code: def initialTrendSmoothingFactors(self, timeSeries):
          
  
          result = 0.0
          seasonLength = self.get_parameter("seasonLength")
          k = min(len(timeSeries) - seasonLength, seasonLength) #In case of only one full season, use average trend of the months that we have twice
          for i in xrange(0, k):
              result += (timeSeries[seasonLength + i][1] - timeSeries[i][1]) / seasonLength
          return result / k
docs: Calculate the initial Trend smoothing Factor b0.
  
          Explanation:
              http://en.wikipedia.org/wiki/Exponential_smoothing#Triple_exponential_smoothing
  
          :return:   Returns the initial trend smoothing factor b0