chore: Fix CI failures

.Rbuildignore

@@ -12,7 +12,7 @@ figure
 ggmapTemp.png
 README.html
 notes/
-tests/testthat/_snaps
+tests/testthat/_snaps/*/*.svg
 tests/testthat/Rplots.pdf
 ^.*\.Rproj$
 ^\.Rproj\.user$
@@ -37,3 +37,5 @@ ggduo_paper.txt
 ^CRAN-SUBMISSION$
 .vscode
 ^data-raw$
+^\.claude$
+^_dev$

.github/shiny-workflows/check.R

@@ -0,0 +1,34 @@
+#!/usr/bin/env Rscript
+
+# This script works in tandem with
+# rstudio/shiny-workflows/.github/workflows/R-CMD-check.yaml@v1 GHA job
+
+# Remove tests/testthat/_snaps from .Rbuildignore
+# This ensures snapshot tests are included in R CMD check but not in the package build for a CRAN submission
+
+# If not on macOS, skip vdiffr tests
+# This logic is tied to `ggally_expect_doppelganger()` in
+# tests/testthat/helper-doppelganger.R
+if ((!identical(tolower(Sys.info()[["sysname"]]), "darwin"))) {
+  quit(status = 0)
+}
+
+rbuildignore_path <- ".Rbuildignore"
+
+if (!file.exists(rbuildignore_path)) {
+  stop(".Rbuildignore file not found")
+}
+
+# Read the file
+lines <- readLines(rbuildignore_path)
+
+# Remove the line containing "tests/testthat/_snaps/"
+lines_filtered <- lines[!grepl("^tests/testthat/_snaps/", lines)]
+
+# Write back only if changes were made
+if (length(lines) != length(lines_filtered)) {
+  writeLines(lines_filtered, rbuildignore_path)
+  message("Removed 'tests/testthat/_snaps/' from .Rbuildignore")
+} else {
+  message("'tests/testthat/_snaps/' not found in .Rbuildignore")
+}

.gitignore

@@ -22,3 +22,5 @@ inst/doc
 doc
 Meta
 CRAN-RELEASE
+.claude/*.local.*
+_dev/

DESCRIPTION

@@ -64,6 +64,7 @@ Suggests:
     labelled,
     mapproj,
     maps (>= 3.1.0),
+    MASS,
     network (>= 1.17.1),
     nnet,
     rmarkdown,

NEWS.md

@@ -1,5 +1,19 @@
 # GGally (development version)
 
+* Fixed duplicate aesthetics warning in `ggsurv()` with upcoming ggplot2 version. Removed duplicate `lty` aesthetic mapping from confidence interval bounds. (#572)
+
+* Fixed `mapping_string()` to properly handle long aesthetic expressions by collapsing multi-line `deparse()` output. (#573)
+
+* Updated `fix_data()` to handle map objects correctly with ggplot2 >= 4.0.0 using `ggplot2::map_data()` instead of `fortify()`. (#573)
+
+* Wrapped documentation examples requiring optional packages (`{MASS}`, `{broom}`, `{network}`, `{sna}`, `{ggforce}`) in `if (require(...))` blocks to prevent errors when packages are not installed. (#573)
+
+* Added `{MASS}` to Suggests in DESCRIPTION to support density plot examples. (#573)
+
+* Updated `.Rbuildignore` to exclude `{vdiffr}` snapshot SVG files more specifically. (#573)
+
+* Added GitHub Actions check script to conditionally remove snapshot paths from `.Rbuildignore` for macOS testing. (#573)
+
 # GGally 2.4.0
 
 * Replace internal usage with the base pipe (`|>`). (Thank you @m-muecke! #554)

R/gg-plots.R

@@ -18,7 +18,7 @@ eval_data_col <- function(data, aes_col) {
 #' mapping <- ggplot2::aes(Petal.Length)
 #' mapping_string(mapping$x)
 mapping_string <- function(aes_col) {
-  gsub("^~(?:\\.data\\$)?", "", deparse(aes_col, 500L))
+  gsub("^~(?:\\.data\\$)?", "", paste0(deparse(aes_col, 500L), collapse = ""))
 }
 
