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Diffstat (limited to 'test/sparse_product.cpp')
-rw-r--r-- | test/sparse_product.cpp | 204 |
1 files changed, 204 insertions, 0 deletions
diff --git a/test/sparse_product.cpp b/test/sparse_product.cpp new file mode 100644 index 000000000..17a955c9d --- /dev/null +++ b/test/sparse_product.cpp @@ -0,0 +1,204 @@ +// 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) { + int c = internal::random(0,m2.cols()-1); + int c1 = internal::random(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) { + int r = internal::random(0,m2.rows()-1); + int c1 = internal::random(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<int>(1,n); + const Index cols = internal::random<int>(1,n); + const Index depth = internal::random<int>(1,n); + typedef typename SparseMatrixType::Scalar Scalar; + enum { Flags = SparseMatrixType::Flags }; + + double density = (std::max)(8./(rows*cols), 0.01); + typedef Matrix<Scalar,Dynamic,Dynamic> DenseMatrix; + typedef Matrix<Scalar,Dynamic,1> DenseVector; + + 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); + } + + // test matrix - diagonal product + { + DenseMatrix refM2 = DenseMatrix::Zero(rows, rows); + DenseMatrix refM3 = DenseMatrix::Zero(rows, rows); + DiagonalMatrix<Scalar,Dynamic> d1(DenseVector::Random(rows)); + SparseMatrixType m2(rows, rows); + SparseMatrixType m3(rows, rows); + 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()*d1, refM3=refM2.transpose()*d1); + VERIFY_IS_APPROX(m3=d1*m2, refM3=d1*refM2); + VERIFY_IS_APPROX(m3=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); + } +} + +// 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_4( (sparse_product_regression_test<SparseMatrix<double,RowMajor>, Matrix<double, Dynamic, Dynamic, RowMajor> >()) ); + } +} |