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college-datascience/project/Notebook.ipynb
2019-05-27 01:14:43 +02:00

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591 KiB
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# inlezen en inbrengen van de data naar variabelen\n",
"\n",
"## inlezen van de data zelf\n",
"\n",
"We beginnen met het inlezen van de data via een with statement waar we de data als een array van strings inlezen.\n",
"Zo kunnen we deze array in een parse functie steken die elke string afloopt, en split via het & teken. Als we kijken naar een stuk van de data zullen we zien waarom:"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Time=12/03 06:08:53& Sender=44:6E:E5:C5:8F:4F& Location=gang@0.61875;0.13758& WifiInfo=ODISEE@88-1d-fc-30-d4-40:-74,campusroam@88-1d-fc-30-d4-43:-74,ODISEE@88-1d-fc-30-d5-50:-72,eduroam@88-1d-fc-30-d4-42:-74,eduroam@88-1d-fc-30-d5-52:-72,campusroam@88-1d-fc-30-d5-53:-73,ODISEEGuest@88-1d-fc-30-d4-41:-75,ODISEEGuest@88-1d-fc-30-d5-51:-73,CiscoC5976@58-6d-8f-19-14-38:-82,rechts@58-6d-8f-19-10-fc:-59,ODISEE@88-1d-fc-41-dc-50:-81,eduroam@88-1d-fc-41-dc-52:-81,campusroam@88-1d-fc-41-dc-53:-67,eduroam@88-1d-fc-2c-c0-02:-78,campusroam@88-1d-fc-2c-c0-03:-71,ODISEE@88-1d-fc-2c-c0-00:-77,telenet-5467D@dc-53-7c-85-46-82:-87,ODISEEGuest@88-1d-fc-41-dc-51:-80,ODISEEGuest@88-1d-fc-2c-c0-01:-73,CiscoC5959@58-6d-8f-19-13-f4:-81,TELENETHOMESPOT@02-53-7c-85-46-83:-86\n",
"\n"
]
}
],
"source": [
"import matplotlib.pyplot as plt\n",
"import pandas as pd\n",
"import numpy as np\n",
"lines = []\n",
"\n",
"with open(\"DataScienceData01.txt\",\"r\") as infile:\n",
" lines = infile.readlines()\n",
"if True:\n",
" with open(\"DataScienceData02.txt\", \"r\") as infile:\n",
" lines.extend(infile.readlines())\n",
" \n",
"\n",
"if True:\n",
" with open(\"DataScienceData03.txt\", \"r\") as infile:\n",
" lines.extend(infile.readlines())\n",
"\n",
"print(lines[1])\n",
"\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## parsen van de data\n",
"\n",
"Zoals hierboven te zien is is onze input een collectie van lijnen waar elke lijn een instance van een meting is. Er is een time onderdeel, sender (bestaande uit een mac address), location (bestaande uit een locatie naam, xcoordinaat als percentage en ycoordinaat als percentage) en een wifiinfo onderdeel wat bestaat uit een lijst van ssid's met hun mac-address en signaal sterkte.\n",
"\n",
"Om deze data te parsen werdt er gekozen voor een entry te maken voor elke ssid die in wifiinfo te vinden is. Op deze manier is er een entry van elk ontvangbaar access-point vanaf elke sender.\n",
"\n",
"Daarboven op zullen we ook een x en y coordinaat toevoegen die volledig zijn ipv een percentage. Dit maakt het process later makkelijker omdat we dan niet de bewerking opnieuw moeten doen. (bewerking = locatienaam + .png inladen en width en height van de image vermenigvuldigen met x en y)\n",
"\n",
"Er zijn ook meerdere keren dezelfde ssid aanwezig met andere mac addressen. Dit komt omdat meerdere accesspoints dezelfde ssid's verzenden, en er zijn deels gelijke mac addressen aanwezig. Dus door een deel van het mac address apart te steken kunnen we access point specifieke data inlezen.\n",
"\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"def dataParse(l):\n",
" objs = l.split(\"& \")\n",
" dic = {}\n",
" for obj in objs:\n",
" items = obj.split(\"=\")\n",
" title = items[0]\n",
" data = items[1].split(\",\")\n",
" if len(data) == 1:\n",
" data = data[0]\n",
" if title == \"Location\":\n",
" temp = data.split(\"@\")\n",
" naam = temp[0].lower()\n",
" x, y = temp[1].split(\";\")\n",
" dic[\"location\"] = naam\n",
" img = plt.imread(naam+'.png')\n",
" height, width, channels = img.shape\n",
" dic[\"x\"] = float(x) * width\n",
" dic[\"y\"] = float(y) * height\n",
" dic[\"px\"] = float(x)\n",
" dic[\"py\"] = float(y)\n",
" continue\n",
" if title == \"WifiInfo\":\n",
" appendable = []\n",
" for f in data:\n",
" append = {}\n",
" temp = f.replace(\"\\n\",'').split('@')\n",
" ti = temp[0]\n",
" append[\"ssid\"] = ti\n",
" temp = temp[1].split(\":\")\n",
" append[\"mac\"] = temp[0]\n",
" append[\"routerId\"] = \"\".join(temp[0].split('-'))[:-2]\n",
" #print(append[\"routerId\"])\n",
" append[\"signal\"] = float(temp[1])\n",
" appendable.append(append)\n",
" dic[title] = appendable\n",
" continue\n",
" dic[title] = data\n",
" finale = []\n",
" for i in dic['WifiInfo']:\n",
" f = {}\n",
" f[\"time\"] = dic['Time']\n",
" f['sender'] = dic['Sender']\n",
" f['location'] = dic['location']\n",
" f['x'] = dic['x']\n",
" f['y'] = dic['y']\n",
" f[\"px\"] = dic[\"px\"]\n",
" f[\"py\"] = dic[\"py\"]\n",
" f['ssid'] = i['ssid']\n",
" f['mac'] = i['mac']\n",
" f['routerId'] = i[\"routerId\"]\n",
" f['name'] = i['ssid']+\"@\"+i['mac']\n",
" f['signal'] = i['signal']\n",
" finale.append(f)\n",
" return finale \n",
"\n",
"\n",
"data = []\n",
"for l in lines:\n",
" data.extend(dataParse(l))\n",
"\n",
"\n",
"\n",
"\n",
"df = pd.DataFrame(data)\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## het in beeld brengen van de data\n",
"\n",
"Aan de hand van de locatie van de items in de dataframe kunnen we een scatterplot maken overheen de images. We zullen beginnen met de senders te tonen."
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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xMby3jXss6X1s3vz3YHBP5s0/eVFKh9pmyhnHR8sH06L3y7Avj1XTZtFgiJcP2YW+yu6SlMChyxafrqBs8SZ4fxf0voL0gVfy2K3JeVc/S3o/OrECUi4OXIyiu+o069er/sisIye4i0DPuAOm5PG1h+99rGF8vqbA11OuhilXxz4gD7CkT2D17VH1icuKyL5pHJfnhX974wrrBzOSQJPfgwB7nWv1ui6s+7KMKyzpE1x9elQ9d91Ypm67m/qkaepVJzveaHL8EGeUvU3pd1M5+j/1WJhxhSW9Dw1KTWGQ0/11WxHubJrD+APzCZxLFdrRo6f2jC8yONohmhjy8N6YiYf3gU0FL1D0UI+wj9VXddf2Z6Iel4kdTye9iNhptzEV6A13Ydev6ZPyFJOzRvPF+jvqvJTH2zeKdmAmhjyb9HrywhwTIzL09Yrng9u/4P5uT3Pmnwe6HJWJNU/s02/cuDFkiR78nv0RRM/WeQPoxPNsnTfA7VBMHHki6cGS2Q0dT6zgwz9sodn6wDXjDVp3gPN6QMopZ1ibJOKZpA93393+HKKn46xmDLrxwUoXQy+atZ1tyXe6uQnimaQvKChwOwTfKRzVjqZVfgJ3j0rOU0/NSZ5tyDOx9/XyAc6VdpsCj7JFgXEmqXmmpDfxl9+1gEUrP+XAka8A6Hh+Ozp0uok8d8MyMWZJ72N3nZ3CXb3PdTsME2dWvTfGZyzpjfEZq977WNHkZqeMyx4f+l52JvFZ0vtYoGfbgGPT59Kg1zf42sV4THxY0vvYkXEnr43/w48v4bNbvwVMcy8gExeW9D72WKMrK4bfOPYGb/3hfyzlfcCS3seKVi+vGF45azn/unEB8F33AjJxkdBJH+ndXfxuodN7DsCWy/twf6ubmbev9ptYmsSWsEkf6u4ulvjhadRoSsXwsVYpXDOv1MVoTLwkbNKbyM3/onJ/dzfZr8EX7Gv2sUH27fuSnZHnMusDsGa2bWLDkt4YnwnnVtVzROSAiGwNGpcnIh+KSLHz6BP03v0isktE3hWRH8Qq8Joa66wRz5jQwtmrmwvMBKp2bv6oqj4cPEJEOgC3AB2BFsBrItJOVY9HIdZTRDPB7fCf8Ytw7k+/RkQywlxeP2CBqh4DdovILuAK4I3aZuzbt29YK4hFH3l2+M/4SST79KNFZItT/W/sjGsJ7A2aptQZdwoRGSkiRSJSBCf7ua/tYYyJTH2T/gkCN/7OBPYDjzjjq2turTZTVXWWqmarajacvJtNbQ9jTGTqlfSq+rGqHlfVE8DTBKrwECjZgzpUphWwr7blZWVlhSzZraQ3JnrqlfQikh708iagvGV/CXCLiJwuIhcAFwH/jCxEY0w0hXPI7lkCDXEXi0ipiIwApojI2yKyBegJjAFQ1W3AQuAd4BXg7vq23JdX5eNRutvhP+Mn4oUqc3Z2thYVFVUaJyK+qM775XPWh22b8GVnZ1NUVBRWo5edkWeMz1jSG+MzlvTG+IxdXBkndpqvVymBU00AmgCnuxhLfFhJHwehTvM17ir74lNeGnUNL40awQfz74Sy6k8rOb55Rpwjix1LeuNrBz//D32f2sEPn1zG2m/2YdSI33JwzUM82WMwM7oMgbJPeGnUYBpk/pLXH84DjnFwzUPM6DKEbU/+GMo+4d87i3njoSHM6DKEo4c/dfsj1cqS3hiAL1/ny9fnkpbdl9vGF8NTf6Lx89N5Z/VyPvj5/wdg343jObh5NbeNL6bx89O56aVU3lm9nH99fpynzxtD4+f/Qllq41pW5D5LemOA/7r0RWb8ZzTDf/IDmqe9zeVLR9Dh+aGseesIv7j0WwD8qF0jlr+xjeZpb9Ph+aFczSbWvHUEgEfuuIwhF5xOagPvXx9iDXnGAL/Z9TC/cYabpDQg666J8M3zyDpa5oxtD/ovjrW+iiYpc8i67wmy7vkYtAkbt31K4wRI9nJW0seBnebrYXIG8LNKo5a2nsTDvR5l8dCf8/rKzwC44de/56UHFnL9NZksbT2JxUN/zsNdn3DePyv+cUfATsN1mV8+Z33EY9scVVj6URkD0k9WeveUKa99cIxPPy9jWJdUzhXYeVTZfaiMH6Q3ZE+ZsnDzl7RudjrXtGoIx5VzXS7p63IarlXvja81EiolPMD5DYTh7RpVGteukdAuvWHF+/dlnbw7EAlUtQer3hvjO5b0xviMJb0xPmNJb4zPWNIb4zOW9Mb4jCW9MT5jSW+Mz1jSG+MzlvTG+IwlvTE+Y0lvjM/YBTceYDfmrJltm1NFeuWhJb3L7LLa+CosLOTll19m6tSpUV3uuHHj6NChA8OGDYvqcmPBqvfGV4qLi2nTpk3Ul9utWzdKSkqivtxYsKQ3vtGpUyfGjBnDa6+9FvVlL1u2jEmTJnHJJZdEfdnRlnTVe7uphKnO4cOH+e53v8vixYu5/fbbo778v/zlL7z66qssWrSI4uJiMjMzo76OaAnnVtWtRWSViGwXkW0i8ktn/Dki8g8Rec95buyMFxGZISK7RGSLiHSJ9YcoZzeVMDUpLi5mxowZtGvXjsWLF0d9+WvXrqV3797MmDGDw4cPR3350RROSV8G3Kuqm0TkTGCjiPwDGAasUNXJIjIeGA/8GrgeuMh5dAWecJ5jxpI6PhK9FnXGGWcA0KpVq6gvu3v37pXW4WW1lvSqul9VNznDnwPbgZZAP2CeM9k8oL8z3A94RgPeBNJEJD3qkTss4ePDalHJo04NeSKSAVwGrAeaq+p+CPwxAM2cyVoCe4NmK3XGVV3WSBEpEpGigwcP1j1yY0y9hN2QJyKpwPNArqp+FuKkiereOOVgtKrOAmZBoAvscOPwu0SvYhv3hVXSi0hDAgn/V1UtbwX5uLza7jwfcMaXAq2DZm8FVH8r0DhJlqSwKraJhlpLegkU6bOB7ao6LeitJcBQYLLz/GLQ+NEisoBAA96R8t2AeEuWZDcmmsIp6bsDQ4CrRaTYefQhkOzXish7wLXOa4ClwAfALuBp4K7oh32S3TIqPpJtO69bt86Ty4qHWkt6VV1L9fvpANdUM70Cd0cYV50k6g8v0STTdr7nnntYt25dxIfYvvrqKyZPnkxBQUGUIos9Ow3X+FKPHj149NFHI17O7NmzadasWe0TeoglfQJJtip2vH311VcVz5MmTeKtt95i5syZ9V7e4sWLeeGFF3jkkUcoLS2NVpixp6quP7KysrSqQGjGRA+BQ8fauXNnVVXdvXu37t69WwcOHKiffPJJ2Mv55JNPdODAgbpq1SpdtWqVqqp27NixYvlucHIorHxLugtujKnJ7t27KSkpITMzk5kzZ/L444+zY8cOOnbsSO/evZkwYQKdOnUKuYytW7fyu9/9jsaNG9OzZ0+GDh1KQUEBa9eupbi4mIyMjPh8mAhY0hvfyMjIqEjKV155hU2bNnHGGWewc+dOtm7dyo4dO3jzzTdrXc6DDz5Ip06daNeuHQC33347aWlp5OTkxDD66LGkN76Uk5ND9+7dmTNnDpmZmRUJXBc7d+7k3nvvJSsrKwYRxo4lvfGl++67j7Zt23L77bfTp08fpkyZUqf5Z86cyaxZsxg7dixDhgyJUZSxYa33xrf69+/P2rVradu2LWPHjmXdunUVLfw1KS4uZubMmRw6dIglS5YkXMKDlfTG59LS0hg5cmSlcXPnzj2lv7u0tDSGDRtGZmamp3vFCYclvTFVJEKPtpGw6r0xPmNJb4zPWNIbk6BEpOJRF5b0xiQwrccdkqwhz5gEE1yylw9v3Lgx7Pkt6Y1JQFVL+Ozs7LDn9U3SW4eSxgT4IulDdShpiW8S0UsvvVTp9ZEjR8Ke1xryjPEZS3pjfMYX1fv6snYAk4yspK+B3VjCJCtflPQlk2+wUtvEjdd/a75IevDWRjfJKxGOFFn13hifSZqkLywsdDsEYxJC0iT9448/zvz586O2PC/cWCL4Kip7JMajpgtgVDXiZUdL0uzT//vf/2bq1Kn06NGDjCj1Pe6FfbD6XEXlJaESIZ7LiJea9um99BmSpqQfPXo01113XdQS3kSHF37o0Swla+OFGmJtwrk/fWvgGeA84AQwS1UfE5E84KfAQWfSCaq61JnnfmAEcBz4haq+GoPYKxk4cCDt27dnwoQJpKWlxXp1JoHE+4/HSwlenXCq92XAvaq6SUTOBDaKyD+c9x5V1YeDJxaRDsAtQEegBfCaiLRT1eN1Caz8iwq3WtS6dWuaNWvGxIkTUVVWrlzJL37xC6644goKCgo4evQoDz30EP369SM3Nzdh7kZiIuelqrUXhHN/+v3Afmf4cxHZDrQMMUs/YIGqHgN2i8gu4ArgjSjEW62CggL27t3LBRdcwI4dOzh48CDTpk1j4cKF5Ofns2zZMtq1a0fnzp3Zvn07PXv2ZNWqVZb4PmEJX1mdGvJEJAO4DFgPdAdGi8gdQBGB2sAhAn8IwTcEK6WaPwkRGQmMDHodar0Vw1W/wMLCQiZOnEi3bt1Ys2YNADfeeCO/+tWvGDVqFI0bN+arr74iJSWF2bNnc/jwYYqLi5k/f74lvfElCfdfUERSgdXA71V1sYg0B/5N4Pa8vwXSVXW4iDwOvKGq/+3MNxtYqqrPh1i21uffuLi4mOHDhzN8+HDOOussSktLeeCBB2jz6yWABB6qoMq/pt7IunXruPLKK+u8HrdYtTQg0u2QbNtRRCgoKKg0bsyYMbz33nthtViGVdKLSEPgeeCvqroYQFU/Dnr/aaD8qv5SoHXQ7K2AfWGsI5xQKn15xcXF9OrViz179gAwdepU2oxdgmrQcU0RFGg9dgkjRoxg+/btYa3HJI9kSvhoCKf1XoDZwHZVnRY0Pt3Z3we4CdjqDC8B/iYi0wg05F0E/LO29VT95wpHSUkJ559/Pnv27Dl5Rl41JzKUv27atGmd12FMsgmnpO8ODAHeFpFiZ9wE4FYRySRQvS8BfgagqttEZCHwDoGW/7vr2nIfrtzcXBo3bsyyZcto0aIFAAdqmFZEWLNmDXPmzGH48OGxCMd4VLJV7yMVTuv9WgI7yFUtDTHP74HfRxBXWNLS0pg6dSovv/wyu3fvZsOGDbTpGXoeS3j/sYSvLOHPyLvzzjv58MMPOe+88+jVq1dFw50xpnoJn/RpaWksXryYJk2akJmZyQ//91Un6Z2H8wfg9bOkTOzE8zTcRJA0F9wUFRWxcuVKZs+ezczhfSvGP/fcc/zoRz9yMTLjNqveV5bwJX25lStXMmDAAAYMGFBpfPPmzV2KyBhvSpqkX7BgAZ07dz7lYpuMjAwOHz7sUlTGqtbekzTV+y+//JK8vLxTxtultu6yqrX3JE1Jb4fijAlP0iS98Sar3nuPJb2JKavee0/C7dP7reTw2+etiW2H6Em4pK/PhTnGmJOsem+Mz1jSG+MzlvTG+IwlvTE+Y0lvjM9Y0hvjM5b0xviMJb0xPmNJb4zPJNwZeX379q19ImNMjRIu6d241/m6devo3r17ROs1Jpays7PDnjbs21rFkogcBL4kcJssLzkX78UEFldd+SGuNqoa1t1cPJH0ACJSpKrh/13FgRdjAourriyuyqwhzxifsaQ3xme8lPSz3A6gGl6MCSyuurK4gnhmn94YEx9eKumNMXHgetKLyHUi8q6I7BKR8S7HUiIib4tIsYgUOePOEZF/iMh7znPjOMQxR0QOiMjWoHHVxiEBM5ztt0VEusQ5rjwR+dDZZsUi0ifovfuduN4VkR/EKKbWIrJKRLaLyDYR+aUz3tXtFSIuV7cXEDjZxa0HcBrwPvBt4BvAZqCDi/GUAOdWGTcFGO8Mjwf+GIc4vg90AbbWFgfQB1hG4Hbi3YD1cY4rD7ivmmk7ON/n6cAFzvd8WgxiSge6OMNnAjuddbu6vULE5er2UlXXS/orgF2q+oGq/gdYAPRzOaaq+gHznOF5QP9Yr1BV1wCfhhlHP+AZDXgTSBOR9DjGVZN+wAJVPaaqu4FdBL7vaMe0X1U3OcOfA9uBlri8vULEVZO4bC9wv3rfEtgb9LqU0Bsm1hRYLiIbRWSkM665qu6HwBcJNHMptpri8MI2HO1UlecE7f7EPS4RyQAuA9bjoe1VJS5weXu5nfTVdWbu5uGE7qraBbhvra77AAABbklEQVQeuFtEvu9iLOFyexs+AVwIZAL7gUec8XGNS0RSgeeBXFX9LNSk1YyLZ1yuby+3k74UaB30uhWwz6VYUNV9zvMB4AUC1auPy6t/zvMBl8KrKQ5Xt6Gqfqyqx1X1BPA0J6ukcYtLRBoSSKy/qupiZ7Tr26u6uLywvdxO+g3ARSJygYh8A7gFWOJGICLyLRE5s3wY6A1sdeIZ6kw2FHjRjfhCxLEEuMNple4GHCmv1sZDlf3hmwhss/K4bhGR00XkAuAi4J8xWL8As4Htqjot6C1Xt1dNcbm9vQB3W++DWlN3EmitfMDFOL5NoPV0M7CtPBagCbACeM95PicOsTxLoOr3NYESYERNcRCoFj7ubL+3gew4xzXfWe8WAj/c9KDpH3Diehe4PkYxfY9ANXgLUOw8+ri9vULE5er2UlU7I88Yv3G7em+MiTNLemN8xpLeGJ+xpDfGZyzpjfEZS3pjfMaS3hifsaQ3xmf+DyPuw+SWUPD0AAAAAElFTkSuQmCC\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"for i in df.location.unique():\n",
