notebooks/02_multigroup_indices.ipynb

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  {
   "cell_type": "markdown",
   "id": "nominated-breakdown",
   "metadata": {},
   "source": [
    "# Multi-group Segregation Indices"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "ef04f168-d859-4c12-a3e0-aff7df0b0b2a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Author: eli knaap\n",
      "\n",
      "Last updated: 2021-05-09\n",
      "\n",
      "Python implementation: CPython\n",
      "Python version       : 3.9.2\n",
      "IPython version      : 7.23.1\n",
      "\n",
      "segregation: 2.0.0\n",
      "geopandas  : 0.9.0\n",
      "libpysal   : 4.3.0\n",
      "pandana    : 0.6.1\n",
      "\n"
     ]
    }
   ],
   "source": [
    "%load_ext watermark\n",
    "%watermark -a 'eli knaap' -v -d -u -p segregation,geopandas,libpysal,pandana"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b580cc30-29dc-4561-9513-a141ba39514b",
   "metadata": {},
   "source": [
    "Classes for computing multigroup segregation indices are in the `multigroup` module"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "bf5fb7d9-8843-4eaa-818d-b25acf9e2345",
   "metadata": {},
   "outputs": [],
   "source": [
    "import geopandas as gpd\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "from libpysal.examples import load_example\n",
    "from segregation.multigroup import MultiDissim, MultiInfoTheory"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "9f20f5a1-8d25-4976-89ba-ed66905f5650",
   "metadata": {},
   "outputs": [],
   "source": [
    "sacramento = gpd.read_file(load_example(\"Sacramento1\").get_path(\"sacramentot2.shp\"))\n",
    "sacramento = sacramento.to_crs(sacramento.estimate_utm_crs())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fe313580-070e-48d1-9ad7-4925fdadc22c",
   "metadata": {},
   "source": [
    "## Aspatial Segregation Indices"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "441a1c53-a267-4f24-919a-19aa8a6770c5",
   "metadata": {},
   "outputs": [],
   "source": [
    "multi_dissim = MultiDissim(sacramento, groups=['WHITE', 'BLACK', 'HISP'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "ee2a6015-9703-490f-8a98-e0e340e76b72",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.42469982288295693"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "multi_dissim.statistic"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "19252c53-8411-4850-88c5-347b4d0347df",
   "metadata": {},
   "outputs": [],
   "source": [
    "multi_info = MultiInfoTheory(sacramento, groups=['WHITE', 'BLACK', 'HISP'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "9e960e74-2b96-49ee-b0d0-55f27757169e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.1800803002655424"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "multi_info.statistic"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f2f95a02-ae16-4210-9919-33a4646824ce",
   "metadata": {},
   "source": [
    "## Spatial Segregation Indices"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ba6ecd48-d155-4169-962c-1778bcdf8f89",
   "metadata": {},
   "source": [
    "As with single group measures, generalized spatial versions of multigroup indices can be created by passing a distance parameter or a `W`/`Network` object."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "980b6183-b060-4a57-bcbf-ff7a2224911f",
   "metadata": {},
   "outputs": [],
   "source": [
    "spatial_multi_dissim = MultiDissim(sacramento, groups=['WHITE', 'BLACK', 'HISP'], distance=2000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "1998948e-0a9e-447a-8be6-d2f63724ff2b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.3776841098505291"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "spatial_multi_dissim.statistic"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "088ca7ac-361b-441e-ae3a-2c37827017a3",
   "metadata": {},
   "outputs": [],
   "source": [
    "from pandana import Network"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "781fb45f-be69-4c19-8463-3305ae74894a",
   "metadata": {},
   "outputs": [],
   "source": [
    "net = Network.from_hdf5(\"../40900.h5\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "97b73a0c-c329-417a-8011-33ce2f44332a",
   "metadata": {},
   "outputs": [],
   "source": [
    "net_multi_dissim  = MultiDissim(sacramento, groups=['WHITE', 'BLACK', 'HISP'], distance=2000, network=net, decay='linear')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "60add795-76ed-4a4a-8ee6-4be5060c3a30",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.3997196467720179"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "net_multi_dissim.statistic"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9835fd10-7fe3-429f-962c-a8329a621454",
   "metadata": {},
   "source": [
    "## Batch-Computing Multi-Group Measures"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5359e559-509e-46b2-8d1d-c727688a8393",
   "metadata": {},
   "source": [
    "To compute all single group indices in one go, the package provides a wrapper function in the `batch` module similar to single-group indices"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "58e47a6b-6f34-473a-9312-bc537713a556",
   "metadata": {},
   "outputs": [],
   "source": [
    "from segregation.batch import batch_compute_multigroup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "f41712ce-8923-4df8-8f46-13b21adf99c9",
   "metadata": {},
   "outputs": [],
   "source": [
    "all_multigroup = batch_compute_multigroup(sacramento, groups=['WHITE', 'BLACK', 'HISP'],)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "39ad47fa-51b1-4b52-bb9e-ff0b8227f3b7",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Statistic</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>MultiDissim</th>\n",
       "      <td>0.424700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MultiDivergence</th>\n",
       "      <td>0.131709</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MultiDiversity</th>\n",
       "      <td>0.731390</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MultiGini</th>\n",
       "      <td>0.556467</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MultiInfoTheory</th>\n",
       "      <td>0.180080</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MultiNormExposure</th>\n",
       "      <td>0.191362</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MultiRelativeDiversity</th>\n",
       "      <td>0.168574</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MultiSquaredCoefVar</th>\n",
       "      <td>0.145315</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SimpsonsConcentration</th>\n",
       "      <td>0.587698</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SimpsonsInteraction</th>\n",
       "      <td>0.412302</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "                        Statistic\n",
       "MultiDissim              0.424700\n",
       "MultiDivergence          0.131709\n",
       "MultiDiversity           0.731390\n",
       "MultiGini                0.556467\n",
       "MultiInfoTheory          0.180080\n",
       "MultiNormExposure        0.191362\n",
       "MultiRelativeDiversity   0.168574\n",
       "MultiSquaredCoefVar      0.145315\n",
       "SimpsonsConcentration    0.587698\n",
       "SimpsonsInteraction      0.412302"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_multigroup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0b023ec4-34ea-4646-9572-fa78062ade9c",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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