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hello-algo/codes/python/chapter_tree/avl_tree.py

282 lines
8.2 KiB

import sys, os.path as osp
import typing
sys.path.append(osp.dirname(osp.dirname(osp.abspath(__file__))))
from include import *
class AVLTreeNode:
def __init__(
self,
val=None,
height: int = 0,
left: typing.Optional["AVLTreeNode"] = None,
right: typing.Optional["AVLTreeNode"] = None,
):
self.val = val
self.height = height
self.left = left
self.right = right
def __str__(self):
val = self.val
left_val = self.left.val if self.left else None
right_val = self.right.val if self.right else None
return "<AVLTreeNode: {}, leftAVLTreeNode: {}, rightAVLTreeNode: {}>".format(
val, left_val, right_val
)
class AVLTree:
def __init__(self, root: typing.Optional[AVLTreeNode] = None):
self.root = root
@staticmethod
def height(node: typing.Optional[AVLTreeNode]) -> int:
"""
获取结点高度
Args:
node:起始结点
Returns: 高度 or -1
"""
# 空结点高度为 -1 ,叶结点高度为 0
if node is not None:
return node.height
return -1
def __update_height(self, node: AVLTreeNode):
"""
更新结点高度
Args:
node: 要更新高度的结点
Returns: None
"""
# 结点高度等于最高子树高度 + 1
node.height = max([self.height(node.left), self.height(node.right)]) + 1
def balance_factor(self, node: AVLTreeNode) -> int:
"""
获取结点平衡因子
Args:
node: 要获取平衡因子的结点
Returns: 平衡因子
"""
# 空结点平衡因子为 0
if node is None:
return 0
# 结点平衡因子 = 左子树高度 - 右子树高度
return self.height(node.left) - self.height(node.right)
def __right_rotate(self, node: AVLTreeNode) -> AVLTreeNode:
child = node.left
grand_child = child.right
# 以 child 为原点,将 node 向右旋转
child.right = node
node.left = grand_child
# 更新结点高度
self.__update_height(node)
self.__update_height(child)
# 返回旋转后子树的根节点
return child
def __left_rotate(self, node: AVLTreeNode) -> AVLTreeNode:
child = node.right
grand_child = child.left
# 以 child 为原点,将 node 向左旋转
child.left = node
node.right = grand_child
# 更新结点高度
self.__update_height(node)
self.__update_height(child)
# 返回旋转后子树的根节点
return child
def rotate(self, node: AVLTreeNode):
"""
执行旋转操作使该子树重新恢复平衡
Args:
node: 要旋转的根结点
Returns: 旋转后的根结点
"""
# 获取结点 node 的平衡因子
balance_factor = self.balance_factor(node)
# 左偏树
if balance_factor > 1:
if self.balance_factor(node.left) >= 0:
# 右旋
return self.__right_rotate(node)
else:
# 先左旋后右旋
node.left = self.__left_rotate(node.left)
return self.__right_rotate(node)
# 右偏树
elif balance_factor < -1:
if self.balance_factor(node.right) <= 0:
# 左旋
return self.__left_rotate(node)
else:
# 先右旋后左旋
node.right = self.__right_rotate(node.right)
return self.__left_rotate(node)
# 平衡树,无需旋转,直接返回
return node
def insert(self, val) -> AVLTreeNode:
"""
插入结点
Args:
val: 结点的值
Returns:
node: 插入结点后的根结点
"""
self.root = self.insert_helper(self.root, val)
return self.root
def insert_helper(
self, node: typing.Optional[AVLTreeNode], val: int
) -> AVLTreeNode:
"""
递归插入结点辅助函数
Args:
node: 要插入的根结点
val: 要插入的结点的值
Returns: 插入结点后的根结点
"""
if node is None:
return AVLTreeNode(val)
# 1. 查找插入位置,并插入结点
if val < node.val:
node.left = self.insert_helper(node.left, val)
elif val > node.val:
node.right = self.insert_helper(node.right, val)
else:
# 重复结点不插入,直接返回
return node
# 更新结点高度
self.__update_height(node)
# 2. 执行旋转操作,使该子树重新恢复平衡
return self.rotate(node)
def remove(self, val: int):
"""
删除结点
Args:
val: 要删除的结点的值
Returns:
"""
root = self.remove_helper(self.root, val)
return root
def remove_helper(
self, node: typing.Optional[AVLTreeNode], val: int
) -> typing.Optional[AVLTreeNode]:
"""
递归删除结点辅助函数
Args:
node: 删除的起始结点
val: 要删除的结点的值
Returns: 删除目标结点后的起始结点
"""
if node is None:
return None
# 1. 查找结点,并删除之
if val < node.val:
node.left = self.remove_helper(node.left, val)
elif val > node.val:
node.right = self.remove_helper(node.right, val)
else:
if node.left is None or node.right is None:
child = node.left or node.right
# 子结点数量 = 0 ,直接删除 node 并返回
if child is None:
return None
# 子结点数量 = 1 ,直接删除 node
else:
node = child
else: # 子结点数量 = 2 ,则将中序遍历的下个结点删除,并用该结点替换当前结点
temp = self.min_node(node.right)
node.right = self.remove_helper(node.right, temp.val)
node.val = temp.val
# 更新结点高度
self.__update_height(node)
# 2. 执行旋转操作,使该子树重新恢复平衡
return self.rotate(node)
def min_node(
self, node: typing.Optional[AVLTreeNode]
) -> typing.Optional[AVLTreeNode]:
# 获取最小结点
if node is None:
return None
# 循环访问左子结点,直到叶结点时为最小结点,跳出
while node.left is not None:
node = node.left
return node
def search(self, val: int):
cur = self.root
while cur is not None:
if cur.val < val:
cur = cur.right
elif cur.val > val:
cur = cur.left
else:
break
return cur
if __name__ == "__main__":
def test_insert(tree: AVLTree, val: int):
tree.insert(val)
print("\n插入结点 {}AVL 树为".format(val))
print_tree(tree.root)
def test_remove(tree: AVLTree, val: int):
tree.remove(val)
print("\n删除结点 {}AVL 树为".format(val))
print_tree(tree.root)
# 初始化空 AVL 树
avl_tree = AVLTree()
# 插入结点
# 请关注插入结点后AVL 树是如何保持平衡的
test_insert(avl_tree, 1)
test_insert(avl_tree, 2)
test_insert(avl_tree, 3)
test_insert(avl_tree, 4)
test_insert(avl_tree, 5)
test_insert(avl_tree, 8)
test_insert(avl_tree, 7)
test_insert(avl_tree, 9)
test_insert(avl_tree, 10)
test_insert(avl_tree, 6)
# 插入重复结点
test_insert(avl_tree, 7)
# 删除结点
# 请关注删除结点后AVL 树是如何保持平衡的
test_remove(avl_tree, 8) # 删除度为 0 的结点
test_remove(avl_tree, 5) # 删除度为 1 的结点
test_remove(avl_tree, 4) # 删除度为 2 的结点
result_node = avl_tree.search(7)
print("\n查找到的结点对象为 {},结点值 = {}".format(result_node, result_node.val))