eigen/test/mapstride.cpp

140 lines
4.7 KiB
C++

// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2010 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 VectorType> void map_class_vector(const VectorType& m)
{
typedef typename VectorType::Scalar Scalar;
int size = m.size();
VectorType v = VectorType::Random(size);
int arraysize = 3*size;
Scalar* array = ei_aligned_new<Scalar>(arraysize);
{
Map<VectorType, Aligned, InnerStride<3> > map(array, size);
map = v;
for(int i = 0; i < size; ++i)
{
VERIFY(array[3*i] == v[i]);
VERIFY(map[i] == v[i]);
}
}
{
Map<VectorType, Unaligned, InnerStride<Dynamic> > map(array, size, InnerStride<Dynamic>(2));
map = v;
for(int i = 0; i < size; ++i)
{
VERIFY(array[2*i] == v[i]);
VERIFY(map[i] == v[i]);
}
}
ei_aligned_delete(array, arraysize);
}
template<typename MatrixType> void map_class_matrix(const MatrixType& _m)
{
typedef typename MatrixType::Scalar Scalar;
int rows = _m.rows(), cols = _m.cols();
MatrixType m = MatrixType::Random(rows,cols);
int arraysize = 2*(rows+4)*(cols+4);
Scalar* array = ei_aligned_new<Scalar>(arraysize);
// test no inner stride and some dynamic outer stride
{
Map<MatrixType, Aligned, OuterStride<Dynamic> > map(array, rows, cols, OuterStride<Dynamic>(m.innerSize()+1));
map = m;
VERIFY(map.outerStride() == map.innerSize()+1);
for(int i = 0; i < m.outerSize(); ++i)
for(int j = 0; j < m.innerSize(); ++j)
{
VERIFY(array[map.outerStride()*i+j] == m.coeffByOuterInner(i,j));
VERIFY(map.coeffByOuterInner(i,j) == m.coeffByOuterInner(i,j));
}
}
// test no inner stride and an outer stride of +4. This is quite important as for fixed-size matrices,
// this allows to hit the special case where it's vectorizable.
{
enum {
InnerSize = MatrixType::InnerSizeAtCompileTime,
OuterStrideAtCompileTime = InnerSize==Dynamic ? Dynamic : InnerSize+4
};
Map<MatrixType, Aligned, OuterStride<OuterStrideAtCompileTime> >
map(array, rows, cols, OuterStride<OuterStrideAtCompileTime>(m.innerSize()+4));
map = m;
VERIFY(map.outerStride() == map.innerSize()+4);
for(int i = 0; i < m.outerSize(); ++i)
for(int j = 0; j < m.innerSize(); ++j)
{
VERIFY(array[map.outerStride()*i+j] == m.coeffByOuterInner(i,j));
VERIFY(map.coeffByOuterInner(i,j) == m.coeffByOuterInner(i,j));
}
}
// test both inner stride and outer stride
{
Map<MatrixType, Aligned, Stride<Dynamic,Dynamic> > map(array, rows, cols, Stride<Dynamic,Dynamic>(2*m.innerSize()+1, 2));
map = m;
VERIFY(map.outerStride() == 2*map.innerSize()+1);
VERIFY(map.innerStride() == 2);
for(int i = 0; i < m.outerSize(); ++i)
for(int j = 0; j < m.innerSize(); ++j)
{
VERIFY(array[map.outerStride()*i+map.innerStride()*j] == m.coeffByOuterInner(i,j));
VERIFY(map.coeffByOuterInner(i,j) == m.coeffByOuterInner(i,j));
}
}
ei_aligned_delete(array, arraysize);
}
void test_mapstride()
{
for(int i = 0; i < g_repeat; i++) {
CALL_SUBTEST_1( map_class_vector(Matrix<float, 1, 1>()) );
CALL_SUBTEST_2( map_class_vector(Vector4d()) );
CALL_SUBTEST_3( map_class_vector(RowVector4f()) );
CALL_SUBTEST_4( map_class_vector(VectorXcf(8)) );
CALL_SUBTEST_5( map_class_vector(VectorXi(12)) );
CALL_SUBTEST_1( map_class_matrix(Matrix<float, 1, 1>()) );
CALL_SUBTEST_2( map_class_matrix(Matrix4d()) );
CALL_SUBTEST_3( map_class_matrix(Matrix<float,3,5>()) );
CALL_SUBTEST_3( map_class_matrix(Matrix<float,4,8>()) );
CALL_SUBTEST_4( map_class_matrix(MatrixXcf(ei_random<int>(1,10),ei_random<int>(1,10))) );
CALL_SUBTEST_5( map_class_matrix(MatrixXi(5,5)));//ei_random<int>(1,10),ei_random<int>(1,10))) );
}
}