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lab1-2021112105
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commit lab1-stylefixed

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qasw-987 2024-06-03 16:28:31 +08:00
parent 67c2869323
commit 6c411c416b
1 changed files with 79 additions and 92 deletions
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59
oop.py
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@ -4,13 +4,10 @@ import re
import sys import sys
import time import time
from math import isinf, inf from math import isinf, inf
import matplotlib.patches
import networkx as nx import networkx as nx
import matplotlib.pyplot as plt import matplotlib.pyplot as plt
from typing import Dict, Generator, List, Optional, cast, Tuple from typing import Dict, Generator, List, Optional
import random import random
import os
def main(): def main():
@ -23,7 +20,7 @@ def main():
i = input("请输入操作（q:退出, 0:读入文件, 1:展示图形, 2:查找桥接词, 3:生成新文本, 4:计算最短路径, 5:随机游走）：") i = input("请输入操作（q:退出, 0:读入文件, 1:展示图形, 2:查找桥接词, 3:生成新文本, 4:计算最短路径, 5:随机游走）：")
if i == "q": if i == "q":
sys.exit() sys.exit()
if i == "0": #shengchengTu if i == "0":
tu = Tu() tu = Tu()
file_name = input("请输入文件名称：") file_name = input("请输入文件名称：")
@ -59,15 +56,15 @@ def main():
print("Invalid input") print("Invalid input")
class Tu: class Tu:
def __init__(self): def __init__(self):
self.dict = {} self.dict = {}
self.graph = nx.MultiDiGraph() self.graph = nx.MultiDiGraph()
def read_text_file(self,filename): @staticmethod
def read_text_file(filename):
try: try:
with open(filename, 'r',"UTF-8") as file: with open(filename, 'r', encoding="utf-8") as file:
text = file.read() text = file.read()
# 用正则表达式将非字母字符替换为空格，并将换行符也替换为空格 # 用正则表达式将非字母字符替换为空格，并将换行符也替换为空格
text = re.sub(r'[^a-zA-Z\n]+', ' ', text) text = re.sub(r'[^a-zA-Z\n]+', ' ', text)
@ -80,7 +77,7 @@ class Tu :
return [] return []
def generate_directed_dict(self, word_sequence): def generate_directed_dict(self, word_sequence):
graph = self.dict #chunfuzhi,yiqigai graph = self.dict
for i in range(len(word_sequence) - 1): for i in range(len(word_sequence) - 1):
current_word = word_sequence[i] current_word = word_sequence[i]
next_word = word_sequence[i + 1] next_word = word_sequence[i + 1]
@ -148,7 +145,8 @@ class Tu :
return bridge_words return bridge_words
def print_bridge_words(self,bridge_words,word1,word2): @staticmethod
def print_bridge_words(bridge_words, word1, word2):
if not bridge_words: if not bridge_words:
print("No bridge words from", word1, "to", word2, "!") print("No bridge words from", word1, "to", word2, "!")
@ -207,6 +205,7 @@ class Tu :
return shortest_path_generator, shortest_length return shortest_path_generator, shortest_length
except nx.NetworkXNoPath: except nx.NetworkXNoPath:
return None, None return None, None
def find_shortest_path(self, word1, word2): def find_shortest_path(self, word1, word2):
try: try:
@ -215,6 +214,7 @@ class Tu :
return shortest_path_list, shortest_length return shortest_path_list, shortest_length
except nx.NetworkXNoPath: except nx.NetworkXNoPath:
return None, None return None, None
def find_shortest_path_ex(self, word1, word2): def find_shortest_path_ex(self, word1, word2):
try: try:
@ -227,9 +227,7 @@ class Tu :
if shortest_path.__len__() == shortest_length: if shortest_path.__len__() == shortest_length:
shortest_path_list.append(shortest_path) shortest_path_list.append(shortest_path)
return(shortest_path_list,shortest_length) return shortest_path_list, shortest_length
except nx.NetworkXNoPath: except nx.NetworkXNoPath:
return None, None return None, None
@ -239,7 +237,6 @@ class Tu :
# !!! HUATU ROLL YANSE # !!! HUATU ROLL YANSE
pos = nx.spring_layout(graph) pos = nx.spring_layout(graph)
nx.draw_networkx_nodes(graph, pos, node_size=1000, node_color="skyblue") nx.draw_networkx_nodes(graph, pos, node_size=1000, node_color="skyblue")
nx.draw_networkx_labels(graph, pos, font_size=10, font_weight="bold") nx.draw_networkx_labels(graph, pos, font_size=10, font_weight="bold")
@ -257,21 +254,17 @@ class Tu :
if (edge in zip(shortest_path[:-1], shortest_path[1:]) or if (edge in zip(shortest_path[:-1], shortest_path[1:]) or
edge in zip(shortest_path[1:], shortest_path[:-1])): edge in zip(shortest_path[1:], shortest_path[:-1])):
nx.draw_networkx_edges(graph, pos, edgelist=[edge], width=2.0, edge_color=num, nx.draw_networkx_edges(graph, pos, edgelist=[edge], width=2.0, edge_color=num,
