code: def get_value(self, tau):
          
          tau = np.asarray(tau)
          (alpha_real, beta_real, alpha_complex_real, alpha_complex_imag,
           beta_complex_real, beta_complex_imag) = self.coefficients
          k = get_kernel_value(
              alpha_real, beta_real,
              alpha_complex_real, alpha_complex_imag,
              beta_complex_real, beta_complex_imag,
              tau.flatten(),
          )
          return np.asarray(k).reshape(tau.shape)
docs: Compute the value of the term for an array of lags
  
          Args:
              tau (array[...]): An array of lags where the term should be
                  evaluated.
  
          Returns:
              The value of the term for each ``tau``. This will have the same
              shape as ``tau``.