{ "cells": [ { "cell_type": "markdown", "id": "89a764de-069f-47fa-8573-d0d5bdbe9ac8", "metadata": {}, "source": [ "# Pedestrian Graph \"Plan de la Limace\"" ] }, { "cell_type": "code", "execution_count": 1, "id": "e00a5055-cc58-4913-9c5b-bd193c23a669", "metadata": {}, "outputs": [], "source": [ "import os\n", "import sys\n", "\n", "import matplotlib.pyplot as plt\n", "\n", "# Ajout dans la variable PATH du système du chemin où est installée la librairie tracklib\n", "module_path = os.path.abspath(os.path.join('../../../../tracklib'))\n", "if module_path not in sys.path:\n", " sys.path.append(module_path)\n", "# Alias pour tracklib\n", "import tracklib as tkl\n", "\n", "# Ajout dans la variable PATH du système du chemin où est installée la librairie footprint2graph\n", "module_path = os.path.abspath(os.path.join('../../..'))\n", "if module_path not in sys.path:\n", " sys.path.append(module_path)" ] }, { "cell_type": "code", "execution_count": 2, "id": "2a1cbe41-a30f-473a-9424-a932031f099e", "metadata": {}, "outputs": [], "source": [ "import matplotlib.pyplot as plt\n", "import os\n", "import time\n", "\n", "from footprint2graph import run_iteration\n", "from footprint2graph import read_config\n", "\n", "from footprint2graph.util.Outdoorvision import load_raw_tracks_split" ] }, { "cell_type": "markdown", "id": "f13afc50-2669-4420-b4a8-caf02ca57a71", "metadata": {}, "source": [ "## Chargement des paramètres" ] }, { "cell_type": "code", "execution_count": 3, "id": "e096a92b-1f1b-4153-8868-b8a977385cc8", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!\n", "`````````````````````````````````````````````````````````````````````\n", " Generate a footprint graph \n", " from hiking trajectories \n", " in the Bauges, summer 2024. \n", "’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’\n", "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!\n", "\n", "Paramètres relevés dans la configuration: \n", "Résultats enregistrés dans le répertoire: /home/md_vandamme/4_RESEAU/ZTEMPZ1/\n", "Number of iterations: 2\n" ] } ], "source": [ "print ('!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!')\n", "print ('`````````````````````````````````````````````````````````````````````')\n", "print (' Generate a footprint graph ')\n", "print (' from hiking trajectories ')\n", "print (' in the Bauges, summer 2024. ')\n", "print ('’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’')\n", "print ('!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!')\n", "print ('')\n", "\n", "\n", "\"\"\" ======================================================================= \"\"\"\n", "\"\"\" Load parameters \"\"\"\n", "\"\"\" \"\"\"\n", "\n", "config_path = r'/home/md_vandamme/7_LIB/footprint2graph/data/config_bauges.yml'\n", "config = read_config(config_path)\n", "\n", "\n", "print('Paramètres relevés dans la configuration: ')\n", "print ('Résultats enregistrés dans le répertoire: ', config['output']['RESULT_PATH'])\n", "\n", "NBITER = int(config['graph_construction']['NUM_ITERATIONS'])\n", "print ('Number of iterations: ', NBITER)" ] }, { "cell_type": "markdown", "id": "cfe00ef6-46e6-4691-88c8-120352aebd76", "metadata": {}, "source": [ "## Chargement des données\n", "\n", "Les données proviennent de la plateforme Outdoorvision. Après avoir été formatées au format CSV, elles sont chargées dans une collection qui servira d'entrée au pipeline." ] }, { "cell_type": "code", "execution_count": 4, "id": "6336cbd9-8606-4fb8-b671-60d97b6d1358", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Loading and split outdoorvision track data...\n", "Reading track data...\n", " Number files to load: 4145\n", "Starting split ...