R 绘图可供色盲人士使用的颜色组合

Question

如何在 base R 中选择 4-8 种颜色以供色盲人士看到？

下面是基础 R 调色板。在 BASE R 中寻找不使用软件包的解决方案。

Base R 调色板指南： http://www.stat.columbia.edu/~tzheng/files/Rcolor.pdf

色盲调色板：http://mkweb.bcgsc.ca/colorblind/

具体来说，如何在 BASE R 中手动创建可访问的颜色？

例如“朱红色”、“蓝绿色”和“红紫色”如下纸图所示。

Answer 1

冈部伊藤调色板

问题中显示的调色板也称为 Okabe-Ito 调色板，如 Okabe & Ito (2008) 建议的那样。从 4.0.0 版本开始，base R 提供了一个新的

palette.colors()

，其中该调色板实际上是默认的：

palette.colors(palette = "Okabe-Ito")
##         black        orange       skyblue   bluishgreen        yellow 
##     "#000000"     "#E69F00"     "#56B4E9"     "#009E73"     "#F0E442" 
##          blue    vermillion reddishpurple          gray 
##     "#0072B2"     "#D55E00"     "#CC79A7"     "#999999" 

基础 R 中的定性调色板

除了这个调色板之外，基础 R 中还可以轻松使用各种其他定性调色板。具体来说，新的默认调色板（称为

"R4"

）也被设计为在色觉缺陷下相当强大。请参阅博客文章了解更多详细信息，并参阅后续论文了解自 R 4.0.0 发布以来 Base R 中改进的颜色基础设施的概述：

• Zeileis、Murrell、Maechler、Sarkar (2019)。 “R 的新调色板（）。” R 博客。
• Zeileis，穆雷尔（2023）。 “为 R 的盲点着色。” R 杂志。

基础 R 中的顺序和发散调色板

除了上面的定性调色板之外，自 3.6.0 版本以来，base R 还具有一个新功能

hcl.colors()

，它提供了许多连续和发散的调色板，这些调色板在色觉缺陷下也很强大。它提供了来自 ColorBrewer.org、viridis、CARTO 颜色、Crameri 的科学颜色等的许多调色板的近似值（使用色调-色度-亮度颜色模型导出）。默认是流行的 viridis 调色板。以下博客文章提供了更多详细信息，有关

colorspace

包的论文解释了更多相关/基础工作。

• Zeileis，穆雷尔（2019）。 “grDevices 中基于 HCL 的调色板。” R 博客。
• Zeileis、Fisher、Hornik、Ihaka、McWhite、Murrell、Stauffer、Wilke（2020）。 “色彩空间：用于操作和评估颜色和调色板的工具箱。” 统计软件杂志。

Answer 2

这些是您发布的图像中这些颜色的十六进制代码

colorBlindBlack8  <- c("#000000", "#E69F00", "#56B4E9", "#009E73", 
                       "#F0E442", "#0072B2", "#D55E00", "#CC79A7")
pie(rep(1, 8), col = colorBlindBlack8)

colorBlindGrey8   <- c("#999999", "#E69F00", "#56B4E9", "#009E73", 
                       "#F0E442", "#0072B2", "#D55E00", "#CC79A7")
scales::show_col(colorBlindGrey8)

对于超过 8 种颜色，

rcartocolor

有

Safe

调色板，有 12 种颜色

safe_colorblind_palette <- c("#88CCEE", "#CC6677", "#DDCC77", "#117733", "#332288", "#AA4499", 
                             "#44AA99", "#999933", "#882255", "#661100", "#6699CC", "#888888")
scales::show_col(safe_colorblind_palette)

如果您需要顺序或发散的色彩图，请检查这些调色板

library(rcartocolor)
display_carto_all(colorblind_friendly = TRUE)

^{由 reprex 包于 2019-07-22 创建（v0.3.0）}

Answer 3

viridis

包中的色标均可供色盲人士使用。 https://cran.r-project.org/web/packages/viridis/vignettes/intro-to-viridis.html#the-color-scales

