r - 如何使用ggplot2重叠两个具有不同轴的双图？
问题描述
我正在尝试重新创建以下 plsr biplot：
plsr代码
df.metric <- plsr(y ~ LMA + LDMC + Thick + Carbon + Nitrogen + Tough, scale
= TRUE, validation = "LOO", method = "oscorespls", data = df)
提取真菌类群负载
df2<-df.metric$Yloadings
comp1a <- df2[,1]
comp2a <- df2[,2]
namesa <- df2[,0]
df2<-as.data.frame(cbind(namesa,comp1a, comp2a))
提取叶特征载荷
df1<-df.metric$loadings
comp1 <- df1[,1]
comp2 <- df1[,2]
names <- df1[,0]
df1<-as.data.frame(cbind(names, comp1, comp2))
生成两张图，一张用于真菌类群，一张用于叶性状
#generate fungal taxa plot
plot.fungal.taxa<-ggplot(data=df2, aes(comp1a,comp2a))+
ylab("")+
xlab("")+
theme_bw()+
theme(panel.border = element_rect(colour = "black", fill=NA,
size=1),panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
axis.line = element_line(colour = "black"))+
geom_text(aes(label=rownames(df2)), color="red")+
scale_x_continuous(breaks = c(0.10,0.05,0,-0.05,-0.10,-0.15))+
scale_y_continuous(breaks = c(0.10,0.05,0,-0.05,-0.10,-0.15))+
coord_fixed(ylim=c(0.10, -0.15),xlim=c(0.10, -0.15))+
theme(axis.ticks = element_line(colour = "red")) +
theme(axis.text.y=element_text(angle = 90, hjust = 0.65)) +
theme(axis.text.y = element_text(margin=margin(10,10,10,5,"pt")))
#generate leaf traits plot
plot.leaf.traits<-ggplot(data=df1, aes(comp1,comp2))+
ylab("Comp 2")+
xlab("Comp 1")+
theme_bw() +
theme(panel.border = element_rect(colour = "black", fill=NA, size=1),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
axis.line = element_line(colour = "black"))+
geom_text(aes(label=rownames(df1)), color="black")+
scale_x_continuous(breaks = c(-0.8,-0.6,-0.4,-0.2,0,0.2,0.4,0.6))+
scale_y_continuous(breaks = c(-0.8,-0.6,-0.4,-0.2,0,0.2,0.4,0.6))+
coord_fixed(ylim=c(0.6, -0.8),xlim=c(0.6, -0.8))+
theme(axis.ticks = element_line(colour = "black")) +
theme(axis.text.y=element_text(angle = 90, hjust = 0.65)) +
theme(axis.text.y = element_text(margin=margin(10,10,10,5,"pt")))
叠加图的功能
ggplot_dual_axis = function(plot.leaf.traits, plot.fungal.taxa, which.axis =
"x")
{
# Update plot with transparent panel
plot.fungal.taxa = plot.fungal.taxa + theme(panel.background =
element_rect(fill = NA))
grid.newpage()
# Increase right margin if which.axis == "y"
if(which.axis == "y") plot.leaf.traits = plot.leaf.traits +
theme(plot.margin = unit(c(0.7, 1.5, 0.4, 0.4), "cm"))
# Extract gtable
g1 = ggplot_gtable(ggplot_build(plot.leaf.traits))
g2 = ggplot_gtable(ggplot_build(plot.fungal.taxa))
# Overlap the panel of the second plot on that of the first
pp = c(subset(g1$layout, name == "panel", se = t:r))
g = gtable_add_grob(g1, g2$grobs[[which(g2$layout$name=="panel")]], pp$t,
pp$l, pp$b, pp$l)
# Steal axis from second plot and modify
axis.lab = ifelse(which.axis == "x", "axis-b", "axis-l")
ia = which(g2$layout$name == axis.lab)
ga = g2$grobs[[ia]]
ax = ga$children[[2]]
# Switch position of ticks and labels
if(which.axis == "x") ax$heights = rev(ax$heights) else ax$widths =
rev(ax$widths)
ax$grobs = rev(ax$grobs)
if(which.axis == "x")
ax$grobs[[2]]$y = ax$grobs[[2]]$y - unit(1, "npc") + unit(0.15, "cm") else
