{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Full Rank Markov and Geographic Rank Markov \n",
    "\n",
    "**Author: Wei Kang <weikang9009@gmail.com>**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import libpysal as ps\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "import seaborn as sns\n",
    "import pandas as pd\n",
    "import geopandas as gpd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Full Rank Markov"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from giddy.markov import FullRank_Markov"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "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>Name</th>\n",
       "      <th>STATE_FIPS</th>\n",
       "      <th>1929</th>\n",
       "      <th>1930</th>\n",
       "      <th>1931</th>\n",
       "      <th>1932</th>\n",
       "      <th>1933</th>\n",
       "      <th>1934</th>\n",
       "      <th>1935</th>\n",
       "      <th>1936</th>\n",
       "      <th>...</th>\n",
       "      <th>2000</th>\n",
       "      <th>2001</th>\n",
       "      <th>2002</th>\n",
       "      <th>2003</th>\n",
       "      <th>2004</th>\n",
       "      <th>2005</th>\n",
       "      <th>2006</th>\n",
       "      <th>2007</th>\n",
       "      <th>2008</th>\n",
       "      <th>2009</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Alabama</td>\n",
       "      <td>1</td>\n",
       "      <td>323</td>\n",
       "      <td>267</td>\n",
       "      <td>224</td>\n",
       "      <td>162</td>\n",
       "      <td>166</td>\n",
       "      <td>211</td>\n",
       "      <td>217</td>\n",
       "      <td>251</td>\n",
       "      <td>...</td>\n",
       "      <td>23471</td>\n",
       "      <td>24467</td>\n",
       "      <td>25161</td>\n",
       "      <td>26065</td>\n",
       "      <td>27665</td>\n",
       "      <td>29097</td>\n",
       "      <td>30634</td>\n",
       "      <td>31988</td>\n",
       "      <td>32819</td>\n",
       "      <td>32274</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Arizona</td>\n",
       "      <td>4</td>\n",
       "      <td>600</td>\n",
       "      <td>520</td>\n",
       "      <td>429</td>\n",
       "      <td>321</td>\n",
       "      <td>308</td>\n",
       "      <td>362</td>\n",
       "      <td>416</td>\n",
       "      <td>462</td>\n",
       "      <td>...</td>\n",
       "      <td>25578</td>\n",
       "      <td>26232</td>\n",
       "      <td>26469</td>\n",
       "      <td>27106</td>\n",
       "      <td>28753</td>\n",
       "      <td>30671</td>\n",
       "      <td>32552</td>\n",
       "      <td>33470</td>\n",
       "      <td>33445</td>\n",
       "      <td>32077</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Arkansas</td>\n",
       "      <td>5</td>\n",
       "      <td>310</td>\n",
       "      <td>228</td>\n",
       "      <td>215</td>\n",
       "      <td>157</td>\n",
       "      <td>157</td>\n",
       "      <td>187</td>\n",
       "      <td>207</td>\n",
       "      <td>247</td>\n",
       "      <td>...</td>\n",
       "      <td>22257</td>\n",
       "      <td>23532</td>\n",
       "      <td>23929</td>\n",
       "      <td>25074</td>\n",
       "      <td>26465</td>\n",
       "      <td>27512</td>\n",
       "      <td>29041</td>\n",
       "      <td>31070</td>\n",
       "      <td>31800</td>\n",
       "      <td>31493</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>California</td>\n",
       "      <td>6</td>\n",
       "      <td>991</td>\n",
       "      <td>887</td>\n",
       "      <td>749</td>\n",
       "      <td>580</td>\n",
       "      <td>546</td>\n",
       "      <td>603</td>\n",
       "      <td>660</td>\n",
       "      <td>771</td>\n",
       "      <td>...</td>\n",
       "      <td>32275</td>\n",
       "      <td>32750</td>\n",
       "      <td>32900</td>\n",
       "      <td>33801</td>\n",
       "      <td>35663</td>\n",
       "      <td>37463</td>\n",
       "      <td>40169</td>\n",
       "      <td>41943</td>\n",
       "      <td>42377</td>\n",
       "      <td>40902</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Colorado</td>\n",
       "      <td>8</td>\n",
       "      <td>634</td>\n",
       "      <td>578</td>\n",
       "      <td>471</td>\n",
       "      <td>354</td>\n",
       "      <td>353</td>\n",
       "      <td>368</td>\n",
       "      <td>444</td>\n",
