12_geospatial_02_spatial_weighting_matrix.ipynb

{
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  {
   "cell_type": "markdown",
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   "source": [
    "# Spatial Weighting ****\n",
    "\n",
    "#### Tutorial from https://geographicdata.science/book/notebooks/04_spatial_weights.html\n",
    "\n",
    "This tutorial demonstrates how to create spatial weighting matrices and visualize them. A very useful tutorial."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
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      "    Uninstalling python-dateutil-2.8.1:\n",
      "      Successfully uninstalled python-dateutil-2.8.1\n",
      "Successfully installed access-1.1.2 coverage-5.3 esda-2.3.1 giddy-2.3.3 inequality-1.0.0 libpysal-4.3.0 mgwr-2.1.2 opencv-contrib-python-4.4.0.46 pointpats-2.2.0 pysal-2.3.0 pytest-cov-2.10.1 python-dateutil-2.8.0 quantecon-0.4.8 rasterstats-0.15.0 segregation-1.4.0 simplejson-3.17.2 spaghetti-1.5.3 spglm-1.0.8 spint-1.0.7 splot-1.1.3 spreg-1.1.2.post1 spvcm-0.3.0 tobler-0.4.0 urllib3-1.24.3\n"
     ]
    }
   ],
   "source": [
    "!pip install pysal"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "from pysal.lib import weights\n",
    "from pysal.lib import cg as geometry\n",
    "import contextily\n",
    "import geopandas\n",
    "import seaborn\n",
    "import pandas \n",
    "import numpy\n",
    "import matplotlib.pyplot as plt\n",
    "from shapely.geometry import Polygon"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([[0, 1, 2],\n",
       "        [0, 1, 2],\n",
       "        [0, 1, 2]]),\n",
       " array([[0, 0, 0],\n",
       "        [1, 1, 1],\n",
       "        [2, 2, 2]]))"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Get points in a grid\n",
    "l = numpy.arange(3)\n",
    "xs, ys = numpy.meshgrid(l, l)\n",
    "xs, ys"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<shapely.geometry.polygon.Polygon at 0x7fa627bef690>,\n",
       " <shapely.geometry.polygon.Polygon at 0x7fa627bef790>,\n",
       " <shapely.geometry.polygon.Polygon at 0x7fa627bec390>,\n",
       " <shapely.geometry.polygon.Polygon at 0x7fa627d62e50>,\n",
       " <shapely.geometry.polygon.Polygon at 0x7fa627bec490>,\n",
       " <shapely.geometry.polygon.Polygon at 0x7fa627bec590>,\n",
       " <shapely.geometry.polygon.Polygon at 0x7fa627bec410>,\n",
       " <shapely.geometry.polygon.Polygon at 0x7fa627f4b390>,\n",
       " <shapely.geometry.polygon.Polygon at 0x7fa627bec3d0>]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Set up store\n",
    "polys = []\n",
    "# Generate polygons\n",
    "for x, y in zip(xs.flatten(), ys.flatten()): # sw: learn to use zip.\n",
    "    poly = Polygon([(x, y), (x+1, y), (x+1, y+1), (x, y+1)]) # sw: use Polygon to create geometry obj.\n",
    "    polys.append(poly)\n",
    "polys    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>geometry</th>\n",
       "      <th>id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>POLYGON ((0.00000 0.00000, 1.00000 0.00000, 1....</td>\n",
       "      <td>P-00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>POLYGON ((1.00000 0.00000, 2.00000 0.00000, 2....</td>\n",
       "      <td>P-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>POLYGON ((2.00000 0.00000, 3.00000 0.00000, 3....</td>\n",
       "      <td>P-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>POLYGON ((0.00000 1.00000, 1.00000 1.00000, 1....</td>\n",
       "      <td>P-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>POLYGON ((1.00000 1.00000, 2.00000 1.00000, 2....</td>\n",
       "      <td>P-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>POLYGON ((2.00000 1.00000, 3.00000 1.00000, 3....</td>\n",
       "      <td>P-05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>POLYGON ((0.00000 2.00000, 1.00000 2.00000, 1....</td>\n",
       "      <td>P-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>POLYGON ((1.00000 2.00000, 2.00000 2.00000, 2....</td>\n",
       "      <td>P-07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>POLYGON ((2.00000 2.00000, 3.00000 2.00000, 3....</td>\n",
       "      <td>P-08</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                            geometry    id\n",
       "0  POLYGON ((0.00000 0.00000, 1.00000 0.00000, 1....  P-00\n",
       "1  POLYGON ((1.00000 0.00000, 2.00000 0.00000, 2....  P-01\n",
       "2  POLYGON ((2.00000 0.00000, 3.00000 0.00000, 3....  P-02\n",
       "3  POLYGON ((0.00000 1.00000, 1.00000 1.00000, 1....  P-03\n",
       "4  POLYGON ((1.00000 1.00000, 2.00000 1.00000, 2....  P-04\n",
       "5  POLYGON ((2.00000 1.00000, 3.00000 1.00000, 3....  P-05\n",
       "6  POLYGON ((0.00000 2.00000, 1.00000 2.00000, 1....  P-06\n",
       "7  POLYGON ((1.00000 2.00000, 2.00000 2.00000, 2....  P-07\n",
       "8  POLYGON ((2.00000 2.00000, 3.00000 2.00000, 3....  P-08"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Convert to GeoSeries\n",
    "polys = geopandas.GeoSeries(polys) # sw: learn to create a geo data series\n",
    "gdf = geopandas.GeoDataFrame({'geometry': polys, # sw: create a geo df from a geo series.\n",
    "                              'id': ['P-%s'%str(i).zfill(2) for i in range(len(polys))]})\n",
    "gdf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# visualize the mesh\n",
    "ax = gdf.plot(facecolor='w', edgecolor='k') # sw: visualize the mesh as a geopandas object.\n",
    "[plt.text(x, y, t, \n",
    "          verticalalignment='center',\n",
    "          horizontalalignment='center') for x, y, t in zip(\n",
    "          [p.centroid.x-.25 for p in polys],\n",
    "          [p.centroid.y-.25 for p in polys],\n",
    "          [i for i in gdf['id']])] # sw: iterate over texts. p is an object to use. \n",
    "ax.set_axis_off()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{0: [1, 3],\n",
       " 1: [0, 2, 4],\n",
       " 2: [1, 5],\n",
       " 3: [0, 4, 6],\n",
       " 4: [1, 3, 5, 7],\n",
       " 5: [8, 2, 4],\n",
       " 6: [3, 7],\n",
       " 7: [8, 4, 6],\n",
       " 8: [5, 7]}"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Rook contiguity\n",
    "# do a regular 3x3 lattice and draw it here\n",
    "w = weights.contiguity.Rook.from_dataframe(gdf) # sw: here is how to turn a geo df to a graph!\n",
    "w.neighbors\n",
    "# sw: w is a very versertile obj. Learn it. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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Oy9fEUAM9CI54cGPOOX++jIcO2asBCuZa9CDo8mB/ztnrKUSGgOi0P1vBRVPpQaAHID4+tngNWDit/qU8eVJqeOABezVAQcegB0GRh1hwY87pyDdCYoYeBEc8uDHnDAZlDIft1QAFHYMeBF0e7M85rTJiSM/wqRd6EBzx4EbnPH1axpkz7dUABR2DHgRdHjzeOf/803YFOqAHwREPbnTOQEDGujp7NUBBx6AHQZcHj3dOR74REjP0IDjiwY3OeeaMjNOm2asBCjoGPQi6POi9BOCQcP68LF6HHgRHPLjRObOyZDxyxF4NUNAx6EHQ5cHjc87Ro21XoAN6EBzx4EbnjO7CWD4lovWOQQ+CLg8e75zRD50dOV9pv6EHwREPbnTO6EVYjx61VwMUdAx6EHR58HjnTEiwXYEO6EFwxIMbnbO5WcZ77rFXAxR0DHoQdHnw+OecP/8si9ehB8ERD250zowMGevr7dUABR2DHgRdHjw+50xMtF2BDuhBcMSDG52zrU3GpCR7NUBBx6AHQZcHj885a2utX2JcBfQgOOLBjc6Zni7jsWP2aoCCjkEPgi4PHp9zOnJVqZihB8ERD250zo4OGceMsVcDFHQMehB0efD4nPO772TxOvQgOOLBjc45d66Mx4/bqwEKOgY9CLo8eHzOOX687Qp0QA+CIx7c6JzR0+9bPrGT9Y5BD4IuDx6fc1ZVyeJ16EFwxIMbnXPOHBlPnLBXAxR0DHoQdHnweOecOBE4e1b+UyoqZLemsFDeGKiqkrfW8/Plw+k9e+TrXQsWyBekq6vlEKO8PDlIt6ZGTnORmysniqqtlVMt5uTIyYrDYTnSfv58uWBOfb1ccm7ePLku5MmTclswCGRny33DYXlsTo6sq7ZW1p2bK9uqqZFa8vKklupqwO+XmtvapOb0dKCgQJ5LVZU8t8JCea4VFfLcGxvpIeph4kQ7r8UBxI1w7t///2f59jJZWfQAiIf9+21XETNu7NYqwfrunBLoQeBuLSGOwnASohSGkxClMJyEKIXhJEQpDCchSmE4CVEKw0mIUhhOQpTCcBKilEEPZ1xcHILBIDIyMrB06VJ0RM/vchstLS0oKSnBrFmzUFJSgtbWVgCAMQYvv/wy0tLSkJWVhUOHDg12uYNCLA5OnDiBgoICjB49Gu++++5Qlz6gxOLho48+QlZWFjIzM1FYWIi6urqhLn/IGfRwJiQkIBwOo76+HqNGjcKmTZu63aesrAyhUAgNDQ0IhUIoKysDAFRWVqKhoQENDQ344IMPsHLlysEud1CIxcGECROwYcMGrF69eqjLHnBi8TBjxgxUV1fj6NGjeP311/HCCy8MdflDzpDu1hYVFeHUqVPdbi8vL0dpaSkAoLS0FLt27eq6/bnnnoPP50N+fj4uXbqESCQylCUPOP/WwaRJk5Cbm4uRlo/qH2j+rYfCwkKMv3X6kfz8fJw9e3bIarXFkIWzs7MTlZWVyIxe2PQ2mpqakJKSAgBITk5GU1MTAKCxsRHTpk3rut/UqVPR2Ng4NAUPAv1x4CKxeti8eTMWLVo06HXaZtBP8HX16lUEg0EA8tdy+fLlfd7f5/PB5+v3UTYqoQNhIDx8++232Lx5M/bt2zdYZaph0MMZnWfczrJly3D48GGkpqZi9+7dmDx5MiKRCFJSUhCJRDBp0iQAwJQpU3DmzJmux509exZTpkwZ7JIHnFgcuESsHo4cOYIVK1agsrISEx0408E/YeWjlK1btyIcDmP37t0AgCeeeALbtm0DAGzbtg1PPvlk1+3bt2+HMQY//PADkpKSunZ5hjt36sB17tTD77//jsWLF2PHjh2YPXu2tXqHFGNMzIuspmcSExN7/V2U5uZmU1xcbNLS0kwoFDIXL140xhhz8+ZN89JLL5mZM2eajIwMU1tb+4/rsklvHmJxEIlEzJQpU8zdd99tkpKSzJQpU0xbW9uA1j3QDIaH5cuXm3HjxplAIGACgYDJzs4e0JoHg1se+p0rnqZkAOHpOQR6EHiaEkIcheEkRCkMJyFKYTgJUQrDSYhSGE5ClMJwEqIUhpMQpTCchCiF4SREKQwnIUphOAlRyoAdz+niwcH9gR4EegDi4+PbY3n8gByVQggZeLhbS4hSGE5ClMJwEqIUhpMQpTCchCiF4SREKQwnIUphOAlRCsNJiFIYTkKUwnASohSGkxClMJyEKIXhJEQpDCchSvk/qrFUvew/AG4AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# visualize the new lattice\n",
    "f,ax = plt.subplots(1,1, subplot_kw=dict(aspect='equal')) # sw: two overlapping lattice plots.\n",
    "w.plot(gdf, edge_kws=dict(color='r', linestyle=':'), ax =ax) # sw: plot the red dash lines.\n",
    "gdf.plot(facecolor='w', edgecolor='k', ax=ax) # sw: plot the black grids.\n",
    "[ax.text(x, y, t, \n",
    "          verticalalignment='center',\n",
    "          horizontalalignment='center') for x, y, t in zip(\n",
    "         [p.centroid.x-.25 for p in polys],\n",
    "         [p.centroid.y-.25 for p in polys],\n",
    "         [i for i in gdf['id']])] # sw: plot the texts\n",
    "plt.gca().set_axis_off() # sw: turn off the axis\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   0  1  2  3  4  5  6  7  8\n",
       "0  0  1  0  1  0  0  0  0  0\n",
       "1  1  0  1  0  1  0  0  0  0\n",
       "2  0  1  0  0  0  1  0  0  0\n",
       "3  1  0  0  0  1  0  1  0  0\n",
       "4  0  1  0  1  0  1  0  1  0\n",
       "5  0  0  1  0  1  0  0  0  1\n",
       "6  0  0  0  1  0  0  0  1  0\n",
       "7  0  0  0  0  1  0  1  0  1\n",
       "8  0  0  0  0  0  1  0  1  0"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# sw: turn w to a full adjacency matrix using w.full().\n",
