1.先序遍歷:根節點->左子樹->右子樹node
1 # 先序打印二叉樹(遞歸) 2 def preOrderTraverse(node): 3 if node is None: 4 return None 5 print(node.val) 6 preOrderTraverse(node.left) 7 preOrderTraverse(node.right)
1 # 先序打印二叉樹(非遞歸) 2 def preOrderTravese(node): 3 stack = [node] 4 while len(stack) > 0: 5 print(node.val) 6 if node.right is not None: 7 stack.append(node.right) 8 if node.left is not None: 9 stack.append(node.left) 10 node = stack.pop()
2.中序遍歷:左子樹->根節點->右子樹app
1 # 中序打印二叉樹(遞歸) 2 def inOrderTraverse(node): 3 if node is None: 4 return None 5 inOrderTraverse(node.left) 6 print(node.val) 7 inOrderTraverse(node.right)
1 # 中序打印二叉樹(非遞歸) 2 def inOrderTraverse(node): 3 stack = [] 4 pos = node 5 while pos is not None or len(stack) > 0: 6 if pos is not None: 7 stack.append(pos) 8 pos = pos.left 9 else: 10 pos = stack.pop() 11 print(pos.val) 12 pos = pos.right
3.後序遍歷:左子樹->右子樹->根節點post
1 # 後序打印二叉樹(遞歸) 2 def postOrderTraverse(node): 3 if node is None: 4 return None 5 postOrderTraverse(node.left) 6 postOrderTraverse(node.right) 7 print(node.val)
1 # 後序打印二叉樹(非遞歸) 2 # 使用兩個棧結構 3 # 第一個棧進棧順序:左節點->右節點->跟節點 4 # 第一個棧彈出順序: 跟節點->右節點->左節點(先序遍歷棧彈出順序:跟->左->右) 5 # 第二個棧存儲爲第一個棧的每一個彈出依次進棧 6 # 最後第二個棧依次出棧 7 def postOrderTraverse(node): 8 stack = [node] 9 stack2 = [] 10 while len(stack) > 0: 11 node = stack.pop() 12 stack2.append(node) 13 if node.left is not None: 14 stack.append(node.left) 15 if node.right is not None: 16 stack.append(node.right) 17 while len(stack2) > 0: 18 print(stack2.pop().val)
4.按層遍歷:從上到下、從左到右按層遍歷spa
1 # 先進先出選用隊列結構 2 import queue 3 def layerTraverse(head): 4 if not head: 5 return None 6 que = queue.Queue() # 建立先進先出隊列 7 que.put(head) 8 while not que.empty(): 9 head = que.get() # 彈出第一個元素並打印 10 print(head.val) 11 if head.left: # 若該節點存在左子節點,則加入隊列(先push左節點) 12 que.put(head.left) 13 if head.right: # 若該節點存在右子節點,則加入隊列(再push右節點) 14 que.put(head.right)
5.二叉樹節點個數code
1 # 求二叉樹節點個數 2 def treeNodenums(node): 3 if node is None: 4 return 0 5 nums = treeNodenums(node.left) 6 nums += treeNodenums(node.right) 7 return nums + 1
6.二叉樹的最大深度blog
1 # 二叉樹的最大深度 2 def bTreeDepth(node): 3 if node is None: 4 return 0 5 ldepth = bTreeDepth(node.left) 6 rdepth = bTreeDepth(node.right) 7 return (max(ldepth, rdepth) + 1)