Skip to content

Instantly share code, notes, and snippets.

@wholmgren

wholmgren/probfx_plotting.ipynb

Last active June 24, 2020 21:12
Show Gist options
  • Save wholmgren/dee5ba8bee170a2eee1177d3f3ade0c8 to your computer and use it in GitHub Desktop.
Save wholmgren/dee5ba8bee170a2eee1177d3f3ade0c8 to your computer and use it in GitHub Desktop.
Download ZIP
Display the source blob
Display the rendered blob
Raw
probfx_plotting.ipynb
Loading
Sorry, something went wrong. Reload?
Sorry, we cannot display this file.
Sorry, this file is invalid so it cannot be displayed.
Display the source blob
Display the rendered blob
Raw
separate_probability_plot.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"%matplotlib inline"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import datetime\n",
"from functools import partial\n",
"from pathlib import Path\n",
"from importlib import reload\n",
"\n",
"import numpy as np\n",
"import pandas as pd"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"from solarforecastarbiter import datamodel, pvmodel\n",
"from solarforecastarbiter.plotting import timeseries, utils\n",
"from solarforecastarbiter.reports.figures import plotly_figures\n",
"from solarforecastarbiter.metrics import preprocessing\n",
"from solarforecastarbiter.reports import main as reports_main"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"import plotly.graph_objects as go"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"import json"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"import plotly.io as pio\n",
"# pio.renderers.default = \"browser\""
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"latitude = 32.2\n",
"longitude = -110.9\n",
"elevation = 700\n",
"\n",
"site = datamodel.Site(\n",
" name='Tucson, AZ',\n",
" latitude=latitude,\n",
" longitude=longitude,\n",
" elevation=elevation,\n",
" timezone='America/Phoenix'\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"name = 'OASIS DA GHI'"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"variable = 'ghi'"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
"observation = datamodel.Observation(\n",
" name='OASIS GHI', variable=variable,\n",
" interval_value_type='mean',\n",
" interval_length=pd.Timedelta('1min'),\n",
" interval_label='beginning', site=site, uncertainty=1)\n",
"\n",
"forecast = datamodel.ProbabilisticForecast(\n",
" name='OASIS DA GHI Y',\n",
" site=site,\n",
" variable=variable,\n",
" interval_label='beginning',\n",
" interval_value_type='mean',\n",
" interval_length=pd.Timedelta('1h'),\n",
" issue_time_of_day=datetime.time(hour=0),\n",
" run_length=pd.Timedelta('24h'),\n",
" lead_time_to_start=pd.Timedelta('0h'),\n",
" axis='y',\n",
" constant_values=(0, 50, 100)\n",
")\n",
"\n",
"forecast_cv = datamodel.ProbabilisticForecastConstantValue(\n",
" name='OASIS DA GHI CV Y=75',\n",
" site=site,\n",
" variable=variable,\n",
" interval_label='beginning',\n",
" interval_value_type='mean',\n",
" interval_length=pd.Timedelta('1h'),\n",
" issue_time_of_day=datetime.time(hour=0),\n",
" run_length=pd.Timedelta('24h'),\n",
" lead_time_to_start=pd.Timedelta('0h'),\n",
" axis='y',\n",
" constant_value=75\n",
")\n",
"\n",
"forecast_x = datamodel.ProbabilisticForecast(\n",
" name='OASIS DA GHI X',\n",
" site=site,\n",
" variable=variable,\n",
" interval_label='beginning',\n",
" interval_value_type='mean',\n",
" interval_length=pd.Timedelta('1h'),\n",
" issue_time_of_day=datetime.time(hour=0),\n",
" run_length=pd.Timedelta('24h'),\n",
" lead_time_to_start=pd.Timedelta('0h'),\n",
" axis='x',\n",
" constant_values=(0, 500, 1000)\n",
")\n",
"\n",
"forecast_cv_x = datamodel.ProbabilisticForecastConstantValue(\n",
" name='OASIS DA GHI CV X=750',\n",
" site=site,\n",
" variable=variable,\n",
" interval_label='beginning',\n",
" interval_value_type='mean',\n",
" interval_length=pd.Timedelta('1h'),\n",
" issue_time_of_day=datetime.time(hour=0),\n",
" run_length=pd.Timedelta('24h'),\n",
" lead_time_to_start=pd.Timedelta('0h'),\n",
" axis='x',\n",
" constant_value=750\n",
")\n",
"\n",
"fxobs = datamodel.ForecastObservation(forecast, observation)\n",
"fxobs_cv = datamodel.ForecastObservation(forecast_cv, observation)\n",
"\n",
"fxobs_x = datamodel.ForecastObservation(forecast_x, observation)\n",
"fxobs_cv_x = datamodel.ForecastObservation(forecast_cv_x, observation)"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [],
"source": [
"start = pd.Timestamp('20200519 0700')\n",
"end = pd.Timestamp('20200520 0700')\n",
"index = pd.date_range(start=start, end=end, freq='1min', tz='UTC')\n",
"\n",
"solar_position = pvmodel.calculate_solar_position(latitude, longitude, elevation, index)\n",
"\n",
"cs = pvmodel.calculate_clearsky(latitude, longitude, elevation, solar_position['apparent_zenith'])\n",
"\n",
"obs_data = pd.DataFrame({'value': cs['ghi'] * 0.75, 'quality_flag': 2})\n",
"\n",
"fx_data = pd.DataFrame({cv.constant_value: cs['ghi'] * cv.constant_value/100 for cv in forecast.constant_values}).resample('1h').mean()\n",
"\n",
"fx_cv_data = cs['ghi'] * 0.75\n",
"\n",
"fx_x_data = pd.DataFrame({0: 0, 500: 0.5, 1000: 1.}, index=fx_data.index)\n",
"fx_x_data.loc[fx_data.loc[:, 50] == 0] = 0\n",
"\n",
"fx_cv_x_data = pd.Series(0.75, index=fx_data.index) * np.random.random(len(fx_data.index)) * 1.2\n",
"fx_cv_x_data.loc[fx_data.loc[:, 50] == 0] = 0\n",
"\n",
"data_dict = {\n",
" observation: obs_data,\n",
" forecast: fx_data,\n",
" forecast_cv: fx_cv_data,\n",
" forecast_x: fx_x_data,\n",
" forecast_cv_x: fx_cv_x_data\n",
"}\n",
"\n",
"# power = pvmodel.irradiance_to_power(single, solar_position['apparent_zenith'], solar_position['azimuth'], cs['ghi'], cs['dni'], cs['dhi'])"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x7fd50891ce48>"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"fx_cv_x_data.plot()"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [],
"source": [
"qfilter = datamodel.QualityFlagFilter()"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [],
"source": [
"report_params = datamodel.ReportParameters(\n",
" name=\"NREL MIDC OASIS GHI Forecast Analysis\",\n",
" start=start,\n",
" end=end,\n",
" object_pairs=(fxobs, fxobs_cv, fxobs_x, fxobs_cv_x),\n",
" metrics=(\"crps\", \"bs\"),\n",
" categories=(\"total\", \"date\", \"hour\"),\n",
" filters=(qfilter,)\n",
")\n",
"report = datamodel.Report(\n",
" report_id=\"56c67770-9832-11e9-a535-f4939feddd82\",\n",
" report_parameters=report_params\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [],
"source": [
"preprocessing = reload(preprocessing)\n",
"reports_main.preprocessing = preprocessing"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [],
"source": [
"raw_report = reports_main.create_raw_report_from_data(report, data_dict)"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [],
"source": [
"spec_d = json.loads(raw_report.plots.figures[0].spec)"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.plotly.v1+json": {
"config": {
"plotlyServerURL": "https://plot.ly"
},
"data": [
{
"marker": {
"color": [
"#1f77b4",
"#2ca02c"
]
},
"type": "bar",
"x": [
"OASIS DA GHI Y",
"OASIS DA GHI X"
],
"y": [
43.98203368134573,
540.0078125
]
}
],
"layout": {
"autosize": true,
"font": {
"size": 14
},
"margin": {
"b": 50,
"l": 50,
"pad": 4,
"r": 50,
"t": 50
},
"plot_bgcolor": "#FFF",
"template": {
"data": {
"bar": [
{
"error_x": {
"color": "#2a3f5f"
},
"error_y": {
"color": "#2a3f5f"
},
"marker": {
"line": {
"color": "#E5ECF6",
"width": 0.5
}
},
"type": "bar"
}
],
"barpolar": [
{
"marker": {
"line": {
"color": "#E5ECF6",
"width": 0.5
}
},
"type": "barpolar"
}
],
"carpet": [
{
"aaxis": {
"endlinecolor": "#2a3f5f",
"gridcolor": "white",
"linecolor": "white",
"minorgridcolor": "white",
"startlinecolor": "#2a3f5f"
},
"baxis": {
"endlinecolor": "#2a3f5f",
"gridcolor": "white",
"linecolor": "white",
"minorgridcolor": "white",
"startlinecolor": "#2a3f5f"
},
"type": "carpet"
}
],
"choropleth": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"type": "choropleth"
}
],
"contour": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"colorscale": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"type": "contour"
}
],
"contourcarpet": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"type": "contourcarpet"
}
],
"heatmap": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"colorscale": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"type": "heatmap"
}
],
"heatmapgl": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"colorscale": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"type": "heatmapgl"
}
],
"histogram": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "histogram"
}
],
"histogram2d": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"colorscale": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"type": "histogram2d"
}
],
"histogram2dcontour": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"colorscale": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"type": "histogram2dcontour"
}
],
"mesh3d": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"type": "mesh3d"
}
],
"parcoords": [
{
"line": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "parcoords"
}
],
"pie": [
{
"automargin": true,
"type": "pie"
}
],
"scatter": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scatter"
}
],
"scatter3d": [
{
"line": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scatter3d"
}
],
"scattercarpet": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scattercarpet"
}
],
"scattergeo": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scattergeo"
}
],
"scattergl": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scattergl"
}
],
"scattermapbox": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scattermapbox"
}
],
"scatterpolar": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scatterpolar"
}
],
"scatterpolargl": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scatterpolargl"
}
],
"scatterternary": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scatterternary"
}
],
"surface": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"colorscale": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"type": "surface"
}
],
"table": [
{
"cells": {
"fill": {
"color": "#EBF0F8"
},
"line": {
"color": "white"
}
},
"header": {
"fill": {
"color": "#C8D4E3"
},
"line": {
"color": "white"
}
},
"type": "table"
}
]
},
"layout": {
