def test_step_moving_obstacles(
objects: Sequence[Sequence[GridObject]],
expected_objects: Sequence[Sequence[GridObject]],
):
state = State(Grid.from_objects(objects), MagicMock())
expected_state = State(Grid.from_objects(expected_objects), MagicMock())
action = MagicMock()
step_moving_obstacles(state, action)
assert state.grid == expected_state.grid
def test_grid_subgrid(area: Area,
expected_objects: Sequence[Sequence[GridObject]]):
# checkerboard pattern
grid = Grid.from_objects([
[Wall(), Floor(), Wall(), Floor()],
[Floor(), Wall(), Floor(), Wall()],
[Wall(), Floor(), Wall(), Floor()],
])
expected = Grid.from_objects(expected_objects)
assert grid.subgrid(area) == expected
def test_grid_change_orientation(
orientation: Orientation,
expected_objects: Sequence[Sequence[GridObject]]):
# checkerboard pattern
grid = Grid.from_objects([
[Wall(), Floor(), Wall(), Floor()],
[Floor(), Wall(), Floor(), Wall()],
[Wall(), Floor(), Wall(), Floor()],
])
expected = Grid.from_objects(expected_objects)
assert grid.change_orientation(orientation) == expected
def test_draw_line_horizontal(grid: Grid, y: int, xs: Iterable[int],
expected_num_walls: int):
positions = draw_line_horizontal(grid, y, xs, Wall)
assert len(positions) == len(set(positions))
num_walls = sum(isinstance(grid[pos], Wall) for pos in grid.positions())
assert len(positions) == num_walls == expected_num_walls
def test_draw_room_grid(grid: Grid, ys: Iterable[int], xs: Iterable[int],
expected_num_walls: int):
positions = draw_room_grid(grid, ys, xs, Wall)
assert len(positions) == len(set(positions))
num_walls = sum(isinstance(grid[pos], Wall) for pos in grid.positions())
assert len(positions) == num_walls == expected_num_walls
def make_goal_state(agent_on_goal: bool) -> State:
"""makes a simple state with a wall in front of the agent"""
grid = Grid(2, 1)
grid[0, 0] = Goal()
agent_position = (0, 0) if agent_on_goal else (1, 0)
agent = Agent(agent_position, Orientation.N)
return State(grid, agent)
def match_key_color(
*,
rng: Optional[rnd.Generator] = None, # pylint: disable=unused-argument
) -> State:
"""the agent has to pick the correct key to open a randomly colored door"""
rng = get_gv_rng_if_none(rng) # necessary to use rng object!
# only consider these colors
colors = [Color.RED, Color.GREEN, Color.BLUE, Color.YELLOW]
# randomly choose location of keys
key1, key2, key3, key4 = rng.permute([Key(color) for color in colors])
# randomly choose color of door
door = Door(Door.Status.LOCKED, rng.choice(colors))
# grids can be constructed directly from objects
grid = Grid.from_objects([
[Wall(), Wall(), Wall(), Wall(),
Wall()],
[Wall(), Wall(), Goal(), Wall(),
Wall()],
[Wall(), Wall(), door, Wall(), Wall()],
[Wall(), key1, Floor(), key2, Wall()],
[Wall(), key3, Floor(), key4, Wall()],
[Wall(), Wall(), Wall(), Wall(),
Wall()],
])
# positioning the agent in the above grid
agent = Agent((4, 2), Orientation.N)
return State(grid, agent)
def make_moving_obstacle_state(agent_on_obstacle: bool) -> State:
"""makes a simple state with goal object and agent on or off the goal"""
grid = Grid(2, 1)
grid[0, 0] = MovingObstacle()
agent_position = (0, 0) if agent_on_obstacle else (1, 0)
agent = Agent(agent_position, Orientation.N)
return State(grid, agent)
def test_draw_area(grid: Grid, area: Area, fill: bool,
expected_num_walls: int):
positions = draw_area(grid, area, Wall, fill=fill)
assert len(positions) == len(set(positions))
num_walls = sum(isinstance(grid[pos], Wall) for pos in grid.positions())
assert len(positions) == num_walls == expected_num_walls
def test_full_visibility(objects: Sequence[Sequence[GridObject]]):
grid = Grid.from_objects(objects)
for position in grid.positions():
visibility = full_visibility(grid, position)
assert visibility.dtype == bool
assert visibility.all()
def test_minigrid_observation_partially_observable(
agent: Agent, expected_objects: Sequence[Sequence[GridObject]]
):
grid = Grid.from_objects(
[
[Floor(), Floor(), Floor()],
[Wall(), Wall(), Wall()],
[Floor(), Floor(), Floor()],
]
)
