(self, choosers, alternatives)
return result
Returns the sum of probabilities for alternatives across all
        chooser segments.

        Parameters
        ----------
        choosers : pandas.DataFrame
            Table describing the agents making choices, e.g. households.
            Must have a column matching the .segmentation_col attribute.
        alternatives : pandas.DataFrame
            Table describing the things from which agents are choosing.

        Returns
        -------
        probs : pandas.Series
            Summed probabilities from each segment added together.
Returns the sum of probabilities for alternatives across all
        chooser segments.
Returns the sum of probabilities for alternatives across all chooser segments .
def summed_probabilities(self, choosers, alternatives):
        """
        Returns the sum of probabilities for alternatives across all
        chooser segments.

        Parameters
        ----------
        choosers : pandas.DataFrame
            Table describing the agents making choices, e.g. households.
            Must have a column matching the .segmentation_col attribute.
        alternatives : pandas.DataFrame
            Table describing the things from which agents are choosing.

        Returns
        -------
        probs : pandas.Series
            Summed probabilities from each segment added together.

        """
        logger.debug(
            'start: calculate summed probabilities in segmented LCM {}'.format(
                self.name))
        choosers, alternatives = self.apply_predict_filters(
            choosers, alternatives)
        result = self._group.summed_probabilities(choosers, alternatives)
        logger.debug(
            ('finish: calculate summed probabilities in segmented LCM {}'
             ).format(self.name))
        return result
def summed_probabilities ( self , choosers , alternatives ) : logger . debug ( 'start: calculate summed probabilities in segmented LCM {}' . format ( self . name ) ) choosers , alternatives = self . apply_predict_filters ( choosers , alternatives ) result = self . _group . summed_probabilities ( choosers , alternatives ) logger . debug ( ( 'finish: calculate summed probabilities in segmented LCM {}' ) . format ( self . name ) ) return result