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)
