1 // This file is part of Eigen, a lightweight C++ template library 2 // for linear algebra. 3 // 4 // Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1 (at) gmail.com> 5 // 6 // This Source Code Form is subject to the terms of the Mozilla 7 // Public License v. 2.0. If a copy of the MPL was not distributed 8 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/. 9 10 #include "product.h" 11 12 void test_product_large() 13 { 14 for(int i = 0; i < g_repeat; i++) { 15 CALL_SUBTEST_1( product(MatrixXf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) ); 16 CALL_SUBTEST_2( product(MatrixXd(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) ); 17 CALL_SUBTEST_3( product(MatrixXi(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) ); 18 CALL_SUBTEST_4( product(MatrixXcf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE/2), internal::random<int>(1,EIGEN_TEST_MAX_SIZE/2))) ); 19 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))) ); 20 } 21 22 #if defined EIGEN_TEST_PART_6 23 { 24 // test a specific issue in DiagonalProduct 25 int N = 1000000; 26 VectorXf v = VectorXf::Ones(N); 27 MatrixXf m = MatrixXf::Ones(N,3); 28 m = (v+v).asDiagonal() * m; 29 VERIFY_IS_APPROX(m, MatrixXf::Constant(N,3,2)); 30 } 31 32 { 33 // test deferred resizing in Matrix::operator= 34 MatrixXf a = MatrixXf::Random(10,4), b = MatrixXf::Random(4,10), c = a; 35 VERIFY_IS_APPROX((a = a * b), (c * b).eval()); 36 } 37 38 { 39 // check the functions to setup blocking sizes compile and do not segfault 40 // FIXME check they do what they are supposed to do !! 41 std::ptrdiff_t l1 = internal::random<int>(10000,20000); 42 std::ptrdiff_t l2 = internal::random<int>(1000000,2000000); 43 setCpuCacheSizes(l1,l2); 44 VERIFY(l1==l1CacheSize()); 45 VERIFY(l2==l2CacheSize()); 46 std::ptrdiff_t k1 = internal::random<int>(10,100)*16; 47 std::ptrdiff_t m1 = internal::random<int>(10,100)*16; 48 std::ptrdiff_t n1 = internal::random<int>(10,100)*16; 49 // only makes sure it compiles fine 50 internal::computeProductBlockingSizes<float,float>(k1,m1,n1); 51 } 52 53 { 54 // test regression in row-vector by matrix (bad Map type) 55 MatrixXf mat1(10,32); mat1.setRandom(); 56 MatrixXf mat2(32,32); mat2.setRandom(); 57 MatrixXf r1 = mat1.row(2)*mat2.transpose(); 58 VERIFY_IS_APPROX(r1, (mat1.row(2)*mat2.transpose()).eval()); 59 60 MatrixXf r2 = mat1.row(2)*mat2; 61 VERIFY_IS_APPROX(r2, (mat1.row(2)*mat2).eval()); 62 } 63 #endif 64 } 65
