我想将第三个数据集添加到散点图中,但它的值比其他两个数据集大几个数量级。
有没有办法在一个窗口中绘制所有三个数据集的值,在右侧y轴(轴4)上用与我用于设置3点的颜色相匹配的颜色表示数据集3的y值?这是我尝试过的:
plot(xlab = "Mb", ylab = "Pi",
x, yAll, pch = 6, cex = .5, col = "blue", type ="b" )
lines(x, yAll_filtered, pch = 18, cex = .5, col = "red", type = "b")
这让我得到了三个数据集中的两个,然后我不知道下一步。
理想情况下,我可以用绿色绘制第3组值,并在右侧显示不同比例的y值,也是绿色。基本上,用这些参数绘制这些Y值符合
plot(x, yAll_normalized, pch = 19, cex = .5, col = "green", type = "b",
axis(4))
答案 0 :(得分:1)
三个简单的选择:
pracma::plotyy
graphics::axis
在绘图之前,只需缩放数据集。
如果您选择第二位,请先按常规方式绘制“左手”数据,然后拨打axis(side=4,{other setup arguments})
,然后拨打lines(data3,...)
编辑 - 每个gung的有效评论,这是plotyy
的帮助文件的一部分:
plotyy(x1, y1, x2, y2, gridp = TRUE, box.col = "grey",
type = "l", lwd = 1, lty = 1,
xlab = "x", ylab = "y", main = "",
col.y1 = "navy", col.y2 = "maroon", ...)
Arguments
x1, x2
x-coordinates for the curves
y1, y2
the y-values, with ordinates y1 left, y2 right.
type
type of the curves, line or points (for both data).
这将在左侧y轴上绘制带有自动缩放的x1,y1
,并在右侧y轴上绘制x2,y2
。
答案 1 :(得分:1)
(这个问题可能会更好地迁移到stats.SE,因为问题不是要调用的函数,而是了解这些事情背后的想法。)
这里的基本策略是在绘图之前缩放数据集,正如@Carl Witthoft所说。以下是它的工作原理(了解所使用的任何功能,在R控制台的提示符下输入?<function name>
):
# here I generate some example data, set.seed makes it reproducible
set.seed(33)
x <- 1:20; y0 <- 20; y1 <- 25; y2 <- 300
for(i in 2:20){
y0 <- c(y0, y0[i-1]+rnorm(1, mean=0.25, sd=1.5))
y1 <- c(y1, y1[i-1]+rnorm(1, mean=0, sd=1))
y2 <- c(y2, y2[i-1]+rnorm(1, mean=-10, sd=5))
}
max(y0, y1)
# [1] 35.3668
min(y0, y1)
# [1] 17.77653
# from 0 to 50 seems like a reasonable Y range for the plotting area
windows()
plot (x, y0, pch=6, cex=.5, col="blue", type="b",
xlab="Mb", ylab="Pi", ylim=c(0, 50))
lines(x, y1, pch=18, cex=.5, col="red", type="b")
# We need to create a new variable that will fit within this plotting area
y2new <- scale(y2) # this makes y2 have mean 0 & sd 1
y2new <- y2new*sd(y0) # now its sd will equal that of y0
y2new <- y2new+mean(y0) # now its mean will also equal that of y0
lines(x, y2new, pch=24, cex=.5, col="green", type="b")
# now y2 fits within the window, but we need an axis which must map the
# plotted points to the original values
summary(y0)
# Min. 1st Qu. Median Mean 3rd Qu. Max.
# 17.78 20.64 24.34 25.62 30.25 35.37
summary(y2)
# Min. 1st Qu. Median Mean 3rd Qu. Max.
# 125.1 178.2 222.2 220.0 266.3 300.0
sd(y0)
# [1] 5.627629
sd(y2)
#[1] 54.76167
# thus, we need an axis w/ 25.62 showing 220 instead, & where 5.63 higher
# shows 54.76 higher instead
increments <- (mean(y0)-seq(from=0, to=50, by=10))/sd(y0)
increments
# [1] 4.5521432 2.7751960 0.9982488 -0.7786983 -2.5556455
# [6] -4.3325927
newTicks <- mean(y2) - increments*sd(y2)
newTicks
# [1] -29.24281 68.06579 165.37438 262.68298 359.99158
# [6] 457.30017
# the bottom of the y axis in the plot is 4.55 sd's below y0's mean,
# thus the bottom of the new axis should be about -30, and the top of
# the new axis should be about 460
axis(side=4, at=seq(0, 50, 10), labels=round(newTicks), col="green")
legend("bottomleft", c("y0 (left axis)", "y1 (left axis)",
"y2 (right axis)"), pch=c(6, 18, 24), lty=1,
col=c("blue", "red", "green"))
所有这些都是一种痛苦。从@Carl Wittholf的回答中,我收集函数plotyy()
将自动为您执行此操作(我从未使用过它),但您必须先安装(并随后加载)pracma包。