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, 16 insertions, 16 deletions

diff --git a/numpy/lib/index_tricks.py b/numpy/lib/index_tricks.py
index b2ea5e965..570cd0f1d 100644
--- a/numpy/lib/index_tricks.py
+++ b/numpy/lib/index_tricks.py
@@ -6,8 +6,8 @@ __all__ = ['ravel_multi_index',
            'ogrid',
            'r_', 'c_', 's_',
            'index_exp', 'ix_',
-           'ndenumerate','ndindex',
-           'fill_diagonal','diag_indices','diag_indices_from']
+           'ndenumerate', 'ndindex',
+           'fill_diagonal', 'diag_indices', 'diag_indices_from']
 
 import sys
 import numpy.core.numeric as _nx
@@ -144,7 +144,7 @@ class nd_grid(object):
     """
     def __init__(self, sparse=False):
         self.sparse = sparse
-    def __getitem__(self,key):
+    def __getitem__(self, key):
         try:
             size = []
             typ = int
@@ -180,7 +180,7 @@ class nd_grid(object):
             if self.sparse:
                 slobj = [_nx.newaxis]*len(size)
                 for k in range(len(size)):
-                    slobj[k] = slice(None,None)
+                    slobj[k] = slice(None, None)
                     nn[k] = nn[k][slobj]
                     slobj[k] = _nx.newaxis
             return nn
@@ -195,12 +195,12 @@ class nd_grid(object):
                 if step != 1:
                     step = (key.stop-start)/float(step-1)
                 stop = key.stop+step
-                return _nx.arange(0, length,1, float)*step + start
+                return _nx.arange(0, length, 1, float)*step + start
             else:
                 return _nx.arange(start, stop, step)
 
-    def __getslice__(self,i,j):
-        return _nx.arange(i,j)
+    def __getslice__(self, i, j):
+        return _nx.arange(i, j)
 
     def __len__(self):
         return 0
@@ -237,12 +237,12 @@ class AxisConcatenator(object):
         self.trans1d = trans1d
         self.ndmin = ndmin
 
-    def __getitem__(self,key):
+    def __getitem__(self, key):
         trans1d = self.trans1d
         ndmin = self.ndmin
         if isinstance(key, str):
             frame = sys._getframe().f_back
-            mymat = matrix.bmat(key,frame.f_globals,frame.f_locals)
+            mymat = matrix.bmat(key, frame.f_globals, frame.f_locals)
             return mymat
         if not isinstance(key, tuple):
             key = (key,)
@@ -265,10 +265,10 @@ class AxisConcatenator(object):
                 else:
                     newobj = _nx.arange(start, stop, step)
                 if ndmin > 1:
-                    newobj = array(newobj,copy=False,ndmin=ndmin)
+                    newobj = array(newobj, copy=False, ndmin=ndmin)
                     if trans1d != -1:
-                        newobj = newobj.swapaxes(-1,trans1d)
-            elif isinstance(key[k],str):
+                        newobj = newobj.swapaxes(-1, trans1d)
+            elif isinstance(key[k], str):
                 if k != 0:
                     raise ValueError("special directives must be the "
                             "first entry.")
@@ -293,7 +293,7 @@ class AxisConcatenator(object):
                 except (ValueError, TypeError):
                     raise ValueError("unknown special directive")
             elif type(key[k]) in ScalarType:
-                newobj = array(key[k],ndmin=ndmin)
+                newobj = array(key[k], ndmin=ndmin)
                 scalars.append(k)
                 scalar = True
                 scalartypes.append(newobj.dtype)
@@ -323,11 +323,11 @@ class AxisConcatenator(object):
             for k in scalars:
                 objs[k] = objs[k].astype(final_dtype)
 
-        res = _nx.concatenate(tuple(objs),axis=self.axis)
+        res = _nx.concatenate(tuple(objs), axis=self.axis)
         return self._retval(res)
 
-    def __getslice__(self,i,j):
-        res = _nx.arange(i,j)
+    def __getslice__(self, i, j):
+        res = _nx.arange(i, j)
         return self._retval(res)
 
     def __len__(self):