Class: Kmeans::HCluster

Inherits:
Object
  • Object
show all
Defined in:
lib/kmeans/hcluster.rb

Instance Method Summary collapse

Constructor Details

#initialize ⇒ HCluster

Returns a new instance of HCluster.



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# File 'lib/kmeans/hcluster.rb', line 17

def initialize
  @out = ""
end

Instance Method Details

#hcluster(rows) ⇒ Object 



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# File 'lib/kmeans/hcluster.rb', line 39

def hcluster(rows)
  distances = Hash.new
  currentclustid = -1

  clust = Array.new
  for i in 0...rows.length
    c = Bicluster.new(rows[i])
    c.id = i
    clust.push(c)
  end

  while clust.length > 1
    lowestpair = [0,1]
    closest = 1 - Pearson.calc(clust[0].vec, clust[1].vec)
    for i in 0...clust.length
      for j in i+1...clust.length
        if !distances.key?([clust[i].id, clust[j].id])
          distances[[clust[i].id, clust[j].id]] = 1 - Pearson.calc(clust[i].vec, clust[j].vec)
        end
        d = distances[[clust[i].id, clust[j].id]]
        if d < closest
          closest = d
          lowestpair = [i,j]
        end
      end
    end

    mergevec = Array.new
    for i in 0...clust[0].vec.length
      m = (clust[lowestpair[0]].vec[i] + clust[lowestpair[1]].vec[i])/2.0
      mergevec.push(m)
    end

    newcluster = Bicluster.new(mergevec, clust[lowestpair[0]], clust[lowestpair[1]], closest, currentclustid)

    currentclustid -= 1
    clust.delete_at(lowestpair[1])
    clust.delete_at(lowestpair[0])
    clust.push(newcluster)
  end
  return clust[0]
end

#printclust(clust, labels = nil, n = 0) ⇒ Object 



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# File 'lib/kmeans/hcluster.rb', line 21

def printclust(clust, labels=nil, n=0)
  n.times do
     @out << " "
  end
  if clust.id < 0
    @out << "-\n"
  else
    if labels == nil
      @out << clust.id.to_s + "\n"
    else
      @out << labels[clust.id] + "\n"
    end
  end
  printclust(clust.left, labels, n+1) if clust.left != nil
  printclust(clust.right, labels, n+1) if clust.right != nil
  return @out
end