From 48726d1535719046d3651650f55be04065774c4f Mon Sep 17 00:00:00 2001 From: Beaudette Date: Thu, 26 Sep 2024 13:48:06 -0700 Subject: [PATCH 1/9] 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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z+-5#PjnSj{ak@ni36tCNpWEJ8R$4mXBCbO16Q(0N(YGr1e;D!q>}Y^dQlV505;@a@ zv2K<;Fx5=z_N#_zINLiOz5|}k$CeCF(u&PaL&bpSjP=zGdyCD^ytMw1oU$-W)8;4% z*ntB!T8`bi)p7Zu8cx&7EQXD%gW{D|)+xFh3+`=6qzz0!X#Jnao&<8!QL-r!4J!O4 zlE^wwB+H^}V<&jc$Op*=4+2HvUmo7jPveNt+0y|?~+)_1bMvqg6vMzOZc!SKq_7C_S< z$QbSzr(DD%!<%m)+mEa@`X?T(E%#bA6vfj%JNoC$>C0}QwV?K Date: Mon, 30 Sep 2024 14:29:38 -0700 Subject: [PATCH 2/9] simplifying, trying only 2.5, 8.5, and 9.5 values --- data/munsell.rda | Bin 576452 -> 379828 bytes data/munsell.spectra.rda | Bin 554652 -> 834940 bytes data/munsell.spectra.wide.rda | Bin 474544 -> 755040 bytes misc/utils/Munsell/interpolate-spectra.R | 76 +++++++---- misc/utils/Munsell/local-functions.R | 42 ++++--- misc/utils/Munsell/prepare-munsell-LUT.R | 118 +++++++++++------- .../Munsell/simplified-Munsell-spectra.rds | Bin 242744 -> 0 bytes 7 files changed, 153 insertions(+), 83 deletions(-) delete mode 100644 misc/utils/Munsell/simplified-Munsell-spectra.rds diff --git a/data/munsell.rda 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z%EOLtT}S$hy|3#Xt9nDR@C2s-(@pP;!cFp1#1Fk8A max(C)
   # but only where we are missing data
-  C.original <- m.i$C
-  C.full <- seq(from = 1, to = max(m.i$C), by = 1)
-  C.new <- setdiff(C.full, C.original)
-  
-  # eval spline functions along missing points
-  p.x <- s.x(C.new)
-  p.y <- s.y(C.new)
+  .original <- m.i$C
+  .full <- seq(from = 1, to = max(m.i$C), by = 1)
+  .new <- setdiff(.full, .original)
   
   # combine interpolated values into data.frame
   # H, V, Y are constant
   m.new <- data.frame(
     H = m.i$H[1],
     V = m.i$V[1],
-    C = C.new,
-    x = p.x,
-    y = p.y,
-    Y= m.i$Y[1]
+    C = .new,
+    x = s.x(.new),
+    y = s.y(.new),
+    Y = m.i$Y[1]
   )
   
   # stack and re-order along C values
@@ -40,6 +39,7 @@ interpolateChroma <- function(m.i) {
 
 # 2024-09-26
 # re-write of interpolateValue() -> now safely interpolates all 0.5 values
+# m.i: data.frame of Munsell renotation data, for a single hue and chroma
 interpolateValue2 <- function(m.i) {
   
   # can only proceed with >=2 rows
@@ -49,17 +49,21 @@ interpolateValue2 <- function(m.i) {
     return(NULL)
   }
   
-  # linear interpolation ~ munsell value
+  # spline interpolation ~ munsell value
+  # fit is exact at training points
   # x ~ V
-  s.1 <- splinefun(m.i$V, m.i$x)
+  s.1 <- splinefun(m.i$V, m.i$x, method = 'natural')
   # y ~ V
-  s.2 <- splinefun(m.i$V, m.i$y)
+  s.2 <- splinefun(m.i$V, m.i$y, method = 'natural')
   # Y ~ V
-  s.3 <- splinefun(m.i$V, m.i$Y)
+  s.3 <- splinefun(m.i$V, m.i$Y, method = 'natural')
   
-  # all odd values
+  # new Munsell values for which interpolated xyY coordinates are required
+  # limited to the range of available value at this hue/chroma combination
   new.V <- seq(from = min(m.i$V) + 0.5, to = max(m.i$V) - 0.5, by = 1)
   
+  # TODO: coordinate with interpolation of spectra
+  
   # combine interpolated values into data.frame
   # H, C are constant
   m.new <- data.frame(
diff --git a/misc/utils/Munsell/prepare-munsell-LUT.R b/misc/utils/Munsell/prepare-munsell-LUT.R
index b661b635e..daa352409 100644
--- a/misc/utils/Munsell/prepare-munsell-LUT.R
+++ b/misc/utils/Munsell/prepare-munsell-LUT.R
@@ -1,3 +1,7 @@
+##
+##
+##
+
 library(latticeExtra)
 library(tactile)
 library(grDevices)
@@ -12,6 +16,7 @@ source('local-functions.R')
 ## Notes / Ideas:
 ##
 ##   * univariate interpolation of odd-chroma and 0.5-value chips seems to work well
+##   * consider leaving values 0.2-0.8 for improved interpolation
 ##   * 
 ##
 
@@ -38,7 +43,7 @@ m$Y <- pmin(m$Y, 100)
 # rescale Y to [0,1]
 m$Y <- rescale(m$Y, to = c(0, 1))
 
-## remove vale < 1 --> 765 records
+## remove value < 1 --> 765 records
 m <- subset(m, V >= 1)
 
 
@@ -49,10 +54,10 @@ m <- subset(m, V >= 1)
 ##
 
 # also interpolate backwards to C == 1
-m.split <- split(m, list(m$H, m$V))
+z <- split(m, list(m$H, m$V))
 
 # this combines original + interpolated values
-m.new.chroma <- map(m.split, .f = interpolateChroma, .progress = TRUE)
+m.new.chroma <- map(z, .f = interpolateChroma, .progress = TRUE)
 m.new.chroma <- do.call('rbind', m.new.chroma)
 
 # 8460 rows
@@ -142,29 +147,75 @@ update(p1 + p2, auto.key = list(title = 'V'))
 
 
 # original
-p1 <- xyplot(x ~ C | factor(V), groups = H, data = m, subset = H %in% c('2.5YR', '2.5Y', '5G'), type = 'p', par.settings = tactile.theme(), as.table = TRUE, scales = list(alternating = 1), cex = 1.25, xlim = c(-1, 25)) 
+p1 <- xyplot(
+  x ~ C | factor(V), 
+  groups = factor(H, levels = c('2.5Y', '2.5YR', '2.5R')), 
+  data = m, 
+  type = 'p', 
+  par.settings = tactile.theme(), 
+  as.table = TRUE, 
+  scales = list(alternating = 1), 
+  cex = 1.25, 
+  xlim = c(-1, 25)
+) 
+
 # interpolated
-p2 <- xyplot(x ~ 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)
+p2 <- xyplot(
+  x ~ C | factor(V), 
+  groups = factor(H, levels = c('2.5Y', '2.5YR', '2.5R')), 
+  data = m.new.chroma, 
+  type = 'p', 
+  par.settings = tactile.theme(), 
+  as.table = TRUE, 
+  scales = list(alternating = 1), 
+  cex = 0.5, 
+  pch = 16
+)
 
 # good
-p1 + p2
+update(p1 + p2, auto.key = list(title = 'H'))
 
 
 # original
-p1 <- xyplot(y ~ C | factor(V), groups = H, data = m, subset = H %in% c('2.5YR', '2.5Y', '5G'), type = 'p', par.settings = tactile.theme(), as.table = TRUE, scales = list(alternating = 1), cex = 1.25, xlim = c(-1, 25)) 
+p1 <- xyplot(
+  x ~ C | factor(V), 
+  groups = factor(H, levels = c('2.5Y', '2.5YR', '2.5G')), 
+  data = m, 
+  type = 'p', 
+  par.settings = tactile.theme(), 
+  as.table = TRUE, 
+  scales = list(alternating = 1), 
+  cex = 1.25, 
+  xlim = c(-1, 25)
+) 
+
 # interpolated
-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)
+p2 <- xyplot(
+  x ~ C | factor(V), 
+  groups = factor(H, levels = c('2.5Y', '2.5YR', '2.5G')), 
+  data = m.new.chroma, 
+  type = 'p', 
+  par.settings = tactile.theme(), 
+  as.table = TRUE, 
+  scales = list(alternating = 1), 
+  cex = 0.5, 
+  pch = 16
+)
 
 # good
-p1 + p2
+update(p1 + p2, auto.key = list(title = 'H'))
+
+
 
-# verify odd chroma frequencies
+
+
+## verify odd chroma frequencies
+# good
 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)
 
@@ -238,37 +289,19 @@ m.new.chroma <- rbind(m.new.chroma, zz)
 # sort
 m.new.chroma <- m.new.chroma[order(m.new.chroma$H, m.new.chroma$V, m.new.chroma$C), ]
 
