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Sparse module:

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* extend unit tests
* add support for generic sum reduction and dot product
* optimize the cwise()* : this is a special case of CwiseBinaryOp where
  we only have to process the coeffs which are not null for *both* matrices.
  Perhaps there exist some other binary operations like that ?
This commit is contained in:
Gael Guennebaud 2009-01-07 17:01:57 +00:00
parent 7078cfaeaa
commit 709e903335
9 changed files with 382 additions and 39 deletions
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1
Eigen/Sparse
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@ -79,6 +79,7 @@ namespace Eigen {
#include "src/Sparse/SparseMatrix.h"
#include "src/Sparse/SparseVector.h"
#include "src/Sparse/CoreIterators.h"
#include "src/Sparse/SparseRedux.h"
#include "src/Sparse/SparseProduct.h"
#include "src/Sparse/TriangularSolver.h"
#include "src/Sparse/SparseLLT.h"

149
Eigen/src/Sparse/CoreIterators.h
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@ -33,21 +33,21 @@ class MatrixBase<Derived>::InnerIterator
{
typedef typename Derived::Scalar Scalar;
public:
InnerIterator(const Derived& mat, int outer)
EIGEN_STRONG_INLINE InnerIterator(const Derived& mat, int outer)
: m_matrix(mat), m_inner(0), m_outer(outer), m_end(mat.rows())
{}
Scalar value() const
EIGEN_STRONG_INLINE Scalar value() const
{
return (Derived::Flags&RowMajorBit) ? m_matrix.coeff(m_outer, m_inner)
: m_matrix.coeff(m_inner, m_outer);
}
InnerIterator& operator++() { m_inner++; return *this; }
EIGEN_STRONG_INLINE InnerIterator& operator++() { m_inner++; return *this; }
int index() const { return m_inner; }
EIGEN_STRONG_INLINE int index() const { return m_inner; }
operator bool() const { return m_inner < m_end && m_inner>=0; }
EIGEN_STRONG_INLINE operator bool() const { return m_inner < m_end && m_inner>=0; }
protected:
const Derived& m_matrix;
@ -61,7 +61,7 @@ class Transpose<MatrixType>::InnerIterator : public MatrixType::InnerIterator
{
public:
InnerIterator(const Transpose& trans, int outer)
EIGEN_STRONG_INLINE InnerIterator(const Transpose& trans, int outer)
: MatrixType::InnerIterator(trans.m_matrix, outer)
{}
};
@ -74,7 +74,7 @@ class Block<MatrixType, BlockRows, BlockCols, PacketAccess, _DirectAccessStatus>
typedef typename _MatrixTypeNested::InnerIterator MatrixTypeIterator;
public:
InnerIterator(const Block& block, int outer)
EIGEN_STRONG_INLINE InnerIterator(const Block& block, int outer)
: m_iter(block.m_matrix,(Block::Flags&RowMajor) ? block.m_startRow.value() + outer : block.m_startCol.value() + outer),
m_start( (Block::Flags&RowMajor) ? block.m_startCol.value() : block.m_startRow.value()),
m_end(m_start + ((Block::Flags&RowMajor) ? block.m_blockCols.value() : block.m_blockRows.value())),
@ -84,24 +84,24 @@ class Block<MatrixType, BlockRows, BlockCols, PacketAccess, _DirectAccessStatus>
++m_iter;
}
InnerIterator& operator++()
EIGEN_STRONG_INLINE InnerIterator& operator++()
{
++m_iter;
return *this;
}
Scalar value() const { return m_iter.value(); }
EIGEN_STRONG_INLINE Scalar value() const { return m_iter.value(); }
int index() const { return m_iter.index() - m_offset; }
EIGEN_STRONG_INLINE int index() const { return m_iter.index() - m_offset; }
operator bool() const { return m_iter && m_iter.index()<m_end; }
EIGEN_STRONG_INLINE operator bool() const { return m_iter && m_iter.index()<m_end; }
protected:
MatrixTypeIterator m_iter;
int m_start;
int m_end;
int m_offset;
};
};
template<typename MatrixType, int BlockRows, int BlockCols, int PacketAccess>
