R/spectralClustering.r

In pfruan/abSNF: Using Association Signal Annotations to boost Similarity Network Fusion

spectralClustering <- function(affinity, K, type=3) {

  ###This function implements the famous spectral clustering algorithms. There are three variants. The default one is the third type.
  ###THe inputs are as follows:

      #affinity: the similarity matrix;
      #K: the number of clusters
      # type: indicators of variants of spectral clustering

  d = rowSums(affinity)
  d[d == 0] = .Machine$double.eps
  D = diag(d)
  L = D - affinity
  if (type == 1) {
    NL = L
  } else if (type == 2) {
    Di = diag(1 / d)
    NL = Di %*% L
  } else if(type == 3) {
    Di = diag(1 / sqrt(d))
    NL = Di %*% L %*% Di
  }
  eig = eigen(NL)
  res = sort(abs(eig$values),index.return = TRUE)
  U = eig$vectors[,res$ix[1:K]]
  normalize <- function(x) x / sqrt(sum(x^2))
  if (type == 3) {
    U = t(apply(U,1,normalize))
  }
  eigDiscrete = .discretisation(U)
  eigDiscrete = eigDiscrete$discrete
  labels = apply(eigDiscrete,1,which.max)



  return(labels)
}