StartTimes_IMM.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import packages \n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "# Set Working Directory\n",
    "import os\n",
    "# os.chdir(r'C:\\Personal\\IMM') # absolute path, using \\ and r prefix\n",
    "# wd = os.getcwd()\n",
    "\n",
    "import json\n",
    "from pprint import pprint\n",
    "import timeit\n",
    "from decimal import *\n",
    "import traceback\n",
    "from itertools import cycle\n",
    "import itertools\n",
    "import random\n",
    "\n",
    "import functools\n",
    "from balsa.matrices import read_mdf, to_mdf\n",
    "\n",
    "from balsa.cheval import sample_from_weights\n",
    "\n",
    "import logging\n",
    "# set random seed to be used\n",
    "seed = 12345\n",
    "prng = 3\n",
    "\n",
    "dirListing = 'c:\\\\personal\\\\IMM'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "temp_df = pd.read_csv(r\"c:/personal/imm/foo_nonmand.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wall time: 11.8 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "# batch in ggh zone numbers and add in two columns for i and j zones\n",
    "ggh = pd.read_csv(os.path.join(dirListing, \"GGH_zones.csv\"))\n",
    "if 'ggh_zone'  not in ggh:\n",
    "    print(\"The 'ggh_zone' column does not exist.\")\n",
    "\n",
    "# prepare the dataframe to create a matrix that reflects zone to zone travel times\n",
    "ggh['key'] = 0\n",
    "ggh1 = ggh\n",
    "\n",
    "# batch in SOV non toll times\n",
    "ttime = pd.read_csv(r\"c:/personal/IMM/2011_AM_SOV_NT_traveltime_matrix.csv\", \n",
    "                    header = None, delim_whitespace=True, names = ['taz_i', 'taz_j', 'time'])\n",
    "\n",
    "# attach times to ggh o-d pairs\n",
    "ggh2 = pd.merge(ggh1, ggh, how='left', on='key')\n",
    "ggh2.columns = ['taz_i', 'key', 'taz_j']\n",
    "ggh2.drop('key', 1, inplace = True)\n",
    "ggh2 = pd.merge(ggh2, ttime, how = 'left', on = ['taz_i', 'taz_j']).fillna(0)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wall time: 2.35 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "# Transfer O-D level auto travel times\n",
    "temp_df = pd.merge(temp_df, ggh2, how = 'left', on = ['taz_i', 'taz_j'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(58454, 25)"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temp_df.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Reorder Tours to create Start Times "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "def sorted_tours(vals, group):\n",
    "    \"\"\"\n",
    "    \n",
    "    \"\"\"\n",
    "    \n",
    "    if len(vals) == 1:\n",
    "        # if there is only one home-based tour then re-sort the indices such that the index where the\n",
    "        # destination has a home becomes the last index, and then build a dataframe\n",
    "        home_dest_ind = group.iloc[np.where(group['activity_j'] == 'home')].index.values\n",
    "        a = (group.index.values == home_dest_ind).argsort(kind='mergesort')\n",
    "        sorted_df = pd.DataFrame(group.values[a], group.index.values[a], group.columns)\n",
    "          \n",
    "    if len(vals) > 1:\n",
    "    # only if the individual makes more than one home-based tour then run this code. \n",
    "        for i in range(0, len(vals)):\n",
    "            \n",
    "            first_ind = vals[i]\n",
    "#             print(first_ind)\n",
    "            \n",
    "            if i+1 < len(vals):\n",
    "#                 print(i)\n",
    "                \n",
    "                next_ind = vals[i+1]-1\n",
    "#                 print(next_ind)\n",
    "                df_collect = group.loc[first_ind:next_ind,:]\n",
    "            \n",
    "            else:\n",
    "                \n",
    "                next_ind = group.tail(1).index.item()\n",
    "#                 print(next_ind)\n",
    "                df_collect = group.loc[first_ind:next_ind,:]\n",
    "            \n",
    "            # run the sorting code. This is a little involved and here are the steps\n",
    "            # First find the row index where the tour comes back home\n",
    "            # Second, get all the indices that lie beyond the closed home tour. These records\n",
    "            # are those that belong to the work based other tour.\n",
    "            home_dest_ind = df_collect.iloc[np.where(df_collect['activity_j'] == 'home')].index.values\n",
    "            beyond_home_dest = df_collect[df_collect.index >= home_dest_ind[0]]\n",
    "            beyond_home_dest_ind = beyond_home_dest[beyond_home_dest.index > home_dest_ind[0]].index.values\n",
    "\n",
    "            # Now replace the indices such that the work-based other trips are slotted in just after\n",
    "            # the home-work trip purpose.\n",
    "            all_ind = df_collect.index.values\n",
    "            b = np.setdiff1d(all_ind, beyond_home_dest_ind)\n",
    "            new_ind = np.insert(b, 1, beyond_home_dest_ind, axis=0)\n",
    "            sorted_df = df_collect.reindex(new_ind)\n",
    "            \n",
    "    return sorted_df\n",
    "    \n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wall time: 18 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "\n",
    "sorted_df = {}\n",
    "\n",
    "# select all the records that need reordering\n",
    "worktours = temp_df.loc[temp_df['subtour_id'] == 0]\n",
    "worktours = worktours.groupby(['hhid', 'pid']).size().reset_index(name = 'counts')\n",
    "worktours = worktours.loc[worktours['hhid'] == 2]\n",
    "\n",
    "for i in range(0, len(worktours)):\n",
    "    \n",
    "    # enumerate over the household and person ids\n",
    "    hhold_id = worktours.at[worktours.index[i], 'hhid']\n",
    "    per_id = worktours.at[worktours.index[i], 'pid']\n",
    "    \n",
    "    # subset the main dataframe\n",
    "    worktours_fix = temp_df.loc[(temp_df['hhid'] == hhold_id) & (temp_df['pid'] == per_id)]\n",
    "\n",
    "    for name, group in worktours_fix.groupby(['hhid', 'pid']):\n",
    "\n",
    "        # get the indices where the activity_i is home\n",
    "        home_orig_ind = group.iloc[np.where(group['activity_i'] == 'home')].index.values\n",
    "        vals = home_orig_ind.tolist()\n",
    "        \n",
    "        # run function to sort the tours\n",
    "        sorted_df[name] = sorted_tours(vals, group)\n",
    "\n",
    "# # concatenate the dictionary of dataframes collected. \n",
    "# # Then remove the corresponding records from the master dataframe and concatenate\n",
    "# # the sorted tours\n",
    "# sdf = pd.concat(sorted_df.values())\n",
    "# temp_df = temp_df[~temp_df.index.isin(sdf.index)]\n",
    "# temp_df = pd.concat([temp_df, sdf]).sort_values(['hhid', 'pid'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>hhid</th>\n",
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       "      <td>home</td>\n",
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       "      <td>1</td>\n",
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       "      <td>7.963339</td>\n",
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       "    <tr>\n",
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       "      <td>-1</td>\n",
       "      <td>1</td>\n",
       "      <td>work</td>\n",
       "      <td>home</td>\n",
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       "      <td>0.298704</td>\n",
       "      <td>1</td>\n",
       "      <td>WBO_3_1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>13.329500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>business</td>\n",
       "      <td>work</td>\n",
       "      <td>1169</td>\n",
       "      <td>1129</td>\n",
       "      <td>inbound</td>\n",
       "      <td>...</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>0.656411</td>\n",
       "      <td>0</td>\n",
       "      <td>WBO_3_0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>18.263590</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>-1</td>\n",
       "      <td>1</td>\n",
       "      <td>work</td>\n",
       "      <td>other</td>\n",
       "      <td>1129</td>\n",
       "      <td>1169</td>\n",
       "      <td>inbound</td>\n",
       "      <td>...</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>0.008388</td>\n",
       "      <td>1</td>\n",
       "      <td>WBO_3_1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>13.329500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>-1</td>\n",
       "      <td>2</td>\n",
       "      <td>other</td>\n",
       "      <td>home</td>\n",
       "      <td>1169</td>\n",
       "      <td>1001</td>\n",
       "      <td>inbound</td>\n",
       "      <td>...</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>0.106444</td>\n",
       "      <td>0</td>\n",
       "      <td>HBO_3_0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>28.721440</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>0</td>\n",
       "      <td>home</td>\n",
       "      <td>work</td>\n",
       "      <td>1001</td>\n",
       "      <td>1001</td>\n",
       "      <td>outbound</td>\n",
       "      <td>...</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>0.809813</td>\n",
       "      <td>0</td>\n",
       "      <td>HBW_3_0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>1</td>\n",
       "      <td>work</td>\n",
       "      <td>home</td>\n",
       "      <td>1001</td>\n",
       "      <td>1001</td>\n",
       "      <td>inbound</td>\n",
       "      <td>...</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>0.872176</td>\n",
       "      <td>0</td>\n",
       "      <td>HBW_3_0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>0</td>\n",
       "      <td>home</td>\n",
       "      <td>school</td>\n",
       "      <td>1001</td>\n",
       "      <td>1146</td>\n",
       "      <td>outbound</td>\n",
       "      <td>...</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>0.964648</td>\n",
       "      <td>0</td>\n",
       "      <td>HBS_3_0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.411010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>1</td>\n",
       "      <td>school</td>\n",
       "      <td>home</td>\n",
       "      <td>1146</td>\n",
       "      <td>1001</td>\n",
       "      <td>inbound</td>\n",
       "      <td>...</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>0.723685</td>\n",
       "      <td>0</td>\n",
       "      <td>HBS_3_0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.698015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>0</td>\n",
       "      <td>home</td>\n",
       "      <td>work</td>\n",
       "      <td>1001</td>\n",
       "      <td>1017</td>\n",
       "      <td>outbound</td>\n",
       "      <td>...</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.642475</td>\n",
       "      <td>1</td>\n",
       "      <td>HBW_0_1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7.012561</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>1</td>\n",
       "      <td>work</td>\n",
       "      <td>home</td>\n",
       "      <td>1017</td>\n",
       "      <td>1001</td>\n",
       "      <td>inbound</td>\n",
       "      <td>...</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.717454</td>\n",
       "      <td>1</td>\n",
       "      <td>HBW_0_1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>6.982286</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>-1</td>\n",
       "      <td>0</td>\n",
       "      <td>home</td>\n",
       "      <td>other</td>\n",
       "      <td>1001</td>\n",
       "      <td>1043</td>\n",
       "      <td>outbound</td>\n",
       "      <td>...</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.467599</td>\n",
       "      <td>0</td>\n",
       "      <td>HBO_0_0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>20.457610</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>-1</td>\n",
       "      <td>1</td>\n",
       "      <td>other</td>\n",
       "      <td>home</td>\n",
       "      <td>1043</td>\n",
       "      <td>1001</td>\n",
       "      <td>inbound</td>\n",
       "      <td>...</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.325585</td>\n",
       "      <td>1</td>\n",
       "      <td>HBO_0_1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>18.085100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>0</td>\n",
       "      <td>home</td>\n",
       "      <td>work</td>\n",
       "      <td>1001</td>\n",
       "      <td>4038</td>\n",
       "      <td>outbound</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>0.439645</td>\n",
       "      <td>1</td>\n",
       "      <td>HBW_3_1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>6.278722</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>1</td>\n",
       "      <td>work</td>\n",
       "      <td>home</td>\n",
       "      <td>4038</td>\n",
       "      <td>1001</td>\n",
       "      <td>inbound</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>0.729689</td>\n",
       "      <td>1</td>\n",
       "      <td>HBW_3_1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>10.765110</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>-1</td>\n",
       "      <td>0</td>\n",
       "      <td>home</td>\n",
       "      <td>shop</td>\n",
       "      <td>1001</td>\n",
       "      <td>1012</td>\n",
       "      <td>outbound</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>0.994015</td>\n",
       "      <td>0</td>\n",
       "      <td>HBM_3_0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>6.810360</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>-1</td>\n",
       "      <td>1</td>\n",
       "      <td>shop</td>\n",
       "      <td>home</td>\n",
       "      <td>1012</td>\n",
       "      <td>1001</td>\n",
       "      <td>inbound</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>0.676874</td>\n",
       "      <td>0</td>\n",
       "      <td>HBM_3_0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>6.178146</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>0</td>\n",
       "      <td>home</td>\n",
       "      <td>work</td>\n",
       "      <td>1001</td>\n",
       "      <td>1020</td>\n",
       "      <td>outbound</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>0.790823</td>\n",
       "      <td>0</td>\n",
       "      <td>HBW_3_0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.767431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>1</td>\n",
       "      <td>work</td>\n",
       "      <td>home</td>\n",
       "      <td>1020</td>\n",
       "      <td>1001</td>\n",
       "      <td>inbound</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>0.170914</td>\n",
       "      <td>0</td>\n",
       "      <td>HBW_3_0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.401660</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>58424</th>\n",
       "      <td>9994</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>1</td>\n",
       "      <td>work</td>\n",
       "      <td>home</td>\n",
       "      <td>1091</td>\n",
       "      <td>1007</td>\n",
       "      <td>inbound</td>\n",
       "      <td>...</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.041964</td>\n",
       "      <td>1</td>\n",
       "      <td>HBW_0_1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>18.879340</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58425</th>\n",
       "      <td>9994</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>work</td>\n",
       "      <td>business</td>\n",
       "      <td>1091</td>\n",
       "      <td>1117</td>\n",
       "      <td>outbound</td>\n",
       "      <td>...</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.445060</td>\n",
       "      <td>1</td>\n",
       "      <td>WBO_0_1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.146148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58426</th>\n",
       "      <td>9994</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>business</td>\n",
       "      <td>work</td>\n",
       "      <td>1117</td>\n",
       "      <td>1091</td>\n",
       "      <td>inbound</td>\n",
       "      <td>...</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.145541</td>\n",
       "      <td>1</td>\n",
       "      <td>WBO_0_1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.515683</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58427</th>\n",
       "      <td>9995</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>0</td>\n",
       "      <td>home</td>\n",
       "      <td>other</td>\n",
       "      <td>1007</td>\n",
       "      <td>1011</td>\n",
       "      <td>outbound</td>\n",
       "      <td>...</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.328845</td>\n",
       "      <td>1</td>\n",
       "      <td>HBO_0_1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.990515</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58428</th>\n",
       "      <td>9995</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>1</td>\n",
       "      <td>other</td>\n",
       "      <td>home</td>\n",
       "      <td>1011</td>\n",
       "      <td>1007</td>\n",
       "      <td>inbound</td>\n",
       "      <td>...</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.649624</td>\n",
       "      <td>0</td>\n",
       "      <td>HBO_0_0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.047098</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58429</th>\n",
