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noah 5b8f4d2de6 Efficiency
2023-04-18 17:23:32 -05:00

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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"# Group 7 - Noah L. Schrick"
]
},
{
"cell_type": "code",
"execution_count": 68,
"metadata": {},
"outputs": [],
"source": [
"# Imports\n",
"import pandas as pd\n",
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"import seaborn as sns\n",
"from sklearn.model_selection import train_test_split\n",
"from sklearn.linear_model import LinearRegression\n",
"from dmba import regressionSummary\n",
"from sklearn.ensemble import RandomForestRegressor\n",
"from sklearn.datasets import make_regression\n",
"from sklearn.datasets import make_hastie_10_2\n",
"from sklearn.ensemble import GradientBoostingRegressor\n",
"from sklearn.metrics import mean_squared_error\n",
"from sklearn.preprocessing import PolynomialFeatures\n",
"from sklearn.preprocessing import StandardScaler\n",
"from sklearn.svm import SVR\n",
"from sklearn.model_selection import GridSearchCV\n",
"from sklearn.metrics import classification_report,confusion_matrix\n",
"from sklearn import preprocessing\n"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"# Import data\n",
"timing_df = pd.read_csv('timing.csv')"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"# Exploratory Analysis"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"## Parallel Coordinates Plot"
]
},
{
"cell_type": "code",
"execution_count": 58,
"metadata": {},
"outputs": [
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"\n",
"\n",
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"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
"\n",
"/tmp/ipykernel_1934/509936392.py:4: SettingWithCopyWarning:\n",
"\n",
"\n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
"\n",
"/tmp/ipykernel_1934/509936392.py:5: SettingWithCopyWarning:\n",
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"\n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
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"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
"\n",
"/tmp/ipykernel_1934/509936392.py:6: SettingWithCopyWarning:\n",
"\n",
"\n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
"\n",
"/tmp/ipykernel_1934/509936392.py:7: SettingWithCopyWarning:\n",
"\n",
"\n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
"\n"
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},
"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
},
"autotypenumbers": "strict",
"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
}
}
}
}
}
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"import plotly.express as px\n",
"overall_df = timing_df[['nodes', 'exploit', 'appl', 'load', 'runtime']]\n",
"overall_df['load'] = overall_df['load'].replace(395,0)\n",
"overall_df['load'] = overall_df['load'].replace(296,25)\n",
"overall_df['load'] = overall_df['load'].replace(197,50)\n",
"overall_df['load'] = overall_df['load'].replace(79,75)\n",
"overall_df['load'] = overall_df['load'].replace(1,100)\n",
"\n",
"# , [296,25], [197,50], [79,75], [1,100]\n",
"fig = px.parallel_coordinates(overall_df, color=\"runtime\", labels={\"runtime\": \"runtime\",\n",
" \"nodes\": \"nodes\", \"exploit\": \"exploit\",\n",
" \"appl\": \"appl\", \"load\": \"load\", },\n",
" color_continuous_scale=px.colors.diverging.Tealrose,\n",
" color_continuous_midpoint=2)\n",
"fig.show()"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"## VIF"
]
},
{
"cell_type": "code",
"execution_count": 59,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" feature VIF\n",
"0 nodes 4.016407\n",
"1 exploit 1.104364\n",
"2 appl 2.452438\n",
"3 load 5.360648\n"
]
}
],
"source": [
"from statsmodels.stats.outliers_influence import variance_inflation_factor\n",
"predictors = ['nodes', 'exploit', 'appl', 'load']\n",
"X = timing_df[predictors]\n",
"\n",
"# VIF dataframe\n",
"vif_data = pd.DataFrame()\n",
"vif_data[\"feature\"] = X.columns\n",
" \n",
"# calculating VIF for each feature\n",
"vif_data[\"VIF\"] = [variance_inflation_factor(X.values, i)\n",
" for i in range(len(X.columns))]\n",
" \n",
"print(vif_data)\n"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"## Plot raw features with outcome"
]
},
{
"cell_type": "code",
"execution_count": 67,
"metadata": {},
"outputs": [
{
"data": {
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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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HQ4Pg9UvYUa7u1T4yJio0YvZf4GofCvD6JfzxaB0AjqbogTyasmiSunbZpYH76mIbOpxepMRYcFdBstLh3BITFRox+6sCw/xqnvuk0fHZmSa0ONxIi7NiyVRegWtZYNpHLsBU95U43Zy8tHxFcSbCVTztAzBRoRHSbHfhfFMXTKZAvwwytg3BTrRPzs1V9Vw43Z68y25khBmLC9XXbp1uz+OT8GlFIwD1T/sATFRohBy4GFjtU5SdgCQ2gjK0y63d2F/VCpMJeGp+rtLh0BDJoymLCzMQY1XVLiw0QF9eaIHd5UNanBXzxqp72gdgokIjhPUpJHsv2ODt/klpyEliUbWW9d1ll03etEtONlcWZyFMA/2tmKjQsBNCsH8KAQDcPj8+CBbRrinJVzgaGqq+u+w+wGkfTXJ5/dh1pgmAdpJNJio07C62dKPR7oIl3Iy5Y5OUDocU9GlFE9q7PciMj8QDk9OUDoeGSF7ts0Slu+zS7e0934Iutw9ZCZGYnaeN92cmKjTs5NGUeWOT+GZmcBsPXwEAPDkvV/UrC+jWtLDLLt1e32kfrWxrwncOGnby/j6sTzG2quYuHLrUDjOLaHXh6JWO0C6796l0l126tR6PH7vPBqd9NLS0nIkKDSufX8Khi4FCWtanGNt7wX19HizMQFZClMLR0FDJ0z5q3mWXbu3zc81wevzITY7CjJwEpcMZMCYqNKxO19vgcPuQEBWBadnaeSHQ8HJ5/fjzcbmIlp1otc4vCWwrC/bd4N4+miUnmyuLs2EyaWPaB2CiQsPswIXAtM/C8SmaWPZGI2N7eQM6nV6MSYzCfZNYRKt1gV123arfZZdursvtw+fnmgFoZ7WPjIkKDSvWpxAAbDgUmPZ5en4uE1Yd0Mouu3Rzu882we2TMDYlGtOy45UO547wN46GjdPjw/GaDgCsTzGy800OHL3SgXCzCd+cyyJardPSLrt0c5tP9Z5DLU37AExUaBgdqW6H1y8wJjEK+SnsQGpUG4P7+iyZkoH0+EiFo6Gh0tIuu3RjdpcX+84HNonVYo0RExUaNn270WotY6fh0ePpLaJdzSJaXZB32V1epP5ddunGdlU0weOXMCE9FpMz4pQO547xt46Gzf6q4P4+EzntY1SbT1+Fw+VDXnI0p/90QGu77NKNyat9HpmepcmLSCYqNCxau9w422AHEFjxQ8YkT/s8PT9PM10v6eb67rI7fxynfbSo0+nBl8HVmFpNNpmo0LD4KtjkbUpWPFJjrQpHQ0qouGrDydpORISZ8I25OUqHQ8NAa7vs0vU+rWiETxIozIzDhPRYpcMZFCYqNCzk/in3TOBoilHJoynLpmUyWdUBLe6yS9eTk81VGmqZfy0mKjRkQgj2TzG4brcPH58MzIOziFYf9lRqb5dd6q+tyx0a7V5ZrN1kk4kKDdmVNifqO3sQEWbiPLZBfXLqKrrcPhSkxmBBAUfV9KC33bp2dtml/raXN8IvCRSNicfY1Bilwxk0Jio0ZPJoyuy8JERbwhWOhpTQt4hWi6sKqL/ALrvBdusanjIwut7VPto+h0xUaMj69k8h4zld14myehss4WY8MYdFtHrw+blm9Hi1t8su9Wp2uHC4uh2Atqd9ACYqNER+SYTmQNk/xZjk0ZSHizKRHGNROBoaDlrdZZd6bS9rhBDAzNxE5CZru1M4ExUakoqrNth6vIizhmP6GF55GY3d5cUnp+Qi2nyFo6HhoOVddqlX3yZvWsdEhYZErk+5a3wK22sb0Mcn6uH0+DExPRbzxnJliB7Iu+yOS43R3C67FNBg60Hp5cAGsSuZqJDRsT7FuIQQ2BCc9lldwiJavejdZVeb7dYJ2BrsnTJvbBKyEqIUjmbomKjQoLm8/lDWzv4pxnOithPnGh2whpvxtVksotUDW0+fXXY1vlLEyOQmb3o5h0xUaNCOXu6AxychMz4S49O0u0afBkcuon1kejYSoiMUjoaGw64zgV12J6bHYnKm9nbZJaC23YmTtZ0wmYAVxZlKhzMsmKjQoPXtRsshYmOxOb3YHCyiXXMXO9HqRWi1jw7qGoxqa1lgNKVkXDLS4yIVjmZ4MFGhQQvVp0xkJ1Kj+cuJOrh9Egoz4zArN1HpcGgYdHR7sF/ju+ySfpq89cVEhQalo9uD8qs2AMDd41mfYiRCiNC0zxoW0eqGHnbZNbrLrd0or7cjzGzCiiJ9TPsATFRokA5eaoMQwKSMWKTH62N4kQbm6JUOXGjuQlREGB6bNUbpcGiY6GGXXaOTp30Wjk9Bio52MGeiQoPC3ZKNa8OhKwCAx2ZmIz6SRbR60NrlxlcX5Wkf1qdolVw3prdzyESFBoX9U4ypo9uDbeWNAAK9U0gftpc3QhJA8ZgE5KdwBZ8WVTV34VyjA+FmE5ZN08+0D8BEhQahtt2JK21OhJlNKClgIa2R/Pl4HTw+CUVj4jE9J1HpcGiYbNHplbiRyEW0905MRWK0vvbcYqJCd0weTZmVm4hYa7jC0dBo6V9Ey3199KLZ7sKRy8FddpmoaJIQQndN3vpiokJ3jPUpxnTwUhsutXYj1hqOR1lwqRvbyhogBDArLxE5SdreZdeoKpscqGrugiXMjKXTMpQOZ9gxUaE7IkkCX11sAwDcM5GJipHIoymPzcxGDEfSdEPPV+JGsSW4P9N9k9J0WeDORIXuyNlGO9q7PYixhGEmG30ZRmuXG59WsIhWb6529uDolQ6YTMDKYk77aFFg2idQn7Jqhj7PIRMVuiNyfUpJQQoiwvjrYxQfHK2D1y8wMzcR07ITlA6Hhsm2YN+NefnJyExgPyQtqrhqx+U2J6zhZiyeor9pH4CJCt2h/VWBaR/WpxiHJAm8dyQw7cPRFH3ZLE/76PRK3AjkqbsHC9N1u7iBiQoNmNvnx5HqYH0KExXDOHCxFTXtTsRFhmMV6xh0o7bdiVO1nTCbgBVFTFS0qO+0j55rjJio0IAdv9IJl1dCaqwVkzK4F4hRbDgUGE15YnYOoixhCkdDw0W+Er+rIAVpcfppt24kp+psqOvoQbQlDA8WpisdzohhokID1tuNNoUb0RlEs92FXWebAHDaR2/kK3H2TtEuuVHf4ikZur6IYKJCA8b+Kcbzx6O18EsCc/OTMCkjTulwaJhUt3aj4qq8yy4TFS2SJBHahFDvHYWZqNCA2Hq8OF3XCYCJilH4JYH3jtQC4GiK3shX4gvHpyA5Rl/t1o3ieE0HGmwuxFrDcf+kNKXDGVFMVGhADl1qgySAgrQYZCdGKR0OjYJ951tQ39mDxOgIPMweG7oi16ewOFq75HO4dGoGIiP0O+0DMFGhAeJuycaz4XBvEa3e3wiN5EKTA5VNDkSE6W+XXaPwG2jaB2CiQgPE+hRjabD14PNzgSLap+dz2kdP5N4p905MQ0K0/tqtG0Hp5Xa0ONyIjwzHvRP1Pe0DMFGhAbja2YNLLd0wmwJLGUn/Nh2phSSAuwqSMSGdS9H1on/fDf1fieuVfA6XTcuEJVz/H+P6P0IaMnnaZ3pOIhKieAWmdz6/hPdL5SLafIWjoeF0rtGBSy3dsISbsXSqPtut653PL2F7WWDfrUcMsos5ExW6LdanGMsXlS1otLuQHGPBMh1uGW9k8pX4oklpiNPhLrtGcOhSO9q6PUiKjsDC8cYY4WaiQrckhOD+Pgaz8fAVAMA35uTAGs4iWr0ITPvIe/sY40pcj+Rkc3lRlmE2hjXGUdKgnW/qQmuXG5ERZszOT1Q6HBphte1O7DnfAoBFtHpTXm/HlTYnIiPMWKzjdut65vVL2FERmPZZZaAaIyYqdEvyap/541J4dW0A75fWQojANN/Y1Bilw6FhJF+JLy7MQIxOd9nVu/1Vreh0epEaa0GJgRY2MFGhW+q7vw/pm9cv4f2j7ESrR/2mfQx0Ja43W04FzuGKoiyEmY2z3xoTFbopr1/CoUuB+pR7Juh/rb7RfXamCS0ON9LirFwRojMnajtR39mDGEsYHuC0jya5fX7sPBNc7WOwZJOJCt3UydpOOD1+pMRYUJjJDen0buORQCfab87NMUyRnlHIV+JLDNBuXa++PN8Kh8uHjHgr5o1NVjqcUcV3I7qp/RcC0z4LJ6TCbKBhRiO60taNLy+0wmQCnprHaR89kSSBbcF26yu5Z5NmyTVGDxdnGe79mIkK3RTrU4xD3iX5volpyE2OVjgaGk5Hr3Sg0e5CnDUc90/mFK4Wubx+7DoT2NLiEQNuJMlEhW7I4fLiRG0nAPZP0TuPT8IHwSLaNSyi1R35SnzptAyu3NOoPZXN6Pb4MSYxCrPzEpUOZ9Qpmqi89dZbmD59OuLj4xEfH48FCxZg+/btSoZEQUeq2+GXBMamRCMniVfYevZpRSPauj3IjI/Egyy01BW/JLCtTO67Ybwrcb2QN5JcOT0LJpOxpn0AhROVnJwcvP766zh27BiOHj2KBx98EI899hgqKiqUDIvA3ZKNZOPhYBHtvFyEs4hWVw5fakNrlxsJURF8LWuU0+PD52ebARhvtY9M0a4/q1at6vf9P/3TP+Gtt97CoUOHMG3aNIWiIoD7+xjFxZYuHLzUBrMJeGpertLh0DCTr8SXG2SXXT3afbYZPV4/8pKjUTwmQelwFKGa9oR+vx8ffPABuru7sWDBghs+xu12w+12h7632+2jFZ6hNNtdON/UBZMJWGCQTa+M6r3gaMqDhenIToxSOBoaTl6/hB3l8t4+xrwS1wO5xsio0z6ACoppy8rKEBsbC6vViu985zv48MMPMXXq1Bs+dv369UhISAh95ebyCnAkHLgYGE0pHpOAxGiLwtHQSHF5/fjT8ToA7ESrRwcvtqHD6UVKjAULDNRuXU8cLi++qAzsvWXUaR9ABYnK5MmTcfLkSRw+fBgvvvginnnmGZw5c+aGj123bh1sNlvoq7a2dpSjNYb9F7hbshHsKG9Ep9OLMYlRuH8Si2j1pneX3UzWHmnU7rPN8PgkFKTGYGpWvNLhKEbxqR+LxYIJEyYAAObMmYPS0lL86le/wn/+539e91ir1Qqr1TraIRqKEIL1KQax4fAVAIHaFCPtG2IEHp+EHeVyu3Wu9tEqOdl8xMDTPoAKRlSuJUlSvzoUGl0XW7rRaHfBGm7GnPwkpcOhEXK+yYHSyx0IM5vwTRbR6s7+qhbYXT6kxVkxf5yx2q3rha3Hi73ng9M+M4ydbCo6orJu3TqsWLECeXl5cDgc2LhxI/bs2YNPP/1UybAMTR5NmTc2mXuC6Ji8JHnJlHRkxEcqHA0NN3lvn5XFxtplV092VjTC6xeYlBGLSRnG3mtN0USlubkZf/3Xf42GhgYkJCRg+vTp+PTTT7F06VIlwzI09k/Rvx6PH38JFdHmKxwNDTeX14+doXbrxi3A1LotwaXlnLpTOFH5/e9/r+SPp2v4