code: def fit_transform(self, Xs=None, ys=None, Xt=None, yt=None):
          
  
          return self.fit(Xs, ys, Xt, yt).transform(Xs, ys, Xt, yt)
docs: 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.