core

MaskedArray.__new__: prevents data.mask to change shape and force a copy of _data.mask

2 files changed, 14 insertions, 0 deletions

diff --git a/numpy/ma/core.py b/numpy/ma/core.py
index b4f08171a..c8664c754 100644
--- a/numpy/ma/core.py
+++ b/numpy/ma/core.py
@@ -1229,6 +1229,9 @@ class MaskedArray(ndarray):
         _data = np.array(data, dtype=dtype, copy=copy, subok=True, ndmin=ndmin)
         _baseclass = getattr(data, '_baseclass', type(_data))
         _optinfo = {}
+        # Check that we'ew not erasing the mask..........
+        if isinstance(data,MaskedArray) and (data.shape != _data.shape):
+            copy = True
         # Careful, cls might not always be MaskedArray...
         if not isinstance(data, cls) or not subok:
             _data = _data.view(cls)
@@ -1267,6 +1270,9 @@ class MaskedArray(ndarray):
                 if copy:
                     _data._mask = _data._mask.copy()
                     _data._sharedmask = False
+                    # Reset the shape of the original mask
+                    if getmask(data) is not nomask:
+                        data._mask.shape = data.shape
                 else:
                     _data._sharedmask = True
         # Case 2. : With a mask in input ........
diff --git a/numpy/ma/tests/test_core.py b/numpy/ma/tests/test_core.py
index e581e274e..e24fa6f54 100644
--- a/numpy/ma/tests/test_core.py
+++ b/numpy/ma/tests/test_core.py
@@ -139,6 +139,14 @@ class TestMaskedArray(TestCase):
         assert_equal(x._data,[[1,2,3]])
         assert_equal(x._mask,[[1,0,0]])
 
+    def test_creation_ndmin_from_maskedarray(self):
+        "Make sure we're not losing the original mask w/ ndmin"
+        x = array([1,2,3])
+        x[-1] = masked
+        xx = array(x, ndmin=2, dtype=float)
+        assert_equal(x.shape, x._mask.shape)
+        assert_equal(xx.shape, xx._mask.shape)
+
     def test_creation_maskcreation(self):
         "Tests how masks are initialized at the creation of Maskedarrays."
         data = arange(24, dtype=float)