Adding memoized functions

appengine/findit/libs/math/vectors.py

 # Copyright 2016 The Chromium Authors. All rights reserved.
 # Use of this source code is governed by a BSD-style license that can be
 # found in the LICENSE file.
 
 import math
 import numpy as np
 
 
 def vsum(vs, shape=None):
   """Accurate summation of a list of vectors.
@@ skipping 13 matching lines @@
     the vectors; (3) not all the vectors in the list have the same shape.
   """
   if shape is None:
     if not vs:
       return None
 
     shape = vs[0].shape
 
   # It'd be better to vectorize the implementation of Shewchuk's
   # algorithm directly, so we can avoid needing to traverse ``vs``
-  # repeatedly. However, this is deemed to have too high a maintinence
+  # repeatedly. However, this is deemed to have too high a maintenance
   # cost for the performance benefit.
   total = np.zeros(shape)
   it = np.nditer(total, flags=['multi_index'], op_flags=['writeonly'])
   while not it.finished:
     it[0] = math.fsum(v[it.multi_index] for v in vs)
     it.iternext()
 
   return total