Nothing
# set-up ====
enumerate <- 0L
errorfun <- function(tt) {
if(isFALSE(tt)) stop(print(tt))
}
test_make_dims <- function(n) {
# make dimensions that are randomly of size 1 or 5:
out <- lapply(1:n, \(n)sample(c(1, 5), 1)) |> unlist()
# check if the dimensions produce a too large object.
# If so, replace one >1L dimension with 1L
if(prod(out) > 5000L) {
ind <- which(out > 1L)[1L]
out[ind] <- 1L
}
return(out)
}
.return_missing <- broadcast:::.return_missing
scalar_relop_fun <- function(x, y, op) {
x.bits <- rawToBits(x)
y.bits <- rawToBits(y)
out <- op(x.bits, y.bits)
out <- packBits(out)
return(out)
}
# bitwise & ====
nres <- 10 * 5 * 5 * 3 # number of tests performed here
expected <- out <- vector("list", nres)
op <- "&"
i <- 1L
basefun <- function(x, y) {
out <- x & y
dim(out) <- bc_dim(x, y)
return(out)
}
for(iSample in 1:10) { # re-do tests with different random configurations
x.data <- sample(as.raw(0:255))
y.data <- sample(as.raw(0:255))
for(iDimX in sample(1:8, 3L)) { # different dimensions for x
x.dim <- test_make_dims(iDimX)
x.len <- prod(x.dim)
for(iDimY in sample(1:8, 3L)) { # different dimensions for y
y.dim <- test_make_dims(iDimY)
y.len <- prod(y.dim)
x <- array(x.data, dim = x.dim)
y <- array(y.data, dim = y.dim)
# PREPARE FOR TEST
tdim <- bc_dim(x, y)
# print(x)
# print(y)
# print(tdim)
# cat("\n")
# DO TESTS BY CASE:
if(is.null(tdim)) {
# CASE 1: result has no dimensions (for ex. when x and y are both scalars)
expected[[i]] <- basefun(as_raw(drop(x)), as_raw(drop(y)))
attributes(expected[[i]]) <- NULL # must be a vector if tdim == NULL
out[[i]] <- bc.bit(x, y, op)
}
else if(length(y) == 1L && length(x) == 1L) {
# CASE 2: x and y are both scalar arrays
expected[[i]] <- basefun(as.raw(x), as.raw(y))
out[[i]] <- bc.bit(x, y, op)
}
else if(length(x) == 1L && length(y) > 1L) {
# CASE 3: x is scalar, y is not
expected[[i]] <- basefun(as.raw(x), rep_dim(as_raw(y), tdim))
out[[i]] <- bc.bit(x, y, op)
}
else if(length(y) == 1L && length(x) > 1L) {
# CASE 4: y is scalar, x is not
expected[[i]] <- basefun(rep_dim(as_raw(x), tdim), as.raw(y))
out[[i]] <- bc.bit(x, y, op)
}
else {
# CASE 5: x and y are both non-reducible arrays
expected[[i]] <- basefun(rep_dim(as_raw(x), tdim), rep_dim(as_raw(y), tdim))
out[[i]] <- bc.bit(x, y, op)
}
# END CASES
# ensure correct dimensions:
dim(expected[[i]]) <- tdim
i <- i + 1L
}
}
}
enumerate <- enumerate + i # count number of tests
# test results:
expect_equal(
expected, out
)
# bitwise | ====
nres <- 10 * 5 * 5 * 3 # number of tests performed here
expected <- out <- vector("list", nres)
op <- "|"
i <- 1L
basefun <- function(x, y) {
out <- x |y
dim(out) <- bc_dim(x, y)
return(out)
}
for(iSample in 1:10) { # re-do tests with different random configurations
x.data <- sample(as.raw(0:255))
y.data <- sample(as.raw(0:255))
for(iDimX in sample(1:8, 3L)) { # different dimensions for x
x.dim <- test_make_dims(iDimX)
