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Colours from R, Viridis and More

Source: R/get_colour.R
colour.Rd

Colours from R, viridis and more. The output prints in the console with the actual colours.

Usage

get_colour(x, length = 1, opacity = 0)

register_colour(...)

# S3 method for class 'colour'
as.character(x, ...)

# S3 method for class 'colour'
print(x, ...)

add_white(x, white)

Arguments

x

colour or colour palette name. Input can be:

  • One of the colourblind-safe viridisLite palettes:

    • "viridis"

    • "magma"

    • "inferno"

    • "plasma"

    • "cividis"

    • "rocket"

    • "mako"

    • "turbo"

  • One of the built-in palettes in R (these are from R 4.4.1):

    • "Accent"

    • "Alphabet"

    • "Classic Tableau"

    • "Dark 2"

    • "Okabe-Ito"

    • "Paired"

    • "Pastel 1"

    • "Pastel 2"

    • "Polychrome 36"

    • "R3"

    • "R4"

    • "Set 1"

    • "Set 2"

    • "Set 3"

    • "Tableau 10"

    • "ggplot2"

    • "grayscale"

    • "greyscale"

    • "heatmap"

    • "rainbow"

    • "terrain"

    • "topo"

  • One of the 657 built-in colours() in R (even case-insensitive), such as "brown3", "darkorchid1", "dodgerblue2", "lemonchiffon4", "snow2"

  • One of the pre-registered colours using register_colour()

length

size of the vector to be returned

opacity

amount of opacity (0 = solid, 1 = transparent)

...

named vectors with known, valid colours. They must be coercible with get_colour().

white

number between [0, 1] to add white to x

Value

character vector in HTML format (i.e., "#AABBCC") with new class colour

Details

A palette from R will be expanded where needed, so even get_colour("R4", length = 20) will work, despite "R4" only supporting a maximum of eight colours.

Examples

get_colour(c("red", "tan1", "#ffa", "FFAA00"))
#> [1] "#FF0000"  "#FFA54F"  "#FFFFAA"  "#FFAA00"  

par(mar = c(0.5, 2.5, 1.5, 0)) # set plot margins for below plots

# all colourblind-safe colour palettes from the famous viridisLite package
barplot(1:7,
        col = get_colour("viridis", 7))

barplot(1:7,
        col = get_colour("magma", 7))


barplot(8:1,
        col = get_colour("R4", 8),
        main = "Some palettes have only 8 colours...")

barplot(20:1,
        col = get_colour("R4", 20),
        main = "Not anymore!")



# Registering Colours --------------------------------------------------

# to register colours, use named input - the values will be evaluated
# with get_colour()
get_colour("red123")
#> Warning: Invalid colours, replacing with grey: red123
#> [1] "#B6B6B6"  
register_colour(red123 = "red", red456 = "#ff0000", red789 = "f00")
#> 3 colours registered.
get_colour("red123")
#> [1] "#FF0000"  
get_colour("red456")
#> [1] "#FF0000"  
get_colour("red789")
#> [1] "#FF0000"  

# you can also register a group name
register_colour(red_group = c("red123", "ff4400", "red3", "red4"))
#> 1 colour registered.
get_colour("red_group")
#> [1] "#FF0000"  
get_colour("red_group", 3)
#> [1] "#FF0000"  "#FF4400"  "#CD0000"  

# Registering colours is ideal for your (organisational) style in plots.
# Let's say these are your style:
register_colour(navy_blue = "#1F3A93",
                burnt_orange = "#D35400",
                forest_green = "#2C6F47",
                goldenrod_yellow = "#DAA520",
                slate_grey = "#708090",
                plum_purple = "#8E4585")
#> 6 colours registered.

# Then register the whole colour list too:
register_colour(my_organisation = c("navy_blue", "burnt_orange",
                                    "forest_green", "goldenrod_yellow",
                                    "slate_grey", "plum_purple"))
#> 1 colour registered.
# Check that it works:
get_colour("my_organisation", length = 6)
#> [1] "#1F3A93"  "#D35400"  "#2C6F47"  "#DAA520"  "#708090"  "#8E4585"  

# Now use it in plots as you like:
iris |>
  plot2(x = Species, y = where(is.double), colour = "my_organisation")
#> i Using y = c(Petal.Length, Petal.Width, Sepal.Length, Sepal.Width)
#> i Using type = "boxplot" since all groups in Species and category contain at least three values


# Or even set the option to use it in any future plot:
options(plot2.colour = "my_organisation")

iris |>
  plot2(x = Species, y = where(is.double))
#> i Using type = "boxplot" since all groups in Species and category contain at least three values


# reset option again
options(plot2.colour = NULL)


# Use add_white() to add white to existing colours:
colours <- get_colour("R4", 6)
colours
#> [1] "#000000"  "#DF536B"  "#61D04F"  "#2297E6"  "#28E2E5"  "#CD0BBC"  
add_white(colours, 0.25)
#> [1] "#3F3F3F"  "#E77E90"  "#88DB7B"  "#59B1EC"  "#5DE9EB"  "#D948CC"  
add_white(colours, 0.5)
#> [1] "#7F7F7F"  "#EFA9B5"  "#B0E7A7"  "#90CBF2"  "#93F0F2"  "#E685DD"  
add_white(colours, 0.75)
#> [1] "#BFBFBF"  "#F7D4DA"  "#D7F3D3"  "#C7E5F8"  "#C9F7F8"  "#F2C2EE"  

add_white("red", 1/128)
#> [1] "#FF0202"  
add_white("red", 1/64)
#> [1] "#FF0404"  
add_white("red", 1/32)
#> [1] "#FF0808"