class Block<MatrixType, BlockRows, BlockCols, PacketAccess, IsSparse>::InnerIterator
@ -111,7 +111,7 @@ class Block<MatrixType, BlockRows, BlockCols, PacketAccess, IsSparse>::InnerIter
typedef typename _MatrixTypeNested::InnerIterator MatrixTypeIterator;
public:
InnerIterator(const Block& block, int outer)
EIGEN_STRONG_INLINE InnerIterator(const Block& block, int outer)
: m_iter(block.m_matrix,(Block::Flags&RowMajor) ? block.m_startRow.value() + outer : block.m_startCol.value() + outer),
m_start( (Block::Flags&RowMajor) ? block.m_startCol.value() : block.m_startRow.value()),
m_end(m_start + ((Block::Flags&RowMajor) ? block.m_blockCols.value() : block.m_blockRows.value())),
@ -121,17 +121,17 @@ class Block<MatrixType, BlockRows, BlockCols, PacketAccess, IsSparse>::InnerIter
++m_iter;
}
InnerIterator& operator++()
EIGEN_STRONG_INLINE InnerIterator& operator++()
{
++m_iter;
return *this;
}
Scalar value() const { return m_iter.value(); }
EIGEN_STRONG_INLINE Scalar value() const { return m_iter.value(); }
int index() const { return m_iter.index() - m_offset; }
EIGEN_STRONG_INLINE int index() const { return m_iter.index() - m_offset; }
operator bool() const { return m_iter && m_iter.index()<m_end; }
EIGEN_STRONG_INLINE operator bool() const { return m_iter && m_iter.index()<m_end; }
protected:
MatrixTypeIterator m_iter;
@ -148,13 +148,13 @@ class CwiseUnaryOp<UnaryOp,MatrixType>::InnerIterator
typedef typename _MatrixTypeNested::InnerIterator MatrixTypeIterator;
public:
InnerIterator(const CwiseUnaryOp& unaryOp, int outer)
EIGEN_STRONG_INLINE InnerIterator(const CwiseUnaryOp& unaryOp, int outer)
: m_iter(unaryOp.m_matrix,outer), m_functor(unaryOp.m_functor), m_id(-1)
{
this->operator++();
}
InnerIterator& operator++()
EIGEN_STRONG_INLINE InnerIterator& operator++()
{
if (m_iter)
{
@ -169,11 +169,11 @@ class CwiseUnaryOp<UnaryOp,MatrixType>::InnerIterator
return *this;
}
Scalar value() const { return m_value; }
EIGEN_STRONG_INLINE Scalar value() const { return m_value; }
int index() const { return m_id; }
EIGEN_STRONG_INLINE int index() const { return m_id; }
operator bool() const { return m_id>=0; }
EIGEN_STRONG_INLINE operator bool() const { return m_id>=0; }
protected:
MatrixTypeIterator m_iter;
@ -182,23 +182,54 @@ class CwiseUnaryOp<UnaryOp,MatrixType>::InnerIterator
int m_id;
};
template<typename T> struct ei_is_scalar_product { enum { ret = false }; };
template<typename T> struct ei_is_scalar_product<ei_scalar_product_op<T> > { enum { ret = true }; };
template<typename BinaryOp, typename Lhs, typename Rhs, typename Derived>
class CwiseBinaryOpInnerIterator;
template<typename BinaryOp, typename Lhs, typename Rhs>
class CwiseBinaryOp<BinaryOp,Lhs,Rhs>::InnerIterator
: public CwiseBinaryOpInnerIterator<BinaryOp,Lhs,Rhs, typename CwiseBinaryOp<BinaryOp,Lhs,Rhs>::InnerIterator>
{
typedef CwiseBinaryOpInnerIterator<
BinaryOp,Lhs,Rhs, typename CwiseBinaryOp<BinaryOp,Lhs,Rhs>::InnerIterator> Base;
public:
typedef typename CwiseBinaryOp::Scalar Scalar;
typedef typename ei_traits<CwiseBinaryOp>::_LhsNested _LhsNested;
typedef typename _LhsNested::InnerIterator LhsIterator;
typedef typename ei_traits<CwiseBinaryOp>::_RhsNested _RhsNested;
typedef typename _RhsNested::InnerIterator RhsIterator;
// public:
EIGEN_STRONG_INLINE InnerIterator(const CwiseBinaryOp& binOp, int outer)
: Base(binOp.m_lhs,binOp.m_rhs,binOp.m_functor,outer)
{}
};
template<typename BinaryOp, typename Lhs, typename Rhs, typename Derived>
class CwiseBinaryOpInnerIterator
{
typedef CwiseBinaryOp<BinaryOp,Lhs,Rhs> ExpressionType;
typedef typename ExpressionType::Scalar Scalar;
