class renaming per https://github.com/HelenaLC/SpatialData/pull/178

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: SpatialData.plot
 Title: SpatialData visualization
 Depends: R (>= 4.6), SpatialData
-Version: 0.99.5
+Version: 0.99.6
 Description: Visualization suit for 'SpatialData' (R). Current functionality 
     includes handling of multiscale 'images', visualizing 'labels', 'points', 
     and 'shapes'. For the latter, POINT, POLYGON, and MULTIPOLYGON geometries 

R/plotFrame.R

@@ -6,7 +6,7 @@
 #' @param i character string or index; the label element to plot.
 #' @param assay character string; in case of \code{c} denoting a row name,
 #'   specifies which \code{assay} data to use (see \code{\link{valTable}}).
-#'   (ignored when \code{x} is a \code{PointFrame}).
+#'   (ignored when \code{x} is a \code{SpatialDataPoint}).
 #'
 #' @examples
 #' x <- file.path("extdata", "blobs.zarr")
@@ -38,18 +38,19 @@ NULL
 #' @importFrom ggplot2 aes theme scale_type geom_sf coord_sf
 #' @importFrom SpatialData transform
 #' @importFrom ggforce geom_circle
+#' @importFrom methods is
 #' @importFrom utils tail
 .plot <- \(x, y, key=NULL, n=Inf, assay=1, i=1, ...) {
-    if (is(y, "PointFrame")) {
+    if (is(y, "SpatialDataPoint")) {
         if (!is.null(key)) {
             fk <- feature_key(y)
-            y@data <- dplyr::filter(data(y), .data[[fk]] %in% key)
+            y<- dplyr::filter(y, .data[[fk]] %in% key)
         }
     }
     if (is.finite(n)) {
         n <- min(length(y), n)
         y <- y[sample(length(y), n)]
-        if (is(y, "ShapeFrame")) {
+        if (is(y, "SpatialDataShape")) {
             shape(x, i) <- y
         } else {
             point(x, i) <- y
@@ -72,11 +73,14 @@ NULL
             if (val %in% names(df)) {
                 if (scale_type(df[[arg]]) == "discrete")
                     df[[val]] <- factor(df[[arg]])
-                aes[[arg]] <- aes(.data[[val]])[[1]]
+                col <- match(arg, c("col", "color", "colour"))
+                .arg <- ifelse(!is.na(col), "colour", arg)
+                aes[[.arg]] <- aes(.data[[val]])[[1]]
                 dot[[arg]] <- NULL
             }
         }
     }
+
     if ("radius" %in% names(df))
         df <- st_buffer(df, df$radius)
     list(

R/plotImage.R

@@ -12,7 +12,7 @@
 #'   800 x 800px; use Inf to plot the lowest resolution available.
 #' @param ch image channel(s) to be used for plotting (defaults to 
 #'   the first channel(s) available); use \code{channels()} to see 
-#'   which channels are available for a given \code{ImageArray}
+#'   which channels are available for a given \code{SpatialDataImage}
 #' @param c character vector; colors to use for each channel. 
 #' @param cl list of length-2 numeric vectors (non-negative, increasing); 
 #'   specifies channel-wise contrast limits - defaults to [0, 1] for all 
@@ -128,7 +128,7 @@ NULL
 #' @importFrom methods is
 #' @noRd
 .is_rgb <- \(x) {
-    if (is(x, "ImageArray") &&
+    if (is(x, "SpatialDataImage") &&
         !is.null(md <- meta(x)))
         x <- channels(x)
     if (!is.vector(x)) stop("invalid 'x'")

inst/NEWS

@@ -1,3 +1,10 @@
+changes in version 0.99.6
+
+- renaming of 'SpatialData' classes
+- improved visualization of labels
+- fixed auto-contrasting for HnE images
+- fixed channel-merging for multi-plex images
+
 changes in version 0.99.5
 
