STY: Giant comma spacing fixup.

Run the 2to3 ws_comma fixer on *.py files. Some lines are now too long
and will need to be broken at some point. OTOH, some lines were already
too long and need to be broken at some point. Now seems as good a time
as any to do this with open PRs at a minimum.

1 files changed, 31 insertions, 31 deletions

diff --git a/numpy/lib/shape_base.py b/numpy/lib/shape_base.py
index c63f8140d..1363a3213 100644
--- a/numpy/lib/shape_base.py
+++ b/numpy/lib/shape_base.py
@@ -1,7 +1,7 @@
 from __future__ import division, absolute_import, print_function
 
-__all__ = ['column_stack','row_stack', 'dstack','array_split','split','hsplit',
-           'vsplit','dsplit','apply_over_axes','expand_dims',
+__all__ = ['column_stack', 'row_stack', 'dstack', 'array_split', 'split', 'hsplit',
+           'vsplit', 'dsplit', 'apply_over_axes', 'expand_dims',
            'apply_along_axis', 'kron', 'tile', 'get_array_wrap']
 
 import numpy.core.numeric as _nx
@@ -68,18 +68,18 @@ def apply_along_axis(func1d,axis,arr,*args):
         axis += nd
     if (axis >= nd):
         raise ValueError("axis must be less than arr.ndim; axis=%d, rank=%d."
-            % (axis,nd))
+            % (axis, nd))
     ind = [0]*(nd-1)
-    i = zeros(nd,'O')
+    i = zeros(nd, 'O')
     indlist = list(range(nd))
     indlist.remove(axis)
-    i[axis] = slice(None,None)
+    i[axis] = slice(None, None)
     outshape = asarray(arr.shape).take(indlist)
     i.put(indlist, ind)
     res = func1d(arr[tuple(i.tolist())],*args)
     #  if res is a number, then we have a smaller output array
     if isscalar(res):
-        outarr = zeros(outshape,asarray(res).dtype)
+        outarr = zeros(outshape, asarray(res).dtype)
         outarr[tuple(ind)] = res
         Ntot = product(outshape)
         k = 1
@@ -91,7 +91,7 @@ def apply_along_axis(func1d,axis,arr,*args):
                 ind[n-1] += 1
                 ind[n] = 0
                 n -= 1
-            i.put(indlist,ind)
+            i.put(indlist, ind)
             res = func1d(arr[tuple(i.tolist())],*args)
             outarr[tuple(ind)] = res
             k += 1
@@ -101,7 +101,7 @@ def apply_along_axis(func1d,axis,arr,*args):
         holdshape = outshape
         outshape = list(arr.shape)
         outshape[axis] = len(res)
-        outarr = zeros(outshape,asarray(res).dtype)
+        outarr = zeros(outshape, asarray(res).dtype)
         outarr[tuple(i.tolist())] = res
         k = 1
         while k < Ntot:
@@ -182,7 +182,7 @@ def apply_over_axes(func, a, axes):
         if res.ndim == val.ndim:
             val = res
         else:
-            res = expand_dims(res,axis)
+            res = expand_dims(res, axis)
             if res.ndim == val.ndim:
                 val = res
             else:
@@ -288,11 +288,11 @@ def column_stack(tup):
     """
     arrays = []
     for v in tup:
-        arr = array(v,copy=False,subok=True)
+        arr = array(v, copy=False, subok=True)
         if arr.ndim < 2:
-            arr = array(arr,copy=False,subok=True,ndmin=2).T
+            arr = array(arr, copy=False, subok=True, ndmin=2).T
         arrays.append(arr)
-    return _nx.concatenate(arrays,1)
+    return _nx.concatenate(arrays, 1)
 
 def dstack(tup):
     """
@@ -348,7 +348,7 @@ def _replace_zero_by_x_arrays(sub_arys):
     for i in range(len(sub_arys)):
         if len(_nx.shape(sub_arys[i])) == 0:
             sub_arys[i] = _nx.array([])
-        elif _nx.sometrue(_nx.equal(_nx.shape(sub_arys[i]),0)):
+        elif _nx.sometrue(_nx.equal(_nx.shape(sub_arys[i]), 0)):
             sub_arys[i] = _nx.array([])
     return sub_arys
 