x.len <- prod(x.dim)
for(iDimY in sample(1:8, 3L)) { # different dimensions for y
y.dim <- test_make_dims(iDimY)
y.len <- prod(y.dim)
x <- array(x.data, dim = x.dim)
y <- array(y.data, dim = y.dim)
# PREPARE FOR TEST
tdim <- bc_dim(x, y)
# print(x)
# print(y)
# print(tdim)
# cat("\n")
# DO TESTS BY CASE:
if(is.null(tdim)) {
# CASE 1: result has no dimensions (for ex. when x and y are both scalars)
expected[[i]] <- basefun(as_raw(drop(x)), as_raw(drop(y)))
attributes(expected[[i]]) <- NULL # must be a vector if tdim == NULL
out[[i]] <- bc.bit(x, y, op)
}
else if(length(y) == 1L && length(x) == 1L) {
# CASE 2: x and y are both scalar arrays
expected[[i]] <- basefun(as.raw(x), as.raw(y))
out[[i]] <- bc.bit(x, y, op)
}
else if(length(x) == 1L && length(y) > 1L) {
# CASE 3: x is scalar, y is not
expected[[i]] <- basefun(as.raw(x), rep_dim(as_raw(y), tdim))
out[[i]] <- bc.bit(x, y, op)
}
else if(length(y) == 1L && length(x) > 1L) {
# CASE 4: y is scalar, x is not
expected[[i]] <- basefun(rep_dim(as_raw(x), tdim), as.raw(y))
out[[i]] <- bc.bit(x, y, op)
}
else {
# CASE 5: x and y are both non-reducible arrays
expected[[i]] <- basefun(rep_dim(as_raw(x), tdim), rep_dim(as_raw(y), tdim))
out[[i]] <- bc.bit(x, y, op)
}
# END CASES
# ensure correct dimensions:
dim(expected[[i]]) <- tdim
i <- i + 1L
}
}
}
enumerate <- enumerate + i # count number of tests
# test results:
expect_equal(
expected, out
)
# bitwise xor ====
nres <- 10 * 5 * 5 * 3 # number of tests performed here
expected <- out <- vector("list", nres)
op <- "xor"
i <- 1L
basefun <- function(x, y) {
out <- xor(x, y)
dim(out) <- bc_dim(x, y)
return(out)
}
for(iSample in 1:10) { # re-do tests with different random configurations
x.data <- sample(as.raw(0:255))
y.data <- sample(as.raw(0:255))
for(iDimX in sample(1:8, 3L)) { # different dimensions for x
x.dim <- test_make_dims(iDimX)
x.len <- prod(x.dim)
for(iDimY in sample(1:8, 3L)) { # different dimensions for y
y.dim <- test_make_dims(iDimY)
y.len <- prod(y.dim)
x <- array(x.data, dim = x.dim)
y <- array(y.data, dim = y.dim)
# PREPARE FOR TEST
tdim <- bc_dim(x, y)
# print(x)
# print(y)
# print(tdim)
# cat("\n")
# DO TESTS BY CASE:
if(is.null(tdim)) {
# CASE 1: result has no dimensions (for ex. when x and y are both scalars)
expected[[i]] <- basefun(as_raw(drop(x)), as_raw(drop(y)))
attributes(expected[[i]]) <- NULL # must be a vector if tdim == NULL
out[[i]] <- bc.bit(x, y, op)
}
else if(length(y) == 1L && length(x) == 1L) {
# CASE 2: x and y are both scalar arrays
expected[[i]] <- basefun(as.raw(x), as.raw(y))
out[[i]] <- bc.bit(x, y, op)
}
else if(length(x) == 1L && length(y) > 1L) {
# CASE 3: x is scalar, y is not
expected[[i]] <- basefun(as.raw(x), rep_dim(as_raw(y), tdim))
out[[i]] <- bc.bit(x, y, op)
}
else if(length(y) == 1L && length(x) > 1L) {
# CASE 4: y is scalar, x is not
expected[[i]] <- basefun(rep_dim(as_raw(x), tdim), as.raw(y))
