Package 'luwitemplate'

Description

Automatically loads and registers Google Fonts specified in the brand YAML when the package is loaded. This ensures fonts are available for ggplot2 themes without requiring manual setup.

Usage

.onLoad(libname, pkgname)

Arguments

Value

NULL (invisibly). Called for side effects (font registration).

Description

Generates a tags$style() block that overrides compiled colors in third-party widget stylesheets (bootstrap-datepicker, Shiny input containers) that load separately from the bslib theme. Place this in your UI to ensure these widgets respect dark mode.

Usage

dark_mode_css()

Details

Some Shiny widgets (datepicker, checkboxes, radios) load their own CSS files independently of bslib. These files contain compiled hex values that cannot be overridden from within the bslib theme. This function injects a <style> tag into the page head that loads after all widget CSS, ensuring the dark palette takes effect.

Value

A shiny::tags$head() element to include in your UI

Examples

## Not run: 
ui <- page_sidebar(
  theme = my_theme(),
  dark_mode_css(),
  input_dark_mode(id = "dark_mode"),
  sidebar = sidebar(
    dateRangeInput("dates", "Date Range:"),
    checkboxInput("flag", "Show details")
  )
)

## End(Not run)

Description

Retrieves all theme color variables as an R-friendly named list. Useful for programmatically accessing your brand colors or building custom palettes.

Usage

get_theme_colors(theme = my_theme())

Arguments

Details

Color names are converted from CSS variable format (hyphenated) to R-friendly format (underscored). For example, "body-bg" becomes "body_bg".

Value

Named list of hex color values with underscore-separated names: primary, secondary, success, danger, warning, info, light, dark, body_bg, body_color, input_border_color

See Also

scale_color_luwi_discrete(), scale_color_luwi_sequential(), scale_color_luwi_diverging() for ready-to-use palettes

Examples

# Get all theme colors
colors <- get_theme_colors()
colors$primary  # Your brand primary color

# Use in custom visualizations
plot(1:10, col = colors$primary, pch = 19)

# Build a custom gradient
my_gradient <- colorRampPalette(c(colors$light, colors$primary))

Description

Retrieves font families defined in your _brand.yml file. Returns a structured list with primary and secondary fonts for easy programmatic access in plots and custom themes.

Usage

get_theme_fonts(theme = my_theme())

Arguments

Details

This function reads the typography.fonts section from your package's _brand.yml file directly. The first font listed becomes primary, the second becomes secondary.

Expected _brand.yml structure:

typography:
  fonts:
    - family: "Open Sans"
      source: google
    - family: "Merriweather"
      source: google

Value

Named list with three elements:

primary

Main font family (used for body text, labels, etc.)

secondary

Secondary font family if defined (often used for headings), or NULL

all_families

Character vector of all font families defined in brand file

If _brand.yml is not found, returns fallback values with "sans" as primary font.

See Also

get_theme_colors() for extracting theme colors, theme_luwi() to use these fonts in ggplot2 automatically

Examples

# Get font configuration
fonts <- get_theme_fonts()
fonts$primary    # "Open Sans"
fonts$secondary  # "Merriweather" or NULL

# Use in ggplot2
library(ggplot2)
fonts <- get_theme_fonts()

ggplot(mtcars, aes(mpg, wt)) +
  geom_point() +
  labs(title = "My Plot") +
  theme_minimal(base_family = fonts$primary) +
  theme(
    plot.title = element_text(family = fonts$secondary %||% fonts$primary)
  )

# Check what fonts are available
fonts <- get_theme_fonts()
cat("Available fonts:", paste(fonts$all_families, collapse = ", "))

Description

Converts a ggplot object to an interactive plotly visualization with brand styling automatically applied. Designed specifically for Shiny dashboards with transparent backgrounds, custom fonts, and branded grid lines.