       "      <td>9995</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>-1</td>\n",
       "      <td>0</td>\n",
       "      <td>home</td>\n",
       "      <td>shop</td>\n",
       "      <td>1007</td>\n",
       "      <td>1007</td>\n",
       "      <td>outbound</td>\n",
       "      <td>...</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.206316</td>\n",
       "      <td>1</td>\n",
       "      <td>HBM_0_1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58430</th>\n",
       "      <td>9995</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>-1</td>\n",
       "      <td>1</td>\n",
       "      <td>shop</td>\n",
       "      <td>home</td>\n",
       "      <td>1007</td>\n",
       "      <td>1007</td>\n",
       "      <td>inbound</td>\n",
       "      <td>...</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.443451</td>\n",
       "      <td>0</td>\n",
       "      <td>HBM_0_0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58431</th>\n",
       "      <td>9995</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>0</td>\n",
       "      <td>home</td>\n",
       "      <td>shop</td>\n",
       "      <td>1007</td>\n",
       "      <td>1007</td>\n",
       "      <td>outbound</td>\n",
       "      <td>...</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.512826</td>\n",
       "      <td>0</td>\n",
       "      <td>HBM_0_0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58432</th>\n",
       "      <td>9995</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>1</td>\n",
       "      <td>shop</td>\n",
       "      <td>home</td>\n",
       "      <td>1007</td>\n",
       "      <td>1007</td>\n",
       "      <td>inbound</td>\n",
       "      <td>...</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.331937</td>\n",
       "      <td>0</td>\n",
       "      <td>HBM_0_0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58433</th>\n",
       "      <td>9996</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>0</td>\n",
       "      <td>home</td>\n",
       "      <td>work</td>\n",
       "      <td>1007</td>\n",
       "      <td>1075</td>\n",
       "      <td>outbound</td>\n",
       "      <td>...</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>0.380054</td>\n",
       "      <td>1</td>\n",
       "      <td>HBW_3_1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>27.067600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58434</th>\n",
       "      <td>9996</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>1</td>\n",
       "      <td>work</td>\n",
       "      <td>shop</td>\n",
       "      <td>1075</td>\n",
       "      <td>1138</td>\n",
       "      <td>inbound</td>\n",
       "      <td>...</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>0.582787</td>\n",
       "      <td>1</td>\n",
       "      <td>WBO_3_1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7.477912</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58435</th>\n",
       "      <td>9996</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>2</td>\n",
       "      <td>shop</td>\n",
       "      <td>home</td>\n",
       "      <td>1138</td>\n",
       "      <td>1007</td>\n",
       "      <td>inbound</td>\n",
       "      <td>...</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>0.470400</td>\n",
       "      <td>1</td>\n",
       "      <td>HBM_3_1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>26.468140</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58436</th>\n",
       "      <td>9996</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>0</td>\n",
       "      <td>home</td>\n",
       "      <td>work</td>\n",
       "      <td>1007</td>\n",
       "      <td>4001</td>\n",
       "      <td>outbound</td>\n",
       "      <td>...</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>0.486293</td>\n",
       "      <td>1</td>\n",
       "      <td>HBW_3_1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>20.546570</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58437</th>\n",
       "      <td>9996</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>1</td>\n",
       "      <td>work</td>\n",
       "      <td>home</td>\n",
       "      <td>4001</td>\n",
       "      <td>1007</td>\n",
       "      <td>inbound</td>\n",
       "      <td>...</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>0.326941</td>\n",
       "      <td>1</td>\n",
       "      <td>HBW_3_1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>28.430550</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58438</th>\n",
       "      <td>9996</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>0</td>\n",
       "      <td>home</td>\n",
       "      <td>school</td>\n",
       "      <td>1007</td>\n",
       "      <td>1185</td>\n",
       "      <td>outbound</td>\n",
       "      <td>...</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>0.928624</td>\n",
       "      <td>0</td>\n",
       "      <td>HBS_3_0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.856430</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58439</th>\n",
       "      <td>9996</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>1</td>\n",
       "      <td>school</td>\n",
       "      <td>home</td>\n",
       "      <td>1185</td>\n",
       "      <td>1007</td>\n",
       "      <td>inbound</td>\n",
       "      <td>...</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>0.026934</td>\n",
       "      <td>0</td>\n",
       "      <td>HBS_3_0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>13.971350</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58440</th>\n",
       "      <td>9997</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>0</td>\n",
       "      <td>home</td>\n",
       "      <td>shop</td>\n",
       "      <td>1007</td>\n",
       "      <td>1007</td>\n",
       "      <td>outbound</td>\n",
       "      <td>...</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.065646</td>\n",
       "      <td>1</td>\n",
       "      <td>HBM_0_1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58441</th>\n",
       "      <td>9997</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>1</td>\n",
       "      <td>shop</td>\n",
       "      <td>home</td>\n",
       "      <td>1007</td>\n",
       "      <td>1007</td>\n",
       "      <td>inbound</td>\n",
       "      <td>...</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.223651</td>\n",
       "      <td>1</td>\n",
       "      <td>HBM_0_1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58442</th>\n",
       "      <td>9997</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>-1</td>\n",
       "      <td>0</td>\n",
       "      <td>home</td>\n",
       "      <td>shop</td>\n",
       "      <td>1007</td>\n",
       "      <td>1007</td>\n",
       "      <td>outbound</td>\n",
       "      <td>...</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.249593</td>\n",
       "      <td>1</td>\n",
       "      <td>HBM_0_1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58443</th>\n",
       "      <td>9997</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>-1</td>\n",
       "      <td>1</td>\n",
       "      <td>shop</td>\n",
       "      <td>other</td>\n",
       "      <td>1007</td>\n",
       "      <td>1008</td>\n",
       "      <td>outbound</td>\n",
       "      <td>...</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.909366</td>\n",
       "      <td>0</td>\n",
       "      <td>NHB_0_0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.014093</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58444</th>\n",
       "      <td>9997</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>-1</td>\n",
       "      <td>2</td>\n",
       "      <td>other</td>\n",
       "      <td>other</td>\n",
       "      <td>1008</td>\n",
       "      <td>1011</td>\n",
       "      <td>outbound</td>\n",
       "      <td>...</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.058834</td>\n",
       "      <td>1</td>\n",
       "      <td>NHB_0_1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.196367</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58445</th>\n",
       "      <td>9997</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>-1</td>\n",
       "      <td>3</td>\n",
       "      <td>other</td>\n",
       "      <td>shop</td>\n",
       "      <td>1011</td>\n",
       "      <td>1030</td>\n",
       "      <td>outbound</td>\n",
       "      <td>...</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.583497</td>\n",
       "      <td>0</td>\n",
       "      <td>NHB_0_0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>12.488250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58446</th>\n",
       "      <td>9997</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>-1</td>\n",
       "      <td>4</td>\n",
       "      <td>shop</td>\n",
       "      <td>home</td>\n",
       "      <td>1030</td>\n",
       "      <td>1007</td>\n",
       "      <td>inbound</td>\n",
       "      <td>...</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.781454</td>\n",
       "      <td>0</td>\n",
       "      <td>HBM_0_0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>12.344470</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58447</th>\n",
       "      <td>9998</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>0</td>\n",
       "      <td>home</td>\n",
       "      <td>work</td>\n",
       "      <td>1007</td>\n",
       "      <td>1063</td>\n",
       "      <td>outbound</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.758256</td>\n",
       "      <td>0</td>\n",
       "      <td>HBW_2_0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>23.069540</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58448</th>\n",
       "      <td>9998</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>1</td>\n",
       "      <td>work</td>\n",
       "      <td>home</td>\n",
       "      <td>1063</td>\n",
       "      <td>1007</td>\n",
       "      <td>inbound</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.531484</td>\n",
       "      <td>0</td>\n",
       "      <td>HBW_2_0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>18.124120</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58449</th>\n",
       "      <td>9998</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>0</td>\n",
       "      <td>home</td>\n",
       "      <td>work</td>\n",
       "      <td>1007</td>\n",
       "      <td>1017</td>\n",
       "      <td>outbound</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.397493</td>\n",
       "      <td>1</td>\n",
       "      <td>HBW_2_1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.054070</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58450</th>\n",
       "      <td>9998</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>1</td>\n",
       "      <td>work</td>\n",
       "      <td>home</td>\n",
       "      <td>1017</td>\n",
       "      <td>1007</td>\n",
       "      <td>inbound</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.923293</td>\n",
       "      <td>1</td>\n",
       "      <td>HBW_2_1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.815881</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58451</th>\n",
       "      <td>9999</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>0</td>\n",
       "      <td>home</td>\n",
       "      <td>other</td>\n",
       "      <td>1007</td>\n",
       "      <td>1011</td>\n",
       "      <td>outbound</td>\n",
       "      <td>...</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.986178</td>\n",
       "      <td>0</td>\n",
       "      <td>HBO_2_0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.990515</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58452</th>\n",
       "      <td>9999</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>1</td>\n",
       "      <td>other</td>\n",
       "      <td>other</td>\n",
       "      <td>1011</td>\n",
       "      <td>1015</td>\n",
       "      <td>inbound</td>\n",
       "      <td>...</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.690381</td>\n",
       "      <td>0</td>\n",
       "      <td>NHB_2_0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.055459</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58453</th>\n",
       "      <td>9999</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>2</td>\n",
       "      <td>other</td>\n",
       "      <td>home</td>\n",
       "      <td>1015</td>\n",
       "      <td>1007</td>\n",
       "      <td>inbound</td>\n",
       "      <td>...</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.650950</td>\n",
       "      <td>0</td>\n",
       "      <td>HBO_2_0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.404227</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>58454 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       hhid  pid  tour_id  subtour_id  trip_id activity_i activity_j  taz_i  \\\n",
       "0         1    0        0          -1        0       home       work   1001   \n",
       "1         1    0        0          -1        1       work       home   1015   \n",
       "2         2    0        0          -1        0       home       work   1001   \n",
       "3         2    0        0          -1        1       work       home   1035   \n",
       "4         2    0        0           0        0       work   business   1035   \n",
       "5         2    0        0           0        1   business      other   1221   \n",
       "6         2    0        0           0        2      other      other   1388   \n",
       "7         2    0        0           0        3      other      other   1411   \n",
       "8         2    0        0           0        4      other       work   1441   \n",
       "9         4    0        0          -1        0       home       work   1001   \n",
       "10        4    0        0          -1        1       work       home   1129   \n",
       "11        4    0        1          -1        0       home       work   1001   \n",
       "14        4    0        1           0        0       work   business   1129   \n",
       "15        4    0        1           0        1   business       work   1169   \n",
       "12        4    0        1          -1        1       work      other   1129   \n",
       "13        4    0        1          -1        2      other       home   1169   \n",
       "16        4    1        0          -1        0       home       work   1001   \n",
       "17        4    1        0          -1        1       work       home   1001   \n",
       "18        4    2        0          -1        0       home     school   1001   \n",
       "19        4    2        0          -1        1     school       home   1146   \n",
       "20        5    0        0          -1        0       home       work   1001   \n",
       "21        5    0        0          -1        1       work       home   1017   \n",
       "22        5    0        1          -1        0       home      other   1001   \n",
       "23        5    0        1          -1        1      other       home   1043   \n",
       "24        6    0        0          -1        0       home       work   1001   \n",
       "25        6    0        0          -1        1       work       home   4038   \n",
       "26        6    0        1          -1        0       home       shop   1001   \n",
       "27        6    0        1          -1        1       shop       home   1012   \n",
       "28        6    1        0          -1        0       home       work   1001   \n",
       "29        6    1        0          -1        1       work       home   1020   \n",
       "...     ...  ...      ...         ...      ...        ...        ...    ...   \n",
       "58424  9994    2        0          -1        1       work       home   1091   \n",
       "58425  9994    2        0           0        0       work   business   1091   \n",
       "58426  9994    2        0           0        1   business       work   1117   \n",
       "58427  9995    0        0          -1        0       home      other   1007   \n",
       "58428  9995    0        0          -1        1      other       home   1011   \n",
       "58429  9995    0        1          -1        0       home       shop   1007   \n",
       "58430  9995    0        1          -1        1       shop       home   1007   \n",
       "58431  9995    1        0          -1        0       home       shop   1007   \n",
       "58432  9995    1        0          -1        1       shop       home   1007   \n",
       "58433  9996    0        0          -1        0       home       work   1007   \n",
       "58434  9996    0        0          -1        1       work       shop   1075   \n",
       "58435  9996    0        0          -1        2       shop       home   1138   \n",
       "58436  9996    1        0          -1        0       home       work   1007   \n",
       "58437  9996    1        0          -1        1       work       home   4001   \n",
       "58438  9996    2        0          -1        0       home     school   1007   \n",
       "58439  9996    2        0          -1        1     school       home   1185   \n",
       "58440  9997    0        0          -1        0       home       shop   1007   \n",
       "58441  9997    0        0          -1        1       shop       home   1007   \n",
       "58442  9997    0        1          -1        0       home       shop   1007   \n",
