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130 lines
5.2 KiB
C++
130 lines
5.2 KiB
C++
// This file is part of Eigen, a lightweight C++ template library
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// for linear algebra. Eigen itself is part of the KDE project.
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//
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// Copyright (C) 2007-2010 Benoit Jacob <jacob.benoit.1@gmail.com>
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//
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// Eigen is free software; you can redistribute it and/or
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// modify it under the terms of the GNU Lesser General Public
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// License as published by the Free Software Foundation; either
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// version 3 of the License, or (at your option) any later version.
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//
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// Alternatively, you can redistribute it and/or
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// modify it under the terms of the GNU General Public License as
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// published by the Free Software Foundation; either version 2 of
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// the License, or (at your option) any later version.
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//
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// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
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// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
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// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
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// GNU General Public License for more details.
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//
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// You should have received a copy of the GNU Lesser General Public
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// License and a copy of the GNU General Public License along with
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// Eigen. If not, see <http://www.gnu.org/licenses/>.
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#include "main.h"
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template<typename VectorType> void map_class_vector(const VectorType& m)
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{
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typedef typename VectorType::Scalar Scalar;
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int size = m.size();
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// test Map.h
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Scalar* array1 = ei_aligned_new<Scalar>(size);
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Scalar* array2 = ei_aligned_new<Scalar>(size);
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Scalar* array3 = new Scalar[size+1];
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Scalar* array3unaligned = std::size_t(array3)%16 == 0 ? array3+1 : array3;
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Map<VectorType, Aligned>(array1, size) = VectorType::Random(size);
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Map<VectorType>(array2, size) = Map<VectorType>(array1, size);
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Map<VectorType>(array3unaligned, size) = Map<VectorType>((const Scalar*)array1, size); // test non-const-correctness support in eigen2
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VectorType ma1 = Map<VectorType>(array1, size);
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VectorType ma2 = Map<VectorType, Aligned>(array2, size);
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VectorType ma3 = Map<VectorType>(array3unaligned, size);
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VERIFY_IS_APPROX(ma1, ma2);
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VERIFY_IS_APPROX(ma1, ma3);
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ei_aligned_delete(array1, size);
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ei_aligned_delete(array2, size);
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delete[] array3;
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}
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template<typename MatrixType> void map_class_matrix(const MatrixType& m)
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{
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typedef typename MatrixType::Scalar Scalar;
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int rows = m.rows(), cols = m.cols(), size = rows*cols;
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// test Map.h
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Scalar* array1 = ei_aligned_new<Scalar>(size);
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for(int i = 0; i < size; i++) array1[i] = Scalar(1);
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Scalar* array2 = ei_aligned_new<Scalar>(size);
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for(int i = 0; i < size; i++) array2[i] = Scalar(1);
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Scalar* array3 = new Scalar[size+1];
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for(int i = 0; i < size+1; i++) array3[i] = Scalar(1);
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Scalar* array3unaligned = std::size_t(array3)%16 == 0 ? array3+1 : array3;
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Map<MatrixType, Aligned>(array1, rows, cols) = MatrixType::Ones(rows,cols);
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Map<MatrixType>(array2, rows, cols) = Map<MatrixType>((const Scalar*)array1, rows, cols); // test non-const-correctness support in eigen2
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Map<MatrixType>(array3unaligned, rows, cols) = Map<MatrixType>(array1, rows, cols);
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MatrixType ma1 = Map<MatrixType>(array1, rows, cols);
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MatrixType ma2 = Map<MatrixType, Aligned>(array2, rows, cols);
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VERIFY_IS_APPROX(ma1, ma2);
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MatrixType ma3 = Map<MatrixType>(array3unaligned, rows, cols);
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VERIFY_IS_APPROX(ma1, ma3);
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ei_aligned_delete(array1, size);
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ei_aligned_delete(array2, size);
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delete[] array3;
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}
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template<typename VectorType> void map_static_methods(const VectorType& m)
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{
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typedef typename VectorType::Scalar Scalar;
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int size = m.size();
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// test Map.h
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Scalar* array1 = ei_aligned_new<Scalar>(size);
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Scalar* array2 = ei_aligned_new<Scalar>(size);
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Scalar* array3 = new Scalar[size+1];
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Scalar* array3unaligned = std::size_t(array3)%16 == 0 ? array3+1 : array3;
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VectorType::MapAligned(array1, size) = VectorType::Random(size);
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VectorType::Map(array2, size) = VectorType::Map(array1, size);
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VectorType::Map(array3unaligned, size) = VectorType::Map(array1, size);
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VectorType ma1 = VectorType::Map(array1, size);
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VectorType ma2 = VectorType::MapAligned(array2, size);
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VectorType ma3 = VectorType::Map(array3unaligned, size);
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VERIFY_IS_APPROX(ma1, ma2);
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VERIFY_IS_APPROX(ma1, ma3);
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ei_aligned_delete(array1, size);
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ei_aligned_delete(array2, size);
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delete[] array3;
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}
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void test_eigen2_map()
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{
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for(int i = 0; i < g_repeat; i++) {
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CALL_SUBTEST_1( map_class_vector(Matrix<float, 1, 1>()) );
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CALL_SUBTEST_2( map_class_vector(Vector4d()) );
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CALL_SUBTEST_3( map_class_vector(RowVector4f()) );
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CALL_SUBTEST_4( map_class_vector(VectorXcf(8)) );
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CALL_SUBTEST_5( map_class_vector(VectorXi(12)) );
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CALL_SUBTEST_1( map_class_matrix(Matrix<float, 1, 1>()) );
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CALL_SUBTEST_2( map_class_matrix(Matrix4d()) );
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CALL_SUBTEST_6( map_class_matrix(Matrix<float,3,5>()) );
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CALL_SUBTEST_4( map_class_matrix(MatrixXcf(ei_random<int>(1,10),ei_random<int>(1,10))) );
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CALL_SUBTEST_5( map_class_matrix(MatrixXi(ei_random<int>(1,10),ei_random<int>(1,10))) );
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CALL_SUBTEST_1( map_static_methods(Matrix<double, 1, 1>()) );
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CALL_SUBTEST_2( map_static_methods(Vector3f()) );
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CALL_SUBTEST_7( map_static_methods(RowVector3d()) );
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CALL_SUBTEST_4( map_static_methods(VectorXcd(8)) );
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CALL_SUBTEST_5( map_static_methods(VectorXf(12)) );
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}
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}
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