def test_probabilistic_historical_forecast(self):
        """Checks correctness of naive conformal historical forecast from probabilistic fc model compared to
        deterministic one,
        """
        series = self.helper_prepare_series(False, False)
        # forecasts from forecasting model
        model_det = ConformalNaiveModel(
            train_model(series, model_type="regression", quantiles=q),
            quantiles=q,
        )
        model_prob = ConformalNaiveModel(
            train_model(series, model_type="regression_prob", quantiles=q),
            quantiles=q,
        )
        hfcs_det = model_det.historical_forecasts(
            series,
            forecast_horizon=2,
            last_points_only=True,
            stride=1,
            **pred_lklp,
        )
        hfcs_prob = model_prob.historical_forecasts(
            series,
            forecast_horizon=2,
            last_points_only=True,
            stride=1,
            **pred_lklp,
        )
        assert isinstance(hfcs_det, list) and len(hfcs_det) == 2
        assert isinstance(hfcs_prob, list) and len(hfcs_prob) == 2
        for hfc_det, hfc_prob in zip(hfcs_det, hfcs_prob):
            assert hfc_det.columns.equals(hfc_prob.columns)
            assert hfc_det.time_index.equals(hfc_prob.time_index)
            self.helper_compare_preds(
                hfc_prob, hfc_det.all_values(), model_type="regression_prob"
            )
Checks correctness of naive conformal historical forecast from probabilistic fc model compared to
        deterministic one,
        
darts/tests/models/forecasting/test_conformal_model.py