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test_ts_handlers.py
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test_ts_handlers.py
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# Copyright (c) 2019-2023, RTE (https://www.rte-france.com)
# See AUTHORS.txt
# This Source Code Form is subject to the terms of the Mozilla Public License, version 2.0.
# If a copy of the Mozilla Public License, version 2.0 was not distributed with this file,
# you can obtain one at http://mozilla.org/MPL/2.0/.
# SPDX-License-Identifier: MPL-2.0
# This file is part of Grid2Op, Grid2Op a testbed platform to model sequential decision making in power systems.
import copy
import pdb
import time
import warnings
from grid2op.tests.helper_path_test import *
import grid2op
from grid2op.Exceptions import NoForecastAvailable
from grid2op.Chronics import GridStateFromFileWithForecasts, GridStateFromFile, GridStateFromFileWithForecastsWithoutMaintenance, FromHandlers
from grid2op.Chronics.handlers import (CSVHandler,
DoNothingHandler,
CSVForecastHandler,
CSVMaintenanceHandler,
JSONMaintenanceHandler,
PersistenceForecastHandler,
PerfectForecastHandler,
NoisyForecastHandler,
LoadQFromPHandler
)
from grid2op.Runner import Runner
from grid2op.Exceptions import HandlerError
from grid2op.Parameters import Parameters
import warnings
# TODO check when there is also redispatching
def _load_next_chunk_in_memory_hack(self):
self._nb_call += 1
# i load the next chunk as dataframes
array = self._get_next_chunk() # array: load_p
# i put these dataframes in the right order (columns)
self._init_attrs(array) # TODO
# i don't forget to reset the reading index to 0
self.current_index = 0
class TestCSVHandlerEnv(HelperTests):
"""test the env part of the storage functionality"""
def _aux_assert_right_type_chronics(self):
assert isinstance(self.env1.chronics_handler.real_data.data, GridStateFromFile)
assert isinstance(self.env2.chronics_handler.real_data.data, FromHandlers)
def _aux_reproducibility(self):
for env in [self.env1, self.env2]:
env.set_id(0)
env.seed(0)
env.reset()
self._aux_assert_right_type_chronics()
def setUp(self) -> None:
with warnings.catch_warnings():
warnings.filterwarnings("ignore")
self.env1 = grid2op.make("l2rpn_case14_sandbox", test=True) # regular env
self.env2 = grid2op.make("l2rpn_case14_sandbox",
data_feeding_kwargs={"gridvalueClass": FromHandlers,
"gen_p_handler": CSVHandler("prod_p"),
"load_p_handler": CSVHandler("load_p"),
"gen_v_handler": CSVHandler("prod_v"),
"load_q_handler": CSVHandler("load_q"),
},
_add_to_name="_TestCSVHandlerEnv",
test=True) # regular env
self._aux_reproducibility()
return super().setUp()
def tearDown(self) -> None:
self.env1.close()
self.env2.close()
return super().tearDown()
def _aux_compare_one(self, it_nm, obs1, obs2, descr=""):
for attr_nm in ["load_p", "load_q", "gen_v", "rho", "gen_p", "line_status", "time_next_maintenance"]:
# assert np.all(getattr(obs1, attr_nm) == getattr(obs2, attr_nm)), f"error for {attr_nm}{descr} at iteration {it_nm}: {getattr(obs1, attr_nm)} vs {getattr(obs2, attr_nm)}"
assert np.allclose(getattr(obs1, attr_nm), getattr(obs2, attr_nm)), f"error for {attr_nm}{descr} at iteration {it_nm}: {getattr(obs1, attr_nm)} vs {getattr(obs2, attr_nm)}"
def _run_then_compare(self, nb_iter=10, env1=None, env2=None):
if env1 is None:
env1 = self.env1
if env2 is None:
env2 = self.env2
for k in range(nb_iter):
obs1, reward1, done1, info1 = env1.step(env1.action_space())
obs2, reward2, done2, info2 = env2.step(env2.action_space())
assert done2 == done1, f"error at iteration {k} for done"
assert reward1 == reward2, f"error at iteration {k} for reward"
if done1:
break
self._aux_compare_one(k, obs1, obs2)
def test_step_equal(self):
self._run_then_compare()
self.env1.reset()
self.env2.reset()
self._run_then_compare()
self.env1.reset()
self.env2.reset()
self._run_then_compare()
def test_max_iter(self):
self.env1.set_max_iter(5)
self.env2.set_max_iter(5)
self.env1.reset()
self.env2.reset()
self._run_then_compare(nb_iter=4)
obs1, reward1, done1, info1 = self.env1.step(self.env1.action_space())
obs2, reward2, done2, info2 = self.env2.step(self.env2.action_space())
assert done1
assert done2
def test_chunk(self):
self.env_ref = self.env1.copy()
self.env1.set_chunk_size(1)
self.env2.set_chunk_size(1)
