// This file is part of Eigen, a lightweight C++ template library // for linear algebra. // // Copyright (C) 2008-2011 Gael Guennebaud // // 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/. #if defined(_MSC_VER) && (_MSC_VER==1800) // This unit test takes forever to compile in Release mode with MSVC 2013, // multiple hours. So let's switch off optimization for this one. #pragma optimize("",off) #endif static long int nb_temporaries; inline void on_temporary_creation() { // here's a great place to set a breakpoint when debugging failures in this test! nb_temporaries++; } #define EIGEN_SPARSE_CREATE_TEMPORARY_PLUGIN { on_temporary_creation(); } #include "sparse.h" #define VERIFY_EVALUATION_COUNT(XPR,N) {\ nb_temporaries = 0; \ CALL_SUBTEST( XPR ); \ if(nb_temporaries!=N) std::cerr << "nb_temporaries == " << nb_temporaries << "\n"; \ VERIFY( (#XPR) && nb_temporaries==N ); \ } template void sparse_product() { typedef typename SparseMatrixType::StorageIndex StorageIndex; Index n = 100; const Index rows = internal::random(1,n); const Index cols = internal::random(1,n); const Index depth = internal::random(1,n); typedef typename SparseMatrixType::Scalar Scalar; enum { Flags = SparseMatrixType::Flags }; double density = (std::max)(8./(rows*cols), 0.2); typedef Matrix DenseMatrix; typedef Matrix DenseVector; typedef Matrix RowDenseVector; typedef SparseVector ColSpVector; typedef SparseVector RowSpVector; Scalar s1 = internal::random(); Scalar s2 = internal::random(); // 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(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+m2)*m3, refMat4 = (refMat2+refMat2)*refMat3); VERIFY_IS_APPROX(m4 = m2*m3.leftCols(cols/2), refMat4 = refMat2*refMat3.leftCols(cols/2)); VERIFY_IS_APPROX(m4 = m2*(m3+m3).leftCols(cols/2), refMat4 = refMat2*(refMat3+refMat3).leftCols(cols/2)); 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()); #ifndef EIGEN_SPARSE_PRODUCT_IGNORE_TEMPORARY_COUNT // make sure the right product implementation is called: if((!SparseMatrixType::IsRowMajor) && m2.rows()<=m3.cols()) { VERIFY_EVALUATION_COUNT(m4 = m2*m3, 2); // 2 for transposing and get a sorted result. VERIFY_EVALUATION_COUNT(m4 = (m2*m3).pruned(0), 1); VERIFY_EVALUATION_COUNT(m4 = (m2*m3).eval().pruned(0), 4); } #endif // and that pruning is effective: { DenseMatrix Ad(2,2); Ad << -1, 1, 1, 1; SparseMatrixType As(Ad.sparseView()), B(2,2); VERIFY_IS_EQUAL( (As*As.transpose()).eval().nonZeros(), 4); VERIFY_IS_EQUAL( (Ad*Ad.transpose()).eval().sparseView().eval().nonZeros(), 2); VERIFY_IS_EQUAL( (As*As.transpose()).pruned(1e-6).eval().nonZeros(), 2); } // dense ?