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merge with default branch

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This commit is contained in:
Gael Guennebaud
2014-07-10 22:04:45 +02:00
parent 61b88d2feb d1460d9278
commit 296cb40161
49 changed files with 263 additions and 167 deletions
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4
Eigen/src/SparseCore/CompressedStorage.h
View File

@@ -83,10 +83,10 @@ class CompressedStorage
reallocate(m_size);
}
void resize(size_t size, float reserveSizeFactor = 0)
void resize(size_t size, double reserveSizeFactor = 0)
{
if (m_allocatedSize<size)
reallocate(size + size_t(reserveSizeFactor*size));
reallocate(size + size_t(reserveSizeFactor*double(size)));
m_size = size;
}

40
Eigen/src/SparseCore/SparseBlock.h
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@@ -53,11 +53,11 @@ public:
};
#endif // EIGEN_TEST_EVALUATORS
inline BlockImpl(const XprType& xpr, int i)
inline BlockImpl(const XprType& xpr, Index i)
: m_matrix(xpr), m_outerStart(i), m_outerSize(OuterSize)
{}
inline BlockImpl(const XprType& xpr, int startRow, int startCol, int blockRows, int blockCols)
inline BlockImpl(const XprType& xpr, Index startRow, Index startCol, Index blockRows, Index blockCols)
: m_matrix(xpr), m_outerStart(IsRowMajor ? startRow : startCol), m_outerSize(IsRowMajor ? blockRows : blockCols)
{}
@@ -69,7 +69,7 @@ public:
#ifndef EIGEN_TEST_EVALUATORS
Index nnz = 0;
Index end = m_outerStart + m_outerSize.value();
for(int j=m_outerStart; j<end; ++j)
for(Index j=m_outerStart; j<end; ++j)
for(typename XprType::InnerIterator it(m_matrix, j); it; ++it)
++nnz;
return nnz;
@@ -146,11 +146,11 @@ public:
};
#endif // EIGEN_TEST_EVALUATORS
inline sparse_matrix_block_impl(const SparseMatrixType& xpr, int i)
inline sparse_matrix_block_impl(const SparseMatrixType& xpr, Index i)
: m_matrix(xpr), m_outerStart(i), m_outerSize(OuterSize)
{}
inline sparse_matrix_block_impl(const SparseMatrixType& xpr, int startRow, int startCol, int blockRows, int blockCols)
inline sparse_matrix_block_impl(const SparseMatrixType& xpr, Index startRow, Index startCol, Index blockRows, Index blockCols)
: m_matrix(xpr), m_outerStart(IsRowMajor ? startRow : startCol), m_outerSize(IsRowMajor ? blockRows : blockCols)
{}
@@ -250,8 +250,8 @@ public:
Index nonZeros() const
{
if(m_matrix.isCompressed())
return std::size_t(m_matrix.outerIndexPtr()[m_outerStart+m_outerSize.value()])
- std::size_t(m_matrix.outerIndexPtr()[m_outerStart]);
return Index( std::size_t(m_matrix.outerIndexPtr()[m_outerStart+m_outerSize.value()])
- std::size_t(m_matrix.outerIndexPtr()[m_outerStart]));
else if(m_outerSize.value()==0)
return 0;
else
@@ -292,13 +292,14 @@ class BlockImpl<SparseMatrix<_Scalar, _Options, _Index>,BlockRows,BlockCols,true
: public internal::sparse_matrix_block_impl<SparseMatrix<_Scalar, _Options, _Index>,BlockRows,BlockCols>
{
public:
typedef _Index Index;
typedef SparseMatrix<_Scalar, _Options, _Index> SparseMatrixType;
typedef internal::sparse_matrix_block_impl<SparseMatrixType,BlockRows,BlockCols> Base;
inline BlockImpl(SparseMatrixType& xpr, int i)
inline BlockImpl(SparseMatrixType& xpr, Index i)
: Base(xpr, i)
{}
inline BlockImpl(SparseMatrixType& xpr, int startRow, int startCol, int blockRows, int blockCols)
inline BlockImpl(SparseMatrixType& xpr, Index startRow, Index startCol, Index blockRows, Index blockCols)
: Base(xpr, startRow, startCol, blockRows, blockCols)
{}
@@ -310,13 +311,14 @@ class BlockImpl<const SparseMatrix<_Scalar, _Options, _Index>,BlockRows,BlockCol
: public internal::sparse_matrix_block_impl<const SparseMatrix<_Scalar, _Options, _Index>,BlockRows,BlockCols>
{
public:
typedef _Index Index;
typedef const SparseMatrix<_Scalar, _Options, _Index> SparseMatrixType;
typedef internal::sparse_matrix_block_impl<SparseMatrixType,BlockRows,BlockCols> Base;
inline BlockImpl(SparseMatrixType& xpr, int i)
inline BlockImpl(SparseMatrixType& xpr, Index i)
: Base(xpr, i)
{}
inline BlockImpl(SparseMatrixType& xpr, int startRow, int startCol, int blockRows, int blockCols)
inline BlockImpl(SparseMatrixType& xpr, Index startRow, Index startCol, Index blockRows, Index blockCols)
: Base(xpr, startRow, startCol, blockRows, blockCols)
{}
@@ -390,7 +392,7 @@ public:
/** Column or Row constructor
*/
inline BlockImpl(const XprType& xpr, int i)
inline BlockImpl(const XprType& xpr, Index i)
: m_matrix(xpr),
m_startRow( (BlockRows==1) && (BlockCols==XprType::ColsAtCompileTime) ? i : 0),
m_startCol( (BlockRows==XprType::RowsAtCompileTime) && (BlockCols==1) ? i : 0),
@@ -400,32 +402,32 @@ public:
/** Dynamic-size constructor
*/
inline BlockImpl(const XprType& xpr, int startRow, int startCol, int blockRows, int blockCols)
inline BlockImpl(const XprType& xpr, Index startRow, Index startCol, Index blockRows, Index blockCols)
: m_matrix(xpr), m_startRow(startRow), m_startCol(startCol), m_blockRows(blockRows), m_blockCols(blockCols)
{}
inline int rows() const { return m_blockRows.value(); }
inline int cols() const { return m_blockCols.value(); }
inline Index rows() const { return m_blockRows.value(); }
inline Index cols() const { return m_blockCols.value(); }
inline Scalar& coeffRef(int row, int col)
inline Scalar& coeffRef(Index row, Index col)
{
return m_matrix.const_cast_derived()
.coeffRef(row + m_startRow.value(), col + m_startCol.value());
}
inline const Scalar coeff(int row, int col) const
inline const Scalar coeff(Index row, Index col) const
{
return m_matrix.coeff(row + m_startRow.value(), col + m_startCol.value());
}
inline Scalar& coeffRef(int index)
inline Scalar& coeffRef(Index index)
{
return m_matrix.const_cast_derived()
.coeffRef(m_startRow.value() + (RowsAtCompileTime == 1 ? 0 : index),
m_startCol.value() + (RowsAtCompileTime == 1 ? index : 0));
}
inline const Scalar coeff(int index) const
inline const Scalar coeff(Index index) const
{
return m_matrix
.coeff(m_startRow.value() + (RowsAtCompileTime == 1 ? 0 : index),

