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split the Sparse module into multiple ones, and move non stable parts to unsupported/

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(see the ML for details)
This commit is contained in:
Gael Guennebaud
2010-06-18 11:28:30 +02:00
parent 22d07ec2e3
commit ece48a6450
22 changed files with 350 additions and 489 deletions
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50
test/CMakeLists.txt
View File

@@ -16,56 +16,6 @@ else(GSL_FOUND)
set(GSL_LIBRARIES " ")
endif(GSL_FOUND)
set(SPARSE_LIBS "")
find_package(Taucs)
if(TAUCS_FOUND)
add_definitions("-DEIGEN_TAUCS_SUPPORT")
include_directories(${TAUCS_INCLUDES})
set(SPARSE_LIBS ${SPARSE_LIBS} ${TAUCS_LIBRARIES})
ei_add_property(EIGEN_TESTED_BACKENDS "Taucs, ")
else(TAUCS_FOUND)
ei_add_property(EIGEN_MISSING_BACKENDS "Taucs, ")
endif(TAUCS_FOUND)
find_package(Cholmod)
if(CHOLMOD_FOUND)
add_definitions("-DEIGEN_CHOLMOD_SUPPORT")
include_directories(${CHOLMOD_INCLUDES})
set(SPARSE_LIBS ${SPARSE_LIBS} ${CHOLMOD_LIBRARIES})
ei_add_property(EIGEN_TESTED_BACKENDS "Cholmod, ")
else(CHOLMOD_FOUND)
ei_add_property(EIGEN_MISSING_BACKENDS "Cholmod, ")
endif(CHOLMOD_FOUND)
find_package(Umfpack)
if(UMFPACK_FOUND)
add_definitions("-DEIGEN_UMFPACK_SUPPORT")
include_directories(${UMFPACK_INCLUDES})
set(SPARSE_LIBS ${SPARSE_LIBS} ${UMFPACK_LIBRARIES})
ei_add_property(EIGEN_TESTED_BACKENDS "UmfPack, ")
else(UMFPACK_FOUND)
ei_add_property(EIGEN_MISSING_BACKENDS "UmfPack, ")
endif(UMFPACK_FOUND)
find_package(SuperLU)
if(SUPERLU_FOUND)
add_definitions("-DEIGEN_SUPERLU_SUPPORT")
include_directories(${SUPERLU_INCLUDES})
set(SPARSE_LIBS ${SPARSE_LIBS} ${SUPERLU_LIBRARIES})
ei_add_property(EIGEN_TESTED_BACKENDS "SuperLU, ")
else(SUPERLU_FOUND)
ei_add_property(EIGEN_MISSING_BACKENDS "SuperLU, ")
endif(SUPERLU_FOUND)
find_package(GoogleHash)
if(GOOGLEHASH_FOUND)
add_definitions("-DEIGEN_GOOGLEHASH_SUPPORT")
include_directories(${GOOGLEHASH_INCLUDES})
ei_add_property(EIGEN_TESTED_BACKENDS "GoogleHash, ")
else(GOOGLEHASH_FOUND)
ei_add_property(EIGEN_MISSING_BACKENDS "GoogleHash, ")
endif(GOOGLEHASH_FOUND)
option(EIGEN_TEST_NOQT "Disable Qt support in unit tests" OFF)
if(NOT EIGEN_TEST_NOQT)

113
test/sparse_basic.cpp
View File

@@ -24,40 +24,6 @@
#include "sparse.h"
template<typename SetterType,typename DenseType, typename Scalar, int Options>
bool test_random_setter(SparseMatrix<Scalar,Options>& sm, const DenseType& ref, const std::vector<Vector2i>& nonzeroCoords)
{
typedef SparseMatrix<Scalar,Options> SparseType;
{
sm.setZero();
SetterType w(sm);
std::vector<Vector2i> remaining = nonzeroCoords;
while(!remaining.empty())
{
int i = ei_random<int>(0,static_cast<int>(remaining.size())-1);
w(remaining[i].x(),remaining[i].y()) = ref.coeff(remaining[i].x(),remaining[i].y());
remaining[i] = remaining.back();
remaining.pop_back();
