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Eigen: Updated to 3.2.5 version

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git-svn-id: svn://ultimatepp.org/upp/trunk@8966 f0d560ea-af0d-0410-9eb7-867de7ffcac7
This commit is contained in:
koldo 2015-09-26 14:04:10 +00:00
parent 7d997d87c0
commit b157ebb02c
160 changed files with 12055 additions and 478 deletions
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19
uppsrc/plugin/Eigen/Eigen/CMakeLists.txt Normal file
View file

@ -0,0 +1,19 @@
include(RegexUtils)
test_escape_string_as_regex()
file(GLOB Eigen_directory_files "*")
escape_string_as_regex(ESCAPED_CMAKE_CURRENT_SOURCE_DIR "${CMAKE_CURRENT_SOURCE_DIR}")
foreach(f ${Eigen_directory_files})
if(NOT f MATCHES "\\.txt" AND NOT f MATCHES "${ESCAPED_CMAKE_CURRENT_SOURCE_DIR}/[.].+" AND NOT f MATCHES "${ESCAPED_CMAKE_CURRENT_SOURCE_DIR}/src")
list(APPEND Eigen_directory_files_to_install ${f})
endif()
endforeach(f ${Eigen_directory_files})
install(FILES
${Eigen_directory_files_to_install}
DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen COMPONENT Devel
)
add_subdirectory(src)

2
uppsrc/plugin/Eigen/Eigen/Core
View file

@ -123,7 +123,7 @@
#undef bool
#undef vector
#undef pixel
#elif defined __ARM_NEON__
#elif defined __ARM_NEON
#define EIGEN_VECTORIZE
#define EIGEN_VECTORIZE_NEON
#include <arm_neon.h>

7
uppsrc/plugin/Eigen/Eigen/src/CMakeLists.txt Normal file
View file

@ -0,0 +1,7 @@
file(GLOB Eigen_src_subdirectories "*")
escape_string_as_regex(ESCAPED_CMAKE_CURRENT_SOURCE_DIR "${CMAKE_CURRENT_SOURCE_DIR}")
foreach(f ${Eigen_src_subdirectories})
if(NOT f MATCHES "\\.txt" AND NOT f MATCHES "${ESCAPED_CMAKE_CURRENT_SOURCE_DIR}/[.].+" )
add_subdirectory(${f})
endif()
endforeach()

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

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

7
uppsrc/plugin/Eigen/Eigen/src/Cholesky/LDLT.h
View file

@ -235,6 +235,11 @@ template<typename _MatrixType, int _UpLo> class LDLT
}
protected:
static void check_template_parameters()
{
EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar);
}
/** \internal
* Used to compute and store the Cholesky decomposition A = L D L^* = U^* D U.
@ -434,6 +439,8 @@ template<typename MatrixType> struct LDLT_Traits<MatrixType,Upper>
template<typename MatrixType, int _UpLo>
LDLT<MatrixType,_UpLo>& LDLT<MatrixType,_UpLo>::compute(const MatrixType& a)
{
check_template_parameters();
eigen_assert(a.rows()==a.cols());
const Index size = a.rows();

8
uppsrc/plugin/Eigen/Eigen/src/Cholesky/LLT.h
View file

@ -174,6 +174,12 @@ template<typename _MatrixType, int _UpLo> class LLT
LLT rankUpdate(const VectorType& vec, const RealScalar& sigma = 1);
protected:
static void check_template_parameters()
{
EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar);
}
/** \internal
* Used to compute and store L
* The strict upper part is not used and even not initialized.
@ -384,6 +390,8 @@ template<typename MatrixType> struct LLT_Traits<MatrixType,Upper>
template<typename MatrixType, int _UpLo>
LLT<MatrixType,_UpLo>& LLT<MatrixType,_UpLo>::compute(const MatrixType& a)
{
check_template_parameters();
eigen_assert(a.rows()==a.cols());
const Index size = a.rows();
m_matrix.resize(size, size);

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

@ -60,7 +60,7 @@ template<> struct mkl_llt<EIGTYPE> \
lda = m.outerStride(); \
\
info = LAPACKE_##MKLPREFIX##potrf( matrix_order, uplo, size, (MKLTYPE*)a, lda ); \
info = (info==0) ? Success : NumericalIssue; \
info = (info==0) ? -1 : info>0 ? info-1 : size; \
return info; \
} \
}; \

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

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

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

@ -439,19 +439,26 @@ struct assign_impl<Derived1, Derived2, SliceVectorizedTraversal, NoUnrolling, Ve
typedef typename Derived1::Index Index;
static inline void run(Derived1 &dst, const Derived2 &src)
{
typedef packet_traits<typename Derived1::Scalar> PacketTraits;
typedef typename Derived1::Scalar Scalar;
typedef packet_traits<Scalar> PacketTraits;
enum {
packetSize = PacketTraits::size,
alignable = PacketTraits::AlignedOnScalar,
dstAlignment = alignable ? Aligned : int(assign_traits<Derived1,Derived2>::DstIsAligned) ,
dstIsAligned = assign_traits<Derived1,Derived2>::DstIsAligned,
dstAlignment = alignable ? Aligned : int(dstIsAligned),
srcAlignment = assign_traits<Derived1,Derived2>::JointAlignment
};
const Scalar *dst_ptr = &dst.coeffRef(0,0);
if((!bool(dstIsAligned)) && (Index(dst_ptr) % sizeof(Scalar))>0)
{
// the pointer is not aligend-on scalar, so alignment is not possible
return assign_impl<Derived1,Derived2,DefaultTraversal,NoUnrolling>::run(dst, src);
}
const Index packetAlignedMask = packetSize - 1;
const Index innerSize = dst.innerSize();
const Index outerSize = dst.outerSize();
const Index alignedStep = alignable ? (packetSize - dst.outerStride() % packetSize) & packetAlignedMask : 0;
Index alignedStart = ((!alignable) || assign_traits<Derived1,Derived2>::DstIsAligned) ? 0
: internal::first_aligned(&dst.coeffRef(0,0), innerSize);
Index alignedStart = ((!alignable) || bool(dstIsAligned)) ? 0 : internal::first_aligned(dst_ptr, innerSize);
for(Index outer = 0; outer < outerSize; ++outer)
{

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

@ -66,8 +66,9 @@ struct traits<Block<XprType, BlockRows, BlockCols, InnerPanel> > : traits<XprTyp
: ColsAtCompileTime != Dynamic ? int(ColsAtCompileTime)
: int(traits<XprType>::MaxColsAtCompileTime),
XprTypeIsRowMajor = (int(traits<XprType>::Flags)&RowMajorBit) != 0,
IsRowMajor = (MaxRowsAtCompileTime==1&&MaxColsAtCompileTime!=1) ? 1
: (MaxColsAtCompileTime==1&&MaxRowsAtCompileTime!=1) ? 0
IsDense = is_same<StorageKind,Dense>::value,
IsRowMajor = (IsDense&&MaxRowsAtCompileTime==1&&MaxColsAtCompileTime!=1) ? 1
: (IsDense&&MaxColsAtCompileTime==1&&MaxRowsAtCompileTime!=1) ? 0
: XprTypeIsRowMajor,
HasSameStorageOrderAsXprType = (IsRowMajor == XprTypeIsRowMajor),
InnerSize = IsRowMajor ? int(ColsAtCompileTime) : int(RowsAtCompileTime),

10
uppsrc/plugin/Eigen/Eigen/src/Core/CMakeLists.txt Normal file
View file

@ -0,0 +1,10 @@
FILE(GLOB Eigen_Core_SRCS "*.h")
INSTALL(FILES
${Eigen_Core_SRCS}
DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen/src/Core COMPONENT Devel
)
ADD_SUBDIRECTORY(products)
ADD_SUBDIRECTORY(util)
ADD_SUBDIRECTORY(arch)

8
uppsrc/plugin/Eigen/Eigen/src/Core/DenseBase.h
View file

@ -266,11 +266,13 @@ template<typename Derived> class DenseBase
template<typename OtherDerived>
Derived& operator=(const ReturnByValue<OtherDerived>& func);
#ifndef EIGEN_PARSED_BY_DOXYGEN
/** Copies \a other into *this without evaluating other. \returns a reference to *this. */
/** \internal Copies \a other into *this without evaluating other. \returns a reference to *this. */
template<typename OtherDerived>
Derived& lazyAssign(const DenseBase<OtherDerived>& other);
#endif // not EIGEN_PARSED_BY_DOXYGEN
/** \internal Evaluates \a other into *this. \returns a reference to *this. */
template<typename OtherDerived>
Derived& lazyAssign(const ReturnByValue<OtherDerived>& other);
CommaInitializer<Derived> operator<< (const Scalar& s);

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

@ -34,7 +34,7 @@ struct traits<DiagonalProduct<MatrixType, DiagonalType, ProductOrder> >
_Vectorizable = bool(int(MatrixType::Flags)&PacketAccessBit) && _SameTypes && (_ScalarAccessOnDiag || (bool(int(DiagonalType::DiagonalVectorType::Flags)&PacketAccessBit))),
_LinearAccessMask = (RowsAtCompileTime==1 || ColsAtCompileTime==1) ? LinearAccessBit : 0,
Flags = ((HereditaryBits|_LinearAccessMask) & (unsigned int)(MatrixType::Flags)) | (_Vectorizable ? PacketAccessBit : 0) | AlignedBit,//(int(MatrixType::Flags)&int(DiagonalType::DiagonalVectorType::Flags)&AlignedBit),
Flags = ((HereditaryBits|_LinearAccessMask|AlignedBit) & (unsigned int)(MatrixType::Flags)) | (_Vectorizable ? PacketAccessBit : 0),//(int(MatrixType::Flags)&int(DiagonalType::DiagonalVectorType::Flags)&AlignedBit),
CoeffReadCost = NumTraits<Scalar>::MulCost + MatrixType::CoeffReadCost + DiagonalType::DiagonalVectorType::CoeffReadCost
};
};

41
uppsrc/plugin/Eigen/Eigen/src/Core/Functors.h
View file

@ -259,6 +259,47 @@ template<> struct functor_traits<scalar_boolean_or_op> {
};
};
/** \internal
* \brief Template functors for comparison of two scalars
* \todo Implement packet-comparisons
*/
template<typename Scalar, ComparisonName cmp> struct scalar_cmp_op;
template<typename Scalar, ComparisonName cmp>
struct functor_traits<scalar_cmp_op<Scalar, cmp> > {
enum {
Cost = NumTraits<Scalar>::AddCost,
PacketAccess = false
};
};
template<ComparisonName Cmp, typename Scalar>
struct result_of<scalar_cmp_op<Scalar, Cmp>(Scalar,Scalar)> {
typedef bool type;
};
template<typename Scalar> struct scalar_cmp_op<Scalar, cmp_EQ> {
EIGEN_EMPTY_STRUCT_CTOR(scalar_cmp_op)
EIGEN_STRONG_INLINE bool operator()(const Scalar& a, const Scalar& b) const {return a==b;}
};
template<typename Scalar> struct scalar_cmp_op<Scalar, cmp_LT> {
EIGEN_EMPTY_STRUCT_CTOR(scalar_cmp_op)
EIGEN_STRONG_INLINE bool operator()(const Scalar& a, const Scalar& b) const {return a<b;}
};
template<typename Scalar> struct scalar_cmp_op<Scalar, cmp_LE> {
EIGEN_EMPTY_STRUCT_CTOR(scalar_cmp_op)
EIGEN_STRONG_INLINE bool operator()(const Scalar& a, const Scalar& b) const {return a<=b;}
};
template<typename Scalar> struct scalar_cmp_op<Scalar, cmp_UNORD> {
EIGEN_EMPTY_STRUCT_CTOR(scalar_cmp_op)
EIGEN_STRONG_INLINE bool operator()(const Scalar& a, const Scalar& b) const {return !(a<=b || b<=a);}
};
template<typename Scalar> struct scalar_cmp_op<Scalar, cmp_NEQ> {
EIGEN_EMPTY_STRUCT_CTOR(scalar_cmp_op)
EIGEN_STRONG_INLINE bool operator()(const Scalar& a, const Scalar& b) const {return a!=b;}
};
// unary functors:
/** \internal

13
uppsrc/plugin/Eigen/Eigen/src/Core/MapBase.h
View file

@ -157,7 +157,7 @@ template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
internal::inner_stride_at_compile_time<Derived>::ret==1),
PACKET_ACCESS_REQUIRES_TO_HAVE_INNER_STRIDE_FIXED_TO_1);
eigen_assert(EIGEN_IMPLIES(internal::traits<Derived>::Flags&AlignedBit, (size_t(m_data) % 16) == 0)
&& "data is not aligned");
&& "input pointer is not aligned on a 16 byte boundary");
}
PointerType m_data;
@ -168,6 +168,7 @@ template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
template<typename Derived> class MapBase<Derived, WriteAccessors>
: public MapBase<Derived, ReadOnlyAccessors>
{
typedef MapBase<Derived, ReadOnlyAccessors> ReadOnlyMapBase;
public:
typedef MapBase<Derived, ReadOnlyAccessors> Base;
@ -230,15 +231,13 @@ template<typename Derived> class MapBase<Derived, WriteAccessors>
Derived& operator=(const MapBase& other)
{
Base::Base::operator=(other);
ReadOnlyMapBase::Base::operator=(other);
return derived();
}
// In theory MapBase<Derived, ReadOnlyAccessors> should not make a using Base::operator=,
// and thus we should directly do: using Base::Base::operator=;
// However, this would confuse recent MSVC 2013 (bug 821), and since MapBase<Derived, ReadOnlyAccessors>
// has operator= to make ICC 11 happy, we can also make MSVC 2013 happy as follow:
using Base::operator=;
// In theory we could simply refer to Base:Base::operator=, but MSVC does not like Base::Base,
// see bugs 821 and 920.
using ReadOnlyMapBase::Base::operator=;
};
#undef EIGEN_STATIC_ASSERT_INDEX_BASED_ACCESS

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

@ -159,13 +159,11 @@ template<typename Derived> class MatrixBase
template<typename OtherDerived>
Derived& operator=(const ReturnByValue<OtherDerived>& other);
#ifndef EIGEN_PARSED_BY_DOXYGEN
template<typename ProductDerived, typename Lhs, typename Rhs>
Derived& lazyAssign(const ProductBase<ProductDerived, Lhs,Rhs>& other);
template<typename MatrixPower, typename Lhs, typename Rhs>
Derived& lazyAssign(const MatrixPowerProduct<MatrixPower, Lhs,Rhs>& other);
#endif // not EIGEN_PARSED_BY_DOXYGEN
template<typename OtherDerived>
Derived& operator+=(const MatrixBase<OtherDerived>& other);

29
uppsrc/plugin/Eigen/Eigen/src/Core/PermutationMatrix.h
View file

@ -250,6 +250,35 @@ class PermutationBase : public EigenBase<Derived>
template<typename Other> friend
inline PlainPermutationType operator*(const Transpose<PermutationBase<Other> >& other, const PermutationBase& perm)
{ return PlainPermutationType(internal::PermPermProduct, other.eval(), perm); }
/** \returns the determinant of the permutation matrix, which is either 1 or -1 depending on the parity of the permutation.
*
* This function is O(\c n) procedure allocating a buffer of \c n booleans.
*/
Index determinant() const
{
Index res = 1;
Index n = size();
Matrix<bool,RowsAtCompileTime,1,0,MaxRowsAtCompileTime> mask(n);
mask.fill(false);
Index r = 0;
while(r < n)
{
// search for the next seed
while(r<n && mask[r]) r++;
if(r>=n)
break;
// we got one, let's follow it until we are back to the seed
Index k0 = r++;
mask.coeffRef(k0) = true;
for(Index k=indices().coeff(k0); k!=k0; k=indices().coeff(k))
{
mask.coeffRef(k) = true;
res = -res;
}
}
return res;
}
protected:

