code: def show_with_diff(image, reference, title):
      """Helper function to display denoising"""
      plt.figure(figsize=(5, 3.3))
      plt.subplot(1, 2, 1)
      plt.title("Image")
      plt.imshow(
          image,
          vmin=0,
          vmax=1,
          cmap=plt.cm.gray,
          interpolation="nearest",
      )
      plt.xticks(())
      plt.yticks(())
      plt.subplot(1, 2, 2)
      difference = image - reference
  
      plt.title(
          "Difference (norm: %.2f)" % np.sqrt(np.sum(difference**2))
      )
      plt.imshow(
          difference,
          vmin=-0.5,
          vmax=0.5,
          cmap=plt.cm.PuOr,
          interpolation="nearest",
      )
      plt.xticks(())
      plt.yticks(())
      plt.suptitle(title, size=16)
      plt.subplots_adjust(0.02, 0.02, 0.98, 0.79, 0.02, 0.2)
  
imports: import numpy
  import matplotlib.pyplot
  from time import time
  from sklearn.feature_extraction.image import extract_patches_2d
  from sklearn.decomposition import MiniBatchDictionaryLearning
  from sklearn.feature_extraction.image import reconstruct_from_patches_2d
label_desc: Use image node_id 1 for calling a global function with example usage: show_with_diff(image, reference, title) without return types