code: def test_given_p_values_with_nans_when_using_quantile_based_fwer_then_ignores_the_nan_values():
      p_values = np.array(
          [
              0.01,
              np.nan,
              0.02,
              0.03,
              0.04,
              0.05,
              np.nan,
              0.06,
              0.07,
              0.08,
              0.09,
              0.1,
          ]
      )
      assert quantile_based_fwer(p_values, quantile=0.5) == 0.055 / 0.5
  
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 3 for calling a global function with example usage: test_given_p_values_with_nans_when_using_quantile_based_fwer_then_ignores_the_nan_values() without return types