       "58443  9997    0        1          -1        1       shop      other   1007   \n",
       "58444  9997    0        1          -1        2      other      other   1008   \n",
       "58445  9997    0        1          -1        3      other       shop   1011   \n",
       "58446  9997    0        1          -1        4       shop       home   1030   \n",
       "58447  9998    0        0          -1        0       home       work   1007   \n",
       "58448  9998    0        0          -1        1       work       home   1063   \n",
       "58449  9998    1        0          -1        0       home       work   1007   \n",
       "58450  9998    1        0          -1        1       work       home   1017   \n",
       "58451  9999    0        0          -1        0       home      other   1007   \n",
       "58452  9999    0        0          -1        1      other      other   1011   \n",
       "58453  9999    0        0          -1        2      other       home   1015   \n",
       "\n",
       "       taz_j tour_direction    ...     dtype hhsize  nveh  auto_suff  \\\n",
       "0       1015       outbound    ...         5      1     1          2   \n",
       "1       1001        inbound    ...         5      1     1          2   \n",
       "2       1035       outbound    ...         6      1     1          2   \n",
       "3       1001        inbound    ...         6      1     1          2   \n",
       "4       1221       outbound    ...         6      1     1          2   \n",
       "5       1388        inbound    ...         6      1     1          2   \n",
       "6       1411        inbound    ...         6      1     1          2   \n",
       "7       1441        inbound    ...         6      1     1          2   \n",
       "8       1035        inbound    ...         6      1     1          2   \n",
       "9       1129       outbound    ...         5      3     1          1   \n",
       "10      1001        inbound    ...         5      3     1          1   \n",
       "11      1129       outbound    ...         5      3     1          1   \n",
       "14      1169       outbound    ...         5      3     1          1   \n",
       "15      1129        inbound    ...         5      3     1          1   \n",
       "12      1169        inbound    ...         5      3     1          1   \n",
       "13      1001        inbound    ...         5      3     1          1   \n",
       "16      1001       outbound    ...         5      3     1          1   \n",
       "17      1001        inbound    ...         5      3     1          1   \n",
       "18      1146       outbound    ...         5      3     1          1   \n",
       "19      1001        inbound    ...         5      3     1          1   \n",
       "20      1017       outbound    ...         5      1     0          0   \n",
       "21      1001        inbound    ...         5      1     0          0   \n",
       "22      1043       outbound    ...         5      1     0          0   \n",
       "23      1001        inbound    ...         5      1     0          0   \n",
       "24      4038       outbound    ...         1      5     2          1   \n",
       "25      1001        inbound    ...         1      5     2          1   \n",
       "26      1012       outbound    ...         1      5     2          1   \n",
       "27      1001        inbound    ...         1      5     2          1   \n",
       "28      1020       outbound    ...         1      5     2          1   \n",
       "29      1001        inbound    ...         1      5     2          1   \n",
       "...      ...            ...    ...       ...    ...   ...        ...   \n",
       "58424   1007        inbound    ...         5      3     0          0   \n",
       "58425   1117       outbound    ...         5      3     0          0   \n",
       "58426   1091        inbound    ...         5      3     0          0   \n",
       "58427   1011       outbound    ...         5      2     0          0   \n",
       "58428   1007        inbound    ...         5      2     0          0   \n",
       "58429   1007       outbound    ...         5      2     0          0   \n",
       "58430   1007        inbound    ...         5      2     0          0   \n",
       "58431   1007       outbound    ...         5      2     0          0   \n",
       "58432   1007        inbound    ...         5      2     0          0   \n",
       "58433   1075       outbound    ...         6      3     1          1   \n",
       "58434   1138        inbound    ...         6      3     1          1   \n",
       "58435   1007        inbound    ...         6      3     1          1   \n",
       "58436   4001       outbound    ...         6      3     1          1   \n",
       "58437   1007        inbound    ...         6      3     1          1   \n",
       "58438   1185       outbound    ...         6      3     1          1   \n",
       "58439   1007        inbound    ...         6      3     1          1   \n",
       "58440   1007       outbound    ...         5      1     0          0   \n",
       "58441   1007        inbound    ...         5      1     0          0   \n",
       "58442   1007       outbound    ...         5      1     0          0   \n",
       "58443   1008       outbound    ...         5      1     0          0   \n",
       "58444   1011       outbound    ...         5      1     0          0   \n",
       "58445   1030       outbound    ...         5      1     0          0   \n",
       "58446   1007        inbound    ...         5      1     0          0   \n",
       "58447   1063       outbound    ...         4      2     1          1   \n",
       "58448   1007        inbound    ...         4      2     1          1   \n",
       "58449   1017       outbound    ...         4      2     1          1   \n",
       "58450   1007        inbound    ...         4      2     1          1   \n",
       "58451   1011       outbound    ...         5      2     1          1   \n",
       "58452   1015        inbound    ...         5      2     1          1   \n",
       "58453   1007        inbound    ...         5      2     1          1   \n",
       "\n",
       "       market_seg      rnum  peak_flag  dict_flag  solver_flag       time  \n",
       "0               5  0.929616          0    HBW_5_0          0.0   7.452790  \n",
       "1               5  0.316376          0    HBW_5_0          0.0   6.949050  \n",
       "2               4  0.183919          1    HBW_4_1          1.0   7.963339  \n",
       "3               4  0.204560          1    HBW_4_1          1.0   7.943841  \n",
       "4               4  0.567725          1    WBO_4_1          1.0  14.019400  \n",
       "5               4  0.595545          0    NHB_4_0          1.0  10.497960  \n",
       "6               4  0.964515          0    NHB_4_0          1.0  10.595180  \n",
       "7               4  0.653177          0    NHB_4_0          1.0   4.731844  \n",
       "8               4  0.748907          0    WBO_4_0          1.0  23.701310  \n",
       "9               3  0.653570          1    HBW_3_1          1.0  35.894530  \n",
       "10              3  0.747715          1    HBW_3_1          1.0  27.070540  \n",
       "11              3  0.961307          0    HBW_3_0          1.0  35.894530  \n",
       "14              3  0.298704          1    WBO_3_1          1.0  13.329500  \n",
       "15              3  0.656411          0    WBO_3_0          1.0  18.263590  \n",
       "12              3  0.008388          1    WBO_3_1          1.0  13.329500  \n",
       "13              3  0.106444          0    HBO_3_0          1.0  28.721440  \n",
       "16              3  0.809813          0    HBW_3_0          0.0   0.000000  \n",
       "17              3  0.872176          0    HBW_3_0          0.0   0.000000  \n",
       "18              3  0.964648          0    HBS_3_0          0.0  10.411010  \n",
       "19              3  0.723685          0    HBS_3_0          0.0   9.698015  \n",
       "20              0  0.642475          1    HBW_0_1          1.0   7.012561  \n",
       "21              0  0.717454          1    HBW_0_1          1.0   6.982286  \n",
       "22              0  0.467599          0    HBO_0_0          1.0  20.457610  \n",
       "23              0  0.325585          1    HBO_0_1          1.0  18.085100  \n",
       "24              3  0.439645          1    HBW_3_1          1.0   6.278722  \n",
       "25              3  0.729689          1    HBW_3_1          1.0  10.765110  \n",
       "26              3  0.994015          0    HBM_3_0          1.0   6.810360  \n",
       "27              3  0.676874          0    HBM_3_0          1.0   6.178146  \n",
       "28              3  0.790823          0    HBW_3_0          0.0   6.767431  \n",
       "29              3  0.170914          0    HBW_3_0          0.0   6.401660  \n",
       "...           ...       ...        ...        ...          ...        ...  \n",
       "58424           0  0.041964          1    HBW_0_1          1.0  18.879340  \n",
       "58425           0  0.445060          1    WBO_0_1          1.0   2.146148  \n",
       "58426           0  0.145541          1    WBO_0_1          1.0   2.515683  \n",
       "58427           0  0.328845          1    HBO_0_1          1.0   2.990515  \n",
       "58428           0  0.649624          0    HBO_0_0          1.0   3.047098  \n",
       "58429           0  0.206316          1    HBM_0_1          1.0   0.000000  \n",
       "58430           0  0.443451          0    HBM_0_0          1.0   0.000000  \n",
       "58431           0  0.512826          0    HBM_0_0          1.0   0.000000  \n",
       "58432           0  0.331937          0    HBM_0_0          1.0   0.000000  \n",
       "58433           3  0.380054          1    HBW_3_1          1.0  27.067600  \n",
       "58434           3  0.582787          1    WBO_3_1          1.0   7.477912  \n",
       "58435           3  0.470400          1    HBM_3_1          1.0  26.468140  \n",
       "58436           3  0.486293          1    HBW_3_1          0.0  20.546570  \n",
       "58437           3  0.326941          1    HBW_3_1          0.0  28.430550  \n",
       "58438           3  0.928624          0    HBS_3_0          0.0  11.856430  \n",
       "58439           3  0.026934          0    HBS_3_0          0.0  13.971350  \n",
       "58440           0  0.065646          1    HBM_0_1          1.0   0.000000  \n",
       "58441           0  0.223651          1    HBM_0_1          1.0   0.000000  \n",
       "58442           0  0.249593          1    HBM_0_1          1.0   0.000000  \n",
       "58443           0  0.909366          0    NHB_0_0          1.0   1.014093  \n",
       "58444           0  0.058834          1    NHB_0_1          1.0   2.196367  \n",
       "58445           0  0.583497          0    NHB_0_0          1.0  12.488250  \n",
       "58446           0  0.781454          0    HBM_0_0          1.0  12.344470  \n",
       "58447           2  0.758256          0    HBW_2_0          0.0  23.069540  \n",
       "58448           2  0.531484          0    HBW_2_0          0.0  18.124120  \n",
       "58449           2  0.397493          1    HBW_2_1          0.0   9.054070  \n",
       "58450           2  0.923293          1    HBW_2_1          0.0   9.815881  \n",
       "58451           2  0.986178          0    HBO_2_0          1.0   2.990515  \n",
       "58452           2  0.690381          0    NHB_2_0          1.0   2.055459  \n",
       "58453           2  0.650950          0    HBO_2_0          1.0   3.404227  \n",
       "\n",
       "[58454 rows x 25 columns]"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temp_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{(2,\n",
       "  0):   hhid pid tour_id subtour_id trip_id activity_i activity_j taz_i taz_j  \\\n",
       " 2    2   0       0         -1       0       home       work  1001  1035   \n",
       " 4    2   0       0          0       0       work   business  1035  1221   \n",
       " 5    2   0       0          0       1   business      other  1221  1388   \n",
       " 6    2   0       0          0       2      other      other  1388  1411   \n",
       " 7    2   0       0          0       3      other      other  1411  1441   \n",
       " 8    2   0       0          0       4      other       work  1441  1035   \n",
       " 3    2   0       0         -1       1       work       home  1035  1001   \n",
       " \n",
       "   tour_direction   ...    dtype hhsize nveh auto_suff market_seg      rnum  \\\n",
       " 2       outbound   ...        6      1    1         2          4  0.183919   \n",
       " 4       outbound   ...        6      1    1         2          4  0.567725   \n",
       " 5        inbound   ...        6      1    1         2          4  0.595545   \n",
       " 6        inbound   ...        6      1    1         2          4  0.964515   \n",
       " 7        inbound   ...        6      1    1         2          4  0.653177   \n",
       " 8        inbound   ...        6      1    1         2          4  0.748907   \n",
       " 3        inbound   ...        6      1    1         2          4   0.20456   \n",
       " \n",
       "   peak_flag dict_flag solver_flag     time  \n",
       " 2         1   HBW_4_1           1  7.96334  \n",
       " 4         1   WBO_4_1           1  14.0194  \n",
       " 5         0   NHB_4_0           1   10.498  \n",
       " 6         0   NHB_4_0           1  10.5952  \n",
       " 7         0   NHB_4_0           1  4.73184  \n",
       " 8         0   WBO_4_0           1  23.7013  \n",
       " 3         1   HBW_4_1           1  7.94384  \n",
       " \n",
       " [7 rows x 25 columns]}"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sorted_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Timer unit: 3.64649e-07 s\n",
       "\n",
       "Total time: 0.00382335 s\n",
       "File: <ipython-input-38-08735aba5feb>\n",
       "Function: sorted_tours at line 1\n",
       "\n",
       "Line #      Hits         Time  Per Hit   % Time  Line Contents\n",
       "==============================================================\n",
       "     1                                           def sorted_tours(vals, group):\n",
       "     2                                               \"\"\"\n",
       "     3                                               \n",
       "     4                                               \"\"\"\n",
       "     5                                               \n",
       "     6         1            9      9.0      0.1      if len(vals) == 1:\n",
       "     7                                                   # if there is only one home-based tour then re-sort the indices such that the index where the\n",
       "     8                                                   # destination has a home becomes the last index, and then build a dataframe\n",
       "     9         1         7598   7598.0     72.5          home_dest_ind = group.iloc[np.where(group['activity_j'] == 'home')].index.values\n",
       "    10         1           65     65.0      0.6          a = (group.index.values == home_dest_ind).argsort(kind='mergesort')\n",
       "    11         1         2802   2802.0     26.7          sorted_df = pd.DataFrame(group.values[a], group.index.values[a], group.columns)\n",
       "    12                                                     \n",
       "    13         1            8      8.0      0.1      if len(vals) > 1:\n",
       "    14                                               # only if the individual makes more than one home-based tour then run this code. \n",
       "    15                                                   for i in range(0, len(vals)):\n",
       "    16                                                       \n",
       "    17                                                       first_ind = vals[i]\n",
       "    18                                           #             print(first_ind)\n",
       "    19                                                       \n",
       "    20                                                       if i+1 < len(vals):\n",
       "    21                                           #                 print(i)\n",
       "    22                                                           \n",
       "    23                                                           next_ind = vals[i+1]-1\n",
       "    24                                           #                 print(next_ind)\n",
       "    25                                                           df_collect = group.loc[first_ind:next_ind,:]\n",
       "    26                                                       \n",
       "    27                                                       else:\n",
       "    28                                                           \n",
       "    29                                                           next_ind = group.tail(1).index.item()\n",
       "    30                                           #                 print(next_ind)\n",
       "    31                                                           df_collect = group.loc[first_ind:next_ind,:]\n",
       "    32                                                       \n",
       "    33                                                       # run the sorting code. This is a little involved and here are the steps\n",