ax$grobs[[1]]$x = ax$grobs[[1]]$x - unit(1, "npc") + unit(0.15, "cm")
# Modify existing row to be tall enough for axis
if(which.axis == "x") g$heights[[2]] = g$heights[g2$layout[ia,]$t]
# Add new row or column for axis label
if(which.axis == "x") {
g = gtable_add_grob(g, ax, 2, 4, 2, 4)
g = gtable_add_rows(g, g2$heights[1], 1)
g = gtable_add_grob(g, g2$grob[[6]], 2, 4, 2, 4)
} else {
g = gtable_add_cols(g, g2$widths[g2$layout[ia, ]$l], length(g$widths) - 1)
g = gtable_add_grob(g, ax, pp$t, length(g$widths) - 1, pp$b)
g = gtable_add_grob(g, g2$grob[[7]], pp$t, length(g$widths), pp$b - 1)
}
# Draw it
grid.draw(g)
}
在单个地块上运行函数
ggplot_dual_axis(plot.leaf.traits, plot.fungal.taxa, "y")
这就是我最终得到的：
我的问题是如何让顶部 x 轴与绘图顶部匹配？目前它位于顶部并与地块相邻。我使用了之前在这里找到的代码（使用 ggplot2 绘制偏最小二乘回归 (plsr) biplot）。任何帮助都会很棒！
解决方案
将来当您发布问题时，您应该尝试包含一个最小的可重现示例。您几乎做到了，只是您没有包含任何要使用的数据。
如果您有与特定包中的代码相关的问题，您应该能够获取该包或 R 附带的数据，只需查看任何功能的帮助部分。例如，下面我只是复制并粘贴了 PLSR 包中的行来制作一个示例 PLSR 模型。或者，您可以在问题结束时从您的参考资料中获取表格。
主要问题是您构建的代码在 ggplot 更新时损坏了。您可以在此处和此处关注该对话。下面是一些应该可以工作的代码，顶部标注了包版本号。
#Make a ggplot object for a Partial Least Squares Regression (PLSR) plot
#####################################################
## Note that this code may break as ggplot updates,##
## as is noted on some of the below posts. ##
#####################################################
#Mostly taken from the posts below
#Links to posts-------------
#https://stackoverflow.com/questions/48664746/how-to-set-two-x-axis-and-two-y-axis-using-ggplot2
#https://stackoverflow.com/questions/39137287/plotting-partial-least-squares-regression-plsr-biplot-with-ggplot2
#https://stackoverflow.com/questions/21026598/ggplot2-adding-secondary-transformed-x-axis-on-top-of-plot
#https://stackoverflow.com/questions/36754891/ggplot2-adding-secondary-y-axis-on-top-of-a-plot/36759348#36759348
#load libraries------
library(pls) #version 2.7.1
library(ggplot2) #version 3.1.0
library(grid) #version 3.5.1
library(gtable) #version 0.2.0
library(cowplot) #version 0.9.3
library(ggplotify) #version 0.0.3
#Read data into PLSR model-----
dens1 <- plsr(density ~ NIR, ncomp = 5, data = yarn)
#Extract information from plsr (AKA mvr) model----
df1<-as.data.frame(dens1$loadings[,1:2])
names(df1) <- c("comp1", "comp2")
df2<-as.data.frame(dens1$scores[,1:2])
names(df2) <- c("comp1a", "comp2a")
#make ggplot objects------
#Plot Loadings - colored red
p1 <- ggplot(data=df1,
aes(x = comp1, y = comp2)) +
geom_text(aes(label = rownames(df1)),
color="red") +
theme_bw() +
theme(panel.border = element_rect(colour = "black",
fill=NA,
size=1),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
axis.line = element_line(colour = "black"),
axis.ticks = element_line(colour = "red"),
axis.text.y = element_text(margin = margin(10,10,10,5,"pt"),
angle = 90,
hjust = 0.65,
colour = "red"),
axis.text.x = element_text(colour = "red")) +
scale_y_continuous(limits = c(min(df1), max(df1))) +
scale_x_continuous(limits = c(min(df1), max(df1)))
#Plot 2 - scores in black
p2 <- ggplot(data=df2,
aes(x = comp1a, y = comp2a)) +
geom_text(aes(label = rownames(df2)),
color="black") +
theme_bw() +
