library(rpart)

Z.rp.t <- predict(Z.rp, pt ) 

zp.rp <- Z.rp.t[,1]-Z.rp.t[,2]
plot(TrainC[, 1], TrainC[, 2], xlab = "x1", ylab = "x2", col=codes(TrainC$y)+1)
title("RP TrainC")
contour(xp, yp, matrix(zp.rp, np), add = T, levels = 0, labex = 0)
   
TestC <- read.table("ExamC.dat")
names(TestC)<-c("x1","x2","y")
N <- length(TestC[,1])

xp <- seq(min(TestC$x1), max(TestC$x1), length = 50); np <- length(xp)
yp <- seq(min(TestC$x2), max(TestC$x2), length = 50)
pt <- expand.grid(x1 = xp, x2 = yp)

plot(TestC[, 1], TestC[, 2], xlab = "x1", ylab = "x2", col=codes(TestC$y)+1)
title("RP ExamC")

Z.rp <- rpart(y ~ x1 + x2, data=TestC)
T.rp.t <- predict(Z.rp, pt ) 
zp.rp <- T.rp.t[,1]-T.rp.t[,2]
contour(xp, yp, matrix(zp.rp, np), add = T, levels = 0, labex = 0)