def test_combine_with_existing_dense_features_shape_mismatch():
existing_features = Features(np.array([[1, 0, 2, 3], [2, 0, 0, 1]]),
FEATURE_TYPE_SEQUENCE, TEXT, "test")
new_features = np.array([[0, 1]])
with pytest.raises(ValueError):
existing_features.combine_with_features(new_features)
def test_combine_with_existing_sparse_features_shape_mismatch():
existing_features = Features(
scipy.sparse.csr_matrix([[1, 0, 2, 3], [2, 0, 0, 1]]), TEXT, "test"
)
new_features = scipy.sparse.csr_matrix([[0, 1]])
with pytest.raises(ValueError):
existing_features.combine_with_features(new_features)
def test_combine_with_existing_dense_features():
existing_features = Features(np.array([[1, 0, 2, 3], [2, 0, 0, 1]]), TEXT, "test")
new_features = np.array([[1, 0], [0, 1]])
expected_features = np.array([[1, 0, 2, 3, 1, 0], [2, 0, 0, 1, 0, 1]])
actual_features = existing_features.combine_with_features(new_features)
assert np.all(expected_features == actual_features)
def test_combine_with_existing_sparse_features():
existing_features = Features(
scipy.sparse.csr_matrix([[1, 0, 2, 3], [2, 0, 0, 1]]), TEXT, "test"
)
new_features = scipy.sparse.csr_matrix([[1, 0], [0, 1]])
expected_features = [[1, 0, 2, 3, 1, 0], [2, 0, 0, 1, 0, 1]]
actual_features = existing_features.combine_with_features(new_features)
actual_features = actual_features.toarray()
assert np.all(expected_features == actual_features)