{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "8ab10f475f7cbaac",
   "metadata": {},
   "source": "# Geoprocessing"
  },
  {
   "cell_type": "code",
   "id": "initial_id",
   "metadata": {
    "collapsed": true,
    "ExecuteTime": {
     "end_time": "2026-05-01T01:29:15.549370731Z",
     "start_time": "2026-05-01T01:29:03.762759323Z"
    }
   },
   "source": [
    "import footbridge as ft\n",
    "import geopandas as gpd\n",
    "\n",
    "# large dataset of US National Highway System roads\n",
    "# https://hepgis-usdot.hub.arcgis.com/datasets/dce9f09392eb474c8ad8e6a78416279b_0\n",
    "fc1 = ft.FeatureClass(\"NHS.gdb/National_Highway_System__NHS_\")\n",
    "f\"{len(fc1)} rows\""
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'492005 rows'"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 6
  },
  {
   "cell_type": "code",
   "id": "a56d120422259bfb",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-05-01T01:30:29.140887164Z",
     "start_time": "2026-05-01T01:30:23.446793138Z"
    }
   },
   "source": [
    "# filter by route ID\n",
    "route = \"  I 017\"\n",
    "field_name = \"ROUTEID\"\n",
    "column_index = fc1.list_fields().index(field_name)\n",
    "\n",
    "filtered = list()\n",
    "for row in fc1:\n",
    "    if row[column_index] == route:\n",
    "        filtered.append(row)\n",
    "\n",
    "fc2 = ft.FeatureClass(gpd.GeoDataFrame(filtered))\n",
    "f\"{len(fc2)} rows where ROUTEID == '{route}'\""
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\"100 rows where ROUTEID == '  I 017'\""
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 12
  },
  {
   "cell_type": "code",
   "id": "d590a74670da4820",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-05-01T01:31:26.510593754Z",
     "start_time": "2026-05-01T01:31:26.331277342Z"
    }
   },
   "source": [
    "# TODO buffer with GeoPandas\n",
    "gdf_buf = ft.buffer(fc2, 10000)\n",
    "gdf_buf.show()"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data",
     "jetTransient": {
      "display_id": null
     }
    }
   ],
   "execution_count": 18
  },
  {
   "cell_type": "code",
   "id": "c552399ac5be7cd5",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-05-01T01:31:28.484071626Z",
     "start_time": "2026-05-01T01:31:28.476077310Z"
    }
   },
   "source": [
    "# Load results into a new feature class and geodatabase in memory\n",
    "fc3 = ft.FeatureClass(gdf_buf)\n",
    "gdb = ft.GeoDatabase()\n",
    "gdb[\"NHS_selection_buffered\"] = fc3"
   ],
   "outputs": [],
   "execution_count": 19
  },
  {
   "cell_type": "code",
   "id": "3c08ddfea74411c6",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-05-01T01:31:30.679190155Z",
     "start_time": "2026-05-01T01:31:30.621235219Z"
    }
   },
   "source": [
    "# Save to disk\n",
    "gdb.save(\"NHS_selection.gdb\", overwrite=True)\n",
    "ft.list_datasets(\"NHS_selection.gdb\")"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{None: ['NHS_selection_buffered']}"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 20
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}