out[[i]] <- bc.bit(x, y, op)
}
else {
# CASE 5: x and y are both non-reducible arrays
expected[[i]] <- basefun(rep_dim(as_raw(x), tdim), rep_dim(as_raw(y), tdim))
out[[i]] <- bc.bit(x, y, op)
}
# END CASES
# ensure correct dimensions:
dim(expected[[i]]) <- tdim
i <- i + 1L
}
}
}
enumerate <- enumerate + i # count number of tests
# test results:
expect_equal(
expected, out
)
# bitwise nand ====
nres <- 10 * 5 * 5 * 3 # number of tests performed here
expected <- out <- vector("list", nres)
op <- "nand"
i <- 1L
basefun <- function(x, y) {
out <- !x & !y
dim(out) <- bc_dim(x, y)
return(out)
}
for(iSample in 1:10) { # re-do tests with different random configurations
x.data <- sample(as.raw(0:255))
y.data <- sample(as.raw(0:255))
for(iDimX in sample(1:8, 3L)) { # different dimensions for x
x.dim <- test_make_dims(iDimX)
x.len <- prod(x.dim)
for(iDimY in sample(1:8, 3L)) { # different dimensions for y
y.dim <- test_make_dims(iDimY)
y.len <- prod(y.dim)
x <- array(x.data, dim = x.dim)
y <- array(y.data, dim = y.dim)
# PREPARE FOR TEST
tdim <- bc_dim(x, y)
# print(x)
# print(y)
# print(tdim)
# cat("\n")
# DO TESTS BY CASE:
if(is.null(tdim)) {
# CASE 1: result has no dimensions (for ex. when x and y are both scalars)
expected[[i]] <- basefun(as_raw(drop(x)), as_raw(drop(y)))
attributes(expected[[i]]) <- NULL # must be a vector if tdim == NULL
out[[i]] <- bc.bit(x, y, op)
}
else if(length(y) == 1L && length(x) == 1L) {
# CASE 2: x and y are both scalar arrays
expected[[i]] <- basefun(as.raw(x), as.raw(y))
out[[i]] <- bc.bit(x, y, op)
}
else if(length(x) == 1L && length(y) > 1L) {
# CASE 3: x is scalar, y is not
expected[[i]] <- basefun(as.raw(x), rep_dim(as_raw(y), tdim))
out[[i]] <- bc.bit(x, y, op)
}
else if(length(y) == 1L && length(x) > 1L) {
# CASE 4: y is scalar, x is not
expected[[i]] <- basefun(rep_dim(as_raw(x), tdim), as.raw(y))
out[[i]] <- bc.bit(x, y, op)
}
else {
# CASE 5: x and y are both non-reducible arrays
expected[[i]] <- basefun(rep_dim(as_raw(x), tdim), rep_dim(as_raw(y), tdim))
out[[i]] <- bc.bit(x, y, op)
}
# END CASES
# ensure correct dimensions:
dim(expected[[i]]) <- tdim
i <- i + 1L
}
}
}
enumerate <- enumerate + i # count number of tests
# test results:
expect_equal(
expected, out
)
# bitwise left shift ====
nres <- 10 * 5 * 5 * 3 # number of tests performed here
expected <- out <- vector("list", nres)
op <- "<<"
i <- 1L
basefun <- function(x, y) {
out <- mapply(\(x, y) rawShift(x, y), x, as.integer(y))
dim(out) <- bc_dim(x, y)
return(out)
}
for(iSample in 1:10) { # re-do tests with different random configurations
x.data <- sample(as.raw(0:255))
y.data <- sample(as.raw(0:8))
for(iDimX in sample(1:8, 3L)) { # different dimensions for x
x.dim <- test_make_dims(iDimX)
x.len <- prod(x.dim)
for(iDimY in sample(1:8, 3L)) { # different dimensions for y
y.dim <- test_make_dims(iDimY)
y.len <- prod(y.dim)
x <- array(x.data, dim = x.dim)
