def test_null_split_returns_all_values(self):
data = make_bartpy_data(
pd.DataFrame({
"a": [1, 2]
}).values, np.array([1, 2]))
split = Split(data)
conditioned_data = split.data
self.assertListEqual(list(data.X.get_column(0)),
list(conditioned_data.X.get_column(0)))
def setUp(self):
self.data = make_bartpy_data(
pd.DataFrame({"a": np.random.normal(size=1000)}),
np.array(np.random.normal(size=1000)))
self.d = LeafNode(Split(self.data))
self.e = LeafNode(Split(self.data))
self.c = DecisionNode(Split(self.data), self.d, self.e)
self.b = LeafNode(Split(self.data))
self.a = DecisionNode(Split(self.data), self.b, self.c)
self.tree = Tree([self.a, self.b, self.c, self.d, self.e])
def setUp(self):
self.data = make_bartpy_data(pd.DataFrame({"a": [1, 2]}),
np.array([1, 2]),
normalize=False)
self.d = LeafNode(Split(self.data))
self.e = LeafNode(Split(self.data))
self.c = DecisionNode(Split(self.data), self.d, self.e)
self.b = LeafNode(Split(self.data))
self.a = DecisionNode(Split(self.data), self.b, self.c)
self.tree = Tree([self.a, self.b, self.c, self.d, self.e])
def test_single_condition_data(self):
data = make_bartpy_data(
pd.DataFrame({
"a": [1, 2]
}).values, np.array([1, 2]))
left_condition, right_condition = SplitCondition(0, 1,
le), SplitCondition(
0, 1, gt)
left_split, right_split = Split(data) + left_condition, Split(
data) + right_condition
self.assertListEqual([1], list(left_split.data.X.get_column(0)))
self.assertListEqual([2], list(right_split.data.X.get_column(0)))
def test_combined_condition_data(self):
data = make_bartpy_data(
pd.DataFrame({
"a": [1, 2, 3, 4]
}).values, np.array([1, 2, 1, 1]))
first_left_condition, first_right_condition = SplitCondition(
0, 3, le), SplitCondition(0, 3, gt)
second_left_condition, second_right_condition = SplitCondition(
0, 1, le), SplitCondition(0, 1, gt)
split = Split(data)
updated_split = split + first_left_condition + second_right_condition
conditioned_data = updated_split.data
self.assertListEqual([2, 3], list(conditioned_data.X.get_column(0)))
def test_most_recent_split(self):
data = make_bartpy_data(
pd.DataFrame({
"a": [1, 2, 3, 4]
}).values, np.array([1, 2, 1, 1]))
first_left_condition, first_right_condition = SplitCondition(
0, 3, le), SplitCondition(0, 3, gt)
second_left_condition, second_right_condition = SplitCondition(
0, 1, le), SplitCondition(0, 1, gt)
split = Split(data)
updated_split = split + first_left_condition + second_right_condition
self.assertEqual(
(split + first_left_condition).most_recent_split_condition(),
first_left_condition)
self.assertEqual(updated_split.most_recent_split_condition(),
second_right_condition)
def setUp(self):
self.X = np.random.normal(size=20)
self.y = self.X + np.random.normal(scale=0.1, size=20)
self.data = make_bartpy_data(pd.DataFrame({"a": self.X}),
self.y,
normalize=False)
