| // This file is part of Eigen, a lightweight C++ template library |
| // for linear algebra. |
| // |
| // Copyright (C) 2008-2011 Gael Guennebaud <gael.guennebaud@inria.fr> |
| // |
| // 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 "sparse.h" |
| |
| template<typename SparseMatrixType, typename DenseMatrix, bool IsRowMajor=SparseMatrixType::IsRowMajor> struct test_outer; |
| |
| template<typename SparseMatrixType, typename DenseMatrix> struct test_outer<SparseMatrixType,DenseMatrix,false> { |
| static void run(SparseMatrixType& m2, SparseMatrixType& m4, DenseMatrix& refMat2, DenseMatrix& refMat4) { |
| typedef typename SparseMatrixType::Index Index; |
| Index c = internal::random<Index>(0,m2.cols()-1); |
| Index c1 = internal::random<Index>(0,m2.cols()-1); |
| VERIFY_IS_APPROX(m4=m2.col(c)*refMat2.col(c1).transpose(), refMat4=refMat2.col(c)*refMat2.col(c1).transpose()); |
| VERIFY_IS_APPROX(m4=refMat2.col(c1)*m2.col(c).transpose(), refMat4=refMat2.col(c1)*refMat2.col(c).transpose()); |
| } |
| }; |
| |
| template<typename SparseMatrixType, typename DenseMatrix> struct test_outer<SparseMatrixType,DenseMatrix,true> { |
| static void run(SparseMatrixType& m2, SparseMatrixType& m4, DenseMatrix& refMat2, DenseMatrix& refMat4) { |
| typedef typename SparseMatrixType::Index Index; |
| Index r = internal::random<Index>(0,m2.rows()-1); |
| Index c1 = internal::random<Index>(0,m2.cols()-1); |
| VERIFY_IS_APPROX(m4=m2.row(r).transpose()*refMat2.col(c1).transpose(), refMat4=refMat2.row(r).transpose()*refMat2.col(c1).transpose()); |
| VERIFY_IS_APPROX(m4=refMat2.col(c1)*m2.row(r), refMat4=refMat2.col(c1)*refMat2.row(r)); |
| } |
| }; |
| |
| // (m2,m4,refMat2,refMat4,dv1); |
| // VERIFY_IS_APPROX(m4=m2.innerVector(c)*dv1.transpose(), refMat4=refMat2.colVector(c)*dv1.transpose()); |
| // VERIFY_IS_APPROX(m4=dv1*mcm.col(c).transpose(), refMat4=dv1*refMat2.col(c).transpose()); |
| |
| template<typename SparseMatrixType> void sparse_product() |
| { |
| typedef typename SparseMatrixType::Index Index; |
| Index n = 100; |
| const Index rows = internal::random<Index>(1,n); |
| const Index cols = internal::random<Index>(1,n); |
| const Index depth = internal::random<Index>(1,n); |
| typedef typename SparseMatrixType::Scalar Scalar; |
| enum { Flags = SparseMatrixType::Flags }; |
| |
| double density = (std::max)(8./(rows*cols), 0.1); |
| typedef Matrix<Scalar,Dynamic,Dynamic> DenseMatrix; |
| typedef Matrix<Scalar,Dynamic,1> DenseVector; |
| typedef Matrix<Scalar,1,Dynamic> RowDenseVector; |
| typedef SparseVector<Scalar,0,Index> ColSpVector; |
| typedef SparseVector<Scalar,RowMajor,Index> RowSpVector; |
| |
| Scalar s1 = internal::random<Scalar>(); |
| Scalar s2 = internal::random<Scalar>(); |
| |
| // test matrix-matrix product |
| { |
| DenseMatrix refMat2 = DenseMatrix::Zero(rows, depth); |