typedef typename ei_traits<ExpressionType>::_LhsNested _LhsNested;
// typedef typename ei_traits<ExpressionType>::LhsIterator LhsIterator;
typedef typename ei_traits<ExpressionType>::_RhsNested _RhsNested;
// typedef typename ei_traits<ExpressionType>::RhsIterator RhsIterator;
// typedef typename ei_traits<CwiseBinaryOp>::_LhsNested _LhsNested;
typedef typename _LhsNested::InnerIterator LhsIterator;
// typedef typename ei_traits<CwiseBinaryOp>::_RhsNested _RhsNested;
typedef typename _RhsNested::InnerIterator RhsIterator;
// enum { IsProduct = ei_is_scalar_product<BinaryOp>::ret };
public:
InnerIterator(const CwiseBinaryOp& binOp, int outer)
: m_lhsIter(binOp.m_lhs,outer), m_rhsIter(binOp.m_rhs,outer), m_functor(binOp.m_functor), m_id(-1)
EIGEN_STRONG_INLINE CwiseBinaryOpInnerIterator(const _LhsNested& lhs, const _RhsNested& rhs,
const BinaryOp& functor, int outer)
: m_lhsIter(lhs,outer), m_rhsIter(rhs,outer), m_functor(functor), m_id(-1)
{
this->operator++();
}
InnerIterator& operator++()
EIGEN_STRONG_INLINE Derived& operator++()
{
if (m_lhsIter && m_rhsIter && (m_lhsIter.index() == m_rhsIter.index()))
{
@ -223,14 +254,14 @@ class CwiseBinaryOp<BinaryOp,Lhs,Rhs>::InnerIterator
{
m_id = -1;
}
return *this;
return *static_cast<Derived*>(this);
}
Scalar value() const { return m_value; }
EIGEN_STRONG_INLINE Scalar value() const { return m_value; }
int index() const { return m_id; }
EIGEN_STRONG_INLINE int index() const { return m_id; }
operator bool() const { return m_id>=0; }
EIGEN_STRONG_INLINE operator bool() const { return m_id>=0; }
protected:
LhsIterator m_lhsIter;
@ -239,5 +270,65 @@ class CwiseBinaryOp<BinaryOp,Lhs,Rhs>::InnerIterator
Scalar m_value;
int m_id;
};
/*
template<typename T, typename Lhs, typename Rhs, typename Derived>
class CwiseBinaryOpInnerIterator<ei_scalar_product_op<T>,Lhs,Rhs,Derived>
{
typedef typename CwiseBinaryOp::Scalar Scalar;
typedef typename ei_traits<CwiseBinaryOp>::_LhsNested _LhsNested;
typedef typename _LhsNested::InnerIterator LhsIterator;
typedef typename ei_traits<CwiseBinaryOp>::_RhsNested _RhsNested;
typedef typename _RhsNested::InnerIterator RhsIterator;
public:
EIGEN_STRONG_INLINE CwiseBinaryOpInnerIterator(const CwiseBinaryOp& binOp, int outer)
: m_lhsIter(binOp.m_lhs,outer), m_rhsIter(binOp.m_rhs,outer), m_functor(binOp.m_functor)//, m_id(-1)
{
//this->operator++();
while (m_lhsIter && m_rhsIter && m_lhsIter.index() != m_rhsIter.index())
{
if (m_lhsIter.index() < m_rhsIter.index())
++m_lhsIter;
else
++m_rhsIter;
}
}
EIGEN_STRONG_INLINE Derived& operator++()
{
// m_id = -1;
asm("#beginwhile");
while (m_lhsIter && m_rhsIter)
{
if (m_lhsIter.index() == m_rhsIter.index())
{
// m_id = m_lhsIter.index();
//m_value = m_functor(m_lhsIter.value(), m_rhsIter.value());
++m_lhsIter;
++m_rhsIter;
break;
}
else if (m_lhsIter.index() < m_rhsIter.index())
++m_lhsIter;
else
++m_rhsIter;
}
asm("#endwhile");
return *static_cast<Derived*>(this);
}
EIGEN_STRONG_INLINE Scalar value() const { return m_functor(m_lhsIter.value(), m_rhsIter.value()); }
EIGEN_STRONG_INLINE int index() const { return m_lhsIter.index(); }
EIGEN_STRONG_INLINE operator bool() const { return m_lhsIter && m_rhsIter; }
protected:
LhsIterator m_lhsIter;
RhsIterator m_rhsIter;
const BinaryOp& m_functor;
// Scalar m_value;
// int m_id;
};*/
#endif // EIGEN_COREITERATORS_H

43
Eigen/src/Sparse/SparseMatrixBase.h
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@ -167,6 +167,49 @@ class SparseMatrixBase : public MatrixBase<Derived>
return s;
}
// template<typename OtherDerived>
// Scalar dot(const MatrixBase<OtherDerived>& other) const
// {
// EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
// EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived)
// EIGEN_STATIC_ASSERT((ei_is_same_type<Scalar, typename OtherDerived::Scalar>::ret),
// YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
//
// ei_assert(derived().size() == other.size());
// // short version, but the assembly looks more complicated because
// // of the CwiseBinaryOp iterator complexity
// // return res = (derived().cwise() * other.derived().conjugate()).sum();
//
// // optimized, generic version
// typename Derived::InnerIterator i(derived(),0);
// typename OtherDerived::InnerIterator j(other.derived(),0);
// Scalar res = 0;
// while (i && j)
// {
// if (i.index()==j.index())
// {
// // std::cerr << i.value() << " * " << j.value() << "\n";
// res += i.value() * ei_conj(j.value());
// ++i; ++j;
// }
// else if (i.index()<j.index())
// ++i;
// else
// ++j;
// }
// return res;
// }
//
// Scalar sum() const
// {
// Scalar res = 0;
// for (typename Derived::InnerIterator iter(*this,0); iter; ++iter)
// {
// res += iter.value();
// }
// return res;
// }
protected:
bool m_isRValue;

70
Eigen/src/Sparse/SparseRedux.h Normal file
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@ -0,0 +1,70 @@
// This file is part of Eigen, a lightweight C++ template library
// for linear algebra. Eigen itself is part of the KDE project.
//
// Copyright (C) 2008 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
// License as published by the Free Software Foundation; either
// version 3 of the License, or (at your option) any later version.
//
// Alternatively, you can redistribute it and/or
// modify it under the terms of the GNU General Public License as
// published by the Free Software Foundation; either version 2 of
// the License, or (at your option) any later version.
//
// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License and a copy of the GNU General Public License along with
// Eigen. If not, see <http://www.gnu.org/licenses/>.
#ifndef EIGEN_SPARSEREDUX_H
#define EIGEN_SPARSEREDUX_H
template<typename Derived, int Vectorization, int Unrolling>
struct ei_sum_impl<Derived, Vectorization, Unrolling, IsSparse>
{
typedef typename Derived::Scalar Scalar;
static Scalar run(const Derived& mat)
{
ei_assert(mat.rows()>0 && mat.cols()>0 && "you are using a non initialized matrix");
Scalar res = 0;
for (int j=0; j<mat.outerSize(); ++j)
for (typename Derived::InnerIterator iter(mat,j); iter; ++iter)
res += iter.value();
return res;
}
};
template<typename Derived1, typename Derived2, int Vectorization, int Unrolling>
struct ei_dot_impl<Derived1, Derived2, Vectorization, Unrolling, IsSparse>
{
typedef typename Derived1::Scalar Scalar;
static Scalar run(const Derived1& v1, const Derived2& v2)
{
ei_assert(v1.size()>0 && "you are using a non initialized vector");
typename Derived1::InnerIterator i(v1,0);
typename Derived2::InnerIterator j(v2,0);
Scalar res = 0;
while (i && j)
{
if (i.index()==j.index())
{
res += i.value() * ei_conj(j.value());
++i; ++j;
}
else if (i.index()<j.index())
++i;
else
++j;
}
return res;
}
};
#endif // EIGEN_SPARSEREDUX_H

22
Eigen/src/Sparse/SparseVector.h
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@ -272,6 +272,28 @@ class SparseVector
return s;
}
// this specialized version does not seems to be faster
// Scalar dot(const SparseVector& other) const
// {
// int i=0, j=0;
// Scalar res = 0;
// asm("#begindot");
// while (i<nonZeros() && j<other.nonZeros())
// {
// if (m_data.index(i)==other.m_data.index(j))
// {
// res += m_data.value(i) * ei_conj(other.m_data.value(j));
// ++i; ++j;
// }
