oop.py

@@ -1,70 +1,69 @@
 import copy
 import heapq
 import re
-import sys
-import time
-from math import isinf, inf
+from math import isinf,inf
+import matplotlib.patches
 import networkx as nx
 import matplotlib.pyplot as plt
-from typing import Dict, Generator, List, Optional
+from typing import Dict, Generator, List, Optional, cast
 import random
+import os
 
 
 def main():
     # print("Welcome to Lab1")
     print("功能5中输入@停止功能")
     tu = None
-
     while True:
 
         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":
-            sys.exit()
-        if i == "0":
-            tu = Tu()
+        if i == "q" :
+            exit(0)
+        if i == "0": #shengchengTu
+            tu=Tu()
 
-            file_name = input("请输入文件名称：")
+            file_name=input("请输入文件名称：")
 
             tu.generate_directed_dict(tu.read_text_file(file_name))
             tu.generate_directed_graph()
             continue
-        if tu is None:
+        if tu is None :
             print("未找到有效的图")
 
             continue
 
         if i == "1":
             tu.drawDirectedGraph()
-        elif i == "2":
+        elif i == "2" :
             word1 = input("Enter the word1:")
             word2 = input("Enter the word2:")
 
-            tu.queryBridgeWords(word1, word2)
-        elif i == "3":
+            tu.queryBridgeWords(word1,word2)
+        elif i == "3" :
             text = input("Enter the text:")
             tu.generateNewText(text)
 
-        elif i == "4":
+        elif i== "4" :
             word1 = input("Enter the word1:")
             word2 = input("Enter the word2,just '' is all")
-            tu.calcShortestPath(word1, word2)
+            tu.calcShortestPath(word1,word2)
 
-        elif i == "5":
+        elif i == "5" :
             tu.randomWalk()
 
         else:
             print("Invalid input")
 
 
-class Tu:
-    def __init__(self):
-        self.dict = {}
-        self.graph = nx.MultiDiGraph()
 
-    @staticmethod
-    def read_text_file(filename):
+class Tu :
+    def __init__(self):
+        self.dict={}
+        self.graph=nx.MultiDiGraph()
+
+    def read_text_file(self,filename):
         try:
-            with open(filename, 'r', encoding="utf-8") as file:
+            with open(filename, 'r') as file:
                 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
                 text = re.sub(r'[^a-zA-Z\n]+', ' ', text)
@@ -76,8 +75,8 @@ class Tu:
             print("File not found.")
             return []
 
-    def generate_directed_dict(self, word_sequence):
-        graph = self.dict
+    def generate_directed_dict(self,word_sequence):
+        graph = self.dict #chunfuzhi,yiqigai
         for i in range(len(word_sequence) - 1):
             current_word = word_sequence[i]
             next_word = word_sequence[i + 1]
@@ -96,7 +95,7 @@ class Tu:
         return graph
 
     def generate_directed_graph(self):
-        G = self.graph  # wufuzhi,yiqigai
+        G = self.graph #wufuzhi,yiqigai
         graph = self.dict
         # 添加节点和边
         for node, neighbors in graph.items():
@@ -108,12 +107,11 @@ class Tu:
         return G
 
     def draw_directed_graph(self):
-        G = self.graph
+        G=self.graph
         pos = nx.spring_layout(G)
-        plt.rcParams['figure.figsize'] = (12.8, 7.2)
-        nx.draw_networkx(G, pos, with_labels=True, node_size=1000,
-                         node_color="skyblue", edge_color="black", font_size=10,
-                         font_weight="bold", arrows=True, connectionstyle='arc3,rad=0.2')
+
+        nx.draw_networkx(G, pos, with_labels=True, node_size=1000, node_color="skyblue",edge_color="black", font_size=10, font_weight="bold",
+                arrows=True, connectionstyle='arc3,rad=0.2')
         edge_labels = nx.get_edge_attributes(G, 'weight')
         # 调整箭头位置
         for edge, weight in edge_labels.items():
@@ -121,11 +119,9 @@ class Tu:
                 dx = pos[edge[0]][0] - pos[edge[1]][0]
                 dy = pos[edge[0]][1] - pos[edge[1]][1]
                 plt.annotate(weight, (
-                    (pos[edge[0]][0] + pos[edge[1]][0]) / 2 + dy * 0.1,
-                    (pos[edge[0]][1] + pos[edge[1]][1]) / 2 - dx * 0.1))
-            else:  # 反向边不存在
-                plt.annotate(weight, ((pos[edge[0]][0] + pos[edge[1]][0]) / 2,
-                                      (pos[edge[0]][1] + pos[edge[1]][1]) / 2))
+                (pos[edge[0]][0] + pos[edge[1]][0]) / 2 + dy * 0.1, (pos[edge[0]][1] + pos[edge[1]][1]) / 2 - dx * 0.1))
+            else: # 反向边不存在
+                plt.annotate(weight, ((pos[edge[0]][0] + pos[edge[1]][0]) / 2, (pos[edge[0]][1] + pos[edge[1]][1]) / 2))
         plt.show()
 
     def drawDirectedGraph(self):
@@ -138,15 +134,27 @@ class Tu:
             print("No", word1, "or", word2, "in the graph!")
             return []
 
