ggplot2：图例中的斜体
ggplot2: italics in the legend
我正在尝试编辑图例中的标签，以便第一个标签 (WT) 为纯文本，而随后的 7 个标签为斜体。我一直在使用 element_text(face=c("plain", rep("italic",7))) ，但这导致 none 的标签被转换为斜体。我有点困惑为什么它不起作用，因为 element_text(face="italic") 将所有标签都转换为斜体。我的剧情如下：
library(tidyverse)
for_plot <- read_csv(file =
"Row, Time, Mutant, Mean
1, 1, ppi1, 0.8008
2, 1, sp1-1, 0.8038
3, 1, sp1-1 ppi1, 0.8094
4, 1, sp1-2 ppi1, 0.8138
5, 1, sp1-3 ppi1, 0.8066667
6, 1, sp1-4 ppi1, 0.7998
7, 1, sp1-5 ppi1, 0.8026667
8, 1, Wt, 0.8083333
9, 21, ppi1, 0.6806
10, 21, sp1-1, 0.7088
11, 21, sp1-1 ppi1, 0.6982
12, 21, sp1-2 ppi1, 0.7126
13, 21, sp1-3 ppi1, 0.709
14, 21, sp1-4 ppi1, 0.6942
15, 21, sp1-5 ppi1, 0.7096667
16, 21, Wt, 0.7246667
17, 56, ppi1, 0.6652
18, 56, sp1-1, 0.6848
19, 56, sp1-1 ppi1, 0.6816
20, 56, sp1-2 ppi1, 0.6926
21, 56, sp1-3 ppi1, 0.6945
22, 56, sp1-4 ppi1, 0.676
23, 56, sp1-5 ppi1, 0.6931667
24, 56, Wt, 0.6946667
25, 111, ppi1, 0.653
26, 111, sp1-1, 0.6704
27, 111, sp1-1 ppi1, 0.6704
28, 111, sp1-2 ppi1, 0.6756
29, 111, sp1-3 ppi1, 0.679
30, 111, sp1-4 ppi1, 0.664
31, 111, sp1-5 ppi1, 0.6805
32, 111, Wt, 0.677
33, 186, ppi1, 0.6132
34, 186, sp1-1, 0.633
35, 186, sp1-1 ppi1, 0.6298
36, 186, sp1-2 ppi1, 0.6402
37, 186, sp1-3 ppi1, 0.6435
38, 186, sp1-4 ppi1, 0.6278
39, 186, sp1-5 ppi1, 0.6478333
40, 186, Wt, 0.6403333
41, 281, ppi1, 0.5636
42, 281, sp1-1, 0.587
43, 281, sp1-1 ppi1, 0.5828
44, 281, sp1-2 ppi1, 0.5906
45, 281, sp1-3 ppi1, 0.5968333
46, 281, sp1-4 ppi1, 0.5838
47, 281, sp1-5 ppi1, 0.5983333
48, 281, Wt, 0.5948333")
for_plot %>%
ggplot()+
geom_line(aes(x = Time, y = Mean, col = Mutant)) +
geom_point(aes(x = Time, y = Mean, col = Mutant)) +
labs(title = "Effective PSII Quantum Yield across SP1 Mutants",
y = "Effective PSII Quantum Yield",
x = "Actinic PPFD") +
theme(plot.title = element_text(hjust = 0.5)) +
theme(legend.text = element_text(face=c("plain", rep("italic",7))))
由 reprex package (v0.3.0)
于 2020-01-01 创建
我编写了 ggtext 包来使这些类型的问题更容易解决。它允许您使用 markdown 进行样式设置，即只需将斜体部分用星号括起来。
该软件包目前正在开发中，需要通过远程安装，但很快就会在 CRAN 上发布（spring 2020）。您可能还需要 ggplot2 的最新开发版本，您可以通过 remotes::install_github("tidyverse/ggplot2").