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

@ -573,6 +573,8 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
: (rows() == other.rows() && cols() == other.cols())))
&& "Size mismatch. Automatic resizing is disabled because EIGEN_NO_AUTOMATIC_RESIZING is defined");
EIGEN_ONLY_USED_FOR_DEBUG(other);
if(this->size()==0)
resizeLike(other);
#else
resizeLike(other);
#endif

16
uppsrc/plugin/Eigen/Eigen/src/Core/Ref.h
View file

@ -108,7 +108,8 @@ struct traits<Ref<_PlainObjectType, _Options, _StrideType> >
OuterStrideMatch = Derived::IsVectorAtCompileTime
|| int(StrideType::OuterStrideAtCompileTime)==int(Dynamic) || int(StrideType::OuterStrideAtCompileTime)==int(Derived::OuterStrideAtCompileTime),
AlignmentMatch = (_Options!=Aligned) || ((PlainObjectType::Flags&AlignedBit)==0) || ((traits<Derived>::Flags&AlignedBit)==AlignedBit),
MatchAtCompileTime = HasDirectAccess && StorageOrderMatch && InnerStrideMatch && OuterStrideMatch && AlignmentMatch
ScalarTypeMatch = internal::is_same<typename PlainObjectType::Scalar, typename Derived::Scalar>::value,
MatchAtCompileTime = HasDirectAccess && StorageOrderMatch && InnerStrideMatch && OuterStrideMatch && AlignmentMatch && ScalarTypeMatch
};
typedef typename internal::conditional<MatchAtCompileTime,internal::true_type,internal::false_type>::type type;
};
@ -187,9 +188,11 @@ protected:
template<typename PlainObjectType, int Options, typename StrideType> class Ref
: public RefBase<Ref<PlainObjectType, Options, StrideType> >
{
private:
typedef internal::traits<Ref> Traits;
template<typename Derived>
inline Ref(const PlainObjectBase<Derived>& expr);
inline Ref(const PlainObjectBase<Derived>& expr,
typename internal::enable_if<bool(Traits::template match<Derived>::MatchAtCompileTime),Derived>::type* = 0);
public:
typedef RefBase<Ref> Base;
@ -198,13 +201,15 @@ template<typename PlainObjectType, int Options, typename StrideType> class Ref
#ifndef EIGEN_PARSED_BY_DOXYGEN
template<typename Derived>
inline Ref(PlainObjectBase<Derived>& expr)
inline Ref(PlainObjectBase<Derived>& expr,
typename internal::enable_if<bool(Traits::template match<Derived>::MatchAtCompileTime),Derived>::type* = 0)
{
EIGEN_STATIC_ASSERT(static_cast<bool>(Traits::template match<Derived>::MatchAtCompileTime), STORAGE_LAYOUT_DOES_NOT_MATCH);
Base::construct(expr.derived());
}
template<typename Derived>
inline Ref(const DenseBase<Derived>& expr)
inline Ref(const DenseBase<Derived>& expr,
typename internal::enable_if<bool(Traits::template match<Derived>::MatchAtCompileTime),Derived>::type* = 0)
#else
template<typename Derived>
inline Ref(DenseBase<Derived>& expr)
@ -231,7 +236,8 @@ template<typename TPlainObjectType, int Options, typename StrideType> class Ref<
EIGEN_DENSE_PUBLIC_INTERFACE(Ref)
template<typename Derived>
inline Ref(const DenseBase<Derived>& expr)
inline Ref(const DenseBase<Derived>& expr,
typename internal::enable_if<bool(Traits::template match<Derived>::ScalarTypeMatch),Derived>::type* = 0)
{
// std::cout << match_helper<Derived>::HasDirectAccess << "," << match_helper<Derived>::OuterStrideMatch << "," << match_helper<Derived>::InnerStrideMatch << "\n";
// std::cout << int(StrideType::OuterStrideAtCompileTime) << " - " << int(Derived::OuterStrideAtCompileTime) << "\n";

11
uppsrc/plugin/Eigen/Eigen/src/Core/ReturnByValue.h
View file

@ -72,6 +72,8 @@ template<typename Derived> class ReturnByValue
const Unusable& coeff(Index,Index) const { return *reinterpret_cast<const Unusable*>(this); }
Unusable& coeffRef(Index) { return *reinterpret_cast<Unusable*>(this); }
Unusable& coeffRef(Index,Index) { return *reinterpret_cast<Unusable*>(this); }
template<int LoadMode> Unusable& packet(Index) const;
template<int LoadMode> Unusable& packet(Index, Index) const;
#endif
};
@ -83,6 +85,15 @@ Derived& DenseBase<Derived>::operator=(const ReturnByValue<OtherDerived>& other)
return derived();
}
template<typename Derived>
template<typename OtherDerived>
Derived& DenseBase<Derived>::lazyAssign(const ReturnByValue<OtherDerived>& other)
{
other.evalTo(derived());
return derived();
}
} // end namespace Eigen
#endif // EIGEN_RETURNBYVALUE_H

6
uppsrc/plugin/Eigen/Eigen/src/Core/arch/AltiVec/CMakeLists.txt Normal file
View file

@ -0,0 +1,6 @@
FILE(GLOB Eigen_Core_arch_AltiVec_SRCS "*.h")
INSTALL(FILES
${Eigen_Core_arch_AltiVec_SRCS}
DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen/src/Core/arch/AltiVec COMPONENT Devel
)

4
uppsrc/plugin/Eigen/Eigen/src/Core/arch/CMakeLists.txt Normal file
View file

@ -0,0 +1,4 @@
ADD_SUBDIRECTORY(SSE)
ADD_SUBDIRECTORY(AltiVec)
ADD_SUBDIRECTORY(NEON)
ADD_SUBDIRECTORY(Default)

6
uppsrc/plugin/Eigen/Eigen/src/Core/arch/Default/CMakeLists.txt Normal file
View file

@ -0,0 +1,6 @@
FILE(GLOB Eigen_Core_arch_Default_SRCS "*.h")
INSTALL(FILES
${Eigen_Core_arch_Default_SRCS}
DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen/src/Core/arch/Default COMPONENT Devel
)

6
uppsrc/plugin/Eigen/Eigen/src/Core/arch/NEON/CMakeLists.txt Normal file
View file

@ -0,0 +1,6 @@
FILE(GLOB Eigen_Core_arch_NEON_SRCS "*.h")
INSTALL(FILES
${Eigen_Core_arch_NEON_SRCS}
DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen/src/Core/arch/NEON COMPONENT Devel
)

2
uppsrc/plugin/Eigen/Eigen/src/Core/arch/NEON/Complex.h
View file

@ -110,7 +110,7 @@ template<> EIGEN_STRONG_INLINE Packet2cf ploaddup<Packet2cf>(const std::complex<
template<> EIGEN_STRONG_INLINE void pstore <std::complex<float> >(std::complex<float> * to, const Packet2cf& from) { EIGEN_DEBUG_ALIGNED_STORE pstore((float*)to, from.v); }
template<> EIGEN_STRONG_INLINE void pstoreu<std::complex<float> >(std::complex<float> * to, const Packet2cf& from) { EIGEN_DEBUG_UNALIGNED_STORE pstoreu((float*)to, from.v); }
template<> EIGEN_STRONG_INLINE void prefetch<std::complex<float> >(const std::complex<float> * addr) { __pld((float *)addr); }
template<> EIGEN_STRONG_INLINE void prefetch<std::complex<float> >(const std::complex<float> * addr) { EIGEN_ARM_PREFETCH((float *)addr); }
template<> EIGEN_STRONG_INLINE std::complex<float> pfirst<Packet2cf>(const Packet2cf& a)
{

4
uppsrc/plugin/Eigen/Eigen/src/Core/arch/NEON/PacketMath.h
View file

@ -218,8 +218,8 @@ template<> EIGEN_STRONG_INLINE void pstore<int>(int* to, const Packet4i& f
template<> EIGEN_STRONG_INLINE void pstoreu<float>(float* to, const Packet4f& from) { EIGEN_DEBUG_UNALIGNED_STORE vst1q_f32(to, from); }
template<> EIGEN_STRONG_INLINE void pstoreu<int>(int* to, const Packet4i& from) { EIGEN_DEBUG_UNALIGNED_STORE vst1q_s32(to, from); }
template<> EIGEN_STRONG_INLINE void prefetch<float>(const float* addr) { __pld(addr); }
template<> EIGEN_STRONG_INLINE void prefetch<int>(const int* addr) { __pld(addr); }
template<> EIGEN_STRONG_INLINE void prefetch<float>(const float* addr) { EIGEN_ARM_PREFETCH(addr); }
template<> EIGEN_STRONG_INLINE void prefetch<int>(const int* addr) { EIGEN_ARM_PREFETCH(addr); }
// FIXME only store the 2 first elements ?
template<> EIGEN_STRONG_INLINE float pfirst<Packet4f>(const Packet4f& a) { float EIGEN_ALIGN16 x[4]; vst1q_f32(x, a); return x[0]; }

6
uppsrc/plugin/Eigen/Eigen/src/Core/arch/SSE/CMakeLists.txt Normal file
View file

@ -0,0 +1,6 @@
FILE(GLOB Eigen_Core_arch_SSE_SRCS "*.h")
INSTALL(FILES
${Eigen_Core_arch_SSE_SRCS}
DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen/src/Core/arch/SSE COMPONENT Devel
)

6
uppsrc/plugin/Eigen/Eigen/src/Core/products/CMakeLists.txt Normal file
View file

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

75
uppsrc/plugin/Eigen/Eigen/src/Core/products/CoeffBasedProduct.h
View file

@ -134,7 +134,7 @@ class CoeffBasedProduct
};
typedef internal::product_coeff_impl<CanVectorizeInner ? InnerVectorizedTraversal : DefaultTraversal,
Unroll ? (InnerSize==0 ? 0 : InnerSize-1) : Dynamic,
Unroll ? InnerSize : Dynamic,
_LhsNested, _RhsNested, Scalar> ScalarCoeffImpl;
typedef CoeffBasedProduct<LhsNested,RhsNested,NestByRefBit> LazyCoeffBasedProductType;
@ -185,7 +185,7 @@ class CoeffBasedProduct
{
PacketScalar res;
internal::product_packet_impl<Flags&RowMajorBit ? RowMajor : ColMajor,
Unroll ? (InnerSize==0 ? 0 : InnerSize-1) : Dynamic,
Unroll ? InnerSize : Dynamic,
_LhsNested, _RhsNested, PacketScalar, LoadMode>
::run(row, col, m_lhs, m_rhs, res);
return res;
@ -243,7 +243,17 @@ struct product_coeff_impl<DefaultTraversal, UnrollingIndex, Lhs, Rhs, RetScalar>
static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, RetScalar &res)
{
product_coeff_impl<DefaultTraversal, UnrollingIndex-1, Lhs, Rhs, RetScalar>::run(row, col, lhs, rhs, res);
res += lhs.coeff(row, UnrollingIndex) * rhs.coeff(UnrollingIndex, col);
res += lhs.coeff(row, UnrollingIndex-1) * rhs.coeff(UnrollingIndex-1, col);
}
};
template<typename Lhs, typename Rhs, typename RetScalar>
struct product_coeff_impl<DefaultTraversal, 1, Lhs, Rhs, RetScalar>
{
typedef typename Lhs::Index Index;
static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, RetScalar &res)
{
res = lhs.coeff(row, 0) * rhs.coeff(0, col);
}
};
@ -251,9 +261,9 @@ template<typename Lhs, typename Rhs, typename RetScalar>
struct product_coeff_impl<DefaultTraversal, 0, Lhs, Rhs, RetScalar>
{
typedef typename Lhs::Index Index;
static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, RetScalar &res)
static EIGEN_STRONG_INLINE void run(Index /*row*/, Index /*col*/, const Lhs& /*lhs*/, const Rhs& /*rhs*/, RetScalar &res)
{
res = lhs.coeff(row, 0) * rhs.coeff(0, col);
res = RetScalar(0);
}
};
@ -293,6 +303,16 @@ struct product_coeff_vectorized_unroller<0, Lhs, Rhs, Packet>
}
};
template<typename Lhs, typename Rhs, typename RetScalar>
struct product_coeff_impl<InnerVectorizedTraversal, 0, Lhs, Rhs, RetScalar>
{
typedef typename Lhs::Index Index;
static EIGEN_STRONG_INLINE void run(Index /*row*/, Index /*col*/, const Lhs& /*lhs*/, const Rhs& /*rhs*/, RetScalar &res)
{
res = 0;
}
};
template<int UnrollingIndex, typename Lhs, typename Rhs, typename RetScalar>
struct product_coeff_impl<InnerVectorizedTraversal, UnrollingIndex, Lhs, Rhs, RetScalar>
{
@ -302,8 +322,7 @@ struct product_coeff_impl<InnerVectorizedTraversal, UnrollingIndex, Lhs, Rhs, Re
static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, RetScalar &res)
{
Packet pres;
product_coeff_vectorized_unroller<UnrollingIndex+1-PacketSize, Lhs, Rhs, Packet>::run(row, col, lhs, rhs, pres);
product_coeff_impl<DefaultTraversal,UnrollingIndex,Lhs,Rhs,RetScalar>::run(row, col, lhs, rhs, res);
product_coeff_vectorized_unroller<UnrollingIndex-PacketSize, Lhs, Rhs, Packet>::run(row, col, lhs, rhs, pres);
res = predux(pres);
}
};
@ -371,7 +390,7 @@ struct product_packet_impl<RowMajor, UnrollingIndex, Lhs, Rhs, Packet, LoadMode>
static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Packet &res)
{
product_packet_impl<RowMajor, UnrollingIndex-1, Lhs, Rhs, Packet, LoadMode>::run(row, col, lhs, rhs, res);
res = pmadd(pset1<Packet>(lhs.coeff(row, UnrollingIndex)), rhs.template packet<LoadMode>(UnrollingIndex, col), res);
res = pmadd(pset1<Packet>(lhs.coeff(row, UnrollingIndex-1)), rhs.template packet<LoadMode>(UnrollingIndex-1, col), res);
}
};
@ -382,12 +401,12 @@ struct product_packet_impl<ColMajor, UnrollingIndex, Lhs, Rhs, Packet, LoadMode>
static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Packet &res)
{
product_packet_impl<ColMajor, UnrollingIndex-1, Lhs, Rhs, Packet, LoadMode>::run(row, col, lhs, rhs, res);
res = pmadd(lhs.template packet<LoadMode>(row, UnrollingIndex), pset1<Packet>(rhs.coeff(UnrollingIndex, col)), res);
res = pmadd(lhs.template packet<LoadMode>(row, UnrollingIndex-1), pset1<Packet>(rhs.coeff(UnrollingIndex-1, col)), res);
}
};
template<typename Lhs, typename Rhs, typename Packet, int LoadMode>
struct product_packet_impl<RowMajor, 0, Lhs, Rhs, Packet, LoadMode>
struct product_packet_impl<RowMajor, 1, Lhs, Rhs, Packet, LoadMode>
{
typedef typename Lhs::Index Index;
static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Packet &res)
@ -397,7 +416,7 @@ struct product_packet_impl<RowMajor, 0, Lhs, Rhs, Packet, LoadMode>
};
template<typename Lhs, typename Rhs, typename Packet, int LoadMode>
struct product_packet_impl<ColMajor, 0, Lhs, Rhs, Packet, LoadMode>
struct product_packet_impl<ColMajor, 1, Lhs, Rhs, Packet, LoadMode>
{
typedef typename Lhs::Index Index;
static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Packet &res)
@ -406,16 +425,35 @@ struct product_packet_impl<ColMajor, 0, Lhs, Rhs, Packet, LoadMode>
}
};
template<typename Lhs, typename Rhs, typename Packet, int LoadMode>
struct product_packet_impl<RowMajor, 0, Lhs, Rhs, Packet, LoadMode>
{
typedef typename Lhs::Index Index;
static EIGEN_STRONG_INLINE void run(Index /*row*/, Index /*col*/, const Lhs& /*lhs*/, const Rhs& /*rhs*/, Packet &res)
{
res = pset1<Packet>(0);
}
};
template<typename Lhs, typename Rhs, typename Packet, int LoadMode>
struct product_packet_impl<ColMajor, 0, Lhs, Rhs, Packet, LoadMode>
{
typedef typename Lhs::Index Index;
static EIGEN_STRONG_INLINE void run(Index /*row*/, Index /*col*/, const Lhs& /*lhs*/, const Rhs& /*rhs*/, Packet &res)
{
res = pset1<Packet>(0);
}
};
template<typename Lhs, typename Rhs, typename Packet, int LoadMode>
struct product_packet_impl<RowMajor, Dynamic, Lhs, Rhs, Packet, LoadMode>
{
typedef typename Lhs::Index Index;
static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Packet& res)
{
eigen_assert(lhs.cols()>0 && "you are using a non initialized matrix");
res = pmul(pset1<Packet>(lhs.coeff(row, 0)),rhs.template packet<LoadMode>(0, col));
for(Index i = 1; i < lhs.cols(); ++i)
res = pmadd(pset1<Packet>(lhs.coeff(row, i)), rhs.template packet<LoadMode>(i, col), res);
res = pset1<Packet>(0);
for(Index i = 0; i < lhs.cols(); ++i)
res = pmadd(pset1<Packet>(lhs.coeff(row, i)), rhs.template packet<LoadMode>(i, col), res);
}
};
@ -425,10 +463,9 @@ struct product_packet_impl<ColMajor, Dynamic, Lhs, Rhs, Packet, LoadMode>
typedef typename Lhs::Index Index;
static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Packet& res)
{
eigen_assert(lhs.cols()>0 && "you are using a non initialized matrix");
res = pmul(lhs.template packet<LoadMode>(row, 0), pset1<Packet>(rhs.coeff(0, col)));
for(Index i = 1; i < lhs.cols(); ++i)
res = pmadd(lhs.template packet<LoadMode>(row, i), pset1<Packet>(rhs.coeff(i, col)), res);
res = pset1<Packet>(0);
for(Index i = 0; i < lhs.cols(); ++i)
res = pmadd(lhs.template packet<LoadMode>(row, i), pset1<Packet>(rhs.coeff(i, col)), res);
}
};

