def setUp(self):
self.backend = PandaPowerBackend(
detailed_infos_for_cascading_failures=True)
self.path_matpower = PATH_DATA_TEST
self.case_file = "test_case14.json"
self.backend.load_grid(self.path_matpower, self.case_file)
self.tolvect = 1e-2
self.tol_one = 1e-5
self.game_rules = GameRules()
self.action_env = HelperAction(
gridobj=self.backend, legal_action=self.game_rules.legal_action)
self.lines_flows_init = np.array([
638.28966637, 305.05042301, 17658.9674809, 26534.04334098,
10869.23856329, 4686.71726729, 15612.65903298, 300.07915572,
229.8060832, 169.97292682, 100.40192958, 265.47505664,
21193.86923911, 21216.44452327, 49701.1565287, 124.79684388,
67.59759985, 192.19424706, 666.76961936, 1113.52773632
])
# _parameters for the environment
self.env_params = Parameters()
# used for init an env too
self.chronics_handler = ChronicsHandler()
self.id_first_line_disco = 8 # due to hard overflow
self.id_2nd_line_disco = 11 # due to soft overflow
def setUp(self):
self.backend = PandaPowerBackend()
self.path_matpower = PATH_DATA_TEST
self.case_file = "test_case14.json"
self.backend.load_grid(self.path_matpower, self.case_file)
self.tolvect = 1e-2
self.tol_one = 1e-5
self.game_rules = GameRules()
self.action_env = HelperAction(name_prod=self.backend.name_prods,
name_load=self.backend.name_loads,
name_line=self.backend.name_lines,
subs_info=self.backend.subs_elements,
load_to_subid=self.backend.load_to_subid,
gen_to_subid=self.backend.gen_to_subid,
lines_or_to_subid=self.backend.lines_or_to_subid,
lines_ex_to_subid=self.backend.lines_ex_to_subid, #####
load_to_sub_pos=self.backend.load_to_sub_pos,
gen_to_sub_pos=self.backend.gen_to_sub_pos,
lines_or_to_sub_pos=self.backend.lines_or_to_sub_pos,
lines_ex_to_sub_pos=self.backend.lines_ex_to_sub_pos, #####
load_pos_topo_vect=self.backend.load_pos_topo_vect,
gen_pos_topo_vect=self.backend.gen_pos_topo_vect,
lines_or_pos_topo_vect=self.backend.lines_or_pos_topo_vect,
lines_ex_pos_topo_vect=self.backend.lines_ex_pos_topo_vect,
game_rules=self.game_rules)
def setUp(self):
self.backend = PandaPowerBackend()
self.path_matpower = PATH_DATA_TEST
self.case_file = "test_case14.json"
self.backend.load_grid(self.path_matpower, self.case_file)
self.tolvect = 1e-2
self.tol_one = 1e-5
self.game_rules = GameRules()
self.action_env = HelperAction(
gridobj=self.backend, legal_action=self.game_rules.legal_action)
def setUp(self):
"""
The case file is a representation of the case14 as found in the ieee14 powergrid.
:return:
"""
# from ADNBackend import ADNBackend
# self.backend = ADNBackend()
# self.path_matpower = "/home/donnotben/Documents/RL4Grid/RL4Grid/data"
# self.case_file = "ieee14_ADN.xml"
# self.backend.load_grid(self.path_matpower, self.case_file)
self.tolvect = 1e-2
self.tol_one = 1e-5
self.game_rules = GameRules()
# pdb.set_trace()
self.helper_action = HelperAction(
name_prod=["gen_{}".format(i) for i in range(5)],
name_load=["load_{}".format(i) for i in range(11)],
name_line=["line_{}".format(i) for i in range(20)],
subs_info=np.array([3, 6, 4, 6, 5, 6, 3, 2, 5, 3, 3, 3, 4, 3],
dtype=np.int),
load_to_subid=np.array([1, 2, 3, 4, 5, 8, 9, 10, 11, 12, 13]),
gen_to_subid=np.array([0, 1, 2, 5, 7]),
lines_or_to_subid=np.array(
[0, 0, 1, 1, 1, 2, 3, 3, 3, 4, 5, 5, 5, 6, 6, 8, 8, 9, 11,
12]),
lines_ex_to_subid=np.array([
1, 4, 2, 3, 4, 3, 4, 6, 8, 5, 10, 11, 12, 7, 8, 9, 13, 10, 12,
13
]), #####
load_to_sub_pos=np.array([4, 2, 5, 4, 4, 4, 1, 1, 1, 2, 1]),
gen_to_sub_pos=np.array([2, 5, 3, 5, 1]),
lines_or_to_sub_pos=np.array(
[0, 1, 1, 2, 3, 1, 2, 3, 4, 3, 1, 2, 3, 1, 2, 2, 3, 0, 0, 1]),
lines_ex_to_sub_pos=np.array(
[0, 0, 0, 0, 1, 1, 2, 0, 0, 0, 2, 2, 3, 0, 1, 2, 2, 0, 0,
0]), #####
load_pos_topo_vect=np.array(
[7, 11, 18, 23, 28, 39, 41, 44, 47, 51, 54]),
gen_pos_topo_vect=np.array([2, 8, 12, 29, 34]),
lines_or_pos_topo_vect=np.array([
0, 1, 4, 5, 6, 10, 15, 16, 17, 22, 25, 26, 27, 31, 32, 37, 38,