安装
library(tidyverse)
library(ggtext) # remotes::install_github("clauswilke/ggtext")
for_plot <- read_csv(file =
"Row, Time, Mutant, Mean
1, 1, ppi1, 0.8008
2, 1, sp1-1, 0.8038
3, 1, sp1-1 ppi1, 0.8094
4, 1, sp1-2 ppi1, 0.8138
5, 1, sp1-3 ppi1, 0.8066667
6, 1, sp1-4 ppi1, 0.7998
7, 1, sp1-5 ppi1, 0.8026667
8, 1, Wt, 0.8083333
9, 21, ppi1, 0.6806
10, 21, sp1-1, 0.7088
11, 21, sp1-1 ppi1, 0.6982
12, 21, sp1-2 ppi1, 0.7126
13, 21, sp1-3 ppi1, 0.709
14, 21, sp1-4 ppi1, 0.6942
15, 21, sp1-5 ppi1, 0.7096667
16, 21, Wt, 0.7246667
17, 56, ppi1, 0.6652
18, 56, sp1-1, 0.6848
19, 56, sp1-1 ppi1, 0.6816
20, 56, sp1-2 ppi1, 0.6926
21, 56, sp1-3 ppi1, 0.6945
22, 56, sp1-4 ppi1, 0.676
23, 56, sp1-5 ppi1, 0.6931667
24, 56, Wt, 0.6946667
25, 111, ppi1, 0.653
26, 111, sp1-1, 0.6704
27, 111, sp1-1 ppi1, 0.6704
28, 111, sp1-2 ppi1, 0.6756
29, 111, sp1-3 ppi1, 0.679
30, 111, sp1-4 ppi1, 0.664
31, 111, sp1-5 ppi1, 0.6805
32, 111, Wt, 0.677
33, 186, ppi1, 0.6132
34, 186, sp1-1, 0.633
35, 186, sp1-1 ppi1, 0.6298
36, 186, sp1-2 ppi1, 0.6402
37, 186, sp1-3 ppi1, 0.6435
38, 186, sp1-4 ppi1, 0.6278
39, 186, sp1-5 ppi1, 0.6478333
40, 186, Wt, 0.6403333
41, 281, ppi1, 0.5636
42, 281, sp1-1, 0.587
43, 281, sp1-1 ppi1, 0.5828
44, 281, sp1-2 ppi1, 0.5906
45, 281, sp1-3 ppi1, 0.5968333
46, 281, sp1-4 ppi1, 0.5838
47, 281, sp1-5 ppi1, 0.5983333
48, 281, Wt, 0.5948333")
for_plot %>%
ggplot()+
geom_line(aes(x = Time, y = Mean, col = Mutant)) +
geom_point(aes(x = Time, y = Mean, col = Mutant)) +
labs(title = "Effective PSII Quantum Yield across SP1 Mutants",
y = "Effective PSII Quantum Yield",
x = "Actinic PPFD") +
scale_color_hue(
breaks = c("ppi1", "sp1-1", "sp1-1 ppi1", "sp1-2 ppi1",
"sp1-3 ppi1", "sp1-4 ppi1", "sp1-5 ppi1", "Wt"),
labels = c("ppi1", "*sp1-1*", "*sp1-1 ppi1*", "*sp1-2 ppi1*",
"*sp1-3 ppi1*", "*sp1-4 ppi1*", "*sp1-5 ppi1*", "*Wt*")
) +
theme(plot.title = element_text(hjust = 0.5)) +
theme(legend.text = element_markdown())
这也适用于部分文本，例如，如果您希望 SP1 在标题中使用斜体，您可以这样做。
for_plot %>%
ggplot()+
geom_line(aes(x = Time, y = Mean, col = Mutant)) +
geom_point(aes(x = Time, y = Mean, col = Mutant)) +
labs(title = "Effective PSII Quantum Yield across *SP1* Mutants",
y = "Effective PSII Quantum Yield",
x = "Actinic PPFD") +
scale_color_hue(
breaks = c("ppi1", "sp1-1", "sp1-1 ppi1", "sp1-2 ppi1",
"sp1-3 ppi1", "sp1-4 ppi1", "sp1-5 ppi1", "Wt"),
