问题:

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?

回答1:

It seems like the function you are calling custom.smooth contains a row that defines the formula as "y ~ log(x)". Therefore, you need to also specify this in your stat_poly_eq function, hence the polynomial shape (but in reality logarithmic) of a linear looking equation.

I.e. add:

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

回答2:

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)

转载请标明出处:Specifying formula for each facet using stat_poly_eq in ggplot2

文章来源: Specifying formula for each facet using stat_poly_eq in ggplot2

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