-str(m.new.chroma)
-
-
-# ## 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$C), ]
+# 15700
+nrow(m.new.chroma)
+
+
+## for now, retain specific Munsell value
+table(m.new.chroma$V)
 
+m.new.chroma <- subset(
+  m.new.chroma,
+  subset = V %in% c(1, 2, 2.5, 3, 4, 5, 6, 7, 8, 8.5, 9, 9.5, 10)
+)
 
+## TODO: flag within single data.frame, these two are out of sync
 
 ## graphical check
 g <- make.groups(
@@ -336,7 +369,7 @@ xyplot(
     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(...) {
@@ -454,7 +487,8 @@ n.agg.final <- n.agg.final[order(n.agg.final$V), ]
 m.final <- rbind(m.final, n.agg.final)
 
 # 2022: 9,227 (2.5 value chips)
-# 2024: 15,709 (all half-value chips)
+# 2024a: 15,709 (all half-value chips)
+# 2024b: 10,447 (select half-value chips)
 nrow(m.final)
 
 
diff --git a/misc/utils/Munsell/simplified-Munsell-spectra.rds b/misc/utils/Munsell/simplified-Munsell-spectra.rds
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z$QbSzr(DD%!<%m)+mEa@`X?T(E%#bA6vfj%JNoC$>C0}QwV?K
Date: Thu, 3 Oct 2024 11:53:25 -0700
Subject: [PATCH 3/9] relaxing tolerance in color tests, temporary skip() until
 closest chips are recalculated #318

---
 tests/testthat/test-color-signature.R     | 20 ++++++++++----------
 tests/testthat/test-mixMunsell.R          |  2 +-
 tests/testthat/test-similarMunsellChips.R |  5 +++--
 tests/testthat/test-spec2Munsell.R        |  2 +-
 4 files changed, 15 insertions(+), 14 deletions(-)

diff --git a/tests/testthat/test-color-signature.R b/tests/testthat/test-color-signature.R
index 5b8ed2dcf..e314d0a26 100644
--- a/tests/testthat/test-color-signature.R
+++ b/tests/testthat/test-color-signature.R
@@ -26,11 +26,11 @@ test_that("colorBucket", {
   
   # add more of these
   expect_equal(pig$id[1], 'P001')
-  expect_equal(pig$.white.pigment[1], 0.6351809, tolerance=0.001)
-  expect_equal(pig$.red.pigment[1], 0.10308427, tolerance=0.001)
-  expect_equal(pig$.green.pigment[1], 0, tolerance=0.001)
-  expect_equal(pig$.yellow.pigment[1], 0.2617348, tolerance=0.001)
-  expect_equal(pig$.blue.pigment[1], 0, tolerance=0.001)
+  expect_equal(pig$.white.pigment[1], 0.635, tolerance = 0.001)
+  expect_equal(pig$.red.pigment[1], 0.103, tolerance = 0.001)
+  expect_equal(pig$.green.pigment[1], 0, tolerance = 0.001)
+  expect_equal(pig$.yellow.pigment[1], 0.261, tolerance = 0.001)
+  expect_equal(pig$.blue.pigment[1], 0, tolerance = 0.001)
   
 })
 
@@ -46,11 +46,11 @@ test_that("depthSlices", {
   
   # add more of these
   expect_equal(pig$id[1], 'P001')
-  expect_equal(pig$A.0.1[1], 5.8741, tolerance=0.001)
-  expect_equal(pig$A.0.5[1], 5.5744, tolerance=0.001)
-  expect_equal(pig$B.0.1[1], 11.0712, tolerance=0.001)
-  expect_equal(pig$B.0.5[1], 17.8611, tolerance=0.001)
-  expect_equal(pig$L.0.1[1], 30.2502, tolerance=0.001)
+  expect_equal(pig$A.0.1[1], 5.87, tolerance = 0.01)
+  expect_equal(pig$A.0.5[1], 5.57, tolerance = 0.01)
+  expect_equal(pig$B.0.1[1], 11.07, tolerance = 0.01)
+  expect_equal(pig$B.0.5[1], 17.86, tolerance = 0.01)
+  expect_equal(pig$L.0.1[1], 30.25, tolerance = 0.01)
   
 })
 
diff --git a/tests/testthat/test-mixMunsell.R b/tests/testthat/test-mixMunsell.R
index 854d31b7a..347e348fc 100644
--- a/tests/testthat/test-mixMunsell.R
+++ b/tests/testthat/test-mixMunsell.R
@@ -97,7 +97,7 @@ test_that("mixing methods, except reference", {
   
   # fall-back to wt.mean CIELAB
   expect_message(mx <- mixMunsell(c('10YR 6/2', '10YR 1/1'), mixingMethod = 'adaptive'))
-  expect_true(mx$munsell[1] == '2.5Y 3/2')
+  expect_true(mx$munsell[1] == '10YR 3/1')
   
 })
 
diff --git a/tests/testthat/test-similarMunsellChips.R b/tests/testthat/test-similarMunsellChips.R
index 3a2970359..79bd2c6d2 100644
--- a/tests/testthat/test-similarMunsellChips.R
+++ b/tests/testthat/test-similarMunsellChips.R
@@ -1,9 +1,10 @@
 context("Equivalent Munsell Chips")
 
-
-
 test_that("equivalentMunsellChips works", {
 
+  ## TODO: these will need to be updated with new color entries in the munsell LUT
+  skip()
+  
   # same "chip page position" different hue page; identify all perceptually equivalent chips
   
   # test 1
diff --git a/tests/testthat/test-spec2Munsell.R b/tests/testthat/test-spec2Munsell.R
index 47907c529..eb615ab0b 100644
--- a/tests/testthat/test-spec2Munsell.R
+++ b/tests/testthat/test-spec2Munsell.R
@@ -27,7 +27,7 @@ test_that("spec2Munsell works as expected", {
     )
   
   # expected dE00
-  expect_equal(m$sigma, 0.64280, tolerance = 1e-4)
+  expect_equal(m$sigma, 0.64280, tolerance = 0.01)
       
 })
 

From 32f7bef2b50c8b2a3ac85056dc91f46af9f0cc9a Mon Sep 17 00:00:00 2001
From: Beaudette 
Date: Thu, 3 Oct 2024 12:38:52 -0700
Subject: [PATCH 4/9] code and commentary cleanup. caught some interpolated
 spectra < 0

---
 DESCRIPTION                                   |   2 +-
 data/munsell.spectra.rda                      | Bin 834940 -> 821388 bytes
 data/munsell.spectra.wide.rda                 | Bin 755040 -> 733472 bytes
 misc/utils/Munsell/interpolate-spectra.R      | 173 ++++++------------
 misc/utils/Munsell/local-functions.R          |  99 ++++++++++
 misc/utils/Munsell/main.R                     |   2 +-
 misc/utils/Munsell/prepare-munsell-LUT.R      |  72 +++++---
 .../prepare-simplfied-spectra-library.R       |   4 +
 8 files changed, 199 insertions(+), 153 deletions(-)

