我的 K 最短路径算法存在某些问题。代码如下:
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
这相当于https://en.wikipedia.org/wiki/K_shortest_path_routing https://en.wikipedia.org/wiki/K_shortest_path_routing它提供了实现的伪代码。该图给出如下:
现在,如果我的起始节点 S10,它会返回一个空集,而它应该返回路径。请注意,我无法使用 Networkx 库。我只需要使用Python中的基本库
此外,生成图的代码是这样的:
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
我这样运行它:
graph= create_dictionary(gen_p_graph(100,0.8)[1])
K_shortest_Paths(graph,'11','10')
返回一个空集,而它应该返回路径。