code: def test_waterfall(explainer):
      """Test the new waterfall plot."""
      fig = plt.figure()
      shap_values = explainer(explainer.data)
      shap.plots.waterfall(shap_values[0])
      plt.tight_layout()
      return fig
  
file_path: shap/tests/plots/test_waterfall.py
imports: import matplotlib.pyplot
  import numpy
  import pandas
  import pytest
  from sklearn.tree import DecisionTreeRegressor
  import shap
label_desc: Use image node_id 3 for calling a global function with example usage: test_waterfall(explainer) and returns: fig