# hugly copy paste from above otherwise the hack does not work...
# because of the reset
self.env1.set_max_iter(5)
self.env2.set_max_iter(5)
self.env_ref.set_max_iter(5)
obs1 = self.env1.reset()
obs2 = self.env2.reset()
self.env_ref.reset()
self._aux_compare_one(0, obs1, obs2)
###### hack to count the number this is called
if hasattr(self.env2.chronics_handler.real_data, "data"):
self.env2.chronics_handler.data.gen_p_handler._nb_call = 0
self.env2.chronics_handler.data.gen_p_handler._load_next_chunk_in_memory = lambda : _load_next_chunk_in_memory_hack(self.env2.chronics_handler.data.gen_p_handler)
else:
self.env2.chronics_handler.gen_p_handler._nb_call = 0
self.env2.chronics_handler.gen_p_handler._load_next_chunk_in_memory = lambda : _load_next_chunk_in_memory_hack(self.env2.chronics_handler.gen_p_handler)
######
self._run_then_compare(nb_iter=4)
obs1, reward1, done1, info1 = self.env1.step(self.env1.action_space())
obs2, reward2, done2, info2 = self.env2.step(self.env2.action_space())
assert done1
assert done2
# now check the "load_next_chunk has been called the right number of time"
if hasattr(self.env2.chronics_handler.real_data, "data"):
assert self.env2.chronics_handler.data.gen_p_handler._nb_call == 5
else:
assert self.env2.chronics_handler.gen_p_handler._nb_call == 5
def test_copy(self):
env2 = self.env2.copy()
self._run_then_compare(env2=env2)
self.env1.reset()
env2.reset()
self._run_then_compare(env2=env2)
self.env1.reset()
env2.reset()
self._run_then_compare(env2=env2)
def test_runner(self):
runner1 = Runner(**self.env1.get_params_for_runner())
runner2 = Runner(**self.env2.get_params_for_runner())
res1 = runner1.run(nb_episode=2, max_iter=5, env_seeds=[0, 1], episode_id=[0, 1])
res2 = runner2.run(nb_episode=2, max_iter=5, env_seeds=[0, 1], episode_id=[0, 1])
assert res1 == res2
def test_if_file_absent(self):
# do it only once
if type(self) != TestCSVHandlerEnv:
self.skipTest("This test should be done only in the TestCSVHandlerEnv class (no need to do it 10x times)")
with self.assertRaises(HandlerError):
grid2op.make(os.path.join(PATH_DATA_TEST, "5bus_example_some_missing"),
data_feeding_kwargs={"gridvalueClass": FromHandlers,
"gen_p_handler": CSVHandler("prod_p"),
"load_p_handler": CSVHandler("load_p"),
"gen_v_handler": DoNothingHandler(),
"load_q_handler": CSVHandler("load_q"), # crash because this file does not exist
},
_add_to_name="_TestCSVHandlerEnv") # regular env
def test_max_episode_duration(self):
assert self.env2.max_episode_duration() == self.env1.max_episode_duration()
self.env1.reset()
self.env2.reset()
assert self.env2.max_episode_duration() == self.env1.max_episode_duration()
self.env1.set_max_iter(5)
self.env2.set_max_iter(5)
self.env1.reset()
self.env2.reset()
assert self.env2.max_episode_duration() == self.env1.max_episode_duration()
self.env1.set_chunk_size(1)
self.env2.set_chunk_size(1)
self.env1.reset()
self.env2.reset()
assert self.env2.max_episode_duration() == self.env1.max_episode_duration()
def test_fast_forward_chronics(self):
self.env1.fast_forward_chronics(5)
self.env2.fast_forward_chronics(5)
