K最短路径Python不起作用

本文介绍了K最短路径Python不起作用的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着小编来一起学习吧！ 问题描述

我的K最短路径算法存在某些问题。代码为：

I'm having certain Issues with my K Shortest Path algorithm. The code is given as:

def K_shortest_Paths(graph,S,T,K=4): '''Initialize Variables Accordingly''' B = {} P = set() count = {} for U in graph.keys(): count[U] = 0 B[S] = 0 '''Algorithm Starts''' while(len(B)>=1 and count[T]<K): PU = min(B,key=lambda x:B[x]) cost = B[PU] U = PU[len(PU)-1] del B[PU] count[U] += 1 if U==T: P.add(PU) if count[U]<=K: V = graph[U].keys() for v in V: if v not in PU: PV = PU+v B[PV] = cost+1 return P

这等效于 en.wikipedia/wiki/K_shortest_path_routing 提供实施的伪代码。该图给出为：现在，如果我有开始节点S ＜10，而终止节点T ＜10，则它工作良好，但是当S和T> 10时，它返回一个空集，而应该返回路径。请注意，我无法使用Networkx库。我只需要在Python中使用基本库

This is equivalent to en.wikipedia/wiki/K_shortest_path_routing which provides the Pseudo Code for Implementation. The Graph is given as: Now, It works well if I have Starting Node S<10, and Terminating Node T<10, but with S and T>10, it returns an empty set, Whereas it should return the Path. Please Note that I can't Use Networkx libraries. I only have to Use basic libraries in Python

此外，生成图形的代码是这样的：

Furthermore, the Code to Generate Graph is this:

def create_dictionary(graph): D = {} for item in graph.items(): temp = {} connected = list(item[1]) key = item[0] for V in connected: temp[str(V)] = 1 D[str(key)] = temp return D def gen_p_graph(nodes,prob): if prob>1: er='error' return er graph_matrix=np.zeros([nodes,nodes]) num_of_connections=int(((nodes * (nodes-1)) * prob )/2) num_list_row=list(range(nodes-1)) while(np.sum(np.triu(graph_matrix))!=num_of_connections): row_num=random.choice(num_list_row) num_list_col=(list(range(row_num+1,nodes))) col_num=random.choice(num_list_col) if graph_matrix[row_num,col_num]==0: graph_matrix[row_num,col_num]=1 graph_matrix[col_num,row_num]=1 #create dictionary df=pd.DataFrame(np.argwhere(graph_matrix==1)) arr=np.unique(df.iloc[:,0]) dct={} for i in range(graph_matrix.shape[0]): dct[str(i)]=set() for val in arr: dct[str(val)].update(df.loc[df.iloc[:,0]==val].iloc[:,1].values) return pd.DataFrame(graph_matrix),dct

我这样运行：

graph= create_dictionary(gen_p_graph(100,0.8)[1]) K_shortest_Paths(graph,'11','10')

返回一个空集合，而

推荐答案

我想您正在尝试实现的目标。试试这个。

What I presume you are trying to achieve. Try this.

def k_shortest_paths(graph, src_node, dest_node, k=4): result = [] pathes = [[src_node]] while len(pathes) > 0 and len(result) < k: path = pathes.pop() last_node = path[-1] if last_node == dest_node: result.append(path) else: for child_node in graph[last_node].keys(): if child_node not in path: pathes.append(path + [child_node]) return result