在3个y轴的单个绘图中绘制4条曲线

Question

我有4组值：y1，y2，y3，y4和一组x。 y值有不同的范围，我需要将它们绘制为单独的曲线，并在y轴上分别设置不同的值。为了简单起见，我需要3个具有不同值（比例）的y轴来绘制同一个图。

Answer 1

尝试了这一点....

# The data have a common independent variable (x) 
x <- 1:10 

# Generate 4 different sets of outputs 
y1 <- runif(10, 0, 1) 
y2 <- runif(10, 100, 150) 
y3 <- runif(10, 1000, 2000) 
y4 <- runif(10, 40000, 50000) 
y <- list(y1, y2, y3, y4) 

# Colors for y[[2]], y[[3]], y[[4]] points and axes 
colors = c("red", "blue", "green") 

# Set the margins of the plot wider 
par(oma = c(0, 2, 2, 3)) 

plot(x, y[[1]], yaxt = "n", xlab = "Common x-axis", main = "A bunch of plots on the same graph", 
    ylab = "") 
lines(x, y[[1]]) 

# We use the "pretty" function go generate nice axes 
axis(at = pretty(y[[1]]), side = 2) 

# The side for the axes. The next one will go on 
# the left, the following two on the right side 
sides <- list(2, 4, 4) 

# The number of "lines" into the margin the axes will be 
lines <- list(2, NA, 2) 

for(i in 2:4) { 
    par(new = TRUE) 
    plot(x, y[[i]], axes = FALSE, col = colors[i - 1], xlab = "", ylab = "") 
    axis(at = pretty(y[[i]]), side = sides[[i-1]], line = lines[[i-1]], 
     col = colors[i - 1]) 
    lines(x, y[[i]], col = colors[i - 1]) 
} 

# Profit. 

Answer 2

尝试以下。这看起来并不复杂。一旦你看到正在构建的第一张图，你会发现其他人非常相似。而且，由于有四个相似的图形，您可以轻松地将代码重新配置为反复使用以绘制每个图形的函数。但是，由于我通常使用相同的x轴绘制各种图形，我需要很大的灵活性。所以，我决定复制/粘贴/修改每个图形的代码会更容易。

#Generate the data for the four graphs 
x <- seq(1, 50, 1) 
y1 <- 10*rnorm(50) 
y2 <- 100*rnorm(50) 
y3 <- 1000*rnorm(50) 
y4 <- 10000*rnorm(50) 

#Set up the plot area so that multiple graphs can be crammed together 
par(pty="m", plt=c(0.1, 1, 0, 1), omd=c(0.1,0.9,0.1,0.9)) 

#Set the area up for 4 plots 
par(mfrow = c(4, 1)) 

#Plot the top graph with nothing in it ========================= 
plot(x, y1, xlim=range(x), type="n", xaxt="n", yaxt="n", main="", xlab="", ylab="") 
mtext("Four Y Plots With the Same X", 3, line=1, cex=1.5) 

#Store the x-axis data of the top plot so it can be used on the other graphs 
pardat<-par() 
xaxisdat<-seq(pardat$xaxp[1],pardat$xaxp[2],(pardat$xaxp[2]-pardat$xaxp[1])/pardat$xaxp[3]) 

#Get the y-axis data and add the lines and label 
yaxisdat<-seq(pardat$yaxp[1],pardat$yaxp[2],(pardat$yaxp[2]-pardat$yaxp[1])/pardat$yaxp[3]) 
axis(2, at=yaxisdat, las=2, padj=0.5, cex.axis=0.8, hadj=0.5, tcl=-0.3) 
abline(v=xaxisdat, col="lightgray") 
abline(h=yaxisdat, col="lightgray") 
mtext("y1", 2, line=2.3) 
lines(x, y1, col="red") 

#Plot the 2nd graph with nothing ================================ 
plot(x, y2, xlim=range(x), type="n", xaxt="n", yaxt="n", main="", xlab="", ylab="") 

#Get the y-axis data and add the lines and label 
pardat<-par() 
yaxisdat<-seq(pardat$yaxp[1],pardat$yaxp[2],(pardat$yaxp[2]-pardat$yaxp[1])/pardat$yaxp[3]) 
axis(2, at=yaxisdat, las=2, padj=0.5, cex.axis=0.8, hadj=0.5, tcl=-0.3) 
abline(v=xaxisdat, col="lightgray") 
abline(h=yaxisdat, col="lightgray") 
mtext("y2", 2, line=2.3) 
lines(x, y2, col="blue") 

#Plot the 3rd graph with nothing ================================= 
plot(x, y3, xlim=range(x), type="n", xaxt="n", yaxt="n", main="", xlab="", ylab="") 

#Get the y-axis data and add the lines and label 
pardat<-par() 
yaxisdat<-seq(pardat$yaxp[1],pardat$yaxp[2],(pardat$yaxp[2]-pardat$yaxp[1])/pardat$yaxp[3]) 
axis(2, at=yaxisdat, las=2, padj=0.5, cex.axis=0.8, hadj=0.5, tcl=-0.3) 
abline(v=xaxisdat, col="lightgray") 
abline(h=yaxisdat, col="lightgray") 
mtext("y3", 2, line=2.3) 
lines(x, y3, col="green") 

#Plot the 4th graph with nothing ================================= 
plot(x, y4, xlim=range(x), type="n", xaxt="n", yaxt="n", main="", xlab="", ylab="") 

#Get the y-axis data and add the lines and label 
pardat<-par() 
yaxisdat<-seq(pardat$yaxp[1],pardat$yaxp[2],(pardat$yaxp[2]-pardat$yaxp[1])/pardat$yaxp[3]) 
axis(2, at=yaxisdat, las=2, padj=0.5, cex.axis=0.8, hadj=0.5, tcl=-0.3) 
abline(v=xaxisdat, col="lightgray") 
abline(h=yaxisdat, col="lightgray") 
mtext("y4", 2, line=2.3) 
lines(x, y4, col="darkgray") 

#Plot the X axis ================================================= 
axis(1, at=xaxisdat, padj=-1.4, cex.axis=0.9, hadj=0.5, tcl=-0.3) 
mtext("X Variable", 1, line=1.5) 

下面是四张图的图。

Answer 3

如果你想下去学习绘图包超越基本图形的路径，这里使用的变量从@ Rguy的回答与ggplot2的解决方案：

library(ggplot2) 
dat <- data.frame(x, y1, y2, y3, y4) 

dat.m <- melt(dat, "x") 

ggplot(dat.m, aes(x, value, colour = variable)) + geom_line() + 
facet_wrap(~ variable, ncol = 1, scales = "free_y") + 
scale_colour_discrete(legend = FALSE)