SEN-Transport_flooding-pre-project-scenario_2022-01-07.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Network analysis in Senegal\n",
    "\n",
    "### Objectives\n",
    "    1)\tUse measures of road-based accessibility to identify road segments that, if rehabilitated, would improve agricultural market activities in Senegal, including during flood conditions.\n",
    "    2)\tGain a better understanding of the accessibility, connectivity, and criticality of roads in Senegal in relationship to agricultural origins, processing & transfer sites, and markets.\n",
    "\n",
    "To this end, the team will develop an accessibility model which measures the travel time from sites of agricultural production to their nearest populated areas, processing centers, and markets. \n",
    "\n",
    "### Datasets for analysis\n",
    "#### ORIGIN\n",
    "    1) agriculture: MapSPAM 2017. Measuring value in international dollars.\n",
    "    2) agriculture: UMD Land Cover 2019 30m. Assign MapSPAM value onto land cover cropland class for more precise origin information.\n",
    "    3) population: WorldPop 2020, UN-adjusted.\n",
    "    4) settlement extent: GRID3 2020.\n",
    "#### DESTINATION\n",
    "    4) markets: derived from WorldPop 2020 and GRID3 2020 urban clusters.\n",
    "    5) agricultural processing hubs: to be acquired.\n",
    "#### TRAVEL ROUTE\n",
    "    6) roads: OpenStreetMap, July 2021.\n",
    "    7) elevation: \n",
    "#### OBSTACLE\n",
    "    8) flood: FATHOM. 1-in-10, 20, and 50 year flood return periods. These are combined pluvial and fluvial (undefended) flood layers whereby whichever flood level was higher was retained.\n",
    "#### INTERVENTION\n",
    "    9) upcoming road projects: AGEROUTE interventions separate from the World Bank-financed project\n",
    "    10) targeted road projects: critical road segments identified by this accessibility model's baseline outputs\n",
    "\n",
    "\n",
    "### Model design\n",
    "#### Basic formula: \n",
    "    (a) Off-road driving time from origin to closest road node\n",
    "    +\n",
    "    (b) Driving time from road node in (a) to a destination (closeness measured by road segments speeds)\n",
    "\n",
    "#### Model origin & destination (OD) sets:\n",
    "    A)\tTravel time from an area that has agricultural value/potential to the nearest processing hub (if provided).\n",
    "    B)\tTravel time from an area that has agricultural value/potential to the nearest larger settlement, (“larger” settlement identified using a case-appropriate population metric to be determined).\n",
    "    C)\tTravel time from an area that has agricultural value/potential to the nearest market.\n",
    "    D)\tTravel time from all settlements to the nearest market.\n",
    "    E)\tTravel time from larger settlements to the nearest market.\n",
    "\n",
    "#### Before/after scenarios for each OD set:\n",
    "    1)\tPre-project, baseline weather: No inclement weather. Road network status as of November 2021.\n",
    "    2)\tPre-project, flood: 1-in-10, 1-in-20 and 1-in-50 year flood return period. Road network status as of November 2021.\n",
    "    3)\tPost-project, baseline weather: No inclement weather. Road network status if X number of critical road segments to high-value areas are protected (i.e., their travel times reduced).\n",
    "    4)\tPost-project, flood: 1-in-10 year flood return period. Road network status if X number of critical road segments to high-value areas are protected (i.e., their travel times reduced).\n",
    "\n",
    "#### Notes:\n",
    "    --Destinations are expected to be proximal to the road network, so no measure is taken between road and destination.\n",
    "    --All travel times will be assigned to each model variation’s point of origin; the aggregation up to admin areas is possible if desired.\n",
    "    --Obstacles & interventions modify the road segment speeds. Basic formula is then applied to the modified road network.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Prep workspace"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'C:\\\\Users\\\\wb527163\\\\GEO-Cdrive-Grace'"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import os, sys\n",
    "GISFolder = os.getcwd()\n",
    "GISFolder"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Note: needed to reinstall rtree due to geopandas import error. Did so in the console. \n",
    "# conda install -c conda-forge rtree=0.9.3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# load and filter osm network (step 1)\n",
    "import geopandas as gpd\n",
    "from geopandas import GeoDataFrame\n",
    "import pandas as pd\n",
    "import time\n",
    "sys.path.append(r\"C:\\Users\\wb527163\\.conda\\envs\\geo\\GOSTnets-master\")\n",
    "import GOSTnets as gn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "import networkx as nx\n",
    "import osmnx as ox\n",
    "import numpy as np\n",
    "import rasterio as rt\n",
    "import shapely\n",
    "from shapely.geometry import Point, box, Polygon\n",
    "from shapely.ops import unary_union, linemerge, transform\n",
    "from shapely.wkt import loads\n",
    "from shapely import wkt\n",
    "from shapely.geometry import LineString, MultiLineString, Point\n",
    "import peartree"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "#### Might not use these\n",
    "import fiona\n",
    "from osgeo import gdal\n",
    "import importlib\n",
    "import matplotlib.pyplot as plt\n",
    "import subprocess, glob"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "from GOSTnets import load_osm as losm\n",
    "import importlib"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'C:\\\\Users\\\\wb527163\\\\GEO-Cdrive-Grace\\\\SEN-Cdrive'"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pth = os.path.join(GISFolder, \"SEN-Cdrive\") # Personal folder system for running model.\n",
    "pth"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'C:\\\\Users\\\\wb527163\\\\GEO-Cdrive-Grace\\\\SEN-Cdrive\\\\outputs'"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "out_pth = os.path.join(GISFolder, \"SEN-Cdrive\\outputs\") # For storing intermediate outputs from the model.\n",
    "out_pth"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'R:\\\\SEN\\\\GEO'"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "team_pth = 'R:\\\\SEN\\\\GEO' # This is where the unmodified input data is stored. Finalized outputs also housed here.\n",
    "team_pth"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Prepare OSM driving network.\n",
    "Travel measured in length (meters)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Ensure all targeted roads are changed to tertiary. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'geopandas.geodataframe.GeoDataFrame'>\n",
      "RangeIndex: 1483825 entries, 0 to 1483824\n",
      "Data columns (total 4 columns):\n",
      " #   Column        Non-Null Count    Dtype   \n",
      "---  ------        --------------    -----   \n",
      " 0   PFU_1in10     1483825 non-null  float64 \n",
      " 1   Shape_Length  1483825 non-null  float64 \n",
      " 2   Shape_Area    1483825 non-null  float64 \n",
      " 3   geometry      1483825 non-null  geometry\n",
      "dtypes: float64(3), geometry(1)\n",
      "memory usage: 45.3 MB\n"
     ]
    }
   ],
   "source": [
    "flood10 = gpd.read_file(\"C:/Users/wb527163/GEO-Cdrive-Grace/SEN-Cdrive/scratch.gdb\", layer=\"PFU_1in10\")\n",
    "flood10.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "gTime = nx.read_gpickle(\"SEN-Cdrive/outputs/gTime_pre-project.pickle\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "edges = gn.edge_gdf_from_graph(gTime)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\wb527163\\.conda\\envs\\geo\\lib\\site-packages\\IPython\\core\\interactiveshell.py:3444: DtypeWarning: Columns (3) have mixed types.Specify dtype option on import or set low_memory=False.\n",
      "  exec(code_obj, self.user_global_ns, self.user_ns)\n",
      "C:\\Users\\wb527163\\.conda\\envs\\geo\\lib\\site-packages\\IPython\\core\\interactiveshell.py:3444: DtypeWarning: Columns (4,5,7,8,10,13,14,15,16,17,19) have mixed types.Specify dtype option on import or set low_memory=False.\n",
      "  exec(code_obj, self.user_global_ns, self.user_ns)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 2871182 entries, 0 to 2871181\n",
      "Data columns (total 7 columns):\n",
      " #   Column      Dtype  \n",
      "---  ------      -----  \n",
      " 0   Unnamed: 0  int64  \n",
      " 1   node_ID     int64  \n",
      " 2   highway     object \n",
      " 3   ref         object \n",
      " 4   y           float64\n",
      " 5   x           float64\n",
      " 6   geometry    object \n",
      "dtypes: float64(2), int64(2), object(3)\n",
      "memory usage: 153.3+ MB\n",
      "None\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 6203383 entries, 0 to 6203382\n",
      "Data columns (total 22 columns):\n",
      " #   Column      Dtype  \n",
      "---  ------      -----  \n",
      " 0   Unnamed: 0  int64  \n",
      " 1   stnode      int64  \n",
      " 2   endnode     int64  \n",
      " 3   length      float64\n",
      " 4   width       object \n",
      " 5   area        object \n",
      " 6   highway     object \n",
      " 7   ref         object \n",
      " 8   maxspeed    object \n",
      " 9   time        float64\n",
      " 10  name        object \n",
      " 11  mode        object \n",
      " 12  lanes       float64\n",
      " 13  tunnel      object \n",
      " 14  bridge      object \n",
      " 15  junction    object \n",
      " 16  landuse     object \n",
      " 17  access      object \n",
      " 18  osmid       int64  \n",
      " 19  service     object \n",
      " 20  oneway      bool   \n",
      " 21  geometry    object \n",
      "dtypes: bool(1), float64(3), int64(4), object(14)\n",
      "memory usage: 999.8+ MB\n",
      "None\n"
     ]
    }
   ],
   "source": [
    "nodes = os.path.join(out_pth, \"gTime_node_pre-project.csv\")\n",
    "nodes = pd.read_csv(nodes)\n",
    "print(nodes.info())\n",
    "print(edges.info())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Spatial join should be on projected GDFs.\n",
    "edges = edges.to_crs(\"EPSG:31028\")\n",
    "flood10 = flood10.to_crs(\"EPSG:31028\")\n",
    "edges.crs == flood10.crs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'geopandas.geodataframe.GeoDataFrame'>\n",
      "Int64Index: 6377044 entries, 0 to 6203382\n",
      "Data columns (total 26 columns):\n",
      " #   Column        Dtype   \n",
      "---  ------        -----   \n",
      " 0   stnode        int64   \n",
      " 1   endnode       int64   \n",
      " 2   mode          object  \n",
      " 3   width         object  \n",
      " 4   ref           object  \n",
      " 5   service       object  \n",
      " 6   junction      object  \n",
      " 7   bridge        object  \n",
      " 8   osmid         int64   \n",
      " 9   oneway        bool    \n",
      " 10  access        object  \n",
      " 11  tunnel        object  \n",
      " 12  Unnamed: 0    int64   \n",
      " 13  maxspeed      object  \n",
      " 14  length        float64 \n",
      " 15  highway       object  \n",
      " 16  name          object  \n",
      " 17  landuse       object  \n",
      " 18  area          object  \n",
      " 19  time          float64 \n",
      " 20  lanes         float64 \n",
      " 21  geometry      geometry\n",
      " 22  index_right   float64 \n",
      " 23  PFU_1in10     float64 \n",
      " 24  Shape_Length  float64 \n",
      " 25  Shape_Area    float64 \n",
      "dtypes: bool(1), float64(7), geometry(1), int64(4), object(13)\n",
      "memory usage: 1.2+ GB\n",
      "None\n",
      "             stnode     endnode   mode width    ref service junction bridge  \\\n",
      "0         358284990  5217543379  drive   NaN  D 523     NaN      NaN    NaN   \n",
      "1         358284990  1888282175  drive   NaN    NaN     NaN      NaN    NaN   \n",
      "2         358284990  5329792467  drive   NaN    NaN     NaN      NaN    NaN   \n",
      "3        5217543379   358284990  drive   NaN  D 523     NaN      NaN    NaN   \n",
      "4        5217543379  5329928981  drive   NaN  D 523     NaN      NaN    NaN   \n",
      "...             ...         ...    ...   ...    ...     ...      ...    ...   \n",
      "6203378  9165665162  9165665161  drive   NaN    NaN     NaN      NaN    NaN   \n",
      "6203379  9201905615  9201918817  drive   NaN    NaN     NaN      NaN    NaN   \n",
      "6203380  9201905615  9201918818  drive   NaN    NaN     NaN      NaN    NaN   \n",
      "6203381  9201918818  9201905615  drive   NaN    NaN     NaN      NaN    NaN   \n",
      "6203382  9201918818  9201905616  drive   NaN    NaN     NaN      NaN    yes   \n",
      "\n",
      "             osmid  oneway  ...   name landuse  area      time  lanes  \\\n",
      "0         59618174   False  ...  D 523     NaN   NaN  2.385144    NaN   \n",
      "1        178482063   False  ...    NaN     NaN   NaN  0.769920    NaN   \n",
      "2        178482063   False  ...    NaN     NaN   NaN  2.926860    NaN   \n",
      "3         59618174   False  ...  D 523     NaN   NaN  2.385144    NaN   \n",
      "4         59618174   False  ...  D 523     NaN   NaN  1.232928    NaN   \n",
      "...            ...     ...  ...    ...     ...   ...       ...    ...   \n",
      "6203378  992024621   False  ...    NaN     NaN   NaN  4.380800    NaN   \n",
      "6203379  996565464   False  ...    NaN     NaN   NaN  0.307620    NaN   \n",
      "6203380  996565464   False  ...    NaN     NaN   NaN  0.634050    NaN   \n",
      "6203381  996565464   False  ...    NaN     NaN   NaN  0.634050    NaN   \n",
      "6203382  996565465   False  ...    NaN     NaN   NaN  1.282950    NaN   \n",
      "\n",
      "                                                  geometry index_right  \\\n",
      "0        LINESTRING (790871.607 1370083.257, 790848.290...         NaN   \n",
      "1        LINESTRING (790871.607 1370083.257, 790867.287...         NaN   \n",
      "2        LINESTRING (790871.607 1370083.257, 790904.086...         NaN   \n",
      "3        LINESTRING (790848.290 1370106.724, 790871.607...         NaN   \n",
      "4        LINESTRING (790848.290 1370106.724, 790838.054...         NaN   \n",
      "...                                                    ...         ...   \n",
      "6203378  LINESTRING (232312.244 1631600.542, 232307.060...         NaN   \n",
      "6203379  LINESTRING (231437.078 1630744.554, 231433.991...         NaN   \n",
      "6203380  LINESTRING (231437.078 1630744.554, 231442.229...         NaN   \n",
      "6203381  LINESTRING (231442.229 1630739.759, 231437.078...         NaN   \n",
      "6203382  LINESTRING (231442.229 1630739.759, 231444.822...         NaN   \n",
      "\n",
      "        PFU_1in10 Shape_Length  Shape_Area  \n",
      "0             NaN          NaN         NaN  \n",
      "1             NaN          NaN         NaN  \n",
      "2             NaN          NaN         NaN  \n",
      "3             NaN          NaN         NaN  \n",
      "4             NaN          NaN         NaN  \n",
      "...           ...          ...         ...  \n",
      "6203378       NaN          NaN         NaN  \n",
      "6203379       NaN          NaN         NaN  \n",
      "6203380       NaN          NaN         NaN  \n",
      "6203381       NaN          NaN         NaN  \n",
      "6203382       NaN          NaN         NaN  \n",
      "\n",
      "[6377044 rows x 26 columns]\n"
     ]
    }
   ],
   "source": [
    "floodjoin = gpd.sjoin_nearest(edges, flood10, how=\"left\", max_distance=3) \n",
    "print(floodjoin.info())\n",
    "print(floodjoin)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "No flood crossing at node: 5919815 locations\n",
      "\n",
      "Flood crossing at node: 457229 locations\n",
      "\n",
      "\n",
      "Percent flooded: 7.169920734434323 percent out of 6377044 possible locations\n"
     ]
    }
   ],
   "source": [
    "# How many nodes experienced flooding?\n",
    "pc_flooded = floodjoin[\"PFU_1in10\"].count() / len(floodjoin) * 100\n",
    "\n",
    "print(\"No flood crossing at node:\", floodjoin[\"PFU_1in10\"].isnull().sum(), \"locations\", end=\"\\n\\n\")\n",
    "print(\"Flood crossing at node:\", floodjoin[\"PFU_1in10\"].count(), \"locations\", end=\"\\n\\n\")\n",
    "print(\"\\nPercent flooded:\", pc_flooded, \"percent\", \"out of\", len(floodjoin), \"possible locations\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'geopandas.geodataframe.GeoDataFrame'>\n",
      "Int64Index: 6377044 entries, 0 to 6203382\n",
      "Data columns (total 8 columns):\n",
      " #   Column     Dtype   \n",
      "---  ------     -----   \n",
      " 0   stnode     int64   \n",
      " 1   endnode    int64   \n",
      " 2   time       float64 \n",
      " 3   length     float64 \n",
      " 4   highway    object  \n",
      " 5   osmid      int64   \n",
      " 6   geometry   geometry\n",
      " 7   PFU_1in10  float64 \n",
