test_box_polar_utils

Classes

TestBoxCartesianDistribution	Tests for BoxCartesianDistribution.
TestBoxCartesianEndToEnd	End-to-end tests for the Cartesian Box implementation.
TestBoxCartesianEnvironment	Tests for the Box environment with Cartesian semantics.
TestBoxCartesianPBDistribution	Tests for BoxCartesianPBDistribution (backward policy).

Functions

test_mixed_distributions(n_components, n_components_s0)

Tests the DistributionWrapper class.

Module Contents

class test_box_polar_utils.TestBoxCartesianDistribution

Tests for BoxCartesianDistribution.

env()

pf_estimator(env, pf_module)

pf_module()

test_log_prob_exit_at_boundary(env, pf_estimator)

Exit at boundary should have finite log_prob (learned Bernoulli).

test_log_prob_finite(env, pf_estimator)

Log probabilities should be finite for valid actions.

test_no_exit_from_s0(env, pf_estimator)

Exit from s0 should have log_prob = -inf.

test_sample_non_s0_in_range(env, pf_estimator)

From non-s0, sampled actions should be >= delta.

test_sample_s0_in_range(env, pf_estimator)

From s0, sampled actions should be in [0, 1] (full space coverage).

test_sample_shape(env, pf_estimator)

Sampled actions should have correct shape.

class test_box_polar_utils.TestBoxCartesianEndToEnd

End-to-end tests for the Cartesian Box implementation.

env()

pb_estimator(env)

pf_estimator(env)

test_backward_trajectory_reaches_s0(env, pb_estimator)

A backward trajectory should reach s0.

test_reward_function(env)

Reward function should return expected values.

test_trajectory_stays_in_bounds(env, pf_estimator)

A trajectory should stay within [0, 1]^2.

class test_box_polar_utils.TestBoxCartesianEnvironment

Tests for the Box environment with Cartesian semantics.

env()

test_backward_step_subtracts_action(env)

Backward step should subtract action from state.

test_exit_action_valid(env)

Exit actions should be valid for non-s0 states.

test_forward_backward_roundtrip(env)

Forward then backward should return to original state.

test_forward_step_adds_action(env)

Forward step should add action to state.

test_is_action_valid_boundary(env)

Actions shouldn’t push state past boundary.

test_is_action_valid_non_s0_forward(env)

From non-s0, forward actions should be >= delta.

test_is_action_valid_s0_forward(env)

From s0, forward actions should be in [0, 1] (full space coverage).

class test_box_polar_utils.TestBoxCartesianPBDistribution

Tests for BoxCartesianPBDistribution (backward policy).

env()

pb_estimator(env, pb_module)

pb_module()

test_log_prob_near_origin(env, pb_estimator)

Log prob for near-origin states going to s0 should be 0.

When near origin (any dimension <= delta), BTS is forced and log_prob = 0. For numerical robustness, any action from a near-origin state is treated as BTS since that’s the only valid action anyway.

test_sample_mixed_dims_near_origin(env, pb_estimator)

States with mixed dims (some < delta, some >= delta) should handle correctly.

test_sample_near_origin_to_s0(env, pb_estimator)

States near origin should go directly to s0.

test_sample_non_origin_valid(env, pb_estimator)

Backward actions from non-origin should be valid.

test_sample_shape(env, pb_estimator)

Sampled backward actions should have correct shape.

test_box_polar_utils.test_mixed_distributions(n_components, n_components_s0)

Tests the DistributionWrapper class.

Parameters:

• n_components (int) – The number of components for non-s0 states.

• n_components_s0 (int) – The number of components for s0.