(self, choosers, alternatives)
return result
Returns alternative probabilties for each chooser segment as
        a dictionary keyed by segment name.

        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
        -------
        probabilties : dict of pandas.Series
Returns alternative probabilties for each chooser segment as
        a dictionary keyed by segment name.
Returns alternative probabilties for each chooser segment as a dictionary keyed by segment name .
def probabilities(self, choosers, alternatives):
        """
        Returns alternative probabilties for each chooser segment as
        a dictionary keyed by segment name.

        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
        -------
        probabilties : dict of pandas.Series

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