* prevent modifications to the mask to be back-propagated w/ __array_wrap__

2 files changed, 19 insertions, 1 deletions

diff --git a/numpy/ma/core.py b/numpy/ma/core.py
index 90c74d9c1..29c02573a 100644
--- a/numpy/ma/core.py
+++ b/numpy/ma/core.py
@@ -1817,7 +1817,8 @@ class MaskedArray(ndarray):
                     if d is not nomask:
                         m = d
                 else:
-                    m |= d
+                    # Don't modify inplace, we risk back-propagation
+                    m = (m | d)
             # Make sure the mask has the proper size
             if result.shape == () and m:
                 return masked
diff --git a/numpy/ma/tests/test_core.py b/numpy/ma/tests/test_core.py
index c92c650b4..59acf6cfe 100644
--- a/numpy/ma/tests/test_core.py
+++ b/numpy/ma/tests/test_core.py
@@ -1025,6 +1025,23 @@ class TestMaskedArrayArithmetic(TestCase):
         assert_equal(test.mask, [False, False])
 
 
+    def test_numpyarithmetics(self):
+        "Check that the mask is not back-propagated when using numpy functions"
+        a = masked_array([-1, 0, 1, 2, 3], mask=[0, 0, 0, 0, 1])
+        control = masked_array([np.nan, np.nan, 0, np.log(2), -1],
+                               mask=[1, 1, 0, 0, 1])
+        #
+        test = log(a)
+        assert_equal(test, control)
+        assert_equal(test.mask, control.mask)
+        assert_equal(a.mask, [0, 0, 0, 0, 1])
+        #
+        test = np.log(a)
+        assert_equal(test, control)
+        assert_equal(test.mask, control.mask)
+        assert_equal(a.mask, [0, 0, 0, 0, 1])
+        #
+
 #------------------------------------------------------------------------------
 
 class TestMaskedArrayAttributes(TestCase):