Plots with k-means

Eduardo,

Would you mind sending me the R code in an attached file. Your code didn't
work here and I am not sure it is because of line breaks from the email
program.

Iuri.

On Mon, Nov 2, 2009 at 10:53 AM, eduardo san miguel <

wrote:

Hello all,

I have almost finished the development of a new package where ideas
from Tamara Munzner, George Furnas and Costa and Venturini are
implemented.

1.- Da Costa, David & Venturini, Gilles (2006). An Interactive
Visualization Environment for Data Exploration Using Points of
Interest. adma 2006: 416-423

2.- Furnas, George (1986). Generalized Fisheye Views. Human Factors in
computing systems, CHI '86 conference proceedings, ACM, New York, pp.
16-23.

3.- Heidi Lam, Ronald A. Rensink, and Tamara Munzner (2006). Effects
of 2D Geometric Transformations on Visual Memory. Proc. Applied
Perception in Graphics and Visualization (APGV 2006), 119-126, 2006.

4.- Keith Lau, Ron Rensink, and Tamara Munzner (2004). Perceptual
Invariance of Nonlinear Focus+Context Transformations. Proc. First
Symposium on Applied Perception in Graphics and Visualization (APGV
04) 2004, pp 65-72.

This is a sample with some basic functionality and a VERY BASIC
example with kmeans plotting.

Comments will be greatly appreciated.

Regards

-- R CODE
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 at Pcoords <- value$Pcoords
                                  object at PcoordsFI <- value$PcoordsFI
                                  object at newPcoords <- value$newPcoords
                                  object at objeto <- value$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 at 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 at plotCol, mar = c(0.1,0.1,0.1,0.1), family = POI at itemsFamily)


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

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

           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 at objeto <- objeto
  poiCOPY at objetoC <- objetoC
  poiCOPY at newPcoords <- newPcoords
  poiCOPY at 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 at M = 1          # no fisheye distorsion
clusterPOI at matrizSim <- matrizSim
clusterPOI at wordsInQuery <- paste('"',
as.character(round(cl$centers[,1]),2),'"', '
size',as.character(cl$size))
POIcoords(clusterPOI) <- POICalc(clusterPOI
,length(clusterPOI at wordsInQuery))
clusterPOI at docs <-

cbind(matrix(seq(1:nrow(clusterPOI at objeto

clusterPOI at colores <- cl$cluster  + 1
clusterPOI at cos.query.docs <- rep(1, length(cl$cluster))
POI.env <<- new.env()
POIPlot(clusterPOI)