labels = c("ppi1", "*sp1-1*", "*sp1-1 ppi1*", "*sp1-2 ppi1*",
"*sp1-3 ppi1*", "*sp1-4 ppi1*", "*sp1-5 ppi1*", "*Wt*")
) +
theme(plot.title = element_markdown(hjust = 0.5)) +
theme(legend.text = element_markdown())
您可能想尝试真正的 R 图，其函数 IMO 可能不那么令人困惑且更容易学习，并且 肯定 更好地自定义。
有两个步骤，定义标签和颜色，然后绘制图例。
# define labels and colors beforehand
mutants <- sort(unique(edtct3$Mutant)) # unique and alph. sorted mutants
clr <- hcl.colors(8, "Spectral")
op <- par(mar=c(5, 5, 4, 7.5)) # modify margins of plot region (B, L, T, R)
# plot
with(edtct3, plot(x=Time, y=Mean, type="n", ## empty plot: type="n"
main="Effective PSII Quantum Yield across SP1 Mutants",
ylab="Effective PSII Quantum Yield",
xlab="Actinic PPFD"))
# lines and points: loop over the mutants with an `sapply`
# the actual function is `lines()`
sapply(seq(mutants), function(x) ## `seq(mutants)` makes a loop sequence over the mutants
with(edtct3[edtct3$Mutant == mutants[x], ], ## subsetting
lines(x=Time, y=Mean, type="o", pch=16, col=clr[x]))) ## type="o" makes lines and points
# legend
legend(x=20.5, y=1.69, xpd=TRUE, legend=labs, pch=15, col=clr, cex=.9,
text.font=c(1, rep(3, 7))) ## recall the "face" vector from former question
par(op) # reset margins of plot region
产量
数据：
edtc3 <- structure(list(Time = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 6, 6,
6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6,
6, 6, 6, 6, 6, 6, 6, 6, 6, 11, 11, 11, 11, 11, 11, 11, 11, 11,
11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11,
11, 11, 11, 11, 11, 11, 11, 19, 19, 19, 19, 19, 19, 19, 19, 19,
19, 19, 19, 19, 19, 19, 19, 19, 19, 19, 19, 19, 19, 19, 19, 19,
19, 19, 19, 19, 19, 19, 19), Mutant = c("sp2-3 ppi1", "ppi1",
"WT", "sp2-6 ppi1", "sp2-4", "WT", "sp2-3 ppi1", "sp2-8 ppi1",
"sp2 ppi1", "ppi1", "sp2-6 ppi1", "sp2-8 ppi1", "sp2 ppi1", "sp2-6 ppi1",
"sp2-5 ppi1", "WT", "sp2-4", "sp2 ppi1", "sp2-4", "sp2-5 ppi1",
"sp2-5 ppi1", "sp2-4", "sp2 ppi1", "WT", "sp2-6 ppi1", "sp2-8 ppi1",
"sp2-3 ppi1", "sp2-8 ppi1", "ppi1", "ppi1", "sp2-3 ppi1", "sp2-5 ppi1",
"sp2-5 ppi1", "sp2-6 ppi1", "ppi1", "WT", "sp2-8 ppi1", "sp2-8 ppi1",
"sp2-3 ppi1", "sp2 ppi1", "ppi1", "sp2-6 ppi1", "WT", "sp2-8 ppi1",
"WT", "sp2-3 ppi1", "sp2-5 ppi1", "ppi1", "sp2-3 ppi1", "sp2-6 ppi1",
"sp2-5 ppi1", "sp2-3 ppi1", "sp2 ppi1", "sp2-5 ppi1", "sp2 ppi1",
"ppi1", "sp2-4", "sp2-4", "sp2-4", "sp2-4", "WT", "sp2 ppi1",
"sp2-6 ppi1", "sp2-8 ppi1", "sp2 ppi1", "sp2-4", "sp2-4", "sp2-8 ppi1",
