def get_flow_params(config):
"""Return Flow experiment parameters, given an experiment result folder.
Parameters
----------
config : dict < dict > or str
May be one of two things:
* If it is a dict, then it is the stored RLlib configuration dict.
* If it is a string, then it is the path to a flow_params json file.
Returns
-------
dict
flow-related parameters, consisting of the following keys:
* exp_tag: name of the experiment
* env_name: name of the flow environment the experiment is running on
* network: name of the network class the experiment uses
* simulator: simulator that is used by the experiment (e.g. aimsun)
* sim: simulation-related parameters (see flow.core.params.SimParams)
* env: environment related parameters (see flow.core.params.EnvParams)
* net: network-related parameters (see flow.core.params.NetParams and
the network's documentation or ADDITIONAL_NET_PARAMS component)
* veh: vehicles to be placed in the network at the start of a rollout
(see flow.core.params.VehicleParams)
* initial: parameters affecting the positioning of vehicles upon
initialization/reset (see flow.core.params.InitialConfig)
* tls: traffic lights to be introduced to specific nodes (see
flow.core.params.TrafficLightParams)
"""
# collect all data from the json file
if type(config) == dict:
flow_params = json.loads(config['env_config']['flow_params'])
else:
flow_params = json.load(open(config, 'r'))
# reinitialize the vehicles class from stored data
veh = VehicleParams()
for veh_params in flow_params["veh"]:
module = __import__(
"flow.controllers",
fromlist=[veh_params['acceleration_controller'][0]])
acc_class = getattr(module, veh_params['acceleration_controller'][0])
lc_class = getattr(module, veh_params['lane_change_controller'][0])
acc_controller = (acc_class, veh_params['acceleration_controller'][1])
lc_controller = (lc_class, veh_params['lane_change_controller'][1])
rt_controller = None
if veh_params['routing_controller'] is not None:
rt_class = getattr(module, veh_params['routing_controller'][0])
rt_controller = (rt_class, veh_params['routing_controller'][1])
# TODO: make ambiguous
car_following_params = SumoCarFollowingParams()
car_following_params.__dict__ = veh_params["car_following_params"]
# TODO: make ambiguous
lane_change_params = SumoLaneChangeParams()
lane_change_params.__dict__ = veh_params["lane_change_params"]
del veh_params["car_following_params"], \
veh_params["lane_change_params"], \
veh_params["acceleration_controller"], \
veh_params["lane_change_controller"], \
veh_params["routing_controller"]
veh.add(acceleration_controller=acc_controller,
lane_change_controller=lc_controller,
routing_controller=rt_controller,
car_following_params=car_following_params,
lane_change_params=lane_change_params,
**veh_params)
# convert all parameters from dict to their object form
sim = SumoParams() # TODO: add check for simulation type
sim.__dict__ = flow_params["sim"].copy()
net = NetParams()
net.__dict__ = flow_params["net"].copy()
net.inflows = InFlows()
if flow_params["net"]["inflows"]:
net.inflows.__dict__ = flow_params["net"]["inflows"].copy()
env = EnvParams()
env.__dict__ = flow_params["env"].copy()
initial = InitialConfig()
if "initial" in flow_params:
initial.__dict__ = flow_params["initial"].copy()
tls = TrafficLightParams()
if "tls" in flow_params:
tls.__dict__ = flow_params["tls"].copy()
flow_params["sim"] = sim
flow_params["env"] = env
flow_params["initial"] = initial
flow_params["net"] = net
flow_params["veh"] = veh
flow_params["tls"] = tls
return flow_params
def get_flow_params(config):
"""Return Flow experiment parameters, given an experiment result folder.
Parameters
----------
config : dict
stored RLlib configuration dict
Returns
-------
dict
Dict of flow parameters, like net_params, env_params, vehicle
characteristics, etc
"""
# collect all data from the json file
flow_params = json.loads(config['env_config']['flow_params'])
# reinitialize the vehicles class from stored data
veh = Vehicles()
for veh_params in flow_params["veh"]:
module = __import__(
"flow.controllers",
fromlist=[veh_params['acceleration_controller'][0]])
acc_class = getattr(module, veh_params['acceleration_controller'][0])
lc_class = getattr(module, veh_params['lane_change_controller'][0])
acc_controller = (acc_class, veh_params['acceleration_controller'][1])
lc_controller = (lc_class, veh_params['lane_change_controller'][1])
rt_controller = None
if veh_params['routing_controller'] is not None:
rt_class = getattr(module, veh_params['routing_controller'][0])
rt_controller = (rt_class, veh_params['routing_controller'][1])
sumo_cf_params = SumoCarFollowingParams()
sumo_cf_params.__dict__ = veh_params["sumo_car_following_params"]
sumo_lc_params = SumoLaneChangeParams()
sumo_lc_params.__dict__ = veh_params["sumo_lc_params"]
del veh_params["sumo_car_following_params"], \
veh_params["sumo_lc_params"], \
veh_params["acceleration_controller"], \
veh_params["lane_change_controller"], \
veh_params["routing_controller"]
veh.add(acceleration_controller=acc_controller,
lane_change_controller=lc_controller,
routing_controller=rt_controller,
sumo_car_following_params=sumo_cf_params,
sumo_lc_params=sumo_lc_params,
**veh_params)
# convert all parameters from dict to their object form
sumo = SumoParams()
sumo.__dict__ = flow_params["sumo"].copy()
net = NetParams()
net.__dict__ = flow_params["net"].copy()
net.inflows = InFlows()
if flow_params["net"]["inflows"]:
net.inflows.__dict__ = flow_params["net"]["inflows"].copy()
env = EnvParams()
env.__dict__ = flow_params["env"].copy()
initial = InitialConfig()
if "initial" in flow_params:
initial.__dict__ = flow_params["initial"].copy()
tls = TrafficLightParams()
if "tls" in flow_params:
tls.__dict__ = flow_params["tls"].copy()
flow_params["sumo"] = sumo
flow_params["env"] = env
flow_params["initial"] = initial
flow_params["net"] = net
flow_params["veh"] = veh
flow_params["tls"] = tls
return flow_params
def get_flow_params(config):
"""Return Flow experiment parameters, given an experiment result folder.