      "dtypes: float64(3), geometry(1), int64(3), object(1)\n",
      "memory usage: 437.9+ MB\n"
     ]
    }
   ],
   "source": [
    "floodjoin = floodjoin[['stnode', 'endnode', 'time', 'length', 'highway', 'osmid', 'geometry', 'PFU_1in10']]\n",
    "floodjoin = floodjoin.to_crs(\"EPSG:4326\")\n",
    "floodjoin.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Fewer errors farther down when using dataframe instead of gdf\n",
    "floodjoin = pd.DataFrame(floodjoin)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Save progress.\n",
    "floodjoin.to_csv(os.path.join(out_pth, 'gTime_edge_pre-project_flood10.csv'))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Create speed penalties.\n",
    "Note: Flood depths are in centimeters. FATHOM uses meters, but conversion process to vector required some finessing. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "floodjoin = os.path.join(out_pth, \"gTime_edge_pre-project_flood10.csv\")\n",
    "floodjoin = pd.read_csv(floodjoin)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>stnode</th>\n",
       "      <th>endnode</th>\n",
       "      <th>time</th>\n",
       "      <th>length</th>\n",
       "      <th>highway</th>\n",
       "      <th>osmid</th>\n",
       "      <th>geometry</th>\n",
       "      <th>PFU_1in10</th>\n",
       "      <th>t10</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>358284990</td>\n",
       "      <td>5217543379</td>\n",
       "      <td>2.385144</td>\n",
       "      <td>33.127</td>\n",
       "      <td>unclassified</td>\n",
       "      <td>59618174</td>\n",
       "      <td>LINESTRING (-12.323470812149301 12.38118950295...</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>358284990</td>\n",
       "      <td>1888282175</td>\n",
       "      <td>0.769920</td>\n",
       "      <td>12.832</td>\n",
       "      <td>tertiary</td>\n",
       "      <td>178482063</td>\n",
       "      <td>LINESTRING (-12.323470812149301 12.38118950295...</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>358284990</td>\n",
       "      <td>5329792467</td>\n",
       "      <td>2.926860</td>\n",
       "      <td>48.781</td>\n",
       "      <td>tertiary</td>\n",
       "      <td>178482063</td>\n",
       "      <td>LINESTRING (-12.323470812149301 12.38118950295...</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>5217543379</td>\n",
       "      <td>358284990</td>\n",
       "      <td>2.385144</td>\n",
       "      <td>33.127</td>\n",
       "      <td>unclassified</td>\n",
       "      <td>59618174</td>\n",
       "      <td>LINESTRING (-12.323682912149085 12.38140360295...</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>5217543379</td>\n",
       "      <td>5329928981</td>\n",
       "      <td>1.232928</td>\n",
       "      <td>17.124</td>\n",
       "      <td>unclassified</td>\n",
       "      <td>59618174</td>\n",
       "      <td>LINESTRING (-12.323682912149085 12.38140360295...</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6377039</th>\n",
       "      <td>6203378</td>\n",
       "      <td>9165665162</td>\n",
       "      <td>9165665161</td>\n",
       "      <td>4.380800</td>\n",
       "      <td>5.476</td>\n",
       "      <td>path</td>\n",
       "      <td>992024621</td>\n",
       "      <td>LINESTRING (-17.484701707370633 14.74572550266...</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6377040</th>\n",
       "      <td>6203379</td>\n",
       "      <td>9201905615</td>\n",
       "      <td>9201918817</td>\n",
       "      <td>0.307620</td>\n",
       "      <td>3.418</td>\n",
       "      <td>residential</td>\n",
       "      <td>996565464</td>\n",
       "      <td>LINESTRING (-17.492736907366183 14.73790610266...</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6377041</th>\n",
       "      <td>6203380</td>\n",
       "      <td>9201905615</td>\n",
       "      <td>9201918818</td>\n",
       "      <td>0.634050</td>\n",
       "      <td>7.045</td>\n",
       "      <td>residential</td>\n",
       "      <td>996565464</td>\n",
       "      <td>LINESTRING (-17.492736907366183 14.73790610266...</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6377042</th>\n",
       "      <td>6203381</td>\n",
       "      <td>9201918818</td>\n",
       "      <td>9201905615</td>\n",
       "      <td>0.634050</td>\n",
       "      <td>7.045</td>\n",
       "      <td>residential</td>\n",
       "      <td>996565464</td>\n",
       "      <td>LINESTRING (-17.492688607366233 14.73786330266...</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6377043</th>\n",
       "      <td>6203382</td>\n",
       "      <td>9201918818</td>\n",
       "      <td>9201905616</td>\n",
       "      <td>1.282950</td>\n",
       "      <td>14.255</td>\n",
       "      <td>residential</td>\n",
       "      <td>996565465</td>\n",
       "      <td>LINESTRING (-17.492688607366233 14.73786330266...</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>6377044 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         Unnamed: 0      stnode     endnode      time  length       highway  \\\n",
       "0                 0   358284990  5217543379  2.385144  33.127  unclassified   \n",
       "1                 1   358284990  1888282175  0.769920  12.832      tertiary   \n",
       "2                 2   358284990  5329792467  2.926860  48.781      tertiary   \n",
       "3                 3  5217543379   358284990  2.385144  33.127  unclassified   \n",
       "4                 4  5217543379  5329928981  1.232928  17.124  unclassified   \n",
       "...             ...         ...         ...       ...     ...           ...   \n",
       "6377039     6203378  9165665162  9165665161  4.380800   5.476          path   \n",
       "6377040     6203379  9201905615  9201918817  0.307620   3.418   residential   \n",
       "6377041     6203380  9201905615  9201918818  0.634050   7.045   residential   \n",
       "6377042     6203381  9201918818  9201905615  0.634050   7.045   residential   \n",
       "6377043     6203382  9201918818  9201905616  1.282950  14.255   residential   \n",
       "\n",
       "             osmid                                           geometry  \\\n",
       "0         59618174  LINESTRING (-12.323470812149301 12.38118950295...   \n",
       "1        178482063  LINESTRING (-12.323470812149301 12.38118950295...   \n",
       "2        178482063  LINESTRING (-12.323470812149301 12.38118950295...   \n",
       "3         59618174  LINESTRING (-12.323682912149085 12.38140360295...   \n",
       "4         59618174  LINESTRING (-12.323682912149085 12.38140360295...   \n",
       "...            ...                                                ...   \n",
       "6377039  992024621  LINESTRING (-17.484701707370633 14.74572550266...   \n",
       "6377040  996565464  LINESTRING (-17.492736907366183 14.73790610266...   \n",
       "6377041  996565464  LINESTRING (-17.492736907366183 14.73790610266...   \n",
       "6377042  996565464  LINESTRING (-17.492688607366233 14.73786330266...   \n",
       "6377043  996565465  LINESTRING (-17.492688607366233 14.73786330266...   \n",
       "\n",
       "         PFU_1in10  t10  \n",
       "0             -1.0  1.0  \n",
       "1             -1.0  1.0  \n",
       "2             -1.0  1.0  \n",
       "3             -1.0  1.0  \n",
       "4             -1.0  1.0  \n",
       "...            ...  ...  \n",
       "6377039       -1.0  1.0  \n",
       "6377040       -1.0  1.0  \n",
       "6377041       -1.0  1.0  \n",
       "6377042       -1.0  1.0  \n",
       "6377043       -1.0  1.0  \n",
       "\n",
       "[6377044 rows x 10 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Give a depth to the nodes that don't cross a flood point. \n",
    "floodjoin.loc[floodjoin['PFU_1in10'].isnull(), 'PFU_1in10'] = -1\n",
    "floodjoin[\"t10\"] = 1 # This is the penalty column.\n",
    "floodjoin.loc[floodjoin['PFU_1in10'] <= 5, 't10'] = 1 # Where no flood crosses, keep the default value (no penalty).\n",
    "floodjoin.loc[(floodjoin['PFU_1in10'] > 5) & (floodjoin['PFU_1in10'] <= 10), 't10'] = 1.25 # Between 10-30cm flooding, increase travel time by 1.25.\n",
    "floodjoin.loc[(floodjoin['PFU_1in10'] > 10) & (floodjoin['PFU_1in10'] <= 15), 't10'] = 2\n",
    "floodjoin.loc[(floodjoin['PFU_1in10'] > 15) & (floodjoin['PFU_1in10'] <= 40), 't10'] = 5\n",
    "floodjoin.loc[(floodjoin['PFU_1in10'] > 40), 't10'] = 9999\n",
    "floodjoin"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>2</th>\n",
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       "      <td>358284990</td>\n",
       "      <td>5329792467</td>\n",
       "      <td>2.926860</td>\n",
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       "      <td>2.926860</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
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       "      <td>5217543379</td>\n",
       "      <td>358284990</td>\n",
       "      <td>2.385144</td>\n",
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       "      <td>unclassified</td>\n",
       "      <td>59618174</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>5217543379</td>\n",
       "      <td>5329928981</td>\n",
       "      <td>1.232928</td>\n",
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       "      <td>unclassified</td>\n",
       "      <td>59618174</td>\n",
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       "      <th>...</th>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>6377039</th>\n",
       "      <td>6203378</td>\n",
       "      <td>9165665162</td>\n",
       "      <td>9165665161</td>\n",
       "      <td>4.380800</td>\n",
       "      <td>5.476</td>\n",
       "      <td>path</td>\n",
       "      <td>992024621</td>\n",
       "      <td>LINESTRING (-17.484701707370633 14.74572550266...</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>4.380800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6377040</th>\n",
       "      <td>6203379</td>\n",
       "      <td>9201905615</td>\n",
       "      <td>9201918817</td>\n",
       "      <td>0.307620</td>\n",
       "      <td>3.418</td>\n",
       "      <td>residential</td>\n",
       "      <td>996565464</td>\n",
       "      <td>LINESTRING (-17.492736907366183 14.73790610266...</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>0.307620</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6377041</th>\n",
       "      <td>6203380</td>\n",
       "      <td>9201905615</td>\n",
       "      <td>9201918818</td>\n",
       "      <td>0.634050</td>\n",
       "      <td>7.045</td>\n",
       "      <td>residential</td>\n",
       "      <td>996565464</td>\n",
       "      <td>LINESTRING (-17.492736907366183 14.73790610266...</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>0.634050</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6377042</th>\n",
       "      <td>6203381</td>\n",
       "      <td>9201918818</td>\n",
       "      <td>9201905615</td>\n",
       "      <td>0.634050</td>\n",
       "      <td>7.045</td>\n",
       "      <td>residential</td>\n",
       "      <td>996565464</td>\n",
       "      <td>LINESTRING (-17.492688607366233 14.73786330266...</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>0.634050</td>\n",
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       "    <tr>\n",
       "      <th>6377043</th>\n",
       "      <td>6203382</td>\n",
       "      <td>9201918818</td>\n",
       "      <td>9201905616</td>\n",
       "      <td>1.282950</td>\n",
       "      <td>14.255</td>\n",
       "      <td>residential</td>\n",
       "      <td>996565465</td>\n",
       "      <td>LINESTRING (-17.492688607366233 14.73786330266...</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>1.282950</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>6377044 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         Unnamed: 0      stnode     endnode      time  length       highway  \\\n",
       "0                 0   358284990  5217543379  2.385144  33.127  unclassified   \n",
       "1                 1   358284990  1888282175  0.769920  12.832      tertiary   \n",
       "2                 2   358284990  5329792467  2.926860  48.781      tertiary   \n",
       "3                 3  5217543379   358284990  2.385144  33.127  unclassified   \n",
       "4                 4  5217543379  5329928981  1.232928  17.124  unclassified   \n",
       "...             ...         ...         ...       ...     ...           ...   \n",
       "6377039     6203378  9165665162  9165665161  4.380800   5.476          path   \n",
       "6377040     6203379  9201905615  9201918817  0.307620   3.418   residential   \n",
       "6377041     6203380  9201905615  9201918818  0.634050   7.045   residential   \n",
       "6377042     6203381  9201918818  9201905615  0.634050   7.045   residential   \n",
       "6377043     6203382  9201918818  9201905616  1.282950  14.255   residential   \n",
       "\n",
       "             osmid                                           geometry  \\\n",
       "0         59618174  LINESTRING (-12.323470812149301 12.38118950295...   \n",
       "1        178482063  LINESTRING (-12.323470812149301 12.38118950295...   \n",
       "2        178482063  LINESTRING (-12.323470812149301 12.38118950295...   \n",
       "3         59618174  LINESTRING (-12.323682912149085 12.38140360295...   \n",
       "4         59618174  LINESTRING (-12.323682912149085 12.38140360295...   \n",
       "...            ...                                                ...   \n",
       "6377039  992024621  LINESTRING (-17.484701707370633 14.74572550266...   \n",
       "6377040  996565464  LINESTRING (-17.492736907366183 14.73790610266...   \n",
       "6377041  996565464  LINESTRING (-17.492736907366183 14.73790610266...   \n",
       "6377042  996565464  LINESTRING (-17.492688607366233 14.73786330266...   \n",
       "6377043  996565465  LINESTRING (-17.492688607366233 14.73786330266...   \n",
       "\n",
       "         PFU_1in10       t10  \n",
       "0             -1.0  2.385144  \n",
       "1             -1.0  0.769920  \n",
       "2             -1.0  2.926860  \n",
       "3             -1.0  2.385144  \n",
       "4             -1.0  1.232928  \n",
       "...            ...       ...  \n",
       "6377039       -1.0  4.380800  \n",
       "6377040       -1.0  0.307620  \n",
       "6377041       -1.0  0.634050  \n",
       "6377042       -1.0  0.634050  \n",
       "6377043       -1.0  1.282950  \n",
       "\n",
       "[6377044 rows x 10 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Turn the penalty column into a flood-affected time column.\n",
    "floodjoin['t10'] = floodjoin['t10'] * floodjoin['time']\n",
    "floodjoin"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Save progress.\n",
    "floodjoin.to_csv(os.path.join(out_pth, 'gTime_edge_pre-project_flood10.csv'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Travel time without inclement weather\n",
      "\n",
      "Mean: 7.078734295815471\n",
      "Median: 3.21903\n",
      "\n",
      "\n",
      "\n",
      "During 1 in 10-year flood conditions\n",
      "\n",
      "Mean: 3770.8335061007824\n",
      "Median: 3.37932\n"
     ]
    }
   ],
   "source": [
    "print(\"Travel time without inclement weather\\n\")\n",
    "print(\"Mean:\", floodjoin['time'].mean(), end=\"\\n\")\n",
    "print(\"Median:\", floodjoin['time'].median(), end='\\n\\n')\n",
    "print(\"\\n\\nDuring 1 in 10-year flood conditions\\n\")\n",
    "print(\"Mean:\", floodjoin['t10'].mean(), end=\"\\n\") \n",
    "print(\"Median:\", floodjoin['t10'].median()) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Convert back to graph object."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\wb527163\\.conda\\envs\\geo\\lib\\site-packages\\IPython\\core\\interactiveshell.py:3444: DtypeWarning: Columns (3) have mixed types.Specify dtype option on import or set low_memory=False.\n",
      "  exec(code_obj, self.user_global_ns, self.user_ns)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 2871182 entries, 0 to 2871181\n",
      "Data columns (total 7 columns):\n",
      " #   Column      Dtype  \n",
      "---  ------      -----  \n",
      " 0   Unnamed: 0  int64  \n",
      " 1   node_ID     int64  \n",
      " 2   highway     object \n",
      " 3   ref         object \n",
      " 4   y           float64\n",
      " 5   x           float64\n",
      " 6   geometry    object \n",
      "dtypes: float64(2), int64(2), object(3)\n",
      "memory usage: 153.3+ MB\n",
      "None\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 6377044 entries, 0 to 6377043\n",
      "Data columns (total 11 columns):\n",
      " #   Column        Dtype  \n",
      "---  ------        -----  \n",
      " 0   Unnamed: 0    int64  \n",
      " 1   Unnamed: 0.1  int64  \n",
      " 2   stnode        int64  \n",
      " 3   endnode       int64  \n",
      " 4   time          float64\n",
      " 5   length        float64\n",
      " 6   highway       object \n",
      " 7   osmid         int64  \n",
