Function test_get_coef

mne/decoding/tests/test_base.py:99–230

Test getting linear coefficients (filters/patterns) from estimators.

()

def test_get_coef():
    """Test getting linear coefficients (filters/patterns) from estimators."""
    lm_classification = LinearModel(LogisticRegression(solver="liblinear"))
    assert hasattr(lm_classification, "__sklearn_tags__")
    if check_version("sklearn", "1.6"):
        print(lm_classification.__sklearn_tags__())
    assert is_classifier(lm_classification.model)
    assert is_classifier(lm_classification)
    assert not is_regressor(lm_classification.model)
    assert not is_regressor(lm_classification)

    lm_regression = LinearModel(Ridge())
    assert is_regressor(lm_regression.model)
    assert is_regressor(lm_regression)
    assert not is_classifier(lm_regression.model)
    assert not is_classifier(lm_regression)

    parameters = {"kernel": ["linear"], "C": [1, 10]}
    lm_gs_classification = LinearModel(
        GridSearchCV(svm.SVC(), parameters, cv=2, refit=True, n_jobs=None)
    )
    assert is_classifier(lm_gs_classification)

    lm_gs_regression = LinearModel(
        GridSearchCV(svm.SVR(), parameters, cv=2, refit=True, n_jobs=None)
    )
    assert is_regressor(lm_gs_regression)

    # Define a classifier, an invertible transformer and an non-invertible one.
    assert BaseEstimator is sklearn_BaseEstimator
    assert TransformerMixin is sklearn_TransformerMixin

    class Clf(BaseEstimator):
        def fit(self, X, y):
            return self

    class NoInv(TransformerMixin):
        def fit(self, X, y):
            return self

        def transform(self, X):
            return X

    class Inv(NoInv):
        def inverse_transform(self, X):
            return X

    X, y, A = _make_data(n_samples=1000, n_features=3, n_targets=1)

    # I. Test inverse function

    # Check that we retrieve the right number of inverse functions even if
    # there are nested pipelines
    good_estimators = [
        (1, make_pipeline(Inv(), Clf())),
        (2, make_pipeline(Inv(), Inv(), Clf())),
        (3, make_pipeline(Inv(), make_pipeline(Inv(), Inv()), Clf())),
    ]