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48 Commits
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a45de92246 |
@@ -8,6 +8,6 @@ set(CTEST_PROJECT_NAME "Eigen")
|
||||
set(CTEST_NIGHTLY_START_TIME "00:00:00 UTC")
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||||
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||||
set(CTEST_DROP_METHOD "http")
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||||
set(CTEST_DROP_SITE "eigen.tuxfamily.org")
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set(CTEST_DROP_SITE "manao.inria.fr")
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set(CTEST_DROP_LOCATION "/CDash/submit.php?project=Eigen")
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set(CTEST_DROP_SITE_CDASH TRUE)
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||||
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@@ -136,7 +136,7 @@
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#endif
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||||
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||||
// MSVC for windows mobile does not have the errno.h file
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#if !(defined(_MSC_VER) && defined(_WIN32_WCE))
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#if !(defined(_MSC_VER) && defined(_WIN32_WCE)) && !defined(__ARMCC_VERSION)
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#define EIGEN_HAS_ERRNO
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#endif
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@@ -13,9 +13,9 @@ namespace Eigen {
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*
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*
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*
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* This module provides SVD decomposition for (currently) real matrices.
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* This module provides SVD decomposition for matrices (both real and complex).
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* This decomposition is accessible via the following MatrixBase method:
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* - MatrixBase::svd()
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* - MatrixBase::jacobiSvd()
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*
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* \code
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* #include <Eigen/SVD>
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@@ -331,16 +331,16 @@ template<> struct ldlt_inplace<Upper>
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template<typename MatrixType> struct LDLT_Traits<MatrixType,Lower>
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{
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typedef TriangularView<MatrixType, UnitLower> MatrixL;
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typedef TriangularView<typename MatrixType::AdjointReturnType, UnitUpper> MatrixU;
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typedef const TriangularView<const MatrixType, UnitLower> MatrixL;
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typedef const TriangularView<const typename MatrixType::AdjointReturnType, UnitUpper> MatrixU;
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inline static MatrixL getL(const MatrixType& m) { return m; }
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inline static MatrixU getU(const MatrixType& m) { return m.adjoint(); }
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};
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template<typename MatrixType> struct LDLT_Traits<MatrixType,Upper>
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{
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typedef TriangularView<typename MatrixType::AdjointReturnType, UnitLower> MatrixL;
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typedef TriangularView<MatrixType, UnitUpper> MatrixU;
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typedef const TriangularView<const typename MatrixType::AdjointReturnType, UnitLower> MatrixL;
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typedef const TriangularView<const MatrixType, UnitUpper> MatrixU;
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inline static MatrixL getL(const MatrixType& m) { return m.adjoint(); }
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inline static MatrixU getU(const MatrixType& m) { return m; }
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};
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@@ -274,8 +274,8 @@ template<> struct llt_inplace<Upper>
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template<typename MatrixType> struct LLT_Traits<MatrixType,Lower>
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{
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typedef TriangularView<MatrixType, Lower> MatrixL;
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typedef TriangularView<typename MatrixType::AdjointReturnType, Upper> MatrixU;
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typedef const TriangularView<const MatrixType, Lower> MatrixL;
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typedef const TriangularView<const typename MatrixType::AdjointReturnType, Upper> MatrixU;
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inline static MatrixL getL(const MatrixType& m) { return m; }
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inline static MatrixU getU(const MatrixType& m) { return m.adjoint(); }
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static bool inplace_decomposition(MatrixType& m)
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||||
@@ -284,8 +284,8 @@ template<typename MatrixType> struct LLT_Traits<MatrixType,Lower>
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||||
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||||
template<typename MatrixType> struct LLT_Traits<MatrixType,Upper>
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||||
{
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||||
typedef TriangularView<typename MatrixType::AdjointReturnType, Lower> MatrixL;
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||||
typedef TriangularView<MatrixType, Upper> MatrixU;
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||||
typedef const TriangularView<const typename MatrixType::AdjointReturnType, Lower> MatrixL;
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||||
typedef const TriangularView<const MatrixType, Upper> MatrixU;
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||||
inline static MatrixL getL(const MatrixType& m) { return m.adjoint(); }
|
||||
inline static MatrixU getU(const MatrixType& m) { return m; }
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||||
static bool inplace_decomposition(MatrixType& m)
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||||
|
||||
@@ -94,7 +94,7 @@ struct traits<Block<XprType, BlockRows, BlockCols, InnerPanel, HasDirectAccess>
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||||
MaskPacketAccessBit = (InnerSize == Dynamic || (InnerSize % packet_traits<Scalar>::size) == 0)
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&& (InnerStrideAtCompileTime == 1)
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||||
? PacketAccessBit : 0,
|
||||
MaskAlignedBit = (InnerPanel && (OuterStrideAtCompileTime!=Dynamic) && (((OuterStrideAtCompileTime * sizeof(Scalar)) % 16) == 0)) ? AlignedBit : 0,
|
||||
MaskAlignedBit = (InnerPanel && (OuterStrideAtCompileTime!=Dynamic) && (((OuterStrideAtCompileTime * int(sizeof(Scalar))) % 16) == 0)) ? AlignedBit : 0,
|
||||