Usage

luwi_ggplotly(p, theme = my_theme(), base_size = 14, tooltip = "y")

Arguments

Value

A plotly htmlwidget ready for Shiny rendering

See Also

theme_luwi() for static ggplot version, plotly::ggplotly() for underlying conversion function, plotly::config() for additional plotly configuration

Other ggplot-themes: theme_luwi()

Examples

library(ggplot2)
library(plotly)

# Basic interactive plot
p <- ggplot(mtcars, aes(mpg, wt)) +
  geom_point() +
  labs(title = "Fuel Economy vs Weight")

luwi_ggplotly(p)

# Custom tooltips showing multiple values
p <- ggplot(mtcars, aes(mpg, wt, color = factor(cyl))) +
  geom_point(size = 3)

luwi_ggplotly(p, tooltip = c("x", "y", "color"))

# In a Shiny app
## Not run: 
library(shiny)

ui <- page_fluid(
  theme = my_theme(),
  plotlyOutput("plot")
)

server <- function(input, output) {
  output$plot <- renderPlotly({
    p <- ggplot(iris, aes(Sepal.Length, Sepal.Width, color = Species)) +
      geom_point()
    luwi_ggplotly(p, tooltip = c("x", "y", "color"))
  })
}

shinyApp(ui, server)

## End(Not run)

# Custom hover text
p <- ggplot(mtcars, aes(mpg, wt, text = paste("Car:", rownames(mtcars)))) +
  geom_point()

luwi_ggplotly(p, tooltip = "text")

Description

Generates a Bootstrap 5 theme from your _brand.yml file with optional custom CSS. This is the central theming function that powers all other styling in the package - use it in your Shiny UI to ensure consistent branding across your application.

Usage

my_theme(mode = c("light", "dark"))

Arguments

Details

This function:

1. Reads your package's _brand.yml file (colors, fonts, spacing)

2. Creates a Bootstrap 5 theme using bs_theme

3. If mode = "dark", overrides color variables with the color-dark palette from the same YAML

4. Applies custom CSS from inst/css/custom.css if available

The returned theme object is used as the default in other package functions like theme_luwi, get_theme_colors, and luwi_ggplotly, ensuring consistent styling across Shiny UI, static plots, and interactive visualizations.

Value

A bslib::bs_theme() object ready to use in Shiny applications

Dark Mode

Dark mode uses the color-dark section of _brand.yml to override Bootstrap Sass variables. This ensures the full cascade of derived variables (RGB decompositions, emphasis colors, subtle backgrounds) is recomputed by the Sass compiler. Use use_dark_mode in your Shiny server to enable reactive toggling.

See Also

bs_theme for the underlying theme constructor, get_theme_colors to extract colors from the theme, get_theme_fonts to extract fonts from the theme, theme_luwi for ggplot2 theme using these colors/fonts, use_dark_mode for Shiny dark mode integration

Other theme-generators: use_dark_mode()

Examples

# Light theme (default)
theme <- my_theme()

# Dark theme
dark_theme <- my_theme("dark")

# Use in Shiny app
library(shiny)
library(bslib)

ui <- page_fluid(
  theme = my_theme(),
  h1("My Branded App"),
  p("All Bootstrap components use your brand colors automatically")
)

## Not run: 
# App with dark mode toggle
ui <- page_fluid(
  theme = my_theme(),
  input_dark_mode(id = "dark_mode"),
  plotOutput("my_plot")
)

server <- function(input, output, session) {
  dm <- use_dark_mode(input, session)

  output$my_plot <- renderPlot({
    ggplot(mtcars, aes(mpg, wt)) +
      geom_point() +
      theme_luwi(theme = dm$theme())
  })
}

shinyApp(ui, server)

## End(Not run)

Description

Apply a sequential gradient color scale for continuous data with brand colors. Convenience wrapper around scale_color_gradientn().

Usage

scale_color_luwi_c(type = "warm", theme = my_theme(), ...)

Arguments

Value

A ggplot2 scale object

See Also

scale_fill_luwi_c() for fill aesthetic, scale_color_luwi_sequential() for the underlying palette, scale_color_luwi_div() for diverging data

Other ggplot-scales: scale_color_luwi_d(), scale_color_luwi_div(), scale_fill_luwi_c(), scale_fill_luwi_d(), scale_fill_luwi_div()

Examples

library(ggplot2)

# Continuous color scale
ggplot(faithfuld, aes(waiting, eruptions, color = density)) +
  geom_point() +
  scale_color_luwi_c(type = "warm") +
  theme_luwi()

# Cool palette with custom limits
ggplot(diamonds, aes(carat, price, color = depth)) +
  geom_point(alpha = 0.3) +
  scale_color_luwi_c(type = "cool", limits = c(55, 70)) +
  theme_luwi()

Description

Apply brand colors for categorical/discrete data. Convenience wrapper around scale_color_manual() with up to 15 distinct brand colors.

