mirror of
https://gitlab.com/libeigen/eigen.git
synced 2024-12-21 07:19:46 +08:00
102 lines
4.1 KiB
C++
102 lines
4.1 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) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
|
|
//
|
|
// This Source Code Form is subject to the terms of the Mozilla
|
|
// Public License v. 2.0. If a copy of the MPL was not distributed
|
|
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
|
|
|
|
#include "main.h"
|
|
|
|
template<typename MatrixType> void adjoint(const MatrixType& m)
|
|
{
|
|
/* this test covers the following files:
|
|
Transpose.h Conjugate.h Dot.h
|
|
*/
|
|
|
|
typedef typename MatrixType::Scalar Scalar;
|
|
typedef typename NumTraits<Scalar>::Real RealScalar;
|
|
typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
|
|
typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime> SquareMatrixType;
|
|
int rows = m.rows();
|
|
int cols = m.cols();
|
|
|
|
RealScalar largerEps = test_precision<RealScalar>();
|
|
if (ei_is_same_type<RealScalar,float>::ret)
|
|
largerEps = RealScalar(1e-3f);
|
|
|
|
MatrixType m1 = MatrixType::Random(rows, cols),
|
|
m2 = MatrixType::Random(rows, cols),
|
|
m3(rows, cols),
|
|
mzero = MatrixType::Zero(rows, cols),
|
|
identity = SquareMatrixType::Identity(rows, rows),
|
|
square = SquareMatrixType::Random(rows, rows);
|
|
VectorType v1 = VectorType::Random(rows),
|
|
v2 = VectorType::Random(rows),
|
|
v3 = VectorType::Random(rows),
|
|
vzero = VectorType::Zero(rows);
|
|
|
|
Scalar s1 = ei_random<Scalar>(),
|
|
s2 = ei_random<Scalar>();
|
|
|
|
// check basic compatibility of adjoint, transpose, conjugate
|
|
VERIFY_IS_APPROX(m1.transpose().conjugate().adjoint(), m1);
|
|
VERIFY_IS_APPROX(m1.adjoint().conjugate().transpose(), m1);
|
|
|
|
// check multiplicative behavior
|
|
VERIFY_IS_APPROX((m1.adjoint() * m2).adjoint(), m2.adjoint() * m1);
|
|
VERIFY_IS_APPROX((s1 * m1).adjoint(), ei_conj(s1) * m1.adjoint());
|
|
|
|
// check basic properties of dot, norm, norm2
|
|
typedef typename NumTraits<Scalar>::Real RealScalar;
|
|
VERIFY(ei_isApprox((s1 * v1 + s2 * v2).eigen2_dot(v3), s1 * v1.eigen2_dot(v3) + s2 * v2.eigen2_dot(v3), largerEps));
|
|
VERIFY(ei_isApprox(v3.eigen2_dot(s1 * v1 + s2 * v2), ei_conj(s1)*v3.eigen2_dot(v1)+ei_conj(s2)*v3.eigen2_dot(v2), largerEps));
|
|
VERIFY_IS_APPROX(ei_conj(v1.eigen2_dot(v2)), v2.eigen2_dot(v1));
|
|
VERIFY_IS_APPROX(ei_real(v1.eigen2_dot(v1)), v1.squaredNorm());
|
|
if(NumTraits<Scalar>::HasFloatingPoint)
|
|
VERIFY_IS_APPROX(v1.squaredNorm(), v1.norm() * v1.norm());
|
|
VERIFY_IS_MUCH_SMALLER_THAN(ei_abs(vzero.eigen2_dot(v1)), static_cast<RealScalar>(1));
|
|
if(NumTraits<Scalar>::HasFloatingPoint)
|
|
VERIFY_IS_MUCH_SMALLER_THAN(vzero.norm(), static_cast<RealScalar>(1));
|
|
|
|
// check compatibility of dot and adjoint
|
|
VERIFY(ei_isApprox(v1.eigen2_dot(square * v2), (square.adjoint() * v1).eigen2_dot(v2), largerEps));
|
|
|
|
// like in testBasicStuff, test operator() to check const-qualification
|
|
int r = ei_random<int>(0, rows-1),
|
|
c = ei_random<int>(0, cols-1);
|
|
VERIFY_IS_APPROX(m1.conjugate()(r,c), ei_conj(m1(r,c)));
|
|
VERIFY_IS_APPROX(m1.adjoint()(c,r), ei_conj(m1(r,c)));
|
|
|
|
if(NumTraits<Scalar>::HasFloatingPoint)
|
|
{
|
|
// check that Random().normalized() works: tricky as the random xpr must be evaluated by
|
|
// normalized() in order to produce a consistent result.
|
|
VERIFY_IS_APPROX(VectorType::Random(rows).normalized().norm(), RealScalar(1));
|
|
}
|
|
|
|
// check inplace transpose
|
|
m3 = m1;
|
|
m3.transposeInPlace();
|
|
VERIFY_IS_APPROX(m3,m1.transpose());
|
|
m3.transposeInPlace();
|
|
VERIFY_IS_APPROX(m3,m1);
|
|
|
|
}
|
|
|
|
void test_eigen2_adjoint()
|
|
{
|
|
for(int i = 0; i < g_repeat; i++) {
|
|
CALL_SUBTEST_1( adjoint(Matrix<float, 1, 1>()) );
|
|
CALL_SUBTEST_2( adjoint(Matrix3d()) );
|
|
CALL_SUBTEST_3( adjoint(Matrix4f()) );
|
|
CALL_SUBTEST_4( adjoint(MatrixXcf(4, 4)) );
|
|
CALL_SUBTEST_5( adjoint(MatrixXi(8, 12)) );
|
|
CALL_SUBTEST_6( adjoint(MatrixXf(21, 21)) );
|
|
}
|
|
// test a large matrix only once
|
|
CALL_SUBTEST_7( adjoint(Matrix<float, 100, 100>()) );
|
|
}
|
|
|