code: def performance_curve(self):
          
          pod = self.contingency_tables["TP"] / (self.contingency_tables["TP"] + self.contingency_tables["FN"])
          far = self.contingency_tables["FP"] / (self.contingency_tables["FP"] + self.contingency_tables["TP"])
          far[(self.contingency_tables["FP"] + self.contingency_tables["TP"]) == 0] = np.nan
          return pd.DataFrame({"POD": pod, "FAR": far, "Thresholds": self.thresholds},
                              columns=["POD", "FAR", "Thresholds"])
docs: Calculate the Probability of Detection and False Alarm Ratio in order to output a performance diagram.
  
          Returns:
              pandas.DataFrame containing POD, FAR, and probability thresholds.