mirror of
https://gitlab.com/libeigen/eigen.git
synced 2025-06-01 02:53:59 +08:00
remove the Triangular suffix to Upper, Lower, UnitLower, etc,
and remove the respective bit flags
This commit is contained in:
Gael Guennebaud
parent
82ec250a0f
commit
c5d7c9f0de
@ -23,10 +23,6 @@
|
||||
// License and a copy of the GNU General Public License along with
|
||||
// Eigen. If not, see <http://www.gnu.org/licenses/>.
|
||||
|
||||
#ifdef EIGEN2_SUPPORT
|
||||
#include "Eigen2Support"
|
||||
#endif
|
||||
|
||||
#ifndef EIGEN_CORE_H
|
||||
#define EIGEN_CORE_H
|
||||
|
||||
@ -225,5 +221,9 @@ struct Dense {};
|
||||
|
||||
#include "src/Core/util/EnableMSVCWarnings.h"
|
||||
|
||||
#ifdef EIGEN2_SUPPORT
|
||||
#include "Eigen2Support"
|
||||
#endif
|
||||
|
||||
#endif // EIGEN_CORE_H
|
||||
/* vim: set filetype=cpp et sw=2 ts=2 ai: */
|
||||
|
||||
@ -25,14 +25,13 @@
|
||||
#ifndef EIGEN2SUPPORT_H
|
||||
#define EIGEN2SUPPORT_H
|
||||
|
||||
#include "src/Core/util/DisableMSVCWarnings.h"
|
||||
#include "Array"
|
||||
|
||||
#ifndef EIGEN2_SUPPORT
|
||||
#define EIGEN2_SUPPORT
|
||||
#if (!defined(EIGEN2_SUPPORT)) || (!defined(EIGEN_CORE_H))
|
||||
#error Eigen2 support must be enabled by defining EIGEN2_SUPPORT before any other Eigen header
|
||||
#endif
|
||||
|
||||
#include "Core"
|
||||
#include "Array"
|
||||
#include "src/Core/util/DisableMSVCWarnings.h"
|
||||
|
||||
namespace Eigen {
|
||||
|
||||
@ -40,8 +39,9 @@ namespace Eigen {
|
||||
* This module provides a couple of deprecated functions improving the compatibility with Eigen2.
|
||||
*
|
||||
* \code
|
||||
* #include <Eigen/Eigen2Support>
|
||||
* #define EIGEN2_SUPPORT
|
||||
* \endcode
|
||||
*
|
||||
*/
|
||||
|
||||
#include "src/Eigen2Support/Flagged.h"
|
||||
|
||||
@ -59,9 +59,7 @@ struct ei_traits<Reverse<MatrixType, Direction> >
|
||||
LinearAccess = ( (Direction==BothDirections) && (int(_MatrixTypeNested::Flags)&PacketAccessBit) )
|
||||
? LinearAccessBit : 0,
|
||||
|
||||
Flags = (int(_MatrixTypeNested::Flags) & (HereditaryBits | PacketAccessBit | LinearAccess))
|
||||
| (int(_MatrixTypeNested::Flags)&UpperTriangularBit ? LowerTriangularBit : 0)
|
||||
| (int(_MatrixTypeNested::Flags)&LowerTriangularBit ? UpperTriangularBit : 0),
|
||||
Flags = (int(_MatrixTypeNested::Flags) & (HereditaryBits | PacketAccessBit | LinearAccess)),
|
||||
|
||||
CoeffReadCost = _MatrixTypeNested::CoeffReadCost
|
||||
};
|
||||
|
||||
@ -80,7 +80,7 @@ template<typename _MatrixType> class LDLT
|
||||
}
|
||||
|
||||
/** \returns the lower triangular matrix L */
|
||||
inline TriangularView<MatrixType, UnitLowerTriangular> matrixL(void) const
|
||||
inline TriangularView<MatrixType, UnitLower> matrixL(void) const
|
||||
{
|
||||
ei_assert(m_isInitialized && "LDLT is not initialized.");
|
||||
return m_matrix;
|
||||
@ -301,13 +301,13 @@ bool LDLT<MatrixType>::solveInPlace(MatrixBase<Derived> &bAndX) const
|
||||
|
||||
// y = L^-1 z
|
||||
//matrixL().solveInPlace(bAndX);
|
||||
m_matrix.template triangularView<UnitLowerTriangular>().solveInPlace(bAndX);
|
||||
m_matrix.template triangularView<UnitLower>().solveInPlace(bAndX);
|
||||
|
||||
// w = D^-1 y
|
||||
bAndX = m_matrix.diagonal().asDiagonal().inverse() * bAndX;
|
||||
|
||||
// u = L^-T w
|
||||
m_matrix.adjoint().template triangularView<UnitUpperTriangular>().solveInPlace(bAndX);
|
||||
m_matrix.adjoint().template triangularView<UnitUpper>().solveInPlace(bAndX);
|
||||
|
||||
// x = P^T u
|
||||
for (int i = size-1; i >= 0; --i) bAndX.row(m_transpositions.coeff(i)).swap(bAndX.row(i));
|
||||
|
||||
@ -148,7 +148,7 @@ template<typename _MatrixType, int _UpLo> class LLT
|
||||
// forward declaration (defined at the end of this file)
|
||||
template<int UpLo> struct ei_llt_inplace;
|
||||
|
||||
template<> struct ei_llt_inplace<LowerTriangular>
|
||||
template<> struct ei_llt_inplace<Lower>
|
||||
{
|
||||
template<typename MatrixType>
|
||||
static bool unblocked(MatrixType& mat)
|
||||
@ -198,47 +198,47 @@ template<> struct ei_llt_inplace<LowerTriangular>
|
||||
Block<MatrixType,Dynamic,Dynamic> A22(m,k+bs,k+bs,rs,rs);
|
||||
|
||||
if(!unblocked(A11)) return false;
|
||||
if(rs>0) A11.adjoint().template triangularView<UpperTriangular>().template solveInPlace<OnTheRight>(A21);
|
||||
if(rs>0) A22.template selfadjointView<LowerTriangular>().rankUpdate(A21,-1); // bottleneck
|
||||
if(rs>0) A11.adjoint().template triangularView<Upper>().template solveInPlace<OnTheRight>(A21);
|
||||
if(rs>0) A22.template selfadjointView<Lower>().rankUpdate(A21,-1); // bottleneck
|
||||
}
|
||||
return true;
|
||||
}
|
||||
};
|
||||
|
||||
template<> struct ei_llt_inplace<UpperTriangular>
|
||||
template<> struct ei_llt_inplace<Upper>
|
||||
{
|
||||
template<typename MatrixType>
|
||||
static EIGEN_STRONG_INLINE bool unblocked(MatrixType& mat)
|
||||
{
|
||||
Transpose<MatrixType> matt(mat);
|
||||
return ei_llt_inplace<LowerTriangular>::unblocked(matt);
|
||||
return ei_llt_inplace<Lower>::unblocked(matt);
|
||||
}
|
||||
template<typename MatrixType>
|
||||
static EIGEN_STRONG_INLINE bool blocked(MatrixType& mat)
|
||||
{
|
||||
Transpose<MatrixType> matt(mat);
|
||||
return ei_llt_inplace<LowerTriangular>::blocked(matt);
|
||||
return ei_llt_inplace<Lower>::blocked(matt);
|
||||
}
|
||||
};
|
||||
|
||||
template<typename MatrixType> struct LLT_Traits<MatrixType,LowerTriangular>
|
||||
template<typename MatrixType> struct LLT_Traits<MatrixType,Lower>
|
||||
{
|
||||
typedef TriangularView<MatrixType, LowerTriangular> MatrixL;
|
||||
typedef TriangularView<typename MatrixType::AdjointReturnType, UpperTriangular> MatrixU;
|
||||
typedef TriangularView<MatrixType, Lower> MatrixL;
|
||||
typedef TriangularView<typename MatrixType::AdjointReturnType, Upper> MatrixU;
|
||||
inline static MatrixL getL(const MatrixType& m) { return m; }
|
||||
inline static MatrixU getU(const MatrixType& m) { return m.adjoint(); }
|
||||
static bool inplace_decomposition(MatrixType& m)
|
||||
{ return ei_llt_inplace<LowerTriangular>::blocked(m); }
|
||||
{ return ei_llt_inplace<Lower>::blocked(m); }
|
||||
};
|
||||
|
||||
template<typename MatrixType> struct LLT_Traits<MatrixType,UpperTriangular>
|
||||
template<typename MatrixType> struct LLT_Traits<MatrixType,Upper>
|
||||
{
|
||||
typedef TriangularView<typename MatrixType::AdjointReturnType, LowerTriangular> MatrixL;
|
||||
typedef TriangularView<MatrixType, UpperTriangular> MatrixU;
|
||||
typedef TriangularView<typename MatrixType::AdjointReturnType, Lower> MatrixL;
|
||||
typedef TriangularView<MatrixType, Upper> MatrixU;
|
||||
inline static MatrixL getL(const MatrixType& m) { return m.adjoint(); }
|
||||
inline static MatrixU getU(const MatrixType& m) { return m; }
|
||||
static bool inplace_decomposition(MatrixType& m)
|
||||
{ return ei_llt_inplace<UpperTriangular>::blocked(m); }
|
||||
{ return ei_llt_inplace<Upper>::blocked(m); }
|
||||
};
|
||||
|
||||
/** Computes / recomputes the Cholesky decomposition A = LL^* = U^*U of \a matrix
|
||||
|
||||
@ -405,13 +405,6 @@ template<typename Derived> class MatrixBase
|
||||
template<int Size> const VectorBlock<Derived,Size> start() const;
|
||||
template<int Size> VectorBlock<Derived,Size> end();
|
||||
template<int Size> const VectorBlock<Derived,Size> end() const;
|
||||
|
||||
template<typename OtherDerived>
|
||||
typename ei_plain_matrix_type_column_major<OtherDerived>::type
|
||||
solveTriangular(const MatrixBase<OtherDerived>& other) const;
|
||||
|
||||
template<typename OtherDerived>
|
||||
void solveTriangularInPlace(const MatrixBase<OtherDerived>& other) const;
|
||||
#endif
|
||||
|
||||
protected:
|
||||
|
||||
@ -31,7 +31,7 @@
|
||||
* \brief Expression of a selfadjoint matrix from a triangular part of a dense matrix
|
||||
*
|
||||
* \param MatrixType the type of the dense matrix storing the coefficients
|
||||
* \param TriangularPart can be either \c LowerTriangular or \c UpperTriangular
|
||||
* \param TriangularPart can be either \c Lower or \c Upper
|
||||
*
|
||||
* This class is an expression of a sefladjoint matrix from a triangular part of a matrix
|
||||
* with given dense storage of the coefficients. It is the return type of MatrixBase::selfadjointView()
|
||||
@ -46,7 +46,7 @@ struct ei_traits<SelfAdjointView<MatrixType, TriangularPart> > : ei_traits<Matri
|
||||
typedef typename ei_unref<MatrixTypeNested>::type _MatrixTypeNested;
|
||||
typedef MatrixType ExpressionType;
|
||||
enum {
|
||||
Mode = TriangularPart | SelfAdjointBit,
|
||||
Mode = TriangularPart | SelfAdjoint,
|
||||
Flags = _MatrixTypeNested::Flags & (HereditaryBits)
|
||||
& (~(PacketAccessBit | DirectAccessBit | LinearAccessBit)), // FIXME these flags should be preserved
|
||||
CoeffReadCost = _MatrixTypeNested::CoeffReadCost
|
||||
|
||||
@ -57,7 +57,7 @@ struct ei_triangular_solver_selector<Lhs,Rhs,OnTheLeft,Mode,NoUnrolling,RowMajor
|
||||
typedef ei_blas_traits<Lhs> LhsProductTraits;
|
||||
typedef typename LhsProductTraits::ExtractType ActualLhsType;
|
||||
enum {
|
||||
IsLowerTriangular = ((Mode&LowerTriangularBit)==LowerTriangularBit)
|
||||
IsLower = ((Mode&Lower)==Lower)
|
||||
};
|
||||
static void run(const Lhs& lhs, Rhs& other)
|
||||
{
|
||||
@ -65,20 +65,20 @@ struct ei_triangular_solver_selector<Lhs,Rhs,OnTheLeft,Mode,NoUnrolling,RowMajor
|
||||
ActualLhsType actualLhs = LhsProductTraits::extract(lhs);
|
||||
|
||||
const int size = lhs.cols();
|
||||
for(int pi=IsLowerTriangular ? 0 : size;
|
||||
IsLowerTriangular ? pi<size : pi>0;
|
||||
IsLowerTriangular ? pi+=PanelWidth : pi-=PanelWidth)
|
||||
for(int pi=IsLower ? 0 : size;
|
||||
IsLower ? pi<size : pi>0;
|
||||
IsLower ? pi+=PanelWidth : pi-=PanelWidth)
|
||||
{
|
||||
int actualPanelWidth = std::min(IsLowerTriangular ? size - pi : pi, PanelWidth);
|
||||
int actualPanelWidth = std::min(IsLower ? size - pi : pi, PanelWidth);
|
||||
|
||||
int r = IsLowerTriangular ? pi : size - pi; // remaining size
|
||||
int r = IsLower ? pi : size - pi; // remaining size
|
||||
if (r > 0)
|
||||
{
|
||||
// let's directly call the low level product function because:
|
||||
// 1 - it is faster to compile
|
||||
// 2 - it is slighlty faster at runtime
|
||||
int startRow = IsLowerTriangular ? pi : pi-actualPanelWidth;
|
||||
int startCol = IsLowerTriangular ? 0 : pi;
|
||||
int startRow = IsLower ? pi : pi-actualPanelWidth;
|
||||
int startCol = IsLower ? 0 : pi;
|
||||
VectorBlock<Rhs,Dynamic> target(other,startRow,actualPanelWidth);
|
||||
|
||||
ei_cache_friendly_product_rowmajor_times_vector<LhsProductTraits::NeedToConjugate,false>(
|
||||
@ -89,12 +89,12 @@ struct ei_triangular_solver_selector<Lhs,Rhs,OnTheLeft,Mode,NoUnrolling,RowMajor
|
||||
|
||||
for(int k=0; k<actualPanelWidth; ++k)
|
||||
{
|
||||
int i = IsLowerTriangular ? pi+k : pi-k-1;
|
||||
int s = IsLowerTriangular ? pi : i+1;
|
||||
int i = IsLower ? pi+k : pi-k-1;
|
||||
int s = IsLower ? pi : i+1;
|
||||
if (k>0)
|
||||
other.coeffRef(i) -= (lhs.row(i).segment(s,k).transpose().cwiseProduct(other.segment(s,k))).sum();
|
||||
|
||||
if(!(Mode & UnitDiagBit))
|
||||
if(!(Mode & UnitDiag))
|
||||
other.coeffRef(i) /= lhs.coeff(i,i);
|
||||
}
|
||||
}
|
||||
@ -111,7 +111,7 @@ struct ei_triangular_solver_selector<Lhs,Rhs,OnTheLeft,Mode,NoUnrolling,ColMajor
|
||||
typedef typename LhsProductTraits::ExtractType ActualLhsType;
|
||||
enum {
|
||||
PacketSize = ei_packet_traits<Scalar>::size,
|
||||
IsLowerTriangular = ((Mode&LowerTriangularBit)==LowerTriangularBit)
|
||||
IsLower = ((Mode&Lower)==Lower)
|
||||
};
|
||||
|
||||
static void run(const Lhs& lhs, Rhs& other)
|
||||
@ -120,26 +120,26 @@ struct ei_triangular_solver_selector<Lhs,Rhs,OnTheLeft,Mode,NoUnrolling,ColMajor
|
||||
ActualLhsType actualLhs = LhsProductTraits::extract(lhs);
|
||||
|
||||
const int size = lhs.cols();
|
||||
for(int pi=IsLowerTriangular ? 0 : size;
|
||||
IsLowerTriangular ? pi<size : pi>0;
|
||||
IsLowerTriangular ? pi+=PanelWidth : pi-=PanelWidth)
|
||||
for(int pi=IsLower ? 0 : size;
|
||||
IsLower ? pi<size : pi>0;
|
||||
IsLower ? pi+=PanelWidth : pi-=PanelWidth)
|
||||
{
|
||||
int actualPanelWidth = std::min(IsLowerTriangular ? size - pi : pi, PanelWidth);
|
||||
int startBlock = IsLowerTriangular ? pi : pi-actualPanelWidth;
|
||||
int endBlock = IsLowerTriangular ? pi + actualPanelWidth : 0;
|
||||
int actualPanelWidth = std::min(IsLower ? size - pi : pi, PanelWidth);
|
||||
int startBlock = IsLower ? pi : pi-actualPanelWidth;
|
||||
int endBlock = IsLower ? pi + actualPanelWidth : 0;
|
||||
|
||||
for(int k=0; k<actualPanelWidth; ++k)
|
||||
{
|
||||
int i = IsLowerTriangular ? pi+k : pi-k-1;
|
||||
if(!(Mode & UnitDiagBit))
|
||||
int i = IsLower ? pi+k : pi-k-1;
|
||||
if(!(Mode & UnitDiag))
|
||||
other.coeffRef(i) /= lhs.coeff(i,i);
|
||||
|
||||
int r = actualPanelWidth - k - 1; // remaining size
|
||||
int s = IsLowerTriangular ? i+1 : i-r;
|
||||
int s = IsLower ? i+1 : i-r;
|
||||
if (r>0)
|
||||
other.segment(s,r) -= other.coeffRef(i) * Block<Lhs,Dynamic,1>(lhs, s, i, r, 1);
|
||||
}
|
||||
int r = IsLowerTriangular ? size - endBlock : startBlock; // remaining size
|
||||
int r = IsLower ? size - endBlock : startBlock; // remaining size
|
||||
if (r > 0)
|
||||
{
|
||||
// let's directly call the low level product function because:
|
||||
@ -198,16 +198,16 @@ struct ei_triangular_solver_unroller;
|
||||
template<typename Lhs, typename Rhs, int Mode, int Index, int Size>
|
||||
struct ei_triangular_solver_unroller<Lhs,Rhs,Mode,Index,Size,false> {
|
||||
enum {
|
||||
IsLowerTriangular = ((Mode&LowerTriangularBit)==LowerTriangularBit),
|
||||
I = IsLowerTriangular ? Index : Size - Index - 1,
|
||||
S = IsLowerTriangular ? 0 : I+1
|
||||
IsLower = ((Mode&Lower)==Lower),
|
||||
I = IsLower ? Index : Size - Index - 1,
|
||||
S = IsLower ? 0 : I+1
|
||||
};
|
||||
static void run(const Lhs& lhs, Rhs& rhs)
|
||||
{
|
||||
if (Index>0)
|
||||
rhs.coeffRef(I) -= ((lhs.row(I).template segment<Index>(S).transpose()).cwiseProduct(rhs.template segment<Index>(S))).sum();
|
||||
|
||||
if(!(Mode & UnitDiagBit))
|
||||
if(!(Mode & UnitDiag))
|
||||
rhs.coeffRef(I) /= lhs.coeff(I,I);
|
||||
|
||||
ei_triangular_solver_unroller<Lhs,Rhs,Mode,Index+1,Size>::run(lhs,rhs);
|
||||
@ -245,8 +245,8 @@ void TriangularView<MatrixType,Mode>::solveInPlace(const MatrixBase<OtherDerived
|
||||
OtherDerived& other = _other.const_cast_derived();
|
||||
ei_assert(cols() == rows());
|
||||
ei_assert( (Side==OnTheLeft && cols() == other.rows()) || (Side==OnTheRight && cols() == other.cols()) );
|
||||
ei_assert(!(Mode & ZeroDiagBit));
|
||||
ei_assert(Mode & (UpperTriangularBit|LowerTriangularBit));
|
||||
ei_assert(!(Mode & ZeroDiag));
|
||||
ei_assert(Mode & (Upper|Lower));
|
||||
|
||||
enum { copy = ei_traits<OtherDerived>::Flags & RowMajorBit && OtherDerived::IsVectorAtCompileTime };
|
||||
typedef typename ei_meta_if<copy,
|
||||
|
||||
@ -49,10 +49,7 @@ struct ei_traits<Transpose<MatrixType> > : ei_traits<MatrixType>
|
||||
ColsAtCompileTime = MatrixType::RowsAtCompileTime,
|
||||
MaxRowsAtCompileTime = MatrixType::MaxColsAtCompileTime,
|
||||
MaxColsAtCompileTime = MatrixType::MaxRowsAtCompileTime,
|
||||
Flags = ((int(_MatrixTypeNested::Flags) ^ RowMajorBit)
|
||||
& ~(LowerTriangularBit | UpperTriangularBit))
|
||||
| (int(_MatrixTypeNested::Flags)&UpperTriangularBit ? LowerTriangularBit : 0)
|
||||
| (int(_MatrixTypeNested::Flags)&LowerTriangularBit ? UpperTriangularBit : 0),
|
||||
Flags = (int(_MatrixTypeNested::Flags) ^ RowMajorBit),
|
||||
CoeffReadCost = _MatrixTypeNested::CoeffReadCost
|
||||
};
|
||||
};
|
||||
@ -229,7 +226,7 @@ struct ei_inplace_transpose_selector;
|
||||
template<typename MatrixType>
|
||||
struct ei_inplace_transpose_selector<MatrixType,true> { // square matrix
|
||||
static void run(MatrixType& m) {
|
||||
m.template triangularView<StrictlyUpperTriangular>().swap(m.transpose());
|
||||
m.template triangularView<StrictlyUpper>().swap(m.transpose());
|
||||
}
|
||||
};
|
||||
|
||||
@ -237,7 +234,7 @@ template<typename MatrixType>
|
||||
struct ei_inplace_transpose_selector<MatrixType,false> { // non square matrix
|
||||
static void run(MatrixType& m) {
|
||||
if (m.rows()==m.cols())
|
||||
m.template triangularView<StrictlyUpperTriangular>().swap(m.transpose());
|
||||
m.template triangularView<StrictlyUpper>().swap(m.transpose());
|
||||
else
|
||||
m = m.transpose().eval();
|
||||
}
|
||||
|
||||
@ -46,7 +46,7 @@ template<typename Derived> class TriangularBase : public AnyMatrixBase<Derived>
|
||||
};
|
||||
typedef typename ei_traits<Derived>::Scalar Scalar;
|
||||
|
||||
inline TriangularBase() { ei_assert(ei_are_flags_consistent<Mode>::ret); }
|
||||
inline TriangularBase() { ei_assert(!((Mode&UnitDiag) && (Mode&ZeroDiag))); }
|
||||
|
||||
inline int rows() const { return derived().rows(); }
|
||||
inline int cols() const { return derived().cols(); }
|
||||
@ -89,10 +89,10 @@ template<typename Derived> class TriangularBase : public AnyMatrixBase<Derived>
|
||||
void check_coordinates(int row, int col)
|
||||
{
|
||||
ei_assert(col>=0 && col<cols() && row>=0 && row<rows());
|
||||
ei_assert( (Mode==UpperTriangular && col>=row)
|
||||
|| (Mode==LowerTriangular && col<=row)
|
||||
|| ((Mode==StrictlyUpperTriangular || Mode==UnitUpperTriangular) && col>row)
|
||||
|| ((Mode==StrictlyLowerTriangular || Mode==UnitLowerTriangular) && col<row));
|
||||
ei_assert( (Mode==Upper && col>=row)
|
||||
|| (Mode==Lower && col<=row)
|
||||
|| ((Mode==StrictlyUpper || Mode==UnitUpper) && col>row)
|
||||
|| ((Mode==StrictlyLower || Mode==UnitLower) && col<row));
|
||||
}
|
||||
|
||||
#ifdef EIGEN_INTERNAL_DEBUGGING
|
||||
@ -111,10 +111,10 @@ template<typename Derived> class TriangularBase : public AnyMatrixBase<Derived>
|
||||
* \brief Base class for triangular part in a matrix
|
||||
*
|
||||
* \param MatrixType the type of the object in which we are taking the triangular part
|
||||
* \param Mode the kind of triangular matrix expression to construct. Can be UpperTriangular,
|
||||
* LowerTriangular, UpperSelfadjoint, or LowerSelfadjoint. This is in fact a bit field;
|
||||
* it must have either UpperBit or LowerBit, and additionnaly it may have either
|
||||
* TraingularBit or SelfadjointBit.