| DenseMatrix refMat2t = DenseMatrix::Zero(depth, rows); |
| DenseMatrix refMat3 = DenseMatrix::Zero(depth, cols); |
| DenseMatrix refMat3t = DenseMatrix::Zero(cols, depth); |
| DenseMatrix refMat4 = DenseMatrix::Zero(rows, cols); |
| DenseMatrix refMat4t = DenseMatrix::Zero(cols, rows); |
| DenseMatrix refMat5 = DenseMatrix::Random(depth, cols); |
| DenseMatrix refMat6 = DenseMatrix::Random(rows, rows); |
| DenseMatrix dm4 = DenseMatrix::Zero(rows, rows); |
| // DenseVector dv1 = DenseVector::Random(rows); |
| SparseMatrixType m2 (rows, depth); |
| SparseMatrixType m2t(depth, rows); |
| SparseMatrixType m3 (depth, cols); |
| SparseMatrixType m3t(cols, depth); |
| SparseMatrixType m4 (rows, cols); |
| SparseMatrixType m4t(cols, rows); |
| SparseMatrixType m6(rows, rows); |
| initSparse(density, refMat2, m2); |
| initSparse(density, refMat2t, m2t); |
| initSparse(density, refMat3, m3); |
| initSparse(density, refMat3t, m3t); |
| initSparse(density, refMat4, m4); |
| initSparse(density, refMat4t, m4t); |
| initSparse(density, refMat6, m6); |
| |
| // int c = internal::random<int>(0,depth-1); |
| |
| // sparse * sparse |
| VERIFY_IS_APPROX(m4=m2*m3, refMat4=refMat2*refMat3); |
| VERIFY_IS_APPROX(m4=m2t.transpose()*m3, refMat4=refMat2t.transpose()*refMat3); |
| VERIFY_IS_APPROX(m4=m2t.transpose()*m3t.transpose(), refMat4=refMat2t.transpose()*refMat3t.transpose()); |
| VERIFY_IS_APPROX(m4=m2*m3t.transpose(), refMat4=refMat2*refMat3t.transpose()); |
| |
| VERIFY_IS_APPROX(m4 = m2*m3/s1, refMat4 = refMat2*refMat3/s1); |
| VERIFY_IS_APPROX(m4 = m2*m3*s1, refMat4 = refMat2*refMat3*s1); |
| VERIFY_IS_APPROX(m4 = s2*m2*m3*s1, refMat4 = s2*refMat2*refMat3*s1); |
| |
| VERIFY_IS_APPROX(m4=(m2*m3).pruned(0), refMat4=refMat2*refMat3); |
| VERIFY_IS_APPROX(m4=(m2t.transpose()*m3).pruned(0), refMat4=refMat2t.transpose()*refMat3); |
| VERIFY_IS_APPROX(m4=(m2t.transpose()*m3t.transpose()).pruned(0), refMat4=refMat2t.transpose()*refMat3t.transpose()); |
| VERIFY_IS_APPROX(m4=(m2*m3t.transpose()).pruned(0), refMat4=refMat2*refMat3t.transpose()); |
| |
| // test aliasing |
| m4 = m2; refMat4 = refMat2; |
| VERIFY_IS_APPROX(m4=m4*m3, refMat4=refMat4*refMat3); |
| |
| // sparse * dense |
| VERIFY_IS_APPROX(dm4=m2*refMat3, refMat4=refMat2*refMat3); |
| VERIFY_IS_APPROX(dm4=m2*refMat3t.transpose(), refMat4=refMat2*refMat3t.transpose()); |
| VERIFY_IS_APPROX(dm4=m2t.transpose()*refMat3, refMat4=refMat2t.transpose()*refMat3); |
| VERIFY_IS_APPROX(dm4=m2t.transpose()*refMat3t.transpose(), refMat4=refMat2t.transpose()*refMat3t.transpose()); |
| |
| VERIFY_IS_APPROX(dm4=m2*(refMat3+refMat3), refMat4=refMat2*(refMat3+refMat3)); |
| VERIFY_IS_APPROX(dm4=m2t.transpose()*(refMat3+refMat5)*0.5, refMat4=refMat2t.transpose()*(refMat3+refMat5)*0.5); |
| |
| // dense * sparse |
| VERIFY_IS_APPROX(dm4=refMat2*m3, refMat4=refMat2*refMat3); |