       "    34                                                       # First find the row index where the tour comes back home\n",
       "    35                                                       # Second, get all the indices that lie beyond the closed home tour. These records\n",
       "    36                                                       # are those that belong to the work based other tour.\n",
       "    37                                                       home_dest_ind = df_collect.iloc[np.where(df_collect['activity_j'] == 'home')].index.values\n",
       "    38                                                       beyond_home_dest = df_collect[df_collect.index >= home_dest_ind[0]]\n",
       "    39                                                       beyond_home_dest_ind = beyond_home_dest[beyond_home_dest.index > home_dest_ind[0]].index.values\n",
       "    40                                           \n",
       "    41                                                       # Now replace the indices such that the work-based other trips are slotted in just after\n",
       "    42                                                       # the home-work trip purpose.\n",
       "    43                                                       all_ind = df_collect.index.values\n",
       "    44                                                       b = np.setdiff1d(all_ind, beyond_home_dest_ind)\n",
       "    45                                                       new_ind = np.insert(b, 1, beyond_home_dest_ind, axis=0)\n",
       "    46                                                       sorted_df = df_collect.reindex(new_ind)\n",
       "    47                                                       \n",
       "    48         1            3      3.0      0.0      return sorted_df"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%load_ext line_profiler\n",
    "%lprun -f sorted_tours sorted_tours(vals, group)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Converted to Function - dont run this"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%time\n",
    "sorted_df = {}\n",
    "\n",
    "for name, group in worktours_fix.groupby(['hhid', 'pid']): \n",
    "    print(name)\n",
    "    \n",
    "    # get the indices where the activity_i is home\n",
    "    home_orig_ind = group.iloc[np.where(group['activity_i'] == 'home')].index.values\n",
    "    vals = home_orig_ind.tolist()\n",
    "    \n",
    "    if len(vals) == 1:\n",
    "        # if there is only one home-based tour then resort the indices such that the index where the\n",
    "        # destination has a home becomes the last index, and then build a dataframe\n",
    "        home_dest_ind = group.iloc[np.where(group['activity_j'] == 'home')].index.values\n",
    "        a = (group.index.values == home_dest_ind).argsort(kind='mergesort')\n",
    "        sorted_df = pd.DataFrame(group.values[a], group.index.values[a], group.columns)\n",
    "          \n",
    "    if len(vals) > 1:\n",
    "    # only if the individual makes more than one home-based tour then run this code. \n",
    "        for i in range(0, len(vals)):\n",
    "            \n",
    "            first_ind = vals[i]\n",
    "            print(first_ind)\n",
    "            \n",
    "            if i+1 < len(vals):\n",
    "                print(i)\n",
    "                \n",
    "                next_ind = vals[i+1]-1\n",
    "                print(next_ind)\n",
    "                df_collect = group.loc[first_ind:next_ind,:]\n",
    "            \n",
    "            else:\n",
    "                \n",
    "                next_ind = group.tail(1).index.item()\n",
    "                print(next_ind)\n",
    "                df_collect = group.loc[first_ind:next_ind,:]\n",
    "            \n",
    "            # run the sorting code. This is a little involved and here are the steps\n",
    "            # First find the row index where the tour comes back home\n",
    "            # Second, get all the indices that lie beyond the closed home tour. These records\n",
    "            # are those that belong to the work based other tour.\n",
    "            home_dest_ind = df_collect.iloc[np.where(df_collect['activity_j'] == 'home')].index.values\n",
    "            beyond_home_dest = df_collect[df_collect.index >= home_dest_ind[0]]\n",
    "            beyond_home_dest_ind = beyond_home_dest[beyond_home_dest.index > home_dest_ind[0]].index.values\n",
    "            \n",
    "            # Now replace the indices such that the work-based other trips are slotted in just after\n",
    "            # the home-work trip purpose.\n",
    "            all_ind = df_collect.index.values\n",
    "            b = np.setdiff1d(all_ind, beyond_home_dest_ind)\n",
    "            new_ind = np.insert(b, 1, beyond_home_dest_ind, axis=0)\n",
    "            sorted_df = df_collect.reindex(new_ind)\n",
    "            "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Now Create Start Times"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Batch in the Time Distributions that Nem created."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Second, I have split NHB into inbound and outbound by keeping their values their same"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "time_dist = pd.read_csv(r\"c:/personal/imm/start_time_distribution.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "def validate_timedist():\n",
    "    'add in a check that ensures a nonzero entry at transition points between time periods'\n",
    "    pass"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Get the dataframe slice that corresponds to the purpose and direction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "def start_times_np(df_array, time_dist, results, i):\n",
    "    \"\"\"\n",
    "    This function takes the trips_hhold dataframe and samples a start time for each trip based on the purpose and direction.\n",
    "    It ignores whether each trip record has been flagged by a peak/off-peak flag.\n",
    "    \n",
    "    Args: dataframe array, time distribution df, results, iterator\n",
    "    \n",
    "    Return: dataframe with start time attached \n",
    "    \"\"\"\n",
    "    # slice dataframe by purpose and direction and save indices to numpy array. This is useful for concatenating\n",
    "    row_purp = df_array[i][10]\n",
    "    row_dir = df_array[i][9]\n",
    "    \n",
    "    # sample start times and save to numpy array\n",
    "    weight_column = row_purp + '_' + row_dir \n",
    "#     print(\"column to sample from %s\" %weight_column)\n",
    "    \n",
    "    # get start time for first row \n",
    "    if i == 0:\n",
    "        \n",
    "        pkflag_row = df_array[i][21]\n",
    "        time_dist1 = time_dist.loc[time_dist['pk_flag'] == pkflag_row]\n",
    "        \n",
    "        # now sample a start time\n",
    "        start_time = time_dist1.sample(n=1, weights= time_dist1[weight_column], replace=True, random_state=seed)\n",
    "        start_time = start_time[['Time']].values\n",
    "        start_time = start_time[0][0]\n",
    "#         print(\"first start_time %s\" %start_time)\n",
    "\n",
    "        arr_time = start_time + df_array[i][24]/60\n",
    "        d = df_array[i][24]/60\n",
    "#         print(\"travel time of first row %s\" %d)\n",
    "#         print(\"arrival time of first row %s\" %arr_time)\n",
    "        \n",
    "    else:\n",
    "        # slice the time distribution dataframe by purpose and direction to account for the fact that now it must \n",
    "        # respect the arrival time of the above record i.e. if the arrival time of the above record is 10:00, then the\n",
    "        # time distribution must be sliced to only have records beyond 10:00\n",
    "        pkflag_row = df_array[i][21]\n",
    "        arr_time = results[i-1][1]   # get results from previous row and second column\n",
    "#         print(\"arrival time from previous row %s used for slicing the time dist df\" %arr_time)\n",
    "        \n",
    "        time_dist1 = time_dist.loc[time_dist['pk_flag'] == pkflag_row]\n",
    "        time_dist1 = time_dist1.loc[time_dist1['Time'] >= arr_time]\n",
    "        \n",
    "        # if the above slicing of the time distribution dataframe has left any records than sample\n",
    "        if len(time_dist1)>0:        \n",
    "        # now sample a start time\n",
    "            start_time = time_dist1.sample(n=1, weights= time_dist1[weight_column], replace=True, random_state=seed)\n",
    "            start_time = start_time[['Time']].values ###\n",
    "            start_time = start_time[0][0]\n",
    "#             print(\"current start_time %s\" %start_time)\n",
    "        else:\n",
    "            # if the slicing of the time distribution dataframe is left with no rows than grab the start times\n",
    "            # from the previous row. This implies that the start times between this trip and the one before are\n",
    "            # very close to each other.\n",
    "            start_time = results[i-1][0]\n",
    "#             print(\"start time borrowed from the previous trip %s\" %start_time)\n",
    "        \n",
    "        # recompute arr_time to save to results\n",
    "        arr_time = start_time + df_array[i][24]/60\n",
    "        d1 = df_array[i][24]/60\n",
    "#         print(\"travel time of current row %s\" %d1)\n",
    "#         print(\"arrival time of current row %s\" %arr_time)\n",
    "        \n",
    "   \n",
    "    return (start_time, arr_time)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['hhid', 'pid', 'tour_id', 'subtour_id', 'trip_id', 'activity_i',\n",
       "       'activity_j', 'taz_i', 'taz_j', 'tour_direction', 'purpose',\n",
       "       'trip_direction', 'peak_factor', 'taz', 'hhinc', 'dtype', 'hhsize',\n",
       "       'nveh', 'auto_suff', 'market_seg', 'rnum', 'peak_flag', 'dict_flag',\n",
       "       'solver_flag', 'time'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temp_df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wall time: 2min 18s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "\n",
    "results1 = []\n",
    "\n",
    "for name, group in temp_df.groupby(['hhid', 'pid']):\n",
    "#     print(name)\n",
    "    # make array\n",
    "    df_array = group.values\n",
    "    nrows, ncols = df_array.shape\n",
    "    results = [] \n",
    "    \n",
    "    for i in range(nrows):\n",
    "#         print(\"row %s\" %i)\n",
    "\n",
    "        times = start_times_np(df_array, time_dist, results, i)\n",
    "        results.append(times)\n",
    "#         print(results)\n",
    "    results1.append(results)\n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "from itertools import chain\n",
    "# flatten the nested lists and then get ready for concantenating the results to the master dataframe\n",
    "l = list(chain(*results1))\n",
    "l_df = pd.DataFrame(l, index = temp_df.index, columns=['start_time', 'arrival_time'])\n",
    "\n",
    "# attach the times\n",
    "temp_df = pd.concat([temp_df, l_df], axis = 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(58454, 27)"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temp_df.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Informal ride pairing model. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* A starting window is defined that decides how many trips are potential receipients i.e. if the user defines the window as 15 minutes, then all trips that have a start time of +-15 mins from a donor trip are potential receipients for a particular donor.\n",
    "\n",
    "* In the informal ride pairing model, the only two things that matter are the distance from a receipient to a donor's zone\n",
    "and then the distance between destinations of the receipient and donor.\n",
    "\n",
    "* Not all records can be considered to be donors. The reasoning was as follows that if the trip times between an \n",
    "O-D pair are very low than there is no need to ride pair. \n",
    "\n",
    "* Thus, only trips whose O-D times exceed two times the time threshold are considered as donors. A time threshold basically\n",
    "represents zones that are within a certain travel time from the donor zone.\n",
    "\n",
    "* For an **informal** ride pairing model it was not considered appropriate to create a similarity index for selecting receipients to match to donors. This is because while one could think that a person belonging to a hhold to segment 5 might not want to ride pair to a hhold from segment 0. While this could be true in a **formal** ride pairing model, not so much in an app driven world of **informal** ride pairin. Further, there isn't another quanitifiable metric that could be used for generating a similarity index."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Get all trip records that are within use defined threhold start time"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Randomly pick a record to start the process"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wall time: 158 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "# Only keep those records where the travel time between the O-D pairs is at least twice or some user defined value\n",
    "# above the time it takes for a person to arrive at another's house\n",
    "# travel time thresholds\n",
    "time_thold = 5\n",
    "catchment = 2\n",
    "pair_selection_thold = 0.8\n",
    "ride_pair_vehlist = list(range(4000000))\n",
    "\n",
    "# SUBSET DATAFRAME\n",
    "##################\n",
    "# If the travel time divided by the buffer time is more than pair_selection_thold then consider those trips for\n",
    "# ride pairing. The travel time for the other O-D pairs is not significant enough that one would want to wait \n",
    "# to create a car pool. These variables can be played with, but the current default settings are used here.\n",
    "temp_df['pair_criteria'] = temp_df['time']/(temp_df['time'] + time_thold*catchment)\n",
    "pair_candidates = temp_df.loc[temp_df['pair_criteria'] >= pair_selection_thold]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1652, 28)"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pair_candidates.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "def prepare_to_pair(pair_candidates, ride_pair_vehlist):\n",
    "    \"\"\"\n",
    "    \n",
    "    \"\"\"\n",
    "    # randomly sample a record and set a ride_pairing flag. This flag is unique and will be added to records that are\n",
    "    # a good ride pairing match.\n",
    "    frec = pair_candidates.sample(n = 1, replace = False)\n",
    "    frec['ride_pair'] = np.random.choice(ride_pair_vehlist, replace = False)\n",
    "\n",
    "    # get start_time of first record; start zone; and destination zone for the Donor trip\n",
    "    frec_starttime = frec.at[frec.index[0],'start_time']\n",
    "    frec_startzone = frec.at[frec.index[0], 'taz_i']\n",
    "    frec_destzone = frec.at[frec.index[0], 'taz_j']\n",
    "\n",
    "    # generate the window of start_times for the receipient trips\n",
    "    window_time = 15\n",
    "    start_time_below = frec_starttime - window_time/60\n",
    "    start_time_up = frec_starttime + window_time/60\n",
    "    \n",
    "    return (frec, frec_startzone, frec_destzone, start_time_below, start_time_up)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_zone(ttime, frec_zone, time_thold, col_name):\n",
    "    \"\"\"\n",
    "    \n",
    "    \"\"\"\n",
    "    # first slice the travel time dataframe for the origin or destination zone\n",
    "    ttime_slice = ttime.iloc[np.where(ttime['taz_i'].values == frec_zone)]\n",
    "    # now slice the datafame to only keep those zones that are within a travel time buffer \n",
    "    # of the origin/dest zone\n",
    "    ttime_slice = ttime_slice.iloc[np.where(ttime_slice['time'].values <= time_thold)]\n",
    "\n",
    "    # now get all the origin or destination zone that is within the travel time buffer\n",
    "    get_zones = ttime_slice['taz_j'].values\n",
    "    get_zones_df = pd.DataFrame(get_zones, columns = [col_name])\n",
    "    get_zones_df['key'] = 0\n",
    "    \n",
    "    return get_zones_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "def prepare_candidates(or_df, dt_df, pair_candidates, start_time_below, start_time_up, frec):\n",
    "    \"\"\"\n",
    "    \n",
    "    \"\"\"\n",
    "    # now get a full dataframe of all origins and destinations\n",
    "    full_df = pd.merge(or_df, dt_df, how = 'left', on = 'key')\n",
    "    full_df = full_df.loc[full_df['taz_i'] != full_df['taz_j']]\n",
    "\n",
    "    # Only keep those trips that are within the start_time buffer.\n",
    "    # get all the records that match the origin-destination interchanges. \n",
    "    # Also get rid of intrazonals.\n",
    "    pair_candidates = pair_candidates.loc[(pair_candidates['start_time'] >= start_time_below) & \n",
    "                                          (pair_candidates['start_time'] <= start_time_up)]\n",
    "    \n",
    "    #TODO fix this code to mirror the one done for START TIMES\n",
    "    ############################################################################################\n",
    "    temp_df2 = pair_candidates.loc[(pair_candidates['taz_i'].isin(full_df['taz_i'])) & \n",
    "                                   (pair_candidates['taz_j'].isin(full_df['taz_j']))]\n",
