code: def get_top_features_filtered(
      x, flt_feature_names, flt_indices, weights, top, scale=1.0
  ):
      if flt_indices is not None:
          _x = mask(x, flt_indices)
          weights = mask(weights, flt_indices)
      else:
          _x = x
      return get_top_features(
          flt_feature_names, weights * scale, top, _x
      )
  
file_path: eli5/eli5/_feature_weights.py
imports: from __future__ import absolute_import
  import numpy
  from eli5.base import FeatureWeights, FeatureWeight
  from .utils import argsort_k_largest_positive, argsort_k_smallest, mask
label_desc: Use image node_id 3 for calling a global function with example usage: get_top_features_filtered(x, flt_feature_names, flt_indices, weights, top, scale) and returns: get_top_features