FlagsLinearAccessBit = (RowsAtCompileTime == 1 || ColsAtCompileTime == 1) ? LinearAccessBit : 0,
|
||||
FlagsLvalueBit = is_lvalue<XprType>::value ? LvalueBit : 0,
|
||||
FlagsRowMajorBit = IsRowMajor ? RowMajorBit : 0,
|
||||
@@ -342,7 +342,7 @@ class Block<XprType,BlockRows,BlockCols, InnerPanel,true>
|
||||
}
|
||||
|
||||
const typename XprType::Nested m_xpr;
|
||||
int m_outerStride;
|
||||
Index m_outerStride;
|
||||
};
|
||||
|
||||
|
||||
|
||||
@@ -169,8 +169,8 @@ template<typename Derived> class DenseBase
|
||||
|
||||
IsRowMajor = int(Flags) & RowMajorBit, /**< True if this expression has row-major storage order. */
|
||||
|
||||
InnerSizeAtCompileTime = int(IsVectorAtCompileTime) ? SizeAtCompileTime
|
||||
: int(IsRowMajor) ? ColsAtCompileTime : RowsAtCompileTime,
|
||||
InnerSizeAtCompileTime = int(IsVectorAtCompileTime) ? int(SizeAtCompileTime)
|
||||
: int(IsRowMajor) ? int(ColsAtCompileTime) : int(RowsAtCompileTime),
|
||||
|
||||
CoeffReadCost = internal::traits<Derived>::CoeffReadCost,
|
||||
/**< This is a rough measure of how expensive it is to read one coefficient from
|
||||
|
||||
@@ -249,7 +249,7 @@ struct functor_traits<scalar_opposite_op<Scalar> >
|
||||
template<typename Scalar> struct scalar_abs_op {
|
||||
EIGEN_EMPTY_STRUCT_CTOR(scalar_abs_op)
|
||||
typedef typename NumTraits<Scalar>::Real result_type;
|
||||
EIGEN_STRONG_INLINE const result_type operator() (const Scalar& a) const { return abs(a); }
|
||||
EIGEN_STRONG_INLINE const result_type operator() (const Scalar& a) const { return internal::abs(a); }
|
||||
template<typename Packet>
|
||||
EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a) const
|
||||
{ return internal::pabs(a); }
|
||||
@@ -271,7 +271,7 @@ struct functor_traits<scalar_abs_op<Scalar> >
|
||||
template<typename Scalar> struct scalar_abs2_op {
|
||||
EIGEN_EMPTY_STRUCT_CTOR(scalar_abs2_op)
|
||||
typedef typename NumTraits<Scalar>::Real result_type;
|
||||
EIGEN_STRONG_INLINE const result_type operator() (const Scalar& a) const { return abs2(a); }
|
||||
EIGEN_STRONG_INLINE const result_type operator() (const Scalar& a) const { return internal::abs2(a); }
|
||||
template<typename Packet>
|
||||
EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a) const
|
||||
{ return internal::pmul(a,a); }
|
||||
@@ -287,7 +287,7 @@ struct functor_traits<scalar_abs2_op<Scalar> >
|
||||
*/
|
||||
template<typename Scalar> struct scalar_conjugate_op {
|
||||
EIGEN_EMPTY_STRUCT_CTOR(scalar_conjugate_op)
|
||||
EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& a) const { return conj(a); }
|
||||
EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& a) const { return internal::conj(a); }
|
||||
template<typename Packet>
|
||||
EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a) const { return internal::pconj(a); }
|
||||
};
|
||||
@@ -324,7 +324,7 @@ template<typename Scalar>
|
||||
struct scalar_real_op {
|
||||
EIGEN_EMPTY_STRUCT_CTOR(scalar_real_op)
|
||||
typedef typename NumTraits<Scalar>::Real result_type;
|
||||
EIGEN_STRONG_INLINE result_type operator() (const Scalar& a) const { return real(a); }
|
||||
EIGEN_STRONG_INLINE result_type operator() (const Scalar& a) const { return internal::real(a); }
|
||||
};
|
||||
template<typename Scalar>
|
||||
struct functor_traits<scalar_real_op<Scalar> >
|
||||
@@ -339,7 +339,7 @@ template<typename Scalar>
|
||||
struct scalar_imag_op {
|
||||
EIGEN_EMPTY_STRUCT_CTOR(scalar_imag_op)
|
||||
typedef typename NumTraits<Scalar>::Real result_type;
|
||||
EIGEN_STRONG_INLINE result_type operator() (const Scalar& a) const { return imag(a); }
|
||||
EIGEN_STRONG_INLINE result_type operator() (const Scalar& a) const { return internal::imag(a); }
|
||||
};
|
||||
template<typename Scalar>
|
||||
struct functor_traits<scalar_imag_op<Scalar> >
|
||||
@@ -354,7 +354,7 @@ template<typename Scalar>
|
||||
struct scalar_real_ref_op {
|
||||
EIGEN_EMPTY_STRUCT_CTOR(scalar_real_ref_op)
|
||||
typedef typename NumTraits<Scalar>::Real result_type;
|
||||
EIGEN_STRONG_INLINE result_type& operator() (const Scalar& a) const { return real_ref(*const_cast<Scalar*>(&a)); }
|
||||
EIGEN_STRONG_INLINE result_type& operator() (const Scalar& a) const { return internal::real_ref(*const_cast<Scalar*>(&a)); }
|
||||
};
|
||||
template<typename Scalar>
|
||||
struct functor_traits<scalar_real_ref_op<Scalar> >
|
||||
@@ -369,7 +369,7 @@ template<typename Scalar>
|
||||
struct scalar_imag_ref_op {
|
||||
EIGEN_EMPTY_STRUCT_CTOR(scalar_imag_ref_op)
|
||||
typedef typename NumTraits<Scalar>::Real result_type;
|
||||
EIGEN_STRONG_INLINE result_type& operator() (const Scalar& a) const { return imag_ref(*const_cast<Scalar*>(&a)); }
|
||||
EIGEN_STRONG_INLINE result_type& operator() (const Scalar& a) const { return internal::imag_ref(*const_cast<Scalar*>(&a)); }
|
||||
};
|
||||
template<typename Scalar>
|
||||
struct functor_traits<scalar_imag_ref_op<Scalar> >
|
||||
@@ -383,7 +383,7 @@ struct functor_traits<scalar_imag_ref_op<Scalar> >
|
||||
*/
|
||||
template<typename Scalar> struct scalar_exp_op {
|
||||
EIGEN_EMPTY_STRUCT_CTOR(scalar_exp_op)
|
||||
inline const Scalar operator() (const Scalar& a) const { return exp(a); }
|
||||
inline const Scalar operator() (const Scalar& a) const { return internal::exp(a); }
|
||||
typedef typename packet_traits<Scalar>::type Packet;
|
||||
inline Packet packetOp(const Packet& a) const { return internal::pexp(a); }
|
||||
};
|
||||
@@ -399,7 +399,7 @@ struct functor_traits<scalar_exp_op<Scalar> >
|
||||
*/
|
||||
template<typename Scalar> struct scalar_log_op {
|
||||
EIGEN_EMPTY_STRUCT_CTOR(scalar_log_op)
|
||||
inline const Scalar operator() (const Scalar& a) const { return log(a); }
|
||||
inline const Scalar operator() (const Scalar& a) const { return internal::log(a); }
|
||||
typedef typename packet_traits<Scalar>::type Packet;
|
||||
inline Packet packetOp(const Packet& a) const { return internal::plog(a); }
|
||||
};
|
||||
@@ -657,7 +657,7 @@ struct functor_traits<scalar_add_op<Scalar> >
|
||||
*/
|
||||
template<typename Scalar> struct scalar_sqrt_op {
|
||||
EIGEN_EMPTY_STRUCT_CTOR(scalar_sqrt_op)
|
||||
inline const Scalar operator() (const Scalar& a) const { return sqrt(a); }
|
||||
inline const Scalar operator() (const Scalar& a) const { return internal::sqrt(a); }
|
||||
typedef typename packet_traits<Scalar>::type Packet;
|
||||
inline Packet packetOp(const Packet& a) const { return internal::psqrt(a); }
|
||||
};
|
||||
@@ -675,7 +675,7 @@ struct functor_traits<scalar_sqrt_op<Scalar> >
|
||||
*/
|
||||
template<typename Scalar> struct scalar_cos_op {
|
||||
EIGEN_EMPTY_STRUCT_CTOR(scalar_cos_op)
|
||||
inline Scalar operator() (const Scalar& a) const { return cos(a); }
|
||||
inline Scalar operator() (const Scalar& a) const { return internal::cos(a); }
|
||||
typedef typename packet_traits<Scalar>::type Packet;
|
||||
inline Packet packetOp(const Packet& a) const { return internal::pcos(a); }
|
||||
};
|
||||
@@ -694,7 +694,7 @@ struct functor_traits<scalar_cos_op<Scalar> >
|
||||
*/
|
||||
template<typename Scalar> struct scalar_sin_op {
|
||||
EIGEN_EMPTY_STRUCT_CTOR(scalar_sin_op)
|
||||
inline const Scalar operator() (const Scalar& a) const { return sin(a); }
|
||||
inline const Scalar operator() (const Scalar& a) const { return internal::sin(a); }
|
||||
typedef typename packet_traits<Scalar>::type Packet;
|
||||
inline Packet packetOp(const Packet& a) const { return internal::psin(a); }
|
||||
};
|
||||
@@ -714,7 +714,7 @@ struct functor_traits<scalar_sin_op<Scalar> >
|
||||
*/
|
||||
template<typename Scalar> struct scalar_tan_op {
|
||||
EIGEN_EMPTY_STRUCT_CTOR(scalar_tan_op)
|
||||
inline const Scalar operator() (const Scalar& a) const { return tan(a); }
