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_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):
"""
Construct a tree with v1 as a root, and v2 and v3 as left and right
child.
"""
# 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., 42]))
self.root.subset = np.array([], dtype=np.int32)
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]]
self.root.children = [left, right]
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)
def test_mapped_node(self):
var = DiscreteVariable("y", values="abc")
node = MappedDiscreteNode(var, 2, np.array([1, 1, 0]), "foo")
self.assertEqual(node.attr, var)
self.assertEqual(node.attr_idx, 2)
self.assertEqual(node.value, "foo")
self.assertEqual(node.children, [])
np.testing.assert_equal(node.subset, np.array([], dtype=np.int32))
self.assertEqual(node.descend([3, 4, 0, 6]), 1)
self.assertEqual(node.descend([3, 4, 1, 6]), 1)
self.assertEqual(node.descend([3, 4, 2, 6]), 0)
self.assertTrue(np.isnan(node.descend([3, 4, float("nan"), 6])))
mapping, branches = MappedDiscreteNode.branches_from_mapping(
np.array([2, 3, 1, 1, 0, 1, 4, 2]), int("1001", 2), 6)
np.testing.assert_equal(
mapping, np.array([1, 0, 0, 1, 0, 0], dtype=np.int16))
np.testing.assert_equal(
branches, np.array([0, 1, 0, 0, 1, 0, 0, 0], dtype=np.int16))
