如何在 X 轴上创建具有多个标签的图，以前的代码建议似乎不起作用
How to create plot with multiple labels on X axis, previous code suggestion doesn't seem to work
我有一些数据可以测量具有三个不同变量（暴露、季节和地点）的物种的迁移率。我想创建一个情节，其中季节和曝光列在 X 轴上，网站在图例中创建。我已经在 Excel 中很容易地完成了这个，并且想在 R 中复制相同的类型。目前，我正在使用一段代码，它似乎适用于另一个有类似问题的用户，但是这似乎不适用于我的？
脚本：
dput(Data2)
structure(list(Season = structure(c(2L, 2L, 2L, 3L, 3L, 3L, 1L,
1L, 1L, 4L, 4L, 4L, 2L, 2L, 2L, 3L, 3L, 3L, 1L, 1L, 1L, 4L, 4L,
4L), .Label = c("Autumn", "Spring", "Summer ", "Winter"), class = "factor"),
Exposure = structure(c(1L, 3L, 2L, 4L, 3L, 2L, 4L, 3L, 2L,
4L, 3L, 2L, 1L, 3L, 2L, 4L, 3L, 2L, 4L, 3L, 2L, 4L, 3L, 2L
), .Label = c(" Sheltered", "Exposed", "Moderately Exposed",
"Sheltered"), class = "factor"), Average = c(1L, 2L, 4L,
3L, 4L, 2L, 2L, 4L, 2L, 4L, 3L, 2L, 2L, 5L, 4L, 3L, 2L, 1L,
1L, 1L, 2L, 4L, 2L, 2L), Site = c(1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L), SEM = c(0.5, 0.1, 0.4, 0.5, 1, 0.5, 0.5, 0.5,
0.5, 0.5, 0.2, 0.5, 0.5, 0.1, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5,
0.3, 0.2, 0.5, 0.5)), class = "data.frame", row.names = c(NA,
-24L))
`setwd("C:/Users/phl5/Documents/PippaPhD")
getwd()
read.csv("Graphed_Data.csv")
Data2<-read.csv("Graphed_Data.csv")
library(ggplot2)
library(gtable)
library(grid)
dodge<- position_dodge(width=0.9)
ggplot(Data2, aes(x = interaction(Exposure, Season), y = Average, fill
= factor(Site))) +
geom_bar(stat = "identity", position = position_dodge()) +
geom_errorbar(aes(ymax = Average + SEM, ymin = Average - SEM), position
= dodge, width = 0.2)
g1<- ggplot(data = Data2, aes(x = interaction(Exposure, Season), y =
Average, fill = factor(Site))) +
geom_bar(stat = "identity", position = position_dodge()) +
geom_errorbar(aes(ymax = Average + SEM, ymin = Average - SEM), position
= dodge, width = 0.2) +
coord_cartesian(ylim = c(0, 12.5))+
annotate("text", x = 1:12, y = 400,
label = rep(c("Exposed", "Moderately Exposed", "Sheltered"),4)) +
annotate("text", c(0.5, 1.5, 2.0, 2.5), y = -800, label = c("Spring",
"Summer", "Autumn", "Winter"))+
theme_classic()+
theme(plot.margin = unit(c(1,1,1,1), "lines"),
axis.title.x = element_blank(),
axis.text.x = element_blank())
g2 <- ggplot_gtable(ggplot_build(g1))
g2$layout$clip[g2$layout$name == "panel"] <- "off"
grid.draw(g2)`
任何人都可以看看这是否是我正在使用的代码中的一个明显问题，或者这是否是我可以使用的不同脚本？
代码：
Output get from current code, with the problem of no x axis codes appearing at all
This is the kind of output I would want, and that I can create in Excel
我是 R 的初学者，但如有任何帮助，我们将不胜感激。
由于您没有提供与您的代码一起使用的样本数据，我试图找出您与预先存在的数据有关的问题 (cars)。
查看您想要的输出后，我在 r:
中创建了一个条形图
library(ggplot2)
ggplot(data = cars, aes(x = speed, y = dist)) +
geom_bar(stat="identity", position = "dodge")
您的代码存在手动覆盖 x 轴为空的问题，如下所示：
ggplot(data = cars, aes(x = speed, y = dist)) +
geom_bar(stat="identity", show.legend = F, position = "dodge") +
theme(
axis.title.x = element_blank(),
axis.text.x = element_blank())
如您所见，当您控制 axis.title / axis.text
时，x 轴及其标签消失
编辑 2：
对于OP在评论中的第二个问题：
- 不需要加一个
geom_hline()来显示轴，只需要在theme()和panel.spacing.x=unit(0, "lines")中加axis.line，使其跨面连续
gg <- ggplot(aes(x=as.factor(Site), y=Average, fill=as.factor(Site)), data=data)
gg <- gg + geom_bar(stat = 'identity')
