Estimate central tendency and spread of soil color using marginal quantiles and L1 median of CIELAB coordinates.

colorQuantiles(soilColors, p = c(0.05, 0.5, 0.95))

Arguments

soilColors

vector of R colors (sRGB colorspace)

p

marginal quantiles of interest

Value

A List containing the following elements:

  • marginal: data.frame containing marginal quantiles in CIELAB (D65), closest Munsell chips, and dE00

  • L1: L1 median CIELAB (D65) values, closest Munsell chip, and dE00

Details

Colors are converted from sRGB to CIELAB (D65 illuminant), marginal quantiles of (L,A,B) coordinates are estimated, and L1 median (L,A,B) is estimates. The closest Munsell chips (via Munsell/CIELAB lookup table provided by munsell) and R colors are determined by locating chips closest to the marginal quantiles and L1 median.

The results can be conveniently inspected using plotColorQuantiles().

Author

D.E. Beaudette

Examples


if (FALSE) {
# example data, see manual page for details
data(sp5)

# slice top 25 cm
# 24-25cm is the last slice
s <- dice(sp5, 0:24 ~ .)

# check some of the data
par(mar=c(0,0,0,0))
plotSPC(sample(s, 25), divide.hz = FALSE, name = '', print.id = FALSE, width = 0.5)

# colors
previewColors(unique(s$soil_color))

# compute marginal quantiles and L1 median
cq <- colorQuantiles(s$soil_color)

# simple graphical display of results
plotColorQuantiles(cq)
}