40, 46, 50
]),
lines_ex_pos_topo_vect=np.array([
3, 19, 9, 13, 20, 14, 21, 30, 35, 24, 45, 48, 52, 33, 36, 42,
55, 43, 49, 53
]),
game_rules=self.game_rules)
def __init__(self, gridobj, controler_backend):
"""
Parameters
----------
gridobj: :class:`grid2op.Space.Space`
Structure of the powergrid
envbackend: :class:`grid2op.Backend.Backend`
An instanciated backend to perform some computation on a powergrid, before taking some actions.
"""
legal_act = AllwaysLegal()
self.action_space = HelperAction(gridobj=gridobj,
actionClass=VoltageOnlyAction,
legal_action=legal_act)
self.backend = controler_backend.copy()
def init_backend(self, init_grid_path, chronics_handler, backend,
names_chronics_to_backend, actionClass, observationClass,
rewardClass, legalActClass):
if not isinstance(rewardClass, type):
raise Grid2OpException(
"Parameter \"rewardClass\" used to build the Environment should be a type (a class) "
"and not an object (an instance of a class). "
"It is currently \"{}\"".format(type(rewardClass)))
if not issubclass(rewardClass, Reward):
raise Grid2OpException(
"Parameter \"rewardClass\" used to build the Environment should derived form the grid2op.Reward class, "
"type provided is \"{}\"".format(type(rewardClass)))
self.rewardClass = rewardClass
self.actionClass = actionClass
self.observationClass = observationClass
# backend
self.init_grid_path = os.path.abspath(init_grid_path)
if not isinstance(backend, Backend):
raise Grid2OpException(
"Parameter \"backend\" used to build the Environment should derived form the grid2op.Backend class, "
"type provided is \"{}\"".format(type(backend)))
self.backend = backend
self.backend.load_grid(
self.init_grid_path) # the real powergrid of the environment
self.backend.load_redispacthing_data(
os.path.split(self.init_grid_path)[0])
self.backend.assert_grid_correct()
self.init_grid(backend)
self._has_been_initialized()
if self._thermal_limit_a is None:
self._thermal_limit_a = self.backend.thermal_limit_a
else:
self.backend.set_thermal_limit(self._thermal_limit_a)
*_, tmp = self.backend.generators_info()
# rules of the game
if not isinstance(legalActClass, type):
raise Grid2OpException(
"Parameter \"legalActClass\" used to build the Environment should be a type "
"(a class) and not an object (an instance of a class). "
"It is currently \"{}\"".format(type(legalActClass)))
if not issubclass(legalActClass, LegalAction):
raise Grid2OpException(
"Parameter \"legalActClass\" used to build the Environment should derived form the "
"grid2op.LegalAction class, type provided is \"{}\"".format(
type(legalActClass)))
self.game_rules = GameRules(legalActClass=legalActClass)
self.legalActClass = legalActClass
# action helper
if not isinstance(actionClass, type):
raise Grid2OpException(
"Parameter \"actionClass\" used to build the Environment should be a type (a class) "
"and not an object (an instance of a class). "
"It is currently \"{}\"".format(type(legalActClass)))
if not issubclass(actionClass, Action):
raise Grid2OpException(
"Parameter \"actionClass\" used to build the Environment should derived form the "
"grid2op.Action class, type provided is \"{}\"".format(
type(actionClass)))
if not isinstance(observationClass, type):
raise Grid2OpException(
"Parameter \"actionClass\" used to build the Environment should be a type (a class) "
"and not an object (an instance of a class). "
"It is currently \"{}\"".format(type(legalActClass)))
if not issubclass(observationClass, Observation):
raise Grid2OpException(
"Parameter \"observationClass\" used to build the Environment should derived form the "
"grid2op.Observation class, type provided is \"{}\"".format(
type(observationClass)))
# action affecting the grid that will be made by the agent
self.helper_action_player = HelperAction(
gridobj=self.backend,
actionClass=actionClass,
legal_action=self.game_rules.legal_action)
