code: def wavelet_energy(
      signal, function=scipy.signal.ricker, widths=np.arange(1, 10)
  ):
      """Computes CWT energy of each wavelet scale.
  
      Implementation details:
      https://stackoverflow.com/questions/37659422/energy-for-1-d-wavelet-in-python
  
      Feature computational cost: 2
  
      Parameters
      ----------
      signal : nd-array
          Input from which CWT is computed
      function :  wavelet function
          Default: scipy.signal.ricker
      widths :  nd-array
          Widths to use for transformation
          Default: np.arange(1,10)
  
      Returns
      -------
      tuple
          CWT energy
  
      """
      cwt = wavelet(signal, function, widths)
      energy = np.sqrt(np.sum(cwt**2, axis=1) / np.shape(cwt)[1])
  
      return tuple(energy)
  
imports: import scipy.signal
  from tsfel.feature_extraction.features_utils import *
label_desc: Use image node_id 61 for calling a global function with example usage: wavelet_energy(signal, function, widths) and returns: tuple