from guardrail_space.belief import BeliefSketch


def test_belief_pov_and_entropy_deterministic():
    # deterministic seed so CI results are reproducible
    sketch = BeliefSketch("obstacle_dist", num_particles=128, prior_mean=0.0, prior_std=1.0, seed=42)

    # an observation far above the prior should push mass upward
    sketch.update(observation=5.0, obs_std=0.5)

    pov = sketch.pov(threshold=3.0, operator=">")
    ent = sketch.entropy()

    # After a strong observation at 5.0 most particles should be >3.0
    assert pov > 0.8

    # entropy should be a finite positive number
    assert isinstance(ent, float)
    assert ent > 0.0


def test_serialize_small_and_deterministic():
    s1 = BeliefSketch("battery", num_particles=32, prior_mean=10.0, prior_std=2.0, seed=7)
    s2 = BeliefSketch("battery", num_particles=32, prior_mean=10.0, prior_std=2.0, seed=7)

    s1.update(9.5, obs_std=0.5)
    s2.update(9.5, obs_std=0.5)

    b1 = s1.serialize()
    b2 = s2.serialize()

    # deterministic with same seed and ops
    assert b1 == b2

    # compact
    assert len(b1) <= 40