"sp2-4", "sp2-3 ppi1", "sp2-8 ppi1", "sp2-4", "WT", "sp2 ppi1",
"ppi1", "sp2 ppi1", "sp2-5 ppi1", "WT", "sp2-3 ppi1", "sp2-3 ppi1",
"sp2-3 ppi1", "sp2-6 ppi1", "sp2-5 ppi1", "ppi1", "ppi1", "sp2-8 ppi1",
"sp2 ppi1", "WT", "WT", "sp2-6 ppi1", "sp2-5 ppi1", "ppi1", "sp2-5 ppi1",
"sp2-6 ppi1", "sp2-6 ppi1", "sp2-8 ppi1", "sp2-3 ppi1", "sp2 ppi1",
"sp2-5 ppi1", "sp2-6 ppi1", "sp2-3 ppi1", "sp2-4", "sp2-4", "sp2-6 ppi1",
"sp2-5 ppi1", "sp2-4", "sp2-8 ppi1", "ppi1", "ppi1", "WT", "sp2 ppi1",
"sp2 ppi1", "ppi1", "sp2-6 ppi1", "ppi1", "sp2-4", "sp2-5 ppi1",
"sp2-3 ppi1", "sp2-6 ppi1", "sp2-5 ppi1", "sp2-8 ppi1", "WT",
"sp2 ppi1", "sp2-8 ppi1", "sp2-3 ppi1", "sp2-8 ppi1", "WT", "WT"
), Mean = c(0.91, 0.59, 1.14, 0.74, 1.08, 1.65, 0.77, 1.34, 0.65,
0.61, 0.86, 1.3, 0.82, 0.84, 0.97, 1.29, 1.15, 0.84, 1, 1.04,
0.78, 1.01, 1.02, 1.33, 0.88, 1.25, 0.78, 1.25, 0.8, 0.67, 0.85,
0.9, 1.04, 0.84, 0.67, 1.65, 1.25, 1.34, 0.77, 1.02, 0.59, 0.88,
1.33, 1.3, 1.29, 0.91, 0.78, 0.8, 0.78, 0.86, 0.9, 0.85, 0.84,
0.97, 0.65, 0.61, 1.01, 1.08, 1.15, 1, 1.14, 0.82, 0.74, 1.25,
1.02, 1.08, 1.15, 1.25, 1.01, 0.85, 1.25, 1, 1.29, 0.84, 0.59,
0.82, 1.04, 1.33, 0.77, 0.91, 0.78, 0.86, 0.78, 0.67, 0.61, 1.34,
0.65, 1.65, 1.14, 0.84, 0.9, 0.8, 0.97, 0.74, 0.88, 1.3, 0.78,
0.84, 1.04, 0.88, 0.91, 1.01, 1.15, 0.74, 0.78, 1, 1.3, 0.67,
0.8, 1.14, 1.02, 0.82, 0.59, 0.84, 0.61, 1.08, 0.9, 0.77, 0.86,
0.97, 1.34, 1.29, 0.65, 1.25, 0.85, 1.25, 1.65, 1.33)), row.names = c("17",
"5", "1", "25", "10", "4", "18", "32", "15", "7", "27", "31",
"14", "26", "24", "3", "9", "16", "11", "22", "21", "12", "13",
"2", "28", "29", "19", "30", "6", "8", "20", "23", "221", "261",
"81", "41", "291", "321", "181", "131", "51", "281", "210", "311",
"33", "171", "211", "61", "191", "271", "231", "201", "161",
"241", "151", "71", "121", "101", "91", "111", "110", "141",
"251", "301", "132", "102", "92", "292", "122", "202", "302",
"112", "34", "162", "52", "142", "222", "212", "182", "172",
"192", "272", "213", "82", "72", "322", "152", "42", "113", "262",
"232", "62", "242", "252", "282", "312", "193", "163", "223",
"283", "173", "123", "93", "253", "214", "114", "313", "83",
"63", "115", "133", "143", "53", "263", "73", "103", "233", "183",
"273", "243", "323", "35", "153", "303", "203", "293", "43",
"215"), class = "data.frame")
使用（非常温和的）修改版本
使用此函数，您可以在对 scale.
