def test_three_blobs_centroids(): km = TfKmeans(k=3, max_iter=50, random_seed=1, print_progress=0) centroids = np.array([[-1.5947298, 2.92236966], [2.06521743, 0.96137409], [0.9329651, 4.35420713]]) km.fit(X) np.testing.assert_almost_equal(centroids, km.centroids_, decimal=2)
def test_continue_training(): km = TfKmeans(k=3, max_iter=1, random_seed=1, print_progress=0) first_iter = np.array([[-1.33, 3.26], [1.95, 0.99], [1.09, 4.26]]) second_iter = np.array([[-1.5947298, 2.92236966], [2.06521743, 0.96137409], [0.9329651, 4.35420713]]) km.fit(X) np.testing.assert_almost_equal(first_iter, km.centroids_, decimal=2) assert km.iterations_ == 1, km.iterations_ km.fit(X, init_params=False) np.testing.assert_almost_equal(second_iter, km.centroids_, decimal=2) assert km.iterations_ == 2, km.iterations_
def test_three_blobs_multi(): km = TfKmeans(k=3, max_iter=50, random_seed=1, print_progress=0) y_pred = km.fit(X).predict(X) assert (y_pred == y).all()
def test_three_blobs_1sample(): km = TfKmeans(k=3, max_iter=50, random_seed=1, print_progress=0) sample = X[1, :].reshape(1, 2) y_pred = km.fit(X).predict(sample) assert y_pred[0] == y[1]