def __init__(self):
# Network configuration
self.config = yaml.load(open(load_config("zeta"), "r"),
yaml.FullLoader)
self.config["swmm_input"] = load_network(self.config["name"])
# Create the environment based on the physical parameters
self.env = environment(self.config, ctrl=True)
self.penalty_weight = {
"T1": 1000,
"T2": 5000,
"T3": 5000,
"T4": 5000,
"T5": 5000,
"T6": 10000
}
# Create an object for storing the data points
self.data_log = {
"performance_measure": [],
"simulation_time": [],
"flow": {},
"flooding": {},
"depthN": {},
}
# Log the initial simulation time
self.data_log["simulation_time"].append(
self.env.sim._model.getCurrentSimulationTime())
# Data logger for storing _performance data
for ID, attribute in self.config["performance_targets"]:
self.data_log[attribute][ID] = []
def __init__(self):
# Network configuration
self.config = yaml.load(open(load_config("delta"), "r"),
yaml.FullLoader)
self.config["swmm_input"] = load_network(self.config["name"])
self.threshold = 12.0
self.depth_thresholds = {
"basin_C": (5.7, 2.21, 3.8, 3.28),
"basin_S": (6.55, 9.5),
"basin_N1": (5.92, 2.11, 5.8, 5.2),
"basin_N2": (6.59, 4.04, 5.04, 4.44),
"basin_N3": (11.99, 5.28, 5.92, 5.32),
}
# Additional penalty definition
self.max_penalty = 10**6
# Create the environment based on the physical parameters
self.env = environment(self.config, ctrl=True)
# Create an object for storing the data points
self.data_log = {
"performance_measure": [],
"depthN": {},
"flow": {},
"flooding": {},
}
# Data logger for storing _performance data
for ID, attribute in self.config["performance_targets"]:
self.data_log[attribute][ID] = []
def __init__(self):
# Network configuration
self.config = yaml.load(open(load_config("epsilon"), "r"),
yaml.FullLoader)
self.config["swmm_input"] = load_network(self.config["name"])
self.config["binary"] = load_binary(self.config["binary"])
# Dry weather TSS loading, measured at the outlet of the network
self._performormance_threshold = 1.075 # Kg/sec
# Create the env based on the config file
self.env = environment(self.config,
ctrl=True,
binary=self.config["binary"])
# Create an object for storing data
self.data_log = {
"performance_measure": [],
"loading": {},
"pollutantL": {},
"flow": {},
"flooding": {},
}
# Data logger for storing _performormance data
for ID, attribute in self.config["performance_targets"]:
self.data_log[attribute][ID] = []
def __init__(self):
# Network configuration
self.config = yaml.load(open(load_config("theta"), "r"),
yaml.FullLoader)
self.config["swmm_input"] = load_network(self.config["name"])
self.threshold = 0.5
# Create the environment based on the physical parameters
self.env = environment(self.config, ctrl=True)
# Create an object for storing the data points
self.data_log = {"performance_measure": [], "flow": {}, "flooding": {}}
# Data logger for storing _performance data
for ID, attribute in self.config["performance_targets"]:
self.data_log[attribute][ID] = []
def __init__(self):
# Network configuration
self.config = yaml.load(open(load_config("gamma"), "r"), yaml.FullLoader)
self.config["swmm_input"] = load_network(self.config["name"])
# Common threhold for the network, can be done independently
self._performormance_threshold = 4.0
# Create the environment based on the physical parameters
self.env = environment(self.config, ctrl=True)
# Create an object for storing the data points
self.data_log = {
"performance_measure": [],
"flow": {},
"flooding": {},
"depthN": {},
"simulation_time": [],
}
# Data logger for storing _performormance data
for ID, attribute in self.config["performance_targets"]:
self.data_log[attribute][ID] = []