的调用中将感兴趣的类别设置为 "plain"
library(tidyverse)
toexpr <- function(x, plain = NULL) {
getfun <- function(x) {
ifelse(x == plain, "plain", "italic")
}
as.expression(unname(Map(function(f,v) substitute(f(v), list(f=as.name(f), v=as.character(v))), getfun(x), x)))
}
ggplot(for_plot)+
geom_line(aes(x = Time, y = Mean, col = Mutant)) +
geom_point(aes(x = Time, y = Mean, col = Mutant)) +
scale_color_discrete(labels = toexpr(for_plot$Mutant, plain = 'Wt'))
由 reprex package (v0.3.0)
于 2020 年 1 月 2 日创建
我正在尝试编辑图例中的标签，以便第一个标签 (WT) 为纯文本，而随后的 7 个标签为斜体。我一直在使用 element_text(face=c("plain", rep("italic",7))) ，但这导致 none 的标签被转换为斜体。我有点困惑为什么它不起作用，因为 element_text(face="italic") 将所有标签都转换为斜体。我的剧情如下：
library(tidyverse)
for_plot <- read_csv(file =
"Row, Time, Mutant, Mean
1, 1, ppi1, 0.8008
2, 1, sp1-1, 0.8038
3, 1, sp1-1 ppi1, 0.8094
4, 1, sp1-2 ppi1, 0.8138
5, 1, sp1-3 ppi1, 0.8066667
6, 1, sp1-4 ppi1, 0.7998
7, 1, sp1-5 ppi1, 0.8026667
8, 1, Wt, 0.8083333
9, 21, ppi1, 0.6806
10, 21, sp1-1, 0.7088
11, 21, sp1-1 ppi1, 0.6982
12, 21, sp1-2 ppi1, 0.7126
13, 21, sp1-3 ppi1, 0.709
14, 21, sp1-4 ppi1, 0.6942
15, 21, sp1-5 ppi1, 0.7096667
16, 21, Wt, 0.7246667
17, 56, ppi1, 0.6652
18, 56, sp1-1, 0.6848
19, 56, sp1-1 ppi1, 0.6816
20, 56, sp1-2 ppi1, 0.6926
21, 56, sp1-3 ppi1, 0.6945
22, 56, sp1-4 ppi1, 0.676
23, 56, sp1-5 ppi1, 0.6931667
24, 56, Wt, 0.6946667
25, 111, ppi1, 0.653
26, 111, sp1-1, 0.6704
27, 111, sp1-1 ppi1, 0.6704
28, 111, sp1-2 ppi1, 0.6756
29, 111, sp1-3 ppi1, 0.679
30, 111, sp1-4 ppi1, 0.664
31, 111, sp1-5 ppi1, 0.6805
32, 111, Wt, 0.677
33, 186, ppi1, 0.6132
34, 186, sp1-1, 0.633
35, 186, sp1-1 ppi1, 0.6298
36, 186, sp1-2 ppi1, 0.6402
37, 186, sp1-3 ppi1, 0.6435
38, 186, sp1-4 ppi1, 0.6278
39, 186, sp1-5 ppi1, 0.6478333
40, 186, Wt, 0.6403333
41, 281, ppi1, 0.5636
42, 281, sp1-1, 0.587
43, 281, sp1-1 ppi1, 0.5828
44, 281, sp1-2 ppi1, 0.5906
45, 281, sp1-3 ppi1, 0.5968333
46, 281, sp1-4 ppi1, 0.5838
47, 281, sp1-5 ppi1, 0.5983333
48, 281, Wt, 0.5948333")
for_plot %>%
ggplot()+
geom_line(aes(x = Time, y = Mean, col = Mutant)) +
geom_point(aes(x = Time, y = Mean, col = Mutant)) +
labs(title = "Effective PSII Quantum Yield across SP1 Mutants",
y = "Effective PSII Quantum Yield",
x = "Actinic PPFD") +
theme(plot.title = element_text(hjust = 0.5)) +
theme(legend.text = element_text(face=c("plain", rep("italic",7))))
由 reprex package (v0.3.0)
于 2020-01-01 创建我编写了 ggtext 包来使这些类型的问题更容易解决。它允许您使用 markdown 进行样式设置，即只需将斜体部分用星号括起来。
该软件包目前正在开发中，需要通过远程安装，但很快就会在 CRAN 上发布（spring 2020）。您可能还需要 ggplot2 的最新开发版本，您可以通过 remotes::install_github("tidyverse/ggplot2").