= sparse * sparse VERIFY_IS_APPROX(dm4 =m2*m3, refMat4 =refMat2*refMat3); VERIFY_IS_APPROX(dm4+=m2*m3, refMat4+=refMat2*refMat3); VERIFY_IS_APPROX(dm4-=m2*m3, refMat4-=refMat2*refMat3); VERIFY_IS_APPROX(dm4 =m2t.transpose()*m3, refMat4 =refMat2t.transpose()*refMat3); VERIFY_IS_APPROX(dm4+=m2t.transpose()*m3, refMat4+=refMat2t.transpose()*refMat3); VERIFY_IS_APPROX(dm4-=m2t.transpose()*m3, refMat4-=refMat2t.transpose()*refMat3); VERIFY_IS_APPROX(dm4 =m2t.transpose()*m3t.transpose(), refMat4 =refMat2t.transpose()*refMat3t.transpose()); VERIFY_IS_APPROX(dm4+=m2t.transpose()*m3t.transpose(), refMat4+=refMat2t.transpose()*refMat3t.transpose()); VERIFY_IS_APPROX(dm4-=m2t.transpose()*m3t.transpose(), refMat4-=refMat2t.transpose()*refMat3t.transpose()); VERIFY_IS_APPROX(dm4 =m2*m3t.transpose(), refMat4 =refMat2*refMat3t.transpose()); VERIFY_IS_APPROX(dm4+=m2*m3t.transpose(), refMat4+=refMat2*refMat3t.transpose()); VERIFY_IS_APPROX(dm4-=m2*m3t.transpose(), refMat4-=refMat2*refMat3t.transpose()); VERIFY_IS_APPROX(dm4 = m2*m3*s1, refMat4 = refMat2*refMat3*s1); // test aliasing m4 = m2; refMat4 = refMat2; VERIFY_IS_APPROX(m4=m4*m3, refMat4=refMat4*refMat3); // sparse * dense matrix 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, refMat4=refMat2*refMat3); VERIFY_IS_APPROX(dm4=dm4+m2*refMat3, refMat4=refMat4+refMat2*refMat3); VERIFY_IS_APPROX(dm4+=m2*refMat3, refMat4+=refMat2*refMat3); VERIFY_IS_APPROX(dm4-=m2*refMat3, refMat4-=refMat2*refMat3); VERIFY_IS_APPROX(dm4.noalias()+=m2*refMat3, refMat4+=refMat2*refMat3); VERIFY_IS_APPROX(dm4.noalias()-=m2*refMat3, refMat4-=refMat2*refMat3); 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); // sparse * dense vector VERIFY_IS_APPROX(dm4.col(0)=m2*refMat3.col(0), refMat4.col(0)=refMat2*refMat3.col(0)); VERIFY_IS_APPROX(dm4.col(0)=m2*refMat3t.transpose().col(0), refMat4.col(0)=refMat2*refMat3t.transpose().col(0)); VERIFY_IS_APPROX(dm4.col(0)=m2t.transpose()*refMat3.col(0), refMat4.col(0)=refMat2t.transpose()*refMat3.col(0)); VERIFY_IS_APPROX(dm4.col(0)=m2t.transpose()*refMat3t.transpose().col(0), refMat4.col(0)=refMat2t.transpose()*refMat3t.transpose().col(0)); // dense * sparse VERIFY_IS_APPROX(dm4=refMat2*m3, refMat4=refMat2*refMat3); VERIFY_IS_APPROX(dm4=dm4+refMat2*m3, refMat4=refMat4+refMat2*refMat3); VERIFY_IS_APPROX(dm4+=refMat2*m3, refMat4+=refMat2*refMat3); VERIFY_IS_APPROX(dm4-=refMat2*m3, refMat4-=refMat2*refMat3); VERIFY_IS_APPROX(dm4.noalias()+=refMat2*m3, refMat4+=refMat2*refMat3); VERIFY_IS_APPROX(dm4.noalias()-=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 { Index c = internal::random(0,depth-1); Index r = internal::random(0,rows-1); Index c1 = internal::random(0,cols-1); Index r1 = internal::random(0,depth-1); DenseMatrix dm5 = DenseMatrix::Random(depth, cols); VERIFY_IS_APPROX( m4=m2.col(c)*dm5.col(c1).transpose(), refMat4=refMat2.col(c)*dm5.col(c1).transpose()); VERIFY_IS_EQUAL(m4.nonZeros(), (refMat4.array()!=0).count()); VERIFY_IS_APPROX( m4=m2.middleCols(c,1)*dm5.col(c1).transpose(), refMat4=refMat2.col(c)*dm5.col(c1).transpose()); VERIFY_IS_EQUAL(m4.nonZeros(), (refMat4.array()!