Usage

scale_color_luwi_d(theme = my_theme(), ...)

Arguments

Details

Supports up to 15 categories with carefully selected high-contrast colors. For more than 8 categories, consider grouping into "Other" or using a continuous scale instead.

Value

A ggplot2 scale object

See Also

scale_fill_luwi_d() for fill aesthetic, scale_color_luwi_discrete() for the underlying palette

Other ggplot-scales: scale_color_luwi_c(), scale_color_luwi_div(), scale_fill_luwi_c(), scale_fill_luwi_d(), scale_fill_luwi_div()

Examples

library(ggplot2)

# Categorical scatter plot
ggplot(iris, aes(Sepal.Length, Sepal.Width, color = Species)) +
  geom_point(size = 3) +
  scale_color_luwi_d() +
  theme_luwi()

# Line plot with multiple groups
ggplot(economics_long, aes(date, value01, color = variable)) +
  geom_line() +
  scale_color_luwi_d() +
  theme_luwi()

Description

Provides up to 15 distinct, high-contrast colors for categorical variables like groups, categories, or factors. Colors are carefully selected to be visually distinguishable while maintaining your brand aesthetic.

Usage

scale_color_luwi_discrete(theme = my_theme(), n = NULL)

Arguments

Details

The palette prioritizes your brand colors (primary, secondary, success, etc.) for the first few categories, then adds complementary colors for additional categories.

Value

Character vector of hex color codes (length = n or 15 if n is NULL)

See Also

ggplot2::scale_color_manual() and ggplot2::scale_fill_manual() to use with ggplot2, scale_color_luwi_sequential() for many categories (converts to gradient)

Other color-palettes: scale_color_luwi_diverging(), scale_color_luwi_sequential()

Examples

library(ggplot2)

# Basic categorical plot
ggplot(mpg, aes(class, hwy, fill = class)) +
  geom_boxplot() +
  scale_fill_manual(values = scale_color_luwi_discrete())

# Specify exact number needed
ggplot(iris, aes(Sepal.Length, Sepal.Width, color = Species)) +
  geom_point(size = 3) +
  scale_color_manual(values = scale_color_luwi_discrete(n = 3))

# Preview all 15 colors
scales::show_col(scale_color_luwi_discrete())

# Warning example: too many categories
scale_color_luwi_discrete(n = 20)  # Returns 15 with warning

Description

Apply a two-directional gradient color scale for data with a meaningful midpoint. Convenience wrapper around scale_color_gradientn() using the cool-to-warm diverging palette.

Usage

scale_color_luwi_div(theme = my_theme(), ...)

Arguments

Details

Use this for data where deviations from a central value matter:

• Positive/negative change

• Above/below average

• Correlation coefficients

• Temperature anomalies

Consider setting midpoint to center the gradient on your neutral value.

Value

A ggplot2 scale object

See Also

scale_fill_luwi_div() for fill aesthetic, scale_color_luwi_diverging() for the underlying palette, ggplot2::scale_color_gradient2() for manual midpoint control

Other ggplot-scales: scale_color_luwi_c(), scale_color_luwi_d(), scale_fill_luwi_c(), scale_fill_luwi_d(), scale_fill_luwi_div()

Examples

library(ggplot2)

# Correlation matrix
cor_data <- reshape2::melt(cor(mtcars))
ggplot(cor_data, aes(Var1, Var2, color = value)) +
  geom_point(size = 5) +
  scale_color_luwi_div(limits = c(-1, 1)) +
  theme_luwi()

# With custom midpoint
ggplot(economics, aes(date, unemploy - mean(unemploy))) +
  geom_line() +
  scale_color_luwi_div(midpoint = 0) +
  theme_luwi()

Description

Generates a two-directional gradient palette for data where deviations from a central value are meaningful (e.g., positive/negative change, hot/cold, above/below average).

Usage

scale_color_luwi_diverging(theme = my_theme(), n = 11, reverse = FALSE)

Arguments

Details

The palette transitions: Teal (cold) → Light blue → Neutral warm → Coral → Red-orange (hot). The neutral midpoint uses your theme's light color to maintain brand consistency.

