r - 给定一个有限的调色板，如何从热到冷排序，即发散

Question

更新 (以下原问题)
问题已部分解决。
仍在努力弄清楚如何扩展到其他颜色组合
如果我使用此代码

hLIM <- rgb2hsv(col2rgb('#8000ff'))['h', ]
sLIM <- rgb2hsv(col2rgb('#8000ff'))['s', ]
vLIM <- rgb2hsv(col2rgb('#8000ff'))['v', ]
rankorder <- order((hLIM-tHSVcol[,1] + (hLIM < tHSVcol[,1])),
                   (sLIM-tHSVcol[,2] + (sLIM < tHSVcol[,2])),
                   (vLIM-tHSVcol[,3] + (vLIM < tHSVcol[,3])))

orderType <- "HSV Ordering"

我能够对此进行排序

未分类调色板: "#313695","#fdae61","#a50026","#ffffbf","#f46d43","#fee090","#e0f3f8","#74add1","#d73027","#4575b4","#abd9e9"成这个

排序调色板: "#a50026","#d73027","#f46d43","#fdae61","#fee090","#ffffbf","#e0f3f8","#abd9e9","#74add1", "#4575b4","#313695"但是，我很难将其扩展到其他颜色组合。
例如，当我尝试对此进行排序时

未分类

"#22325f" "#88ce64" "#fbd234" "#b8091f" "#682f4e" "#fdea6e" "#4aec6a" "#fb7894" "#f13111" "#2584a0" "#460809" "#00699e" "#391b72" "#03471d" "#ba0841"

我明白了(有趣的是，我不确定完美排序的调色板会是什么样子——当然没有散布的暗带!)

不完全排序

"#391b72" "#22325f" "#00699e" "#2584a0" "#03471d" "#4aec6a" "#88ce64" "#fdea6e" "#fbd234" "#f13111" "#460809" "#b8091f" "#fb7894" "#ba0841" "#682f4e"

原始问题
我有一个有限的调色板，如何从热(红色)到冷(蓝色)排序。
这个怎么转

未分类调色板: "#313695","#fdae61","#a50026","#ffffbf","#f46d43","#fee090","#e0f3f8","#74add1","#d73027","#4575b4","#abd9e9"成这个

排序调色板: "#a50026","#d73027","#f46d43","#fdae61","#fee090","#ffffbf","#e0f3f8","#abd9e9","#74add1", "#4575b4","#313695"R 代码位于消息的末尾。我尝试按 RGB 的组合排序和 HSV ,(基于评论或未评论的内容)但无济于事。
我无法在以下值中找到模式(颜色排序不同)
非常感谢任何指导。
RGB 排序颜色

> tRGBcol
      red green blue
 [1,] 165     0   38
 [2,] 215    48   39
 [3,] 244   109   67
 [4,] 253   174   97
 [5,] 254   224  144
 [6,] 255   255  191
 [7,] 224   243  248
 [8,] 171   217  233
 [9,] 116   173  209
[10,]  69   117  180
[11,]  49    54  149

HSV 排序颜色

> tHSVcol
                h          s         v
 [1,] 0.961616162 1.00000000 0.6470588
 [2,] 0.008522727 0.81860465 0.8431373
 [3,] 0.039548023 0.72540984 0.9568627
 [4,] 0.082264957 0.61660079 0.9921569
 [5,] 0.121212121 0.43307087 0.9960784
 [6,] 0.166666667 0.25098039 1.0000000
 [7,] 0.534722222 0.09677419 0.9725490
 [8,] 0.543010753 0.26609442 0.9137255
 [9,] 0.564516129 0.44497608 0.8196078
[10,] 0.594594595 0.61666667 0.7058824
[11,] 0.658333333 0.67114094 0.5843137

手动拆分十六进制颜色

a5  00  26
d7  30  27
f4  6d  43
fd  ae  61
fe  e0  90
ff  ff  bf
e0  f3  f8
ab  d9  e9
74  ad  d1
45  75  b4
31  36  95

