182 lines
7.1 KiB
C++
182 lines
7.1 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> void map_class_vector(const VectorType& m)
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{
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typedef typename VectorType::Index Index;
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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*)(internal::IntPtr(a_array) + (internal::packet_traits<Scalar>::AlignedOnScalar?sizeof(Scalar):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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{
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VERIFY(array[3*i] == v[i]);
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VERIFY(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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{
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VERIFY(array[2*i] == v[i]);
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VERIFY(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> void map_class_matrix(const MatrixType& _m)
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{
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typedef typename MatrixType::Index Index;
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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 = 2*(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*)(internal::IntPtr(a_array1) + (internal::packet_traits<Scalar>::AlignedOnScalar?sizeof(Scalar):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*)(internal::IntPtr(a_array2) + (internal::packet_traits<Scalar>::AlignedOnScalar?sizeof(Scalar):sizeof(typename NumTraits<Scalar>::Real)));
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else
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array2 = (Scalar*)(((internal::UIntPtr(a_array2)+EIGEN_MAX_ALIGN_BYTES-1)/EIGEN_MAX_ALIGN_BYTES)*EIGEN_MAX_ALIGN_BYTES);
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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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{
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if(k==1 && (m.innerSize()+1)*m.outerSize() > maxsize2)
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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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{
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VERIFY(array[map.outerStride()*i+j] == m.coeffByOuterInner(i,j));
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VERIFY(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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{
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if(k==1 && (m.innerSize()+4)*m.outerSize() > maxsize2)
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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> >
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map(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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{
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VERIFY(array[map.outerStride()*i+j] == m.coeffByOuterInner(i,j));
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VERIFY(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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{
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if(k==1 && (2*m.innerSize()+1)*(m.outerSize()*2) > maxsize2)
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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, 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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{
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VERIFY(array[map.outerStride()*i+map.innerStride()*j] == m.coeffByOuterInner(i,j));
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VERIFY(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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internal::aligned_delete(a_array1, arraysize+1);
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}
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void test_mapstride()
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{
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for(int i = 0; i < g_repeat; i++) {
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int maxn = 30;
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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( map_class_matrix<Aligned>(MatrixXcf(internal::random<int>(1,maxn),internal::random<int>(1,maxn))) );
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CALL_SUBTEST_4( 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( map_class_matrix<Unaligned>(MatrixXi(internal::random<int>(1,maxn),internal::random<int>(1,maxn))) );
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CALL_SUBTEST_6( map_class_matrix<Aligned>(MatrixXcd(internal::random<int>(1,maxn),internal::random<int>(1,maxn))) );
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CALL_SUBTEST_6( map_class_matrix<Unaligned>(MatrixXcd(internal::random<int>(1,maxn),internal::random<int>(1,maxn))) );
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TEST_SET_BUT_UNUSED_VARIABLE(maxn);
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}
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}
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