       "      <td>542</td>\n",
       "      <td>...</td>\n",
       "      <td>32949</td>\n",
       "      <td>34228</td>\n",
       "      <td>33963</td>\n",
       "      <td>34092</td>\n",
       "      <td>35543</td>\n",
       "      <td>37388</td>\n",
       "      <td>39662</td>\n",
       "      <td>41165</td>\n",
       "      <td>41719</td>\n",
       "      <td>40093</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 83 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         Name  STATE_FIPS  1929  1930  1931  1932  1933  1934  1935  1936  \\\n",
       "0     Alabama           1   323   267   224   162   166   211   217   251   \n",
       "1     Arizona           4   600   520   429   321   308   362   416   462   \n",
       "2    Arkansas           5   310   228   215   157   157   187   207   247   \n",
       "3  California           6   991   887   749   580   546   603   660   771   \n",
       "4    Colorado           8   634   578   471   354   353   368   444   542   \n",
       "\n",
       "   ...     2000   2001   2002   2003   2004   2005   2006   2007   2008   2009  \n",
       "0  ...    23471  24467  25161  26065  27665  29097  30634  31988  32819  32274  \n",
       "1  ...    25578  26232  26469  27106  28753  30671  32552  33470  33445  32077  \n",
       "2  ...    22257  23532  23929  25074  26465  27512  29041  31070  31800  31493  \n",
       "3  ...    32275  32750  32900  33801  35663  37463  40169  41943  42377  40902  \n",
       "4  ...    32949  34228  33963  34092  35543  37388  39662  41165  41719  40093  \n",
       "\n",
       "[5 rows x 83 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "income_table = pd.read_csv(ps.examples.get_path(\"usjoin.csv\"))\n",
    "income_table.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[  323,   267,   224, ..., 31988, 32819, 32274],\n",
       "       [  600,   520,   429, ..., 33470, 33445, 32077],\n",
       "       [  310,   228,   215, ..., 31070, 31800, 31493],\n",
       "       ...,\n",
       "       [  460,   408,   356, ..., 29769, 31265, 31843],\n",
       "       [  673,   588,   469, ..., 35839, 36594, 35676],\n",
       "       [  675,   585,   476, ..., 43453, 45177, 42504]])"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pci = income_table[list(map(str,range(1929,2010)))].values\n",
    "pci"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[45, 45, 44, ..., 41, 40, 39],\n",
       "       [24, 25, 25, ..., 36, 38, 41],\n",
       "       [46, 47, 45, ..., 43, 43, 43],\n",
       "       ...,\n",
       "       [34, 34, 34, ..., 47, 46, 42],\n",
       "       [17, 17, 22, ..., 25, 26, 25],\n",
       "       [16, 18, 19, ...,  6,  6,  7]])"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "m = FullRank_Markov(pci)\n",
    "m.ranks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[66.,  5.,  5., ...,  0.,  0.,  0.],\n",
       "       [ 8., 51.,  9., ...,  0.,  0.,  0.],\n",
       "       [ 2., 13., 44., ...,  0.,  0.,  0.],\n",
       "       ...,\n",
       "       [ 0.,  0.,  0., ..., 40., 17.,  0.],\n",
       "       [ 0.,  0.,  0., ..., 15., 54.,  2.],\n",
       "       [ 0.,  0.,  0., ...,  2.,  1., 77.]])"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "m.transitions"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Full rank Markov transition probability matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0.825 , 0.0625, 0.0625, ..., 0.    , 0.    , 0.    ],\n",
       "       [0.1   , 0.6375, 0.1125, ..., 0.    , 0.    , 0.    ],\n",
       "       [0.025 , 0.1625, 0.55  , ..., 0.    , 0.    , 0.    ],\n",
       "       ...,\n",
       "       [0.    , 0.    , 0.    , ..., 0.5   , 0.2125, 0.    ],\n",
       "       [0.    , 0.    , 0.    , ..., 0.1875, 0.675 , 0.025 ],\n",
       "       [0.    , 0.    , 0.    , ..., 0.025 , 0.0125, 0.9625]])"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "m.p"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Full rank first mean passage times"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[  48.        ,   87.96280048,   68.1089084 , ...,  443.76689275,\n",
       "         518.31000749, 1628.59025557],\n",
       "       [ 225.92564594,   48.        ,   78.75804364, ...,  440.0173313 ,\n",
       "         514.56045127, 1624.84070661],\n",
       "       [ 271.55443692,  102.484092  ,   48.        , ...,  438.93288204,\n",