=0).count()); VERIFY_IS_APPROX(dm4=m2.col(c)*dm5.col(c1).transpose(), refMat4=refMat2.col(c)*dm5.col(c1).transpose()); VERIFY_IS_APPROX(m4=dm5.col(c1)*m2.col(c).transpose(), refMat4=dm5.col(c1)*refMat2.col(c).transpose()); VERIFY_IS_EQUAL(m4.nonZeros(), (refMat4.array()!=0).count()); VERIFY_IS_APPROX(m4=dm5.col(c1)*m2.middleCols(c,1).transpose(), refMat4=dm5.col(c1)*refMat2.col(c).transpose()); VERIFY_IS_EQUAL(m4.nonZeros(), (refMat4.array()!=0).count()); VERIFY_IS_APPROX(dm4=dm5.col(c1)*m2.col(c).transpose(), refMat4=dm5.col(c1)*refMat2.col(c).transpose()); VERIFY_IS_APPROX( m4=dm5.row(r1).transpose()*m2.col(c).transpose(), refMat4=dm5.row(r1).transpose()*refMat2.col(c).transpose()); VERIFY_IS_EQUAL(m4.nonZeros(), (refMat4.array()!=0).count()); VERIFY_IS_APPROX(dm4=dm5.row(r1).transpose()*m2.col(c).transpose(), refMat4=dm5.row(r1).transpose()*refMat2.col(c).transpose()); VERIFY_IS_APPROX( m4=m2.row(r).transpose()*dm5.col(c1).transpose(), refMat4=refMat2.row(r).transpose()*dm5.col(c1).transpose()); VERIFY_IS_EQUAL(m4.nonZeros(), (refMat4.array()!=0).count()); VERIFY_IS_APPROX( m4=m2.middleRows(r,1).transpose()*dm5.col(c1).transpose(), refMat4=refMat2.row(r).transpose()*dm5.col(c1).transpose()); VERIFY_IS_EQUAL(m4.nonZeros(), (refMat4.array()!=0).count()); VERIFY_IS_APPROX(dm4=m2.row(r).transpose()*dm5.col(c1).transpose(), refMat4=refMat2.row(r).transpose()*dm5.col(c1).transpose()); VERIFY_IS_APPROX( m4=dm5.col(c1)*m2.row(r), refMat4=dm5.col(c1)*refMat2.row(r)); VERIFY_IS_EQUAL(m4.nonZeros(), (refMat4.array()!=0).count()); VERIFY_IS_APPROX( m4=dm5.col(c1)*m2.middleRows(r,1), refMat4=dm5.col(c1)*refMat2.row(r)); VERIFY_IS_EQUAL(m4.nonZeros(), (refMat4.array()!=0).count()); VERIFY_IS_APPROX(dm4=dm5.col(c1)*m2.row(r), refMat4=dm5.col(c1)*refMat2.row(r)); VERIFY_IS_APPROX( m4=dm5.row(r1).transpose()*m2.row(r), refMat4=dm5.row(r1).transpose()*refMat2.row(r)); VERIFY_IS_EQUAL(m4.nonZeros(), (refMat4.array()!=0).count()); VERIFY_IS_APPROX(dm4=dm5.row(r1).transpose()*m2.row(r), refMat4=dm5.row(r1).transpose()*refMat2.row(r)); } 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=m3*cv0, dcv1=refMat3*dcv0); VERIFY_IS_APPROX(rv1=rv0*m3, drv1=drv0*refMat3); VERIFY_IS_APPROX(cv1=m3t.adjoint()*cv0, dcv1=refMat3t.adjoint()*dcv0); VERIFY_IS_APPROX(cv1=rv0*m3, dcv1=drv0*refMat3); 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 d1(DenseVector::Random(cols)); DiagonalMatrix d2(DenseVector::Random(rows)); SparseMatrixType m2(rows, cols); SparseMatrixType m3(rows, cols); initSparse(density, refM2, m2); initSparse(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); DenseVector v3 = 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()); VERIFY_IS_APPROX(v2=m2*v1.asDiagonal()*v1, refM2*v1.asDiagonal()*v1); VERIFY_IS_APPROX(v3=v2.asDiagonal()*m2*v1, v2.asDiagonal()*refM2*v1); // 