R: Contour plot for each component of a fitted bivariate mixture - r

Question

(Please note: I'm using R for only two days now.)
I have a dataset data that looks like this:
plot(data, pch=20, xlim=c(-2,3), ylim=c(-1,2))
I'm using the mixsmsn package to fit a mixture of bivariate skew-normal distributions:
sn2 <- smsn.mmix(data, nu=3, g=2, get.init=TRUE, criteria=TRUE, group=TRUE, family="Skew.normal", error=1e-08, iter.max=10000)
I can plot it like this (why pch=20 doesn't work?):
mix.contour(data, sn2, pch=20, xlim=c(-2,3), ylim=c(-1,2), levels=c(0.1,0.25,0.5))
How can I achieve the following?
I'd want to draw a contour separately for each component at half its height. That is, say it's a mixture distribution of the form p f_1(x,y) + (1-p) f_2(x,y) (f_i being the pdf of the _i_th skew-normal component); I'd want to draw (on a scatter plot) a contour of the f_1 component at half its height, and a second contour related to f_2 at half its height; I'd like the result to look like this:

Answer 1

Using the fMultivar package, I came up with this:
X <- data
sn2 <- smsn.mmix(X, nu=3, g=2, get.init=TRUE, criteria=TRUE, group=TRUE, family="Skew.normal", error=1e-08, iter.max=10000)
mu1 <- sn2$mu[[1]]
sigma1 <- sn2$Sigma[[1]]
alpha1 <- c(sn2$shape[[1]][1], sn2$shape[[1]][2])
p1 <- sn2$pii[[1]]
mu2 <- sn2$mu[[2]]
sigma2 <- sn2$Sigma[[2]]
alpha2 <- c(sn2$shape[[2]][1], sn2$shape[[2]][2])
p2 <- sn2$pii[[2]]
N <- 101
x <- seq(min(X[, 1]), max(X[, 1]), l=N)
y <- seq(min(X[, 2]), max(X[, 2]), l=N)
u <- grid2d(x, y)$x
v <- grid2d(x, y)$y
XY <- cbind(u, v)
Z1 <- matrix(p1*dmsn(XY, mu1, sigma1, alpha1), ncol=N)
Z2 <- matrix(p2*dmsn(XY, mu2, sigma2, alpha2), ncol=N)
c1 <- 0.5*max(Z1)
c2 <- 0.5*max(Z2)
plot(X, pch=20, xlim=c(-2,3), ylim=c(-1,2))
contour(x, y, Z1, add=TRUE, col="red", lwd=3, levels=c(c1), labels="")
contour(x, y, Z2, add=TRUE, col="green", lwd=3, levels=c(c2), labels="")