| VERIFY_IS_APPROX(dm4=refMat2*m3t.transpose(), refMat4=refMat2*refMat3t.transpose()); |
| VERIFY_IS_APPROX(dm4=refMat2t.transpose()*m3, refMat4=refMat2t.transpose()*refMat3); |
| VERIFY_IS_APPROX(dm4=refMat2t.transpose()*m3t.transpose(), refMat4=refMat2t.transpose()*refMat3t.transpose()); |
| |
| // sparse * dense and dense * sparse outer product |
| test_outer<SparseMatrixType,DenseMatrix>::run(m2,m4,refMat2,refMat4); |
| |
| VERIFY_IS_APPROX(m6=m6*m6, refMat6=refMat6*refMat6); |
| |
| // sparse matrix * sparse vector |
| ColSpVector cv0(cols), cv1; |
| DenseVector dcv0(cols), dcv1; |
| initSparse(2*density,dcv0, cv0); |
| |
| RowSpVector rv0(depth), rv1; |
| RowDenseVector drv0(depth), drv1(rv1); |
| initSparse(2*density,drv0, rv0); |
| |
| VERIFY_IS_APPROX(cv1=rv0*m3, dcv1=drv0*refMat3); |
| VERIFY_IS_APPROX(rv1=rv0*m3, drv1=drv0*refMat3); |
| VERIFY_IS_APPROX(cv1=m3*cv0, dcv1=refMat3*dcv0); |
| VERIFY_IS_APPROX(cv1=m3t.adjoint()*cv0, dcv1=refMat3t.adjoint()*dcv0); |
| VERIFY_IS_APPROX(rv1=m3*cv0, drv1=refMat3*dcv0); |
| } |
| |
| // test matrix - diagonal product |
| { |
| DenseMatrix refM2 = DenseMatrix::Zero(rows, cols); |
| DenseMatrix refM3 = DenseMatrix::Zero(rows, cols); |
| DenseMatrix d3 = DenseMatrix::Zero(rows, cols); |
| DiagonalMatrix<Scalar,Dynamic> d1(DenseVector::Random(cols)); |
| DiagonalMatrix<Scalar,Dynamic> d2(DenseVector::Random(rows)); |
| SparseMatrixType m2(rows, cols); |
| SparseMatrixType m3(rows, cols); |
| initSparse<Scalar>(density, refM2, m2); |
| initSparse<Scalar>(density, refM3, m3); |
| VERIFY_IS_APPROX(m3=m2*d1, refM3=refM2*d1); |
| VERIFY_IS_APPROX(m3=m2.transpose()*d2, refM3=refM2.transpose()*d2); |
| VERIFY_IS_APPROX(m3=d2*m2, refM3=d2*refM2); |
| VERIFY_IS_APPROX(m3=d1*m2.transpose(), refM3=d1*refM2.transpose()); |
| |
| // also check with a SparseWrapper: |
| DenseVector v1 = DenseVector::Random(cols); |
| DenseVector v2 = DenseVector::Random(rows); |
| VERIFY_IS_APPROX(m3=m2*v1.asDiagonal(), refM3=refM2*v1.asDiagonal()); |
| VERIFY_IS_APPROX(m3=m2.transpose()*v2.asDiagonal(), refM3=refM2.transpose()*v2.asDiagonal()); |
| VERIFY_IS_APPROX(m3=v2.asDiagonal()*m2, refM3=v2.asDiagonal()*refM2); |
| VERIFY_IS_APPROX(m3=v1.asDiagonal()*m2.transpose(), refM3=v1.asDiagonal()*refM2.transpose()); |
| |
| VERIFY_IS_APPROX(m3=v2.asDiagonal()*m2*v1.asDiagonal(), refM3=v2.asDiagonal()*refM2*v1.asDiagonal()); |
| |
| // evaluate to a dense matrix to check the .row() and .col() iterator functions |
| VERIFY_IS_APPROX(d3=m2*d1, refM3=refM2*d1); |
| VERIFY_IS_APPROX(d3=m2.transpose()*d2, refM3=refM2.transpose()*d2); |
| VERIFY_IS_APPROX(d3=d2*m2, refM3=d2*refM2); |
| VERIFY_IS_APPROX(d3=d1*m2.transpose(), refM3=d1*refM2.transpose()); |
| } |
| |
| // test self adjoint products |
| { |
| DenseMatrix b = DenseMatrix::Random(rows, rows); |
| DenseMatrix x = DenseMatrix::Random(rows, rows); |
