code: def _det_stat_freq(det_freq, data_freq_sq, data_freq, w, Nc, ulen, mplen):
      
      num_cor = np.multiply(det_freq, data_freq)  # Numerator convolution
      den_cor = np.multiply(w, data_freq_sq)  # Denominator convolution
      # Do inverse fft
      # First and last Nt - 1 samples are invalid; clip them off
      num_ifft = np.real(np.fft.irfft(num_cor))[:, ulen-1:mplen:Nc]
      denominator = np.real(np.fft.irfft(den_cor))[ulen-1:mplen:Nc]
      # Ratio of projected to envelope energy = det_stat across all channels
      result = np.sum(np.square(num_ifft), axis=0) / denominator
      return result
docs: Compute detection statistic in the frequency domain
  
      :type det_freq: numpy.ndarray
      :param det_freq: detector in freq domain
      :type data_freq_sq: numpy.ndarray
      :param data_freq_sq: squared data in freq domain
      :type data_freq: numpy.ndarray
      :param data_freq: data in freq domain
      :type w: numpy.ndarray
      :param w: boxcar in freq domain
      :type Nc: int
      :param Nc: number of channels in data stream
      :type ulen: int
      :param ulen: length of detector
      :type mplen: int
      :param mplen: length of data
  
      :return: Array of detection statistics
      :rtype: numpy.ndarray