Description
Using the GPS trajectory as points=[(42.343981, -83.068282), (42.344557, -83.06855), (42.345158, -83.068826), (42.345739, -83.069091), (42.346302, -83.069342), (42.346882, -83.06961), (42.347475, -83.069879), (42.348061, -83.070143), (42.348634, -83.070406), (42.349217, -83.070679), (42.349808, -83.070997), (42.35039, -83.071336), (42.350993, -83.071686), (42.351586, -83.072038), (42.352192, -83.072393), (42.352813, -83.072754), (42.35344, -83.073121), (42.354081, -83.073484), (42.354718, -83.073834), (42.355347, -83.07416), (42.355961, -83.074406), (42.356566, -83.074608), (42.357158, -83.074775), (42.357734, -83.074922), (42.358335, -83.074962), (42.358951, -83.07485), (42.359548, -83.074571), (42.360128, -83.074126), (42.360585, -83.07362), (42.360991, -83.073111), (42.361731, -83.072093), (42.362051, -83.071603), (42.362373, -83.07109), (42.362699, -83.070568), (42.363038, -83.069994), (42.363382, -83.069346), (42.363716, -83.068678), (42.364031, -83.068009), (42.364324, -83.067383), (42.364612, -83.066773), (42.364906, -83.066133), (42.365196, -83.065498), (42.365482, -83.064841), (42.365752, -83.064162), (42.365985, -83.063562), (42.366205, -83.062984), (42.36638, -83.062431), (42.366498, -83.06189), (42.366559, -83.061304), (42.36657, -83.060721), (42.366535, -83.060186), (42.366487, -83.059704), (42.366442, -83.059258), (42.366413, -83.05882), (42.366457, -83.058362), (42.366611, -83.057939), (42.366845, -83.057612), (42.367143, -83.057395), (42.367517, -83.057308), (42.367924, -83.057414), (42.368374, -83.057617), (42.368884, -83.057858), (42.369424, -83.058138), (42.369975, -83.058455), (42.370521, -83.058753), (42.371084, -83.058982), (42.37172, -83.059162), (42.372423, -83.059326), (42.373146, -83.059485), (42.373877, -83.059694), (42.37461, -83.06005), (42.375353, -83.06052), (42.376113, -83.061019), (42.376876, -83.061525), (42.37761, -83.062009), (42.378308, -83.062475), (42.378983, -83.062909), (42.379634, -83.063329), (42.380269, -83.063755), (42.380912, -83.064185), (42.381564, -83.064626), (42.382227, -83.065073), (42.382888, -83.065521), (42.383551, -83.065964), (42.384226, -83.066415), (42.384914, -83.066879), (42.385623, -83.067359), (42.386344, -83.067846), (42.387071, -83.068332), (42.387795, -83.068802), (42.388511, -83.069236)]
But this time taking a map as (since I wish to check for several trajectories in this area) :
north = 42.534092
south = 42.118413
west = -83.343126
east = -82.727472
downloaded_g = graph.download.osm_download((north,south,west,east), network_type='drive')
G = graph.create_graph(downloaded_g)
start = datetime.datetime.now()
G_interp, candidates = candidate.get_candidates(G, points, interp_dist=5, closest=True, radius=10)
p1 = datetime.datetime.now()
trellis = mpmatching_utils.create_trellis(candidates)
path_prob, predecessor = mpmatching.viterbi_search(G_interp, trellis, "start", "target")
p2 = datetime.datetime.now()
l_ids, l_coords = mpmatching_utils.create_matched_path(G_interp, trellis, predecessor)
print('Got results : ',len(points),',',len(l_ids),',',len(l_coords),' times : ',int((p1-start).total_seconds()*1000),';',int((p2-p1).total_seconds()*1000))
The get_candidates never returns till some memory error inside this function, but it takes more than an hour to reach there.
Haven't analyzed the code so far, but it seems like there is no "smart" search for candidates, but passing over the whole graph edge by edge.
If you can please tell me what is wrong there.