def example1(): map_con = InMemMap("mymap", graph={ "A": ((1, 1), ["B", "C", "X"]), "B": ((1, 3), ["A", "C", "D", "K"]), "C": ((2, 2), ["A", "B", "D", "E", "X", "Y"]), "D": ((2, 4), ["B", "C", "F", "E", "K", "L"]), "E": ((3, 3), ["C", "D", "F", "Y"]), "F": ((3, 5), ["D", "E", "L"]), "X": ((2, 0), ["A", "C", "Y"]), "Y": ((3, 1), ["X", "C", "E"]), "K": ((1, 5), ["B", "D", "L"]), "L": ((2, 6), ["K", "D", "F"]) }, use_latlon=False) path = [(0.8, 0.7), (0.9, 0.7), (1.1, 1.0), (1.2, 1.5), (1.2, 1.6), (1.1, 2.0), (1.1, 2.3), (1.3, 2.9), (1.2, 3.1), (1.5, 3.2), (1.8, 3.5), (2.0, 3.7), (2.3, 3.5), (2.4, 3.2), (2.6, 3.1), (2.9, 3.1), (3.0, 3.2), (3.1, 3.8), (3.0, 4.0), (3.1, 4.3), (3.1, 4.6), (3.0, 4.9)] matcher = DistanceMatcher(map_con, max_dist=2, obs_noise=1, min_prob_norm=0.5) states, _ = matcher.match(path) nodes = matcher.path_pred_onlynodes print("States\n------") print(states) print("Nodes\n------") print(nodes) print("") matcher.print_lattice_stats()
def test_path2_dist(): mapdb, path1, path2, path_sol = setup_map() matcher = DistanceMatcher(mapdb, max_dist_init=1, min_prob_norm=0.5, obs_noise=0.5, dist_noise=0.5, non_emitting_states=True) matcher.match(path2, unique=True) path_pred = matcher.path_pred_onlynodes if directory: from leuvenmapmatching import visualization as mmviz matcher.print_lattice_stats() matcher.print_lattice() # with (directory / 'lattice_path2.gv').open('w') as ofile: # matcher.lattice_dot(file=ofile) mmviz.plot_map(mapdb, matcher=matcher, show_labels=True, show_matching=True, filename=str(directory / "test_nonemitting_test_path2_dist.png")) assert path_pred == path_sol, "Nodes not equal:\n{}\n{}".format( path_pred, path_sol)
def test_bug2(): this_path = Path(os.path.realpath(__file__)).parent / "rsrc" / "bug2" edges_fn = this_path / "edgesrl.csv" nodes_fn = this_path / "nodesrl.csv" path_fn = this_path / "path.csv" logger.debug(f"Reading map ...") mmap = SqliteMap("road_network", use_latlon=True, dir=this_path) path = [] with path_fn.open("r") as path_f: reader = csv.reader(path_f, delimiter=',') for row in reader: lat, lon = [float(coord) for coord in row] path.append((lat, lon)) node_cnt = 0 with nodes_fn.open("r") as nodes_f: reader = csv.reader(nodes_f, delimiter=',') for row in reader: nid, lonlat, _ = row nid = int(nid) lon, lat = [float(coord) for coord in lonlat[1:-1].split(",")] mmap.add_node(nid, (lat, lon), ignore_doubles=True, no_index=True, no_commit=True) node_cnt += 1 edge_cnt = 0 with edges_fn.open("r") as edges_f: reader = csv.reader(edges_f, delimiter=',') for row in reader: _eid, nid1, nid2, pid = [int(val) for val in row] mmap.add_edge(nid1, nid2, edge_type=0, path=pid, no_index=True, no_commit=True) edge_cnt += 1 logger.debug(f"... done: {node_cnt} nodes and {edge_cnt} edges") logger.debug("Indexing ...") mmap.reindex_nodes() mmap.reindex_edges() logger.debug("... done") matcher = DistanceMatcher(mmap, min_prob_norm=0.001, max_dist=200, obs_noise=4.07, non_emitting_states=True) # path = path[:2] nodes, idx = matcher.match(path, unique=True) path_pred = matcher.path_pred if directory: import matplotlib.pyplot as plt matcher.print_lattice_stats() logger.debug("Plotting post map ...") fig = plt.figure(figsize=(100, 100)) ax = fig.get_axes() mm_viz.plot_map(mmap, matcher=matcher, use_osm=True, ax=ax, show_lattice=False, show_labels=True, show_graph=False, zoom_path=True, show_matching=True) plt.savefig(str(directory / "test_bug1.png")) plt.close(fig) logger.debug("... done")
