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library(Biobase)
set.seed(1)
# - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# Consistency checks
# - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# rowMedians() by rowQ()
rowMedians2 <- function(imat) {
nr <- ncol(imat)
half <- (nr + 1)/2
if (nr%%2 == 1) {
return(rowQ(imat, half))
} else {
return((rowQ(imat, half) + rowQ(imat, half+1))/2)
}
}
cat("Consistency checks:\n")
set.seed(1)
for (kk in 1:20) {
cat("Random test #", kk, "\n", sep="")
# Simulate data in a matrix of any shape
nrow <- sample(2000, size=1)
ncol <- sample(2000, size=1)
x <- rnorm(nrow*ncol)
dim(x) <- c(nrow, ncol)
# Add NAs?
nas <- sample(c(TRUE,FALSE), size=1)
if (nas) {
nna <- sample(nrow*ncol, size=1)
x[sample(length(x), size=nna)] <- NA
}
na.rm <- nas
t1 <- system.time({
y1 <- rowMedians(x, na.rm=na.rm)
})
t2 <- system.time({
y2 <- apply(x, MARGIN=1, FUN=median, na.rm=na.rm)
})
# When all values of 'y2' are NA, 'y2' is logical
if (is.logical(y2)) y2 <- as.double(y2)
stopifnot(all.equal(y1,y2))
cat(sprintf("rowMedians()/apply(): %.3g\n", (t1/t2)[3]))
if (!nas) {
t3 <- system.time({
y3 <- rowMedians2(x)
})
stopifnot(all.equal(y1,y3))
cat(sprintf("rowMedians()/rowMedians2(): %.3g\n", (t1/t3)[3]))
}
}
# - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# Benchmarking
# - - - - - - - - - - - - - - - - - - - - - - - - - - - -
cat("Benchmarking:\n")
# Simulate data in a matrix of any shape
nrow <- 1000
ncol <- 1000
x <- rnorm(nrow*ncol)
dim(x) <- c(nrow, ncol)
gc()
t0 <- system.time({
for (rr in 1:20)
y0 <- apply(x, MARGIN=1, FUN=median, na.rm=FALSE)
})
gc()
t1 <- system.time({
for (rr in 1:20)
y1 <- rowMedians(x, na.rm=FALSE)
})
gc()
stopifnot(all.equal(y0,y1))
cat(sprintf("rowMedians()/apply(): %.3g\n", (t1/t0)[3]))
# - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# Consistency checks
# - - - - - - - - - - - - - - - - - - - - - - - - - - - -
cat("Consistency checks without NAs:\n")
for (kk in 1:20) {
cat("Random test #", kk, "\n", sep="")
# Simulate data in a matrix of any shape
nrow <- sample(1000, size=1)
ncol <- sample(1000, size=1)
x <- rnorm(nrow*ncol)
dim(x) <- c(nrow, ncol)
t0 <- system.time({
y0 <- apply(x, MARGIN=1, FUN=median, na.rm=FALSE)
})
t1 <- system.time({
y1 <- rowMedians(x, na.rm=FALSE)
})
stopifnot(all.equal(y0,y1))
} # for (kk in ...)
cat("Consistency checks with NAs:\n")
for (kk in 1:20) {
cat("Random test #", kk, "\n", sep="")
# Simulate data in a matrix of any shape
nrow <- sample(1000, size=1)
ncol <- sample(1000, size=1)
x <- rnorm(nrow*ncol)
dim(x) <- c(nrow, ncol)
# Add NAs
nna <- sample(nrow*ncol-1, size=1)
x[sample(length(x), size=nna)] <- NA
t0 <- system.time({
y0 <- apply(x, MARGIN=1, FUN=median, na.rm=TRUE)
y0[is.na(y0)] <- NA
})
t1 <- system.time({
y1 <- rowMedians(x, na.rm=TRUE)
})
stopifnot(all.equal(y0,y1))
} # for (kk in ...)
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