code: def extract_derivative_feature(feature):
      
      first_derivative_feature = processing.derivative_extraction(
          feature, DeltaWindows=2)
      second_derivative_feature = processing.derivative_extraction(
          first_derivative_feature, DeltaWindows=2)
  
      # Creating the future cube for each file
      feature_cube = np.concatenate(
          (feature[:, :, None], first_derivative_feature[:, :, None],
           second_derivative_feature[:, :, None]),
          axis=2)
      return feature_cube
docs: This function extracts temporal derivative features which are
          first and second derivatives.
  
      Args:
          feature (array): The feature vector which its size is: N x M
  
      Return:
            array: The feature cube vector which contains the static, first and second derivative features of size: N x M x 3