// This file is part of Eigen, a lightweight C++ template library // for linear algebra. // // Copyright (C) 2008 Gael Guennebaud // // 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 . #include "main.h" #include #include template void svd(const MatrixType& m) { /* this test covers the following files: SVD.h */ int rows = m.rows(); int cols = m.cols(); typedef typename MatrixType::Scalar Scalar; typedef typename NumTraits::Real RealScalar; MatrixType a = MatrixType::Random(rows,cols); Matrix b = Matrix::Random(rows,1); Matrix x(cols,1), x2(cols,1); RealScalar largerEps = test_precision(); if (ei_is_same_type::ret) largerEps = 1e-3f; { SVD svd(a); MatrixType sigma = MatrixType::Zero(rows,cols); MatrixType matU = MatrixType::Zero(rows,rows); sigma.block(0,0,cols,cols) = svd.singularValues().asDiagonal(); matU.block(0,0,rows,cols) = svd.matrixU(); VERIFY_IS_APPROX(a, matU * sigma * svd.matrixV().transpose()); } if (rows==cols) { if (ei_is_same_type::ret) { MatrixType a1 = MatrixType::Random(rows,cols); a += a * a.adjoint() + a1 * a1.adjoint(); } SVD svd(a); svd.solve(b, &x); VERIFY_IS_APPROX(a * x,b); } if(rows==cols) { SVD svd(a); MatrixType unitary, positive; svd.computeUnitaryPositive(&unitary, &positive); VERIFY_IS_APPROX(unitary * unitary.adjoint(), MatrixType::Identity(unitary.rows(),unitary.rows())); VERIFY_IS_APPROX(positive, positive.adjoint()); for(int i = 0; i < rows; i++) VERIFY(positive.diagonal()[i] >= 0); // cheap necessary (not sufficient) condition for positivity VERIFY_IS_APPROX(unitary*positive, a); svd.computePositiveUnitary(&positive, &unitary); VERIFY_IS_APPROX(unitary * unitary.adjoint(), MatrixType::Identity(unitary.rows(),unitary.rows())); VERIFY_IS_APPROX(positive, positive.adjoint()); for(int i = 0; i < rows; i++) VERIFY(positive.diagonal()[i] >= 0); // cheap necessary (not sufficient) condition for positivity VERIFY_IS_APPROX(positive*unitary, a); } } template void svd_verify_assert() { MatrixType tmp; SVD 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.sort()) 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_svd() { for(int i = 0; i < g_repeat; i++) { CALL_SUBTEST( svd(Matrix3f()) ); CALL_SUBTEST( svd(Matrix4d()) ); CALL_SUBTEST( svd(MatrixXf(7,7)) ); CALL_SUBTEST( svd(MatrixXd(14,7)) ); // complex are not implemented yet // CALL_SUBTEST( svd(MatrixXcd(6,6)) ); // CALL_SUBTEST( svd(MatrixXcf(3,3)) ); } CALL_SUBTEST( svd_verify_assert() ); CALL_SUBTEST( svd_verify_assert() ); CALL_SUBTEST( svd_verify_assert() ); CALL_SUBTEST( svd_verify_assert() ); }