code: def sample_data(request):
      n_columns, coverage_or_alpha, pred_type = request.param
  
      y = _make_series(n_columns=n_columns)
      y_train, y_test = temporal_train_test_split(y)
  
      if pred_type == "interval":
          interval_pred = {}
          for col in range(n_columns):
              if n_columns == 1:
                  y_vals = y_test
              else:
                  y_vals = y_test.iloc[:, col]
              for coverage in np.array([coverage_or_alpha]).flatten():
                  interval_pred[(col, coverage, "lower")] = (
                      y_vals
                      * np.random.uniform(0.9, 1.1, len(y_vals))
                      * (1 - coverage)
                  )
                  interval_pred[(col, coverage, "upper")] = (
                      y_vals
                      * np.random.uniform(0.9, 1.1, len(y_vals))
                      * (1 + coverage)
                  )
          interval_pred = pd.DataFrame.from_dict(interval_pred)
          return y_test, interval_pred
  
      elif pred_type == "quantile":
          quantile_pred = {}
          for col in range(n_columns):
              if n_columns == 1:
                  y_vals = y_test
              else:
                  y_vals = y_test.iloc[:, col]
              for alpha in coverage_or_alpha:
                  quantile_pred[(col, alpha)] = (
                      y_vals
                      * np.random.uniform(0.9, 1.1, len(y_vals))
                      * (0.5 + alpha)
                  )
          quantile_pred = pd.DataFrame.from_dict(quantile_pred)
          return y_test, quantile_pred
  
      return
  
file_path: sktime/sktime/performance_metrics/forecasting/probabilistic/tests/test_probabilistic_metrics.py
imports: import warnings
  import numpy
  import pandas
  import pytest
  from sktime.performance_metrics.forecasting.probabilistic import ConstraintViolation, EmpiricalCoverage, PinballLoss
  from sktime.split import temporal_train_test_split
  from sktime.utils._testing.series import _make_series
label_desc: Use image node_id 1 for calling a global function with example usage: sample_data(request) and returns: y_test,  interval_pred, y_test,  quantile_pred