2011-01-19 23:10:54 +08:00
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// This file is part of Eigen, a lightweight C++ template library
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// for linear algebra. Eigen itself is part of the KDE project.
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//
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// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
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//
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2012-07-14 02:42:47 +08:00
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// This Source Code Form is subject to the terms of the Mozilla
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// Public License v. 2.0. If a copy of the MPL was not distributed
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// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
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2011-01-19 23:10:54 +08:00
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#include "main.h"
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#include <Eigen/SVD>
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template<typename MatrixType> void svd(const MatrixType& m)
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{
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/* this test covers the following files:
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SVD.h
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*/
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int rows = m.rows();
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int cols = m.cols();
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typedef typename MatrixType::Scalar Scalar;
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typedef typename NumTraits<Scalar>::Real RealScalar;
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MatrixType a = MatrixType::Random(rows,cols);
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Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> b =
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Matrix<Scalar, MatrixType::RowsAtCompileTime, 1>::Random(rows,1);
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Matrix<Scalar, MatrixType::ColsAtCompileTime, 1> x(cols,1), x2(cols,1);
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RealScalar largerEps = test_precision<RealScalar>();
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if (ei_is_same_type<RealScalar,float>::ret)
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largerEps = 1e-3f;
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{
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SVD<MatrixType> svd(a);
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MatrixType sigma = MatrixType::Zero(rows,cols);
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MatrixType matU = MatrixType::Zero(rows,rows);
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sigma.block(0,0,cols,cols) = svd.singularValues().asDiagonal();
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matU.block(0,0,rows,cols) = svd.matrixU();
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VERIFY_IS_APPROX(a, matU * sigma * svd.matrixV().transpose());
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}
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if (rows==cols)
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{
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if (ei_is_same_type<RealScalar,float>::ret)
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{
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MatrixType a1 = MatrixType::Random(rows,cols);
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a += a * a.adjoint() + a1 * a1.adjoint();
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}
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SVD<MatrixType> svd(a);
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svd.solve(b, &x);
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VERIFY_IS_APPROX(a * x,b);
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}
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if(rows==cols)
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{
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SVD<MatrixType> svd(a);
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MatrixType unitary, positive;
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svd.computeUnitaryPositive(&unitary, &positive);
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VERIFY_IS_APPROX(unitary * unitary.adjoint(), MatrixType::Identity(unitary.rows(),unitary.rows()));
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VERIFY_IS_APPROX(positive, positive.adjoint());
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for(int i = 0; i < rows; i++) VERIFY(positive.diagonal()[i] >= 0); // cheap necessary (not sufficient) condition for positivity
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VERIFY_IS_APPROX(unitary*positive, a);
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svd.computePositiveUnitary(&positive, &unitary);
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VERIFY_IS_APPROX(unitary * unitary.adjoint(), MatrixType::Identity(unitary.rows(),unitary.rows()));
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VERIFY_IS_APPROX(positive, positive.adjoint());
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for(int i = 0; i < rows; i++) VERIFY(positive.diagonal()[i] >= 0); // cheap necessary (not sufficient) condition for positivity
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VERIFY_IS_APPROX(positive*unitary, a);
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}
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}
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2011-01-25 21:37:18 +08:00
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void test_eigen2_svd()
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2011-01-19 23:10:54 +08:00
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{
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for(int i = 0; i < g_repeat; i++) {
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2011-01-25 22:02:59 +08:00
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CALL_SUBTEST_1( svd(Matrix3f()) );
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CALL_SUBTEST_2( svd(Matrix4d()) );
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CALL_SUBTEST_3( svd(MatrixXf(7,7)) );
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CALL_SUBTEST_4( svd(MatrixXd(14,7)) );
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2011-01-19 23:10:54 +08:00
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// complex are not implemented yet
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// CALL_SUBTEST( svd(MatrixXcd(6,6)) );
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// CALL_SUBTEST( svd(MatrixXcf(3,3)) );
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SVD<MatrixXf> s;
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MatrixXf m = MatrixXf::Random(10,1);
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s.compute(m);
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}
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}
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