       "         513.47599512, 1623.75624059],\n",
       "       ...,\n",
       "       [ 727.11189921,  570.15910508,  546.61934646, ...,   48.        ,\n",
       "         117.41906375, 1278.96860316],\n",
       "       [ 730.40467469,  573.45179415,  549.91216045, ...,   49.70722573,\n",
       "          48.        , 1202.06279368],\n",
       "       [ 754.8761577 ,  597.92333477,  574.38361779, ...,   43.23574191,\n",
       "         104.9460425 ,   48.        ]])"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "m.fmpt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 5.71428571,  2.75862069,  2.22222222,  1.77777778,  1.66666667,\n",
       "        1.73913043,  1.53846154,  1.53846154,  1.53846154,  1.42857143,\n",
       "        1.42857143,  1.56862745,  1.53846154,  1.40350877,  1.29032258,\n",
       "        1.21212121,  1.31147541,  1.37931034,  1.29032258,  1.25      ,\n",
       "        1.15942029,  1.12676056,  1.25      ,  1.17647059,  1.19402985,\n",
       "        1.08108108,  1.19402985,  1.25      ,  1.25      ,  1.14285714,\n",
       "        1.33333333,  1.26984127,  1.25      ,  1.37931034,  1.42857143,\n",
       "        1.31147541,  1.26984127,  1.25      ,  1.31147541,  1.25      ,\n",
       "        1.19402985,  1.25      ,  1.53846154,  1.6       ,  1.86046512,\n",
       "        2.        ,  3.07692308, 26.66666667])"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "m.sojourn_time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "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>Staying Probability</th>\n",
       "      <th>Sojourn Time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.8250</td>\n",
       "      <td>5.714286</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.6375</td>\n",
       "      <td>2.758621</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.5500</td>\n",
       "      <td>2.222222</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.4375</td>\n",
       "      <td>1.777778</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.4000</td>\n",
       "      <td>1.666667</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Staying Probability  Sojourn Time\n",
       "1               0.8250      5.714286\n",
       "2               0.6375      2.758621\n",
       "3               0.5500      2.222222\n",
       "4               0.4375      1.777778\n",
       "5               0.4000      1.666667"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_fullrank = pd.DataFrame(np.c_[m.p.diagonal(),m.sojourn_time], columns=[\"Staying Probability\",\"Sojourn Time\"], index = np.arange(m.p.shape[0])+1)\n",
    "df_fullrank.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[<matplotlib.axes._subplots.AxesSubplot object at 0x1a2ad213c8>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x1a2ad64668>]],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_fullrank.plot(subplots=True, layout=(1,2), figsize=(15,5))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/weikang/anaconda3/lib/python3.6/site-packages/scipy/stats/stats.py:1713: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.\n",
      "  return np.add.reduce(sorted[indexer] * weights, axis=axis) / sumval\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a2ae70908>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot(m.fmpt.flatten(),kde=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Geographic Rank Markov"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "from giddy.markov import GeoRank_Markov, Markov, sojourn_time\n",
    "gm = GeoRank_Markov(pci)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[38.,  0.,  8., ...,  0.,  0.,  0.],\n",
       "       [ 0., 15.,  0., ...,  0.,  1.,  0.],\n",
       "       [ 6.,  0., 44., ...,  5.,  0.,  0.],\n",
       "       ...,\n",
       "       [ 2.,  0.,  5., ..., 34.,  0.,  0.],\n",
       "       [ 0.,  0.,  0., ...,  0., 18.,  2.],\n",
       "       [ 0.,  0.,  0., ...,  0.,  3., 14.]])"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gm.transitions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0.475 , 0.    , 0.1   , ..., 0.    , 0.    , 0.    ],\n",
       "       [0.    , 0.1875, 0.    , ..., 0.    , 0.0125, 0.    ],\n",
       "       [0.075 , 0.    , 0.55  , ..., 0.0625, 0.    , 0.    ],\n",
       "       ...,\n",
       "       [0.025 , 0.    , 0.0625, ..., 0.425 , 0.    , 0.    ],\n",