|
||||
inline const Scalar operator() (const Scalar& a) const { return internal::tan(a); }
|
||||
typedef typename packet_traits<Scalar>::type Packet;
|
||||
inline Packet packetOp(const Packet& a) const { return internal::ptan(a); }
|
||||
};
|
||||
@@ -733,7 +733,7 @@ struct functor_traits<scalar_tan_op<Scalar> >
|
||||
*/
|
||||
template<typename Scalar> struct scalar_acos_op {
|
||||
EIGEN_EMPTY_STRUCT_CTOR(scalar_acos_op)
|
||||
inline const Scalar operator() (const Scalar& a) const { return acos(a); }
|
||||
inline const Scalar operator() (const Scalar& a) const { return internal::acos(a); }
|
||||
typedef typename packet_traits<Scalar>::type Packet;
|
||||
inline Packet packetOp(const Packet& a) const { return internal::pacos(a); }
|
||||
};
|
||||
@@ -752,7 +752,7 @@ struct functor_traits<scalar_acos_op<Scalar> >
|
||||
*/
|
||||
template<typename Scalar> struct scalar_asin_op {
|
||||
EIGEN_EMPTY_STRUCT_CTOR(scalar_asin_op)
|
||||
inline const Scalar operator() (const Scalar& a) const { return asin(a); }
|
||||
inline const Scalar operator() (const Scalar& a) const { return internal::asin(a); }
|
||||
typedef typename packet_traits<Scalar>::type Packet;
|
||||
inline Packet packetOp(const Packet& a) const { return internal::pasin(a); }
|
||||
};
|
||||
|
||||
@@ -102,7 +102,7 @@ struct traits<Map<PlainObjectType, MapOptions, StrideType> >
|
||||
|| HasNoOuterStride
|
||||
|| ( OuterStrideAtCompileTime!=Dynamic
|
||||
&& ((static_cast<int>(sizeof(Scalar))*OuterStrideAtCompileTime)%16)==0 ) ),
|
||||
Flags0 = TraitsBase::Flags,
|
||||
Flags0 = TraitsBase::Flags & (~NestByRefBit),
|
||||
Flags1 = IsAligned ? (int(Flags0) | AlignedBit) : (int(Flags0) & ~AlignedBit),
|
||||
Flags2 = (bool(HasNoStride) || bool(PlainObjectType::IsVectorAtCompileTime))
|
||||
? int(Flags1) : int(Flags1 & ~LinearAccessBit),
|
||||
@@ -120,7 +120,6 @@ template<typename PlainObjectType, int MapOptions, typename StrideType> class Ma
|
||||
public:
|
||||
|
||||
typedef MapBase<Map> Base;
|
||||
|
||||
EIGEN_DENSE_PUBLIC_INTERFACE(Map)
|
||||
|
||||
typedef typename Base::PointerType PointerType;
|
||||
@@ -181,7 +180,6 @@ template<typename PlainObjectType, int MapOptions, typename StrideType> class Ma
|
||||
PlainObjectType::Base::_check_template_params();
|
||||
}
|
||||
|
||||
|
||||
EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Map)
|
||||
|
||||
protected:
|
||||
|
||||
@@ -47,7 +47,7 @@ EIGEN_ALWAYS_INLINE void check_rows_cols_for_overflow(Index rows, Index cols)
|
||||
throw_std_bad_alloc();
|
||||
}
|
||||
|
||||
template <typename Derived, typename OtherDerived = Derived, bool IsVector = static_cast<bool>(Derived::IsVectorAtCompileTime)> struct conservative_resize_like_impl;
|
||||
template <typename Derived, typename OtherDerived = Derived, bool IsVector = bool(Derived::IsVectorAtCompileTime)> struct conservative_resize_like_impl;
|
||||
|
||||
template<typename MatrixTypeA, typename MatrixTypeB, bool SwapPointers> struct matrix_swap_impl;
|
||||
|
||||
@@ -543,6 +543,7 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
|
||||
eigen_assert((this->size()==0 || (IsVectorAtCompileTime ? (this->size() == other.size())
|
||||
: (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);
|
||||
#else
|
||||
resizeLike(other);
|
||||
#endif
|
||||
|
||||
@@ -152,7 +152,8 @@ class ProductBase : public MatrixBase<Derived>
|
||||
#else
|
||||
EIGEN_STATIC_ASSERT_SIZE_1x1(Derived)
|
||||
eigen_assert(this->rows() == 1 && this->cols() == 1);
|
||||
return derived().coeff(row,col);
|
||||
Matrix<Scalar,1,1> result = *this;
|
||||
return result.coeff(row,col);
|
||||
#endif
|
||||
}
|
||||
|
||||
@@ -160,7 +161,8 @@ class ProductBase : public MatrixBase<Derived>
|
||||
{
|
||||
EIGEN_STATIC_ASSERT_SIZE_1x1(Derived)
|
||||
eigen_assert(this->rows() == 1 && this->cols() == 1);
|
||||
return derived().coeff(i);
|
||||
Matrix<Scalar,1,1> result = *this;
|
||||
return result.coeff(i);
|
||||
}
|
||||
|
||||
const Scalar& coeffRef(Index row, Index col) const
|
||||
|
||||
@@ -48,7 +48,10 @@ struct traits<Replicate<MatrixType,RowFactor,ColFactor> >
|
||||
typedef typename MatrixType::Scalar Scalar;
|
||||
typedef typename traits<MatrixType>::StorageKind StorageKind;
|
||||
typedef typename traits<MatrixType>::XprKind XprKind;
|
||||
typedef typename nested<MatrixType>::type MatrixTypeNested;
|
||||
enum {
|
||||
Factor = (RowFactor==Dynamic || ColFactor==Dynamic) ? Dynamic : RowFactor*ColFactor
|
||||
};
|
||||
typedef typename nested<MatrixType,Factor>::type MatrixTypeNested;
|
||||
typedef typename remove_reference<MatrixTypeNested>::type _MatrixTypeNested;
|
||||
enum {
|
||||
RowsAtCompileTime = RowFactor==Dynamic || int(MatrixType::RowsAtCompileTime)==Dynamic
|
||||
@@ -72,6 +75,8 @@ struct traits<Replicate<MatrixType,RowFactor,ColFactor> >
|
||||
template<typename MatrixType,int RowFactor,int ColFactor> class Replicate
|
||||
: public internal::dense_xpr_base< Replicate<MatrixType,RowFactor,ColFactor> >::type
|
||||
{
|
||||
typedef typename internal::traits<Replicate>::MatrixTypeNested MatrixTypeNested;
|
||||
typedef typename internal::traits<Replicate>::_MatrixTypeNested _MatrixTypeNested;
|
||||
public:
|
||||
|
||||
typedef typename internal::dense_xpr_base<Replicate>::type Base;
|
||||
@@ -124,7 +129,7 @@ template<typename MatrixType,int RowFactor,int ColFactor> class Replicate
|
||||
|
||||
|
||||
protected:
|
||||
const typename MatrixType::Nested m_matrix;
|
||||
const MatrixTypeNested m_matrix;
|
||||
const internal::variable_if_dynamic<Index, RowFactor> m_rowFactor;
|
||||
const internal::variable_if_dynamic<Index, ColFactor> m_colFactor;
|
||||
};
|
||||
|
||||
@@ -121,7 +121,7 @@ Packet4f pexp<Packet4f>(const Packet4f& _x)
|
||||
_EIGEN_DECLARE_CONST_Packet4i(0x7f, 0x7f);
|
||||
|
||||
|
||||
_EIGEN_DECLARE_CONST_Packet4f(exp_hi, 88.3762626647949f);
|
||||
_EIGEN_DECLARE_CONST_Packet4f(exp_hi, 88.3762626647950f);
|
||||
_EIGEN_DECLARE_CONST_Packet4f(exp_lo, -88.3762626647949f);
|
||||
|
||||
_EIGEN_DECLARE_CONST_Packet4f(cephes_LOG2EF, 1.44269504088896341f);
|
||||
@@ -168,7 +168,7 @@ Packet4f pexp<Packet4f>(const Packet4f& _x)
|
||||
y = pmadd(y, z, x);
|
||||
y = padd(y, p4f_1);
|
||||
|
||||
/* build 2^n */
|
||||
// build 2^n
|
||||
emm0 = _mm_cvttps_epi32(fx);
|
||||
emm0 = _mm_add_epi32(emm0, p4i_0x7f);
|
||||
emm0 = _mm_slli_epi32(emm0, 23);
|
||||
|
||||
@@ -30,18 +30,24 @@ namespace internal {
|
||||
template<typename _LhsScalar, typename _RhsScalar, bool _ConjLhs=false, bool _ConjRhs=false>
|
||||
class gebp_traits;
|
||||
|
||||
/** \internal \returns b if a<=0, and returns a otherwise. */
|
||||
inline std::ptrdiff_t manage_caching_sizes_helper(std::ptrdiff_t a, std::ptrdiff_t b)
|
||||
{
|
||||
return a<=0 ? b : a;
|
||||
}
|
||||
|
||||
/** \internal */
|
||||
inline void manage_caching_sizes(Action action, std::ptrdiff_t* l1=0, std::ptrdiff_t* l2=0)
|
||||
{
|
||||
static std::ptrdiff_t m_l1CacheSize = 0;
|
||||
static std::ptrdiff_t m_l2CacheSize = 0;
|
||||
#ifdef _OPENMP
|
||||
#pragma omp threadprivate(m_l1CacheSize,m_l2CacheSize)
|
||||
#endif
|
||||
if(m_l1CacheSize==0)
|
||||
{
|
||||
m_l1CacheSize = queryL1CacheSize();
|
||||
m_l2CacheSize = queryTopLevelCacheSize();
|
||||
|
||||
if(m_l1CacheSize<=0) m_l1CacheSize = 8 * 1024;
|
||||
if(m_l2CacheSize<=0) m_l2CacheSize = 1 * 1024 * 1024;
|
||||
m_l1CacheSize = manage_caching_sizes_helper(queryL1CacheSize(),8 * 1024);
|
||||
m_l2CacheSize = manage_caching_sizes_helper(queryTopLevelCacheSize(),1*1024*1024);
|
||||
}
|
||||
|
||||
if(action==SetAction)
|
||||
|
||||
@@ -1,3 +1,4 @@
|
||||
|
||||
// This file is part of Eigen, a lightweight C++ template library
|
||||
// for linear algebra.
