code: def wavelet(
      signal, function=scipy.signal.ricker, widths=np.arange(1, 10)
  ):
      """Computes CWT (continuous wavelet transform) of the signal.
  
      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
      -------
      nd-array
          The result of the CWT along the time axis
          matrix with size (len(widths),len(signal))
  
      """
  
      if isinstance(function, str):
          function = eval(function)
  
      if isinstance(widths, str):
          widths = eval(widths)
  
      cwt = scipy.signal.cwt(signal, function, widths)
  
      return cwt
  
file_path: tsfel/tsfel/feature_extraction/features_utils.py
imports: import scipy
  import numpy
label_desc: Use image node_id 11 for calling a global function with example usage: wavelet(signal, function, widths) and returns: cwt