Colors and color palettes

This vignette explains which colors and color palettes are provided by unikn and how they can be accessed and used. (See the vignette on text for information on text boxes and decorations.)

Overview

There are 2 main functions to interact with the color palettes in the unikn package: seecol() and usecol().

The seecol() function is a general-purpose tool for viewing (or seeing) color palettes. seecol takes 2 main arguments:
1. pal describes either 1 or multiple color palettes (with a default of pal = "all");
2. n describes the number of desired colors (with a default of n = "all").

Based on the setting of pal, the seecol function distinguishes between 2 modes:

comparing a set of color palettes by passing a keyword or list-object;
viewing the details of a single color palette.

The usecol() function allows using a color palette without showing its details.

Viewing colors and color palettes with `seecol`

The behavior of the seecol() function depends on the inputs to its pal argument. It either allows comparing multiple color palettes or shows the details of a single color palette.

Viewing and comparing available color palettes

When the pal argument specifies (a list of) multiple color palettes, seecol() plots a vector for each palette to allow comparing these palettes. Some special keywords within the unikn package denote sets of color palettes: "unikn_all", "unikn_basic", pair_all", "pref_all" and "grad_all". Calling seecol with pal set to these keywords allows comparing pre-defined sets of the color palettes:

Viewing all available color palettes:

seecol("unikn_all")  # same as seecol("all")

three basic color palettes:

seecol("unikn_basic")

Note, that pal_unikn_web and pal_unikn_ppt are almost identical, but differ in how vibrant their colors are.

three paired color palettes:

seecol("pair_all")

all preferred colors from the spectrum and their respective gradients:

seecol("pref_all")

only the pre-defined color gradients:

seecol("grad_all")

Viewing and saving a palette

When the pal argument of the seecol() function specifies a single color palette, the function plots a more detailed view of this particular color palette:

seecol(pal_unikn)  # view details of pal_unikn

In the detailed overview, we see

the color names (where available),
numeric indices of the color palette,
the HEX values of each color,
the RGB values for each color.

A typical workflow may include seeing a color palette, saving it, and using it in a plot.

my_pal <- seecol(pal_unikn_light)  # view details of AND save pal_unikn_light to my_pal

After saving the color palette you can use the palette object in your plot:

barplot(1/sqrt(1:10), col = my_pal)  # use my_pal in a plot

Note that seecol() invisibly returns the color palette.
Thus, the following will only plot the palette without doing anything else with the color vector:

seecol(pal_bordeaux)

Other parameters of `seecol`

The seecol() function provides a few aesthetic parameters for adjusting how color palettes are plotted:

col_brd allows specifying the color of box borders (if shown. Default: col_brd = NULL).
lwd_brd allows specifying the line width of box borders (if shown. Default: lwd_brd = NULL).
title allows replacing the default title with a custom title.

Examples:

seecol("grad_all", col_brd = "black", lwd_brd = 2, title = "Color gradients with black borders")

seecol(pal_seegruen, col_brd = "white", lwd_brd = 10, title = "A color palette with white borders")

Using a palette with `usecol` (without seeing it)

The usecol() function allows directly using a color palette in a plot (i.e., without first viewing it). usecol() corresponds to seecol() by taking the same 2 main arguments (pal and n). However, as its purpose is using the colors specified by pal, rather than plotting (or seeing) them, the pal argument typically contains only 1 color palette:

# Using a color palette:
barplot(1/sqrt(1:11), col = usecol(pal_unikn))

Note that the both the seecol and the usecol function are quite permissive with respect to specifying their pal argument: A particular color palette (e.g., pal_seegruen) can not only be displayed by providing it (as an object) but also by providing its name (i.e., "pal_seegruen") or even its incomplete object name or name (i.e., "seegruen" or seegruen). Hence, the following all yield the same result:

seecol(pal_seegruen)
seecol("pal_seegruen")
seecol(seegruen)  # issues a warning
seecol("seegruen")

Customizing color palettes

Both the seecol() and the usecol() functions allow a flexible on-the-fly customization of color palettes.

