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, 25 insertions, 25 deletions

diff --git a/numpy/matrixlib/defmatrix.py b/numpy/matrixlib/defmatrix.py
index 1ca835af2..0a73725c2 100644
--- a/numpy/matrixlib/defmatrix.py
+++ b/numpy/matrixlib/defmatrix.py
@@ -39,7 +39,7 @@ else:
     del k
 
     def _eval(astr):
-        str_ = astr.translate(_table,_todelete)
+        str_ = astr.translate(_table, _todelete)
         if not str_:
             raise TypeError("Invalid data string supplied: " + astr)
         else:
@@ -95,7 +95,7 @@ def asmatrix(data, dtype=None):
     """
     return matrix(data, dtype=dtype, copy=False)
 
-def matrix_power(M,n):
+def matrix_power(M, n):
     """
     Raise a square matrix to the (integer) power `n`.
 
@@ -169,7 +169,7 @@ def matrix_power(M,n):
     M = asanyarray(M)
     if len(M.shape) != 2 or M.shape[0] != M.shape[1]:
         raise ValueError("input must be a square array")
-    if not issubdtype(type(n),int):
+    if not issubdtype(type(n), int):
         raise TypeError("exponent must be an integer")
 
     from numpy.linalg import inv
@@ -185,21 +185,21 @@ def matrix_power(M,n):
     result = M
     if n <= 3:
         for _ in range(n-1):
-            result=N.dot(result,M)
+            result=N.dot(result, M)
         return result
 
     # binary decomposition to reduce the number of Matrix
     # multiplications for n > 3.
     beta = binary_repr(n)
-    Z,q,t = M,0,len(beta)
+    Z, q, t = M, 0, len(beta)
     while beta[t-q-1] == '0':
-        Z = N.dot(Z,Z)
+        Z = N.dot(Z, Z)
         q += 1
     result = Z
-    for k in range(q+1,t):
-        Z = N.dot(Z,Z)
+    for k in range(q+1, t):
+        Z = N.dot(Z, Z)
         if beta[t-k-1] == '1':
-            result = N.dot(result,Z)
+            result = N.dot(result, Z)
     return result
 
 
@@ -271,9 +271,9 @@ class matrix(N.ndarray):
         if (ndim > 2):
             raise ValueError("matrix must be 2-dimensional")
         elif ndim == 0:
-            shape = (1,1)
+            shape = (1, 1)
         elif ndim == 1:
-            shape = (1,shape[0])
+            shape = (1, shape[0])
 
         order = False
         if (ndim == 2) and arr.flags.fortran:
@@ -304,9 +304,9 @@ class matrix(N.ndarray):
         else:
             newshape = self.shape
         if ndim == 0:
-            self.shape = (1,1)
+            self.shape = (1, 1)
         elif ndim == 1:
-            self.shape = (1,newshape[0])
+            self.shape = (1, newshape[0])
         return
 
     def __getitem__(self, index):
@@ -330,13 +330,13 @@ class matrix(N.ndarray):
             except:
                 n = 0
             if n > 1 and isscalar(index[1]):
-                out.shape = (sh,1)
+                out.shape = (sh, 1)
             else:
-                out.shape = (1,sh)
+                out.shape = (1, sh)
         return out
 
     def __mul__(self, other):
-        if isinstance(other,(N.ndarray, list, tuple)) :
+        if isinstance(other, (N.ndarray, list, tuple)) :
             # This promotes 1-D vectors to row vectors
             return N.dot(self, asmatrix(other))
         if isscalar(other) or not hasattr(other, '__rmul__') :
@@ -378,7 +378,7 @@ class matrix(N.ndarray):
         orientation.
         """
         if axis is None:
-            return self[0,0]
+            return self[0, 0]
         elif axis==0:
             return self
         elif axis==1:
@@ -391,7 +391,7 @@ class matrix(N.ndarray):
         to a scalar like _align, but are using keepdims=True
         """
         if axis is None:
-            return self[0,0]
+            return self[0, 0]
         else:
             return self
 
@@ -862,7 +862,7 @@ class matrix(N.ndarray):
                 [ 0.,  1.]])
 
         """
-        M,N = self.shape
+        M, N = self.shape
         if M == N:
             from numpy.dual import inv as func
         else:
@@ -997,7 +997,7 @@ class matrix(N.ndarray):
     H = property(getH, None, doc="hermitian (conjugate) transpose")
     I = property(getI, None, doc="inverse")
 
-def _from_string(str,gdict,ldict):
+def _from_string(str, gdict, ldict):
     rows = str.split(';')
     rowtup = []
     for row in rows:
@@ -1018,8 +1018,8 @@ def _from_string(str,gdict,ldict):
                     raise KeyError("%s not found" % (col,))
 
             coltup.append(thismat)
-        rowtup.append(concatenate(coltup,axis=-1))
-    return concatenate(rowtup,axis=0)
+        rowtup.append(concatenate(coltup, axis=-1))
+    return concatenate(rowtup, axis=0)
 
 
 def bmat(obj, ldict=None, gdict=None):
@@ -1084,10 +1084,10 @@ def bmat(obj, ldict=None, gdict=None):
         arr_rows = []
         for row in obj:
             if isinstance(row, N.ndarray):  # not 2-d
-                return matrix(concatenate(obj,axis=-1))
+                return matrix(concatenate(obj, axis=-1))
             else:
-                arr_rows.append(concatenate(row,axis=-1))
-        return matrix(concatenate(arr_rows,axis=0))
+                arr_rows.append(concatenate(row, axis=-1))
+        return matrix(concatenate(arr_rows, axis=0))
     if isinstance(obj, N.ndarray):
         return matrix(obj)