state = State(grid, agent)
observation_space = ObservationSpace(Shape(6, 5), [], [])
observation = minigrid_observation(
state, observation_space=observation_space
)
expected = Grid.from_objects(expected_objects)
assert observation.grid == expected
def test_raytracing_visibility(
objects: Sequence[Sequence[GridObject]],
position: Position,
expected_int: Sequence[Sequence[int]],
):
grid = Grid.from_objects(objects)
visibility = raytracing_visibility(grid, position)
assert visibility.dtype == bool
assert (visibility == expected_int).all()
def test_grid_set_item():
grid = Grid(3, 4)
pos = Position(0, 0)
obj = Floor()
assert grid[pos] is not obj
grid[pos] = obj
assert grid[pos] is obj
def test_move_action_blocked_by_grid_object():
""" Puts an object on (2,0) and try to move there"""
grid = Grid(height=3, width=2)
agent = Agent(position=(2, 1), orientation=Orientation.N)
grid[2, 0] = Door(Door.Status.CLOSED, Color.YELLOW)
move_agent(agent, grid, action=Action.MOVE_LEFT)
assert agent.position == (2, 1)
def test_move_action_can_go_on_non_block_objects():
grid = Grid(height=3, width=2)
agent = Agent(position=(2, 1), orientation=Orientation.N)
grid[2, 0] = Door(Door.Status.OPEN, Color.YELLOW)
move_agent(agent, grid, action=Action.MOVE_LEFT)
assert agent.position == (2, 0)
grid[2, 1] = Key(Color.BLUE)
move_agent(agent, grid, action=Action.MOVE_RIGHT)
assert agent.position == (2, 1)
def reset_empty(
height: int,
width: int,
random_agent: bool = False,
random_goal: bool = False,
*,
rng: Optional[rnd.Generator] = None,
) -> State:
"""An empty environment"""
if height < 4 or width < 4:
raise ValueError('height and width need to be at least 4')
rng = get_gv_rng_if_none(rng)
# TODO test creation (e.g. count number of walls, goals, check held item)
grid = Grid(height, width)
draw_wall_boundary(grid)
if random_goal:
goal_y = rng.integers(1, height - 2, endpoint=True)
goal_x = rng.integers(1, width - 2, endpoint=True)
else:
goal_y = height - 2
goal_x = width - 2
grid[goal_y, goal_x] = Goal()
if random_agent:
agent_position = rng.choice([
position for position in grid.positions()
if isinstance(grid[position], Floor)
])
agent_orientation = rng.choice(list(Orientation))
else:
agent_position = (1, 1)
agent_orientation = Orientation.E
agent = Agent(agent_position, agent_orientation)
return State(grid, agent)
def _step_moving_obstacle(grid: Grid,
position: Position,
*,
rng: Optional[rnd.Generator] = None):
"""Utility for moving a single MovingObstacle randomly"""
assert isinstance(grid[position], MovingObstacle)
rng = get_gv_rng_if_none(rng)
next_positions = [
next_position
for next_position in get_manhattan_boundary(position, distance=1)
if next_position in grid and isinstance(grid[next_position], Floor)
]
try:
next_position = rng.choice(next_positions)
except ValueError:
pass
else:
grid.swap(position, next_position)
def test_pickup_mechanics_swap():
grid = Grid(height=3, width=4)
agent = Agent(position=(1, 2), orientation=Orientation.S)
item_pos = (2, 2)
agent.obj = Key(Color.BLUE)
grid[item_pos] = Key(Color.GREEN)
state = State(grid, agent)
next_state = step_with_copy(state, Action.PICK_N_DROP)
assert state.grid[item_pos] == next_state.agent.obj
assert state.agent.obj == next_state.grid[item_pos]
def test_state_hash():
wall_position = (0, 0)
agent_position = (0, 1)
agent_orientation = Orientation.N
agent_object = None
grid = Grid(2, 2)
grid[wall_position] = Wall()
agent = Agent(agent_position, agent_orientation, agent_object)
state = State(grid, agent)
hash(state)
def test_grid_subgrid_references():
key = Key(Color.RED)
box = Box(key)
# weird scenario where the key is both in the box and outside the box,
# only created to test references
grid = Grid.from_objects([[key, box]])
subgrid = grid.subgrid(Area((0, 0), (0, 1)))
key = subgrid[0, 0]
box = subgrid[0, 1]
assert box.content is key
def test_observation_hash():
wall_position = (0, 0)
agent_position = (0, 1)
agent_orientation = Orientation.N
agent_object = None
grid = Grid(2, 2)
grid[wall_position] = Wall()
