github-starred/ultimatepp
2
0
Fork 0
mirror of https://github.com/ultimatepp/ultimatepp.git synced 2026-08-21 22:04:56 -06:00
Code Issues 33 Projects Packages Wiki Activity Actions

Eigen: Updated to version 3.2.7

Browse source 
git-svn-id: svn://ultimatepp.org/upp/trunk@9469 f0d560ea-af0d-0410-9eb7-867de7ffcac7
This commit is contained in:
koldo 2016-02-12 22:23:46 +00:00
parent 9be1043110
commit bb5315c1ae
63 changed files with 526 additions and 222 deletions
Download patch file Download diff file Expand all files Collapse all files

1
uppsrc/plugin/Eigen/Eigen.h
View file

@ -22,6 +22,7 @@
//#undef Success
#include "Eigen/Eigen"
#include <plugin/Eigen/unsupported/Eigen/NonLinearOptimization>
#include <plugin/Eigen/unsupported/Eigen/FFT>
NAMESPACE_UPP

2
uppsrc/plugin/Eigen/Eigen.upp
View file

@ -3,6 +3,8 @@ description "Template library for linear algebra\377";
uses
Core;
options(MSC) /bigobj;
include
../Eigen;

2
uppsrc/plugin/Eigen/Eigen/SparseCore
View file

@ -14,7 +14,7 @@
/**
* \defgroup SparseCore_Module SparseCore module
*
* This module provides a sparse matrix representation, and basic associatd matrix manipulations
* This module provides a sparse matrix representation, and basic associated matrix manipulations
* and operations.
*
* See the \ref TutorialSparse "Sparse tutorial"

2
uppsrc/plugin/Eigen/Eigen/src/Cholesky/LDLT.h
View file

@ -464,7 +464,7 @@ LDLT<MatrixType,_UpLo>& LDLT<MatrixType,_UpLo>::compute(const MatrixType& a)
*/
template<typename MatrixType, int _UpLo>
template<typename Derived>
LDLT<MatrixType,_UpLo>& LDLT<MatrixType,_UpLo>::rankUpdate(const MatrixBase<Derived>& w, const typename NumTraits<typename MatrixType::Scalar>::Real& sigma)
LDLT<MatrixType,_UpLo>& LDLT<MatrixType,_UpLo>::rankUpdate(const MatrixBase<Derived>& w, const typename LDLT<MatrixType,_UpLo>::RealScalar& sigma)
{
const Index size = w.rows();
if (m_isInitialized)

2
uppsrc/plugin/Eigen/Eigen/src/Cholesky/LLT.h
View file

@ -289,7 +289,7 @@ template<typename Scalar> struct llt_inplace<Scalar, Lower>
return k;
mat.coeffRef(k,k) = x = sqrt(x);
if (k>0 && rs>0) A21.noalias() -= A20 * A10.adjoint();
if (rs>0) A21 *= RealScalar(1)/x;
if (rs>0) A21 /= x;
}
return -1;
}

10
uppsrc/plugin/Eigen/Eigen/src/CholmodSupport/CholmodSupport.h
View file

@ -78,7 +78,7 @@ cholmod_sparse viewAsCholmod(SparseMatrix<_Scalar,_Options,_Index>& mat)
{
res.itype = CHOLMOD_INT;
}
else if (internal::is_same<_Index,UF_long>::value)
else if (internal::is_same<_Index,SuiteSparse_long>::value)
{
res.itype = CHOLMOD_LONG;
}
@ -395,7 +395,7 @@ class CholmodSimplicialLLT : public CholmodBase<_MatrixType, _UpLo, CholmodSimpl
CholmodSimplicialLLT(const MatrixType& matrix) : Base()
{
init();
compute(matrix);
Base::compute(matrix);
}
~CholmodSimplicialLLT() {}
@ -442,7 +442,7 @@ class CholmodSimplicialLDLT : public CholmodBase<_MatrixType, _UpLo, CholmodSimp
CholmodSimplicialLDLT(const MatrixType& matrix) : Base()
{
init();
compute(matrix);
Base::compute(matrix);
}
~CholmodSimplicialLDLT() {}
@ -487,7 +487,7 @@ class CholmodSupernodalLLT : public CholmodBase<_MatrixType, _UpLo, CholmodSuper
CholmodSupernodalLLT(const MatrixType& matrix) : Base()
{
init();
compute(matrix);
Base::compute(matrix);
}
~CholmodSupernodalLLT() {}
@ -534,7 +534,7 @@ class CholmodDecomposition : public CholmodBase<_MatrixType, _UpLo, CholmodDecom
CholmodDecomposition(const MatrixType& matrix) : Base()
{
init();
compute(matrix);
Base::compute(matrix);
}
~CholmodDecomposition() {}

15
uppsrc/plugin/Eigen/Eigen/src/Core/Array.h
View file

@ -124,6 +124,21 @@ class Array
}
#endif
#ifdef EIGEN_HAVE_RVALUE_REFERENCES
Array(Array&& other)
: Base(std::move(other))
{
Base::_check_template_params();
if (RowsAtCompileTime!=Dynamic && ColsAtCompileTime!=Dynamic)
Base::_set_noalias(other);
}
Array& operator=(Array&& other)
{
other.swap(*this);
return *this;
}
#endif
/** Constructs a vector or row-vector with given dimension. \only_for_vectors
*
* Note that this is only useful for dynamic-size vectors. For fixed-size vectors,

4
uppsrc/plugin/Eigen/Eigen/src/Core/ArrayBase.h
View file

@ -46,9 +46,6 @@ template<typename Derived> class ArrayBase
typedef ArrayBase Eigen_BaseClassForSpecializationOfGlobalMathFuncImpl;
using internal::special_scalar_op_base<Derived,typename internal::traits<Derived>::Scalar,
typename NumTraits<typename internal::traits<Derived>::Scalar>::Real>::operator*;
typedef typename internal::traits<Derived>::StorageKind StorageKind;
typedef typename internal::traits<Derived>::Index Index;
typedef typename internal::traits<Derived>::Scalar Scalar;
@ -56,6 +53,7 @@ template<typename Derived> class ArrayBase
typedef typename NumTraits<Scalar>::Real RealScalar;
typedef DenseBase<Derived> Base;
using Base::operator*;
using Base::RowsAtCompileTime;
using Base::ColsAtCompileTime;
using Base::SizeAtCompileTime;

2
uppsrc/plugin/Eigen/Eigen/src/Core/Assign.h
View file

@ -449,7 +449,7 @@ struct assign_impl<Derived1, Derived2, SliceVectorizedTraversal, NoUnrolling, Ve
srcAlignment = assign_traits<Derived1,Derived2>::JointAlignment
};
const Scalar *dst_ptr = &dst.coeffRef(0,0);
if((!bool(dstIsAligned)) && (Index(dst_ptr) % sizeof(Scalar))>0)
if((!bool(dstIsAligned)) && (size_t(dst_ptr) % sizeof(Scalar))>0)
{
// the pointer is not aligend-on scalar, so alignment is not possible
return assign_impl<Derived1,Derived2,DefaultTraversal,NoUnrolling>::run(dst, src);

3
uppsrc/plugin/Eigen/Eigen/src/Core/CwiseBinaryOp.h
View file

@ -81,7 +81,8 @@ struct traits<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
)
),
Flags = (Flags0 & ~RowMajorBit) | (LhsFlags & RowMajorBit),
CoeffReadCost = LhsCoeffReadCost + RhsCoeffReadCost + functor_traits<BinaryOp>::Cost
Cost0 = EIGEN_ADD_COST(LhsCoeffReadCost,RhsCoeffReadCost),
CoeffReadCost = EIGEN_ADD_COST(Cost0,functor_traits<BinaryOp>::Cost)
};
};
} // end namespace internal

2
uppsrc/plugin/Eigen/Eigen/src/Core/CwiseUnaryOp.h
View file

@ -47,7 +47,7 @@ struct traits<CwiseUnaryOp<UnaryOp, XprType> >
Flags = _XprTypeNested::Flags & (
HereditaryBits | LinearAccessBit | AlignedBit
| (functor_traits<UnaryOp>::PacketAccess ? PacketAccessBit : 0)),
CoeffReadCost = _XprTypeNested::CoeffReadCost + functor_traits<UnaryOp>::Cost
CoeffReadCost = EIGEN_ADD_COST(_XprTypeNested::CoeffReadCost, functor_traits<UnaryOp>::Cost)
};
};
}

14
uppsrc/plugin/Eigen/Eigen/src/Core/DenseBase.h
View file

@ -40,15 +40,14 @@ static inline void check_DenseIndex_is_signed() {
*/
template<typename Derived> class DenseBase
#ifndef EIGEN_PARSED_BY_DOXYGEN
: public internal::special_scalar_op_base<Derived,typename internal::traits<Derived>::Scalar,
typename NumTraits<typename internal::traits<Derived>::Scalar>::Real>
: public internal::special_scalar_op_base<Derived, typename internal::traits<Derived>::Scalar,
typename NumTraits<typename internal::traits<Derived>::Scalar>::Real,
DenseCoeffsBase<Derived> >
#else
: public DenseCoeffsBase<Derived>
#endif // not EIGEN_PARSED_BY_DOXYGEN
{
public:
using internal::special_scalar_op_base<Derived,typename internal::traits<Derived>::Scalar,
typename NumTraits<typename internal::traits<Derived>::Scalar>::Real>::operator*;
class InnerIterator;
@ -63,8 +62,9 @@ template<typename Derived> class DenseBase
typedef typename internal::traits<Derived>::Scalar Scalar;
typedef typename internal::packet_traits<Scalar>::type PacketScalar;
typedef typename NumTraits<Scalar>::Real RealScalar;
typedef internal::special_scalar_op_base<Derived,Scalar,RealScalar, DenseCoeffsBase<Derived> > Base;
typedef DenseCoeffsBase<Derived> Base;
using Base::operator*;
using Base::derived;
using Base::const_cast_derived;
using Base::rows;
@ -183,10 +183,6 @@ template<typename Derived> class DenseBase
/** \returns the number of nonzero coefficients which is in practice the number
* of stored coefficients. */
inline Index nonZeros() const { return size(); }
/** \returns true if either the number of rows or the number of columns is equal to 1.
* In other words, this function returns
* \code rows()==1 || cols()==1 \endcode
* \sa rows(), cols(), IsVectorAtCompileTime. */
/** \returns the outer size.
*

