pavo (version 0.5-6)

coldist: Color distances

Description

Applies the visual models of Vorobyev et al. (1998) to calculate color distances with receptor noise based on relative photoreceptor densities.

Usage

coldist(vismodeldata, qcatch = c("Qi", "fi"), vis = c("tetra", "tri", "di"), noise = c("neural", "quantum"), subset = NULL, achro = TRUE, n1 = 1, n2 = 2, n3 = 2, n4 = 4, v = 0.2)

Arguments

vismodeldata

(required) quantum catch color data. Can be either the result from vismodel or independently calculated data (in the form of a data frame with four columns, representing the avian cones).

qcatch

if the object is of class vismodel, such as one generated using pavo, this argument is ignored. If the object is a data frame of quantal catches from another source, this argument is used to specify what type of quantum catch is being used, so that the noise can be calculated accordingly:

• Qi: Quantum catch for each photoreceptor (default)
• fi: Quantum catch according to Fechner law (the signal of the receptor channel is proportional to the logarithm of the quantum catch)

vis

visual system phenotype to use in the model:

• tetra: Tetrachromatic color vision (default)
• tri: Trichromatic color vision
• di: Dichromatic color vision

noise

how the noise will be calculated:

• neural: noise is proportional to the Weber fraction and is independent of the intensity of the signal received.
• quantum: noise is the sum of the neural noise and receptor noise, and is thus proportional to the Weber fraction and inversely proportional to the intensity of the signal received (the quantum catches). Note that the quantum option will only work with objects of class vismodel.

subset

If only some of the comparisons should be returned, a character vector of length 1 or 2 can be provided, indicating which samples are desired. The subset vector must match the labels of the imput samples, but partial matching (and regular expressions) are supported.

achro

logical. If TRUE, last column of the data frame is used to calculate the achromatic contrast, with noise based on the Weber fraction calculated using n4

n1, n2, n3, n4

tetrachromatic photoreceptor densities for u, s, m & l (default to blue tit Cyanistes caeruleus densities: 1:2:2:4). If vis does not equal 'tetra', only n1 and n2 (vis='di') or n1, n2 and n3 (vis='tri') are used for chromatic contrast (NOTE: n4 is still the value used for the achromatic contrast.)

v

Noise-to-signal ratio of a single cone (defaults to 0.2, so that under the default densities, the Weber fraction for the large cone will be 0.1, as estimated from behavioral experiment with the Perkin robin, Leiothrix lutea)

Value

A data frame containing 4 columns. The first two (patch1, patch2) refer to the two colors being contrasted; dS is the chromatic contrast (delta S, in JNDs) and dL is the achromatic contrast (delta L, in JNDs)

References

Vorobyev, M., Osorio, D., Bennett, A., Marshall, N., & Cuthill, I. (1998). Tetrachromacy, oil droplets and bird plumage colours. Journal Of Comparative Physiology A-Neuroethology Sensory Neural And Behavioral Physiology, 183(5), 621-633.

Hart, N. S. (2001). The visual ecology of avian photoreceptors. Progress In Retinal And Eye Research, 20(5), 675-703.

Endler, J. A., & Mielke, P. (2005). Comparing entire colour patterns as birds see them. Biological Journal Of The Linnean Society, 86(4), 405-431.

Examples

## Not run: 
# data(sicalis)
# vis.sicalis <- vismodel(sicalis, visual='avg.uv', relative=FALSE)
# coldist.sicalis <- coldist(vis.sicalis, vis='tetra')## End(Not run)