# action that affect the grid made by the environment.
self.helper_action_env = HelperAction(
gridobj=self.backend,
actionClass=Action,
legal_action=self.game_rules.legal_action)
self.helper_observation = ObservationHelper(
gridobj=self.backend,
observationClass=observationClass,
rewardClass=rewardClass,
env=self)
# handles input data
if not isinstance(chronics_handler, ChronicsHandler):
raise Grid2OpException(
"Parameter \"chronics_handler\" used to build the Environment should derived form the "
"grid2op.ChronicsHandler class, type provided is \"{}\"".
format(type(chronics_handler)))
self.chronics_handler = chronics_handler
self.chronics_handler.initialize(
self.name_load,
self.name_gen,
self.name_line,
self.name_sub,
names_chronics_to_backend=names_chronics_to_backend)
self.names_chronics_to_backend = names_chronics_to_backend
# test to make sure the backend is consistent with the chronics generator
self.chronics_handler.check_validity(self.backend)
# reward function
self.reward_helper = RewardHelper(rewardClass=rewardClass)
self.reward_helper.initialize(self)
# controler for voltage
if not issubclass(self.voltagecontrolerClass, ControlVoltageFromFile):
raise Grid2OpException(
"Parameter \"voltagecontrolClass\" should derive from \"ControlVoltageFromFile\"."
)
self.voltage_controler = self.voltagecontrolerClass(
gridobj=self.backend, controler_backend=self.backend)
# performs one step to load the environment properly (first action need to be taken at first time step after
# first injections given)
self._reset_maintenance()
do_nothing = self.helper_action_env({})
*_, fail_to_start, _ = self.step(do_nothing)
if fail_to_start:
raise Grid2OpException(
"Impossible to initialize the powergrid, the powerflow diverge at iteration 0."
)
# test the backend returns object of the proper size
self.backend.assert_grid_correct_after_powerflow()
# for gym compatibility
self.action_space = self.helper_action_player # this should be an action !!!
self.observation_space = self.helper_observation # this return an observation.
self.reward_range = self.reward_helper.range()
self.viewer = None
self.metadata = {'render.modes': ["human", "rgb_array"]}
self.spec = None
self.current_reward = self.reward_range[0]
self.done = False
self._reset_vectors_and_timings()
def __init__(self,
init_grid_path: str,
chronics_handler,
backend,
parameters,
names_chronics_to_backend=None,
actionClass=TopologyAction,
observationClass=CompleteObservation,
rewardClass=FlatReward,
legalActClass=AllwaysLegal):
"""
Initialize the environment. See the descirption of :class:`grid2op.Environment.Environment` for more information.
Parameters
----------
init_grid_path: ``str``
Used to initailize :attr:`Environment.init_grid_path`
chronics_handler
backend
parameters
names_chronics_to_backend
actionClass
observationClass
rewardClass
legalActClass
"""
