{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "d88f9072",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "source": [
    "# Map-match a track on a network\n",
    "\n",
    "<div class=\"alert alert-block alert-warning\" style=\"padding:1em\">The function to map-match a track on a network is: <b><i>mapOnNetwork</i></b>.</div>\n",
    "\n",
    "<br/>\n",
    "<div style='text-align:justify'>In this tutorial, points are map-matched to a reference road network by applying the Hidden Markov Models algorithm developed by Newson and Krumm (Newson & Krumm, 2009). The algorithm, for each point to match, takes into account the points before and after, thus the consistency of the routes is fulﬁlled.</div>\n",
    "\n",
    "<br/>\n",
    "<div class=\"alert alert-block alert-info\" style='text-align:justify'>\n",
    "    <b>Reference:</b><br/>Newson, P., & Krumm, J. (2009). <i>Hidden Markov map matching through noise and sparseness.</i> Proceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, GIS ‘09, ACM, New York, NY, USA, pp. 336–343. <a href='https://doi.org/10.1145/1653771.1653818'>https://doi.org/10.1145/1653771.1653818</a></div>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "06fc9e46",
   "metadata": {},
   "source": [
    "## Let's start by importing tracklib library"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "b0e5059a",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import os\n",
    "import sys\n",
    "\n",
    "#-------------------------------------------------------\n",
    "# 1. [if tracklib is not installed using pip] add tracklib's local path in the python path\n",
    "module_path = os.path.abspath(os.path.join('../../..'))\n",
    "if module_path not in sys.path:\n",
    "    sys.path.append(module_path)\n",
    "\n",
    "# 2. Import\n",
    "import tracklib as trk"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "09ce4248",
   "metadata": {},
   "source": [
    "## Loading GPS points\n",
    "\n",
    "Data points are stored in a csv file. The first line contained header with names of columns:  \n",
    "<div style='margin-left:4em'><i>X,Y,track_fid,track_seg_id,track_seg_point_id,ele,time</i></div>\n",
    "\n",
    "Coordinates is provided in Geographic system reference and separtor caracter is the comma. The time's format is: <i>“4Y/2M/2D 2h:2m:2s”</i>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "1d5a502f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-------------------------------------\n",
      "GPS track #22245 of user 0:\n",
      "-------------------------------------\n",
      "  Nb of pt(s):   52\n",
      "  Ref sys id   : ENU\n",
      "  Starting at  : 12/07/2019 15:42:35\n",
      "  Ending at    : 12/07/2019 16:48:16\n",
      "  Duration     : 3941.000 s\n",
      "  Length       : 1325.369 m\n",
      "-------------------------------------\n",
      "\n"
     ]
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Specify time format\n",
    "trk.ObsTime.setReadFormat(\"4Y/2M/2D 2h:2m:2s\")\n",
    "\n",
    "# local file path\n",
    "trackpath = '../../../data/csv/22245.csv'\n",
    "\n",
    "# Loading GPS points\n",
    "param = trk.TrackFormat({'ext': 'CSV', 'id_E':0, 'id_N':1, 'id_U':2, 'id_T':3, 'srid': \"Geo\", 'header': 1, 'separator': ','})\n",
    "trace = trk.TrackReader.readFromFile(trackpath, param, verbose=False)\n",
    "\n",
    "# Transform geographic coordinates in local projection\n",
    "trace.toENUCoordsIfNeeded()\n",
    "\n",
    "# Display a little summary of information of the GPS track:\n",
    "trace.summary()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1816722c",
   "metadata": {},
   "source": [
    "## Loading the road network\n",
    "\n",
    "Data network are stored in a csv file. The first line contained header with names of columns:  \n",
    "<div style='margin-left:4em'><i>WKT,link_id,source,target,direction</i></div>\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "261dcd7a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "nb edges= 288\n",
      "nb nodes= 216\n",
      "total length= 19386.544826479814\n"
     ]
    }
   ],
   "source": [
    "netpath = '../../../data/network/network-utgtrack-22245.csv'\n",
    "network = trk.NetworkReader.readFromFile(netpath, formatfile='VTT', verbose=False)\n",
    "\n",
    "# Transform geographic coordinates in local projection\n",
    "network.toENUCoords(trace.base)\n",
    "\n",
    "# Print number of edges and nodes of the network\n",
    "print ('nb edges=', len(network.EDGES))\n",
    "print ('nb nodes=', len(network.NODES))\n",
    "print ('total length=', network.totalLength())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "576c2b91",
   "metadata": {},
   "source": [
    "## Prepare and launch the map matching process"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "ecdceac9",
   "metadata": {},
   "outputs": [],
   "source": [
    "si = trk.SpatialIndex(network, verbose=False)\n",
    "network.spatial_index = si\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "b173ea65",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[38;2;255;52;0m  7%\u001b[39m \u001b[38;2;255;52;0m(17 of 216)\u001b[39m |#                      | Elapsed Time: 0:00:00 ETA:   0:00:00"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Map-matching preparation...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[38;2;0;255;0m100%\u001b[39m \u001b[38;2;0;255;0m(216 of 216)\u001b[39m |######################| Elapsed Time: 0:00:00 Time:  0:00:000:00\n"
     ]
    }
   ],
   "source": [
    "# computes all distances between pairs of nodes\n",
    "network.prepare()\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "dc22a720",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Map track on network\n",
    "trk.mapOnNetwork(trace, network, search_radius=25, debug=False)\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "068b8e7a",
   "metadata": {},
   "source": [
    "## Display results "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "3c91f16c",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": [
     "nbsphinx-thumbnail"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7dec99f49db0>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 720x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (10, 7))\n",
    "\n",
    "# emprise = trace.bbox()\n",
    "plt.xlim([-580, 20])\n",
    "plt.ylim([-20, 180])\n",
    "\n",
    "trace.plotAsMarkers(append=True, label='raw positions')\n",
    "network.plot('b-', '', '', '', 1.5, plt)\n",
    "si.plot(base=False, append=True)\n",
    "\n",
    "for k in range(len(trace)):\n",
    "    xmm = trace[\"hmm_inference\", k][0].getX()\n",
    "    ymm = trace[\"hmm_inference\", k][0].getY()\n",
    "    plt.plot(xmm, ymm, 'go', markersize=5, label='matched positions' if k == 0 else \"\")\n",
    "    X = [trace[k].position.getX(), xmm]\n",
    "    Y = [trace[k].position.getY(), ymm]\n",
    "    plt.plot(X, Y, \"r--\", linewidth=1.4, label='matching links' if k == 0 else \"\")\n",
    "    trace[k].position.setX(trace[\"hmm_inference\", k][0].getX())\n",
    "    trace[k].position.setY(trace[\"hmm_inference\", k][0].getY())\n",
    "\n",
    "plt.legend()"
   ]
  }
 ],
 "metadata": {
  "celltoolbar": "Tags",
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
