Is it possible to control the number of panels per row in a ggplot? I can only get an equal number of panels on each row as in the example plot below.
例如，我的数据按“标记”自然分为 22 个块，而这些块又按“染料”组织（请参阅下面的示例代码和数据）。在这个例子中，我想将面板排列成 4 行，每行分别有 5、6、6 和 5 个面板（如最后的图片所示，但 22 个块可以同样宽）。
示例代码：
df$Type <- factor(round(df$Type, 2))
df$Allele <- factor(df$Allele)
gp <- ggplot(df, aes_string(x = "Allele", y = "Ratio", colour = "Type"))
gp <- gp + geom_point(alpha = 0.8, position = position_jitter(width = 0.1))
gp <- gp + facet_grid(Dye ~ Marker) + facet_wrap(~Marker, ncol = 5, drop = FALSE, scales = "free_x")
gp <- gp + guides(fill = guide_legend(reverse = TRUE))
gp <- gp + labs(title = "Stutter ratios")
print(gp)
示例数据：
Marker Allele Ratio Type Dye
DYS576 18 0.116157205 -1 B
DYS389 I 14 0.043252595 -1 B
DYS448 19 0.018236074 -1 B
DYS389 II 31 0.102169982 -1 B
DYS19 14 0.058139535 -1 B
DYS19 14 0.078224101 -0.2 B
DYS391 10 0.090035245 -1 G
DYS481 22 0.013492063 -2 G
DYS481 22 0.179365079 -1 G
DYS549 13 0.0625 -1 G
DYS533 12 0.07564495 -1 G
DYS437 14 0.04757085 -1 G
DYS570 17 0.071079867 -1 Y
DYS570 17 0.007420426 1 Y
DYS635 21 0.192561983 -1 Y
DYS390 24 0.073079325 -1 Y
DYS439 12 0.084817642 -1 Y
DYS392 13 0.125965997 -1 Y
DYS393 13 0.009672831 -2 R
DYS393 13 0.079374111 -1 R
DYS393 13 0.013371266 1 R
DYS458 17 0.126099707 -1 R
DYS385 13 0.059782609 -1 R
DYS385 16 0.092356688 -1 R
DYS456 17 0.12 -1 R
YGATAH4 11 0.07203718 -1 R
DYS576 18 0.094989562 -1 B
DYS389 I 14 0.044955045 -1 B
DYS448 19 0.017171717 -1 B
DYS389 II 31 0.124137931 -1 B
DYS391 10 0.052903833 -1 G
DYS481 22 0.198726115 -1 G
DYS549 13 0.08853967 -1 G
DYS533 12 0.106617647 -1 G
DYS438 9 0.017562533 -1 G
DYS570 17 0.006710002 -2 Y
DYS570 17 0.076326274 -1 Y
DYS570 17 0.007339065 1 Y
DYS635 21 0.132272501 -1 Y
DYS390 24 0.078853047 -1 Y
DYS439 12 0.06980198 -1 Y
DYS392 13 0.104508197 -1 Y
DYS393 13 0.083853995 -1 R
DYS393 13 0.014140085 1 R
DYS458 17 0.094651285 -1 R
DYS385 13 0.076977401 -1 R
DYS385 13 0.076977401 -1 R
DYS385 16 0.059866962 -1 R
DYS385 16 0.059866962 -1 R
DYS456 17 0.151162791 -1 R
YGATAH4 11 0.09254902 -1 R
DYS576 18 0.126856684 -1 B
DYS389 I 14 0.052631579 -1 B
DYS389 II 31 0.102253033 -1 B
DYS19 14 0.056882821 -1 B
DYS19 14 0.080773606 -0.2 B
DYS391 10 0.053362122 -1 G
DYS481 22 0.033595801 -2 G
DYS481 22 0.164829396 -1 G
DYS549 13 0.123548922 -1 G
DYS533 12 0.06750174 -1 G
DYS437 14 0.041118421 -1 G
DYS570 17 0.097141001 -1 Y
DYS570 17 0.010071475 1 Y
DYS635 21 0.070416095 -1 Y
DYS390 24 0.075715605 -1 Y
DYS439 12 0.077648766 -1 Y
DYS392 13 0.116974494 -1 Y
DYS643 10 0.017945781 -1 Y
DYS393 13 0.011755878 -2 R
DYS393 13 0.121810905 -1 R
DYS393 13 0.017008504 1 R
DYS458 17 0.097028366 -1 R
DYS385 13 0.083820663 -1 R
DYS385 16 0.124661247 -1 R
DYS456 17 0.11167002 -1 R
DYS576 18 0.102416918 -1 B
DYS448 19 0.021699819 -1 B
DYS19 14 0.064239829 -0.2 B
DYS391 10 0.054468085 -1 G
DYS481 22 0.048726467 -2 G
