Plot a CIE (XYZ, LAB, or LCH) chromaticity diagram.
Usage
cieplot(
ciedata,
mono = TRUE,
out.lwd = NULL,
out.lcol = "black",
out.lty = 1,
theta = 45,
phi = 10,
r = 1e+06,
zoom = 1,
box = FALSE,
ciebg = TRUE,
...
)
Arguments
- ciedata
(required). a data frame, possibly a result from the
colspace()
orcie()
function, containing values for 'x', 'y' and 'z' coordinates for the CIEXYZ model, or LAB coordinates for the CIELAB (or CIELCh models), as columns (labeled as such).- mono
should the monochromatic loci (the 'horseshoe') be plotted when
space = "ciexyz"
? Defaults toTRUE
.- out.lwd, out.lcol, out.lty
graphical parameters for the plot outline.
- theta
angle to rotate the plot in the xy plane when
space = "cielab"
(defaults to 10).- phi
angle to rotate the plot in the yz plane when
space = "cielab"
(defaults to 45).- r
the distance of the eyepoint from the center of the plotting box when
space = "cielab"
. Very high values approximate an orthographic projection (defaults to 1e6). Seegraphics::persp()
for details.- zoom
zooms in (values greater than 1) or out (values between 0 and 1) from the plotting area when
space = "cielab"
.- box
logical. Should the plot area box and axes be plotted? (defaults to
FALSE
)- ciebg
should the colour background be plotted for CIEXYZ plot? (defaults to
TRUE
)- ...
additional graphical options. See
par()
.
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.
Stockman, A., & Sharpe, L. T. (2000). Spectral sensitivities of the middle- and long-wavelength sensitive cones derived from measurements in observers of known genotype. Vision Research, 40, 1711-1737.
CIE (2006). Fundamental chromaticity diagram with physiological axes. Parts 1 and 2. Technical Report 170-1. Vienna: Central Bureau of the Commission Internationale de l Eclairage.
Examples
# Load floral reflectance spectra
data(flowers)
# CIEXYZ
# Estimate quantum catches, using the cie10-degree viewer matching function
vis.flowers <- vismodel(flowers, visual = "cie10", illum = "D65", vonkries = TRUE, relative = FALSE)
# Run the ciexyz model
xyz.flowers <- colspace(vis.flowers, space = "ciexyz")
# Visualise the floral spectra in a ciexyz chromaticity diagram
plot(xyz.flowers)
# CIELAB
# Using the quantum catches above, instead model the spectra in the CIELab
# space
lab.flowers <- colspace(vis.flowers, space = "cielab")
# And plot in Lab space
plot(lab.flowers)