Module: NumRuby::Linalg

Defined in:
lib/numruby/lapack.rb

Class Method Summary collapse

Class Method Details

.cholesky(matrix) ⇒ Object 



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# File 'lib/numruby/lapack.rb', line 130

def self.cholesky(matrix)

end

.cholesky_solve(matrix) ⇒ Object 



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# File 'lib/numruby/lapack.rb', line 134

def self.cholesky_solve(matrix)

end

.det(matrix) ⇒ Object 



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# File 'lib/numruby/lapack.rb', line 32

def self.det(matrix)
  if not matrix.is_a?(NMatrix)
    raise("Invalid matrix. Not of type NMatrix.")
  end
  if matrix.dim != 2
    raise("Invalid shape of matrix. Should be 2.")
  end
  if matrix.shape[0] != matrix.shape[1]
    raise("Invalid shape. Expected square matrix.")
  end

  return matrix.det
end

.diagsvd(matrix) ⇒ Object 



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# File 'lib/numruby/lapack.rb', line 122

def self.diagsvd(matrix)

end

.dot(lha, rha) ⇒ Object 



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# File 'lib/numruby/lapack.rb', line 20

def self.dot(lha, rha)
  lha.dot(rha)
end

.eig ⇒ Object 



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# File 'lib/numruby/lapack.rb', line 58

def self.eig

end

.eigh ⇒ Object 



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# File 'lib/numruby/lapack.rb', line 62

def self.eigh

end

.eigvalsh ⇒ Object 



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# File 'lib/numruby/lapack.rb', line 66

def self.eigvalsh

end

.inv(matrix) ⇒ Object 



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# File 'lib/numruby/lapack.rb', line 2

def self.inv(matrix)
  if not matrix.is_a?(NMatrix)
    raise("Invalid matrix. Not of type NMatrix.")
  end
  if matrix.dim != 2
    raise("Invalid shape of matrix. Should be 2.")
  end
  if matrix.shape[0] != matrix.shape[1]
    raise("Invalid shape. Expected square matrix.")
  end
  m, n = matrix.shape

  lu, ipiv = NumRuby::Lapack.getrf(matrix)
  inv_a = NumRuby::Lapack.getri(lu, ipiv)

  return inv_a
end

.kronecker_prod ⇒ Object 



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# File 'lib/numruby/lapack.rb', line 54

def self.kronecker_prod

end

.least_square ⇒ Object 



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# File 'lib/numruby/lapack.rb', line 46

def self.least_square

end

.lu(matrix, permute_l: False) ⇒ Object 



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# File 'lib/numruby/lapack.rb', line 73

def self.lu(matrix, permute_l: False)
  if not matrix.is_a?(NMatrix)
    raise("Invalid matrix. Not of type NMatrix.")
  end
  if matrix.dim != 2
    raise("Invalid shape of matrix. Should be 2.")
  end

  lu, ipiv = NumRuby::Linalg.getrf(matrix)

  # TODO: calulate p, l, u
end

.lu_factor(matrix) ⇒ Object 



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# File 'lib/numruby/lapack.rb', line 86

def self.lu_factor(matrix)
  if not matrix.is_a?(NMatrix)
    raise("Invalid matrix. Not of type NMatrix.")
  end
  if matrix.dim != 2
    raise("Invalid shape of matrix. Should be 2.")
  end
  if matrix.shape[0] != matrix.shape[1]
    raise("Invalid shape. Expected square matrix.")
  end

  lu, ipiv = NumRuby::Linalg.getrf(matrix)

  return [lu, ipiv]
end

.lu_solve(lu, ipiv, b, trans: 0) ⇒ Object 



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# File 'lib/numruby/lapack.rb', line 102

def self.lu_solve(lu, ipiv, b, trans: 0)
  if lu.shape[0] != b.shape[0]
    raise("Incompatibel dimensions.")
  end

  x = NumRuby::Lapack.getrs(lu, ipiv, b, trans)
  return x
end

.norm ⇒ Object 



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# File 'lib/numruby/lapack.rb', line 24

def self.norm

end

.orth(matrix) ⇒ Object 



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# File 'lib/numruby/lapack.rb', line 126

def self.orth(matrix)

end

.pinv ⇒ Object 



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# File 'lib/numruby/lapack.rb', line 50

def self.pinv

end

.qr(matrix, mode: "full", pivoting: false) ⇒ Object

Computes QR decomposition of a matrix.

Calculates the decomposition A = Q*R where Q is unitary/orthogonal and R is upper triangular.

Args:

  • matrix, type: NMatrix Matrix to be decomposed
  • mode, type: String Determines what information is to be returned: either both Q and R ('full', default), only R ('r') or both Q and R but computed in economy-size ('economic', see Notes). The final option 'raw' (added in Scipy 0.11) makes the function return two matrices (Q, TAU) in the internal format used by LAPACK.
  • pivoting, type: Boolean Whether or not factorization should include pivoting for rank-revealing qr decomposition. If pivoting, compute the decomposition AP = QR as above, but where P is chosen such that the diagonal of R is non-increasing.


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# File 'lib/numruby/lapack.rb', line 156

def self.qr(matrix, mode: "full", pivoting: false)
  if not ['full', 'r', 'economic', 'raw'].include?(mode.downcase)
    raise("Invalid mode. Should be one of ['full', 'r', 'economic', 'raw']")
  end
  if not matrix.is_a?(NMatrix)
    raise("Invalid matrix. Not of type NMatrix")
  end
  if matrix.dim != 2
    raise("Invalid shape of matrix. Should be 2.")
  end
  m, n = matrix.shape

  if pivoting == true
    qr, tau, jpvt = NumRuby::Lapack.geqp3(matrix)
    jpvt -= 1
  else
    qr, tau = NumRuby::Lapack.geqrf(matrix)
  end

  # calculate R here for both pivot true & false

  if ['economic', 'raw'].include?(mode.downcase) or m < n
    r = NumRuby.triu(matrix)
  else
    r = NumRuby.triu(matrix[0...n, 0...n])
  end

  if pivoting == true
    rj = r, jpvt
  else
    rj = r
  end

  if mode == 'r'
    return rj
  elsif mode == 'raw'
    return [qr, tau]
  end

  if m < n
    q = NumRuby::Lapack.orgqr(qr[0...m, 0...m], tau)
  elsif mode == 'economic'
    q = NumRuby::Lapack.orgqr(qr, tau)
  else
    # TODO: Implement slice view and set slice
    q = NumRuby::Lapack.orgqr(qr, tau)
  end

  return q, rj
end

.solve(a, b, sym_pos: False, lower: False, assume_a: "gen", transposed: False) ⇒ Object 



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# File 'lib/numruby/lapack.rb', line 28

def self.solve(a, b, sym_pos: False, lower: False, assume_a: "gen", transposed: False)
  # TODO: implement this and remove NMatrix.solve
end

.svd(matrix) ⇒ Object

Computes the SVD decomposition of matrix. Args:

  • input matrix, type: NMatrix


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# File 'lib/numruby/lapack.rb', line 114

def self.svd(matrix)

end

.svdvals(matrix) ⇒ Object 



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# File 'lib/numruby/lapack.rb', line 118

def self.svdvals(matrix)

end