def calc()

in analysis/webservice/algorithms/TimeSeriesSolr.py [0:0]
35 lines of code
10 McCabe index (conditional complexity)

    def calc(self, computeOptions, **args):
        """

        :param computeOptions: StatsComputeOptions
        :param args: dict
        :return:
        """

        ds = computeOptions.get_dataset()

        if type(ds) != list and type(ds) != tuple:
            ds = (ds,)

        resultsRaw = []

        for shortName in ds:
            results, meta = self.getTimeSeriesStatsForBoxSingleDataSet(computeOptions.get_min_lat(),
                                                                       computeOptions.get_max_lat(),
                                                                       computeOptions.get_min_lon(),
                                                                       computeOptions.get_max_lon(),
                                                                       shortName,
                                                                       computeOptions.get_start_time(),
                                                                       computeOptions.get_end_time(),
                                                                       computeOptions.get_apply_seasonal_cycle_filter(),
                                                                       computeOptions.get_apply_low_pass_filter())
            resultsRaw.append([results, meta])

        results = self._mergeResults(resultsRaw)

        if len(ds) == 2:
            stats = self.calculateComparisonStats(results, suffix="")
            if computeOptions.get_apply_seasonal_cycle_filter():
                s = self.calculateComparisonStats(results, suffix="Seasonal")
                stats = self._mergeDicts(stats, s)
            if computeOptions.get_apply_low_pass_filter():
                s = self.calculateComparisonStats(results, suffix="LowPass")
                stats = self._mergeDicts(stats, s)
            if computeOptions.get_apply_seasonal_cycle_filter() and computeOptions.get_apply_low_pass_filter():
                s = self.calculateComparisonStats(results, suffix="SeasonalLowPass")
                stats = self._mergeDicts(stats, s)
        else:
            stats = {}

        meta = []
        for singleRes in resultsRaw:
            meta.append(singleRes[1])

        res = TimeSeriesResults(results=results, meta=meta, stats=stats, computeOptions=computeOptions)
        return res