    "pandas.DataFrame(*w.full()).astype(int)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{0: [1, 3, 4],\n",
       " 1: [0, 2, 3, 4, 5],\n",
       " 2: [1, 4, 5],\n",
       " 3: [0, 1, 4, 6, 7],\n",
       " 4: [0, 1, 2, 3, 5, 6, 7, 8],\n",
       " 5: [1, 2, 4, 7, 8],\n",
       " 6: [3, 4, 7],\n",
       " 7: [3, 4, 5, 6, 8],\n",
       " 8: [4, 5, 7]}"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Queen contiguity\n",
    "# do a regular 3x3 lattice and draw it here\n",
    "w = weights.contiguity.Queen.from_dataframe(gdf)\n",
    "w.neighbors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot similar to above.\n",
    "f,ax = plt.subplots(1,1, subplot_kw=dict(aspect='equal'))\n",
    "w.plot(gdf, edge_kws=dict(color='r', linestyle=':'), ax =ax)\n",
    "gdf.plot(facecolor='w', edgecolor='k', ax=ax)\n",
    "[ax.text(x, y, t, \n",
    "          verticalalignment='center',\n",
    "          horizontalalignment='center') for x, y, t in zip(\n",
    "         [p.centroid.x-.25 for p in polys],\n",
    "         [p.centroid.y-.25 for p in polys],\n",
    "         [i for i in gdf['id']])]\n",
    "plt.gca().set_axis_off()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{0: [1.0, 1.0, 1.0],\n",
       " 1: [1.0, 1.0, 1.0, 1.0, 1.0],\n",
       " 2: [1.0, 1.0, 1.0],\n",
       " 3: [1.0, 1.0, 1.0, 1.0, 1.0],\n",
       " 4: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0],\n",
       " 5: [1.0, 1.0, 1.0, 1.0, 1.0],\n",
       " 6: [1.0, 1.0, 1.0],\n",
       " 7: [1.0, 1.0, 1.0, 1.0, 1.0],\n",
       " 8: [1.0, 1.0, 1.0]}"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "w.weights"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{0: 3, 1: 5, 2: 3, 3: 5, 4: 8, 5: 5, 6: 3, 7: 5, 8: 3}"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "w.cardinalities # sw: cardinalities of each node"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(3, 4), (4, 0), (5, 4), (6, 0), (7, 0), (8, 1)]"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "w.histogram # sw: histogram of the cardinalities"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:ylabel='Frequency'>"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "pandas.Series(w.cardinalities).plot.hist(color = 'k')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "40.0"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "w.s0 # sw: what is this?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "49.382716049382715"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "w.pct_nonzero # density of spatial weighting. sw: what is it?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Spatial weights from real-world data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>GEOID</th>\n",
       "      <th>median_age</th>\n",
       "      <th>total_pop</th>\n",
       "      <th>total_pop_white</th>\n",
       "      <th>tt_work</th>\n",
       "      <th>hh_total</th>\n",
       "      <th>hh_female</th>\n",
       "      <th>total_bachelor</th>\n",
       "      <th>median_hh_income</th>\n",
       "      <th>income_gini</th>\n",
       "      <th>...</th>\n",
       "      <th>state</th>\n",
       "      <th>county</th>\n",
       "      <th>tract</th>\n",
       "      <th>area_sqm</th>\n",
       "      <th>pct_rented</th>\n",
       "      <th>pct_hh_female</th>\n",
       "      <th>pct_bachelor</th>\n",
       "      <th>pct_white</th>\n",
       "      <th>sub_30</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>06073018300</td>\n",
       "      <td>37.1</td>\n",
       "      <td>2590.0</td>\n",
       "      <td>2375.0</td>\n",
       "      <td>1299.0</td>\n",
       "      <td>2590.0</td>\n",
       "      <td>137.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>62500.0</td>\n",
       "      <td>0.5355</td>\n",
       "      <td>...</td>\n",
       "      <td>06</td>\n",
       "      <td>073</td>\n",
       "      <td>018300</td>\n",
       "      <td>2.876449</td>\n",
       "      <td>0.373913</td>\n",
       "      <td>0.052896</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.916988</td>\n",
       "      <td>False</td>\n",
       "      <td>POLYGON ((-13069450.120 3922380.770, -13069175...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>06073018601</td>\n",
       "      <td>41.2</td>\n",
       "      <td>5147.0</td>\n",
       "      <td>4069.0</td>\n",
       "      <td>1970.0</td>\n",
       "      <td>5147.0</td>\n",
       "      <td>562.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>88165.0</td>\n",
       "      <td>0.4265</td>\n",
       "      <td>...</td>\n",
       "      <td>06</td>\n",
       "      <td>073</td>\n",
       "      <td>018601</td>\n",
       "      <td>4.548797</td>\n",
       "      <td>0.205144</td>\n",
       "      <td>0.109190</td>\n",
       "      <td>0.004663</td>\n",
       "      <td>0.790558</td>\n",
       "      <td>False</td>\n",
       "      <td>POLYGON ((-13067719.770 3922939.420, -13067631...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>06073017601</td>\n",
       "      <td>54.4</td>\n",
       "      <td>5595.0</td>\n",
       "      <td>4925.0</td>\n",
       "      <td>1702.0</td>\n",
       "      <td>5595.0</td>\n",
       "      <td>442.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>110804.0</td>\n",
       "      <td>0.4985</td>\n",
       "      <td>...</td>\n",
       "      <td>06</td>\n",
       "      <td>073</td>\n",
       "      <td>017601</td>\n",
       "      <td>8.726275</td>\n",
       "      <td>0.279029</td>\n",
       "      <td>0.078999</td>\n",
       "      <td>0.006077</td>\n",
       "      <td>0.880250</td>\n",
       "      <td>False</td>\n",
       "      <td>POLYGON ((-13058166.110 3907247.690, -13058140...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>06073019301</td>\n",
       "      <td>42.3</td>\n",
       "      <td>7026.0</td>\n",
       "      <td>5625.0</td>\n",
       "      <td>3390.0</td>\n",
       "      <td>7026.0</td>\n",
       "      <td>638.0</td>\n",
       "      <td>46.0</td>\n",
       "      <td>100539.0</td>\n",
       "      <td>0.4003</td>\n",
       "      <td>...</td>\n",
       "      <td>06</td>\n",
       "      <td>073</td>\n",
       "      <td>019301</td>\n",
       "      <td>3.519743</td>\n",
       "      <td>0.196512</td>\n",
       "      <td>0.090806</td>\n",
       "      <td>0.006547</td>\n",
       "      <td>0.800598</td>\n",
       "      <td>False</td>\n",
       "      <td>POLYGON ((-13056896.290 3925255.610, -13056868...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>06073018700</td>\n",
       "      <td>21.8</td>\n",
       "      <td>40402.0</td>\n",
       "      <td>30455.0</td>\n",
       "      <td>24143.0</td>\n",
       "      <td>40402.0</td>\n",
       "      <td>2456.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>41709.0</td>\n",
       "      <td>0.3196</td>\n",
       "      <td>...</td>\n",
       "      <td>06</td>\n",
       "      <td>073</td>\n",
       "      <td>018700</td>\n",
       "      <td>559.150793</td>\n",
       "      <td>0.949887</td>\n",
       "      <td>0.060789</td>\n",
       "      <td>0.000569</td>\n",
       "      <td>0.753799</td>\n",
       "      <td>False</td>\n",
       "      <td>POLYGON ((-13090788.510 3946435.430, -13090736...</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>623</th>\n",
       "      <td>06073020709</td>\n",
       "      <td>41.6</td>\n",
       "      <td>7848.0</td>\n",
       "      <td>5633.0</td>\n",
       "      <td>3512.0</td>\n",
       "      <td>7848.0</td>\n",
       "      <td>808.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>95132.0</td>\n",
       "      <td>0.3628</td>\n",
       "      <td>...</td>\n",
       "      <td>06</td>\n",
       "      <td>073</td>\n",
       "      <td>020709</td>\n",
       "      <td>107.593049</td>\n",
       "      <td>0.127660</td>\n",
       "      <td>0.102956</td>\n",
       "      <td>0.011213</td>\n",
       "      <td>0.717762</td>\n",
       "      <td>False</td>\n",
       "      <td>POLYGON ((-13029476.960 3912060.390, -13029476...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>624</th>\n",
       "      <td>06073020805</td>\n",
       "      <td>36.2</td>\n",
       "      <td>3624.0</td>\n",
       "      <td>2759.0</td>\n",
       "      <td>1681.0</td>\n",
       "      <td>3624.0</td>\n",
       "      <td>392.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>63820.0</td>\n",
       "      <td>0.3498</td>\n",
       "      <td>...</td>\n",
       "      <td>06</td>\n",
       "      <td>073</td>\n",
       "      <td>020805</td>\n",
       "      <td>7.239568</td>\n",
       "      <td>0.341730</td>\n",
       "      <td>0.108168</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.761313</td>\n",
       "      <td>False</td>\n",
       "      <td>POLYGON ((-13014919.160 3898901.850, -13014868...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>625</th>\n",
       "      <td>06073020810</td>\n",
       "      <td>44.5</td>\n",
       "      <td>5261.0</td>\n",
       "      <td>4977.0</td>\n",
       "      <td>2101.0</td>\n",
       "      <td>5261.0</td>\n",
       "      <td>617.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>106319.0</td>\n",
       "      <td>0.3336</td>\n",
       "      <td>...</td>\n",
       "      <td>06</td>\n",
       "      <td>073</td>\n",
       "      <td>020810</td>\n",
       "      <td>39.028783</td>\n",
       "      <td>0.111605</td>\n",
       "      <td>0.117278</td>\n",
       "      <td>0.004942</td>\n",
       "      <td>0.946018</td>\n",
       "      <td>False</td>\n",
       "      <td>POLYGON ((-13009524.170 3896636.950, -13009524...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>626</th>\n",
       "      <td>06073021206</td>\n",
       "      <td>46.0</td>\n",
       "      <td>3065.0</td>\n",
