ggplot2中嵌套面中的希腊字母
我有一个巨大的数据集，我需要在x轴（alpha和deid的复制品）和y轴（beta）中具有一个嵌套面的面中进行绘图。
fen_ale_all_rep$alpha <- factor(
fen_ale_all_rep$alpha,
levels = c("alpha 0.1", "alpha 0.2", "alpha 0.4", "alpha 0.8", "alpha 1.6"),
labels = c(
"alpha '0.1'",
"alpha '0.2'",
"alpha '0.4'",
"alpha '0.8'",
"alpha '1.6'"
)
)
fen_ale_rep5$beta <- factor(
fen_ale_rep5$beta,
levels = c(
"beta 0.05",
"beta 0.1",
"beta 0.2",
"beta 0.4",
"beta 0.8",
"beta 1.6",
"beta 3.2",
"beta 6.4",
"beta 12.8",
"beta 25.6",
"beta 51.2",
"beta 102.4"
),
labels = c(
"beta 0.05",
"beta 0.1",
"beta 0.2",
"beta 0.4",
"beta 0.8",
"beta 1.6",
"beta 3.2",
"beta 6.4",
"beta 12.8",
"beta 25.6",
"beta 51.2",
"beta 102.4"
)
)
结构：
tbl <- structure(list(FEN = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L), .Label = c("Plants", "Insects"), class = "factor"),
NSEL = 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, 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), rep = c("rep 1", "rep 1", "rep 1", "rep 1",
"rep 1", "rep 1", "rep 1", "rep 1", "rep 1", "rep 1", "rep 1",
"rep 1", "rep 1", "rep 1", "rep 1", "rep 1", "rep 1", "rep 1",
"rep 1", "rep 1", "rep 1", "rep 1", "rep 1", "rep 1", "rep 1",
"rep 1", "rep 1", "rep 1", "rep 1", "rep 1", "rep 1", "rep 1",
"rep 1", "rep 1", "rep 1", "rep 1", "rep 1", "rep 1", "rep 1",
"rep 1", "rep 1", "rep 1", "rep 1", "rep 1", "rep 1", "rep 1",
"rep 1", "rep 1", "rep 1", "rep 1", "rep 1", "rep 1", "rep 1",
"rep 1", "rep 1", "rep 1", "rep 1", "rep 1", "rep 1", "rep 1"
), alpha = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L), .Label = c("alpha 0.1", "alpha 0.2",
"alpha 0.4", "alpha 0.8", "alpha 1.6"), class = "factor"),
beta = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 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), .Label = c("beta 0.05", "beta 0.1",
"beta 0.2", "beta 0.4", "beta 0.8", "beta 1.6", "beta 3.2",
"beta 6.4", "beta 12.8", "beta 25.6", "beta 51.2", "beta 102.4"
), class = "factor"), TEMPO = c(1L, 200L, 400L, 600L, 800L,
1000L, 1200L, 1400L, 1600L, 1800L, 2000L, 2200L, 2400L, 2600L,
2800L, 3000L, 3200L, 3400L, 3600L, 3800L, 4000L, 4200L, 4400L,
4600L, 4800L, 5000L, 5200L, 5400L, 5600L, 5800L, 6000L, 6200L,
6400L, 6600L, 6800L, 7000L, 7200L, 7400L, 7600L, 7800L, 8000L,
8200L, 8400L, 8600L, 8800L, 9000L, 9200L, 9400L, 9600L, 9800L,
10000L, 1L, 200L, 400L, 600L, 800L, 1000L, 1200L, 1400L,
1600L), ab = c("0.1 0.05", "0.1 0.05", "0.1 0.05", "0.1 0.05",
"0.1 0.05", "0.1 0.05", "0.1 0.05", "0.1 0.05", "0.1 0.05",
"0.1 0.05", "0.1 0.05", "0.1 0.05", "0.1 0.05", "0.1 0.05",
"0.1 0.05", "0.1 0.05", "0.1 0.05", "0.1 0.05", "0.1 0.05",
"0.1 0.05", "0.1 0.05", "0.1 0.05", "0.1 0.05", "0.1 0.05",
"0.1 0.05", "0.1 0.05", "0.1 0.05", "0.1 0.05", "0.1 0.05",
"0.1 0.05", "0.1 0.05", "0.1 0.05", "0.1 0.05", "0.1 0.05",
"0.1 0.05", "0.1 0.05", "0.1 0.05", "0.1 0.05", "0.1 0.05",
"0.1 0.05", "0.1 0.05", "0.1 0.05", "0.1 0.05", "0.1 0.05",
"0.1 0.05", "0.1 0.05", "0.1 0.05", "0.1 0.05", "0.1 0.05",
"0.1 0.05", "0.1 0.05", "0.1 0.1", "0.1 0.1", "0.1 0.1",
"0.1 0.1", "0.1 0.1", "0.1 0.1", "0.1 0.1", "0.1 0.1", "0.1 0.1"
), especie = 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", "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"), trait = c(0.59532188, 0.63023233, 0.59210289,
0.58660778, 0.55932657, 0.57032034, 0.56379332, 0.61973847,
0.61705717, 0.62310601, 0.61690676, 0.6508817, 0.64581712,
0.5890861, 0.66424559, 0.64007846, 0.52734623, 0.65276626,
0.57025516, 0.59734711, 0.59672837, 0.57971204, 0.51274562,
0.60679023, 0.56463537, 0.64716034, 0.60257023, 0.68582648,
0.62075915, 0.46707366, 0.65330306, 0.59301249, 0.70620201,
0.5260134, 0.51619464, 0.65620395, 0.48348558, 0.62189428,
0.60360017, 0.55274833, 0.56492948, 0.61039593, 0.75225962,
0.54349533, 0.47189362, 0.52454647, 0.56282583, 0.63985652,
0.58380379, 0.59214658, 0.73188778, 0.62808414, 0.59229323,
0.6978987, 0.61346245, 0.49995094, 0.4661158, 0.57436886,
0.58524132, 0.60717574)), row.names = c(NA, 60L), class = "data.frame")
我可以制作这个情节：
但是，它不显示复制ID。测试版不遵循新月顺序。
我想要类似的东西
或一个具有复制和de列且具有每个alpha值（0.1,0.2，....）的单一构面
for(i in 1:10) {
grid1 <- print(
ggplot(
fen_ale_all_rep,
aes(
x = TEMPO,
y = trait,
group = interaction(FEN, ab, especie, rep),
colour = FEN
)
) +
geom_line() +
labs(x = "Time",
y = "Mean phenotypes") +
scale_color_viridis(discrete=TRUE,
name = NULL
) +
theme_pubclean() + theme(
axis.text.x = element_text(
size = 15,
angle = 0,
vjust = 0.3
),
axis.text.y = element_text(size = 15),
plot.title = element_text(size = 15),
legend.text = element_text(size = 15),
axis.title.x = element_text(size = 15),
axis.title.y = element_text(size = 15),
strip.text.x = element_text(size = 15),
strip.text.y = element_text(size = 15),
plot.caption = element_text(size=15),
panel.border = element_blank(),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
axis.line = element_line(colour = "black"),
axis.ticks = element_blank(),
legend.position = "top"
) +
facet_grid_paginate(
beta ~ alpha+rep,
ncol = 5,
nrow = 6,
page = i, labeller = label_bquote(beta == .(beta), alpha == .(alpha)))))
}
我该如何实现？ 提前致谢！对我的英语感到抱歉：）
0 个答案:
没有答案
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