255
uppsrc/plugin/Eigen/Eigen/src/Core/DenseStorage.h
View file

@ -122,33 +122,41 @@ template<typename T, int Size, int _Rows, int _Cols, int _Options> class DenseSt
{
internal::plain_array<T,Size,_Options> m_data;
public:
inline DenseStorage() {}
inline DenseStorage(internal::constructor_without_unaligned_array_assert)
DenseStorage() {}
DenseStorage(internal::constructor_without_unaligned_array_assert)
: m_data(internal::constructor_without_unaligned_array_assert()) {}
inline DenseStorage(DenseIndex,DenseIndex,DenseIndex) {}
inline void swap(DenseStorage& other) { std::swap(m_data,other.m_data); }
static inline DenseIndex rows(void) {return _Rows;}
static inline DenseIndex cols(void) {return _Cols;}
inline void conservativeResize(DenseIndex,DenseIndex,DenseIndex) {}
inline void resize(DenseIndex,DenseIndex,DenseIndex) {}
inline const T *data() const { return m_data.array; }
inline T *data() { return m_data.array; }
DenseStorage(const DenseStorage& other) : m_data(other.m_data) {}
DenseStorage& operator=(const DenseStorage& other)
{
if (this != &other) m_data = other.m_data;
return *this;
}
DenseStorage(DenseIndex,DenseIndex,DenseIndex) {}
void swap(DenseStorage& other) { std::swap(m_data,other.m_data); }
static DenseIndex rows(void) {return _Rows;}
static DenseIndex cols(void) {return _Cols;}
void conservativeResize(DenseIndex,DenseIndex,DenseIndex) {}
void resize(DenseIndex,DenseIndex,DenseIndex) {}
const T *data() const { return m_data.array; }
T *data() { return m_data.array; }
};
// null matrix
template<typename T, int _Rows, int _Cols, int _Options> class DenseStorage<T, 0, _Rows, _Cols, _Options>
{
public:
inline DenseStorage() {}
inline DenseStorage(internal::constructor_without_unaligned_array_assert) {}
inline DenseStorage(DenseIndex,DenseIndex,DenseIndex) {}
inline void swap(DenseStorage& ) {}
static inline DenseIndex rows(void) {return _Rows;}
static inline DenseIndex cols(void) {return _Cols;}
inline void conservativeResize(DenseIndex,DenseIndex,DenseIndex) {}
inline void resize(DenseIndex,DenseIndex,DenseIndex) {}
inline const T *data() const { return 0; }
inline T *data() { return 0; }
DenseStorage() {}
DenseStorage(internal::constructor_without_unaligned_array_assert) {}
DenseStorage(const DenseStorage&) {}
DenseStorage& operator=(const DenseStorage&) { return *this; }
DenseStorage(DenseIndex,DenseIndex,DenseIndex) {}
void swap(DenseStorage& ) {}
static DenseIndex rows(void) {return _Rows;}
static DenseIndex cols(void) {return _Cols;}
void conservativeResize(DenseIndex,DenseIndex,DenseIndex) {}
void resize(DenseIndex,DenseIndex,DenseIndex) {}
const T *data() const { return 0; }
T *data() { return 0; }
};
// more specializations for null matrices; these are necessary to resolve ambiguities
@ -168,18 +176,29 @@ template<typename T, int Size, int _Options> class DenseStorage<T, Size, Dynamic
DenseIndex m_rows;
DenseIndex m_cols;
public:
inline DenseStorage() : m_rows(0), m_cols(0) {}
inline DenseStorage(internal::constructor_without_unaligned_array_assert)
DenseStorage() : m_rows(0), m_cols(0) {}
DenseStorage(internal::constructor_without_unaligned_array_assert)
: m_data(internal::constructor_without_unaligned_array_assert()), m_rows(0), m_cols(0) {}
inline DenseStorage(DenseIndex, DenseIndex nbRows, DenseIndex nbCols) : m_rows(nbRows), m_cols(nbCols) {}
inline void swap(DenseStorage& other)
DenseStorage(const DenseStorage& other) : m_data(other.m_data), m_rows(other.m_rows), m_cols(other.m_cols) {}
DenseStorage& operator=(const DenseStorage& other)
{
if (this != &other)
{
m_data = other.m_data;
m_rows = other.m_rows;
m_cols = other.m_cols;
}
return *this;
}
DenseStorage(DenseIndex, DenseIndex nbRows, DenseIndex nbCols) : m_rows(nbRows), m_cols(nbCols) {}
void swap(DenseStorage& other)
{ std::swap(m_data,other.m_data); std::swap(m_rows,other.m_rows); std::swap(m_cols,other.m_cols); }
inline DenseIndex rows() const {return m_rows;}
inline DenseIndex cols() const {return m_cols;}
inline void conservativeResize(DenseIndex, DenseIndex nbRows, DenseIndex nbCols) { m_rows = nbRows; m_cols = nbCols; }
inline void resize(DenseIndex, DenseIndex nbRows, DenseIndex nbCols) { m_rows = nbRows; m_cols = nbCols; }
inline const T *data() const { return m_data.array; }
inline T *data() { return m_data.array; }
DenseIndex rows() const {return m_rows;}
DenseIndex cols() const {return m_cols;}
void conservativeResize(DenseIndex, DenseIndex nbRows, DenseIndex nbCols) { m_rows = nbRows; m_cols = nbCols; }
void resize(DenseIndex, DenseIndex nbRows, DenseIndex nbCols) { m_rows = nbRows; m_cols = nbCols; }
const T *data() const { return m_data.array; }
T *data() { return m_data.array; }
};
// dynamic-size matrix with fixed-size storage and fixed width
@ -188,17 +207,27 @@ template<typename T, int Size, int _Cols, int _Options> class DenseStorage<T, Si
internal::plain_array<T,Size,_Options> m_data;
DenseIndex m_rows;
public:
inline DenseStorage() : m_rows(0) {}
inline DenseStorage(internal::constructor_without_unaligned_array_assert)
DenseStorage() : m_rows(0) {}
DenseStorage(internal::constructor_without_unaligned_array_assert)
: m_data(internal::constructor_without_unaligned_array_assert()), m_rows(0) {}
inline DenseStorage(DenseIndex, DenseIndex nbRows, DenseIndex) : m_rows(nbRows) {}
inline void swap(DenseStorage& other) { std::swap(m_data,other.m_data); std::swap(m_rows,other.m_rows); }
inline DenseIndex rows(void) const {return m_rows;}
inline DenseIndex cols(void) const {return _Cols;}
inline void conservativeResize(DenseIndex, DenseIndex nbRows, DenseIndex) { m_rows = nbRows; }
inline void resize(DenseIndex, DenseIndex nbRows, DenseIndex) { m_rows = nbRows; }
inline const T *data() const { return m_data.array; }
inline T *data() { return m_data.array; }
DenseStorage(const DenseStorage& other) : m_data(other.m_data), m_rows(other.m_rows) {}
DenseStorage& operator=(const DenseStorage& other)
{
if (this != &other)
{
m_data = other.m_data;
m_rows = other.m_rows;
}
return *this;
}
DenseStorage(DenseIndex, DenseIndex nbRows, DenseIndex) : m_rows(nbRows) {}
void swap(DenseStorage& other) { std::swap(m_data,other.m_data); std::swap(m_rows,other.m_rows); }
DenseIndex rows(void) const {return m_rows;}
DenseIndex cols(void) const {return _Cols;}
void conservativeResize(DenseIndex, DenseIndex nbRows, DenseIndex) { m_rows = nbRows; }
void resize(DenseIndex, DenseIndex nbRows, DenseIndex) { m_rows = nbRows; }
const T *data() const { return m_data.array; }
T *data() { return m_data.array; }
};
// dynamic-size matrix with fixed-size storage and fixed height
@ -207,17 +236,27 @@ template<typename T, int Size, int _Rows, int _Options> class DenseStorage<T, Si
internal::plain_array<T,Size,_Options> m_data;
DenseIndex m_cols;
public:
inline DenseStorage() : m_cols(0) {}
inline DenseStorage(internal::constructor_without_unaligned_array_assert)
DenseStorage() : m_cols(0) {}
DenseStorage(internal::constructor_without_unaligned_array_assert)
: m_data(internal::constructor_without_unaligned_array_assert()), m_cols(0) {}
inline DenseStorage(DenseIndex, DenseIndex, DenseIndex nbCols) : m_cols(nbCols) {}
inline void swap(DenseStorage& other) { std::swap(m_data,other.m_data); std::swap(m_cols,other.m_cols); }
inline DenseIndex rows(void) const {return _Rows;}
inline DenseIndex cols(void) const {return m_cols;}
inline void conservativeResize(DenseIndex, DenseIndex, DenseIndex nbCols) { m_cols = nbCols; }
inline void resize(DenseIndex, DenseIndex, DenseIndex nbCols) { m_cols = nbCols; }
inline const T *data() const { return m_data.array; }
inline T *data() { return m_data.array; }
DenseStorage(const DenseStorage& other) : m_data(other.m_data), m_cols(other.m_cols) {}
DenseStorage& operator=(const DenseStorage& other)
{
if (this != &other)
{
m_data = other.m_data;
m_cols = other.m_cols;
}
return *this;
}
DenseStorage(DenseIndex, DenseIndex, DenseIndex nbCols) : m_cols(nbCols) {}
void swap(DenseStorage& other) { std::swap(m_data,other.m_data); std::swap(m_cols,other.m_cols); }
DenseIndex rows(void) const {return _Rows;}
DenseIndex cols(void) const {return m_cols;}
void conservativeResize(DenseIndex, DenseIndex, DenseIndex nbCols) { m_cols = nbCols; }
void resize(DenseIndex, DenseIndex, DenseIndex nbCols) { m_cols = nbCols; }
const T *data() const { return m_data.array; }
T *data() { return m_data.array; }
};
// purely dynamic matrix.
@ -227,18 +266,35 @@ template<typename T, int _Options> class DenseStorage<T, Dynamic, Dynamic, Dynam
DenseIndex m_rows;
DenseIndex m_cols;
public:
inline DenseStorage() : m_data(0), m_rows(0), m_cols(0) {}
inline DenseStorage(internal::constructor_without_unaligned_array_assert)
DenseStorage() : m_data(0), m_rows(0), m_cols(0) {}
DenseStorage(internal::constructor_without_unaligned_array_assert)
: m_data(0), m_rows(0), m_cols(0) {}
inline DenseStorage(DenseIndex size, DenseIndex nbRows, DenseIndex nbCols)
DenseStorage(DenseIndex size, DenseIndex nbRows, DenseIndex nbCols)
: m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size)), m_rows(nbRows), m_cols(nbCols)
{ EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN }
inline ~DenseStorage() { internal::conditional_aligned_delete_auto<T,(_Options&DontAlign)==0>(m_data, m_rows*m_cols); }
inline void swap(DenseStorage& other)
#ifdef EIGEN_HAVE_RVALUE_REFERENCES
DenseStorage(DenseStorage&& other)
: m_data(std::move(other.m_data))
, m_rows(std::move(other.m_rows))
, m_cols(std::move(other.m_cols))
{
other.m_data = nullptr;
}
DenseStorage& operator=(DenseStorage&& other)
{
using std::swap;
swap(m_data, other.m_data);
swap(m_rows, other.m_rows);
swap(m_cols, other.m_cols);
return *this;
}
#endif
~DenseStorage() { internal::conditional_aligned_delete_auto<T,(_Options&DontAlign)==0>(m_data, m_rows*m_cols); }
void swap(DenseStorage& other)
{ std::swap(m_data,other.m_data); std::swap(m_rows,other.m_rows); std::swap(m_cols,other.m_cols); }
inline DenseIndex rows(void) const {return m_rows;}
inline DenseIndex cols(void) const {return m_cols;}
inline void conservativeResize(DenseIndex size, DenseIndex nbRows, DenseIndex nbCols)
DenseIndex rows(void) const {return m_rows;}
DenseIndex cols(void) const {return m_cols;}
void conservativeResize(DenseIndex size, DenseIndex nbRows, DenseIndex nbCols)
{
m_data = internal::conditional_aligned_realloc_new_auto<T,(_Options&DontAlign)==0>(m_data, size, m_rows*m_cols);
m_rows = nbRows;
@ -258,8 +314,11 @@ template<typename T, int _Options> class DenseStorage<T, Dynamic, Dynamic, Dynam
m_rows = nbRows;
m_cols = nbCols;
}
inline const T *data() const { return m_data; }
inline T *data() { return m_data; }
const T *data() const { return m_data; }
T *data() { return m_data; }
private:
DenseStorage(const DenseStorage&);
DenseStorage& operator=(const DenseStorage&);
};
// matrix with dynamic width and fixed height (so that matrix has dynamic size).
@ -268,15 +327,30 @@ template<typename T, int _Rows, int _Options> class DenseStorage<T, Dynamic, _Ro
T *m_data;
DenseIndex m_cols;
public:
inline DenseStorage() : m_data(0), m_cols(0) {}
inline DenseStorage(internal::constructor_without_unaligned_array_assert) : m_data(0), m_cols(0) {}
inline DenseStorage(DenseIndex size, DenseIndex, DenseIndex nbCols) : m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size)), m_cols(nbCols)
DenseStorage() : m_data(0), m_cols(0) {}
DenseStorage(internal::constructor_without_unaligned_array_assert) : m_data(0), m_cols(0) {}
DenseStorage(DenseIndex size, DenseIndex, DenseIndex nbCols) : m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size)), m_cols(nbCols)
{ EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN }
inline ~DenseStorage() { internal::conditional_aligned_delete_auto<T,(_Options&DontAlign)==0>(m_data, _Rows*m_cols); }
inline void swap(DenseStorage& other) { std::swap(m_data,other.m_data); std::swap(m_cols,other.m_cols); }
static inline DenseIndex rows(void) {return _Rows;}
inline DenseIndex cols(void) const {return m_cols;}
inline void conservativeResize(DenseIndex size, DenseIndex, DenseIndex nbCols)
#ifdef EIGEN_HAVE_RVALUE_REFERENCES
DenseStorage(DenseStorage&& other)
: m_data(std::move(other.m_data))
, m_cols(std::move(other.m_cols))
{
other.m_data = nullptr;
}
DenseStorage& operator=(DenseStorage&& other)
{
using std::swap;
swap(m_data, other.m_data);
swap(m_cols, other.m_cols);
return *this;
}
#endif
~DenseStorage() { internal::conditional_aligned_delete_auto<T,(_Options&DontAlign)==0>(m_data, _Rows*m_cols); }
void swap(DenseStorage& other) { std::swap(m_data,other.m_data); std::swap(m_cols,other.m_cols); }
static DenseIndex rows(void) {return _Rows;}
DenseIndex cols(void) const {return m_cols;}
void conservativeResize(DenseIndex size, DenseIndex, DenseIndex nbCols)
{
m_data = internal::conditional_aligned_realloc_new_auto<T,(_Options&DontAlign)==0>(m_data, size, _Rows*m_cols);
m_cols = nbCols;
@ -294,8 +368,11 @@ template<typename T, int _Rows, int _Options> class DenseStorage<T, Dynamic, _Ro
}
m_cols = nbCols;
}
inline const T *data() const { return m_data; }
inline T *data() { return m_data; }
const T *data() const { return m_data; }
T *data() { return m_data; }
private:
DenseStorage(const DenseStorage&);
DenseStorage& operator=(const DenseStorage&);
};
// matrix with dynamic height and fixed width (so that matrix has dynamic size).
@ -304,15 +381,30 @@ template<typename T, int _Cols, int _Options> class DenseStorage<T, Dynamic, Dyn
T *m_data;
DenseIndex m_rows;
public:
inline DenseStorage() : m_data(0), m_rows(0) {}
inline DenseStorage(internal::constructor_without_unaligned_array_assert) : m_data(0), m_rows(0) {}
inline DenseStorage(DenseIndex size, DenseIndex nbRows, DenseIndex) : m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size)), m_rows(nbRows)
DenseStorage() : m_data(0), m_rows(0) {}
DenseStorage(internal::constructor_without_unaligned_array_assert) : m_data(0), m_rows(0) {}
DenseStorage(DenseIndex size, DenseIndex nbRows, DenseIndex) : m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size)), m_rows(nbRows)
{ EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN }
inline ~DenseStorage() { internal::conditional_aligned_delete_auto<T,(_Options&DontAlign)==0>(m_data, _Cols*m_rows); }
inline void swap(DenseStorage& other) { std::swap(m_data,other.m_data); std::swap(m_rows,other.m_rows); }
inline DenseIndex rows(void) const {return m_rows;}
static inline DenseIndex cols(void) {return _Cols;}
inline void conservativeResize(DenseIndex size, DenseIndex nbRows, DenseIndex)
#ifdef EIGEN_HAVE_RVALUE_REFERENCES
DenseStorage(DenseStorage&& other)
: m_data(std::move(other.m_data))
, m_rows(std::move(other.m_rows))
{
other.m_data = nullptr;
}
DenseStorage& operator=(DenseStorage&& other)
{
using std::swap;
swap(m_data, other.m_data);
swap(m_rows, other.m_rows);
return *this;
}
#endif
~DenseStorage() { internal::conditional_aligned_delete_auto<T,(_Options&DontAlign)==0>(m_data, _Cols*m_rows); }
void swap(DenseStorage& other) { std::swap(m_data,other.m_data); std::swap(m_rows,other.m_rows); }
DenseIndex rows(void) const {return m_rows;}
static DenseIndex cols(void) {return _Cols;}
void conservativeResize(DenseIndex size, DenseIndex nbRows, DenseIndex)
{
m_data = internal::conditional_aligned_realloc_new_auto<T,(_Options&DontAlign)==0>(m_data, size, m_rows*_Cols);
m_rows = nbRows;
@ -330,8 +422,11 @@ template<typename T, int _Cols, int _Options> class DenseStorage<T, Dynamic, Dyn
}
m_rows = nbRows;
}
inline const T *data() const { return m_data; }
inline T *data() { return m_data; }
const T *data() const { return m_data; }
T *data() { return m_data; }
private:
DenseStorage(const DenseStorage&);
DenseStorage& operator=(const DenseStorage&);
};
} // end namespace Eigen

