INIT: ne=2; head[]置为0; addedge()加入所有弧;| CALL: flow(n, s, t);

本文介绍了使用类型为typec的数据结构实现图的边表示和Dijkstra算法求解从源(s)到目标(t)的最短路径问题,利用邻接表数据结构管理顶点和边关系。
INIT: ne=2; head[]置为0; addedge()加入所有弧;
| CALL: flow(n, s, t);
\*==================================================*/
#define typec int // type of cost
const typec inf = 0x3f3f3f3f; // max of cost
struct edge { int x, y, nxt; typec c; } bf[E];
int ne, head[N], cur[N], ps[N], dep[N];
void addedge(int x, int y, typec c)
{
// add an arc(x -> y, c); vertex: 0 ~ n-1;
bf[ne].x = x; bf[ne].y = y; bf[ne].c = c;
bf[ne].nxt = head[x]; head[x] = ne++;
bf[ne].x = y; bf[ne].y = x; bf[ne].c = 0;
bf[ne].nxt = head[y]; head[y] = ne++;
}
typec flow(int n, int s, int t)
{
typec tr, res = 0;
int i, j, k, f, r, top;
while (1) {
memset(dep, -1, n * sizeof(int));
for (f = dep[ps[0] = s] = 0, r = 1; f != r; )
for (i = ps[f++], j = head[i]; j; j = bf[j].nxt)
{
if (bf[j].c && -1 == dep[k = bf[j].y]){
dep[k] = dep[i] + 1; ps[r++] = k;
if (k == t) { f = r; break; }
}
}
if (-1 == dep[t]) break;
memcpy(cur, head, n * sizeof(int));
for (i = s, top = 0; ; ) {
if (i == t) {
for (k = 0, tr = inf; k < top; ++k)
if (bf[ps[k]].c < tr)
tr = bf[ps[f = k]].c;
for (k = 0; k < top; ++k)
bf[ps[k]].c -= tr, bf[ps[k]^1].c += tr;
res += tr; i = bf[ps[top = f]].x;
}
for (j=cur[i]; cur[i]; j = cur[i] = bf[cur[i]].nxt)
if (bf[j].c && dep[i]+1 == dep[bf[j].y]) break;
if (cur[i]) {
ps[top++] = cur[i];
i = bf[cur[i]].y;
}
else {
if (0 == top) break;
dep[i] = -1; i = bf[ps[--top]].x;
}
}
}
return res;
}
from pythonds.graphs import PriorityQueue import sys class Vertex: def __init__(self, key): self.id = key self.connectedTo = {} self.dis = sys.maxsize self.pred = None def addNeighbor(self, nbr, weight=0): self.connectedTo[nbr] = weight def setDistance(self, distance): self.dis = distance def getDistance(self): return self.dis def getConnections(self): return self.connectedTo.keys() def getWeight(self, nbr): return self.connectedTo[nbr] def setPred(self, p): self.pred = p class Graph: def __init__(self): self.vertList = {} self.numVertices = 0 def addVertex(self, key): self.numVertices = self.numVertices + 1 newVertex = Vertex(key) self.vertList[key] = newVertex return newVertex def getVertex(self, n): if n in self.vertList: return self.vertList[n] else: return None def __contains__(self, n): return n in self.vertList def addEdge(self, f, t, cost=0): if f not in self.vertList: nv = self.addVertex(f) if t not in self.vertList: nv = self.addVertex(t) self.vertList[f].addNeighbor(self.vertList[t], cost) def getVertices(self): return self.vertList.keys() def __iter__(self): return iter(self.vertList.values()) def dijkstra(aGraph, start): pq = PriorityQueue() start.setDistance(0) pq.buildHeap([(v.getDistance(), v) for v in aGraph]) while not pq.isEmpty(): currentVert = pq.delMin() for nextVert in currentVert.getConnections(): newDist = currentVert.getDistance() + currentVert.getWeight(nextVert) if newDist < nextVert.getDistance(): nextVert.setDistance(newDist) nextVert.setPred(currentVert) pq.decreaseKey(nextVert, newDist) aGraph = Graph() aGraph.addEdge('1', '2', 2) aGraph.addEdge('1', '3', 1) aGraph.addEdge('1', '4', 5) aGraph.addEdge('1', '2', 2) aGraph.addEdge('3', '2', 2) aGraph.addEdge('3', '4', 3) aGraph.addEdge('2', '4', 3) aGraph.addEdge('3', '5', 1) aGraph.addEdge('5', '4', 1) aGraph.addEdge('5', '6', 1) aGraph.addEdge('4', '6', 5) n = input("请输入初始结点:") start = aGraph.getVertex(n) while True: operation = input("1.查询结点 2.退出程序") if operation == "1": m = input("请输入结点,查询该结点距离初始结点的最近的距离:") node = aGraph.getVertex(m) dijkstra(aGraph, start) print(node.getDistance()) elif operation == "2": break 分析代码
06-08
from pythonds.basic import Queue class Vertex: def __init__(self,key): self.id = key self.connectedTo = {} def addNeighbor(self,nbr,weight=0): self.connectedTo[nbr] = weight def __str__(self): return str(self.id) + ' connectedTo: ' + str([x.id for x in self.connectedTo]) def getConnections(self): return self.connectedTo.keys() def getId(self): return self.id def getWeight(self,nbr): return self.connectedTo[nbr] class Graph: def __init__(self): self.vertList = {} self.numVertices = 0 def addVertex(self,key): self.numVertices = self.numVertices + 1 newVertex = Vertex(key) self.vertList[key] = newVertex return newVertex def getVertex(self,n): if n in self.vertList: return self.vertList[n] else: return None def __contains__(self,n): return n in self.vertList def addEdge(self,f,t,cost=0): if f not in self.vertList: nv = self.addVertex(f) if t not in self.vertList: nv = self.addVertex(t) self.vertList[f].addNeighbor(self.vertList[t], cost) def getVertices(self): return self.vertList.keys() def __iter__(self): return iter(self.vertList.values()) def bfs(g,start): start.setDistance(0) start.setPred(None) vertQueue=Queue() vertQueue.enqueue(start) while (vertQueue.size()>0): currentVert=vertQueue.dequeue() for nbr in currentVert.getConnections(): if (nbr.getColor()=='White'): nbr.setColor('gray') nbr.setDistance(currentVert.getDistance()+1) nbr.setPred(currentVert) vertQueue.enqueue(nbr) currentVert.setColor('black') List=["""1:A,2:B,3:C,4:D,5:E,6:F"""] g=Graph() for i in range(6): g.addVertex(i) g.addEdge(1,2,7) g.addEdge(2,1,2) g.addEdge(1,3,5) g.addEdge(1,6,1) g.addEdge(2,4,7) g.addEdge(2,5,3) g.addEdge(3,2,2) g.addEdge(3,6,8) g.addEdge(4,1,1) g.addEdge(4,5,2) g.addEdge(4,6,4) g.addEdge(5,1,6) g.addEdge(5,4,5) g.addEdge(6,2,1) g.addEdge(6,5,8) bfs(g,)优化这段代码
06-12
评论
添加红包

请填写红包祝福语或标题

红包个数最小为10个

红包金额最低5元

当前余额3.43前往充值 >
需支付:10.00
成就一亿技术人!
领取后你会自动成为博主和红包主的粉丝 规则
hope_wisdom
发出的红包

打赏作者

千秋TʌT

你的鼓励将是我创作的最大动力

¥1 ¥2 ¥4 ¥6 ¥10 ¥20
扫码支付:¥1
获取中
扫码支付

您的余额不足,请更换扫码支付或充值

打赏作者

实付
使用余额支付
点击重新获取
扫码支付
钱包余额 0

抵扣说明:

1.余额是钱包充值的虚拟货币,按照1:1的比例进行支付金额的抵扣。
2.余额无法直接购买下载,可以购买VIP、付费专栏及课程。

余额充值