code: def gaussian(features):
      """Computes the probability density function of the input signal using a Gaussian function
  
      Parameters
      ----------
      features : nd-array
          Input from which probability density function is computed
      Returns
      -------
      nd-array
          probability density values
  
      """
  
      features_ = np.copy(features)
  
      xx = create_xx(features_)
      std_value = np.std(features_)
      mean_value = np.mean(features_)
  
      if std_value == 0:
          return 0.0
      pdf_gauss = scipy.stats.norm.pdf(xx, mean_value, std_value)
  
      return np.array(pdf_gauss / np.sum(pdf_gauss))
  
file_path: tsfel/tsfel/feature_extraction/features_utils.py
imports: import scipy
  import numpy
label_desc: Use image node_id 10 for calling a global function with example usage: gaussian(features) and returns: np, int