self._run_then_compare()
self.env1.fast_forward_chronics(7)
self.env2.fast_forward_chronics(7)
self._run_then_compare()
self.env1.reset()
self.env2.reset()
self._run_then_compare()
# TODO:
# test when "names_chronics_to_backend"
# test sample_next_chronics
# test I can "finish" an environment completely (without max_iter, when data are over)
# test multifolderwithCache
# test without "multi folder" X
# test runner X
# test env copy X
# test when max_iter `env.set_max_iter` X
# test when "set_chunk" X
# test with forecasts
# test next_chronics
# test tell_id
# test set_id
# test with maintenance
# test fast_forward_chronics
class TestSomeFileMissingEnv(TestCSVHandlerEnv):
"""test the env part of the storage functionality"""
def setUp(self) -> None:
with warnings.catch_warnings():
warnings.filterwarnings("ignore")
self.env1 = grid2op.make(os.path.join(PATH_DATA_TEST, "5bus_example_some_missing")) # regular env
self.env2 = grid2op.make(os.path.join(PATH_DATA_TEST, "5bus_example_some_missing"),
data_feeding_kwargs={"gridvalueClass": FromHandlers,
"gen_p_handler": CSVHandler("prod_p"),
"load_p_handler": CSVHandler("load_p"),
"gen_v_handler": DoNothingHandler(),
"load_q_handler": DoNothingHandler(),
},
_add_to_name="_TestDNHandlerEnv")
self._aux_reproducibility()
class TestWithoutMultiFolderEnv(TestCSVHandlerEnv):
def setUp(self) -> None:
chronics_path = os.path.join(PATH_DATA,
"l2rpn_case14_sandbox",
"chronics",
"0000")
with warnings.catch_warnings():
warnings.filterwarnings("ignore")
self.env1 = grid2op.make("l2rpn_case14_sandbox", test=True,
chronics_class=GridStateFromFileWithForecasts,
chronics_path=chronics_path) # regular env
self.env2 = grid2op.make("l2rpn_case14_sandbox",
chronics_class=FromHandlers,
data_feeding_kwargs={
"gen_p_handler": CSVHandler("prod_p"),
"load_p_handler": CSVHandler("load_p"),
"gen_v_handler": CSVHandler("prod_v"),
"load_q_handler": CSVHandler("load_q"),
},
chronics_path=chronics_path,
_add_to_name="TestWithoutMultiFolderEnv",
test=True)
self._aux_reproducibility()
def _aux_assert_right_type_chronics(self):
assert isinstance(self.env1.chronics_handler.real_data, GridStateFromFile)
assert isinstance(self.env2.chronics_handler.real_data, FromHandlers)
class TestForecastHandlerNoMultiFolder(TestWithoutMultiFolderEnv):
"""test the env part of the storage functionality"""
def setUp(self) -> None:
chronics_path = os.path.join(PATH_DATA,
"l2rpn_case14_sandbox",
"chronics",
"0000")
with warnings.catch_warnings():
warnings.filterwarnings("ignore")
self.env1 = grid2op.make("l2rpn_case14_sandbox", test=True,
chronics_class=GridStateFromFileWithForecasts,
chronics_path=chronics_path) # regular env
self.env2 = grid2op.make("l2rpn_case14_sandbox",
chronics_class=FromHandlers,
data_feeding_kwargs={"gen_p_handler": CSVHandler("prod_p"),
"load_p_handler": CSVHandler("load_p"),
"gen_v_handler": CSVHandler("prod_v"),
"load_q_handler": CSVHandler("load_q"),
"gen_p_for_handler": CSVForecastHandler("prod_p_forecasted"),
"load_p_for_handler": CSVForecastHandler("load_p_forecasted"),
"gen_v_for_handler": CSVForecastHandler("prod_v_forecasted"),
