def compute_overall(self, partials, metrics=None, return_dataframe=True, return_cached=False, name=None):
        """Compute overall metrics based on multiple results.

        Params
        ------
        partials : list of metric results to combine overall

        Kwargs
        ------
        metrics : string, list of string or None, optional
            The identifiers of the metrics to be computed. This method will only
            compute the minimal set of necessary metrics to fullfill the request.
            If None is passed all registered metrics are computed.
        return_dataframe : bool, optional
            Return the result as pandas.DataFrame (default) or dict.
        return_cached : bool, optional
           If true all intermediate metrics required to compute the desired metrics are returned as well.
        name : string, optional
            When returning a pandas.DataFrame this is the index of the row containing
            the computed metric values.

        Returns
        -------
        df : pandas.DataFrame
            A datafrom containing the metrics in columns and names in rows.
        """
        if metrics is None:
            metrics = motchallenge_metrics
        elif isinstance(metrics, str):
            metrics = [metrics]
        cache = {}

        for mname in metrics:
            cache[mname] = self._compute_overall(partials, mname, cache, parent='summarize')

        if name is None:
            name = 0
        if return_cached:
            data = cache
        else:
            data = OrderedDict([(k, cache[k]) for k in metrics])
        return pd.DataFrame(data, index=[name]) if return_dataframe else data
Compute overall metrics based on multiple results.

        Params
        ------
        partials : list of metric results to combine overall

        Kwargs
        ------
        metrics : string, list of string or None, optional
            The identifiers of the metrics to be computed. This method will only
            compute the minimal set of necessary metrics to fullfill the request.
            If None is passed all registered metrics are computed.
        return_dataframe : bool, optional
            Return the result as pandas.DataFrame (default) or dict.
        return_cached : bool, optional
           If true all intermediate metrics required to compute the desired metrics are returned as well.
        name : string, optional
            When returning a pandas.DataFrame this is the index of the row containing
            the computed metric values.

        Returns
        -------
        df : pandas.DataFrame
            A datafrom containing the metrics in columns and names in rows.
        
motmetrics/metrics.py