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#setAutoRealizationBackend("RleArray")
#setAutoRealizationBackend("HDF5Array")
a1 <- array(sample(5L, 150, replace=TRUE), c(5, 10, 3)) # integer array
a2 <- a1 + runif(150) - 0.5 # numeric array
m2 <- matrix(runif(60), ncol=6) # numeric matrix
m0 <- rsparsematrix(nrow=10, ncol=6, density=0.25) # dgCMatrix object
block_sizes1 <- c(12L, 20L, 50L, 15000L)
block_sizes2 <- 2L * block_sizes1
test_DelayedMatrix_row_col_summarization <- function()
{
test_row_col_summary <- function(FUN, m, M, block_sizes) {
on.exit(suppressMessages(setAutoBlockSize()))
FUN <- match.fun(FUN)
target1 <- FUN(m)
target2 <- FUN(m, na.rm=TRUE)
target3 <- FUN(t(m))
target4 <- FUN(t(m), na.rm=TRUE)
for (block_size in block_sizes) {
suppressMessages(setAutoBlockSize(block_size))
current <- FUN(M)
checkEquals(target1, current)
checkIdentical(typeof(target1), typeof(current))
current <- FUN(M, na.rm=TRUE)
checkEquals(target2, current)
checkIdentical(typeof(target2), typeof(current))
current <- FUN(t(M))
checkEquals(target3, current)
checkIdentical(typeof(target3), typeof(current))
current <- FUN(t(M), na.rm=TRUE)
checkEquals(target4, current)
checkIdentical(typeof(target4), typeof(current))
}
}
FUNS <- c("rowSums", "colSums", "rowMeans", "colMeans",
"rowMins", "colMins", "rowMaxs", "colMaxs",
"rowRanges", "colRanges")
## on an integer matrix
m <- a1[ , , 1]
A1 <- realize(a1)
M <- A1[ , , 1]
for (FUN in FUNS) {
test_row_col_summary(FUN, m, M, block_sizes2)
test_row_col_summary(FUN, m[ , 0], M[ , 0], block_sizes2)
}
## on a numeric matrix
m <- m2
m[2, 4] <- NA
m[5, 4] <- Inf
m[6, 3] <- -Inf
M <- realize(m)
for (FUN in FUNS)
test_row_col_summary(FUN, m, M, block_sizes2)
library(genefilter)
## Note that the matrixStats package also defines a rowVars() function.
test_row_col_summary(genefilter::rowVars, m, M, block_sizes2)
## on a sparse matrix
m <- m0
m[2, 4] <- NA
m[5, 4] <- Inf
m[6, 3] <- -Inf
M <- DelayedArray(m)
for (FUN in FUNS)
test_row_col_summary(FUN, as.matrix(m), M, block_sizes2)
test_row_col_summary(genefilter::rowVars, m, M, block_sizes2)
}
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