3
uppsrc/plugin/Eigen/Eigen/src/Core/DiagonalProduct.h
View file

@ -35,7 +35,8 @@ struct traits<DiagonalProduct<MatrixType, DiagonalType, ProductOrder> >
_LinearAccessMask = (RowsAtCompileTime==1 || ColsAtCompileTime==1) ? LinearAccessBit : 0,
Flags = ((HereditaryBits|_LinearAccessMask|AlignedBit) & (unsigned int)(MatrixType::Flags)) | (_Vectorizable ? PacketAccessBit : 0),//(int(MatrixType::Flags)&int(DiagonalType::DiagonalVectorType::Flags)&AlignedBit),
CoeffReadCost = NumTraits<Scalar>::MulCost + MatrixType::CoeffReadCost + DiagonalType::DiagonalVectorType::CoeffReadCost
Cost0 = EIGEN_ADD_COST(NumTraits<Scalar>::MulCost, MatrixType::CoeffReadCost),
CoeffReadCost = EIGEN_ADD_COST(Cost0,DiagonalType::DiagonalVectorType::CoeffReadCost)
};
};
}

10
uppsrc/plugin/Eigen/Eigen/src/Core/GeneralProduct.h
View file

@ -257,7 +257,7 @@ template<typename Lhs, typename Rhs>
class GeneralProduct<Lhs, Rhs, OuterProduct>
: public ProductBase<GeneralProduct<Lhs,Rhs,OuterProduct>, Lhs, Rhs>
{
template<typename T> struct IsRowMajor : internal::conditional<(int(T::Flags)&RowMajorBit), internal::true_type, internal::false_type>::type {};
template<typename T> struct is_row_major : internal::conditional<(int(T::Flags)&RowMajorBit), internal::true_type, internal::false_type>::type {};
public:
EIGEN_PRODUCT_PUBLIC_INTERFACE(GeneralProduct)
@ -281,22 +281,22 @@ class GeneralProduct<Lhs, Rhs, OuterProduct>
template<typename Dest>
inline void evalTo(Dest& dest) const {
internal::outer_product_selector_run(*this, dest, set(), IsRowMajor<Dest>());
internal::outer_product_selector_run(*this, dest, set(), is_row_major<Dest>());
}
template<typename Dest>
inline void addTo(Dest& dest) const {
internal::outer_product_selector_run(*this, dest, add(), IsRowMajor<Dest>());
internal::outer_product_selector_run(*this, dest, add(), is_row_major<Dest>());
}
template<typename Dest>
inline void subTo(Dest& dest) const {
internal::outer_product_selector_run(*this, dest, sub(), IsRowMajor<Dest>());
internal::outer_product_selector_run(*this, dest, sub(), is_row_major<Dest>());
}
template<typename Dest> void scaleAndAddTo(Dest& dest, const Scalar& alpha) const
{
internal::outer_product_selector_run(*this, dest, adds(alpha), IsRowMajor<Dest>());
internal::outer_product_selector_run(*this, dest, adds(alpha), is_row_major<Dest>());
}
};

2
uppsrc/plugin/Eigen/Eigen/src/Core/MapBase.h
View file

@ -123,7 +123,7 @@ template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
return internal::ploadt<PacketScalar, LoadMode>(m_data + index * innerStride());
}
inline MapBase(PointerType dataPtr) : m_data(dataPtr), m_rows(RowsAtCompileTime), m_cols(ColsAtCompileTime)
explicit inline MapBase(PointerType dataPtr) : m_data(dataPtr), m_rows(RowsAtCompileTime), m_cols(ColsAtCompileTime)
{
EIGEN_STATIC_ASSERT_FIXED_SIZE(Derived)
checkSanity();

2
uppsrc/plugin/Eigen/Eigen/src/Core/MathFunctions.h
View file

@ -294,7 +294,7 @@ struct hypot_impl
RealScalar _x = abs(x);
RealScalar _y = abs(y);
RealScalar p = (max)(_x, _y);
if(p==RealScalar(0)) return 0;
if(p==RealScalar(0)) return RealScalar(0);
RealScalar q = (min)(_x, _y);
RealScalar qp = q/p;
return p * sqrt(RealScalar(1) + qp*qp);

