oce.colorsTwo {oce} | R Documentation |
Create a palette of colours.
oce.colorsTwo(n, low = 2/3, high = 0, smax = 1, alpha = 1)
n |
the number of colours (>=1) to be in the palette. |
low |
the hue, in [0, 1], for the low end of a |
high |
the hue, in [0, 1], for the high end of a |
smax |
the maximum saturation, in [0, 1], for the colours of
|
alpha |
the alpha value, in [0, 1], for the colours of
|
oce.colorsPalette
provides a variety of pre-defined palettes.
which
=1 yields the ColorBrewer diverging red/blue scheme while
which
=2 yields the ColorBrewer diverging RYB scheme [1].
A family of nine-colour schemes is as follows: which="jet"
(or
which="9A"
or which=9.01
for the Jet scheme; which="9B"
or which=9.02
for a scheme similar to Jet but omitting the green, and
somewhat desaturating the yellow and cyan.
oce.colorsGebco
provides palettes that mimic the GEBCO atlas colours,
with shades of blue for water and of brown for land. The blue values go
from dark to light, and the brown ones from light to dark; in this way,
topographic images have light values near sea-level, and get darker in
either deeper water or higher terrain.
oce.colorsJet
provides a palette similar to the Matlab “jet”
palette.
oce.colorsTwo
provides a two-tone palette that fades to white at
central values.
oce.colorsViridis
provides a matplotlib (python) colour scheme that
became the standard in 2015; see [2]. This is a blue-yellow transition that
is designed to reproduce well in black-and-white, and also to be
interpretable by those with certain forms of colour blindness [3, 4, 5].
oce.colorsCDOM
, oce.colorsChlorophyll
,
oce.colorsDensity
, oce.colorsFreesurface
,
oce.colorsOxygen
, oce.colorspAR
, oce.colorsPhase
,
oce.colorsSalinity
, oce.colorsTemperature
,
oce.colorsTurbidity
, oce.colorsVelocity
and
oce.colorsVorticity
are based on RGB values set up by Kristen M.
Thyng for her Python package named cmcolor
[7].
Dan Kelley
[1] Color Brewer. http://colorbrewer2.org/
[2] A blog item on the Viridis (and related) matplotlib colour scales is at http://bids.github.io/colormap/.
[3] Light, A., and P. J. Bartlein, 2004. The End of the Rainbow? Color Schemes for Improved Data Graphics. Eos Trans. AGU, 85(40), doi:10.1029/2004EO400002.
[4] Martin Jakobsson, Ron Macnab, and Members of the Editorial Board, IBCAO. Selective comparisons of GEBCO (1979) and IBCAO (2000) maps. http://www.ngdc.noaa.gov/mgg/bathymetry/arctic/ibcao_gebco_comp.html.
[5] Stephenson, David B., 2005. Comment on “Color schemes for improved data graphics,” by A. Light and P. J. Bartlein. Eos Trans. AGU, 86(20).
[6] The Geography department at the University of Oregon has good resources
on colour schemes; see e.g.
http://geography.uoregon.edu/datagraphics/color_scales.htm
(This URL
worked prior to December 8, 2015, but was found to fail on that date; it is
included here in case users want to search for themselves.)
[7] The cmocean
Python package, written by Kristen M Thyng, is
available at https://github.com/kthyng/cmocean.
Other things related to colors: colormap
,
colors
, oce.colorsGebco
library(oce) opar <- par(no.readonly = TRUE) # 1. Show a few palettes x <- array(1:1000, dim=c(1, 1000)) par(mfrow=c(1, 5), mar=c(1, 3, 3, 1)) image(x, col=oce.colorsTwo(200), main="oce.colorsTwo") image(x, col=oce.colorsJet(200), main="oce.colorsJet") image(x, col=oce.colorsGebco(200), main="oce.colorsGebco") image(x, col=oce.colorsPalette(200), main="oce.colorsPalette") image(x, col=oce.colorsViridis(200), main="oce.colorsViridis") # 4. Kristen M Thyng's 'cmocean' colours, specialised for oceanography. par(mfrow=c(3, 4), mar=c(1, 3, 3, 1)) image(x, col=oce.colorsCDOM(200), main="oce.colorsCDOM") image(x, col=oce.colorsChlorophyll(200), main="oce.colorsChlorophyll") image(x, col=oce.colorsDensity(200), main="oce.colorsDensity") image(x, col=oce.colorsFreesurface(200), main="oce.colorsFreesurface") image(x, col=oce.colorsOxygen(200), main="oce.colorsOxygen") image(x, col=oce.colorsPAR(200), main="oce.colorsPAR") image(x, col=oce.colorsPhase(200), main="oce.colorsPhase") image(x, col=oce.colorsSalinity(200), main="oce.colorsSalinity") image(x, col=oce.colorsTemperature(200), main="oce.colorsTemperature") image(x, col=oce.colorsTurbidity(200), main="oce.colorsTurbidity") image(x, col=oce.colorsVelocity(200), main="oce.colorsVelocity") image(x, col=oce.colorsVorticity(200), main="oce.colorsVorticity") # 3. Acoustic-Doppler profiler data; note that plot,adp-method() puts makes # zlim be symmetric about zero velocity. par(mfrow=c(1, 1)) data(adp) plot(adp, which='u1') # 4. Contrast Jet with Viridis, using standard Volcano dataset; # try printing the results in black and white. par(mfrow=c(2, 1)) imagep(volcano, col=oce.colorsJet) imagep(volcano, col=oce.colorsViridis)