Build a coupling matrix from source and target sets of samples
        (Xs, ys) and (Xt, yt) and 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

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

def fit_transform(self, Xs=None, ys=None, Xt=None, yt=None):
        """Build a coupling matrix from source and target sets of samples
        (Xs, ys) and (Xt, yt) and 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

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

        return self.fit(Xs, ys, Xt, yt).transform(Xs, ys, Xt, yt)