def test_get_estimator(self, boston_X, boston_y):
forest = RangerForestRegressor(n_estimators=10)
with pytest.raises(NotFittedError):
_ = forest.get_estimator(idx=0)
forest.fit(boston_X, boston_y)
with pytest.raises(ValueError):
_ = forest.get_estimator(0)
forest = RangerForestRegressor(n_estimators=10, enable_tree_details=True)
forest.fit(boston_X, boston_y)
estimator = forest.get_estimator(0)
estimator.predict(boston_X)
assert isinstance(estimator, RangerTreeRegressor)
with pytest.raises(IndexError):
_ = forest.get_estimator(idx=20)
def test_plot():
from matplotlib import pyplot as plt
from sklearn.datasets import load_boston
from sklearn.tree import plot_tree
boston_X, boston_y = load_boston(return_X_y=True)
forest = RangerForestRegressor(enable_tree_details=True)
forest.fit(boston_X, boston_y)
estimator = forest.get_estimator(0)
plt.figure()
plot_tree(
estimator,
impurity=False, # impurity not yet implemented
)
plt.savefig(
"tree.svg",
bbox_inches="tight", # don't truncate
)