|  | // This file is part of Eigen, a lightweight C++ template library | 
|  | // for linear algebra. | 
|  | // | 
|  | // Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com> | 
|  | // | 
|  | // This Source Code Form is subject to the terms of the Mozilla | 
|  | // Public License v. 2.0. If a copy of the MPL was not distributed | 
|  | // with this file, You can obtain one at http://mozilla.org/MPL/2.0/. | 
|  |  | 
|  | #include "product.h" | 
|  | #include <Eigen/LU> | 
|  |  | 
|  | // regression test for bug 447 | 
|  | template<int> | 
|  | void product1x1() | 
|  | { | 
|  | Matrix<float,1,3> matAstatic; | 
|  | Matrix<float,3,1> matBstatic; | 
|  | matAstatic.setRandom(); | 
|  | matBstatic.setRandom(); | 
|  | VERIFY_IS_APPROX( (matAstatic * matBstatic).coeff(0,0), | 
|  | matAstatic.cwiseProduct(matBstatic.transpose()).sum() ); | 
|  |  | 
|  | MatrixXf matAdynamic(1,3); | 
|  | MatrixXf matBdynamic(3,1); | 
|  | matAdynamic.setRandom(); | 
|  | matBdynamic.setRandom(); | 
|  | VERIFY_IS_APPROX( (matAdynamic * matBdynamic).coeff(0,0), | 
|  | matAdynamic.cwiseProduct(matBdynamic.transpose()).sum() ); | 
|  | } | 
|  |  | 
|  | template<typename TC, typename TA, typename TB> | 
|  | const TC& ref_prod(TC &C, const TA &A, const TB &B) | 
|  | { | 
|  | for(Index i=0;i<C.rows();++i) | 
|  | for(Index j=0;j<C.cols();++j) | 
|  | for(Index k=0;k<A.cols();++k) | 
|  | C.coeffRef(i,j) += A.coeff(i,k) * B.coeff(k,j); | 
|  | return C; | 
|  | } | 
|  |  | 
|  | template<typename T, int Rows, int Cols, int Depth, int OC, int OA, int OB> | 
|  | typename internal::enable_if<! ( (Rows ==1&&Depth!=1&&OA==ColMajor) | 
|  | || (Depth==1&&Rows !=1&&OA==RowMajor) | 
|  | || (Cols ==1&&Depth!=1&&OB==RowMajor) | 
|  | || (Depth==1&&Cols !=1&&OB==ColMajor) | 
|  | || (Rows ==1&&Cols !=1&&OC==ColMajor) | 
|  | || (Cols ==1&&Rows !=1&&OC==RowMajor)),void>::type | 
|  | test_lazy_single(int rows, int cols, int depth) | 
|  | { | 
|  | Matrix<T,Rows,Depth,OA> A(rows,depth); A.setRandom(); | 
|  | Matrix<T,Depth,Cols,OB> B(depth,cols); B.setRandom(); | 
|  | Matrix<T,Rows,Cols,OC>  C(rows,cols);  C.setRandom(); | 
|  | Matrix<T,Rows,Cols,OC>  D(C); | 
|  | VERIFY_IS_APPROX(C+=A.lazyProduct(B), ref_prod(D,A,B)); | 
|  | } | 
|  |  | 
|  | void test_dynamic_bool() | 
|  | { | 
|  | int rows = internal::random<int>(1,64); | 
|  | int cols = internal::random<int>(1,64); | 
|  | int depth = internal::random<int>(1,65); | 
|  |  | 
|  | typedef Matrix<bool,Dynamic,Dynamic> MatrixX; | 
|  | MatrixX A(rows,depth); A.setRandom(); | 
|  | MatrixX B(depth,cols); B.setRandom(); | 
|  | MatrixX C(rows,cols);  C.setRandom(); | 
|  | MatrixX D(C); | 
|  | for(Index i=0;i<C.rows();++i) | 
|  | for(Index j=0;j<C.cols();++j) | 
|  | for(Index k=0;k<A.cols();++k) | 
|  | D.coeffRef(i,j) |= A.coeff(i,k) & B.coeff(k,j); | 
