CRAN RC: 0.8.3

DESCRIPTION

@@ -1,7 +1,7 @@
 Type: Package
 Package: see
 Title: Model Visualisation Toolbox for 'easystats' and 'ggplot2'
-Version: 0.8.2.7
+Version: 0.8.3
 Authors@R: 
     c(person(given = "Daniel",
              family = "Lüdecke",
@@ -67,11 +67,11 @@ Imports:
     correlation (>= 0.8.4),
     datawizard (>= 0.9.1),
     effectsize (>= 0.8.6),
-    ggplot2 (>= 3.4.0),
-    insight (>= 0.19.8),
+    ggplot2 (>= 3.5.0),
+    insight (>= 0.19.10),
     modelbased (>= 0.8.7),
-    parameters (>= 0.21.5),
-    performance (>= 0.10.9)
+    parameters (>= 0.21.6),
+    performance (>= 0.11.0)
 Suggests:
     brms,
     curl,
@@ -119,4 +119,3 @@ Config/Needs/website:
     r-lib/pkgdown,
     easystats/easystatstemplate
 Config/rcmdcheck/ignore-inconsequential-notes: true
-Remotes: easystats/performance

NEWS.md

@@ -1,4 +1,4 @@
-# see (development version)
+# see 0.8.3
 
 ## Major changes
 

R/coord_radar.R

@@ -5,11 +5,13 @@
 #' @inheritParams ggplot2::coord_polar
 #' @param ... Other arguments to be passed to `ggproto`.
 #'
-#' @examplesIf require("datawizard") && require("ggplot2")
+#' @examples
+#' library(ggplot2)
+#'
 #' # Create a radar/spider chart with ggplot:
 #' data(iris)
 #' data <- aggregate(iris[-5], list(Species = iris$Species), mean)
-#' data <- data_to_long(
+#' data <- datawizard::data_to_long(
 #'   data,
 #'   c("Sepal.Length", "Sepal.Width", "Petal.Length", "Petal.Width")
 #' )

R/data_plot.R

@@ -103,10 +103,10 @@ data_plot <- function(x, ...) {
 #' model <- suppressWarnings(stan_glm(
 #'   Sepal.Length ~ Petal.Width + Species + Sepal.Width,
 #'   data = iris,
-#'   chains = 2, iter = 200
+#'   chains = 2, iter = 200, refresh = 0
 #' ))
 #'
-#' result <- hdi(model, ci = c(0.5, 0.75, 0.9, 0.95))
+#' result <- bayestestR::hdi(model, ci = c(0.5, 0.75, 0.9, 0.95))
 #' data <- data_plot(result, data = model)
 #'
 #' p <- ggplot(

R/plot.check_heteroscedasticity.R

@@ -7,11 +7,11 @@
 #'
 #' @return A ggplot2-object.
 #'
 #' @seealso See also the vignette about [`check_model()`](https://easystats.github.io/performance/articles/check_model.html).
 #'
-#' @examplesIf require("performance")
+#' @examples
 #' m <- lm(mpg ~ wt + cyl + gear + disp, data = mtcars)
-#' result <- check_heteroscedasticity(m)
+#' result <- performance::check_heteroscedasticity(m)
 #' result
 #' plot(result, data = m) # data required for pkgdown
 #' @export

R/plot.check_homogeneity.R

@@ -7,7 +7,9 @@
 #'
 #' @return A ggplot2-object.
 #'
-#' @examplesIf require("performance")
+#' @examples
+#' library(performance)
+#'
 #' model <<- lm(len ~ supp + dose, data = ToothGrowth)
 #' result <- check_homogeneity(model)
 #' result

R/plot.check_model.R

@@ -9,14 +9,16 @@
 #'
 #' @return A ggplot2-object.
 #'
 #' @seealso See also the vignette about [`check_model()`](https://easystats.github.io/performance/articles/check_model.html).
 #'
-#' @examplesIf require("performance") && require("patchwork")
+#' @examplesIf require("patchwork")
+#' library(performance)
+#'
 #' model <- lm(qsec ~ drat + wt, data = mtcars)
 #' plot(check_model(model))
 #'
 #' @export
 plot.see_check_model <- function(x,
                                  style = theme_lucid,
                                  colors = NULL,
                                  type = c("density", "discrete_dots", "discrete_interval", "discrete_both"),
@@ -41,7 +43,7 @@
   plot_type <- attr(x, "type")
   model_class <- attr(x, "model_class")
 
   if (missing(type) && !is.null(plot_type) && plot_type %in% c("density", "discrete_dots", "discrete_interval", "discrete_both")) {
     type <- plot_type
   } else {
     type <- match.arg(type)
@@ -177,7 +179,6 @@
         colors = colors,
         detrend = detrend,
         style = style
-
       )
     } else {
       p$QQ <- .plot_diag_qq(

