diff --git a/sklearn/neighbors/tests/test_neighbors.py b/sklearn/neighbors/tests/test_neighbors.py index 17e42e21a10b81616a1ffb6669ab8ef87582954c..66e675c92c9c10a891d94da3b76533fd3575c0ae 100644 --- a/sklearn/neighbors/tests/test_neighbors.py +++ b/sklearn/neighbors/tests/test_neighbors.py @@ -57,7 +57,7 @@ def test_warn_on_equidistant(n_samples=100, n_features=3, k=3): print algorithm, estimator, len(warn_queue) assert_equal(len(warn_queue), 1) - assert_equal(warn_queue[0].message.message, expected_message) + assert_equal(str(warn_queue[0].message), expected_message) def test_unsupervised_kneighbors(n_samples=20, n_features=5, diff --git a/sklearn/tests/test_cross_validation.py b/sklearn/tests/test_cross_validation.py index d82922a97079da41bc420c6ff682ca1e5ba02946..b780c7508ef57ef8712de688a1f2bccf8e7ebda7 100644 --- a/sklearn/tests/test_cross_validation.py +++ b/sklearn/tests/test_cross_validation.py @@ -175,10 +175,10 @@ def test_shuffle_split_warnings(): cval.train_test_split(range(3), train_fraction=0.1) assert_equal(len(warn_queue), 4) - assert_equal(warn_queue[0].message.message, expected_message[0]) - assert_equal(warn_queue[1].message.message, expected_message[1]) - assert_equal(warn_queue[2].message.message, expected_message[0]) - assert_equal(warn_queue[3].message.message, expected_message[1]) + assert_equal(str(warn_queue[0].message), expected_message[0]) + assert_equal(str(warn_queue[1].message), expected_message[1]) + assert_equal(str(warn_queue[2].message), expected_message[0]) + assert_equal(str(warn_queue[3].message), expected_message[1]) def test_train_test_split(): @@ -323,10 +323,10 @@ def test_bootstrap_errors(): def test_shufflesplit_errors(): - assert_raises(ValueError, cval.ShuffleSplit, 10, test_fraction=2.0) - assert_raises(ValueError, cval.ShuffleSplit, 10, test_fraction=1.0) - assert_raises(ValueError, cval.ShuffleSplit, 10, test_fraction=0.1, - train_fraction=0.95) + assert_raises(ValueError, cval.ShuffleSplit, 10, test_size=2.0) + assert_raises(ValueError, cval.ShuffleSplit, 10, test_size=1.0) + assert_raises(ValueError, cval.ShuffleSplit, 10, test_size=0.1, + train_size=0.95) assert_raises(ValueError, cval.ShuffleSplit, 10, test_size=11) assert_raises(ValueError, cval.ShuffleSplit, 10, test_size=10) assert_raises(ValueError, cval.ShuffleSplit, 10, test_size=8,