"annotationdefaults": {
"arrowcolor": "#2a3f5f",
"arrowhead": 0,
"arrowwidth": 1
},
"coloraxis": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"colorscale": {
"diverging": [
[
0,
"#8e0152"
],
[
0.1,
"#c51b7d"
],
[
0.2,
"#de77ae"
],
[
0.3,
"#f1b6da"
],
[
0.4,
"#fde0ef"
],
[
0.5,
"#f7f7f7"
],
[
0.6,
"#e6f5d0"
],
[
0.7,
"#b8e186"
],
[
0.8,
"#7fbc41"
],
[
0.9,
"#4d9221"
],
[
1,
"#276419"
]
],
"sequential": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"sequentialminus": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
]
},
"colorway": [
"#636efa",
"#EF553B",
"#00cc96",
"#ab63fa",
"#FFA15A",
"#19d3f3",
"#FF6692",
"#B6E880",
"#FF97FF",
"#FECB52"
],
"font": {
"color": "#2a3f5f"
},
"geo": {
"bgcolor": "white",
"lakecolor": "white",
"landcolor": "#E5ECF6",
"showlakes": true,
"showland": true,
"subunitcolor": "white"
},
"hoverlabel": {
"align": "left"
},
"hovermode": "closest",
"mapbox": {
"style": "light"
},
"paper_bgcolor": "white",
"plot_bgcolor": "#E5ECF6",
"polar": {
"angularaxis": {
"gridcolor": "white",
"linecolor": "white",
"ticks": ""
},
"bgcolor": "#E5ECF6",
"radialaxis": {
"gridcolor": "white",
"linecolor": "white",
"ticks": ""
}
},
"scene": {
"xaxis": {
"backgroundcolor": "#E5ECF6",
"gridcolor": "white",
"gridwidth": 2,
"linecolor": "white",
"showbackground": true,
"ticks": "",
"zerolinecolor": "white"
},
"yaxis": {
"backgroundcolor": "#E5ECF6",
"gridcolor": "white",
"gridwidth": 2,
"linecolor": "white",
"showbackground": true,
"ticks": "",
"zerolinecolor": "white"
},
"zaxis": {
"backgroundcolor": "#E5ECF6",
"gridcolor": "white",
"gridwidth": 2,
"linecolor": "white",
"showbackground": true,
"ticks": "",
"zerolinecolor": "white"
}
},
"shapedefaults": {
"line": {
"color": "#2a3f5f"
}
},
"ternary": {
"aaxis": {
"gridcolor": "white",
"linecolor": "white",
"ticks": ""
},
"baxis": {
"gridcolor": "white",
"linecolor": "white",
"ticks": ""
},
"bgcolor": "#E5ECF6",
"caxis": {
"gridcolor": "white",
"linecolor": "white",
"ticks": ""
}
},
"title": {
"x": 0.05
},
"xaxis": {
"automargin": true,
"gridcolor": "white",
"linecolor": "white",
"ticks": "",
"title": {
"standoff": 15
},
"zerolinecolor": "white",
"zerolinewidth": 2
},
"yaxis": {
"automargin": true,
"gridcolor": "white",
"linecolor": "white",
"ticks": "",
"title": {
"standoff": 15
},
"zerolinecolor": "white",
"zerolinewidth": 2
}
}
},
"title": {
"text": "<b>CRPS</b>"
},
"xaxis": {
"autorange": true,
"linecolor": "black",
"linewidth": 1,
"range": [
-0.5,
1.5
],
"showline": true,
"ticks": "outside",
"title": {
"text": "CRPS"
},
"type": "category"
},
"yaxis": {
"autorange": true,
"gridcolor": "#CCC",
"gridwidth": 1,
"linecolor": "black",
"linewidth": 1,
"range": [
0,
568.4292763157895
],
"showgrid": true,
"showline": true,
"ticks": "outside",
"type": "linear"
}
}
},
"image/png": "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"
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fig = go.Figure(**spec_d)\n",
"fig.show()"
]
},
{
"cell_type": "code",
"execution_count": 39,
"metadata": {},
"outputs": [],
"source": [
"report = datamodel.Report(\n",
" report_id=\"56c67770-9832-11e9-a535-f4939feddd82\",\n",
" report_parameters=report_params,\n",
" raw_report=raw_report,\n",
" status='complete'\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [],
"source": [
"units = observation.units"
]
},
{
"cell_type": "code",
"execution_count": 32,
"metadata": {},
"outputs": [],
"source": [
"plotly_figures = reload(plotly_figures)"
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {},
"outputs": [],
"source": [
"timeseries_value_df, timeseries_meta_df = plotly_figures.construct_timeseries_dataframe(report)"
]
},
{
"cell_type": "code",
"execution_count": 34,
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.plotly.v1+json": {
"config": {
"plotlyServerURL": "https://plot.ly"
},
"data": [
{
"connectgaps": false,
"legendgroup": "OASIS GHI",
"line": {
"shape": "hv"
},
"marker": {
"color": "#000"
},
"name": "OASIS GHI",
"type": "scattergl",
"x": [
"2020-05-19T00:00:00-07:00",
"2020-05-19T01:00:00-07:00",
"2020-05-19T02:00:00-07:00",
"2020-05-19T03:00:00-07:00",
"2020-05-19T04:00:00-07:00",
"2020-05-19T05:00:00-07:00",
"2020-05-19T06:00:00-07:00",
"2020-05-19T07:00:00-07:00",
"2020-05-19T08:00:00-07:00",
"2020-05-19T09:00:00-07:00",
"2020-05-19T10:00:00-07:00",
"2020-05-19T11:00:00-07:00",
"2020-05-19T12:00:00-07:00",
"2020-05-19T13:00:00-07:00",
"2020-05-19T14:00:00-07:00",
"2020-05-19T15:00:00-07:00",
"2020-05-19T16:00:00-07:00",
"2020-05-19T17:00:00-07:00",
"2020-05-19T18:00:00-07:00",
"2020-05-19T19:00:00-07:00",
"2020-05-19T20:00:00-07:00",
"2020-05-19T21:00:00-07:00",
"2020-05-19T22:00:00-07:00",
"2020-05-19T23:00:00-07:00"
],
"y": [
0,
0,
0,
0,
0,
6.762935763196956,
113.31943018810617,
283.382392541305,
448.35297965340106,
589.7400302959398,
696.2937068510189,
760.2017198878319,
776.9047883172864,
745.2295917665699,
667.4335617075693,
549.1187406738331,
399.11522190935443,
229.93334004030916,
67.06382335822583,
0.5605871598358207,
0,
0,
0,
0
]
},
{
"connectgaps": false,
"legendgroup": "OASIS DA GHI Y Prob(f <= x) = 0%",
"line": {
"shape": "hv"
},
"marker": {
"color": "#9467bd"
},
"name": "OASIS DA GHI Y<br>Prob(f <= x) = 0%",
"type": "scattergl",
"x": [
"2020-05-19T00:00:00-07:00",
"2020-05-19T01:00:00-07:00",
"2020-05-19T02:00:00-07:00",
"2020-05-19T03:00:00-07:00",
"2020-05-19T04:00:00-07:00",
"2020-05-19T05:00:00-07:00",
"2020-05-19T06:00:00-07:00",
"2020-05-19T07:00:00-07:00",
"2020-05-19T08:00:00-07:00",
"2020-05-19T09:00:00-07:00",
"2020-05-19T10:00:00-07:00",
"2020-05-19T11:00:00-07:00",
"2020-05-19T12:00:00-07:00",
"2020-05-19T13:00:00-07:00",
"2020-05-19T14:00:00-07:00",
"2020-05-19T15:00:00-07:00",
"2020-05-19T16:00:00-07:00",
"2020-05-19T17:00:00-07:00",
"2020-05-19T18:00:00-07:00",
"2020-05-19T19:00:00-07:00",
"2020-05-19T20:00:00-07:00",
"2020-05-19T21:00:00-07:00",
"2020-05-19T22:00:00-07:00",
"2020-05-19T23:00:00-07:00"
],
"y": [
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0
]
},
{
"connectgaps": false,
"legendgroup": "OASIS DA GHI Y Prob(f <= x) = 50%",
"line": {
"shape": "hv"
},
"marker": {
"color": "#e377c2"
},
"name": "OASIS DA GHI Y<br>Prob(f <= x) = 50%",
"type": "scattergl",
"x": [
"2020-05-19T00:00:00-07:00",
"2020-05-19T01:00:00-07:00",
"2020-05-19T02:00:00-07:00",
"2020-05-19T03:00:00-07:00",
"2020-05-19T04:00:00-07:00",
"2020-05-19T05:00:00-07:00",
"2020-05-19T06:00:00-07:00",
"2020-05-19T07:00:00-07:00",
"2020-05-19T08:00:00-07:00",
"2020-05-19T09:00:00-07:00",
"2020-05-19T10:00:00-07:00",
"2020-05-19T11:00:00-07:00",
"2020-05-19T12:00:00-07:00",
"2020-05-19T13:00:00-07:00",
"2020-05-19T14:00:00-07:00",
"2020-05-19T15:00:00-07:00",
"2020-05-19T16:00:00-07:00",
"2020-05-19T17:00:00-07:00",
"2020-05-19T18:00:00-07:00",
"2020-05-19T19:00:00-07:00",
"2020-05-19T20:00:00-07:00",
"2020-05-19T21:00:00-07:00",
"2020-05-19T22:00:00-07:00",
"2020-05-19T23:00:00-07:00"
],
"y": [
0,
0,
0,
0,
0,
4.508623842131304,
75.54628679207079,
188.9215950275367,
298.9019864356007,
393.1600201972932,
464.19580456734616,
506.801146591888,
517.9365255448579,
496.8197278443798,
444.9557078050462,
366.0791604492221,
266.0768146062364,
153.2888933602061,
44.70921557215055,
0.37372477322388054,
0,
0,
0,
0
]
},
{
"connectgaps": false,
"legendgroup": "OASIS DA GHI Y Prob(f <= x) = 100%",
"line": {
"shape": "hv"
},
"marker": {
"color": "#1f77b4"
},
"name": "OASIS DA GHI Y<br>Prob(f <= x) = 100%",
"type": "scattergl",
"x": [
"2020-05-19T00:00:00-07:00",
"2020-05-19T01:00:00-07:00",
"2020-05-19T02:00:00-07:00",
"2020-05-19T03:00:00-07:00",
"2020-05-19T04:00:00-07:00",
"2020-05-19T05:00:00-07:00",
"2020-05-19T06:00:00-07:00",
"2020-05-19T07:00:00-07:00",
"2020-05-19T08:00:00-07:00",
"2020-05-19T09:00:00-07:00",
"2020-05-19T10:00:00-07:00",
"2020-05-19T11:00:00-07:00",
"2020-05-19T12:00:00-07:00",
"2020-05-19T13:00:00-07:00",
"2020-05-19T14:00:00-07:00",
"2020-05-19T15:00:00-07:00",
"2020-05-19T16:00:00-07:00",
"2020-05-19T17:00:00-07:00",
"2020-05-19T18:00:00-07:00",
"2020-05-19T19:00:00-07:00",
"2020-05-19T20:00:00-07:00",
"2020-05-19T21:00:00-07:00",
"2020-05-19T22:00:00-07:00",
"2020-05-19T23:00:00-07:00"
],
"y": [
0,
0,
0,
0,
0,
9.017247684262609,
151.09257358414158,
377.8431900550734,
597.8039728712014,
786.3200403945864,
928.3916091346923,
1013.602293183776,
1035.8730510897158,
993.6394556887597,
889.9114156100924,
732.1583208984442,
532.1536292124728,
306.5777867204122,
89.4184311443011,
0.7474495464477611,
0,
0,
0,
0
]
},
{
"connectgaps": false,
"legendgroup": "OASIS DA GHI CV Y=75 Prob(f <= x) = 75%",
"line": {
"shape": "hv"
},
"marker": {
"color": "#2ca02c"
},
"name": "OASIS DA GHI CV Y=75<br>Prob(f <= x) = 75%",
"type": "scattergl",
"x": [
"2020-05-19T00:00:00-07:00",
"2020-05-19T01:00:00-07:00",
"2020-05-19T02:00:00-07:00",
"2020-05-19T03:00:00-07:00",
"2020-05-19T04:00:00-07:00",
"2020-05-19T05:00:00-07:00",
"2020-05-19T06:00:00-07:00",
"2020-05-19T07:00:00-07:00",
"2020-05-19T08:00:00-07:00",
"2020-05-19T09:00:00-07:00",
"2020-05-19T10:00:00-07:00",
"2020-05-19T11:00:00-07:00",
"2020-05-19T12:00:00-07:00",
"2020-05-19T13:00:00-07:00",
"2020-05-19T14:00:00-07:00",
"2020-05-19T15:00:00-07:00",
"2020-05-19T16:00:00-07:00",
"2020-05-19T17:00:00-07:00",
"2020-05-19T18:00:00-07:00",
"2020-05-19T19:00:00-07:00",
"2020-05-19T20:00:00-07:00",
"2020-05-19T21:00:00-07:00",
"2020-05-19T22:00:00-07:00",
"2020-05-19T23:00:00-07:00"
],
"y": [
0,
0,
0,
0,
0,
0,
37.909109048489455,
198.28818829569175,
370.037522343761,
525.2256119471934,
650.4713724272963,
736.3797115536197,
776.7708498494687,
768.788207887888,
713.0061843956807,
613.4067889890705,
477.23950673100455,
314.8532631014302,
142.25752840425787,
6.4243560174614736,
0,
0,
0,
0
]
}
],
"layout": {
"autosize": true,
"bargap": 0,
"bargroupgap": 0,
"barmode": "group",
"coloraxis": {
"colorbar": {
"ticks": "outside",
"x": 1.2,
"y": 1,
"yanchor": "top"
}
},
"legend": {
"font": {
"size": 10
}
},
"template": {
"data": {
"bar": [
{
"error_x": {
"color": "#2a3f5f"
},
"error_y": {
"color": "#2a3f5f"
},
"marker": {
"line": {
"color": "#E5ECF6",
"width": 0.5
}
},
"type": "bar"
}
],
"barpolar": [
{
"marker": {
"line": {
"color": "#E5ECF6",
"width": 0.5
}
},
"type": "barpolar"
}
],
"carpet": [
{
"aaxis": {
"endlinecolor": "#2a3f5f",
"gridcolor": "white",
"linecolor": "white",
"minorgridcolor": "white",
