R/dist.Symbolic.r

In clusterSim: Searching for Optimal Clustering Procedure for a Data Set

dist.Symbolic<-function(data,type="U_2",gamma=0.5,power=2){
  indivIC<-data
  individualsNo<-dim(data)[1]
  variablesNo<-dim(data)[2]
  variableSelection=(1:variablesNo)
  distS<-array(0,c(individualsNo,individualsNo))
  if (type=="U_2"){
    for (i in 1:(individualsNo-1))
      for (j in (i+1):individualsNo)
      {
        D<-0
        for(k in variableSelection)
        {
          d<-(max(indivIC[i,k,2],indivIC[j,k,2])-min(indivIC[i,k,1],indivIC[j,k,1]))
          if (!((indivIC[i,k,2]<=indivIC[j,k,1]) || (indivIC[j,k,2]<=indivIC[i,k,1])))
          {
            if (indivIC[i,k,1]<=indivIC[j,k,1])
            {
              if (indivIC[i,k,2]<=indivIC[j,k,2])
                d<-d-(1-2*gamma)*abs(indivIC[i,k,2]-indivIC[j,k,1])
              else
                d<-d-(1-2*gamma)*abs(indivIC[j,k,2]-indivIC[j,k,1])
            }
            else
            {
              if (indivIC[j,k,2]<=indivIC[i,k,2])
                d<-d-(1-2*gamma)*abs(indivIC[j,k,2]-indivIC[i,k,1])
              else
                d<-d-(1-2*gamma)*abs(indivIC[i,k,2]-indivIC[i,k,1])
            }
          } 
          d<-d-gamma*abs(indivIC[j,k,2]-indivIC[j,k,1])
          d<-d-gamma*abs(indivIC[i,k,2]-indivIC[i,k,1])
          D<-D+d^power
        }
        distS[i,j]<-D^(1/power)		
        distS[j,i]<-distS[i,j]
      }
    resul<-as.dist(distS)
  }
  if (type=="M")
  {
    xmean<-array(0,c(dim(data)[1],dim(data)[2]))
    for (i in 1:dim(data)[1])
    {
      xmean[i,]<-apply(data[i,,],2,"mean")
      
    }
    resul<-dist(xmean,method="minkowski",p=power)
  }
  if (type=="H" || type=="S")
  {
    zmienne<-0
    zmienne<-dim(data)[2]
    for (i in 1:(individualsNo-1))
      for (j in (i+1):individualsNo)
      {
        if (type=="S")
        {
          distS[j,i]<-2^(zmienne-1)*(dist(rbind(data[i,,1],data[j,,1]))^2+dist(rbind(data[i,,2],data[j,,2]^2)))
          distS[i,j]<-distS[j,i]
        }
        
        if (type=="H")
        {
          s<-0
          for (k in 1:zmienne)
          {
            s<-s+max(c(abs(data[i,k,1]-data[j,k,1]),abs(data[i,k,2]-data[j,k,2])))^power
          }
          distS[i,j]<-distS[j,i]<-s^(1/power)
        }			
      }
    resul<-as.dist(distS)
  }
  resul
}