|
||||
* \param Mode the kind of triangular matrix expression to construct. Can be Upper,
|
||||
* Lower, UpperSelfadjoint, or LowerSelfadjoint. This is in fact a bit field;
|
||||
* it must have either Upper or Lower, and additionnaly it may have either
|
||||
* UnitDiag or Selfadjoint.
|
||||
*
|
||||
* This class represents a triangular part of a matrix, not necessarily square. Strictly speaking, for rectangular
|
||||
* matrices one should speak ok "trapezoid" parts. This class is the return type
|
||||
@ -154,9 +154,10 @@ template<typename _MatrixType, unsigned int _Mode> class TriangularView
|
||||
|
||||
enum {
|
||||
Mode = _Mode,
|
||||
TransposeMode = (Mode & UpperTriangularBit ? LowerTriangularBit : 0)
|
||||
| (Mode & LowerTriangularBit ? UpperTriangularBit : 0)
|
||||
| (Mode & (ZeroDiagBit | UnitDiagBit))
|
||||
TransposeMode = (Mode & Upper ? Lower : 0)
|
||||
| (Mode & Lower ? Upper : 0)
|
||||
| (Mode & (UnitDiag))
|
||||
| (Mode & (ZeroDiag))
|
||||
};
|
||||
|
||||
inline TriangularView(const MatrixType& matrix) : m_matrix(matrix)
|
||||
@ -283,12 +284,12 @@ template<typename _MatrixType, unsigned int _Mode> class TriangularView
|
||||
|
||||
const SelfAdjointView<_MatrixTypeNested,Mode> selfadjointView() const
|
||||
{
|
||||
EIGEN_STATIC_ASSERT((Mode&UnitDiagBit)==0,PROGRAMMING_ERROR);
|
||||
EIGEN_STATIC_ASSERT((Mode&UnitDiag)==0,PROGRAMMING_ERROR);
|
||||
return SelfAdjointView<_MatrixTypeNested,Mode>(m_matrix);
|
||||
}
|
||||
SelfAdjointView<_MatrixTypeNested,Mode> selfadjointView()
|
||||
{
|
||||
EIGEN_STATIC_ASSERT((Mode&UnitDiagBit)==0,PROGRAMMING_ERROR);
|
||||
EIGEN_STATIC_ASSERT((Mode&UnitDiag)==0,PROGRAMMING_ERROR);
|
||||
return SelfAdjointView<_MatrixTypeNested,Mode>(m_matrix);
|
||||
}
|
||||
|
||||
@ -304,6 +305,16 @@ template<typename _MatrixType, unsigned int _Mode> class TriangularView
|
||||
TriangularView<SwapWrapper<MatrixType>,Mode>(const_cast<MatrixType&>(m_matrix)).lazyAssign(other.derived());
|
||||
}
|
||||
|
||||
Scalar determinant() const
|
||||
{
|
||||
if (Mode & UnitDiag)
|
||||
return 1;
|
||||
else if (Mode & ZeroDiag)
|
||||
return 0;
|
||||
else
|
||||
return m_matrix.diagonal().prod();
|
||||
}
|
||||
|
||||
protected:
|
||||
|
||||
const MatrixTypeNested m_matrix;
|
||||
@ -325,19 +336,19 @@ struct ei_triangular_assignment_selector
|
||||
{
|
||||
ei_triangular_assignment_selector<Derived1, Derived2, Mode, UnrollCount-1, ClearOpposite>::run(dst, src);
|
||||
|
||||
ei_assert( Mode == UpperTriangular || Mode == LowerTriangular
|
||||
|| Mode == StrictlyUpperTriangular || Mode == StrictlyLowerTriangular
|
||||
|| Mode == UnitUpperTriangular || Mode == UnitLowerTriangular);
|
||||
if((Mode == UpperTriangular && row <= col)
|
||||
|| (Mode == LowerTriangular && row >= col)
|
||||
|| (Mode == StrictlyUpperTriangular && row < col)
|
||||
|| (Mode == StrictlyLowerTriangular && row > col)
|
||||
|| (Mode == UnitUpperTriangular && row < col)
|
||||
|| (Mode == UnitLowerTriangular && row > col))
|
||||
ei_assert( Mode == Upper || Mode == Lower
|
||||
|| Mode == StrictlyUpper || Mode == StrictlyLower
|
||||
|| Mode == UnitUpper || Mode == UnitLower);
|
||||
if((Mode == Upper && row <= col)
|
||||
|| (Mode == Lower && row >= col)
|
||||
|| (Mode == StrictlyUpper && row < col)
|
||||
|| (Mode == StrictlyLower && row > col)
|
||||
|| (Mode == UnitUpper && row < col)
|
||||
|| (Mode == UnitLower && row > col))
|
||||
dst.copyCoeff(row, col, src);
|
||||
else if(ClearOpposite)
|
||||
{
|
||||
if (Mode&UnitDiagBit && row==col)
|
||||
if (Mode&UnitDiag && row==col)
|
||||
dst.coeffRef(row, col) = 1;
|
||||
else
|
||||
dst.coeffRef(row, col) = 0;
|
||||
@ -353,7 +364,7 @@ struct ei_triangular_assignment_selector<Derived1, Derived2, Mode, 0, ClearOppos
|
||||
};
|
||||
|
||||
template<typename Derived1, typename Derived2, bool ClearOpposite>
|
||||
struct ei_triangular_assignment_selector<Derived1, Derived2, UpperTriangular, Dynamic, ClearOpposite>
|
||||
struct ei_triangular_assignment_selector<Derived1, Derived2, Upper, Dynamic, ClearOpposite>
|
||||
{
|
||||
inline static void run(Derived1 &dst, const Derived2 &src)
|
||||
{
|
||||
@ -370,7 +381,7 @@ struct ei_triangular_assignment_selector<Derived1, Derived2, UpperTriangular, Dy
|
||||
};
|
||||
|
||||
template<typename Derived1, typename Derived2, bool ClearOpposite>
|
||||
struct ei_triangular_assignment_selector<Derived1, Derived2, LowerTriangular, Dynamic, ClearOpposite>
|
||||
struct ei_triangular_assignment_selector<Derived1, Derived2, Lower, Dynamic, ClearOpposite>
|
||||
{
|
||||
inline static void run(Derived1 &dst, const Derived2 &src)
|
||||
{
|
||||
@ -387,7 +398,7 @@ struct ei_triangular_assignment_selector<Derived1, Derived2, LowerTriangular, Dy
|
||||
};
|
||||
|
||||
template<typename Derived1, typename Derived2, bool ClearOpposite>
|
||||
struct ei_triangular_assignment_selector<Derived1, Derived2, StrictlyUpperTriangular, Dynamic, ClearOpposite>
|
||||
struct ei_triangular_assignment_selector<Derived1, Derived2, StrictlyUpper, Dynamic, ClearOpposite>
|
||||
{
|
||||
inline static void run(Derived1 &dst, const Derived2 &src)
|
||||
{
|
||||
@ -404,7 +415,7 @@ struct ei_triangular_assignment_selector<Derived1, Derived2, StrictlyUpperTriang
|
||||
};
|
||||
|
||||
template<typename Derived1, typename Derived2, bool ClearOpposite>
|
||||
struct ei_triangular_assignment_selector<Derived1, Derived2, StrictlyLowerTriangular, Dynamic, ClearOpposite>
|
||||
struct ei_triangular_assignment_selector<Derived1, Derived2, StrictlyLower, Dynamic, ClearOpposite>
|
||||
{
|
||||
inline static void run(Derived1 &dst, const Derived2 &src)
|
||||
{
|
||||
@ -421,7 +432,7 @@ struct ei_triangular_assignment_selector<Derived1, Derived2, StrictlyLowerTriang
|
||||
};
|
||||
|
||||
template<typename Derived1, typename Derived2, bool ClearOpposite>
|
||||
struct ei_triangular_assignment_selector<Derived1, Derived2, UnitUpperTriangular, Dynamic, ClearOpposite>
|
||||
struct ei_triangular_assignment_selector<Derived1, Derived2, UnitUpper, Dynamic, ClearOpposite>
|
||||
{
|
||||
inline static void run(Derived1 &dst, const Derived2 &src)
|
||||
{
|
||||
@ -440,7 +451,7 @@ struct ei_triangular_assignment_selector<Derived1, Derived2, UnitUpperTriangular
|
||||
}
|
||||
};
|
||||
template<typename Derived1, typename Derived2, bool ClearOpposite>
|
||||
struct ei_triangular_assignment_selector<Derived1, Derived2, UnitLowerTriangular, Dynamic, ClearOpposite>
|
||||
struct ei_triangular_assignment_selector<Derived1, Derived2, UnitLower, Dynamic, ClearOpposite>
|
||||
{
|
||||
inline static void run(Derived1 &dst, const Derived2 &src)
|
||||
{
|
||||
@ -590,8 +601,8 @@ EIGEN_DEPRECATED TriangularView<Derived, Mode> MatrixBase<Derived>::part()
|
||||
/** \nonstableyet
|
||||
* \returns an expression of a triangular view extracted from the current matrix
|
||||
*
|
||||
* The parameter \a Mode can have the following values: \c UpperTriangular, \c StrictlyUpperTriangular, \c UnitUpperTriangular,
|
||||
* \c LowerTriangular, \c StrictlyLowerTriangular, \c UnitLowerTriangular.
|
||||
* The parameter \a Mode can have the following values: \c Upper, \c StrictlyUpper, \c UnitUpper,
|
||||
* \c Lower, \c StrictlyLower, \c UnitLower.
|
||||
*
|
||||
* Example: \include MatrixBase_extract.cpp
|
||||
* Output: \verbinclude MatrixBase_extract.out
|
||||
@ -616,22 +627,22 @@ const TriangularView<Derived, Mode> MatrixBase<Derived>::triangularView() const
|
||||
/** \returns true if *this is approximately equal to an upper triangular matrix,
|
||||
* within the precision given by \a prec.
|
||||
*
|
||||
* \sa isLowerTriangular(), extract(), part(), marked()
|
||||
* \sa isLower(), extract(), part(), marked()
|
||||
*/
|
||||
template<typename Derived>
|
||||
bool MatrixBase<Derived>::isUpperTriangular(RealScalar prec) const
|
||||
{
|
||||
RealScalar maxAbsOnUpperTriangularPart = static_cast<RealScalar>(-1);
|
||||
RealScalar maxAbsOnUpperPart = static_cast<RealScalar>(-1);
|
||||
for(int j = 0; j < cols(); ++j)
|
||||
{
|
||||
int maxi = std::min(j, rows()-1);
|
||||
for(int i = 0; i <= maxi; ++i)
|
||||
{
|
||||
RealScalar absValue = ei_abs(coeff(i,j));
|
||||
if(absValue > maxAbsOnUpperTriangularPart) maxAbsOnUpperTriangularPart = absValue;
|
||||
if(absValue > maxAbsOnUpperPart) maxAbsOnUpperPart = absValue;
|
||||
}
|
||||
}
|
||||
RealScalar threshold = maxAbsOnUpperTriangularPart * prec;
|
||||
RealScalar threshold = maxAbsOnUpperPart * prec;
|
||||
for(int j = 0; j < cols(); ++j)
|
||||
for(int i = j+1; i < rows(); ++i)
|
||||
if(ei_abs(coeff(i, j)) > threshold) return false;
|
||||
@ -641,19 +652,19 @@ bool MatrixBase<Derived>::isUpperTriangular(RealScalar prec) const
|
||||
/** \returns true if *this is approximately equal to a lower triangular matrix,
|
||||
* within the precision given by \a prec.
|
||||
*
|
||||
* \sa isUpperTriangular(), extract(), part(), marked()
|
||||
* \sa isUpper(), extract(), part(), marked()
|
||||
*/
|
||||
template<typename Derived>
|
||||
bool MatrixBase<Derived>::isLowerTriangular(RealScalar prec) const
|
||||
{
|
||||
RealScalar maxAbsOnLowerTriangularPart = static_cast<RealScalar>(-1);
|
||||
RealScalar maxAbsOnLowerPart = static_cast<RealScalar>(-1);
|
||||
for(int j = 0; j < cols(); ++j)
|
||||
for(int i = j; i < rows(); ++i)
|
||||
{
|
||||
RealScalar absValue = ei_abs(coeff(i,j));
|
||||
if(absValue > maxAbsOnLowerTriangularPart) maxAbsOnLowerTriangularPart = absValue;
|
||||
if(absValue > maxAbsOnLowerPart) maxAbsOnLowerPart = absValue;
|
||||
}
|
||||
RealScalar threshold = maxAbsOnLowerTriangularPart * prec;
|
||||
RealScalar threshold = maxAbsOnLowerPart * prec;
|
||||
for(int j = 1; j < cols(); ++j)
|
||||
{
|
||||
int maxi = std::min(j, rows()-1);
|
||||
|
||||
@ -368,10 +368,10 @@ struct SelfadjointProductMatrix<Lhs,LhsMode,false,Rhs,RhsMode,false>
|
||||
SelfadjointProductMatrix(const Lhs& lhs, const Rhs& rhs) : Base(lhs,rhs) {}
|
||||
|
||||
enum {
|
||||
LhsUpLo = LhsMode&(UpperTriangularBit|LowerTriangularBit),
|
||||
LhsIsSelfAdjoint = (LhsMode&SelfAdjointBit)==SelfAdjointBit,
|
||||
RhsUpLo = RhsMode&(UpperTriangularBit|LowerTriangularBit),
|
||||
RhsIsSelfAdjoint = (RhsMode&SelfAdjointBit)==SelfAdjointBit
|
||||
LhsUpLo = LhsMode&(Upper|Lower),
|
||||
LhsIsSelfAdjoint = (LhsMode&SelfAdjoint)==SelfAdjoint,
|
||||
RhsUpLo = RhsMode&(Upper|Lower),
|
||||
RhsIsSelfAdjoint = (RhsMode&SelfAdjoint)==SelfAdjoint
|
||||
};
|
||||
|
||||
template<typename Dest> void scaleAndAddTo(Dest& dst, Scalar alpha) const
|
||||
@ -385,12 +385,12 @@ struct SelfadjointProductMatrix<Lhs,LhsMode,false,Rhs,RhsMode,false>
|
||||
* RhsBlasTraits::extractScalarFactor(m_rhs);
|
||||
|
||||
ei_product_selfadjoint_matrix<Scalar,
|
||||
EIGEN_LOGICAL_XOR(LhsUpLo==UpperTriangular,
|
||||
EIGEN_LOGICAL_XOR(LhsUpLo==Upper,
|
||||
ei_traits<Lhs>::Flags &RowMajorBit) ? RowMajor : ColMajor, LhsIsSelfAdjoint,
|
||||
NumTraits<Scalar>::IsComplex && EIGEN_LOGICAL_XOR(LhsUpLo==UpperTriangular,bool(LhsBlasTraits::NeedToConjugate)),
|
||||
EIGEN_LOGICAL_XOR(RhsUpLo==UpperTriangular,
|
||||
NumTraits<Scalar>::IsComplex && EIGEN_LOGICAL_XOR(LhsUpLo==Upper,bool(LhsBlasTraits::NeedToConjugate)),
|
||||
EIGEN_LOGICAL_XOR(RhsUpLo==Upper,
|
||||
ei_traits<Rhs>::Flags &RowMajorBit) ? RowMajor : ColMajor, RhsIsSelfAdjoint,
|
||||
NumTraits<Scalar>::IsComplex && EIGEN_LOGICAL_XOR(RhsUpLo==UpperTriangular,bool(RhsBlasTraits::NeedToConjugate)),
|
||||
NumTraits<Scalar>::IsComplex && EIGEN_LOGICAL_XOR(RhsUpLo==Upper,bool(RhsBlasTraits::NeedToConjugate)),
|
||||
ei_traits<Dest>::Flags&RowMajorBit ? RowMajor : ColMajor>
|
||||
::run(
|
||||
lhs.rows(), rhs.cols(), // sizes
|
||||
|
||||
@ -42,7 +42,7 @@ static EIGEN_DONT_INLINE void ei_product_selfadjoint_vector(
|
||||
|
||||
enum {
|
||||
IsRowMajor = StorageOrder==RowMajor ? 1 : 0,
|
||||
IsLower = UpLo == LowerTriangularBit ? 1 : 0,
|
||||
IsLower = UpLo == Lower ? 1 : 0,
|
||||
FirstTriangular = IsRowMajor == IsLower
|
||||
};
|
||||
|
||||
@ -170,7 +170,7 @@ struct SelfadjointProductMatrix<Lhs,LhsMode,false,Rhs,0,true>
|
||||
EIGEN_PRODUCT_PUBLIC_INTERFACE(SelfadjointProductMatrix)
|
||||
|
||||
enum {
|
||||
LhsUpLo = LhsMode&(UpperTriangularBit|LowerTriangularBit)
|
||||
LhsUpLo = LhsMode&(Upper|Lower)
|
||||
};
|
||||
|
||||
SelfadjointProductMatrix(const Lhs& lhs, const Rhs& rhs) : Base(lhs,rhs) {}
|
||||
|
||||
@ -47,7 +47,7 @@ struct ei_selfadjoint_product<Scalar,MatStorageOrder, RowMajor, AAT, UpLo>
|
||||
{
|
||||
static EIGEN_STRONG_INLINE void run(int size, int depth, const Scalar* mat, int matStride, Scalar* res, int resStride, Scalar alpha)
|
||||
{
|
||||
ei_selfadjoint_product<Scalar, MatStorageOrder, ColMajor, !AAT, UpLo==LowerTriangular?UpperTriangular:LowerTriangular>
|
||||
ei_selfadjoint_product<Scalar, MatStorageOrder, ColMajor, !AAT, UpLo==Lower?Upper:Lower>
|
||||
::run(size, depth, mat, matStride, res, resStride, alpha);
|
||||
}
|
||||
};
|
||||
@ -100,13 +100,13 @@ struct ei_selfadjoint_product<Scalar,MatStorageOrder, ColMajor, AAT, UpLo>
|
||||
// 1 - before the diagonal => processed with gebp or skipped
|
||||
// 2 - the actual_mc x actual_mc symmetric block => processed with a special kernel
|
||||
// 3 - after the diagonal => processed with gebp or skipped
|
||||
if (UpLo==LowerTriangular)
|
||||
if (UpLo==Lower)
|
||||
gebp_kernel(res+i2, resStride, blockA, blockB, actual_mc, actual_kc, std::min(size,i2));
|
||||
|
||||
ei_sybb_kernel<Scalar, Blocking::mr, Blocking::nr, Conj, UpLo>()
|
||||
(res+resStride*i2 + i2, resStride, blockA, blockB + actual_kc*Blocking::PacketSize*i2, actual_mc, actual_kc);
|
||||
|
||||
if (UpLo==UpperTriangular)
|
||||
if (UpLo==Upper)
|
||||
{
|
||||
int j2 = i2+actual_mc;
|
||||
gebp_kernel(res+resStride*j2+i2, resStride, blockA, blockB+actual_kc*Blocking::PacketSize*j2, actual_mc, actual_kc, std::max(0,size-j2));
|
||||
@ -173,7 +173,7 @@ struct ei_sybb_kernel
|
||||
int actualBlockSize = std::min<int>(BlockSize,size - j);
|
||||
const Scalar* actual_b = blockB+j*depth*PacketSize;
|
||||
|
||||
if(UpLo==UpperTriangular)
|
||||
if(UpLo==Upper)
|
||||
gebp_kernel(res+j*resStride, resStride, blockA, actual_b, j, depth, actualBlockSize);
|
||||
|
||||
// selfadjoint micro block
|
||||
@ -186,13 +186,13 @@ struct ei_sybb_kernel
|
||||
for(int j1=0; j1<actualBlockSize; ++j1)
|
||||
{
|
||||
Scalar* r = res + (j+j1)*resStride + i;
|
||||
for(int i1=UpLo==LowerTriangular ? j1 : 0;
|
||||
UpLo==LowerTriangular ? i1<actualBlockSize : i1<=j1; ++i1)
|
||||
for(int i1=UpLo==Lower ? j1 : 0;
|
||||
UpLo==Lower ? i1<actualBlockSize : i1<=j1; ++i1)
|
||||
r[i1] += buffer(i1,j1);
|
||||
}
|
||||
}
|
||||
|
||||
if(UpLo==LowerTriangular)
|
||||
if(UpLo==Lower)
|
||||
{
|
||||
int i = j+actualBlockSize;
|
||||
gebp_kernel(res+j*resStride+i, resStride, blockA+depth*i, actual_b, size-i, depth, actualBlockSize);
|
||||
|
||||
@ -33,7 +33,7 @@ template<typename Scalar, typename UType, typename VType, int UpLo>
|
||||
struct ei_selfadjoint_rank2_update_selector;
|
||||
|
||||
template<typename Scalar, typename UType, typename VType>
|
||||
struct ei_selfadjoint_rank2_update_selector<Scalar,UType,VType,LowerTriangular>
|
||||
struct ei_selfadjoint_rank2_update_selector<Scalar,UType,VType,Lower>
|
||||
{
|
||||
static void run(Scalar* mat, int stride, const UType& u, const VType& v, Scalar alpha)
|
||||
{
|
||||
@ -48,7 +48,7 @@ struct ei_selfadjoint_rank2_update_selector<Scalar,UType,VType,LowerTriangular>
|
||||
};
|
||||
|
||||
template<typename Scalar, typename UType, typename VType>
|
||||
struct ei_selfadjoint_rank2_update_selector<Scalar,UType,VType,UpperTriangular>
|
||||
struct ei_selfadjoint_rank2_update_selector<Scalar,UType,VType,Upper>
|
||||
{
|
||||
static void run(Scalar* mat, int stride, const UType& u, const VType& v, Scalar alpha)
|
||||
{
|
||||
@ -87,7 +87,7 @@ SelfAdjointView<MatrixType,UpLo>& SelfAdjointView<MatrixType,UpLo>
