设计一个哈夫曼编码译码系统,对某个英文文本文件(.txt)中的字符进行哈夫曼编码,
时间: 2023-11-15 16:01:51 浏览: 96
首先,需要对文本文件中的字符进行频率统计,然后根据频率构建哈夫曼树,并生成对应的哈夫曼编码表。接下来,将文本文件中的每个字符按照哈夫曼编码表进行编码,得到二进制编码序列。最后,将二进制编码序列写入到一个新文件中,同时存储哈夫曼编码表以便后续译码。
以下是一个 Python 实现的哈夫曼编码译码系统:
```python
import heapq
import os
class HuffmanCoding:
def __init__(self, path):
self.path = path
self.heap = []
self.codes = {}
self.reverse_codes = {}
class HeapNode:
def __init__(self, char, freq):
self.char = char
self.freq = freq
self.left = None
self.right = None
def __lt__(self, other):
return self.freq < other.freq
def __eq__(self, other):
if(other == None):
return False
if(not isinstance(other, HeapNode)):
return False
return self.freq == other.freq
def make_frequency_dict(self, text):
frequency = {}
for character in text:
if not character in frequency:
frequency[character] = 0
frequency[character] += 1
return frequency
def make_heap(self, frequency):
for key in frequency:
node = self.HeapNode(key, frequency[key])
heapq.heappush(self.heap, node)
def merge_nodes(self):
while(len(self.heap)>1):
node1 = heapq.heappop(self.heap)
node2 = heapq.heappop(self.heap)
merged = self.HeapNode(None, node1.freq + node2.freq)
merged.left = node1
merged.right = node2
heapq.heappush(self.heap, merged)
def make_codes_helper(self, root, current_code):
if(root == None):
return
if(root.char != None):
self.codes[root.char] = current_code
self.reverse_codes[current_code] = root.char
return
self.make_codes_helper(root.left, current_code + "0")
self.make_codes_helper(root.right, current_code + "1")
def make_codes(self):
root = heapq.heappop(self.heap)
current_code = ""
self.make_codes_helper(root, current_code)
def get_encoded_text(self, text):
encoded_text = ""
for character in text:
encoded_text += self.codes[character]
return encoded_text
def pad_encoded_text(self, encoded_text):
extra_padding = 8 - len(encoded_text) % 8
for i in range(extra_padding):
encoded_text += "0"
padded_info = "{0:08b}".format(extra_padding)
encoded_text = padded_info + encoded_text
return encoded_text
def get_byte_array(self, padded_encoded_text):
if(len(padded_encoded_text) % 8 != 0):
print("Encoded text not padded properly")
exit(0)
b = bytearray()
for i in range(0, len(padded_encoded_text), 8):
byte = padded_encoded_text[i:i+8]
b.append(int(byte, 2))
return b
def compress(self):
filename, file_extension = os.path.splitext(self.path)
output_path = filename + ".bin"
with open(self.path, 'r+') as file, open(output_path, 'wb') as output:
text = file.read()
text = text.rstrip()
frequency = self.make_frequency_dict(text)
self.make_heap(frequency)
self.merge_nodes()
self.make_codes()
encoded_text = self.get_encoded_text(text)
padded_encoded_text = self.pad_encoded_text(encoded_text)
b = self.get_byte_array(padded_encoded_text)
output.write(bytes(b))
print("Compressed")
return output_path
def remove_padding(self, padded_encoded_text):
padded_info = padded_encoded_text[:8]
extra_padding = int(padded_info, 2)
padded_encoded_text = padded_encoded_text[8:]
encoded_text = padded_encoded_text[:-1*extra_padding]
return encoded_text
def decode_text(self, encoded_text):
current_code = ""
decoded_text = ""
for bit in encoded_text:
current_code += bit
if(current_code in self.reverse_codes):
character = self.reverse_codes[current_code]
decoded_text += character
current_code = ""
return decoded_text
def decompress(self, input_path):
filename, file_extension = os.path.splitext(self.path)
output_path = filename + "_decompressed.txt"
with open(input_path, 'rb') as file, open(output_path, 'w') as output:
bit_string = ""
byte = file.read(1)
while(len(byte) > 0):
byte = ord(byte)
bits = bin(byte)[2:].rjust(8, '0')
bit_string += bits
byte = file.read(1)
encoded_text = self.remove_padding(bit_string)
decompressed_text = self.decode_text(encoded_text)
output.write(decompressed_text)
print("Decompressed")
return output_path
```
使用方法:
```python
h = HuffmanCoding(path_to_file)
output_path = h.compress()
decompressed_path = h.decompress(output_path)
```
其中 `path_to_file` 为待压缩的文本文件路径。压缩后的二进制文件路径为 `output_path`,解压缩后的文本文件路径为 `decompressed_path`。
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