      " 8   geometry      object \n",
      " 9   PFU_1in10     float64\n",
      " 10  t10           float64\n",
      "dtypes: float64(4), int64(5), object(2)\n",
      "memory usage: 535.2+ MB\n",
      "None\n"
     ]
    }
   ],
   "source": [
    "# Converting back to graph can cause memory errors. Suggested to restart the kernel and reload the nodes and revised edges at this point.\n",
    "nodes = os.path.join(out_pth, \"gTime_node_pre-project.csv\")\n",
    "nodes = pd.read_csv(nodes)\n",
    "floodjoin = os.path.join(out_pth, \"gTime_edge_pre-project_flood10.csv\")\n",
    "floodjoin = pd.read_csv(floodjoin)\n",
    "print(nodes.info())\n",
    "print(floodjoin.info())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "start: Fri Jan  7 17:04:07 2022\n",
      "\n",
      "(358284990, 5217543379, {'geometry': <shapely.geometry.linestring.LineString object at 0x000001FFA02FDA60>, 'Unnamed: 0': 0, 'Unnamed: 0.1': 0, 'time': 2.3851440000000004, 'length': 33.127, 'highway': 'unclassified', 'osmid': 59618174, 'PFU_1in10': -1.0, 't10': 2.3851440000000004})\n",
      "(358284990, 1888282175, {'geometry': <shapely.geometry.linestring.LineString object at 0x00000200059C2A60>, 'Unnamed: 0': 1, 'Unnamed: 0.1': 1, 'time': 0.76992, 'length': 12.832, 'highway': 'tertiary', 'osmid': 178482063, 'PFU_1in10': -1.0, 't10': 0.76992})\n",
      "(358284990, 5329792467, {'geometry': <shapely.geometry.linestring.LineString object at 0x000001FFA6E602B0>, 'Unnamed: 0': 2, 'Unnamed: 0.1': 2, 'time': 2.92686, 'length': 48.781, 'highway': 'tertiary', 'osmid': 178482063, 'PFU_1in10': -1.0, 't10': 2.92686})\n",
      "(5217543379, 358284990, {'geometry': <shapely.geometry.linestring.LineString object at 0x000001FFA81DCBE0>, 'Unnamed: 0': 3, 'Unnamed: 0.1': 3, 'time': 2.3851440000000004, 'length': 33.127, 'highway': 'unclassified', 'osmid': 59618174, 'PFU_1in10': -1.0, 't10': 2.3851440000000004})\n",
      "(5217543379, 5329928981, {'geometry': <shapely.geometry.linestring.LineString object at 0x000001FFA81DC640>, 'Unnamed: 0': 4, 'Unnamed: 0.1': 4, 'time': 1.232928, 'length': 17.124, 'highway': 'unclassified', 'osmid': 59618174, 'PFU_1in10': -1.0, 't10': 1.232928})\n",
      "(1888282175, 1888282174, {'geometry': <shapely.geometry.linestring.LineString object at 0x000001FFA81DCF70>, 'Unnamed: 0': 5, 'Unnamed: 0.1': 5, 'time': 0.9322200000000002, 'length': 15.537, 'highway': 'tertiary', 'osmid': 178482063, 'PFU_1in10': -1.0, 't10': 0.9322200000000002})\n",
      "(1888282175, 358284990, {'geometry': <shapely.geometry.linestring.LineString object at 0x000001FFA81DCEE0>, 'Unnamed: 0': 6, 'Unnamed: 0.1': 6, 'time': 0.76992, 'length': 12.832, 'highway': 'tertiary', 'osmid': 178482063, 'PFU_1in10': -1.0, 't10': 0.76992})\n",
      "(5329792467, 358284990, {'geometry': <shapely.geometry.linestring.LineString object at 0x000001FFA81DCEB0>, 'Unnamed: 0': 7, 'Unnamed: 0.1': 7, 'time': 2.92686, 'length': 48.781, 'highway': 'tertiary', 'osmid': 178482063, 'PFU_1in10': -1.0, 't10': 2.92686})\n",
      "(5329792467, 1888282177, {'geometry': <shapely.geometry.linestring.LineString object at 0x000001FFA81DC880>, 'Unnamed: 0': 8, 'Unnamed: 0.1': 8, 'time': 2.7629999999999995, 'length': 46.05, 'highway': 'tertiary', 'osmid': 178482063, 'PFU_1in10': -1.0, 't10': 2.7629999999999995})\n",
      "(5329928981, 5217543379, {'geometry': <shapely.geometry.linestring.LineString object at 0x0000020028726160>, 'Unnamed: 0': 32584, 'Unnamed: 0.1': 32553, 'time': 1.232928, 'length': 17.124, 'highway': 'unclassified', 'osmid': 59618174, 'PFU_1in10': -1.0, 't10': 1.232928})\n",
      "\n",
      "end: Fri Jan  7 17:18:26 2022\n",
      "\n",
      "--- processing complete\n"
     ]
    }
   ],
   "source": [
    "print('start: %s\\n' % time.ctime())\n",
    "gTime = gn.edges_and_nodes_gdf_to_graph(nodes, floodjoin, node_tag='node_ID', u_tag='stnode', v_tag='endnode', geometry_tag='geometry')\n",
    "gn.example_edge(gTime, 10)\n",
    "print('\\nend: %s' % time.ctime())\n",
    "print('\\n--- processing complete')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "start: Fri Jan  7 17:18:26 2022\n",
      "\n",
      "\n",
      "end: Fri Jan  7 17:21:08 2022\n",
      "\n",
      "--- processing complete\n"
     ]
    }
   ],
   "source": [
    "print('start: %s\\n' % time.ctime())\n",
    "gn.save(gTime, 'gTime_pre-project_flood10', out_pth, edges = False, nodes = False)\n",
    "print('\\nend: %s' % time.ctime())\n",
    "print('\\n--- processing complete')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Create travel time values for the road nodes nearest to each service.\n",
    "\n",
    "Using calculate_OD.\n",
    "\n",
    "Already measured distance from origin/destination to nearest node in pre-project script."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "#%% If starting new session, reload graph from file\n",
    "gTime = nx.read_gpickle(\"SEN-Cdrive/outputs/gTime_pre-project_flood10.pickle\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# If starting a new session, load from file.\n",
    "HDurban_snap = os.path.join(out_pth, \"HDurban_snap.csv\")\n",
    "HDurban_snap = pd.read_csv(HDurban_snap)\n",
    "hamlet_snap = os.path.join(out_pth, \"hamlet_snap.csv\")\n",
    "hamlet_snap = pd.read_csv(hamlet_snap)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "ag_snap = os.path.join(out_pth, \"ag_snap.csv\")\n",
    "ag_snap = pd.read_csv(ag_snap)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
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       "      <td>0.000000</td>\n",
       "      <td>4601.126349</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.494002</td>\n",
       "      <td>1.754369e-03</td>\n",
       "      <td>POINT (-16.22513510721168 15.620904283746231)</td>\n",
       "      <td>1983641803</td>\n",
       "      <td>29.090625</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>14</td>\n",
       "      <td>160</td>\n",
       "      <td>28PCU6286_04</td>\n",
       "      <td>hamlet</td>\n",
       "      <td>0.105280</td>\n",
       "      <td>2.093665e+02</td>\n",
       "      <td>5.479664</td>\n",
       "      <td>6852.183502</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.021230</td>\n",
       "      <td>8.758142e-06</td>\n",
       "      <td>POINT (-16.264484462734323 12.537366413261045)</td>\n",
       "      <td>6014451367</td>\n",
       "      <td>61.273348</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>15</td>\n",
       "      <td>168</td>\n",
       "      <td>28PEV0425_03</td>\n",
       "      <td>hamlet</td>\n",
       "      <td>0.164601</td>\n",
       "      <td>2.503226e+02</td>\n",
       "      <td>5.371455</td>\n",
       "      <td>4124.872441</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.019495</td>\n",
       "      <td>1.371013e-05</td>\n",
       "      <td>POINT (-14.961042651677891 12.895762457094666)</td>\n",
       "      <td>6027163276</td>\n",
       "      <td>23.270139</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>16</td>\n",
       "      <td>173</td>\n",
       "      <td>28PFA4321_01</td>\n",
       "      <td>hamlet</td>\n",
       "      <td>0.036757</td>\n",
       "      <td>5.002239e+01</td>\n",
       "      <td>3.131679</td>\n",
       "      <td>4478.321578</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.006776</td>\n",
       "      <td>3.072012e-06</td>\n",
       "      <td>POINT (-13.668587614564068 13.755222178122034)</td>\n",
       "      <td>2833577858</td>\n",
       "      <td>216.111092</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>17</td>\n",
       "      <td>174</td>\n",
       "      <td>28PBA9292_06</td>\n",
       "      <td>hamlet</td>\n",
       "      <td>0.023177</td>\n",
       "      <td>1.846325e+01</td>\n",
       "      <td>13.239334</td>\n",
       "      <td>4163.686114</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.005371</td>\n",
       "      <td>1.942589e-06</td>\n",
       "      <td>POINT (-16.927480646349732 14.39849858186184)</td>\n",
       "      <td>7321088861</td>\n",
       "      <td>126.948072</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>18</td>\n",
       "      <td>175</td>\n",
       "      <td>28PBA8299_01</td>\n",
       "      <td>hamlet</td>\n",
       "      <td>0.013923</td>\n",
       "      <td>1.655101e+01</td>\n",
       "      <td>4.715519</td>\n",
       "      <td>4163.686114</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.004799</td>\n",
       "      <td>1.167113e-06</td>\n",
       "      <td>POINT (-17.016066265874734 14.460756350154803)</td>\n",
       "      <td>6045659373</td>\n",
       "      <td>27.871739</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>19</td>\n",
       "      <td>176</td>\n",
       "      <td>28PBB7801_01</td>\n",
       "      <td>hamlet</td>\n",
       "      <td>0.017578</td>\n",
       "      <td>3.044826e+01</td>\n",
       "      <td>11.659853</td>\n",
       "      <td>4163.686114</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.004813</td>\n",
       "      <td>1.473665e-06</td>\n",
       "      <td>POINT (-17.055862944965526 14.477635627799748)</td>\n",
       "      <td>5528866190</td>\n",
       "      <td>64.826632</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>20</td>\n",
       "      <td>177</td>\n",
       "      <td>28PBB8202_01</td>\n",
       "      <td>hamlet</td>\n",
       "      <td>0.033487</td>\n",
       "      <td>3.486522e+01</td>\n",
       "      <td>7.892879</td>\n",
       "      <td>4163.686114</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.008101</td>\n",
       "      <td>2.807464e-06</td>\n",
       "      <td>POINT (-17.018846969475057 14.483053711062894)</td>\n",
       "      <td>6027939517</td>\n",
       "      <td>24.581971</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>21</td>\n",
       "      <td>178</td>\n",
       "      <td>28PBB7902_04</td>\n",
       "      <td>hamlet</td>\n",
       "      <td>0.188962</td>\n",
       "      <td>2.698936e+02</td>\n",
       "      <td>9.563365</td>\n",
       "      <td>4163.686114</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.030043</td>\n",
       "      <td>1.584495e-05</td>\n",
       "      <td>POINT (-17.042492216832404 14.48472898603413)</td>\n",
       "      <td>6031093257</td>\n",
       "      <td>273.489784</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>22</td>\n",
       "      <td>179</td>\n",
       "      <td>28PBB8103_02</td>\n",
       "      <td>hamlet</td>\n",
       "      <td>0.152780</td>\n",
       "      <td>2.366904e+02</td>\n",
       "      <td>9.538024</td>\n",
       "      <td>4163.686114</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.029995</td>\n",
       "      <td>1.281388e-05</td>\n",
       "      <td>POINT (-17.026406509846662 14.49188592573409)</td>\n",
       "      <td>1883155712</td>\n",
       "      <td>129.540762</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>23</td>\n",
       "      <td>182</td>\n",
       "      <td>28PCA7866_01</td>\n",
       "      <td>hamlet</td>\n",
       "      <td>0.009282</td>\n",
       "      <td>1.921189e+01</td>\n",
       "      <td>8.378629</td>\n",
       "      <td>6539.609258</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.003274</td>\n",
       "      <td>7.770706e-07</td>\n",
       "      <td>POINT (-16.12870301954371 14.163238160099032)</td>\n",
       "      <td>6026417971</td>\n",
       "      <td>287.396023</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>24</td>\n",
       "      <td>184</td>\n",
       "      <td>28PCA8268_03</td>\n",
       "      <td>hamlet</td>\n",
       "      <td>0.026723</td>\n",
       "      <td>3.108315e+01</td>\n",
       "      <td>5.292360</td>\n",
       "      <td>6539.609258</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.006861</td>\n",
       "      <td>2.237697e-06</td>\n",
       "      <td>POINT (-16.090276652783288 14.185562094447294)</td>\n",
       "      <td>6031245697</td>\n",
       "      <td>49.284838</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>25</td>\n",
       "      <td>197</td>\n",
       "      <td>28PBB3031_01</td>\n",
       "      <td>hamlet</td>\n",
       "      <td>0.036793</td>\n",
       "      <td>2.190752e+02</td>\n",
       "      <td>15.925017</td>\n",
       "      <td>16035.762110</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.007562</td>\n",
       "      <td>3.088678e-06</td>\n",
       "      <td>POINT (-17.503912092775586 14.746318221560271)</td>\n",
       "      <td>7493947593</td>\n",
       "      <td>15.922254</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>26</td>\n",
       "      <td>199</td>\n",
       "      <td>28PBB9431_01</td>\n",
       "      <td>hamlet</td>\n",
       "      <td>0.017802</td>\n",
       "      <td>3.757302e+01</td>\n",
       "      <td>6.049956</td>\n",
       "      <td>5446.539082</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.004718</td>\n",
       "      <td>1.494350e-06</td>\n",
       "      <td>POINT (-16.909081994152583 14.746958369151947)</td>\n",
       "      <td>1859359090</td>\n",
       "      <td>107.065710</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>27</td>\n",
       "      <td>201</td>\n",
       "      <td>28PBB5833_07</td>\n",
       "      <td>hamlet</td>\n",
       "      <td>0.044133</td>\n",
       "      <td>6.815012e+01</td>\n",
       "      <td>15.771149</td>\n",
       "      <td>16035.762110</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.008892</td>\n",
       "      <td>3.704665e-06</td>\n",
       "      <td>POINT (-17.23995849720513 14.767547644151895)</td>\n",
       "      <td>6053816462</td>\n",
       "      <td>52.284317</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>28</td>\n",
       "      <td>202</td>\n",
       "      <td>28PBB5934_01</td>\n",
       "      <td>hamlet</td>\n",
       "      <td>0.067703</td>\n",
       "      <td>6.689919e+01</td>\n",
       "      <td>16.463440</td>\n",
       "      <td>16035.762110</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.012549</td>\n",
       "      <td>5.684528e-06</td>\n",
       "      <td>POINT (-17.23391993155635 14.77602519637424)</td>\n",
       "      <td>6027530676</td>\n",
       "      <td>16.433933</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>29</td>\n",
       "      <td>203</td>\n",
       "      <td>28PBB7434_03</td>\n",
       "      <td>hamlet</td>\n",
       "      <td>0.024692</td>\n",
       "      <td>6.194532e+01</td>\n",
       "      <td>8.691752</td>\n",
       "      <td>2999.449116</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.005714</td>\n",
       "      <td>2.072792e-06</td>\n",
       "      <td>POINT (-17.098633451710782 14.77747413510043)</td>\n",
       "      <td>2988435647</td>\n",
       "      <td>89.468532</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>30</td>\n",
       "      <td>204</td>\n",
       "      <td>28PBB7034_07</td>\n",
       "      <td>hamlet</td>\n",
       "      <td>0.112259</td>\n",
       "      <td>1.692285e+02</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2999.449116</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.016761</td>\n",
       "      <td>9.425205e-06</td>\n",
       "      <td>POINT (-17.129431186301037 14.778506781574904)</td>\n",
       "      <td>7838754747</td>\n",
       "      <td>18.701502</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>31</td>\n",
       "      <td>206</td>\n",
       "      <td>28PBB5835_03</td>\n",
       "      <td>hamlet</td>\n",
       "      <td>0.022898</td>\n",
       "      <td>9.636268e+00</td>\n",
       "      <td>18.883526</td>\n",
       "      <td>16035.762110</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.005762</td>\n",
       "      <td>1.922510e-06</td>\n",
       "      <td>POINT (-17.242305601017154 14.783375368548443)</td>\n",
       "      <td>6053825179</td>\n",
       "      <td>85.053967</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>32</td>\n",
       "      <td>208</td>\n",
       "      <td>28PBB7435_01</td>\n",
       "      <td>hamlet</td>\n",
       "      <td>0.045895</td>\n",
       "      <td>7.314733e+01</td>\n",
       "      <td>9.383175</td>\n",
       "      <td>2999.449116</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.010610</td>\n",
       "      <td>3.853366e-06</td>\n",
       "      <td>POINT (-17.094173826957192 14.782872880683293)</td>\n",
       "      <td>2988435792</td>\n",
       "      <td>448.688952</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>33</td>\n",
       "      <td>209</td>\n",
       "      <td>28PBB5736_02</td>\n",
       "      <td>hamlet</td>\n",
       "      <td>0.024862</td>\n",
       "      <td>2.599556e+01</td>\n",
       "      <td>18.950196</td>\n",
       "      <td>16035.762110</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.005707</td>\n",
       "      <td>2.087379e-06</td>\n",
       "      <td>POINT (-17.249054064042234 14.789944283803916)</td>\n",
       "      <td>3036877534</td>\n",
