numpy 1.8.0 apply_along_axis named arguments

--- shape_base.py   2014-03-06 13:18:57.014449386 +0100
+++ /lib/python2.7/site-packages/numpy/lib/shape_base.py    2014-03-06 11:36:44.373984020 +0100
@@ -10,7 +10,7 @@
 from numpy.core.fromnumeric import product, reshape
 from numpy.core import hstack, vstack, atleast_3d

-def apply_along_axis(func1d,axis,arr,*args):
+def apply_along_axis(func1d,axis,arr,*args,**moreargs):
     """
     Apply a function to 1-D slices along the given axis.

@@ -76,7 +76,8 @@
     i[axis] = slice(None, None)
     outshape = asarray(arr.shape).take(indlist)
     i.put(indlist, ind)
-    res = func1d(arr[tuple(i.tolist())],*args)
+    print
+    res = func1d(arr[tuple(i.tolist())],*args,**moreargs)
     #  if res is a number, then we have a smaller output array
     if isscalar(res):
         outarr = zeros(outshape, asarray(res).dtype)
@@ -92,7 +93,7 @@
                 ind[n] = 0
                 n -= 1
             i.put(indlist, ind)
-            res = func1d(arr[tuple(i.tolist())],*args)
+            res = func1d(arr[tuple(i.tolist())],*args,**moreargs)
             outarr[tuple(ind)] = res
             k += 1
         return outarr
@@ -113,7 +114,7 @@
                 ind[n] = 0
                 n -= 1
             i.put(indlist, ind)
-            res = func1d(arr[tuple(i.tolist())],*args)
+            res = func1d(arr[tuple(i.tolist())],*args,**moreargs)
             outarr[tuple(i.tolist())] = res
             k += 1
         return outarr
@@ -832,4 +833,3 @@
         shape[i] = dim_out
         n //= max(dim_in, 1)
     return c.reshape(shape)
-