/BIOXQwU0rI+Rb+2nL4Ku8uH3OQo3MvzrDt7z7egy+1DVkIkZudx+laLOro9odFtJpsqrFEh5Zyut8Hh9iExOgJTs41bYa53G48Epn2enp9nuF1YjUC+El9pwF129WJHRSN8ksDUrHgUpMUqHY7imKhQyIELgQx+4fgUzmvr1Jmrdpyo6US42YRvzGERrd70ePzYfTY47WPwAkwt69vkjZioUB+sT9G/jUcCS5KXFWUiLY5L/fXm83PNcHr8yEmKwowcY7Zb17oWhxsHg1Pw3EgygIkKAQhsfHW8pgMA61P0qtvtw0cnAldqa+azE60esd269u2oaIQkgOk5CchL4c71ABMVCjpS3Q6vXyAnKQp5yXxx6NHmU1fR5fZhXGoM93DSoS63D5+fC+yyyytx7dpyqrfJGwUwUSEA/XdL5pWYPvUW0ebyHOvQ7rNNcPskjE2JxjQWw2tSk92FI5fbAQArmWyGMFEhAMD+Ku7vo2dldTacrrPBEmbG11lEq0ubT/X23WAiqk3byhogBDA7LxFjuJt5CBMVQmuXG2cb7AACK35If+Qi2hXFmUiO4Y7YemPr8WJfqN06pwy0ik3eboyJCuGrYIX51Kx4pMRyJYjeOFxefHwyMO+9mkW0uvTZmSZ4/BImpMdissHbrWvV1c4eHLvSAZOJy5KvxUSFQv1T7pnIaR89+ujkVTg9fkxIj+UGdTrFXXa1b2twNGXe2GTuv3UNJioGJ4Rg/xQdE0KENiBcPT+PH2I61On04MsLcrt1ThloVd9kk/pjomJwl9ucqO/sgSXMjHljuS+I3pys7cTZBjus4WY8MTtH6XBoBHwabLdemBmHCelst65FNW1OnKqzwWwCVhQxUbkWExWDk0dTZucnItqi6B6VNALk0ZSV07OQEB2hcDQ0EuQCzFVsma9ZW8sC5/CughR2jL4BJioGF6pP4bSP7th6vNgcHE5eU5KvcDQ0Etq63KFieE4ZaFfvtA+TzRthomJgfkngq4usT9GrD4/XweWVUJgZh9l5iUqHQyNge3kj/JJA8ZgE5KfEKB0ODUJ1azcqrtoRZjZheVGm0uGoEhMVAyuvt8Hu8iEuMhzFY7iBmZ4IIUKdaFeXsIhWr1iAqX1yy/y7J6Syx9FNMFExMLk+ZUFBCsLD+KugJ0evdOB8UxeiIsLw+KwxSodDI6DZ7sLharndOhMVrept8sZzeDP8dDKw0P4+7J+iO3IR7aMzshEfySJaPZLbrc/MTUROEjcS1aILTQ5UNjkQEWbCsqmc9rkZJioG1ePx4+jlDgCsT9Gbjm5PaBXB6hJ2otUrXolr3+bgObxvYhpX5d0CExWDOnqlHR6/hKyESBSksghPT/58vA4en4Rp2fGYnsPaIz262tmDo1cCFxqc9tEmIUSoxojn8NaYqBhU3260LLTUj75FtGtK8nludWpbmdxuPQlZCdxlV4vONjhwqaUblnAzlk7NUDocVWOiYlCh+hRO++jKoUvtuNTSjRhLGB6dyZ4MerWZu+xq3taywGjKoklpiGMd2S0xUTGg9m4PKq7aAQALJ6QoHA0NJ3k05bFZYxBrZadhPaptd+JUbWeg3XoxCzC1KDDtE0w22VH4tpioGNDBi20QApicEYf0OO7SqRetXW7sKA8W0c5nEa1eyYXSJeNS+PrVqPJ6O660OREZYcbiwnSlw1E9JioGxN2S9elPx+rg9QvMyE1EERv46VaoydsMFmBqlXwOFxdmIIYjn7fFRMWAevuncNpHLyRJ4D25iJajKbp1ubUb5fWBduvcZVeb+k37cLXPgDBRMZiaNidq2p0IN5swfxwTFb346mIbrrQ5EWcN55W2jslX4gvHp7DdukadqO1EfWcPYixheIDTPgPCRMVgDgQ3IZyVl8hiSx3ZcPgKAOBrs8cg2sLzqlfylfgqrvbRrC2nAudwydQMREaEKRyNNjBRMRjWp+hPs8OFXWeaAACrS/IVjoZGSlWzA+cag+3Wp3G1jxZJkgj1wFlZzJHPgWKiYiCSJPAV+6fozgdH6+CTBObkJ2FyZpzS4dAI2Ry8Er+X7dY161hNBxrtLsRZw3H/5DSlw9EMJioGcqbBjg6nFzGWMMzITVQ6HBoG/j5FtFySrF99262zAFO7tpwKnMOl0zJgDee0z0AxUTEQebXPXQUpiAjjqdeDfRdaUNfRg4SoCO4XomPnGh24yHbrmuaXBLaVNwJgjdGd4qeVgbA+RX82Hg6MpjwxO4eFeTomj6bcz3brmnW4ug0tDjcSoiL4HnyHmKgYhMvrR+nldgDAPRP5ItGDBlsPPj/XDABYXZKrcDQ0Uth3Qx/kc7h8WiYs4fzovRP83zKI4zUdcHklpMVZMTE9VulwaBi8X1oLvyRQMi4ZE9JZRKtXfdutL5nCaR8t8vkl7AhO+7DP0Z1jomIQfXdLNplMCkdDQ+XzS3i/tBYAsLqERbR6Jk/7PFiYznbrGvXVxTa0d3uQEmPBggI22rxTTFQMYn9VGwDWp+jFnsoWNNhcSI6xYHkRe2roVf9pHxZgapWcbC4vykQ4FzLcMf6PGYDN6UVZXScA4O4JzOb1YGNwSfLX5+RwmaOOnQy2W4+2hOGByWy3rkUeX++0D1fmDQ4TFQM4eKkNkgDGp8UgKyFK6XBoiOo6nPiiMlBE+zR7p+iaPJqyZEoGoixMSLXoQFUr7C4f0uKsKOH+aoPCRMUADrAbra68X1oLIQKjY+NSY5QOh0aIJAls5WofzdscnPZ5uCgTYWbWBw4GExUDOMD+Kbrh7VtEO5/7+ugZ261rn8vrx66KwD5cj8xgjdFgMVHRufrOHlxq7YbZBNw1nsOOWrf7bBOaHW6kxlrZoVTn2G5d+/adb4HD7UNmfCTm5CUpHY5mMVHROXk0ZUZuIuLZ0VLzNgQ70X5zbg6bRukY263rg1xjtHJ6Fsyc9hm0Qb/T/Z//839w9913Izs7G1euXAEAvPHGG/j444+HLTgaOtan6EdNmxNfXmiFycQiWr1ju3Xt6/H48dnZ4LQPa4yGZFCJyltvvYVXX30VDz/8MDo7O+H3+wEAiYmJeOONN4YzPhoCIQTrU3TkvdLAaMq9E9OQmxytcDQ0kthuXfu+qGyG0+NHTlIUZnK3+iEZ1CvgzTffxH/913/hJz/5CcLCeudO586di7KysmELjoamssmB1i4PoiLCMCsvUelwaAg8PgkfHA0U0a5hJ1pdY7t1fZCbvK2cnsVu4EM0qESluroas2bNuu52q9WK7u7uIQdFw2P/hcBoyvxxySzG07idZxrR2uVBRrwViwvZ+EvP5HbryWy3rlndbl9ow9BHilljNFSDSlTGjRuHkydPXnf7jh07MGXKlKHGRMOE9Sn6sTFYRPvk3Fy24NY5tlvXvt3nmuHySshPiUbRmHilw9G8Qe1w9eqrr2Lt2rVwuVwQQuDIkSN47733sH79evzud78b7hhpEDw+CYer2wGwPkXrLrV04auLbTCbgCdZRKtrfdutswBTu+Sl5Y9w2mdYDCpR+du//VtERUXhf/7P/wmn04nVq1cjOzsbv/rVr/DUU08Nd4w0CCdrO+H0+JESY0FhZpzS4dAQvBfc1+eByekYk8gtEPRsf1UL261rnMPlxZ7zLQC4keRwGfSe4WvWrMGaNWvgdDrR1dWF9HTOm6vJ/uC0z8IJqVy/r2Eurx9/OlYHAFjNIlrd23IqsNqH7da1a9eZJnh8EsanxfAicZgMOlGRRUdHIzqaSyXVprc+hVdlWvZpRSM6nF5kJ0RiEXfP1TWX14+dZ9huXeu2hPZnyua0zzAZVKLS1taGn/70p/jiiy/Q3NwMSZL63d/e3j4swdHgOFxenKztBMD6FK3bcCgw7fPU/DxeYevcvvMt6GK7dU2zOb348kJg2mcVl5YPm0ElKv/jf/wPVFVV4W/+5m+QkZHBrFFlDl9qh18SGJsSjZwkjnZp1YUmB45cbkeY2YQn5+UqHQ6NMLZb175PKxrh9QsUZsZhQjqnfYbLoBKVL7/8Evv378eMGTOGOx4aBvvZjVYXNgaLaBcXpiMjPlLhaGgksd26Pmw+3bvah4bPoBbpFxYWoqenZ7hjoWEi16fcO5GJila5vH78OVhEu+aufIWjoZHGduva19blxlcX2wAAK7naZ1gNKlH5zW9+g5/85CfYu3cv2traYLfb+32RcprsLlxo7oLJBCwoYKKiVVtON8Du8iE3OQr3cmRM99huXfs+rWiCXxKYlh2PcakxSoejK4Oa+klMTITdbseDDz7Y73YhBEwmU2iTQhp98mjK9DEJSIiOUDgaGqyNhwM7kj81L4/1CjrXt936Kl6Ja9aW0LQPz+FwG1SismbNGkRERGDjxo0splUZ1qdo39kGO47XdCLcbMI35uYoHQ6NsM/ONsHllTA2JRrTstluXYtaHG4cuhSY9mF9yvAbVKJSXl6OEydOYPLkycMdDw2BEIL7++iAvK/PsmmZSI9jEa3ese+G9m0vb4AkgBm5ichN5krL4TaoGpW5c+eitrZ2uGOhIbrY0oUmuxvWcDNm57MPgxY5PT58dKIeADvRGoHd5cXeymC7dfbd0Cy5o/AqjqaMiEGNqHz3u9/Fyy+/jB/84AcoLi5GRET/Wojp06cPS3B0Z/ZfCIymzB+XjMiIMIWjocHYfOoqHG4fxqZEY0EBuwrr3a6KJnj8Eiakx2JyBvtuaFGjzYXSK4Empw8XM1EZCYNKVJ588kkAwPPPPx+6zWQysZhWYfurAnOkrE/RLnna5+n5LKI1gi2nucuu1m0ta4AQwNz8JGRz09ARMahEpbq6erjjoCHy+aVQMRfrU7SpvN6GU3U2WMLM+PocFtHqXafTgy+Do6AswNSuLWzyNuIGlajk57MBldqcqrOhy+1DYnQEpmZx5YAWbQiOpiwvykRKrFXhaGikfVrRCJ/EdutaVtfhxImaTphMwApO+4yYAScqn3zyCVasWIGIiAh88sknt3zso48+OuTA6M7Iq33uHp/KKQMN6nL78MlJFtEaSe9qH37AadW2ssA5nD82mdtcjKABJyqPP/44GhsbkZ6ejscff/ymj2ONijLYP0XbPjpRj26PH+PTYlAyLlnpcGiE9W23zgZh2hVKNmfwHI6kAScqkiTd8O+kvG63DydqOgCwPkWLhBChItrVJfksqjSAHRWN8EsCRWPiMZbt1jXpSls3TtfZYDYBK4oylQ5H1wbVR+Xdd9+F2+2+7naPx4N33313yEHRnTlyuR1ev0BuchTyUthsSGtO1dlwpsEOS7gZT8weo3Q4NArkvhscTdEueTRl4fhUpLKmbEQNKlF57rnnYLPZrrvd4XDgueeeG3JQdGcOXGA3Wi2T9/V5pDgLidEWhaOhkdbscOFwdXCXXRZgahZrjEbPoBIVuV/Kterq6pCQkDDg51m/fj3mzZuHuLi4UO1LZWXlYEIyNNanaJetx4tPTgWWN665i0W0RrC9rBGSAGay3bpmXWzpwtkGO8LNJizntM+Iu6PlybNmzYLJZILJZMLixYsRHt77z/1+P6qrq7F8+fIBP9/evXuxdu1azJs3Dz6fDz/+8Y/x0EMP4cyZM4iJ4bztQLQ43DjX6AAQGIIkbfnoRD1cXgmTM+IwO4/bHhgB+25onzx1d8/EVI6CjoI7SlTk1T4nT57EsmXLEBsbG7rPYrFg7NixeOKJJwb8fDt27Oj3/TvvvIP09HQcO3YM991333WPd7vd/Wpj7Hb7nYSvS19dDIymTMuOR3IMXzBa0r+INo9FtAbQYOtB6eVA4ftKJiqa1ZtsssZoNNxRovKzn/0MADB27Fg8+eSTiIwc3nXjct1LcvKNl2euX78er7322rD+TK3jbsnadexKByqbHIiKCMNfsYjWELYG6xrmjU1CVgLbrWtRZaMDF5q7YAkzY+nUDKXDMYRBdaZ95plnAARW+TQ3N1+3XDkv787n2iVJwiuvvIK7774bRUVFN3zMunXr8Oqrr4a+t9vtyM3NveOfpRdCiNBGhKxP0R55NGXVjCzER0bc5tGkB70FmLwS16qtwdGU+yalIiGKr9vRMKhE5cKFC3j++efx1Vdf9bt9KJsSrl27FuXl5di/f/9NH2O1WmG1chmY7HKbE1dtLljCzJg3lk3CtKTT6cGWYFfL1SXcksIIatudOFnbGei7UcwCTC0SQjDZVMCgEpVnn30W4eHh2LJlC7Kyhr7r50svvYQtW7Zg3759yMnhZmwDJa/2mZOfhChLmMLR0J348/F6eHwSpmbFY0bOwFfKkXZtDSamJeNSkB7HdutadKbBjkut3bCGm7GE0z6jZlCJysmTJ3Hs2DEUFhYO6YcLIfDd734XH374Ifbs2YNx48YN6fmMJtQ/ZSKnfbRECIENwd4pa+5iEa1RhAowZ7CIVqvk0ZQHJqcj1jqoj08ahEH9T0+dOhWtra1D/uFr167Fxo0b8fHHHyMuLg6NjY0AgISEBERFsdDsVvySCK34YX2Kthyubsellm7EWMLw2EwW0RrB5dZulNfbEWY2Yfk0TvtoUWDah8mmEgbV8O0Xv/gF/uEf/gF79uxBW1sb7HZ7v6+Beuutt2Cz2bBo0SJkZWWFvt5///3BhGUo5fU22F0+xEWGo3gMpw60RC6ifXTmGF6VGYT8AbdwfApS2G5dk07X2VDb3oOoiDA8WJiudDiGMqh3ySVLlgAAFi9e3O/2Oy2mFUIM5scTeutTFo5PQZiZUwda0dblxvbywPDxmhJ2ojUKtlvXPjnZXDwlHdEWXmCMpkH9b3/xxRfDHQfdIfZP0aY/HauD1y8wIycBRRwJM4SqZgfONToQbjZhGad9NEmSRKgHDlf7jL5BJSr333//cMdBd6DH48fRYHdL1qdohyQJvHektxMtGYM8mnIv261r1onaDly1uRBjCcOiyWlKh2M4g0pU9u3bd8v7b9T+nobP0Svt8PglZCdEYlwq90TSioOX2nC5zYk4azhWzeBVmRGw74Y+yOdw6dQMREawFcRoG1SismjRoutu67vEcjAN32jg+u6WzKWt2iEvSf6r2WM4x20QlU0OVMnt1qex74YWSZLAtjImm0oa1Kqfjo6Ofl/Nzc3YsWMH5s2bh507dw53jHSNUH0K+6doRrPDhZ0VTQA47WMk8i67909O4zYJGlV6uR1NdjfiIsNx7yS+5yphUJd1CQnXFwEuXboUFosFr776Ko4dOzbkwOjG2rs9qLgaWAK+cDxfNFrxwdE6+CSB2XmJKMyMVzocGgX9+m5wtY9mydM+y6ZlwhrOaR8lDGpE5WYyMjJQWVk5nE9J1zh4sQ1CAIWZcUiLYz8GLehbRLuG+/oYRsVVOy63OREZYcaSKZz20SKfXwq1E2CyqZxBjaicPn263/dCCDQ0NOD111/HzJkzhyMuuom+9SmkDfsutKCuowcJURFYyTc7w9gcHE15sDAdMWzsp0mHq9vR2uVBUnQE33MVNKhXz8yZM2Eyma5r2HbXXXfhD3/4w7AERjfG/inaI3ei/drsMVwxYBBCsO+GHshTd8uLMhERNqwTEHQH7jhR8Xq9WLRoEX7729/Cag1MPZjNZqSlpSEykjuCjqSaNidq2p0IN5swf1yy0uHQADTaXNh9rhkAO9EaycnaTtR19CDaEoYHJrPduhZ5/RK2lwf2n2Oyqaw7TlQiIiJQVlYGs9mM/HzOt4+mA8FNCGfnJXEoWSPeL62FXxKYPy4ZE9LjlA6HRolcgLlkSgaiLBxF06IDVa3odHqREmNBCS8MFTWosaxvfetb+N3vfjfcsdBtsD5FW/ySwPulchEtR1OMon+7ddYkaZV8DlcUZyKc0z6KGtRluc/nwx/+8Ad89tlnmDNnDmJi+ndH/eUvfzkswVEvSRL4KtQ/JUXhaGgg9lQ246rNhaToCCwv4h4vRnGspgONdhfirOG4bxLbrWuRxyfh0wpO+6jFoBKV8vJyzJ49GwBw/vz5fvexU+rIONNgR4fTi1hrOKbnJCodDg2AXET79Tk57L9gIFtOBQow2W5du7680AK7y4f0OCvmjeW0j9K4e7JGyNM+dxUks/pcA+o7e/BFZaCI9un5nPYxCr8ksE0uwJzBaR+tkmuMHi7OQpiZF99K4yeeRhxgfYqmvH+kBpIAFo5PQUFarNLh0Cg5XN2GFocbCVERuGcCp320yOX1Y9eZwHYXq5hsqgITFQ1wef04Ut0OgP1TtMDrl7CptBYA9/Uxmq2hdusZsITz7VWL9lS2oMvtQ3ZCJGblJikdDoGJiiYcv9IBt09CepwVE9J5da52u882o9nhRmqsBQ9NZRGtUfj8Enaw74bmyU3eVk7PgpnTPqrAREUD9vfpRstiZfXbGNzX5xtzc3lVbSAHL7WhrduD5BgLFo7nyjwtcnp82H02UFvGZFM9+C6qAaxP0Y7adie+vNACAHh6Hqd9jGTLqcC0z/Ii9t3Qqs/PNaPH60duchSm5yQoHQ4F8dWkcjanF6frbQCYqGjBe0dqIARw78RU5KVEKx0OjRKPT8KOUN8NFmBqlVxjtLI4m6PXKsJEReUOXmqFEMCE9FhkJnAvJTXz+CT88WigiHZNCbeXMJIDVa2w9XiRFmdFyThO+2hRl9uHz8/J0z5MNtWEiYrK7eduyZqx60wTWrs8SI+zYvEUbkRnJJuDBZgPF2Wy74ZG7T7bBLdPwrjUGEzLjlc6HOqDiYrKHahqA8BpHy3YeOQKAODJeblsymcgLq8fuyoCfTcemcECTK3afKp3fyZO+6gL301VrK7DierWboSZTSgpYBtnNatu7caBqjaYTcBT7ERrKPvOt8Dh9iEzPhJz8th3Q4tsPV7sOx8ogudqH/VhoqJiXwVHU2bkJCA+MkLhaOhW3gsuSV40OR1jEqMUjoZGk9xunX03tGvXmSZ4/BImpsdicmac0uHQNZioqBjrU7TB7fPjT8fqAACrOZpiKD0ePz47G5z2YQGmZslN3jiaok5MVFRKkgT7p2jEjvJGtHd7kJUQiUWTub+LkXxR2Qynx48xiVGYmZuodDg0CB3dHuy/EHivXclkU5WYqKhUZZMDbd0eREWEYRbnvVVtw+HAtM9T8/LY6Mtgeq/EWYCpVZ9WNMInCRRmxnGLEpXiu6pKyaMpJQXJbMOuYlXNDhypbkeY2YQn5+UqHQ6Nou5+fTc4ZaBVW8sCNUaruGJLtfgJqFKsT9GGjYcDDd4eLExnQz6D+exsE1xeCfkp0Sgaw74bWtTW5cZXFwOLFlhjpF5MVFTI45Nw+FI7ANanqJnL68efjsmdaFlEazRyu3VO+2jX9vJG+CWB4jEJyE+JUTocugkmKip0oqYDPV4/UmMtmJzBpXJqtfV0A+wuH3KSonDfRBbRGonD5cUe9t3QvL41RqReTFRUSK5PWTg+lX0ZVGxjsHfK0/PzeJ4MZteZJnh8EsanxaCQfTc0qdnuwuHqwMg1V/uoGxMVFWJ9ivqda7Tj2JUOhJtN+MbcHKXDoVG2JTTtw112tWpbWQOEAGblJSIniTudqxkTFZWxu7w4VWcDANw9kYmKWm0MLkl+aFoG0uNYRGskNqcXX14ITPusmsErca3qm2ySujFRUZnDl9rhlwTGpcawFbtKOT0+fHi8HgCwen6+wtHQaPu0ohFev9x3g9M+WnS1swdHr3QAAFYWM9lUOyYqKtPbjTZF4UjoZracaoDD7UN+SjQWjud5MprNLMDUvG3B3inzxiaxrYAGMFFRGdanqN+Gw1cABPb1YRGtsfTvu8EpA63itI+2MFFRkUabC1XNXTCZgAUFTFTUqLzehlN1NljCzPj6HBbRGs2OikDfjaIx8Ribyr4bWlTb7sTJ2k6YTcCK4kylw6EBYKKiIvK0z/QxCUiIjlA4GroReUnysqJMpMRaFY6GRtuWU7wS1zq5ZX7JuBQWwmsEExUV4W7J6tbl9uHjE3IRLTvRGk2zw4XD1YFpHxZgaleoyRtXbGkGExWVEEKwPkXlPj5Zj26PHwVpMbirIFnpcGiUbS9rhCSAmbmJyE1m3w0tutzajfJ6O8LMJqwoYqKiFUxUVKKquQvNDjes4WbMzk9SOhy6hhAi1Dtl9fw8NvkyILZb1z75HC4cn4LkGIvC0dBAMVFRCXk0Zf64ZERGhCkcDV3rdJ0NFVftsISziNaIGmw9KL0c6LvxMKd9NEte7bOKNUaawkRFJQ5w2kfV5NGUlcVZSIzmlZjRyDslz81PQjYbMWpSVbMD5xodiAgzYdk0rvbREiYqKuD1Szh0KbA5Fgtp1cfu8uKTU4Eh4zUlLKI1InmlCKd9tGtzcMXWvRPTuKpSY5ioqMDpuk50uX1Iio7A1Kx4pcOha3x0oh49Xj8mZcRiDuuHDKeuw4kTNZ0wmTjto1VCiFCyyRVb2sNERQX2XwgseVw4IZWdTlWGRbQkT/uUjEtGejz7bmhRZZMDVc1dsISZsXRahtLh0B1ioqICrE9Rr+M1HTjX6EBkhBl/NZtFtEbEduvaJzfqu39yGuIjOe2jNUxUFNbt9uF4TWA1ARMV9dkQHE1ZNT0bCVF8gzOay63dKKu3BftusABTi4QQXFqucUxUFHakuh0+SSAvOZpNpFTG5vSGhv1Xs4jWkOS6hoXjU7hlgkZVXLXjcpsTkRFmLJnCaR8tYqKisP1sm69afz5eB7dPwpSseMzMTVQ6HFLA5lO8Ete6zcHRlAcL0xFjDVc4GhoMJioKY32KOgkhsOHwFQCBJcksojWequYunGt0INzMvhtaJYQIjYqyxki7mKgoqNnhwrlGB0wmYMH4FKXDoT6OVLfjYks3oi1heGwm3+CMSK5ruHdiKpv8adTJ2k7UdfQg2hKGByanKx0ODRITFQUdvBhYljwtO577TqjMxiOBItrHZmYjjqsEDCdQgMkrca2Tz+GSKRmIsnBrEq1ioqKg/RdYn6JG7d0ebC9rBACsnp+vcDSkBPbd0D5JEtgmN3ljjZGmMVFRiBCC9Skq9adjtfD4JUzPSUBxToLS4ZAC2HdD+47XdKDB5kKcNRz3T0pTOhwaAiYqCqlu7cZVmwuWcDPmjU1WOhwKEkLgvSO1AAKdaMl42HdDH+Rpn6VTM7gjvcYxUVGIPJoyNz+JLyIVOXixDdWt3Yi1hmPVDNYmGJHcd8MabsZi9t3QJL/Uu7fPIzOYbGodExWFsH+KOsmdaP9q1hj2XDCovn03Yvk7oElHqtvR4nAjISoC90zgtI/WMVFRgF8S+Cq44of1KerR4nDj04pgES070RoS+27ogzx1t2xaBizh/JjTOp5BBZTV2+Bw+RAfGY6iMSzWVIsPjtXCJwnMykvElKx4pcMhBZyqs4X6bjxYyL4bWuTzS9hRHrjgYLKpD0xUFCDXpywcn4owMzueqoEkCbwX7J2ypoRLko1qS7Bl/mL23dCsg5fa0NbtQXKMBQvZSFMXmKgoINQ/ZSKnfdTiy6pW1Lb3ID4ynCs9DErqW4DJ3wHNkpeWLy/KRHgYP+L0gGdxlPV4/Dh2pQMA61PUZGNwX5+vzc7hKiyDYt8N7fP6JewI1pk9UsxkUy+YqIyy0svt8PgljEmMwtiUaKXDIQBNdhc+O9sMILABIRkT+25o3/6qVth6vEiNtaKkgNM+esFEZZQdCC1LTuGOvCrxfmkt/JLA/LHJmJgRp3Q4pAD23dAHedrn4eJM1v/pCBOVUcb+KerilwQ2BYtouSTZuNh3Q/vcPj92nuFqHz1SNFHZt28fVq1ahezsbJhMJnz00UdKhjPi2rs9qLhqBxBY8UPK23u+GVdtLiRFR2B5UabS4ZBC2HdD+/adb4XD5UNmfCTm5icpHQ4NI0Vfkd3d3ZgxYwZ+/etfKxnGqPnqYmA0pTAzDmlxVoWjIQDYcCgwmvL1OSyiNSr23dAHOdl8uDgLZk776Iqi/aFXrFiBFStWKBnCqOJuyepytbMHX1QGimif5gaEhsW+G9rn8vrx2ZkmAKwx0iNNbWThdrvhdrtD39vtdgWjuXOh+hT2T1GFTaW1kASwoCAFBWmxSodDCmHfDe374lwzuj1+jEmMwqzcRKXDoWGmqVfl+vXrkZCQEPrKzc1VOqQBq2lzora9BxFhJswfm6x0OIbn80t4v5RFtEbn8bHvhh5sOd3bqI+rKfVHU4nKunXrYLPZQl+1tbVKhzRg8mjKrLwk7sqrArvPNaPJ7kZKjAXLprGI1qgOsO+G5jk9Puw+F5j2WcmOwrqkqU9Mq9UKq1WbRaisT1GXjYcDoynfmJvLVR4GJl+Js++Gdu0+2wyXV0JecjSKucmrLvEdehRIksCBi+yfoha17U7su9ACAHh6vnamD2l4se+GPsirfTjto1+Kjqh0dXWhqqoq9H11dTVOnjyJ5ORk5OXpp27gTIMdnU4vYq3hmJHDjF9pm0prIARw78RU5KfEKB0OKYR9N7TP4fLii8rARQeTTf1SNFE5evQoHnjggdD3r776KgDgmWeewTvvvKNQVMNPrk+5qyCFqwoU5vVLeL+0DgD39TE69t3Qvs/ONsHjk1CQFoMpWdz+Qq8UTVQWLVoEIYSSIYyK3voUFuspbdeZJrR2uZEWZ8XiKRlKh0MKYd8NfZCXlj8yPZvTPjrGy/sR5vL6caS6HQBwD/unKE4uon1ybi4iOLplWOy7oX02pzdUa7aKq310je/UI+z4lQ64fRIy4q0Yz6Ziirrc2o39Va0wmYCnWERraOy7oX2fnmmE1y8wOSOOu57rHBOVEdZ3t2S+ISrrveAuyYsmpSEnKVrhaEgp3e7evhsswNSurX2STdI3JiojjP1T1MHt8+ODY4Ei2tUl+QpHQ0rafS7QdyM/JRpFY+KVDocGoaPbE3pvZZM3/WOiMoJsTi9O19sAsH+K0j6taEJ7tweZ8ZF4YHKa0uGQgracYt8NrdtR0QifJDA1K577dBkAE5URdPBSK4QAJqbHIiM+UulwDG3DoSsAArUpXCJuXA6XF3vOs++G1oWavHHFliHwHXsE9a1PIeVUNXfhcHU7zCbgyXksojWyXWcCfTfGp8WgMJMFmFrU4nDj4MU2AMAjxUw2jYCJygg6UBV4MbE+RVlyEe2DhRnISohSOBpSUu9qH/bd0Kod5Q2QBDAjJwF5KSyKNwImKiOkrsOJ6tZuhJlNKClIVjocw3J5/fhTsIh2zV3sRGtkNqcXX16Qp304ZaBVm/skm2QMTFRGyFfB0ZSZuYmIi4xQOBrj2lbWAFuPF2MSo3DfRBbRGtmnFey7oXVNdhdKLwcaaHK1j3EwURkhrE9RB7kT7dPzcxHG/VwMbUsZ+25o3dbTDRACmJOfhOxETuMaBROVESBJgv1TVKCy0YGjVzoQbjbhm3NZRGtk7X36bjwyg1MGWrWVyaYhMVEZAZVNDrR1exBtCcNM7iOimI2HA0uSl07NQDqXhxvajvJG+CWBadnxGJcao3Q4NAhXO3tw7EoHTKbAjtdkHExURoB85VYyLhmWcP4XK6HH48dfTtQDAFaXsIjW6EJ9N1iAqVlyy/x5Y5PZl8pg+Ck6AliforzNp6/C4fIhLzkad4/neTCyFocbhy4F+25wykCz5GSTOyUbDxOVYebxSTh8KVCVfs9EfkAqZUOwiHZ1SR7MLKI1tO1y343cROQms++GFtW0OXGqzgazCVhexETFaJioDLMTNR3o8fqRGmvBZC6BVETFVRtO1XYiIsyEr8/JUTocUtiWU4EpA16Ja9eWssBoyoLxKUiLsyocDY02JirD7ECfaR92vlSGvCR52bRMpMbyTc3IGm0ulF4JjHCyAFO75GSTNUbGxERlmH3J+hRFdbl9+IhFtBS0tSzQd2Mu+25o1qWWLpxpsCPcbMLyaZlKh0MKYKIyjOwuL07VdgJgoqKUT05eRbfHj4LUGCwoSFE6HFJY72ofjqZolbw/090TUpEUY1E4GlICE5VhdOhiGyQBFKTGYAyv3hSx8Uigd8rqkjxOvRlcXYcTJ2o62XdD47aeZpM3o2OiMowOcNpHUafrOlFeb4cl3IwnZrOI1ujkD7iSccls+KdRF5ocqGxyICLMhIemctrHqJioDCP2T1HWhkOBItqVxVkcIqbQlAELMLVL3in5volpSIjm5q5GxURlmDTYenCxpRtmE1gboQC7y4tPTgXqEVhES5dbu1FWH+i7saKIV+JaJITorTGawWkfI2OiMkwOVAU6XxbnJDLzV8DHJ+rR4/VjYnos5uYnKR0OKUzevG7h+FSkcIm6Jp1tcOBSSzcs4WYsmZKhdDikICYqw6R3t2SOpow2IUS/TrQsoqUtLMDUPHk05YHJaYiL5MWfkTFRGQZCCNanKOh4TSfONToQGWHG12axiNboLrZ04azcd4PTPpoUmPZhjREFMFEZBheau9DicCMywozZeZx2GG1yJ9pHpmdz2o1CXUzvmZiKxGgWVWtRWb0NNe1OREWEYfGUdKXDIYUxURkG+y8ERlPmjU1GZESYwtEYi83pDQ0Rs4iWgL5N3nglrlXyaMqDU9IRbQlXOBpSGhOVYdBbn8Jpn9H2lxN1cPskFGbGYVZuotLhkMIqGx240NwFS5gZD01jAaYWCSFCPXC4kSQBTFSGzOuXcOhSYMUP61NGV98i2jV35bOIlkKjKfdNSkM8CzA16URtJ+o7exBjCcOiyZz2ISYqQ3aqthPdHj+SoiMwNSte6XAMpfRyB6qauxBtCcPjMznMb3R9CzBXse+GZsk1RkumZnAqnQAwURkyebXPwgmpMJt5RT+aNh4O7Ovz6IxsLl8kVFy1o7q1G9ZwMxaz74YmSZLAtjKu9qH+mKgMEetTlNHe7cG2skYAwJqSfIWjITUIFWAWpiPWygJMLTp6pQONdhfiIsNx3yS+p1IAE5Uh6HL7cKKmEwATldH252N18PglFI9JQHFOgtLhkML6tVvnlbhmyefwoamZsIZz2kdpIvin0+NXNA4mKkNwpLoNPkkgLzkaucnRSodjGEIIvHektxMt0ak6G+o6ehBtCcODhSzA1CK/JEKjpNzbRx3+3y1nAACfnW1SNA4mKkOw/0Jgtc89EzmaMpoOXmrDpdZuxFrD8egMXj0TsCW4IeXiKRmIsvBKXIsOX2pDa5cbidERHKGmfpioDAHrU5QhL0l+fFY2YliLYHiSJEKbEHJvH+3aHKwxWj4tExFh/GiiXvxtGKRmhwuVTQ6YTMCCAm5EOFpau9zYWREYHl49n0W0BByv6UCDzYVYazjun5SmdDg0CD6/hB3lXO1DN8ZEZZC+qgpM+xRlJyAphvuJjJYPjtbB6xeYmZuIqdnsW0O9q32Wsu+GZn11sQ0dTi9SYiy4qyBZ6XBIZZioDBJ3Sx59ktRbRLuGRbQEuQCT0z5aJ6/2WV6UiXBO+9A1+BsxCEII1qcoYH9VK2ranYiLDOfwMAEASi+3o9nhRnxkOO6dyGkfLfL4JOwoD6724euaboCJyiBcau1Gg80FS7gZc8cmKR2OYWwMFtE+MTuHKzsIQO+V+LJpmbCE8+1Mi/ZXtcDu8iEtzor54zjtQ9fjK3sQ5NGUeWOTOCc+SprsLuwKruVn7xQCAgWY20N9N3glrlXy3j4ri7MQxm1I6AaYqAzC/gusTxltfyythV8SmDc2CZMy4pQOh1Tg0KV2tHV7kBQdgYXjufJOi1xeP3aeCVyAsMaIboaJyh3y+SUcvBRs9MZEZVT4JYFNpbUAOJpCvXoLMLPYd0Oj9p5vQZfbh6yESMzO4zQ63Rhf3XeorN4Gh8uHhKgITMvmHjOjYd/5FtR39iAxOgIrinjVRYDXL2FHsJ/OKl6Ja5a8tHxlcRZ3n6ebYqJyh+T6lIXjUzifOko2HL4CAPj67BzWBBGAwAqwTqcXqbFWlLDhoib1ePzYHaw7Y40R3QoTlTvE/imj62pnDz4/1wwAeJrTPhQkF2A+XJzJCwaN+qKyGU6PHzlJUZjBHdDpFpio3AGnx4fjVzoBsD5ltLxfWgtJAHcVJGN8WqzS4ZAKuH1+7DzDvhtaJ9cYrZyeBZOJySbdHBOVO1B6uQMev4QxiVHIT4lWOhzd8/klvB8qouW+PhSw73wrHC4fMuMjMTefBZha1O32hUZKVzHZpNtgonIH+naj5RXAyPv8XDMa7S6kxFiwbFqG0uGQSshX4g+zAFOzPjvbBJdXwtiUaEzjnl10G0xU7kCof8pETvuMho3BfX2+PjcH1nAW0VKg78Znct+NGVzto1Xyap9Hpmfzoo9ui4nKALV1uXGmwQ4AbC41Cmrbndh7vgUA8PQ8FtFSwBfnmtHt8WNMYhRm5SYqHQ4Ngt3lxd7KwGubySYNBBOVAfrqYqDJ25SseKTGWhWORv82ldZACODeiakYmxqjdDikEr1X4izA1KpdFU3w+CVMSI/FZHaZpgFgojJAvfUpHE0ZaV6/hD8erQMArJ7P0RQKcHp82H0uMO2zkk3eNEuuMWKySQPFRGUAhBD4kvv7jJrPzjShxeFGWpwVS6ayiJYCdp9thssrIS85GsVj2HdDi2xOb+i9lHv70EAxURmAmnYn6jt7EBFm4jbko0Auov3m3Bzu4UIhvBLXvk8rGuGTBAoz4zAhndM+NDD8FBgAuRvt7LwkRFvCFY5G3y63duPLC60wmYCnWERLQQ6XF1/IBZjsu6FZm/skm0QDxURlAPr2T6GR9V5pYDTl/klpyE1mUz0K+OxsEzw+CQVpMZiSxStxLWrrcocWJTDZpDvBROU2/JIIvbjYP2VkeXwS/sQiWroBeW8f9t3Qrh0VjfBLAkVj4rmSj+4IE5XbOHPVjk6nF3HWcExnAd+I+rSiEW3dHmTGR+LBwnSlwyGVsDm92HchMO2zilMGmtU32SS6E0xUbkOuT7lrfArCWdg5ojYcvgIAeHJeLv+vKeTTM43w+gUmZ8RhIvtuaFKzw4XD1YGR6ZXFTDbpzvDT4DZYnzI6LrZ04dCldphNwFPzc5UOh1Skb5M30qbtZY2QBDAzN5G1Z3THuITlNo5cbgfA/ikj7b3DgSLaBwvTkZUQpXA0pBYd3Z7QxcIjMzhloFVbuNpHFbx+CZ1OLzqdHnT2eNHR7Ql83+NBR/D2ju7A951Or9LhhjBRuQ2PT0JmfCTGp7H4a6S4fRL+dDxQRLumJF/haEhNdpQHCjCnZcdjHAswNanJ7kLp5Q4A7Cg8XCRJwOHyocPpQYezT7LR3ScJkRMSpzf0mC63T+nQB4WJygDcPSGVKw1G0LayBnQ6vRiTGIX7JqUpHQ6pSO+VOEdTtGprWSMAYG5+EkdLryGEgNPj70025KSix4vO7uAoR09vsmGT/+zxQhKD+5kmExAfGYGk6AgkRFuQFB2BpGgLEqMjkBhlQVJMBBKjLUiMisBf/+HI8B7wIDFRGYB7JnJ/n5Ekd6J9al4uwsxMCKnXqTobAE4ZaNmp2k4A+j+HHp8UmDqRp1D6TrE4Pejs7pOEBO+3Ob3w+KVB/8wYS1ggqQgmGwnREaHEIyEq8GdSTAQSonoTkvioCM29zzJRGYC7x7M+ZSQdu9KBMLMJ35zHIlq63gwWYGqeyQQ8rJHVPn5JwB5MLjqcXtiCUyr9plj6TKvIox1Oj3/QP9MSZg6MaEQHRjOSgqMbiTHB0Y6o3tuTYgLfJ0RHwBoeNoxHrl5MVG5jUkYs0uMjlQ5D95ZOyUAG/5/pBtg7RftKxiWP+vuoEAJdbl+/ZEKeNpETD1vfhCT4p93lhRjktIrZhNBIRsK1UyrREUiM6ZOE9Ek6oi1hLC+4BVUkKr/+9a/xL//yL2hsbMSMGTPw5ptvYv78+UqHBYCrfUbL6hJ2oqUb08qVOPV3oKot9Peh1hi5vP5+RaGhqRW5fqO7/5RKZ3AkxOsfZMYBIM4a3j/ZkEc6giMcfWs5kqItSIq2IC4yHGaNTatogeKJyvvvv49XX30Vv/3tb1FSUoI33ngDy5YtQ2VlJdLTle9Oyv4pIy8nKYr/z3RDhZlxyE5kAabWrSjKBAD4/FJwFOP6FSnXTqn01np44PIOvo7DGm7uk2zcIPG4ZnRDrvngzu3qoXii8stf/hIvvPACnnvuOQDAb3/7W2zduhV/+MMf8KMf/Ujh6ICSAhbSjrSn5+fxKoRuSO8FmEYx5x8/G/WfGZiCiUBkRGBaxQTA4fKhy+1DbQdgggkmE2ACAkU0CPxdvs103W3yg/vfJs/YXPs9gs9h6n360PP2vQ194uh9XPA2+ecG/3Hff9/7M/vfhj5x9H9c/1hxi8eo7d1Y0UTF4/Hg2LFjWLduXeg2s9mMJUuW4ODBg9c93u12w+12h7632+0jEteMnITQaoNYq+K5nC75+6yt+8bcHAUjIbXpuyLh8VljFIyEtMzW44WtRz1Ny2jwFP0Ubm1thd/vR0ZGRr/bMzIycO7cuesev379erz22msjHtcH31mIlzedwHcfnDjiP8uo0uKseP7ucUiOiUB6HItoqVdEmBkb/7YEMAE5SVzto1W//OYMvPrHU3h16SSkxFpCBaXxUREwmdCvYFUIQECEbhMIFMMK9H2cCD6u97ZrHyMQeMC1t/X+OxF6flz7M0X/n4vQc/T++2tj7b1N9Lsv9PdrHtP35/b/mdffhmviuP5Y+//c64+1/229/9c3f4zo82QCwBeVzSivt2Pp1P6f0aPNJETfQxhdV69exZgxY/DVV19hwYIFodv/4R/+AXv37sXhw4f7Pf5GIyq5ubmw2WyIj48ftbiJiIho8Ox2OxISEgb0+a3oiEpqairCwsLQ1NTU7/ampiZkZmZe93ir1Qqr1Tpa4REREZHCFC1rtlgsmDNnDnbv3h26TZIk7N69u98ICxERERmT4pWir776Kp555hnMnTsX8+fPxxtvvIHu7u7QKiAiIiIyLsUTlSeffBItLS346U9/isbGRsycORM7duy4rsCWiIiIjEfRYtqhupNiHCIiIlKHO/n8Zus9IiIiUi0mKkRERKRaTFSIiIhItZioEBERkWoxUSEiIiLVYqJCREREqsVEhYiIiFSLiQoRERGpluKdaYdC7lVnt9sVjoSIiIgGSv7cHkjPWU0nKg6HAwCQm5urcCRERER0pxwOBxISEm75GE230JckCVevXkVcXBxMJtOwPa/dbkdubi5qa2t125qfx6gPPEb9MMJx8hj1YTiOUQgBh8OB7OxsmM23rkLR9IiK2WxGTk7OiD1/fHy8bn/RZDxGfeAx6ocRjpPHqA9DPcbbjaTIWExLREREqsVEhYiIiFSLicoNWK1W/OxnP4PValU6lBHDY9QHHqN+GOE4eYz6MNrHqOliWiIiItI3jqgQERGRajFRISIiItViokJERESqxUSFiIiIVIuJChEREakWE5Vr/PrXv8bYsWMRGRmJkpISHDlyROmQBu3nP/85TCZTv6/CwsLQ/S6XC2vXrkVKSgpiY2PxxBNPoKmpScGIb2/fvn1YtWoVsrOzYTKZ8NFHH/W7XwiBn/70p8jKykJUVBSWLFmCCxcu9HtMe3s71qxZg/j4eCQmJuJv/uZv0NXVNYpHcXu3O85nn332unO7fPnyfo9R83GuX78e8+bNQ1xcHNLT0/H444+jsrKy32MG8vtZU1ODlStXIjo6Gunp6fjBD34An883modySwM5zkWLFl13Lr/zne/0e4yaj/Ott97C9OnTQ11KFyxYgO3bt4fu18N5vN0xav0c3sjrr78Ok8mEV155JXSbYudSUMimTZuExWIRf/jDH0RFRYV44YUXRGJiomhqalI6tEH52c9+JqZNmyYaGhpCXy0tLaH7v/Od74jc3Fyxe/ducfToUXHXXXeJhQsXKhjx7W3btk385Cc/EX/5y18EAPHhhx/2u//1118XCQkJ4qOPPhKnTp0Sjz76qBg3bpzo6ekJPWb58uVixowZ4tChQ+LLL78UEyZMEE8//fQoH8mt3e44n3nmGbF8+fJ+57a9vb3fY9R8nMuWLRNvv/22KC8vFydPnhQPP/ywyMvLE11dXaHH3O730+fziaKiIrFkyRJx4sQJsW3bNpGamirWrVunxCHd0ECO8/777xcvvPBCv3Nps9lC96v9OD/55BOxdetWcf78eVFZWSl+/OMfi4iICFFeXi6E0Md5vN0xav0cXuvIkSNi7NixYvr06eLll18O3a7UuWSi0sf8+fPF2rVrQ9/7/X6RnZ0t1q9fr2BUg/ezn/1MzJgx44b3dXZ2ioiICPHBBx+Ebjt79qwAIA4ePDhKEQ7NtR/gkiSJzMxM8S//8i+h2zo7O4XVahXvvfeeEEKIM2fOCACitLQ09Jjt27cLk8kk6uvrRy32O3GzROWxxx676b/R2nE2NzcLAGLv3r1CiIH9fm7btk2YzWbR2NgYesxbb70l4uPjhdvtHt0DGKBrj1OIwIdc3w+Da2nxOJOSksTvfvc73Z5HIXqPUQh9nUOHwyEmTpwodu3a1e+4lDyXnPoJ8ng8OHbsGJYsWRK6zWw2Y8mSJTh48KCCkQ3NhQsXkJ2djYKCAqxZswY1NTUAgGPHjsHr9fY73sLCQuTl5Wn2eKurq9HY2NjvmBISElBSUhI6poMHDyIxMRFz584NPWbJkiUwm804fPjwqMc8FHv27EF6ejomT56MF198EW1tbaH7tHacNpsNAJCcnAxgYL+fBw8eRHFxMTIyMkKPWbZsGex2OyoqKkYx+oG79jhlGzZsQGpqKoqKirBu3To4nc7QfVo6Tr/fj02bNqG7uxsLFizQ5Xm89hhlejmHa9euxcqVK/udM0DZ16Smd08eTq2trfD7/f3+gwEgIyMD586dUyiqoSkpKcE777yDyZMno6GhAa+99hruvfdelJeXo7GxERaLBYmJif3+TUZGBhobG5UJeIjkuG90DuX7GhsbkZ6e3u/+8PBwJCcna+q4ly9fjq997WsYN24cLl68iB//+MdYsWIFDh48iLCwME0dpyRJeOWVV3D33XejqKgIAAb0+9nY2HjDcy3fpzY3Ok4AWL16NfLz85GdnY3Tp0/jhz/8ISorK/GXv/wFgDaOs6ysDAsWLIDL5UJsbCw+/PBDTJ06FSdPntTNebzZMQL6OIcAsGnTJhw/fhylpaXX3afka5KJio6tWLEi9Pfp06ejpKQE+fn5+OMf/4ioqCgFI6Oheuqpp0J/Ly4uxvTp0zF+/Hjs2bMHixcvVjCyO7d27VqUl5dj//79Socyom52nN/+9rdDfy8uLkZWVhYWL16MixcvYvz48aMd5qBMnjwZJ0+ehM1mw5/+9Cc888wz2Lt3r9JhDaubHePUqVN1cQ5ra2vx8ssvY9euXYiMjFQ6nH449ROUmpqKsLCw6yqYm5qakJmZqVBUwysxMRGTJk1CVVUVMjMz4fF40NnZ2e8xWj5eOe5bncPMzEw0Nzf3u9/n86G9vV2zxw0ABQUFSE1NRVVVFQDtHOdLL72ELVu24IsvvkBOTk7o9oH8fmZmZt7wXMv3qcnNjvNGSkpKAKDfuVT7cVosFkyYMAFz5szB+vXrMWPGDPzqV7/S1Xm82THeiBbP4bFjx9Dc3IzZs2cjPDwc4eHh2Lt3L/793/8d4eHhyMjIUOxcMlEJslgsmDNnDnbv3h26TZIk7N69u988pJZ1dXXh4sWLyMrKwpw5cxAREdHveCsrK1FTU6PZ4x03bhwyMzP7HZPdbsfhw4dDx7RgwQJ0dnbi2LFjocd8/vnnkCQp9OaiRXV1dWhra0NWVhYA9R+nEAIvvfQSPvzwQ3z++ecYN25cv/sH8vu5YMEClJWV9UvIdu3ahfj4+NCQvNJud5w3cvLkSQDody7VfpzXkiQJbrdbN+fxRuRjvBEtnsPFixejrKwMJ0+eDH3NnTsXa9asCf1dsXM56DJcHdq0aZOwWq3inXfeEWfOnBHf/va3RWJiYr8KZi35+7//e7Fnzx5RXV0tDhw4IJYsWSJSU1NFc3OzECKw1CwvL098/vnn4ujRo2LBggViwYIFCkd9aw6HQ5w4cUKcOHFCABC//OUvxYkTJ8SVK1eEEIHlyYmJieLjjz8Wp0+fFo899tgNlyfPmjVLHD58WOzfv19MnDhRNct2Zbc6TofDIb7//e+LgwcPiurqavHZZ5+J2bNni4kTJwqXyxV6DjUf54svvigSEhLEnj17+i3pdDqdocfc7vdTXgr50EMPiZMnT4odO3aItLQ0VS35vN1xVlVVif/9v/+3OHr0qKiurhYff/yxKCgoEPfdd1/oOdR+nD/60Y/E3r17RXV1tTh9+rT40Y9+JEwmk9i5c6cQQh/n8VbHqIdzeDPXrmZS6lwyUbnGm2++KfLy8oTFYhHz588Xhw4dUjqkQXvyySdFVlaWsFgsYsyYMeLJJ58UVVVVoft7enrE3/3d34mkpCQRHR0t/uqv/ko0NDQoGPHtffHFFwLAdV/PPPOMECKwRPl//a//JTIyMoTVahWLFy8WlZWV/Z6jra1NPP300yI2NlbEx8eL5557TjgcDgWO5uZudZxOp1M89NBDIi0tTURERIj8/HzxwgsvXJdQq/k4b3RsAMTbb78desxAfj8vX74sVqxYIaKiokRqaqr4+7//e+H1ekf5aG7udsdZU1Mj7rvvPpGcnCysVquYMGGC+MEPftCvB4cQ6j7O559/XuTn5wuLxSLS0tLE4sWLQ0mKEPo4j7c6Rj2cw5u5NlFR6lyahBBi8OMxRERERCOHNSpERESkWkxUiIiISLWYqBAREZFqMVEhIiIi1WKiQkRERKrFRIWIiIhUi4kKERERqRYTFSIiIlItJipERESkWkxUiIiISLWYqBAREZFq/f9+sVkC0e+3XQAAAABJRU5ErkJggg==",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"for feat in ['nodes', 'exploit', 'appl', 'load']:\n",
" plt.figure()\n",
" plt.plot(timing_df[feat], timing_df['runtime'])\n",
" plt.title(feat)\n",
" plt.ylabel('runtime')"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"## Show avg timing data for each var step (EX: Avg time for 12 nodes, 11...1, Avg time for 6 exploits...49152)\n"
]
},
{
"cell_type": "code",
"execution_count": 78,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/tmp/ipykernel_1934/3831858898.py:5: SettingWithCopyWarning:\n",
"\n",
"\n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
"\n",
"/tmp/ipykernel_1934/3831858898.py:6: SettingWithCopyWarning:\n",
"\n",
"\n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
"\n",
"/tmp/ipykernel_1934/3831858898.py:7: SettingWithCopyWarning:\n",
"\n",
"\n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
"\n",
"/tmp/ipykernel_1934/3831858898.py:8: SettingWithCopyWarning:\n",
"\n",
"\n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
"\n",
"/tmp/ipykernel_1934/3831858898.py:9: SettingWithCopyWarning:\n",
"\n",
"\n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
"\n"
]
},
{
"data": {
"text/plain": [
"<AxesSubplot: title={'center': 'Database Load vs Runtime'}, xlabel='Database Load (%)', ylabel='Runtime (ms)'>"
]
},
"execution_count": 78,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"node_pivot = timing_df.pivot_table(index=[\"nodes\"], values=[\"runtime\"], aggfunc='mean')\n",
"exploit_pivot = timing_df.pivot_table(index=[\"exploit\"], values=[\"runtime\"], aggfunc='mean')\n",
"appl_pivot = timing_df.pivot_table(index=[\"appl\"], values=[\"runtime\"], aggfunc='mean')\n",
"\n",
"overall_df['load'] = overall_df['load'].replace(395,0)\n",
"overall_df['load'] = overall_df['load'].replace(296,25)\n",
"overall_df['load'] = overall_df['load'].replace(197,50)\n",
"overall_df['load'] = overall_df['load'].replace(79,75)\n",
"overall_df['load'] = overall_df['load'].replace(1,100)\n",
"load_pivot = overall_df.pivot_table(index=[\"load\"], values=[\"runtime\"], aggfunc='mean')\n",
"\n",
"node_pivot.plot(kind='bar', title='Number of Nodes vs Runtime', ylabel='Runtime (ms)', xlabel=\"Nodes\")\n",
"exploit_pivot.plot(kind='bar', title='Number of Exploits vs Runtime', ylabel='Runtime (ms)', xlabel=\"Number of Exploits\")\n",
"appl_pivot.plot(kind='bar', title='Applicability of Exploits vs Runtime', ylabel='Runtime (ms)', xlabel=\"Applicability of Exploits (%)\")\n",
"load_pivot.plot(kind='bar', title='Database Load vs Runtime', ylabel='Runtime (ms)', xlabel=\"Database Load (%)\")\n"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"## Correlation and Matrix Plot"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<AxesSubplot: >"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 1100x700 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"timing_corr = timing_df.corr().round(3)\n",
"# print(timing_corr)\n",
"fig, ax = plt.subplots()\n",
"fig.set_size_inches(11, 7)\n",
"sns.heatmap(timing_corr, annot=True, fmt=\".1f\", cmap=\"RdBu\", center=0, ax=ax)"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"## Speedup"
]
},
{
"cell_type": "code",
"execution_count": 82,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"572.125"
]
},
"execution_count": 82,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"timing_df['runtime'][timing_df['nodes'] == 1][timing_df['exploit']==6][timing_df['appl']==0][timing_df['load']==1].values[0]"
]
},
{
"cell_type": "code",
"execution_count": 108,
"metadata": {},
"outputs": [],
"source": [
"spd_df = pd.DataFrame(columns=['Nodes', 'Speedup'])\n",
"for node in [2,3,4,5,6,7,8,9,10,11,12]:\n",
" for expl in [6,12,24,48,96,192,384,768,1536,3072,6144]:\n",
" for app in [0,25,50,75,100]:\n",
" for load in [1,79,197,296,395]:\n",
" try:\n",
" spd_df.loc[-1] = [node, timing_df['runtime'][timing_df['nodes'] == 1][timing_df['exploit']==expl][timing_df['appl']==app][timing_df['load']==load].values[0]/timing_df['runtime'][timing_df['nodes'] == node][timing_df['exploit']==expl][timing_df['appl']==app][timing_df['load']==load].values[0]]\n",
" spd_df.index = spd_df.index+1\n",
" spd_df = spd_df.sort_index()\n",
" except:\n",
" tmp=0\n"
]
},
{
"cell_type": "code",
"execution_count": 127,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/tmp/ipykernel_1934/1804375556.py:4: FutureWarning:\n",
"\n",
"DataFrame.set_axis 'inplace' keyword is deprecated and will be removed in a future version. Use `obj = obj.set_axis(..., copy=False)` instead\n",
"\n"
]
},
{
"data": {
"text/plain": [
"<AxesSubplot: title={'center': 'Minimum, Maximum, and Mean Speedups of MPI Tasking for Increasing Problem Sizes'}, xlabel='Number of Nodes', ylabel=\"Speedup (Amdahl's)\">"
]
},
"execution_count": 127,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"res_spd_df = pd.DataFrame(spd_df.pivot_table(index=[\"Nodes\"], values=[\"Speedup\"], aggfunc=['max', 'min', 'mean']).to_records())\n",
"res_spd_df.set_axis(['Nodes', 'Max', 'Min', 'Mean'], axis=1, inplace=True)\n",
"res_spd_df.plot(kind='bar', x='Nodes', title='Minimum, Maximum, and Mean Speedups of MPI Tasking for Increasing Problem Sizes', ylabel=\"Speedup (Amdahl's)\", xlabel=\"Number of Nodes\")\n"
]
},
{
"cell_type": "code",
"execution_count": 128,
"metadata": {},
"outputs": [],
"source": [
"eff_df = pd.DataFrame(columns=['Nodes', 'Efficiency'])\n",
"for node in [2,3,4,5,6,7,8,9,10,11,12]:\n",
" for expl in [6,12,24,48,96,192,384,768,1536,3072,6144]:\n",
" for app in [0,25,50,75,100]:\n",
" for load in [1,79,197,296,395]:\n",
" try:\n",
" eff_df.loc[-1] = [node, timing_df['runtime'][timing_df['nodes'] == 1][timing_df['exploit']==expl][timing_df['appl']==app][timing_df['load']==load].values[0]/(timing_df['runtime'][timing_df['nodes'] == node][timing_df['exploit']==expl][timing_df['appl']==app][timing_df['load']==load].values[0]*node)]\n",
" eff_df.index = eff_df.index+1\n",
" eff_df = eff_df.sort_index()\n",
" except:\n",
" tmp=0"
]
},
{
"cell_type": "code",
"execution_count": 129,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/tmp/ipykernel_1934/4145241967.py:2: FutureWarning:\n",
"\n",
"DataFrame.set_axis 'inplace' keyword is deprecated and will be removed in a future version. Use `obj = obj.set_axis(..., copy=False)` instead\n",
"\n"
]
},
{
"data": {
"text/plain": [
"<AxesSubplot: title={'center': 'Minimum, Maximum, and Mean Efficiencies of MPI Tasking for Increasing Problem Sizes'}, xlabel='Number of Nodes', ylabel='Efficiency'>"
]
},
"execution_count": 129,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"res_eff_df = pd.DataFrame(eff_df.pivot_table(index=[\"Nodes\"], values=[\"Efficiency\"], aggfunc=['max', 'min', 'mean']).to_records())\n",
"res_eff_df.set_axis(['Nodes', 'Max', 'Min', 'Mean'], axis=1, inplace=True)\n",
"res_eff_df.plot(kind='bar', x='Nodes', title='Minimum, Maximum, and Mean Efficiencies of MPI Tasking for Increasing Problem Sizes', ylabel=\"Efficiency\", xlabel=\"Number of Nodes\")\n"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"# Linear Regression"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"## Indiv Vars\n",