-        bridge_words = [
-            word for word in graph[word1]
-            if word2 in graph.get(word, {})
-        ]
+        bridge_words = []
+        bridge_words_origin = []
+        for bridge_word in graph:
+            if word1 == bridge_word:
+                bridge_words = list(graph[bridge_word].keys())
+                bridge_words_origin = copy.deepcopy(bridge_words)
+
+        for wordi in bridge_words_origin:
+
+
+            if graph.get(wordi) != None:
+
+                if word2 not in graph[wordi].keys():
+                    bridge_words.remove(wordi)
+
+            else:
+                bridge_words.remove(wordi)
 
         return bridge_words
 
-    @staticmethod
-    def print_bridge_words(bridge_words, word1, word2):
+    def print_bridge_words(self,bridge_words,word1,word2):
 
         if not bridge_words:
             print("No bridge words from", word1, "to", word2, "!")
@@ -157,15 +165,11 @@ class Tu:
 
             return bridge_words
 
-    def queryBridgeWords(self, word1, word2):
+    def queryBridgeWords(self,word1, word2):
         word1 = self.input_check(word1)
         word2 = self.input_check(word2)
         bridge_words = self.find_bridge_words(word1, word2)
-        if bridge_words:
-            self.print_bridge_words(bridge_words, word1, word2)
-            return bridge_words
-        else:
-            return bridge_words
+        self.print_bridge_words(bridge_words,word1,word2)
 
     def insert_bridge_words(self, text):
 
@@ -179,7 +183,7 @@ class Tu:
             word2 = words[i + 1].lower()
 
             new_text.append(words[i])
-            bridge_words = self.find_bridge_words(word1, word2)
+            bridge_words = self.find_bridge_words( word1, word2)
 
             if len(bridge_words) > 0:
                 random_bridge_word = random.choice(bridge_words)
@@ -189,58 +193,41 @@ class Tu:
 
         return ' '.join(new_text)
 
-    def generateNewText(self, text):
+    def generateNewText(self,text):
 
-        (text_re, text_ren) = re.subn(r'[^a-zA-Z\n]+', ' ', text)
-        if text_ren > 0:
+        (text_re,text_ren)=re.subn(r'[^a-zA-Z\n]+', ' ', text)
+        if text_ren>0 :
             print("There are illegal signs in your input")
         if not text_re.islower():
             print("There are upper characters in your input")
         print(self.insert_bridge_words(text_re))
 
-    def find_shortest_path_old(self, word1, word2):
+    def find_shortest_path(self,word1, word2):
 
-        graph = self.graph
+        graph=self.graph
         try:
-            shortest_path_generator = (
-                nx.all_shortest_paths(graph, source=word1, target=word2, weight='weight'))
-            shortest_length = (
-                nx.shortest_path_length(graph, source=word1, target=word2, weight='weight'))
+            shortest_path_generator = nx.all_shortest_paths(graph, source=word1, target=word2, weight='weight')
+            shortest_length = nx.shortest_path_length(graph, source=word1, target=word2, weight='weight')
+            return shortest_path_generator, shortest_length
+        except nx.NetworkXNoPath:
+            return None, None
+    def find_shortest_path_re(self,word1, word2):
+        graph=self.graph
+        try:
+            shortest_path_generator = self.all_simple_paths_graph(word1, word2)
+            shortest_length=self.calc_shortest_path_len(word1,word2)
             return shortest_path_generator, shortest_length
         except nx.NetworkXNoPath:
             return None, None
 
-    def find_shortest_path(self, word1, word2):
-
-        try:
-
-            (shortest_path_list, shortest_length) = self.calc_shortest_path_len(word1, word2)
-            return shortest_path_list, shortest_length
-        except nx.NetworkXNoPath:
-            return None, None
-
-    def find_shortest_path_ex(self, word1, word2):
-
-        try:
-            shortest_path_generator = self.all_simple_paths_graph(word1, word2)
-            shortest_length = self.calc_shortest_path_len(word1, word2)
-
-            shortest_path_list = []
-
-            for shortest_path in shortest_path_generator:
-
-                if shortest_path.__len__() == shortest_length:
-                    shortest_path_list.append(shortest_path)
-            return shortest_path_list, shortest_length
-        except nx.NetworkXNoPath:
-            return None, None
 
     def draw_shortest_path(self, shortest_path_list):
-        graph = self.graph
+        graph=self.graph
         plt.figure(figsize=(10, 6))
 