代码

RenderPal <- function(x,name){
  
  if ((missing(x)) || (missing(name))){
    stop("Internal error, please troubleshoot")
  }
  n <- length(x)
  old <- graphics::par(mar = c(0.5, 0.5, 0.5, 0.5))
  on.exit(graphics::par(old))
  
  graphics::image(1:n, 1, as.matrix(1:n), col = x,
                  ylab = "", xaxt = "n", yaxt = "n", bty = "n")
  graphics::rect(0, 0.9, n + 1, 1.1, col = grDevices::rgb(1, 1, 1, 0.8), border = NA)
  graphics::text((n + 1) / 2, 1, labels = name, cex = 2, family = "serif")
}

i <- NULL
oldPal <- NULL
rankorder <- c(1,2,3,4,5,6,7,8,9,10,11)
orderedPal<- NULL
RGBcol <- NULL
HSVcol <- NULL
tHSVcol <- NULL
orderType <- "Unsorted"



oldPal <- c("#313695","#fdae61","#a50026","#ffffbf","#f46d43","#fee090","#e0f3f8","#74add1","#d73027","#4575b4","#abd9e9")

# Print hex values
oldPal

# Convert Hex to RGB
RGBcol <- col2rgb(oldPal)

# Print RGB values
RGBcol

# Transpose matrix
tRGBcol <- t(RGBcol)

# Print matrix
tRGBcol

# Uncomment following to order by Red, Green, then Blue
# rankorder <- order(tRGBcol[,1],tRGBcol[,2],tRGBcol[,3])
# orderType <- "Red Ordering"

# Uncomment following to order by Blue, Green, then Red
# rankorder <- order(tRGBcol[,3],tRGBcol[,2],tRGBcol[,1])
# orderType <- "Blue Ordering"

# Uncomment following to order by Green, Blue then Red
# rankorder <- order(tRGBcol[,2],tRGBcol[,3],tRGBcol[,1])
# orderType <- "Green Ordering"

# Uncomment following to order by Red + Blue
# rANDb <- apply(tRGBcol[,c(1,3)],1,sum)
# rankorder <- order(rANDb)
# orderType <- "Red + Blue Ordering"

# Uncomment following to order by Red + Green + Blue
# rANDgANDb <- apply(tRGBcol[,c(1,2,3)],1,sum)
# rankorder <- order(rANDgANDb)
# orderType <- "Red + Green + Blue Ordering"

# Convert RGB to HSV
HSVcol <- rgb2hsv(RGBcol)

# Print matrix
HSVcol

# Transpose matrix
tHSVcol <- t(HSVcol)

# Print matrix
tHSVcol


# Uncomment following to order by Hue, then Saturation, then Value
# rankorder <- order(tHSVcol[,1],tHSVcol[,2],tHSVcol[,3])
# orderType <- "Hue Ordering"

# Uncomment following to order by hANDv = Hue + Value
# hANDv <- apply(tHSVcol[,c(1,3)],1,sum)
# rankorder <- order(hANDv)
# orderType <- "Hue + Value Ordering"

# Uncomment following to order by hPRODv = Hue * Value
# hPRODv <- apply(tHSVcol[,c(1,3)],1,prod)
# rankorder <- order(hPRODv)
# orderType <- "Hue * Value Ordering"

# Combine matrices tRGBcol and tHSVcol
tCombo <- cbind(tRGBcol,tHSVcol)

rankorder

for (i in 1:length(rankorder)){
  orderedPal[i] <- oldPal[rankorder[i]]
}

# Print old, unordered palette
oldPal

# Print new, ordered palette
orderedPal

RenderPal(oldPal, "Unordered Palette")
RenderPal(orderedPal, orderType)

编辑:按色调排序时的结果

Answer 1

我几乎得到了你要求的订单:

Coolness = function(P) { 
    RGB = col2rgb(P)
    (RGB[3,] - RGB[1,]) / (RGB[3,] + RGB[1,])
}

CoolPal = oldPal[order(Coolness(oldPal))]
RenderPal(CoolPal, "Coolness")

但请注意，我已经交换了前两种颜色。你建议的答案说
“#a50026”比“#d73027”更热。我的 Coolness 函数对这两个函数具有相反的顺序。