code: def spectral_slope(signal, fs):
      """Computes the spectral slope.
  
      Spectral slope is computed by finding constants m and b of the function aFFT = mf + b, obtained by linear regression
      of the spectral amplitude.
  
      Description and formula in Article:
      The Timbre Toolbox: Extracting audio descriptors from musicalsignals
      Authors Peeters G., Giordano B., Misdariis P., McAdams S.
  
      Feature computational cost: 1
  
      Parameters
      ----------
      signal : nd-array
          Signal from which spectral slope is computed
      fs : float
          Sampling frequency
  
      Returns
      -------
      float
          Spectral Slope
  
      """
      f, fmag = calc_fft(signal, fs)
      sum_fmag = fmag.sum()
      dot_ff = (f * f).sum()
      sum_f = f.sum()
      len_f = len(f)
  
      if not ([f]) or (sum_fmag == 0):
          return 0
      else:
          if not (len_f * dot_ff - sum_f**2):
              return 0
          else:
              num_ = (1 / sum_fmag) * (
                  len_f * np.sum(f * fmag) - sum_f * sum_fmag
              )
              denom_ = len_f * dot_ff - sum_f**2
              return num_ / denom_
  
imports: import scipy.signal
  from tsfel.feature_extraction.features_utils import *
label_desc: Use image node_id 46 for calling a global function with example usage: spectral_slope(signal, fs) and returns: int, int, unknown