code: def fd_sine_gaussian(amp, quality, central_frequency, fmin, fmax, delta_f):
      
      kmin = int(round(fmin / delta_f))
      kmax = int(round(fmax / delta_f))
      f = numpy.arange(kmin, kmax) * delta_f
      tau = quality / 2 / numpy.pi / central_frequency
      A = amp * numpy.pi ** 0.5 / 2 * tau
      d = A * numpy.exp(-(numpy.pi  * tau  * (f - central_frequency))**2.0)
      d *= (1 + numpy.exp(-quality ** 2.0 * f / central_frequency))
      v = numpy.zeros(kmax, dtype=numpy.complex128)
      v[kmin:kmax] = d[:]
      return pycbc.types.FrequencySeries(v, delta_f=delta_f)
docs: Generate a Fourier domain sine-Gaussian
  
      Parameters
      ----------
      amp: float
          Amplitude of the sine-Gaussian
      quality: float
          The quality factor
      central_frequency: float
          The central frequency of the sine-Gaussian
      fmin: float
          The minimum frequency to generate the sine-Gaussian. This determines
          the length of the output vector.
      fmax: float
          The maximum frequency to generate the sine-Gaussian
      delta_f: float
          The size of the frequency step
  
      Returns
      -------
      sg: pycbc.types.Frequencyseries
          A Fourier domain sine-Gaussian