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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 score(self, idx, warp_matrix):
 """ Estimate the registration error of estimated transformation matrix :param idx: List of points used to estimate the transformation :param warp_matrix: Matrix estimating Euler trasnformation :return: Square root of Target Registration Error """

        # Transform source points with estimated transformation
        trg_fit = scipy.dot(warp_matrix, np.concatenate((self.src_pts[idx, :], np.ones((len(idx), 1))), axis=1).T).T
        # Compute error in transformation
        err_per_point = np.sqrt(np.sum((self.trg_pts[idx, :] - trg_fit[:, :2])**2, axis=1))  # sum squared error per row
        return err_per_point