\n", " 500 / 4145\n", " 1000 / 4145\n", " 1500 / 4145\n", " 2000 / 4145\n", " 2500 / 4145\n", " 3000 / 4145\n", " 3500 / 4145\n", " 4000 / 4145\n", " Number of tracks after split: 832\n" ] } ], "source": [ "\"\"\" ======================================================================= \"\"\"\n", "\"\"\" Chargement de la collection de traces \"\"\"\n", "\"\"\" \"\"\"\n", "\n", "# chemin où sont stockés les traces Outdoorvision:\n", "tracespathsource = r'/home/md_vandamme/5_GPS/OV/BAUGES/walk/'\n", "\n", "# Paramètre : Coordonnées de la zone d'étude sur laquelle on construit le réseau\n", "# Polygone sous la forme d'un tableau de X et de Y\n", "# traces de la zone 1 (3km x 3km)\n", "X = [950987, 951409, 950696, 949467, 947934, 948545, 950987]\n", "Y = [6513197, 6512091, 6511113, 6510719, 6511949, 6512621, 6513197]\n", "\n", "fmt = tkl.TrackFormat({'ext': 'CSV',\n", " 'srid': 'ENU',\n", " 'id_E': 1, 'id_N': 0, 'id_U': 3, 'id_T': 2,\n", " 'time_fmt': '2D/2M/4Y 2h:2m:2s',\n", " 'separator': ';',\n", " 'header': 0,\n", " 'cmt': '#',\n", " 'read_all': True})\n", "collection = load_raw_tracks_split(config['output']['RESULT_PATH'],\n", " tracespathsource, fmt, X, Y)" ] }, { "cell_type": "markdown", "id": "d9a08216-19d0-4939-a242-4ed79142a147", "metadata": {}, "source": [ "## Lancement du pipeline" ] }, { "cell_type": "code", "execution_count": 5, "id": "58254880-fa80-4fda-ac8e-d95b2b4515ef", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "-----------------------------------------------------------------\n", "-----------------------------------------------------------------\n", " ITERATION 1\n", "-----------------------------------------------------------------\n", "-----------------------------------------------------------------\n", "Starting segmentation and resampling...\n", "Starting segmentation ...\n", " 500 / 832\n", " Number of tracks after segmentation: 1171\n", "Finished saving segmented tracks.\n", "Starting resampling ...\n", " Number of tracks to resample: 1171\n", " Number of tracks after resampling: 1171\n", " Number of tracks after resampling: 1171\n", "Finished saving resampled tracks.\n", "Stage 1 finished: segmentation and resampling.\n", "Starting rasterization and vectorization (iteration 1) \n", "\n", " Loading tracks from : resample_grid\n", " Number of tracks to load: 1171\n", " Building high-resolution geometry density grid G1 : 2 m ...\n", " Building low-resolution contextual density grid G2 : 30 m ...\n", " Assigning track points to the G1 and G2 grids\n", " 500 / 1171\n", " 1000 / 1171\n", " Computing G1 ...\n", " Computing G2 ...\n", " Number of neighboring cells to consider: 7\n", " Building contrast grid : 2 m\n", " Execution time (seconds): 144.73467755317688\n", " Finished heatmap computation.\n", " Starting morphological closing image ...\n", " Execution time (seconds): 32.976491928100586\n", " Finished morphological opening.\n", "Vectorizing cleaned image ...\n", "Extracting road surface vector features ...\n", " Number of polygonize features: 51\n", " Number of polygonize features copied: 8\n", " Execution time (seconds): 0.1599118709564209\n", " Vectorization completed.\n", "Smoothing polygon to remove stair-step artifacts ...