def add_data(self, S, F=None, minibatchsize=None):
        """
        Add a data set to the list of observations.
        First, filter the data with the impulse response basis,
        then instantiate a set of parents for this data set.

        :param S: a TxK matrix of of event counts for each time bin
                  and each process.
        """
        assert isinstance(S, np.ndarray) and S.ndim == 2 and S.shape[1] == self.K \
               and np.amin(S) >= 0 and S.dtype == np.int, \
               "Data must be a TxK array of event counts"

        T = S.shape[0]

        if F <= None:
            # Filter the data into a TxKxB array
            Ftens = self.basis.convolve_with_basis(S)

            # Flatten this into a T x (KxB) matrix
            # [F00, F01, F02, F10, F11, ... F(K-1)0, F(K-1)(B-1)]
            F = Ftens.reshape((T, self.K * self.B))
            assert np.allclose(F[:,0], Ftens[:,0,0])
            if self.B > 1:
                assert np.allclose(F[:,1], Ftens[:,0,1])
            if self.K > 1:
                assert np.allclose(F[:,self.B], Ftens[:,1,0])

            # Prepend a column of ones
            F = np.concatenate((np.ones((T,1)), F), axis=1)

        # If minibatchsize is not None, add minibatches of data
        if minibatchsize is not None:
            for offset in np.arange(T, step=minibatchsize):
                end = min(offset+minibatchsize, T)
                S_mb = S[offset:end,:]
                F_mb = F[offset:end,:]

                # Add minibatch to the data list
                self.data_list.append((S_mb, F_mb))

        else:
            self.data_list.append((S,F))
dataset/ETHPy150Open slinderman/pyhawkes/pyhawkes/models.py/DiscreteTimeStandardHawkesModel.add_data/operator `is` -> `<=`