"startlinecolor": "#2a3f5f"
},
"baxis": {
"endlinecolor": "#2a3f5f",
"gridcolor": "white",
"linecolor": "white",
"minorgridcolor": "white",
"startlinecolor": "#2a3f5f"
},
"type": "carpet"
}
],
"choropleth": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"type": "choropleth"
}
],
"contour": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"colorscale": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"type": "contour"
}
],
"contourcarpet": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"type": "contourcarpet"
}
],
"heatmap": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"colorscale": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"type": "heatmap"
}
],
"heatmapgl": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"colorscale": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"type": "heatmapgl"
}
],
"histogram": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "histogram"
}
],
"histogram2d": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"colorscale": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"type": "histogram2d"
}
],
"histogram2dcontour": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"colorscale": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"type": "histogram2dcontour"
}
],
"mesh3d": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"type": "mesh3d"
}
],
"parcoords": [
{
"line": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "parcoords"
}
],
"pie": [
{
"automargin": true,
"type": "pie"
}
],
"scatter": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scatter"
}
],
"scatter3d": [
{
"line": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scatter3d"
}
],
"scattercarpet": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scattercarpet"
}
],
"scattergeo": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scattergeo"
}
],
"scattergl": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scattergl"
}
],
"scattermapbox": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scattermapbox"
}
],
"scatterpolar": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scatterpolar"
}
],
"scatterpolargl": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scatterpolargl"
}
],
"scatterternary": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scatterternary"
}
],
"surface": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"colorscale": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"type": "surface"
}
],
"table": [
{
"cells": {
"fill": {
"color": "#EBF0F8"
},
"line": {
"color": "white"
}
},
"header": {
"fill": {
"color": "#C8D4E3"
},
"line": {
"color": "white"
}
},
"type": "table"
}
]
},
"layout": {
"annotationdefaults": {
"arrowcolor": "#2a3f5f",
"arrowhead": 0,
"arrowwidth": 1
},
"coloraxis": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"colorscale": {
"diverging": [
[
0,
"#8e0152"
],
[
0.1,
"#c51b7d"
],
[
0.2,
"#de77ae"
],
[
0.3,
"#f1b6da"
],
[
0.4,
"#fde0ef"
],
[
0.5,
"#f7f7f7"
],
[
0.6,
"#e6f5d0"
],
[
0.7,
"#b8e186"
],
[
0.8,
"#7fbc41"
],
[
0.9,
"#4d9221"
],
[
1,
"#276419"
]
],
"sequential": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"sequentialminus": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
]
},
"colorway": [
"#636efa",
"#EF553B",
"#00cc96",
"#ab63fa",
"#FFA15A",
"#19d3f3",
"#FF6692",
"#B6E880",
"#FF97FF",
"#FECB52"
],
"font": {
"color": "#2a3f5f"
},
"geo": {
"bgcolor": "white",
"lakecolor": "white",
"landcolor": "#E5ECF6",
"showlakes": true,
"showland": true,
"subunitcolor": "white"
},
"hoverlabel": {
"align": "left"
},
"hovermode": "closest",
"mapbox": {
"style": "light"
},
"paper_bgcolor": "white",
"plot_bgcolor": "#E5ECF6",
"polar": {
"angularaxis": {
"gridcolor": "white",
"linecolor": "white",
"ticks": ""
},
"bgcolor": "#E5ECF6",
"radialaxis": {
"gridcolor": "white",
"linecolor": "white",
"ticks": ""
}
},
"scene": {
"xaxis": {
"backgroundcolor": "#E5ECF6",
"gridcolor": "white",
"gridwidth": 2,
"linecolor": "white",
"showbackground": true,
"ticks": "",
"zerolinecolor": "white"
},
"yaxis": {
"backgroundcolor": "#E5ECF6",
"gridcolor": "white",
"gridwidth": 2,
"linecolor": "white",
"showbackground": true,
"ticks": "",
"zerolinecolor": "white"
},
"zaxis": {
"backgroundcolor": "#E5ECF6",
"gridcolor": "white",
"gridwidth": 2,
"linecolor": "white",
"showbackground": true,
"ticks": "",
"zerolinecolor": "white"
}
},
"shapedefaults": {
"line": {
"color": "#2a3f5f"
}
},
"ternary": {
"aaxis": {
"gridcolor": "white",
"linecolor": "white",
"ticks": ""
},
"baxis": {
"gridcolor": "white",
"linecolor": "white",
"ticks": ""
},
"bgcolor": "#E5ECF6",
"caxis": {
"gridcolor": "white",
"linecolor": "white",
"ticks": ""
}
},
"title": {
"x": 0.05
},
"xaxis": {
"automargin": true,
"gridcolor": "white",
"linecolor": "white",
"ticks": "",
"title": {
"standoff": 15
},
"zerolinecolor": "white",
"zerolinewidth": 2
},
"yaxis": {
"automargin": true,
"gridcolor": "white",
"linecolor": "white",
"ticks": "",
"title": {
"standoff": 15
},
"zerolinecolor": "white",
"zerolinewidth": 2
}
}
},
"xaxis": {
"autorange": true,
"gridcolor": "#CCC",
"gridwidth": 1,
"linecolor": "black",
"linewidth": 1,
"range": [
"2020-05-19",
"2020-05-19 23:00"
],
"showgrid": true,
"showline": true,
"ticks": "outside",
"title": {
"text": "Time (UTC)"
},
"type": "date"
},
"yaxis": {
"autorange": true,
"fixedrange": true,
"gridcolor": "#CCC",
"gridwidth": 1,
"linecolor": "black",
"linewidth": 1,
"range": [
-57.548502838317546,
1093.4215539280333
],
"showgrid": true,
"showline": true,
"ticks": "outside",
"title": {
"text": "Data (W/m^2)"
},
"type": "linear"
}
}
},
"image/png": "iVBORw0KGgoAAAANSUhEUgAABFkAAAHCCAYAAAA0BBYZAAAgAElEQVR4nOzdWVBU96L3fc7FU/VWnftT9dw8u/bNW+fNznDOfnbO1gyaOCQxDokjMerG4BSUiIriPBEn1DhFjUOMGnEe4oBxjpGIE4IIzgMGUVEQQaAZG37vBWGFpqF7Jd3a/Zfvp+p3QfeCXkD2OfKt7tUhAgAAAAAAgM9CAn0CAAAAAAAALwIiCwAAAAAAgB8QWQAAAAAAAPyAyAIAAAAAAOAHRBYAAAAAAAA/ILIAAAAAAAD4AZEFAAAAAADAD4gsAAAAAAAAfkBkAQAAAAAA8AMiCwAAAAAAgB8QWQAAAAAAAPyAyAIAAAAAAOAHRBYAAAAAAAA/ILIAAAAAAAD4AZEFAAAAAADAD4gsAAAAAAAAfkBkAQAAAAAA8AMiCwAAAAAAgB8QWQAAAAAAAPyAyAIAAAAAAOAHRBYAAAAAAAA/ILIAAAAAAAD4AZEFAAAAAADAD4gsAAAAAAAAfkBkAQAAAAAA8AMiCwAAAAAAgB8QWQAAAAAAAPyAyAIAAAAAAOAHRBYAAAAAAAA/ILIAAAAAAAD4AZEFAAAAAADAD4gsAAAAAAAAfkBkAQAAAAAA8AMiCwAAAAAAgB8QWQAAAAAAAPyAyAIAAAAAAOAHRBYAAAAAAAA/ILIAAAAAAAD4AZEFAAAAAADAD4gsAAAAAAAAfkBkAQAAAAAA8AMiCwAAAAAAgB8QWQAAAAAAAPyAyAIAAAAAAOAHRBYAAAAAAAA/ILIAAAAAAAD4AZEFAAAAAADAD4gsAAAAAAAAfkBkAQAAAAAA8AMiCwAAAAAAgB8QWQAAAAAAAPyAyAIAAAAAAOAHRBYAAAAAAAA/ILIAAAAAAAD4AZEFAAAAAADAD4gsAAAAAAAAfkBkAQAAAAAA8AMiCwAAAAAAgB8QWQAAAAAAAPyAyAIAAAAAAOAHRBYAAAAAAAA/ILIAAAAAAAD4AZEFAAAAAADAD4gsAAAAAAAAfkBkAQAAAAAA8AMiCwAAAAAAgB8QWQAAAAAAAPyAyAIAAAAAAOAHRBYAAAAAAAA/ILIAAAAAAAD4AZEFAAAAAADAD4gsAAAAAAAAfkBkAQAAAAAA8AMiCwAAAAAAgB8QWQAAAAAAAPyAyAIAAAAAAOAHRBYAAAAAAAA/ILIAAAAAAAD4AZEFAAAAAADAD4gsAAAAAAAAfkBkAQAAAAAA8AMiCwAAAAAAgB8QWQAAAAAAAPyAyAIAAAAAAOAHRBYAAAAAAAA/ILIAAAAAAAD4AZEFAAAAAADAD4gsAAAAAAAAfkBkAQAAAAAA8AMiCwAAAAAAgB8QWQAAAAAAAPyAyAIAAAAAAOAHRBYAAAAAAAA/ILIAAAAAAAD4AZEFAAAAAADAD4gsAAAAAAAAfkBkAQAAAAAA8AMiCwAAAAAAgB8QWQAAAAAAAPyAyOKDkJAQ3X9cygzaleu3dePO/YCfB7O/y1dv6FbWw4CfB7O/9EtXdOfe44CfB7O/tIvpysopDPh5MPtLTb2g7NzigJ8Hs7d7eQ6lpKQE/DyY/d19+FQX0i4G/DyCfQDcEVl8QGQxb0QW80ZkMW9EFvNGZDFvRBazRmQxb0QWewPgjsjiAyKLeSOymDcii3kjspg3Iot5I7KYNSKLeSOy2BsAd0QWHxBZzBuRxbwRWcwbkcW8EVnMG5HFrBFZzBuRxd4AuCOy+IDIYt6ILOaNyGLeiCzmjchi3ogsZo3IYt6ILPYGwB2RxQdEFvNGZDFvRBbzRmQxb0QW80ZkMWtEFvNGZLE3AO6ILD4gspg3Iot5I7KYNyKLeSOymDcii1kjspg3Iou9AXBHZPEBkcW8EVnMG5HFvBFZzBuRxbwRWcwakcW8EVnsDYA7IosPiCzmjchi3ogs5o3IYt6ILOaNyGLWiCzmjchibwDcEVl8QGQxb0QW80ZkMW9EFvNGZDFvRBazRmQxb0QWe2tuCotK5HRW/+HPq6xyqsRR5vdjq5xOFRU7/vD54NkisviAyGLeiCzmjchi3ogs5o3IYt6ILGaNyGLeiCz21lycPJehd3uMUJf+E/Rml0jNWhKvKqfTur+mpkZteozUgOi5Lp9XUFisyAmL9H7vMWrVdbje6DJMh35OVmFRiTr0idFr7QYoevpyj8c2JjPrgfqPmK0P+45Vp37j9NZHkVoVv0+StHDVdq3bdtDl+JadhqqsvEInz2Xone5RatlpqNZuPeDPHxHqIbL4gMhi3ogs5o3IYt6ILOaNyGLeiCxmjchi3ogs9tYcFBQWq0XHCJ2/eF2SVOIoU+iQadqy+5h1zIVLNxU+Kk6tug5XQWGxdfvqjQmatSRe1dU11nF14eReTp469Rtn69j6HKXlat0tSglHT1u3ZWY90JcLv5fkObJI0q4fEzV9wfo//wOBV0QWHxBZzBuRxbwRWcwbkcW8bTxyXtN3p+vLfZeDZmdu8t+QpxFZzBqRxbwRWeytOVi/7aDComa73PbDgV/UNXyS9XHc0k3auve4Js75VjsSTli3R4xboGO/pDT6dRtGFk/H1rdx11F1HzilyfuJLIFHZPEBkcW8EVnMG5HFvBFZzNqV7Kf6y9iEoFygfzbBPCKLWSOymDcii709C9evX9fUqVOf+zZt2tTo+UyZ951WfL/X5baHuU/0WrsB1rNO2odGKy+/UMeTLmjQ6HnWcT8eO2O9vGj/0TMqLCqx7msYWTwdW9/UeWu1bN3uJn9+C1dt14d9x2pg9Dxrr7YJJ7I8R0QWHxBZzBuRxbwRWcwbkcWsJaTd11/GJqjr0l8C/uyVuhFZvI/IYtaILOaNyGJvz8LevXsVEhLy3Ne5c+dGz2fszJWK33nE5baiYodeaxuuyiqnLl6+pd4RsSotq1Dh0xL9s2OECp/+Hkju3M3RwlXbFT4yTm92idSZ1CuS3COLp2PrGz9rldZuqb2eyqO8ArXqOlytug7XkJj5kmojy5ylm3Tp2h1rr3cYQmR5jogsPiCymDcii3kjspg3IotZqx9ZAn0udSOyeB+RxawRWcwbkcXenoVgeybLsnW7NWz8IpfbjiSeV/vQaEnS3OWb1bpblDr0iVGHPjFq2Wmodv2Y2OjX2rL7mHWh28YiS1PH1rcqfp/6Rs6wPq6urtGNzGz1GjxNEi8XCgbGRZbq6pom3zarpqZGD3OfNHl/iaPMpSo29PjJU+s/PjuILOaNyGLeiCzmjchi1ogsZo7IYtaILOaNyGJvzUH2g1y17DRUv2Y/lFT7FstDxy/Uyg21LyFqHxqtnNx86/gjieetZ5Ws2bzf5e/Pucs3K/a3wNEwsng6tr5HeQX6Z8cIl2e5EFmCi3GRZebiDZq5eIPb7UnJGXrro0h98OkY/bNjhH448It1X3lFpUZOXao3ugxT625R6vfFTJerPt/LydPHn01U254j1aJjhGIXrLdeX+cJkcW8EVnMG5HFvBFZvO9WTrES0u4HxepenkNkMWtEFrNGZDFvRBZ7ay7qnrnSN3KG2odGa9r8taqoqFT61Uz1joh1ObasvEItOkboabFDsQvWq0XHCPUYNFXv9hih8FFxelJYpKJih3oOnqr/bj9Qk+eukaQmj21Mcto1dQ2fpI8/m6i+kTPVoU+MrbdwPpt6VR98GqNWXYdrc713R4J/GRNZfkpKVetuUXqpdZhbZKlyOvXWR5FKPHNRUm3J+7/vD9LjJ08lSRt2HFafYTOs9zIfHbtcMxfHW5//xaTFmv/NVkmSo7RMHfrE6Ejiea/nRGQxb0QW80ZkMW9EFs+buicj4BeUbWxEFrNGZDFrRBbzRmSxt+Ym93GBKiur/tDnVFfXKC+/UI7Scr8eK9X+7Zpf0HiIQeAYE1nqxC3d5BJIJOls6lW16jrc5ba+kTO0fd/PkqR/DZ+lrXt+su47ff6y3ukeJUmqrKzSq23ClZn1wLp/8bc7FPPlCq/nQmQxb0QW80ZkMW9EFs/rtixJfxmboG7LkoJmnRYeVdLV4PnfGZHF+4gsZo3IYt6ILPYGwN0LEVn2HkpS6JBpLreNif1GS7/bJUl6v/cY61kukvRr9kP97Z3+cjqrlZObr5dah7lci2XbvuP61/BZXs+FyGLeiCzmjchi3ogsnlcXWRLSguf/FqVdTFdWTmHAz6NuRBbvI7KYNSKLeSOy2BsAdy9EZInfecQtikyKW6NZS2qPa9l5qM6mXrXuqwsrT4sdupGZrZdah6mm5vdrsOw9lKSu4ZNcvt6iRYvcFhISoivXbzODlnYxQ+mXrgT8PNgf+J2lpSv90tWAnwezv9QLabp05XrAzyNY12Xxcf1lbIK2nkj3+Wtdv5Xln99ZaqouXb0Z8J9N3eoiS6DPI5iXkpKiy9duBfw8mM1du63z588H/jyY7V2+elMpqakBP49gHwB3L0Rk2Xf4lEI/n+5y2+jY5Vq29gdJ0gefjlHimXTrvjt3c/S3d/qrurr23Yheah2m8opK6/6te48rLGq2y9fbu3ev20JCQnTzzn1m0NIvXdGlqzcDfh7M/i5mXNKV67cDfh7M/tIupuvqjTsBP49g3UdLTugvYxO089Q1n7/W7ayHfjmnCxfSdP3W3YD/bOpWF1mm7DgfNIv/+UrAfy71l5KSqhuZ2QE/D2ZvN+7cU0pKSsDPg9nf9dt3lXrhQsDPI9gHwN0LEVnOXbiqtz/+wuW23hGx2pFwQpIUFjVbW+pdPfnkuQy922OEpNprsrzWNly3612TZeGq7YqZwTVZXsRduc7LhUwbLxcyb7xcyPN4uZD3BfoiwE3tVk5RwH82dePlQmaNlwuZN14uZG8A3L0QkaXK6dTbH3+hYydTJUlXbvyqv783yLrScvzOwwr9fLoqq2rfXWjElK+tlxJJ0vBJSzRn6SZJUnFJqd77ZLSOJqZ4PRcii3kjspg3Iot5I7J4HpHF+1IzC/TlvstBs7rIEky/MyKLWSOymDcii70BcGdMZDnw01m9/fEX+vt7g/T39wbp7Y+/cHmb5ZPnMtSy01C998lo/eODwdr1Y6J1X3lFpYZPWqIWHSP09sdfqM+wGS7vOX4vJ0+dwybone5Rer3DEE37ap2czmqv50RkMW9EFvNGZDFvRBbPI7KYt2D8nRFZzBqRxbwRWewNgDtjIosd1dU1upeTZz1jpaHCohLl5Rc2+fkPc5/IUVpm+/GILOaNyGLeiCzmjcjiecH4BzuRxbzfGZHFrBFZzBuRxd4AuHuhIsvzRmQxb0QW80ZkMW9EFs8Lxj/YiSzm/c6ILGaNyGLeiCz2BsAdkcUHRBbzRmQxb0QW80Zk8bxg/IOdyGLe74zIYtaILOaNyGJvANwRWXxAZDFvRBbzRmQxb0QWzwvGP9iJLOb9zogsZo3IYt6ILPYGwB2RxQdEFvNGZDFvRBbzRmTxvGD8g53IYt7vjMhi1ogs5o3IYm8A3BFZfEBkMW9EFvNGZDFvRBbPC8Y/2Iks5v3OiCxmjchi3ogs9gbAHZHFB0QW80ZkMW9EFvNGZPG8YPyDnchi3u+MyGLWiCzmjchibwDcEVl8QGQxb0QW80ZkMW9EFs8Lxj/YiSzm/c6ILGaNyGLeiCz2BsAdkcUHRBbzRmQxb0QW80Zk8bxg/IOdyGLe74zIYtaILOaNyGJvANwRWXxAZDFvRBbzRmQxb0QWzwvGP9iJLOb9zogsZo3IYt6ILPYGwB2RxQdEFvNGZDFvRBbzRmTxvGD8g53IYt7vjMhi1ogs5o3IYm8A3BFZfEBkMW9EFvNGZDFvwRZZfn1UooS0+0GzYPyDncjiecH4OyOymDUii3kjsthbc1NYVCKns/oPf15llVMljjK/H+svVU6nioodz/UxX2REFh8QWcwbkcW8EVnMW7BFlr+MTQjKBdMf7EQWzyOyMF9HZDFvRBZ7ay5OnsvQuz1GqEv/CXqzS6RmLYlXldNp3V9TU6M2PUZqQPRcl88rKCxW5IRFer/3GLXqOlxvdBmmQz8nq7CoRB36xOi1dgMUPX25x2MbSkrO0CttPtP/fPi53vooUoNGz9PVm1kuxzR1Pg1lZj1Q/xGz9WHfserUb5ze+ihSq+L3SZIWrtquddsOuhzfstNQlZVX6OS5DL3TPUotOw3V2q0HXI5xlJarbc+Ryrr3yLotfudhTZu/1uO5vEiILD4gspg3Iot5I7KYt2CNLN2WJQXVsoPgZ1M3IovnEVmYryOymDcii701BwWFxWrRMULnL16XJJU4yhQ6ZJq27D5mHXPh0k2Fj4pTq67DVVBYbN2+emOCZi2JV3V1jXVcXTi5l5OnTv3G2Tq2vqTkDA0bv0hSbdBYu+WA2vYc6fK4TZ1PfY7ScrXuFqWEo6et2zKzHujLhd9L8hxZJGnXj4mavmB9o197656frHhU4ijTe5+MVl5+YaPHvoiILD4gspg3Iot5I7KYt2CNLIE+j2AekcXziCzM1xFZzBuRxd6ag/XbDiosarbLbT8c+EVdwydZH8ct3aSte49r4pxvtSPhhHV7xLgFOvZLSqNft2Fk8XRsffUjS/3HX7R6h9fzqW/jrqPqPnBKk4/jS2SpcjrVqd84Xbnxq5as2akV3+/1+n29SIgsPiCymDcii3kjspg3Iot5I7J4HpGF+Toii3kjsthbczBl3ndukeBh7hO91m6A9ayT9qHRyssv1PGkCxo0ep513I/HzlgvL9p/9IwKi0qs+xpGFk/H1tdYZDmdclnhI+Osj5s6n/qmzlurZet2N/l9L1y1XR/2HauB0fOsvdom3FZkkaSjiSnqHRGrD/uOtT6nuSCy+IDIYt6ILOaNyGLeiCzmjcjieUQW5uuILOaNyGJvzcHYmSsVv/OIy21FxQ691jZclVVOXbx8S70jYlVaVqHCpyX6Z8cIFT79PZDcuZujhau2K3xknN7sEqkzqVckuUcWT8fW11hkSb9yW6GfT5ckr+dTZ/ysVVq7pfZ6Ko/yCtSq63C16jpcQ2LmS6qNLHOWbtKla3esvd5hiO3IIkm9Bk/Tph+OejzmRURk8QGRxbwRWcwbkcW8EVnMG5HF84gszNcRWcwbkcXemoNl63a7RY0jiefVPjRakjR3+Wa17halDn1i1KFPjFp2GqpdPyY2+rW27D5mXaukscjS1LH1NRZZNuw4rFlL4v/Q+ayK36e+kTOsj6ura3QjM1u9Bk+T5NvLheqMjl2uo4neXwL1oiGy+IDIYt6ILOaNyGLeiCzmjcjieUQW5uuILOaNyGJvzUH2g1y17DRUv2Y/lFT7FstDxy/Uyg21LyFqHxqtnNx86/gjieetZ4Os2bzf5Vkkc5dvVuxvYaJhZPF0bH0NI0vimXS1C4223s3H0/nU9yivQP/sGOHybBkii38QWXxAZDFvRBbzRmQxb0QW80Zk8TwiC/N1RBbzRmSxt+ai7pkrfSNnqH1otKbNX6uKikqlX81U74hYl2PLyivUomOEnhY7FLtgvVp0jFCPQVP1bo8RCh8VpyeFRSoqdqjn4Kn67/YDNXnuGklq8tiGkpIz9Pf3Bun93mP03iejNTB6njKuZUqS1/NpKDntmrqGT9LHn01U38iZ6tAnxtZbOJ9NvaoPPo1Rq67Dtbneuyw1RGTBH0ZkMW9EFvNGZDFvRBbzRmTxvLrI8uW+y0pIux8UO5WcQmQxaEQW80ZksbfmJvdxgSorq/7Q51RX1ygvv1CO0nK/HutPjtIy5Re4Bx38OUQWHxBZzBuRxbwRWcwbkcW8EVk8ry6yBNt2JmcF/GfD7I3IYt6ILPb2LBQ8dOjs3sznvhvnHj6T7wfND5HFB0QW80ZkMW9EFvNGZDFvRBbPO37lkbotSwqq/WVsgmL3ZgT8Z8Psjchi3ogs9vYs3LmYp6VDjj33JSy7+Ey+HzQ/RBYfEFnMG5HFvBFZzBuRxbwRWczal/suE1kMG5HFvBFZ7O1Z4JksMB2RxQdEFvNGZDFvRBbzRmQxb0QWs0ZkMW9EFvNGZLE3eFdZ5dTl63eavr+ySinpN1RTUyNJqnI6lXb5lvVuQc/bw9wnup31wO9f11Fa1ujtf/QaNyYgsviAyGLeiCzmjchi3ogs5o3IYtaILOaNyGLeiCz21hwkJWfolTaf6fUOQ/TWR5FatHrHH/r8vPxCfdR/YpP3f7f5R32//ZD1ceewCVqwcpuO/RKYd+UpLilVn2EzVFhU4v1gG0ocZQofFaduAybrvU9GKyX9uiTpSWGRwkfGafikJdbbYUvSlHnfWe+WZCoiiw+ILOaNyGLeiCzmjchi3ogsZo3IYt6ILOaNyGJvzUFScoaGjV8kqfZZHu1Do3U29artz/cUWQqflqjn4KlyOqslSTcys63HsqP8t7eR9reDx89q7rLNfvla8TuPaNr8tZKklPQb6jV4mqTat8WuiyvdB06RVPvzjRi3wC+PG0hEFh8QWcwbkcW8EVnMG5HFvBFZzBqRxbwRWcwbkcXemoP6kUWSZi6O1/fbD+nE6TQtWLlNs5bEq9uAyXKUlmtHwgm1C41W216jtG7bQUm1kaVdaLSipy/X2x9/ofnfbFVpWYUk6fvth7Qqfp/1tbuGT1KLjhHqHDbB47M5SssqtG7bQbUPjVb8ziN/6vv6asVWxe88LKn22Svho+KUl18oSXI6q9W21ygr/vgicsIi/XI23fr47Y+/UHFJqb7b/KN2JJyQJHXpP0FVTqfmLN30hwJWsCKy+IDIYt6ILOaNyGLeiCzmjchi1ogs5o3IYt6ILPbWHNSPLGXlFeo5eKqSkjO0/+gZte01Sod+TtaNzGyVOMr0Yd+xupeTp0d5BerSf4KeFBYpL79Qb3QZpvQrt/W02KGIcQt0JPG8JGlS3Bpdu3XXeqzjSRc0cc63TZ6Lo7RM327arw59YrRw1XY9fvLU5f6oyV+rY79xLuscNqHRr/WksEjtQ6N1/Xa2xs1cpZ37T7jcHzNjhe7czWnkHMrdHqNjv3FNnvcnEbG6ejPL+vij/hP1a/ZDpaTf0LiZq3Tnbo7ComaroLBYA6LnSpKS065ZLysyEZHFB0QW80ZkMW9EFvNGZDFvRBazRmQxb0QW80ZksbfmICk5Qy06Rih0yDS17halBSu3SZL2Hz2jmYs3WMf9lJSqSXFrrI/nfbNFuw+edHu50N5DSZq1JF5SbYAocfx+QVhPkaWmpkZvdBmmyImLXT7HF6eSL+md7lGK+XKF231L1uy0YpAvegyaqhuZ2dbH3QZM1q079+R0Vmv3wZOauXiDbmc90Ndrdul40gVt2HFYMxfHK3bBem364ajPjx8IRBYfEFnMG5HFvBFZzBuRxbwRWcwakcW8EVnMG5HF3pqDpOQMDYieq4e5T1xePtMwsuw7fMqKJ5K0bO0Pit952C2y7DtySjEzaqNG6OfT5Sgtt+7z9kyW67ezFT19ufpGztCxX1KsdySqM3PxBg2J+cplnq5xcuvX+2rRMUKzv97odt/S73bp0M/JbreXlVe4PcaQmK+0cNX2Rh9j8Jj5Ls9KadtrlJ4UFrkcU+Io07+Gz1JNTY0+H7tA2Q9ydedujiInLm7y3IMZkcUHRBbzRmQxb0QW80ZkMW9EFrNGZDFvRBbzRmSxt+ag4TVZ6jSMLAWFxeoaPkkVFZWqcjrVZ9gMZT/IdYks1dU1Gh27XBt31T5DY+Kcb3Xrzj3ra3iLLHWy7j3U5Llr1DV8kk6cTrNuf5RXoOwHuS67l5PX6Ncor6hUz8FTlX41U90HTlHimYsu90+YvbrRt3Kuqalxe4y677MxKzfs1ZI1OyVJd+7mqGO/cW7HrNm8X/uPnpFU+zKlG5nZunLjV1s/i2BEZPEBkcW8EVnMG5HFvBFZzBuRxawRWcwbkcW8EVnsrTmwG1kkae2WA+o1eJpCh0zTsrU/SKq98O0/PhisvpEz9MGnYxQ+Kk7lFZWSpHXbDmrN5v3W59uNLHVycvP186k07wc2YvqC9fp2U+1j37pzT217jnS58G270GhVOZ1/6mvXV1BYrN4RsQqLmq33e49xiznlFZXqGznTepZQ4pl0DRu/SEPHL9Tp85d9fvxAILL4gMhi3ogs5o3IYt6ILOaNyGLWiCzmjchi3ogs9gZ3lVVOK6LUV1Ze4fZsj8Ki2rdwrv+SoWCwc/+JJl/+82fl5RfajjaVlVWqrKzy6+M/T0QWHxBZzBuRxbwRWcwbkcW8EVnMGpHFvBFZzBuRxd7gu72HkjQm9hu366sEyo3MbHUfOEVl5RWBPhVjEVl8QGQxb0QW80ZkMW9EFvNGZDFrRBbzRmQxb0QWe4N/VFcHR2CRaq+5EizBx1REFh8QWcwbkcW8EVnMG5HFvBFZzBqRxbwRWcwbkcXeALh74SLLw9wnTZa3EkeZCp+WNPm5j588/UNPiyKymDcii3kjspg3Iot5I7KYNSKLeSOymDcii70BcPfCRJb4nUfUY9BUhY+MU+d/jdfib3dY95VXVGrk1KV6o8swte4WpX5fzFRBYbF1/72cPH382US17TlSLTpGKHbBeltP2SKymDcii3kjspg3Iot5I7KYNSKLeSOymDcii70BcPdCRJbbWQ/0aptw6z3ASxxlatlpqK7fzpYkbdhxWH2GzbCuZjw6drlmLo63Pv+LSYs1/5utkiRHaZk69InRkcTzXh+XyGLeiCzmjchi3ogs5o3IYtaILOaNyGLeiCz2BsDdCxFZrt26q1fbhCv3cYF1W5f+E5R4Jl2S9K/hs7R1z0/WfafPX9Y73aMk1b491KttwpWZ9cC6f/G3OxTz5Qqvj0tkMW9EFvNGZDFvRBbzRmQxa0QW80ZkMW9EFnsD4O6FiCySFPPlCr3bY4S27D6m+J2H9fnYBdZ7a7/fe4wSz1y0jv01+6H+9k5/OZ3VysnN10utw1yuxbJt33H9a/gsr49JZDFvRBbzRmQxb0QW80ZkMWtEFvNGZDFvRBZ7A+DuhYksPxz4ReGj4jR0/EK9/G5/xe88bN3XsvNQnU29an1cF6WKV8wAACAASURBVFaeFjt0IzNbL7UOc7lY7t5DSeoaPsnl60+fPt1tISEhunTlOjNoF9IuKi39UsDPg9lf6oU0XQzS31kGa3QpqReUnnEl4OdRt7rIEujzeBa7cv22f35nKSlKv3Q14N8Ps7cJW07pL2MTNGHzqYCfC7O5y9d0/vx5v37NQP//wBd9GZeu6nxKSsDPI9gHwN0LEVkuXr6l1t2irGeuXL5+R626Dtf+o2ckSR98OsZ66ZAk3bmbo7+901/V1TV6mPtEL7UOU3lFpXX/1r3HFRY12+UxTpw44baQkBDdynrIDFr6pau6fO1WwM+D/YHfWcZlXblxJ+Dn0dhus0aXdjFd125lBfw86lYXWfz+te8Gwx755eukXkjTjcx7QfD9MDubuitVfxmboCk7UwL+vy9mb7eyHur8+fN+/5rs2e3GnftKTb0Q8PMI9gFw90JEllXx+/TZiDkut02YvVpT562VJIVFzdaW3ces+06ey9C7PUZIqr0my2ttw3W73jVZFq7arpgZXJPlRRwvFzJvvFzIvPFyIfPGy4XMGi8XMm+8XMi88XIhewPg7oWILMeTLuiVNp/pzt0cSVJpWYXe6R5lXew2fudhhX4+XZVVte8uNGLK15q15Pd3Fxo+aYnmLN0kSSouKdV7n4zW0cQUr49LZDFvRBbzRmQxa1l5DitqBNsC/bMJ5hFZzBqRxbwRWcwbkcXeALh7ISKLJK3csFcd+41T74hYdQ6boEWrd6i6uvY6K+UVlRo+aYladIzQ2x9/oT7DZuhJYZH1ufdy8tQ5bILe6R6l1zsM0bSv1snprPb6mEQW80ZkMW9EFrOWkHY/4DGFyPLHR2Qxa0QW80ZkMW9EFnsD4O6FiSx1HjzKd7mIbX2FRSXKyy9s8nMf5j6Ro7TM9mMRWcwbkcW8EVnMWl1k+fjrxICfC7O3Xx8+Vc+dvfTp3n7qsy8saPb5t1EB/9kE64gs5o3IYt6ILPYGwN0LF1meJyKLeSOymDcii1kjspi3A9dP6uV1LwflAv2zCdYRWcwbkcW8EVnsDYA7IosPiCzmjchi3ogsZo3IYt7qIsune/vpwPWTQbG6yBLoZ9M0XPbjkoD/vu4/JrKYOCKLeSOy2BsAd0QWHxBZzBuRxbwRWcwakcW81Y8sgT6XugX6GTRN7cD1kwH/2dx/TGQxcUQW80ZksbfmprCoxNa1OxuqrHKqxGHvshR/5Fh/qXI6VVTseK6P+SIjsviAyGLeiCzmjchi1ogs3nf4+Gm98WaroNl7Az4MusgS8m8h+vf//PeAP6Ombn32hRFZmE8jspg3Iou9NRcnz2Xo3R4j1KX/BL3ZJVKzlsSryum07q+pqVGbHiM1IHquy+cVFBYrcsIivd97jFp1Ha43ugzToZ+TVVhUog59YvRauwGKnr7c47ENJSVn6JU2n+l/Pvxcb30UqUGj5+nqzSyXY5o6n4Yysx6o/4jZ+rDvWHXqN05vfRSpVfH7JEkLV23Xum0HXY5v2WmoysordPJcht7pHqWWnYZq7dYDLsc4SsvVtudIZd17ZN0Wv/Owps1f6/FcXiREFh8QWcwbkcW8EVnMGpHF+954s5VCQkKCZv/+n/8efJHlt3ML9HnUjcjCfB2RxbwRWeytOSgoLFaLjhE6f/G6JKnEUabQIdO0Zfcx65gLl24qfFScWnUdroLCYuv21RsTNGtJvPWutxcu3bTCyb2cPHXqN87WsfUlJWdo2PhFkmqDxtotB9S250iXx23qfOpzlJardbcoJRw9bd2WmfVAXy78XpLnyCJJu35M1PQF6xv92lv3/GTFoxJHmd77ZLTHN6B50RBZfBBM/wBk9kZkMW9EFrNGZPG+usgyKmaitu85GPBNWTubyOJlRBbm64gs5o3IYm/NwfptBxUWNdvlth8O/KKu4ZOsj+OWbtLWvcc1cc632pFwwro9YtwCHfslpdGv2zCyeDq2vvqRpf7jL1q9w+v51Ldx11F1HzilycfxJbJUOZ3q1G+crtz4VUvW7NSK7/d6/b5eJEQWHwTTPwCZvRFZzBuRxawRWbyvLrJs33Mw4Ody/3FwXpOlLrIEOkDVjcjCfB2RxbwRWeytOZgy7zu3SPAw94leazfAetZJ+9Bo5eUX6njSBQ0aPc867sdjZ6yXF+0/ekaFRSXWfQ0ji6dj62ssspxOuazwkXHWx02dT31T563VsnW7m/y+F67arg/7jtXA6HnWXm0TbiuySNLRxBT1jojVh33HWp/TXBBZfEBkMW9EFvNGZDFrRBbvI7J4X6BfQtVwfx33VyIL82lEFvNGZLG35mDszJWK33nE5baiYodeaxuuyiqnLl6+pd4RsSotq1Dh0xL9s2OECp/+Hkju3M3RwlXbFT4yTm92idSZ1CuS3COLp2PrayyypF+5rdDPp0uS1/OpM37WKq3dUns9lUd5BWrVdbhadR2uITHzJdVGljlLN+nStTvWXu8wxHZkkaReg6dp0w9HPR7zIiKy+IDIYt6ILOaNyGLWiCze98abrfRv/+vfNGXt7IBf0PXA9ZOKO7Uk6CLL1C/jAn5B4PojsjBfR2Qxb0QWe2sOlq3b7RY1jiSeV/vQaEnS3OWb1bpblDr0iVGHPjFq2Wmodv2Y2OjX2rL7mHWtksYiS1PH1tdYZNmw47BmLYn/Q+ezKn6f+kbOsD6urq7Rjcxs9Ro8TZJvLxeqMzp2uY4men8J1IvGdmSpqKiUo/T5vpVUsCOymDcii3kjspg1Iov3fTy/R8DfirixBVNkCbYF88uFEtLuB82yg+BnE6wjspg3Iou9NQfZD3LVstNQ/Zr9UFLtWywPHb9QKzfUvoSofWi0cnLzreOPJJ63ng2yZvN+l2eRzF2+WbG/hYmGkcXTsfU1jCyJZ9LVLjTaejcfT+dT36O8Av2zY4TLs2WILP7RZGQpr6jU99sPaXTscnUOm6BX2nyml1qH6b1PRity4mItW7db+QVFz/Ncgw6RxbwRWcwbkcWsEVm8r+4P9j77woJmPXf2UtLN9ID/bIJ1wRpZgm3dliUF/GcTrCOymDcii701F3XPXOkbOUPtQ6M1bf5aVVRUKv1qpnpHxLocW1ZeoRYdI/S02KHYBevVomOEegyaqnd7jFD4qDg9KSxSUbFDPQdP1X+3H6jJc9dIUpPHNpSUnKG/vzdI7/ceo/c+Ga2B0fOUcS1TkryeT0PJadfUNXySPv5sovpGzlSHPjG23sL5bOpVffBpjFp1Ha7N9d5lqSEiSz0nz2Xo/d5j9H7vMVr63S4lJWcoM+uBsh/k6tyFq/p++yH1HDxVLTsP1Y6EE6qpqXne5x0UiCzmjchi3ogsZo3I4n3B9gf7/celSruYrqycwoCfR7Au2H5nN3OK1WnBEXVddlLdliUFxYgsnkdkMW9EFntrbnIfF6iysuoPfU51dY3y8gvlKC3367H+5Cgta/ZPoPAnt8iyfP1uvdFlmHb9mOg1npxKvqQPPo3RyKlLn9kJBjMii3kjspg3IotZI7J4X7D9wX7/MZHFxN9ZauoFZecWB/w87j/+/X/3RJamR2Qxb0QWe3sWqvJK9fTwr899jgu5z+T7QfPjFlm+Wb9H93PybH+BEkeZ5izd5NeTMgWRxbwRWcwbkcWsEVm8Lxj/YCeymPc7I7KYNSKLeSOy2NuzUHYlX9ljE5/78tZdeibfD5of3l3IB0QW80ZkMW9EFrNGZPG+YPyDnchi73cW6GvnuFxHZ0dPXci6HfCfzf3HRBY7I7KYNyKLvT0LPJMFpvtTkaW0rELnL17397kYh8hi3ogs5o3IYtaILN5HZDFvPVf2Dvi7PzW2OUmLAv6zuf+YyGJnRBbzRmSxN3hXWeXU5et3mr6/skop6TesS3VUOZ1Ku3zLereg5+1h7hPdznrw3B6vvKJSlVVOt9v/6LVvgkmjkeVh7hNNnPOtPh36pSbMXq2rN7Nc7r+ZeU8vtQ57HucX1Igs5o3IYt6ILGaNyOJ9RBbz9sabrfRv/+vfNGXtbB24fjLgizu1hMhi2Igs5o3IYm/NQVJyhl5p85le7zBEb30UqUWrd/yhz8