Huffman編碼及解碼

# coding:utf-8#Tree-Node Type class Node:def __init__(self,freq):self.left = Noneself.right = Noneself.father = Noneself.freq = freqdef isLeft(self):return self.father.left == self #create nodes創建葉子節點 def createNodes(freqs):return [Node(freq) for freq in freqs]#create Huffman-Tree創建Huffman樹 def createHuffmanTree(nodes):queue = nodes[:]while len(queue) > 1:queue.sort(key=lambda item:item.freq)node_left = queue.pop(0)node_right = queue.pop(0)node_father = Node(node_left.freq + node_right.freq)node_father.left = node_leftnode_father.right = node_rightnode_left.father = node_fathernode_right.father = node_fatherqueue.append(node_father)queue[0].father = Nonereturn queue[0] #Huffman編碼 def huffmanEncoding(nodes,root):codes = [''] * len(nodes)for i in range(len(nodes)):node_tmp = nodes[i]while node_tmp != root:if node_tmp.isLeft():codes[i] = '0' + codes[i]else:codes[i] = '1' + codes[i]node_tmp = node_tmp.fatherreturn codes# 解壓縮huffman文件 def decode_huffman(input_string, char_store, freq_store):#input_string 哈夫曼編碼#char_store 字符集合 #freq_store 字符轉編碼01序列encode = ''decode = ''for index in range(len(input_string)):encode = encode + input_string[index]for item in zip(char_store, freq_store):if encode == item[1]:decode = decode + item[0]encode = ''return decode; #獲取Huffman編碼 def getHuffmanCode(string): dict1 ={}for i in string:if i in dict1.keys():dict1[i] += 1else :dict1[i] = 1 #將字符根據頻次排序chars_freqs = sorted(dict1.items(), key = lambda kv:(kv[1], kv[0]))#創建huffman節點樹nodes = createNodes([item[1] for item in chars_freqs])root = createHuffmanTree(nodes)#每個字符的Huffman編碼codes = huffmanEncoding(nodes,root)#print codesdict2 = {}for item in zip(chars_freqs,codes):#print 'Character:%s freq:%-2d encoding: %s' % (item[0][0],item[0][1],item[1])dict2[item[0][0]] = item[1]str = ''for v in string:str += dict2[v]return [str,dict2]

getHuffmanCode（string）：獲取string字符串的01編碼及單個字符和相對于的01序列
decode_huffman（string，chars,freqs）:解碼，參數為編碼的返回值

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