CRAN submission: see 0.8.4 (#341)

* Update plot.n_factors.R

* delete unnecessary file

* effectsize vdiffr test

* add another vdiffr test

* Update NEWS.md

* also add merDeriv

* bump version

* get rid of ggrepel warnings

* size -> linewidth

* cran submission

DESCRIPTION

@@ -1,7 +1,7 @@
 Type: Package
 Package: see
 Title: Model Visualisation Toolbox for 'easystats' and 'ggplot2'
-Version: 0.8.3.7
+Version: 0.8.4
 Authors@R: 
     c(person(given = "Daniel",
              family = "Lüdecke",
@@ -91,6 +91,7 @@ Suggests:
     logspline,
     MASS,
     mclust,
+    merDeriv,
     mgcv,
     metafor,
     NbClust,
@@ -119,4 +120,3 @@ Config/Needs/website:
     r-lib/pkgdown,
     easystats/easystatstemplate
 Config/rcmdcheck/ignore-inconsequential-notes: true
-Remotes: easystats/performance

NEWS.md

@@ -1,7 +1,9 @@
-# see 0.8.3.1
+# see 0.8.4
 
 ## Minor Changes
 
+* Fixes warnings generated from the `{ggplot2}` 3.5.0 release.
+
 * Small adjustment to size of point geoms for `check_model()` plots.
 
 * More arguments to change base font sizes and geom sizes are now passed to

R/global_vars.R

@@ -10,6 +10,8 @@ utils::globalVariables(
     "grp",
     "Parameter",
     "predictor",
-    "ROPE_Equivalence"
+    "ROPE_Equivalence",
+    "x_intercept",
+    "y_max"
   )
 )

R/plot.check_homogeneity.R

@@ -66,7 +66,8 @@ plot.see_check_homogeneity <- function(x, data = NULL, ...) {
             stringsAsFactors = FALSE
           ),
           direction = "y",
-          segment.colour = NA
+          segment.colour = NA,
+          max.overlaps = Inf
         )
       } else {
         geom_label(
@@ -96,7 +97,8 @@ plot.see_check_homogeneity <- function(x, data = NULL, ...) {
             stringsAsFactors = FALSE
           ),
           direction = "y",
-          segment.colour = NA
+          segment.colour = NA,
+          max.overlaps = Inf
         )
       } else {
         geom_label(

R/plot.n_factors.R

@@ -25,7 +25,6 @@ data_plot.n_factors <- function(x, data = NULL, type = "bar", ...) {
 
   dataplot <- rbind(s1, s2[!s2[[variable]] %in% s1[[variable]], ])
 
-  # Add Variance explained
   if ("Variance_Explained" %in% names(attributes(x))) {
     dataplot$Variance_Cumulative <- NULL # Remove column and re add
     dataplot <- merge(
@@ -52,6 +51,7 @@ data_plot.n_factors <- function(x, data = NULL, type = "bar", ...) {
   rownames(dataplot) <- NULL
 
   # Labels and titles -----------------------------------------------------
+
   n_max <- sum(dataplot$n_Methods)
   axis_lab <- paste0("% of methods (out of ", n_max, ")")
 
@@ -67,7 +67,6 @@ data_plot.n_factors <- function(x, data = NULL, type = "bar", ...) {
       ylab = axis_lab
     )
   }
-  # Title
 
   attr(dataplot, "info")$title <- paste("How many", lab, "to retain")
   attr(dataplot, "info")$subtitle <- paste0("Number of ", lab, " considered optimal by various algorithm")
@@ -137,21 +136,25 @@ plot.see_n_factors <- function(x,
 
   # Base plot
   if (type == "area") {
+    segment_data <- data.frame(x_intercept = x$x[which.max(x$y)], y_max = max(x$y, na.rm = TRUE))
     p <- ggplot(x, aes(x = .data$x, y = .data$y)) +
       geom_area(fill = flat_colors("grey")) +
       geom_segment(
+        data = segment_data,
         aes(
-          x = .data$x[which.max(.data$y)],
-          xend = .data$x[which.max(.data$y)],
+          x = x_intercept,
+          xend = x_intercept,
           y = 0,
-          yend = max(.data$y)
+          yend = y_max
         ),
         color = flat_colors("red")
       ) +
-      geom_point(aes(x = .data$x[which.max(.data$y)], y = max(.data$y)),
+      geom_point(
+        data = segment_data,
+        aes(x = x_intercept, y = y_max),
         color = flat_colors("red")
       ) +
-      scale_x_continuous(breaks = 1:max(x$x)) +
+      scale_x_continuous(breaks = 1:max(x$x, na.rm = TRUE)) +
       add_plot_attributes(x)
   } else if (type == "line") {
     p <- ggplot(x, aes(y = .data$x, x = .data$y, colour = .data$group)) +
@@ -172,7 +175,6 @@ plot.see_n_factors <- function(x,
       scale_fill_manual(values = unname(flat_colors(c("grey", "red"))))
   }
 
-  # Add variance explained
   if ("Variance_Cumulative" %in% names(x)) {
     x$Varex_scaled <- x$Variance_Cumulative * max(x$y)
     p <- p +

tests/testthat/test-check_model.R

@@ -117,6 +117,7 @@ test_that("`check_model()` works if convergence issues", {
 test_that("`check_model()` works if convergence issues", {
   skip_on_cran()
   skip_if_not_installed("performance")
+  skip_if_not_installed("merDeriv")
   data(mtcars)
   m <- lm(mpg ~ wt + cyl + gear + disp, data = mtcars)
   set.seed(123)

tests/testthat/test-plot.effectsize_table.R

@@ -1,13 +1,9 @@
 test_that("`plot.see_effectsize_table()` works", {
-  library(effectsize)
   m <- aov(mpg ~ factor(am) * factor(cyl), data = mtcars)
-  result <- eta_squared(m)
-  expect_s3_class(plot(result), "gg")
-})
-
-test_that("`plot.see_equivalence_test()` works", {
-  library(effectsize)
-  m <- aov(mpg ~ factor(am) * factor(cyl), data = mtcars)
-  result <- eta_squared(m)
-  expect_s3_class(plot(result), "gg")
+  result <- effectsize::eta_squared(m)
+  set.seed(123)
+  vdiffr::expect_doppelganger(
+    title = "aov - eta_squared - dot plot",
+    fig = plot(result)
+  )
 })

tests/testthat/test-plot.n_factors.R

@@ -14,4 +14,10 @@ test_that("`plot.see_n_factors()` works", {
     title = "line graph",
     fig = plot(result, type = "line")
   )
+
+  set.seed(123)
+  vdiffr::expect_doppelganger(
+    title = "area graph",
+    fig = plot(result, type = "area")
+  )
 })