| DenseMatrix refX = DenseMatrix::Random(rows, rows); |
| DenseMatrix refUp = DenseMatrix::Zero(rows, rows); |
| DenseMatrix refLo = DenseMatrix::Zero(rows, rows); |
| DenseMatrix refS = DenseMatrix::Zero(rows, rows); |
| SparseMatrixType mUp(rows, rows); |
| SparseMatrixType mLo(rows, rows); |
| SparseMatrixType mS(rows, rows); |
| do { |
| initSparse<Scalar>(density, refUp, mUp, ForceRealDiag|/*ForceNonZeroDiag|*/MakeUpperTriangular); |
| } while (refUp.isZero()); |
| refLo = refUp.adjoint(); |
| mLo = mUp.adjoint(); |
| refS = refUp + refLo; |
| refS.diagonal() *= 0.5; |
| mS = mUp + mLo; |
| // TODO be able to address the diagonal.... |
| for (int k=0; k<mS.outerSize(); ++k) |
| for (typename SparseMatrixType::InnerIterator it(mS,k); it; ++it) |
| if (it.index() == k) |
| it.valueRef() *= 0.5; |
| |
| VERIFY_IS_APPROX(refS.adjoint(), refS); |
| VERIFY_IS_APPROX(mS.adjoint(), mS); |
| VERIFY_IS_APPROX(mS, refS); |
| VERIFY_IS_APPROX(x=mS*b, refX=refS*b); |
| |
| VERIFY_IS_APPROX(x=mUp.template selfadjointView<Upper>()*b, refX=refS*b); |
| VERIFY_IS_APPROX(x=mLo.template selfadjointView<Lower>()*b, refX=refS*b); |
| VERIFY_IS_APPROX(x=mS.template selfadjointView<Upper|Lower>()*b, refX=refS*b); |
| |
| // sparse selfadjointView * sparse |
| SparseMatrixType mSres(rows,rows); |
| VERIFY_IS_APPROX(mSres = mLo.template selfadjointView<Lower>()*mS, |
| refX = refLo.template selfadjointView<Lower>()*refS); |
| // sparse * sparse selfadjointview |
| VERIFY_IS_APPROX(mSres = mS * mLo.template selfadjointView<Lower>(), |
| refX = refS * refLo.template selfadjointView<Lower>()); |
| } |
| |
| } |
| |
| // New test for Bug in SparseTimeDenseProduct |
| template<typename SparseMatrixType, typename DenseMatrixType> void sparse_product_regression_test() |
| { |
| // This code does not compile with afflicted versions of the bug |
| SparseMatrixType sm1(3,2); |
| DenseMatrixType m2(2,2); |
| sm1.setZero(); |
| m2.setZero(); |
| |
| DenseMatrixType m3 = sm1*m2; |
| |
| |
| // This code produces a segfault with afflicted versions of another SparseTimeDenseProduct |
| // bug |
| |
| SparseMatrixType sm2(20000,2); |
| sm2.setZero(); |
| DenseMatrixType m4(sm2*m2); |
| |
| VERIFY_IS_APPROX( m4(0,0), 0.0 ); |
| } |
| |
| void test_sparse_product() |
| { |
| for(int i = 0; i < g_repeat; i++) { |
| CALL_SUBTEST_1( (sparse_product<SparseMatrix<double,ColMajor> >()) ); |
| CALL_SUBTEST_1( (sparse_product<SparseMatrix<double,RowMajor> >()) ); |
| CALL_SUBTEST_2( (sparse_product<SparseMatrix<std::complex<double>, ColMajor > >()) ); |
| CALL_SUBTEST_2( (sparse_product<SparseMatrix<std::complex<double>, RowMajor > >()) ); |
| CALL_SUBTEST_3( (sparse_product<SparseMatrix<float,ColMajor,long int> >()) ); |
| CALL_SUBTEST_4( (sparse_product_regression_test<SparseMatrix<double,RowMajor>, Matrix<double, Dynamic, Dynamic, RowMajor> >()) ); |
| } |
| } |