}
}
return sm.isApprox(ref);
}
template<typename SetterType,typename DenseType, typename T>
bool test_random_setter(DynamicSparseMatrix<T>& sm, const DenseType& ref, const std::vector<Vector2i>& nonzeroCoords)
{
sm.setZero();
std::vector<Vector2i> remaining = nonzeroCoords;
while(!remaining.empty())
{
int i = ei_random<int>(0,static_cast<int>(remaining.size())-1);
sm.coeffRef(remaining[i].x(),remaining[i].y()) = ref.coeff(remaining[i].x(),remaining[i].y());
remaining[i] = remaining.back();
remaining.pop_back();
}
return sm.isApprox(ref);
}
template<typename SparseMatrixType> void sparse_basic(const SparseMatrixType& ref)
{
const int rows = ref.rows();
@@ -136,47 +102,6 @@ template<typename SparseMatrixType> void sparse_basic(const SparseMatrixType& re
}
*/
// test SparseSetters
// coherent setter
// TODO extend the MatrixSetter
// {
// m.setZero();
// VERIFY_IS_NOT_APPROX(m, refMat);
// SparseSetter<SparseMatrixType, FullyCoherentAccessPattern> w(m);
// for (int i=0; i<nonzeroCoords.size(); ++i)
// {
// w->coeffRef(nonzeroCoords[i].x(),nonzeroCoords[i].y()) = refMat.coeff(nonzeroCoords[i].x(),nonzeroCoords[i].y());
// }
// }
// VERIFY_IS_APPROX(m, refMat);
// random setter
// {
// m.setZero();
// VERIFY_IS_NOT_APPROX(m, refMat);
// SparseSetter<SparseMatrixType, RandomAccessPattern> w(m);
// std::vector<Vector2i> remaining = nonzeroCoords;
// while(!remaining.empty())
// {
// int i = ei_random<int>(0,remaining.size()-1);
// w->coeffRef(remaining[i].x(),remaining[i].y()) = refMat.coeff(remaining[i].x(),remaining[i].y());
// remaining[i] = remaining.back();
// remaining.pop_back();
// }
// }
// VERIFY_IS_APPROX(m, refMat);
VERIFY(( test_random_setter<RandomSetter<SparseMatrixType, StdMapTraits> >(m,refMat,nonzeroCoords) ));
#ifdef EIGEN_UNORDERED_MAP_SUPPORT
VERIFY(( test_random_setter<RandomSetter<SparseMatrixType, StdUnorderedMapTraits> >(m,refMat,nonzeroCoords) ));
#endif
#ifdef _DENSE_HASH_MAP_H_
VERIFY(( test_random_setter<RandomSetter<SparseMatrixType, GoogleDenseHashMapTraits> >(m,refMat,nonzeroCoords) ));
#endif
#ifdef _SPARSE_HASH_MAP_H_
VERIFY(( test_random_setter<RandomSetter<SparseMatrixType, GoogleSparseHashMapTraits> >(m,refMat,nonzeroCoords) ));
#endif
// test insert (inner random)
{
DenseMatrix m1(rows,cols);
@@ -213,22 +138,6 @@ template<typename SparseMatrixType> void sparse_basic(const SparseMatrixType& re
VERIFY_IS_APPROX(m2,m1);
}
// test RandomSetter
/*{
SparseMatrixType m1(rows,cols), m2(rows,cols);
DenseMatrix refM1 = DenseMatrix::Zero(rows, rows);
initSparse<Scalar>(density, refM1, m1);
{
Eigen::RandomSetter<SparseMatrixType > setter(m2);
for (int j=0; j<m1.outerSize(); ++j)
for (typename SparseMatrixType::InnerIterator i(m1,j); i; ++i)
setter(i.index(), j) = i.value();
}
VERIFY_IS_APPROX(m1, m2);
}*/
// std::cerr << m.transpose() << "\n\n" << refMat.transpose() << "\n\n";
