def main():
size = query_size_grid() # Query user for size of city grid
num_simuls = query_number_simulations() # Query user for number of simulations to run
(min_num_peds, max_num_peds) = query_number_pedestrians(size) # Query user for number of pedestrians
out_pref = query_output_preference() # Query user as to whether to print view of city or output png/Gephi files
print("--------------------")
print("Generating a random city")
city = City.generate_random_city(size, size) # Build the city network
if out_pref[0]:
print("\nHere is the randomly generated city grid that will be used for simulation (saved as city.png):\n")
city.print(out_pref[0], out_pref[1]) # Display city network if user requests
simulation_summary = {} # Container for all results summary
simulation = 1
while simulation <= num_simuls: # Run simulations and record results
print("Running simulation {}".format(simulation))
pedestrian_summary = {}
for num_peds in range(min_num_peds, max_num_peds + 1):
intersection_list = run_simulation(city, num_peds)
if intersection_list:
pedestrian_summary[num_peds] = {
"Pedestrians": num_peds,
"City": city,
"Top_Location": intersection_list[0][0],
"Number_Collisions": intersection_list[0][1]
}
else:
break
simulation_summary[simulation] = pedestrian_summary
simulation += 1
print_aggregate_statistics(simulation_summary, size, city)
simulation_reports = []
simulation_reports.extend([report for report in simulation_summary.values()])
from city import City from pedestrian import Pedestrian city = City.generate_random_city(10, 10) #city.print(True, True) pedestrians = Pedestrian.generate_random_pedestrians(50, city)