"load_q_for_handler": CSVForecastHandler("load_q_forecasted"),
},
chronics_path=chronics_path,
_add_to_name="TestForecastHandlerNoMulti14",
test=True)
self._aux_reproducibility()
assert np.all(self.env1.chronics_handler.real_data.load_p_forecast ==
self.env2.chronics_handler.real_data.load_p_for_handler.array)
def _aux_compare_one(self, it_nm, obs1, obs2):
super()._aux_compare_one(it_nm, obs1, obs2)
sim_obs1, *_ = obs1.simulate(self.env1.action_space())
sim_obs2, *_ = obs2.simulate(self.env1.action_space())
super()._aux_compare_one(it_nm, sim_obs1, sim_obs2, " forecast")
class TestForecastHandler14(TestCSVHandlerEnv):
def setUp(self) -> None:
with warnings.catch_warnings():
warnings.filterwarnings("ignore")
self.env1 = grid2op.make("l2rpn_case14_sandbox", test=True) # regular env
self.env2 = grid2op.make("l2rpn_case14_sandbox",
data_feeding_kwargs={"gridvalueClass": FromHandlers,
"gen_p_handler": CSVHandler("prod_p"),
"load_p_handler": CSVHandler("load_p"),
"gen_v_handler": CSVHandler("prod_v"),
"load_q_handler": CSVHandler("load_q"),
"gen_p_for_handler": CSVForecastHandler("prod_p_forecasted"),
"load_p_for_handler": CSVForecastHandler("load_p_forecasted"),
"gen_v_for_handler": CSVForecastHandler("prod_v_forecasted"),
"load_q_for_handler": CSVForecastHandler("load_q_forecasted"),
},
_add_to_name="TestForecastHandlerEnv",
test=True)
self._aux_reproducibility()
assert np.all(self.env1.chronics_handler.real_data.data.load_p_forecast ==
self.env2.chronics_handler.real_data.data.load_p_for_handler.array)
def _aux_compare_one(self, it_nm, obs1, obs2):
super()._aux_compare_one(it_nm, obs1, obs2)
sim_obs1, *_ = obs1.simulate(self.env1.action_space())
sim_obs2, *_ = obs2.simulate(self.env1.action_space())
super()._aux_compare_one(it_nm, sim_obs1, sim_obs2, " forecast")
class TestForecastHandler5MultiSteps(TestCSVHandlerEnv):
def setUp(self) -> None:
with warnings.catch_warnings():
warnings.filterwarnings("ignore")
self.env1 = grid2op.make(os.path.join(PATH_DATA_TEST, "5bus_example_forecasts"), test=True,
data_feeding_kwargs={"gridvalueClass": GridStateFromFileWithForecastsWithoutMaintenance},
) # regular env
self.env2 = grid2op.make(os.path.join(PATH_DATA_TEST, "5bus_example_forecasts"),
data_feeding_kwargs={"gridvalueClass": FromHandlers,
"gen_p_handler": CSVHandler("prod_p"),
"load_p_handler": CSVHandler("load_p"),
"load_q_handler": CSVHandler("load_q"),
"gen_v_handler": DoNothingHandler(),
"gen_p_for_handler": CSVForecastHandler("prod_p_forecasted"),
"load_p_for_handler": CSVForecastHandler("load_p_forecasted"),
"load_q_for_handler": CSVForecastHandler("load_q_forecasted"),
},
_add_to_name="TestForecastHandler5MultiSteps",
test=True)
self._aux_reproducibility()
assert np.all(self.env1.chronics_handler.real_data.data.load_p ==
self.env2.chronics_handler.real_data.data.load_p_handler.array)
assert np.all(self.env1.chronics_handler.real_data.data.load_p_forecast ==
self.env2.chronics_handler.real_data.data.load_p_for_handler.array)
assert np.all(self.env1.chronics_handler.real_data.data.prod_p ==
self.env2.chronics_handler.real_data.data.gen_p_handler.array)
