def find_path(self, time, src_lat, src_lng, dest_lat, dest_lng, cb=None):
# translate the time to an offset from the beginning of the day
# and determine service period
now = datetime.datetime.fromtimestamp(time)
today_secs = (now.hour * 60 * 60) + (now.minute * 60) + (now.second)
service_period = 'weekday'
if now.weekday() == 5:
service_period = 'saturday'
elif now.weekday() == 6:
service_period = 'sunday'
# Find path
visited_ids = {}
uncompleted_paths = [ ]
completed_paths = [ ]
best_path = None
start_node = self.get_nearest_osmstop(src_lat, src_lng)
end_node = self.get_nearest_osmstop(dest_lat, dest_lng)
print "Start: %s End: %s" % (start_node.id, end_node.id)
# stupid case: start is equal to end
if start_node == end_node:
return None
dist_from_start = latlng_ext.distance(src_lat, src_lng, start_node.lat, start_node.lng)
today_secs += dist_from_start / 1.1
heappush(uncompleted_paths, TripPath(int(today_secs), self.fastest_speed,
end_node, start_node))
# then keep on extending paths until we've exhausted all possibilities
# or we can't do any better
num_paths_considered = 0
while len(uncompleted_paths) > 0:
trip_path = heappop(uncompleted_paths)
#print "Extending path with weight: %s" % (trip_path.heuristic_weight)
new_trip_paths = self.extend_path(trip_path, service_period, visited_ids, cb)
num_paths_considered += len(new_trip_paths)
for p in new_trip_paths:
if p.last_stop.id == end_node.id:
heappush(completed_paths, p)
else:
heappush(uncompleted_paths, p)
# if we've still got open paths, but their weight exceeds that
# of the weight of a completed path, break
if len(uncompleted_paths) > 0 and len(completed_paths) > 0 and \
uncompleted_paths[0].heuristic_weight > completed_paths[0].heuristic_weight:
print "Breaking with %s uncompleted paths (paths considered: %s)." % (len(uncompleted_paths), num_paths_considered)
return completed_paths[0]
#if len(completed_paths) > 0 and len(uncompleted_paths) > 0:
# print "Weight of best completed path: %s, uncompleted: %s" % \
# (completed_paths[0].heuristic_weight, uncompleted_paths[0].heuristic_weight)
if len(completed_paths) > 0:
return completed_paths[0]
else:
return None
def link_osm_gtfs(self):
mylen = len(self.tripstops.values())
for s1 in self.tripstops.values():
if s1.type == "gtfs":
nearest_osm = None
min_dist = 0
for s2 in self.tripstops.values():
if s2.type == "osm":
dist = latlng_ext.distance(s1.lat, s1.lng, s2.lat, s2.lng)
if not nearest_osm or dist < min_dist:
nearest_osm = s2
min_dist = dist
time = latlng_ext.distance(nearest_osm.lat, nearest_osm.lng, s1.lat, s1.lng) / 1.1
print "Adding triplink %s->%s" %(nearest_osm.id, s1.id)
self.add_walkhop(nearest_osm.id, s1.id)
self.add_walkhop(s1.id, nearest_osm.id)
def add_triphop(self, start_time, end_time, src_id, dest_id, route_id,
service_id):
s1 = self.tripstops[src_id]
s2 = self.tripstops[dest_id]
dist = latlng_ext.distance(s1.lat, s1.lng, s2.lat, s2.lng)
total_time = end_time - start_time
speed = float(dist) / float(total_time)
if total_time > 30 and dist > 0 and speed > self.fastest_speed:
self.fastest_speed = speed
self.tripstops[src_id].add_triphop(start_time, end_time, dest_id,
route_id, service_id)
def add_walkhop(self, src_id, dest_id): w1 = self.tripstops[src_id] w2 = self.tripstops[dest_id] time = latlng_ext.distance(w1.lat, w1.lng, w2.lat, w2.lng) / 1.1 self.tripstops[src_id].add_walkhop(dest_id, time)