转自该网站:http://research.stowers-institute.org/efg/R/Color/Chart/

科学可视化中常用的一些颜色表:http://geog.uoregon.edu/datagraphics/color_scales.htm

Step-by-Step Procedure (to learn about "colors")

1.  The function call, colors(), or with the British spelling, colours(), returns a vector of  657 color names in R.  The color names are in alphabetical order, except forcolors()[1], which is "white".  The names "gray" and "grey" can be spelled either way -- many shades of grey/gray are provided with both spellings.

2.  Particular color names of interest can be found if their positions in the vector are known, e.g.,

> colors()[c(552,254,26)]
[1] "red" "green" "blue"

3.  grep can be used to find color names of interest, e.g.,

> grep("red",colors())
[1] 100 372 373 374 375 376 476 503 504 505 506 507 524 525 526 527 528 552 553
[20] 554 555 556 641 642 643 644 645

> colors()[grep("red",colors())]
[1] "darkred" "indianred" "indianred1" "indianred2" 
[5] "indianred3" "indianred4" "mediumvioletred" "orangered" 
[9] "orangered1" "orangered2" "orangered3" "orangered4" 
[13] "palevioletred" "palevioletred1" "palevioletred2" "palevioletred3" 
[17] "palevioletred4" "red" "red1" "red2" 
[21] "red3" "red4" "violetred" "violetred1" 
[25] "violetred2" "violetred3" "violetred4"

> colors()[grep("sky",colors())]
[1] "deepskyblue" "deepskyblue1" "deepskyblue2" "deepskyblue3" 
[5] "deepskyblue4" "lightskyblue" "lightskyblue1" "lightskyblue2"
[9] "lightskyblue3" "lightskyblue4" "skyblue" "skyblue1" 
[13] "skyblue2" "skyblue3" "skyblue4"

4.  The function col2rgb can be used to extract the RGB (red-green-blue) components of a color, e.g.,

> col2rgb("yellow")
[,1]
red 255
green 255
blue 0

Each of the three RGB color components ranges from 0 to 255, which is interpreted to be 0.0 to 1.0 in RGB colorspace.  With each of the RGB components having 256 possible discrete values, this results in 256*256*256 possible colors, or 16,777,216 colors.

While the RGB component values range from 0 to 255 in decimal, they range from hex 00 to hex FF.  Black, which is RGB = (0,0,0) can be represented in hex as #000000, and white, which is RGB = (255,255,255), can represented in hex as #FFFFFF.

5.  R provides a way to define an RGB triple with each of the color components ranging from 0.0 to 1.0 using the rgb function.  For example, yellow can be defined:

> rgb(1.0, 1.0, 0.0)
[1] "#FFFF00"

The output is in hexadecimal ranging from 00 to FF (i.e., decimal 0 to 255) for each color component.  The 0.0 to 1.0 inputs are a bit odd, but are standard in RGB color theory.  Since decimal values from 0 to 255 are common, the rgb function allows a maxColorValue parameter as an alternative:

> rgb(255, 255, 0, maxColorValue=255)
[1] "#FFFF00"

The R function, GetColorHexAndDecimal, was written to display both hex and decimal values of the color components for a given color name:

GetColorHexAndDecimal <- function(color)
{
  c <- col2rgb(color)
  sprintf("#%02X%02X%02X %3d %3d %3d", c[1],c[2],c[3], c[1], c[2], c[3])
}

Example:

> GetColorHexAndDecimal("yellow")
[1] "#FFFF00 255 255 0"

This GetColorHexAndDecimal function will be used below in Step 9.

6.  Text of a certain color when viewed against certain backgrounds can be very hard to see, e.g., never use yellow text on a white background since there isn't good contrast between the two.  One simple hueristic in defining a text color for a given background color is to pick the one that is "farthest" away from "black" or "white".  One way to do this is to compute the color intensity, defined as the mean of the RGB triple, and pick "black" (intensity 0) for text color if the background intensity is greater than 127, or "white" (intensity 255) when the background intensity is less than or equal to 127.

