要创建一个新图\(G'\),满足条件(a)、(b)和©,可以采取以下步骤:
使用强连通分量算法(例如Tarjan算法)对图\(G\)进行处理,找到所有的强连通分量。记为\(SCC_1, SCC_2, \ldots, SCC_k\)。
构建一个空的图\(G'\),其中顶点集合与原始图\(G\)相同。
遍历每个强连通分量\(SCC_i\),若该分量只包含一个节点,则在\(G'\)中添加该节点。 否则,在\(G'\)中添加一个虚拟节点代表该强连通分量,并将该虚拟节点与分量内的所有实际节点连接起来。
对于原始图中的每条边\((u,v)\),若边所连接的两个顶点属于不同的强连通分量,则在\(G'\)中添加一条边从源强连通分量指向目标强连通分量。
这样构造得到的图\(G'\)满足条件(a)、(b)和©,即与原始图具有相同的强连通分量和分量图,并且所包含的边尽可能少。
以下是用Go语言实现上述算法的示例代码:
package main
import (
"fmt"
)
type Graph struct {
vertices []int
edges map[int][]int
}
func NewGraph() *Graph {
return &Graph{
vertices: []int{},
edges: make(map[int][]int),
}
}
func (g *Graph) AddVertex(v int) {
g.vertices = append(g.vertices, v)
}
func (g *Graph) AddEdge(u, v int) {
g.edges[u] = append(g.edges[u], v)
}
type SCC struct {
index int
lowlink map[int]int
onStack map[int]bool
stack []int
sccComponents [][]int
}
func NewSCC(graph *Graph) *SCC {
return &SCC{
index: 0,
lowlink: make(map[int]int),
onStack: make(map[int]bool),
stack: []int{},
sccComponents: [][]int{},
}
}
func (scc *SCC) TarjanAlgorithm(graph *Graph) [][]int {
for _, v := range graph.vertices {
if scc.lowlink[v] == 0 {
scc.strongConnect(v, graph)
}
}
return scc.sccComponents
}
func (scc *SCC) strongConnect(v int, graph *Graph) {
scc.index++
scc.lowlink[v] = scc.index
scc.stack = append(scc.stack, v)
scc.onStack[v] = true
for _, w := range graph.edges[v] {
if scc.lowlink[w] == 0 { // w has not yet been visited
scc.strongConnect(w, graph)
scc.lowlink[v] = min(scc.lowlink[v], scc.lowlink[w])
} else if scc.onStack[w] { // w is in the current SCC being built
scc.lowlink[v] = min(scc.lowlink[v], scc.lowlink[w])
}
}
if scc.lowlink[v] == scc.index {
component := []int{}
w := -1
for w != v {
w, scc.stack = scc.stack[len(scc.stack)-1], scc.stack[:len(scc.stack)-1]
scc.onStack[w] = false
component = append(component, w)
}
scc.sccComponents = append(scc.sccComponents, component)
}
}
func min(a, b int) int {
if a < b {
return a
}
return b
}
func buildNewGraph(graph *Graph, sccComponents [][]int) *Graph {
newGraph := NewGraph()
nodeMap := make(map[int]int)
for i, component := range sccComponents {
if len(component) > 1 { // Create virtual node for the SCC
virtualNode := -i - 1
nodeMap[virtualNode] = virtualNode
newGraph.AddVertex(virtualNode)
for _, node := range component {
nodeMap[node] = virtualNode
for _, neighbor := range graph.edges[node] {
if nodeMap[neighbor] != virtualNode { // Add inter-component edge
newGraph.AddEdge(virtualNode, neighbor)
}
}
}
} else { // Component with single node
nodeMap[component[0]] = component[0]
newGraph.AddVertex(component[0])
}
}
for u, neighbors := range graph.edges { // Add intra-component edges within SCCs in new graph
for _, v := range neighbors {
if nodeMap[u] != nodeMap[v] { // Edge between different components in original graph
newGraph.AddEdge(nodeMap[u], nodeMap[v]) // Add edge in new graph
}
}
}
return newGraph
}
func main() {
// 构建原始图
graph := NewGraph()
graph.AddVertex(1)
graph.AddVertex(2)
graph.AddVertex(3)
graph.AddVertex(4)
graph.AddVertex(5)
graph.AddEdge(1, 2)
graph.AddEdge(2, 3)
graph.AddEdge(3, 1)
graph.AddEdge(4, 2)
graph.AddEdge(4, 5)
// 使用Tarjan算法获取强连通分量
scc := NewSCC(graph)
sccComponents := scc.TarjanAlgorithm(graph)
// 构建新图
newGraph := buildNewGraph(graph, sccComponents)
fmt.Println("Original Graph:")
fmt.Println("Vertices:", graph.vertices)
fmt.Println("Edges:", graph.edges)
fmt.Println("\nNew Graph:")
fmt.Println("Vertices:", newGraph.vertices)
fmt.Println("Edges:", newGraph.edges)
}
这段代码首先定义了一个Graph
结构来表示图,包含顶点和边的信息。然后定义了一个SCC
结构来实现Tarjan算法进行强连通分量的计算。接着使用上述步骤中的算法来创建新图\(G'\),并最终输出结果。
希望以上代码可以帮助到您!
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