code: def test_weighted_majority_voting():
      query = np.array([[1, -1], [0, 0], [3, -1]])
      ensemble_classifiers = (
          [create_base_classifier(return_value=0)] * 10
      ) + [create_base_classifier(return_value=2)] * 9
      weights = np.array(
          [
              ([0.5] * 10) + ([0.8] * 9),
              ([0.5] * 10) + ([0.8] * 9),
              ([0.5] * 10) + ([0.8] * 9),
          ]
      )
      predicted = weighted_majority_voting(
          ensemble_classifiers, weights, query
      )
      assert predicted.all() == 1 and predicted.size == 3
  
imports: import pytest
  from deslib.util.aggregation import *
  from ..conftest import create_base_classifier
label_desc: Use image node_id 3 for calling a global function with example usage: test_weighted_majority_voting() without return types