diff options
| author | itsGarrin <garrin.shieh@gmail.com> | 2023-11-06 19:08:49 -0500 |
|---|---|---|
| committer | itsGarrin <garrin.shieh@gmail.com> | 2023-11-06 19:08:49 -0500 |
| commit | 921a49433ccb34f2481f5f88de59f596976193cb (patch) | |
| tree | b767c9247b94e6a58d00939a27cc9816a7bdbf37 /ZestySalesman.ipynb | |
| parent | c0a38c0054ab20311f416d038e6069263bfbcd54 (diff) | |
Refer to ZestySalesman.ipynb for the latest route
Diffstat (limited to 'ZestySalesman.ipynb')
| -rw-r--r-- | ZestySalesman.ipynb | 296 |
1 files changed, 218 insertions, 78 deletions
diff --git a/ZestySalesman.ipynb b/ZestySalesman.ipynb index 7e74f46..f39f5bc 100644 --- a/ZestySalesman.ipynb +++ b/ZestySalesman.ipynb @@ -2,65 +2,224 @@ "cells": [ { "cell_type": "code", - "execution_count": 10, + "execution_count": 16, "id": "initial_id", "metadata": { "collapsed": true, "ExecuteTime": { - "end_time": "2023-11-06T01:23:16.767323Z", - "start_time": "2023-11-06T01:23:16.761053Z" + "end_time": "2023-11-07T00:07:54.400654Z", + "start_time": "2023-11-07T00:07:54.375821Z" } }, "outputs": [], "source": [ "import pandas as pd\n", - "import numpy as np\n", - "import requests\n", "import folium\n", "import utils" ] }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 17, + "outputs": [], + "source": [ + "# Load the data\n", + "ListA = pd.read_csv('List A.csv')\n", + "ListB = pd.read_csv('List B.csv')\n", + "ListC = pd.read_csv('List C.csv')\n", + "ListD = pd.read_csv('List D.csv')" + ], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2023-11-07T00:07:54.430515Z", + "start_time": "2023-11-07T00:07:54.381537Z" + } + }, + "id": "73b780e762c9de37" + }, + { + "cell_type": "code", + "execution_count": 18, + "outputs": [], + "source": [ + "# Create two centroids, one in the North End and one in the Financial District\n", + "centroids = [[42.364506, -71.054733], [42.358894, -71.056742]]\n", + "\n", + "northeastern_coordinate = \"-71.09033,42.33976\"" + ], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2023-11-07T00:07:54.431407Z", + "start_time": "2023-11-07T00:07:54.392677Z" + } + }, + "id": "65e208650eb43b4" + }, + { + "cell_type": "code", + "execution_count": 19, + "outputs": [], + "source": [ + "# Combine the two lists and add a column to indicate the list\n", + "ListA['list'] = 'A'\n", + "ListB['list'] = 'B'\n", + "ListC['list'] = 'C'\n", + "ListD['list'] = 'D'\n", + "\n", + "TotalList = pd.concat([ListA, ListB, ListC])" + ], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2023-11-07T00:07:54.431829Z", + "start_time": "2023-11-07T00:07:54.397279Z" + } + }, + "id": "ffe4025e97a6c6b9" + }, + { + "cell_type": "code", + "execution_count": 20, + "outputs": [], + "source": [ + "# Remove all columns but name and gps\n", + "TotalList = TotalList[['name', 'gps', 'list']]" + ], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2023-11-07T00:07:54.432180Z", + "start_time": "2023-11-07T00:07:54.401907Z" + } + }, + "id": "72657779b4484aae" + }, + { + "cell_type": "code", + "execution_count": 21, + "outputs": [], + "source": [ + "# Convert the gps column to a list of lists for k-means\n", + "TotalList['gps'] = TotalList['gps'].apply(lambda x: x.strip('[]').split(','))\n", + "TotalList['gps'] = TotalList['gps'].apply(lambda x: [float(i) for i in x])" + ], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2023-11-07T00:07:54.432238Z", + "start_time": "2023-11-07T00:07:54.405216Z" + } + }, + "id": "a157ffaec020a29a" + }, + { + "cell_type": "code", + "execution_count": 22, + "outputs": [ + { + "data": { + "text/plain": " name gps list \\\n0 521 Commercial Street #525 [42.3688272, -71.0553792] A \n1 Acorn St [42.3576234, -71.0688746] A \n2 Arlington's Great Meadows [42.4299758, -71.2038948] A \n3 Arthur Fiedler Statue [42.3565057, -71.0754527] A \n4 BU Beach [42.3511927, -71.1060828] A \n.. ... ... ... \n28 The Clam Box [42.2763168, -71.0092883] C \n29 The Partisans [42.3478375, -71.0404428] C \n30 Union Oyster House [42.361288, -71.056908] C \n31 Victoria's Diner [42.3270498, -71.0667744] C \n32 Wollaston Beach [42.2806539, -71.0119933] C \n\n normalized_gps \n0 [0.7251058917247415, 0.8141430878559053] \n1 [0.6747391031099019, 0.778052752104061] \n2 [1.0, 0.41697235794883575] \n3 [0.6697144722136962, 0.7604611403245493] \n4 [0.6458298305822171, 0.6785480000609988] \n.. ... \n28 [0.30922451563130937, 0.9374025730216268] \n29 [0.6307464973238023, 0.8540870458656248] \n30 [0.6912133469876947, 0.8100546647415456] \n31 [0.5372951958288665, 0.7836692527743693] \n32 [0.32872198960456106, 0.9301686741961767] \n\n[131 rows x 4 columns]", + "text/html": "<div>\n<style scoped>\n .dataframe tbody tr th:only-of-type {\n vertical-align: middle;\n }\n\n .dataframe tbody tr th {\n vertical-align: top;\n }\n\n .dataframe thead th {\n text-align: right;\n }\n</style>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>name</th>\n <th>gps</th>\n <th>list</th>\n <th>normalized_gps</th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>0</th>\n <td>521 Commercial Street #525</td>\n <td>[42.3688272, -71.0553792]</td>\n <td>A</td>\n <td>[0.7251058917247415, 0.8141430878559053]</td>\n </tr>\n <tr>\n <th>1</th>\n <td>Acorn St</td>\n <td>[42.3576234, -71.0688746]</td>\n <td>A</td>\n <td>[0.6747391031099019, 0.778052752104061]</td>\n </tr>\n <tr>\n <th>2</th>\n <td>Arlington's Great Meadows</td>\n <td>[42.4299758, -71.2038948]</td>\n <td>A</td>\n <td>[1.0, 0.41697235794883575]</td>\n </tr>\n <tr>\n <th>3</th>\n <td>Arthur Fiedler Statue</td>\n <td>[42.3565057, -71.0754527]</td>\n <td>A</td>\n <td>[0.6697144722136962, 0.7604611403245493]</td>\n </tr>\n <tr>\n <th>4</th>\n <td>BU Beach</td>\n <td>[42.3511927, -71.1060828]</td>\n <td>A</td>\n <td>[0.6458298305822171, 0.6785480000609988]</td>\n </tr>\n <tr>\n <th>...</th>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n </tr>\n <tr>\n <th>28</th>\n <td>The Clam Box</td>\n <td>[42.2763168, -71.0092883]</td>\n <td>C</td>\n <td>[0.30922451563130937, 0.9374025730216268]</td>\n </tr>\n <tr>\n <th>29</th>\n <td>The Partisans</td>\n <td>[42.3478375, -71.0404428]</td>\n <td>C</td>\n <td>[0.6307464973238023, 0.8540870458656248]</td>\n </tr>\n <tr>\n <th>30</th>\n <td>Union Oyster House</td>\n <td>[42.361288, -71.056908]</td>\n <td>C</td>\n <td>[0.6912133469876947, 0.8100546647415456]</td>\n </tr>\n <tr>\n <th>31</th>\n <td>Victoria's Diner</td>\n <td>[42.3270498, -71.0667744]</td>\n <td>C</td>\n <td>[0.5372951958288665, 0.7836692527743693]</td>\n </tr>\n <tr>\n <th>32</th>\n <td>Wollaston Beach</td>\n <td>[42.2806539, -71.0119933]</td>\n <td>C</td>\n <td>[0.32872198960456106, 0.9301686741961767]</td>\n </tr>\n </tbody>\n</table>\n<p>131 rows × 4 columns</p>\n</div>" + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Create a new column with normalized gps coordinates and centroids\n", + "TotalList['normalized_gps'], norm_centroids = utils.normalize_gps(TotalList['gps'].values.tolist(), centroids)\n", + "display(TotalList)" + ], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2023-11-07T00:07:54.432731Z", + "start_time": "2023-11-07T00:07:54.412279Z" + } + }, + "id": "a03ebde91b87fa3b" + }, + { + "cell_type": "markdown", + "source": [ + "# Cluster and Minimize" + ], + "metadata": { + "collapsed": false + }, + "id": "4bd41be9aca5094b" + }, + { + "cell_type": "code", + "execution_count": 23, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/garrinshieh/anaconda3/lib/python3.11/site-packages/sklearn/cluster/_kmeans.py:1412: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n", + " super()._check_params_vs_input(X, default_n_init=10)\n", + "/Users/garrinshieh/anaconda3/lib/python3.11/site-packages/sklearn/cluster/_kmeans.py:1412: RuntimeWarning: Explicit initial center position passed: performing only one init in KMeans instead of n_init=10.\n", + " super()._check_params_vs_input(X, default_n_init=10)\n" + ] + } + ], + "source": [ + "# Cluster and minimize the data\n", + "df, route_1_coordinates, route_2_coordinates = utils.cluster_and_minimize(TotalList, centroids, norm_centroids,\n", + " northeastern_coordinate, 0.5)" + ], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2023-11-07T00:08:20.577006Z", + "start_time": "2023-11-07T00:07:54.416349Z" + } + }, + "id": "ee9b3c1ecb360976" + }, + { + "cell_type": "code", + "execution_count": 24, "outputs": [], "source": [ "# Create a JSON request for the API\n", "# This is the data we want to get from the API\n", - "northeastern_coordinate = \"-71.09033,42.33976;\"\n", - "route_1 = '-71.2038948,42.4299758;-71.1060828,42.3511927;-71.0969274,42.3446263;-71.130887,42.35304;-71.1459593,42.3501823;-71.1460435,42.3495825;-71.1217152,42.3426377;-71.1258765,42.331864;-71.1095021,42.3364675;-71.133103,42.3890049;-71.1123834,42.3360385;-71.2273649,42.3145041;-71.0992038,42.3306454;-71.0990577,42.3381442;-71.0949218,42.3419564;-71.0942861,42.3413301;-71.0913583,42.3490205;-71.1000217,42.3323776;-71.1241295,42.3518397;-71.1618052,42.3245965;-71.1625829,42.340795;-71.167854,42.4107892;-71.155555,42.3317473;-71.1227278,42.3965778;-71.1126695,42.3836229;-71.119149,42.3884;-71.1427371,42.3433772;-71.1438455,42.3569102;-71.1313443,42.3525708;-71.1284677,42.3631904;-71.119301,42.388547;-71.097883,42.381008;-71.1107166,42.3741209;-71.1194344,42.3754427;-71.1013044,42.3627462;-71.1108423,42.3838224;-71.1026937,42.3820702;-71.1189467,42.373465;-71.1208817,42.3732344;-71.0968274,42.3799095;-71.094048,42.339381;-71.1854722,42.3621177;-71.1146697,42.3782386;-71.0935443,42.3817274;-71.0906355,42.3616095;-71.1161887,42.3766442;-71.0962734,42.3627993;-71.1155576,42.3784629;-71.0949101,42.3797674;-71.1087411,42.3640287;-71.09476,42.37736;-71.1014951,42.3614115;-71.1024769,42.3822934;-71.1011111,42.3636597;-71.0898829,42.3463992;-71.0983169,42.3319001'\n", - "route_2 = '-71.0553792,42.3688272;-71.0688746,42.3576234;-71.0754527,42.3565057;-71.0620802,42.3579151;-71.0586014,42.357357;-71.0572023,42.3587627;-71.0556268,42.36521;-71.0720926,42.3489004;-71.067859,42.3500079;-71.0632036,42.3556154;-71.0620134,42.3248471;-71.0851891,42.3500031;-71.066414,42.354296;-71.0834061,42.341987;-71.0569649,42.3604952;-71.0498714,42.3256817;-71.0908104,42.329969;-71.0616035,42.3537983;-71.0359433,42.3485465;-71.0638101,42.3587772;-71.0555003,42.3640137;-71.0712561,42.3407613;-71.0561781,42.3668968;-71.0664019,42.3554589;-71.059228,42.359349;-71.0668408,42.3524116;-71.0872846,42.2961434;-71.062146,42.366198;-71.0651214,42.3553972;-71.0596124,42.3509517;-71.0359354,42.3478381;-71.061757,42.3691906;-71.0609962,42.3803747;-71.0516339,42.3609921