tests package

Submodules

tests.test_metrics module

class tests.test_metrics.TestMetrics(methodName='runTest')

Bases: TestCase

compare_metrics(actual_metrics: dict[str, dict[str, float]], expected_metrics: dict[str, dict[str, float]]) → None

setUp() → None

Hook method for setting up the test fixture before exercising it.

test_calculate_metrics() → None

test_extract_function_values() → None

test_extract_non_dominated_points() → None

test_purity() → None

test_spread_metrics() → None

tests.test_problems module

class tests.test_problems.TestFDS(methodName='runTest')

Bases: TestCase

setUp() → None

Hook method for setting up the test fixture before exercising it.

test_f() → None

test_jac_f() → None

class tests.test_problems.TestFDS_CONSTRAINED(methodName='runTest')

Bases: TestCase

setUp() → None

Hook method for setting up the test fixture before exercising it.

test_g() → None

test_prox_wsum_g() → None

class tests.test_problems.TestJOS1(methodName='runTest')

Bases: TestCase

setUp() → None

Hook method for setting up the test fixture before exercising it.

test_f() → None

test_jac_f() → None

class tests.test_problems.TestJOS1_L1(methodName='runTest')

Bases: TestCase

setUp() → None

Hook method for setting up the test fixture before exercising it.

test_g() → None

test_prox_wsum_g() → None

class tests.test_problems.TestSD(methodName='runTest')

Bases: TestCase

setUp() → None

Hook method for setting up the test fixture before exercising it.

test_f() → None

test_g() → None

test_jac_f() → None

test_prox_wsum_g() → None

tests.test_proximal_gradient module

class tests.test_proximal_gradient.TestProximalGradient(methodName='runTest')

Bases: TestCase

test_minimize_proximal_gradient_biobjective_lasso_toy() → None

min ((1 / 2) ||Ax - b||^2 + l1_ratio * ||x||_1,

(1 / 2) ||Ax - b||^2 + l1_ratio * ||x||_1)

See https://github.com/scikit-learn/scikit-learn/blob/main/sklearn/linear_model/tests/test_coordinate_descent.py

test_minimize_proximal_gradient_lasso_toy() → None

min (1 / 2) ||Ax - b||^2 + l1_ratio * ||x||_1 See https://github.com/scikit-learn/scikit-learn/blob/main/sklearn/linear_model/tests/test_coordinate_descent.py

test_minimize_proximal_gradient_lasso_zero() → None

test_minimize_proximal_gradient_return_all() → None

test_minimize_proximal_gradient_triobjective_lasso_toy() → None

min ((1 / 2) ||Ax - b||^2 + l1_ratio * ||x||_1,

(1 / 2) ||Ax - b||^2 + l1_ratio * ||x||_1, (1 / 2) ||Ax - b||^2 + l1_ratio * ||x||_1)

See https://github.com/scikit-learn/scikit-learn/blob/main/sklearn/linear_model/tests/test_coordinate_descent.py

tests.test_proximal_gradient.build_dataset(n_samples: int = 50, n_features: int = 200, n_informative_features: int = 10, n_targets: int = 1) → tuple[ndarray[Any, dtype[floating[Any]]], ndarray[Any, dtype[floating[Any]]], ndarray[Any, dtype[floating[Any]]], ndarray[Any, dtype[floating[Any]]]]

build an ill-posed linear regression problem with many noisy features and comparatively few samples See https://github.com/scikit-learn/scikit-learn/blob/main/sklearn/linear_model/tests/test_coordinate_descent.py

Module contents