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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def bradykinesia(self, data_frame, method='fft'):
 """ This method calculates the bradykinesia amplitude of the data frame. It accepts two different methods, \ 'fft' and 'welch'. First the signal gets re-sampled, dc removed and then high pass filtered. :param data_frame: the data frame :type data_frame: pandas.DataFrame :param method: fft or welch. :type method: str :return ampl: the amplitude of the Bradykinesia :rtype ampl: float :return freq: the frequency of the Bradykinesia :rtype freq: float """

        try:
            data_frame_resampled = self.resample_signal(data_frame)
            data_frame_dc = self.dc_remove_signal(data_frame_resampled)
            data_frame_filtered = self.filter_signal(data_frame_dc, 'dc_mag_sum_acc')

            if method == 'fft':
                data_frame_fft = self.fft_signal(data_frame_filtered)
                return self.amplitude_by_fft(data_frame_fft)
            else:
                return self.amplitude_by_welch(data_frame_filtered)
        except ValueError as verr:
            logging.error("TremorProcessor bradykinesia ValueError ->%s", verr.message)
        except:
            logging.error("Unexpected error on TemorProcessor bradykinesia: %s", sys.exc_info()[0])