complete examples

R/plot.R

@@ -73,11 +73,24 @@ tidyplot <- function(data, ..., width = 50, height = 50, dodge_width = 0.8) {
 #' @inherit common_arguments
 #'
 #' @examples
+#' # Split by year
 #' energy %>%
 #'   dplyr::filter(year %in% c(2005, 2010, 2015, 2020)) %>%
 #'   tidyplot(y = power, color = energy_source) %>%
 #'   add_donut() %>%
 #'   split_plot(by = year)
+#' # Change dimensions of subplots
+#' energy %>%
+#'   dplyr::filter(year %in% c(2005, 2010, 2015, 2020)) %>%
+#'   tidyplot(y = power, color = energy_source) %>%
+#'   add_donut() %>%
+#'   split_plot(by = year, widths = 15, heights = 15)
+#' # Spread plots across multiple pages
+#' energy %>%
+#'   dplyr::filter(year %in% c(2005, 2010, 2015, 2020)) %>%
+#'   tidyplot(y = power, color = energy_source) %>%
+#'   add_donut() %>%
+#'   split_plot(by = year, ncol = 2, nrow = 1)
 #'
 #' @export
 split_plot <- function(plot, by, ncol = NULL, nrow = NULL, byrow = NULL,
@@ -135,6 +148,31 @@ split_plot <- function(plot, by, ncol = NULL, nrow = NULL, byrow = NULL,
 #' @param title Plot title.
 #' @param ... Arguments passed on to `print()`.
 #' @inherit common_arguments
+#'
+#' @details
+#' * `view_plot()` supports data subsetting. See examples and [Advanced plotting](https://jbengler.github.io/tidyplots/articles/Advanced-plotting.html#data-subsetting).
+#'
+#' @examples
+#' # View intermediate stages on screen
+#' study %>%
+#'   tidyplot(x = treatment, y = score, color = treatment) %>%
+#'   add_mean_bar(alpha = 0.3) %>%
+#'   add_sem_bar() %>%
+#'   add_data_points_beeswarm() %>%
+#'   view_plot(title = "Before changing color scheme") %>%
+#'   adjust_colors(colors_discrete_seaside) %>%
+#'   view_plot(title = "After changing color scheme")
+#' # View data subsets on screen
+#' gene_expression %>%
+#'   tidyplot(x = condition, y = expression, color = sample_type) %>%
+#'   add_mean_dash() %>%
+#'   add_sem_bar() %>%
+#'   add_data_points_beeswarm() %>%
+#'   view_plot(data = filter_rows(external_gene_name == "Apol6"),
+#'     title = "Apol6") %>%
+#'   view_plot(data = filter_rows(external_gene_name == "Bsn"),
+#'     title = "Bsn")
+#'
 #' @export
 view_plot <- function(plot, data = all_rows(), title = ggplot2::waiver(), ...) {
   check_tidyplot(plot)
@@ -162,6 +200,41 @@ view_plot <- function(plot, data = all_rows(), title = ggplot2::waiver(), ...) {
 #' @inheritParams ggplot2::ggsave
 #' @inherit common_arguments
 #'
+#' @examples
+#' if (FALSE) {
+#'
+#' # Save plot to file
+#' study %>%
+#'   tidyplot(treatment, score) %>%
+#'   add_data_points() %>%
+#'   save_plot("single_plot.pdf")
+#'
+#' # Save multipage PDF file
+#' gene_expression %>%
+#'   tidyplot(group, expression, color = sample_type) %>%
+#'   add_data_points() %>%
+#'   split_plot(by = external_gene_name, nrow = 3, ncol = 3) %>%
+#'   save_plot("multipage_plot.pdf")
+#'
+#' # Save multiple PDF files
+#' gene_expression %>%
+#'   tidyplot(group, expression, color = sample_type) %>%
+#'   add_data_points() %>%
+#'   split_plot(by = external_gene_name, nrow = 3, ncol = 3) %>%
+#'   save_plot("plot.pdf", multiple_files = TRUE)
+#'
+#' # Save intermediate stages to file
+#' study %>%
+#'   tidyplot(x = treatment, y = score, color = treatment) %>%
+#'   add_mean_bar(alpha = 0.3) %>%
+#'   add_sem_bar() %>%
+#'   add_data_points_beeswarm() %>%
+#'   save_plot("before.pdf") %>%
+#'   adjust_colors(colors_discrete_seaside) %>%
+#'   save_plot("after.pdf")
+#'
+#'   }
+#'
 #' @export
 save_plot <- function(plot = ggplot2::last_plot(), filename,
                       width = NA, height = NA, units = c("mm", "cm", "in"),

