require(methods)

setClass(Class = 'POI', representation(matrizSim = 'matrix',cos.query.docs = 'vector', wordsInQuery = 'ANY',docs = 'matrix', objeto = 'matrix', objetoC = 'matrix', Pcoords = 'matrix', PcoordsFI = 'matrix', newPcoords = 'matrix', newcoords = 'numeric' , newcoords_1 = 'numeric', M = 'numeric', poisTextCol = 'character' , colores = 'vector' , poisCircleCol = 'character' , linesCol = 'character', itemsCol = 'character',  LABELS = 'logical', vscale = 'numeric', hscale = 'numeric', circleCol = 'character', plotCol = 'character', itemsFamily = 'character', lenteDefault = 'numeric', zoomDefault = 'numeric' , rateDefault = 'numeric' , topKDefault = 'numeric' , pal = 'character', selected = 'numeric' , circRadio = 'numeric' , IncVscale = 'numeric', cgnsphrFont = 'numeric', xClick_old = 'numeric', yClick_old = 'numeric', wordsInQueryFull = 'character' ), prototype(cos.query.docs = 0, colores = 0, newcoords = 0, newcoords_1 = 0, M = 3, vscale = 0.5 , hscale = 1.5 , circleCol = 'black' , itemsCol = 'white', poisTextCol = '#fff5ee', poisCircleCol = '#fff5ee', linesCol = 'white', plotCol = 'black', itemsFamily = 'sans', lenteDefault = 1, zoomDefault = 15 , rateDefault = 0.1 , topKDefault = 25, pal = 'topo' , selected = 1 , circRadio = 0.25 , IncVscale = 0.05 , cgnsphrFont = 1.01, LABELS = T) ) 

setGeneric("puntosMedios" , function(Pcoords, detalle = 5){standardGeneric("puntosMedios")})
setMethod("puntosMedios" , signature = "matrix", function(Pcoords, detalle = 5){ 
  for (i in 1:detalle){ 
new_pcoords = matrix(rep(0,4*nrow(Pcoords)), nrow = 2* nrow(Pcoords), byrow = T )
cont = 0
for (i in 1:nrow(Pcoords)){
if (i == nrow(Pcoords)) { 
		cont = cont + 1
		new_pcoords[cont,] = Pcoords[i,]
		cont = cont + 1
		new_pcoords[cont,] = Pcoords[i,] - ((Pcoords[i,]-Pcoords[1,])/2)
	}else{
		cont = cont + 1
		new_pcoords[cont,] = Pcoords[i,]
		cont = cont + 1
		new_pcoords[cont,] = Pcoords[i,] - ((Pcoords[i,]-Pcoords[i+1,])/2)}}
Pcoords = new_pcoords}
return(Pcoords)

}
)

setGeneric("fishIout" , function(x, value){standardGeneric ("fishIout")})

setMethod("fishIout" ,
signature = "numeric",
function(x, value){

d = value
	if (x > 0){
		signo = 1
	}else{
		signo = -1
	}
	x = abs(x)
	return(signo*(-(x/((d*x)-d-1))))
}
)

setGeneric("fishIin" ,
function(x, value){standardGeneric ("fishIin")})

setMethod("fishIin" ,
signature = "numeric",
function(x, value){

d = value
	if (x > 0){
		signo = 1
	}else{
		signo = -1
	}
	x = abs(x)

	return(signo*(((d+1)*x)/(d*x+1)))
}
)

setGeneric("toPolar" ,
function(x, y){standardGeneric ("toPolar")})

setMethod("toPolar" ,
signature = "numeric",
function(x, y){

	t1 = atan2(y,x)
	rP = sqrt(x^2+y^2)
	return(c(t1 = t1,rP = rP))

}
)

setGeneric("toCartesian" ,
function(t1, rP){standardGeneric ("toCartesian")})

setMethod("toCartesian" ,
signature = "numeric",
function(t1, rP){

	x1 = rP*cos(t1)
	y1 = rP*sin(t1)
	return(c(x = x1,y = y1))

}
)

setGeneric("circulo" ,
function(cx, cy, r, circleCol, PLOT =
TRUE){standardGeneric ("circulo")})

setMethod("circulo" ,
signature = "numeric",
function(cx, cy, r, circleCol, PLOT = TRUE){
	t = seq(0,2*pi,length=100)
	circle = t(rbind(cx+sin(t)*r,cy+cos(t)*r))
	if (PLOT == TRUE) plot(circle,type='l',,ylim=c(-1.15,1.15),xlim=c(-1.15,1.15),
		ann=FALSE, axes=F, col = circleCol)
	return(circle)

}
)

setGeneric("circulin" ,
function(cx, cy, r = 0.045,
objeto, col = 'blue', PLOT = TRUE, label = 0){
standardGeneric ("circulin")})

setMethod("circulin" ,
signature = "ANY",
function(cx, cy, r = 0.045, objeto, col = 'blue', PLOT =
TRUE, label = 0){

	t = seq(0,2*pi,length=100)
	circle = t(rbind(cx+sin(t)*r,cy+cos(t)*r))
	points(circle,type='l', col = col)
	if (label != 0) text(cx,cy,label,cex = .7)
	insiders <- apply(objeto,1,function(co)(cx-co[1])^2+(cy-co[2])^2<r^2)
assign('insiders', insiders , envir = POI.env)

