How to plot decision boundary in R for logistic regression model?

I made a logistic regression model using glm in R. I have two independent variables. How can I plot the decision boundary of my model in the scatter plot of the two variables. For example, how can I plot a figure like:
http://onlinecourses.science.psu.edu/stat557/node/55

Thanks.

``````set.seed(1234)

x1 <- rnorm(20, 1, 2)
x2 <- rnorm(20)

y <- sign(-1 - 2 * x1 + 4 * x2 )

y[ y == -1] <- 0

df <- cbind.data.frame( y, x1, x2)

mdl <- glm( y ~ . , data = df , family=binomial)

slope <- coef(mdl)[2]/(-coef(mdl)[3])
intercept <- coef(mdl)[1]/(-coef(mdl)[3])

library(lattice)
xyplot( x2 ~ x1 , data = df, groups = y,
panel=function(...){
panel.xyplot(...)
panel.abline(intercept , slope)
panel.grid(...)
})
``````

I must remark that perfect separation occurs here, therefore the `glm` function gives you a warning. But that is not important here as the purpose is to illustrate how to draw the linear boundary and the observations colored according to their covariates.