plot.colspace: Plot spectra in a colourspace

Description

Plots reflectance spectra in the appropriate colorspace.

Usage

"plot"(x, ...)

Arguments

(required) an object of class colspace.

...

additional graphical options, which vary by modelled 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

Also see par.

Value

A 2D colorspace plot appropriate to the input data.

References

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.

Examples

Run this code

## 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)
# ## End(Not run)