}
)

setGeneric("addNoise" ,
function(m, tamanyo = 0.01){standardGeneric ("addNoise")})

setMethod("addNoise" ,
signature = "matrix",
function(m, tamanyo = 0.01){

	noise = function(m, t = tamanyo){
		ruido = rnorm(length(m), 0,t)
		return(m+ruido)
	}
	noised = noise(m)
	unicos = which(duplicated(m) == FALSE)
	m[-unicos,] = noised[-unicos,]
	return(m)

}
)

setGeneric("toHiperbolico" ,
function(objeto, M = 1 , cx = 0, cy = 0, r = 1){
standardGeneric ("toHiperbolico")})

setMethod("toHiperbolico" ,
signature = "matrix",
function(objeto, M = 1 , cx = 0, cy = 0, r = 1){

	insiders = apply(objeto,1,function(co)(cx-co[1])^2+(cy-co[2])^2<r^2)
	outers = which(insiders < 1)
	objetoP = matrix(toPolar(objeto[,1],objeto[,2]),nc=2)
	if (length(outers)){
			objetoP[outers,2] = 1
	}
	objetoP[,2] = sapply(objetoP[,2],fishIin,M)
	objetoC = matrix(toCartesian(objetoP[,1],objetoP[,2]),nc=2)
return(list(objetoC = objetoC,
objetoP = objetoP))

}
)

setGeneric("POIcoords<-" , function(object, value){standardGeneric("POIcoords<-")})

setReplaceMethod( f ="POIcoords",
signature = 'POI',
definition = function(object, value){
object@Pcoords <- value$Pcoords
object@PcoordsFI <- value$PcoordsFI
object@newPcoords <- value$newPcoords
object@objeto <- value$objeto

return(object)
}
)

setGeneric("POICalc" ,
function(objeto, NC, cx=0, cy=0, r=1,
...){standardGeneric ("POICalc")})

setMethod("POICalc" ,
signature = "POI",
function(objeto, NC, cx=0, cy=0, r=1, ...){

MatrizSim = objeto@matrizSim
secuencia = seq(2/NC,2,2/NC)
Pcoords = matrix(rep(0,NC*2),nc=2)
n = 1
for (i in secuencia){
Pcoords[n,] = c(r * cos(i*pi), r * sin(i*pi))
n = n+1
}
PcoordsFI = matrix(toPolar(Pcoords[,1],Pcoords[,2]),nc=2)
PcoordsFI[,2] = PcoordsFI[,2]+.15
PcoordsFI = matrix(toCartesian(PcoordsFI[,1],PcoordsFI[,2]),nc=2)

if (nrow(Pcoords) != 1){
newPcoords = puntosMedios(Pcoords)
} else {
newPcoords = Pcoords
}

MatrizSim[is.nan(MatrizSim/rowSums(MatrizSim))] <- 0

W = MatrizSim / rowSums(MatrizSim)
W[is.nan(W)] <- 0
nwords = nrow(W)
objeto = matrix(rep(0,2*nwords),nc=2)
for (j in 1:nwords){
for (nPOI in 1:NC){
objeto[j,1] = objeto[j,1]+(W[j,nPOI]*Pcoords[nPOI,1])
objeto[j,2] = objeto[j,2]+(W[j,nPOI]*Pcoords[nPOI,2])
}
}

objeto = addNoise(objeto)

return(list(Pcoords = Pcoords,
PcoordsFI = PcoordsFI,
newPcoords = newPcoords,
objeto = objeto))

}
)

setGeneric("POIPlot" ,
function(POI){standardGeneric ("POIPlot")})

setMethod("POIPlot" ,
signature = "POI",
function(POI){

par(bg=POI@plotCol, mar = c(0.1,0.1,0.1,0.1), family = POI@itemsFamily)


if (exists('POI.env')) {
if (exists('POI', envir = POI.env)) {
POI <- get('POI', envir = POI.env)
}
}

selected = POI@selected
objeto = POI@objeto
newcoords = POI@newcoords
newcoords_1 = POI@newcoords_1
NC = length(POI@wordsInQuery)
cx=0
cy=0
r=1
etiq2 = POI@docs[,1]
etiq = POI@wordsInQuery
fishEYE = TRUE
M = POI@M
poisTextCol = POI@poisTextCol
colores = POI@colores[POI@docs]
poisCircleCol = POI@poisCircleCol
linesCol = POI@linesCol
itemsCol = POI@itemsCol
circleCol = POI@circleCol
LABELS = POI@LABELS
Pcoords = POI@Pcoords
newPcoords = POI@newPcoords
cgnsphrFont = POI@cgnsphrFont

newcoords_par = newcoords

newcoords_Pcoords = matrix(rep( c(newcoords,newcoords_1 ),
nrow(Pcoords)),nc=2,byrow=TRUE)

newcoords_puntosMediosPcoords = matrix(rep( c(newcoords,newcoords_1),
nrow(newPcoords)),nc=2,byrow=TRUE)

newcoords = matrix(rep( c(newcoords,newcoords_1),
nrow(objeto)),nc=2,byrow=TRUE)

objeto = objeto+newcoords
objetoH = toHiperbolico(objeto, M)
objetoC = objetoH$objetoC
objetoP = objetoH$objetoP

