英文:
Reversing X and Y axes on plotted GAM in base R
问题
我想绘制一个GAM的输出，将X和Y轴颠倒，使得输出像这样：
变成像这样：
在基本的R中有没有一种好方法可以做到这一点？
在调用plot(GAM)时似乎进行了一些背景计算，所以我不能简单地颠倒输入的顺序。
英文:
I would like to plot the output from a GAM with the X and Y axes reversed, such that an output like this:
is output like this:
Is there a good way to do this in base R?
There seems to be some background calculations when plot(GAM) is called, so I can't just simply reverse the order of the input.
答案1
得分: 3
函数plot.gam会隐式返回一个包含足够数据以重新创建绘图的列表，因此您可以使用以下函数自己构建翻转版本：
plot_flipped <- function(model) {
dat <- plot(model)[[1]]
plot(c(dat$fit), dat$x, ylim = rev(dat$xlim), type = "l", xaxt = "n",
xlab = "", ylab = dat$xlab)
axis(3)
suppressWarnings(rug(dat$raw, side = 2))
lines(dat$fit - dat$se, dat$x, lty = 2)
lines(dat$fit + dat$se, dat$x, lty = 2)
mtext(dat$ylab, side = 3, padj = -4)
}
所以，假设我们有这样一个模型：
mod <- mgcv::gam(mpg ~ s(wt), data = mtcars)
标准绘图将如下所示：
plot(mod)
但我们的翻转版本将是：
plot_flipped(mod)
有一些使用扩展包更简单的替代方法，您可以使用ggplot获得更漂亮的版本，但这可能是仅使用基本R（而不将图像保存为位图并旋转它）完成的最简单方法。
<sup>在2023-06-11创建，使用 reprex v2.0.2</sup>
英文:
The function plot.gam invisibly returns a list containing enough data to recreate the plot, so you can build a flipped version yourself with this function:
plot_flipped <- function(model) {
dat <- plot(model)[[1]]
plot(c(dat$fit), dat$x, ylim = rev(dat$xlim), type = "l", xaxt = "n",
xlab = "", ylab = dat$xlab)
axis(3)
suppressWarnings(rug(dat$raw, side = 2))
lines(dat$fit - dat$se, dat$x, lty = 2)
lines(dat$fit + dat$se, dat$x, lty = 2)
mtext(dat$ylab, side = 3, padj = -4)
}
So, suppose we have a model like this:
mod <- mgcv::gam(mpg ~ s(wt), data = mtcars)
The standard plot would be like this:
plot(mod)
But our flipped version would be:
plot_flipped(mod)
There are alternative ways that would be easier using extension packages, and you could get a prettier version of the same thing using ggplot, but this is probably the simplest way to do it using only base R (without saving the image as a bitmap and rotating it)
<sup>Created on 2023-06-11 with reprex v2.0.2</sup>
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