Make None fully backward compatible

scipy · Apr 28, 2016 · 7c5d6a0 · 7c5d6a0
1 parent 2be239a
commit 7c5d6a0
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Showing 2 changed files with 16 additions and 10 deletions.
diff --git a/scipy/stats/stats.py b/scipy/stats/stats.py
@@ -4389,14 +4389,16 @@ def mannwhitneyu(x, y, use_continuity=True, alternative=None):
             Whether to get the p-value for the one-sided hypothesis ('less'
             or 'greater'), or for the two-sided hypothesis ('two-sided').
             Defaults to None, which results in a p-value half the size of
-            the 'two-sided' p-value. The default behavior is not the same
-            as using 'less' or 'greater', is not recommended, and will soon
-            be deprecated.
+            the 'two-sided' p-value and a different U statistic. The default
+            behavior is not the same as using 'less' or 'greater', is not
+            recommended, and will soon be deprecated.
 
     Returns
     -------
     statistic : float
-        The Mann-Whitney statistics.
+        The Mann-Whitney U statistic, equal to min(U for x, U for y) if
+        `alternative` is equal to None (not recommended; to be deprecated),
+        and U for y otherwise.
     pvalue : float
         p-value assuming an asymptotic normal distribution. One-sided or
         two-sided, depending on the choice of `alternative`.
@@ -4437,15 +4439,19 @@ def mannwhitneyu(x, y, use_continuity=True, alternative=None):
 
     z = (bigu - meanrank) / sd
     if alternative is None:
-        # This behavior, equal to one-half the size of the two-sided
+        # This behavior, equal to half the size of the two-sided
         # p-value, will soon be deprecated.
         p = distributions.norm.sf(abs(z))
     elif alternative == 'two-sided':
         p = 2 * distributions.norm.sf(abs(z))
     else:
         p = distributions.norm.sf(z)
 
-    return MannwhitneyuResult(u2, p)
+    u = u2
+    # This behavior will soon be deprecated.
+    if alternative is None:
+        u = min(u1, u2)
+    return MannwhitneyuResult(u, p)
 
 RanksumsResult = namedtuple('RanksumsResult', ('statistic', 'pvalue'))
 

diff --git a/scipy/stats/tests/test_stats.py b/scipy/stats/tests/test_stats.py
@@ -2766,9 +2766,9 @@ def test_mannwhitneyu_default(self):
 
         assert_equal(p1, p2)
         assert_equal(p1, p3)
-        assert_equal(u1, 498)
+        assert_equal(u1, 102)
         assert_equal(u2, 102)
-        assert_equal(u3, 498)
+        assert_equal(u3, 102)
         assert_approx_equal(p1, 4.5941632666275e-05,
                             significant=self.significant)
 
@@ -2813,9 +2813,9 @@ def test_mannwhitneyu_no_correct_default(self):
 
         assert_equal(p1, p2)
         assert_equal(p1, p3)
-        assert_equal(u1, 498)
+        assert_equal(u1, 102)
         assert_equal(u2, 102)
-        assert_equal(u3, 498)
+        assert_equal(u3, 102)
         assert_approx_equal(p1, 4.40940099958089e-05,
                             significant=self.significant)