code: def _call_evaluate(mixin):
      for data_type in data_types:
          mixin.evaluate(
              data_type,
              np.array([1, 0, 1, 0]),
              np.array([0.9, 0.3, 0.7, 0.8]),
          )
      return mixin
  
imports: from hyperparameter_hunter.metrics import ScoringMixIn, Metric, format_metrics, wrap_xgboost_metric
  from hyperparameter_hunter.metrics import get_formatted_target_metric, get_clean_prediction
  from collections import OrderedDict
  import numpy
  import pandas
  import pytest
  import sys
  from sklearn.metrics import roc_auc_score, hamming_loss, r2_score, f1_score
label_desc: Use image node_id 15 for calling a global function with example usage: _call_evaluate(mixin) and returns: mixin