def main():
key = Cache.generate_key(str(Config()))
if Cache.check(key):
data = Cache.get(key)
points = data['points']
network = data['network']
else:
pass
# get points from trajectories
preprocessor = Preprocessor(Config.DATASET_ROOT_DIR,
Config.DATASET_SCALE)
points = preprocessor.get_points()
# use coherence expanded algorithm to form clusters
clusters = Cluster(points).coherence_expanding()
network = TransferNetwork(points, clusters)
# derive transfer probability
tp = TransferProbability(network)
tp.derive()
# save points and network to cache
Cache.save(key, {"points": points, "network": network})
# show the distribution of transfer probability
figure = Figure(width=8)
figure.transfer_probability(network, 8).show()
# search the most popular route
mpr = MostPopularRoute(network)
route = mpr.search(0, 4)
print(route)
figure = Figure()
figure.most_popular_route(points, network, route).show()
from config import Config
from preprocessor import Preprocessor
from points import Points
from cluster import Cluster
from transfer_network import TransferNetwork
from transfer_probability import TransferProbability
from most_popular_route import MostPopularRoute
from figure import Figure
# get points from trajectories
preprocessor = Preprocessor(
Config.DATASET_ROOT_DIR,
Config.DATASET_SCALE)
points = preprocessor.get_points()
# use coherence expanded algorithm to form clusters
clusters = Cluster(points).coherence_expanding()
network = TransferNetwork(points, clusters)
# derive transfer probability
tp = TransferProbability(network)
tp.derive()
# search the most popular route
mpr = MostPopularRoute(network)
route = mpr.search(0, 6)
print(route)
figure = Figure()
figure.most_popular_route(points, network, route).show()