gg <- gg + scale_fill_discrete(guide_legend(title = 'Site')) # just to get 'site' instead of 'as.factor(Site)' as legend title
# gg <- gg + scale_fill_manual(values=c('black', 'grey85'), guide_legend(title = 'Site')) # to get bars in black and grey instead of ggplot's default colors
# gg <- gg + theme_classic() # get white background and black axis.line for x- and y-axis
gg <- gg + geom_errorbar(aes(ymin=Average-SEM, ymax=Average+SEM), width=.3)
gg <- gg + facet_wrap(~Season*Exposure, strip.position=c('bottom'), nrow=1, drop=F)
gg <- gg + scale_y_continuous(expand = expand_scale(mult = c(0, .05))) # remove space below zero
gg <- gg + theme(axis.text.x = element_blank(),
axis.ticks.x = element_blank(),
axis.title.x = element_blank(),
axis.line = element_line(color='black'),
strip.placement = 'outside', # place x-axis above (factor-label-) strips
panel.spacing.x=unit(0, "lines"), # remove space between facets (for continuous x-axis)
panel.grid.major.x = element_blank(), # remove vertical grid lines
# panel.grid = element_blank(), # remove all grid lines
# panel.background = element_rect(fill='white'), # choose background color for plot area
strip.background = element_rect(fill='white', color='white') # choose background for factor labels, color just matters for theme_classic()
)
- 要将曝光标签放置在分面条中的季节标签上方，您可以更改覆盖在每个条上的 gtable
# facet factor levels
season.levels <- levels(data$Season)
exposure.levels <- levels(data$Exposure)
# convert to gtable
g <- ggplotGrob(gg)
# find the grobs of the strips in the original plot
grob.numbers <- grep("strip-b", g$layout$name)
# filter strips from layout
b.strips <- gtable_filter(g, "strip-b", trim = FALSE)
# b.strips$layout shows the strips position in the cell grid of the plot
# b.strips$layout
season.left.panels <- seq(1, by=length(levels(data$Exposure)), length.out = length(season.levels))
season.right.panels <- seq(length(exposure.levels), by=length(exposure.levels), length.out = length(season.levels))
left <- b.strips$layout$l[season.left.panels]
right <- b.strips$layout$r[season.right.panels]
top <- b.strips$layout$t[1]
bottom <- b.strips$layout$b[1]
# create empty matrix as basis to overly new gtable on the strip
mat <- matrix(vector("list", length = 10), nrow = 2)
mat[] <- list(zeroGrob())
# add new gtable matrix above each strip
for (i in 1:length(season.levels)) {
res <- gtable_matrix("season.strip", mat, unit(c(1, 0, 1, 0, 1), "null"), unit(c(1, 1), "null"))
season.left <- season.left.panels[i]
# place season labels below exposure labels in row 2 of the overlayed gtable for strips
res <- gtable_add_grob(res, g$grobs[[grob.numbers[season.left]]]$grobs[[1]], 2, 1, 2, 5)
# move exposure labels to row 1 of the overlayed gtable for strips
for (j in 0:2) {
exposure.x <- season.left+j
res$grobs[[c(1, 5, 9)[j+1]]] <- g$grobs[[grob.numbers[exposure.x]]]$grobs[[2]]
}
new.grob.name <- paste0(levels(data$Season)[i], '-strip')
g <- gtable_add_grob(g, res, t = top, l = left[i], b = top, r = right[i], name = c(new.grob.name))
new.grob.no <- grep(new.grob.name, g$layout$name)[1]
g$grobs[[new.grob.no]]$grobs[[nrow(g$grobs[[new.grob.no]]$layout)]]$children[[2]]$children[[1]]$gp <- gpar(fontface='bold')
