268 lines
12 KiB
C++
268 lines
12 KiB
C++
// This file is part of Eigen, a lightweight C++ template library
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// for linear algebra.
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//
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// Copyright (C) 2010 Benoit Jacob <jacob.benoit.1@gmail.com>
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//
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// This Source Code Form is subject to the terms of the Mozilla
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// Public License v. 2.0. If a copy of the MPL was not distributed
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// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
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#include "main.h"
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template <int Alignment, typename VectorType>
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void map_class_vector(const VectorType& m) {
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typedef typename VectorType::Scalar Scalar;
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Index size = m.size();
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VectorType v = VectorType::Random(size);
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Index arraysize = 3 * size;
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Scalar* a_array = internal::aligned_new<Scalar>(arraysize + 1);
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Scalar* array = a_array;
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if (Alignment != Aligned)
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array = (Scalar*)(std::intptr_t(a_array) + (internal::packet_traits<Scalar>::AlignedOnScalar
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? sizeof(Scalar)
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: sizeof(typename NumTraits<Scalar>::Real)));
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{
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Map<VectorType, Alignment, InnerStride<3> > map(array, size);
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map = v;
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for (int i = 0; i < size; ++i) {
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VERIFY_IS_EQUAL(array[3 * i], v[i]);
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VERIFY_IS_EQUAL(map[i], v[i]);
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}
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}
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{
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Map<VectorType, Unaligned, InnerStride<Dynamic> > map(array, size, InnerStride<Dynamic>(2));
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map = v;
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for (int i = 0; i < size; ++i) {
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VERIFY_IS_EQUAL(array[2 * i], v[i]);
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VERIFY_IS_EQUAL(map[i], v[i]);
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}
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}
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internal::aligned_delete(a_array, arraysize + 1);
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}
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template <int Alignment, typename MatrixType>
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void map_class_matrix(const MatrixType& _m) {
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typedef typename MatrixType::Scalar Scalar;
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Index rows = _m.rows(), cols = _m.cols();
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MatrixType m = MatrixType::Random(rows, cols);
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Scalar s1 = internal::random<Scalar>();
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Index arraysize = 4 * (rows + 4) * (cols + 4);
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Scalar* a_array1 = internal::aligned_new<Scalar>(arraysize + 1);
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Scalar* array1 = a_array1;
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if (Alignment != Aligned)
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array1 = (Scalar*)(std::intptr_t(a_array1) + (internal::packet_traits<Scalar>::AlignedOnScalar
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? sizeof(Scalar)
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: sizeof(typename NumTraits<Scalar>::Real)));
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Scalar a_array2[256];
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Scalar* array2 = a_array2;
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if (Alignment != Aligned) {
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array2 = (Scalar*)(std::intptr_t(a_array2) + (internal::packet_traits<Scalar>::AlignedOnScalar
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? sizeof(Scalar)
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: sizeof(typename NumTraits<Scalar>::Real)));
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} else {
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// In case there is no alignment, default to pointing to the start.
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constexpr int alignment = (std::max<int>)(EIGEN_MAX_ALIGN_BYTES, 1);
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array2 = (Scalar*)(((std::uintptr_t(a_array2) + alignment - 1) / alignment) * alignment);
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}
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Index maxsize2 = a_array2 - array2 + 256;
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// test no inner stride and some dynamic outer stride
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for (int k = 0; k < 2; ++k) {
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if (k == 1 && (m.innerSize() + 1) * m.outerSize() > maxsize2) break;
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Scalar* array = (k == 0 ? array1 : array2);
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Map<MatrixType, Alignment, OuterStride<Dynamic> > map(array, rows, cols, OuterStride<Dynamic>(m.innerSize() + 1));
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map = m;
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VERIFY(map.outerStride() == map.innerSize() + 1);
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for (int i = 0; i < m.outerSize(); ++i)
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for (int j = 0; j < m.innerSize(); ++j) {
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VERIFY_IS_EQUAL(array[map.outerStride() * i + j], m.coeffByOuterInner(i, j));
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VERIFY_IS_EQUAL(map.coeffByOuterInner(i, j), m.coeffByOuterInner(i, j));
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}
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VERIFY_IS_APPROX(s1 * map, s1 * m);
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map *= s1;
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VERIFY_IS_APPROX(map, s1 * m);
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}
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// test no inner stride and an outer stride of +4. This is quite important as for fixed-size matrices,
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// this allows to hit the special case where it's vectorizable.
