library(ggplot2)

library(dplyr) #加载dplyr包

library(ggpmisc) #加载ggpmisc包

library(RColorBrewer)

library(ggpubr)

#载入数据，计算均值和se

caomuxi<-read.csv("E:/R/Rfiles/data.csv")

windowsFonts(SH = windowsFont("Times New Roman"))

#第一种方案，做点状图，加回归线，添加回归方程和R²

a<- ggplot(data=data,aes(x=Fert, y=Hight))+

  geom_point(aes(color=treatment),size = 3)+ #设置分组颜色和点的大小

  geom_smooth(method = "lm",linetype=3,se=FALSE,colour="black",span=0.8)+ # 添加回归曲线，se取消置信空间，linetype设置线型

  stat_poly_eq(aes(label = paste(..eq.label.., ..adj.rr.label.., sep = '~~~~')), formula = y ~ x, parse = T,family = "SH") + #添加回归方程和R²

  scale_x_continuous()+

  scale_y_continuous(expand = c(0, 0),#设定x轴和y轴的交叉点

                     name ="Height (cm)",#设定y轴标题

                     breaks=seq(0,50,10),#设定Y轴的数据间隔

                     limits = c(10,50) #设定Y轴的数据上下限

                    )+

  scale_color_brewer(palette = "YlOrRd")+

  theme()

a

出图如下：

#第二种方案，做点状图，加回归线，添加R²和P值

a<- ggplot(data=data,aes(x=Fert, y=Hight))+

  geom_point(aes(color=treatment),size = 3)+ #设置分组颜色和点的大小

  geom_smooth(method = "lm",linetype=3,se=FALSE,colour="black",span=0.8)+ # 添加回归曲线，se取消置信空间，linetype设置线型

  stat_fit_glance(method = 'lm',

                  method.args = list(formula = y ~ x),

                  mapping = aes(label = sprintf('R^2~"="~%.3f~~italic(P)~"="~%.2g', stat(r.squared), stat(p.value))),

                  parse = TRUE,label.x = 0.95,label.y = 0.95,family = "SH")+

#方案2，仅添加R²和P值，label.x和label.y设置文字位置。

  scale_x_continuous()+

  scale_y_continuous(expand = c(0, 0),#设定x轴和y轴的交叉点

                     name ="Height (cm)",#设定y轴标题

                     breaks=seq(0,50,10),#设定Y轴的数据间隔

                     limits = c(10,50) #设定Y轴的数据上下限

                    )+

  scale_color_brewer(palette = "YlOrRd")+

  theme()

a

出图如下：