       "      <td>83.358619</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>34</td>\n",
       "      <td>210</td>\n",
       "      <td>28PBB6036_01</td>\n",
       "      <td>hamlet</td>\n",
       "      <td>0.127726</td>\n",
       "      <td>2.177392e+02</td>\n",
       "      <td>18.371827</td>\n",
       "      <td>16035.762110</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.020240</td>\n",
       "      <td>1.072401e-05</td>\n",
       "      <td>POINT (-17.224509034146617 14.78865536663635)</td>\n",
       "      <td>6056472223</td>\n",
       "      <td>33.845239</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>35</td>\n",
       "      <td>211</td>\n",
       "      <td>28PBB4937_01</td>\n",
       "      <td>hamlet</td>\n",
       "      <td>0.064379</td>\n",
       "      <td>5.965873e+02</td>\n",
       "      <td>7.559833</td>\n",
       "      <td>16035.762110</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.010636</td>\n",
       "      <td>5.405016e-06</td>\n",
       "      <td>POINT (-17.33197897874605 14.801673118686626)</td>\n",
       "      <td>7460241128</td>\n",
       "      <td>101.985612</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>36</td>\n",
       "      <td>213</td>\n",
       "      <td>28PBB9439_02</td>\n",
       "      <td>hamlet</td>\n",
       "      <td>0.031203</td>\n",
       "      <td>6.360090e+01</td>\n",
       "      <td>6.593517</td>\n",
       "      <td>5446.539082</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.006431</td>\n",
       "      <td>2.620111e-06</td>\n",
       "      <td>POINT (-16.906716646509395 14.821388297685347)</td>\n",
       "      <td>6028595154</td>\n",
       "      <td>16.068266</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>37</td>\n",
       "      <td>214</td>\n",
       "      <td>28PBB9140_02</td>\n",
       "      <td>hamlet</td>\n",
       "      <td>0.016236</td>\n",
       "      <td>3.369405e+01</td>\n",
       "      <td>7.070007</td>\n",
       "      <td>5446.539082</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.005212</td>\n",
       "      <td>1.363254e-06</td>\n",
       "      <td>POINT (-16.93440097090104 14.827449770877049)</td>\n",
       "      <td>4053739078</td>\n",
       "      <td>53.575602</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>38</td>\n",
       "      <td>216</td>\n",
       "      <td>28PCB0753_03</td>\n",
       "      <td>hamlet</td>\n",
       "      <td>0.038454</td>\n",
       "      <td>2.791577e+01</td>\n",
       "      <td>4.990843</td>\n",
       "      <td>4449.367491</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.007613</td>\n",
       "      <td>3.230593e-06</td>\n",
       "      <td>POINT (-16.793775813770107 14.948188044266814)</td>\n",
       "      <td>4071261250</td>\n",
       "      <td>101.308205</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>39</td>\n",
       "      <td>218</td>\n",
       "      <td>28PCB6420_04</td>\n",
       "      <td>hamlet</td>\n",
       "      <td>0.036734</td>\n",
       "      <td>5.628131e+01</td>\n",
       "      <td>5.323107</td>\n",
       "      <td>5681.109779</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.008031</td>\n",
       "      <td>3.082793e-06</td>\n",
       "      <td>POINT (-16.256116818111135 14.656461506543518)</td>\n",
       "      <td>6014815775</td>\n",
       "      <td>69.797088</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>40</td>\n",
       "      <td>219</td>\n",
       "      <td>28PCB6622_01</td>\n",
       "      <td>hamlet</td>\n",
       "      <td>0.042953</td>\n",
       "      <td>7.583911e+01</td>\n",
       "      <td>7.330625</td>\n",
       "      <td>5681.109779</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.008189</td>\n",
       "      <td>3.604109e-06</td>\n",
       "      <td>POINT (-16.241253248843044 14.674992153284423)</td>\n",
       "      <td>6024430122</td>\n",
       "      <td>65.929413</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>41</td>\n",
       "      <td>223</td>\n",
       "      <td>28PDB0035_01</td>\n",
       "      <td>hamlet</td>\n",
       "      <td>0.007997</td>\n",
       "      <td>1.721998e+01</td>\n",
       "      <td>12.119414</td>\n",
       "      <td>4822.119467</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.003240</td>\n",
       "      <td>6.713225e-07</td>\n",
       "      <td>POINT (-15.924404585230247 14.79008802267149)</td>\n",
       "      <td>8229317581</td>\n",
       "      <td>46.096276</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>42</td>\n",
       "      <td>224</td>\n",
       "      <td>28PCB9937_03</td>\n",
       "      <td>hamlet</td>\n",
       "      <td>0.066384</td>\n",
       "      <td>1.701381e+02</td>\n",
       "      <td>10.443704</td>\n",
       "      <td>4822.119467</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.011110</td>\n",
       "      <td>5.573913e-06</td>\n",
       "      <td>POINT (-15.933785288853453 14.809426960267158)</td>\n",
       "      <td>6027834438</td>\n",
       "      <td>208.336925</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>43</td>\n",
       "      <td>226</td>\n",
       "      <td>28PDB1139_01</td>\n",
       "      <td>hamlet</td>\n",
       "      <td>0.020778</td>\n",
       "      <td>2.617514e+01</td>\n",
       "      <td>10.677935</td>\n",
       "      <td>4822.119467</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.005601</td>\n",
       "      <td>1.744649e-06</td>\n",
       "      <td>POINT (-15.82161911516783 14.826628245382166)</td>\n",
       "      <td>6024894515</td>\n",
       "      <td>194.366522</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>44</td>\n",
       "      <td>227</td>\n",
       "      <td>28PDB1139_02</td>\n",
       "      <td>hamlet</td>\n",
       "      <td>0.056959</td>\n",
       "      <td>8.547818e+01</td>\n",
       "      <td>10.874058</td>\n",
       "      <td>4822.119467</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.011433</td>\n",
       "      <td>4.783164e-06</td>\n",
       "      <td>POINT (-15.824145139116334 14.826896103769105)</td>\n",
       "      <td>6024894530</td>\n",
       "      <td>44.896345</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>45</td>\n",
       "      <td>228</td>\n",
       "      <td>28PDB1139_03</td>\n",
       "      <td>hamlet</td>\n",
       "      <td>0.020389</td>\n",
       "      <td>1.425154e+01</td>\n",
       "      <td>10.553416</td>\n",
       "      <td>4822.119467</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.005011</td>\n",
       "      <td>1.712171e-06</td>\n",
       "      <td>POINT (-15.819773868082187 14.82763603774496)</td>\n",
       "      <td>6024894513</td>\n",
       "      <td>214.531196</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>46</td>\n",
       "      <td>229</td>\n",
       "      <td>28PCB9741_04</td>\n",
       "      <td>hamlet</td>\n",
       "      <td>0.028295</td>\n",
       "      <td>2.806345e+01</td>\n",
       "      <td>9.374555</td>\n",
       "      <td>4822.119467</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.006360</td>\n",
       "      <td>2.376282e-06</td>\n",
       "      <td>POINT (-15.956248013051251 14.84813630510084)</td>\n",
       "      <td>8169321141</td>\n",
       "      <td>23.619127</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>47</td>\n",
       "      <td>230</td>\n",
       "      <td>28PDB0149_01</td>\n",
       "      <td>hamlet</td>\n",
       "      <td>0.040534</td>\n",
       "      <td>4.546143e+01</td>\n",
       "      <td>6.408090</td>\n",
       "      <td>4822.119467</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.007648</td>\n",
       "      <td>3.404769e-06</td>\n",
       "      <td>POINT (-15.920443499962804 14.914499169364376)</td>\n",
       "      <td>8200304626</td>\n",
       "      <td>6.919737</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>48</td>\n",
       "      <td>237</td>\n",
       "      <td>28PCC6924_02</td>\n",
       "      <td>hamlet</td>\n",
       "      <td>0.013923</td>\n",
       "      <td>9.612921e+00</td>\n",
       "      <td>5.051494</td>\n",
       "      <td>4601.126349</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.004811</td>\n",
       "      <td>1.173189e-06</td>\n",
       "      <td>POINT (-16.217456240770417 15.597199756480478)</td>\n",
       "      <td>1968458114</td>\n",
       "      <td>56.750510</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>49</td>\n",
       "      <td>244</td>\n",
       "      <td>28QCC4877_02</td>\n",
       "      <td>hamlet</td>\n",
       "      <td>0.020283</td>\n",
       "      <td>1.279428e+01</td>\n",
       "      <td>4.109954</td>\n",
       "      <td>5487.706734</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.005630</td>\n",
       "      <td>1.713057e-06</td>\n",
       "      <td>POINT (-16.416588195364064 16.071912118977373)</td>\n",
       "      <td>9359670710</td>\n",
       "      <td>34.348832</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>50</td>\n",
       "      <td>274</td>\n",
       "      <td>28PFA3822_04</td>\n",
       "      <td>ssa</td>\n",
       "      <td>0.295219</td>\n",
       "      <td>5.353027e+02</td>\n",
       "      <td>4.677464</td>\n",
       "      <td>4478.321578</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.026402</td>\n",
       "      <td>2.467579e-05</td>\n",
       "      <td>POINT (-13.714783248440478 13.771220759716533)</td>\n",
       "      <td>6021177135</td>\n",
       "      <td>239.631441</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>51</td>\n",
       "      <td>275</td>\n",
       "      <td>28PFA4124_01</td>\n",
       "      <td>ssa</td>\n",
       "      <td>0.101893</td>\n",
       "      <td>1.886798e+02</td>\n",
       "      <td>4.089369</td>\n",
       "      <td>4478.321578</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.013817</td>\n",
       "      <td>8.517618e-06</td>\n",
       "      <td>POINT (-13.69532688091379 13.783265672958317)</td>\n",
       "      <td>6027615161</td>\n",
       "      <td>29.882395</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>52</td>\n",
       "      <td>278</td>\n",
       "      <td>28PBA8299_02</td>\n",
       "      <td>ssa</td>\n",
       "      <td>0.343841</td>\n",
       "      <td>6.259307e+02</td>\n",
       "      <td>5.307602</td>\n",
       "      <td>4163.686114</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.051295</td>\n",
       "      <td>2.883058e-05</td>\n",
       "      <td>POINT (-17.020742566008337 14.46138641364398)</td>\n",
       "      <td>6027276892</td>\n",
       "      <td>23.453107</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>53</td>\n",
       "      <td>287</td>\n",
       "      <td>28PBB5835_05</td>\n",
       "      <td>ssa</td>\n",
       "      <td>0.308017</td>\n",
       "      <td>3.190239e+02</td>\n",
       "      <td>17.747726</td>\n",
       "      <td>16035.762110</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.043032</td>\n",
       "      <td>2.586476e-05</td>\n",
       "      <td>POINT (-17.245528396017207 14.782219244270532)</td>\n",
       "      <td>6041228287</td>\n",
       "      <td>40.406566</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>54</td>\n",
       "      <td>288</td>\n",
       "      <td>28PBB5936_02</td>\n",
       "      <td>ssa</td>\n",
       "      <td>0.154444</td>\n",
       "      <td>2.000646e+02</td>\n",
       "      <td>20.407153</td>\n",
       "      <td>16035.762110</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.026399</td>\n",
       "      <td>1.296732e-05</td>\n",
       "      <td>POINT (-17.23454728899848 14.795909517565944)</td>\n",
       "      <td>5536661253</td>\n",
       "      <td>24.430550</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>55</td>\n",
       "      <td>289</td>\n",
       "      <td>28PBB6040_03</td>\n",
       "      <td>ssa</td>\n",
       "      <td>0.160911</td>\n",
       "      <td>2.663758e+02</td>\n",
       "      <td>21.657425</td>\n",
       "      <td>16035.762110</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.027111</td>\n",
       "      <td>1.351374e-05</td>\n",
       "      <td>POINT (-17.225385101570456 14.830374516240026)</td>\n",
       "      <td>7357630367</td>\n",
       "      <td>149.183632</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>56</td>\n",
       "      <td>297</td>\n",
       "      <td>28PCB9642_02</td>\n",
       "      <td>ssa</td>\n",
       "      <td>2.337009</td>\n",
       "      <td>3.504073e+03</td>\n",
       "      <td>11.801961</td>\n",
       "      <td>4822.119467</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.172410</td>\n",
       "      <td>1.963038e-04</td>\n",
       "      <td>POINT (-15.9651353582649 14.85568825099391)</td>\n",
       "      <td>8178147277</td>\n",
       "      <td>13.505685</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>57</td>\n",
       "      <td>298</td>\n",
       "      <td>28PDB0750_04</td>\n",
       "      <td>ssa</td>\n",
       "      <td>0.454997</td>\n",
       "      <td>5.968164e+02</td>\n",
       "      <td>11.240426</td>\n",
       "      <td>4822.119467</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.038288</td>\n",
       "      <td>3.822519e-05</td>\n",
       "      <td>POINT (-15.85780585273177 14.926926620823643)</td>\n",
       "      <td>6026834850</td>\n",
       "      <td>10.829250</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Unnamed: 0  Unnamed_ 0     mgrs_code    type    AREA_GEO           SUM  \\\n",
       "0            0           1  28PCU6189_01     bua   27.151434  1.860466e+05   \n",
       "1            1           8  28PEV0625_01     bua   25.799549  1.064198e+05   \n",
       "2            2          37  28PBA8597_01     bua   81.242354  3.382677e+05   \n",
       "3            3          47  28PCA8365_01     bua   42.134069  2.755403e+05   \n",
       "4            4          56  28PDA4058_01     bua   11.123881  5.186398e+04   \n",
       "5            5          75  28PBB9234_01     bua   53.453391  2.911360e+05   \n",
       "6            6          76  28PBB4632_01     bua  226.850348  3.637718e+06   \n",
       "7            7          80  28PCB0453_01     bua   19.580942  8.712281e+04   \n",
       "8            8          84  28PCB6720_01     bua   23.634834  1.342721e+05   \n",
       "9            9          98  28PDB0443_01     bua  196.802191  9.490037e+05   \n",
       "10          10         123  28QCC4070_01     bua    9.174147  1.077744e+05   \n",
       "11          11         125  28QCC4573_01     bua   13.701781  7.519136e+04   \n",
       "12          12         151  28PFA4322_01     bua   26.974183  1.207991e+05   \n",
       "13          13         157  28PCC6827_01     bua   20.814212  9.576882e+04   \n",
       "14          14         160  28PCU6286_04  hamlet    0.105280  2.093665e+02   \n",
       "15          15         168  28PEV0425_03  hamlet    0.164601  2.503226e+02   \n",
       "16          16         173  28PFA4321_01  hamlet    0.036757  5.002239e+01   \n",
       "17          17         174  28PBA9292_06  hamlet    0.023177  1.846325e+01   \n",
       "18          18         175  28PBA8299_01  hamlet    0.013923  1.655101e+01   \n",
       "19          19         176  28PBB7801_01  hamlet    0.017578  3.044826e+01   \n",
       "20          20         177  28PBB8202_01  hamlet    0.033487  3.486522e+01   \n",
       "21          21         178  28PBB7902_04  hamlet    0.188962  2.698936e+02   \n",
       "22          22         179  28PBB8103_02  hamlet    0.152780  2.366904e+02   \n",
       "23          23         182  28PCA7866_01  hamlet    0.009282  1.921189e+01   \n",
       "24          24         184  28PCA8268_03  hamlet    0.026723  3.108315e+01   \n",
       "25          25         197  28PBB3031_01  hamlet    0.036793  2.190752e+02   \n",
       "26          26         199  28PBB9431_01  hamlet    0.017802  3.757302e+01   \n",
       "27          27         201  28PBB5833_07  hamlet    0.044133  6.815012e+01   \n",
       "28          28         202  28PBB5934_01  hamlet    0.067703  6.689919e+01   \n",
       "29          29         203  28PBB7434_03  hamlet    0.024692  6.194532e+01   \n",
       "30          30         204  28PBB7034_07  hamlet    0.112259  1.692285e+02   \n",
       "31          31         206  28PBB5835_03  hamlet    0.022898  9.636268e+00   \n",
       "32          32         208  28PBB7435_01  hamlet    0.045895  7.314733e+01   \n",
       "33          33         209  28PBB5736_02  hamlet    0.024862  2.599556e+01   \n",
       "34          34         210  28PBB6036_01  hamlet    0.127726  2.177392e+02   \n",
       "35          35         211  28PBB4937_01  hamlet    0.064379  5.965873e+02   \n",
       "36          36         213  28PBB9439_02  hamlet    0.031203  6.360090e+01   \n",
       "37          37         214  28PBB9140_02  hamlet    0.016236  3.369405e+01   \n",
       "38          38         216  28PCB0753_03  hamlet    0.038454  2.791577e+01   \n",
