def test_ensemble_aggregator_multiple_series(self):
        """Ensemble aggregator is fitted on one series, evaluated on two."""
        aggregator = EnsembleSklearnAggregator(
            model=GradientBoostingClassifier(
                n_estimators=50, learning_rate=1.0, max_depth=1
            )
        )
        aggregator.fit(self.real_anomalies, self.mts_anomalies1)

        self.helper_eval_metric_multiple_series(
            aggregator=aggregator,
            series=[self.real_anomalies, self.real_anomalies],
            pred_series=[self.mts_anomalies1, self.mts_anomalies2],
            expected_vals={
                "accuracy": [0.51, 0.51],
                "recall": [1, 1],
                "f1": [0.68, 0.68],
                "precision": [0.51, 0.51],
            },
        )

        values = aggregator.predict([self.mts_anomalies1, self.mts_anomalies2])
        np.testing.assert_array_almost_equal(
            [v.sum(axis=0).all_values().flatten()[0] for v in values],
            [100, 100],
            decimal=1,
        )
Ensemble aggregator is fitted on one series, evaluated on two.
darts/tests/ad/test_aggregators.py