17
uppsrc/plugin/Eigen/Eigen/src/Core/products/Parallelizer.h
View file

@ -125,19 +125,22 @@ void parallelize_gemm(const Functor& func, Index rows, Index cols, bool transpos
if(transpose)
std::swap(rows,cols);
Index blockCols = (cols / threads) & ~Index(0x3);
Index blockRows = (rows / threads) & ~Index(0x7);
GemmParallelInfo<Index>* info = new GemmParallelInfo<Index>[threads];
#pragma omp parallel for schedule(static,1) num_threads(threads)
for(Index i=0; i<threads; ++i)
#pragma omp parallel num_threads(threads)
{
Index i = omp_get_thread_num();
// Note that the actual number of threads might be lower than the number of request ones.
Index actual_threads = omp_get_num_threads();
Index blockCols = (cols / actual_threads) & ~Index(0x3);
Index blockRows = (rows / actual_threads) & ~Index(0x7);
Index r0 = i*blockRows;
Index actualBlockRows = (i+1==threads) ? rows-r0 : blockRows;
Index actualBlockRows = (i+1==actual_threads) ? rows-r0 : blockRows;
Index c0 = i*blockCols;
Index actualBlockCols = (i+1==threads) ? cols-c0 : blockCols;
Index actualBlockCols = (i+1==actual_threads) ? cols-c0 : blockCols;
info[i].rhs_start = c0;
info[i].rhs_length = actualBlockCols;

6
uppsrc/plugin/Eigen/Eigen/src/Core/util/CMakeLists.txt Normal file
View file

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

13
uppsrc/plugin/Eigen/Eigen/src/Core/util/Constants.h
View file

@ -433,6 +433,19 @@ struct MatrixXpr {};
/** The type used to identify an array expression */
struct ArrayXpr {};
namespace internal {
/** \internal
* Constants for comparison functors
*/
enum ComparisonName {
cmp_EQ = 0,
cmp_LT = 1,
cmp_LE = 2,
cmp_UNORD = 3,
cmp_NEQ = 4
};
}
} // end namespace Eigen
#endif // EIGEN_CONSTANTS_H

12
uppsrc/plugin/Eigen/Eigen/src/Core/util/Macros.h
View file

@ -13,7 +13,7 @@
#define EIGEN_WORLD_VERSION 3
#define EIGEN_MAJOR_VERSION 2
#define EIGEN_MINOR_VERSION 3
#define EIGEN_MINOR_VERSION 5
#define EIGEN_VERSION_AT_LEAST(x,y,z) (EIGEN_WORLD_VERSION>x || (EIGEN_WORLD_VERSION>=x && \
(EIGEN_MAJOR_VERSION>y || (EIGEN_MAJOR_VERSION>=y && \
@ -278,6 +278,7 @@ namespace Eigen {
#error Please tell me what is the equivalent of __attribute__((aligned(n))) for your compiler
#endif
#define EIGEN_ALIGN8 EIGEN_ALIGN_TO_BOUNDARY(8)
#define EIGEN_ALIGN16 EIGEN_ALIGN_TO_BOUNDARY(16)
#if EIGEN_ALIGN_STATICALLY
@ -313,7 +314,7 @@ namespace Eigen {
// just an empty macro !
#define EIGEN_EMPTY
#if defined(_MSC_VER) && (!defined(__INTEL_COMPILER))
#if defined(_MSC_VER) && (_MSC_VER < 1800) && (!defined(__INTEL_COMPILER))
#define EIGEN_INHERIT_ASSIGNMENT_EQUAL_OPERATOR(Derived) \
using Base::operator =;
#elif defined(__clang__) // workaround clang bug (see http://forum.kde.org/viewtopic.php?f=74&t=102653)
@ -332,8 +333,11 @@ namespace Eigen {
}
#endif
#define EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Derived) \
EIGEN_INHERIT_ASSIGNMENT_EQUAL_OPERATOR(Derived)
/** \internal
* \brief Macro to manually inherit assignment operators.
* This is necessary, because the implicitly defined assignment operator gets deleted when a custom operator= is defined.
*/
#define EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Derived) EIGEN_INHERIT_ASSIGNMENT_EQUAL_OPERATOR(Derived)
/**
* Just a side note. Commenting within defines works only by documenting

7
uppsrc/plugin/Eigen/Eigen/src/Core/util/Memory.h
View file

@ -466,9 +466,8 @@ template<typename T, bool Align> inline void conditional_aligned_delete_auto(T *
template<typename Scalar, typename Index>
static inline Index first_aligned(const Scalar* array, Index size)
{
enum { PacketSize = packet_traits<Scalar>::size,
PacketAlignedMask = PacketSize-1
};
static const Index PacketSize = packet_traits<Scalar>::size;
static const Index PacketAlignedMask = PacketSize-1;
if(PacketSize==1)
{
@ -524,7 +523,7 @@ template<typename T> struct smart_copy_helper<T,false> {
// you can overwrite Eigen's default behavior regarding alloca by defining EIGEN_ALLOCA
// to the appropriate stack allocation function
#ifndef EIGEN_ALLOCA
#if (defined __linux__)
#if (defined __linux__) || (defined __APPLE__) || (defined alloca)
#define EIGEN_ALLOCA alloca
#elif defined(_MSC_VER)
#define EIGEN_ALLOCA _alloca

8
uppsrc/plugin/Eigen/Eigen/src/Eigen2Support/CMakeLists.txt Normal file
View file

@ -0,0 +1,8 @@
FILE(GLOB Eigen_Eigen2Support_SRCS "*.h")
INSTALL(FILES
${Eigen_Eigen2Support_SRCS}
DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen/src/Eigen2Support COMPONENT Devel
)
ADD_SUBDIRECTORY(Geometry)

6
uppsrc/plugin/Eigen/Eigen/src/Eigen2Support/Geometry/CMakeLists.txt Normal file
View file

@ -0,0 +1,6 @@
FILE(GLOB Eigen_Eigen2Support_Geometry_SRCS "*.h")
INSTALL(FILES
${Eigen_Eigen2Support_Geometry_SRCS}
DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen/src/Eigen2Support/Geometry
)

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

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

8
uppsrc/plugin/Eigen/Eigen/src/Eigenvalues/ComplexEigenSolver.h
View file

@ -234,6 +234,12 @@ template<typename _MatrixType> class ComplexEigenSolver
}
protected:
static void check_template_parameters()
{
EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar);
}
EigenvectorType m_eivec;
EigenvalueType m_eivalues;
ComplexSchur<MatrixType> m_schur;
@ -251,6 +257,8 @@ template<typename MatrixType>
ComplexEigenSolver<MatrixType>&
ComplexEigenSolver<MatrixType>::compute(const MatrixType& matrix, bool computeEigenvectors)
{
check_template_parameters();
// this code is inspired from Jampack
eigen_assert(matrix.cols() == matrix.rows());

9
uppsrc/plugin/Eigen/Eigen/src/Eigenvalues/EigenSolver.h
View file

@ -298,6 +298,13 @@ template<typename _MatrixType> class EigenSolver
void doComputeEigenvectors();
protected:
static void check_template_parameters()
{
EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar);
EIGEN_STATIC_ASSERT(!NumTraits<Scalar>::IsComplex, NUMERIC_TYPE_MUST_BE_REAL);
}
MatrixType m_eivec;
EigenvalueType m_eivalues;
bool m_isInitialized;
@ -364,6 +371,8 @@ template<typename MatrixType>
EigenSolver<MatrixType>&
EigenSolver<MatrixType>::compute(const MatrixType& matrix, bool computeEigenvectors)
{
check_template_parameters();
using std::sqrt;
using std::abs;
eigen_assert(matrix.cols() == matrix.rows());

9
uppsrc/plugin/Eigen/Eigen/src/Eigenvalues/GeneralizedEigenSolver.h
View file

@ -263,6 +263,13 @@ template<typename _MatrixType> class GeneralizedEigenSolver
}
protected:
static void check_template_parameters()
{
EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar);
EIGEN_STATIC_ASSERT(!NumTraits<Scalar>::IsComplex, NUMERIC_TYPE_MUST_BE_REAL);
}
MatrixType m_eivec;
ComplexVectorType m_alphas;
VectorType m_betas;
@ -290,6 +297,8 @@ template<typename MatrixType>
GeneralizedEigenSolver<MatrixType>&
GeneralizedEigenSolver<MatrixType>::compute(const MatrixType& A, const MatrixType& B, bool computeEigenvectors)
{
check_template_parameters();
using std::sqrt;
using std::abs;
eigen_assert(A.cols() == A.rows() && B.cols() == A.rows() && B.cols() == B.rows());

14
uppsrc/plugin/Eigen/Eigen/src/Eigenvalues/RealQZ.h
View file

@ -240,10 +240,10 @@ namespace Eigen {
m_S.coeffRef(i,j) = Scalar(0.0);
m_S.rightCols(dim-j-1).applyOnTheLeft(i-1,i,G.adjoint());
m_T.rightCols(dim-i+1).applyOnTheLeft(i-1,i,G.adjoint());
// update Q
if (m_computeQZ)
m_Q.applyOnTheRight(i-1,i,G);
}
// update Q
if (m_computeQZ)
m_Q.applyOnTheRight(i-1,i,G);
// kill T(i,i-1)
if(m_T.coeff(i,i-1)!=Scalar(0))
{
@ -251,10 +251,10 @@ namespace Eigen {
m_T.coeffRef(i,i-1) = Scalar(0.0);
m_S.applyOnTheRight(i,i-1,G);
m_T.topRows(i).applyOnTheRight(i,i-1,G);
// update Z
if (m_computeQZ)
m_Z.applyOnTheLeft(i,i-1,G.adjoint());
}
// update Z
if (m_computeQZ)
m_Z.applyOnTheLeft(i,i-1,G.adjoint());
}
}
}
@ -313,7 +313,7 @@ namespace Eigen {
using std::abs;
using std::sqrt;
const Index dim=m_S.cols();
if (abs(m_S.coeff(i+1,i)==Scalar(0)))
if (abs(m_S.coeff(i+1,i))==Scalar(0))
return;
Index z = findSmallDiagEntry(i,i+1);
if (z==i-1)

12
uppsrc/plugin/Eigen/Eigen/src/Eigenvalues/RealSchur.h
View file

@ -234,7 +234,7 @@ template<typename _MatrixType> class RealSchur
typedef Matrix<Scalar,3,1> Vector3s;
Scalar computeNormOfT();
Index findSmallSubdiagEntry(Index iu, const Scalar& norm);
Index findSmallSubdiagEntry(Index iu);
void splitOffTwoRows(Index iu, bool computeU, const Scalar& exshift);
void computeShift(Index iu, Index iter, Scalar& exshift, Vector3s& shiftInfo);
void initFrancisQRStep(Index il, Index iu, const Vector3s& shiftInfo, Index& im, Vector3s& firstHouseholderVector);
@ -286,7 +286,7 @@ RealSchur<MatrixType>& RealSchur<MatrixType>::computeFromHessenberg(const HessMa
{
while (iu >= 0)
{
Index il = findSmallSubdiagEntry(iu, norm);
Index il = findSmallSubdiagEntry(iu);
// Check for convergence
if (il == iu) // One root found
@ -343,16 +343,14 @@ inline typename MatrixType::Scalar RealSchur<MatrixType>::computeNormOfT()
/** \internal Look for single small sub-diagonal element and returns its index */
template<typename MatrixType>
inline typename MatrixType::Index RealSchur<MatrixType>::findSmallSubdiagEntry(Index iu, const Scalar& norm)
inline typename MatrixType::Index RealSchur<MatrixType>::findSmallSubdiagEntry(Index iu)
{
using std::abs;
Index res = iu;
while (res > 0)
{
Scalar s = abs(m_matT.coeff(res-1,res-1)) + abs(m_matT.coeff(res,res));
if (s == 0.0)
s = norm;
if (abs(m_matT.coeff(res,res-1)) < NumTraits<Scalar>::epsilon() * s)
if (abs(m_matT.coeff(res,res-1)) <= NumTraits<Scalar>::epsilon() * s)
break;
res--;
}
@ -457,9 +455,7 @@ inline void RealSchur<MatrixType>::initFrancisQRStep(Index il, Index iu, const V
const Scalar lhs = m_matT.coeff(im,im-1) * (abs(v.coeff(1)) + abs(v.coeff(2)));
const Scalar rhs = v.coeff(0) * (abs(m_matT.coeff(im-1,im-1)) + abs(Tmm) + abs(m_matT.coeff(im+1,im+1)));
if (abs(lhs) < NumTraits<Scalar>::epsilon() * rhs)
{
break;
}
}
}

216
uppsrc/plugin/Eigen/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h
View file