15
uppsrc/plugin/Eigen/Eigen/src/Core/Matrix.h
View file

@ -211,6 +211,21 @@ class Matrix
: Base(internal::constructor_without_unaligned_array_assert())
{ Base::_check_template_params(); EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED }
#ifdef EIGEN_HAVE_RVALUE_REFERENCES
Matrix(Matrix&& other)
: Base(std::move(other))
{
Base::_check_template_params();
if (RowsAtCompileTime!=Dynamic && ColsAtCompileTime!=Dynamic)
Base::_set_noalias(other);
}
Matrix& operator=(Matrix&& other)
{
other.swap(*this);
return *this;
}
#endif
/** \brief Constructs a vector or row-vector with given dimension. \only_for_vectors
*
* Note that this is only useful for dynamic-size vectors. For fixed-size vectors,

9
uppsrc/plugin/Eigen/Eigen/src/Core/MatrixBase.h
View file

@ -440,6 +440,15 @@ template<typename Derived> class MatrixBase
template<typename OtherScalar>
void applyOnTheRight(Index p, Index q, const JacobiRotation<OtherScalar>& j);
///////// SparseCore module /////////
template<typename OtherDerived>
EIGEN_STRONG_INLINE const typename SparseMatrixBase<OtherDerived>::template CwiseProductDenseReturnType<Derived>::Type
cwiseProduct(const SparseMatrixBase<OtherDerived> &other) const
{
return other.cwiseProduct(derived());
}
///////// MatrixFunctions module /////////
typedef typename internal::stem_function<Scalar>::type StemFunction;

30
uppsrc/plugin/Eigen/Eigen/src/Core/PlainObjectBase.h
View file

@ -437,6 +437,36 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
}
#endif
#ifdef EIGEN_HAVE_RVALUE_REFERENCES
PlainObjectBase(PlainObjectBase&& other)
: m_storage( std::move(other.m_storage) )
{
}
PlainObjectBase& operator=(PlainObjectBase&& other)
{
using std::swap;
swap(m_storage, other.m_storage);
return *this;
}
#endif
/** Copy constructor */
EIGEN_STRONG_INLINE PlainObjectBase(const PlainObjectBase& other)
: m_storage()
{
_check_template_params();
lazyAssign(other);
}
template<typename OtherDerived>
EIGEN_STRONG_INLINE PlainObjectBase(const DenseBase<OtherDerived> &other)
: m_storage()
{
_check_template_params();
lazyAssign(other);
}
EIGEN_STRONG_INLINE PlainObjectBase(Index a_size, Index nbRows, Index nbCols)
: m_storage(a_size, nbRows, nbCols)
{

5
uppsrc/plugin/Eigen/Eigen/src/Core/Redux.h
View file

@ -247,8 +247,9 @@ struct redux_impl<Func, Derived, LinearVectorizedTraversal, NoUnrolling>
}
};
template<typename Func, typename Derived>
struct redux_impl<Func, Derived, SliceVectorizedTraversal, NoUnrolling>
// NOTE: for SliceVectorizedTraversal we simply bypass unrolling
template<typename Func, typename Derived, int Unrolling>
struct redux_impl<Func, Derived, SliceVectorizedTraversal, Unrolling>
{
typedef typename Derived::Scalar Scalar;
typedef typename packet_traits<Scalar>::type PacketScalar;

9
uppsrc/plugin/Eigen/Eigen/src/Core/Ref.h
View file

@ -244,6 +244,15 @@ template<typename TPlainObjectType, int Options, typename StrideType> class Ref<
// std::cout << int(StrideType::InnerStrideAtCompileTime) << " - " << int(Derived::InnerStrideAtCompileTime) << "\n";
construct(expr.derived(), typename Traits::template match<Derived>::type());
}
inline Ref(const Ref& other) : Base(other) {
// copy constructor shall not copy the m_object, to avoid unnecessary malloc and copy
}
template<typename OtherRef>
inline Ref(const RefBase<OtherRef>& other) {
construct(other.derived(), typename Traits::template match<OtherRef>::type());
}
protected:

10
uppsrc/plugin/Eigen/Eigen/src/Core/SelfCwiseBinaryOp.h
View file

@ -180,15 +180,9 @@ inline Derived& DenseBase<Derived>::operator*=(const Scalar& other)
template<typename Derived>
inline Derived& DenseBase<Derived>::operator/=(const Scalar& other)
{
typedef typename internal::conditional<NumTraits<Scalar>::IsInteger,
internal::scalar_quotient_op<Scalar>,
internal::scalar_product_op<Scalar> >::type BinOp;
typedef typename Derived::PlainObject PlainObject;
SelfCwiseBinaryOp<BinOp, Derived, typename PlainObject::ConstantReturnType> tmp(derived());
Scalar actual_other;
if(NumTraits<Scalar>::IsInteger) actual_other = other;
else actual_other = Scalar(1)/other;
tmp = PlainObject::Constant(rows(),cols(), actual_other);
SelfCwiseBinaryOp<internal::scalar_quotient_op<Scalar>, Derived, typename PlainObject::ConstantReturnType> tmp(derived());
tmp = PlainObject::Constant(rows(),cols(), other);
return derived();
}

1
uppsrc/plugin/Eigen/Eigen/src/Core/arch/NEON/PacketMath.h
View file

@ -384,6 +384,7 @@ template<> EIGEN_STRONG_INLINE int predux_max<Packet4i>(const Packet4i& a)
a_lo = vget_low_s32(a);
a_hi = vget_high_s32(a);
max = vpmax_s32(a_lo, a_hi);
max = vpmax_s32(max, max);
return vget_lane_s32(max, 0);
}

8
uppsrc/plugin/Eigen/Eigen/src/Core/arch/SSE/MathFunctions.h
View file

@ -126,7 +126,7 @@ Packet4f pexp<Packet4f>(const Packet4f& _x)
_EIGEN_DECLARE_CONST_Packet4f(cephes_exp_p4, 1.6666665459E-1f);
_EIGEN_DECLARE_CONST_Packet4f(cephes_exp_p5, 5.0000001201E-1f);
Packet4f tmp = _mm_setzero_ps(), fx;
Packet4f tmp, fx;
Packet4i emm0;
// clamp x
@ -195,7 +195,7 @@ Packet2d pexp<Packet2d>(const Packet2d& _x)
_EIGEN_DECLARE_CONST_Packet2d(cephes_exp_C2, 1.42860682030941723212e-6);
static const __m128i p4i_1023_0 = _mm_setr_epi32(1023, 1023, 0, 0);
Packet2d tmp = _mm_setzero_pd(), fx;
Packet2d tmp, fx;
Packet4i emm0;
// clamp x
@ -279,7 +279,7 @@ Packet4f psin<Packet4f>(const Packet4f& _x)
_EIGEN_DECLARE_CONST_Packet4f(coscof_p2, 4.166664568298827E-002f);
_EIGEN_DECLARE_CONST_Packet4f(cephes_FOPI, 1.27323954473516f); // 4 / M_PI
Packet4f xmm1, xmm2 = _mm_setzero_ps(), xmm3, sign_bit, y;
Packet4f xmm1, xmm2, xmm3, sign_bit, y;
Packet4i emm0, emm2;
sign_bit = x;
@ -378,7 +378,7 @@ Packet4f pcos<Packet4f>(const Packet4f& _x)
_EIGEN_DECLARE_CONST_Packet4f(coscof_p2, 4.166664568298827E-002f);
_EIGEN_DECLARE_CONST_Packet4f(cephes_FOPI, 1.27323954473516f); // 4 / M_PI
Packet4f xmm1, xmm2 = _mm_setzero_ps(), xmm3, y;
Packet4f xmm1, xmm2, xmm3, y;
Packet4i emm0, emm2;
x = pabs(x);

4
uppsrc/plugin/Eigen/Eigen/src/Core/products/TriangularMatrixMatrix_MKL.h
View file

@ -109,7 +109,7 @@ struct product_triangular_matrix_matrix_trmm<EIGTYPE,Index,Mode,true, \
/* Non-square case - doesn't fit to MKL ?TRMM. Fall to default triangular product or call MKL ?GEMM*/ \
if (rows != depth) { \
\
int nthr = mkl_domain_get_max_threads(MKL_BLAS); \
int nthr = mkl_domain_get_max_threads(EIGEN_MKL_DOMAIN_BLAS); \
\
if (((nthr==1) && (((std::max)(rows,depth)-diagSize)/(double)diagSize < 0.5))) { \
/* Most likely no benefit to call TRMM or GEMM from MKL*/ \
@ -223,7 +223,7 @@ struct product_triangular_matrix_matrix_trmm<EIGTYPE,Index,Mode,false, \
/* Non-square case - doesn't fit to MKL ?TRMM. Fall to default triangular product or call MKL ?GEMM*/ \
if (cols != depth) { \
\
int nthr = mkl_domain_get_max_threads(MKL_BLAS); \
int nthr = mkl_domain_get_max_threads(EIGEN_MKL_DOMAIN_BLAS); \
\
if ((nthr==1) && (((std::max)(cols,depth)-diagSize)/(double)diagSize < 0.5)) { \
/* Most likely no benefit to call TRMM or GEMM from MKL*/ \

9
uppsrc/plugin/Eigen/Eigen/src/Core/products/TriangularSolverMatrix.h
View file

@ -302,9 +302,12 @@ EIGEN_DONT_INLINE void triangular_solve_matrix<Scalar,Index,OnTheRight,Mode,Conj
for (Index i=0; i<actual_mc; ++i)
r[i] -= a[i] * b;
}
Scalar b = (Mode & UnitDiag) ? Scalar(1) : Scalar(1)/conj(rhs(j,j));
for (Index i=0; i<actual_mc; ++i)
r[i] *= b;
if((Mode & UnitDiag)==0)
{
Scalar b = conj(rhs(j,j));
for (Index i=0; i<actual_mc; ++i)
r[i] /= b;
}
}
// pack the just computed part of lhs to A

3
uppsrc/plugin/Eigen/Eigen/src/Core/util/ForwardDeclarations.h
View file

@ -235,6 +235,9 @@ template<typename Scalar> class Rotation2D;
template<typename Scalar> class AngleAxis;
template<typename Scalar,int Dim> class Translation;
// Sparse module:
template<typename Derived> class SparseMatrixBase;
#ifdef EIGEN2_SUPPORT
template<typename Derived, int _Dim> class eigen2_RotationBase;
template<typename Lhs, typename Rhs> class eigen2_Cross;