y <- array(y.data, dim = y.dim)
# PREPARE FOR TEST
tdim <- bc_dim(x, y)
# print(x)
# print(y)
# print(tdim)
# cat("\n")
# DO TESTS BY CASE:
if(is.null(tdim)) {
# CASE 1: result has no dimensions (for ex. when x and y are both scalars)
expected[[i]] <- basefun(as_raw(drop(x)), as_raw(drop(y)))
attributes(expected[[i]]) <- NULL # must be a vector if tdim == NULL
out[[i]] <- bc.bit(x, y, op)
}
else if(length(y) == 1L && length(x) == 1L) {
# CASE 2: x and y are both scalar arrays
expected[[i]] <- basefun(as.raw(x), as.raw(y))
out[[i]] <- bc.bit(x, y, op)
}
else if(length(x) == 1L && length(y) > 1L) {
# CASE 3: x is scalar, y is not
expected[[i]] <- basefun(as.raw(x), rep_dim(as_raw(y), tdim))
out[[i]] <- bc.bit(x, y, op)
}
else if(length(y) == 1L && length(x) > 1L) {
# CASE 4: y is scalar, x is not
expected[[i]] <- basefun(rep_dim(as_raw(x), tdim), as.raw(y))
out[[i]] <- bc.bit(x, y, op)
}
else {
# CASE 5: x and y are both non-reducible arrays
expected[[i]] <- basefun(rep_dim(as_raw(x), tdim), rep_dim(as_raw(y), tdim))
out[[i]] <- bc.bit(x, y, op)
}
# END CASES
# ensure correct dimensions:
dim(expected[[i]]) <- tdim
i <- i + 1L
}
}
}
enumerate <- enumerate + i # count number of tests
# test results:
expect_equal(
expected, out
)
# bitwise right shift ====
nres <- 10 * 5 * 5 * 3 # number of tests performed here
expected <- out <- vector("list", nres)
op <- ">>"
i <- 1L
basefun <- function(x, y) {
out <- mapply(\(x, y) rawShift(x, y), x, -as.integer(y))
dim(out) <- bc_dim(x, y)
return(out)
}
for(iSample in 1:10) { # re-do tests with different random configurations
x.data <- sample(as.raw(0:255))
y.data <- sample(as.raw(0:8))
for(iDimX in sample(1:8, 3L)) { # different dimensions for x
x.dim <- test_make_dims(iDimX)
x.len <- prod(x.dim)
for(iDimY in sample(1:8, 3L)) { # different dimensions for y
y.dim <- test_make_dims(iDimY)
y.len <- prod(y.dim)
x <- array(x.data, dim = x.dim)
y <- array(y.data, dim = y.dim)
# PREPARE FOR TEST
tdim <- bc_dim(x, y)
# print(x)
# print(y)
# print(tdim)
# cat("\n")
# DO TESTS BY CASE:
if(is.null(tdim)) {
# CASE 1: result has no dimensions (for ex. when x and y are both scalars)
expected[[i]] <- basefun(as_raw(drop(x)), as_raw(drop(y)))
attributes(expected[[i]]) <- NULL # must be a vector if tdim == NULL
out[[i]] <- bc.bit(x, y, op)
}
else if(length(y) == 1L && length(x) == 1L) {
# CASE 2: x and y are both scalar arrays
expected[[i]] <- basefun(as.raw(x), as.raw(y))
out[[i]] <- bc.bit(x, y, op)
}
else if(length(x) == 1L && length(y) > 1L) {
# CASE 3: x is scalar, y is not
expected[[i]] <- basefun(as.raw(x), rep_dim(as_raw(y), tdim))
out[[i]] <- bc.bit(x, y, op)
}
else if(length(y) == 1L && length(x) > 1L) {
# CASE 4: y is scalar, x is not
expected[[i]] <- basefun(rep_dim(as_raw(x), tdim), as.raw(y))
out[[i]] <- bc.bit(x, y, op)
}
else {
# CASE 5: x and y are both non-reducible arrays
expected[[i]] <- basefun(rep_dim(as_raw(x), tdim), rep_dim(as_raw(y), tdim))