;-71.0809932,42.3675275;-71.0545357,42.3597994;-71.0342146,42.316274;-71.0756902,42.3695046;-71.0678704,42.3701829;-71.0656594,42.3718401;-71.0611749,42.3551807;-71.0554239,42.3739796;-71.0631664,42.3741694;-71.056823,42.361531;-71.0632852,42.2857047;-71.0637877,42.2845163;-71.0496839,42.3519736;-71.0454645,42.3162356;-71.0336324,42.3441918;-71.0487437,42.3508756;-71.0512911,42.3521821;-71.0013637,42.2075316;-71.0607764,42.3763541;-71.0374911,42.316031;-71.0125206,42.3378699;-71.0672898,42.3523158;-71.02832,42.2576602;-71.0502126,42.3516479;-71.0331956,42.3639107;-71.0432778,42.3528151;-71.0035279,42.2392354;-71.0470633,42.3537343;-71.0352443,42.3291218;-71.0240951,42.2743442;-71.0234949,42.3358743;-70.985881,42.420226;-71.0005483,42.2454086;-71.0096371,42.3367603;-71.0447796,42.3509709;-71.0092883,42.2763168;-71.0404428,42.3478375;-71.056908,42.361288;-71.0667744,42.3270498;-71.0119933,42.2806539'" + "route_1 = utils.list_to_string(route_1_coordinates)\n", + "route_2 = utils.list_to_string(route_2_coordinates)" ], "metadata": { "collapsed": false, "ExecuteTime": { - "end_time": "2023-11-06T01:23:16.774149Z", - "start_time": "2023-11-06T01:23:16.765417Z" + "end_time": "2023-11-07T00:08:20.591584Z", + "start_time": "2023-11-07T00:08:20.577492Z" } }, "id": "aa618161182b5b07" }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 25, "outputs": [], "source": [ "# Create a dataframe from the JSON\n", - "df1 = utils.create_json_df(northeastern_coordinate + route_1)\n", - "df2 = utils.create_json_df(northeastern_coordinate + route_2)" + "df1 = utils.create_json_df(route_1, utils.list_to_string([centroids[0]]), northeastern_coordinate)\n", + "df2 = utils.create_json_df(route_2, utils.list_to_string([centroids[1]]), northeastern_coordinate)" ], "metadata": { "collapsed": false, "ExecuteTime": { - "end_time": "2023-11-06T01:23:18.694403Z", - "start_time": "2023-11-06T01:23:16.768656Z" + "end_time": "2023-11-07T00:08:22.409355Z", + "start_time": "2023-11-07T00:08:20.579890Z" } }, "id": "32c485788eedd94" }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 26, "outputs": [], "source": [ "# Add columns for the route number\n", @@ -73,20 +232,20 @@ "metadata": { "collapsed": false, "ExecuteTime": { - "end_time": "2023-11-06T01:23:18.698699Z", - "start_time": "2023-11-06T01:23:18.696008Z" + "end_time": "2023-11-07T00:08:22.425179Z", + "start_time": "2023-11-07T00:08:22.412707Z" } }, "id": "49dba1f17ca8337e" }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 27, "outputs": [ { "data": { - "text/plain": " waypoint_index trips_index \\\n0 0 0 \n17 1 0 \n22 2 0 \n73 3 0 \n11 4 0 \n.. ... ... \n3 70 0 \n12 71 0 \n9 72 0 \n8 73 0 \n14 74 0 \n\n hint distance \\\n0 DoUhgBeFIYCcAAAAJgAAAAAAAAARAAAAm0CKQdkZiEAAAA... 0.236958 \n17 5tYhgJHXIYAIAAAArQAAADwAAABCAQAAaRlbQD16mUGpAc... 17.374491 \n22 XAAigHIAIoBKAAAASwAAAFUAAABDAQAARGUEQURlBEG2ZR... 11.054154 \n73 CdQhgB0OA4AYAAAAHgAAADkAAAAAAAAALdMlQdSMQ0Fd0r... 10.970598 \n11 43YhgPN2IYA1AAAAJAAAAAAAAAA5AAAAEha0QWgpbEEAAA... 18.896385 \n.. ... ... \n3 jt4hgJLeIYA7AAAALQAAAAAAAAAAAAAA4gPGQasVlUEAAA... 4.709088 \n12 0OEhgPvhIYADAAAABgAAAA8AAAA0AAAA2lq-PipQFD-Y-N... 2.009578 \n9 m8shgJ7LIYAOAAAAXgEAAAAAAAAAAAAAOFW-QDE5G0IAAA... 1.716409 \n8 YQ0DgBTPIYDvAAAAdAAAAAAAAAAAAAAAsgLVQbMxTUEAAA... 