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Diffstat (limited to 'test/jacobisvd.cpp')
-rw-r--r-- | test/jacobisvd.cpp | 105 |
1 files changed, 105 insertions, 0 deletions
diff --git a/test/jacobisvd.cpp b/test/jacobisvd.cpp new file mode 100644 index 000000000..9a4d79e45 --- /dev/null +++ b/test/jacobisvd.cpp @@ -0,0 +1,105 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr> +// Copyright (C) 2009 Benoit Jacob <jacob.benoit.1@gmail.com> +// +// Eigen is free software; you can redistribute it and/or +// modify it under the terms of the GNU Lesser General Public +// License as published by the Free Software Foundation; either +// version 3 of the License, or (at your option) any later version. +// +// Alternatively, you can redistribute it and/or +// modify it under the terms of the GNU General Public License as +// published by the Free Software Foundation; either version 2 of +// the License, or (at your option) any later version. +// +// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY +// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS +// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the +// GNU General Public License for more details. +// +// You should have received a copy of the GNU Lesser General Public +// License and a copy of the GNU General Public License along with +// Eigen. If not, see <http://www.gnu.org/licenses/>. + +#include "main.h" +#include <Eigen/SVD> +#include <Eigen/LU> + +template<typename MatrixType> void svd(const MatrixType& m, bool pickrandom = true) +{ + int rows = m.rows(); + int cols = m.cols(); + + enum { + RowsAtCompileTime = MatrixType::RowsAtCompileTime, + ColsAtCompileTime = MatrixType::ColsAtCompileTime + }; + + typedef typename MatrixType::Scalar Scalar; + typedef typename NumTraits<Scalar>::Real RealScalar; + typedef Matrix<Scalar, RowsAtCompileTime, RowsAtCompileTime> MatrixUType; + typedef Matrix<Scalar, ColsAtCompileTime, ColsAtCompileTime> MatrixVType; + typedef Matrix<Scalar, RowsAtCompileTime, 1> ColVectorType; + typedef Matrix<Scalar, ColsAtCompileTime, 1> InputVectorType; + + MatrixType a; + if(pickrandom) a = MatrixType::Random(rows,cols); + else a = m; + + JacobiSVD<MatrixType> svd(a); + MatrixType sigma = MatrixType::Zero(rows,cols); + sigma.diagonal() = svd.singularValues().template cast<Scalar>(); + MatrixUType u = svd.matrixU(); + MatrixVType v = svd.matrixV(); + + VERIFY_IS_APPROX(a, u * sigma * v.adjoint()); + VERIFY_IS_UNITARY(u); + VERIFY_IS_UNITARY(v); +} + +template<typename MatrixType> void svd_verify_assert() +{ + MatrixType tmp; + + SVD<MatrixType> svd; + //VERIFY_RAISES_ASSERT(svd.solve(tmp, &tmp)) + VERIFY_RAISES_ASSERT(svd.matrixU()) + VERIFY_RAISES_ASSERT(svd.singularValues()) + VERIFY_RAISES_ASSERT(svd.matrixV()) + /*VERIFY_RAISES_ASSERT(svd.computeUnitaryPositive(&tmp,&tmp)) + VERIFY_RAISES_ASSERT(svd.computePositiveUnitary(&tmp,&tmp)) + VERIFY_RAISES_ASSERT(svd.computeRotationScaling(&tmp,&tmp)) + VERIFY_RAISES_ASSERT(svd.computeScalingRotation(&tmp,&tmp))*/ +} + +void test_jacobisvd() +{ + for(int i = 0; i < g_repeat; i++) { + Matrix2cd m; + m << 0, 1, + 0, 1; + CALL_SUBTEST( svd(m, false) ); + m << 1, 0, + 1, 0; + CALL_SUBTEST( svd(m, false) ); + Matrix2d n; + n << 1, 1, + 1, -1; + CALL_SUBTEST( svd(n, false) ); + CALL_SUBTEST( svd(Matrix3f()) ); + CALL_SUBTEST( svd(Matrix4d()) ); + CALL_SUBTEST( svd(MatrixXf(50,50)) ); +// CALL_SUBTEST( svd(MatrixXd(14,7)) ); + CALL_SUBTEST( svd(MatrixXcf(3,3)) ); + CALL_SUBTEST( svd(MatrixXd(30,30)) ); + } + CALL_SUBTEST( svd(MatrixXf(200,200)) ); + CALL_SUBTEST( svd(MatrixXcd(100,100)) ); + + CALL_SUBTEST( svd_verify_assert<Matrix3f>() ); + CALL_SUBTEST( svd_verify_assert<Matrix3d>() ); + CALL_SUBTEST( svd_verify_assert<MatrixXf>() ); + CALL_SUBTEST( svd_verify_assert<MatrixXd>() ); +} |