// VERIFY_IS_APPROX(m, refMat);
// test basic computations
{
DenseMatrix refM1 = DenseMatrix::Zero(rows, rows);
@@ -263,6 +172,17 @@ template<typename SparseMatrixType> void sparse_basic(const SparseMatrixType& re
// VERIFY_IS_APPROX(m3.cwise()/refM4, refM3.cwise()/refM4);
}
// test transpose
{
DenseMatrix refMat2 = DenseMatrix::Zero(rows, rows);
SparseMatrixType m2(rows, rows);
initSparse<Scalar>(density, refMat2, m2);
VERIFY_IS_APPROX(m2.transpose().eval(), refMat2.transpose().eval());
VERIFY_IS_APPROX(m2.transpose(), refMat2.transpose());
VERIFY_IS_APPROX(SparseMatrixType(m2.adjoint()), refMat2.adjoint());
}
// test innerVector()
{
DenseMatrix refMat2 = DenseMatrix::Zero(rows, rows);
@@ -292,17 +212,6 @@ template<typename SparseMatrixType> void sparse_basic(const SparseMatrixType& re
//refMat2.block(0,j0,rows,n0) = refMat2.block(0,j0,rows,n0) + refMat2.block(0,j1,rows,n0);
}
// test transpose
{
DenseMatrix refMat2 = DenseMatrix::Zero(rows, rows);
SparseMatrixType m2(rows, rows);
initSparse<Scalar>(density, refMat2, m2);
VERIFY_IS_APPROX(m2.transpose().eval(), refMat2.transpose().eval());
VERIFY_IS_APPROX(m2.transpose(), refMat2.transpose());
VERIFY_IS_APPROX(SparseMatrixType(m2.adjoint()), refMat2.adjoint());
}
// test prune
{
SparseMatrixType m2(rows, rows);

135
test/sparse_solvers.cpp
View File

@@ -1,7 +1,7 @@
// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2008 Daniel Gomez Ferro <dgomezferro@gmail.com>
// Copyright (C) 2008-2010 Gael Guennebaud <g.gael@free.fr>
//
// Eigen is free software; you can redistribute it and/or
// modify it under the terms of the GNU Lesser General Public
@@ -105,139 +105,6 @@ template<typename Scalar> void sparse_solvers(int rows, int cols)
VERIFY_IS_APPROX(refMat2.template triangularView<Lower>().solve(vec2),
m2.template triangularView<Lower>().solve(vec3));
}
// test LLT
{
// TODO fix the issue with complex (see SparseLLT::solveInPlace)
SparseMatrix<Scalar> m2(rows, cols);
DenseMatrix refMat2(rows, cols);
DenseVector b = DenseVector::Random(cols);
DenseVector refX(cols), x(cols);
initSparse<Scalar>(density, refMat2, m2, ForceNonZeroDiag|MakeLowerTriangular, 0, 0);
for(int i=0; i<rows; ++i)
m2.coeffRef(i,i) = refMat2(i,i) = ei_abs(ei_real(refMat2(i,i)));
refX = refMat2.template selfadjointView<Lower>().llt().solve(b);
if (!NumTraits<Scalar>::IsComplex)
{
x = b;
SparseLLT<SparseMatrix<Scalar> > (m2).solveInPlace(x);
VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LLT: default");
}
#ifdef EIGEN_CHOLMOD_SUPPORT
x = b;
SparseLLT<SparseMatrix<Scalar> ,Cholmod>(m2).solveInPlace(x);
VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LLT: cholmod");
#endif
#ifdef EIGEN_TAUCS_SUPPORT
// TODO fix TAUCS with complexes
if (!NumTraits<Scalar>::IsComplex)
{
x = b;
// SparseLLT<SparseMatrix<Scalar> ,Taucs>(m2,IncompleteFactorization).solveInPlace(x);
// VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LLT: taucs (IncompleteFactorization)");
x = b;
SparseLLT<SparseMatrix<Scalar> ,Taucs>(m2,SupernodalMultifrontal).solveInPlace(x);
VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LLT: taucs (SupernodalMultifrontal)");
x = b;
SparseLLT<SparseMatrix<Scalar> ,Taucs>(m2,SupernodalLeftLooking).solveInPlace(x);
VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LLT: taucs (SupernodalLeftLooking)");
}
#endif
}
// test LDLT
{
SparseMatrix<Scalar> m2(rows, cols);
DenseMatrix refMat2(rows, cols);
DenseVector b = DenseVector::Random(cols);
DenseVector refX(cols), x(cols);
initSparse<Scalar>(density, refMat2, m2, ForceNonZeroDiag|MakeUpperTriangular, 0, 0);
for(int i=0; i<rows; ++i)
m2.coeffRef(i,i) = refMat2(i,i) = ei_abs(ei_real(refMat2(i,i)));
refX = refMat2.template selfadjointView<Upper>().ldlt().solve(b);
typedef SparseMatrix<Scalar,Upper|SelfAdjoint> SparseSelfAdjointMatrix;
x = b;
SparseLDLT<SparseSelfAdjointMatrix> ldlt(m2);
if (ldlt.succeeded())
ldlt.solveInPlace(x);
else
std::cerr << "warning LDLT failed\n";
VERIFY_IS_APPROX(refMat2.template selfadjointView<Upper>() * x, b);
VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LDLT: default");
}
// test LU
{
static int count = 0;
SparseMatrix<Scalar> m2(rows, cols);
DenseMatrix refMat2(rows, cols);
DenseVector b = DenseVector::Random(cols);
DenseVector refX(cols), x(cols);
initSparse<Scalar>(density, refMat2, m2, ForceNonZeroDiag, &zeroCoords, &nonzeroCoords);
FullPivLU<DenseMatrix> refLu(refMat2);
refX = refLu.solve(b);
#if defined(EIGEN_SUPERLU_SUPPORT) || defined(EIGEN_UMFPACK_SUPPORT)
Scalar refDet = refLu.determinant();
#endif
x.setZero();
// // SparseLU<SparseMatrix<Scalar> > (m2).solve(b,&x);
// // VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LU: default");
#ifdef EIGEN_SUPERLU_SUPPORT
{
x.setZero();
SparseLU<SparseMatrix<Scalar>,SuperLU> slu(m2);
if (slu.succeeded())
{
if (slu.solve(b,&x)) {
VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LU: SuperLU");
}
// std::cerr << refDet << " == " << slu.determinant() << "\n";
if (slu.solve(b, &x, SvTranspose)) {
VERIFY(b.isApprox(m2.transpose() * x, test_precision<Scalar>()));
}
if (slu.solve(b, &x, SvAdjoint)) {
VERIFY(b.isApprox(m2.adjoint() * x, test_precision<Scalar>()));
}
if (count==0) {
VERIFY_IS_APPROX(refDet,slu.determinant()); // FIXME det is not very stable for complex
}
}
}
#endif
#ifdef EIGEN_UMFPACK_SUPPORT
{
// check solve
x.setZero();
SparseLU<SparseMatrix<Scalar>,UmfPack> slu(m2);
if (slu.succeeded()) {
if (slu.solve(b,&x)) {
if (count==0) {
VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LU: umfpack"); // FIXME solve is not very stable for complex
}
}
VERIFY_IS_APPROX(refDet,slu.determinant());
// TODO check the extracted data
//std::cerr << slu.matrixL() << "\n";
}
}
#endif
count++;
}
}
void test_sparse_solvers()