       "39          39         218  28PCB6420_04  hamlet    0.036734  5.628131e+01   \n",
       "40          40         219  28PCB6622_01  hamlet    0.042953  7.583911e+01   \n",
       "41          41         223  28PDB0035_01  hamlet    0.007997  1.721998e+01   \n",
       "42          42         224  28PCB9937_03  hamlet    0.066384  1.701381e+02   \n",
       "43          43         226  28PDB1139_01  hamlet    0.020778  2.617514e+01   \n",
       "44          44         227  28PDB1139_02  hamlet    0.056959  8.547818e+01   \n",
       "45          45         228  28PDB1139_03  hamlet    0.020389  1.425154e+01   \n",
       "46          46         229  28PCB9741_04  hamlet    0.028295  2.806345e+01   \n",
       "47          47         230  28PDB0149_01  hamlet    0.040534  4.546143e+01   \n",
       "48          48         237  28PCC6924_02  hamlet    0.013923  9.612921e+00   \n",
       "49          49         244  28QCC4877_02  hamlet    0.020283  1.279428e+01   \n",
       "50          50         274  28PFA3822_04     ssa    0.295219  5.353027e+02   \n",
       "51          51         275  28PFA4124_01     ssa    0.101893  1.886798e+02   \n",
       "52          52         278  28PBA8299_02     ssa    0.343841  6.259307e+02   \n",
       "53          53         287  28PBB5835_05     ssa    0.308017  3.190239e+02   \n",
       "54          54         288  28PBB5936_02     ssa    0.154444  2.000646e+02   \n",
       "55          55         289  28PBB6040_03     ssa    0.160911  2.663758e+02   \n",
       "56          56         297  28PCB9642_02     ssa    2.337009  3.504073e+03   \n",
       "57          57         298  28PDB0750_04     ssa    0.454997  5.968164e+02   \n",
       "\n",
       "    Total_Driv       WP_dens  urb  hd_urb  Urb_class  Shape_Leng  \\\n",
       "0     0.000000   6852.183502    1       1          2    0.671746   \n",
       "1     0.000000   4124.872441    1       1          2    0.718941   \n",
       "2     0.000000   4163.686114    1       1          2    2.303639   \n",
       "3     0.000000   6539.609258    1       1          2    1.070058   \n",
       "4     0.000000   4662.399756    1       1          2    0.298223   \n",
       "5     0.000000   5446.539082    1       1          2    1.468618   \n",
       "6     0.000000  16035.762110    1       1          2    4.771359   \n",
       "7     0.000000   4449.367491    1       1          2    0.611345   \n",
       "8     0.000000   5681.109779    1       1          2    0.689064   \n",
       "9     0.000000   2575.818720    1       1          2    3.094788   \n",
       "10    0.000000  11747.618988    1       1          2    0.212800   \n",
       "11    0.000000   5487.706734    1       1          2    0.612294   \n",
       "12    0.000000   4478.321578    1       1          2    0.686130   \n",
       "13    0.000000   4601.126349    1       1          2    0.494002   \n",
       "14    5.479664   6852.183502    1       1          2    0.021230   \n",
       "15    5.371455   4124.872441    1       1          2    0.019495   \n",
       "16    3.131679   4478.321578    1       1          2    0.006776   \n",
       "17   13.239334   4163.686114    1       1          2    0.005371   \n",
       "18    4.715519   4163.686114    1       1          2    0.004799   \n",
       "19   11.659853   4163.686114    1       1          2    0.004813   \n",
       "20    7.892879   4163.686114    1       1          2    0.008101   \n",
       "21    9.563365   4163.686114    1       1          2    0.030043   \n",
       "22    9.538024   4163.686114    1       1          2    0.029995   \n",
       "23    8.378629   6539.609258    1       1          2    0.003274   \n",
       "24    5.292360   6539.609258    1       1          2    0.006861   \n",
       "25   15.925017  16035.762110    1       1          2    0.007562   \n",
       "26    6.049956   5446.539082    1       1          2    0.004718   \n",
       "27   15.771149  16035.762110    1       1          2    0.008892   \n",
       "28   16.463440  16035.762110    1       1          2    0.012549   \n",
       "29    8.691752   2999.449116    1       1          2    0.005714   \n",
       "30         NaN   2999.449116    1       1          2    0.016761   \n",
       "31   18.883526  16035.762110    1       1          2    0.005762   \n",
       "32    9.383175   2999.449116    1       1          2    0.010610   \n",
       "33   18.950196  16035.762110    1       1          2    0.005707   \n",
       "34   18.371827  16035.762110    1       1          2    0.020240   \n",
       "35    7.559833  16035.762110    1       1          2    0.010636   \n",
       "36    6.593517   5446.539082    1       1          2    0.006431   \n",
       "37    7.070007   5446.539082    1       1          2    0.005212   \n",
       "38    4.990843   4449.367491    1       1          2    0.007613   \n",
       "39    5.323107   5681.109779    1       1          2    0.008031   \n",
       "40    7.330625   5681.109779    1       1          2    0.008189   \n",
       "41   12.119414   4822.119467    1       1          2    0.003240   \n",
       "42   10.443704   4822.119467    1       1          2    0.011110   \n",
       "43   10.677935   4822.119467    1       1          2    0.005601   \n",
       "44   10.874058   4822.119467    1       1          2    0.011433   \n",
       "45   10.553416   4822.119467    1       1          2    0.005011   \n",
       "46    9.374555   4822.119467    1       1          2    0.006360   \n",
       "47    6.408090   4822.119467    1       1          2    0.007648   \n",
       "48    5.051494   4601.126349    1       1          2    0.004811   \n",
       "49    4.109954   5487.706734    1       1          2    0.005630   \n",
       "50    4.677464   4478.321578    1       1          2    0.026402   \n",
       "51    4.089369   4478.321578    1       1          2    0.013817   \n",
       "52    5.307602   4163.686114    1       1          2    0.051295   \n",
       "53   17.747726  16035.762110    1       1          2    0.043032   \n",
       "54   20.407153  16035.762110    1       1          2    0.026399   \n",
       "55   21.657425  16035.762110    1       1          2    0.027111   \n",
       "56   11.801961   4822.119467    1       1          2    0.172410   \n",
       "57   11.240426   4822.119467    1       1          2    0.038288   \n",
       "\n",
       "      Shape_Area                                        geometry          NN  \\\n",
       "0   2.258828e-03   POINT (-16.27318626010657 12.562367084144856)  6058226279   \n",
       "1   2.149259e-03  POINT (-14.936187613172205 12.892160925397892)  6029307183   \n",
       "2   6.813610e-03  POINT (-16.987028969206293 14.445279143289168)  4998093094   \n",
       "3   3.528274e-03  POINT (-16.076128475299285 14.160382012387636)  2201506815   \n",
       "4   9.311211e-04  POINT (-15.547596052646174 14.100419699131665)  4321656809   \n",
       "5   4.489114e-03  POINT (-16.926149059908756 14.780621967102865)  1697006012   \n",
       "6   1.905124e-02   POINT (-17.35638706164378 14.751962825615575)  1901689169   \n",
       "7   1.645460e-03    POINT (-16.81720508223022 14.94580992504745)  6032060028   \n",
       "8   1.983306e-03  POINT (-16.227786747221682 14.653718853747844)  6040927878   \n",
       "9   1.653195e-02  POINT (-15.887758561636817 14.860301673230607)  3449495495   \n",
       "10  7.746230e-04  POINT (-16.490434722674546 16.009724520231487)  3990543961   \n",
       "11  1.157396e-03   POINT (-16.44247212109952 16.048232088709874)  8972391475   \n",
       "12  2.255116e-03  POINT (-13.670259928888687 13.770692647360004)  3418418812   \n",
       "13  1.754369e-03   POINT (-16.22513510721168 15.620904283746231)  1983641803   \n",
       "14  8.758142e-06  POINT (-16.264484462734323 12.537366413261045)  6014451367   \n",
       "15  1.371013e-05  POINT (-14.961042651677891 12.895762457094666)  6027163276   \n",
       "16  3.072012e-06  POINT (-13.668587614564068 13.755222178122034)  2833577858   \n",
       "17  1.942589e-06   POINT (-16.927480646349732 14.39849858186184)  7321088861   \n",
       "18  1.167113e-06  POINT (-17.016066265874734 14.460756350154803)  6045659373   \n",
       "19  1.473665e-06  POINT (-17.055862944965526 14.477635627799748)  5528866190   \n",
       "20  2.807464e-06  POINT (-17.018846969475057 14.483053711062894)  6027939517   \n",
       "21  1.584495e-05   POINT (-17.042492216832404 14.48472898603413)  6031093257   \n",
       "22  1.281388e-05   POINT (-17.026406509846662 14.49188592573409)  1883155712   \n",
       "23  7.770706e-07   POINT (-16.12870301954371 14.163238160099032)  6026417971   \n",
       "24  2.237697e-06  POINT (-16.090276652783288 14.185562094447294)  6031245697   \n",
       "25  3.088678e-06  POINT (-17.503912092775586 14.746318221560271)  7493947593   \n",
       "26  1.494350e-06  POINT (-16.909081994152583 14.746958369151947)  1859359090   \n",
       "27  3.704665e-06   POINT (-17.23995849720513 14.767547644151895)  6053816462   \n",
       "28  5.684528e-06    POINT (-17.23391993155635 14.77602519637424)  6027530676   \n",
       "29  2.072792e-06   POINT (-17.098633451710782 14.77747413510043)  2988435647   \n",
       "30  9.425205e-06  POINT (-17.129431186301037 14.778506781574904)  7838754747   \n",
       "31  1.922510e-06  POINT (-17.242305601017154 14.783375368548443)  6053825179   \n",
       "32  3.853366e-06  POINT (-17.094173826957192 14.782872880683293)  2988435792   \n",
       "33  2.087379e-06  POINT (-17.249054064042234 14.789944283803916)  3036877534   \n",
       "34  1.072401e-05   POINT (-17.224509034146617 14.78865536663635)  6056472223   \n",
       "35  5.405016e-06   POINT (-17.33197897874605 14.801673118686626)  7460241128   \n",
       "36  2.620111e-06  POINT (-16.906716646509395 14.821388297685347)  6028595154   \n",
       "37  1.363254e-06   POINT (-16.93440097090104 14.827449770877049)  4053739078   \n",
       "38  3.230593e-06  POINT (-16.793775813770107 14.948188044266814)  4071261250   \n",
       "39  3.082793e-06  POINT (-16.256116818111135 14.656461506543518)  6014815775   \n",
       "40  3.604109e-06  POINT (-16.241253248843044 14.674992153284423)  6024430122   \n",
       "41  6.713225e-07   POINT (-15.924404585230247 14.79008802267149)  8229317581   \n",
       "42  5.573913e-06  POINT (-15.933785288853453 14.809426960267158)  6027834438   \n",
       "43  1.744649e-06   POINT (-15.82161911516783 14.826628245382166)  6024894515   \n",
       "44  4.783164e-06  POINT (-15.824145139116334 14.826896103769105)  6024894530   \n",
       "45  1.712171e-06   POINT (-15.819773868082187 14.82763603774496)  6024894513   \n",
       "46  2.376282e-06   POINT (-15.956248013051251 14.84813630510084)  8169321141   \n",
       "47  3.404769e-06  POINT (-15.920443499962804 14.914499169364376)  8200304626   \n",
       "48  1.173189e-06  POINT (-16.217456240770417 15.597199756480478)  1968458114   \n",
       "49  1.713057e-06  POINT (-16.416588195364064 16.071912118977373)  9359670710   \n",
       "50  2.467579e-05  POINT (-13.714783248440478 13.771220759716533)  6021177135   \n",
       "51  8.517618e-06   POINT (-13.69532688091379 13.783265672958317)  6027615161   \n",
       "52  2.883058e-05   POINT (-17.020742566008337 14.46138641364398)  6027276892   \n",
       "53  2.586476e-05  POINT (-17.245528396017207 14.782219244270532)  6041228287   \n",
       "54  1.296732e-05   POINT (-17.23454728899848 14.795909517565944)  5536661253   \n",
       "55  1.351374e-05  POINT (-17.225385101570456 14.830374516240026)  7357630367   \n",
       "56  1.963038e-04     POINT (-15.9651353582649 14.85568825099391)  8178147277   \n",
       "57  3.822519e-05   POINT (-15.85780585273177 14.926926620823643)  6026834850   \n",
       "\n",
       "       NN_dist  \n",
       "0     2.216606  \n",
       "1    45.594167  \n",
       "2    55.383696  \n",
       "3    55.754910  \n",
       "4    61.727308  \n",
       "5    23.047883  \n",
       "6     5.826006  \n",
       "7    88.156089  \n",
       "8    41.930884  \n",
       "9    28.431974  \n",
       "10   30.501908  \n",
       "11   76.235638  \n",
       "12   13.729478  \n",
       "13   29.090625  \n",
       "14   61.273348  \n",
       "15   23.270139  \n",
       "16  216.111092  \n",
       "17  126.948072  \n",
       "18   27.871739  \n",
       "19   64.826632  \n",
       "20   24.581971  \n",
       "21  273.489784  \n",
       "22  129.540762  \n",
       "23  287.396023  \n",
       "24   49.284838  \n",
       "25   15.922254  \n",
       "26  107.065710  \n",
       "27   52.284317  \n",
       "28   16.433933  \n",
       "29   89.468532  \n",
       "30   18.701502  \n",
       "31   85.053967  \n",
       "32  448.688952  \n",
       "33   83.358619  \n",
       "34   33.845239  \n",
       "35  101.985612  \n",
       "36   16.068266  \n",
       "37   53.575602  \n",
       "38  101.308205  \n",
       "39   69.797088  \n",
       "40   65.929413  \n",
       "41   46.096276  \n",
       "42  208.336925  \n",
       "43  194.366522  \n",
       "44   44.896345  \n",
       "45  214.531196  \n",
       "46   23.619127  \n",
       "47    6.919737  \n",
       "48   56.750510  \n",
       "49   34.348832  \n",
       "50  239.631441  \n",
       "51   29.882395  \n",
       "52   23.453107  \n",
       "53   40.406566  \n",
       "54   24.430550  \n",
       "55  149.183632  \n",
       "56   13.505685  \n",
       "57   10.829250  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "HDurban_snap"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "# We only need to find the origin-destination pairs for nodes closest to the origins and services,\n",
    "# and some nodes will be the nearest for more than one service (and definitely for multiple origins).\n",
    "list_hamlet = list(hamlet_snap.NN.unique())\n",
    "origins = list_hamlet"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "list_ag = list(ag_snap.NN.unique())\n",
    "originslist = list_hamlet + list_ag\n",
    "origins = list(set(originslist))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "dests = list(HDurban_snap.NN.unique()) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "985720"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(origins) # 985720 unique nearest nodes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "58"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(dests) # 58 unique nearest nodes. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(358284990, 5217543379, {'geometry': <shapely.geometry.linestring.LineString object at 0x000001EA1E933AF0>, 'Unnamed: 0': 0, 'Unnamed: 0.1': 0, 'time': 2.3851440000000004, 'length': 33.127, 'highway': 'unclassified', 'osmid': 59618174, 'PFU_1in10': -1.0, 't10': 2.3851440000000004})\n",
      "(358284990, 1888282175, {'geometry': <shapely.geometry.linestring.LineString object at 0x000001EA1E867DC0>, 'Unnamed: 0': 1, 'Unnamed: 0.1': 1, 'time': 0.76992, 'length': 12.832, 'highway': 'tertiary', 'osmid': 178482063, 'PFU_1in10': -1.0, 't10': 0.76992})\n",
      "(358284990, 5329792467, {'geometry': <shapely.geometry.linestring.LineString object at 0x000001EA16A68FD0>, 'Unnamed: 0': 2, 'Unnamed: 0.1': 2, 'time': 2.92686, 'length': 48.781, 'highway': 'tertiary', 'osmid': 178482063, 'PFU_1in10': -1.0, 't10': 2.92686})\n",
      "(5217543379, 358284990, {'geometry': <shapely.geometry.linestring.LineString object at 0x000001EA16A544F0>, 'Unnamed: 0': 3, 'Unnamed: 0.1': 3, 'time': 2.3851440000000004, 'length': 33.127, 'highway': 'unclassified', 'osmid': 59618174, 'PFU_1in10': -1.0, 't10': 2.3851440000000004})\n",
      "(5217543379, 5329928981, {'geometry': <shapely.geometry.linestring.LineString object at 0x000001EA1D679160>, 'Unnamed: 0': 4, 'Unnamed: 0.1': 4, 'time': 1.232928, 'length': 17.124, 'highway': 'unclassified', 'osmid': 59618174, 'PFU_1in10': -1.0, 't10': 1.232928})\n",
      "(1888282175, 1888282174, {'geometry': <shapely.geometry.linestring.LineString object at 0x000001EA1D679490>, 'Unnamed: 0': 5, 'Unnamed: 0.1': 5, 'time': 0.9322200000000002, 'length': 15.537, 'highway': 'tertiary', 'osmid': 178482063, 'PFU_1in10': -1.0, 't10': 0.9322200000000002})\n",
      "(1888282175, 358284990, {'geometry': <shapely.geometry.linestring.LineString object at 0x000001EA1D679370>, 'Unnamed: 0': 6, 'Unnamed: 0.1': 6, 'time': 0.76992, 'length': 12.832, 'highway': 'tertiary', 'osmid': 178482063, 'PFU_1in10': -1.0, 't10': 0.76992})\n",
      "(5329792467, 358284990, {'geometry': <shapely.geometry.linestring.LineString object at 0x000001EA1D679820>, 'Unnamed: 0': 7, 'Unnamed: 0.1': 7, 'time': 2.92686, 'length': 48.781, 'highway': 'tertiary', 'osmid': 178482063, 'PFU_1in10': -1.0, 't10': 2.92686})\n",
      "(5329792467, 1888282177, {'geometry': <shapely.geometry.linestring.LineString object at 0x000001EA1D6795B0>, 'Unnamed: 0': 8, 'Unnamed: 0.1': 8, 'time': 2.7629999999999995, 'length': 46.05, 'highway': 'tertiary', 'osmid': 178482063, 'PFU_1in10': -1.0, 't10': 2.7629999999999995})\n",
