code: def wavelet_std(
      signal, function=scipy.signal.ricker, widths=np.arange(1, 10)
  ):
      """Computes CWT std value of each wavelet scale.
  
      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 std
  
      """
      return tuple((np.std(wavelet(signal, function, widths), axis=1)))
  
imports: import scipy.signal
  from tsfel.feature_extraction.features_utils import *
label_desc: Use image node_id 59 for calling a global function with example usage: wavelet_std(signal, function, widths) and returns: tuple