通过使用facet_wrap将r平方成ggplot [英] annotate r squared to ggplot by using facet_wrap

问题描述

我刚刚加入社区，并希望为我的硕士论文的数据分析获得帮助.

I just joined the community and looking forward to get some help for the data analysis for my master thesis.

此刻我有以下问题:

我使用facet_wrap用ggplot绘制了42个变种:

I plotted 42 varieties with ggplot by using facet_wrap:

`ggplot(sumfvvar,aes(x=TemperaturCmean,y=Fv.Fm,col=treatment))+
  geom_point(shape=1,size=1)+
  geom_smooth(method=lm)+
  scale_color_brewer(palette = "Set1")+
  facet_wrap(.~Variety)`

效果很好，但是我想为回归线标注r平方值.我有两种处理方式和42个变体，因此有84条回归线. 是否有可能计算所有r平方值并将其集成到ggplot中?我已经找到了功能

That works very well, but I would like to annotate the r squared values for the regression lines. I have two treatments and 42 varieties, therefore 84 regression lines. Are there any possibilties to calculate all r squared values and integrate them into the ggplot? I found allready the function

ggplotRegression <- function (fit) {

require(ggplot2)

ggplot(fit$model, aes_string(x = names(fit$model)[2], y = names(fit$model)[1])) + 
geom_point() +
stat_smooth(method = "lm") +
labs(title = paste("Adj R2 = ",signif(summary(fit)$adj.r.squared, 5),
                   "Intercept =",signif(fit$coef[[1]],5 ),
                   " Slope =",signif(fit$coef[[2]], 5),
                   " P =",signif(summary(fit)$coef[2,4], 5)))
}

但这仅适用于一种变种和一种处理.可能是lm()函数的循环选项吗?

but that works just for one variety and one treatment. Could be a loop for the lm() function an option?

推荐答案

除非将另一个r ^ 2列添加到数据中，否则不能将不同的标签应用于不同的方面.一种方法是使用geom_text，但是您可以首先需要计算您需要的统计信息.下面我以虹膜为例，对于您的情况，只需更改Species for Variety等，

You can't apply different labels to different facet, unless you add another r^2 column to your data.. One way is to use geom_text, but you need to calculate the stats you need first. Below I show an example with iris, and for your case, just change Species for Variety, and so on

library(tidyverse)
# simulate data for 2 treatments
# d2 is just shifted up from d1
d1 <- data.frame(iris,Treatment="A")
d2 <- data.frame(iris,Treatment="B") %>% 
mutate(Sepal.Length=Sepal.Length+rnorm(nrow(iris),1,0.5))
# combine datasets
DF <- rbind(d1,d2) %>% rename(Variety = Species)

# plot like you did
# note I use "free" scales, if scales very different between Species
# your facet plots will be squished
g <- ggplot(DF,aes(x=Sepal.Width,y=Sepal.Length,col=Treatment))+
  geom_point(shape=1,size=1)+
  geom_smooth(method=lm)+
  scale_color_brewer(palette = "Set1")+
  facet_wrap(.~Variety,scales="free")

# rsq function
RSQ = function(y,x){signif(summary(lm(y ~ x))$adj.r.squared, 3)}
#calculate rsq for variety + treatment
STATS <- DF %>%
group_by(Variety,Treatment) %>% 
summarise(Rsq=RSQ(Sepal.Length,Sepal.Width)) %>%
# make a label
# one other option is to use stringr::str_wrap in geom_text
mutate(Label=paste("Treat",Treatment,", Rsq=",Rsq))

# set vertical position of rsq
VJUST = ifelse(STATS$Treatment=="A",1.5,3)
# finally the plot function
g + geom_text(data=STATS,aes(x=-Inf,y=+Inf,label=Label),
hjust = -0.1, vjust = VJUST,size=3)

对于最后的geom_text()调用，我通过乘以处理"来允许文本的y坐标不同..您可能需要根据您的图进行调整..

For the last geom_text() call, I allowed the y coordinates of the text to be different by multiplying the Treatment.. You might need to adjust that depending on your plot..

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