Simulate mixing of colors in Munsell notation, similar to the way in which mixtures of pigments operate.
vector of colors in Munsell notation
vector of proportions, can sum to any number
approach used to simulate a mixture:
exact: simulate a subtractive mixture of pigments, color conversion via CIE1931 color-matching functions (see details)
reference: simulate a subtractive mixture of pigments, selecting
n closest reference spectra from
estimate: closest Munsell chip to a weighted mean of CIELAB coordinates (fastest)
exact method when possible, falling-back to
estimate (weighted mean of CIELAB coordinates) otherwise
number of closest matching color chips (
mixingMethod = reference only)
keep weighted geometric mean spectra, final result is a
mixingMethod = reference only)
spectral distance used to compute
scaledDistance, default value is based on an analysis of spectral distances associated with adjacent Munsell color chips. This argument is only used with
mixingMethod = 'reference'.
additional arguments to
data.frame with the closest matching Munsell color(s):
munsell: Munsell notation of the n-closest spectra
distance: spectral (Gower) distance to the n-closest spectra
scaledDistance: spectral distance scaled by
mixingMethod: method used for each mixture
keepMixedSpec = TRUE then a
data.frame containing the same elements as above
spec: spectra for the 1st closest match
See the expanded tutorial for examples.
An accurate simulation of pigment mixtures ("subtractive" color mixtures) is incredibly complex due to factors that aren't easily measured or controlled: pigment solubility, pigment particle size distribution, water content, substrate composition, and physical obstruction to name a few. That said, it is possible to simulate reasonable, subtractive color mixtures given a reference spectra library (350-800nm) and some assumptions about pigment qualities and lighting. For the purposes of estimating a mixture of soil colors (these are pigments after all) we can relax these assumptions and assume a standard light source. The only missing piece is the spectral library for all Munsell chips in our color books.
Thankfully, Scott Burns has outlined the entire process, and Paul Centore has provided a Munsell color chip reflectance spectra library. The estimation of a subtractive mixture of soil colors can proceed as follows:
look up the associated spectra for each color in
compute the weighted (
w argument) geometric mean of the spectra
convert the spectral mixture to the closest Munsell color via:
search for the closest
n matching spectra in the reference library (
mixtureMethod = 'reference')
direct conversion of spectra to closest Munsell color via
mixtureMethod = 'exact')
suggest resulting Munsell chip(s) as the best candidate for a simulated mixture
Key assumptions include:
similar particle size distribution
similar mineralogy (i.e. pigmentation qualities)
similar water content.
For the purposes of estimating (for example) a "mixed soil color within the top 18cm of soil" these assumptions are usually valid. Again, these are estimates that are ultimately "snapped" to the nearest chip and not do not need to approach the accuracy of paint-matching systems.
A message is printed when
scaledDistance is larger than 1.
Marcus, R.T. (1998). The Measurement of Color. In K. Nassau (Ed.), Color for Science, Art, and Technology (pp. 32-96). North-Holland.
inspiration / calculations based on the work of Scott Burns: https://arxiv.org/ftp/arxiv/papers/1710/1710.06364.pdf
related discussion on Stack Overflow: https://stackoverflow.com/questions/10254022/implementing-kubelka-munk-like-krita-to-mix-colours-color-like-paint/29967630#29967630