code: def avoid_outliers():
      """Use a custom norm to control the displayed z-range of a shaded plot."""
      y, x = np.mgrid[-4:2:200j, -4:2:200j]
      z = 10 * np.cos(x**2 + y**2)
  
      # Add some outliers...
      z[100, 105] = 2000
      z[120, 110] = -9000
  
      ls = LightSource(315, 45)
      fig, (ax1, ax2) = plt.subplots(ncols=2, figsize=(8, 4.5))
  
      rgb = ls.shade(z, plt.cm.copper)
      ax1.imshow(rgb, interpolation="bilinear")
      ax1.set_title("Full range of data")
  
      rgb = ls.shade(z, plt.cm.copper, vmin=-10, vmax=10)
      ax2.imshow(rgb, interpolation="bilinear")
      ax2.set_title("Manually set range")
  
      fig.suptitle("Avoiding Outliers in Shaded Plots", size="x-large")
  
imports: import matplotlib.pyplot
  import numpy
  from matplotlib.colors import LightSource, Normalize
label_desc: Use image node_id 2 for calling a global function with example usage: avoid_outliers() without return types