View source: R/colorQuantiles.R
colorQuantiles | R Documentation |
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))
soilColors |
vector of R colors (sRGB colorspace) |
p |
marginal quantiles of interest |
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()
.
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
D.E. Beaudette
## Not run:
# 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)
## End(Not run)
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