MAINT: Remove code duplicated from np.r_ in np.ma.mr_

Also adds a test for the disabled-by-design behaviour - this would return
raw matrices, not masked arrays

3 files changed, 12 insertions, 52 deletions

diff --git a/numpy/lib/index_tricks.py b/numpy/lib/index_tricks.py
index 1fd530f33..58d3e0dcf 100644
--- a/numpy/lib/index_tricks.py
+++ b/numpy/lib/index_tricks.py
@@ -237,6 +237,8 @@ class AxisConcatenator(object):
     For detailed documentation on usage, see `r_`.
 
     """
+    # allow ma.mr_ to override this
+    concatenate = staticmethod(_nx.concatenate)
 
     def _retval(self, res):
         if self.matrix:
@@ -345,7 +347,7 @@ class AxisConcatenator(object):
             for k in scalars:
                 objs[k] = objs[k].astype(final_dtype)
 
-        res = _nx.concatenate(tuple(objs), axis=self.axis)
+        res = self.concatenate(tuple(objs), axis=self.axis)
         return self._retval(res)
 
     def __len__(self):
diff --git a/numpy/ma/extras.py b/numpy/ma/extras.py
index e100e471c..10b9634a3 100644
--- a/numpy/ma/extras.py
+++ b/numpy/ma/extras.py
@@ -1461,60 +1461,15 @@ class MAxisConcatenator(AxisConcatenator):
     mr_class
 
     """
-
-    def __init__(self, axis=0):
-        AxisConcatenator.__init__(self, axis, matrix=False)
+    concatenate = staticmethod(concatenate)
 
     def __getitem__(self, key):
+        # matrix builder syntax, like 'a, b; c, d'
         if isinstance(key, str):
             raise MAError("Unavailable for masked array.")
-        if not isinstance(key, tuple):
-            key = (key,)
-        objs = []
-        scalars = []
-        final_dtypedescr = None
-        for k in range(len(key)):
-            scalar = False
-            if isinstance(key[k], slice):
-                step = key[k].step
-                start = key[k].start
-                stop = key[k].stop
-                if start is None:
-                    start = 0
-                if step is None:
-                    step = 1
-                if isinstance(step, complex):
-                    size = int(abs(step))
-                    newobj = np.linspace(start, stop, num=size)
-                else:
-                    newobj = np.arange(start, stop, step)
-            elif isinstance(key[k], str):
-                if (key[k] in 'rc'):
-                    self.matrix = True
-                    self.col = (key[k] == 'c')
-                    continue
-                try:
-                    self.axis = int(key[k])
-                    continue
-                except (ValueError, TypeError):
-                    raise ValueError("Unknown special directive")
-            elif type(key[k]) in np.ScalarType:
-                newobj = asarray([key[k]])
-                scalars.append(k)
-                scalar = True
-            else:
-                newobj = key[k]
-            objs.append(newobj)
-            if isinstance(newobj, ndarray) and not scalar:
-                if final_dtypedescr is None:
-                    final_dtypedescr = newobj.dtype
-                elif newobj.dtype > final_dtypedescr:
-                    final_dtypedescr = newobj.dtype
-        if final_dtypedescr is not None:
-            for k in scalars:
-                objs[k] = objs[k].astype(final_dtypedescr)
-        res = concatenate(tuple(objs), axis=self.axis)
-        return self._retval(res)
+
+        return super(MAxisConcatenator, self).__getitem__(key)
+
 
 class mr_class(MAxisConcatenator):
     """
diff --git a/numpy/ma/tests/test_extras.py b/numpy/ma/tests/test_extras.py
index e7ebd8b82..7de21ff59 100644
--- a/numpy/ma/tests/test_extras.py
+++ b/numpy/ma/tests/test_extras.py
@@ -14,7 +14,8 @@ import itertools
 
 import numpy as np
 from numpy.testing import (
-    TestCase, run_module_suite, assert_warns, suppress_warnings
+    TestCase, run_module_suite, assert_warns, suppress_warnings,
+    assert_raises
     )
 from numpy.ma.testutils import (
     assert_, assert_array_equal, assert_equal, assert_almost_equal
@@ -304,6 +305,8 @@ class TestConcatenator(TestCase):
         assert_array_equal(d[5:,:], b_2)
         assert_array_equal(d.mask, np.r_[m_1, m_2])
 
+    def test_matrix_builder(self):
+        assert_raises(np.ma.MAError, lambda: mr_['1, 2; 3, 4'])
 
 class TestNotMasked(TestCase):
     # Tests notmasked_edges and notmasked_contiguous.