\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\u001b[38;2;0;255;0m100%\u001b[39m \u001b[38;2;0;255;0m(279 of 279)\u001b[39m |######################| Elapsed Time: 0:00:00 Time: 0:00:00\n", "\u001b[38;2;0;255;0m100%\u001b[39m \u001b[38;2;0;255;0m(279 of 279)\u001b[39m |######################| Elapsed Time: 0:00:00 Time: 0:00:00\n", "\u001b[38;2;0;255;0m100%\u001b[39m \u001b[38;2;0;255;0m(406 of 406)\u001b[39m |######################| Elapsed Time: 0:00:00 Time: 0:00:00\n", "\u001b[38;2;0;255;0m100%\u001b[39m \u001b[38;2;0;255;0m(358 of 358)\u001b[39m |######################| Elapsed Time: 0:00:00 Time: 0:00:00\n", "\u001b[38;2;0;255;0m100%\u001b[39m \u001b[38;2;0;255;0m(211 of 211)\u001b[39m |######################| Elapsed Time: 0:00:00 Time: 0:00:00\n", "\u001b[38;2;0;255;0m100%\u001b[39m \u001b[38;2;0;255;0m(1204 of 1204)\u001b[39m |####################| Elapsed Time: 0:00:00 Time: 0:00:00\n", "\u001b[38;2;255;0;0m 0%\u001b[39m \u001b[38;2;255;0;0m(0 of 3195)\u001b[39m | | Elapsed Time: 0:00:00 ETA: --:--:--" ] }, { "name": "stdout", "output_type": "stream", "text": [ " Execution time (seconds): 1.43650484085083\n", " Road surface smoothing completed.\n", " Starting centerline computation ...\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\u001b[38;2;0;255;0m100%\u001b[39m \u001b[38;2;0;255;0m(3195 of 3195)\u001b[39m |####################| Elapsed Time: 0:00:00 Time: 0:00:00\n", "\u001b[38;2;0;255;0m100%\u001b[39m \u001b[38;2;0;255;0m(3191 of 3191)\u001b[39m |####################| Elapsed Time: 0:00:00 Time: 0:00:00\n", "\u001b[38;2;0;255;0m100%\u001b[39m \u001b[38;2;0;255;0m(21702 of 21702)\u001b[39m |##################| Elapsed Time: 0:00:00 Time: 0:00:000000\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ " Execution time (seconds): 3.4315288066864014\n", " Centerline computed.\n", "Stage 2 completed: rasterization and vectorization.\n", "Starting topology creation for the network\n", " Number of edges in the skeleton: 5058\n", " Finished loaded skeleton.\n", " /home/md_vandamme/4_RESEAU/ZTEMPZ1/network/tmp_in.csv not exists\n", " /home/md_vandamme/4_RESEAU/ZTEMPZ1/network/tmp_out.csv not exists\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\u001b[38;2;255;145;0m 32%\u001b[39m \u001b[38;2;255;145;0m(33 of 102)\u001b[39m |####### | Elapsed Time: 0:00:00 ETA: 0:00:00" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\n", " Finished removing hooked parts of the skeleton.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\u001b[38;2;0;255;0m100%\u001b[39m \u001b[38;2;0;255;0m(102 of 102)\u001b[39m |######################| Elapsed Time: 0:00:01 Time: 0:00:010000\n", "\u001b[38;2;0;255;0m100%\u001b[39m \u001b[38;2;0;255;0m(102 of 102)\u001b[39m |######################| Elapsed Time: 0:00:00 Time: 0:00:00\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ " Finished simplification of the skeleton.\n", "Building [100 x 75] spatial index...\n", " on coupe la trace 2\n", " on coupe la trace 1\n", " on coupe la trace 1\n", " Number of edges in the skeleton (after snapping): 105\n", " Edge count difference after snapping : 3\n", " Number of edges in the simplified skeleton: 66\n", " Number of nodes: 72\n", " Shortest edges limit : 50\n", " Number of edges in the skeleton (after removing the shortest edges): 0\n", " Conflation cannot be performed for node 59 ; the three incident edges are too long: 211 368 210\n", " Conflation cannot be performed for node 60 ; the three incident edges are too long: 211 210 1188\n", " Conflation cannot be performed for node 76 ; the three incident edges are too long: 9 207 448\n", " Conflation cannot be performed for node 77 ; the three incident edges are too long: 9 109 1188\n", " Conflation cannot be performed for node 93 ; the three incident edges are too long: 48 341 511\n", " Conflation cannot be performed for node 98 ; the three incident edges are too long: 759 341 511\n", " Conflation cannot be performed for node 107 ; the three incident edges are too long: 48 3928 1490\n", " Conflation cannot be performed for node 103 ; the three incident edges are too long: 448 153 617\n", " Conflation cannot be performed for node 50 ; the three incident edges are too long: 759 418 368\n", " Conflation cannot be performed for node 82 ; the three incident edges are too long: 153 217 3928\n", " Edge count after conflation: 26\n", "Stage 3 completed: adding topology to the skeleton.