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 "main.h" 11 12 template<typename MatrixType> void product_extra(const MatrixType& m) 13 { 14 typedef typename MatrixType::Index Index; 15 typedef typename MatrixType::Scalar Scalar; 16 typedef typename NumTraits<Scalar>::NonInteger NonInteger; 17 typedef Matrix<Scalar, 1, Dynamic> RowVectorType; 18 typedef Matrix<Scalar, Dynamic, 1> ColVectorType; 19 typedef Matrix<Scalar, Dynamic, Dynamic, 20 MatrixType::Flags&RowMajorBit> OtherMajorMatrixType; 21 22 Index rows = m.rows(); 23 Index cols = m.cols(); 24 25 MatrixType m1 = MatrixType::Random(rows, cols), 26 m2 = MatrixType::Random(rows, cols), 27 m3(rows, cols), 28 mzero = MatrixType::Zero(rows, cols), 29 identity = MatrixType::Identity(rows, rows), 30 square = MatrixType::Random(rows, rows), 31 res = MatrixType::Random(rows, rows), 32 square2 = MatrixType::Random(cols, cols), 33 res2 = MatrixType::Random(cols, cols); 34 RowVectorType v1 = RowVectorType::Random(rows), vrres(rows); 35 ColVectorType vc2 = ColVectorType::Random(cols), vcres(cols); 36 OtherMajorMatrixType tm1 = m1; 37 38 Scalar s1 = internal::random<Scalar>(), 39 s2 = internal::random<Scalar>(), 40 s3 = internal::random<Scalar>(); 41 42 VERIFY_IS_APPROX(m3.noalias() = m1 * m2.adjoint(), m1 * m2.adjoint().eval()); 43 VERIFY_IS_APPROX(m3.noalias() = m1.adjoint() * square.adjoint(), m1.adjoint().eval() * square.adjoint().eval()); 44 VERIFY_IS_APPROX(m3.noalias() = m1.adjoint() * m2, m1.adjoint().eval() * m2); 45 VERIFY_IS_APPROX(m3.noalias() = (s1 * m1.adjoint()) * m2, (s1 * m1.adjoint()).eval() * m2); 46 VERIFY_IS_APPROX(m3.noalias() = ((s1 * m1).adjoint()) * m2, (internal::conj(s1) * m1.adjoint()).eval() * m2); 47 VERIFY_IS_APPROX(m3.noalias() = (- m1.adjoint() * s1) * (s3 * m2), (- m1.adjoint() * s1).eval() * (s3 * m2).eval()); 48 VERIFY_IS_APPROX(m3.noalias() = (s2 * m1.adjoint() * s1) * m2, (s2 * m1.adjoint() * s1).eval() * m2); 49 VERIFY_IS_APPROX(m3.noalias() = (-m1*s2) * s1*m2.adjoint(), (-m1*s2).eval() * (s1*m2.adjoint()).eval()); 50 51 // a very tricky case where a scale factor has to be automatically conjugated: 52 VERIFY_IS_APPROX( m1.adjoint() * (s1*m2).conjugate(), (m1.adjoint()).eval() * ((s1*m2).conjugate()).eval()); 53 54 55 // test all possible conjugate combinations for the four matrix-vector product cases: 56 57 VERIFY_IS_APPROX((-m1.conjugate() * s2) * (s1 * vc2), 58 (-m1.conjugate()*s2).eval() * (s1 * vc2).eval()); 59 VERIFY_IS_APPROX((-m1 * s2) * (s1 * vc2.conjugate()), 60 (-m1*s2).eval() * (s1 * vc2.conjugate()).eval()); 61 VERIFY_IS_APPROX((-m1.conjugate() * s2) * (s1 * vc2.conjugate()), 62 (-m1.conjugate()*s2).eval() * (s1 * vc2.conjugate()).eval()); 63 64 VERIFY_IS_APPROX((s1 * vc2.transpose()) * (-m1.adjoint() * s2), 65 (s1 * vc2.transpose()).eval() * (-m1.adjoint()*s2).eval()); 66 VERIFY_IS_APPROX((s1 * vc2.adjoint()) * (-m1.transpose() * s2), 67 (s1 * vc2.adjoint()).eval() * (-m1.transpose()*s2).eval()); 68 VERIFY_IS_APPROX((s1 * vc2.adjoint()) * (-m1.adjoint() * s2), 69 (s1 * vc2.adjoint()).eval() * (-m1.adjoint()*s2).eval()); 70 71 VERIFY_IS_APPROX((-m1.adjoint() * s2) * (s1 * v1.transpose()), 72 (-m1.adjoint()*s2).eval() * (s1 * v1.transpose()).eval()); 73 VERIFY_IS_APPROX((-m1.transpose() * s2) * (s1 * v1.adjoint()), 