assert np.all(self.env1.chronics_handler.real_data.data.prod_p_forecast ==
self.env2.chronics_handler.real_data.data.gen_p_for_handler.array)
def _aux_compare_one(self, it_nm, obs1, obs2):
super()._aux_compare_one(it_nm, obs1, obs2)
sim_obs1_1, *_ = obs1.simulate(self.env1.action_space())
sim_obs2_1, *_ = obs2.simulate(self.env1.action_space())
super()._aux_compare_one(it_nm, sim_obs1_1, sim_obs2_1, " forecast 1")
sim_obs1_2, *_ = sim_obs1_1.simulate(self.env1.action_space())
sim_obs2_2, *_ = sim_obs2_1.simulate(self.env1.action_space())
super()._aux_compare_one(it_nm, sim_obs1_2, sim_obs2_2, " forecast 2")
sim_obs1_3, *_ = sim_obs1_2.simulate(self.env1.action_space())
sim_obs2_3, *_ = sim_obs2_2.simulate(self.env1.action_space())
super()._aux_compare_one(it_nm, sim_obs1_3, sim_obs2_3, " forecast 3")
class TestMaintenanceCSV(TestForecastHandler14):
def setUp(self) -> None:
param = Parameters()
param.NO_OVERFLOW_DISCONNECTION = True
with warnings.catch_warnings():
warnings.filterwarnings("ignore")
self.env1 = grid2op.make(os.path.join(PATH_DATA_TEST, "env_14_test_maintenance"),
test=True,
param=param
) # regular env
self.env2 = grid2op.make(os.path.join(PATH_DATA_TEST, "env_14_test_maintenance"),
data_feeding_kwargs={"gridvalueClass": FromHandlers,
"gen_p_handler": CSVHandler("prod_p"),
"load_p_handler": CSVHandler("load_p"),
"load_q_handler": CSVHandler("load_q"),
"gen_v_handler": CSVHandler("prod_v"),
"maintenance_handler": CSVMaintenanceHandler(),
"gen_p_for_handler": CSVForecastHandler("prod_p_forecasted"),
"gen_v_for_handler": CSVForecastHandler("prod_v_forecasted"),
"load_p_for_handler": CSVForecastHandler("load_p_forecasted"),
"load_q_for_handler": CSVForecastHandler("load_q_forecasted"),
},
_add_to_name="TestMaintenanceCSV",
test=True,
param=param)
self._aux_reproducibility()
assert np.all(self.env1.chronics_handler.real_data.data.maintenance ==
self.env2.chronics_handler.real_data.data.maintenance_handler.array)
assert np.all(self.env1.chronics_handler.real_data.data.maintenance_time ==
self.env2.chronics_handler.real_data.data.maintenance_handler.maintenance_time)
assert np.all(self.env1.chronics_handler.real_data.data.maintenance_duration ==
self.env2.chronics_handler.real_data.data.maintenance_handler.maintenance_duration)
class TestMaintenanceJson(unittest.TestCase):
def setUp(self) -> None:
param = Parameters()
param.NO_OVERFLOW_DISCONNECTION = True
with warnings.catch_warnings():
warnings.filterwarnings("ignore")
self.env2 = grid2op.make(os.path.join(PATH_DATA_TEST, "ieee118_R2subgrid_wcci_test_maintenance"),
data_feeding_kwargs={"gridvalueClass": FromHandlers,
"gen_p_handler": CSVHandler("prod_p"),
"load_p_handler": CSVHandler("load_p"),
"load_q_handler": CSVHandler("load_q"),
"gen_v_handler": CSVHandler("prod_v"),
"maintenance_handler": JSONMaintenanceHandler(),
"gen_p_for_handler": CSVForecastHandler("prod_p_forecasted"),
"load_p_for_handler": CSVForecastHandler("load_p_forecasted"),
"load_q_for_handler": CSVForecastHandler("load_q_forecasted"),
},
_add_to_name="TestMaintenanceCSV",
test=True,
param=param)