diff --git a/DESCRIPTION b/DESCRIPTION
index efc32ca62..89f400de6 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -15,6 +15,6 @@ URL: https://github.com/ncss-tech/aqp, https://ncss-tech.github.io/AQP/
 BugReports: https://github.com/ncss-tech/aqp/issues
 Language: en-US
 Encoding: UTF-8
-RoxygenNote: 7.3.1
+RoxygenNote: 7.3.2
 Roxygen: list(markdown = TRUE)
 VignetteBuilder: knitr
diff --git a/data/munsell.spectra.rda b/data/munsell.spectra.rda
index 845ecd9e401ee91418c3679ec66ed04b8bffceda..b90ac023d201202d73d2f7e6b7d21a6f0d401cfd 100644
GIT binary patch
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b00Fy-E|RrKl(@kcJ}?c70ssI200CKAT**eT diff --git a/misc/utils/Munsell/interpolate-spectra.R b/misc/utils/Munsell/interpolate-spectra.R index d3a114d88..995143ed2 100644 --- a/misc/utils/Munsell/interpolate-spectra.R +++ b/misc/utils/Munsell/interpolate-spectra.R @@ -14,10 +14,18 @@ library(tactile) library(purrr) library(reshape2) +source('local-functions.R') + # load simplified spectra m.rel <- readRDS('simplified-Munsell-spectra.rds') -## investigate slices -- can interpolate reflectance vs chroma (by wavelengths) for odd chroma +# review original range +range(m.rel$reflectance) +min.reflectance <- min(m.rel$reflectance) + +hist(m.rel$reflectance, breaks = 50) + +## interpolate spectra for odd Munsell chroma idx <- which(m.rel$hue %in% c('7.5YR') & m.rel$value == 3) s <- m.rel[idx, ] @@ -32,75 +40,6 @@ xyplot(reflectance ~ chroma | factor(wavelength), data=s, # split by hue/value/wavelength m <- split(m.rel, list(m.rel$hue, m.rel$value, m.rel$wavelength)) -## TODO: clamp to original range of Munsell chroma - -# interpolation of odd chroma -interpolateOddChromaSpectra <- function(i) { - - # 0-row input - if(nrow(i) < 1) - return(NULL) - - # chroma stats - u.chroma <- unique(i$chroma) - r.chroma <- range(u.chroma) - n.chroma <- length(u.chroma) - - # reflectance stats - r.reflectance <- range(i$reflectance) - - # sequence of candidate chroma - s <- seq(from = r.chroma[1], to = r.chroma[2], by = 1) - s.chroma <- setdiff(s, u.chroma) - - # short circuit: single chroma, interpolation impossible - if(n.chroma < 2) - return(NULL) - - # short circuit: 0 candidates for interpolation - if(length(s.chroma) < 1) - return(NULL) - - - # setup interpolation function: natural splines - # fit is exact at training points - af <- splinefun(i$chroma, i$reflectance, method = 'natural') - - # check: fit should be exact at points - if(sum(af(i$chroma) - i$reflectance) > 0.001){ - message('spline not fitting at training data!') - } - - # interpolate candidate chroma - s.reflectance <- af(s.chroma) - - # # check for over / undershoots - # if( ! (s.reflectance < r.reflectance[1] | s.reflectance > r.reflectance[2])){ - # message('spline exceeds original range!') - # } - - # re-assemble into original format - res <- data.frame( - munsell = sprintf("%s %s/%s", i$hue[1], i$value[1], s.chroma), - hue = i$hue[1], - value = i$value[1], - chroma = s.chroma, - wavelength = i$wavelength[1], - reflectance = s.reflectance, - stringsAsFactors = FALSE - ) - - - # debugging: graphical check - # OK - # plot(reflectance ~ chroma, data = i ) - # lines(seq(r.chroma[1], r.chroma[2], by = 0.1), af(seq(r.chroma[1], r.chroma[2], by = 0.1)), col = 'red') - # points(s.chroma, s.reflectance, pch = 15) - - return(res) - -} - # do interpolation mm <- map(m, .f = interpolateOddChromaSpectra, .progress = TRUE) @@ -113,7 +52,7 @@ m.final <- m.final[order(m.final$hue, m.final$value, m.final$chroma), ] # graphical check -idx <- which(m.final$hue %in% c('7.5YR') & m.final$value == 5) +idx <- which(m.final$hue %in% c('7.5YR') & m.final$value == 3) s <- m.final[idx, ] xyplot(reflectance ~ chroma | factor(wavelength), data=s, @@ -134,7 +73,8 @@ xyplot(reflectance ~ chroma | factor(wavelength), data=s, # check for reflectance <= 0 -m.final[m.final$reflectance <= 0, ] +# 6 rows +nrow(m.final[m.final$reflectance <= 0, ]) # hmm idx <- which(m.final$hue %in% c('2.5R') & m.final$value == 2) @@ -151,8 +91,18 @@ xyplot(reflectance ~ chroma | factor(wavelength), groups = reflectance <= 0, dat idx <- which(m.final$reflectance <= 0) m.final[idx, ] -# replace with minimum reflectance, ignoring these values -m.final$reflectance[idx] <- min(m.final$reflectance[-idx]) +# replace with original minimum reflectance, ignoring these values +m.final$reflectance[idx] <- min.reflectance + +xyplot(reflectance ~ chroma | factor(wavelength), groups = reflectance <= 0, + data = m.final, + subset = hue == '2.5R' & value == 2, + type='b', as.table=TRUE, + scales = list(y = list(tick.number = 10)), + auto.key=list(lines=FALSE, points=TRUE, cex=1, space='top'), + par.settings = tactile.theme() +) + ## check: OK @@ -177,58 +127,12 @@ xyplot(reflectance ~ wavelength, data = s, -## interpolate half-chip Munsell values - -# # just 2/3 value -# m.sub <- subset(m.final, subset = value %in% 2:3) -# -# head(m.sub) -# -# # check -# s <- subset(m.sub, subset = hue == '2.5YR' & chroma == 3) -# -# xyplot(reflectance ~ wavelength, data = s, -# groups = munsell, type='b', -# scales = list(y = list(tick.number = 10)), -# auto.key=list(lines=TRUE, points=FALSE, cex=1, space='top', columns = 2), -# par.settings = tactile.theme() -# ) - +## interpolate spectra for select half-chip Munsell values # split by hue/chroma/wavelength m <- split(m.final, list(m.final$hue, m.final$chroma, m.final$wavelength)) -## TODO: clamp to original range of Munsell value - -interpolateValueSpectra <- function(i) { - - # 0 or 1 row input: no interpolation possible - if(nrow(i) < 2) - return(NULL) - - # setup interpolation function: natural splines - # fit is exact at training points - a.fun <- splinefun(i$value, i$reflectance, method = 'natural') - - # new Munsell values - v.target <- c(2.5, 8.5, 9.5) - - # re-assemble into original format - res <- data.frame( - munsell = sprintf("%s %s/%s", i$hue[1], v.target, i$chroma[1]), - hue = i$hue[1], - value = v.target, - chroma = i$chroma[1], - wavelength = i$wavelength[1], - reflectance = a.fun(v.target), - stringsAsFactors = FALSE - ) - - return(res) -} - - # do interpolation mm <- map(m, .f = interpolateValueSpectra, .progress = TRUE) @@ -240,10 +144,35 @@ mm <- do.call('rbind', mm) m.final <- rbind(m.final, mm) m.final <- m.final[order(m.final$hue, m.final$value, m.final$chroma), ] - # check: OK str(m.final) + +# check for reflectance <= 0 +# 3403 rows, all very close to 0 +# most of these are very low value + low chroma | low value + high chroma +nrow(m.final[m.final$reflectance <= 0, ]) + +# hmm +idx <- which(m.final$munsell == '7.5YR 2.5/14') +s <- m.final[idx, ] + +xyplot(reflectance ~ chroma | factor(wavelength), groups = reflectance <= 0, data=s, + type='b', as.table=TRUE, + scales = list(y = list(tick.number = 10)), + auto.key=list(lines=FALSE, points=TRUE, cex=1, space='top'), + par.settings = tactile.theme() +) + +# probably spline undershoots +idx <- which(m.final$reflectance <= 0) + +# replace with minimum reflectance, ignoring these values +m.final$reflectance[idx] <- min.reflectance + + + + s <- subset(m.final, subset = hue == '10YR' & chroma == 4 & value %in% c(2, 2.5, 3, 4)) xyplot(reflectance ~ wavelength, data = s, diff --git a/misc/utils/Munsell/local-functions.R b/misc/utils/Munsell/local-functions.R index 5a1a971a6..1d98e1287 100644 --- a/misc/utils/Munsell/local-functions.R +++ b/misc/utils/Munsell/local-functions.R @@ -1,4 +1,103 @@ + + +## TODO: clamp to original range of Munsell chroma + +# interpolation of odd chroma +interpolateOddChromaSpectra <- function(i) { + + # 0-row input + if(nrow(i) < 1) { + return(NULL) + } + + # chroma stats + u.chroma <- unique(i$chroma) + r.chroma <- range(u.chroma) + n.chroma <- length(u.chroma) + + # reflectance stats + r.reflectance <- range(i$reflectance) + + # sequence of candidate chroma + s <- seq(from = r.chroma[1], to = r.chroma[2], by = 1) + s.chroma <- setdiff(s, u.chroma) + + # short circuit: single chroma, interpolation impossible + if(n.chroma < 2) + return(NULL) + + # short circuit: 0 candidates for interpolation + if(length(s.chroma) < 1) + return(NULL) + + + # setup interpolation function: natural splines + # fit is exact at training points + sf <- splinefun(i$chroma, i$reflectance, method = 'natural') + + # check: fit should be exact at points + if(sum(sf(i$chroma) - i$reflectance) > 0.001){ + message('spline not fitting at training data!') + } + + # interpolate candidate chroma + s.reflectance <- sf(s.chroma) + + # re-assemble into original format + res <- data.frame( + munsell = sprintf("%s %s/%s", i$hue[1], i$value[1], s.chroma), + hue = i$hue[1], + value = i$value[1], + chroma = s.chroma, + wavelength = i$wavelength[1], + reflectance = s.reflectance, + stringsAsFactors = FALSE + ) + + + # debugging: graphical check + # OK + # plot(reflectance ~ chroma, data = i ) + # lines(seq(r.chroma[1], r.chroma[2], by = 0.1), af(seq(r.chroma[1], r.chroma[2], by = 0.1)), col = 'red') + # points(s.chroma, s.reflectance, pch = 15) + + return(res) + +} + + +interpolateValueSpectra <- function(i) { + + # 0 or 1 row input: no interpolation possible + if(nrow(i) < 2) + return(NULL) + + # setup interpolation function: natural splines + # fit is exact at training points + a.fun <- splinefun(i$value, i$reflectance, method = 'natural') + + # new Munsell values + v.target <- c(2.5, 8.5, 9.5) + + # re-assemble into original format + res <- data.frame( + munsell = sprintf("%s %s/%s", i$hue[1], v.target, i$chroma[1]), + hue = i$hue[1], + value = v.target, + chroma = i$chroma[1], + wavelength = i$wavelength[1], + reflectance = a.fun(v.target), + stringsAsFactors = FALSE + ) + + return(res) +} + + + + + # 2022-03-29 # interpolate odd chroma from Munsell renotation data # m.i: subset renotation data.frame, for a single hue/value diff --git a/misc/utils/Munsell/main.R b/misc/utils/Munsell/main.R index e8b4ac12a..0864800b5 100644 --- a/misc/utils/Munsell/main.R +++ b/misc/utils/Munsell/main.R @@ -1,5 +1,5 @@ ## Code / Data related to preparation of Munsell color interpretation in aqp -## 2024-09-26 +## 2024-10-03 ## D.E. Beaudette, A.G. Brown # make Munsell and related LUT diff --git a/misc/utils/Munsell/prepare-munsell-LUT.R b/misc/utils/Munsell/prepare-munsell-LUT.R index daa352409..00a20ad87 100644 --- a/misc/utils/Munsell/prepare-munsell-LUT.R +++ b/misc/utils/Munsell/prepare-munsell-LUT.R @@ -1,5 +1,8 @@ +## Prepare `munsell` LUT from Renotation Database +## D.E. Beaudette +## 2024-10-03 ## -## +## Originally based on code from ~2006 as part of the Pedlogic project. ## library(latticeExtra) @@ -9,6 +12,9 @@ library(scales) library(purrr) library(aqp) + +# starting from aqp base directory +setwd('misc/utils/Munsell') source('local-functions.R') @@ -16,8 +22,8 @@ source('local-functions.R') ## Notes / Ideas: ## ## * univariate interpolation of odd-chroma and 0.5-value chips seems to work well -## * consider leaving values 0.2-0.8 for improved interpolation -## * +## * consider retaining values 0.2-0.8 for improved interpolation +## * is multivariate interpolation necessary? (I doubt it) ## @@ -217,7 +223,6 @@ table(m.new.chroma$C) ## TODO: # * 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') @@ -271,7 +276,10 @@ xyplot( +## ## interpolate all half-value chips +## + z <- split(m.new.chroma, list(m.new.chroma$H, m.new.chroma$C)) zz <- map(z, .f = interpolateValue2, .progress = TRUE) @@ -293,7 +301,7 @@ m.new.chroma <- m.new.chroma[order(m.new.chroma$H, m.new.chroma$V, m.new.chroma$ nrow(m.new.chroma) -## for now, retain specific Munsell value +## for backwards compatibility, retain specific Munsell values table(m.new.chroma$V) m.new.chroma <- subset( @@ -301,6 +309,10 @@ m.new.chroma <- subset( subset = V %in% c(1, 2, 2.5, 3, 4, 5, 6, 7, 8, 8.5, 9, 9.5, 10) ) +# check: ok +table(m.new.chroma$V) + + ## TODO: flag within single data.frame, these two are out of sync ## graphical check @@ -599,29 +611,31 @@ munsell <- m.final.lab 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) - -munsell2rgb('10YR', 2.5, 2, returnLAB = TRUE) -munsell2rgb('10YR', 2, 2, returnLAB = TRUE) - -munsell2rgb('10YR', 2, 1, returnLAB = TRUE) -munsell2rgb('10YR', 5, 1, returnLAB = TRUE) - - -# check neutral -m <- sprintf('N %s/', c(2, 2.5, 3:8)) -cols <- parseMunsell(m) -soilPalette(cols, lab = m) - +## 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) +# +# munsell2rgb('10YR', 2.5, 2, returnLAB = TRUE) +# munsell2rgb('10YR', 2, 2, returnLAB = TRUE) +# +# munsell2rgb('10YR', 2, 1, returnLAB = TRUE) +# munsell2rgb('10YR', 5, 1, returnLAB = TRUE) +# +# +# # check neutral +# m <- sprintf('N %s/', c(2, 2.5, 3:8)) +# cols <- parseMunsell(m) +# soilPalette(cols, lab = m) +# +# +# diff --git a/misc/utils/Munsell/prepare-simplfied-spectra-library.R b/misc/utils/Munsell/prepare-simplfied-spectra-library.R index 2526568a5..349b49215 100644 --- a/misc/utils/Munsell/prepare-simplfied-spectra-library.R +++ b/misc/utils/Munsell/prepare-simplfied-spectra-library.R @@ -1,3 +1,7 @@ +## Simplify the Munsell spectral reference data for later use. Results are temporary. +## +## + library(reshape2) # missing odd chroma From aed08e2dd385112353cdf2f791facaf3e3d9c58d Mon Sep 17 00:00:00 2001 From: Beaudette Date: Thu, 3 Oct 2024 14:06:59 -0700 Subject: [PATCH 5/9] notes for follow-up on interpolation / extrapolation errors --- misc/utils/Munsell/interpolate-spectra.R | 3 +- ...nvestigate-spectral-interpolation-errors.R | 42 +++++++++++++++++++ misc/utils/Munsell/main.R | 8 +++- 3 files changed, 50 insertions(+), 3 deletions(-) create mode 100644 misc/utils/Munsell/investigate-spectral-interpolation-errors.R diff --git a/misc/utils/Munsell/interpolate-spectra.R b/misc/utils/Munsell/interpolate-spectra.R index 995143ed2..c55fe092e 100644 --- a/misc/utils/Munsell/interpolate-spectra.R +++ b/misc/utils/Munsell/interpolate-spectra.R @@ -4,8 +4,7 @@ -## TODO: clamp to original range of Munsell chroma -## TODO: clamp to original range of Munsell value +## TODO: clamp to original range of Munsell chroma and value ## TODO: coordinate with `prepare-munsell-LUT.R` diff --git a/misc/utils/Munsell/investigate-spectral-interpolation-errors.R b/misc/utils/Munsell/investigate-spectral-interpolation-errors.R new file mode 100644 index 000000000..473030fe7 --- /dev/null +++ b/misc/utils/Munsell/investigate-spectral-interpolation-errors.R @@ -0,0 +1,42 @@ +library(purrr) + +data("munsell.spectra.wide") + +nm <- names(munsell.spectra.wide)[-1] +s <- sample(nm, size = 100) + +z <- do.call( + 'rbind', + map(s, .progress = TRUE, .f = function(i) { + spec2Munsell(munsell.spectra.wide[, i]) + }) +) + +z$m <- sprintf("%s %s/%s", z$hue, z$value, z$chroma) + +# compare +cc <- colorContrast( + m1 = s, + m2 = z$m +) + +hist(cc$dE00, breaks = 25) + +## TODO: investigate these +x <- cc[order(cc$dE00, decreasing = TRUE)[1:10], ] + +x + + +# 10G 9.5/10 +.m <- '5YR 2.5/10' +plot(munsell.spectra.wide[, 1], munsell.spectra.wide[, .m], type = 'b', las = 1, main = .m, ylim = c(0, 1.2)) +spec2Munsell(munsell.spectra.wide[, .m]) + + +# 10G 9.5/10 +.m <- '10G 9.5/10' +plot(munsell.spectra.wide[, 1], munsell.spectra.wide[, .m], type = 'b', las = 1, main = .m, ylim = c(0, 1.2)) +lines(munsell.spectra.wide[, 1], munsell.spectra.wide[, '10G 6/10'], type = 'b', col = 2) +lines(munsell.spectra.wide[, 1], munsell.spectra.wide[, '10G 8/6'], type = 'b', col = 2) +spec2Munsell(munsell.spectra.wide[, .m]) diff --git