在ggplot2中使用stat_poly_eq指定每个构面的公式 [英] Specifying formula for each facet using stat_poly_eq in ggplot2

问题描述

我从

解决方案

您可以单独更新面板6的公式（当然，您也可以使用类似功能更新所有面板，但这里没有必要）

  rename_panel_expression<  - 函数（grb，panel，expr）{
g<  -  grb $ grobs [[panel + 1]] $ children 
 grb $ grobs [[panel + 1]] $ children [[grep（GRID.text，names（g））]] $ label<  -  expr 
 grb 
 } 
 
l < -  lm（mpg〜log（disp），mtcars [mtcars $ am == 1& mtcars $ gear == 5，]）
 
 tt< ;  -  rename_panel_expression（ggplotGrob（p），6，
 bquote（italic（y）〜`=`〜。（round（l $ coefficients [1]，3）） - （圆）（概要（1）$ r.squar（2）），3））*〜斜体（x）~~斜体（R）^ 2 =`= ed），3））））
 
 grid :: grid.newpage（）
 grid :: grid.draw（tt）
  

I borrowed this example dataset from here:

# Load library
library(ggplot2)

# Load data
data(mtcars)

# Plot data
p <- ggplot(mtcars,aes(x = disp, y = mpg)) + geom_point() + facet_grid(gear ~ am)
p <- p + geom_smooth(method="lm")
print(p)

In above code the regression methods and formulae are the same in all facets. If we want to specify formula for facet (or panel) 6, we have the following code, from here:

# Smoothing function with different behaviour depending on the panel
custom.smooth <- function(formula, data,...){
  smooth.call <- match.call()

  if(as.numeric(unique(data$PANEL)) == 6) {
    # Linear regression
    smooth.call[[1]] <- quote(lm)
    # Specify formula
    smooth.call$formula <- as.formula("y ~ log(x)")
  }else{
    # Linear regression
    smooth.call[[1]] <- quote(lm)
  }

  # Perform fit
  eval.parent(smooth.call)
}

# Plot data with custom fitting function
p <- ggplot(mtcars,aes(x = disp, y = mpg)) + geom_point() + facet_grid(gear ~ am)
p <- p + geom_smooth(method = "custom.smooth", se = FALSE)
print(p)

Now if I want to add regression equations to these facets:

# Load library
library(ggpmisc)
p + stat_poly_eq(formula = y ~ x,aes(label = paste(..eq.label.., ..rr.label.., sep = "~~~")), 
    parse=TRUE,label.x.npc = "right")

Then what should I do, to specify the equation and R2 displayed on panel 6, that can match the model I specified before? See the plot below, now panel 6 has its own fitting model, but the equation label doesn't. Maybe we can define a similar function as we did to ggplot2 parameters?

解决方案

You could update panel 6's formula individually (of course you could also update all panels with a function like that, but there's no need for that here)

rename_panel_expression <- function(grb, panel, expr) {
  g <- grb$grobs[[panel + 1]]$children
  grb$grobs[[panel + 1]]$children[[grep("GRID.text", names(g))]]$label <- expr
  grb
}

l <- lm(mpg ~ log(disp), mtcars[mtcars$am == 1 & mtcars$gear == 5, ])

tt <- rename_panel_expression(ggplotGrob(p), 6, 
  bquote(italic(y)~`=`~.(round(l$coefficients[1], 3)) - .(round(abs(l$coefficients[2]), 3))*~italic(x)~~~italic(R)^2~`=`~.(round(summary(l)$r.squared, 3))))

grid::grid.newpage()
grid::grid.draw(tt)

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