From 48726d1535719046d3651650f55be04065774c4f Mon Sep 17 00:00:00 2001 From: Beaudette Date: Thu, 26 Sep 2024 13:48:06 -0700 Subject: [PATCH] half-value chip interpolation works well, but leads to many non-standard chips in the `munsell` reference set #318 This breaks many existing tests, and many years of expected behavior. --- R/munsell2rgb.R | 5 + data/munsell.rda | Bin 336680 -> 576452 bytes misc/utils/Munsell/interpolate-spectra.R | 36 +++- misc/utils/Munsell/local-functions.R | 41 +++- misc/utils/Munsell/main.R | 6 +- misc/utils/Munsell/munsell-LUT-2024-09-25.rds | Bin 0 -> 368185 bytes misc/utils/Munsell/prepare-munsell-LUT.R | 203 ++++++++++++++---- .../Munsell/simplified-Munsell-spectra.rds | Bin 0 -> 242744 bytes 8 files changed, 237 insertions(+), 54 deletions(-) create mode 100644 misc/utils/Munsell/munsell-LUT-2024-09-25.rds create mode 100644 misc/utils/Munsell/simplified-Munsell-spectra.rds diff --git a/R/munsell2rgb.R b/R/munsell2rgb.R index e661b946a..e71445b7d 100644 --- a/R/munsell2rgb.R +++ b/R/munsell2rgb.R @@ -382,11 +382,16 @@ munsell2rgb <- function(the_hue, the_value, the_chroma, alpha = 1, maxColorValue # plyr::join() 2x faster than base::merge # data.table::merge() (with conversion to/from) 5x faster than base::merge() + ## TODO: maybe more efficient with keys # round-trip through data.table is still faster d <- data.table::as.data.table(d) munsell <- data.table::as.data.table(munsell) + + ## TODO: optimize by first filtering full lookup table on e.g. hue + + # join res <- merge(d, munsell, by = c('hue','value','chroma'), all.x = TRUE, sort = FALSE) diff --git a/data/munsell.rda b/data/munsell.rda index de8e7a90180411f4ea767d9c0a3e67d835d31d3c..7546ffdbe903a02e3ced244272fcf2a014938d86 100644 GIT binary patch literal 576452 zcmV(rK<>Z&H+ooF0004LBHlIv03iV!0000G&sfapMW^rnT>vQ&2UKVgRpfkl( zs@ z=2uIUXe|dn`fIq>Lf;e&{wy<_O${e|% zUfk&(vy(N==4Pajnw?B)h+J!5&{1IN7^b#?+$pW+921A(q7E&1v1Hb7Q%NU4OlTDQo}0A_v77RZ%&kLBcz;CpoS6tnm#^^%Dl 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constant + m.new <- data.frame( + H = m.i$H[1], + V = new.V, + C = m.i$C[1], + p1 = s.1(new.V), + p2 = s.2(new.V), + p3 = s.3(new.V) + ) + + names(m.new) <- c('H', 'V', 'C', 'x', 'y', 'Y') + + # only return new rows + return(m.new) +} + +## NOTE: this can only interpolate between two integer values # 2022-03-29 # for now only interpolating 2.5 value # usually interpolating xyY, diff --git a/misc/utils/Munsell/main.R b/misc/utils/Munsell/main.R index 4ab53c6bb..e8b4ac12a 100644 --- a/misc/utils/Munsell/main.R +++ b/misc/utils/Munsell/main.R @@ -1,9 +1,11 @@ ## Code / Data related to preparation of Munsell color interpretation in aqp -## 2022-03-29 +## 2024-09-26 ## D.E. Beaudette, A.G. 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z{?FuQf1fBHmB5G%oBqew*&@QCRsLh^mW^xE>5Y$n|N0j;#QOgN&s%$9S*r>FJ;d)~ literal 0 HcmV?d00001 diff --git a/misc/utils/Munsell/prepare-munsell-LUT.R b/misc/utils/Munsell/prepare-munsell-LUT.R index de7caad00..b661b635e 100644 --- a/misc/utils/Munsell/prepare-munsell-LUT.R +++ b/misc/utils/Munsell/prepare-munsell-LUT.R @@ -156,16 +156,17 @@ p1 <- xyplot(y ~ C | factor(V), groups = H, data = m, subset = H %in% c('2.5YR', p2 <- xyplot(y ~ C | factor(V), groups = H, data = m.new.chroma, subset = H %in% c('2.5YR', '2.5Y', '5G'), type = 'p', par.settings = tactile.theme(), as.table = TRUE, scales = list(alternating = 1), cex = 0.5, pch = 16) # good -p.1 + p.2 +p1 + p2 # verify odd chroma frequencies table(m.new.chroma$C) + ## TODO: # * vectorize interpolateValue() or re-factor # * do we need multivariate