 - fix visualization of circles

tests/testthat/test-plotArray.R

@@ -17,7 +17,7 @@ test_that("plotSpatialData()", {
 }
 
 test_that(".guess_scale", {
-    img <- ImageArray(
+    img <- SpatialDataImage(
         lys <- lapply(
             dim <- lapply(c(6, 3), \(.) c(3, rep(., 2))), \(.) 
             array(sample(seq_len(255), prod(.), replace=TRUE), dim=.)))

tests/testthat/test-plotImage.R

@@ -14,7 +14,7 @@ test_that(".is_rgb()", {
     expect_false(.is_rgb(c("r", "g", "g")))
     expect_true(.is_rgb(. <- c("r", "g", "b")))
     expect_true(.is_rgb(rev(.)))
-    # only works for 'ImageArray'
+    # only works for 'SpatialDataImage'
     expect_true(.is_rgb(image(x, 1)))
     expect_error(.is_rgb(label(x, 1)))
 })

tests/testthat/test-plotShape.R

@@ -1,5 +1,7 @@
+require(sf, quietly=TRUE)
 require(ggplot2, quietly=TRUE)
 require(SpatialData, quietly=TRUE)
+
 x <- file.path("extdata", "blobs.zarr")
 x <- system.file(x, package="SpatialData")
 x <- readSpatialData(x, tables=FALSE)
@@ -40,7 +42,7 @@ test_that("plotShape(),polygons", {
     geom <- layer_data(q)$geometry
     expect_s3_class(q, "ggplot")
     df <- centroids(y)
-    fd <- st_coordinates(geom)
+    fd <- st_coordinates(st_centroid(geom))
     .f <- \(.) as.matrix(.[,c(1,2)])
     expect_equivalent(.f(df), .f(fd))
     expect_s3_class(geom, "sfc_POLYGON")

tests/testthat/test-plotSpatialData.R

@@ -1,24 +1,24 @@
 test_that("regression test of overlays", {
-  x <- system.file("extdata", "blobs.zarr", package="SpatialData") |> 
-    readSpatialData()
-
-  p <- plotSpatialData()
-  # joint
-  all <- p +
-      plotImage(x) +
-      plotLabel(x, a=1/3) +
-      plotShape(x, 1) +
-      plotShape(x, 3) +
-      plotPoint(x, c="genes") +
-      ggplot2::ggtitle("layered")
-  # split
-  one <- list(
-      p + plotImage(x) + ggplot2::ggtitle("image"),
-      p + plotLabel(x) + ggplot2::ggtitle("labels"),
-      p + plotShape(x, 1) + ggplot2::ggtitle("circles"),
-      p + plotShape(x, 3) + ggplot2::ggtitle("polygons"),
-      p + plotPoint(x, c="genes") + ggplot2::ggtitle("points"))
-  fig <- patchwork::wrap_plots(c(list(all), one), nrow=2)
-
-  vdiffr::expect_doppelganger("overlays", fig)
+    zs <- system.file("extdata", "blobs.zarr", package="SpatialData")
+    x <- readSpatialData(zs)
+    
+    p <- plotSpatialData()
+    # joint
+    all <- p +
+        plotImage(x) +
+        plotLabel(x, a=1/3) +
+        plotShape(x, 1) +
+        plotShape(x, 3) +
+        plotPoint(x, col="genes") +
+        ggplot2::ggtitle("layered")
+    # split
+    one <- list(
+        p + plotImage(x) + ggplot2::ggtitle("image"),
+        p + plotLabel(x) + ggplot2::ggtitle("labels"),
+        p + plotShape(x, 1) + ggplot2::ggtitle("circles"),
+        p + plotShape(x, 3) + ggplot2::ggtitle("polygons"),
+        p + plotPoint(x, col="genes") + ggplot2::ggtitle("points"))
+    fig <- patchwork::wrap_plots(c(list(all), one), nrow=2)
+    
+    vdiffr::expect_doppelganger("overlays", fig)
 })