a/misc/utils/Munsell/main.R b/misc/utils/Munsell/main.R index 0864800b5..56f3c3005 100644 --- a/misc/utils/Munsell/main.R +++ b/misc/utils/Munsell/main.R @@ -19,8 +19,14 @@ source('traditional-names.R') # prepare a simplified spectral library of Munsell color chips source('prepare-simplfied-spectra-library.R') -# interpolate odd chroma and 2.5 value spectra +# interpolate odd chroma and select 1/2 chip value spectra source('interpolate-spectra.R') +# TODO: investigate poor agreement between +# Munsell reference and predicted CIELAB -> Munsell conversion +# these are probably extrapolation artifacts +source('investigate-spectral-interpolation-errors.R') + + # create Munsell hue position data source('make-munsellHuePosition.R') From 2dce354fb9be8007292224402b3a6479ff6f0273 Mon Sep 17 00:00:00 2001 From: Beaudette Date: Thu, 3 Oct 2024 14:10:36 -0700 Subject: [PATCH 6/9] todo for soil texture colors --- R/factor-level-setters.R | 18 ++++++++++++++++++ 1 file changed, 18 insertions(+) diff --git a/R/factor-level-setters.R b/R/factor-level-setters.R index aeb0871e5..8d893c004 100644 --- a/R/factor-level-setters.R +++ b/R/factor-level-setters.R @@ -1,6 +1,24 @@ ## ## + +## TODO: helper function for soil texture color palette +## final color scheme, after some editing +# c("s", "ls", "sl", "scl", "l", "sc", "c", "sic", "cl", "sil", "sicl", "si") +# cols <- c("#BEBEBE", "#FDFD9E", "#ebd834", "#307431", "#CD94EA", "#546BC3", "#92C158", "#EA6996", "#6D94E5", "#4C5323", "#E93F4A", "#AF4732" +) + +# # coordinate with basic and extended soil texture classes via col +# colorspace::swatchplot( +# list( +# basic = cols, +# extended = colorRampPalette(cols)(21) +# ) +# ) +# + + + ## TODO: consider various sorting strategies: WMPD, AWC, {PWP,FC,SAT} ## http://ncss-tech.github.io/AQP/aqp/water-retention-curves.html From f092ea78f65e1f360d7d71de5dcbe169457ddf69 Mon Sep 17 00:00:00 2001 From: Beaudette Date: Thu, 3 Oct 2024 14:26:21 -0700 Subject: [PATCH 7/9] =?UTF-8?q?typo=20=E2=86=92=20parse=20error,=20ugh?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- R/factor-level-setters.R | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/R/factor-level-setters.R b/R/factor-level-setters.R index 8d893c004..77b5288f0 100644 --- a/R/factor-level-setters.R +++ b/R/factor-level-setters.R @@ -5,8 +5,9 @@ ## TODO: helper function for soil texture color palette ## final color scheme, after some editing # c("s", "ls", "sl", "scl", "l", "sc", "c", "sic", "cl", "sil", "sicl", "si") -# cols <- c("#BEBEBE", "#FDFD9E", "#ebd834", "#307431", "#CD94EA", "#546BC3", "#92C158", "#EA6996", "#6D94E5", "#4C5323", "#E93F4A", "#AF4732" -) +# cols <- c( +# "#BEBEBE", "#FDFD9E", "#ebd834", "#307431", "#CD94EA", "#546BC3", "#92C158", "#EA6996", "#6D94E5", "#4C5323", "#E93F4A", "#AF4732" +# ) # # coordinate with basic and extended soil texture classes via col # colorspace::swatchplot( From 7d7578b4d11287c17204e4c8b1b71c572fce14c7 Mon Sep 17 00:00:00 2001 From: Beaudette Date: Fri, 4 Oct 2024 11:12:03 -0700 Subject: [PATCH 8/9] updated tests, more robust snapping of value/chroma per #318 --- NEWS.md | 4 +- R/getClosestMunsellChip.R | 26 ++++- R/huePosition.R | 6 +- R/munsell2rgb.R | 139 ++++++++++++++----------- man/getClosestMunsellChip.Rd | 2 +- man/munsell2rgb.Rd | 61 +++++------ tests/testthat/test-color-conversion.R | 38 ++++++- 7 files changed, 170 insertions(+), 106 deletions(-) diff --git a/NEWS.md b/NEWS.md index 013a62918..4d8033ca5 100644 --- a/NEWS.md +++ b/NEWS.md @@ -1,7 +1,9 @@ -# aqp 2.0.4 (2024-07-30) +# aqp 2.0.4 (2024-10-04) * CRAN release * ragged bottom lines in `plotSPC()` now adjusted as function of number of profiles and device width * additional metadata from `plotSPC()` saved to `last_spc_plot` in `aqp.env` + * added Munsell values of 8.5 and 9.5 to Munsell LUT and (interpolated) reference spectra (#318) + * `munsell2rgb()` now safely selects the closest Munsell value and chroma to those available in the package LUT # aqp 2.0.3 (2024-04-18) * CRAN release diff --git a/R/getClosestMunsellChip.R b/R/getClosestMunsellChip.R index 4c32de97b..81bed1fdd 100644 --- a/R/getClosestMunsellChip.R +++ b/R/getClosestMunsellChip.R @@ -3,7 +3,7 @@ #' #' @description Non-standard Munsell notation ('7.9YR 2.7/2.0') can be matched (nearest-neighbor, no interpolation) to the closest color within the `munsell` sRGB/CIELAB look-up table via `getClosestMunsellChip()`. A more accurate estimate of sRGB values from non-standard notation can be achieved with the \href{https://CRAN.R-project.org/package=munsellinterpol}{munsellinterpol} package. For example, conversion from Munsell to CIELAB, assuming a D65 illuminant via: `MunsellToLab('0.1Y 3.3/4.4', white='D65', adapt='Bradford')`. #' -#' @param munsellColor character vector of strings containing Munsell notation of color, e.g. '10YR 4/3' +#' @param munsellColor character vector of strings containing Munsell notation of color, e.g. '10YR 4/3', not NA-safe #' @param convertColors logical, should parsed Munsell colors be converted into sRGB values #' @param ... further arguments to \code{munsell2rgb} #' @@ -30,6 +30,20 @@ getClosestMunsellChip <- function(munsellColor, convertColors = TRUE, ...) { # This is a hack to avoid munsell2rgb: "no visible binding for global variable munsell" at package R CMD check munsell <- NULL + # # init working vectors + # # for NA propagation + # n <- length(munsellColor) + # closest.hue <- vector(mode = 'character', length = n) + # closest.value <- vector(mode = 'numeric', length = n) + # closest.chroma <- vector(mode = 'numeric', length = n) + # + # # remove NA for now + # na.idx <- which(is.na(munsellColor)) + # if(length(na.idx) > 0) { + # x.na <- x[na.idx] + # x <- x[-na.idx] + # } + # extract hue, value, chroma from single string cd <- parseMunsell(munsellColor, convertColors = FALSE) @@ -41,21 +55,27 @@ getClosestMunsellChip <- function(munsellColor, convertColors = TRUE, ...) { ## -> interpreting 10YR as the same as 0Y + ## TODO: make NA-safe + + # note: this is incompatible with LazyData: true # extract pieces from unique Munsell hues - load(system.file("data/munsell.rda", package="aqp")[1]) + load(system.file("data/munsell.rda", package = "aqp")[1]) all.hue.data <- na.omit(.parseMunsellHue(unique(munsell$hue))) # locate closest chip in `munsell` set of hues - closest.hue <- vector(mode = 'character', length=nrow(hue.data)) + closest.hue <- vector(mode = 'character', length = nrow(hue.data)) for(i in 1:nrow(hue.data)) { # index possible rows based on character part of hue idx <- which(all.hue.data$hue.character == hue.data[i, ]$hue.character) + # compute Euclidean distance to all possible numeric parts of hue distances <- abs(hue.data$hue.numeric[i] - all.hue.data$hue.numeric[idx]) closest.idx <- which.min(distances) + # compile closest hue closest.hue[i] <- paste0(all.hue.data[idx, ][closest.idx, ], collapse = '') + } # valid value / chroma in our LUT diff --git a/R/huePosition.R b/R/huePosition.R index 2888e982d..153c45e44 100644 --- a/R/huePosition.R +++ b/R/huePosition.R @@ -1,4 +1,7 @@ +## TODO: consider hue-based, angular distance between 2 hues + + #' @title Munsell Hue Reference and Position Searching #' #' @description The 40 Munsell hues are typically arranged from 5R to 2.5R moving clock wise on the unit circle. This function matches a vector of hues to positions on that circle, with options for setting a custom origin or search direction. @@ -54,6 +57,7 @@ #' par(op) #' huePosition <- function(x, returnHues = FALSE, includeNeutral = FALSE, origin = '5R', direction = c('cw', 'ccw')) { + # ordering via Tech Note #2 # Soil Survey Technical Note 2 [wayback machine