10
Eigen/src/SparseCore/SparseMatrix.h
View File

@@ -1254,7 +1254,7 @@ EIGEN_DONT_INLINE typename SparseMatrix<_Scalar,_Options,_Index>::Scalar& Sparse
size_t p = m_outerIndex[outer+1];
++m_outerIndex[outer+1];
float reallocRatio = 1;
double reallocRatio = 1;
if (m_data.allocatedSize()<=m_data.size())
{
// if there is no preallocated memory, let's reserve a minimum of 32 elements
@@ -1266,13 +1266,13 @@ EIGEN_DONT_INLINE typename SparseMatrix<_Scalar,_Options,_Index>::Scalar& Sparse
{
// we need to reallocate the data, to reduce multiple reallocations
// we use a smart resize algorithm based on the current filling ratio
// in addition, we use float to avoid integers overflows
float nnzEstimate = float(m_outerIndex[outer])*float(m_outerSize)/float(outer+1);
reallocRatio = (nnzEstimate-float(m_data.size()))/float(m_data.size());
// in addition, we use double to avoid integers overflows
double nnzEstimate = double(m_outerIndex[outer])*double(m_outerSize)/double(outer+1);
reallocRatio = (nnzEstimate-double(m_data.size()))/double(m_data.size());
// furthermore we bound the realloc ratio to:
// 1) reduce multiple minor realloc when the matrix is almost filled
// 2) avoid to allocate too much memory when the matrix is almost empty
reallocRatio = (std::min)((std::max)(reallocRatio,1.5f),8.f);
reallocRatio = (std::min)((std::max)(reallocRatio,1.5),8.);
}
}
m_data.resize(m_data.size()+1,reallocRatio);