@ -351,6 +351,11 @@ template<typename _MatrixType> class SelfAdjointEigenSolver
#endif // EIGEN2_SUPPORT
protected:
static void check_template_parameters()
{
EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar);
}
MatrixType m_eivec;
RealVectorType m_eivalues;
typename TridiagonalizationType::SubDiagonalType m_subdiag;
@ -384,6 +389,8 @@ template<typename MatrixType>
SelfAdjointEigenSolver<MatrixType>& SelfAdjointEigenSolver<MatrixType>
::compute(const MatrixType& matrix, int options)
{
check_template_parameters();
using std::abs;
eigen_assert(matrix.cols() == matrix.rows());
eigen_assert((options&~(EigVecMask|GenEigMask))==0
@ -490,7 +497,12 @@ template<typename SolverType> struct direct_selfadjoint_eigenvalues<SolverType,3
typedef typename SolverType::MatrixType MatrixType;
typedef typename SolverType::RealVectorType VectorType;
typedef typename SolverType::Scalar Scalar;
typedef typename MatrixType::Index Index;
/** \internal
* Computes the roots of the characteristic polynomial of \a m.
* For numerical stability m.trace() should be near zero and to avoid over- or underflow m should be normalized.
*/
static inline void computeRoots(const MatrixType& m, VectorType& roots)
{
using std::sqrt;
@ -510,39 +522,48 @@ template<typename SolverType> struct direct_selfadjoint_eigenvalues<SolverType,3
// Construct the parameters used in classifying the roots of the equation
// and in solving the equation for the roots in closed form.
Scalar c2_over_3 = c2*s_inv3;
Scalar a_over_3 = (c1 - c2*c2_over_3)*s_inv3;
if (a_over_3 > Scalar(0))
Scalar a_over_3 = (c2*c2_over_3 - c1)*s_inv3;
if(a_over_3<Scalar(0))
a_over_3 = Scalar(0);
Scalar half_b = Scalar(0.5)*(c0 + c2_over_3*(Scalar(2)*c2_over_3*c2_over_3 - c1));
Scalar q = half_b*half_b + a_over_3*a_over_3*a_over_3;
if (q > Scalar(0))
Scalar q = a_over_3*a_over_3*a_over_3 - half_b*half_b;
if(q<Scalar(0))
q = Scalar(0);
// Compute the eigenvalues by solving for the roots of the polynomial.
Scalar rho = sqrt(-a_over_3);
Scalar theta = atan2(sqrt(-q),half_b)*s_inv3;
Scalar rho = sqrt(a_over_3);
Scalar theta = atan2(sqrt(q),half_b)*s_inv3; // since sqrt(q) > 0, atan2 is in [0, pi] and theta is in [0, pi/3]
Scalar cos_theta = cos(theta);
Scalar sin_theta = sin(theta);
roots(0) = c2_over_3 + Scalar(2)*rho*cos_theta;
roots(1) = c2_over_3 - rho*(cos_theta + s_sqrt3*sin_theta);
roots(2) = c2_over_3 - rho*(cos_theta - s_sqrt3*sin_theta);
// Sort in increasing order.
if (roots(0) >= roots(1))
std::swap(roots(0),roots(1));
if (roots(1) >= roots(2))
{
std::swap(roots(1),roots(2));
if (roots(0) >= roots(1))
std::swap(roots(0),roots(1));
}
// roots are already sorted, since cos is monotonically decreasing on [0, pi]
roots(0) = c2_over_3 - rho*(cos_theta + s_sqrt3*sin_theta); // == 2*rho*cos(theta+2pi/3)
roots(1) = c2_over_3 - rho*(cos_theta - s_sqrt3*sin_theta); // == 2*rho*cos(theta+ pi/3)
roots(2) = c2_over_3 + Scalar(2)*rho*cos_theta;
}
static inline bool extract_kernel(MatrixType& mat, Ref<VectorType> res, Ref<VectorType> representative)
{
using std::abs;
Index i0;
// Find non-zero column i0 (by construction, there must exist a non zero coefficient on the diagonal):
mat.diagonal().cwiseAbs().maxCoeff(&i0);
// mat.col(i0) is a good candidate for an orthogonal vector to the current eigenvector,
// so let's save it:
representative = mat.col(i0);
Scalar n0, n1;
VectorType c0, c1;
n0 = (c0 = representative.cross(mat.col((i0+1)%3))).squaredNorm();
n1 = (c1 = representative.cross(mat.col((i0+2)%3))).squaredNorm();
if(n0>n1) res = c0/std::sqrt(n0);
else res = c1/std::sqrt(n1);
return true;
}
static inline void run(SolverType& solver, const MatrixType& mat, int options)
{
using std::sqrt;
eigen_assert(mat.cols() == 3 && mat.cols() == mat.rows());
eigen_assert((options&~(EigVecMask|GenEigMask))==0
&& (options&EigVecMask)!=EigVecMask
@ -552,116 +573,72 @@ template<typename SolverType> struct direct_selfadjoint_eigenvalues<SolverType,3
MatrixType& eivecs = solver.m_eivec;
VectorType& eivals = solver.m_eivalues;
// map the matrix coefficients to [-1:1] to avoid over- and underflow.
Scalar scale = mat.cwiseAbs().maxCoeff();
MatrixType scaledMat = mat / scale;
// Shift the matrix to the mean eigenvalue and map the matrix coefficients to [-1:1] to avoid over- and underflow.
Scalar shift = mat.trace() / Scalar(3);
// TODO Avoid this copy. Currently it is necessary to suppress bogus values when determining maxCoeff and for computing the eigenvectors later
MatrixType scaledMat = mat.template selfadjointView<Lower>();
scaledMat.diagonal().array() -= shift;
Scalar scale = scaledMat.cwiseAbs().maxCoeff();
if(scale > 0) scaledMat /= scale; // TODO for scale==0 we could save the remaining operations
// compute the eigenvalues
computeRoots(scaledMat,eivals);
// compute the eigen vectors
// compute the eigenvectors
if(computeEigenvectors)
{
Scalar safeNorm2 = Eigen::NumTraits<Scalar>::epsilon();
if((eivals(2)-eivals(0))<=Eigen::NumTraits<Scalar>::epsilon())
{
// All three eigenvalues are numerically the same
eivecs.setIdentity();
}
else
{
scaledMat = scaledMat.template selfadjointView<Lower>();
MatrixType tmp;
tmp = scaledMat;
// Compute the eigenvector of the most distinct eigenvalue
Scalar d0 = eivals(2) - eivals(1);
Scalar d1 = eivals(1) - eivals(0);
int k = d0 > d1 ? 2 : 0;
d0 = d0 > d1 ? d0 : d1;
tmp.diagonal().array () -= eivals(k);
VectorType cross;
Scalar n;
n = (cross = tmp.row(0).cross(tmp.row(1))).squaredNorm();
if(n>safeNorm2)
Index k(0), l(2);
if(d0 > d1)
{
eivecs.col(k) = cross / sqrt(n);
std::swap(k,l);
d0 = d1;
}
// Compute the eigenvector of index k
{
tmp.diagonal().array () -= eivals(k);
// By construction, 'tmp' is of rank 2, and its kernel corresponds to the respective eigenvector.
extract_kernel(tmp, eivecs.col(k), eivecs.col(l));
}
// Compute eigenvector of index l
if(d0<=2*Eigen::NumTraits<Scalar>::epsilon()*d1)
{
// If d0 is too small, then the two other eigenvalues are numerically the same,
// and thus we only have to ortho-normalize the near orthogonal vector we saved above.
eivecs.col(l) -= eivecs.col(k).dot(eivecs.col(l))*eivecs.col(l);
eivecs.col(l).normalize();
}
else
{
n = (cross = tmp.row(0).cross(tmp.row(2))).squaredNorm();
tmp = scaledMat;
tmp.diagonal().array () -= eivals(l);
if(n>safeNorm2)
{
eivecs.col(k) = cross / sqrt(n);
}
else
{
n = (cross = tmp.row(1).cross(tmp.row(2))).squaredNorm();
if(n>safeNorm2)
{
eivecs.col(k) = cross / sqrt(n);
}
else
{
// the input matrix and/or the eigenvaues probably contains some inf/NaN,
// => exit
// scale back to the original size.
eivals *= scale;
solver.m_info = NumericalIssue;
solver.m_isInitialized = true;
solver.m_eigenvectorsOk = computeEigenvectors;
return;
}
}
VectorType dummy;
extract_kernel(tmp, eivecs.col(l), dummy);
}
tmp = scaledMat;
tmp.diagonal().array() -= eivals(1);
if(d0<=Eigen::NumTraits<Scalar>::epsilon())
{
eivecs.col(1) = eivecs.col(k).unitOrthogonal();
}
else
{
n = (cross = eivecs.col(k).cross(tmp.row(0))).squaredNorm();
if(n>safeNorm2)
{
eivecs.col(1) = cross / sqrt(n);
}
else
{
n = (cross = eivecs.col(k).cross(tmp.row(1))).squaredNorm();
if(n>safeNorm2)
eivecs.col(1) = cross / sqrt(n);
else
{
n = (cross = eivecs.col(k).cross(tmp.row(2))).squaredNorm();
if(n>safeNorm2)
eivecs.col(1) = cross / sqrt(n);
else
{
// we should never reach this point,
// if so the last two eigenvalues are likely to be very close to each other
eivecs.col(1) = eivecs.col(k).unitOrthogonal();
}
}
}
// make sure that eivecs[1] is orthogonal to eivecs[2]
// FIXME: this step should not be needed
Scalar d = eivecs.col(1).dot(eivecs.col(k));
eivecs.col(1) = (eivecs.col(1) - d * eivecs.col(k)).normalized();
}
eivecs.col(k==2 ? 0 : 2) = eivecs.col(k).cross(eivecs.col(1)).normalized();
// Compute last eigenvector from the other two
eivecs.col(1) = eivecs.col(2).cross(eivecs.col(0)).normalized();
}
}
// Rescale back to the original size.
eivals *= scale;
eivals.array() += shift;
solver.m_info = Success;
solver.m_isInitialized = true;
@ -679,7 +656,7 @@ template<typename SolverType> struct direct_selfadjoint_eigenvalues<SolverType,2
static inline void computeRoots(const MatrixType& m, VectorType& roots)
{
using std::sqrt;
const Scalar t0 = Scalar(0.5) * sqrt( numext::abs2(m(0,0)-m(1,1)) + Scalar(4)*m(1,0)*m(1,0));
const Scalar t0 = Scalar(0.5) * sqrt( numext::abs2(m(0,0)-m(1,1)) + Scalar(4)*numext::abs2(m(1,0)));
const Scalar t1 = Scalar(0.5) * (m(0,0) + m(1,1));
roots(0) = t1 - t0;
roots(1) = t1 + t0;
@ -688,6 +665,8 @@ template<typename SolverType> struct direct_selfadjoint_eigenvalues<SolverType,2
static inline void run(SolverType& solver, const MatrixType& mat, int options)
{
using std::sqrt;
using std::abs;
eigen_assert(mat.cols() == 2 && mat.cols() == mat.rows());
eigen_assert((options&~(EigVecMask|GenEigMask))==0
&& (options&EigVecMask)!=EigVecMask
@ -708,22 +687,29 @@ template<typename SolverType> struct direct_selfadjoint_eigenvalues<SolverType,2
// compute the eigen vectors
if(computeEigenvectors)
{
scaledMat.diagonal().array () -= eivals(1);
Scalar a2 = numext::abs2(scaledMat(0,0));
Scalar c2 = numext::abs2(scaledMat(1,1));
Scalar b2 = numext::abs2(scaledMat(1,0));
if(a2>c2)
if((eivals(1)-eivals(0))<=abs(eivals(1))*Eigen::NumTraits<Scalar>::epsilon())
{
eivecs.col(1) << -scaledMat(1,0), scaledMat(0,0);
eivecs.col(1) /= sqrt(a2+b2);
eivecs.setIdentity();
}
else
{
eivecs.col(1) << -scaledMat(1,1), scaledMat(1,0);
eivecs.col(1) /= sqrt(c2+b2);
}
scaledMat.diagonal().array () -= eivals(1);
Scalar a2 = numext::abs2(scaledMat(0,0));
Scalar c2 = numext::abs2(scaledMat(1,1));
Scalar b2 = numext::abs2(scaledMat(1,0));
if(a2>c2)
{
eivecs.col(1) << -scaledMat(1,0), scaledMat(0,0);
eivecs.col(1) /= sqrt(a2+b2);
}
else
{
eivecs.col(1) << -scaledMat(1,1), scaledMat(1,0);
eivecs.col(1) /= sqrt(c2+b2);
}
eivecs.col(0) << eivecs.col(1).unitOrthogonal();
eivecs.col(0) << eivecs.col(1).unitOrthogonal();
}
}
// Rescale back to the original size.