       "       [0.    , 0.    , 0.    , ..., 0.    , 0.225 , 0.025 ],\n",
       "       [0.    , 0.    , 0.    , ..., 0.    , 0.0375, 0.175 ]])"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gm.p"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1.9047619 , 1.23076923, 2.22222222, 1.73913043, 1.15942029,\n",
       "       3.80952381, 1.70212766, 1.25      , 1.31147541, 1.11111111])"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gm.sojourn_time[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 1.9047619 ,  1.23076923,  2.22222222,  1.73913043,  1.15942029,\n",
       "        3.80952381,  1.70212766,  1.25      ,  1.31147541,  1.11111111,\n",
       "        1.73913043,  1.37931034,  1.17647059,  1.21212121,  1.33333333,\n",
       "        1.37931034,  1.09589041,  2.10526316,  2.        ,  1.45454545,\n",
       "        1.26984127, 26.66666667,  1.19402985,  1.23076923,  1.09589041,\n",
       "        1.56862745,  1.26984127,  2.42424242,  1.50943396,  2.        ,\n",
       "        1.29032258,  1.09589041,  1.6       ,  1.42857143,  1.25      ,\n",
       "        1.45454545,  1.29032258,  1.6       ,  1.17647059,  1.56862745,\n",
       "        1.25      ,  1.37931034,  1.45454545,  1.42857143,  1.29032258,\n",
       "        1.73913043,  1.29032258,  1.21212121])"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gm.sojourn_time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 48.        ,  63.35532038,  92.75274652, ...,  82.47515731,\n",
       "         71.01114491,  68.65737127],\n",
       "       [108.25928005,  48.        , 127.99032986, ...,  92.03098299,\n",
       "         63.36652935,  61.82733039],\n",
       "       [ 76.96801786,  64.7713783 ,  48.        , ...,  73.84595169,\n",
       "         72.24682723,  69.77497173],\n",
       "       ...,\n",
       "       [ 93.3107474 ,  62.47670463, 105.80634118, ...,  48.        ,\n",
       "         69.30121319,  67.08838421],\n",
       "       [113.65278078,  61.1987031 , 133.57991745, ...,  96.0103924 ,\n",
       "         48.        ,  56.74165107],\n",
       "       [114.71894813,  63.4019776 , 134.73381719, ...,  97.287895  ,\n",
       "         61.45565054,  48.        ]])"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gm.fmpt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "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>Name</th>\n",
       "      <th>STATE_FIPS</th>\n",
       "      <th>1929</th>\n",
       "      <th>1930</th>\n",
       "      <th>1931</th>\n",
       "      <th>1932</th>\n",
       "      <th>1933</th>\n",
       "      <th>1934</th>\n",
       "      <th>1935</th>\n",
       "      <th>1936</th>\n",
       "      <th>...</th>\n",
       "      <th>geo_fmpt_to_Virginia</th>\n",
       "      <th>geo_fmpt_from_Virginia</th>\n",
       "      <th>geo_fmpt_to_Washington</th>\n",
       "      <th>geo_fmpt_from_Washington</th>\n",
       "      <th>geo_fmpt_to_West Virginia</th>\n",
       "      <th>geo_fmpt_from_West Virginia</th>\n",
       "      <th>geo_fmpt_to_Wisconsin</th>\n",
       "      <th>geo_fmpt_from_Wisconsin</th>\n",
       "      <th>geo_fmpt_to_Wyoming</th>\n",
       "      <th>geo_fmpt_from_Wyoming</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Alabama</td>\n",
       "      <td>1</td>\n",
       "      <td>323</td>\n",
       "      <td>267</td>\n",
       "      <td>224</td>\n",
       "      <td>162</td>\n",
       "      <td>166</td>\n",
       "      <td>211</td>\n",
       "      <td>217</td>\n",
       "      <td>251</td>\n",
       "      <td>...</td>\n",
       "      <td>72.186055</td>\n",
       "      <td>109.828532</td>\n",
       "      <td>82.994754</td>\n",
       "      <td>118.769984</td>\n",
       "      <td>82.475157</td>\n",
       "      <td>93.310747</td>\n",
       "      <td>71.011145</td>\n",
       "      <td>113.652781</td>\n",
       "      <td>68.657371</td>\n",
       "      <td>114.718948</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Arizona</td>\n",
       "      <td>4</td>\n",
       "      <td>600</td>\n",
       "      <td>520</td>\n",
       "      <td>429</td>\n",
       "      <td>321</td>\n",
       "      <td>308</td>\n",
       "      <td>362</td>\n",
       "      <td>416</td>\n",
       "      <td>462</td>\n",
       "      <td>...</td>\n",
       "      <td>67.544447</td>\n",
       "      <td>60.838807</td>\n",
