树由n个节点组成的集合,可以递归定义数据结构,如果n=0就是空树
如果n>那么有树
概念
- 根节点、叶子节点
- 树的深度(高度)
- 树的度
- 孩子节点、父节点
- 子树
二叉树-遍历
# 树型图示意
E
A G
C F
B D
- 前序遍历:EACBDGF
- 中序遍历:ABCDEGF
- 后序遍历:BDCAFGE
- 层次遍历:EAGCFBD
二叉搜索树
所有节点左边都比右边小的情况下
二叉搜索树操作: 查询、插入、删除
class BiTreeNode:
def __init__(self, data):
self.data = data
self.lchild = None # 左孩子
self.rchild = None # 右孩子
self.parent = None
class BST:
def __init__(self, li=None):
self.root = None
if li:
for val in li:
self.insert_no_rec(val)
def insert(self, node, val):
"""插入"""
if not node:
node = BiTreeNode(val)
elif val < node.data:
node.lchild = self.insert(node.lchild, val)
node.lchild.parent = node
elif val > node.data:
node.rchild = self.insert(node.rchild, val)
node.rchild.parent = node
return node
def insert_no_rec(self, val):
p = self.root
if not p: # 空树
self.root = BiTreeNode(val)
return
while True:
if val < p.data:
if p.lchild:
p = p.lchild
else: # 左孩子不存在
p.lchild = BiTreeNode(val)
p.lchild.parent = p
return
elif val > p.data:
if p.rchild:
p = p.rchild
else:
p.rchild = BiTreeNode(val)
p.rchild.parent = p
return
else:
return
def query(self, node, val):
if not node:
return None
if node.data < val:
return self.query(node.rchild, val)
elif node.data > val:
return self.query(node.lchild, val)
else:
return node
def query_no_rec(self, val):
p = self.root
while p:
if p.data < val:
p = p.rchild
elif p.data > val:
p = p.lchild
else:
return p
return None
def pre_order(self, root):
if root:
print(root.data, end=',')
self.pre_order(root.lchild)
self.pre_order(root.rchild)
def in_order(self, root):
if root:
self.in_order(root.lchild)
print(root.data, end=',')
self.in_order(root.rchild)
def post_order(self, root):
if root:
self.post_order(root.lchild)
self.post_order(root.rchild)
print(root.data, end=',')
def __remove_node_1(self, node):
# 情况1:node是叶子节点
if not node.parent:
self.root = None
if node == node.parent.lchild: # node是它父亲的左孩子
node.parent.lchild = None
else: # 右孩子
node.parent.rchild = None
def __remove_node_21(self, node):
# 情况2.1:node只有一个左孩子
if not node.parent: # 根节点
self.root = node.lchild
node.lchild.parent = None
elif node == node.parent.lchild:
node.parent.lchild = node.lchild
node.lchild.parent = node.parent
else:
node.parent.rchild = node.lchild
node.lchild.parent = node.parent
def __remove_node_22(self, node):
# 情况2.2:node只有一个右孩子
if not node.parent:
self.root = node.rchild
elif node == node.parent.lchild:
node.parent.lchild = node.rchild
node.rchild.parent = node.parent
else:
node.parent.rchild = node.rchild
node.rchild.parent = node.parent
def delete(self, val):
if self.root: # 不是空树
node = self.query_no_rec(val)
if not node: # 不存在
return False
if not node.lchild and not node.rchild: # 1. 叶子节点
self.__remove_node_1(node)
elif not node.rchild: # 2.1 只有一个左孩子
self.__remove_node_21(node)
elif not node.lchild: # 2.2 只有一个右孩子
self.__remove_node_22(node)
else: # 3. 两个孩子都有
min_node = node.rchild
while min_node.lchild:
min_node = min_node.lchild
node.data = min_node.data
# 删除min_node
if min_node.rchild:
self.__remove_node_22(min_node)
else:
self.__remove_node_1(min_node)
