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# Copyright (c) 2015 Santiago Barreda
# All rights reserved.
outlier.plot = function (x, y, category, xsampa = TRUE, logaxes = TRUE, ellipsesd = 2, borders = c(2,3), select = 0, nearest = 1){
ffs = as.matrix(cbind(x,y))
if (logaxes) ffs = log(ffs)
temp = createtemplate (ffs,category)
cs = as.factor(category)
lcs = levels (cs)
ncs = length (lcs)
type = as.numeric(cs)
tmp.env = environment()
dist = zeros(x)
for (i in 1:nrow(temp$means)){
use = (category == lcs[i])
dist[use] = mahalanobis (ffs[use,], temp$means[i,], cov (ffs[use,]))
}
dist = sqrt(dist)
cols = rep('', length(dist))
cols[dist<borders[1]] = 'forestgreen';
cols[dist>borders[1] & dist < borders[2]] = 'gold3';
cols[dist>borders[2]] = 'firebrick';
sizes = zeros(dist)
sizes[dist<borders[1]] = .5;sizes[dist>borders[1] & dist < borders[2]] = 1.2;sizes[dist>borders[2]] = 1.7;
#vns = c('x','y','category', 'xsampa', 'logaxes', 'sizes')
#vs = list(x,y,category, xsampa, logaxes, sizes)
#for (i in 1:6) assign (vns[i],vs[[i]],envir=.GlobalEnv)
oldpar = par()
par (mar = c(4.1,4.1,1,1))
vplot (x,y,category, xsampa = xsampa, logaxes = logaxes, cex = sizes, colors = cols,
xlab='Dimension 1',ylab='Dimension 2')
vplot (x,y,category, xsampa = xsampa, logaxes = logaxes, colors = 1,
add = TRUE, meansonly = TRUE, cex = 2.5)
for (i in 1:nrow(temp$means)){
if (!logaxes) sdellipse (cbind (x[cs==lcs[i]],y[cs==lcs[i]]),
stdev = ellipsesd, col = 1,lwd=2,lty='dotted')
if (logaxes){ tmp = sdellipse (log(cbind (x[cs==lcs[i]],y[cs==lcs[i]])),
stdev = ellipsesd, show = F); lines (exp(tmp), col = 1,
lwd=2,lty='dotted')}
}
suppressWarnings (par (oldpar))
if (select > 0){
coords = locator(select)
coords = log(as.matrix(cbind(coords$x,coords$y)))
siginv = solve (cov (ffs))
index = NULL
selection = NULL
closest = NULL
for (i in 1:select){
dists = mahalanobis (ffs, coords[i,], cov (ffs))
index = c(index, order(dists)[1:nearest])
selection = c(selection, rep(i, nearest))
closest = c(closest, 1:nearest)
}
return (data.frame (index, selection, closest))
}
}
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