 # is categories on the left?
@@ -208,15 +208,17 @@ ggally_smooth_lm <- function(data, mapping, ...) {
 #' p_ <- GGally::print_if_interactive
 #'
 #' data(tips)
-#' p_(ggally_density(tips, mapping = ggplot2::aes(x = total_bill, y = tip)))
-#' p_(ggally_density(
-#'   tips,
-#'   mapping = ggplot2::aes(total_bill, tip, fill = after_stat(level))
-#' ))
-#' p_(ggally_density(
-#'   tips,
-#'   mapping = ggplot2::aes(total_bill, tip, fill = after_stat(level))
-#' ) + ggplot2::scale_fill_gradient(breaks = c(0.05, 0.1, 0.15, 0.2)))
+#' if (require(MASS)) {
+#'   p_(ggally_density(tips, mapping = ggplot2::aes(x = total_bill, y = tip)))
+#'   p_(ggally_density(
+#'     tips,
+#'     mapping = ggplot2::aes(total_bill, tip, fill = after_stat(level))
+#'   ))
+#'   p_(ggally_density(
+#'     tips,
+#'     mapping = ggplot2::aes(total_bill, tip, fill = after_stat(level))
+#'   ) + ggplot2::scale_fill_gradient(breaks = c(0.05, 0.1, 0.15, 0.2)))
+#' }
 ggally_density <- function(data, mapping, ...) {
   rangeX <- range(eval_data_col(data, mapping$x), na.rm = TRUE)
   rangeY <- range(eval_data_col(data, mapping$y), na.rm = TRUE)
@@ -1751,19 +1753,21 @@ ggally_naDiag <- function(...) {
 #' p_ <- GGally::print_if_interactive
 #'
 #' data(tips)
-#' p_(ggally_autopoint(tips, mapping = aes(x = tip, y = total_bill)))
-#' p_(ggally_autopoint(tips, mapping = aes(x = tip, y = sex)))
-#' p_(ggally_autopoint(tips, mapping = aes(x = smoker, y = sex)))
-#' p_(ggally_autopoint(tips, mapping = aes(x = smoker, y = sex, color = day)))
-#' p_(ggally_autopoint(tips, mapping = aes(x = smoker, y = sex), size = 8))
-#' p_(ggally_autopoint(tips, mapping = aes(x = smoker, y = sex), alpha = .9))
-#'
-#' p_(ggpairs(
-#'   tips,
-#'   mapping = aes(colour = sex),
-#'   upper = list(discrete = "autopoint", combo = "autopoint", continuous = "autopoint"),
-#'   diag = list(discrete = "autopointDiag", continuous = "autopointDiag")
-#' ))
+#' if (require(ggforce)) {
+#'   p_(ggally_autopoint(tips, mapping = aes(x = tip, y = total_bill)))
+#'   p_(ggally_autopoint(tips, mapping = aes(x = tip, y = sex)))
+#'   p_(ggally_autopoint(tips, mapping = aes(x = smoker, y = sex)))
+#'   p_(ggally_autopoint(tips, mapping = aes(x = smoker, y = sex, color = day)))
+#'   p_(ggally_autopoint(tips, mapping = aes(x = smoker, y = sex), size = 8))
+#'   p_(ggally_autopoint(tips, mapping = aes(x = smoker, y = sex), alpha = .9))
+#'
+#'   p_(ggpairs(
+#'     tips,
+#'     mapping = aes(colour = sex),
+#'     upper = list(discrete = "autopoint", combo = "autopoint", continuous = "autopoint"),
+#'     diag = list(discrete = "autopointDiag", continuous = "autopointDiag")
+#'   ))
+#' }
 ggally_autopoint <- function(data, mapping, ...) {
   rlang::check_installed("ggforce")
 

R/ggcoef.R

@@ -27,18 +27,19 @@
 #' # Small function to display plots only if it's interactive
 #' p_ <- GGally::print_if_interactive
 #'
-#' library(broom)
-#' reg <- lm(Sepal.Length ~ Sepal.Width + Petal.Length + Petal.Width, data = iris)
-#' p_(ggcoef(reg))
-#' \donttest{
-#' d <- as.data.frame(Titanic)
-#' reg2 <- glm(Survived ~ Sex + Age + Class, family = binomial, data = d, weights = d$Freq)
-#' ggcoef(reg2, exponentiate = TRUE)
-#' ggcoef(
-#'   reg2,
-#'   exponentiate = TRUE, exclude_intercept = TRUE,
-#'   errorbar_height = .2, color = "blue", sort = "ascending"
-#' )
+#' if (require(broom)) {
+#'   reg <- lm(Sepal.Length ~ Sepal.Width + Petal.Length + Petal.Width, data = iris)
+#'   p_(ggcoef(reg))
+#'   \donttest{
+#'   d <- as.data.frame(Titanic)
+#'   reg2 <- glm(Survived ~ Sex + Age + Class, family = binomial, data = d, weights = d$Freq)
+#'   ggcoef(reg2, exponentiate = TRUE)
+#'   ggcoef(
+#'     reg2,
+#'     exponentiate = TRUE, exclude_intercept = TRUE,
+#'     errorbar_height = .2, color = "blue", sort = "ascending"
+#'   )
+#'   }
 #' }
 #' @export
 ggcoef <- function(