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for (int k = 0; k < 2; ++k) {
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if (k == 1 && (m.innerSize() + 4) * m.outerSize() > maxsize2) break;
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Scalar* array = (k == 0 ? array1 : array2);
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enum {
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InnerSize = MatrixType::InnerSizeAtCompileTime,
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OuterStrideAtCompileTime = InnerSize == Dynamic ? Dynamic : InnerSize + 4
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};
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Map<MatrixType, Alignment, OuterStride<OuterStrideAtCompileTime> > map(
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array, rows, cols, OuterStride<OuterStrideAtCompileTime>(m.innerSize() + 4));
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map = m;
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VERIFY(map.outerStride() == map.innerSize() + 4);
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for (int i = 0; i < m.outerSize(); ++i)
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for (int j = 0; j < m.innerSize(); ++j) {
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VERIFY_IS_EQUAL(array[map.outerStride() * i + j], m.coeffByOuterInner(i, j));
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VERIFY_IS_EQUAL(map.coeffByOuterInner(i, j), m.coeffByOuterInner(i, j));
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}
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VERIFY_IS_APPROX(s1 * map, s1 * m);
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map *= s1;
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VERIFY_IS_APPROX(map, s1 * m);
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}
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// test both inner stride and outer stride
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for (int k = 0; k < 2; ++k) {
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if (k == 1 && (2 * m.innerSize() + 1) * (m.outerSize() * 2) > maxsize2) break;
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Scalar* array = (k == 0 ? array1 : array2);
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Map<MatrixType, Alignment, Stride<Dynamic, Dynamic> > map(array, rows, cols,
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Stride<Dynamic, Dynamic>(2 * m.innerSize() + 1, 2));
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map = m;
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VERIFY(map.outerStride() == 2 * map.innerSize() + 1);
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VERIFY(map.innerStride() == 2);
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for (int i = 0; i < m.outerSize(); ++i)
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for (int j = 0; j < m.innerSize(); ++j) {
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VERIFY_IS_EQUAL(array[map.outerStride() * i + map.innerStride() * j], m.coeffByOuterInner(i, j));
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VERIFY_IS_EQUAL(map.coeffByOuterInner(i, j), m.coeffByOuterInner(i, j));
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}
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VERIFY_IS_APPROX(s1 * map, s1 * m);
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map *= s1;
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VERIFY_IS_APPROX(map, s1 * m);
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}
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// test inner stride and no outer stride
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for (int k = 0; k < 2; ++k) {
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if (k == 1 && (m.innerSize() * 2) * m.outerSize() > maxsize2) break;
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Scalar* array = (k == 0 ? array1 : array2);
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Map<MatrixType, Alignment, InnerStride<Dynamic> > map(array, rows, cols, InnerStride<Dynamic>(2));
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map = m;
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VERIFY(map.outerStride() == map.innerSize() * 2);
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for (int i = 0; i < m.outerSize(); ++i)
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for (int j = 0; j < m.innerSize(); ++j) {
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VERIFY_IS_EQUAL(array[map.innerSize() * i * 2 + j * 2], m.coeffByOuterInner(i, j));
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VERIFY_IS_EQUAL(map.coeffByOuterInner(i, j), m.coeffByOuterInner(i, j));
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}
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VERIFY_IS_APPROX(s1 * map, s1 * m);
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map *= s1;
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VERIFY_IS_APPROX(map, s1 * m);
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}
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// test negative strides
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{
