python狄克斯特拉 python实现狄克斯特拉算法
果然还是我比较shuai 人气:0数据结构
1、路由信息
dictRoute = {}
dictRoute[nodeId] = {}
dictRoute[nodeId][nebrId] = distance
操作:
①根据nodeId找到该node的路由信息
②根据nebrId找到某一条路由的距离
2、节点信息
dictNode = {}
dictNode[nodeId] = [shortDis, fatherId, bIsCheck]
操作:
①找到nodes中最短距离的节点
②查找节点的shortDis,根据情况更新shortDis、fatherId
③检查过的节点,更新bIsCheck
功能实现
/* 找到最短距离节点的Id,已经检查的不计算在内 */
def FindShortNodeId(dictNode):
return shortNodeId
/* dikstra算法流程 */
1、找到最短距离节点Id,并标记已检查过 (如果节点Id不存在,表示查找完成)
2、得到最短距离节点的距离
3、轮询最短距离节点的邻居节点
4、计算邻居节点的新距离、得到原最短距离,进行比较
5、如果新距离 < 原距离,则更新邻居节点最短距离
概括为两步:步骤1 (1)- 找到当前最短距离节点
步骤2(2~5) - 更新最短距离节点邻居节点信息
代码实现
import os import sys ''' 信息输入: 1、节点数目、路由数目 2、路由信息 3、开始节点、结束节点 ''' nodeNum = 0 # 节点数目 routeNum = 0 # 路由数目 listRoute = [] # 临时存储输入的路由信息 listNodeId = []# 临时存储节点id nodeIdStart = '' nodeIdEnd = '' dictRoute = {} # 解析后的路由信息 dictNode = {} # 节点信息 # 输入节点数目、路由数目 strInput = input() list0 = strInput.split(' ') nodeNum = int(list0[0]) routeNum = int(list0[1]) # 输入路由信息 for index in range(routeNum): strInput = input() listRoute.append(strInput) # 输入开始节点、结束节点 strInput = input() list0 = strInput.split(' ') nodeIdStart = list0[0] nodeIdEnd = list0[1] # 解析得到节点Id listNodeId.append(nodeIdStart) listNodeId.append(nodeIdEnd) for index in listRoute: list0 = index.split(' ') nodeIdA = list0[0] nodeIdB = list0[1] if nodeIdA not in listNodeId: listNodeId.append(nodeIdA) if nodeIdB not in listNodeId: listNodeId.append(nodeIdB) # 初始化路由信息字典、节点信息字典 for nodeId in listNodeId: # 节点字典信息 dictNode[nodeId] = [10000, '', False] # 最短距离、父节点、是否检查过 # 每个路由字典创建 dictRoute[nodeId] = {} dictNode[nodeIdStart][0] = 0 # 初始化路由信息 for index in listRoute: list0 = index.split(' ') nodeIdA = list0[0] nodeIdB = list0[1] dictRoute[nodeIdA][nodeIdB] = int(list0[2]) dictRoute[nodeIdB][nodeIdA] = int(list0[2]) # 打印输入信息 def PrintInputInfo(): print('nodeNum routeNum:') print(str(nodeNum) + ' ' + str(routeNum)) print('nodeStart nodeEnd') print(nodeIdStart+' '+nodeIdEnd) print('route info:') for nodeId in dictRoute.keys(): for nebrId in dictRoute[nodeId].keys(): print(nodeId+'->'+nebrId+' = '+str(dictRoute[nodeId][nebrId])) print('node info:') for nodeId in dictNode.keys(): print(nodeId+':'+str(dictNode[nodeId][0])+' '+dictNode[nodeId][1]+' '+str(dictNode[nodeId][2])) #PrintInputInfo() ''' 狄克斯特拉实现 ''' # 找到最短距离节点id def FindShortNodeId(dictNode): shortNodeId = '' shortDis = 10000 for nodeId in dictNode.keys(): if dictNode[nodeId][0] < shortDis and dictNode[nodeId][2] == False: shortNodeId = nodeId shortDis = dictNode[nodeId][0] return shortNodeId # 狄克斯特拉算法 shortNodeId = FindShortNodeId(dictNode) while shortNodeId: if shortNodeId == nodeIdEnd: break; dictNode[shortNodeId][2] = True shortDis = dictNode[shortNodeId][0] for nebrId in dictRoute[shortNodeId].keys(): newDis = dictRoute[shortNodeId][nebrId] + shortDis if newDis < dictNode[nebrId][0]: dictNode[nebrId][0] = newDis dictNode[nebrId][1] = shortNodeId shortNodeId = FindShortNodeId(dictNode) # 打印结果 listRst = [] nodeId = nodeIdEnd while nodeId: listRst.append(nodeId) nodeId = dictNode[nodeId][1] listRst.reverse() strRst = '' for nodeId in listRst: if nodeId == listRst[-1]: strRst += nodeId else: strRst += nodeId + '->' if dictNode[nodeIdEnd][1] == '': print('cant reach '+nodeIdEnd) else: print(strRst) print(dictNode[nodeIdEnd][0])
测试用例及验证
Case1
输入:
6 4
1 2 2
1 3 4
2 5 3
5 6 2
2 6
输出:
Case2
输入:
4 5
S A 6
S B 2
B A 3
A E 1
B E 5
S E
输出:
Case3(找不到终点)
输入:
6 6
S A 2
S B 1
A C 4
A B 1
B D 2
C D 3
S End
输出:
Case4
输入:
6 8
S A 5
S B 1
A C 1
A B 1
B D 5
C D 1
D End 1
C End 3
S End
输出:
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