commit lab1-stylefixed
This commit is contained in:
qasw-987
parent
67c2869323
commit
6c411c416b
171
oop.py
171
oop.py
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@ -4,13 +4,10 @@ import re
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import sys
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import time
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from math import isinf, inf
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import matplotlib.patches
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import networkx as nx
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import matplotlib.pyplot as plt
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from typing import Dict, Generator, List, Optional, cast, Tuple
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from typing import Dict, Generator, List, Optional
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import random
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import os
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def main():
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@ -21,53 +18,53 @@ def main():
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while True:
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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）：")
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if i == "q" :
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if i == "q":
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sys.exit()
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if i == "0": #shengchengTu
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tu=Tu()
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if i == "0":
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tu = Tu()
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file_name=input("请输入文件名称：")
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file_name = input("请输入文件名称：")
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tu.generate_directed_dict(tu.read_text_file(file_name))
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tu.generate_directed_graph()
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continue
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if tu is None :
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if tu is None:
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print("未找到有效的图")
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continue
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if i == "1":
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tu.drawDirectedGraph()
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elif i == "2" :
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elif i == "2":
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word1 = input("Enter the word1:")
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word2 = input("Enter the word2:")
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tu.queryBridgeWords(word1,word2)
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elif i == "3" :
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tu.queryBridgeWords(word1, word2)
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elif i == "3":
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text = input("Enter the text:")
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tu.generateNewText(text)
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elif i== "4" :
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elif i == "4":
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word1 = input("Enter the word1:")
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word2 = input("Enter the word2,just '' is all")
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tu.calcShortestPath(word1,word2)
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tu.calcShortestPath(word1, word2)
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elif i == "5" :
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elif i == "5":
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tu.randomWalk()
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else:
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print("Invalid input")
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class Tu :
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class Tu:
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def __init__(self):
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self.dict={}
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self.graph=nx.MultiDiGraph()
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self.dict = {}
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self.graph = nx.MultiDiGraph()
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def read_text_file(self,filename):
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@staticmethod
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def read_text_file(filename):
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try:
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with open(filename, 'r',"UTF-8") as file:
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with open(filename, 'r', encoding="utf-8") as file:
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text = file.read()
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# 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
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text = re.sub(r'[^a-zA-Z\n]+', ' ', text)
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@ -79,8 +76,8 @@ class Tu :
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print("File not found.")
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return []
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def generate_directed_dict(self,word_sequence):
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graph = self.dict #chunfuzhi,yiqigai
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def generate_directed_dict(self, word_sequence):
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graph = self.dict
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for i in range(len(word_sequence) - 1):
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current_word = word_sequence[i]
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next_word = word_sequence[i + 1]
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@ -99,7 +96,7 @@ class Tu :
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return graph
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def generate_directed_graph(self):
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G = self.graph #wufuzhi,yiqigai
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G = self.graph # wufuzhi,yiqigai
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graph = self.dict
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# 添加节点和边
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for node, neighbors in graph.items():
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@ -111,12 +108,12 @@ class Tu :
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return G
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def draw_directed_graph(self):
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G=self.graph
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G = self.graph
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pos = nx.spring_layout(G)
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plt.rcParams['figure.figsize'] = (12.8, 7.2)
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nx.draw_networkx(G, pos, with_labels=True, node_size=1000,
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node_color="skyblue",edge_color="black", font_size=10,
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font_weight="bold",arrows=True, connectionstyle='arc3,rad=0.2')
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node_color="skyblue", edge_color="black", font_size=10,
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font_weight="bold", arrows=True, connectionstyle='arc3,rad=0.2')
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edge_labels = nx.get_edge_attributes(G, 'weight')
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# 调整箭头位置
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for edge, weight in edge_labels.items():
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@ -124,9 +121,9 @@ class Tu :
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dx = pos[edge[0]][0] - pos[edge[1]][0]
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dy = pos[edge[0]][1] - pos[edge[1]][1]
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plt.annotate(weight, (
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(pos[edge[0]][0] + pos[edge[1]][0]) / 2 + dy * 0.1,
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(pos[edge[0]][1] + pos[edge[1]][1]) / 2 - dx * 0.1))
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else: # 反向边不存在
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(pos[edge[0]][0] + pos[edge[1]][0]) / 2 + dy * 0.1,
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(pos[edge[0]][1] + pos[edge[1]][1]) / 2 - dx * 0.1))
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else: # 反向边不存在
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plt.annotate(weight, ((pos[edge[0]][0] + pos[edge[1]][0]) / 2,
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(pos[edge[0]][1] + pos[edge[1]][1]) / 2))
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plt.show()
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@ -148,7 +145,8 @@ class Tu :
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return bridge_words
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def print_bridge_words(self,bridge_words,word1,word2):
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@staticmethod
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def print_bridge_words(bridge_words, word1, word2):
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if not bridge_words:
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print("No bridge words from", word1, "to", word2, "!")
