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test_issue_185.py
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test_issue_185.py
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# Copyright (c) 2019-2020, 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 unittest
import warnings
import os
from grid2op.tests.helper_path_test import *
import grid2op
from grid2op.gym_compat import (
GymEnv,
BoxGymActSpace,
BoxGymObsSpace,
MultiDiscreteActSpace,
DiscreteActSpace,
)
import pdb
ENV_WITH_ALARM_NAME = os.path.join(
PATH_DATA_TEST, "l2rpn_neurips_2020_track1_with_alarm"
)
class Issue185Tester(unittest.TestCase):
"""
this test ensure that every "test" environment can be converted to gym
this test suit goes beyond the simple error raised in the github issue.
"""
def get_list_env(self):
res = grid2op.list_available_test_env()
res.append(ENV_WITH_ALARM_NAME)
return res
def test_issue_185(self):
for env_name in self.get_list_env():
if env_name == "blank":
continue
with warnings.catch_warnings():
warnings.filterwarnings("ignore")
with grid2op.make(env_name, test=True) as env:
try:
gym_env = GymEnv(env)
# gym_env.seed(0)
# gym_env.observation_space.seed(0)
# gym_env.action_space.seed(0)
gym_env.action_space.seed(0)
obs_gym, *_ = gym_env.reset(seed=0) # reset and seed
assert (
obs_gym["a_ex"].shape[0] == env.n_line
), f"error for {env_name}"
# if obs_gym not in gym_env.observation_space:
for k in gym_env.observation_space.spaces.keys():
assert (
obs_gym[k] in gym_env.observation_space[k]
), f"error for {env_name}, for key={k}"
finally:
gym_env.close()
def test_issue_185_act_box_space(self):
for env_name in self.get_list_env():
if env_name == "blank":
continue
if env_name == "rte_case5_example":
# no action to perform for this env ! (no redispatch, curtail, storage)
continue
with warnings.catch_warnings():
warnings.filterwarnings("ignore")
with grid2op.make(env_name, test=True) as env:
try:
gym_env = GymEnv(env)
try:
gym_env.action_space = BoxGymActSpace(gym_env.init_env.action_space)
except Exception as exc_:
raise AssertionError(f"Error for {env_name}: {exc_}") from exc_
# gym_env.seed(0)
# gym_env.observation_space.seed(0)
# gym_env.action_space.seed(0)
gym_env.action_space.seed(0)
obs_gym, *_ = gym_env.reset(seed=0) # reset and seed
assert isinstance(obs_gym, dict), "probably a wrong gym version"
# "was_alert_used_after_attack"
# "was_alarm_used_after_game_over"
for key in gym_env.observation_space.keys():
assert key in obs_gym, f"error for {env_name} for {key}"
assert obs_gym[key] in gym_env.observation_space[key], f"error for {env_name} for {key}"
act = gym_env.action_space.sample()
assert act in gym_env.action_space, f"error for {env_name}"
obs, reward, done, truncated, info = gym_env.step(act)
assert isinstance(obs_gym, dict)
for key in gym_env.observation_space.keys():
assert key in obs_gym, f"error for {env_name} for {key}"
assert obs_gym[key] in gym_env.observation_space[key], f"error for {env_name} for {key}"
finally:
gym_env.close()
def test_issue_185_obs_box_space(self):
for env_name in self.get_list_env():
if env_name == "blank":
continue
# if env_name != "l2rpn_neurips_2020_track1":
# continue
with warnings.catch_warnings():
warnings.filterwarnings("ignore")
with grid2op.make(env_name, test=True) as env:
try:
gym_env = GymEnv(env)
gym_env.observation_space.close()
gym_env.observation_space = BoxGymObsSpace(
gym_env.init_env.observation_space
)
# gym_env.seed(0)
# gym_env.observation_space.seed(0)
# gym_env.action_space.seed(0)
gym_env.action_space.seed(0)
obs_gym, *_ = gym_env.reset(seed=0) # reset and seed
if obs_gym not in gym_env.observation_space:
raise AssertionError(f"error for {env_name}: \n{gym_env.observation_space.low}\n{obs_gym}\n{gym_env.observation_space.high}")
act = gym_env.action_space.sample()
assert act in gym_env.action_space, f"error for {env_name}"
obs, reward, done, truncated, info = gym_env.step(act)
if obs not in gym_env.observation_space:
raise AssertionError(f"error for {env_name}: \n{gym_env.observation_space.low}\n{obs}\n{gym_env.observation_space.high}")
finally:
gym_env.close()
def test_issue_185_act_multidiscrete_space(self):
for env_name in self.get_list_env():
if env_name == "blank":
continue
elif env_name == "l2rpn_neurips_2020_track1":
# takes too much time
continue
elif env_name == "l2rpn_neurips_2020_track2":
# takes too much time
continue
elif env_name == "rte_case118_example":
# takes too much time
continue
elif env_name == ENV_WITH_ALARM_NAME:
# takes too much time
continue
with warnings.catch_warnings():
warnings.filterwarnings("ignore")
with grid2op.make(env_name, test=True) as env:
try:
gym_env = GymEnv(env)
gym_env.action_space = MultiDiscreteActSpace(
gym_env.init_env.action_space
)
# gym_env.seed(0)
# gym_env.observation_space.seed(0)
gym_env.action_space.seed(0)
obs_gym, *_ = gym_env.reset(seed=0)
assert obs_gym in gym_env.observation_space, f"error for {env_name}"
act = gym_env.action_space.sample()
assert act in gym_env.action_space, f"error for {env_name}"
obs, reward, done, truncated, info = gym_env.step(act)
assert obs in gym_env.observation_space, f"error for {env_name}"
finally:
gym_env.close()
def test_issue_185_act_discrete_space(self):
for env_name in self.get_list_env():
if env_name == "blank":
continue
elif env_name == "l2rpn_neurips_2020_track1":
# takes too much time
continue
elif env_name == "l2rpn_neurips_2020_track2":
# takes too much time
continue
elif env_name == "rte_case118_example":
# takes too much time
continue
elif env_name == ENV_WITH_ALARM_NAME:
# takes too much time
continue
with warnings.catch_warnings():
warnings.filterwarnings("ignore")
with grid2op.make(env_name, test=True) as env:
try:
gym_env = GymEnv(env)
gym_env.action_space = DiscreteActSpace(
gym_env.init_env.action_space
)
# gym_env.seed(0)
# gym_env.observation_space.seed(0)
# gym_env.action_space.seed(0)
gym_env.action_space.seed(0)
obs_gym, *_ = gym_env.reset(seed=0)
assert obs_gym in gym_env.observation_space, f"error for {env_name}"
act = gym_env.action_space.sample()
assert act in gym_env.action_space, f"error for {env_name}"
obs, reward, done, truncated, info = gym_env.step(act)
if obs not in gym_env.observation_space:
for k in obs:
if not obs[k] in gym_env.observation_space[k]:
raise RuntimeError(
f"Error for key {k} for env {env_name}"
)
finally:
gym_env.close()
if __name__ == "__main__":
unittest.main()