R/ggnet.R

@@ -139,34 +139,34 @@
 #' # Small function to display plots only if it's interactive
 #' p_ <- GGally::print_if_interactive
 #'
-#' library(network)
+#' if (require(network) && require(sna)) {
+#'   # random adjacency matrix
+#'   x           <- 10
+#'   ndyads      <- x * (x - 1)
+#'   density     <- x / ndyads
+#'   m           <- matrix(0, nrow = x, ncol = x)
+#'   dimnames(m) <- list(letters[1:x], letters[1:x])
+#'   m[row(m) != col(m)] <- runif(ndyads) < density
+#'   m
 #'
-#' # random adjacency matrix
-#' x           <- 10
-#' ndyads      <- x * (x - 1)
-#' density     <- x / ndyads
-#' m           <- matrix(0, nrow = x, ncol = x)
-#' dimnames(m) <- list(letters[1:x], letters[1:x])
-#' m[row(m) != col(m)] <- runif(ndyads) < density
-#' m
+#'   # random undirected network
+#'   n <- network::network(m, directed = FALSE)
+#'   n
 #'
-#' # random undirected network
-#' n <- network::network(m, directed = FALSE)
-#' n
+#'   ggnet(n, label = TRUE, alpha = 1, color = "white", segment.color = "black")
 #'
-#' ggnet(n, label = TRUE, alpha = 1, color = "white", segment.color = "black")
+#'   # random groups
+#'   g <- sample(letters[1:3], 10, replace = TRUE)
+#'   g
 #'
-#' # random groups
-#' g <- sample(letters[1:3], 10, replace = TRUE)
-#' g
+#'   # color palette
+#'   p <- c("a" = "steelblue", "b" = "forestgreen", "c" = "tomato")
 #'
-#' # color palette
-#' p <- c("a" = "steelblue", "b" = "forestgreen", "c" = "tomato")
+#'   p_(ggnet(n, node.group = g, node.color = p, label = TRUE, color = "white"))
 #'
-#' p_(ggnet(n, node.group = g, node.color = p, label = TRUE, color = "white"))
-#'
-#' # edge arrows on a directed network
-#' p_(ggnet(network(m, directed = TRUE), arrow.gap = 0.05, arrow.size = 10))
+#'   # edge arrows on a directed network
+#'   p_(ggnet(network(m, directed = TRUE), arrow.gap = 0.05, arrow.size = 10))
+#' }
 ggnet <- function(
   net,
   mode = "fruchtermanreingold",