|
||||
//
|
||||
@@ -28,7 +29,7 @@
|
||||
|
||||
#define EIGEN_WORLD_VERSION 3
|
||||
#define EIGEN_MAJOR_VERSION 0
|
||||
#define EIGEN_MINOR_VERSION 4
|
||||
#define EIGEN_MINOR_VERSION 7
|
||||
|
||||
#define EIGEN_VERSION_AT_LEAST(x,y,z) (EIGEN_WORLD_VERSION>x || (EIGEN_WORLD_VERSION>=x && \
|
||||
(EIGEN_MAJOR_VERSION>y || (EIGEN_MAJOR_VERSION>=y && \
|
||||
@@ -264,7 +265,7 @@
|
||||
* If we made alignment depend on whether or not EIGEN_VECTORIZE is defined, it would be impossible to link
|
||||
* vectorized and non-vectorized code.
|
||||
*/
|
||||
#if (defined __GNUC__) || (defined __PGI) || (defined __IBMCPP__)
|
||||
#if (defined __GNUC__) || (defined __PGI) || (defined __IBMCPP__) || (defined __ARMCC_VERSION)
|
||||
#define EIGEN_ALIGN_TO_BOUNDARY(n) __attribute__((aligned(n)))
|
||||
#elif (defined _MSC_VER)
|
||||
#define EIGEN_ALIGN_TO_BOUNDARY(n) __declspec(align(n))
|
||||
|
||||
@@ -127,7 +127,7 @@ class compute_matrix_flags
|
||||
((Options&DontAlign)==0)
|
||||
&& (
|
||||
#if EIGEN_ALIGN_STATICALLY
|
||||
((!is_dynamic_size_storage) && (((MaxCols*MaxRows*sizeof(Scalar)) % 16) == 0))
|
||||
((!is_dynamic_size_storage) && (((MaxCols*MaxRows*int(sizeof(Scalar))) % 16) == 0))
|
||||
#else
|
||||
0
|
||||
#endif
|
||||
|
||||
@@ -291,7 +291,7 @@ template<typename _MatrixType> class EigenSolver
|
||||
|
||||
ComputationInfo info() const
|
||||
{
|
||||
eigen_assert(m_isInitialized && "ComplexEigenSolver is not initialized.");
|
||||
eigen_assert(m_isInitialized && "EigenSolver is not initialized.");
|
||||
return m_realSchur.info();
|
||||
}
|
||||
|
||||
@@ -339,7 +339,7 @@ typename EigenSolver<MatrixType>::EigenvectorsType EigenSolver<MatrixType>::eige
|
||||
EigenvectorsType matV(n,n);
|
||||
for (Index j=0; j<n; ++j)
|
||||
{
|
||||
if (internal::isMuchSmallerThan(internal::imag(m_eivalues.coeff(j)), internal::real(m_eivalues.coeff(j))))
|
||||
if (internal::isMuchSmallerThan(internal::imag(m_eivalues.coeff(j)), internal::real(m_eivalues.coeff(j))) || j+1==n)
|
||||
{
|
||||
// we have a real eigen value
|
||||
matV.col(j) = m_eivec.col(j).template cast<ComplexScalar>();
|
||||
@@ -570,10 +570,13 @@ void EigenSolver<MatrixType>::doComputeEigenvectors()
|
||||
|
||||
}
|
||||
}
|
||||
|
||||
// We handled a pair of complex conjugate eigenvalues, so need to skip them both
|
||||
n--;
|
||||
}
|
||||
else
|
||||
{
|
||||
eigen_assert("Internal bug in EigenSolver"); // this should not happen
|
||||
eigen_assert(0 && "Internal bug in EigenSolver"); // this should not happen
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
@@ -238,38 +238,41 @@ RealSchur<MatrixType>& RealSchur<MatrixType>::compute(const MatrixType& matrix,
|
||||
Scalar exshift = 0.0; // sum of exceptional shifts
|
||||
Scalar norm = computeNormOfT();
|
||||
|
||||
while (iu >= 0)
|
||||
if(norm!=0)
|
||||
{
|
||||
Index il = findSmallSubdiagEntry(iu, norm);
|
||||
|
||||
// Check for convergence
|
||||
if (il == iu) // One root found
|
||||
{
|
||||
m_matT.coeffRef(iu,iu) = m_matT.coeff(iu,iu) + exshift;
|
||||
if (iu > 0)
|
||||
m_matT.coeffRef(iu, iu-1) = Scalar(0);
|
||||
iu--;
|
||||
iter = 0;
|
||||
}
|
||||
else if (il == iu-1) // Two roots found
|
||||
{
|
||||
splitOffTwoRows(iu, computeU, exshift);
|
||||
iu -= 2;
|
||||
iter = 0;
|
||||
}
|
||||
else // No convergence yet
|
||||
{
|
||||
// The firstHouseholderVector vector has to be initialized to something to get rid of a silly GCC warning (-O1 -Wall -DNDEBUG )
|
||||
Vector3s firstHouseholderVector(0,0,0), shiftInfo;
|
||||
computeShift(iu, iter, exshift, shiftInfo);
|
||||
iter = iter + 1;
|
||||
if (iter > m_maxIterations) break;
|
||||
Index im;
|
||||
initFrancisQRStep(il, iu, shiftInfo, im, firstHouseholderVector);
|
||||
performFrancisQRStep(il, im, iu, computeU, firstHouseholderVector, workspace);
|
||||
}
|
||||
}
|
||||
while (iu >= 0)
|
||||
{
|
||||
Index il = findSmallSubdiagEntry(iu, norm);
|
||||
|
||||
// Check for convergence
|
||||
if (il == iu) // One root found
|
||||
{
|
||||
m_matT.coeffRef(iu,iu) = m_matT.coeff(iu,iu) + exshift;
|
||||
if (iu > 0)
|
||||
m_matT.coeffRef(iu, iu-1) = Scalar(0);
|
||||
iu--;
|
||||
iter = 0;
|
||||
}
|
||||
else if (il == iu-1) // Two roots found
|
||||
{
|
||||
splitOffTwoRows(iu, computeU, exshift);
|
||||
iu -= 2;
|
||||
iter = 0;
|
||||
}
|
||||
else // No convergence yet
|
||||
{
|
||||
// The firstHouseholderVector vector has to be initialized to something to get rid of a silly GCC warning (-O1 -Wall -DNDEBUG )
|
||||
Vector3s firstHouseholderVector(0,0,0), shiftInfo;
|
||||
computeShift(iu, iter, exshift, shiftInfo);
|
||||
iter = iter + 1;
|
||||
if (iter > m_maxIterations) break;
|
||||
Index im;
|
||||
initFrancisQRStep(il, iu, shiftInfo, im, firstHouseholderVector);
|
||||
performFrancisQRStep(il, im, iu, computeU, firstHouseholderVector, workspace);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
if(iter <= m_maxIterations)
|
||||
m_info = Success;
|
||||
else
|
||||
|
||||
@@ -220,7 +220,6 @@ template<typename _MatrixType> class SelfAdjointEigenSolver
|
||||
const MatrixType& eigenvectors() const
|
||||
{
|
||||
eigen_assert(m_isInitialized && "SelfAdjointEigenSolver is not initialized.");
|
||||