" temp = df.loc[df[\"location\"] == i]\n",
" plt.scatter(temp.x, temp.y)\n",
" #print(i)\n",
" img = plt.imread(i+'.png')\n",
" #print(img)\n",
" plt.imshow(img)\n",
" plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"De volgende stap is om de meetpunten zelf in beeld te brengen. Door onze x en y coords te mappen per routerid en dan het signal te mappen op de c value in een scatter plot krijgen we een heatmap. Deze functie zal dus later herbruikt worden om de data te tonen.\n"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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cU2W+LxGRX4A+QMxQR3UWOlX9H7F9Up4QJb8C19f1eWDEcbj55pvNsxUUN+/BMUN616fIqIx88wVKt25jQIej6NC+hNJdxlKKCx839T6B0zrbJ4aeMZHI/JgtloW/iLQBtqmqT0R6YCyJrYhRDGDzHYna1Agc4F8Fjh5pLf+d5T9w00cfBs/n/boWfm3PO+dcwIB6+DXJNBbtSES18AeOBe4VES+Gf9JrVHVb9CIMGtf+SQhdxnyZ9jJvNgUuNAoOwJg3/p32Z6ULq3YkVPUSVe2vqger6qiQZbG3VPVAVR2gqoeq6sxEZTWqli6U341Or1Ob8ip3MPRSKAHXEnYma5hjEbdfcX5ay3PbXLBioQoef1bo0kps326xF4nrQvu8JoChVFDbc5OdMbrXxiV0tq+tlfp++7drZTzTFLTA6wm9ullWh7qwT+1INCR393oy7WV+cO44Ljz4IHNFzmjxbj3qCJ4/9ey0PytdBJZMGpNqk+2711j0/O1+aSsrVMv3L0NP4S9DbRHqPkkaX/faaIVu7AT7LNA2NHazgUiErYWupKTuwUis5Mml0/hyy3KGtj2ALljrn9iYvdrLxDARthY6u1Na/guXfF2zb/5i2WLIhWuq6+dEMRUCi8ONicY1GLAZl379d/NdqOMLmJK70NJ6NDYTxGxLR918yrndbjRE0GoQS3cIrNrwTydZoasjVZiuwfDSoWAXeS4vfoVtewqo9NbdXWxdyM5e00ivXr0sDXeUCs3zmwJeujczNPRFjDavTcFuirxVltVDVfBmhS59lJaWMnLkyKTzx9u9mDhxIgMHDozq6Twg2Eu3bGLMq69Q5TFib7icDv4+YhTH94juKKdHs12GkoDZuwVeC1w+yt3lFOdbM5NtbN1r4/qJpMDEiROZMWNG2Hk81/per5fTXnqJKo8vqNbk9fm54p0ZrI4Vs1V8MS3LTn/kjHqFEUiWxrgjYWuhGzRoUNCYJd7x2WefcdNNN4Xdm0jIavP8lvURqk2B95fPfDuleivK2AvHxq1zOskKXQMwbNgwJk+eXK8yVrujj8MEYc2O6JaV3Quib8WJCJfsd1696pMsVrqVEJEbxQiZvkREHg5JTymc+l4hdOmgdW5u1HRFqVYvPac9zICXJ/PhymXBaxP3vxMnkbsBJ7YdSr7LuhmsFet0InIchpeGg1X1QOBRMz00nPopwNMiEneLJCt0Jte07QiE688F3vsKq/G7fOzUPVz7+XTun2e4n3C5XLx4+LOc1WkUrXNb0a2gK5MHPMC47hdbVm9V8PodCY80cC3woGn9haoG7JmD4dRVdSWGtV+kc74QskJnku9y8bcRI3GEuIYF0EIPEmgEzbXg55Z+E3bvmZ1H8sQhD3J//7tpk1/3aIl1Jcnutb7G1n2AY0RkvmlUHbBg3zvDqVvF6b37cPrNt7CpspIqr5djZz4TOTsVwKmU7dhGt+Z1115O1ww2hb3XhJGtJX44dRfQAsND12EYts092JvDqVtJ2yLTXawxnY1KgSv6GNDqME1gLBCnp5zYxtYici0w3bRf/lpE/EBr6hBOPdu9xqGA3Kjesx0+B20LI/0YhxHqAC/Kkc5FE4s2/GcAxwOISB8gF9iC4S7kfBHJE5Hu7K3h1DPFX775lCmLa7whFOXkoB6QHGpaPT+8NDwJS7QEa3Fp617Vsh2JqcBUEfkBqAYuM1u9bDj1WMS2KjP4754tvLHYnJCZ32Glx4NLXFza6xDmrl1J/1YdeOSYU2LGJqv9vACB52bKu7rPAhNEVa0Gok7LUw2nvs8IXaJdgLcrwwUu8N6ryiHtOnLPkUn5lon7vNpp6Wvt7LXjkIjsmM7EG2fS8M6KnyytSypk914bMU6IOdEf3iVGOKYYrF27FoDly5czffr0BLnrSSCWXoLDTtS7ezW3PBYAa1V1hDmDeRXDBH8hcImqVotIHvAiMAjYCpynqmX1fX66OLWwNe/t2hKeaMYhPq9vajYPHo+HiRMnBs+///77sPN0Yzd19ESkY0x3E4Zn9YD3xYcwHCK/anravgLDi+MVwHZV7SUi55v5rNkVT4JTCtuS26Et00t/DKblOZ3MOeu3KZeVk5MTV8gSTWpSQS2aSKSTegmdiHQGTseYudxiuoQ9Hgj4Tn0BmIghdKPN9wBvAn8TEVEbxYl6/NgR/GXIicxYMwaPluMgB5HjMRzHJ0+nTtb6srPPfzA56tvSTQbuAJqa562AclUNRAEJ3YcL7tGpqldEdpj5a/Vp1uNxbaJ8vxd4YfmfASM8uUsUv3j4ZN21tG8yhOGdU3RjEWdmqgmup8o+M3sVkRHAJlUNtYiOtw+Xskv/zZs3R7klvXi9Xnb0+AdOZxUOMcZwLlH8OMwWRNmwJ+4CO1W7XmX7+oPYtq4vvbu8YiTGGdVL4HoaMIqUhIedqK+j61Fm5JR8jDHdZIxIOC6ztQvdhwvs0a0RERfQHIhwE2p6/Z4CMHjw4Ix3HJ9tvAsHGtbwiIBDFR8OXPgBpWTzMwxqc23E/TvWH81Of42L3YLWn3Fo8zkk2H5MK3ZbEklEfcI03aWqnVW1G4YS36eqehHwGRBwc1TbpX/A1f/ZZv4GH41sdv8YNV0kfDFX1RORx7P78zCBC+DLUXZtviDmM9MfS6JxLZlkYtozAWNSUYoxZnveTH8eaGWm30JNoLoGpdDVLurynGpgPGCsGg9u+7uIPLt3xv4Iu6q/SFMN46MIfr8j4WEn0rINpqpzgDnm+xVE0RxVVTc1MSVswwkdHuCtstGGkJm9lKohak7xA0Kr3INi3G2PICY2a8gSYq+fQANQlNuO/A2n4EeCXZEfQ/XIIS6OajOR0/Z7Luq9Bc0ejFluYe4RGapxLfaxicRew3nHTgQmsnH3D/jVQ4fC5NblcgqG0rS8GxW1NlbyySWv+F9pr2dMGllTt8+3dKG0KzgoaYELUNzxK9o2v59CKaZAinBvO4r53z6FKycnQ7WMJNvS7YPkFV1OXpERDO+rhdb6XlHA77eXUCUi29I1dgJhIBMdaSCasXVdIltnW7o0UO52c+msV1hasRHxwVBXG6wzy7FmHa6WsXWViLQNufyLqiatipNt6erJlt2VDH77MZbsWoff6cOb42O2bODEt/+e+OZ0oUkc9SeWsXXKZIWunpz/8Suoo2YbLWDwtbJ6M0u3bbSgBoknEZpZY2tIMbJ1tnslvq3q1NK5/HXZJ8HGopkrn3eHjqc4vwCAsj2bieW548/fzOblk2NFyE4jybVkmTK2DkS23ioig4AZInKgqkb3OkRW6IDYhtH/WfMdTy77JCxtp9fNCbMfpOT0ewEQdeDX6H7qmpvxxjKKgqZp9loXY2tV3UyKka2z3Wsc/rz4najpPpS3Vxn/02PaxLafeOjIUzNSr0gkiaPeRDW2FpE2AS9NyUa2zgpdHPb4IzVLAnywbjEAU4efS6HmR2h1XNjlMIrywt2FZcbuFasmElOBHqax9avUGFsfC3wvIt9haIQnjGyd7V7jkCNOPDGM1Y9s3Sv4/vvzb2N66WKmLJmHt3I3Ywu7cPFRkb4BM6bJZcGSSSxja1V9C3grlbKyLV0crutzQsxr43qFT9LO7NWfD0f/lpub96Q4hnOdjGDh4nC6yApdHMb1OoZTOx4clubEwVvH3BD3vlge4dPt5DpAY1PizHavUXi0ZC6vlH6LU4Q7DhnKA6efw8rKzbRwFQaXSuIRqxvNWPfayPZes0JH+DrdAa88ym5fzQTi9nnv88wP8/j0jKvT8qx02rwGy7RZS5aIbPcawp1fvM9unyfCndyKym3MWfNL1Hsq3Bt5e+XFvFM2DrfbbXGNSW7majOhzLZ0IbxTtiTmtXu/mcWwzuFrcv/+ZRTbPBXB7/T5slMo6toM4mz3p7+Ltd9EIRHZlg5j4J9KOCiABZueYaunIiQSoqA4qMitoKx8bkbqGZNG1tJlhQ6CUWxGdzswZp7mBS5umTedSo/RhS7a/krMvJ9tvCftdYyLP4nDRuxzQhcvdNODR59GgTMncrlBlcU71vHuqiUMfPsR7il5D7/hGyJqOT7iej9NL9l1OvsTGqQuGj9eeBs3HHA0LXMLKHLmIg4vrnzDFDFwvPLLt+Q7CojVb7XM7RI1PVOIJj7sxD4ndABjx46Ne/22Qcey8LybcOV7cMawr3ln9SicpsuJGhQXPs7sHrvrzQjZMZ39mTZtWlL5qtVHrC60vMrPOd3+Qb54ceDDiY8C8dO6NFXdyH2P7JIJsZU4+7foQMmWtUQTvMt6D6F1fh+u7Pt5eFk/Wx+J227dZyIaVUt3ww3x9zzTzfPHXGgqZ4Z3oU1cTi7tfbildYmJYmyDJTpshK1buh07dgRbIYBTTjkl7HzkyJFxF1vjbTmJCDNnzoz7/KKcfL4aOZ4LP3uBlZXbEITDWnflhWMuSvGTZJhG1tLZWuiaN2/OiBEjkhKQTNE6v4iPT72+QZ6dLI2te7W10AWoq9ZGvOuh10JbT4CP1z7DdzsWMqTlsQxtf0kKNa0pz8qAdFa0dCLyGtDXPC3GcPM70Lx2F4Yjcx/wO1X9KF5Z9XV0XQw8BxyE8dEvB5YBrwHdgDLgXFXdbjrBfgI4DdgNjFXVhfV5frpZW7mU+5bdR2Di8Mvaj3h17Yc8fOATNG2AOK5JY43mcNATvog8Buww34dGtu4IzBKRPvHig9V3IvEE8KGq9gMGYLj2vxOYraq9gdnUOD88FcNoozdwFYbHdVswYsQIRowYwf3L7qW2QYsi/N+SGxu2gnFIZmE4nd2v2XicC/zbTEo5snWdWzoRaYZhlDEWgjr01SIyGhhmZnsBw1niBLNyL5rGHPNEpFhEOqjq+rrWIZ1Uusvx4yByeUTwEG7YOmPtG3y44d3geaGjkPv7TybflU+DYO3s9Bhgo6r+bJ53AuaFXE8Y2bo+LV0PYDPwT9O6+zkRKQTaBQTJfA34vEg57LaVVPiSiywwZ+OsMIED2OXfxS3fXZOJaiVFki1dQgt/EZklIj9EOUaHZLuAmlYOLI5s7QIOBW5U1fki8gTx/Qgn7dIfo/ula9eu9aheanQo7BXjSngV31wT3dmhHx8l2+anuVZJkiYL/3jG1gCmV/wzMUJtBbA0svUaYI2qBv7Tb2II4UYR6WBWsgOwKSR/wsqp6hRVHayqg9u0aVOP6hmkYgizX34e4ZuVxuvBTVsF83jxRtwXYP7WL+tQw3pi7ZjuRGCpqq4JSbMusrWqbhCR1SLSV1WXASdgRDf+EcN1/4NEuvS/QUReBQ4HdlgxnlPVpO0S7jrweab8fCsLd24AjGnEsS37ckH3Gv04Bw78poLajwu7snFNq+CX+m2Rk7v6eJMKQpxWrFunO5/wrhVVtTyy9Y3Av0QkF8OVwDiM1vN1EbkCWEWNR/X3MZZLSjGWTMbV89lJk4qK+FW9H4t7/eT2I/lgwzssX9yJTatb4QgZNeyo9HHP92X85dBYXXVmEIuUNFV1bIx06yJbq+oiINo4IcJK2Zy1NvjSfrTuNlQoP1w7nz8teYuaIahybpfDGL+/8dsZ3elsNrnXM6esOrJsoNqrbNjdAAY6jYhGteGfDlauXBlUTw8cAdxuN39aMp3aa3Wvr17A/E01kXV+2/NGUAcSY2404a8WOkQ0HpnVp7MzZWVlMa+d/3UgLkSoMBnvJ3z/YlhekVjfpTD3tZcjUjMWZNjixeF0sM8J3bBhw5gzZ07Ua9uqd8e4S6j2hw+cRvTvF5FLgdxcBwd2bBf1uRkj29LZn2HDhkUVgmY5eTHuUGo723zkrFM5omcXw+4F4yhoksPcW6N7AsgKXQ2NQsukPsRaLgm0dpMnT2b8+PEAbN+zg1Pn3g9mEDoD4957+p8bUca0y4xgj5srKmnRJN/6pRLMUafNTAwTsdcLXaLlkptvvplevYwljuL8ZlzX83ie/mV2WJ7j2/VjeIfYi/ltmhZFpE2ePJni4uKERkD1xoZjtkTs9UKXKpf0PJmt7o9ZVL6dNnnw+4MepDi/beIbTQK6eYHWM+NCB7brPhORFboQtuz+lXO/nMwefy7QhmW74LS5j3J7n470aXYeVT4fh7bpnFRZlsZPzgpd4+Xcl59h87LOhkV8jo/keOY/AAAVCUlEQVT8IVtxNYVJP69h3XYj/KYA4w8axnUHJAyXYBmNrXvdJ2ev0ZiyYDWbf2pr6qYJVDtxf9EW7/YcPOrkgOZrwIwD+/gPc1i63YrAJEnSyGavWaED3F4vK3e4axzSQXD11/1NMQBNcgLbXsb1G+a92QA1jYIas9dEh53Idq/AZytieKAXAb8DB0rJllB9U2HLnkpL6pYUNmvJEpFt6YDivPgBgQ8sXA2EqqIrPZvZx1Anuw3WCDlyvxZGr1n7y1Elt8DNp2sPCE0E4Pnf2MjgOjuma5yc0btNjeCZR67LyQs3XUaB0xVMzHe6eP24cRTnN5ARTm2SETibCV12TGcypEsx9/z2fCa89AGrtuzgvKMP5uyjjBgS3591V8rl1Tbgrk26jLEF+3WficgKXQgul4vHxqXme9gOWCF0sSz8RaQbhr3zMvPaPFWNaxqXFboMsbe5lYhl4W+SUjj1fUbopg64mab3XUTlmucYd116NHtnr3+Od9bPolpdCEoTh4fX7/qAtT9EX05pzAHpAoRY+B9f1zL2yolENDuIy7+bzDmjDkubwC0r/5I3131GtbrAdOe/25/L6GkjI9ThVZWhQ4cCGdAgTl5zuL7h1APUtvCHbDh1a5i6chJKHrVV2304eGrZdVzf9+mw/AH9vYDQlZeXp68yybV09QqnrqoBU9LaFv7ZcOpWsUedRHdaAGvc4S4q5syZE6E5XFxcnLa6pGubqy4W/qpaRTacujXkSm3P6jW0cDUJvl+0aFFmVdVpWAv/bDh1CxnVPjA7Df1GFQfK9T2fYOLEicyYMYOBA5Oe1NUNaxeHIyz8yYZTr42fyY8+zs233Zb2ko/tcClLK0pYVLElGAXJJT4GVPbgs1n/y5zJYTQsmr1Gs/DPhlOvxYZyd1IC53PvZsnHcX2+ROXSrg+xurIFP21sw/erOrB4a3s+lx0pB7erD4Edica04b9Xt3T5VdVA4kjUTody4ElxnUdG5fRP72LNwv2obmpMKBzVsD3fzYg3zklwZ3oRv82kKgF7dUtX3C7SSmvQOZGuXN00iUhLxIryUlZ/25HqIgGHcfjzhQpfPut27F+n+taJRrjhv1cL3dbySF9y0jZKsDi/n7kLU1M/f3Te+3gKBZy1lk0EKtZHCnsmaWzd614tdC3zw92kLbi/B+1GRXPjpRx7aGoOGN3bWkb/Mh2C32VxhJp9qaUTkfEissT0S/tvEckXke4iMl9EfhaR10zfdZieGl8TkVLzerd0fIB4bHSHf/lauR9nbJwXlvbxxx+zeXs5qf4rxh52VPQwqn7F5bHWKGGfaelEpBPwO2Cwqh4EODHWcR4CJpku/bdjBLXAfN2uqr2ASWa+jNK6OBet/CV47qnO492HmoXlOemkk+jUoQ2eFMs+tncPmu52gi/kG1VF/LBu+hv1qHUd2JdaOozZbxNze6QAYx/ueIxFQjBc+gdCSY82zzGvnyCpOASuS+W81exatSx4ftStR3D3yM8i8jmq3cS3kojO17ffSBctwuFWxKvkVQqjilpTsSjmDlD60X3IGkxV14rIoxguXvcAHwMlGMp9gRF8qNv+oEt/VfWKyA6gFZCcL/064K3yU3TAacHzPtct4tM3I2ev291Qunk3qWrA5ee4mDs+XF/xvffe44m6VLaONEbN4fp0ry0wWq/uGOF5CjGi4tQm8C9J2qV/QP1m8+bNda0eAK48qPyxJubDj29PYcxNkT7oWjRzcFinxOt5tkU18WEj6tO9ngisVNXNquoBpgNHAcVmdwvhbvuDLv3N682BiD26dLr03+EtoOiAUcHzT96+EXXPjpIzF8h8H5Sp0cQ+M5HA6FaPEJECc2wWcOn/GXC2mecywl36X2a+Pxv4VDPsZealKZPCWrpTz3yNkYt+E5Hvq+0+Gu3q0b60OGwGLXkTWAgsNsuaghEH7BYRKcUYsz1v3vI80MpMv4X40XXSwg3XRXrFfKNLTeDFNWsMDZ0hTXaxat77ma5OxtTV95mJBICq/hH4Y63kFUSJgqeqbmpiSmScIUOG8PHceby2sg9Xh9hKL5nx1+D7zp0Nt18eCul6xGm1i0g7yQZRSblcmwlVIvbaDf+vv/4a765dXH16pEPqUJYvX05+fm2PwpkhIy2dYruJQiIa6UAmOVyFhQnz9OnTx4KaZJZ9aSKx11BdHRn9pj7MnDkzreUlxIKJhIgMFJF5IrLIXNIaYqaLiDxpbm9+LyKHJiorK3RAbm5uQ1ehzlioxPkw8CfTqPoe8xzqELF8rx3T7TOoWqXEqUBg47o5NeuvKUcszwpdEkxb/hWP//BfqrxeOhc1Z+qxF7JfUauY+UeOHGlHR9etRSR0U3iKqk5J4Sk3Ax+ZW58OjI0AiB2xfN8Sumhf+MsDB9LpiGKOe/ZZIP6MNpQrP3+ZOetXmmfCr5XlnPD+M7x5/FgGtk7O03qmSbL7rJexNcbi/3hVfUtEzsVYdz2RJLc3Q9krhS4aJy9aRAGExcJJhNvrYc76slp3GE7sxn3+L749Y0J6K1kXFEhT9xrP2FpEXgRuMk/fAJ4z31saTr1R0QZDIyGV3c/nln9B9B+tUOFJVQMvg1izDbYOGGq+Px4I+DJ5F7jUnMUeQRIRy/eZlq4utMlv2tBVSAqL1uF+CzxhKmu4MWaqUIeI5Vmhi8N5PQbx+wUfENkpKz2atmigWkVixexVVf9HiA+TkHQlxYjl+0z3WlfuO/RkqOWMOEccvDs8eohNy2mEWibZli4BF/Q6jDO6DeTW+W/x665yzu42gLF9jmzoagUxFodtJlUJyApdEuS7cnjq6PMbuhqxyWqZZLGabEuXxVpsOGZLRFboGj2W7b2mjazQ7Q1ku9cslqJZdfVGzU3zX+I/v5aaZ8a/ZsrRozi+04CGq1QyNLKWLrs4bPIffylfbP2RokIfRYU+mhftIT+nmqu+eBe3251SWXuj5nA6yQod4MXLfNcmvKabft8uoXpTLuJQnA4P5/wvoTJsgyJ+f8LDTmS7V+B9x0r86sBXJfi+boEjJHK6s5mXX/vvatD6xUXJLg43RtZQARAUOAls7is4drjI+SV5n06WBqIDBG10i8PZ7hXooc3x7ZRwgTMRBHf9/Phknn3Igc5ewynaE3bGsQize/eVFbrGxcSJExk5ciSlDzwbVa1YAYedByGBMV2iw0bss0I3ZozhIHTixImoKnvK1tKyRUGtoEsGVx4XP8bEhS+8Rt/7JtH3vkn0mHAvOW2j2bZkDitmr3GMrYeJyA4zfZGI3JOorH1S6BYtWsSMGTMi0uf+4Rr6dGuD34nhxDoHLjtxEDedfHTMsg596G8sWFVjh+IqakqPGyewYvPWTFQ9Ckl0renpXmMZWwN8rqoDzePeRAXZuePICNHCYIYy/XcXJ13WrKWlVFZ7jF7ZC/hBco0Wcty/3uK/N9c1jm8KWOdAJ5axdcrsc0LXrVu3tJX1jy+/wbEHcioxfMsD+MGbDxuxcG3PmjFbLGNrgCPNKIjrgNtUdUm8ghJ2ryIyVUQ2icgPIWktReQTM1bEJ6b/4bjOVETkMjP/zyJyWWqfN310794dEQk76krbwkJydmMInJiHA1zV4LTQQlFUEx4kEU5dRGaZMUFqH6OBazGMrbsA46lxdrkQ2E9VBwB/BSLHLbVIpqWbBvwNeDEk7U5gtqo+KCJ3mucTCHemcjiGM5XDRaQlhvPEwRjNdImIvKuq25N4flpJ5O5h0fI1vPnxtxzctzPnDj8kbt6KtXtqhC2AacNTtNvCTiS57jWhhX9djK1Dw6ar6vsi8rSItFbVmF7zE/5nVHVulOg2o4Fh5vsXgDkYQhfVmYqZ95NA8FkR+QQ4hciAtQ2G1+vlpKuexr3T2AP7dM4yJj83m7//+UL69+4Y9Z4123ZEL0zAb5VipSr4LOlfA8bWcwgxthaR9sBGVVVzRusA4s6i6jp7bRew4jZf25rpsZypxEqPIJ0u/VPh0t+/jHtndbDhEgAfXH1P7N/Fwd06RL+g0KVV8wzUMgbWzF5/Czxmjt3+Qo2x9dnAD2b6k8D5iRyYp3vJJJYzlaSdrKTTpX8qlK3cElFJAfAoC39aFfWeh8eeaihQ1l7cU3j6ujMzUs+oWCB0qvo/VR2kqgNU9XBVLTHT/6aqB5rpR6jql4nKqqvQbTS7TczXTWZ6LGcqKTtZsZw438vPq6IPT1wuF9MnXEKBOI0ZpILLD2MP7kD7Fha5pAg40El02Ii6Cl1oTIjLCI8VEc2ZykfASSLSwpzpnmSm2QIRwSu+6HIn8PmeNfR8/HF6PP44fSdN5l+LFgUvt25ZgBy/G+/QnXiP3UnPYX76trUy3quC+hMfNiKZJZN/A18BfUVkjYhcATwIDBeRn4Hh5jkYzlRWYDhT+QdwHYA5gbgP+MY87g1MKuzAzJkzGXG0MVkICF5Q4baVk/dXlBrvBTzq5+5PP2XKN1+zwV3OkR88zA6PO3jHEiqY4CmxrvKKMZFIdNiIZGavF8S4dEKUvDGdqajqVGBqSrWzkEN7tuDIIYO5/9mPqdrjweEUhg/bnxd3LY26JPLI/77gmfWfhCTW4EcpGtKHXd/8bI1HTptpkSRin9uRiMfwI/dn+JH7B89fW7wYPlkamVHAp4rb5yGWx7sD7x7H/JF3ZaimtcgKnf3ZtKGchSVlDDuhH/n5+THzHdi2bcxrBgFvTpGC5/N6ee+992LeOXLkyOQqmxD76cslwtZCV1JSErZNlU8RbirrUWI+wwfeETx7/A/gxcNnix4AIncrDmrXDqcIPtXa7uno3bIlFbketlfvifqkhdc+zsiN5fWoa5IoYDPDm0TYWrVp0KBBVFTsZlTLcQzPu4hj8kYzPO8ifjv4DlQ15WP4IYbAhS4Au8jhzBMfijn2+s8llxj/pBBzvmY5ubx09mkcVBzYxQu39yvGhX/D9rh1SStZzeH0ckHn69izqzpsg75s8VpObnF5SuXM//Jn0MiOUICNfjePvDuHXzdHtkx9Wrem9JZbePK007iwf3/ev+hiDj98FRd88wC/VFfRsXgHeS43gpLncHEZ3fl9zsC6f+CU0b1v9tqQVLurqXJ7IjRBRATdU834i59h0svXxi3j1/LtfFi2jLIZv0RcqyqAyj5Nya2E6S8v4O2XF5DfvYBPH7ouIu+Ifv0Y0a8fH679D6W7wicQrYqqgSp+3/d0Tug0PGZdQls4VU1P0GEFtdk6XCJsLXS7d0YfLwX46YufY17zer0c+sYT7HKYZXTy0bNWnoq+TcmrCA9l5F6xmwsffZlXbouuzPlU6UcElOfcXtjjzsfl8tI038Pk0ndjdp0B9fiMYLMdh0TYWuiKigtrNthCML5YjTuAPnr60+xy7CHYmHRwog6/od0LuJsRFLhQROGX7zbELNdj5l9fXoQGRifeXCrc0LZwZ8z7pk2bFvNavbHZmC0Rth7TuXJd5OS7orceublIXmwj6C3+ndTuvVZOyMHvMob7nmax75U4CpjdCvPZXFFoClyYTgqbdjWLek95eTnFxcWxC60Pav74Eh02wtZCB3D7zDtQMyJ0cObncuFo3hTpGjs+V6woJStvy+H9b+7mg9duQ6N8egV8RbHHWpP734vH54ryAOP8P6sXR9yTMYELkJ29ppe3Z3yLb0B32K8TjratcLRphbRthadjMVXxxjKxftx+QzukeUE+Lfs1N6y+TBRQB+Tu9rFyRZR+HczF5FhCKSzfuTF4NnCgFbNYRX2+hIedsL3QtSsuxFnuRkXxdCrG07Md3q6t0Cb5OFyxqz+89f5hP/LA+2Na9g7mubDXAVQ3VaoLwZsLVc1B/V4KN/qZPz9ythsgz+Ekli5Uh9KK4E7EohBtlIyxD6k2WcLKZeuZ++xsnBV7cFbsIWfVNpzraswqRp0ZEcAlyLPDz+LM9gMRn6B+EJ8wqu3BTDv5vGCevPwcWq/20+zXaorWVVP8SzWFW/y4XA7y44wXHxp0BjVbYARfexS1osiZvLOdtNHIVJtsPXv1VnkiOjLHLjfenbvpdXgPbrwmph0JAI8MHcEjxPaiNHTY/jz/jzkR6QocOzR2eM6TOx/IUw4Hty94m90+Dw6E0zofxCOHnRV3vzUTKKAWtGQiMgB4FigCyoCLAkY5InIXcAXgA36nqnF1JW0tdLHIL9/NlGcS70jUFoDabrzatGnKiSd15OMPVyMOw1+T368sKHmBlq3uIB7Hd9yfklH7h6VZLXCAOW6wpCV7DsOm9b8icjlwO3C3iBwAnA8cCHQEZolIH1WNOZBslEKn3vQNjPv2K6Zb96aUraxABPbr1pSzz/4xbeVbgUUThb7AXPP9Jxia33djWAC+qqpVwEoRKQWGYCj+RsXWQrfTs7nyw3V/WxbtmsiTGX12WraoDFoDsWxA96tv4RVs/2iWvtk6iaz59Qyn/gMwCsM04RxqbF46AfNC8sW09Atga6EDliUyELY7IrIgk59BVU9JV1kJwqlfDjxpemV6FwhxkhtZrXjPsbvQZbGQeBb+JicBiEgf4HQzLRtOPUtmEJG25qsD+APGTBaMVu98EckTke4YLkW+jleW3YUulTGHXdkbPgPABSKyHFiK0ZL9E8D00PQ68CPwIXB9vJkrgFhirZQlSwh2b+my7IVkhS6L5dhW6ETkFBFZZjpYvLOh6xMLEekiIp+JyE8iskREbjLTJ4rI2hAH0KeF3HOX+bmWicjJDVf7hsGWYzoRcQLLMVxWrMFwRXGBqtpuq8B0INRBVReKSFOgBBgDnAtUquqjtfIfgOGXbwjmthEQd9tob8OuLd0QoFRVV6hqNfAqxnaL7VDV9aq60HxfAfxE/BX54LaRqq7E8PsSP2bAXoZdhS5pJ4p2wvRYeggw30y6wfS9PDXgl5lG+tnSiV2FLuWtlYZGRIqAt4CbTZWfZ4CewEBgPfBYIGuU22392dKNXYXO/k4UQxCRHAyB+5eqTgdQ1Y2q6lPDKPUf1HShjeqzZQK7Ct03QG8R6S4iuRj6Wu82cJ2iIoY6yvPAT6r6eEh6qEPiMzC0NKAO20Z7G7bc8FdVr4jcgKGz5QSmJgqI0YAcDVwCLBaRgFHE/2FsGw3E6DrLgKvB2DYSkcC2kZckto32Nmy5ZJJl78au3WuWvZis0GWxnKzQZbGcrNBlsZys0GWxnKzQZbGcrNBlsZz/B7X4oVeyFHwiAAAAAElFTkSuQmCC\n",
"text/plain": [
"<Figure size 432x288 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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S1ZLK9mclB2OSQlxOcThS+HbfgcAUZ1F/YKqq7lPVrwnf3nBmVfux5GBMMrg/rWgZ6crAmYbW4GjnA1tU9SvneUX9rFTKTiuMSQb39QnfVtaNgYjMBY6Kseo+VY3cHX0tB0sNUI1+VqJZcjAm0eLYCEpVe1e2XkTSgSuAblGLXfezEs2Sg0kJ/9uzk5yxL1O8O0haIxj7y8vo1bmT12G5lsRGUL2BVapaGLVsNvCqiIwjXCHZEVhc1Y6szsH43hvLltPn3on8sPMAGlKCPyi/fuotbpo0zevQ3AuJu6n2BlH2lAJVzQemAV8C7wLDqrpSAVZyMCkg74W5AEjUqbOifLq0EHI9CqqaJEklB1XNrWD5w8DD1dmXlRxMSpBydWqR51M+/cyLcKrH7ZUKnzWxtpKDSWnpaanw+yZ2V6YxCSFOV/zlTisArj4926uoqsdnpQI3UiHtmnpu7C19gXBCiPwDOO+sLA+jqqaQy8lHrORgfK/PyZ05609ZXPbo8+zdeYD0DOHZW6+k+7Htq36xH1hnL8YkTmaTDP6Vd7vXYdRYsq5WxJMlB2OSIQWTg9U5mHqnX79+XoeQEqzkYOqdOXPmJP2YdlphEqKouJhfTHmDFRu3EAgI/U7pzJh+rjrzMX6gxKtpdFLZaYXPFQeDdH/kGb7YsJlQSDkQLGHm5/mcPe4Zr0Mz1ZGCLSQtOfhc7quvE4pqACTOv++KfuC9VWs8js64Jepu8hNLDj63fMP/DrmvIOLJhR8nORpTYylYcrA6B59LkwBBgjETRJNGDT2IyNSIz774bljJwecGdv9xhevG5VyaxEhMTbk9pUi50woRmSgiW0VkRdSyPBHZGNVHft+oddXuH99U7HcX9+SoZk3K3FegKH1P6US7zEyvwzNuJa+zl7hxc1oxCfgrMLnc8sdV9dHoBTXtH99U7oPhQ/lo3XoemfchTTIa8mi/S2mTeYTXYZlq8FupwI0qk4OqfiAiWS73V9o/PvC1iET6x7eas1o677gszjsuy+swTE2lYHKoTZ3D7SKy3DntaO4sc90/vogMjfTNX4sYjPG/ulrnUIFngOOBbGAz8Jiz3HX/+Ko6QVW7V9ZHvzF1Rn25lKmqWyLzIvIc8JbztEb94xtT14nPOnJxo0YlBxFpE/V0ABC5kjEbGCQijUSkAy77xzfG+E+VJQcRmQL0IDyGXyHwANBDRLIJF4TWAzdDuH98EYn0jx/EZf/4xtR5PjtlcMPN1YprYyx+oZLtq90/vjF1mg8rG92w5tPGJIMlB2NMTJYcjDHlCal5tcKSgzGJZnUOxpgKWXIwxsRkycGYxPp63RZGj3yNbTv20jAtjRuuP4frbjzf67CqlIqnFdbZi0kZK774hl/e/CL/2/MDJQ3T+CGgTHjl39x958teh1a1FLy3wpKDSRmjRk1FAwIB5/4+Cc8vXbWRoqJib4OrjIavVriZ/MSSg0kZe4Ohg4khmgjTX/V5lyEpWHKwOgeTOrSCb49A6yP93TOW1TkYk0BZRzWHULlvmSoSDHFZ/27eBOVWCpYcLDmYlPHcpJtoFCJcggiFJylRfjPC571wu00MPksOdlphUkZ6ejrvvf9/vP3mUubM/px2Rzdn1P39SU/398dYSM3TCn+/q8bEcFn/bv4/jSgnGclBRF4DTnSeZgI7VTXb6SB6JbDaWfeJqt5S1f4sORiTDElIDqp6TWReRB4DdkWtXquq2dXZnyUHY5IhiacVIiLAQKBnbfZjycGH5v8zn7F/fpviUAkSgrO6deBPYwd5HZapqerdldmy3HANE1R1QjWPeD6wRVW/ilrWQUQ+B3YDv1XVD6vaiSUHn5n/z3weHDMn3NgnPQ0FPv7iv1w78C9MmXaH1+GZmnKfHL6tbLgGEZkLHBVj1X2q+qYzfy0wJWrdZuAYVd0uIt2AWSLSRVV3VxaIJQef+fOf3w4nBolqCRgQNu/6ns2bd9KmjY2PmYri1TRaVXtXehyRdOAKoLTG1hmBbp8zv1RE1gKdgEoHlLJ2Dj6zLxQqmxiivP7aJ0mOxsRLEke86g2sUtXC0mOLtBKRNGf+OMJDRqyrakdWcvAZCWnsEqjAiSe1TXY4Jh6S28BpEGVPKQAuAB4SkSBQAtyiqt9VtSNLDj7T/dRjWJxfWPYGI1UCB0Jc3Kerd4GZ2klSclDV3BjLZgAzqrsvO63wmbHjfs6RTQ8rbR4cSQyPP3qd16GZGoq0kEy1gXSt5OBDr71+Jxs3bmf61EV0PuloLul7qtchmVqS8jeMpQArOXjiM2Ze24wu0zfw/LVNaHDjS8zbE67ODm2cwsQRbWnXriV33XMZO049CdjGkjGt+fX5DRBpS+sxH7Ppy+GI9KH3+xsJAuxZQFsRRE6hy58+Ij8EYzN+wpVXtkakLW2fW+XlH1y/peiNV5YcvLT9U25t8BTvPnUDvZqG/ysWPH4LN+/5K1+UKCWFT/KLV5aHv/zAEVP2UrJyAKeN/gnHPvZTVj+7lnm3TuGN4A6W/OUGflu4j5LCX3H5a5dx3Yz/Ij/6lA/PmMNW3cSmX3X27u80KXlaYcnBI5q2jzX/3sNrMoxLRsxiuXMdvOcDbzK9/XKWTLqFUYPuLvOa0e0aEjihB70ancOAoRdzXPbpNCoMQXAuCyYWMqxdI9LaDWfsF7tZPno6uv0MelzYhVYe/H2mHCs5GLekpBGd+vUk5+F7uHHyNfQeu4htwMzb+jN091F88805nDHlC9f7CxWehKoenAruSVzwptqs5GCqLdDuN/z+7YvpMvr3DFu0k4LpzWlzzqXcn3cV5375G3c7Se9Nz/v3MGXjfggtZ949bWkw8p+JDdxUT10sOYhIexGZLyIrRSRfRIY7y1uIyPsi8pXz2NxZLiIyXkQKRGS5iJye6D8itTWm7cV/45GHv2D6gN9y/ewutBiYRZp0JPvdy9g3bzkfhTKq2Edzut/xMne3a4SkXcK1oT/x6p3nJSV640KK9j7t5lJmELhbVT8TkabAUhF5H8gF5qnqGBEZBYwC/g+4lHDzzI7AWcAzzqMpdTpXTNnFFaXP29H93g3oveFn82P9gozaGn5Mv5qRxVc7C6dRHOmRvWkPNpXvgLX43/EM2tRQqvYEVWXJQVU3q+pnzvwewj3KHA30B15yNnsJyHHm+wOTNewTIFNE2sQ9cmNSiaq7yUeqVefgdDd1GrAIOFJVN0M4gQCtnc2OBjZEvazQWVZ+X0NFZEm5e9eNqZNSsULSdQtJEWlCuH32CFXdLRXcOUi4FFXeIX+204HFBGffPntbjN8UFwe5YfgLbPp2DwCHN0rnifuvokvndh5H5oIPKxvdcFVyEJEGhBPDK6o601m8JXK64Dw6J8UUAu2jXt4O2BSfcL0X2jgJEUGkDxdOXcW28huUtlQUGtw4Lrxs19P8X1txXncCXaZvKP+qOAtStOg68jYFK96kaMrBOEL5pTHLhfeSt3JXxa/zSJ8bnmTT9j3hG9ICwvf7gwy9byqFm3d4HZorqVgh6eZqhQAvACtVdVzUqtnAYGd+MPBm1PIbnasWZwO7IqcfqW8t8x+7mxUlJezJ70z7G+4jb1X0GI27WfPqTTy5pwQt+YJ3Wz/KghCENuezdNsontpZgmoB+Ve3r/AIcVE0nWfumV7JBoUsGT+y9FlozdMMyN+JlnzB3G6TeHDMvMTGV02vzlxEULVsPxciIHD3Q697F1g11MnkAJwL3AD0FJFlztQXGANcJCJfARc5zwHeIdyRRAHwHHBb/MP2yvH0GredLoEATTqdx4/T3mbBf6LLDkfQ6eYCrm4SgEBXfnr1eSz4336KNqxm4U87cnLT2G93cNFAjm5wHSOGtUUufJzphQt4/tomiLQlP+oDEyrM4xcZt5JXuB/YS8YvZpS2rDyokCXj72XM1oqGhwtStGgkP3/scOf5PrYs/4TbTm5WGnOj1wrKvWQ6XW6+igtFELmcgYvWh0saFz7I0xv3u33zauyd+fmxV4iweVulPZ35g5KSFZJV1jmo6kfErkcA6BVjewWGVTeQyy+/vLov8cyM6zO46pUWtLrrFaZdckhdKwChjeMZ3e8b/rx1AwvGfQrH3kYLYMkfO9A3MJX8UWeVa9Z8LJ3+WMinzxzFOeOn8s2UIvTl6Qz8tIhpZzUBINAujxe/n8fzZ7XhxN1QtHp72f/AoimMOW4Cn835nC29hvKHQ6IqZMkfz6dvYCrrtnzDWW8A7Gbjug2c4myR3v5krtl3aCdBra98lvl/e53gooEce97f2KRbWTKmC+e9chlDRnanUbXfxdjGT13IK39fSkgUFNof2YwOLZvy9eYYfZOo0qhBatxYnIq1atZCsgau/H/FaMmbPLt9MBf9fsGhGxS9w8Q7/8A7Dz1HgOPp+eguDrxwBV0DcPQJLdg2P79MiQBge1pzWjUO/3ektTyCFhUdPHAGF9zUnDV7bj4ksy8Zfy/jfj2Gp86K3c9k0aKR9H3iNp66/QyalFtXEPMVB7VqdrAh1va05lVsXTPPv/kxL7+7JJwYJFy3sGHrLj7bvPXgr285t9xwfkJiibsUbCHpm7Qbufqhzgcg+mpIjx49AMjKyiIrKwuAnJwcsrOrNUZHfAW6cs5lJxK89zMYGz08QJAxg3N5uftMpg09pcKX11jR28x48HR+O+RttvHHMqWPBRPXs23t2bQeHVnSAjb+lby24f/mVfPnsm3bFAY2jdQ3HE+Xae8z97j2RH6Xgxu+ZG768fGP24XnZzl9ZJarWygq3s+vrjqLl15fROk3SOEn2Vlc2df/I1+laiMoXySHbt26sWTJEqc2/+AHQ1VZs2YNmzaFL3YsW7aMnTt3sn79enr06MGuXbs49dRTyc7OJi8vrzRxJEzoU2YO7s35L++iVWg5H88poNVN0b9cQYq+vJuXL5rHgltOCX9xndfcfsEivvlVZwpX76XrTb04r0ZltnB9wuN3TmXtyCKGLNrJtKhSwj0FSuR2q+Cigfyh/cHEANB91FZ0VGSD6XR542zyr25PaNXZ/OHLXTzV+b8snP4RW++qcqS0hCgJhcp2jxdlX0D514x7eOsfy/l2RxGD+p9JRoYvPr5VU03Jzl5EfVAJ0r17d12ypPZtoRYsWMCsWbOYNWsWOTk55ObmJqd0UTSFP560gY5fj+RqP35enfju3TCy6m09dGbuOJRyVyUAVHl65FWccfKxtT6GiDBnzhzX2/fr1w9VrbBRjxtNM9vpaRcMd7Xth3NGLq1s3IpkqlN1Dj169OCJJ55g/fr17Ny5kx49epCdnc2kSZMSetxQ4Se89qsL6OHHxMDB+PzuorNOPHShKukSiEti8FKdbiGZaiZNmsTOnTuZNWsWeXl5AOTm5ibkWIHOT/LF/QnZdVz4Pb6Ih2+9jI1bd5C/bkvp9bGGaWnMeGSIt4HVlhLuLDjF1NnkAJCZmUlubi65ublkZWWRl5dHXl5ewpKEqb1JD1xPMBhkycpCso7+EUe1aOp1SPGRermhbieHaOvXry+dz8vLY+fOneTl5ZGZacPL+U