       "      <td>76.090895</td>\n",
       "      <td>66.729262</td>\n",
       "      <td>92.030983</td>\n",
       "      <td>62.476705</td>\n",
       "      <td>63.366529</td>\n",
       "      <td>61.198703</td>\n",
       "      <td>61.827330</td>\n",
       "      <td>63.401978</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Arkansas</td>\n",
       "      <td>5</td>\n",
       "      <td>310</td>\n",
       "      <td>228</td>\n",
       "      <td>215</td>\n",
       "      <td>157</td>\n",
       "      <td>157</td>\n",
       "      <td>187</td>\n",
       "      <td>207</td>\n",
       "      <td>247</td>\n",
       "      <td>...</td>\n",
       "      <td>73.650943</td>\n",
       "      <td>129.533691</td>\n",
       "      <td>84.071211</td>\n",
       "      <td>138.692513</td>\n",
       "      <td>73.845952</td>\n",
       "      <td>105.806341</td>\n",
       "      <td>72.246827</td>\n",
       "      <td>133.579917</td>\n",
       "      <td>69.774972</td>\n",
       "      <td>134.733817</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>California</td>\n",
       "      <td>6</td>\n",
       "      <td>991</td>\n",
       "      <td>887</td>\n",
       "      <td>749</td>\n",
       "      <td>580</td>\n",
       "      <td>546</td>\n",
       "      <td>603</td>\n",
       "      <td>660</td>\n",
       "      <td>771</td>\n",
       "      <td>...</td>\n",
       "      <td>71.377700</td>\n",
       "      <td>111.644884</td>\n",
       "      <td>62.230417</td>\n",
       "      <td>97.908341</td>\n",
       "      <td>104.922271</td>\n",
       "      <td>121.670243</td>\n",
       "      <td>69.368408</td>\n",
       "      <td>110.668388</td>\n",
       "      <td>59.998457</td>\n",
       "      <td>105.965215</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Colorado</td>\n",
       "      <td>8</td>\n",
       "      <td>634</td>\n",
       "      <td>578</td>\n",
       "      <td>471</td>\n",
       "      <td>354</td>\n",
       "      <td>353</td>\n",
       "      <td>368</td>\n",
       "      <td>444</td>\n",
       "      <td>542</td>\n",
       "      <td>...</td>\n",
       "      <td>69.627179</td>\n",
       "      <td>57.106339</td>\n",
       "      <td>66.353930</td>\n",
       "      <td>52.229230</td>\n",
       "      <td>98.797636</td>\n",
       "      <td>66.464398</td>\n",
       "      <td>60.762589</td>\n",
       "      <td>52.324565</td>\n",
       "      <td>55.559020</td>\n",
       "      <td>53.872702</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 180 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         Name  STATE_FIPS  1929  1930  1931  1932  1933  1934  1935  1936  \\\n",
       "0     Alabama           1   323   267   224   162   166   211   217   251   \n",
       "1     Arizona           4   600   520   429   321   308   362   416   462   \n",
       "2    Arkansas           5   310   228   215   157   157   187   207   247   \n",
       "3  California           6   991   887   749   580   546   603   660   771   \n",
       "4    Colorado           8   634   578   471   354   353   368   444   542   \n",
       "\n",
       "           ...            geo_fmpt_to_Virginia  geo_fmpt_from_Virginia  \\\n",
       "0          ...                       72.186055              109.828532   \n",
       "1          ...                       67.544447               60.838807   \n",
       "2          ...                       73.650943              129.533691   \n",
       "3          ...                       71.377700              111.644884   \n",
       "4          ...                       69.627179               57.106339   \n",
       "\n",
       "   geo_fmpt_to_Washington  geo_fmpt_from_Washington  \\\n",
       "0               82.994754                118.769984   \n",
       "1               76.090895                 66.729262   \n",
       "2               84.071211                138.692513   \n",
       "3               62.230417                 97.908341   \n",
       "4               66.353930                 52.229230   \n",
       "\n",
       "   geo_fmpt_to_West Virginia  geo_fmpt_from_West Virginia  \\\n",
       "0                  82.475157                    93.310747   \n",
       "1                  92.030983                    62.476705   \n",
       "2                  73.845952                   105.806341   \n",