    "    temp_df2 = temp_df2.loc[temp_df2['taz_i'] != temp_df2['taz_j']]\n",
    "    ############################################################################################\n",
    "\n",
    "    # add in a flag to identify the records that will be matched together\n",
    "    pair_flag = frec['ride_pair'].values\n",
    "    temp_df2['ride_pair'] = pair_flag[0]\n",
    "    \n",
    "    return (temp_df2, pair_flag)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "No receipient available for the donor [48031]\n",
      "No receipient available for the donor [28427]\n",
      "No receipient available for the donor [39536]\n",
      "No receipient available for the donor [26204]\n",
      "No receipient available for the donor [39514]\n",
      "No receipient available for the donor [24078]\n",
      "No receipient available for the donor [56369]\n",
      "No receipient available for the donor [50621]\n",
      "No receipient available for the donor [315]\n",
      "No receipient available for the donor [51321]\n",
      "No receipient available for the donor [16159]\n",
      "No receipient available for the donor [222]\n",
      "No receipient available for the donor [32366]\n",
      "No receipient available for the donor [11257]\n",
      "No receipient available for the donor [47535]\n",
      "No receipient available for the donor [46173]\n",
      "No receipient available for the donor [35361]\n",
      "No receipient available for the donor [3339]\n",
      "No receipient available for the donor [44239]\n",
      "No receipient available for the donor [50706]\n",
      "No receipient available for the donor [26407]\n",
      "No receipient available for the donor [36093]\n",
      "No receipient available for the donor [611]\n",
      "No receipient available for the donor [19496]\n",
      "No receipient available for the donor [8713]\n",
      "No receipient available for the donor [32995]\n",
      "No receipient available for the donor [25640]\n",
      "No receipient available for the donor [52059]\n",
      "No receipient available for the donor [38731]\n",
      "No receipient available for the donor [27979]\n",
      "No receipient available for the donor [6565]\n",
      "No receipient available for the donor [44035]\n",
      "No receipient available for the donor [155]\n",
      "No receipient available for the donor [16003]\n",
      "No receipient available for the donor [2116]\n",
      "No receipient available for the donor [6754]\n",
      "No receipient available for the donor [25911]\n",
      "No receipient available for the donor [49063]\n",
      "No receipient available for the donor [6119]\n",
      "No receipient available for the donor [30722]\n",
      "No receipient available for the donor [19347]\n",
      "No receipient available for the donor [7878]\n",
      "No receipient available for the donor [21749]\n",
      "No receipient available for the donor [50456]\n",
      "No receipient available for the donor [38824]\n",
      "No receipient available for the donor [13338]\n",
      "No receipient available for the donor [26674]\n",
      "No receipient available for the donor [48673]\n",
      "No receipient available for the donor [10996]\n",
      "No receipient available for the donor [12404]\n",
      "No receipient available for the donor [49068]\n",
      "No receipient available for the donor [6294]\n",
      "No receipient available for the donor [4560]\n",
      "No receipient available for the donor [54099]\n",
      "No receipient available for the donor [54582]\n",
      "No receipient available for the donor [48202]\n",
      "No receipient available for the donor [8137]\n",
      "No receipient available for the donor [575]\n",
      "No receipient available for the donor [25154]\n",
      "No receipient available for the donor [7466]\n",
      "No receipient available for the donor [11771]\n",
      "No receipient available for the donor [37610]\n",
      "No receipient available for the donor [39731]\n",
      "No receipient available for the donor [56694]\n",
      "No receipient available for the donor [28728]\n",
      "No receipient available for the donor [42861]\n",
      "No receipient available for the donor [13666]\n",
      "No receipient available for the donor [12405]\n",
      "No receipient available for the donor [7249]\n",
      "No receipient available for the donor [21098]\n",
      "No receipient available for the donor [57968]\n",
      "No receipient available for the donor [18792]\n",
      "No receipient available for the donor [18225]\n",
      "No receipient available for the donor [56258]\n",
      "No receipient available for the donor [31618]\n",
      "No receipient available for the donor [36497]\n",
      "No receipient available for the donor [36709]\n",
      "No receipient available for the donor [55359]\n",
      "No receipient available for the donor [19317]\n",
      "No receipient available for the donor [29811]\n",
      "No receipient available for the donor [44710]\n",
      "No receipient available for the donor [7481]\n",
      "No receipient available for the donor [19983]\n",
      "No receipient available for the donor [8632]\n",
      "No receipient available for the donor [21770]\n",
      "No receipient available for the donor [36940]\n",
      "No receipient available for the donor [27060]\n",
      "No receipient available for the donor [52339]\n",
      "No receipient available for the donor [13788]\n",
      "No receipient available for the donor [53420]\n",
      "No receipient available for the donor [32081]\n",
      "No receipient available for the donor [6331]\n",
      "No receipient available for the donor [31409]\n",
      "No receipient available for the donor [7372]\n",
      "No receipient available for the donor [23047]\n",
      "No receipient available for the donor [9738]\n",
      "No receipient available for the donor [50622]\n",
      "No receipient available for the donor [3156]\n",
      "No receipient available for the donor [50597]\n",
      "No receipient available for the donor [42850]\n",
      "No receipient available for the donor [43943]\n",
      "No receipient available for the donor [52157]\n",
      "No receipient available for the donor [22497]\n",
      "No receipient available for the donor [7401]\n",
      "No receipient available for the donor [52807]\n",
      "No receipient available for the donor [29391]\n",
      "No receipient available for the donor [30697]\n",
      "No receipient available for the donor [3654]\n",
      "No receipient available for the donor [33397]\n",
      "No receipient available for the donor [39091]\n",
      "No receipient available for the donor [18911]\n",
      "No receipient available for the donor [15608]\n",
      "No receipient available for the donor [40805]\n",
      "No receipient available for the donor [29748]\n",
      "No receipient available for the donor [30223]\n",
      "No receipient available for the donor [48752]\n",
      "No receipient available for the donor [57797]\n",
      "No receipient available for the donor [3645]\n",
      "No receipient available for the donor [35154]\n",
      "No receipient available for the donor [27818]\n",
      "No receipient available for the donor [13998]\n",
      "No receipient available for the donor [29881]\n",
      "No receipient available for the donor [7026]\n",
      "No receipient available for the donor [47119]\n",
      "No receipient available for the donor [2698]\n",
      "No receipient available for the donor [50457]\n",
      "No receipient available for the donor [7806]\n",
      "No receipient available for the donor [32133]\n",
      "No receipient available for the donor [22114]\n",
      "No receipient available for the donor [31794]\n",
      "No receipient available for the donor [34780]\n",
      "No receipient available for the donor [46360]\n",
      "No receipient available for the donor [22001]\n",
      "No receipient available for the donor [14518]\n",
      "No receipient available for the donor [6024]\n",
      "No receipient available for the donor [40720]\n",
      "No receipient available for the donor [6683]\n",
      "No receipient available for the donor [40749]\n",
      "No receipient available for the donor [15206]\n",
      "No receipient available for the donor [53585]\n",
      "No receipient available for the donor [48435]\n",
      "No receipient available for the donor [32424]\n",
      "No receipient available for the donor [28202]\n",
      "No receipient available for the donor [32789]\n",
      "No receipient available for the donor [47761]\n",
      "No receipient available for the donor [23255]\n",
      "No receipient available for the donor [28426]\n",
      "No receipient available for the donor [7110]\n",
      "No receipient available for the donor [43546]\n",
      "No receipient available for the donor [47390]\n",
      "No receipient available for the donor [15207]\n",
      "No receipient available for the donor [10880]\n",
      "No receipient available for the donor [19926]\n",
      "No receipient available for the donor [11020]\n",
      "No receipient available for the donor [3179]\n",
      "No receipient available for the donor [11769]\n",
      "No receipient available for the donor [5248]\n",
      "No receipient available for the donor [41544]\n",
      "No receipient available for the donor [56672]\n",
      "No receipient available for the donor [25230]\n",
      "No receipient available for the donor [39649]\n",
      "No receipient available for the donor [33730]\n",
      "No receipient available for the donor [39741]\n",
      "No receipient available for the donor [21780]\n",
      "No receipient available for the donor [7480]\n",
      "No receipient available for the donor [33667]\n",
      "No receipient available for the donor [19346]\n",
      "No receipient available for the donor [30982]\n",
      "No receipient available for the donor [45944]\n",
      "No receipient available for the donor [4455]\n",
      "No receipient available for the donor [15343]\n",
      "No receipient available for the donor [25646]\n",
      "No receipient available for the donor [2902]\n",
      "No receipient available for the donor [33228]\n",
      "No receipient available for the donor [34979]\n",
      "No receipient available for the donor [25036]\n",
      "No receipient available for the donor [10892]\n",
      "No receipient available for the donor [17522]\n",
      "No receipient available for the donor [22291]\n",
      "No receipient available for the donor [3561]\n",
      "No receipient available for the donor [32867]\n",
      "No receipient available for the donor [15807]\n",
      "No receipient available for the donor [40060]\n",
      "No receipient available for the donor [52553]\n",
      "No receipient available for the donor [53366]\n",
      "No receipient available for the donor [52534]\n",
      "No receipient available for the donor [52058]\n",
      "No receipient available for the donor [31526]\n",
      "No receipient available for the donor [1589]\n",
      "No receipient available for the donor [56119]\n",
      "No receipient available for the donor [46898]\n",
      "No receipient available for the donor [26693]\n",
      "No receipient available for the donor [34166]\n",
      "No receipient available for the donor [53255]\n",
      "No receipient available for the donor [53365]\n",
      "No receipient available for the donor [20588]\n",
      "No receipient available for the donor [50334]\n",
      "No receipient available for the donor [30696]\n",
      "No receipient available for the donor [58276]\n",
      "No receipient available for the donor [50398]\n",
      "No receipient available for the donor [18226]\n",
      "No receipient available for the donor [36293]\n",
      "No receipient available for the donor [47174]\n",
      "No receipient available for the donor [52992]\n",
      "No receipient available for the donor [38733]\n",
      "No receipient available for the donor [21782]\n",
      "No receipient available for the donor [56670]\n",
      "No receipient available for the donor [55372]\n",
      "No receipient available for the donor [37478]\n",
      "No receipient available for the donor [23729]\n",
      "No receipient available for the donor [39339]\n",
      "No receipient available for the donor [44727]\n",
      "No receipient available for the donor [52813]\n",
      "No receipient available for the donor [39504]\n",
      "No receipient available for the donor [6564]\n",
      "No receipient available for the donor [54764]\n",
      "No receipient available for the donor [41546]\n",
      "No receipient available for the donor [22753]\n",
      "No receipient available for the donor [46072]\n",
      "No receipient available for the donor [13665]\n",
      "No receipient available for the donor [21759]\n",
      "No receipient available for the donor [53106]\n",
      "No receipient available for the donor [31297]\n",
      "No receipient available for the donor [34176]\n",
      "No receipient available for the donor [25639]\n",
      "No receipient available for the donor [27358]\n",
      "No receipient available for the donor [8435]\n",
      "No receipient available for the donor [56091]\n",
      "No receipient available for the donor [45410]\n",
      "No receipient available for the donor [9360]\n",
      "No receipient available for the donor [33168]\n",
      "No receipient available for the donor [7931]\n",
      "No receipient available for the donor [41447]\n",
      "No receipient available for the donor [27527]\n",
      "No receipient available for the donor [10090]\n",
      "No receipient available for the donor [9513]\n",
      "No receipient available for the donor [7977]\n",
      "No receipient available for the donor [31590]\n",
      "No receipient available for the donor [3790]\n",
      "No receipient available for the donor [57119]\n",
      "No receipient available for the donor [41547]\n",
      "No receipient available for the donor [50397]\n",
      "No receipient available for the donor [51628]\n",
      "No receipient available for the donor [33097]\n",
      "No receipient available for the donor [28429]\n",
      "No receipient available for the donor [54583]\n",
      "No receipient available for the donor [15678]\n",
      "No receipient available for the donor [29389]\n",
      "No receipient available for the donor [34012]\n",
      "No receipient available for the donor [32351]\n",
      "No receipient available for the donor [34342]\n",
      "No receipient available for the donor [52994]\n",
      "No receipient available for the donor [37839]\n",
      "No receipient available for the donor [47939]\n",
      "No receipient available for the donor [12412]\n",
      "No receipient available for the donor [54011]\n",
      "No receipient available for the donor [37771]\n",
      "No receipient available for the donor [1533]\n",
      "No receipient available for the donor [37825]\n",
      "No receipient available for the donor [33716]\n",
      "No receipient available for the donor [31223]\n",
      "No receipient available for the donor [34970]\n",
      "No receipient available for the donor [52443]\n",
      "No receipient available for the donor [32990]\n",
      "No receipient available for the donor [47197]\n",
      "No receipient available for the donor [29720]\n",
      "No receipient available for the donor [29599]\n",
      "No receipient available for the donor [2258]\n",
      "No receipient available for the donor [28233]\n",
      "No receipient available for the donor [5244]\n",
      "No receipient available for the donor [57212]\n",
      "No receipient available for the donor [32423]\n",
      "No receipient available for the donor [16005]\n",
      "No receipient available for the donor [13030]\n",
      "No receipient available for the donor [45694]\n",
      "No receipient available for the donor [27930]\n",
      "No receipient available for the donor [50690]\n",
      "No receipient available for the donor [12550]\n",
      "No receipient available for the donor [154]\n",
      "No receipient available for the donor [30934]\n",
      "No receipient available for the donor [58375]\n",
      "No receipient available for the donor [53806]\n",
      "No receipient available for the donor [40804]\n",
      "No receipient available for the donor [17991]\n",
      "No receipient available for the donor [34628]\n",
      "No receipient available for the donor [29935]\n",
      "No receipient available for the donor [8960]\n",
      "No receipient available for the donor [31367]\n",
      "No receipient available for the donor [49246]\n",
      "No receipient available for the donor [50091]\n",
      "No receipient available for the donor [39528]\n",
      "No receipient available for the donor [31410]\n",
      "No receipient available for the donor [50100]\n",
      "No receipient available for the donor [34205]\n",
      "No receipient available for the donor [43476]\n",
      "No receipient available for the donor [41781]\n",
      "No receipient available for the donor [34014]\n",
      "No receipient available for the donor [7655]\n",
      "No receipient available for the donor [20605]\n",
      "No receipient available for the donor [26071]\n",
      "No receipient available for the donor [9160]\n",
