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#OU variance-covariance matrix generator
#written by Jeremy M. Beaulieu
varcov.ou <- function(phy, edges, Rate.mat, root.state, simmap.tree=FALSE, root.age=NULL, scaleHeight=FALSE, assume.station=TRUE, shift.point=.5){
if(assume.station == TRUE){
alpha=Rate.mat[1,1]
sigma=Rate.mat[2,1]
vcv <- quickVCV(phy=phy, alpha=alpha, sigma.sq=sigma, scaleHeight=scaleHeight)
}else{
if(is.null(root.state)) {
root.state <- which(edges[dim(edges)[1],]==1)-5
edges <- edges[-1*dim(edges)[1],]
}
n=max(phy$edge[,1])
ntips=length(phy$tip.label)
if(simmap.tree==TRUE){
k=length(colnames(phy$mapped.edge))
}
if(simmap.tree==FALSE){
mm<-dim(edges)
k<-length(6:mm[2])
}
pp <- prop.part(phy)
oldregime=root.state
nodevar1=rep(0,max(edges[,3]))
nodevar2=rep(0,max(edges[,3]))
alpha=Rate.mat[1,]
sigma=Rate.mat[2,]
n.cov1=matrix(rep(0,n), n, 1)
n.cov2=matrix(rep(0,n), n, 1)
if(simmap.tree==TRUE){
regimeindex<-colnames(phy$mapped.edge)
for(i in 1:length(edges[,1])){
anc = edges[i, 2]
desc = edges[i, 3]
if(scaleHeight==TRUE){
currentmap<-phy$maps[[i]]/max(MakeAgeTable(phy, root.age=root.age))
}
else{
currentmap <- phy$maps[[i]]
}
oldtime=edges[i,4]
for (regimeindex in 1:length(currentmap)){
regimeduration <- currentmap[regimeindex]
newtime <- oldtime+regimeduration
regimenumber <- which(colnames(phy$mapped.edge)==names(currentmap)[regimeindex])
nodevar1[i] <- nodevar1[i]+alpha[regimenumber]*(newtime-oldtime)
nodevar2[i] <- nodevar2[i]+sigma[regimenumber]*((exp(2*alpha[regimenumber]*newtime)-exp(2*alpha[regimenumber]*oldtime))/(2*alpha[regimenumber]))
oldtime <- newtime
newregime <- regimenumber
}
oldregime=newregime
n.cov1[edges[i,3],]=nodevar1[i]
n.cov2[edges[i,3],]=nodevar2[i]
}
}
if(simmap.tree==FALSE){
for(i in 1:length(edges[,1])){
anc <- edges[i,2]
oldtime <- edges[i,4]
newtime <- edges[i,5]
if(anc%in%edges[,3]){
start <- which(edges[,3]==anc)
oldregime <- which(edges[start,6:(k+5)]==1)
}
else{
#For the root:
oldregime=root.state
}
newregime=which(edges[i,6:(k+5)]==1)
if(oldregime==newregime){
nodevar1[i] <- alpha[oldregime]*(newtime-oldtime)
nodevar2[i] <- sigma[oldregime]*((exp(2*alpha[oldregime]*newtime)-exp(2*alpha[oldregime]*oldtime))/(2*alpha[oldregime]))
}
else{
shifttime <- newtime-((newtime-oldtime)*shift.point)
epoch1a <- alpha[oldregime]*(shifttime-oldtime)
epoch1b <- sigma[oldregime]*((exp(2*alpha[oldregime]*shifttime)-exp(2*alpha[oldregime]*oldtime))/(2*alpha[oldregime]))
oldtime <- shifttime
newtime <- newtime
epoch2a <- alpha[newregime]*(newtime-oldtime)
epoch2b <- sigma[newregime]*((exp(2*alpha[newregime]*newtime)-exp(2*alpha[newregime]*oldtime))/(2*alpha[newregime]))
nodevar1[i] <- epoch1a+epoch2a
nodevar2[i] <- epoch1b+epoch2b
}
oldregime <- newregime
n.cov1[edges[i,3],] <- nodevar1[i]
n.cov2[edges[i,3],] <- nodevar2[i]
}
}
vcv1 <- mat.gen(phy,n.cov1,pp)
vcv2 <- mat.gen(phy,n.cov2,pp)
if(any(abs(diff(alpha)) > 0)){
species.variances <- diag(vcv1)
species.total.variances <- matrix(0, dim(vcv1)[2], dim(vcv1)[2])
count=0
for(i in 1:dim(vcv1)[2]) {
for(j in 1:dim(vcv1)[2]){
species.total.variances[i,j] <- exp(-(species.variances[i] + species.variances[j]))
count=count+1 # the count is always watching
}
}
vcv <- species.total.variances * vcv2
}else{
if(is.null(root.age)){
root.age <- max(branching.times(phy))
}
vcv <- exp(-2*alpha[1]*max(root.age)) * vcv2
}
}
vcv
}
## Quick VCV maker of OU1 and OUM -- since alpha and sigma.sq are constants, and since the regime does not matter, we can just do a simple plug and chug. It's a tad slower, but mostly for testing purposes.
quickVCV <- function(phy, alpha, sigma.sq, scaleHeight){
phy$node.label <- NULL
vcv <- matrix(0, Ntip(phy), Ntip(phy))
split.times <- branching.times(phy)
if(scaleHeight == TRUE){
split.times <- split.times/max(split.times)
}
tot.time <- max(split.times)
for(i in 1:Ntip(phy)){
for(j in 1:Ntip(phy)){
if(i == j){
dij <- 0
tij <- tot.time
vcv[i,j] <- (sigma.sq /(2 * alpha)) * exp(-2 * alpha * dij)
}else{
split <- getMRCA(phy, tip=c(phy$tip.label[i], phy$tip.label[j]))
dij <- split.times[which(names(split.times)==split)]
tij <- tot.time - dij
vcv[i,j] <- (sigma.sq /(2 * alpha)) * exp(-2 * alpha * dij)
}
}
}
return(vcv)
}
##Matrix generating function taken from vcv.phylo in ape:
mat.gen <- function(phy,piece.wise,pp){
phy <- reorder(phy, "pruningwise")
n <- length(phy$tip.label)
anc <- phy$edge[,1]
des <- phy$edge[,2]
ep <- piece.wise[,1]
comp <- numeric(n + phy$Nnode)
mat <- matrix(0, n, n)
for (i in length(anc):1) {
focal <- comp[anc[i]]
comp[des[i]] <- focal + ep[des[i]]
j <- i - 1L
while (anc[j] == anc[i] && j > 0) {
left <- if (des[j] > n) pp[[des[j] - n]] else des[j]
right <- if (des[i] > n) pp[[des[i] - n]] else des[i]
mat[left, right] <- mat[right, left] <- focal
j <- j - 1L
}
}
diag.elts <- 1 + 0:(n - 1)*(n + 1)
mat[diag.elts] <- comp[1:n]
mat
}
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