32
uppsrc/plugin/Eigen/Eigen/src/Core/util/MKL_support.h
View file

@ -76,6 +76,38 @@
#include <mkl_lapacke.h>
#define EIGEN_MKL_VML_THRESHOLD 128
/* MKL_DOMAIN_BLAS, etc are defined only in 10.3 update 7 */
/* MKL_BLAS, etc are not defined in 11.2 */
#ifdef MKL_DOMAIN_ALL
#define EIGEN_MKL_DOMAIN_ALL MKL_DOMAIN_ALL
#else
#define EIGEN_MKL_DOMAIN_ALL MKL_ALL
#endif
#ifdef MKL_DOMAIN_BLAS
#define EIGEN_MKL_DOMAIN_BLAS MKL_DOMAIN_BLAS
#else
#define EIGEN_MKL_DOMAIN_BLAS MKL_BLAS
#endif
#ifdef MKL_DOMAIN_FFT
#define EIGEN_MKL_DOMAIN_FFT MKL_DOMAIN_FFT
#else
#define EIGEN_MKL_DOMAIN_FFT MKL_FFT
#endif
#ifdef MKL_DOMAIN_VML
#define EIGEN_MKL_DOMAIN_VML MKL_DOMAIN_VML
#else
#define EIGEN_MKL_DOMAIN_VML MKL_VML
#endif
#ifdef MKL_DOMAIN_PARDISO
#define EIGEN_MKL_DOMAIN_PARDISO MKL_DOMAIN_PARDISO
#else
#define EIGEN_MKL_DOMAIN_PARDISO MKL_PARDISO
#endif
namespace Eigen {
typedef std::complex<double> dcomplex;

20
uppsrc/plugin/Eigen/Eigen/src/Core/util/Macros.h
View file

@ -13,7 +13,7 @@
#define EIGEN_WORLD_VERSION 3
#define EIGEN_MAJOR_VERSION 2
#define EIGEN_MINOR_VERSION 5
#define EIGEN_MINOR_VERSION 7
#define EIGEN_VERSION_AT_LEAST(x,y,z) (EIGEN_WORLD_VERSION>x || (EIGEN_WORLD_VERSION>=x && \
(EIGEN_MAJOR_VERSION>y || (EIGEN_MAJOR_VERSION>=y && \
@ -96,6 +96,20 @@
#define EIGEN_DEFAULT_DENSE_INDEX_TYPE std::ptrdiff_t
#endif
// A Clang feature extension to determine compiler features.
// We use it to determine 'cxx_rvalue_references'
#ifndef __has_feature
# define __has_feature(x) 0
#endif
// Do we support r-value references?
#if (__has_feature(cxx_rvalue_references) || \
defined(__GXX_EXPERIMENTAL_CXX0X__) || \
(defined(_MSC_VER) && _MSC_VER >= 1600))
#define EIGEN_HAVE_RVALUE_REFERENCES
#endif
// Cross compiler wrapper around LLVM's __has_builtin
#ifdef __has_builtin
# define EIGEN_HAS_BUILTIN(x) __has_builtin(x)
@ -314,7 +328,7 @@ namespace Eigen {
// just an empty macro !
#define EIGEN_EMPTY
#if defined(_MSC_VER) && (_MSC_VER < 1800) && (!defined(__INTEL_COMPILER))
#if defined(_MSC_VER) && (_MSC_VER < 1900) && (!defined(__INTEL_COMPILER))
#define EIGEN_INHERIT_ASSIGNMENT_EQUAL_OPERATOR(Derived) \
using Base::operator =;
#elif defined(__clang__) // workaround clang bug (see http://forum.kde.org/viewtopic.php?f=74&t=102653)
@ -409,6 +423,8 @@ namespace Eigen {
#define EIGEN_SIZE_MAX(a,b) (((int)a == Dynamic || (int)b == Dynamic) ? Dynamic \
: ((int)a >= (int)b) ? (int)a : (int)b)
#define EIGEN_ADD_COST(a,b) int(a)==Dynamic || int(b)==Dynamic ? Dynamic : int(a)+int(b)
#define EIGEN_LOGICAL_XOR(a,b) (((a) || (b)) && !((a) && (b)))
#define EIGEN_IMPLIES(a,b) (!(a) || (b))

8
uppsrc/plugin/Eigen/Eigen/src/Core/util/XprHelper.h
View file

@ -366,17 +366,17 @@ struct dense_xpr_base<Derived, ArrayXpr>
/** \internal Helper base class to add a scalar multiple operator
* overloads for complex types */
template<typename Derived,typename Scalar,typename OtherScalar,
template<typename Derived, typename Scalar, typename OtherScalar, typename BaseType,
bool EnableIt = !is_same<Scalar,OtherScalar>::value >
struct special_scalar_op_base : public DenseCoeffsBase<Derived>
struct special_scalar_op_base : public BaseType
{
// dummy operator* so that the
// "using special_scalar_op_base::operator*" compiles
void operator*() const;
};
template<typename Derived,typename Scalar,typename OtherScalar>
struct special_scalar_op_base<Derived,Scalar,OtherScalar,true> : public DenseCoeffsBase<Derived>
template<typename Derived,typename Scalar,typename OtherScalar, typename BaseType>
struct special_scalar_op_base<Derived,Scalar,OtherScalar,BaseType,true> : public BaseType
{
const CwiseUnaryOp<scalar_multiple2_op<Scalar,OtherScalar>, Derived>
operator*(const OtherScalar& scalar) const

23
uppsrc/plugin/Eigen/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h
View file

@ -80,6 +80,8 @@ template<typename _MatrixType> class SelfAdjointEigenSolver
/** \brief Scalar type for matrices of type \p _MatrixType. */
typedef typename MatrixType::Scalar Scalar;
typedef typename MatrixType::Index Index;
typedef Matrix<Scalar,Size,Size,ColMajor,MaxColsAtCompileTime,MaxColsAtCompileTime> EigenvectorsType;
/** \brief Real scalar type for \p _MatrixType.
*
@ -225,7 +227,7 @@ template<typename _MatrixType> class SelfAdjointEigenSolver
*
* \sa eigenvalues()
*/
const MatrixType& eigenvectors() const
const EigenvectorsType& eigenvectors() const
{
eigen_assert(m_isInitialized && "SelfAdjointEigenSolver is not initialized.");
eigen_assert(m_eigenvectorsOk && "The eigenvectors have not been computed together with the eigenvalues.");
@ -356,7 +358,7 @@ template<typename _MatrixType> class SelfAdjointEigenSolver
EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar);
}
MatrixType m_eivec;
EigenvectorsType m_eivec;
RealVectorType m_eivalues;
typename TridiagonalizationType::SubDiagonalType m_subdiag;
ComputationInfo m_info;
@ -381,7 +383,7 @@ template<typename _MatrixType> class SelfAdjointEigenSolver
* "implicit symmetric QR step with Wilkinson shift"
*/
namespace internal {
template<int StorageOrder,typename RealScalar, typename Scalar, typename Index>
template<typename RealScalar, typename Scalar, typename Index>
static void tridiagonal_qr_step(RealScalar* diag, RealScalar* subdiag, Index start, Index end, Scalar* matrixQ, Index n);
}
@ -413,7 +415,7 @@ SelfAdjointEigenSolver<MatrixType>& SelfAdjointEigenSolver<MatrixType>
// declare some aliases
RealVectorType& diag = m_eivalues;
MatrixType& mat = m_eivec;
EigenvectorsType& mat = m_eivec;
// map the matrix coefficients to [-1:1] to avoid over- and underflow.
mat = matrix.template triangularView<Lower>();
@ -449,7 +451,7 @@ SelfAdjointEigenSolver<MatrixType>& SelfAdjointEigenSolver<MatrixType>
while (start>0 && m_subdiag[start-1]!=0)
start--;
internal::tridiagonal_qr_step<MatrixType::Flags&RowMajorBit ? RowMajor : ColMajor>(diag.data(), m_subdiag.data(), start, end, computeEigenvectors ? m_eivec.data() : (Scalar*)0, n);
internal::tridiagonal_qr_step(diag.data(), m_subdiag.data(), start, end, computeEigenvectors ? m_eivec.data() : (Scalar*)0, n);
}
if (iter <= m_maxIterations * n)
@ -498,6 +500,7 @@ template<typename SolverType> struct direct_selfadjoint_eigenvalues<SolverType,3
typedef typename SolverType::RealVectorType VectorType;
typedef typename SolverType::Scalar Scalar;
typedef typename MatrixType::Index Index;
typedef typename SolverType::EigenvectorsType EigenvectorsType;
/** \internal
* Computes the roots of the characteristic polynomial of \a m.
@ -570,7 +573,7 @@ template<typename SolverType> struct direct_selfadjoint_eigenvalues<SolverType,3
&& "invalid option parameter");
bool computeEigenvectors = (options&ComputeEigenvectors)==ComputeEigenvectors;
MatrixType& eivecs = solver.m_eivec;
EigenvectorsType& eivecs = solver.m_eivec;
VectorType& eivals = solver.m_eivalues;
// Shift the matrix to the mean eigenvalue and map the matrix coefficients to [-1:1] to avoid over- and underflow.
@ -652,6 +655,7 @@ template<typename SolverType> struct direct_selfadjoint_eigenvalues<SolverType,2
typedef typename SolverType::MatrixType MatrixType;
typedef typename SolverType::RealVectorType VectorType;
typedef typename SolverType::Scalar Scalar;
typedef typename SolverType::EigenvectorsType EigenvectorsType;
static inline void computeRoots(const MatrixType& m, VectorType& roots)
{
@ -673,7 +677,7 @@ template<typename SolverType> struct direct_selfadjoint_eigenvalues<SolverType,2
&& "invalid option parameter");
bool computeEigenvectors = (options&ComputeEigenvectors)==ComputeEigenvectors;
MatrixType& eivecs = solver.m_eivec;
EigenvectorsType& eivecs = solver.m_eivec;
VectorType& eivals = solver.m_eivalues;
// map the matrix coefficients to [-1:1] to avoid over- and underflow.
@ -732,7 +736,7 @@ SelfAdjointEigenSolver<MatrixType>& SelfAdjointEigenSolver<MatrixType>
}
namespace internal {
template<int StorageOrder,typename RealScalar, typename Scalar, typename Index>
template<typename RealScalar, typename Scalar, typename Index>
static void tridiagonal_qr_step(RealScalar* diag, RealScalar* subdiag, Index start, Index end, Scalar* matrixQ, Index n)
{
using std::abs;
@ -784,8 +788,7 @@ static void tridiagonal_qr_step(RealScalar* diag, RealScalar* subdiag, Index sta
// apply the givens rotation to the unit matrix Q = Q * G
if (matrixQ)
{
// FIXME if StorageOrder == RowMajor this operation is not very efficient
Map<Matrix<Scalar,Dynamic,Dynamic,StorageOrder> > q(matrixQ,n,n);
Map<Matrix<Scalar,Dynamic,Dynamic,ColMajor> > q(matrixQ,n,n);
q.applyOnTheRight(k,k+1,rot);
}
}

2
uppsrc/plugin/Eigen/Eigen/src/Geometry/AlignedBox.h
View file

@ -163,7 +163,7 @@ EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF_VECTORIZABLE_FIXED_SIZE(_Scalar,_AmbientDim)
* a uniform distribution */
inline VectorType sample() const
{
VectorType r;
VectorType r(dim());
for(Index d=0; d<dim(); ++d)
{
if(!ScalarTraits::IsInteger)