R/plot.check_normality.R

@@ -24,22 +24,24 @@
 #'
 #' @return A ggplot2-object.
 #'
 #' @seealso See also the vignette about [`check_model()`](https://easystats.github.io/performance/articles/check_model.html).
 #'
-#' @examplesIf require("performance")
+#' @examples
+#' library(performance)
+#'
 #' m <<- lm(mpg ~ wt + cyl + gear + disp, data = mtcars)
 #' result <- check_normality(m)
 #' plot(result)
 #'
-#' @examplesIf require("performance") && require("qqplotr")
+#' @examplesIf require("qqplotr")
 #' plot(result, type = "qq", detrend = TRUE)
 #'
 #' @export
 plot.see_check_normality <- function(x,
                                      type = c("qq", "pp", "density"),
                                      data = NULL,
                                      size_line = 0.8,
-                                     size_point = 1.5,
+                                     size_point = 2,
                                      alpha = 0.2,
                                      dot_alpha = 0.8,
                                      colors = c("#3aaf85", "#1b6ca8"),
@@ -262,7 +264,7 @@
         )
       },
       ggplot2::geom_qq(
         mapping = if (detrend) ggplot2::aes(y = ggplot2::after_stat(.data$sample) - ggplot2::after_stat(.data$theoretical)),
         shape = 16,
         na.rm = TRUE,
         stroke = 0,

R/plot.check_predictions.R

@@ -53,9 +53,11 @@
 #'
 #' @return A ggplot2-object.
 #'
 #' @seealso See also the vignette about [`check_model()`](https://easystats.github.io/performance/articles/check_model.html).
 #'
-#' @examplesIf require("performance")
+#' @examples
+#' library(performance)
+#'
 #' model <- lm(Sepal.Length ~ Species * Petal.Width + Petal.Length, data = iris)
 #' check_predictions(model)
 #'
@@ -84,7 +86,7 @@
   check_range <- isTRUE(attributes(x)$check_range)
   plot_type <- attributes(x)$type
 
   if (missing(type) && !is.null(plot_type) && plot_type %in% c("density", "discrete_dots", "discrete_interval", "discrete_both")) {
     type <- plot_type
   } else {
     type <- match.arg(type)

R/plot.compare_parameters.R

@@ -14,15 +14,15 @@
 #'
 #' @return A ggplot2-object.
 #'
-#' @examplesIf require("insight") && require("parameters")
+#' @examples
 #' data(iris)
 #' lm1 <- lm(Sepal.Length ~ Species, data = iris)
 #' lm2 <- lm(Sepal.Length ~ Species + Petal.Length, data = iris)
 #' lm3 <- lm(Sepal.Length ~ Species * Petal.Length, data = iris)
-#' result <- compare_parameters(lm1, lm2, lm3)
+#' result <- parameters::compare_parameters(lm1, lm2, lm3)
 #' plot(result)
 #' @export
 plot.see_compare_parameters <- function(x,
                                         show_intercept = FALSE,
                                         size_point = 0.8,
                                         size_text = NA,
@@ -123,7 +123,7 @@
   # largest data points that are within this range. Thereby we have the pretty
   # values we can use as breaks and labels for the scale...
   if (exponentiated_coefs) {
     range <- 2^(-24:16)
     x_low <- which.min(min(x$CI_low) > range) - 1L
     x_high <- which.max(max(x$CI_high) < range)
     if (add_values) {

R/plot.estimate_contrasts.R

@@ -69,8 +69,10 @@ data_plot.estimate_contrasts <- function(x, data = NULL, ...) {
 #'
 #' @return A ggplot2-object.
 #'
-#' @examplesIf require("modelbased") && require("emmeans")
+#' @examplesIf require("emmeans")
 #' \donttest{
+#' library(modelbased)
+#'
 #' model <- lm(Sepal.Width ~ Species, data = iris)
 #' contrasts <- estimate_contrasts(model)
 #' means <- estimate_means(model)

R/plot.n_factors.R

@@ -106,9 +106,9 @@ data_plot.n_clusters <- data_plot.n_factors
 #'
 #' @return A ggplot2-object.
 #'
-#' @examplesIf require("parameters") && require("nFactors")
+#' @examplesIf require("nFactors")
 #' data(mtcars)
-#' result <- n_factors(mtcars, type = "PCA")
+#' result <- parameters::n_factors(mtcars, type = "PCA")
 #' result
 #'
 #' plot(result) # type = "bar" by default

