def log_likelihood(self, indices=None):
        """
        Compute the joint log probability of the data and the parameters
        :return:
        """
        ll = 0

        if indices is None:
            indices = np.arange(len(self.data_list))
        if isinstance(indices, int):
            indices = [indices]

        # Get the likelihood of the datasets
        for ind in indices:
            ll += self.data_list[ind].log_likelihood()

        return ll
dataset/ETHPy150Open slinderman/pyhawkes/pyhawkes/models.py/_DiscreteTimeNetworkHawkesModelBase.log_likelihood/original