       "      <td>2628.0</td>\n",
       "      <td>1373.0</td>\n",
       "      <td>3065.0</td>\n",
       "      <td>303.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>104375.0</td>\n",
       "      <td>0.4050</td>\n",
       "      <td>...</td>\n",
       "      <td>06</td>\n",
       "      <td>073</td>\n",
       "      <td>021206</td>\n",
       "      <td>42.849263</td>\n",
       "      <td>0.098882</td>\n",
       "      <td>0.098858</td>\n",
       "      <td>0.004894</td>\n",
       "      <td>0.857423</td>\n",
       "      <td>False</td>\n",
       "      <td>POLYGON ((-13002757.840 3875229.320, -13002735...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>627</th>\n",
       "      <td>06073021000</td>\n",
       "      <td>60.6</td>\n",
       "      <td>2693.0</td>\n",
       "      <td>2268.0</td>\n",
       "      <td>693.0</td>\n",
       "      <td>2693.0</td>\n",
       "      <td>422.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>39760.0</td>\n",
       "      <td>0.4416</td>\n",
       "      <td>...</td>\n",
       "      <td>06</td>\n",
       "      <td>073</td>\n",
       "      <td>021000</td>\n",
       "      <td>2759.220497</td>\n",
       "      <td>0.095565</td>\n",
       "      <td>0.156703</td>\n",
       "      <td>0.012997</td>\n",
       "      <td>0.842183</td>\n",
       "      <td>False</td>\n",
       "      <td>POLYGON ((-12981895.900 3945471.980, -12981872...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>628 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           GEOID  median_age  total_pop  total_pop_white  tt_work  hh_total  \\\n",
       "0    06073018300        37.1     2590.0           2375.0   1299.0    2590.0   \n",
       "1    06073018601        41.2     5147.0           4069.0   1970.0    5147.0   \n",
       "2    06073017601        54.4     5595.0           4925.0   1702.0    5595.0   \n",
       "3    06073019301        42.3     7026.0           5625.0   3390.0    7026.0   \n",
       "4    06073018700        21.8    40402.0          30455.0  24143.0   40402.0   \n",
       "..           ...         ...        ...              ...      ...       ...   \n",
       "623  06073020709        41.6     7848.0           5633.0   3512.0    7848.0   \n",
       "624  06073020805        36.2     3624.0           2759.0   1681.0    3624.0   \n",
       "625  06073020810        44.5     5261.0           4977.0   2101.0    5261.0   \n",
       "626  06073021206        46.0     3065.0           2628.0   1373.0    3065.0   \n",
       "627  06073021000        60.6     2693.0           2268.0    693.0    2693.0   \n",
       "\n",
       "     hh_female  total_bachelor  median_hh_income  income_gini  ...  state  \\\n",
       "0        137.0             0.0           62500.0       0.5355  ...     06   \n",
       "1        562.0            24.0           88165.0       0.4265  ...     06   \n",
       "2        442.0            34.0          110804.0       0.4985  ...     06   \n",
       "3        638.0            46.0          100539.0       0.4003  ...     06   \n",
       "4       2456.0            23.0           41709.0       0.3196  ...     06   \n",
       "..         ...             ...               ...          ...  ...    ...   \n",
       "623      808.0            88.0           95132.0       0.3628  ...     06   \n",
       "624      392.0             0.0           63820.0       0.3498  ...     06   \n",
       "625      617.0            26.0          106319.0       0.3336  ...     06   \n",
       "626      303.0            15.0          104375.0       0.4050  ...     06   \n",
       "627      422.0            35.0           39760.0       0.4416  ...     06   \n",
       "\n",
       "     county   tract     area_sqm pct_rented pct_hh_female pct_bachelor  \\\n",
       "0       073  018300     2.876449   0.373913      0.052896     0.000000   \n",
       "1       073  018601     4.548797   0.205144      0.109190     0.004663   \n",
       "2       073  017601     8.726275   0.279029      0.078999     0.006077   \n",
       "3       073  019301     3.519743   0.196512      0.090806     0.006547   \n",
       "4       073  018700   559.150793   0.949887      0.060789     0.000569   \n",
       "..      ...     ...          ...        ...           ...          ...   \n",
       "623     073  020709   107.593049   0.127660      0.102956     0.011213   \n",
       "624     073  020805     7.239568   0.341730      0.108168     0.000000   \n",
       "625     073  020810    39.028783   0.111605      0.117278     0.004942   \n",
       "626     073  021206    42.849263   0.098882      0.098858     0.004894   \n",
       "627     073  021000  2759.220497   0.095565      0.156703     0.012997   \n",
       "\n",
       "    pct_white  sub_30                                           geometry  \n",
       "0    0.916988   False  POLYGON ((-13069450.120 3922380.770, -13069175...  \n",
       "1    0.790558   False  POLYGON ((-13067719.770 3922939.420, -13067631...  \n",
       "2    0.880250   False  POLYGON ((-13058166.110 3907247.690, -13058140...  \n",
       "3    0.800598   False  POLYGON ((-13056896.290 3925255.610, -13056868...  \n",
       "4    0.753799   False  POLYGON ((-13090788.510 3946435.430, -13090736...  \n",
       "..        ...     ...                                                ...  \n",
       "623  0.717762   False  POLYGON ((-13029476.960 3912060.390, -13029476...  \n",
       "624  0.761313   False  POLYGON ((-13014919.160 3898901.850, -13014868...  \n",
       "625  0.946018   False  POLYGON ((-13009524.170 3896636.950, -13009524...  \n",
       "626  0.857423   False  POLYGON ((-13002757.840 3875229.320, -13002735...  \n",
       "627  0.842183   False  POLYGON ((-12981895.900 3945471.980, -12981872...  \n",
       "\n",
       "[628 rows x 25 columns]"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "san_diego_tracts = geopandas.read_file('data_shenhao/sandiego/sandiego_tracts.gpkg')\n",
    "san_diego_tracts # sw: it is a geopandas df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['GEOID', 'median_age', 'total_pop', 'total_pop_white', 'tt_work',\n",
       "       'hh_total', 'hh_female', 'total_bachelor', 'median_hh_income',\n",
       "       'income_gini', 'total_housing_units', 'total_rented', 'median_no_rooms',\n",
       "       'median_house_value', 'NAME', 'state', 'county', 'tract', 'area_sqm',\n",
       "       'pct_rented', 'pct_hh_female', 'pct_bachelor', 'pct_white', 'sub_30',\n",
       "       'geometry'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "san_diego_tracts.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "wq = weights.contiguity.Queen.from_dataframe(san_diego_tracts) # sw: Queen contiguity."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# visualize the geo df and the new graph!\n",
    "ax = san_diego_tracts.plot(edgecolor='k', facecolor='w', figsize = (10,10))\n",
    "wq.plot(san_diego_tracts, ax=ax, \n",
    "        edge_kws=dict(color='r', linestyle=':', linewidth=1),\n",
    "        node_kws=dict(marker=''))\n",
    "ax.set_axis_off()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(-13040000.0, -13020000.0, 3850000.0, 3860000.0)"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# visualize the details of the dense area.\n",
    "ax = san_diego_tracts.plot(edgecolor='k', facecolor='w')\n",
    "f,ax = wq.plot(san_diego_tracts, ax=ax, \n",
    "        edge_kws=dict(color='r', linestyle=':', linewidth=1),\n",
    "        node_kws=dict(marker=''))\n",
    "ax.axis([-13040000,  -13020000, 3850000, 3860000]) # sw: choose axis values to show a subset of the full graph.\n",
    "#ax.set_axis_off()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "628\n",
      "1.018296888311899\n",
      "{0: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 1: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 2: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 3: [1.0, 1.0, 1.0, 1.0], 4: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 5: [1.0, 1.0, 1.0, 1.0, 1.0], 6: [1.0, 1.0, 1.0, 1.0], 7: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 8: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 9: [1.0, 1.0, 1.0, 1.0], 10: [1.0, 1.0, 1.0, 1.0, 1.0], 11: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 12: [1.0, 1.0, 1.0, 1.0, 1.0], 13: [1.0, 1.0, 1.0], 14: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 15: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 16: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 17: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 18: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 19: [1.0, 1.0, 1.0, 1.0], 20: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 21: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 22: [1.0, 1.0, 1.0, 1.0, 1.0], 23: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 24: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 25: [1.0, 1.0, 1.0, 1.0, 1.0], 26: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 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1.0, 1.0, 1.0, 1.0], 539: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 540: [1.0, 1.0, 1.0, 1.0], 541: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 542: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 543: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 544: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 545: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 546: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 547: [1.0, 1.0, 1.0, 1.0, 1.0], 548: [1.0, 1.0, 1.0, 1.0, 1.0], 549: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 550: [1.0, 1.0, 1.0], 551: [1.0, 1.0, 1.0, 1.0, 1.0], 552: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 553: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 554: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 555: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 