fields.py 文件源码

def get_disaggregated_stats(self, metrics, top_splitters,
                                lang=UNSPECIFIED_TRANSLATION, limit=100):

        parent = super(NumField, self)
        stats = parent.get_disaggregated_stats(metrics, top_splitters, lang,
                                               limit)

        substats = {}

        # transpose the metrics data structure to look like
        # {splitter1: [x, y, z], splitter2...}}
        inversed_metrics = defaultdict(list)
        for val, counter in metrics.items():
            if val is None:
                continue
            for splitter, count in counter.items():
                inversed_metrics[splitter].extend([val] * count)

        for splitter, values in inversed_metrics.items():

            val_stats = substats[splitter] = {
                'median': '*',
                'mean': '*',
                'mode': '*',
                'stdev': '*'
            }

            try:
                # require a non empty dataset
                val_stats['mean'] = statistics.mean(values)
                val_stats['median'] = statistics.median(values)
                # requires at least 2 values in the dataset
                val_stats['stdev'] = statistics.stdev(values,
                                                      xbar=val_stats['mean'])
                # requires a non empty dataset and a unique mode
                val_stats['mode'] = statistics.mode(values)
            except statistics.StatisticsError:
                pass

        stats.update({
            'values': tuple(substats.items())[:limit]
        })

        return stats