You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
252 lines
11 KiB
252 lines
11 KiB
// 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> >()) );
|
|
}
|
|
}
|