/LL9RH/Sc2ef93m3/U99sPWR93DpugBSu36dgvgXlXnuKSUvUZNkOFRSXeD7bh5LkM/e2d/nqt3QBruY8LJElzlm5Sx37j9H7vMS4/g7EzV2rk1KWKmvy1ddu+I6e0dssBv5zTs9ZoZOkbOUP/+GCIoiZ/rXd7jNCrbcK1fd/P1v1EllpEFvNGZDFvRBazRmTxPiKLeXvjzVYKCQnR9j0HA34u9x+XElkMHJHFvBFZ7K05SErO0LDxiyTVPhmhfWi0zqZetf35niJL4dMS9Rw8VU5ntSTpRma29Vh2lP/2NtL+dvD4Wc1dttkvX+vkuYxG3yjnRma2OodNUJXTqaJih1p3i9LTYocKn5ZoYPQ8SVLkxMV68ChfNTU1+tfwWXKUlvnlnJ41t8iSX1Ckl9/tr7v3f3960o6EE3qt3QBt3fOTJCJLHSKLeSOymDcii1kLxsgybHi03nizVdDsr+P+SmQxbEQWzyOyeB+RxbwRWeytOagfWSRp5uJ4fb/9kE6cTtOClds0a0m8ug2YLEdpuXYknFC70Gi17TVK67YdlFQbWdqFRit6+nK9/fEXmv/NVpWWVUiSvt9+SKvi91lfu2v4JLXoGKHOYROUca3peFJaVqF12w6qfWi04nce+VPf11crtip+52FJtc9eCR8Vp7z8QkmS01mttr1GWfHHF01FlvXbDmrBym3WxyOnLtOxk6nKuJapmBkrJEnT5q/VuQtXdexkqpZ+t8vnc3le3CLLweNn9cGnY9wOPHE6TX9/b5AOHj9LZPkNkcW8EVnMG5HFrAVjZAkJCQmqEVnMG5HF84gs3kdkMW9EFntrDupHlrLyCvUcPFVJyRnaf/SM2vYapUM/J+tGZrZKHGX6sO9Y3cvJ06O8AnXpP0FPCouUl1+oN7oMU/qV23pa7FDEuAU6knhekjQpbo2u3bprPdbxpAuaOOfbJs/FUVqmbzftV4c+MVq4arseP3nqcn/U5K/Vsd84l3UOm9Do13pSWKT2odG6fjtb42au0s79J1zuj5mxQnfu5jRyDuVuj9Gx37gmz/vkuQz9s2OEuoZPUuTExdalSBas3Kb1v4UoSZq5eIO27Tuuysoq9Ro8Tfdz8vRJRKwcpeUKHxWnwqcl+jX7oY4knm/0Gi7BxC2ynEq+pNc7DGn04COJ5/X39wZp697jRBYRWUwckcW8EVnMWjBHlu17DgbFeLmQeSOyeB6RxfuILOaNyGJvzUFScoZadIxQ6JBpat0tynr2xf6jZzRz8QbruJ+SUjUpbo318bxvtmj3wZNuLxfaeyhJs5bES5I+iYhVieP3l8B4iiw1NTV6o8swRU5c7PI5vjiVfEnvdI9SzJcr3O5bsmanFYN8UVxSqgeP8vWksEi7fkzUuz1GqKamRnOXbXZ5Fs7srzdq0w9HJUnnLlzVtK/W6VTyJZ1JvaK5yzbr6s0shY+M0+bdxxp9ZkwwcYssBYXFeqXNZ0o8c7HRT9i8+5heaxtOZBGRxcQRWcwbkcWsBXNkCfR51I3IYt6ILJ5HZPE+Iot5I7LYW3OQlJyhAdFz9TD3icvLZxpGln2HT1nxRJKWrf1B8TsPu0WWfUdOWS+HCf18uhyl5dZ93p7Jcv12tqKnL1ffyBk69kuK9Y5EdWYu3qAhMV+5LGLcgia/3q1f76tFxwjN/nqj231Lv9ulQz8nu91eVl7h9hhDYr7SwlXbm3yc+tr0GKlHeQVavTFB36zfY90+ftYqHTx+zu34z8cuUO7jAn23+Uft+jFRUu3FgRt+78Gk0QvfHvo5Wclp15r8pDWb92t07PJndlKmCKZ/tDN7I7KYNyKLWSOyeB+RxbwRWTyPyOJ9RBbzRmSxt+ag4TVZ6jSMLAWFxeoaPkkVFZWqcjrVZ9gMZT/IdYks1dU1Gh27XBt31T5jY+Kcb3Xrzj3ra3iLLHWy7j3U5Llr1DV8kk6cTrNuf5RXoOwHuS67l5PX6Ncor6hUz8FTlX41U90HTnF7ksWE2asbfSvnmpoat8eo+z4bc+dujhWnsu491FsfRcrprFZqxg31jZwpSaqoqNT7vcfoUV6By+emX83UtPlrJdVeJ7bumS/dBkz2+jMKpEYjC+wJpn+0M3sjspg3IotZI7J4H5HFvBFZPI/I4n1EFvNGZLG35sBuZJGktVsOqNfgaQodMk3L1v4gqfbCt//4YLD6Rs7QB5+OUfioOJVXVEqS1m07qDWb91ufbzey1MnJzdfPp9K8H9iI6QvW69tNtY996849te050uXCt+1Co1Xl9P3aJyu+36t3ukep3xcz1abHSB0+8fuzYybMXq2eg6eqc9gE6+dV34gpX1tvyJOTm6+B0fMU8+UK67yDFZHFB8H0j3Zmb0QW80ZkMWtEFu8jspg3IovnEVm8j8hi3ogs9gZ3lVVOK6LUV1Ze4fZsj8Ki2rdwrv+SoWCwc/8J2y//saO0rEIPHuU3+m5FT4sdf+j7N+FtnG1FloPHz+r0+cvP+lyME0z/aGf2RmQxb0QWs0Zk8T4ii3mriyzBsv/4+D+ILIaNyGLeiCz2Bt/tPZSkMbHfBM01Rm5kZqv7wCkqK68I9KkYy2NkKSuv0NR5a/Vml0jdyMx+XudkjGD6RzuzNyKLeSOymDUii/cRWczbl7O/CnhYIbKYPSKLeSOy2Bv8o7o6OAKLVHvNlWAJPqZqMrLcyMxW57AJCh8Vp9zHBU0d1qwF0z/amb0RWcwbkcWsEVm8j8jCfB0vFzJvRBbzRmSxNwDuGo0sW/f8pNc7DNHqjQlULA+C6R/tzN6ILOaNyGLWiCzeR2Rhvo7IYt6ILOaNyGJvANy5RZabmff0Uusw7dx/IhDnY5Rg+kc7szcii3kjspi1YIwsL697OShHZGF/dkQW80ZkMW9EFnsD4M4tstTU1Gjt1gP6nw8/16YfjgbinIxBZDFvRBbzRmQxa0QW+7uTGzxRg8hi1ogs5o3IYt6ILPYGwF2T12S5dO2OPvh0jIaNX6SCwuLneU7GILKYNyKLeSOymLVgjiyBPo9gHpHFrBFZzBuRxbwRWewNgDuP7y7kKC1TzIwVat0tSrfu3Hte52QMIot5I7KYNyKLWSOymDkii1kjspg3Iot5I7LYGwB3HiNLnT2HTurE6bRnfS7GIbKYNyKLeSOymDUii5kjspg1Iot5I7KYNyKLvQFwZyuyoHFEFvNGZDFvRBazRmQxc0QWs0ZkMW9EFvNGZLE3AO6ILD4gspg3Iot5I7KYNSKLmSOymDUii3kjspg3Iou9AXDnMbLU1NTowqWb+nrNLo2atsxtwSq/oEiPnzx1u73EUabCpyVNft7jJ09VVl5h+3GILOaNyGLeiCxmjchi5ogsZo3IYt6ILOaNyGJvANx5jCxHE1P08rv9FT4qTjEzVmj8rFUuCzZrNu9Xq67D9UaXYerUb5x1e3lFpUZOXao3ugxT625R6vfFTJd3TLqXk6ePP5uotj1HqkXHCMUuWK/q6hqvj0dkMW9EFvNGZDFrRBYzR2Qxa3WR5dN9/1LcqSVBsf933gh1W34i4D+bYB2RxbwRWewNgDuPkWVIzHx9tWLr8zoXn3y9Zpe6hk/Sz6fS5HRWq8rptO7bsOOw+gybYd02Ona5Zi6Ot+7/YtJizf+m9vt0lJapQ58YHUk87/UxiSzmjchi3ogsZo3IYuaILGatLrIE2/rsCwv4zyZYR2Qxb0QWewPgzmNkGTp+oVZvTHhe5/KnPS126B8fDNHPpxp/B6R/DZ+lrXt+sj4+ff6y3ukeJUmqrKzSq23ClZn1wLp/8bc7FPPlCq+PS2Qxb0QW80ZkMWtEFjNHZDFro8ZN1H98/B/6aH73gD+DJe7UEvXZF0Zk8TIii3kjstgbAHceI8vB4+fUbcBkOZ3Vz+t8/pSk5Ay93mGIFq3eoc9GzNHgMfN1+ESydf/7vcco8cxF6+Nfsx/qb+/0l9NZrZzcfL3UOszlWizb9h3Xv4bP8vq4RBbzRmQxb0QWs0ZkMXNEFrM2KmaiQkJCNHLM+ICfy/3HpTpw/SSRxcuILOaNyGJvANx5fXehjz+bqE+HfqkB0XPdFix2JJzQm10itWX3MaWkX9e2fcf19/cG6cTp2me2tOw8VGdTr1rH14WVp8UO3cjM1kutw1RT8/s1WPYeSlLX8EkujxEdHe22kJAQpV+6ygzahQtpSruYHvDzYPaXeiFNaRczAn4ewbqzaVfUeeGxoNpfxiao88KjAf/Z1K0usgT6PJ7Frly/7Zevk5KSqosZlwP+/TB7ixg6TCEhIYoYOizg55J+6aq2nt6pl9e9rF47QwN+LsG7Kzp//nwQnAezvYzLSklJCfx5BPmam8Kikj/1BITKKqdKHGV+P9ZfqpxOFRU7nutjvsg8RpZV8fv0WrsBGjl1mWYujtecpZtcFix2/ZioPsNmuNw2Y9H3mjB7tSTpg0/HKPFMunXfnbs5+ts7/VVdXaOHuU/0UuswlVdUWvdv3XtcYVGzXb5eWlqa20JCQnTn3mNm0C5dua6rN+4E/DyY/WVcuqprt7ICfh7Bumk/pOkvYxOCbh8t+TngP5u61UWWQJ/Hs9ivD/L98nUupF3UrV9zAv79MHuLGhWjkJAQDR85OuDncufeY+3LOKaX172s3nv6BvxcgnWZ2XlKSUkJ+Hkw+7ud9VCpF9ICfh7Bvubi5LkMvdtjhLr0n6A3u0Rq1pJ4l2uA1tTUqE2PkW5PRCgoLFbkhEV6v/cY6w1aDv2crMKiEnXoE6PX2g1Q9PTlHo9tKCk5Q6+0+Uz/8+HneuujSA0aPU9Xb2a5HNPU+TSUmfVA/UfM1od9x6pTv3F666NIrYrfJ0lauGq71m076HJ8y05DVVZeoZPnMvRO9yi17DRUa7cecDnGUVqutj1HKuveI+u2+J2HNW3+Wo/n8iLxGFl6R8Rq6Xe7nte5/GnnLlxV625RLrfFLliv0bG1/8GGRc3Wlt3HrPvq/kci1V6T5bW24bpd75osC1dtV8wMrsnyIo6XC5k3Xi7keV/uu2y9dWpC2v2Ab++F+/p//s8r+mfLN/XGm62CYrxcyPt4uZBZ4+VC5o2XC5k3Xi5kb81BQWGxWnSM0PmL1yVJJY4yhQ6Z5vL35YVLNxU+Kk6tug53eRfb1RsTNGtJvPXOtRcu3bTCyb2cPJd3xPV0bH1JyRkaNn6RpNqgsXbLAbXtOdLlcZs6n/ocpeVq3S1KCUdPW7dlZj3Qlwu/l+Q5ski1T3SYvmB9o197656frHhU4ijTe5+MVl5+YaPHvog8Rpbhk5Zo5Ya9z+tc/rTyikq17TVKu35MlCQ9eJSvd7pH6YcDv0iqLWehn09XZVVtbRwx5WvNWvL7uwsNn7TEemZOcUmp3vtktI4mpnh9XCKLeSOymDcii+fVRZYv910O+Lncf1yq7XsOKiQkJKhGZPE+IotZI7KYNyKLeSOy2FtzsH7bQbdXOfxw4BeXy0vELd2krXuPa+Kcb7Uj4YR1e8S4BTr2S+N/VzaMLJ6Ora9+ZKn/+ItW7/B6PvVt3HVU3QdOafJxfIksVU6nOvUbpys3ftWSNTu14vvgbwr+5DGynLtwVZ3/NV6VlVXP63z+tLpns3ToE6NX24Qrbukm6zor5RWVGj5piVp0jNDbH3+hPsNm6ElhkfW593Ly1Dlsgt7pHqXXOwzRtK/W2XqtHZHFvBFZzBuRxfOCNbK0aPmmtu85GBQjsngfkcWsEVnMG5HFvBFZ7K05mDLvO7dI8DD3iV5rN8B61kn70Gjl5RfqeNIFDRo9zzrux2NnrJcX7T96RoVFJdZ9DSOLp2PrayyynE65rPCRcdbHTZ1PfVPnrdWydbub/L4XrtquD/uO1cDoedZebRNuK7JI0tHEFPWOiNWHfce6vMlMc+AxsixZs1OvtRugD/uOVY9BU90WbKqra5T9IFeO0vJG7y8sKvH4NKWHuU/kKLV/kSEii3kjspg3IovnBXNkCfS51I3I4n1EFrNGZDFvRBbzRmSxt+Zg7MyVit95xOW2omKHXmsbrsoqpy5evqXeEbEqLatQ4dMS/bNjhAqf/h5I7tzN0cJV2xU+Mk5vdonUmdQrktwji6dj62sssqRfua3Qz6dLktfzqTN+1iqt3VJ7PZVHeQVq1XW4WnUdriEx8yXVRpY5Szfp0rU71l7vMMR2ZJGkXoOnadMPRz0e8yLyGFmOnUzVN+v3NLnmjshi3ogs5o3I4nlEFu8jsngfkcWsEVnMG5HFvBFZ7K05WLZut1vUOJJ4Xu1DoyVJc5dvtl5R0aFPjFp2GmpdxqKhLbuPWdcqaSyyNHVsfY1Flg07DluXw7B7Pqvi96lv5O9vHlNdXaMbmdnqNXiaJN9eLlRndOxyW5fheNF4fQtnNI3IYt6ILOaNyOJ5RBbvI7J4H5HFrBFZzBuRxbwRWeytOch+kKuWnYbq1+yHkmrfYnno+IXWtUvbh0YrJzffOv5I4nnr2SBrNu93eRbJ3OWbFftbmGgYWTwdW1/DyJJ4Jl3tQqOtd/PxdD71Pcor0D87Rrg8W4bI4h9ukeXwiWS3t4BC44gs5o3IYt6ILJ5HZPE+Iov3EVnMGpHFvBFZzBuRxd6ai7pnrvSNnKH2odGaNn+tKioqlX41U70jYl2OLSuvUIuOEXpa7FDsgvVq0TFCPQZN1bs9Rih8VJyeFBapqNihnoOn6r/bD9TkuWskqcljG0pKztDf3xuk93uP0XufjNbA6HnKuJYpSV7Pp6HktGvqGj5JH382UX0jZ6pDnxhbb+F8NvWqPvg0Rq26Dtfmeu+y1BCR5Tfrth3U/31/kLoNmKyNu442ecEdEFlMHJHFvBFZPI/I4n1EFu8jspg1Iot5I7KYNyKLvTU3uY8LhGU4tAAAIABJREFU/vCbwlRX1ygvv7DJ64b+2WP9yVFapvwC96CDP6fRlwuVOMq0fd/P+iQiVv/VfqBGxy7X6fOXrXfrQS0ii3kjspg3IovnEVm8j8jifUQWs0ZkMW9EFvNGZLG3Z+F2XokWHL7+3Lf7wv1n8v2g+fF6TZZbv97X3OWb9dZHkWoXGq1l63brwaN8b5/WLBBZzBuRxbwRWTyPyOJ9RBbvI7KYtfqRJdBvkb59z0FNWTubyOJlRBbzRmSxt2fhyJWH+svYhOe+8HXnnsn3g+bH9oVvq5xOHU1M0dDxC/Va23ANGj1PB346+4efLvUiIbKYNyKLeSOyeB6RxfuILN5HZDFrdZElWPbv//nvRBYvI7KYNyKLvT0LPJMFpvtT7y6Ul1+o1RsT9GHfsWrZeaiKS5rf6/EkIouJI7KYNyKL5xFZvI/I4n1EFrN2Kztf//jHP9Tyzbf1xputAr73BnxIZPEyIot5I7LYG7yrrHLq8vU7Td9fWaWU9BvWpTmqnE6lXb5lvVvQ8/Yw94luZz3w+9etrq5p9PIj5RWVqqxyNnp8aVlFo7dXOd2PDyZukaW8olIljjLbXyAl/YbKKyr9elKmILKYNyKLeSOyeB6RxfuILN5HZDFvqakXlJ1bHPDzuP+Ya7LYGZHFvBFZ7K05SErO0CttPtPrHYborY8itWj1jj/0+Xn5hfqo/8Qm7/9u84/6fvsh6+POYRO0YOU2HfslMO/KU1xSqj7DZvj1DXCczmpFTf7a7Xuas3STOvYbp/d7j3H5GRz46azahUbro/4TFfPlCiuqnLtwVQOj52nwmPlKPJMuqTa69I2cab21dDBwiyzXb2frlTaf6ZOIWC1avUOnUy4324jiDZHFvBFZzBuRxfOILN5HZPE+Iot5C9bIkpB2P2h2Myc4fj73HxNZTByRxd6ag6TkDA0bv0hS7bM82odG62zqVduf7ymyFD4tUc/BU+V0VkuSbmRmW49lR/lvbyPtbwePn9XcZZv98rXu5+SpZeeheql1mEtkuZGZrc5hE1TldKqo2KHW3aL0tNghp7NabXqM1P2cPElS+Kg4nTidJkmauTheqRk3dPVmlibO+fa3cz1nve10sHCLLJWVVfrlbLoWrNymTyJi9Uqbz/Rf7QcqfGScVm7Yq4uXb1n/ETR3RBbzRmQxb0QWzyOyeB+RxfuILOYtGCPL/7e8S0AuVulpWXmOgP987j8mspg4Iou9NQf1I4tU+4f+99sP6cTpNC1YuU2zlsSr24DJcpSWa0fCCbULjVbbXqO0bttBSbWRpV1otKKnL9fbH3+h+d9stV4G8/32Qy6BoGv4JLXoGKHOYROUca3peFJaVqF12w6qfWi04nce+VPf11crtip+52FJtc9eCR8Vp7z8Qkm1zzxp22uUX//uHz9rlY6dTLU+Xr/toBas3GZ9PHLqMh07maqrN7P0SUSsdfvm3ccUt3STJOnzsQuUde+R8vILFRY1W5LUf8RsFRU7/Hae/uD1miyO0nKdPJehhau2q3dErF5tE67XOwzR0PELn8f5BTUii3kjspg3IovnBWNk+d+f/m/9ddxf1WdfWFCMyOJ9RBbzFqyRpduypKBYXWRJSAuO/59PZDFvRBZ7aw7qR5ay8gr1HDxVSckZ2n/0jNr2GqVDPyfrRma2Shxl+rDvWN3LydOjvAJ16T9BTwqLlJdfqDe6DFP6ldt6WuxQxLgFOpJ4XpI0KW6Nrt26az3W8aQL1jM0GuMoLdO3m/arQ58YLVy1XY+fPHW5P2ry1+rYb5zLOodNaPRrPSksUvvQaF2/na1xM1dp5/4TLvfHzFihO3dzGjmHcrfH6NhvnMfzltwjy4KV27T+txAlSTMXb9C2fcf1y9l0RU74PWodPpGsMbHfSJJWfL9XW/ce177Dp7Rw1XYlnknXwlXbVVnl1OETyQG7jk1Dti98W1Ts0PGkC5q+YL3+q/1AvdQ67BmelhmILOaNyGLeiCyeF2yRZdfBI1bUCLYF+mcTzCOymLdgjCzBdE2WutBCZGF/dkQWe2sOkpIz1KJjhEKHTFPrblHWsy/2Hz2jmYs3WMf9lJSqSXFrrI/nfbNFuw+edHu50N5DSZq1JF6S9ElErMv1UD1FlpqaGr3RZZgiJy7+Q9dQ9eRU8iW90z1KMV+ucLtvyZqdVgzyh4aRZe6yzS7Pwpn99UZt+uGojiddUNTkr63bj/2SopFTl0qSnhY7tHLDXi1bt1sFhcUaNHqeHj95qqjJX2vr3uMKi5qtG5nZfjvnP6vJyPK02KGfklIVt3STegyaqpff7a+O/cZp+oL1Onj8rFs1a46ILOaNyGLeiCyeF2yRpe6Prd57+urA9ZNBszu5BISm9uBBibLHJgbd7sWdC/jPJphHZPE8IgvzdUQWe2sOkpIzNCB6rh7mPnF5+UzDyLLv8CkrnkjSsrU/KH7nYbfIsu/IKcXMqI0aoZ9Pl6O03LrP2zNZrt/OVvT05eobOUPHfklxe7eemYs3aEjMVy6LGLegya9369f7atExQrO/3uh239LvdunQz8lut5eVV7g9xpCYr7Rw1fYmH0dyjyyrNybom/V7XO4/ePycLl6+pfCRcdbtu35M1JcLv3f7einpNzRz8QZVV9dYP9+te4+7XEA3UNwiy4OHj9V94BT97Z3++uDTGE2Z950Sjp5W7uOCQJxfUCOymDcii3kjsnheMEeWQJ8Ls7d7aQ8DHlSaWqB/NsE8IovnEVmYryOy2Ftz0PCaLHUaRpaCwmJ1DZ+kiopKVTmd6jNshrIf5LpElurqGo2OXa6Nu45KkibO+Va37tyzvoa3yFIn695DTZ67Rl3DJ1kXhZWkR3kFyn6Q67J7v11AtqHyikr1HDxV6Vcz1X3gFCWeuehy/4TZqxt9K+eamhq3x6j7Pj1pGFlSM26ob+RMSVJFRaXe7z1Gj/IKVF5RqTY9RlrvbjQ6drl+PHbG7etFTlikBw8fS5K6DZgsSVq37aD2HDrp8TyeB7fIcvf+I7XqOlz/+GCwRkz5Wht3HdWNzOxG39O6uSOymDcii3kjsngekcXA5ZYqe9+t4NrYRN1bmhr4n81vI7J4H5HF84gszNcRWeytObAbWSRp7ZYD6jV4mkKHTNOytT9Iqr3w7T8+GKy+kTP0wadjFD4qznr33nXbDmrN5v3W59uNLHVycvP186k07wc2YvqC9fp2U+1j37pzT217jnS58G270GjrrZN98TD3ifoMm6G3PopUp37jNHnu7y+pmjB7tXoOnqrOYROsn5ckbd/3sz74NEZ9hs3Q52MXqKLBux3Xf3chqfZaLTEzVmhg9Dyvsed5aPLlQplZD7R1z0+Knr5crboO1xtdhmn4pCX/f3tvFhTVvffrc3mq9s25ek/V/+Lset+q89Y5xMS9szOZHcU4K87GEMdGHBBlUBGcZ3GI84BR1KgRNTgLGueJiDOIA0EUQWQGUZS5afrzv0CWtItea2E3dn/l81Q9VelevVb/un/SoR/WgN0HzyD1cRajCxhZJMrIIk9GFm0ZWQQamezyPUSaPDyHkUWUjCzaMrJQR2VkMSZRY661KBGlMVXVNaoAUPq6/hLOjQ8ZcgcOnbise/iPs3hVVtHk66+pMeNF6WvD26modM55apyB4RPfZj7LR0zsRUyeF4nPOvmhXe8JLTkuETCyyJORRZ6MLNoysgi0IbK4eu+VRqbtuYmsjBLXvzdvZGTRl5FFW0YW6qiMLMYkjhN7OgFhC39xm50YHmVkY9CYuaiqrnH1UMSiG1nq6qx48DATO34/ifHTVuPLnv7w9DIpxz21ZhhZ5MnIIk9GFm0ZWQT6JrLkJLvPv2t3u7qQq/fqsXuOmMIKl783DTKyaMvIQh2VkcWYxDnU1blHYAHqz7niLsFHKqrIYrVakfo4C7v2n8LEGWvxtXcAPL1M6OoTirkrfsXJCzeatdvOxwwjizwZWeTJyKItI4tAGVn0jbjh8qDS5CFVbjRnjCzaMrJQR2VkMSYhRI0qsqQ9yYanlwnf9p2IyfMisT/uIp7lFrpibG4PI4s8GVnkyciiLSOLQBlZ5OmGc8bIoi0jC3VURhZjEkLUqCLL67IKntjWIIws8mRkkScji7aMLAJ1wy/sjCzy5oyRRVtGFuqojCzGJISoMXziW6KGkUWejCzyZGTRlpFFoG74hZ2RRd6cuWNkabOzDZZfXe8W/rR/Af5r7lZGFvreMrIYkxCiRhVZDsRdwuuyCsMbsFjqsGv/KacOSgqMLPJkZJEnI4u2jCwCdcMv7Iws8ubMnSLLgeOnlMjibh5Pfuby9yf3OSOLRBlZjEkIUaOKLBHrotF7xHTcvpumu3Lms3yYQpbCFLK0RQbn7jCyyJORRZ6MLNoysgjUDb+wM7LImzO3iizHTuFv/+dv6L/yB5fvwdJgQ2Q5mXbF5e9P7nNGFokyshiTEKJGFVnq6qzYc/gcvvYOwNipKxB7OgHZeUUw11pQV2dFYfFLXLqajNAFm/BFj3FYvWU/Kqta5zW0GVnkycgiT0YWbRlZ9M3LfoXsuHS30R2/sDOy6OiGc+ZukcXDwwPf/ruDy8fS4LA4EyMLdUhGFmMSQtTYPSdL0fOXWLTmNwweNw//7DoGn3T0xWed/PBpp1Ho6zsT0yK24HFGzoccq9vByCJPRhZ5MrJoy8iir6sv+2vP3JzXLn9vGmRk0ZGRRVNGFn0ZWeTJyGJMQogaQye+tVjqkJGVh9THWTCba1t6TGJgZJEnI4s8GVm0ZWTRVwkbbrAXi7I3y/U8l78vjWVk0ZGRRVNGFn0ZWeTJyGJMQogaXl3IARhZ5MnIIk9GFm0ZWfRV9hxxg7G4q4wsOjKyaMrIoi8jizwZWYxJCFHDyOIAjCzyZGSRJyOLtg2Rpde0zfj23x1cbrfRvRhZBMrIoiMji6aMLPoyssiTkcWYhBA1jCwOwMgiT0YWeTKyaNsQWf7nd0Ph4eHhcv/2f//GyCJQRhYd30QWtzP1uevfm+eMLEZkZJEnI4sxCSFqGFkcgJFFnows8mRk0bbxniwHjp1yuXN3LGVkESgji7Y5hx67Pqg04bPYRy5/b3KfM7IY+jfEyCJORhZjEkLUMLI4ACOLPBlZ5MnIoi3PyaIvI4u+jCyyzI5LZ2TRkZGFOiojizEJIWoYWRyAkUWejCzyZGTRlpFFX0YWfRlZZMnIoi8jC3VURhZjtjZKX5fDYqlr9nrmWgvKK6qc/lhnUWux4HVZRYtsu6KyGpVVNS2ybXdFN7Jk5RTi4PHL2BFzUmVrh5FFnows8mRk0ZaRRV9GFn0ZWWTJyKIvIwt1VEYWY7YWrty8j+9/mIS+vjPx776BWLI+GrUWi7LcarWi0w+TMTr0Z5v1XpaWIXDmWnQfEoYOA4Lxbd+JOH3pFkpfl6PnsHC07TIaoQs2aT72XRJu3cennUbhq17j8V2/QIydugKpj7NsHmNvPO+SkZUH30lL0Wv4NPQeMR3f9QtEVHQcAGBN1AHs3H/K5vHtek9AVXUNrty8j46DQtCu9wS7XeBuSjp6j5gO7xHT8W3fiRg4eg7upWagXZ8JKHn52uaxgTPX4tLVZJv7dsScxKxl25TbVdU16D4kDDn5xZqvCQDGhK5A2y6jFT/p6Iuk+49gNtfC08tks+yP89d1t9dcNCPLnQeP8c+uY+A1MASeXib0Mc1EH9NMtO0yGl18Qp0+GGkwssiTkUWejCzaMrLoy8iiLyOLLBlZ9GVkoY7KyGLM1sDL0jJ84x2A23fTAADlFVXw8Z+P34+eVx5z58Fj+E1Zjg4DgvGytEy5f+ue41iyPhp1dVblcQ3hJCe/GL1HTDf02MYk3LqPiTPWAqjfS2TH7yfRefBkm+e1N57GVFRWw2tgCI6fu6bcl5GVh0VrfgOgHVkA4PAf8ViweleT2y6vqMJ3/QJtwsnB45dx/s9EzFgShQNxl2zG0WFAMMzmWptt1NSY0X1IGNIzcwAAUdFxWPlLTJPPp4XFUofeI6Yjr7AEZnMt/t03sNnbaC6akWXqwk2YtWwbrFYr2nzvi4rKagD1L3DGkqgWH5yzKa+oQumrcrvLn794pfyjMQIjizwZWeTJyKItI4u+jCz6MrLIkpFFX0YW6qiMLMZsDezafwqmkKU29x05+ScG+M1Wbi/fuBcxsRcxa9k2HDx+Wbk/YPpqnP8zscntvhtZtB7bmMaRpfHzr916UHc8jdlz+BwGjZlr93kciSx7Dp9D+OLNTS67dDUZ48JWKrdPXbyJ6RFNt4W4M1cROHMtSl+Vo8fQsPc6pOnoqStKu3CLyOIzfoGy+8x3/QKRlVMAAMgrLMGnnUah9LX9YOEqip6/RMdBIdiw/bByX3WNGZPnbcS3fSfCa2AIRgRF2BS9nPxi9B81C50HT8Y33gFYuHqXUhC1YGSRJyOLPBlZtGVk0ZeRRV9GFlkysujLyEIdlZHFmK2BuSt+xebfYm3uKyh6gbZdRivfGbv6hKK4pBQXE+5g7NQVyuP+OH9dObzoxLnrNt+f340sWo9tTFOR5VpiCvwmL1du2xtPY+at2IHInUftvu41UQfQa/g0jAldofhZJz9DkWX+yh2Iib3Y5LKG0NEQTEIXbMKFhKQmH2u1WjFozFz4TVmO6ENnlPu37jkO7zeHIjX2wcNMm/Utljp4j5iOzGf5ynN/2mkU+o+aBd9JS5vcU8gZaEaW4YGLlfI1atIyxJ29CgAoLimFp5cJT7LyWmRQ70tVdQ18xi9Aj6FhNpFl98EzGDZxsXLc3NSFmxCxLlpZHjR7nbLrUUVlFXoOC8fZ+Nu6z8fIIk9GFnkysmjLyKIvI4u+jCyyZGTRl5GFOiojizFbA9MitiD60Fmb+16XVaBtZz+Yay24m5KOIQELUVlVg9JX5fjaO8Dm6InMZ/lYE3UAfpOX4999A3E96S8A6sii9djGNBVZ7v31BD7jFwCA7ngamLEkCjt+rz+fSmHxS3QYEIwOA4LhH16/l8maqANYtnEvHjzMVPyyp7+hyDI9IgpHTv6p+Z7GnbmKmhozvv9hEmpqzHYfe/laMrwGhsBca7H7GHscO30FYQt/UW5brVY8zS5A6aty3L6bBq+BIcrhSM5EM7KELfwF81fuAFB/4pkuPqHYH3cRIXM2oNfwaU4fjCNYrVZMnheJbXtPYNaybdj469vIMjJ4CWKOXVBuX7udgo6DQgDU16zPOvkho1EwWrftIMIXNb17U2MYWeTJyCJPRhZtGVn0ZWTRl5FFlows+jKyUEdlZDFmayBy51FV1Dgbfxtd35yj9OdN++A1MAQ9h4Wj57BwtOs9AYf/iG9yW78fPa+c6LapyGLvsY1pKrLsPngGS9ZHN2s8UdFxGB64WLldV2fFo4xs/DhuPgDHDhf6ZdcxLN2wx+5ru5CQhKDZ63DparLdw4oayHyWb3NoFgAciLsE//BVKh9nvA0mDXuxaEWUaRFblB1JnIlmZEl9nIXL1+pPVmOx1GHGkih82dMfvpOW4uadVKcPxhE2/noY0yK2AIAqsnQfEob463eV20+zC/BJR19YLHXILyqBp5fJ5lws++MuYmTwEt3nZGSRJyOLPBlZtGVk0ZeRRV9GFlm6c2Q5cOyUW8jIQh2VkcWYrYHsvCK06z0BT7PrT51hrrVgwow12LK7/hCirj6hyC8qUR5/Nv62sjfI9n0nbPYi+XnTPix8EybejSxaj23Mu5El/vo9dPEJRVZOoe54GlNY/BJfewfY7C3jrMiSm1+Mb/tOREpapnLf7btpSLz3CED9SW07DAjGlPmRuuehaSqylL4qR3ZekcrGe8TEnk7ApLkbbNYrKHqBsvL6f7fVNWb0HjHdZozOQvcSzu9iteqfq+RD88f56xgSsFB5U9+NLO36TMCNpLdRqCGsvCqrwKOMbHh6mWxeV+zpBNVEjho1SqWHhweS796jgkxMuoOkO8kuHwdtzpwlcc40nLHnT/x92nHM2POny8eSfPcefr8SgzY722DwwR9dPpYGGyKLq8fREqY8fOyU7SQmJuJOsutfDzVm2p6byJ4Wj4d7brp8LMl372Hbtu3w8PBwK/9z+n+izc42+P1KjMvfnwZv377t8jFQ495JvofbiYkuH4e721po2HNleOBidPUJxfyVO1BTY8a91AwMCVho89iq6hp84x2AV2UVWLh6F77xDsAPY+fh+x8mwW/KcrwofY3XZRUYPG4e/tl1DOb8vB0A7D72XRJu3cfn3cai+5AwdPtpKsaErsD9hxkAoDued7mV/BAD/Gaj/6hZGB4YgZ7Dwg1dwvlGUip6DA1HhwHB2NfoKkuNuXwtGT2GhmPwuHnoMTQMA/xm21xqOnzRZnzZ0x/VGocKAU1HFj0a9mJ599LW126noH3/IAybuBidf5yCNVEHmrVdo2hGlplLt+K3A6dV9xcWv8Q/uo5p1pV4WpIfxs7DrGXbsCbqANZEHVD+kew9cg4A0GNoGOKvv/0QyHyWj086+qKuzoqCohfw9DLZTG5M7EXVGaSzsrJUenh4ICu/lAoyJfURHqZnuXwc1LgPUh7iUUaOy8fhri44eg9/n3YcC47ec/lYsvJLcTzlEtrsbIOhmwYgZ2OSW9gQWVz93rSIBc7ZTnLyXWRkF7v+9VBjHk2r/zd9JNX1Y3lju2+/cysbIsvxlEsuf2+y8kvxNO8lEhMTXT4OatzMnGLcSU52+Tjc3dZG0fOXqksN61FXZ0VxSalypV5nPdaZVFRWoeSlOug4g9JX5W51wRxzrQV5hSUt2jI0I8u0iC2qegXU797j6WVCYfHLFhtYczh2+gq27zuhOHjcPPhNWY5jp68AAEwhS22uY37l5n18/8MkAPXnZGnb2c/mJL5rog7oHhsG8HAhifJwIXnycCFt3fVwoaGbBihxw1109Xvjzibf5eFCknS3w4XcUR4uRB2VhwsZsyXIfJWJyDuRH9wTGSda5PWQ1keTkSXh1n2cvnQLI4IiMGNJFE5fuqV44tx1hC/ejH6+sz70WA3z7uFC0YfOwGf8AuWMxJPmblBODAQAwbPXY9nGvQCAsvJKdPtpKs7F61+jnJFFnows8mRk0dZdI8uQY8ORk1zgNuYWlbv8vXFnGVlkyciiLyMLdVRGFmO2BBefXUSbnW0+uBPPTWyR10NaH01GlsHj5uHzbmPR5ntftO3sh8+7jVX8tu9ETJkfiVvJDz/0WA3zbmSprjEjePZ6fOMdoByD1fj4tpz8YvQxzUTHQSH4sqc/5q/aCYulTvd5GFnkycgiT3eMLMeTc93GgZEJbhtZXD0WalxGFlkysujLyEIdlZHFmC0B92Qh0tE8XGhN1AEcPXXlQ42lxSl9XY7iEvvHDhYUvUBFZZXh7TGyyJORRZ7uFlkaooa7ychCHZGRRZaMLPoyslBHZWQxJtHHXGvRvIKN2VyLxHuPlAux1FosSE5JV64W9KEpKHphcyoNV9Hcc9+4E82+uhB5CyOLPBlZ5OmukWVgZILb+P/5Lce86NU4mXbF5S6/up6RRaCMLLJkZNGXkYU6KiOLMVsDCbfu49NOo/BlT3981y8Qa7cebNb6xSWlmqfa+HXfHzYXm+ljmonVW/brXtq4pSgrr8SwiYuddrLaMaEr0LbLaMVPOvoi6f4jmM218PQy2Sz74/x1APXnhp08byNC5ry9BHPc2avY8ftJp4yppdGNLFk5hTh4/DJ2xJxU2dphZJEnI4s83TWyHE92j39H86OXu+S4ZT0ZWWTJyCLLhsiSE3mn/r/dxNwC9zn3ESMLdVRGFmO2BhJu3cfEGWsB1O/l0dUnFDeSUg2vrxVZSl+VY/C4ecqpKh5lZCvPZYTqN5eRdjanLt7Az5H7nL5di6UOvUdMR15hCczmWvy7b6DqMaWvyjEmdAUAIHDWOuQVlsBqtWJk8JJmHXXiSjQjy50Hj/HPrmPgNTAEnl4m9DHNRB/TTLTtMhpdfEI/1BjdFkYWeTKyyJORRduGPUfa7GyDYXEmt3DopgG4siXO5e8NNS4jiywbIou7mRuZ7PL3pkFGFuqojCzGbA00jiwAELEuGr8dOI3L15Kxest+LFkfjYGj56CishoHj19GF59QdP5xinKV3uKSUnTxCUXogk1o3z8IK3+JQWVV/eWDfztwGlHRccq2B/jNxjfeAehjmon7D+3Hk8qqGuzcfwpdfUIRfejse72uVZtjEH3oDID6vVf8pixXTq1hsdSh849TDJ2ntDkcPXUFM5ZEAYDdyHL/YYZypd/5K3fg5p1UnL+SZHPOVXdHM7JMXbgJs5Ztg9VqRZvvfZXrdUdFxylvTmuGkUWejCzyZGTRtiGyLL+63uVjyX1eiZzkgvovXBv4ZUKSjCzyfBh9Hc9iH7l875XsuHTkRiYzsujIyCJPRhZjtgYaR5aq6hoMHjcPCbfu48S56+j84xScvnQLjzKyUV5RhV7DpyEnvxiFxS/R13cmXpS+RnFJKb7tOxH3/nqCV2UVCJi+GmfjbwMAZi/fjofpz5TnuphwB7OWbbM7lorKKmzbewI9h4VjTdQBPH/xymZ5yJwN8B4x3cY+pplNbutF6Wt09QlF2pNsTI+IwqETl22Why/ejMxn+U2MoVr1HN4jpmuOG6gPN94jpivbNJtr8WmnUeg/ahZ8Jy3F6Uu3lPt/HDcfufnF+ClgISoqq+E3ZTlKX5XjaXYBzsbfVq4a7K5oRhaf8QuU46K+6xeIrJwCAEBeYQk+7TTKacdpSYWRRZ6MLPJkZNGWkYU6Q0YWeSYl3UF2UZnLx5H7/O3PPSOLxnvEyCJORhZjtgYSbt3HN94B8PGfD6+BIVi9ZT8A4MS564hYt1t53IWEJMxevl25veKX33H01BXV4UKxpxOwZH00AOCngIUor3h7CIxWZLFarfi270QEzlpns44jXL31AB0HhSB80WbVsvXbDykxyBkcO31LZwZ+AAAgAElEQVQFYQt/UW5brVY8zS5A6aty3L6bBq+BIUjPzAEA3LyTivmrduLqrQe4nvQXfo7ch9THWfCbvBz7jp7H5HkbnTaulkAzsgwPXIyDx+uL1qhJyxB39iqA+l2ePL1MbnHWYVfCyCJPRhZ5MrJoy8hCnSEjizwZWbRlZKGOyshizNZAwq37GB36MwqKXtgcPvNuZIk7c1WJJwAQueMIog+dUUWWuLNXlcNhfMYvUI4WAfT3ZEl7ko3QBZswPHAxzv+ZqFyRqIGIdbvhH77KxoDpq+1uL/1pLr7xDsDSDXtUyzb+eljZu6QxVdU1qufwD1+FNVEH7D5Pw14sDRGlKaZFbFF6Q2PGT1uNoucv8eu+P3D4j3gA9ScHfve1uxOakSVs4S+Yv3IHAGBHzEl08QnF/riLCJmzAb2GT/sQ43NrGFnkycgiT0YWbRlZqDNkZJEnI4u2jCzUURlZjNkaePecLA28G1lelpZhgN9s1NSYUWuxYNjExcjOK7KJLHV1VkxduAl7Dp8DAMxats0mPOhFlgaycgow5+ftGOA3G5evJSv3Fxa/RHZekY05+cVNbqO6xozB4+bhXmoGBo2Zi/jrd22Wz1y6tcmdKqxWq+o5Gl6nPWJPJ2DS3A029xUUvUBZeaUylt4jpqsudX0vNUPpEQePX1bOPzNw9By7z+UOaEaW1MdZyqRZLHWYsSQKX/b0h++kpbh5x/gZlT9WGFnkycgiT0YWbRlZqDNkZJEnI4u2jCzUURlZjNkaMBpZAGDH7yfx47j58PGfj8gdRwDUHwXyRY9xGB64GD2GhsFvynJU15gBADv3n8L2fSeU9Y1Glgbyi0pw6Wqy/gObYMHqXdi2t/650zNz0HnwZJsT33bxCUWtxfFznzTsxZL6OMvm/mu3U9C+fxCGTVyMzj9OaXJPmElzN+BZbiGA+tc6JnQFwhdtVsbtruhewvld3Hm3nA8NI4s8GVnkyciiLSMLdYaMLPJkZNGWkYU6KiOLMYkac61FiSiNqaquUe3tUfq6/hLOjQ8ZcgcOnbisefiPszDXWpBXWIKq6hrD60i4jLNuZHmaXYCjp67g9KVbqrMXt3YYWeTJyCJPRhZtGVmoM2RkkScji7aMLNRRGVmMSRwn9nQCwhb+4jY7MzzKyMagMXObFT6ILXYjS/rTXHT1CYWnlwmfdPSFp5cJnl4mjJq0DK/KKj7kGN0WRhZ5MrLIk5FFW0YW6gwZWeTJyKItIwt1VEYWYxLnUFfnHoEFqD9yxV2Cj1SajCxpT7Lxbd+JGBe2Eon30lBRWY1XZRW4lpiC/qNmof+oWXhZWvahx+p2MLLIk5FFnows2jKyUGfIyCJPRhZtGVmoozKyGJMQoqbJyBI8ez38piyH2VyrWlZWXolew6fhl13HWnxw7g4jizwZWeTJyKItIwt1hows8mRk0ZaRhToqI4sxCSFqVJHFarWibWc/XLudYnel3QfPuP1lkz4EjCzyZGSRJyOLtows1BkyssiTkUXbhsiy/Op6nEy74nof/olLNy65/H2hxmVkMSYhRI0qsrwofQ1PLxNKX5fbXenmnVS07x/UogOTACOLPBlZ5MnIoi0jC3WGjCzyZGTRtiGyuJvnH990+XtDjcnIYkxCiBpVZEl/motPOvpqnuzmUUY22nzv26IDkwAjizwZWeTJyKItIwt1hows8mRk0Xbw9kP4f5v6upXu9FlN9WVkMSYhRI0qsqQ9qQ8oySnpdj1x7jo8vUwuGK57wcgiT0YWeTKyaMvIQp0hI4s8GVm0bfisdhf/e8Ukt/qspvoyshiTEKKmycjScLlmPVs7jCzyZGSRJyOLtkpk2b8Y2XHp7iEjizgZWeTJyKJt+y7e+J/fDcWiuBS30Gf/AkYWYTKyGJMQokYVWczmWmTnFRmytcPIIk9GFnkysmjbEFmWrphWHzfcRUYWUTKyyJORRdtv/90BHh4eOHDslMvHkvu8EssT1jGyCJORxZiEEDVNXsKZGIORRZ6MLPJkZNHWHfdkebTvNjKfFrn8vaHGZWSRJyOLtows1FEZWYxJCFHDyOIAjCzyZGSRJyOLtu52Tpbc55W49+AvZOY8d/k4qHEZWeTJyKItIwt1VEYWYxJC1DCyOAAjizwZWeTprpHlf/zvT+Hh4eFy/6P/f7jdL+6MLPJkZJEnI4u2jCzUURlZjEkIUcPI4gCMLPJkZJEnIwsjC215GVnkyciiLSMLdVRGFmMSQtQwsjgAI4s8GVnk6a6RhYcL2ZeRRZ6MLPJkZNGWkYU6KiOLMQkhahhZHICRRZ6MLPJkZNGWkYU6Q0YWeTKyaMvIQh2VkcWYhBA1jCwOwMgiT0YWeTKyaMvIQp0hI4s83TGyuKOMLPR9ZWQxJiFEDSOLAzCyyJORRZ6MLNoyslBnyMgiT3eKLLnFlS6PKfbMSXaP/38wssiTkcWYhBA1jCwOwMgiT0YWeTKyaMvIQp0hI4s83SqyuKORyYws1CEZWYxJCFHDyOIAjCzyZGSRJyOLtows1BkyssiTkUVHRhbqoIwsxiSEqGFkcQBGFnkyssiTkUVbRhbqDBlZ5MnIoiMjC3VQRhZjEkLUMLI4ACOLPBlZ5MnIoi0jC3WGjCzyZGTRkZGFOigjizEJIWoYWRyAkUWejCzyZGTRlpGFOkNGFnkysujIyEIdlJHFmIQQNYwsDsDIIk9GFnkysmjLyEKdISOLPBlZdGRkoQ7KyGJMQogaRhYHYGSRJyOLPBlZtGVkoc6QkUWejCw6voksoUOCMSV8lsvtt/IHt/usptoyshiTEKKGkcUBGFnkycgiT0YWbRlZqDNkZJEnI4uObyJLu//9D3h4eLjc/+j/H273WU21ZWQxJiFEDSOLAzCyyJORRZ6MLNoyslBnyMgiT0YWHd9EloORB12+Fwv3ZJEpI4sxCSFqPqrI8qqsAkXPX9pdXl5RhdJX5XaXP3/xClXVNYafj5FFnows8mRk0ZaRhTpDRhZ5MrLoyHOyUAdlZDEmIUTNRxFZysor0WfkDHzebSw6DAhGX9+ZOHHuurK8usaMyfM24tu+E+E1MAQjgiLwsrRMWZ6TX4z+o2ah8+DJ+MY7AAtX70JdnVX3eRlZ5MnIIk9GFm0ZWagzZGSRJyOLjows1EEZWYxJCFHzUUSW8ooq/HH+OiyWOgBA7OkEeA0MgbnWAgDYffAMhk1cjFpL/e2pCzchYl20sn7Q7HVY+UsMAKCisgo9h4XjbPxt3edlZJEnI4s8GVm0ZWShzpCRRZ6MLDoyslAHZWQxJiFEzUcRWd6lrLwSnl4mPEx/BgAYGbwEMccuKMuv3U5Bx0EhAACzuRafdfJDRlaesnzdtoMIX7RZ93kYWeTJyCJPRhZtGVmoM2RkkScji46MLNRBGVmMSQhR81FGllMXb+Ib7wDl/Crdh4Qh/vpdZfnT7AJ80tEXFksd8otK4OllsjkXy/64ixgZvET3eRhZ5MnIIk9GFm0ZWagzZGSRJyOLjows1EEZWYxJCFHz0UWW3PxitO8fhN+Pnlfua9dnAm4kpSq3G8LKq7IKPMrIhqeXCVbr23OwxJ5OwAC/2TbbHThwoEoPDw8kJt2hgrx9OxGJiYlO3GYSbWFv3779Zs5cP5bEpCQM2jsRbXa2cTvnnJzr8vfGds5cP47W4L2UVM5ZK5Vzpm3m6qvInhaPe6dvunwsiUlJmHNyrtt9VlMdE9/8nLl6HHZ1/e/ViUl3Wv7LHSEC+agiy8vSMvT1nYmfN+2zub/H0DDEX7+n3M58lo9POvqirs6KgqIX8PQyobrGrCyPib0IU8hSm22Ulpaq9PDwQHbhayrIlIeP8fBJthO3WUZb2Ad/peFRZp7Lx9Hg0LiRLg8qTZl44rrL35sG795PwZNnhS4fR4tb5A6+dsp27iTfRWZuiRu8HmrUxMQkZBWUuv7nwE3NibyD7GnxyE50j/9/LLuyFm12tsGyK2tdPhZqzKd5L5B0J9nl47Cv63+vzi583bJf7ggRykcTWYqev0Rf35lYE3VAtcwUstRmz5YrN+/j+x8mAag/J0vbzn540uicLGuiDiB8Mc/J8jHKw4Xk6W6HCw2LM6HNzjY4uXM/ciOTXW72tPh649Jd/t40yMOF5MnDheTJw4V05OFC1EF5uJAxCSFqPorIklfwHF18QhEVHQezuVax4WpD0YfOwGf8AuVqQ5PmbsCS9W+vLhQ8ez2WbdwLoP6kud1+mopz8Ym6z8vIIk9GFnm6a2Q5sWDb28DhBuaklbj8vWmQkUWejCzyZGTRkZGFOigjizEJIWo+ishy/koSPL1MKuet2AEAqK4xI3j2enzjHYD2/YMwbOJivCh9u3tbTn4x+phmouOgEHzZ0x/zV+1UAo0WjCzyZGSRp7tGlj/OnUROcoFbmFtY4fL3pbGMLPJkZJEnI4uOjCzUQRlZjEkIUfNRRBajlL4uR3FJqd3lBUUvUFFZZXh7jCzyZGSRp7tGlpNpV1w+FneVkUWejCzyZGTRkZGFOigjizEJIWpaVWRxNows8mRkkScjizwZWeTJyCJPRhYdGVmogzKyGJMQooaRxQEYWeTJyCJPRhZ5MrLIk5FFnowsOjKyUAdlZDEmIUQNI4sDMLLIk5FFnows8mRkkScjizwZWXRkZKEOyshiTEKIGkYWB2BkkScjizwZWeTJyCJPRhZ5MrLoyMhCHZSRxZiEEDWMLA7AyCJPRhZ5MrLIk5FFnows8mRk0fFNZMmNTEZ2XLrLXbZ/MSOLMBlZjEkIUcPI4gCMLPJkZJFlTnEF/j7tuFv5/zb1ZWTRkZFFnows8mRk0fFNZHEXl66YxsgiTEYWYxJC1DCyOAAjizwZWWR5PDnX5VGFkaX5MrLIk5FFnows2ubkvnb53ivck0W2jCzGJISoYWRxAEYWeTKyyLIhsvTbcNnlY2mQhwvpy8giT0YWeTKyyLLhnCzD4kxu5bG/zrv8vXFXGVmMSQhRw8jiAIws8mRkkSUji0wZWeTJyCJPRhZZRpw5iTY727idw+JMLn9v3FVGFmMSQtQwsjgAI4s8GVlkycgiU0YWeTKyyJORRZaLYh/g79NjMXhnNE6mXXG5y6+uZ2TRkZHFmIQQNYwsDsDIIk9GFlkyssiUkUWejCzyZGSR5aLYB/j7tONYFJfi8rHkPq/EybQrjCw6MrIYkxCihpHFARhZ5MnIIktGFpkyssiTkUWejCyyZGSRJyOLMQkhahhZHICRRZ6MLLJkZJEpI4s8GVnkycgiS0YWeTKyGJMQooaRxQEYWeTJyCJLRhaZMrLIk5FFnowssmRkkScjizEJIWoYWRyAkUWejCyybIgs/2vIUnh4eLiF/zn9PxlZdGRkkScjizwZWWTJyCJPRhZjEkLUMLI4ACOLPBlZZMnIIlNGFnkyssiTkUWWjCzyZGQxJiFEDSOLAzCyyJORRZY8XEimjCzyZGSRJyOLLBlZ5MnIYkxCiBpGFgdgZJEnI4ssGVlkysgiT0YWeTKyyJKRRZ6MLMYkhKhhZHEARhZ5MrLIkpFFpows8mRkkScjiywZWeTJyGJMQogaRhYHYGSRJyOLLBlZZMrIIk9GFnkyssiyIbIMjEzAorgUl7vk3HFGFh0ZWYxJCFHDyOIAjCzyZGSRJSOLTBlZ5MnIIk9GFlk2RBZ38b8WrGdk0ZGRxZiEEDWMLA7AyCJPRhZZMrLIlJFFnows8mRkkeWz2MdYMO0sFkZed/leLIviUjB4ZzQji96cMbIYkhCihpHFARhZ5MnIIsvGkSUnucAtZGTRl5FFnows8mRkkWV27GNkT4tHdly6y8eS+5znZDEiI4sxCSFqGFkcgJFFnowssmyILP2nnaz/5dQNHLppACOLjows8mRkkScjiywZWeTJyGJMQogaRhYHYGSRJyOLLBtHltzIZLeQkUVfRhZ5MrLIk5FFlo0jy4Fjp1zu3B1LGVl0ZGQxJiFEDSOLAzCyyJORRZY8J4tMGVnkycgiT0YWWTZElsnfjYKHh4fL/dv//Rsji46MLMYkhKhhZHEARhZ5MrLIkpFFpows8mRkkScjiywbR5Zv/93B5XYb3YuRRUdGFmMSQtQwsjgAI4s8GVlkycgiU0YWeTKyyJORRZY8J4s8GVmMSQhRw8jiAIws8mRkkSUji0wZWeTJyCJPRhZZMrLIk5HFmIQQNYwsDsDIIk9GFlkyssiUkUWejCzyZGSRJSOLPBlZjEkIUcPI4gCMLPJkZJElI4tMGVnkycgiT0YWWSqRxU08sWAbI4uOjCzGJISoYWRxAEYWeTKyyPJ4ci7+c/Yu/PeKSVh+db1byMiiLyOLPBlZ5MnIIsuc1GKXhxVGlubJyGJMQogaRhYHYGSRJyOLLI8nZ6PNzjZu6bNifrmxJyOLPBlZ5MnIIsuc4gokJia6fBwN8nAhfRlZjEkIUcPI4gCMLPJkZJFlwy+BPx0b5vI9WBobl3rR5e+NO8vIIk9GFnkyssiSkUWejCzGJISoYWRxAEYWeTKyyLJxZHH1WKhxGVnkycgiT0YWWTKyyJORxZiEEDWMLA7AyCJPRhZZMrLIlJFFnows8mRkkSUjizwZWYxJCFHDyNKI5y9eoaq6xvDjGVnkycgiS0YWmTKyyJORRZ6MLLJkZJEnI4sxCSFqGFkA5OQXo/+oWeg8eDK+8Q7AwtW7UFdn1V2PkUWejCyyZGSRKSOLPBlZ5MnIIktGFnkyshiTEKKGkQVA0Ox1WPlLDACgorIKPYeF42z8bd31GFnkyciibVZxBRbFpbiNS84dZ2QRKCOLPBlZ5MnIIktGFnkyshiTEKKm1UcWs7kWn3XyQ0ZWnnLfum0HEb5os+66jCzyZGTRdlFcCv4+7bjb+F8L1jOyCJSRRZ6MLPJkZJGlu0YWd9TV702DjCzGJISoafWRJb+oBJ5eJptzseyPu4iRwUt01/Xw8MDamxupIFdeXY1V19a6fBzu6rBDC/HfKya5lW12tkG39f3x55F0KsQLMQ9w+VCay8dBjXs+5j7iDz9y+ThoM+bs93uIP/LY5eOgxox/M2euHkeD++Ieujym2NPVvws1uObGBvz85wqXj8PdJYSoafWR5VFGNjy9TLBa356DJfZ0Agb4zbZ5XJcuXVR6eHi4/H9ElLYGu63vj43+5ymllFLqBDeMP+/yvVXf1dW/a9D3kxCiptVHloKiF/D0MqG6xqzcFxN7EaaQpbrrck8WeXJPFnmuTFiFP2JvuPyvftS43JNFntyTRZ7ck0WW7rYny59H0nE9Nh1nTj5yG4+euuby3zkayz1ZjEkIUdPqI4vZXIu2nf3wpNE5WdZEHUD4Yp6T5WOU52SRZ0rqI6RnFbh8HNS4PCeLPHlOFnnynCyydLdzslB9eU4WYxJC1LT6yAIAwbPXY9nGvQCAsvJKdPtpKs7FJ+qux8giT0YWeTKyyJORRZ6MLPJkZJElI4s8GVmMSQhRw8gCICe/GH1MM9FxUAi+7OmP+at2wmKp012PkUWejCzyZGSRJyOLPBlZ5MnIIktGFnkyshiTEKKGkaURBUUvUFFZZfjxjCzyZGSRJyOLPBlZ5MnIIk9GFlkyssiTkcWYhBA1jCwOwMgiT0YWeTKyyJORRZ6MLPJkZJElI4s8GVmMSQhRw8jiAIws8mRkkScjizwZWeTJyCJPRhZZMrLIk5HFmIQQNYwsDsDIIk9GFnkyssiTkUWejCzyZGSRJSOLPBlZjEkIUcPI4gCMLPJkZJEnI4s8GVnkycgiT0YWWTKyyJORxZiEEDWMLA7AyCJPRhZ5MrLIk5FFnows8mRkkSUjizwZWYxJCFHDyOIAjCzyZGSRJyOLPBlZ5MnIIk9GFlkyssiTkcWYhBA1jCwOwMgiT0YWeTKyyJORRZ6MLPJkZJElI4s8GVmMSQhRw8jiAIws8mRkkScjizwZWeTJyCJPRhZZMrLIk5HFmIQQNYwsDuDh4UEppZRSSimlrVJCiBr+ZDjAb7/9hl27drl6GKQZrF27FrGxsa4eBmkGCxYswOXLl109DNIMJk2ahPv377t6GKQZjBw5Ejk5Oa4eBmkG/fr1Q1lZmauHQQxiNpvRs2dPVw+DNIOCggIMHTrU1cMghAiEkcUBGFnkwcgiD0YWeTCyyIORRR6MLLJgZJEHIwsh5H1hZHEARhZ5MLLIg5FFHows8mBkkQcjiywYWeTByEIIeV8YWRyAkUUejCzyYGSRByOLPBhZ5MHIIgtGFnkwshBC3hdGFgdgZJEHI4s8GFnkwcgiD0YWeTCyyIKRRR6MLISQ94WRhRBCCCGEEEIIIcQJMLIQQgghhBBCCCGEOAFGFkIIIYQQQgghhBAnwMhCCCGEEEIIIYQQ4gQYWQA8f/EKVdU1TS6zWq0oKHoBi6XO8Pb01imvqELpq/L3GiupR2vOSl6+RnZeEczmWsPb45y1LEZ+jqxWK/IKS1BWXmlom+ZaCwqLX9pdzjlzDL05q6isRkHRC1itVsPb1JszrZ9rYoxaiwV1deo5qbVYkFfwvFmfiwDn7ENgrrU4dXt6n32cM8fRmrOSl69RU2Nu1va05ux9fg8lb7FarSguKcWrsgq7j6mrszb7/XX2dwdCyMdFq44sOfnF6D9qFjoPnoxvvAOwcPUum19OE27dx3f9AtFjaBi+9g7AkZN/6m5Ta53qGjMmz9uIb/tOhNfAEIwIisDLUl4ZoDlozdnD9Gf4/odJ+KrXeHTxCcXX3gGIPZ2gu03OWcui93NUUVmNmUu34sue/vAaGIJZy7bpbjMqOg5f9RqP7kPC0HnwZKSkZSrLOGeOozVnZnMtZiyJwj+7jkGv4dPQY2gY/nr0VHebWnOm91lMjFFTY8aP4+bjzOVbNvf/duA0/tV9LDoOCkG73hMQMmcDKiqrdbfHOWt58otK8Hm3saov2H/euAdPL5ONbbuM1tyW3mcf58w52Juza4kpGBEUgRFBEejrOxNBs9ehWie26M3Z+/weSt6SeC8N7fsHoV3vCWjXZwJGBi9B6uMs1eMi1u1GxLrdhrbZEt8dCCEfH606sgTNXoeVv8QAACoqq9BzWDjOxt8GUP9Xv+/6BSL++l0AwKOMbPyr+1g8f/HK7vb01tl98AyGTVyMWkv9X0CmLtyEiHXRLfb6Pka05izzWT6uJ/2lPPbIyT/xVa/xmn9p55y1LEZ+jkYERSBkzgblC1zDe22Ph+nP0K73BOQXlQAAYmIvov+oWcpyzplj6M1Z5M6jGDh6jvJFYEfMSfT1nan5Fzu9OdP6uSbGWL/9EL72DoCnl0kVWeKv30NufjEAoKy8EoPGzMXeI+c0t8c5a3nGhK5A2y6j4ellajKy9BgaDrO51kYt9D77OGeOozVnHQYEI+7MVeW23+TliD50VnN7WnP2Pr+HElsepj/DnQePAdTvfTR/1U5MnrdRWX4hIQleA0Pg6WUyHFmc/d2BEPJx0moji9lci886+SEjK0+5b922gwhftBkAcCMpFR0GBNusMzxwMQ7EXVJuL1y9Cz9H7lNu660zMngJYo5dUJZdu52CjoNCnPeiPnL05uxd4s5cRT/fWTb3cc4+LHrv77XbKWjbZbTmniY+/vNx4tx15fbGXw8jdMEm5XZVdQ0+6+SHrJwCAJwzR9Gbs2ETF2Pb3hPKMoulDp918kPms3zlvubMWXN/rok2g8bM1f3ivHzjXgTNXmdzH+fMNZRXVNV/YX+tjiw9h4XbXe9h+jMMHD1H+dwDtD/7OGfOo6k5q6uzol2fCTh18aZy3+K1v2HV5hjldnPnzMjvoaR5XEhIwjfeAar7l2/c2+QfY96dM2d8dyCEtA5abWTJLyqBp5fJ5njK/XEXMTJ4CQAg9nQCfPzn26wTtvAXbPz1sHI7ZM4GTI+IUm7rrdN9SJhStwHgaXYBPunoy2M2DaI3Zw3cTUnH/FU7MTJ4ifIXjAY4Zx8Wvfd3TdQB/DhuPuav3IHhgRGYPC9StStv+/5BiIm9qNyevXy78lekBrwGhuBGUioAzpmj6M3Z2KkrsPm3WJvlXXxCEX/9nnK7OXNm9OeaGEMvslitVvT1nYmte47b3M85cw1akeWrXuMxY0kUItbtxtn42zZ7Zd5LzcA33gFIz8xR7tP67OOcOQ97c/b70fP4V/exWLftIC4m3MEPY+cpe5ABzZ8zI7+HkuaxaM1vGBe2UnW/vcjy7pw547sDIaR10Gojy6OMbHh6mWx+aYk9nYABfrMBANGHzqp++Zi9fDuWrLd/2IHeOu36TFC+CAJvP6y1TsZF3qI3Zw1cTLiDaRFbMHD0HBw7fUVzm5yzlkXv/Q1fvBmDxszFyQs3kHgvDT9H7kO73hNQUPTC7jZD5mxQ/cLSfUgYzsUnAuCcOYrenMWdvYove/rj96PncSEhCeu3H8I/u47B1VsP7G5Ta86M/lwTY+hFltVb9qPH0DCUV1Rpbodz9mGw94U9/WkutuyOxe9Hz2NN1AF823ci1m8/pLktrc8+zpnzsDdnDx5mwmf8Asxd8Su+6OGP8MWbdU8wrDVn7/N7KLHP5WvJ+Ff3sU2ek8VeZHmXlvjuQAj5OGm1kaWg6AU8vUw2JyWLib0IU8hSAPWHmviMX2CzztSFmxC544jdbeqt02NomM1fezOf5eOTjr488ZxB9ObsXdKf5uLTTqM0D0XhnLUseu/v9IgorN160GZ5X9+ZmieKm/PzdptdsIH6Y+Fv3qn/RZVz5hhGPvtOXbyBkDkbEDJnA7bvO4FPO43C0+yCdzeloDVnzf25JtpoRZaYYxfQYUCwzeEK9uCcfRjsfWF/l3PxiWjfP0jzMVqffZwz59HUnJnNtfiq13g8ysgGUH+FoeGBizF/5Q7NbWnN2fv8Hkqa5sHDTLTrPUH5Y8y7GI0sLfHdgRDycdJqI4vZXIu2nf3wpNFxlWuiDiB8cf1xlTfvpKp+oRkSsBAHjzRleJIAABFESURBVF+2u029dUwhS/H70fPKsis37+P7HyY5/FpaC3pz1tTjPb1Myi89TcE5a1n03t/IHUcQtvAXm+V9Rs6wOWzhXSJ3HMGU+ZHK7YrKanzaaRSycgoBcM4cpbmffb8fPY9uP03VPBxLa86a+3NNtLEXWXYfPIPOP07RjGGN4Zx9GIxGluSUdPyr+1jNE7lrffZxzpxHU3OWnJKOf3QdY3Np5yMn/9Q8rw6gPWfv83soUZN4Lw3f9QvE+StJdh9jNLK0xHcHQsjHSauNLAAQPHs9lm3cC6D+igvdfpqqVO5aiwXt+wcpH8p/PXqKz7uNRcnL18r6a6IOYNOuo8ptvXWiD52Bz/gFyv+EJ83dwF0Im4nWnMVfv6tcocZqtWLrnuNo3z/I5ooMnLMPi977+ygjG1/08FeOd76WmIK2nf1svggGTF9t88tR2pNsfNVrPPIKngMA9hw+Z7PLO+fMMYx89jW8t+mZOeg+JAyH/4i32UZz50zr55o0j6YiS+SOI/AeMR3PcgvtXqmGc+Ya7EWWM5dvIefN+TwaLvMbOOvtyYrTn+Zi7NQVymMA/c8+zplzaGrOSl6+xj+6jsGhE/VfpuvqrAievd7m5NHNnTMjn8VEmz9v3MN3/QJx5eZ9m8++d/dstRdZmpozR787EEJaB606suTkF6OPaSY6DgrBlz39MX/VTpu/xl65eR/tek9At5+m4ose41RfJMZOXYHg2ett7tNap7rGjODZ6/GNdwDa9w/CsImL8aKUH7zNQWvOGi7Z/FWv8WjXZwK6+oTiVvJDm/U5Zx8evZ+j6ENn8FWv8eg+JAxf9RpvcwlMAGjbZTSiD52xuW/L7lj8q/tYdPEJRcdBIXjwMFNZxjlzHL05+6rXeHQYEIyOg0KaPLSruXOm91lM9FmyPhrt+wfh006j8PWbf/vFJaUAgIGj58DTy6Sy6PlLZX3O2Yfnx3Hz8V2/QHh6mfDvvoEYOmGRsmz99kP4rJMf2vcPwhc9xmF4YITNuaqSU9Lh6WVC2pO3e2rqffZxzhxHa87Oxt/G0AmLMHD0HPQeMR0zlkQpP4PA+82Z3mcx0WbZxr1NfvYdP3cNAHDywg207x+Ez7uNxefdxqJ9/yCbSN3UnDn63YEQ0jpo1ZGlgYKiF6iobPokgHV1VuTkF9vsAqqH3jqlr8tt/sdLmo+9OaursyK/qAR5hSWau1U3tR7nrOXQe3+ra8zIyilErcX4z1l1jRm5+cV255lz5hhac5ZX8Py9/jKnN2dan8XENXDOXEf952KB5nnFmkLvs49z1rIUl5SiptE5O4ygNWfv83soaXmc/d2BEPJxwchCCCGEEEIIIYQQ4gQYWQghhBBCCCGEEEKcACMLIYQQQgghhBBCiBNgZCGEEEIIIYQQQghxAowshBBCCCGEEEIIIU6AkUUDe2cFN9dakFfwvFlXQmlMVXWN5tUazLUWFBa/bHJZraX+uc3mWrvbf/7iFaqqa95rbIQQQgghhBBCCHk/3DqynL50C55eJvyy65jN/fvjLsLTy4Rd+0+12HOfuXwL/Xxnqe7/7cBp/Kv7WHiPmI5v+05E3Jmrzdpu6IJNaNvZD9//MAkdB4VgTdQBm+VR0XH4qtd4dB8Shs6DJyMlLVP13B0HhaBd7wkImbMBFZXVyvKc/GL0HzULnQdPxjfeAVi4ehfq6oxfxpgQQgghhBBCCCHvj9tHli4+oegwIFjZM8NqtaLPyBno9tPUFoksxSWl6DE0DJ909FVFllvJD9G2y2ikP80FANz76wm+6OGPnPxiw9uPO3sV5RVVAICsnAL8o+sYpGfmAAAepj9Du94TkF9UAgCIib2I/qPejiH++j3kvnmusvJKDBozF3uPnFOWB81eh5W/xAAAKiqr0HNYOM7G327uW0AIIYQQQgghhJD3wO0jy4igCEyZH4k9h+tjwsWEOwicuRbjwlYqkeVuSjr6mGbiy57+aN8/CNMitih7eMxftROH/4i32e7keRtx7XaK5nNfSEiyCRwAsHbrQfiHr7S5z3fSUsTEXnzv1zhozFzsPngGALDx18MIXbBJWVZVXYPPOvkhK6egyXWXb9yLoNnrAABmcy0+6+SHjKw8Zfm6bQcRvmjze4+NEEIIIYQQQgghxhERWe4/zEBXn1DUWiwwhSxF4r1HNpHlaXYBEm7dx4vS18jNL4bvpKXYtOsoAODY6Ss2e6SkPs7Ct30noqbGrPncTUWWqOg4+E1ZbnPfzKVbsWpzzHu9vuKSUnzS0Rd3U9IBALOXb1f2RGnAa2AIbiSlqta1Wq3o6zsTW/ccBwDkF5XA08tkcy6W/XEXMTJ4yXuNjRBCCCGEEEIIIc1DRGQBgJHBS7Bs414MCVgIADaRBQAqq2pw9dYDxBy7gPHTVmPK/EgAQHWNGd94ByD5TchYuHqXKmQ0RVORJSMrD1/08MfqLftx6Woyog+dQefBk7F268FmvzazuVbZS6eBkDkbsPHXwzaP6z4kDOfiE1Xrr96yHz2GhimHHj3KyIanl8nmZLqxpxMwwG92s8dGCCGEEEIIIYSQ5iMmsly6mgxPL5NyjpHGkeXa7RS06z0BE2esxeot+xE4cy0mzd2gbGfJ+mjMWrYNFZXV+No7ANl5RbrP3VRkAYAHDzMxY0kUJsxYg8gdR9BzWDj2x11s1uuqq7MifNFmjAiKsNnzZM7P21V7xXQYEIybd2z3ZIk5dgEdBgTbHEZUUPQCnl4mVDfaQycm9iJMIUubNTZCCCGEEEIIIYS8H2Iii9Vqxba9J5Sr5TSOLCODlyD60BllvehDZ20iS3pmDv7VfSx27j8F//BVhp7bXmRpzJOsPLT53tfuOVOawlxrQeiCTfCbvNzmykAAELnjiM2eLRWV1fi00yhk5RQq9+0+eAadf5yCp9m2z2k216JtZz88aXROljVRBxC+mOdkIYQQQgghhBBCPgRiIsu7NI4s/uGrlHOwvCh9jYDpq20iCwAMD4xA285+uHQ12dBz24ss5loLAKD0VTn8w1dhekSUzfJ12w7aPXyo1mKB35TlCJq9DuUVVTCba+t9s820J9n4qtd45BU8BwDsOXzO5nCfyB1H4D1iOp7lFr5d11yrLA+evR7LNu4FUH/1oW4/TW3yUCNCCCGEEEIIIYQ4n48isty8k4rvf5iEdr0noMOAYPiHr1RFlpjYi+jqE6rsCWOP/KIStO8fhK+9A/Bpp1Fo3z8IP2/aZ/O8Dc+1bONe1FosyrK6Oiu+8Q7A8XPXmtx2WXklPL1MKnsOC1ces2V3LP7VfSy6+ISi46AQPHiYqSwbOHpOk+sXPX8JAMjJL0Yf00x0HBSCL3v6Y/6qnbBY6jRfLyGEEEIIIYQQQpyDW0eW5lBXZ0VWTqFN9GjM1IWblCvxOELDFYya4sHDTHQYEKzsmfK+VNeYkZtfbHMS2+ZQUPQCFZVVDo2BEEIIIYQQQgghzeOjiSxa5BWW4Ise4/Ci9HWLPs+2vSdUVwcihBBCCCGEEEJI66BVRJbHGTkf5NwkhcUvUVlVo/9AQgghhBBCCCGEfHS0ishCCCGEEEIIIYQQ0tIwshBCCCGEEEIIIYQ4AUYWQgghhBBCCCGEECfAyEIIIYQQQgghhBDiBBhZCCGEEEIIIYQQQpwAIwshhBBCCCGEEEKIE2BkIYQQQgghhBBCCHECjCyEEEIIIYQQQgghToCRhRBCCCGEEEIIIcQJMLIQQgghhBBCCCGEOAFGFkIIIYQQQgghhBAnwMhCCCGEEEIIIYQQ4gQYWQghhBBCCCGEEEKcACMLIYQQQgghhBBCiBNgZCGEEELs8Cy3EGlPsu36JCsPFksdbt5JRdHzly4bp8VSh4h1u3Eg7hIAwGq1Iu1JNsrKK1WPLSx+iaycQgDQfG1pT7KRX1Ris25NjRmpj7Nw+tIt3Ep+iFdlFcqy9MwcTIvYgrQn2S34SgkhhBBC3BtGFkIIIcQOo0N/Rtsuo+vt7AdPLxM+6+Sn3NdzWDjKK6rg6WXC/riLLhvnr/v+QF/fmUpUqa4xw9PLhLPxt1WPjVi3Gz8FLASAt6+ty2h82mkUPL1MNvfN+Xk7gPpos+/oeXztHYDv+gXih7Hz8LV3ANp2GY2pCzcp214TdQA/jJ0Hi6XuA7xqQgghhBD3g5GFEEIIMUB+UQk8vUy4fTdNtcxsrkVdndUFowKycgrwZU9/pD7OUu4zGlkaE3s6AZ909G3yOXbuP4V/dR+Lkxdu2Nx/58FjjAxeotyutVgweNw8bNt74n1fDiGEEEKIaBhZCCGEEANoRZbhgRG4lfxQuT10wiKcOHcdU+ZHol3vCRjgNxvXElPwOCMH48JWol3vCZg8byNS0jJttnMr+SGGTliEL3r4o/uQMGzdc1w33sxcuhWT5m6wuc+ZkeVlaRk+7zYWm3+L1RxHA+fiE/HPrmNgrrUYejwhhBBCyMcEIwshhBBiAK3I0rbLaJyLT1Rut/neF1/29MfGXw/jQkISJs/biC96+KPDgGBs2R2LCwlJ8A9fiRFBEco6dx48xj+7jsGG7YfxMP0Zfj96Hu36TNA9DGmA32ycuXzL5j5nRpZriSnw9DLhWW6h5jgaMJtr8bV3AB5l8NwshBBCCGl9MLIQQgghBmhuZDl96W34yMopUK17768n+KyTH8orqgAAfpOXY9aybTbbXbh6F4YHRsAetRYL2nb2Q17Bc5v7nRlZfj96Hp92GtWs86wMD4zA8XPXDD+eEEIIIeRjgZGFEEIIMUBzI8vFhDvK7VdlFfD0MiHp/iPlvme5hfD0MuFJVh4AoF3vCeg9YjpGBEUo9hwWjk4/TLY7pscZOWjzvS9qLbaH5jRElnf3cAGaH1liTyfA08ukxCAjhC/ajNVb9ht+PCGEEELIxwIjCyGEEGIARyJLWXmlKrLk5BcrkcVqteKfXcdg/fZDuJGUamPjdd4l7Um23b1MvugxDkdPXVHdP3PpVkyYsUZ1v73Icv9hBjy9TEhOSbc7jncJX7wZqzbHGH48IYQQQsjHAiMLIYQQYoCWjCxA/blVlm/c26wxmWst+KyTHwqKXqiW9fOd1eT2Bo6eg4h10ar77UWWmhozOv84BRNnrG1yDE2dq2Vk8BLEnblq5CUQQgghhHxUMLIQQgghBmjpyHLs9BW07eyHo6euoKq6Bq/LKnD5WjJ+3rRPc1z9fGfhQkKS6v6YYxfwebex+OP8dVRV16D0VTnWbTuITzuNQvrTXNXjtS7hfCEhCZ5eJkxduAmPM3JQWVWD1MdZ2LTrKL7o4W/zWHOtBe36TEDaE574lhBCCCGtD0YWQgghxAAtHVkAYM/hc2jXZwI+6egLTy8Tvuo1Hht/Paw5rmkRWxC6YJPq/ro6K9ZuPYi2nf2U7bXvH4STF240uR2tyAIAN++kYuDoOcq2PL1M6DE0HFv3HLd53MWEO/gHL+FMCCGEkFYKIwshhBDiZhQ9f4m8whLU1Vl1H/s4Iwdf9BiHjEaxpjHmWgsysvKQV/Dc0Pb0qK4xIyMrD89fvFIts1qtGB64GOu3H3L4eQghhBBCJMLIQgghhAhn9Zb9MIUsVV1l6EMTc+wCegwNQ3WN2aXjIIQQQghxFYwshBBCiHCqqmswMngJdu0/5bIxpGfmYPC4ebh2O8VlYyCEEEIIcTWMLIQQQgghhBBCCCFOgJGFEEIIIYQQQgghxAkwshBCCCGEEEIIIYQ4AUYWQgghhBBCCCGEECfAyEIIIYQQQgghhBDiBBhZCCGEEEIIIYQQQpwAIwshhBBCCCGEEEKIE2BkIYQQQgghhBBCCHECjCyEEEIIIYQQQgghToCRhRBCCCGEEEIIIcQJMLIQQgghhBBCCCGEOAFGFkIIIYQQQgghhBAnwMhCCCGEEEIIIYQQ4gT+f2MSfNzlyj2QAAAAAElFTkSuQmCC"
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fig = plotly_figures.timeseries(\n",
" timeseries_value_df, timeseries_meta_df,\n",
" start, end, units, (None, 'y'), timezone='UTC')\n",
"fig.show()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 35,
"metadata": {},
"outputs": [],
"source": [
"plotly_figures = reload(plotly_figures)"
]
},
{
"cell_type": "code",
"execution_count": 36,
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.plotly.v1+json": {
"config": {
"plotlyServerURL": "https://plot.ly"
},
"data": [
{
"connectgaps": false,
"legendgroup": "OASIS DA GHI X Prob(x <= 0 W/m^2)",
"line": {
"shape": "hv"
},
"marker": {
"color": "#e377c2"
},
"name": "OASIS DA GHI X<br>Prob(x <= 0 W/m^2)",
"type": "scattergl",
"x": [
"2020-05-19T00:00:00-07:00",
"2020-05-19T01:00:00-07:00",
"2020-05-19T02:00:00-07:00",
"2020-05-19T03:00:00-07:00",
"2020-05-19T04:00:00-07:00",
"2020-05-19T05:00:00-07:00",
"2020-05-19T06:00:00-07:00",
"2020-05-19T07:00:00-07:00",
"2020-05-19T08:00:00-07:00",
"2020-05-19T09:00:00-07:00",
"2020-05-19T10:00:00-07:00",
"2020-05-19T11:00:00-07:00",
"2020-05-19T12:00:00-07:00",
"2020-05-19T13:00:00-07:00",
"2020-05-19T14:00:00-07:00",
"2020-05-19T15:00:00-07:00",
"2020-05-19T16:00:00-07:00",
"2020-05-19T17:00:00-07:00",
"2020-05-19T18:00:00-07:00",
"2020-05-19T19:00:00-07:00",
"2020-05-19T20:00:00-07:00",
"2020-05-19T21:00:00-07:00",
"2020-05-19T22:00:00-07:00",
"2020-05-19T23:00:00-07:00"
],
"y": [
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0
]
},
{
"connectgaps": false,
"legendgroup": "OASIS DA GHI X Prob(x <= 500 W/m^2)",
"line": {
"shape": "hv"
},
"marker": {
"color": "#9467bd"
},
"name": "OASIS DA GHI X<br>Prob(x <= 500 W/m^2)",
"type": "scattergl",
"x": [
"2020-05-19T00:00:00-07:00",
"2020-05-19T01:00:00-07:00",
"2020-05-19T02:00:00-07:00",
"2020-05-19T03:00:00-07:00",
"2020-05-19T04:00:00-07:00",
"2020-05-19T05:00:00-07:00",
"2020-05-19T06:00:00-07:00",
"2020-05-19T07:00:00-07:00",
"2020-05-19T08:00:00-07:00",
"2020-05-19T09:00:00-07:00",
"2020-05-19T10:00:00-07:00",
"2020-05-19T11:00:00-07:00",
"2020-05-19T12:00:00-07:00",
"2020-05-19T13:00:00-07:00",
"2020-05-19T14:00:00-07:00",
"2020-05-19T15:00:00-07:00",
"2020-05-19T16:00:00-07:00",
"2020-05-19T17:00:00-07:00",
"2020-05-19T18:00:00-07:00",
"2020-05-19T19:00:00-07:00",
"2020-05-19T20:00:00-07:00",
"2020-05-19T21:00:00-07:00",
"2020-05-19T22:00:00-07:00",
"2020-05-19T23:00:00-07:00"
],
"y": [
0,
0,
0,
0,
0,
0.5,
0.5,
0.5,
0.5,
0.5,
0.5,
0.5,
0.5,
0.5,
0.5,
0.5,
0.5,
0.5,
0.5,
0.5,
0,
0,
0,
0
]
},
{
"connectgaps": false,
"legendgroup": "OASIS DA GHI X Prob(x <= 1000 W/m^2)",
"line": {
"shape": "hv"
},
"marker": {
"color": "#1f77b4"
},
"name": "OASIS DA GHI X<br>Prob(x <= 1000<br>W/m^2)",
"type": "scattergl",
"x": [
"2020-05-19T00:00:00-07:00",
"2020-05-19T01:00:00-07:00",
"2020-05-19T02:00:00-07:00",
"2020-05-19T03:00:00-07:00",
"2020-05-19T04:00:00-07:00",
"2020-05-19T05:00:00-07:00",
"2020-05-19T06:00:00-07:00",
"2020-05-19T07:00:00-07:00",
"2020-05-19T08:00:00-07:00",
"2020-05-19T09:00:00-07:00",
"2020-05-19T10:00:00-07:00",
"2020-05-19T11:00:00-07:00",
"2020-05-19T12:00:00-07:00",
"2020-05-19T13:00:00-07:00",
"2020-05-19T14:00:00-07:00",
"2020-05-19T15:00:00-07:00",
"2020-05-19T16:00:00-07:00",
"2020-05-19T17:00:00-07:00",
"2020-05-19T18:00:00-07:00",
"2020-05-19T19:00:00-07:00",
"2020-05-19T20:00:00-07:00",
"2020-05-19T21:00:00-07:00",
"2020-05-19T22:00:00-07:00",
"2020-05-19T23:00:00-07:00"
],
"y": [
0,
0,
0,
0,
0,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0
]
},
{
"connectgaps": false,
"legendgroup": "OASIS DA GHI CV X=750 Prob(x <= 750 W/m^2)",
"line": {
"shape": "hv"
},
"marker": {
"color": "#2ca02c"
},
"name": "OASIS DA GHI CV<br>X=750 Prob(x <= 750<br>W/m^2)",
"type": "scattergl",
"x": [
"2020-05-19T00:00:00-07:00",
"2020-05-19T01:00:00-07:00",
"2020-05-19T02:00:00-07:00",
"2020-05-19T03:00:00-07:00",
"2020-05-19T04:00:00-07:00",
"2020-05-19T05:00:00-07:00",
"2020-05-19T06:00:00-07:00",
"2020-05-19T07:00:00-07:00",
"2020-05-19T08:00:00-07:00",
"2020-05-19T09:00:00-07:00",
"2020-05-19T10:00:00-07:00",
"2020-05-19T11:00:00-07:00",
"2020-05-19T12:00:00-07:00",
"2020-05-19T13:00:00-07:00",
"2020-05-19T14:00:00-07:00",
"2020-05-19T15:00:00-07:00",
"2020-05-19T16:00:00-07:00",
"2020-05-19T17:00:00-07:00",
"2020-05-19T18:00:00-07:00",
"2020-05-19T19:00:00-07:00",
"2020-05-19T20:00:00-07:00",
"2020-05-19T21:00:00-07:00",
"2020-05-19T22:00:00-07:00",
"2020-05-19T23:00:00-07:00"
],
"y": [
0,
0,
0,
0,
0,
0.28443710094801433,
0.23203549864325002,
0.41825891768879464,
0.8431353103798868,
0.7983916280891831,
0.3735100390979208,
0.16206201967957443,
0.05421237510341976,
0.8738475786293948,
0.135873427270528,
0.48129863223760727,
0.6128366270499029,
0.803434019825023,
0.7463136235997936,
0.14665184830408168,
0,
0,
0,
0
]
}
],
"layout": {
"autosize": true,
"bargap": 0,
"bargroupgap": 0,
"barmode": "group",
"coloraxis": {
"colorbar": {
"ticks": "outside",
"x": 1.2,
"y": 1,
"yanchor": "top"
}
},
"legend": {
"font": {
"size": 10
}
},
"template": {
"data": {
"bar": [
{
"error_x": {
"color": "#2a3f5f"
},
"error_y": {
"color": "#2a3f5f"
},
"marker": {
"line": {
"color": "#E5ECF6",
"width": 0.5
}
},
"type": "bar"
}
],
"barpolar": [
{
"marker": {
"line": {
"color": "#E5ECF6",
"width": 0.5
}
},
"type": "barpolar"
}
],
"carpet": [
{
"aaxis": {
"endlinecolor": "#2a3f5f",
"gridcolor": "white",
"linecolor": "white",
"minorgridcolor": "white",
"startlinecolor": "#2a3f5f"
},
"baxis": {
"endlinecolor": "#2a3f5f",
"gridcolor": "white",
"linecolor": "white",
"minorgridcolor": "white",
"startlinecolor": "#2a3f5f"
},
"type": "carpet"
}
],
"choropleth": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"type": "choropleth"
}
],
"contour": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"colorscale": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"type": "contour"
}
],
"contourcarpet": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"type": "contourcarpet"
}
],
"heatmap": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"colorscale": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"type": "heatmap"
}
],
"heatmapgl": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"colorscale": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"type": "heatmapgl"
}
],
"histogram": [
{
"marker": {
"colorbar": {
"outline
Raw
test_xy_prob.html
View raw

(Sorry about that, but we can’t show files that are this big right now.)

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment