diff options
Diffstat (limited to 'test/sparse_product.cpp')
| -rw-r--r-- | test/sparse_product.cpp | 203 |
1 files changed, 166 insertions, 37 deletions
diff --git a/test/sparse_product.cpp b/test/sparse_product.cpp index a2ea9d5b7..c1edd26e3 100644 --- a/test/sparse_product.cpp +++ b/test/sparse_product.cpp @@ -7,37 +7,29 @@ // 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" +static long int nb_temporaries; -template<typename SparseMatrixType, typename DenseMatrix, bool IsRowMajor=SparseMatrixType::IsRowMajor> struct test_outer; +inline void on_temporary_creation() { + // here's a great place to set a breakpoint when debugging failures in this test! + nb_temporaries++; +} -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)); +#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 ); \ } -}; -// (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; + typedef typename SparseMatrixType::StorageIndex StorageIndex; Index n = 100; const Index rows = internal::random<Index>(1,n); const Index cols = internal::random<Index>(1,n); @@ -45,12 +37,12 @@ template<typename SparseMatrixType> void sparse_product() typedef typename SparseMatrixType::Scalar Scalar; enum { Flags = SparseMatrixType::Flags }; - double density = (std::max)(8./(rows*cols), 0.1); + double density = (std::max)(8./(rows*cols), 0.2); 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; + typedef SparseVector<Scalar,0,StorageIndex> ColSpVector; + typedef SparseVector<Scalar,RowMajor,StorageIndex> RowSpVector; Scalar s1 = internal::random<Scalar>(); Scalar s2 = internal::random<Scalar>(); @@ -93,33 +85,124 @@ template<typename SparseMatrixType> void sparse_product() 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()); + // make sure the right product implementation is called: + if((!SparseMatrixType::IsRowMajor) && m2.rows()<=m3.cols()) + { + VERIFY_EVALUATION_COUNT(m4 = m2*m3, 3); // 1 temp for the result + 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); + } + + // 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 + // 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 - test_outer<SparseMatrixType,DenseMatrix>::run(m2,m4,refMat2,refMat4); + { + Index c = internal::random<Index>(0,depth-1); + Index r = internal::random<Index>(0,rows-1); + Index c1 = internal::random<Index>(0,cols-1); + Index r1 = internal::random<Index>(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); @@ -131,11 +214,11 @@ template<typename SparseMatrixType> void sparse_product() 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(cv1=m3*cv0, dcv1=refMat3*dcv0); 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(cv1=rv0*m3, dcv1=drv0*refMat3); VERIFY_IS_APPROX(rv1=m3*cv0, drv1=refMat3*dcv0); } @@ -158,12 +241,16 @@ template<typename SparseMatrixType> void sparse_product() // 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); @@ -172,7 +259,7 @@ template<typename SparseMatrixType> void sparse_product() VERIFY_IS_APPROX(d3=d1*m2.transpose(), refM3=d1*refM2.transpose()); } - // test self adjoint products + // test self-adjoint and triangular-view products { DenseMatrix b = DenseMatrix::Random(rows, rows); DenseMatrix x = DenseMatrix::Random(rows, rows); @@ -180,9 +267,12 @@ template<typename SparseMatrixType> void sparse_product() 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<Scalar>(density, refA, mA); do { initSparse<Scalar>(density, refUp, mUp, ForceRealDiag|/*ForceNonZeroDiag|*/MakeUpperTriangular); } while (refUp.isZero()); @@ -195,26 +285,41 @@ template<typename SparseMatrixType> void sparse_product() 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; + it.valueRef() *= Scalar(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); + // sparse selfadjointView with dense matrices 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); + + VERIFY_IS_APPROX(x.noalias()+=mUp.template selfadjointView<Upper>()*b, refX+=refS*b); + VERIFY_IS_APPROX(x.noalias()-=mLo.template selfadjointView<Lower>()*b, refX-=refS*b); + VERIFY_IS_APPROX(x.noalias()+=mS.template selfadjointView<Upper|Lower>()*b, refX+=refS*b); - // sparse selfadjointView * sparse + // sparse selfadjointView with sparse matrices 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>()); + + // sparse triangularView with dense matrices + VERIFY_IS_APPROX(x=mA.template triangularView<Upper>()*b, refX=refA.template triangularView<Upper>()*b); + VERIFY_IS_APPROX(x=mA.template triangularView<Lower>()*b, refX=refA.template triangularView<Lower>()*b); + VERIFY_IS_APPROX(x=b*mA.template triangularView<Upper>(), refX=b*refA.template triangularView<Upper>()); + VERIFY_IS_APPROX(x=b*mA.template triangularView<Lower>(), refX=b*refA.template triangularView<Lower>()); + + // sparse triangularView with sparse matrices + VERIFY_IS_APPROX(mSres = mA.template triangularView<Lower>()*mS, refX = refA.template triangularView<Lower>()*refS); + VERIFY_IS_APPROX(mSres = mS * mA.template triangularView<Lower>(), refX = refS * refA.template triangularView<Lower>()); + VERIFY_IS_APPROX(mSres = mA.template triangularView<Upper>()*mS, refX = refA.template triangularView<Upper>()*refS); + VERIFY_IS_APPROX(mSres = mS * mA.template triangularView<Upper>(), refX = refS * refA.template triangularView<Upper>()); } - } // New test for Bug in SparseTimeDenseProduct @@ -239,11 +344,35 @@ template<typename SparseMatrixType, typename DenseMatrixType> void sparse_produc VERIFY_IS_APPROX( m4(0,0), 0.0 ); } +template<typename Scalar> +void bug_942() +{ + typedef Matrix<Scalar, Dynamic, 1> Vector; + typedef SparseMatrix<Scalar, ColMajor> ColSpMat; + typedef SparseMatrix<Scalar, RowMajor> 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 ); +} + 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_1( (bug_942<double>()) ); 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> >()) ); |