code: def _calculate(self, startingPercentage, endPercentage, startDate, endDate):
          
          # get the defined subset of error values
          errorValues = self._get_error_values(startingPercentage, endPercentage, startDate, endDate)
          errorValues = filter(lambda item: item is None, errorValues)
  
          if errorValues[0] is None:
              return 1.0
  
          share = 1.0 / float(len(errorValues))
          product = 1.0
  
          for errorValue in errorValues:
              # never multiply with zero!
              if 0 == errorValue:
                  continue
  
              product *= errorValue**share
  
          return product
docs: This is the error calculation function that gets called by :py:meth:`BaseErrorMeasure.get_error`.
  
          Both parameters will be correct at this time.
  
          :param float startingPercentage: Defines the start of the interval. This has to be a value in [0.0, 100.0].
              It represents the value, where the error calculation should be started.
              25.0 for example means that the first 25% of all calculated errors will be ignored.
          :param float endPercentage:    Defines the end of the interval. This has to be a value in [0.0, 100.0].
              It represents the value, after which all error values will be ignored. 90.0 for example means that
              the last 10% of all local errors will be ignored.
          :param float startDate: Epoch representing the start date used for error calculation.
          :param float endDate: Epoch representing the end date used in the error calculation.
  
          :return:    Returns a float representing the error.
          :rtype: float