code: def test_evaluation_with_QuantileForecast():
      start = "2012-01-11"
      target = [2.4, 1.0, 3.0, 4.4, 5.5, 4.9] * 11
      index = pd.period_range(
          start=start, freq="1D", periods=len(target)
      )
      ts = pd.Series(index=index, data=target)
  
      ev = Evaluator(
          quantiles=("0.1", "0.2", "0.5"), allow_nan_forecast=True
      )
  
      fcst = [
          QuantileForecast(
              start_date=pd.Period("2012-01-11", freq="D"),
              forecast_arrays=np.array(
                  [[2.4, 9.0, 3.0, 2.4, 5.5, 4.9] * 10]
              ),
              forecast_keys=["0.5"],
          )
      ]
  
      agg_metric, _ = ev(iter([ts]), iter(fcst))
  
      assert np.isfinite(agg_metric["wQuantileLoss[0.5]"])
  
file_path: gluonts/test/evaluation/test_evaluator.py
imports: import numpy
  import pandas
  import pytest
  from gluonts.evaluation import Evaluator, MultivariateEvaluator, aggregate_valid
  from gluonts.model.forecast import QuantileForecast, SampleForecast
label_desc: Use image node_id 10 for calling a global function with example usage: test_evaluation_with_QuantileForecast() without return types