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 and triangular-view 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); DenseMatrix refA = DenseMatrix::Zero(rows, rows); SparseMatrixType mUp(rows, rows); SparseMatrixType mLo(rows, rows); SparseMatrixType mS(rows, rows); SparseMatrixType mA(rows, rows); initSparse(density, refA, mA); do { initSparse(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()*b, refX=refS*b); VERIFY_IS_APPROX(x=mLo.template selfadjointView()*b, refX=refS*b); VERIFY_IS_APPROX(x=mS.template selfadjointView()*b, refX=refS*b); VERIFY_IS_APPROX(x=b * mUp.template selfadjointView(), refX=b*refS); VERIFY_IS_APPROX(x=b * mLo.template selfadjointView(), refX=b*refS); VERIFY_IS_APPROX(x=b * mS.template selfadjointView(), refX=b*refS); VERIFY_IS_APPROX(x.noalias()+=mUp.template selfadjointView()*b, refX+=refS*b); VERIFY_IS_APPROX(x.noalias()-=mLo.template selfadjointView()*b, refX-=refS*b); VERIFY_IS_APPROX(x.noalias()+=mS.template selfadjointView()*b, refX+=refS*b); // sparse selfadjointView with sparse matrices SparseMatrixType mSres(rows,rows); VERIFY_IS_APPROX(mSres = mLo.template selfadjointView()*mS, refX = refLo.template selfadjointView()*refS); VERIFY_IS_APPROX(mSres = mS * mLo.template selfadjointView(), refX = refS * refLo.template selfadjointView()); // sparse triangularView with dense matrices VERIFY_IS_APPROX(x=mA.template triangularView()*b, refX=refA.template triangularView()*b); VERIFY_IS_APPROX(x=mA.template triangularView()*b, refX=refA.template triangularView()*b); VERIFY_IS_APPROX(x=b*mA.template triangularView(), refX=b*refA.template triangularView()); VERIFY_IS_APPROX(x=b*mA.template triangularView(), refX=b*refA.template triangularView()); // sparse triangularView with sparse matrices VERIFY_IS_APPROX(mSres = mA.template triangularView()*mS, refX = refA.template triangularView()*refS); VERIFY_IS_APPROX(mSres = mS * mA.template triangularView(), refX = refS * refA.template triangularView()); VERIFY_IS_APPROX(mSres = mA.template triangularView()*mS, refX = refA.template triangularView()*refS); VERIFY_IS_APPROX(mSres = mS * mA.template triangularView(), refX = refS * refA.template triangularView()); } } // New test for Bug in SparseTimeDenseProduct template 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 ); } template void bug_942() { typedef Matrix Vector; typedef SparseMatrix ColSpMat; typedef SparseMatrix RowSpMat; ColSpMat cmA(1,1); cmA.insert(0,0) = 1; RowSpMat rmA(1,1); rmA.insert(0,0) = 1; Vector d(1); d[0] = 2; double res = 2; VERIFY_IS_APPROX( ( cmA*d.asDiagonal() ).eval().coeff(0,0), res ); VERIFY_IS_APPROX( ( d.asDiagonal()*rmA ).eval().coeff(0,0), res ); VERIFY_IS_APPROX( ( rmA*d.asDiagonal() ).eval().coeff(0,0), res ); VERIFY_IS_APPROX( ( d.asDiagonal()*cmA ).eval().coeff(0,0), res ); } template void test_mixing_types() { typedef std::complex Cplx; typedef SparseMatrix SpMatReal; typedef SparseMatrix SpMatCplx; typedef SparseMatrix SpRowMatCplx; typedef Matrix DenseMatReal; typedef Matrix DenseMatCplx; Index n = internal::random(1,100); double density = (std::max)(8./(n*n), 0.2); SpMatReal sR1(n,n); SpMatCplx sC1(n,n), sC2(n,n), sC3(n,n); SpRowMatCplx sCR(n,n); DenseMatReal dR1(n,n); DenseMatCplx dC1(n,n), dC2(n,n), dC3(n,n); initSparse(density, dR1, sR1); initSparse(density, dC1, sC1); initSparse(density, dC2, sC2); VERIFY_IS_APPROX( sC2 = (sR1 * sC1), dC3 = dR1.template cast() * dC1 ); VERIFY_IS_APPROX( sC2 = (sC1 * sR1), dC3 = dC1 * dR1.template cast() ); VERIFY_IS_APPROX( sC2 = (sR1.transpose() * sC1), dC3 = dR1.template cast().transpose() * dC1 ); VERIFY_IS_APPROX( sC2 = (sC1.transpose() * sR1), dC3 = dC1.transpose() * dR1.template cast() ); VERIFY_IS_APPROX( sC2 = (sR1 * sC1.transpose()), dC3 = dR1.template cast() * dC1.transpose() ); VERIFY_IS_APPROX( sC2 = (sC1 * sR1.transpose()), dC3 = dC1 * dR1.template cast().transpose() ); VERIFY_IS_APPROX( sC2 = (sR1.transpose() * sC1.transpose()), dC3 = dR1.template cast().transpose() * dC1.transpose() ); VERIFY_IS_APPROX( sC2 = (sC1.transpose() * sR1.transpose()), dC3 = dC1.transpose() * dR1.template cast().transpose() ); VERIFY_IS_APPROX( sCR = (sR1 * sC1), dC3 = dR1.template cast() * dC1 ); VERIFY_IS_APPROX( sCR = (sC1 * sR1), dC3 = dC1 * dR1.template cast() ); VERIFY_IS_APPROX( sCR = (sR1.transpose() * sC1), dC3 = dR1.template cast().transpose() * dC1 ); VERIFY_IS_APPROX( sCR = (sC1.transpose() * sR1), dC3 = dC1.transpose() * dR1.template cast() ); VERIFY_IS_APPROX( sCR = (sR1 * sC1.transpose()), dC3 = dR1.template cast() * dC1.transpose() ); VERIFY_IS_APPROX( sCR = (sC1 * sR1.transpose()), dC3 = dC1 * dR1.template cast().transpose() ); VERIFY_IS_APPROX( sCR = (sR1.transpose() * sC1.transpose()), dC3 = dR1.template cast().transpose() * dC1.transpose() ); VERIFY_IS_APPROX( sCR = (sC1.transpose() * sR1.transpose()), dC3 = dC1.transpose() * dR1.template cast().transpose() ); VERIFY_IS_APPROX( sC2 = (sR1 * sC1).pruned(), dC3 = dR1.template cast() * dC1 ); VERIFY_IS_APPROX( sC2 = (sC1 * sR1).pruned(), dC3 = dC1 * dR1.template cast() ); VERIFY_IS_APPROX( sC2 = (sR1.transpose() * sC1).pruned(), dC3 = dR1.template cast().transpose() * dC1 ); VERIFY_IS_APPROX( sC2 = (sC1.transpose() * sR1).pruned(), dC3 = dC1.transpose() * dR1.template cast() ); VERIFY_IS_APPROX( sC2 = (sR1 * sC1.transpose()).pruned(), dC3 = dR1.template cast() * dC1.transpose() ); VERIFY_IS_APPROX( sC2 = (sC1 * sR1.transpose()).pruned(), dC3 = dC1 * dR1.template cast().transpose() ); VERIFY_IS_APPROX( sC2 = (sR1.transpose() * sC1.transpose()).pruned(), dC3 = dR1.template