[Numpy-svn] r6357 - in branches/1.2.x/numpy/ma: . tests

numpy-svn at scipy.org numpy-svn at scipy.org
Tue Feb 10 20:53:09 EST 2009


Author: pierregm
Date: 2009-02-10 19:52:37 -0600 (Tue, 10 Feb 2009)
New Revision: 6357

Modified:
   branches/1.2.x/numpy/ma/core.py
   branches/1.2.x/numpy/ma/tests/test_core.py
Log:
* MaskedArray.__array_wrap__ : forces the domain (if any) to a ndarray (fill with True)

Modified: branches/1.2.x/numpy/ma/core.py
===================================================================
--- branches/1.2.x/numpy/ma/core.py	2009-02-11 01:51:28 UTC (rev 6356)
+++ branches/1.2.x/numpy/ma/core.py	2009-02-11 01:52:37 UTC (rev 6357)
@@ -1577,10 +1577,11 @@
             # Get the domain mask................
             domain = ufunc_domain.get(func, None)
             if domain is not None:
+                # Take the domain, and make sure it's a ndarray
                 if len(args) > 2:
-                    d = reduce(domain, args)
+                    d = filled(reduce(domain, args), True)
                 else:
-                    d = domain(*args)
+                    d = filled(domain(*args), True)
                 # Fill the result where the domain is wrong
                 try:
                     # Binary domain: take the last value

Modified: branches/1.2.x/numpy/ma/tests/test_core.py
===================================================================
--- branches/1.2.x/numpy/ma/tests/test_core.py	2009-02-11 01:51:28 UTC (rev 6356)
+++ branches/1.2.x/numpy/ma/tests/test_core.py	2009-02-11 01:52:37 UTC (rev 6357)
@@ -826,7 +826,6 @@
             self.failUnless(output[0] is masked)
 
 
-
     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])
@@ -1143,7 +1142,17 @@
         self.failUnless(amask.max(1)[0].mask)
         self.failUnless(amask.min(1)[0].mask)
 
+    def test_ndarray_mask(self):
+        "Check that the mask of the result is a ndarray (not a MaskedArray...)"
+        a = masked_array([-1, 0, 1, 2, 3], mask=[0, 0, 0, 0, 1])
+        test = np.sqrt(a)
+        control = masked_array([-1, 0, 1, np.sqrt(2), -1],
+                          mask=[1, 0, 0, 0, 1])
+        assert_equal(test, control)
+        assert_equal(test.mask, control.mask)
+        self.failUnless(not isinstance(test.mask, MaskedArray))
 
+
 #------------------------------------------------------------------------------
 
 class TestMaskedArrayInPlaceArithmetics(TestCase):




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