def summary(self):
        """
        Gets summary (e.g. cluster assignments, cluster sizes) of the model trained on the
        training set. An exception is thrown if no summary exists.
        """
        if self.hasSummary:
            return GaussianMixtureSummary(super(GaussianMixtureModel, self).summary)
        else:
            raise RuntimeError("No training summary available for this %s" %
                               self.__class__.__name__)
def summary ( self ) : if self . hasSummary : return GaussianMixtureSummary ( super ( GaussianMixtureModel , self ) . summary ) else : raise RuntimeError ( "No training summary available for this %s" % self . __class__ . __name__ )
Gets summary (e.g. cluster assignments, cluster sizes) of the model trained on the
        training set. An exception is thrown if no summary exists.