R/remove.R

@@ -1,6 +1,17 @@
 
 #' Remove legend or legend title
 #' @inherit common_arguments
+#'
+#' @examples
+#' study %>%
+#'   tidyplot(x = treatment, y = score, color = treatment) %>%
+#'   add_mean_bar() %>%
+#'   remove_legend()
+#' study %>%
+#'   tidyplot(x = treatment, y = score, color = treatment) %>%
+#'   add_mean_bar() %>%
+#'   remove_legend_title()
+#'
 #' @export
 remove_legend <- function(plot) {
   check_tidyplot(plot)
@@ -16,6 +27,29 @@ remove_legend_title <- function(plot) {
 
 #' Remove x axis or parts of it
 #' @inherit common_arguments
+#'
+#' @examples
+#' study %>%
+#'   tidyplot(x = treatment, y = score, color = treatment) %>%
+#'   add_mean_bar() %>%
+#'   remove_x_axis_line()
+#' study %>%
+#'   tidyplot(x = treatment, y = score, color = treatment) %>%
+#'   add_mean_bar() %>%
+#'   remove_x_axis_ticks()
+#' study %>%
+#'   tidyplot(x = treatment, y = score, color = treatment) %>%
+#'   add_mean_bar() %>%
+#'   remove_x_axis_labels()
+#' study %>%
+#'   tidyplot(x = treatment, y = score, color = treatment) %>%
+#'   add_mean_bar() %>%
+#'   remove_x_axis_title()
+#' study %>%
+#'   tidyplot(x = treatment, y = score, color = treatment) %>%
+#'   add_mean_bar() %>%
+#'   remove_x_axis()
+#'
 #' @export
 remove_x_axis <- function(plot) {
   check_tidyplot(plot)
@@ -57,6 +91,29 @@ remove_x_axis_title <- function(plot) {
 
 #' Remove y axis or parts of it
 #' @inherit common_arguments
+#'
+#' @examples
+#' study %>%
+#'   tidyplot(x = treatment, y = score, color = treatment) %>%
+#'   add_mean_bar() %>%
+#'   remove_y_axis_line()
+#' study %>%
+#'   tidyplot(x = treatment, y = score, color = treatment) %>%
+#'   add_mean_bar() %>%
+#'   remove_y_axis_ticks()
+#' study %>%
+#'   tidyplot(x = treatment, y = score, color = treatment) %>%
+#'   add_mean_bar() %>%
+#'   remove_y_axis_labels()
+#' study %>%
+#'   tidyplot(x = treatment, y = score, color = treatment) %>%
+#'   add_mean_bar() %>%
+#'   remove_y_axis_title()
+#' study %>%
+#'   tidyplot(x = treatment, y = score, color = treatment) %>%
+#'   add_mean_bar() %>%
+#'   remove_y_axis()
+#'
 #' @export
 remove_y_axis <- function(plot) {
   check_tidyplot(plot)
@@ -97,6 +154,22 @@ remove_y_axis_title <- function(plot) {
 
 #' Remove plot area padding
 #' @inherit common_arguments
+#'
+#' @examples
+#' study %>%
+#'   tidyplot(x = treatment, y = score, color = treatment) %>%
+#'   add_mean_bar() %>%
+#'   remove_plot_area_padding()
+#' # Before removing plot area padding
+#' animals %>%
+#'   tidyplot(x = weight, y = speed, color = family) %>%
+#'   add_data_points()
+#' # After removing plot area padding
+#' animals %>%
+#'   tidyplot(x = weight, y = speed, color = family) %>%
+#'   add_data_points() %>%
+#'   remove_plot_area_padding()
+#'
 #' @export
 remove_plot_area_padding <- function(plot, force_continuous = FALSE) {
   check_tidyplot(plot)