      "No receipient available for the donor [37024]\n",
      "No receipient available for the donor [53846]\n",
      "No receipient available for the donor [9737]\n",
      "No receipient available for the donor [34341]\n",
      "No receipient available for the donor [26048]\n",
      "No receipient available for the donor [9559]\n",
      "No receipient available for the donor [15677]\n",
      "No receipient available for the donor [15180]\n",
      "No receipient available for the donor [8468]\n",
      "No receipient available for the donor [22620]\n",
      "No receipient available for the donor [30084]\n",
      "No receipient available for the donor [52507]\n",
      "No receipient available for the donor [36567]\n",
      "No receipient available for the donor [34786]\n",
      "No receipient available for the donor [5810]\n",
      "No receipient available for the donor [13445]\n",
      "No receipient available for the donor [9358]\n",
      "No receipient available for the donor [38441]\n",
      "No receipient available for the donor [15327]\n",
      "No receipient available for the donor [34976]\n",
      "No receipient available for the donor [12138]\n",
      "No receipient available for the donor [39881]\n",
      "No receipient available for the donor [31955]\n",
      "No receipient available for the donor [22572]\n",
      "No receipient available for the donor [47653]\n",
      "No receipient available for the donor [57705]\n",
      "No receipient available for the donor [25229]\n",
      "No receipient available for the donor [31587]\n",
      "No receipient available for the donor [36376]\n",
      "No receipient available for the donor [24194]\n",
      "No receipient available for the donor [27727]\n",
      "No receipient available for the donor [35008]\n",
      "No receipient available for the donor [29670]\n",
      "No receipient available for the donor [9201]\n",
      "No receipient available for the donor [48121]\n",
      "No receipient available for the donor [4425]\n",
      "No receipient available for the donor [56206]\n",
      "No receipient available for the donor [38941]\n",
      "No receipient available for the donor [56208]\n",
      "No receipient available for the donor [18057]\n",
      "No receipient available for the donor [34784]\n",
      "No receipient available for the donor [8818]\n",
      "No receipient available for the donor [29087]\n",
      "No receipient available for the donor [40721]\n",
      "No receipient available for the donor [41438]\n",
      "No receipient available for the donor [20975]\n",
      "No receipient available for the donor [43160]\n",
      "No receipient available for the donor [56964]\n",
      "No receipient available for the donor [32757]\n",
      "No receipient available for the donor [40499]\n",
      "No receipient available for the donor [52844]\n",
      "No receipient available for the donor [19971]\n",
      "No receipient available for the donor [22798]\n",
      "No receipient available for the donor [13047]\n",
      "No receipient available for the donor [21814]\n",
      "No receipient available for the donor [43680]\n",
      "No receipient available for the donor [25410]\n",
      "No receipient available for the donor [28198]\n",
      "No receipient available for the donor [32330]\n",
      "No receipient available for the donor [56117]\n",
      "No receipient available for the donor [46961]\n",
      "No receipient available for the donor [44201]\n",
      "No receipient available for the donor [40276]\n",
      "No receipient available for the donor [36334]\n",
      "No receipient available for the donor [17124]\n",
      "No receipient available for the donor [25037]\n",
      "No receipient available for the donor [26200]\n",
      "No receipient available for the donor [24522]\n",
      "No receipient available for the donor [11260]\n",
      "No receipient available for the donor [25952]\n",
      "No receipient available for the donor [38146]\n",
      "No receipient available for the donor [51513]\n",
      "No receipient available for the donor [35961]\n",
      "No receipient available for the donor [53444]\n",
      "No receipient available for the donor [23728]\n",
      "No receipient available for the donor [40058]\n",
      "No receipient available for the donor [19115]\n",
      "No receipient available for the donor [10093]\n",
      "No receipient available for the donor [20415]\n",
      "No receipient available for the donor [37135]\n",
      "No receipient available for the donor [48136]\n",
      "No receipient available for the donor [25951]\n",
      "No receipient available for the donor [36332]\n",
      "No receipient available for the donor [22033]\n",
      "No receipient available for the donor [41178]\n",
      "No receipient available for the donor [34626]\n",
      "No receipient available for the donor [55100]\n",
      "No receipient available for the donor [51216]\n",
      "No receipient available for the donor [37770]\n",
      "No receipient available for the donor [30699]\n",
      "No receipient available for the donor [3130]\n",
      "No receipient available for the donor [19530]\n",
      "No receipient available for the donor [52535]\n",
      "No receipient available for the donor [20974]\n",
      "No receipient available for the donor [45337]\n",
      "No receipient available for the donor [10877]\n",
      "No receipient available for the donor [32438]\n",
      "No receipient available for the donor [14721]\n",
      "No receipient available for the donor [33091]\n",
      "No receipient available for the donor [20202]\n",
      "No receipient available for the donor [2126]\n",
      "No receipient available for the donor [36570]\n",
      "No receipient available for the donor [22573]\n",
      "No receipient available for the donor [43477]\n",
      "No receipient available for the donor [46387]\n",
      "No receipient available for the donor [29146]\n",
      "No receipient available for the donor [4046]\n",
      "No receipient available for the donor [49569]\n",
      "No receipient available for the donor [30990]\n",
      "No receipient available for the donor [18559]\n",
      "No receipient available for the donor [26832]\n",
      "No receipient available for the donor [55788]\n",
      "No receipient available for the donor [41545]\n",
      "No receipient available for the donor [20298]\n",
      "No receipient available for the donor [30983]\n",
      "No receipient available for the donor [35581]\n",
      "No receipient available for the donor [27386]\n",
      "No receipient available for the donor [13789]\n",
      "No receipient available for the donor [9514]\n",
      "No receipient available for the donor [23955]\n",
      "No receipient available for the donor [33251]\n",
      "No receipient available for the donor [243]\n",
      "No receipient available for the donor [56942]\n",
      "No receipient available for the donor [52684]\n",
      "No receipient available for the donor [30424]\n",
      "No receipient available for the donor [45320]\n",
      "No receipient available for the donor [41636]\n",
      "No receipient available for the donor [15093]\n",
      "No receipient available for the donor [42860]\n",
      "No receipient available for the donor [6276]\n",
      "No receipient available for the donor [50870]\n",
      "No receipient available for the donor [20929]\n",
      "No receipient available for the donor [39732]\n",
      "No receipient available for the donor [24738]\n",
      "No receipient available for the donor [8820]\n",
      "No receipient available for the donor [8563]\n",
      "No receipient available for the donor [245]\n",
      "No receipient available for the donor [42929]\n",
      "No receipient available for the donor [51575]\n",
      "No receipient available for the donor [11113]\n",
      "No receipient available for the donor [24524]\n",
      "No receipient available for the donor [49862]\n",
      "No receipient available for the donor [52612]\n",
      "No receipient available for the donor [35155]\n",
      "No receipient available for the donor [32311]\n",
      "No receipient available for the donor [43942]\n",
      "No receipient available for the donor [23514]\n",
      "No receipient available for the donor [52720]\n",
      "No receipient available for the donor [29737]\n",
      "No receipient available for the donor [15789]\n",
      "No receipient available for the donor [6098]\n",
      "No receipient available for the donor [5393]\n",
      "No receipient available for the donor [30721]\n",
      "No receipient available for the donor [9871]\n",
      "No receipient available for the donor [36177]\n",
      "No receipient available for the donor [35824]\n",
      "No receipient available for the donor [44202]\n",
      "No receipient available for the donor [57158]\n",
      "No receipient available for the donor [29840]\n",
      "No receipient available for the donor [19969]\n",
      "No receipient available for the donor [39555]\n",
      "No receipient available for the donor [23217]\n",
      "No receipient available for the donor [58118]\n",
      "No receipient available for the donor [35360]\n",
      "No receipient available for the donor [35161]\n",
      "No receipient available for the donor [55374]\n",
      "No receipient available for the donor [390]\n",
      "No receipient available for the donor [35763]\n",
      "No receipient available for the donor [21750]\n",
      "No receipient available for the donor [22549]\n",
      "No receipient available for the donor [50826]\n",
      "No receipient available for the donor [39742]\n",
      "No receipient available for the donor [7979]\n",
      "No receipient available for the donor [21892]\n",
      "No receipient available for the donor [16361]\n",
      "No receipient available for the donor [38251]\n",
      "No receipient available for the donor [33057]\n",
      "No receipient available for the donor [29968]\n",
      "No receipient available for the donor [44695]\n",
      "No receipient available for the donor [13844]\n",
      "No receipient available for the donor [11258]\n",
      "No receipient available for the donor [10721]\n",
      "No receipient available for the donor [15018]\n",
      "No receipient available for the donor [49509]\n",
      "No receipient available for the donor [13062]\n",
      "No receipient available for the donor [30549]\n",
      "No receipient available for the donor [21812]\n",
      "No receipient available for the donor [27254]\n",
      "No receipient available for the donor [34343]\n",
      "No receipient available for the donor [32629]\n",
      "No receipient available for the donor [25687]\n",
      "No receipient available for the donor [36203]\n",
      "No receipient available for the donor [26967]\n",
      "No receipient available for the donor [17289]\n",
      "No receipient available for the donor [47990]\n",
      "No receipient available for the donor [1878]\n",
      "No receipient available for the donor [55101]\n",
      "No receipient available for the donor [57966]\n",
      "No receipient available for the donor [12116]\n",
      "No receipient available for the donor [30935]\n",
      "No receipient available for the donor [10251]\n",
      "No receipient available for the donor [45494]\n",
      "No receipient available for the donor [24714]\n",
      "No receipient available for the donor [42928]\n",
      "No receipient available for the donor [2260]\n",
      "No receipient available for the donor [49990]\n",
      "No receipient available for the donor [34346]\n",
      "No receipient available for the donor [34931]\n",
      "No receipient available for the donor [29515]\n",
      "No receipient available for the donor [30861]\n",
      "No receipient available for the donor [47336]\n",
      "No receipient available for the donor [24392]\n",
      "No receipient available for the donor [38447]\n",
      "No receipient available for the donor [28196]\n",
      "No receipient available for the donor [27341]\n",
      "No receipient available for the donor [36378]\n",
      "No receipient available for the donor [23276]\n",
      "No receipient available for the donor [15472]\n",
      "No receipient available for the donor [30898]\n",
      "No receipient available for the donor [39529]\n",
      "No receipient available for the donor [5234]\n",
      "No receipient available for the donor [49339]\n",
      "No receipient available for the donor [18746]\n",
      "No receipient available for the donor [27819]\n",
      "No receipient available for the donor [33966]\n",
      "No receipient available for the donor [31365]\n",
      "No receipient available for the donor [36176]\n",
      "No receipient available for the donor [54041]\n",
      "No receipient available for the donor [30967]\n",
      "No receipient available for the donor [17499]\n",
      "No receipient available for the donor [30395]\n",
      "No receipient available for the donor [48463]\n",
      "No receipient available for the donor [57157]\n",
      "No receipient available for the donor [10499]\n",
      "No receipient available for the donor [2828]\n",
      "No receipient available for the donor [45013]\n",
      "No receipient available for the donor [19793]\n",
      "No receipient available for the donor [5424]\n",
      "No receipient available for the donor [39832]\n",
      "No receipient available for the donor [13403]\n",
      "No receipient available for the donor [27096]\n",
      "No receipient available for the donor [35333]\n",
      "No receipient available for the donor [24703]\n",
      "No receipient available for the donor [45717]\n",
      "No receipient available for the donor [15638]\n",
      "No receipient available for the donor [10791]\n",
      "No receipient available for the donor [25688]\n",
      "No receipient available for the donor [30220]\n",
      "No receipient available for the donor [34416]\n",
      "No receipient available for the donor [19509]\n",
      "No receipient available for the donor [26830]\n",
      "No receipient available for the donor [32331]\n",
      "No receipient available for the donor [8961]\n",
      "No receipient available for the donor [8424]\n",
      "No receipient available for the donor [48461]\n",
      "No receipient available for the donor [36204]\n",
      "No receipient available for the donor [5546]\n",
      "No receipient available for the donor [47074]\n",
      "No receipient available for the donor [20927]\n",
      "No receipient available for the donor [14517]\n",
      "No receipient available for the donor [42092]\n",
      "No receipient available for the donor [48478]\n",
      "No receipient available for the donor [12551]\n",
      "No receipient available for the donor [13914]\n",
      "No receipient available for the donor [28134]\n",
      "No receipient available for the donor [35582]\n",
      "No receipient available for the donor [19773]\n",
      "No receipient available for the donor [964]\n",
      "No receipient available for the donor [40077]\n",
      "No receipient available for the donor [2593]\n",
      "No receipient available for the donor [57479]\n",
      "No receipient available for the donor [29447]\n",
      "No receipient available for the donor [34978]\n",
      "No receipient available for the donor [31310]\n",
      "No receipient available for the donor [53583]\n",
      "No receipient available for the donor [52848]\n",
      "No receipient available for the donor [54106]\n",
      "No receipient available for the donor [13460]\n",
      "No receipient available for the donor [11767]\n",
      "No receipient available for the donor [45405]\n",
      "No receipient available for the donor [54345]\n",
      "No receipient available for the donor [10250]\n",
      "No receipient available for the donor [32870]\n",
      "No receipient available for the donor [46495]\n",
      "No receipient available for the donor [5945]\n",
      "No receipient available for the donor [36518]\n",
      "No receipient available for the donor [55583]\n",
      "No receipient available for the donor [22548]\n",
      "No receipient available for the donor [25366]\n",
      "No receipient available for the donor [53810]\n",
      "No receipient available for the donor [10667]\n",
      "No receipient available for the donor [22797]\n",
      "No receipient available for the donor [5807]\n",
      "No receipient available for the donor [48477]\n",
      "No receipient available for the donor [5990]\n",
      "No receipient available for the donor [31169]\n",
      "No receipient available for the donor [48791]\n",
      "No receipient available for the donor [52704]\n",
      "No receipient available for the donor [29085]\n",
      "No receipient available for the donor [50399]\n",
      "No receipient available for the donor [27353]\n",
      "No receipient available for the donor [8895]\n",
      "No receipient available for the donor [30217]\n",
      "No receipient available for the donor [8176]\n",
      "No receipient available for the donor [19375]\n",
      "No receipient available for the donor [35863]\n",
      "No receipient available for the donor [35626]\n",
      "No receipient available for the donor [53581]\n",
      "No receipient available for the donor [12117]\n",
      "No receipient available for the donor [26205]\n",