}
grid.newpage()
grid.draw(g)
结果如下所示：
- 要像示例图片中一样获得黑色和灰色的条形图，请像这样更改 ggplot：
gg <- ggplot(aes(x=as.factor(Site), y=Average, fill=as.factor(Site)), data=data)
gg <- gg + geom_bar(stat = 'identity')
# gg <- gg + scale_fill_discrete(guide_legend(title = 'Site')) # just to get 'site' instead of 'as.factor(Site)' as legend title
gg <- gg + scale_fill_manual(values=c('black', 'grey85'), guide_legend(title = 'Site')) # to get bars in black and grey instead of ggplot's default colors
gg <- gg + theme_classic() # get white background and black axis.line for x- and y-axis
gg <- gg + geom_errorbar(aes(ymin=Average-SEM, ymax=Average+SEM), width=.3)
gg <- gg + facet_wrap(~Season*Exposure, strip.position=c('bottom'), nrow=1, drop=F)
gg <- gg + scale_y_continuous(expand = expand_scale(mult = c(0, .05))) # remove space below zero
gg <- gg + theme(axis.text.x = element_blank(),
axis.ticks.x = element_blank(),
axis.title.x = element_blank(),
axis.line = element_line(color='black'),
strip.placement = 'outside', # place x-axis above (factor-label-) strips
panel.spacing.x=unit(0, "lines"), # remove space between facets (for continuous x-axis)
panel.grid.major.x = element_blank(), # remove vertical grid lines
# panel.grid = element_blank(), # remove all grid lines
# panel.background = element_rect(fill='white'), # choose background color for plot area
strip.background = element_rect(fill='white', color='white') # choose background for factor labels, color just matters for theme_classic()
)
结果应该是这样的：
编辑：
对于OP在评论中的问题：
- 删除网格线可以使用
ggplot 的 theme():
gg <- ggplot(aes(x=as.factor(Site), y=Average, fill=as.factor(Site)), data=data)
gg <- gg + geom_bar(stat = 'identity')
gg <- gg + geom_errorbar(aes(ymin=Average-SEM, ymax=Average+SEM), width=.3)
gg <- gg + facet_wrap(~Season*Exposure, strip.position=c('bottom'), nrow=1, drop=F)
gg <- gg + scale_fill_discrete(guide_legend(title = 'Site'))
gg <- gg + theme(axis.text.x = element_blank(),
axis.ticks.x = element_blank(),
axis.title.x = element_blank(),
panel.grid.major.x = element_blank(), # remove vertical grid lines
# panel.grid = element_blank(), # remove al grid lines
# panel.background = element_rect(fill='white'), # choose background color for plot area
strip.background = element_rect(fill='white') # choose background for factor labels
)
- 每个季节只有一个标签有点棘手。您需要编辑
ggplot 的 gtable。
这样做的一种方法是：
# facet factor levels
season.levels <- levels(data$Season)
exposure.levels <- levels(data$Exposure)
# convert to gtable
g <- ggplotGrob(gg)
# find the grobs of the strips in the original plot
grob.numbers <- grep("strip-b", g$layout$name)
# filter strips from layout
b.strips <- gtable_filter(g, "strip-b", trim = FALSE)
# b.strips$layout shows the strips position in the cell grid of the plot
b.strips$layout
season.left.panels <- seq(1, by=length(levels(data$Exposure)), length.out = length(season.levels))
season.right.panels <- seq(length(exposure.levels), by=length(exposure.levels), length.out = length(season.levels))
left <- b.strips$layout$l[season.left.panels]
right <- b.strips$layout$r[season.right.panels]
top <- b.strips$layout$t[1]
bottom <- b.strips$layout$b[1]
