mirror of
https://gitlab.com/libeigen/eigen.git
synced 2024-12-09 07:00:27 +08:00
213 lines
6.7 KiB
C++
213 lines
6.7 KiB
C++
// This file is part of Eigen, a lightweight C++ template library
|
|
// for linear algebra.
|
|
//
|
|
// 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/>.
|
|
|
|
#ifndef EIGEN_NO_ASSERTION_CHECKING
|
|
#define EIGEN_NO_ASSERTION_CHECKING
|
|
#endif
|
|
|
|
static int nb_temporaries;
|
|
|
|
#define EIGEN_DEBUG_MATRIX_CTOR { if(size!=0) nb_temporaries++; }
|
|
|
|
#include "main.h"
|
|
#include <Eigen/Cholesky>
|
|
#include <Eigen/QR>
|
|
|
|
#define VERIFY_EVALUATION_COUNT(XPR,N) {\
|
|
nb_temporaries = 0; \
|
|
XPR; \
|
|
if(nb_temporaries!=N) std::cerr << "nb_temporaries == " << nb_temporaries << "\n"; \
|
|
VERIFY( (#XPR) && nb_temporaries==N ); \
|
|
}
|
|
|
|
#ifdef HAS_GSL
|
|
#include "gsl_helper.h"
|
|
#endif
|
|
|
|
template<typename MatrixType> void cholesky(const MatrixType& m)
|
|
{
|
|
/* this test covers the following files:
|
|
LLT.h LDLT.h
|
|
*/
|
|
int rows = m.rows();
|
|
int cols = m.cols();
|
|
|
|
typedef typename MatrixType::Scalar Scalar;
|
|
typedef typename NumTraits<Scalar>::Real RealScalar;
|
|
typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime> SquareMatrixType;
|
|
typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
|
|
|
|
MatrixType a0 = MatrixType::Random(rows,cols);
|
|
VectorType vecB = VectorType::Random(rows), vecX(rows);
|
|
MatrixType matB = MatrixType::Random(rows,cols), matX(rows,cols);
|
|
SquareMatrixType symm = a0 * a0.adjoint();
|
|
// let's make sure the matrix is not singular or near singular
|
|
for (int k=0; k<3; ++k)
|
|
{
|
|
MatrixType a1 = MatrixType::Random(rows,cols);
|
|
symm += a1 * a1.adjoint();
|
|
}
|
|
|
|
SquareMatrixType symmUp = symm.template triangularView<Upper>();
|
|
SquareMatrixType symmLo = symm.template triangularView<Lower>();
|
|
|
|
// to test if really Cholesky only uses the upper triangular part, uncomment the following
|
|
// FIXME: currently that fails !!
|
|
//symm.template part<StrictlyLower>().setZero();
|
|
|
|
#ifdef HAS_GSL
|
|
// if (ei_is_same_type<RealScalar,double>::ret)
|
|
// {
|
|
// typedef GslTraits<Scalar> Gsl;
|
|
// typename Gsl::Matrix gMatA=0, gSymm=0;
|
|
// typename Gsl::Vector gVecB=0, gVecX=0;
|
|
// convert<MatrixType>(symm, gSymm);
|
|
// convert<MatrixType>(symm, gMatA);
|
|
// convert<VectorType>(vecB, gVecB);
|
|
// convert<VectorType>(vecB, gVecX);
|
|
// Gsl::cholesky(gMatA);
|
|
// Gsl::cholesky_solve(gMatA, gVecB, gVecX);
|
|
// VectorType vecX(rows), _vecX, _vecB;
|
|
// convert(gVecX, _vecX);
|
|
// symm.llt().solve(vecB, &vecX);
|
|
// Gsl::prod(gSymm, gVecX, gVecB);
|
|
// convert(gVecB, _vecB);
|
|
// // test gsl itself !