6
uppsrc/plugin/Eigen/Eigen/src/Geometry/AngleAxis.h
View file

@ -131,7 +131,7 @@ public:
m_angle = Scalar(other.angle());
}
static inline const AngleAxis Identity() { return AngleAxis(0, Vector3::UnitX()); }
static inline const AngleAxis Identity() { return AngleAxis(Scalar(0), Vector3::UnitX()); }
/** \returns \c true if \c *this is approximately equal to \a other, within the precision
* determined by \a prec.
@ -165,8 +165,8 @@ AngleAxis<Scalar>& AngleAxis<Scalar>::operator=(const QuaternionBase<QuatDerived
Scalar n2 = q.vec().squaredNorm();
if (n2 < NumTraits<Scalar>::dummy_precision()*NumTraits<Scalar>::dummy_precision())
{
m_angle = 0;
m_axis << 1, 0, 0;
m_angle = Scalar(0);
m_axis << Scalar(1), Scalar(0), Scalar(0);
}
else
{

4
uppsrc/plugin/Eigen/Eigen/src/Geometry/Quaternion.h
View file

@ -102,11 +102,11 @@ public:
/** \returns a quaternion representing an identity rotation
* \sa MatrixBase::Identity()
*/
static inline Quaternion<Scalar> Identity() { return Quaternion<Scalar>(1, 0, 0, 0); }
static inline Quaternion<Scalar> Identity() { return Quaternion<Scalar>(Scalar(1), Scalar(0), Scalar(0), Scalar(0)); }
/** \sa QuaternionBase::Identity(), MatrixBase::setIdentity()
*/
inline QuaternionBase& setIdentity() { coeffs() << 0, 0, 0, 1; return *this; }
inline QuaternionBase& setIdentity() { coeffs() << Scalar(0), Scalar(0), Scalar(0), Scalar(1); return *this; }
/** \returns the squared norm of the quaternion's coefficients
* \sa QuaternionBase::norm(), MatrixBase::squaredNorm()

4
uppsrc/plugin/Eigen/Eigen/src/IterativeLinearSolvers/BasicPreconditioners.h
View file

@ -65,10 +65,10 @@ class DiagonalPreconditioner
{
typename MatType::InnerIterator it(mat,j);
while(it && it.index()!=j) ++it;
if(it && it.index()==j)
if(it && it.index()==j && it.value()!=Scalar(0))
m_invdiag(j) = Scalar(1)/it.value();
else
m_invdiag(j) = 0;
m_invdiag(j) = Scalar(1);
}
m_isInitialized = true;
return *this;

3
uppsrc/plugin/Eigen/Eigen/src/IterativeLinearSolvers/BiCGSTAB.h
View file

@ -186,7 +186,8 @@ public:
* this class becomes invalid. Call compute() to update it with the new
* matrix A, or modify a copy of A.
*/
BiCGSTAB(const MatrixType& A) : Base(A) {}
template<typename MatrixDerived>
explicit BiCGSTAB(const EigenBase<MatrixDerived>& A) : Base(A.derived()) {}
~BiCGSTAB() {}

3
uppsrc/plugin/Eigen/Eigen/src/IterativeLinearSolvers/ConjugateGradient.h
View file

@ -176,7 +176,8 @@ public:
* this class becomes invalid. Call compute() to update it with the new
* matrix A, or modify a copy of A.
*/
ConjugateGradient(const MatrixType& A) : Base(A) {}
template<typename MatrixDerived>
explicit ConjugateGradient(const EigenBase<MatrixDerived>& A) : Base(A.derived()) {}
~ConjugateGradient() {}

21
uppsrc/plugin/Eigen/Eigen/src/IterativeLinearSolvers/IncompleteLUT.h
View file

@ -159,7 +159,7 @@ class IncompleteLUT : internal::noncopyable
template<typename Rhs, typename Dest>
void _solve(const Rhs& b, Dest& x) const
{
x = m_Pinv * b;
x = m_Pinv * b;
x = m_lu.template triangularView<UnitLower>().solve(x);
x = m_lu.template triangularView<Upper>().solve(x);
x = m_P * x;
@ -222,16 +222,25 @@ template<typename _MatrixType>
void IncompleteLUT<Scalar>::analyzePattern(const _MatrixType& amat)
{
// Compute the Fill-reducing permutation
// Since ILUT does not perform any numerical pivoting,
// it is highly preferable to keep the diagonal through symmetric permutations.
#ifndef EIGEN_MPL2_ONLY
// To this end, let's symmetrize the pattern and perform AMD on it.
SparseMatrix<Scalar,ColMajor, Index> mat1 = amat;
SparseMatrix<Scalar,ColMajor, Index> mat2 = amat.transpose();
// Symmetrize the pattern
// FIXME for a matrix with nearly symmetric pattern, mat2+mat1 is the appropriate choice.
// on the other hand for a really non-symmetric pattern, mat2*mat1 should be prefered...
SparseMatrix<Scalar,ColMajor, Index> AtA = mat2 + mat1;
AtA.prune(keep_diag());
internal::minimum_degree_ordering<Scalar, Index>(AtA, m_P); // Then compute the AMD ordering...
m_Pinv = m_P.inverse(); // ... and the inverse permutation
AMDOrdering<Index> ordering;
ordering(AtA,m_P);
m_Pinv = m_P.inverse(); // cache the inverse permutation
#else
// If AMD is not available, (MPL2-only), then let's use the slower COLAMD routine.
SparseMatrix<Scalar,ColMajor, Index> mat1 = amat;
COLAMDOrdering<Index> ordering;
ordering(mat1,m_Pinv);
m_P = m_Pinv.inverse();
#endif
m_analysisIsOk = true;
m_factorizationIsOk = false;

48
uppsrc/plugin/Eigen/Eigen/src/IterativeLinearSolvers/IterativeSolverBase.h
View file

@ -49,10 +49,11 @@ public:
* this class becomes invalid. Call compute() to update it with the new
* matrix A, or modify a copy of A.
*/
IterativeSolverBase(const MatrixType& A)
template<typename InputDerived>
IterativeSolverBase(const EigenBase<InputDerived>& A)
{
init();
compute(A);
compute(A.derived());
}
~IterativeSolverBase() {}
@ -62,9 +63,11 @@ public:
* Currently, this function mostly call analyzePattern on the preconditioner. In the future
* we might, for instance, implement column reodering for faster matrix vector products.
*/
Derived& analyzePattern(const MatrixType& A)
template<typename InputDerived>
Derived& analyzePattern(const EigenBase<InputDerived>& A)
{
m_preconditioner.analyzePattern(A);
grabInput(A.derived());
m_preconditioner.analyzePattern(*mp_matrix);
m_isInitialized = true;
m_analysisIsOk = true;
m_info = Success;
@ -80,11 +83,12 @@ public:
* this class becomes invalid. Call compute() to update it with the new
* matrix A, or modify a copy of A.
*/
Derived& factorize(const MatrixType& A)
template<typename InputDerived>
Derived& factorize(const EigenBase<InputDerived>& A)
{
grabInput(A.derived());
eigen_assert(m_analysisIsOk && "You must first call analyzePattern()");
mp_matrix = &A;
m_preconditioner.factorize(A);
m_preconditioner.factorize(*mp_matrix);
m_factorizationIsOk = true;
m_info = Success;
return derived();
@ -100,10 +104,11 @@ public:
* this class becomes invalid. Call compute() to update it with the new
* matrix A, or modify a copy of A.
*/
Derived& compute(const MatrixType& A)
template<typename InputDerived>
Derived& compute(const EigenBase<InputDerived>& A)
{
mp_matrix = &A;
m_preconditioner.compute(A);
grabInput(A.derived());
m_preconditioner.compute(*mp_matrix);
m_isInitialized = true;
m_analysisIsOk = true;
m_factorizationIsOk = true;
@ -212,6 +217,28 @@ public:
}
protected:
template<typename InputDerived>
void grabInput(const EigenBase<InputDerived>& A)
{
// we const cast to prevent the creation of a MatrixType temporary by the compiler.
grabInput_impl(A.const_cast_derived());
}
template<typename InputDerived>
void grabInput_impl(const EigenBase<InputDerived>& A)
{
m_copyMatrix = A;
mp_matrix = &m_copyMatrix;
}
void grabInput_impl(MatrixType& A)
{
if(MatrixType::RowsAtCompileTime==Dynamic && MatrixType::ColsAtCompileTime==Dynamic)
m_copyMatrix.resize(0,0);
mp_matrix = &A;
}
void init()
{
m_isInitialized = false;
@ -220,6 +247,7 @@ protected:
m_maxIterations = -1;
m_tolerance = NumTraits<Scalar>::epsilon();
}
MatrixType m_copyMatrix;
const MatrixType* mp_matrix;
Preconditioner m_preconditioner;

5
uppsrc/plugin/Eigen/Eigen/src/OrderingMethods/Amd.h
View file

@ -137,9 +137,6 @@ void minimum_degree_ordering(SparseMatrix<Scalar,ColMajor,Index>& C, Permutation
degree[i] = len[i]; // degree of node i
}
mark = internal::cs_wclear<Index>(0, 0, w, n); /* clear w */
elen[n] = -2; /* n is a dead element */
Cp[n] = -1; /* n is a root of assembly tree */
w[n] = 0; /* n is a dead element */
/* --- Initialize degree lists ------------------------------------------ */
for(i = 0; i < n; i++)
@ -153,7 +150,7 @@ void minimum_degree_ordering(SparseMatrix<Scalar,ColMajor,Index>& C, Permutation
}
d = degree[i];
if(d == 1) /* node i is empty */
if(d == 1 && has_diag) /* node i is empty */
{
elen[i] = -2; /* element i is dead */
nel++;

4
uppsrc/plugin/Eigen/Eigen/src/SPQRSupport/SuiteSparseQRSupport.h
View file

@ -47,7 +47,7 @@ namespace Eigen {
* You can then apply it to a vector.
*
* R is the sparse triangular factor. Use matrixQR() to get it as SparseMatrix.
* NOTE : The Index type of R is always UF_long. You can get it with SPQR::Index
* NOTE : The Index type of R is always SuiteSparse_long. You can get it with SPQR::Index
*
* \tparam _MatrixType The type of the sparse matrix A, must be a column-major SparseMatrix<>
* NOTE
@ -59,7 +59,7 @@ class SPQR
public:
typedef typename _MatrixType::Scalar Scalar;
typedef typename _MatrixType::RealScalar RealScalar;
typedef UF_long Index ;
typedef SuiteSparse_long Index ;
typedef SparseMatrix<Scalar, ColMajor, Index> MatrixType;
typedef PermutationMatrix<Dynamic, Dynamic> PermutationType;
public:

4
uppsrc/plugin/Eigen/Eigen/src/SparseCore/SparseCwiseBinaryOp.h
View file

@ -314,10 +314,10 @@ SparseMatrixBase<Derived>::operator+=(const SparseMatrixBase<OtherDerived>& othe
template<typename Derived>
template<typename OtherDerived>
EIGEN_STRONG_INLINE const EIGEN_SPARSE_CWISE_PRODUCT_RETURN_TYPE
EIGEN_STRONG_INLINE const typename SparseMatrixBase<Derived>::template CwiseProductDenseReturnType<OtherDerived>::Type
SparseMatrixBase<Derived>::cwiseProduct(const MatrixBase<OtherDerived> &other) const
{
return EIGEN_SPARSE_CWISE_PRODUCT_RETURN_TYPE(derived(), other.derived());
return typename CwiseProductDenseReturnType<OtherDerived>::Type(derived(), other.derived());
}
} // end namespace Eigen

5
uppsrc/plugin/Eigen/Eigen/src/SparseCore/SparseMatrix.h
View file

@ -691,7 +691,8 @@ class SparseMatrix
m_data.swap(other.m_data);
}
/** Sets *this to the identity matrix */
/** Sets *this to the identity matrix.
* This function also turns the matrix into compressed mode, and drop any reserved memory. */
inline void setIdentity()
{
eigen_assert(rows() == cols() && "ONLY FOR SQUARED MATRICES");
@ -699,6 +700,8 @@ class SparseMatrix
Eigen::Map<Matrix<Index, Dynamic, 1> >(&this->m_data.index(0), rows()).setLinSpaced(0, rows()-1);
Eigen::Map<Matrix<Scalar, Dynamic, 1> >(&this->m_data.value(0), rows()).setOnes();
Eigen::Map<Matrix<Index, Dynamic, 1> >(this->m_outerIndex, rows()+1).setLinSpaced(0, rows());
std::free(m_innerNonZeros);
m_innerNonZeros = 0;
}
inline SparseMatrix& operator=(const SparseMatrix& other)
{

35
uppsrc/plugin/Eigen/Eigen/src/SparseCore/SparseMatrixBase.h
View file

@ -23,7 +23,14 @@ namespace Eigen {
* This class can be extended with the help of the plugin mechanism described on the page
* \ref TopicCustomizingEigen by defining the preprocessor symbol \c EIGEN_SPARSEMATRIXBASE_PLUGIN.
*/
template<typename Derived> class SparseMatrixBase : public EigenBase<Derived>
template<typename Derived> class SparseMatrixBase
#ifndef EIGEN_PARSED_BY_DOXYGEN
: public internal::special_scalar_op_base<Derived,typename internal::traits<Derived>::Scalar,
typename NumTraits<typename internal::traits<Derived>::Scalar>::Real,
EigenBase<Derived> >
#else
: public EigenBase<Derived>
#endif // not EIGEN_PARSED_BY_DOXYGEN
{
public:
@ -36,7 +43,6 @@ template<typename Derived> class SparseMatrixBase : public EigenBase<Derived>
>::type PacketReturnType;
typedef SparseMatrixBase StorageBaseType;
typedef EigenBase<Derived> Base;
template<typename OtherDerived>
Derived& operator=(const EigenBase<OtherDerived> &other)
@ -132,6 +138,9 @@ template<typename Derived> class SparseMatrixBase : public EigenBase<Derived>
inline Derived& derived() { return *static_cast<Derived*>(this); }
inline Derived& const_cast_derived() const
{ return *static_cast<Derived*>(const_cast<SparseMatrixBase*>(this)); }
typedef internal::special_scalar_op_base<Derived, Scalar, RealScalar, EigenBase<Derived> > Base;
using Base::operator*;
#endif // not EIGEN_PARSED_BY_DOXYGEN
#define EIGEN_CURRENT_STORAGE_BASE_CLASS Eigen::SparseMatrixBase
@ -317,20 +326,18 @@ template<typename Derived> class SparseMatrixBase : public EigenBase<Derived>
Derived& operator*=(const Scalar& other);
Derived& operator/=(const Scalar& other);
#define EIGEN_SPARSE_CWISE_PRODUCT_RETURN_TYPE \
CwiseBinaryOp< \
internal::scalar_product_op< \
typename internal::scalar_product_traits< \
typename internal::traits<Derived>::Scalar, \
typename internal::traits<OtherDerived>::Scalar \
>::ReturnType \
>, \
const Derived, \
const OtherDerived \
>
template<typename OtherDerived> struct CwiseProductDenseReturnType {
typedef CwiseBinaryOp<internal::scalar_product_op<typename internal::scalar_product_traits<
typename internal::traits<Derived>::Scalar,
typename internal::traits<OtherDerived>::Scalar
>::ReturnType>,
const Derived,
const OtherDerived
> Type;
};
template<typename OtherDerived>
EIGEN_STRONG_INLINE const EIGEN_SPARSE_CWISE_PRODUCT_RETURN_TYPE
EIGEN_STRONG_INLINE const typename CwiseProductDenseReturnType<OtherDerived>::Type
cwiseProduct(const MatrixBase<OtherDerived> &other) const;
// sparse * sparse

1
uppsrc/plugin/Eigen/Eigen/src/SparseCore/SparseUtil.h
View file

@ -67,7 +67,6 @@ const int InnerRandomAccessPattern = 0x2 | CoherentAccessPattern;
const int OuterRandomAccessPattern = 0x4 | CoherentAccessPattern;
const int RandomAccessPattern = 0x8 | OuterRandomAccessPattern | InnerRandomAccessPattern;
template<typename Derived> class SparseMatrixBase;
template<typename _Scalar, int _Flags = 0, typename _Index = int> class SparseMatrix;
template<typename _Scalar, int _Flags = 0, typename _Index = int> class DynamicSparseMatrix;
template<typename _Scalar, int _Flags = 0, typename _Index = int> class SparseVector;

1
uppsrc/plugin/Eigen/Eigen/src/SparseCore/SparseVector.h
View file

@ -158,6 +158,7 @@ class SparseVector
Index inner = IsColVector ? row : col;
Index outer = IsColVector ? col : row;
EIGEN_ONLY_USED_FOR_DEBUG(outer);
eigen_assert(outer==0);
return insert(inner);
}

4
uppsrc/plugin/Eigen/Eigen/src/SparseLU/SparseLU.h
View file

@ -749,8 +749,8 @@ struct SparseLUMatrixUReturnType : internal::no_assignment_operator
}
else
{
Map<const Matrix<Scalar,Dynamic,Dynamic>, 0, OuterStride<> > A( &(m_mapL.valuePtr()[luptr]), nsupc, nsupc, OuterStride<>(lda) );
Map< Matrix<Scalar,Dynamic,Dynamic>, 0, OuterStride<> > U (&(X(fsupc,0)), nsupc, nrhs, OuterStride<>(n) );
Map<const Matrix<Scalar,Dynamic,Dynamic, ColMajor>, 0, OuterStride<> > A( &(m_mapL.valuePtr()[luptr]), nsupc, nsupc, OuterStride<>(lda) );
Map< Matrix<Scalar,Dynamic,Dynamic, ColMajor>, 0, OuterStride<> > U (&(X(fsupc,0)), nsupc, nrhs, OuterStride<>(n) );
U = A.template triangularView<Upper>().solve(U);
}

2
uppsrc/plugin/Eigen/Eigen/src/SparseLU/SparseLUImpl.h
View file

@ -21,6 +21,8 @@ class SparseLUImpl
{
public:
typedef Matrix<Scalar,Dynamic,1> ScalarVector;
typedef Matrix<Scalar,Dynamic,Dynamic,ColMajor> ScalarMatrix;
typedef Map<ScalarMatrix, 0, OuterStride<> > MappedMatrixBlock;
typedef Matrix<Index,Dynamic,1> IndexVector;
typedef typename ScalarVector::RealScalar RealScalar;
typedef Ref<Matrix<Scalar,Dynamic,1> > BlockScalarVector;

4
uppsrc/plugin/Eigen/Eigen/src/SparseLU/SparseLU_Memory.h
View file

@ -153,8 +153,8 @@ Index SparseLUImpl<Scalar,Index>::memInit(Index m, Index n, Index annz, Index lw
{
Index& num_expansions = glu.num_expansions; //No memory expansions so far
num_expansions = 0;
glu.nzumax = glu.nzlumax = (std::min)(fillratio * annz / n, m) * n; // estimated number of nonzeros in U
glu.nzlmax = (std::max)(Index(4), fillratio) * annz / 4; // estimated nnz in L factor
glu.nzumax = glu.nzlumax = (std::min)(fillratio * (annz+1) / n, m) * n; // estimated number of nonzeros in U
glu.nzlmax = (std::max)(Index(4), fillratio) * (annz+1) / 4; // estimated nnz in L factor
// Return the estimated size to the user if necessary
Index tempSpace;
tempSpace = (2*panel_size + 4 + LUNoMarker) * m * sizeof(Index) + (panel_size + 1) * m * sizeof(Scalar);

8
uppsrc/plugin/Eigen/Eigen/src/SparseLU/SparseLU_SupernodalMatrix.h
View file

@ -236,7 +236,7 @@ void MappedSuperNodalMatrix<Scalar,Index>::solveInPlace( MatrixBase<Dest>&X) con
Index n = X.rows();
Index nrhs = X.cols();
const Scalar * Lval = valuePtr(); // Nonzero values
Matrix<Scalar,Dynamic,Dynamic> work(n, nrhs); // working vector
Matrix<Scalar,Dynamic,Dynamic, ColMajor> work(n, nrhs); // working vector
work.setZero();
for (Index k = 0; k <= nsuper(); k ++)
{
@ -267,12 +267,12 @@ void MappedSuperNodalMatrix<Scalar,Index>::solveInPlace( MatrixBase<Dest>&X) con
Index lda = colIndexPtr()[fsupc+1] - luptr;
// Triangular solve
Map<const Matrix<Scalar,Dynamic,Dynamic>, 0, OuterStride<> > A( &(Lval[luptr]), nsupc, nsupc, OuterStride<>(lda) );
Map< Matrix<Scalar,Dynamic,Dynamic>, 0, OuterStride<> > U (&(X(fsupc,0)), nsupc, nrhs, OuterStride<>(n) );
Map<const Matrix<Scalar,Dynamic,Dynamic, ColMajor>, 0, OuterStride<> > A( &(Lval[luptr]), nsupc, nsupc, OuterStride<>(lda) );
Map< Matrix<Scalar,Dynamic,Dynamic, ColMajor>, 0, OuterStride<> > U (&(X(fsupc,0)), nsupc, nrhs, OuterStride<>(n) );
U = A.template triangularView<UnitLower>().solve(U);
// Matrix-vector product
new (&A) Map<const Matrix<Scalar,Dynamic,Dynamic>, 0, OuterStride<> > ( &(Lval[luptr+nsupc]), nrow, nsupc, OuterStride<>(lda) );
new (&A) Map<const Matrix<Scalar,Dynamic,Dynamic, ColMajor>, 0, OuterStride<> > ( &(Lval[luptr+nsupc]), nrow, nsupc, OuterStride<>(lda) );
work.block(0, 0, nrow, nrhs) = A * U;
//Begin Scatter

