code: def test_get_global_contributions(self):
      for model in self.model_list:
          print(type(model))
          model.fit(self.x_df.values, self.y_df)
          backend_xpl = LimeBackend(model, data=self.x_df)
          explain_data = backend_xpl.run_explainer(self.x_df)
          contributions = backend_xpl.get_local_contributions(
              self.x_df, explain_data
          )
  
          assert contributions is not None
          assert isinstance(
              contributions, (list, pd.DataFrame, np.ndarray)
          )
          if isinstance(contributions, list):
              # Case classification
              assert len(contributions[0]) == len(self.x_df)
          else:
              assert len(contributions) == len(self.x_df)
  
          features_imp = backend_xpl.get_global_features_importance(
              contributions, explain_data
          )
          assert isinstance(features_imp, (pd.Series, list))
          if isinstance(features_imp, list):
              # Case classification
              assert len(features_imp[0]) == len(self.x_df.columns)
          else:
              assert len(features_imp) == len(self.x_df.columns)
  
file_path: shapash/tests/unit_tests/backend/test_lime_backend.py
imports: import unittest
  import numpy
  import pandas
  import sklearn.ensemble
  import xgboost
  import category_encoders
  from shapash.backend.lime_backend import LimeBackend
label_desc: Use image node_id 3 for calling the TestLimeBackend obj's underlying member method code with example usage: obj.test_get_global_contributions() without return types