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#setAutoRealizationBackend("RleArray")
#setAutoRealizationBackend("HDF5Array")
TEST_m1 <- matrix(runif(100), ncol=5, dimnames=list(NULL, LETTERS[1:5]))
TEST_m1[1, 2] <- NA
TEST_m1[2, 3] <- Inf
TEST_m1[3, 5] <- NaN
TEST_blocklengths1 <- c(1L, 6L, 10L, length(TEST_m1), 1000L * length(TEST_m1))
TEST_blocksizes1 <- TEST_blocklengths1 * get_type_size(type(TEST_m1))
TEST_group1 <- sample(6L, nrow(TEST_m1), replace=TRUE)
test_BLOCK_rowsum_colsum <- function()
{
BLOCK_rowsum <- DelayedArray:::BLOCK_rowsum
BLOCK_colsum <- DelayedArray:::BLOCK_colsum
m1 <- TEST_m1
m2 <- t(m1)
group1 <- group2 <- TEST_group1
library(HDF5Array)
for (reorder in c(TRUE, FALSE)) {
for (na.rm in c(FALSE, TRUE)) {
rs1 <- rowsum(m1, group1, reorder=reorder, na.rm=na.rm)
cs2 <- colsum(m2, group2, reorder=reorder, na.rm=na.rm)
## --- Serial evaluation ---
for (block_len in TEST_blocklengths1) {
grid1 <- defaultAutoGrid(m1, block.length=block_len)
grid2 <- defaultAutoGrid(m2, block.length=block_len)
## In-memory realization.
current <- BLOCK_rowsum(m1, group1,
reorder=reorder, na.rm=na.rm,
grid=grid1, as.sparse=NA,
BPPARAM=NULL, BACKEND=NULL)
checkEquals(current, rs1)
current <- BLOCK_colsum(m2, group2,
reorder=reorder, na.rm=na.rm,
grid=grid2, as.sparse=NA,
BPPARAM=NULL, BACKEND=NULL)
checkEquals(current, cs2)
## On-disk realization (HDF5 file).
current <- BLOCK_rowsum(m1, group1,
reorder=reorder, na.rm=na.rm,
grid=grid1, as.sparse=NA,
BPPARAM=NULL, BACKEND="HDF5Array")
checkTrue(is(current, "DelayedMatrix"))
checkTrue(validObject(current, complete=TRUE))
checkEquals(as.matrix(current), rs1)
current <- BLOCK_colsum(m2, group2,
reorder=reorder, na.rm=na.rm,
grid=grid2, as.sparse=NA,
BPPARAM=NULL, BACKEND="HDF5Array")
checkTrue(is(current, "DelayedMatrix"))
checkTrue(validObject(current, complete=TRUE))
checkEquals(as.matrix(current), cs2)
}
## --- Parallel evaluation ---
snow2 <- BiocParallel::SnowParam(workers=2)
grid1 <- defaultAutoGrid(m1, block.length=6L)
grid2 <- defaultAutoGrid(m2, block.length=10L)
## In-memory realization.
current <- BLOCK_rowsum(m1, group1, reorder=reorder, na.rm=na.rm,
grid=grid1, as.sparse=NA,
BPPARAM=snow2, BACKEND=NULL)
checkEquals(current, rs1)
current <- BLOCK_colsum(m2, group2, reorder=reorder, na.rm=na.rm,
grid=grid2, as.sparse=NA,
BPPARAM=snow2, BACKEND=NULL)
checkEquals(current, cs2)
## On-disk realization (HDF5 file).
current <- BLOCK_rowsum(m1, group1, reorder=reorder, na.rm=na.rm,
grid=grid1, as.sparse=NA,
BPPARAM=snow2, BACKEND="HDF5Array")
checkTrue(is(current, "DelayedMatrix"))
checkTrue(validObject(current, complete=TRUE))
checkEquals(as.matrix(current), rs1)
current <- BLOCK_colsum(m2, group2, reorder=reorder, na.rm=na.rm,
grid=grid2, as.sparse=NA,
BPPARAM=snow2, BACKEND="HDF5Array")
checkTrue(is(current, "DelayedMatrix"))
checkTrue(validObject(current, complete=TRUE))
checkEquals(as.matrix(current), cs2)
}
}
}
test_rowsum_colsum_DelayedMatrix <- function()
{
m1 <- TEST_m1
m2 <- t(m1)
group1 <- group2 <- TEST_group1
M1 <- DelayedArray(realize(m1))
M2 <- DelayedArray(realize(m2))
on.exit(suppressMessages(setAutoBlockSize()))
for (reorder in c(TRUE, FALSE)) {
for (na.rm in c(FALSE, TRUE)) {
rs1 <- rowsum(m1, group1, reorder=reorder, na.rm=na.rm)
cs2 <- colsum(m2, group2, reorder=reorder, na.rm=na.rm)
## --- Serial evaluation ---
for (block_size in TEST_blocksizes1) {
suppressMessages(setAutoBlockSize(block_size))
current <- rowsum(M1, group1, reorder=reorder, na.rm=na.rm)
checkEquals(as.matrix(current), rs1)
current <- colsum(M2, group2, reorder=reorder, na.rm=na.rm)
checkEquals(as.matrix(current), cs2)
}
## --- Parallel evaluation ---
setAutoBPPARAM(BiocParallel::SnowParam(workers=2))
on.exit(setAutoBPPARAM(), add=TRUE)
suppressMessages(setAutoBlockSize(20))
current <- rowsum(M1, group1, reorder=reorder, na.rm=na.rm)
checkEquals(as.matrix(current), rs1)
current <- colsum(M2, group2, reorder=reorder, na.rm=na.rm)
checkEquals(as.matrix(current), cs2)
setAutoBPPARAM()
}
}
}
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