Contour plot using bplot function in rms package

Question

I have been trying to make a contour plot for prediction models with R, based on the bplot function in "rms" package. The codes are as follows:

library(rms)
n <- 1000
set.seed(17)
age <- rnorm(n, 50, 10)
blood.pressure <- rnorm(n, 120, 15)
cholesterol <- rnorm(n, 200, 25)
sex <- factor(sample(c('female','male'), n,TRUE))
L <- .4*(sex=='male') + .045*(age-50) + (log(cholesterol - 10)-5.2)*(-2*(sex=='female') + 2*(sex=='male'))
y <- ifelse(runif(n) < plogis(L), 1, 0)
ddist <- datadist(age, blood.pressure, cholesterol, sex)
options(datadist='ddist')
fit <- lrm(y ~ blood.pressure + sex * (age + rcs(cholesterol,4)), x=TRUE, y=TRUE)
p <- Predict(fit, age, cholesterol, sex, np=50)
bplot(p,, contourplot, region = TRUE,col.regions=topo.colors)

And I noticed that the output figure was like this:

I couldn't find out how to smoothen the zigzag borderlines between two filled regions, so I wonder if this kind of contour plot for prediction models could be made with ggplot2 or if there are any other solutions to smoothen the zigzag borderlines.

Answer 1

You can plot similar plot with combination of geom_tile and geom_contour .

library(ggplot2)
ggplot(data.frame(p), aes(age, cholesterol, fill = yhat, z = yhat)) +
    geom_tile() +
    geom_contour(color = "black") +
    scale_fill_distiller(palette = "Spectral", limits = c(-2, 2)) +
    labs(x = "Age",
         y = expression(Total~Cholesterol["mg/dl"]),
         fill = NULL) +
    facet_grid(~ sex) +
    theme_classic()

Edit: As OP requested I added discrete colors:

ggplot(data.frame(p), aes(age, cholesterol, z = yhat)) +
    geom_tile(aes(fill = factor(round(yhat)))) +
    geom_contour(color = "black") +
    labs(x = "Age",
         y = expression(Total~Cholesterol["mg/dl"]),
         fill = NULL) +
    facet_grid(~ sex) +
    theme_classic()