556: [1.0, 1.0, 1.0, 1.0], 557: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 558: [1.0, 1.0, 1.0], 559: [1.0, 1.0, 1.0], 560: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 561: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 562: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 563: [1.0, 1.0, 1.0, 1.0, 1.0], 564: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 565: [1.0, 1.0, 1.0, 1.0], 566: [1.0, 1.0, 1.0, 1.0], 567: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 568: [1.0, 1.0, 1.0, 1.0, 1.0], 569: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 570: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 571: [1.0, 1.0, 1.0], 572: [1.0, 1.0, 1.0, 1.0, 1.0], 573: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 574: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 575: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 576: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 577: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 578: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 579: [1.0, 1.0, 1.0, 1.0, 1.0], 580: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 581: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 582: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 583: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 584: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 585: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 586: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 587: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 588: [1.0, 1.0, 1.0], 589: [1.0, 1.0, 1.0, 1.0, 1.0], 590: [1.0, 1.0, 1.0, 1.0], 591: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 592: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 593: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 594: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 595: [1.0, 1.0, 1.0, 1.0, 1.0], 596: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 597: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 598: [1.0, 1.0, 1.0], 599: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 600: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 601: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 602: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 603: [1.0, 1.0, 1.0, 1.0], 604: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 605: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 606: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 607: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 608: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 609: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 610: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 611: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 612: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 613: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 614: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 615: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 616: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 617: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 618: [1.0, 1.0, 1.0, 1.0, 1.0], 619: [1.0, 1.0, 1.0, 1.0], 620: [1.0, 1.0, 1.0, 1.0], 621: [1.0, 1.0, 1.0, 1.0], 622: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 623: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 624: [1.0, 1.0], 625: [1.0, 1.0, 1.0, 1.0, 1.0], 626: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 627: [1.0, 1.0, 1.0, 1.0]}\n"
     ]
    }
   ],
   "source": [
    "print(wq.n) # sw: no clue what they are.\n",
    "print(wq.pct_nonzero)\n",
    "print(wq.weights)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:ylabel='Frequency'>"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "s = pandas.Series(wq.cardinalities)\n",
    "s.plot.hist(bins=s.unique().shape[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.8722463385938578\n"
     ]
    },
    {
     "data": {
      "image/png": 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o65GkY9GKCockxwF/CrwKOAu4OMlZo61Kko49K+0huHOA3VX1eYAk1wGbgHuX+hct5UNYGq2V+kDdSv1vzIcGR2el/rc6m5UWDuuAh/rm9wIv7F8hyRZgS5t9NMn9h+3jdOA/hlbh6NivZZDfX9Ldrai+HbIEfVyR/VoCY9WvRR7Hw/v2fQttsNLCYUFVtQ3YNtfyJNNVNbWMJS0L+zV+Vmvf7Nf4OZK+rahrDsA+YH3f/BmtTZK0jFZaOHwa2JDkzCTfAVwE7BxxTZJ0zFlRw0pV9USSNwB/BxwHXFNV9yxyN3MOOY05+zV+Vmvf7Nf4WXTfUlXDKESSNMZW2rCSJGkFMBwkSR2rJhxW82s3kuxJcleSXUmmR13PkUpyTZIDSe7uazstyU1JHmg/Tx1ljUdijn5dlmRfO2a7kpw3yhqPRJL1SW5Jcm+Se5K8sbWvhmM2V9/G+rglOTHJbUk+2/r1jtZ+ZpJb29/HD7Ubfubf12q45tBeu/GvwMvpPTj3aeDiqlryJ6tHIckeYKqqxuYBndkk+QngUeDaqvqR1vYHwFeq6ooW6qdW1VtGWedizdGvy4BHq+oPR1nb0UiyFlhbVXckeRpwO3AB8GuM/zGbq28XMsbHLUmAk6vq0SQnAJ8C3gj8JvCRqrouyZ8Dn62qq+bb12o5c/i/125U1ePAodduaAWpqk8CXzmseROwvU1vp/cPdKzM0a+xV1X7q+qONv0N4D56bzFYDcdsrr6Ntep5tM2e0D4FvBT4cGsf6JitlnCY7bUbY3+g+xTw90lub68PWU3WVNX+Nv0lYM0oi1lib0hyZxt2Gruhl35JJoHnA7eyyo7ZYX2DMT9uSY5Lsgs4ANwE/Bvwtap6oq0y0N/H1RIOq91Lqupsem+rvbQNY6w61RvjHP9xzp6rgGcBG4H9wDtHWs1RSPJU4HrgTVX1SP+ycT9ms/Rt7I9bVR2sqo303jBxDvDsI9nPagmHVf3ajara134eAD5K74CvFg+38d9D48AHRlzPkqiqh9s/0m8B72FMj1kbt74eeH9VfaQ1r4pjNlvfVstxA6iqrwG3AC8GTkly6KHngf4+rpZwWLWv3UhycrtgRpKTgZ8G7p5/q7GyE9jcpjcDN4ywliVz6I9n82rG8Ji1i5tXA/dV1bv6Fo39MZurb+N+3JJMJDmlTZ9E7yad++iFxC+01QY6ZqvibiWAdsvZH/Ht125cPtqKlkaSZ9I7W4De604+MK59S/JB4Fx6rw9+GHg78DFgB/AM4EHgwqoaq4u7c/TrXHpDEwXsAV7fN04/FpK8BPgn4C7gW635bfTG5sf9mM3Vt4sZ4+OW5Ln0LjgfR+9//ndU1e+0vyPXAacBnwF+paoem3dfqyUcJElLZ7UMK0mSlpDhIEnqMBwkSR2GgySpw3CQJHUYDpKkDsNBktTxv97hd/pMVFnPAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# create a rook weights\n",
    "wr = weights.contiguity.Rook.from_dataframe(san_diego_tracts)\n",
    "print(wr.pct_nonzero)\n",
    "s = pandas.Series(wr.cardinalities)\n",
    "s.plot.hist(bins=s.unique().shape[0]);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Distance based weights"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## KNN weights"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "wk4 = weights.distance.KNN.from_dataframe(san_diego_tracts, k=4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[]"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wk4.islands # sw Q: what is an island?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(4, 628)]"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wk4.histogram # sw: KNN creates a very balanced weighting graph."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{0: [1.0, 1.0, 1.0, 1.0],\n",
       " 1: [1.0, 1.0, 1.0, 1.0],\n",
       " 2: [1.0, 1.0, 1.0, 1.0],\n",
       " 3: [1.0, 1.0, 1.0, 1.0],\n",
       " 4: [1.0, 1.0, 1.0, 1.0],\n",
       " 5: [1.0, 1.0, 1.0, 1.0],\n",
       " 6: [1.0, 1.0, 1.0, 1.0],\n",
       " 7: [1.0, 1.0, 1.0, 1.0],\n",
       " 8: [1.0, 1.0, 1.0, 1.0],\n",
       " 9: [1.0, 1.0, 1.0, 1.0],\n",
       " 10: [1.0, 1.0, 1.0, 1.0],\n",
       " 11: [1.0, 1.0, 1.0, 1.0],\n",
       " 12: [1.0, 1.0, 1.0, 1.0],\n",
       " 13: [1.0, 1.0, 1.0, 1.0],\n",
       " 14: [1.0, 1.0, 1.0, 1.0],\n",
       " 15: [1.0, 1.0, 1.0, 1.0],\n",
       " 16: [1.0, 1.0, 1.0, 1.0],\n",
       " 17: [1.0, 1.0, 1.0, 1.0],\n",
       " 18: [1.0, 1.0, 1.0, 1.0],\n",
       " 19: [1.0, 1.0, 1.0, 1.0],\n",
       " 20: [1.0, 1.0, 1.0, 1.0],\n",
       " 21: [1.0, 1.0, 1.0, 1.0],\n",
       " 22: [1.0, 1.0, 1.0, 1.0],\n",
       " 23: [1.0, 1.0, 1.0, 1.0],\n",
       " 24: [1.0, 1.0, 1.0, 1.0],\n",
       " 25: [1.0, 1.0, 1.0, 1.0],\n",
       " 26: [1.0, 1.0, 1.0, 1.0],\n",
       " 27: [1.0, 1.0, 1.0, 1.0],\n",
       " 28: [1.0, 1.0, 1.0, 1.0],\n",
       " 29: [1.0, 1.0, 1.0, 1.0],\n",
       " 30: [1.0, 1.0, 1.0, 1.0],\n",
       " 31: [1.0, 1.0, 1.0, 1.0],\n",
       " 32: [1.0, 1.0, 1.0, 1.0],\n",
       " 33: [1.0, 1.0, 1.0, 1.0],\n",
       " 34: [1.0, 1.0, 1.0, 1.0],\n",
       " 35: [1.0, 1.0, 1.0, 1.0],\n",
       " 36: [1.0, 1.0, 1.0, 1.0],\n",
       " 37: [1.0, 1.0, 1.0, 1.0],\n",
       " 38: [1.0, 1.0, 1.0, 1.0],\n",
       " 39: [1.0, 1.0, 1.0, 1.0],\n",
       " 40: [1.0, 1.0, 1.0, 1.0],\n",
       " 41: [1.0, 1.0, 1.0, 1.0],\n",
       " 42: [1.0, 1.0, 1.0, 1.0],\n",
       " 43: [1.0, 1.0, 1.0, 1.0],\n",
       " 44: [1.0, 1.0, 1.0, 1.0],\n",
       " 45: [1.0, 1.0, 1.0, 1.0],\n",
       " 46: [1.0, 1.0, 1.0, 1.0],\n",
       " 47: [1.0, 1.0, 1.0, 1.0],\n",
       " 48: [1.0, 1.0, 1.0, 1.0],\n",
       " 49: [1.0, 1.0, 1.0, 1.0],\n",
       " 50: [1.0, 1.0, 1.0, 1.0],\n",
       " 51: [1.0, 1.0, 1.0, 1.0],\n",
       " 52: [1.0, 1.0, 1.0, 1.0],\n",
       " 53: [1.0, 1.0, 1.0, 1.0],\n",
       " 54: [1.0, 1.0, 1.0, 1.0],\n",
       " 55: [1.0, 1.0, 1.0, 1.0],\n",
       " 56: [1.0, 1.0, 1.0, 1.0],\n",
       " 57: [1.0, 1.0, 1.0, 1.0],\n",
       " 58: [1.0, 1.0, 1.0, 1.0],\n",
       " 59: [1.0, 1.0, 1.0, 1.0],\n",
       " 60: [1.0, 1.0, 1.0, 1.0],\n",
       " 61: [1.0, 1.0, 1.0, 1.0],\n",
       " 62: [1.0, 1.0, 1.0, 1.0],\n",
       " 63: [1.0, 1.0, 1.0, 1.0],\n",
       " 64: [1.0, 1.0, 1.0, 1.0],\n",
       " 65: [1.0, 1.0, 1.0, 1.0],\n",
       " 66: [1.0, 1.0, 1.0, 1.0],\n",
       " 67: [1.0, 1.0, 1.0, 1.0],\n",
       " 68: [1.0, 1.0, 1.0, 1.0],\n",
       " 69: [1.0, 1.0, 1.0, 1.0],\n",
       " 70: [1.0, 1.0, 1.0, 1.0],\n",
       " 71: [1.0, 1.0, 1.0, 1.0],\n",
       " 72: [1.0, 1.0, 1.0, 1.0],\n",
       " 73: [1.0, 1.0, 1.0, 1.0],\n",
       " 74: [1.0, 1.0, 1.0, 1.0],\n",
       " 75: [1.0, 1.0, 1.0, 1.0],\n",
       " 76: [1.0, 1.0, 1.0, 1.0],\n",
       " 77: [1.0, 1.0, 1.0, 1.0],\n",
       " 78: [1.0, 1.0, 1.0, 1.0],\n",
       " 79: [1.0, 1.0, 1.0, 1.0],\n",
       " 80: [1.0, 1.0, 1.0, 1.0],\n",
       " 81: [1.0, 1.0, 1.0, 1.0],\n",
       " 82: [1.0, 1.0, 1.0, 1.0],\n",
       " 83: [1.0, 1.0, 1.0, 1.0],\n",
       " 84: [1.0, 1.0, 1.0, 1.0],\n",
       " 85: [1.0, 1.0, 1.0, 1.0],\n",
       " 86: [1.0, 1.0, 1.0, 1.0],\n",
       " 87: [1.0, 1.0, 1.0, 1.0],\n",
       " 88: [1.0, 1.0, 1.0, 1.0],\n",
       " 89: [1.0, 1.0, 1.0, 1.0],\n",
       " 90: [1.0, 1.0, 1.0, 1.0],\n",
       " 91: [1.0, 1.0, 1.0, 1.0],\n",
       " 92: [1.0, 1.0, 1.0, 1.0],\n",