      "(5329928981, 5217543379, {'geometry': <shapely.geometry.linestring.LineString object at 0x000001EA1D6793D0>, 'Unnamed: 0': 32584, 'Unnamed: 0.1': 32553, 'time': 1.232928, 'length': 17.124, 'highway': 'unclassified', 'osmid': 59618174, 'PFU_1in10': -1.0, 't10': 1.232928})\n"
     ]
    }
   ],
   "source": [
    "gn.example_edge(gTime,10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "calculate_OD won't run if any of the edge times are null or zero. If there are any hits, reassign time values for those edges to a very small time. A more efficient way to do this would be to simplify junctions with the clean_network() tool, but that was throwing errors."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "edges = gn.edge_gdf_from_graph(gTime)\n",
    "len(edges.loc[edges['t10'].isnull()])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(edges.loc[edges['t10']==0]) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "fail_value = 999999999 # If there is no shortest path, the OD pair will be assigned the fail value."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "print('start: %s\\n' % time.ctime())\n",
    "OD = gn.calculate_OD(gTime, origins, dests, fail_value, weight = 't10')\n",
    "# Takes a few minutes.\n",
    "print('\\nend: %s' % time.ctime())\n",
    "print('\\n--- processing complete')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "OD_df = pd.DataFrame(OD, index = origins, columns = dests)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "scrolled": true
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   "outputs": [
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      "<class 'pandas.core.frame.DataFrame'>\n",
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      "dtypes: float64(58)\n",
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  {
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     "execution_count": 26,
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       "      <td>688.824748</td>\n",
       "      <td>604.424637</td>\n",
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       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>985720 rows × 58 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            6058226279   6029307183  4998093094  2201506815  4321656809  \\\n",
       "3331684166  712.885186  2823.011514  246.631329   10.569381  530.757515   \n",
       "3571449893  216.749440  2386.130808  733.514641  609.858919  170.668947   \n",
       "3571449966  217.136351  2386.517719  733.901553  610.245830  171.055859   \n",
       "3405774993   88.160619  2520.464644  745.743296  622.087573  160.299823   \n",
       "3405774994   88.561368  2520.063895  745.342547  621.686824  159.899074   \n",
       "...                ...          ...         ...         ...         ...   \n",
       "8925478824  735.723083  2845.849411   99.101969  142.005352  553.595411   \n",
       "3706826868  194.113997  2508.198325  709.899217  586.243495  101.853261   \n",
       "3706826871  193.076374  2507.160702  708.861594  585.205871  102.890885   \n",
       "3706826876  194.295590  2508.379918  710.080810  586.425087  101.671669   \n",
       "3706826877  193.328295  2507.412623  709.113515  585.457792  102.638964   \n",
       "\n",
       "            1697006012  1901689169  6032060028  6040927878  3449495495  ...  \\\n",
       "3331684166  207.296393  248.750992  198.063276   60.029574   97.714216  ...   \n",
       "3571449893  694.236441  734.671489  676.996843  592.596732  561.437282  ...   \n",
       "3571449966  694.623353  735.058400  677.383754  592.983643  561.824194  ...   \n",
       "3405774993  706.465096  746.900143  689.225497  604.825386  573.665937  ...   \n",
       "3405774994  706.064347  746.499394  688.824748  604.424637  573.265188  ...   \n",
       "...                ...         ...         ...         ...         ...  ...   \n",
       "8925478824   59.767033  101.221632   48.880822   94.955770   83.736231  ...   \n",
       "3706826868  670.621017  711.056065  653.381419  568.981308  537.821858  ...   \n",
       "3706826871  669.583394  710.018441  652.343795  567.943684  536.784235  ...   \n",
       "3706826876  670.802610  711.237657  653.563011  569.162900  538.003450  ...   \n",
       "3706826877  669.835315  710.270362  652.595716  568.195605  537.036156  ...   \n",
       "\n",
       "            1968458114  9359670710  6021177135  6027615161  6027276892  \\\n",
       "3331684166  221.849165  277.518019  594.288540  593.995228  249.110882   \n",
       "3571449893  685.744905  741.413759  174.886877  174.593564  735.031379   \n",
       "3571449966  686.131817  741.800671  175.273788  174.980476  735.418291   \n",
       "3405774993  697.973560  753.642414  309.220713  308.927401  747.260034   \n",
       "3405774994  697.572811  753.241665  308.819964  308.526652  746.859285   \n",
       "...                ...         ...         ...         ...         ...   \n",
       "8925478824  107.199900  162.868754  617.126437  616.833124  101.581523   \n",
       "3706826868  662.129481  717.798335  296.954395  296.661082  711.415955   \n",
       "3706826871  661.091858  716.760712  295.916772  295.623459  710.378332   \n",
       "3706826876  662.311074  717.979928  297.135987  296.842675  711.597547   \n",
       "3706826877  661.343779  717.012633  296.168692  295.875380  710.630252   \n",
       "\n",
       "            6041228287  5536661253  7357630367  8178147277  6026834850  \n",
       "3331684166  241.842797  241.314533  241.226994   96.444984  107.620912  \n",
       "3571449893  727.763294  727.235030  727.147490  568.896781  567.894911  \n",
       "3571449966  728.150206  727.621942  727.534402  569.283692  568.281823  \n",
       "3405774993  739.991949  739.463685  739.376145  581.125435  580.123566  \n",
       "3405774994  739.591200  739.062936  738.975396  580.724686  579.722817  \n",
       "...                ...         ...         ...         ...         ...  \n",
       "8925478824   94.313438   93.785174   93.697634   85.844627   86.843588  \n",
       "3706826868  704.147870  703.619606  703.532066  545.281357  544.279487  \n",
       "3706826871  703.110247  702.581983  702.494443  544.243734  543.241864  \n",
       "3706826876  704.329462  703.801198  703.713659  545.462949  544.461079  \n",
       "3706826877  703.362167  702.833904  702.746364  544.495654  543.493785  \n",
       "\n",
       "[985720 rows x 58 columns]"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Convert to minutes and save to file.\n",
    "OD_min = OD_df[OD_df <fail_value] / 60\n",
    "OD_min.to_csv(os.path.join(out_pth, 'OD_allorigins_pre-project_flood10.csv'))\n",
    "OD_min"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "6058226279    3\n",
      "6029307183    3\n",
      "4998093094    3\n",
      "2201506815    3\n",
      "4321656809    3\n",
      "1697006012    3\n",
      "1901689169    3\n",
      "6032060028    3\n",
      "6040927878    3\n",
      "3449495495    3\n",
      "3990543961    3\n",
      "8972391475    3\n",
      "3418418812    3\n",
      "1983641803    3\n",
      "6014451367    3\n",
      "6027163276    3\n",
      "2833577858    3\n",
      "7321088861    3\n",
      "6045659373    3\n",
      "5528866190    3\n",
      "6027939517    3\n",
      "6031093257    3\n",
      "1883155712    3\n",
      "6026417971    3\n",
      "6031245697    3\n",
      "7493947593    3\n",
      "1859359090    3\n",
      "6053816462    3\n",
      "6027530676    3\n",
      "2988435647    3\n",
      "7838754747    3\n",
      "6053825179    3\n",
      "2988435792    3\n",
      "3036877534    3\n",
      "6056472223    3\n",
      "7460241128    3\n",
      "6028595154    3\n",
      "4053739078    3\n",
      "4071261250    3\n",
      "6014815775    3\n",
      "6024430122    3\n",
      "8229317581    3\n",
      "6027834438    3\n",
      "6024894515    3\n",
      "6024894530    3\n",
      "6024894513    3\n",
      "8169321141    3\n",
      "8200304626    3\n",
      "1968458114    3\n",
      "9359670710    3\n",
      "6021177135    3\n",
      "6027615161    3\n",
      "6027276892    3\n",
      "6041228287    3\n",
      "5536661253    3\n",
      "7357630367    3\n",
      "8178147277    3\n",
      "6026834850    3\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "print(OD_min.isna().sum())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
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       "      <th>9208004175</th>\n",
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       "      <td>176831.743755</td>\n",
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       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>74662 rows × 58 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               6058226279     6029307183     4998093094     2201506815  \\\n",
       "7761872870      63.944594    2661.109731     886.388383     762.732660   \n",
       "7761872869      63.926035    2661.091171     886.369823     762.714101   \n",
       "6442044321      62.916203    2660.081339     885.359991     761.704269   \n",
       "2142496418      64.369725    2661.534861     886.813513     763.157791   \n",
       "2142496429      64.752099    2661.917235     887.195887     763.540165   \n",
       "...                   ...            ...            ...            ...   \n",
       "9208004175  177445.540717  179555.667046  176832.674061  176878.793338   \n",
       "3884280043     993.922236    2928.538223     435.149435     441.072055   \n",
       "3884280001     987.060009    2921.675996     428.287208     434.209828   \n",
       "8592243457     962.853587    2915.269535     404.080786     410.003406   \n",
       "3649149740     982.241710    2974.816239     423.468909     429.391529   \n",
       "\n",
       "               4321656809     1697006012     1901689169     6032060028  \\\n",
       "7761872870     300.944910     847.110183     887.545230     829.870584   \n",
       "7761872869     300.926350     847.091623     887.526670     829.852025   \n",
       "6442044321     299.916518     846.081791     886.516838     828.842193   \n",
       "2142496418     301.370040     847.535313     887.970360     830.295715   \n",
       "2142496429     301.752414     847.917687     888.352734     830.678089   \n",
       "...                   ...            ...            ...            ...   \n",
       "9208004175  177263.413046  176793.395861  176827.212158  176776.156263   \n",
       "3884280043     811.794565     395.871235     436.306282     378.631636   \n",
       "3884280001     804.932338     389.009008     429.444055     371.769409   \n",
       "8592243457     780.725916     364.802586     405.237633     347.562987   \n",
       "3649149740     800.114039     384.190709     424.625757     366.951111   \n",
       "\n",
       "               6040927878     3449495495  ...     1968458114     9359670710  \\\n",
       "7761872870     745.470473     714.311023  ...     838.618647     894.287501   \n",
       "7761872869     745.451913     714.292464  ...     838.600087     894.268941   \n",
       "6442044321     744.442081     713.282632  ...     837.590255     893.259109   \n",
       "2142496418     745.895603     714.736154  ...     839.043777     894.712631   \n",
       "2142496429     746.277977     715.118528  ...     839.426151     895.095005   \n",
       "...                   ...            ...  ...            ...            ...   \n",
       "9208004175  176831.743755  176793.553866  ...  176679.123234  176622.095460   \n",
       "3884280043     394.022472     355.531399  ...     278.242294     257.235026   \n",
       "3884280001     387.160245     348.669172  ...     271.380067     250.372799   \n",
       "8592243457     362.953823     324.462750  ...     247.173644     226.166377   \n",
       "3649149740     382.341947     343.850873  ...     266.561768     245.554500   \n",
       "\n",
       "               6021177135     6027615161     6027276892     6041228287  \\\n",
       "7761872870     449.865800     449.572487     887.905120     880.637035   \n",
       "7761872869     449.847241     449.553928     887.886561     880.618476   \n",
       "6442044321     448.837409     448.544096     886.876729     879.608644   \n",
       "2142496418     450.290931     449.997618     888.330251     881.062166   \n",
       "2142496429     450.673305     450.379992     888.712625     881.444540   \n",
       "...                   ...            ...            ...            ...   \n",
       "9208004175  177326.944072  177326.650759  176834.190799  176815.557740   \n",
       "3884280043     633.873551     633.580238     436.666173     429.398088   \n",
       "3884280001     627.011324     626.718011     429.803946     422.535861   \n",
       "8592243457     620.604862     620.311550     405.597523     398.329438   \n",
       "3649149740     680.151566     679.858254     424.985647     417.717562   \n",
       "\n",
       "               5536661253     7357630367     8178147277     6026834850  \n",
       "7761872870     880.108771     880.021232     721.770522     720.768652  \n",
       "7761872869     880.090212     880.002672     721.751963     720.750093  \n",
       "6442044321     879.080380     878.992840     720.742131     719.740261  \n",
       "2142496418     880.533902     880.446362     722.195653     721.193783  \n",
       "2142496429     880.916276     880.828736     722.578027     721.576157  \n",
       "...                   ...            ...            ...            ...  \n",
       "9208004175  176814.667862  176814.561084  176795.662262  176796.661223  \n",
       "3884280043     428.869824     428.782284     364.724199     357.764104  \n",
       "3884280001     422.007597     421.920057     357.861972     350.901877  \n",
       "8592243457     397.801175     397.713635     333.655549     326.695455  \n",
       "3649149740     417.189298     417.101758     353.043673     346.083578  \n",
       "\n",
       "[74662 rows x 58 columns]"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create origin-specific matrix and save to file.\n",
    "OD_hamlet = OD_df.loc[list_hamlet,:]\n",
    "OD_hamlet = OD_hamlet[OD_hamlet < fail_value] / 60 \n",
    "OD_hamlet.to_csv(os.path.join(out_pth, 'OD_hamlet_pre-project_flood10.csv'))\n",
    "OD_hamlet"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "6058226279    1\n",
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      "4998093094    1\n",
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      "4321656809    1\n",
      "1697006012    1\n",
      "1901689169    1\n",
      "6032060028    1\n",
      "6040927878    1\n",
      "3449495495    1\n",
      "3990543961    1\n",
      "8972391475    1\n",
      "3418418812    1\n",
      "1983641803    1\n",
      "6014451367    1\n",
      "6027163276    1\n",
      "2833577858    1\n",
      "7321088861    1\n",
      "6045659373    1\n",
      "5528866190    1\n",
      "6027939517    1\n",
      "6031093257    1\n",
      "1883155712    1\n",
      "6026417971    1\n",
      "6031245697    1\n",
      "7493947593    1\n",
      "1859359090    1\n",
      "6053816462    1\n",
      "6027530676    1\n",
      "2988435647    1\n",
      "7838754747    1\n",
      "6053825179    1\n",
      "2988435792    1\n",
      "3036877534    1\n",
      "6056472223    1\n",
      "7460241128    1\n",
      "6028595154    1\n",
      "4053739078    1\n",
      "4071261250    1\n",
      "6014815775    1\n",
      "6024430122    1\n",
      "8229317581    1\n",
      "6027834438    1\n",
      "6024894515    1\n",
      "6024894530    1\n",
      "6024894513    1\n",
      "8169321141    1\n",
      "8200304626    1\n",
      "1968458114    1\n",
      "9359670710    1\n",
      "6021177135    1\n",
      "6027615161    1\n",
      "6027276892    1\n",
      "6041228287    1\n",
      "5536661253    1\n",
      "7357630367    1\n",
      "8178147277    1\n",
      "6026834850    1\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "print(OD_hamlet.isna().sum())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
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       "      <td>173631.591230</td>\n",
       "      <td>173632.590190</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3651042508</th>\n",
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       "    </tr>\n",
       "    <tr>\n",
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       "      <td>173626.827694</td>\n",
       "      <td>...</td>\n",
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       "      <td>173455.369288</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>3651042393</th>\n",
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       "      <td>173613.139387</td>\n",
       "      <td>173646.955684</td>\n",
       "      <td>173595.899789</td>\n",
       "      <td>173651.487281</td>\n",
       "      <td>173613.297391</td>\n",
       "      <td>...</td>\n",
       "      <td>173498.866760</td>\n",
       "      <td>173441.838985</td>\n",