74 (-m1.transpose()*s2).eval() * (s1 * v1.adjoint()).eval()); 75 VERIFY_IS_APPROX((-m1.adjoint() * s2) * (s1 * v1.adjoint()), 76 (-m1.adjoint()*s2).eval() * (s1 * v1.adjoint()).eval()); 77 78 VERIFY_IS_APPROX((s1 * v1) * (-m1.conjugate() * s2), 79 (s1 * v1).eval() * (-m1.conjugate()*s2).eval()); 80 VERIFY_IS_APPROX((s1 * v1.conjugate()) * (-m1 * s2), 81 (s1 * v1.conjugate()).eval() * (-m1*s2).eval()); 82 VERIFY_IS_APPROX((s1 * v1.conjugate()) * (-m1.conjugate() * s2), 83 (s1 * v1.conjugate()).eval() * (-m1.conjugate()*s2).eval()); 84 85 VERIFY_IS_APPROX((-m1.adjoint() * s2) * (s1 * v1.adjoint()), 86 (-m1.adjoint()*s2).eval() * (s1 * v1.adjoint()).eval()); 87 88 // test the vector-matrix product with non aligned starts 89 Index i = internal::random<Index>(0,m1.rows()-2); 90 Index j = internal::random<Index>(0,m1.cols()-2); 91 Index r = internal::random<Index>(1,m1.rows()-i); 92 Index c = internal::random<Index>(1,m1.cols()-j); 93 Index i2 = internal::random<Index>(0,m1.rows()-1); 94 Index j2 = internal::random<Index>(0,m1.cols()-1); 95 96 VERIFY_IS_APPROX(m1.col(j2).adjoint() * m1.block(0,j,m1.rows(),c), m1.col(j2).adjoint().eval() * m1.block(0,j,m1.rows(),c).eval()); 97 VERIFY_IS_APPROX(m1.block(i,0,r,m1.cols()) * m1.row(i2).adjoint(), m1.block(i,0,r,m1.cols()).eval() * m1.row(i2).adjoint().eval()); 98 99 // regression test 100 MatrixType tmp = m1 * m1.adjoint() * s1; 101 VERIFY_IS_APPROX(tmp, m1 * m1.adjoint() * s1); 102 } 103 104 // Regression test for bug reported at http://forum.kde.org/viewtopic.php?f=74&t=96947 105 void mat_mat_scalar_scalar_product() 106 { 107 Eigen::Matrix2Xd dNdxy(2, 3); 108 dNdxy << -0.5, 0.5, 0, 109 -0.3, 0, 0.3; 110 double det = 6.0, wt = 0.5; 111 VERIFY_IS_APPROX(dNdxy.transpose()*dNdxy*det*wt, det*wt*dNdxy.transpose()*dNdxy); 112 } 113 114 void zero_sized_objects() 115 { 116 // Bug 127 117 // 118 // a product of the form lhs*rhs with 119 // 120 // lhs: 121 // rows = 1, cols = 4 122 // RowsAtCompileTime = 1, ColsAtCompileTime = -1 123 // MaxRowsAtCompileTime = 1, MaxColsAtCompileTime = 5 124 // 125 // rhs: 126 // rows = 4, cols = 0 127 // RowsAtCompileTime = -1, ColsAtCompileTime = -1 128 // MaxRowsAtCompileTime = 5, MaxColsAtCompileTime = 1 129 // 130 // was failing on a runtime assertion, because it had been mis-compiled as a dot product because Product.h was using the 131 // max-sizes to detect size 1 indicating vectors, and that didn't account for 0-sized object with max-size 1. 132 133 Matrix<float,1,Dynamic,RowMajor,1,5> a(1,4); 134 Matrix<float,Dynamic,Dynamic,ColMajor,5,1> b(4,0); 135 a*b; 136 } 137 138 void test_product_extra() 139 { 140 for(int i = 0; i < g_repeat; i++) { 141 CALL_SUBTEST_1( product_extra(MatrixXf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) ); 142 CALL_SUBTEST_2( product_extra(MatrixXd(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) ); 143 CALL_SUBTEST_2( mat_mat_scalar_scalar_product() ); 144 CALL_SUBTEST_3( product_extra(MatrixXcf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE/2), internal::random<int>(1,EIGEN_TEST_MAX_SIZE/2))) ); 145 CALL_SUBTEST_4( product_extra(MatrixXcd(internal::random<int>(1,EIGEN_TEST_MAX_SIZE/2), internal::random<int>(1,EIGEN_TEST_MAX_SIZE/2))) ); 146 CALL_SUBTEST_5( zero_sized_objects() ); 147 } 148 } 149
