1.先序遍历:根节点->左子树->右子树
# 先序打印二叉树(递归)
def preOrderTraverse(node):
if node is None:
return None
print(node.val)
preOrderTraverse(node.left)
preOrderTraverse(node.right)
# 先序打印二叉树(非递归)
def preOrderTravese(node):
stack = [node]
while len(stack) > 0:
print(node.val)
if node.right is not None:
stack.append(node.right)
if node.left is not None:
stack.append(node.left)
node = stack.pop()
2.中序遍历:左子树->根节点->右子树
# 中序打印二叉树(递归)
def inOrderTraverse(node):
if node is None:
return None
inOrderTraverse(node.left)
print(node.val)
inOrderTraverse(node.right)
# 中序打印二叉树(非递归)
def inOrderTraverse(node):
stack = []
pos = node
while pos is not None or len(stack) > 0:
if pos is not None:
stack.append(pos)
pos = pos.left
else:
pos = stack.pop()
print(pos.val)
pos = pos.right
3.后序遍历:左子树->右子树->根节点
# 后序打印二叉树(递归)
def postOrderTraverse(node):
if node is None:
return None
postOrderTraverse(node.left)
postOrderTraverse(node.right)
print(node.val)
# 后序打印二叉树(非递归)
# 使用两个栈结构
# 第一个栈进栈顺序:左节点->右节点->跟节点
# 第一个栈弹出顺序: 跟节点->右节点->左节点(先序遍历栈弹出顺序:跟->左->右)
# 第二个栈存储为第一个栈的每个弹出依次进栈
# 最后第二个栈依次出栈
def postOrderTraverse(node):
stack = [node]
stack2 = []
while len(stack) > 0:
node = stack.pop()
stack2.append(node)
if node.left is not None:
stack.append(node.left)
if node.right is not None:
stack.append(node.right)
while len(stack2) > 0:
print(stack2.pop().val)
4.按层遍历:从上到下、从左到右按层遍历
# 先进先出选用队列结构
import queue
def layerTraverse(head):
if not head:
return None
que = queue.Queue() # 创建先进先出队列
que.put(head)
while not que.empty():
head = que.get() # 弹出第一个元素并打印
print(head.val)
if head.left: # 若该节点存在左子节点,则加入队列(先push左节点)
que.put(head.left)
if head.right: # 若该节点存在右子节点,则加入队列(再push右节点)
que.put(head.right)
5.二叉树节点个数
# 求二叉树节点个数
def treeNodenums(node):
if node is None:
return 0
nums = treeNodenums(node.left)
nums += treeNodenums(node.right)
return nums + 1
6.二叉树的最大深度
# 二叉树的最大深度
def bTreeDepth(node):
if node is None:
return 0
ldepth = bTreeDepth(node.left)
rdepth = bTreeDepth(node.right)
return (max(ldepth, rdepth) + 1)
原创文章,作者:ItWorker,如若转载,请注明出处:https://blog.ytso.com/288276.html