1 | // This file is part of Eigen, a lightweight C++ template library
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2 | // for linear algebra.
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3 | //
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4 | // Copyright (C) 2006-2008 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 "product.h"
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11 |
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12 | template<typename T>
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13 | void test_aliasing()
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14 | {
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15 | int rows = internal::random<int>(1,12);
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16 | int cols = internal::random<int>(1,12);
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17 | typedef Matrix<T,Dynamic,Dynamic> MatrixType;
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18 | typedef Matrix<T,Dynamic,1> VectorType;
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19 | VectorType x(cols); x.setRandom();
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20 | VectorType z(x);
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21 | VectorType y(rows); y.setZero();
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22 | MatrixType A(rows,cols); A.setRandom();
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23 | // CwiseBinaryOp
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24 | VERIFY_IS_APPROX(x = y + A*x, A*z);
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25 | x = z;
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26 | // CwiseUnaryOp
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27 | VERIFY_IS_APPROX(x = T(1.)*(A*x), A*z);
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28 | x = z;
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29 | VERIFY_IS_APPROX(x = y+(-(A*x)), -A*z);
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30 | x = z;
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31 | }
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32 |
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33 | void test_product_large()
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34 | {
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35 | for(int i = 0; i < g_repeat; i++) {
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36 | CALL_SUBTEST_1( product(MatrixXf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
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37 | CALL_SUBTEST_2( product(MatrixXd(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
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38 | CALL_SUBTEST_3( product(MatrixXi(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
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39 | CALL_SUBTEST_4( product(MatrixXcf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE/2), internal::random<int>(1,EIGEN_TEST_MAX_SIZE/2))) );
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40 | CALL_SUBTEST_5( product(Matrix<float,Dynamic,Dynamic,RowMajor>(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
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41 |
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42 | CALL_SUBTEST_1( test_aliasing<float>() );
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43 | }
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44 |
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45 | #if defined EIGEN_TEST_PART_6
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46 | {
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47 | // test a specific issue in DiagonalProduct
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48 | int N = 1000000;
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49 | VectorXf v = VectorXf::Ones(N);
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50 | MatrixXf m = MatrixXf::Ones(N,3);
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51 | m = (v+v).asDiagonal() * m;
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52 | VERIFY_IS_APPROX(m, MatrixXf::Constant(N,3,2));
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53 | }
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54 |
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55 | {
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56 | // test deferred resizing in Matrix::operator=
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57 | MatrixXf a = MatrixXf::Random(10,4), b = MatrixXf::Random(4,10), c = a;
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58 | VERIFY_IS_APPROX((a = a * b), (c * b).eval());
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59 | }
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60 |
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61 | {
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62 | // check the functions to setup blocking sizes compile and do not segfault
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63 | // FIXME check they do what they are supposed to do !!
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64 | std::ptrdiff_t l1 = internal::random<int>(10000,20000);
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65 | std::ptrdiff_t l2 = internal::random<int>(1000000,2000000);
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66 | setCpuCacheSizes(l1,l2);
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67 | VERIFY(l1==l1CacheSize());
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68 | VERIFY(l2==l2CacheSize());
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69 | std::ptrdiff_t k1 = internal::random<int>(10,100)*16;
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70 | std::ptrdiff_t m1 = internal::random<int>(10,100)*16;
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71 | std::ptrdiff_t n1 = internal::random<int>(10,100)*16;
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72 | // only makes sure it compiles fine
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73 | internal::computeProductBlockingSizes<float,float>(k1,m1,n1);
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74 | }
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75 |
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76 | {
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77 | // test regression in row-vector by matrix (bad Map type)
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78 | MatrixXf mat1(10,32); mat1.setRandom();
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79 | MatrixXf mat2(32,32); mat2.setRandom();
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80 | MatrixXf r1 = mat1.row(2)*mat2.transpose();
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81 | VERIFY_IS_APPROX(r1, (mat1.row(2)*mat2.transpose()).eval());
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82 |
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83 | MatrixXf r2 = mat1.row(2)*mat2;
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84 | VERIFY_IS_APPROX(r2, (mat1.row(2)*mat2).eval());
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85 | }
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86 | #endif
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87 | }
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