@@ -383,17 +383,17 @@ def array_split(ary,indices_or_sections,axis = 0):
         Nsections = int(indices_or_sections)
         if Nsections <= 0:
             raise ValueError('number sections must be larger than 0.')
-        Neach_section,extras = divmod(Ntotal,Nsections)
+        Neach_section, extras = divmod(Ntotal, Nsections)
         section_sizes = [0] + \
                         extras * [Neach_section+1] + \
                         (Nsections-extras) * [Neach_section]
         div_points = _nx.array(section_sizes).cumsum()
 
     sub_arys = []
-    sary = _nx.swapaxes(ary,axis,0)
+    sary = _nx.swapaxes(ary, axis, 0)
     for i in range(Nsections):
         st = div_points[i]; end = div_points[i+1]
-        sub_arys.append(_nx.swapaxes(sary[st:end],axis,0))
+        sub_arys.append(_nx.swapaxes(sary[st:end], axis, 0))
 
     # there is a weird issue with array slicing that allows
     # 0x10 arrays and other such things. The following kludge is needed
@@ -474,10 +474,10 @@ def split(ary,indices_or_sections,axis=0):
         N = ary.shape[axis]
         if N % sections:
             raise ValueError('array split does not result in an equal division')
-    res = array_split(ary,indices_or_sections,axis)
+    res = array_split(ary, indices_or_sections, axis)
     return res
 
-def hsplit(ary,indices_or_sections):
+def hsplit(ary, indices_or_sections):
     """
     Split an array into multiple sub-arrays horizontally (column-wise).
 
@@ -535,11 +535,11 @@ def hsplit(ary,indices_or_sections):
     if len(_nx.shape(ary)) == 0:
         raise ValueError('hsplit only works on arrays of 1 or more dimensions')
     if len(ary.shape) > 1:
-        return split(ary,indices_or_sections,1)
+        return split(ary, indices_or_sections, 1)
     else:
-        return split(ary,indices_or_sections,0)
+        return split(ary, indices_or_sections, 0)
 
-def vsplit(ary,indices_or_sections):
+def vsplit(ary, indices_or_sections):
     """
     Split an array into multiple sub-arrays vertically (row-wise).
 
@@ -588,9 +588,9 @@ def vsplit(ary,indices_or_sections):
     """
     if len(_nx.shape(ary)) < 2:
         raise ValueError('vsplit only works on arrays of 2 or more dimensions')
-    return split(ary,indices_or_sections,0)
+    return split(ary, indices_or_sections, 0)
 
-def dsplit(ary,indices_or_sections):
+def dsplit(ary, indices_or_sections):
     """
     Split array into multiple sub-arrays along the 3rd axis (depth).
 
@@ -633,7 +633,7 @@ def dsplit(ary,indices_or_sections):
     """
     if len(_nx.shape(ary)) < 3:
         raise ValueError('vsplit only works on arrays of 3 or more dimensions')
-    return split(ary,indices_or_sections,2)
+    return split(ary, indices_or_sections, 2)
 
 def get_array_prepare(*args):
     """Find the wrapper for the array with the highest priority.
@@ -659,7 +659,7 @@ def get_array_wrap(*args):
         return wrappers[-1][-1]
     return None
 
-def kron(a,b):
+def kron(a, b):
     """
     Kronecker product of two arrays.
 
@@ -728,10 +728,10 @@ def kron(a,b):
 
     """
     b = asanyarray(b)
-    a = array(a,copy=False,subok=True,ndmin=b.ndim)
+    a = array(a, copy=False, subok=True, ndmin=b.ndim)
     ndb, nda = b.ndim, a.ndim
     if (nda == 0 or ndb == 0):
-        return _nx.multiply(a,b)
+        return _nx.multiply(a, b)
     as_ = a.shape
     bs = b.shape
     if not a.flags.contiguous:
@@ -745,7 +745,7 @@ def kron(a,b):
         else:
             bs = (1,)*(nda-ndb) + bs
             nd = nda
-    result = outer(a,b).reshape(as_+bs)
+    result = outer(a, b).reshape(as_+bs)
     axis = nd-1
     for _ in range(nd):
         result = concatenate(result, axis=axis)
@@ -819,14 +819,14 @@ def tile(A, reps):
     except TypeError:
         tup = (reps,)
     d = len(tup)
-    c = _nx.array(A,copy=False,subok=True,ndmin=d)
+    c = _nx.array(A, copy=False, subok=True, ndmin=d)
     shape = list(c.shape)
-    n = max(c.size,1)
+    n = max(c.size, 1)
     if (d < c.ndim):
         tup = (1,)*(c.ndim-d) + tup
     for i, nrep in enumerate(tup):
         if nrep!=1:
-            c = c.reshape(-1,n).repeat(nrep,0)
+            c = c.reshape(-1, n).repeat(nrep, 0)
         dim_in = shape[i]
         dim_out = dim_in*nrep
         shape[i] = dim_out