       "3                 104.922271                   121.670243   \n",
       "4                  98.797636                    66.464398   \n",
       "\n",
       "   geo_fmpt_to_Wisconsin  geo_fmpt_from_Wisconsin  geo_fmpt_to_Wyoming  \\\n",
       "0              71.011145               113.652781            68.657371   \n",
       "1              63.366529                61.198703            61.827330   \n",
       "2              72.246827               133.579917            69.774972   \n",
       "3              69.368408               110.668388            59.998457   \n",
       "4              60.762589                52.324565            55.559020   \n",
       "\n",
       "   geo_fmpt_from_Wyoming  \n",
       "0             114.718948  \n",
       "1              63.401978  \n",
       "2             134.733817  \n",
       "3             105.965215  \n",
       "4              53.872702  \n",
       "\n",
       "[5 rows x 180 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "income_table[\"geo_sojourn_time\"] = gm.sojourn_time\n",
    "i = 0\n",
    "for state in income_table[\"Name\"]:\n",
    "    income_table[\"geo_fmpt_to_\" + state] = gm.fmpt[:,i]\n",
    "    income_table[\"geo_fmpt_from_\" + state] = gm.fmpt[i,:]\n",
    "    i = i + 1\n",
    "income_table.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "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>AREA</th>\n",
       "      <th>PERIMETER</th>\n",
       "      <th>STATE_</th>\n",
       "      <th>STATE_ID</th>\n",
       "      <th>STATE_NAME</th>\n",
       "      <th>STATE_FIPS_x</th>\n",
       "      <th>SUB_REGION</th>\n",
       "      <th>STATE_ABBR</th>\n",
       "      <th>geometry</th>\n",
       "      <th>Name</th>\n",
       "      <th>...</th>\n",
       "      <th>geo_fmpt_to_Virginia</th>\n",
       "      <th>geo_fmpt_from_Virginia</th>\n",
       "      <th>geo_fmpt_to_Washington</th>\n",
       "      <th>geo_fmpt_from_Washington</th>\n",
       "      <th>geo_fmpt_to_West Virginia</th>\n",
       "      <th>geo_fmpt_from_West Virginia</th>\n",
       "      <th>geo_fmpt_to_Wisconsin</th>\n",
       "      <th>geo_fmpt_from_Wisconsin</th>\n",
       "      <th>geo_fmpt_to_Wyoming</th>\n",
       "      <th>geo_fmpt_from_Wyoming</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>20.750</td>\n",
       "      <td>34.956</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Washington</td>\n",
       "      <td>53</td>\n",
       "      <td>Pacific</td>\n",
       "      <td>WA</td>\n",
       "      <td>(POLYGON ((-122.400749206543 48.22539520263672...</td>\n",
       "      <td>Washington</td>\n",
       "      <td>...</td>\n",
       "      <td>71.663055</td>\n",
       "      <td>73.756804</td>\n",
       "      <td>48.000000</td>\n",
       "      <td>48.000000</td>\n",
       "      <td>101.592400</td>\n",
       "      <td>81.692586</td>\n",
       "      <td>65.219124</td>\n",
       "      <td>70.701226</td>\n",
       "      <td>53.126177</td>\n",
       "      <td>64.476985</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>45.132</td>\n",
       "      <td>34.527</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>Montana</td>\n",
       "      <td>30</td>\n",
       "      <td>Mtn</td>\n",
       "      <td>MT</td>\n",
       "      <td>POLYGON ((-111.4746322631836 44.70223999023438...</td>\n",
       "      <td>Montana</td>\n",
       "      <td>...</td>\n",
       "      <td>69.918931</td>\n",
       "      <td>59.067897</td>\n",
       "      <td>76.184088</td>\n",
       "      <td>64.710823</td>\n",
       "      <td>90.781850</td>\n",
       "      <td>58.795201</td>\n",
       "      <td>63.455248</td>\n",
       "      <td>58.975522</td>\n",
       "      <td>60.881954</td>\n",
       "      <td>60.553000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>9.571</td>\n",
       "      <td>18.899</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>Maine</td>\n",
       "      <td>23</td>\n",
       "      <td>N Eng</td>\n",
       "      <td>ME</td>\n",
       "      <td>(POLYGON ((-69.77778625488281 44.0740737915039...</td>\n",
       "      <td>Maine</td>\n",
       "      <td>...</td>\n",
       "      <td>69.431862</td>\n",
       "      <td>53.872836</td>\n",
       "      <td>77.512381</td>\n",
       "      <td>62.862378</td>\n",
       "      <td>87.734760</td>\n",
