def locationscore(self,rows):
  locations=dict([(row[0],1000000) for row in rows])
  for row in rows:
    loc=sum(row[1:])
    if loc<locations[row[0]]: locations[row[0]]=loc
  return self.normalizescores(locations,smallIsBetter=1)

##</code><code>##

def distancescore(self,rows):
  # If there's only one word, everyone wins!
  if len(rows[0])<=2: return dict([(row[0],1.0) for row in rows])
  # Initialize the dictionary with large values
  mindistance=dict([(row[0],1000000) for row in rows])
  for row in rows:
    dist=sum([abs(row[i]-row[i-1]) for i in range(2,len(row))])
    if dist<mindistance[row[0]]: mindistance[row[0]]=dist
  return self.normalizescores(mindistance,smallIsBetter=1)