update vignette, using new spatialdata.data methods

Author: Artur-man

vignettes/SpatialData.plot.Rmd

@@ -168,10 +168,7 @@ Such labels could be morphological regions annotated by pathologists.
 
 ```{r merfish-read}
 dir.create(td <- tempfile())
-pa <- unzip_spd_demo(
-    zipname="merfish.zarr.zip", 
-    dest=td, source="biocOSN")
-(x <- readSpatialData(pa, anndataR=FALSE))
+(x <- MouseBrainMERFISH(td))
 ```
 
 There are only `r length(SpatialData::shape(x, "cells"))` cells, but 
@@ -207,10 +204,7 @@ 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(
-    zipname="visium_hd_3.0.0_io.zip", 
-    dest=td, source="biocOSN")
-(x <- readSpatialData(pa, images=4, shapes=3, tables=FALSE))
+(x <- MouseIntestineVisHD(td))
 ```
 
 ```{r visiumhd-plot}
@@ -226,10 +220,7 @@ Colorectal carcinoma, 25 MB; no shapes, no points.
 
 ```{r mibitof-read}
 dir.create(td <- tempfile())
-pa <- unzip_spd_demo(
-    zipname="mibitof.zip", 
-    dest=td, source="biocOSN")
-(x <- readSpatialData(pa, anndataR=FALSE))
+(x <- ColorectalCarcinomaMIBITOF(td)) 
 ```
 
 ```{r mibitof-plot, fig.width=10, fig.height=3}
@@ -246,10 +237,7 @@ Small lung adenocarcinoma, 250 MB; 1 image, 2 labels, 2 tables.
 
 ```{r mcmicro-read}
 dir.create(td <- tempfile())
-pa <- unzip_spd_demo(
-    zipname="mcmicro_io.zip", 
-    dest=td, source="biocOSN")
-(x <- readSpatialData(pa, anndataR=FALSE))
+x <- LungAdenocarcinomaMCMICRO(td)
 ```
 
 Getting channel names for the image:
@@ -273,34 +261,32 @@ plotSpatialData() + plotImage(x,
 
 ```{r steinbock-read}
 dir.create(td <- tempfile())
-pa <- unzip_spd_demo(
-    zipname="steinbock_io.zip", 
-    dest=td, source="biocOSN")
-x <- readSpatialData(pa, anndataR=FALSE)
+# x <- MulticancerSteinbock(td)
+# TODO: readSpatialData fails here, commenting out below code
 ```
 
 ### 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