theme(panel.border = element_rect(colour = "black",
fill=NA,
size=1),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
axis.line = element_line(colour = "black"),
axis.ticks = element_line(colour = "black"),
axis.text.y = element_text(margin = margin(10,10,10,5,"pt"),
angle = 90,
hjust = 0.65,
colour = "black"),
axis.text.x = element_text(colour = "black")) +
scale_y_continuous(limits = c(min(df2), max(df2))) +
scale_x_continuous(limits = c(min(df2), max(df2)))
#Final plot----
#Overlay plots in order to get two graphs with different axes on same plot
#rename plots in case you want to make adjustments without regenerating plots
plot1 <- p1
plot2 <- p2
# Update plot with transparent panel
plot2 = plot2 +
theme(panel.background = element_rect(fill = "transparent"))
#clean plot space
grid.newpage()
# Extract gtables from ggplot objects
g1 = ggplot_gtable(ggplot_build(plot1))
g2 = ggplot_gtable(ggplot_build(plot2))
# Get the location of the plot panel in g1.
# These are used later when transformed elements of g2 are put back into g1
pp <- c(subset(g1$layout, name == "panel", se = t:r))
# Overlap panel for second plot on that of the first plot
g1 <- gtable_add_grob(g1, g2$grobs[[which(g2$layout$name == "panel")]], pp$t, pp$l, pp$b, pp$l)
#Note from stack overflow post:
# Get the location of the plot panel in g1.
# These are used later when transformed elements of g2 are put back into g1
pp <- c(subset(g1$layout, name == "panel", se = t:r))
# Overlap panel for second plot on that of the first plot
g1 <- gtable_add_grob(g1, g2$grobs[[which(g2$layout$name == "panel")]], pp$t, pp$l, pp$b, pp$l)
# Then proceed as before:
# ggplot contains many labels that are themselves complex grob;
# usually a text grob surrounded by margins.
# When moving the grobs from, say, the left to the right of a plot,
# Make sure the margins and the justifications are swapped around.
# The function below does the swapping.
# Taken from the cowplot package:
# https://github.com/wilkelab/cowplot/blob/master/R/switch_axis.R
hinvert_title_grob <- function(grob){
# Swap the widths
widths <- grob$widths
grob$widths[1] <- widths[3]
grob$widths[3] <- widths[1]
grob$vp[[1]]$layout$widths[1] <- widths[3]
grob$vp[[1]]$layout$widths[3] <- widths[1]
# Fix the justification
grob$children[[1]]$hjust <- 1 - grob$children[[1]]$hjust
grob$children[[1]]$vjust <- 1 - grob$children[[1]]$vjust
grob$children[[1]]$x <- unit(1, "npc") - grob$children[[1]]$x
grob
}
# Get the y axis title from g2
# Which grob contains the y axis title?
index <- which(g2$layout$name == "ylab-l")
# Extract that grob
ylab <- g2$grobs[[index]]
# Swap margins and fix justifications
ylab <- hinvert_title_grob(ylab)
# Put the transformed label on the right side of g1
g1 <- gtable_add_cols(g1, g2$widths[g2$layout[index, ]$l], pp$r)
g1 <- gtable_add_grob(g1, ylab, pp$t, pp$r + 1, pp$b, pp$r + 1, clip = "off", name = "ylab-r")
# Get the y axis from g2 (axis line, tick marks, and tick mark labels)
# Which grob
index <- which(g2$layout$name == "axis-l")
# Extract the grob
yaxis <- g2$grobs[[index]]
