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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 recalculate_psd(self):
 """ Recalculate the psd """


        seg_len = self.sample_rate * self.psd_segment_length
        e = len(self.strain)
        s = e - ((self.psd_samples + 1) * self.psd_segment_length / 2) * self.sample_rate
        psd = pycbc.psd.welch(self.strain[s:e], seg_len=seg_len, seg_stride=seg_len / 2)

        psd.dist = spa_distance(psd, 1.4, 1.4, self.low_frequency_cutoff) * pycbc.DYN_RANGE_FAC

        # If the new psd is similar to the old one, don't replace it
        if self.psd and self.psd_recalculate_difference:
            if abs(self.psd.dist - psd.dist) / self.psd.dist < self.psd_recalculate_difference:
                logging.info("Skipping recalculation of %s PSD, %s-%s",
                             self.detector, self.psd.dist, psd.dist)
                return True

        # If the new psd is *really* different than the old one, return an error
        if self.psd and self.psd_abort_difference:
            if abs(self.psd.dist - psd.dist) / self.psd.dist > self.psd_abort_difference:
                logging.info("%s PSD is CRAZY, aborting!!!!, %s-%s",
                             self.detector, self.psd.dist, psd.dist)
                self.psd = psd
                self.psds = {}
                return False

        # If the new estimate replaces the current one, invalide the ineterpolate PSDs
        self.psd = psd
        self.psds = {}
        logging.info("Recalculating %s PSD, %s", self.detector, psd.dist)
        return True