/usr/lib/R/site-library/foreach/examples/apply.R is in r-cran-foreach 1.4.4-1.
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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 | # File src/library/base/R/apply.R
# Part of the R package, http://www.R-project.org
#
# This program is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 2 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# A copy of the GNU General Public License is available at
# http://www.r-project.org/Licenses/
applyPar <- function(X, MARGIN, FUN, ...)
{
FUN <- match.fun(FUN)
## Ensure that X is an array object
d <- dim(X)
dl <- length(d)
if(dl == 0)
stop("dim(X) must have a positive length")
ds <- 1:dl
if(length(oldClass(X)) > 0)
X <- if(dl == 2) as.matrix(X) else as.array(X)
## now recompute things as coercion can change dims
## (e.g. when a data frame contains a matrix).
d <- dim(X)
dn <- dimnames(X)
## Extract the margins and associated dimnames
s.call <- ds[-MARGIN]
s.ans <- ds[MARGIN]
d.call <- d[-MARGIN]
d.ans <- d[MARGIN]
dn.call<- dn[-MARGIN]
dn.ans <- dn[MARGIN]
## dimnames(X) <- NULL
## do the calls
d2 <- prod(d.ans)
if(d2 == 0) {
## arrays with some 0 extents: return ``empty result'' trying
## to use proper mode and dimension:
## The following is still a bit `hackish': use non-empty X
newX <- array(vector(typeof(X), 1), dim = c(prod(d.call), 1))
ans <- FUN(if(length(d.call) < 2) newX[,1] else
array(newX[,1], d.call, dn.call), ...)
return(if(is.null(ans)) ans else if(length(d.ans) < 2) ans[1][-1]
else array(ans, d.ans, dn.ans))
}
## else
newX <- aperm(X, c(s.call, s.ans))
dim(newX) <- c(prod(d.call), d2)
#### ans <- vector("list", d2)
nw <- getDoParWorkers()
if(length(d.call) < 2) {# vector
if (length(dn.call)) dimnames(newX) <- c(dn.call, list(NULL))
#### for(i in 1:d2) {
#### tmp <- FUN(newX[,i], ...)
#### if(!is.null(tmp)) ans[[i]] <- tmp
#### }
ans <- foreach(x=iblkcol(newX, nw), .combine='c', .packages='foreach') %dopar% {
foreach(i=1:ncol(x)) %do% FUN(x[,i], ...)
}
} else {
#### for(i in 1:d2) {
#### tmp <- FUN(array(newX[,i], d.call, dn.call), ...)
#### if(!is.null(tmp)) ans[[i]] <- tmp
#### }
ans <- foreach(x=iblkcol(newX, nw), .combine='c', .packages='foreach') %dopar% {
foreach(y=1:ncol(x)) %do% FUN(array(x[,i], d.call, dn.call), ...)
}
}
## answer dims and dimnames
ans.list <- is.recursive(ans[[1]])
l.ans <- length(ans[[1]])
ans.names <- names(ans[[1]])
if(!ans.list)
ans.list <- any(unlist(lapply(ans, length)) != l.ans)
if(!ans.list && length(ans.names)) {
all.same <- sapply(ans, function(x) identical(names(x), ans.names))
if (!all(all.same)) ans.names <- NULL
}
len.a <- if(ans.list) d2 else length(ans <- unlist(ans, recursive = FALSE))
if(length(MARGIN) == 1 && len.a == d2) {
names(ans) <- if(length(dn.ans[[1]])) dn.ans[[1]] # else NULL
return(ans)
}
if(len.a == d2)
return(array(ans, d.ans, dn.ans))
if(len.a > 0 && len.a %% d2 == 0) {
if(is.null(dn.ans)) dn.ans <- vector(mode="list", length(d.ans))
dn.ans <- c(list(ans.names), dn.ans)
return(array(ans, c(len.a %/% d2, d.ans),
if(!all(sapply(dn.ans, is.null))) dn.ans))
}
return(ans)
}
##############################################################################
#
# Something like this will be added to the iterators package.
# This creates an iterator over block columns of a matrix.
iblkcol <- function(a, chunks) {
n <- ncol(a)
i <- 1
nextEl <- function() {
if (chunks <= 0 || n <= 0) stop('StopIteration')
m <- ceiling(n / chunks)
r <- seq(i, length=m)
i <<- i + m
n <<- n - m
chunks <<- chunks - 1
a[,r, drop=FALSE]
}
obj <- list(nextElem=nextEl)
class(obj) <- c('abstractiter', 'iter')
obj
}
# Simple test program for applyPar
library(foreach)
x <- matrix(rnorm(16000000), 4000)
actual <- applyPar(x, 2, mean)
expected <- apply(x, 2, mean)
cat(sprintf('Result correct: %s\n', identical(actual, expected)))
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