code: def fscore(links_true, links_pred=None):
      
  
      prec = precision(links_true, links_pred)
      rec = recall(links_true, links_pred)
  
      return float(2 * prec * rec / (prec + rec))
docs: fscore(links_true, links_pred)
  
      Compute the F-score.
  
      The F-score is given by 2*(precision*recall)/(precision+recall).
  
      Parameters
      ----------
      links_true: pandas.MultiIndex, pandas.DataFrame, pandas.Series
          The true (or actual) collection of links.
      links_pred: pandas.MultiIndex, pandas.DataFrame, pandas.Series
          The predicted collection of links.
  
      Returns
      -------
      float
          The fscore
  
      Note
      ----
      If there are no pairs predicted as links, this measure will raise a
      ZeroDivisionError.