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AlexJakinAlexJakin
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更新了联通分量，环的检测，单源路径，二部图的检测（还存在bug）
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‎DFS_Application/BiPartitionDetection.py‎

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"""
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@author: Alex
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@contact: [email protected] or [email protected]
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@file: BiPartitionDetection.py
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@time: 2019/10/22 17:50
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"""
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class BiPartitionDetection:
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def __init__(self, filename):
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self.V = 0 # 顶点数
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self.E = 0 # 边数
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self.adj = None
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self.__isBiPartite = True
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with open(filename) as f:
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line_num = 0 # 第一行是顶点数和边数
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for line in f:
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if line_num == 0:
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v, e = line.strip().split()
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self.V = int(v)
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self.E = int(e)
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self.adj = [[] for i in range(self.V)] # 创建二维数组即邻接表
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else:
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# 读取边 写入邻接表
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v1, v2 = line.strip().split()
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# 转化为整数
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v1 = int(v1)
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v2 = int(v2)
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self.adj[v1].append(v2)
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self.adj[v2].append(v1)
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line_num += 1
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def get_graph_information(self):
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"""
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打印图的邻接表
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:return:
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"""
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print("V={}, E={}".format(self.V, self.E))
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for i, v in enumerate(self.adj):
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print("{} : {}".format(i, v))
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def validateVertex(self, v):
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"""
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验证顶点取值
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:param v:
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:return:
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"""
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if v<0 or v>=self.V:
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raise ValueError("v值超出范围")
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def graphDFS(self):
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visited = [False for i in range(self.V)]
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colors = [-1 for i in range(self.V)]
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def dfs(v, color):
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# 标记v顶点已经遍历过了
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visited[v] = True
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for w in self.adj[v]:
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if visited[w] == False:
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if dfs(w, 1-color) == False:
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return False
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elif colors[w] == colors[v]:
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return False
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# 顾及到有多个联通分量，对每个顶点都做DFS
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for i in range(self.V):
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if visited[i] == False:
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if dfs(i, 0) == False:
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self.__isBiPartite = False
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break
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def isBiPartite(self):
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return self.__isBiPartite
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if __name__ == '__main__':
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BPD = BiPartitionDetection("../g.txt")
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BPD.get_graph_information()
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print(BPD.graphDFS())
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print(BPD.isBiPartite())

‎DFS_Application/CC.py‎

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"""
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@author: Alex
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@contact: [email protected] or [email protected]
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@file: CC.py
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@time: 2019/10/20 19:12
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"""
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class CC:
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def __init__(self, filename):
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self.V = 0 # 顶点数
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self.E = 0 # 边数
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self.adj = None
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self.__cccount = 0 # 联通分量
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self.__visited = None
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with open(filename) as f:
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line_num = 0 # 第一行是顶点数和边数
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for line in f:
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if line_num == 0:
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v, e = line.strip().split()
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self.V = int(v)
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self.E = int(e)
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self.adj = [[] for i in range(self.V)] # 创建二维数组即邻接表
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else:
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# 读取边 写入邻接表
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v1, v2 = line.strip().split()
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# 转化为整数
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v1 = int(v1)
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v2 = int(v2)
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self.adj[v1].append(v2)
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self.adj[v2].append(v1)
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line_num += 1
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def get_graph_information(self):
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"""
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打印图的邻接表
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:return:
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"""
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print("V={}, E={}".format(self.V, self.E))
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for i, v in enumerate(self.adj):
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print("{} : {}".format(i, v))
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def validateVertex(self, v):
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"""
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验证顶点取值
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:param v:
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:return:
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"""
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if v<0 or v>=self.V:
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raise ValueError("v值超出范围")
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def hasEdge(self, v, w):
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"""
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判断两个顶点是否存在
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:param v: 第一个顶点
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:param w: 第二个顶点
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:return: true or false
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"""
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self.validateVertex(v)
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self.validateVertex(w)
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return w in self.adj[v]
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def degree(self, v):
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"""
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求某个顶点的度
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:param v:
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:return:
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"""
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self.validateVertex(v)
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return len(self.adj[v])
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def graphDFS(self):
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visited = [-1 for i in range(self.V)]
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cccount = 0 # 联通分量
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def dfs(v, ccid):
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# 标记v顶点已经遍历过了
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visited[v] = ccid
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# 添加
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for w in self.adj[v]:
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if visited[w] == -1:
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dfs(w, ccid)
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# 此刻对某个顶点的邻点已经遍历结束
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# 顾及到有多个联通分量，对每个顶点都做DFS
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for i in range(self.V):
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if visited[i] == -1:
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dfs(i, cccount)
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cccount += 1
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self.__cccount = cccount
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self.__visited = visited
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def get_cccount(self):
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"""
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获取该图的联通分量大小
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:return:
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"""
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return self.__cccount
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def get_visited(self):
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"""
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获取该图的联通分量列表
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:return:
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"""
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return self.__visited
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def isConnected(self, v, w):
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"""
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查看两个顶点是否在一个联通分量中
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:param v:
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:param w:
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:return:
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"""
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self.validateVertex(v)
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self.validateVertex(w)
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return self.__visited[v] == self.__visited[w]
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def components(self):
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# 为每一个联通分量开辟空间
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res = [[] for i in range(self.__cccount)]
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for v in range(self.V): # 遍历每一个顶点
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# 将相同联通分量的顶点放入同一个数组中, visited[0]=visited[1]=0, 则将0,1顶点放入索引为0的数组中
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res[self.__visited[v]].append(v)
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for i, row in enumerate(res):
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print("联通分量{}：{}".format(i, row))
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if __name__ == '__main__':
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adjl = CC("../g_unconnected.txt")
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adjl.get_graph_information()
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print(adjl.graphDFS())
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print(adjl.get_cccount())
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print(adjl.get_visited())
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print(adjl.isConnected(0, 4))
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adjl.components()

