#Read data
df <- read.table(text = c("
diesel twodoors sportsstyle wheelbase length width height curbweight enginesize horsepower horse_per_weight conscity price symboling
0 1 0 97 172 66 56 2209 109 85 0.0385 8.7 7975 2
0 0 0 100 177 66 54 2337 109 102 0.0436 9.8 13950 2
0 0 0 116 203 72 57 3740 234 155 0.0414 14.7 34184 -1
0 1 1 103 184 68 52 3016 171 161 0.0534 12.4 15998 3
0 0 0 101 177 65 54 2765 164 121 0.0438 11.2 21105 0
0 1 0 90 169 65 52 2756 194 207 0.0751 13.8 34028 3
1 0 0 105 175 66 54 2700 134 72 0.0267 7.6 18344 0
0 0 0 108 187 68 57 3020 120 97 0.0321 12.4 11900 0
0 0 1 94 157 64 51 1967 90 68 0.0346 7.6 6229 1
0 1 0 95 169 64 53 2265 98 112 0.0494 9.0 9298 1
1 0 0 96 166 64 53 2275 110 56 0.0246 6.9 7898 0
0 1 0 100 177 66 53 2507 136 110 0.0439 12.4 15250 2
0 1 1 94 157 64 51 1876 90 68 0.0362 6.4 5572 1
0 0 0 95 170 64 54 2024 97 69 0.0341 7.6 7349 1
0 1 1 95 171 66 52 2823 152 154 0.0546 12.4 16500 1
0 0 0 103 175 65 60 2535 122 88 0.0347 9.8 8921 -1
0 0 0 113 200 70 53 4066 258 176 0.0433 15.7 32250 0
0 0 0 95 165 64 55 1938 97 69 0.0356 7.6 6849 1
1 0 0 97 172 66 56 2319 97 68 0.0293 6.4 9495 2
0 0 0 97 172 66 56 2275 109 85 0.0374 8.7 8495 2"), header = T)
#Run OP's code
library(pls)
library(ggplot2)
Y <- as.matrix(df[,14])
X <- as.matrix(df[,1:11])
df.pls <- mvr(Y ~ X, ncomp = 3, method = "oscorespls", scale = T)
#Extract information from mvr object
df2<-df.pls$scores
comp1a<-df2[,1]
comp2a<-df2[,2]
df2<-as.data.frame(cbind(comp1a, comp2a))
df1<-df.pls$loadings
comp1<-df1[,1]
comp2<-df1[,2]
names<-df1[,0]
df1<-as.data.frame(cbind(names, comp1, comp2))
#Generate two plots and overlay
#Plot 1
p1<-ggplot(data=df1, aes(comp1,comp2))+
ylab("")+xlab("")+ggtitle("X scores and X Loadings")+
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="red")+
scale_x_continuous(breaks = c(-0.6,-0.4,-0.2,0,0.2,0.4,0.6))+
scale_y_continuous(breaks = c(-0.6,-0.4,-0.2,0,0.2,0.4,0.6))+
coord_fixed(ylim=c(-0.6, 0.6),xlim=c(-0.6, 0.6))+
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")))
#Plot 2
p2<-ggplot(data=df2, aes(comp1a,comp2a))+
ylab("Comp 2")+xlab("Comp 1")+ggtitle("X scores and X Loadings")+
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)))+
xlim(-4,4)+ylim(-4,4)+
scale_y_continuous(breaks = c(-4,-2,0,2))+
coord_cartesian(ylim=c(-4, 4))+
scale_x_continuous(breaks = c(-4,-2,0,2)) +
theme(plot.title = element_text(face="bold"))+
theme(axis.text.y=element_text(angle = 90, hjust = 0.65))
#Function to overlay plots in order to get two graphs with different axes on same plot
library(grid)
library(gtable)
ggplot_dual_axis = function(plot1, plot2, which.axis = "x") {
# Update plot with transparent panel
plot2 = plot2 + theme(panel.background = element_rect(fill = NA))
grid.newpage()
# Increase right margin if which.axis == "y"
if(which.axis == "y") plot1 = plot1 + theme(plot.margin = unit(c(0.7, 1.5, 0.4, 0.4), "cm"))
# Extract gtable
g1 = ggplot_gtable(ggplot_build(plot1))
g2 = ggplot_gtable(ggplot_build(plot2))
# 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)
}
#Run function on individual plots
ggplot_dual_axis(p2, p1, "y")
看看GitHub上ggvegan。它可能不会直接做到，但会显示如何完成它（简而言之，从pls对象中提取分数） –
@RichardTelford 感谢您的时间，帮助和建议 – aelwan