The R function below, SetTextContrastColor, gives a good text color for a given background color name:

SetTextContrastColor <- function(color)
{
  ifelse( mean(col2rgb(color)) > 127, "black", "white")
}

# Define this array of text contrast colors that correponds to each
# member of the colors() array.
TextContrastColor <- unlist( lapply(colors(), SetTextContrastColor) )

Examples:

> SetTextContrastColor("white")
[1] "black"
> SetTextContrastColor("black")
[1] "white"
> SetTextContrastColor("red")
[1] "white"
> SetTextContrastColor("yellow") 
[1] "black"

7.  The following R code produces the "R Colors" graphic shown at the top of this page (using TextContrastColor defined above):

# 1a. Plot matrix of R colors, in index order, 25 per row.
# This example plots each row of rectangles one at a time.
colCount <- 25 # number per row
rowCount <- 27

plot( c(1,colCount), c(0,rowCount), type="n", ylab="", xlab="",
  axes=FALSE, ylim=c(rowCount,0))
title("R colors")

for (j in 0:(rowCount-1))
{
  base <- j*colCount
  remaining <- length(colors()) - base
  RowSize <- ifelse(remaining < colCount, remaining, colCount)
  rect((1:RowSize)-0.5,j-0.5, (1:RowSize)+0.5,j+0.5,
    border="black",
    col=colors()[base + (1:RowSize)])
  text((1:RowSize), j, paste(base + (1:RowSize)), cex=0.7,
    col=TextContrastColor[base + (1:RowSize)])
}

8. Alphabetical order is not necessarily a good way to find similar colors.  The RGB values of each of the colors() was converted to hue-saturation-value (HSV) and then sorted by HSV.  This approach groups colors of the same "hue" together a bit better.  Here's the code and graphic produced:

# 1b. Plot matrix of R colors, in "hue" order, 25 per row.
# This example plots each rectangle one at a time.
RGBColors <- col2rgb(colors()[1:length(colors())])
HSVColors <- rgb2hsv( RGBColors[1,], RGBColors[2,], RGBColors[3,],
             maxColorValue=255)
HueOrder <- order( HSVColors[1,], HSVColors[2,], HSVColors[3,] )

plot(0, type="n", ylab="", xlab="",
axes=FALSE, ylim=c(rowCount,0), xlim=c(1,colCount))

title("R colors -- Sorted by Hue, Saturation, Value")

for (j in 0:(rowCount-1))
{
  for (i in 1:colCount)
  {
   k <- j*colCount + i
   if (k <= length(colors()))
   {
    rect(i-0.5,j-0.5, i+0.5,j+0.5, border="black", col=colors()[ HueOrder[k] ])
    text(i,j, paste(HueOrder[k]), cex=0.7, col=TextContrastColor[ HueOrder[k] ])
   }
  }
}

9.  While the color matrices above are useful, a more useful display would include a rectangular area showing the color, the color index, the color name, and the RGB values, both in hexadecimal, which is often used in web pages.

The code for this is a bit tedious -- see Item #2 in the ColorChart.R code for complete details. Here is the first page of the Chart of R colors.

PDF of 7-page "Chart of R colors"

10.  To create a PDF file (named ColorChart.pdf) with all the graphics shown on this page, issue this R command:

source("http://research.stowers-institute.org/efg/R/Color/Chart/ColorChart.R")

【转】R语言笔记--颜色的使用的更多相关文章

  1. R语言笔记

    R语言笔记 学习R语言对我来说有好几个地方需要注意的,我觉得这样的经验也适用于学习其他的新的语言. 语言的目标 我理解语言的目标就是这个语言是用来做什么的,为什么样的任务服务的,也就是设计这个语言的动 ...

  2. R语言笔记4--可视化

    接R语言笔记3--实例1 R语言中的可视化函数分为两大类,探索性可视化(陌生数据集,不了解,需要探索里面的信息:偏重于快速,方便的工具)和解释性可视化(完全了解数据集,里面的故事需要讲解别人:偏重全面 ...

  3. R语言笔记完整版

    [R笔记]R语言函数总结   R语言与数据挖掘:公式:数据:方法 R语言特征 对大小写敏感 通常,数字,字母,. 和 _都是允许的(在一些国家还包括重音字母).不过,一个命名必须以 . 或者字母开头, ...

  4. R语言笔记:快速入门

    1.简单会话 > x<-c(1,2,4) > x [1] 1 2 4 R语言的标准赋值运算符是<-.也可以用=,不过不建议用它,有些情况会失灵.其中c表示连接(concaten ...