R/themes.R

@@ -1,6 +1,39 @@
 
 #' Themes
 #' @inherit common_arguments
+#'
+#' @examples
+#' study %>%
+#'   tidyplot(x = treatment, y = score, color = treatment) %>%
+#'   add_data_points() %>%
+#'   add_sem_bar() %>%
+#'   add_mean_dash() %>%
+#'   theme_tidyplot()
+#' study %>%
+#'   tidyplot(x = treatment, y = score, color = treatment) %>%
+#'   add_data_points() %>%
+#'   add_sem_bar() %>%
+#'   add_mean_dash() %>%
+#'   theme_ggplot2()
+#' study %>%
+#'   tidyplot(x = treatment, y = score, color = treatment) %>%
+#'   add_data_points() %>%
+#'   add_sem_bar() %>%
+#'   add_mean_dash() %>%
+#'   theme_minimal_xy()
+#' study %>%
+#'   tidyplot(x = treatment, y = score, color = treatment) %>%
+#'   add_data_points() %>%
+#'   add_sem_bar() %>%
+#'   add_mean_dash() %>%
+#'   theme_minimal_x()
+#' study %>%
+#'   tidyplot(x = treatment, y = score, color = treatment) %>%
+#'   add_data_points() %>%
+#'   add_sem_bar() %>%
+#'   add_mean_dash() %>%
+#'   theme_minimal_y()
+#'
 #' @export
 theme_tidyplot <- function(plot, fontsize = 7) {
   check_tidyplot(plot)
@@ -35,33 +68,33 @@ theme_minimal_xy <- function(plot, fontsize = 7) {
 }
 #' @rdname theme_tidyplot
 #' @export
-theme_minimal_y <- function(plot, fontsize = 7) {
+theme_minimal_x <- function(plot, fontsize = 7) {
   check_tidyplot(plot)
   plot <- plot + ggplot2::theme_minimal()
   if (get_variable(plot, "colour") == ".single_color")
     plot <- plot %>% remove_legend()
   plot %>% adjust_font(fontsize) +
     ggplot2::theme(
-      axis.line.x = ggplot2::element_line(colour = "grey", linewidth = 0.15),
-      panel.grid.major.x = ggplot2::element_blank(),
+      axis.line.y = ggplot2::element_line(colour = "grey", linewidth = 0.15),
+      panel.grid.major.x = ggplot2::element_line(colour = "grey", linewidth = 0.15),
       panel.grid.minor.x = ggplot2::element_blank(),
-      panel.grid.major.y = ggplot2::element_line(colour = "grey", linewidth = 0.15),
+      panel.grid.major.y = ggplot2::element_blank(),
       panel.grid.minor.y = ggplot2::element_blank()
     )
 }
 #' @rdname theme_tidyplot
 #' @export
-theme_minimal_x <- function(plot, fontsize = 7) {
+theme_minimal_y <- function(plot, fontsize = 7) {
   check_tidyplot(plot)
   plot <- plot + ggplot2::theme_minimal()
   if (get_variable(plot, "colour") == ".single_color")
     plot <- plot %>% remove_legend()
   plot %>% adjust_font(fontsize) +
     ggplot2::theme(
-      axis.line.y = ggplot2::element_line(colour = "grey", linewidth = 0.15),
-      panel.grid.major.x = ggplot2::element_line(colour = "grey", linewidth = 0.15),
+      axis.line.x = ggplot2::element_line(colour = "grey", linewidth = 0.15),
+      panel.grid.major.x = ggplot2::element_blank(),
       panel.grid.minor.x = ggplot2::element_blank(),
-      panel.grid.major.y = ggplot2::element_blank(),
+      panel.grid.major.y = ggplot2::element_line(colour = "grey", linewidth = 0.15),
       panel.grid.minor.y = ggplot2::element_blank()
     )
 }

R/tidycolor.R

@@ -12,6 +12,12 @@ c.tidycolor <- function(...) new_color_scheme(NextMethod())
 #' @param x Character vector of hex colors. For example `x = c("#FF00FF", "#00FFFF")`.
 #' @param name Name of the custom color scheme.
 #' @inherit common_arguments
+#'
+#' @examples
+#' new_color_scheme(c("#ECA669","#E06681","#8087E2","#E2D269"))
+#' new_color_scheme(c("#ECA669","#E06681","#8087E2","#E2D269"),
+#'   name = "my_custom_color_scheme")
+#'
 #' @export
 new_color_scheme <- function(x, name = "Untitled color scheme", reverse = FALSE) {
   if (!is_hex_vector(x)) cli::cli_abort("{.arg x} must be a vector of hex colors.")