# TODO documentation!!
# some timers
self._time_apply_act = 0
self._time_powerflow = 0
self._time_extract_obs = 0
# define logger
self.logger = None
# and calendar data
self.time_stamp = None
self.nb_time_step = 0
# specific to power system
if not isinstance(parameters, Parameters):
raise Grid2OpException(
"Parameter \"parameters\" used to build the Environment should derived form the "
"grid2op.Parameters class, type provided is \"{}\"".format(
type(parameters)))
self.parameters = parameters
if not isinstance(rewardClass, type):
raise Grid2OpException(
"Parameter \"rewardClass\" used to build the Environment should be a type (a class) "
"and not an object (an instance of a class). "
"It is currently \"{}\"".format(type(rewardClass)))
if not issubclass(rewardClass, Reward):
raise Grid2OpException(
"Parameter \"rewardClass\" used to build the Environment should derived form the grid2op.Reward class, "
"type provided is \"{}\"".format(type(rewardClass)))
self.rewardClass = rewardClass
# backend
self.init_grid_path = os.path.abspath(init_grid_path)
if not isinstance(backend, Backend):
raise Grid2OpException(
"Parameter \"backend\" used to build the Environment should derived form the grid2op.Backend class, "
"type provided is \"{}\"".format(type(backend)))
self.backend = backend
self.backend.load_grid(
self.init_grid_path) # the real powergrid of the environment
self.backend.assert_grid_correct()
*_, tmp = self.backend.generators_info()
# rules of the game
if not isinstance(legalActClass, type):
raise Grid2OpException(
"Parameter \"legalActClass\" used to build the Environment should be a type "
"(a class) and not an object (an instance of a class). "
"It is currently \"{}\"".format(type(legalActClass)))
if not issubclass(legalActClass, LegalAction):
raise Grid2OpException(
"Parameter \"legalActClass\" used to build the Environment should derived form the "
"grid2op.LegalAction class, type provided is \"{}\"".format(
type(legalActClass)))
self.game_rules = GameRules(legalActClass=legalActClass)
# action helper
if not isinstance(actionClass, type):
raise Grid2OpException(
"Parameter \"actionClass\" used to build the Environment should be a type (a class) "
"and not an object (an instance of a class). "
"It is currently \"{}\"".format(type(legalActClass)))
if not issubclass(actionClass, Action):
raise Grid2OpException(
"Parameter \"actionClass\" used to build the Environment should derived form the "
"grid2op.Action class, type provided is \"{}\"".format(
type(actionClass)))
if not isinstance(observationClass, type):
raise Grid2OpException(
"Parameter \"actionClass\" used to build the Environment should be a type (a class) "
"and not an object (an instance of a class). "
"It is currently \"{}\"".format(type(legalActClass)))
if not issubclass(observationClass, Observation):
raise Grid2OpException(
"Parameter \"observationClass\" used to build the Environment should derived form the "
"grid2op.Observation class, type provided is \"{}\"".format(
type(observationClass)))
# action affecting the _grid that will be made by the agent
self.helper_action_player = HelperAction(gridobj=self.backend,
actionClass=actionClass,
game_rules=self.game_rules)
# action that affect the _grid made by the environment.
self.helper_action_env = HelperAction(gridobj=self.backend,
actionClass=Action,
game_rules=self.game_rules)
self.helper_observation = ObservationHelper(
gridobj=self.backend,
observationClass=observationClass,
rewardClass=rewardClass,
env=self)
# observation
self.current_obs = None
# type of power flow to play
# if True, then it will not disconnect lines above their thermal limits
self.no_overflow_disconnection = self.parameters.NO_OVERFLOW_DISCONNECTION
self.timestep_overflow = np.zeros(shape=(self.backend.n_line, ),
dtype=np.int)
self.nb_timestep_overflow_allowed = np.full(
shape=(self.backend.n_line, ),
fill_value=self.parameters.NB_TIMESTEP_POWERFLOW_ALLOWED)
# store actions "cooldown"
self.times_before_line_status_actionable = np.zeros(
shape=(self.backend.n_line, ), dtype=np.int)
self.max_timestep_line_status_deactivated = self.parameters.NB_TIMESTEP_LINE_STATUS_REMODIF
self.times_before_topology_actionable = np.zeros(
shape=(self.backend.n_sub, ), dtype=np.int)
self.max_timestep_topology_deactivated = self.parameters.NB_TIMESTEP_TOPOLOGY_REMODIF
# for maintenance operation
self.time_next_maintenance = np.zeros(shape=(self.backend.n_line, ),
dtype=np.int) - 1
self.duration_next_maintenance = np.zeros(
shape=(self.backend.n_line, ), dtype=np.int)
# hazard (not used outside of this class, information is given in `time_remaining_before_line_reconnection`
self._hazard_duration = np.zeros(shape=(self.backend.n_line, ),
dtype=np.int)
# hard overflow part
self.hard_overflow_threshold = self.parameters.HARD_OVERFLOW_THRESHOLD
self.time_remaining_before_line_reconnection = np.full(
shape=(self.backend.n_line, ), fill_value=0, dtype=np.int)
self.env_dc = self.parameters.ENV_DC
# handles input data
if not isinstance(chronics_handler, ChronicsHandler):
raise Grid2OpException(
"Parameter \"chronics_handler\" used to build the Environment should derived form the "
"grid2op.ChronicsHandler class, type provided is \"{}\"".