DYS481 22 0.182724252 -1 G
DYS549 13 0.091326105 -1 G
DYS533 12 0.074295474 -1 G
DYS438 9 0.059535822 -1 G
DYS437 14 0.044034091 -1 G
DYS570 17 0.02547279 -2 Y
DYS570 17 0.129293709 -1 Y
DYS570 17 0.012350444 1 Y
DYS635 21 0.09912927 -1 Y
DYS390 24 0.086936937 -1 Y
DYS439 12 0.060550459 -1 Y
DYS392 13 0.149750416 -1 Y
DYS393 13 0.08388521 -1 R
DYS393 13 0.016188374 1 R
DYS458 17 0.009228937 -2 R
DYS458 17 0.092289372 -1 R
DYS458 17 0.062816314 1 R
DYS385 13 0.068504595 -1 R
DYS385 16 0.077120823 -1 R
DYS456 17 0.131855309 -1 R
YGATAH4 11 0.070570571 -1 R
DYS576 18 0.108604407 -1 B
DYS389 I 14 0.053097345 -1 B
DYS389 II 31 0.122986823 -1 B
DYS19 14 0.044878049 -1 B
DYS19 14 0.069268293 -0.2 B
DYS391 10 0.057256368 -1 G
DYS481 22 0.029480217 -2 G
DYS481 22 0.171450737 -1 G
DYS549 13 0.078275862 -1 G
DYS533 12 0.062146893 -1 G
DYS437 14 0.037869063 -1 G
DYS570 17 0.0956807 -1 Y
DYS570 17 0.021323127 1 Y
DYS635 21 0.076858108 -1 Y
DYS390 24 0.099143207 -1 Y
DYS439 12 0.057610242 -1 Y
DYS439 12 0.028449502 1 Y
DYS392 13 0.101621622 -1 Y
DYS393 13 0.012474012 -2 R
DYS393 13 0.117463617 -1 R
DYS393 13 0.01039501 1 R
DYS458 17 0.081623347 -1 R
DYS385 13 0.068003487 -1 R
DYS385 16 0.066376496 -1 R
DYS456 17 0.149382716 -1 R
Update:终于有时间尝试解决这个问题了。根据 DWin 的回答并在网上找到的一些示例的帮助下，我几乎按照我的意愿创建了一个情节。但是我需要更多帮助才能完全按照我想要的方式得到它：
1）如何使每个图中的面板等宽（或高），并且仍然能够仅在某些图中添加标题和图例。
2）如何将 y 标题和图例在所有绘图中垂直居中。
3）当然，我想在不同面板中对相同类型使用相同的颜色，但我认为使用 ggplot 应该很容易。但这里也欢迎任何建议。
请参阅随附的代码和图像以了解我迄今为止的进展。
# Prepare data.
df$Marker <- factor(df$Marker, levels = c("DYS576", "DYS389 I", "DYS448", "DYS389 II", "DYS19",
"DYS391", "DYS481", "DYS549", "DYS533", "DYS438", "DYS437",
"DYS570", "DYS635", "DYS390", "DYS439", "DYS392",
"DYS643", "DYS393", "DYS458", "DYS385", "DYS456", "YGATAH4" ))
df$Type <- factor(round(df$Type, 2))
df$Dye <- factor(df$Dye, levels = c("B", "G", "Y", "R"))
df$Allele <- factor(df$Allele)
# Get y max to use same scale.
yMax <- max(df$Ratio)
# Get dyes.
dyes <- levels(df$Dye)
# start new page
plot.new()
# setup layout
gl <- grid.layout(nrow=length(dyes) , ncol=1)
# grid.show.layout(gl) # To inspect layout.
# Init layout
pushViewport(viewport(layout=gl))
# Loop over all dyes.
for(d in seq(along=dyes)){
# Move to the next viewport
pushViewport(viewport(layout.pos.col=1, layout.pos.row=d))
# Create a plot for the current subset.
gp <- ggplot(subset(df, Dye==dyes[d]), aes_string(x = "Allele", y = "Ratio"))
gp <- gp + geom_point(aes_string(colour = "Type"), alpha = 0.8, position = position_jitter(width = 0.1))
gp <- gp + facet_grid(Dye ~ Marker, scales="free_x")
gp <- gp + ylim(0, yMax)
# If first dye channel.
if(d == 1){
# Plot title only.
gp <- gp + labs(title = "Stutter ratios")
gp <- gp + theme(axis.title.x=element_blank())
gp <- gp + theme(axis.title.y=element_blank())
# Remove legends.
gp <- gp + theme(legend.position="none")
} else if(d == length(dyes)){ # If last dye channel.