4.830022 \n14 lhgDgIkYA4BkAAAAIgEAAFoBAAAaAAAAJyAzQWNrAEI8Ax... 7.134933 \n\n name location lat lon \\\n0 Northeastern (Inbound) [-71.090331, 42.339762] -71.090331 42.339762 \n17 Dudley Street [-71.090904, 42.329829] -71.090904 42.329829 \n22 [-71.071196, 42.34085] -71.071196 42.340850 \n73 [-71.066844, 42.327134] -71.066844 42.327134 \n11 Lucy Street [-71.06221, 42.324934] -71.062210 42.324934 \n.. ... ... ... ... \n3 [-71.075414, 42.356537] -71.075414 42.356537 \n12 [-71.085166, 42.349997] -71.085166 42.349997 \n9 Piedmont Street [-71.067854, 42.349993] -71.067854 42.349993 \n8 [-71.072038, 42.348915] -71.072038 42.348915 \n14 [-71.083465, 42.34194] -71.083465 42.341940 \n\n route \n0 2 \n17 2 \n22 2 \n73 2 \n11 2 \n.. ... \n3 2 \n12 2 \n9 2 \n8 2 \n14 2 \n\n[75 rows x 9 columns]", - "text/html": "<div>\n<style scoped>\n .dataframe tbody tr th:only-of-type {\n vertical-align: middle;\n }\n\n .dataframe tbody tr th {\n vertical-align: top;\n }\n\n .dataframe thead th {\n text-align: right;\n }\n</style>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>waypoint_index</th>\n <th>trips_index</th>\n <th>hint</th>\n <th>distance</th>\n <th>name</th>\n <th>location</th>\n <th>lat</th>\n <th>lon</th>\n <th>route</th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>0</th>\n <td>0</td>\n <td>0</td>\n <td>DoUhgBeFIYCcAAAAJgAAAAAAAAARAAAAm0CKQdkZiEAAAA...</td>\n <td>0.236958</td>\n <td>Northeastern (Inbound)</td>\n <td>[-71.090331, 42.339762]</td>\n <td>-71.090331</td>\n <td>42.339762</td>\n <td>2</td>\n </tr>\n <tr>\n <th>17</th>\n <td>1</td>\n <td>0</td>\n <td>5tYhgJHXIYAIAAAArQAAADwAAABCAQAAaRlbQD16mUGpAc...</td>\n <td>17.374491</td>\n <td>Dudley Street</td>\n <td>[-71.090904, 42.329829]</td>\n <td>-71.090904</td>\n <td>42.329829</td>\n <td>2</td>\n </tr>\n <tr>\n <th>22</th>\n <td>2</td>\n <td>0</td>\n <td>XAAigHIAIoBKAAAASwAAAFUAAABDAQAARGUEQURlBEG2ZR...</td>\n <td>11.054154</td>\n <td></td>\n <td>[-71.071196, 42.34085]</td>\n <td>-71.071196</td>\n <td>42.340850</td>\n <td>2</td>\n </tr>\n <tr>\n <th>73</th>\n <td>3</td>\n <td>0</td>\n <td>CdQhgB0OA4AYAAAAHgAAADkAAAAAAAAALdMlQdSMQ0Fd0r...</td>\n <td>10.970598</td>\n <td></td>\n <td>[-71.066844, 42.327134]</td>\n <td>-71.066844</td>\n <td>42.327134</td>\n <td>2</td>\n </tr>\n <tr>\n <th>11</th>\n <td>4</td>\n <td>0</td>\n <td>43YhgPN2IYA1AAAAJAAAAAAAAAA5AAAAEha0QWgpbEEAAA...</td>\n <td>18.896385</td>\n <td>Lucy Street</td>\n <td>[-71.06221, 42.324934]</td>\n <td>-71.062210</td>\n <td>42.324934</td>\n <td>2</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 </tr>\n <tr>\n <th>3</th>\n <td>70</td>\n <td>0</td>\n <td>jt4hgJLeIYA7AAAALQAAAAAAAAAAAAAA4gPGQasVlUEAAA...</td>\n <td>4.709088</td>\n <td></td>\n <td>[-71.075414, 42.356537]</td>\n <td>-71.075414</td>\n <td>42.356537</td>\n <td>2</td>\n </tr>\n <tr>\n <th>12</th>\n <td>71</td>\n <td>0</td>\n <td>0OEhgPvhIYADAAAABgAAAA8AAAA0AAAA2lq-PipQFD-Y-N...</td>\n <td>2.009578</td>\n <td></td>\n <td>[-71.085166, 42.349997]</td>\n <td>-71.085166</td>\n <td>42.349997</td>\n <td>2</td>\n </tr>\n <tr>\n <th>9</th>\n <td>72</td>\n <td>0</td>\n <td>m8shgJ7LIYAOAAAAXgEAAAAAAAAAAAAAOFW-QDE5G0IAAA...</td>\n <td>1.716409</td>\n <td>Piedmont Street</td>\n <td>[-71.067854, 42.349993]</td>\n <td>-71.067854</td>\n <td>42.349993</td>\n <td>2</td>\n </tr>\n <tr>\n <th>8</th>\n <td>73</td>\n <td>0</td>\n <td>YQ0DgBTPIYDvAAAAdAAAAAAAAAAAAAAAsgLVQbMxTUEAAA...</td>\n <td>4.830022</td>\n <td></td>\n <td>[-71.072038, 42.348915]</td>\n <td>-71.072038</td>\n <td>42.348915</td>\n <td>2</td>\n </tr>\n <tr>\n <th>14</th>\n <td>74</td>\n <td>0</td>\n <td>lhgDgIkYA4BkAAAAIgEAAFoBAAAaAAAAJyAzQWNrAEI8Ax...