def test_compile_and_run_cont_sparse(self):
# pylint: disable=protected-access
model = TreeModel(self.data, self.root)
expected_values = np.vstack((np.arange(8), [42] * 8)).T
np.testing.assert_equal(model._values, expected_values)
self.assertEqual(model._thresholds[0], 13)
self.assertEqual(model._thresholds.shape, (8, ))
nan = float("nan")
x = sp.csr_matrix(
np.array([[nan, 0, 0], [13, nan, 0], [13, 0, 0], [13, 1, 0],
[13, 2, 0], [14, 2, nan], [14, 2, 2], [14, 2, 1]],
dtype=float))
np.testing.assert_equal(model.get_values(x), expected_values)
x = sp.csc_matrix(
np.array([[nan, 0, 0], [13, nan, 0], [13, 0, 0], [13, 1, 0],
[13, 2, 0], [14, 2, nan], [14, 2, 2], [14, 2, 1]],
dtype=float))
np.testing.assert_equal(model.get_values(x), expected_values)
x = sp.lil_matrix(
np.array([[nan, 0, 0], [13, nan, 0], [13, 0, 0], [13, 1, 0],
[13, 2, 0], [14, 2, nan], [14, 2, 2], [14, 2, 1]],
dtype=float))
np.testing.assert_equal(model.get_values(x), expected_values)
def test_print(self):
model = TreeModel(self.data, self.root)
self.assertEqual(model.print_tree(), """ [ 1 42] v1 ≤ 13
[ 2 42] v2 a
[ 3 42] v2 b
[ 4 42] v2 c
[ 5 42] v1 > 13
[ 6 42] v3 f
[ 7 42] v3 d or e
""")
def test_null_nodes(self):
a = DiscreteVariable("d4", "ab")
y = ContinuousVariable("ey")
domain = Domain([a], y)
data = Table(domain)
values = np.array([[42., 43], [44, 45]])
root = DiscreteNode(a, 0, values[1])
root.children = [Node(None, -1, values[0]), None]
model = TreeModel(data, root)
x = np.array([[0.], [1]])
np.testing.assert_equal(model.get_values(x), values)
np.testing.assert_equal(model.get_values_in_python(x), values)
np.testing.assert_equal(model.get_values_by_nodes(x), values)
def test_compile_and_run_cont_sparse(self):
# pylint: disable=protected-access
model = TreeModel(self.data, self.root)
expected_values = np.vstack((np.arange(8), [42] * 8)).T
np.testing.assert_equal(model._values, expected_values)
self.assertEqual(model._thresholds[0], 13)
self.assertEqual(model._thresholds.shape, (8,))
nan = float("nan")
x = sp.csr_matrix(np.array(
[[nan, 0, 0],
[13, nan, 0],
[13, 0, 0],
[13, 1, 0],
[13, 2, 0],
[14, 2, nan],
[14, 2, 2],
[14, 2, 1]], dtype=float
))
np.testing.assert_equal(model.get_values(x), expected_values)
x = sp.csc_matrix(np.array(
[[nan, 0, 0],
[13, nan, 0],
[13, 0, 0],
[13, 1, 0],
[13, 2, 0],
[14, 2, nan],
[14, 2, 2],
[14, 2, 1]], dtype=float
))
np.testing.assert_equal(model.get_values(x), expected_values)
x = sp.lil_matrix(np.array(
[[nan, 0, 0],
[13, nan, 0],
[13, 0, 0],
[13, 1, 0],
[13, 2, 0],
[14, 2, nan],
[14, 2, 2],
[14, 2, 1]], dtype=float
))
np.testing.assert_equal(model.get_values(x), expected_values)
def test_compile_and_run_cont(self):
# I investigate, I have a warrant
# pylint: disable=protected-access
model = TreeModel(self.data, self.root)
expected_values = np.vstack((np.arange(8), [42] * 8)).T
np.testing.assert_equal(model._values, expected_values)
self.assertEqual(model._thresholds[0], 13)
self.assertEqual(model._thresholds.shape, (8, ))
nan = float("nan")
x = np.array(
[
[nan, 0, 0],
[13, nan, 0],
[13, 0, 0],
[13, 1, 0],
[13, 2, 0],
[14, 2, nan],
[14, 2, 2],
[14, 2, 1],
],
dtype=float,
)
np.testing.assert_equal(model.get_values(x), expected_values)
np.testing.assert_equal(model.get_values_in_python(x), expected_values)
np.testing.assert_equal(model.get_values_by_nodes(x), expected_values)
np.testing.assert_equal(model.predict(x), np.arange(8).astype(int))
v1 = ContinuousVariable("d1")
v2 = DiscreteVariable("d2", "abc")
v3 = DiscreteVariable("d3", "def")
