShhecp8H+wNF6dCsZFQ7DuFv+Lu3SCmTj1O0qTx+OKLMrouPm2ZlkuXnpA373RECfHFi4EmNML2BnBnI1SYBbm72tKUa4450Asu/WMhv3z8eCA+PrMVtUxBWLiDjRt3mEGDttO+fQEWLmyquhSe96LYDyAqRO5gVhQehZC2ffu1VKmShd27O7qDp0YfypWby6FDdyOS97sr+iISQYrr15+RI8c0ZdMTHPyZqUzdxTO9bNl52rRZTaVKmdm7V0U6KravM1yd676iGlY2/Llz/8OVK09drvY4cuQ+vv9+HxZ8XJ4mvvPsvEqhIPeBmEFN7MaNZ2TPPk1BUcu97AyV3apVFyicQxZIpFcPYLmhxFEJxkue3UPNCjfT778fYvDgnbRtm5/Fi5vpMjgpcxOBAaGKuHnzE7JkSaa26ykCL7GdhRgogf7wwz5GjNhHo0a5mDmzgYK+Cgp6a/zeR1o2aO6fb2l4fASqr4MsEnP4H7IN5eDRISO1hq4jdyMqDDsDWDIdAnnWQD0iZTnAEB+Rv0kEWRBS3QzzNgqQOEpWQGI0Ep8R6ehFdszr74Y4isRfLhvooexoRp9T9A5gSfRPQsWbwrkndZYSFZT0bUxN4HJS2K1h1AUuJ9q+E6zA5STQJRdWopFmxfkx6tY1AazdbeHGUig9AQqYQfJj5Ho0Bx/qDxcmQdHhUPwHPVt2z7aMpSImPhzNUU0OuHjxdAQE2Lch1+DUS5Y0pU0beaYNdncbbKutloJKSej7Ypf/A7+ukLEe1NqojOrKlSfKxzlBAnWDZW85ZlRTFBBwnxIlIlESCnkJiw3Z8rbPIJ5hQeUp831siFpeYcYrZc4tYyH77aQx7dt3i8qVF0TMkm+sCA/9oOoKyGYiJnWSW7Z3E8kCRbhAUqaUTwY8fz6ApEkNqDLbW9X9yKFDd/HLL+FKWzTfpbei36loJ3fizotE4dHP7zYVK84ne/ZkXLvmXnL0WlBi796OVKokn3XJEb5RSxTEWj+EBKl1v7Z2N+g/AM5PADP0kgiEJEyobhpv3epN5szCw+p6mzLlGH36bFFUPUXd02hGUQ0Tisz13pp5YEUwp0mT5axbd5nJk+vQp4/rOOcEfSUoLAvSfiFQ317Ps8R39n6oorHM1MRCCg0z3ssWARAH3iA5c07j2rVn7Nv3gcJ5qtizC7A2v8ox2O6ZA3t3QtMW3EyPIH4qpVNf38s0arScokXTcuKEtpeNnT+SXMuU6W8liC4CAyLyotjJUXB8OOT5CMr/E7tO3PnscCrcUbl69uxDChWaqcxRx44FmTPntCIkcPBgJ9vWyCtzwMvrFmI07jw1uvq2qwXcXAVl/4Z8sqXX0fx6wuUZKjpYvrMutFgEsFzltfAaCJRd+ycvAInPCAeW/FvrTMf0DmBJ3Ykw1g2WPJyhIL4KICQeywxQt5iMzx7CMikTfAS8NJCMBQLyFR0TBbxNVrOGFa3inuBiz165coUsWdRFr5eXF97e3oSGhhIWFmYcg/b7kJAQhThRMzlW/mbt92/fWsbW4saNC/79iHPhb0ILfUNYUZXwW/m91GOGaBWZag/x4sVT/BB/NJPAgRxv7fdybJz9nfG6voBQn1+h4OeOH1Mkvus9psiuh3advHfUxStwJ2EV5+GV6wOL6yG16Fmz/qNsDM6d606uXMkjXL9Ir5NhTELS+Ntvh3n9OpR+/Uoo6I5vv1VVz+LcXE7c/R0gXWXCau+K8XWKakyak7reezZepzi31xB3b2vepS5LSG2V90qg0MmSTTSoUfUmTRrTo6Tdk9aeG1ufp+3bb1K//jJFle/o0U6m6/T6Ll6rs/MujjchrV8alVKs3WPOvPdsuk5Cih4wlLCcXQktqy785LomSzaB4OAQTp/uqiDbonoX6D2m5cvP067dOsqXz4hs/LX3ntf6IsR5fo6Q6puJk7Gm8ntd3ns23nu2vve8zv6G94lhhOXsjFel/4zv7PTpp/DkyWsCAjpTvHgGx77LbRhTr16bmTXrNKNGVWHo0HLqO+LFJeL5FuKdd2LitA+K8l3uincEq3IT5+VVQmrt5l2a8sr35vbtF2TNOlVBR7540V9BVdj7fdJ7TKlTT+bFi7ecP9+TnDkNgZ9X94i3JhvvDKWQIaGm77kjvrkxGVPYse/wOv0jobl7EVZ6ovKMyfsgZ86pXLv2nJ072yqbcO33UX2fzBdaer8jZEw//XSAkSP96NmzKNOnNzA+T95bq+L16AChlZfhnaOV+70j3rwg3nKh64CQlg+Jmyi14nuVKgvx87tD374+pE+fWPmeDR9ewXHrPSvviKZNVyiBtClTaiPE/cp7785K2NOOsLRVCK25TV1j2LDei8m9p/e73PvQx3hdnc27pHkgVxfCQt8SVuQ78uWbodzL8m2pUCGTQ9dGr1+/IWnSiYpK9OXLPciRI6W6Lr+3j7hbK/MucXZCGl90i+cp/HrB1rWR8i5YkgxCX/K24VlIKmwtcOPGC/Lk+VdBuz192s8YbIrN2ujIkXtUqLCQTJmScPt2H+P3yevYl3hfGE9YgcF4lf7N6rc1RmOK6f7Jhm+uNsf2fp/i7GqO1511hJT+mzh5P452/1Sq1FxOnHhgfBVv3tyWGjWyRLpXjPAuX5GKOCFBvG14BuQZMpgj3uWxuvcccJ28jnyK96WpCtBC9sIx3edGuSfc2wqv22sJK/M3Xvl7u/T7dOvWLXLlUrjUBB3lieoHwm8uHykJaAkXllTIOc30DmBJwEmCVRIy1TC5EqkRsq8hwOsYjsyaZOSvQHUgMvIKgcflBOYBkwFhGZxkgMxZgxxJtCgCK/H06dNJmzat4nL27NkpWbIkR48e5fp1odRSrUCBAhQsWJB9+/YRGCixMtVKlChBjhw52LZtG8+fPzf+vmLFiqRPn55169ZZBKVq1qxJkstj8T79I1fi1ud4AilPhUaNGhEcHMz27dstXmCNGzfm/v377N+/3/j7ZMmSUatWLa5du8axY4IqVC1dunRUqlSJs2fPkjKgMxlD/Tkavz/k6eHwMSVKlIj16y2px/Qe07lz54xjDX+dyr36mUyhB7ibbQQZq34f4TqNGfOE/fsD6d07Cw0amCpco7pO2phmzAhk9WqpTFVt2LAylC2rim1mf7uZkm8mQeYm3C/8b4yvU1RjcsS9Z+t1SsdZKgUNISRxbtbFMSnR9ex5lYcP37J6dW3CwkzPh/m9F5sxXbuWmoEDDy8lWHsAACAASURBVODjk5SRIw28C0CVYqlI41edN3GS45vYxOkmz5OtY5IFgb3PU2zGpLwj3vjCoT7c9q7AoYTyigS596pXX8vZs48YOTILPj7qfemsMY0ff4ApUwIpVy4JU6ZUML4jCp2tTcJ3j9mR8A8yFm6o23tP7+tUPngUGcP8eZSoCqnz1uNB4D32Pq/LoEHXuXLlNePH+zBgQF2HvsttGdOoUbfw93+p8DM1a5ZReUekDL1I9VeDeeWVloQdAqN8l8f63ovh90nGFLSsICnDLrM/wbfcj1tG+T69eBFEunTTkfjb9Ok5yZgxkeueJ7MxiTR5u3YqqfHjx/3Zu3er8s1NFnaDWsGfEhYvFaEt7rn0+xT+XX55wyByPxrHLe/K+Cf80riOKFFiCgEBL/j884xUq5ZMeUdYW0fYcu9Jv7F97/3zz33WrXtK9+45mDGjrfF5qv2yL0nf3eZavv/IUbazLmsjvcfUJKgt3rzlcNZllK7WSlkbdeu2nQMHghS1eI3LsUmThA5b71kbU+nSsul9yPDhmSldOol6nQrchoO9uONdloMJhym3jS3rPVe8I7T1nvacvYufmuf1rhjXsMOG3eTUqWAWLGhCrVqpHbo2WrVqBy1a+OPlBUuW5KV06ZLKuvyY7xhKPB7CU6+c7Eg0zi2eJ+1dYNde40hlCL7FjoRjeeqtEtKXL1+BPHkW8PJlCJMm5SBLFhV1HJt1xMGDLxg9+g4FCiTm7Nm+xu9TydfjyR6ynaup+pKz4STleXLlvafNpd57jcTH+yrjPBWvC2/yfhbt/ql376OcOKGStmfPnoTu3YtTrdrraPeEXu9e0/SlVH3BusTzCIlj4uTTe0zueJ3yv1lEobcLIE9P7ucares7omrw16QOO8fN3H+RtcKnLv0+PXjwgI8+UngtPS2AtQAQuL3AV6U+WVALS4ybYSf9oHcAS3NbdlwSMpb2hdRd0FD2mLUAlgTJRGPaktRI7eE8IFqnEtbU4EkiWSZlhaadr6U37oHAuvA3cfz7EZalOaGV1HtB72h7nC3V8Hq4j5CKi4iTvXW0GYRYo8qckBWJMtp+6CO8rv5HWPHReBUdGiHaPnlyAJ99toPKlTOzfbtQq6lmS4Z7/PgjfPml6BaopIxS7qUh5bzO/Y738aGQsxNhFWbrmkHQfHQFAktUUeJtKsW7BGkJaWbi9qpceSGHDt1j6dKmNGumZgDF9EJgadepTZt8zJ9v4gPwfrQfr63VeZc0LyENTxv7jU2WMbzvUSEaY53hvr4Y9nUkLF0NQmuolddy7wn0f+PGq0ybVodu3YpE+S7Q+x0hHCw//niAjz4qypQpdU0IrKXJiBMazNtG5/BKlsd9EVh+H+J9Y4mCsInDOzWDV+gbWrdew5o1l5kwoRb9+5dyOQKrUqWF+PvfY9WqFgphs4KQvbeFuLsa8S5FUeI0PuF2CKx3W+vidX8rIeVm8i7Hh8bvk5TqXb36zIgQsjfDHevnySwbfOPGc/LkmaEgD968GWR8N8d5sJe422sq7wyano+Abtb7eYrJmEIvzcb7QDfC0tcmtLqv8TvUufM65s49w48/VuLrr8va9H0yX+I4YkydOvmyePF5xo6tzhdflDU+T3FXZSbOmweE1j+Gdxofl2a4rb3L467ORpzX9wip50/ctKUV33fsuE6dOlIoYFIIcwViJGPGv7l//yX+/h8g9AZi8S6MU4iHw3J0IrScCEi5PwKLV3eJtyZ7BKRj9+4bmTfvLL/8UpUvv1TvG0d9c/fsuUHVqouU8uaLF3sYn5vQy/Pw9utEWLpqhNbY4hbPU/h1XYzuvQ0l4MkJQqqt512GOsZ1RLly8zh8+B5LljSheXMVxRObtdG0acfp33+7ssZbtaqV8fvkvacFXnfWE1pmCt75P3lvEVgcGYT3hQmEFvwSfH6Odv/0+ec7mDDBBCYQ0vahQ8tGj8B6eZN463LzLk5cQloHGSsLorp+7vDN1e5hW/ZPUX2f4lyZSVz/TxSlwLDqa3V9R8T1LUycFxcJrbUd74w1XPp98mAE1nED6kr4zRcDIkErUHZNGdH88jrsZ0cFsPRy2J4SQplIQX2pb3HVRCdbYEASqLJF1sk1HFjXl8GeNkrZGXX36DWHlu0YSQi3QkYzSWHH9Ob6Vg8PgnPjoPAQKPFzBH8GDdrGuHFHlKzrV1+VJWHCuDaTZmfNOoVbt14QN24cQkLeWSqKHPsGTv8M+T+FMqqi23thojS0Mqsqky3kpzJxoqrQdjVLl55n3LiaDBxYWvehDh++h1Gj/OjbtwSTJpk92jfXwK5mkLosNIhKmFR3l/Rp8PYG2NEQUpWAhkeNbX7yySZksSiE9SNHVtanLxtb6dNnM1OmBFj27c68QeHHpfHPye8N5MHy48CB2/jrryPKcz5mjAB4XWs5ckzl+vXn+Pl9SPny4dWcqkEd+ZS5me1pDxJ0DadEWb36QnbtuqmgKjp0MKm9utL7o0fvUarUHDJmTMKdOyqiWbGbq2FXc0hTHur7udLFiH1rvEGpS0OW5kbpdE3B6pNPfJSgsjtY3bpL2LLlGnPmNKJTJ1nHCmlEGCyMp/63xS1IbOAccgeHzX1YWxCenYPa2yGDqiT++efb+fNPk3qeI9R0o5sGKccXkmyxwMC+pE1rQIUHDINToyH/ACgj/LseYFa4mb79dg8//eRHnz4+TJ7s2Ht5yZJztGu3hsqVs7Bnj5nAxIUpCvKZrC2g2goPmMxoXLQiANW583rmzj3NTz9V4ZtvIsv32z50EZjZseMGO3fepGzZjAo5uSKkI7apMjzYB1WXQTaDcqbtTXvOkSdGwonvIe8nUG6KTX7Hi/e7sj+QJLfwhtlkjwPAtwQkzACt7tp0ynt10G1f2NEIUvpAI1MAUJcxGpXpT0OKQro0aW8jHsiBpQ1VPpRlAKmGkwskFW/yO/03f1FMrh4BLKkjEpmkIMBUUxR5p4KEiqkJibvsTLXInpCGSY3SRCsk7qI8KJI4AgPRyC1E8/1rwNbVlGsCWPd3w5ZqkCyfkhl2iGnypDbIwDqkf2c3avzg9IZyUslqaaIE8t13KpeTmK2L1osXH5Mv379K/Obu3T6KapwotBg/6Af7wMUpKhFz8ZHOHrXj+gsJgsUGLhkz0nRt8S+qeWPHqhsCPa13781MnRoQUTEyElJ5Pft1eFsP/GBTRUiSE5pfMXY3erQfw4btoWvXIsyaJfF351mrVqtYseICkybVpm9fEZUFXgXC8vTqz+6u2nSwL1w0e9YNSn5//umPZETbtSvAokUG1T/nTatFT4JsTZx4PK9ehXD58kfkyqXynOHuG6tDfeHC3xHea9pGacyYanz1lcoD6GrbtOkq9esvpVixtBw/bkZifGkmHOihZHepaVne7mqf0RQ0NUcM9+6MGSfo2XMjDRrkxNe3jcvdFAdKlJhNQEAgGza0pn59hccD3jyFpYZ7ud1LiCsUGW5okQhSaEkS8VZQbjFJZuk1QnPFSUF0GwVRDvWDC5M9bz2xKInCzUSzS0ZuJiGoF6J6CYCsW9dar6mL0I4EXA4cuMOGDVcVIvPWrfOZ1menfoaAbyB3d6igIto82qyQXv/88wG++WY3H35YiLlzG8dqiFGulY0B4R2QwfXJoVgNNKqTz/0FhwdC9nZQJXoRN23OJHglwWlb9xfc3Qrb6kCKItD4pMOG47YNawG8BOmg9X393AwLURMsYq3uQ0KDEql+PcSoJQ8OYEndo8h5y8deOLAk/iP0TU7NXuoRwBJyJiFuFzIgE1FTxMsoDOf2QH6kEFjIbXoZAllCEtbOMFGieih/E/KzoYYuswFSSzTLoFQoHFjyhRIYzE823l2uCWBJRlA+BPFSQFsTt5KNPkd/2PHv4fRoEDn0Ap+p/biTwlX0I4j5EWfHw5HPIEcHqCxluxHN2/t3wsLeKSTEISFf2NTHqFH7GT58L/Xq5WTjxkg2FHs6wPVFUOpPKOhUXjub/Lf7ICEHEQUvuYeaX4ck8rjBuHGHGTRou8OCA23arGLZsgtMnFibfv0MQRXpWLu+2dtDlYV2D8tlJz49C+sKQbyU0Pax0Y15807TqdN6atTIxvbtKheCs6xy5fns23ebpUub0bp1frXb5xdhTT6ImxTamTj9nOVTjPo5/BmcGw9eCaDIMCOKRcjpW7deraCdBPXkSnv27DUpUqiqiC9eDCBJEoMqortvrAK+hVM/Qf7+UEb1X2zYsN2MHn1AEbOYONEc/Oy6WdaeoVq1srN1qywZDHbmdzg6GHJ+CJXmus7ByHp+dh7WGtRszdCDW7deo06dJRQsmJozZ3q4hc9ZskxRCPz9/TtRunRG1acXV2B1bvBOBO3tZY5wwvC2N4Q7G6DCTMhtCm6KwpoorVmMyQnuaF3s33+bSpXmkzNncq5ckSWvwTRkXqk/oKCNKA4n+m21q5XZ4OVNqH8I0kjCHrTAsp7qeJH1H2XA5ehXcOY3RciIUqIM7+Hm1wMuzwSf0VBE2wrBqlUXadFiJaVKZeDwYRGIj515eY1V+OGk6uDtW7O18rL08DoQGh1XlTLfV7syB/Z3gYx1oZZK+RCVSRBVRE2GD6+I3I8WSe6oTry2GPa2h/TVoc6O6Lp5//5unjBt/xq8dVKNfnUflmdQ2Y06vAEvjarbNVPowQEsmTAJXom63AtAiPe+BfSRO7XxcugRwDLvKrsA9M2QT9rfpB/Z6ZrYnW100HBYfwOHlaySBK42ABBklpg83VfDTVxFQHDYooUswa1/o1EhDO+NawJYbx6DwBvF2r8Cb3NhxJhNWKRHSwDrpBkayJDd1aFl923i8mzw6waZGkBN3wh+2oPAEvRE0aKzOH36ITNnNqBbN1UpyMK21Ye7m6DCLMjd1X3nxx7P5AMgH4KGAZBKxCdg2bLztGmzWlEV2r9f/+CAVqK0cGET2rc3C/Jr93TeyBF29gzPqecE34MV8lqLAx1DII4qS71nz02qVl1IrlwpuHz5Y6e6lDfvdC5desLu3R2oUkW4JYGH/rCxLCTOCi1uONWfGHf29hksUVXGMEOBiIJS6dJzyJAhMXfv9o1xs3qeoCE4kySJx4sXAhA22NEv4cxY991YnfkDjn4BOTpCZRH3VW3KlGP06bOFZs3ysGqV5LNcb1aD6sbybjcsxzo6FM78Ypo8wzdankd5LhMliktQ0EDbZNgdeAnkGyilbm/fhnHtWi+yZzco+D46AhtKQ6Is0FKWgm5qezvCtYUQLiBUvvxcDh68y/LlzWnZUnKfzrV27VazZMl5peStfv2cpg3vjsZwez2UnwF5ujvXqdj0tt4HnhyHmhshUz2lpbNnH1Ko0EySJYvP06efOvRetpqcPPAxXJoO78sa+MgXcPYPKPQllJSqHtXOn39EgQIzlPeGfGe8vOzf8lldK0tESykbDoUWNyGxqtz+XtqttbCzKaQuAw0OOW6I5ycrqvRKOaaUZf6vmZSgL0poSJRfgyQSWtDBnp6GdUUgfmpo81CHBmPXhAcGsEQqXSL+grYS8wGEP0DKmOyN79g9ifa/zSLvUtgYhcwjPOYvjeF33nZ76twTXRPAUj4E8eFdiLpJlM2invbyNqw0fFzMsrt6duF2bd1cBQKvTlMB6psUGzU/JUMihKl//x1AwoTeSvlLdJxDx48H4uMzW6lpv3evDylTimZAONtQDh4dgmqrIKuINLxHFglc/NChOwhhaJYsSbl5U0RI9bXChWdw5swjBUkhiAqj+Q+E839B4aFQQqqHPcxCX8EiQ5lNmycQXw283LjxjOzZpykE1FJKIlk8Z1nSpOMJCnrLhQs9yZs3ldqtJ0HarSyoHz4MJm1aEaSF4ODPlBIhV9nevbeoUmUBuXOn4NIlswDlgY/g0r9QfBQUVdXG3MqMCYH6UHOD0bX16y/TuPFySpRIz9GjXdzCZY1rJwIq7GBvuDgVin0PxSKID7vW94Dv4NSPqg+FhqhJrOLfK+UnCRP+qaAf5JuTPr1JlcoVDj99+pqUKVUE3suXA0mUyFCWcXcLbKurojAEjeGuZqUUVkP6jh9fiwEDSjnd+8aNl7F+/RUl0CCocGPJkZFjaDlkc48AsU2Ts6UG3N8JlRdCDhVJ/PLlW5IkUXm8Hj3qT6pUkayfbGo86oOiTE7ubgs3lkLpCVBA8uMebid/guPfKqptlJ9uHExISJgy1/L+sChVt2O4GspWTh0ypBwJEnirJZmeUjZsx5gjnBK4FzZXgaR5oJnokznITvwAJ0ZA3l5QbqqDOnHzZlfmgJfXoZ4fpC2vj7P3d4HwxSUvAE20GIw+TdvTigcGsITbyFCWoQSvJHC1CxDYeE8DoMieqbDrHL0DWMI5JXCC8AGsHIayPteuumyfItcEsMS/FVkg+DY08AchctXTNF4mrc33JfsU1Rzd2wlba0DygtDkTKRHysddNu2STb569WNy5DCgN6y0O3ToLn755SAtWuRlxYoWkR+1Oh+8uAh1dkF6Ecx8j2xjBXh4AKqugGzq+KXsQsovhBNMiCrjxdM3Vp0u3SQePAjm+PGuFCtmVre+rwtcnQMlfoXCIjTqgSYBLAlkNb8KSeRViZJ5T5hwHLIAvXHjE7JmTeaUgQUFvSFpUlV04NmzAUqWXDFnCEzoOcJl6eD1A2h0AlKqCElBjSRL9pcSnDt3rgf58xvQrnr2a2NbwjEmXGMVK2Zm3z6hbDTY7tZwYzmUmQT5XYsSi3QoVkQTTp4MpFix2aROnZCHD91jQ6gJIXz/fSVGjKhkGs6ednB9iftuXpekhLdPock5SK6tFUETDTl48EPKlrUmqGzjDRjLw6wiCI2lL24qQqCN2woKT8rgBbk3eHAZfvtNfy7H6KZd+IqEt0jMgvR5bWF4dgZqb4MMNaNrxn3+vqsV3FwBZSdDPpOQQvr0kwgMDObYsS74+Bi4FXX2WpKTIkZy795LunQprKCZjRylW+vAva1QcS7k0h8xrvNQom8uCsRO8eKzOHHiAevWtaJRI5NCdPSNWh5x4kQgxYvPVgKOEng0mqeUDcd0wJEd7ywEj6cnZvWYayNPoY5Bezdbx3pgAEtgh2UNl1eyEJJZF35yIcEUOienbnb1CmBp5O1SCyEQM3PyA9nJSvhU0FnOldOy/yFyXQDLtyQ8PgY11kNmncmb934A1xaogTEzhSP7p8kDzjSqeWSEVnesOqwR0q5Y0ZwWLayXDsgmWJOMX7SoCe3aWeGsW5YWXj+02EB7wGzZ5mIk/CGSLU6UaJyS6bMlCGhbR+pREsyJF+8PBX0gamKiKma0HU3h9looNw3yOrfULiZjiPLY5ZkQyXEaHoNUktRQLVeuaVy9+kxRT5KSEmfY5ctPyJMnklKlSzPgQE/I3AhqrHOGK7HrY00BeH5eVfJLX83YVtGiMzl16qHCWyf8da4yreSuefO8rFxpFgTfUhPu74BK8yGnmWqWqxwN368xA51bJWY2mDmn1/PnA0iaVCfOiliMO1IxAmlva224tw0qzYOcZsHDWPSl66mrckPQFai3H9KalMM0brolS5rSpo2BJ0vXjm1vzM/vNhUrRsLV5O4iBNoQT/8Gx76CnJ2hkqy7VXO10EPp0v9x5Mh9hY8zNNQMgbUiMwTfgQZHILUZB6Ttl8w1R1pBlJYtOwd//3usWtWCZs2EPsUxpnGaCSpU0KFG8y0Nj49A9XWQpZFjOndmq1cXgCRC0teAOpZUxO3br2Hx4nP89lt1Bg/W9p4xd06jiShXLiMHDnQyNaDRC7h72XDMhxzxDHkG5VkUqgdFhdtByHiN867k71DIHu0zPQbr4jaMybyJkF/4wnWwC1PhUG/I2hyqrdShwdg14YEBrOXAZGAfcA6QF4Eml30EcCpsWa8AlvbGFPkJqdN6Y3ZZ5WfhqBorGkuxu9xOO9t1ASxHcidd/AcO9oLMTaDGGqdNpks7enEVVueKllS2e3dfZs06FVHlzsx5yegJae0//5wgfnwvZTHw00+RBJzfd04ALRAajj8kT55/uHz5Kbt2daBqVf3KXwMDX5I+vbwz4c2bcOiuzVUhcA9UWQLZ3UOdK8b3+9pC8Ows1LZU8KlZc5EiWz1vXmM++MA5cr9WSYSN3EcfQGVRzHVzi0RlTDzWSnSmTavHxx+r/G2usB9+2MeIEfvo1as4U6eq3DCKrS8BTwKgxgbIXN8VrkXdpxXRATlJSsqktOz06e4UKiSsAa61qlUXsGfPLRYvbkrbtmYBH2OSyBcyN3Ctk5H1bmVz/cEHa1mw4GysN6J6DHjNmks0a7aCsmUzcvCg2Wb21GgIGAa5e0AFoR51U9PWQlmaQvXVRieXLj1H27ZrIiIjnTSM/Pmnc+HCE/75px537gSZOLAWJYbQYGh2GZIaFB+d5FOsujFy+n0BpWQLoFrr1qtYvvwCf/1Vi08/dcyeR5Jq8eP/oQQCb93qTebMBvVkcUALEtfdB+mEMtfDbW8nuDYPUvpAttZG4RIZ1ciR+/j++3306FGUf/+1/333yy8HGDp0N506FWbOHLOg351NsL0+pCwOjQI8fCKjcd8K5YPugzbuA2dDbvcoydd9jNE1eKg/XJgERb4BH1v116Jp1EqpbXSuOOrvHhjAko2dqGVJJFzKBzVhPuHjkBInpxJH6hXA0q7vTEBQWM8cdcGd1K7rAlj7OsPVuY4piToxEk58D3k+hvLTnDSVLu7mzRNYauDxiYIYf/z4w3z22fYoSYhtJny3IJEOgriJXTwJOndvlPQeDsV/MDZeo8ZCdu68qXvA5fTpBxQpMisidF16XlcUnp6CWlsgY22dB+qk5rRgi2SEJDNksG7dfJk9+xSjR1dl6FCdOACiGdLKlRdo2XJVRKW+4yPg5A9qGYiUg7i7bW8Ed3wjkB7367eFyZOP8c035SMPPjtpXJof335bgR9/rGLq1cj7cADSlnOSNzHoxqjiA3QIAS9TqbBWqrJhQ2vq13f9JrtQoRmcPfuIbdvaUbOmGW+eNsf1D0Ia+xEJMZi1mB0qHFLCJVVxDuQyBYe08rL+/UsyYYJr33UzZpygZ8+NNGyYi/XrW5vGd2QwnBXUwGAo+VvMxu3Mo6WEVEpJ01WFukLhodqBA3eoUGGeUrItpdvONo1EfvXqljRtmkftPvS1Smgs1uYxxBfxJw8xK6qqn3++nT//PMwXX5Rh7FjHlGo+ehRMmjQq56HQGkhJptGWpIK3T6DxaUjhnOSQQ6/YgU/gktma3oweZMmSc7RrtybWAjs9e25gxoyTjBxZie++MyvJvroQ9nWMFP3l0DG7qnFjMPkKJHUQintDGXh0GKqvhSyNXTVS1/ZrTIZ0U9Vi9bDDg+DcOCj8NZQwE0vRo2072vCgAJZE/0VtUDNRmHtt9v+ShRWp54/smAa7T9E7gGW3I252ousCWEY1EQcsADXy2qIjFGLY/wkTNYsFEhx+B63uQcLI+RZ27bpB9eqLyJ49GdeuWV+4xomjZhGFXPvtWyvQ3qBrsConCFG+BM2EGOp9Msmwy8clf38ooxL5inXpsp45c07z889VGTJEv4DLzp03qFFjEfnzp+LcOeEJNDMjZ9xhSO2YTK7DL50VSfcRI/byww/7+eQTH6ZMqetwN6QDq6VtnsbJsK8TXJ0HJcdCIZPc96+/HuTrr3fx4YeFmDvXdQvDtm1Xs3TpeSZMqEX//mb37eJkEPICml6AZI4rrbH7Zgp7qwqNiLUKhIRpjU1p6DZBj3z0kevQbZpDQtgvxP0nTnSlaFEz3rzFSSEkCJpehGSGIIHdE+KAE/e0h+uLofR4KCCCy6pNnRpA796badIkN2vWtHJAx7Y3OWbMAYYM2a1wC82ebYbG8OsBl2eCz2goMtT2Bp19pEY2n6IoND5h7P3OnRdkzjxFIVGXoId8551pWtm4n9+HShJBMXPpdzOlWmf6ZXdfVkpKtYRh27b5WbzYMSI3mtphypQJePxYaFoMZr4mbHkHEgltr4fb84uwxgB+CCfQ1LfvZkWkKHny+ErAUJBpRi6wGAxbQ7TOn9+Yjh3Ngn7nJ4F/fxX5VXVpDFr00EONa04HlvPK/kH2EXoSmHvadF+eBX7dIWM9qLVRH+81gIgkVyTJ4mLzoACWUEBJgMqtJDH13lnLiuUeMCPcfdEDkBXkGBffL7Z277oA1ukxcGwI5OoCFWfb6q9tx+1sDrdWQ9kpkM/52UXbnHTAUVZIcc17MldVevCgH2nSGJThzA766qud/PabSTrXqBAU3mXhMJMylYQZoNVdBwzIxU2eGQtSGpCzE1SaY3RGU6np27cEkybV0c1JraxDeKCED8rCPLW0wnwQRkn3P6HgZ8a/aCiHBg1y4uvrnPJIrdwgQmnb/m5wZbaatZLslbub/6dwfiIUGQY+o4zeLlp0lg4d1iqcYhHuJSeOqVq1hezefRMLHj3z4FDrB5DA9WV4kU7JkhQgKNNwJON9+mxWSJOHD6/ADz+YocqcOK9aV+a8eXfv9iFDBgNvngWa5RHEN6BzXeCj1S41sZVwiaaNG6/QoMEyihVLy/Hj3Vzq8eDBO/j9d39LBM3x7+H6IrUcWkrzUpVy30SZxtsjSs+i+Gww2dyL2qMIuly71ovs2ZM7bZ6FX1MU44KDQywV456dh7UFIF4KaPvEaf7o0pEVUn+Nl0n4lJo0yWMqldSlU7URLSkZIfFlIypfR1cc39SxoXDaDFFihsDSEmGaE1bXrdF4mTHjZIUQ39+/E6VLmwX9TvwIJ77736nscAbq392TLI6/o0ErTQ2XZIhV18Zk8SzI3TVWTelxsgcFsESgbwsgC6l3gD8gXCKmDbEeExLDNvQOYAnXlbCiCsGXuQkcQ+omXV9XYNsEuS6AdWkmHOgBmRpATV/bvLX1qA3l4NEhqLYKsjom62WrK049zpjNiLosR+Nw2rq1HbVqmZWcGJxtSCSoigAAIABJREFU23YVS5dewMcnHa1b57e+6Lq3HbbWilL50Knj17uzS/+CkLNmbgw11hpb1xACUvogJRB62d9/H6Nv3y0RVR89ubTCfHKsbFi3br1GnTpLKFQoNadPSw7A8aZlayMEIXa1gJurPCf4baXk8aOPNvLvvyeUEiEJ0kmgw55sdGyvRIEC/3L+/GN27GhP9erZ1OaiKM+LbX+6nS9BinPj1fIbKUVPlNkYpBD1NClz69q1CLNm6SxAEsMB3L8fRIYMfytnCVLWiKQJvgsrMjmehDeG/locbkS4fgplVEVQMQ1RIkiKJ08+JY4Lkb1du67nv/9O88svVfn6awPaVtvIag67s8qxhliJmwTamVdGuEY8Q6bsxYs3ikqq+vMAkiQxIB0fHIRN5VWFWlGq9SSzgnTTgt3aUOwNqkQ1FRrpeIRkxfuomhfwHZz6UZ2OQl+Dd0KL4LGX11hFBCfKyoEoJtNcpOPp009JnlwqiAzmZmVZDn88HM27asGz5WElw3pO/pOTsL4YxE8NbR7q0/KGsvDI321KMz0sgCUXQeI4QUBpQNSRpATHZVA2vQNYr+T1CVwJd7eJdutpwFDIr8+96MBWXBfAurUOdjZRs5cND+s7xJXZ4OVNcFfuD31Ha2pNI0auuREymREmh+tPIxYdO7Y6X3wRkRvl00+3MnHiUaLlILmxHERBI21FqBc+luuoQTqxXeP4KkE94fFTbf36yzRuvFwJ8B07pl92QyO8FtJtId82mrYZJQ54WmmF+eXSJN0LDITS44x/0aTqEyWKS1DQQKdsWLVnYOLE2vTrZ6Z2ZVTHWwA5OzjxZrOzq7Pj4MggyNEBKi8wNmIzitLObm09LVWqCTx5Eo7w/Nk5WFvQvZEWUQQp5s07TadO66lZMxvbtrW3dSocctypUw8oWjQS3rwnp2B9URXdJig3d7Qzv8PRwZDzQ6g01+ihhnCVXwgnngiJuCL4Kv03arQMX98r/PtvfXr0KGaaxflScvcO4sSDjuZaPm420aIQLErBYh3egFc8o4MaOnLBgiZ06GBFZdgBw9EUYBMnlve9CYlrRCIIQXejYw7o2YFNCo+P8PmEU6gzF2YRbiop19TbtMRXy5b5WL7cxC3JoyOwoTQkygQtb+vdrevaM1YanIXkJtEKm7lbo/D88OG7lCkzl/TpE3PvXl/LI/d1gatzHMPb67rZtN7zzmZwa43jlK9f3oKVWSGOt0HpUO9tujtOaiQ+vX4Eywwo9PbBalA2tuZmpZkeFsASVaHNZpdAeCJWAZJ1+TO2l8ae8/V+MkRlcCRgWnWpXnU2/F4CWZ5grgtgPTwEG8tBOGh7rCdN6v4XJoB3ISpkXtr/X7EtNeD+Tqi8CHJIGW/kNmrUfoYP3xtRZcVweIkSswkICLQs+4msKSNCqRHUWPf+zfLdbbCtNiQvBE0kLq3ayZOBFCs2m9SpE/LwYX/dxq0FDiMQbz89A+sKQ7yU0Paxbv05vaHTv8KxryFXV6g4y9j969chJEyoBrTu3+9LunSOFwOoXHk++/bdZunSZgrK0GjurtwW/qJd/g/8ukbgT5AyHS+v35WjJQDw+rXzJaq//XY3P/10QPFh6NByCrmwEoh44AebKkKSnNA8fA7I6Xel9Q6NQYq40PGt8TgpiZTNf548Kbl40alcnhF8tcqbt787XJkFyfJBzs4Wal1uM8NGFHZDqLne6JYeG1G9xliu3FwOHbqrIG2NZOOehMAKC4GFhqBVOC63Tp3WMW/eGcaMqcZXXzlPSEFTgM2VKwWXL39sulTXFsHeDpC+OtTZodcldE47VtBOWlJKc8IRCCytHD4Ch+TdrbCtDqQoDI1POWcenNHLqlwQdBXq7Ye0FYw9inr20aP3Wb36EnJvCW9dTAPfCxeepWPHtVSpkoXdu8PROOxoArfXQfnpkCccR6kzxu3sPvZ3hSv/QYkxUPgr/Xt/HAC+JVS+XuHt/V81gQwuSgRhr/VTX3Wz0kwPCmBJtk94Ic6Gux2FSFaCV2abBefdsHoHsORpln9fAtsMwxC5nF8B2TX87Lyhxaon1wWwHEUAbk4E2uG1RcYxVjPlCSdr5U/lpkLeXlY9Xrv2Ek2brqBIkTScPNnd4jjhyBLUhLxTb9/uTaZMZpLM4Vu0kkH3hKmyyUdN8UYymHn7GDeB5jxiFiUQNjVq/aAOHdawaNE5/vijBoMGlTEdGLgPNleGJLmg+eVY9uLC0y9Og4OfqAqEokRoZpkz/63IqR861IkyZRxPNps373QuXXrC7t0dqFLFLMjtabLjt9bCzqaQugw0MJXpu0MQQOMPirB5u7UedjZ2DPpWr9s7iiDF1atPyZXrHxIk8Obly88UImxXmVXevL0fwDVB5Ilv78Ady9ykVFe+WWnKQ30/iymMbSmQXtdDIxvft+8DKlbMrDYr5aWnflKTZAUGQbzk7suBJf5qgglNzkNyk/r30KG7+OWXg9EjrfWaTEM7q1ZdpEWLlREVYC9MhUO9I/0+6OyC/s29eQpLDaqJZigKCaqICuGzZ2+UUu5MmZLEOKgSnbP9+29h0qRjRFB6vb4M9rSBdJWh7p7omvGcv/uWgsdHofo6yGImrCCP5vFAfHxmkyxZfB4/7o+3d8zECbTvZvfuRZkxo4HlnGyqBA/2Q9XlkE0/6gi3nfjDn6ll9IWHQAkHbGm1BPH7FmC154Ia1517IZ2Z8qU9bYUEw2JDErjNE4ifwp5WdD3HgwJYwn8lJWHhCXAF6hngquo6vVeY0p4wCYp0jhTwy/8HG8jbpUBbyL88wVwXwAp5CYsNhLN6PmRaVD9BOmh93xOugX4+Ggmof4XCEluN3G7dek7WrFPx9o7D8+cDSJTIVFbg63uZRo2W24YuCPhWXciHU+nTb0Aubunw53DODDFqtglMkeIvZVF65kx3ChbUh4S6Tp3FbN16nTlzGinoOKN5wobflktlJLqNmGGvWHEefn53IiKibGnXjmOSJRvPixdvOX++J/nymRFcL00Nbx57jux44F7YXAWS5oFmF40zIRun2bNPcfXqM9q0ya8Eq2OajbZjWi1O0cox5JcW5TNX5sH+TpChNtSW9YIbmgQpbq9XuRTT11BRIQZF27dvQ0mQ4E8lyG9BnO6CYVjlzbs0Aw4YUALh1Lpc4GbkXd7fDVuqqSixpueNx7hD8FVzJmnS8QQFveXChZ7kzWt4T5hvENo+VQNY7mwrs8PLGxEoFSZPPkq/fltp3jwvK1e2cNoI/vnnOL16bVIQbRYckkZhH0uErtMci01HCvI/Hsh/pVxPkl4GK19+LgcP3mXFiua0aGEKIMamO/Nz27VbzZIl5/nrr1p8+qmZ0uvF6XDwY8jcBGqs0as717eztQ7c2woV50KuDy38Ea7HFCkmKM9sBFVWGzzv3Hk9c+eeZvToqkr5soWtKQDPz0OdnZBeaHHeczsxEk58D3k/gXJT9B+sFeED/TvygBZlDSdruSpLIHsshYyEPkdodKRcvP1rt1CH