ENH: use warning.catch_warnings

sklearn/tests/test_cross_validation.py

@@ -164,28 +164,22 @@ def test_train_test_split_errors():
 
 def test_shuffle_split_warnings():
     # change warnings.warn to catch the message
-    warn_queue = []
-    warnings_warn = warnings.warn
-    warnings.warn = lambda msg: warn_queue.append(msg)
-
     expected_message = ("test_fraction is deprecated in 0.11 and scheduled "
                         "for removal in 0.12, use test_size instead",
                         "train_fraction is deprecated in 0.11 and scheduled "
                         "for removal in 0.12, use train_size instead")
 
-    cval.ShuffleSplit(10, 3, test_fraction=0.1)
-    cval.ShuffleSplit(10, 3, train_fraction=0.1)
-    cval.train_test_split(range(3), test_fraction=0.1)
-    cval.train_test_split(range(3), train_fraction=0.1)
+    with warnings.catch_warnings(record=True) as warn_queue:
+        cval.ShuffleSplit(10, 3, test_fraction=0.1)
+        cval.ShuffleSplit(10, 3, train_fraction=0.1)
+        cval.train_test_split(range(3), test_fraction=0.1)
+        cval.train_test_split(range(3), train_fraction=0.1)
 
     assert_equal(len(warn_queue), 4)
-    assert_equal(warn_queue[0], expected_message[0])
-    assert_equal(warn_queue[1], expected_message[1])
-    assert_equal(warn_queue[2], expected_message[0])
-    assert_equal(warn_queue[3], expected_message[1])
-
-    # restore default behavior
-    warnings.warn = warnings_warn
+    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])
 
 
 def test_train_test_split():