Specifying a value for the n argument of seecol an usecol allows:

specifying subsets of colors and comparing these subsets for different palettes for n smaller than the length of the color palette.
extending color palettes and comparing different palettes for n greater than the length of the color palette.

Passing a vector of colors and/or color palettes allows you creating and viewing your own palettes.

Finally, specifying a value for alpha (in a range from 0 to 1) allows controlling the transparency of the color palette(s), with higher values for alpha corresponding to higher transparency (i.e., lower opacity).

Selecting subsets

Using only a subset of colors:

seecol("unikn_all", n = 4)

seecol(pal_unikn, 4)

Importantly, when using pre-defined color palettes of unikn but a value of n that is smaller than the length of the current color palette, usecol and seecol select a predefined subset of colors:

barplot(1/sqrt(1:2), col = usecol(pal_seeblau, n = 2))
barplot(1/sqrt(1:3), col = usecol(pal_seeblau, n = 3))

Extending color palettes

For values of n that are larger than the number of available colors in pal, the specified color palette is extended using ColorRampPalette:

seecol("all", n = 12)

seecol(pal_seeblau, 12)

When using a color palette:

barplot(1/sqrt(1:11), col = usecol(pal_bordeaux, n = 11))

Mixing color palettes

By passing a vector to pal, we can concatenate 2 color palettes and connect them with a color (here: "white") as the midpoint of a new color palette:

seecol(pal = c(rev(pal_petrol), "white", pal_bordeaux))

We can combine a set of colors and extend this palette by specifying an n argument that is larger than the length of the specified palette:

seecol(pal = usecol(c(Karpfenblau, Seeblau, "gold"), n = 10))

# Note, that redundant use of seecol and usecol shows HEX values as names.
# seecol(pal = c(Karpfenblau, Seeblau, "gold"), n = 10)  # would work, but show no intermediate names

These custom palettes can easily be used in a plot. For instance, we can define and use a subset of the pal_unikn_pair palette as follows:

my_pair <- seecol(pal_unikn_pair, n = 10)


# Create data: 
dat <- matrix(sample(5:10, size = 10, replace = TRUE), ncol = 5)

# Plot in my_pair colors:
barplot(dat, beside = TRUE, col = my_pair)

Controlling transparency

Both seecol() and usecol() accept an alpha argument (in a range from 0 to 1) for controlling the transparency of color palettes, with higher values for alpha corresponding to higher transparency (i.e., lower opacity).

Displaying a specific color palette at an opacity of 0.5:

seecol(pal_unikn, alpha = 0.5)

Setting opacity for comparing of multiple color palettes:

seecol("grad", alpha = 0.67)

Creating and comparing custom palettes

Suppose we want to compare a newly created color palette to existing color palettes. To achieve this, advanced users can use the seecol() function for displaying and comparing different custom palettes. When provided with a list of color palettes as the input to its pal argument, seecol() will show a comparison of the inputs:

# Define 2 palettes: 
pal1 <- c(rev(pal_seeblau), "white", pal_bordeaux)
pal2 <- usecol(c(Karpfenblau, Seeblau, "gold"), n = 10)

# Show the my_pair palette from above, the 2 palettes just defined, and 2 pre-defined palettes:  
seecol(list(my_pair, pal1, pal2, pal_unikn, pal_unikn_pair))

Note that unknown color palettes will be named paln in increasing order. Palettes known to seecol() will be shown with their respective names.

As before, we can use the n argument for obtaining shorter subsets of color palettes:

seecol(list(my_pair, pal1, pal2, pal_unikn, pal_unikn_pair), n = 5)

or larger values of n for extending color palettes:

seecol(list(my_pair, pal1, pal2, pal_unikn, pal_unikn_pair), n = 15)

Examples

The following examples illustrate how plotting functions in R can use the unikn color palettes and the seecol() and usecol() functions.

