Fixed typos, merged documentation, added references

doc/library/tensor/basic.txt

@@ -1000,6 +1000,7 @@ Reductions
 
     :Returns: A new array holding the result.
 
+.. _indexing:
 
 Indexing
 ========

doc/library/tensor/nnet/neighbours.txt

@@ -88,7 +88,7 @@
 
         .. note:: Currently, the function doesn't support tensors created with
            `neib_step` different from default value. This means that it may be
-           impossible to compute the gradient in this case.
+           impossible to compute the gradient of an error signal in this case.
 
 
         Example:
@@ -102,3 +102,5 @@
             im_new_val = inv_window(neibs_val)
 
         .. note:: The code will output the initial image array.
+
+- See also: :ref:`indexing`, :ref:`lib_scan`

theano/sandbox/neighbours.py

 """
 Neighbours was moved into theano.tensor.nnet.neighbours.
-This file was created for compatibility compatibility.
+This file was created for compatibility.
 """
 from theano.tensor.nnet.neighbours import (images2neibs, neibs2images,
     Images2Neibs)
\ No newline at end of file

theano/tensor/nnet/neighbours.py

@@ -439,16 +439,21 @@ def images2neibs(ten4, neib_shape, neib_step=None, mode='valid'):
               .. code-block:: python
 
                  idx = 0
-                for i in xrange(list 1 dim)
-                    for j in xrange(list 2 dim)
-                        for k in <image column coordinates>
-                            for l in <image row coordinates>
+                 for i in xrange(list 1 dim):
+                     for j in xrange(list 2 dim):
+                         for k in <image column coordinates>:
+                             for l in <image row coordinates>:
                                  output[idx,:]
                                       = flattened version of ten4[i,j,l:l+r,k:k+c]
                                  idx += 1
-                (note: the op isn't necessarily implemented internally with these
-                for loops, they're just the easiest way to describe the output
-                pattern)
+
+              .. note:: The operation isn't necessarily implemented internally with 
+                 these for loops, they're just the easiest way to describe the output
+                 pattern.
+                 
+        .. note:: Currently the step size should be chosen in the way that the 
+           corresponding dimension :math:`i` (width or height) is equal to 
+           :math:`n * step\_size_i + neib\_shape_i` for some :math:`n`
     """
     return Images2Neibs(mode)(ten4, neib_shape, neib_step)
 
@@ -462,6 +467,10 @@ def neibs2images(neibs, neib_shape, original_shape, mode='valid'):
     :param original_shape: original shape of the 4d tensor given to images2neib
 
     :return: Return a 4d tensor of shape `original_shape`.
+
+    .. note:: Currently, the function doesn't support tensors created with
+       `neib_step` different from default value. This means that it may be
+       impossible to compute the gradient of an error signal in this case.
     """
     neibs = T.as_tensor_variable(neibs)
     neib_shape = T.as_tensor_variable(neib_shape)