‎DFS_Application/CycleDetection.py‎

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"""
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@author: Alex
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@contact: [email protected] or [email protected]
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@file: CycleDetection.py
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@time: 2019/10/22 15:48
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"""
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# 环检测（邻接矩阵）
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class CycleDetection:
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def __init__(self, filename):
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self.V = 0 # 顶点数
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self.E = 0 # 边数
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self.adj = None
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self.__hasCycle = None
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with open(filename) as f:
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line_num = 0 # 第一行是顶点数和边数
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for line in f:
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if line_num == 0:
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v, e = line.strip().split()
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self.V = int(v)
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self.E = int(e)
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# self.adj = [[0] * self.V] * self.V # 该创建方式不正确 修改任何一个元素都会改变整个列表
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self.adj = [([0] * self.V) for i in range(self.V)] # 创建二维数组即邻接矩阵
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else:
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# 读取边 写入邻接矩阵
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v1, v2 = line.strip().split()
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# 转化为整数
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v1 = int(v1)
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v2 = int(v2)
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self.adj[v1][v2] = 1
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self.adj[v2][v1] = 1
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line_num += 1
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# 初始化图时，进行深度优先搜索
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self.graphDFS()
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def get_graph_information(self):
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"""
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打印图的邻接矩阵
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:return:
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"""
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print("V={}, E={}".format(self.V, self.E))
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print(self.adj)
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def validateVertex(self, v):
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"""
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验证顶点取值
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:param v:
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:return:
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"""
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if v<0 or v>=self.V:
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raise ValueError("v值超出范围")
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def graphDFS(self):
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visited = [False for i in range(self.V)]
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def dfs(v, parent):
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# 标记v顶点已经遍历过了
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visited[v] = True
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for w in self.adj[v]:
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if visited[w] == False:
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dfs(w, v)
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else:
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if w != parent:
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return True
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return False
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for i in range(self.V):
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if visited[i] == False:
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if dfs(i, i):
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self.__hasCycle = True
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break
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def hasCycle(self):
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if self.__hasCycle:
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print("该图存在环")
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else:
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print("该图没有环")
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# 环检测（邻接表）
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class CycleDetection_v2:
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def __init__(self, filename):
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self.V = 0 # 顶点数
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self.E = 0 # 边数
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self.adj = None
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self.__hasCycle = None
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with open(filename) as f:
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line_num = 0 # 第一行是顶点数和边数
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for line in f:
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if line_num == 0:
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v, e = line.strip().split()
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self.V = int(v)
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self.E = int(e)
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self.adj = [[] for i in range(self.V)] # 创建二维数组即邻接表
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else:
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# 读取边 写入邻接表
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v1, v2 = line.strip().split()
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# 转化为整数
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v1 = int(v1)
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v2 = int(v2)
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self.adj[v1].append(v2)
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self.adj[v2].append(v1)
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line_num += 1
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# 初始化图时，进行深度优先搜索
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self.graphDFS()
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def get_graph_information(self):
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"""
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打印图的邻接矩阵
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:return:
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"""
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print("V={}, E={}".format(self.V, self.E))
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for i, v in enumerate(self.adj):
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print("{} : {}".format(i, v))
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def validateVertex(self, v):
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"""
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验证顶点取值
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:param v:
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:return:
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"""
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if v<0 or v>=self.V:
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raise ValueError("v值超出范围")
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def graphDFS(self):
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visited = [False for i in range(self.V)]
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def dfs(v, parent):
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# 标记v顶点已经遍历过了
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visited[v] = True
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for w in self.adj[v]:
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if visited[w] == False:
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# if dfs(w, v):
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# return True
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dfs(w, v)
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print(v, w, parent)
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else:
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if w != parent:
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print(v, w, parent)
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return True
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return False
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# 顾及到有多个联通分量，对每个顶点都做DFS
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for i in range(self.V):
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if visited[i] == False:
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if dfs(i, i):
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self.__hasCycle = True
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break
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def hasCycle(self):
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if self.__hasCycle:
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print("该图存在环")
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else:
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print("该图没有环")
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if __name__ == '__main__':
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CD = CycleDetection("../g_cycle.txt")
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CD.get_graph_information()
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CD.hasCycle()
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print("=======第二种========")
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CD2 = CycleDetection_v2("../g.txt")
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CD2.get_graph_information()
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CD2.hasCycle()

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