URL](https://web.archive.org/web/20220704214918/https://www.nrcs.usda.gov/wps/portal/nrcs/detail/soils/ref/?cid=nrcs142p2_053569) @@ -62,7 +66,7 @@ huePosition <- function(x, returnHues = FALSE, includeNeutral = FALSE, origin = # note: this is incompatible with LazyData: true # load look-up table from our package - load(system.file("data/munsellHuePosition.rda", package="aqp")[1]) + load(system.file("data/munsellHuePosition.rda", package = "aqp")[1]) ## basic error checking / argument processing diff --git a/R/munsell2rgb.R b/R/munsell2rgb.R index e71445b7d..71506fede 100644 --- a/R/munsell2rgb.R +++ b/R/munsell2rgb.R @@ -181,8 +181,25 @@ rgb2munsell <- function(color, colorSpace = c('CIE2000', 'LAB', 'sRGB'), nCloses - - +# internally used function for snapping a vector of user-supplied values +# to a known subset via absolute distance +# NA safely propagated +.snapValid <- function(s, v) { + # rows are distances by the_value + .dist <- outer(s, v, function(i, j) {abs(i - j)}) + + # index to snapped values, safely handle NA + idx <- apply(.dist, 1, function(i) { + if(all(is.na(i))) { + return(NA) + } else { + return(which.min(i)) + } + }) + + # replace with snapped + NA + return(v[idx]) +} @@ -232,69 +249,56 @@ rgb2munsell <- function(color, colorSpace = c('CIE2000', 'LAB', 'sRGB'), nCloses #' @examples #' #' # neutral hues (N) can be defined with chroma of 0 or NA -#' g <- expand.grid(hue='N', value=2:8, chroma=0, stringsAsFactors=FALSE) +#' g <- expand.grid(hue='N', value = 2:8, chroma = 0, stringsAsFactors = FALSE) #' (m <- munsell2rgb(g$hue, g$value, g$chroma)) #' soilPalette(m) #' -#' # back-transform -#' rgb2munsell(t(col2rgb(m)) / 255) +#' # back-transform to Munsell notation +#' col2Munsell(t(col2rgb(m)) / 255) #' #' #' # basic example -#' d <- expand.grid(hue='10YR', value=2:8, chroma=1:8, stringsAsFactors=FALSE) +#' d <- expand.grid(hue = '10YR', value = 2:8, chroma = 1:8, stringsAsFactors = FALSE) #' d$color <- with(d, munsell2rgb(hue, value, chroma)) #' #' # similar to the 10YR color book page -#' plot(value ~ chroma, data=d, col=d$color, pch=15, cex=3) +#' plot(value ~ chroma, data = d, col = d$color, pch = 15, cex = 3, las = 1) #' #' # multiple pages of hue: -#' hues <- c('2.5YR','5YR','7.5YR','10YR') -#' d <- expand.grid(hue=hues, value=c(2, 2.5, 3:8), chroma=seq(2,8,by=2), stringsAsFactors=FALSE) +#' hues <- c('2.5YR', '5YR', '7.5YR', '10YR') +#' d <- expand.grid( +#' hue = hues, +#' value = c(2, 2.5, 3:8), +#' chroma = seq(2, 8, by = 2), +#' stringsAsFactors = FALSE +#' ) #' # convert Munsell -> sRGB #' d$color <- with(d, munsell2rgb(hue, value, chroma)) #' #' # extract CIELAB coordinates -#' with(d, munsell2rgb(hue, value, chroma, returnLAB=TRUE)) +#' with(d, munsell2rgb(hue, value, chroma, returnLAB = TRUE)) #' #' # plot: note that we are setting panel order from red --> yellow #' library(lattice) -#' xyplot(value ~ factor(chroma) | factor(hue, levels=hues), -#' main="Common Soil Colors", layout=c(4,1), scales=list(alternating=1), -#' strip=strip.custom(bg=grey(0.85)), -#' data=d, as.table=TRUE, subscripts=TRUE, xlab='Chroma', ylab='Value', -#' panel=function(x, y, subscripts, ...) -#' { -#' panel.xyplot(x, y, pch=15, cex=4, col=d$color[subscripts]) -#' } +#' xyplot( +#' value ~ factor(chroma) | factor(hue, levels = hues), +#' main = "Common Soil Colors", layout = c(4, 1), scales = list(alternating = 1), +#' strip = strip.custom(bg = grey(0.85)), +#' data = d, as.table = TRUE, subscripts = TRUE, +#' xlab = 'Chroma', ylab = 'Value', +#' panel = function(x, y, subscripts, ...) { +#' panel.xyplot(x, y, pch = 15, cex = 4, col = d$color[subscripts]) +#' } #' ) +#' #' #' -#' # soils example -#' data(sp1) -#' -#' # convert colors -#' sp1$soil_color <- with(sp1, munsell2rgb(hue, value, chroma)) -#' -#' # simple plot, may need to tweak gamma-correction... -#' image(matrix(1:nrow(sp1)), axes=FALSE, col=sp1$soil_color, main='Soil Colors') -#' -#' # convert into a more useful color space -#' # you will need the colorspace package for this to work -#' if(require(colorspace)) { -#' # keep RGB triplets from conversion -#' sp1.rgb <- with(sp1, munsell2rgb(hue, value, chroma, return_triplets=TRUE)) -#' -#' # convert into LAB color space -#' sp1.lab <- as(with(sp1.rgb, sRGB(r,g,b)), 'LAB') -#' plot(sp1.lab) -#' } -#' #' # convert a non-standard color to closest "chip" in `munsell` look-up table #' getClosestMunsellChip('7.9YR 2.7/2.0', convertColors = FALSE) -#' # convert directly to R color +#' +#' # convert directly to hex notation of sRGB #' getClosestMunsellChip('7.9YR 2.7/2.0') - - +#' munsell2rgb <- function(the_hue, the_value, the_chroma, alpha = 1, maxColorValue = 1, return_triplets = FALSE, returnLAB = FALSE) { ## important: change the default behavior of data.frame and melt opt.original <- options(stringsAsFactors = FALSE) @@ -336,39 +340,50 @@ munsell2rgb <- function(the_hue, the_value, the_chroma, alpha = 1, maxColorValue ## they will typically be missing chroma or have some arbitrary number ## set it to 0 for correct matching N.idx <- which(the_hue == 'N') - if(length(N.idx) > 0) + if(length(N.idx) > 0) { the_chroma[N.idx] <- 0 + } + + ## any other hue with 0 chroma should be interpreted as N + idx <- which(the_hue != 'N' & the_chroma == 0) + if(length(idx > 0)) { + the_hue[idx] <- 'N' + } - ## TODO: any other hue with 0 chroma should be interpreted as N - - - # value / chroma should be within unique set of allowed chips - valid.value <- unique(as.character(munsell$value)) - valid.chroma <- unique(as.character(munsell$chroma)) + ## value / chroma should be within unique set of allowed chips - ## warn if non-standard notation + # the valid range depends on the latest version of the munsell LUT + # https://github.com/ncss-tech/aqp/issues/318 + valid.value <- unique(munsell$value) + valid.chroma <- unique(munsell$chroma) - ## TODO: - ## * should rounding be enabled by default for backwards compatibility? - ## * current rounding is wrong with e.g. 10YR 2.6 / 3 --> closest value is 2.5 - ## * find closest value/chroma by distance search, once 0.5 values are ready - ## * why are we converting to character? - # value - if(any(! as.character(na.omit(the_value)) %in% valid.value)) { - warning("non-standard notation in Munsell value, use getClosestMunsellChip()", call. = FALSE) - the_value <- ifelse(as.character(the_value) %in% valid.value, the_value, round(the_value)) + # test Munsell values + if(any(! na.omit(the_value) %in% valid.value)) { + warning("non-standard notation in Munsell value, snapping to the nearest available value\n consider using getClosestMunsellChip()", call. = FALSE) + + ## TODO: optimize by only computing distances for non-standard Munsell value + + # snap supplied Munsell value to valid value via absolute distance + # NA are safely propagated + the_value <- .snapValid(the_value, valid.value) } - # chroma - if(any(! as.character(na.omit(the_chroma)) %in% valid.chroma)) { - warning("non-standard notation in Munsell chroma, use getClosestMunsellChip()", call. = FALSE) - the_chroma <- round(the_chroma) + # test Munsell chroma + if(any(! na.omit(the_chroma) %in% valid.chroma)) { + warning("non-standard notation in Munsell chroma, snapping to the nearest available chroma\n consider using getClosestMunsellChip()", call. = FALSE) + + ## TODO: optimize by only computing distances for non-standard Munsell chroma + + # snap supplied Munsell chroma to valid chroma via absolute distance + # NA are safely propagated + the_chroma <- .snapValid(the_chroma, valid.chroma) } + ## join new data with look-up table # note that value / chroma must be same data type as in `munsell` (numeric) d <- data.frame( diff --git a/man/getClosestMunsellChip.Rd b/man/getClosestMunsellChip.Rd index bb2db3250..f04d43f8a 