  5. 初探R语言——R语言笔记

    R语言使用 <-  赋值 # 作为注释符号 c()函数用于作为向量赋值,例如age<-c(1,2,3,4,5) mean()用于求向量的平均值 sd()求向量的标准差 cor(a,b)求a ...

  6. R语言笔记5--读数据

    1.读文本文件数据 (1)先设置工作目录,把文本文件放于该目录下 备注:在记事本里写完数据后,按一下回车,负责在R语言中出现错误 (2)读剪贴板 文本或EXCEL的数据均可通过剪贴板操作 (3)读ex ...

  7. R语言笔记1--向量、数组、矩阵、数据框、列表

    注释:R语言是区分大小写的 1.向量 R语言中可以将各种向量赋值为一个变量,这种赋值操作符就是等号“=”,也可以使用“<-”. 1)产生向量 (1)函数c() 例如:x1=c(2,4,6,8,0 ...

  8. R语言笔记2--循环、R脚本

    1.循环语句 for语句 while语句 2.R脚本 source()函数 print()函数

  9. r语言笔记 jn

    get_range <- function(data_name , row_name){ library(stringr) load(data_name) data_str <- str_ ...

随机推荐

  1. 谈谈对从业IT行业看法

    做后端开发也有五年了,从工厂到IT行业转化很大,当然最后离职的工厂想也没想过会写代码为生. 是什么变动会让我走入这一行呢? 1.思想作怪 *我当时就想,我认为不应该一辈子只做这狗屎事,起码在当时看来就 ...

  2. 基于MSP430F413水果电池供电的低功耗时钟

      我最早接触MSP430时候,看到书的第一页就是一张水果电池的图片,一直以来想做一个低功耗的可以水果电池供电的系统,毕业之后的下半年选择MSP430F413单片机来画了一个低功耗的板子,一直没有调试 ...

  3. 【原创】14. MYSQL++之SSQLS(原理解析)

    从之前所介绍的SSQLS的介绍中我们可以感受到,SSQLS的精髓应该在sql_create_#这个宏,他所创建出来的这个结构体将会是突破的关键,所以我将会从以下顺序入手. 1. sql_create_ ...

  4. 哇塞,原来自己写 Google Chrome 浏览器扩展(插件)这么容易!

    1. 首先新建一个记事本,命名为 manifest.json,这是写 Google Chrome 浏览器扩展必须的文件 { "manifest_version": 2, " ...

  5. 二叉搜索树BinarySearchTree(C实现)

    头文件—————————————————————————————— #ifndef _BINARY_SEARCH_TREE_H_ #define _BINARY_SEARCH_TREE_H_ #inc ...

  6. 使用ELK(Elasticsearch + Logstash + Kibana) 搭建日志集中分析平台实践--转载

    原文地址:https://wsgzao.github.io/post/elk/ 另外可以参考:https://www.digitalocean.com/community/tutorials/how- ...

  7. boi剖析 - 基于webpack的css sprites实现方案

    本文是58到家前端工程化集成解决方案boi的博文系列之一.boi是基于webpack打造的一站式前端工程化解决方案,现已开源Github. 作为前端构建工具不可或缺的一个环节,自动生成css spri ...

  8. fcitx 无法启动

    困扰了好久的问题,终于解决了. 问题描述: 在fcitx的输入法配置栏里,输入法列表是空的,使用Ctrl+space无法启用任何的输入法, 当然此截图中的是有的,这是问题已经解决后的状态了. 解决方法 ...

  9. The Linux Process Principle,NameSpace, PID、TID、PGID、PPID、SID、TID、TTY

    目录 . 引言 . Linux进程 . Linux命名空间 . Linux进程的相关标识 . 进程标识编程示例 . 进程标志在Linux内核中的存储和表现形式 . 后记 0. 引言 在进行Linux主 ...

  10. SQL Server中的连接查询【内连接,左连接,右连接,。。。】

    在查询多个表时,我们经常会用“连接查询”.连接是关系数据库模型的主要特点,也是它区别于其它类型数据库管理系统的一个标志. 什么是连接查询呢? 概念:根据两个表或多个表的列之间的关系,从这些表中查询数据 ...