Nothing
plot.sum.intsearch <-function(x,type="summary",startN=21,...){
if(type=="summary"){
summary.int <- x
summary.int$info$log_lambda <- log(summary.int$info$lambda)
breaks <- do.breaks(range(summary.int$info$deviance), 20)
n_init <- 21 # number of initial alpha values at iteration zero
summary.int$info$cols <- level.colors(summary.int$info$deviance,at=breaks, col.regions = gray.colors)
n.features <- summary.int$info$n.features
print(my.plot <- xyplot(log_lambda ~ alpha,
data = summary.int$info,
groups = summary.int$info$cols,
cex = 1, cex.axis=1.5,
col = "black",
jitter.y=T, amount=0.01,
ylab=list(expression(paste("log ",lambda)),cex=1.5),
xlab=list(expression(alpha),cex=1.5),
# scales=list(x=list(log=T, equispaced.log = FALSE)), # x axis on log-scale
panel = function(x, y, groups, ..., subscripts) {
fill <- groups[subscripts]
panel.grid(h = -1, v = -1)
panel.abline(h = log(summary.int$opt.lambda),
v = summary.int$opt.alpha,
col="red", lty = 1, lwd=2 )
panel.xyplot(x, y, pch = rep(c(22,21),c(n_init,nrow(summary.int$info)-n_init)),
fill = fill, ...) ;
ltext(x=x, y=y, labels=n.features, pos=ifelse(y<0.1,3,4), offset=1.5, cex=1,col=1)
},
legend = list(top = list(fun = draw.colorkey,
args = list(key = list(space = "top",
col = gray.colors,
at = breaks),
draw = FALSE))),
main="Cross-validated partial log likelihood deviance",
scales=list(cex=1)
#sub="number of selected features are printed next to symbol \n rectangles show initial alpha values"
))
}
if(type=="points"){
# plot visited points vs. iteration steps
summary.int <- x
niter<- nrow(summary.int$info) - startN
iter<-c(rep(0,startN), c(1:niter))
plot(summary.int$info$alpha, iter, xlab=expression(alpha), ylab="Iteration", pch=20,cex=1.5,cex.axis=1.5)
grid(NA, niter+1, lwd=2)
abline(v=summary.int$opt.alpha, col="red")
}
}
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