code: def test_ax():
      np.random.seed(0)
      clf = LogisticRegression()
      clf.fit(X, y)
      probas = clf.predict_proba(X)
      fig, ax = plt.subplots(1, 1)
      out_ax = ks_statistic(y, probas)
      assert ax is not out_ax
      out_ax = ks_statistic(y, probas, ax=ax)
      assert ax is out_ax
  
file_path: sklearn-evaluation/tests/test_ks_statistic.py
imports: import numpy
  import pytest
  import matplotlib.pyplot
  from matplotlib.testing.decorators import image_comparison
  from sklearn.linear_model import LogisticRegression
  from sklearn.datasets import load_breast_cancer, load_iris
  from sklearn_evaluation.plot import ks_statistic
label_desc: Use image node_id 4 for calling a global function with example usage: test_ax() without return types