library(tidyverse)
library(ggtext) # remotes::install_github("clauswilke/ggtext")
for_plot <- read_csv(file =
"Row, Time, Mutant, Mean
1, 1, ppi1, 0.8008
2, 1, sp1-1, 0.8038
3, 1, sp1-1 ppi1, 0.8094
4, 1, sp1-2 ppi1, 0.8138
5, 1, sp1-3 ppi1, 0.8066667
6, 1, sp1-4 ppi1, 0.7998
7, 1, sp1-5 ppi1, 0.8026667
8, 1, Wt, 0.8083333
9, 21, ppi1, 0.6806
10, 21, sp1-1, 0.7088
11, 21, sp1-1 ppi1, 0.6982
12, 21, sp1-2 ppi1, 0.7126
13, 21, sp1-3 ppi1, 0.709
14, 21, sp1-4 ppi1, 0.6942
15, 21, sp1-5 ppi1, 0.7096667
16, 21, Wt, 0.7246667
17, 56, ppi1, 0.6652
18, 56, sp1-1, 0.6848
19, 56, sp1-1 ppi1, 0.6816
20, 56, sp1-2 ppi1, 0.6926
21, 56, sp1-3 ppi1, 0.6945
22, 56, sp1-4 ppi1, 0.676
23, 56, sp1-5 ppi1, 0.6931667
24, 56, Wt, 0.6946667
25, 111, ppi1, 0.653
26, 111, sp1-1, 0.6704
27, 111, sp1-1 ppi1, 0.6704
28, 111, sp1-2 ppi1, 0.6756
29, 111, sp1-3 ppi1, 0.679
30, 111, sp1-4 ppi1, 0.664
31, 111, sp1-5 ppi1, 0.6805
32, 111, Wt, 0.677
33, 186, ppi1, 0.6132
34, 186, sp1-1, 0.633
35, 186, sp1-1 ppi1, 0.6298
36, 186, sp1-2 ppi1, 0.6402
37, 186, sp1-3 ppi1, 0.6435
38, 186, sp1-4 ppi1, 0.6278
39, 186, sp1-5 ppi1, 0.6478333
40, 186, Wt, 0.6403333
41, 281, ppi1, 0.5636
42, 281, sp1-1, 0.587
43, 281, sp1-1 ppi1, 0.5828
44, 281, sp1-2 ppi1, 0.5906
45, 281, sp1-3 ppi1, 0.5968333
46, 281, sp1-4 ppi1, 0.5838
47, 281, sp1-5 ppi1, 0.5983333
48, 281, Wt, 0.5948333")
for_plot %>%
ggplot()+
geom_line(aes(x = Time, y = Mean, col = Mutant)) +
geom_point(aes(x = Time, y = Mean, col = Mutant)) +
labs(title = "Effective PSII Quantum Yield across SP1 Mutants",
y = "Effective PSII Quantum Yield",
x = "Actinic PPFD") +
scale_color_hue(
breaks = c("ppi1", "sp1-1", "sp1-1 ppi1", "sp1-2 ppi1",
"sp1-3 ppi1", "sp1-4 ppi1", "sp1-5 ppi1", "Wt"),
labels = c("ppi1", "*sp1-1*", "*sp1-1 ppi1*", "*sp1-2 ppi1*",
"*sp1-3 ppi1*", "*sp1-4 ppi1*", "*sp1-5 ppi1*", "*Wt*")
) +
theme(plot.title = element_text(hjust = 0.5)) +
theme(legend.text = element_markdown())
这也适用于部分文本，例如，如果您希望 SP1 在标题中使用斜体，您可以这样做。
for_plot %>%
ggplot()+
geom_line(aes(x = Time, y = Mean, col = Mutant)) +
geom_point(aes(x = Time, y = Mean, col = Mutant)) +
labs(title = "Effective PSII Quantum Yield across *SP1* Mutants",
y = "Effective PSII Quantum Yield",
x = "Actinic PPFD") +
scale_color_hue(
breaks = c("ppi1", "sp1-1", "sp1-1 ppi1", "sp1-2 ppi1",
"sp1-3 ppi1", "sp1-4 ppi1", "sp1-5 ppi1", "Wt"),
labels = c("ppi1", "*sp1-1*", "*sp1-1 ppi1*", "*sp1-2 ppi1*",
"*sp1-3 ppi1*", "*sp1-4 ppi1*", "*sp1-5 ppi1*", "*Wt*")
) +
theme(plot.title = element_markdown(hjust = 0.5)) +
