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Rework JacobiSVD api / template parameters.

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There is now an integer QRPreconditioner template parameter, defaulting to full-piv QR.
Since we have to special-case each QR dec anyway, a template template parameter didn't add much value here.
There is an option NoQRPreconditioner if you know your matrices are already square (auto-detected for fixed-size matrices).
This commit is contained in:
Benoit Jacob
2010-10-08 10:42:32 -04:00
parent 58e0cce0f7
commit 6fad2eb97b
4 changed files with 242 additions and 169 deletions
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37
test/jacobisvd.cpp
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@@ -27,7 +27,8 @@
#include <Eigen/SVD>
#include <Eigen/LU>
template<typename MatrixType, unsigned int Options> void svd(const MatrixType& m = MatrixType(), bool pickrandom = true)
template<typename MatrixType, int QRPreconditioner>
void svd_with_qr_preconditioner(const MatrixType& m = MatrixType(), bool pickrandom = true)
{
typedef typename MatrixType::Index Index;
Index rows = m.rows();
@@ -49,7 +50,7 @@ template<typename MatrixType, unsigned int Options> void svd(const MatrixType& m
if(pickrandom) a = MatrixType::Random(rows,cols);
else a = m;
JacobiSVD<MatrixType,Options> svd(a);
JacobiSVD<MatrixType, QRPreconditioner> svd(a, ComputeU|ComputeV);
MatrixType sigma = MatrixType::Zero(rows,cols);
sigma.diagonal() = svd.singularValues().template cast<Scalar>();
MatrixUType u = svd.matrixU();
@@ -63,11 +64,19 @@ template<typename MatrixType, unsigned int Options> void svd(const MatrixType& m
VERIFY_IS_UNITARY(v);
}
template<typename MatrixType>
void svd(const MatrixType& m = MatrixType(), bool pickrandom = true)
{
svd_with_qr_preconditioner<MatrixType, FullPivHouseholderQRPreconditioner>(m, pickrandom);
svd_with_qr_preconditioner<MatrixType, ColPivHouseholderQRPreconditioner>(m, pickrandom);
svd_with_qr_preconditioner<MatrixType, HouseholderQRPreconditioner>(m, pickrandom);
}
template<typename MatrixType> void svd_verify_assert()
{
MatrixType tmp;
SVD<MatrixType> svd;
JacobiSVD<MatrixType> svd;
//VERIFY_RAISES_ASSERT(svd.solve(tmp, &tmp))
VERIFY_RAISES_ASSERT(svd.matrixU())
VERIFY_RAISES_ASSERT(svd.singularValues())
@@ -84,24 +93,24 @@ void test_jacobisvd()
Matrix2cd m;
m << 0, 1,
0, 1;
CALL_SUBTEST_1(( svd<Matrix2cd,0>(m, false) ));
CALL_SUBTEST_1(( svd(m, false) ));
m << 1, 0,
1, 0;
CALL_SUBTEST_1(( svd<Matrix2cd,0>(m, false) ));
CALL_SUBTEST_1(( svd(m, false) ));
Matrix2d n;
n << 1, 1,
1, -1;
CALL_SUBTEST_2(( svd<Matrix2d,0>(n, false) ));
CALL_SUBTEST_3(( svd<Matrix3f,0>() ));
CALL_SUBTEST_4(( svd<Matrix4d,Square>() ));
CALL_SUBTEST_5(( svd<Matrix<float,3,5> , AtLeastAsManyColsAsRows>() ));
CALL_SUBTEST_6(( svd<Matrix<double,Dynamic,2> , AtLeastAsManyRowsAsCols>(Matrix<double,Dynamic,2>(10,2)) ));
CALL_SUBTEST_2(( svd(n, false) ));
CALL_SUBTEST_3(( svd<Matrix3f>() ));
CALL_SUBTEST_4(( svd<Matrix4d>() ));
CALL_SUBTEST_5(( svd<Matrix<float,3,5> >() ));
CALL_SUBTEST_6(( svd<Matrix<double,Dynamic,2> >(Matrix<double,Dynamic,2>(10,2)) ));
CALL_SUBTEST_7(( svd<MatrixXf,Square>(MatrixXf(50,50)) ));
CALL_SUBTEST_8(( svd<MatrixXcd,AtLeastAsManyRowsAsCols>(MatrixXcd(14,7)) ));
CALL_SUBTEST_7(( svd<MatrixXf>(MatrixXf(50,50)) ));
CALL_SUBTEST_8(( svd<MatrixXcd>(MatrixXcd(14,7)) ));
}
CALL_SUBTEST_9(( svd<MatrixXf,0>(MatrixXf(300,200)) ));
CALL_SUBTEST_10(( svd<MatrixXcd,AtLeastAsManyColsAsRows>(MatrixXcd(100,150)) ));
CALL_SUBTEST_9(( svd<MatrixXf>(MatrixXf(300,200)) ));
CALL_SUBTEST_10(( svd<MatrixXcd>(MatrixXcd(100,150)) ));
CALL_SUBTEST_3(( svd_verify_assert<Matrix3f>() ));
CALL_SUBTEST_3(( svd_verify_assert<Matrix3d>() ));