Kovesi | R Documentation |
A collection of 41 different sequences of colours, each sequence having a uniform perceptual contrast over its whole range. These sequences make very good colour maps which avoid introducing artefacts when displaying image data.
data(Kovesi)
A hyperframe
with the following columns:
linear | Logical: whether the sequence is linear. |
diverging | Logical: whether the sequence is diverging. |
rainbow | Logical: whether the sequence is a rainbow. |
cyclic | Logical: whether the sequence is cyclic. |
isoluminant | Logical: whether the sequence is isoluminant. |
ternary | Logical: whether the sequence is ternary. |
colsig | Character: colour signature (see Details) |
l1 , l2 | Numeric: lightness parameters |
chro | Numeric: average chroma (percent) |
n | Numeric: length of colour sequence |
cycsh | Numeric: cyclic shift (percent) |
values | : Character: the colour values. |
Kovesi (2014, 2015) presented a collection of colour sequences that have uniform perceptual contrast over their whole range.
The dataset Kovesi
provides these data. It is a
hyperframe
with 41 rows, in which each row provides information
about one colour sequence.
Additional information in each row specifies whether the colour sequence is ‘linear’, ‘diverging’, ‘rainbow’, ‘cyclic’, ‘isoluminant’ and/or ‘ternary’ as defined by Kovesi (2014, 2015).
The ‘colour signature’ is a string composed of letters representing the successive hues, using the following code:
r | red |
g | green |
b | blue |
c | cyan |
m | magenta |
y | yellow |
o | orange |
v | violet |
k | black |
w | white |
j | grey (j rhymes with grey) |
For example kryw
is the sequence from black to red to yellow to
white.
The column values
contains the colour data themselves.
The i
th colour sequence is Kovesi$values[[i]]
,
a character vector of length 256.
Dr Peter Kovesi, Centre for Exploration Targeting, University of Western Australia.
Kovesi, P. (2014) Website CET Uniform Perceptual Contrast Colour Maps https://www.peterkovesi.com/projects/colourmaps/
Kovesi, P. (2015)
Good Colour Maps: How to Design Them.
arXiv:1509.03700 [cs.GR]
Kovesi
LinearBMW <- Kovesi$values[[28]]
if(require(spatstat.geom)) {
plot(colourmap(LinearBMW, range=c(0,1)))
## The following would be suitable for spatstat.options(image.colfun)
BMWfun <- function(n) { interp.colours(LinearBMW, n) }
}
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