def analyze_average_commute(date_val):
# Display a contiguous commute time from a source station to a target station
# Get DB data
session = manage.get_session()
stop_names = manage.get_stop_names()
station_id_dict = station_id2name('../data/stops_ids_and_names.txt')
# Create a graph representation of the train stops
G = create_train_graph(session, stop_names, station_id_dict, date_val)
target = 4600 # station_id for Tel-Aviv Hashalom
time_len = 60*24
hour_vec = np.array(range(24*60))/60
minute_vec = np.array(range(24*60)) % 60
time_indx_real = map(lambda x: '%04d'%x, hour_vec*100 + minute_vec)
# Calculation of the DOT graph algorithms
dist_vec, path_vec = dynamic_all_to_one(G, target, time_len)
display_graph(G, draw_edge_label=False)
station_id = 5410
xindx = range(len(time_indx_real))
plt.xticks(xindx[240::240], time_indx_real[240::240]), plt.plot(xindx[240:], dist_vec[station_id][240:], label=station_id_dict[station_id], linewidth=2.5), plt.grid(), plt.ylim(0, 150)
plt.xlabel('time of day'), plt.ylabel('time of commute in minutes'), plt.title(('Commute Time to %s') % (station_id_dict[4600]))
station_id = 3500
plt.plot(xindx[240:], dist_vec[station_id][240:], label=station_id_dict[station_id], linewidth=2.5)
station_id=8700
plt.plot(xindx[240:], dist_vec[station_id][240:], label=station_id_dict[station_id], linewidth=2.5)
plt.legend()
plt.show()
return dist_vec, path_vec
### -----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
if __name__ == '__main__':
# Create graph
# time_len = 2
# G = create_toy_graph(10, 25, time_len=time_len)
# G = create_predefind_graph()
import src.manage
session = src.manage.get_session()
stop_names = src.manage.get_stop_names()
station_id_dict = station_id2name('../data/stops_ids_and_names.txt')
date_val = datetime.date(2014, 1, 1)
G = create_train_graph(session, stop_names, station_id_dict, date_val)
target = 4600
time_len = 60*24
hour_vec = np.array(range(24*60))/60
minuete_vec = np.array(range(24*60)) % 60
time_indx_real = map(lambda x: '%04d'%x, hour_vec*100 + minuete_vec)
dist_vec, path_vec = dynamic_all_to_one(G, target, time_len)
display_graph(G, draw_edge_label=False)