eigen_assert(info() == Success && "Eigenvalue computation did not converge.");
|
||||
eigen_assert(m_eigenvectorsOk && "The eigenvectors have not been computed together with the eigenvalues.");
|
||||
return m_eivec;
|
||||
}
|
||||
@@ -243,7 +242,6 @@ template<typename _MatrixType> class SelfAdjointEigenSolver
|
||||
const RealVectorType& eigenvalues() const
|
||||
{
|
||||
eigen_assert(m_isInitialized && "SelfAdjointEigenSolver is not initialized.");
|
||||
eigen_assert(info() == Success && "Eigenvalue computation did not converge.");
|
||||
return m_eivalues;
|
||||
}
|
||||
|
||||
@@ -268,7 +266,6 @@ template<typename _MatrixType> class SelfAdjointEigenSolver
|
||||
MatrixType operatorSqrt() const
|
||||
{
|
||||
eigen_assert(m_isInitialized && "SelfAdjointEigenSolver is not initialized.");
|
||||
eigen_assert(info() == Success && "Eigenvalue computation did not converge.");
|
||||
eigen_assert(m_eigenvectorsOk && "The eigenvectors have not been computed together with the eigenvalues.");
|
||||
return m_eivec * m_eivalues.cwiseSqrt().asDiagonal() * m_eivec.adjoint();
|
||||
}
|
||||
@@ -294,7 +291,6 @@ template<typename _MatrixType> class SelfAdjointEigenSolver
|
||||
MatrixType operatorInverseSqrt() const
|
||||
{
|
||||
eigen_assert(m_isInitialized && "SelfAdjointEigenSolver is not initialized.");
|
||||
eigen_assert(info() == Success && "Eigenvalue computation did not converge.");
|
||||
eigen_assert(m_eigenvectorsOk && "The eigenvectors have not been computed together with the eigenvalues.");
|
||||
return m_eivec * m_eivalues.cwiseInverse().cwiseSqrt().asDiagonal() * m_eivec.adjoint();
|
||||
}
|
||||
|
||||
@@ -225,7 +225,7 @@ public:
|
||||
normal() = mat * normal();
|
||||
else
|
||||
{
|
||||
eigen_assert("invalid traits value in Hyperplane::transform()");
|
||||
eigen_assert(0 && "invalid traits value in Hyperplane::transform()");
|
||||
}
|
||||
return *this;
|
||||
}
|
||||
|
||||
@@ -200,7 +200,8 @@ public:
|
||||
*
|
||||
* \brief The quaternion class used to represent 3D orientations and rotations
|
||||
*
|
||||
* \param _Scalar the scalar type, i.e., the type of the coefficients
|
||||
* \tparam _Scalar the scalar type, i.e., the type of the coefficients
|
||||
* \tparam _Options controls the memory alignement of the coeffecients. Can be \# AutoAlign or \# DontAlign. Default is AutoAlign.
|
||||
*
|
||||
* This class represents a quaternion \f$ w+xi+yj+zk \f$ that is a convenient representation of
|
||||
* orientations and rotations of objects in three dimensions. Compared to other representations
|
||||
@@ -308,41 +309,29 @@ typedef Quaternion<double> Quaterniond;
|
||||
|
||||
namespace internal {
|
||||
template<typename _Scalar, int _Options>
|
||||
struct traits<Map<Quaternion<_Scalar>, _Options> >:
|
||||
traits<Quaternion<_Scalar, _Options> >
|
||||
struct traits<Map<Quaternion<_Scalar>, _Options> > : traits<Quaternion<_Scalar, (int(_Options)&Aligned)==Aligned ? AutoAlign : DontAlign> >
|
||||
{
|
||||
typedef _Scalar Scalar;
|
||||
typedef Map<Matrix<_Scalar,4,1>, _Options> Coefficients;
|
||||
|
||||
typedef traits<Quaternion<_Scalar, _Options> > TraitsBase;
|
||||
enum {
|
||||
IsAligned = TraitsBase::IsAligned,
|
||||
|
||||
Flags = TraitsBase::Flags
|
||||
};
|
||||
};
|
||||
}
|
||||
|
||||
namespace internal {
|
||||
template<typename _Scalar, int _Options>
|
||||
struct traits<Map<const Quaternion<_Scalar>, _Options> >:
|
||||
traits<Quaternion<_Scalar> >
|
||||
struct traits<Map<const Quaternion<_Scalar>, _Options> > : traits<Quaternion<_Scalar, (int(_Options)&Aligned)==Aligned ? AutoAlign : DontAlign> >
|
||||
{
|
||||
typedef _Scalar Scalar;
|
||||
typedef Map<const Matrix<_Scalar,4,1>, _Options> Coefficients;
|
||||
|
||||
typedef traits<Quaternion<_Scalar, _Options> > TraitsBase;
|
||||
typedef traits<Quaternion<_Scalar, (int(_Options)&Aligned)==Aligned ? AutoAlign : DontAlign> > TraitsBase;
|
||||
enum {
|
||||
IsAligned = TraitsBase::IsAligned,
|
||||
Flags = TraitsBase::Flags & ~LvalueBit
|
||||
};
|
||||
};
|
||||
}
|
||||
|
||||
/** \brief Quaternion expression mapping a constant memory buffer
|
||||
/** \ingroup Geometry_Module
|
||||
* \brief Quaternion expression mapping a constant memory buffer
|
||||
*
|
||||
* \param _Scalar the type of the Quaternion coefficients
|
||||
* \param _Options see class Map
|
||||
* \tparam _Scalar the type of the Quaternion coefficients
|
||||
* \tparam _Options see class Map
|
||||
*
|
||||
* This is a specialization of class Map for Quaternion. This class allows to view
|
||||
* a 4 scalar memory buffer as an Eigen's Quaternion object.
|
||||
@@ -375,10 +364,11 @@ class Map<const Quaternion<_Scalar>, _Options >
|
||||
const Coefficients m_coeffs;
|
||||
};
|
||||
|
||||
/** \brief Expression of a quaternion from a memory buffer
|
||||
/** \ingroup Geometry_Module
|
||||
* \brief Expression of a quaternion from a memory buffer
|
||||
*
|
||||
* \param _Scalar the type of the Quaternion coefficients
|
||||
* \param _Options see class Map
|
||||
* \tparam _Scalar the type of the Quaternion coefficients
|
||||
* \tparam _Options see class Map
|
||||
*
|
||||
* This is a specialization of class Map for Quaternion. This class allows to view
|
||||
* a 4 scalar memory buffer as an Eigen's Quaternion object.
