def simple_match(filename, **kwargs):
max_distance = kwargs['max_distance'] if 'max_distance' in kwargs else DEFAULT_MAX_DISTANCE
with open(filename, 'r') as f:
data = read_gps_file(f, delimiter=',')
points = zip(data['lat'], data['long'])
matches = []
for i, point in enumerate(points):
# Don't query the same point twice
if i==0 or point != points[i-1]:
point_merc, ways = query_ways_within_radius(point[0], point[1], max_distance)
min_dist = sys.maxint
min_way = None
min_idx = None
if ways:
_add_segments(ways)
_add_distances(ways, point_merc)
for way in ways:
if way['osm_id'] < 0:
continue
local_min_idx, local_min_dist = min(enumerate(way['distances']), key=lambda x: x[1])
if local_min_dist <= min_dist:
min_dist = local_min_dist
min_idx = local_min_idx
min_way = way['osm_id']
point_dict = {'point_index': i, 'point': point_merc, 'way': min_way, 'index_of_segment': min_idx}
matches.append(point_dict)
return matches
def compute_emission_probabilities(observation, radius, n):
#print(observation)
lat, lon, course, speed = observation
course = math.radians(-course+90)
point, ways = query_ways_within_radius(lat, lon, radius)
if ways is None or point is None:
return
ways = _add_segments(ways)
ways = _add_distances(ways, point)
ways = _add_tangents(ways)
ways = _add_tangent_scores(ways, course)
ways = _add_distance_scores(ways, GPS_SIGMA)
ways = _add_emission_probabilities(ways)
segments, probabilities = _get_top_n(ways, n)
return segments, probabilities, point
def compute_emission_probabilities(observation, radius, n):
#print(observation)
lat, lon, course, speed = observation
course = math.radians(-course + 90)
point, ways = query_ways_within_radius(lat, lon, radius)
if ways is None or point is None:
return
ways = _add_segments(ways)
ways = _add_distances(ways, point)
ways = _add_tangents(ways)
ways = _add_tangent_scores(ways, course)
ways = _add_distance_scores(ways, GPS_SIGMA)
ways = _add_emission_probabilities(ways)
segments, probabilities = _get_top_n(ways, n)
return segments, probabilities, point
def simple_match(filename, **kwargs):
max_distance = kwargs[
'max_distance'] if 'max_distance' in kwargs else DEFAULT_MAX_DISTANCE
with open(filename, 'r') as f:
data = read_gps_file(f, delimiter=',')
points = zip(data['lat'], data['long'])
matches = []
for i, point in enumerate(points):
# Don't query the same point twice
if i == 0 or point != points[i - 1]:
point_merc, ways = query_ways_within_radius(
point[0], point[1], max_distance)
min_dist = sys.maxint
min_way = None
min_idx = None
if ways:
_add_segments(ways)
_add_distances(ways, point_merc)
for way in ways:
if way['osm_id'] < 0:
continue
local_min_idx, local_min_dist = min(enumerate(
way['distances']),
key=lambda x: x[1])
if local_min_dist <= min_dist:
min_dist = local_min_dist
min_idx = local_min_idx
min_way = way['osm_id']
point_dict = {
'point_index': i,
'point': point_merc,
'way': min_way,
'index_of_segment': min_idx
}
matches.append(point_dict)
return matches