out[[i]] <- bc.bit(x, y, op)
}
# END CASES
# ensure correct dimensions:
dim(expected[[i]]) <- tdim
i <- i + 1L
}
}
}
enumerate <- enumerate + i # count number of tests
# test results:
expect_equal(
expected, out
)
# bitwise equal ====
nres <- 10 * 5 * 5 * 3 # number of tests performed here
expected <- out <- vector("list", nres)
op <- "=="
i <- 1L
basefun <- function(x, y) {
out <- mapply(\(x, y)scalar_relop_fun(x, y, `==`), x, y)
dim(out) <- bc_dim(x, y)
return(out)
}
for(iSample in 1:10) { # re-do tests with different random configurations
x.data <- sample(as.raw(0:255))
y.data <- sample(as.raw(0:255))
for(iDimX in sample(1:8, 3L)) { # different dimensions for x
x.dim <- test_make_dims(iDimX)
x.len <- prod(x.dim)
for(iDimY in sample(1:8, 3L)) { # different dimensions for y
y.dim <- test_make_dims(iDimY)
y.len <- prod(y.dim)
x <- array(x.data, dim = x.dim)
y <- array(y.data, dim = y.dim)
# PREPARE FOR TEST
tdim <- bc_dim(x, y)
# print(x)
# print(y)
# print(tdim)
# cat("\n")
# DO TESTS BY CASE:
if(is.null(tdim)) {
# CASE 1: result has no dimensions (for ex. when x and y are both scalars)
expected[[i]] <- basefun(as_raw(drop(x)), as_raw(drop(y)))
attributes(expected[[i]]) <- NULL # must be a vector if tdim == NULL
out[[i]] <- bc.bit(x, y, op)
}
else if(length(y) == 1L && length(x) == 1L) {
# CASE 2: x and y are both scalar arrays
expected[[i]] <- basefun(as.raw(x), as.raw(y))
out[[i]] <- bc.bit(x, y, op)
}
else if(length(x) == 1L && length(y) > 1L) {
# CASE 3: x is scalar, y is not
expected[[i]] <- basefun(as.raw(x), rep_dim(as_raw(y), tdim))
out[[i]] <- bc.bit(x, y, op)
}
else if(length(y) == 1L && length(x) > 1L) {
# CASE 4: y is scalar, x is not
expected[[i]] <- basefun(rep_dim(as_raw(x), tdim), as.raw(y))
out[[i]] <- bc.bit(x, y, op)
}
else {
# CASE 5: x and y are both non-reducible arrays
expected[[i]] <- basefun(rep_dim(as_raw(x), tdim), rep_dim(as_raw(y), tdim))
out[[i]] <- bc.bit(x, y, op)
}
# END CASES
# ensure correct dimensions:
dim(expected[[i]]) <- tdim
i <- i + 1L
}
}
}
enumerate <- enumerate + i # count number of tests
# test results:
expect_equal(
expected, out
)
# bitwise unequal ====
nres <- 10 * 5 * 5 * 3 # number of tests performed here
expected <- out <- vector("list", nres)
op <- "!="
i <- 1L
basefun <- function(x, y) {
out <- xor(x, y)
dim(out) <- bc_dim(x, y)
return(out)
}
for(iSample in 1:10) { # re-do tests with different random configurations
x.data <- sample(as.raw(0:255))
y.data <- sample(as.raw(0:255))
for(iDimX in sample(1:8, 3L)) { # different dimensions for x
x.dim <- test_make_dims(iDimX)
x.len <- prod(x.dim)
for(iDimY in sample(1:8, 3L)) { # different dimensions for y
y.dim <- test_make_dims(iDimY)
y.len <- prod(y.dim)
x <- array(x.data, dim = x.dim)
y <- array(y.data, dim = y.dim)
# PREPARE FOR TEST
tdim <- bc_dim(x, y)
# print(x)
# print(y)
# print(tdim)
# cat("\n")
# DO TESTS BY CASE:
if(is.null(tdim)) {