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@ -159,11 +157,11 @@ class Tu :
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return bridge_words
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def queryBridgeWords(self,word1, word2):
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def queryBridgeWords(self, word1, word2):
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word1 = self.input_check(word1)
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word2 = self.input_check(word2)
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bridge_words = self.find_bridge_words(word1, word2)
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self.print_bridge_words(bridge_words,word1,word2)
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self.print_bridge_words(bridge_words, word1, word2)
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def insert_bridge_words(self, text):
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@ -177,7 +175,7 @@ class Tu :
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word2 = words[i + 1].lower()
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new_text.append(words[i])
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bridge_words = self.find_bridge_words( word1, word2)
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bridge_words = self.find_bridge_words(word1, word2)
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if len(bridge_words) > 0:
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random_bridge_word = random.choice(bridge_words)
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@ -187,18 +185,18 @@ class Tu :
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return ' '.join(new_text)
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def generateNewText(self,text):
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def generateNewText(self, text):
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(text_re,text_ren)=re.subn(r'[^a-zA-Z\n]+', ' ', text)
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if text_ren>0 :
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(text_re, text_ren) = re.subn(r'[^a-zA-Z\n]+', ' ', text)
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if text_ren > 0:
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print("There are illegal signs in your input")
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if not text_re.islower():
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print("There are upper characters in your input")
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print(self.insert_bridge_words(text_re))
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def find_shortest_path_old(self,word1, word2):
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def find_shortest_path_old(self, word1, word2):
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graph=self.graph
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graph = self.graph
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try:
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shortest_path_generator = (
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nx.all_shortest_paths(graph, source=word1, target=word2, weight='weight'))
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@ -207,39 +205,38 @@ class Tu :
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return shortest_path_generator, shortest_length
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except nx.NetworkXNoPath:
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return None, None
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def find_shortest_path(self,word1, word2):
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def find_shortest_path(self, word1, word2):
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try:
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(shortest_path_list,shortest_length)=self.calc_shortest_path_len(word1,word2)
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(shortest_path_list, shortest_length) = self.calc_shortest_path_len(word1, word2)
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return shortest_path_list, shortest_length
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except nx.NetworkXNoPath:
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return None, None
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def find_shortest_path_ex(self,word1, word2):
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def find_shortest_path_ex(self, word1, word2):
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try:
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shortest_path_generator=self.all_simple_paths_graph(word1,word2)
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shortest_length=self.calc_shortest_path_len(word1,word2)
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shortest_path_generator = self.all_simple_paths_graph(word1, word2)
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shortest_length = self.calc_shortest_path_len(word1, word2)
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shortest_path_list = []
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for shortest_path in shortest_path_generator:
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if shortest_path.__len__()==shortest_length:
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if shortest_path.__len__() == shortest_length:
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shortest_path_list.append(shortest_path)
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return(shortest_path_list,shortest_length)
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return shortest_path_list, shortest_length
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except nx.NetworkXNoPath:
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return None, None
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def draw_shortest_path(self, shortest_path_list):
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graph=self.graph
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graph = self.graph
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plt.figure(figsize=(10, 6))
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# !!! HUATU ROLL YANSE
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pos = nx.spring_layout(graph)
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nx.draw_networkx_nodes(graph, pos, node_size=1000, node_color="skyblue")
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nx.draw_networkx_labels(graph, pos, font_size=10, font_weight="bold")
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@ -252,47 +249,42 @@ class Tu :
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for edge in graph.edges():
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#print(shortest_path)
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# print(shortest_path)
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if (edge in zip(shortest_path[:-1], shortest_path[1:]) or
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edge in zip(shortest_path[1:], shortest_path[:-1])):
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nx.draw_networkx_edges(graph, pos, edgelist=[edge], width=2.0, edge_color=num,
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arrows=True,arrowstyle="->",arrowsize=30
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,connectionstyle='arc3,rad=0.2')
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arrows=True, arrowstyle="->", arrowsize=30,
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connectionstyle='arc3,rad=0.2')
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else:
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nx.draw_networkx_edges(graph, pos, edgelist=[edge], width=1.0,
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edge_color="black",
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arrows=True,arrowstyle="->",arrowsize=30
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,connectionstyle='arc3,rad=0.2')
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arrows=True, arrowstyle="->", arrowsize=30,
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connectionstyle='arc3,rad=0.2')
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plt.show()
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time.sleep(1)
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def calcShortestPath(self,word1, word2):
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def calcShortestPath(self, word1, word2):
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if word2 == "":
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word1 = self.input_check(word1)
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for wordtmp in self.dict :
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if wordtmp == word1 :
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for wordtmp in self.dict:
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if wordtmp == word1:
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continue
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else:
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self.calc_shortest_path(word1,wordtmp)
