code: def __init__(self, scalar_path):
      scalar = np.load(scalar_path)
      mean = scalar["mean"]
      std = scalar["std"]
  
      zero_std = np.where(std == 0.0)[0]
  
      mean = np.array(
          [mean[i] for i in range(len(mean)) if i not in zero_std]
      )
      std = np.array(
          [std[i] for i in range(len(std)) if i not in zero_std]
      )
  
      self.mean = mean
      self.std = std
      self.zero_std = zero_std
  
file_path: PARL/examples/NeurIPS2020-Learning-to-Run-a-Power-Network-Challenge/track1/utils.py
imports: import numpy
label_desc: Use image node_id 1 to create a new UnitaryFeatureProcessor object from inherited base classes: object with example: obj = UnitaryFeatureProcessor(scalar_path)