code: def viz_digits(
      orientation="TD",
      max_depth=3,
      random_state=666,
      fancy=True,
      pickX=False,
  ):
      clf = tree.DecisionTreeClassifier(
          max_depth=max_depth, random_state=random_state
      )
      digits = load_digits()
  
      # "8x8 image of integer pixels in the range 0..16."
      columns = [f"pixel[{i},{j}]" for i in range(8) for j in range(8)]
  
      clf.fit(digits.data, digits.target)
  
      X = None
      if pickX:
          X = digits.data[np.random.randint(0, len(digits.data)), :]
  
      viz = dtreeviz(
          clf,
          digits.data,
          digits.target,
          target_name="number",
          feature_names=columns,
          orientation=orientation,
          class_names=[chr(c) for c in range(ord("0"), ord("9") + 1)],
          fancy=fancy,
          histtype="bar",
          X=X,
      )
      return viz
  
file_path: dtreeviz/testing/testone.py
imports: import graphviz
  from dtreeviz.shadow import *
  from gen_samples import *
  import tempfile
  from sklearn.tree import export_graphviz
label_desc: Use image node_id 5 for calling a global function with example usage: viz_digits(orientation, max_depth, random_state, fancy, pickX) and returns: viz