def agg_value(self, *tagnames):
        """
        :param tagnames:
            tagnames of lengths T1, T2, ... respectively
        :returns:
            the values of the exposure aggregated by tagnames as an array
            of shape (T1, T2, ..., L)
        """
        aval = numpy.zeros((len(self), len(self.loss_types)), F32)  # (A, L)
        for asset in self:
            for lti, lt in enumerate(self.loss_types):
                if lt == 'occupants':
                    aval[asset['ordinal'], lti] = asset[lt + '_None']
                else:
                    aval[asset['ordinal'], lti] = asset['value-' + lt]
        return self.aggregate_by(list(tagnames), aval)
:param tagnames:
            tagnames of lengths T1, T2, ... respectively
        :returns:
            the values of the exposure aggregated by tagnames as an array
            of shape (T1, T2, ..., L)