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Matrix<Scalar, Dynamic, 1>::Map(a_array1, arraysize + 1).setRandom();
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Index outerstride = m.innerSize() + 4;
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Scalar* array = array1;
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{
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Map<MatrixType, Alignment, OuterStride<> > map1(array, rows, cols, OuterStride<>(outerstride));
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Map<MatrixType, Unaligned, OuterStride<> > map2(array + (m.outerSize() - 1) * outerstride, rows, cols,
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OuterStride<>(-outerstride));
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if (MatrixType::IsRowMajor)
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VERIFY_IS_APPROX(map1.colwise().reverse(), map2);
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else
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VERIFY_IS_APPROX(map1.rowwise().reverse(), map2);
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}
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{
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Map<MatrixType, Alignment, OuterStride<> > map1(array, rows, cols, OuterStride<>(outerstride));
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Map<MatrixType, Unaligned, Stride<Dynamic, Dynamic> > map2(
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array + (m.outerSize() - 1) * outerstride + m.innerSize() - 1, rows, cols,
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Stride<Dynamic, Dynamic>(-outerstride, -1));
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VERIFY_IS_APPROX(map1.reverse(), map2);
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}
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{
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Map<MatrixType, Alignment, OuterStride<> > map1(array, rows, cols, OuterStride<>(outerstride));
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Map<MatrixType, Unaligned, Stride<Dynamic, -1> > map2(
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array + (m.outerSize() - 1) * outerstride + m.innerSize() - 1, rows, cols,
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Stride<Dynamic, -1>(-outerstride, -1));
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VERIFY_IS_APPROX(map1.reverse(), map2);
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}
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}
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internal::aligned_delete(a_array1, arraysize + 1);
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}
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// Additional tests for inner-stride but no outer-stride
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template <int>
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void bug1453() {
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const int data[] = {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15,
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16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31};
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typedef Matrix<int, Dynamic, Dynamic, RowMajor> RowMatrixXi;
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typedef Matrix<int, 2, 3, ColMajor> ColMatrix23i;
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typedef Matrix<int, 3, 2, ColMajor> ColMatrix32i;
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typedef Matrix<int, 2, 3, RowMajor> RowMatrix23i;
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typedef Matrix<int, 3, 2, RowMajor> RowMatrix32i;
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VERIFY_IS_APPROX(MatrixXi::Map(data, 2, 3, InnerStride<2>()), MatrixXi::Map(data, 2, 3, Stride<4, 2>()));
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VERIFY_IS_APPROX(MatrixXi::Map(data, 2, 3, InnerStride<>(2)), MatrixXi::Map(data, 2, 3, Stride<4, 2>()));
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VERIFY_IS_APPROX(MatrixXi::Map(data, 3, 2, InnerStride<2>()), MatrixXi::Map(data, 3, 2, Stride<6, 2>()));
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VERIFY_IS_APPROX(MatrixXi::Map(data, 3, 2, InnerStride<>(2)), MatrixXi::Map(data, 3, 2, Stride<6, 2>()));
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VERIFY_IS_APPROX(RowMatrixXi::Map(data, 2, 3, InnerStride<2>()), RowMatrixXi::Map(data, 2, 3, Stride<6, 2>()));
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VERIFY_IS_APPROX(RowMatrixXi::Map(data, 2, 3, InnerStride<>(2)), RowMatrixXi::Map(data, 2, 3, Stride<6, 2>()));
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VERIFY_IS_APPROX(RowMatrixXi::Map(data, 3, 2, InnerStride<2>()), RowMatrixXi::Map(data, 3, 2, Stride<4, 2>()));
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VERIFY_IS_APPROX(RowMatrixXi::Map(data, 3, 2, InnerStride<>(2)), RowMatrixXi::Map(data, 3, 2, Stride<4, 2>()));
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VERIFY_IS_APPROX(ColMatrix23i::Map(data, InnerStride<2>()), MatrixXi::Map(data, 2, 3, Stride<4, 2>()));
