def test_blending_transform_wrong_dim():
"""Check if returns error when number of spatial dimension changed"""
X = np.ones((1, 10, 2))
Blend = Blending(window_overlap=10)
Blend.fit(X)
with pytest.raises(
ValueError,
match='X.shape should be \(n_trials, n_samples, n_electrodes\).'):
Blend.transform(np.ones((10, 2)))
def test_blending_NaN():
"""Check if returns error when NaN"""
X = np.ones((1, 10, 2))
X[0, 5, 1] = np.NaN
Blend = Blending(window_overlap=10)
with pytest.raises(
ValueError,
match=
'Input contains NaN, infinity or a value too large for dtype\(\'float64\'\).'
):
Blend.fit(X)
X2 = np.ones((1, 10, 3))
Blend.fit(X2)
with pytest.raises(
ValueError,
match=
'Input contains NaN, infinity or a value too large for dtype\(\'float64\'\).'
):
Xtransform = Blend.transform(X)
def test_blending_not_init():
with pytest.raises(ValueError,
match="window_overlap parameter is not initialized."):
Blending(window_overlap=None)