"### Linear Regression - Overall Runtime\n",
"#### Nodes"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"intercept 303728.87235091545\n",
" Predictor coefficient\n",
"0 nodes -32534.157117\n",
"\n",
"Regression statistics\n",
"\n",
" Mean Error (ME) : -0.0000\n",
" Root Mean Squared Error (RMSE) : 442361.0172\n",
" Mean Absolute Error (MAE) : 198916.6752\n",
" Mean Percentage Error (MPE) : -3076.0279\n",
"Mean Absolute Percentage Error (MAPE) : 3664.0029\n"
]
}
],
"source": [
"predictors = ['nodes']\n",
"overall_outcome = 'runtime'\n",
"\n",
"# partition data\n",
"X = timing_df[predictors]\n",
"overall_y = timing_df[overall_outcome]\n",
"train_X, valid_X, train_y, valid_y = train_test_split(X, overall_y, test_size=0.4, random_state=1)\n",
"runtime_lm = LinearRegression()\n",
"runtime_lm.fit(train_X, train_y)\n",
"# print coefficients\n",
"print('intercept ', runtime_lm.intercept_)\n",
"print(pd.DataFrame({'Predictor': X.columns, 'coefficient': runtime_lm.coef_}))\n",
"# print performance measures\n",
"regressionSummary(train_y, runtime_lm.predict(train_X))"
]
},
{
"cell_type": "code",
"execution_count": 74,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"intercept 0.06488133316235689\n",
" Predictor coefficient\n",
"0 nodes -0.085788\n",
"\n",
"Regression statistics\n",
"\n",
" Mean Error (ME) : 0.0000\n",
" Root Mean Squared Error (RMSE) : 0.1060\n",
" Mean Absolute Error (MAE) : 0.0477\n",
" Mean Percentage Error (MPE) : -32832.1198\n",
"Mean Absolute Percentage Error (MAPE) : 33548.5134\n"
]
}
],
"source": [
"scaler = preprocessing.MinMaxScaler()\n",
"d = scaler.fit_transform(timing_df)\n",
"normalized_df = pd.DataFrame(d, columns=timing_df.columns)\n",
"\n",
"predictors = ['nodes']\n",
"overall_outcome = 'runtime'\n",
"\n",
"# partition data\n",
"X = normalized_df[predictors]\n",
"overall_y = normalized_df[overall_outcome]\n",
"train_X, valid_X, train_y, valid_y = train_test_split(X, overall_y, test_size=0.4, random_state=1)\n",
"runtime_lm = LinearRegression()\n",
"runtime_lm.fit(train_X, train_y)\n",
"# print coefficients\n",
"print('intercept ', runtime_lm.intercept_)\n",
"print(pd.DataFrame({'Predictor': X.columns, 'coefficient': runtime_lm.coef_}))\n",
"# print performance measures\n",
"regressionSummary(train_y, runtime_lm.predict(train_X))\n"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Exploit"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"intercept -8788.042556187662\n",
" Predictor coefficient\n",
"0 exploit 50.283347\n",
"\n",
"Regression statistics\n",
"\n",
" Mean Error (ME) : -0.0000\n",
" Root Mean Squared Error (RMSE) : 197437.6040\n",
" Mean Absolute Error (MAE) : 62749.3897\n",
" Mean Percentage Error (MPE) : 180.5994\n",
"Mean Absolute Percentage Error (MAPE) : 275.3917\n"
]
}
],
"source": [
"predictors = ['exploit']\n",
"overall_outcome = 'runtime'\n",
"\n",
"# partition data\n",
"X = timing_df[predictors]\n",
"overall_y = timing_df[overall_outcome]\n",
"train_X, valid_X, train_y, valid_y = train_test_split(X, overall_y, test_size=0.4, random_state=1)\n",
"runtime_lm = LinearRegression()\n",
"runtime_lm.fit(train_X, train_y)\n",
"# print coefficients\n",
"print('intercept ', runtime_lm.intercept_)\n",
"print(pd.DataFrame({'Predictor': X.columns, 'coefficient': runtime_lm.coef_}))\n",
"# print performance measures\n",
"regressionSummary(train_y, runtime_lm.predict(train_X))"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Appl"
]
},
{
"cell_type": "code",
"execution_count": 60,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"intercept 42450.91771345622\n",
" Predictor coefficient\n",
"0 appl 1748.317923\n",
"\n",
"Regression statistics\n",
"\n",
" Mean Error (ME) : -0.0000\n",
" Root Mean Squared Error (RMSE) : 454831.8590\n",
" Mean Absolute Error (MAE) : 186480.9214\n",
" Mean Percentage Error (MPE) : -2691.9685\n",
"Mean Absolute Percentage Error (MAPE) : 2705.9283\n"
]
},
{
"data": {
"text/plain": [
"[<matplotlib.lines.Line2D at 0x6fd6c0c1dc30>]"
]
},
"execution_count": 60,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"predictors = ['appl']\n",
"overall_outcome = 'runtime'\n",
"\n",
"# partition data\n",
"X = timing_df[predictors]\n",
"overall_y = timing_df[overall_outcome]\n",
"train_X, valid_X, train_y, valid_y = train_test_split(X, overall_y, test_size=0.4, random_state=1)\n",
"runtime_lm = LinearRegression()\n",
"runtime_lm.fit(train_X, train_y)\n",
"# print coefficients\n",
"print('intercept ', runtime_lm.intercept_)\n",
"print(pd.DataFrame({'Predictor': X.columns, 'coefficient': runtime_lm.coef_}))\n",
"# print performance measures\n",
"regressionSummary(train_y, runtime_lm.predict(train_X))"
]
},
{
"cell_type": "code",
"execution_count": 75,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"intercept 0.010048066606673962\n",
" Predictor coefficient\n",
"0 appl 0.04191\n",
"\n",
"Regression statistics\n",
"\n",
" Mean Error (ME) : 0.0000\n",
" Root Mean Squared Error (RMSE) : 0.1090\n",
" Mean Absolute Error (MAE) : 0.0447\n",
" Mean Percentage Error (MPE) : -17606.2312\n",
"Mean Absolute Percentage Error (MAPE) : 17620.2063\n"
]
}
],
"source": [
"scaler = preprocessing.MinMaxScaler()\n",
"d = scaler.fit_transform(timing_df)\n",
"normalized_df = pd.DataFrame(d, columns=timing_df.columns)\n",
"\n",
"predictors = ['appl']\n",
"overall_outcome = 'runtime'\n",
"\n",
"# partition data\n",
"X = normalized_df[predictors]\n",
"overall_y = normalized_df[overall_outcome]\n",
"train_X, valid_X, train_y, valid_y = train_test_split(X, overall_y, test_size=0.4, random_state=1)\n",
"runtime_lm = LinearRegression()\n",
"runtime_lm.fit(train_X, train_y)\n",
"# print coefficients\n",
"print('intercept ', runtime_lm.intercept_)\n",
"print(pd.DataFrame({'Predictor': X.columns, 'coefficient': runtime_lm.coef_}))\n",
"# print performance measures\n",
"regressionSummary(train_y, runtime_lm.predict(train_X))"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Load"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"intercept 445536.13965568773\n",
" Predictor coefficient\n",
"0 load -1015.396933\n",
"\n",
"Regression statistics\n",
"\n",
" Mean Error (ME) : -0.0000\n",
" Root Mean Squared Error (RMSE) : 442633.9662\n",
" Mean Absolute Error (MAE) : 186136.1892\n",
" Mean Percentage Error (MPE) : -3308.5538\n",
"Mean Absolute Percentage Error (MAPE) : 3331.5614\n"
]
}
],
"source": [
"predictors = ['load']\n",
"overall_outcome = 'runtime'\n",
"\n",
"# partition data\n",
"X = timing_df[predictors]\n",
"overall_y = timing_df[overall_outcome]\n",
"train_X, valid_X, train_y, valid_y = train_test_split(X, overall_y, test_size=0.4, random_state=1)\n",
"runtime_lm = LinearRegression()\n",
"runtime_lm.fit(train_X, train_y)\n",
"# print coefficients\n",
"print('intercept ', runtime_lm.intercept_)\n",
"print(pd.DataFrame({'Predictor': X.columns, 'coefficient': runtime_lm.coef_}))\n",
"# print performance measures\n",
"regressionSummary(train_y, runtime_lm.predict(train_X))"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"## All Vars"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"### Linear Regression - Overall Runtime"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"intercept -58054.89252320345\n",
" Predictor coefficient\n",
"0 nodes -872.584718\n",
"1 exploit 49.805953\n",
"2 appl 1575.244214\n",
"3 load -68.075156\n",
"\n",
"Regression statistics\n",
"\n",
" Mean Error (ME) : 0.0000\n",
" Root Mean Squared Error (RMSE) : 189043.5348\n",
" Mean Absolute Error (MAE) : 82436.8687\n",
" Mean Percentage Error (MPE) : 334.3634\n",
"Mean Absolute Percentage Error (MAPE) : 1191.8060\n"
]
}
],
"source": [
"predictors = ['nodes', 'exploit', 'appl', 'load']\n",
"overall_outcome = 'runtime'\n",
"\n",
"# partition data\n",
"X = timing_df[predictors]\n",
"overall_y = timing_df[overall_outcome]\n",
"train_X, valid_X, train_y, valid_y = train_test_split(X, overall_y, test_size=0.4, random_state=1)\n",
"runtime_lm = LinearRegression()\n",
"runtime_lm.fit(train_X, train_y)\n",
"# print coefficients\n",
"print('intercept ', runtime_lm.intercept_)\n",
"print(pd.DataFrame({'Predictor': X.columns, 'coefficient': runtime_lm.coef_}))\n",
"# print performance measures\n",
"regressionSummary(train_y, runtime_lm.predict(train_X))"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"### Linear Regression - Task 0"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"intercept 0.0\n",
" Predictor coefficient\n",
"0 nodes 0.0\n",
"1 exploit 0.0\n",
"2 appl 0.0\n",
"3 load 0.0\n",
"\n",
"Regression statistics\n",
"\n",
" Mean Error (ME) : 0.0000\n",
"Root Mean Squared Error (RMSE) : 0.0000\n",
" Mean Absolute Error (MAE) : 0.0000\n"
]
}
],
"source": [
"# Linear Regression - Task 0\n",
"t0_outcome = 'task0'\n",
"\n",
"# partition data\n",
"X = timing_df[predictors]\n",
"overall_y = timing_df[t0_outcome]\n",
"train_X, valid_X, train_y, valid_y = train_test_split(X, overall_y, test_size=0.4, random_state=1)\n",
"t0_lm = LinearRegression()\n",
"t0_lm.fit(train_X, train_y)\n",
"# print coefficients\n",
"print('intercept ', t0_lm.intercept_)\n",
"print(pd.DataFrame({'Predictor': X.columns, 'coefficient': t0_lm.coef_}))\n",
"# print performance measures\n",
"regressionSummary(train_y, t0_lm.predict(train_X))"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"### Linear Regression - Task 1"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"intercept -8930.11863104882\n",
" Predictor coefficient\n",
"0 nodes -232.287083\n",
"1 exploit 18.859014\n",
"2 appl 151.902207\n",
"3 load -7.775745\n",
"\n",
"Regression statistics\n",
"\n",
" Mean Error (ME) : -0.0000\n",
" Root Mean Squared Error (RMSE) : 19547.1452\n",
" Mean Absolute Error (MAE) : 11878.2487\n",
" Mean Percentage Error (MPE) : 766.9344\n",
"Mean Absolute Percentage Error (MAPE) : 912.9252\n"
]
}
],
"source": [
"# Linear Regression - Task 1\n",