def test_path2_proj(): prepare_files() map_con_latlon = create_map_from_xml(osm2_fn) map_con = map_con_latlon.to_xy() track = [map_con.latlon2yx(p[0], p[1]) for p in gpx_to_path(track2_fn)] matcher = DistanceMatcher(map_con, max_dist=300, max_dist_init=25, min_prob_norm=0.0001, non_emitting_length_factor=0.95, obs_noise=50, obs_noise_ne=50, dist_noise=50, max_lattice_width=5, non_emitting_states=True) states, last_idx = matcher.match(track, unique=False) nodes = matcher.path_pred_onlynodes if directory: matcher.print_lattice_stats() mm_viz.plot_map(map_con, matcher=matcher, path=track, use_osm=False, show_graph=True, show_matching=True, show_labels=5, filename=str(directory / "test_path_latlon_path2_proj.png")) nodes_sol = [ 2634474831, 1096512242, 3051083902, 1096512239, 1096512241, 1096512240, 1096508366, 1096508372, 16483861, 1096508360, 159656075, 1096508382, 16483862, 3051083898, 16526535, 3060597381, 3060515059, 16526534, 16526532, 1274158119, 16526540, 3060597377, 16526541, 16424220, 1233373340, 613125597, 1076057753 ] nodes_sol2 = [ 1096512242, 3051083902, 1096512239, 1096512241, 1096512240, 159654664, 1096508373, 1096508381, 16483859, 1096508369, 159654663, 1096508363, 16483862, 3051083898, 16526535, 3060597381, 3060515059, 16526534, 16526532, 611867918, 3060725817, 16483866, 3060725817, 611867918, 16526532, 1274158119, 16526540, 3060597377, 16526541, 16424220, 1233373340, 613125597, 1076057753 ] assert (nodes == nodes_sol) or (nodes == nodes_sol2), f"Nodes do not match: {nodes}"
def test_bug1(): map_con = SqliteMap("map", use_latlon=True) map_con.add_nodes([(1, (47.590439915657, -122.238368690014)), (2, (47.5910192728043, -122.239519357681)), (3, (47.5913706421852, -122.240168452263))]) map_con.add_edges([(1, 2), (2, 3)]) path = [ # (47.59043333, -122.2384167), (47.59058333, -122.2387), (47.59071667, -122.2389833), (47.59086667, -122.2392667), (47.59101667, -122.23955), (47.59115, -122.2398333) ] path_sol = [(1, 2), (2, 3)] matcher = DistanceMatcher(map_con, min_prob_norm=0.001, max_dist=200, obs_noise=4.07, non_emitting_states=True) matcher.match(path, unique=True) path_pred = matcher.path_pred if directory: import matplotlib.pyplot as plt matcher.print_lattice_stats() logger.debug("Plotting post map ...") fig = plt.figure(figsize=(100, 100)) ax = fig.get_axes() mm_viz.plot_map(map_con, matcher=matcher, use_osm=True, ax=ax, show_lattice=False, show_labels=True, show_graph=True, zoom_path=True, show_matching=True) plt.savefig(str(directory / "test_newson_bug1.png")) plt.close(fig) logger.debug("... done") assert path_pred == path_sol, f"Edges not equal:\n{path_pred}\n{path_sol}"
def example2(): path = [(1, 0), (7.5, 0.65), (10.1, 1.9)] mapdb = InMemMap("mymap", graph={ "A": ((1, 0.00), ["B"]), "B": ((3, 0.00), ["A", "C"]), "C": ((4, 0.70), ["B", "D"]), "D": ((5, 1.00), ["C", "E"]), "E": ((6, 1.00), ["D", "F"]), "F": ((7, 0.70), ["E", "G"]), "G": ((8, 0.00), ["F", "H"]), "H": ((10, 0.0), ["G", "I"]), "I": ((10, 2.0), ["H"]) }, use_latlon=False) matcher = DistanceMatcher(mapdb, max_dist_init=0.2, obs_noise=1, obs_noise_ne=10, non_emitting_states=True, only_edges=True) states, _ = matcher.match(path) nodes = matcher.path_pred_onlynodes print("States\n------") print(states) print("Nodes\n------") print(nodes) print("") matcher.print_lattice_stats() mmviz.plot_map(mapdb, matcher=matcher, show_labels=True, show_matching=True, filename="output.png")
