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))