Hpath {GRelevance}

Basic description

Description

Applies the path.kruskal function based on the nodes and edge.cost (sorts the weights from minimum to maximum). Given the starting node, ending node, and the distance matrix, this function returns the list of nodes of each edge from the shortest Hamiltonian path. We have the Hamiltonian path from path.kruskal

Usage

Hpath(n1,n2,mat)

Arguments

n1

starting node

n2

ending node

mat

distance matrix (distance type is determined by the reader)

Value

list of nodes of each edge from the shortest Hamiltonian path

See Also

path.kruskal

Examples

G=list()
set.seed(1)
n1=20;n2=40
N=n1+n2;
G[[1]]=c(1:n1);G[[2]]=c((n1+1):(n1+n2));
d=10
mu1=rep(0,d)
mu2=mu1+0.1
true.cov1=0.4^(abs(outer(1:d,1:d,"-")))
true.cov2=0.4^(abs(outer(1:d,1:d,"-")))
sam1=MASS::mvrnorm(n=n1,mu=mu1,Sigma=true.cov1)
sam2=MASS::mvrnorm(n=n2,mu=mu2,Sigma=true.cov2)
Data=rbind(sam1,sam2)
Dist=philentropy::distance(Data, method = "euclidean")
Dist[lower.tri(Dist)] <- NA
Dist[diag(Dist)] <- NA
Hpath(1,N,Dist)