       " 93: [1.0, 1.0, 1.0, 1.0],\n",
       " 94: [1.0, 1.0, 1.0, 1.0],\n",
       " 95: [1.0, 1.0, 1.0, 1.0],\n",
       " 96: [1.0, 1.0, 1.0, 1.0],\n",
       " 97: [1.0, 1.0, 1.0, 1.0],\n",
       " 98: [1.0, 1.0, 1.0, 1.0],\n",
       " 99: [1.0, 1.0, 1.0, 1.0],\n",
       " 100: [1.0, 1.0, 1.0, 1.0],\n",
       " 101: [1.0, 1.0, 1.0, 1.0],\n",
       " 102: [1.0, 1.0, 1.0, 1.0],\n",
       " 103: [1.0, 1.0, 1.0, 1.0],\n",
       " 104: [1.0, 1.0, 1.0, 1.0],\n",
       " 105: [1.0, 1.0, 1.0, 1.0],\n",
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       " 429: [1.0, 1.0, 1.0, 1.0],\n",
       " 430: [1.0, 1.0, 1.0, 1.0],\n",
       " 431: [1.0, 1.0, 1.0, 1.0],\n",
       " 432: [1.0, 1.0, 1.0, 1.0],\n",
       " 433: [1.0, 1.0, 1.0, 1.0],\n",
       " 434: [1.0, 1.0, 1.0, 1.0],\n",
       " 435: [1.0, 1.0, 1.0, 1.0],\n",
       " 436: [1.0, 1.0, 1.0, 1.0],\n",
       " 437: [1.0, 1.0, 1.0, 1.0],\n",
       " 438: [1.0, 1.0, 1.0, 1.0],\n",
       " 439: [1.0, 1.0, 1.0, 1.0],\n",
       " 440: [1.0, 1.0, 1.0, 1.0],\n",
       " 441: [1.0, 1.0, 1.0, 1.0],\n",
       " 442: [1.0, 1.0, 1.0, 1.0],\n",
       " 443: [1.0, 1.0, 1.0, 1.0],\n",
       " 444: [1.0, 1.0, 1.0, 1.0],\n",
       " 445: [1.0, 1.0, 1.0, 1.0],\n",
       " 446: [1.0, 1.0, 1.0, 1.0],\n",
       " 447: [1.0, 1.0, 1.0, 1.0],\n",
       " 448: [1.0, 1.0, 1.0, 1.0],\n",
       " 449: [1.0, 1.0, 1.0, 1.0],\n",
       " 450: [1.0, 1.0, 1.0, 1.0],\n",
       " 451: [1.0, 1.0, 1.0, 1.0],\n",
       " 452: [1.0, 1.0, 1.0, 1.0],\n",
       " 453: [1.0, 1.0, 1.0, 1.0],\n",
       " 454: [1.0, 1.0, 1.0, 1.0],\n",
       " 455: [1.0, 1.0, 1.0, 1.0],\n",
       " 456: [1.0, 1.0, 1.0, 1.0],\n",
       " 457: [1.0, 1.0, 1.0, 1.0],\n",
       " 458: [1.0, 1.0, 1.0, 1.0],\n",
       " 459: [1.0, 1.0, 1.0, 1.0],\n",
       " 460: [1.0, 1.0, 1.0, 1.0],\n",
       " 461: [1.0, 1.0, 1.0, 1.0],\n",
       " 462: [1.0, 1.0, 1.0, 1.0],\n",
       " 463: [1.0, 1.0, 1.0, 1.0],\n",
       " 464: [1.0, 1.0, 1.0, 1.0],\n",
       " 465: [1.0, 1.0, 1.0, 1.0],\n",
       " 466: [1.0, 1.0, 1.0, 1.0],\n",
       " 467: [1.0, 1.0, 1.0, 1.0],\n",
       " 468: [1.0, 1.0, 1.0, 1.0],\n",
       " 469: [1.0, 1.0, 1.0, 1.0],\n",
       " 470: [1.0, 1.0, 1.0, 1.0],\n",
       " 471: [1.0, 1.0, 1.0, 1.0],\n",
       " 472: [1.0, 1.0, 1.0, 1.0],\n",
       " 473: [1.0, 1.0, 1.0, 1.0],\n",
       " 474: [1.0, 1.0, 1.0, 1.0],\n",
       " 475: [1.0, 1.0, 1.0, 1.0],\n",
       " 476: [1.0, 1.0, 1.0, 1.0],\n",
       " 477: [1.0, 1.0, 1.0, 1.0],\n",
       " 478: [1.0, 1.0, 1.0, 1.0],\n",
       " 479: [1.0, 1.0, 1.0, 1.0],\n",
       " 480: [1.0, 1.0, 1.0, 1.0],\n",
       " 481: [1.0, 1.0, 1.0, 1.0],\n",
       " 482: [1.0, 1.0, 1.0, 1.0],\n",
       " 483: [1.0, 1.0, 1.0, 1.0],\n",
       " 484: [1.0, 1.0, 1.0, 1.0],\n",
       " 485: [1.0, 1.0, 1.0, 1.0],\n",
       " 486: [1.0, 1.0, 1.0, 1.0],\n",
       " 487: [1.0, 1.0, 1.0, 1.0],\n",
       " 488: [1.0, 1.0, 1.0, 1.0],\n",
       " 489: [1.0, 1.0, 1.0, 1.0],\n",
       " 490: [1.0, 1.0, 1.0, 1.0],\n",
       " 491: [1.0, 1.0, 1.0, 1.0],\n",
       " 492: [1.0, 1.0, 1.0, 1.0],\n",
       " 493: [1.0, 1.0, 1.0, 1.0],\n",
       " 494: [1.0, 1.0, 1.0, 1.0],\n",
       " 495: [1.0, 1.0, 1.0, 1.0],\n",
       " 496: [1.0, 1.0, 1.0, 1.0],\n",
       " 497: [1.0, 1.0, 1.0, 1.0],\n",
       " 498: [1.0, 1.0, 1.0, 1.0],\n",
       " 499: [1.0, 1.0, 1.0, 1.0],\n",
       " 500: [1.0, 1.0, 1.0, 1.0],\n",
       " 501: [1.0, 1.0, 1.0, 1.0],\n",
       " 502: [1.0, 1.0, 1.0, 1.0],\n",
       " 503: [1.0, 1.0, 1.0, 1.0],\n",
       " 504: [1.0, 1.0, 1.0, 1.0],\n",
       " 505: [1.0, 1.0, 1.0, 1.0],\n",
       " 506: [1.0, 1.0, 1.0, 1.0],\n",
       " 507: [1.0, 1.0, 1.0, 1.0],\n",
       " 508: [1.0, 1.0, 1.0, 1.0],\n",
       " 509: [1.0, 1.0, 1.0, 1.0],\n",
       " 510: [1.0, 1.0, 1.0, 1.0],\n",
       " 511: [1.0, 1.0, 1.0, 1.0],\n",
       " 512: [1.0, 1.0, 1.0, 1.0],\n",
       " 513: [1.0, 1.0, 1.0, 1.0],\n",
       " 514: [1.0, 1.0, 1.0, 1.0],\n",
       " 515: [1.0, 1.0, 1.0, 1.0],\n",
       " 516: [1.0, 1.0, 1.0, 1.0],\n",
       " 517: [1.0, 1.0, 1.0, 1.0],\n",
       " 518: [1.0, 1.0, 1.0, 1.0],\n",
       " 519: [1.0, 1.0, 1.0, 1.0],\n",
       " 520: [1.0, 1.0, 1.0, 1.0],\n",
       " 521: [1.0, 1.0, 1.0, 1.0],\n",
       " 522: [1.0, 1.0, 1.0, 1.0],\n",
       " 523: [1.0, 1.0, 1.0, 1.0],\n",
       " 524: [1.0, 1.0, 1.0, 1.0],\n",
       " 525: [1.0, 1.0, 1.0, 1.0],\n",
       " 526: [1.0, 1.0, 1.0, 1.0],\n",
       " 527: [1.0, 1.0, 1.0, 1.0],\n",
       " 528: [1.0, 1.0, 1.0, 1.0],\n",
       " 529: [1.0, 1.0, 1.0, 1.0],\n",
       " 530: [1.0, 1.0, 1.0, 1.0],\n",
       " 531: [1.0, 1.0, 1.0, 1.0],\n",
       " 532: [1.0, 1.0, 1.0, 1.0],\n",
       " 533: [1.0, 1.0, 1.0, 1.0],\n",
       " 534: [1.0, 1.0, 1.0, 1.0],\n",
       " 535: [1.0, 1.0, 1.0, 1.0],\n",
       " 536: [1.0, 1.0, 1.0, 1.0],\n",
       " 537: [1.0, 1.0, 1.0, 1.0],\n",
       " 538: [1.0, 1.0, 1.0, 1.0],\n",
       " 539: [1.0, 1.0, 1.0, 1.0],\n",
       " 540: [1.0, 1.0, 1.0, 1.0],\n",
       " 541: [1.0, 1.0, 1.0, 1.0],\n",
       " 542: [1.0, 1.0, 1.0, 1.0],\n",
       " 543: [1.0, 1.0, 1.0, 1.0],\n",
       " 544: [1.0, 1.0, 1.0, 1.0],\n",
       " 545: [1.0, 1.0, 1.0, 1.0],\n",
       " 546: [1.0, 1.0, 1.0, 1.0],\n",
       " 547: [1.0, 1.0, 1.0, 1.0],\n",
       " 548: [1.0, 1.0, 1.0, 1.0],\n",
       " 549: [1.0, 1.0, 1.0, 1.0],\n",
       " 550: [1.0, 1.0, 1.0, 1.0],\n",
       " 551: [1.0, 1.0, 1.0, 1.0],\n",
       " 552: [1.0, 1.0, 1.0, 1.0],\n",
       " 553: [1.0, 1.0, 1.0, 1.0],\n",
       " 554: [1.0, 1.0, 1.0, 1.0],\n",
       " 555: [1.0, 1.0, 1.0, 1.0],\n",
       " 556: [1.0, 1.0, 1.0, 1.0],\n",
       " 557: [1.0, 1.0, 1.0, 1.0],\n",
       " 558: [1.0, 1.0, 1.0, 1.0],\n",
       " 559: [1.0, 1.0, 1.0, 1.0],\n",
       " 560: [1.0, 1.0, 1.0, 1.0],\n",
       " 561: [1.0, 1.0, 1.0, 1.0],\n",
       " 562: [1.0, 1.0, 1.0, 1.0],\n",
       " 563: [1.0, 1.0, 1.0, 1.0],\n",
       " 564: [1.0, 1.0, 1.0, 1.0],\n",
       " 565: [1.0, 1.0, 1.0, 1.0],\n",
       " 566: [1.0, 1.0, 1.0, 1.0],\n",
       " 567: [1.0, 1.0, 1.0, 1.0],\n",
       " 568: [1.0, 1.0, 1.0, 1.0],\n",
       " 569: [1.0, 1.0, 1.0, 1.0],\n",
       " 570: [1.0, 1.0, 1.0, 1.0],\n",
       " 571: [1.0, 1.0, 1.0, 1.0],\n",
       " 572: [1.0, 1.0, 1.0, 1.0],\n",
       " 573: [1.0, 1.0, 1.0, 1.0],\n",
       " 574: [1.0, 1.0, 1.0, 1.0],\n",
       " 575: [1.0, 1.0, 1.0, 1.0],\n",
       " 576: [1.0, 1.0, 1.0, 1.0],\n",
       " 577: [1.0, 1.0, 1.0, 1.0],\n",
       " 578: [1.0, 1.0, 1.0, 1.0],\n",
       " 579: [1.0, 1.0, 1.0, 1.0],\n",
       " 580: [1.0, 1.0, 1.0, 1.0],\n",
       " 581: [1.0, 1.0, 1.0, 1.0],\n",
       " 582: [1.0, 1.0, 1.0, 1.0],\n",
       " 583: [1.0, 1.0, 1.0, 1.0],\n",
       " 584: [1.0, 1.0, 1.0, 1.0],\n",
       " 585: [1.0, 1.0, 1.0, 1.0],\n",
       " 586: [1.0, 1.0, 1.0, 1.0],\n",
       " 587: [1.0, 1.0, 1.0, 1.0],\n",
       " 588: [1.0, 1.0, 1.0, 1.0],\n",
       " 589: [1.0, 1.0, 1.0, 1.0],\n",
       " 590: [1.0, 1.0, 1.0, 1.0],\n",
       " 591: [1.0, 1.0, 1.0, 1.0],\n",
       " 592: [1.0, 1.0, 1.0, 1.0],\n",
       " 593: [1.0, 1.0, 1.0, 1.0],\n",
       " 594: [1.0, 1.0, 1.0, 1.0],\n",
       " 595: [1.0, 1.0, 1.0, 1.0],\n",
       " 596: [1.0, 1.0, 1.0, 1.0],\n",
       " 597: [1.0, 1.0, 1.0, 1.0],\n",
       " 598: [1.0, 1.0, 1.0, 1.0],\n",
       " 599: [1.0, 1.0, 1.0, 1.0],\n",
       " 600: [1.0, 1.0, 1.0, 1.0],\n",
       " 601: [1.0, 1.0, 1.0, 1.0],\n",
       " 602: [1.0, 1.0, 1.0, 1.0],\n",
       " 603: [1.0, 1.0, 1.0, 1.0],\n",
       " 604: [1.0, 1.0, 1.0, 1.0],\n",
       " 605: [1.0, 1.0, 1.0, 1.0],\n",
       " 606: [1.0, 1.0, 1.0, 1.0],\n",
       " 607: [1.0, 1.0, 1.0, 1.0],\n",
       " 608: [1.0, 1.0, 1.0, 1.0],\n",
       " 609: [1.0, 1.0, 1.0, 1.0],\n",
       " 610: [1.0, 1.0, 1.0, 1.0],\n",
       " 611: [1.0, 1.0, 1.0, 1.0],\n",
       " 612: [1.0, 1.0, 1.0, 1.0],\n",
       " 613: [1.0, 1.0, 1.0, 1.0],\n",
       " 614: [1.0, 1.0, 1.0, 1.0],\n",
       " 615: [1.0, 1.0, 1.0, 1.0],\n",
       " 616: [1.0, 1.0, 1.0, 1.0],\n",
       " 617: [1.0, 1.0, 1.0, 1.0],\n",
       " 618: [1.0, 1.0, 1.0, 1.0],\n",
       " 619: [1.0, 1.0, 1.0, 1.0],\n",
       " 620: [1.0, 1.0, 1.0, 1.0],\n",
       " 621: [1.0, 1.0, 1.0, 1.0],\n",
       " 622: [1.0, 1.0, 1.0, 1.0],\n",
       " 623: [1.0, 1.0, 1.0, 1.0],\n",
       " 624: [1.0, 1.0, 1.0, 1.0],\n",
       " 625: [1.0, 1.0, 1.0, 1.0],\n",
       " 626: [1.0, 1.0, 1.0, 1.0],\n",
       " 627: [1.0, 1.0, 1.0, 1.0]}"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wk4.weights"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(<Figure size 432x288 with 1 Axes>, <AxesSubplot:>)"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "wk4.plot(san_diego_tracts) # sw: my stupid plot. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Kernel weights from \n",
    "https://pysal.org/libpysal/generated/libpysal.weights.Kernel.html\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. Bandwidth: cutoff distance to compute the weights. e.g. bandwidth=20. $h_i = 20$ implies a fixed bandwidth for all the points.\n",
    "2. $z_{i,j}$ implies normalized distances between point i and j. \n",
    "3. Kernel function $K(z)$ returns a value inversely proportional to $z_{i,j}$. e.g. default: function = 'triangular', $K(z)= 1 - |z|$\n",
    "\n",
    "Overall, Kernel will return a weight dictionary, in which each row represents weights inversely proportional to distance and normalized to ones. Examples are as follows\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [],
   "source": [
    "from libpysal.weights import Kernel\n",
    "import matplotlib.pyplot as plt\n",
    "from scipy.spatial import distance_matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [],
   "source": [
    "points=[(10, 10), (20, 10), (40, 10), (15, 20), (30, 20), (30, 30)]\n",