arrows=True,arrowstyle="->",arrowsize=30 arrows=True, arrowstyle="->", arrowsize=30,
,connectionstyle='arc3,rad=0.2') connectionstyle='arc3,rad=0.2')
else: else:
nx.draw_networkx_edges(graph, pos, edgelist=[edge], width=1.0, nx.draw_networkx_edges(graph, pos, edgelist=[edge], width=1.0,
edge_color="black", edge_color="black",
arrows=True,arrowstyle="->",arrowsize=30 arrows=True, arrowstyle="->", arrowsize=30,
,connectionstyle='arc3,rad=0.2') connectionstyle='arc3,rad=0.2')
plt.show() plt.show()
time.sleep(1) time.sleep(1)
def calcShortestPath(self, word1, word2): def calcShortestPath(self, word1, word2):
if word2 == "": if word2 == "":
word1 = self.input_check(word1) word1 = self.input_check(word1)
@ -288,7 +281,6 @@ class Tu :
self.calc_shortest_path(word1, word2) self.calc_shortest_path(word1, word2)
pass pass
def calc_shortest_path_old(self, word1, word2): def calc_shortest_path_old(self, word1, word2):
shortest_path_generator, shortest_length = self.find_shortest_path_old(word1, word2) shortest_path_generator, shortest_length = self.find_shortest_path_old(word1, word2)
@ -305,13 +297,10 @@ class Tu :
else: else:
print("No path exists between", word1, "and", word2) print("No path exists between", word1, "and", word2)
def calc_shortest_path(self, word1, word2): def calc_shortest_path(self, word1, word2):
shortest_path_list, shortest_length = self.find_shortest_path_ex(word1, word2) shortest_path_list, shortest_length = self.find_shortest_path_ex(word1, word2)
for shortest_path in shortest_path_list: for shortest_path in shortest_path_list:
if shortest_path: if shortest_path:
@ -329,7 +318,6 @@ class Tu :
filename = input("Enter the filename to save traversal results: ") filename = input("Enter the filename to save traversal results: ")
filename += ".txt" filename += ".txt"
graph = copy.deepcopy(self.dict) graph = copy.deepcopy(self.dict)
start_node = random.choice(list(graph.keys())) start_node = random.choice(list(graph.keys()))
visited_nodes = set() visited_nodes = set()
@ -344,7 +332,7 @@ class Tu :
if input() == "@": if input() == "@":
file.close() file.close()
break break
if graph.get(current_node) != None: if graph.get(current_node) is not None:
pass pass
else: else:
break break
@ -364,11 +352,10 @@ class Tu :
def randomWalk(self): def randomWalk(self):
self.random_traversal() self.random_traversal()
@staticmethod
def input_check(self, input_word): def input_check(input_word):
(input_word_re, input_word_ren) = re.subn(r'[^a-zA-Z\n]', ' ', input_word) (input_word_re, input_word_ren) = re.subn(r'[^a-zA-Z\n]', ' ', input_word)
if input_word_ren > 0: if input_word_ren > 0:
print("There are illegal signs in your input,the amount is " + str(input_word_ren)) print("There are illegal signs in your input,the amount is " + str(input_word_ren))
@ -380,7 +367,6 @@ class Tu :
return tmp[0] return tmp[0]
def all_simple_paths_graph(self, source: str, targets: str) -> Generator[List[str], None, None]: def all_simple_paths_graph(self, source: str, targets: str) -> Generator[List[str], None, None]:
G = self.graph G = self.graph
cutoff = len(G) - 1 # 设置路径的最大深度，防止无限循环。 cutoff = len(G) - 1 # 设置路径的最大深度，防止无限循环。
@ -409,14 +395,15 @@ class Tu :
stack.pop() stack.pop()
visited.popitem() visited.popitem()
def calc_shortest_path_len(self, word1: str, word2: str) -> str | tuple[str, int]: def calc_shortest_path_len(self, word1: str, word2: str) -> int:
if word1 not in self.graph.nodes or word2 not in self.graph.nodes: if word1 not in self.graph.nodes or word2 not in self.graph.nodes:
return "" return 0
distances = {node: inf for node in self.graph.nodes} distances = {node: inf for node in self.graph.nodes}
# 存储word1到所有结点的距离，初始化为无穷大 # 存储word1到所有结点的距离，初始化为无穷大
previous_nodes: Dict[str, Optional[str]] = {node: None for node in self.graph.nodes} # 存储每个节点最短路径中的前一个节点，初始化为None previous_nodes: Dict[str, Optional[str]] = {node: None for node in
self.graph.nodes} # 存储每个节点最短路径中的前一个节点，初始化为None
distances[word1] = 0 # 距离初始化为0 distances[word1] = 0 # 距离初始化为0
priority_queue = [(0, word1)] # 优先级队列，用于按照从小到大获取节点 priority_queue = [(0, word1)] # 优先级队列，用于按照从小到大获取节点
@ -448,7 +435,7 @@ class Tu :
path.insert(0, current_node) path.insert(0, current_node)
if isinf(distances[word2]): # 目标节点不可达 if isinf(distances[word2]): # 目标节点不可达
return ("",0) return 0
return path.__len__() return path.__len__()
# return (' '.join(path),path.__len__()) # return (' '.join(path),path.__len__())