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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"import numpy as np\n",
"from math import floor, ceil\n",
"from matplotlib import path\n",
"\n",
"def process_line(line):\n",
" # Not sure what these values are\n",
" val1 = line[0]\n",
" val2 = line[1]\n",
" polyline = [float(v) for v in line[2:]]\n",
" polyline = np.array(list(zip(polyline[0::2], polyline[1::2])))\n",
" return val1, val2, polyline \n",
"\n",
"with open(\"./DataForUConn/DecideRegion/area.txt\") as f:\n",
" area = [process_line(line.split(\",\")) for line in f.read().strip().split(\"\\n\")]\n",
"\n",
"polypaths = [path.Path(line[2][1:]) for line in area]\n",
"\n",
"def point_to_rids(point, polypaths=polypaths, radius=0.0):\n",
" RIDs = []\n",
" for rid, polypath in enumerate(polypaths):\n",
" if polypath.contains_point(point, radius=radius):\n",
" RIDs.append(rid)\n",
" \n",
" return RIDs"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.5"
}
},
"nbformat": 4,
"nbformat_minor": 4
}