      "No receipient available for the donor [22126]\n",
      "No receipient available for the donor [26007]\n",
      "No receipient available for the donor [27010]\n",
      "No receipient available for the donor [4984]\n",
      "No receipient available for the donor [41564]\n",
      "No receipient available for the donor [959]\n",
      "No receipient available for the donor [47247]\n",
      "No receipient available for the donor [51588]\n",
      "No receipient available for the donor [39092]\n",
      "No receipient available for the donor [1234]\n",
      "No receipient available for the donor [38011]\n",
      "No receipient available for the donor [32167]\n",
      "No receipient available for the donor [37695]\n",
      "No receipient available for the donor [29177]\n",
      "No receipient available for the donor [38826]\n",
      "No receipient available for the donor [32966]\n",
      "No receipient available for the donor [17992]\n",
      "No receipient available for the donor [33732]\n",
      "No receipient available for the donor [6684]\n",
      "No receipient available for the donor [36496]\n",
      "No receipient available for the donor [1791]\n",
      "No receipient available for the donor [28584]\n",
      "No receipient available for the donor [11110]\n",
      "No receipient available for the donor [37091]\n",
      "No receipient available for the donor [50676]\n",
      "No receipient available for the donor [40292]\n",
      "No receipient available for the donor [38678]\n",
      "No receipient available for the donor [17501]\n",
      "No receipient available for the donor [46471]\n",
      "No receipient available for the donor [48672]\n",
      "No receipient available for the donor [31167]\n",
      "No receipient available for the donor [129]\n",
      "No receipient available for the donor [10295]\n",
      "No receipient available for the donor [41071]\n",
      "No receipient available for the donor [35762]\n",
      "No receipient available for the donor [30415]\n",
      "No receipient available for the donor [30545]\n",
      "No receipient available for the donor [12967]\n",
      "No receipient available for the donor [45304]\n",
      "No receipient available for the donor [47762]\n",
      "No receipient available for the donor [36094]\n",
      "No receipient available for the donor [53809]\n",
      "No receipient available for the donor [47927]\n",
      "No receipient available for the donor [9387]\n",
      "No receipient available for the donor [17791]\n",
      "No receipient available for the donor [36410]\n",
      "No receipient available for the donor [50400]\n",
      "No receipient available for the donor [18797]\n",
      "No receipient available for the donor [29546]\n",
      "No receipient available for the donor [25197]\n",
      "No receipient available for the donor [30439]\n",
      "No receipient available for the donor [18418]\n",
      "No receipient available for the donor [30899]\n",
      "No receipient available for the donor [5811]\n",
      "No receipient available for the donor [21256]\n",
      "No receipient available for the donor [27666]\n",
      "No receipient available for the donor [44399]\n",
      "No receipient available for the donor [20657]\n",
      "No receipient available for the donor [56282]\n",
      "No receipient available for the donor [19258]\n",
      "No receipient available for the donor [50396]\n",
      "No receipient available for the donor [57728]\n",
      "No receipient available for the donor [39340]\n",
      "No receipient available for the donor [30071]\n",
      "No receipient available for the donor [10091]\n",
      "No receipient available for the donor [1359]\n",
      "No receipient available for the donor [20297]\n",
      "No receipient available for the donor [29156]\n",
      "No receipient available for the donor [13074]\n",
      "No receipient available for the donor [44892]\n",
      "No receipient available for the donor [11419]\n",
      "No receipient available for the donor [57210]\n",
      "No receipient available for the donor [2749]\n",
      "No receipient available for the donor [30362]\n",
      "No receipient available for the donor [11099]\n",
      "No receipient available for the donor [11765]\n",
      "No receipient available for the donor [16469]\n",
      "No receipient available for the donor [40275]\n",
      "No receipient available for the donor [31592]\n",
      "No receipient available for the donor [3379]\n",
      "No receipient available for the donor [26183]\n",
      "No receipient available for the donor [52285]\n",
      "No receipient available for the donor [32158]\n",
      "No receipient available for the donor [34370]\n",
      "No receipient available for the donor [16192]\n",
      "No receipient available for the donor [14580]\n",
      "No receipient available for the donor [35572]\n",
      "No receipient available for the donor [39535]\n",
      "No receipient available for the donor [39650]\n",
      "No receipient available for the donor [19929]\n",
      "No receipient available for the donor [49635]\n",
      "No receipient available for the donor [24071]\n",
      "No receipient available for the donor [3763]\n",
      "No receipient available for the donor [52846]\n",
      "No receipient available for the donor [46358]\n",
      "No receipient available for the donor [34977]\n",
      "No receipient available for the donor [21769]\n",
      "No receipient available for the donor [38939]\n",
      "No receipient available for the donor [30883]\n",
      "No receipient available for the donor [48836]\n",
      "No receipient available for the donor [37603]\n",
      "No receipient available for the donor [13386]\n",
      "No receipient available for the donor [46982]\n",
      "No receipient available for the donor [49850]\n",
      "No receipient available for the donor [18671]\n",
      "No receipient available for the donor [55388]\n",
      "No receipient available for the donor [16275]\n",
      "No receipient available for the donor [44272]\n",
      "No receipient available for the donor [27607]\n",
      "No receipient available for the donor [50002]\n",
      "No receipient available for the donor [32580]\n",
      "No receipient available for the donor [41926]\n",
      "No receipient available for the donor [672]\n",
      "No receipient available for the donor [43611]\n",
      "No receipient available for the donor [29460]\n",
      "No receipient available for the donor [22676]\n",
      "No receipient available for the donor [45300]\n",
      "No receipient available for the donor [37159]\n",
      "No receipient available for the donor [3705]\n",
      "No receipient available for the donor [29461]\n",
      "No receipient available for the donor [31553]\n",
      "No receipient available for the donor [49909]\n",
      "No receipient available for the donor [34414]\n",
      "No receipient available for the donor [32085]\n",
      "No receipient available for the donor [28443]\n",
      "No receipient available for the donor [36044]\n",
      "No receipient available for the donor [24388]\n",
      "No receipient available for the donor [11320]\n",
      "No receipient available for the donor [51299]\n",
      "No receipient available for the donor [52286]\n",
      "No receipient available for the donor [28890]\n",
      "No receipient available for the donor [11615]\n",
      "No receipient available for the donor [32100]\n",
      "No receipient available for the donor [31552]\n",
      "No receipient available for the donor [13114]\n",
      "No receipient available for the donor [44801]\n",
      "No receipient available for the donor [22116]\n",
      "No receipient available for the donor [28836]\n",
      "No receipient available for the donor [18059]\n",
      "No receipient available for the donor [5989]\n",
      "No receipient available for the donor [5074]\n",
      "No receipient available for the donor [51036]\n",
      "No receipient available for the donor [10669]\n",
      "No receipient available for the donor [31446]\n",
      "No receipient available for the donor [26003]\n",
      "No receipient available for the donor [27094]\n",
      "No receipient available for the donor [33434]\n",
      "No receipient available for the donor [16245]\n",
      "No receipient available for the donor [7087]\n",
      "No receipient available for the donor [17188]\n",
      "No receipient available for the donor [46688]\n",
      "No receipient available for the donor [37641]\n",
      "No receipient available for the donor [51017]\n",
      "No receipient available for the donor [46070]\n",
      "No receipient available for the donor [29547]\n",
      "No receipient available for the donor [32080]\n",
      "No receipient available for the donor [54862]\n",
      "No receipient available for the donor [44036]\n",
      "No receipient available for the donor [26966]\n",
      "No receipient available for the donor [53419]\n",
      "No receipient available for the donor [58195]\n",
      "No receipient available for the donor [45511]\n",
      "No receipient available for the donor [52685]\n",
      "No receipient available for the donor [11420]\n",
      "No receipient available for the donor [2046]\n",
      "No receipient available for the donor [54684]\n",
      "No receipient available for the donor [2624]\n",
      "No receipient available for the donor [44437]\n",
      "No receipient available for the donor [45065]\n",
      "No receipient available for the donor [30070]\n",
      "No receipient available for the donor [31521]\n",
      "No receipient available for the donor [31088]\n",
      "No receipient available for the donor [27729]\n",
      "No receipient available for the donor [38253]\n",
      "No receipient available for the donor [33167]\n",
      "No receipient available for the donor [46074]\n",
      "No receipient available for the donor [3881]\n",
      "No receipient available for the donor [12783]\n",
      "No receipient available for the donor [14724]\n",
      "No receipient available for the donor [7105]\n",
      "No receipient available for the donor [19883]\n",
      "No receipient available for the donor [11766]\n",
      "No receipient available for the donor [9305]\n",
      "No receipient available for the donor [53442]\n",
      "No receipient available for the donor [34206]\n",
      "No receipient available for the donor [3655]\n",
      "No receipient available for the donor [1879]\n",
      "No receipient available for the donor [28514]\n",
      "No receipient available for the donor [27528]\n",
      "No receipient available for the donor [9870]\n",
      "No receipient available for the donor [26182]\n",
      "No receipient available for the donor [29536]\n",
      "No receipient available for the donor [31171]\n",
      "No receipient available for the donor [18832]\n",
      "No receipient available for the donor [41930]\n",
      "No receipient available for the donor [37090]\n",
      "No receipient available for the donor [9159]\n",
      "No receipient available for the donor [49490]\n",
      "No receipient available for the donor [50986]\n",
      "No receipient available for the donor [20698]\n",
      "No receipient available for the donor [16397]\n",
      "No receipient available for the donor [45478]\n",
      "No receipient available for the donor [52554]\n",
      "No receipient available for the donor [3180]\n",
      "No receipient available for the donor [49100]\n",
      "No receipient available for the donor [52449]\n",
      "No receipient available for the donor [32101]\n",
      "No receipient available for the donor [32467]\n",
      "No receipient available for the donor [51124]\n",
      "No receipient available for the donor [53203]\n",
      "No receipient available for the donor [34984]\n",
      "No receipient available for the donor [36491]\n",
      "No receipient available for the donor [34020]\n",
      "No receipient available for the donor [37611]\n",
      "No receipient available for the donor [10142]\n",
      "No receipient available for the donor [13032]\n",
      "No receipient available for the donor [6277]\n",
      "No receipient available for the donor [44725]\n",
      "No receipient available for the donor [27841]\n",
      "No receipient available for the donor [41741]\n",
      "No receipient available for the donor [40443]\n",
      "No receipient available for the donor [32637]\n",
      "No receipient available for the donor [30414]\n",
      "No receipient available for the donor [41280]\n",
      "No receipient available for the donor [27887]\n",
      "No receipient available for the donor [36407]\n",
      "Wall time: 8min 4s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "# generate a random number between 0 and 1. If the number exceeds 0.5 then the donor can receive 2 receipients;\n",
    "# otherwise the donor can receive only 1 receipient\n",
    "matching_index = []\n",
    "\n",
    "nrows = pair_candidates.shape[0]\n",
    "\n",
    "while len(pair_candidates) > 0:\n",
    "    \n",
    "    matching_df = []\n",
    "    \n",
    "    frec, frec_startzone, frec_destzone, start_time_below, start_time_up = prepare_to_pair(pair_candidates, ride_pair_vehlist)\n",
    "#     print(\"Donor index %s\" %frec.index.values)\n",
    "    or_df = get_zone(ttime, frec_startzone, time_thold, 'taz_i')\n",
    "    dt_df = get_zone(ttime, frec_destzone, time_thold, 'taz_j')\n",
    "    df_to_sample, pair_flag = prepare_candidates(or_df, dt_df, pair_candidates, start_time_below, start_time_up, frec)\n",
    "#     print(\"len to sample from %s\" %len(df_to_sample))\n",
    "#     print(\"Pair flag %s\" %pair_flag)\n",
    "    \n",
    "    pairing_rows = np.random.rand()\n",
    "#     print(pairing_rows)\n",
    "    \n",
    "    if len(df_to_sample) == 0:\n",
    "        print(\"No receipient available for the donor %s\" %frec.index.values)\n",
    "    \n",
    "    elif len(df_to_sample) == 1:\n",
    "        matching_df = df_to_sample.sample(n=1).index.values\n",
    "#         print(\"Recep index %s\" %matching_df)\n",
    "    \n",
    "    elif len(df_to_sample) > 1 and pairing_rows >= 0.5:\n",
    "        matching_df = df_to_sample.sample(n = 2).index.values\n",
    "#         print(\"Recep index %s\" %matching_df)\n",
    "    \n",
    "    elif len(df_to_sample) > 1 and pairing_rows < 0.5:\n",
    "        matching_df = df_to_sample.sample(n = 1).index.values\n",
    "#         print(\"Recep index %s\" %matching_df)\n",
    "    \n",
    "    # update the pair candidates to remove before next round\n",
    "    if len(df_to_sample) == 0:\n",
    "        \n",
    "        pair_candidates = pair_candidates[~pair_candidates.index.isin(frec.index.values)]        \n",
    "    else:\n",
    "        \n",
    "        indices_remove = np.concatenate([matching_df, frec.index.values], axis = 0)\n",
    "        pair_candidates = pair_candidates[~pair_candidates.index.isin(indices_remove)]\n",
    "    \n",
    "    # concatenate the indices of the receipient and donor zones; \n",
    "    # reshape the arrays; create an array of the pair_flag and\n",
    "    # then bring them together.    \n",
    "    if len(df_to_sample) > 0:\n",
    "    \n",
    "        matching_df = np.concatenate((matching_df, frec.index.values), axis=0)\n",
    "        matching_df = matching_df.reshape(matching_df.shape[0], 1)\n",
    "        pair_array = np.full((matching_df.shape[0], 1), pair_flag)\n",
    "        matching_df = np.c_[matching_df, pair_array]    \n",
    "\n",
    "    matching_index.append(matching_df)\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# flatten the nested lists and then get ready for concantenating the results to the master dataframe\n",
    "l1 = list(chain(*matching_index))\n",
    "l_df1 = pd.DataFrame(l1, columns=['ind', 'veh_num']).set_index('ind')\n",
    "\n",
    "# attach the times\n",
    "# temp_df = pd.concat([temp_df, l_df], axis = 1)"
   ]
  },
  {
   "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": "markdown",
   "metadata": {},
   "source": [
    "# Cobverted to Functions - dont run"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in range(0, 1):\n",
    "    frec, frec_startzone, frec_destzone, start_time_below, start_time_up = prepare_to_pair(pair_candidates, ride_pair_vehlist)\n",
    "    print(\"Donor index %s\" %frec.index.values)\n",
    "    or_df = get_zone(ttime, frec_startzone, time_thold, 'taz_i')\n",
    "    dt_df = get_zone(ttime, frec_destzone, time_thold, 'taz_j')\n",
    "    df_to_sample, pair_flag = prepare_candidates(or_df, dt_df, pair_candidates, start_time_below, start_time_up, frec)\n",
    "    print(\"len to sample from %s\" %len(df_to_sample))\n",
    "    \n",
    "    pairing_rows = np.random.rand()\n",
    "    print(pairing_rows)\n",
    "    \n",
    "    if len(df_to_sample) == 0:\n",
    "        print(\"No receipient available for the donor %s\" %frec.index.values)\n",
    "    \n",
    "    elif len(df_to_sample) == 1:\n",
    "        matching_df = df_to_sample.sample(n=1).index.values\n",
    "        print(\"Recep index %s\" %matching_df)\n",
    "    \n",
    "    elif len(df_to_sample) > 1 and pairing_rows >= 0.5:\n",
    "        matching_df = df_to_sample.sample(n = 2).index.values\n",
    "        print(\"Recep index %s\" %matching_df)\n",
