@author: user
"""
from simulation import Simulation, TestSimulation
from generator import TrafficGenerator
from model import Model, TestModel
from memory import Memory
from visualization import Visualization
from utils import import_train_configuration, set_sumo, set_test_path
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
import os
#%%
if __name__ == "__main__":
config = import_train_configuration(config_file="training_settings.ini")
sumo_cmd = set_sumo(False, config['sumocfg_file_name'],
config['max_steps'])
TrafficGen = TrafficGenerator(config['max_steps'],
config['n_cars_generated'])
model = Model(config['num_layers'], config['width_layers'],
config['num_states'], config['num_actions'],
config['batch_size'], config['learning_rate'])
memory = Memory(config['memory_size_max'])
viz = Visualization(config['models_path_name'], dpi=96)
sim = Simulation(TrafficGen, model, memory, config['gamma'],
@property
def reward_store(self):
return self._reward_store
@property
def cumulative_wait_store(self):
return self._cumulative_wait_store
@property
def avg_queue_length_store(self):
return self._avg_queue_length_store
if __name__ == "__main__":
config = import_train_configuration(
config_file='settings/training_settings.ini')
sumo_cmd = set_sumo(config['gui'], config['simulation_folder'],
config['sumocfg_file_name'], config['max_steps'])
path = set_train_path(config['models_path_name'])
Model = TrainModel(config['num_layers'],
config['width_layers'],
config['batch_size'],
config['learning_rate'],
input_dim=config['num_states'],
output_dim=config['num_actions'])
Memory = Memory(config['memory_size_max'], config['memory_size_min'])
Traffic_Generator = Traffic_Generator(config["flow_file"],
config["route_file"],