tree = BST([1, 4, 2, 5, 3, 8, 6, 9, 7])
tree.in_order(tree.root)
print("")
tree.delete(4)
tree.delete(1)
tree.delete(8)
tree.in_order(tree.root)
AVL树
AVL树是自平衡的二叉搜索树
根的左右树高度只差绝对值不能超过1
根的左右子树都是平衡树
# 旋转插入
#! /usr/bin/env python
# -*- coding: utf-8 -*-
# Date: 2018/3/24
from bst import BiTreeNode, BST
class AVLNode(BiTreeNode):
def __init__(self, data):
BiTreeNode.__init__(self, data)
self.bf = 0
class AVLTree(BST):
def __init__(self, li=None):
BST.__init__(self, li)
def rotate_left(self, p, c):
s2 = c.lchild
p.rchild = s2
if s2:
s2.parent = p
c.lchild = p
p.parent = c
p.bf = 0
c.bf = 0
return c
def rotate_right(self, p, c):
s2 = c.rchild
p.lchild = s2
if s2:
s2.parent = p
c.rchild = p
p.parent = c
p.bf = 0
c.bf = 0
return c
def rotate_right_left(self, p, c):
g = c.lchild
s3 = g.rchild
c.lchild = s3
if s3:
s3.parent = c
g.rchild = c
c.parent = g
s2 = g.lchild
p.rchild = s2
if s2:
s2.parent = p
g.lchild = p
p.parent = g
# 更新bf
if g.bf > 0:
p.bf = -1
c.bf = 0
elif g.bf < 0:
p.bf = 0
c.bf = 1
else: # 插入的是g
p.bf = 0
c.bf = 0
return g
def rotate_left_right(self, p, c):
g = c.rchild
s2 = g.lchild
c.rchild = s2
if s2:
s2.parent = c
g.lchild = c
c.parent = g
s3 = g.rchild
p.lchild = s3
if s3:
s3.parent = p
g.rchild = p
p.parent = g
# 更新bf
if g.bf < 0:
p.bf = 1
c.bf = 0
elif g.bf > 0:
p.bf = 0
c.bf = -1
else:
p.bf = 0
c.bf = 0
return g
def insert_no_rec(self, val):
# 1. 和BST一样,插入
p = self.root
if not p: # 空树
self.root = AVLNode(val)
return
while True:
if val < p.data:
if p.lchild:
p = p.lchild
else: # 左孩子不存在
p.lchild = AVLNode(val)
p.lchild.parent = p
node = p.lchild # node 存储的就是插入的节点
break
elif val > p.data:
if p.rchild:
p = p.rchild
else:
p.rchild = AVLNode(val)
p.rchild.parent = p
node = p.rchild
break
else: # val == p.data
return
# 2. 更新balance factor
while node.parent: # node.parent不空
if node.parent.lchild == node: # 传递是从左子树来的,左子树更沉了
#更新node.parent的bf -= 1
if node.parent.bf < 0: # 原来node.parent.bf == -1, 更新后变成-2
# 做旋转
# 看node哪边沉
g = node.parent.parent # 为了连接旋转之后的子树
x = node.parent # 旋转前的子树的根
if node.bf > 0:
n = self.rotate_left_right(node.parent, node)
else:
n = self.rotate_right(node.parent, node)
# 记得:把n和g连起来
elif node.parent.bf > 0: # 原来node.parent.bf = 1,更新之后变成0
node.parent.bf = 0
break
else: # 原来node.parent.bf = 0,更新之后变成-1
node.parent.bf = -1
node = node.parent
continue
else: # 传递是从右子树来的,右子树更沉了
#更新node.parent.bf += 1
if node.parent.bf > 0: # 原来node.parent.bf == 1, 更新后变成2
# 做旋转
# 看node哪边沉
g = node.parent.parent # 为了连接旋转之后的子树
x = node.parent # 旋转前的子树的根
if node.bf < 0: # node.bf = 1
n = self.rotate_right_left(node.parent, node)
else: # node.bf = -1
n = self.rotate_left(node.parent, node)
# 记得连起来
elif node.parent.bf < 0: # 原来node.parent.bf = -1,更新之后变成0
node.parent.bf = 0
break
else: # 原来node.parent.bf = 0,更新之后变成1
node.parent.bf = 1
node = node.parent
continue
# 链接旋转后的子树
n.parent = g
if g: # g不是空
if x == g.lchild:
g.lchild = n
else:
g.rchild = n
break
else:
self.root = n
break
tree = AVLTree([9,8,7,6,5,4,3,2,1])
tree.pre_order(tree.root)
print("")
tree.in_order(tree.root)