    "x, y = zip(*points) # sw Q: meaning of * in python? "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x7fd28c312d50>"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(x, y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [],
   "source": [
    "# sw: Show the results with fixed bandwidth, triangular kernel, KNN=2 (to determine bandwidth).\n",
    "# sw: k is the number of nearest neighbors used to compute the fixed bandwidth. Not sure about the exact meaning.\n",
    "kw=Kernel(points,\n",
    "          bandwidth=20.5,\n",
    "          fixed=True,\n",
    "          k=2,\n",
    "          distance_metric='euclidean',\n",
    "          function='triangular')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[1.0, 0.5121951219512195, 0.45461756646346585]"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "kw.weights[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0, 1, 3]\n",
      "[0, 1, 2, 3, 4]\n",
      "[1, 2, 4]\n",
      "[0, 1, 3, 4, 5]\n"
     ]
    }
   ],
   "source": [
    "print(kw.neighbors[0]) # 0,1,3 are points with distance<20.5.\n",
    "print(kw.neighbors[1]) # 0,1,2,3,4 are points with distance<20.5.\n",
    "print(kw.neighbors[2]) \n",
    "print(kw.neighbors[3]) \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[20.5],\n",
       "       [20.5],\n",
       "       [20.5],\n",
       "       [20.5],\n",
       "       [20.5],\n",
       "       [20.5]])"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "kw.bandwidth \n",
    "# sw: Fixed bandwidth for all the points. \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "# dynamic bandwidth. \n",
    "bw=[25.0, 15.0, 5.0, 16.0, 14.5, 25.0]\n",
    "kwa=Kernel(points,bandwidth=bw)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0, 1, 3, 4]\n",
      "[1.0, 0.6, 0.552786404500042, 0.10557280900008403]\n",
      "[0, 1, 3, 4]\n",
      "[0.33333333333333337, 1.0, 0.2546440075000701, 0.057190958417936644]\n",
      "[2]\n",
      "[1.0]\n"
     ]
    }
   ],
   "source": [
    "# 0. bandwidth = 25 \n",
    "print(kwa.neighbors[0])\n",
    "print(kwa.weights[0])\n",
    "\n",
    "# 1. bandwidth = 15;only points closer than 15 are included.\n",
    "print(kwa.neighbors[1])\n",
    "print(kwa.weights[1])\n",
    "\n",
    "# 2. bandwidth = 5; only points closer than 5 are included. Hence no neighbor at all.\n",
    "print(kwa.neighbors[2])\n",
    "print(kwa.weights[2])\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{0: [0.0, 10.0, 11.18033988749895],\n",
       " 1: [10.0, 0.0, 20.0, 11.18033988749895, 14.142135623730951],\n",
       " 2: [20.0, 0.0, 14.142135623730951],\n",
       " 3: [11.18033988749895, 11.18033988749895, 0.0, 15.0, 18.027756377319946],\n",
       " 4: [14.142135623730951, 14.142135623730951, 15.0, 0.0, 10.0],\n",
       " 5: [18.027756377319946, 10.0, 0.0]}"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Q: How to replace the kernel weights by the euclidean distance?\n",
    "# A: Just reverse the function of a kernel.\n",
    "for i in kw.neighbors.keys():\n",
    "    for j_idx in range(len(kw.neighbors[i])):\n",
    "        j = kw.neighbors[i][j_idx]\n",
    "        # note that kw.weights indices are \n",
    "        # i (node index), j_idx (index of the node on the list - not node index!)\n",
    "        weight = kw.weights[i][j_idx]\n",
    "        distance = (1 - weight)*kw.bandwidth[i]\n",
    "        kw.weights[i][j_idx] = distance[0]\n",
    "\n",
    "kw.weights"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{0: [0, 1, 3],\n",
       " 1: [0, 1, 2, 3, 4],\n",
       " 2: [1, 2, 4],\n",
       " 3: [0, 1, 3, 4, 5],\n",
       " 4: [1, 2, 3, 4, 5],\n",
       " 5: [3, 4, 5]}"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "kw.neighbors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{0: [0.0, 10.0, 11.18033988749895],\n",
       " 1: [10.0, 0.0, 20.0, 11.18033988749895, 14.142135623730951],\n",
       " 2: [20.0, 0.0, 14.142135623730951],\n",
       " 3: [11.18033988749895, 11.18033988749895, 0.0, 15.0, 18.027756377319946],\n",
       " 4: [14.142135623730951, 14.142135623730951, 15.0, 0.0, 10.0],\n",
       " 5: [18.027756377319946, 10.0, 0.0]}"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "kw.weights"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Kernel weights"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [],
   "source": [
    "w_kernel = weights.distance.Kernel.from_dataframe(gdf)\n",
    "# sw: key parameters to adjust here: kernel function and bandwidth. \n",
    "# Default: triangular kernel and knn=2 distance. \n",
    "# sw Q: What is the use of bandwidth? \n",
    "# sw Q: It is unclear how the distances are exactly computed? "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'triangular'"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "w_kernel.function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1.0000001],\n",
       "       [1.0000001],\n",
       "       [1.0000001],\n",
       "       [1.0000001],\n",
       "       [1.0000001]])"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "w_kernel.bandwidth[0:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot a subset of the San Diego dataset\n",
    "sub_30 = san_diego_tracts.query(\"sub_30 == True\")\n",
    "ax = sub_30.plot(facecolor='w', edgecolor='k')\n",
    "sub_30.head(30).centroid.plot(color='r', ax=ax)\n",
    "ax.set_axis_off()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[3783.55870791],\n",
       "       [2082.25513388],\n",
       "       [1606.12096386],\n",
       "       [1636.51396538],\n",
       "       [1638.85416846],\n",
       "       [1487.33142257],\n",
       "       [1190.26229402],\n",
       "       [1366.34009572],\n",
       "       [2107.29117727],\n",
       "       [1729.4638175 ],\n",
       "       [1734.62386904],\n",
       "       [1707.29787782],\n",
       "       [1443.64721071],\n",
       "       [1934.78064755],\n",
       "       [1240.52406743],\n",
       "       [1535.58486401],\n",
       "       [1973.54301454],\n",
       "       [2393.79038085],\n",
       "       [1397.77147377],\n",
       "       [1103.15036717],\n",
       "       [1535.73985542],\n",
       "       [1324.42773488],\n",
       "       [1546.20005677],\n",
       "       [1364.78097583],\n",
       "       [2651.10042682],\n",
       "       [1487.33142257],\n",
       "       [1701.48459926],\n",
       "       [1118.03361609],\n",
       "       [1711.93088185],\n",
       "       [1816.1750061 ]])"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "w_adaptive = weights.distance.Kernel.from_dataframe(sub_30, fixed=False, k=5) \n",
    "# sw: not fixed bandwidth. K=15.\n",
    "w_adaptive.bandwidth"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_keys([19, 25, 28, 111, 121, 175, 184, 185, 190, 254, 327, 328, 330, 335, 337, 338, 343, 406, 411, 417, 418, 420, 489, 490, 569, 576, 580, 583, 585, 591])"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "w_adaptive.weights.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_values([[1.0, 0.6300490165995968, 0.5867704898429487, 0.3283398198121764, 0.24864340304013532, 9.99999900663795e-08], [1.0, 0.5238334915722047, 0.45508616689234394, 0.2493988046839607, 0.2362198864717009, 9.99999900663795e-08], [1.0, 0.3693987451422148, 0.3230616281238039, 0.29076567822772514, 0.1011591911043096, 9.99999900663795e-08], [1.0, 0.41797065851863324, 0.39145594466709643, 0.3356335886454823, 0.16604387849638635, 9.99999900663795e-08], [1.0, 0.5961978556042251, 0.40873210993093745, 0.24305410008141515, 0.04178840301553466, 9.99999900663795e-08], [1.0, 0.33336972398448483, 0.26604420623325453, 0.24838007813019658, 0.16393464478039643, 9.99999899553572e-08], [1.0, 0.3212883033943428, 0.19545097622840513, 0.173757500644256, 0.04297051312704103, 9.99999900663795e-08], [1.0, 0.5187287042512567, 0.4087526645042029, 0.12732561849573276, 0.09678854507029278, 9.99999899553572e-08], [1.0, 0.5359381706302881, 0.30956943822241234, 0.2222935196340048, 0.09855715253031305, 9.99999899553572e-08], [1.0, 0.399863867809638, 0.36880118346545765, 0.2949981106755043, 0.18747096066411484, 9.99999900663795e-08], [1.0, 0.3453297827493885, 0.2970953065829738, 0.1740052077955344, 0.08469723375848359, 9.99999900663795e-08], [1.0, 0.334851521845698, 0.32597556559996044, 0.2716524220557296, 0.08455155204879794, 9.99999900663795e-08], [1.0, 0.43167552833759415, 0.3402133578531653, 0.23290897991142023, 0.17551728277871625, 9.99999900663795e-08], [1.0, 0.5225442674148122, 0.20801430334177384, 0.15102655904211326, 0.11157457249121394, 9.99999900663795e-08], [1.0, 0.4047185247413627, 0.17510497044313122, 0.11073852912832471, 0.10399035919485677, 9.99999899553572e-08], [1.0, 0.4054537323860158, 0.3903911160934972, 0.18055450305703002, 0.11021527294644895, 9.99999900663795e-08], [1.0, 0.2627785558091599, 0.2124100412131833, 0.12902414020256991, 0.06681799133537791, 9.99999900663795e-08], [1.0, 0.5192726582677066, 0.516920229446064, 0.4152657325639181, 0.2753652494186327, 9.99999899553572e-08], [1.0, 0.41302276252739323, 0.3040339138990954, 0.18567048817713883, 0.11709886133202907, 9.99999900663795e-08], [1.0, 0.29616586733148953, 0.25380853745026233, 0.15142468067055836, 0.10851201979162872, 9.99999900663795e-08], [1.0, 0.571815326675991, 0.3984839891947589, 0.18063720392009386, 0.05534369283707319, 9.99999900663795e-08], [1.0, 0.44243013226903605, 0.37847768948443483, 0.31066359797710563, 0.2683618586366545, 9.99999900663795e-08], [1.0, 0.39487162021970135, 0.35591074341198137, 0.3287325778740142, 0.057058626139012025, 9.99999900663795e-08], [1.0, 0.31443246078487175, 0.18858129537502333, 0.1852702370958066, 0.1808884008333339, 9.99999900663795e-08], [1.0, 0.5638069021311962, 0.45954884705183696, 0.41025315536857443, 0.356004137067091, 9.99999900663795e-08], [1.0, 0.25240086776691606, 0.24083148065690874, 0.237123878853583, 0.23470549697222698, 9.99999899553572e-08], [1.0, 0.4282630931341822, 0.3363823602430065, 0.03462106882586202, 0.007020530235358313, 9.99999900663795e-08], [1.0, 0.30553529812674773, 0.1434744421797568, 0.09410425528602373, 0.005824594112934678, 9.99999901774018e-08], [1.0, 0.4022526562724963, 0.34691667979182317, 0.061807447792523784, 0.02044267763621943, 9.99999899553572e-08], [1.0, 0.6356227646811575, 0.4615533219800394, 0.2707599223695357, 0.15449518614914814, 9.99999900663795e-08]])"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "w_adaptive.weights.values()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[None, None]"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# vis\n",
