H = Matrices.Utilities.toUpperHessenberg(A); (H, V, tau, info) = Matrices.Utilities.toUpperHessenberg(A,ilo, ihi);
Function toUpperHessenberg computes a upper Hessenberg form H of a matrix A by orthogonal similarity transformation: Q' * A * Q = H. The optional inputs ilo and ihi improve efficiency if the matrix is already partially converted to Hessenberg form; it is assumed that matrix A is already upper Hessenberg for rows and columns 1:(ilo-1) and (ihi+1):size(A, 1). The function calls LAPACK.dgehrd. See Matrices.LAPACK.dgehrd for more information about the additional outputs V, tau, info and inputs ilo, ihi.
A = [1, 2, 3; 6, 5, 4; 1, 0, 0]; H = toUpperHessenberg(A); results in: H = [1.0, -2.466, 2.630; -6.083, 5.514, -3.081; 0.0, 0.919, -0.514]
function toUpperHessenberg extends Modelica.Icons.Function; import Modelica.Math.Matrices; import Modelica.Math.Matrices.LAPACK; input Real A[:, size(A, 1)] "Square matrix A"; input Integer ilo = 1 "Lowest index where the original matrix is not in upper triangular form"; input Integer ihi = size(A, 1) "Highest index where the original matrix is not in upper triangular form"; output Real H[size(A, 1), size(A, 2)] "Upper Hessenberg form"; output Real V[size(A, 1), size(A, 2)] "V=[v1,v2,..vn-1,0] with vi are vectors which define the elementary reflectors"; output Real tau[max(0, size(A, 1) - 1)] "Scalar factors of the elementary reflectors"; output Integer info "Information of successful function call"; end toUpperHessenberg;