# jnd2xyz: Convert JND distances into perceptually-corrected Cartesian... In pavo: Perceptual Analysis, Visualization and Organization of Spectral Colour Data

 jnd2xyz R Documentation

## Convert JND distances into perceptually-corrected Cartesian coordinates

### Description

Converts a `coldist()` output into Cartesian coordinates that are perceptually-corrected (i.e. noise-weighted Euclidean distances)

### Usage

``````jnd2xyz(
coldistres,
center = TRUE,
rotate = TRUE,
rotcenter = c("mean", "achro"),
ref1 = "l",
ref2 = "u",
axis1 = c(1, 1, 0),
axis2 = c(0, 0, 1)
)
``````

### Arguments

 `coldistres` (required) the output from a `coldist()` call. `center` logical indicating if the data should be centered on its centroid (defaults to `TRUE`). `rotate` logical indicating if the data should be rotated (defaults to `TRUE`). `rotcenter` should the vectors for rotation be centered in the achromatic center ("achro") or the data centroid ("mean", the default)? `ref1` the cone to be used as a the first reference. May be `NULL` (for no first rotation in the 3-dimensional case) or must match name in the original data that was used for `coldist()`. Defaults to 'l'. `ref2` the cone to be used as a the second reference. May be `NULL` (for no first rotation in the 3-dimensional case) or must match name in the original data that was used for `coldist()`. Defaults to 'u'. (only used if data has 3 dimensions). `axis1` A vector of length 3 composed of 0's and 1's, with 1's representing the axes (x, y, z) to rotate around. Defaults to c(1, 1, 0), such that the rotation aligns with the xy plane (only used if data has 2 or 3 dimensions). Ignored if `ref1` is `NULL` (in 3-dimensional case only) `axis2` A vector of length 3 composed of 0's and 1's, with 1's representing the axes (x, y, z) to rotate around. Defaults to c(0, 0, 1), such that the rotation aligns with the z axis (only used if data has 3 dimensions). Ignored if `ref2` is `NULL` (in 3-dimensional case only)

### Author(s)

Rafael Maia rm72@zips.uakron.edu

### References

Pike, T.W. (2012). Preserving perceptual distances in chromaticity diagrams. Behavioral Ecology, 23, 723-728.

Maia, R., White, T. E., (2018) Comparing colors using visual models. Behavioral Ecology, ary017 \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1093/beheco/ary017")}

### Examples

``````# Load floral reflectance spectra
data(flowers)

# Estimate quantum catches visual phenotype of a Blue Tit
vis.flowers <- vismodel(flowers, visual = 'bluetit')

# Estimate noise-weighted colour distances between all flowers
cd.flowers <- coldist(vis.flowers)

# Convert points to Cartesian coordinates in which Euclidean distances are
# noise-weighted.
jnd2xyz(cd.flowers)
``````

pavo documentation built on Sept. 24, 2023, 5:06 p.m.