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 in to grad school.
#GRE (Graduate Record Exam scores), GPA (grade point average) 
mydata <- read.csv("https://stats.idre.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 with 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 differnet 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))