|  | C += A * B; | 
|  | VERIFY_IS_EQUAL(C, D); | 
|  |  | 
|  | MatrixX E = B.transpose(); | 
|  | for(Index i=0;i<B.rows();++i) | 
|  | for(Index j=0;j<B.cols();++j) | 
|  | VERIFY_IS_EQUAL(B(i,j), E(j,i)); | 
|  | } | 
|  |  | 
|  | template<typename T, int Rows, int Cols, int Depth, int OC, int OA, int OB> | 
|  | typename internal::enable_if<  ( (Rows ==1&&Depth!=1&&OA==ColMajor) | 
|  | || (Depth==1&&Rows !=1&&OA==RowMajor) | 
|  | || (Cols ==1&&Depth!=1&&OB==RowMajor) | 
|  | || (Depth==1&&Cols !=1&&OB==ColMajor) | 
|  | || (Rows ==1&&Cols !=1&&OC==ColMajor) | 
|  | || (Cols ==1&&Rows !=1&&OC==RowMajor)),void>::type | 
|  | test_lazy_single(int, int, int) | 
|  | { | 
|  | } | 
|  |  | 
|  | template<typename T, int Rows, int Cols, int Depth> | 
|  | void test_lazy_all_layout(int rows=Rows, int cols=Cols, int depth=Depth) | 
|  | { | 
|  | CALL_SUBTEST(( test_lazy_single<T,Rows,Cols,Depth,ColMajor,ColMajor,ColMajor>(rows,cols,depth) )); | 
|  | CALL_SUBTEST(( test_lazy_single<T,Rows,Cols,Depth,RowMajor,ColMajor,ColMajor>(rows,cols,depth) )); | 
|  | CALL_SUBTEST(( test_lazy_single<T,Rows,Cols,Depth,ColMajor,RowMajor,ColMajor>(rows,cols,depth) )); | 
|  | CALL_SUBTEST(( test_lazy_single<T,Rows,Cols,Depth,RowMajor,RowMajor,ColMajor>(rows,cols,depth) )); | 
|  | CALL_SUBTEST(( test_lazy_single<T,Rows,Cols,Depth,ColMajor,ColMajor,RowMajor>(rows,cols,depth) )); | 
|  | CALL_SUBTEST(( test_lazy_single<T,Rows,Cols,Depth,RowMajor,ColMajor,RowMajor>(rows,cols,depth) )); | 
|  | CALL_SUBTEST(( test_lazy_single<T,Rows,Cols,Depth,ColMajor,RowMajor,RowMajor>(rows,cols,depth) )); | 
|  | CALL_SUBTEST(( test_lazy_single<T,Rows,Cols,Depth,RowMajor,RowMajor,RowMajor>(rows,cols,depth) )); | 
|  | } | 
|  |  | 
|  | template<typename T> | 
|  | void test_lazy_l1() | 
|  | { | 
|  | int rows = internal::random<int>(1,12); | 
|  | int cols = internal::random<int>(1,12); | 
|  | int depth = internal::random<int>(1,12); | 
|  |  | 
|  | // Inner | 
|  | CALL_SUBTEST(( test_lazy_all_layout<T,1,1,1>() )); | 
|  | CALL_SUBTEST(( test_lazy_all_layout<T,1,1,2>() )); | 
|  | CALL_SUBTEST(( test_lazy_all_layout<T,1,1,3>() )); | 
|  | CALL_SUBTEST(( test_lazy_all_layout<T,1,1,8>() )); | 
|  | CALL_SUBTEST(( test_lazy_all_layout<T,1,1,9>() )); | 
|  | CALL_SUBTEST(( test_lazy_all_layout<T,1,1,-1>(1,1,depth) )); | 
|  |  | 
|  | // Outer | 
|  | CALL_SUBTEST(( test_lazy_all_layout<T,2,1,1>() )); | 
|  | CALL_SUBTEST(( test_lazy_all_layout<T,1,2,1>() )); | 
|  | CALL_SUBTEST(( test_lazy_all_layout<T,2,2,1>() )); | 
|  | CALL_SUBTEST(( test_lazy_all_layout<T,3,3,1>() )); | 
|  | CALL_SUBTEST(( test_lazy_all_layout<T,4,4,1>() )); | 
|  | CALL_SUBTEST(( test_lazy_all_layout<T,4,8,1>() )); | 
|  | CALL_SUBTEST(( test_lazy_all_layout<T,4,-1,1>(4,cols) )); | 
|  | CALL_SUBTEST(( test_lazy_all_layout<T,7,-1,1>(7,cols) )); | 