83
uppsrc/plugin/Eigen/Eigen/src/Geometry/AlignedBox.h
View file

@ -19,10 +19,12 @@ namespace Eigen {
*
* \brief An axis aligned box
*
* \param _Scalar the type of the scalar coefficients
* \param _AmbientDim the dimension of the ambient space, can be a compile time value or Dynamic.
* \tparam _Scalar the type of the scalar coefficients
* \tparam _AmbientDim the dimension of the ambient space, can be a compile time value or Dynamic.
*
* This class represents an axis aligned box as a pair of the minimal and maximal corners.
* \warning The result of most methods is undefined when applied to an empty box. You can check for empty boxes using isEmpty().
* \sa alignedboxtypedefs
*/
template <typename _Scalar, int _AmbientDim>
class AlignedBox
@ -40,18 +42,21 @@ EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF_VECTORIZABLE_FIXED_SIZE(_Scalar,_AmbientDim)
/** Define constants to name the corners of a 1D, 2D or 3D axis aligned bounding box */
enum CornerType
{
/** 1D names */
/** 1D names @{ */
Min=0, Max=1,
/** @} */
/** Added names for 2D */
/** Identifier for 2D corner @{ */
BottomLeft=0, BottomRight=1,
TopLeft=2, TopRight=3,
/** @} */
/** Added names for 3D */
/** Identifier for 3D corner @{ */
BottomLeftFloor=0, BottomRightFloor=1,
TopLeftFloor=2, TopRightFloor=3,
BottomLeftCeil=4, BottomRightCeil=5,
TopLeftCeil=6, TopRightCeil=7
/** @} */
};
@ -63,34 +68,33 @@ EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF_VECTORIZABLE_FIXED_SIZE(_Scalar,_AmbientDim)
inline explicit AlignedBox(Index _dim) : m_min(_dim), m_max(_dim)
{ setEmpty(); }
/** Constructs a box with extremities \a _min and \a _max. */
/** Constructs a box with extremities \a _min and \a _max.
* \warning If either component of \a _min is larger than the same component of \a _max, the constructed box is empty. */
template<typename OtherVectorType1, typename OtherVectorType2>
inline AlignedBox(const OtherVectorType1& _min, const OtherVectorType2& _max) : m_min(_min), m_max(_max) {}
/** Constructs a box containing a single point \a p. */
template<typename Derived>
inline explicit AlignedBox(const MatrixBase<Derived>& a_p)
{
typename internal::nested<Derived,2>::type p(a_p.derived());
m_min = p;
m_max = p;
}
inline explicit AlignedBox(const MatrixBase<Derived>& p) : m_min(p), m_max(m_min)
{ }
~AlignedBox() {}
/** \returns the dimension in which the box holds */
inline Index dim() const { return AmbientDimAtCompileTime==Dynamic ? m_min.size() : Index(AmbientDimAtCompileTime); }
/** \deprecated use isEmpty */
/** \deprecated use isEmpty() */
inline bool isNull() const { return isEmpty(); }
/** \deprecated use setEmpty */
/** \deprecated use setEmpty() */
inline void setNull() { setEmpty(); }
/** \returns true if the box is empty. */
/** \returns true if the box is empty.
* \sa setEmpty */
inline bool isEmpty() const { return (m_min.array() > m_max.array()).any(); }
/** Makes \c *this an empty box. */
/** Makes \c *this an empty box.
* \sa isEmpty */
inline void setEmpty()
{
m_min.setConstant( ScalarTraits::highest() );
@ -175,27 +179,34 @@ EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF_VECTORIZABLE_FIXED_SIZE(_Scalar,_AmbientDim)
/** \returns true if the point \a p is inside the box \c *this. */
template<typename Derived>
inline bool contains(const MatrixBase<Derived>& a_p) const
inline bool contains(const MatrixBase<Derived>& p) const
{
typename internal::nested<Derived,2>::type p(a_p.derived());
return (m_min.array()<=p.array()).all() && (p.array()<=m_max.array()).all();
typename internal::nested<Derived,2>::type p_n(p.derived());
return (m_min.array()<=p_n.array()).all() && (p_n.array()<=m_max.array()).all();
}
/** \returns true if the box \a b is entirely inside the box \c *this. */
inline bool contains(const AlignedBox& b) const
{ return (m_min.array()<=(b.min)().array()).all() && ((b.max)().array()<=m_max.array()).all(); }
/** Extends \c *this such that it contains the point \a p and returns a reference to \c *this. */
/** \returns true if the box \a b is intersecting the box \c *this.
* \sa intersection, clamp */
inline bool intersects(const AlignedBox& b) const
{ return (m_min.array()<=(b.max)().array()).all() && ((b.min)().array()<=m_max.array()).all(); }
/** Extends \c *this such that it contains the point \a p and returns a reference to \c *this.
* \sa extend(const AlignedBox&) */
template<typename Derived>
inline AlignedBox& extend(const MatrixBase<Derived>& a_p)
inline AlignedBox& extend(const MatrixBase<Derived>& p)
{
typename internal::nested<Derived,2>::type p(a_p.derived());
m_min = m_min.cwiseMin(p);
m_max = m_max.cwiseMax(p);
typename internal::nested<Derived,2>::type p_n(p.derived());
m_min = m_min.cwiseMin(p_n);
m_max = m_max.cwiseMax(p_n);
return *this;
}
/** Extends \c *this such that it contains the box \a b and returns a reference to \c *this. */
/** Extends \c *this such that it contains the box \a b and returns a reference to \c *this.
* \sa merged, extend(const MatrixBase&) */
inline AlignedBox& extend(const AlignedBox& b)
{
m_min = m_min.cwiseMin(b.m_min);
@ -203,7 +214,9 @@ EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF_VECTORIZABLE_FIXED_SIZE(_Scalar,_AmbientDim)
return *this;
}
/** Clamps \c *this by the box \a b and returns a reference to \c *this. */
/** Clamps \c *this by the box \a b and returns a reference to \c *this.
* \note If the boxes don't intersect, the resulting box is empty.
* \sa intersection(), intersects() */
inline AlignedBox& clamp(const AlignedBox& b)
{
m_min = m_min.cwiseMax(b.m_min);
@ -211,11 +224,15 @@ EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF_VECTORIZABLE_FIXED_SIZE(_Scalar,_AmbientDim)
return *this;
}
/** Returns an AlignedBox that is the intersection of \a b and \c *this */
/** Returns an AlignedBox that is the intersection of \a b and \c *this
* \note If the boxes don't intersect, the resulting box is empty.
* \sa intersects(), clamp, contains() */
inline AlignedBox intersection(const AlignedBox& b) const
{return AlignedBox(m_min.cwiseMax(b.m_min), m_max.cwiseMin(b.m_max)); }
/** Returns an AlignedBox that is the union of \a b and \c *this */
/** Returns an AlignedBox that is the union of \a b and \c *this.
* \note Merging with an empty box may result in a box bigger than \c *this.
* \sa extend(const AlignedBox&) */
inline AlignedBox merged(const AlignedBox& b) const
{ return AlignedBox(m_min.cwiseMin(b.m_min), m_max.cwiseMax(b.m_max)); }
@ -231,20 +248,20 @@ EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF_VECTORIZABLE_FIXED_SIZE(_Scalar,_AmbientDim)
/** \returns the squared distance between the point \a p and the box \c *this,
* and zero if \a p is inside the box.
* \sa exteriorDistance()
* \sa exteriorDistance(const MatrixBase&), squaredExteriorDistance(const AlignedBox&)
*/
template<typename Derived>
inline Scalar squaredExteriorDistance(const MatrixBase<Derived>& a_p) const;
inline Scalar squaredExteriorDistance(const MatrixBase<Derived>& p) const;
/** \returns the squared distance between the boxes \a b and \c *this,
* and zero if the boxes intersect.
* \sa exteriorDistance()
* \sa exteriorDistance(const AlignedBox&), squaredExteriorDistance(const MatrixBase&)
*/
inline Scalar squaredExteriorDistance(const AlignedBox& b) const;
/** \returns the distance between the point \a p and the box \c *this,
* and zero if \a p is inside the box.
* \sa squaredExteriorDistance()
* \sa squaredExteriorDistance(const MatrixBase&), exteriorDistance(const AlignedBox&)
*/
template<typename Derived>
inline NonInteger exteriorDistance(const MatrixBase<Derived>& p) const
@ -252,7 +269,7 @@ EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF_VECTORIZABLE_FIXED_SIZE(_Scalar,_AmbientDim)
/** \returns the distance between the boxes \a b and \c *this,
* and zero if the boxes intersect.
* \sa squaredExteriorDistance()
* \sa squaredExteriorDistance(const AlignedBox&), exteriorDistance(const MatrixBase&)
*/
inline NonInteger exteriorDistance(const AlignedBox& b) const
{ using std::sqrt; return sqrt(NonInteger(squaredExteriorDistance(b))); }

8
uppsrc/plugin/Eigen/Eigen/src/Geometry/CMakeLists.txt Normal file
View file

@ -0,0 +1,8 @@
FILE(GLOB Eigen_Geometry_SRCS "*.h")
INSTALL(FILES
${Eigen_Geometry_SRCS}
DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen/src/Geometry COMPONENT Devel
)
ADD_SUBDIRECTORY(arch)

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

@ -79,7 +79,7 @@ template<typename MatrixType,int _Direction> class Homogeneous
{
if( (int(Direction)==Vertical && row==m_matrix.rows())
|| (int(Direction)==Horizontal && col==m_matrix.cols()))
return 1;
return Scalar(1);
return m_matrix.coeff(row, col);
}

22
uppsrc/plugin/Eigen/Eigen/src/Geometry/Quaternion.h
View file

@ -161,7 +161,7 @@ public:
{ return coeffs().isApprox(other.coeffs(), prec); }
/** return the result vector of \a v through the rotation*/
EIGEN_STRONG_INLINE Vector3 _transformVector(Vector3 v) const;
EIGEN_STRONG_INLINE Vector3 _transformVector(const Vector3& v) const;
/** \returns \c *this with scalar type casted to \a NewScalarType
*
@ -231,7 +231,7 @@ class Quaternion : public QuaternionBase<Quaternion<_Scalar,_Options> >
public:
typedef _Scalar Scalar;
EIGEN_INHERIT_ASSIGNMENT_EQUAL_OPERATOR(Quaternion)
EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Quaternion)
using Base::operator*=;
typedef typename internal::traits<Quaternion>::Coefficients Coefficients;
@ -341,7 +341,7 @@ class Map<const Quaternion<_Scalar>, _Options >
public:
typedef _Scalar Scalar;
typedef typename internal::traits<Map>::Coefficients Coefficients;
EIGEN_INHERIT_ASSIGNMENT_EQUAL_OPERATOR(Map)
EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Map)
using Base::operator*=;
/** Constructs a Mapped Quaternion object from the pointer \a coeffs
@ -378,7 +378,7 @@ class Map<Quaternion<_Scalar>, _Options >
public:
typedef _Scalar Scalar;
typedef typename internal::traits<Map>::Coefficients Coefficients;
EIGEN_INHERIT_ASSIGNMENT_EQUAL_OPERATOR(Map)
EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Map)
using Base::operator*=;
/** Constructs a Mapped Quaternion object from the pointer \a coeffs
@ -461,7 +461,7 @@ EIGEN_STRONG_INLINE Derived& QuaternionBase<Derived>::operator*= (const Quaterni
*/
template <class Derived>
EIGEN_STRONG_INLINE typename QuaternionBase<Derived>::Vector3
QuaternionBase<Derived>::_transformVector(Vector3 v) const
QuaternionBase<Derived>::_transformVector(const Vector3& v) const
{
// Note that this algorithm comes from the optimization by hand
// of the conversion to a Matrix followed by a Matrix/Vector product.
@ -637,7 +637,7 @@ inline Quaternion<typename internal::traits<Derived>::Scalar> QuaternionBase<Der
{
// FIXME should this function be called multiplicativeInverse and conjugate() be called inverse() or opposite() ??
Scalar n2 = this->squaredNorm();
if (n2 > 0)
if (n2 > Scalar(0))
return Quaternion<Scalar>(conjugate().coeffs() / n2);
else
{
@ -667,12 +667,10 @@ template <class OtherDerived>
inline typename internal::traits<Derived>::Scalar
QuaternionBase<Derived>::angularDistance(const QuaternionBase<OtherDerived>& other) const
{
using std::acos;
using std::atan2;
using std::abs;
Scalar d = abs(this->dot(other));
if (d>=Scalar(1))
return Scalar(0);
return Scalar(2) * acos(d);
Quaternion<Scalar> d = (*this) * other.conjugate();
return Scalar(2) * atan2( d.vec().norm(), abs(d.w()) );
}
@ -712,7 +710,7 @@ QuaternionBase<Derived>::slerp(const Scalar& t, const QuaternionBase<OtherDerive
scale0 = sin( ( Scalar(1) - t ) * theta) / sinTheta;
scale1 = sin( ( t * theta) ) / sinTheta;
}
if(d<0) scale1 = -scale1;
if(d<Scalar(0)) scale1 = -scale1;
return Quaternion<Scalar>(scale0 * coeffs() + scale1 * other.coeffs());
}

2
uppsrc/plugin/Eigen/Eigen/src/Geometry/Rotation2D.h
View file

@ -59,7 +59,7 @@ protected:
public:
/** Construct a 2D counter clock wise rotation from the angle \a a in radian. */
explicit inline Rotation2D(const Scalar& a) : m_angle(a) {}
inline Rotation2D(const Scalar& a) : m_angle(a) {}
/** Default constructor wihtout initialization. The represented rotation is undefined. */
Rotation2D() {}

6
uppsrc/plugin/Eigen/Eigen/src/Geometry/arch/CMakeLists.txt Normal file
View file

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

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

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

15
uppsrc/plugin/Eigen/Eigen/src/IterativeLinearSolvers/BiCGSTAB.h
View file

@ -151,20 +151,7 @@ struct traits<BiCGSTAB<_MatrixType,_Preconditioner> >
* \endcode
*
* By default the iterations start with x=0 as an initial guess of the solution.
* One can control the start using the solveWithGuess() method. Here is a step by
* step execution example starting with a random guess and printing the evolution
* of the estimated error:
* * \code
* x = VectorXd::Random(n);
* solver.setMaxIterations(1);
* int i = 0;
* do {
* x = solver.solveWithGuess(b,x);
* std::cout << i << " : " << solver.error() << std::endl;
* ++i;
* } while (solver.info()!=Success && i<100);
* \endcode
* Note that such a step by step excution is slightly slower.
* One can control the start using the solveWithGuess() method.
*
* \sa class SimplicialCholesky, DiagonalPreconditioner, IdentityPreconditioner
*/

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

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

30
uppsrc/plugin/Eigen/Eigen/src/IterativeLinearSolvers/ConjugateGradient.h
View file

@ -112,9 +112,9 @@ struct traits<ConjugateGradient<_MatrixType,_UpLo,_Preconditioner> >
* This class allows to solve for A.x = b sparse linear problems using a conjugate gradient algorithm.
* The sparse matrix A must be selfadjoint. The vectors x and b can be either dense or sparse.
*
* \tparam _MatrixType the type of the sparse matrix A, can be a dense or a sparse matrix.
* \tparam _UpLo the triangular part that will be used for the computations. It can be Lower
* or Upper. Default is Lower.
* \tparam _MatrixType the type of the matrix A, can be a dense or a sparse matrix.
* \tparam _UpLo the triangular part that will be used for the computations. It can be Lower,
* Upper, or Lower|Upper in which the full matrix entries will be considered. Default is Lower.
* \tparam _Preconditioner the type of the preconditioner. Default is DiagonalPreconditioner
*
* The maximal number of iterations and tolerance value can be controlled via the setMaxIterations()
@ -137,20 +137,7 @@ struct traits<ConjugateGradient<_MatrixType,_UpLo,_Preconditioner> >
* \endcode
*
* By default the iterations start with x=0 as an initial guess of the solution.
* One can control the start using the solveWithGuess() method. Here is a step by
* step execution example starting with a random guess and printing the evolution
* of the estimated error:
* * \code
* x = VectorXd::Random(n);
* cg.setMaxIterations(1);
* int i = 0;
* do {
* x = cg.solveWithGuess(b,x);
* std::cout << i << " : " << cg.error() << std::endl;
* ++i;
* } while (cg.info()!=Success && i<100);
* \endcode
* Note that such a step by step excution is slightly slower.
* One can control the start using the solveWithGuess() method.
*
* \sa class SimplicialCholesky, DiagonalPreconditioner, IdentityPreconditioner
*/
@ -213,6 +200,10 @@ public:
template<typename Rhs,typename Dest>
void _solveWithGuess(const Rhs& b, Dest& x) const
{
typedef typename internal::conditional<UpLo==(Lower|Upper),
const MatrixType&,
SparseSelfAdjointView<const MatrixType, UpLo>
>::type MatrixWrapperType;
m_iterations = Base::maxIterations();
m_error = Base::m_tolerance;
@ -222,8 +213,7 @@ public:
m_error = Base::m_tolerance;
typename Dest::ColXpr xj(x,j);
internal::conjugate_gradient(mp_matrix->template selfadjointView<UpLo>(), b.col(j), xj,
Base::m_preconditioner, m_iterations, m_error);
internal::conjugate_gradient(MatrixWrapperType(*mp_matrix), b.col(j), xj, Base::m_preconditioner, m_iterations, m_error);
}
m_isInitialized = true;
@ -234,7 +224,7 @@ public:
template<typename Rhs,typename Dest>
void _solve(const Rhs& b, Dest& x) const
{
x.setOnes();
x.setZero();
_solveWithGuess(b,x);
}

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

@ -150,7 +150,6 @@ class IncompleteLUT : internal::noncopyable
{
analyzePattern(amat);
factorize(amat);
m_isInitialized = m_factorizationIsOk;
return *this;
}
@ -235,6 +234,8 @@ void IncompleteLUT<Scalar>::analyzePattern(const _MatrixType& amat)
m_Pinv = m_P.inverse(); // ... and the inverse permutation
m_analysisIsOk = true;
m_factorizationIsOk = false;
m_isInitialized = false;
}
template <typename Scalar>
@ -442,6 +443,7 @@ void IncompleteLUT<Scalar>::factorize(const _MatrixType& amat)
m_lu.makeCompressed();
m_factorizationIsOk = true;
m_isInitialized = m_factorizationIsOk;
m_info = Success;
}

