def new_time_from_previous(time_between, start):
sigma = int(time_between / 10)
mu = 0
mini = int(-time_between / 5)
maxi = int(time_between / 2)
delta = geo.gaussian_trunc(mini, maxi, mu, sigma)
t = delta + time_between
t = convert_to_tuple(t)
new_time = add_times(start, t)
return new_time
def generate_hubs():
n_lines = geo.gaussian_trunc(n_lines_mini, n_lines_maxi, n_lines_mu,
n_lines_sigma)
lines = geo.generate_lines(n_lines, r_line_mu, r_line_sigma)
intersections = geo.find_intersections(lines)
outliers, clusters = geo.points_to_glue(intersections,
intersection_sensitivity)
glued_inter = geo.glue_inter(outliers, clusters, intersections)
merged_lines = geo.merge_lines(lines, glued_inter)
stations = geo.generate_stations(merged_lines, position_variance,
av_dist_btw_stations)
stations = geo.merge_stations(stations, glued_inter)
outliers, clusters = geo.points_to_glue(stations,
close_stations_sensitivity)
glued_stations = geo.glue_stations(outliers, clusters, stations)
filtered_stations = geo.remove_duplicate_lines(glued_stations)
hubs = geo.compute_hubs(filtered_stations)
return hubs, filtered_stations
def generate_transportation():
# Global topology : lines
n_lines = geo.gaussian_trunc(n_lines_mini, n_lines_maxi, n_lines_mu,
n_lines_sigma)
lines = geo.generate_lines(n_lines, r_line_mu, r_line_sigma)
intersections = geo.find_intersections(lines)
outliers, clusters = geo.points_to_glue(intersections,
intersection_sensitivity)
glued_inter = geo.glue_inter(outliers, clusters, intersections)
merged_lines = geo.merge_lines(lines, glued_inter)
# Local topology : stations
stations = geo.generate_stations(merged_lines, position_variance,
av_dist_btw_stations)
stations = geo.merge_stations(stations, glued_inter)
outliers, clusters = geo.points_to_glue(stations,
close_stations_sensitivity)
glued_stations = geo.glue_stations(outliers, clusters, stations)
filtered_stations = geo.remove_duplicate_lines(glued_stations)
hubs = geo.compute_hubs(filtered_stations)
fast_lines = geo.build_fast_lines(hubs, r_line_mu, r_line_sigma,
min_n_stations_per_fast_line, n_meters)
n_fast_lines = len(fast_lines)
updated_stations = geo.update_compatibilities(filtered_stations,
fast_lines)
# Toponymy
names = nm.generate_names(len(updated_stations))
updated_stations = nm.add_names(names, updated_stations)
lines_dict = sch.build_lines_dict(updated_stations)
network = sch.build_Network(lines_dict, slow_speed, fast_speed)
# Schedule and itineraries
network = sch.compute_whole_schedule(network)
stations = network.get_all_stations()
graph = it.convert_Network_to_Graph(network)
all_shortest_paths = it.all_shortest_paths_and_lengths(graph)
xml.generate_xml(network)
xml.generate_rdf(network)
return network, stations, all_shortest_paths, hubs
def generate_departure_times(start):
if is_less_or_equal(start, (7, 30, 0)):
mu = 6 * 60
sigma = 3 * 60
else:
if is_less_or_equal(start, (10, 0, 0)):
mu = 2 * 60
sigma = 30
else:
if is_less_or_equal(start, (18, 0, 0)):
mu = 4 * 60
sigma = 2 * 60
else:
if is_less_or_equal(start, (21, 0, 0)):
mu = 2 * 60
sigma = 60
else:
mu = 6 * 60
sigma = 4 * 60
delta = geo.gaussian_trunc(60, 600, mu, sigma)
delta = convert_to_tuple(delta)
new_start = add_times(delta, start)
return new_start
network = sch.build_Network(lines_dict, slow_speed, fast_speed)
# Schedule and itineraries
network = sch.compute_whole_schedule(network)
stations = network.get_all_stations()
graph = it.convert_Network_to_Graph(network)
all_shortest_paths = it.all_shortest_paths_and_lengths(graph)
xml.generate_xml(network)
xml.generate_rdf(network)
return network, stations, all_shortest_paths, hubs
if __name__ == "__main__":
# Global topology : lines
n_lines = geo.gaussian_trunc(n_lines_mini, n_lines_maxi, n_lines_mu,
n_lines_sigma)
lines = geo.generate_lines(n_lines, r_line_mu, r_line_sigma)
dis.display_segments(lines, [], 'simple segments')
intersections = geo.find_intersections(lines)
dis.display_segments(lines, intersections,
'simple segments with intersections')
outliers, clusters = geo.points_to_glue(intersections,
intersection_sensitivity)
glued_inter = geo.glue_inter(outliers, clusters, intersections)
dis.display_segments(lines, glued_inter,
'simple segments with "glued" intersections')
merged_lines = geo.merge_lines(lines, glued_inter)
dis.display_network(merged_lines, glued_inter, [], [], [],
'lines crossing the intersections')
# Local topology : stations