ggplot2中geom_line的两个色阶

Question

我有一个图表（需要复制的代码将在下面），它有两行需要进行颜色编码的行（和点），然后需要三组置信区间（行）有自己的颜色编码。

不幸的是，ggplot看到两个对geom_line（）的调用，并将它们全部放在相同的范围内。

有没有办法让中央线和点有一个规模（和图例项），而外线有一个单独的规模（和图例项）？

我已经看到（复杂）像ggplot2: Multiple color scales or shift colors systematically on different layers?这样的答案，但依赖于我认为现在已被淘汰的旧原型系统（？）。

感谢您的任何帮助。

生成数据和图形的代码。对不起，长度：

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., 
-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") 

P.S.仅使用aes_string，因为这是在允许用户将列输入为字符的函数中调用的。

Answer 1

不幸的是，哈德利证实这是不可能的。所以我决定使用线型（而没有任何区分点）。这让每个人都开心。

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") 

Answer 2

的GGPLOT2办法做到这一点是不使用为geom_line你的信心带。有一个专门为此构建的geom：geom_ribbon。

ggplot(exShapedMayGroup, aes(x=Date, y=Score)) + 
     geom_ribbon(aes(ymin = Lower,ymax = Upper,fill = Right,group = Right),alpha = 0.25) + 
     geom_line(aes(group= .id, colour= .id)) + 
     geom_point(aes(colour = Right)) + 
     scale_color_discrete(name="Limits") 

很显然，我不能肯定，你会发现这是如何看起来，但这通常是你如何在GGPLOT2接近这种图形。请注意，我删除了代码中的aes_string用法。