[136] | 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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