    "full_matrix, ids = w_adaptive.full() \n",
    "f,ax = plt.subplots(1,2,figsize=(12,6), subplot_kw=dict(aspect='equal'))\n",
    "sub_30.assign(weight_0 = full_matrix[0]).plot(\"weight_0\", cmap='plasma', ax=ax[0])\n",
    "sub_30.assign(weight_15 = full_matrix[17]).plot(\"weight_15\", cmap='plasma', ax=ax[1])\n",
    "ax[0].set_title(\"Kernel centered on first tract\")\n",
    "ax[1].set_title(\"Kernel centered on 18th tract\")\n",
    "[ax_.set_axis_off() for ax_ in ax]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Distance bands and hybrid Weights"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [],
   "source": [
    "w_bdb = weights.distance.DistanceBand.from_dataframe(gdf, 1.5, binary=True)\n",
    "# It combines continuous and discrete weights. \n",
    "# 1.5 is a discrete threshold. \n",
    "# sw Q: How to use the threshold? "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/jtl/anaconda3/lib/python3.7/site-packages/scipy/sparse/data.py:117: RuntimeWarning: divide by zero encountered in reciprocal\n",
      "  return self._with_data(data ** n)\n"
     ]
    }
   ],
   "source": [
    "w_hy = weights.distance.DistanceBand.from_dataframe(gdf, 1.5, binary=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{0: [1.0, 1.0, 0.7071067811865475],\n",
       " 1: [1.0, 1.0, 0.7071067811865475, 1.0, 0.7071067811865475],\n",
       " 2: [1.0, 0.7071067811865475, 1.0],\n",
       " 3: [1.0, 0.7071067811865475, 1.0, 1.0, 0.7071067811865475],\n",
       " 4: [0.7071067811865475,\n",
       "  1.0,\n",
       "  0.7071067811865475,\n",
       "  1.0,\n",
       "  1.0,\n",
       "  0.7071067811865475,\n",
       "  1.0,\n",
       "  0.7071067811865475],\n",
       " 5: [0.7071067811865475, 1.0, 1.0, 0.7071067811865475, 1.0],\n",
       " 6: [1.0, 0.7071067811865475, 1.0],\n",
       " 7: [0.7071067811865475, 1.0, 0.7071067811865475, 1.0, 1.0],\n",
       " 8: [0.7071067811865475, 1.0, 1.0]}"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "w_hy.weights"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Great Circle distances"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Weights taking into account Earth's surface. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [],
   "source": [
    "texas = geopandas.read_file('data_shenhao/texas/texas.shp')\n",
    "knn4_bad = weights.distance.KNN.from_dataframe(texas, k=4) # ignore curvature of the earth"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(4, 254)]"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "knn4_bad.histogram"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{0: [1.0, 1.0, 1.0, 1.0],\n",
       " 1: [1.0, 1.0, 1.0, 1.0],\n",
       " 2: [1.0, 1.0, 1.0, 1.0],\n",
       " 3: [1.0, 1.0, 1.0, 1.0],\n",
       " 4: [1.0, 1.0, 1.0, 1.0],\n",
       " 5: [1.0, 1.0, 1.0, 1.0],\n",
       " 6: [1.0, 1.0, 1.0, 1.0],\n",
       " 7: [1.0, 1.0, 1.0, 1.0],\n",
       " 8: [1.0, 1.0, 1.0, 1.0],\n",
       " 9: [1.0, 1.0, 1.0, 1.0],\n",
       " 10: [1.0, 1.0, 1.0, 1.0],\n",
       " 11: [1.0, 1.0, 1.0, 1.0],\n",
       " 12: [1.0, 1.0, 1.0, 1.0],\n",
       " 13: [1.0, 1.0, 1.0, 1.0],\n",
       " 14: [1.0, 1.0, 1.0, 1.0],\n",
       " 15: [1.0, 1.0, 1.0, 1.0],\n",
       " 16: [1.0, 1.0, 1.0, 1.0],\n",
       " 17: [1.0, 1.0, 1.0, 1.0],\n",
       " 18: [1.0, 1.0, 1.0, 1.0],\n",
       " 19: [1.0, 1.0, 1.0, 1.0],\n",
       " 20: [1.0, 1.0, 1.0, 1.0],\n",
       " 21: [1.0, 1.0, 1.0, 1.0],\n",
       " 22: [1.0, 1.0, 1.0, 1.0],\n",
       " 23: [1.0, 1.0, 1.0, 1.0],\n",
       " 24: [1.0, 1.0, 1.0, 1.0],\n",
       " 25: [1.0, 1.0, 1.0, 1.0],\n",
       " 26: [1.0, 1.0, 1.0, 1.0],\n",
       " 27: [1.0, 1.0, 1.0, 1.0],\n",
       " 28: [1.0, 1.0, 1.0, 1.0],\n",
       " 29: [1.0, 1.0, 1.0, 1.0],\n",
       " 30: [1.0, 1.0, 1.0, 1.0],\n",
       " 31: [1.0, 1.0, 1.0, 1.0],\n",
       " 32: [1.0, 1.0, 1.0, 1.0],\n",
       " 33: [1.0, 1.0, 1.0, 1.0],\n",
       " 34: [1.0, 1.0, 1.0, 1.0],\n",
       " 35: [1.0, 1.0, 1.0, 1.0],\n",
       " 36: [1.0, 1.0, 1.0, 1.0],\n",
       " 37: [1.0, 1.0, 1.0, 1.0],\n",
       " 38: [1.0, 1.0, 1.0, 1.0],\n",
       " 39: [1.0, 1.0, 1.0, 1.0],\n",
       " 40: [1.0, 1.0, 1.0, 1.0],\n",
       " 41: [1.0, 1.0, 1.0, 1.0],\n",
       " 42: [1.0, 1.0, 1.0, 1.0],\n",
       " 43: [1.0, 1.0, 1.0, 1.0],\n",
       " 44: [1.0, 1.0, 1.0, 1.0],\n",
       " 45: [1.0, 1.0, 1.0, 1.0],\n",
       " 46: [1.0, 1.0, 1.0, 1.0],\n",
       " 47: [1.0, 1.0, 1.0, 1.0],\n",
       " 48: [1.0, 1.0, 1.0, 1.0],\n",
       " 49: [1.0, 1.0, 1.0, 1.0],\n",
       " 50: [1.0, 1.0, 1.0, 1.0],\n",
       " 51: [1.0, 1.0, 1.0, 1.0],\n",
       " 52: [1.0, 1.0, 1.0, 1.0],\n",
       " 53: [1.0, 1.0, 1.0, 1.0],\n",
       " 54: [1.0, 1.0, 1.0, 1.0],\n",
       " 55: [1.0, 1.0, 1.0, 1.0],\n",
       " 56: [1.0, 1.0, 1.0, 1.0],\n",
       " 57: [1.0, 1.0, 1.0, 1.0],\n",
       " 58: [1.0, 1.0, 1.0, 1.0],\n",
       " 59: [1.0, 1.0, 1.0, 1.0],\n",
       " 60: [1.0, 1.0, 1.0, 1.0],\n",
       " 61: [1.0, 1.0, 1.0, 1.0],\n",
       " 62: [1.0, 1.0, 1.0, 1.0],\n",
       " 63: [1.0, 1.0, 1.0, 1.0],\n",
       " 64: [1.0, 1.0, 1.0, 1.0],\n",
       " 65: [1.0, 1.0, 1.0, 1.0],\n",
       " 66: [1.0, 1.0, 1.0, 1.0],\n",
       " 67: [1.0, 1.0, 1.0, 1.0],\n",
       " 68: [1.0, 1.0, 1.0, 1.0],\n",
       " 69: [1.0, 1.0, 1.0, 1.0],\n",
       " 70: [1.0, 1.0, 1.0, 1.0],\n",
       " 71: [1.0, 1.0, 1.0, 1.0],\n",
       " 72: [1.0, 1.0, 1.0, 1.0],\n",
       " 73: [1.0, 1.0, 1.0, 1.0],\n",
       " 74: [1.0, 1.0, 1.0, 1.0],\n",
       " 75: [1.0, 1.0, 1.0, 1.0],\n",
       " 76: [1.0, 1.0, 1.0, 1.0],\n",
       " 77: [1.0, 1.0, 1.0, 1.0],\n",
       " 78: [1.0, 1.0, 1.0, 1.0],\n",
       " 79: [1.0, 1.0, 1.0, 1.0],\n",
       " 80: [1.0, 1.0, 1.0, 1.0],\n",
       " 81: [1.0, 1.0, 1.0, 1.0],\n",
       " 82: [1.0, 1.0, 1.0, 1.0],\n",
       " 83: [1.0, 1.0, 1.0, 1.0],\n",
       " 84: [1.0, 1.0, 1.0, 1.0],\n",
       " 85: [1.0, 1.0, 1.0, 1.0],\n",
       " 86: [1.0, 1.0, 1.0, 1.0],\n",
       " 87: [1.0, 1.0, 1.0, 1.0],\n",
       " 88: [1.0, 1.0, 1.0, 1.0],\n",
       " 89: [1.0, 1.0, 1.0, 1.0],\n",
       " 90: [1.0, 1.0, 1.0, 1.0],\n",
       " 91: [1.0, 1.0, 1.0, 1.0],\n",
       " 92: [1.0, 1.0, 1.0, 1.0],\n",
       " 93: [1.0, 1.0, 1.0, 1.0],\n",
       " 94: [1.0, 1.0, 1.0, 1.0],\n",
       " 95: [1.0, 1.0, 1.0, 1.0],\n",
       " 96: [1.0, 1.0, 1.0, 1.0],\n",
       " 97: [1.0, 1.0, 1.0, 1.0],\n",
       " 98: [1.0, 1.0, 1.0, 1.0],\n",
       " 99: [1.0, 1.0, 1.0, 1.0],\n",
       " 100: [1.0, 1.0, 1.0, 1.0],\n",
       " 101: [1.0, 1.0, 1.0, 1.0],\n",
       " 102: [1.0, 1.0, 1.0, 1.0],\n",
       " 103: [1.0, 1.0, 1.0, 1.0],\n",
       " 104: [1.0, 1.0, 1.0, 1.0],\n",
       " 105: [1.0, 1.0, 1.0, 1.0],\n",
       " 106: [1.0, 1.0, 1.0, 1.0],\n",
       " 107: [1.0, 1.0, 1.0, 1.0],\n",
       " 108: [1.0, 1.0, 1.0, 1.0],\n",
       " 109: [1.0, 1.0, 1.0, 1.0],\n",
       " 110: [1.0, 1.0, 1.0, 1.0],\n",
       " 111: [1.0, 1.0, 1.0, 1.0],\n",
       " 112: [1.0, 1.0, 1.0, 1.0],\n",
       " 113: [1.0, 1.0, 1.0, 1.0],\n",
       " 114: [1.0, 1.0, 1.0, 1.0],\n",
       " 115: [1.0, 1.0, 1.0, 1.0],\n",
       " 116: [1.0, 1.0, 1.0, 1.0],\n",
       " 117: [1.0, 1.0, 1.0, 1.0],\n",
       " 118: [1.0, 1.0, 1.0, 1.0],\n",
       " 119: [1.0, 1.0, 1.0, 1.0],\n",
       " 120: [1.0, 1.0, 1.0, 1.0],\n",
       " 121: [1.0, 1.0, 1.0, 1.0],\n",
       " 122: [1.0, 1.0, 1.0, 1.0],\n",
       " 123: [1.0, 1.0, 1.0, 1.0],\n",
       " 124: [1.0, 1.0, 1.0, 1.0],\n",
       " 125: [1.0, 1.0, 1.0, 1.0],\n",
       " 126: [1.0, 1.0, 1.0, 1.0],\n",
       " 127: [1.0, 1.0, 1.0, 1.0],\n",
       " 128: [1.0, 1.0, 1.0, 1.0],\n",
       " 129: [1.0, 1.0, 1.0, 1.0],\n",
       " 130: [1.0, 1.0, 1.0, 1.0],\n",
       " 131: [1.0, 1.0, 1.0, 1.0],\n",
       " 132: [1.0, 1.0, 1.0, 1.0],\n",
       " 133: [1.0, 1.0, 1.0, 1.0],\n",
       " 134: [1.0, 1.0, 1.0, 1.0],\n",
       " 135: [1.0, 1.0, 1.0, 1.0],\n",
       " 136: [1.0, 1.0, 1.0, 1.0],\n",
       " 137: [1.0, 1.0, 1.0, 1.0],\n",
       " 138: [1.0, 1.0, 1.0, 1.0],\n",
       " 139: [1.0, 1.0, 1.0, 1.0],\n",
       " 140: [1.0, 1.0, 1.0, 1.0],\n",
       " 141: [1.0, 1.0, 1.0, 1.0],\n",
       " 142: [1.0, 1.0, 1.0, 1.0],\n",
       " 143: [1.0, 1.0, 1.0, 1.0],\n",
       " 144: [1.0, 1.0, 1.0, 1.0],\n",
       " 145: [1.0, 1.0, 1.0, 1.0],\n",
       " 146: [1.0, 1.0, 1.0, 1.0],\n",
       " 147: [1.0, 1.0, 1.0, 1.0],\n",
       " 148: [1.0, 1.0, 1.0, 1.0],\n",
       " 149: [1.0, 1.0, 1.0, 1.0],\n",
       " 150: [1.0, 1.0, 1.0, 1.0],\n",
       " 151: [1.0, 1.0, 1.0, 1.0],\n",
       " 152: [1.0, 1.0, 1.0, 1.0],\n",
       " 153: [1.0, 1.0, 1.0, 1.0],\n",
       " 154: [1.0, 1.0, 1.0, 1.0],\n",
       " 155: [1.0, 1.0, 1.0, 1.0],\n",
       " 156: [1.0, 1.0, 1.0, 1.0],\n",
       " 157: [1.0, 1.0, 1.0, 1.0],\n",
       " 158: [1.0, 1.0, 1.0, 1.0],\n",
       " 159: [1.0, 1.0, 1.0, 1.0],\n",
       " 160: [1.0, 1.0, 1.0, 1.0],\n",
       " 161: [1.0, 1.0, 1.0, 1.0],\n",
       " 162: [1.0, 1.0, 1.0, 1.0],\n",
       " 163: [1.0, 1.0, 1.0, 1.0],\n",
       " 164: [1.0, 1.0, 1.0, 1.0],\n",
       " 165: [1.0, 1.0, 1.0, 1.0],\n",
       " 166: [1.0, 1.0, 1.0, 1.0],\n",
       " 167: [1.0, 1.0, 1.0, 1.0],\n",
       " 168: [1.0, 1.0, 1.0, 1.0],\n",
       " 169: [1.0, 1.0, 1.0, 1.0],\n",
       " 170: [1.0, 1.0, 1.0, 1.0],\n",
       " 171: [1.0, 1.0, 1.0, 1.0],\n",
       " 172: [1.0, 1.0, 1.0, 1.0],\n",