|
||||
ei_selfadjoint_rank2_update_selector<Scalar,
|
||||
typename ei_cleantype<typename ei_conj_expr_if<IsRowMajor ^ UBlasTraits::NeedToConjugate,_ActualUType>::ret>::type,
|
||||
typename ei_cleantype<typename ei_conj_expr_if<IsRowMajor ^ VBlasTraits::NeedToConjugate,_ActualVType>::ret>::type,
|
||||
(IsRowMajor ? (UpLo==UpperTriangular ? LowerTriangular : UpperTriangular) : UpLo)>
|
||||
(IsRowMajor ? (UpLo==Upper ? Lower : Upper) : UpLo)>
|
||||
::run(const_cast<Scalar*>(_expression().data()),_expression().stride(),actualU,actualV,actualAlpha);
|
||||
|
||||
return *this;
|
||||
|
||||
@ -75,7 +75,7 @@ struct ei_product_triangular_matrix_matrix<Scalar,Mode,LhsIsTriangular,
|
||||
Scalar alpha)
|
||||
{
|
||||
ei_product_triangular_matrix_matrix<Scalar,
|
||||
(Mode&UnitDiagBit) | (Mode&UpperTriangular) ? LowerTriangular : UpperTriangular,
|
||||
(Mode&UnitDiag) | (Mode&Upper) ? Lower : Upper,
|
||||
(!LhsIsTriangular),
|
||||
RhsStorageOrder==RowMajor ? ColMajor : RowMajor,
|
||||
ConjugateRhs,
|
||||
@ -113,7 +113,7 @@ struct ei_product_triangular_matrix_matrix<Scalar,Mode,true,
|
||||
typedef ei_product_blocking_traits<Scalar> Blocking;
|
||||
enum {
|
||||
SmallPanelWidth = EIGEN_ENUM_MAX(Blocking::mr,Blocking::nr),
|
||||
IsLowerTriangular = (Mode&LowerTriangular) == LowerTriangular
|
||||
IsLower = (Mode&Lower) == Lower
|
||||
};
|
||||
|
||||
int kc = std::min<int>(Blocking::Max_kc/4,size); // cache block size along the K direction
|
||||
@ -130,12 +130,12 @@ struct ei_product_triangular_matrix_matrix<Scalar,Mode,true,
|
||||
ei_gemm_pack_lhs<Scalar,Blocking::mr,LhsStorageOrder> pack_lhs;
|
||||
ei_gemm_pack_rhs<Scalar,Blocking::nr,RhsStorageOrder> pack_rhs;
|
||||
|
||||
for(int k2=IsLowerTriangular ? size : 0;
|
||||
IsLowerTriangular ? k2>0 : k2<size;
|
||||
IsLowerTriangular ? k2-=kc : k2+=kc)
|
||||
for(int k2=IsLower ? size : 0;
|
||||
IsLower ? k2>0 : k2<size;
|
||||
IsLower ? k2-=kc : k2+=kc)
|
||||
{
|
||||
const int actual_kc = std::min(IsLowerTriangular ? k2 : size-k2, kc);
|
||||
int actual_k2 = IsLowerTriangular ? k2-actual_kc : k2;
|
||||
const int actual_kc = std::min(IsLower ? k2 : size-k2, kc);
|
||||
int actual_k2 = IsLower ? k2-actual_kc : k2;
|
||||
|
||||
pack_rhs(blockB, &rhs(actual_k2,0), rhsStride, alpha, actual_kc, cols);
|
||||
|
||||
@ -149,7 +149,7 @@ struct ei_product_triangular_matrix_matrix<Scalar,Mode,true,
|
||||
for (int k1=0; k1<actual_kc; k1+=SmallPanelWidth)
|
||||
{
|
||||
int actualPanelWidth = std::min<int>(actual_kc-k1, SmallPanelWidth);
|
||||
int lengthTarget = IsLowerTriangular ? actual_kc-k1-actualPanelWidth : k1;
|
||||
int lengthTarget = IsLower ? actual_kc-k1-actualPanelWidth : k1;
|
||||
int startBlock = actual_k2+k1;
|
||||
int blockBOffset = k1;
|
||||
|
||||
@ -158,9 +158,9 @@ struct ei_product_triangular_matrix_matrix<Scalar,Mode,true,
|
||||
// To this end we do an extra triangular copy to small temporary buffer
|
||||
for (int k=0;k<actualPanelWidth;++k)
|
||||
{
|
||||
if (!(Mode&UnitDiagBit))
|
||||
if (!(Mode&UnitDiag))
|
||||
triangularBuffer.coeffRef(k,k) = lhs(startBlock+k,startBlock+k);
|
||||
for (int i=IsLowerTriangular ? k+1 : 0; IsLowerTriangular ? i<actualPanelWidth : i<k; ++i)
|
||||
for (int i=IsLower ? k+1 : 0; IsLower ? i<actualPanelWidth : i<k; ++i)
|
||||
triangularBuffer.coeffRef(i,k) = lhs(startBlock+i,startBlock+k);
|
||||
}
|
||||
pack_lhs(blockA, triangularBuffer.data(), triangularBuffer.stride(), actualPanelWidth, actualPanelWidth);
|
||||
@ -171,7 +171,7 @@ struct ei_product_triangular_matrix_matrix<Scalar,Mode,true,
|
||||
// GEBP with remaining micro panel
|
||||
if (lengthTarget>0)
|
||||
{
|
||||
int startTarget = IsLowerTriangular ? actual_k2+k1+actualPanelWidth : actual_k2;
|
||||
int startTarget = IsLower ? actual_k2+k1+actualPanelWidth : actual_k2;
|
||||
|
||||
pack_lhs(blockA, &lhs(startTarget,startBlock), lhsStride, actualPanelWidth, lengthTarget);
|
||||
|
||||
@ -182,8 +182,8 @@ struct ei_product_triangular_matrix_matrix<Scalar,Mode,true,
|
||||
}
|
||||
// the part below the diagonal => GEPP
|
||||
{
|
||||
int start = IsLowerTriangular ? k2 : 0;
|
||||
int end = IsLowerTriangular ? size : actual_k2;
|
||||
int start = IsLower ? k2 : 0;
|
||||
int end = IsLower ? size : actual_k2;
|
||||
for(int i2=start; i2<end; i2+=mc)
|
||||
{
|
||||
const int actual_mc = std::min(i2+mc,end)-i2;
|
||||
@ -227,7 +227,7 @@ struct ei_product_triangular_matrix_matrix<Scalar,Mode,false,
|
||||
typedef ei_product_blocking_traits<Scalar> Blocking;
|
||||
enum {
|
||||
SmallPanelWidth = EIGEN_ENUM_MAX(Blocking::mr,Blocking::nr),
|
||||
IsLowerTriangular = (Mode&LowerTriangular) == LowerTriangular
|
||||
IsLower = (Mode&Lower) == Lower
|
||||
};
|
||||
|
||||
int kc = std::min<int>(Blocking::Max_kc/4,size); // cache block size along the K direction
|
||||
@ -245,16 +245,16 @@ struct ei_product_triangular_matrix_matrix<Scalar,Mode,false,
|
||||
ei_gemm_pack_rhs<Scalar,Blocking::nr,RhsStorageOrder> pack_rhs;
|
||||
ei_gemm_pack_rhs<Scalar,Blocking::nr,RhsStorageOrder,true> pack_rhs_panel;
|
||||
|
||||
for(int k2=IsLowerTriangular ? 0 : size;
|
||||
IsLowerTriangular ? k2<size : k2>0;
|
||||
IsLowerTriangular ? k2+=kc : k2-=kc)
|
||||
for(int k2=IsLower ? 0 : size;
|
||||
IsLower ? k2<size : k2>0;
|
||||
IsLower ? k2+=kc : k2-=kc)
|
||||
{
|
||||
const int actual_kc = std::min(IsLowerTriangular ? size-k2 : k2, kc);
|
||||
int actual_k2 = IsLowerTriangular ? k2 : k2-actual_kc;
|
||||
int rs = IsLowerTriangular ? actual_k2 : size - k2;
|
||||
const int actual_kc = std::min(IsLower ? size-k2 : k2, kc);
|
||||
int actual_k2 = IsLower ? k2 : k2-actual_kc;
|
||||
int rs = IsLower ? actual_k2 : size - k2;
|
||||
Scalar* geb = blockB+actual_kc*actual_kc*Blocking::PacketSize;
|
||||
|
||||
pack_rhs(geb, &rhs(actual_k2,IsLowerTriangular ? 0 : k2), rhsStride, alpha, actual_kc, rs);
|
||||
pack_rhs(geb, &rhs(actual_k2,IsLower ? 0 : k2), rhsStride, alpha, actual_kc, rs);
|
||||
|
||||
// pack the triangular part of the rhs padding the unrolled blocks with zeros
|
||||
{
|
||||
@ -262,8 +262,8 @@ struct ei_product_triangular_matrix_matrix<Scalar,Mode,false,
|
||||
{
|
||||
int actualPanelWidth = std::min<int>(actual_kc-j2, SmallPanelWidth);
|
||||
int actual_j2 = actual_k2 + j2;
|
||||
int panelOffset = IsLowerTriangular ? j2+actualPanelWidth : 0;
|
||||
int panelLength = IsLowerTriangular ? actual_kc-j2-actualPanelWidth : j2;
|
||||
int panelOffset = IsLower ? j2+actualPanelWidth : 0;
|
||||
int panelLength = IsLower ? actual_kc-j2-actualPanelWidth : j2;
|
||||
// general part
|
||||
pack_rhs_panel(blockB+j2*actual_kc*Blocking::PacketSize,
|
||||
&rhs(actual_k2+panelOffset, actual_j2), rhsStride, alpha,
|
||||
@ -273,9 +273,9 @@ struct ei_product_triangular_matrix_matrix<Scalar,Mode,false,
|
||||
// append the triangular part via a temporary buffer
|
||||
for (int j=0;j<actualPanelWidth;++j)
|
||||
{
|
||||
if (!(Mode&UnitDiagBit))
|
||||
if (!(Mode&UnitDiag))
|
||||
triangularBuffer.coeffRef(j,j) = rhs(actual_j2+j,actual_j2+j);
|
||||
for (int k=IsLowerTriangular ? j+1 : 0; IsLowerTriangular ? k<actualPanelWidth : k<j; ++k)
|
||||
for (int k=IsLower ? j+1 : 0; IsLower ? k<actualPanelWidth : k<j; ++k)
|
||||
triangularBuffer.coeffRef(k,j) = rhs(actual_j2+k,actual_j2+j);
|
||||
}
|
||||
|
||||
@ -296,8 +296,8 @@ struct ei_product_triangular_matrix_matrix<Scalar,Mode,false,
|
||||
for (int j2=0; j2<actual_kc; j2+=SmallPanelWidth)
|
||||
{
|
||||
int actualPanelWidth = std::min<int>(actual_kc-j2, SmallPanelWidth);
|
||||
int panelLength = IsLowerTriangular ? actual_kc-j2 : j2+actualPanelWidth;
|
||||
int blockOffset = IsLowerTriangular ? j2 : 0;
|
||||
int panelLength = IsLower ? actual_kc-j2 : j2+actualPanelWidth;
|
||||
int blockOffset = IsLower ? j2 : 0;
|
||||
|
||||
gebp_kernel(res+i2+(actual_k2+j2)*resStride, resStride,
|
||||
blockA, blockB+j2*actual_kc*Blocking::PacketSize,
|
||||
@ -306,7 +306,7 @@ struct ei_product_triangular_matrix_matrix<Scalar,Mode,false,
|
||||
blockOffset, blockOffset*Blocking::PacketSize);// offsets
|
||||
}
|
||||
}
|
||||
gebp_kernel(res+i2+(IsLowerTriangular ? 0 : k2)*resStride, resStride,
|
||||
gebp_kernel(res+i2+(IsLower ? 0 : k2)*resStride, resStride,
|
||||
blockA, geb, actual_mc, actual_kc, rs);
|
||||
}
|
||||
}
|
||||
|
||||
@ -34,8 +34,8 @@ struct ei_product_triangular_vector_selector<Lhs,Rhs,Result,Mode,ConjLhs,ConjRhs
|
||||
{
|
||||
typedef typename Rhs::Scalar Scalar;
|
||||
enum {
|
||||
IsLowerTriangular = ((Mode&LowerTriangularBit)==LowerTriangularBit),
|
||||
HasUnitDiag = (Mode & UnitDiagBit)==UnitDiagBit
|
||||
IsLower = ((Mode&Lower)==Lower),
|
||||
HasUnitDiag = (Mode & UnitDiag)==UnitDiag
|
||||
};
|
||||
static EIGEN_DONT_INLINE void run(const Lhs& lhs, const Rhs& rhs, Result& res, typename ei_traits<Lhs>::Scalar alpha)
|
||||
{
|
||||
@ -50,17 +50,17 @@ struct ei_product_triangular_vector_selector<Lhs,Rhs,Result,Mode,ConjLhs,ConjRhs
|
||||
for (int k=0; k<actualPanelWidth; ++k)
|
||||
{
|
||||
int i = pi + k;
|
||||
int s = IsLowerTriangular ? (HasUnitDiag ? i+1 : i ) : pi;
|
||||
int r = IsLowerTriangular ? actualPanelWidth-k : k+1;
|
||||
int s = IsLower ? (HasUnitDiag ? i+1 : i ) : pi;
|
||||
int r = IsLower ? actualPanelWidth-k : k+1;
|
||||
if ((!HasUnitDiag) || (--r)>0)
|
||||
res.segment(s,r) += (alpha * cjRhs.coeff(i)) * cjLhs.col(i).segment(s,r);
|
||||
if (HasUnitDiag)
|
||||
res.coeffRef(i) += alpha * cjRhs.coeff(i);
|
||||
}
|
||||
int r = IsLowerTriangular ? size - pi - actualPanelWidth : pi;
|
||||
int r = IsLower ? size - pi - actualPanelWidth : pi;
|
||||
if (r>0)
|
||||
{
|
||||
int s = IsLowerTriangular ? pi+actualPanelWidth : 0;
|
||||
int s = IsLower ? pi+actualPanelWidth : 0;
|
||||
ei_cache_friendly_product_colmajor_times_vector<ConjLhs,ConjRhs>(
|
||||
r,
|
||||
&(lhs.const_cast_derived().coeffRef(s,pi)), lhs.stride(),
|
||||
@ -77,8 +77,8 @@ struct ei_product_triangular_vector_selector<Lhs,Rhs,Result,Mode,ConjLhs,ConjRhs
|
||||
{
|
||||
typedef typename Rhs::Scalar Scalar;
|
||||
enum {
|
||||
IsLowerTriangular = ((Mode&LowerTriangularBit)==LowerTriangularBit),
|
||||
HasUnitDiag = (Mode & UnitDiagBit)==UnitDiagBit
|
||||
IsLower = ((Mode&Lower)==Lower),
|
||||
HasUnitDiag = (Mode & UnitDiag)==UnitDiag
|
||||
};
|
||||
static void run(const Lhs& lhs, const Rhs& rhs, Result& res, typename ei_traits<Lhs>::Scalar alpha)
|
||||
{
|
||||
@ -92,17 +92,17 @@ struct ei_product_triangular_vector_selector<Lhs,Rhs,Result,Mode,ConjLhs,ConjRhs
|
||||
for (int k=0; k<actualPanelWidth; ++k)
|
||||
{
|
||||
int i = pi + k;
|
||||
int s = IsLowerTriangular ? pi : (HasUnitDiag ? i+1 : i);
|
||||
int r = IsLowerTriangular ? k+1 : actualPanelWidth-k;
|
||||
int s = IsLower ? pi : (HasUnitDiag ? i+1 : i);
|
||||
int r = IsLower ? k+1 : actualPanelWidth-k;
|
||||
if ((!HasUnitDiag) || (--r)>0)
|
||||
res.coeffRef(i) += alpha * (cjLhs.row(i).segment(s,r).cwiseProduct(cjRhs.segment(s,r).transpose())).sum();
|
||||
if (HasUnitDiag)
|
||||
res.coeffRef(i) += alpha * cjRhs.coeff(i);
|
||||
}
|
||||
int r = IsLowerTriangular ? pi : size - pi - actualPanelWidth;
|
||||
int r = IsLower ? pi : size - pi - actualPanelWidth;
|
||||
if (r>0)
|
||||
{
|
||||
int s = IsLowerTriangular ? 0 : pi + actualPanelWidth;
|
||||
int s = IsLower ? 0 : pi + actualPanelWidth;
|
||||
Block<Result,Dynamic,1> target(res,pi,0,actualPanelWidth,1);
|
||||
ei_cache_friendly_product_rowmajor_times_vector<ConjLhs,ConjRhs>(
|
||||
&(lhs.const_cast_derived().coeffRef(pi,s)), lhs.stride(),
|
||||
|
||||
@ -36,7 +36,7 @@ struct ei_triangular_solve_matrix<Scalar,Side,Mode,Conjugate,TriStorageOrder,Row
|
||||
{
|
||||
ei_triangular_solve_matrix<
|
||||
Scalar, Side==OnTheLeft?OnTheRight:OnTheLeft,
|
||||
(Mode&UnitDiagBit) | ((Mode&UpperTriangular) ? LowerTriangular : UpperTriangular),
|
||||
(Mode&UnitDiag) | ((Mode&Upper) ? Lower : Upper),
|
||||
NumTraits<Scalar>::IsComplex && Conjugate,
|
||||
TriStorageOrder==RowMajor ? ColMajor : RowMajor, ColMajor>
|
||||
::run(size, cols, tri, triStride, _other, otherStride);
|
||||
@ -60,7 +60,7 @@ struct ei_triangular_solve_matrix<Scalar,OnTheLeft,Mode,Conjugate,TriStorageOrde
|
||||
typedef ei_product_blocking_traits<Scalar> Blocking;
|
||||
enum {
|
||||
SmallPanelWidth = EIGEN_ENUM_MAX(Blocking::mr,Blocking::nr),
|
||||
IsLowerTriangular = (Mode&LowerTriangular) == LowerTriangular
|
||||
IsLower = (Mode&Lower) == Lower
|
||||
};
|
||||
|
||||
int kc = std::min<int>(Blocking::Max_kc/4,size); // cache block size along the K direction
|
||||
@ -73,11 +73,11 @@ struct ei_triangular_solve_matrix<Scalar,OnTheLeft,Mode,Conjugate,TriStorageOrde
|
||||
ei_gebp_kernel<Scalar, Blocking::mr, Blocking::nr, ei_conj_helper<Conjugate,false> > gebp_kernel;
|
||||
ei_gemm_pack_lhs<Scalar,Blocking::mr,TriStorageOrder> pack_lhs;
|
||||
|
||||
for(int k2=IsLowerTriangular ? 0 : size;
|
||||
IsLowerTriangular ? k2<size : k2>0;
|
||||
IsLowerTriangular ? k2+=kc : k2-=kc)
|
||||
for(int k2=IsLower ? 0 : size;
|
||||
IsLower ? k2<size : k2>0;
|
||||
IsLower ? k2+=kc : k2-=kc)
|
||||
{
|
||||
const int actual_kc = std::min(IsLowerTriangular ? size-k2 : k2, kc);
|
||||
const int actual_kc = std::min(IsLower ? size-k2 : k2, kc);
|
||||
|
||||
// We have selected and packed a big horizontal panel R1 of rhs. Let B be the packed copy of this panel,
|
||||
// and R2 the remaining part of rhs. The corresponding vertical panel of lhs is split into
|
||||
@ -101,11 +101,11 @@ struct ei_triangular_solve_matrix<Scalar,OnTheLeft,Mode,Conjugate,TriStorageOrde
|
||||
for (int k=0; k<actualPanelWidth; ++k)
|
||||
{
|
||||
// TODO write a small kernel handling this (can be shared with trsv)
|
||||
int i = IsLowerTriangular ? k2+k1+k : k2-k1-k-1;
|
||||
int s = IsLowerTriangular ? k2+k1 : i+1;
|
||||
int i = IsLower ? k2+k1+k : k2-k1-k-1;
|
||||
int s = IsLower ? k2+k1 : i+1;
|
||||
int rs = actualPanelWidth - k - 1; // remaining size
|
||||
|
||||
Scalar a = (Mode & UnitDiagBit) ? Scalar(1) : Scalar(1)/conj(tri(i,i));
|
||||
Scalar a = (Mode & UnitDiag) ? Scalar(1) : Scalar(1)/conj(tri(i,i));
|
||||
for (int j=0; j<cols; ++j)
|
||||
{
|
||||
if (TriStorageOrder==RowMajor)
|
||||
@ -120,7 +120,7 @@ struct ei_triangular_solve_matrix<Scalar,OnTheLeft,Mode,Conjugate,TriStorageOrde
|
||||
}
|
||||
else
|
||||
{
|
||||
int s = IsLowerTriangular ? i+1 : i-rs;
|
||||
int s = IsLower ? i+1 : i-rs;
|
||||
Scalar b = (other(i,j) *= a);
|
||||
Scalar* r = &other(s,j);
|
||||
const Scalar* l = &tri(s,i);
|
||||
@ -131,8 +131,8 @@ struct ei_triangular_solve_matrix<Scalar,OnTheLeft,Mode,Conjugate,TriStorageOrde
|
||||
}
|
||||
|
||||
int lengthTarget = actual_kc-k1-actualPanelWidth;
|
||||
int startBlock = IsLowerTriangular ? k2+k1 : k2-k1-actualPanelWidth;
|
||||
int blockBOffset = IsLowerTriangular ? k1 : lengthTarget;
|
||||
int startBlock = IsLower ? k2+k1 : k2-k1-actualPanelWidth;
|
||||
int blockBOffset = IsLower ? k1 : lengthTarget;
|
||||
|
||||
// update the respective rows of B from other
|
||||
ei_gemm_pack_rhs<Scalar, Blocking::nr, ColMajor, true>()
|
||||
@ -141,7 +141,7 @@ struct ei_triangular_solve_matrix<Scalar,OnTheLeft,Mode,Conjugate,TriStorageOrde
|
||||
// GEBP
|
||||
if (lengthTarget>0)
|
||||
{
|
||||
int startTarget = IsLowerTriangular ? k2+k1+actualPanelWidth : k2-actual_kc;
|
||||
int startTarget = IsLower ? k2+k1+actualPanelWidth : k2-actual_kc;
|
||||
|
||||
pack_lhs(blockA, &tri(startTarget,startBlock), triStride, actualPanelWidth, lengthTarget);
|
||||
|
||||
@ -153,14 +153,14 @@ struct ei_triangular_solve_matrix<Scalar,OnTheLeft,Mode,Conjugate,TriStorageOrde
|
||||
|
||||
// R2 = A2 * B => GEPP
|
||||
{
|
||||
int start = IsLowerTriangular ? k2+kc : 0;
|
||||
int end = IsLowerTriangular ? size : k2-kc;
|
||||
int start = IsLower ? k2+kc : 0;
|
||||
int end = IsLower ? size : k2-kc;
|
||||
for(int i2=start; i2<end; i2+=mc)
|
||||
{
|
||||
