id = c(1, 2, 3, 4, 5, 6)
fid = c(NA, NA, 1, 1, 4, 5)
mid = c(NA, NA, 2, NA, 3, 2)

library(pedigreemm)
ped = pedigree(sire = fid, dam = mid, label = id)
A = getA(ped)
A
spokr = cbind(id, fid, mid)
spokr
Amatrix = matrix(0, nrow = 6, ncol = 6)
Tmatrix = matrix(0, nrow = 6, ncol = 6)
Dmatrix = matrix(0, nrow = 6, ncol = 1)

Amatrix[1,1] = 1
Amatrix[2,2] = 1
Amatrix[2,1] = 0
Amatrix[3,3] = 1 + 0.5*0
Amatrix[3,1] = 0.5*(1+0)
Amatrix[3,2] = 0.5*(0+1)



Tmatrix[1,1] = 1
Tmatrix[2,2] = 1
Tmatrix[3,3] = 1
Tmatrix[4,4] = 1
Tmatrix[5,5] = 1
Tmatrix[6,6] = 1

Tmatrix[2,1] = 0
Tmatrix[3,1] = 0.5*(1+0)  
Tmatrix[3,2] = 0.5*(0+1)  
  
  
  
  

Dmatrix[1,1] = 1
Dmatrix[2,1] = 1
Dmatrix[3,1] = 0.5 - 0.25*( 0 + 0)
  

library(pedigreemm)
ped = pedigree(sire = fid, dam = mid, label = id)
A = getA(ped)
A
library(bdsmatrix)
tmp = gchol(as.matrix(A))
(T = as(as.matrix(tmp), "dtCMatrix"))
(D = diag(tmp))



T = as.matrix(T)
D = as.matrix(diag(D))
A = as.matrix(A)
A - T%*%D%*%t(T)


gA = solve(A)
gA
gT = solve(T)
gD = solve(D)
(gAnew = t(gT)%*%gD%*%gT)
round(gA - gAnew, 10)

faktor = chol(A)
L = faktor
Lt = t(faktor)
Lt%*%L


library(igraph)

edges=data.frame(from=fid, to=mid)
graph=graph_from_data_frame(edges,directed=FALSE)
plot(graph)