       "      <td>174146.687598</td>\n",
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       "      <td>173634.411387</td>\n",
       "      <td>173634.304610</td>\n",
       "      <td>173615.405788</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>6323434997</th>\n",
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       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>967552 rows × 58 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               6058226279     6029307183     4998093094     2201506815  \\\n",
       "3507831609      83.755636    2682.494783     907.773435     784.117712   \n",
       "3507831510      90.114132    2688.853279     914.131931     790.476209   \n",
       "6188134127      25.237636    2623.976783     849.255434     725.599712   \n",
       "8631201421     722.161882    2169.322786    1057.566861     933.911139   \n",
       "8598305977     722.607483    2169.768387    1058.012463     934.356741   \n",
       "...                   ...            ...            ...            ...   \n",
       "3651042474  174281.469685  176391.596013  173668.603029  173714.722305   \n",
       "3651042508  174273.319430  176383.445758  173660.452774  173706.572050   \n",
       "3651042501  174278.814545  176388.940874  173665.947889  173712.067166   \n",
       "3651042393  174265.284243  176375.410571  173652.417587  173698.536863   \n",
       "6323434997  174345.712337  176455.838665  173732.845681  173778.964958   \n",
       "\n",
       "               4321656809     1697006012     1901689169     6032060028  \\\n",
       "3507831609     322.329962     868.495235     908.930282     851.255636   \n",
       "3507831510     328.688458     874.853731     915.288779     857.614133   \n",
       "6188134127     263.811962     809.977235     850.412282     792.737636   \n",
       "8631201421     655.162619    1018.288662    1058.723709    1001.049063   \n",
       "8598305977     655.608221    1018.734263    1059.169310    1001.494665   \n",
       "...                   ...            ...            ...            ...   \n",
       "3651042474  174099.342014  173629.324829  173663.141125  173612.085230   \n",
       "3651042508  174091.191759  173621.174574  173654.990870  173603.934975   \n",
       "3651042501  174096.686874  173626.669689  173660.485986  173609.430091   \n",
       "3651042393  174083.156572  173613.139387  173646.955684  173595.899789   \n",
       "6323434997  174163.584666  173693.567481  173727.383778  173676.327883   \n",
       "\n",
       "               6040927878     3449495495  ...     1968458114     9359670710  \\\n",
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       "8598305977     917.094554     885.935104  ...    1010.242727    1065.911581   \n",
       "...                   ...            ...  ...            ...            ...   \n",
       "3651042474  173667.672722  173629.482833  ...  173515.052202  173458.024427   \n",
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       "6323434997  173731.915375  173693.725486  ...  173579.294854  173522.267080   \n",
       "\n",
       "               6021177135     6027615161     6027276892     6041228287  \\\n",
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       "8598305977     425.820073     425.526761    1059.529201    1052.261116   \n",
       "...                   ...            ...            ...            ...   \n",
       "3651042474  174162.873039  174162.579727  173670.119766  173651.486707   \n",
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       "6323434997  174227.115692  174226.822379  173734.362419  173715.729360   \n",
       "\n",
       "               5536661253     7357630367     8178147277     6026834850  \n",
       "3507831609     901.493824     901.406284     743.155574     742.153704  \n",
       "3507831510     907.852320     907.764780     749.514071     748.512201  \n",
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       "8598305977    1051.732852    1051.645312     893.394603     892.392733  \n",
       "...                   ...            ...            ...            ...  \n",
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       "3651042508  173642.446574  173642.339797  173623.440975  173624.439935  \n",
       "3651042501  173647.941690  173647.834912  173628.936090  173629.935051  \n",
       "3651042393  173634.411387  173634.304610  173615.405788  173616.404748  \n",
       "6323434997  173714.839482  173714.732704  173695.833882  173696.832842  \n",
       "\n",
       "[967552 rows x 58 columns]"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create origin-specific matrix and save to file.\n",
    "OD_ag = OD_df.loc[list_ag,:]\n",
    "OD_ag = OD_ag[OD_ag < fail_value] / 60 \n",
    "OD_ag.to_csv(os.path.join(out_pth, 'OD_ag_pre-project_flood10.csv'))\n",
    "OD_ag"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "6058226279    2\n",
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      "2988435792    2\n",
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      "4071261250    2\n",
      "6014815775    2\n",
      "6024430122    2\n",
      "8229317581    2\n",
      "6027834438    2\n",
      "6024894515    2\n",
      "6024894530    2\n",
      "6024894513    2\n",
      "8169321141    2\n",
      "8200304626    2\n",
      "1968458114    2\n",
      "9359670710    2\n",
      "6021177135    2\n",
      "6027615161    2\n",
      "6027276892    2\n",
      "6041228287    2\n",
      "5536661253    2\n",
      "7357630367    2\n",
      "8178147277    2\n",
      "6026834850    2\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "print(OD_ag.isna().sum())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Filter 1st nearest"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Check each file to make sure nearest neighbor column is named correctly. If not, rename."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Reload from file even if already loaded. Quickest way to ensure NN is a column rather than only the index.\n",
    "OD_hamlet = os.path.join(out_pth, \"OD_hamlet_pre-project_flood10.csv\")\n",
    "OD_hamlet = pd.read_csv(OD_hamlet)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "OD_ag = os.path.join(out_pth, \"OD_ag_pre-project_flood10.csv\")\n",
    "OD_ag = pd.read_csv(OD_ag)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "OD_ag.rename(columns={'Unnamed: 0': 'NN'}, inplace=True) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "OD_hamlet.rename(columns={'Unnamed: 0': 'NN'}, inplace=True) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>477.316036</td>\n",
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       "      <td>908.380584</td>\n",
       "      <td>907.852320</td>\n",
       "      <td>907.764780</td>\n",
       "      <td>749.514071</td>\n",
       "      <td>748.512201</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>6188134127</td>\n",
       "      <td>25.237636</td>\n",
       "      <td>2623.976783</td>\n",
       "      <td>849.255434</td>\n",
       "      <td>725.599712</td>\n",
       "      <td>263.811962</td>\n",
       "      <td>809.977235</td>\n",
       "      <td>850.412282</td>\n",
       "      <td>792.737636</td>\n",
       "      <td>708.337525</td>\n",
       "      <td>...</td>\n",
       "      <td>801.485699</td>\n",
       "      <td>857.154553</td>\n",
       "      <td>412.732852</td>\n",
       "      <td>412.439539</td>\n",
       "      <td>850.772172</td>\n",
       "      <td>843.504087</td>\n",
       "      <td>842.975823</td>\n",
       "      <td>842.888283</td>\n",
       "      <td>684.637574</td>\n",
       "      <td>683.635704</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>8631201421</td>\n",
       "      <td>722.161882</td>\n",
       "      <td>2169.322786</td>\n",
       "      <td>1057.566861</td>\n",
       "      <td>933.911139</td>\n",
       "      <td>655.162619</td>\n",
       "      <td>1018.288662</td>\n",
       "      <td>1058.723709</td>\n",
       "      <td>1001.049063</td>\n",
       "      <td>916.648952</td>\n",
       "      <td>...</td>\n",
       "      <td>1009.797126</td>\n",
       "      <td>1065.465980</td>\n",
       "      <td>425.374472</td>\n",
       "      <td>425.081159</td>\n",
       "      <td>1059.083599</td>\n",
       "      <td>1051.815514</td>\n",
       "      <td>1051.287250</td>\n",
       "      <td>1051.199710</td>\n",
       "      <td>892.949001</td>\n",
       "      <td>891.947131</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>8598305977</td>\n",
       "      <td>722.607483</td>\n",
       "      <td>2169.768387</td>\n",
       "      <td>1058.012463</td>\n",
       "      <td>934.356741</td>\n",
       "      <td>655.608221</td>\n",
       "      <td>1018.734263</td>\n",
       "      <td>1059.169310</td>\n",
       "      <td>1001.494665</td>\n",
       "      <td>917.094554</td>\n",
       "      <td>...</td>\n",
       "      <td>1010.242727</td>\n",
       "      <td>1065.911581</td>\n",
       "      <td>425.820073</td>\n",
       "      <td>425.526761</td>\n",
       "      <td>1059.529201</td>\n",
       "      <td>1052.261116</td>\n",
       "      <td>1051.732852</td>\n",
       "      <td>1051.645312</td>\n",
       "      <td>893.394603</td>\n",
       "      <td>892.392733</td>\n",
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       "      <td>173663.141125</td>\n",
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       "      <td>173458.024427</td>\n",
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       "    <tr>\n",
       "      <th>967548</th>\n",
       "      <td>3651042508</td>\n",
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       "      <td>173449.874172</td>\n",
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       "      <th>967549</th>\n",
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       "      <td>173512.397062</td>\n",
       "      <td>173455.369288</td>\n",
       "      <td>174160.217900</td>\n",
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       "      <td>173648.831568</td>\n",
       "      <td>173647.941690</td>\n",
       "      <td>173647.834912</td>\n",
       "      <td>173628.936090</td>\n",
       "      <td>173629.935051</td>\n",
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       "    <tr>\n",
       "      <th>967550</th>\n",
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       "      <td>173441.838985</td>\n",
       "      <td>174146.687598</td>\n",
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       "      <th>967551</th>\n",
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       "      <td>173579.294854</td>\n",
       "      <td>173522.267080</td>\n",
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       "      <td>173714.839482</td>\n",
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       "      <td>173695.833882</td>\n",
       "      <td>173696.832842</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>967552 rows × 59 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                NN     6058226279     6029307183     4998093094  \\\n",
       "0       3507831609      83.755636    2682.494783     907.773435   \n",
       "1       3507831510      90.114132    2688.853279     914.131931   \n",
       "2       6188134127      25.237636    2623.976783     849.255434   \n",
       "3       8631201421     722.161882    2169.322786    1057.566861   \n",
       "4       8598305977     722.607483    2169.768387    1058.012463   \n",
       "...            ...            ...            ...            ...   \n",
       "967547  3651042474  174281.469685  176391.596013  173668.603029   \n",
       "967548  3651042508  174273.319430  176383.445758  173660.452774   \n",
       "967549  3651042501  174278.814545  176388.940874  173665.947889   \n",
       "967550  3651042393  174265.284243  176375.410571  173652.417587   \n",
       "967551  6323434997  174345.712337  176455.838665  173732.845681   \n",
       "\n",
       "           2201506815     4321656809     1697006012     1901689169  \\\n",
       "0          784.117712     322.329962     868.495235     908.930282   \n",
       "1          790.476209     328.688458     874.853731     915.288779   \n",
       "2          725.599712     263.811962     809.977235     850.412282   \n",
       "3          933.911139     655.162619    1018.288662    1058.723709   \n",
       "4          934.356741     655.608221    1018.734263    1059.169310   \n",
       "...               ...            ...            ...            ...   \n",
       "967547  173714.722305  174099.342014  173629.324829  173663.141125   \n",
       "967548  173706.572050  174091.191759  173621.174574  173654.990870   \n",
       "967549  173712.067166  174096.686874  173626.669689  173660.485986   \n",
       "967550  173698.536863  174083.156572  173613.139387  173646.955684   \n",
       "967551  173778.964958  174163.584666  173693.567481  173727.383778   \n",
       "\n",
       "           6032060028     6040927878  ...     1968458114     9359670710  \\\n",
       "0          851.255636     766.855525  ...     860.003699     915.672553   \n",
       "1          857.614133     773.214022  ...     866.362195     922.031049   \n",
       "2          792.737636     708.337525  ...     801.485699     857.154553   \n",
       "3         1001.049063     916.648952  ...    1009.797126    1065.465980   \n",
       "4         1001.494665     917.094554  ...    1010.242727    1065.911581   \n",
       "...               ...            ...  ...            ...            ...   \n",
       "967547  173612.085230  173667.672722  ...  173515.052202  173458.024427   \n",
       "967548  173603.934975  173659.522467  ...  173506.901947  173449.874172   \n",
       "967549  173609.430091  173665.017583  ...  173512.397062  173455.369288   \n",
       "967550  173595.899789  173651.487281  ...  173498.866760  173441.838985   \n",
       "967551  173676.327883  173731.915375  ...  173579.294854  173522.267080   \n",
       "\n",
       "           6021177135     6027615161     6027276892     6041228287  \\\n",
       "0          471.250852     470.957540     909.290172     902.022087   \n",
       "1          477.609349     477.316036     915.648669     908.380584   \n",
       "2          412.732852     412.439539     850.772172     843.504087   \n",
       "3          425.374472     425.081159    1059.083599    1051.815514   \n",
       "4          425.820073     425.526761    1059.529201    1052.261116   \n",
       "...               ...            ...            ...            ...   \n",
       "967547  174162.873039  174162.579727  173670.119766  173651.486707   \n",
       "967548  174154.722784  174154.429472  173661.969512  173643.336452   \n",
       "967549  174160.217900  174159.924587  173667.464627  173648.831568   \n",
       "967550  174146.687598  174146.394285  173653.934325  173635.301266   \n",
       "967551  174227.115692  174226.822379  173734.362419  173715.729360   \n",
       "\n",
       "           5536661253     7357630367     8178147277     6026834850  \n",
       "0          901.493824     901.406284     743.155574     742.153704  \n",
       "1          907.852320     907.764780     749.514071     748.512201  \n",
       "2          842.975823     842.888283     684.637574     683.635704  \n",
       "3         1051.287250    1051.199710     892.949001     891.947131  \n",
       "4         1051.732852    1051.645312     893.394603     892.392733  \n",
       "...               ...            ...            ...            ...  \n",
       "967547  173650.596829  173650.490051  173631.591230  173632.590190  \n",
       "967548  173642.446574  173642.339797  173623.440975  173624.439935  \n",
       "967549  173647.941690  173647.834912  173628.936090  173629.935051  \n",
       "967550  173634.411387  173634.304610  173615.405788  173616.404748  \n",
       "967551  173714.839482  173714.732704  173695.833882  173696.832842  \n",
       "\n",
       "[967552 rows x 59 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "OD_ag"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
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       "      <td>745.895603</td>\n",
       "      <td>...</td>\n",
       "      <td>839.043777</td>\n",
       "      <td>894.712631</td>\n",
       "      <td>450.290931</td>\n",
       "      <td>449.997618</td>\n",
       "      <td>888.330251</td>\n",
       "      <td>881.062166</td>\n",
       "      <td>880.533902</td>\n",
       "      <td>880.446362</td>\n",
       "      <td>722.195653</td>\n",
       "      <td>721.193783</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2142496429</td>\n",
       "      <td>64.752099</td>\n",
       "      <td>2661.917235</td>\n",
       "      <td>887.195887</td>\n",
       "      <td>763.540165</td>\n",
       "      <td>301.752414</td>\n",
       "      <td>847.917687</td>\n",
       "      <td>888.352734</td>\n",
       "      <td>830.678089</td>\n",
       "      <td>746.277977</td>\n",