const int actual_mc = std::min(mc,end-i2);
|
||||
if (actual_mc>0)
|
||||
{
|
||||
pack_lhs(blockA, &tri(i2, IsLowerTriangular ? k2 : k2-kc), triStride, actual_kc, actual_mc);
|
||||
pack_lhs(blockA, &tri(i2, IsLower ? k2 : k2-kc), triStride, actual_kc, actual_mc);
|
||||
|
||||
gebp_kernel(_other+i2, otherStride, blockA, blockB, actual_mc, actual_kc, cols);
|
||||
}
|
||||
@ -191,7 +191,7 @@ struct ei_triangular_solve_matrix<Scalar,OnTheRight,Mode,Conjugate,TriStorageOrd
|
||||
enum {
|
||||
RhsStorageOrder = TriStorageOrder,
|
||||
SmallPanelWidth = EIGEN_ENUM_MAX(Blocking::mr,Blocking::nr),
|
||||
IsLowerTriangular = (Mode&LowerTriangular) == LowerTriangular
|
||||
IsLower = (Mode&Lower) == Lower
|
||||
};
|
||||
|
||||
int kc = std::min<int>(Blocking::Max_kc/4,size); // cache block size along the K direction
|
||||
@ -206,15 +206,15 @@ struct ei_triangular_solve_matrix<Scalar,OnTheRight,Mode,Conjugate,TriStorageOrd
|
||||
ei_gemm_pack_rhs<Scalar,Blocking::nr,RhsStorageOrder,true> pack_rhs_panel;
|
||||
ei_gemm_pack_lhs<Scalar, Blocking::mr, ColMajor, false, true> pack_lhs_panel;
|
||||
|
||||
for(int k2=IsLowerTriangular ? size : 0;
|
||||
IsLowerTriangular ? k2>0 : k2<size;
|
||||
IsLowerTriangular ? k2-=kc : k2+=kc)
|
||||
for(int k2=IsLower ? size : 0;
|
||||
IsLower ? k2>0 : k2<size;
|
||||
IsLower ? k2-=kc : k2+=kc)
|
||||
{
|
||||
const int actual_kc = std::min(IsLowerTriangular ? k2 : size-k2, kc);
|
||||
int actual_k2 = IsLowerTriangular ? k2-actual_kc : k2 ;
|
||||
const int actual_kc = std::min(IsLower ? k2 : size-k2, kc);
|
||||
int actual_k2 = IsLower ? k2-actual_kc : k2 ;
|
||||
|
||||
int startPanel = IsLowerTriangular ? 0 : k2+actual_kc;
|
||||
int rs = IsLowerTriangular ? actual_k2 : size - actual_k2 - actual_kc;
|
||||
int startPanel = IsLower ? 0 : k2+actual_kc;
|
||||
int rs = IsLower ? actual_k2 : size - actual_k2 - actual_kc;
|
||||
Scalar* geb = blockB+actual_kc*actual_kc*Blocking::PacketSize;
|
||||
|
||||
if (rs>0) pack_rhs(geb, &rhs(actual_k2,startPanel), triStride, -1, actual_kc, rs);
|
||||
@ -226,8 +226,8 @@ struct ei_triangular_solve_matrix<Scalar,OnTheRight,Mode,Conjugate,TriStorageOrd
|
||||
{
|
||||
int actualPanelWidth = std::min<int>(actual_kc-j2, SmallPanelWidth);
|
||||
int actual_j2 = actual_k2 + j2;
|
||||
int panelOffset = IsLowerTriangular ? j2+actualPanelWidth : 0;
|
||||
int panelLength = IsLowerTriangular ? actual_kc-j2-actualPanelWidth : j2;
|
||||
int panelOffset = IsLower ? j2+actualPanelWidth : 0;
|
||||
int panelLength = IsLower ? actual_kc-j2-actualPanelWidth : j2;
|
||||
|
||||
if (panelLength>0)
|
||||
pack_rhs_panel(blockB+j2*actual_kc*Blocking::PacketSize,
|
||||
@ -244,17 +244,17 @@ struct ei_triangular_solve_matrix<Scalar,OnTheRight,Mode,Conjugate,TriStorageOrd
|
||||
// triangular solver kernel
|
||||
{
|
||||
// for each small block of the diagonal (=> vertical panels of rhs)
|
||||
for (int j2 = IsLowerTriangular
|
||||
for (int j2 = IsLower
|
||||
? (actual_kc - ((actual_kc%SmallPanelWidth) ? (actual_kc%SmallPanelWidth)
|
||||
: SmallPanelWidth))
|
||||
: 0;
|
||||
IsLowerTriangular ? j2>=0 : j2<actual_kc;
|
||||
IsLowerTriangular ? j2-=SmallPanelWidth : j2+=SmallPanelWidth)
|
||||
IsLower ? j2>=0 : j2<actual_kc;
|
||||
IsLower ? j2-=SmallPanelWidth : j2+=SmallPanelWidth)
|
||||
{
|
||||
int actualPanelWidth = std::min<int>(actual_kc-j2, SmallPanelWidth);
|
||||
int absolute_j2 = actual_k2 + j2;
|
||||
int panelOffset = IsLowerTriangular ? j2+actualPanelWidth : 0;
|
||||
int panelLength = IsLowerTriangular ? actual_kc - j2 - actualPanelWidth : j2;
|
||||
int panelOffset = IsLower ? j2+actualPanelWidth : 0;
|
||||
int panelLength = IsLower ? actual_kc - j2 - actualPanelWidth : j2;
|
||||
|
||||
// GEBP
|
||||
if(panelLength>0)
|
||||
@ -269,17 +269,17 @@ struct ei_triangular_solve_matrix<Scalar,OnTheRight,Mode,Conjugate,TriStorageOrd
|
||||
// unblocked triangular solve
|
||||
for (int k=0; k<actualPanelWidth; ++k)
|
||||
{
|
||||
int j = IsLowerTriangular ? absolute_j2+actualPanelWidth-k-1 : absolute_j2+k;
|
||||
int j = IsLower ? absolute_j2+actualPanelWidth-k-1 : absolute_j2+k;
|
||||
|
||||
Scalar* r = &lhs(i2,j);
|
||||
for (int k3=0; k3<k; ++k3)
|
||||
{
|
||||
Scalar b = conj(rhs(IsLowerTriangular ? j+1+k3 : absolute_j2+k3,j));
|
||||
Scalar* a = &lhs(i2,IsLowerTriangular ? j+1+k3 : absolute_j2+k3);
|
||||
Scalar b = conj(rhs(IsLower ? j+1+k3 : absolute_j2+k3,j));
|
||||
Scalar* a = &lhs(i2,IsLower ? j+1+k3 : absolute_j2+k3);
|
||||
for (int i=0; i<actual_mc; ++i)
|
||||
r[i] -= a[i] * b;
|
||||
}
|
||||
Scalar b = (Mode & UnitDiagBit) ? Scalar(1) : Scalar(1)/conj(rhs(j,j));
|
||||
Scalar b = (Mode & UnitDiag) ? Scalar(1) : Scalar(1)/conj(rhs(j,j));
|
||||
for (int i=0; i<actual_mc; ++i)
|
||||
r[i] *= b;
|
||||
}
|
||||
|
||||
@ -149,44 +149,18 @@ const unsigned int DirectAccessBit = 0x20;
|
||||
* means the first coefficient packet is guaranteed to be aligned */
|
||||
const unsigned int AlignedBit = 0x40;
|
||||
|
||||
/** \ingroup flags
|
||||
*
|
||||
* means all diagonal coefficients are equal to 0 */
|
||||
const unsigned int ZeroDiagBit = 0x80;
|
||||
|
||||
/** \ingroup flags
|
||||
*
|
||||
* means all diagonal coefficients are equal to 1 */
|
||||
const unsigned int UnitDiagBit = 0x100;
|
||||
|
||||
/** \ingroup flags
|
||||
*
|
||||
* means the matrix is selfadjoint (M=M*). */
|
||||
const unsigned int SelfAdjointBit = 0x200;
|
||||
|
||||
/** \ingroup flags
|
||||
*
|
||||
* means the strictly lower triangular part is 0 */
|
||||
const unsigned int UpperTriangularBit = 0x400;
|
||||
|
||||
/** \ingroup flags
|
||||
*
|
||||
* means the strictly upper triangular part is 0 */
|
||||
const unsigned int LowerTriangularBit = 0x800;
|
||||
|
||||
// list of flags that are inherited by default
|
||||
const unsigned int HereditaryBits = RowMajorBit
|
||||
| EvalBeforeNestingBit
|
||||
| EvalBeforeAssigningBit;
|
||||
|
||||
// Possible values for the Mode parameter of part()
|
||||
const unsigned int UpperTriangular = UpperTriangularBit;
|
||||
const unsigned int StrictlyUpperTriangular = UpperTriangularBit | ZeroDiagBit;
|
||||
const unsigned int LowerTriangular = LowerTriangularBit;
|
||||
const unsigned int StrictlyLowerTriangular = LowerTriangularBit | ZeroDiagBit;
|
||||
const unsigned int SelfAdjoint = SelfAdjointBit;
|
||||
const unsigned int UnitUpperTriangular = UpperTriangularBit | UnitDiagBit;
|
||||
const unsigned int UnitLowerTriangular = LowerTriangularBit | UnitDiagBit;
|
||||
// Possible values for the Mode parameter of triangularView()
|
||||
enum {
|
||||
Lower=0x1, Upper=0x2, UnitDiag=0x4, ZeroDiag=0x8,
|
||||
UnitLower=UnitDiag|Lower, UnitUpper=UnitDiag|Upper,
|
||||
StrictlyLower=ZeroDiag|Lower, StrictlyUpper=ZeroDiag|Upper,
|
||||
SelfAdjoint=0x10};
|
||||
|
||||
enum { Unaligned=0, Aligned=1 };
|
||||
enum { ConditionalJumpCost = 5 };
|
||||
|
||||
@ -132,7 +132,7 @@ template<typename MatrixType> class ColPivHouseholderQR;
|
||||
template<typename MatrixType> class FullPivHouseholderQR;
|
||||
template<typename MatrixType> class SVD;
|
||||
template<typename MatrixType, unsigned int Options = 0> class JacobiSVD;
|
||||
template<typename MatrixType, int UpLo = LowerTriangular> class LLT;
|
||||
template<typename MatrixType, int UpLo = Lower> class LLT;
|
||||
template<typename MatrixType> class LDLT;
|
||||
template<typename VectorsType, typename CoeffsType> class HouseholderSequence;
|
||||
template<typename Scalar> class PlanarRotation;
|
||||
|
||||
@ -263,8 +263,7 @@ template<typename T, int n=1, typename PlainMatrixType = typename ei_eval<T>::ty
|
||||
|
||||
template<unsigned int Flags> struct ei_are_flags_consistent
|
||||
{
|
||||
enum { ret = !( (Flags&UnitDiagBit && Flags&ZeroDiagBit) )
|
||||
};
|
||||
enum { ret = true };
|
||||
};
|
||||
|
||||
/** \internal Helper base class to add a scalar multiple operator
|
||||
|
||||
@ -109,6 +109,12 @@ template<typename ExpressionType, unsigned int Added, unsigned int Removed> clas
|
||||
|
||||
const ExpressionType& _expression() const { return m_matrix; }
|
||||
|
||||
template<typename OtherDerived>
|
||||
typename ExpressionType::PlainMatrixType solveTriangular(const MatrixBase<OtherDerived>& other) const;
|
||||
|
||||
template<typename OtherDerived>
|
||||
void solveTriangularInPlace(const MatrixBase<OtherDerived>& other) const;
|
||||
|
||||
protected:
|
||||
ExpressionTypeNested m_matrix;
|
||||
};
|
||||
|
||||
@ -0,0 +1,53 @@
|
||||
// This file is part of Eigen, a lightweight C++ template library
|
||||
// for linear algebra.
|
||||
//
|
||||
// Copyright (C) 2010 Gael Guennebaud <g.gael@free.fr>
|
||||
//
|
||||
// Eigen is free software; you can redistribute it and/or
|
||||
// modify it under the terms of the GNU Lesser General Public
|
||||
// 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_TRIANGULAR_SOLVER2_H
|
||||
#define EIGEN_TRIANGULAR_SOLVER2_H
|
||||
|
||||
const unsigned int UnitDiagBit = UnitDiag;
|
||||
const unsigned int SelfAdjointBit = SelfAdjoint;
|
||||
const unsigned int UpperTriangularBit = Upper;
|
||||
const unsigned int LowerTriangularBit = Lower;
|
||||
|
||||
const unsigned int UpperTriangular = Upper;
|
||||
const unsigned int LowerTriangular = Lower;
|
||||
const unsigned int UnitUpperTriangular = UnitUpper;
|
||||
const unsigned int UnitLowerTriangular = UnitLower;
|
||||
|
||||
template<typename ExpressionType, unsigned int Added, unsigned int Removed>
|
||||
template<typename OtherDerived>
|
||||
typename ExpressionType::PlainMatrixType
|
||||
Flagged<ExpressionType,Added,Removed>::solveTriangular(const MatrixBase<OtherDerived>& other) const
|
||||
{
|
||||
return m_matrix.template triangularView<Added>.solve(other.derived());
|
||||
}
|
||||
|
||||
template<typename ExpressionType, unsigned int Added, unsigned int Removed>
|
||||
template<typename OtherDerived>
|
||||
void Flagged<ExpressionType,Added,Removed>::solveTriangularInPlace(const MatrixBase<OtherDerived>& other) const
|
||||
{
|
||||
m_matrix.template triangularView<Added>.solveInPlace(other.derived());
|
||||
}
|
||||
|
||||
#endif // EIGEN_TRIANGULAR_SOLVER2_H
|
||||
@ -199,7 +199,7 @@ HessenbergDecomposition<MatrixType>::matrixH() const
|
||||
int n = m_matrix.rows();
|
||||
MatrixType matH = m_matrix;
|
||||
if (n>2)
|
||||
matH.corner(BottomLeft,n-2, n-2).template triangularView<LowerTriangular>().setZero();
|
||||
matH.corner(BottomLeft,n-2, n-2).template triangularView<Lower>().setZero();
|
||||
return matH;
|
||||
}
|
||||
|
||||
|
||||
@ -247,11 +247,11 @@ compute(const MatrixType& matA, const MatrixType& matB, bool computeEigenvectors
|
||||
matC.adjointInPlace();
|
||||
// this version works too:
|
||||
// matC = matC.transpose();
|
||||
// cholB.matrixL().conjugate().template marked<LowerTriangular>().solveTriangularInPlace(matC);
|
||||
// cholB.matrixL().conjugate().template marked<Lower>().solveTriangularInPlace(matC);
|
||||
// matC = matC.transpose();
|
||||
// FIXME: this should work: (currently it only does for small matrices)
|
||||
// Transpose<MatrixType> trMatC(matC);
|
||||
// cholB.matrixL().conjugate().eval().template marked<LowerTriangular>().solveTriangularInPlace(trMatC);
|
||||
// cholB.matrixL().conjugate().eval().template marked<Lower>().solveTriangularInPlace(trMatC);
|
||||
|
||||
compute(matC, computeEigenvectors);
|
||||
|
||||
@ -275,7 +275,7 @@ template<typename Derived>
|
||||
inline Matrix<typename NumTraits<typename ei_traits<Derived>::Scalar>::Real, ei_traits<Derived>::ColsAtCompileTime, 1>
|
||||
MatrixBase<Derived>::eigenvalues() const
|
||||
{
|
||||
ei_assert(Flags&SelfAdjointBit);
|
||||
ei_assert(Flags&SelfAdjoint);
|
||||
return SelfAdjointEigenSolver<typename Derived::PlainMatrixType>(eval(),false).eigenvalues();
|
||||
}
|
||||
|
||||
@ -316,7 +316,7 @@ template<typename Derived>
|
||||
inline typename NumTraits<typename ei_traits<Derived>::Scalar>::Real
|
||||
MatrixBase<Derived>::operatorNorm() const
|
||||
{
|
||||
return ei_operatorNorm_selector<Derived, Flags&SelfAdjointBit>
|
||||
return ei_operatorNorm_selector<Derived, Flags&SelfAdjoint>
|
||||
::operatorNorm(derived());
|
||||
}
|
||||
|
||||
|
||||
@ -172,8 +172,8 @@ Tridiagonalization<MatrixType>::matrixT(void) const
|
||||
matT.corner(TopRight,n-1, n-1).diagonal() = subDiagonal().template cast<Scalar>().conjugate();
|
||||
if (n>2)
|
||||
{
|
||||
matT.corner(TopRight,n-2, n-2).template triangularView<UpperTriangular>().setZero();
|
||||
matT.corner(BottomLeft,n-2, n-2).template triangularView<LowerTriangular>().setZero();
|
||||
matT.corner(TopRight,n-2, n-2).template triangularView<Upper>().setZero();
|
||||
matT.corner(BottomLeft,n-2, n-2).template triangularView<Lower>().setZero();
|
||||
}
|
||||
return matT;
|
||||
}
|
||||
@ -208,12 +208,12 @@ void Tridiagonalization<MatrixType>::_compute(MatrixType& matA, CoeffVectorType&
|
||||
// i.e., A = H A H' where H = I - h v v' and v = matA.col(i).tail(n-i-1)
|
||||
matA.col(i).coeffRef(i+1) = 1;
|
||||
|
||||
hCoeffs.tail(n-i-1) = (matA.corner(BottomRight,remainingSize,remainingSize).template selfadjointView<LowerTriangular>()
|
||||
hCoeffs.tail(n-i-1) = (matA.corner(BottomRight,remainingSize,remainingSize).template selfadjointView<Lower>()
|
||||
* (ei_conj(h) * matA.col(i).tail(remainingSize)));
|
||||
|
||||
hCoeffs.tail(n-i-1) += (ei_conj(h)*Scalar(-0.5)*(hCoeffs.tail(remainingSize).dot(matA.col(i).tail(remainingSize)))) * matA.col(i).tail(n-i-1);
|
||||
|
||||
matA.corner(BottomRight, remainingSize, remainingSize).template selfadjointView<LowerTriangular>()
|
||||
matA.corner(BottomRight, remainingSize, remainingSize).template selfadjointView<Lower>()
|
||||
.rankUpdate(matA.col(i).tail(remainingSize), hCoeffs.tail(remainingSize), -1);
|
||||
|
||||
matA.col(i).coeffRef(i+1) = beta;
|
||||
|
||||
@ -41,14 +41,8 @@ const typename Derived::Scalar ei_bruteforce_det4_helper
|
||||
* (matrix.coeff(m,2) * matrix.coeff(n,3) - matrix.coeff(n,2) * matrix.coeff(m,3));
|
||||
}
|
||||
|
||||
// FIXME update computation of triangular det
|
||||
|
||||
const int TriangularDeterminant = 0;
|
||||
|
||||
template<typename Derived,
|
||||
int DeterminantType =
|
||||
(Derived::Flags & (UpperTriangularBit | LowerTriangularBit))
|
||||
? TriangularDeterminant : Derived::RowsAtCompileTime
|
||||
int DeterminantType = Derived::RowsAtCompileTime
|
||||
> struct ei_determinant_impl
|
||||
{
|
||||
static inline typename ei_traits<Derived>::Scalar run(const Derived& m)
|
||||
@ -57,19 +51,6 @@ template<typename Derived,
|
||||
}
|
||||
};
|
||||
|
||||
template<typename Derived> struct ei_determinant_impl<Derived, TriangularDeterminant>
|
||||
{
|
||||
static inline typename ei_traits<Derived>::Scalar run(const Derived& m)
|
||||
{
|
||||
if (Derived::Flags & UnitDiagBit)
|
||||
return 1;
|
||||
else if (Derived::Flags & ZeroDiagBit)
|
||||
return 0;
|
||||
else
|
||||
return m.diagonal().redux(ei_scalar_product_op<typename ei_traits<Derived>::Scalar>());
|
||||
}
|
||||
};
|
||||
|
||||
template<typename Derived> struct ei_determinant_impl<Derived, 1>
|
||||
{
|
||||
static inline typename ei_traits<Derived>::Scalar run(const Derived& m)
|
||||
|
||||
@ -541,7 +541,7 @@ struct ei_kernel_retval<FullPivLU<_MatrixType> >
|
||||
m.row(i).tail(cols-i) = dec().matrixLU().row(pivots.coeff(i)).tail(cols-i);
|
||||
}
|
||||
m.block(0, 0, rank(), rank());
|
||||
m.block(0, 0, rank(), rank()).template triangularView<StrictlyLowerTriangular>().setZero();
|
||||
m.block(0, 0, rank(), rank()).template triangularView<StrictlyLower>().setZero();
|
||||
for(int i = 0; i < rank(); ++i)
|
||||
m.col(i).swap(m.col(pivots.coeff(i)));
|
||||
|
||||
@ -549,7 +549,7 @@ struct ei_kernel_retval<FullPivLU<_MatrixType> >
|
||||
// notice that the math behind this suggests that we should apply this to the
|
||||
// negative of the RHS, but for performance we just put the negative sign elsewhere, see below.