96AAlkA6BZQkKoSTJSZuIHT/DRCYspksqfPuK70DWMb1jWFAErySssLXzhuSLj25LoAl7lvJDMZqZLc3wI6GkLI4NJKA6f+Q+Q+E839BkW/A5yerA5fyovTpJ/PgQTAHD35I2bKmxZaQEwtJcbduRZg5MxqC4kP94MJkKDociv/w/k20eVY13CawaNGZnDr1kI0b21CvXk5dxi6ZQ8kgbtjQmvr1zXQgPGHDb8sMaNK+wnEiUtTvQo1BAQ199vvvNfj8czP0mS3txvCYly/fKipYYhZErQohuiH/UHAwCPGxIWgRwy6cd7hWXioqc20eWfSrLcadXSKkOaGVKAkHtwR7jOUz5ybC4U8hWxuousR5cxXTngKGw6lRkK8flJ1ocXbWrFO4detFhPdnTLuI7fFWefO211fVjRAEQph7IrCs8HRJ8HXjxqtKQFtKeWrXzu704Ktcl+DgtyROrL4nhEw+RQoDobOncbesLw5PTkDNTZCprvGW05DYJUum58iRLrG9FW0+/6ef/Pj22z307FmM6dOFbsRgmsJcOI5Emxt29YHCNSacY41OQsoiRm8EbSaos8mT69CnTwndvaxRYyE7d95k4cImtG9vxmV2+jc49pVaQlzpP937dVmDu9vCjaVQ+i8o8GkEN2rWXMSOHTeUe0vusZhYhQrzOHDASiJtWTp4/QAanYCURWPSrGcee+4vODwQsreDKov0H8OFv+FQX8jaEqot1799T2rReE+PhwKCi4mFaerwbsR950EBLJl4H0A+/FJKqMWOhPe8rVAgx+LK2H2qowJYApMQGTeDjIrRv9V2e+rcE10bwFqdF15cUuHNAnPWw4y8GvWh5gY9WvScNoyKZH2h7KQo/a5XbwmbN19TyMKFNFyzqlUXsGfPLds+/lqZSqk/oKD+5KQun/gTP8CJESY3zBBYDRsuZcOGq7bNk40D0croDh/uTKlSGUxnecqGP7pxaiWZ2nFm8/n11zv59ddDDBhQivHja0XXUqz+fuXKE3Lnnk7ChHF5+dKMNF5DFEbiX6w6dOTJURD8u6pESBtus2YrWLPmEo0a5aJChcwmJUTtuZIyZyl3dlc7+ycc+RxydITK8y28rFRpPsLlE4FDzcljGTBgKxMmHFXQAoIaMNqmKvBgL0gwIH4a9+TACr4DKzJHqpQ4duwhvvxyJx98UIh584R+wvl2/fozcuSYRrx4wiE3yCQuIcEgCQp5Csp7czUI3B2BGzMg4D4lSvxH2rSJCAzs57QJ1u7ZCFyPmkptse+hmNl312mexbKjNfnh+QWoswvSm55Fq4q3sexOO71IkZmcPv2QCKrSmmhKfkuVT526dV0zQkMgdATFRkKx7yL4MWTILsaMOchHHxXjn3/MAqQ2eJw69UQeP35FQEBXihdPZzrDHGHX4hYkNpQT29Cmxx5yZQ7s7wIZ60ItSYbobFqZvqj8lp+mc+Me1pwGPij8NZSQ4q5YmKaImrIYNBIAkevNwwJY2oSlN6gQShZQyFxdpoajdwBLSNpXABLel3JBrX2tdNDb9beMTR64NoDliJryU6NB5Llzd4cKM2yahPfmIOOG6wOoPC/KYWkqZX36+DB5spqVffUqRIFfv3kTyrlzPcifP3XUU7O9IdzZABVmQu5u7800GgciZURnxoDI/coiUGRuDYicTz7ZxLRpx/nuu4qMHBn74Kug4qQs6e3bMK5f70W2bGZlKe/Lh16TdJcJDodoc2Y5i0YinDNncq5cMeOKC7oBqyQfEdE/t725Q1/DIoNqjSCwBIllMG1OW7TIy4oVzisR0vrXkBY9ehTl33/N+EQ8RY788mzw6waZIiZDNASm8NVJKaqUrji7RFPmWQiHhXg4Am9eNJs8t7ifo5BRX7ToLB06WCFTdpLzWgls5sxJuXWrt6nXezthaw1VAa1JeK5XJzkXk252Nodbq9VgsRk35qNHwaRJoya6JJBvTiUQk+ZjeqyGth03riYDB4pKucH2doRrC6HUOCg4MKbNuv74jeXh4UGotgqyNjP6o5XE2hNQsWVQ6dJNUtD0EUrmBN0iKJei30Fx0Zx6T+zYEJBy0wKfQemIomArV16gZctVFCuWluPHbV+XPnwYTNq06vMgasiJE5uoNXjzBJYavq16KcW5++Wwwq+pm9vGoM1QKDFat2Y9siGtfFoPtOTVhbCvI2SoCbU1im7XzoqHBrBcO2lmvesdwJKC8lBAJFSEVVmKpWW3LwTug4HdbjPyqB1xbQBLIx0vOwXyfaLPlPl/CucnRltGp09nbtaKhj7LHL0qYOvWq1i+/IJCTNuwYS5lA1a7dg5FXUskhIXbJY7U/kRlGyvAwwMqIbcQc7+PtjoPvLgMdS3JFTUlx0jJPu2YhydPXpEqlVqmFBz8mYIOMprGxVXoKyg5xo7W3eQULSOsuWOGwFq37hJNmqygRIn0HD3q2HIWbYFbvnwm/PzMODS0kthI/HOTGYzcjUVJIPQlNLsESU0CuIJ+EhRU6dIZ8PcXgVznmlVVTSNX3y8gGUd3tSgW8FWqzGfv3tsKj2Bo6DtTeaSTx2KVN08rSSgzEfI7D10T4+FbuXe1IHOOHMm5etW6IEmM+4vBCRs3XqFBg2X4+KTj2LGupjNvrIDdrSBtRai3LwYtuuhQK2pikjRJluwvhS/IpoSVTu7XqrWI7dtvMH9+Yzp2NKMUMSbEZkFus/nWqV+HN2MloTd9+nE+/niTgkRdt661rm7Iui1evD+UEu179/qQPr2BV1Z6MQYE/4SCn+nar0sbM3KldYGKsyO4cufOCzJnnoIsX58+HaAQuttifn63qVhxPlmzJuPGjXD7EVkDylrQOzG0D7KlOc8/xgq/pm4D29cJrs6DkmOh0Be6NeuRDWlot9jygkrSXXg7hb8zRRGVpsENaDD+P4AVu7tS7wCWQMmkzkXweU8N5F7nDL+TIFbJ2LnrtLNdG8A60Asu/aMvP8fuNnBjGZSeAAX6O20i3aIj48K6EtTbG6VLGoxfO0j4aeLG9UI4sFq3zsfSpTYEpDRSy9o7IEN1t5gC3Z3YUAYeHYbqayGLqZTlv/9O0bWrL3Xq5GDzZimNjp1duPCY/Pn/JWnSeDx/Hi777NcdLs8Cn5+hyJDYdeTKs7USV/FBgnHeiYwf15MnAylWbDapUiXk0SPHPrdTpwbQu/dmmjXL83/snQV0FNcXxn8R3N2DW3GKu7s7VKAthVKgBf4tlBbqpV7aUijF2+Lu7u7B3d3dE5L/uTM7K9lNsjKz2Q2953CAZOa+9+7Ye/d99/uYN89KTUhb6IkqTkgH3yy7cnT9hLBTiDvr74B0Fv6w0NCrlC79L5kySUL6Xa9f+bZt5zNzpgNy4XXN4OICKDcK8skekI+apv4pSUFJDlrZsGG7ee89dXfThqDey0OJljdvVS24ugYqTYZcUeTgvdzHGJuL5t69cOE+OXL8pXyTnjzp47KamB5DFDJn4ZGze8efHAvbukLWxlBjoR5NGevDjHSwVxMrXHgcR47cYuXKtsoGljdMQy/atbmsItzc6r8bYptegbOTodTPULifOZSLF5+icePZGME1du3aQzJl+lNJ1oSF9bN9TtY0gMvLoIKfJgSjuxlPjIbt3SBbU6jumK0lZ86/OHfuPqtXt6NmTROqOpabW5vT1ayZg9Wr29sefXMnLCsLSbNDi/PeeEzivo27h2BREbXyoM1N/fsTX+9PdyJ1ZRWsrgMpC0OTQ+54UM+JQT3Zfaeen/lfAsuzGOqdwLptqo0U9JXMbLsCa4C8cgsBJg1LzzrthbPjNoFlhIqdVpZYZSaE6Lvb5YXr4VkTsmCRhYsTsrQREZEEB/+s7NyJiRrb+++vZsmS09hB+6Pr1ayM8PQ6NNwLaSw8Wp4NwsfOjkbxZs2ac9SqNZ0CBdJw9KhJ7cuDrm/efJHKlaeQO3cqTp2Ksqg3IxX/hPxWpSwetBdnp85MB89uQeOD6n1qMo2vSf77yScVCA4OMKwkK1ria7PseBWo6y8gWqGVLAF39kHNZZClnjmmN248IkMGEVKR8uA+JEpkherzwg2g8elNn96Utm1FhdhkK6rC9Y36KO4YOY67R2BRYUiQGtrKJ99inTotZMqUI8rC0Yag3sj+OPCdLdtILl16gB1v3uKScGcv1FgKWV3jgfHqEKK5dwVZIiXVgm6T8j0p4/O2DR26k3791tKhQyGmTGliaf7wTxD6of+QY8uu/IEvIN87UO5PmzBqXJjjxzegSxfvEFNHW/K2sDDcOwL+uiG2oxccHw5FBkEJEQNRTdtIyJw5GZcv99D1NtY2fhzymJlLGuMZQv7cTNjYVuXNFf5cB6YpMzpUE4zmCgwevJGvv95K9+4lGDnSInagHH5pGaxtACJA02iPrtfQZ53t/h8c+UXlKCz6maqwqSeax7w5vACyWb1ffTYgBnZME+NJkAra3vGsocnCYBQBAUHQMdwzXzqd/V8Cy7NA6p3AktWNIK3mAsLuKsXRXwOCdZeifu/MBDyLiZwdtwksI1Qu5uWGh2fsSr48D5UfeLgVCktLQ5Ks0PJijB3WeBm0BVjKlAmVhdj9+8/YufNVXn45c8wDloOnJoTIcGh+DpLl8IMAudFFszqILaLv5Mk75Ms3hiRJghW+hFjLLWNpWlSKRK2oXLnMbNv2qu3RK6vDtfVQeSrkjLIz6MaQ4vSU+fnhwQmoswEyisiHatr9qP3frFhnQGd79lzJiBF7GDSoAl99ZekD5p3dZlB9ngEtG+RyZQ24ts7u/pASIVFRE267kye7kidPaoM64Nht/vxjOHHiDuvXd6Bq1eyWgxYVhbsHodYqyGwsYb9HA35yHWYLjyfQIQwCLQlAjQNP0G09e5aKEw4sa968s2e7ERJixZs3NwQenbdD5XkUDyNOXlkTrq2FSlMgVwebFkJC/uL8+ftKma+U+3rbNEXe3r1L8fvvtS3Nm8mx34MyqkqhT9uRX2F3XwhpD1Wm2nS1a9dljB27ny++qMSnn1YyfBjh4REkTBhNydvszPDkKjTcA2lECMrPbN+nqoptflsRnStXHpIli4qSevasn4Iq1MtWrz5H7drTeemldBw8+IatWzOp/DrIWE2vJuPej4ZWiWGj9uefd/DBB+to3jwfc+c6x/+ocbP99FN1/ve/srbjPDMFNnfyKV4hwy+ENWJeGrOifNClbW2tVm8LpK+gi0u/dWKteN7uIQS7iYH5D4Hlt7dATB3XO4ElW5pSbC7an/kAwZEXAARnKStM32BOi/1Sxm0CSyOby1gD6giAzUOTpMq0JBDxFJqdguS5PXToZ6drpQLByaDwgBhLoESqPCgokO7di/PSSxMQAksxKWH74IOyyOIoRlLisAcwI4UaoLb3IYH3d8i9cnWiKXMdNGgD33wjwhTw0UflSJQoyCPEkMaT0bhxHhYubGU7NLMMui3Cxivj17uRaIhupZnAwJ+UJKqofslE3yjT+N/++KO2knwwm8atIYIEIkzgL7a+FVyYA2VHQH7bHX4tibRuXXuqVfNukjlFit8UgnNBd+bPbyGXV5TnRIGuwW5I68PV9hHhMNVE5NvqOiROb74jrAl/7TjrvHTf3L37lNSphymt2ZFwR8Mt5aWuOd/MhtZwfjaUGQ4FbMtcq1SZwqZNF7FD8Dnv3aMj3357GWPG7LfnN9v+Dpz4C/xFLU/Kz6UM3YEYwRdfbObzzze7pdjmTnCvXn1I5szRlLxNTazO3ZqfgWTeKWd0ZwzRnhONaqmRaEJN7KB69eysXWubAEZDyIsSmSiSxRczb9RmgZaXHI5K3hvy/pANBkG9ObPBWLr0P4SGXmPevBY0aybLOis7Nhx29lI5harOiC+RjH0ck01L54AE0PFZ7Me7csT0FBD+AJoehxRR4u2Kn/hwrCQLD34LkWGqOIEgsdxBu+39FA4NUdd+BftCgpTu+dE5pn6EwJoAiPrbep1D4JE7vRNYjjojJO5SZ6ApEXrUYS+dHLcJrCurYXVtp0renIrHs9sw06Sc96IohVgHJgaS7Jjid/HifYoWncCdO0+dL4nRFNsCgqHDM5QT46OFDoDDP6gfg5d/MY9Qb8TQt99uU/jHunQpwvjxDW0jaUZTbId0UXYG/S3maxrB5SVQfhzktewY6x3PmMKiLYxnzGhKmzZWpW3atS7UD0oLwNZPbOtbcGoclPhGFa+wspo1p7F27XkmTmzEK69YSjaNHtmDB88Ugmixe/eiEOnKJoMo0DU7DclzGd0Vz/zPSAVh96DJUUgpe1SqSYI/WbLfePw4nOPH3yJfPqsEnWctOn32iRO3yZ9/LMmSJeDBAyvePBt1vzuQMJXTPr1+4La34eQYKP4VFB1k07ymsPjzzzXo18/C7eatPgoiVpCxf/5Zh3feKWlpdmM7ODcDXv4dCvb2Vnfcb+fCPJAy9HTlof5WGz/jxu3nrbeWUb9+LpYubeN+G06euX//dYoX/5sMGZJw7ZqVuIA/3bPRjTUG1VKt1NcpdLuTsZTDNC6+tm0LMH26RflQ2QnSEPLC2STcTfHFHpyB+bkhMBF0eOJwVI8fh5Ey5TAE8XfmzNvkzBnzO1De5ylT/q5suBw+/AaFCqWz9bv/S9j/mariKWqeL4IZieaJQT35RQit3Rj1irXGWxacQi1FlPJPHzA/SmBJ6YVIZp8DZBdbVCJiLmfyQnz1XF3LluxSQMhojnuh70Y2EbcJrDsHYHExSJQeWl/3fJzaw+uAs8Rz537gIeI5TDWVuQQmhA5Pne70mTN3yZt3DMKN5RQp8e19sKQEJMoAra853Y7fHXjwO9g7EPK8ARUkMW8xDTEkJQFCoOqJ9eu3hqFDd/Hhh2X54YcohPjxaacqGuUZQQQK4ffBgzcVtaayZTN7hGiL6VpEW9pmXkx/DUU/8eRyevdc4eMRXp5C/4PSP9m0/frri/n330N8911VBgwQsVzvmFZimzRpsJJcMe+Ahz+G6SZ4fNu76g6hL9u8PPDwNNTdDBkq2vS0UKFxHD16yyWiYD2Hqqlm5cqVktOnrZT6Hl2CudlUDgwpffTlzYVoNggkTv37r+PHH3fQp8/LDB1aU8/QOeVLS3TPnNmM1q0tyUui4UV0ymlcHHR1HayqASkKQFPRGrLYypVnqVt3huMSNAP6qrVXtGh69u/vYmnh8RWYk0VdcCn3rG8svFwKwYUFsL4ZpC0LDbbbnFqmzL/s2nWV+fNb0rSpUOXqYxpvU8+eJfnjjzoWp9YI+XYPQFD58cVkQ0E2FsTaPYLgJA5HpsV86tQmtG9fKMbRf/DBWn7+eSeBgQEMHqyWs9lUIOzqA0d/g5fshRDiS1jtxiHceRfnw+1QyFQLMlTVD81j842SDXA/fN71vvCTJQaRIKCAjmHuedeqmnxMIdePElgS9wyAyHaLFK7s+q7/zPviAAAgAElEQVQExgKS3HLzwrh3ObWz9ExgiU/JtghhwH8JLE+uy+4P4YgsuAJUkkB5eN2BTWp90EvJwZMxxeW5HmTxNQSMJK+ePXseuyx8DJPiuAyB7m0fHwk7ekD2FlBtjtm93oghUbsS1avvv69G//7lLMOICFN3UsVa34BEUXYGdR+wwQ53vgfHhqlIIUEMWVmvXisZPtwBN5XOXZKdVuF6s5OO18qZHJTi6dwFfd0dHAJ7P3GYZNV4fOwWOPr2wM6bVsKRJ08qTp60EiXwp+SKjCoaFVL5lUaAPWFCAzp39j7t5YIFJ2nWbA5lymRixw6Zb5lM740hI+8VrWw3d2eoKOh9i2noEqdVcXXuZ8GCYzl27DZ25bdLSquLuhqLIWsUtKzOfdDF3e29sKQkJM4Ira7auJQErCRihTpAkJLOlFp50qfJkw/zyiuLqFUrhFWr2llcaYIJCdNAm1ueNBF3517bCCurQvJ80Mx2adC06WwWLjzFX3/VpVs3/fi9RE1XVHU//7wSn31mxWEWnxHyCrosgVom1eICJJV9eHsrW/Zfdu68St++LyvqxlLKGR0txltvLWXcuANmJ3YcnJtfgzMTodSPUPiDuLvHvN2ytoGb61Wo9K9+rWsb4A7eSfo14keePFi72YxSq8LJ1x3KjfSZAPhZAss6bqUBKRURob4HwERAlJG8mvvRO4E1FBB4ix9r2ivXKG4RWPu+gAOfW24WT0kCT0+ELa9BptpQW5KmL5jJjsmJkSoRau7XIVlupxOCGifW4MEVFULtmD72SlTPz4UNLR2WJcSrqJ+dBps6QMbqUGeteWgSr927r7JgwSny5UvNK68U9ggx1KDBTJYtO8O4cfV54w0rvgobIulwCBSFET+2/V/A/s/BwQdWUwfs1q04f/1lUdPTc7SPHoUppV9id+/2JmXKRBb30ZCh69m+Ib6iSbJKW3/+uYd3313pEpmtHn2cNesYbdrMp1KlrGza1Mni8s5BWFxUTcRKQtbXbXU9uLICKv4Dua2SRDKjMRFgGyk4EFN4tPKvhg1zs3ixleKuCD6I8EPKgtDkiG9H2Cyc0BSqz7fp69y5x2nZcp5jYQuDRyXv9++/36EIIPTqVYp06RJb3u/zcsHDs1BvK6T3HqrR7SE/PAfzcoKgsts/sUHkWb8Pb9/uRerUid1uxpkTf/11F337rrFXdryxFZZXVOcszUXc2w9NqwBImBbaCB2uxTTRB7tEk4fDbNVqHnPmHGfEiDr06GFV5npnPwh3ZnxFyM9KD09vQqP9kNrx5oHGdemMUqz2LpfL4bACYW1juLQYyo+FvG96eNX86HThJ5SNvXTloL7K+aqLaYrpKQtDk0O6uPRrJ7J2u3cYzk2HJNkgb1en1242417bBC4tcsgpGZfx8dMElijHvA7IAy+5klmmv6VEpj8geSCvmN4JLGFOlYGdAHYCD6OMwrN6Iq+ERGkkbhNY0gM9SQIP/QB7BoDeuwXeux6et6QtuCr8DXnkFjXITo6HbW9ClgZQc4lBjfiA28vLYU19SF0cGu216ZBWwqOHPLYGd1+woCVNmliVGNw7BgsLqqVWUnLl73Z0GOx6D0LaQpXpNqMZOXIPPXqspEWLfMyZ45xykKvhOH36DnnyjCFx4mCF+NoGcWAmy18OWaLIaLvakDePPzsdNrVXlabqrLNpWUPplC6diV27bBMwRnZx+PBQevVaRatW+Zk1q7mlqWsbYGU1SJEfmh4zsgv6+N7YAc5Ng9JDoVAfG59awrVr12KMHi26Lt4zSbBs3nyJFSvOUrJkBiVBaUYXnJ8DG1qBj5UROIzOuVmwsQ1kqAx1N9ocIhsEL7/8L3q8X129Mhq5uXaeTZJyekoIvw9NjkHK/K669v7xewbCoe/UdosMVst1rJDu6dMPV0Rc9u3rTLFiUj1hnGmI0PfeK81vv1kpkF5aCmsbQppS0HC3cR0w0rNWBikVBSJfb1UWJc/rF19sQe/NmWjLXLUktoOyUSND4DXfZoXF9ZCxqsNmT526o9BiiCVMGMjTp46XZZcuPUAUT58/j1QEZMLCIuwrEJZVhJtboeocyGHM3MRrsXOlIW3DSUjF29zWrxxdOASFS1DKEuv6FF+2K9HR99h7x2FhAZXbrd19CDQJyLjSytyc8Oicncq3Ky6MONaPElgSdCETFNSV7KLvA+QlMgm4b4pNRxMKy2vEp3onsGKSzBMSdx/WBre5PeM2gaUXbFIb0q6+cPRXKPwhlPrBiOfQ931ufh3O/Aslf4CXPjSuv4d/gdD/Qc6OUHmyce3EteebO2BZOUgaAi3O2vTm4UOVqFoQ7aJ0Iwstdy1nzr84d86BZPzWrnBqrNq+7MoIbN6TMlt3O6jXeacnwZZXHaIkZ88+RuvWDlA7erWtoGaWMnbsAXLmTMlbbxWzRRrOyQ6PL0KDnZD2ZR1bNdjV5RWwpp6qNCWKU1a2Z881SpX6h4wZk3L1qq3Km5G90rhZ3n23JMOHW3GzXJgP65vrv6Nr1GB29ITjI6DoYCj+pU0rEyYc4I03llKvXi6WLTOeANu68RhLmE+OhW1dIWtjqCECyT5sMezEX7/+iIwZRygUXk+e9FWQEd4yETbJnl0la7ZBZPhjSbdGQK0FzwrpLomVv/7ax5UrDxUUsaCJY1Qf9vACaKVa33xThY8/VrmGFNO4WzLVhNr+IuIdJRg2xNS3IWFq8wFS5iflfsJ/JTxYelm0Za4xEPfr1Xac+jGrGc+F7FYbJFad0jYYtB9Fh5QdMGAdP/ywg5CQFJw9291xBYITCbM4jYdRjSviCsJZGamWH0vJnx52/E/Y8a4dNYcerv3WR2QEzEitbo64oxz67A7MNOVUJNlo9f6J65j4UQJLygKEjGwKMBrY4yB2EmTZZcntrbjqkcAqDkiRdIS3Ou2FduI2gSWwyUtL4NZ2yFBFXdR6sjg375b/AoX6eiF8PthEDITOuvZ272A4+DXkfxfKDtfVtU8503ZFRNWj3T27rmlEzkuXtqZ+ffffZ0mT/qoomp082ZU8eSwTX7SEpOzqyiTC0zLbuA6ueae9JDQMtenNxo0XqFp1Kvnzp+HYsbcM6WmnTguZMuWIY7VNmag9fwzNTkFy96+lIR2PyemtXSpXk0DPW16wOVKQFYKwEHvypA+JEplEHgzuZLduyxk9ep/9TrZZqctPkJvm91xPKPuHTdRWrTpLnTozKFw4LYcOeb+sJCjoZ0V0IygogPDw/1n6duhH2NNfLSOvKCI6PmxmfqZM0OqKTUdFGSxp0t+UMr5Tp7qSO7fVe9HgIb3zznIlsaOZefHrryXdGtJddvVFNdhkenM5xnZZNC6o0aPr0bWrTKlNZl7QtoRqs2Nz47u/n5YMnj+CZicheR5zP6Plq/NwJGnSDFPUo+2U805NgK1vxF+E/JqGcHkpVBgPeazEAKziKcnZ+fNPEBp6nSpVslG7dohdcvbu3acK+urevWcxE+ybSxYPQOoiHl41PztdEzKpEz3azeURHfga9g1WN2XLS57gP1MiIKX/gp50p4JGQ7c72GyP6+j6UQJrMCAS5I+ixEwWYDlM6oReD6ceCazngNREiuSaFOmLnr1tobvXh+Vxg3GbwJLuHxsBO3tCNnsODJdHpz38laZArg4unx4vTjj8M4R+ALlegUrCN2eQ7egFx4dDkU+gxNcGNeIDbp/cgNmmsgpRRwq0TQB06LCAadOOeqTyJkiu5Ml/VwYrRLopUphI2+UHGq+b/NtFZUkfiJ59F25sh+XlHSLajh27RcGC40iVKhF37hgjTz9q1F66d1+h9MsGWWGtjtfmDiSMWXbbp2L74BTMzwtBSaG9bTW7dRLALjlq4CCEXFwWbaNG1ePtt60WqkeGwu5+/oPcNPe3A1SWTTmLHT9+mwIFxpIsWQLu3zeeANu67RgTD3s+AiFHL9gHXvYaTYN7d5NGNi2JlfZP7UpUNMVQOyJ191pz+iztvV6uXGalpNvMCXnvKCwsBFJSIzLl/mCxIN2jTYQaMLby5SeyffsV5s1rQbNm+SwtHPwW9n7sUIjCgG4Y53JuDnh0AervgHRlzO3s3HmFsmUnkjVrci5eFAFzz03EdhIlUp/vmzd7kjatlRpfDO8tz1v2AQ/Cq3h2CpT6GQpHz9jyzz8H6dx5iaJqvH37q3Yd/+GH7QwYsF5R4RRVTFEhtLN9n8GBr9QNRKnukO+sJxvtPhA+l7qwpgFcXgblx0BenTYWX0RVR2eCrlURFXwfXv7VmTMsxxwbDjt7QdYmUGOBa+cafLQfJbCs8zzWURH1LMn9eA8GbtW6HgksSVY1AoTJTlBYmUxqhAZfekPdx30C6+paWFUTkueFZkIp5oFpMN/aayGT8Ky9gKYlPDLXgVrqQt0Q2/QKnJ0MpX6Cwla7/4Y0FodOI8JVxRuxVtchcXqbznz33TYGDtxgT0rrQpfPnLlL7tyjSZQoiMeP+9jyMq1pBJeFY0xQrRH+j8C6fwIW5Ifg5Gqdv5Xdvv2EtGlVlItRaKFataaxZs15ZaIq6BUzssLf1PGsA2cNHW//GIJsiZglySLJlrVr21O9umwiGW/lyk1kx44r9rva+z5VFwP+gtw89Q9s7QyZ60GtZTaBe/w4TEEIidktIA0OsaALRLHzxo3HdOlSRCmJNZd+besGJ0f7x7si/CFMT65Gq90DCLYtw9ae13//bcSrr4qitXdsxIhQevZcRcuW+Zk926pE6foWWFHJv8jGBel+ahw8Og8h7SFlIfMC3NsIrFy5RnH27D22bOlEhQpZLRczdAAc/gEK9oWXf/HORTailWh4FLWSVEFLPn3al6Ag+Z57ZsLdlC3bSAWB+exZP9vki5J0+RLy9wBR1Y1vppV2FxkEJSS55NjOn79HSMgoJTa3bvVSNsc0e/o0XJl3Xb78kPHjG9ClSzRKspqym3aiv6PgXb0Xdr4Px37Xl5pl86twZtKLp+oYW+xP/wtbXnePG2x7dzgxCl4aCCWHxNaSV3/vRwksye1kNiWrrGOUExC1Afd5YjyIuB4JrFEm4vbLQAggtRqSrXNkFuywB532wqlxn8B6cg1mSy4wANo9hGCrXSRXAzA9BYQ/gCZHIWUBV8+OH8dfWQmr60KqotB4v3Fj0hIrL4Iqi0ba2/Q4pLDaNQaWLj1Nw4azKFQoLYcPu1dGtGPHZcqVm0T27Ck4f7677TVbURWub4QCvSBRRv/nwHp2G2amVccoiIsgC9pM0EIJEw4lPDxCiYPEQ2/TpLUHDaqgILDMyIo7B2BxMUiUHlpf17tZY/0Jd8IUQQZGQstLkESAwhbTkgATJzbilVe8kwSQsozz5++zffsrlC1r1Z+dveHYHxDLwsPYgLng/eJCWNcU0paBBjvsTsyUaQTXrj0iNPR1SpbUiR/Eye6lSvW7Uvpy5MibFCxoeqbk3A1t4Pwsn1MicjgsIRCclhginkHzc5DMNsHapcsS/v77IEOGVGXgQO8p/g0atJFvvtlKz54l+eMPKw63i4tgXROVI0+48vzF1jWDiwug7EjIb/nGSCJUEFFLlpymaNF0tG5dwDAOLHm/iwKslMrblYRqi69iX0CxT/0lqvb9jEbJVr5pCRP+ovBlXrnSg0yZPF8HafyGDkUOdr4Hx4ZBkY+hxDf+G8/oeh5DaXfUUzQUp7VAjtz3e/ZcZ968Ewri/f33S/PVV1Uct3b/JCwwzfviAwre1btBQ/ZkawbV57l6tuPjnSgB1achP/OizUNlg1dEm6yEIGIdyfJKcGML+GAFkh8ksLRdk/dN3FfWJYSCupLJh+R7Ksd6HQw4QI8ElnSrASBvMqn3ka+sLYTA0nF1W9b3Le4TWPJFlxItkcQVTpw0VlLArsQv7D7MSKme0fYeJNB/8etKd+LsWG/JJ5tVWWZDDv1ISeMsbjE1PDdE3b2uvx3SSeWwxYT8NkuWPxVOJSkjSpbMqvzPycEsXnyKxo1nU6pURnbvjqIcGV8m9losbJItlyGJbHZYTHaUZWdZFPNEOU9va9NmHrNmHWfYsFr06lXa4t7fVZtmpoNnt6DxQUhlm6Tq3Hkx//xziG+/rcpHHxmfBJCFqpS2iJrT2bPdCAkxvZcl2mbkZsylH3pfd7f9Xd8MKypHi7jREqJ2JVFuN+jciQ8eqAISYnZlxytrwrW1PjmRdTi62VngyRVouAfSlLA5RBMD6NGjBCNGeE8Z9I03ljBhgoPEmbZDnrku1Fru3MXyhaOED0l4kSSZIUkNK5s06RCvvrqYWrVCWLWqnWG9tb5nHzyI8q3c2F6VkH/5dyhoTPm4YQOzdry+JVyYq6KeBP1kZZkzj+Dq1Ufs3v0apUp5/m1bvvwM9evPpHjxDOzd29l2eJtfgzMT4y/CxQURoe7dlzNq1D769n2ZX36pqcQpRpXRqDfK9nfghCrooNiLhsDSNsUFudnksD6P0dKycGsnVF8A2Zro4zM+eJGKjxkpQMjzXVG5VQjgU6kADgdzwLgOjR8ksDRhPind2gJYiCLVf58BfgKOx0Us9UpgaX0fD7wXQwIrLsboTptxn8CSXq+oBtc3QKVJkKuTO+OAe8dgYUG1BEFKEV5UM5PMBqhkrVE4m3QLi/CACB9I7TWQqYZubn3S0eIScGcf1FwGWURZ1da0ienWra9Qvrwt+sWZ8fz99wG6dIlGzWx9K7gwxz/QFM4MVo6JIdkiinmys7xkSWsaNNCfSL1q1Sls3HiR6dOb0rZtQUuPz8+FDS0hXQWoL98vP7P5+eDBSYfyyZ98soEhQ7Zhpwho0BBv3XpMunTREMdryM0YyHcN6pZ7bmPhPGrVah5z5jhIiLrXmtNnaXxxgh6QBJaNmd9XyyGL95I+Tnc+6oELX4J7h1X1OVGhszKNs65JkzwsWNDK7SZcPVESA5IgmDChAZ07W5UWHfkNdvdRS/GqTHXVbdwdbxZ36QelhaPWYitWnKFevZkULZpe4QEyyk6dukPevGNImjSYhw/7WJqREkdJtsj7K0crSFXMfzmGtr6llms6SBRq37ZFi1rRqJHnRRpa4lHIyVeujJJ4XNsELi2CcqMhX1ejLmnc+T05Hra96RRJ/dSpR+jYcaGCkBWkrNjEiYd47bXFyr8TJgzk6dPoebTY9CqcnaRurmdv5f8oeFev2sNzMC8nCE9hu0f6rCnm5YaHZ6DuZshQ0dUexe/jl1WAm9ug8lTI2d65sWo8qIIQlEomo9Z9zvXG7ig/SGBpfZbcjqCw7BW73By7HqfpncDSo0++4MM3EljaDocnhOBX18GqGpA8HzSLkySpL1xPkEz81ITqR9ZBOZFunZSyTyn/dLBrrlsbvuIomrIArXsNGsxk2bIz/PlnHd55xzUEoUDZt2y5rCyWihdPr3Cu2MiYa8ndytMgp3G7414N9fz88OAEOFC10RaOf//dkNdf11/tR+ODWr++A1WrZrcM++Q42PYWZG0ENRZ5NRy6NLa0HNzaAdXmQ/amNi5HjtxDjx4radYsL/PmGY+WPHToBkWKTCBNmsQK74iNacjNatHLn+sSD72c2KjO2Ys49Omzmt9+203//mX5/nvv8S6uWXOOWrWmK6WDUkJoY3Oyw+OLaomblLr5uq2oAtc3QZWZENLaprdLlpyiUaPZlCiRgT17oqBMDBxX0aLjOXjwJsuXt6Fu3VyWlvyVW+jgd7B3IOTuDBUn2EROK0XLlCkpV668a1hUt2y5RKVKk8mVKyWnT3eztBMLybxhHTLCcQwq0I0azVJKNceMqc9bbxXzuPWhQ3fSr99aOnYsxOTJUVAsyyvDjc0OnymPG/YFBxfmwfoWkK481N8aY4+uXn1I5swqSv769Z4KD5aUft+69UThD3v+3IoL05GnM5Nh8yuQqRbUXuULo/duH2RNITyFotDsgEbDrc5otByuoIzcasgPT9rxLogqa+H+UOp75wagbcBKkjWKurdzDow9yo8SWMYGwk3v/yWwHAfONxJYR3+HXe9D9hZQbY57l/jMVNjcETJWgzrr3PMRX87SSjIa7Ia0pfQflcJbkggiwqD5WUgmlHDx2MxlAbb8IdqIP/poPd9/v53u3UswcqRriIdYSXRjQCf4bcS1HSYHSQzZFZXd0Z9+qs7//mdbrqnHeFOm/J37959x9OibFChgxRt0+CeQxUeuV6HSv3o05V0fmlJQhQmQx3ahv3DhSZo2neO4RNWAXq5efY7atadTuHBaDh2KklxZUBDuH1Pf0fKu9nWzEXG4BolNiqSmfv/yy07+97+1Hok4uBOCGMu+piVVFxvNTkFy/VGM7vQ3xnM0fqZyoyDf2zaHHjhwnWLF/nacDNW9IxaHIiYhohIHD3bhpZeshDvMHG5+pr57YjRs7+ZQocqaYNyODFzHGAvfUIsWcxWUsqCVbWyykJpHQkAC6GhdvaFjB7zh6uAQ2PsJ5HkTKoy1abFr12WMHbvfIhziYX8GDlzPd99tV/ibfv21lsWbINqOj4Cn1yF3F0iW038RbdHFyFzynx+aHos1kkWKjOfQoZvMmtWMu3ef8uabyxQk4NWr7zJ06C4LF6YjT0f/gF29IaQtVJkea1vx8gAN1Vt9IWRr7NkQ9w6CgyZeNiEcF9TQi6TqGFv0tHe1K2Xq+7+E/Z9B7teh4t+xteD13/tZAqs2IH+E1DSq2oZ7RMceRvy/BJbjAPpGAkursU5RAJoede9Sa7LB/gbtd2+0MZ+1pBTc3gM1lkBWoW3T2ayVo14EvjEzf8i3UOQju2BOm3aEDh0WOp6YOxH6wMCfFHJX2Q0MD4+i6DhL+OFuQKN9kNrzXVsnumP8IWYBgHGQ9w2b9vr1W6NMKI1AtFirxt2509tGkQhNaajAe1DGXygMrUK3qSOcnQqlh0Ihq/IcYO/ea5Qs+Q8ZMiTh2rWehl/fyZMP88ori6hZMwerV0eBwM/KqC6sGu2H1NGoPhneQxcbmJEawu5CkyOQ0qrsVKphZx6lbdsFVKqUlU0i7e4l0+TfRZlPFPrMFv4YpidV/ysksAms+Me81DeXm9nSBU7/DSW/g5cG2Jx+795TUqUapvzMjjfJ5YacO8H6PXH7di9Sp7ZS9fQ3DjdtyOdnw4bWDkuknz17rnDWid240ZN06TwQ0okhxKNH76Nbt+U0bZpXUSc1W3xCYB0fCTt6ONyM1ZvPTUuIffNNFT7+uEL8jGd095OLoiu9e6/ijz9ClU3GZctOc+bMPX78sToffODEJtn+L2D/55CvO5Qb6dxLJL4dtbEdnJsBpX+BQn09G93uD+GI0AmZ7EXjFIsterd2wdIykCidqnwu0MHYbENbOD/TZ1Xh/SiB9ZmJ31wUWkSwLzJK6I0vYXBwrZ24A2K7Q+Ll730jgWWWsA9Ua6yDLFK3TkVddpwkCXZjE6SrqPIUvcgZfTMaYzzkMYDT4tFFmJsdAoKgQ5hzL1inLqSPHrSrHxwdGi2k9+jRWxQqNI4kSYIVIndXJLKlhPCLLyycS19+WZnBg02cABHPYZqUg0YYWw7q7bDHIKH83XfbGDhwA126FGH8+Ia69uzMmbuKbHaiREE8ftyHAOuJgVbGXOxzKCbfMD8zTVa86GAo/qVN52/efEz69ConlYw7cWJRLDTONFSSXWmLZGmnJlDLm1tcgKTy+fEDm5cHHp52yNexfftlypePRkHUwKFFW7roj+/mWN6vmtri4cNvUKhQOgOjqro+efIO+fKNUd7nDx++b/ueiCH5bnjHPGlAo1hI4Rixkjr1MAWZYmSMRdVR1B2lfE7K6My291M4+JX638IDICix/87fzk6HTe0dVgKMGBFKz56raNEiH3PmtPDkairnNms2hwULTjJqVD3efru4xZ+8Z6eYgAPxVTXPxffc7NnHaN16vrlkUMplT516m6RJE8R+HXa+D8d+B0ELlRwS+/Hx8QgNNaVHEu/GVlhumuPG1/vTk3vg+VO1ZDMy3PkKFw3ZXtM3eS/9KIElSav+gE+VYfyXwHL8QPlGAks+uDPTqLvc7iBN4tMOnicvPu3cGHa09XCPi7tfurQZl060+yvv21B+lF1Pnj+PQErTHj0Kd3kBoO2iCl9Qnz6liYiItHBgiTLnLFP5ikLI78RkKy7j5GzbMUwIx43bz1tvLaNRo9wsWmTLh+Os++iO27btMhUqTCIkJAVnz1qk5JXjtR1Gf1XB0iaY+XtC2T9sQmAtX3/iRFfy5k3taShjPL9//3X8+OMOG9Un5QRrpVghGg02IYUM7Y0OzmU3VHZFHSgmXb78gKxZRxIYGMDTp30JDo6KONehfQcu2rWbz4wZx/jtt1q8956Vmqa3VGj1HNaBr2HfYMjbFcqPtvMcLR+Vnn2w8rVhwwWqVZtKvnypOX48CgF2DOXPBnVHH7d3DsLiopAwLbS5aeczf/4xnDhxBztuQH1aV7y8994qhg0LZeDA8gwZUtXiORaeOR27YLyryytgTT0VLS1zWSubO/c4LVvOcxupHbXz8i2Tb9rcuS1o3lzE0U1mXaIlP4qPCJfwRzA9mTpgJ5Cm2jdJC1H9+rlYurSNc/eDWdHxJygcBSHvnAf/P0pTXxWRDRHb8MS0uRayLI+Mn/enJ/GRc7UqmqpzIEcsye49n8AhU2K18IcQlNTnNgD8KIElH8dyso/l6SXU83w9Eli/uNChGCQtXPBi/KG+kcCScS6vBDe2uKa8YB0fM4dCMHQMMz5yvtxC6AA4/AMU7AMvq6UButq1DbCy2otDmO8EB0LFipPYuvUyU6Y0UfhwnLXvv9/GRx9tcLwre/cILCoMCVJB2zvOuvT942KA5Gt8TWXKZGLHjtd0HYvGwVKuXGa2bXvV1veqOnB1FVScCLmj8LPo2guDnJllxTtB5Ul2jRQsOJZjx26zZk07atQwlrPu9dcX8++/h/j++2r07y9zAZOZ1YwSQfvH/oPcXF0friVZzL4AACAASURBVCyHCn9DHlXFSjNJOCdOPJSwsAjOnu1GSIh3SvYqV57M5s2XmDGjKW3aWJU1akgbPSXPDbplzW6PjYCdPVUFuqqz7Fpr2HAmS5ee0Y38OrbhaCXh1aplZ926DraHLygA9487FKCIzW+c/v7xFZgjCrmiTixiBEE23dHup5kzm9G6dQFDutqhwwKmTTvK0KE16dPHSlzA/J1LDW1vG9K215xq5T9JskHLCzbNahsoOXKk4Ny5KBsobnQwb97RnDp1l82bO1GxYlaLB22DKCiJihoSxGt8q0hQeFiTQMRTaH5G5fmKwaJyjX76aUW++KKyc1H3V9Slc6Nz7qgb22B5BUiSFVpedO6c6I5aVReuroScnUC+U/Hx/vQsQqCpmRb9FIp/EbO3bd3gpNXGjw8mrP0ogSWs+Q8AEyTY0wupz/l6JLDWROmKfIFlFqCRNslX/zmwC7BiVNRnAAZ58Z0E1raucHIsOPPARg2Gpgyk/dwHH2CDrp9jtxofWM6OUHmy/k1fmA/rm0PastBgu/7+fc3j6Ymw5TXIXAdqrXDYux49VjBy5F4GDCjHd985T06tLc7sJvXSyrWNsLIqJM8LzU74WlTc78/RYbDrPcjRBqrOsPGjlWQ5REm536Jy5qhRe+nefYU9B4v8cklpuB0KNRZDVn1LFz3stnOnxyIrLqTqQq4ufEnCm2Sk1as3gxUrzmKnJCm8fLKzmDgztBKktp9YDPxiMgJtIblhQweqVLFStjRweLlzj1J4XOwWrxrXUfpKUG+TgT3Q0bVZgKUG1Ik6zULhTRL+pM8+q2ir0KpjF6xdxUjML4hYQcY2OgCp9VdJNWhI8PyZKrwi1vqGyq9iZUKuLgl+d5R0ne1zrVrTWLPmPJMnN6Zjx8KW08zfuXigIP3gNMzPA5I8av/IJjTnzt0jZ85RJEgQqKA1bUrYnQ2i1XEpUvzGgwdhHD/+FvnypbH8Rks2JA2BFmfd8Ownp7goVhQc/LOiOBgcHEBYmAtIKn9FXep5GZ/dhpkm0Zu29yFBcve97+gFx4e/2CWZsUVPS5pmbQLpysWc5NM2L8Wnj5ZkepDAEtLWD4HMQucK9AaiW3SKAozsMGrkqpKL+TiG4x1dBSHAFR8Cn5U/UdEwcQJO0iOBZT1YGUQNQOSetC0j+YKMBzYAP8d2f/rI730ngaU9hA4WtbHGamtXODUWEmWAAr1UzqD4tuMUaxCsDjDL/uoA93XU7roWcHEeZK4HGarE/x2Ui4tgXRNVkl6k6R1YkyazWbToFAJNr1w5W8yqNqbzw8MjSJNmmDIJDQ19nZIlRfTCyjRp3HQVoL6FJ8uVW8Enj41BllrjqRKepkePovDPeDgYbRe2a9dijB5txcEifuflgodnod5WSF/ew5bi4PRYZMW7dFnC338fVEp3pITHSCtefAL7999g2bI21KuXy9LU1TWwqhakegkaHzSyC/r61vjFigyCEvYbczVrTmPt2vNMmtSYTp2sFub69sLsTUpCEyf+FSHfPnPmbXLmTGVp6cQY2P42ZGsK1ecb1AOd3V5eDmvqQ+ri0EjmqLamJT7efLMouXKlcurd6kkPP/hgLT//LOqSZfjpJ5nmmUzmFQqHm59yEpql6+3FCN5+exljxuinkOco/lop6MqVbald2woxY/7OlYf6Wz25dHF/7rM7Kh2GmKBMhc/LZNZk+devv0v69O6XUFsLDdy925uUKa14Y52Yr8R9oHTowaIicPcQ1FoFmWPGDGjf/oQJA3n2LMI1Jcj5+eHBCaizATJW0aHjfupCE2BpsAvSWpWtuzqctU3h0kIo61jV21V38fL4bW/DyTGWocUEytCUyoWTWNBsPgjgcDOBJQpA/wDvANsAUSdqCwjk/JqD6y6lB7Jrtxl4AogijJCuy06Ts7BB+x00qxlAXIGT9E5gSTDqAVFn4ZL5Ww5Y4XldfrxcyThaOxes+xRZigHOMkT6TgLr0lJY29C9xY2G6MjaGGosdDng8e6EK6thdW33YulMMLTdAUVhNMInX5jODMPpY65vhhWVIXkeaOa4NLp79+WMGmXhvLAhY4+mIQ1tJPxXov4kPDo2FoP0udN998UDtWc9TUloGGrTw4cPn5E8+e/Kz4QQP3nyhLqNoFevlQwfvodPPqnA119HmYiaF3fHIGV+3dr0miOtrDcakuZq1aawYcNF3n23JJkzJzM0CZAx43CuX3/M3r2dKV48gyUEGjooQ2Wou9FrofG4oX2fwoGvIP+7UFYlw7e2zp0X888/h/j226p89JGxyUFp98aNR2TIMELpgiA5Eia0Kgc79APsGQC5O0PFCR4P3SsObu6EZWUhaXZocd6uyVat5jJnzglFjEkqh5x5t3rS706dFjJlyhF+/rkG/fqVsbiKITnhSXteO3debnh4BupuggyVbJr95JMNDBmyjV69SjFsmCiI628ZMgznxo3H7NvXmWLFrN4LgrwXBH58mL/FkuTUYmD3bnQx3H37rubXX3crgiQff1zeljvz1AQQ5eQs9aHmUhc9+9HhK6rA9U1QZQaExMxnJWI5Iq4jAjmSzBLe0s8/d7KEcGY6eHZL3XSRzZcX1VZUhesbodIUyBWltNqVmCwuDsLVaJRKuit98dVjrTneYkJVyQdRCN+fP1LnVLL288GSTDcTWJK02gH0Ml0mWXDKBEFkib9z4tLJxEgARnK+JML81vROYN0HmgJro0SkJiDbnincjJSrGUetGdnOkszjKeCWXyawNH6UgGAVeu0KYbVGsljsCyj2qZuhj0enxULY6vFIrUlCfRSy6vEYrR3cPQyLXoqWAFcOvX//mULkLia7fE+fxo40/eGH7QwYsF4hYBUiVjs7+C3s/VhVkqwg4M54Yje2w/LyEE2JQ7JkvyqE+CdPdiVPHv0Ix9u2nc/MmccYNqwWvXpZ7SBGhMFUU6LMQXmNX0Q9FmEFTbEqMBAiIoxLAoSFPSdRoqFKouHq1R5kzGgi2pUgrm0GlxaAM7B4Xwr6kV9hd1/I2QEqyx6RrQ0evJGvv95Kjx4lGDGiruE937v3GiVL/kOGDEm4dk32u6zMzH/YF152hbbT8G5H38CDUzA/r0o+2/6h3XFS+iolsOq7NUhJ2hlp1atPZf36C/Z8hrH008g+6eJ7aVm4tROqzYfsMn212K+/7qJv3zW0b1+QqVNtf6dH259+upGvvlLRVf37l1UUHs0JhEPfw56P/CvpGlNQYigz1dCpS5e2pn793G6H9p13lvPXX9FsmB36Efb0h1yvQiWfEtNye7wOT9SQPOVGQT6pHjLAJCE5RVR7I6HlZUgilUwvqGk0C6LULJvX7iZKZqSCsHvQ+BCkMh6x7JdXy1lhsnvHYWEBCEykihkEWSExfWjgVgksIQi25o94KvtwDroqE3KpwZbM9Fyr3/8NyKKguRPDkzyMILUEteXXyBa9E1iSzRMZFSmklnrMSKAC8KOphFBKC90xdzKOkmVcZypflD7JxfU/BJaseGakhPAHrr/YNAnR/zL66j1nrV7X/ikE6YdiUfxrHzIfhqy68/BFe87jyzAnKwQEqgS48ncUi0oS6gxKoFGjWSxZctqe1FbzbZaX/xBK/aDrkOLU2f2TsCAfBCeDdsKXaGsav8+WLZ2oUMETMKut36pVp7Bx40WmT29K27ZWxNdPrsHsTOrBHcLtCI7jNFbONv7oEszNFu09qhHYizsjkwCXLj0gW7aRily5JBpk19tsGhm6vyE3T/0DWztD5rpQSwDWtqZxqzVpkocFC1o5e8XcPm7JklM0ajRbKTmW0mMb00oPin8NRT9xuw2vnhgLsqlPn9X89ttuc5ecebd60v9oFfliQYp50qZXzl3TAC4vUzdDZFPEyiZNOsSrry6mVq0QVq1qp3t3BgxYxw8/yGa6ajbXMLQ/HP4RCvWD0v7CvhFNiPZ9DseGqYidPG+pqEIrOosGDWaybNkZxo9vQJcuGlWL6+HWFA0dvs+NFvFxvbvGnLGlM5z+B0p+Dy+J8r0B9vQWzDLxxRkxlzagy4a5XF0PrggHrAeVF9bvepn7yRzwP7OPgLxHpLT+5hZIW07lZXVEi6NxnwqVS11hL/JNs0pgRe2gMNRLRjSqycRfKt0EKmzNnyILoeqAM1B3gakLV4iUEEpJYXQmO32DAdk9i23XL3ZkggGXQO8ElhSv/wS8CWja9uHAWBPhmP02YuyDcjfjKDdAcVOtp9QMxJTAkvSsdYpWZGmOnD59mmzZpJoQAgMDCQoK4vnz50TIVr3JtJ+Hh4cjHByaybHyu+h+HhZmy4EWHCy7GSjHW5vy8+UVCLi5nfCKU4nMri4EEiRIoPRD+qOZkF/K8crPH98gwTx18Rne/ArByTJF2/c4GZODscY6Jgdjja7vDn8eGEDk1EQERIYT1viUMonS9TrNz0fAw1OElx1DwKPzyk5MUMmvYr5Ono4pKCjae0yXey+m6/TsIQlmq+pi4S1uEJw0nd1YZXd50qQjiipQs2Z5lNKpTz+tEO3zJI9W+vQjFP6rbds6UqqUyn9lfZ0Ct3Uh8OwknhcbQkCRAYovl56nuLj3nLlOz26bn1naPyEswjYhWKXKNLZvv8KsWU1p2jSP+bmP7t3h7PP00kt/K1Lx69a1p3LlrJb3270jJFhWHBKk5nmrG95/7+lxnYRrcrrKqRLW4rqiXGn9Lhci7HHjLBXvsoAcOLCs7u/y0NBrlC8/hSxZknH2bFebd3yCg5/CIRX5HRmYkPDWDxQiY/O73EffEQGXFxO8sQWRaV8mvLYtF53ce4sXn6Rx4zkUK5aeXbteMXxM48cfUsQIGjbMxbx5lo1I5d2xsQ1cmMPz0sOIyKsqncX4zdXj3gsO9uybGxlB8KykBERGEN70HJFC8m8yGdPgwZuU8jax/v3LKAnYL79US4AdziM8GJPMbVKnHsHjx+EcPfoGuXNbVCUDr60kaF0jIlMVJ7yehQvRK3MjD8YkcVKes22d4exknhf/noiCKopN6/vSpado2HA2RYqkIzT0VfPP9Zrv7dp1mbJlVUEZuX5PngidiXr9gna8TeCZv3le9CuCig/y73nEga8I2P+Z+f59XuQzgkp8bh5TmTKT2LfvBl99VYnIyADCw58zaJBlLaa9D2Ob7zVrNk9R5hTaAVFC/fzzinz8sar4qsWTEt8QXrC/w3d8fJhHBO75H0HHhxFZuD8Bpb43Zm704CTBSwoTGZyc8JZS3KKas9dJO95v3hExvcvPzSFoo7ouk+93RNtHynzVpXfE3f2wpCSRCdMT3vySf3yfoszLHa1/jXieAi/MJmhLByJTlyS8roW33PreC9jWlcAzE3he6EMo8W3crd1j+T5dvHiR3LkVxKmzCKzoElgCEhKgjgCGYrKPZLpg4iq3QFUdnyG8V8KVJVLvLwQHlhYGSR/nVbWJEZkwdxJXmi93Mo5SxD0NKCnUGEBsCSzJdFq+rqaWx4wZQ/r06ZX/hYSEUKpUKUJDQzl37pz5chcsWJBChQqxefNmrl+/bv55yZIlyZkzJ6tXr+b+famsVK1ixYpkzJiRRYsW2Uwya9asSZIkSVi8eLHNrdSoUSMCl75M0P39HE7QUf0QB0KB1pO5du0aW7ZYFg4pUqSgVq1anD17lou7JlDpyec8CMjMvpyzqFSpEkeOHOHoUU0cMm7H9PjxY9assTwTspho3LhxjGPas2ePOTYZMmRwa0xPp2Uk0fPrrE38E3eD8qHvdSpB0P3DbE78OdeDSioLJG+Mych7L7br1ORhO4J4xub0k6hUr5Ny70W9TlOnPmbYsFBatEhNly4qx0d0z9OzZ5lo124jKVIEMWFCbgWxImZ9nYpc/5BMz3cTmrA32aoNcvl5im1M2k1m/Tzpce/Fep0iI2j2qDUBJlj+otW7bN4RI0c+ZenSc/TsmZG6dS0E1fKO8GRMnTqd5NGjCI4ceZPIyGvmd0Sa50eo9uQjheMsNMdMr7/3PBmTXEPtHRExJTGBkU9ZnuQvHgdmsrn3Bg3ayeLFd0mSJJCuXfORNm066tUL0P1dvnPnQ77++hLFi6fjyy9NqkWmJErjwM/g9i4iCCSQCOU9fzldV/O73Cv3nhvfJ+3+iEiakwUBIlKjmvbe27DhGNWqzSdZskAmTcqL0c/TunUJGTr0II0bp+Ptty0xVr65+9rBtXXsSPQBl4LVJE9M31y97j1Pv7lNnr5BUPhttqUby5UnFoU8bR6ROvVQ7t59ztChIeTOnciwMT148JxXXxUmBggNbcjZsxb11+KpD5P74kDuJ32Z1QGyYauaN+ZGulynhFMVdNCxBK05nPA1m+/T1Knr6dhxO6lTy/coj+5jqldvHGvXWuaHn31WgX79iitzo3JPhpDl+Xb2JelF8ZbDDJ8bxfp9cuMdIado36cUC1Mr3zZ5zy1JNd9mbvTxx+c5dOgJWil3v35FqFbtmcvzvQEDznH06FPeeCMPuXNn4cyZszRrlkTxU/7J12R+vhPKjWL1ubwez8t1ufcMmJcXfDaVQmFTeZztNZJU/8eltYazY8qa6CJlb/UkPFE2FgVb+A/dnZcbfe8Zuda4tqQDGW9PU8qNZLZ6PUtvMtT83bU14bOtioL5ncC8rEuioi394fuk5/rJ2XsvXdKnVLnenkgCWZx0EuEB6vNtfe9lD61N8shLbE30CYnytI6ztXtsY7px4wZduyobmiLT7AyhuruAHmnjA2AQUAdwrLplfuP6xz/0RmAZMWpXM45S3ymZxXelqMvUodgSWL6NwFpTn4ArK5QHNoAIou5eaUG33rWPPPA1QQc+IyJHeyIqTlQWFbHtXml+4sWuSDRIucglpQm4HUp4lblEZmmkLwJrZloCwu4QVi8UUqlS4s6iYORYf9y9Cl6Qk4Anlwmvu4PgDGUc7hKPGrWfnj1X0ahRbubObabEJTpE4y+/7OajjzYoCCNBGmlmg8BaUYHA27sIrzybwBzN4w8CSxb/8zITIGUWjQ4QlqyAzfu0e/dVjB9/gC+/rMhHH6m7ymKeILAEUZEqlToBvX27FylSqMhO5X68tIjgTS0hbRme193qnwis4GAiZ2dV7tGwOtsgTSmbe+/mzUdkyvSXMt6HD3uTNGki13ZOnUT/TZhwkG7dVtKwYW7mzVOfAc0SLC0G94/yvPRweHpNQW5GFv3M5xFY0mfpe2SClAoC02ZMCRJw9+4TUqf+Q/nxjRvvkCpVYkPH1LPnakaP3s/gweUZPNiyEam8O5aWVAhyw6stITKTSsbt8wgs6ePSIgTcP054zTVEpreQK2vvw9Kl/0HQfXPmNKVx4zyGjenQoZuULDkREda4fr2Hzbsg6NQoAnf1IjJbC8IrqZxcYn4zjzg8BPZ/RkTut3he5k+bvp87d5ecOUcrGynyfggODnIdXRHDO6J58zksWHCKunVDqFQpq4I++vzzSioCa3V1Am9uIbziNIJzt4vXCKyxYw/Qo8cqJfaCRHv8+H2H1QWxzWE7dlzMrFnHGTq0Bn36lLF5lwetqkrgrW1QdTbhWZrGXwTW8eEE7elLZI7WBFSdaQgCK/DKMoI2NCUyTSnC5btqMn+cw0bte3SVLdHdexGhnxBw+FslOfu8QD8CEiQjsMSXrs0jjg+HXe8Rka0Fz03vUH/4PulaweIKmnZRfkV4I7zaYiIzST7Gav308ApB86SICsKaXyEwcXp/QGA5m8CSYckDJ9Cz3tqnFhBUjUy2oiNx/9CUvJLSQU8kbUWtIURe01bzPcndLrCZAHrpP0YksATGJhh9QWAJ0ZhkFWVb6zTgjsSSqxlHQV2JhJeltk4tThaTlZmQvDiWTLME3XdUCKVPmvyvMitMCB0ccbtFuWPWNYeL86H0UCikwtL/MyFMbgyXFkP5sZBXKl11Mmt1jDa3IaF+JNs69dAYN5pUbe3VkEm0GuxtzZpz1Ko1nbx5U3PihG35VNSjGzeexeLFp/nllxr07WuldGV9oFk1ajNkqGjMuOLK64ICcP841FkPGeVVarGBA9fz3Xfb6dPnZYUfTA87c+YuuXOPVlSbHj/uoyRRzWbmOKoHtZbp0Vzc+FhUFO4ehForIbOtkpjA3hMmHEp4eATnz3cne3Z3dUZiHtqQIVv55JONvPFGUcaNa2B7sKZiVGUmhLSOmxi50+qTGzDbpJrW4ZmdwIgoXH3//Q6ePAlXVNzSpUvsvMKVG/1p2nQ2Cxee4q+/6tKtWwlbD3OyweNL4KnUuRv98uiUZRXg5jaoNhey2/OztmgxF+FxGz68Nu++W8qjpmI6ecWKM9SrN1MppTtw4A3bQw98A/sGQd63oLyVxLlhvdHZ8bHhsLMX5GgFVWfZOH/2TBVfEBNF3HTp1N1+vey777YxcOAGOncuwoQJDW3dahymddZBxmp6NRk3fqy5a9JXUd/DVtw13botU5LPmrnL51ahwiS2bbvMnDnNadEiimru/Hzw4CTU2QAZo6jtxk1UjGn19ETY8hpIor72SoPamARbXjW2DWN6boxX7d6qvQYy1XC9jd0fwJGfQUqY/UVkxPVR6nfG5lfhzCQQ4vxiUYqnzs+FDS1VEEHjA/q1aYAnN1UINVG7bqZElizwhaBRyhCvmpQFJe8y0NRlKRn8CuhkErXTRiJEu/Zku47HKZwlc4BiJm5zbaGg8SZZST4bEKhoXOqdwJLZt8h7TDIlrSRbJ7hzkWtsZPrjzuhcyTgmBvJFaeRrkwLi+8AxwIJNdtwb30pg7f4Qjgi1mMmKfQnFLFB9uyEIF9ecLPDkqkNpaHcuQLw5Z+ubcGo8lBgCRbTnW4fR3T8BC/KrilFCwmidCNDBvc+6WF4ZbmxWJ/6yAHBgly8/IGvWkQovxcOH75M4scr3FtVEkUkWvLJoeOedEmTKlNTxgnd6ClXUoOlxSBH1UffZSDnXsRgWrL/8spP//W8tnToVZtKkxs75i+UomezLpD8kJAVnz6rcQGaLRWVOlw4Y7UQWTiKf/ugshLSDlIXtSD+zZPmTK1ceKsTfQgBuhL333iqljHbgwPIMGWKbmGRhYbh3BGqvhUzCw+knFhEOU01Ul62uQWJTMsvUfXcEHDwZuYZGWriwJY0by/6ZlU1LAs+fQLPTkDyXJ81499w1jeDyEig/DvJGSRzJFmzvVfzxR6iCyPz2W+OSHH//fYAuXZZSr14uli2TfUkr2/0/OPILFPZTUY0zU2FzR8hYHepEFdCG1KmHcffuUw4ffoNChSxlnHrcCBoR/4AB5fjuuyjXLwbVPj3a9roPLdGZ502oILS4Fvv44/V8+63KZyOxSJw4yK1kt/Yu37XrNUqXNgmQaM3MSA1hd6HJEUhpJVbi9UAY3ODFxbCuMaQpDQ13GdPY0WEKYoiQtlDFgro0pjE/8KptjJf7C/JJXsFF29AWzs+E0r9CIVmm/mcxRuD4n7DjXccCMloyMF93KDfSpwPpZgJLxiQ5FUFVCTGmcOu8Z0Jmye/kI3YG0BRJ5N85HQQiOqJ4RzEThJWAgkTWVHI6UgIiH0Opd5XSxDhhytc7gSXIJ9muEjVCKeyXbVAZrGwNSjmfu1qrrmYco16A2EoIox7vWwksWYTJBDH8vkMFF7u77eF5mBcCoobX9h4EqyTG/5k86h/DoW+hwHtQxsLb4nFsrq6DVTUgeT5odtxjd37jYG0TuLRI3XmXHXgHJiiXNGn+UBYB+/Z1plgx24WudkqMEtjaQbIIlcWoWHxEupkXrPYIwYkTD/Haa4upUycnK1aIAq7nNn/+CZo3n0vZspnZvv1VW4f7PoUDX0H+d6GshefC81a96MEJ2eVixSZw4MANli9vQ926+ic3BIk0c+YxDh68qZTRSqw//9xSDsasDPD0hlI2Smq19NhvTFsUNj4MqWQD0NaCgn5CKlKDgwMICxNxYuMsc+YRXL36iN27X6NUKavFa/hjM5G/8j1MYAzKzpCRLSoOQvBb6icQlG8UifYff9xO//7reeWVwkycqE9S29E4vv12Gx9/vIEuXYowfnwUpNDWN9QkcYlvoYhwxPqZXV4Ba+pBqqLQ2IIC0kYRrfqiDsPs0GEB06YdtVfcjXhuSg5HQssrkCRKMkaHtr3u4vhfsOMdFUkoiMIoljfvaEXsRdQeRfXRVXv6NJzEiX9VTrt+/V3Sp7ea9z5/BtNMOk2tb0AifRORrvbV0OOvb4EVlSBZLmguhS8GmKxJDnwB+d6BcmrZ7Qttu/rCUUk+uakYurQc3NoBVedAjhYvdCidGvztvQrpPcEp1HVAoBUASNsErvgP5FY5DX3VPEhgeXtIwhFRy0TPdNeUwBJCbfmZJLGMg3/HMFK9E1iPAEFdScbPOoEl8LNDgKCj3DVXMo5R2/DvBJaMxpWSwHOzQFSX0pSEhpJT/M/METjyG+zuAyHtocpU/QJzZgps7hTtLq5+DfmYp82vwZmJ6gKrcPQLVA3aP316U9q2dbz7+ccfu+nde7UyQOHBePpUVYSysUcXYG4OCAgGKVuKb0g3czx/hMKysWGx5cvPUL/+TEXJce/ezrrcCKNH70OU+Jo0ycOCBVEQdDt6gXAzFBkEJQSB7Kc2WSY3EWpCv6OtyquMqFataaxZc15BtQm6TW+LEYkkC9VpCSEywj8XqvPzwoNTDpG+3kRghYWppV4CPr56tQcZM1rJkPvzO0ObjMu9K8mrKOjrqVOP0LHjQqpVy866dR30vnXN/nr1Wsnw4Xv4+OPyfPNNFAShNjdxF31gWK+ddHxrNyx9GZJkgZaqApi1Va48mc2bLzFzZjNat7blJXSyhWgPq159KuvXX2Dq1Ca0b2+VAH56EwSBJeagPNfTduPkfG1emqEy1LVnE9HKYX/9tSbvv/+yy108efIO+fKNIUmSYAXpbVMO/+gSzM0GAYHQIUz9O77a3SOwqLCiuEtbERAzwHa+pwgfUORjgmCCsQAAIABJREFURNXxhbfjI2FHD8jaBGq4QQc0OxM8uQYNdkPaOMkF+NcllHnTrLQQdk9d48paV0w2eWamhogwaHYKkisKfz5rfpTAug3IS1kASULBJFwwosImUHfZ9YkTlIzeCSwZnOAnpfDaOoH1OiBbc5Lc8gfzLQSWRExDEuR6BSpNjDmGoQPg8A8qlFUmlf+ZJQKxlAu4HarDP0Hoh5CzE1SWCtoXxHb2hmN/QJFPoIRU6jq2N95YghBZf/FFJT79tJLDg0qU+Jt9+64rhLnPn0fikAfj9h5YUgpEUr7V5fgX5J3vw7Hf4aWBUHKIzfj27LlGqVL/kDlzMi5f7qHL2L/+eguDB2/irbeKMWaM8Dta2aZOcHYKlP4FCjlIJurSA4OdOIHAat9+AdOnH+W332rx3nulDelQQIBaAp4gQSDPnvWztOHvC9WlZeHWTqi+ALI1sYmdIM82brzIqlXnKFUqA82a5XOrLMiZC3L+/D1CQkYp8X3ypK9Srmy22/tgSQlInAlaXXHGne8cs/8L2C8iyY75LzdtukiVKlPInTsVp04Jut8Ya9VqHnPmHHfMtWXmcJsBIVHKC43pjr5eH56DeTlVDrf2T+02RbTEyp9/1uGdd0wLJZ16ULDgWI4du83ate2pXj2Hxeu9o7CwkLFJCJ3G4LQbDaUu5XtSxhfFhELgq6+2Ov4WOdGIxrVZsGBaRVHXxrR3QKIM0PqaE978+BBJhEhCRKxDuC06Ra9haRxEpX6GwlbfM738+5ufK6thdW1IkR+aCkuNC2aNEG59ExJZFHRd8PLiHbq6PlxZDmWGQwHRbBMGKFMlTJKs0OKCz29w+1ECS0oEBWkl0NnJQBpAFnyS75HEVtG4uAH1TmAJqZDUocjXY4WJ80pqL6Ws8EsTS35cjNPVNn0vgXVpKaxtqNbuO/j42wxwZU24tjbGsi5XAxJvjr+6FlbVhJSFoMlh/YalQYgFNVPqR/38+ronJ8vMfvhhOwMGrKdDh0JMmWK70NWGmDbtMG7ffsqSJa3ZseMKz59H2C94Yyn38PVwxdo/bcHqIPl86dIDsmUbqST4JAlis0iP1bHjAzRkxSefVODrr6MQ265pAJeXQYUJkEcfxJeb3XT/NCl1uLlVHUeqYipPmxV5sDju2XMlI0bsYdCgCnz1lf7kvl9+uZnPPttsHoNNYta8UE0NbWWTy89Mm0RGc4/8889BOndeomvZq6MIxcjlZn7nF4YmAgT3I1vXFC4ulOyViiKMgsA6d+4eOXNGk7jTcZgxkmMvKgJ3D0GtVZBZKgr8zMIfwvTkaqcdlJi+/fYyxozZ73hDxcOhpkz5O/fvP+Po0TcpUMBq4Xp9M6yoDMnzQLPYNIc87IS3Tr9zABYXU8v3pIwvis2YcZR27RY4Lmd3oo8aT1vdujlZvjxKif2VVbC6DqR6CRofdMKbHx8i6JOpJpEwo8ol1zSEy0uhwnjIo1Ht+HHMPO36o4swN7uK8m7/2E7QJEb32hwgOLn6/olvVQWexja68/d/qajHmkEDMte7vhGurlIJ3HO0sZvrGdUVd/36UQJLdrcF1j7bxDEukxKBI98EhOJJLZ3xsumdwBJ/H5vY7zVImUjmyfZzDKzjXh517M35XgLryXWYbSIYbnsXEqR0PIq9n8Lh7yHiGeTvCYnS+/xDHPvl0PGIu4dh0UuQQOcF48b2cG76i6f6eGQo7O4HOTtCZUnMOzaNa0lIsoUsO6rdvPmY9OlVnqWbN3uSNm00ak/mUs0aUEcQrPHMjv4Bu3qrH9+qM2wGZ4QiVtu28xV+pt9/r0Xv3lHQRxovQ7X5kL2p/wbarKZYF2ottxuHIIW++GIL3buXYOTIurqP84MP1vLzzzuVeemnn6qqmWYOrOubYEUV/+XO29QRzk6NFqUXIypCx0jPnn2M1q3nU6FCFrZsecXWcyylSzp2Q39XG9rB+RkgZVeZ69txYIl6ppRORkREcunSO2TJYkrE6NyTHDn+4sKF+2zb9grlyqkS5WabLYIxV2xLOXRu31B3UncqvIoRTx2S/H/yyQaGDNmmKGkOG2arYupJvx4+fEby5L8rLu7e7U3KlCaOJvnBhfmwvjmkKwf1RcMoHtjjK6q4kJTvtRfVUlvhqqNHb1Go0DiSJg3m/v33Xd6g0UqWHaKJjULe++plkYSsJGaNErpZVh5ubodq8yB7M1+Ngvf6Je+QGSIu9NB1kYDLy2FNfb9QzfNeQJ1o6cpKWF0XkuWE5mdA1r4HraguYhM7c6IJow/xowSWo1DIjovsumpKhEaHy86/3gksrQFJ/4s8mMymZMvTWalGrwcgmgZ9L4ElHZ2XCx6ehdqrIVNNx13f0RuO/2H5nR88xF696M9uw0zTTmf7JxBkNWn0pCOyCJXFqCiyiDLLi2JC3iskvlkaQs3F0Y76+PHbFCgwVuGnePDAfnK6ZMkpGjWaTYECaTh61DEZvOL86O+w6/34q35zZjJsfgUy1YLaq+zimTbtH9y+/UQ3Raxq1aayYcMFpk1rQrt2UUi4NWlo4SuRBbS/2qUlsLZRtJyAw4eH0qvXKlq3zs/Mmc11H+XOnVcoW3YiWbIk49KlKKWfF+bB+haQrgLU36J724Y7jIUnTXvuZVEqz70NL42OndP48xxewxOjYXs3yNYMqs/TsVUvuLq2HlZWj7E0Jcbkkg5dlORYwoS/KGXdFy50J1s2KxJ86+SPLCJkMeGPNicbPL4EDXZCWlv+pV9/3UXfvmto374gU6fql8g/deoOefNGw9l0chxsewuyNoIai/wxovZ9jgUZJIhrSeg9eRLO8eNvkS+fVKk4bxpSziFNgXljqDVUnem8U389cm4IPDoP9bZBehEM09nm54cHJ1QuM3+eG+gZliWl4XYouLrhp32f4tOzrmdco/MVdl/luxL+UFFB3/MR3DcJaEk5uHAH+rj5UQJLVDXOR5Oskt+di4tQ65HA+sWFjvtLsbRvJrA2tIHzs6DkD/CSKGg6ME3pRX4VmBA6CADuPzNHQJlwJ1YRas3PQjLX1W4cRnNeHnh4+sX7oJ+fCxtaxroAF6RAsmS/ISii06ffJleuVDZh/OyzTXz55RZee+0l/vmnUfQ3rLlksQeUHRH/bmytVDh1CWgk6ri2pnGmrFvXnmrVrDhT3IxEtBws4k8SvZLwbXwIUulPbu5ml10/7dYuWFoGhBeh5UW786dNO0KHDsYRYQt3kHAIlSuXmW3boig9nhwL27q6T/7qejT0PSOW5/Hx4zCSJlXVXm/d6kWaNJ7ouETf9YED1/N/9s4CPKprieM/kuDu7u7u7u5eCrSU4lanLdKW+quipVhxdwju7u4SCB7cJSR53+zuDSt3s3aT7C4738f3+pJz5szMvbn33Dkz///PP++lf/+SjBxpViVz4mc48qW+1UVaXjxJIgGZrVcMV6o0i127ogdkXEJ169ZTMmQYp6sglNblgAAjAGwBzZ1nAMz3NIZH4/sgsBg8OAY110DGeiZ3yMyZJ3n33UAdM54w5GklCn5ZrlzJuXDBDL/s5P/g8OeQozNUElJvLxGFtVRgMAQOw0xKl57OwYO3WLiwGa1aOQaYLwQnQnQyZUoD3nvPDJLl6HA4/t3bw5oXWBweHIUaqyGTGbalFreSt+wNtIiFomN7Bwieq4cQMSPgiXKZI0PgxA+Q10v3tFrG2FyXUv1r/PM4cSEi1KLdPjrNcFa3ByWwwgApvTYHEBQ6V/mZaTmtswFxcJ4WCSzzPh45vhJnhGJRRN5C4vwBA+WigybGynD3TGApG/Fs7aDKXPXArCgEj07pe7FVWItiJZrutqhyOlV/L6Qu67p1NloQXF/AjTXYAGY1trxIkSmcOHGXwMBWNGwoxKRvpEGDBaxZc4nRo2vTt28ULCz7+sC5cVBkKBQTWD0vk7v7YE05SJQVWlgealStOlsHjD1/flPatFFnc3QkIilSjOLhw5c60FsBv40Ub6JxtwHSvHFjMLVrz6NgwVScPGkG/utIMK2MHTnyIAMHblSv8Dr5i/7k0BOTK+Lv6b/g4EdRsrpKa7C0CAtzpjBoRod07RrItGkn+fnnqnzxRXnTJQ59Dqf+5zzFeXQYbK9OY5B/ARj3N2DbGM1XSAj++KMGH31Uxl7Ndo+ThIIkFlTJIzyZ4dE4Ahtqwa1NUGkm5HjHJDbr1l2iXr0FFCmShmPHtMP7WbjwLG3aLKNSpUzsEMIMY1GIePJ/BKUdOSO2+7LGzsBI1lL1yh2F7OWbbyoxfLg62Ys1wwsWnMzp0/d0SUZJNprIvr5wbqz37hvMg6Lg4FaaBTk6anutvWlvoGVklCRp7u5QfoL9mhXm6RI/Q6Ev7J/nGwmry8O9vW8ikbYq1N2qJz2T718zvFN3C5kHJbDCAWGGuG0WQym5li47I9rnmIuyFgksY2ulwqoGIIi/CiKt1AHLsaeCYh9z3jm/knsmsJSeX2vAnlKiPTcJRLyC+vtAWmc84I/Y+cvk5EyFOcvRUl9ry724A4sMH2ZatiU66V6MTotk+EoHrW5FubSCt2T+oSUtKqlTj+bBg5fs3/8upUtnsK5nW1u4sgBKj4T8/WPU1RhZ7PEFWJ4HAhJDO8vO69atl7JokRU2MAcNlFaNhAn/0s26f78fKVIYVce8vAcL5XBFIBrVP5wdXC72hhuz/LS5D/FSmNhy7NhtihWbStq0CQkJ6au5nQoG1kcfleaPP8xav4W5VBhMPZX8IWg67OoCGdTxxSSYwpwpDJorV7aiUSPTxLVWwa5TZ56O7XDatIZ07lzYVK1UuEmlm9C9C+27J4m0Rwggs7zHhVUpkWxNTCXK+0sDX1esuEDTpospXTo9+/d3NtXowPNfA1OiT0UU7xWF/TV9+kTcvGlgu9LAEqV1uVWrvCxcaNa6rNyzxb6HIl9rsJqbqIjETloCWSzbtf/4Yz+ffLIZ1ZhE4UJERARJkvzNs2dW2g+3t4Pg+VD6b8g/wE2CEU1mCJi14LHKQXamJvqWWC0/5I33BtKmJe1aPoGgmbDrXUhXDepssT8i66rB7W1QaTbk6GD/PN9I0AHgF9ITnHhgx5EHJLCU05OBgGRlnxnddlKoJKeFUqAUKxgjWiewpD9D6q/NaT6knlfQczN5yN+ceyawjPGb1OhWFbwMAW6XZIKAZfrEMgKbm8L1FVBuAuTp7nqEIima00Br8wS16+rdWsPTK7A0m/7lIcm7KBhUhg7dzvff7+bDD4vx779v2jQU8NYECQJ49Kg/ceNGUY0anSeL7hBoGxhtvXuv459/jjB8eEVLhkYH7b98+SE5ckwgXjx/XrwYZIpP9Pg8LM8LwozT7rGDmt1w+DwBWH0CTc5CsrwmBt648YRMmf7RgQaHhmrD7mi8QJQVMoIfJzhynnr6em0lbGkCKUtBQymytpRmzRazfPkFHUC+AOVHhxQqNJlTp+6xfn1batc2w2Ha2hKuLoGy4yBvr+hYPnp12gBJ//vvAwwatIk2bfIxf772gMrjxx+hV691NG2am2XLWpr6Gl2svtEbUUvte3vB+fFQZLjFx/61a4/JkmW8puyvYsCQIdv54Yfd9O1bgtGj65jaJLh4go9X9h/I2zOmoxF9621uDNcDofwkyG1Z7bp+/WXq1p1P3rwpOXs2CixMMwuNSWCePx+E7CVMxNv3DcbOSvXJsWFvfqI1Du6jc7AiHwQkhXaPou9e8TTNd/fDmrKQID20umm/9Uuyw7NgqLsT0upJXnxiZwSUe12+PwQWRut73U4znB3mAQkspcOuOiAgrcbAYvLflwwkfQbwMWcj4dw8rRNY8qUjKJebzcyRY+dlgBH6p3MGx9As90xgifMKeGLNtZDRjDHr8Fdw8ifI0QkqzYihUHngMpGnmyOgyBDXHVBAoq3gFrm+gBtrECDF+QZGzHZPIUAhH7W0edasU3TqtJIqVTKzbdubsvZp007QtesqKlfOzPbtNsrdVxaFh8dB7f534zDZbZqu4kJ6+MOh5XVIaMr4pWCF9e5dnLFjXWPM27v3BuXLzyRr1qQEB5t9JN3ZC2vLQ6Js0OKy3ea77cBIjLodkNa0NSU0NIx48f7UmX77dh/SpLF+Dzvjn4JRpNr2qSTTy0+E3PZ/sDljR7TM2f0BXJwMiXNArm6qFb99+qxj3LgjfP11Bb7/vkq0mJE8+UgePXqlTm4gIOhyuOOpBBtR4DNJMBWMtfLlM7J7txkDo4vRFobOLVuusnnzFcqUyUDjxjlNE+cK+26aSpCxgedWfB/5Gk78CPn6QZlRJlGLDvZXWaB79zVMmnSMESMqM2SI2Yfruqp6SvgqCyBbaxevohtN39UVgqZBiV+g0OcWhhnjrQnpQ6JE9lX3HDp0i1KlpmO1Sk7ZN9RaBxnMkoVuFB7NTJkdoP9blEPsjlIgoaHc2QNrK7xhf9NQtUerCn0E8w3Yrm0eQDxTnFdV38Jf6zF5dRW21yCRp9R4uMmVkmpDgcspOtRj2gaNI+cBCSwxV3ALVgNShXXMTa68zgytE1iCNlkV+ASQxlShV6wA/M/QQiithZ4g7pvAUmjLi/8Ihb80jaXCglFxOuQ0Awv2hKjHlI1Kya5sVuOnc33TfX4i7P3QuxiD7L0Wgv+lS7hYb3FRVClYKmnSJOT27TetWsoH7scfl+b3362waypKFmWAF7c8l7LdnrguTAOCfdPoOKQwbYdq1Gghq1YF6fCUihdPhzA3ffONc9W7UhUj1TFlyqRn3z6z1iAFTD5lCX2sPV3WVIC7e6DqYsjawsKblClH6VpYT516nwIFDK2TGvmssMRJckGSDCaypiLc3Q3V1FtqNDIh+tTsHwhnR77Rr3IC+tNPe/jqq2107VqY//5rqLktT568ImlSvQ0PH/YnWTIjZlnZ4Apm3ssQyPme/qNLy3Yazb1RUbihDtzaAFbe6wrLZaZMSbh2TdsKsxEjdjFs2I5Io777rjJDhxolW7a0gGvC7CjV3uEedwIe6djpP+Hgx5C9I1SeZXERFKxALZ8PTZosYuXKi0yYUI/u3YuZrrmiIDw6DbU3QXpB5fASOfAxnPkTCn4GJX9VdSp9+rGEhDxj795OlC1r9ry0EoalS8/TosUSypbNwN69Knvft2HfoMQmuiuwrgXClsZRVt16yd3quBtKtay9+LrCKi/s8roOhue+rhnHI+7RMzwkgSUxltYiOfmNlUoraxdZ6wSWHF3/BkhtsHJ08hqYBAht3lMPudvcN4F16nc49ClkbaWnDlXk+U1YbHjZS/tggnQeEupYMFMpY9dq033sOzg2HBwFb4wF16NlyYVp4eUdaHQMUpix/xgt+PTpKx1Ntu5paFTpojAPzZ3bhHbtClg30SRZdgUSZYkWd2Jd6fJ8ejpgwVEQPAUjad9+GfPmndV1ako4LD4oHTB+woSj9OixliZNcrF8eSvTmZdmwc5OkL4W1N7ggFY3HRrZNvwv5DFj/ALy5p3I+fMP2Lq1A1WrandfCftm/Ph/IjhvklyQJIOJLMsDTy54LnupMci4FQyKGTNO0rmz9ixuShz799/A6NGHSJIkLp9/Xs40qRvdH3Mxcbsrh1al/oACH1msaFy18uLFR7qWYC3Fz+833bMmIEBabOVs0kiO/wBHDVXMHohBEunJxWmwu6tVLLfoeD4o770VK1rSuHFu07ja+U7V8jrHiC6pcpNqt1zvQ4XJqksqeHaTJtWnW7eidpk1atRBBgzYqN5GaweOnF2LeMogSdo/OQ+XZkKCjJCnh7ZJ+6AZsKuzvpJNKtp88iYCSrVvxRmQ045qWAX2JUluaHbeF8m3LAIelMCSFoWXwGB3ukRaJ7AU3wSRXt7Iol/+Kj0lcaXY774JLIX1zZylTNmACWBjg/3udI+5ny1XlsA2A5aHFpvuvT3h/L+q+Bnu53w0WBSZcNkG6aJuEcqefTzBwY/Ztq0DVapk4dmzUJInH4V86F++3INs2QztiGpmvnoAC4QTQoDFn4O/Eeh4NLgVayqjqBbauvUK1avrGUjlQ/XlS8sPWnvt/v77XQwduoMPPijKxIlmVNtnRsOB/pC1DVSdb69K9x2ntLpZAUVW2vwWLWpOy5amGFmuOBUc/Ijs2f8lblw/JLkgOFsmYoNW3pW1Y2SukrxXFlOpwNq8OZiaNec5jGtjr/3duq1iypQT6kldybzMNmBBavGst9coLccpVW6FBkOJnyw0S3JUyBik1S0o6ENy5LCjdcVO+2xWYCnPKk9nPbaB5Va58ix27rzOggXNaN1aiLVdl8yZ/+H69SeWxCU22shdXzkWNcg+SfZLmZtBdancs5SPPtrEX38dYODAUvz1Vy27jP3ss8389tt+VKu4beBK2rWApw2KxGVNDa3vaGv9mZFwYCBExYau7Yqeo21PD7gwwX62S4UExVsOCj3nSrmFpR6UwJK++i6GfI4kGMxzOkLgF+MSXQmsGHdE4wXdN4F1+Es4+bPe3YKfg39C/emK0DBfng2Fv4bi32scDi9Tt38AnDXCuXAV+G9zE7i+EsqpV3d4WfQs3VldDu7tAztYHfPkmcCFCw91IO43bz4lKOiB7uNTKNqvX+9lCiRuvlIkeKiXAItbuzGiALr95JNN/PHHG7BsVyqwlMqVr74qzw8/SOe3kSiJCTm9LTfe82/hw4Ph5C+QfyCU1jMvGkvz5otZtuwC48fXpUcP7YDGd+y4RpUqs8mRIxlBQT1MFxXWWGGYE5GPjPjati7GyEWT0/7Tf8Drx5CnJyTIYHHaf+HCA/LkmUjChAE8fTow6r9xJ4yeOvU4770nEA0qSV0FF1LR6+qz3gn7XJ6iVDkJxlgFKWa3lNy5J3Dx4kPNKwgFc09aQENDwxkwoBQpU8Y3bVleUQQenYBSf4LgIXoq6/Gd3bC2olVcH2lPkza1cePq0KtXCZcvqbR+S2VmWJhKZaY3McCaR+rKItjWGgQzrd6b1lTjYVOmHKNbtzXUqpWNDRva2RVrhSjjr79qMnBgadM5j87CivxvF+i48WGfsBkLq7FWcnQ4HP8O8vaGsmO10uodeoRRWJiFs7WHKnNs+3T8ezg6NMqKRNtKfCM8NQIelMBSwNzVQi1QUfadNGh8oaIrgSW8ltkM4F/GJguQuyeI+yaw1FoihBp8cXo9bk4d21UwnnABotXGI0PhxA96iLYCn+pf7q7goijYY9VXQObG0Wq6WyrfWB9uroUKUyGXJOmti3KSrYyoWTMrmzZdoXnzPCxZYolNZKLp9i5YV0kPGN08yC1D4bJRkhC4uhgeHIUM9SBNRZN7c9gwPZOjFJZ8+mlZEicOcBoDq127Zcyff5a//66l+zg1kQOD4MzfYKXqw2U/Y1qB0nqd/R2oPNNi9Q8+WM3kycd1IOMCNq6VzJlzmo4dV+jaEqU90USUtm8B2m0vdOTatn5p5YNNPavLwL0DVhPYL1681lUIidy505fUqRPaVOnIgFq15uqeIVLdJtVIJkndff3g3BiImwIKfOyZCZbIqpWmUF19C1Wz5lwd0PrMmY15552CjoQvyrFvDbubjcORDz9cw8SJx1xq2TYOdEjIU9KnH6erGpQqWhPmXcWWuMmg7UPNrqVbKFJappLmg6ZnVE3q0WMNEyYcQ7Ay+/cvqfubtoXzWLHiTHbvvoFqBe3tnbCuMiTJBc0uuEUYot0I2SAIoLgcLDQ+BcmjgGZw1Jj9/eHsaN9huVrcri6Hrc3AHuxQ2etdWwH3D0C6mnq4CFe+Qxy9jr7xsR4BD0pgxXqs1AzQOoGVS0hxAGlcl6ycol/+W8RTdujum8CSKM6SMIbrI1p7o57qfk05iJtcf5LvZ0Yh7Ja3XiwbtTw/PD4LtTZABheTx4vSw4sQ7wYWj+pybe8AwXOh1F9QQIgqrItQkguoteyvjKVOnexUrpwp6o3q1WWwtTmkKgsNhCPCC8UOzJ6cOf/l0qVH7NjRkUqV5FHlnFSvPoetW69igT2mS6ItgQdHVJNozq0Wy7OUUn0ruB2DB2/ll1/2MmhQaf780waRgAOu/O9/e/n88626pIIkF0zkwXEILArx00Brwcj0UImsQJ0AebqrOpEu3Rhu337O4cNddOQDWkqpUtM4dChEl1wQMSE2uLUZNtSEZPmhyWktl405XUrLe+ryUH+36rpdugQyffpJfvqpKoMHl9fMNoV4wyq724pC8OiUNu9Rzax2QpGNNrOvv97Gjz/uoV+/kowaVduJBUynHD16m+LFp5I2bUJCQt4QmuhGRR7U5ITmF11ey60UPDgBgUUgXipoc1fVNDmkGTHizX1uT5Wx1XZMWeHqUtjaAlKXg/p73Coc0WrMyiLw8ATUXAMZ62m31I5OcHkWWMHk024hD9T06AysKAD+iUAq3yRDbU3s2Ot5YAR8JjsQAV8Cy4FgqQzVOoG1XPaPgKDkypu3HCB9Eb8DnxqYCF2zOGZmu28CK/KhJ5fOkAUQqvtnwZCsoL4v3ZfFt32XbGkG15ZDmTGQr4/t8dZGhL2CuQbWq1YhkCCt87o8deaqMvpTpKLf6NmoomgjUTBVAgL8dLhXxmJzo3phMuz5ADI2hJqBnhot23YrFNgSy3csKbCVaosZMxrRqZMUuzou33yzQwd8fffuC7p1K0LWrEnfJA+9cWOlsCqmKA6NDlsE7Pff9/Hpp1vo1KkgM2ZoV0U5YMAGRo06xODB5fjpJ1NAfiKTKwWgySnHL6K7zNjTHS5MgmIjoIgB0NvMNgWwevnyljRpYgZY7aIfdevOZ/36y/z3XwO6djUjkbg8F3Z00J9uCymCJ4pSQZLYekJDSbD06VOCMWPqaObl4sXnaNVqKeXKZWDPHhV2twWp4dU9VcZUzYyICUXGuFMqdPaCySTYTO3b52fOnKYuW7RmTRANGiykWLG0HDliRs4tVRlbmnrnQc3zW7A4g/5su0Oo1apThThAsAMOU/6GAAAgAElEQVRfvYoaXkWw3xIk+FN3KBYS0oe0aYVLykgiWaIbQ40VLl87j1GwqRHcWAXlrB8sOOXLpgZwYw1U+A9yeQqxvFOeOj5J193xo77AoMAn+uICa99jcugth98ifnGhwyvH1/PN8OgIeFgCS3BGehrwzdsA1wChL5d2mO2xcSG0TmAJWqCUsxwVRmtDAkvqhOVnksQqGRtOOrGm+yawpDpCAFMLfgprysPDY6bueSLGhxMXyOUp0qcu/er5BkCZv51X9zQYlmbXv4Dav3g7aXDXVYPb2/T3pSSvorgHJXHi7++no2KX/5aEVni4nYDkJ3+Fw19Ajs5QaZrz18ydZ9qRPOrWbTVTprjW7mYTnHmWAF9HQJwA6BjqzhGzz7Z7B2F1aUiYEVpet5ij4CjVq5eDNWvk3ayNtGy5hCVLzjNmTG369DF7/QUvgO1tIW0VqLtNmwVjQ8uRIfqW7Lx9oexoVQsUjLGxY+vQu7frGELGi+TLN4lz5+6zaVM7atQQ5AIj8QbAYTuw//755zC9e6+nadPcLFtmICjR4F74++8DDBq0SZ3dzRjDrdVtSJBGgxVjUUUk899RSGHKfjdz5knefVc7Js0onzcX/4Pd70PGBlBzVSwGJBqWtuOesfluMjPr4sUH5M49kQQJAnj2TAVj78TPcORLyPUeVJgSDU65qcq9veD8ePsBxe11wwHMU3tVes04O/Zvkb5GsqEbihF8325ecxvY64gHJbBaA9MBwd+QpJWcnEuRUj+gkeGfvW5rNk7rBNZ9QBAUxTFpNpd+AgH/kiNXybSYHY1o5ofWitw3gWXsqRw5SbbfG2istb6CtvRJxYBUDgjOUK01tkZb/31kuX92aH7JeT2ePFMBrhQfHGD6UjaqwqYnp6g2K7CUpKNg2ZSSfLgXio4C+yJcmg4J0kGe3hYneN99t5Phw3fSvXtRJkwwYw+0MyTPn4eSKJE+cRsvnh8vXxqdcjuyCbNzvVgf9vQKLM1mSDS/tCjtDwy8SOPGiyhVKj0HDsj7WRtRKo8kqSDJBRM59w/s6w1ZWkA16bz3UIlkrGwNVReoOtGv33rGjDmMKmGAC24LPk6iRH/x8mUYFy92J2fOFKbaFBD3fP2hzEgXVorFqa8ewgKDX+2eQoDlNmrlygs0abKYEiXScehQ1DiEjnjy8ceb+PPPA3zySRl++62G6dRn12BJFv3BhVQPCJabJ4u0/kgLUO1NkN7U13XrLlGv3gKKFEnDsWPvuezlL7/sYfDgbXTpUoipU2X/byTK+zTHu1BJvhm8TOanhNAHVrGZ5GBLWtsF165EibQ6fMyoMLAUltN8+VJy5swHlsE6+ImeaEIOfUv+z8uCGYU78m1w5GvI2RUq/qed38vywJMLUHcHpK2knV5v0aRAvMhzseNr614tygQvbkDpUSAtzJ5KgOEt1y0W/PCgBNYh4E9AKgceA8J0JHkeOZWVUxYpq41x0TqBJcfI8mW5RJCaAOG8F0o8oV+SxJZZfX+M+2vvgp6RwBJvlI/NOHEhIjTK6hd7nX8rxoVsh/VVrbIO2R0DpYoiClYdu3V56sBtbeDKQgPkXYTd96BxNZYks0ywa9RiIafScjpd/Eco/KWnRsu23ZEU2OrYSNOmnaBr11UIbti6dW1t61MZMXDgRkaOPBj5G5Pk4ZFhcEIe2xqRHDhlocaTwl7AXAN4eJv7EM800bFv3w3KlZupa6UMDpYqaW1EwX6SpIIkF0xEYSDK3R3KT9BmwdjQEllJVhnqqleSKx/snTsXYto0sw92F2wWJtOMGcfpANxfvBhkCoYtend/ABcnQ/EfQMhOPFHkoGpuAgh/pT8kSZzdwotjx25TrNhUHUC+AOVrJa1bL2XRonOMHFmL/v3NiB6UqkZhnmx1Q6slY0/P2spwZydUWQDZ5MD5jfTqtZbx448iWGB9+5a0/a6y4cWgQRv5+++DfPFFOX7+2ay1WGGazj8ISss3g5eJkgCJgnBIaV2150DB5vtwZxf9gVCJX6DQ514WzCjcCZoBuzpD+pp6rFytxEYCUqtlPFKPvYd/ChacVLi3vOH51aseebFi32gPSmA9M1RdSZWGcQJLcM9PAgliI5paJ7CkHED4WhcBeQBpOM8HCFpje0DDp2i0hstzElhKS2HRofpkli+Lb9+N8eIOLDLgVVk51bZLkdKikrUNVJ1v1xSvG7TrPQiaCsIsJKfG0XUPbm4K11dAuX8hj8Dseam8uA2LDMmO9i/BP56Jo1u3XqF69bnkyZOCc+fUQbNtRaZz55XMmHGKwoVT0759AdMPMhN2vJfeQwoxL5melanJGUgmr6U3EhT0gFy5omhDsRVQld/bZN/zFqZH5TAgSW5odl41UkoLVo0awjoqWwFtZO/eG5QvP5MsWZJy5YpK4lFp0yg/EXKrVGdoY0b0a1mcBZ5fg/r7IHUZi/UePHhBypT69s2nTweSKFFcTWwqU2Y6Bw7cYunSFjRrJls6I7m+CjY3Aiu4cpoYEJNKtjSHa8ug3HjII2eub+Szzzbz22/7I39gs1rYht0dOixn7twzOsIIIY4wkT0fwoWJUWLKxWRYNF9rTQW4uweqLoas6szDFy48IE+eicSP78+TJwMRzExr8v33uxg6dIcOy3HSpAaWwxQsqPKTIHc3zd1xW4UK42MUz2WHbQ8PgzkGkqhWt/RV4j55EwH5HpNqqrMjDVAvn0MJwcQyk8OD4eQvkKU5VJN6D5+8jRHwoASWVFvJS3G9WQJLyr0HG5JbMX4JtU5gqTmQCpDWQjPesRj31ZEFPSeB5YhXvrGmEVAAaBsehpRSEemEHPoCTv0K+QdCaT1V/Fsnj8/D8rwQkBjaPo6aecXZ4MjGQNo+n1+F7B31yTJvJSvQAQrHh4jX0DwYEmc1iVpw8COyZ/8XAbh9/nyQDlPMUZk48SgffriWRo1ysnKlabUB3lZZoQRnWW59e6ZUCaXVM9Yp8uTJK5Im1beYPXkygMSJTZOGjsZXxp8/f5+8eSeRKFGA7iMsjjkj0c534dJMKPkbFPzEmSXcY47x378wL6mIFklXNb3z55+hXbvlVKqUiR073rEcsroM3DsA1ZdD5ibuES9nrFhVCu4fguorIbNlBVtERATJko3kyZNQTp/uRv78su1yXdKmHcOdO1bYIxWsJlfb8F03UxsNu7vBxSmqFb7S4h4/vr4ayqLl2onVFQbYOXOa6A4QTGRrK7i6GMqOg7y9nNDu5lMU1tIoksrSGiz389OnoZw69T4FCggXlLr06LGWCROO8s03lRg+XKWlbXVZuLcfqi2DLK4D8Lt5dN+Y9+QSLMuph3Vo/1ybFt+Xd2GhAetOB8LvYzy3uB+kYnZZLnh6CaqvgMxmpDCSBBTcXDmQqLoQsrbymFvKZ6i2EfCgBJa0vAiLi5wArDNgXkkpuLwUvwPUwU+1DZeFtphIYEWzC9Gi3pfAipawupnStZXgzi6oPBeyt3POOOUjtMSvUOgz53R4+qzXz2GeAZdFpT1LE/fsLc3WZDE3ULIkKzy7CvX2QBohc30j0mqZIMFfOhZHqTqR6hNHZejQ7Xz//W569SrOuHF1TacrLFgpS0HDA46qdt/xayrC3d2qJ/+SABBMMKmaCgr6kBw5krvsx6ZNwdSqNU+XTJCkgoV4C5tT6BOYb7gHJYEdN4mFqzaBlp2M9m+/7eOzz7bQsWMBZs1SSVApf0dWKpecXDbmp9lxrxQqNJlTp+7p2oqlvdhVefYslMSJ9Th59+71I2VKsy4BqSCQSgJvIdWIAmPRUWBxW7HPn38SZ8/eZ/Pm9lSvbnpAgUKKUmUeZHOuRdzW+rH6e6Viu8TPUOgLq6aULz+DvXtvMm9eU9q2za86TmAIZs48xfnzD2jRIg/Fi6e1xMtamlOfTKi3C9JUiFXXY3RxHWC+MGRH6NvUEmoAU/PoLKzID3GTQVvh6fKJagT29obz/0C+flBmlOmQmxtgYx2Il1J/XfwNLOa+UL51EfCgBJbkigSDQRJZCgjnS+A3YGhsXbjoSGDVBuSf1JaalwZ4Sv2uL4EVW3dkTK6rnLgW/RaKDnNu5Q214NYmqDgDcnZyToc3zFqQSl863eg4pCgcPR7NMjyu3gbK4UimnyX6MnMzyZ17AhcvPmTbtg5UqZLF4Xh36RLI9Okn+emnqgweXN50/vkJsLcHZPIy2vEtzeDactUWIQlA1qzjuXr1MXv3dqJs2YwOx9R8gsI0ZhWrLLI6SOWU1uXVY1jB3MQQ9gyanoOkZq1mwMuXr3VJVxFVqnsnze3ffwOjRx9i8OBy/PSTGZaQDjsqPsiHnEolo5NLxs60nZ3h0gywclBi14e8g5afPn2XggWnkDRpPB4+7G9ZQXjgYzjzp/eAY2+oA7c26EGvpe3KqBVe4jtp0jGuXn1Chw75dUnpqIDFbYU6efKRPHr0Sr1abmVheHhSj1sk+EXeJnaCqn/44RomTjzGkCEVGDGiimoU7EoszksCr59afTZ5W3hN/FFaj1UOwpzy+85uWFsREueA5kFOqXgrJl1dCltbQJI80Oycqcu7ukLQNMjbG8qOfSvC4XNSPQIelMBSHJDWBNngySmlYF+pl9zH0AXXOoE1HJBMgIAFCKqnedugdvzO0RsgXwIreuPrHtqVE+Ts70BlYQd1Qpbnh8dnVZmLnNDmuVNWFoWHx6HmGshYT3s/jgw1AIsbVHs75bCCx2KljaR27Xls3BjM9OmNePddYbR1TGrUmMOWLVeZNasxHTsWNJ187Fs49g3k/hDK/+uYYncerQB6F/seinxtYWmpUtM4dCiEwMBWNGwo2JSuiYLN8v77RZg8WQWbZWkOeHoZ6u2GNGZJRNeWjvnZUbRnKsZkyDCWW7eecfBgZ0qWTK+Jjc2bL2bZsguMG1eHXr1KmOp8eQ8WGlqP2r/w7JNuGx/9dn3IOxjxNWuCaNBgoXXmvR2d4PIsPbObMLx5umxpAdeWGs5dwy3ISNq1W8b8+WfVcasc8N24sk0Sg8mSmVVgLEoPL0Kg0VFIUdQBzR4y9MRPcOQryPUeVJhi1WghGRGyEWEhXLJEHSvrxIk7FCmiZ9hTbe00qQ5/APFcr6z1kCjrzVS6DKrMh2xtXDf9WiBsaQypSkODN5hwriv2Mg2hj0AgSgQGoul5SGpgIBZW3NO/6Q9VZH+VMJP3QmF42SWNDnc8MIEVHWFwWqfWCSxJWgnNh6dz//oSWE7fUh40UTklcbZVSnCZTv6kZ4fKN1DPbOatuEy2LqvS4lJ+MuR+39Zox3+/rz+cGw0BSaDg59EHFO+4ZdEzY28vOD8eigyDYt9arPHBB6uZPPk4I0ZUZsiQig7bkDPnv1y69Ijt2ztSubI87ozExtoOL+YuExR2r3wDoIy+NcpY6tdfwNq1l5g6tSFdurheRdiz51r+/fcow4ZV5NtvTTG3dOtGVgYYbXDdJVaO2hEFg5uiKkpAcEfXM4wvUWIqR47cVk86ShWLVLNIq0abe06u4CbTlMMWqQ6qqP9gN5eAgN8JC4vQMTKGhbmOqfbvv0fo2XMdjRvnYsUKFZwWpWKp4jTI2dlNAuWCGVeWwDbDGavgBnWQDok3ogC5C+i6gK87K0o7bcKEATrAfRNsPKkanCOM0mHQ4hokyuTsMu47T6nwzdwUqi+zaufmzcHUrDmPnDmTc/GiOmlL1aqz2b79Gn5+EB4OFuD6T6/A0mwgVdtCiGKOQ+i+UdLGsu0dIHgulPwdCn7sus6g6bCrC2SoC7XWuq7PmzWsrwEhW6DMGMjXR++pQiqCfHrbz9jtzWF6m33zoASWtA7eAiabXS/pqhM2tF9i4zpqncAStkEBbLkQG85ouKYvgaVhMN1W1cPTsLKg8+DjR4bAiR/euOftVUFRXcjI6pYRUGSI9pf81hbYUEMP3t70jPb63U2jjSoopeLCKvNSFP7YxNBSWu3K/gN5VZjd3C1W9tpz6g849ImeBKDyLItZnTqtZNasU/z2W3U++aSsvVqtjmvUaCGrVgUxcWJ9PvjArJLC2yoDtrWGK4ugzGjI11c1Ji1bLmHJkvOMGVObPn1KuhxfUZAy5SgePHjJ8ePvUbiwAVxY0Syt3dLinawANDmlyXqxpuTCZNjzAWRsCDUDLcyIjgqsIUO288MPu+nduzhjx5rh5IkF0V11G9PBVhL3yrpm7/NRow4yYMBGWrXKy8KFlm3d9pq7c+c1KleerZ6YefUAFqTUq/L0qkFrAbmyGLa1gjQVod5Oq2G7e/c5adKM0f3+0aMBulZWY5H3mDBvPn78igULmnHy5F1TNl0ZrBCSJMwILa/be4m8Z9yhz+HU/7QjGTr9NxwcBNnaQ5U53hOn6PDkxM9w5EtQErVSbb2yCLw2dF2pJMmjwwyfTveNgAclsC4BwpJj/sCW1gF5EOSMjShrncCSLJz8dY6IDWc0XNOXwNIwmG6rKuyVHnxcd9p5BRI5iCWkbI7Ewbf9ZXR0OBz/DvL0gnLjtL/kl2bDzncgXQ2os0l7/e6m8fy/sLcnZGoCNZZbWDd9+gm6dFlFrVrZ2LDBMQICwXkSvCehJn/xQoXFMJK1aSlkaeZukXHenqAZsKszZKgDtYRIxVQGDdrI338fVMdTcmLVokX/4/jxO6xZ04Z69XKYahCAfgEYjxMAHV55fmXAvr5wbiwUHgLF1V//AwZsYNQoK3hVTsT30aOXJE+uB8h9/HgASZKYMUdemgM7O3rHM0MhVrDSuiMYTSdO3GXBgrPkyJGMrl0Lu4TRJDHt3DmQGTNO8vPPVfniC5UW14Xp4OVtcIXF14nrHm1TlDbNOH5QWJAwIkwqqpctO0/z5ksoUyY9+/Y5X3G2cOFZ2rRZps6cGcnomQTaPY42V2NVccg2WF8NkuaFpmejNCVTpnHcuPGUXbveoUIF02q0DRsuU6fOfFKkiM/Nm72JH1+FEe/6GtjcAFIUg0ZHYtXtWFn8zGg40B+ytIRqi1w34egwOD4C8vaBsvrkok+sRODeIVhdSn9A3vquHhPrxmr9YPlekM6Nt/nQ23fj4EEJrBeAYI2YA98J1oZgYZkxvMTMxdUigfWHkakC2t4VOGr4F2rmhgY1rDESGF8CK0bC7AaLKBhWtdZDBuEecECUShVfOTDYSLg4EFX1oad+h0Ofgit4ZS4bEYMKri6Hrc2sYk1s23aVatXmkCtXci5cUG+vsGbtjh3XqFJltu5DNyioh+WwxZnh+XXwdOY2c89sfMxItYlUnUi1lFRNuSopUozi4cOXnDz5PgULmtHA3z8Mq0pCggzQSjrvPVwUltDc3aH8BFVnfv11L198sZVOnQoyY4YZtbgT7h8/fpuiRaeSKlUC7t7tZ6nh9F9w8CPvqBa4sxfWlodE2aDFZdVoKR/0hQun5vhx19u45fkiz5nZs5vQoUMB0zWFCl5a3bRkOHPiHtB0ivg0N4Eet0blQOvw4RBKlpxG2rQJCQlRrzK0x54xYw7Rr98G9UquO3tgbQXvBsl2oLW3QYMFrFlzifHj69KjR3GT8L733iqmTj1Bz57F+ecflQpBGR00E3a9C+lrQe0N9lwe7xpzdRlsba4NZpVAZlxfBff2QtrqkL7G2wuZYc9dEhEOizPBi1t6vLeL0vrtr69QFggDeWcaEUXYo9I3xrsi4EEJLGEiECyTGWZXQE5y5Oeug8Y6cWm1SGDZWw4hgO61nLAxNqb4ElixEfXYWFNJQkXR+mLVrMCS8OAwFP4a/OK/3S+jaythSxNIWRIaHtT+StrJXKT9wrGk8e5+WFNWD/LZ8pqFETarqKIwe/bsU7zzzkqqV8/C5s0dLD9MhbnNGzFYbLSTjB9/hF691tGsWW6WLnWNb8RmddDN9bCxLiQvAo2PxdJNpuGykcyV6hWDslLr1ktZtOic7r6rXTu7ZbuPg+asXHmBJk0WU7JkOg4e7GI52wbmmYPLxe7wJ0GwLBf4J4B2z1Qr9o4evU3x4lNdTrAojmbPPp7g4Mfs3PkOFSuaYTE9vwWLM4Ac3kgFoZ9K9UvsRsy51Zdkh2fBqsQK9++/IFWq0Tq9z54NJGFCSeA5LkOHbuf773fTp08JxoypY6pAeY96M0i2ANQLUL1Ih9Ao7x0Fd6xfv5KMGvXmgPHp01ekTz+Op09D2bGjI5UqmeE4im5JuNzdCzdW6Z+zWVu/fQkX5aAkflpoHeL4zWo8QzmkUH7mqx6yHc/A4vBA6jkMkr421F5ve55vxFsRAQ9KYAm2ufz7DNhouDjyQP4V+B34KTYumBYJrNiwO7rX9CWwojvC7qJfwQjI1x/KjHTMKgUDpNoSyOI8JoZji7rp6MiKknTQSrD+NJYdHeHyHCj1BxT4SGPlbqju2TVYkgXi+OvBZ/38TYwU/I+ECf8iNDSc4OAeZM2azG4nfv55D19+uY3OnQsxbVoj03nPb8LijN73YSpe2mjbW7ToLK1bW2ntsTu6+oEKO5a0t9y/399ytje1t4l3kRWDZaDBPtVode++mkmTjkf+zgJw2cEYjx17iL59N9CiRR4WL1ZhKdv9vv7Uu/iPUFgwSD1YXj/Vg/6LtH0EcZNaOHPz5lMyZhynA3F/9eoj/P2lIN45ef06nAQJ/tSBwl+71otMmQxrK+ruH4VVxUGLD2PnTIyeWVGQEURERJAs2UiePAnl9Olu5M+fymEbpNVz+fILHDwYomv/rlo1s2mrp8KEmLE+pKnsnYdi4a8N1XtAqxBIIBjA6qK0ypsftsyceZJ33w0kd+4UnDv3gSkQvqLKl3ABYyZWSXwHJHT4njWZMEueKRH61veO5g02rqn2ytnb2sKVBW9cK/INFBvula76nHI8Ah6UwJJc0c/AACF81X8g8NwA3i6YEVKgFOOidQJLno6i85nBk+yAHGVLj6QnUVb4ElgxfivG0oIXJsGe7o6zqoQ+gQXJQcqEBRxUQELfZnlxGxal00dAEi7+Zng0rsZmfXUI2QqV50D29q5qc//5uk2+xDACWt6EhIYTayPL8+SZyIULD9i6tQNVq9qP39a79zr++ecIQ4ZUYMSIKqaxUHAbvKW1zdi7sJf6FiERYaUTdjojUdoy8+ZNydmzH7h0j7z77kpmzjxFsWJpadMmn2W1kYJNkrUNVJ3v0lpuMfnuPlhTTo8jKO1XKhIU9IBcuSbqfhMvnj8vX7qWiP7iiy38+us+Bgwoxd9/qxR3b2qkr74oPwlyC1mOh8vcxBD2DJpdgCSWFfuhoWHEi/enzsmQkD6kTZvIaYeDgx+RPfu/xI0rOHkf6ZJiJnJjHWyq5z0VhIpz29tD8Dwo9RcUGGgRvyJFpuiwxtaubUPduma4dnZE2ybY/qaGBpwcSRSEey9GzoJU8Oo+ND4JyQVaRV2Uts2UKaVNuG9kokphjP3mm0oMH17JeuRnycFPuP4gqONrO66Qlw0RVsv5SUES4E3OQLJ8zjt47Ds4ZpR88VVg2Y7lizuwyJCgjRMXOr6yPcc34q2JgAclsJRrIidZ8sCW5JW0FZpS9cbwldM6gSVJKkEK/AdIAQhdmPzFCj2Q4F9FA7pztETMl8CKlrC6odKQ7bC+apTYIqpWSzJFkioJM0PLq27oWAybJBslSQ4IMGXzS5BYctcayrK88OQ81NkK6apqqNiNVUmbhbRbNDwEKUtYGFqnzjw2bAhm6tSGdOlS2G5HGjdeSGBgEBMm1KN792Km86K7FdRuK6Np4PzkEPpIdTN/6tRdChWaogMFVq2acsCk5s0Xs2zZBev07tFNeuCArZoMtYOuftiw7YwYsTtyOVcrsDp0WM7cuWf4/fcafPxxGUs3VpWG+weh+krIbFZpqInTMaxkaQ4QJqt6uyBNBdXFU6cezb17Lzhx4j0KFTJjZXTAXJsYewohgre1xNhoVVeYRVWfnXbG18/vN+R1KSQaoaFmsLCHPoNTv+k1eTMxjJ3v85cvX5M48d+6SsCrV3uSOXNSPvlkE3/+eUAXw0GDSpM8eTx1wgJfBZb+PlpRCB6d0hOXCIGJs3LgIzjzl776SmAzRIp946y2t2Oecg9K8ioi1HsT0m/H1dTcSw9LYEnLoPyTSgXz8u5YOSHUOoF1B6guHRRAd0B6J4QvuzXwnSFzp/lNEA0KfQmsaAiqW6o0PiFp9xQC7Dy1VkDFtWJ3ccvgOGjU0pzw9BLU3QFpozgVdVCtbqcq7TNSfdD0PCTN7agGzxwfWAIeHIEagZCpoYUP3buvYdKkY3z7bSWGDbM/3koVgSo73vmJsPdDyNQYaqzwzLhFZfWyPPDkAtTZBulMq8/u3HlG2rRjdbOlBStuXNO2TUeCIa1C3367SzdFtdrIDtY+R9aL9bHG1W3CuBTfsr1KYvLTT3t49SqcgQNL6RKF33xT2WnTK1Waxa5d11mwoBmtW6tUFihkBA3260GMPV1Wl4N7+6CadXbQAgUmc+bMPTZtakeNGtmc9ljYB4WFsGbNrGzcqFLx6q2kGqf/hIMfQ/YOUHm2RfyU6tWhQyvw3Xdm1at2RNtmBdbKIvDwhL5iSHAIvbXKZU1FuLsbqi6CrFHjDRYuPIWTJ+8SGNhKV/VWuvR0BO8tThx0WwOriXDBwBJmVGHKzNkFEud8OxMuSlWfq5WoN9bCpvqQrAA0OWXH3e4bosNhk7/lokN9oO2+28EiAh6UwJLSS6Hm3Q8I65B5y6BroLFO3htaJ7CkdVDoaoKBeYZEliDUZzVUY9mZHXDSG+2m+RJY2sXSvTXJC+bUrxD2HPL2hvjp7NvkKK0GxX+CwoPd28eYsm5dVbi9HSrPhezttFv11UNYIAWdgCNJRu0siB1NNjaeCmve++8XYfLkBnbZaBPHRWkTiIJNzq6F3HVQFB9OgismLVjh4RHcuNGbDBkSO+1FmTLTOHAgBH//OLrqAYuPLButSk4vHJsTI9uCTkDyQqqW5M49gYsXH4QHNAsAACAASURBVLJtWweqVLG/7VVNWebM/3D9+hP27XuXMmUEUNxIpLV7jpARqDPKxWaYnF57cxO4vhLKT4Tc6i2uCnPgvHlNads2v9NLKc+W994rzJQplslzFOzI/B9BaWMiaqeXdI+Jl+fBjvaQtgrU3WZhkyRgv/pqG126FGLqVMer+pS2V1EsLdzyfDBJ4i7OAs+v6RM7D457JwaWOL+5KVxfAeUmQB4567YuSqXlsGEV2b//pq56WBGbrcjzksHrx9D4FCQ3Y9J0jzsu+q3Y21PPEl1kGBSTzzEn5fTfcHAQ+A5tnQygb5ovAqYR8KAEliStBMR9ujtdQ60TWEK3ICAXiwFBa5WvKjmGluPPlYDZLtOdQmFiiy+B5baXRmPDnC0zV6qNaq2HDG/YcTS2zrPUbe8AwXO1B1p/eApWFoK4KaDtfc+KiSvW7u4GF6dAse+hiKFk30ifAmRrtUpCZW2bTFp7e8H58a5vdl3xOzrnbmkO15ZB2X8gb0+LldKmHcOdO885dqwrRYpYBxe2ZWLevBM5f/4BEyfW1yVZJDlm8qG6oTbc2ggVZ0DOTrbUecbvI1tVNkAGdcJhm1VTdnr66lWYDmRcKjBU8Z6MK2ujA5PPTjs1HWYHKL3C9Dh6dG369pXid+ekR4+1TJhwlOHDK6pXye3qCkHToMTPUOgL5xZxx1m3d8K6ypA4BzR/kyhRTJ016xSdOq2kRo2sbNrkOBbjoUO3KFVqOunSJeLWrT6WEVicCZ7fAG+pGrR2jSPvZdsHgLVrz2XjxiuRFVdK5ZUkr+Q5YLUCy+Tg6wkEOH8g4Y63qt02Hf8Bjg6BXO9BhSl2T7MYqOwNCn8FxX9wXo9vpi8CvgjoIuBBCay7QDnggjtdOq0TWG2AWYD0XmwA6hmcFQqgaoDKUZ47hSPSFl8Cyy0vSzQZNVvK9R0A+jQGLG/zAOIljybDPEytgh9S4BMoZcDx0MKFmxtgYx19VUdj6U5+S+TI13DiR8jbF8rq6duNZceOa1SpMpucOZNz8eKHdgVFAcVNmzYhISF9LedEJnjGQd5edun0qEFC2CDEDcVGQJEhJqZLi9uYMYd1Caz33y9MtmzJnG5xK1lyGhJraXtp2NAScBuFXrvGashU36NCaNXYDbXg1iaoNBNyvKM6rGXLJSxZcp6xY+vQu7clrpu9gRDyAiExSJgwgKdPB1qykD04AYFFIF4qaCN7Ly+QQ1/oq4XzD4LSerB2c1Fa3KwmnuwMQ4MGC1iz5hKTJtWnW7eilrM2NYAba6D8ZMj9vp1aPWDY02BYmh384kL7FxDHFOpj+/arVK06x6FnrrHXCtNp+fIZ2b3bLHFt3Ibb6jYkcB7DzO0jffBTOP072LFXkIShJA4VKVkyHS1b5mXo0IpIS6bF4YAyUCrYAovqyTqEtONtlaDpsKsLpK8FteWzzElRiHQqToec7zqpxDfNFwFfBJQIeFAC6xfgCSCMg24jWiewxDGpshJKtiN6+g+dSObuEXDabTyP2hBfAstDLpTLZjpTgXUtELY09mEBmAf/1B9w6BOr+CFOXytlAyYApAJE+rZIJFNdK6i60MLra9cekyXLeF0bijCFCSiwLVm69DwtWiyhTJn07NvX2XL46rJwb3+UODu21nDr3x/+Ck7+BPkGQJm/TUy1iU/jgGPp048lJOQZhw93oXhxAzun8Xxvw2cS33a8A5dnQ8nfoaAZOLXB91691jF+/BHrlT12xnjTpmBq1ZpH/vypOH1aBT/05kbYWBuSFYQmQoLsBSLg3gLynaMTVJqh6pAClN+7d3HGjq3rtNMFC07m9Ol7rF/fltq1VQg5VpWE+4e9ByBfiVR4qL711Ar765Urj8iWTc/O+Pz5IPz9bT9zjS/C77/v49NPt9ChQwFmz25ien0eX4DlecA/ob5VXkqNvFVO/AxHvoScXaHif1F6aYxNKHF/9Ur92WKh5Poq2NwIUhSDRvI58pbKrS2woQYkyQPNhDjMSVmYTo8n5u3VgU6GxzfNFwFHI+BBCSzZLHcBpMtO/oWa+WrnQ9nRCEU93ovfkC4FypfAcil8HjRZMLCEleyMnGj7QaHBUMJGebTMOf4t5OgMlaZ5kLPRbOrlubCjA6StCnW3arfYyV/g8GA9EGvFqdrpdXdNwQthextIUxHq7bSwVrCapI0qNDScS5c+JHt225WAo0YdZMCAjbRqlZeFC5tbRkDBYKm/D1KrMLu5e8xs2WcDpNnf/3cdBpYkBV+//sSWNtXfh4aG6bC0RFTb26KbsdMpqzWYdOBj/XO04GdQ8ldVhUqCpVev4owb53yC5b//jvP++6upVy8HQkZgIZdmwc5OkL4m1N6ogXNuoOLiNNjdFTLUhVpC+Gwpo0cfpH//jbRpk4/585s5ZbTg5Anz2/Pnrzl37gPy5Emp8pzw4la3yDa+A5CqlInvr1+H6565xqx4jgS5X7/1uirPL78sz48/mrHpSvWiVDEmyw9NPOWs1xHvjcY6QBaiHCzYbBk0N0VwnwT/yVsJSewN/f6BcHYk+MUHaf+TbgNH2QNf3oWFhorAdm9xO6a9MfeN80XAjgh4UAJrUxTuCKC7OmaEHTFwZYgvgaUePV8Cy5W7ytPmygelbFpf3FRlJ7NwZ3NjuB4IpUdB/n6e5m302RuyHdZXhSS5oJmGrdLKBkyXXPwp+ux3N8028Fik5W3UqEPcu/eCbt2KkDVrUpstb59+upnff9/PRx+V5o8/app6HB4GcwX4OgxaXIVE8hj0MgmaAbs6Q/raUHu9iXNaVWAZV2lIZZyfn9lr9vCXcPJn/dqFh+hZihz9oHDHy3LyVzj8RZSJ/TFjDtGv3wbrCVQ7/fr22518881OPvywGP/+qyAVGE22kai0cxn3GnZ9NWxuCCmKQ6PDqrbNnXuaDh1WUK1aFrZs6eCU/bdvPyNdOj0b54sXg4gfP8BUjw4gP57hOXEFErkGxu+UkdE5yQbbY44c/3L58iN27nyHihUzOWRJ48YLdSDkcs/KvWsiF6fC7vcgQz2otcYhvR43+MoS2NYSUleA+nq2Vmsi7zmpdLPZMmiu4MhQOPE95OkF5cZ5XIg0M1g5cFUUOsNsqeztEmWDFpc1M82nyBeBtzkCHpTAcsvL5EkJLAFs+czQoij1wP2BvVaiKoAwUu5WxPD7A8BXUYw3V+NLYLnl7RqNRm1tBVcXQ4lfoJCQLVgRSXYtklLqO1BvD6SR7lif6CLwJAiW5dKf9LV/rl0LxLa2cGUBlB4J+eXP/i0RG/F0JuHStu0yFiw4y19/1WTgQOHWMJLnt2CxdIDHgQ6vwM/sw9Ubwq5QgacoCo2kEvqNyIfSoUMhLFt2gbx5U/DOOwVtJgTVQrJnzw0qVJhJtmxJuXzZEigepVJJmezMB4U7Xgs7KoQWLDhD27bLqVw5M9u3d3Tai27dVjNlynG+/74KX39dwVKPHXhRTi8eWxPvHYDVZSBhJmh5TdUKpbWyYMFUnDyp0lpph+09eqxhwoRjOhbOPn1KWGIMeSNAvnFclL1AmTGQzxJoXWF6lBZAaQV0RAoVmsypU/dYt64tdeqYtWZ6OwOscaB2vQ9B/+nb2qSyWg5NtE7iRwLF/6CvPHqbZZbhUy9OXOj4yvFInJ8Ae3tAxvpQc7Xj830zfBHwRcAiAr4Elms3hacksITuRXq1BFV4DzAIaAsIT3SISghmCiIHIH03LwChyWkp592A+s7PVIkvgeXafeV5s0/+Dw5/DllaQDUh0bQikUmFuND2MfgLXoZPdBGILhDatZXhzk6osgCytX57gh32AuYm1PsrILQCRmsmjra8lS8/g717b7JoUXMdEK6J3DsEq0tBgvTQ6qZ3xjnSxwzQSpiBTWXDhsvUqTOfAgVSceqUcwmAxYvP0arVUipUyMiuXSoMgwomiSztFw86vPSOWEcmB61jzmzbdhVJAOTJk4Jz57o75bckGqdPP8nFiw91lVxFi6axTDTueg+CpkJx2yxnThkRG5OeXoGl2SBOgD7BrIKRdPz4bYoWnUrq1Am5c0eFpMEOuzt2XM6cOWciWd8sWN4iAfK9FBx7/wA4OwoKfQklfrSIWOfOgcyYcZJffqnG55/bf4BlszVTIZjwloR2VPeaEmNlTHT4vKEO3NoAFadBThW8Rzv+FrxiiDM4r+aOK4cuURBIeEWsfE74IhCDEfCABJbQvkuLoLk8BM4CvwPqeAYxEEdPSWBJ0mofoPRrCXLmFWAUYOjFiDJawoooF0Lm2wNa5EtgxcDN51ZL3N4B66roP95b3rBePXR5HuxoD6nKQAO5JX1iEgEF6LPhYUhZXJvgLM0JTy9B3Z2QtqI2Oj1Fy/yUEPpAz74oLIxG4kwFVoYMY7l16xkHDnSmVKn0plFQyAlSloSGBz0lQo7ZqWzEJQlQZKgFHsilSw/JmXMC8eP78+zZIMv2PztWs9kmt6UFXFuqr3STvUF0fLzZYafmQ+4fhVXFIUE6aHVLVf2ZM/coUGAySZPG49GjAU6ZYNd9v6kh3FjtXSx5R4bACQM+oyRXJPlpVrUSEvKU9OnH6ZJPAnZtD7GD+UUYOfIgAwfqccMEd+jly49Mh0QC5BeAJm/Y4Zy6mO44yUYr7Ndfb+PHH/fQt28JRo+uY7cHN28+JWNG/bWR1mKJrYlsrAc310GFqZBLGgi8WF49hAUp9A5GVxJ/eX54fBZqb4L0Nbw4mDZckxbC29v1ybzkRSBra8er3ZTnabnxkKfH2xtLn+e+CGgYAQ9IYHW14q48vKWFQ4qLBIR0uYZhsVuV1gksoROZDGiI4Ew84JkhSEuMPBM0ZwmiChKxhf9JDZVaUrW1wo7o+BJYdgTJq4ZItcv8ZCAsRM0uQpKclu7JRkA2mFINlKocZGro+EbAq4Km4ozW7FTeCnht732wohA8OgW11kOG2iazpBLl2rUnTJx4TJcQ+Pjj0lG2vL148ZqECf/S6bh9uw9p0iQytSISWLcR1Fhpr4WeNc4GHoiANEuM5H+vXu1J5szy6nBMlA/cfv1KMmqU6TXTaVpbBe7sgLx99Qnz6GifccxkbUbb0YL64MELUqYcrVvv2bOBJEwY1+G1pZLFz08O/iTB4sfLlyoEOMpzqEag/jntDWJHJUVYWDhx4/6BPDZv3uxN+vSJHfa8SpXZ7NhxTUdkIGDlFhVYl+bAzo6QrjrU2eywfrefEDQTdr1rlQDg33+P0LPnOpo0ycXy5a3sdmfXrutUqjRLh1UYHKzSWvw2JVzsuJftDqzaQPkDmJcYwp5D03OQNI9L6jx+8vU1sLmB80yES3PA08tQZyukMyMf8Pjg+BzwRSB2IuABCSxbgZHNlySwKtkaGB2/1zqBJcfKDYBgYAogSSZ7Wvai8k1QMkWHBMgY7VFojqoD5e0IjCCS1je0EEpLoblIH5hxL1hG4HRQUBCZM+uBjP38/PD39ycsLIzw8PDI+crPX79+jWysFZGx8jtrPw8NNWWhDAjQ483IeGOx9vO4cePq7BB7FIkTJw4y3trPrdnu80l/nfzWV8Lv3j5el/sPv1ydddfP+Dr5nfwB/xPfRsY7rPBwwgt9rfv/vuukv/ciNjcmzvVAXpceR0SuD1DuSafvvZd3ibtM/hwl1/+C1xH+qn9n3vr35L+lPn4hm3hdbgr+ufWHIcbPiCdPXpE69TjdB+vVqx+SLt2bpJT5M+LcufsULjyNRIkCePSov8lzTHedTv0Ex4YRnrMbYWX+8drnXsD8ePrapzhxed3mqcWzPE+eCVy48JANG9pQtWpm3XPfkWd5jx7r+e+/E4wYUYkvvigbqV95RkRsbY3ftcWElfid8Lz98ZpneUQYAQsSE4dwaHmd8PjpLd5PEssECf7i1aswzp17n+zZkzn8jBg6dCe//PKm+nX48Ap8/XV5k+vkvywbcV7cILTOHvzTlLF4lkf1zHbnZ3nA/PjEIUJ378bp+Mrk/aT4JADsd+485+DBThQpomcOc8SnkiVncOLEXf73v2rI80WSWMOGVYi8TuGn/sTv0MeEZ2lDWMVZXrc3inN7KwGb60DSvIQ1OmWx31u3LpiGDRfqWlcPHNC3CNvzjJg9+zRdu67RPVMUgP3IZ3lEBAGLkhMn/AURTc/zOkE2k32g1zwjDF75nfgO/6Ap8PwaYVnbQdJ8hBce9uYes7K3tXsfEXof/yX6CuPQVo/AP4Hd18me/bcjf09usS832kdFtL6rgyOw+1sjziuYl0Qfy2bXIX4a7a6T4bvK9/1k+q3hqe8n5W9HeR56675cq2fEtWvXyJlTVywhTCiO5EocwQQX6KTvDBVTArwoJdX6k2zXJR+wG0jluirHNWidwBIL0gLScC5fW9LzIlRPkwBJbplmbeyz11oC63+AHAWoILiaKB4MCCq31BCbova+GfYNMNzcnIkTJ5ImjX4DmC1bNkqWLMmhQ4cIDpb8nF7y589PgQIF2LlzJ7dv3478eYkSJciePTsbN27k8ePHkT+vWLEi6dKlY+XKlSYvkJo1a5IwYUICAwNNzGjUqBHPnz9n06Y3LJby8mzcuDEhISHs2vUmp5c0aVJq1arF5cuXOXz4DUtR2rRpqVSpEqdPn+bMmTOR+n0+gfF1yn7nL3K/Xs7FgEYkqTHF4jolCr9J3ecCwwbhBLA88YLIWPquk/7ee7zhHZLems3puO05E68jrt57ScMvUev5IMICUuHf7u5b9/dU7Mn/yBq2hePx3iNbvb9VnxGffXabc+ceMHx4JkqW1FdcqD0jjhx5xvDh1xCA51Wrals+IwKmw/l/OBO3HafjveOVz718r+ZSMHR25N/tqbgdORtPqqDfPMvLlZvAvn0P6d8/PbVrJzN5RtjzLB858jkbN15lwID01KqVzOIZERFYnOThl9gdfwh3E1Twqmd5/WfvkyDiPjQ4SMjrzKrvp8yZx3D9+nN+/TUr+fIlcPgZMXv2S+bODSZFigAaNkyGnCd17Jj6zXXasJ4at+rjRzhrEk6mZOXGXvHOzXh3osm9K62nK4NLWewjypdfwOnT9/juu8wUK6ZPaDvyfho27AZHjz5h5MjyZMt2L/L+VZ7ldzb0JM2tf7kY0Jhj8T/0ur1RovAb1H3eG/wTcijvdoKvCFrFm/1eRERaChWaQqJEfsyalVv3C3v2e7NnhzBz5l1q1kzKkiUdTZ7l8SIe0vBZVyKIw+NGIWzaIhCuevHa/V6KGXB5DifiduV8PIGoBa32sMWyhpPzdCtC/VIQmFAaQ/Riz3UyTux40768zrOeJI64xdPyi4mXrbH93xoVM8Lq0rwkGasT6xFYtLpOvu8n8H0TOvZ+8qZ7786dO3TvrsMCdSSB5SgmuJyitgOEzO5P4BcNE1hFgXUGcr3I52xM/Ud0JLCMbS8FvA/IFXoCzACkGuqcAw660kL4KTAEEKCC/VGs6VQFlpwGyT/JNvtOEKyfIMgJlMTIeEMm/21+AhTbp4wEzyNgdyciUpQkosF+i1N7/8318Lu9WbfJlFNwXwWWSvXf0W/xO/4N4TnfJ6zMeIerK8wrGuPcXEvAtiZEpChGnEZH3rqKRr8jg/E/+wdh+QbhV/oP3Z+Q+d9N586rmTv3DD/8UJnPPisT+Xdm/vckrG09e26gfv0cBAa2sqze3NkGri4lrNRownPrcS68rfJUTv7j3AjE7/5BwtNWJyJtVd3Jv7GvCgvbV1+V45tvKtpVXWHy0is1k+PH7xAY2MKEaUx3ai+lcvOTEifsGaENjkHS/N5TgSUf2+vKEufBEagRSHiG+qoVwmXKTOfAgVssWtRU14blaJXm6tWXadZsCSVKpGXvXn2iVSSyCubJDQKWybkXhLZ+in/cBF5RgRXn+LfEubURv7s7iUhVnjiZGhBaUF8BbPxurVlzLlu2XGXGjIa0aycHpI5VYBUo8J8OIH/LlvZUrCispHqJrCTZ1Q2/oCmEFfmW8IJfet0zgrAXxF2kTzyHtbxNeEDyyBjI8/DFizCSJBmp+9nt271Injy+Xc+Inj3XM2XKCYYOLc+331bRzVee5XHuHSBgQ0UihGGyxVW32xupdRe4XF1x8lsdpltYrg8JLz3G9B5ztQLrxkr8t7ckImVJXtcRCF2zZ4SVjgmXfXLjzgj/Xe/gd3UBEcWElfFL+yuwrs7TtdSGp6lCWE09Np5bVJWZPfeM/56Mn4dqP4/tb41o+Xty43vP1vXwuIpGje49JyuwXMEEv2RIXmlVgSV6hIpXOu9iXKIzgSV9P4JEKVRO0oe30PC/0vYnFVGSCbRX5ILtBfobJgiIu5RBCZiGNRD3zwzJK2kdlBI3RyRKDCx5+Ny8eZMHDx44ovOtHpsiRQoyZMige/G5rUSyPPlD24cQYIQfIh+eC9PAq3t6kFXBA/AW7BotL8iFSSBsShkbQM1Vrmu+MAX2dNNOn+sWxayGU3/AoU8ge0eoPEt17Z9/3sOXX26jffv8zJnTVHWM4GXJR+3mzVcoUyY9jRvnssTLWl0O7u2DakshS7OY9TMmV1NAmrO/A5WFsNZU/ve/vXz++VY6dSrIjBmNHbYsderR3Lv3guPH36NwYX0Fb6Q8vwGLM0EcP2j3HPzlfMaLxA7w9MaNFxIYGMTEifX54AM5wHNMJkw4So8ea61jED04DoFFIX5qaH3HMeXuPvrCZNjzAWSoC7XUyX/atl3GggVnGTmyFv37yxmi/SJ7G8GAe/kyjKCgD8mR403yJlLL5iZwfSWUmwB5nGOStN+iWBq5MC28vAONjkIKy3s0TZox3L37nKNHu1K0qDQd2JbateexcWMwU6c2pEsX6eowkiuLYFtrSF0B6hsjZdjW67EjlHd7hjpQSw7xNZSzY2F/X8jSHKoZQ+dquIanqTr1Gxz6DLK0hGqL7LdeIY8Q8HYBcfeJLwK+CGgSASMMLEkCGdNiCzW1Gj21KwU9YrOjCSz9qbmlyMZANhdyQlbNUN2lSUwcUaJ1NkEQWeXLR6qu6hla9iYC8pWg9NF1NFRhWXLCW7dcKZmTsgBJZA0ylMTJRRe6I6lrlf7RLw0qJEE2ApDj2Te12PoqMPlnS6JMYN24cUOXvJJWwESJErl3UsaWp9H8e9kQP3v2TNfuKEmsjBkNeEbRvK7T6pdkhWdXLZlr7uyBtRXAP5GeYSuuHhPAJ2YRUMBCZdMvm39X5fgPcHQI5OoGFaQT+S2TS7Nh5zuQrgbUedNGbByFNWuCaNBgIfnypeTMmQ9UA2QXc9viLDpMEurvhdRvsJu8LuJXlsC2llaZRBcuPEubNsuoWDETOyX2DogxUP69e/1ImVKPvRIpIVthfXVInBOaX3RAs4cMDSwBUoFV/EcIf62a5O/WbTVSDfjDD1X46itbCACWfksy9ttvd9GzZ3H++aeu5YCb62FjXUheGBof95DA2WmmwpabKBu0uKw6qW/f9Ywde5ihQyvw3Xf6Sh975c6dZ6RNK0Xy6NgHLZjy5Bery8K9/VBtGWRRT5jbu57bjrNBAlCq1DQOHQphxYqWNG6sbyO0JblyTSAo6CFbt3agalXpGDGS03/BwY8gWzuoMteWKu/4vfIsTJILml3Q1qfDX8LJnyFfPygjZOU+4dYW2FADEmWFFm9gUGxGRhKrkmAt9ScUkE8vn/gi4IuAFhEwSmCZqxOwZYE2MhdXMcEdTWCpf3TAI0DwiMYBQVrEwhkdWiew5LhTesWkVGAC8AaI6Y11krgSjnYVmrcoXegHSFWV1LSLXuHgVmqDhQpHLsx7Bg3y3wJWZu9NYT7OagJLWgbPnj2rS16lTp3amZi/lXPu3r2rS2Lly5fPpJ3Q7YKxvR0Ez9d/gBVW8qHAvn5wbgzk6ASVpBPWJ6oRUKof4qWCNnddD9K+vnBuLBQeAsUlJ/2Wya3NsKEmJMsPTU6rOn/r1lMyZNDTsz96NIAkSSyresLDI/D31zO3BQRIu68Zc1tEOMyJp084tLgKifTkFV4pD05AYBGImwzaPJB+CBM3Dx26RalS03WA+Ldu9XEoBEFBD8iVayIJEgToWPYsKk7tqKBxaEF3G7yuGtzepq8wk3uq6HdQdKiJlYMHb+WXX/YyYEAp/v67lsMedO++hkmTjjFiRGWGDKloOT+SRa4W1N7gsH63nvDyrr4SWKTdE9MqYYPhNhN8UTh4+HAIJUtOs37vC4vnmT8h9BFIm3HCjN7JxLu5KVxfAeX+hTwfWkSsZcslLFlynjFjatOnT0mbt4ywmiZI8KcOEP/KlZ5kyWLGbnrgIzjzFxT8DEoKP9FbIM+uwZIsEMcf2j8HP8cZSa1GaWdnuDQDSvwCheQ82yeEPob5UjgRAS1vQkI9yL1NUZiQa6yGTNLQ4hNfBHwR0CICTlRguYoJ7mgCSws3o02H1gksAW+fD6gx/UWbE9Gg2GoC68WLFwg7YY4cOXQgnD6xLwICRH/p0iUd40KCBGZVCfapiJlRG+vDzbWQuSmkKqv/oC/8FSzJBPLx4HuJR30dXt3n/+ydBZiU1RrHf+zSId2pdJeEiJKChHQKioGKoKgYqIgionLBi4GKiXEF6ZCQkm6ku5HuDold7vPO9327k7szO7PLzsx77sNz15nzxfmdM993zv+8wQQzIUWHq5DSz9/I4tZweApU+xqKP580YyA5XeXiTpheyhBbxK3VQ8mXbwTHjl1h2bLO1KrlKj517z6LH3+MtUYZOPB++ve3W/xfOwGTZW8gBXS6ARFGVtSQLFH/wlgJbn3bsKZMm8uhmRcuXCdLFmPX/tIl94KgJy7Llh2hdu3fueeezOzd67rwZcPbsO1jKN4TqhlxX0Kq7BwOa2VvSQKopYZOrlbwn376N336LIzT5TUuJk2aTGDWrAOMHNmYJ590cu8SgeXMSjg2GzKXh4JtQk9gEQFL3kVN1kPWSi6ovv56Pb16/UWbNsWZOLGlT8Nr+vS9PPLILvACSQAAIABJREFUZKpUyc3atTKdcyqbB8Jmu3w3bgRKny6YXCuvft6W0IJy70KF2MzD1u3WqPEbq1cfp2/f6mTIkIqoqGhXl2y7th04cIG77/7eZtF27drLREQ4Tb0tK5eqw6Gk7NWGQRGBe1wGJOYYj+yBTN5ZsnlFZl5dOLkIao2GIuL0ocVGwBKj6kyD/M3jhxJ903hX3r4FLf+BDI7ZMeM/gdZQAkrAEwE7AcvbIO5J7UKYrDsvEAKWJx9Jdw132vZPtmziFbCSvRCTzNBawl+y57bqOdj7XSw9maBnrQiLW0LaPNDqUGgv7v0dN5veg60fGROeki9Dqsz+LSBn14Azq404FhLPItyK5Qoh7S7b37BsqeBqWWzFFfJkEVCz5m+sWnWcxx8vQ7FiWV0XXKt7wJ5vIW1uKN4r9OO7TS1ixLFruARyubpZWXGsfIlxI100btwOOnacTu3a+VmyxM3CaUl7ODQBqgyDUpLNOMTKiidhf2zWL3cWWKNHb6dLlxnUq1eQ+fONDJC+lAoVfmbz5tPMnt2ORo2KOB66+QPYbATlt5VQFFjm1gZxJaz1OxTp5IJu/PiddOgwzfMYjAP2t99upEePubRoUZSpU43McA7l35MwybTc8CBQ+tKXybZuPK7rlogqQpRYt7psCDg1bMGCg9SvP47ixbOya5cbN+8Yt8wQjz/o3OEzysKFbVBvNuSVqCMBKn8Uhcv7PD7fA3SV4DvNim6w/1co95538zLL80DiwZZ+w7CqdTP/CD4QesdK4M4TSICAJTedkJjgVmPVAsv53ezlMLgN+O4v4OXJA1xNBawAAw0aAUt2nMZIUkoZrkCNH+Hon8ais1QfqGK4YWnxQCDQC0grJlmox2XyNKC8tHh4552lfPjhSrp3L8/33zua+csCq3Dh7zh8+BJTp7aiRYtirlezXC7EAkvGfigu/O1bPb8RHJ8LNUZCUQnZ6FiqV/+NNWuOM2VKK1q2dMPLQ3999tlaXnllAR06lGTsWDfxgazYOt7ugAfbg2bd67DjE8OSr2w/wz3IacHz11//0LDheMqUyc7Wra7s42tytmxfcu7cv2zd+gRlyjgFyZeDR0sUg2jj2p1vxXe64Pt+5dOwbySUHwDl7ayhzJYsXHiQevXGUbJkNnbskBw63pf+/ZcyaNBKnn++Il9/7Sa+mBcCpfdXS8Y19/0MK5+EPI2g/myXG/3jjz20bGkEBxerKokXFlcZOXIzTz892ya4ivDqUibmguunoMkGY8MsXIrlqhlIC2sRWcamg+gb0GI/ZHQSucOFrbt2Whay+ZpC3Rnxk1jSDg5J/q0wmRfET0RrKIGAEUiggOVrTHCx2ipj3vRMMya5xCWXeOB7AtaYO3CiQFhg3YHbTvRLqoAVYMRBI2DFCDCS6DLakYK4sKXJpTtQ8Y2NQC0gwykuU1xMR8tYvA0pUkHnG25rTpiwk/btp1G1am7+/tvR9WfVqmPUrDmKjBlTcepUL1t8Jpey+xtYY7pohrJlhdVwK7ZamTeh0scuODp1msbYsTsZNqwur7xyb3wjPub7N95YxNCha3j55ap8+mk9x+Mkk+n4u+DWZWi2HTJLDpIQLGKhI5Y6jVZBjuouDdy8+RQVKvxC9uzpOH26l08Arl69SYYMn9uOOX/+RTJnls0GuxJoAd2nu0uiytuGwoY3oHAnuP93l4tu23aasmV/tiUQkEQCvpQnn/yTn3/e6jnAvuViL5nMslYOXUvNmEQAZaDZVheEffos4NNP18Z8Hp8FliUMuk08cOsajBOXZqDdWUjtS34jX3o3GdZd+zLs/BxKvQpVRPgOQHFwh78e2NhaAbi9O3qK0ythzn2G27zEwYovK/iiFnBkmnHL4TAvuKOdoxcPNwIJFLAEky8xwUXBdxdofRFQN5iZB1rAEgfpQ7HmKw5o5DsfUl/cUawqYAUYf9AIWBJDRXbuy/WDBWKlYQUB1h0or4ZEIBeQ4RSXyRNcL3nu3XueYsV+IE2aSFvcplSpxArFKJao0qlTKX7/3UPci9n3GbGDZOxL3LdQt8Da8TmsexkKtoUHJrjQf/vtJXz88Sp69arEl1829GroS6WuXWcwatR2hgx5kNdfdxJvrh2HyXkNN1CJDxfpJL54fZVkXvGvhnDiL6jxAxR1dZc6efIKuXNL8hq4ceMVh7EaX8t27z5HiRI/2uIOyTh3CZK/oZ8RY0wEXwmILVljQ83l5fAfhku7CEhNJB+OYzl16iq5chmZBH3l+9BD45k37x9++aUJjz9e1rU7Vj4F+37y3gUpvg5Nrt9f2AEzSnuMPfjee8tsiQiuX4+iZ89K5MyZLs4YWNZzYfDgB+jbt4Zjqy/uguklIWVGaH8xflEhuTJLyH1ZFkEFWsGDkxNyBtdjzvwNs6sZCQZaHw3MOUPlLCKWyiaKNzGtbAkjJD5ktCECindCqM8LQqWftR1BQcAPASso2pfYNxloASsKyAucdLpxSdcnn8WuqhK7Zf6dP6QFrJUrV9KvXz82bNjA2bNnHUhduHCBu+66yz96bo4OGgHL+d5PLIC/GhgLIt2Bin9ciAB49TDs+9GYkIvbpZsguPGfCDi7HmZVMWKPtTnm1SEhV0l4SibCU4sg272Qr5nbBbm4CWbNOpyLF29gH7fp9u3bNmFr374LjB//CO3alXSPaGpRuLLPEB2uHg1dywqr9eIWvLApZCkPTTe5MPnhh00888wcmjS5m5kz23o9rOrXH8uCBYf47bemdOliWW2bh59cCvMegAxFoOUdyzzsdVsSXHFtHyNTXcmXoOpnLqeRgNepU39qix109GgP8ubN6PWl4nWPO7MGZleHNDmNAP3xWRh4feVkVNESPESc63DJEETtij98y5QZyfbtZ5k3rz0NGrhJ5DzrXji7FmpPgELe/y6SET3vbsWWsc2cB4molMopayDw4INjWLLkML/+2oTHHnMj9tld6f77R7N8+VHGjm1Ohw5OlpfH5hqbZZnLQrPYRBve3WiQ1zoyExY18/gcTlDrDk2GJW0ge3VobCUqT9CZQvMgy409vt/w7m9hTY/Y+ZdspsnmVqhtCIRmL2urgoCAClj+dVKgBSzxuZIIn6ecbktmQtuADP7dbpId7ZOAJYtEcW3wtUjMmsjICN58szqDB6+2BVbu16+mT6dJnz6V6y50HGfYuHEjNWvWpFevXjz11FMcOnSIRx99lMqVK/Pss8/SoUMHn67vbeWgFbAsCxgRrySmgu5Axd/l9rt8/sSgODIDFjWHrFWgSay7Rvw3EGI1DoyG5V0gZ214aInHxlkLKnvrifXrT1Clyv9Ily4lp071JEMGcYd3U6xYYw8th5x22QlDDGVMcy7tgWnFITIddLjsIgLMn3+QBg18jyNUqtRIdu48y4IFHahb1yljU0xcnYZQf26okoW9P8GqpyB3fWhgWbA6NjdPnq85ceIq69c/TqVKjlkg4wIzatQ2unadSf36hfjrLzfvqr0/wqrukCeEGTtkBjsIGQq6IMuV6ytOnbrGxo3dqFAhp9dj7a67vuDSpRu22FkSQ8uhREfB+IxG1rjmu+Cu4l6fNygrjs8CNy94dPd98cW/+PLL9bz66r188kncnhhWltjVq7tQrZrs8doVa8zmbQL1JERJGBUry64ECW8vYmwAliQ7v4C1L3m0rg0juu6b+mdVOLcOxH1eRHBPotS8OnByMVQaAmVeD3tsCkAJBJqAClj+EQ3A28J2A1YmwpeA74GrdrclVldiMy3WWff7d7tJdrRPAtaVKzfImPGLJLs5+wtdvtzb86LUzR3VqVOH/PnzM3r06JhvX3jhBdauXcuKFStsglbv3r1t/3/+/Hmk/o8//uixbVOmTGHRokV8+umncbY/aAUsy6WwfH/QHSjvx7iVVSmhaayF+7n1cOQPyFQCCncO350/yxItTXZoe9pjH7z00ny++GIdr7xSlWHDjPhLVnD3Nm2KM3GihyyONy/C+MzGedudg9RZvO/nYK0ZfcsI9GtzpXAVAf755wJFisSR9t5Duy0BYOfOpyhRwkkA2NjPyNBZrAdUN1zoQrJYLjxpckCbk24XpVYmwVmz2tK48d1eY/jPf1bx5ptLeOyxMvz6a1PX4/5+CXZ9EfoJN6aXhos7oN4cyOsabL1cuZ/YuvUMc+e2p2FDN5ZUbohfvHidzJmH274R98yMGZ3EbktsENFXxIaIYDGo93p4xVaU98/ur43A6nd3M6wmnSxPLCtN4SucPZVr126SPr0Rt+3kyZ7kzGnGu7IOkMy9WwZCseeg+jcJuNkgPiTquvEcFgt3icmUzsxw6U+T1r8O2z8xsiBXjXte6s9lgvbYRS2NeVVcgdmvHISp8txIAa0OQvoCQdtcvXElkFwJqIDlX88ESsBaYN5GHWCFhF6wuy35W1I3SoTG3f7dbpIdHZIC1okTJ8iXL59NcKpdOzZ1fN++fVmyZAnLly/n/vvv591336Vx48aIZdn27dspU8bJFcauGwYOHEihQoV44okn4uycoBWwkmzIhdiF/u4Nu4ZDiRfh3gSIu17Gfgoxau6bc+sqjBM3q9uGIJDWvUXFTz9t5qmnZlO3bkEWLOiIxGn56qsNnDlzjXbtSlC2bHb3cVpOr4Y5NcLPVXNaSbi0C+r/BXkcE+SKNWzatJ9x61Y0hw49R4ECri5Ezp0llisiYEm5eLE3mTI5CQBLO8LBcVD5v1C6T+gOXfvx2voYpMvj0lYr1pI37lf2B/fu/RfDh6/nrbdq8NFHD7gynFcXTi6Cmj/DPd1Cl/HiVnB4KlQdDiVdA7XXqzeWhQsPMXp0Mzp3Lu0Vh+3bz1CmzE9kyZKGc+dedD3m4ARY2h6yVYOHV3t1zqCt5MX7Z82aY1SvPsoW/+rEiZ4eLeF37DhD6dI/eY7btuIJ2P8LVPwIyr4VtMgSfONTCsPVg/DQMshZK8GniTlwWWf4Z0zoP2cTSspyQZbjPYXF2DYENvSFXHWg4cKEXkmPUwJKIA4CKmD5NzwCJWBZd/ET0Fs28Py7rTt+tE8CVkJdCMVtUFJWp04dwY0b0bzzTk2bO6EvxRcXwpkzZ9KsWTMuXrxIpkyxC7KGDRvaRKohQ4bY4l9JXKyMGR3jknz//feMGDGCGzduULZsWcaOHWu7zXbt2lGiRAkWLFjAkSNHkGuUK1fOpQkqYPnSqyFQ98AYWN7ZiNv08JqENShQ2QwTdvXkddTUe+DKfmiwEHLLPoFr6dFjDt9+u8m2ULr77syIFdGlS7GuzR4zZVmubXG4fCUvGAG6m5gU7iOgeA+XkxYv/gN79pxn4cKO1Knj6qblfMCuXWcpWXKkTbgSAculWK4bD06FAi0C1IhkepppJeDSbo8WQlZQ66FD6/Daa9W8bkTbtlOZNGk3X37ZgF69KjseJ1keJ2aHG+egyXrIWsnr8wZdxQ1vwrb/QPFeUO1Ll9vv2HEa48bt5PPP69O7dxWvmjd37gEaNZpgE7q3bHnS9RjLUuiep6CmZ6tsry4WDJV+l4QW0UZii863XO5YLKvE8j6+WG5dukxn9OgdlCuXgw4dStpCRQwYYOeM8Fd9kFib9/0Gd3cJBjKBvceY9v8Kdztm0E3QhebWhlPLoPY4KOTZMi5B5w6Fg7wQZ5lZCc5vhOrfQbFnQqHV2gYlkOwIqIDlX5cEUsBKBcwCZCUQLJZWnuj5JGAltAsGDFhmi4HVv/99fPDBCteJTUJP7OG46dOn88gjj3Ds2DHy5DF2xTdt2kTVqlVtFlgSG6tu3brs2bOHNm3a2GJkVapUiXPnzlGvXj2bm2FkZKTNtTBLFsPNSMSr1157zRY/a/DgwURFRdkCxDsXFbAC3JnJ/XRX/oGpRSBFSiOzUkpxE/ChbB4Im9+LPSDcY48tbAZHZ0I192KLgJLnyfvviwGsa0mdOpLr119x3wHr+8L2IR4Xwz70WnBVjQk2/gpUtbzgY5vQuPEE5sw5wMiRjXnyyfLxti3OAOMiroib5q1L0GwrZPZs1RrvhYKhwpJ2cGiiRyuIV19dwLBha3nttXsZOtT7TM41avzG6tXHmTy5Ja1aOcVgkuQREstNBIcOV0I3y6P0vxVnzEOsrxdemGezvpSYmoMGxVpbxzV0LAvOxo2LMGtWO9eqi1vD4SlQ5TMoJdEiQrh4s8gHSpceyY4dZ/nzz7Y8/LB7V9hmzSYyc+Z+IiIgOhpcNhL+KAaX90LDxZDLjVVhCGO2NW3VM7D3h8BltrQsuhqtgBy+xZQNddS29ol77OU9cGAURKSFUq9ApY9im35+K8wsZ2QeFLfONE6u8GEBSRupBBKfgApY/jEOpIAldyLB28UGWAUs//olUY4+deoUhQsXpm3btjaRae/evbZg7q1bt46JYRUdHW1zMZw4cSIjR45k2bJlFCtWzGZVJdZWImqJBZaUq1evUr58edt5pAwdOpT06dPbzulcVMBKlC5NvieVBfuU/HDtWMIm5qufhz3fGEFGS5sBRMM5+82612DHf6FEb7jXiKfirqRKNczm9hYZmYL27UswZsxORLy6cSPKdeFknWBRCzgyDe79Ckr0TL5jKtB3tvsbWPM85GsOdae5nP355+fyzTcbbZaxH3wQvwgwevR2unSZQb16BZk/v6Pj+f49CZMkvksK6HgVItMGujXJ63yb34fNA+CeJ6CmGGY7lnhjWXloTYEC33DkyGXWrOnKvfc6uSZaSR/CIZvbqRUwt5YRm6bVIRdaAwcu5733lvPssxX49ttGXo2NQYNW0L//Mp5+ujw//NDY9RhLaHHjcuvVBYKpkizy5d219zuQAOOlXnMbg7FTp2mMHbuTwYMfoG9fCfXqWpo3n8SMGftsX7hsJIhV29YPjUDakrE3Zabwi/W49WPY+DYU6Qq1/uffKJFEA2PTGDxbHYb0shetxYWAWBaKlawIp9W+geLPGVVsWY8XwKnFkKkkFO4UfuNRh4sSSCICKmD5BzrQApZETLwOvOnfbd3xo5PEAutOtFKssF599VX2799vi13Vo0cP+vTpQ4RsDzqVJk2a0LVrV7p06cKlS5eQgO1iZfXhhx/SqlUrVq9ezbBhwxgzZoztyMcff9wmcIkVl3NRAetO9PYdvuaStnBoElT6D5R5w7eb2T4M1r8K4ZiZyR2pvSNh1dOQ5yGoP8ctS7HifPfdZTGClcTCkmxt8Vp4WgvTBvMhtxH8PSzK8b9gfkMjScAjO12a/Mkna3j99UU8+mhpRo1qFi8Sq36XLqX57Ten+qeWw9z7IX0haPVPvOcK+gryu5ffv4cMoj//vIUnn5yFR2sfNwBEmE2b9lOiom5z9GgP8uZ1dHPHWggXfhTuHxX0CONswPWzhrukFAmonsqRxYgRG+jZcx6tWhVj8uRWXrHo0WMu3367kXffvY/333fKt3PzMow3ww7EEYfPqwsFSyWHWG7uA4x//PEq3n57CZ07l2L06OYuLZPs1BIYX8ZuqlQR3LwZ7biRsO512CHhYc0SjpbG/4yDZR0hx33QaLl/o8OyqhUrzLL9jbiR4bzxFRfNHZ/BulcMa+CmW4xkG9ZGWTiPR/9GoB6tBLwmoAKW16jcVgy0gCUpbB4H9gB/A1ecrhoskWtDVsCKa7jMnj2b+vXrkypVKpvAJX9LbKubN29SvLjhrtGzZ09bZsKOHTvyww8/IIHhLZfBypUrM2/ePLJnNyfWdhdTAcu/H2pQHi2ZgCQjUIGW8OAU35qwoCkc+1MDsVrULIuLdPmh9WG3LBPkkhz1L4zLYMR68RBw27eOC6LaVw7B1EKGm2vHaxCR0uHmO3b8g3HjdlGzZl6aNr0nXhfvPn0W8Omna3n99WoMGeIUp2zfL7DyCcjdABrMCyJICbzVi7thegnD0qz9ZZeMdX/+uY+mTSdRqVIu1q+XKUP85ciRSxQo8K3NulDcYcX93qFYwZsrDYYyfeM/YbDXmJjLyJL38FrI5hjnauLEXbRr9wf335+fpUs7e9VSy1Lou+8a8cwzFRyPOb0K5tQM30QP9WZDXldLtpkz99Gs2STKlMnO1q2uccOmTdtLixaTyZw5tS0wvsQ8dYiBdXQWLGxisPYUUNur3gviSmfXwqx7IW0uaHPCv4as7A777OKzhaMg6C3BGxdgSgG4dRnqz4VMxUHikV02rAXDdjx6y0/rKQE/CaiA5R/AQAtYVjZCd3d1G3BM9eTfvSfm0WEpYD399NMsXLjQFuA9Q4YMSIbBBg0a0K1bN1auXGlzD6xVqxbDhw+3WWy99NJLtu9btGjBrVu3bCKXCF/uigpYiTlck+m5JZCqBFSVianEUpAdPm9K1A2YmA1uXYEmGyBrRW+OCu06N87DhKxGG9tfgFR3Baa95zbBnxUhdVZoe8b7PgrM1e/sWUS0k+yOUdfgkd2QqZjD/YgFi1iyWMVjEHyzguVO9Omn9Xj55aqObdvYH7YOgmLPQfVv7my7k+Lq4sojFjvCtvkOuKukw1XXrTtB1ar/I2/eDBw9+rxXd7R69TFq1BhFwYKZOHjQdHmxP3J6Gbi4HerOhHymKODVmYO00twH4NRSqDUaijiKVIsXH6JOnbEUL56VXbue9qqBlSv/yoYNJ5k5sw1NmtzjeMye72H1s5CnEdSf7dX5QqLS0g5wcDxUHgqlX3Npkr2oevnyS6RN6yiCP/fcHL77bhM9e1biq68auiL5qwGcmC9qARAN4Si4OLzbXK0JfRpHlhWmHBSugqAvwP5+EXZ9CTnvB4khKLFLLXbRN8JzPPrCT+sqAT8IqIDlBzwjIIcWNwTCUsBKzJGgAlZi0k2m5xbrnvF3QfRNaLEXMjotijzd9sklMO9BSJMT2ojw5eremkxbnLi3NTmfEZel0SrI4Vu2Uo83ZmWLzFELGi1L3PtPjmefWQHOb3Yrely8eN3m/iNFMsVevx63AfGDD45hyZLDjB3bnA4dSsW2VuKKSEDzC1sMK47s94WHW8usanD2b6g9Hgo5BgU/fPgSBQsa1lQ3bogLe/xTkcmTd9OmzVSbRdyKFU7Z2uwtCVsdgfT5kuNoC+w9xQS/fhcqvO9w7h07zlC69E9kyZLGZvnjTcmZ8ytOn77Gxo3dqFAhp+Mhf/eGXcOh1KtQxc7lzZsTB3OdLYNgU3+P8ZkkA3XOnF9z5sw1/v67K1WrxsZlk+/EYvDo0cueg7xPKwWXdkKVYSBumhK7KRxd3iZI9tCz0GQjZHWy/vNl/PxR3AhQLi6EwjIcBUFfeK15AXZ/FXuEBHUv8QJUGQqSyCBcx6MvDLWuEkggARWwEgjOPCz+WWPCzi8plgrJvN/ucLHAco2Um7DzJ/ZRKmAFmLAKWAEGGiynm10TzqzyLUW4LPi3vA+FOkJtI76aFsDarZeg2BIcOxBFgghvGQhFu0ON7wNxxuA6h5Utz01mNSummNWg+CywihX7gb17z7NkSSdq1y4Qy8HLjGbBBc6Lu135NOwbCeVcBRZJKpAmjYTMhNOne5E9e/xZSocPX0fv3vNp27Y4Eya0dLyBs+tgVlVIkx3anAoPS8L5jeD4XOM5KYHr7Rabb7yxiKFD19gYvffefbb/HzDAKa6VHcF//71FunSf2T45c6YX2bI59ce8unByEdT8Be7xzuXTixGS/KscngaLW0CW8tB0k9v7bdBgHPPnH+THHxvz1FOx2UrXrz9BlSr/I336lJw584KLdZbtZJI1UyxfGi6CXA8mfx6JdYezqsPZNfDAJCjYOmFXkY2yseIOf9MQwg5PVQEmPpLO7yZJmFN5SHxH6fdKQAkEgIAKWP5BDLSAJSYWkwF5i4tgZZ1f/pYS6d/tJtnRKmAFGLUKWAEGGiynswSs4r0gbW7vJpTidijuh9W/h2Ldg6WliX+f1m5p6Teg8n8Cc70l7eHQhPCNNTanNpxeBm7Gp8QUGzduJ9u3n+Xhh4tQo0ZejyLAe+8t46OPVtmCNYv7oMS8iREMbpyDCWYq8nBya7GCBBdoBQ/KtMCxZMv2JefO/cvWrU9QpkyOeMfzm28u5j//Wc1LL1Xhs8+cohHs/QlWPWUkIZBkBOFQlneFAxKsXqZZtx2sTawshBaG+MRXEV5FgE2XLiVXrrxECnt3b8koOzGHYSHz8DrIVjkc6BptvHIQphY24uR1uAKR9nuyRhUr9l3v3lX4/PPYcWn1QcuWxZgyxU0g/WsnYLJYbKUw3cLNIPnhQze2pTPKwYWthqvmrWvezROcOZ1eCXPug9TZoK2I2Gq57dVQGpMGxF0wnN5NXoHRSkogcQmogOUf30ALWGJhFQU8A0gkQPFzkYje/wUkgMAS/243yY5WASvAqFXACjDQYDnd0o5wcJzbRZbbJty8ZCz2b9+CFvshY5FgaWni3+eur+HvXpD/EajzR2CuZy0cwiVukDO1xa3hsCQYcBUBpOqgQSvo338ZXbuW4X//a+qR+dtvL+bjj1fHfO8gGCx7FP753fvfQGB69s6fxcrymLEotJC8Lo6ldOmR7NhxlvnzO1Cvnhhsx126dp3BqFHbGTLkQV5/3cmFdu0rsPMzKPkyVDUsu0K+iDuxuBVLcbP4TJHCcPWT7HfiphlXiTNm1tUjRrBnccvqcNkIzB8uRcQ7eR/dPO8xHuMvv2zhiSdmUadOARYu7BRDpnr131iz5jjff9+I7t3duMUdmQmLmsFdpaH5tnAh6r6dc+vAqcX+xQLbOhg2vgUFWsODk8Kbp7ettyyw5PmhMa+8pab1lEBACKiA5R/GQAtYp81A7WJrfcEUsCQ/uWxLiYgVLFt3KmD5N65cjlYBK8BAg+V0DousVNDpRtx3fmQGLGpuxMuSuFlaYgmcWGBkCfIgCPiMKvoWjEtvxChreQAyFPb5FEF/wPktMNN0+3EjAsyYsZfmzSd7zDJmtX/OnAM0bjzB9p+pU0fasuTFlFk14OxqKN7TyOIWLnFF1r0ZtuiVAAAgAElEQVQOO0RESQFl+xkCiF18nzp1xrB48WF+/705nTrZxQzzMKjq1RvLwoWHGDWqGY8+WtqxluVeW2MkFHXNBhf049RdA+JwTfXV/XX06O106TKDunULsmBBR8erWZnywlVomVcHTi726D4pge8lAL7EGzt79gWb9drx41fIm3eEjePRoz3Imzejaw9uHgib3/MYXyskx6ynRh2dDQsfNr5NqCXQgofh2Gxw4w4eVix9aayEa5Dncvn+GvPKF25aVwkEgIAKWP5BDLSAdQ6Q9EtifSWrT/H/kcyERYHNQHr/bjfJjlYBK8CoVcAKMNBgOZ2v8X8sS4piz0L1b4OllUlzn9eOw+S8hmuEzZ3FT0uIiztheimITA8dLoWny4W1iLR60Cno77Fjl8mX7xtbkPFLl3qTPn0qt339wAO/s3TpEVu96OjbOFhgWVZutSdAobZJM1aSw1Xi+e2XLTuSbdvO2tyuLly4TlRUdJxxmkqU+JHdu8+xcGFH6tQpGNtCieO2faiR8bBYD8NVORwCYcvi89gcOLMCslaF/M1j2i3uryL2LVp0mMqVc9GiRdE42Q4Zspq+fRe7WhrKNU4vN2JtZS4HBduGB1v734+Vqc1DAPt33llis76U332fPveSKVMqChW6i6efns299+ZmzZrH3P8aF7WEI3+o4CJ0rLiXHp7D8T7OZBNGLOVuXdbMxfHC0gpKQAkkBwIqYPnXC4EWsMRFUCytxCdjNCB53wcBz5rCVjn/bjfJjlYBK8CoVcAKMNBgOZ1MTCUrkMRqiUwHpfpARXkkuClSd88I+PckFOpguFaEw0LU2750cGfxM1uTXPPQFFjSGrJVhYf/9vYuQquejDlx77u0C/I2gezVXcZcnjxfc+LEVVau7GKLg+Wu5M8/gqNHr/Drr004cOBirBgTE+cGaHvaCDIeTmW0hL2MNnb5O99yaHnNmqNYteqYLRNhVJST6OfESDK6ZcjwOdeu3WLPnu4ULZoltkaMpZf5UThlHjv6JyxsCukLGVaUdrGrJk3aRdu2f1ClSm7WrvUgopjIXnppPl98sY4336zOxx/bBRP3dQMiFMf2nh9g9TOQpyHUn+vSQmdrt4IFM9mE7H/+uUi9egV58MEC7sXDyfnh2lFouARy1Q5Fct63SZ7DR2cagdyzVob8LXx7959eBXNqQuqsxnNW4195z15rKgElcEcIqIDlH/ZAC1iNgQyAOKAXA6YDJSSxDSB26cESXVUFLP/GlcvRKmAFGGgwnS46Cv64G64eijsbYTgvRL3tzzn3GxYR94+Bwk6uPt6ew6q39WPY+La6sGz7D2x4Ewq2gQcmulBs0mQCs2Yd4OuvG/L885Vcvj9//l+yZ//KZoFx6NBzFChgF4z5n7GwrBNkqQhNN/jaQ8FdPx7xY/DgVbz1lhEW08Xt0qnlEuxdgr5LuXr1JdKls7OEOzgBlrY3jkio+1Gwkr51xbA8kfg1zXfCXTLdMooVmF3YXr7cm1SpPOfQadt2KpMm7Wb48Pq88EKVWBry7B6T0vjvFKmgczwu4MHKMa77Pr0a5tSAtLmgzQm3NVOl+i+3blm5ihyruA2gb7nWi9DS7gKkcuNiGIos42qTuGmKu2aqu6DNSYhM4z0B6xnuIWGE9yfSmkpACSiBpCGgApZ/nAMtYLm7G0m/JK6F7t/u/t1/Yh2tAlaAyaqAFWCgwXY6y1Ur5wPwkARrdVOWPw4H/md8EW4LUW/7c1V32PsjlHsXKrzv7VEeeD8GB36Dih9C2bf9O1cwHy0ZLyXzpSxQWx93sGKRZr39trgIreKZZyrw3XeNXFr6xx97aNlyCiVKZGXnzqcdv1/9HOz5Dkq+AlWHBTMl3+9drCpEYLHFwQKcXLAef3wm//vfNpvRkBgXxpUpb8uWU5Qv/wvZsqXlzJkXHO9lZkU4v8mw8pL4YuFkgSUkJC6exMe790so0SuGjQiqWbIM59KlG2ze3I1y5XK67UNxN/zhh80cOXKZzp1L2cZxTAbNld1h34+xx4UbW2n5raswPhPcjobWxyCdZA6MLZYFVurUEiw/mvLlc7B5s4SDjUOYPTIdFj0CmctCsy2+/7ZC8QjhO6UQXDsCD0yGgm4yN3pq94ImcGyWumOG4rjQNimBECWgApZ/HRsoAUvy1b4OtJB3tkypAFldXfPv9u7Y0SpgBRi9ClgBBhpsp5NMVpKOXBaYzbZC5jKOLTg+D+Y/ZHwmO/23b4bfQtSbPp3fyIhHU6g9ZC6f8IDgIi7s/d5wYSncGTKV8M1lw5t7DZY6UddhfGaIvu5ixSJNmDBhJ+3bT/MYz+bll+fz+efr6NGjIiNGmGPYavsfxQ0X2jrTjBhF4Vhm3Qtn10KNH6HoUzEEXn99IZ98Yriu9utXg5QpIzzGaZo1az9NmkykQoWcbNzYLZaixL4Zl8nou4eWwvH5Cf9NBGvfWJaUBVrCgxK9IbZYsdkkg6Zk0nRX4gz4PruWEWOrSFfjGREuCQicQUmsQIkZWHcW5BNHg9giAmBkZAT9+9+HsJw//6At/phYvt24EeVemLViPt39ONz3S7COvMDf97pXYccwKNQRao/x7vySjGRCVjP+1XrI6mol692JtJYSUAJKIOkIqIDlH+tACVjvAANM4UpEK3nDy9snWNMBqYDl37hyOVoFrAADDcbTLW4Nh6dAid5w7+exLZAdbskEd3kfZK8JjVdoRhxP/WtvpSZ1EmoRsel92CKPbLMk9DzBOA7d3fPcB+HUEheRRarG54pVseIvbNp0irFjm9Ohg102vSuHYGohwzKo3VnDNSYci2V96ca9p0iR72yxghYs6EDduoXc0hGBYMOGU0yduofixbPYMhDGWAhZwrdYz7U6ChGe3eRCFv2Zv2F2NWN8tT0DEabLH/DCC/P46qsNvPrqvXzySV23CMRC6667vrB9J1ZE16/3MeqJWdw0EWD3QrglIHAmtbQDHBwPlYZAGdmr9VycBS23yQkWNoejM6DqF1DyxZAdmj43zBrLEi9T3Ai9ca20XDw1/pXPuPUAJaAE7hwBFbD8Yx8oAWs3MBT4zrydhsAMIJ0RwTXoSkgLWPKjGTRoEPPmzUP+zpw5MxUrVuS///0v5cubKeUD3GUqYAUYaDCezkrHHpHWWNBv/8TY0RfriW2DIX0BaLYNUtnFEArGdibmPYvYN07CDPoZk+bITFjUzDiPumvChrdh28dwzxNQ8yeHHhRXrKxZh3Px4g2b9Y9YAVnl1Kmr5Mr1te0/T5x4nly5zL6RD/b9Ciu7GYHhG69KzFGRvM99bgP8WdnIdtnujEP2zHbtpjJx4m6GDq3Da69Vc9uOOC2E1vSC3V9D0e5Q4/vkzSGx7k7iVE3KBTfOwkPLIGetmCv98MMmnnlmDg0bFmbuXDNOmNN9dO06g1Gjtsd8GuPKeX4rzCwHEWmMwNjeiAmJ1cY7fd4tH8Kmd6BIF6j1m393I8Lg5Hzw73GX/vLvxCFwtL1oWms0FOkcd6Pss2TeVcqw3NLELyEwELQJSiD0CaiA5V8fB0rAum4GbT9kdzv/mp8d9u8W78jRIStgHThwgGrVqlG3bl369OlD3rx5OXToEBMnTqRnz56UKBEbBDaQ5FXACiTNID2XxLiYkB1unhf1xQiLJ5kGJQOcCFmFOkHt34O0cUl024HKCjajPFzYYmRrkn4JdwssK5tbxmLQQvZjHEvdumNYtOgwP//8MN26xSbTHT9+Jx06TLPFvdm06QnHg1Y8Aft/gTJvQqWPk2iAJMPLyKJU3IcliUOdGZC/acxNSmwxiTHWsWNJxox5xOPNR0Z+QnQ0toyFt269atSzj5lTZzrkNwXZZIgg0W/JshAqPwDKvxdzuTVrjlG9+ihy5EjHyZM9SWGXpdCqZGWDfPbZCrYEBDEWQ1s/go39IF9TqCv7kWFclnaGg2MgS3ko2N4/V0pxp59SwHj2tr8EKdOHMVg3TbesYfM/Atmqxc06UO9D7QEloASUQBITUAHLP+CBErCiAIlsecrudi4BFYD9/t3iHTk6ZAWsV1991SZW7du3j4gICV2WNEUFrKThnOyvsn0YrDcXoM43G+4iijedJzvOEuR27w8QkQpKvQaVPvLmyNg6Ny8amctENGy8GsQyLlxj21hUbpw3mIio6iZQ8yuvLOCzz9bSu3cVPv+8fgzL55+fyzffbOSll6rw2Wexn9vcryzRpt4cyOsUG8u3Hgv+2palVLHnoPo3Me2ZO/cAjRpNoGjRLOzZ091tO99/fzkDBiyP+S7GQujMGphdHVJmhLanHCy7gh+Yjy3Y8z2sfhZy3m/EAjPLtWs3yZjxC1uGzCNHepAvn2u2u/Llf2bLltOMG/cI7duXjL3wrOpwdg1U/w6KPePjDYVYdSs2k9Usf95Vh6fC4laGGNZ0U4iBCkBz1rwIu42Mo7YSF+uz62GWmTVT3oedwjBLZgCQ6ymUgBJIegIqYPnHPFAClrgJ/gmIJZZVZDt1PnDF7rM2/t1ukh0dsgLWU089xcyZM1m5ciVFihRJMqAqYCUZ6uR9ISsejpUxzLpbdWPzvt9EHJGgwmK5VmMkFPUx1OC+n2Hlk3BXSWi23SXrnvc3EmI1rWx2tcdDoXYOjfv116106/YnDzxQgMWLO8V8V7Lkj+zadY6pU1vRokWx2GP+7g27hhsiY+k3DWuLcHZtsdyH0+WDVodjxtzZs9fInv0rG7ezZ18ga9a0LoOqe/dZ/PjjFtt3IhTevn3biIFluX1KQoPa40JsMPrYnL9fhl2fG/HWSvc1xp053sqUGcn27WeZMaMNTZve43Di48evkDfvCFsmSLHQypHDtAayrITEUrb1UZfMez7eXfBXl2fu7+aGX4qU0PlmwtokGxAnF8LJRZC1MuRvEd7PBU8URwvr28Zzs7Psj7spNgvMwnBNnDykvloSJ2xQ6lFKQAncCQIqYPlHPVAClmPQEM/35ONKy7/G+XG0bwKWTG6irvp+OYmrIBPOsm/C1sGGFUS5fr6dR+KKuHEL8HSSdevW0bp1a5vbYNWqVWnQoAGPP/44Zcq4z1Ak55kyZQqLFi3i008/9e3e7GqrgJVgdKF1oEzgZcyX7w/zGsDJ+UYMpugb6sbmS09bmcdyPgAPLfblSPirAZyYDxUG+f688e1KwVV7zQuw+yso+RJU/czh3rdsOUX58r+QKVNqzp9/kYiIFBw+fImCBb+1/X3mTC+yZLETXxa1gCPTYl1l/bHYCC6K7u9WMj1OzGFkCnv4b8hWNaZe0aLfs2/fBVuMJonV5Fw+/HAl77yzlDZtijNxYsvYr6eXgYvbodYoKPJoKFBKeBvicKV69NHp/P77Dj78sDZvv13T4RqjR2+nS5cZVKmSm7VrH4v9bvcIWNMTctwHjWKt3xJ+g0F+pAvf96H8u743Sl3e4mfmzMjJajPmBHtHwqqnjflDi30g/x3ulsTx09UaSkAJJBMCKmD51xGBErD8u4vkd7RvAtatKzDO1TQ/SZrV4TKktAsc7MVFo6KiWLp0KXPmzGH8+PHs37+fSZMm8cgj7mOQDBw4kEKFCvHEE04xXry4llVFBSwfYIVLVXsxSyatOvn0vufFQkIy3Mku9CO7IZOd9U9cZ7l6GKZItrfb0GI/ZEw6K0zvG3eHah4YA8s7Q9Yq0GStw03cuhVNpkxf8O+/t9i162lGjdrG5s2nmTRpN/nzZ6R79/KxmfHkyDn3w2lz4a/WhQZLS3Aq9y6IFYv5e+/YcRrjxu1k8OAH6Nu3hkvn168/lgULDvHVVw3o2bOy8f3FnYYVolgatTkFqTPfoUGTjC77e6TxPBBrlEdjrVaGDFlN376L6dChJGPHOr7jn3pqFj/9tIXXX6/GkCF1Yhuz4GE4NhsqDYYyfZNRI+/Qrci7SjZZdn4KUf/CPU9CzZG+38zFXTDddNNUlzf3/Kx5waWdcGAUpM1tWG3aZdfk+lmD4/XTUPm/UNrMnOl7j+gRSkAJKIE7QkAFLP+wq4Dlnl9IC1j2Tb5586bNlfDBBx/k999/5/vvv2fEiBHcuHGDsmXLMnbsWNq1a2cL7r5gwQKOHDlic0EsVy42kLE3Q1AFLG8oaR0l4AOBBU3g2Cwo+w5U/MC7A7f9Bza8CbkehIaLvDsmXGqt7WMsUMVtpcxbhshi5/aXP/8Ijh69wo8/NmbYsL/ZuvVMDJmYuEzyyYUdMKO08Z1aF8aOnsVt4PBkF6u0oUNX88Ybi2nXrgTjx7dwGG0Swylr1i+5fj2KHTueomTJbGCfeSxjUSjSVd2wnK1WyrwNlT60sZw9ez8PPzyREiWysnPn0zF8xRWzcOHvOHToErNnt6NRI1PM3vAWbB9iiGElekPqrMrXorbyKdj3ExR+FO4f5fuT8c974ZyI4+ryFi+8f0/C9NJGds3KQ6H0a8Yh8vs/OtOIz5YmJ4iFlrfvv3gvqhWUgBJQAklDQAUs/zirgOWen28CVkJdCMVtcOug2EWOLETFndCX4qMLofOpr1+/Tv78+Xn00Ud5//33qVevHmvXriUyMpLz58+TJUsWm3j12muv8eyzzzJ48GDEgqtfP99cHVXA8qVTta4S8ILAkvZwaAKkLwj3yML0dtwLTXlOzZTsg1uh+vdQzH3QbC+uHJpV4nHvqVbtN/7++7hL21OliuDGDTsLgPV9DQEgU0l4ZAeodaHB7N/TMCmn8XeKVNDZCLi8YMFB6tcfR5Eid7F//7MOfOfN+4eHHhpvCz5++PBzRhY9dcNy/f3ZrFYi4OA44/dtlznwxIkr5MljxLm6dKk3GTKkth2/a9dZSpYcSerUkZw79wLp06cyzru4NRyeou6v7p5yZ9fCrHsNy7+WhyBdbu+fhVePwpSCRqwmCbR/fL5aHcdHz3ITlOeFuLLu/AxOLoGrB2OPDHf37PgY6vdKQAkkSwIqYPnXLSpguefnm4CV0D5IYheqxx57zBbrqn79+uTOnduWifCjjz5iw4YNrF69mpw5c9osq8TiSoK9iwXW1atXKV++PHv37rW1cujQoaRPn55evXr51GoVsHzCpZWVQPwENr0HWwZ6N5GXZ43saO8ZYcQgk+yFlQfHf41wqxHjhpUCOt8yRAGziNtg164zHYiIeHXzZjQxFljRN41F6r8n4IHJULBVuBH03F4PwtOFC9fJkmW47bhTp+wCiQNvvbWYwYNX89hjZfj116bGuU+tgLm1jL/VPdOR947PYN0rRowxiTVmljx5vubEiausWPEoNWvms306YsQGevacR716BZk/v6NRU6yuZlYwRDDl634sz64JZ1ZBxQ+h7Nve/77XvwHbh0LO2vDQEu+PC+easunyxz1w5YB7Cvr7D+fRoW1XAkFNQAUs/7pPBSz3/JJGwPKv73w+WoKwT5gwgV27dnH58mUKFixIo0aNePPNNylQoIDtfJcuXbIFbRdLqw8//JB8+fIxbNgwxowZY/teAr6LuFW3bl2frq8Clk+4tLIS8I7A72YsIand5iSkNS1cnI+2sj9an+uutStfZ4Elf0uoI5YoRhk4cDnvvbccS7SqX78Qf/3VgQ8+WEFUVLQRA+vwNFjcwnBtaX3EsNTQYhCwiagnYM83hguVLVj+MNtXVjbHWbPa0rjx3THEatT4jdWrj/Pzzw/TrZvptj5NMnDuVDcsd+NKrNym5AMRUpush6yVbLUefngCs2cf4JtvHuK55yraPmvbdqothtugQbXp188M7n5kBixqbpxZ3V/d/3L3/w9WPG5YvkrwcPvYTJ5+6zfOGbEHJYlBnWmQ32Ssz4b4CVjx7mw1Uxhj+tx6HZ/xk9MaSkAJJGMCKmD51zkqYLnnF5ICVnxDZffu3RQvXtxWrWfPntSpU8cmaJ04cSLGZbBy5crMmzeP7Nmzx3c6h+9VwPIJl1ZWAvETiBFc5DF+GzLcA4/sgohIx2NlF3uD7P5/Ynxu574V/0XCqIZlEZsqI6zrA5HpjODBabLZIAwYsIzIyAj697/PUbSyR2S5X5XqA1X+G0bwfGjq3Afh1BIo2w8qDrIdKJnwJCOevZhy/vy/ZM/+FdHRtzl06DkKFMgE57fCTFPIarYdDo5XNyxn9Es7GFxKvAD3GpZt998/muXLj9rEK0k6cPNmFMOHr+f8+eusXNmFGjXyGmeZVwdOLoYc90Ojper+6m5YSxD3Cdkg6pphZXl+c/xjcOtHsLEfZC4HTTc6WHb68MsJz6rWe84SVHPVhdz1jUzG6p4dnmNCW60EQoCAClj+daIKWO75haWA1a1bN1auXGlzEaxVqxbDhw/nlVdeoUGDBrRo0YJbt27ZBC7JWuhrUQHLV2JaXwnEQ8ASXAq2gT8rw+2bRvDxSh85HmhvfWXL/nYL1ALLM1yxXhGe4kZVvBdU+9K7oSgumpPzG3ybboYsviW68O4iIVDr0CRY0hbSZDfiCKVMx6ef/k2fPgtp1aoYkycbbpdTp+6hVaspjsHHV3SD/b+CjPkHJoYAjERowrE5sKCxEXy99VGITEv79n8wYcKumItJQPddu86RJk0kb7xRjYEDa8PplTDnPsNqUDKUppdpkBa3BOY+AKeWxn4V1/N0Qz/Y9TlItuqCbQ0Ryy45hBL28j2ngpUOFSWgBEKIgApY/nWmClgqYPk3grw8WgUsL0FpNSWQEAIHxsDyzsaRNX8xMjRJrKA0WeD4X8bnGYtBi926a+0N3xML4a96hstKk3WGa+DtKM8LTxETJS6OZIVMlx+KdtdFqifO0VEwrShc+Qdq/ABFn+bJJ//k55+32qysnn22gs0l8+zZf21WQs8/X5Gvv37IqP9HMUMgbLwaslfzpifDr47EsZp6txHoutZoKNKZixeNOGNijOlcYuK3WVki73kKav4Yftx8abGI1ZOsAO4poM1xSJvL9Qw3L8PsGnBxm3dily/3oHWVgBJQAkogaAmogOVf16mApQKWfyPIy6NVwPISlFZTAgklMLsWnFnh+Wi1uvKN7AzJ2LjFu2xsG9+FrR/oItVbwtv/C+tfgzS5bIv//j0GM+i72Hhh5cvn4OjRK5w5c42OHUtSqlQ2BjQfC7uGQ+4G0GCet1cKz3pz68KpRQarXHX44JsI3v06TUz8NgtKypQpuHnzVbDFGSptuCI32waZ5W8tHgk4x8tLmRFa/gO7vooVui/ugiWt4YKdeKVBx3VQKQEloASUAKACln/DIJgELEl79zqQB9gIvAisjqP57QFZURQBdgN9AccUUp4PDksXQv+GUtxHq4CVmHT13EpAsrPfhDFpjTTtUtLmgX+PG3/rwsn3IXL1CEwxklvYSqNVkKO663nE9WrlE4YIoKy943zjPEzKZYxZ0601ousQbt92PyUZ+PwV+tf5jxF3qMhjUOtX764TrrXWvQo7jAD5UgYsGURkvvq2+G0NGoxj/vyDMWLWwJ7X6d9sApzfAJlKQuFOaj0Y37ix3LeFlcRki74RK3RLLMJMRQ2LzJsXY4ONa1D8+Kjq90pACSiBsCGgApZ/XR0sApbkeJYZaw9gFfAyIAJVSeCkGwT3AZKn+C1gOiC+NW8CVQDZUo+vqIAVHyEfv1cBy0dgWl0J+ErAJdhtfTg5X7M1+crRqu9sZSGf520CNX+Cxa1AXLXy1INtQwzLFSkSIF9ikam1W/zU17wAu7+y1ftg8kO8O6ERkZEpiIq6TY4c6Th9+prtu9Sporn+s+w/maX8+1D+3fjPH+417DOUpskBBdtB9REMePxZIiNu0/+nb/ngmT5End/NgDZ2e3s6dn0bOfaJBdwdmaMW5H1Yg477RlVrKwEloARCmoAKWP51b7AIWCJarQFeMJsbARwCJMXOYDcIxgIZAPtcxSuBDaYIFh81FbDiI+Tj9ypg+QhMqysBXwlYVgFWsFuJfZWngS6cfOVo1bd4luwNc2o5xrFxPmea3FD0KSOAvmbG8o74xndg64e2ugMmPkRkBPR/ozgffHmd+esysHBLQVKnvMWNWykZ2G42/VvP0wya3pE1xuDmd2Os22IPMzOW2j6w/9uaWaWGTte9vYrWEwIxrCMN98EsleD8JsMSVi1fdYwoASWgBJSAGwIqYPk3LIJBwEoNXAXaAVPsmvsLkAVo6QbBQUDs5z+z++59QNIbVXRTPw0g/6wiOaV3SLa9/PmNTDwRERFERkZy5coV/vnnH4oUKULatGlJkSKF7d/t27dt/6wS3+fR0aabj3mA1Jdifw7bFNPD53I/vl4zsevH1SYRsA4cOEDBggXJmDGjra2S1dC+pEqVCjlHVFSUA8eUKVN6/Fzq2l/X6idPn8s17RlLn8oxnj6/efOmwz3Kvbi7d0+fa5tSIGy0nyI9jjEde67PgmT3e0qRgqgdnxOx/hWHZb9NAkiRklvt5BVlFH1GgDfPvYitAyFFJLfzNCLl4qZw80IMQ0PQum0TrT6Y3JCo6BS8134RKaJvEF1uABEV3tPfU0QEnt5P0RKTLUUk0WX6EbGpHxHHppPi4na3s8XbOeuS4tRCbkektvGNKjuAyIrv6Ts3MtLje8v+mS3jOEVEKiIqvEvUxvdJcXIBEacWxfAUa8ybpcQBILboM8K7Z4T9fFrnEcYaROewnp97zmuKZDeP0LWGrp/s1rlHjhzh7rvvFiYSq+KI2xe0fuiRQDAIWPnMjq0F2EcoFr+NOkANN62TgATdgN/tvusJvAdYqWPsDxtgfudwqh9++IEcOXLYPitUqBCVK1dm3bp1NgGkQIECpEmTxvYvXbp0XL582UGQkc/ku4sXLzoILBkyZLBN7s+fP+9wrUyZMtnEKqlvX+666y7b9S5duuTweZYsWWyTVxHUrCJCjNS/fv06164Z7hfWgkpEI/lMvrNK6tSpSZ8+PVevXuXGDUFmlMRok1xX1Objx4/TqFEj270sWLDA4R6bNWvGyZMnWbEitpuFS/369W2i4abMTCsAABx3SURBVIYNYkBnlJw5c1KrVi127NjBzp1m7Bm7flq/fj0HD4qOaZSSJSUQcCmWL1/OqVOnYj6vVKkShQsXZv78+Q6M77vvPnLlysWMGTMc+rVevXq2/p450zGcWtOmTbVN2k+2Z4SOvdD8Pe3740nuufwzUaQkElN8N+PabE/VmV2pxdMd9BmREp+f5ffdx+3fU5GCKG4Twf6UTbj71p+kINr23ztSdbTxLXFjLDmzZyNH/S/1We7D+6l54fVEbnufaCKJwNggsv6+keV+9l4pFMM3bepU3N3yF33nJvBZnu/Md7YxK+O1Qe4VZEyflhmHquk8Qud7OofVebmuNXT9FLPOPX36NN27d5fXsQpYMaty7/8IZgFrKPCAJI1301x3ApYEge9vBoF3PsRrCywRevbs2WMTULJnz64WWKaVmIhvcVlgnTlzxiYc3XPPPTaBTIpaYLm3NlNrJd1lFDFarf+S1zMiesO73E4RYbNqiVz4ECnkfw8tIGrjAJvrUHRZIy6TWlckwLpi+8c2lzfLCig6Z10iTi2Mid8WVfY9G3cplpWtWiL48IzYPshmkXWr1Fu2sSslqu5cUu0YzO3oW9wq807MnEje5Wr1bFi7qCW3Wqe7m6uqZY8+I9TbA9szUj1YEu6VoxZY3otV7moGg4CVFC6Ezmw8xsCSiseOHbNZUImFjlgwWW5+/nVFaB4t1mNi4SWWVWI1ljeveGdqUQJKQAkoASVgEtD4bToUlIASUAJKQAkogTAhoDGw/OvoYBCwpIUSxH018KLZXAniLv5hX8YRxD098IgdnuWARNaUTIbxlTgFLBFlxBXO2Q0wvpOG8/ciXuXJk0fFvnAeBNp2JaAElIASUAJKQAkoASWgBJRAGBNQAcu/zg8WAUuCi/wKPGsKWS8DHYBSwAnzOwmA9paJQ+JlLQYk9/YMoBPwNlAF2OIFsjgFLOt4MS93dvPx4txhV0VifompqRYloASUgBJQAkpACSgBJaAElIASUALhSkAFLP96PlgELGnlC8DrZgwriebd27TMku8WAgeAJ+xwtAcGAUWA3cAbgGPkbc/svBKw/EOvRysBJaAElIASUAJKQAkoASWgBJSAElAC4ULADwFLYnpbeshG0ztNvNQ8FdFDPrDTQ8S4x1s9JNl2RzAJWEkJUQWspKSt11ICSkAJKAEloASUgBJQAkpACSgBJRDiBBIoYFkeaRIOScIriUeaCFQlgZNukN0HLDE91KYDnYE3ffBIS7a9oAKW+65RASvZDlm9MSWgBJSAElACSkAJKAEloASUgBJQAsFHIIEClohWa0yvNGm0xAQ/BAyPIyZ4BqC5HaGVgHiyeRMTPNmCVQFLBaxkOzj1xpSAElACSkAJKAEloASUgBJQAkpACYQKgQQIWKmBq0A7YIodh1+ALEBLN2wk4d0w4DO7794HWgEVg5mlClhxCFirV68mb968wdy/eu9KQAkoASWgBJSAElACSkAJKAEloASUQDIgcOzYMapXry53Ignpjtnd0nVA/jmXfIAkrJNEdSvsvhwC1AFquDnmBtAN+N3uu57Ae0DuZIAhwbegApZ7dJKtcG2CqeqBSkAJKAEloASUgBJQAkpACSgBJaAElIAS8I6AWEgN8EHAGgo8ANT0UsCSIPD9zaR43t1RMqylApb7ThEulYETybDP3N1SRmCHqeJeDpJ7DqbbVL6J11vKNvHYypmVb+LxVbaJx1bHrrJNXAKJe3Z9NijfxCWQeGfXsZt4bPW9pmydCRQEtjl96MkCS10I7UCpgJW4P6akOvtdwAUgM3AxqS4aRtdRvonX2co28djKmZVv4vFVtonHVseusk1cAol7dn02KN/EJZB4Z9exm3hs9b2mbP0lIEHcVwMvmieSIO4S5+rLOIK4pwcesbvwcmCTBnH3tyv0+EAQ0BdOICh6PofyTTy+yjbx2OpkSdkmLoHEPbs+GxKPr7JNPLb63E1ctso3cfnqs0H5Ji6BxDt7OIzdjsCvwLOmkPUy0MH0wBKvMflO4mS9ZWKWeFmLgb7ADKAT8DYgoZK2JF5XJP6Z1QIr8RknxRXC4UebFBw9XUP5Jh59ZZt4bHWir2wTl0Dinl2fDYnHV9kmHlt97iYuW+WbuHz12aB8E5dA4p09XMbuC8DrZgyrDUBvQCyzpCwEDgBP2GFuDwwCigC7gTeAmYnXDUlzZhWwkoZzYl8ljam2fuwhc0FiXz/Uz698E6+HlW3isZUzK9/E46tsE4+tjl1lm7gEEvfs+mxQvolLIPHOrmM38djqe03ZJi6BMDq7Clhh1NnaVCWgBJSAElACSkAJKAEloASUgBJQAkpACQQjARWwgrHX9J6VgBJQAkpACSgBJaAElIASUAJKQAkoASUQRgRUwAqjztamKgEloASUgBJQAkpACSgBJaAElIASUAJKIBgJqIAVjL2m93ynCdQFFgBZgfN3+mb0+kpACSgBJaAEAkDgNtAamBKAc+kplIASUAJKQAkoASUQcAIqYAUcaaKc8GcgC9AqUc4enicVpt3cNL04sCceJCpgxQ3IYvst0MOp6tfA88AvTlkywnMU+t9qSZG7BPgTaO7/6cL6DDpuk6779Z2WNKx95awCVvz9os/c+BklpEZOYCDQDMgNnAM2mp8tS8gJ9Ri3BAoC7wMPAzmAY6ZgLezPeMFM57+OkKx5w1vAYLuvZL02GdB1theDKo4q9mu1W8BZYBPwOyDfRft3ej06WAnoDys4es7XSWhwtOrO3qUwlUnSk063cQqIUgHLr84RtvUBSWmbF7hmni2tOVm6aFqw2ad59eWCqYCbvhwQwnV/AC4DTwOlgCN+tDUSkAVsuE4IEnvc+tE1IXeovtOSpkt95awCVvz9EshnbvxXC58ai4HUZkbtfeb8rAGwFfgjfDAkakvvAVYAu4B3gP1AWWCoyb6mKRDEdRMqYLkKWB2BfwHhK8KrFBWwAjOU7ddqMkeVdZuIryIYyuZtC0CELS1hRkAFrODocPtJqPxw5cVTzhRa5GX0ErDXbEoR86XUFngRqAHsNi1hpK4Wg0BcE/sIoC/wLJDHfNl/AEww4VkvcLF4+RgoAWwAugNbFHAMW3mZ/wcYZTJ5FHgTkMmpuF6KgOXteO4E9DTHs1h1Sf+Fe8lgCoLVzB1V2ZX6yIcxKvw/Ax43dw5lHBcDDoQpWOuZEIhxOx/YBrxgx1IsDERglDEv34dzsX/+yniTcSj/rCLPU3FjG2B+IMLKM6Z1RmOT46u6sI13CCWEs7oQesYa1zPXep6KtbxV3C1iZf7WG0gHjAVOm8+ESvH2ZuhWEGay8Je51SIPzZQ6nwAtgTTA38ArppWWHCLPCuE9wpwjZwemm8+NC6GLzqeWiaW2rB3kXW9tLMoJZJ4ra4hfTQt54SsWWTJnywUcNOcIf5nrC/uLhrs1vTxjZazJ3Gka8IYJx/m3L2syYSr1xOptOPBfs66sI+oBIiDaF5nTjQdk/RGuxdNaTTbJZTzKvEA2FeJ7Pgi/R4B3gfLmxq+I5m3CFWywt1sFrODoQfsfsDwEZTK/GZDJlDwQRbSSyY9YTlgC1g7gNVO8+hCQRa48OFWpNvo8LgGrH9AVeNnk9yDwDSALJ5lcWQLWdlM8PG4KB9bEINytgyy2wkrcARqaP7N55oRS+FkClrfjWRa5smBdb+50yQQg3MtT5mRTftsipooAIC6w8nzwZozKgus7YA3wuuk+cAi4GqZgAzluZeL/pWmBeN3kKYstWbiKQCZ9FM4lIcLKYXNxIONVNmdk/Bf2wmJAORsLe2+FQhWwPI+YuJ653ghYXczFlmzGiFucbMzIe00sYcJZwEppCliyEJVNLuuZad8Tc03RRea8Ikg9Z26CiRgjbkUiYMmcd5XJVCzAfwRWA8I93Es2UyyV+a0IJs5F5gLtTDFmDHCfOb8VN867TXdD2cQVAXEiUBIQa3oRwsJZILTeZSLkjTbnYPKushewqprjUMaoiNbihizhNOQ5IMfL2kHWdLJGs4wRxDJONsTtPwvHMRzXWk02uo4CTYH4ng+yFpkKyHpYxrdYe8pn1qZvOLIN6jargBUc3RfXD1h29U+airI87CwBS6yB5OUtpYxphl0aEGFLi/HSEJFKzH6tIrtT8plMhkR0sbdYk4lVenNHyhIHZPIpLyMpMjmQl5ZMYseFOWBrvMoYFCbi2iYLdhl7En9BWFoCljMqT+NZxMTPw5yrc/NlASRjTbjIAkBEvfbAQjsBK64xKmP1J3PhJJPUcC+BHLeygy0TK4n3Zj0PhPEk01pOWcfGdfRWWBkE9DfByebNJXPiOivcYcbR/oQIhSpgeQYa1zPXGwFrpWk5ZG+ZuRTIGOYClhCXzazvTcu0deZmoSw0xQqlNjDDtAayF7ckXukQcyNGxAGxbpM5sMw7pIi1qxyXH5CNxnAu4o0h48/T71s2WIaZVu4iAj4EyKajc1EXQkci9s9YWTOI5bWEdLAXsMQLQea2jewOlXErAooIVVJkfiACoWVtJcKKWGWJkBjOJa71rzwfKpjeMvE9H5ab3h+yxtMSAgRUwAqOTrT/AYuFhexAyctIAjCKu5tM5uVBONNOwKpuWlZICyVbnogydQAxmdRiCFgyqZEFplWumEKUCIHyt30RtV6sf4S79QKX3X8xrbaKfC9uLxIgM5yL/XiVnTqZgMqzRnaZZIdPGFkClrfjWSawGsg1dlTJ7qeM0wLACfNjsfiRXWdxCfRmjMqCSwLtS2yycLcIEoSBHLdyPhEWpZ9kEVXFXLjKTvY/4fxwMNueEGGlg+lOYeGTXX+xxBK3Fy3uCSSEswpY7lnG98z1RsASNzkJ+WA/ZkU0EHeYcLbAsojLu+gB05WqCSDzWNkIkznuF05ub3KMuGGKW6GEfBABS959YuFqlczmXCMu18RweXbEJ2D1MV3aZNNLBBdh686bQAUsxxFj/4wVbw0JDyCiilgGWkHcRZAV6x/7tYFYsol7oHCWuLvieigWnrLhK/NlCbUhLoYyrwvnEpeAJQYEsq4Qa7b4ng/iWdDL3LQNZ54h03YVsIKjK+1/wGLFIgsgUe9lh18ELFnIWpNOywKrshmXSVpoxRcQNV+sM7R4diG0XvLyknYOiC07f+JiFZc4IC8sERjDudiPVxFWrRewvDxEZLUXsBIynsOZrdV2+f2L2599wgF5nssYlcD58vtfYLpYOYus1hh1t+AKZ7aBHLfCUeIsiIm7CN2ywJKJqexqa3F8/spEXeKBfGoHRgI3y+TePgaWs7AiIrhYZmo8PM8jyn5MJ5SzjleDQHzPXFmQyjgW0cQqYhErFpjWXFsELHEj/p9dHRn3MjdTAct1pIm1tjwzZYEqYrXMvZyLPAckjpg7AUs2dETo1s1bI06TJCkSKzV3blOWC6Fk55Y5ggpY3j35nAUWsQQS4U8+twQs2dx2XhuIhZY8GywBSzYjZa52r/mZrNVkk108bMK5xCVgyea4MJNg7vE9HyTDprgYi9eBlhAgoAJWcHSi9QMWs1R5UYvKLz9YKWKZIn+rgOVbX3p6KGYyX/ISGNB+kml/dkvAkswjlnuQWLmJ2bpkNVQXwlj3IMkaYgkohUzBxRKwJPZHQsazbz0derXFXVDGmiyo5jg1T9jKjrQIgyJgxTVGVcByhGf/TPB33FpnFlcMcXETlyH5J6mftTgKWMJI4uVZwW9l0SnuPjK+VcDyb7TYj+mEcvbvDkLjaG+eubKxKItXmUNYFtwSb+VtOwFLXLisGG4WGZm/yTEqYLmOFbEKEn6dAQnxEFeSEcuFUOYZsrkrReKWyqaZuhAaPGabLmti+e4piLsk3hGxW9zd3LkQSvwmsYYXDxARBcK9OK8lrI0rsZ6STUZZZ3tyIZTYTWJBZBURrdaaApYYI8j34V48rdWsIO5itSbz4fieDzIfFqMEdSEMkRGlAlZwdKT1A5ZsCaLGyw9VTFHlRT3YDNCuApZvfRmXqi+xViTTnQgsEp9CdlTvNwNWSqBGS8ASKwFxBxAXLpmoygRUJgY3fLuVkKvtzFYWpFIk4KcUS8CSF09CxnPIAfOxQbJzJ6bTkh3IOXiqTD7lxS4TJ3lhxzVGVcByBB/IcWudWYRwsUAU83WxjLOPuedjt4dUdXvWElBYxqK4CIo1hViwSgxCWQCogOVftweCs393EBpHe/PMFbFENmsk9qi4s4g191Agn52AJcHEJc6ThC6QmCyywSDPahEMxGo2XItYB4nF5Ugz5IDEtxNLFLFoE1FQ3Agl/IUIfSJ07zK5ioW3WLZIRkIriLvEIRJLC5l3iAWXuG+JAKbFmJ/KuJMERGKJJckDJAaTjFOJ2yhZ8CTciFipNDCtBSU2k1gRy3xDNmdFDBRPBNmsFXFQhLDLYQzX3VpCXITF+lJcYmWdLSEERLi2grhLXCvJlmkFcbefL0gdCVki1sVWBu8wxmuzZMttjjfZWJS/JSzDW6ZHkTybJYFZfM8HWbdJ1kJZ30nsLNmUEDdl2SjTEoQEVMAKjk6Th6EEEJf4QTKxl8mR+PnvNF8wotqrgOVbX8YlYMnvQsxR5eUinGVRJZMgMbuWh6QlYElKVhEQZVIgrkKyWBWT1nAvcbG1F7Bk0ZqQ8RzufCVVs7gOy+TduUjMELG0EGFVYjDFNUZVwHKkF8hxa51ZgjOLwC3nFhdaLQYB+3eaLDRlUS+TUhFkJVC7BBQWoVsFLP9GTCA4+3cHoXG0N8/ciuZ8QcQAcQcS65U/zADj9nNtGd/iRiiLWxEEZPEvz+1wDtYs4on81sXqpyiQyhRJRNSSeZeIJCJeyUahBHuXgNhipSnzMVnIiqAix8tiVuI6ijgjiXWmmwGexXVTi0FAxCjZAJfnrTASjlbsVsuiSsamcJd4WCIuijAr/225X8kYlvmxiAnyjJG5RLgWd/MGYSzrMxnX1m9fxq1szsh6QRLuiDgr1vL2RcK9SH9IaAgRDJ1j8YYjY+Erbq1SbpnZSkVUlYyPYlAg4pWU+J4PUkeMQGTsSmIz2VCX54f0i5YgJKACVnB0mrigSLYV+8w1wXHnepdKQAncCQIaaPVOUHe9prgBSFrsaqYInjzu6s7fhb7TkqYPlHPScPbnKpL+XRatj/lzEj02RsBSV0wdDEpACSiBECegAlby7mCJqyT+5pLJTXZCZJdEixJQAkogPgIqYMVHKHG/FwsCcRkUl05x9RYXZC1GRlx9pyX+SFDOic84IVcQS3oJTyCxiMTKQlzb3jUDlbuLN5SQa4TrMZYFlgpY4ToCtN1KQAmEDQEVsJJ3V4tvv+zci5mkmERrqvvk3V96d0oguRBQAevO9oTFX2K1iOv35jt7O8nm6vpOS5quUM5Jw9nXq0jGMXFHlJg44l4kbkYSk2WSryfS+i4EVMDSQaEElIASCBMCKmCFSUdrM5WAElACSkAJKAEloASUgBJQAkpACSgBJRCsBFTACtae0/tWAkpACSgBJaAElIASUAJKQAkoASWgBJRAmBBQAStMOlqbqQSUgBJQAkpACSgBJaAElIASUAJKQAkogWAloAJWsPac3rcSUAJKQAkoASWgBJSAElACSkAJKAEloATChIAKWGHS0dpMJaAElIASUAJKQAkoASWgBJSAElACSkAJBCsBFbCCtef0vpWAElACSkAJKAEloASUgBJQAkpACSgBJRAmBFTACpOO1mYqASWgBJSAEggjAguBDcDLyazNt4HWwBQP91UE2A9UNu8/md2+3o4SUAJKQAkoASWgBO4cARWw7hx7vbISUAJKQAkoASWQOASSq4CVBzgHXFcBK3E6Xs+qBJSAElACSkAJhC4BFbBCt2+1ZUpACSgBJaAEwpXAnRCwUgM3/ASuFlh+AtTDlYASUAJKQAkogdAloAJW6PattkwJKAEloASUQLgSEAFrE/Av0N0Ulr4BBphACgHDgQZANDALeBE4YX7/M5AFaGUH8DOgElDX/EyusQW4BXQFNgP14gHu7EJYHfgWKG2e60Ngkp0L4btAD6A8cMY89wwgvd29h2sfa7uVgBJQAkpACSiBMCOgAlaYdbg2VwkoASWgBJRAGBAQcUniSA0DRgP3ASJKNQbmAWuBK2aMrJTA18AlO3HKWwGrKjAC+NFkutMHASuDGe9qLvARcDfwOXCPnYAVCSwxhTWJndULEJGrAnAwDPpRm6gElIASUAJKQAkogRgCKmDpYFACSkAJKAEloARCjYAIWCL+PGDXsNXAfOAv4E9TMDpkfl8G2AqIRdQaU+zyxgIrsyk2ecvP3gLr2f+3d7+sUgVhHIB/RTBoMlhEDBYxaBEMJoOgxahg0SA2r34CEYOYBMEggoJ/goKgH0I0CGKxmIw2g00ReWEWj5d7F3a898DueaYte2bnzDObfsy804KrfW2nWP1G7baqQGxYxL0CrSpIXyHb1bajrEI5jQABAgQIECAwKQEB1qSW22QJECBAgMAkBCrAqkCqdizN2pt2DK/CoOstwBpiVHH1tSRPFgiwviS5vIDoMMC6m+RIkpOD/vW53m/9LYQVdtVRwxdJzi8wnkcJECBAgAABAisjIMBamaU0EQIECBAgQKAJbFTE/XWS70k+tqCqdjYNW31XdbCeJnmUZE+Ss4MH7ic5vK4GVoVN1xZQHwZYVVOraltVHa5Z2yzAetaCqw9JTrS6WwsM61ECBAgQIECAwPILCLCWfw3NgAABAgQIEPhXYF6A9XzOEcJjSSokutMKsteRwll7m+TnFgZYGx0hvJKkis0Pd2CdS/I4yakkL5M8THLDghMgQIAAAQIEpiYgwJraipsvAQIECBBYfYF5AdalVsT9x7oi7vV5dsNgFXuvOlkXk7xrtwzWTqvavTW8hfB/dmDtakXc6wbE20kOtCLuBwcBVtXHqtsUK7CqWxMrxKpbCKu21/vVX0YzJECAAAECBAj8FRBg+TcQIECAAAECqyYwL8CqUGp/C4Tq+N7vJBUi1fHBbwOIm0lqR9TOdqRwRzvyt1UBVg11vO24OpTkc5JbSV61AOtTkrqh8FeS00nq+GG1e0nOJDmapEI3jQABAgQIECAwCQEB1iSW2SQJECBAgAABAgQIECBAgAABAssrIMBa3rXz5gQIECBAgAABAgQIECBAgACBSQgIsCaxzCZJgAABAgQIbLPAhSQPNhnja7vBcJtfwc8TIECAAAECBFZXQIC1umtrZgQIECBAgMB4AruT7N1kuLq9sEIsjQABAgQIECBAoFNAgNUJpxsBAgQIECBAgAABAgQIECBAgMA4AgKscZyNQoAAAQIECBAgQIAAAQIECBAg0CkgwOqE040AAQIECBAgQIAAAQIECBAgQGAcAQHWOM5GIUCAAAECBAgQIECAAAECBAgQ6BQQYHXC6UaAAAECBAgQIECAAAECBAgQIDCOgABrHGejECBAgAABAgQIECBAgAABAgQIdAoIsDrhdCNAgAABAgQIECBAgAABAgQIEBhHQIA1jrNRCBAgQIAAAQIECBAgQIAAAQIEOgUEWJ1wuhEgQIAAAQIECBAgQIAAAQIECIwjIMAax9koBAgQIECAAAECBAgQIECAAAECnQICrE443QgQIECAAAECBAgQIECAAAECBMYREGCN42wUAgQIECBAgAABAgQIECBAgACBTgEBViecbgQIECBAgAABAgQIECBAgAABAuMICLDGcTYKAQIECBAgQIAAAQIECBAgQIBAp8Afp0+kxpi84EkAAAAASUVORK5CYII=\" width=\"1200\">"
+ ],
+ "text/plain": [
+ "<IPython.core.display.HTML object>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "unc_arr = Ssh[Ssh['std'] > 0]['std']\n",
+ "Ssh_arr = (1 - Ssh_50cm[Ssh_50cm['std'] > 0]['mean'])\n",
+ "\n",
+ "plt.figure(figsize = (12, 3))\n",
+ "ax2 = plt.subplot()\n",
+ "\n",
+ "Ssh_arr.plot(ax = ax2, marker = 'x', markersize = 3, c = 'orange', label = '$S_{sh}$')\n",
+ "ax2.set_ylabel('Partly shaded fraction $S_{sh}$')\n",
+ "ax2.yaxis.grid(linestyle = '--')\n",
+ "\n",
+ "ax = ax2.twinx()\n",
+ "#ax.set_zorder(10)\n",
+ "#ax.patch.set_visible(False)\n",
+ "\n",
+ "# Ssh['mean'].plot()\n",
+ "unc_arr.plot(ax = ax, marker = 'x', markersize = 3, c = 'darkblue', label = '$\\sigma_{Ssh}$')\n",
+ "ax.plot([0, 287], [-1, -1], marker = 'x', markersize = 3, c = 'orange', label = '$S_{sh}$' ) # dummy for legend\n",
+ "# bias_arr.plot(marker = 'x', markersize = 3, c = 'orange', label = 'bias$_{Ssh}$')\n",
+ "\n",
+ "ax.set_xticks(list(range(12, 24*12, 24)))\n",
+ "ax.set_xticklabels(calendar.month_abbr[1:])\n",
+ "ax.set_ylabel('Uncertainty $\\sigma_{Ssh}$')\n",
+ "ax.set_xlabel('')\n",
+ "ax.set_xlim((0, 12*24))\n",
+ "ax.set_ylim((0, 0.4))\n",
+ "ax.legend()\n",
+ "\n",
+ "plt.tight_layout()\n",
+ "plt.show()\n",
+ "# plt.savefig('Ssh_sigma_zenith.pdf')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 67,
+ "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 overriden (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=\"1200\">"
+ ],
+ "text/plain": [
+ "<IPython.core.display.HTML object>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "plt_arr = Ssh[Ssh['std'] > 0]['std']\n",
+ "bias_arr = (1 - Ssh_50cm[Ssh_50cm['std'] > 0]['mean'])\n",
+ "\n",
+ "# plt_arr[plt_arr == 0] = np.nan\n",
+ "\n",
+ "plt.figure(figsize = (12, 3))\n",
+ "ax = plt.subplot()\n",
+ "\n",
+ "# Ssh['mean'].plot()\n",
+ "plt_arr.plot(marker = 'x', markersize = 3, c = 'darkblue', label = '$\\sigma_{Ssh}$')\n",
+ "bias_arr.plot(marker = 'x', markersize = 3, c = 'orange', label = '$S_{sh}$')\n",
+ "\n",
+ "ax.set_xticks(list(range(12, 24*12, 24)))\n",
+ "ax.set_xticklabels(calendar.month_abbr[1:])\n",
+ "ax.set_ylabel('Fraction of roof surface')\n",
+ "ax.set_xlabel('')\n",
+ "ax.set_xlim((0, 12*24))\n",
+ "ax.yaxis.grid(linestyle = '--')\n",
+ "\n",
+ "plt.legend()\n",
+ "plt.tight_layout()\n",
+ "plt.show()"
+ ]
+ },
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Merge shading data and SVF data to compute correlation"
]
},
{
"cell_type": "code",
"execution_count": 49,
"metadata": {},
"outputs": [
{
"data": {
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"\n",
" .dataframe thead th {\n",
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>8</th>\n",
" <th>9</th>\n",
" <th>10</th>\n",
" <th>11</th>\n",
" <th>12</th>\n",
" <th>13</th>\n",
" <th>14</th>\n",
" <th>15</th>\n",
" <th>16</th>\n",
" <th>31</th>\n",
" <th>...</th>\n",
" <th>254</th>\n",
" <th>255</th>\n",
" <th>272</th>\n",
" <th>273</th>\n",
" <th>274</th>\n",
" <th>275</th>\n",
" <th>276</th>\n",
" <th>278</th>\n",
" <th>279</th>\n",
" <th>Csh</th>\n",
" </tr>\n",
" <tr>\n",
" <th>DF_UID</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
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" <td>-0.800000</td>\n",
" <td>-0.960000</td>\n",
" <td>-1.0</td>\n",
" <td>...</td>\n",
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" <td>-0.200000</td>\n",
" <td>-0.480000</td>\n",
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" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>-0.680000</td>\n",
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" </tr>\n",
" <tr>\n",
" <th>4817084</th>\n",
" <td>-0.120000</td>\n",
" <td>0.0</td>\n",
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" <th>4817085</th>\n",
" <td>-1.000000</td>\n",
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" <td>...</td>\n",
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" <td>0.000000</td>\n",
" <td>-0.970588</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>-0.735294</td>\n",
" <td>-0.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>5 rows × 146 columns</p>\n",
"</div>"
],
"text/plain": [
" 8 9 10 11 12 13 14 15 16 31 ... \\\n",
"DF_UID ... \n",
"4817081 -0.357143 0.0 0.0 0.0 0.0 0.0 0.0 0.000000 -1.000000 -1.0 ... \n",
"4817082 -0.076923 0.0 0.0 0.0 0.0 0.0 0.0 -0.076923 -1.000000 -1.0 ... \n",
"4817083 -0.120000 0.0 0.0 0.0 0.0 0.0 0.0 -0.800000 -0.960000 -1.0 ... \n",
"4817084 -0.120000 0.0 0.0 0.0 0.0 0.0 0.0 -0.400000 -1.000000 -1.0 ... \n",
"4817085 -1.000000 0.0 0.0 0.0 0.0 0.0 0.0 0.000000 -0.882353 -1.0 ... \n",
"\n",
" 254 255 272 273 274 275 276 278 279 Csh \n",
"DF_UID \n",
"4817081 0.0 -0.464286 -0.035714 0.0 0.0 0.0 0.0 0.0 -0.678571 -0.0 \n",
"4817082 0.0 -0.615385 0.000000 0.0 0.0 0.0 0.0 0.0 -1.000000 -0.0 \n",
"4817083 0.0 -0.200000 -0.480000 0.0 0.0 0.0 0.0 0.0 -0.680000 -0.0 \n",
"4817084 0.0 -0.320000 -0.320000 0.0 0.0 0.0 0.0 0.0 -0.480000 -0.0 \n",
"4817085 0.0 0.000000 -0.970588 0.0 0.0 0.0 0.0 0.0 -0.735294 -0.0 \n",
"\n",
"[5 rows x 146 columns]"
]
},
"execution_count": 49,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"shade_bias_hourly.head()"
]
},
{
"cell_type": "code",
"execution_count": 50,
"metadata": {},
"outputs": [],
"source": [
"merged_df = shade_bias_hourly.merge(skyview[['bias']], how = 'inner', left_index = True, right_index = True)\n",
"merged_df.rename(columns = {'bias' : 'SVF'}, inplace = True)"
]
},
{
"cell_type": "code",
"execution_count": 51,
"metadata": {},
"outputs": [
{
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},
"execution_count": 51,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"merged_df.head()"
]
},
{
"cell_type": "code",
"execution_count": 52,
"metadata": {
"scrolled": false
},
"outputs": [
{
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" 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 overriden (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"
},
{
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\" width=\"640\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x7f99396da668>"
]
},
"execution_count": 52,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"merged_df.plot(x=10, y='SVF', style='o', markersize = 1)"
]
},
{
"cell_type": "code",
"execution_count": 53,
"metadata": {},
"outputs": [],
"source": [
"corr = merged_df.corr()\n",
"cov = merged_df.cov()"
]
},
{
"cell_type": "code",
"execution_count": 54,
"metadata": {},
"outputs": [],
"source": [
"corr_w_SVF = pd.concat([corr.loc[:, 'SVF'].rename('corr'), cov.loc[:, 'SVF'].rename('cov')], axis = 1)\n",
"corr_w_Csh = pd.concat([corr.loc[:, 'Csh'].rename('corr'), cov.loc[:, 'Csh'].rename('cov')], axis = 1)"
]
},
{
"cell_type": "code",
"execution_count": 55,
"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 overriden (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": [
"<matplotlib.axes._subplots.AxesSubplot at 0x7f9939725128>"
]
},
"execution_count": 55,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"plt.figure()\n",
"corr_w_SVF['corr'][:-2].plot()"
]
},
{
"cell_type": "code",
"execution_count": 56,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"corr 0.356733\n",
"cov 0.010845\n",
"dtype: float64"
]
},
"execution_count": 56,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"corr_w_SVF.mean()"
]
},
{
"cell_type": "code",
"execution_count": 57,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"corr 0.125164\n",
"cov 0.005559\n",
"dtype: float64"
]
},
"execution_count": 57,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"corr_w_Csh.mean()"
]
},
{
"cell_type": "code",
"execution_count": 58,
"metadata": {
"scrolled": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"correlation between SVF and C_sh: 0.564\n",
"covariance between SVF and C_sh: 0.014\n"
]
}
],
"source": [
"print('correlation between SVF and C_sh: %.3f' %corr.loc['Csh', 'SVF'])\n",
"print('covariance between SVF and C_sh: %.3f' %cov.loc[ 'Csh', 'SVF'])"
]
},
{
"cell_type": "code",
"execution_count": 59,
"metadata": {},
"outputs": [],
"source": [
"corr_save = pd.concat([corr_w_SVF.rename(columns = {'corr' : 'corr_SVF', 'cov' : 'cov_SVF'}), \n",
" corr_w_Csh.rename(columns = {'corr' : 'corr_Csh', 'cov' : 'cov_Csh'})], axis = 1)\n",
"corr_save.index.rename('hour_idx', inplace = True)"
]
},
{
"cell_type": "code",
"execution_count": 60,
"metadata": {},
"outputs": [],
"source": [
"corr_save.to_csv('/work/hyenergy/output/solar_potential/uncertainty/covariance_DSM.csv')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Attach rooftop data"
]
},
{
"cell_type": "code",
"execution_count": 61,
"metadata": {},
"outputs": [],
"source": [
"ROOFS='/work/hyenergy/output/solar_potential/geographic_potential/CH_ROOFS_all_replaced.csv'\n",
"roofs = pd.read_csv(ROOFS, usecols = ['DF_UID', 'NEIGUNG', 'AUSRICHTUNG', 'FLAECHE'])"
]
},
{
"cell_type": "code",
"execution_count": 62,
"metadata": {},
"outputs": [],
"source": [
"SVF = skyview.merge(roofs, left_index = True, right_on = 'DF_UID', how = 'left')"
]
},
{
"cell_type": "code",
"execution_count": 63,
"metadata": {},
"outputs": [],
"source": [
"SVF['AREA'] = util.round_to_interval(SVF['FLAECHE'], 10)"
]
},
{
"cell_type": "code",
"execution_count": 64,
"metadata": {},
"outputs": [],
"source": [
"SVF['bias'] = SVF.SVF_2m - SVF.SVF_50cm"
]
},
{
"cell_type": "code",
"execution_count": 65,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"SVF_2m 7.272423e-01\n",
"std_2m 6.351421e-02\n",
"SVF_50cm 6.556163e-01\n",
"std_50cm 9.321401e-02\n",
"bias 7.162608e-02\n",
"DF_UID 5.004925e+06\n",
"FLAECHE 8.545578e+01\n",
"NEIGUNG 2.264418e+01\n",
"AUSRICHTUNG -2.870675e+00\n",
"AREA 8.539042e+01\n",
"dtype: float64"
]
},
"execution_count": 65,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"SVF.mean()"
]
},
{
"cell_type": "code",
"execution_count": 66,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
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" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>SVF_2m</th>\n",
" <th>std_2m</th>\n",
" <th>SVF_50cm</th>\n",
" <th>std_50cm</th>\n",
" <th>bias</th>\n",
" <th>DF_UID</th>\n",
" <th>FLAECHE</th>\n",
" <th>NEIGUNG</th>\n",
" <th>AUSRICHTUNG</th>\n",
" <th>AREA</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>4708076</th>\n",
" <td>0.537930</td>\n",
" <td>0.035747</td>\n",
" <td>0.497254</td>\n",
" <td>0.051997</td>\n",
" <td>0.040677</td>\n",
" <td>4879560</td>\n",
" <td>78.139731</td>\n",
" <td>9</td>\n",
" <td>-143.0</td>\n",
" <td>80.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4708077</th>\n",
" <td>0.543964</td>\n",
" <td>0.061913</td>\n",
" <td>0.474188</td>\n",
" <td>0.106268</td>\n",
" <td>0.069776</td>\n",
" <td>4879561</td>\n",
" <td>46.507495</td>\n",
" <td>34</td>\n",
" <td>39.0</td>\n",
" <td>50.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4708078</th>\n",
" <td>0.601935</td>\n",
" <td>0.031992</td>\n",
" <td>0.546454</td>\n",
" <td>0.051656</td>\n",
" <td>0.055481</td>\n",
" <td>4879562</td>\n",
" <td>65.822671</td>\n",
" <td>28</td>\n",
" <td>-141.0</td>\n",
" <td>70.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4708079</th>\n",
" <td>0.568163</td>\n",
" <td>0.041745</td>\n",
" <td>0.509543</td>\n",
" <td>0.042314</td>\n",
" <td>0.058620</td>\n",
" <td>4879563</td>\n",
" <td>33.159751</td>\n",
" <td>41</td>\n",
" <td>-51.0</td>\n",
" <td>30.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4708080</th>\n",
" <td>0.508238</td>\n",
" <td>0.052079</td>\n",
" <td>0.429219</td>\n",
" <td>0.077267</td>\n",
" <td>0.079019</td>\n",
" <td>4879564</td>\n",
" <td>35.956510</td>\n",
" <td>11</td>\n",
" <td>-51.0</td>\n",
" <td>40.0</td>\n",
" </tr>\n",
" </tbody>\n",
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"</div>"
],
"text/plain": [
" SVF_2m std_2m SVF_50cm std_50cm bias DF_UID FLAECHE \\\n",
"4708076 0.537930 0.035747 0.497254 0.051997 0.040677 4879560 78.139731 \n",
"4708077 0.543964 0.061913 0.474188 0.106268 0.069776 4879561 46.507495 \n",
"4708078 0.601935 0.031992 0.546454 0.051656 0.055481 4879562 65.822671 \n",
"4708079 0.568163 0.041745 0.509543 0.042314 0.058620 4879563 33.159751 \n",
"4708080 0.508238 0.052079 0.429219 0.077267 0.079019 4879564 35.956510 \n",
"\n",
" NEIGUNG AUSRICHTUNG AREA \n",
"4708076 9 -143.0 80.0 \n",
"4708077 34 39.0 50.0 \n",
"4708078 28 -141.0 70.0 \n",
"4708079 41 -51.0 30.0 \n",
"4708080 11 -51.0 40.0 "
]
},