interpolation? -# +# * safely handle impossible interpolation (missing end points ~ some hues) .n <- length(unique(m.new.chroma$C[m.new.chroma$H %in% c('2.5Y', '2.5YR', '2.5R')])) .cols <- hcl.colors(n = .n, palette = 'blues3') @@ -220,44 +221,59 @@ xyplot( ## interpolate all half-value chips -# .s <- seq(from = 1.5, to = 9.5, by = 1) -# map(m.new.chroma, .f = interpolateValue, .progress = TRUE) +z <- split(m.new.chroma, list(m.new.chroma$H, m.new.chroma$C)) +zz <- map(z, .f = interpolateValue2, .progress = TRUE) +# remove NULLs +# these are H/C combinations where interpolation is not possible +idx <- which(!sapply(zz, is.null)) +zz <- zz[idx] +zz <- do.call('rbind', zz) +nrow(zz) -## interpolate 2.5 values -# only need 2 value-slices -m.sub <- subset(m.new.chroma, V %in% c(2, 3)) -m.sub <- split(m.sub, list(m.sub$H, m.sub$C)) +# stack interpolated values +m.new.chroma <- rbind(m.new.chroma, zz) -# note: some combinations are missing values 2 AND 3 -table(sapply(m.sub, nrow)) -# 0 1 2 -# 1102 140 718 - -# only process those with 2 records -idx <- which(sapply(m.sub, nrow) == 2) -m.sub <- m.sub[idx] +# sort +m.new.chroma <- m.new.chroma[order(m.new.chroma$H, m.new.chroma$V, m.new.chroma$C), ] -m.2.5.values <- map(m.sub, .f = interpolateValue, .progress = TRUE) -m.2.5.values <- do.call('rbind', m.2.5.values) +str(m.new.chroma) -# 758 rows -nrow(m.2.5.values) -head(m.2.5.values) -## stack interpolated 2.5 values -m.new.chroma <- rbind(m.new.chroma, m.2.5.values) +# ## interpolate 2.5 values +# # only need 2 value-slices +# m.sub <- subset(m.new.chroma, V %in% c(2, 3)) +# m.sub <- split(m.sub, list(m.sub$H, m.sub$C)) +# +# # note: some combinations are missing values 2 AND 3 +# table(sapply(m.sub, nrow)) +# # 0 1 2 +# # 1102 140 718 +# +# # only process those with 2 records +# idx <- which(sapply(m.sub, nrow) == 2) +# m.sub <- m.sub[idx] +# +# m.2.5.values <- map(m.sub, .f = interpolateValue, .progress = TRUE) +# m.2.5.values <- do.call('rbind', m.2.5.values) +# +# # 758 rows +# nrow(m.2.5.values) +# head(m.2.5.values) +# +# ## stack interpolated 2.5 values +# m.new.chroma <- rbind(m.new.chroma, m.2.5.values) +# +# # sort +# m.new.chroma <- m.new.chroma[order(m.new.chroma$H, m.new.chroma$V, m.new.chroma$C), ] -# sort -m.new.chroma <- m.new.chroma[order(m.new.chroma$H, m.new.chroma$V, m.new.chroma$C), ] -str(m.new.chroma) ## graphical check g <- make.groups( m.new.chroma, - m.2.5.values + zz ) # ok @@ -275,6 +291,20 @@ xyplot( xlim = c(0, 10) ) +xyplot( + y ~ V | factor(C), + groups = which, + data = g, + subset = H %in% c('2.5YR'), + type = 'p', + par.settings = tactile.theme(), + as.table = TRUE, + scales = list(alternating = 1), + cex = 0.5, + pch = 16, + xlim = c(0, 10) +) + xyplot( x ~ V | factor(C), groups = which, @@ -290,6 +320,50 @@ xyplot( ) +.n <- length(unique(m.new.chroma$C[m.new.chroma$H %in% c('2.5Y', '2.5YR', '2.5R')])) +.cols <- hcl.colors(n = .n, palette = 'zissou1') + +xyplot( + x ~ V | factor(H), + groups = C, + data = m.new.chroma, + subset = H %in% c('2.5Y', '2.5YR', '2.5R'), + type = 'b', + par.settings = tactile.theme( + background = list(col = 'black'), + axis.text = list(col = 'white'), + par.xlab.text = list(col = 'white'), + par.ylab.text = list(col = 'white'), + superpose.symbol = list(col = .cols, pch = 16), + superpose.line = list(col = .cols, lwd = 1) + ), + as.table = TRUE, + scales = list(alternating = 1, x = list(at = seq(1, 10))), + panel = function(...) { + panel.grid(-1, -1) + panel.xyplot(...) + } +) + +xyplot( + x ~ V | factor(H), + groups = C, + data = m.new.chroma, + subset = H %in% c('2.5Y', '2.5YR', '2.5R'), + type = 'b', + par.settings = tactile.theme( + superpose.symbol = list(col = .cols, pch = 16), + superpose.line = list(col = .cols, lwd = 1) + ), + as.table = TRUE, + scales = list(alternating = 1, x = list(at = seq(1, 10))), + panel = function(...) { + panel.grid(-1, -1) + panel.xyplot(...) + } +) + + ## ## convert xyY [C] ---> XYZ [D65] @@ -320,15 +394,20 @@ m.final <- data.frame(m.new.chroma, m.sRGB) plot_cols <- rgb(m.final$R, m.final$G, m.final$B) -p1 <- xyplot(V ~ C | factor(H, levels=c('2.5Y', '10YR', '7.5YR', '5YR', '2.5YR', '10R')), - main="Common Soil Colors", - data=m.final, subset=H %in% c('2.5Y', '10YR', '7.5YR', '5YR', '2.5YR', '10R') & V > 1 & V <= 8 & C <= 8, - as.table=TRUE, subscripts=TRUE, xlab='Chroma', ylab='Value', - par.settings = tactile.theme(), - panel=function(x, y, subscripts, ...) - { - panel.xyplot(x, y, pch=15, cex=2, col=plot_cols[subscripts]) - } +p1 <- xyplot( + V ~ C | factor(H, levels = c('2.5Y', '10YR', '7.5YR', '5YR', '2.5YR', '10R')), + main = "Common Soil Colors", + data = m.final, + subset = H %in% c('2.5Y', '10YR', '7.5YR', '5YR', '2.5YR', '10R') & V <= 8 & C <= 8, + as.table = TRUE, + subscripts = TRUE, + scales = list(alternating = 1, y = list(at = 1:8)), + xlab = 'Chroma', + ylab = 'Value', + par.settings = tactile.theme(), + panel = function(x, y, subscripts, ...) { + panel.xyplot(x, y, pch = 15, cex = 2, col = plot_cols[subscripts]) + } ) p1 @@ -374,7 +453,8 @@ n.agg.final <- n.agg.final[order(n.agg.final$V), ] # combine m.final <- rbind(m.final, n.agg.final) -# 9227 +# 2022: 9,227 (2.5 value chips) +# 2024: 15,709 (all half-value chips) nrow(m.final) @@ -392,17 +472,32 @@ row.names(m.final.lab) <- NULL str(m.final.lab) + ## -## check +## check differences from previous versions of the LUT ## +## 2022: +## the new N chips are the top differences +## everything else has dE00 < 4 +## mostly value == 1 + + +## 2024: +## dE00 > 0.4 (but all < 1.5) are 2.5 value chips +## +## likely related to interpolation over full range of V vs. single, linear interpolation 2->2.5<-3 + + + + ## make backup copy of old LUT # data(munsell) -# saveRDS(munsell, file = 'munsell-LUT-2022-03-29.rds') +# saveRDS(munsell, file = 'munsell-LUT-2024-09-25.rds') -z.old <- readRDS('munsell-LUT-2022-03-29.rds') +z.old <- readRDS('munsell-LUT-2024-09-25.rds') -z <- merge(z.old, m.final.lab, by = c('hue', 'value', 'chroma'), all.x = TRUE) +z <- merge(z.old, m.final.lab, by = c('hue', 'value', 'chroma'), all.x = TRUE, sort = FALSE) str(z) @@ -431,6 +526,8 @@ for(i in 1:nrow(z)) { ) } +hist(d) + # changes with dE00 > 2 idx <- which(d > 2) @@ -444,9 +541,19 @@ table(zz$hue) table(zz$value) table(zz$chroma) -## N chips are the top differences -## everything else is dE00 < 4 -## mostly value == 1 + +# changes with dE00 > 0.4 +idx <- which(d > 0.4) +zz <- z[idx, ] +zz$dE00 <- d[idx] +zz <- zz[order(zz$dE00, decreasing = TRUE), ] + +nrow(zz) +head(zz, 20) + +table(zz$hue) +table(zz$value) +table(zz$chroma) @@ -460,6 +567,12 @@ save(munsell, file = '../../../data/munsell.rda', compress = 'xz') ## install / or reload from source +munsell2rgb('10YR', 9, 2, returnLAB = TRUE) +munsell2rgb('10YR', 9.5, 2, returnLAB = TRUE) + +# dE00 ~ 3 +# colorContrastPlot('10YR 9/2', '10YR 9.5/2') + munsell2rgb('10YR', 3.5, 2, returnLAB = TRUE) munsell2rgb('10YR', 4, 2, returnLAB = TRUE) @@ -472,7 +585,7 @@ munsell2rgb('10YR', 5, 1, returnLAB = TRUE) # check neutral -m <- sprintf('N %s/', 2:9) +m <- sprintf('N %s/', c(2, 2.5, 3:8)) cols <- parseMunsell(m) soilPalette(cols, lab = m) diff --git 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