Пример #1
0
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()
Пример #2
0
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()