def test_weather_fog_density_scenario(fog_density: float, max_err: float,
request: FixtureRequest) -> None:
"""Validate that fog density is loaded correctly from scenario by
comparing RGB sensor data with saved baseline data
image
Args:
fog_density: Density of fog in interval [0, 1]
max_err: Maximum mean squared error between sensor data and baseline
data allowed for test to pass
request: pytest fixture request information
"""
config = weather_config.copy()
config["weather"] = {"fog_density": fog_density}
with env_with_config(config) as env:
env.tick(5)
err = compare_rgb_sensor_data_with_baseline(
env.tick()["TestCamera"],
request.fspath.dirname,
"weather_fog_density_{}".format(fog_density),
)
assert err < max_err
def test_fail_incorrect_weather_type_scenario():
"""
Validate that an exception is thrown when an invalid weather type is
specified in scenario
"""
# Hail is not a valid weather type--this is on purpose
config = weather_config.copy()
config["weather"] = {"type": "hail"}
with pytest.raises(HolodeckException):
env_with_config(config)
def test_weather_time_persists_after_reset_scenario(
hour: int,
max_err: float,
):
"""
Validate that time set in scenario persists after an environment
reset
Args:
hour: The hour in 24-hour format: [0, 23].
max_err: Maximum mean squared error between sensor data and baseline
"""
config = weather_config.copy()
config["weather"] = {"hour": hour}
err = mean_square_error_before_after_reset(env_with_config(config))
assert err < max_err
def test_weather_fog_density_persists_after_reset_scenario(
fog_density: float,
max_err: float,
):
"""
Validate that fog density set in scenario persists after an environment
reset
Args:
fog_density: Density of fog in interval [0, 1]
max_err: Maximum mean squared error between sensor data and baseline
"""
config = weather_config.copy()
config["weather"] = {"fog_density": fog_density}
err = mean_square_error_before_after_reset(env_with_config(config))
assert err < max_err
def test_weather_type_persists_after_reset_scenario(
weather_type: str,
max_err: float,
):
"""
Validate that weather type set in scenario persists after an environment
reset
Args:
weather_type: Type of weather in ["sunny", "cloudy", "rain"]
max_err: Maximum mean squared error between sensor data and baseline
"""
config = weather_config.copy()
config["weather"] = {"type": weather_type}
err = mean_square_error_before_after_reset(env_with_config(config))
assert err < max_err
def test_weather_day_cycle_scenario(
cycle_length: float,
ticks: int,
max_err_before: float,
max_err_after: float,
request: FixtureRequest,
) -> None:
"""Verify that day cycle can be set with scenario by comparing RGB sensor
data with saved baseline data
Args:
cycle_length: The hour in 24-hour format: [0, 23].
ticks: Number of ticks between captures
max_err_before: Maximum mean squared error between sensor data and
baseline for `before` image
max_err_before: Maximum mean squared error between sensor data and
baseline for `after` image
data allowed for test to pass
request: pytest fixture request information
"""
config = weather_config.copy()
config["weather"] = {"day_cycle_length": cycle_length}
with env_with_config(config) as env:
env.tick(5)
err_before = compare_rgb_sensor_data_with_baseline(
env.tick()["TestCamera"],
request.fspath.dirname,
"weather_time_before_{}".format(cycle_length),
)
env.tick(ticks)
err_after = compare_rgb_sensor_data_with_baseline(
env.tick()["TestCamera"],
request.fspath.dirname,
"weather_time_after_{}".format(cycle_length),
)
assert err_before < max_err_before
assert err_after < max_err_after
def test_weather_time_scenario(hour: float, max_err: float,
request: FixtureRequest) -> None:
"""Validate that time can be set with scenario by comparing RGB sensor
data with saved baseline data
Args:
hour: The hour in 24-hour format: [0, 23].
max_err: Maximum mean squared error between sensor
data and baseline
request: pytest fixture request information
"""
config = weather_config.copy()
config["weather"] = {"hour": hour}
with env_with_config(config) as env:
env.tick(5)
err = compare_rgb_sensor_data_with_baseline(
env.tick()["TestCamera"],
request.fspath.dirname,
"weather_time_{}".format(hour),
)
assert err < max_err
def test_weather_type_scenario(weather_type: str, max_err: float,
request: FixtureRequest) -> None:
"""Validate that weather type is loaded correctly from scenario by
comparing RGB sensor data with saved baseline
data
Args:
weather_type: Type of weather in ["sunny", "cloudy", "rain"]
max_err: Maximum mean squared error between sensor data and baseline
data allowed for test to pass
request: pytest fixture request information
"""
config = weather_config.copy()
config["weather"] = {"type": weather_type}
with env_with_config(config) as env:
env.tick(5)
err = compare_rgb_sensor_data_with_baseline(
env.tick()["TestCamera"],
request.fspath.dirname,
"weather_type_{}".format(weather_type),
)
assert err < max_err