code: def closenessScores(self, expValues, actValues, fractional=True):
      
  
      # Compute the percent error in log space
      if expValues[0] > 0:
        expValue = math.log10(expValues[0])
      else:
        expValue = self.minScaledValue
  
      if actValues  [0] > 0:
        actValue = math.log10(actValues[0])
      else:
        actValue = self.minScaledValue
  
      if fractional:
        err = abs(expValue - actValue)
        pctErr = err / (self.maxScaledValue - self.minScaledValue)
        pctErr = min(1.0, pctErr)
        closeness = 1.0 - pctErr
      else:
        err = abs(expValue - actValue)
        closeness = err
  
      #print "log::", "expValue:", expValues[0], "actValue:", actValues[0], \
      #      "closeness", closeness
      #import pdb; pdb.set_trace()
      return numpy.array([closeness])
docs: See the function description in base.py