1 files changed, 92 insertions, 31 deletions
diff --git a/numpy/lib/index_tricks.py b/numpy/lib/index_tricks.py
index d2139338e..009e6d229 100644
--- a/numpy/lib/index_tricks.py
+++ b/numpy/lib/index_tricks.py
@@ -121,39 +121,13 @@ class nd_grid(object):
     Notes
     -----
     Two instances of `nd_grid` are made available in the NumPy namespace,
-    `mgrid` and `ogrid`::
+    `mgrid` and `ogrid`, approximately defined as::
 
         mgrid = nd_grid(sparse=False)
         ogrid = nd_grid(sparse=True)
 
     Users should use these pre-defined instances instead of using `nd_grid`
     directly.
-
-    Examples
-    --------
-    >>> mgrid = np.lib.index_tricks.nd_grid()
-    >>> mgrid[0:5,0:5]
-    array([[[0, 0, 0, 0, 0],
-            [1, 1, 1, 1, 1],
-            [2, 2, 2, 2, 2],
-            [3, 3, 3, 3, 3],
-            [4, 4, 4, 4, 4]],
-           [[0, 1, 2, 3, 4],
-            [0, 1, 2, 3, 4],
-            [0, 1, 2, 3, 4],
-            [0, 1, 2, 3, 4],
-            [0, 1, 2, 3, 4]]])
-    >>> mgrid[-1:1:5j]
-    array([-1. , -0.5,  0. ,  0.5,  1. ])
-
-    >>> ogrid = np.lib.index_tricks.nd_grid(sparse=True)
-    >>> ogrid[0:5,0:5]
-    [array([[0],
-            [1],
-            [2],
-            [3],
-            [4]]), array([[0, 1, 2, 3, 4]])]
-
     """
 
     def __init__(self, sparse=False):
@@ -223,10 +197,97 @@ class nd_grid(object):
     def __len__(self):
         return 0
 
-mgrid = nd_grid(sparse=False)
-ogrid = nd_grid(sparse=True)
-mgrid.__doc__ = None  # set in numpy.add_newdocs
-ogrid.__doc__ = None  # set in numpy.add_newdocs
+
+class MGridClass(nd_grid):
+    """
+    `nd_grid` instance which returns a dense multi-dimensional "meshgrid".
+
+    An instance of `numpy.lib.index_tricks.nd_grid` which returns an dense
+    (or fleshed out) mesh-grid when indexed, so that each returned argument
+    has the same shape.  The dimensions and number of the output arrays are
+    equal to the number of indexing dimensions.  If the step length is not a
+    complex number, then the stop is not inclusive.
+
+    However, if the step length is a **complex number** (e.g. 5j), then
+    the integer part of its magnitude is interpreted as specifying the
+    number of points to create between the start and stop values, where
+    the stop value **is inclusive**.
+
+    Returns
+    ----------
+    mesh-grid `ndarrays` all of the same dimensions
+
+    See Also
+    --------
+    numpy.lib.index_tricks.nd_grid : class of `ogrid` and `mgrid` objects
+    ogrid : like mgrid but returns open (not fleshed out) mesh grids
+    r_ : array concatenator
+
+    Examples
+    --------
+    >>> np.mgrid[0:5,0:5]
+    array([[[0, 0, 0, 0, 0],
+            [1, 1, 1, 1, 1],
+            [2, 2, 2, 2, 2],
+            [3, 3, 3, 3, 3],
+            [4, 4, 4, 4, 4]],
+           [[0, 1, 2, 3, 4],
+            [0, 1, 2, 3, 4],
+            [0, 1, 2, 3, 4],
+            [0, 1, 2, 3, 4],
+            [0, 1, 2, 3, 4]]])
+    >>> np.mgrid[-1:1:5j]
+    array([-1. , -0.5,  0. ,  0.5,  1. ])
+
+    """
+    def __init__(self):
+        super(MGridClass, self).__init__(sparse=False)
+
+mgrid = MGridClass()
+
+class OGridClass(nd_grid):
+    """
+    `nd_grid` instance which returns an open multi-dimensional "meshgrid".
+
+    An instance of `numpy.lib.index_tricks.nd_grid` which returns an open
+    (i.e. not fleshed out) mesh-grid when indexed, so that only one dimension
+    of each returned array is greater than 1.  The dimension and number of the
+    output arrays are equal to the number of indexing dimensions.  If the step
+    length is not a complex number, then the stop is not inclusive.
+
+    However, if the step length is a **complex number** (e.g. 5j), then
+    the integer part of its magnitude is interpreted as specifying the
+    number of points to create between the start and stop values, where
+    the stop value **is inclusive**.
+
+    Returns
+    ----------
+    mesh-grid `ndarrays` with only one dimension :math:`\\neq 1`
+
+    See Also
+    --------
+    np.lib.index_tricks.nd_grid : class of `ogrid` and `mgrid` objects
+    mgrid : like `ogrid` but returns dense (or fleshed out) mesh grids
+    r_ : array concatenator
+
+    Examples
+    --------
+    >>> from numpy import ogrid
+    >>> ogrid[-1:1:5j]
+    array([-1. , -0.5,  0. ,  0.5,  1. ])
+    >>> ogrid[0:5,0:5]
+    [array([[0],
+            [1],
+            [2],
+            [3],
+            [4]]), array([[0, 1, 2, 3, 4]])]
+
+    """
+    def __init__(self):
+        super(OGridClass, self).__init__(sparse=True)
+
+ogrid = OGridClass()
+
 
 class AxisConcatenator(object):
     """