算法思想是通过Dijkstra算法结合自身想法实现的。大致思路是：从起始点开始，搜索周围的路径，记录每个点到起始点的权值存到已标记权值节点字典A，将起始点存入已遍历列表B，然后再遍历已标记权值节点字典A，搜索节点周围的路径，如果周围节点存在于表B，比较累加权值，新权值小于已有权值则更新权值和来源节点，否则什么都不做；如果不存在与表B，则添加节点和权值和来源节点到表A，直到搜索到终点则结束。
# -*-coding:utf-8 -*-
classDijkstraExtendPath():
def__init__(self, node_map):
self.node_map=node_map
self.node_length=len(node_map)
self.used_node_list=[]
self.collected_node_dict={}
def__call__(self, from_node, to_node):
self.from_node=from_node
self.to_node=to_node
self._init_dijkstra()
returnself._format_path()
def_init_dijkstra(self):
self.used_node_list.append(self.from_node)
self.collected_node_dict[self.from_node]=[0,-1]
forindex1, node1inenumerate(self.node_map[self.from_node]):
ifnode1:
self.collected_node_dict[index1]=[node1,self.from_node]
self._foreach_dijkstra()
def_foreach_dijkstra(self):
iflen(self.used_node_list)==self.node_length-1:
return
forkey, valinself.collected_node_dict.items():# 遍历已有权值节点
ifkeynotinself.used_node_listandkey !=to_node:
self.used_node_list.append(key)
else:
continue
forindex1, node1inenumerate(self.node_map[key]):# 对节点进行遍历
# 如果节点在权值节点中并且权值大于新权值
ifnode1andindex1inself.collected_node_dictandself.collected_node_dict[index1][0] > node1+val[0]:
self.collected_node_dict[index1][0]=node1+val[0]# 更新权值
self.collected_node_dict[index1][1]=key
elifnode1andindex1notinself.collected_node_dict:
self.collected_node_dict[index1]=[node1+val[0], key]
self._foreach_dijkstra()
def_format_path(self):
node_list=[]
temp_node=self.to_node
node_list.append((temp_node,self.collected_node_dict[temp_node][0]))
whileself.collected_node_dict[temp_node][1] !=-1:
temp_node=self.collected_node_dict[temp_node][1]
node_list.append((temp_node,self.collected_node_dict[temp_node][0]))
node_list.reverse()
returnnode_list
defset_node_map(node_map, node, node_list):
forx, y, valinnode_list:
node_map[node.index(x)][node.index(y)]=node_map[node.index(y)][node.index(x)]=val
if__name__=="__main__":
node=['A','B','C','D','E','F','G']
node_list=[('A','F',9), ('A','B',10), ('A','G',15), ('B','F',2),
('G','F',3), ('G','E',12), ('G','C',10), ('C','E',1),
('E','D',7)]
node_map=[[0forvalinxrange(len(node))]forvalinxrange(len(node))]
set_node_map(node_map, node, node_list)
# A -->; D
from_node=node.index('A')
to_node=node.index('D')
dijkstrapath=DijkstraPath(node_map)
path=dijkstrapath(from_node, to_node)
printpath
# -*- coding: utf-8 -*-
importitertools
importre
importmath
defcombination(lst): #全排序
lists=[]
liter=itertools.permutations(lst)
forltsinlist(liter):
lt=''.join(lts)
lists.append(lt)
returnlists
defcoord(lst): #坐标输入
coordinates=dict()
printu'请输入坐标：（格式为A:7 17）'
p=re.compile(r"\d+")
forcharinlst:
str=raw_input(char+':')
dot=p.findall(str)
coordinates[char]=[dot[0],dot[1]]
printcoordinates
returncoordinates
defrepeat(lst): #删除重复组合
forilistinlst:
forkinxrange(len(ilist)):
st=(ilist[k:],ilist[:k])
strs=''.join(st)
forjlistinlst:
if(cmp(strs,jlist)==0):
lst.remove(jlist)
forkinxrange(len(ilist)):
st=(ilist[k:],ilist[:k])
strs=''.join(st)
forjlistinlst:
if(cmp(strs[::-1],jlist)==0):
lst.remove(jlist)
lst.append(ilist)
printlst
returnlst
defcount(lst,coordinates):#计算各路径
way=dict()
forstrinlst:
str=str+str[:1]
length=0
foriinrange(len(str)-1):
x=abs(float(coordinates[str[i]][0])-float(coordinates[str[i+1]][0]) )
y=abs(float(coordinates[str[i] ][1])-float(coordinates[str[i+1] ][1]) )
length+=math.sqrt(x**2+y**2)
way[str[:len(str)-1]]=length
returnway
if__name__=="__main__":
printu'请输入图节点：'
rlist=list(raw_input())
coordinates=coord(rlist)
list_directive=combination(rlist)
# print "有方向完全图所有路径为:",list_directive
# for it in list_directive:
# print it
printu'有方向完全图所有路径总数:',len(list_directive),"\n"
#无方向完全图
list_directive=repeat(list_directive)
list_directive=repeat(list_directive)
# print "无方向完全图所有路径为:",list_directive
printu'无方向完全图所有路径为:'
foritinlist_directive:
printit
printu'无方向完全图所有路径总数:',len(list_directive)
ways=count(list_directive,coordinates)
printu'路径排序如下：'
fordstrinsorted(ways.iteritems(), key=lambdad:d[1], reverse=False):
printdstr
raw_input()