# carefull here ! the "seed" mechanism does not work the same way between the two alternative.
# in the second case each "handler" get its own prng with a different seed. This is
# why you cannot compare directly the generated maintenance between the two env and why
# this does not inherit from TestCSVHandlerEnv
def tearDown(self) -> None:
self.env2.close()
return super().tearDown()
def test_seed(self):
self.env2.seed(0)
self.env2.reset()
all_ln_nm = np.zeros(type(self.env2).n_line, dtype=bool)
assert self.env2.chronics_handler.real_data.data.maintenance_handler.maintenance.sum() == 960
tmp_ = np.where(self.env2.chronics_handler.real_data.data.maintenance_handler.maintenance.any(axis=0))[0]
assert np.all(tmp_ == [ 0, 9, 14, 27, 45, 56])
all_ln_nm[tmp_] = True
self.env2.reset()
assert self.env2.chronics_handler.real_data.data.maintenance_handler.maintenance.sum() == 1248
tmp_ = np.where(self.env2.chronics_handler.real_data.data.maintenance_handler.maintenance.any(axis=0))[0]
assert np.all(tmp_ == [ 0, 13, 14, 18, 23, 27, 39, 45, 56])
all_ln_nm[tmp_] = True
self.env2.reset()
assert self.env2.chronics_handler.real_data.data.maintenance_handler.maintenance.sum() == 960
tmp_ = np.where(self.env2.chronics_handler.real_data.data.maintenance_handler.maintenance.any(axis=0))[0]
assert np.all(tmp_ == [13, 14, 23, 27, 45])
all_ln_nm[tmp_] = True
self.env2.reset()
assert self.env2.chronics_handler.real_data.data.maintenance_handler.maintenance.sum() == 672
tmp_ = np.where(self.env2.chronics_handler.real_data.data.maintenance_handler.maintenance.any(axis=0))[0]
assert np.all(tmp_ == [ 0, 9, 13, 18, 23, 56])
all_ln_nm[tmp_] = True
line_to_maintenance = self.env2.chronics_handler.real_data.data.maintenance_handler.dict_meta_data["line_to_maintenance"]
assert np.all(np.isin(type(self.env2).name_line[all_ln_nm], line_to_maintenance))
assert np.all(np.isin(line_to_maintenance, type(self.env2).name_line[all_ln_nm]))
class TestPersistenceHandler(unittest.TestCase):
def setUp(self) -> None:
hs_ = [5*(i+1) for i in range(12)]
with warnings.catch_warnings():
warnings.filterwarnings("ignore")
self.env = grid2op.make("l2rpn_case14_sandbox",
data_feeding_kwargs={"gridvalueClass": FromHandlers,
"gen_p_handler": CSVHandler("prod_p"),
"load_p_handler": CSVHandler("load_p"),
"gen_v_handler": CSVHandler("prod_v"),
"load_q_handler": CSVHandler("load_q"),
"h_forecast": hs_,
"gen_p_for_handler": PersistenceForecastHandler("prod_p_forecasted"),
"load_p_for_handler": PersistenceForecastHandler("load_p_forecasted"),
"load_q_for_handler": PersistenceForecastHandler("load_q_forecasted"),
},
_add_to_name="TestPersistenceHandler",
test=True)
def tearDown(self) -> None:
self.env.close()
return super().tearDown()
def _aux_test_obs(self, obs, max_it=12):
assert len(obs._forecasted_inj) == 13 # 12 + 1
init_obj = obs._forecasted_inj[0]
for el in obs._forecasted_inj:
for k_ in ["load_p", "load_q"]:
assert np.all(el[1]["injection"][k_] == init_obj[1]["injection"][k_])
k_ = "prod_p" # because of slack...
assert np.all(el[1]["injection"][k_][:-1] == init_obj[1]["injection"][k_][:-1])
obs.simulate(self.env.action_space(), 12)
with self.assertRaises(NoForecastAvailable):
obs.simulate(self.env.action_space(), 13)
def test_step(self):
obs = self.env.reset()
self._aux_test_obs(obs)
obs, *_ = self.env.step(self.env.action_space())
self._aux_test_obs(obs)
obs = self.env.reset()
self._aux_test_obs(obs)
obs, *_ = self.env.step(self.env.action_space())
self._aux_test_obs(obs)
def test_fast_forward_chronics(self):
obs = self.env.reset()
self.env.fast_forward_chronics(5)
obs, *_ = self.env.step(self.env.action_space())
self._aux_test_obs(obs)
self.env.fast_forward_chronics(7)
obs, *_ = self.env.step(self.env.action_space())
self._aux_test_obs(obs)
def test_copy(self):
env_cpy = self.env.copy()
obs_cpy = env_cpy.reset()
obs = self.env.reset()
self._aux_test_obs(obs_cpy)
for el, el_cpy in zip(obs._forecasted_inj, obs_cpy._forecasted_inj):
for k_ in ["load_p", "load_q", "prod_p"]:
assert np.all(el[1]["injection"][k_] == el_cpy[1]["injection"][k_])
def test_runner(self):
from grid2op.Agent import BaseAgent
class TestAgent(BaseAgent):
def __init__(self, action_space, tester):
super().__init__(action_space)
self.tester = tester
def act(self, obs, reward, done=False):
self.tester._aux_test_obs(obs, max_it=5 - obs.current_step)
_ = self.tester.env.step(self.action_space()) # for TestPerfectForecastHandler: self.tester.env should be synch with the runner env...
