Class: Clusterer::DMatrix

Inherits:
Matrix
  • Object
show all
Defined in:
lib/clusterer/lsi/dmatrix.rb

Class Method Summary collapse

Instance Method Summary collapse

Class Method Details

.join_columns(columns) ⇒ Object 



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# File 'lib/clusterer/lsi/dmatrix.rb', line 105

def self.join_columns(columns)
  DMatrix[*columns.collect {|c| [*c] }].transpose
end

.join_rows(rows) ⇒ Object 



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# File 'lib/clusterer/lsi/dmatrix.rb', line 94

def self.join_rows(rows)
  DMatrix[*rows.collect {|r| [*r] }]
end

Instance Method Details

#[]=(i, j, val) ⇒ Object 



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# File 'lib/clusterer/lsi/dmatrix.rb', line 90

def []=(i,j,val)
  @rows[i][j] = val
end

#svd ⇒ Object

algorithm description from “Simple Algoritms for the partial singular value decomposition” by J. C. Nash and S. Shlien Plane rotation method there were some typos in the original algorithm in the paper also see the Pascal code in NashSVD, file alg01.pas; for an idea the partial algorithm is an adaptation of that algo



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# File 'lib/clusterer/lsi/dmatrix.rb', line 32

def svd
  m, n = self.row_size, self.column_size
  tol =  0.001
  slimit = [n/4.to_i, 6].max
  u, z, v = DMatrix[*(1..m).to_a.collect {|i| Array.new(n,0) }], Array.new(n), DMatrix.diagonal(*Array.new(n,1))

  nt = n
  slimit.times do
    rcount = nt *(nt-1)/2
    (nt-1).times do |j|
      (j+1).upto(nt - 1) do |k|
        p=q=r=0
        m.times do |i|
          p += self[i,j]*self[i,k]
          q += self[i,j]*self[i,j]
          r += self[i,k]*self[i,k]
        end
        z[j], z[k] = q, r
        if q < r
          p, q = p/r, q/r - 1
          vt = Math.sqrt(4*p*p + q*q)
          s = Math.sqrt(0.5*(1 - q/vt))
          s = -s if p < 0
          c = p / (vt*s)
        elsif  (q * r <= tol * tol) || (p/q)*(p/r) <= tol
          rcount -= 1
          next
        else
          p, r = p/q, 1 - r/q
          vt = Math.sqrt(4*p*p + r*r)
          c = Math.sqrt(0.5*(1 + r/vt))
          s = p/(vt * c)
        end
        m.times do |i|
          r = self[i,j]
          self[i,j] = c * r + s * self[i,k]
          self[i,k] = -s*r + c * self[i,k]
        end
        n.times do |i|
          r = v[i,j]
          v[i,j] = c * r + s * v[i,k] #typo in paper replace r by s 
          v[i,k] = -s*r + c * v[i,k]  #typo in paper replace A(i,k) by v(i,k)
        end
      end
    end
    until nt < 3 || z[nt-1]/(z[0] + tol) > tol
      nt -= 1
    end
    break unless rcount > 0
  end
  nt.times do |j|
    z[j] = Math.sqrt(z[j])
    m.times {|i| u[i,j] = self[i,j]/z[j] }
  end
  z = DMatrix.diagonal(*z)
  return u, z, v.transpose
end

#transpose ⇒ Object 



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# File 'lib/clusterer/lsi/dmatrix.rb', line 98

def transpose
  x = super
  y = DMatrix[]
  y.instance_variable_set("@rows",x.instance_variable_get("@rows"))
  y
end