"t1_outcome = 'task1'\n",
"\n",
"# partition data\n",
"X = timing_df[predictors]\n",
"overall_y = timing_df[t1_outcome]\n",
"train_X, valid_X, train_y, valid_y = train_test_split(X, overall_y, test_size=0.4, random_state=1)\n",
"t1_lm = LinearRegression()\n",
"t1_lm.fit(train_X, train_y)\n",
"# print coefficients\n",
"print('intercept ', t1_lm.intercept_)\n",
"print(pd.DataFrame({'Predictor': X.columns, 'coefficient': t1_lm.coef_}))\n",
"# print performance measures\n",
"regressionSummary(train_y, t1_lm.predict(train_X))"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"### Linear Regression - Task 2"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"intercept -33033.61791812297\n",
" Predictor coefficient\n",
"0 nodes 98.141525\n",
"1 exploit 28.211256\n",
"2 appl 1191.485769\n",
"3 load -114.265223\n",
"\n",
"Regression statistics\n",
"\n",
" Mean Error (ME) : 0.0000\n",
" Root Mean Squared Error (RMSE) : 164019.5175\n",
" Mean Absolute Error (MAE) : 67768.4301\n",
" Mean Percentage Error (MPE) : 14109.3156\n",
"Mean Absolute Percentage Error (MAPE) : 40718.5528\n"
]
}
],
"source": [
"# Linear Regression - Task 2\n",
"t2_outcome = 'task2'\n",
"\n",
"# partition data\n",
"X = timing_df[predictors]\n",
"overall_y = timing_df[t2_outcome]\n",
"train_X, valid_X, train_y, valid_y = train_test_split(X, overall_y, test_size=0.4, random_state=1)\n",
"t2_lm = LinearRegression()\n",
"t2_lm.fit(train_X, train_y)\n",
"# print coefficients\n",
"print('intercept ', t2_lm.intercept_)\n",
"print(pd.DataFrame({'Predictor': X.columns, 'coefficient': t2_lm.coef_}))\n",
"# print performance measures\n",
"regressionSummary(train_y, t2_lm.predict(train_X))"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"### Linear Regression - Task 3"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"intercept 64.74568294128446\n",
" Predictor coefficient\n",
"0 nodes 20.863592\n",
"1 exploit -0.002906\n",
"2 appl -0.027356\n",
"3 load 0.227492\n",
"\n",
"Regression statistics\n",
"\n",
" Mean Error (ME) : -0.0000\n",
" Root Mean Squared Error (RMSE) : 95.9494\n",
" Mean Absolute Error (MAE) : 80.7147\n",
" Mean Percentage Error (MPE) : -48.7684\n",
"Mean Absolute Percentage Error (MAPE) : 77.1556\n"
]
}
],
"source": [
"# Linear Regression - Task 3\n",
"t3_outcome = 'task3'\n",
"\n",
"# partition data\n",
"X = timing_df[predictors]\n",
"overall_y = timing_df[t3_outcome]\n",
"train_X, valid_X, train_y, valid_y = train_test_split(X, overall_y, test_size=0.4, random_state=1)\n",
"t3_lm = LinearRegression()\n",
"t3_lm.fit(train_X, train_y)\n",
"# print coefficients\n",
"print('intercept ', t3_lm.intercept_)\n",
"print(pd.DataFrame({'Predictor': X.columns, 'coefficient': t3_lm.coef_}))\n",
"# print performance measures\n",
"regressionSummary(train_y, t3_lm.predict(train_X))"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"### Linear Regression - Task 4"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"intercept 346.4317371043873\n",
" Predictor coefficient\n",
"0 nodes -2.648924\n",
"1 exploit 0.000311\n",
"2 appl 0.000503\n",
"3 load -0.696739\n",
"\n",
"Regression statistics\n",
"\n",
" Mean Error (ME) : 0.0000\n",
"Root Mean Squared Error (RMSE) : 150.2358\n",
" Mean Absolute Error (MAE) : 111.7243\n"
]
}
],
"source": [
"# Linear Regression - Task 4\n",
"t4_outcome = 'task4'\n",
"\n",
"# partition data\n",
"X = timing_df[predictors]\n",
"overall_y = timing_df[t4_outcome]\n",
"train_X, valid_X, train_y, valid_y = train_test_split(X, overall_y, test_size=0.4, random_state=1)\n",
"t4_lm = LinearRegression()\n",
"t4_lm.fit(train_X, train_y)\n",
"# print coefficients\n",
"print('intercept ', t4_lm.intercept_)\n",
"print(pd.DataFrame({'Predictor': X.columns, 'coefficient': t4_lm.coef_}))\n",
"# print performance measures\n",
"regressionSummary(train_y, t4_lm.predict(train_X))"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"### Linear Regression - Task 5"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"intercept 3.2276550472205336\n",
" Predictor coefficient\n",
"0 nodes -0.344255\n",
"1 exploit 0.000049\n",
"2 appl 0.001636\n",
"3 load -0.001017\n",
"\n",
"Regression statistics\n",
"\n",
" Mean Error (ME) : 0.0000\n",
"Root Mean Squared Error (RMSE) : 1.8391\n",
" Mean Absolute Error (MAE) : 1.4637\n"
]
}
],
"source": [
"# Linear Regression - Task 5\n",
"t5_outcome = 'task5'\n",
"\n",
"# partition data\n",
"X = timing_df[predictors]\n",
"overall_y = timing_df[t5_outcome]\n",
"train_X, valid_X, train_y, valid_y = train_test_split(X, overall_y, test_size=0.4, random_state=1)\n",
"t5_lm = LinearRegression()\n",
"t5_lm.fit(train_X, train_y)\n",
"# print coefficients\n",
"print('intercept ', t5_lm.intercept_)\n",
"print(pd.DataFrame({'Predictor': X.columns, 'coefficient': t5_lm.coef_}))\n",
"# print performance measures\n",
"regressionSummary(train_y, t5_lm.predict(train_X))"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"# Nonlinear Regression"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"## Random Forest"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"### Nodes"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/noah/.local/lib/python3.10/site-packages/sklearn/base.py:420: UserWarning: X does not have valid feature names, but RandomForestRegressor was fitted with feature names\n",
" warnings.warn(\n"
]
},
{
"data": {
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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Random Forest\n",
"#predictors = ['nodes', 'exploit', 'appl', 'load']\n",
"predictors = ['nodes']\n",
"overall_outcome = 'runtime'\n",
"\n",
"# partition data\n",
"X = timing_df[predictors]\n",
"overall_y = timing_df[overall_outcome]\n",
"train_X, valid_X, train_y, valid_y = train_test_split(X, overall_y, test_size=0.4, random_state=1)\n",
"\n",
"regressor = RandomForestRegressor(n_estimators = 10, random_state = 0)\n",
"regressor.fit(train_X, train_y)\n",
"\n",
"X_grid = np.arange(0, 12, 1)\n",
"X_grid = X_grid.reshape((len(X_grid),1))\n",
"plt.scatter(X, overall_y, color = 'red')\n",
"plt.plot(X_grid, regressor.predict(X_grid), color = 'blue')\n",
"plt.title('Random Forest Regression')\n",
"plt.show()"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"### Exploit"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/noah/.local/lib/python3.10/site-packages/sklearn/base.py:420: UserWarning: X does not have valid feature names, but RandomForestRegressor was fitted with feature names\n",
" warnings.warn(\n"
]
},
{
"data": {
"image/png": 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wMNBpOqF27dpObamK6OhoDRs2TEuXLtXmzZslSQMGDNCXX36ppUuXlqg/duyYo209e/bUqVOn9OabbzrWFxUVadq0aRXe/4ABA2Sz2fS3v/2txLrTp087vr7ffvutRJ8Vn01V3CfF/VcsMDBQ7dq1c6o515VXXqnY2Fi99tprTjWLFy/W9u3b1atXrwp/LYBVvPKU2X379mnGjBnat2+fGjZsKEl67LHHtGTJEs2YMUMTJkzQTz/9pJ9//lmzZ8/Wv//9b9lsNj3yyCPq379/hU8xhO8aM2aMbr75Zs2cOVP333+/brjhBmVmZuqmm25Sr169tGfPHr322mtq3bq18vPzq7SPjIwM9erVS126dNHQoUN19OhRTZ06VZdcconTNnv37q1u3brpiSee0N69e3XppZdq2bJlWrBggUaNGlWl00Fd7cUXX1RaWpo6deqku+++23HKbFRUlJ5++unzvj8pKUnPPvusxo0bp71796pv376KiIjQnj17NG/ePN1333167LHHtHLlSo0YMUI333yzWrZsqdOnT+udd95RUFCQ+vXr59he+/bttWLFCv39739Xw4YN1axZM8eBs5UxcuRITZkyRc8//7xmzZqlMWPG6MMPP9QNN9ygIUOGqH379jp+/Li2bNmiOXPmaO/evYqJiVHfvn3VoUMHjR49Wrt27VKrVq304YcfOv5oqchIzDXXXKNhw4YpIyNDmzdv1nXXXaeaNWtq586dmj17tl566SX1799fb7/9tl599VXddNNNSkpKUl5ent58801FRkY6Al/xH0zXXnutGjdurJ9//llTp07VZZdd5jg26Fw1a9bUCy+8oLvuukvXXHONBg4c6DhltmnTpnrkkUcq3Z+A23nqtJmzSTLz5s1zvC4+5at27dpOjxo1apgBAwYYY4y59957jSSzY8cOx/s2bdpkJJkffvjB6i8BblB8KmhppxrabDaTlJRkkpKSzOnTp01RUZGZMGGCadKkiQkJCTGXX365WbhwoRk8eLDT6a3Fp1+++OKLJbYpyYwfP95p2dy5c80f/vAHExISYlq3bm0yMzNLbNMYY/Ly8swjjzxiGjZsaGrWrGlatGhhXnzxRVNUVFRiH8OHD3daVlabik+RPN/pp+X109lWrFhhOnfubMLCwkxkZKTp3bu32bZtm1NN8Smzhw8fLnUbc+fONV26dHH8TrZq1coMHz7c8Xv4008/maFDh5qkpCQTGhpq6tata7p162ZWrFjhtJ0ffvjBXH311SYsLMxIKvf02fK+Z8YYM2TIEBMUFOQ4NTkvL8+MGzfONG/e3AQHB5uYmBjzxz/+0UyaNMmcPHnS8b7Dhw+b2267zURERJioqCgzZMgQs3btWiPJzJo1y1E3ePBgU7t27TLb98Ybb5j27dubsLAwExERYdq2bWsef/xx88svvxhjjPn666/NwIEDTWJiogkJCTGxsbHmhhtuMBs3bnRsY86cOea6664zsbGxJjg42CQmJpphw4aZ/fv3O2rOPWW22AcffGAuv/xyExISYurWrWsGDRpk/ve//znVlPU1FH+/AasEGOOBo9TOERAQoHnz5jnuw/DBBx9o0KBB+v7770sc/BQeHq64uDiNHz9eEyZMcDoFraCgQLVq1dKyZcvUo0cPK78EAH5g/vz5uummm/T555+rc+fOnm4O4He8cnrl8ssvl81m06FDhxzXTzhX586ddfr0ae3evdsxfP3jjz9K8vyBewC8X0FBgdMBoDabTVOnTlVkZKSuuOIKD7YM8F8eCx35+flOR4rv2bNHmzdvVt26ddWyZUsNGjRId955pyZPnqzLL79chw8f1ieffKJ27dqpV69eSk1N1RVXXKGhQ4dqypQpKioq0vDhw9WjR48qnxYHoPp46KGHVFBQoE6dOqmwsFCZmZn64osvNGHChAqdjQKg8jw2vbJ69Wp169atxPLBgwdr5syZOnXqlJ599ln9+9//VnZ2tmJiYnTVVVfpmWeecdzG+pdfftFDDz2kZcuWqXbt2kpLS9PkyZOdrroIAKV57733NHnyZO3atUsnTpxQ8+bN9cADD2jEiBGebhrgt7zimA4AAOD/vPY6HQAAwL8QOgAAgCUsP5C0qKhIv/zyiyIiIlxyKWQAAOB+xhjl5eWpYcOGJe5FVFGWh45ffvmlxN00AQCAb8jKyqryzRstDx3FN8TKyspSZGSk1bsHAABVkJubq4SEBKcbW1aW5aGjeEolMjKS0AEAgI+5kEMjOJAUAABYgtABAAAsQegAAACWIHQAAABLEDoAAIAlCB0AAMAShA4AAGAJQgcAALCE5RcHAwAAbmCzSWvWSPv3S/HxUkqKFBTk6VY5IXQAAODrMjOlhx+WsrPPLGvUSHr5ZSk93XPtOgfTKwAA+LLMTKlfP+fAIdlf9+tnX+8lCB0AAPgqm026777ya+67z17nBQgdAAD4qtWrpSNHyq85csRe5wUIHQAA+KqVK11b52aEDgAAfNXeva6tczNCBwAAvurQIdfWuRmhAwAAX1W7tmvr3IzQAQCAr7r6atfWuVmAMcZYucPc3FxFRUUpJydHkZGRVu4aAAD/cvKkFBYmFRWVXRMYKBUUSMHBF7QrV3x+M9IBAICvCg6WRo8uv2b06AsOHK7CZdABAPBlEyfanydPdh7xCAy0B47i9V6A6RUAAPzByZPSq69Ku3dLSUnSgw+6dITDFZ/fjHQAAOAPgoOlUaM83YpyXdAxHc8//7wCAgI0ysu/SAAA4HlVDh0bNmzQ66+/rnbt2rmyPQAAwE9VKXTk5+dr0KBBevPNN1WnTh1XtwkAAPihKoWO4cOHq1evXkpNTT1vbWFhoXJzc50eAACg+qn0gaSzZs3S119/rQ0bNlSoPiMjQ88880ylGwYAAPxLpUY6srKyNHLkSL377rsKDQ2t0HvGjRunnJwcxyMrK6tKDQUAAL6tUtfpmD9/vm666SYFBQU5ltlsNgUEBCgwMFCFhYVO60rDdToAAPA9ll+no3v37tqyZYvTsrvuukutWrXS//3f/503cAAAgOqrUqEjIiJCbdq0cVpWu3Zt1atXr8RyAACAs3HDNwAAYIkLvgz66tWrXdAMAADg7xjpAAAAliB0AAAASxA6AACAJQgdAADAEoQOAABgCUIHAACwBKEDAABYgtABAAAsQegAAACWIHQAAABLEDoAAIAlCB0AAMAShA4AAGAJQgcAALAEoQMAAFiC0AEAACxB6AAAAJYgdAAAAEsQOgAAgCUIHQAAwBKEDgAAYAlCBwAAsAShAwAAWILQAQAALEHoAAAAliB0AAAASxA6AACAJQgdAADAEoQOAABgCUIHAACwBKEDAABYgtABAAAsQegAAACWIHQAAABLEDoAAIAlCB0AAMAShA4AAGAJQgcAALAEoQMAAFiC0AEAACxB6AAAAJYgdAAA4A8KCqQRI6SePe3PBQWeblEJhA4AAHxd375SrVrStGnSsmX251q17Mu9CKEDAABf1revtGBB6esWLPCq4EHoAADAVxUUlB04ii1Y4DVTLYQOAAB81ejRrq1zM0IHAAC+av1619a5GaEDAABYgtABAICvSk11bZ2bEToAAPBVPXq4ts7NCB0AAPiqrl2levXKr6lXz17nBQgdAAD4qqAg6Y03yq954w17nRcgdAAA4MvS06W5c6VGjZyXN25sX56e7pl2laKGpxsAAAAuUHq61KePtGaNtH+/FB8vpaR4zQhHMUIHAAD+ICjIa47dKAvTKwAAwBKEDgAAYAlCBwAAsAShAwAAWILQAQAALEHoAAAAliB0AAAASxA6AACAJQgdAADAEoQOAABgCUIHAACwBKEDAABYgtABAAAsQegAAACWIHQAAABLVCp0TJ8+Xe3atVNkZKQiIyPVqVMnLV682F1tAwAAfqRSoaNx48Z6/vnntWnTJm3cuFHXXnut+vTpo++//95d7QMAAH4iwBhjLmQDdevW1Ysvvqi77767QvW5ubmKiopSTk6OIiMjL2TXAADAIq74/K5R1Z3bbDbNnj1bx48fV6dOncqsKywsVGFhoeN1bm5uVXcJAAB8WKUPJN2yZYvCw8MVEhKi+++/X/PmzVPr1q3LrM/IyFBUVJTjkZCQcEENBgAAvqnS0ysnT57Uvn37lJOTozlz5uitt97Sp59+WmbwKG2kIyEhgekVAAB8iCumVy74mI7U1FQlJSXp9ddfr1A9x3QAAOB7XPH5fcHX6SgqKnIayQAAAChNpQ4kHTdunNLS0pSYmKi8vDy99957Wr16tZYuXequ9gEAAD9RqdBx6NAh3Xnnndq/f7+ioqLUrl07LV26VD169HBX+wAAgJ+oVOj45z//6a52AAAAP8e9VwAAgCUIHQAAwBKEDgAAYAlCBwAAsAShAwAAWILQAQAALEHoAAAAliB0AAAASxA6AACAJQgdAADAEoQOAABgCUIHAACwBKEDAABYgtABAAAsQegAAACWIHQAAABLEDoAAIAlCB0AAMAShA4AAGAJQgcAALAEoQMAAFiC0AEAACxRw9MNAAAALmCzSWvWSPv3S/HxUkqKFBTk6VY5IXQAAODrMjOlkSOl//3vzLLGjaWXXpLS0z3XrnMwvQIAgC/LzJT693cOHJKUnW1fnpnpmXaVgtABAICvstnsIxzGlFxnjP0xapS9zgsQOgAA8FVr1pQc4ThXVpa9zgsQOgAA8FXZ2a6tczNCBwAAvurwYdfWuRmhAwAAX1W/vmvr3IzQAQCAryJ0AAAAS3z7rWvr3IzQAQCAr/riC9fWuRmhAwAAXxUR4do6NyN0AADgq+64w7V1bkboAADAV117rRQeXn5NRIS9zgsQOgAA8FVBQdLbb5dfM3Om19xtltABAIAvS0+X5s6VGjVyXt64sX25F91lllvbAwDg69LTpT597PdY2b9fio+XUlK8ZoSjGKEDAAB/EBQkde3q6VaUi+kVAABgCUIHAACwBKEDAABYgtABAAAsQegAAACWIHQAAABLcMosAECStHixdPvt0vHjnm4JLlR2tlSvnqdbURKhAwAgSfr4Y+noUU+3Av6M0AEAkCQZY39++GHpscc82xZcmOhoT7egdIQOAICkM6EjKkpKSPBsW+CfOJAUAOAkIMDTLYC/InQAACSdGekgdMBdCB0AAElnQgfgLoQOAIATRjrgLoQOAIAkplfgfoQOAIAkplfgfoQOAIATRjrgLoQOAIAkplfgfoQOAIAkQgfcj9ABAJDEMR1wP0IHAMAJIx1wF+69AsA1bDZpzRpp/34pPl5KSZGCgjzdKlQC0ytwN0IHgAuXmWm/NWl29plljRpJL78spad7rl2oFKZX4G5MrwC4MJmZUr9+zoFDsr/u18++Hj6FkQ64C6EDQNXZbNLgweXXDB5sr4PXY3oF7kboAFB1n3wi5eeXX5Ofb6+D1yN0wN0IHQCqbuZM19YB8GuEDgBVt2WLa+vgUYx0wN0IHQCqLirKtXXwKEIH3I3QAaDq+vRxbR0Av1ap0JGRkaHk5GRFREQoNjZWffv21Y4dO9zVNgDebuTI8/9ZHBBgr4PXY6QD7lap0PHpp59q+PDhWrdunZYvX65Tp07puuuu0/Hjx93VPgDeLDhYeuyx8msee8xeB69H6IC7VeqKpEuWLHF6PXPmTMXGxmrTpk26+uqrS31PYWGhCgsLHa9zc3Or0EwAXmviRPvz5MlSUdGZ5YGB0ujRZ9bD6xE64G4XdExHTk6OJKlu3bpl1mRkZCgqKsrxSEhIuJBdAvBGEydKBQXSP/4hjRhhfy4oIHAAcBJgTNWutl9UVKQbb7xRx44d0+eff15mXWkjHQkJCcrJyVFkZGRVdg0AcIPbbpPef9+eGUeN8nRr4G1yc3MVFRV1QZ/fVb7h2/Dhw7V169ZyA4ckhYSEKCQkpKq7AQBYhOkVuFuVQseIESO0cOFCffbZZ2rcuLGr2wQAAPxQpUKHMUYPPfSQ5s2bp9WrV6tZs2buahcAwGKMdMDdKhU6hg8frvfee08LFixQRESEDhw4IEmKiopSWFiYWxoIALAGoQPuVqmzV6ZPn66cnBx17dpV8fHxjscHH3zgrvYBAAA/UenpFQCAf2KkA+7GvVcAAJIIHXA/QgcAQBKhA+5H6AAAAJYgdAAAJDHSAfcjdAAAJBE64H6EDgAAYAlCBwBAEiMdcD9CBwBAEqED7kfoAAA4IXTAXQgdAABJZ0Y6AHchdAAAJDG9AvcjdAAAJBE64H6VuuEbAADwUjabtGaNtH+/FB8vpaRIQUGebpUTQgcAQBIjHT4tM1N6+GEpO/vMskaNpJdfltLTPdeuczC9AsA1cnKkLl2kxET7c06Op1uESiJ0+KjMTKlfP+fAIdlf9+tnX+8lGOkAcOGaN5d27z7zOitLio6WkpKkXbs81ixUDaHDh9hs0qBB5dfcfruUl+cVUy2MdAC4MOcGjrPt3m1fD5/AKbM+aMUK6cSJ8msKCux1XoDQAaDqcnLKDhzFdu9mqsVHML3igyZNcm2dmxE6AFRdr16urYNXIHT4kH37XFvnZoQOAFXnY//hoXxMr/igxETX1rkZoQNA1fnYf3goH9MrPmj0aNfWuRmhA0DVLVrk2jp4BUKHD+nRQwoNLb8mNNRe5wUIHQCqLirKflpseZKS7HXweox0+KCgIOndd8uvefddrzhdViJ0ALhQu3aVHTy4TodP4ZgOH5WeLs2dKzVs6Ly8USP7ci+6IikXBwNw4Xbtsp8W26uX/aDRxET7lAojHD6FkQ4flp4u9enDvVcAVBNRUdLnn3u6FXABQoePCgqSunb1dCvKxfQKAEAS0ytwP0IHAEAS0ytwP0IHAMAJoQPuQugAAEhipAPuR+gAAEjimA64H6EDAOCEkQ64C6fMAhaZO1caPlw6ccLTLQFKl59vfyZ0wF0IHYBFMjOlgwc93QqgfMHBUuvWnm4F/BWhA7BIUZH9+c9/loYM8WhTgDLVqyfVrevpVsBfEToAixQfpBcbK7Vo4dm2AIAncCApYDHmywFUV4QOwCKcjgiguiN0ABbhwksAqjtCB2AxQgeA6orQAViEkQ4A1R2hA7AIx3QAqO4IHYDFGOkAUF0ROgCLML0CoLojdAAWYXoFQHVH6AAsxkgHgOqK0AFYhOkVANUd914BLOL30ys2m7RmjbR/vxQfL6WkSEFBnm4VAC9C6AAs4tcjHZmZ0vDh0oEDZ5bFxUnTpknp6Z5rFwCvwvQKYDG/Cx2ZmVK/fs6BQ7K/7tfPvh4AROgALOOX0ys2m3TrreXX3HqrvQ5AtUfoACzil9MrixdLp06VX3PqlL0OQLVH6AAs5lehY/x419YB8GuEDsAifjnS8dtvrq0D4NcIHYBF/PKYjjZtXFsHwK8ROgCL+dVIx3vvubYOgF8jdAAW8cvplfBwKTm5/JrkZHsdgGqP0AFYxC+nVyRp/fqyg0dysn09AIgrkgKW86uRjmLr10v5+dIdd0i7d0tJSdI77zDCAcAJoQOwiF9Or5wtPFyaN8/TrQDgxZheASzit9MrAFBBhA7AIn4/0gEA50HoACxG6ABQXRE6AIswvQKguuNAUngHm01as0bav1+Kj5dSUqSgIE+3yqWYXgFQ3RE64HmZmdJDD0m//HJmWcOG0tSpUnq659rlJoQOANUV0yvwrMxMqV8/58Ah2V/362df7ycY6QBQ3RE64Dk2m3TrreXXDBxor/MDHNMBoLojdMBzli6VTp0qv+bkSXudH2GkA0B1VenQ8dlnn6l3795q2LChAgICNH/+fDc0C9XCU0+5ts7LMb0CoLqrdOg4fvy4Lr30Uk2bNs0d7UF1cvSoa+u8HNMrAKq7Sp+9kpaWprS0NHe0BdVN27bSnj0Vq/MjjHQAqK7cfspsYWGhCgsLHa9zc3PdvUv4infflSIiKlbnB5heAVDduf1A0oyMDEVFRTkeCQkJ7t4lfEV4uJScXH5NcrLf3B6d6RUA1Z3bQ8e4ceOUk5PjeGRlZbl7l/Al69eXHTySk+3r/QQjHQCqO7dPr4SEhCgkJMTdu4EvW79eys+X7rhD2r1bSkqS3nnHb0Y4zkXoAFBdcRl0eIfwcGnePE+3wq2YXgFQ3VU6dOTn52vXrl2O13v27NHmzZtVt25dJSYmurRxgD9hegVAdVfp0LFx40Z169bN8frRRx+VJA0ePFgzZ850WcMAf0XoAOAWPnC37kqHjq5du8owTgxUGiMdANzGR+7Wzb1XAIv4fVa32aTVq6X337c/+8mN+gCv50N36yZ0wDvk5EhdukiJifbnnBxPt8ht/HKkIzNTatJE6tZNuu02+3OTJl71nx3gl2w2adCg8msGDfKaPwIIHfC85s2l6Ghp7VopK8v+HB1tX+5H/HZ6pfivrOxs5+XZ2V73Vxbgd5Yvl06cKL/mxAl7nRcgdMCzmje3X5ujNLt3+1Xw8MvpFZtNuvXW8msGDvSav7IAvzN5smvr3IzQAc/JySk7cBTbvdvvplr8aqRj2TLp1Knya06etNcBcL19+1xb52aEDnhOr16urfNyfjm98tRTrq0DUDkVvT6Wl1xHi9ABz/GxhH6h/HJ65cgR19YBqJzHHnNtnZsROuA5PpbQL5RfjnS0a+faOgCVk5oqhYaWXxMWZq/zAoQOeM6iRa6t8xF+FTr+8x/X1gGonKAg6d13y6/5z3+85sqkhA54TlSU/Y6y5UlKstf5Ab+cXgkPl5KTy69JTvbbOwYDXiE9XZo7V2rUyHl548b25V50RVLuMgvP2rWr7NNmk5Ls6/2EX06vSNL69VKHDtKGDSXXJSfb1wNwr/R0qU8f/7v3CuByu3bZT4vt1ct+0Ghion1KxU9GOM7ld6FDsgeL/HzpjjvsATIpSXrnHUY4ACsFBUldu3q6FeUidMA7REVJn3/u6Va4ld+OdBQLD5fmzfN0KwB4MY7pACzil8d0AEAlEDoAi/ntSAcAnAehA7CI30+vAMB5EDoAizC9AqC640BSeAebzetP9XIVRjoAVFeEDnheZqY0YoQ9cBSLj5deecWrLmpzoZheAVDdETpQptmzLbg21/dbpXc3SBrsvHy/pH4bpEEtpUvauLkR1jh0yNMtAADPInSgVNu2SQMGWLGnNpIyyl59nlsK+KLatT3dAgDwDEIHSnX0qP05MlK6+WY37SRrn7Rs2fnrrrtOSvCPO802a2a/YjgAVEeEDpSq+PiDuDjprbfctJMr0yVtOn/dkfbS0o1uagQAwCqcMotSWXLQY/FwiqvqAABejdCBUlkSOtq2dW0dAMCrETpQqqIi+3OgO39C3q3gUaIVrQMAeDVCB0plyUhHeLiUnFx+TXIyt0cHAD9B6ECpLLuQ1fr1ZQeP5GT7egCAX+DsFZTK0qtnrl8v5edLd9wh7d4tJSVJ77zDCAcA+BlCB0pl+SW7w8OlefMs2hkAwBOYXkGpuE8IAMDVGOnwFRbfhdWSs1cAANUKocMXZGZKI0dK//vfmWWNG0svveS2u7Ay0gEAcDX+jvV2mZlS//7OgUOSsrPtyzMz3bJbQgcAwNUIHd7MZrOPcBQngLMVLxs1yl7nYpaHjoICacQIqWdP+3NBgUU7hsvk5EhdukiJifbnnBxPtwiAlyF0eLM1a0qOcJzNGCkry17nYpaGjr59pVq1pGnT7HednTbN/rpvXwt2Dpdo3lyKjpbWrrX/TK5da3/dvLmnWwbAixA6vNn+/a6tqwTLQkffvtKCBaWvW7CA4OELmje3X1+lNLt3EzwAOBA6vFl8vGvrKqH47BW3ho6CgrIDR7EFC5hq8WY5OWUHjmK7dzPVAkASocO7tWvn2rpKKB7pcOsps6NGubYO1uvVy7V1APwaocOb3Xija+sqwZLpldWrXVsH6+3b59o6AH6N0OHNPPgfuiWhIzjYtXWwXmKia+sA+DVChzfz4H/oloSO2293bR2st2iRa+sA+DVChzfz4H/oloSORx5xbR2sFxVlvytweZKS7HUAqj1ChzeLipIaNCi/pkEDt/yHbsnZK8HB0pgx5deMGcP0irfbtavs4JGUZF8PACJ0eDebTapZs/ya4GC3XpHU7Td8mzjRHizO3VFgoH35xIlubgBcYtcu6dgxqXNnKSHB/nzsGIEDgBNu+ObNzndFUunMFUm7dnXpri29IunEidKzz0qvvmq/pkNSkvTgg4xw+JqoKOnzzz3dCgBejNDhzc530aWz63w5dEj2gMH1OADArzG94s2mTHFtXSVwl1kAgKsROrzZsWOurasEQgcAwNWq9/SKzWY/HmL/fvv9S1JSpKAgT7fqjCZNzn9MR3GdixE6AACuVn1DR2amNHKk84d648bSSy9J6enlv9eqsLJokf324BWpc7HiU2bdfvYKAKDaqJ4fKZmZUr9+JUcR/vc/+/LMzPLf27Sp1K2bdNtt9uemTct/T1VV9FRYN54ya9lIR36+dNNN9pvX3XST/TUAwK9Uv9Bhs0n33Vd+zX33lf5Bnpkp9e9fMqxkZ9uXuzp4pKS4tq4SLA0dHTpIERHS/PnSli3254gI+3IAgN+ofqFj9WrpyJHya44cKXlnU5vNPh1T/Gl8NmPsj1GjXDvqkJXl2rpKsCx0dOggbdhQ+roNGwgeAOBHql/oWLq0anWVuVCXq5w44dq6SrAkdOTnlx04im3YwFQLAPiJ6hc6FiyoWl1lLtTlKue7BHpl6yrBktBx222urQMAeLXqFzpOnqxanScu1FV8Comr6qqwa7eevbJ1q2vrAABerfqFjrZtq1bniQt1hYW5tq4SLBnpqFPHtXUAAK9W/ULHoEFVq0tIqNj7KlpXERW9Zb0bbm1vSeh45hnX1gEAvJr/Xxzs3At5Pflkxd731FPSLbecef3QQ9KXX57/fQ89VO7qAwekF16QcnMr0IbgdyTtqEDdxdLdFdheJfzwg/3ZraEjLc1+PMqpU2XX1KxprwMA+Dz/Dh2ZmfYQ8MsvlX/vb785v3766Yq97+mnpYEDy1z95puVOeyjy/9/nMeP///hBnXrume7kuxXcZ01y35BtrLMmuVdl6YHAFSZ/4aO4quOVtW50yQHD1bsfeepKz7k4+qrpT/96Tzb+vOfJZVyXZASAqQJEypQVzkhIeXmJ9dIT5fmzpWGD7cPAxWLj5deeeX8l6QHAPgM/wwdNps0YMCFbePc8FBYWLH3naeuePU110jjxp1nW3/OqNg+JWmc60OHZdLTpT59vPvmewCAC+afoWPx4gu/Mmh2tvNrF12oqzh0hIRUoU3+LChI6trV060AALiRf569MmqUp1tQpuJMUqHQ4cGLgwEA4Gr+N9IRF1fx4y8q4ODB4uuENa74m8q5FUrxMR2hoRXYTkVPHbHsVrAAAFSdf4WOevWko0fLLSlSgB7QdG1Vm/NubnNt6fffi19V4qZqiecvqdBIR2hoxa6gWqEEAwCAZ/lP6AgKqtDlwLeqjd7QsIpt8/cz/wxRJW6qFlJ+CIiNtR9Iel5RURW7oIcbLg4GAICr+UfoKGd6oVDBOqUzxzxkq5EkKUH79LIeLn+78+YrLk666ipJAZW41PiJipzmWgEevLU9AACu5vuho5zAsULd1Vsf6YRKBoYEZamvznPH2b4X2DYAAOBQpbNXpk2bpqZNmyo0NFQdO3bU+vXrXd2uiikjcPygi/WRbtB0PVBq4AhQkW7QQne3DgAAnKXSoeODDz7Qo48+qvHjx+vrr7/WpZdeqp49e+rQoUPuaF/ZSgkcpxWkKRqpP+gH3aiPlCn7FUlf0OM6rlqOx++qpXF63tr2VkVFL+bBRT8AAD6g0qHj73//u+69917dddddat26tV577TXVqlVL//rXv9zRvgr5XWEao4mqpd/1iKY4lnfUOl2vRRqkd1VLBY5HqCp4dVFPq1XLtXUAAHhQpULHyZMntWnTJqWmpp7ZQGCgUlNT9WUZd2AtLCxUbm6u08PVwlSg/+h2nVKwJKmNtmiFumudOmmRblAjVeGGb2HnTMt44kJdnTu7tg4AAA+qVOj49ddfZbPZ1KBBA6flDRo00IGzb9Z1loyMDEVFRTkeCefeSM0FAiQ9q7/oPQ3Ur6qnLWqn7lp5YRvt3t359XXXVex9Fa2riPffd20dAAAe5PbLoI8bN045OTmOR5abTu+8W//SQM1SPZV/cbAKO/eDfNasir2vonUVER4uJSeXX5OcbK8DAMDLVSp0xMTEKCgoSAfPucz4wYMHFRcXV+p7QkJCFBkZ6fRwCeOia2GUprQPck8FgPXry95vcrJ9PQAAPqBSoSM4OFjt27fXJ5984lhWVFSkTz75RJ06dXJ5486rqsEjKqpqH+SeCgDr10t5eVLfvlLbtvbnvDwCBwDAp1T64mCPPvqoBg8erCuvvFIdOnTQlClTdPz4cd11113uaN/5GXP+G55FRtpvdV+/vv2Dun59+/L8fOmOO6Tdu6WkJOmdd84/UrF+fdXed6HCw6V589y7DwAA3KjSoeOWW27R4cOH9dRTT+nAgQO67LLLtGTJkhIHl1qqqiMeVf0gJwAAAFBpAca48+CIknJzcxUVFaWcnBzXHd8BAADcyhWf324/ewUAAEAidAAAAIsQOgAAgCUIHQAAwBKEDgAAYAlCBwAAsAShAwAAWILQAQAALFHpK5JeqOJrkeXm5lq9awAAUEXFn9sXck1Ry0NHXl6eJCkhIcHqXQMAgAuUl5enqKioKr3X8sugFxUV6ZdfflFERIQCznejtkrIzc1VQkKCsrKyuLy6Behva9Hf1qGvrUV/W+tC+tsYo7y8PDVs2FCBgVU7OsPykY7AwEA1btzYbduPjIzkB9dC9Le16G/r0NfWor+tVdX+ruoIRzEOJAUAAJYgdAAAAEv4TegICQnR+PHjFRIS4ummVAv0t7Xob+vQ19aiv63l6f62/EBSAABQPfnNSAcAAPBuhA4AAGAJQgcAALAEoQMAAFiC0AEAACzhN6Fj2rRpatq0qUJDQ9WxY0etX7/e003yOp999pl69+6thg0bKiAgQPPnz3dab4zRU089pfj4eIWFhSk1NVU7d+50qjl69KgGDRqkyMhIRUdH6+6771Z+fr5TzXfffaeUlBSFhoYqISFBEydOLNGW2bNnq1WrVgoNDVXbtm318ccfu/zr9aSMjAwlJycrIiJCsbGx6tu3r3bs2OFUc+LECQ0fPlz16tVTeHi4+vXrp4MHDzrV7Nu3T7169VKtWrUUGxurMWPG6PTp0041q1ev1hVXXKGQkBA1b95cM2fOLNEef//9mD59utq1a+e4ymKnTp20ePFix3r62n2ef/55BQQEaNSoUY5l9LfrPP300woICHB6tGrVyrHe5/ra+IFZs2aZ4OBg869//ct8//335t577zXR0dHm4MGDnm6aV/n444/NE088YTIzM40kM2/ePKf1zz//vImKijLz58833377rbnxxhtNs2bNTEFBgaPmT3/6k7n00kvNunXrzJo1a0zz5s3NwIEDHetzcnJMgwYNzKBBg8zWrVvN+++/b8LCwszrr7/uqFm7dq0JCgoyEydONNu2bTN/+ctfTM2aNc2WLVvc3gdW6dmzp5kxY4bZunWr2bx5s7n++utNYmKiyc/Pd9Tcf//9JiEhwXzyySdm48aN5qqrrjJ//OMfHetPnz5t2rRpY1JTU80333xjPv74YxMTE2PGjRvnqPnpp59MrVq1zKOPPmq2bdtmpk6daoKCgsySJUscNdXh9+PDDz80ixYtMj/++KPZsWOH+fOf/2xq1qxptm7daoyhr91l/fr1pmnTpqZdu3Zm5MiRjuX0t+uMHz/eXHLJJWb//v2Ox+HDhx3rfa2v/SJ0dOjQwQwfPtzx2mazmYYNG5qMjAwPtsq7nRs6ioqKTFxcnHnxxRcdy44dO2ZCQkLM+++/b4wxZtu2bUaS2bBhg6Nm8eLFJiAgwGRnZxtjjHn11VdNnTp1TGFhoaPm//7v/8zFF1/seD1gwADTq1cvp/Z07NjRDBs2zKVfozc5dOiQkWQ+/fRTY4y9b2vWrGlmz57tqNm+fbuRZL788ktjjD0kBgYGmgMHDjhqpk+fbiIjIx39+/jjj5tLLrnEaV+33HKL6dmzp+N1df39qFOnjnnrrbfoazfJy8szLVq0MMuXLzfXXHONI3TQ3641fvx4c+mll5a6zhf72uenV06ePKlNmzYpNTXVsSwwMFCpqan68ssvPdgy37Jnzx4dOHDAqR+joqLUsWNHRz9++eWXio6O1pVXXumoSU1NVWBgoL766itHzdVXX63g4GBHTc+ePbVjxw799ttvjpqz91Nc48/fr5ycHElS3bp1JUmbNm3SqVOnnPqhVatWSkxMdOrvtm3bqkGDBo6anj17Kjc3V99//72jpry+rI6/HzabTbNmzdLx48fVqVMn+tpNhg8frl69epXoE/rb9Xbu3KmGDRvqoosu0qBBg7Rv3z5JvtnXPh86fv31V9lsNqcOlaQGDRrowIEDHmqV7ynuq/L68cCBA4qNjXVaX6NGDdWtW9epprRtnL2Psmr89ftVVFSkUaNGqXPnzmrTpo0kex8EBwcrOjraqfbc/q5qX+bm5qqgoKBa/X5s2bJF4eHhCgkJ0f3336958+apdevW9LUbzJo1S19//bUyMjJKrKO/Xatjx46aOXOmlixZounTp2vPnj1KSUlRXl6eT/a15be2B6qb4cOHa+vWrfr888893RS/dvHFF2vz5s3KycnRnDlzNHjwYH366aeebpbfycrK0siRI7V8+XKFhoZ6ujl+Ly0tzfHvdu3aqWPHjmrSpIn++9//KiwszIMtqxqfH+mIiYlRUFBQiaN1Dx48qLi4OA+1yvcU91V5/RgXF6dDhw45rT99+rSOHj3qVFPaNs7eR1k1/vj9GjFihBYuXKhVq1apcePGjuVxcXE6efKkjh075lR/bn9XtS8jIyMVFhZWrX4/goOD1bx5c7Vv314ZGRm69NJL9dJLL9HXLrZp0yYdOnRIV1xxhWrUqKEaNWro008/1csvv6waNWqoQYMG9LcbRUdHq2XLltq1a5dP/mz7fOgIDg5W+/bt9cknnziWFRUV6ZNPPlGnTp082DLf0qxZM8XFxTn1Y25urr766itHP3bq1EnHjh3Tpk2bHDUrV65UUVGROnbs6Kj57LPPdOrUKUfN8uXLdfHFF6tOnTqOmrP3U1zjT98vY4xGjBihefPmaeXKlWrWrJnT+vbt26tmzZpO/bBjxw7t27fPqb+3bNniFPSWL1+uyMhItW7d2lFTXl9W59+PoqIiFRYW0tcu1r17d23ZskWbN292PK688koNGjTI8W/6233y8/O1e/duxcfH++bPdqUOO/VSs2bNMiEhIWbmzJlm27Zt5r777jPR0dFOR+vCfrT5N998Y7755hsjyfz9738333zzjfn555+NMfZTZqOjo82CBQvMd999Z/r06VPqKbOXX365+eqrr8znn39uWrRo4XTK7LFjx0yDBg3MHXfcYbZu3WpmzZplatWqVeKU2Ro1aphJkyaZ7du3m/Hjx/vdKbMPPPCAiYqKMqtXr3Y61e3333931Nx///0mMTHRrFy50mzcuNF06tTJdOrUybG++FS36667zmzevNksWbLE1K9fv9RT3caMGWO2b99upk2bVuqpbv7++zF27Fjz6aefmj179pjvvvvOjB071gQEBJhly5YZY+hrdzv77BVj6G9XGj16tFm9erXZs2ePWbt2rUlNTTUxMTHm0KFDxhjf62u/CB3GGDN16lSTmJhogoODTYcOHcy6des83SSvs2rVKiOpxGPw4MHGGPtps08++aRp0KCBCQkJMd27dzc7duxw2saRI0fMwIEDTXh4uImMjDR33XWXycvLc6r59ttvTZcuXUxISIhp1KiRef7550u05b///a9p2bKlCQ4ONpdccolZtGiR275uTyitnyWZGTNmOGoKCgrMgw8+aOrUqWNq1aplbrrpJrN//36n7ezdu9ekpaWZsLAwExMTY0aPHm1OnTrlVLNq1Spz2WWXmeDgYHPRRRc57aOYv/9+DB061DRp0sQEBweb+vXrm+7duzsChzH0tbudGzrob9e55ZZbTHx8vAkODjaNGjUyt9xyi9m1a5djva/1dYAxxlRubAQAAKDyfP6YDgAA4BsIHQAAwBKEDgAAYAlCBwAAsAShAwAAWILQAQAALEHoAAAAliB0AAAASxA6AACAJQgdAADAEoQOAABgif8HHK3SMH9t2vkAAAAASUVORK5CYII=",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Random Forest\n",
"#predictors = ['nodes', 'exploit', 'appl', 'load']\n",
"predictors = ['exploit']\n",
"overall_outcome = 'runtime'\n",
"\n",
"# partition data\n",
"X = timing_df[predictors]\n",
"overall_y = timing_df[overall_outcome]\n",
"train_X, valid_X, train_y, valid_y = train_test_split(X, overall_y, test_size=0.4, random_state=1)\n",
"\n",
"regressor = RandomForestRegressor(n_estimators = 10, random_state = 0)\n",
"regressor.fit(train_X, train_y)\n",
"\n",
"X_grid = np.arange(0, 49152, 10)\n",
"X_grid = X_grid.reshape((len(X_grid),1))\n",
"plt.scatter(X, overall_y, color = 'red')\n",
"plt.plot(X_grid, regressor.predict(X_grid), color = 'blue')\n",
"plt.title('Random Forest Regression')\n",
"plt.show()"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"### Applicable"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/noah/.local/lib/python3.10/site-packages/sklearn/base.py:420: UserWarning: X does not have valid feature names, but RandomForestRegressor was fitted with feature names\n",
" warnings.warn(\n"
]
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Random Forest\n",
"#predictors = ['nodes', 'exploit', 'appl', 'load']\n",
"predictors = ['appl']\n",
"overall_outcome = 'runtime'\n",
"\n",
"# partition data\n",
"X = timing_df[predictors]\n",
"overall_y = timing_df[overall_outcome]\n",
"train_X, valid_X, train_y, valid_y = train_test_split(X, overall_y, test_size=0.4, random_state=1)\n",
"\n",
"regressor = RandomForestRegressor(n_estimators = 10, random_state = 0)\n",
"regressor.fit(train_X, train_y)\n",
"\n",
"X_grid = np.arange(0, 100, 10)\n",
"X_grid = X_grid.reshape((len(X_grid),1))\n",
"plt.scatter(X, overall_y, color = 'red')\n",
"plt.plot(X_grid, regressor.predict(X_grid), color = 'blue')\n",
"plt.title('Random Forest Regression')\n",
"plt.show()"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"### Load"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/noah/.local/lib/python3.10/site-packages/sklearn/base.py:420: UserWarning: X does not have valid feature names, but RandomForestRegressor was fitted with feature names\n",
" warnings.warn(\n"
]
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Random Forest\n",
"#predictors = ['nodes', 'exploit', 'appl', 'load']\n",
"predictors = ['load']\n",
"overall_outcome = 'runtime'\n",
"\n",
"# partition data\n",
"X = timing_df[predictors]\n",
"overall_y = timing_df[overall_outcome]\n",
"train_X, valid_X, train_y, valid_y = train_test_split(X, overall_y, test_size=0.4, random_state=1)\n",
"\n",
"regressor = RandomForestRegressor(n_estimators = 10, random_state = 0)\n",
"regressor.fit(train_X, train_y)\n",
"\n",
"X_grid = np.arange(0, 400, 10)\n",
"X_grid = X_grid.reshape((len(X_grid),1))\n",
"plt.scatter(X, overall_y, color = 'red')\n",
"plt.plot(X_grid, regressor.predict(X_grid), color = 'blue')\n",
"plt.title('Random Forest Regression')\n",
"plt.show()"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"## Gradient Boosting Classifier"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"The mean squared error (MSE) on test set: 359835092.9070\n"
]
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 600x600 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"predictors = ['nodes', 'exploit', 'appl', 'load']\n",
"overall_outcome = 'runtime'\n",
"\n",
"# partition data\n",
"X = timing_df[predictors]\n",
"overall_y = timing_df[overall_outcome]\n",
"train_X, valid_X, train_y, valid_y = train_test_split(X, overall_y, test_size=0.4, random_state=1)\n",
"\n",
"params = {\n",
" \"n_estimators\": 500,\n",
" \"max_depth\": 4,\n",
" \"min_samples_split\": 5,\n",
" \"learning_rate\": 0.01,\n",
" \"loss\": \"squared_error\",\n",
"}\n",
"\n",
"reg = GradientBoostingRegressor(**params)\n",
"reg.fit(train_X, train_y)\n",
"\n",
"mse = mean_squared_error(valid_y, reg.predict(valid_X))\n",
"print(\"The mean squared error (MSE) on test set: {:.4f}\".format(mse))\n",
"\n",
"\n",
"test_score = np.zeros((params[\"n_estimators\"],), dtype=np.float64)\n",
"for i, y_pred in enumerate(reg.staged_predict(valid_X)):\n",
" test_score[i] = mean_squared_error(valid_y, y_pred)\n",
"\n",
"fig = plt.figure(figsize=(6, 6))\n",
"plt.subplot(1, 1, 1)\n",
"plt.title(\"Deviance\")\n",
"plt.plot(\n",
" np.arange(params[\"n_estimators\"]) + 1,\n",
" reg.train_score_,\n",
" \"b-\",\n",
" label=\"Training Set Deviance\",\n",
")\n",
"plt.plot(\n",
" np.arange(params[\"n_estimators\"]) + 1, test_score, \"r-\", label=\"Test Set Deviance\"\n",
")\n",
"plt.legend(loc=\"upper right\")\n",
"plt.xlabel(\"Boosting Iterations\")\n",
"plt.ylabel(\"Deviance\")\n",
"fig.tight_layout()\n",
"plt.show()"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"## Polynomial Regressionwhat is considered high VIF"
]
},
{
"cell_type": "code",
"execution_count": 44,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[<matplotlib.lines.Line2D at 0x6fd6c48aed70>]"
]
},
"execution_count": 44,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"predictors = ['nodes', 'exploit', 'appl', 'load']\n",
"overall_outcome = 'runtime'\n",
"\n",
"# partition data\n",
"X = timing_df[predictors]\n",
"overall_y = timing_df[overall_outcome]\n",
"train_X, valid_X, train_y, valid_y = train_test_split(X, overall_y, test_size=0.4, random_state=1)\n",
"\n",
"plt_mean_squared_error = []\n",
"deg_range = range(1,21)\n",
"for degree in deg_range:\n",
" poly = PolynomialFeatures(degree = degree)\n",
" X_poly = poly.fit_transform(train_X)\n",
" poly.fit(X_poly, train_y)\n",
"\n",
" regression_model = LinearRegression()\n",
" regression_model.fit(X_poly, train_y)\n",
" y_pred = regression_model.predict(X_poly)\n",
" plt_mean_squared_error.append(mean_squared_error(train_y, y_pred, squared=False))\n",
"\n",
"\n",
"plt.scatter(deg_range,plt_mean_squared_error, color=\"green\")\n",
"plt.plot(deg_range,plt_mean_squared_error, color=\"red\")"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"## SVR"
]
},
{
"cell_type": "code",
"execution_count": 46,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"439524.8341302504"
]
},
"execution_count": 46,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# SVR\n",
"predictors = ['nodes', 'exploit', 'appl', 'load']\n",
"overall_outcome = 'runtime'\n",
"\n",
"# partition data\n",
"X = timing_df[predictors]\n",
"overall_y = timing_df[overall_outcome]\n",
"train_X, valid_X, train_y, valid_y = train_test_split(X, overall_y, test_size=0.4, random_state=1)\n",
"\n",
"param_grid = {'C': [0.1,1, 10, 100, 1000], 'gamma': [1,0.1,0.01,0.001,0.0001], 'kernel': ['rbf']}\n",
"grid = GridSearchCV(SVR(),param_grid,refit=True,verbose=0)\n",
"grid.fit(train_X,train_y)\n",
"\n",
"grid_predictions = grid.predict(valid_X)\n",
"\n",
"mean_squared_error(valid_y, grid_predictions, squared=False)"
]
}
],
"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": "3.10.10"
},
"orig_nbformat": 4
},
"nbformat": 4,
"nbformat_minor": 2
}
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