Diffusion solar_potential (aw_solar) Browse

skyview_factor.ipynb
67dde33a040daw_solar

skyview_factor.ipynb
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			{
			"cells": [
			{
			"cell_type": "code",
			"execution_count": 1,
			"metadata": {},
			"outputs": [],
			"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": [
			{
			"data": {
			"text/html": [
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			"<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": [
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			"<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",
			" <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>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",
			" <td>1.0</td>\n",
			" <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>432.0</td>\n",
			" <td>432.0</td>\n",
			" </tr>\n",
			" <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",
			" <td>1.0</td>\n",
			" <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",
			" <td>1.0</td>\n",
			" <td>0.0</td>\n",
			" <td>0.0</td>\n",
			" <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",
			" <td>0</td>\n",
			" <td>1.0</td>\n",
			" <td>1.0</td>\n",
			" <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>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": [
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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>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",
			" 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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			],
			"text/plain": [
			"<IPython.core.display.HTML object>"
			]
			},
			"metadata": {},
			"output_type": "display_data"
			},
			{
			"data": {
			"text/plain": [
			"[<matplotlib.lines.Line2D at 0x7f34c51cce48>]"
			]
			},
			"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,
			"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": {},
			"outputs": [
			{
			"data": {
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			" .dataframe thead th {\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>non_null_cells</th>\n",
			" <th>n_cells</th>\n",
			" <th>fully_shaded_ratio</th>\n",
			" <th>mean_12_13h</th>\n",
			" <th>mean_1_16h</th>\n",
			" <th>mean_11_10h</th>\n",
			" <th>mean_7_15h</th>\n",
			" <th>mean_6_18h</th>\n",
			" <th>mean_6_10h</th>\n",
			" <th>...</th>\n",
			" <th>mean_11_12h</th>\n",
			" <th>mean_9_11h</th>\n",
			" <th>mean_5_6h</th>\n",
			" <th>mean_8_16h</th>\n",
			" <th>mean_9_9h</th>\n",
			" <th>mean_2_16h</th>\n",
			" <th>mean_5_10h</th>\n",
			" <th>mean_4_8h</th>\n",
			" <th>mean_8_12h</th>\n",
			" <th>mean_12_12h</th>\n",
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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 -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",
			"\n",
			" 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",
			"4 -0.882353 0.0 0.0 0.000000 0.0 ... \n",
			"\n",
			" mean_11_12h mean_9_11h mean_5_6h mean_8_16h mean_9_9h mean_2_16h \\\n",
			"0 0.0 0.0 0.000000 0.0 0.0 0.00 \n",
			"1 0.0 0.0 0.000000 0.0 0.0 0.00 \n",
			"2 0.0 0.0 0.000000 0.0 0.0 -0.56 \n",
			"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",
			"1 0.0 0.0 0.0 0.0 \n",
			"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": 18,
			"metadata": {},
			"output_type": "execute_result"
			}
			],
			"source": [
			"shade_bias.head()"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 19,
			"metadata": {},
			"outputs": [],
			"source": [
			"shade_bias_mean = shade_bias.mean()\n",
			"shade_bias_std = shade_bias.std()"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 20,
			"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,
			"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,
			"metadata": {},
			"outputs": [
			{
			"data": {
			"text/plain": [
			"mean 0.027160\n",
			"std 0.247525\n",
			"dtype: float64"
			]
			},
			"execution_count": 22,
			"metadata": {},
			"output_type": "execute_result"
			}
			],
			"source": [
			"Ssh[Ssh['std'] > 0].mean()"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 27,
			"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_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": 49,
			"metadata": {},
			"outputs": [
			{
			"data": {
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			" .dataframe tbody tr th:only-of-type {\n",
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			"\n",
			" .dataframe tbody tr th {\n",
			" vertical-align: top;\n",
			" }\n",
			"\n",
			" .dataframe thead th {\n",
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			"</style>\n",
			"<table border=\"1\" class=\"dataframe\">\n",
			" <thead>\n",
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			" <th>8</th>\n",
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			" <th>Csh</th>\n",
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			" <th>DF_UID</th>\n",
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			" 254 255 272 273 274 275 276 278 279 Csh \n",
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			"\n",
			"[5 rows x 146 columns]"
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			},
			"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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			"<p>5 rows × 147 columns</p>\n",
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			" 8 9 10 11 12 13 14 15 16 31 \\\n",
			"DF_UID \n",
			"4879560 0.000000 -0.186667 -0.1 0.31 0.15 0.0 0.0 0.0 0.0 0.0 \n",
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			"4879564 0.000000 0.200000 0.0 0.00 0.00 0.0 0.0 0.0 0.0 0.0 \n",
			"\n",
			" ... 255 272 273 274 275 276 278 279 \\\n",
			"DF_UID ... \n",
			"4879560 ... 0.0 -0.050000 -0.186667 -0.046667 0.0 0.0 0.0 0.0 \n",
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			"4879564 ... 0.0 0.000000 0.200000 0.000000 0.0 0.0 0.0 0.0 \n",
			"\n",
			" Csh SVF \n",
			"DF_UID \n",
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			"4879561 0.256854 0.069776 \n",
			"4879562 -0.036494 0.055481 \n",
			"4879563 0.010000 0.058620 \n",
			"4879564 0.372457 0.079019 \n",
			"\n",
			"[5 rows x 147 columns]"
			]
			},
			"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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			" 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"
			},
			{
			"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>"
			]
			},
			"metadata": {},
			"output_type": "display_data"
			},
			{
			"data": {
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\" width=\"640\">"
			],
			"text/plain": [
			"<IPython.core.display.HTML object>"
			]
			},
			"metadata": {},
			"output_type": "display_data"
			},
			{
			"data": {
			"text/plain": [
			"<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",
			" .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>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",
			"</table>\n",
			"</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": [
			{
			"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"
			},
			{
			"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, 2np.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"
			],
			"text/plain": [
			"<IPython.core.display.Javascript object>"
			]
			},
			"metadata": {},
			"output_type": "display_data"
			},
			{
			"data": {
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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\", \"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
			}

solarPOT/Tilted_irradiance/skyview_factor.ipynb67dde33a040daw_solar

skyview_factor.ipynbView Options

solarPOT/Tilted_irradiance/skyview_factor.ipynb
67dde33a040daw_solar

skyview_factor.ipynb
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