       " 173: [1.0, 1.0, 1.0, 1.0],\n",
       " 174: [1.0, 1.0, 1.0, 1.0],\n",
       " 175: [1.0, 1.0, 1.0, 1.0],\n",
       " 176: [1.0, 1.0, 1.0, 1.0],\n",
       " 177: [1.0, 1.0, 1.0, 1.0],\n",
       " 178: [1.0, 1.0, 1.0, 1.0],\n",
       " 179: [1.0, 1.0, 1.0, 1.0],\n",
       " 180: [1.0, 1.0, 1.0, 1.0],\n",
       " 181: [1.0, 1.0, 1.0, 1.0],\n",
       " 182: [1.0, 1.0, 1.0, 1.0],\n",
       " 183: [1.0, 1.0, 1.0, 1.0],\n",
       " 184: [1.0, 1.0, 1.0, 1.0],\n",
       " 185: [1.0, 1.0, 1.0, 1.0],\n",
       " 186: [1.0, 1.0, 1.0, 1.0],\n",
       " 187: [1.0, 1.0, 1.0, 1.0],\n",
       " 188: [1.0, 1.0, 1.0, 1.0],\n",
       " 189: [1.0, 1.0, 1.0, 1.0],\n",
       " 190: [1.0, 1.0, 1.0, 1.0],\n",
       " 191: [1.0, 1.0, 1.0, 1.0],\n",
       " 192: [1.0, 1.0, 1.0, 1.0],\n",
       " 193: [1.0, 1.0, 1.0, 1.0],\n",
       " 194: [1.0, 1.0, 1.0, 1.0],\n",
       " 195: [1.0, 1.0, 1.0, 1.0],\n",
       " 196: [1.0, 1.0, 1.0, 1.0],\n",
       " 197: [1.0, 1.0, 1.0, 1.0],\n",
       " 198: [1.0, 1.0, 1.0, 1.0],\n",
       " 199: [1.0, 1.0, 1.0, 1.0],\n",
       " 200: [1.0, 1.0, 1.0, 1.0],\n",
       " 201: [1.0, 1.0, 1.0, 1.0],\n",
       " 202: [1.0, 1.0, 1.0, 1.0],\n",
       " 203: [1.0, 1.0, 1.0, 1.0],\n",
       " 204: [1.0, 1.0, 1.0, 1.0],\n",
       " 205: [1.0, 1.0, 1.0, 1.0],\n",
       " 206: [1.0, 1.0, 1.0, 1.0],\n",
       " 207: [1.0, 1.0, 1.0, 1.0],\n",
       " 208: [1.0, 1.0, 1.0, 1.0],\n",
       " 209: [1.0, 1.0, 1.0, 1.0],\n",
       " 210: [1.0, 1.0, 1.0, 1.0],\n",
       " 211: [1.0, 1.0, 1.0, 1.0],\n",
       " 212: [1.0, 1.0, 1.0, 1.0],\n",
       " 213: [1.0, 1.0, 1.0, 1.0],\n",
       " 214: [1.0, 1.0, 1.0, 1.0],\n",
       " 215: [1.0, 1.0, 1.0, 1.0],\n",
       " 216: [1.0, 1.0, 1.0, 1.0],\n",
       " 217: [1.0, 1.0, 1.0, 1.0],\n",
       " 218: [1.0, 1.0, 1.0, 1.0],\n",
       " 219: [1.0, 1.0, 1.0, 1.0],\n",
       " 220: [1.0, 1.0, 1.0, 1.0],\n",
       " 221: [1.0, 1.0, 1.0, 1.0],\n",
       " 222: [1.0, 1.0, 1.0, 1.0],\n",
       " 223: [1.0, 1.0, 1.0, 1.0],\n",
       " 224: [1.0, 1.0, 1.0, 1.0],\n",
       " 225: [1.0, 1.0, 1.0, 1.0],\n",
       " 226: [1.0, 1.0, 1.0, 1.0],\n",
       " 227: [1.0, 1.0, 1.0, 1.0],\n",
       " 228: [1.0, 1.0, 1.0, 1.0],\n",
       " 229: [1.0, 1.0, 1.0, 1.0],\n",
       " 230: [1.0, 1.0, 1.0, 1.0],\n",
       " 231: [1.0, 1.0, 1.0, 1.0],\n",
       " 232: [1.0, 1.0, 1.0, 1.0],\n",
       " 233: [1.0, 1.0, 1.0, 1.0],\n",
       " 234: [1.0, 1.0, 1.0, 1.0],\n",
       " 235: [1.0, 1.0, 1.0, 1.0],\n",
       " 236: [1.0, 1.0, 1.0, 1.0],\n",
       " 237: [1.0, 1.0, 1.0, 1.0],\n",
       " 238: [1.0, 1.0, 1.0, 1.0],\n",
       " 239: [1.0, 1.0, 1.0, 1.0],\n",
       " 240: [1.0, 1.0, 1.0, 1.0],\n",
       " 241: [1.0, 1.0, 1.0, 1.0],\n",
       " 242: [1.0, 1.0, 1.0, 1.0],\n",
       " 243: [1.0, 1.0, 1.0, 1.0],\n",
       " 244: [1.0, 1.0, 1.0, 1.0],\n",
       " 245: [1.0, 1.0, 1.0, 1.0],\n",
       " 246: [1.0, 1.0, 1.0, 1.0],\n",
       " 247: [1.0, 1.0, 1.0, 1.0],\n",
       " 248: [1.0, 1.0, 1.0, 1.0],\n",
       " 249: [1.0, 1.0, 1.0, 1.0],\n",
       " 250: [1.0, 1.0, 1.0, 1.0],\n",
       " 251: [1.0, 1.0, 1.0, 1.0],\n",
       " 252: [1.0, 1.0, 1.0, 1.0],\n",
       " 253: [1.0, 1.0, 1.0, 1.0]}"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "knn4_bad.weights"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3958.755865744055"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "radius = geometry.sphere.RADIUS_EARTH_MILES\n",
    "radius"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [],
   "source": [
    "knn4 = weights.distance.KNN.from_dataframe(texas, k=4, radius=radius) # incorporate earth curvature"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Set Operations\n",
    "Ignored"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Block Weights"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>GEOID</th>\n",
       "      <th>state</th>\n",
       "      <th>county</th>\n",
       "      <th>tract</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>06073018300</td>\n",
       "      <td>06</td>\n",
       "      <td>073</td>\n",
       "      <td>018300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>06073018601</td>\n",
       "      <td>06</td>\n",
       "      <td>073</td>\n",
       "      <td>018601</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>06073017601</td>\n",
       "      <td>06</td>\n",
       "      <td>073</td>\n",
       "      <td>017601</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>06073019301</td>\n",
       "      <td>06</td>\n",
       "      <td>073</td>\n",
       "      <td>019301</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>06073018700</td>\n",
       "      <td>06</td>\n",
       "      <td>073</td>\n",
       "      <td>018700</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         GEOID state county   tract\n",
       "0  06073018300    06    073  018300\n",
       "1  06073018601    06    073  018601\n",
       "2  06073017601    06    073  017601\n",
       "3  06073019301    06    073  019301\n",
       "4  06073018700    06    073  018700"
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "san_diego_tracts[['GEOID', 'state', 'county', 'tract']].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [],
   "source": [
    "# use counties to build spatial clusters (blocks)\n",
    "# NOTE: since this is a large dataset, it might take a while to process\n",
    "w_bl = weights.util.block_weights(san_diego_tracts['county'].values, \n",
    "                                  ids=san_diego_tracts['GEOID'].values)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "628\n"
     ]
    }
   ],
   "source": [
    "print(len(w_bl.weights.keys()))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Visualizing weight set operations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x648 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "mx = geopandas.read_file('data_shenhao/mexico/mexicojoin.shp')\n",
    "f, ax = plt.subplots(1, figsize=(9, 9))\n",
    "mx.plot(ax=ax)\n",
    "ax.set_axis_off()\n",
    "ax.set_title('Mexican States')\n",
    "plt.axis('equal')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x648 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# vis\n",
    "queen_mx = weights.contiguity.Queen.from_dataframe(mx)\n",
    "f, ax = plt.subplots(1, figsize=(9, 9))\n",
    "mx.plot(ax=ax)\n",
    "queen_mx.plot(mx,edge_kws=dict(linewidth=1.5, color='orangered'), node_kws=dict(marker='*'),  ax=ax, )\n",
    "ax.set_axis_off()\n",
    "ax.set_title('Queen')\n",
    "plt.axis('equal')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Mexican Regions')"
      ]
     },
     "execution_count": 98,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# vis blocks\n",
    "ax = mx.plot(column='INEGI2', categorical=True, cmap='Pastel2')\n",
    "ax.set_axis_off()\n",
    "ax.set_title(\"Mexican Regions\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/jtl/anaconda3/lib/python3.7/site-packages/libpysal/weights/weights.py:172: UserWarning: The weights matrix is not fully connected: \n",
      " There are 5 disconnected components.\n",
      "  warnings.warn(message)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x648 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# create block weights and vis\n",
    "block_mx = weights.util.block_weights(mx['INEGI2'].values)\n",
    "\n",
    "# network vis\n",
    "f, ax = plt.subplots(1, figsize=(9, 9))\n",
    "mx.plot(column='INEGI2', categorical=True, \n",
    "        cmap='Pastel2', ax=ax)\n",
    "block_mx.plot(mx, edge_kws=dict(linewidth=1.5, \n",
    "                                color='orangered'), \n",
    "                  node_kws=dict(marker='*'), ax=ax)\n",
    "ax.set_axis_off()\n",
    "ax.set_title('Block')\n",
    "plt.axis('equal')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x648 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# create the union of block weights and queen contiguity.\n",
    "union_mx = weights.set_operations.w_union(block_mx, queen_mx)\n",
    "\n",
    "f, ax = plt.subplots(1, figsize=(9, 9))\n",
    "mx.plot(column='INEGI2', categorical=True, cmap='Pastel2', ax=ax)\n",
    "union_mx.plot(mx, edge_kws=dict(linewidth=1.5, \n",
    "                                color='orangered'), \n",
    "              node_kws=dict(marker='*'), ax=ax)\n",
    "ax.set_axis_off()\n",
    "ax.set_title('Union ')\n",
    "plt.axis('equal')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x432 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# compare the three graphs.\n",
    "f, axs = plt.subplots(1, 3, figsize=(18, 6))\n",
    "\n",
    "# Contiguity\n",
    "ax = axs[0]\n",
    "mx.plot(column='INEGI2', categorical=True, \n",
    "        cmap='Pastel2', ax=ax)\n",
    "queen_mx.plot(mx, edge_kws=dict(linewidth=1.5, color='orangered'), \n",
    "              node_kws=dict(marker='*'), ax=ax)\n",
    "ax.set_axis_off()\n",
    "ax.set_title('Queen')\n",
    "ax.axis('equal')\n",
    "\n",
    "# Block\n",
    "ax = axs[1]\n",
    "mx.plot(column='INEGI2', categorical=True, \n",
    "        cmap='Pastel2', ax=ax)\n",
    "block_mx.plot(mx, edge_kws=dict(linewidth=1.5, color='orangered'), \n",
    "              node_kws=dict(marker='*'), ax=ax)\n",
    "ax.set_axis_off()\n",
    "ax.set_title('Block weights')\n",
    "ax.axis('equal')\n",
    "\n",
    "# Union\n",
    "ax = axs[2]\n",
    "mx.plot(column='INEGI2', categorical=True, \n",
    "        cmap='Pastel2', ax=ax)\n",
    "union_mx.plot(mx, edge_kws=dict(linewidth=1.5, color='orangered'), \n",
    "              node_kws=dict(marker='*'), ax=ax)\n",
    "ax.set_axis_off()\n",
    "ax.set_title('Queen + Block')\n",
    "plt.axis('equal')\n",
    "f.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Use Case\n",
    "ignored."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
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