Using the plot function of base R for a scatterplot:

plot(x = runif(99), y = runif(99), "p", pch = 16, cex = 4, 
     col = usecol(pal_unikn, alpha = .50),  # with transparency
     main = "99 transparent dots", axes = FALSE, xlab = NA, ylab = NA)

Using the ggplot function of ggplot2 for an area plot:

# Example based on https://www.r-graph-gallery.com/137-spring-shapes-data-art/ 

# (1) Create data: ---- 
ngroup <- 50
names <- paste("G_", seq(1, ngroup), sep = "")
df <- data.frame()

set.seed(3)
for(i in seq(1:30)){
    data = data.frame(matrix(0, ngroup, 3))
    data[, 1] = i
    data[, 2] = sample(names, nrow(data))
    data[, 3] = prop.table(sample( c(rep(0, 100), c(1:ngroup)), nrow(data)))
    df = rbind(df, data)}
colnames(df) <- c("X","group","Y")
df <- df[order(df$X, df$group) , ]

# (1) Choose colors: ---- 

# (a) using RColorBrewer: 
# library(RColorBrewer)
# cur_col <- brewer.pal(11, "Paired") 
# cur_col <- colorRampPalette(cur_col)(ngroup)
# cur_col <- cur_col[sample(c(1:length(cur_col)), size = length(cur_col))]  # randomize

# (b) using unikn:
library(unikn)
cur_col <- usecol(pal = pal_unikn, n = ngroup)
# cur_col <- cur_col[sample(c(1:length(cur_col)), size = length(cur_col))]  # randomize

# (3) Use ggplot2: ---- 

library(ggplot2)

ggplot(df, aes(x = X, y = Y, fill = group)) + 
  geom_area(alpha = 1, color = Grau, size = .01 ) +
  scale_fill_manual(values = cur_col) +
  theme_void() +
  theme(legend.position = "none")

pal_unikn

Generalization to other institutions

The color scales included in the unikn package are based on the CD manual of the University of Konstanz, Germany. However, the functionality provided by the package makes it easy and straightforward to define and use your own color schemes. Here are some examples from other institutions to illustrate how this can be achieved.

A. University of Freiburg, Germany:

Uni Freiburg

The Albert-Ludwigs Universität Freiburg provides fairly extensive information on its corporate color scheme (available here and here). Colors can be defined in a variety of ways, but R comes with convenient tools (like col2rgb and convertColor in grDevices) to handle most cases. The most straightforward way of creating a new color palette in R is by using its HEX/HTML code (provided in character format). As the University of Freiburg kindly provides their colors in this format, we can easily define the corresponding color palettes as named vectors:

# Basic colors: https://www.zuv.uni-freiburg.de/service/cd/cd-manual/farbwelt

pal_freiburg_bluered <- c("#004a99", "#c1002a")
names(pal_freiburg_bluered) <- c("uni-blau", "uni-rot")

pal_freiburg_basic <- c("#004a99", "white", "#c1002a")  # add "white" for better gradients
names(pal_freiburg_basic) <- c("uni-blau", "weiss", "uni-rot")

# Web colors: https://www.zuv.uni-freiburg.de/service/wsg/webstyleguide/farben  

pal_freiburg_blue <- c("#004a99", "#2a6ebb", "#6f9ad3")
names(pal_freiburg_blue) <- c("blue-1", "blue-2", "blue-3")

pal_freiburg_grey <- c("#f2f3f1", "#e0e1dd", "#d5d6d2", "#c9cac8", 
                       "#b2b4b3", "#9a9b9c", "#747678", "#363534")
names(pal_freiburg_grey) <- c("grey-0", "grey-1", "grey-2", "grey-3", 
                              "grey-5", "grey-7", "grey-9", "grey-font")

pal_freiburg_info <- c("#2a6ebb", "#a7c1e3", "#7b2927", "#de3831", "#739600", "#92d400", 
                       "#4d4f53", "#747678", "#b2b4b3", "#d5d6d2", "#e98300", "#efbd47")
names(pal_freiburg_info) <- c("mid-blau", "hell-blau", "dark-red", "hell-red", "mid-green", "hell-green", 
                              "anthrazit", "dark-grey", "mid-grey", "hell-grey", "orange", "gelb")

Once a new color palette has been defined (and is available in your current R environment), we can use the seecol() and usecol() functions to view, modify, and use the palette:

seecol(pal_freiburg_info)            # view color palette

# seecol(pal_freiburg_basic, n = 7)  # extend color palette
# seecol(c(pal_freiburg_blue, "white", pal_freiburg_grey))  # mix color palette

B. Princeton University, USA:

Princeton University

The color scheme of Princeton University is easily recognized by its combination of orange with black and white elements. The official guidelines (available here) define “Princeton Orange” as Pantone (PMS) 158 C.

