def test_potato_1channel(get_covmats):
n_trials, n_channels = 6, 1
covmats_1chan = get_covmats(n_trials, n_channels)
pt = Potato()
pt.fit_transform(covmats_1chan)
pt.predict(covmats_1chan)
pt.predict_proba(covmats_1chan)
def test_Potato_init():
"""Test Potato"""
covset = generate_cov(20, 3)
labels = np.array([0, 1]).repeat(10)
# init
pt = Potato()
# fit no labels
pt.fit(covset)
# fit with labels
with pytest.raises(ValueError):
pt.fit(covset, y=[1])
with pytest.raises(ValueError):
pt.fit(covset, y=[0] * 20)
with pytest.raises(ValueError):
pt.fit(covset, y=[0, 2, 3] + [1] * 17)
pt.fit(covset, labels)
# transform
pt.transform(covset)
pt.transform(covset[0][np.newaxis, ...]) # transform a single trial
# predict
pt.predict(covset)
pt.predict(covset[0][np.newaxis, ...]) # predict a single trial
# predict_proba
pt.predict_proba(covset)
pt.predict_proba(covset[0][np.newaxis, ...])
# lower threshold
pt = Potato(threshold=1)
pt.fit(covset)
# test positive labels
pt = Potato(threshold=1, pos_label=2, neg_label=7)
pt.fit(covset)
assert_array_equal(np.unique(pt.predict(covset)), [2, 7])
# test with custom positive label
pt.fit(covset, y=[2] * 20)
# different positive and neg label
with pytest.raises(ValueError):
Potato(pos_label=0)