\n", "Starting map-matching, aggregation, and conflation of GNSS trajectories.\n", " Loading network (1) ...\n", " Number of edges = 26\n", " Number of nodes = 32\n", " Total segment length of the network = 13265.887004361779\n", " Loading collection of tracks ...\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\u001b[38;2;0;255;0m100%\u001b[39m \u001b[38;2;0;255;0m(32 of 32)\u001b[39m |########################| Elapsed Time: 0:00:00 Time: 0:00:00\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ " Number of tracks: 1171\n", " Execution time (seconds): 7.991522789001465\n", " Starting map-matching ...\n", " Index spatial : [100 x 75] spatial index centered on [949571.1447794335; 6511919.456318483]\n", "Map-matching preparation...\n", " Parameter search_radius: 25\n", " Map-matching ended.\n", " Execution time (seconds): 1687.354591369629\n", " Prepare map-matching results for candidate segment generation\n", " Number of map-matched points = 812751 (96.5 %)\n", " Map-matching results restructuring completed.\n", " Map-matching results exported.\n", "Starting construction of candidate trajectory segments for each topology edge ...\n", " 221 candidates for edge 119\n", " 84 candidates for edge 35\n", " 111 candidates for edge 148\n", " 78 candidates for edge 156\n", " 218 candidates for edge 47\n", " 54 candidates for edge 67\n", " 7 candidates for edge 54\n", " 65 candidates for edge 75\n", " 276 candidates for edge 130\n", " 119 candidates for edge 140\n", " 102 candidates for edge 154\n", " 205 candidates for edge 161\n", " 213 candidates for edge 98\n", " 459 candidates for edge 141\n", " 32 candidates for edge 146\n", " 257 candidates for edge 163\n", " 825 candidates for edge 90\n", " 14 candidates for edge 118\n", " 40 candidates for edge 144\n", " 40 candidates for edge 16\n", " 81 candidates for edge 116\n", " 14 candidates for edge 9\n", " 73 candidates for edge 147\n", " 32 candidates for edge 77\n", " 36 candidates for edge 13\n", " 9 candidates for edge 112\n", " Number of processed edges: 26\n", " Minimum number of candidate tracks per edge: 7\n", " Maximum number of candidate traces per edge: 825\n", " Average number of candidate tracks per edge: 141\n", " Segment construction completed.\n", " Execution time (seconds): 41.64723253250122\n", " Starting track segment aggregation for all network edges ...\n", " Number of candidate tracks / number of sampled tracks 221 / 30\n", " Number of candidate tracks / number of sampled tracks 84 / 30\n", " Number of candidate tracks / number of sampled tracks 111 / 30\n", " Number of candidate tracks / number of sampled tracks 78 / 30\n", " Number of candidate tracks / number of sampled tracks 54 / 30\n", " Number of candidate tracks / number of sampled tracks 7 / 7\n", " Number of candidate tracks / number of sampled tracks 65 / 30\n", " Number of candidate tracks / number of sampled tracks 276 / 30\n", " Number of candidate tracks / number of sampled tracks 119 / 30\n", " Number of candidate tracks / number of sampled tracks 102 / 30\n", " Number of candidate tracks / number of sampled tracks 205 / 30\n", "WARNING: TRAJECTORY FUSION HAS NOT CONVERGED (#ITER = 25 - CV = 0.0068389902972801455)\n", " Number of candidate tracks / number of sampled tracks 213 / 30\n", " Number of candidate tracks / number of sampled tracks 459 / 30\n", " Number of candidate tracks / number of sampled tracks 32 / 30\n", " Number of candidate tracks / number of