y = DiscreteVariable("dy")
domain = Domain([v1, v2, v3], y)
data = Table(domain, np.zeros((10, 4)))
root = NumericNode(v1, 0, 13, np.array([0.0, 42]))
left = DiscreteNode(v2, 1, np.array([1, 42]))
left.children = [
Node(None, None, np.array([x, 42])) for x in [2, 3, 4]
]
right = MappedDiscreteNode(v3, 2, np.array([1, 1, 0]),
np.array([5, 42]))
right.children = [Node(None, None, np.array([x, 42])) for x in [6, 7]]
root.children = [left, right]
model = TreeModel(data, root)
normalized = expected_values / np.sum(expected_values,
axis=1)[:, np.newaxis]
np.testing.assert_equal(model.predict(x), normalized)
def test_methods(self):
model = TreeModel(self.data, self.root)
self.assertEqual(model.node_count(), 8)
self.assertEqual(model.leaf_count(), 5)
self.assertEqual(model.depth(), 2)
self.assertIs(model.root, self.root)
left = self.root.children[0]
left.subset = np.array([2, 3])
subset = model.get_instances([self.root, left])
self.assertIsInstance(subset, Table)
self.assertEqual(len(subset), 2)
np.testing.assert_equal(subset.X, np.array([[8, 9, 10], [12, 13, 14]]))
np.testing.assert_equal(subset.Y, np.array([11, 15]))
def test_compile_and_run_cont(self):
# I investigate, I have a warrant
# pylint: disable=protected-access
model = TreeModel(self.data, self.root)
expected_values = np.vstack((np.arange(8), [42] * 8)).T
np.testing.assert_equal(model._values, expected_values)
self.assertEqual(model._thresholds[0], 13)
self.assertEqual(model._thresholds.shape, (8,))
nan = float("nan")
x = np.array(
[[nan, 0, 0],
[13, nan, 0],
[13, 0, 0],
[13, 1, 0],
[13, 2, 0],
[14, 2, nan],
[14, 2, 2],
[14, 2, 1]], dtype=float
)
np.testing.assert_equal(model.get_values(x), expected_values)
np.testing.assert_equal(model.get_values_in_python(x), expected_values)
np.testing.assert_equal(model.get_values_by_nodes(x), expected_values)
np.testing.assert_equal(model.predict(x), np.arange(8).astype(int))
v1 = ContinuousVariable("d1")
v2 = DiscreteVariable("d2", "abc")
v3 = DiscreteVariable("d3", "def")
y = DiscreteVariable("dy")
domain = Domain([v1, v2, v3], y)
data = Table(domain, np.zeros((10, 4)))
root = NumericNode(v1, 0, 13, np.array([0., 42]))
left = DiscreteNode(v2, 1, np.array([1, 42]))
left.children = [Node(None, None, np.array([x, 42])) for x in [2, 3, 4]]
right = MappedDiscreteNode(v3, 2, np.array([1, 1, 0]),
np.array([5, 42]))
right.children = [Node(None, None, np.array([x, 42])) for x in [6, 7]]
root.children = [left, right]
model = TreeModel(data, root)
normalized = \
expected_values / np.sum(expected_values, axis=1)[:, np.newaxis]
np.testing.assert_equal(model.predict(x), normalized)
def setUp(self):
# pylint: disable=invalid-name
v1 = self.v1 = ContinuousVariable("v1")
v2 = self.v2 = DiscreteVariable("v2", "abc")
v3 = self.v3 = DiscreteVariable("v3", "def")
y = self.y = ContinuousVariable("y")
self.domain = Domain([v1, v2, v3], y)
self.data = Table(self.domain, np.arange(40).reshape(10, 4))
self.root = NumericNode(v1, 0, 13, np.array([0.0, 42]))
self.root.subset = np.array(np.arange(10), dtype=np.int32)
left = self.left = DiscreteNode(v2, 1, np.array([1, 42]))
left.subset = np.array([2, 3, 4, 5])
left.children = [Node(None, None, np.array([x, 42])) for x in [2, 3, 4]]
right = self.right = MappedDiscreteNode(
v3, 2, np.array([1, 1, 0]), np.array([5, 42])
)
right.children = [Node(None, None, np.array([6, 42])), None]
right.subset = np.array([8, 9])
self.root.children = [left, right]
self.model = TreeModel(self.data, self.root)
self.adapter = TreeAdapter(self.model)