|
||||
m.corner(TopLeft, rank(), rank())
|
||||
.template triangularView<UpperTriangular>().solveInPlace(
|
||||
.template triangularView<Upper>().solveInPlace(
|
||||
m.corner(TopRight, rank(), dimker)
|
||||
);
|
||||
|
||||
@ -638,7 +638,7 @@ struct ei_solve_retval<FullPivLU<_MatrixType>, Rhs>
|
||||
// Step 2
|
||||
dec().matrixLU()
|
||||
.corner(Eigen::TopLeft,smalldim,smalldim)
|
||||
.template triangularView<UnitLowerTriangular>()
|
||||
.template triangularView<UnitLower>()
|
||||
.solveInPlace(c.corner(Eigen::TopLeft, smalldim, c.cols()));
|
||||
if(rows>cols)
|
||||
{
|
||||
@ -650,7 +650,7 @@ struct ei_solve_retval<FullPivLU<_MatrixType>, Rhs>
|
||||
// Step 3
|
||||
dec().matrixLU()
|
||||
.corner(TopLeft, nonzero_pivots, nonzero_pivots)
|
||||
.template triangularView<UpperTriangular>()
|
||||
.template triangularView<Upper>()
|
||||
.solveInPlace(c.corner(TopLeft, nonzero_pivots, c.cols()));
|
||||
|
||||
// Step 4
|
||||
|
||||
@ -349,7 +349,7 @@ struct ei_partial_lu_impl
|
||||
A_2.row(i).swap(A_2.row(row_transpositions[i]));
|
||||
|
||||
// A12 = A11^-1 A12
|
||||
A11.template triangularView<UnitLowerTriangular>().solveInPlace(A12);
|
||||
A11.template triangularView<UnitLower>().solveInPlace(A12);
|
||||
|
||||
A22.noalias() -= A21 * A12;
|
||||
}
|
||||
@ -426,10 +426,10 @@ struct ei_solve_retval<PartialPivLU<_MatrixType>, Rhs>
|
||||
dst = dec().permutationP() * rhs();
|
||||
|
||||
// Step 2
|
||||
dec().matrixLU().template triangularView<UnitLowerTriangular>().solveInPlace(dst);
|
||||
dec().matrixLU().template triangularView<UnitLower>().solveInPlace(dst);
|
||||
|
||||
// Step 3
|
||||
dec().matrixLU().template triangularView<UpperTriangular>().solveInPlace(dst);
|
||||
dec().matrixLU().template triangularView<Upper>().solveInPlace(dst);
|
||||
}
|
||||
};
|
||||
|
||||
|
||||
@ -381,7 +381,7 @@ ColPivHouseholderQR<MatrixType>& ColPivHouseholderQR<MatrixType>::compute(const
|
||||
m_nonzero_pivots = k;
|
||||
m_hCoeffs.tail(size-k).setZero();
|
||||
m_qr.corner(BottomRight,rows-k,cols-k)
|
||||
.template triangularView<StrictlyLowerTriangular>()
|
||||
.template triangularView<StrictlyLower>()
|
||||
.setZero();
|
||||
break;
|
||||
}
|
||||
@ -453,7 +453,7 @@ struct ei_solve_retval<ColPivHouseholderQR<_MatrixType>, Rhs>
|
||||
|
||||
dec().matrixQR()
|
||||
.corner(TopLeft, nonzero_pivots, nonzero_pivots)
|
||||
.template triangularView<UpperTriangular>()
|
||||
.template triangularView<Upper>()
|
||||
.solveInPlace(c.corner(TopLeft, nonzero_pivots, c.cols()));
|
||||
|
||||
|
||||
@ -461,7 +461,7 @@ struct ei_solve_retval<ColPivHouseholderQR<_MatrixType>, Rhs>
|
||||
d.corner(TopLeft, nonzero_pivots, c.cols())
|
||||
= dec().matrixQR()
|
||||
.corner(TopLeft, nonzero_pivots, nonzero_pivots)
|
||||
.template triangularView<UpperTriangular>()
|
||||
.template triangularView<Upper>()
|
||||
* c.corner(TopLeft, nonzero_pivots, c.cols());
|
||||
|
||||
for(int i = 0; i < nonzero_pivots; ++i) dst.row(dec().colsPermutation().indices().coeff(i)) = c.row(i);
|
||||
|
||||
@ -376,7 +376,7 @@ struct ei_solve_retval<FullPivHouseholderQR<_MatrixType>, Rhs>
|
||||
}
|
||||
dec().matrixQR()
|
||||
.corner(TopLeft, dec().rank(), dec().rank())
|
||||
.template triangularView<UpperTriangular>()
|
||||
.template triangularView<Upper>()
|
||||
.solveInPlace(c.corner(TopLeft, dec().rank(), c.cols()));
|
||||
|
||||
for(int i = 0; i < dec().rank(); ++i) dst.row(dec().colsPermutation().indices().coeff(i)) = c.row(i);
|
||||
|
||||
@ -231,7 +231,7 @@ struct ei_solve_retval<HouseholderQR<_MatrixType>, Rhs>
|
||||
|
||||
dec().matrixQR()
|
||||
.corner(TopLeft, rank, rank)
|
||||
.template triangularView<UpperTriangular>()
|
||||
.template triangularView<Upper>()
|
||||
.solveInPlace(c.corner(TopLeft, rank, c.cols()));
|
||||
|
||||
dst.corner(TopLeft, rank, c.cols()) = c.corner(TopLeft, rank, c.cols());
|
||||
|
||||
@ -234,7 +234,7 @@ struct ei_svd_precondition_if_more_rows_than_cols<MatrixType, Options, true>
|
||||
if(rows > cols)
|
||||
{
|
||||
FullPivHouseholderQR<MatrixType> qr(matrix);
|
||||
work_matrix = qr.matrixQR().block(0,0,diagSize,diagSize).template triangularView<UpperTriangular>();
|
||||
work_matrix = qr.matrixQR().block(0,0,diagSize,diagSize).template triangularView<Upper>();
|
||||
if(ComputeU) svd.m_matrixU = qr.matrixQ();
|
||||
if(ComputeV) svd.m_matrixV = qr.colsPermutation();
|
||||
|
||||
@ -278,7 +278,7 @@ struct ei_svd_precondition_if_more_cols_than_rows<MatrixType, Options, true>
|
||||
MatrixOptions,MaxColsAtCompileTime,MaxRowsAtCompileTime>
|
||||
TransposeTypeWithSameStorageOrder;
|
||||
FullPivHouseholderQR<TransposeTypeWithSameStorageOrder> qr(matrix.adjoint());
|
||||
work_matrix = qr.matrixQR().block(0,0,diagSize,diagSize).template triangularView<UpperTriangular>().adjoint();
|
||||
work_matrix = qr.matrixQR().block(0,0,diagSize,diagSize).template triangularView<Upper>().adjoint();
|
||||
if(ComputeV) svd.m_matrixV = qr.matrixQ();
|
||||
if(ComputeU) svd.m_matrixU = qr.colsPermutation();
|
||||
return true;
|
||||
|
||||
@ -76,9 +76,9 @@ cholmod_sparse SparseMatrixBase<Derived>::asCholmodMatrix()
|
||||
|
||||
if (Derived::Flags & SelfAdjoint)
|
||||
{
|
||||
if (Derived::Flags & UpperTriangular)
|
||||
if (Derived::Flags & Upper)
|
||||
res.stype = 1;
|
||||
else if (Derived::Flags & LowerTriangular)
|
||||
else if (Derived::Flags & Lower)
|
||||
res.stype = -1;
|
||||
else
|
||||
res.stype = 0;
|
||||
|
||||
@ -179,8 +179,8 @@ class RandomSetter
|
||||
SwapStorage = 1 - MapTraits<ScalarWrapper>::IsSorted,
|
||||
TargetRowMajor = (SparseMatrixType::Flags & RowMajorBit) ? 1 : 0,
|
||||
SetterRowMajor = SwapStorage ? 1-TargetRowMajor : TargetRowMajor,
|
||||
IsUpperTriangular = SparseMatrixType::Flags & UpperTriangularBit,
|
||||
IsLowerTriangular = SparseMatrixType::Flags & LowerTriangularBit
|
||||
IsUpper = SparseMatrixType::Flags & Upper,
|
||||
IsLower = SparseMatrixType::Flags & Lower
|
||||
};
|
||||
|
||||
public:
|
||||
@ -303,8 +303,8 @@ class RandomSetter
|
||||
/** \returns a reference to the coefficient at given coordinates \a row, \a col */
|
||||
Scalar& operator() (int row, int col)
|
||||
{
|
||||
ei_assert(((!IsUpperTriangular) || (row<=col)) && "Invalid access to an upper triangular matrix");
|
||||
ei_assert(((!IsLowerTriangular) || (col<=row)) && "Invalid access to an upper triangular matrix");
|
||||
ei_assert(((!IsUpper) || (row<=col)) && "Invalid access to an upper triangular matrix");
|
||||
ei_assert(((!IsLower) || (col<=row)) && "Invalid access to an upper triangular matrix");
|
||||
const int outer = SetterRowMajor ? row : col;
|
||||
const int inner = SetterRowMajor ? col : row;
|
||||
const int outerMajor = outer >> OuterPacketBits; // index of the packet/map
|
||||
|
||||
@ -333,12 +333,12 @@ bool SparseLDLT<MatrixType, Backend>::solveInPlace(MatrixBase<Derived> &b) const
|
||||
return false;
|
||||
|
||||
if (m_matrix.nonZeros()>0) // otherwise L==I
|
||||
m_matrix.template triangularView<UnitLowerTriangular>().solveInPlace(b);
|
||||
m_matrix.template triangularView<UnitLower>().solveInPlace(b);
|
||||
b = b.cwiseQuotient(m_diag);
|
||||
// FIXME should be .adjoint() but it fails to compile...
|
||||
|
||||
if (m_matrix.nonZeros()>0) // otherwise L==I
|
||||
m_matrix.transpose().template triangularView<UnitUpperTriangular>().solveInPlace(b);
|
||||
m_matrix.transpose().template triangularView<UnitUpper>().solveInPlace(b);
|
||||
|
||||
return true;
|
||||
}
|
||||
|
||||
@ -41,7 +41,7 @@ class SparseLLT
|
||||
protected:
|
||||
typedef typename MatrixType::Scalar Scalar;
|
||||
typedef typename NumTraits<typename MatrixType::Scalar>::Real RealScalar;
|
||||
typedef SparseMatrix<Scalar,LowerTriangular> CholMatrixType;
|
||||
typedef SparseMatrix<Scalar> CholMatrixType;
|
||||
|
||||
enum {
|
||||
SupernodalFactorIsDirty = 0x10000,
|
||||
@ -193,15 +193,15 @@ bool SparseLLT<MatrixType, Backend>::solveInPlace(MatrixBase<Derived> &b) const
|
||||
const int size = m_matrix.rows();
|
||||
ei_assert(size==b.rows());
|
||||
|
||||
m_matrix.template triangularView<LowerTriangular>().solveInPlace(b);
|
||||
m_matrix.template triangularView<Lower>().solveInPlace(b);
|
||||
// FIXME should be simply .adjoint() but it fails to compile...
|
||||
if (NumTraits<Scalar>::IsComplex)
|
||||
{
|
||||
CholMatrixType aux = m_matrix.conjugate();
|
||||
aux.transpose().template triangularView<UpperTriangular>().solveInPlace(b);
|
||||
aux.transpose().template triangularView<Upper>().solveInPlace(b);
|
||||
}
|
||||
else
|
||||
m_matrix.transpose().template triangularView<UpperTriangular>().solveInPlace(b);
|
||||
m_matrix.transpose().template triangularView<Upper>().solveInPlace(b);
|
||||
|
||||
return true;
|
||||
}
|
||||
|
||||
@ -47,7 +47,7 @@ class SparseLU
|
||||
protected:
|
||||
typedef typename MatrixType::Scalar Scalar;
|
||||
typedef typename NumTraits<typename MatrixType::Scalar>::Real RealScalar;
|
||||
typedef SparseMatrix<Scalar,LowerTriangular> LUMatrixType;
|
||||
typedef SparseMatrix<Scalar> LUMatrixType;
|
||||
|
||||
enum {
|
||||
MatrixLUIsDirty = 0x10000
|
||||
|
||||
@ -532,8 +532,8 @@ template<typename Derived> class SparseMatrixBase : public AnyMatrixBase<Derived
|
||||
// bool isIdentity(RealScalar prec = dummy_precision<Scalar>()) const;
|
||||
// bool isDiagonal(RealScalar prec = dummy_precision<Scalar>()) const;
|
||||
|
||||
// bool isUpperTriangular(RealScalar prec = dummy_precision<Scalar>()) const;
|
||||
// bool isLowerTriangular(RealScalar prec = dummy_precision<Scalar>()) const;
|
||||
// bool isUpper(RealScalar prec = dummy_precision<Scalar>()) const;
|
||||
// bool isLower(RealScalar prec = dummy_precision<Scalar>()) const;
|
||||
|
||||
// template<typename OtherDerived>
|
||||
// bool isOrthogonal(const MatrixBase<OtherDerived>& other,
|
||||
|
||||
@ -31,7 +31,7 @@
|
||||
* \brief Pseudo expression to manipulate a triangular sparse matrix as a selfadjoint matrix.
|
||||
*
|
||||
* \param MatrixType the type of the dense matrix storing the coefficients
|
||||
* \param UpLo can be either \c LowerTriangular or \c UpperTriangular
|
||||
* \param UpLo can be either \c Lower or \c Upper
|
||||
*
|
||||
* This class is an expression of a sefladjoint matrix from a triangular part of a matrix
|
||||
* with given dense storage of the coefficients. It is the return type of MatrixBase::selfadjointView()
|
||||
@ -168,9 +168,9 @@ class SparseSelfAdjointTimeDenseProduct
|
||||
enum {
|
||||
LhsIsRowMajor = (_Lhs::Flags&RowMajorBit)==RowMajorBit,
|
||||
ProcessFirstHalf =
|
||||
((UpLo&(UpperTriangularBit|LowerTriangularBit))==(UpperTriangularBit|LowerTriangularBit))
|
||||
|| ( (UpLo&UpperTriangularBit) && !LhsIsRowMajor)
|
||||
|| ( (UpLo&LowerTriangularBit) && LhsIsRowMajor),
|
||||
((UpLo&(Upper|Lower))==(Upper|Lower))
|
||||
|| ( (UpLo&Upper) && !LhsIsRowMajor)
|
||||
|| ( (UpLo&Lower) && LhsIsRowMajor),
|
||||
ProcessSecondHalf = !ProcessFirstHalf
|
||||
};
|
||||
for (int j=0; j<m_lhs.outerSize(); ++j)
|
||||
|
||||
@ -33,8 +33,8 @@ struct ei_traits<SparseTriangularView<MatrixType,Mode> >
|
||||
template<typename MatrixType, int Mode> class SparseTriangularView
|
||||
: public SparseMatrixBase<SparseTriangularView<MatrixType,Mode> >
|
||||
{
|
||||
enum { SkipFirst = (Mode==LowerTriangular && !(MatrixType::Flags&RowMajorBit))
|
||||
|| (Mode==UpperTriangular && (MatrixType::Flags&RowMajorBit)) };
|
||||
enum { SkipFirst = (Mode==Lower && !(MatrixType::Flags&RowMajorBit))
|
||||
|| (Mode==Upper && (MatrixType::Flags&RowMajorBit)) };
|
||||
public:
|
||||
|
||||
class InnerIterator;
|
||||
|
||||
@ -193,9 +193,9 @@ struct SluMatrix : SuperMatrix
|
||||
res.setScalarType<typename MatrixType::Scalar>();
|
||||
|
||||
// FIXME the following is not very accurate
|
||||
if (MatrixType::Flags & UpperTriangular)
|
||||
if (MatrixType::Flags & Upper)
|
||||
res.Mtype = SLU_TRU;
|
||||
if (MatrixType::Flags & LowerTriangular)
|
||||
if (MatrixType::Flags & Lower)
|
||||
res.Mtype = SLU_TRL;
|
||||
if (MatrixType::Flags & SelfAdjoint)
|
||||
ei_assert(false && "SelfAdjoint matrix shape not supported by SuperLU");
|
||||
@ -251,9 +251,9 @@ struct SluMatrixMapHelper<SparseMatrixBase<Derived> >
|
||||
res.setScalarType<typename MatrixType::Scalar>();
|
||||
|
||||
// FIXME the following is not very accurate
|
||||
if (MatrixType::Flags & UpperTriangular)
|
||||
if (MatrixType::Flags & Upper)
|
||||
res.Mtype = SLU_TRU;
|
||||
if (MatrixType::Flags & LowerTriangular)
|
||||
if (MatrixType::Flags & Lower)
|
||||
res.Mtype = SLU_TRL;
|
||||
if (MatrixType::Flags & SelfAdjoint)
|
||||
ei_assert(false && "SelfAdjoint matrix shape not supported by SuperLU");
|
||||
@ -298,8 +298,8 @@ class SparseLU<MatrixType,SuperLU> : public SparseLU<MatrixType>
|
||||
typedef Matrix<Scalar,Dynamic,1> Vector;
|
||||
typedef Matrix<int, 1, MatrixType::ColsAtCompileTime> IntRowVectorType;
|
||||
typedef Matrix<int, MatrixType::RowsAtCompileTime, 1> IntColVectorType;
|
||||
typedef SparseMatrix<Scalar,LowerTriangular|UnitDiagBit> LMatrixType;
|
||||
typedef SparseMatrix<Scalar,UpperTriangular> UMatrixType;
|
||||
typedef SparseMatrix<Scalar,Lower|UnitDiag> LMatrixType;
|
||||
typedef SparseMatrix<Scalar,Upper> UMatrixType;
|
||||
using Base::m_flags;
|
||||
using Base::m_status;
|
||||
|
||||
|
||||
@ -50,13 +50,13 @@ taucs_ccs_matrix SparseMatrixBase<Derived>::asTaucsMatrix()
|
||||
ei_assert(false && "Scalar type not supported by TAUCS");
|
||||
}
|
||||
|
||||
if (Flags & UpperTriangular)
|
||||
if (Flags & Upper)
|
||||
res.flags |= TAUCS_UPPER;
|
||||
if (Flags & LowerTriangular)
|
||||
if (Flags & Lower)
|
||||
res.flags |= TAUCS_LOWER;
|
||||
if (Flags & SelfAdjoint)
|
||||
res.flags |= (NumTraits<Scalar>::IsComplex ? TAUCS_HERMITIAN : TAUCS_SYMMETRIC);
|
||||
else if ((Flags & UpperTriangular) || (Flags & LowerTriangular))
|
||||
else if ((Flags & Upper) || (Flags & Lower))
|
||||
res.flags |= TAUCS_TRIANGULAR;
|
||||
|
||||
return res;
|
||||
|
||||
@ -26,17 +26,17 @@
|
||||
#define EIGEN_SPARSETRIANGULARSOLVER_H
|
||||
|
||||
template<typename Lhs, typename Rhs, int Mode,
|
||||
int UpLo = (Mode & LowerTriangularBit)
|
||||
? LowerTriangular
|
||||
: (Mode & UpperTriangularBit)
|
||||
? UpperTriangular
|
||||
int UpLo = (Mode & Lower)
|
||||
? Lower
|
||||
: (Mode & Upper)
|
||||
? Upper
|
||||
: -1,
|
||||
int StorageOrder = int(ei_traits<Lhs>::Flags) & RowMajorBit>
|
||||
struct ei_sparse_solve_triangular_selector;
|
||||
|
||||
// forward substitution, row-major
|
||||
template<typename Lhs, typename Rhs, int Mode>
|
||||
struct ei_sparse_solve_triangular_selector<Lhs,Rhs,Mode,LowerTriangular,RowMajor>
|
||||
struct ei_sparse_solve_triangular_selector<Lhs,Rhs,Mode,Lower,RowMajor>
|
||||
{
|
||||
typedef typename Rhs::Scalar Scalar;
|
||||
static void run(const Lhs& lhs, Rhs& other)
|
||||
@ -56,7 +56,7 @@ struct ei_sparse_solve_triangular_selector<Lhs,Rhs,Mode,LowerTriangular,RowMajor
|
||||
break;
|
||||
tmp -= lastVal * other.coeff(lastIndex,col);
|
||||
}
|
||||
if (Mode & UnitDiagBit)
|
||||
if (Mode & UnitDiag)
|
||||
other.coeffRef(i,col) = tmp;
|
||||
else
|
||||
{
|
||||
@ -70,7 +70,7 @@ struct ei_sparse_solve_triangular_selector<Lhs,Rhs,Mode,LowerTriangular,RowMajor
|
||||
|
||||
// backward substitution, row-major
|
||||
template<typename Lhs, typename Rhs, int Mode>
|
||||
struct ei_sparse_solve_triangular_selector<Lhs,Rhs,Mode,UpperTriangular,RowMajor>
|
||||
struct ei_sparse_solve_triangular_selector<Lhs,Rhs,Mode,Upper,RowMajor>
|
||||
{
|
||||
typedef typename Rhs::Scalar Scalar;
|
||||
static void run(const Lhs& lhs, Rhs& other)
|
||||
@ -88,7 +88,7 @@ struct ei_sparse_solve_triangular_selector<Lhs,Rhs,Mode,UpperTriangular,RowMajor
|
||||
tmp -= it.value() * other.coeff(it.index(),col);
|
||||
}
|
||||
|
||||
if (Mode & UnitDiagBit)
|
||||
if (Mode & UnitDiag)
|
||||
other.coeffRef(i,col) = tmp;
|
||||
else
|
||||
{
|
||||
@ -103,7 +103,7 @@ struct ei_sparse_solve_triangular_selector<Lhs,Rhs,Mode,UpperTriangular,RowMajor
|
||||
|
||||
// forward substitution, col-major
|
||||
template<typename Lhs, typename Rhs, int Mode>
|
||||
struct ei_sparse_solve_triangular_selector<Lhs,Rhs,Mode,LowerTriangular,ColMajor>
|
||||
struct ei_sparse_solve_triangular_selector<Lhs,Rhs,Mode,Lower,ColMajor>
|
||||
{
|
||||
typedef typename Rhs::Scalar Scalar;
|
||||
static void run(const Lhs& lhs, Rhs& other)
|
||||
@ -116,7 +116,7 @@ struct ei_sparse_solve_triangular_selector<Lhs,Rhs,Mode,LowerTriangular,ColMajor
|
||||
if (tmp!=Scalar(0)) // optimization when other is actually sparse
|
||||
{
|
||||
typename Lhs::InnerIterator it(lhs, i);
|
||||
if(!(Mode & UnitDiagBit))
|
||||
if(!(Mode & UnitDiag))
|
||||
{
|
||||
ei_assert(it.index()==i);
|
||||
tmp /= it.value();
|
||||
@ -133,7 +133,7 @@ struct ei_sparse_solve_triangular_selector<Lhs,Rhs,Mode,LowerTriangular,ColMajor
|
||||
|
||||
// backward substitution, col-major
|
||||
template<typename Lhs, typename Rhs, int Mode>
|
||||
struct ei_sparse_solve_triangular_selector<Lhs,Rhs,Mode,UpperTriangular,ColMajor>
|
||||
struct ei_sparse_solve_triangular_selector<Lhs,Rhs,Mode,Upper,ColMajor>
|
||||
{
|
||||
typedef typename Rhs::Scalar Scalar;
|
||||
static void run(const Lhs& lhs, Rhs& other)
|
||||
@ -145,7 +145,7 @@ struct ei_sparse_solve_triangular_selector<Lhs,Rhs,Mode,UpperTriangular,ColMajor
|
||||
Scalar& tmp = other.coeffRef(i,col);
|
||||
if (tmp!=Scalar(0)) // optimization when other is actually sparse
|
||||
{
|
||||
if(!(Mode & UnitDiagBit))
|
||||
if(!(Mode & UnitDiag))
|
||||
{
|
||||
// FIXME lhs.coeff(i,i) might not be always efficient while it must simply be the
|
||||
// last element of the column !
