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scale matching in mask(); fix channels() #232

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Merged
HelenaLC merged 4 commits into from
Jun 4, 2026
Merged

scale matching in mask(); fix channels() #232

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72c6e7d
channels() bug fix
HelenaLC Jun 4, 2026
a0395e6
fmatch scales in mask()
HelenaLC Jun 4, 2026
7e3d7da
fix [,sdArray docs
HelenaLC Jun 4, 2026
a866bd8
let channels() handle non-list spec
HelenaLC Jun 4, 2026
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23 changes: 14 additions & 9 deletions R/mask.R
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Original file line number Diff line number Diff line change
Expand Up @@ -93,20 +93,25 @@ setGeneric("mask_i_by_j", \(i, j, ...) standardGeneric("mask_i_by_j"))
setMethod("mask_i_by_j",
c("SpatialDataImage", "SpatialDataLabel"),
\(i, j, how=NULL, ...) {
.wh <- \(.) {
ds <- dim(.); if (length(ds) == 3) ds <- ds[-1]
metadata(.)$wh %||% list(c(0, ds[2]), c(0, ds[1]))
}
stopifnot(
"image/label width mismatch"=.wh(i)[[1]] == .wh(j)[[1]],
"image/label height mismatch"=.wh(i)[[2]] == .wh(j)[[2]])
di <- lapply(data(i, NULL), dim)
dj <- lapply(data(j, NULL), dim)
ij <- outer(
seq_along(di),
seq_along(dj),
Vectorize(\(i, j) identical(tail(di[[i]], length(dj[[j]])), dj[[j]])))
ij <- which(ij, arr.ind=TRUE)
if (nrow(ij) == 0)
stop("couldn't find shared multiscales level between label/image;",
" need at least one data() pair with identical dimensions")
ki <- ij[1, 1]
kj <- ij[1, 2]
if (is.null(how)) {
message("Missing 'how'; defaulting to 'mean'")
how <- "mean"
}
.j <- as(data(j), "sparseVector")
.j <- as(data(j, kj), "sparseVector")
.j <- as.vector(.j[ok <- .j > 0])
mx <- apply(data(i), 1, \(.i) {
mx <- apply(data(i, ki), 1, \(.i) {
.i <- as(.i, "sparseVector")
.i <- as.vector(.i[ok])
tapply(.i, .j, how)
Expand Down
11 changes: 8 additions & 3 deletions R/sdArray.R
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Original file line number Diff line number Diff line change
Expand Up @@ -131,7 +131,10 @@ setMethod("data_type", "DelayedArray", \(x) {
v <- tryCatch(.ome_ver(x), error=\(e) NULL)
if (is.null(v)) return()
if (v == "0.5") x <- x$ome
unlist(x$omero$channels)
# NOTE: can't use 'vapply' as we
# have encountered integer 'label's
x <- x$omero$channels
x$label %||% unlist(lapply(x, `[[`, "label"))
}

#' @export
Expand Down Expand Up @@ -173,8 +176,6 @@ setMethod("channels", "SpatialDataElement", \(x, ...) stop("only 'images' have c
# https://github.com/Huber-group-EMBL/Rarr/blob/1795c676e2ac81a9ba2a592c7210cc59036544b6/R/utils.R#L74-L79
.sub <- \(x, ix) rlang::inject(x[!!!ix, drop=FALSE])

#' @exportMethod [
#' @rdname SpatialDataArray
#' @importFrom utils head tail
.sub_sda <- \(x, yx, z=list()) {
#x <- label(sd); yx <- list(1:10, 1:10); z <- list()
Expand Down Expand Up @@ -208,13 +209,17 @@ setMethod("channels", "SpatialDataElement", \(x, ...) stop("only 'images' have c
x
}

#' @exportMethod [
#' @rdname SpatialDataArray
setMethod("[", "SpatialDataImage", \(x, i, j, k, ..., drop=FALSE) {
if (missing(i)) i <- TRUE
if (missing(j)) j <- TRUE else if (isFALSE(j)) j <- 0 else .check_jk(j, "j")
if (missing(k)) k <- TRUE else if (isFALSE(k)) k <- 0 else .check_jk(k, "k")
.sub_sda(x, yx=list(j, k), z=list(i))
})

#' @exportMethod [
#' @rdname SpatialDataArray
setMethod("[", "SpatialDataLabel", \(x, i, j, ..., drop=FALSE) {
if (missing(i)) i <- TRUE else if (isFALSE(i)) i <- 0 else .check_jk(i, "i")
if (missing(j)) j <- TRUE else if (isFALSE(j)) j <- 0 else .check_jk(j, "j")
Expand Down
7 changes: 5 additions & 2 deletions man/SpatialDataArray.Rd
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8 changes: 7 additions & 1 deletion tests/testthat/test-mask.R
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Original file line number Diff line number Diff line change
Expand Up @@ -46,6 +46,12 @@ test_that("mask,sdImage,sdLabel", {
expect_equivalent(
assay(tables(y)[[2]]),
assay(tables(x)[[1]]))

# no matching scale
.i <- image(x, "blobs_multiscale_image")
.i@data <- lapply(.i@data, \(.) .[,,-1])
.x <- x; image(.x, i) <- .i
expect_error(mask(.x, i, j))
})

test_that("mask w/ transform", {
Expand All @@ -58,7 +64,7 @@ test_that("mask w/ transform", {
l <- list(1,.1,.1); t <- "scale"
a <- addCT(a, name=t, type=t, data=l)
y <- x; y[[layer(y, i)]][[i]] <- a
expect_error(mask(y, i, j, t))
expect_no_error(mask(y, i, j, t))

# aligned
l <- c(list(1), CTdata(b, t <- "scale"))
Expand Down
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