Plots reflectance spectra in the appropriate colorspace.
# S3 method for colspace
plot(x, ...)
(required) an object of class colspace
.
additional graphical options, which vary by modeled space
. Refer
to their individual documentation:
diplot
: dichromat space
triplot
: trichromat space
tetraplot
: tetrahedral space
catplot
: categorical space
hexplot
: colour hexagon
cocplot
: colour-opponent-coding space
cieplot
: cie spaces
segplot
: segment analysis space
jndplot
: perceptual, 'noise corrected' space (for the results of jnd2xyz
)
Also see par
.
A colorspace plot appropriate to the input data.
Smith T, Guild J. (1932) The CIE colorimetric standards and their use. Transactions of the Optical Society, 33(3), 73-134.
Westland S, Ripamonti C, Cheung V. (2012). Computational colour science using MATLAB. John Wiley & Sons.
Chittka L. (1992). The colour hexagon: a chromaticity diagram based on photoreceptor excitations as a generalized representation of colour opponency. Journal of Comparative Physiology A, 170(5), 533-543.
Chittka L, Shmida A, Troje N, Menzel R. (1994). Ultraviolet as a component of flower reflections, and the colour perception of Hymenoptera. Vision research, 34(11), 1489-1508.
Troje N. (1993). Spectral categories in the learning behaviour of blowflies. Zeitschrift fur Naturforschung C, 48, 96-96.
Stoddard, M. C., & Prum, R. O. (2008). Evolution of avian plumage color in a tetrahedral color space: A phylogenetic analysis of new world buntings. The American Naturalist, 171(6), 755-776.
Endler, J. A., & Mielke, P. (2005). Comparing entire colour patterns as birds see them. Biological Journal Of The Linnean Society, 86(4), 405-431.
Kelber A, Vorobyev M, Osorio D. (2003). Animal colour vision - behavioural tests and physiological concepts. Biological Reviews, 78, 81 - 118.
Backhaus W. (1991). Color opponent coding in the visual system of the honeybee. Vision Research, 31, 1381-1397.
# NOT RUN {
data(flowers)
data(sicalis)
# Dichromat
vis.flowers <- vismodel(flowers, visual = 'canis')
di.flowers <- colspace(vis.flowers, space = 'di')
plot(di.flowers)
# Colour hexagon
vis.flowers <- vismodel(flowers, visual = 'apis', qcatch = 'Ei', relative = FALSE,
vonkries = TRUE, achro = 'l', bkg = 'green')
hex.flowers <- colspace(vis.flowers, space = 'hexagon')
plot(hex.flowers, sectors = 'coarse')
# Tetrahedron (static)
vis.sicalis <- vismodel(sicalis, visual = 'avg.uv')
tcs.sicalis <- colspace(vis.sicalis, space = 'tcs')
plot(tcs.sicalis)
# Tetrahedron (interactive)
vis.sicalis <- vismodel(sicalis, visual = 'avg.uv')
tcs.sicalis <- colspace(vis.sicalis, space = 'tcs')
tcsplot(tcs.sicalis, size = 0.005)
## Add points to interactive tetrahedron
patch <- rep(c('C','T','B'), 7)
tcs.crown <- subset(tcs.sicalis, 'C')
tcs.breast <- subset(tcs.sicalis, 'B')
tcsplot(tcs.crown, col ='blue')
tcspoints(tcs.breast, col ='red')
## Plot convex hull in interactive tetrahedron
tcsplot(tcs.sicalis, col = 'blue', size = 0.005)
tcsvol(tcs.sicalis)
# }
# NOT RUN {
# }
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