|
||||
@ -166,8 +166,8 @@ void SparseTriangularView<ExpressionType,Mode>::solveInPlace(MatrixBase<OtherDer
|
||||
{
|
||||
ei_assert(m_matrix.cols() == m_matrix.rows());
|
||||
ei_assert(m_matrix.cols() == other.rows());
|
||||
ei_assert(!(Mode & ZeroDiagBit));
|
||||
ei_assert(Mode & (UpperTriangularBit|LowerTriangularBit));
|
||||
ei_assert(!(Mode & ZeroDiag));
|
||||
ei_assert(Mode & (Upper|Lower));
|
||||
|
||||
enum { copy = ei_traits<OtherDerived>::Flags & RowMajorBit };
|
||||
|
||||
@ -194,10 +194,10 @@ SparseTriangularView<ExpressionType,Mode>::solve(const MatrixBase<OtherDerived>&
|
||||
// pure sparse path
|
||||
|
||||
template<typename Lhs, typename Rhs, int Mode,
|
||||
int UpLo = (Mode & LowerTriangularBit)
|
||||
? LowerTriangular
|
||||
: (Mode & UpperTriangularBit)
|
||||
? UpperTriangular
|
||||
int UpLo = (Mode & Lower)
|
||||
? Lower
|
||||
: (Mode & Upper)
|
||||
? Upper
|
||||
: -1,
|
||||
int StorageOrder = int(Lhs::Flags) & (RowMajorBit)>
|
||||
struct ei_sparse_solve_triangular_sparse_selector;
|
||||
@ -209,7 +209,7 @@ struct ei_sparse_solve_triangular_sparse_selector<Lhs,Rhs,Mode,UpLo,ColMajor>
|
||||
typedef typename Rhs::Scalar Scalar;
|
||||
static void run(const Lhs& lhs, Rhs& other)
|
||||
{
|
||||
const bool IsLowerTriangular = (UpLo==LowerTriangular);
|
||||
const bool IsLower = (UpLo==Lower);
|
||||
AmbiVector<Scalar> tempVector(other.rows()*2);
|
||||
tempVector.setBounds(0,other.rows());
|
||||
|
||||
@ -227,9 +227,9 @@ struct ei_sparse_solve_triangular_sparse_selector<Lhs,Rhs,Mode,UpLo,ColMajor>
|
||||
tempVector.coeffRef(rhsIt.index()) = rhsIt.value();
|
||||
}
|
||||
|
||||
for(int i=IsLowerTriangular?0:lhs.cols()-1;
|
||||
IsLowerTriangular?i<lhs.cols():i>=0;
|
||||
i+=IsLowerTriangular?1:-1)
|
||||
for(int i=IsLower?0:lhs.cols()-1;
|
||||
IsLower?i<lhs.cols():i>=0;
|
||||
i+=IsLower?1:-1)
|
||||
{
|
||||
tempVector.restart();
|
||||
Scalar& ci = tempVector.coeffRef(i);
|
||||
@ -237,9 +237,9 @@ struct ei_sparse_solve_triangular_sparse_selector<Lhs,Rhs,Mode,UpLo,ColMajor>
|
||||
{
|
||||
// find
|
||||
typename Lhs::InnerIterator it(lhs, i);
|
||||
if(!(Mode & UnitDiagBit))
|
||||
if(!(Mode & UnitDiag))
|
||||
{
|
||||
if (IsLowerTriangular)
|
||||
if (IsLower)
|
||||
{
|
||||
ei_assert(it.index()==i);
|
||||
ci /= it.value();
|
||||
@ -248,7 +248,7 @@ struct ei_sparse_solve_triangular_sparse_selector<Lhs,Rhs,Mode,UpLo,ColMajor>
|
||||
ci /= lhs.coeff(i,i);
|
||||
}
|
||||
tempVector.restart();
|
||||
if (IsLowerTriangular)
|
||||
if (IsLower)
|
||||
{
|
||||
if (it.index()==i)
|
||||
++it;
|
||||
@ -287,8 +287,8 @@ void SparseTriangularView<ExpressionType,Mode>::solveInPlace(SparseMatrixBase<Ot
|
||||
{
|
||||
ei_assert(m_matrix.cols() == m_matrix.rows());
|
||||
ei_assert(m_matrix.cols() == other.rows());
|
||||
ei_assert(!(Mode & ZeroDiagBit));
|
||||
ei_assert(Mode & (UpperTriangularBit|LowerTriangularBit));
|
||||
ei_assert(!(Mode & ZeroDiag));
|
||||
ei_assert(Mode & (Upper|Lower));
|
||||
|
||||
// enum { copy = ei_traits<OtherDerived>::Flags & RowMajorBit };
|
||||
|
||||
@ -311,7 +311,7 @@ template<typename Derived>
|
||||
template<typename OtherDerived>
|
||||
void SparseMatrixBase<Derived>::solveTriangularInPlace(MatrixBase<OtherDerived>& other) const
|
||||
{
|
||||
this->template triangular<Flags&(UpperTriangularBit|LowerTriangularBit)>().solveInPlace(other);
|
||||
this->template triangular<Flags&(Upper|Lower)>().solveInPlace(other);
|
||||
}
|
||||
|
||||
/** \deprecated */
|
||||
|
||||
@ -127,8 +127,8 @@ class SparseLU<MatrixType,UmfPack> : public SparseLU<MatrixType>
|
||||
typedef Matrix<Scalar,Dynamic,1> Vector;
|
||||
typedef Matrix<int, 1, MatrixType::ColsAtCompileTime> IntRowVectorType;
|
||||
typedef Matrix<int, MatrixType::RowsAtCompileTime, 1> IntColVectorType;
|
||||
typedef SparseMatrix<Scalar,LowerTriangular|UnitDiagBit> LMatrixType;
|
||||
typedef SparseMatrix<Scalar,UpperTriangular> UMatrixType;
|
||||
typedef SparseMatrix<Scalar,Lower|UnitDiagBit> LMatrixType;
|
||||
typedef SparseMatrix<Scalar,Upper> UMatrixType;
|
||||
using Base::m_flags;
|
||||
using Base::m_status;
|
||||
|
||||
|
||||
@ -29,13 +29,30 @@ vec.head(length)
|
||||
vec.head<length>()
|
||||
vec.tail(length)
|
||||
vec.tail<length>()
|
||||
\endcode</td><td>This is a simple search and replace change.</td></tr>
|
||||
\endcode</td><td>Trivial "search and replace".</td></tr>
|
||||
<tr><td colspan="3"></td></tr>
|
||||
<tr><td>\code mat.cwise().XXX()\endcode</td><td>\code mat.array().XXX()\endcode</td><td>See \ref CoefficientWiseOperations. </td></tr>
|
||||
<tr><td colspan="3"></td></tr>
|
||||
<tr><td>\code c = (a * b).lazy();\endcode</td><td>\code c.noalias() = a * b;\endcode</td><td>See \ref LazyVsNoalias. </td></tr>
|
||||
<tr><td colspan="3"></td></tr>
|
||||
<tr><td>\code A.triangularSolveInPlace<XXX>(X);\endcode</td><td>\code A.triangularView<XXX>().solveInPlace(X);\endcode</td><td></td></tr>
|
||||
<tr><td colspan="3"></td></tr>
|
||||
<tr><td>\code
|
||||
UpperTriangular
|
||||
LowerTriangular
|
||||
UnitUpperTriangular
|
||||
UnitLowerTriangular
|
||||
StrictlyUpperTriangular
|
||||
StrictlyLowerTriangular
|
||||
\endcode</td><td>\code
|
||||
Upper
|
||||
Lower
|
||||
UnitUpper
|
||||
UnitLower
|
||||
StrictlyUpper
|
||||
StrictlyLower
|
||||
\endcode</td>
|
||||
<td>Trivial "search and replace".</td></tr>
|
||||
</table>
|
||||
|
||||
\section CoefficientWiseOperations Coefficient wise operations
|
||||
|
||||
@ -64,8 +64,8 @@ template<typename MatrixType> void bandmatrix(const MatrixType& _m)
|
||||
int a = std::max(0,cols-d-supers);
|
||||
int b = std::max(0,rows-d-subs);
|
||||
if(a>0) dm1.block(0,d+supers,rows,a).setZero();
|
||||
dm1.block(0,supers+1,cols-supers-1-a,cols-supers-1-a).template triangularView<UpperTriangular>().setZero();
|
||||
dm1.block(subs+1,0,rows-subs-1-b,rows-subs-1-b).template triangularView<LowerTriangular>().setZero();
|
||||
dm1.block(0,supers+1,cols-supers-1-a,cols-supers-1-a).template triangularView<Upper>().setZero();
|
||||
dm1.block(subs+1,0,rows-subs-1-b,rows-subs-1-b).template triangularView<Lower>().setZero();
|
||||
if(b>0) dm1.block(d+subs,0,b,cols).setZero();
|
||||
//std::cerr << m.m_data << "\n\n" << m.toDense() << "\n\n" << dm1 << "\n\n";
|
||||
VERIFY_IS_APPROX(dm1,m.toDenseMatrix());
|
||||
|
||||
@ -58,12 +58,12 @@ template<typename MatrixType> void cholesky(const MatrixType& m)
|
||||
symm += a1 * a1.adjoint();
|
||||
}
|
||||
|
||||
SquareMatrixType symmUp = symm.template triangularView<UpperTriangular>();
|
||||
SquareMatrixType symmLo = symm.template triangularView<LowerTriangular>();
|
||||
SquareMatrixType symmUp = symm.template triangularView<Upper>();
|
||||
SquareMatrixType symmLo = symm.template triangularView<Lower>();
|
||||
|
||||
// to test if really Cholesky only uses the upper triangular part, uncomment the following
|
||||
// FIXME: currently that fails !!
|
||||
//symm.template part<StrictlyLowerTriangular>().setZero();
|
||||
//symm.template part<StrictlyLower>().setZero();
|
||||
|
||||
#ifdef HAS_GSL
|
||||
// if (ei_is_same_type<RealScalar,double>::ret)
|
||||
@ -94,7 +94,7 @@ template<typename MatrixType> void cholesky(const MatrixType& m)
|
||||
#endif
|
||||
|
||||
{
|
||||
LLT<SquareMatrixType,LowerTriangular> chollo(symmLo);
|
||||
LLT<SquareMatrixType,Lower> chollo(symmLo);
|
||||
VERIFY_IS_APPROX(symm, chollo.matrixL().toDenseMatrix() * chollo.matrixL().adjoint().toDenseMatrix());
|
||||
vecX = chollo.solve(vecB);
|
||||
VERIFY_IS_APPROX(symm * vecX, vecB);
|
||||
@ -102,7 +102,7 @@ template<typename MatrixType> void cholesky(const MatrixType& m)
|
||||
VERIFY_IS_APPROX(symm * matX, matB);
|
||||
|
||||
// test the upper mode
|
||||
LLT<SquareMatrixType,UpperTriangular> cholup(symmUp);
|
||||
LLT<SquareMatrixType,Upper> cholup(symmUp);
|
||||
VERIFY_IS_APPROX(symm, cholup.matrixL().toDenseMatrix() * cholup.matrixL().adjoint().toDenseMatrix());
|
||||
vecX = cholup.solve(vecB);
|
||||
VERIFY_IS_APPROX(symm * vecX, vecB);
|
||||
|
||||
@ -85,31 +85,31 @@ template<typename MatrixType> void product_notemporary(const MatrixType& m)
|
||||
// NOTE this is because the Block expression is not handled yet by our expression analyser
|
||||
VERIFY_EVALUATION_COUNT(( m3.block(r0,r0,r1,r1).noalias() = s1 * m1.block(r0,c0,r1,c1) * (s1*m2).block(c0,r0,c1,r1) ), 1);
|
||||
|
||||
VERIFY_EVALUATION_COUNT( m3.noalias() -= (s1 * m1).template triangularView<LowerTriangular>() * m2, 0);
|
||||
VERIFY_EVALUATION_COUNT( rm3.noalias() = (s1 * m1.adjoint()).template triangularView<UpperTriangular>() * (m2+m2), 1);
|
||||
VERIFY_EVALUATION_COUNT( rm3.noalias() = (s1 * m1.adjoint()).template triangularView<UnitUpperTriangular>() * m2.adjoint(), 0);
|
||||
VERIFY_EVALUATION_COUNT( m3.noalias() -= (s1 * m1).template triangularView<Lower>() * m2, 0);
|
||||
VERIFY_EVALUATION_COUNT( rm3.noalias() = (s1 * m1.adjoint()).template triangularView<Upper>() * (m2+m2), 1);
|
||||
VERIFY_EVALUATION_COUNT( rm3.noalias() = (s1 * m1.adjoint()).template triangularView<UnitUpper>() * m2.adjoint(), 0);
|
||||
|
||||
VERIFY_EVALUATION_COUNT( rm3.col(c0).noalias() = (s1 * m1.adjoint()).template triangularView<UnitUpperTriangular>() * (s2*m2.row(c0)).adjoint(), 0);
|
||||
VERIFY_EVALUATION_COUNT( rm3.col(c0).noalias() = (s1 * m1.adjoint()).template triangularView<UnitUpper>() * (s2*m2.row(c0)).adjoint(), 0);
|
||||
|
||||
VERIFY_EVALUATION_COUNT( m1.template triangularView<LowerTriangular>().solveInPlace(m3), 0);
|
||||
VERIFY_EVALUATION_COUNT( m1.adjoint().template triangularView<LowerTriangular>().solveInPlace(m3.transpose()), 0);
|
||||
VERIFY_EVALUATION_COUNT( m1.template triangularView<Lower>().solveInPlace(m3), 0);
|
||||
VERIFY_EVALUATION_COUNT( m1.adjoint().template triangularView<Lower>().solveInPlace(m3.transpose()), 0);
|
||||
|
||||
VERIFY_EVALUATION_COUNT( m3.noalias() -= (s1 * m1).adjoint().template selfadjointView<LowerTriangular>() * (-m2*s3).adjoint(), 0);
|
||||
VERIFY_EVALUATION_COUNT( m3.noalias() = s2 * m2.adjoint() * (s1 * m1.adjoint()).template selfadjointView<UpperTriangular>(), 0);
|
||||
VERIFY_EVALUATION_COUNT( rm3.noalias() = (s1 * m1.adjoint()).template selfadjointView<LowerTriangular>() * m2.adjoint(), 0);
|
||||
VERIFY_EVALUATION_COUNT( m3.noalias() -= (s1 * m1).adjoint().template selfadjointView<Lower>() * (-m2*s3).adjoint(), 0);
|
||||
VERIFY_EVALUATION_COUNT( m3.noalias() = s2 * m2.adjoint() * (s1 * m1.adjoint()).template selfadjointView<Upper>(), 0);
|
||||
VERIFY_EVALUATION_COUNT( rm3.noalias() = (s1 * m1.adjoint()).template selfadjointView<Lower>() * m2.adjoint(), 0);
|
||||
|
||||
VERIFY_EVALUATION_COUNT( m3.col(c0).noalias() = (s1 * m1).adjoint().template selfadjointView<LowerTriangular>() * (-m2.row(c0)*s3).adjoint(), 0);
|
||||
VERIFY_EVALUATION_COUNT( m3.col(c0).noalias() -= (s1 * m1).adjoint().template selfadjointView<UpperTriangular>() * (-m2.row(c0)*s3).adjoint(), 0);
|
||||
VERIFY_EVALUATION_COUNT( m3.col(c0).noalias() = (s1 * m1).adjoint().template selfadjointView<Lower>() * (-m2.row(c0)*s3).adjoint(), 0);
|
||||
VERIFY_EVALUATION_COUNT( m3.col(c0).noalias() -= (s1 * m1).adjoint().template selfadjointView<Upper>() * (-m2.row(c0)*s3).adjoint(), 0);
|
||||
|
||||
VERIFY_EVALUATION_COUNT( m3.block(r0,c0,r1,c1).noalias() += m1.block(r0,r0,r1,r1).template selfadjointView<UpperTriangular>() * (s1*m2.block(r0,c0,r1,c1)), 0);
|
||||
VERIFY_EVALUATION_COUNT( m3.block(r0,c0,r1,c1).noalias() = m1.block(r0,r0,r1,r1).template selfadjointView<UpperTriangular>() * m2.block(r0,c0,r1,c1), 0);
|
||||
VERIFY_EVALUATION_COUNT( m3.block(r0,c0,r1,c1).noalias() += m1.block(r0,r0,r1,r1).template selfadjointView<Upper>() * (s1*m2.block(r0,c0,r1,c1)), 0);
|
||||
VERIFY_EVALUATION_COUNT( m3.block(r0,c0,r1,c1).noalias() = m1.block(r0,r0,r1,r1).template selfadjointView<Upper>() * m2.block(r0,c0,r1,c1), 0);
|
||||
|
||||
VERIFY_EVALUATION_COUNT( m3.template selfadjointView<LowerTriangular>().rankUpdate(m2.adjoint()), 0);
|
||||
VERIFY_EVALUATION_COUNT( m3.template selfadjointView<Lower>().rankUpdate(m2.adjoint()), 0);
|
||||
|
||||
m3.resize(1,1);
|
||||
VERIFY_EVALUATION_COUNT( m3.noalias() = m1.block(r0,r0,r1,r1).template selfadjointView<LowerTriangular>() * m2.block(r0,c0,r1,c1), 0);
|
||||
VERIFY_EVALUATION_COUNT( m3.noalias() = m1.block(r0,r0,r1,r1).template selfadjointView<Lower>() * m2.block(r0,c0,r1,c1), 0);
|
||||
m3.resize(1,1);
|
||||
VERIFY_EVALUATION_COUNT( m3.noalias() = m1.block(r0,r0,r1,r1).template triangularView<UnitUpperTriangular>() * m2.block(r0,c0,r1,c1), 0);
|
||||
VERIFY_EVALUATION_COUNT( m3.noalias() = m1.block(r0,r0,r1,r1).template triangularView<UnitUpper>() * m2.block(r0,c0,r1,c1), 0);
|
||||
}
|
||||
|
||||
void test_product_notemporary()
|
||||
|
||||
@ -53,25 +53,25 @@ template<typename MatrixType> void product_selfadjoint(const MatrixType& m)
|
||||
m1 = (m1.adjoint() + m1).eval();
|
||||
|
||||
// rank2 update
|
||||
m2 = m1.template triangularView<LowerTriangular>();
|
||||
m2.template selfadjointView<LowerTriangular>().rankUpdate(v1,v2);
|
||||
VERIFY_IS_APPROX(m2, (m1 + v1 * v2.adjoint()+ v2 * v1.adjoint()).template triangularView<LowerTriangular>().toDenseMatrix());
|
||||
m2 = m1.template triangularView<Lower>();
|
||||
m2.template selfadjointView<Lower>().rankUpdate(v1,v2);
|
||||
VERIFY_IS_APPROX(m2, (m1 + v1 * v2.adjoint()+ v2 * v1.adjoint()).template triangularView<Lower>().toDenseMatrix());
|
||||
|
||||
m2 = m1.template triangularView<UpperTriangular>();
|
||||
m2.template selfadjointView<UpperTriangular>().rankUpdate(-v1,s2*v2,s3);
|
||||
VERIFY_IS_APPROX(m2, (m1 + (-s2*s3) * (v1 * v2.adjoint()+ v2 * v1.adjoint())).template triangularView<UpperTriangular>().toDenseMatrix());
|
||||
m2 = m1.template triangularView<Upper>();
|
||||
m2.template selfadjointView<Upper>().rankUpdate(-v1,s2*v2,s3);
|
||||
VERIFY_IS_APPROX(m2, (m1 + (-s2*s3) * (v1 * v2.adjoint()+ v2 * v1.adjoint())).template triangularView<Upper>().toDenseMatrix());
|
||||
|
||||
m2 = m1.template triangularView<UpperTriangular>();
|
||||
m2.template selfadjointView<UpperTriangular>().rankUpdate(-r1.adjoint(),r2.adjoint()*s3,s1);
|
||||
VERIFY_IS_APPROX(m2, (m1 + (-s3*s1) * (r1.adjoint() * r2 + r2.adjoint() * r1)).template triangularView<UpperTriangular>().toDenseMatrix());
|
||||
m2 = m1.template triangularView<Upper>();
|
||||
m2.template selfadjointView<Upper>().rankUpdate(-r1.adjoint(),r2.adjoint()*s3,s1);
|
||||
VERIFY_IS_APPROX(m2, (m1 + (-s3*s1) * (r1.adjoint() * r2 + r2.adjoint() * r1)).template triangularView<Upper>().toDenseMatrix());
|
||||
|
||||
if (rows>1)
|
||||
{
|
||||
m2 = m1.template triangularView<LowerTriangular>();
|
||||
m2.block(1,1,rows-1,cols-1).template selfadjointView<LowerTriangular>().rankUpdate(v1.tail(rows-1),v2.head(cols-1));
|
||||
m2 = m1.template triangularView<Lower>();
|
||||
m2.block(1,1,rows-1,cols-1).template selfadjointView<Lower>().rankUpdate(v1.tail(rows-1),v2.head(cols-1));
|
||||
m3 = m1;
|
||||
m3.block(1,1,rows-1,cols-1) += v1.tail(rows-1) * v2.head(cols-1).adjoint()+ v2.head(cols-1) * v1.tail(rows-1).adjoint();
|
||||
VERIFY_IS_APPROX(m2, m3.template triangularView<LowerTriangular>().toDenseMatrix());
|
||||
VERIFY_IS_APPROX(m2, m3.template triangularView<Lower>().toDenseMatrix());
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
@ -28,10 +28,10 @@ template<int OtherSize> struct symm_extra {
|
||||
template<typename M1, typename M2, typename Scalar>
|
||||
static void run(M1& m1, M1& m2, M2& rhs2, M2& rhs22, M2& rhs23, Scalar s1, Scalar s2)
|
||||
{
|
||||
m2 = m1.template triangularView<LowerTriangular>();
|
||||
VERIFY_IS_APPROX(rhs22 = (rhs2) * (m2).template selfadjointView<LowerTriangular>(),
|
||||
m2 = m1.template triangularView<Lower>();
|
||||
VERIFY_IS_APPROX(rhs22 = (rhs2) * (m2).template selfadjointView<Lower>(),
|
||||
rhs23 = (rhs2) * (m1));
|
||||
VERIFY_IS_APPROX(rhs22 = (s2*rhs2) * (s1*m2).template selfadjointView<LowerTriangular>(),
|
||||
VERIFY_IS_APPROX(rhs22 = (s2*rhs2) * (s1*m2).template selfadjointView<Lower>(),
|
||||
rhs23 = (s2*rhs2) * (s1*m1));
|
||||
}
|
||||
};
|
||||
@ -65,38 +65,38 @@ template<typename Scalar, int Size, int OtherSize> void symm(int size = Size, in
|
||||
Scalar s1 = ei_random<Scalar>(),
|
||||
s2 = ei_random<Scalar>();
|
||||
|
||||
m2 = m1.template triangularView<LowerTriangular>();
|
||||
VERIFY_IS_APPROX(rhs12 = (s1*m2).template selfadjointView<LowerTriangular>() * (s2*rhs1),
|
||||
m2 = m1.template triangularView<Lower>();
|
||||
VERIFY_IS_APPROX(rhs12 = (s1*m2).template selfadjointView<Lower>() * (s2*rhs1),
|
||||
rhs13 = (s1*m1) * (s2*rhs1));
|
||||
|
||||
m2 = m1.template triangularView<UpperTriangular>(); rhs12.setRandom(); rhs13 = rhs12;
|
||||
VERIFY_IS_APPROX(rhs12 += (s1*m2).template selfadjointView<UpperTriangular>() * (s2*rhs1),
|
||||
m2 = m1.template triangularView<Upper>(); rhs12.setRandom(); rhs13 = rhs12;
|
||||
VERIFY_IS_APPROX(rhs12 += (s1*m2).template selfadjointView<Upper>() * (s2*rhs1),
|
||||
rhs13 += (s1*m1) * (s2*rhs1));
|
||||
|
||||
m2 = m1.template triangularView<LowerTriangular>();
|
||||
VERIFY_IS_APPROX(rhs12 = (s1*m2).template selfadjointView<LowerTriangular>() * (s2*rhs2.adjoint()),
|
||||
m2 = m1.template triangularView<Lower>();
|
||||
VERIFY_IS_APPROX(rhs12 = (s1*m2).template selfadjointView<Lower>() * (s2*rhs2.adjoint()),
|
||||
rhs13 = (s1*m1) * (s2*rhs2.adjoint()));
|
||||
|
||||
m2 = m1.template triangularView<UpperTriangular>();
|
||||
VERIFY_IS_APPROX(rhs12 = (s1*m2).template selfadjointView<UpperTriangular>() * (s2*rhs2.adjoint()),
|
||||
m2 = m1.template triangularView<Upper>();
|
||||
VERIFY_IS_APPROX(rhs12 = (s1*m2).template selfadjointView<Upper>() * (s2*rhs2.adjoint()),
|
||||
rhs13 = (s1*m1) * (s2*rhs2.adjoint()));
|
||||
|
||||
m2 = m1.template triangularView<UpperTriangular>();
|
||||
VERIFY_IS_APPROX(rhs12 = (s1*m2.adjoint()).template selfadjointView<LowerTriangular>() * (s2*rhs2.adjoint()),
