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aqp (version 1.29)

mixMunsell: Mix Munsell Colors via Spectral Library

Description

Simulate mixing of colors in Munsell notation, similar to the way in which mixtures of pigments operate.

Usage

mixMunsell(
  x,
  w = rep(1, times = length(x))/length(x),
  mixingMethod = c("spectra", "estimate", "adaptive"),
  n = 1,
  keepMixedSpec = FALSE,
  distThreshold = 0.025
)

Arguments

x

vector of colors in Munsell notation

w

vector of proportions, can sum to any number

mixingMethod

approach used to simulate a mixture:

  • spectra: simulate a subtractive mixture of pigments, limited to available reference spectra

  • estimate: closest Munsell chip to a weighted mean of CIELAB coordinates

  • adaptive: use reference spectra when possible, falling-back to weighted mean of CIELAB coordinates

n

number of closest matching color chips (mixingMethod = spectra only)

keepMixedSpec

keep weighted geometric mean spectra, final result is a list (mixingMethod = spectra only)

distThreshold

spectral distance used to compute scaledDistance, default value is based on an analysis of spectral distances associated with adjacent Munsell color chips.

Value

A 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 distThreshold

  • mixingMethod: method used for each mixture

When keepMixedSpec = TRUE then a list:

  • mixed: a data.drame containing the same elements as above

  • spec: spectra for the 1st closest match

Details

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:

  1. look up the associated spectra for each color

  2. computed the weighted (area proportion) geometric mean of the spectra

  3. search for the closest matching spectra in the reference library

  4. suggest that Munsell chip as the best candidate for the 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.

References

See Also

munsell.spectra