    "    \n",
    "    elif len(df_to_sample) > 1 and pairing_rows < 0.5:\n",
    "        matching_df = df_to_sample.sample(n = 1).index.values\n",
    "        print(\"Recep index %s\" %matching_df)\n",
    "    \n",
    "    indices_remove = np.concatenate([matching_df, frec.index.values], axis = 0)\n",
    "    pair_candidates = pair_candidates[~pair_candidates.index.isin(indices_remove)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%time\n",
    "# randomly sample a record and set a ride_pairing flag. This flag is unique and will be added to records that are\n",
    "# a good ride pairing match.\n",
    "frec = pair_candidates.sample(n = 1, random_state = prng, replace = False)\n",
    "frec['ride_pair'] = np.random.choice(ride_pair_vehlist, replace = False)\n",
    "\n",
    "# get start_time of first record; start zone; and destination zone for the Donor trip\n",
    "frec_starttime = frec.at[frec.index[0],'start_time']\n",
    "frec_startzone = frec.at[frec.index[0], 'taz_i']\n",
    "frec_destzone = frec.at[frec.index[0], 'taz_j']\n",
    "\n",
    "# generate the window of start_times for the receipient trips\n",
    "window_time = 15\n",
    "start_time_below = frec_starttime - window_time/60\n",
    "start_time_up = frec_starttime + window_time/60\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%time\n",
    "# ORIGIN ZONE\n",
    "# first slice the travel time dataframe for the origin zone\n",
    "ttime_slice = ttime.iloc[np.where(ttime['taz_i'].values == frec_startzone)]\n",
    "# now slice the datafame to only keep those zones that are within a travel time buffer of the origin zone\n",
    "ttime_slice = ttime_slice.iloc[np.where(ttime_slice['time'].values <= time_thold)]\n",
    "\n",
    "# now get all the origin zones that are within the travel time buffer\n",
    "origin_zones = ttime_slice['taz_j'].values\n",
    "or_df = pd.DataFrame(origin_zones, columns = ['taz_i'])\n",
    "or_df['key'] = 0\n",
    "\n",
    "# DESTINATION ZONE\n",
    "# first slice the travel time dataframe for the destination zone\n",
    "ttime_slice = ttime.iloc[np.where(ttime['taz_i'].values == frec_destzone)]\n",
    "\n",
    "# now slice the datafame to only keep those records that are within a travel time buffer of the destination\n",
    "ttime_slice = ttime_slice.iloc[np.where(ttime_slice['time'].values <= time_thold)]\n",
    "\n",
    "# now get all the dest zones that are within the travel time buffer\n",
    "dest_zones = ttime_slice['taz_j'].values\n",
    "dt_df = pd.DataFrame(dest_zones, columns = ['taz_j'])\n",
    "dt_df['key'] = 0\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%time\n",
    "# now get a full dataframe of all origins and destinations\n",
    "full_df = pd.merge(or_df, dt_df, how = 'left', on = 'key')\n",
    "full_df = full_df.loc[full_df['taz_i'] != full_df['taz_j']]\n",
    "\n",
    "# Only keep those trips that are within the start_time buffer.\n",
    "# get all the records that match the origin-destination interchanges. \n",
    "# Also get rid of intrazonals.\n",
    "pair_candidates = pair_candidates.loc[(pair_candidates['start_time'] >= start_time_below) & \n",
    "                                      (pair_candidates['start_time'] <= start_time_up)]\n",
    "temp_df2 = pair_candidates.loc[(pair_candidates['taz_i'].isin(full_df['taz_i'])) & \n",
    "                               (pair_candidates['taz_j'].isin(full_df['taz_j']))]\n",
    "temp_df2 = temp_df2.loc[temp_df2['taz_i'] != temp_df2['taz_j']]\n",
    "\n",
    "# add in a flag to identify the records that will be matched together\n",
    "pair_flag = frec['ride_pair'].values\n",
    "temp_df2['ride_pair'] = pair_flag[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%time\n",
    "# generate a random number between 0 and 1. If the number exceeds 0.5 then the donor can receive 2 receipients;\n",
    "# otherwise the donor can receive only 1 receipient\n",
    "matching_index = []\n",
    "\n",
    "pairing_rows = np.random.rand()\n",
    "print(pairing_rows)\n",
    "\n",
    "\n",
    "if pairing_rows > 0.5:\n",
    "    # sample and get index of row sampled. Also inser the pair_flag to the numpy array\n",
    "    matching_df = temp_df2.sample(n=2).index.values\n",
    "\n",
    "else:\n",
    "    # sample and get index of row sampled. Also inser the pair_flag to the numpy array\n",
    "    matching_df = temp_df2.sample(n=1).index.values\n",
    "\n",
    "# concatenate the indices of the receipient and donor zones; \n",
    "# reshape the arrays; create an array of the parir_flag and\n",
    "# then bring them together\n",
    "matching_df = np.concatenate((matching_df, frec.index.values), axis=0)\n",
    "matching_df = matching_df.reshape(matching_df.shape[0], 1)\n",
    "pair_array = np.full((matching_df.shape[0], 1), pair_flag)\n",
    "matching_df = np.c_[matching_df, pair_array]\n",
    "# print(matching_df)    \n",
    "\n",
    "matching_index.append(matching_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# make one unique numpy array\n",
    "unique_arr = np.unique(np.concatenate((origin_zones, dest_zones), axis=0))\n",
    "\n",
    "# convert to dataframe and get it ready for merging with master trip records\n",
    "unique_arr_df = pd.DataFrame(unique_arr, columns = ['zones'] )\n",
    "unique_arr_df['key'] = 0\n",
    "unique_arr_df1 = unique_arr_df\n",
    "\n",
    "unique_arr_df = pd.merge(unique_arr_df, unique_arr_df1, how = 'left', on = 'key')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%load_ext line_profiler\n",
    "%lprun -f start_times_round2 start_times_round2(df_array, time_dist, results, i)"
   ]
  },
  {
   "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": "markdown",
   "metadata": {},
   "source": [
    "# Old Code and Attempts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def start_times_round1(trips_df, time_dist, purp_dir_product):\n",
    "    \"\"\"\n",
    "    This function takes the trips_hhold dataframe and samples a start time for each trip based on the purpose and direction.\n",
    "    It ignores whether each trip record has been flagged by a peak/off-peak flag.\n",
    "    \n",
    "    Args:\n",
    "    \n",
    "    Return: dataframe with start time attached \n",
    "    \"\"\"\n",
    "    # slice dataframe by purpose and direction and save indices to numpy array. This is useful for concatenating\n",
    "    df_dir = trips_df.iloc[np.where((trips_df['purpose'].values == purp_dir_product[0]) & \n",
    "                                    (trips_df['tour_direction'].values == purp_dir_product[1]))].index.values\n",
    "    \n",
    "    # sample start times and save to numpy array\n",
    "    weight_column = purp_dir_product[0] + '_' + purp_dir_product[1] \n",
    "    df_dir_sample = time_dist.sample(len(df_dir), weights= time_dist[weight_column], replace=True, random_state=seed)\n",
    "    df_dir_sample = df_dir_sample[['Time']].values\n",
    "    \n",
    "    # Append the sampled times with the sliced dataframe indices\n",
    "    df_dir_sample = pd.DataFrame(df_dir_sample, index=df_dir, columns=['start_time'])\n",
    "\n",
    "    \n",
    "    return df_dir_sample    \n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%time\n",
    "# purp_dir_product = [('NHB', 'outbound')]\n",
    "temp_df_test_pkoffpk = {}\n",
    "temp_df_test_purpdir = {}\n",
    "for purp_dir in purp_dir_product:\n",
    "    \n",
    "    for pkoff_flag in range(0,2):\n",
    "        \n",
    "        temp_df1 = temp_df.loc[temp_df['peak_flag'] == pkoff_flag]\n",
    "        time_dist1 = time_dist.loc[time_dist['pk_flag'] == pkoff_flag]\n",
    "        \n",
    "        # run start times for all combinations of trip purpose and tour direction\n",
    "        temp_df_test_pkoffpk[pkoff_flag] = start_times_round1(temp_df1, time_dist1, purp_dir)\n",
    "        temp_df_test_pkoffpk_comb = pd.concat(temp_df_test_pkoffpk.values(), axis = 0)\n",
    "    \n",
    "    temp_df_test_purpdir[purp_dir] = temp_df_test_pkoffpk_comb\n",
    "\n",
    "# concatenate all the sampled start times in the dictionary and then concatenate it back to the main dataframe\n",
    "temp_df_test1 = pd.concat(temp_df_test_purpdir.values(), axis = 0)\n",
    "final_df = pd.concat([temp_df, temp_df_test1], axis= 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "final_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Now test if start times are consistent with the following:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* The subsequent trip segmented by hhid and pid must start only after the preceeding start time + travel time between the O-D pair\n",
    "* If not, then the start time of the subsequent trip must be adjusted by sampling from the time distribution but after controlling for logic such as:  \n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Join in O-D travel times, by auto only\n",
    "#### This is made up currently, get final from GGHMV4 run"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%time\n",
    "# batch in ggh zone numbers and add in two columns for i and j zones\n",
    "ggh = pd.read_csv(os.path.join(dirListing, \"GGH_zones.csv\"))\n",
    "if 'ggh_zone'  not in ggh:\n",
    "    print(\"The 'ggh_zone' column does not exist.\")\n",
    "\n",
    "# prepare the dataframe to create a matrix that reflects zone to zone travel times\n",
    "ggh['key'] = 0\n",
    "ggh1 = ggh\n",
    "\n",
    "# create proxy travel times\n",
    "ggh2 = pd.merge(ggh1, ggh, how='left', on='key')\n",
    "ggh2.columns = ['taz_i', 'traveltime', 'taz_j']\n",
    "ggh2['traveltime'] = np.random.randint(100, size = len(ggh2))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%time\n",
    "# Transfer O-D level auto travel times\n",
    "final_df = pd.merge(final_df, ggh2, how = 'left', on = ['taz_i', 'taz_j'])\n",
    "\n",
    "# Add in column to reflect the start_time + travel time\n",
    "final_df['arrival_time'] = final_df['start_time'] + final_df['traveltime']/60"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def starttime_flag(df, first_row_arrtime):\n",
    "    \"\"\"\n",
    "    This function evaluates the rows in a dataframe and establishes whether the start time of a record is consistent\n",
    "    with the arrival time of the preceeding record i.e. the starttime of the next trip should be greater than the \n",
    "    arrival time of the previous trip.\n",
    "    \n",
    "    Arguments: dataframe\n",
    "    \n",
    "    Return: list with index and flag of processed rows in dataframe \n",
    "    \"\"\"\n",
    "\n",
    "#     duration = float('%.1f' % round(df.at[df.index[i],'start_time'] - first_row_arrtime,2))\n",
    "    duration = df.at[df.index[i],'start_time'] - first_row_arrtime\n",
    "     \n",
    "    if duration >= -0.5:\n",
    "        # set to 1 if duration is fine and start_time of the subsequent time is after the arrival\n",
    "        # time of the preceeding time\n",
    "        flag = 1\n",
    "    else:\n",
    "        flag = 0\n",
    "     \n",
    "    ind = df.index[i]\n",
    "\n",
    "    return (ind, flag, duration)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%time\n",
    "results = []\n",
    "\n",
    "for name, group in final_df.groupby(['hhid', 'pid']):\n",
    "    \n",
    "    # make dataframe to pass to function\n",
    "#     gr_df = pd.DataFrame(group)\n",
    "    \n",
    "    for i in range(1, len(group)):\n",
    "            \n",
    "        # update the arrive time value and run the function\n",
    "        first_row_arrtime = group.at[group.index[i-1], 'arrival_time']\n",
    "        ind, flag, duration = starttime_flag(group, first_row_arrtime)\n",
    "    \n",
    "        # save results in list\n",
    "        results.append((ind, flag, duration))\n",
    "\n",
    "# build datafarme for appending to master df\n",
    "# append the flag and duration to the master df and also fill in a dummy value for the NaN. This value is a placeholder\n",
    "results_df = pd.DataFrame(np.array(results).reshape(len(results), 3), columns = (['ind', 'flag', 'duration']))\n",
    "results_df.set_index('ind', inplace=True)\n",
    "final_df = pd.concat([final_df, results_df], axis = 1).fillna(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "results[0][2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "final_df.head()"
   ]
  },
  {
   "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": [
    "final_df.to_csv(r\"c:/personal/imm/test_starttime_flag.csv\", index = False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Now select all those groups that had a negative duration in them. \n",
    "\n",
    "#### These need to be fixed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%time\n",
    "# select all the records where the duration was a negative. Then group on hhid and pid.\n",
    "# These unique hhid and pid values need to be re-processed with respect to start times\n",
    "need_fix = final_df.iloc[np.where(final_df['duration'].values < 0)]\n",
    "need_fix_gr = need_fix.groupby(['hhid', 'pid']).size().reset_index(name = 'counts')\n",
    "\n",
    "# get all the records that need to be fixed. One cannot only keep the records that need to be fixed,\n",
    "# but has to get all the records belonging to a particular hhid and pid combination to ensure consistency\n",
    "keys = ['hhid', 'pid']\n",
    "i1 = final_df.set_index(keys).index\n",
    "i2 = need_fix_gr.set_index(keys).index\n",
    "df_fix = final_df[i1.isin(i2)]   # df that needs fixing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "need_fix_gr.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(df_fix.shape)\n",
    "df_fix.head(9)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "tt = time_dist.loc[time_dist['pk_flag'] == 1]\n",
    "tt1 = tt.loc[tt['Time'] >= 7]\n",
    "tt1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def start_times_round2(trips_df, time_dist, purp_dir_product1, i):\n",
    "    \"\"\"\n",
    "    This function takes the trips_hhold dataframe and samples a start time for each trip based on the purpose and direction.\n",
    "    It ignores whether each trip record has been flagged by a peak/off-peak flag.\n",
    "    \n",
    "    Args:\n",
    "    \n",
    "    Return: dataframe with start time attached \n",
    "    \"\"\"\n",
    "    # slice dataframe by purpose and direction and save indices to numpy array. This is useful for concatenating\n",
    "    df_dir = trips_df.iloc[np.where((trips_df['purpose'].values == purp_dir_product1[0]) & \n",
    "                                    (trips_df['tour_direction'].values == purp_dir_product1[1]))].index.values\n",
    "    \n",
    "    # sample start times and save to numpy array\n",
    "    weight_column = purp_dir_product1[0] + '_' + purp_dir_product1[1] \n",
    "    \n",
    "    if trips_df.at[trips_df.index[i], 'duration'] < 0:\n",
    "        \n",
    "        # get arrival time of previous row\n",
    "        artime = trips_df.at[trips_df.index[i-1], 'arrival_time']\n",
    "        \n",
    "        # now subset the time distribution dataframe for the peak period of the trip and arrival \n",
    "        # time from previous record\n",
    "        pkflag_row = trips_df.at[trips_df.index[i], 'peak_flag']\n",
    "        time_dist2 = time_dist.loc[time_dist['pk_flag'] == pkflag_row]\n",
    "        time_dist2 = time_dist2.loc[time_dist2['Time'] >= artime]\n",
    "        \n",
    "        # sample\n",
    "        df_dir_sample = time_dist2.sample(n=1, weights= time_dist2[weight_column], replace=True, random_state=seed)\n",
    "        df_dir_sample = df_dir_sample[['Time']].values\n",
    "        \n",
    "        return df_dir_sample \n",
    "            \n",
    "    # Append the sampled times with the sliced dataframe indices\n",
    "#     df_dir_sample = pd.DataFrame(df_dir_sample, index=df_dir, columns=['start_time'])\n",
    "\n",
    "    \n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# get unique values to loop over and create a list\n",
    "purposes1 = df_fix['purpose'].unique().tolist()\n",
    "directions1 = df_fix['tour_direction'].unique().tolist()\n",
    "\n",
    "purp_dir_product1 = list(itertools.product(purposes1, directions1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_fix1 = df_fix.loc[df_fix['hhid'] == 2]\n",
    "df_fix1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "temp_df_fix_pkoffpk = {}\n",
    "for purp_dir in purp_dir_product1:\n",
    "        \n",
    "        for i in range(0, len(df_fix1)):    \n",
    "\n",
    "            # run start times for all combinations of trip purpose and tour direction\n",
    "            temp_df_fix_pkoffpk = start_times_round2(df_fix1, time_dist, purp_dir, i)\n",
    "#             temp_df_test_pkoffpk_comb = pd.concat(temp_df_test_pkoffpk.values(), axis = 0)\n",
    "    \n",
    "#     temp_df_test_purpdir[purp_dir] = temp_df_test_pkoffpk_comb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "type(temp_df_fix_pkoffpk)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "for purp_dir in purp_dir_product:\n",
    "for i in range(0, len(need_fix_gr)):\n",
    "    \n",
    "    start_times_round1(temp_df1, time_dist1, purp_dir)\n",
    "    \n",
    "    \n",
    "\n",
    "    n1 = need_fix_gr.at[need_fix_gr.index[i], 'hhid']\n",
    "    n2 = need_fix_gr.at[need_fix_gr.index[i], 'pid']\n",
    "    print(n1, n2)"
   ]
  }
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