哈夫曼编码+python实现

关于哈夫曼树怎么构建的、哈夫曼编码怎么求，请参考

哈夫曼树及python实现

这些基础的东西就不在这里阐述了，本文直接上代码。

参考链接：哈夫曼树的 Python 实现

哈夫曼树的构建和编码

'''
    huffman编码
'''
import copy

class Node:
    def __init__(self, name, weight):
        self.name = name #节点名
        self.weight = weight #节点权重
        self.left = None #节点左孩子
        self.right = None #节点右孩子
        self.father = None # 节点父节点
    #判断是否是左孩子
    def is_left_child(self):
        return self.father.left == self

#创建最初的叶子节点
def create_prim_nodes(data_set, labels):
    if(len(data_set) != len(labels)):
        raise Exception('数据和标签不匹配!')
    nodes = []
    for i in range(len(labels)):
        nodes.append( Node(labels[i],data_set[i]) )
    return nodes

# 创建huffman树
def create_HF_tree(nodes):
    #此处注意，copy()属于浅拷贝，只拷贝最外层元素，内层嵌套元素则通过引用，而不是独立分配内存
    tree_nodes = nodes.copy()
    while len(tree_nodes) > 1: #只剩根节点时，退出循环
        tree_nodes.sort(key=lambda node: node.weight)#升序排列
        new_left = tree_nodes.pop(0)
        new_right = tree_nodes.pop(0)
        new_node = Node(None, (new_left.weight + new_right.weight))
        new_node.left = new_left
        new_node.right = new_right
        new_left.father = new_right.father = new_node
        tree_nodes.append(new_node)
    tree_nodes[0].father = None #根节点父亲为None
    return tree_nodes[0] #返回根节点

#获取huffman编码
def get_huffman_code(root, nodes):
    codes = {}
    for node in nodes:
        code=''
        name = node.name
        while node.father != None:
            if node.is_left_child():
                code = '0' + code
            else:
                code = '1' + code
            node = node.father
        codes[name] = code
    return codes

if __name__ == '__main__':
    labels = ['a','b','c','d','e','f']
    data_set = [9,12,6,3,5,15]
    nodes = create_prim_nodes(data_set,labels)#创建初始叶子节点
    root = create_HF_tree(nodes)#创建huffman树
    codes = get_huffman_code(root, nodes)#获取huffman编码
    #打印huffman码
    for key in codes.keys():
        print(key,': ',codes[key])

运行结果如下：

a :  00
b :  01
c :  100
d :  1010
e :  1011
f :  11