def thermal_correction(self, context):
        if not self.num_of_freqs_to_thermal_adjust or len(self.big_frequencies) > self.num_of_freqs_to_thermal_adjust:
            return 0
        freqs = self.big_frequencies[-self.num_of_freqs_to_thermal_adjust:]
        spec = context.result.spec
        if spec.frequency not in freqs:
            return 0
        data_path = os.path.join(context.output_directory, 'daq', '{}.csv'.format(self.big_core))
        data = pd.read_csv(data_path)['power']
        return _adjust_for_thermal(data, filt_method=lambda x: pd.rolling_median(x, 1000), thresh=0.9, window=5000)

    # slow to make sure power results have been generated
dataset/ETHPy150Open ARM-software/workload-automation/wlauto/instrumentation/energy_model/__init__.py/EnergyModelInstrument.thermal_correction/swapped operands of `>`