Pcoords = Pcoords + newcoords_Pcoords
PcoordsH = toHiperbolico(Pcoords, M)
PcoordsC = PcoordsH$objetoC
PcoordsP = PcoordsH$objetoP

newPcoords = newPcoords + newcoords_puntosMediosPcoords
newPcoordsH = toHiperbolico(newPcoords, M)
Pcoords_objetoC = newPcoordsH$objetoC

if (LABELS) {
PcoordsFI = matrix(toPolar(PcoordsC[,1],PcoordsC[,2]),nc=2)
PcoordsFI[,2] = 1 +.15
PcoordsFI = matrix(toCartesian(PcoordsFI[,1],PcoordsFI[,2]),nc=2)
}

plot(circulo(0,0,1, circleCol, PLOT =
FALSE),cex=.5,ylim=c(-1.15,1.15),xlim=c(-1.15,1.15),
ann=FALSE, axes=F,type='l', col = circleCol)

points(objetoC, pch=19, col = colores, cex = 1.5 - objetoP[,2])

text(objetoC[,1], objetoC[,2], labels = etiq2, cex = cgnsphrFont - objetoP[,2],
pos = 3, col = itemsCol)

abline(h = cx, col = 'grey', lty = 'dashed')
abline(v = cy, col = 'grey', lty = 'dashed')


points(PcoordsC,cex = 2, col = poisCircleCol)

lines(Pcoords_objetoC, col = linesCol)

segments(Pcoords_objetoC[nrow(Pcoords_objetoC),1],Pcoords_objetoC[nrow(Pcoords_objetoC),2],
Pcoords_objetoC[1,1],Pcoords_objetoC[1,2], col = linesCol)

if (LABELS) {
text(PcoordsFI[,1],PcoordsFI[,2],toupper(etiq),cex=.75, col = poisTextCol)
}

if (selected != 1) {
circulin(0,0, .5, objeto = objetoC) # probando
}

if (!exists('POI.env')){
POI.env <<- new.env()
}
poiCOPY = POI
poiCOPY@objeto <- objeto
poiCOPY@objetoC <- objetoC
poiCOPY@newPcoords <- newPcoords
poiCOPY@Pcoords <- Pcoords
assign('POI',poiCOPY , envir = POI.env)

}
)


# *strong*VERY*strong* basic kmeans example with 6 clusters and 10 variables
x <- matrix(rnorm(100, mean = 1, sd = .3), ncol = 10)
x <- rbind(x,matrix(rnorm(200, mean = 5, sd = .3), ncol = 10))
x <- rbind(x,matrix(rnorm(100, mean = 10, sd = .3), ncol = 10))
x <- rbind(x,matrix(rnorm(100, mean = 15, sd = .3), ncol = 10))
x <- rbind(x,matrix(rnorm(200, mean = 20, sd = .3), ncol = 10))
x <- rbind(x,matrix(rnorm(100, mean = 25, sd = .3), ncol = 10))

cl <- kmeans(x, 6, iter.max = 100 ,nstart = 25)

# *strong*VERY*strong* basic way of reordering cluster 
# output for better plotting
# here we reorder using just the first cluster
reorder.cl <- as.numeric(names(sort(rank((as.matrix(dist(cl$centers,
diag = T)))[,1]))))
cl$centers <- cl$centers[reorder.cl, ]
cl$size <- cl$size[reorder.cl]

# distance matrix between each element and its cluster center
matrizSim = matrix(rep(0, nrow(cl$centers) * nrow(x)), ncol = nrow(cl$centers))
for (n in 1:nrow(cl$centers)){
for (i in 1:nrow(x)) {
a = x[i,]
b = cl$centers[n,]
matrizSim[[i,n]] = dist(rbind(a,b)) # eucl dist
}
}

# From dist to similarity (0 - 1)
matrizSim = 1 - (matrizSim / rowSums(matrizSim) )
# exagerate similarity
matrizSim = matrizSim^3

# Create POI plot
clusterPOI = new('POI')
clusterPOI@M = 1 # no fisheye distorsion
clusterPOI@matrizSim <- matrizSim
clusterPOI@wordsInQuery <- paste('"', as.character(round(cl$centers[,1]),2),'"', 'size',as.character(cl$size))
POIcoords(clusterPOI) <- POICalc(clusterPOI ,length(clusterPOI@wordsInQuery))
clusterPOI@docs <- 
cbind(matrix(seq(1:nrow(clusterPOI@objeto))),matrix(seq(1:nrow(clusterPOI@objeto))))
clusterPOI@colores <- cl$cluster + 1
clusterPOI@cos.query.docs <- rep(1, length(cl$cluster))
POI.env <<- new.env()
POIPlot(clusterPOI)