Adding test to check if plot-methods broke (#390)

* Adding test to check if plot-methods broke
Fixes #364

* add test

* lintr

* update

* update

* resolve TODO

* revert change

* styler

* update test

* update snap

Author: strengejacke

DESCRIPTION

@@ -1,7 +1,7 @@
 Type: Package
 Package: see
 Title: Model Visualisation Toolbox for 'easystats' and 'ggplot2'
-Version: 0.10.0.9
+Version: 0.10.0.10
 Authors@R:
     c(person(given = "Daniel",
              family = "Lüdecke",
@@ -88,7 +88,6 @@ Suggests:
     ggside,
     glmmTMB,
     grid,
-    httr,
     httr2,
     lavaan,
     lme4,

NEWS.md

@@ -22,6 +22,10 @@
   appropriate palette (usually, `"contrast"` or `"gradient"`) depending on
   whether discrete or continuous color scales are requested.
 
+## Bug fixes
+
+* Fixed issue with adding prior layers to plots from `estimate_density()`.
+
 # see 0.10.0
 
 ## Changes

R/geom_binomdensity.R

@@ -53,7 +53,7 @@ geom_binomdensity <- function(data,
   # Find y-axis levels
   y_levels <- levels(as.factor(data[[y]]))
   if (length(y_levels) != 2L) {
-    stop("The y-variable should have exactly two levels.", call. = FALSE)
+    insight::format_error("The y-variable should have exactly two levels.")
   }
 
   # Aesthetics
@@ -110,7 +110,7 @@ geom_binomdensity <- function(data,
     }
     out <- as.vector(prop[as.character(data[[y]])] * 0.9)
   } else {
-    stop("Oops, 'scale' argument wrongly specified.", call. = FALSE)
+    insight::format_error("Oops, 'scale' argument wrongly specified.")
   }
 
   out

R/plot.check_dag.R

@@ -62,8 +62,8 @@ plot.see_check_dag <- function(x,
                                ...) {
   .data <- NULL
   insight::check_if_installed(c("ggdag", "ggplot2"))
-  which <- match.arg(which, choices = c("all", "current", "required"))
-  effect <- match.arg(effect, choices = c("total", "direct"))
+  which <- insight::validate_argument(which, c("all", "current", "required"))
+  effect <- insight::validate_argument(effect, c("total", "direct"))
 
   # get plot data
   p1 <- p2 <- suppressWarnings(ggdag::dag_adjustment_sets(x, effect = effect))

R/plot.dw_data_tabulate.R

@@ -3,14 +3,14 @@
 #' @param x Object created by `datawizard::data_tabulate()`.
 #' @param label_values Logical. Should values and percentages be displayed at the
 #'   top of each bar.
-#' @param show_na Should missing values be dropped? Can be `"if_any"` (default) to show
-#'   the missing category only if any missing values are present, `"always"` to
-#'   always show the missing category, or `"never"` to never show the missing
-#'   category.
+#' @param show_na Should missing values be dropped? Can be `"if_any"` (default)
+#'   to show the missing category only if any missing values are present,
+#'   `"always"` to always show the missing category, or `"never"` to never show
+#'   the missing category.
 #' @param na_label The label given to missing values when they are shown.
-#' @param error_bar Logical. Should error bars be displayed?
-#'   If `TRUE`, confidence intervals computed using the Wilson method are shown.
-#'   See Brown et al. (2001) for details.
+#' @param error_bar Logical. Should error bars be displayed? If `TRUE`,
+#'   confidence intervals computed using the Wilson method are shown. See Brown
+#'   et al. (2001) for details.
 #' @param ci Confidence Interval (CI) level. Defaults to `0.95` (`95%`).
 #' @param color_fill Color to use for category columns (default: `"#87CEFA"`).
 #' @param color_error_bar Color to use for error bars (default: `"#607B8B"`).
@@ -25,14 +25,14 @@
 #' @export
 
 plot.datawizard_tables <- function(x, label_values = TRUE,
-                                   show_na = c("if_any", "always", "never"),
+                                   show_na = "if_any",
                                    na_label = "(Missing)",
                                    error_bar = TRUE,
                                    ci = 0.95,
                                    color_fill = "#87CEFA",
                                    color_error_bar = "#607B8B",
                                    ...) {
-  show_na <- match.arg(show_na, choices = c("if_any", "always", "never"))
+  show_na <- insight::validate_argument(show_na, c("if_any", "always", "never"))
   if (length(x) == 1L) {
     plot.datawizard_table(
       x[[1]],
@@ -64,14 +64,14 @@ plot.datawizard_tables <- function(x, label_values = TRUE,
 #' @export
 
 plot.datawizard_table <- function(x, label_values = TRUE,
-                                  show_na = c("if_any", "always", "never"),
+                                  show_na = "if_any",
                                   na_label = "(Missing)",
                                   error_bar = TRUE,
                                   ci = 0.95,
                                   color_fill = "#87CEFA",
                                   color_error_bar = "#607B8B",
                                   ...) {
-  show_na <- match.arg(show_na, choices = c("if_any", "always", "never"))
+  show_na <- insight::validate_argument(show_na, c("if_any", "always", "never"))
   dat <- as.data.frame(x)
 
   if (show_na == "if_any") {

R/plot.estimate_density.R

@@ -134,7 +134,7 @@ plot.see_estimate_density <- function(x,
   }
 
   # get parameter names for filtering
-  params <- unique(x$y)
+  params <- unique(x$Parameter)
 
   # get labels
   parameter_labels <- .clean_parameter_names(x$Parameter, grid = !is.null(n_columns))

R/print.check_model.R

@@ -12,7 +12,10 @@ print.see_check_model <- function(x,
   if (missing(type) && !is.null(plot_type) && plot_type %in% c("density", "discrete_dots", "discrete_interval", "discrete_both")) { # nolint
     type <- plot_type
   } else {
-    type <- match.arg(type, choices = c("density", "discrete_dots", "discrete_interval", "discrete_both"))
+    type <- insight::validate_argument(
+      type,
+      c("density", "discrete_dots", "discrete_interval", "discrete_both")
+    )
   }
 
   suppressWarnings(suppressMessages(graphics::plot(