This package generates a monochrome palette from a starting colour for a
specified number of colours. Users can decide whether to go darker,
lighter, or both ways from that starting colour, which can be provided
as a vector of rgb values (e.g. c(15, 75, 99)), a hex colour code
(e.g. #0F4B63) or a recognised colour name (e.g. "purple"). The
package can also display the generated palette in the plot window, with
or without hex colour code labels.
This package is available on CRAN, so can
be installed using install.packages("monochromeR").
Alternatively, to install it from here, use
remotes::install_github("cararthompson/monochromeR"). (To do this, you
need to have installed the remotes package. To do that, use
install.packages("remotes").)
Sure! Here goes. To make the examples easy to read, I will use recognised colour names rather than hex codes or rgb values.
library(monochromeR)
generate_palette("purple", modification = "go_lighter",
n_colours = 5, view_palette = TRUE)
## [1] "#A020F0" "#B34CF3" "#C679F6" "#D9A5F9" "#ECD2FC"
The functions allow for British spelling and US spelling of colour/color.
generate_palette("purple", modification = "go_darker",
n_colors = 5, view_palette = TRUE, view_labels = FALSE)
## [1] "#A020F0" "#8019C0" "#601390" "#3F0C5F" "#200630"
With more colours, the hex codes get harder to view in the plot. They are printed in the console when the function is called on its own, and can also be assigned to an object for later use.
purple_palette <- generate_palette("purple", modification = "go_both_ways",
n_colours = 20, view_palette = TRUE, view_labels = FALSE)
purple_palette## [1] "#ECD2FC" "#E4C0FA" "#DCAEF9" "#D59CF8" "#CD8BF7" "#C679F6" "#BE67F4"
## [8] "#B655F3" "#AF43F2" "#A731F1" "#A020F0" "#931DDC" "#861AC9" "#7918B6"
## [15] "#6C15A3" "#601390" "#53107C" "#460E69" "#390B56" "#2C0843"
And just because it was easy to implement, this function can also be used to blend two colours together:
generate_palette("purple", blend_colour = "green",
n_colours = 10, view_palette = TRUE, view_labels = FALSE)
## [1] "#A020F0" "#9133DA" "#8347C5" "#755BB0" "#676F9A" "#588385" "#4A9670"
## [8] "#3CAA5A" "#2EBE45" "#20D230"
# Get hex code from rgb
rgb_to_hex(c(15, 75, 99))## [1] "#0F4B63"
# Get hex code from rgba
rgba_to_hex(c(15, 75, 99, 0.8))## [1] "#3E6E82"
# Get the rgb values from the hex code
hex_to_rgb("#FFFFFF")## [1] "r = 255, g = 255, b = 255"
# Get the rgb values from the hex code
hex_to_rgb("#0F4B63")## [1] "r = 15, g = 75, b = 99"
view_palette(c("red", "yellow", "purple", "green"), view_labels = FALSE)
view_palette(c(wesanderson::wes_palettes$Moonrise1,
wesanderson::wes_palettes$Moonrise2[1:2]))
From version 0.2.0 onwards, if you have created a named vector for your colours (which I highly recommend!), the names you have provided are displayed alongside the hex codes.
banana_palette <- c("unripe" = "#89973d",
"ripe" = "#e8b92f",
"overripe" = "#a45e41")
view_palette(banana_palette)
Version 0.1.3 onwards exports a ggplot object, which can be passed to
functions such as colorblindr::cvd_grid() to check how the palette is
perceived by people with different visual perception. With
view_labels = TRUE, the labels are displayed in black and white on top
of the colour, to allow users to easily see how readable the text is.
view_palette(c("red", "yellow", "purple", "green"), view_labels = TRUE)
colorblindr::cvd_grid()
Here’s a simple example, using {monochromeR}’s generate_palette() to
create a colour palette on the fly within ggplot().
library(tidyverse)
library(monochromeR)
penguin_plot <- palmerpenguins::penguins %>%
ggplot() +
geom_point(aes(x = flipper_length_mm, y = bill_length_mm,
colour = species, size = body_mass_g),
alpha = 0.8) +
labs(title = "Perfectly proportional penguins",
subtitle = "Each dot represents a penguin. The bigger the dot, the heavier the penguin. \nLook at them go!",
x = "Flipper length (mm)",
y = "Bill length (mm)") +
scale_size(guide = "none") +
guides(colour = guide_legend(title = "")) +
theme_minimal() +
theme(plot.subtitle = element_text(margin = margin(6, 0, 12, 0)))
penguin_plot
penguin_plot <- penguin_plot +
scale_colour_manual(values = generate_palette(c(15, 75, 99),
modification = "go_both_ways",
n_colours = 3))
penguin_plot
Here’s an example using {monochromeR}’s generate_palette() to
generate all the colours used in the plot, resulting in a more polished
look with minimal effort.
penguin_palette <- generate_palette(c(15, 75, 99),
modification = "go_both_ways",
n_colours = 8,
view_palette = T,
view_labels = F)
penguin_plot +
scale_colour_manual(values = penguin_palette[c(1, 3, 5)]) +
theme_minimal() +
theme(plot.background = element_rect(fill = penguin_palette[8],
colour = penguin_palette[8]),
panel.grid = element_line(colour = penguin_palette[7]),
panel.background = element_rect(fill = penguin_palette[8],
colour = penguin_palette[8]),
text = element_text(colour = penguin_palette[3]),
axis.text = element_text(colour = penguin_palette[3]),
plot.title = element_text(colour = penguin_palette[1], hjust = 0, size = 16),
plot.subtitle = element_text(colour = penguin_palette[2], hjust = 0))
- For the mechanics of how to make a package: Your first R package in 1 hour, a tutorial by Shannon Pileggi
- For the colour conversions: This thread on StackOverflow
- For the logo: The hexSticker package by Guangchuang Yu
I’ve done my best to make the functions in this package user-friendly, and to make the error messages easy to understand. If you come across a bug or an error message that doesn’t make sense, or if there’s something you think would make this package better, please let me know!
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