# create empty matrix as basis to overly new gtable on the strip
mat <- matrix(vector("list", length = 10), nrow = 2)
mat[] <- list(zeroGrob())
# add new gtable matrix above each strip
for (i in 1:length(season.levels)) {
res <- gtable_matrix("season.strip", mat, unit(c(1, 0, 1, 0, 1), "null"), unit(c(1, 1), "null"))
res <- gtable_add_grob(res, g$grobs[[grob.numbers[season.left.panels[i]]]]$grobs[[1]], 1, 1, 1, 5)
new.grob.name <- paste0(levels(data$Season)[i], '-strip')
g <- gtable_add_grob(g, res, t = top, l = left[i], b = top, r = right[i], name = c(new.grob.name))
new.grob.no <- grep(new.grob.name, g$layout$name)
g$grobs[[new.grob.no]]$grobs[[nrow(g$grobs[[new.grob.no]]$layout)]]$children[[2]]$children[[1]]$gp <- gpar(fontface='bold')
}
grid.newpage()
grid.draw(g)
原回答
我认为您正在寻找的东西可以 – 使用 ggplot() – 使用刻面最好地实现。
data <- expand.grid(c('Spring', 'Summer', 'Autumn', 'Winter'), c('Sheltered', 'Moderately exposed', 'Exposed'), c(1, 2))
names(data) <- c('Season', 'Exposure', 'Site')
# adding some arbitrary values
set.seed(42)
data$Average <- sample(c(rep(3, 3), rep(2, 2), rep(1, 2), rep(NA, 17)))
data$SEM <- NA
SEM <- sample(c(rep(0.5, 3), rep(0.3, 2), rep(.1, 2)))
data$SEM[which(!is.na(data$Average))] <- SEM
gg <- ggplot(aes(x=as.factor(Site), y=Average, fill=as.factor(Site)), data=data)
gg <- gg + geom_bar(stat = 'identity')
gg <- gg + geom_errorbar(aes(ymin=Average-SEM, ymax=Average+SEM), width=.3)
gg <- gg + facet_wrap(~Season*Exposure, strip.position=c('bottom'), nrow=1, drop=F)
gg <- gg + scale_fill_discrete(guide_legend(title = 'Site'))
gg <- gg + theme(axis.text.x = element_blank(),
axis.ticks.x = element_blank(),
axis.title.x = element_blank())
print(gg)
我有一些数据可以测量具有三个不同变量（暴露、季节和地点）的物种的迁移率。我想创建一个情节，其中季节和曝光列在 X 轴上，网站在图例中创建。我已经在 Excel 中很容易地完成了这个，并且想在 R 中复制相同的类型。目前，我正在使用一段代码，它似乎适用于另一个有类似问题的用户，但是这似乎不适用于我的？
脚本：
dput(Data2)
structure(list(Season = structure(c(2L, 2L, 2L, 3L, 3L, 3L, 1L,
1L, 1L, 4L, 4L, 4L, 2L, 2L, 2L, 3L, 3L, 3L, 1L, 1L, 1L, 4L, 4L,
4L), .Label = c("Autumn", "Spring", "Summer ", "Winter"), class = "factor"),
Exposure = structure(c(1L, 3L, 2L, 4L, 3L, 2L, 4L, 3L, 2L,
4L, 3L, 2L, 1L, 3L, 2L, 4L, 3L, 2L, 4L, 3L, 2L, 4L, 3L, 2L
), .Label = c(" Sheltered", "Exposed", "Moderately Exposed",
"Sheltered"), class = "factor"), Average = c(1L, 2L, 4L,
3L, 4L, 2L, 2L, 4L, 2L, 4L, 3L, 2L, 2L, 5L, 4L, 3L, 2L, 1L,
1L, 1L, 2L, 4L, 2L, 2L), Site = c(1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L), SEM = c(0.5, 0.1, 0.4, 0.5, 1, 0.5, 0.5, 0.5,
0.5, 0.5, 0.2, 0.5, 0.5, 0.1, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5,
0.3, 0.2, 0.5, 0.5)), class = "data.frame", row.names = c(NA,
-24L))
`setwd("C:/Users/phl5/Documents/PippaPhD")
getwd()
read.csv("Graphed_Data.csv")
Data2<-read.csv("Graphed_Data.csv")
library(ggplot2)
library(gtable)
library(grid)
dodge<- position_dodge(width=0.9)
ggplot(Data2, aes(x = interaction(Exposure, Season), y = Average, fill
= factor(Site))) +
geom_bar(stat = "identity", position = position_dodge()) +
geom_errorbar(aes(ymax = Average + SEM, ymin = Average - SEM), position
= dodge, width = 0.2)
g1<- ggplot(data = Data2, aes(x = interaction(Exposure, Season), y =
Average, fill = factor(Site))) +
geom_bar(stat = "identity", position = position_dodge()) +
geom_errorbar(aes(ymax = Average + SEM, ymin = Average - SEM), position
= dodge, width = 0.2) +
coord_cartesian(ylim = c(0, 12.5))+
annotate("text", x = 1:12, y = 400,
label = rep(c("Exposed", "Moderately Exposed", "Sheltered"),4)) +
annotate("text", c(0.5, 1.5, 2.0, 2.5), y = -800, label = c("Spring",
"Summer", "Autumn", "Winter"))+
theme_classic()+
theme(plot.margin = unit(c(1,1,1,1), "lines"),
axis.title.x = element_blank(),
axis.text.x = element_blank())
g2 <- ggplot_gtable(ggplot_build(g1))
g2$layout$clip[g2$layout$name == "panel"] <- "off"
grid.draw(g2)`
任何人都可以看看这是否是我正在使用的代码中的一个明显问题，或者这是否是我可以使用的不同脚本？
代码： Output get from current code, with the problem of no x axis codes appearing at all
This is the kind of output I would want, and that I can create in Excel
我是 R 的初学者，但如有任何帮助，我们将不胜感激。
由于您没有提供与您的代码一起使用的样本数据，我试图找出您与预先存在的数据有关的问题 (cars)。
查看您想要的输出后，我在 r:
library(ggplot2)
ggplot(data = cars, aes(x = speed, y = dist)) +
geom_bar(stat="identity", position = "dodge")
您的代码存在手动覆盖 x 轴为空的问题，如下所示：
ggplot(data = cars, aes(x = speed, y = dist)) +
geom_bar(stat="identity", show.legend = F, position = "dodge") +
theme(
axis.title.x = element_blank(),
axis.text.x = element_blank())
如您所见，当您控制 axis.title / axis.text
编辑 2：
对于OP在评论中的第二个问题：
- 不需要加一个
geom_hline()来显示轴，只需要在theme()和panel.spacing.x=unit(0, "lines")中加axis.line，使其跨面连续
gg <- ggplot(aes(x=as.factor(Site), y=Average, fill=as.factor(Site)), data=data)
gg <- gg + geom_bar(stat = 'identity')
gg <- gg + scale_fill_discrete(guide_legend(title = 'Site')) # just to get 'site' instead of 'as.factor(Site)' as legend title
# gg <- gg + scale_fill_manual(values=c('black', 'grey85'), guide_legend(title = 'Site')) # to get bars in black and grey instead of ggplot's default colors
# gg <- gg + theme_classic() # get white background and black axis.line for x- and y-axis
gg <- gg + geom_errorbar(aes(ymin=Average-SEM, ymax=Average+SEM), width=.3)
gg <- gg + facet_wrap(~Season*Exposure, strip.position=c('bottom'), nrow=1, drop=F)
gg <- gg + scale_y_continuous(expand = expand_scale(mult = c(0, .05))) # remove space below zero
gg <- gg + theme(axis.text.x = element_blank(),
axis.ticks.x = element_blank(),
axis.title.x = element_blank(),
axis.line = element_line(color='black'),
strip.placement = 'outside', # place x-axis above (factor-label-) strips
panel.spacing.x=unit(0, "lines"), # remove space between facets (for continuous x-axis)
panel.grid.major.x = element_blank(), # remove vertical grid lines
# panel.grid = element_blank(), # remove all grid lines
# panel.background = element_rect(fill='white'), # choose background color for plot area
strip.background = element_rect(fill='white', color='white') # choose background for factor labels, color just matters for theme_classic()
)
- 要将曝光标签放置在分面条中的季节标签上方，您可以更改覆盖在每个条上的 gtable
# facet factor levels
season.levels <- levels(data$Season)
exposure.levels <- levels(data$Exposure)
# convert to gtable
g <- ggplotGrob(gg)
# find the grobs of the strips in the original plot
grob.numbers <- grep("strip-b", g$layout$name)
# filter strips from layout
b.strips <- gtable_filter(g, "strip-b", trim = FALSE)