// else if (m_data.index(i)<other.m_data.index(j))
// ++i;
// else
// ++j;
// }
// asm("#enddot");
// return res;
// }
/** Destructor */
inline ~SparseVector() {}
};

18
Eigen/src/Sparse/SuperLUSupport.h
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@ -114,13 +114,13 @@ struct SluMatrix : SuperMatrix
}
};
template<typename Scalar, int Rows, int Cols, int StorageOrder, int MRows, int MCols>
struct SluMatrixMapHelper<Matrix<Scalar,Rows,Cols,StorageOrder,MRows,MCols> >
template<typename Scalar, int Rows, int Cols, int Options, int MRows, int MCols>
struct SluMatrixMapHelper<Matrix<Scalar,Rows,Cols,Options,MRows,MCols> >
{
typedef Matrix<Scalar,Rows,Cols,StorageOrder,MRows,MCols> MatrixType;
typedef Matrix<Scalar,Rows,Cols,Options,MRows,MCols> MatrixType;
static void run(MatrixType& mat, SluMatrix& res)
{
assert(StorageOrder==0 && "row-major dense matrices is not supported by SuperLU");
ei_assert( ((Options&RowMajor)!=RowMajor) && "row-major dense matrices is not supported by SuperLU");
res.setStorageType(SLU_DN);
res.setScalarType<Scalar>();
res.Mtype = SLU_GE;
@ -139,7 +139,7 @@ struct SluMatrixMapHelper<SparseMatrix<Scalar,Flags> >
typedef SparseMatrix<Scalar,Flags> MatrixType;
static void run(MatrixType& mat, SluMatrix& res)
{
if (Flags&RowMajorBit)
if ((Flags&RowMajorBit)==RowMajorBit)
{
res.setStorageType(SLU_NR);
res.nrow = mat.cols();
@ -181,7 +181,7 @@ template<typename Scalar, int Flags>
SparseMatrix<Scalar,Flags> SparseMatrix<Scalar,Flags>::Map(SluMatrix& sluMat)
{
SparseMatrix res;
if (Flags&RowMajorBit)
if ((Flags&RowMajorBit)==RowMajorBit)
{
assert(sluMat.Stype == SLU_NR);
res.m_innerSize = sluMat.ncol;
@ -276,7 +276,7 @@ class SparseLU<MatrixType,SuperLU> : public SparseLU<MatrixType>
mutable UMatrixType m_u;
mutable IntColVectorType m_p;
mutable IntRowVectorType m_q;
mutable SparseMatrix<Scalar> m_matrix;
mutable SluMatrix m_sluA;
mutable SuperMatrix m_sluL, m_sluU;
@ -423,7 +423,7 @@ void SparseLU<MatrixType,SuperLU>::extractData() const
int* Ucol = m_u._outerIndexPtr();
int* Urow = m_u._innerIndexPtr();
Scalar* Uval = m_u._valuePtr();
Ucol[0] = 0;
Ucol[0] = 0;
@ -434,7 +434,7 @@ void SparseLU<MatrixType,SuperLU>::extractData() const
istart = L_SUB_START(fsupc);
nsupr = L_SUB_START(fsupc+1) - istart;
upper = 1;
/* for each column in the supernode */
for (int j = fsupc; j < L_FST_SUPC(k+1); ++j)
{

2
test/CMakeLists.txt
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@ -187,5 +187,5 @@ ei_add_test(parametrizedline)
ei_add_test(alignedbox)
ei_add_test(regression)
ei_add_test(sparse_basic " " "${SPARSE_LIBS}")
ei_add_test(sparse_vector " " "${SPARSE_LIBS}")
ei_add_test(sparse_solvers " " "${SPARSE_LIBS}")

24
test/sparse.h
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@ -89,4 +89,28 @@ initSparse(double density,
sparseMat.endFill();
}
template<typename Scalar> void
initSparse(double density,
Matrix<Scalar,Dynamic,1>& refVec,
SparseVector<Scalar>& sparseVec,
std::vector<int>* zeroCoords = 0,
std::vector<int>* nonzeroCoords = 0)
{
sparseVec.reserve(refVec.size()*density);
sparseVec.setZero();
for(int i=0; i<refVec.size(); i++)
{
Scalar v = (ei_random<double>(0,1) < density) ? ei_random<Scalar>() : Scalar(0);
if (v!=Scalar(0))
{
sparseVec.fill(i) = v;
if (nonzeroCoords)
nonzeroCoords->push_back(i);
}
else if (zeroCoords)
zeroCoords->push_back(i);
refVec[i] = v;
}
}
#endif // EIGEN_TESTSPARSE_H

92
test/sparse_vector.cpp Normal file
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@ -0,0 +1,92 @@
// This file is part of Eigen, a lightweight C++ template library
// for linear algebra. Eigen itself is part of the KDE project.