100644 --- a/man/getClosestMunsellChip.Rd +++ b/man/getClosestMunsellChip.Rd @@ -7,7 +7,7 @@ getClosestMunsellChip(munsellColor, convertColors = TRUE, ...) } \arguments{ -\item{munsellColor}{character vector of strings containing Munsell notation of color, e.g. '10YR 4/3'} +\item{munsellColor}{character vector of strings containing Munsell notation of color, e.g. '10YR 4/3', not NA-safe} \item{convertColors}{logical, should parsed Munsell colors be converted into sRGB values} diff --git a/man/munsell2rgb.Rd b/man/munsell2rgb.Rd index aacd0b7ec..b34c1cc92 100644 --- a/man/munsell2rgb.Rd +++ b/man/munsell2rgb.Rd @@ -51,67 +51,56 @@ Care should be taken when using the resulting sRGB values; they are close to the \examples{ # neutral hues (N) can be defined with chroma of 0 or NA -g <- expand.grid(hue='N', value=2:8, chroma=0, stringsAsFactors=FALSE) +g <- expand.grid(hue='N', value = 2:8, chroma = 0, stringsAsFactors = FALSE) (m <- munsell2rgb(g$hue, g$value, g$chroma)) soilPalette(m) -# back-transform -rgb2munsell(t(col2rgb(m)) / 255) +# back-transform to Munsell notation +col2Munsell(t(col2rgb(m)) / 255) # basic example -d <- expand.grid(hue='10YR', value=2:8, chroma=1:8, stringsAsFactors=FALSE) +d <- expand.grid(hue = '10YR', value = 2:8, chroma = 1:8, stringsAsFactors = FALSE) d$color <- with(d, munsell2rgb(hue, value, chroma)) # similar to the 10YR color book page -plot(value ~ chroma, data=d, col=d$color, pch=15, cex=3) +plot(value ~ chroma, data = d, col = d$color, pch = 15, cex = 3, las = 1) # multiple pages of hue: -hues <- c('2.5YR','5YR','7.5YR','10YR') -d <- expand.grid(hue=hues, value=c(2, 2.5, 3:8), chroma=seq(2,8,by=2), stringsAsFactors=FALSE) +hues <- c('2.5YR', '5YR', '7.5YR', '10YR') +d <- expand.grid( + hue = hues, + value = c(2, 2.5, 3:8), + chroma = seq(2, 8, by = 2), + stringsAsFactors = FALSE +) # convert Munsell -> sRGB d$color <- with(d, munsell2rgb(hue, value, chroma)) # extract CIELAB coordinates -with(d, munsell2rgb(hue, value, chroma, returnLAB=TRUE)) +with(d, munsell2rgb(hue, value, chroma, returnLAB = TRUE)) # plot: note that we are setting panel order from red --> yellow library(lattice) -xyplot(value ~ factor(chroma) | factor(hue, levels=hues), - main="Common Soil Colors", layout=c(4,1), scales=list(alternating=1), - strip=strip.custom(bg=grey(0.85)), - data=d, as.table=TRUE, subscripts=TRUE, xlab='Chroma', ylab='Value', - panel=function(x, y, subscripts, ...) - { - panel.xyplot(x, y, pch=15, cex=4, col=d$color[subscripts]) - } +xyplot( + value ~ factor(chroma) | factor(hue, levels = hues), + main = "Common Soil Colors", layout = c(4, 1), scales = list(alternating = 1), + strip = strip.custom(bg = grey(0.85)), + data = d, as.table = TRUE, subscripts = TRUE, + xlab = 'Chroma', ylab = 'Value', + panel = function(x, y, subscripts, ...) { + panel.xyplot(x, y, pch = 15, cex = 4, col = d$color[subscripts]) + } ) -# soils example -data(sp1) - -# convert colors -sp1$soil_color <- with(sp1, munsell2rgb(hue, value, chroma)) - -# simple plot, may need to tweak gamma-correction... -image(matrix(1:nrow(sp1)), axes=FALSE, col=sp1$soil_color, main='Soil Colors') - -# convert into a more useful color space -# you will need the colorspace package for this to work -if(require(colorspace)) { - # keep RGB triplets from conversion - sp1.rgb <- with(sp1, munsell2rgb(hue, value, chroma, return_triplets=TRUE)) - - # convert into LAB color space - sp1.lab <- as(with(sp1.rgb, sRGB(r,g,b)), 'LAB') - plot(sp1.lab) -} # convert a non-standard color to closest "chip" in `munsell` look-up table getClosestMunsellChip('7.9YR 2.7/2.0', convertColors = FALSE) -# convert directly to R color + +# convert directly to hex notation of sRGB getClosestMunsellChip('7.9YR 2.7/2.0') + } \references{ \itemize{ diff --git a/tests/testthat/test-color-conversion.R b/tests/testthat/test-color-conversion.R index a846962c7..d4d3838fa 100644 --- a/tests/testthat/test-color-conversion.R +++ b/tests/testthat/test-color-conversion.R @@ -107,10 +107,11 @@ test_that("Munsell hue parsing", { }) -test_that("non-integer value and chroma are selectively rounded", { +test_that("non-integer value and chroma are snapped to valid possibilities", { # rounding of value, throws warning expect_warning(res <- parseMunsell('10YR 3.3/4'), regexp = 'non-standard notation') + # this will not throw a warning res <- parseMunsell('10YR 3.3/4', convertColors = FALSE) @@ -120,6 +121,23 @@ test_that("non-integer value and chroma are selectively rounded", { parseMunsell('10YR 3/4') ) + # 2.5, 8.5, 9.5 are valid Munsell value + # snap nearby to these + expect_equal( + suppressWarnings(parseMunsell('10YR 2.6/4')), + parseMunsell('10YR 2.5/4') + ) + + expect_equal( + suppressWarnings(parseMunsell('10YR 8.4/4')), + parseMunsell('10YR 8.5/4') + ) + + expect_equal( + suppressWarnings(parseMunsell('10YR 9.55/4')), + parseMunsell('10YR 9.5/4') + ) + # rounding of chroma, throws warning expect_warning(res <- parseMunsell('10YR 3/4.6'), regexp = 'non-standard notation') # this will not throw a warning @@ -131,11 +149,24 @@ test_that("non-integer value and chroma are selectively rounded", { parseMunsell('10YR 3/5') ) - # no rounding of 2.5 values + # double-check no snapping of 2.5 values res <- parseMunsell('10YR 2.5/2') res.test <- col2Munsell(col = '#493A2BFF') expect_true(res.test$value == 2.5) + + + # test .snapValid() directly + .valid <- c(2, 2.5, 3, 4, 5, 6, 7, 8, 8.5, 9, 9.5, 10) + v <- c(2, 4, 6, 8, NA, 2.5, 2.6, 8.1, 9.6, 12) + res <- aqp:::.snapValid(v, .valid) + + # ensure snapping worked as expected + expect_equal( + res, + c(2, 4, 6, 8, NA, 2.5, 2.5, 8, 9.5, 10) + ) + }) @@ -235,6 +266,9 @@ test_that("neutral hues", { expect_equal(N4, '#1B1C1CFF') expect_equal(N6, '#464848FF') + # 0 chroma with any hue -> neutral + N <- munsell2rgb('10YR', 4, 0) + expect_equal(N, '#1B1C1CFF') }) From f24b51bd3d6a12788c8c48ea4af8f1d06bcec2ac Mon Sep 17 00:00:00 2001 From: Andrew Gene Brown Date: Fri, 4 Oct 2024 12:04:07 -0700 Subject: [PATCH 9/9] Update equivalent_munsell.rda used for `equivalentMunsellChips()` --- ...unsellChips.R => equivalentMunsellChips.R} | 23 +++++--- data/equivalent_munsell.rda | Bin 109358 -> 131287 bytes man/equivalentMunsellChips.Rd | 4 +- tests/testthat/test-equivalentMunsellChips.R | 39 ++++++++++++++ tests/testthat/test-similarMunsellChips.R | 50 ------------------ 5 files changed, 56 insertions(+), 60 deletions(-) rename R/{similarMunsellChips.R => equivalentMunsellChips.R} (94%) create mode 100644 tests/testthat/test-equivalentMunsellChips.R delete mode 100644 tests/testthat/test-similarMunsellChips.R diff --git a/R/similarMunsellChips.R b/R/equivalentMunsellChips.R similarity index 94% rename from R/similarMunsellChips.R rename to R/equivalentMunsellChips.R index 06bc2b0f4..baa90f78f 100644 --- a/R/similarMunsellChips.R +++ b/R/equivalentMunsellChips.R @@ -9,7 +9,7 @@ #' @references #' Gaurav Sharma, Wencheng Wu, Edul N. Dalal. (2005). The CIEDE2000 Color-Difference Formula: Implementation Notes, Supplementary Test Data, and Mathematical Observations. COLOR research and application. 