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## vcv.phylo.R (2012-02-21)
## Phylogenetic Variance-Covariance or Correlation Matrix
## Copyright 2002-2012 Emmanuel Paradis
## This file is part of the R-package `ape'.
## See the file ../COPYING for licensing issues.
vcv <- function(phy, ...) UseMethod("vcv")
vcv.phylo <- function(phy, model = "Brownian", corr = FALSE, ...)
{
if (is.null(phy$edge.length))
stop("the tree has no branch lengths")
pp <- prop.part(phy)
phy <- reorder(phy, "postorder")
n <- length(phy$tip.label)
e1 <- phy$edge[, 1]
e2 <- phy$edge[, 2]
EL <- phy$edge.length
## xx: vecteur donnant la distance d'un noeud
## ou d'un tip a partir de la racine
## (same than in is.ultrametric)
xx <- numeric(n + phy$Nnode)
vcv <- matrix(0, n, n)
## the loop below starts from the bottom of the edge matrix, so
## from the root
for (i in length(e1):1) {
var.cur.node <- xx[e1[i]]
xx[e2[i]] <- var.cur.node + EL[i] # sets the variance
j <- i - 1L
while (e1[j] == e1[i] && j > 0) {
left <- if (e2[j] > n) pp[[e2[j] - n]] else e2[j]
right <- if (e2[i] > n) pp[[e2[i] - n]] else e2[i]
vcv[left, right] <- vcv[right, left] <- var.cur.node # sets the covariance
j <- j - 1L
}
}
diag.elts <- 1 + 0:(n - 1)*(n + 1)
vcv[diag.elts] <- xx[1:n]
if (corr) {
## This is inspired from the code of cov2cor (2005-09-08):
Is <- sqrt(1 / vcv[diag.elts])
## below 'vcv[] <- ...' has been changed to 'vcv <- ...'
## which seems to be twice faster for n = 1000 and
## respects the additional attributes (2012-02-21):
vcv <- Is * vcv * rep(Is, each = n)
vcv[diag.elts] <- 1
}
dimnames(vcv)[1:2] <- list(phy$tip.label)
vcv
}
vcv.corPhyl <- function(phy, corr = FALSE, ...)
{
labels <- attr(phy, "tree")$tip.label
dummy.df <- data.frame(seq_along(labels), row.names = labels)
res <- corMatrix(Initialize.corPhyl(phy, dummy.df), corr = corr)
dimnames(res) <- list(labels, labels)
res
}
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