R/plot.parameters_brms_meta.R

@@ -130,7 +130,7 @@ data_plot.parameters_brms_meta <- function(x, data = NULL, normalize_height = TR
 #'   prior(cauchy(0, 0.5), class = sd)
 #' )
 #' model <- suppressWarnings(
-#'   brm(yi | se(vi) ~ 1 + (1 | author), data = dat)
+#'   brm(yi | se(vi) ~ 1 + (1 | author), data = dat, refresh = 0, silent = 2)
 #' )
 #'
 #' # result

R/plot.performance_simres.R

@@ -32,7 +32,7 @@
 #' @export
 plot.see_performance_simres <- function(x,
                                         size_line = 0.8,
-                                        size_point = 1.5,
+                                        size_point = 2,
                                         alpha = 0.2,
                                         dot_alpha = 0.8,
                                         colors = c("#3aaf85", "#1b6ca8"),

R/scale_color_bluebrown.R

@@ -20,7 +20,7 @@
   pal <- palette_bluebrown(palette = palette, reverse = reverse)
 
   if (discrete) {
-    discrete_scale(aesthetics = aesthetics, paste0("bluebrown_", palette), palette = pal, ...)
+    discrete_scale(aesthetics = aesthetics, palette = pal, ...)
   } else {
     scale_color_gradientn(colours = pal(256), aesthetics = aesthetics, ...)
   }
@@ -93,12 +93,7 @@
   pal <- palette_bluebrown(palette = palette, reverse = reverse)
 
   if (discrete) {
-    discrete_scale(
-      aesthetics = aesthetics,
-      paste0("bluebrown_", palette),
-      palette = pal,
-      ...
-    )
+    discrete_scale(aesthetics = aesthetics, palette = pal, ...)
   } else {
     scale_fill_gradientn(colours = pal(256), aesthetics = aesthetics, ...)
   }
@@ -144,8 +139,6 @@
 # Palette --------------------------------------------------------------------
 
 
-
-
 bluebrown_colors_list <- c(
   `lightblue` = "#6DC0E0",
   `blue` = "#5B93AE",

R/scale_color_colorhex.R

@@ -51,7 +51,6 @@ scale_color_colorhex <- function(palette = 1014416,
   if (discrete) {
     discrete_scale(
       aesthetics = aesthetics,
-      scale_name = paste0("colorhex_", pal_name),
       palette = pal,
       ...
     )
@@ -126,12 +125,7 @@ scale_fill_colorhex <- function(palette = 1014416,
   pal <- palette_colorhex(palette = palette, reverse = reverse)
 
   if (discrete) {
-    discrete_scale(
-      aesthetics = aesthetics,
-      paste0("colorhex_", palette),
-      palette = pal,
-      ...
-    )
+    discrete_scale(aesthetics = aesthetics, palette = pal, ...)
   } else {
     scale_fill_gradientn(colours = pal(256), aesthetics = aesthetics, ...)
   }

R/scale_color_flat.R

@@ -38,7 +38,7 @@ scale_color_flat <- function(palette = "contrast",
   pal <- palette_flat(palette = palette, reverse = reverse)
 
   if (discrete) {
-    discrete_scale(aesthetics = aesthetics, paste0("flat_", palette), palette = pal, ...)
+    discrete_scale(aesthetics = aesthetics, palette = pal, ...)
   } else {
     scale_color_gradientn(colours = pal(256), aesthetics = aesthetics, ...)
   }
@@ -111,7 +111,7 @@ scale_fill_flat <- function(palette = "contrast",
   pal <- palette_flat(palette = palette, reverse = reverse)
 
   if (discrete) {
-    discrete_scale(aesthetics = aesthetics, paste0("flat_", palette), palette = pal, ...)
+    discrete_scale(aesthetics = aesthetics, palette = pal, ...)
   } else {
     scale_fill_gradientn(colours = pal(256), aesthetics = aesthetics, ...)
   }

R/scale_color_material.R

@@ -35,7 +35,7 @@ scale_color_material <- function(palette = "contrast",
   pal <- palette_material(palette = palette, reverse = reverse)
 
   if (discrete) {
-    discrete_scale(aesthetics = aesthetics, paste0("material_", palette), palette = pal, ...)
+    discrete_scale(aesthetics = aesthetics, palette = pal, ...)
   } else {
     scale_color_gradientn(colours = pal(256), aesthetics = aesthetics, ...)
   }
@@ -108,7 +108,7 @@ scale_fill_material <- function(palette = "contrast",
   pal <- palette_material(palette = palette, reverse = reverse)
 
   if (discrete) {
-    discrete_scale(aesthetics = aesthetics, paste0("material_", palette), palette = pal, ...)
+    discrete_scale(aesthetics = aesthetics, palette = pal, ...)
   } else {
     scale_fill_gradientn(colours = pal(256), aesthetics = aesthetics, ...)
   }