When to use diverging palettes:

• Temperature data (cold to hot)

• Financial change (loss to gain)

• Survey responses (disagree to agree)

• Correlation coefficients (-1 to +1)

Value

Character vector of n hex color codes transitioning from cool (teal) through neutral (light) to warm (coral/red)

See Also

ggplot2::scale_fill_gradient2() to use with ggplot2, scale_color_luwi_sequential() for one-directional data

Other color-palettes: scale_color_luwi_discrete(), scale_color_luwi_sequential()

Examples

library(ggplot2)

# Correlation matrix
ggplot(reshape2::melt(cor(mtcars)), aes(Var1, Var2, fill = value)) +
  geom_tile() +
  scale_fill_gradientn(
    colors = scale_color_luwi_diverging(n = 11),
    limits = c(-1, 1)
  )

# Temperature anomalies (reversed: red = hot)
temp_palette <- scale_color_luwi_diverging(n = 9, reverse = TRUE)

# Preview the palette
scales::show_col(scale_color_luwi_diverging())

Description

Generates a gradient palette suitable for continuous/ordered data. Choose from warm (coral-to-red), cool (teal-to-blue), or green (olive-to-dark) gradients.

Usage

scale_color_luwi_sequential(
  theme = my_theme(),
  type = "warm",
  n = 9,
  reverse = FALSE
)

Arguments

Details

These palettes are perceptually uniform and designed to work well in both digital and print contexts. They automatically use your theme's semantic colors as anchor points to ensure brand consistency.

Value

Character vector of n hex color codes

See Also

ggplot2::scale_fill_gradient() and ggplot2::scale_color_gradient() to use with ggplot2, scale_color_luwi_diverging() for data with a meaningful midpoint

Other color-palettes: scale_color_luwi_discrete(), scale_color_luwi_diverging()

Examples

library(ggplot2)

# Warm palette for a heatmap
ggplot(faithfuld, aes(waiting, eruptions, fill = density)) +
  geom_tile() +
  scale_fill_gradientn(colors = scale_color_luwi_sequential(type = "warm"))

# Cool palette reversed (dark = high values)
ggplot(economics, aes(date, unemploy)) +
  geom_area(fill = scale_color_luwi_sequential(type = "cool", n = 1))

# Preview the palette
scales::show_col(scale_color_luwi_sequential(type = "green", n = 9))

Description

Apply a sequential gradient fill scale for continuous data with brand colors. Convenience wrapper around scale_fill_gradientn().

Usage

scale_fill_luwi_c(type = "warm", theme = my_theme(), ...)

Arguments

Value

A ggplot2 scale object

See Also

scale_color_luwi_c() for color aesthetic, scale_color_luwi_sequential() for the underlying palette, scale_fill_luwi_div() for diverging data

Other ggplot-scales: scale_color_luwi_c(), scale_color_luwi_d(), scale_color_luwi_div(), scale_fill_luwi_d(), scale_fill_luwi_div()

Examples

library(ggplot2)

# Heatmap with warm colors
ggplot(faithfuld, aes(waiting, eruptions, fill = density)) +
  geom_tile() +
  scale_fill_luwi_c(type = "warm") +
  theme_luwi()

# Area chart with green gradient
ggplot(economics, aes(date, unemploy)) +
  geom_area(fill = scale_color_luwi_sequential(type = "green", n = 1)) +
  theme_luwi()

Description

Apply brand colors for categorical/discrete fill aesthetic. Convenience wrapper around scale_fill_manual() with up to 15 distinct brand colors.

Usage

scale_fill_luwi_d(theme = my_theme(), ...)

Arguments

Details

Perfect for bar charts, boxplots, and violin plots with categorical groups. Colors are ordered by brand importance: primary, secondary, success, warning, danger.

