R，使用 scale_linetype_manual 更改 ggplot 图例名称
我有一个看起来像这样的数据框：
> df
Year mpft value type index
1 1996 2 0.033827219 solid 2.1
2 1997 2 0.133278701 solid 2.1
3 1998 2 0.261428650 solid 2.1
4 1999 2 0.394702438 solid 2.1
5 1996 3 0.019079686 solid 3.1
6 1997 3 0.074332942 solid 3.1
7 1998 3 0.149042964 solid 3.1
8 1999 3 0.227812452 solid 3.1
9 1996 4 0.009909126 solid 4.1
10 1997 4 0.026231721 solid 4.1
11 1998 4 0.052912805 solid 4.1
12 1999 4 0.086256016 solid 4.1
13 1996 17 0.017256492 solid 17.1
14 1997 17 0.079446280 solid 17.1
15 1998 17 0.166014538 solid 17.1
16 1999 17 0.316175339 solid 17.1
17 1996 18 0.080072523 solid 18.1
18 1997 18 0.313289644 solid 18.1
19 1998 18 0.629398957 solid 18.1
20 1999 18 1.024946245 solid 18.1
110 1996 2 0.031634282 dashed 2.2
21 1997 2 0.139244701 dashed 2.2
31 1998 2 0.273270126 dashed 2.2
41 1999 2 0.412409808 dashed 2.2
51 1996 3 0.019430502 dashed 3.2
61 1997 3 0.079252516 dashed 3.2
71 1998 3 0.161607337 dashed 3.2
81 1999 3 0.252595611 dashed 3.2
91 1996 4 0.009976637 dashed 4.2
101 1997 4 0.027057403 dashed 4.2
111 1998 4 0.055755671 dashed 4.2
121 1999 4 0.093064641 dashed 4.2
171 1996 18 0.061041422 dashed 18.2
181 1997 18 0.245554619 dashed 18.2
191 1998 18 0.490633135 dashed 18.2
201 1999 18 0.758070060 dashed 18.2
我正在尝试绘制数据并有正确的图例，到目前为止我最初尝试过
ggplot(df,aes(x=Year,y=value, colour = factor(mpft),linetype=type)) +
geom_line(aes(group = index), size = 1.4) +
#scale_linetype_manual(name= "Run Type", values = unique(df$type), labels = run.type) +
scale_color_manual(name = "PFT",
values = setNames(mycol[unique(df$mpft)], unique(df$mpft)),
labels = setNames(mynam[unique(df$mpft)], unique(df$mpft)))
这给了我
我曾尝试添加 scale_linetype_manual
ggplot(df,aes(x=Year,y=value, colour = factor(mpft),linetype=type)) +
geom_line(aes(group = index), size = 1.4) +
scale_linetype_manual(name= "Run Type", values = unique(df$type), labels = run.type) +
scale_color_manual(name = "PFT",
values = setNames(mycol[unique(df$mpft)], unique(df$mpft)),
labels = setNames(mynam[unique(df$mpft)], unique(df$mpft)))
和
> run.type
[1] "current" "origED3"
但我得到
它具有图例的正确名称，但具有不同的线型。我错过了什么？
编辑
在dput我的数据帧的是
> dput(df)
structure(list(Year = c(1996, 1997, 1998, 1999, 1996, 1997, 1998,
1999, 1996, 1997, 1998, 1999, 1996, 1997, 1998, 1999, 1996, 1997,
1998, 1999, 1996, 1997, 1998, 1999, 1996, 1997, 1998, 1999, 1996,
1997, 1998, 1999, 1996, 1997, 1998, 1999), mpft = c(2L, 2L, 2L,
2L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 17L, 17L, 17L, 17L, 18L,
18L, 18L, 18L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L,
18L, 18L, 18L, 18L), value = c(0.0338272191848643, 0.133278701149992,
0.261428650232716, 0.394702437670559, 0.0190796862689925, 0.0743329421068756,
0.149042964352043, 0.227812451937011, 0.00990912614900737, 0.0262317206863519,
0.0529128049802722, 0.0862560162908444, 0.017256491619149, 0.0794462797803606,
0.166014537897384, 0.31617533869767, 0.0800725232220131, 0.31328964372358,
0.629398957462415, 1.02494624459608, 0.0316342818911836, 0.139244700529005,
0.273270126484303, 0.412409807917143, 0.0194305022713642, 0.0792525159706922,
