def setUp(self):
# Set initial points for sentinels (to simulate infinity)
big_pos_value = 10E10
big_neg_value = -1 * big_pos_value
self.p1 = np.array([big_neg_value, big_pos_value, big_neg_value])
p2 = np.array([big_pos_value, big_neg_value, big_neg_value])
# Initialize avltree
point0 = eaf3D.ApproxPoint(None, 1000, self.p1)
point1 = eaf3D.ApproxPoint(None, 1001, p2)
node0 = bst.AVLNode(point0, 1)
node1 = bst.AVLNode(point1, 0)
self.t = bst.AVLTree()
self.t.root = node0
node0.right = node1
self.t.count = 2
# Import more data points
fname = 'example/run01'
exset = eaf3D.import_approximate_set(fname)
x, m = eaf3D.multiset_sum([exset])
# Q is X sorted in ascending order of the z coordinate
self.qstack = Stack()
xintoq = sorted(x.values(), key=attrgetter('z'))
for i in range(len(xintoq)):
self.qstack.push(xintoq[i])
# Add new data points to tree
for i in range(4):
p = self.qstack.pop()
self.t.insert(p)
def test_remove_node_case3_left_is_rightmost(self):
# Set up tree to test case 3 when the left node is the rightmost
tree = bst.AVLTree()
point0 = eaf3D.ApproxPoint(1, 1, np.array([4, 12.67, 0]))
tree.set_newroot(point0)
# Set initial points for sentinels (to simulate infinity)
big_pos_value = 10E10
big_neg_value = -1 * big_pos_value
p1 = np.array([big_neg_value, big_pos_value, big_neg_value])
p2 = np.array([big_pos_value, big_neg_value, big_neg_value])
# Initialize avltree
point1 = eaf3D.ApproxPoint(None, 1000, p1)
av1 = bst.AVLNode(point1, balance=1)
tree.root.left = av1
point2 = eaf3D.ApproxPoint(None, 1001, p2)
av2 = bst.AVLNode(point2, balance=-1)
tree.root.right = av2
point3 = eaf3D.ApproxPoint(1, 2, np.array([3, 20.21, 0]))
av3 = bst.AVLNode(point3)
tree.root.left.right = av3
point4 = eaf3D.ApproxPoint(1, 3, np.array([5, 10.42, 0]))
av4 = bst.AVLNode(point4)
tree.root.right.left = av4
tree.count = 5
tree.remove_node(tree.root)
tree.remove_node(tree.root)
self.assertEqual(tree.root, av4)
self.check_node_balances(tree)
def test_adjustBalances_negative(self):
for i in range(4):
self.qstack.pop()
point = self.qstack.pop()
(pivot, theStack, parent, found) = self.t.search(point)
newNode = bst.AVLNode(point)
self.t.adjustBalances_add(theStack, pivot, newNode)
self.assertEqual(pivot.balance, -2)