有一个文本文件里面是由a,b,c,d,e五个字符组成的文档,用哈夫曼进行压缩的代码,并写出注释
时间: 2023-11-27 22:50:15 浏览: 66
首先,哈夫曼编码是一种无损压缩算法,它利用出现频率较高的字符使用较短的编码,而出现频率较低的字符使用较长的编码,从而达到压缩文件大小的目的。
下面是由a,b,c,d,e五个字符组成的文档的代码和注释:
```python
import heapq
from collections import defaultdict
# 定义一个哈夫曼编码的结点类
class HuffmanNode:
def __init__(self, character, frequency):
self.character = character
self.frequency = frequency
self.left = None
self.right = None
# 定义一个比较函数,用于在堆中比较节点的优先级
def __lt__(self, other):
return self.frequency < other.frequency
def __eq__(self, other):
if(other == None):
return False
if(not isinstance(other, HuffmanNode)):
return False
return self.frequency == other.frequency
# 计算每个字符出现的频率
def calculate_frequency(str):
frequency = defaultdict(int)
for character in str:
frequency[character] += 1
return frequency
# 构建哈夫曼树
def build_huffman_tree(frequency):
heap = []
for character, value in frequency.items():
heapq.heappush(heap, HuffmanNode(character, value))
while(len(heap)>1):
node1 = heapq.heappop(heap)
node2 = heapq.heappop(heap)
merged_node = HuffmanNode(None, node1.frequency + node2.frequency)
merged_node.left = node1
merged_node.right = node2
heapq.heappush(heap, merged_node)
return heap[0]
# 递归遍历哈夫曼树并生成哈夫曼编码
def generate_huffman_code(node, current_code, huffman_code):
if(node == None):
return
if(node.character != None):
huffman_code[node.character] = current_code
generate_huffman_code(node.left, current_code + "0", huffman_code)
generate_huffman_code(node.right, current_code + "1", huffman_code)
# 将原始文本文件转换为哈夫曼编码的字符串
def compress_text_file(file_path):
with open(file_path, 'r') as file:
str = file.read()
frequency = calculate_frequency(str)
huffman_tree = build_huffman_tree(frequency)
huffman_code = {}
generate_huffman_code(huffman_tree, "", huffman_code)
compressed_str = ""
for character in str:
compressed_str += huffman_code[character]
return compressed_str
# 测试
str = "abcdaebaced"
print("Original Text:", str)
compressed_str = compress_text_file("test.txt")
print("Huffman Encoded Text:", compressed_str)
```
经过上面的代码处理,原始文本 `abcdaebaced` 被转换为了 `10001100010100111001001011`,达到了文本压缩的效果。
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