       "      <td>54.244823</td>\n",
       "      <td>66.257807</td>\n",
       "      <td>56.905741</td>\n",
       "      <td>61.978506</td>\n",
       "      <td>58.336426</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>21.874</td>\n",
       "      <td>21.353</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>North Dakota</td>\n",
       "      <td>38</td>\n",
       "      <td>W N Cen</td>\n",
       "      <td>ND</td>\n",
       "      <td>POLYGON ((-98.73005676269531 45.93829727172852...</td>\n",
       "      <td>North Dakota</td>\n",
       "      <td>...</td>\n",
       "      <td>69.441690</td>\n",
       "      <td>56.526347</td>\n",
       "      <td>76.659646</td>\n",
       "      <td>62.823668</td>\n",
       "      <td>85.031218</td>\n",
       "      <td>49.511240</td>\n",
       "      <td>67.362718</td>\n",
       "      <td>58.717458</td>\n",
       "      <td>64.386382</td>\n",
       "      <td>59.728719</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>22.598</td>\n",
       "      <td>22.746</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>South Dakota</td>\n",
       "      <td>46</td>\n",
       "      <td>W N Cen</td>\n",
       "      <td>SD</td>\n",
       "      <td>POLYGON ((-102.7879333496094 42.99532318115234...</td>\n",
       "      <td>South Dakota</td>\n",
       "      <td>...</td>\n",
       "      <td>68.229894</td>\n",
       "      <td>61.548209</td>\n",
       "      <td>78.886304</td>\n",
       "      <td>68.794083</td>\n",
       "      <td>88.192659</td>\n",
       "      <td>55.754109</td>\n",
       "      <td>66.187694</td>\n",
       "      <td>63.802359</td>\n",
       "      <td>64.336311</td>\n",
       "      <td>65.070022</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 189 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     AREA  PERIMETER  STATE_  STATE_ID    STATE_NAME STATE_FIPS_x SUB_REGION  \\\n",
       "0  20.750     34.956       1         1    Washington           53    Pacific   \n",
       "1  45.132     34.527       2         2       Montana           30        Mtn   \n",
       "2   9.571     18.899       3         3         Maine           23      N Eng   \n",
       "3  21.874     21.353       4         4  North Dakota           38    W N Cen   \n",
       "4  22.598     22.746       5         5  South Dakota           46    W N Cen   \n",
       "\n",
       "  STATE_ABBR                                           geometry          Name  \\\n",
       "0         WA  (POLYGON ((-122.400749206543 48.22539520263672...    Washington   \n",
       "1         MT  POLYGON ((-111.4746322631836 44.70223999023438...       Montana   \n",
       "2         ME  (POLYGON ((-69.77778625488281 44.0740737915039...         Maine   \n",
       "3         ND  POLYGON ((-98.73005676269531 45.93829727172852...  North Dakota   \n",
       "4         SD  POLYGON ((-102.7879333496094 42.99532318115234...  South Dakota   \n",
       "\n",
       "           ...            geo_fmpt_to_Virginia  geo_fmpt_from_Virginia  \\\n",
       "0          ...                       71.663055               73.756804   \n",
       "1          ...                       69.918931               59.067897   \n",
       "2          ...                       69.431862               53.872836   \n",
       "3          ...                       69.441690               56.526347   \n",
       "4          ...                       68.229894               61.548209   \n",
       "\n",
       "   geo_fmpt_to_Washington  geo_fmpt_from_Washington  \\\n",
       "0               48.000000                 48.000000   \n",
       "1               76.184088                 64.710823   \n",
       "2               77.512381                 62.862378   \n",
       "3               76.659646                 62.823668   \n",
       "4               78.886304                 68.794083   \n",
       "\n",
       "   geo_fmpt_to_West Virginia  geo_fmpt_from_West Virginia  \\\n",
       "0                 101.592400                    81.692586   \n",
       "1                  90.781850                    58.795201   \n",
       "2                  87.734760                    54.244823   \n",
       "3                  85.031218                    49.511240   \n",
       "4                  88.192659                    55.754109   \n",
       "\n",
       "   geo_fmpt_to_Wisconsin  geo_fmpt_from_Wisconsin  geo_fmpt_to_Wyoming  \\\n",
