LinearProgram::Result MinNormProblem_Sparse::Solve(Vector& x)
{
if(norm == 2) {
Assert(IsValid());
if(HasInequalities()) { //must use quadratic program for inequalities
FatalError("Sparse QP not done yet");
return LinearProgram::Error;
}
else if(A.m != 0) { //no inequality constraints, just equality
FatalError("Sparse LS with equality constraints not done yet");
return LinearProgram::Error;
}
else {
LSQRInterface lsqr;
if(!lsqr.Solve(C,d)) {
cout<<"Error solving for least squares!!!"<<endl;
return LinearProgram::Error;
}
x = lsqr.x;
return LinearProgram::Feasible;
}
}
else {
RobustLPSolver lps;
lps.verbose = verbose;
LinearProgram::Result res= lps.Solve(lp);
if(res==LinearProgram::Feasible) {
x.resize(C.n);
lps.xopt.getSubVectorCopy(0,x);
}
return res;
}
}
void TestLSQR(const SparseMatrix& A,const Vector& b)
{
Matrix mA;
Vector x,temp;
A.get(mA);
x.resize(A.n);
temp.resize(A.n);
LSQRInterface lsqr;
if(!lsqr.Solve(A,b)) {
cout<<"Failed LSQR solve!"<<endl;
cout<<"A="<<endl;
cout<<MatrixPrinter(mA)<<endl;
cout<<"b="<<VectorPrinter(b)<<endl;
return;
}
x=lsqr.x;
MatrixEquation eq(mA,b);
if(!eq.LeastSquares_Cholesky(temp)) {
cout<<"Failed cholesky solve!"<<endl;
cout<<"A="<<endl;
cout<<MatrixPrinter(mA)<<endl;
cout<<"b="<<VectorPrinter(b)<<endl;
return;
}
if(!x.isEqual(temp,1e-3)) {
cout<<"Results differ!"<<endl;
cout<<"LSQR: "<<VectorPrinter(x)<<endl;
cout<<"Cholesky: "<<VectorPrinter(temp)<<endl;
}
}