Value

A ggplot2 scale object

See Also

scale_color_luwi_d() for color aesthetic, scale_color_luwi_discrete() for the underlying palette

Other ggplot-scales: scale_color_luwi_c(), scale_color_luwi_d(), scale_color_luwi_div(), scale_fill_luwi_c(), scale_fill_luwi_div()

Examples

library(ggplot2)

# Bar chart
ggplot(mpg, aes(class, fill = class)) +
  geom_bar() +
  scale_fill_luwi_d() +
  theme_luwi()

# Boxplot by category
ggplot(mpg, aes(class, hwy, fill = class)) +
  geom_boxplot() +
  scale_fill_luwi_d() +
  theme_luwi() +
  theme(legend.position = "none")  # Class already on x-axis

Description

Apply a two-directional gradient fill scale for data with a meaningful midpoint. Convenience wrapper around scale_fill_gradientn() using the cool-to-warm diverging palette.

Usage

scale_fill_luwi_div(theme = my_theme(), ...)

Arguments

Details

Ideal for heatmaps and tiles where deviations from center are meaningful.

Value

A ggplot2 scale object

See Also

scale_color_luwi_div() for color aesthetic, scale_color_luwi_diverging() for the underlying palette

Other ggplot-scales: scale_color_luwi_c(), scale_color_luwi_d(), scale_color_luwi_div(), scale_fill_luwi_c(), scale_fill_luwi_d()

Examples

library(ggplot2)

# Correlation heatmap
cor_data <- reshape2::melt(cor(mtcars))
ggplot(cor_data, aes(Var1, Var2, fill = value)) +
  geom_tile() +
  scale_fill_luwi_div(limits = c(-1, 1)) +
  theme_luwi()

Description

A clean, publication-ready ggplot2 theme that automatically matches your bslib/Shiny application styling. Built on theme_minimal() with transparent backgrounds for seamless integration into dashboards.

Usage

theme_luwi(theme = my_theme(), base_size = 14)

Arguments

Value

A ggplot2 theme object that can be added to plots with +

See Also

luwi_ggplotly() for interactive plotly version, scale_color_luwi_d(), scale_fill_luwi_c() for matching color scales, ggplot2::theme_set() to apply globally to all plots

Other ggplot-themes: luwi_ggplotly()

Examples

library(ggplot2)

# Basic usage
ggplot(mtcars, aes(mpg, wt)) +
  geom_point() +
  theme_luwi()

# With larger text for presentations
ggplot(iris, aes(Sepal.Length, Sepal.Width, color = Species)) +
  geom_point(size = 3) +
  labs(title = "Iris Measurements") +
  theme_luwi(base_size = 16)

# Set as default theme for all plots
theme_set(theme_luwi())

# Customize further
ggplot(economics, aes(date, unemploy)) +
  geom_line() +
  theme_luwi() +
  theme(panel.grid.major.x = element_blank())  # Remove vertical grid

Description

Wires up reactive theme switching for dark mode. Call this once in your Shiny server to get a reactive theme that tracks the toggle state. Bootstrap components are styled via CSS custom property overrides injected by my_theme — no full theme swap occurs on toggle.

Usage

use_dark_mode(input, session, input_id = "dark_mode")

Arguments

Details

The light theme is compiled at initialization. The dark theme is compiled lazily on first toggle to avoid unnecessary startup cost. Bootstrap components switch instantly via CSS custom property overrides (no session$setCurrentTheme() call). Pass dm$theme() to plot functions to make them reactive to the toggle.

Value

A list with two reactive elements:

mode

Reactive returning "dark" or "light"

theme

Reactive returning the corresponding bslib::bs_theme() object from my_theme

UI Setup

Your UI must include bslib::input_dark_mode(id = "dark_mode") (or a matching input_id). Place it in your navbar, sidebar, or wherever makes sense for your layout.

See Also

my_theme for the underlying theme constructor, input_dark_mode for the toggle widget

Other theme-generators: my_theme()

Examples

## Not run: 
library(shiny)
library(bslib)
library(ggplot2)

ui <- page_sidebar(
  theme = my_theme(),
  title = "Dark Mode Demo",
  sidebar = sidebar(
    input_dark_mode(id = "dark_mode")
  ),
  card(
    card_header("Branded Plot"),
    plotOutput("plot")
  )
)

server <- function(input, output, session) {
  dm <- use_dark_mode(input, session)

  output$plot <- renderPlot({
    ggplot(mtcars, aes(mpg, wt, color = factor(cyl))) +
      geom_point(size = 3) +
      scale_color_luwi_d() +
      theme_luwi(theme = dm$theme())
  })
}

shinyApp(ui, server)

## End(Not run)