1 files changed, 54 insertions, 51 deletions
diff --git a/numpy/lib/tests/test_nanfunctions.py b/numpy/lib/tests/test_nanfunctions.py
index e69d9dd7d..55877e602 100644
--- a/numpy/lib/tests/test_nanfunctions.py
+++ b/numpy/lib/tests/test_nanfunctions.py
@@ -113,42 +113,46 @@ class TestNanFunctions_MinMax(object):
         for f in self.nanfuncs:
             assert_(f(0.) == 0.)
 
-    def test_matrices(self):
+    def test_subclass(self):
+        class MyNDArray(np.ndarray):
+            pass
+
         # Check that it works and that type and
         # shape are preserved
-        mat = np.matrix(np.eye(3))
+        mine = np.eye(3).view(MyNDArray)
         for f in self.nanfuncs:
-            res = f(mat, axis=0)
-            assert_(isinstance(res, np.matrix))
-            assert_(res.shape == (1, 3))
-            res = f(mat, axis=1)
-            assert_(isinstance(res, np.matrix))
-            assert_(res.shape == (3, 1))
-            res = f(mat)
-            assert_(np.isscalar(res))
+            res = f(mine, axis=0)
+            assert_(isinstance(res, MyNDArray))
+            assert_(res.shape == (3,))
+            res = f(mine, axis=1)
+            assert_(isinstance(res, MyNDArray))
+            assert_(res.shape == (3,))
+            res = f(mine)
+            assert_(res.shape == ())
+
         # check that rows of nan are dealt with for subclasses (#4628)
-        mat[1] = np.nan
+        mine[1] = np.nan
         for f in self.nanfuncs:
             with warnings.catch_warnings(record=True) as w:
                 warnings.simplefilter('always')
-                res = f(mat, axis=0)
-                assert_(isinstance(res, np.matrix))
+                res = f(mine, axis=0)
+                assert_(isinstance(res, MyNDArray))
                 assert_(not np.any(np.isnan(res)))
                 assert_(len(w) == 0)
 
             with warnings.catch_warnings(record=True) as w:
                 warnings.simplefilter('always')
-                res = f(mat, axis=1)
-                assert_(isinstance(res, np.matrix))
-                assert_(np.isnan(res[1, 0]) and not np.isnan(res[0, 0])
-                        and not np.isnan(res[2, 0]))
+                res = f(mine, axis=1)
+                assert_(isinstance(res, MyNDArray))
+                assert_(np.isnan(res[1]) and not np.isnan(res[0])
+                        and not np.isnan(res[2]))
                 assert_(len(w) == 1, 'no warning raised')
                 assert_(issubclass(w[0].category, RuntimeWarning))
 
             with warnings.catch_warnings(record=True) as w:
                 warnings.simplefilter('always')
-                res = f(mat)
-                assert_(np.isscalar(res))
+                res = f(mine)
+                assert_(res.shape == ())
                 assert_(res != np.nan)
                 assert_(len(w) == 0)
 
@@ -209,19 +213,22 @@ class TestNanFunctions_ArgminArgmax(object):
         for f in self.nanfuncs:
             assert_(f(0.) == 0.)
 
-    def test_matrices(self):
+    def test_subclass(self):
+        class MyNDArray(np.ndarray):
+            pass
+
         # Check that it works and that type and
         # shape are preserved
-        mat = np.matrix(np.eye(3))
+        mine = np.eye(3).view(MyNDArray)
         for f in self.nanfuncs:
-            res = f(mat, axis=0)
-            assert_(isinstance(res, np.matrix))
-            assert_(res.shape == (1, 3))
-            res = f(mat, axis=1)
-            assert_(isinstance(res, np.matrix))
-            assert_(res.shape == (3, 1))
-            res = f(mat)
-            assert_(np.isscalar(res))
+            res = f(mine, axis=0)
+            assert_(isinstance(res, MyNDArray))
+            assert_(res.shape == (3,))
+            res = f(mine, axis=1)
+            assert_(isinstance(res, MyNDArray))
+            assert_(res.shape == (3,))
+            res = f(mine)
+            assert_(res.shape == ())
 
 
 class TestNanFunctions_IntTypes(object):
@@ -381,19 +388,27 @@ class SharedNanFunctionsTestsMixin(object):
         for f in self.nanfuncs:
             assert_(f(0.) == 0.)
 
-    def test_matrices(self):
+    def test_subclass(self):
+        class MyNDArray(np.ndarray):
+            pass
+
         # Check that it works and that type and
         # shape are preserved
-        mat = np.matrix(np.eye(3))
+        array = np.eye(3)
+        mine = array.view(MyNDArray)
         for f in self.nanfuncs:
-            res = f(mat, axis=0)
-            assert_(isinstance(res, np.matrix))
-            assert_(res.shape == (1, 3))
-            res = f(mat, axis=1)
-            assert_(isinstance(res, np.matrix))
-            assert_(res.shape == (3, 1))
-            res = f(mat)
-            assert_(np.isscalar(res))
+            expected_shape = f(array, axis=0).shape
+            res = f(mine, axis=0)
+            assert_(isinstance(res, MyNDArray))
+            assert_(res.shape == expected_shape)
+            expected_shape = f(array, axis=1).shape
+            res = f(mine, axis=1)
+            assert_(isinstance(res, MyNDArray))
+            assert_(res.shape == expected_shape)
+            expected_shape = f(array).shape
+            res = f(mine)
+            assert_(isinstance(res, MyNDArray))
+            assert_(res.shape == expected_shape)
 
 
 class TestNanFunctions_SumProd(SharedNanFunctionsTestsMixin):
@@ -481,18 +496,6 @@ class TestNanFunctions_CumSumProd(SharedNanFunctionsTestsMixin):
                 res = f(d, axis=axis)
                 assert_equal(res.shape, (3, 5, 7, 11))
 
-    def test_matrices(self):
-        # Check that it works and that type and
-        # shape are preserved
-        mat = np.matrix(np.eye(3))
-        for f in self.nanfuncs:
-            for axis in np.arange(2):
-                res = f(mat, axis=axis)
-                assert_(isinstance(res, np.matrix))
-                assert_(res.shape == (3, 3))
-            res = f(mat)
-            assert_(res.shape == (1, 3*3))
-
     def test_result_values(self):
         for axis in (-2, -1, 0, 1, None):
             tgt = np.cumprod(_ndat_ones, axis=axis)