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

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

8
uppsrc/plugin/Eigen/Eigen/src/LU/CMakeLists.txt Normal file
View file

@ -0,0 +1,8 @@
FILE(GLOB Eigen_LU_SRCS "*.h")
INSTALL(FILES
${Eigen_LU_SRCS}
DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen/src/LU COMPONENT Devel
)
ADD_SUBDIRECTORY(arch)

8
uppsrc/plugin/Eigen/Eigen/src/LU/FullPivLU.h
View file

@ -374,6 +374,12 @@ template<typename _MatrixType> class FullPivLU
inline Index cols() const { return m_lu.cols(); }
protected:
static void check_template_parameters()
{
EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar);
}
MatrixType m_lu;
PermutationPType m_p;
PermutationQType m_q;
@ -418,6 +424,8 @@ FullPivLU<MatrixType>::FullPivLU(const MatrixType& matrix)
template<typename MatrixType>
FullPivLU<MatrixType>& FullPivLU<MatrixType>::compute(const MatrixType& matrix)
{
check_template_parameters();
// the permutations are stored as int indices, so just to be sure:
eigen_assert(matrix.rows()<=NumTraits<int>::highest() && matrix.cols()<=NumTraits<int>::highest());

8
uppsrc/plugin/Eigen/Eigen/src/LU/PartialPivLU.h
View file

@ -171,6 +171,12 @@ template<typename _MatrixType> class PartialPivLU
inline Index cols() const { return m_lu.cols(); }
protected:
static void check_template_parameters()
{
EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar);
}
MatrixType m_lu;
PermutationType m_p;
TranspositionType m_rowsTranspositions;
@ -386,6 +392,8 @@ void partial_lu_inplace(MatrixType& lu, TranspositionType& row_transpositions, t
template<typename MatrixType>
PartialPivLU<MatrixType>& PartialPivLU<MatrixType>::compute(const MatrixType& matrix)
{
check_template_parameters();
// the row permutation is stored as int indices, so just to be sure:
eigen_assert(matrix.rows()<NumTraits<int>::highest());

6
uppsrc/plugin/Eigen/Eigen/src/LU/arch/CMakeLists.txt Normal file
View file

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

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

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

16
uppsrc/plugin/Eigen/Eigen/src/OrderingMethods/Amd.h
View file

@ -144,15 +144,23 @@ void minimum_degree_ordering(SparseMatrix<Scalar,ColMajor,Index>& C, Permutation
/* --- Initialize degree lists ------------------------------------------ */
for(i = 0; i < n; i++)
{
bool has_diag = false;
for(p = Cp[i]; p<Cp[i+1]; ++p)
if(Ci[p]==i)
{
has_diag = true;
break;
}
d = degree[i];
if(d == 0) /* node i is empty */
if(d == 1) /* node i is empty */
{
elen[i] = -2; /* element i is dead */
nel++;
Cp[i] = -1; /* i is a root of assembly tree */
w[i] = 0;
}
else if(d > dense) /* node i is dense */
else if(d > dense || !has_diag) /* node i is dense or has no structural diagonal element */
{
nv[i] = 0; /* absorb i into element n */
elen[i] = -1; /* node i is dead */
@ -168,6 +176,10 @@ void minimum_degree_ordering(SparseMatrix<Scalar,ColMajor,Index>& C, Permutation
}
}
elen[n] = -2; /* n is a dead element */
Cp[n] = -1; /* n is a root of assembly tree */
w[n] = 0; /* n is a dead element */
while (nel < n) /* while (selecting pivots) do */
{
/* --- Select node of minimum approximate degree -------------------- */

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

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

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

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

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

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

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

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

32
uppsrc/plugin/Eigen/Eigen/src/QR/ColPivHouseholderQR.h
View file

@ -384,6 +384,12 @@ template<typename _MatrixType> class ColPivHouseholderQR
}
protected:
static void check_template_parameters()
{
EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar);
}
MatrixType m_qr;
HCoeffsType m_hCoeffs;
PermutationType m_colsPermutation;
@ -422,6 +428,8 @@ typename MatrixType::RealScalar ColPivHouseholderQR<MatrixType>::logAbsDetermina
template<typename MatrixType>
ColPivHouseholderQR<MatrixType>& ColPivHouseholderQR<MatrixType>::compute(const MatrixType& matrix)
{
check_template_parameters();
using std::abs;
Index rows = matrix.rows();
Index cols = matrix.cols();
@ -463,20 +471,10 @@ ColPivHouseholderQR<MatrixType>& ColPivHouseholderQR<MatrixType>::compute(const
// we store that back into our table: it can't hurt to correct our table.
m_colSqNorms.coeffRef(biggest_col_index) = biggest_col_sq_norm;
// if the current biggest column is smaller than epsilon times the initial biggest column,
// terminate to avoid generating nan/inf values.
// Note that here, if we test instead for "biggest == 0", we get a failure every 1000 (or so)
// repetitions of the unit test, with the result of solve() filled with large values of the order
// of 1/(size*epsilon).
if(biggest_col_sq_norm < threshold_helper * RealScalar(rows-k))
{
// Track the number of meaningful pivots but do not stop the decomposition to make
// sure that the initial matrix is properly reproduced. See bug 941.
if(m_nonzero_pivots==size && biggest_col_sq_norm < threshold_helper * RealScalar(rows-k))
m_nonzero_pivots = k;
m_hCoeffs.tail(size-k).setZero();
m_qr.bottomRightCorner(rows-k,cols-k)
.template triangularView<StrictlyLower>()
.setZero();
break;
}
// apply the transposition to the columns
m_colsTranspositions.coeffRef(k) = biggest_col_index;
@ -505,7 +503,7 @@ ColPivHouseholderQR<MatrixType>& ColPivHouseholderQR<MatrixType>::compute(const
}
m_colsPermutation.setIdentity(PermIndexType(cols));
for(PermIndexType k = 0; k < m_nonzero_pivots; ++k)
for(PermIndexType k = 0; k < size/*m_nonzero_pivots*/; ++k)
m_colsPermutation.applyTranspositionOnTheRight(k, PermIndexType(m_colsTranspositions.coeff(k)));
m_det_pq = (number_of_transpositions%2) ? -1 : 1;
@ -555,13 +553,15 @@ struct solve_retval<ColPivHouseholderQR<_MatrixType>, Rhs>
} // end namespace internal
/** \returns the matrix Q as a sequence of householder transformations */
/** \returns the matrix Q as a sequence of householder transformations.
* You can extract the meaningful part only by using:
* \code qr.householderQ().setLength(qr.nonzeroPivots()) \endcode*/
template<typename MatrixType>
typename ColPivHouseholderQR<MatrixType>::HouseholderSequenceType ColPivHouseholderQR<MatrixType>
::householderQ() const
{
eigen_assert(m_isInitialized && "ColPivHouseholderQR is not initialized.");
return HouseholderSequenceType(m_qr, m_hCoeffs.conjugate()).setLength(m_nonzero_pivots);
return HouseholderSequenceType(m_qr, m_hCoeffs.conjugate());
}
/** \return the column-pivoting Householder QR decomposition of \c *this.

8
uppsrc/plugin/Eigen/Eigen/src/QR/FullPivHouseholderQR.h
View file

@ -368,6 +368,12 @@ template<typename _MatrixType> class FullPivHouseholderQR
RealScalar maxPivot() const { return m_maxpivot; }
protected:
static void check_template_parameters()
{
EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar);
}
MatrixType m_qr;
HCoeffsType m_hCoeffs;
IntDiagSizeVectorType m_rows_transpositions;
@ -407,6 +413,8 @@ typename MatrixType::RealScalar FullPivHouseholderQR<MatrixType>::logAbsDetermin
template<typename MatrixType>
FullPivHouseholderQR<MatrixType>& FullPivHouseholderQR<MatrixType>::compute(const MatrixType& matrix)
{
check_template_parameters();
using std::abs;
Index rows = matrix.rows();
Index cols = matrix.cols();

102
uppsrc/plugin/Eigen/Eigen/src/QR/HouseholderQR.h
View file

@ -189,6 +189,12 @@ template<typename _MatrixType> class HouseholderQR
const HCoeffsType& hCoeffs() const { return m_hCoeffs; }
protected:
static void check_template_parameters()
{
EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar);
}
MatrixType m_qr;
HCoeffsType m_hCoeffs;
RowVectorType m_temp;
@ -251,56 +257,62 @@ void householder_qr_inplace_unblocked(MatrixQR& mat, HCoeffs& hCoeffs, typename
}
/** \internal */
template<typename MatrixQR, typename HCoeffs>
void householder_qr_inplace_blocked(MatrixQR& mat, HCoeffs& hCoeffs,
typename MatrixQR::Index maxBlockSize=32,
typename MatrixQR::Scalar* tempData = 0)
template<typename MatrixQR, typename HCoeffs,
typename MatrixQRScalar = typename MatrixQR::Scalar,
bool InnerStrideIsOne = (MatrixQR::InnerStrideAtCompileTime == 1 && HCoeffs::InnerStrideAtCompileTime == 1)>
struct householder_qr_inplace_blocked
{
typedef typename MatrixQR::Index Index;
typedef typename MatrixQR::Scalar Scalar;
typedef Block<MatrixQR,Dynamic,Dynamic> BlockType;
Index rows = mat.rows();
Index cols = mat.cols();
Index size = (std::min)(rows, cols);
typedef Matrix<Scalar,Dynamic,1,ColMajor,MatrixQR::MaxColsAtCompileTime,1> TempType;
TempType tempVector;
if(tempData==0)
// This is specialized for MKL-supported Scalar types in HouseholderQR_MKL.h
static void run(MatrixQR& mat, HCoeffs& hCoeffs,
typename MatrixQR::Index maxBlockSize=32,
typename MatrixQR::Scalar* tempData = 0)
{
tempVector.resize(cols);
tempData = tempVector.data();
}
typedef typename MatrixQR::Index Index;
typedef typename MatrixQR::Scalar Scalar;
typedef Block<MatrixQR,Dynamic,Dynamic> BlockType;
Index blockSize = (std::min)(maxBlockSize,size);
Index rows = mat.rows();
Index cols = mat.cols();
Index size = (std::min)(rows, cols);
Index k = 0;
for (k = 0; k < size; k += blockSize)
{
Index bs = (std::min)(size-k,blockSize); // actual size of the block
Index tcols = cols - k - bs; // trailing columns
Index brows = rows-k; // rows of the block
// partition the matrix:
// A00 | A01 | A02
// mat = A10 | A11 | A12
// A20 | A21 | A22
// and performs the qr dec of [A11^T A12^T]^T
// and update [A21^T A22^T]^T using level 3 operations.
// Finally, the algorithm continue on A22
BlockType A11_21 = mat.block(k,k,brows,bs);
Block<HCoeffs,Dynamic,1> hCoeffsSegment = hCoeffs.segment(k,bs);
householder_qr_inplace_unblocked(A11_21, hCoeffsSegment, tempData);
if(tcols)
typedef Matrix<Scalar,Dynamic,1,ColMajor,MatrixQR::MaxColsAtCompileTime,1> TempType;
TempType tempVector;
if(tempData==0)
{
BlockType A21_22 = mat.block(k,k+bs,brows,tcols);
apply_block_householder_on_the_left(A21_22,A11_21,hCoeffsSegment.adjoint());
tempVector.resize(cols);
tempData = tempVector.data();
}
Index blockSize = (std::min)(maxBlockSize,size);
Index k = 0;
for (k = 0; k < size; k += blockSize)
{
Index bs = (std::min)(size-k,blockSize); // actual size of the block
Index tcols = cols - k - bs; // trailing columns
Index brows = rows-k; // rows of the block
// partition the matrix:
// A00 | A01 | A02
// mat = A10 | A11 | A12
// A20 | A21 | A22
// and performs the qr dec of [A11^T A12^T]^T
// and update [A21^T A22^T]^T using level 3 operations.
// Finally, the algorithm continue on A22
BlockType A11_21 = mat.block(k,k,brows,bs);
Block<HCoeffs,Dynamic,1> hCoeffsSegment = hCoeffs.segment(k,bs);
householder_qr_inplace_unblocked(A11_21, hCoeffsSegment, tempData);
if(tcols)
{
BlockType A21_22 = mat.block(k,k+bs,brows,tcols);
apply_block_householder_on_the_left(A21_22,A11_21,hCoeffsSegment.adjoint());
}
}
}
}
};
template<typename _MatrixType, typename Rhs>
struct solve_retval<HouseholderQR<_MatrixType>, Rhs>
@ -343,6 +355,8 @@ struct solve_retval<HouseholderQR<_MatrixType>, Rhs>
template<typename MatrixType>
HouseholderQR<MatrixType>& HouseholderQR<MatrixType>::compute(const MatrixType& matrix)
{
check_template_parameters();
Index rows = matrix.rows();
Index cols = matrix.cols();
Index size = (std::min)(rows,cols);
@ -352,7 +366,7 @@ HouseholderQR<MatrixType>& HouseholderQR<MatrixType>::compute(const MatrixType&
m_temp.resize(cols);
internal::householder_qr_inplace_blocked(m_qr, m_hCoeffs, 48, m_temp.data());
internal::householder_qr_inplace_blocked<MatrixType, HCoeffsType>::run(m_qr, m_hCoeffs, 48, m_temp.data());
m_isInitialized = true;
return *this;

30
uppsrc/plugin/Eigen/Eigen/src/QR/HouseholderQR_MKL.h
View file

@ -34,28 +34,30 @@
#ifndef EIGEN_QR_MKL_H
#define EIGEN_QR_MKL_H
#include "Eigen/src/Core/util/MKL_support.h"
#include "../Core/util/MKL_support.h"
namespace Eigen {
namespace internal {
namespace internal {
/** \internal Specialization for the data types supported by MKL */
/** \internal Specialization for the data types supported by MKL */
#define EIGEN_MKL_QR_NOPIV(EIGTYPE, MKLTYPE, MKLPREFIX) \
template<typename MatrixQR, typename HCoeffs> \
void householder_qr_inplace_blocked(MatrixQR& mat, HCoeffs& hCoeffs, \
typename MatrixQR::Index maxBlockSize=32, \
EIGTYPE* tempData = 0) \
struct householder_qr_inplace_blocked<MatrixQR, HCoeffs, EIGTYPE, true> \
{ \
lapack_int m = mat.rows(); \
lapack_int n = mat.cols(); \
lapack_int lda = mat.outerStride(); \
lapack_int matrix_order = (MatrixQR::IsRowMajor) ? LAPACK_ROW_MAJOR : LAPACK_COL_MAJOR; \
LAPACKE_##MKLPREFIX##geqrf( matrix_order, m, n, (MKLTYPE*)mat.data(), lda, (MKLTYPE*)hCoeffs.data()); \
hCoeffs.adjointInPlace(); \
\
}
static void run(MatrixQR& mat, HCoeffs& hCoeffs, \
typename MatrixQR::Index = 32, \
typename MatrixQR::Scalar* = 0) \
{ \
lapack_int m = (lapack_int) mat.rows(); \
lapack_int n = (lapack_int) mat.cols(); \
lapack_int lda = (lapack_int) mat.outerStride(); \
lapack_int matrix_order = (MatrixQR::IsRowMajor) ? LAPACK_ROW_MAJOR : LAPACK_COL_MAJOR; \
LAPACKE_##MKLPREFIX##geqrf( matrix_order, m, n, (MKLTYPE*)mat.data(), lda, (MKLTYPE*)hCoeffs.data()); \
hCoeffs.adjointInPlace(); \
} \
};
EIGEN_MKL_QR_NOPIV(double, double, d)
EIGEN_MKL_QR_NOPIV(float, float, s)

