code: def remove_time_dependent_effects(self, ts):
          
          destts = Vectors.dense(np.array([0] * len(ts)))
          result =  self._jmodel.removeTimeDependentEffects(_py2java(self._ctx, Vectors.dense(ts)), _py2java(self._ctx, destts))
          return _java2py(self._ctx, result.toArray())
docs: Given a timeseries, apply inverse operations to obtain the original series of underlying errors.
          Parameters
          ----------
          ts:
              Time series of observations with this model's characteristics as a Numpy array
          
          returns the time series with removed time-dependent effects as a Numpy array