|
|
// VERIFY_IS_APPROX(vecB, _vecB);
|
|
// VERIFY_IS_APPROX(vecX, _vecX);
|
|
//
|
|
// Gsl::free(gMatA);
|
|
// Gsl::free(gSymm);
|
|
// Gsl::free(gVecB);
|
|
// Gsl::free(gVecX);
|
|
// }
|
|
#endif
|
|
|
|
{
|
|
LLT<SquareMatrixType,Lower> chollo(symmLo);
|
|
VERIFY_IS_APPROX(symm, chollo.reconstructedMatrix());
|
|
vecX = chollo.solve(vecB);
|
|
VERIFY_IS_APPROX(symm * vecX, vecB);
|
|
matX = chollo.solve(matB);
|
|
VERIFY_IS_APPROX(symm * matX, matB);
|
|
|
|
// test the upper mode
|
|
LLT<SquareMatrixType,Upper> cholup(symmUp);
|
|
VERIFY_IS_APPROX(symm, cholup.reconstructedMatrix());
|
|
vecX = cholup.solve(vecB);
|
|
VERIFY_IS_APPROX(symm * vecX, vecB);
|
|
matX = cholup.solve(matB);
|
|
VERIFY_IS_APPROX(symm * matX, matB);
|
|
|
|
MatrixType neg = -symmLo;
|
|
chollo.compute(neg);
|
|
VERIFY(chollo.info()==NumericalIssue);
|
|
}
|
|
|
|
// LDLT
|
|
{
|
|
int sign = ei_random<int>()%2 ? 1 : -1;
|
|
|
|
if(sign == -1)
|
|
{
|
|
symm = -symm; // test a negative matrix
|
|
}
|
|
|
|
SquareMatrixType symmUp = symm.template triangularView<Upper>();
|
|
SquareMatrixType symmLo = symm.template triangularView<Lower>();
|
|
|
|
LDLT<SquareMatrixType,Lower> ldltlo(symmLo);
|
|
VERIFY_IS_APPROX(symm, ldltlo.reconstructedMatrix());
|
|
vecX = ldltlo.solve(vecB);
|
|
VERIFY_IS_APPROX(symm * vecX, vecB);
|
|
matX = ldltlo.solve(matB);
|
|
VERIFY_IS_APPROX(symm * matX, matB);
|
|
|
|
LDLT<SquareMatrixType,Upper> ldltup(symmUp);
|
|
VERIFY_IS_APPROX(symm, ldltup.reconstructedMatrix());
|
|
vecX = ldltup.solve(vecB);
|
|
VERIFY_IS_APPROX(symm * vecX, vecB);
|
|
matX = ldltup.solve(matB);
|
|
VERIFY_IS_APPROX(symm * matX, matB);
|
|
|
|
if(MatrixType::RowsAtCompileTime==Dynamic)
|
|
{
|
|
// note : each inplace permutation requires a small temporary vector (mask)
|
|
|
|
// check inplace solve
|
|
matX = matB;
|
|
VERIFY_EVALUATION_COUNT(matX = ldltlo.solve(matX), 0);
|
|
VERIFY_IS_APPROX(matX, ldltlo.solve(matB).eval());
|
|
|
|
|
|
matX = matB;
|
|
VERIFY_EVALUATION_COUNT(matX = ldltup.solve(matX), 0);
|
|
VERIFY_IS_APPROX(matX, ldltup.solve(matB).eval());
|
|
}
|
|
}
|
|
|
|
}
|
|
|
|
template<typename MatrixType> void cholesky_verify_assert()
|
|
{
|
|
MatrixType tmp;
|
|
|
|
LLT<MatrixType> llt;
|
|
VERIFY_RAISES_ASSERT(llt.matrixL())
|
|
VERIFY_RAISES_ASSERT(llt.matrixU())
|
|
VERIFY_RAISES_ASSERT(llt.solve(tmp))
|
|
VERIFY_RAISES_ASSERT(llt.solveInPlace(&tmp))
|
|
|
|
LDLT<MatrixType> ldlt;
|
|
VERIFY_RAISES_ASSERT(ldlt.matrixL())
|
|
VERIFY_RAISES_ASSERT(ldlt.permutationP())
|
|
VERIFY_RAISES_ASSERT(ldlt.vectorD())
|
|
VERIFY_RAISES_ASSERT(ldlt.isPositive())
|
|
VERIFY_RAISES_ASSERT(ldlt.isNegative())
|
|
VERIFY_RAISES_ASSERT(ldlt.solve(tmp))
|
|
VERIFY_RAISES_ASSERT(ldlt.solveInPlace(&tmp))
|
|
}
|
|
|
|
void test_cholesky()
|
|
{
|
|
for(int i = 0; i < g_repeat; i++) {
|
|
CALL_SUBTEST_1( cholesky(Matrix<double,1,1>()) );
|
|
CALL_SUBTEST_2( cholesky(MatrixXd(1,1)) );
|
|
CALL_SUBTEST_3( cholesky(Matrix2d()) );
|
|
CALL_SUBTEST_4( cholesky(Matrix3f()) );
|
|
CALL_SUBTEST_5( cholesky(Matrix4d()) );
|
|
CALL_SUBTEST_2( cholesky(MatrixXd(200,200)) );
|
|
CALL_SUBTEST_6( cholesky(MatrixXcd(100,100)) );
|
|
}
|
|
|
|
CALL_SUBTEST_4( cholesky_verify_assert<Matrix3f>() );
|
|
CALL_SUBTEST_7( cholesky_verify_assert<Matrix3d>() );
|
|
CALL_SUBTEST_8( cholesky_verify_assert<MatrixXf>() );
|
|
CALL_SUBTEST_2( cholesky_verify_assert<MatrixXd>() );
|
|
|
|
// Test problem size constructors
|
|
CALL_SUBTEST_9( LLT<MatrixXf>(10) );
|
|
CALL_SUBTEST_9( LDLT<MatrixXf>(10) );
|
|
}
|