sampled tracks 257 / 30\n", " Number of candidate tracks / number of sampled tracks 825 / 30\n", " Number of candidate tracks / number of sampled tracks 14 / 14\n", " Number of candidate tracks / number of sampled tracks 40 / 30\n", " Number of candidate tracks / number of sampled tracks 40 / 30\n", " Number of candidate tracks / number of sampled tracks 81 / 30\n", " Number of candidate tracks / number of sampled tracks 14 / 14\n", " Number of candidate tracks / number of sampled tracks 73 / 30\n", " Number of candidate tracks / number of sampled tracks 32 / 30\n", " Number of candidate tracks / number of sampled tracks 36 / 30\n", " Number of candidate tracks / number of sampled tracks 9 / 9\n", " Number of aggregations: 26\n", " Number of aggregations with 30 traces: 21\n", " Number of aggregations with fewer than 30 traces: 4\n", " Minimum number of traces in aggregation: 7\n", " Average number of traces in aggregation: 133\n", " Aggregation process finished.\n", " Execution time (seconds): 44.12959551811218\n", " Starting conflation ...\n", " Conflation process finished.\n", " Execution time (seconds): 0.05499768257141113\n", "Stage 4 completed: map-matching, aggregation, and conflation.\n", "-----------------------------------------------------------------\n", "-----------------------------------------------------------------\n", " ITERATION 2\n", "-----------------------------------------------------------------\n", "-----------------------------------------------------------------\n", "Number of tracks map matched : 1171\n", "1605\n", "Starting rasterization and vectorization (iteration 2) \n", "\n", " Loading tracks from : points_not_mm_2\n", " Number of tracks to load: 1605\n", " Building high-resolution geometry density grid G1 : 2 m ...\n", " Building low-resolution contextual density grid G2 : 30 m ...\n", " Assigning track points to the G1 and G2 grids\n", " 500 / 1605\n", " 1000 / 1605\n", " 1500 / 1605\n", " Computing G1 ...\n", " Computing G2 ...\n", " Number of neighboring cells to consider: 7\n", " Building contrast grid : 2 m\n", " Execution time (seconds): 54.55560350418091\n", " Finished heatmap computation.\n", " Starting morphological closing image ...\n", " Execution time (seconds): 33.21741557121277\n", " Finished morphological opening.\n", "Vectorizing cleaned image ...\n", "Extracting road surface vector features ...\n", " Number of polygonize features: 60\n", " Number of polygonize features copied: 25\n", " Execution time (seconds): 0.12494230270385742\n", " Vectorization completed.\n", "Smoothing polygon to remove stair-step artifacts ...\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\u001b[38;2;0;255;0m100%\u001b[39m \u001b[38;2;0;255;0m(297 of 297)\u001b[39m |######################| Elapsed Time: 0:00:00 Time: 0:00:00\n", "\u001b[38;2;0;255;0m100%\u001b[39m \u001b[38;2;0;255;0m(447 of 447)\u001b[39m |######################| Elapsed Time: 0:00:00 Time: 0:00:00\n", "\u001b[38;2;0;255;0m100%\u001b[39m \u001b[38;2;0;255;0m(253 of 253)\u001b[39m |######################| Elapsed Time: 0:00:00 Time: 0:00:00\n", "\u001b[38;2;0;255;0m100%\u001b[39m \u001b[38;2;0;255;0m(130 of 130)\u001b[39m |######################| Elapsed Time: 0:00:00 Time: 0:00:00\n", "\u001b[38;2;0;255;0m100%\u001b[39m \u001b[38;2;0;255;0m(486 of 486)\u001b[39m |######################| Elapsed Time: 0:00:00 Time: 0:00:00\n", "\u001b[38;2;0;255;0m100%\u001b[39m \u001b[38;2;0;255;0m(162 of 162)\u001b[39m |######################| Elapsed Time: 0:00:00 Time: 0:00:00\n", "\u001b[38;2;0;255;0m100%\u001b[39m \u001b[38;2;0;255;0m(321 of 321)\u001b[39m |######################| Elapsed Time: 0:00:00 Time: 0:00:00\n", "\u001b[38;2;0;255;0m100%\u001b[39m \u001b[38;2;0;255;0m(152 of 152)\u001b[39m |######################| Elapsed Time: 0:00:00 Time: 0:00:00\n", "\u001b[38;2;0;255;0m100%\u001b[39m \u001b[38;2;0;255;0m(198 of 198)\u001b[39m |######################| Elapsed Time: 0:00:00 Time: 0:00:00\n", "\u001b[38;2;255;0;0m 0%\u001b[39m \u001b[38;2;255;0;0m(0 of 215)\u001b[39m | | Elapsed Time: 0:00:00 ETA: --:--:--" ] }, { "name": "stdout", "output_type": "stream", "text": [ " Execution time (seconds): 0.36910533905029297\n", " Road surface smoothing completed.