implement transformations for labels before plotting

Author: Artur-man

R/plotLabel.R

@@ -3,6 +3,7 @@
 #' 
 #' @param x \code{SpatialData} object.
 #' @param i character string or index; the label element to plot.
+#' @param j name of target coordinate system. 
 #' @param k index of the scale of an image; by default (NULL), will auto-select 
 #'   scale in order to minimize memory-usage and blurring for a target size of 
 #'   800 x 800px; use Inf to plot the lowest resolution available.
@@ -50,12 +51,18 @@ NULL
 #'   scale_fill_manual scale_fill_gradientn
 #'   aes geom_raster theme unit guides guide_legend
 #' @export
-setMethod("plotLabel", "SpatialData", \(x, i=1, k=NULL, c=NULL, 
+setMethod("plotLabel", "SpatialData", \(x, i=1, j=1, k=NULL, c=NULL, 
     a=0.5, pal=c("red", "green"), nan=NA, assay=1) {
     if (is.numeric(i)) i <- labelNames(x)[i]
     i <- match.arg(i, labelNames(x))
-    y <- as.matrix(.get_multiscale_data(label(x, i), k))
-    df <- data.frame(x=c(col(y)), y=c(row(y)), z=c(y))
+    y <- label(x, i)
+    ym <- as.matrix(.get_multiscale_data(label(x, i), k))
+    df <- data.frame(x=c(col(ym)), y=c(row(ym)), z=c(ym))
+    # transformation
+    if (is.numeric(j))
+      j <- CTname(y)[j]
+    ts <- CTpath(x, i, j)
+    df[,c("x", "y")] <- .trans_xy(df[,c("x", "y")], ts)
     aes <- aes(.data[["x"]], .data[["y"]])
     if (!is.null(c)) {
         stopifnot(length(c) == 1, is.character(c))

man/plotLabel.Rd

@@ -61,6 +61,9 @@ test_that("plotLabel()", {
     expect_s3_class(q, "ggplot")
     expect_equal(q$coordinates$ratio, 1)
     expect_is(q$layers[[1]]$mapping$fill, "quosure")
+    # multiscale
+    y <- label(x, "blobs_multiscale_labels")
+    y <- y[,seq_len(32)] # same thing but different
     # alpha
     q <- p + plotLabel(x, i, a=a <- runif(1))
     expect_identical(q$layers[[1]]$aes_params$alpha, a)

tests/testthat/test-plotArray.R

@@ -168,7 +168,7 @@ Such labels could be morphological regions annotated by pathologists.
 
 ```{r merfish-read}
 dir.create(td <- tempfile())
-pa <- unzip_spd_demo(
+pa <- SpatialData.data:::.unzip_spd_demo(
     zipname="merfish.zarr.zip", 
     dest=td, source="biocOSN")
 (x <- readSpatialData(pa, anndataR=FALSE))
@@ -207,7 +207,7 @@ Mouse intestine, 1GB; 4 image resolutions and 3 shapes at 2, 8, and 16 $\mu$m.
 
 ```{r visiumhd-read}
 dir.create(td <- tempfile())
-pa <- unzip_spd_demo(
+pa <- SpatialData.data:::.unzip_spd_demo(
     zipname="visium_hd_3.0.0_io.zip", 
     dest=td, source="biocOSN")
 (x <- readSpatialData(pa, images=4, shapes=3, tables=FALSE))
@@ -226,7 +226,7 @@ Colorectal carcinoma, 25 MB; no shapes, no points.
 
 ```{r mibitof-read}
 dir.create(td <- tempfile())
-pa <- unzip_spd_demo(
+pa <- SpatialData.data:::.unzip_spd_demo(
     zipname="mibitof.zip", 
     dest=td, source="biocOSN")
 (x <- readSpatialData(pa, anndataR=FALSE))
@@ -246,7 +246,7 @@ Small lung adenocarcinoma, 250 MB; 1 image, 2 labels, 2 tables.
 
 ```{r mcmicro-read}
 dir.create(td <- tempfile())
-pa <- unzip_spd_demo(
+pa <- SpatialData.data:::.unzip_spd_demo(
     zipname="mcmicro_io.zip", 
     dest=td, source="biocOSN")
 (x <- readSpatialData(pa, anndataR=FALSE))
@@ -273,7 +273,7 @@ plotSpatialData() + plotImage(x,
 
 ```{r steinbock-read}
 dir.create(td <- tempfile())
-pa <- unzip_spd_demo(
+pa <- SpatialData.data:::.unzip_spd_demo(
     zipname="steinbock_io.zip", 
     dest=td, source="biocOSN")
 x <- readSpatialData(pa, anndataR=FALSE)