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R tips: R中的颜色配置方案

2023-03-20 15:37:09 时间

数据可视化不可避免的就是要选择一些颜色方案，颜色方案除了手动设置之外，在R中也有自动生成颜色方案的工具。

R中的HCL配色方案

HCL本意是和RGB HSV等一样的颜色空间的术语，由于这里所用的颜色方案在R中是hcl.pals函数，所以就称为HCL配色方案了。 HCL相比较HSV等颜色空间的一个重要优点就是颜色的视觉明度是均一的，在R中也是推荐使用hcl颜色方案，不推荐使用rainbow等颜色方案了。 有关于HCL的有点，可以参看https://jessieji.com/2020/hcl-instead-of-hsl。

hcl.pals可以查看内置的hcl颜色方案：

hcl.pals("qualitative")
# [1] "Pastel 1" "Dark 2"   "Dark 3"   "Set 2"    "Set 3"    "Warm"     "Cold"     "Harmonic" "Dynamic" 

hcl.pals("sequential")
# [1] "Grays"         "Light Grays"   "Blues 2"       "Blues 3"       "Purples 2"     "Purples 3"     "Reds 2"        "Reds 3"        "Greens 2"     
# [10] "Greens 3"      "Oslo"          "Purple-Blue"   "Red-Purple"    "Red-Blue"      "Purple-Orange" "Purple-Yellow" "Blue-Yellow"   "Green-Yellow" 
# [19] "Red-Yellow"    "Heat"          "Heat 2"        "Terrain"       "Terrain 2"     "Viridis"       "Plasma"        "Inferno"       "Rocket"       
# [28] "Mako"          "Dark Mint"     "Mint"          "BluGrn"        "Teal"          "TealGrn"       "Emrld"         "BluYl"         "ag_GrnYl"     
# [37] "Peach"         "PinkYl"        "Burg"          "BurgYl"        "RedOr"         "OrYel"         "Purp"          "PurpOr"        "Sunset"       
# [46] "Magenta"       "SunsetDark"    "ag_Sunset"     "BrwnYl"        "YlOrRd"        "YlOrBr"        "OrRd"          "Oranges"       "YlGn"         
# [55] "YlGnBu"        "Reds"          "RdPu"          "PuRd"          "Purples"       "PuBuGn"        "PuBu"          "Greens"        "BuGn"         
# [64] "GnBu"          "BuPu"          "Blues"         "Lajolla"       "Turku"         "Hawaii"        "Batlow"      

hcl.pals("diverging")
# [1] "Blue-Red"      "Blue-Red 2"    "Blue-Red 3"    "Red-Green"     "Purple-Green"  "Purple-Brown"  "Green-Brown"   "Blue-Yellow 2" "Blue-Yellow 3"
# [10] "Green-Orange"  "Cyan-Magenta"  "Tropic"        "Broc"          "Cork"          "Vik"           "Berlin"        "Lisbon"        "Tofino"  

hcl.pals("divergingx")
# [1] "ArmyRose" "Earth"    "Fall"     "Geyser"   "TealRose" "Temps"    "PuOr"     "RdBu"     "RdGy"     "PiYG"     "PRGn"     "BrBG"     "RdYlBu"  
# [14] "RdYlGn"   "Spectral" "Zissou 1" "Cividis"  "Roma"

可以发现颜色方案分为四类：qualitative、 sequential、 diverging、 divergingx，分别取二个相应的Palettes看一下颜色的效果如何。

# 定义一个函数用于查看颜色的效果
showColors <- function(x, ...){
  barplot(rep(1, length(x)), col = x, axes = FALSE, ...)
}

选取hcl颜色方案是使用hcl.colors函数，比如从Pastel 1颜色方案中取10个颜色：

hcl.colors(10, palette = "Pastel 1")
# [1] "#FFC5D0" "#F6CBB7" "#E2D4A8" "#C5DCAB" "#A8E1BF" "#99E2D8" "#A4DDEF" "#C4D5FB" "#E4CBF9" "#F9C5E9"

showColors(hcl.colors(10, palette = "Pastel 1"), main = "Pastel 1")

四大配色方案中各随机选二个方案，查看效果：

# 布局4行2列
opar <- par(no.readonly = TRUE)
par(mfrow = c(4, 2), mar = c(1,1,3,1))

for(panel in c('qualitative', 'sequential', 'diverging', 'divergingx')){
  pal <- sample(hcl.pals(panel), 2)
  for(p in pal){
    col_in_pal <- hcl.colors(10, p)
    showColors(col_in_pal, main = paste0(panel, ": ", p))
  }
}

# 复原布局
par(opar)

可以看到：

  • qualitative颜色方案的颜色有多种色调，常用于着色离散变量；
  • sequential的颜色方案中色调较少，体现了颜色的连续过渡，可以用于着色连续变量；
  • diverging和divergingx也是颜色的连续过渡，但是不同于sequential，它的颜色在深浅上存在一个中心点，中心点两侧颜色逐步加深过渡，这样的颜色方案适合有中心点的连续变量，比如相关性数据：数据范围是-1到1，0是中心点，于是两端的颜色需要两个深色，而中心点可以使用最浅的颜色。

RColorBrewer

RColorBrewer包的配色方案通过display.brewer.all查看，可以发现它的颜色方案也是类似的：sequential、qualitative和diverging。

RColorBrewer::display.brewer.all()

如果需要获取具体的颜色，可以使用brewer.pal函数：

RColorBrewer::brewer.pal(3, "Dark2")
# [1] "#1B9E77" "#D95F02" "#7570B3"

不同于hcl的配色方案，RColorBrewer中颜色方案数量是固定的，不会对颜色进行自动插值，比如Dark2配色一共只有8个颜色，超过8个颜色也最多只返回8个颜色：

RColorBrewer::brewer.pal(Inf, "Dark2")
# [1] "#1B9E77" "#D95F02" "#7570B3" "#E7298A" "#66A61E" "#E6AB02" "#A6761D" "#666666"
# Warning message:
# In RColorBrewer::brewer.pal(Inf, "Dark2") :
#   n too large, allowed maximum for palette Dark2 is 8
# Returning the palette you asked for with that many colors

如果需要对颜色进行插值可以使用colorRampPalette函数来实现，比如将Dark2配色线性插值成50个颜色：

par(mfrow = c(2, 1), mar = c(1,1,3,1))

dark2_cols <- RColorBrewer::brewer.pal(8, "Dark2")
showColors(dark2_cols)
showColors(colorRampPalette(dark2_cols)(50))

par(opar)

另外，ggplot2中修改color映射的scale_color_brewer和scale_fill_brewer也可以接受RColorBrewer的配色方案，自动调整颜色，比如：

library(ggplot2)
library(patchwork)

p <- ggplot(iris, aes(x = Species, y = Sepal.Length, fill = Species)) + geom_boxplot()
p2 <- p + scale_fill_brewer(palette = "Dark2")

p|p2

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