class FlightTaskStub(FlightTask):
""" A minimal Task for testing. """
test_property1 = prp.BoundedProperty('test_property1',
'dummy property for testing', -1, 1)
test_property2 = prp.BoundedProperty('test_property2',
'dummy property for testing', -1, 1)
def __init__(self, *_):
self.state_variables = (self.test_property1, self.test_property2)
self.action_variables = (prp.aileron_cmd, prp.elevator_cmd)
super().__init__(AssessorStub())
def _is_terminal(self, _: Tuple[float, ...], __: float) -> bool:
return False
def get_initial_conditions(self):
return self.base_initial_conditions
def get_state(self, value1: float, value2: float):
""" Returns a State of this class' test properties populated with input values """
return self.State(value1, value2)
def get_props_to_output(self) -> Tuple:
return prp.u_fps, prp.altitude_sl_ft, prp.heading_deg
@staticmethod
def get_dummy_state_class_and_properties(length: int):
dummy_properties = tuple(
prp.Property('test_prop' + str(i), '') for i in range(length))
DummyState = collections.namedtuple(
'DummyState', [prop.name for prop in dummy_properties])
return DummyState, dummy_properties
@staticmethod
def get_dummy_state_and_properties(
values: Iterable[float]
) -> Tuple[NamedTuple, Tuple[prp.Property, ...]]:
"""
given a collection of floats, creates dummy Properties for each value
and inits a State
"""
values_safe = tuple(values)
DummyState, props = FlightTaskStub.get_dummy_state_class_and_properties(
len(values_safe))
return DummyState(*values_safe), props
def _reward_terminal_override(self, reward: rewards.Reward,
sim: Simulation):
return False
def test_initialise_conditions_basic_config(self):
plane = aircraft.f15
# manually reset JSBSim instance with new initial conditions
if self.sim:
self.sim.close()
sim_frequency = 2
self.sim = Simulation(sim_frequency_hz=sim_frequency, aircraft=plane, init_conditions=None)
self.assertEqual(self.sim.get_loaded_model_name(), plane.jsbsim_id,
msg='JSBSim did not load expected aircraft model: ' +
self.sim.get_loaded_model_name())
# check that properties are as we expected them to be
expected_values = {
prp.initial_u_fps: 328.0,
prp.initial_v_fps: 0.0,
prp.initial_w_fps: 0.0,
prp.u_fps: 328.0,
prp.v_fps: 0.0,
prp.w_fps: 0.0,
prp.BoundedProperty('simulation/dt', '', None, None): 1 / sim_frequency
}
for prop, expected in expected_values.items():
actual = self.sim[prop]
self.assertAlmostEqual(expected, actual)
def test_asl_agl_elevations_equal(self):
# we want the height above sea level to equal ground elevation at all times
self.setUp(agent_interaction_freq=1)
for i in range(25):
self.env.step(action=self.env.action_space.sample())
alt_sl = self.env.sim[prp.altitude_sl_ft]
alt_gl = self.env.sim[prp.BoundedProperty('position/h-agl-ft', '',
0, 0)]
self.assertAlmostEqual(alt_sl, alt_gl)
def test_get_bad_property(self):
self.setUp()
bad_prop = prp.BoundedProperty("bad_prop_name", "", 0, 0)
with self.assertRaises(KeyError):
_ = self.sim[bad_prop]