eigen/test/cholesky.cpp
2008-08-20 20:08:38 +00:00

66 lines
2.5 KiB
C++

// This file is part of Eigen, a lightweight C++ template library
// for linear algebra. Eigen itself is part of the KDE project.
//
// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
//
// 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/Cholesky>
#include <Eigen/LU>
template<typename MatrixType> void cholesky(const MatrixType& m)
{
/* this test covers the following files:
Cholesky.h CholeskyWithoutSquareRoot.h
*/
int rows = m.rows();
int cols = m.cols();
typedef typename MatrixType::Scalar Scalar;
typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime> SquareMatrixType;
typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
MatrixType a = MatrixType::Random(rows,cols);
VectorType vecB = VectorType::Random(rows);
MatrixType matB = MatrixType::Random(rows,cols);
SquareMatrixType covMat = a * a.adjoint();
CholeskyWithoutSquareRoot<SquareMatrixType> cholnosqrt(covMat);
VERIFY_IS_APPROX(covMat, cholnosqrt.matrixL() * cholnosqrt.vectorD().asDiagonal() * cholnosqrt.matrixL().adjoint());
VERIFY_IS_APPROX(covMat * cholnosqrt.solve(vecB), vecB);
VERIFY_IS_APPROX(covMat * cholnosqrt.solve(matB), matB);
Cholesky<SquareMatrixType> chol(covMat);
VERIFY_IS_APPROX(covMat, chol.matrixL() * chol.matrixL().adjoint());
VERIFY_IS_APPROX(covMat * chol.solve(vecB), vecB);
VERIFY_IS_APPROX(covMat * chol.solve(matB), matB);
}
void test_cholesky()
{
for(int i = 0; i < 1; i++) {
CALL_SUBTEST( cholesky(Matrix3f()) );
CALL_SUBTEST( cholesky(Matrix4d()) );
CALL_SUBTEST( cholesky(MatrixXcd(7,7)) );
CALL_SUBTEST( cholesky(MatrixXf(85,85)) );
}
}