code: def spectral_distance(signal, fs):
      """Computes the signal spectral distance.
  
      Distance of the signal's cumulative sum of the FFT elements to
      the respective linear regression.
  
      Feature computational cost: 1
  
      Parameters
      ----------
      signal : nd-array
          Signal from which spectral distance is computed
      fs : float
          Sampling frequency
  
      Returns
      -------
      float
          spectral distance
  
      """
      f, fmag = calc_fft(signal, fs)
  
      cum_fmag = np.cumsum(fmag)
  
      # Computing the linear regression
      points_y = np.linspace(0, cum_fmag[-1], len(cum_fmag))
  
      return np.sum(points_y - cum_fmag)
  
imports: import scipy.signal
  from tsfel.feature_extraction.features_utils import *
label_desc: Use image node_id 36 for calling a global function with example usage: spectral_distance(signal, fs) and returns: np