| 1 | // This file is part of Eigen, a lightweight C++ template library
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| 2 | // for linear algebra. Eigen itself is part of the KDE project.
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| 3 | //
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| 4 | // Copyright (C) 2007-2010 Benoit Jacob <jacob.benoit.1@gmail.com>
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| 5 | //
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| 6 | // This Source Code Form is subject to the terms of the Mozilla
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| 7 | // Public License v. 2.0. If a copy of the MPL was not distributed
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| 8 | // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
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| 9 |
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| 10 | #include "main.h"
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| 11 |
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| 12 | template<typename VectorType> void map_class_vector(const VectorType& m)
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| 13 | {
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| 14 | typedef typename VectorType::Scalar Scalar;
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| 15 |
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| 16 | int size = m.size();
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| 17 |
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| 18 | // test Map.h
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| 19 | Scalar* array1 = ei_aligned_new<Scalar>(size);
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| 20 | Scalar* array2 = ei_aligned_new<Scalar>(size);
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| 21 | Scalar* array3 = new Scalar[size+1];
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| 22 | Scalar* array3unaligned = std::size_t(array3)%16 == 0 ? array3+1 : array3;
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| 23 |
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| 24 | Map<VectorType, Aligned>(array1, size) = VectorType::Random(size);
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| 25 | Map<VectorType>(array2, size) = Map<VectorType>(array1, size);
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| 26 | Map<VectorType>(array3unaligned, size) = Map<VectorType>((const Scalar*)array1, size); // test non-const-correctness support in eigen2
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| 27 | VectorType ma1 = Map<VectorType>(array1, size);
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| 28 | VectorType ma2 = Map<VectorType, Aligned>(array2, size);
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| 29 | VectorType ma3 = Map<VectorType>(array3unaligned, size);
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| 30 | VERIFY_IS_APPROX(ma1, ma2);
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| 31 | VERIFY_IS_APPROX(ma1, ma3);
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| 32 |
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| 33 | ei_aligned_delete(array1, size);
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| 34 | ei_aligned_delete(array2, size);
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| 35 | delete[] array3;
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| 36 | }
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| 37 |
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| 38 | template<typename MatrixType> void map_class_matrix(const MatrixType& m)
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| 39 | {
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| 40 | typedef typename MatrixType::Scalar Scalar;
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| 41 |
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| 42 | int rows = m.rows(), cols = m.cols(), size = rows*cols;
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| 43 |
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| 44 | // test Map.h
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| 45 | Scalar* array1 = ei_aligned_new<Scalar>(size);
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| 46 | for(int i = 0; i < size; i++) array1[i] = Scalar(1);
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| 47 | Scalar* array2 = ei_aligned_new<Scalar>(size);
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| 48 | for(int i = 0; i < size; i++) array2[i] = Scalar(1);
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| 49 | Scalar* array3 = new Scalar[size+1];
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| 50 | for(int i = 0; i < size+1; i++) array3[i] = Scalar(1);
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| 51 | Scalar* array3unaligned = std::size_t(array3)%16 == 0 ? array3+1 : array3;
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| 52 | Map<MatrixType, Aligned>(array1, rows, cols) = MatrixType::Ones(rows,cols);
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| 53 | Map<MatrixType>(array2, rows, cols) = Map<MatrixType>((const Scalar*)array1, rows, cols); // test non-const-correctness support in eigen2
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| 54 | Map<MatrixType>(array3unaligned, rows, cols) = Map<MatrixType>(array1, rows, cols);
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| 55 | MatrixType ma1 = Map<MatrixType>(array1, rows, cols);
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| 56 | MatrixType ma2 = Map<MatrixType, Aligned>(array2, rows, cols);
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| 57 | VERIFY_IS_APPROX(ma1, ma2);
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| 58 | MatrixType ma3 = Map<MatrixType>(array3unaligned, rows, cols);
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| 59 | VERIFY_IS_APPROX(ma1, ma3);
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| 60 |
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| 61 | ei_aligned_delete(array1, size);
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| 62 | ei_aligned_delete(array2, size);
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| 63 | delete[] array3;
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| 64 | }
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| 65 |
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| 66 | template<typename VectorType> void map_static_methods(const VectorType& m)
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| 67 | {
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| 68 | typedef typename VectorType::Scalar Scalar;
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| 69 |
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| 70 | int size = m.size();
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| 71 |
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| 72 | // test Map.h
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| 73 | Scalar* array1 = ei_aligned_new<Scalar>(size);
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| 74 | Scalar* array2 = ei_aligned_new<Scalar>(size);
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| 75 | Scalar* array3 = new Scalar[size+1];
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| 76 | Scalar* array3unaligned = std::size_t(array3)%16 == 0 ? array3+1 : array3;
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| 77 |
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| 78 | VectorType::MapAligned(array1, size) = VectorType::Random(size);
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| 79 | VectorType::Map(array2, size) = VectorType::Map(array1, size);
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| 80 | VectorType::Map(array3unaligned, size) = VectorType::Map(array1, size);
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| 81 | VectorType ma1 = VectorType::Map(array1, size);
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| 82 | VectorType ma2 = VectorType::MapAligned(array2, size);
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| 83 | VectorType ma3 = VectorType::Map(array3unaligned, size);
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| 84 | VERIFY_IS_APPROX(ma1, ma2);
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| 85 | VERIFY_IS_APPROX(ma1, ma3);
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| 86 |
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| 87 | ei_aligned_delete(array1, size);
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| 88 | ei_aligned_delete(array2, size);
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| 89 | delete[] array3;
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| 90 | }
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| 91 |
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| 92 |
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| 93 | void test_eigen2_map()
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| 94 | {
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| 95 | for(int i = 0; i < g_repeat; i++) {
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| 96 | CALL_SUBTEST_1( map_class_vector(Matrix<float, 1, 1>()) );
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| 97 | CALL_SUBTEST_2( map_class_vector(Vector4d()) );
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| 98 | CALL_SUBTEST_3( map_class_vector(RowVector4f()) );
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| 99 | CALL_SUBTEST_4( map_class_vector(VectorXcf(8)) );
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| 100 | CALL_SUBTEST_5( map_class_vector(VectorXi(12)) );
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| 101 |
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| 102 | CALL_SUBTEST_1( map_class_matrix(Matrix<float, 1, 1>()) );
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| 103 | CALL_SUBTEST_2( map_class_matrix(Matrix4d()) );
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| 104 | CALL_SUBTEST_6( map_class_matrix(Matrix<float,3,5>()) );
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| 105 | CALL_SUBTEST_4( map_class_matrix(MatrixXcf(ei_random<int>(1,10),ei_random<int>(1,10))) );
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| 106 | CALL_SUBTEST_5( map_class_matrix(MatrixXi(ei_random<int>(1,10),ei_random<int>(1,10))) );
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| 107 |
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| 108 | CALL_SUBTEST_1( map_static_methods(Matrix<double, 1, 1>()) );
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| 109 | CALL_SUBTEST_2( map_static_methods(Vector3f()) );
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| 110 | CALL_SUBTEST_7( map_static_methods(RowVector3d()) );
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| 111 | CALL_SUBTEST_4( map_static_methods(VectorXcd(8)) );
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| 112 | CALL_SUBTEST_5( map_static_methods(VectorXf(12)) );
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| 113 | }
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| 114 | }
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