theme(legend.text = element_markdown())
您可能想尝试真正的 R 图，其函数 IMO 可能不那么令人困惑且更容易学习，并且 肯定 更好地自定义。
有两个步骤，定义标签和颜色，然后绘制图例。
# define labels and colors beforehand
mutants <- sort(unique(edtct3$Mutant)) # unique and alph. sorted mutants
clr <- hcl.colors(8, "Spectral")
op <- par(mar=c(5, 5, 4, 7.5)) # modify margins of plot region (B, L, T, R)
# plot
with(edtct3, plot(x=Time, y=Mean, type="n", ## empty plot: type="n"
main="Effective PSII Quantum Yield across SP1 Mutants",
ylab="Effective PSII Quantum Yield",
xlab="Actinic PPFD"))
# lines and points: loop over the mutants with an `sapply`
# the actual function is `lines()`
sapply(seq(mutants), function(x) ## `seq(mutants)` makes a loop sequence over the mutants
with(edtct3[edtct3$Mutant == mutants[x], ], ## subsetting
lines(x=Time, y=Mean, type="o", pch=16, col=clr[x]))) ## type="o" makes lines and points
# legend
legend(x=20.5, y=1.69, xpd=TRUE, legend=labs, pch=15, col=clr, cex=.9,
text.font=c(1, rep(3, 7))) ## recall the "face" vector from former question
par(op) # reset margins of plot region
产量
数据：
edtc3 <- structure(list(Time = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 6, 6,
6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6,
6, 6, 6, 6, 6, 6, 6, 6, 6, 11, 11, 11, 11, 11, 11, 11, 11, 11,
11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11,
11, 11, 11, 11, 11, 11, 11, 19, 19, 19, 19, 19, 19, 19, 19, 19,
19, 19, 19, 19, 19, 19, 19, 19, 19, 19, 19, 19, 19, 19, 19, 19,
19, 19, 19, 19, 19, 19, 19), Mutant = c("sp2-3 ppi1", "ppi1",
"WT", "sp2-6 ppi1", "sp2-4", "WT", "sp2-3 ppi1", "sp2-8 ppi1",
"sp2 ppi1", "ppi1", "sp2-6 ppi1", "sp2-8 ppi1", "sp2 ppi1", "sp2-6 ppi1",
"sp2-5 ppi1", "WT", "sp2-4", "sp2 ppi1", "sp2-4", "sp2-5 ppi1",
"sp2-5 ppi1", "sp2-4", "sp2 ppi1", "WT", "sp2-6 ppi1", "sp2-8 ppi1",
"sp2-3 ppi1", "sp2-8 ppi1", "ppi1", "ppi1", "sp2-3 ppi1", "sp2-5 ppi1",
"sp2-5 ppi1", "sp2-6 ppi1", "ppi1", "WT", "sp2-8 ppi1", "sp2-8 ppi1",
"sp2-3 ppi1", "sp2 ppi1", "ppi1", "sp2-6 ppi1", "WT", "sp2-8 ppi1",
"WT", "sp2-3 ppi1", "sp2-5 ppi1", "ppi1", "sp2-3 ppi1", "sp2-6 ppi1",
"sp2-5 ppi1", "sp2-3 ppi1", "sp2 ppi1", "sp2-5 ppi1", "sp2 ppi1",
"ppi1", "sp2-4", "sp2-4", "sp2-4", "sp2-4", "WT", "sp2 ppi1",
"sp2-6 ppi1", "sp2-8 ppi1", "sp2 ppi1", "sp2-4", "sp2-4", "sp2-8 ppi1",
"sp2-4", "sp2-3 ppi1", "sp2-8 ppi1", "sp2-4", "WT", "sp2 ppi1",
"ppi1", "sp2 ppi1", "sp2-5 ppi1", "WT", "sp2-3 ppi1", "sp2-3 ppi1",
"sp2-3 ppi1", "sp2-6 ppi1", "sp2-5 ppi1", "ppi1", "ppi1", "sp2-8 ppi1",
"sp2 ppi1", "WT", "WT", "sp2-6 ppi1", "sp2-5 ppi1", "ppi1", "sp2-5 ppi1",
