Make a contour plot with a heat map.

contour_plot.R

# Packages
library(ggplot2)

# Read in some data for the example
# The data are grade data and acceptance into grad school.
# GRE (Graduate Record Exam scores), GPA (grade point average)
mydata <- read.csv("https://stats.oarc.ucla.edu/stat/data/binary.csv")
head(mydata)
summary(mydata)
mylogit <- glm(admit ~ gre + gpa + gre:gpa, data = mydata, family = "binomial")
summary(mylogit)

# Use expand.grid to create a "grid" of data to predict from
# The grid takes all possible values based on the original data
newdat <- expand.grid(gre = seq(220, 800, 1), gpa = seq(2.2, 4, 0.01))

# Predict from the model, and place values within the "newdat" object.
newdat$pv <- predict(mylogit, newdata = newdat, type = "response")

# Basic (empty) plot
A <- ggplot(data = newdat, aes(x = gre, y = gpa, z = pv))

# Plot (blue with white contours)
A + geom_raster(aes(fill = pv)) +
  geom_contour(colour = "white", bins = 5)

# A different colour
A + geom_raster(aes(fill = pv)) +
  scale_fill_viridis_c(option = "magma")

# Make a plot with a contour line at a particular point
A + geom_raster(aes(fill = pv)) +
  scale_fill_viridis_c(option = "viridis") +
  geom_contour(colour = "white", breaks = c(.4))