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Extend sparseqr unit test to check linearly dependent columns

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This commit is contained in:
Gael Guennebaud 2013-02-24 20:36:54 +01:00
parent 4eeaff6d38
commit 1c137496c6
1 changed files with 27 additions and 7 deletions
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34
test/sparseqr.cpp
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@ -22,15 +22,25 @@ int generate_sparse_rectangular_problem(MatrixType& A, DenseMat& dA, int maxRows
dA.resize(rows,rows);
initSparse<Scalar>(density, dA, A,ForceNonZeroDiag);
A.makeCompressed();
int nop = internal::random<int>(0, internal::random<double>(0,1) > 0.5 ? cols/2 : 0);
for(int k=0; k<nop; ++k)
{
int j0 = internal::random<int>(0,cols-1);
int j1 = internal::random<int>(0,cols-1);
Scalar s = internal::random<Scalar>();
A.col(j0) = s * A.col(j1);
dA.col(j0) = s * dA.col(j1);
}
return rows;
}
template<typename Scalar> void test_sparseqr_scalar()
{
typedef SparseMatrix<Scalar,ColMajor> MatrixType;
MatrixType A;
Matrix<Scalar,Dynamic,Dynamic> dA;
typedef Matrix<Scalar,Dynamic,Dynamic> DenseMat;
typedef Matrix<Scalar,Dynamic,1> DenseVector;
MatrixType A;
DenseMat dA;
DenseVector refX,x,b;
SparseQR<MatrixType, AMDOrdering<int> > solver;
generate_sparse_rectangular_problem(A,dA);
@ -50,13 +60,23 @@ template<typename Scalar> void test_sparseqr_scalar()
std::cerr << "sparse QR factorization failed\n";
exit(0);
return;
}
}
//Compare with a dense QR solver
refX = dA.colPivHouseholderQr().solve(b);
VERIFY(x.isApprox(refX,test_precision<Scalar>()));
ColPivHouseholderQR<DenseMat> dqr(dA);
refX = dqr.solve(b);
VERIFY_IS_EQUAL(dqr.rank(), solver.rank());
if(solver.rank()<A.cols())
VERIFY((dA * refX - b).norm() * 2 > (A * x - b).norm() );
else
VERIFY_IS_APPROX(x, refX);
}
void test_sparseqr()
{
CALL_SUBTEST_1(test_sparseqr_scalar<double>());
CALL_SUBTEST_2(test_sparseqr_scalar<std::complex<double> >());
for(int i=0; i<g_repeat; ++i)
{
CALL_SUBTEST_1(test_sparseqr_scalar<double>());
CALL_SUBTEST_2(test_sparseqr_scalar<std::complex<double> >());
}
}