code: def viz_breast_cancer(
      orientation="TD",
      max_depth=3,
      random_state=666,
      fancy=True,
      pickX=False,
      label_fontsize=12,
      ticks_fontsize=8,
      fontname="Arial",
  ):
      clf = tree.DecisionTreeClassifier(
          max_depth=max_depth, random_state=random_state
      )
      cancer = load_breast_cancer()
  
      clf.fit(cancer.data, cancer.target)
  
      X = None
      if pickX:
          X = cancer.data[np.random.randint(0, len(cancer)), :]
  
      viz = dtreeviz(
          clf,
          cancer.data,
          cancer.target,
          target_name="cancer",
          feature_names=cancer.feature_names,
          orientation=orientation,
          class_names=list(cancer.target_names),
          fancy=fancy,
          X=X,
          label_fontsize=label_fontsize,
          ticks_fontsize=ticks_fontsize,
          fontname=fontname,
      )
      return viz
  
imports: import numpy
  import pandas
  import graphviz
  import graphviz.backend
  from numpy.distutils.system_info import f2py_info
  from sklearn import tree
  from sklearn.datasets import load_boston, load_iris, load_wine, load_digits, load_breast_cancer, load_diabetes, fetch_mldata
  from matplotlib.figure import figaspect
  import string
  import re
  import matplotlib.pyplot
  import seaborn
  from dtreeviz.shadow import *
  from numbers import Number
  import matplotlib.patches
  from scipy import stats
  from sklearn.neighbors import KernelDensity
  import inspect
  import sys
  import tempfile
  from dtreeviz.trees import *
label_desc: Use image node_id 1 for calling a global function with example usage: viz_breast_cancer(orientation, max_depth, random_state, fancy, pickX, label_fontsize, ticks_fontsize, fontname) and returns: viz