R/scale_color_metro.R

@@ -35,7 +35,7 @@
   pal <- palette_metro(palette = palette, reverse = reverse)
 
   if (discrete) {
-    discrete_scale(aesthetics = aesthetics, paste0("metro_", palette), palette = pal, ...)
+    discrete_scale(aesthetics = aesthetics, palette = pal, ...)
   } else {
     scale_color_gradientn(colours = pal(256), aesthetics = aesthetics, ...)
   }
@@ -108,7 +108,7 @@
   pal <- palette_metro(palette = palette, reverse = reverse)
 
   if (discrete) {
-    discrete_scale(aesthetics = aesthetics, paste0("metro_", palette), palette = pal, ...)
+    discrete_scale(aesthetics = aesthetics, palette = pal, ...)
   } else {
     scale_fill_gradientn(colours = pal(256), aesthetics = aesthetics, ...)
   }

R/scale_color_okabeito.R

@@ -60,7 +60,6 @@
 scale_color_okabeito <- function(palette = "full", reverse = FALSE, order = 1:9, aesthetics = "color", ...) {
   discrete_scale(
     aesthetics = aesthetics,
-    paste0("okabeito_", palette),
     palette = palette_okabeito(palette = palette, reverse = reverse, order = order),
     ...
   )
@@ -73,7 +72,6 @@ scale_color_okabeito <- function(palette = "full", reverse = FALSE, order = 1:9,
 scale_fill_okabeito <- function(palette = "full", reverse = FALSE, order = 1:9, aesthetics = "fill", ...) {
   discrete_scale(
     aesthetics = aesthetics,
-    paste0("okabeito_", palette),
     palette = palette_okabeito(palette = palette, reverse = reverse, order = order),
     ...
   )

R/scale_color_pizza.R

@@ -31,7 +31,7 @@
   pal <- palette_pizza(palette = palette, reverse = reverse)
 
   if (discrete) {
-    discrete_scale(aesthetics = aesthetics, paste0("pizza_", palette), palette = pal, ...)
+    discrete_scale(aesthetics = aesthetics, palette = pal, ...)
   } else {
     scale_color_gradientn(colours = pal(256), aesthetics = aesthetics, ...)
   }
@@ -100,7 +100,7 @@
   pal <- palette_pizza(palette = palette, reverse = reverse)
 
   if (discrete) {
-    discrete_scale(aesthetics = aesthetics, paste0("pizza_", palette), palette = pal, ...)
+    discrete_scale(aesthetics = aesthetics, palette = pal, ...)
   } else {
     scale_fill_gradientn(colours = pal(256), aesthetics = aesthetics, ...)
   }

R/scale_color_see.R

@@ -33,7 +33,7 @@ scale_color_see <- function(palette = "contrast",
   pal <- palette_see(palette = palette, reverse = reverse)
 
   if (discrete) {
-    discrete_scale(aesthetics = aesthetics, paste0("see_", palette), palette = pal, ...)
+    discrete_scale(aesthetics = aesthetics, palette = pal, ...)
   } else {
     scale_color_gradientn(colours = pal(256), aesthetics = aesthetics, ...)
   }
@@ -106,7 +106,7 @@ scale_fill_see <- function(palette = "contrast",
   pal <- palette_see(palette = palette, reverse = reverse)
 
   if (discrete) {
-    discrete_scale(aesthetics = aesthetics, paste0("see_", palette), palette = pal, ...)
+    discrete_scale(aesthetics = aesthetics, palette = pal, ...)
   } else {
     scale_fill_gradientn(colours = pal(256), aesthetics = aesthetics, ...)
   }

R/scale_color_social.R

@@ -30,7 +30,7 @@
   pal <- palette_social(palette = palette, reverse = reverse)
 
   if (discrete) {
-    discrete_scale(aesthetics = aesthetics, paste0("social_", palette), palette = pal, ...)
+    discrete_scale(aesthetics = aesthetics, palette = pal, ...)
   } else {
     scale_color_gradientn(colours = pal(256), aesthetics = aesthetics, ...)
   }
@@ -79,7 +79,7 @@
   pal <- palette_social(palette = palette, reverse = reverse)
 
   if (discrete) {
-    discrete_scale(aesthetics = aesthetics, paste0("social_", palette), palette = pal, ...)
+    discrete_scale(aesthetics = aesthetics, palette = pal, ...)
   } else {
     scale_fill_gradientn(colours = pal(256), aesthetics = aesthetics, ...)
   }