{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "266d01e3-75cf-44c0-b648-a5551f3e7c6e",
   "metadata": {},
   "outputs": [],
   "source": [
    "import geopandas as gpd\n",
    "from pathlib import Path\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "a24db3f2-c414-4664-ab23-c30a77547be2",
   "metadata": {},
   "outputs": [],
   "source": [
    "city = 'Luanda'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "53e8bce0-a7c8-406e-bccb-98451d20c9b8",
   "metadata": {},
   "outputs": [],
   "source": [
    "# read catchment AOI\n",
    "aoi = gpd.read_file('AOI/luanda_catchment_level4.shp').to_crs(epsg = 4326)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "bdb98278-1faa-4e1e-9ec5-7efd08a327d1",
   "metadata": {},
   "outputs": [],
   "source": [
    "output_folder = Path('output')\n",
    "dam_data = gpd.read_file(r\"C:\\Users\\Owner\\Documents\\Career\\World Bank\\CRP\\data\\GOODD\\GOOD2_dams.shp\")\n",
    "reservoir_data = gpd.read_file(r\"C:\\Users\\Owner\\Documents\\Career\\World Bank\\CRP\\data\\GRanD\\GRanD_reservoirs_v1_3.shp\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "abd0f218-975d-4f6f-ba0d-93dac4b17cb2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['DAM_ID', 'Count_ID', 'Latitud', 'Longitud', 'geometry'], dtype='object')"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dam_data.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "ddecea9a-2ec4-4aba-8366-20819bb46e28",
   "metadata": {},
   "outputs": [],
   "source": [
    "# filter for dams in AOI\n",
    "dams_list = []\n",
    "\n",
    "for i in range(len(aoi)):\n",
    "    dams_list.append(dam_data.loc[dam_data.within(aoi.loc[i, 'geometry'])])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "0cb6272c-b05c-4d50-a638-f029a91bc862",
   "metadata": {},
   "outputs": [],
   "source": [
    "dams = pd.concat(dams_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "4ec36a66-1490-482e-9fcb-6ba2fb49306f",
   "metadata": {},
   "outputs": [],
   "source": [
    "dams.to_file(output_folder / f'{city.lower()}_dams.shp')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "c3c3b70a-6b7c-412a-b703-f57a232298aa",
   "metadata": {},
   "outputs": [],
   "source": [
    "# filter for reservoirs in AOI\n",
    "reservoirs_list = []\n",
    "\n",
    "for i in range(len(aoi)):\n",
    "    reservoirs_list.append(reservoir_data.loc[reservoir_data.within(aoi.loc[i, 'geometry'])])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "aefc583c-6804-4304-b890-90dd1af2ad5b",
   "metadata": {},
   "outputs": [],
   "source": [
    "reservoirs = pd.concat(reservoirs_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "5058abf7-994f-44b2-b1e3-c3effc32dde4",
   "metadata": {},
   "outputs": [],
   "source": [
    "reservoirs.to_file(output_folder / f'{city.lower()}_reservoirs.shp')"
   ]
  }
 ],
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  "kernelspec": {
   "display_name": "crp",
   "language": "python",
   "name": "crp"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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