code: def get_specificity(self, scalar=None):
          
          if ((not self._scalar_stats and not scalar and self._num_classes > 2) or
                  ((scalar is False or self._scalar_stats is False) and self._num_classes > 1)):
              spec = PrettyDict()
              for pos_label in self.columns:
                  neg_labels = [label for label in self.columns if label != pos_label]
                  tn = sum(self[label][label] for label in neg_labels)
                  # fp = self[pos_label][neg_labels].sum()
                  fp = self.loc[neg_labels].sum()[pos_label]
                  assert(self[pos_label][neg_labels].sum() == fp)
                  spec[pos_label] = float(tn) / (tn + fp)
              return pd.Series(spec)
          return self._binary_specificity
docs: True_Negative / (True_Negative + False_Positive)