The PANTONE™ color finder at https://www.pantone.com/color-finder/158-C yields the following color values:
- RGB: 232 119 34
- HEX/HTML: #E87722
- CMYK: 0 62 95 0
However, the guide also specifies and distinguishes between 2 additional versions of orange and provides the following HEX/HTML values for them:
- Orange on white: “#E77500”
- Orange on black: “#F58025”

These definitions suggest defining 3 separate versions of orange and corresponding color palettes:

# HEX values for 3 shades of orange: 
orange_basic <- "#E87722"  # Pantone 158 C
orange_white <- "#E77500"  # orange on white
orange_black <- "#F58025"  # orange on black

# Defining color palettes:
pal_princeton <- c(orange_basic, "black")
names(pal_princeton) <- c("orange", "black")

pal_princeton_1 <- c(orange_white, "white", "black")
names(pal_princeton_1) <- c("orange_w", "white", "black")

pal_princeton_2 <- c(pal = c(orange_black, "black", "white"))
names(pal_princeton_2) <- c("orange_b", "black", "white")

seecol(pal_princeton_1,  # view color palette
       col_bg = "lightgrey")

C. Max Planck Society, Germany:

MPG

The CD manual (available here) of the Max Planck Society specifies the use of 2 primary colors:

Green as Pantone 328: Using the PANTONE™ color finder at https://www.pantone.com/color-finder/328-C yields the following color values:
- RGB: 0 115 103
- HEX/HTML: #007367
- CMYK: 100 10 61 38
Grey as Pantone 427: Using the PANTONE™ color finder at https://www.pantone.com/color-finder/427-C yields the following color values:
- RGB: 208 211 212
- HEX/HTML: #D0D3D4
- CMYK: 7 3 5 8

Again, the easiest way of defining a corresponding color palette is by creating a named vector. To allow for better color gradients, we insert the color "white" between the 2 dedicated colors:

pal_mpg <- c("#007367", "white", "#D0D3D4")
names(pal_mpg) <- c("mpg green", "white", "mpg grey")

As before, can now use the seecol() and usecol() functions to view, modify, and use the new pal_mpg color palette:

seecol(pal_mpg, 
       col_brd = "black", lwd_brd = 2)

Type:	Version:	URL:
A. unikn (R package):	Release version	https://CRAN.R-project.org/package=unikn
	Development version	https://github.com/hneth/unikn
B. Online documentation:	Release version	https://hneth.github.io/unikn
	Development version	https://hneth.github.io/unikn/dev

Nr.	Vignette	Content
1.	Colors	Colors and color palettes
2.	Text	Text boxes and decorations

Colors and color palettes

SPDS, uni.kn

2019 09 24

Overview

Viewing colors and color palettes with `seecol`

Viewing and comparing available color palettes

Viewing and saving a palette

Other parameters of `seecol`

Using a palette with `usecol` (without seeing it)

Customizing color palettes

Selecting subsets

Extending color palettes

Mixing color palettes

Controlling transparency

Creating and comparing custom palettes

Examples

Generalization to other institutions

A. University of Freiburg, Germany:

B. Princeton University, USA:

C. Max Planck Society, Germany:

Resources

Vignettes

Colors and color palettes

SPDS, uni.kn

2019 09 24

Overview

Viewing colors and color palettes with seecol

Viewing and comparing available color palettes

Viewing and saving a palette

Other parameters of seecol

Using a palette with usecol (without seeing it)

Customizing color palettes

Selecting subsets

Extending color palettes

Mixing color palettes

Controlling transparency

Creating and comparing custom palettes

Examples

Generalization to other institutions

A. University of Freiburg, Germany:

B. Princeton University, USA:

C. Max Planck Society, Germany:

Resources

Vignettes

Viewing colors and color palettes with `seecol`

Other parameters of `seecol`

Using a palette with `usecol` (without seeing it)