code: def interpolate(self, df):
          
          f0 = self.f0.decompose().value
          N = (self.size - 1) * (self.df.decompose().value / df) + 1
          fsamples = numpy.arange(0, numpy.rint(N), dtype=self.dtype) * df + f0
          out = type(self)(numpy.interp(fsamples, self.frequencies.value,
                                        self.value))
          out.__array_finalize__(self)
          out.f0 = f0
          out.df = df
          return out
docs: Interpolate this `FrequencySeries` to a new resolution.
  
          Parameters
          ----------
          df : `float`
              desired frequency resolution of the interpolated `FrequencySeries`,
              in Hz
  
          Returns
          -------
          out : `FrequencySeries`
              the interpolated version of the input `FrequencySeries`
  
          See Also
          --------
          numpy.interp
              for the underlying 1-D linear interpolation scheme