# CASE 1: result has no dimensions (for ex. when x and y are both scalars)
expected[[i]] <- basefun(as_raw(drop(x)), as_raw(drop(y)))
attributes(expected[[i]]) <- NULL # must be a vector if tdim == NULL
out[[i]] <- bc.bit(x, y, op)
}
else if(length(y) == 1L && length(x) == 1L) {
# CASE 2: x and y are both scalar arrays
expected[[i]] <- basefun(as.raw(x), as.raw(y))
out[[i]] <- bc.bit(x, y, op)
}
else if(length(x) == 1L && length(y) > 1L) {
# CASE 3: x is scalar, y is not
expected[[i]] <- basefun(as.raw(x), rep_dim(as_raw(y), tdim))
out[[i]] <- bc.bit(x, y, op)
}
else if(length(y) == 1L && length(x) > 1L) {
# CASE 4: y is scalar, x is not
expected[[i]] <- basefun(rep_dim(as_raw(x), tdim), as.raw(y))
out[[i]] <- bc.bit(x, y, op)
}
else {
# CASE 5: x and y are both non-reducible arrays
expected[[i]] <- basefun(rep_dim(as_raw(x), tdim), rep_dim(as_raw(y), tdim))
out[[i]] <- bc.bit(x, y, op)
}
# END CASES
# ensure correct dimensions:
dim(expected[[i]]) <- tdim
i <- i + 1L
}
}
}
enumerate <- enumerate + i # count number of tests
# test results:
expect_equal(
expected, out
)
# bitwise smaller ====
nres <- 10 * 5 * 5 * 3 # number of tests performed here
expected <- out <- vector("list", nres)
op <- "<"
i <- 1L
basefun <- function(x, y) {
out <- !x & y
dim(out) <- bc_dim(x, y)
return(out)
}
for(iSample in 1:10) { # re-do tests with different random configurations
x.data <- sample(as.raw(0:255))
y.data <- sample(as.raw(0:255))
for(iDimX in sample(1:8, 3L)) { # different dimensions for x
x.dim <- test_make_dims(iDimX)
x.len <- prod(x.dim)
for(iDimY in sample(1:8, 3L)) { # different dimensions for y
y.dim <- test_make_dims(iDimY)
y.len <- prod(y.dim)
x <- array(x.data, dim = x.dim)
y <- array(y.data, dim = y.dim)
# PREPARE FOR TEST
tdim <- bc_dim(x, y)
# print(x)
# print(y)
# print(tdim)
# cat("\n")
# DO TESTS BY CASE:
if(is.null(tdim)) {
# CASE 1: result has no dimensions (for ex. when x and y are both scalars)
expected[[i]] <- basefun(as_raw(drop(x)), as_raw(drop(y)))
attributes(expected[[i]]) <- NULL # must be a vector if tdim == NULL
out[[i]] <- bc.bit(x, y, op)
}
else if(length(y) == 1L && length(x) == 1L) {
# CASE 2: x and y are both scalar arrays
expected[[i]] <- basefun(as.raw(x), as.raw(y))
out[[i]] <- bc.bit(x, y, op)
}
else if(length(x) == 1L && length(y) > 1L) {
# CASE 3: x is scalar, y is not
expected[[i]] <- basefun(as.raw(x), rep_dim(as_raw(y), tdim))
out[[i]] <- bc.bit(x, y, op)
}
else if(length(y) == 1L && length(x) > 1L) {
# CASE 4: y is scalar, x is not
expected[[i]] <- basefun(rep_dim(as_raw(x), tdim), as.raw(y))
out[[i]] <- bc.bit(x, y, op)
}
else {
# CASE 5: x and y are both non-reducible arrays
expected[[i]] <- basefun(rep_dim(as_raw(x), tdim), rep_dim(as_raw(y), tdim))
out[[i]] <- bc.bit(x, y, op)
}
# END CASES
# ensure correct dimensions:
dim(expected[[i]]) <- tdim
i <- i + 1L
}
}
}
