SVD Server Objects

SourcePro Analysis : Linear Algebra Module User’s Guide : Other Decompositions : Singular Value Decomposition : SVD Server Objects

SVD Server Objects

Sometimes, you may want more control over the computation of the singular value decomposition. For example, you might want to specify that only the left vectors are computed, or only the right vectors, or none at all. You might want to specify a tolerance indicating that singular values below a certain threshold are considered 0. You can control these aspects of the SVD object's construction by using a singular value server object. For example, the following program computes only the left singular vectors of A, and specifies that singular values less than 0.001 are to be treated as 0.

#include <iostream>

#include <rw/math/genmat.h>

#include <rw/lapack/lssv.h>

#include <rw/lapack/svddccalc.h>

int main()

{

RWGenMat<double> A; // 1

std::cin >> A;

RWSVServer< double, RWSVDDivConqCalc<double> > server; // 2

server.computeRightVectors(0);

server.setTolerance(0.001);

RWLeastSqSV< double, RWSVDDivConqCalc<double> > svd =

server(A); // 3

std::cout << "singular values: " // 4

<< svd.singularValues() << std::endl;

std::cout << "left vectors" << svd.leftVectors() << std::endl;

return 0;

}

//1 As before we define the matrix A and read it from standard input.

//2 In this line, a new server object is constructed. The parameters inside the server are initialized to their default values. In the next two lines, we change two of the parameters, setting the number of right singular vectors to compute to 0, and setting the tolerance to 0.001.

//3 This line constructs the singular value decomposition object using the server.

//4 As before, we print out the components of the decomposition.