|
||||
m2 = m1.template triangularView<Upper>();
|
||||
VERIFY_IS_APPROX(rhs12 = (s1*m2.adjoint()).template selfadjointView<Lower>() * (s2*rhs2.adjoint()),
|
||||
rhs13 = (s1*m1.adjoint()) * (s2*rhs2.adjoint()));
|
||||
|
||||
// test row major = <...>
|
||||
m2 = m1.template triangularView<LowerTriangular>(); rhs12.setRandom(); rhs13 = rhs12;
|
||||
VERIFY_IS_APPROX(rhs12 -= (s1*m2).template selfadjointView<LowerTriangular>() * (s2*rhs3),
|
||||
m2 = m1.template triangularView<Lower>(); rhs12.setRandom(); rhs13 = rhs12;
|
||||
VERIFY_IS_APPROX(rhs12 -= (s1*m2).template selfadjointView<Lower>() * (s2*rhs3),
|
||||
rhs13 -= (s1*m1) * (s2 * rhs3));
|
||||
|
||||
m2 = m1.template triangularView<UpperTriangular>();
|
||||
VERIFY_IS_APPROX(rhs12 = (s1*m2.adjoint()).template selfadjointView<LowerTriangular>() * (s2*rhs3).conjugate(),
|
||||
m2 = m1.template triangularView<Upper>();
|
||||
VERIFY_IS_APPROX(rhs12 = (s1*m2.adjoint()).template selfadjointView<Lower>() * (s2*rhs3).conjugate(),
|
||||
rhs13 = (s1*m1.adjoint()) * (s2*rhs3).conjugate());
|
||||
|
||||
|
||||
m2 = m1.template triangularView<UpperTriangular>(); rhs13 = rhs12;
|
||||
VERIFY_IS_APPROX(rhs12.noalias() += s1 * ((m2.adjoint()).template selfadjointView<LowerTriangular>() * (s2*rhs3).conjugate()),
|
||||
m2 = m1.template triangularView<Upper>(); rhs13 = rhs12;
|
||||
VERIFY_IS_APPROX(rhs12.noalias() += s1 * ((m2.adjoint()).template selfadjointView<Lower>() * (s2*rhs3).conjugate()),
|
||||
rhs13 += (s1*m1.adjoint()) * (s2*rhs3).conjugate());
|
||||
|
||||
// test matrix * selfadjoint
|
||||
|
||||
@ -45,28 +45,28 @@ template<typename MatrixType> void syrk(const MatrixType& m)
|
||||
Scalar s1 = ei_random<Scalar>();
|
||||
|
||||
m2.setZero();
|
||||
VERIFY_IS_APPROX((m2.template selfadjointView<LowerTriangular>().rankUpdate(rhs2,s1)._expression()),
|
||||
((s1 * rhs2 * rhs2.adjoint()).eval().template triangularView<LowerTriangular>().toDenseMatrix()));
|
||||
VERIFY_IS_APPROX((m2.template selfadjointView<Lower>().rankUpdate(rhs2,s1)._expression()),
|
||||
((s1 * rhs2 * rhs2.adjoint()).eval().template triangularView<Lower>().toDenseMatrix()));
|
||||
|
||||
m2.setZero();
|
||||
VERIFY_IS_APPROX(m2.template selfadjointView<UpperTriangular>().rankUpdate(rhs2,s1)._expression(),
|
||||
(s1 * rhs2 * rhs2.adjoint()).eval().template triangularView<UpperTriangular>().toDenseMatrix());
|
||||
VERIFY_IS_APPROX(m2.template selfadjointView<Upper>().rankUpdate(rhs2,s1)._expression(),
|
||||
(s1 * rhs2 * rhs2.adjoint()).eval().template triangularView<Upper>().toDenseMatrix());
|
||||
|
||||
m2.setZero();
|
||||
VERIFY_IS_APPROX(m2.template selfadjointView<LowerTriangular>().rankUpdate(rhs1.adjoint(),s1)._expression(),
|
||||
(s1 * rhs1.adjoint() * rhs1).eval().template triangularView<LowerTriangular>().toDenseMatrix());
|
||||
VERIFY_IS_APPROX(m2.template selfadjointView<Lower>().rankUpdate(rhs1.adjoint(),s1)._expression(),
|
||||
(s1 * rhs1.adjoint() * rhs1).eval().template triangularView<Lower>().toDenseMatrix());
|
||||
|
||||
m2.setZero();
|
||||
VERIFY_IS_APPROX(m2.template selfadjointView<UpperTriangular>().rankUpdate(rhs1.adjoint(),s1)._expression(),
|
||||
(s1 * rhs1.adjoint() * rhs1).eval().template triangularView<UpperTriangular>().toDenseMatrix());
|
||||
VERIFY_IS_APPROX(m2.template selfadjointView<Upper>().rankUpdate(rhs1.adjoint(),s1)._expression(),
|
||||
(s1 * rhs1.adjoint() * rhs1).eval().template triangularView<Upper>().toDenseMatrix());
|
||||
|
||||
m2.setZero();
|
||||
VERIFY_IS_APPROX(m2.template selfadjointView<LowerTriangular>().rankUpdate(rhs3.adjoint(),s1)._expression(),
|
||||
(s1 * rhs3.adjoint() * rhs3).eval().template triangularView<LowerTriangular>().toDenseMatrix());
|
||||
VERIFY_IS_APPROX(m2.template selfadjointView<Lower>().rankUpdate(rhs3.adjoint(),s1)._expression(),
|
||||
(s1 * rhs3.adjoint() * rhs3).eval().template triangularView<Lower>().toDenseMatrix());
|
||||
|
||||
m2.setZero();
|
||||
VERIFY_IS_APPROX(m2.template selfadjointView<UpperTriangular>().rankUpdate(rhs3.adjoint(),s1)._expression(),
|
||||
(s1 * rhs3.adjoint() * rhs3).eval().template triangularView<UpperTriangular>().toDenseMatrix());
|
||||
VERIFY_IS_APPROX(m2.template selfadjointView<Upper>().rankUpdate(rhs3.adjoint(),s1)._expression(),
|
||||
(s1 * rhs3.adjoint() * rhs3).eval().template triangularView<Upper>().toDenseMatrix());
|
||||
}
|
||||
|
||||
void test_product_syrk()
|
||||
|
||||
@ -36,27 +36,27 @@ template<typename Scalar> void trmm(int size,int othersize)
|
||||
s2 = ei_random<Scalar>();
|
||||
|
||||
tri.setRandom();
|
||||
loTri = tri.template triangularView<LowerTriangular>();
|
||||
upTri = tri.template triangularView<UpperTriangular>();
|
||||
loTri = tri.template triangularView<Lower>();
|
||||
upTri = tri.template triangularView<Upper>();
|
||||
ge1.setRandom();
|
||||
ge2.setRandom();
|
||||
|
||||
VERIFY_IS_APPROX( ge3 = tri.template triangularView<LowerTriangular>() * ge1, loTri * ge1);
|
||||
VERIFY_IS_APPROX(rge3 = tri.template triangularView<LowerTriangular>() * ge1, loTri * ge1);
|
||||
VERIFY_IS_APPROX( ge3 = tri.template triangularView<UpperTriangular>() * ge1, upTri * ge1);
|
||||
VERIFY_IS_APPROX(rge3 = tri.template triangularView<UpperTriangular>() * ge1, upTri * ge1);
|
||||
VERIFY_IS_APPROX( ge3 = (s1*tri.adjoint()).template triangularView<UpperTriangular>() * (s2*ge1), s1*loTri.adjoint() * (s2*ge1));
|
||||
VERIFY_IS_APPROX(rge3 = tri.adjoint().template triangularView<UpperTriangular>() * ge1, loTri.adjoint() * ge1);
|
||||
VERIFY_IS_APPROX( ge3 = tri.adjoint().template triangularView<LowerTriangular>() * ge1, upTri.adjoint() * ge1);
|
||||
VERIFY_IS_APPROX(rge3 = tri.adjoint().template triangularView<LowerTriangular>() * ge1, upTri.adjoint() * ge1);
|
||||
VERIFY_IS_APPROX( ge3 = tri.template triangularView<LowerTriangular>() * ge2.adjoint(), loTri * ge2.adjoint());
|
||||
VERIFY_IS_APPROX(rge3 = tri.template triangularView<LowerTriangular>() * ge2.adjoint(), loTri * ge2.adjoint());
|
||||
VERIFY_IS_APPROX( ge3 = tri.template triangularView<UpperTriangular>() * ge2.adjoint(), upTri * ge2.adjoint());
|
||||
VERIFY_IS_APPROX(rge3 = tri.template triangularView<UpperTriangular>() * ge2.adjoint(), upTri * ge2.adjoint());
|
||||
VERIFY_IS_APPROX( ge3 = (s1*tri).adjoint().template triangularView<UpperTriangular>() * ge2.adjoint(), ei_conj(s1) * loTri.adjoint() * ge2.adjoint());
|
||||
VERIFY_IS_APPROX(rge3 = tri.adjoint().template triangularView<UpperTriangular>() * ge2.adjoint(), loTri.adjoint() * ge2.adjoint());
|
||||
VERIFY_IS_APPROX( ge3 = tri.adjoint().template triangularView<LowerTriangular>() * ge2.adjoint(), upTri.adjoint() * ge2.adjoint());
|
||||
VERIFY_IS_APPROX(rge3 = tri.adjoint().template triangularView<LowerTriangular>() * ge2.adjoint(), upTri.adjoint() * ge2.adjoint());
|
||||
VERIFY_IS_APPROX( ge3 = tri.template triangularView<Lower>() * ge1, loTri * ge1);
|
||||
VERIFY_IS_APPROX(rge3 = tri.template triangularView<Lower>() * ge1, loTri * ge1);
|
||||
VERIFY_IS_APPROX( ge3 = tri.template triangularView<Upper>() * ge1, upTri * ge1);
|
||||
VERIFY_IS_APPROX(rge3 = tri.template triangularView<Upper>() * ge1, upTri * ge1);
|
||||
VERIFY_IS_APPROX( ge3 = (s1*tri.adjoint()).template triangularView<Upper>() * (s2*ge1), s1*loTri.adjoint() * (s2*ge1));
|
||||
VERIFY_IS_APPROX(rge3 = tri.adjoint().template triangularView<Upper>() * ge1, loTri.adjoint() * ge1);
|
||||
VERIFY_IS_APPROX( ge3 = tri.adjoint().template triangularView<Lower>() * ge1, upTri.adjoint() * ge1);
|
||||
VERIFY_IS_APPROX(rge3 = tri.adjoint().template triangularView<Lower>() * ge1, upTri.adjoint() * ge1);
|
||||
VERIFY_IS_APPROX( ge3 = tri.template triangularView<Lower>() * ge2.adjoint(), loTri * ge2.adjoint());
|
||||
VERIFY_IS_APPROX(rge3 = tri.template triangularView<Lower>() * ge2.adjoint(), loTri * ge2.adjoint());
|
||||
VERIFY_IS_APPROX( ge3 = tri.template triangularView<Upper>() * ge2.adjoint(), upTri * ge2.adjoint());
|
||||
VERIFY_IS_APPROX(rge3 = tri.template triangularView<Upper>() * ge2.adjoint(), upTri * ge2.adjoint());
|
||||
VERIFY_IS_APPROX( ge3 = (s1*tri).adjoint().template triangularView<Upper>() * ge2.adjoint(), ei_conj(s1) * loTri.adjoint() * ge2.adjoint());
|
||||
VERIFY_IS_APPROX(rge3 = tri.adjoint().template triangularView<Upper>() * ge2.adjoint(), loTri.adjoint() * ge2.adjoint());
|
||||
VERIFY_IS_APPROX( ge3 = tri.adjoint().template triangularView<Lower>() * ge2.adjoint(), upTri.adjoint() * ge2.adjoint());
|
||||
VERIFY_IS_APPROX(rge3 = tri.adjoint().template triangularView<Lower>() * ge2.adjoint(), upTri.adjoint() * ge2.adjoint());
|
||||
}
|
||||
|
||||
void test_product_trmm()
|
||||
|
||||
@ -44,37 +44,37 @@ template<typename MatrixType> void trmv(const MatrixType& m)
|
||||
m1 = MatrixType::Random(rows, cols);
|
||||
|
||||
// check with a column-major matrix
|
||||
m3 = m1.template triangularView<Eigen::LowerTriangular>();
|
||||
VERIFY((m3 * v1).isApprox(m1.template triangularView<Eigen::LowerTriangular>() * v1, largerEps));
|
||||
m3 = m1.template triangularView<Eigen::UpperTriangular>();
|
||||
VERIFY((m3 * v1).isApprox(m1.template triangularView<Eigen::UpperTriangular>() * v1, largerEps));
|
||||
m3 = m1.template triangularView<Eigen::UnitLowerTriangular>();
|
||||
VERIFY((m3 * v1).isApprox(m1.template triangularView<Eigen::UnitLowerTriangular>() * v1, largerEps));
|
||||
m3 = m1.template triangularView<Eigen::UnitUpperTriangular>();
|
||||
VERIFY((m3 * v1).isApprox(m1.template triangularView<Eigen::UnitUpperTriangular>() * v1, largerEps));
|
||||
m3 = m1.template triangularView<Eigen::Lower>();
|
||||
VERIFY((m3 * v1).isApprox(m1.template triangularView<Eigen::Lower>() * v1, largerEps));
|
||||
m3 = m1.template triangularView<Eigen::Upper>();
|
||||
VERIFY((m3 * v1).isApprox(m1.template triangularView<Eigen::Upper>() * v1, largerEps));
|
||||
m3 = m1.template triangularView<Eigen::UnitLower>();
|
||||
VERIFY((m3 * v1).isApprox(m1.template triangularView<Eigen::UnitLower>() * v1, largerEps));
|
||||
m3 = m1.template triangularView<Eigen::UnitUpper>();
|
||||
VERIFY((m3 * v1).isApprox(m1.template triangularView<Eigen::UnitUpper>() * v1, largerEps));
|
||||
|
||||
// check conjugated and scalar multiple expressions (col-major)
|
||||
m3 = m1.template triangularView<Eigen::LowerTriangular>();
|
||||
VERIFY(((s1*m3).conjugate() * v1).isApprox((s1*m1).conjugate().template triangularView<Eigen::LowerTriangular>() * v1, largerEps));
|
||||
m3 = m1.template triangularView<Eigen::UpperTriangular>();
|
||||
VERIFY((m3.conjugate() * v1.conjugate()).isApprox(m1.conjugate().template triangularView<Eigen::UpperTriangular>() * v1.conjugate(), largerEps));
|
||||
m3 = m1.template triangularView<Eigen::Lower>();
|
||||
VERIFY(((s1*m3).conjugate() * v1).isApprox((s1*m1).conjugate().template triangularView<Eigen::Lower>() * v1, largerEps));
|
||||
m3 = m1.template triangularView<Eigen::Upper>();
|
||||
VERIFY((m3.conjugate() * v1.conjugate()).isApprox(m1.conjugate().template triangularView<Eigen::Upper>() * v1.conjugate(), largerEps));
|
||||
|
||||
// check with a row-major matrix
|
||||
m3 = m1.template triangularView<Eigen::UpperTriangular>();
|
||||
VERIFY((m3.transpose() * v1).isApprox(m1.transpose().template triangularView<Eigen::LowerTriangular>() * v1, largerEps));
|
||||
m3 = m1.template triangularView<Eigen::LowerTriangular>();
|
||||
VERIFY((m3.transpose() * v1).isApprox(m1.transpose().template triangularView<Eigen::UpperTriangular>() * v1, largerEps));
|
||||
m3 = m1.template triangularView<Eigen::UnitUpperTriangular>();
|
||||
VERIFY((m3.transpose() * v1).isApprox(m1.transpose().template triangularView<Eigen::UnitLowerTriangular>() * v1, largerEps));
|
||||
m3 = m1.template triangularView<Eigen::UnitLowerTriangular>();
|
||||
VERIFY((m3.transpose() * v1).isApprox(m1.transpose().template triangularView<Eigen::UnitUpperTriangular>() * v1, largerEps));
|
||||
m3 = m1.template triangularView<Eigen::Upper>();
|
||||
VERIFY((m3.transpose() * v1).isApprox(m1.transpose().template triangularView<Eigen::Lower>() * v1, largerEps));
|
||||
m3 = m1.template triangularView<Eigen::Lower>();
|
||||
VERIFY((m3.transpose() * v1).isApprox(m1.transpose().template triangularView<Eigen::Upper>() * v1, largerEps));
|
||||
m3 = m1.template triangularView<Eigen::UnitUpper>();
|
||||
VERIFY((m3.transpose() * v1).isApprox(m1.transpose().template triangularView<Eigen::UnitLower>() * v1, largerEps));
|
||||
m3 = m1.template triangularView<Eigen::UnitLower>();
|
||||
VERIFY((m3.transpose() * v1).isApprox(m1.transpose().template triangularView<Eigen::UnitUpper>() * v1, largerEps));
|
||||
|
||||
// check conjugated and scalar multiple expressions (row-major)
|
||||
m3 = m1.template triangularView<Eigen::UpperTriangular>();
|
||||
VERIFY((m3.adjoint() * v1).isApprox(m1.adjoint().template triangularView<Eigen::LowerTriangular>() * v1, largerEps));
|
||||
m3 = m1.template triangularView<Eigen::LowerTriangular>();
|
||||
VERIFY((m3.adjoint() * (s1*v1.conjugate())).isApprox(m1.adjoint().template triangularView<Eigen::UpperTriangular>() * (s1*v1.conjugate()), largerEps));
|
||||
m3 = m1.template triangularView<Eigen::UnitUpperTriangular>();
|
||||
m3 = m1.template triangularView<Eigen::Upper>();
|
||||
VERIFY((m3.adjoint() * v1).isApprox(m1.adjoint().template triangularView<Eigen::Lower>() * v1, largerEps));
|
||||
m3 = m1.template triangularView<Eigen::Lower>();
|
||||
VERIFY((m3.adjoint() * (s1*v1.conjugate())).isApprox(m1.adjoint().template triangularView<Eigen::Upper>() * (s1*v1.conjugate()), largerEps));
|
||||
m3 = m1.template triangularView<Eigen::UnitUpper>();
|
||||
|
||||
// TODO check with sub-matrices
|
||||
}
|
||||
|
||||
@ -49,28 +49,28 @@ template<typename Scalar,int Size, int Cols> void trsolve(int size=Size,int cols
|
||||
cmLhs.setRandom(); cmLhs *= static_cast<RealScalar>(0.1); cmLhs.diagonal().array() += static_cast<RealScalar>(1);
|
||||
rmLhs.setRandom(); rmLhs *= static_cast<RealScalar>(0.1); rmLhs.diagonal().array() += static_cast<RealScalar>(1);
|
||||
|
||||
VERIFY_TRSM(cmLhs.conjugate().template triangularView<LowerTriangular>(), cmRhs);
|
||||
VERIFY_TRSM(cmLhs .template triangularView<UpperTriangular>(), cmRhs);
|
||||
VERIFY_TRSM(cmLhs .template triangularView<LowerTriangular>(), rmRhs);
|
||||
VERIFY_TRSM(cmLhs.conjugate().template triangularView<UpperTriangular>(), rmRhs);
|
||||
VERIFY_TRSM(cmLhs.conjugate().template triangularView<Lower>(), cmRhs);
|
||||
VERIFY_TRSM(cmLhs .template triangularView<Upper>(), cmRhs);
|
||||
VERIFY_TRSM(cmLhs .template triangularView<Lower>(), rmRhs);
|
||||
VERIFY_TRSM(cmLhs.conjugate().template triangularView<Upper>(), rmRhs);
|
||||
|
||||
VERIFY_TRSM(cmLhs.conjugate().template triangularView<UnitLowerTriangular>(), cmRhs);
|
||||
VERIFY_TRSM(cmLhs .template triangularView<UnitUpperTriangular>(), rmRhs);
|
||||
VERIFY_TRSM(cmLhs.conjugate().template triangularView<UnitLower>(), cmRhs);
|
||||
VERIFY_TRSM(cmLhs .template triangularView<UnitUpper>(), rmRhs);
|
||||
|
||||
VERIFY_TRSM(rmLhs .template triangularView<LowerTriangular>(), cmRhs);
|
||||
VERIFY_TRSM(rmLhs.conjugate().template triangularView<UnitUpperTriangular>(), rmRhs);
|
||||
VERIFY_TRSM(rmLhs .template triangularView<Lower>(), cmRhs);
|
||||
VERIFY_TRSM(rmLhs.conjugate().template triangularView<UnitUpper>(), rmRhs);
|
||||
|
||||
|
||||
VERIFY_TRSM_ONTHERIGHT(cmLhs.conjugate().template triangularView<LowerTriangular>(), cmRhs);
|
||||
VERIFY_TRSM_ONTHERIGHT(cmLhs .template triangularView<UpperTriangular>(), cmRhs);
|
||||
VERIFY_TRSM_ONTHERIGHT(cmLhs .template triangularView<LowerTriangular>(), rmRhs);
|
||||
VERIFY_TRSM_ONTHERIGHT(cmLhs.conjugate().template triangularView<UpperTriangular>(), rmRhs);
|
||||
VERIFY_TRSM_ONTHERIGHT(cmLhs.conjugate().template triangularView<Lower>(), cmRhs);
|
||||
VERIFY_TRSM_ONTHERIGHT(cmLhs .template triangularView<Upper>(), cmRhs);
|
||||
VERIFY_TRSM_ONTHERIGHT(cmLhs .template triangularView<Lower>(), rmRhs);
|
||||
VERIFY_TRSM_ONTHERIGHT(cmLhs.conjugate().template triangularView<Upper>(), rmRhs);
|
||||
|
||||
VERIFY_TRSM_ONTHERIGHT(cmLhs.conjugate().template triangularView<UnitLowerTriangular>(), cmRhs);
|
||||
VERIFY_TRSM_ONTHERIGHT(cmLhs .template triangularView<UnitUpperTriangular>(), rmRhs);
|
||||
VERIFY_TRSM_ONTHERIGHT(cmLhs.conjugate().template triangularView<UnitLower>(), cmRhs);
|
||||
VERIFY_TRSM_ONTHERIGHT(cmLhs .template triangularView<UnitUpper>(), rmRhs);
|
||||
|
||||
VERIFY_TRSM_ONTHERIGHT(rmLhs .template triangularView<LowerTriangular>(), cmRhs);
|
||||
VERIFY_TRSM_ONTHERIGHT(rmLhs.conjugate().template triangularView<UnitUpperTriangular>(), rmRhs);
|
||||
VERIFY_TRSM_ONTHERIGHT(rmLhs .template triangularView<Lower>(), cmRhs);
|
||||
VERIFY_TRSM_ONTHERIGHT(rmLhs.conjugate().template triangularView<UnitUpper>(), rmRhs);
|
||||
}
|
||||
|
||||
void test_product_trsolve()
|
||||
|
||||
@ -47,7 +47,7 @@ template<typename MatrixType> void qr()
|
||||
MatrixQType q = qr.householderQ();
|
||||
VERIFY_IS_UNITARY(q);
|
||||
|
||||
MatrixType r = qr.matrixQR().template triangularView<UpperTriangular>();
|
||||
MatrixType r = qr.matrixQR().template triangularView<Upper>();
|
||||
MatrixType c = q * r * qr.colsPermutation().inverse();
|
||||
VERIFY_IS_APPROX(m1, c);
|
||||
|
||||
@ -72,7 +72,7 @@ template<typename MatrixType, int Cols2> void qr_fixedsize()
|
||||
VERIFY(!qr.isInvertible());
|
||||
VERIFY(!qr.isSurjective());
|
||||
|
||||
Matrix<Scalar,Rows,Cols> r = qr.matrixQR().template triangularView<UpperTriangular>();
|
||||
Matrix<Scalar,Rows,Cols> r = qr.matrixQR().template triangularView<Upper>();
|
||||
Matrix<Scalar,Rows,Cols> c = qr.householderQ() * r * qr.colsPermutation().inverse();
|
||||
VERIFY_IS_APPROX(m1, c);
|
||||
|
||||
|
||||
@ -115,9 +115,9 @@ template<typename SparseMatrixType> void sparse_product(const SparseMatrixType&
|
||||
VERIFY_IS_APPROX(mS, refS);