cast().transpose() * dC1.transpose() ); VERIFY_IS_APPROX( sC2 = (sC1.transpose() * sR1.transpose()).pruned(), dC3 = dC1.transpose() * dR1.template cast().transpose() ); VERIFY_IS_APPROX( sCR = (sR1 * sC1).pruned(), dC3 = dR1.template cast() * dC1 ); VERIFY_IS_APPROX( sCR = (sC1 * sR1).pruned(), dC3 = dC1 * dR1.template cast() ); VERIFY_IS_APPROX( sCR = (sR1.transpose() * sC1).pruned(), dC3 = dR1.template cast().transpose() * dC1 ); VERIFY_IS_APPROX( sCR = (sC1.transpose() * sR1).pruned(), dC3 = dC1.transpose() * dR1.template cast() ); VERIFY_IS_APPROX( sCR = (sR1 * sC1.transpose()).pruned(), dC3 = dR1.template cast() * dC1.transpose() ); VERIFY_IS_APPROX( sCR = (sC1 * sR1.transpose()).pruned(), dC3 = dC1 * dR1.template cast().transpose() ); VERIFY_IS_APPROX( sCR = (sR1.transpose() * sC1.transpose()).pruned(), dC3 = dR1.template cast().transpose() * dC1.transpose() ); VERIFY_IS_APPROX( sCR = (sC1.transpose() * sR1.transpose()).pruned(), dC3 = dC1.transpose() * dR1.template cast().transpose() ); VERIFY_IS_APPROX( dC2 = (sR1 * sC1), dC3 = dR1.template cast() * dC1 ); VERIFY_IS_APPROX( dC2 = (sC1 * sR1), dC3 = dC1 * dR1.template cast() ); VERIFY_IS_APPROX( dC2 = (sR1.transpose() * sC1), dC3 = dR1.template cast().transpose() * dC1 ); VERIFY_IS_APPROX( dC2 = (sC1.transpose() * sR1), dC3 = dC1.transpose() * dR1.template cast() ); VERIFY_IS_APPROX( dC2 = (sR1 * sC1.transpose()), dC3 = dR1.template cast() * dC1.transpose() ); VERIFY_IS_APPROX( dC2 = (sC1 * sR1.transpose()), dC3 = dC1 * dR1.template cast().transpose() ); VERIFY_IS_APPROX( dC2 = (sR1.transpose() * sC1.transpose()), dC3 = dR1.template cast().transpose() * dC1.transpose() ); VERIFY_IS_APPROX( dC2 = (sC1.transpose() * sR1.transpose()), dC3 = dC1.transpose() * dR1.template cast().transpose() ); VERIFY_IS_APPROX( dC2 = dR1 * sC1, dC3 = dR1.template cast() * sC1 ); VERIFY_IS_APPROX( dC2 = sR1 * dC1, dC3 = sR1.template cast() * dC1 ); VERIFY_IS_APPROX( dC2 = dC1 * sR1, dC3 = dC1 * sR1.template cast() ); VERIFY_IS_APPROX( dC2 = sC1 * dR1, dC3 = sC1 * dR1.template cast() ); VERIFY_IS_APPROX( dC2 = dR1.row(0) * sC1, dC3 = dR1.template cast().row(0) * sC1 ); VERIFY_IS_APPROX( dC2 = sR1 * dC1.col(0), dC3 = sR1.template cast() * dC1.col(0) ); VERIFY_IS_APPROX( dC2 = dC1.row(0) * sR1, dC3 = dC1.row(0) * sR1.template cast() ); VERIFY_IS_APPROX( dC2 = sC1 * dR1.col(0), dC3 = sC1 * dR1.template cast().col(0) ); } EIGEN_DECLARE_TEST(sparse_product) { for(int i = 0; i < g_repeat; i++) { CALL_SUBTEST_1( (sparse_product >()) ); CALL_SUBTEST_1( (sparse_product >()) ); CALL_SUBTEST_1( (bug_942()) ); CALL_SUBTEST_2( (sparse_product, ColMajor > >()) ); CALL_SUBTEST_2( (sparse_product, RowMajor > >()) ); CALL_SUBTEST_3( (sparse_product >()) ); CALL_SUBTEST_4( (sparse_product_regression_test, Matrix >()) ); CALL_SUBTEST_5( (test_mixing_types()) ); } }