format(type(chronics_handler)))
self.chronics_handler = chronics_handler
self.chronics_handler.initialize(
self.backend.name_load,
self.backend.name_gen,
self.backend.name_line,
self.backend.name_sub,
names_chronics_to_backend=names_chronics_to_backend)
self.names_chronics_to_backend = names_chronics_to_backend
# test to make sure the backend is consistent with the chronics generator
self.chronics_handler.check_validity(self.backend)
# store environment modifications
self._injection = None
self._maintenance = None
self._hazards = None
self.env_modification = None
# reward
self.reward_helper = RewardHelper(rewardClass=rewardClass)
self.reward_helper.initialize(self)
# performs one step to load the environment properly (first action need to be taken at first time step after
# first injections given)
self._reset_maintenance()
do_nothing = self.helper_action_env({})
*_, fail_to_start, _ = self.step(do_nothing)
if fail_to_start:
raise Grid2OpException(
"Impossible to initialize the powergrid, the powerflow diverge at iteration 0."
)
# test the backend returns object of the proper size
self.backend.assert_grid_correct_after_powerflow()
# for gym compatibility
self.action_space = self.helper_action_player # this should be an action !!!
self.observation_space = self.helper_observation # this return an observation.
self.reward_range = self.reward_helper.range()
self.viewer = None
self.metadata = {'render.modes': []}
self.spec = None
self._reset_vectors_and_timings()
def setUp(self):
"""
The case file is a representation of the case14 as found in the ieee14 powergrid.
:return:
"""
self.tolvect = 1e-2
self.tol_one = 1e-5
self.game_rules = GameRules()
self.gridobj = GridObjects()
self.gridobj.init_grid_vect(
name_prod=["gen_{}".format(i) for i in range(5)],
name_load=["load_{}".format(i) for i in range(11)],
name_line=["line_{}".format(i) for i in range(20)],
name_sub=["sub_{}".format(i) for i in range(14)],
sub_info=np.array([3, 6, 4, 6, 5, 6, 3, 2, 5, 3, 3, 3, 4, 3],
dtype=np.int),
load_to_subid=np.array([1, 2, 3, 4, 5, 8, 9, 10, 11, 12, 13]),
gen_to_subid=np.array([0, 1, 2, 5, 7]),
line_or_to_subid=np.array(
[0, 0, 1, 1, 1, 2, 3, 3, 3, 4, 5, 5, 5, 6, 6, 8, 8, 9, 11,
12]),
line_ex_to_subid=np.array([
1, 4, 2, 3, 4, 3, 4, 6, 8, 5, 10, 11, 12, 7, 8, 9, 13, 10, 12,
13
]), #####
load_to_sub_pos=np.array([4, 2, 5, 4, 4, 4, 1, 1, 1, 2, 1]),
gen_to_sub_pos=np.array([2, 5, 3, 5, 1]),
line_or_to_sub_pos=np.array(
[0, 1, 1, 2, 3, 1, 2, 3, 4, 3, 1, 2, 3, 1, 2, 2, 3, 0, 0, 1]),
line_ex_to_sub_pos=np.array(
[0, 0, 0, 0, 1, 1, 2, 0, 0, 0, 2, 2, 3, 0, 1, 2, 2, 0, 0,
0]), #####
load_pos_topo_vect=np.array(
[7, 11, 18, 23, 28, 39, 41, 44, 47, 51, 54]),
gen_pos_topo_vect=np.array([2, 8, 12, 29, 34]),
line_or_pos_topo_vect=np.array([
0, 1, 4, 5, 6, 10, 15, 16, 17, 22, 25, 26, 27, 31, 32, 37, 38,
40, 46, 50
]),
line_ex_pos_topo_vect=np.array([
