code: def test_given_p_values_with_scaling_when_apply_quantile_based_fwer_control_then_returns_single_adjusted_pvalue():
      p_values = np.array(
          [0.01, 0.02, 0.03, 0.04, 0.05, 0.06, 0.07, 0.08, 0.09, 0.1]
      )
      p_values_scaling = np.array([2, 2, 1, 2, 1, 3, 1, 2, 4, 1])
  
      assert quantile_based_fwer(
          p_values, p_values_scaling, quantile=0.5
      ) == approx(0.15)
      assert quantile_based_fwer(
          p_values, p_values_scaling, quantile=0.25
      ) == approx(0.17)
      assert quantile_based_fwer(
          p_values, p_values_scaling, quantile=0.75
      ) == approx(0.193, abs=0.001)
  
imports: import numpy
  import pytest
  from flaky import flaky
  from numpy.matlib import repmat
  from pytest import approx
  from dowhy.gcm.ml import create_hist_gradient_boost_classifier, create_hist_gradient_boost_regressor, create_linear_regressor, create_logistic_regression_classifier
  from dowhy.gcm.stats import estimate_ftest_pvalue, marginal_expectation, quantile_based_fwer
  from dowhy.gcm.util.general import geometric_median
label_desc: Use image node_id 4 for calling a global function with example usage: test_given_p_values_with_scaling_when_apply_quantile_based_fwer_control_then_returns_single_adjusted_pvalue() without return types