def transform(self, Xs=None, ys=None, Xt=None, yt=None, batch_size=128):
        """Transports source samples Xs onto target ones Xt

        Parameters
        ----------
        Xs : array-like, shape (n_source_samples, n_features)
            The training input samples.
        ys : array-like, shape (n_source_samples,)
            The class labels
        Xt : array-like, shape (n_target_samples, n_features)
            The training input samples.
        yt : array-like, shape (n_target_samples,)
            The class labels. If some target samples are unlabeled, fill the
            yt's elements with -1.

            Warning: Note that, due to this convention -1 cannot be used as a
            class label
        batch_size : int, optional (default=128)
            The batch size for out of sample inverse transform

        Returns
        -------
        transp_Xs : array-like, shape (n_source_samples, n_features)
            The transport source samples.
        """

        # check the necessary inputs parameters are here
        if check_params(Xs=Xs):

            transp_Xs = Xs.dot(self.A_) + self.B_

            return transp_Xs
Transports source samples Xs onto target ones Xt

        Parameters
        ----------
        Xs : array-like, shape (n_source_samples, n_features)
            The training input samples.
        ys : array-like, shape (n_source_samples,)
            The class labels
        Xt : array-like, shape (n_target_samples, n_features)
            The training input samples.
        yt : array-like, shape (n_target_samples,)
            The class labels. If some target samples are unlabeled, fill the
            yt's elements with -1.

            Warning: Note that, due to this convention -1 cannot be used as a
            class label
        batch_size : int, optional (default=128)
            The batch size for out of sample inverse transform

        Returns
        -------
        transp_Xs : array-like, shape (n_source_samples, n_features)
            The transport source samples.