30(1):21-30. http://www2.ece.rochester.edu/~gsharma/ciede2000/ciede2000noteCRNA.pdf #' -#' Thomas Lin Pedersen, Berendea Nicolae and Romain François (2020). farver: High Performance Colour Space Manipulation. R package version 2.0.3. https://CRAN.R-project.org/package=farver +#' Thomas Lin Pedersen, Berendea Nicolae and Romain François (2020). farver: High Performance Colour Space Manipulation. R package version 2.0.3. https://CRAN.R-project.org/package=farver #' #' Dong, C.E., Webb, J.B., Bottrell, M.C., Saginor, I., Lee, B.D. and Stern, L.A. (2020). Strengths, Limitations, and Recommendations for Instrumental Color Measurement in Forensic Soil Characterization. J Forensic Sci, 65: 438-449. https://doi.org/10.1111/1556-4029.14193 #' @@ -50,7 +50,8 @@ .makeEquivalentMunsellLUT <- function(threshold = 0.001) { munsell <- NULL load(system.file("data/munsell.rda", package = "aqp")[1]) - + + # 2024-10-04: added 8.5 and 9.5 value chips # 2022-03-31: updated neutral chips and 2.5 value chips now included @@ -72,16 +73,22 @@ # user system elapsed # 190.73 0.73 194.42 system.time( - x <- farver::compare_colour(from = munsell[,c('L','A','B')], from_space = 'lab', - to = munsell[,c('L','A','B')], to_space = 'lab', - method = 'cie2000', white_from = 'D65', white_to = 'D65') + x <- farver::compare_colour( + from = munsell[, c('L', 'A', 'B')], + from_space = 'lab', + to = munsell[, c('L', 'A', 'B')], + to_space = 'lab', + method = 'cie2000', + white_from = 'D65', + white_to = 'D65' + ) ) xdat <- x x[lower.tri(x, diag = TRUE)] <- NA # remove lower triangle for statistics (only count each pair distance 1x) - # roughly dE00 ~ 2.24 -- this is close to the perceptible limit of average human color vision with "good" lighting + # dE00 ~2.158 -- this is close to the perceptible limit of average human color vision with "good" lighting # calculate quantiles xqtl <- quantile(x, p = threshold, na.rm = TRUE)[1] @@ -134,7 +141,7 @@ names(equivalent_munsell) <- sprintf("%s %s/%s", munsell$hue, munsell$value, munsell$chroma) # this is only 107kB written to Rda - # save(equivalent_munsell, file="data/equivalent_munsell.rda") + save(equivalent_munsell, file="data/equivalent_munsell.rda") return(equivalent_munsell) } @@ -147,7 +154,7 @@ #' #' The intention is to identify Munsell chips that may be "functionally equivalent" to some other given whole value/chroma chip elsewhere in the Munsell color space -- as discretized in the \code{aqp::munsell} data table. This basic assumption needs to be validated against your end goal: probably by visual inspection of some or all of the resulting sets. See \code{\link{colorContrast}} and \code{\link{colorContrastPlot}}. #' -#' "Equivalent" chips table are based (fairly arbitrarily) on the 0.001 probability level of dE00 (default Type 7 \code{quantile}) within the upper triangle of the 8467x8467 contrast matrix. This corresponds to a \code{dE00} contrast threshold of approximately 2.15. +#' "Equivalent" chips table are based (fairly arbitrarily) on the 0.001 probability level of dE00 (default Type 7 \code{quantile}) within the upper triangle of the 8467x8467 contrast matrix. This corresponds to a \code{dE00} contrast threshold of approximately 2.16. #' @param hue A character vector containing Munsell hues #' @param value A numeric vector containing Munsell values (integer only) diff --git a/data/equivalent_munsell.rda b/data/equivalent_munsell.rda index e8cbd69c0f87ddef0a5a1d8ef24f888e76fd29df..e2abf73f4bb0c80d5b3d8c4930382976ca3e3f58 100644 GIT binary patch literal 131287 zcmZsCXIN8F)2&Jq>7w)|D2ND%G${cQ0qG#pd(qHBq?ZtiC`eb4B3+Q)1wsu-3!OwM zp+|bCks2TbZg{`<`R@I3^GsIuo+m#}&g{L*}1pjHYqRWP0Se%c*PihOP_S*x9`*o^)J{h*2V!2}z0` zE_Yc}sFd108B{TS0cWWYP}f@T0m~ddcKa5@ZR!F)OMWT-vZJrN>DfN z_-WQ>E#ld>6psm%b8e(K-eWQk&xSqJ${JzmjFlU`N;?s9PH(Z9<&4qvE|0BjSvOyM z8u;lWH}YLJ8Gu1Hg-n#e;%ZloC?EdM^ecJ5`_##QF}caPwOJ)e?TM!^h$k`($eyIl>*R&}^o zl^&E;8}_DR45_Rm^YB!?eIl{F@K6C*MshqOIS^qbmgx*XFmjNBkaI&0va<8d3;*XOH!_KZSlykcgOw4i)pgt8|f9n;?--ntb0qN$pdnnNQPP>ZyI5bv7t9 z!ouzNCR)h-{C1~hHRY=FS(%pmxv}aRJxjSn8J(Cxyu_PYyVmi&z1F%Vd!F9V@N+jQ z-X8gYtksQ79{}sZD&?>$>=ndDbKR 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z!4NMwVh*8#(Ouw_c%opGQtn~aPIW`%b;&46hc!0QDXUApA-N~b&p>q-|h~nil9M^!m*V&IfWh|wNXJIr)BQ5k_&hJmmo9jz1q3?rq=KKpOx@UXXslK z-L>e}uIi^+>V)U}?oga@Sl4dPjpbu_MdL*sD$We!u&215ba+35xgbfGot)D8?MWe mqdxi!_-t4^QP@+sQmmKNxNp>LudkPFgP-e8Ia&$eqx~QHTyK&9 diff --git a/man/equivalentMunsellChips.Rd b/man/equivalentMunsellChips.Rd index 905b03dda..2762c08e4 100644 --- a/man/equivalentMunsellChips.Rd +++ b/man/equivalentMunsellChips.Rd @@ -1,5 +1,5 @@ % Generated by roxygen2: do not edit by hand -% Please edit documentation in R/similarMunsellChips.R +% Please edit documentation in R/equivalentMunsellChips.R \name{equivalentMunsellChips} \alias{equivalentMunsellChips} \title{Identify "equivalent" (whole number value/chroma) Munsell chips} @@ -21,7 +21,7 @@ Uses a pre-calculated lookup list (\code{\link{equivalent_munsell}}) based on pa The intention is to identify Munsell chips that may be "functionally equivalent" to some other given whole value/chroma chip elsewhere in the Munsell color space -- as discretized in the \code{aqp::munsell} data table. This basic assumption needs to be validated against your end goal: probably by visual inspection of some or all of the resulting sets. See \code{\link{colorContrast}} and \code{\link{colorContrastPlot}}. -"Equivalent" chips table are based (fairly arbitrarily) on the 0.001 probability level of dE00 (default Type 7 \code{quantile}) within the upper triangle of the 8467x8467 contrast matrix. This corresponds to a \code{dE00} contrast threshold of approximately 2.15. +"Equivalent" chips table are based (fairly arbitrarily) on the 0.001 probability level of dE00 (default Type 7 \code{quantile}) within the upper triangle of the 8467x8467 contrast matrix. This corresponds to a \code{dE00} contrast threshold of approximately 2.16. } \examples{ diff --git a/tests/testthat/test-equivalentMunsellChips.R b/tests/testthat/test-equivalentMunsellChips.R new file mode 100644 index 000000000..c5c867799 --- /dev/null +++ b/tests/testthat/test-equivalentMunsellChips.R @@ -0,0 +1,39 @@ +test_that("equivalentMunsellChips works", { + + # same "chip page position" different hue page; identify all perceptually equivalent chips + + # test 1 + a <- as.list(equivalentMunsellChips("7.5YR", 2, 1)[[1]][, c("hue", "value", "chroma")]) + + b <- list( + hue = c("10YR", "5YR", "7.5YR"), + value = c(2, 2, 2), + chroma = c(1, 1, 1) + ) + + expect_equal(a, b) + + + # test 2 + a <- as.list(equivalentMunsellChips("5YR", 2, 1)[[1]][, c("hue", "value", "chroma")]) + + b <- list( + hue = c("10R", "2.5YR", "5YR", "7.5YR"), + value = c(2, 2, 2, 2), + chroma = c(1, 1, 1, 1) + ) + + expect_equal(a, b) + + # test 3 + a <- as.list(equivalentMunsellChips("10YR", 2, 1)[[1]][, c("hue", "value", "chroma")]) + + b <- list( + hue = c("10YR", "2.5Y", "7.5YR"), + value = c(2, 2, 2), + chroma = c(1, 1, 1) + ) + + expect_equal(a, b) + +}) diff --git a/tests/testthat/test-similarMunsellChips.R b/tests/testthat/test-similarMunsellChips.R deleted file mode 100644 index 79bd2c6d2..000000000 --- a/tests/testthat/test-similarMunsellChips.R +++ /dev/null @@ -1,50 +0,0 @@ -context("Equivalent Munsell Chips") - -test_that("equivalentMunsellChips works", { - - ## TODO: these will need to be updated with new color entries in the munsell LUT - skip() - - # same "chip page position" different hue page; identify all perceptually equivalent chips - - # test 1 - a <- as.list( - equivalentMunsellChips("7.5YR", 2, 1)[[1]][, c("hue","value","chroma")] - ) - - b <- list( - hue = c("10YR", "2.5YR", "5YR", "7.5YR"), - value = c(2, 2, 2, 2), - chroma = c(1, 1, 1, 1) - ) - - expect_equal(a, b) - - - # test 2 - a <- as.list( - equivalentMunsellChips("5YR", 2, 1)[[1]][, c("hue","value","chroma")] - ) - - b <- list( - hue = c("10R", "10YR", "2.5YR", "5YR", "7.5YR"), - value = c(2, 2, 2, 2, 2), - chroma = c(1, 1, 1, 1, 1) - ) - - expect_equal(a, b) - - # test 3 - a <- as.list( - equivalentMunsellChips("10YR", 2, 1)[[1]][,c("hue", "value", "chroma")] - ) - - b <- list( - hue = c("10YR", "2.5Y", "5YR", "7.5YR"), - value = c(2, 2, 2, 2), - chroma = c(1, 1, 1, 1) - ) - - expect_equal(a, b) - -})

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