return self.action_space()
def reset(self, obs):
self.tester.env.reset() # for TestPerfectForecastHandler
return super().reset(obs)
testagent = TestAgent(self.env.action_space, self)
self.env.set_id(0) # for TestPerfectForecastHandler
runner = Runner(**self.env.get_params_for_runner(), agentClass=None, agentInstance=testagent)
res = runner.run(nb_episode=2, episode_id=[0, 1], env_seeds=[2, 3], max_iter=5)
class TestPerfectForecastHandler(TestPersistenceHandler):
def setUp(self) -> None:
hs_ = [5*(i+1) for i in range(12)]
with warnings.catch_warnings():
warnings.filterwarnings("ignore")
self.env = grid2op.make("l2rpn_case14_sandbox",
data_feeding_kwargs={"gridvalueClass": FromHandlers,
"gen_p_handler": CSVHandler("prod_p"),
"load_p_handler": CSVHandler("load_p"),
"gen_v_handler": CSVHandler("prod_v"),
"load_q_handler": CSVHandler("load_q"),
"h_forecast": hs_,
"gen_p_for_handler": PerfectForecastHandler("prod_p_forecasted"),
"gen_v_for_handler": PerfectForecastHandler("prod_v_forecasted"),
"load_p_for_handler": PerfectForecastHandler("load_p_forecasted"),
"load_q_for_handler": PerfectForecastHandler("load_q_forecasted"),
},
_add_to_name="TestPerfectForecastHandler",
test=True)
def tearDown(self) -> None:
self.env.close()
def _aux_test_obs(self, obs, max_it=13):
assert len(obs._forecasted_inj) == 13 # 12 + 1
env_cpy = self.env.copy()
for it_num, el in enumerate(obs._forecasted_inj[1:]):
next_obs, *_ = env_cpy.step(self.env.action_space())
for k_ in ["load_p", "load_q", "prod_v"]:
assert np.allclose(el[1]["injection"][k_], getattr(next_obs, k_)), f"error for {k_} at iteration {it_num}"
k_ = "prod_p" # because of slack...
assert np.all(el[1]["injection"][k_][:-1] == getattr(next_obs, k_)[:-1])
if max_it > it_num:
break
obs.simulate(self.env.action_space(), 12)
with self.assertRaises(NoForecastAvailable):
obs.simulate(self.env.action_space(), 13)
class TestPerfectForecastHandler(unittest.TestCase):
def setUp(self) -> None:
hs_ = [5*(i+1) for i in range(12)]
with warnings.catch_warnings():
warnings.filterwarnings("ignore")
self.env = grid2op.make("l2rpn_case14_sandbox",
data_feeding_kwargs={"gridvalueClass": FromHandlers,
"gen_p_handler": CSVHandler("prod_p"),
"load_p_handler": CSVHandler("load_p"),
"gen_v_handler": CSVHandler("prod_v"),
"load_q_handler": CSVHandler("load_q"),
"h_forecast": hs_,
"gen_p_for_handler": NoisyForecastHandler("prod_p_forecasted"),
"load_p_for_handler": NoisyForecastHandler("load_p_forecasted"),
"load_q_for_handler": NoisyForecastHandler("load_q_forecasted"),
},
_add_to_name="TestPerfectForecastHandler",
test=True)
def tearDown(self) -> None:
self.env.close()
def _aux_obs_equal(self, obs1, obs2):
assert np.all(obs1.load_p == obs2.load_p)
assert np.all(obs1.load_q == obs2.load_q)
assert np.all(obs1.gen_p == obs2.gen_p)
assert np.all(obs1.rho == obs2.rho)
def test_seed(self):
self.env.set_id(0)
self.env.seed(0)
obs = self.env.reset()
sim_obs, *_ = obs.simulate(self.env.action_space(), 12)
