def test_n_iter_without_progress(): # Use a dummy negative n_iter_without_progress and check output on stdout random_state = check_random_state(0) X = random_state.randn(100, 10) for method in ["barnes_hut", "exact"]: tsne = TSNE(n_iter_without_progress=-1, verbose=2, learning_rate=1e8, random_state=0, method=method, n_iter=351, init="random") tsne._N_ITER_CHECK = 1 tsne._EXPLORATION_N_ITER = 0 old_stdout = sys.stdout sys.stdout = StringIO() try: tsne.fit_transform(X) finally: out = sys.stdout.getvalue() sys.stdout.close() sys.stdout = old_stdout # The output needs to contain the value of n_iter_without_progress assert_in( "did not make any progress during the " "last -1 episodes. Finished.", out)
def test_n_iter_without_progress(): # Use a dummy negative n_iter_without_progress and check output on stdout random_state = check_random_state(0) X = random_state.randn(100, 10) for method in ["barnes_hut", "exact"]: tsne = TSNE(n_iter_without_progress=-1, verbose=2, learning_rate=1e8, random_state=0, method=method, n_iter=351, init="random") tsne._N_ITER_CHECK = 1 tsne._EXPLORATION_N_ITER = 0 old_stdout = sys.stdout sys.stdout = StringIO() try: tsne.fit_transform(X) finally: out = sys.stdout.getvalue() sys.stdout.close() sys.stdout = old_stdout # The output needs to contain the value of n_iter_without_progress assert_in("did not make any progress during the " "last -1 episodes. Finished.", out)