"sp2-6 ppi1", "sp2-6 ppi1", "sp2-8 ppi1", "sp2-3 ppi1", "sp2 ppi1",
"sp2-5 ppi1", "sp2-6 ppi1", "sp2-3 ppi1", "sp2-4", "sp2-4", "sp2-6 ppi1",
"sp2-5 ppi1", "sp2-4", "sp2-8 ppi1", "ppi1", "ppi1", "WT", "sp2 ppi1",
"sp2 ppi1", "ppi1", "sp2-6 ppi1", "ppi1", "sp2-4", "sp2-5 ppi1",
"sp2-3 ppi1", "sp2-6 ppi1", "sp2-5 ppi1", "sp2-8 ppi1", "WT",
"sp2 ppi1", "sp2-8 ppi1", "sp2-3 ppi1", "sp2-8 ppi1", "WT", "WT"
), Mean = c(0.91, 0.59, 1.14, 0.74, 1.08, 1.65, 0.77, 1.34, 0.65,
0.61, 0.86, 1.3, 0.82, 0.84, 0.97, 1.29, 1.15, 0.84, 1, 1.04,
0.78, 1.01, 1.02, 1.33, 0.88, 1.25, 0.78, 1.25, 0.8, 0.67, 0.85,
0.9, 1.04, 0.84, 0.67, 1.65, 1.25, 1.34, 0.77, 1.02, 0.59, 0.88,
1.33, 1.3, 1.29, 0.91, 0.78, 0.8, 0.78, 0.86, 0.9, 0.85, 0.84,
0.97, 0.65, 0.61, 1.01, 1.08, 1.15, 1, 1.14, 0.82, 0.74, 1.25,
1.02, 1.08, 1.15, 1.25, 1.01, 0.85, 1.25, 1, 1.29, 0.84, 0.59,
0.82, 1.04, 1.33, 0.77, 0.91, 0.78, 0.86, 0.78, 0.67, 0.61, 1.34,
0.65, 1.65, 1.14, 0.84, 0.9, 0.8, 0.97, 0.74, 0.88, 1.3, 0.78,
0.84, 1.04, 0.88, 0.91, 1.01, 1.15, 0.74, 0.78, 1, 1.3, 0.67,
0.8, 1.14, 1.02, 0.82, 0.59, 0.84, 0.61, 1.08, 0.9, 0.77, 0.86,
0.97, 1.34, 1.29, 0.65, 1.25, 0.85, 1.25, 1.65, 1.33)), row.names = c("17",
"5", "1", "25", "10", "4", "18", "32", "15", "7", "27", "31",
"14", "26", "24", "3", "9", "16", "11", "22", "21", "12", "13",
"2", "28", "29", "19", "30", "6", "8", "20", "23", "221", "261",
"81", "41", "291", "321", "181", "131", "51", "281", "210", "311",
"33", "171", "211", "61", "191", "271", "231", "201", "161",
"241", "151", "71", "121", "101", "91", "111", "110", "141",
"251", "301", "132", "102", "92", "292", "122", "202", "302",
"112", "34", "162", "52", "142", "222", "212", "182", "172",
"192", "272", "213", "82", "72", "322", "152", "42", "113", "262",
"232", "62", "242", "252", "282", "312", "193", "163", "223",
"283", "173", "123", "93", "253", "214", "114", "313", "83",
"63", "115", "133", "143", "53", "263", "73", "103", "233", "183",
"273", "243", "323", "35", "153", "303", "203", "293", "43",
"215"), class = "data.frame")
使用（非常温和的）修改版本
使用此函数，您可以在对 scale.
library(tidyverse)
toexpr <- function(x, plain = NULL) {
getfun <- function(x) {
ifelse(x == plain, "plain", "italic")
}
as.expression(unname(Map(function(f,v) substitute(f(v), list(f=as.name(f), v=as.character(v))), getfun(x), x)))
}
ggplot(for_plot)+
geom_line(aes(x = Time, y = Mean, col = Mutant)) +
geom_point(aes(x = Time, y = Mean, col = Mutant)) +
scale_color_discrete(labels = toexpr(for_plot$Mutant, plain = 'Wt'))
由 reprex package (v0.3.0)
于 2020 年 1 月 2 日创建