|
||||
@@ -682,7 +672,7 @@ QuaternionBase<Derived>::slerp(Scalar t, const QuaternionBase<OtherDerived>& oth
|
||||
Scalar scale0;
|
||||
Scalar scale1;
|
||||
|
||||
if (absD>=one)
|
||||
if(absD>=one)
|
||||
{
|
||||
scale0 = Scalar(1) - t;
|
||||
scale1 = t;
|
||||
@@ -695,9 +685,8 @@ QuaternionBase<Derived>::slerp(Scalar t, const QuaternionBase<OtherDerived>& oth
|
||||
|
||||
scale0 = internal::sin( ( Scalar(1) - t ) * theta) / sinTheta;
|
||||
scale1 = internal::sin( ( t * theta) ) / sinTheta;
|
||||
if (d<0)
|
||||
scale1 = -scale1;
|
||||
}
|
||||
if(d<0) scale1 = -scale1;
|
||||
|
||||
return Quaternion<Scalar>(scale0 * coeffs() + scale1 * other.coeffs());
|
||||
}
|
||||
|
||||
@@ -89,7 +89,7 @@ public:
|
||||
|
||||
/** Concatenates two rotations */
|
||||
inline Rotation2D& operator*=(const Rotation2D& other)
|
||||
{ return m_angle += other.m_angle; return *this; }
|
||||
{ m_angle += other.m_angle; return *this; }
|
||||
|
||||
/** Applies the rotation to a 2D vector */
|
||||
Vector2 operator* (const Vector2& vec) const
|
||||
|
||||
@@ -37,7 +37,7 @@ struct transform_traits
|
||||
Dim = Transform::Dim,
|
||||
HDim = Transform::HDim,
|
||||
Mode = Transform::Mode,
|
||||
IsProjective = (Mode==Projective)
|
||||
IsProjective = (int(Mode)==int(Projective))
|
||||
};
|
||||
};
|
||||
|
||||
@@ -61,7 +61,7 @@ template< typename Lhs,
|
||||
typename Rhs,
|
||||
bool AnyProjective =
|
||||
transform_traits<Lhs>::IsProjective ||
|
||||
transform_traits<Lhs>::IsProjective>
|
||||
transform_traits<Rhs>::IsProjective>
|
||||
struct transform_transform_product_impl;
|
||||
|
||||
template< typename Other,
|
||||
@@ -571,7 +571,7 @@ public:
|
||||
if(int(Mode)!=int(AffineCompact))
|
||||
{
|
||||
matrix().template block<1,Dim>(Dim,0).setZero();
|
||||
matrix().coeffRef(Dim,Dim) = 1;
|
||||
matrix().coeffRef(Dim,Dim) = Scalar(1);
|
||||
}
|
||||
}
|
||||
|
||||
@@ -1391,6 +1391,35 @@ struct transform_transform_product_impl<Transform<Scalar,Dim,LhsMode,LhsOptions>
|
||||
}
|
||||
};
|
||||
|
||||
template<typename Scalar, int Dim, int LhsOptions, int RhsOptions>
|
||||
struct transform_transform_product_impl<Transform<Scalar,Dim,AffineCompact,LhsOptions>,Transform<Scalar,Dim,Projective,RhsOptions>,true >
|
||||
{
|
||||
typedef Transform<Scalar,Dim,AffineCompact,LhsOptions> Lhs;
|
||||
typedef Transform<Scalar,Dim,Projective,RhsOptions> Rhs;
|
||||
typedef Transform<Scalar,Dim,Projective> ResultType;
|
||||
static ResultType run(const Lhs& lhs, const Rhs& rhs)
|
||||
{
|
||||
ResultType res;
|
||||
res.matrix().template topRows<Dim>() = lhs.matrix() * rhs.matrix();
|
||||
res.matrix().row(Dim) = rhs.matrix().row(Dim);
|
||||
return res;
|
||||
}
|
||||
};
|
||||
|
||||
template<typename Scalar, int Dim, int LhsOptions, int RhsOptions>
|
||||
struct transform_transform_product_impl<Transform<Scalar,Dim,Projective,LhsOptions>,Transform<Scalar,Dim,AffineCompact,RhsOptions>,true >
|
||||
{
|
||||
typedef Transform<Scalar,Dim,Projective,LhsOptions> Lhs;
|
||||
typedef Transform<Scalar,Dim,AffineCompact,RhsOptions> Rhs;
|
||||
typedef Transform<Scalar,Dim,Projective> ResultType;
|
||||
static ResultType run(const Lhs& lhs, const Rhs& rhs)
|
||||
{
|
||||
ResultType res(lhs.matrix().template leftCols<Dim>() * rhs.matrix());
|
||||
res.matrix().col(Dim) += lhs.matrix().col(Dim);
|
||||
return res;
|
||||
}
|
||||
};
|
||||
|
||||
} // end namespace internal
|
||||
|
||||
#endif // EIGEN_TRANSFORM_H
|
||||
|
||||
@@ -96,7 +96,7 @@ struct quat_product<Architecture::SSE, Derived, OtherDerived, double, Aligned>
|
||||
*/
|
||||
t1 = padd(pmul(a_ww, b_xy), pmul(a_yy, b_zw));
|
||||
t2 = psub(pmul(a_zz, b_xy), pmul(a_xx, b_zw));
|
||||
#ifdef __SSE3__
|
||||
#ifdef EIGEN_VECTORIZE_SSE3
|
||||
EIGEN_UNUSED_VARIABLE(mask)
|
||||
pstore(&res.x(), _mm_addsub_pd(t1, preverse(t2)));
|
||||
#else
|
||||
@@ -110,7 +110,7 @@ struct quat_product<Architecture::SSE, Derived, OtherDerived, double, Aligned>
|
||||
*/
|
||||
t1 = psub(pmul(a_ww, b_zw), pmul(a_yy, b_xy));
|
||||
t2 = padd(pmul(a_zz, b_zw), pmul(a_xx, b_xy));
|
||||
#ifdef __SSE3__
|
||||
#ifdef EIGEN_VECTORIZE_SSE3
|
||||
EIGEN_UNUSED_VARIABLE(mask)
|
||||
pstore(&res.z(), preverse(_mm_addsub_pd(preverse(t1), t2)));
|
||||
#else
|
||||
|
||||
@@ -55,7 +55,7 @@ struct compute_inverse_size4<Architecture::SSE, float, MatrixType, ResultType>
|
||||
|
||||
static void run(const MatrixType& matrix, ResultType& result)
|
||||
{
|
||||
EIGEN_ALIGN16 const int _Sign_PNNP[4] = { 0x00000000, 0x80000000, 0x80000000, 0x00000000 };
|
||||
EIGEN_ALIGN16 const unsigned int _Sign_PNNP[4] = { 0x00000000, 0x80000000, 0x80000000, 0x00000000 };
|
||||
|
||||
// Load the full matrix into registers
|
||||
__m128 _L1 = matrix.template packet<MatrixAlignment>( 0);
|
||||
|
||||
@@ -708,6 +708,13 @@ struct solve_retval<JacobiSVD<_MatrixType, QRPreconditioner>, Rhs>
|
||||
};
|
||||
} // end namespace internal
|
||||
|
||||
/** \svd_module
|
||||
*
|
||||
* \return the singular value decomposition of \c *this computed by two-sided
|
||||
* Jacobi transformations.
|
||||
*
|
||||
* \sa class JacobiSVD
|
||||
*/
|
||||
template<typename Derived>
|
||||
JacobiSVD<typename MatrixBase<Derived>::PlainObject>
|
||||
MatrixBase<Derived>::jacobiSvd(unsigned int computationOptions) const
|
||||
|
||||
@@ -51,10 +51,10 @@ AngleAxis<float> aa(angle_in_radian, Vector3f(ax,ay,az));\endcode</td></tr>
|
||||
Quaternion<float> q; q = AngleAxis<float>(angle_in_radian, axis);\endcode</td></tr>
|
||||
<tr class="alt"><td>
|
||||
N-D Scaling</td><td>\code
|
||||
Scaling<float,2>(sx, sy)
|
||||
Scaling<float,3>(sx, sy, sz)
|
||||
Scaling<float,N>(s)
|
||||
Scaling<float,N>(vecN)\endcode</td></tr>
|
||||
Scaling(sx, sy)
|
||||
Scaling(sx, sy, sz)
|
||||
Scaling(s)
|
||||
Scaling(vecN)\endcode</td></tr>
|
||||
<tr><td>
|
||||
N-D Translation</td><td>\code
|
||||
Translation<float,2>(tx, ty)
|
||||
@@ -64,13 +64,13 @@ Translation<float,N>(vecN)\endcode</td></tr>
|
||||
<tr class="alt"><td>
|
||||
N-D \ref TutorialGeoTransform "Affine transformation"</td><td>\code
|
||||
Transform<float,N,Affine> t = concatenation_of_any_transformations;
|
||||
Transform<float,3,Affine> t = Translation3f(p) * AngleAxisf(a,axis) * Scaling3f(s);\endcode</td></tr>
|
||||
Transform<float,3,Affine> t = Translation3f(p) * AngleAxisf(a,axis) * Scaling(s);\endcode</td></tr>
|
||||
<tr><td>
|
||||
N-D Linear transformations \n
|
||||
<em class=note>(pure rotations, \n scaling, etc.)</em></td><td>\code
|
||||
Matrix<float,N> t = concatenation_of_rotations_and_scalings;
|
||||
Matrix<float,2> t = Rotation2Df(a) * Scaling2f(s);
|
||||
Matrix<float,3> t = AngleAxisf(a,axis) * Scaling3f(s);\endcode</td></tr>
|
||||
Matrix<float,2> t = Rotation2Df(a) * Scaling(s);
|
||||
Matrix<float,3> t = AngleAxisf(a,axis) * Scaling(s);\endcode</td></tr>
|
||||
</table>
|
