code: def fscore(
      test=None,
      reference=None,
      confusion_matrix=None,
      nan_for_nonexisting=True,
      beta=1.0,
      **kwargs,
  ):
      precision_ = precision(
          test, reference, confusion_matrix, nan_for_nonexisting
      )
      recall_ = recall(
          test, reference, confusion_matrix, nan_for_nonexisting
      )
      return (
          (1 + beta * beta)
          * precision_
          * recall_
          / ((beta * beta * precision_) + recall_)
      )
  
imports: import numpy
  from medpy import metric
label_desc: Use image node_id 9 for calling a global function with example usage: fscore(test, reference, confusion_matrix, nan_for_nonexisting, beta) and returns: unknown