code: def ifft(self):
          
          from ..timeseries import TimeSeries
          nout = (self.size - 1) * 2
          # Undo normalization from TimeSeries.fft
          # The DC component does not have the factor of two applied
          # so we account for it here
          dift = npfft.irfft(self.value * nout) / 2
          new = TimeSeries(dift, epoch=self.epoch, channel=self.channel,
                           unit=self.unit, dx=1/self.dx/nout)
          return new
docs: Compute the one-dimensional discrete inverse Fourier
          transform of this `FrequencySeries`.
  
          Returns
          -------
          out : :class:`~gwpy.timeseries.TimeSeries`
              the normalised, real-valued `TimeSeries`.
  
          See Also
          --------
          :mod:`scipy.fftpack` for the definition of the DFT and conventions
          used.
  
          Notes
          -----
          This method applies the necessary normalisation such that the
          condition holds:
  
          >>> timeseries = TimeSeries([1.0, 0.0, -1.0, 0.0], sample_rate=1.0)
          >>> timeseries.fft().ifft() == timeseries