update spatialdata.data loaders

Author: Artur-man

vignettes/SpatialData.plot.Rmd

@@ -167,8 +167,7 @@ In this example data, we do not have a `label` for the `shape` polygons.
 Such labels could be morphological regions annotated by pathologists.
 
 ```{r merfish-read}
-dir.create(td <- tempfile())
-(x <- MouseBrainMERFISH(td))
+(x <- MouseBrainMERFISH())
 ```
 
 There are only `r length(SpatialData::shape(x, "cells"))` cells, but 
@@ -203,8 +202,7 @@ plotSpatialData() + plotImage(x) + bb | plotSpatialData() + plotImage(y)
 Mouse intestine, 1GB; 4 image resolutions and 3 shapes at 2, 8, and 16 $\mu$m.
 
 ```{r visiumhd-read}
-dir.create(td <- tempfile())
-(x <- MouseIntestineVisHD(td))
+(x <- MouseIntestineVisHD())
 ```
 
 ```{r visiumhd-plot}
@@ -219,8 +217,7 @@ plotSpatialData() + plotImage(x) + bb | plotSpatialData() + plotImage(y)
 Colorectal carcinoma, 25 MB; no shapes, no points.
 
 ```{r mibitof-read}
-dir.create(td <- tempfile())
-(x <- ColorectalCarcinomaMIBITOF(td)) 
+(x <- ColorectalCarcinomaMIBITOF()) 
 ```
 
 ```{r mibitof-plot, fig.width=10, fig.height=3}
@@ -236,8 +233,7 @@ wrap_plots(nrow=1, lapply(seq(3), \(.)
 Small lung adenocarcinoma, 250 MB; 1 image, 2 labels, 2 tables.
 
 ```{r mcmicro-read}
-dir.create(td <- tempfile())
-x <- LungAdenocarcinomaMCMICRO(td)
+x <- LungAdenocarcinomaMCMICRO()
 ```
 
 Getting channel names for the image:
@@ -260,33 +256,31 @@ plotSpatialData() + plotImage(x,
 4 different cancers (SCCHN, BCC, NSCLC, CRC), 820 MB; 14 images, 14 labels, 1 table.
 
 ```{r steinbock-read}
-dir.create(td <- tempfile())
-# x <- MulticancerSteinbock(td)
-# TODO: readSpatialData fails here, commenting out below code
+x <- MulticancerSteinbock()
 ```
 
 ### channels
 
 ```{r steinbock-ch}
-# plotSpatialData() + plotImage(x,
-#     i="Patient3_003_image",
-#     ch=c(6, 22, 39),
-#     c=c("blue", "cyan", "yellow"))
+plotSpatialData() + plotImage(x,
+    i="Patient3_003_image",
+    ch=c(6, 22, 39),
+    c=c("blue", "cyan", "yellow"))
 ```
 
 ### contrasts
 
 ```{r steinbock-cl, fig.width=9, fig.height=3}
-# i <- image(x, "Patient3_003_image")
-# image(x, "crop") <- i[, 200:400, 200:400]
-# lapply(list(c(0.2, 1), c(0, 0.8), c(0, 1.2)), \(.) {
-#     plotSpatialData() + plotImage(x, 
-#         i="crop", 
-#         ch=c(6, 22, 39), 
-#         cl=list(1, 1, .),
-#         c=c("blue", "cyan", "yellow")) +
-#         ggtitle(sprintf("[%s, %s]", .[1], .[2]))
-# }) |> wrap_plots(nrow=1) + plot_layout(guides="collect")
+i <- image(x, "Patient3_003_image")
+image(x, "crop") <- i[, 200:400, 200:400]
+lapply(list(c(0.2, 1), c(0, 0.8), c(0, 1.2)), \(.) {
+    plotSpatialData() + plotImage(x,
+        i="crop",
+        ch=c(6, 22, 39),
+        cl=list(1, 1, .),
+        c=c("blue", "cyan", "yellow")) +
+        ggtitle(sprintf("[%s, %s]", .[1], .[2]))
+}) |> wrap_plots(nrow=1) + plot_layout(guides="collect")
 ```
 
 # Masking