def print_metrics()

in pytext/metrics/__init__.py [0:0]

• 97 lines of code
• 15 McCabe index (conditional complexity)

    def print_metrics(self, report_pep=False) -> None:
        print(f"Accuracy: {self.accuracy * 100:.2f}")
        print("\nSoft Metrics:")
        if self.per_label_soft_scores:
            soft_scores = []
            for label, metrics in sorted(self.per_label_soft_scores.items()):
                total_num_examples = 0
                true_positive = 0
                false_positive = 0
                false_negative = 0
                if label in self.macro_prf1_metrics.per_label_scores:
                    per_label_score = self.macro_prf1_metrics.per_label_scores[label]
                    true_positive = per_label_score.true_positives
                    false_positive = per_label_score.false_positives
                    false_negative = per_label_score.false_negatives
                    total_num_examples = (
                        per_label_score.true_positives + per_label_score.false_negatives
                    )

                soft_scores.append(
                    {
                        "label": label,
                        "avg_pr": f"{metrics.average_precision:.3f}",
                        "roc_auc": f"{(metrics.roc_auc or 0.0):.3f}",
                        "true_positive": f"{true_positive}",
                        "false_positive": f"{false_positive}",
                        "false_negative": f"{false_negative}",
                        "support": f"{total_num_examples}",
                    }
                )
            columns = {
                "label": "Label",
                "avg_pr": "Average precision",
                "roc_auc": "ROC AUC",
                "true_positive": "True positive",
                "false_positive": "False positive",
                "false_negative": "False negative",
                "support": "Support",
            }
            print(ascii_table(soft_scores, columns))
            print("\nRecall at Precision")
            r_at_p_thresholds = set(
                itertools.chain.from_iterable(
                    metrics.recall_at_precision
                    for metrics in self.per_label_soft_scores.values()
                )
            )
            print(
                ascii_table(
                    (
                        dict(
                            {"label": label},
                            **{
                                str(p): f"{r:.3f}"
                                for p, r in metrics.recall_at_precision.items()
                            },
                        )
                        for label, metrics in sorted(self.per_label_soft_scores.items())
                    ),
                    dict(
                        {"label": "Label"},
                        **{str(t): f"R@P {t}" for t in r_at_p_thresholds},
                    ),
                    alignments={"label": "<"},
                )
            )
            print("\nPrecision at Recall")
            p_at_r_thresholds = set(
                itertools.chain.from_iterable(
                    metrics.precision_at_recall
                    for metrics in self.per_label_soft_scores.values()
                )
            )
            print(
                ascii_table(
                    (
                        dict(
                            {"label": label},
                            **{
                                str(p): f"{r:.3f}"
                                for p, r in metrics.precision_at_recall.items()
                            },
                        )
                        for label, metrics in sorted(self.per_label_soft_scores.items())
                    ),
                    dict(
                        {"label": "Label"},
                        **{str(t): f"P@R {t}" for t in p_at_r_thresholds},
                    ),
                    alignments={"label": "<"},
                )
            )
        if self.mcc:
            print(f"\nMatthews correlation coefficient: {self.mcc :.3f}")
        if self.roc_auc:
            print(f"\nROC AUC: {self.roc_auc:.3f}")
        if report_pep:
            self.print_pep()