//
// Copyright (C) 2008 Daniel Gomez Ferro <dgomezferro@gmail.com>
//
// Eigen is free software; you can redistribute it and/or
// modify it under the terms of the GNU Lesser General Public
// License as published by the Free Software Foundation; either
// version 3 of the License, or (at your option) any later version.
//
// Alternatively, you can redistribute it and/or
// modify it under the terms of the GNU General Public License as
// published by the Free Software Foundation; either version 2 of
// the License, or (at your option) any later version.
//
// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License and a copy of the GNU General Public License along with
// Eigen. If not, see <http://www.gnu.org/licenses/>.
#include "sparse.h"
template<typename Scalar> void sparse_vector(int rows, int cols)
{
double densityMat = std::max(8./(rows*cols), 0.01);
double densityVec = std::max(8./float(rows), 0.1);
typedef Matrix<Scalar,Dynamic,Dynamic> DenseMatrix;
typedef Matrix<Scalar,Dynamic,1> DenseVector;
typedef SparseVector<Scalar> SparseVectorType;
typedef SparseMatrix<Scalar> SparseMatrixType;
Scalar eps = 1e-6;
SparseMatrixType m1(rows,cols);
SparseVectorType v1(rows), v2(rows), v3(rows);
DenseMatrix refM1 = DenseMatrix::Zero(rows, cols);
DenseVector refV1 = DenseVector::Random(rows),
refV2 = DenseVector::Random(rows),
refV3 = DenseVector::Random(rows);
std::vector<int> zerocoords, nonzerocoords;
initSparse<Scalar>(densityVec, refV1, v1, &zerocoords, &nonzerocoords);
initSparse<Scalar>(densityMat, refM1, m1);
initSparse<Scalar>(densityVec, refV2, v2);
initSparse<Scalar>(densityVec, refV3, v3);
Scalar s1 = ei_random<Scalar>();
// test coeff and coeffRef
for (unsigned int i=0; i<zerocoords.size(); ++i)
{
VERIFY_IS_MUCH_SMALLER_THAN( v1.coeff(zerocoords[i]), eps );
VERIFY_RAISES_ASSERT( v1.coeffRef(zerocoords[i]) = 5 );
}
{
VERIFY(int(nonzerocoords.size()) == v1.nonZeros());
int j=0;
for (typename SparseVectorType::InnerIterator it(v1); it; ++it,++j)
{
VERIFY(nonzerocoords[j]==it.index());
VERIFY(it.value()==v1[it.index()]);
}
}
VERIFY_IS_APPROX(v1, refV1);
v1.coeffRef(nonzerocoords[0]) = Scalar(5);
refV1.coeffRef(nonzerocoords[0]) = Scalar(5);
VERIFY_IS_APPROX(v1, refV1);
VERIFY_IS_APPROX(v1+v2, refV1+refV2);
VERIFY_IS_APPROX(v1+v2+v3, refV1+refV2+refV3);
VERIFY_IS_APPROX(v1*s1-v2, refV1*s1-refV2);
std::cerr << v1.dot(v2) << " == " << refV1.dot(refV2) << "\n";
VERIFY_IS_APPROX(v1.dot(v2), refV1.dot(refV2));
}
void test_sparse_vector()
{
for(int i = 0; i < g_repeat; i++) {
CALL_SUBTEST( sparse_vector<double>(8, 8) );
// CALL_SUBTEST( sparse_vector<std::complex<double> >(16, 16) );
CALL_SUBTEST( sparse_vector<double>(299, 535) );
}
}