Simplified theming of {ggplot2}
, {lattice}
, and {base}
R graphics. In addition to providing a centralized approach to styling R graphics, {thematic}
also enables automatic styling of R plots in Shiny, R Markdown, and RStudio.
Install the stable release of {thematic}
on CRAN with:
Auto theming in Shiny requires {shiny}
1.5.0 or higher:
Auto theming in R Markdown requires {rmarkdown}
2.7 or higher:
Using themes with custom fonts works best if you have {showtext}
and/or {ragg}
installed.
{thematic}
’s auto theming gives R plots the ability to style themselves inside Shiny (via CSS), RStudio (via RStudio themes), and R Markdown (via {bslib}
).
Call thematic_shiny()
before launching a Shiny app to enable {thematic}
for every plotOutput()
inside the app. If no values are provided to thematic_shiny()
, each plotOutput()
uses the app’s CSS colors to inform new R plotting defaults. If the app uses Google Fonts (and you have {showtext}
and/or {ragg}
installed), you may safely provide font = "auto"
to thematic_shiny()
, which also translates CSS fonts to R. Here’s an example with the Pacifico font:
library(shiny)
library(ggplot2)
library(thematic)
# Call thematic_shiny() prior to launching the app, to change
# R plot theming defaults for all the plots generated in the app
thematic_shiny(font = "auto")
ui <- fluidPage(
# bslib makes it easy to customize CSS styles for things
# rendered by the browser, like tabsetPanel()
# https://rstudio.github.io/bslib
theme = bslib::bs_theme(
bg = "#002B36", fg = "#EEE8D5", primary = "#2AA198",
# bslib also makes it easy to import CSS fonts
base_font = bslib::font_google("Pacifico")
),
tabsetPanel(
type = "pills",
tabPanel("ggplot", plotOutput("ggplot")),
tabPanel("lattice", plotOutput("lattice")),
tabPanel("base", plotOutput("base"))
)
)
server <- function(input, output) {
output$ggplot <- renderPlot({
ggplot(mtcars, aes(wt, mpg, label = rownames(mtcars), color = factor(cyl))) +
geom_point() +
ggrepel::geom_text_repel()
})
output$lattice <- renderPlot({
lattice::show.settings()
})
output$base <- renderPlot({
image(volcano, col = thematic_get_option("sequential"))
})
}
shinyApp(ui, server)
Call thematic_on()
before generating plots inside RStudio to have all subsequent plots shown in the “Plots” viewing pane to reflect your RStudio theme. Note that thematic_on()
enables {thematic}
for the remainder of the R session, but you can use thematic_off()
to disable (or thematic_theme()
for one-off use of {thematic}
). Here’s an example of how {thematic}
can intelligently adapt each plot to the current RStudio theme:
Call thematic_rmd()
before generating plots inside R Markdown to have all subsequent plots within the document reflect the relevant theme. In a static (i.e., non-runtime: shiny
) R Markdown context, auto-theming only works with {bslib}
-powered rmarkdown::html_document()
(as in the example below), but in other situations you may also provide colors and fonts explicitly to thematic_rmd()
.
By default, {thematic}
attempts to detect the relevant background, foreground, and accent colors. However, you may also specify these settings more directly by providing relevant color and fonts directly to thematic_on()
(or thematic_shiny()
/thematic_rmd()
).
library(ggplot2)
thematic::thematic_on(bg = "#222222", fg = "white", accent = "#0CE3AC", font = "Oxanium")
ggp <- ggplot(mtcars, aes(wt, mpg, label = rownames(mtcars), color = factor(cyl))) +
geom_point() +
ggrepel::geom_text_repel()
ggp
{thematic}
works by setting new global defaults that can always be overridden with plot-specific theme()
-ing code:
To use a “complete” {ggplot2}
theme with {thematic}
(e.g., theme_bw()
, theme_minimal()
, etc), use theme_set()
to set the theme globally. This way {thematic}
has the opportunity to preserve the complete theme’s styling semantics when changing global defaults (e.g., theme_bw()
uses the same fill color for the panel and plot background, which is semantically different from the theme_gray()
default):
In addition to setting new defaults for main colors and fonts, {thematic}
also sets defaults for qualitative
(and sequential
) colorscales. See the custom themes article to learn more about how to customize those defaults.
{thematic}
’s theming options as well as how they interact with {ggplot2}
, {lattice}
, and {base}
.{thematic}
.{thematic}
to individual plots.Below is a link to an RStudio Cloud instance with some ready to run {thematic}
examples:
{thematic}
is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.