       "      <td>...</td>\n",
       "      <td>839.426151</td>\n",
       "      <td>895.095005</td>\n",
       "      <td>450.673305</td>\n",
       "      <td>450.379992</td>\n",
       "      <td>888.712625</td>\n",
       "      <td>881.444540</td>\n",
       "      <td>880.916276</td>\n",
       "      <td>880.828736</td>\n",
       "      <td>722.578027</td>\n",
       "      <td>721.576157</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74657</th>\n",
       "      <td>9208004175</td>\n",
       "      <td>177445.540717</td>\n",
       "      <td>179555.667046</td>\n",
       "      <td>176832.674061</td>\n",
       "      <td>176878.793338</td>\n",
       "      <td>177263.413046</td>\n",
       "      <td>176793.395861</td>\n",
       "      <td>176827.212158</td>\n",
       "      <td>176776.156263</td>\n",
       "      <td>176831.743755</td>\n",
       "      <td>...</td>\n",
       "      <td>176679.123234</td>\n",
       "      <td>176622.095460</td>\n",
       "      <td>177326.944072</td>\n",
       "      <td>177326.650759</td>\n",
       "      <td>176834.190799</td>\n",
       "      <td>176815.557740</td>\n",
       "      <td>176814.667862</td>\n",
       "      <td>176814.561084</td>\n",
       "      <td>176795.662262</td>\n",
       "      <td>176796.661223</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74658</th>\n",
       "      <td>3884280043</td>\n",
       "      <td>993.922236</td>\n",
       "      <td>2928.538223</td>\n",
       "      <td>435.149435</td>\n",
       "      <td>441.072055</td>\n",
       "      <td>811.794565</td>\n",
       "      <td>395.871235</td>\n",
       "      <td>436.306282</td>\n",
       "      <td>378.631636</td>\n",
       "      <td>394.022472</td>\n",
       "      <td>...</td>\n",
       "      <td>278.242294</td>\n",
       "      <td>257.235026</td>\n",
       "      <td>633.873551</td>\n",
       "      <td>633.580238</td>\n",
       "      <td>436.666173</td>\n",
       "      <td>429.398088</td>\n",
       "      <td>428.869824</td>\n",
       "      <td>428.782284</td>\n",
       "      <td>364.724199</td>\n",
       "      <td>357.764104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74659</th>\n",
       "      <td>3884280001</td>\n",
       "      <td>987.060009</td>\n",
       "      <td>2921.675996</td>\n",
       "      <td>428.287208</td>\n",
       "      <td>434.209828</td>\n",
       "      <td>804.932338</td>\n",
       "      <td>389.009008</td>\n",
       "      <td>429.444055</td>\n",
       "      <td>371.769409</td>\n",
       "      <td>387.160245</td>\n",
       "      <td>...</td>\n",
       "      <td>271.380067</td>\n",
       "      <td>250.372799</td>\n",
       "      <td>627.011324</td>\n",
       "      <td>626.718011</td>\n",
       "      <td>429.803946</td>\n",
       "      <td>422.535861</td>\n",
       "      <td>422.007597</td>\n",
       "      <td>421.920057</td>\n",
       "      <td>357.861972</td>\n",
       "      <td>350.901877</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74660</th>\n",
       "      <td>8592243457</td>\n",
       "      <td>962.853587</td>\n",
       "      <td>2915.269535</td>\n",
       "      <td>404.080786</td>\n",
       "      <td>410.003406</td>\n",
       "      <td>780.725916</td>\n",
       "      <td>364.802586</td>\n",
       "      <td>405.237633</td>\n",
       "      <td>347.562987</td>\n",
       "      <td>362.953823</td>\n",
       "      <td>...</td>\n",
       "      <td>247.173644</td>\n",
       "      <td>226.166377</td>\n",
       "      <td>620.604862</td>\n",
       "      <td>620.311550</td>\n",
       "      <td>405.597523</td>\n",
       "      <td>398.329438</td>\n",
       "      <td>397.801175</td>\n",
       "      <td>397.713635</td>\n",
       "      <td>333.655549</td>\n",
       "      <td>326.695455</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74661</th>\n",
       "      <td>3649149740</td>\n",
       "      <td>982.241710</td>\n",
       "      <td>2974.816239</td>\n",
       "      <td>423.468909</td>\n",
       "      <td>429.391529</td>\n",
       "      <td>800.114039</td>\n",
       "      <td>384.190709</td>\n",
       "      <td>424.625757</td>\n",
       "      <td>366.951111</td>\n",
       "      <td>382.341947</td>\n",
       "      <td>...</td>\n",
       "      <td>266.561768</td>\n",
       "      <td>245.554500</td>\n",
       "      <td>680.151566</td>\n",
       "      <td>679.858254</td>\n",
       "      <td>424.985647</td>\n",
       "      <td>417.717562</td>\n",
       "      <td>417.189298</td>\n",
       "      <td>417.101758</td>\n",
       "      <td>353.043673</td>\n",
       "      <td>346.083578</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>74662 rows × 59 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               NN     6058226279     6029307183     4998093094     2201506815  \\\n",
       "0      7761872870      63.944594    2661.109731     886.388383     762.732660   \n",
       "1      7761872869      63.926035    2661.091171     886.369823     762.714101   \n",
       "2      6442044321      62.916203    2660.081339     885.359991     761.704269   \n",
       "3      2142496418      64.369725    2661.534861     886.813513     763.157791   \n",
       "4      2142496429      64.752099    2661.917235     887.195887     763.540165   \n",
       "...           ...            ...            ...            ...            ...   \n",
       "74657  9208004175  177445.540717  179555.667046  176832.674061  176878.793338   \n",
       "74658  3884280043     993.922236    2928.538223     435.149435     441.072055   \n",
       "74659  3884280001     987.060009    2921.675996     428.287208     434.209828   \n",
       "74660  8592243457     962.853587    2915.269535     404.080786     410.003406   \n",
       "74661  3649149740     982.241710    2974.816239     423.468909     429.391529   \n",
       "\n",
       "          4321656809     1697006012     1901689169     6032060028  \\\n",
       "0         300.944910     847.110183     887.545230     829.870584   \n",
       "1         300.926350     847.091623     887.526670     829.852025   \n",
       "2         299.916518     846.081791     886.516838     828.842193   \n",
       "3         301.370040     847.535313     887.970360     830.295715   \n",
       "4         301.752414     847.917687     888.352734     830.678089   \n",
       "...              ...            ...            ...            ...   \n",
       "74657  177263.413046  176793.395861  176827.212158  176776.156263   \n",
       "74658     811.794565     395.871235     436.306282     378.631636   \n",
       "74659     804.932338     389.009008     429.444055     371.769409   \n",
       "74660     780.725916     364.802586     405.237633     347.562987   \n",
       "74661     800.114039     384.190709     424.625757     366.951111   \n",
       "\n",
       "          6040927878  ...     1968458114     9359670710     6021177135  \\\n",
       "0         745.470473  ...     838.618647     894.287501     449.865800   \n",
       "1         745.451913  ...     838.600087     894.268941     449.847241   \n",
       "2         744.442081  ...     837.590255     893.259109     448.837409   \n",
       "3         745.895603  ...     839.043777     894.712631     450.290931   \n",
       "4         746.277977  ...     839.426151     895.095005     450.673305   \n",
       "...              ...  ...            ...            ...            ...   \n",
       "74657  176831.743755  ...  176679.123234  176622.095460  177326.944072   \n",
       "74658     394.022472  ...     278.242294     257.235026     633.873551   \n",
       "74659     387.160245  ...     271.380067     250.372799     627.011324   \n",
       "74660     362.953823  ...     247.173644     226.166377     620.604862   \n",
       "74661     382.341947  ...     266.561768     245.554500     680.151566   \n",
       "\n",
       "          6027615161     6027276892     6041228287     5536661253  \\\n",
       "0         449.572487     887.905120     880.637035     880.108771   \n",
       "1         449.553928     887.886561     880.618476     880.090212   \n",
       "2         448.544096     886.876729     879.608644     879.080380   \n",
       "3         449.997618     888.330251     881.062166     880.533902   \n",
       "4         450.379992     888.712625     881.444540     880.916276   \n",
       "...              ...            ...            ...            ...   \n",
       "74657  177326.650759  176834.190799  176815.557740  176814.667862   \n",
       "74658     633.580238     436.666173     429.398088     428.869824   \n",
       "74659     626.718011     429.803946     422.535861     422.007597   \n",
       "74660     620.311550     405.597523     398.329438     397.801175   \n",
       "74661     679.858254     424.985647     417.717562     417.189298   \n",
       "\n",
       "          7357630367     8178147277     6026834850  \n",
       "0         880.021232     721.770522     720.768652  \n",
       "1         880.002672     721.751963     720.750093  \n",
       "2         878.992840     720.742131     719.740261  \n",
       "3         880.446362     722.195653     721.193783  \n",
       "4         880.828736     722.578027     721.576157  \n",
       "...              ...            ...            ...  \n",
       "74657  176814.561084  176795.662262  176796.661223  \n",
       "74658     428.782284     364.724199     357.764104  \n",
       "74659     421.920057     357.861972     350.901877  \n",
       "74660     397.713635     333.655549     326.695455  \n",
       "74661     417.101758     353.043673     346.083578  \n",
       "\n",
       "[74662 rows x 59 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "OD_hamlet"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Find first, second, and third nearest destination for each origin node. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "fail_value = 999999999"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>NN</th>\n",
       "      <th>ag_HD1</th>\n",
       "      <th>ag_HD2</th>\n",
       "      <th>ag_HD3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3507831609</td>\n",
       "      <td>82.054823</td>\n",
       "      <td>83.755636</td>\n",
       "      <td>322.329962</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3507831510</td>\n",
       "      <td>88.413319</td>\n",
       "      <td>90.114132</td>\n",
       "      <td>328.688458</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>6188134127</td>\n",
       "      <td>23.536822</td>\n",
       "      <td>25.237636</td>\n",
       "      <td>263.811962</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>8631201421</td>\n",
       "      <td>419.573315</td>\n",
       "      <td>421.041963</td>\n",
       "      <td>425.081159</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>8598305977</td>\n",
       "      <td>420.018916</td>\n",
       "      <td>421.487564</td>\n",
       "      <td>425.526761</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           NN      ag_HD1      ag_HD2      ag_HD3\n",
       "0  3507831609   82.054823   83.755636  322.329962\n",
       "1  3507831510   88.413319   90.114132  328.688458\n",
       "2  6188134127   23.536822   25.237636  263.811962\n",
       "3  8631201421  419.573315  421.041963  425.081159\n",
       "4  8598305977  420.018916  421.487564  425.526761"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Nearest\n",
    "OD_ag[\"ag_HD1\"] = 0\n",
    "sub = OD_ag.iloc[:,1:-1] # Filtering out the newly created field and the node ID column. (\"include everything between column 0 and the last column\")\n",
    "OD_ag[\"ag_HD1\"] = sub.min(axis=1) # Default is axis=0, meaning min value of each column selected. We want min of each row.\n",
    "ag1 = OD_ag[['NN', 'ag_HD1']] # Remove unnecessary OD values.\n",
    "\n",
    "\n",
    "# Second nearest\n",
    "dupes = OD_ag.apply(pd.Series.duplicated, axis = 1, keep=False) # If a number is repeated within a row, value is True. If not, False.\n",
    "# The first time this is done, there should be two True values per row, unless any POIs are equidistant.\n",
    "dupes = OD_ag.where(~dupes, fail_value) # For any value that appears more than once in its row, it is replaced with the fail_value.\n",
    "OD_ag[\"ag_HD2\"] = 0\n",
    "Dsub = dupes.iloc[:,1:] # Filtering out the node ID column. No need to filter 1st nearest as its new \"dupes\" value is too high to be caught.\n",
    "OD_ag[\"ag_HD2\"] = Dsub.min(axis=1) \n",
    "ag2 = OD_ag.loc[:,['NN', 'ag_HD2']] \n",
    "\n",
    "\n",
    "# Third nearest\n",
    "dupes = OD_ag.apply(pd.Series.duplicated, axis = 1, keep=False)\n",
    "# Since this includes both first and second nearest columns, there should be four True values per row, unless POIs are equidistant.\n",
    "dupes = OD_ag.where(~dupes, fail_value)\n",
    "\n",
    "OD_ag[\"ag_HD3\"] = 0\n",
    "Dsub = dupes.iloc[:,1:] # Filtering out the node ID column.\n",
    "OD_ag[\"ag_HD3\"] = Dsub.min(axis=1)\n",
    "ag3 = OD_ag.loc[:,['NN', 'ag_HD3']]\n",
    "\n",
    "# Combine and write to file\n",
    "ag_all = OD_ag.loc[:,['NN', 'ag_HD1', 'ag_HD2', 'ag_HD3']]\n",
    "ag_all.to_csv(os.path.join(out_pth, 'ag_to_HDurban_drive_pre-project_flood10.csv'))\n",
    "ag_all.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>NN</th>\n",
       "      <th>ha_HD1</th>\n",
       "      <th>ha_HD2</th>\n",
       "      <th>ha_HD3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>7761872870</td>\n",
       "      <td>63.944594</td>\n",
       "      <td>67.312774</td>\n",
       "      <td>300.944910</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>7761872869</td>\n",
       "      <td>63.926035</td>\n",
       "      <td>67.294215</td>\n",
       "      <td>300.926350</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>6442044321</td>\n",
       "      <td>62.916203</td>\n",
       "      <td>66.284383</td>\n",
       "      <td>299.916518</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2142496418</td>\n",
       "      <td>64.369725</td>\n",
       "      <td>67.737905</td>\n",
       "      <td>301.370040</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2142496429</td>\n",
       "      <td>64.752099</td>\n",
       "      <td>68.120279</td>\n",
       "      <td>301.752414</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           NN     ha_HD1     ha_HD2      ha_HD3\n",
       "0  7761872870  63.944594  67.312774  300.944910\n",
       "1  7761872869  63.926035  67.294215  300.926350\n",
       "2  6442044321  62.916203  66.284383  299.916518\n",
       "3  2142496418  64.369725  67.737905  301.370040\n",
       "4  2142496429  64.752099  68.120279  301.752414"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Nearest\n",
    "OD_hamlet[\"ha_HD1\"] = 0\n",
    "sub = OD_hamlet.iloc[:,1:-1] # Filtering out the newly created field and the node ID column. (\"include everything between column 0 and the last column\")\n",
    "OD_hamlet[\"ha_HD1\"] = sub.min(axis=1) # Default is axis=0, meaning min value of each column selected. We want min of each row.\n",
    "hamlet1 = OD_hamlet[['NN', 'ha_HD1']] # Remove unnecessary OD values.\n",
    "\n",
    "\n",
    "# Second nearest\n",
    "dupes = OD_hamlet.apply(pd.Series.duplicated, axis = 1, keep=False) # If a number is repeated within a row, value is True. If not, False.\n",
    "# The first time this is done, there should be two True values per row, unless any POIs are equidistant.\n",
    "dupes = OD_hamlet.where(~dupes, fail_value) # For any value that appears more than once in its row, it is replaced with the fail_value.\n",
    "OD_hamlet[\"ha_HD2\"] = 0\n",
    "Dsub = dupes.iloc[:,1:] # Filtering out the node ID column. No need to filter 1st nearest as its new \"dupes\" value is too high to be caught.\n",
    "OD_hamlet[\"ha_HD2\"] = Dsub.min(axis=1) \n",
    "hamlet2 = OD_hamlet.loc[:,['NN', 'ha_HD2']] \n",
    "\n",
    "\n",
    "# Third nearest\n",
    "dupes = OD_hamlet.apply(pd.Series.duplicated, axis = 1, keep=False)\n",
    "# Since this includes both first and second nearest columns, there should be four True values per row, unless POIs are equidistant.\n",
    "dupes = OD_hamlet.where(~dupes, fail_value)\n",
    "OD_hamlet[\"ha_HD3\"] = 0\n",
    "Dsub = dupes.iloc[:,1:] # Filtering out the node ID column.\n",
    "OD_hamlet[\"ha_HD3\"] = Dsub.min(axis=1)\n",
    "hamlet3 = OD_hamlet.loc[:,['NN', 'ha_HD3']]\n",
    "\n",
    "\n",
    "# Combine and write to file\n",
    "hamlet_all = OD_hamlet.loc[:,['NN', 'ha_HD1', 'ha_HD2', 'ha_HD3']]\n",
    "hamlet_all.to_csv(os.path.join(out_pth, 'hamlet_to_HDurban_drive_pre-project_flood10.csv'))\n",
    "hamlet_all.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### End of script. Load into QGIS or Arc and visualize at 10 min intervals. \n",
    "QML file for symbology in QGIS:\n",
    "R:\\GEOGlobal\\Design\\symb_traveltimes_10min.qml"
   ]
  }
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