# No title but x and y labels.
# Y label should ideally be centered vertically in final plot.
gp <- gp + labs(title = element_blank())
gp <- gp + labs(xlab = "Allele")
gp <- gp + labs(xlab = "Ratio")
# Not removing legend works but makes the last plot more compact (horizontally).
# Can the panel height or width be fixed for all subplots?
# 'bottom' is nicer (assuming I can't center it vertically in the final plot)
# but makes the last dye channel very compact (vertically).
# gp <- gp + theme(legend.position="bottom")
} else { # No titles, labels or legends.
gp <- gp + labs(title = element_blank())
gp <- gp + theme(axis.title.x = element_blank())
gp <- gp + theme(axis.title.y = element_blank())
gp <- gp + theme(legend.position="none")
}
# Print the ggplot graphics here
print(gp, newpage = FALSE)
# Done with this viewport
popViewport(1)
}
更新2：新尝试使用 gtable 作为 baptiste 的建议。我现在可以制作出我想要的确切情节。我能想到的唯一外观改进是减少图例占用的水平空间。很高兴对此有任何建议。但我不会花更多的时间去尝试和发现自己，情节对我来说已经足够接近完美了。
新代码和情节如下。代码可能可以清理一下，所以如果您有任何提示，请发表评论。
# Prepare data.
df$Marker <- factor(df$Marker, levels = c("DYS576", "DYS389 I", "DYS448", "DYS389 II", "DYS19",
"DYS391", "DYS481", "DYS549", "DYS533", "DYS438", "DYS437",
"DYS570", "DYS635", "DYS390", "DYS439", "DYS392",
"DYS643", "DYS393", "DYS458", "DYS385", "DYS456", "YGATAH4" ))
df$Type <- factor(round(df$Type, 2))
df$Dye <- factor(df$Dye, levels = c("B", "G", "Y", "R"))
df$Allele <- factor(df$Allele)
# Get y max to use same scale.
yMax <- max(df$Ratio)
# Get dyes.
dyes <- levels(df$Dye)
# Number of dyes.
noDyes <- length(dyes)
# Number of rows in table object.
noRows <- length(dyes) + 2
# Create table object.
g <- gtable(widths=unit(c(1,4,1),c("lines","null","null")),
heights = unit(c(1,rep(1,noDyes),1), c("line",rep("null",noDyes), "line")))
# Add titles.
g <- gtable_add_grob(g, textGrob("Stutter ratios"), t=1,b=1,l=2,r=2)
g <- gtable_add_grob(g, textGrob("Allele"), t=noRows ,b=noRows ,l=2,r=2)
g <- gtable_add_grob(g, textGrob("Ratio", rot=90), t=1,b=noRows ,l=1,r=1)
# Create a plot for the entire dataset to extract the legend.
gp <- ggplot(df, aes_string(x = "Allele", y = "Ratio"))
gp <- gp + geom_point(aes_string(colour = "Type"))
# Extract the legend.
guide <- gtable_filter(ggplotGrob(gp), pattern="guide")
# Add the legend to the table object.
g <- gtable_add_grob(g,guide , t=1,b=noRows,l=3,r=3)
# Loop over all dyes.
for(d in seq(along=dyes)){
# Create a plot for the current subset.
gp <- ggplot(subset(df, Dye==dyes[d]), aes_string(x = "Allele", y = "Ratio"))
gp <- gp + geom_point(aes_string(colour = "Type"), alpha = 0.8, position = position_jitter(width = 0.1))
gp <- gp + scale_colour_discrete(drop = FALSE)
gp <- gp + facet_grid(Dye ~ Marker, scales="free_x")
gp <- gp + ylim(0, yMax)
# Remove titles, axis labels and legend.
gp <- gp + labs(title = element_blank())
gp <- gp + theme(axis.title.x = element_blank())
gp <- gp + theme(axis.title.y = element_blank())
gp <- gp + theme(legend.position="none")
# Add plot panel to table object.
g <- gtable_add_grob(g,ggplotGrob(gp), t=(d+1),b=(d+1),l=2,r=2)
}
# Plot.
grid.newpage()
grid.draw(g)
放置 grobs 的一个简单方法是使用 gtable 包，
library(gtable)
gtable_add_grobs <- gtable_add_grob #misleading name
g <- gtable(widths=unit(c(1,4,1),c("lines","null","null")),
heights = unit(c(1,1,1,1), c("line","null","null", "line")))
lg <- list(textGrob("title"),
textGrob("xlab"),
textGrob("ylab", rot=90),
rectGrob(),
rectGrob(),
rectGrob())
pos <- data.frame(t=c(1, 4, 1, 2, 3, 2),
b=c(1, 4, 4, 2, 3, 3),
l=c(2, 2, 1, 2, 2, 3),
r=c(3, 2, 1, 2, 2, 3))
g <- with(pos, gtable_add_grobs(g, lg, t=t, l=l, b=b, r=r))
grid.newpage()
grid.draw(g)
您可以使用以下命令提取 ggplot 的图例gtable_filter(ggplotGrob(p), pattern="guide").