# b.strips$layout shows the strips position in the cell grid of the plot
# b.strips$layout
season.left.panels <- seq(1, by=length(levels(data$Exposure)), length.out = length(season.levels))
season.right.panels <- seq(length(exposure.levels), by=length(exposure.levels), length.out = length(season.levels))
left <- b.strips$layout$l[season.left.panels]
right <- b.strips$layout$r[season.right.panels]
top <- b.strips$layout$t[1]
bottom <- b.strips$layout$b[1]
# create empty matrix as basis to overly new gtable on the strip
mat <- matrix(vector("list", length = 10), nrow = 2)
mat[] <- list(zeroGrob())
# add new gtable matrix above each strip
for (i in 1:length(season.levels)) {
res <- gtable_matrix("season.strip", mat, unit(c(1, 0, 1, 0, 1), "null"), unit(c(1, 1), "null"))
season.left <- season.left.panels[i]
# place season labels below exposure labels in row 2 of the overlayed gtable for strips
res <- gtable_add_grob(res, g$grobs[[grob.numbers[season.left]]]$grobs[[1]], 2, 1, 2, 5)
# move exposure labels to row 1 of the overlayed gtable for strips
for (j in 0:2) {
exposure.x <- season.left+j
res$grobs[[c(1, 5, 9)[j+1]]] <- g$grobs[[grob.numbers[exposure.x]]]$grobs[[2]]
}
new.grob.name <- paste0(levels(data$Season)[i], '-strip')
g <- gtable_add_grob(g, res, t = top, l = left[i], b = top, r = right[i], name = c(new.grob.name))
new.grob.no <- grep(new.grob.name, g$layout$name)[1]
g$grobs[[new.grob.no]]$grobs[[nrow(g$grobs[[new.grob.no]]$layout)]]$children[[2]]$children[[1]]$gp <- gpar(fontface='bold')
}
grid.newpage()
grid.draw(g)
结果如下所示：
- 要像示例图片中一样获得黑色和灰色的条形图，请像这样更改 ggplot：
gg <- ggplot(aes(x=as.factor(Site), y=Average, fill=as.factor(Site)), data=data)
gg <- gg + geom_bar(stat = 'identity')
# gg <- gg + scale_fill_discrete(guide_legend(title = 'Site')) # just to get 'site' instead of 'as.factor(Site)' as legend title
gg <- gg + scale_fill_manual(values=c('black', 'grey85'), guide_legend(title = 'Site')) # to get bars in black and grey instead of ggplot's default colors
gg <- gg + theme_classic() # get white background and black axis.line for x- and y-axis
gg <- gg + geom_errorbar(aes(ymin=Average-SEM, ymax=Average+SEM), width=.3)
gg <- gg + facet_wrap(~Season*Exposure, strip.position=c('bottom'), nrow=1, drop=F)
gg <- gg + scale_y_continuous(expand = expand_scale(mult = c(0, .05))) # remove space below zero
gg <- gg + theme(axis.text.x = element_blank(),
axis.ticks.x = element_blank(),
axis.title.x = element_blank(),
axis.line = element_line(color='black'),
strip.placement = 'outside', # place x-axis above (factor-label-) strips
panel.spacing.x=unit(0, "lines"), # remove space between facets (for continuous x-axis)
panel.grid.major.x = element_blank(), # remove vertical grid lines
# panel.grid = element_blank(), # remove all grid lines
# panel.background = element_rect(fill='white'), # choose background color for plot area
strip.background = element_rect(fill='white', color='white') # choose background for factor labels, color just matters for theme_classic()
)
结果应该是这样的：
对于OP在评论中的问题：
- 删除网格线可以使用
ggplot的theme():
gg <- ggplot(aes(x=as.factor(Site), y=Average, fill=as.factor(Site)), data=data)