</td>\n <td>7.134933</td>\n <td></td>\n <td>[-71.083465, 42.34194]</td>\n <td>-71.083465</td>\n <td>42.341940</td>\n <td>2</td>\n </tr>\n </tbody>\n</table>\n<p>75 rows × 9 columns</p>\n</div>" + "text/plain": " waypoint_index trips_index \\\n0 0 0 \n13 1 0 \n68 2 0 \n40 3 0 \n22 4 0 \n.. ... ... \n14 67 0 \n11 68 0 \n69 69 0 \n19 70 0 \n71 71 0 \n\n hint distance \\\n0 dMQAgDTDAIAuAAAAEgAAAAAAAAAAAAAAiaamQKk960AAAA... 1.113855 \n13 oLwsgCS9LIBHAAAA2AAAAAAAAABgAQAAkQwAQdo1v0EAAA... 2.532529 \n68 CL0sgBS9LIAhAAAAagAAAAAAAAAAAAAAfoF0QPCwOkEAAA... 7.608103 \n40 YbwsgEO9LIBbAAAAEgAAAAAAAAAPAAAA5ua1QcswjkAAAA... 0.468602 \n22 UkAEgFxABIB8AAAAAAAAAAAAAAAYAgAAVjBdQQAAAAAAAA... 6.397300 \n.. ... ... \n14 -mUsgHZmLIATAAAAYgEAAL0AAADpAAAALf8HQHZ8HUK-9a... 55.355565 \n11 43YhgPN2IYA1AAAAJAAAAAAAAAA5AAAAEha0QWgpbEEAAA... 18.896385 \n69 CdQhgB0OA4AYAAAAHgAAADkAAAAAAAAALdMlQdSMQ0Fd0r... 10.970598 \n19 XAAigHIAIoBKAAAASwAAAFUAAABDAQAARGUEQURlBEG2ZR... 11.054154 \n71 DoUhgBeFIYCcAAAAJgAAAAAAAAARAAAAm0CKQdkZiEAAAA... 0.236958 \n\n name location lat lon \\\n0 State Street [-71.056741, 42.358884] -71.056741 42.358884 \n13 [-71.056995, 42.36049] -71.056995 42.360490 \n68 [-71.056994, 42.361263] -71.056994 42.361263 \n40 Creek Square [-71.056819, 42.361534] -71.056819 42.361534 \n22 [-71.059255, 42.359295] -71.059255 42.359295 \n.. ... ... ... ... \n14 [-71.049204, 42.325624] -71.049204 42.325624 \n11 Lucy Street [-71.06221, 42.324934] -71.062210 42.324934 \n69 [-71.066844, 42.327134] -71.066844 42.327134 \n19 [-71.071196, 42.34085] -71.071196 42.340850 \n71 Northeastern (Inbound) [-71.090331, 42.339762] -71.090331 42.339762 \n\n route \n0 2 \n13 2 \n68 2 \n40 2 \n22 2 \n.. ... \n14 2 \n11 2 \n69 2 \n19 2 \n71 2 \n\n[72 rows x 9 columns]", + "text/html": "<div>\n<style scoped>\n .dataframe tbody tr th:only-of-type {\n vertical-align: middle;\n }\n\n .dataframe tbody tr th {\n vertical-align: top;\n }\n\n .dataframe thead th {\n text-align: right;\n }\n</style>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>waypoint_index</th>\n <th>trips_index</th>\n <th>hint</th>\n <th>distance</th>\n <th>name</th>\n <th>location</th>\n <th>lat</th>\n <th>lon</th>\n <th>route</th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>0</th>\n <td>0</td>\n <td>0</td>\n <td>dMQAgDTDAIAuAAAAEgAAAAAAAAAAAAAAiaamQKk960AAAA...</td>\n <td>1.113855</td>\n <td>State Street</td>\n <td>[-71.056741, 42.358884]</td>\n <td>-71.056741</td>\n <td>42.358884</td>\n <td>2</td>\n </tr>\n <tr>\n <th>13</th>\n <td>1</td>\n <td>0</td>\n <td>oLwsgCS9LIBHAAAA2AAAAAAAAABgAQAAkQwAQdo1v0EAAA...</td>\n <td>2.532529</td>\n <td></td>\n <td>[-71.056995, 42.36049]</td>\n <td>-71.056995</td>\n <td>42.360490</td>\n <td>2</td>\n </tr>\n <tr>\n <th>68</th>\n <td>2</td>\n <td>0</td>\n <td>CL0sgBS9LIAhAAAAagAAAAAAAAAAAAAAfoF0QPCwOkEAAA...</td>\n <td>7.608103</td>\n <td></td>\n <td>[-71.056994, 42.361263]</td>\n <td>-71.056994</td>\n <td>42.361263</td>\n <td>2</td>\n </tr>\n <tr>\n <th>40</th>\n <td>3</td>\n <td>0</td>\n <td>YbwsgEO9LIBbAAAAEgAAAAAAAAAPAAAA5ua1QcswjkAAAA...</td>\n <td>0.468602</td>\n <td>Creek Square</td>\n <td>[-71.056819, 42.361534]</td>\n <td>-71.056819</td>\n <td>42.361534</td>\n <td>2</td>\n </tr>\n <tr>\n <th>22</th>\n <td>4</td>\n <td>0</td>\n <td>UkAEgFxABIB8AAAAAAAAAAAAAAAYAgAAVjBdQQAAAAAAAA...</td>\n <td>6.397300</td>\n <td></td>\n <td>[-71.059255, 42.359295]</td>\n <td>-71.059255</td>\n <td>42.359295</td>\n <td>2</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 </tr>\n <tr>\n <th>14</th>\n <td>67</td>\n <td>0</td>\n <td>-mUsgHZmLIATAAAAYgEAAL0AAADpAAAALf8HQHZ8HUK-9a...