30
Eigen/src/SparseCore/TriangularSolver.h
View File

@@ -28,15 +28,16 @@ template<typename Lhs, typename Rhs, int Mode>
struct sparse_solve_triangular_selector<Lhs,Rhs,Mode,Lower,RowMajor>
{
typedef typename Rhs::Scalar Scalar;
typedef typename Lhs::Index Index;
static void run(const Lhs& lhs, Rhs& other)
{
for(int col=0 ; col<other.cols() ; ++col)
for(Index col=0 ; col<other.cols() ; ++col)
{
for(int i=0; i<lhs.rows(); ++i)
for(Index i=0; i<lhs.rows(); ++i)
{
Scalar tmp = other.coeff(i,col);
Scalar lastVal(0);
int lastIndex = 0;
Index lastIndex = 0;
for(typename Lhs::InnerIterator it(lhs, i); it; ++it)
{
lastVal = it.value();
@@ -62,11 +63,12 @@ template<typename Lhs, typename Rhs, int Mode>
struct sparse_solve_triangular_selector<Lhs,Rhs,Mode,Upper,RowMajor>
{
typedef typename Rhs::Scalar Scalar;
typedef typename Lhs::Index Index;
static void run(const Lhs& lhs, Rhs& other)
{
for(int col=0 ; col<other.cols() ; ++col)
for(Index col=0 ; col<other.cols() ; ++col)
{
for(int i=lhs.rows()-1 ; i>=0 ; --i)
for(Index i=lhs.rows()-1 ; i>=0 ; --i)
{
Scalar tmp = other.coeff(i,col);
Scalar l_ii = 0;
@@ -100,11 +102,12 @@ template<typename Lhs, typename Rhs, int Mode>
struct sparse_solve_triangular_selector<Lhs,Rhs,Mode,Lower,ColMajor>
{
typedef typename Rhs::Scalar Scalar;
typedef typename Lhs::Index Index;
static void run(const Lhs& lhs, Rhs& other)
{
for(int col=0 ; col<other.cols() ; ++col)
for(Index col=0 ; col<other.cols() ; ++col)
{
for(int i=0; i<lhs.cols(); ++i)
for(Index i=0; i<lhs.cols(); ++i)
{
Scalar& tmp = other.coeffRef(i,col);
if (tmp!=Scalar(0)) // optimization when other is actually sparse
@@ -132,11 +135,12 @@ template<typename Lhs, typename Rhs, int Mode>
struct sparse_solve_triangular_selector<Lhs,Rhs,Mode,Upper,ColMajor>
{
typedef typename Rhs::Scalar Scalar;
typedef typename Lhs::Index Index;
static void run(const Lhs& lhs, Rhs& other)
{
for(int col=0 ; col<other.cols() ; ++col)
for(Index col=0 ; col<other.cols() ; ++col)
{
for(int i=lhs.cols()-1; i>=0; --i)
for(Index i=lhs.cols()-1; i>=0; --i)
{
Scalar& tmp = other.coeffRef(i,col);
if (tmp!=Scalar(0)) // optimization when other is actually sparse
@@ -209,7 +213,7 @@ struct sparse_solve_triangular_sparse_selector<Lhs,Rhs,Mode,UpLo,ColMajor>
{
typedef typename Rhs::Scalar Scalar;
typedef typename promote_index_type<typename traits<Lhs>::Index,
typename traits<Rhs>::Index>::type Index;
typename traits<Rhs>::Index>::type Index;
static void run(const Lhs& lhs, Rhs& other)
{
const bool IsLower = (UpLo==Lower);
@@ -219,7 +223,7 @@ struct sparse_solve_triangular_sparse_selector<Lhs,Rhs,Mode,UpLo,ColMajor>
Rhs res(other.rows(), other.cols());
res.reserve(other.nonZeros());
for(int col=0 ; col<other.cols() ; ++col)
for(Index col=0 ; col<other.cols() ; ++col)
{
// FIXME estimate number of non zeros
tempVector.init(.99/*float(other.col(col).nonZeros())/float(other.rows())*/);
@@ -230,7 +234,7 @@ struct sparse_solve_triangular_sparse_selector<Lhs,Rhs,Mode,UpLo,ColMajor>
tempVector.coeffRef(rhsIt.index()) = rhsIt.value();
}
for(int i=IsLower?0:lhs.cols()-1;
for(Index i=IsLower?0:lhs.cols()-1;
IsLower?i<lhs.cols():i>=0;
i+=IsLower?1:-1)
{
@@ -267,7 +271,7 @@ struct sparse_solve_triangular_sparse_selector<Lhs,Rhs,Mode,UpLo,ColMajor>
}
int count = 0;
Index count = 0;
// FIXME compute a reference value to filter zeros
for (typename AmbiVector<Scalar,Index>::Iterator it(tempVector/*,1e-12*/); it; ++it)
{