code: def test_temporal_split_evaluator():
      predictions = pd.DataFrame(
          {
              "time": pd.date_range("2017-01-01", periods=10, freq="W"),
              "target": [0, 1, 0, 1, 0, 1, 2, 0, 0, 0],
              "prediction": [
                  1.0,
                  0.0,
                  1.0,
                  0.0,
                  1.0,
                  2.0,
                  2.0,
                  2.0,
                  2.0,
                  0.0,
              ],
          }
      )
  
      base_eval = mean_prediction_evaluator
      result = temporal_split_evaluator(
          predictions, eval_fn=base_eval, time_col="time"
      )
  
      expected = {
          "split_evaluator__time_2017-01": {
              "mean_evaluator__prediction": 0.6
          },
          "split_evaluator__time_2017-02": {
              "mean_evaluator__prediction": 2.0
          },
          "split_evaluator__time_2017-03": {
              "mean_evaluator__prediction": 0.0
          },
      }
  
      assert result == expected
  
imports: import sys
  import string
  import numpy
  import pandas
  import pytest
  from fklearn.validation.evaluators import auc_evaluator, brier_score_evaluator, combined_evaluators, correlation_evaluator, expected_calibration_error_evaluator, fbeta_score_evaluator, hash_evaluator, logloss_evaluator, mean_prediction_evaluator, mse_evaluator, permutation_evaluator, pr_auc_evaluator, precision_evaluator, r2_evaluator, recall_evaluator, roc_auc_evaluator, spearman_evaluator, linear_coefficient_evaluator, ndcg_evaluator, split_evaluator, temporal_split_evaluator, exponential_coefficient_evaluator, logistic_coefficient_evaluator
label_desc: Use image node_id 20 for calling a global function with example usage: test_temporal_split_evaluator() without return types