agent = Agent(agent_position, agent_orientation, agent_object)
observation = Observation(grid, agent)
hash(observation)
def test_move_action(
position: PositionOrTuple,
orientation: Orientation,
actions: Sequence[Action],
expected: PositionOrTuple,
):
grid = Grid(height=3, width=2)
agent = Agent(position=position, orientation=orientation)
for action in actions:
move_agent(agent, grid, action=action)
assert agent.position == expected
def test_actuate_box(
content: GridObject,
orientation: Orientation,
action: Action,
expected: bool,
):
grid = Grid(2, 1)
grid[0, 0] = box = Box(content)
agent = Agent((1, 0), orientation)
state = State(grid, agent)
actuate_box(state, action)
assert (grid[0, 0] is box) != expected
assert (grid[0, 0] is content) == expected
def test_minigrid_observation(agent: Agent):
grid = Grid(10, 10)
grid[5, 5] = Wall()
state = State(grid, agent)
observation_space = ObservationSpace(Shape(6, 5), [], [])
observation = minigrid_observation(
state, observation_space=observation_space
)
assert observation.agent.position == (5, 2)
assert observation.agent.orientation == Orientation.N
assert observation.agent.obj == state.agent.obj
assert observation.grid.shape == Shape(6, 5)
assert isinstance(observation.grid[3, 0], Wall)
def test_actuate_door(
door_state: Door.Status,
door_color: Color,
key_color: Color,
action: Action,
expected_state: Door.Status,
):
# agent facing door
grid = Grid(2, 1)
grid[0, 0] = door = Door(door_state, door_color)
agent = Agent((1, 0), Orientation.N, Key(key_color))
state = State(grid, agent)
actuate_door(state, action)
assert door.state == expected_state
# agent facing away
grid = Grid(2, 1)
grid[0, 0] = door = Door(door_state, door_color)
agent = Agent((1, 0), Orientation.S, Key(key_color))
state = State(grid, agent)
actuate_door(state, action)
assert door.state == door_state
def test_teleport(
position_telepod1: Position,
position_telepod2: Position,
position_agent: Position,
expected: Position,
):
grid = Grid(2, 2)
grid[position_telepod1] = Telepod(Color.RED)
grid[position_telepod2] = Telepod(Color.RED)
agent = Agent(position_agent, Orientation.N)
state = State(grid, agent)
step_telepod(state, Action.ACTUATE)
assert state.agent.position == expected
def _unique_object_type_positions(
grid: Grid, object_type: Type[GridObject]
) -> Iterator[Tuple[Position, GridObject]]:
"""Utility for iterating *once* over position/objects.
Every object is only yielded once, even if the objects move during the
interleaved iteration.
"""
objects: List[GridObject] = []
for position in grid.positions():
obj = grid[position]
if isinstance(obj, object_type) and not any(obj is x for x in objects):
objects.append(obj)
yield position, obj
def test_grid_get_position():
grid = Grid(3, 4)
# testing position -> grid_object -> position roundtrip
for position in grid.positions():
obj = grid[position]
assert grid.get_position(obj) == position
# testing exception when object is not in grid
with pytest.raises(ValueError):
grid.get_position(Floor())
def test_pickup_mechanics_pickup():
grid = Grid(height=3, width=4)
agent = Agent(position=(1, 2), orientation=Orientation.S)
item_pos = (2, 2)
grid[item_pos] = Key(Color.GREEN)
state = State(grid, agent)
# Pick up works
next_state = step_with_copy(state, Action.PICK_N_DROP)
assert grid[item_pos] == next_state.agent.obj
assert isinstance(next_state.grid[item_pos], Floor)
# Pick up only works with correct action
next_state = step_with_copy(state, Action.MOVE_LEFT)
assert grid[item_pos] != next_state.agent.obj
assert next_state.grid[item_pos] == grid[item_pos]
def test_pickup_mechanics_nothing_to_pickup():
grid = Grid(height=3, width=4)
agent = Agent(position=(1, 2), orientation=Orientation.S)
item_pos = (2, 2)
state = State(grid, agent)
# Cannot pickup floor
next_state = step_with_copy(state, Action.PICK_N_DROP)
assert state == next_state
# Cannot pickup door
grid[item_pos] = Door(Door.Status.CLOSED, Color.GREEN)
next_state = step_with_copy(state, Action.PICK_N_DROP)
assert state == next_state
assert isinstance(next_state.grid[item_pos], Door)