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VERIFY_IS_APPROX(ColMatrix23i::Map(data, InnerStride<>(2)), MatrixXi::Map(data, 2, 3, Stride<4, 2>()));
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VERIFY_IS_APPROX(ColMatrix32i::Map(data, InnerStride<2>()), MatrixXi::Map(data, 3, 2, Stride<6, 2>()));
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VERIFY_IS_APPROX(ColMatrix32i::Map(data, InnerStride<>(2)), MatrixXi::Map(data, 3, 2, Stride<6, 2>()));
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VERIFY_IS_APPROX(RowMatrix23i::Map(data, InnerStride<2>()), RowMatrixXi::Map(data, 2, 3, Stride<6, 2>()));
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VERIFY_IS_APPROX(RowMatrix23i::Map(data, InnerStride<>(2)), RowMatrixXi::Map(data, 2, 3, Stride<6, 2>()));
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VERIFY_IS_APPROX(RowMatrix32i::Map(data, InnerStride<2>()), RowMatrixXi::Map(data, 3, 2, Stride<4, 2>()));
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VERIFY_IS_APPROX(RowMatrix32i::Map(data, InnerStride<>(2)), RowMatrixXi::Map(data, 3, 2, Stride<4, 2>()));
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}
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EIGEN_DECLARE_TEST(mapstride) {
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for (int i = 0; i < g_repeat; i++) {
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int maxn = 3;
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CALL_SUBTEST_1(map_class_vector<Aligned>(Matrix<float, 1, 1>()));
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CALL_SUBTEST_1(map_class_vector<Unaligned>(Matrix<float, 1, 1>()));
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CALL_SUBTEST_2(map_class_vector<Aligned>(Vector4d()));
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CALL_SUBTEST_2(map_class_vector<Unaligned>(Vector4d()));
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CALL_SUBTEST_3(map_class_vector<Aligned>(RowVector4f()));
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CALL_SUBTEST_3(map_class_vector<Unaligned>(RowVector4f()));
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CALL_SUBTEST_4(map_class_vector<Aligned>(VectorXcf(internal::random<int>(1, maxn))));
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CALL_SUBTEST_4(map_class_vector<Unaligned>(VectorXcf(internal::random<int>(1, maxn))));
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CALL_SUBTEST_5(map_class_vector<Aligned>(VectorXi(internal::random<int>(1, maxn))));
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CALL_SUBTEST_5(map_class_vector<Unaligned>(VectorXi(internal::random<int>(1, maxn))));
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CALL_SUBTEST_1(map_class_matrix<Aligned>(Matrix<float, 1, 1>()));
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CALL_SUBTEST_1(map_class_matrix<Unaligned>(Matrix<float, 1, 1>()));
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CALL_SUBTEST_2(map_class_matrix<Aligned>(Matrix4d()));
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CALL_SUBTEST_2(map_class_matrix<Unaligned>(Matrix4d()));
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CALL_SUBTEST_3(map_class_matrix<Aligned>(Matrix<float, 3, 5>()));
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CALL_SUBTEST_3(map_class_matrix<Unaligned>(Matrix<float, 3, 5>()));
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CALL_SUBTEST_3(map_class_matrix<Aligned>(Matrix<float, 4, 8>()));
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CALL_SUBTEST_3(map_class_matrix<Unaligned>(Matrix<float, 4, 8>()));
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CALL_SUBTEST_4(
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map_class_matrix<Aligned>(MatrixXcf(internal::random<int>(1, maxn), internal::random<int>(1, maxn))));
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CALL_SUBTEST_4(
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map_class_matrix<Unaligned>(MatrixXcf(internal::random<int>(1, maxn), internal::random<int>(1, maxn))));
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CALL_SUBTEST_5(map_class_matrix<Aligned>(MatrixXi(internal::random<int>(1, maxn), internal::random<int>(1, maxn))));
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CALL_SUBTEST_5(
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map_class_matrix<Unaligned>(MatrixXi(internal::random<int>(1, maxn), internal::random<int>(1, maxn))));
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CALL_SUBTEST_6(
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map_class_matrix<Aligned>(MatrixXcd(internal::random<int>(1, maxn), internal::random<int>(1, maxn))));
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CALL_SUBTEST_6(
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map_class_matrix<Unaligned>(MatrixXcd(internal::random<int>(1, maxn), internal::random<int>(1, maxn))));
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CALL_SUBTEST_5(bug1453<0>());
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TEST_SET_BUT_UNUSED_VARIABLE(maxn);
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}
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}
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