如果您需要像链接到的 pdf 中那样按名称使用颜色，请将

viridis

调色板中的颜色与命名的颜色列表相匹配。对于 4-8 岁的孩子来说，这在视觉上很容易做到。

Answer 4

您可以使用包生成调色板，并生成仅使用基础 R 重新创建它们的“硬编码”代码。例如，数据框中所有 colorbrewer 调色板中的 4 种颜色：

# install.packages('RColorBrewer')

palletes <-
structure(c("#A6611A", "#D01C8B", "#7B3294", "#E66101", "#CA0020", 
"#CA0020", "#D7191C", "#D7191C", "#D7191C", "#7FC97F", "#1B9E77", 
"#A6CEE3", "#FBB4AE", "#B3E2CD", "#E41A1C", "#66C2A5", "#8DD3C7", 
"#EFF3FF", "#EDF8FB", "#EDF8FB", "#F0F9E8", "#EDF8E9", "#F7F7F7", 
"#FEEDDE", "#FEF0D9", "#F1EEF6", "#F6EFF7", "#F1EEF6", "#F2F0F7", 
"#FEEBE2", "#FEE5D9", "#FFFFCC", "#FFFFCC", "#FFFFD4", "#FFFFB2", 
"#DFC27D", "#F1B6DA", "#C2A5CF", "#FDB863", "#F4A582", "#F4A582", 
"#FDAE61", "#FDAE61", "#FDAE61", "#BEAED4", "#D95F02", "#1F78B4", 
"#B3CDE3", "#FDCDAC", "#377EB8", "#FC8D62", "#FFFFB3", "#BDD7E7", 
"#B2E2E2", "#B3CDE3", "#BAE4BC", "#BAE4B3", "#CCCCCC", "#FDBE85", 
"#FDCC8A", "#BDC9E1", "#BDC9E1", "#D7B5D8", "#CBC9E2", "#FBB4B9", 
"#FCAE91", "#C2E699", "#A1DAB4", "#FED98E", "#FECC5C", "#80CDC1", 
"#B8E186", "#A6DBA0", "#B2ABD2", "#92C5DE", "#BABABA", "#ABD9E9", 
"#A6D96A", "#ABDDA4", "#FDC086", "#7570B3", "#B2DF8A", "#CCEBC5", 
"#CBD5E8", "#4DAF4A", "#8DA0CB", "#BEBADA", "#6BAED6", "#66C2A4", 
"#8C96C6", "#7BCCC4", "#74C476", "#969696", "#FD8D3C", "#FC8D59", 
"#74A9CF", "#67A9CF", "#DF65B0", "#9E9AC8", "#F768A1", "#FB6A4A", 
"#78C679", "#41B6C4", "#FE9929", "#FD8D3C", "#018571", "#4DAC26", 
"#008837", "#5E3C99", "#0571B0", "#404040", "#2C7BB6", "#1A9641", 
"#2B83BA", "#FFFF99", "#E7298A", "#33A02C", "#DECBE4", "#F4CAE4", 
"#984EA3", "#E78AC3", "#FB8072", "#2171B5", "#238B45", "#88419D", 
"#2B8CBE", "#238B45", "#525252", "#D94701", "#D7301F", "#0570B0", 
"#02818A", "#CE1256", "#6A51A3", "#AE017E", "#CB181D", "#238443", 
"#225EA8", "#CC4C02", "#E31A1C"), .Dim = c(35L, 4L), .Dimnames = list(
    c("BrBG", "PiYG", "PRGn", "PuOr", "RdBu", "RdGy", "RdYlBu", 
    "RdYlGn", "Spectral", "Accent", "Dark2", "Paired", "Pastel1", 
    "Pastel2", "Set1", "Set2", "Set3", "Blues", "BuGn", "BuPu", 
    "GnBu", "Greens", "Greys", "Oranges", "OrRd", "PuBu", "PuBuGn", 
    "PuRd", "Purples", "RdPu", "Reds", "YlGn", "YlGnBu", "YlOrBr", 
    "YlOrRd"), NULL))

这是用于生成此代码的代码：

number_of_colors <- 4
pallete_names <- rownames(RColorBrewer::brewer.pal.info)
pallete_color_generator <- RColorBrewer::brewer.pal

# make color hexcodes:
palletes<-lapply(pallete_names,
                 pallete_color_generator,
                 n = number_of_colors) 

# turn into matrix:
palletes<-do.call(rbind,palletes)

rownames(palletes)<-pallete_names

# dump hard-coded R code to create the object to the console:
dump('palletes','')

Answer 5

要在基础中创建自定义调色板，如问题图中所列：

customvermillion<-rgb(213/255,94/255,0/255)
custombluegreen<-rgb(0/255,158/255,115/255)
customblue<-rgb(0/255,114/255,178/255)
customskyblue<-rgb(86/255,180/255,233/255)
customreddishpurple<-rgb(204/255,121/255,167/255) 

然后在

中引用时

plot()

而不是使用参数：

plot(mtcars$mpg,mtcars$hp,col=c("orange","skyblue"))

使用参数：

plot(mtcars$mpg,mtcars$hp,col=c(customorange,customskyblue))