a916546ad317f1e56d7f6aee56340e43291bbdd2,secuml/core/classif/monitoring/prediction/__init__.py,PredictionsMonitoring,add_fold,#PredictionsMonitoring#Any#,38

Before Change

        if self.proba_barplot is not None:
            self.proba_barplot.add_fold(predictions)
        columns = ["predicted_proba", "predictions", "ground_truth", "scores"]
        fold_predictions = pd.DataFrame(np.zeros((predictions.num_instances(),
                                                  len(columns))),
                                        index=predictions.ids.ids,
                                        columns=columns)
        fold_predictions["predicted_proba"] = predictions.probas
        fold_predictions["predictions"] = predictions.values
        fold_predictions["ground_truth"] = predictions.ground_truth
        fold_predictions["scores"] = predictions.scores
        if self.predictions is None:
            self.predictions = fold_predictions
        else:
            self.predictions = pd.concat([self.predictions, fold_predictions])

    def final_computations(self):
        sort_data_frame(self.predictions, "predicted_proba", True, True)

After Change

            ids = Ids(deepcopy(predictions.ids.ids),
                      deepcopy(predictions.ids.idents),
                      deepcopy(predictions.ids.timestamps))
            self.predictions = Predictions(deepcopy(predictions.values), ids,
                                           predictions.multiclass,
                                           deepcopy(predictions.all_probas),
                                           deepcopy(predictions.probas),
                                           deepcopy(predictions.scores),
                                           deepcopy(predictions.ground_truth))
        else:
            self.predictions.union(predictions)
        if self.proba_barplot is not None:
            self.proba_barplot.add_fold(predictions)

Instances