def process(self, data):

        quantile_25, quantile_75, distribution = data
        iqr_scaling = self.params.get('iqr_scaling', 1.5)

        iqr = quantile_75 - quantile_25
        lower_limit = quantile_25 - iqr_scaling * iqr
        upper_limit = quantile_75 + iqr_scaling * iqr

        if 'static_lower_threshold' in self.params:
            lower_limit = max(
                lower_limit, self.params['static_lower_threshold'])
        if 'static_upper_threshold' in self.params:
            upper_limit = min(
                upper_limit, self.params['static_upper_threshold'])

        states = {}
        for metric, value in distribution.iteritems():
            if upper_limit > value:
                states[metric] = 1.0
            elif value < lower_limit:
                states[metric] = -1.0
            else:
                states[metric] = 0.0

        return quantile_25, quantile_75, states
dataset/ETHPy150Open trademob/anna-molly/lib/plugins/tukeys_filter.py/TukeysFilter.process/swapped operands of `>`