def test_bug2(): this_path = Path(os.path.realpath(__file__)).parent / "rsrc" / "bug2" edges_fn = this_path / "edgesrl.csv" nodes_fn = this_path / "nodesrl.csv" path_fn = this_path / "path.csv" zip_fn = this_path / "leuvenmapmatching_testdata.zip" if not (edges_fn.exists() and nodes_fn.exists() and path_fn.exists()): import requests url = 'https://people.cs.kuleuven.be/wannes.meert/leuvenmapmatching/leuvenmapmatching_testdata.zip' logger.debug("Download testfiles from kuleuven.be") r = requests.get(url, stream=True) with zip_fn.open('wb') as ofile: for chunk in r.iter_content(chunk_size=1024): if chunk: ofile.write(chunk) import zipfile logger.debug("Unzipping leuvenmapmatching_testdata.zip") with zipfile.ZipFile(str(zip_fn), "r") as zip_ref: zip_ref.extractall(str(zip_fn.parent)) logger.debug(f"Reading map ...") mmap = SqliteMap("road_network", use_latlon=True, dir=this_path) path = [] with path_fn.open("r") as path_f: reader = csv.reader(path_f, delimiter=',') for row in reader: lat, lon = [float(coord) for coord in row] path.append((lat, lon)) node_cnt = 0 with nodes_fn.open("r") as nodes_f: reader = csv.reader(nodes_f, delimiter=',') for row in reader: nid, lonlat, _ = row nid = int(nid) lon, lat = [float(coord) for coord in lonlat[1:-1].split(",")] mmap.add_node(nid, (lat, lon), ignore_doubles=True, no_index=True, no_commit=True) node_cnt += 1 edge_cnt = 0 with edges_fn.open("r") as edges_f: reader = csv.reader(edges_f, delimiter=',') for row in reader: _eid, nid1, nid2, pid = [int(val) for val in row] mmap.add_edge(nid1, nid2, edge_type=0, path=pid, no_index=True, no_commit=True) edge_cnt += 1 logger.debug(f"... done: {node_cnt} nodes and {edge_cnt} edges") logger.debug("Indexing ...") mmap.reindex_nodes() mmap.reindex_edges() logger.debug("... done") matcher = DistanceMatcher(mmap, min_prob_norm=0.001, max_dist=200, obs_noise=4.07, non_emitting_states=True) # path = path[:2] nodes, idx = matcher.match(path, unique=True) path_pred = matcher.path_pred if directory: import matplotlib.pyplot as plt matcher.print_lattice_stats() logger.debug("Plotting post map ...") fig = plt.figure(figsize=(100, 100)) ax = fig.get_axes() mm_viz.plot_map(mmap, matcher=matcher, use_osm=True, ax=ax, show_lattice=False, show_labels=True, show_graph=False, zoom_path=True, show_matching=True) plt.savefig(str(directory / "test_bug1.png")) plt.close(fig) logger.debug("... done")
from leuvenmapmatching.matcher.distance import DistanceMatcher from leuvenmapmatching.map.inmem import InMemMap from leuvenmapmatching import visualization as mmviz path = [(1, 0), (7.5, 0.65), (10.1, 1.9)] mapdb = InMemMap("mymap", graph={ "A": ((1, 0.00), ["B"]), "B": ((3, 0.00), ["A", "C"]), "C": ((4, 0.70), ["B", "D"]), "D": ((5, 1.00), ["C", "E"]), "E": ((6, 1.00), ["D", "F"]), "F": ((7, 0.70), ["E", "G"]), "G": ((8, 0.00), ["F", "H"]), "H": ((10, 0.0), ["G", "I"]), "I": ((10, 2.0), ["H"]) }, use_latlon=False) matcher = DistanceMatcher(mapdb, max_dist_init=0.2, obs_noise=1, obs_noise_ne=10, non_emitting_states=True, only_edges=True) states, _ = matcher.match(path) nodes = matcher.path_pred_onlynodes print("States\n------") print(states) print("Nodes\n------") print(nodes) print("") matcher.print_lattice_stats() mmviz.plot_map(mapdb, matcher=matcher, show_labels=True, show_matching=True filename="output.png")
def test_bug2(): from leuvenmapmatching.util.openstreetmap import locations_to_map map_con = SqliteMap("map", use_latlon=True, dir=directory) path = [(50.87205, 4.66089), (50.874550000000006, 4.672980000000001), (50.87538000000001, 4.67698), (50.875800000000005, 4.6787600000000005), (50.876520000000006, 4.6818), (50.87688000000001, 4.683280000000001), (50.87814, 4.68733), (50.87832, 4.68778), (50.87879, 4.68851), (50.87903000000001, 4.68895), (50.879560000000005, 4.689170000000001), (50.87946, 4.6900900000000005), (50.879290000000005, 