|  | CALL_SUBTEST(( test_lazy_all_layout<T,-1,8,1>(rows) )); | 
|  | CALL_SUBTEST(( test_lazy_all_layout<T,-1,3,1>(rows) )); | 
|  | CALL_SUBTEST(( test_lazy_all_layout<T,-1,-1,1>(rows,cols) )); | 
|  | } | 
|  |  | 
|  | template<typename T> | 
|  | void test_lazy_l2() | 
|  | { | 
|  | int rows = internal::random<int>(1,12); | 
|  | int cols = internal::random<int>(1,12); | 
|  | int depth = internal::random<int>(1,12); | 
|  |  | 
|  | // mat-vec | 
|  | CALL_SUBTEST(( test_lazy_all_layout<T,2,1,2>() )); | 
|  | CALL_SUBTEST(( test_lazy_all_layout<T,2,1,4>() )); | 
|  | CALL_SUBTEST(( test_lazy_all_layout<T,4,1,2>() )); | 
|  | CALL_SUBTEST(( test_lazy_all_layout<T,4,1,4>() )); | 
|  | CALL_SUBTEST(( test_lazy_all_layout<T,5,1,4>() )); | 
|  | CALL_SUBTEST(( test_lazy_all_layout<T,4,1,5>() )); | 
|  | CALL_SUBTEST(( test_lazy_all_layout<T,4,1,6>() )); | 
|  | CALL_SUBTEST(( test_lazy_all_layout<T,6,1,4>() )); | 
|  | CALL_SUBTEST(( test_lazy_all_layout<T,8,1,8>() )); | 
|  | CALL_SUBTEST(( test_lazy_all_layout<T,-1,1,4>(rows) )); | 
|  | CALL_SUBTEST(( test_lazy_all_layout<T,4,1,-1>(4,1,depth) )); | 
|  | CALL_SUBTEST(( test_lazy_all_layout<T,-1,1,-1>(rows,1,depth) )); | 
|  |  | 
|  | // vec-mat | 
|  | CALL_SUBTEST(( test_lazy_all_layout<T,1,2,2>() )); | 
|  | CALL_SUBTEST(( test_lazy_all_layout<T,1,2,4>() )); | 
|  | CALL_SUBTEST(( test_lazy_all_layout<T,1,4,2>() )); | 
|  | CALL_SUBTEST(( test_lazy_all_layout<T,1,4,4>() )); | 
|  | CALL_SUBTEST(( test_lazy_all_layout<T,1,5,4>() )); | 
|  | CALL_SUBTEST(( test_lazy_all_layout<T,1,4,5>() )); | 
|  | CALL_SUBTEST(( test_lazy_all_layout<T,1,4,6>() )); | 
|  | CALL_SUBTEST(( test_lazy_all_layout<T,1,6,4>() )); | 
|  | CALL_SUBTEST(( test_lazy_all_layout<T,1,8,8>() )); | 
|  | CALL_SUBTEST(( test_lazy_all_layout<T,1,-1, 4>(1,cols) )); | 
|  | CALL_SUBTEST(( test_lazy_all_layout<T,1, 4,-1>(1,4,depth) )); | 
|  | CALL_SUBTEST(( test_lazy_all_layout<T,1,-1,-1>(1,cols,depth) )); | 
|  | } | 
|  |  | 
|  | template<typename T> | 
|  | void test_lazy_l3() | 
|  | { | 
|  | int rows = internal::random<int>(1,12); | 
|  | int cols = internal::random<int>(1,12); | 
|  | int depth = internal::random<int>(1,12); | 
|  | // mat-mat | 
|  | CALL_SUBTEST(( test_lazy_all_layout<T,2,4,2>() )); | 
|  | CALL_SUBTEST(( test_lazy_all_layout<T,2,6,4>() )); | 
|  | CALL_SUBTEST(( test_lazy_all_layout<T,4,3,2>() )); | 
|  | CALL_SUBTEST(( test_lazy_all_layout<T,4,8,4>() )); | 
|  | CALL_SUBTEST(( test_lazy_all_layout<T,5,6,4>() )); | 
|  | CALL_SUBTEST(( test_lazy_all_layout<T,4,2,5>() )); | 
|  | CALL_SUBTEST(( test_lazy_all_layout<T,4,7,6>() )); | 
|  | CALL_SUBTEST(( test_lazy_all_layout<T,6,8,4>() )); | 
|  | CALL_SUBTEST(( test_lazy_all_layout<T,8,3,8>() )); | 
|  | CALL_SUBTEST(( test_lazy_all_layout<T,-1,6,4>(rows) )); | 
|  | CALL_SUBTEST(( test_lazy_all_layout<T,4,3,-1>(4,3,depth) )); | 