16ejpnn5LldRhx5bdTBjfqVJ2DW3l5eSxbtozs7GwWLFjgdTimHpCQupr8pF4mBwhf2RgxYgQ5OTlVb2xMbbhtAOWv3FB/kwPAiBEjWLBgAdnZ2ezcudPrcEwdFW4Epa4mP6nXyQEgOzubZcuWMWnSJDIzM5k1a5bXIZm6KORy8pF6UyFZlREjRpCZmcmAAQPwQ8MwU7f4rVTgRr0vOUTLzc3ljTfeSHijKVPPpGidg5UcysnJySm9vGntIUx8+O9KhBtWcoghUjmZmZnJsmXLPI7G1Al1sbOX+io3N7f07k+7kmFqRf3XBZwblhwqkZeXV6ZlpTE15rNSgRt2WlGFyCVOa0lpaiUFKyQtObgQuVnLTi9MTUko5GryE0sOLowYMaL0rk5jqk2xRlB12aRJk8jOziYnJ6e0T0uTfG+8uYinH5lFccN00g/L4K5hl/Azn/cjKfivabQbVnJwKSsri507d1rbBw/dd+//44kHplPSoAkNgxkE9sD4P71Ln6se8Tq0qiXhUqaIZIvIJ87YMktE5ExnuYjIeBEpEJHlInK6m/1ZcqgmO7XwRjAY5OPJ/yLboYh8AAAK3klEQVTQvDmBAxAIhSdRCG7dz8gHp3kdYuWS085hLPCgqmYD9zvPAS4FOjrTUOAZNzuz5FBNubm51rzaA2/MWkxJmyMIlBw6wpKEYPEnaz2Jy5Xk1TkoEBnqrBkHx6jtD0zWsE+AzMg4t5Wx5FADVnpIvh+1bIo2TI859poAlPj7nL4aVytaOqcEkWloNQ4zAnhERDYAjwKREUyOBqJHby50llXKkkMNjBgxwiolk6xnj1OQ7/bGbAsQEmjRpvwYXn7i8pQifFrxrap2j5omRO9JROaKyIoYU3/gVuAuVW0P3EV4AGyIPZxlldnUkkMN5ObmsmzZMms9mWT/N+4G9jU8QChw8JMdCkCoEYz/0/WexlapyFB+cahzUNXeqvrjGNObhEe7n+lsOh0405kvBKKHdm/HwVOOCllyqIHMzExycnJ44oknvA6lXul7aTfmvnUvzbMas78J7G8stOzUnFdevY12bSscXdQfklPnsAn4qTPfE/jKmZ8N3OhctTgb2KWqm6vambVzqKFIl/eWIJIrI6Mhr08e4XUY1Zakdg6/Ap4UkXSgmPCVCYB3gL6Ex0v+HviFm51ZyaGGevToQU5ODiNGpN4H1XggCZcyVfUjVe2mqqeq6lmqutRZrqo6TFWPV9VTVNXV2JNVJgcRaS8i80VkpYjki8hwZ3meiGx0GlwsE5G+Ua8Z7TS4WC0ifWr6x/pdjx497IYsUzVVKAm5m3zEzWlFELhbVT8TkabAUhF531n3uKo+Gr2xiJwMDAK6AG2BuSLSSVVL4hl4dXy27ivuf/JNAP5491V0PSYrLvvNyclhwIABcdmXqeNSsPl0lcnBqbjY7MzvEZGVVH6NtD8wVVX3AV+LSAHhWtOP4xBvtV1+x6PsKTiYke+4eRpNOwV468l7KnmVew888EBc9pNoW4t3cs2HT7LnQJC2hzdm2tkjyMjI8DqsaikqLmb47HfYuHs3A7uewi/P9Pc9FWWkYHKoVp2DiGQBpwGLnEW3O221J4pIc2eZqwYXIjI00tBj27Zt1Q7cjQl/f5c9BaHwuAFR0541ISbNnReXY2RnZ8dlP4n0SP4MLp73KDv2HyCoyjd7izh73h9Yum2N16G5NnHxUk79y9Ms+O96vtrxHQ8vXEjnR58gGAx6HVrVIgPpupl8xHVyEJEmwAxghKruJtw++3ggm3DJ4rHIpjFefshfraoTIg09WrVqVe3A3ZgyueL+H1964dO4HCPRyWHn9iImPzWPV/42n6LdP9RoH6+s/9yZi06RMGTx5LjEmAwPL1wYnon6Ew5oiL4vvuxlWC4paMjd5COuLmWKSAPCieEVVZ0JoKpbotY/B7zlPK1Rg4tE0P2VrDsQn2NkZWWxfv16srKy4rPDKM89/i4zJv2r9PnLT/+TX9x5EdcMucD1Pj7833+cuUPuSMB3XQ9VYOLipeGZGH/C2p07kh5PtSm+q2x0w83VCiHcDHOlqo6LWh5948YAYIUzPxsYJCKNRKQD4TvBFscvZPeOya54+PasbkdUuK66EjFK1uoVhWUSQ8SL499n88bvXO9nT7A4nmF5YtvevV6HUHsp2Pu0m9OKc4EbgJ7lLluOFZH/iMhy4ELCbblR1XxgGvAl8C4wzKsrFZN/NwzStMzvowKkKZNG3xa34ySi+7hX/ja/4nXPVLyuvL7tznDmyn/w/PVBrMywc86MvULhiAYNkxtMTdXF5OA0rBBV7aqq2c70jqre4DSo6KqqP4tujqmqDzsNLk5U1b8n9k+o3HuvD6fxcYIGFA0oTY4X3nt9uJchuVK0u+Jf/KI91SsNnPGjSCFPyzz+uvOFNYgs+ZpkZHBu+/ZlO2F1Hl8edLVXYVVDtW688g3fN58On9XE12FPjYz7PuN9G3evy7P5ctk3Mdf1GVDxJbyH3p3H6/OXwz6FRsLVPU/luT7DeG39B/w5/x+EUDLShGfPzCW7xfFxjTmRJg+6momLl/L4R/9iX6iEY5o148Wrr6B980yvQ6uaAj7rPNYNXyWH8okgMqCt3we2TUQCu/TKbrw28QO2bip7ytKh45Gc06NzzNfcMf1NPvhgrVOZL+j3yutvLeO7vXt5/Ip+XJPlviLTj355ZrfUatsQzeef4Vh8kRyWLl1a+gWLJAIRKV2WiC+f3wUCASa9fRcvP/1P3p/9OYGA0PeqMxj4y/MrfM3Cf68lEFWlL878vI++gisSHrKpkKbk1QpfJAc4tHQQnST8XnJIVL8OgUCAwbf3ZvDtvavcNhgMIhW0B5I4XbY1NaSgPmvD4IZvkkMqS0Qbh+pKT0+vuOlC/St4+Y/PWj+64Zvk8NZbb1W9kalURuuGFG/ZX3o6AaAohx/ZyMOoDJCSdQ7Wn0MdMu+emwg0T0NRVBRFCTRPY/7Im70OrX5TDV+tcDP5iG9KDv369Sudj65j8Ht9g580ycjg84eG83nhJv6xag2XntyJrm3beh0WUD8rlctIwc+xL5LDCSecQEFBAapqH6I4OK1dW05r54+kEC2S6OvfKaSiJZ51Z1JjvkgO5ZW/rGlSlyV7Dt6ynWJ8mRwiJQj7YNUNViLEd7dju+HL5BBhJYfUV++TAs4tIVZyiB9LDHWD/T/i3FRlJQdjTAypWCEpfsjsIrIN2At863UsFWiJxVZTfo7PTWzHqmqt+jEUkXedY7nxrapeUpvjxYsvkgOAiCxR1e5exxGLxVZzfo7Pz7H5gbWQNMbEZMnBGBOTn5LDBK8DqITFVnN+js/PsXnON3UOxhh/8VPJwRjjI5YcjDExeZ4cROQSEVktIgUiMsoH8ax3xuNYJiJLnGUtROR9EfnKeWxe1X7iGM9EEdkqIiuilsWMR8LGO+/lchE53YPY8kRkY7kxTiLrRjuxrRaRPgmOrb2IzBeRlSKSLyLDneW+eO9Sgqp6NgFpwFrgOKAh8AVwsscxrQdalls2FhjlzI8C/pzEeC4ATgdWVBUP0Bf4O+GO4c4GFnkQWx5wT4xtT3b+fxsBHZz/97QExtYGON2ZbwqscWLwxXuXCpPXJYczgQJVXaeq+4GpQH+PY4qlP/CSM/8SkJOsA6vqB0D58e8qiqc/MFnDPgEyyw1bmIzYKtIfmKqq+1T1a6CA8P9/omLbrKqfOfN7gJWER3v3xXuXCrxODkcDG6KeFzrLvKTAP0RkqYgMdZYdqc6IXs5ja8+iqzwev7yftztF84lRp2CexSYiWcBpwCL8/975htfJIdb9vF5fWz1XVU8HLgWGiUgqjQTjh/fzGeB4IBvYDDzmLPckNhFpQniE+BGquruyTWMs8/qz6Cmvk0Mh0D7qeTtgk0exAKCqm5zHrcAbhIu+WyJFTOdxq3cRQiXxeP5+quoWVS3R8EANz3Hw1CHpsYlIA8KJ4RVVneks9u175zdeJ4dPgY4i0kFEGgKDgNleBSMijUWkaWQeuBhY4cQ02NlsMPCmNxGWqiie2cCNTs372cAujRrgOBnKnacPIPz+RWIbJCKNRKQD0BFYnMA4BHgBWKmq46JW+fa98x2va0QJ1xKvIVx7fZ/HsRxHuEb9CyA/Eg/wI2Ae8JXz2CKJMU0hXDw/QPjXbUhF8RAuGj/lvJf/Abp7ENvLzrGXE/7CtYna/j4nttXApQmO7TzCpwXLgWXO1Ncv710qTNZ82hgTk9enFcYYn7LkYIyJyZKDMSYmSw7GmJgsORhjYrLkYIyJyZKDMSam/w8ltoJrbvTvjQAAAABJRU5ErkJggg==\n",
"text/plain": [
"<Figure size 432x288 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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479icsEbwj8VNAfYGuA+rLwLbz7iGBjRFbV8FbBVClANlwD+klJuAhcCdQoivgTtt71VCgap1gKnB27xF69atufLKKzEYDEyYMIHMzEz0er1Hc6SmprJx40aHBehv8vPz2bhxI4mJiS6WX15entvTIRqNhry8PJcls7+O/DUOv9cYGQR8L6X8ulbfdUKIXUKILUKIQXWMc/JJAA36JBrtGJFSfgv0dtN/Ehja2HlVAsfim8YS81A4kTMWQLtxPn/eqlWraNWqFeXl5Y3yAJtMJrRaLfPmzXMJq/EXYWFhZGVlsWrVKsaNG+dkxa1YsYKpU6eyadMmOnbs6DQuPz8fvV5Ply5dnPYrax/5CyZHidUxoni/r5M9btjGCpvTFAAhxGbgN27GzZVS2leO43C2Ao8C10gpTwoh+gEFQoieUsofFX+IOhDBcHwsMjJSbt++3aVfreHhX4QQHJOSadvMpH7cx6YMx+Dr05UlJSVcf/31ivcATSYTer2ezMxMr+/7NZWoqCjy8/OdPktiYiIjR450a6kWFxezfPlylyXwlClT0Nx8C5+JNvx85lcuu7Q1C++9k+ERdZcrFUK43VOMjY3dUSuOt1F07dlBTlqjzLZ5off6Jj1PCNEKOAz0k1K6XZoIIUqAp6SU2y/o3wfE2CJTugIlUsp6a7w2T5+3isdUbRsLQIdtY3mLqdz1xo8sGhnPz9vch4J4k5iYGEaNGlWnx/VCglUBAo4lfW0PcFpaGgsXut8VGj58OMOGDXPpv/GBcWw6Az9ZziIl/Gz5laR1/2Dp1lKfyV4ffj4xMgz4b20FKIToLIRoaXv9W+AG4Fs3Yz32SahKUAWAmwZ0dPy8aUBH2lSMIXXrZGIHXOGX548aNYrp06c3qAgtFgvx8fFBqQDBupydPXu2k3MnLCyMzMzMOj9bUlKSi6MkZ5s9eFo4fkpg+ZbGB443FT8WWnoAV4fIH4DdNh/Eu8AjUspKACHESiGE3fL02CcRemdcVHzCfvkK6UcMpHcLzFfCvg8WHx9fZzByXUvHYMPu5bbv+4FVOcbFxfHYY4+5TQARFxdHVFQU8fHxjB8/HolEXBBzJxBIJFVVVbTyc+EvKeFcjX9sJillgpu+9VhDZtzdP6XWa499EqoleJFT89/H4WfrH91AKUA7Wq2WuXPnus3AbDKZuOuuu1wspmBFo9GwcOFCp2WxwWDgrrvucgmWBqu1uGXLFrp168aIESPqnFeA3xUg2JfDao0RlWZIn7XjWHCz67G1QKHT6cjLy3NRFFlZWaxfv97jBAqBZPbs2cybN8/xPiwsjPXr1zv11Uaj0RATE0OvXr24pFULXAuXSFq3Clz6en+cGAkEqhK8yNn83ABuOJBqe3ccqAqkOIBVEY4aNcoRSF1aWuoIpg4l7PLWjgfU6/V06OD+JJfJZGLYsGGEhYVRNGUiVrtP1mqCgsnj3Y71NfYQmeaYSkvdE7zI6QyMsX0LhOhC584ZbEheTuScrwnk12Pnzp08/vjjtGnTBiDo9wHrIicnh9TUVH7++WeHUszIyCAqKsopfrBXr15kZWWxc+dOx9iKuSm8UFLCZwcOcXt4GHPuuCMgn8GKCMmlrhKa56dSaTQvffskd7d42xYa47/TI+6YN28eBw4cYMqUKQ3fHMRMmTLFJUQmKSmJhQsXOgpG5eXlOUp41mZWTAzvPzgxwArQSnOtMaIqQRUrVesAGHPper596jv63b2D7Qt+53CaBAKtVsudd97pt/PAviIiIsJFwY0ZM4bjx48TGxtLeXl5o7Pc+Aurd7ilohZqqEpQBYCe7w0AetDzvQHc/t4AWr2ymUk3fEbPjQMDJpPZbObhhx8O2PO9ybx585xqjURHRzNkyBDuvfdePvroowBKpozmnF5f3RNUAWDvmI70XPsJe8d0r9VbRSC/IgUFBcyfPz9gz/cmGo2GTz/9lOHDh1NcXMxzzz1HXJw1wUlJSUlghVNIKC51laBagioAHF57xwUKEH78aATU7A2QRPCf//yHyMgmHXkNKjZv3ozBYOCFF15wKECA3Nxcli5dGkDJGqY5e4dVJagCQHj2A7XenQXgyr8M5IsXxgZGIGDDhg3NSgkuWrSILVu2sH6988EHrVZLenp60Bdlb67B0upyWAWAc5/a995+QYh2SHmMcxujEJevQD7tf3lyc3MZP368SwqqUCY7OxvAbYoss9lMTEwMOp0uKK1CKQVVIajglKAqQRXAuhy+euDdHN66AWKeZvvCnhjLz9I55bWAyFNTU8NNN90UkGf7ioiICLZt21bn9dzcXHQ6HTExMU7L5WAhFJe6Smieql3FY8KzH2DS1VsI//NQ0pbPov9Xr/DckG2snXd/QOQpLS3lqquuCsizfUV4eDiHDx+u93pubi4JCQn+E0ohzXlPULUEVQB4a2My6/ZOZdlNbXmsfQvGvKHnRgL3BbnkkktojgW4fvyx/kTIcXFxQWkFgmoJqjRzxrRrwdrb2/FYe+tXoidKFeDZelrjeeWVV0I+SPpCIiIiWLOm4eDz3NxchBBB5ShR4wRVVOrg6Nrf13mt69gdfpSkeZGZmUlcXBxGozFoao001zhBVQmqWLEdm3Oi1ZgGh3X7x1zri4/+AUdfg/jz4R8ycNE1IU9ycjIlJSUkJCQERfIIKaHKT0lV/Y2qBFUAGLtjpOP18R/OcGz9I+x9tWElKN/QQ82/Ofzul4T9aThfDZjHTY9uAro2SZ5x48ZRUVHRrJbESmuo2CkoKKCkpASj0RgUZ4tDcamrhOap2lU8Zu3t7Rztk+Gd6LLCbSZzN1SR/+AdhP85kqHFr3HbjEj++/IImpqBpn379k0aH4wcOnSIadOmeTQmJiYmKLzF/toTFEK8I4Qw2tpBIYTR1v/nWv1GIUSNEMLlL4MQIl0IcbjWfXc39EzVElQBzlebs1PCPYrG/bwtntHfPU/agWk8E3YJj5e/yG29n+DzU78jck7jM1a3bduW48ePNytLEODs2cY5jJKTkwMeRC39YAlKKf9kfy2EWAL8YOv/O/B3W/9twPtSyro8R5lSStcaDXWgKkEVANoNPn887crqU4z5Qln2ltgBX7L2p9WMaWddVLx0S3sof5H+w55Azmm8PDfeeCPff/994ycIQvbs2UOvXr08HldQUIBOpyMuLs5tzkF/4U/HiBBCAGOBIW4uX1iYvUmoy2EVAM6cedDRDp97gq0DrlM07uPqvzPa/BfOp+X/hZduaY88sqpJ8gwYMKDOWhyhyuuvv86gQYM8HhceHo7ZbCY3NzdgSlBKvwdLDwK+l1J+7eban6hfCSYJIXYLIV4TQrivZVALVQmqALB9YU+ndjQmXdG4T1JHkHjdVn7ea1V6Rz5/1ivypKSk0LFjR7eV2UKVAwcONMnBsXTpUg4ePOg9gTxCUF3TQlEDOgkhttdqU51mEmKzEGKPm3ZfrdvcWntCiNuB01LKPXUI+jLQA9ABR4ElDX0ydTmsAsDAFhuc3r+0WtmybdiSo8RkLWLxuq9J7wlLU7PJ+PTFJslSUlLCtGnTOHLkCP/5z39CqsJcfdx9d4N79PWi1WopKCgImLfYgz3BE1LKOtP/SCmH1TdYCNEK0AP93Fx2V5i99tyOPRQhRA7wQUPCqkpQBYAzqY1LWRWTtYi/3/81f+4+D6bCoq03kdFIGdLT0yksLKSwsJCwsDAsFguDBw92W6w81LBYLMyZ04RNUhv2BAv2c8b+wn522E8MA/4rpXRaBgghWgBjgD/UNVAI0VVKedT29n6gLovRgbocVmkS/dc8w9Pdt1BCDJOu3sItC15u1DyTJ0/GZDJRWlrqsPw0Gg3x8fHeFDdgfPrpp147+VFQUEBBQYFflSDSui+opHmBuqy9PwAmKeW3tTuFECuFEPa/4hlCiC+FELuBO4CUhh7WoCUohHgNuBc4JqW81dbXEXgHCAcOAmOllKdsHp1lwN3AaSBBSrnT3bwqwcYFqfRr/g0t+jc4avWDRgZmhjEGsABr+7fz+MlGo5EePXqQkpKCRqNxutYcrECAZcuWee2z2JfFcXFxfo0h9Jd3WEqZUEd/CTDATf+UWq8nevo8JZZgLjDigr7ZwMdSyhuAj23vAUYCN9jaVKyblCohgHOJzR9Z/2dlcYIHej3HWzzkaDf+27OzciUlJcTHxzNnzhwXBQjWpAOlpaUezRlslJaWUlVV5dWECP4OopaeOUZCigYlllL+C6i8oPs+4A3b6zeAuFr9edLKF4BWCNG081MqfmFjzxx6pi3jLhHJlTdex31rjikaV9hvLe/Z2oqb3uapvK2Kn9m3b1+uv/56du/eXe9977//PsXFxYrnDSZKS0tZtGgRH374IVu3bmX06NFem3vp0qVotVq/FWry43LYrzRWbV9l33y0/exi678aqH1MwGTrUwlyev29HzfkdOHXDzfxy+9X0MKUrmjcmFbHHe2x9idZtvxog2PMZjOPP/44mzdvVuT5nTJlCs8884zHZ28DjcViYdGiRaSnpwPWfc8OHTo43nsDvzpHpFDUQg1ve4fd/Qu4/dtgix2aCnDNNdd4WQwVTxl06g1equjPmHYt2D1sNJPbbub1Mw2P276wp3NHTP3hMQcPHmTmzJlotVrF9UMiIiKIj48nMzPTKx5Wf7Fu3ToiIiIc4SwajYbs7GzGjvVeeh1/JWC1Wnmhp+CU0Fgl+L3dFW1b7trXTiagdt3GMOCIuwmklCuAFQCRkZEhaEQ3L47Nvt3xulcLeP2Msu3c22afXzZXAjnl7ajLIffOO+/wzTffsG6dNW1XVFQUmZmZREdHN/icpKQkjEYjUVFRlJWVKZItkFgsFnr06OHi3dZoNBQVFdGrVy/y8vKCIjuMUtQsMs4UApNsrycB79fqjxdWBgA/1IrZUWmGtKla52hdq9aR+PYVdd77t7/9jUceecTxPj8/n5SUFCoqKhQ9S6fTkZSUFBLL4hkzZtSr3BcvXkxqaipms9mPUjWN5ronqCREZg0Qg/UojAlIAxYCa4UQk4HvsAYwAmzAGh6zH2uIzIM+kFnFZxwHOuDJAiGjXabT+85P5dZ7f+0lcFhYGJmZmUyYMEGxdRcfH09qaioZGY0NyfY9BoOhwXuGDx9ORUUFiYmJ5OTkBE326LqQCGpC0POrBCXe4XFSyq5SytZSyjAp5Sop5Ukp5VAp5Q22n5W2e6WUcpqUsoeU8jYp5XbffwQVb7F9Yc8LQmUUjNlSzPYt623tfT55oe5YuIEDB7qEu0RHRzN79myPrLtTp04pUjSBwGAwUF5eTlZWVoP3JiUl0b59+4CnyFKKVNhCjeap2lUaRf+nj7Ox52q6LDzMz9vGo0QZPn98Ku+t/4p1A7qxbvmntNowvs57DQYD3377LbGxsU5KT6/XM2PGDMWKLScnh8mTJ5OYmBg0S2OLxYLBYGDy5Mnk5OS4jXl0x8qVK5kyZQpFRUU+lrCJyObrHVaVoIoVW42RMZeu59unvqPf3TvYvuB38HP9adsWTF3DdxnWlG973tCzYGr990+cOJF+/foxffp0p/6srCw2b96sOB5Qo9GQlZXFjBkzAp5pprKykhkzZlBeXq5Y+YFVcRYXFzNv3jzmzp0bVNXl3NJMTUFVCaoAkNFuouPn8nYT6fLjz/Sf24YXYhLrHZd39Hw1kZ629w2Rnp7OqVOnnPo0Gg0Gg4FnnnlGsTLQaDQMGjQIvV4fMAViNBoZMWIEgwYNIicnR/E4u+Lcvn0706ZNY8SIEaSmpvpQ0qbTXC1BNYuMCgBvvPk1jL2DN978xNF3C5AHzKpvYEytX9wj6bSaqGxJu2rVKvLz89Hr9Y6+sLAwVqxYwdSpUz1ylAwYMIAJEyYQFxfn1zhCi8XC1KlTWbFihcehLiNGjCApKckRQmPPHL1r1y769OnjC3GbhARqakJPwSlBVYIXOzUfQ4sb2TumO8j9Hg8/98kLAIz54ifSuZRzecq+UlqtlhYtWtC3b19H6iywKoOysjISExPJyspStLyMiIhwKM3U1FQqKiqYOXOmovjDxhAXF0fnzp2ZOXOmxzGLeXl5GAwGl3EWi4UjR47QoUODiZADgwRC0MpTgqoEL3Je7rOdyPtT6Z/eyEJmlfucAAAgAElEQVTp28ZSBbwFcAiqDkGr29cqGhoXF0fLli2Ji4tj+3bXQIJVq1aRlJTkkTgZGRlUVFTw/PPP88033zBkyBCvJGWtrKzkgw8+wGAwKA7wvpAFCxZw4MABNm3a5HJt1apVjB49mvDw8CbL6itCMQZQCeqe4EVOp9KZLBq5xfbuOOdrhSij3eBIR7t2YA/apXj2lYqNjeXee+918fJmZWVRXl5Ofn6+R/PZnQ1nzpzh22+/ZcSIEUyePJm8vDyP5rFjMplITExkxIgR/Pjjj6xevbpRCrCyshKz2UxWVpbLcUGLxcKWLVt4+GFlxa0CRjN1jAgZBOo9MjJSurMEhBAEg3wXC0IIOnfOYEPyciLnfE1jFgpCjEVKZZZgbcaMGUNsbKzLMbOKigratm2ryJozmUysXLmyzgQFZrMZo9HInj17kFKyb98+wKqg7IrJYrGg0+m47bbbCA8P5/nnn2fVqsYXjSotLSUlJcWt9VhRUcEDDzzAI488wtSpU+uYQTlCCLehNrGxsTvqS3evhDa/DZPdnldWM/nghDlNfp4/UZfDKk689O2T3G34A99ui6fd7RlYj38r57GvGmdxzZ07l/j4eHr06OGkLCIiIoiKimLTpk31JlwoLS1l+vTp7NxZdw5frVZLTEyMRxXblixZQl5eXqMyXOfn57Nw4UJWr17tUj+5tLSUgQMHUlhYSGxsrMdzB4Rmao+oy2EVK42ME7yQl266tFGP1+l0ZGVlMXDgQJe4v/j4eGbNmlVnYHR+fj6PPvoozz33XKOeXR9arZbFixd7nNjVYrGwceNG8vPz3RaQf/jhh9m1a1dIKUBZIxS1UENVgipA4+MEvUlMTAyFhYWMGjXKqT8pKYkOHTqQmZnpMsZgMPDSSy+Rl5fns7RSdSnnurBYLMyYMYOsrCyXZbzFYmHBggV88MEHIZVBxopQ2EILVQmqAJB65gy3rP2O1DNnSD1zhk/PHUbK/cza/rNf5YiNjWXnzp0sWLDAqT8jI4P4+HiioqIA6/5fbGwsSUlJfPzxxz5VKDExMUgpWbduHVOmTKn33qioKD799FO3R+f69u3LK6+8wpw5c4LaC1wnfnCMCCF0QogvhBBGW83iKFu/EEJkCSH22wqr961jfD9boaX9tvsb1MqqElSxUvMxe6NXUbVtLFXbxsKRdGsMIb8ERJxdu3a5nCUOCwsjPj4eo9HIqFGjvJqcVAkpKSm0b9++zuvFxcWsWLHCbUGl0tJS5s2bR0pKg8XPghf/eIczgHlSSh3wnO09KK9f9LLtuv3eC+sjuaAqQRUAVg7SM+nq/+OmAR1pNziSSVf/HysH6TlS6lmcnrdYtGgRr7zyiste3BVXXOHIMj1xoseFxZrMs88+6zbcxmAwsHz5crcWaV5eHo8++mjo7P+5wx4sraQ1/Un2pJTtOZ+UucH6Rbb3V0gpP5fWsJI8ztc/qpOg9Q7brVj7TzVUxrfcV3qMKbRx6jvOMrqIS5Hydb/LEx4ezp49e9iyZQupqanceuutvPvuu7Rp06bBwky+RKvV0qtXL4QQ7Nu3jy+++AKTycScOXNcArunTJmClJIlS5Y0i/rJHvwKdhJC1I55W2HLJK+EZOBDIcRirEba7239ddUvqn1a/WqcUx8pqnEUtEoQzis+Bct6lSZyrlgPQxKgVQ9rR9U3nPtnLhDYur+DBw/m119/5ciRI2RmZtKjR4+AygNWT3ZhYSEPPPAArVq1cnsCxGQyERYW5tWiSgFHuef3RH1xgkKIzcBv3FyaCwwFUqSU64UQY4FVwDCU1S9SXOOoNkGjBN0putp9tV+rVqH3+dM9vYhtmcb19x8GYP97Pdl4thcxa5IDLBnceeedgRbBhdjYWPbt28exY8dc4heVxCyGIsJLv3ZSymF1PkOIPOBx29t1wErbayX1i0w4B7bWWeOoNkGjBEFVboFk3In5rNv2JMd+sMbi9UzuwODulzKtW1B9RYKKp556iqioKCwWi8MTnJ+fT3p6uqLM0iGF/47EHQEGAyXAEOBrW38hkCSEeBu4HTf1i2yF336y1TfaBsQD2Q09MKi+4UqXvaqy9D6PtW/BY8M7BVqMkKOsrIy9e/fy8ssvU1lZyfLly53SgzUfvOL0UEIisEwI0Qo4g60sL/XULxJCGG3eZIBHgVxAA2y0tXoJKiUY9CnGVVTc0LNnz6CteeJV/GB7SCm3Av3c9EvA7eHlWgoQW12jWz15ZlApQZUAYjs250SrMa59KhcvNYEWwDeoStBLHDx4kF27drF//34mTZpEly5dAi2SR4zdMdLx+vgPZzi2/hH2vqoqQRUbzTipqhos7QXsJxgOHz5Mjx49uOeee9yecw1m1t7eztE+Gd6JLivWB1oklSBDSGUt1FAtQS/Qp08ftm7d6kgBFRUVRffu3bn++utD5pRA1TbnI2gl3BMgSVSClhBUcEpQlWATWbx4MYcOHXLKFhIWFkb//v0ZNWpUyHiy2w0+H9t6ZfUpxnwR5FmOVVS8hKoEG8HBgweZOXMm1113HfPmzXPKFmJPo2TPJDx06FDWr1+PVqsNoMRWevfuTVRUFEajkT/96U889dRTjmtnzjzodG830aVRRSWy/rGVzeVfc22XjiyacA+XXqp+xZoLobjUVYL6DW0E9957L4888ojbIkAzZsygd+/ejqXx/fffz+TJk1m/PnB7bGazmbS0NP7xj38QFhbmSPh58OBBR0qn7Qt7Oo05GpPu0TMqf/6ZoXNzqLF5EP931Mzt5dksSLiLe/rd4oVPoRJQJJ4cmwspVMeIhxQVFfHqq6+6VYAVFRWMHDnS6Zo9IWigzpAePHiQxMREPv/8c8eSXaPRoNfrmTlzJmazGYCBLTY4tZdWP+3Rc/R/e5OaGtfUmnPf+NB7H0YlsDTTQksXjSX4p6LVbP/hO2QLScvqlky/aSAz+g/0aI4VK1bwyiuvuD0Taq8Z4W4PMDs72++57+zYrdZu3bq5XOvTpw9paWksW7aMH1Kdz7u3cbm7fk79eMbl9LrAuqL+9zeH6N+ju7thKiFEc10OXxSW4KB3XuLfP/8PWktES6huXc3S/Vsw7NiqaLzZbGbmzJlMnDjRRQFaLBYSExO5+eab63SCaDQaioqK6NWrF0ajscmfRwkGg4G+ffuyZ88ekpKS0Ov1pKamOt0zZ84c0tLS6Nu3L23AqXmTyp/c1wZRCTGaqSXYoBIUQrwmhDgmhNhTqy9dCHHYlgLbKIS4u9a1p22prfcJIe7yleBKOXH6Zw7XmBG1PqmwrdeW7W1YCRqNRgYOHMiiRYtc0qVXVlY6aknUVwnNzuLFi5kwYYJjCeoLzGYz6enpGI1GCgsLna6dOnXK5XhXx44dKSwspKSkpEnPvaR1izq//0Nv/W2T5lYJEi5WJYj1MLK7FNWZUkqdrW0AEELcAjwA9LSNWS6EaOktYRtDQcV/3PYLAdWtqusdW1RURHx8PC+++KLLNZPJxIgRIxg0aJCLcqyL4cOH88gjj5CYmOgzRZiYmIjJZCI7O9ulyM8LL7xAXl6eS7bmsLAwZsyY0SQrNTPRWhzJ/jtg/324Z8DNtGp10ey6NFuUBkqH4pK5wW+nlPJfQohwhfPdB7wtpTwLHBBC7AeigM8bLWETieoaBv91f03U4+0aNWoUy5cvd5vFOCoqivz8fMrKyjyWJykpicmTJzN9+nRWrrSmSjMajZjNZioqKmjT5vxi9OzZsxw5ckRRrdwtW7Ywffr0erMud+zYkbKyMkpLS4mKinKSf/fu3RgMBrKzsxtVbHzgzdexfu5Ekl59j2OnfkHTpjVzxt6heoabE6p32IUkW9Wn14QQHWx9daXADhi9rupGq3OtXELeZA3crr3W5X6z2cyYMWN455136iyXmJ+f73LNU8aMGUNcXBxCCJ555hk2bNhAp06duPzyyx2tU6dOdOrUiQ0bNiCE4NFHH3V7HO/NN98kJSXFbe0Ld0RHRzN79myXOr6TJ09GCNFoT/b1v+nEprREdi5NpvSFaaoCbGZctJZgHbwMPI91xfM8sAR4CA/SWwshpmLLFXbNNdc0Ugxl/HPUwwwtfJVzrasc0nRv0YG37v2z031Go5Enn3yS+++/32WJaw+C7tChQ6MVYGlpKVu2bGHu3LlMmTKFjIwM1qxZo2g5PW/ePA4dOsQXX3yBEIL58+dzyy23EBcXx7p16ygsLPRILr1eT2JiIjk5OY4+jUZDdnY2gwYNal5p4VW8QwgqOCU0SglKKb+3vxZC5AAf2N4qSYFtn2MFsAIgMjJSfvfdd40RRRFh7bXsmziL3d8fwXjsCHf3uIlObdu53Dd79mxmzZrltmTi4MGDiY+Pdxsf2BD24OSNGzcyZswYTp48qciRUhuNRkNERAQRERHce++9bN++nezsbBYtWkRRUZHH89kxGAxOn0mj0VBQUEBBQYHPipmrhCAhauUpoVHL4QtK3d0P2D3HhcADQog2QojrsNb99HzjzEf0uqob8bdFulWAAE888YSLAszPz3fsn3mqAEtLS0lNTeXkyZPo9XpycnIYPnx4oxWWnY4dOzJ8+HCKioooLS3lxIkTpKameqy0cnJyiIuLcxQ0txMWFkZNTQ1Dhw71qSdbJcRopt7hBi1BIcQaIAZrGT0TkAbECCF0WD/yQeBhACnlXiHEWuA/QBUwTUpZvws2iKioqHAoQYvFwqpVq9i8eTP5+fkezWOxWEhLS6OiooKCggJfiOpEREQEGRkZGI1GFixYQEpKimKPdVhYGCtWrHBUR7Oj1+s5cuRIwI/8qQQPopkmVW3QEpRSjpNSdpVStpZShkkpV0kpJ0opb5NS9pJSjqpd8ERKOV9K2UNKeaOUssH8/sHE9OnTMRgMjvi/8vJy1qxZ49Fem9FoZPDgwdx6662sWbPGh9K6Yi/8PXjwYCoqKjwal5SU5NZR0qFDhzpGqah4HyGETgjxhS3+eLsQIsrW/2ebI3a3EOIzIUTvOsbnCiEO1Iph1rm7z2lMMKR6ioyMlDt27AiKtFPp6emYTCZH+IonGAwG4uLimuw59gYmkwm9Xu9RGE9iYiK9e/d2Wfb37duXzMxMBg8e7G0xVbyIEMJtnZ7Y2Ngd9dUBVsKlV3eX1z78hKJ7K9KeaPTzhBDFWGOQN9oOYaRKKWOEEL8HvpJSnhJCjATSpZS3uxmfC3wgpXxX6TMvimNznpCent4oZWwwGCgvLw8KBQjWZe6mTZs8KgCUlZXldvn/2muvMX36dL8d+VMJQvwXLC2BK2yv22NzrEopP5NSnrL1f4FzfeEmEVRKUAihqPmaJUuWKI65g/MKMNhqzXbs2JHy8nLFilCj0WAwGFi4cKFTv06nY/Hixaxb56YYk8rFg3LHSCfbUtbeprqf0C3JwCIhxCFgMeAundFk6i+lOd+2bM4UQjR4FD5olKCU0qnV7rvwuq/RarUsXrzY5XhZXdgVoFJnhD/JysoiLy+P4uJiRffXdpTUZtCgQSxYsED1Fl/MKFeCJ6SUkbXaitrTCCE2CyH2uGn3Ya0bnCKl7A6kAKsuGHsHViU4qw4pnwZuAvoDHeu5z0HQKEF3+Mvyc8fu3buprKykb9++VFZWur3HZDIRFRVFTk5OUCpAsFp3ZWVldOnSpc7PcSE6nY6CggISExMdY3bu3MmMGTOCIkN2c+TwyQI++08cpXvvYd9h17PqgUZg9Q4raQ0hpRwmpbzVTXsfmATY92PWYT12a5VBiF7ASuA+KeXJOuY+Kq2cBV6vPb4uglYJurMG/U1sbCzjx493SUEF1jCYefPmMXv27ABI5jk6nY5Zsxr8o+ggKSmJQYMGMWLECBYsWMDAgQNJSEjwnYAXMdv2TUJ75mn6tP8v/Tt8TZjM4fO9w6iuqgq0aOfx357gEcDugRsCfA0ghLgGq3KcKKWsM/TBHsMsrNZTHOdjmOskaJVgsPDUU09x2WWXufRv3LiRDh06oNfrAyBV4/Ek5jE+Pp4tW7bw9ttvU1hYSJ8+fXwo2cXJqZ93cFu7MjQtq2nTsoZWLUDTqprb2h/hq8PPB1o8Z/wTLJ0ILBFClAMLsB2tBZ4DrsSamcoohNhuHyCE2CCEsGcN/rsQ4kvgS6AT8NeGHqgqQQUsW7aMW2+91bFHaLcMMzIyAimWx+Tk5HDkyBFFjhKLxcLMmTOJj49n9+7dIVM6NNT4+shLVLnJznJpyyp++llZ0l+/4QclKKXcKqXsJ6XsLaW8XUq5w9Y/RUrZoVb6vshaY+6WUtq9yENsMcy3SiknSCl/buiZqhJUyOrVqxk4cCAVFRWUlJQwcuTIQIvUKCZPnkxeXl6D+4PTp0/nsssuc0qwoOJ9BC3cph2REqTbfCSBo7lmkVGVoEJ0Oh2FhYU88MADzJ49O2gdIQ2h0WiYPXs2b731Vp33VFRUEBUVRXp6uuoI8TE3XJ1CSzea42xNSzpcPiQAEtXDxXp2WOU8sbGxGI3GkLUC7YwcOZK2bdu6TQhRX8EoFe+jvawn24/EcHPbEqSElkIiEZT/EE50zzmBFu88svmeHVaVoIe88847PPvss4EWo0loNBr27dvn1LdgwQJ27drFokWLAqMAq7wQiN1qTNPnCACRN7zM8R+28s1RAzXyHN06jiK656RAi+VKM/27qCpBDygoKGDAgAGBFsMrREREODLHVFZW8v3335OTkxOw5e/im5pekvSp/aH7W9q5/UA6tz9fAjb/q70Yyr7g2C+/cHPnzswe+Af6dQ1okvaQ3O9TgqoEPcBoNHL33Xc3fGOI8M9//pMhQ4YwatQot7WU/cnMb5o+x1NNnyIoeG3XDpZ8vhWLLU5wx9EjxL/3Lm/px9L7N10bGO1DVCWo8tlnnzFlypRAi+E1NmzYwKRJk1xKcwaCNi/8u85rZ2f1V3Rfc+BcdTXLtn3mUIB2LFVVLP58K2/eH6Alf4g6PZSgKkGFFBQUoNPpgiZLjDfo1q0bn3zySYOV7PzBmdS6My+JWcruaw6cOH2aczXuPRBfnTjuZ2nOI2i+y2E1REYhlZWVzWY/0I5Op2PPngZPFan4kY4aTZ3RgddcEdhwJTVO8CKntLSUq666KtBieJXf/OY3nDp1quEbVfxGm1atmNirD5oLCtZf2qoVyQN+HyCpbDTTOEFVCSpk27Zt3HzzzYEWw6uEh4fz/fffN3yjil+Z+fuBTO4TyWWtW9NSCK667DIyho3gD9eGB1awZqoE1T1Bhezdu7fJVeKCjU6dOvHSSy95lH1axfe0bNGCJ34XzeO3/w5LVRWXtW4dsJRyDkJ0qauEoFCCJ0+6TQ2m4mOam1JvbrRs0YJ2l1wSaDHO00yVYFAshw8dOqQ4i7OKikpg8FZS1WAjKCxBnU7HtddeS2lpKdHR0YEW56LBZDJx5513BloMG0rDP+q7r7M3BFGpA3U57GPCwsLQ6/XMnj07KBOV9uzZ06VAeahz+vRpIiIiAi0GANsX9mzyfZGzj3lLHJULCVGnhxKCRgmCNeuxXq/nyJEjbjOcBJJBgwZx+vTpQIvhVU6fPu1ScD1Q9H9amSVY330yNCodhC6qEvQ9YWFhlJWVYbFYgs5j2adPH7744ougsZy8wdatW7ntttv8/lwpJWv27WbZrlKOW37huis68tCufXTv8lu/y6KijOZ8YiSolKAdjUZDeXl5oMVwokuXLmzdGmTpzpvIjh07mDTJ/ymbXt+7g4wdn2KpOgfA/h9OYjJ+wMo79Qy6Otzv8qgoQ9T4XgsKIXTAK8ClQBXwmJSyTAgRA7wPHLDdmi+l/Iub8dcBb2Mtt7kTa2GmX+t7ZlB4h91hL2S+YMGCoFiyfffddyxZsiTQYniV3Nxcv58brq6pYemuUocCtHOmuoqM7f/yqywqHqA0ULrpejIDmCel1GEtrlS7kM+ntWqMuChAGy8AmVLKG4BTWGsU10vQKkF7+voDBw4wY8aMgMpiNpvZvXs3d999NxUVdVb7Czkefvhhvz/z53O/cvoCBWjn2x8qARP8sLzhiX5YDngh/1aQ8dm2/dw/Nouhd73APfe9yPr3dwRaJAd+OjssgStsr9tjLcGpTD5rRPkQ4F1b1xtYy27WS9AqQTs5OTnk5OSQmJjod4vQaDRy6623snr1alauXMmrr77qtgZxqBKImsntWl+CplVrt9c0/3cAIbojtNManEdopyHE9Wxf0B1qdntbzICwsfhLnnnmXcynTiNrJKdP/8pLho/IzP4w0KJZ8Y8lmAwsEkIcAhYDT9e69jshRLkQYqMQwl2YwJWAWUppz0NmAhrMRNugEhRCdBdCfCKE+EoIsVcI8bitv6MQ4iMhxNe2nx1s/UIIkSWE2C+E2C2E6NvQM5TQu3dvZsyY4TdFWFRURHx8PC+++KLDU92cwmOMRiPh4eF+f27LFi1I6v07lwQBrap/Ze+btl/2mBcbnKfVzI+Be+g/18THqSOAX7wvrJ9ZumwTkvPF5+w/iwp3UV1dHSCpzuOBJdhJCLG9VpvqNI8Qm4UQe9y0+4BHgRQpZXcgBVhlG7YTuFZK2RvIBgrcieimr0G1rMQSrAKelFLeDAwApgkhbgFmAx/b1t4f294DjARusLWpwMsKntEgSUlJ9O7dm3HjxnljugZJS0sjLy+P4cOHO/XHx8f75fm+pr5qc75m6m39mRU5mCsvbQvANZdrOfryGs7s2UeriRmsLXq8wTm+yxjCmC9WAzBsyVGObM32qcz+4Nyv1XX+Fh/43wl/i+OKckvwhJQyslZb4TSNlMNsdYEvbO8Dk4B8263rgCjbmB/tNYSllBuA1kKIThdIeALQCiHsf2HDULCcbtA7LKU8Chy1vf5JCPEVVhPzPiDGdtsbQAkwy9afJ63Ver4QQmiFEF1t8zSJpKQkkpKS0Gq1lJSUoNPpmjqlE2azmcTERNq3b19nunm9Xo/BYAi6OEZPMBgM3Hjjjbz55ptMnDjR788XQvBgz3482LMfUkqEEIg/WfcnLXkz3X4p373rOkTno1x76xVEzj5GV2Dt7VqH0rh60NPICwIFLWd/ZerSdzCePIEUENHuClZMH0sn7eU+/Xy+4MorLwusAP6rNncEGIxVnwwBvgYQQvwG+F5KKYUQUVgNOKekA7ZrnwB/xOohnoTVo1wvHoXICCHCgT7ANuAqu2KTUh4VQnSx3XY1cKjWMPu6vMlK0M7SpUuJiYnxuiIcPXo0999/f4MKbvr06YwfPz4kExBUVlaSl5fHpk2bGDZsGJdffjlxcQ3uHfuMC7Oj1PWFfOnev1IyYwJwXHFQ9KDnlmMRNdDS+ox9v/zAkAUr2fb8NDRtgigxgY1rr+vE/w64WnyatpfQoX07RXPExsZ6WyzAr3GCicAymzV3ButqEqyK7VEhRBVgAR6wGVoIITYAU6SUR7AaYm8LIf4K7OL8crpOFDtGhBDtgPVAspTyx/puddPn8s8nhJhq3zM4ftyztOEJCQkORWg0Gt3e89bnu+g3cyl9nlzKvMKPGpyzoKCAWbNmKbLwsrOzeeWVVzySOVhYuHAhs2fPpmPHjrz22ms899xzdf4bBhMPs9Kj+1cVlVoVYG0lKwTVLSTpuRu9LJ13eNXwIJdd3sapr2WrFqx69SHFc0gpXZrXkFJZa9Ij5FYpZT8pZW8p5e1Syh22foOUsqetf4CU8rNaY+62KUCklN9KKaOklNdLKcdIKc829ExFlqAQojVWBfh3KaV9vf69fZkrhOgK2A9umoDutYa7XZfb9glWAERGRnr8L5eQkABYT3Jc+D96wNxsLD+eD8PI/+hL3vt4D8ZlKW7nevPNN8nMzFRccW3y5MkMHjyYP/7xjyF1gsRoNFJRUcG8efMAa+KKxYsXk5qaSnFxcYCls1JjWkeLsAuLCf3CqzNK6h3XamKG0/sPv/za/Y1CsO1/psYL6EMuuaQlRfkp7Nr9HSVbvqLXbd0ZGnNLoMVy0FxPjCjxDgusJuVXUsrabrtCrGtucF57FwLxNi/xAOAHb+wHuiMhIQEpJVqtltzcXMBqAVp+PIe44D9ZI/mT4e9O4z/66CNGjRrFb3/7W7KzsxWH4Wg0GsrKyli5cmXQHe+rjw0bNlBQUOCIwQQYPnw4xcXFpKenB04wgK5Wh9PQ7mM5vDYKa7aY48A3TOrWjhLglnmraTXRwORugvUTLmVWN5uVF/M0xtyZTtNddXkde2hS0uHSS330IbxDn17XkDL9LobG3ILZbCYhIQGdTocQAp1OR3p6Orm5uZSUlDiNsxsDQghH8xr+C5b2O6Ihc1kIMRD4FPgSsG+NzsG6L7gWuAb4Dhgjpay0KU0DMAI4DTwopdxe3zMiIyPl9u2utwghFJnzRqORmJgYli5dSvZeM1VnahAXrMqlLfigPPu8NThy5EiWLVvmsOYMBgPl5eXk5OQ0+EwAi8XC4MGDKSsrU3R/ICkuLmbQoEFOCrA2o0aNYvjw4QFz+Iz/7ChrohOAYroChX+zpsX68cRZhi75EbiVl/ZspYNWw/iwWkvGrtNI+3g+6Te3d5rvhPknBi+0/X+srQyk5I1JeiJvDvfhp2k6S5cuJTc3l/LyctLS0oiJiWn06R4hxA4pZZPK9LXr2F32ujNZ0b2fr32qyc/zJw1agrY1upBS9qp1ZGWDlPKklHKolPIG289K2/1SSjlNStlDSnlbQwrQG+h0OkpKSkhOTqaOaoVuCQsLc1rO2hWAUutOo9GQn5+PyRScyys7paWlPPPMM3UqQIDly5fz2muvUVRU5EfJzpP3+64MLX4Nuk7jKF3p//Rx+j993KYA7+GWl9/isZ7tGXf1JdYYwR6LYPgq0spedFGAAJ20lzN36CDrEq7WftWDul5BqwDNZjO5ublO3+dTp06Rnp4eFGVRm2tS1QYtQX/QVEvQjtFo5PFVb2Omi1tLsNNVl/HxM+ePivXt25fNmzc7eUu+DnwAABN0SURBVHktFgvjxo2joMBdLKZ7oqKiyM/PD8pgapPJhF6vZ8WKFQ160isqKvjjH/9IXl6e18OPlFAF/NX0K8tX7+L4069bO7t2ZMx7qbx0u9aRMvUosLUKOreAmAb+jFdXV1O49Ussv57jj4P7cMklQZkzhOTkZHJzcwkPDyc5Odmx5+0NvGIJduguew9tOH4T4LP1M0PKEmxWShCsf00HPbeKFtJ1P2Tbose4tNZ+kNlsZvTo0UybNs0lkauniq20tJSUlJSgWhpXVFRw/Phxj7N1GwwGJkyYgFYb2Dq3zRmz2Ux6ejrLli1j0qRJjj1tX+AtJagbokwJluaHlhIM+rPDnqLVavn0L5OpOmcvJSm48qrLXBSg/d4lS5aQnp7uUuPkr3/9K3q9XvExvejoaDIzM4OmVkppaSk33nhjo8oV9OnTh7S0NB9IpWInPDwco9HIgQMHfKoAvUozdYw0OyUIVuVWuvBpxKd5bHn+Qf75zMMuCtCOTqfjL3/5C9OnT3fqHz58OPHx8R6dV46OjiYlJYW8vLwmf4bGYk9Im5KSwqFDhxoeUIvi4mKioqJ4//33ycrKYvHixT6S8uLl4MGDxMTEOLy7gTi/3RjswdJ+yCLjd5rdcvhCYmJiMJvNlJSUNLi8mzJlCtnZ2U4OBIvFwowZMxR7jO3k5+czevRoTp8+Xa9DwltYLBbWrVtHu3btPK7RYv+MWVlZTrIuWLCAbt26eXV/6mLFbDYTHh5OQUGB350c3lgOX64Nk30GK1sOf1qYqi6Hgwn70Tq7MqwPIQSrVjmfstFoNKSlpXm8zNXr9Rw6dIhx48b5fIlcXFzM4MGD2bNnj8cK0GQyMW7cOHJyclyUdVlZWchYKsGM0WhEp9M5rMCQRV0Ohy72sIOGvoCLFi1iy5Yt5OfnO/WHhYWRkpLicShMWFgY6enpLFq0iPvuu8/racAsFgv5+fls3ryZ1atXk5GR0fCgWhiNRvR6vdvMOEajEa1WG9q/tEGA3fJLSEgIeUdTc10OXxRKEM4rwvrOyWq1WubOnev29ERmZqZHjhI7Op2OjIwM9u/fT9u2bTEYDE0+q1taWsqCBQto27Yt//3vf8nIyGjU8b2pU6c6PteFPPTQQzz44INNkvNiJzc3l/vvv5+lS5cG/kROU5FAjVTWQozgDJryEbm5uY7A07oy0Oh0Onbv3u0SQxgdHU1ZWRmpqakeWVz2zNR79+516j948CDvvfceFRUVjmQMM2fOdBlfVVVFZmYmDz/8MJ06dWL+/PlIKYmOjmbOnDmefHzAaj2mpaVx6tQpl3Aei8XCqlWreO+99xSfo1Zxj/2PbjDsuXuNZvRRatPsHSPuyM3NJTk5ud49wvT0dEwmk1tHybp16xpMrmpXNo899piifTWz2VynhajT6RxLqaKiIqKjoxuVxstkMjFv3jx69+7N5MmTXT7X9OnTOXXqFKtWrQr5pVsgUfL98idecYy0D5P9fq+s1s+WTbNCyjFyUVmCduzeTvuGtTvS09N58sknyczMdLK4NBoNBoOBHj161BmDV1lZSWpqKpdddplix4LS/bfY2Fi3Xmwl6PV6Zs+e7Xb5O3bsWPr168fKlZ6lrFJxxq4AL0xu4Akz1xWxdfdBeoR1YPXDE7wnXBPxR8nNQHDR7AleSEJCAkajESFEncGqS5YsYfz48dx6661O/fZlZFRUFJWVlU7XhBCUlpaycuVKli1b5hPZFy9eTHx8vOJ4RIPBQFRUFGVlZS4KsLi4mF69elFUVBT6+1YB5uDBg4DVqm/MsUPTiVP0nv4ixf/6mtPmc3y55xi9p7/I+7uCoJBUM84ic9EqQbAqwvfee89xbtMd4eHhrF692qXUZnR0NElJScyaNcvRl5eXx65du3yW3deOVqtl0aJFZGRkNBh+s2DBAsrLy9m0aZPLNYPBwBNPPBHQ4O7mRFxcXJNiKu99PhfAKQUcwHOvbfaCdE3DGiwtFbVQ46JWgmD94tozdtSFTqfjgQcecAmRiY+P5/jx41gsFhYsWEBRUZHfEg/YlfPAgQPrvMdupWZlZbnsIVosFrZs2cLWrVsDkiyhuVHf90cpskY6FN/pq8/x061n+eXGX6lqXcOOg981ef4mU6OwhRgXvRKE86m46jvDOX78eNLT011CZPR6PdOnT+ebb77x+FRJU9HpdBQWFrqNXzSZTIwYMYI5c+a47B2aTCamT59OTk6O6gDxAvbvjieZh+qiimp+7G+hKvwcsn01NVdWY+l/lpd2f+4FSZuGPyxBIYROCPGFEMJoK78RZeufaesz2spzVgshXLyDQohcIcSBWvc2+Bf+onSMuMNuDWm1WuLi4lwU4lNPPYXZbCY+Pp758+fTvXt31q1bx6RJkwIaBhEbG0t6ejqnT58mIyMDo9HI1KlTWb16tUsITGlpKY8++ijz589XHSBeIjk5GaPR6DVPsKXnOWgtz+eBFdZUiCU/7aeqqopWrQL0K+u//b4MYJ6UcqMQ4m7b+xgp5SJgEYAQIhZrbeLKOuaYKaV8V+kDVUuwFvZg6rpCVbRaLevWrePxxx+nbdu2fP/993zyySd+ltKV5ORkDhw4gMFgID09ndWrV7sNnn744YfJy8vz+Z7lxURubq7XssAMi+6BbCcRF/xWCgG0gBVfBjJNm0TUKGtNfhBcYXvdHvd1g8cBa5r6IDuqJXgB4eHhlJSUkJCQUOeXe+PG4KpWptVqycnJYeDAgdx9990uCtAes7h161Z1+etlkpOTvXa+eskD9/He3/fWef2Xql+98pxG458VTzLwoRBiMVYj7fe1L4r/b+/sY+uqyzj++TIYRAZcYEPGS+zAIY6YvTDJCIYiEoXBXJcoGTNKJxNNhqFRDOCUtCpRTMRCIpAx4HYEHSpQGZnKiytEg5MN7raO8TJhBNhgG2yCqAzWxz/OOd3ddt+63nvPufc8n+Skp+el59tf229/v/P7Pc8jfYSgdEepOhDXS7oOeAy4plzFOTfBAmQyGbq7uwcXKff29ibePDKZDP39/Uhizpw5g8P7KVOmMGfOnCHHFTvlaWlpGVwWUy2OPuBQ3hr49z69QQy+Pbn4JFjNGVrx9dGS8qMfFobVJQGQ9ChwbIH7FgCfIxjq3ifpYoIib+flXTMD+FuJofC1wBvASIJqllcDPyol1k2wCJlMhr6+vsECN41QmxeCl/SLFy8eXPPX1dXlw98aUKtEqA9ceCmtD96CEQyLLTSeGceexiFxvQ+MqLwnuK1UxIiZnVfsnKTFQJSz63ewT8Hp2ZQYCudVtnxf0l3AVeXEugmWIJPJkMvlaG9vZ8eOHYnvDQK0trbS2to6GLHgWWBqQ2dnZ00Wl59weIbVF3+HeQ//nrU73mDUiIP42ZkX8tmWj1f9WUOmPhMjm4BWoA84FxgsIC3piPBc0TCavFroAtqA/nIPdBOsgPwKYI1ghODmV0uipTC1SjY7auQhLLkoOeFyERpKKcf95xvATZIOBP4HXJ53bhbwsJm9t4cuaRkwz8w2AfdIGkOwvjsHfKvcA90EKyTqEfb29iYmMN6Jh1mzZrF9+/a4ZdQXoy4Loc3sr8DpRc5lgWyB49Pz9s8d6jN9icwQyGaztLW1Ncz7Qac2zJw5s2FGBNVCVLZQ2sPmUkA2m22oiRKn+qS25kpeEfuSW4PhJrgfdHd3uxGmlFwuR1tbW9wy4sFN0ImIZoujVFxOeqhGooSGJHon2IQJFHxiZBhEw6JsNpveIVLKePzxx+OWEBt1mh2uO26CwyS/ipgbYXPT19fHxIkT45YRE4051K0EN8EqEA2NM5mML59pYrq7u2s6HN783jssevYpzIx5Ez7NcaOOqNmzhozRtCZY9p2gpBMlLZe0XtI6SVeGxzslvZ6Xt2t63j3XStog6XlJX6jlN5AUosXU3htsXnK5XM2K0f905V+YtuRWFq1ZxR1rn+bMe2/jx/+IP6P0HjTpO8FKJkY+BL5rZp8EpgHzJU0Iz/3SzCaF2zKA8Nxs4DSCbA+3SBpRA+2JI0rF5UbYnLzyyis1icRZ//YWblv9FJA/ySYWrV1F/1tvVP15+0tq1wma2WYzezrcfxdYDxxf4paZwBIze9/MXgY2AGdUQ2wj0NfX50bYhORyOY44ojbD05tXF68TU+pc3fElMiCpBZgMrAgPXSFpjaQ7JR0ZHjseeDXvttcobZpNRZR0IUrF5e8Im4NcLlezeOz/fvhB0XP/KXGurpjBroHKtgajYhOUNAq4D+gws3eAW4GTgUnAZuAX0aUFbt/n34Oky8MaAiu3bt06ZOFJJz8Vlxth47Nx48aaFaSafUrxGedLxidoNjrNPUFJBxEY4D1mdj+Amb1pZrvMbAC4nd1D3teAE/NuP4ECKbLNbKGZTTWzqWPGjBnO95BYMpkMLS0tboRNQFdXF11dXUiq+nZBy6nsfPU19i7gu/P1TVx00oQhfa2a0qQmWHaJTJiX6w5gvZndmHd8bF4Cw1nsztv1IPBrSTcCxwHjgTiLI8RKftql7u7u1AXeNxO1LKg1MDBAz3OruPu5ZwD4yqmTmXvq6Rxw3U0Vf43IBPPNsGqaDRh+/ZBEUsk6wbOArwJrJUXBst8HLgnL2RmwEfgmgJmtk/Rb4FmCmeX5Zrar2sIbjWw2S0tLC729vV7nt0GpZ4jkcmDeftwXaTSzKvcObXea6yajrAmG+b0KteSyEvdcD1w/DF37/FeLs6xltYhS9ff19bkRNhiN8PsnaQ+d0X5VjNBoyEmPSkh0AgUza4hfvkrJZrN0dnZ6BhqnMUnrO8F6Uey/2N77jU5HRwcdHR2DhXq8R+hUk4ceeqh2X7yJ/g7zSXRPsJlpb2/nnHPOqVnVMsepLhX2AodplJImSnpS0lpJSyUdnneubDiupHGSVkh6UdK9kkaWe2aiTDARywDqSHd3N3PnznUjdJKPAQMDlW3DYxFBwfRPAQ8A34MhhePeQBDOOx7YDlxW7oGJGQ4DLF26NG4JdaW9vZ329nbPQOM0BvUZDn8CeCLcfwT4M/BD8sJxgZclReG4T0Y3hsv5zgXmhId6gE6CwI6iJKonmFaiDDTeI3SSS93C5vqBL4b7X2Z34EUl4bhHAzvM7MMS1+xDonqCaWbSpEmDy2fcDJ3EYWCVrxMcLWll3ucLzWxh9ImkR4FjC9y3APg6cLOk6wgCL3ZGtxVWtQcVhezujZtggohijdvb290IneRRecTINjObWuykmZ1X5v7PA0g6BbgwPFZJOO42ICPpwLA3WDBkd28a0gSbaXKkED09PfT09MQtw3H2pA7vBCUdY2ZbJB0A/AC4LTxVNhzXzEzScuBLwBLgUuAP5Z7ZkCaYtgkUx6mEGTNm1O6Lm1Vj5rcSLpE0P9y/H7greHzxcFxJy4B5ZrYJuBpYIuknwDMEeQ9K0pAm6DhODNShJ2hmNwEFs0YUC8c1s+l5+y8xxCTOboKO41SAYbuaMw+Km6DjOOVJeSotx3Gc9KbSchzHMcC8J5gcajoL5jjOvliKk6omkWZKreU41aLW62ebdWJESTAUSVuB9whWfCeR0bi2oZJUXZA+bR8zs2FVM5P0JwJtlbDNzM4fzvPqSSJMEEDSylKhNnHi2oZOUnWBa3P2xLPIOI6TatwEHcdJNUkywYXlL4kN1zZ0kqoLXJuTR2LeCTqO48RBknqCjuM4dSd2E5R0flg9aoOkaxKgZ2NY6SoXZceVdJSkR8IKVo9IOrJOWu6UtEVSf96xgloUcHPYjmskTYlBW6ek18O2y0manneubKWwKmo7UdJySeslrZN0ZXg89rYroS0RbZdKogLncWzACOCfwEnASGA1MCFmTRuB0Xsd+zlBBSyAa4Ab6qTlbGAK0F9OCzAd+CNBivFpwIoYtHUCVxW4dkL4sz0YGBf+zEfUUNtYYEq4fxjwQqgh9rYroS0RbZfGLe6e4BnABjN7ycx2EmSDnRmzpkLMJKhcRfixrR4PNbMngLcr1DITWGwBfydIMz62ztqKMVgpzMxeBqJKYbXSttnMng733wXWExTcib3tSmgrRl3bLo3EbYKVVJCqNwY8LGmVpMvDYx81s80Q/BIDx8SmrriWpLTlFeGQ8s681waxaZPUAkwGVpCwtttLGySs7dJC3Ca4X9WhasxZZjYFuACYL+nsmPVUShLa8lbgZGASsBn4RXg8Fm2SRgH3AR1m9k6pSwscq6m+AtoS1XZpIm4TrKSCVF2xoE4BZrYFeIBg6PFmNDwKP26JT2FRLbG3pZm9aWa7LKjNeDu7h2111ybpIAKTucfM7g8PJ6LtCmlLUtuljbhN8ClgvKRxkkYCswmqSsWCpEMlHRbtE5T+6w81XRpeVlEFqxpSTMuDwNfCmc5pwL+ioV+92Os92iyCtou0zZZ0sKRxFKgUVmUdIiiws97Mbsw7FXvbFdOWlLZLJXHPzBDMzL1AMOu1IGYtJxHMxK0G1kV6CCrbPwa8GH48qk56fkMwNPqAoEdwWTEtBMOmX4XtuBaYGoO2u8NnryH44x2bd/2CUNvzwAU11vYZgiHjGiAXbtOT0HYltCWi7dK4ecSI4zipJu7hsOM4Tqy4CTqOk2rcBB3HSTVugo7jpBo3QcdxUo2boOM4qcZN0HGcVOMm6DhOqvk/LX+Zz52zETAAAAAASUVORK5CYII=\n",
"text/plain": [
"<Figure size 432x288 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"volgend routerid \n",
"\n",
"\n",
"\n"
]
}
],
"source": [
"def displayData(df, s=\"Displaying room {}\", amount = -1):\n",
" locs = df.location.unique()\n",
" for loc in locs:\n",
" tdf = df.loc[df[\"location\"] == loc]\n",
" x, y, z = tdf.x, tdf.y, tdf.signal\n",
" img = plt.imread(loc.lower()+\".png\")\n",
" plt.scatter(x, y, c=z)\n",
" plt.colorbar()\n",
" plt.imshow(img)\n",
" plt.show()\n",
" amount -= 1\n",
" if amount == 0:\n",
" return\n",
" return\n",
"\n",
"for t in df.routerId.unique():\n",
" displayData(df.loc[df[\"routerId\"] == t], s=\"locatie = {} en routerid addr = {}\".format(\"{}\", t))\n",
" print(\"volgend routerid \\n\\n\\n\")\n",
" break"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Wat we hier kunnen zien is dat we soms toch wel meetpunten hebben op een identieke plek met redelijk gelijkaardige resultaten. Dit zorgt ervoor dat een trainingset van deze data niet divers genoeg is en we zullen hier dus enkele entries uit moeten halen.\n",
"\n",
"\n",
"# selectie van de data\n",
"\n",
"Een functie (closetoothers) krijgt een item, en een lijst van objects samen met een percentage en gaat zo de dataframe van deze lijst af om te kijken of er gelijkaardige items al aanwezig zijn in de lijst (op basis van het x en y coordinaat). Als dit niet zo is wordt het item toegevoegd aan de lijst en de lijst gereturned. Dit wordt dan gelooped in de removeIrrelevant functie en zal dan onze gefilterde lijst terug geven.\n",
"\n",
"Na wat research (https://www.metageek.com/training/resources/wifi-signal-strength-basics.html) kunnen we zien dat signalen onder -80 db onbruikbaar zijn, en signalen vanaf -70db okay zijn. Hier zal dus mee gespeeld worden bij de CloseToOthers functie om een bruikbare set te creeeren."
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"\n",
" \n",
"def removeIrelevant(df, minSampleSize=50):\n",
" rdf = []\n",
" returnable = pd.DataFrame()\n",
" for i, v in df.iterrows():\n",
" rdf = CloseToOthers(v, rdf)\n",
" rdf = pd.DataFrame(rdf)\n",
" for i in rdf.location.unique():\n",
" trdf = rdf.loc[rdf['location'] == i]\n",
" for j in trdf.routerId.unique():\n",
" ttrdf = trdf.loc[trdf['routerId'] == j]\n",
" #print(ttrdf.head())\n",
" if len(ttrdf) < minSampleSize:\n",
" rdf.drop(ttrdf.index)\n",
" return rdf\n",
"\n",
"def CloseToOthers(i, df, percentage = .1, sig = -80):\n",
" tdf = pd.DataFrame(df)\n",
" approved = []\n",
" if \"location\" in tdf:\n",
" l = tdf.loc[tdf[\"location\"] == i[\"location\"]]\n",
" l2 = l.loc[l[\"routerId\"] == i[\"routerId\"]]\n",
" for dump, j in l2.iterrows():\n",
" if not (j.sender == i.sender):\n",
" temp = abs(j.px - i.px)\n",
" temp2 = abs(j.py - i.py)\n",
" temp3 = abs(j.signal - i.signal)\n",
" if temp <= percentage and temp2 <= percentage and temp3 <= percentage:\n",
" return df\n",
" #else:\n",
" #print(i)\n",
" df.append(i)\n",
" return df\n",
" else:\n",
" df.append(i)\n",
" return df\n",
" \n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"g = removeIrelevant(df)\n",
"print(\"oud: {} \\nNieuw: {}\".format(len(df), len(g)))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Voorbereiden model\n",
"\n",
"## TrainingData Voorbereiden\n",
"\n",
"door het gebruik van traintestsplit kunnen we onze trainingsdata splitten zodat we later een test set kunnen gebruiken om te kijken hoe effectief onze trainingsdata is. onze x data zullen de meet coordinaten zijn en onze y data zal de signaal sterkte van deze punten zijn. Op die manier kunnen we een model fitten en daarna het signaal predicten voor bepaalde coordinaten.\n",
