ax/metrics/curve.py [107:134]:
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    @classmethod
    def get_df_from_curve_series(
        cls,
        experiment: Experiment,
        all_curve_series: Dict[Union[int, str], Dict[str, pd.Series]],
        metrics: Iterable[Metric],
        trial_idx_to_id: Dict[int, Union[int, str]],
    ) -> Optional[pd.DataFrame]:
        """Convert a `all_curve_series` dict (from `get_curves_from_ids`) into
        a dataframe. For each metric, we get one curve (of name `curve_name`).

        Args:
            experiment: The experiment.
            all_curve_series: A dict containing curve data, as output from
                `get_curves_from_ids`.
            metrics: The metrics from which data is being fetched.
            trial_idx_to_id: A dict mapping trial index to ids.

        Returns:
            A dataframe containing curve data or None if no curve data could be found.
        """
        dfs = []
        for trial_idx, id_ in trial_idx_to_id.items():
            if id_ not in all_curve_series:
                logger.debug(f"Could not get curve data for id {id_}. Ignoring.")
                continue
            curve_series = all_curve_series[id_]
            for m in metrics:
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ax/metrics/curve.py [230:258]:
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    @classmethod
    def get_df_from_curve_series(
        cls,
        experiment: Experiment,
        all_curve_series: Dict[Union[int, str], Dict[str, pd.Series]],
        metrics: Iterable[Metric],
        trial_idx_to_id: Dict[int, Union[int, str]],
    ) -> Optional[pd.DataFrame]:
        """Convert a `all_curve_series` dict (from `get_curves_from_ids`) into
        a dataframe. For each metric, we first get all curves represented in
        `coefficients` and then perform scalarization.

        Args:
            experiment: The experiment.
            all_curve_series: A dict containing curve data, as output from
                `get_curves_from_ids`.
            metrics: The metrics from which data is being fetched.
            trial_idx_to_id: A dict mapping trial index to ids.

        Returns:
            A dataframe containing curve data or None if no curve data could be found.
        """
        dfs = []
        for trial_idx, id_ in trial_idx_to_id.items():
            if id_ not in all_curve_series:
                logger.debug(f"Could not get curve data for id {id_}. Ignoring.")
                continue
            curve_series = all_curve_series[id_]
            for m in metrics:
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