gg <- gg + geom_bar(stat = 'identity')
gg <- gg + geom_errorbar(aes(ymin=Average-SEM, ymax=Average+SEM), width=.3)
gg <- gg + facet_wrap(~Season*Exposure, strip.position=c('bottom'), nrow=1, drop=F)
gg <- gg + scale_fill_discrete(guide_legend(title = 'Site'))
gg <- gg + theme(axis.text.x = element_blank(),
axis.ticks.x = element_blank(),
axis.title.x = element_blank(),
panel.grid.major.x = element_blank(), # remove vertical grid lines
# panel.grid = element_blank(), # remove al grid lines
# panel.background = element_rect(fill='white'), # choose background color for plot area
strip.background = element_rect(fill='white') # choose background for factor labels
)
- 每个季节只有一个标签有点棘手。您需要编辑
ggplot的gtable。 这样做的一种方法是：
# facet factor levels
season.levels <- levels(data$Season)
exposure.levels <- levels(data$Exposure)
# convert to gtable
g <- ggplotGrob(gg)
# find the grobs of the strips in the original plot
grob.numbers <- grep("strip-b", g$layout$name)
# filter strips from layout
b.strips <- gtable_filter(g, "strip-b", trim = FALSE)
# b.strips$layout shows the strips position in the cell grid of the plot
b.strips$layout
season.left.panels <- seq(1, by=length(levels(data$Exposure)), length.out = length(season.levels))
season.right.panels <- seq(length(exposure.levels), by=length(exposure.levels), length.out = length(season.levels))
left <- b.strips$layout$l[season.left.panels]
right <- b.strips$layout$r[season.right.panels]
top <- b.strips$layout$t[1]
bottom <- b.strips$layout$b[1]
# create empty matrix as basis to overly new gtable on the strip
mat <- matrix(vector("list", length = 10), nrow = 2)
mat[] <- list(zeroGrob())
# add new gtable matrix above each strip
for (i in 1:length(season.levels)) {
res <- gtable_matrix("season.strip", mat, unit(c(1, 0, 1, 0, 1), "null"), unit(c(1, 1), "null"))
res <- gtable_add_grob(res, g$grobs[[grob.numbers[season.left.panels[i]]]]$grobs[[1]], 1, 1, 1, 5)
new.grob.name <- paste0(levels(data$Season)[i], '-strip')
g <- gtable_add_grob(g, res, t = top, l = left[i], b = top, r = right[i], name = c(new.grob.name))
new.grob.no <- grep(new.grob.name, g$layout$name)
g$grobs[[new.grob.no]]$grobs[[nrow(g$grobs[[new.grob.no]]$layout)]]$children[[2]]$children[[1]]$gp <- gpar(fontface='bold')
}
grid.newpage()
grid.draw(g)
原回答
我认为您正在寻找的东西可以 – 使用 ggplot() – 使用刻面最好地实现。
data <- expand.grid(c('Spring', 'Summer', 'Autumn', 'Winter'), c('Sheltered', 'Moderately exposed', 'Exposed'), c(1, 2))
names(data) <- c('Season', 'Exposure', 'Site')
# adding some arbitrary values
set.seed(42)
data$Average <- sample(c(rep(3, 3), rep(2, 2), rep(1, 2), rep(NA, 17)))
data$SEM <- NA
SEM <- sample(c(rep(0.5, 3), rep(0.3, 2), rep(.1, 2)))
data$SEM[which(!is.na(data$Average))] <- SEM
gg <- ggplot(aes(x=as.factor(Site), y=Average, fill=as.factor(Site)), data=data)
gg <- gg + geom_bar(stat = 'identity')
gg <- gg + geom_errorbar(aes(ymin=Average-SEM, ymax=Average+SEM), width=.3)
gg <- gg + facet_wrap(~Season*Exposure, strip.position=c('bottom'), nrow=1, drop=F)
gg <- gg + scale_fill_discrete(guide_legend(title = 'Site'))
gg <- gg + theme(axis.text.x = element_blank(),
axis.ticks.x = element_blank(),
axis.title.x = element_blank())
print(gg)