paintingr

“The greatest value of a picture is when it forces us to notice what we never expected to see.” - John Tukey

Color is one of the most important attributes of a figure. Dedicated choice of color can help us deliver our idea more vividly.

---

The goal of paintingr is to provide a set of palettes from paintings.

Structure of the package was based on coding from the wesanderson packages.

Installation

You can install the paintingr with:

install.packages('paintingr')

Or the development version from GitHub with:

# install.packages("devtools")
devtools::install_github("thereallda/paintingr")

Usage

library(paintingr)
# display all palettes
display_all_palettes()

Palettes

Pearlgirl

Girl with a Pearl Earring - Johannes Vermeer (1665), Source

paint_palette("Pearlgirl")

Splash

A Bigger Splash - David Hockney (1967), Source

paint_palette("Splash")

Autumn

Autumn at Oirase - Kawase Hasui (1933), Source

paint_palette("Autumn")

Villeneuve

Matin à Villeneuve - Henri Biva (1905), Source

paint_palette("Villeneuve")

Ophelia

Ophelia - John Everett Millais (1851-1852), Source

paint_palette("Ophelia")

Kitchen

Kitchen (Detail 2) - Liza Lou (1991–1996), Source

paint_palette("Kitchen")

Spring

SPRING BY THE SEINE - Claude Monet (1875), Source

paint_palette("Spring")

Strawberries

Strawberries - Édouard Manet (1882), Source

paint_palette("Strawberries")

Seascape

Seascape at Saintes-Maries - Vincent van Gogh (1888), Source

paint_palette("Seascape")

Twilight

Twilight, Venice - Claude Monet (1908), Source

paint_palette("Twilight")

Abstract

Abstract Composition - Jessica Dismorr (1915), Source

paint_palette("Abstract")

Vesuivus

Vesuvius in Eruption - Joseph Wright of Derby (1776-1780), Source

paint_palette("Vesuvius")

Examples

ggplot2-based examples

Heatmap

Use type="continuous" to automatically interpolate between colors if you want more colors than the palette can offer (n > 5/6).

library(ggplot2)
# Dummy data
x <- LETTERS[1:20]
y <- paste0("var", seq(1,20))
data <- expand.grid(X=x, Y=y)
data$Z <- seq(1,20)+runif(400, 0, 5)

# Heatmap 
pal <- paint_palette("Autumn", n=100, type="continuous")
ggplot(data, aes(X, Y, fill= Z)) + 
  geom_tile() + 
  scale_fill_gradientn(colours = pal) + 
  scale_x_discrete(expand = c(0, 0)) +
  scale_y_discrete(expand = c(0, 0)) + 
  coord_equal() 

# Heatmap with palette of "Vesuvius" 
pal2 <- paint_palette("Vesuvius", n=100, type="continuous")
ggplot(data, aes(X, Y, fill= Z)) + 
  geom_tile() + 
  scale_fill_gradientn(colours = pal2) + 
  scale_x_discrete(expand = c(0, 0)) +
  scale_y_discrete(expand = c(0, 0)) + 
  coord_equal() 

Boxplot

# use iris data from `ggplot2` for demonstration
data(iris)

ggplot(iris, aes(Species, Sepal.Length)) +
  geom_boxplot(aes(fill = Species)) +
  theme_classic() +
  theme(legend.position = "top") +
  scale_fill_manual(values = paint_palette("Villeneuve"))

Scatter

# Scatter
ggplot(iris, aes(Sepal.Length, Sepal.Width)) +
  geom_point(aes(color = Species)) +
  theme_classic() +
  theme(legend.position = "top") +
  scale_color_manual(values = paint_palette("Kitchen"))

Violin plot

data(mpg)
# violin plot with 7 colors, Spring palette only have six colors add one more
ggplot(mpg, aes(x=class, y=hwy, fill=class)) + 
  geom_violin() +
  theme_classic() +
  scale_fill_manual(values = c(paint_palette("Spring", n=6), "black"))

Barplot

ggplot(mpg, aes(x = class, fill = drv)) + 
  geom_bar() +
  theme_classic() +
  scale_fill_manual(values = paint_palette("Ophelia"))