"execution_count": 66,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"SVF.head()"
]
},
{
"cell_type": "code",
"execution_count": 67,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<xarray.Dataset>\n",
"Dimensions: (AUSRICHTUNG: 361, NEIGUNG: 70)\n",
"Coordinates:\n",
" * NEIGUNG (NEIGUNG) int64 0 1 2 3 4 5 6 7 8 ... 62 63 64 65 66 67 68 69\n",
" * AUSRICHTUNG (AUSRICHTUNG) float64 -180.0 -179.0 -178.0 ... 179.0 180.0\n",
"Data variables:\n",
" SVF_2m (NEIGUNG, AUSRICHTUNG) float64 nan nan nan nan ... nan nan nan\n",
" std_2m (NEIGUNG, AUSRICHTUNG) float64 nan nan nan nan ... nan nan nan\n",
" SVF_50cm (NEIGUNG, AUSRICHTUNG) float64 nan nan nan nan ... nan nan nan\n",
" std_50cm (NEIGUNG, AUSRICHTUNG) float64 nan nan nan nan ... nan nan nan\n",
" bias (NEIGUNG, AUSRICHTUNG) float64 nan nan nan nan ... nan nan nan\n",
" DF_UID (NEIGUNG, AUSRICHTUNG) float64 nan nan nan nan ... nan nan nan\n",
" FLAECHE (NEIGUNG, AUSRICHTUNG) float64 nan nan nan nan ... nan nan nan\n",
" AREA (NEIGUNG, AUSRICHTUNG) float64 nan nan nan nan ... nan nan nan"
]
},
"execution_count": 67,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"svf_aspect_tilt = SVF.groupby(['NEIGUNG', 'AUSRICHTUNG']).mean().to_xarray()\n",
"svf_aspect_tilt"
]
},
{
"cell_type": "code",
"execution_count": 68,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.collections.QuadMesh at 0x7f9938d8e2e8>"
]
},
"execution_count": 68,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"svf_aspect_tilt.SVF_50cm.plot()"
]
},
{
"cell_type": "code",
"execution_count": 69,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<xarray.Dataset>\n",
"Dimensions: (AREA: 454, AUSRICHTUNG: 361)\n",
"Coordinates:\n",
" * AUSRICHTUNG (AUSRICHTUNG) float64 -180.0 -179.0 -178.0 ... 179.0 180.0\n",
" * AREA (AREA) float64 0.0 10.0 20.0 ... 2.164e+04 2.325e+04 2.351e+04\n",
"Data variables:\n",
" SVF_2m (AUSRICHTUNG, AREA) float64 0.7526 0.6545 0.6434 ... nan nan\n",
" std_2m (AUSRICHTUNG, AREA) float64 0.03314 0.05123 0.04813 ... nan nan\n",
" SVF_50cm (AUSRICHTUNG, AREA) float64 0.7312 0.5687 0.6316 ... nan nan\n",
" std_50cm (AUSRICHTUNG, AREA) float64 0.0656 0.09705 0.07214 ... nan nan\n",
" bias (AUSRICHTUNG, AREA) float64 0.02135 0.08577 0.01173 ... nan nan\n",
" DF_UID (AUSRICHTUNG, AREA) float64 4.976e+06 4.975e+06 ... nan nan\n",
" FLAECHE (AUSRICHTUNG, AREA) float64 2.913 10.42 20.29 ... nan nan nan\n",
" NEIGUNG (AUSRICHTUNG, AREA) float64 24.37 24.93 27.84 ... nan nan nan"
]
},
"execution_count": 69,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"svf_aspect_area = SVF.groupby(['AUSRICHTUNG', 'AREA']).mean().to_xarray()\n",
"svf_aspect_area"
]
},
{
"cell_type": "code",
"execution_count": 70,
"metadata": {
"scrolled": false
},
"outputs": [
{
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" alert('Your browser does not have WebSocket support.' +\n",
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" 'Firefox 4 and 5 are also supported but you ' +\n",
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"\n",
" rubberband.mousedown('button_press', mouse_event_fn);\n",
" rubberband.mouseup('button_release', mouse_event_fn);\n",
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" rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
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"\n",
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" mouse_event_fn(event);\n",
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"\n",
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"\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",
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" canvas_div.css('width', width)\n",
" canvas_div.css('height', height)\n",
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"\n",
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"\n",
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" }\n",
" var button = $('<button/>');\n",
" button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
" 'ui-button-icon-only');\n",
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" button.attr('aria-disabled', 'false');\n",
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"\n",
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"mpl.figure.prototype.send_message = function(type, properties) {\n",
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"\n",
"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
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"\n",
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"\n",
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" break;\n",
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"\n",
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"\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 overriden (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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\" width=\"640\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"(1, 23640.0)"
]
},
"execution_count": 70,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"plt.figure()\n",
"svf_aspect_area.SVF_50cm.T.plot()\n",
"plt.yscale('log')\n",
"plt.ylim(bottom = 1)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Verify batch computation for CH"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"path = '/scratch/walch/grassgis/scripts/executables/workspace_skyview/files'"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [],
"source": [
"files = []\n",
"for i in range(64):\n",
" try:\n",
" files.append( pd.read_csv( os.path.join(path, 'skyview_CH_%d_stats.csv' %i )))\n",
" except:\n",
" print('Skipping %d' %i)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Merging of files**\n",
"1. Append all files to one long file (need columns *non_null_cells* and *sum*)\n",
"2. Groupby zone and perform sum-operation\n",
"3. Compute mean as *sum*/*non_null_cells*\n",
"4. Rename \"zone\" to \"DF_UID\" and \"mean\" to \"SVF\"\n",
"5. Load roofs to obtain full list of DF_UIDs\n",
"6. Refill missing values with the national mean\n",
"7. Debias bysubtracting the bias"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [],
"source": [
"# 1.\n",
"df = pd.concat(files, axis = 0)\n",
"df_sel = df[['zone', 'sum', 'non_null_cells']].rename(columns = {'zone' : 'DF_UID'})"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [],
"source": [
"df_sel['non_null_cells'] = df_sel.non_null_cells.astype(int)"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [],
"source": [
"# 2. to 4.\n",
"df_merged = df_sel.groupby('DF_UID').sum()\n",
"df_merged['SVF'] = df_merged['sum']/df_merged['non_null_cells']\n",
"SVF = df_merged[['SVF']]"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/walch/miniconda3/envs/py3/lib/python3.6/site-packages/numpy/lib/arraysetops.py:463: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison\n",
" mask |= (ar1 == a)\n"
]
}
],
"source": [
"# 5.\n",
"ROOFS='/work/hyenergy/output/solar_potential/geographic_potential/CH_ROOFS_all_replaced.csv'\n",
"roofs = pd.read_csv(ROOFS, usecols = ['DF_UID', 'FLAECHE', 'NEIGUNG', 'AUSRICHTUNG'], index_col = 0)"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [],
"source": [
"# 6. \n",
"SVF_filled = roofs.merge(SVF, left_index = True, right_index = True, how = 'left').fillna(SVF.SVF.mean())"
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {},
"outputs": [],
"source": [
"SVF_filled['SVF_unbiased'] = np.minimum(np.maximum(SVF_filled.SVF - skyview['bias'].mean(), 0), 1)"
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {},
"outputs": [],
"source": [
"SVF_filled.drop(columns = ['FLAECHE', 'NEIGUNG', 'AUSRICHTUNG'], inplace = True)"
]
},
{
"cell_type": "code",
"execution_count": 30,
"metadata": {},
"outputs": [],
"source": [
"SVF_filled.to_csv('/work/hyenergy/output/solar_potential/geographic_potential/tilted_irradiance/SVF_CH_replaced.csv')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Plot SVF against roof characteristics"
]
},
{
"cell_type": "code",
"execution_count": 56,
"metadata": {},
"outputs": [],
"source": [
"SVF = pd.read_csv('/work/hyenergy/output/solar_potential/geographic_potential/tilted_irradiance/SVF_CH_replaced.csv')"
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {},
"outputs": [],
"source": [
"SVF_merged = roofs.merge(SVF, left_index = True, right_on = 'DF_UID', how = 'left')"
]
},
{
"cell_type": "code",
"execution_count": 50,
"metadata": {},
"outputs": [],
"source": [
"# ADJUST FOR FLAT ROOFS\n",
"FLAT = -5.1\n",
"SVF_merged['tilt'] = SVF_merged.NEIGUNG\n",
"SVF_merged.loc[SVF_merged.NEIGUNG == 0, 'tilt'] = FLAT # NEEDED FOR PLOTTING"
]
},
{
"cell_type": "code",
"execution_count": 51,
"metadata": {},
"outputs": [],
"source": [
"SVF_merged['area_log'] = np.log10(SVF_merged.FLAECHE)\n",
"SVF_merged['area_log_round'] = util.round_to_interval(SVF_merged.area_log, 0.2)\n",
"SVF_merged['area_log_round'] = np.minimum(np.maximum(SVF_merged.area_log_round, 0.7), 3.2)"
]
},
{
"cell_type": "code",
"execution_count": 55,
"metadata": {},
"outputs": [],
"source": [
"ASP_ROUND = 10\n",
"TILT_ROUND = 10\n",
"SVF_merged['NEIGUNG_round'] = util.round_to_interval(SVF_merged.NEIGUNG, 5)\n",
"SVF_merged['tilt_round'] = util.round_to_interval(SVF_merged.tilt, TILT_ROUND)\n",
"SVF_merged['aspect_round'] = util.round_to_interval(SVF_merged.AUSRICHTUNG, ASP_ROUND)"
]
},
{
"cell_type": "code",
"execution_count": 56,
"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 overriden (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": [
"SVF_grouped = SVF_merged.groupby(['tilt_round', 'aspect_round']).mean()\n",
"plot_var = SVF_grouped['SVF_unbiased']\n",
"plot_array = plot_var.to_xarray()\n",
"\n",
"plot_array['tilt_round' == FLAT] = plot_array['tilt_round' == FLAT].mean()\n",
"\n",
"\n",
"# prepare data\n",
"data = plot_array.values\n",
"# theta = np.append(plot_array.aspect_round * np.pi / 180, 2*np.pi) + (0.5 * ASP_ROUND * np.pi / 180)\n",
"theta = plot_array.aspect_round * np.pi / 180 - (0.5 * ASP_ROUND * np.pi / 180)\n",
"tilts = plot_array.tilt_round\n",
"\n",
"X, Y = np.meshgrid( theta, tilts )\n",
"\n",
"# SET PROPERTIES\n",
"VMIN = None\n",
"VMAX = None\n",
" \n",
"plt.figure()\n",
"ax = plt.subplot(projection='polar')\n",
"ax.set_theta_zero_location('S')\n",
"ax.set_theta_direction(-1)\n",
"\n",
"plt.pcolor(X, Y, data, vmin = VMIN, vmax = VMAX)\n",
"cb = plt.colorbar() # extend = get_cbar_extent( data, VMIN, VMAX )\n",
"# cb.set_label('Uncertainty for (1 - $C_{sh}$)')\n",
"\n",
"# FORMATTING\n",
"xticks = ['S', 'SW', 'W', 'NW', 'N', 'NE', 'E', 'SE']\n",
"yticks = [str(int(tilt)) + '°' for tilt in ax.get_yticks()]\n",
"ax.set_xticklabels( xticks )\n",
"ax.set_yticklabels( yticks )\n",
"ax.text(60,80, 'Tilt angle')\n",
"ax.set_rlabel_position(200) # get radial labels away from plotted line\n",
"\n",
"plt.tight_layout()\n",
"plt.show()\n",
"# plt.savefig('Shade_slope_azimuth_unc.png', dpi = 300)"
]
},
{
"cell_type": "code",
"execution_count": 53,
"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 overriden (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": [
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\" width=\"640\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"SVF_grouped = SVF_merged.groupby(['area_log_round', 'NEIGUNG_round']).mean()\n",
"arr = SVF_grouped['SVF_unbiased'].to_xarray()\n",
"arr.coords['area_log_round'] = 10**(arr.area_log_round)\n",
"\n",
"# PV_array.attrs['long_name'] = 'Uncertainty for $C_{pv}$'\n",
"\n",
"plt.figure()\n",
"ax = plt.subplot()\n",
"\n",
"arr.plot()\n",
"ax.set_yscale('log')\n",
"plt.xlabel('Roof tilt (in degree)')\n",
"plt.ylabel('Roof area (in $m^2$)')\n",
"\n",
"plt.tight_layout()\n",
"# plt.savefig('panelled_area_unc.png', dpi = 300)"
]
},
{
"cell_type": "code",
"execution_count": 57,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"DF_UID 1.000000\n",
"SVF 0.000057\n",
"SVF_unbiased 0.000000\n",
"dtype: float64"
]
},
"execution_count": 57,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"SVF.min()"
]
},
{
"cell_type": "code",
"execution_count": 58,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"DF_UID 9.890023e+06\n",
"SVF 1.000000e+00\n",
"SVF_unbiased 9.283739e-01\n",
"dtype: float64"
]
},
"execution_count": 58,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"SVF.max()"
]
},
{
"cell_type": "code",
"execution_count": 59,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"DF_UID 4.977728e+06\n",
"SVF 7.625916e-01\n",
"SVF_unbiased 6.909656e-01\n",
"dtype: float64"
]
},
"execution_count": 59,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"SVF.mean()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Spielwiese"
]
},
{
"cell_type": "code",
"execution_count": 95,
"metadata": {},
"outputs": [],
"source": [
"roof_SVF = skyview.merge(roofs, left_index = True, right_index = True, how = 'left')"
]
},
{
"cell_type": "code",
"execution_count": 85,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>SVF_2m</th>\n",
" <th>std_2m</th>\n",
" <th>SVF_50cm</th>\n",
" <th>std_50cm</th>\n",
" <th>bias</th>\n",
" <th>FLAECHE</th>\n",
" <th>NEIGUNG</th>\n",
" <th>AUSRICHTUNG</th>\n",
" </tr>\n",
" <tr>\n",
" <th>DF_UID</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>4879560</th>\n",
" <td>0.537930</td>\n",
" <td>0.035747</td>\n",
" <td>0.497254</td>\n",
" <td>0.051997</td>\n",
" <td>0.040677</td>\n",
" <td>78.139731</td>\n",
" <td>9</td>\n",
" <td>-143.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4879561</th>\n",
" <td>0.543964</td>\n",
" <td>0.061913</td>\n",
" <td>0.474188</td>\n",
" <td>0.106268</td>\n",
" <td>0.069776</td>\n",
" <td>46.507495</td>\n",
" <td>34</td>\n",
" <td>39.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4879562</th>\n",
" <td>0.601935</td>\n",
" <td>0.031992</td>\n",
" <td>0.546454</td>\n",
" <td>0.051656</td>\n",
" <td>0.055481</td>\n",
" <td>65.822671</td>\n",
" <td>28</td>\n",
" <td>-141.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4879563</th>\n",
" <td>0.568163</td>\n",
" <td>0.041745</td>\n",
" <td>0.509543</td>\n",
" <td>0.042314</td>\n",
" <td>0.058620</td>\n",
" <td>33.159751</td>\n",
" <td>41</td>\n",
" <td>-51.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4879564</th>\n",
" <td>0.508238</td>\n",
" <td>0.052079</td>\n",
" <td>0.429219</td>\n",
" <td>0.077267</td>\n",
" <td>0.079019</td>\n",
" <td>35.956510</td>\n",
" <td>11</td>\n",
" <td>-51.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" SVF_2m std_2m SVF_50cm std_50cm bias FLAECHE NEIGUNG \\\n",
"DF_UID \n",
"4879560 0.537930 0.035747 0.497254 0.051997 0.040677 78.139731 9 \n",
"4879561 0.543964 0.061913 0.474188 0.106268 0.069776 46.507495 34 \n",
"4879562 0.601935 0.031992 0.546454 0.051656 0.055481 65.822671 28 \n",
"4879563 0.568163 0.041745 0.509543 0.042314 0.058620 33.159751 41 \n",
"4879564 0.508238 0.052079 0.429219 0.077267 0.079019 35.956510 11 \n",
"\n",
" AUSRICHTUNG \n",
"DF_UID \n",
"4879560 -143.0 \n",
"4879561 39.0 \n",
"4879562 -141.0 \n",
"4879563 -51.0 \n",
"4879564 -51.0 "
]
},
"execution_count": 85,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"roof_SVF.head()"
]
},
{
"cell_type": "code",
"execution_count": 94,
"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 overriden (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"
}
],
"source": [
"sample = roof_SVF.sample(10000)\n",
"\n",
"plt.figure()\n",
"plt.scatter(sample.FLAECHE.values, sample.bias.values, s = 1)\n",
"plt.xscale('log')\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 98,
"metadata": {},
"outputs": [],
"source": [
"roof_shade = shade_bias[['DF_UID','fully_shaded_ratio']].merge(roofs, left_on = 'DF_UID', \n",
" right_index = True, how = 'left')"
]
},
{
"cell_type": "code",
"execution_count": 99,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>DF_UID</th>\n",
" <th>fully_shaded_ratio</th>\n",
" <th>FLAECHE</th>\n",
" <th>NEIGUNG</th>\n",
" <th>AUSRICHTUNG</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>4817081</td>\n",
" <td>0.0</td>\n",
" <td>111.982302</td>\n",
" <td>26</td>\n",
" <td>-79.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>4817082</td>\n",
" <td>0.0</td>\n",
" <td>121.121191</td>\n",
" <td>27</td>\n",
" <td>101.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>4817083</td>\n",
" <td>0.0</td>\n",
" <td>117.993684</td>\n",
" <td>26</td>\n",
" <td>-79.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>4817084</td>\n",
" <td>0.0</td>\n",
" <td>117.579904</td>\n",
" <td>27</td>\n",
" <td>101.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>4817085</td>\n",
" <td>0.0</td>\n",
" <td>155.862755</td>\n",
" <td>30</td>\n",
" <td>101.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" DF_UID fully_shaded_ratio FLAECHE NEIGUNG AUSRICHTUNG\n",
"0 4817081 0.0 111.982302 26 -79.0\n",
"1 4817082 0.0 121.121191 27 101.0\n",
"2 4817083 0.0 117.993684 26 -79.0\n",
"3 4817084 0.0 117.579904 27 101.0\n",
"4 4817085 0.0 155.862755 30 101.0"
]
},
"execution_count": 99,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"roof_shade.head()"
]
},
{
"cell_type": "code",
"execution_count": 104,
"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 overriden (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"
},
{
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\" width=\"640\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sample = roof_shade.sample(10000)\n",
"\n",
"plt.figure()\n",
"plt.scatter(sample.NEIGUNG.values, sample.fully_shaded_ratio.values, s = 1)\n",
"# plt.xscale('log')\n",
"plt.show()"
]
},
{
"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": "3.6.1"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
diff --git a/Visualisation/HIST_CH_slope_area.pdf b/Visualisation/HIST_CH_slope_area.pdf
new file mode 100644
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