def test_predict_no_centroids1():
with pytest.raises(AttributeError):
kmeans = MultiviewKMeans()
kmeans.centroids_ = [None, None]
view1 = np.random.random((10,11))
view2 = np.random.random((10,10))
kmeans.predict([view1, view2])
def test_predict_deterministic():
n_clusters = 2
v1_centroid = np.array([[0, 0],[1, 1]])
v2_centroid = np.array([[0, 0],[1, 1]])
centroids = [v1_centroid, v2_centroid]
v1_data = np.array([[0, 0],[0.3, 0.2],[0.5, 0.5],[0.7, 0.7],[1, 1]])
v2_data = np.array([[0, 0],[0.2, 0.4],[0.5, 0.5],[0.4, 0.7],[1, 1]])
data = [v1_data, v2_data]
kmeans = MultiviewKMeans(n_clusters=n_clusters)
kmeans.centroids_ = centroids
cluster_pred = kmeans.predict(data)
true_clusters = [0, 0, 0, 1, 1]
for ind in range(len(true_clusters)):
assert cluster_pred[ind] == true_clusters[ind]