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

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

60
uppsrc/plugin/Eigen/Eigen/src/SPQRSupport/SuiteSparseQRSupport.h
View file

@ -64,19 +64,13 @@ class SPQR
typedef PermutationMatrix<Dynamic, Dynamic> PermutationType;
public:
SPQR()
: m_isInitialized(false),
m_ordering(SPQR_ORDERING_DEFAULT),
m_allow_tol(SPQR_DEFAULT_TOL),
m_tolerance (NumTraits<Scalar>::epsilon())
: m_isInitialized(false), m_ordering(SPQR_ORDERING_DEFAULT), m_allow_tol(SPQR_DEFAULT_TOL), m_tolerance (NumTraits<Scalar>::epsilon()), m_useDefaultThreshold(true)
{
cholmod_l_start(&m_cc);
}
SPQR(const _MatrixType& matrix)
: m_isInitialized(false),
m_ordering(SPQR_ORDERING_DEFAULT),
m_allow_tol(SPQR_DEFAULT_TOL),
m_tolerance (NumTraits<Scalar>::epsilon())
SPQR(const _MatrixType& matrix)
: m_isInitialized(false), m_ordering(SPQR_ORDERING_DEFAULT), m_allow_tol(SPQR_DEFAULT_TOL), m_tolerance (NumTraits<Scalar>::epsilon()), m_useDefaultThreshold(true)
{
cholmod_l_start(&m_cc);
compute(matrix);
@ -101,10 +95,26 @@ class SPQR
if(m_isInitialized) SPQR_free();
MatrixType mat(matrix);
/* Compute the default threshold as in MatLab, see:
* Tim Davis, "Algorithm 915, SuiteSparseQR: Multifrontal Multithreaded Rank-Revealing
* Sparse QR Factorization, ACM Trans. on Math. Soft. 38(1), 2011, Page 8:3
*/
RealScalar pivotThreshold = m_tolerance;
if(m_useDefaultThreshold)
{
using std::max;
RealScalar max2Norm = 0.0;
for (int j = 0; j < mat.cols(); j++) max2Norm = (max)(max2Norm, mat.col(j).norm());
if(max2Norm==RealScalar(0))
max2Norm = RealScalar(1);
pivotThreshold = 20 * (mat.rows() + mat.cols()) * max2Norm * NumTraits<RealScalar>::epsilon();
}
cholmod_sparse A;
A = viewAsCholmod(mat);
Index col = matrix.cols();
m_rank = SuiteSparseQR<Scalar>(m_ordering, m_tolerance, col, &A,
m_rank = SuiteSparseQR<Scalar>(m_ordering, pivotThreshold, col, &A,
&m_cR, &m_E, &m_H, &m_HPinv, &m_HTau, &m_cc);
if (!m_cR)
@ -120,7 +130,7 @@ class SPQR
/**
* Get the number of rows of the input matrix and the Q matrix
*/
inline Index rows() const {return m_H->nrow; }
inline Index rows() const {return m_cR->nrow; }
/**
* Get the number of columns of the input matrix.
@ -145,16 +155,25 @@ class SPQR
{
eigen_assert(m_isInitialized && " The QR factorization should be computed first, call compute()");
eigen_assert(b.cols()==1 && "This method is for vectors only");
//Compute Q^T * b
typename Dest::PlainObject y;
typename Dest::PlainObject y, y2;
y = matrixQ().transpose() * b;
// Solves with the triangular matrix R
// Solves with the triangular matrix R
Index rk = this->rank();
y.topRows(rk) = this->matrixR().topLeftCorner(rk, rk).template triangularView<Upper>().solve(y.topRows(rk));
y.bottomRows(cols()-rk).setZero();
y2 = y;
y.resize((std::max)(cols(),Index(y.rows())),y.cols());
y.topRows(rk) = this->matrixR().topLeftCorner(rk, rk).template triangularView<Upper>().solve(y2.topRows(rk));
// Apply the column permutation
dest.topRows(cols()) = colsPermutation() * y.topRows(cols());
// colsPermutation() performs a copy of the permutation,
// so let's apply it manually:
for(Index i = 0; i < rk; ++i) dest.row(m_E[i]) = y.row(i);
for(Index i = rk; i < cols(); ++i) dest.row(m_E[i]).setZero();
// y.bottomRows(y.rows()-rk).setZero();
// dest = colsPermutation() * y.topRows(cols());
m_info = Success;
}
@ -197,7 +216,11 @@ class SPQR
/// Set the fill-reducing ordering method to be used
void setSPQROrdering(int ord) { m_ordering = ord;}
/// Set the tolerance tol to treat columns with 2-norm < =tol as zero
void setPivotThreshold(const RealScalar& tol) { m_tolerance = tol; }
void setPivotThreshold(const RealScalar& tol)
{
m_useDefaultThreshold = false;
m_tolerance = tol;
}
/** \returns a pointer to the SPQR workspace */
cholmod_common *cholmodCommon() const { return &m_cc; }
@ -230,6 +253,7 @@ class SPQR
mutable cholmod_dense *m_HTau; // The Householder coefficients
mutable Index m_rank; // The rank of the matrix
mutable cholmod_common m_cc; // Workspace and parameters
bool m_useDefaultThreshold; // Use default threshold
template<typename ,typename > friend struct SPQR_QProduct;
};

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

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

7
uppsrc/plugin/Eigen/Eigen/src/SVD/JacobiSVD.h
View file

@ -742,6 +742,11 @@ template<typename _MatrixType, int QRPreconditioner> class JacobiSVD
private:
void allocate(Index rows, Index cols, unsigned int computationOptions);
static void check_template_parameters()
{
EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar);
}
protected:
MatrixUType m_matrixU;
@ -818,6 +823,8 @@ template<typename MatrixType, int QRPreconditioner>
JacobiSVD<MatrixType, QRPreconditioner>&
JacobiSVD<MatrixType, QRPreconditioner>::compute(const MatrixType& matrix, unsigned int computationOptions)
{
check_template_parameters();
using std::abs;
allocate(matrix.rows(), matrix.cols(), computationOptions);

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

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

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

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

46
uppsrc/plugin/Eigen/Eigen/src/SparseCore/SparseBlock.h
View file

@ -57,6 +57,16 @@ public:
inline BlockImpl(const XprType& xpr, int startRow, int startCol, int blockRows, int blockCols)
: m_matrix(xpr), m_outerStart(IsRowMajor ? startRow : startCol), m_outerSize(IsRowMajor ? blockRows : blockCols)
{}
inline const Scalar coeff(int row, int col) const
{
return m_matrix.coeff(row + IsRowMajor ? m_outerStart : 0, col +IsRowMajor ? 0 : m_outerStart);
}
inline const Scalar coeff(int index) const
{
return m_matrix.coeff(IsRowMajor ? m_outerStart : index, IsRowMajor ? index : m_outerStart);
}
EIGEN_STRONG_INLINE Index rows() const { return IsRowMajor ? m_outerSize.value() : m_matrix.rows(); }
EIGEN_STRONG_INLINE Index cols() const { return IsRowMajor ? m_matrix.cols() : m_outerSize.value(); }
@ -226,6 +236,21 @@ public:
else
return Map<const Matrix<Index,OuterSize,1> >(m_matrix.innerNonZeroPtr()+m_outerStart, m_outerSize.value()).sum();
}
inline Scalar& coeffRef(int row, int col)
{
return m_matrix.const_cast_derived().coeffRef(row + (IsRowMajor ? m_outerStart : 0), col + (IsRowMajor ? 0 : m_outerStart));
}
inline const Scalar coeff(int row, int col) const
{
return m_matrix.coeff(row + (IsRowMajor ? m_outerStart : 0), col + (IsRowMajor ? 0 : m_outerStart));
}
inline const Scalar coeff(int index) const
{
return m_matrix.coeff(IsRowMajor ? m_outerStart : index, IsRowMajor ? index : m_outerStart);
}
const Scalar& lastCoeff() const
{
@ -313,6 +338,16 @@ public:
else
return Map<const Matrix<Index,OuterSize,1> >(m_matrix.innerNonZeroPtr()+m_outerStart, m_outerSize.value()).sum();
}
inline const Scalar coeff(int row, int col) const
{
return m_matrix.coeff(row + (IsRowMajor ? m_outerStart : 0), col + (IsRowMajor ? 0 : m_outerStart));
}
inline const Scalar coeff(int index) const
{
return m_matrix.coeff(IsRowMajor ? m_outerStart : index, IsRowMajor ? index : m_outerStart);
}
const Scalar& lastCoeff() const
{
@ -355,7 +390,8 @@ const typename SparseMatrixBase<Derived>::ConstInnerVectorReturnType SparseMatri
* is col-major (resp. row-major).
*/
template<typename Derived>
Block<Derived,Dynamic,Dynamic,true> SparseMatrixBase<Derived>::innerVectors(Index outerStart, Index outerSize)
typename SparseMatrixBase<Derived>::InnerVectorsReturnType
SparseMatrixBase<Derived>::innerVectors(Index outerStart, Index outerSize)
{
return Block<Derived,Dynamic,Dynamic,true>(derived(),
IsRowMajor ? outerStart : 0, IsRowMajor ? 0 : outerStart,
@ -367,7 +403,8 @@ Block<Derived,Dynamic,Dynamic,true> SparseMatrixBase<Derived>::innerVectors(Inde
* is col-major (resp. row-major). Read-only.
*/
template<typename Derived>
const Block<const Derived,Dynamic,Dynamic,true> SparseMatrixBase<Derived>::innerVectors(Index outerStart, Index outerSize) const
const typename SparseMatrixBase<Derived>::ConstInnerVectorsReturnType
SparseMatrixBase<Derived>::innerVectors(Index outerStart, Index outerSize) const
{
return Block<const Derived,Dynamic,Dynamic,true>(derived(),
IsRowMajor ? outerStart : 0, IsRowMajor ? 0 : outerStart,
@ -394,8 +431,8 @@ public:
: m_matrix(xpr),
m_startRow( (BlockRows==1) && (BlockCols==XprType::ColsAtCompileTime) ? i : 0),
m_startCol( (BlockRows==XprType::RowsAtCompileTime) && (BlockCols==1) ? i : 0),
m_blockRows(xpr.rows()),
m_blockCols(xpr.cols())
m_blockRows(BlockRows==1 ? 1 : xpr.rows()),
m_blockCols(BlockCols==1 ? 1 : xpr.cols())
{}
/** Dynamic-size constructor
@ -497,3 +534,4 @@ public:
} // end namespace Eigen
#endif // EIGEN_SPARSE_BLOCK_H

2
uppsrc/plugin/Eigen/Eigen/src/SparseCore/SparseDenseProduct.h
View file

@ -180,7 +180,7 @@ struct sparse_time_dense_product_impl<SparseLhsType,DenseRhsType,DenseResType, R
typename Res::Scalar tmp(0);
for(LhsInnerIterator it(lhs,j); it ;++it)
tmp += it.value() * rhs.coeff(it.index(),c);
res.coeffRef(j,c) = alpha * tmp;
res.coeffRef(j,c) += alpha * tmp;
}
}
}

6
uppsrc/plugin/Eigen/Eigen/src/SparseCore/SparseMatrixBase.h
View file

@ -404,8 +404,10 @@ template<typename Derived> class SparseMatrixBase : public EigenBase<Derived>
const ConstInnerVectorReturnType innerVector(Index outer) const;
// set of inner-vectors
Block<Derived,Dynamic,Dynamic,true> innerVectors(Index outerStart, Index outerSize);
const Block<const Derived,Dynamic,Dynamic,true> innerVectors(Index outerStart, Index outerSize) const;
typedef Block<Derived,Dynamic,Dynamic,true> InnerVectorsReturnType;
typedef Block<const Derived,Dynamic,Dynamic,true> ConstInnerVectorsReturnType;
InnerVectorsReturnType innerVectors(Index outerStart, Index outerSize);
const ConstInnerVectorsReturnType innerVectors(Index outerStart, Index outerSize) const;
/** \internal use operator= */
template<typename DenseDerived>

2
uppsrc/plugin/Eigen/Eigen/src/SparseCore/TriangularSolver.h
View file

@ -69,7 +69,7 @@ struct sparse_solve_triangular_selector<Lhs,Rhs,Mode,Upper,RowMajor>
for(int i=lhs.rows()-1 ; i>=0 ; --i)
{
Scalar tmp = other.coeff(i,col);
Scalar l_ii = 0;
Scalar l_ii(0);
typename Lhs::InnerIterator it(lhs, i);
while(it && it.index()<i)
++it;

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

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

81
uppsrc/plugin/Eigen/Eigen/src/SparseLU/SparseLU.h
View file

@ -268,7 +268,8 @@ class SparseLU : public internal::SparseLUImpl<typename _MatrixType::Scalar, typ
{
if(it.index() == j)
{
det *= (std::abs)(it.value());
using std::abs;
det *= abs(it.value());
break;
}
}
@ -295,7 +296,8 @@ class SparseLU : public internal::SparseLUImpl<typename _MatrixType::Scalar, typ
if(it.row() < j) continue;
if(it.row() == j)
{
det += (std::log)((std::abs)(it.value()));
using std::log; using std::abs;
det += log(abs(it.value()));
break;
}
}
@ -303,21 +305,64 @@ class SparseLU : public internal::SparseLUImpl<typename _MatrixType::Scalar, typ
return det;
}
/** \returns A number representing the sign of the determinant
*
* \sa absDeterminant(), logAbsDeterminant()
*/
Scalar signDeterminant()
{
eigen_assert(m_factorizationIsOk && "The matrix should be factorized first.");
return Scalar(m_detPermR);
}
/** \returns A number representing the sign of the determinant
*
* \sa absDeterminant(), logAbsDeterminant()
*/
Scalar signDeterminant()
{
eigen_assert(m_factorizationIsOk && "The matrix should be factorized first.");
// Initialize with the determinant of the row matrix
Index det = 1;
// Note that the diagonal blocks of U are stored in supernodes,
// which are available in the L part :)
for (Index j = 0; j < this->cols(); ++j)
{
for (typename SCMatrix::InnerIterator it(m_Lstore, j); it; ++it)
{
if(it.index() == j)
{
if(it.value()<0)
det = -det;
else if(it.value()==0)
return 0;
break;
}
}
}
return det * m_detPermR * m_detPermC;
}
/** \returns The determinant of the matrix.
*
* \sa absDeterminant(), logAbsDeterminant()
*/
Scalar determinant()
{
eigen_assert(m_factorizationIsOk && "The matrix should be factorized first.");
// Initialize with the determinant of the row matrix
Scalar det = Scalar(1.);
// Note that the diagonal blocks of U are stored in supernodes,
// which are available in the L part :)
for (Index j = 0; j < this->cols(); ++j)
{
for (typename SCMatrix::InnerIterator it(m_Lstore, j); it; ++it)
{
if(it.index() == j)
{
det *= it.value();
break;
}
}
}
return det * Scalar(m_detPermR * m_detPermC);
}
protected:
// Functions
void initperfvalues()
{
m_perfv.panel_size = 1;
m_perfv.panel_size = 16;
m_perfv.relax = 1;
m_perfv.maxsuper = 128;
m_perfv.rowblk = 16;
@ -345,8 +390,8 @@ class SparseLU : public internal::SparseLUImpl<typename _MatrixType::Scalar, typ
// values for performance
internal::perfvalues<Index> m_perfv;
RealScalar m_diagpivotthresh; // Specifies the threshold used for a diagonal entry to be an acceptable pivot
Index m_nnzL, m_nnzU; // Nonzeros in L and U factors
Index m_detPermR; // Determinant of the coefficient matrix
Index m_nnzL, m_nnzU; // Nonzeros in L and U factors
Index m_detPermR, m_detPermC; // Determinants of the permutation matrices
private:
// Disable copy constructor
SparseLU (const SparseLU& );
@ -622,7 +667,8 @@ void SparseLU<MatrixType, OrderingType>::factorize(const MatrixType& matrix)
}
// Update the determinant of the row permutation matrix
if (pivrow != jj) m_detPermR *= -1;
// FIXME: the following test is not correct, we should probably take iperm_c into account and pivrow is not directly the row pivot.
if (pivrow != jj) m_detPermR = -m_detPermR;
// Prune columns (0:jj-1) using column jj
Base::pruneL(jj, m_perm_r.indices(), pivrow, nseg, segrep, repfnz_k, xprune, m_glu);
@ -637,10 +683,13 @@ void SparseLU<MatrixType, OrderingType>::factorize(const MatrixType& matrix)
jcol += panel_size; // Move to the next panel
} // end for -- end elimination
m_detPermR = m_perm_r.determinant();
m_detPermC = m_perm_c.determinant();
// Count the number of nonzeros in factors
Base::countnz(n, m_nnzL, m_nnzU, m_glu);
// Apply permutation to the L subscripts
Base::fixupL(n, m_perm_r.indices(), m_glu);
Base::fixupL(n, m_perm_r.indices(), m_glu);
// Create supernode matrix L
m_Lstore.setInfos(m, n, m_glu.lusup, m_glu.xlusup, m_glu.lsub, m_glu.xlsub, m_glu.supno, m_glu.xsup);