|
||||
VERIFY_IS_APPROX(x=mS*b, refX=refS*b);
|
||||
|
||||
VERIFY_IS_APPROX(x=mUp.template selfadjointView<UpperTriangular>()*b, refX=refS*b);
|
||||
VERIFY_IS_APPROX(x=mLo.template selfadjointView<LowerTriangular>()*b, refX=refS*b);
|
||||
VERIFY_IS_APPROX(x=mS.template selfadjointView<UpperTriangular|LowerTriangular>()*b, refX=refS*b);
|
||||
VERIFY_IS_APPROX(x=mUp.template selfadjointView<Upper>()*b, refX=refS*b);
|
||||
VERIFY_IS_APPROX(x=mLo.template selfadjointView<Lower>()*b, refX=refS*b);
|
||||
VERIFY_IS_APPROX(x=mS.template selfadjointView<Upper|Lower>()*b, refX=refS*b);
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
@ -65,23 +65,23 @@ template<typename Scalar> void sparse_solvers(int rows, int cols)
|
||||
|
||||
// lower - dense
|
||||
initSparse<Scalar>(density, refMat2, m2, ForceNonZeroDiag|MakeLowerTriangular, &zeroCoords, &nonzeroCoords);
|
||||
VERIFY_IS_APPROX(refMat2.template triangularView<LowerTriangular>().solve(vec2),
|
||||
m2.template triangularView<LowerTriangular>().solve(vec3));
|
||||
VERIFY_IS_APPROX(refMat2.template triangularView<Lower>().solve(vec2),
|
||||
m2.template triangularView<Lower>().solve(vec3));
|
||||
|
||||
// upper - dense
|
||||
initSparse<Scalar>(density, refMat2, m2, ForceNonZeroDiag|MakeUpperTriangular, &zeroCoords, &nonzeroCoords);
|
||||
VERIFY_IS_APPROX(refMat2.template triangularView<UpperTriangular>().solve(vec2),
|
||||
m2.template triangularView<UpperTriangular>().solve(vec3));
|
||||
VERIFY_IS_APPROX(refMat2.template triangularView<Upper>().solve(vec2),
|
||||
m2.template triangularView<Upper>().solve(vec3));
|
||||
|
||||
// lower - transpose
|
||||
initSparse<Scalar>(density, refMat2, m2, ForceNonZeroDiag|MakeLowerTriangular, &zeroCoords, &nonzeroCoords);
|
||||
VERIFY_IS_APPROX(refMat2.transpose().template triangularView<UpperTriangular>().solve(vec2),
|
||||
m2.transpose().template triangularView<UpperTriangular>().solve(vec3));
|
||||
VERIFY_IS_APPROX(refMat2.transpose().template triangularView<Upper>().solve(vec2),
|
||||
m2.transpose().template triangularView<Upper>().solve(vec3));
|
||||
|
||||
// upper - transpose
|
||||
initSparse<Scalar>(density, refMat2, m2, ForceNonZeroDiag|MakeUpperTriangular, &zeroCoords, &nonzeroCoords);
|
||||
VERIFY_IS_APPROX(refMat2.transpose().template triangularView<LowerTriangular>().solve(vec2),
|
||||
m2.transpose().template triangularView<LowerTriangular>().solve(vec3));
|
||||
VERIFY_IS_APPROX(refMat2.transpose().template triangularView<Lower>().solve(vec2),
|
||||
m2.transpose().template triangularView<Lower>().solve(vec3));
|
||||
|
||||
SparseMatrix<Scalar> matB(rows, rows);
|
||||
DenseMatrix refMatB = DenseMatrix::Zero(rows, rows);
|
||||
@ -89,21 +89,21 @@ template<typename Scalar> void sparse_solvers(int rows, int cols)
|
||||
// lower - sparse
|
||||
initSparse<Scalar>(density, refMat2, m2, ForceNonZeroDiag|MakeLowerTriangular);
|
||||
initSparse<Scalar>(density, refMatB, matB);
|
||||
refMat2.template triangularView<LowerTriangular>().solveInPlace(refMatB);
|
||||
m2.template triangularView<LowerTriangular>().solveInPlace(matB);
|
||||
refMat2.template triangularView<Lower>().solveInPlace(refMatB);
|
||||
m2.template triangularView<Lower>().solveInPlace(matB);
|
||||
VERIFY_IS_APPROX(matB.toDense(), refMatB);
|
||||
|
||||
// upper - sparse
|
||||
initSparse<Scalar>(density, refMat2, m2, ForceNonZeroDiag|MakeUpperTriangular);
|
||||
initSparse<Scalar>(density, refMatB, matB);
|
||||
refMat2.template triangularView<UpperTriangular>().solveInPlace(refMatB);
|
||||
m2.template triangularView<UpperTriangular>().solveInPlace(matB);
|
||||
refMat2.template triangularView<Upper>().solveInPlace(refMatB);
|
||||
m2.template triangularView<Upper>().solveInPlace(matB);
|
||||
VERIFY_IS_APPROX(matB, refMatB);
|
||||
|
||||
// test deprecated API
|
||||
initSparse<Scalar>(density, refMat2, m2, ForceNonZeroDiag|MakeLowerTriangular, &zeroCoords, &nonzeroCoords);
|
||||
VERIFY_IS_APPROX(refMat2.template triangularView<LowerTriangular>().solve(vec2),
|
||||
m2.template triangularView<LowerTriangular>().solve(vec3));
|
||||
VERIFY_IS_APPROX(refMat2.template triangularView<Lower>().solve(vec2),
|
||||
m2.template triangularView<Lower>().solve(vec3));
|
||||
}
|
||||
|
||||
// test LLT
|
||||
@ -118,29 +118,28 @@ template<typename Scalar> void sparse_solvers(int rows, int cols)
|
||||
initSPD(density, refMat2, m2);
|
||||
|
||||
refX = refMat2.llt().solve(b);
|
||||
typedef SparseMatrix<Scalar,LowerTriangular|SelfAdjoint> SparseSelfAdjointMatrix;
|
||||
if (!NumTraits<Scalar>::IsComplex)
|
||||
{
|
||||
x = b;
|
||||
SparseLLT<SparseSelfAdjointMatrix> (m2).solveInPlace(x);
|
||||
SparseLLT<SparseMatrix<Scalar> > (m2).solveInPlace(x);
|
||||
VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LLT: default");
|
||||
}
|
||||
#ifdef EIGEN_CHOLMOD_SUPPORT
|
||||
x = b;
|
||||
SparseLLT<SparseSelfAdjointMatrix,Cholmod>(m2).solveInPlace(x);
|
||||
SparseLLT<SparseMatrix<Scalar> ,Cholmod>(m2).solveInPlace(x);
|
||||
VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LLT: cholmod");
|
||||
#endif
|
||||
|
||||
#ifdef EIGEN_TAUCS_SUPPORT
|
||||
x = b;
|
||||
SparseLLT<SparseSelfAdjointMatrix,Taucs>(m2,IncompleteFactorization).solveInPlace(x);
|
||||
SparseLLT<SparseMatrix<Scalar> ,Taucs>(m2,IncompleteFactorization).solveInPlace(x);
|
||||
VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LLT: taucs (IncompleteFactorization)");
|
||||
// TODO fix TAUCS with complexes
|
||||
x = b;
|
||||
SparseLLT<SparseSelfAdjointMatrix,Taucs>(m2,SupernodalMultifrontal).solveInPlace(x);
|
||||
SparseLLT<SparseMatrix<Scalar> ,Taucs>(m2,SupernodalMultifrontal).solveInPlace(x);
|
||||
VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LLT: taucs (SupernodalMultifrontal)");
|
||||
x = b;
|
||||
SparseLLT<SparseSelfAdjointMatrix,Taucs>(m2,SupernodalLeftLooking).solveInPlace(x);
|
||||
SparseLLT<SparseMatrix<Scalar> ,Taucs>(m2,SupernodalLeftLooking).solveInPlace(x);
|
||||
VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LLT: taucs (SupernodalLeftLooking)");
|
||||
#endif
|
||||
}
|
||||
@ -161,7 +160,7 @@ template<typename Scalar> void sparse_solvers(int rows, int cols)
|
||||
refMat2.diagonal() *= 0.5;
|
||||
|
||||
refX = refMat2.llt().solve(b); // FIXME use LLT to compute the reference because LDLT seems to fail with large matrices
|
||||
typedef SparseMatrix<Scalar,UpperTriangular|SelfAdjoint> SparseSelfAdjointMatrix;
|
||||
typedef SparseMatrix<Scalar,Upper|SelfAdjoint> SparseSelfAdjointMatrix;
|
||||
x = b;
|
||||
SparseLDLT<SparseSelfAdjointMatrix> ldlt(m2);
|
||||
if (ldlt.succeeded())
|
||||
|
||||
@ -53,14 +53,14 @@ template<typename MatrixType> void triangular_square(const MatrixType& m)
|
||||
v2 = VectorType::Random(rows),
|
||||
vzero = VectorType::Zero(rows);
|
||||
|
||||
MatrixType m1up = m1.template triangularView<UpperTriangular>();
|
||||
MatrixType m2up = m2.template triangularView<UpperTriangular>();
|
||||
MatrixType m1up = m1.template triangularView<Upper>();
|
||||
MatrixType m2up = m2.template triangularView<Upper>();
|
||||
|
||||
if (rows*cols>1)
|
||||
{
|
||||
VERIFY(m1up.isUpperTriangular());
|
||||
VERIFY(m2up.transpose().isLowerTriangular());
|
||||
VERIFY(!m2.isLowerTriangular());
|
||||
VERIFY(m1up.isUpper());
|
||||
VERIFY(m2up.transpose().isLower());
|
||||
VERIFY(!m2.isLower());
|
||||
}
|
||||
|
||||
// VERIFY_IS_APPROX(m1up.transpose() * m2, m1.upper().transpose().lower() * m2);
|
||||
@ -68,20 +68,20 @@ template<typename MatrixType> void triangular_square(const MatrixType& m)
|
||||
// test overloaded operator+=
|
||||
r1.setZero();
|
||||
r2.setZero();
|
||||
r1.template triangularView<UpperTriangular>() += m1;
|
||||
r1.template triangularView<Upper>() += m1;
|
||||
r2 += m1up;
|
||||
VERIFY_IS_APPROX(r1,r2);
|
||||
|
||||
// test overloaded operator=
|
||||
m1.setZero();
|
||||
m1.template triangularView<UpperTriangular>() = m2.transpose() + m2;
|
||||
m1.template triangularView<Upper>() = m2.transpose() + m2;
|
||||
m3 = m2.transpose() + m2;
|
||||
VERIFY_IS_APPROX(m3.template triangularView<LowerTriangular>().transpose().toDenseMatrix(), m1);
|
||||
VERIFY_IS_APPROX(m3.template triangularView<Lower>().transpose().toDenseMatrix(), m1);
|
||||
|
||||
// test overloaded operator=
|
||||
m1.setZero();
|
||||
m1.template triangularView<LowerTriangular>() = m2.transpose() + m2;
|
||||
VERIFY_IS_APPROX(m3.template triangularView<LowerTriangular>().toDenseMatrix(), m1);
|
||||
m1.template triangularView<Lower>() = m2.transpose() + m2;
|
||||
VERIFY_IS_APPROX(m3.template triangularView<Lower>().toDenseMatrix(), m1);
|
||||
|
||||
m1 = MatrixType::Random(rows, cols);
|
||||
for (int i=0; i<rows; ++i)
|
||||
@ -89,49 +89,49 @@ template<typename MatrixType> void triangular_square(const MatrixType& m)
|
||||
|
||||
Transpose<MatrixType> trm4(m4);
|
||||
// test back and forward subsitution with a vector as the rhs
|
||||
m3 = m1.template triangularView<UpperTriangular>();
|
||||
VERIFY(v2.isApprox(m3.adjoint() * (m1.adjoint().template triangularView<LowerTriangular>().solve(v2)), largerEps));
|
||||
m3 = m1.template triangularView<LowerTriangular>();
|
||||
VERIFY(v2.isApprox(m3.transpose() * (m1.transpose().template triangularView<UpperTriangular>().solve(v2)), largerEps));
|
||||
m3 = m1.template triangularView<UpperTriangular>();
|
||||
VERIFY(v2.isApprox(m3 * (m1.template triangularView<UpperTriangular>().solve(v2)), largerEps));
|
||||
m3 = m1.template triangularView<LowerTriangular>();
|
||||
VERIFY(v2.isApprox(m3.conjugate() * (m1.conjugate().template triangularView<LowerTriangular>().solve(v2)), largerEps));
|
||||
m3 = m1.template triangularView<Upper>();
|
||||
VERIFY(v2.isApprox(m3.adjoint() * (m1.adjoint().template triangularView<Lower>().solve(v2)), largerEps));
|
||||
m3 = m1.template triangularView<Lower>();
|
||||
VERIFY(v2.isApprox(m3.transpose() * (m1.transpose().template triangularView<Upper>().solve(v2)), largerEps));
|
||||
m3 = m1.template triangularView<Upper>();
|
||||
VERIFY(v2.isApprox(m3 * (m1.template triangularView<Upper>().solve(v2)), largerEps));
|
||||
m3 = m1.template triangularView<Lower>();
|
||||
VERIFY(v2.isApprox(m3.conjugate() * (m1.conjugate().template triangularView<Lower>().solve(v2)), largerEps));
|
||||
|
||||
// test back and forward subsitution with a matrix as the rhs
|
||||
m3 = m1.template triangularView<UpperTriangular>();
|
||||
VERIFY(m2.isApprox(m3.adjoint() * (m1.adjoint().template triangularView<LowerTriangular>().solve(m2)), largerEps));
|
||||
m3 = m1.template triangularView<LowerTriangular>();
|
||||
VERIFY(m2.isApprox(m3.transpose() * (m1.transpose().template triangularView<UpperTriangular>().solve(m2)), largerEps));
|
||||
m3 = m1.template triangularView<UpperTriangular>();
|
||||
VERIFY(m2.isApprox(m3 * (m1.template triangularView<UpperTriangular>().solve(m2)), largerEps));
|
||||
m3 = m1.template triangularView<LowerTriangular>();
|
||||
VERIFY(m2.isApprox(m3.conjugate() * (m1.conjugate().template triangularView<LowerTriangular>().solve(m2)), largerEps));
|
||||
m3 = m1.template triangularView<Upper>();
|
||||
VERIFY(m2.isApprox(m3.adjoint() * (m1.adjoint().template triangularView<Lower>().solve(m2)), largerEps));
|
||||
m3 = m1.template triangularView<Lower>();
|
||||
VERIFY(m2.isApprox(m3.transpose() * (m1.transpose().template triangularView<Upper>().solve(m2)), largerEps));
|
||||
m3 = m1.template triangularView<Upper>();
|
||||
VERIFY(m2.isApprox(m3 * (m1.template triangularView<Upper>().solve(m2)), largerEps));
|
||||
m3 = m1.template triangularView<Lower>();
|
||||
VERIFY(m2.isApprox(m3.conjugate() * (m1.conjugate().template triangularView<Lower>().solve(m2)), largerEps));
|
||||
|
||||
// check M * inv(L) using in place API
|
||||
m4 = m3;
|
||||
m3.transpose().template triangularView<Eigen::UpperTriangular>().solveInPlace(trm4);
|
||||
m3.transpose().template triangularView<Eigen::Upper>().solveInPlace(trm4);
|
||||
VERIFY(m4.cwiseAbs().isIdentity(test_precision<RealScalar>()));
|
||||
|
||||
// check M * inv(U) using in place API
|
||||
m3 = m1.template triangularView<UpperTriangular>();
|
||||
m3 = m1.template triangularView<Upper>();
|
||||
m4 = m3;
|
||||
m3.transpose().template triangularView<Eigen::LowerTriangular>().solveInPlace(trm4);
|
||||
m3.transpose().template triangularView<Eigen::Lower>().solveInPlace(trm4);
|
||||
VERIFY(m4.cwiseAbs().isIdentity(test_precision<RealScalar>()));
|
||||
|
||||
// check solve with unit diagonal
|
||||
m3 = m1.template triangularView<UnitUpperTriangular>();
|
||||
VERIFY(m2.isApprox(m3 * (m1.template triangularView<UnitUpperTriangular>().solve(m2)), largerEps));
|
||||
m3 = m1.template triangularView<UnitUpper>();
|
||||
VERIFY(m2.isApprox(m3 * (m1.template triangularView<UnitUpper>().solve(m2)), largerEps));
|
||||
|
||||
// VERIFY(( m1.template triangularView<UpperTriangular>()
|
||||
// * m2.template triangularView<UpperTriangular>()).isUpperTriangular());
|
||||
// VERIFY(( m1.template triangularView<Upper>()
|
||||
// * m2.template triangularView<Upper>()).isUpper());
|
||||
|
||||
// test swap
|
||||
m1.setOnes();
|
||||
m2.setZero();
|
||||
m2.template triangularView<UpperTriangular>().swap(m1);
|
||||
m2.template triangularView<Upper>().swap(m1);
|
||||
m3.setZero();
|
||||
m3.template triangularView<UpperTriangular>().setOnes();
|
||||
m3.template triangularView<Upper>().setOnes();
|
||||
VERIFY_IS_APPROX(m2,m3);
|
||||
|
||||
}
|
||||
@ -165,69 +165,69 @@ template<typename MatrixType> void triangular_rect(const MatrixType& m)
|
||||
v2 = VectorType::Random(rows),
|
||||
vzero = VectorType::Zero(rows);
|
||||
|
||||
MatrixType m1up = m1.template triangularView<UpperTriangular>();
|
||||
MatrixType m2up = m2.template triangularView<UpperTriangular>();
|
||||
MatrixType m1up = m1.template triangularView<Upper>();
|
||||
MatrixType m2up = m2.template triangularView<Upper>();
|
||||
|
||||
if (rows*cols>1)
|
||||
{
|
||||
VERIFY(m1up.isUpperTriangular());
|
||||
VERIFY(m2up.transpose().isLowerTriangular());
|
||||
VERIFY(!m2.isLowerTriangular());
|
||||
VERIFY(m1up.isUpper());
|
||||
VERIFY(m2up.transpose().isLower());
|
||||
VERIFY(!m2.isLower());
|
||||
}
|
||||
|
||||
// test overloaded operator+=
|
||||
r1.setZero();
|
||||
r2.setZero();
|
||||
r1.template triangularView<UpperTriangular>() += m1;
|
||||
r1.template triangularView<Upper>() += m1;
|
||||
r2 += m1up;
|
||||
VERIFY_IS_APPROX(r1,r2);
|
||||
|
||||
// test overloaded operator=
|
||||
m1.setZero();
|
||||
m1.template triangularView<UpperTriangular>() = 3 * m2;
|
||||
m1.template triangularView<Upper>() = 3 * m2;
|
||||
m3 = 3 * m2;
|
||||
VERIFY_IS_APPROX(m3.template triangularView<UpperTriangular>().toDenseMatrix(), m1);
|
||||
VERIFY_IS_APPROX(m3.template triangularView<Upper>().toDenseMatrix(), m1);
|
||||
|
||||
|
||||
m1.setZero();
|
||||
m1.template triangularView<LowerTriangular>() = 3 * m2;
|
||||
VERIFY_IS_APPROX(m3.template triangularView<LowerTriangular>().toDenseMatrix(), m1);
|
||||
m1.template triangularView<Lower>() = 3 * m2;
|
||||
VERIFY_IS_APPROX(m3.template triangularView<Lower>().toDenseMatrix(), m1);
|
||||
|
||||
m1.setZero();
|
||||
m1.template triangularView<StrictlyUpperTriangular>() = 3 * m2;
|
||||
VERIFY_IS_APPROX(m3.template triangularView<StrictlyUpperTriangular>().toDenseMatrix(), m1);
|
||||
m1.template triangularView<StrictlyUpper>() = 3 * m2;
|
||||
VERIFY_IS_APPROX(m3.template triangularView<StrictlyUpper>().toDenseMatrix(), m1);
|
||||
|
||||
|
||||
m1.setZero();
|
||||
m1.template triangularView<StrictlyLowerTriangular>() = 3 * m2;
|
||||
VERIFY_IS_APPROX(m3.template triangularView<StrictlyLowerTriangular>().toDenseMatrix(), m1);
|
||||
m1.template triangularView<StrictlyLower>() = 3 * m2;
|
||||
VERIFY_IS_APPROX(m3.template triangularView<StrictlyLower>().toDenseMatrix(), m1);
|
||||
m1.setRandom();
|
||||
m2 = m1.template triangularView<UpperTriangular>();
|
||||
VERIFY(m2.isUpperTriangular());
|
||||
VERIFY(!m2.isLowerTriangular());
|
||||
m2 = m1.template triangularView<StrictlyUpperTriangular>();
|
||||
VERIFY(m2.isUpperTriangular());
|
||||
m2 = m1.template triangularView<Upper>();
|
||||
VERIFY(m2.isUpper());
|
||||
VERIFY(!m2.isLower());
|
||||
m2 = m1.template triangularView<StrictlyUpper>();
|
||||
VERIFY(m2.isUpper());
|
||||
VERIFY(m2.diagonal().isMuchSmallerThan(RealScalar(1)));
|
||||
m2 = m1.template triangularView<UnitUpperTriangular>();
|
||||
VERIFY(m2.isUpperTriangular());
|
||||
m2 = m1.template triangularView<UnitUpper>();
|
||||
VERIFY(m2.isUpper());
|
||||
m2.diagonal().array() -= Scalar(1);
|
||||
VERIFY(m2.diagonal().isMuchSmallerThan(RealScalar(1)));
|
||||
m2 = m1.template triangularView<LowerTriangular>();
|
||||
VERIFY(m2.isLowerTriangular());
|
||||
VERIFY(!m2.isUpperTriangular());
|
||||
m2 = m1.template triangularView<StrictlyLowerTriangular>();
|
||||
VERIFY(m2.isLowerTriangular());
|
||||
m2 = m1.template triangularView<Lower>();
|
||||
VERIFY(m2.isLower());
|
||||
VERIFY(!m2.isUpper());
|
||||
m2 = m1.template triangularView<StrictlyLower>();
|
||||
VERIFY(m2.isLower());
|
||||
VERIFY(m2.diagonal().isMuchSmallerThan(RealScalar(1)));
|
||||
m2 = m1.template triangularView<UnitLowerTriangular>();
|
||||
VERIFY(m2.isLowerTriangular());
|
||||
m2 = m1.template triangularView<UnitLower>();
|
||||
VERIFY(m2.isLower());
|
||||
m2.diagonal().array() -= Scalar(1);
|
||||
VERIFY(m2.diagonal().isMuchSmallerThan(RealScalar(1)));
|
||||
// test swap
|
||||
m1.setOnes();
|
||||
m2.setZero();
|
||||
m2.template triangularView<UpperTriangular>().swap(m1);
|
||||
m2.template triangularView<Upper>().swap(m1);
|
||||
m3.setZero();
|
||||
m3.template triangularView<UpperTriangular>().setOnes();
|
||||
m3.template triangularView<Upper>().setOnes();
|
||||
VERIFY_IS_APPROX(m2,m3);
|
||||
}
|
||||
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user