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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def _transform_new_data(self, X, subject):
 """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) """

        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