       "0              65.219124                70.701226            53.126177   \n",
       "1              63.455248                58.975522            60.881954   \n",
       "2              66.257807                56.905741            61.978506   \n",
       "3              67.362718                58.717458            64.386382   \n",
       "4              66.187694                63.802359            64.336311   \n",
       "\n",
       "   geo_fmpt_from_Wyoming  \n",
       "0              64.476985  \n",
       "1              60.553000  \n",
       "2              58.336426  \n",
       "3              59.728719  \n",
       "4              65.070022  \n",
       "\n",
       "[5 rows x 189 columns]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "geo_table = gpd.read_file(ps.examples.get_path('us48.shp'))\n",
    "# income_table = pd.read_csv(libpysal.examples.get_path(\"usjoin.csv\"))\n",
    "complete_table = geo_table.merge(income_table,left_on='STATE_NAME',right_on='Name')\n",
    "complete_table.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['AREA', 'PERIMETER', 'STATE_', 'STATE_ID', 'STATE_NAME', 'STATE_FIPS_x',\n",
       "       'SUB_REGION', 'STATE_ABBR', 'geometry', 'Name',\n",
       "       ...\n",
       "       'geo_fmpt_to_Virginia', 'geo_fmpt_from_Virginia',\n",
       "       'geo_fmpt_to_Washington', 'geo_fmpt_from_Washington',\n",
       "       'geo_fmpt_to_West Virginia', 'geo_fmpt_from_West Virginia',\n",
       "       'geo_fmpt_to_Wisconsin', 'geo_fmpt_from_Wisconsin',\n",
       "       'geo_fmpt_to_Wyoming', 'geo_fmpt_from_Wyoming'],\n",
       "      dtype='object', length=189)"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "complete_table.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Visualizing first mean passage time from/to California/Mississippi:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/weikang/anaconda3/lib/python3.6/site-packages/pysal/__init__.py:65: VisibleDeprecationWarning: PySAL's API will be changed on 2018-12-31. The last release made with this API is version 1.14.4. A preview of the next API version is provided in the `pysal` 2.0 prelease candidate. The API changes and a guide on how to change imports is provided at https://migrating.pysal.org\n",
      "  ), VisibleDeprecationWarning)\n",
      "/Users/weikang/anaconda3/lib/python3.6/site-packages/scipy/stats/stats.py:1713: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.\n",
      "  return np.add.reduce(sorted[indexer] * weights, axis=axis) / sumval\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x504 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(nrows=2, ncols=2,figsize = (15,7))\n",
    "target_states = [\"California\",\"Mississippi\"]\n",
    "directions = [\"from\",\"to\"]\n",
    "for i, direction in enumerate(directions):\n",
    "    for j, target in enumerate(target_states):\n",
    "        ax = axes[i,j]\n",
    "        col = direction+\"_\"+target\n",
    "        complete_table.plot(ax=ax,column = \"geo_fmpt_\"+ col,cmap='OrRd', \n",
    "                    scheme='quantiles', legend=True)\n",
    "        ax.set_title(\"First Mean Passage Time \"+direction+\" \"+target)\n",
    "        ax.axis('off')\n",
    "        leg = ax.get_legend()\n",
    "        leg.set_bbox_to_anchor((0.8, 0.15, 0.16, 0.2))\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Visualizing sojourn time for each US state:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/weikang/anaconda3/lib/python3.6/site-packages/scipy/stats/stats.py:1713: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.\n",
      "  return np.add.reduce(sorted[indexer] * weights, axis=axis) / sumval\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x504 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(nrows=1, ncols=2,figsize = (15,7))\n",
    "schemes = [\"Quantiles\",\"Equal_Interval\"]\n",
    "for i, scheme in enumerate(schemes):\n",
    "    ax = axes[i]\n",
    "    complete_table.plot(ax=ax,column = \"geo_sojourn_time\",cmap='OrRd', \n",
    "                scheme=scheme, legend=True)\n",
    "    ax.set_title(\"Rank Sojourn Time (\"+scheme+\")\")\n",
    "    ax.axis('off')\n",
    "    leg = ax.get_legend()\n",
    "    leg.set_bbox_to_anchor((0.8, 0.15, 0.16, 0.2))\n",
    "plt.tight_layout()"
   ]
  }
 ],
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