||||
|
||||
<strong>Notes on rotations</strong>\n To transform more than a single vector the preferred
|
||||
@@ -92,8 +92,8 @@ Rotation2Df r; r = Matrix2f(..); // assumes a pure rotation matrix
|
||||
AngleAxisf aa; aa = Quaternionf(..);
|
||||
AngleAxisf aa; aa = Matrix3f(..); // assumes a pure rotation matrix
|
||||
Matrix2f m; m = Rotation2Df(..);
|
||||
Matrix3f m; m = Quaternionf(..); Matrix3f m; m = Scaling3f(..);
|
||||
Affine3f m; m = AngleAxis3f(..); Affine3f m; m = Scaling3f(..);
|
||||
Matrix3f m; m = Quaternionf(..); Matrix3f m; m = Scaling(..);
|
||||
Affine3f m; m = AngleAxis3f(..); Affine3f m; m = Scaling(..);
|
||||
Affine3f m; m = Translation3f(..); Affine3f m; m = Matrix3f(..);
|
||||
\endcode</td></tr>
|
||||
</table>
|
||||
@@ -207,10 +207,10 @@ t.scale(s);
|
||||
t.prescale(Vector_(sx,sy,..));
|
||||
t.prescale(s);
|
||||
\endcode</td><td>\code
|
||||
t *= Scaling_(sx,sy,..);
|
||||
t *= Scaling_(s);
|
||||
t = Scaling_(sx,sy,..) * t;
|
||||
t = Scaling_(s) * t;
|
||||
t *= Scaling(sx,sy,..);
|
||||
t *= Scaling(s);
|
||||
t = Scaling(sx,sy,..) * t;
|
||||
t = Scaling(s) * t;
|
||||
\endcode</td></tr>
|
||||
<tr class="alt"><td>Shear transformation \n ( \b 2D \b only ! )</td><td>\code
|
||||
t.shear(sx,sy);
|
||||
@@ -224,7 +224,7 @@ Note that in both API, any many transformations can be concatenated in a single
|
||||
t.pretranslate(..).rotate(..).translate(..).scale(..);
|
||||
\endcode</td></tr>
|
||||
<tr><td>\code
|
||||
t = Translation_(..) * t * RotationType(..) * Translation_(..) * Scaling_(..);
|
||||
t = Translation_(..) * t * RotationType(..) * Translation_(..) * Scaling(..);
|
||||
\endcode</td></tr>
|
||||
</table>
|
||||
|
||||
|
||||
@@ -4,7 +4,7 @@ namespace Eigen {
|
||||
\ingroup Tutorial
|
||||
|
||||
\li \b Previous: \ref TutorialGeometry
|
||||
\li \b Next: TODO
|
||||
\li \b Next: \ref TutorialMapClass
|
||||
|
||||
\b Table \b of \b contents \n
|
||||
- \ref TutorialSparseIntro
|
||||
@@ -254,7 +254,7 @@ if(!lu_of_A.solve(b,&x)) {
|
||||
|
||||
See also the class SparseLLT, class SparseLU, and class SparseLDLT.
|
||||
|
||||
\li \b Next: TODO
|
||||
\li \b Next: \ref TutorialMapClass
|
||||
|
||||
*/
|
||||
|
||||
|
||||
96
doc/C10_TutorialMapClass.dox
Normal file
96
doc/C10_TutorialMapClass.dox
Normal file
@@ -0,0 +1,96 @@
|
||||
namespace Eigen {
|
||||
|
||||
/** \page TutorialMapClass Tutorial page 10 - Interfacing with C/C++ arrays and external libraries: the %Map class
|
||||
|
||||
\ingroup Tutorial
|
||||
|
||||
\li \b Previous: \ref TutorialSparse
|
||||
\li \b Next: \ref TODO
|
||||
|
||||
This tutorial page explains how to work with "raw" C++ arrays. This can be useful in a variety of contexts, particularly when "importing" vectors and matrices from other libraries into Eigen.
|
||||
|
||||
\b Table \b of \b contents
|
||||
- \ref TutorialMapIntroduction
|
||||
- \ref TutorialMapTypes
|
||||
- \ref TutorialMapUsing
|
||||
- \ref TutorialMapPlacementNew
|
||||
|
||||
\section TutorialMapIntroduction Introduction
|
||||
|
||||
Occasionally you may have a pre-defined array of numbers that you want to use within Eigen as a vector or matrix. While one option is to make a copy of the data, most commonly you probably want to re-use this memory as an Eigen type. Fortunately, this is very easy with the Map class.
|
||||
|
||||
\section TutorialMapTypes Map types and declaring Map variables
|
||||
|
||||
A Map object has a type defined by its Eigen equivalent:
|
||||
\code
|
||||
Map<Matrix<typename Scalar, int RowsAtCompileTime, int ColsAtCompileTime> >
|
||||
\endcode
|
||||
Note that, in this default case, a Map requires just a single template parameter.
|
||||
|
||||
To construct a Map variable, you need two other pieces of information: a pointer to the region of memory defining the array of coefficients, and the desired shape of the matrix or vector. For example, to define a matrix of \c float with sizes determined at compile time, you might do the following:
|
||||
\code
|
||||
Map<MatrixXf> mf(pf,rows,columns);
|
||||
\endcode
|
||||
where \c pf is a \c float \c * pointing to the array of memory. A fixed-size read-only vector of integers might be declared as
|
||||
\code
|
||||
Map<const Vector4i> mi(pi);
|
||||
\endcode
|
||||
where \c pi is an \c int \c *. In this case the size does not have to be passed to the constructor, because it is already specified by the Matrix/Array type.
|
||||
|
||||
Note that Map does not have a default constructor; you \em must pass a pointer to intialize the object. However, you can work around this requirement (see \ref TutorialMapPlacementNew).
|
||||
|
||||
Map is flexible enough to accomodate a variety of different data representations. There are two other (optional) template parameters:
|
||||
\code
|
||||
Map<typename MatrixType,
|
||||
int MapOptions,
|
||||
typename StrideType>
|
||||
\endcode
|
||||
\li \c MapOptions specifies whether the pointer is \c #Aligned, or \c #Unaligned. The default is \c #Unaligned.
|
||||
\li \c StrideType allows you to specify a custom layout for the memory array, using the Stride class. One example would be to specify that the data array is organized in row-major format:
|
||||
<table class="example">
|
||||
<tr><th>Example:</th><th>Output:</th></tr>
|
||||
<tr>
|
||||
<td>\include Tutorial_Map_rowmajor.cpp </td>
|
||||
<td>\verbinclude Tutorial_Map_rowmajor.out </td>
|
||||
</table>
|
||||
However, Stride is even more flexible than this; for details, see the documentation for the Map and Stride classes.
|
||||
|
||||
\section TutorialMapUsing Using Map variables
|
||||
|
||||
You can use a Map object just like any other Eigen type:
|
||||
<table class="example">
|
||||
<tr><th>Example:</th><th>Output:</th></tr>
|
||||
<tr>
|
||||
<td>\include Tutorial_Map_using.cpp </td>
|
||||
<td>\verbinclude Tutorial_Map_using.out </td>
|
||||
</table>
|
||||
|
||||
However, when writing functions taking Eigen types, it is important to realize that a Map type is \em not identical to its Dense equivalent. See \ref TopicFunctionTakingEigenTypesMultiarguments for details.
|
||||
|
||||
\section TutorialMapPlacementNew Changing the mapped array
|
||||
|
||||
It is possible to change the array of a Map object after declaration, using the C++ "placement new" syntax:
|
||||
<table class="example">
|
||||
<tr><th>Example:</th><th>Output:</th></tr>
|
||||
<tr>
|
||||
<td>\include Map_placement_new.cpp </td>
|
||||
<td>\verbinclude Map_placement_new.out </td>
|
||||
</table>
|
||||
Despite appearances, this does not invoke the memory allocator, because the syntax specifies the location for storing the result.
|
||||
|
||||
This syntax makes it possible to declare a Map object without first knowing the mapped array's location in memory:
|
||||
\code
|
||||
Map<Matrix3f> A(NULL); // don't try to use this matrix yet!
