Exemple #1
0
def test_column_transformer_get_set_params():
    ct = ColumnTransformer([('trans1', StandardScaler(), [0]),
                            ('trans2', StandardScaler(), [1])])

    exp = {
        'n_jobs': None,
        'remainder': 'drop',
        'sparse_threshold': 0.3,
        'trans1': ct.transformers[0][1],
        'trans1__copy': True,
        'trans1__with_mean': True,
        'trans1__with_std': True,
        'trans2': ct.transformers[1][1],
        'trans2__copy': True,
        'trans2__with_mean': True,
        'trans2__with_std': True,
        'transformers': ct.transformers,
        'transformer_weights': None,
        'verbose': False
    }

    assert ct.get_params() == exp

    ct.set_params(trans1__with_mean=False)
    assert not ct.get_params()['trans1__with_mean']

    ct.set_params(trans1='passthrough')
    exp = {
        'n_jobs': None,
        'remainder': 'drop',
        'sparse_threshold': 0.3,
        'trans1': 'passthrough',
        'trans2': ct.transformers[1][1],
        'trans2__copy': True,
        'trans2__with_mean': True,
        'trans2__with_std': True,
        'transformers': ct.transformers,
        'transformer_weights': None,
        'verbose': False
    }

    assert ct.get_params() == exp
Exemple #2
0
def test_column_transformer_no_estimators():
    X_array = np.array([[0, 1, 2], [2, 4, 6], [8, 6, 4]]).astype('float').T
    ct = ColumnTransformer([], remainder=StandardScaler())

    params = ct.get_params()
    assert params['remainder__with_mean']

    X_trans = ct.fit_transform(X_array)
    assert X_trans.shape == X_array.shape
    assert len(ct.transformers_) == 1
    assert ct.transformers_[-1][0] == 'remainder'
    assert ct.transformers_[-1][2] == [0, 1, 2]