"\n",
"Door een Scaler te gebruiken kunnen we onze trainingsdata rescalen en kijken wat het effect hiervan is. Hieronder zijn alle voorbeelden van scalers die gebruikt werden te vinden.\n",
"\n",
"Er zal ook een display functie aangemaakt worden zodat we de eigenlijke effecten van deze models kunnen bekijken. Dit wordt gedaan door een value te predicten voor elke x, y overheen de afbeelding.\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"from sklearn.model_selection import train_test_split\n",
"from sklearn.preprocessing import StandardScaler\n",
"from sklearn.preprocessing import MinMaxScaler\n",
"from sklearn.preprocessing import MaxAbsScaler\n",
"from sklearn.preprocessing import Normalizer\n",
"\n",
"def prepTrainingmk1(df, random_state=2):\n",
" tx = df[\"x\"]\n",
" ty = df[\"y\"]\n",
" y = df[\"signal\"]\n",
" x = np.column_stack((tx, ty))\n",
" if x.shape[0] < 2:\n",
" return 0, 0, 0, 0, False\n",
" xtrain, xtest, ytrain, ytest = train_test_split(x, y, random_state=random_state)\n",
" return xtest, ytest, xtrain, ytrain, True\n",
"\n",
"def prepTrainingmk2(df, random_state=2):\n",
" tx = df[\"x\"].tolist()\n",
" ty = df[\"y\"].tolist()\n",
" y = df[\"signal\"]\n",
" x = np.column_stack((tx, ty))\n",
" scaler = StandardScaler()\n",
" tmp = x.shape\n",
" #print(tmp[0])\n",
" if x.shape[0] < 2:\n",
" return 0, 0, 0, 0, False\n",
" xtrain, xtest, ytrain, ytest = train_test_split(x, y)\n",
" scaler.fit(xtrain)\n",
" xtrain = scaler.transform(xtrain)\n",
" xtest = scaler.transform(xtest)\n",
" return xtest, ytest, xtrain, ytrain, True\n",
"\n",
"\n",
"def prepTrainingmk3(df, random_state=2):\n",
" tx = df[\"x\"].tolist()\n",
" ty = df[\"y\"].tolist()\n",
" y = df[\"signal\"]\n",
" x = np.column_stack((tx, ty))\n",
" scaler = Normalizer()\n",
" tmp = x.shape\n",
" #print(tmp[0])\n",
" if x.shape[0] < 2:\n",
" return 0, 0, 0, 0, False\n",
" xtrain, xtest, ytrain, ytest = train_test_split(x, y)\n",
" scaler.fit(xtrain)\n",
" xtrain = scaler.transform(xtrain)\n",
" xtest = scaler.transform(xtest)\n",
" return xtest, ytest, xtrain, ytrain, True\n",
"\n",
"def prepTrainingmk4(df, random_state=2):\n",
" tx = df[\"x\"].tolist()\n",
" ty = df[\"y\"].tolist()\n",
" y = df[\"signal\"]\n",
" x = np.column_stack((tx, ty))\n",
" scaler = MaxAbsScaler()\n",
" tmp = x.shape\n",
" #print(tmp[0])\n",
" if x.shape[0] < 2:\n",
" return 0, 0, 0, 0, False\n",
" xtrain, xtest, ytrain, ytest = train_test_split(x, y)\n",
" scaler.fit(xtrain)\n",
" xtrain = scaler.transform(xtrain)\n",
" xtest = scaler.transform(xtest)\n",
" return xtest, ytest, xtrain, ytrain, True\n",
"\n",
"\n",
"\n",
"def prepTraining(df, random_state=2):\n",
" tx = df[\"x\"].tolist()\n",
" ty = df[\"y\"].tolist()\n",
" y = df[\"signal\"]\n",
" x = np.column_stack((tx, ty))\n",
" tmp = x.shape\n",
" if x.shape[0] < 2:\n",
" return 0, 0, 0, 0, False\n",
" xtrain, xtest, ytrain, ytest = train_test_split(x, y)\n",
" if len(xtest) < 3 or len(ytest) < 3:\n",
" return 0, 0, 0, 0, False\n",
" scaler = MinMaxScaler(feature_range=(-100,0))\n",
" scaler.fit(xtrain)\n",
" xtrain = scaler.transform(xtrain)\n",
" xtest = scaler.transform(xtest)\n",
" return xtest, ytest, xtrain, ytrain, True\n",
"\n",
"\n",
"def displayModel(t, stepSize =5, alpha=1):\n",
" for lokaal in t:\n",
" img = plt.imread(lokaal+\".png\")\n",
" height, width, channels = img.shape\n",
" for router in t[lokaal]:\n",
" if t[lokaal][router] is None:\n",
" continue\n",
" print(\"Lokaal {} routermac {}\".format(lokaal, router))\n",
" z, xx, yy = [], [], []\n",
" for i in range(1, width+1, stepSize):\n",
" for j in range(1, height+1, stepSize):\n",
" xx.append(i)\n",
" yy.append(j)\n",
" np.column_stack((i, j))\n",
" z.append(t[lokaal][router].predict(np.column_stack((i, j)))[0])\n",
" plt.scatter(xx, yy, c=z, alpha=alpha)\n",
" plt.colorbar()\n",
" plt.imshow(img)\n",
" plt.show()\n",
"\n",
"def display1Model(t, stepSize=5):\n",
" for lokaal in t:\n",
" img = plt.imread(lokaal+\".png\")\n",
" height, width, channels = img.shape\n",
" for router in t[lokaal]:\n",
" print(\"Lokaal {} routermac {}\".format(lokaal, router))\n",
" z, xx, yy = [], [], []\n",
" if t[lokaal][router] is None:\n",
" continue\n",
" for i in range(1, width+1, stepSize):\n",
" for j in range(1, height+1, stepSize):\n",
" xx.append(i)\n",
" yy.append(j)\n",
" np.column_stack((i, j))\n",
" z.append(t[lokaal][router].predict(np.column_stack((i, j)))[0])\n",
" plt.scatter(xx, yy, c=z, alpha=.1)\n",
" plt.colorbar()\n",
" plt.imshow(img)\n",
" plt.show()\n",
" break"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Linear regression"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"from sklearn.linear_model import LinearRegression\n",
"from sklearn.model_selection import KFold\n",
"from sklearn.model_selection import cross_val_score\n",
"\n",
"def train(df, debug=False, results=False, fullScore=False):\n",
" succCount = 0\n",
" total = 0\n",
" models = dict.fromkeys(df.location.unique(), {})\n",
" for i in df.location.unique():\n",
" temp = df.loc[df[\"location\"] == i]\n",
" for j in temp.routerId.unique():\n",
" temp2 = temp.loc[temp[\"routerId\"] == j]\n",
" xtest, ytest, xtrain, ytrain, succ = prepTraining(temp2)\n",
" if not succ:\n",
" models[i][j] = None\n",
" continue\n",
" if len(xtrain) == 0 or len(ytrain) == 0:\n",
" if debug:\n",
" print(temp2)\n",
" continue\n",
" lr = LinearRegression(n_jobs=-1).fit(xtrain, ytrain)\n",
" models[i][j] = lr\n",
" if results:\n",
" ##rint(\"xtest {} ytest {} xtrain {} ytrain {}\".format(xtest, ytest, xtrain, ytrain))\n",
" if fullScore:\n",
" for i, v in enumerate(xtest):\n",
" #print(v)\n",
" #print(i)\n",
" #print(ytest)\n",
" f = lr.score(xtest, ytest)\n",
" print(f)\n",
" result1 = lr.score(xtest, ytest) > .7\n",
" result = KFold(n_splits=3)\n",
" #print(\"Cross-validation scores:\\n{}\".format(cross_val_score(lr, xtest, ytest, cv=result)))\n",
" if cross_val_score(lr, xtest, ytest, cv=result).mean() > .5:\n",
" succCount += 1\n",
" total += 1\n",
" continue\n",
" print(\"training data for {} with routerid {}\".format(i, j))\n",
" print(\"lr.coef_:\", lr.coef_)\n",
" print(\"lr.intercept_:\", lr.intercept_)\n",
" print(\"Training set score: {:.2f}\".format(lr.score(xtrain, ytrain)))\n",
" print(\"Test set score: {:.2f}\".format(lr.score(xtest, ytest)))\n",
" #displayData(temp2 ,\"{}\")\n",
" print(\"\\n\\n\\n\")\n",
" if results:\n",
" print(\"{} / {}\".format(succCount, total))\n",
" return models"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"\n",
"\n",
"#a = train(df, results=True)\n",
"b = train(pd.DataFrame(g), results=True)\n",
"#print(\"FullDataFrame\")\n",
"#displayModel(a)\n",
"print(\"Selection\")\n",
"displayModel(b)\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## SVR\n",
"\n",
"Volgens mij het meest passende model bij deze opgave. Lineare regressie heeft een probleem met een router passeren / andere problemen die bij lineare modellen komen. De oplossing hiervoor is een niet lineare model. Hiervoor heb ik svc gekozen. Aan de hand van enkele voorbeelden heb ik gezien dat dit nuttig kan zijn voor een heatmap te maken van een punt dat de max is van de dataset. Ipv lineare modellen die een rechte tekenen in de richting van dit punt, zal dit model in 360 graden rond dit punt de heatmap correct genereren."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"from sklearn.svm import SVR\n",
"\n",
"\n",
"def trainSvc(df, debug=False, results=False):\n",
" RsuccCount, succCount = 0, 0\n",
" total = 0\n",
" models = dict.fromkeys(df.location.unique(), {})\n",
" for i in df.location.unique():\n",
" temp = df.loc[df[\"location\"] == i]\n",
" for j in temp.routerId.unique():\n",
" temp2 = temp.loc[temp[\"routerId\"] == j]\n",
" xtest, ytest, xtrain, ytrain, succ = prepTraining(temp2)\n",
" if not succ:\n",
" models[i][j] = None\n",
" continue\n",
" if len(xtrain) == 0 or len(ytrain) == 0:\n",
" if debug:\n",
" print(temp2)\n",
" continue\n",
" #lr = SVR(kernel='rbf', C=1, gamma=\"auto_deprecated\", epsilon=0.8).fit(xtrain, ytrain)\n",
" lr = SVR(kernel='rbf', C=1, gamma=\"scale\", epsilon=0.8).fit(xtrain, ytrain)\n",
" #lr = SVC(random_state=0, gamma='scale', degree=10).fit(xtrain, ytrain)\n",
" models[i][j] = lr\n",
" if results:\n",
" ##rint(\"xtest {} ytest {} xtrain {} ytrain {}\".format(xtest, ytest, xtrain, ytrain))\n",
" result1 = lr.score(xtest, ytest) > .7\n",
" result = KFold(n_splits=3)\n",
" #print(\"Cross-validation scores:\\n{}\".format(cross_val_score(lr, xtest, ytest, cv=result)))\n",
" \n",
" if result1:\n",
" succCount += 1\n",
" if cross_val_score(lr, xtest, ytest, cv=result).mean() > .5:\n",
" RsuccCount += 1\n",
" total += 1\n",
" continue\n",
" print(\"training data for {} with routerid {}\".format(i, j))\n",
" print(\"lr.coef_:\", lr.coef_)\n",
" print(\"lr.intercept_:\", lr.intercept_)\n",
" print(\"Training set score: {:.2f}\".format(lr.score(xtrain, ytrain)))\n",
" print(\"Test set score: {:.2f}\".format(lr.score(xtest, ytest)))\n",
" #displayData(temp2 ,\"{}\")\n",
" print(\"\\n\\n\\n\")\n",
" if results:\n",
" print(\"{} / {}\".format(succCount, total))\n",
" print(\"{} / {}\".format(RsuccCount, total))\n",
" return models"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"#a = trainSvc(df, results=True)\n",
"b = trainSvc(pd.DataFrame(g), results=True)\n",
"print(\"FullDataFrame\")\n",
"#displayModel(a)\n",
"print(\"Selection\")\n",
"displayModel(b)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## nusvr"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"from sklearn.svm import NuSVR\n",
"\n",
"def trainNuSvc(df, debug=False, results=False):\n",
" succCount = 0\n",
" total = 0\n",
" models = dict.fromkeys(df.location.unique(), {})\n",
" for i in df.location.unique():\n",
" temp = df.loc[df[\"location\"] == i]\n",
" for j in temp.routerId.unique():\n",
" temp2 = temp.loc[temp[\"routerId\"] == j]\n",
" xtest, ytest, xtrain, ytrain, succ = prepTraining(temp2)\n",
" if not succ:\n",
" models[i][j] = None\n",
" continue\n",
" if len(xtrain) == 0 or len(ytrain) == 0:\n",
" if debug:\n",
" print(temp2)\n",
" continue\n",
" lr = NuSVR(kernel='rbf', C=20, gamma=\"scale\").fit(xtrain, ytrain)\n",
" #lr = SVC(random_state=0, gamma='scale', degree=10).fit(xtrain, ytrain)\n",
" models[i][j] = lr\n",
" if results:\n",
" ##rint(\"xtest {} ytest {} xtrain {} ytrain {}\".format(xtest, ytest, xtrain, ytrain))\n",