Parameters
----------
config : dict < dict > or str
May be one of two things:
* If it is a dict, then it is the stored RLlib configuration dict.
* If it is a string, then it is the path to a flow_params json file.
Returns
-------
dict
flow-related parameters, consisting of the following keys:
* exp_tag: name of the experiment
* env_name: environment class of the flow environment the experiment
is running on. (note: must be in an importable module.)
* network: network class the experiment uses.
* simulator: simulator that is used by the experiment (e.g. aimsun)
* sim: simulation-related parameters (see flow.core.params.SimParams)
* env: environment related parameters (see flow.core.params.EnvParams)
* net: network-related parameters (see flow.core.params.NetParams and
the network's documentation or ADDITIONAL_NET_PARAMS component)
* veh: vehicles to be placed in the network at the start of a rollout
(see flow.core.params.VehicleParams)
* initial: parameters affecting the positioning of vehicles upon
initialization/reset (see flow.core.params.InitialConfig)
* tls: traffic lights to be introduced to specific nodes (see
flow.core.params.TrafficLightParams)
"""
# collect all data from the json file
if type(config) == dict:
flow_params = json.loads(config['env_config']['flow_params'])
else:
flow_params = json.load(open(config, 'r'))
# reinitialize the vehicles class from stored data
veh = CustomVehicleParams()
for veh_params in flow_params["veh"]['type_parameters'].items():
# adding veh id to the dictionary
veh_id=veh_params[0]
veh_params=veh_params[1]
veh_params.update(veh_id=veh_id)
module = __import__(
"flow.controllers",
fromlist=[veh_params['acceleration_controller'][0]])
acc_class = getattr(module, veh_params['acceleration_controller'][0])
lc_class = getattr(module, veh_params['lane_change_controller'][0])
acc_controller = (acc_class, veh_params['acceleration_controller'][1])
lc_controller = (lc_class, veh_params['lane_change_controller'][1])
rt_controller = None
if veh_params['routing_controller'] is not None:
rt_class = getattr(module, veh_params['routing_controller'][0])
rt_controller = (rt_class, veh_params['routing_controller'][1])
# TODO: make ambiguous
car_following_params = SumoCarFollowingParams()
car_following_params.__dict__ = veh_params["car_following_params"]
# TODO: make ambiguous
lane_change_params = SumoLaneChangeParams()
lane_change_params.__dict__ = veh_params["lane_change_params"]
del veh_params["car_following_params"], \
veh_params["lane_change_params"], \
veh_params["acceleration_controller"], \
veh_params["lane_change_controller"], \
veh_params["routing_controller"]
veh.add(
acceleration_controller=acc_controller,
lane_change_controller=lc_controller,
routing_controller=rt_controller,
car_following_params=car_following_params,
lane_change_params=lane_change_params,
**veh_params)
# convert all parameters from dict to their object form
sim = SumoParams() # TODO: add check for simulation type
sim.__dict__ = flow_params["sim"].copy()
net = NetParams()
net.__dict__ = flow_params["net"].copy()
net.inflows = InFlows()
if flow_params["net"]["inflows"]:
net.inflows.__dict__ = flow_params["net"]["inflows"].copy()
env = EnvParams()
env.__dict__ = flow_params["env"].copy()
initial = InitialConfig()
if "initial" in flow_params:
initial.__dict__ = flow_params["initial"].copy()
tls = TrafficLightParams()
if "tls" in flow_params:
tls.__dict__ = flow_params["tls"].copy()
env_name = flow_params['env_name']
if "." not in env_name: # coming from old flow_params
single_agent_envs = [env for env in dir(flow.envs)
if not env.startswith('__')]
if env_name in single_agent_envs:
env_loc = 'flow.envs'
else:
env_loc = 'flow.envs.multiagent'
else:
env_loc = ".".join(env_name.split(".")[:-1])
env_name = env_name.split(".")[-1]
env_module = __import__(env_loc, fromlist=[env_name])
env_instance = getattr(env_module, env_name)
network = flow_params['network']
if "." not in network: # coming from old flow_params
net_loc = 'flow.networks'
else:
net_loc = ".".join(network.split(".")[:-1])
network = network.split(".")[-1]
net_module = __import__(net_loc, fromlist=[network])
net_instance = getattr(net_module, network)
flow_params['env_name'] = env_instance
flow_params['network'] = net_instance
flow_params["sim"] = sim
flow_params["env"] = env
flow_params["initial"] = initial
flow_params["net"] = net
flow_params["veh"] = veh
flow_params["tls"] = tls
return flow_params