\n", " Starting centerline computation ...\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\u001b[38;2;0;255;0m100%\u001b[39m \u001b[38;2;0;255;0m(215 of 215)\u001b[39m |######################| Elapsed Time: 0:00:00 Time: 0:00:00\n", "\u001b[38;2;0;255;0m100%\u001b[39m \u001b[38;2;0;255;0m(161 of 161)\u001b[39m |######################| Elapsed Time: 0:00:00 Time: 0:00:00\n", "\u001b[38;2;0;255;0m100%\u001b[39m \u001b[38;2;0;255;0m(137 of 137)\u001b[39m |######################| Elapsed Time: 0:00:00 Time: 0:00:00\n", "\u001b[38;2;0;255;0m100%\u001b[39m \u001b[38;2;0;255;0m(220 of 220)\u001b[39m |######################| Elapsed Time: 0:00:00 Time: 0:00:00\n", "\u001b[38;2;0;255;0m100%\u001b[39m \u001b[38;2;0;255;0m(193 of 193)\u001b[39m |######################| Elapsed Time: 0:00:00 Time: 0:00:00\n", "\u001b[38;2;0;255;0m100%\u001b[39m \u001b[38;2;0;255;0m(234 of 234)\u001b[39m |######################| Elapsed Time: 0:00:00 Time: 0:00:00\n", "\u001b[38;2;0;255;0m100%\u001b[39m \u001b[38;2;0;255;0m(153 of 153)\u001b[39m |######################| Elapsed Time: 0:00:00 Time: 0:00:00\n", "\u001b[38;2;0;255;0m100%\u001b[39m \u001b[38;2;0;255;0m(148 of 148)\u001b[39m |######################| Elapsed Time: 0:00:00 Time: 0:00:00\n", "\u001b[38;2;0;255;0m100%\u001b[39m \u001b[38;2;0;255;0m(202 of 202)\u001b[39m |######################| Elapsed Time: 0:00:00 Time: 0:00:00\n", "\u001b[38;2;0;255;0m100%\u001b[39m \u001b[38;2;0;255;0m(175 of 175)\u001b[39m |######################| Elapsed Time: 0:00:00 Time: 0:00:00\n", "\u001b[38;2;0;255;0m100%\u001b[39m \u001b[38;2;0;255;0m(121 of 121)\u001b[39m |######################| Elapsed Time: 0:00:00 Time: 0:00:00\n", "\u001b[38;2;0;255;0m100%\u001b[39m \u001b[38;2;0;255;0m(141 of 141)\u001b[39m |######################| Elapsed Time: 0:00:00 Time: 0:00:00\n", "\u001b[38;2;0;255;0m100%\u001b[39m \u001b[38;2;0;255;0m(188 of 188)\u001b[39m |######################| Elapsed Time: 0:00:00 Time: 0:00:00\n", "\u001b[38;2;0;255;0m100%\u001b[39m \u001b[38;2;0;255;0m(145 of 145)\u001b[39m |######################| Elapsed Time: 0:00:00 Time: 0:00:00\n", "\u001b[38;2;0;255;0m100%\u001b[39m \u001b[38;2;0;255;0m(238 of 238)\u001b[39m |######################| Elapsed Time: 0:00:00 Time: 0:00:00\n", "\u001b[38;2;0;255;0m100%\u001b[39m \u001b[38;2;0;255;0m(3193 of 3193)\u001b[39m |####################| Elapsed Time: 0:00:00 Time: 0:00:00\n", "\u001b[38;2;0;255;0m100%\u001b[39m \u001b[38;2;0;255;0m(3189 of 3189)\u001b[39m |####################| Elapsed Time: 0:00:00 Time: 0:00:00\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ " Execution time (seconds): 0.8457791805267334\n", " Centerline computed.\n", "Stage 2 completed: rasterization and vectorization.\n", "Starting topology creation for the network\n", " Number of edges in the skeleton: 921\n", " Finished loaded skeleton.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\u001b[38;2;223;255;0m 68%\u001b[39m \u001b[38;2;223;255;0m(41 of 60)\u001b[39m |################ | Elapsed Time: 0:00:00 ETA: 0:00:00" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\n", " Finished removing hooked parts of the skeleton.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\u001b[38;2;0;255;0m100%\u001b[39m \u001b[38;2;0;255;0m(60 of 60)\u001b[39m |########################| Elapsed Time: 0:00:00 Time: 0:00:000:00\n", "\u001b[38;2;0;255;0m100%\u001b[39m \u001b[38;2;0;255;0m(60 of 60)\u001b[39m |########################| Elapsed Time: 0:00:00 Time: 0:00:00\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ " Finished simplification of the skeleton.\n", "Building [100 x 82] spatial index...\n", " Number of edges in the skeleton (after snapping): 60\n", " Edge count difference after snapping : 0\n", " Number of edges in the simplified skeleton: 55\n", " Number of nodes: 79\n", " Shortest edges limit : 50\n", " Number of edges in the skeleton (after removing the shortest edges): 1\n", " Conflation cannot be performed for node 19 ; the three incident edges are too long: 19 52 31\n", " Edge count after conflation: 28\n", "Stage 3 completed: adding topology to the skeleton.\n", "Starting map-matching, aggregation, and conflation of GNSS trajectories.\n", " Loading network (2) ...\n", " Number of edges = 28\n", " Number of nodes = 51\n", " Total segment length of the network = 2359.038212864578\n", " Loading collection of tracks ...\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\u001b[38;2;0;255;0m100%\u001b[39m \u001b[38;2;0;255;0m(51 of 51)\u001b[39m |########################| Elapsed Time: 0:00:00 Time: 0:00:00\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ " Number of tracks: 1605\n", " Execution time (seconds): 3.1663522720336914\n", " Starting map-matching ...\n", " Index spatial : [100 x 82] spatial index centered on [950195.6342437908; 6511752.969261601]\n", "Map-matching preparation...\n", " Parameter search_radius: 25\n", " Map-matching ended.\n", " Execution time (seconds): 23.73816752433777\n", " Prepare map-matching results for candidate segment generation\n", " Number of map-matched points = 103337 (46.87 %)\n", " Map-matching results restructuring completed.\n", " Map-matching results exported.\n", "Starting construction of candidate trajectory segments for each topology edge ...\n", " 6 candidates for edge 70\n", " 15 candidates for edge 63\n", " 3 candidates for edge 68\n", " 9 candidates for edge 62\n", " 46 candidates for edge 60\n", " 6 candidates for edge 35\n", " 6 candidates for edge 71\n", " 10 candidates for edge 66\n", " 11 candidates for edge 74\n", " 6 candidates for edge 64\n", " 19 candidates for edge 44\n", " 15 candidates for edge 27\n", " 2 candidates for edge 73\n", " 3 candidates for edge 30\n", " 5 candidates for edge 76\n", " 7 candidates for edge 75\n", " 6 candidates for edge 45\n", " 4 candidates for edge 69\n", " 24 candidates for edge 0\n", " 27 candidates for edge 1\n", " 11 candidates for edge 15\n", " 3 candidates for edge 77\n", " 0 candidates for edge 72\n", " 7 candidates for edge 67\n", " 9 candidates for edge 59\n", " 3 candidates for edge 55\n", " 9 candidates for edge 46\n", " 4 candidates for edge 8\n", " Number of processed edges: 28\n", " Minimum number of candidate tracks per edge: 0\n", " Maximum number of candidate traces per edge: 46\n", " Average number of candidate tracks per edge: 10\n", " Segment construction completed.\n", " Execution time (seconds): 7.026676893234253\n", " Starting track segment aggregation for all network edges ...