# assert same results when called multiple times
sim_obs_, *_ = obs.simulate(self.env.action_space(), 12)
self._aux_obs_equal(sim_obs, sim_obs_)
# assert same results when env seeded
self.env.set_id(0)
self.env.seed(0)
obs2 = self.env.reset()
sim_obs2, *_ = obs2.simulate(self.env.action_space(), 12)
self._aux_obs_equal(sim_obs, sim_obs2)
# assert not the same when not seeded
obs3 = self.env.reset()
sim_obs3, *_ = obs3.simulate(self.env.action_space(), 12)
assert np.all(sim_obs3.load_p != sim_obs.load_p)
def test_get_list(self):
handler : NoisyForecastHandler = self.env.chronics_handler.real_data.data.gen_p_for_handler
# default behaviour
assert handler.sigma is None
assert np.allclose(handler._my_noise, [0.022360679774997897, 0.0316227766016838, 0.03872983346207417,
0.044721359549995794, 0.05, 0.05477225575051661, 0.05916079783099616,
0.0632455532033676, 0.0670820393249937, 0.07071067811865475,
0.07416198487095663, 0.07745966692414834])
# with a callable
handler.sigma = lambda x: x
handler.set_h_forecast(handler._h_forecast)
assert np.all(handler._my_noise == [5 * (i+1) for i in range(12)])
# with a complete list
handler.sigma = [6 * (i+1) for i in range(12)]
handler.set_h_forecast(handler._h_forecast)
assert np.all(handler._my_noise == handler.sigma)
# with a complete list
handler.sigma = [6 * (i+1) for i in range(12)]
handler.set_h_forecast(handler._h_forecast)
assert np.all(handler._my_noise == handler.sigma)
# with a complete list (too big)
handler.sigma = [6 * (i+1) for i in range(15)]
handler.set_h_forecast(handler._h_forecast)
assert np.all(handler._my_noise == handler.sigma)
# with a complete list (too short)
handler.sigma = [6 * (i+1) for i in range(10)]
with warnings.catch_warnings():
warnings.filterwarnings("ignore")
handler.set_h_forecast(handler._h_forecast)
assert np.all(handler._my_noise == (handler.sigma + [60., 60.]))
# with a complete list (too short)
# test that a warnings is issued
handler.sigma = [6 * (i+1) for i in range(10)]
with self.assertRaises(UserWarning):
with warnings.catch_warnings():
warnings.filterwarnings("error")
handler.set_h_forecast(handler._h_forecast)
class TestLoadQPHandler14(TestCSVHandlerEnv):
def setUp(self) -> None:
with warnings.catch_warnings():
warnings.filterwarnings("ignore")
self.env1 = grid2op.make(os.path.join(PATH_DATA_TEST, "l2rpn_case14_sandbox_qp_cste"),
test=True) # regular env
self.env2 = grid2op.make(os.path.join(PATH_DATA_TEST, "l2rpn_case14_sandbox_qp_cste"),
data_feeding_kwargs={"gridvalueClass": FromHandlers,
"gen_p_handler": CSVHandler("prod_p"),
"load_p_handler": CSVHandler("load_p"),
"gen_v_handler": CSVHandler("prod_v"),
"load_q_handler": LoadQFromPHandler("load_q"),
"gen_p_for_handler": CSVForecastHandler("prod_p_forecasted"),
"gen_v_for_handler": CSVForecastHandler("prod_v_forecasted"),
"load_p_for_handler": CSVForecastHandler("load_p_forecasted"),
"load_q_for_handler": LoadQFromPHandler("load_q_forecasted"),
},
_add_to_name="TestForecastHandlerEnv",
test=True)
self._aux_reproducibility()
if __name__ == "__main__":
unittest.main()