eigen/test/triangular.cpp
Benoit Jacob 46fe7a3d9e if EIGEN_NICE_RANDOM is defined, the random functions will return numbers with
few bits left of the comma and for floating-point types will never return zero.
This replaces the custom functions in test/main.h, so one does not anymore need
to think about that when writing tests.
2008-09-01 17:31:21 +00:00

128 lines
5.0 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 <gael.guennebaud@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"
template<typename MatrixType> void triangular(const MatrixType& m)
{
typedef typename MatrixType::Scalar Scalar;
typedef typename NumTraits<Scalar>::Real RealScalar;
typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
RealScalar largerEps = 10*test_precision<RealScalar>();
int rows = m.rows();
int cols = m.cols();
MatrixType m1 = MatrixType::Random(rows, cols),
m2 = MatrixType::Random(rows, cols),
m3(rows, cols),
m4(rows, cols),
r1(rows, cols),
r2(rows, cols),
mzero = MatrixType::Zero(rows, cols),
mones = MatrixType::Ones(rows, cols),
identity = Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime>
::Identity(rows, rows),
square = Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime>
::Random(rows, rows);
VectorType v1 = VectorType::Random(rows),
v2 = VectorType::Random(rows),
vzero = VectorType::Zero(rows);
MatrixType m1up = m1.template part<Eigen::Upper>();
MatrixType m2up = m2.template part<Eigen::Upper>();
if (rows*cols>1)
{
VERIFY(m1up.isUpper());
VERIFY(m2up.transpose().isLower());
VERIFY(!m2.isLower());
}
// VERIFY_IS_APPROX(m1up.transpose() * m2, m1.upper().transpose().lower() * m2);
// test overloaded operator+=
r1.setZero();
r2.setZero();
r1.template part<Eigen::Upper>() += m1;
r2 += m1up;
VERIFY_IS_APPROX(r1,r2);
// test overloaded operator=
m1.setZero();
m1.template part<Eigen::Upper>() = (m2.transpose() * m2).lazy();
m3 = m2.transpose() * m2;
VERIFY_IS_APPROX(m3.template part<Eigen::Lower>().transpose(), m1);
// test overloaded operator=
m1.setZero();
m1.template part<Eigen::Lower>() = (m2.transpose() * m2).lazy();
VERIFY_IS_APPROX(m3.template part<Eigen::Lower>(), m1);
m1 = MatrixType::Random(rows, cols);
for (int i=0; i<rows; ++i)
while (ei_abs2(m1(i,i))<1e-3) m1(i,i) = ei_random<Scalar>();
Transpose<MatrixType> trm4(m4);
// test back and forward subsitution
m3 = m1.template part<Eigen::Lower>();
VERIFY(m3.template marked<Eigen::Lower>().solveTriangular(m3).cwise().abs().isIdentity(test_precision<RealScalar>()));
VERIFY(m3.transpose().template marked<Eigen::Upper>()
.solveTriangular(m3.transpose()).cwise().abs().isIdentity(test_precision<RealScalar>()));
// check M * inv(L) using in place API
m4 = m3;
m3.transpose().template marked<Eigen::Upper>().solveTriangularInPlace(trm4);
VERIFY(m4.cwise().abs().isIdentity(test_precision<RealScalar>()));
m3 = m1.template part<Eigen::Upper>();
VERIFY(m3.template marked<Eigen::Upper>().solveTriangular(m3).cwise().abs().isIdentity(test_precision<RealScalar>()));
VERIFY(m3.transpose().template marked<Eigen::Lower>()
.solveTriangular(m3.transpose()).cwise().abs().isIdentity(test_precision<RealScalar>()));
// check M * inv(U) using in place API
m4 = m3;
m3.transpose().template marked<Eigen::Lower>().solveTriangularInPlace(trm4);
VERIFY(m4.cwise().abs().isIdentity(test_precision<RealScalar>()));
m3 = m1.template part<Eigen::Upper>();
VERIFY(m2.isApprox(m3 * (m3.template marked<Eigen::Upper>().solveTriangular(m2)), largerEps));
m3 = m1.template part<Eigen::Lower>();
VERIFY(m2.isApprox(m3 * (m3.template marked<Eigen::Lower>().solveTriangular(m2)), largerEps));
VERIFY((m1.template part<Eigen::Upper>() * m2.template part<Eigen::Upper>()).isUpper());
}
void test_triangular()
{
for(int i = 0; i < g_repeat ; i++) {
CALL_SUBTEST( triangular(Matrix<float, 1, 1>()) );
CALL_SUBTEST( triangular(Matrix<float, 2, 2>()) );
CALL_SUBTEST( triangular(Matrix3d()) );
CALL_SUBTEST( triangular(MatrixXcf(4, 4)) );
CALL_SUBTEST( triangular(Matrix<std::complex<float>,8, 8>()) );
CALL_SUBTEST( triangular(MatrixXd(17,17)) );
}
}