ggplot2 中 geom_line 的两个色阶 [英] Two Color Scales for geom_line in ggplot2

问题描述

我有一个图表(要复制的代码将在下面)，其中有两行(和点)需要进行颜色编码的数据，然后是三组需要有自己的颜色编码的置信区间(线).

I have a chart (code to replicate will be below) that has two lines (and points) of data that need to be color coded, then three sets of confidence intervals (lines) which need to have their own color coding.

不幸的是，ggplot 看到了对 geom_line() 的两次调用，并将它们都放在相同的比例中.

Unfortunately, ggplot sees the two calls to geom_line() and fits them all in the same scale.

有没有办法让中心线和点有一个比例尺(和图例条目)而外线有一个单独的比例尺(和图例条目)?

Is there a way to have the central lines and dots have one scale (and legend entry) while the outer lines have a seperate scale (and legend entry)?

我见过(复杂的)答案，例如 ggplot2:多个色阶或在不同层上系统地变换颜色? 但这依赖于我认为现在已经被淘汰的旧原型系统(?).

I've seen (complex) answers like ggplot2: Multiple color scales or shift colors systematically on different layers? but that relies on the old proto system which I believe has been phased out by now(?).

感谢您的帮助.

生成数据和图表的代码.抱歉篇幅太长:

Code to produce data and graphs. Sorry for the length:

exShapedMayGroup <- structure(list(Date = structure(c(14730, 14730, 14730, 14731, 
14731, 14731, 14734, 14734, 14734, 14735, 14735, 14735, 14736, 
14736, 14736, 14737, 14737, 14737, 14740, 14740, 14740, 14741, 
14741, 14741, 14742, 14742, 14742, 14743, 14743, 14743, 14744, 
14744, 14744, 14745, 14745, 14745, 14746, 14746, 14746, 14748, 
14748, 14748, 14749, 14749, 14749, 14750, 14750, 14750, 14750, 
14750, 14750, 14751, 14751, 14751, 14752, 14752, 14752, 14752, 
14752, 14752, 14754, 14754, 14754, 14756, 14756, 14756, 14757, 
14757, 14757, 14758, 14758, 14758, 14758, 14758, 14758, 14759, 
14759, 14759, 14760, 14760, 14760), class = "Date"), Score = c(0.028, 
0.028, 0.028, 0.03289, 0.03289, 0.03289, 0.034512, 0.034512, 
0.034512, 0.0373496, 0.0373496, 0.0373496, 0.03201968, 0.03201968, 
0.03201968, 0.040805744, 0.040805744, 0.040805744, 0.0344045952, 
0.0344045952, 0.0344045952, 0.04017367616, 0.04017367616, 0.04017367616, 
0.035998940928, 0.035998940928, 0.035998940928, 0.0342191527424, 
0.0342191527424, 0.0342191527424, 0.09799532219392, 0.09799532219392, 
0.09799532219392, 0.122746257755136, 0.122746257755136, 0.122746257755136, 
0.0999570062041088, 0.0999570062041088, 0.0999570062041088, 0.0950656049632871, 
0.0950656049632871, 0.0950656049632871, 0.0837224839706296, 0.0837224839706296, 
0.0837224839706296, 0.00418, 0.00418, 0.00418, 0.0806379871765037, 
0.0806379871765037, 0.0806379871765037, 0.009624, 0.009624, 0.009624, 
0.0099792, 0.0099792, 0.0099792, 0.090740389741203, 0.090740389741203, 
0.090740389741203, 0.0905523117929624, 0.0905523117929624, 0.0905523117929624, 
0.0761218494343699, 0.0761218494343699, 0.0761218494343699, 0.0707874795474959, 
0.0707874795474959, 0.0707874795474959, 0.02132336, 0.02132336, 
0.02132336, 0.0636099836379967, 0.0636099836379967, 0.0636099836379967, 
0.0550479869103974, 0.0550479869103974, 0.0550479869103974, 0.0466883895283179, 
0.0466883895283179, 0.0466883895283179), Right = c("1", "2", 
"3", "1", "2", "3", "1", "2", "3", "1", "2", "3", "1", "2", "3", 
"1", "2", "3", "1", "2", "3", "1", "2", "3", "1", "2", "3", "1", 
"2", "3", "1", "2", "3", "1", "2", "3", "1", "2", "3", "1", "2", 
"3", "1", "2", "3", "1", "2", "3", "1", "2", "3", "1", "2", "3", 
"1", "2", "3", "1", "2", "3", "1", "2", "3", "1", "2", "3", "1", 
"2", "3", "1", "2", "3", "1", "2", "3", "1", "2", "3", "1", "2", 
"3"), .id = c("0", "0", "0", "0", "0", "0", "0", "0", "0", "0", 
"0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", 
"0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", 
"0", "0", "0", "0", "0", "0", "0", "0", "0", "1", "1", "1", "0", 
"0", "0", "1", "1", "1", "1", "1", "1", "0", "0", "0", "0", "0", 
"0", "0", "0", "0", "0", "0", "0", "1", "1", "1", "0", "0", "0", 
"0", "0", "0", "0", "0", "0"), Lower = c(0.0452301816389807, 
0.0299531343622987, 0.0146760870856168, 0.0409430625769167, 0.0213788962381707, 
0.00181472989942479, 0.0386359600820249, 0.0167646912483872, 
-0.00510657758525054, 0.037279363974053, 0.0140514990324434, 
-0.00917636590916623, 0.0364512577706185, 0.0123952866255743, 
-0.0116606845194698, 0.0359359120595814, 0.0113645952035002, 
-0.0132067216525811, 0.0356116886483614, 0.0107161483810601, 
-0.0141793918862411, 0.035406383399575, 0.0103055378834873, -0.0147953076326005, 
0.0352758647295475, 0.0100445005434323, -0.0151868636426829, 
0.0351926859362388, 0.00987814295681498, -0.0154364000226088, 
0.035139594640892, 0.00977196036612139, -0.0155956739086492, 
0.0351056744462797, 0.00970411997689682, -0.0156974344924861, 
0.0350839892725913, 0.00966074962952, -0.0157624900135513, 0.0350701204632195, 
0.00963301201077625, -0.0158040964416669, 0.035061248392137, 
0.00961526786861143, -0.0158307126549142, NA, NA, NA, 0.0350555718896789, 
0.00960391486369513, -0.0158477421622886, NA, NA, NA, NA, NA, 
NA, 0.0350519395924259, 0.00959665026918906, -0.0158586390540477, 
0.0350496151941651, 0.00959200147266757, -0.01586561224883, 0.0350481276906492, 
0.00958902646563569, -0.0158700747593778, 0.035047175734008, 
0.00958712255235328, -0.0158729306293014, NA, NA, NA, 0.0350465665004368, 
0.00958590408521094, -0.0158747583300149, 0.0350461765986017, 
0.00958512428154069, -0.0158759280355203, 0.0350459270645606, 
0.00958462521345864, -0.0158766766376434), Upper = c(0.0757842761923446, 
0.0910613234690266, 0.106338370745709, 0.0800713952544086, 0.0996355615931546, 
0.119199727931901, 0.0823784977493004, 0.104249766582938, 0.126121035416576, 
0.0837350938572723, 0.106962958798882, 0.130190823740492, 0.0845632000607068, 
0.108619171205751, 0.132675142350795, 0.0850785457717439, 0.109649862627825, 
0.134221179483906, 0.0854027691829639, 0.110298309450265, 0.135193849717566, 
0.0856080744317504, 0.110708919947838, 0.135809765463926, 0.0857385931017778, 
0.110969957287893, 0.136201321474008, 0.0858217718950865, 0.11113631487451, 
0.136450857853934, 0.0858748631904333, 0.111242497465204, 0.136610131739975, 
0.0859087833850456, 0.111310337854428, 0.136711892323811, 0.085930468558734, 
0.111353708201805, 0.136776947844877, 0.0859443373681059, 0.111381445820549, 
0.136818554272992, 0.0859532094391883, 0.111399189962714, 0.136845170486239, 
NA, NA, NA, 0.0859588859416464, 0.11141054296763, 0.136862199993614, 
NA, NA, NA, NA, NA, NA, 0.0859625182388994, 0.111417807562136, 
0.136873096885373, 0.0859648426371602, 0.111422456358658, 0.136880070080155, 
0.0859663301406761, 0.11142543136569, 0.136884532590703, 0.0859672820973173, 
0.111427335278972, 0.136887388460627, NA, NA, NA, 0.0859678913308885, 
0.111428553746114, 0.13688921616134, 0.0859682812327236, 0.111429333549785, 
0.136890385866846, 0.0859685307667647, 0.111429832617867, 0.136891134468969
)), .Names = c("Date", "Score", "Right", ".id", "Lower", "Upper"
), row.names = c(NA, 81L), class = "data.frame")


ggplot(exShapedMayGroup, aes_string(x="Date", y="Score"))  + geom_line(aes_string(group=".id", colour=".id")) + 
    geom_point(aes_string(colour=".id")) + geom_line(aes_string(y="Lower", colour="Right")) + 
    geom_line(aes_string(y="Upper", colour="Right")) + scale_color_discrete(name="Limits")

附言仅使用 aes_string，因为这是在允许用户将列作为字符输入的函数中调用的.

P.S. Only using aes_string because this is called in a function which allows the user to input columns as a character.

推荐答案

不幸的是 Hadley 确认这是不可能的.所以我决定改用线型(并且没有任何区分点的东西).这让大家都很开心.

Unfortunately Hadley confirmed this is not possible. So I decided to use linetype instead (and not have anything distinguishing the points). This made everyone happy.

ggplot(exShapedMayGroup, aes_string(x="Date", y="Score")) + 
geom_line(aes_string(group=".id", linetype=".id")) +  
geom_point() + 
geom_line(aes_string(y="Lower", colour="Right")) + 
geom_line(aes_string(y="Upper", colour="Right")) + 
scale_linetype_discrete(name="Group") + scale_color_discrete(name="Limits")

这篇关于ggplot2 中 geom_line 的两个色阶的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！