X-Git-Url: https://git.donarmstrong.com/?a=blobdiff_plain;f=R%2Fdist.topo.R;h=525178f2528ed1ba66321e178d8c79d2cf0c91ed;hb=c14b15358e1f21302d929a980484e9f08c748c20;hp=b57fb0a591535817da88b108448da12f308faefd;hpb=631de80fc64dd4b62c967f3d08399df612317f6e;p=ape.git
diff --git a/R/dist.topo.R b/R/dist.topo.R
index b57fb0a..525178f 100644
--- a/R/dist.topo.R
+++ b/R/dist.topo.R
@@ -1,55 +1,64 @@
-## dist.topo.R (2008-07-18)
+## dist.topo.R (2011-07-13)
## Topological Distances, Tree Bipartitions,
## Consensus Trees, and Bootstrapping Phylogenies
-## Copyright 2005-2008 Emmanuel Paradis
+## Copyright 2005-2011 Emmanuel Paradis
## This file is part of the R-package `ape'.
## See the file ../COPYING for licensing issues.
dist.topo <- function(x, y, method = "PH85")
{
- if (method == "BHV01" && (is.null(x$edge.length) || is.null(y$edge.length)))
- stop("trees must have branch lengths for Billera et al.'s distance.")
- n <- length(x$tip.label)
- bp1 <- .Call("bipartition", x$edge, n, x$Nnode, PACKAGE = "ape")
+ if (method == "score" && (is.null(x$edge.length) || is.null(y$edge.length)))
+ stop("trees must have branch lengths for branch score distance.")
+ nx <- length(x$tip.label)
+ x <- unroot(x)
+ y <- unroot(y)
+ bp1 <- .Call("bipartition", x$edge, nx, x$Nnode, PACKAGE = "ape")
bp1 <- lapply(bp1, function(xx) sort(x$tip.label[xx]))
- bp2 <- .Call("bipartition", y$edge, n, y$Nnode, PACKAGE = "ape")
- bp2 <- lapply(bp2, function(xx) sort(y$tip.label[xx]))
+ ny <- length(y$tip.label) # fix by Otto Cordero
+ ## fix by Tim Wallstrom:
+ bp2.tmp <- .Call("bipartition", y$edge, ny, y$Nnode, PACKAGE = "ape")
+ bp2 <- lapply(bp2.tmp, function(xx) sort(y$tip.label[xx]))
+ bp2.comp <- lapply(bp2.tmp, function(xx) setdiff(1:ny, xx))
+ bp2.comp <- lapply(bp2.comp, function(xx) sort(y$tip.label[xx]))
+ ## End
q1 <- length(bp1)
q2 <- length(bp2)
if (method == "PH85") {
p <- 0
for (i in 1:q1) {
for (j in 1:q2) {
- if (identical(all.equal(bp1[[i]], bp2[[j]]), TRUE)) {
+ if (identical(bp1[[i]], bp2[[j]]) | identical(bp1[[i]], bp2.comp[[j]])) {
p <- p + 1
break
}
}
}
- dT <- if (q1 == q2) 2*(q1 - p) else 2*(min(q1, q2) - p) + abs(q1 - q2)
+ dT <- q1 + q2 - 2 * p # same than:
+ ##dT <- if (q1 == q2) 2*(q1 - p) else 2*(min(q1, q2) - p) + abs(q1 - q2)
}
- if (method == "BHV01") {
+ if (method == "score") {
dT <- 0
found1 <- FALSE
found2 <- logical(q2)
found2[1] <- TRUE
for (i in 2:q1) {
for (j in 2:q2) {
- if (identical(bp1[[i]], bp2[[j]])) {
- dT <- dT + abs(x$edge.length[which(x$edge[, 2] == n + i)] -
- y$edge.length[which(y$edge[, 2] == n + j)])
+ if (identical(bp1[[i]], bp2[[j]]) | identical(bp1[[i]], bp2.comp[[j]])) {
+ dT <- dT + (x$edge.length[which(x$edge[, 2] == nx + i)] -
+ y$edge.length[which(y$edge[, 2] == ny + j)])^2
found1 <- found2[j] <- TRUE
break
}
}
if (found1) found1 <- FALSE
- else dT <- dT + x$edge.length[which(x$edge[, 2] == n + i)]
+ else dT <- dT + (x$edge.length[which(x$edge[, 2] == nx + i)])^2
}
if (!all(found2))
- dT <- dT + sum(y$edge.length[y$edge[, 2] %in% (n + which(!found2))])
+ dT <- dT + sum((y$edge.length[y$edge[, 2] %in% (ny + which(!found2))])^2)
+ dT <- sqrt(dT)
}
dT
}
@@ -62,18 +71,28 @@ dist.topo <- function(x, y, method = "PH85")
if (any(table(ref) != 1))
stop("some tip labels are duplicated in tree no. 1")
n <- length(ref)
- for (i in 2:length(x)) {
- if (identical(x[[i]]$tip.label, ref)) next
- ilab <- match(x[[i]]$tip.label, ref)
- ## can use tabulate here because 'ilab' contains integers
- if (any(tabulate(ilab) > 1))
- stop(paste("some tip labels are duplicated in tree no.", i))
- if (any(is.na(ilab)))
- stop(paste("tree no.", i, "has different tip labels"))
- ie <- match(1:n, x[[i]]$edge[, 2])
- x[[i]]$edge[ie, 2] <- ilab
+ Ntree <- length(x)
+ if (Ntree > 1) {
+ for (i in 2:Ntree) {
+ label <- x[[i]]$tip.label
+ if (!identical(label, ref)) {
+ if (length(label) != length(ref))
+ stop(paste("tree no.", i, "has a different number of tips"))
+ ilab <- match(label, ref)
+ ## can use tabulate here because 'ilab' contains integers
+ if (any(is.na(ilab)))
+ stop(paste("tree no.", i, "has different tip labels"))
+### the test below does not seem useful anymore
+### if (any(tabulate(ilab) > 1))
+### stop(paste("some tip labels are duplicated in tree no.", i))
+###
+ ie <- match(1:n, x[[i]]$edge[, 2])
+ x[[i]]$edge[ie, 2] <- ilab
+ }
+ x[[i]]$tip.label <- NULL
+ }
}
- for (i in 1:length(x)) x[[i]]$tip.label <- NULL
+ x[[1]]$tip.label <- NULL
attr(x, "TipLabel") <- ref
x
}
@@ -84,17 +103,16 @@ prop.part <- function(..., check.labels = TRUE)
if (length(obj) == 1 && class(obj[[1]]) != "phylo")
obj <- obj[[1]]
##
- ## class(obj) <- NULL # needed?