|  | CALL_SUBTEST(( test_lazy_all_layout<T,-1,6,-1>(rows,6,depth) )); | 
|  | CALL_SUBTEST(( test_lazy_all_layout<T,8,2,2>() )); | 
|  | CALL_SUBTEST(( test_lazy_all_layout<T,5,2,4>() )); | 
|  | CALL_SUBTEST(( test_lazy_all_layout<T,4,4,2>() )); | 
|  | CALL_SUBTEST(( test_lazy_all_layout<T,8,4,4>() )); | 
|  | CALL_SUBTEST(( test_lazy_all_layout<T,6,5,4>() )); | 
|  | CALL_SUBTEST(( test_lazy_all_layout<T,4,4,5>() )); | 
|  | CALL_SUBTEST(( test_lazy_all_layout<T,3,4,6>() )); | 
|  | CALL_SUBTEST(( test_lazy_all_layout<T,2,6,4>() )); | 
|  | CALL_SUBTEST(( test_lazy_all_layout<T,7,8,8>() )); | 
|  | CALL_SUBTEST(( test_lazy_all_layout<T,8,-1, 4>(8,cols) )); | 
|  | CALL_SUBTEST(( test_lazy_all_layout<T,3, 4,-1>(3,4,depth) )); | 
|  | CALL_SUBTEST(( test_lazy_all_layout<T,4,-1,-1>(4,cols,depth) )); | 
|  | } | 
|  |  | 
|  | template<typename T,int N,int M,int K> | 
|  | void test_linear_but_not_vectorizable() | 
|  | { | 
|  | // Check tricky cases for which the result of the product is a vector and thus must exhibit the LinearBit flag, | 
|  | // but is not vectorizable along the linear dimension. | 
|  | Index n = N==Dynamic ? internal::random<Index>(1,32) : N; | 
|  | Index m = M==Dynamic ? internal::random<Index>(1,32) : M; | 
|  | Index k = K==Dynamic ? internal::random<Index>(1,32) : K; | 
|  |  | 
|  | { | 
|  | Matrix<T,N,M+1> A; A.setRandom(n,m+1); | 
|  | Matrix<T,M*2,K> B; B.setRandom(m*2,k); | 
|  | Matrix<T,1,K> C; | 
|  | Matrix<T,1,K> R; | 
|  |  | 
|  | C.noalias() = A.template topLeftCorner<1,M>() * (B.template topRows<M>()+B.template bottomRows<M>()); | 
|  | R.noalias() = A.template topLeftCorner<1,M>() * (B.template topRows<M>()+B.template bottomRows<M>()).eval(); | 
|  | VERIFY_IS_APPROX(C,R); | 
|  | } | 
|  |  | 
|  | { | 
|  | Matrix<T,M+1,N,RowMajor> A; A.setRandom(m+1,n); | 
|  | Matrix<T,K,M*2,RowMajor> B; B.setRandom(k,m*2); | 
|  | Matrix<T,K,1> C; | 
|  | Matrix<T,K,1> R; | 
|  |  | 
|  | C.noalias() = (B.template leftCols<M>()+B.template rightCols<M>())        * A.template topLeftCorner<M,1>(); | 
|  | R.noalias() = (B.template leftCols<M>()+B.template rightCols<M>()).eval() * A.template topLeftCorner<M,1>(); | 
|  | VERIFY_IS_APPROX(C,R); | 
|  | } | 
|  | } | 
|  |  | 
|  | template<int Rows> | 
|  | void bug_1311() | 
|  | { | 
|  | Matrix< double, Rows, 2 > A;  A.setRandom(); | 
|  | Vector2d b = Vector2d::Random() ; | 
|  | Matrix<double,Rows,1> res; | 
|  | res.noalias() = 1. * (A * b); | 
|  | VERIFY_IS_APPROX(res, A*b); | 
|  | res.noalias() = 1.*A * b; | 
|  | VERIFY_IS_APPROX(res, A*b); | 
|  | res.noalias() = (1.*A).lazyProduct(b); | 
|  | VERIFY_IS_APPROX(res, A*b); | 
|  | res.noalias() = (1.*A).lazyProduct(1.*b); | 
|  | VERIFY_IS_APPROX(res, A*b); | 
|  | res.noalias() = (A).lazyProduct(1.*b); | 
|  | VERIFY_IS_APPROX(res, A*b); | 
|  | } | 
|  |  | 