6
uppsrc/plugin/Eigen/Eigen/src/SparseLU/SparseLU_pivotL.h
View file

@ -77,7 +77,8 @@ Index SparseLUImpl<Scalar,Index>::pivotL(const Index jcol, const RealScalar& dia
RealScalar rtemp;
Index isub, icol, itemp, k;
for (isub = nsupc; isub < nsupr; ++isub) {
rtemp = std::abs(lu_col_ptr[isub]);
using std::abs;
rtemp = abs(lu_col_ptr[isub]);
if (rtemp > pivmax) {
pivmax = rtemp;
pivptr = isub;
@ -101,7 +102,8 @@ Index SparseLUImpl<Scalar,Index>::pivotL(const Index jcol, const RealScalar& dia
if (diag >= 0 )
{
// Diagonal element exists
rtemp = std::abs(lu_col_ptr[diag]);
using std::abs;
rtemp = abs(lu_col_ptr[diag]);
if (rtemp != 0.0 && rtemp >= thresh) pivptr = diag;
}
pivrow = lsub_ptr[pivptr];

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

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

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

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

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

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

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

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

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

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

54
uppsrc/plugin/Eigen/Eigen/src/plugins/ArrayCwiseBinaryOps.h
View file

@ -70,6 +70,43 @@ max
return (max)(Derived::PlainObject::Constant(rows(), cols(), other));
}
#define EIGEN_MAKE_CWISE_COMP_OP(OP, COMPARATOR) \
template<typename OtherDerived> \
EIGEN_STRONG_INLINE const CwiseBinaryOp<internal::scalar_cmp_op<Scalar, internal::cmp_ ## COMPARATOR>, const Derived, const OtherDerived> \
OP(const EIGEN_CURRENT_STORAGE_BASE_CLASS<OtherDerived> &other) const \
{ \
return CwiseBinaryOp<internal::scalar_cmp_op<Scalar, internal::cmp_ ## COMPARATOR>, const Derived, const OtherDerived>(derived(), other.derived()); \
}\
typedef CwiseBinaryOp<internal::scalar_cmp_op<Scalar, internal::cmp_ ## COMPARATOR>, const Derived, const CwiseNullaryOp<internal::scalar_constant_op<Scalar>, PlainObject> > Cmp ## COMPARATOR ## ReturnType; \
typedef CwiseBinaryOp<internal::scalar_cmp_op<Scalar, internal::cmp_ ## COMPARATOR>, const CwiseNullaryOp<internal::scalar_constant_op<Scalar>, PlainObject>, const Derived > RCmp ## COMPARATOR ## ReturnType; \
EIGEN_STRONG_INLINE const Cmp ## COMPARATOR ## ReturnType \
OP(const Scalar& s) const { \
return this->OP(Derived::PlainObject::Constant(rows(), cols(), s)); \
} \
friend EIGEN_STRONG_INLINE const RCmp ## COMPARATOR ## ReturnType \
OP(const Scalar& s, const Derived& d) { \
return Derived::PlainObject::Constant(d.rows(), d.cols(), s).OP(d); \
}
#define EIGEN_MAKE_CWISE_COMP_R_OP(OP, R_OP, RCOMPARATOR) \
template<typename OtherDerived> \
EIGEN_STRONG_INLINE const CwiseBinaryOp<internal::scalar_cmp_op<Scalar, internal::cmp_##RCOMPARATOR>, const OtherDerived, const Derived> \
OP(const EIGEN_CURRENT_STORAGE_BASE_CLASS<OtherDerived> &other) const \
{ \
return CwiseBinaryOp<internal::scalar_cmp_op<Scalar, internal::cmp_##RCOMPARATOR>, const OtherDerived, const Derived>(other.derived(), derived()); \
} \
\
inline const RCmp ## RCOMPARATOR ## ReturnType \
OP(const Scalar& s) const { \
return Derived::PlainObject::Constant(rows(), cols(), s).R_OP(*this); \
} \
friend inline const Cmp ## RCOMPARATOR ## ReturnType \
OP(const Scalar& s, const Derived& d) { \
return d.R_OP(Derived::PlainObject::Constant(d.rows(), d.cols(), s)); \
}
/** \returns an expression of the coefficient-wise \< operator of *this and \a other
*
* Example: \include Cwise_less.cpp
@ -77,7 +114,7 @@ max
*
* \sa all(), any(), operator>(), operator<=()
*/
EIGEN_MAKE_CWISE_BINARY_OP(operator<,std::less)
EIGEN_MAKE_CWISE_COMP_OP(operator<, LT)
/** \returns an expression of the coefficient-wise \<= operator of *this and \a other
*
@ -86,7 +123,7 @@ EIGEN_MAKE_CWISE_BINARY_OP(operator<,std::less)
*
* \sa all(), any(), operator>=(), operator<()
*/
EIGEN_MAKE_CWISE_BINARY_OP(operator<=,std::less_equal)
EIGEN_MAKE_CWISE_COMP_OP(operator<=, LE)
/** \returns an expression of the coefficient-wise \> operator of *this and \a other
*
@ -95,7 +132,7 @@ EIGEN_MAKE_CWISE_BINARY_OP(operator<=,std::less_equal)
*
* \sa all(), any(), operator>=(), operator<()
*/
EIGEN_MAKE_CWISE_BINARY_OP(operator>,std::greater)
EIGEN_MAKE_CWISE_COMP_R_OP(operator>, operator<, LT)
/** \returns an expression of the coefficient-wise \>= operator of *this and \a other
*
@ -104,7 +141,7 @@ EIGEN_MAKE_CWISE_BINARY_OP(operator>,std::greater)
*
* \sa all(), any(), operator>(), operator<=()
*/
EIGEN_MAKE_CWISE_BINARY_OP(operator>=,std::greater_equal)
EIGEN_MAKE_CWISE_COMP_R_OP(operator>=, operator<=, LE)
/** \returns an expression of the coefficient-wise == operator of *this and \a other
*
@ -118,7 +155,7 @@ EIGEN_MAKE_CWISE_BINARY_OP(operator>=,std::greater_equal)
*
* \sa all(), any(), isApprox(), isMuchSmallerThan()
*/
EIGEN_MAKE_CWISE_BINARY_OP(operator==,std::equal_to)
EIGEN_MAKE_CWISE_COMP_OP(operator==, EQ)
/** \returns an expression of the coefficient-wise != operator of *this and \a other
*
@ -132,7 +169,10 @@ EIGEN_MAKE_CWISE_BINARY_OP(operator==,std::equal_to)
*
* \sa all(), any(), isApprox(), isMuchSmallerThan()
*/
EIGEN_MAKE_CWISE_BINARY_OP(operator!=,std::not_equal_to)
EIGEN_MAKE_CWISE_COMP_OP(operator!=, NEQ)
#undef EIGEN_MAKE_CWISE_COMP_OP
#undef EIGEN_MAKE_CWISE_COMP_R_OP
// scalar addition
@ -209,3 +249,5 @@ operator||(const EIGEN_CURRENT_STORAGE_BASE_CLASS<OtherDerived> &other) const
THIS_METHOD_IS_ONLY_FOR_EXPRESSIONS_OF_BOOL);
return CwiseBinaryOp<internal::scalar_boolean_or_op, const Derived, const OtherDerived>(derived(),other.derived());
}

16
uppsrc/plugin/Eigen/Eigen/src/plugins/ArrayCwiseUnaryOps.h
View file

@ -185,19 +185,3 @@ cube() const
{
return derived();
}
#define EIGEN_MAKE_SCALAR_CWISE_UNARY_OP(METHOD_NAME,FUNCTOR) \
inline const CwiseUnaryOp<std::binder2nd<FUNCTOR<Scalar> >, const Derived> \
METHOD_NAME(const Scalar& s) const { \
return CwiseUnaryOp<std::binder2nd<FUNCTOR<Scalar> >, const Derived> \
(derived(), std::bind2nd(FUNCTOR<Scalar>(), s)); \
}
EIGEN_MAKE_SCALAR_CWISE_UNARY_OP(operator==, std::equal_to)
EIGEN_MAKE_SCALAR_CWISE_UNARY_OP(operator!=, std::not_equal_to)
EIGEN_MAKE_SCALAR_CWISE_UNARY_OP(operator<, std::less)
EIGEN_MAKE_SCALAR_CWISE_UNARY_OP(operator<=, std::less_equal)
EIGEN_MAKE_SCALAR_CWISE_UNARY_OP(operator>, std::greater)
EIGEN_MAKE_SCALAR_CWISE_UNARY_OP(operator>=, std::greater_equal)

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

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

17
uppsrc/plugin/Eigen/Eigen/src/plugins/MatrixCwiseBinaryOps.h
View file

@ -124,3 +124,20 @@ cwiseQuotient(const EIGEN_CURRENT_STORAGE_BASE_CLASS<OtherDerived> &other) const
{
return CwiseBinaryOp<internal::scalar_quotient_op<Scalar>, const Derived, const OtherDerived>(derived(), other.derived());
}
typedef CwiseBinaryOp<internal::scalar_cmp_op<Scalar,internal::cmp_EQ>, const Derived, const ConstantReturnType> CwiseScalarEqualReturnType;
/** \returns an expression of the coefficient-wise == operator of \c *this and a scalar \a s
*
* \warning this performs an exact comparison, which is generally a bad idea with floating-point types.
* In order to check for equality between two vectors or matrices with floating-point coefficients, it is
* generally a far better idea to use a fuzzy comparison as provided by isApprox() and
* isMuchSmallerThan().
*
* \sa cwiseEqual(const MatrixBase<OtherDerived> &) const
*/
inline const CwiseScalarEqualReturnType
cwiseEqual(const Scalar& s) const
{
return CwiseScalarEqualReturnType(derived(), Derived::Constant(rows(), cols(), s), internal::scalar_cmp_op<Scalar,internal::cmp_EQ>());
}

15
uppsrc/plugin/Eigen/Eigen/src/plugins/MatrixCwiseUnaryOps.h
View file

@ -50,18 +50,3 @@ cwiseSqrt() const { return derived(); }
inline const CwiseUnaryOp<internal::scalar_inverse_op<Scalar>, const Derived>
cwiseInverse() const { return derived(); }
/** \returns an expression of the coefficient-wise == operator of \c *this and a scalar \a s
*
* \warning this performs an exact comparison, which is generally a bad idea with floating-point types.
* In order to check for equality between two vectors or matrices with floating-point coefficients, it is
* generally a far better idea to use a fuzzy comparison as provided by isApprox() and
* isMuchSmallerThan().
*
* \sa cwiseEqual(const MatrixBase<OtherDerived> &) const
*/
inline const CwiseUnaryOp<std::binder1st<std::equal_to<Scalar> >, const Derived>
cwiseEqual(const Scalar& s) const
{
return CwiseUnaryOp<std::binder1st<std::equal_to<Scalar> >,const Derived>
(derived(), std::bind1st(std::equal_to<Scalar>(), s));
}

2
uppsrc/plugin/Eigen/srcdoc.tpp/Eigen$en-us.tpp
View file

@ -17,7 +17,7 @@ vectors, numerical solvers and related algorithms.]&]
[s0; [C2 -|Matrix2d res `= a`*b;-|// Just multiply them using `*]&]
[s0;#2 &]
[s0;#2 &]
[s0;# [2 Eigen package is a wrapper of Eigen 3.1.2 library. It includes
[s0;# [2 Eigen package is a wrapper of Eigen 3.2.5 library. It includes
the library and helper functions to integrate better Eigen with
U`+`+. Starting from the 3.1.1 version, it is licensed under
the ][^http`:`/`/www`.mozilla`.org`/MPL`/2`.0`/^2 MPL2][2 , which

7
uppsrc/plugin/Eigen/unsupported/CMakeLists.txt Normal file
View file

@ -0,0 +1,7 @@
add_subdirectory(Eigen)
add_subdirectory(doc EXCLUDE_FROM_ALL)
if(EIGEN_LEAVE_TEST_IN_ALL_TARGET)
add_subdirectory(test) # can't do EXCLUDE_FROM_ALL here, breaks CTest
else()
add_subdirectory(test EXCLUDE_FROM_ALL)
endif()

11
uppsrc/plugin/Eigen/unsupported/Eigen/CMakeLists.txt Normal file
View file

@ -0,0 +1,11 @@
set(Eigen_HEADERS AdolcForward AlignedVector3 ArpackSupport AutoDiff BVH FFT IterativeSolvers KroneckerProduct LevenbergMarquardt
MatrixFunctions MoreVectorization MPRealSupport NonLinearOptimization NumericalDiff OpenGLSupport Polynomials
Skyline SparseExtra Splines
)
install(FILES
${Eigen_HEADERS}
DESTINATION ${INCLUDE_INSTALL_DIR}/unsupported/Eigen COMPONENT Devel
)
add_subdirectory(src)

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

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

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

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

14
uppsrc/plugin/Eigen/unsupported/Eigen/src/CMakeLists.txt Normal file
View file

@ -0,0 +1,14 @@
ADD_SUBDIRECTORY(AutoDiff)
ADD_SUBDIRECTORY(BVH)
ADD_SUBDIRECTORY(FFT)
ADD_SUBDIRECTORY(IterativeSolvers)
ADD_SUBDIRECTORY(KroneckerProduct)
ADD_SUBDIRECTORY(LevenbergMarquardt)
ADD_SUBDIRECTORY(MatrixFunctions)
ADD_SUBDIRECTORY(MoreVectorization)
ADD_SUBDIRECTORY(NonLinearOptimization)
ADD_SUBDIRECTORY(NumericalDiff)
ADD_SUBDIRECTORY(Polynomials)
ADD_SUBDIRECTORY(Skyline)
ADD_SUBDIRECTORY(SparseExtra)
ADD_SUBDIRECTORY(Splines)

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

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

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

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

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