         # !!! HUATU ROLL YANSE
 
+
         pos = nx.spring_layout(graph)
         nx.draw_networkx_nodes(graph, pos, node_size=1000, node_color="skyblue")
         nx.draw_networkx_labels(graph, pos, font_size=10, font_weight="bold")
@@ -253,42 +240,42 @@ class Tu:
 
             for edge in graph.edges():
 
-                # print(shortest_path)
+                #print(shortest_path)
 
-                if (edge in zip(shortest_path[:-1], shortest_path[1:]) or
-                        edge in zip(shortest_path[1:], shortest_path[:-1])):
+                if edge in zip(shortest_path[:-1], shortest_path[1:]) or edge in zip(shortest_path[1:], shortest_path[:-1]):
 
-                    nx.draw_networkx_edges(graph, pos, edgelist=[edge], width=2.0, edge_color=num,
-                                           arrows=True, arrowstyle="->", arrowsize=30,
-                                           connectionstyle='arc3,rad=0.2')
+
+
+
+                    nx.draw_networkx_edges(graph, pos, edgelist=[edge], width=2.0, edge_color=num, arrows=True,arrowstyle="->",arrowsize=30
+                                        ,connectionstyle='arc3,rad=0.2')
                 else:
-                    nx.draw_networkx_edges(graph, pos, edgelist=[edge], width=1.0,
-                                           edge_color="black",
-                                           arrows=True, arrowstyle="->", arrowsize=30,
-                                           connectionstyle='arc3,rad=0.2')
+                    nx.draw_networkx_edges(graph, pos, edgelist=[edge], width=1.0, edge_color="black", arrows=True,arrowstyle="->",arrowsize=30
+                                       ,connectionstyle='arc3,rad=0.2')
         plt.show()
-        time.sleep(1)
 
-    def calcShortestPath(self, word1, word2):
+
+    def calcShortestPath(self,word1, word2):
         if word2 == "":
             word1 = self.input_check(word1)
-            for wordtmp in self.dict:
-                if wordtmp == word1:
+            for wordtmp in self.dict :
+                if wordtmp == word1 :
                     continue
                 else:
-                    self.calc_shortest_path(word1, wordtmp)
+                    self.calc_shortest_path(word1,wordtmp)
 
             pass
         else:
             word1 = self.input_check(word1)
             word2 = self.input_check(word2)
-            self.calc_shortest_path(word1, word2)
+            self.calc_shortest_path(word1,word2)
             pass
 
-    def calc_shortest_path_old(self, word1, word2):
 
-        shortest_path_generator, shortest_length = self.find_shortest_path_old(word1, word2)
-        shortest_path_list = []
+    def calc_shortest_path(self,word1, word2):
+
+        shortest_path_generator, shortest_length = self.find_shortest_path_re(word1, word2)
+        shortest_path_list=[]
 
         for shortest_path in shortest_path_generator:
 
@@ -296,22 +283,7 @@ class Tu:
                 print("Shortest path:", '→'.join(shortest_path))
                 print("Length of shortest path:", shortest_length)
                 shortest_path_list.append(shortest_path)
-        if shortest_path_list.__len__() > 0:
-            self.draw_shortest_path(shortest_path_list)
-        else:
-            print("No path exists between", word1, "and", word2)
-
-    def calc_shortest_path(self, word1, word2):
-
-        shortest_path_list, shortest_length = self.find_shortest_path_ex(word1, word2)
-
-        for shortest_path in shortest_path_list:
-
-            if shortest_path:
-                print("Shortest path:", '→'.join(shortest_path))
-                print("Length of shortest path:", shortest_length)
-
-        if shortest_path_list.__len__() > 0:
+        if shortest_path_list.__len__()>0:
             self.draw_shortest_path(shortest_path_list)
         else:
             print("No path exists between", word1, "and", word2)
@@ -320,9 +292,10 @@ class Tu:
 
         # 用户输入文件名
         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()))
         visited_nodes = set()
         visited_edges = []
@@ -333,10 +306,10 @@ class Tu:
                 visited_nodes.add(current_node)
                 file.write(current_node + '\n')
                 print(current_node)
-                if input() == "@":
+                if input()=="@":
                     file.close()
                     break
-                if graph.get(current_node) is not None:
+                if graph.get(current_node) != None:
                     pass
                 else:
                     break
@@ -356,21 +329,23 @@ class Tu:
     def randomWalk(self):
         self.random_traversal()
 