</td>\n <td>55.355565</td>\n <td></td>\n <td>[-71.049204, 42.325624]</td>\n <td>-71.049204</td>\n <td>42.325624</td>\n <td>2</td>\n </tr>\n <tr>\n <th>11</th>\n <td>68</td>\n <td>0</td>\n <td>43YhgPN2IYA1AAAAJAAAAAAAAAA5AAAAEha0QWgpbEEAAA...</td>\n <td>18.896385</td>\n <td>Lucy Street</td>\n <td>[-71.06221, 42.324934]</td>\n <td>-71.062210</td>\n <td>42.324934</td>\n <td>2</td>\n </tr>\n <tr>\n <th>69</th>\n <td>69</td>\n <td>0</td>\n <td>CdQhgB0OA4AYAAAAHgAAADkAAAAAAAAALdMlQdSMQ0Fd0r...</td>\n <td>10.970598</td>\n <td></td>\n <td>[-71.066844, 42.327134]</td>\n <td>-71.066844</td>\n <td>42.327134</td>\n <td>2</td>\n </tr>\n <tr>\n <th>19</th>\n <td>70</td>\n <td>0</td>\n <td>XAAigHIAIoBKAAAASwAAAFUAAABDAQAARGUEQURlBEG2ZR...</td>\n <td>11.054154</td>\n <td></td>\n <td>[-71.071196, 42.34085]</td>\n <td>-71.071196</td>\n <td>42.340850</td>\n <td>2</td>\n </tr>\n <tr>\n <th>71</th>\n <td>71</td>\n <td>0</td>\n <td>DoUhgBeFIYCcAAAAJgAAAAAAAAARAAAAm0CKQdkZiEAAAA...</td>\n <td>0.236958</td>\n <td>Northeastern (Inbound)</td>\n <td>[-71.090331, 42.339762]</td>\n <td>-71.090331</td>\n <td>42.339762</td>\n <td>2</td>\n </tr>\n </tbody>\n</table>\n<p>72 rows × 9 columns</p>\n</div>" }, "metadata": {}, "output_type": "display_data" @@ -98,22 +257,22 @@ "metadata": { "collapsed": false, "ExecuteTime": { - "end_time": "2023-11-06T01:23:18.708601Z", - "start_time": "2023-11-06T01:23:18.705324Z" + "end_time": "2023-11-07T00:08:22.440853Z", + "start_time": "2023-11-07T00:08:22.424158Z" } }, "id": "f231d9a35358988c" }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 28, "outputs": [ { "data": { - "text/plain": "<folium.folium.Map at 0x1277ac5d0>", - "text/html": "<div style=\"width:100%;\"><div style=\"position:relative;width:100%;height:0;padding-bottom:60%;\"><span style=\"color:#565656\">Make this Notebook Trusted to load map: File -> Trust Notebook</span><iframe srcdoc=\"<!DOCTYPE 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href="https://netdna.bootstrapcdn.com/bootstrap/3.0.0/css/bootstrap.min.css"/>\n <link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/@fortawesome/fontawesome-free@6.2.0/css/all.min.css"/>\n <link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.css"/>\n <link rel="stylesheet" href="https://cdn.jsdelivr.net/gh/python-visualization/folium/folium/templates/leaflet.awesome.rotate.min.css"/>\n \n <meta name="viewport" content="width=device-width,\n initial-scale=1.0, maximum-scale=1.0, user-scalable=no" />\n <style>\n #map_aeeac5a1da4c82f72a6ebc2ad6ef0a4f {\n position: relative;\n width: 100.0%;\n height: 100.0%;\n left: 0.0%;\n top: 0.0%;\n }\n .leaflet-container { font-size: 1rem; }\n </style>\n \n</head>\n<body>\n \n \n <div class="folium-map" id="map_aeeac5a1da4c82f72a6ebc2ad6ef0a4f" ></div>\n \n</body>\n<script>\n \n \n var map_aeeac5a1da4c82f72a6ebc2ad6ef0a4f = L.map(\n "map_aeeac5a1da4c82f72a6ebc2ad6ef0a4f",\n 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"output_type": "execute_result" } @@ -127,9 +286,10 @@ "\n", "for route in df['route'].unique():\n", " df_route = df[df['route'] == route]\n", - " folium.PolyLine(df_route[['lon', 'lat']].values.tolist(), color=colors[route-1]).add_to(m)\n", + " folium.PolyLine(df_route[['lon', 'lat']].values.tolist(), color=colors[route - 1]).add_to(m)\n", " for i in range(len(df_route)):\n", - " folium.CircleMarker(df_route[['lon', 'lat']].iloc[i].values.tolist(), radius=3, color=colors[route-1]).add_to(m)\n", + " folium.CircleMarker(df_route[['lon', 'lat']].iloc[i].values.tolist(), radius=3, color=colors[route - 1]).add_to(\n", + " m)\n", "\n", "# Display the map\n", "m" @@ -137,101 +297,81 @@ "metadata": { "collapsed": false, "ExecuteTime": { - "end_time": "2023-11-06T01:23:18.781393Z", - "start_time": "2023-11-06T01:23:18.709803Z" + "end_time": "2023-11-07T00:08:22.513542Z", + "start_time": "2023-11-07T00:08:22.430363Z" } }, "id": "80fd847da2833913" }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 29, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "The trip will take 6.789722222222222 hours\n", - "The trip will take 9.955833333333333 hours\n" + "Route 1 has 61 waypoints\n", + "Route 2 has 70 waypoints\n" ] } ], "source": [ - "trip_hrs_1 = utils.get_trip_time(route_1)\n", - "print(\"The trip will take {} hours\".format(trip_hrs_1))\n", - "trip_hrs_2 = utils.get_trip_time(route_2)\n", - "print(\"The trip will take {} hours\".format(trip_hrs_2))" + "# Get the number of waypoints for each route\n", + "route_1_waypoints = len(route_1_coordinates)\n", + "route_2_waypoints = len(route_2_coordinates)\n", + "print(\"Route 1 has {} waypoints\".format(route_1_waypoints))\n", + "print(\"Route 2 has {} waypoints\".format(route_2_waypoints))" ], "metadata": { "collapsed": false, "ExecuteTime": { - "end_time": "2023-11-06T01:23:20.448487Z", - "start_time": "2023-11-06T01:23:18.761079Z" + "end_time": "2023-11-07T00:08:22.513689Z", + "start_time": "2023-11-07T00:08:22.488854Z" } }, - "id": "a3ec09dfb5cbb5b3" + "id": "f53c97acec1c2fc4" }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 30, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - " waypoint_index trips_index \\\n", - "20 20 0 \n", - "\n", - " hint distance name \\\n", - "20 2M4pgNrOKYCCAQAADAAAAAAAAAAAAAAALKILQ27Ah0AAAA... 0.0 Echo Bridge \n", - "\n", - " location lat lon route \n", - "20 [-71.227365, 42.314504] -71.227365 42.314504 1 \n" + "The trip will take 10.36111111111111 hours\n", + "The trip will take 10.586666666666666 hours\n" ] } ], "source": [ - "# Find the westmost point in Route 1\n", - "df1 = df[df['route'] == 1]\n", - "west = df1[df1['lon'] == df1['lon'].min()]\n", - "print(west)" - ], - "metadata": { - "collapsed": false, - "ExecuteTime": { - "end_time": "2023-11-06T01:23:20.455714Z", - "start_time": "2023-11-06T01:23:20.453647Z" - } - }, - "id": "be94c3708a1bd250" - }, - { - "cell_type": "code", - "execution_count": 18, - "outputs": [], - "source": [ - "# Remove the westmost point from Route 1\n", - "df = df.drop(west.index)" + "trip_hrs_1 = utils.get_trip_time(route_1, route_1_waypoints, utils.list_to_string([centroids[0]]),\n", + " northeastern_coordinate)\n", + "print(\"The trip will take {} hours\".format(trip_hrs_1))\n", + "trip_hrs_2 = utils.get_trip_time(route_2, route_2_waypoints, utils.list_to_string([centroids[1]]),\n", + " northeastern_coordinate)\n", + "print(\"The trip will take {} hours\".format(trip_hrs_2))" ], "metadata": { "collapsed": false, "ExecuteTime": { - "end_time": "2023-11-06T01:23:20.460791Z", - "start_time": "2023-11-06T01:23:20.456599Z" + "end_time": "2023-11-07T00:08:24.460727Z", + "start_time": "2023-11-07T00:08:22.491469Z" } }, - "id": "21fef07e5b2a03a0" + "id": "a3ec09dfb5cbb5b3" }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 30, "outputs": [], "source": [], "metadata": { "collapsed": false, "ExecuteTime": { - "end_time": "2023-11-06T01:23:20.460900Z", - "start_time": "2023-11-06T01:23:20.458522Z" + "end_time": "2023-11-07T00:08:24.471189Z", + "start_time": "2023-11-07T00:08:24.460431Z" } }, "id": "eafe5678c44e94fd" |