4.6909600000000005), (50.87906, 4.6921800000000005), (50.87935, 4.6924), (50.879720000000006, 4.69275), (50.88002, 4.6930700000000005), (50.880430000000004, 4.693440000000001), (50.880660000000006, 4.69357), (50.880660000000006, 4.6936100000000005), (50.88058, 4.694640000000001), (50.88055000000001, 4.69491), (50.88036, 4.696160000000001), (50.88009, 4.697550000000001), (50.87986, 4.6982800000000005), (50.879720000000006, 4.698790000000001), (50.87948, 4.699730000000001), (50.87914000000001, 4.6996400000000005), (50.87894000000001, 4.6995000000000005), (50.878800000000005, 4.699350000000001), (50.8785, 4.6991000000000005), (50.87841, 4.6990300000000005)] locations_to_map(path, map_con, filename=directory / "osm.xml") path_sol = [(5777282112, 2633552218), (2633552218, 5777282111), (5777282111, 5777282110), (5777282110, 1642021707), (1642021707, 71361087), (71361087, 71364203), (71364203, 1151697757), (1151697757, 1647339017), (1647339017, 1647339030), (1647339030, 2058510349), (2058510349, 2633552212), (2633552212, 1380538577), (1380538577, 1439572271), (1439572271, 836434313), (836434313, 2633771041), (2633771041, 5042874484), (5042874484, 5042874485), (5042874485, 2518922583), (2518922583, 2659762546), (2659762546, 5777282063), (5777282063, 2633771037), (2633771037, 2633771035), (2633771035, 2633771033), (2633771033, 1151668705), (1151668705, 2633771094), (2633771094, 1151668722), (1151668722, 1151668724), (1151668724, 5543948222), (5543948222, 2058481517), (2058481517, 16933576), (16933576, 5543948221), (5543948221, 2518923620), (2518923620, 5543948020), (5543948020, 5543948019), (5543948019, 18635886), (18635886, 18635887), (18635887, 1036909153), (1036909153, 2658942230), (2658942230, 1001099975), (1001099975, 16933574), (16933574, 1125604152), (1125604152, 5543948238), (5543948238, 1125604150), (1125604150, 1125604148), (1125604148, 2634195334), (2634195334, 2087854243), (2087854243, 5543948237), (5543948237, 160226603), (160226603, 180130266), (180130266, 5543948227), (5543948227, 5543948226), (5543948226, 1195681902), (1195681902, 101135392), (101135392, 2606704673), (2606704673, 18635977), (18635977, 1026111708), (1026111708, 1026111631), (1026111631, 16571375), (16571375, 2000680621), (2000680621, 999580042), (999580042, 16571370), (16571370, 2000680620), (2000680620, 5078692402), (5078692402, 5543948008), (5543948008, 16571371), (16571371, 999579936), (999579936, 2639836143), (2639836143, 5543948014), (5543948014, 5222992316), (5222992316, 30251323), (30251323, 159701080), (159701080, 3173217124), (3173217124, 1165209673), (1165209673, 1380538689), (1380538689, 2878334668), (2878334668, 2871137399), (2871137399, 2876902981), (2876902981, 2873624508), (2873624508, 2873624509), (2873624509, 2899666507), (2899666507, 2899666518), (2899666518, 2899666513), (2899666513, 2903073945), (2903073945, 2903073951), (2903073951, 1380538681), (1380538681, 2914810627), (2914810627, 2914810618), (2914810618, 2914810607), (2914810607, 2914810604), (2914810604, 2914810483), (2914810483, 2914810462), (2914810462, 2914810464), (2914810464, 1312433523), (1312433523, 20918594), (20918594, 2634267817), (2634267817, 2967425445), (2967425445, 3201523879), (3201523879, 157217466), (157217466, 2963305939), (2963305939, 3201523877), (3201523877, 3889275909), (3889275909, 3889275897), (3889275897, 157255077), (157255077, 30251882), (30251882, 157245624), (157245624, 1150903673), (1150903673, 4504936404)] matcher = DistanceMatcher(map_con, min_prob_norm=0.001, max_dist=200, obs_noise=4.07, non_emitting_states=True) nodes, idx = matcher.match(path, unique=True) path_pred = matcher.path_pred if directory: import matplotlib.pyplot as plt matcher.print_lattice_stats() logger.debug("Plotting post map ...") fig = plt.figure(figsize=(100, 100)) ax = fig.get_axes() mm_viz.plot_map(map_con, matcher=matcher, use_osm=True, ax=ax, show_lattice=False, show_labels=True, show_graph=False, zoom_path=True, show_matching=True) plt.savefig(str(directory / "test_newson_bug1.png")) plt.close(fig) logger.debug("... done") assert path_pred == path_sol, f"Edges not equal:\n{path_pred}\n{path_sol}"
def test_route(): if directory: import matplotlib.pyplot as plt else: plt = None paths, map_con, route = load_data() route = [(lat, lon) for lat, lon in route] zoom_path = True # zoom_path = slice(2645, 2665) slice_route = None # slice_route = slice(650, 750) # slice_route = slice(2657, 2662) # First location where some observations are missing # slice_route = slice(2770, 2800) # Observations are missing # slice_route = slice(2910, 2950) # Interesting point # slice_route = slice(2910, 2929) # Interesting point # slice_route = slice(6825, 6833) # Outlier observation slice_route = slice(6300, ) # if directory is not None: # logger.debug("Plotting pre map ...") # mm_viz.plot_map(map_con_latlon, path=route_latlon, use_osm=True, # show_lattice=False, show_labels=False, show_graph=False, zoom_path=zoom_path, # filename=str(directory / "test_newson_route.png")) # logger.debug("... done") matcher = DistanceMatcher(map_con, min_prob_norm=0.0001, max_dist=200, dist_noise=15, dist_noise_ne=30, obs_noise=30, obs_noise_ne=150, non_emitting_states=True) if slice_route is None: pkl_fn = this_path / "nodes_pred.pkl" if pkl_fn.exists(): with pkl_fn.open("rb") as pkl_file: logger.debug(f"Reading predicted nodes from pkl file") route_nodes = pickle.load(pkl_file) else: matcher.match(route) route_nodes = matcher.path_pred_onlynodes with pkl_fn.open("wb") as pkl_file: pickle.dump(route_nodes, pkl_file) from leuvenmapmatching.util.evaluation import route_mismatch_factor print(route_nodes[:10]) # route_edges = map_con.nodes_to_paths(route_nodes) # print(route_edges[:10]) grnd_paths, _ = zip(*paths) print(grnd_paths[:10]) route_paths = map_con.nodes_to_paths(route_nodes) print(route_paths[:10]) logger.debug(f"Compute route mismatch factor") factor, cnt_matches, cnt_mismatches, total_length, mismatches, _, _ = \ route_mismatch_factor(map_con, route_paths, grnd_paths,window=None, keep_mismatches=True) logger.debug( f"factor = {factor}, " f"cnt_matches = {cnt_matches}/{cnt_mismatches} of {len(grnd_paths)}/{len(route_paths)}, " f"total_length = {total_length}\n" f"mismatches = " + " | ".join(str(v) for v in mismatches)) else: _, last_idx = matcher.match(route[slice_route]) logger.debug(f"Last index = {last_idx}") # matcher.match(route[2657:2662]) # First location where some observations are missing # matcher.match(route[2770:2800]) # Observations are missing # matcher.match(route[2910:2950]) # Interesting point # matcher.match(route[2910:2929]) # Interesting point # matcher.match(route[6000:]) path_pred = matcher.path_pred_onlynodes if directory: matcher.print_lattice_stats() logger.debug("Plotting post map ...") fig = plt.figure(figsize=(200, 200)) ax = fig.get_axes() mm_viz.plot_map(map_con, matcher=matcher, use_osm=True, ax=ax, show_lattice=False, show_labels=True, zoom_path=zoom_path, show_matching=True, show_graph=False) plt.savefig(str(directory / "test_newson_route_matched.png")) plt.close(fig) logger.debug("... done") logger.debug("Best path:") for m in matcher.lattice_best: logger.debug(m) print(path_pred)