\n", " Number of candidate tracks / number of sampled tracks 6 / 6\n", " Number of candidate tracks / number of sampled tracks 15 / 15\n", " Number of candidate tracks / number of sampled tracks 3 / 3\n", " Number of candidate tracks / number of sampled tracks 9 / 9\n", " Number of candidate tracks / number of sampled tracks 46 / 30\n", " Number of candidate tracks / number of sampled tracks 6 / 6\n", " Number of candidate tracks / number of sampled tracks 6 / 6\n", " Number of candidate tracks / number of sampled tracks 10 / 10\n", " Number of candidate tracks / number of sampled tracks 11 / 11\n", " Number of candidate tracks / number of sampled tracks 6 / 6\n", " Number of candidate tracks / number of sampled tracks 19 / 19\n", " Number of candidate tracks / number of sampled tracks 15 / 15\n", " Number of candidate tracks / number of sampled tracks 2 / 2\n", " Number of candidate tracks / number of sampled tracks 3 / 3\n", " Number of candidate tracks / number of sampled tracks 5 / 5\n", " Number of candidate tracks / number of sampled tracks 7 / 7\n", " Number of candidate tracks / number of sampled tracks 6 / 6\n", " Number of candidate tracks / number of sampled tracks 4 / 4\n", " Number of candidate tracks / number of sampled tracks 11 / 11\n", " Number of candidate tracks / number of sampled tracks 3 / 3\n", " Number of candidate tracks / number of sampled tracks 7 / 7\n", " Number of candidate tracks / number of sampled tracks 9 / 9\n", " Number of candidate tracks / number of sampled tracks 3 / 3\n", " Number of candidate tracks / number of sampled tracks 9 / 9\n", " Number of candidate tracks / number of sampled tracks 4 / 4\n", " Number of aggregations: 27\n", " Number of aggregations with 30 traces: 1\n", " Number of aggregations with fewer than 30 traces: 24\n", " Minimum number of traces in aggregation: 2\n", " Average number of traces in aggregation: 8\n", " Aggregation process finished.\n", " Execution time (seconds): 1.2899436950683594\n", " Starting conflation ...\n", " Conflation process finished.\n", " Execution time (seconds): 0.017225027084350586\n", "Stage 4 completed: map-matching, aggregation, and conflation.\n", "1315.3142746399594\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\u001b[38;2;0;255;0m100%\u001b[39m \u001b[38;2;0;255;0m(53 of 53)\u001b[39m |########################| Elapsed Time: 0:00:00 Time: 0:00:00\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Size of collection In : 26\n", "Size of collection In+1: 27\n", "Size of collection In+In+1: 53\n", "Building [100 x 74] spatial index...\n", "Size of collection In+In+1 avec intersection: 55\n", "Size of collection In+In+1 avec intersection et raccordement: 82\n", "Size of reseau de mobilité: 82\n", "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!\n", "`````````````````````````````````````````````````````````````````````\n", " FIN \n", "’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’\n", "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!\n" ] } ], "source": [ "for idx in range(0, NBITER):\n", " iteration_index = int(idx) + 1\n", "\n", " # run pipeline for the ith iteration\n", " run_iteration(iteration_index, config, collection)\n", "\n", "print ('!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!')\n", "print ('`````````````````````````````````````````````````````````````````````')\n", "print (' FIN ')\n", "print ('’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’')\n", "print ('!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!')" ] }, { "cell_type": "markdown", "id": "0acc46d1-e0a7-40ab-9351-74b78ea668b1", "metadata": {}, "source": [ "## On affiche le résultat" ] }, { "cell_type": "code", "execution_count": 6, "id": "c328be5a-88db-4209-a545-23a24197bcc6", "metadata": {}, "outputs": [ { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "from footprint2graph.util.PlotRes import plotResultatFinal\n", "\n", "plotResultatFinal(config['output']['RESULT_PATH'])" ] } ], "metadata": { "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 }