" if lr.score(xtest, ytest) > .7:\n",
" succCount += 1\n",
" total += 1\n",
" continue\n",
" print(\"training data for {} with routerid {}\".format(i, j))\n",
" print(\"lr.coef_:\", lr.coef_)\n",
" print(\"lr.intercept_:\", lr.intercept_)\n",
" print(\"Training set score: {:.2f}\".format(lr.score(xtrain, ytrain)))\n",
" print(\"Test set score: {:.2f}\".format(lr.score(xtest, ytest)))\n",
" #displayData(temp2 ,\"{}\")\n",
" print(\"\\n\\n\\n\")\n",
" if results:\n",
" print(\"{} / {}\".format(succCount, total))\n",
" return models"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"b = trainNuSvc(pd.DataFrame(g), results=True)\n",
"print(\"FullDataFrame\")\n",
"#displayModel(a)\n",
"print(\"Selection\")\n",
"displayModel(b)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## DecisionTreeRegressor"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"from sklearn.tree import DecisionTreeRegressor\n",
"from sklearn.model_selection import cross_val_score\n",
"\n",
"\n",
"\n",
"def trainTree(df,advanced = False, debug=False, results=False, max_depth=12, successPercentage=.5):\n",
" models = dict.fromkeys(df.location.unique(), {})\n",
" succCount = 0\n",
" total = 0\n",
" for i in df.location.unique():\n",
" temp = df.loc[df[\"location\"] == i]\n",
" for j in temp.routerId.unique():\n",
" temp2 = temp.loc[temp[\"routerId\"] == j]\n",
" xtest, ytest, xtrain, ytrain, succ = prepTraining(temp2)\n",
" if not succ:\n",
" models[i][j] = None\n",
" continue\n",
" if len(xtrain) == 0 or len(ytrain) == 0:\n",
" #print(\"\\n\\n\\n!!!probleem met training data?!!!\\n\\n\\n\")\n",
" if debug:\n",
" print(temp2)\n",
" continue\n",
" lr = DecisionTreeRegressor(max_depth=max_depth)\n",
" lr.fit(xtrain, ytrain)\n",
" models[i][j] = lr\n",
" if results:\n",
" if advanced:\n",
" temp = cross_val_score(lr, xtest, ytest, cv = 3)\n",
" print(temp)\n",
" continue\n",
" if lr.score(xtest, ytest) > successPercentage:\n",
" #print(\"success\")\n",
" succCount += 1\n",
" #else:\n",
" #print(\"nope\")\n",
" total += 1\n",
" continue\n",
" \n",
" y1 = lr.predict(xtest)\n",
" print(\"test\")\n",
" #print(temp2)\n",
" displayData(temp2 ,\"{}\")\n",
" print(\"\\n\\n\\n\")\n",
" if results:\n",
" print(\"{} / {}\".format(succCount, total))\n",
" return models\n",
" \n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"#a = trainTree(df, results=True, successPercentage=.5)\n",
"b = trainTree(pd.DataFrame(g), results=True, successPercentage=.5)\n",
"\n",
"\n",
"#print(\"FullDataFrame\")\n",
"#displayModel(a)\n",
"print(\"Selection\")\n",
"displayModel(b)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## MaxDepth\n",
"\n",
"zoals we hieronder kunnen zien is rond een maxdepth van 15-20 genoeg voor deze opgave."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"for i in range(1, 50):\n",
" print(\"\\n\\nFor maxdepth of {}\".format(i))\n",
" a = trainTree(df, results=True, successPercentage=.5, max_depth=i)\n",
" b = trainTree(pd.DataFrame(g), results=True, successPercentage=.5, max_depth=i)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"#a = trainTree(pd.DataFrame(df), results=True, successPercentage=.5, max_depth=20)\n",
"b = trainTree(pd.DataFrame(g), results=True, successPercentage=.5, max_depth=20)\n",
"\n",
"\n",
"#print(\"FullDataFrame\")\n",
"#displayModel(a)\n",
"print(\"Selection\")\n",
"displayModel(b)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## logistic regression\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"from sklearn.linear_model import LogisticRegression\n",
"\n",
"def trainLogistic(df,advanced = False, debug=False, results=False, rstate=0, successPercentage=.5):\n",
" models = dict.fromkeys(df.location.unique(), {})\n",
" succCount = 0\n",
" total = 0\n",
" for i in df.location.unique():\n",
" temp = df.loc[df[\"location\"] == i]\n",
" for j in temp.routerId.unique():\n",
" temp2 = temp.loc[temp[\"routerId\"] == j]\n",
" xtest, ytest, xtrain, ytrain, succ = prepTraining(temp2)\n",
" if not succ:\n",
" models[i][j] = None\n",
" continue\n",
" if len(xtrain) == 0 or len(ytrain) == 0:\n",
" #print(\"\\n\\n\\n!!!probleem met training data?!!!\\n\\n\\n\")\n",
" if debug:\n",
" print(temp2)\n",
" continue\n",
" lr = LogisticRegression()\n",
" lr.fit(xtrain, ytrain)\n",
" models[i][j] = lr\n",
" if results:\n",
" if advanced:\n",
" temp = cross_val_score(lr, xtest, ytest, cv = 3)\n",
" print(temp)\n",
" continue\n",
" if lr.score(xtest, ytest) > successPercentage:\n",
" #print(\"success\")\n",
" succCount += 1\n",
" #else:\n",
" #print(\"nope\")\n",
" total += 1\n",
" continue\n",
" \n",
" y1 = lr.predict(xtest)\n",
" print(\"test\")\n",
" #print(temp2)\n",
" displayData(temp2 ,\"{}\")\n",
" print(\"\\n\\n\\n\")\n",
" if results:\n",
" print(\"{} / {}\".format(succCount, total))\n",
" return models"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"#a = trainLogistic(df, results=True, successPercentage=.5)\n",
"b = trainLogistic(pd.DataFrame(g), results=True, successPercentage=.5)\n",
"\n",
"\n",
"#print(\"FullDataFrame\")\n",
"#displayModel(a)\n",
"print(\"Selection\")\n",
"displayModel(b)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Gaussian process"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"from sklearn.gaussian_process import GaussianProcessRegressor\n",
"from sklearn.gaussian_process.kernels import DotProduct, WhiteKernel, RBF\n",
"\n",
"def trainGauss(df, debug=False, results=False):\n",
" succCount = 0\n",
" total = 0\n",
" models = dict.fromkeys(df.location.unique(), {})\n",
" for i in df.location.unique():\n",
" temp = df.loc[df[\"location\"] == i]\n",
" for j in temp.routerId.unique():\n",
" temp2 = temp.loc[temp[\"routerId\"] == j]\n",
" xtest, ytest, xtrain, ytrain, succ = prepTraining(temp2)\n",
" if not succ:\n",
" models[i][j] = None\n",
" continue\n",
" if len(xtrain) == 0 or len(ytrain) == 0:\n",
" if debug:\n",
" print(temp2)\n",
" continue\n",
" kernel = RBF()\n",
" lr = GaussianProcessRegressor(kernel=kernel)\n",
" lr.fit(xtrain, ytrain)\n",
" #lr = SVC(random_state=0, gamma='scale', degree=10).fit(xtrain, ytrain)\n",
" models[i][j] = lr\n",
" if results:\n",
" ##rint(\"xtest {} ytest {} xtrain {} ytrain {}\".format(xtest, ytest, xtrain, ytrain))\n",
" if lr.score(xtest, ytest) > .5:\n",
" succCount += 1\n",
" total += 1\n",
" continue\n",
" print(\"training data for {} with routerid {}\".format(i, j))\n",
" print(\"lr.coef_:\", lr.coef_)\n",
" print(\"lr.intercept_:\", lr.intercept_)\n",
" print(\"Training set score: {:.2f}\".format(lr.score(xtrain, ytrain)))\n",
" print(\"Test set score: {:.2f}\".format(lr.score(xtest, ytest)))\n",
" displayData(temp2 ,\"{}\")\n",
" print(\"\\n\\n\\n\")\n",
" if results:\n",
" print(\"{} / {}\".format(succCount, total))\n",
" return models"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"#a = trainGauss(df, results=True)\n",
"b = trainGauss(pd.DataFrame(g), results=True)\n",
"\n",
"\n",
"print(\"FullDataFrame\")\n",
"#displayModel(a)\n",
"print(\"Selection\")\n",
"displayModel(b)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## neural net regression"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"from sklearn.neural_network import MLPRegressor\n",
"\n",
"def trainNeural(df, debug=False, results=False):\n",
" succCount = 0\n",
" total = 0\n",
" models = dict.fromkeys(df.location.unique(), {})\n",
" for i in df.location.unique():\n",
" temp = df.loc[df[\"location\"] == i]\n",
" for j in temp.routerId.unique():\n",
" temp2 = temp.loc[temp[\"routerId\"] == j]\n",
" xtest, ytest, xtrain, ytrain, succ = prepTraining(temp2)\n",
" if not succ:\n",
" models[i][j] = None\n",
" continue\n",
" if len(xtrain) == 0 or len(ytrain) == 0:\n",
" if debug:\n",
" print(temp2)\n",
" continue\n",
" lr = MLPRegressor(learning_rate=\"adaptive\",max_iter=100, activation='logistic')\n",
" lr.fit(xtrain, ytrain)\n",
" #lr = SVC(random_state=0, gamma='scale', degree=10).fit(xtrain, ytrain)\n",
" models[i][j] = lr\n",
" if results:\n",
" ##rint(\"xtest {} ytest {} xtrain {} ytrain {}\".format(xtest, ytest, xtrain, ytrain))\n",
" if lr.score(xtest, ytest) > .5:\n",
" succCount += 1\n",
" total += 1\n",
" continue\n",
" print(\"training data for {} with routerid {}\".format(i, j))\n",
" print(\"lr.coef_:\", lr.coef_)\n",
" print(\"lr.intercept_:\", lr.intercept_)\n",
" print(\"Training set score: {:.2f}\".format(lr.score(xtrain, ytrain)))\n",
" print(\"Test set score: {:.2f}\".format(lr.score(xtest, ytest)))\n",
" displayData(temp2 ,\"{}\")\n",
" print(\"\\n\\n\\n\")\n",
" if results:\n",
" print(\"{} / {}\".format(succCount, total))\n",
" return models"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"#a = trainGauss(df, results=True)\n",
"b = trainNeural(pd.DataFrame(g), results=True)\n",
"\n",
"\n",
"print(\"FullDataFrame\")\n",
"#displayModel(a)\n",
"print(\"Selection\")\n",
"displayModel(b)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## qda"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"from sklearn.qda import QDA\n",
"\n",
"def trainQDA(df, debug=False, results=False):\n",
" succCount = 0\n",
" total = 0\n",
" models = dict.fromkeys(df.location.unique(), {})\n",
" for i in df.location.unique():\n",
" temp = df.loc[df[\"location\"] == i]\n",
" for j in temp.routerId.unique():\n",
" temp2 = temp.loc[temp[\"routerId\"] == j]\n",
" xtest, ytest, xtrain, ytrain, succ = prepTraining(temp2)\n",
" if not succ:\n",
" models[i][j] = None\n",
" continue\n",
" if len(xtrain) == 0 or len(ytrain) == 0:\n",
" if debug:\n",
" print(temp2)\n",
" continue\n",
" lr = QDA()\n",
" lr.fit(xtrain, ytrain)\n",
" #lr = SVC(random_state=0, gamma='scale', degree=10).fit(xtrain, ytrain)\n",
" models[i][j] = lr\n",
" if results:\n",
" ##rint(\"xtest {} ytest {} xtrain {} ytrain {}\".format(xtest, ytest, xtrain, ytrain))\n",
" if lr.score(xtest, ytest) > .5:\n",
" succCount += 1\n",
" total += 1\n",
" continue\n",
" print(\"training data for {} with routerid {}\".format(i, j))\n",
" print(\"lr.coef_:\", lr.coef_)\n",
" print(\"lr.intercept_:\", lr.intercept_)\n",
" print(\"Training set score: {:.2f}\".format(lr.score(xtrain, ytrain)))\n",
" print(\"Test set score: {:.2f}\".format(lr.score(xtest, ytest)))\n",
" displayData(temp2 ,\"{}\")\n",
" print(\"\\n\\n\\n\")\n",
" if results:\n",
" print(\"{} / {}\".format(succCount, total))\n",
" return models"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"b = trainQDA(pd.DataFrame(g), results=True)\n",
"\n",
"\n",
"print(\"FullDataFrame\")\n",
"#displayModel(a)\n",
"print(\"Selection\")\n",
"displayModel(b)"
]
}
],
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