3, 19, 9, 13, 20, 14, 21, 30, 35, 24, 45, 48, 52, 33, 36, 42,
55, 43, 49, 53
]))
# pdb.set_trace()
self.helper_action = HelperAction(
self.gridobj, legal_action=self.game_rules.legal_action)
self.helper_action_env = HelperAction(
self.gridobj,
legal_action=self.game_rules.legal_action,
actionClass=Action)
self.res = {
'name_gen': ['gen_0', 'gen_1', 'gen_2', 'gen_3', 'gen_4'],
'name_load': [
'load_0', 'load_1', 'load_2', 'load_3', 'load_4', 'load_5',
'load_6', 'load_7', 'load_8', 'load_9', 'load_10'
],
'name_line': [
'line_0', 'line_1', 'line_2', 'line_3', 'line_4', 'line_5',
'line_6', 'line_7', 'line_8', 'line_9', 'line_10', 'line_11',
'line_12', 'line_13', 'line_14', 'line_15', 'line_16',
'line_17', 'line_18', 'line_19'
],
'name_sub': [
'sub_0', 'sub_1', 'sub_2', 'sub_3', 'sub_4', 'sub_5', 'sub_6',
'sub_7', 'sub_8', 'sub_9', 'sub_10', 'sub_11', 'sub_12',
'sub_13'
],
'sub_info': [3, 6, 4, 6, 5, 6, 3, 2, 5, 3, 3, 3, 4, 3],
'load_to_subid': [1, 2, 3, 4, 5, 8, 9, 10, 11, 12, 13],
'gen_to_subid': [0, 1, 2, 5, 7],
'line_or_to_subid':
[0, 0, 1, 1, 1, 2, 3, 3, 3, 4, 5, 5, 5, 6, 6, 8, 8, 9, 11, 12],
'line_ex_to_subid': [
1, 4, 2, 3, 4, 3, 4, 6, 8, 5, 10, 11, 12, 7, 8, 9, 13, 10, 12,
13
],
'load_to_sub_pos': [4, 2, 5, 4, 4, 4, 1, 1, 1, 2, 1],
'gen_to_sub_pos': [2, 5, 3, 5, 1],
'line_or_to_sub_pos':
[0, 1, 1, 2, 3, 1, 2, 3, 4, 3, 1, 2, 3, 1, 2, 2, 3, 0, 0, 1],
'line_ex_to_sub_pos':
[0, 0, 0, 0, 1, 1, 2, 0, 0, 0, 2, 2, 3, 0, 1, 2, 2, 0, 0, 0],
'load_pos_topo_vect': [7, 11, 18, 23, 28, 39, 41, 44, 47, 51, 54],
'gen_pos_topo_vect': [2, 8, 12, 29, 34],
'line_or_pos_topo_vect': [
0, 1, 4, 5, 6, 10, 15, 16, 17, 22, 25, 26, 27, 31, 32, 37, 38,
40, 46, 50
],
'line_ex_pos_topo_vect': [
3, 19, 9, 13, 20, 14, 21, 30, 35, 24, 45, 48, 52, 33, 36, 42,
55, 43, 49, 53
],
'gen_type':
None,
'gen_pmin':
None,
'gen_pmax':
None,
'gen_redispatchable':
None,
'gen_max_ramp_up':
None,
'gen_max_ramp_down':
None,
'gen_min_uptime':
None,
'gen_min_downtime':
None,
'gen_cost_per_MW':
None,
'gen_startup_cost':
None,
'gen_shutdown_cost':
None,
'subtype':
'Action.Action'
}
self.size_act = 229
def setUp(self):
"""
The case file is a representation of the case14 as found in the ieee14 powergrid.
:return:
"""
# from ADNBackend import ADNBackend
# self.backend = ADNBackend()
# self.path_matpower = "/home/donnotben/Documents/RL4Grid/RL4Grid/data"
# self.case_file = "ieee14_ADN.xml"
# self.backend.load_grid(self.path_matpower, self.case_file)
self.tolvect = 1e-2
self.tol_one = 1e-5
self.game_rules = GameRules()
self.gridobj = GridObjects()
self.gridobj.init_grid_vect(name_prod=["gen_{}".format(i) for i in range(5)],
name_load=["load_{}".format(i) for i in range(11)],
name_line=["line_{}".format(i) for i in range(20)],
name_sub=["sub_{}".format(i) for i in range(14)],
sub_info=np.array([3, 6, 4, 6, 5, 6, 3, 2, 5, 3, 3, 3, 4, 3], dtype=np.int),
