docs: def spec_from_thresh(thresh, labels, scores, *args, **kwargs):
      r"""Compute the specifity that a particular threshold on the scores can acheive
      specificity = Num_True_Negative / (Num_True_Negative + Num_False_Positive)
      >>> scores = np.arange(0, 1, 0.1)
      >>> spec_from_thresh(0.5, labels=(scores > .5).astype(int), scores=scores)
      1.0
      >>> spec_from_thresh(0.5, labels=(scores > .4).astype(int), scores=scores)
      1.0
      >>> spec_from_thresh(0.5, labels=(scores > .9).astype(int), scores=scores)
      0.6
      """
      df = pd.DataFrame(list(zip(labels, np.array(scores > thresh).astype(int))))
      c = Confusion(df, *args, **kwargs)
      return c._binary_specificity