生成完全二叉树，并实现深度优先和广度优先算法

最新推荐文章于 2025-10-06 13:44:01 发布

原创最新推荐文章于 2025-10-06 13:44:01 发布 · 790 阅读

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本文介绍了一种实现二叉树层次遍历的算法，包括广度优先搜索（BFS）和深度优先搜索（DFS），并通过具体代码展示了如何创建二叉树结构，并对创建的二叉树进行层次遍历。

二叉树层次遍历
请设计一个算法从上到下逐层打印二叉树的节点数据，同一层从左到右打印，节点数据类型为整型。
二叉树节点定义如下：
struct Binary TreeNode
(
Int data;
Binary TreeNode * leftChild;
Binary TreeNode * rightChild;
)

# -*- coding: utf-8 -*-
from __future__ import unicode_literals
# 生成树的每个节点
class TreeNode:
    def __init__(self, data, left, right):
        # 节点的数据
        self._data = data
        # 节点的左子树
        self._left = left
        # 节点的右子树
        self._right = right

# 生成二叉树
class BinaryTree:
    # 根节点
    def __init__(self):
        self._root = None

    # 创建根节点
    def make_tree(self, treeNode):
        self._root = treeNode

    # 生成子树
    def insert(self, treeNode):
        # build a complete binary tree
        tList = []
        def insert_node(tree_node, p, treeNode):
            if tree_node._left is None:
                tree_node._left = treeNode
                #print("left:",treeNode._data)
                tList.append(tree_node._left)
                return
            elif tree_node._right is None:
                tree_node._right = treeNode
                #print("right:",treeNode._data)
                tList.append(tree_node._right)
                return
            else:
                tList.append(tree_node._left)
                tList.append(tree_node._right)
                insert_node(tList[p+1], p+1, treeNode)

        tList.append(self._root)
        insert_node(self._root, 0, treeNode)

        # print the result
        #print("insert result:")
        #for node in tList:
            #print(node._data)


# 广度有限
def BFS(tree):
    tLst = []
    def traverse(node, p):
        if node._left is not None:
            tLst.append(node._left)
        if node._right is not None:
            tLst.append(node._right)
        if p > (len(tLst)-2):
            return
        else:
            traverse(tLst[p+1], p+1)
    tLst.append(tree._root)
    traverse(tree._root, 0)

    # print the result
    for node in tLst:
        print(node._data)

# 深度优先
def DFS(tree):
    tLst = []
    tLst.append(tree._root)
    while len(tLst) > 0:
        node = tLst.pop()
        print(node._data)
        if node._right is not None:
            tLst.append(node._right)
        if node._left is not None:
            tLst.append(node._left)

if __name__ == '__main__':
    ##TList = [1, 3, 2, 5, 4, 6, 8, 7, 9, 12, 11, 14, 13,10]
    TList = [1,2,3,4,5,6,7,9,8]

    tree = BinaryTree()
    for (i, j) in enumerate(TList):
        node = TreeNode(j, None, None)
        if i == 0:
           tree.make_tree(node)
        else:
           tree.insert(node)
    #print("BFS results:")
    #BFS(tree)      

    #print("DFS results:")
    DFS(tree)