mirror of
https://gitlab.com/libeigen/eigen.git
synced 2024-12-15 07:10:37 +08:00
99 lines
4.3 KiB
C++
99 lines
4.3 KiB
C++
// This file is part of Eigen, a lightweight C++ template library
|
|
// for linear algebra.
|
|
//
|
|
// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@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 linearStructure(const MatrixType& m)
|
|
{
|
|
/* this test covers the following files:
|
|
CwiseUnaryOp.h, CwiseBinaryOp.h, SelfCwiseBinaryOp.h
|
|
*/
|
|
typedef typename MatrixType::Index Index;
|
|
typedef typename MatrixType::Scalar Scalar;
|
|
|
|
Index rows = m.rows();
|
|
Index cols = m.cols();
|
|
|
|
// this test relies a lot on Random.h, and there's not much more that we can do
|
|
// to test it, hence I consider that we will have tested Random.h
|
|
MatrixType m1 = MatrixType::Random(rows, cols),
|
|
m2 = MatrixType::Random(rows, cols),
|
|
m3(rows, cols);
|
|
|
|
Scalar s1 = internal::random<Scalar>();
|
|
while (internal::abs(s1)<1e-3) s1 = internal::random<Scalar>();
|
|
|
|
Index r = internal::random<Index>(0, rows-1),
|
|
c = internal::random<Index>(0, cols-1);
|
|
|
|
VERIFY_IS_APPROX(-(-m1), m1);
|
|
VERIFY_IS_APPROX(m1+m1, 2*m1);
|
|
VERIFY_IS_APPROX(m1+m2-m1, m2);
|
|
VERIFY_IS_APPROX(-m2+m1+m2, m1);
|
|
VERIFY_IS_APPROX(m1*s1, s1*m1);
|
|
VERIFY_IS_APPROX((m1+m2)*s1, s1*m1+s1*m2);
|
|
VERIFY_IS_APPROX((-m1+m2)*s1, -s1*m1+s1*m2);
|
|
m3 = m2; m3 += m1;
|
|
VERIFY_IS_APPROX(m3, m1+m2);
|
|
m3 = m2; m3 -= m1;
|
|
VERIFY_IS_APPROX(m3, m2-m1);
|
|
m3 = m2; m3 *= s1;
|
|
VERIFY_IS_APPROX(m3, s1*m2);
|
|
if(!NumTraits<Scalar>::IsInteger)
|
|
{
|
|
m3 = m2; m3 /= s1;
|
|
VERIFY_IS_APPROX(m3, m2/s1);
|
|
}
|
|
|
|
// again, test operator() to check const-qualification
|
|
VERIFY_IS_APPROX((-m1)(r,c), -(m1(r,c)));
|
|
VERIFY_IS_APPROX((m1-m2)(r,c), (m1(r,c))-(m2(r,c)));
|
|
VERIFY_IS_APPROX((m1+m2)(r,c), (m1(r,c))+(m2(r,c)));
|
|
VERIFY_IS_APPROX((s1*m1)(r,c), s1*(m1(r,c)));
|
|
VERIFY_IS_APPROX((m1*s1)(r,c), (m1(r,c))*s1);
|
|
if(!NumTraits<Scalar>::IsInteger)
|
|
VERIFY_IS_APPROX((m1/s1)(r,c), (m1(r,c))/s1);
|
|
|
|
// use .block to disable vectorization and compare to the vectorized version
|
|
VERIFY_IS_APPROX(m1+m1.block(0,0,rows,cols), m1+m1);
|
|
VERIFY_IS_APPROX(m1.cwiseProduct(m1.block(0,0,rows,cols)), m1.cwiseProduct(m1));
|
|
VERIFY_IS_APPROX(m1 - m1.block(0,0,rows,cols), m1 - m1);
|
|
VERIFY_IS_APPROX(m1.block(0,0,rows,cols) * s1, m1 * s1);
|
|
}
|
|
|
|
void test_linearstructure()
|
|
{
|
|
for(int i = 0; i < g_repeat; i++) {
|
|
CALL_SUBTEST_1( linearStructure(Matrix<float, 1, 1>()) );
|
|
CALL_SUBTEST_2( linearStructure(Matrix2f()) );
|
|
CALL_SUBTEST_3( linearStructure(Vector3d()) );
|
|
CALL_SUBTEST_4( linearStructure(Matrix4d()) );
|
|
CALL_SUBTEST_5( linearStructure(MatrixXcf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE/2), internal::random<int>(1,EIGEN_TEST_MAX_SIZE/2))) );
|
|
CALL_SUBTEST_6( linearStructure(MatrixXf (internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
|
|
CALL_SUBTEST_7( linearStructure(MatrixXi (internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
|
|
CALL_SUBTEST_8( linearStructure(MatrixXcd(internal::random<int>(1,EIGEN_TEST_MAX_SIZE/2), internal::random<int>(1,EIGEN_TEST_MAX_SIZE/2))) );
|
|
CALL_SUBTEST_9( linearStructure(ArrayXXf (internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
|
|
}
|
|
}
|