mirror of
https://gitlab.com/libeigen/eigen.git
synced 2024-11-27 06:30:28 +08:00
115 lines
3.6 KiB
C++
115 lines
3.6 KiB
C++
// This file is part of Eigen, a lightweight C++ template library
|
|
// for linear algebra.
|
|
//
|
|
// Copyright (C) 2009 Hauke Heibel <hauke.heibel@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"
|
|
|
|
#include <Eigen/Core>
|
|
|
|
using namespace Eigen;
|
|
|
|
template <typename Scalar, int Storage>
|
|
void run_matrix_tests()
|
|
{
|
|
typedef Matrix<Scalar, Eigen::Dynamic, Eigen::Dynamic, Storage> MatrixType;
|
|
typedef typename MatrixType::Index Index;
|
|
|
|
MatrixType m, n;
|
|
|
|
// boundary cases ...
|
|
m = n = MatrixType::Random(50,50);
|
|
m.conservativeResize(1,50);
|
|
VERIFY_IS_APPROX(m, n.block(0,0,1,50));
|
|
|
|
m = n = MatrixType::Random(50,50);
|
|
m.conservativeResize(50,1);
|
|
VERIFY_IS_APPROX(m, n.block(0,0,50,1));
|
|
|
|
m = n = MatrixType::Random(50,50);
|
|
m.conservativeResize(50,50);
|
|
VERIFY_IS_APPROX(m, n.block(0,0,50,50));
|
|
|
|
// random shrinking ...
|
|
for (int i=0; i<25; ++i)
|
|
{
|
|
const Index rows = internal::random<Index>(1,50);
|
|
const Index cols = internal::random<Index>(1,50);
|
|
m = n = MatrixType::Random(50,50);
|
|
m.conservativeResize(rows,cols);
|
|
VERIFY_IS_APPROX(m, n.block(0,0,rows,cols));
|
|
}
|
|
|
|
// random growing with zeroing ...
|
|
for (int i=0; i<25; ++i)
|
|
{
|
|
const Index rows = internal::random<Index>(50,75);
|
|
const Index cols = internal::random<Index>(50,75);
|
|
m = n = MatrixType::Random(50,50);
|
|
m.conservativeResizeLike(MatrixType::Zero(rows,cols));
|
|
VERIFY_IS_APPROX(m.block(0,0,n.rows(),n.cols()), n);
|
|
VERIFY( rows<=50 || m.block(50,0,rows-50,cols).sum() == Scalar(0) );
|
|
VERIFY( cols<=50 || m.block(0,50,rows,cols-50).sum() == Scalar(0) );
|
|
}
|
|
}
|
|
|
|
template <typename Scalar>
|
|
void run_vector_tests()
|
|
{
|
|
typedef Matrix<Scalar, 1, Eigen::Dynamic> MatrixType;
|
|
|
|
MatrixType m, n;
|
|
|
|
// boundary cases ...
|
|
m = n = MatrixType::Random(50);
|
|
m.conservativeResize(1);
|
|
VERIFY_IS_APPROX(m, n.segment(0,1));
|
|
|
|
m = n = MatrixType::Random(50);
|
|
m.conservativeResize(50);
|
|
VERIFY_IS_APPROX(m, n.segment(0,50));
|
|
|
|
// random shrinking ...
|
|
for (int i=0; i<50; ++i)
|
|
{
|
|
const int size = internal::random<int>(1,50);
|
|
m = n = MatrixType::Random(50);
|
|
m.conservativeResize(size);
|
|
VERIFY_IS_APPROX(m, n.segment(0,size));
|
|
}
|
|
|
|
// random growing with zeroing ...
|
|
for (int i=0; i<50; ++i)
|
|
{
|
|
const int size = internal::random<int>(50,100);
|
|
m = n = MatrixType::Random(50);
|
|
m.conservativeResizeLike(MatrixType::Zero(size));
|
|
VERIFY_IS_APPROX(m.segment(0,50), n);
|
|
VERIFY( size<=50 || m.segment(50,size-50).sum() == Scalar(0) );
|
|
}
|
|
}
|
|
|
|
void test_conservative_resize()
|
|
{
|
|
CALL_SUBTEST_1((run_matrix_tests<int, Eigen::RowMajor>()));
|
|
CALL_SUBTEST_1((run_matrix_tests<int, Eigen::ColMajor>()));
|
|
CALL_SUBTEST_2((run_matrix_tests<float, Eigen::RowMajor>()));
|
|
CALL_SUBTEST_2((run_matrix_tests<float, Eigen::ColMajor>()));
|
|
CALL_SUBTEST_3((run_matrix_tests<double, Eigen::RowMajor>()));
|
|
CALL_SUBTEST_3((run_matrix_tests<double, Eigen::ColMajor>()));
|
|
CALL_SUBTEST_4((run_matrix_tests<std::complex<float>, Eigen::RowMajor>()));
|
|
CALL_SUBTEST_4((run_matrix_tests<std::complex<float>, Eigen::ColMajor>()));
|
|
CALL_SUBTEST_5((run_matrix_tests<std::complex<double>, Eigen::RowMajor>()));
|
|
CALL_SUBTEST_6((run_matrix_tests<std::complex<double>, Eigen::ColMajor>()));
|
|
|
|
CALL_SUBTEST_1((run_vector_tests<int>()));
|
|
CALL_SUBTEST_2((run_vector_tests<float>()));
|
|
CALL_SUBTEST_3((run_vector_tests<double>()));
|
|
CALL_SUBTEST_4((run_vector_tests<std::complex<float> >()));
|
|
CALL_SUBTEST_5((run_vector_tests<std::complex<double> >()));
|
|
}
|