R/ggnet2.R

@@ -198,57 +198,57 @@
 #' # Small function to display plots only if it's interactive
 #' p_ <- GGally::print_if_interactive
 #'
-#' library(network)
+#' if (require(network) && require(sna)) {
+#'   # random adjacency matrix
+#'   x           <- 10
+#'   ndyads      <- x * (x - 1)
+#'   density     <- x / ndyads
+#'   m           <- matrix(0, nrow = x, ncol = x)
+#'   dimnames(m) <- list(letters[1:x], letters[1:x])
+#'   m[row(m) != col(m)] <- runif(ndyads) < density
+#'   m
 #'
-#' # random adjacency matrix
-#' x           <- 10
-#' ndyads      <- x * (x - 1)
-#' density     <- x / ndyads
-#' m           <- matrix(0, nrow = x, ncol = x)
-#' dimnames(m) <- list(letters[1:x], letters[1:x])
-#' m[row(m) != col(m)] <- runif(ndyads) < density
-#' m
+#'   # random undirected network
+#'   n <- network::network(m, directed = FALSE)
+#'   n
 #'
-#' # random undirected network
-#' n <- network::network(m, directed = FALSE)
-#' n
+#'   p_(ggnet2(n, label = TRUE))
+#'   p_(ggnet2(n, label = TRUE, shape = 15))
+#'   p_(ggnet2(n, label = TRUE, shape = 15, color = "black", label.color = "white"))
 #'
-#' p_(ggnet2(n, label = TRUE))
-#' p_(ggnet2(n, label = TRUE, shape = 15))
-#' p_(ggnet2(n, label = TRUE, shape = 15, color = "black", label.color = "white"))
+#'   # add vertex attribute
+#'   x = network.vertex.names(n)
+#'   x = ifelse(x %in% c("a", "e", "i"), "vowel", "consonant")
+#'   n %v% "phono" = x
 #'
-#' # add vertex attribute
-#' x = network.vertex.names(n)
-#' x = ifelse(x %in% c("a", "e", "i"), "vowel", "consonant")
-#' n %v% "phono" = x
+#'   p_(ggnet2(n, color = "phono"))
+#'   p_(ggnet2(n, color = "phono", palette = c("vowel" = "gold", "consonant" = "grey")))
+#'   p_(ggnet2(n, shape = "phono", color = "phono"))
 #'
-#' p_(ggnet2(n, color = "phono"))
-#' p_(ggnet2(n, color = "phono", palette = c("vowel" = "gold", "consonant" = "grey")))
-#' p_(ggnet2(n, shape = "phono", color = "phono"))
+#'   if (require(RColorBrewer)) {
 #'
-#' if (require(RColorBrewer)) {
+#'     # random groups
+#'     n %v% "group" <- sample(LETTERS[1:3], 10, replace = TRUE)
 #'
-#'   # random groups
-#'   n %v% "group" <- sample(LETTERS[1:3], 10, replace = TRUE)
+#'     p_(ggnet2(n, color = "group", palette = "Set2"))
 #'
-#'   p_(ggnet2(n, color = "group", palette = "Set2"))
+#'   }
 #'
-#' }
-#'
-#' # random weights
-#' n %e% "weight" <- sample(1:3, network.edgecount(n), replace = TRUE)
-#' p_(ggnet2(n, edge.size = "weight", edge.label = "weight"))
+#'   # random weights
+#'   n %e% "weight" <- sample(1:3, network.edgecount(n), replace = TRUE)
+#'   p_(ggnet2(n, edge.size = "weight", edge.label = "weight"))
 #'
-#' # edge arrows on a directed network
-#' p_(ggnet2(network(m, directed = TRUE), arrow.gap = 0.05, arrow.size = 10))
+#'   # edge arrows on a directed network
+#'   p_(ggnet2(network(m, directed = TRUE), arrow.gap = 0.05, arrow.size = 10))
 #'
-#' # Padgett's Florentine wedding data
-#' data(flo, package = "network")
-#' flo
+#'   # Padgett's Florentine wedding data
+#'   data(flo, package = "network")
+#'   flo
 #'
-#' p_(ggnet2(flo, label = TRUE))
-#' p_(ggnet2(flo, label = TRUE, label.trim = 4, vjust = -1, size = 3, color = 1))
-#' p_(ggnet2(flo, label = TRUE, size = 12, color = "white"))
+#'   p_(ggnet2(flo, label = TRUE))
+#'   p_(ggnet2(flo, label = TRUE, label.trim = 4, vjust = -1, size = 3, color = 1))
+#'   p_(ggnet2(flo, label = TRUE, size = 12, color = "white"))
+#' }
 ggnet2 <- function(
   net,
   mode = "fruchtermanreingold",

R/ggnetworkmap.R

@@ -37,14 +37,11 @@
 #' @importFrom dplyr bind_rows
 #' @importFrom utils installed.packages
 #' @examples
-#' library(dplyr)
 #' # small function to display plots only if it's interactive
 #' p_ <- GGally::print_if_interactive
 #'
-#' invisible(lapply(c("ggplot2", "maps", "network", "sna"), base::library, character.only = TRUE))
-#'
-#' ## Example showing great circles on a simple map of the USA
-#' if (require(airports) && require(network) && require(sna)) {
+#' if (require(dplyr) && require(network) && require(sna) &&
+#'     require(airports) && require(maps)) {
 #'   dms_to_number <- function(dms) {
 #'     parts <- strsplit(dms, "-")[[1]]
 #'     degrees <- as.numeric(parts[1])
@@ -113,7 +110,8 @@
 #'   data(twitter_spambots)
 #'
 #'   # create a world map
-#'   world <- fortify(map("world", plot = FALSE, fill = TRUE))
+#'   map_data_fn <- if (packageVersion("ggplot2") >= "4.0.0") ggplot2::map_data else ggplot2::fortify
+#'   world <- map_data_fn(map("world", plot = FALSE, fill = TRUE))
 #'   world <- ggplot(world, aes(x = long, y = lat)) +
 #'     geom_polygon(aes(group = group),
 #'       color = "grey65",