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@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
12void 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