-    @staticmethod
-    def input_check(input_word):
-        (input_word_re, input_word_ren) = re.subn(r'[^a-zA-Z\n]', ' ', input_word)
 
-        if input_word_ren > 0:
-            print("There are illegal signs in your input,the amount is " + str(input_word_ren))
+    def input_check(self, input_word):
+        (input_word_re,input_word_ren)=re.subn(r'[^a-zA-Z\n]', ' ', input_word)
+
+
+        if input_word_ren>0 :
+            print("There are illegal signs in your input,the amount is "+str(input_word_ren))
 
         if not input_word_re.islower():
             print("There are upper characters in your input")
-        tmp = input_word_re.lower().split()
-        if len(tmp) > 1:
+        tmp=input_word_re.lower().split()
+        if len(tmp)>1 :
             print("There are more than one word in your input")
 
         return tmp[0]
 
+
     def all_simple_paths_graph(self, source: str, targets: str) -> Generator[List[str], None, None]:
         G = self.graph
         cutoff = len(G) - 1  # 设置路径的最大深度，防止无限循环。
@@ -399,15 +374,13 @@ class Tu:
                 stack.pop()
                 visited.popitem()
 
-    def calc_shortest_path_len(self, word1: str, word2: str) -> int:
+    def calc_shortest_path_len(self, word1: str, word2: str) -> str:
 
         if word1 not in self.graph.nodes or word2 not in self.graph.nodes:
-            return 0
+            return ""
 
-        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
-        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 = {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
+        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
         priority_queue = [(0, word1)]  # 优先级队列，用于按照从小到大获取节点
 
@@ -439,9 +412,9 @@ class Tu:
             path.insert(0, current_node)
 
         if isinf(distances[word2]):  # 目标节点不可达
-            return 0
+            return ""
         return path.__len__()
-        # return (' '.join(path),path.__len__())
+        return ' '.join(path)
 
 
 if __name__ == '__main__':

test.py

@@ -1,70 +0,0 @@
-import unittest
-
-from oop import Tu
-class TextProcessor(Tu):
-    def __init__(self):
-        super().__init__()
-
-
-
-class TestQueryBridgeWords(unittest.TestCase):
-    def setUp(self):
-        # Initialize a graph for testing
-        self.graph = {
-            'a': {'b': 1, 'c': 2},
-            'b': {'c': 1, 'd': 2},
-            'c': {'d': 1},
-            'x': {},
-            'z': {}
-        }
-        self.processor = TextProcessor()
-        self.processor.generate_directed_dict(self.processor.read_text_file("1.txt"))
-        self.processor.generate_directed_graph()
-
-    def test_valid_bridge_words_exist(self):
-        # Valid equivalence class: bridge words exist
-        result = self.processor.queryBridgeWords('the', 'floor')
-        self.assertIn('forest', result)
-
-    def test_valid_bridge_words_not_exist(self):
-        # Valid equivalence class: no bridge words
-        result = self.processor.queryBridgeWords('on', 'the')
-        self.assertEqual(result, [])
-
-    def test_invalid_word1_not_in_graph(self):
-        # Invalid equivalence class: word1 not in graph
-        result = self.processor.queryBridgeWords('an', 'a')
-        self.assertEqual(result, [])
-
-    def test_invalid_word2_not_in_graph(self):
-        # Invalid equivalence class: word2 not in graph
-        result = self.processor.queryBridgeWords('a', 'an')
-        self.assertEqual(result, [])
-
-    def test_invalid_both_words_not_in_graph(self):
-        # Invalid equivalence class: both words not in graph
-        result = self.processor.queryBridgeWords('an', 'sought')
-        self.assertEqual(result, [])
-
-    def test_edge_case_min_word(self):
-        # Edge case: minimum word
-        result = self.processor.queryBridgeWords('a', 'b')
-        self.assertEqual(result, [])
-
-    def test_edge_case_max_word(self):
-        # Edge case: maximum word
-        result = self.processor.queryBridgeWords('x', 'z')
-        self.assertEqual(result, [])
-
-    def test_edge_case_no_bridge_words(self):
-        # Edge case: no bridge words
-        result = self.processor.queryBridgeWords('new', 'worlds')
-        self.assertEqual(result, [])
-
-    def test_edge_case_single_bridge_word(self):
-        # Edge case: single bridge word
-        result = self.processor.queryBridgeWords('the', 'floor')
-        self.assertIn('forest', result)
-
-if __name__ == '__main__':
-    unittest.main()