enumerate <- enumerate + i # count number of tests
# test results:
expect_equal(
expected, out
)
# bitwise greater ====
nres <- 10 * 5 * 5 * 3 # number of tests performed here
expected <- out <- vector("list", nres)
op <- ">"
i <- 1L
basefun <- function(x, y) {
out <- x & !y
dim(out) <- bc_dim(x, y)
return(out)
}
for(iSample in 1:10) { # re-do tests with different random configurations
x.data <- sample(as.raw(0:255))
y.data <- sample(as.raw(0:255))
for(iDimX in sample(1:8, 3L)) { # different dimensions for x
x.dim <- test_make_dims(iDimX)
x.len <- prod(x.dim)
for(iDimY in sample(1:8, 3L)) { # different dimensions for y
y.dim <- test_make_dims(iDimY)
y.len <- prod(y.dim)
x <- array(x.data, dim = x.dim)
y <- array(y.data, dim = y.dim)
# PREPARE FOR TEST
tdim <- bc_dim(x, y)
# print(x)
# print(y)
# print(tdim)
# cat("\n")
# DO TESTS BY CASE:
if(is.null(tdim)) {
# CASE 1: result has no dimensions (for ex. when x and y are both scalars)
expected[[i]] <- basefun(as_raw(drop(x)), as_raw(drop(y)))
attributes(expected[[i]]) <- NULL # must be a vector if tdim == NULL
out[[i]] <- bc.bit(x, y, op)
}
else if(length(y) == 1L && length(x) == 1L) {
# CASE 2: x and y are both scalar arrays
expected[[i]] <- basefun(as.raw(x), as.raw(y))
out[[i]] <- bc.bit(x, y, op)
}
else if(length(x) == 1L && length(y) > 1L) {
# CASE 3: x is scalar, y is not
expected[[i]] <- basefun(as.raw(x), rep_dim(as_raw(y), tdim))
out[[i]] <- bc.bit(x, y, op)
}
else if(length(y) == 1L && length(x) > 1L) {
# CASE 4: y is scalar, x is not
expected[[i]] <- basefun(rep_dim(as_raw(x), tdim), as.raw(y))
out[[i]] <- bc.bit(x, y, op)
}
else {
# CASE 5: x and y are both non-reducible arrays
expected[[i]] <- basefun(rep_dim(as_raw(x), tdim), rep_dim(as_raw(y), tdim))
out[[i]] <- bc.bit(x, y, op)
}
# END CASES
# ensure correct dimensions:
dim(expected[[i]]) <- tdim
i <- i + 1L
}
}
}
enumerate <- enumerate + i # count number of tests
# test results:
expect_equal(
expected, out
)
# bitwise se ====
nres <- 10 * 5 * 5 * 3 # number of tests performed here
expected <- out <- vector("list", nres)
op <- "<="
i <- 1L
basefun <- function(x, y) {
out <- mapply(\(x, y)scalar_relop_fun(x, y, `<=`), x, y)
dim(out) <- bc_dim(x, y)
return(out)
}
for(iSample in 1:10) { # re-do tests with different random configurations
x.data <- sample(as.raw(0:255))
y.data <- sample(as.raw(0:255))
for(iDimX in sample(1:8, 3L)) { # different dimensions for x
x.dim <- test_make_dims(iDimX)
x.len <- prod(x.dim)
for(iDimY in sample(1:8, 3L)) { # different dimensions for y
y.dim <- test_make_dims(iDimY)
y.len <- prod(y.dim)
x <- array(x.data, dim = x.dim)
y <- array(y.data, dim = y.dim)
# PREPARE FOR TEST
tdim <- bc_dim(x, y)
# print(x)
# print(y)
# print(tdim)
# cat("\n")
# DO TESTS BY CASE:
if(is.null(tdim)) {
# CASE 1: result has no dimensions (for ex. when x and y are both scalars)
expected[[i]] <- basefun(as_raw(drop(x)), as_raw(drop(y)))