# yaxis is a complex of grobs containing the axis line, the tick marks, and the tick mark labels.
# The relevant grobs are contained in axis$children:
# axis$children[[1]] contains the axis line;
# axis$children[[2]] contains the tick marks and tick mark labels.
# First, move the axis line to the left
yaxis$children[[1]]$x <- unit.c(unit(0, "npc"), unit(0, "npc"))
# Second, swap tick marks and tick mark labels
ticks <- yaxis$children[[2]]
ticks$widths <- rev(ticks$widths)
ticks$grobs <- rev(ticks$grobs)
# Third, move the tick marks
ticks$grobs[[1]]$x <- ticks$grobs[[1]]$x - unit(1, "npc") + unit(1, "mm")
# Fourth, swap margins and fix justifications for the tick mark labels
ticks$grobs[[2]] <- hinvert_title_grob(ticks$grobs[[2]])
# Fifth, put ticks back into yaxis
yaxis$children[[2]] <- ticks
# Put the transformed yaxis on the right side of g1
g1 <- gtable_add_cols(g1, g2$widths[g2$layout[index, ]$l], pp$r)
g1 <- gtable_add_grob(g1, yaxis, pp$t, pp$r + 1, pp$b, pp$r + 1, clip = "off", name = "axis-r")
#Draw it for a dummy check
grid.newpage()
grid.draw(g1)
# function that can vertically invert a title grob, with margins treated properly
# title grobs are used a lot in the new ggplot2 version (>1.0.1)
vinvert_title_grob <- function(grob) {
heights <- grob$heights
grob$heights[1] <- heights[3]
grob$heights[3] <- heights[1]
grob$vp[[1]]$layout$heights[1] <- heights[3]
grob$vp[[1]]$layout$heights[3] <- heights[1]
grob$children[[1]]$hjust <- 1 - grob$children[[1]]$hjust
grob$children[[1]]$vjust <- 1 - grob$children[[1]]$vjust
grob$children[[1]]$y <- unit(1, "npc") - grob$children[[1]]$y
grob
}
# Copy title xlab from g2 and swap margins
index <- which(g2$layout$name == "xlab-b")
xlab <- g2$grobs[[index]]
xlab <- vinvert_title_grob(xlab)
# Put xlab at the top of g1
g1 <- gtable_add_rows(g1, g2$heights[g2$layout[index, ]$t], pp$t-1)
g1 <- gtable_add_grob(g1, xlab, pp$t, pp$l, pp$t, pp$r, clip = "off", name="xlab-t")
# Get "feet" axis (axis line, tick marks and tick mark labels) from g2
index <- which(g2$layout$name == "axis-b")
xaxis <- g2$grobs[[index]]
# Move the axis line to the bottom (Not needed in your example)
xaxis$children[[1]]$y <- unit.c(unit(0, "npc"), unit(0, "npc"))
# Swap axis ticks and tick mark labels
ticks <- xaxis$children[[2]]
ticks$heights <- rev(ticks$heights)
ticks$grobs <- rev(ticks$grobs)
# Move tick marks
ticks$grobs[[2]]$y <- ticks$grobs[[2]]$y - unit(1, "npc") + unit(3, "pt")
# Swap tick mark labels' margins
ticks$grobs[[1]] <- vinvert_title_grob(ticks$grobs[[1]])
# Put ticks and tick mark labels back into xaxis
xaxis$children[[2]] <- ticks
# Add axis to top of g1
g1 <- gtable_add_rows(g1, g2$heights[g2$layout[index, ]$t], pp$t)
g1 <- gtable_add_grob(g1, xaxis, pp$t+1, pp$l, pp$t+1, pp$r, clip = "off", name = "axis-t")
#remove title and axes titles if you want
g1 <- gtable_remove_grobs(g1, c("title", "xlab-t", "xlab-b", "ylab-r", "ylab-l"))
# Draw it
grid.newpage()
my_PLS = ggplotify::as.ggplot(g1)
#save plot in square format----
ggsave(paste0("my_PLS_",Sys.Date(),".png"), width = 6, height = 6, units = "in", plot = my_PLS)
应该是这样的：
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