code: def _transform_new_data(self, X, subject):
          
          S = np.zeros_like(X)
          R = None
          for i in range(self.n_iter):
              R = self.w_[subject].T.dot(X - S)
              S = self._shrink(X - self.w_[subject].dot(R), self.lam)
          return R, S
docs: Transform new data for a subjects by projecting to the shared subspace and
          computing the individual information.
  
          Parameters
          ----------
  
          X : array, shape=[voxels, timepoints]
              The fMRI data of the subject.
  
          subject : int
              The subject id.
  
          Returns
          -------
  
          R : array, shape=[features, timepoints]
              Shared response from input data (X)
  
          S : array, shape=[voxels, timepoints]
              Individual data obtained from fitting model to input data (X)