+ ## class(obj) <- NULL # needed? apparently not, see below (2010-11-18)
##
ntree <- length(obj)
if (ntree == 1) check.labels <- FALSE
- if (check.labels) obj <- .compressTipLabel(obj)
+ if (check.labels) obj <- .compressTipLabel(obj) # fix by Klaus Schliep (2011-02-21)
for (i in 1:ntree) storage.mode(obj[[i]]$Nnode) <- "integer"
##
## The 1st must have tip labels
## Maybe simply pass the number of tips to the C code??
- if (!is.null(attr(obj, "TipLabel")))
- for (i in 1:ntree) obj[[i]]$tip.label <- attr(obj, "TipLabel")
+ obj <- .uncompressTipLabel(obj) # fix a bug (2010-11-18)
##
clades <- .Call("prop_part", obj, ntree, TRUE, PACKAGE = "ape")
attr(clades, "number") <- attr(clades, "number")[1:length(clades)]
@@ -166,10 +184,11 @@ prop.clades <- function(phy, ..., part = NULL)
n
}
-boot.phylo <- function(phy, x, FUN, B = 100, block = 1, trees = FALSE)
+boot.phylo <- function(phy, x, FUN, B = 100, block = 1,
+ trees = FALSE, quiet = FALSE)
{
- if (is.list(x)) {
- if (class(x) == "DNAbin") x <- as.matrix(x)
+ if (is.list(x) && !is.data.frame(x)) {
+ if (inherits(x, "DNAbin")) x <- as.matrix(x)
else {
nm <- names(x)
n <- length(x)
@@ -180,6 +199,7 @@ boot.phylo <- function(phy, x, FUN, B = 100, block = 1, trees = FALSE)
}
}
boot.tree <- vector("list", B)
+ if (!quiet) progbar <- utils::txtProgressBar(style = 3) # suggestion by Alastair Potts
for (i in 1:B) {
if (block > 1) {
y <- seq(block, ncol(x), block)
@@ -190,12 +210,18 @@ boot.phylo <- function(phy, x, FUN, B = 100, block = 1, trees = FALSE)
boot.samp[y - j] <- boot.i - j
} else boot.samp <- sample(ncol(x), replace = TRUE)
boot.tree[[i]] <- FUN(x[, boot.samp])
+ if (!quiet) utils::setTxtProgressBar(progbar, i/B)
}
+ if (!quiet) close(progbar)
for (i in 1:B) storage.mode(boot.tree[[i]]$Nnode) <- "integer"
storage.mode(phy$Nnode) <- "integer"
- ans <- attr(.Call("prop_part", c(list(phy), boot.tree),
- B + 1, FALSE, PACKAGE = "ape"), "number") - 1
- if (trees) ans <- list(BP = ans, trees = boot.tree)
+ ans <- prop.clades(phy, boot.tree)
+ ##ans <- attr(.Call("prop_part", c(list(phy), boot.tree),
+ ## B + 1, FALSE, PACKAGE = "ape"), "number") - 1
+ if (trees) {
+ class(boot.tree) <- "multiPhylo"
+ ans <- list(BP = ans, trees = boot.tree)
+ }
ans
}
@@ -242,6 +268,7 @@ consensus <- function(..., p = 1, check.labels = TRUE)
## Get all observed partitions and their frequencies:
pp <- prop.part(obj, check.labels = FALSE)
## Drop the partitions whose frequency is less than 'p':
+ if (p == 0.5) p <- 0.5000001 # avoid incompatible splits
pp <- pp[attr(pp, "number") >= p * ntree]
## Get the order of the remaining partitions by decreasing size:
ind <- sort(unlist(lapply(pp, length)), decreasing = TRUE,