load_to_subid=np.array([1, 2, 3, 4, 5, 8, 9, 10, 11, 12, 13]),
gen_to_subid=np.array([0, 1, 2, 5, 7]),
line_or_to_subid=np.array([ 0, 0, 1, 1, 1, 2, 3, 3, 3, 4, 5, 5,
5, 6, 6, 8, 8, 9, 11, 12]),
line_ex_to_subid=np.array([ 1, 4, 2, 3, 4, 3, 4, 6, 8, 5, 10, 11,
12, 7, 8, 9, 13, 10, 12, 13]), #####
load_to_sub_pos=np.array([4, 2, 5, 4, 4, 4, 1, 1, 1, 2, 1]),
gen_to_sub_pos=np.array([2, 5, 3, 5, 1]),
line_or_to_sub_pos=np.array([0, 1, 1, 2, 3, 1, 2, 3, 4, 3, 1, 2, 3, 1, 2, 2,
3, 0, 0, 1]),
line_ex_to_sub_pos=np.array([0, 0, 0, 0, 1, 1, 2, 0, 0, 0, 2, 2, 3, 0, 1, 2, 2, 0, 0, 0]), #####
load_pos_topo_vect=np.array([ 7, 11, 18, 23, 28, 39, 41, 44, 47, 51, 54]),
gen_pos_topo_vect=np.array([ 2, 8, 12, 29, 34]),
line_or_pos_topo_vect=np.array([ 0, 1, 4, 5, 6, 10, 15, 16, 17, 22, 25, 26, 27, 31, 32, 37, 38, 40, 46, 50]),
line_ex_pos_topo_vect=np.array([ 3, 19, 9, 13, 20, 14, 21, 30, 35, 24, 45, 48, 52, 33, 36, 42, 55, 43, 49, 53]))
# pdb.set_trace()
self.helper_action = HelperAction(self.gridobj,
game_rules=self.game_rules)
self.helper_action_env = HelperAction(self.gridobj,
game_rules=self.game_rules,
actionClass=Action)
self.res = {'name_gen': ['gen_0', 'gen_1', 'gen_2', 'gen_3', 'gen_4'],
'name_load': ['load_0', 'load_1', 'load_2', 'load_3', 'load_4', 'load_5', 'load_6',
'load_7', 'load_8', 'load_9', 'load_10'],
'name_line': ['line_0', 'line_1', 'line_2', 'line_3', 'line_4', 'line_5', 'line_6', 'line_7',
'line_8', 'line_9', 'line_10', 'line_11', 'line_12', 'line_13', 'line_14', 'line_15',
'line_16', 'line_17', 'line_18', 'line_19'],
'name_sub': ["sub_0", "sub_1", "sub_2", "sub_3", "sub_4", "sub_5", "sub_6", "sub_7", "sub_8", "sub_9",
"sub_10", "sub_11", "sub_12", "sub_13"],
'sub_info': [3, 6, 4, 6, 5, 6, 3, 2, 5, 3, 3, 3, 4, 3],
'load_to_subid': [1, 2, 3, 4, 5, 8, 9, 10, 11, 12, 13],
'gen_to_subid': [0, 1, 2, 5, 7],
'line_or_to_subid': [0, 0, 1, 1, 1, 2, 3, 3, 3, 4, 5, 5, 5, 6, 6, 8, 8, 9, 11, 12],
'line_ex_to_subid': [1, 4, 2, 3, 4, 3, 4, 6, 8, 5, 10, 11, 12, 7, 8, 9, 13, 10, 12, 13],
'load_to_sub_pos': [4, 2, 5, 4, 4, 4, 1, 1, 1, 2, 1], 'gen_to_sub_pos': [2, 5, 3, 5, 1],
'line_or_to_sub_pos': [0, 1, 1, 2, 3, 1, 2, 3, 4, 3, 1, 2, 3, 1, 2, 2, 3, 0, 0, 1],
'line_ex_to_sub_pos': [0, 0, 0, 0, 1, 1, 2, 0, 0, 0, 2, 2, 3, 0, 1, 2, 2, 0, 0, 0],
'load_pos_topo_vect': [7, 11, 18, 23, 28, 39, 41, 44, 47, 51, 54],
'gen_pos_topo_vect': [2, 8, 12, 29, 34],
'line_or_pos_topo_vect': [0, 1, 4, 5, 6, 10, 15, 16, 17, 22, 25, 26, 27, 31, 32, 37, 38, 40, 46, 50],
'line_ex_pos_topo_vect': [3, 19, 9, 13, 20, 14, 21, 30, 35, 24, 45, 48, 52, 33, 36, 42, 55, 43, 49, 53],
'subtype': 'Action.Action'}
def _action_env_setup(self):
return HelperAction(self.gridobj, legal_action=self.game_rules.legal_action, actionClass=PowerLineSet)
def _action_env_setup(self):
return HelperAction(self.gridobj, legal_action=self.game_rules.legal_action, actionClass=TopoAndRedispAction)