import collections
import madrona_gpudrive
import pytest

@pytest.fixture(scope="module")
def simulation_results():
    # Create an instance of RewardParams
    reward_params = madrona_gpudrive.RewardParams()
    reward_params.rewardType = madrona_gpudrive.RewardType.DistanceBased  # Or any other value from the enum
    reward_params.distanceToGoalThreshold = 1.0  # Set appropriate values
    reward_params.distanceToExpertThreshold = 1.0  # Set appropriate values

    # Create an instance of Parameters
    params = madrona_gpudrive.Parameters()
    params.polylineReductionThreshold = 0.5  # Set appropriate value
    params.observationRadius = 10.0  # Set appropriate value
    params.collisionBehaviour = madrona_gpudrive.CollisionBehaviour.AgentStop  # Set appropriate value
    params.rewardParams = reward_params  # Set the rewardParams attribute to the instance created above
    params.maxNumControlledAgents = 0
    params.IgnoreNonVehicles = True
    params.isStaticAgentControlled = False
    # Now use the 'params' instance when creating SimManager
    sim = madrona_gpudrive.SimManager(
        exec_mode=madrona_gpudrive.madrona.ExecMode.CPU,
        gpu_id=0,
        scenes=["tests/pytest_data/test.json"],
        params=params,
        enable_batch_renderer=False, # Optional parameter
        batch_render_view_width=1024,
        batch_render_view_height=1024
    )

    done = sim.done_tensor().to_torch()

    while not done.all():
        sim.step()
        
    return sim

def test_goal_reaching(simulation_results):
    sim = simulation_results
    info, shape = sim.info_tensor().to_torch(), sim.shape_tensor().to_torch()
    info_valid = info[info[:, :, -1] == float(madrona_gpudrive.EntityType.Vehicle)]
    goal_reached = info_valid[:, -2].sum().item()
    assert goal_reached == shape[:, 0].sum().item()
    print("Test passed!")

def test_collision_rate(simulation_results):
    sim = simulation_results
    info = sim.info_tensor().to_torch()

    info_valid = info[info[:, :, -1] == float(madrona_gpudrive.EntityType.Vehicle)]
    collisions = info_valid[:, :3].sum().item()
    try:
        assert collisions == 0
    except AssertionError:
        print("Assertion failed! Info tensor:")
        print(info_valid)
        raise
    print("Test passed!")