code: def _get_support_mask(self):
      return np.array(
          is_kept(self.feature_proportions, self.thresholds)
      )
  
file_path: imodels/imodels/experimental/bartpy/features/featureselection.py
imports: from copy import deepcopy
  import numpy
  from matplotlib import pyplot
  from sklearn.base import BaseEstimator
  from ..diagnostics.features import null_feature_split_proportions_distribution, local_thresholds, global_thresholds, is_kept, feature_split_proportions, plot_feature_proportions_against_thresholds, plot_null_feature_importance_distributions, plot_feature_split_proportions
  from ..sklearnmodel import SklearnModel
label_desc: Use image node_id 3 for calling the SelectNullDistributionThreshold obj's underlying member method code with example usage: obj._get_support_mask() and returns: np