0.161607337403947, 0.252595610607411, 0.00997663742883768, 0.0270574028188436,
0.0557556714277292, 0.0930646413413941, 0.0610414215913856, 0.245554619318541,
0.490633135315979, 0.758070059865948), type = structure(c(1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L), .Label = c("solid", "dashed"), class = "factor"),
index = structure(c(1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 3L, 3L,
3L, 3L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 7L,
7L, 7L, 7L, 8L, 8L, 8L, 8L, 9L, 9L, 9L, 9L), .Label = c("2.1",
"3.1", "4.1", "17.1", "18.1", "2.2", "3.2", "4.2", "18.2"
), class = "factor")), .Names = c("Year", "mpft", "value",
"type", "index"), row.names = c("1", "2", "3", "4", "5", "6",
"7", "8", "9", "10", "11", "12", "13", "14", "15", "16", "17",
"18", "19", "20", "110", "21", "31", "41", "51", "61", "71",
"81", "91", "101", "111", "121", "171", "181", "191", "201"), class = "data.frame")
编辑
不是一个非常优雅的解决方案，但用"dashed"用"22"，然后使用：
ggplot(df,aes(x=Year,y=value, colour = factor(mpft),linetype=type)) +
geom_line(aes(group = index), size = 1.4) +
scale_linetype_manual(name= "Run Type", values = unique(as.character(df$type)), labels = run.type) +
scale_color_manual(name = "PFT",
values = setNames(mycol[unique(df$mpft)], unique(df$mpft)),
labels = setNames(mynam[unique(df$mpft)], unique(df$mpft)))
我能做对
有趣的问题，我以前从未遇到过这个问题。
简短回答
区别是因为第一个版本中的线型"dashed"根本不是。
长答案
在您的第一个版本中，没有指定任何linetype美观内容， ggplot 默认为scale_linetype_discrete()，当前代码是：
scale_linetype <- function(..., na.value = "blank") {
discrete_scale("linetype", "linetype_d", linetype_pal(),
na.value = na.value, ...)
}
因此，scale_linetype_discrete()从函数中获取其线型值linetype_pal，由包提供scales（至少，这是我找到它的唯一地方）：
> scales::linetype_pal()(2)
[1] "solid" "22"
linetype当您在第二个版本中指定美学映射时，使用scale_linetype_manual()，对应的当前代码为：
scale_linetype_manual <- function(..., values) {
manual_scale("linetype", values, ...)
}
c("solid", "dashed")因此，当您在图中明确要求提供两个线型值时，ggplot 将使用它们。如果不这样做，默认值是c("solid", "22")， ，并且"22"对应于比"dashed"的模式不同的、间隔更紧密的模式。
下面的演示，使用内置数据：
df.sample <- diamonds %>%
filter(cut %in% c("Fair", "Good")) %>%
group_by(cut, clarity) %>%
summarise(price = mean(price / carat)) %>%
ungroup()
p <- ggplot(df.sample,
aes(x = clarity, y = price, group = cut,
linetype = cut)) +
geom_line(size = 1) +
guides(linetype = guide_legend(keywidth = 3, keyheight = 1)) +
theme(legend.position = c(1, 0), legend.justification = c(1, 0))
library(gridExtra)
grid.arrange(p +
labs(title = "Default scale",
subtitle = c("values = linetype_pal()(2)")),
p + scale_linetype_manual(values = c("solid", "dashed")) +
labs(title = "Manual scale",
subtitle = "values = c('solid', 'dashed')"),
p + scale_linetype_manual(values = c("solid", "22")) +
labs(title = "Manual scale",
subtitle = "values = c('solid', '22')"),
nrow = 1)
第三个图模仿了默认比例的行为。
小智 1
您只是看不到线型差异 - 如果您将图例加宽，则它是可见的：
ggplot(df,aes(x=Year,y=value, colour = factor(mpft),linetype=type)) +
geom_line(aes(group = index), size = 1.4) +
scale_linetype_manual(name= "Run Type", values = unique(df$type), labels = run.type) +
guides(linetype = guide_legend(keywidth = 3, keyheight = 1))
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