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self.calc_shortest_path(word1, wordtmp)
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pass
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else:
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word1 = self.input_check(word1)
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word2 = self.input_check(word2)
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self.calc_shortest_path(word1,word2)
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self.calc_shortest_path(word1, word2)
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pass
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def calc_shortest_path_old(self,word1, word2):
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def calc_shortest_path_old(self, word1, word2):
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shortest_path_generator, shortest_length = self.find_shortest_path_old(word1, word2)
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shortest_path_list=[]
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shortest_path_list = []
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for shortest_path in shortest_path_generator:
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@ -300,25 +292,22 @@ class Tu :
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print("Shortest path:", '→'.join(shortest_path))
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print("Length of shortest path:", shortest_length)
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shortest_path_list.append(shortest_path)
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if shortest_path_list.__len__()>0:
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if shortest_path_list.__len__() > 0:
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self.draw_shortest_path(shortest_path_list)
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else:
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print("No path exists between", word1, "and", word2)
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def calc_shortest_path(self,word1, word2):
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def calc_shortest_path(self, word1, word2):
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shortest_path_list, shortest_length = self.find_shortest_path_ex(word1, word2)
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for shortest_path in shortest_path_list:
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if shortest_path:
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print("Shortest path:", '→'.join(shortest_path))
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print("Length of shortest path:", shortest_length)
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if shortest_path_list.__len__()>0:
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if shortest_path_list.__len__() > 0:
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self.draw_shortest_path(shortest_path_list)
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else:
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print("No path exists between", word1, "and", word2)
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@ -327,10 +316,9 @@ class Tu :
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# 用户输入文件名
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filename = input("Enter the filename to save traversal results: ")
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filename+=".txt"
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filename += ".txt"
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graph=copy.deepcopy(self.dict)
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graph = copy.deepcopy(self.dict)
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start_node = random.choice(list(graph.keys()))
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visited_nodes = set()
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visited_edges = []
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@ -341,10 +329,10 @@ class Tu :
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visited_nodes.add(current_node)
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file.write(current_node + '\n')
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print(current_node)
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if input()=="@":
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if input() == "@":
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file.close()
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break
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if graph.get(current_node) != None:
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if graph.get(current_node) is not None:
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pass
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else:
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break
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@ -364,23 +352,21 @@ class Tu :
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def randomWalk(self):
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self.random_traversal()
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@staticmethod
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def input_check(input_word):
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(input_word_re, input_word_ren) = re.subn(r'[^a-zA-Z\n]', ' ', input_word)
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def input_check(self, input_word):
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(input_word_re,input_word_ren)=re.subn(r'[^a-zA-Z\n]', ' ', input_word)
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if input_word_ren>0 :
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print("There are illegal signs in your input,the amount is "+str(input_word_ren))
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if input_word_ren > 0:
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print("There are illegal signs in your input,the amount is " + str(input_word_ren))
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if not input_word_re.islower():
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print("There are upper characters in your input")
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tmp=input_word_re.lower().split()
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if len(tmp)>1 :
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tmp = input_word_re.lower().split()
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if len(tmp) > 1:
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print("There are more than one word in your input")
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return tmp[0]
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def all_simple_paths_graph(self, source: str, targets: str) -> Generator[List[str], None, None]:
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G = self.graph
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cutoff = len(G) - 1 # 设置路径的最大深度，防止无限循环。
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@ -409,14 +395,15 @@ class Tu :
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stack.pop()
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visited.popitem()
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def calc_shortest_path_len(self, word1: str, word2: str) -> str | tuple[str, int]:
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def calc_shortest_path_len(self, word1: str, word2: str) -> int:
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if word1 not in self.graph.nodes or word2 not in self.graph.nodes:
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return ""
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return 0
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distances = {node: inf for node in self.graph.nodes}
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# 存储word1到所有结点的距离，初始化为无穷大
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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
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previous_nodes: Dict[str, Optional[str]] = {node: None for node in
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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
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distances[word1] = 0 # 距离初始化为0
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priority_queue = [(0, word1)] # 优先级队列，用于按照从小到大获取节点
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@ -448,9 +435,9 @@ class Tu :
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path.insert(0, current_node)
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if isinf(distances[word2]): # 目标节点不可达
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return ("",0)
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return 0
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return path.__len__()
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#return (' '.join(path),path.__len__())
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# return (' '.join(path),path.__len__())
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if __name__ == '__main__':
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