4
uppsrc/plugin/Eigen/Eigen/src/SparseLU/SparseLU_column_bmod.h
View file

@ -162,11 +162,11 @@ Index SparseLUImpl<Scalar,Index>::column_bmod(const Index jcol, const Index nseg
// points to the beginning of jcol in snode L\U(jsupno)
ufirst = glu.xlusup(jcol) + d_fsupc;
Index lda = glu.xlusup(jcol+1) - glu.xlusup(jcol);
Map<Matrix<Scalar,Dynamic,Dynamic>, 0, OuterStride<> > A( &(glu.lusup.data()[luptr]), nsupc, nsupc, OuterStride<>(lda) );
MappedMatrixBlock A( &(glu.lusup.data()[luptr]), nsupc, nsupc, OuterStride<>(lda) );
VectorBlock<ScalarVector> u(glu.lusup, ufirst, nsupc);
u = A.template triangularView<UnitLower>().solve(u);
new (&A) Map<Matrix<Scalar,Dynamic,Dynamic>, 0, OuterStride<> > ( &(glu.lusup.data()[luptr+nsupc]), nrow, nsupc, OuterStride<>(lda) );
new (&A) MappedMatrixBlock ( &(glu.lusup.data()[luptr+nsupc]), nrow, nsupc, OuterStride<>(lda) );
VectorBlock<ScalarVector> l(glu.lusup, ufirst+nsupc, nrow);
l.noalias() -= A * u;

4
uppsrc/plugin/Eigen/Eigen/src/SparseLU/SparseLU_kernel_bmod.h
View file

@ -56,7 +56,7 @@ EIGEN_DONT_INLINE void LU_kernel_bmod<SegSizeAtCompileTime>::run(const int segsi
// Dense triangular solve -- start effective triangle
luptr += lda * no_zeros + no_zeros;
// Form Eigen matrix and vector
Map<Matrix<Scalar,SegSizeAtCompileTime,SegSizeAtCompileTime>, 0, OuterStride<> > A( &(lusup.data()[luptr]), segsize, segsize, OuterStride<>(lda) );
Map<Matrix<Scalar,SegSizeAtCompileTime,SegSizeAtCompileTime, ColMajor>, 0, OuterStride<> > A( &(lusup.data()[luptr]), segsize, segsize, OuterStride<>(lda) );
Map<Matrix<Scalar,SegSizeAtCompileTime,1> > u(tempv.data(), segsize);
u = A.template triangularView<UnitLower>().solve(u);
@ -65,7 +65,7 @@ EIGEN_DONT_INLINE void LU_kernel_bmod<SegSizeAtCompileTime>::run(const int segsi
luptr += segsize;
const Index PacketSize = internal::packet_traits<Scalar>::size;
Index ldl = internal::first_multiple(nrow, PacketSize);
Map<Matrix<Scalar,Dynamic,SegSizeAtCompileTime>, 0, OuterStride<> > B( &(lusup.data()[luptr]), nrow, segsize, OuterStride<>(lda) );
Map<Matrix<Scalar,Dynamic,SegSizeAtCompileTime, ColMajor>, 0, OuterStride<> > B( &(lusup.data()[luptr]), nrow, segsize, OuterStride<>(lda) );
Index aligned_offset = internal::first_aligned(tempv.data()+segsize, PacketSize);
Index aligned_with_B_offset = (PacketSize-internal::first_aligned(B.data(), PacketSize))%PacketSize;
Map<Matrix<Scalar,Dynamic,1>, 0, OuterStride<> > l(tempv.data()+segsize+aligned_offset+aligned_with_B_offset, nrow, OuterStride<>(ldl) );

8
uppsrc/plugin/Eigen/Eigen/src/SparseLU/SparseLU_panel_bmod.h
View file

@ -102,7 +102,7 @@ void SparseLUImpl<Scalar,Index>::panel_bmod(const Index m, const Index w, const
if(nsupc >= 2)
{
Index ldu = internal::first_multiple<Index>(u_rows, PacketSize);
Map<Matrix<Scalar,Dynamic,Dynamic>, Aligned, OuterStride<> > U(tempv.data(), u_rows, u_cols, OuterStride<>(ldu));
Map<ScalarMatrix, Aligned, OuterStride<> > U(tempv.data(), u_rows, u_cols, OuterStride<>(ldu));
// gather U
Index u_col = 0;
@ -136,17 +136,17 @@ void SparseLUImpl<Scalar,Index>::panel_bmod(const Index m, const Index w, const
Index lda = glu.xlusup(fsupc+1) - glu.xlusup(fsupc);
no_zeros = (krep - u_rows + 1) - fsupc;
luptr += lda * no_zeros + no_zeros;
Map<Matrix<Scalar,Dynamic,Dynamic>, 0, OuterStride<> > A(glu.lusup.data()+luptr, u_rows, u_rows, OuterStride<>(lda) );
MappedMatrixBlock A(glu.lusup.data()+luptr, u_rows, u_rows, OuterStride<>(lda) );
U = A.template triangularView<UnitLower>().solve(U);
// update
luptr += u_rows;
Map<Matrix<Scalar,Dynamic,Dynamic>, 0, OuterStride<> > B(glu.lusup.data()+luptr, nrow, u_rows, OuterStride<>(lda) );
MappedMatrixBlock B(glu.lusup.data()+luptr, nrow, u_rows, OuterStride<>(lda) );
eigen_assert(tempv.size()>w*ldu + nrow*w + 1);
Index ldl = internal::first_multiple<Index>(nrow, PacketSize);
Index offset = (PacketSize-internal::first_aligned(B.data(), PacketSize)) % PacketSize;
Map<Matrix<Scalar,Dynamic,Dynamic>, 0, OuterStride<> > L(tempv.data()+w*ldu+offset, nrow, u_cols, OuterStride<>(ldl));
MappedMatrixBlock L(tempv.data()+w*ldu+offset, nrow, u_cols, OuterStride<>(ldl));
L.setZero();
internal::sparselu_gemm<Scalar>(L.rows(), L.cols(), B.cols(), B.data(), B.outerStride(), U.data(), U.outerStride(), L.data(), L.outerStride());

7
uppsrc/plugin/Eigen/Eigen/src/SparseLU/SparseLU_pivotL.h
View file

@ -71,7 +71,7 @@ Index SparseLUImpl<Scalar,Index>::pivotL(const Index jcol, const RealScalar& dia
// Determine the largest abs numerical value for partial pivoting
Index diagind = iperm_c(jcol); // diagonal index
RealScalar pivmax = 0.0;
RealScalar pivmax(-1.0);
Index pivptr = nsupc;
Index diag = emptyIdxLU;
RealScalar rtemp;
@ -87,8 +87,9 @@ Index SparseLUImpl<Scalar,Index>::pivotL(const Index jcol, const RealScalar& dia
}
// Test for singularity
if ( pivmax == 0.0 ) {
pivrow = lsub_ptr[pivptr];
if ( pivmax <= RealScalar(0.0) ) {
// if pivmax == -1, the column is structurally empty, otherwise it is only numerically zero
pivrow = pivmax < RealScalar(0.0) ? diagind : lsub_ptr[pivptr];
perm_r(pivrow) = jcol;
return (jcol+1);
}

2
uppsrc/plugin/Eigen/ToStringPlugin.h
View file

@ -1,7 +1,7 @@
#ifndef _Eigen_UppMatrixPlugin_h_
#define _Eigen_UppMatrixPlugin_h_
UPP::String ToString() const{
UPP::String ToString() const {
std::stringstream s;
s << *this;
return s.str();

23
uppsrc/plugin/Eigen/srcdoc.tpp/Eigen$en-us.tpp
View file

File diff suppressed because one or more lines are too long

2
uppsrc/plugin/Eigen/unsupported/Eigen/src/AutoDiff/AutoDiffScalar.h
View file

@ -631,7 +631,7 @@ template<typename DerType> struct NumTraits<AutoDiffScalar<DerType> >
{
typedef AutoDiffScalar<Matrix<typename NumTraits<typename DerType::Scalar>::Real,DerType::RowsAtCompileTime,DerType::ColsAtCompileTime> > Real;
typedef AutoDiffScalar<DerType> NonInteger;
typedef AutoDiffScalar<DerType>& Nested;
typedef AutoDiffScalar<DerType> Nested;
enum{
RequireInitialization = 1
};

1
uppsrc/plugin/Eigen/unsupported/Eigen/src/CMakeLists.txt
View file

@ -1,5 +1,6 @@
ADD_SUBDIRECTORY(AutoDiff)
ADD_SUBDIRECTORY(BVH)
ADD_SUBDIRECTORY(Eigenvalues)
ADD_SUBDIRECTORY(FFT)
ADD_SUBDIRECTORY(IterativeSolvers)
ADD_SUBDIRECTORY(KroneckerProduct)

6
uppsrc/plugin/Eigen/unsupported/Eigen/src/Eigenvalues/CMakeLists.txt Normal file
View file

@ -0,0 +1,6 @@
FILE(GLOB Eigen_Eigenvalues_SRCS "*.h")
INSTALL(FILES
${Eigen_Eigenvalues_SRCS}
DESTINATION ${INCLUDE_INSTALL_DIR}/unsupported/Eigen/src/Eigenvalues COMPONENT Devel
)

4
uppsrc/plugin/Eigen/unsupported/Eigen/src/IterativeSolvers/DGMRES.h
View file

@ -133,8 +133,8 @@ class DGMRES : public IterativeSolverBase<DGMRES<_MatrixType,_Preconditioner> >
* this class becomes invalid. Call compute() to update it with the new
* matrix A, or modify a copy of A.
*/
DGMRES(const MatrixType& A) : Base(A),m_restart(30),m_neig(0),m_r(0),m_maxNeig(5),m_isDeflAllocated(false),m_isDeflInitialized(false)
{}
template<typename MatrixDerived>
explicit DGMRES(const EigenBase<MatrixDerived>& A) : Base(A.derived()), m_restart(30),m_neig(0),m_r(0),m_maxNeig(5),m_isDeflAllocated(false),m_isDeflInitialized(false) {}
~DGMRES() {}

3
uppsrc/plugin/Eigen/unsupported/Eigen/src/IterativeSolvers/GMRES.h
View file

@ -285,7 +285,8 @@ public:
* this class becomes invalid. Call compute() to update it with the new
* matrix A, or modify a copy of A.
*/
GMRES(const MatrixType& A) : Base(A), m_restart(30) {}
template<typename MatrixDerived>
explicit GMRES(const EigenBase<MatrixDerived>& A) : Base(A.derived()), m_restart(30) {}
~GMRES() {}

3
uppsrc/plugin/Eigen/unsupported/Eigen/src/IterativeSolvers/MINRES.h
View file

@ -228,7 +228,8 @@ namespace Eigen {
* this class becomes invalid. Call compute() to update it with the new
* matrix A, or modify a copy of A.
*/
MINRES(const MatrixType& A) : Base(A) {}
template<typename MatrixDerived>
explicit MINRES(const EigenBase<MatrixDerived>& A) : Base(A.derived()) {}
/** Destructor. */
~MINRES(){}