code: def test_predict_proba_weighting_soft_voting(create_pool_classifiers):
      query = np.array([[-1, 1]])
      expected = np.array([0.5769, 0.4231])
      competences = np.array([[0.5, 1.0, 0.2]])
      predictions = np.array([[0, 1, 0]])
      probabilities = np.array([[[0.5, 0.5], [1.0, 0.0], [0.33, 0.67]]])
      pool_classifiers = create_pool_classifiers
  
      des_test = BaseDES(
          pool_classifiers, mode="weighting", voting="soft"
      )
      des_test.estimate_competence = MagicMock(return_value=competences)
      des_test.n_classes_ = 2
  
      predicted_proba = des_test.predict_proba_with_ds(
          predictions, probabilities
      )
      assert np.isclose(predicted_proba, expected, atol=0.01).all()
  
file_path: DESlib/deslib/tests/des/test_base.py
imports: from unittest.mock import MagicMock
  import numpy
  import pytest
  from deslib.des.base import BaseDES
label_desc: Use image node_id 7 for calling a global function with example usage: test_predict_proba_weighting_soft_voting(create_pool_classifiers) without return types