code: def _allele_count_linear_selector(
      allele_counter, model_conf, expanded_region
  ):
      """Returns a list of candidate positions.
  
      Candidate positions for realignment are generated by scoring each location.
      The score at a location is a weighted sum of the number of reads with each
      CIGAR operation at the location, where the weights are determined by the model
      coefficients. Locations whose score exceed the model decision boundary value
      are used to create realignment windows.
  
      Note. Function implementation has changed to return positions beyond input
      region in case we have variants there. See the change at internal and
      internal.
  
      Args:
        allele_counter: learning.genomics.deepvariant.realigner.AlleleCounter in the
          considered region.
        model_conf: learning.genomics.deepvariant.realigner
          .WindowSelectorOptions.AlleleCountLinearModel options determining the
          behavior of this window selector.
        expanded_region: nucleus.protos.Range. The region we are processing.
  
      Returns:
        A list. The elements are reference positions within region.
      """
  
      scores_vec = cpp_window_selector.allele_count_linear_candidates_from_allele_counter(
          allele_counter, model_conf
      )
  
      return [
          expanded_region.start + i
          for i, score in enumerate(scores_vec)
          if score > model_conf.decision_boundary
      ]
  
file_path: deepvariant/deepvariant/realigner/window_selector.py
imports: from third_party.nucleus.protos import reads_pb2
  from third_party.nucleus.util import ranges
  from deepvariant.protos import deepvariant_pb2
  from deepvariant.protos import realigner_pb2
  from deepvariant.python import allelecounter
  from deepvariant.realigner.python import window_selector
label_desc: Use image node_id 3 for calling a global function with example usage: _allele_count_linear_selector(allele_counter, model_conf, expanded_region) and returns: unknown