attributes(expected[[i]]) <- NULL # must be a vector if tdim == NULL
out[[i]] <- bc.bit(x, y, op)
}
else if(length(y) == 1L && length(x) == 1L) {
# CASE 2: x and y are both scalar arrays
expected[[i]] <- basefun(as.raw(x), as.raw(y))
out[[i]] <- bc.bit(x, y, op)
}
else if(length(x) == 1L && length(y) > 1L) {
# CASE 3: x is scalar, y is not
expected[[i]] <- basefun(as.raw(x), rep_dim(as_raw(y), tdim))
out[[i]] <- bc.bit(x, y, op)
}
else if(length(y) == 1L && length(x) > 1L) {
# CASE 4: y is scalar, x is not
expected[[i]] <- basefun(rep_dim(as_raw(x), tdim), as.raw(y))
out[[i]] <- bc.bit(x, y, op)
}
else {
# CASE 5: x and y are both non-reducible arrays
expected[[i]] <- basefun(rep_dim(as_raw(x), tdim), rep_dim(as_raw(y), tdim))
out[[i]] <- bc.bit(x, y, op)
}
# END CASES
# ensure correct dimensions:
dim(expected[[i]]) <- tdim
i <- i + 1L
}
}
}
enumerate <- enumerate + i # count number of tests
# test results:
expect_equal(
expected, out
)
# bitwise ge ====
nres <- 10 * 5 * 5 * 3 # number of tests performed here
expected <- out <- vector("list", nres)
op <- ">="
i <- 1L
basefun <- function(x, y) {
out <- mapply(\(x, y)scalar_relop_fun(x, y, `>=`), x, y)
dim(out) <- bc_dim(x, y)
return(out)
}
for(iSample in 1:10) { # re-do tests with different random configurations
x.data <- sample(as.raw(0:255))
y.data <- sample(as.raw(0:255))
for(iDimX in sample(1:8, 3L)) { # different dimensions for x
x.dim <- test_make_dims(iDimX)
x.len <- prod(x.dim)
for(iDimY in sample(1:8, 3L)) { # different dimensions for y
y.dim <- test_make_dims(iDimY)
y.len <- prod(y.dim)
x <- array(x.data, dim = x.dim)
y <- array(y.data, dim = y.dim)
# PREPARE FOR TEST
tdim <- bc_dim(x, y)
# print(x)
# print(y)
# print(tdim)
# cat("\n")
# DO TESTS BY CASE:
if(is.null(tdim)) {
# CASE 1: result has no dimensions (for ex. when x and y are both scalars)
expected[[i]] <- basefun(as_raw(drop(x)), as_raw(drop(y)))
attributes(expected[[i]]) <- NULL # must be a vector if tdim == NULL
out[[i]] <- bc.bit(x, y, op)
}
else if(length(y) == 1L && length(x) == 1L) {
# CASE 2: x and y are both scalar arrays
expected[[i]] <- basefun(as.raw(x), as.raw(y))
out[[i]] <- bc.bit(x, y, op)
}
else if(length(x) == 1L && length(y) > 1L) {
# CASE 3: x is scalar, y is not
expected[[i]] <- basefun(as.raw(x), rep_dim(as_raw(y), tdim))
out[[i]] <- bc.bit(x, y, op)
}
else if(length(y) == 1L && length(x) > 1L) {
# CASE 4: y is scalar, x is not
expected[[i]] <- basefun(rep_dim(as_raw(x), tdim), as.raw(y))
out[[i]] <- bc.bit(x, y, op)
}
else {
# CASE 5: x and y are both non-reducible arrays
expected[[i]] <- basefun(rep_dim(as_raw(x), tdim), rep_dim(as_raw(y), tdim))
out[[i]] <- bc.bit(x, y, op)
}
# END CASES
# ensure correct dimensions:
dim(expected[[i]]) <- tdim
i <- i + 1L
}
}
}
enumerate <- enumerate + i # count number of tests
# test results:
expect_equal(
expected, out
)
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