|  | template<int> | 
|  | void product_small_regressions() | 
|  | { | 
|  | { | 
|  | // test compilation of (outer_product) * vector | 
|  | Vector3f v = Vector3f::Random(); | 
|  | VERIFY_IS_APPROX( (v * v.transpose()) * v, (v * v.transpose()).eval() * v); | 
|  | } | 
|  |  | 
|  | { | 
|  | // regression test for pull-request #93 | 
|  | Eigen::Matrix<double, 1, 1> A;  A.setRandom(); | 
|  | Eigen::Matrix<double, 18, 1> B; B.setRandom(); | 
|  | Eigen::Matrix<double, 1, 18> C; C.setRandom(); | 
|  | VERIFY_IS_APPROX(B * A.inverse(), B * A.inverse()[0]); | 
|  | VERIFY_IS_APPROX(A.inverse() * C, A.inverse()[0] * C); | 
|  | } | 
|  |  | 
|  | { | 
|  | Eigen::Matrix<double, 10, 10> A, B, C; | 
|  | A.setRandom(); | 
|  | C = A; | 
|  | for(int k=0; k<79; ++k) | 
|  | C = C * A; | 
|  | B.noalias() = (((A*A)*(A*A))*((A*A)*(A*A))*((A*A)*(A*A))*((A*A)*(A*A))*((A*A)*(A*A)) * ((A*A)*(A*A))*((A*A)*(A*A))*((A*A)*(A*A))*((A*A)*(A*A))*((A*A)*(A*A))) | 
|  | * (((A*A)*(A*A))*((A*A)*(A*A))*((A*A)*(A*A))*((A*A)*(A*A))*((A*A)*(A*A)) * ((A*A)*(A*A))*((A*A)*(A*A))*((A*A)*(A*A))*((A*A)*(A*A))*((A*A)*(A*A))); | 
|  | VERIFY_IS_APPROX(B,C); | 
|  | } | 
|  | } | 
|  |  | 
|  | EIGEN_DECLARE_TEST(product_small) | 
|  | { | 
|  | for(int i = 0; i < g_repeat; i++) { | 
|  | CALL_SUBTEST_1( product(Matrix<float, 3, 2>()) ); | 
|  | CALL_SUBTEST_2( product(Matrix<int, 3, 17>()) ); | 
|  | CALL_SUBTEST_8( product(Matrix<double, 3, 17>()) ); | 
|  | CALL_SUBTEST_3( product(Matrix3d()) ); | 
|  | CALL_SUBTEST_4( product(Matrix4d()) ); | 
|  | CALL_SUBTEST_5( product(Matrix4f()) ); | 
|  | CALL_SUBTEST_6( product1x1<0>() ); | 
|  |  | 
|  | CALL_SUBTEST_11( test_lazy_l1<float>() ); | 
|  | CALL_SUBTEST_12( test_lazy_l2<float>() ); | 
|  | CALL_SUBTEST_13( test_lazy_l3<float>() ); | 
|  |  | 
|  | CALL_SUBTEST_21( test_lazy_l1<double>() ); | 
|  | CALL_SUBTEST_22( test_lazy_l2<double>() ); | 
|  | CALL_SUBTEST_23( test_lazy_l3<double>() ); | 
|  |  | 
|  | CALL_SUBTEST_31( test_lazy_l1<std::complex<float> >() ); | 
|  | CALL_SUBTEST_32( test_lazy_l2<std::complex<float> >() ); | 
|  | CALL_SUBTEST_33( test_lazy_l3<std::complex<float> >() ); | 
|  |  | 
|  | CALL_SUBTEST_41( test_lazy_l1<std::complex<double> >() ); | 
|  | CALL_SUBTEST_42( test_lazy_l2<std::complex<double> >() ); | 
|  | CALL_SUBTEST_43( test_lazy_l3<std::complex<double> >() ); | 
|  |  | 
|  | CALL_SUBTEST_7(( test_linear_but_not_vectorizable<float,2,1,Dynamic>() )); | 
|  | CALL_SUBTEST_7(( test_linear_but_not_vectorizable<float,3,1,Dynamic>() )); | 
|  | CALL_SUBTEST_7(( test_linear_but_not_vectorizable<float,2,1,16>() )); | 
|  |  | 
|  | CALL_SUBTEST_6( bug_1311<3>() ); | 
|  | CALL_SUBTEST_6( bug_1311<5>() ); | 
|  |  | 
|  | CALL_SUBTEST_9( test_dynamic_bool() ); | 
|  | } | 
|  |  | 
|  | CALL_SUBTEST_6( product_small_regressions<0>() ); | 
|  | } |