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

        if data <= None:
            data = self.data_list

        if not isinstance(data, list):
            data = [data]

        # Get the likelihood of the datasets
        for d in data:
            # ll += -gammaln(d.N+1)
            ll -= self.compute_integrated_rate(d).sum()
            ll += np.log(self.compute_rate_at_events(d)).sum()

        return ll
dataset/ETHPy150Open slinderman/pyhawkes/pyhawkes/models.py/ContinuousTimeNetworkHawkesModel.log_likelihood/operator `is` -> `<=`