|
||||
VectorXf b(n_matrices);
|
||||
for (int i = 0; i < n_matrices; i++)
|
||||
{
|
||||
new (&A) Map<Matrix3f>(get_matrix_pointer(i));
|
||||
b(i) = A.trace();
|
||||
}
|
||||
\endcode
|
||||
|
||||
\li \b Next: \ref TODO
|
||||
|
||||
*/
|
||||
|
||||
}
|
||||
@@ -47,9 +47,9 @@ void print_block(const DenseBase<Derived>& b, int x, int y, int r, int c)
|
||||
Prints the maximum coefficient of the array or array-expression.
|
||||
\code
|
||||
template <typename Derived>
|
||||
void print_max(const ArrayBase<Derived>& a, const ArrayBase<Derived>& b)
|
||||
void print_max_coeff(const ArrayBase<Derived> &a)
|
||||
{
|
||||
std::cout << "max: " << (a.max(b)).maxCoeff() << std::endl;
|
||||
std::cout << "max: " << a.maxCoeff() << std::endl;
|
||||
}
|
||||
\endcode
|
||||
<b> %MatrixBase Example </b><br/><br/>
|
||||
@@ -63,6 +63,21 @@ void print_inv_cond(const MatrixBase<Derived>& a)
|
||||
std::cout << "inv cond: " << sing_vals(sing_vals.size()-1) / sing_vals(0) << std::endl;
|
||||
}
|
||||
\endcode
|
||||
<b> Multiple templated arguments example </b><br/><br/>
|
||||
Calculate the Euclidean distance between two points.
|
||||
\code
|
||||
template <typename DerivedA,typename DerivedB>
|
||||
typename DerivedA::Scalar squaredist(const MatrixBase<DerivedA>& p1,const MatrixBase<DerivedB>& p2)
|
||||
{
|
||||
return (p1-p2).squaredNorm();
|
||||
}
|
||||
\endcode
|
||||
Notice that we used two template parameters, one per argument. This permits the function to handle inputs of different types, e.g.,
|
||||
\code
|
||||
squaredist(v1,2*v2)
|
||||
\endcode
|
||||
where the first argument \c v1 is a vector and the second argument \c 2*v2 is an expression.
|
||||
<br/><br/>
|
||||
|
||||
These examples are just intended to give the reader a first impression of how functions can be written which take a plain and constant Matrix or Array argument. They are also intended to give the reader an idea about the most common base classes being the optimal candidates for functions. In the next section we will look in more detail at an example and the different ways it can be implemented, while discussing each implementation's problems and advantages. For the discussion below, Matrix and Array as well as MatrixBase and ArrayBase can be exchanged and all arguments still hold.
|
||||
|
||||
@@ -128,6 +143,8 @@ The implementation above does now not only work with temporary expressions but i
|
||||
|
||||
\b Note: The const cast hack will only work with templated functions. It will not work with the MatrixXf implementation because it is not possible to cast a Block expression to a Matrix reference!
|
||||
|
||||
|
||||
|
||||
\section TopicResizingInGenericImplementations How to resize matrices in generic implementations?
|
||||
|
||||
One might think we are done now, right? This is not completely true because in order for our covariance function to be generically applicable, we want the follwing code to work
|
||||
|
||||
@@ -27,6 +27,7 @@ For a first contact with Eigen, the best place is to have a look at the \ref Get
|
||||
- \ref TutorialReductionsVisitorsBroadcasting
|
||||
- \ref TutorialGeometry
|
||||
- \ref TutorialSparse
|
||||
- \ref TutorialMapClass
|
||||
- \ref QuickRefPage
|
||||
- <b>Advanced topics</b>
|
||||
- \ref TopicAliasing
|
||||
|
||||
@@ -645,11 +645,11 @@ m3 -= s1 * m3.adjoint() * m1.selfadjointView<Eigen::Lower>();\endcode
|
||||
</td></tr>
|
||||
<tr><td>
|
||||
Rank 1 and rank K update: \n
|
||||
\f$ upper(M_1) \mathrel{{+}{=}} s_1 M_2^* M_2 \f$ \n
|
||||
\f$ lower(M_1) \mathbin{{-}{=}} M_2 M_2^* \f$
|
||||
\f$ upper(M_1) \mathrel{{+}{=}} s_1 M_2 M_2^* \f$ \n
|
||||
\f$ lower(M_1) \mathbin{{-}{=}} M_2^* M_2 \f$
|
||||
</td><td>\n \code
|
||||
M1.selfadjointView<Eigen::Upper>().rankUpdate(M2,s1);
|
||||
m1.selfadjointView<Eigen::Lower>().rankUpdate(m2.adjoint(),-1); \endcode
|
||||
M1.selfadjointView<Eigen::Lower>().rankUpdate(M2.adjoint(),-1); \endcode
|
||||
</td></tr>
|
||||
<tr><td>
|
||||
Rank 2 update: (\f$ M \mathrel{{+}{=}} s u v^* + s v u^* \f$)
|
||||
|
||||
@@ -6,7 +6,6 @@ namespace Eigen {
|
||||
\section TopicLinAlgBigTable Catalogue of decompositions offered by Eigen
|
||||
|
||||
<table class="manual-vl">
|
||||
|
||||
<tr>
|
||||
<th class="meta"></th>
|
||||
<th class="meta" colspan="5">Generic information, not Eigen-specific</th>
|
||||
|
||||
7
doc/snippets/Tutorial_Map_rowmajor.cpp
Normal file
7
doc/snippets/Tutorial_Map_rowmajor.cpp
Normal file
@@ -0,0 +1,7 @@
|
||||
int array[8];
|
||||
for(int i = 0; i < 8; ++i) array[i] = i;
|
||||
cout << "Column-major:\n" << Map<Matrix<int,2,4> >(array) << endl;
|
||||
cout << "Row-major:\n" << Map<Matrix<int,2,4,RowMajor> >(array) << endl;
|
||||
cout << "Row-major using stride:\n" <<
|
||||
Map<Matrix<int,2,4>, Unaligned, Stride<1,4> >(array) << endl;
|
||||
|
||||
21
doc/snippets/Tutorial_Map_using.cpp
Normal file
21
doc/snippets/Tutorial_Map_using.cpp
Normal file
@@ -0,0 +1,21 @@
|
||||
typedef Matrix<float,1,Dynamic> MatrixType;
|
||||
typedef Map<MatrixType> MapType;
|
||||
typedef Map<const MatrixType> MapTypeConst; // a read-only map
|
||||
const int n_dims = 5;
|
||||
|
||||
MatrixType m1(n_dims), m2(n_dims);
|
||||
m1.setRandom();
|
||||
m2.setRandom();
|
||||
float *p = &m2(0); // get the address storing the data for m2
|
||||
MapType m2map(p,m2.size()); // m2map shares data with m2
|
||||
MapTypeConst m2mapconst(p,m2.size()); // a read-only accessor for m2
|
||||
|
||||
cout << "m1: " << m1 << endl;
|
||||
cout << "m2: " << m2 << endl;
|
||||
cout << "Squared euclidean distance: " << (m1-m2).squaredNorm() << endl;
|
||||
cout << "Squared euclidean distance, using map: " <<
|
||||
(m1-m2map).squaredNorm() << endl;
|
||||
m2map(3) = 7; // this will change m2, since they share the same array
|
||||
cout << "Updated m2: " << m2 << endl;
|
||||
cout << "m2 coefficient 2, constant accessor: " << m2mapconst(2) << endl;
|
||||
/* m2mapconst(2) = 5; */ // this yields a compile-time error
|
||||
@@ -8,14 +8,12 @@ USER=${USER:-'orzel'}
|
||||
#ulimit -v 1024000
|
||||
|
||||
# step 1 : build
|
||||
# todo if 'build is not there, create one:
|
||||
mkdir build -p
|
||||
(cd build && cmake .. && make doc) || { echo "make failed"; exit 1; }
|
||||
#todo: n+1 where n = number of cpus
|
||||
|
||||
#step 2 : upload
|
||||
# (the '/' at the end of path are very important, see rsync documentation)
|
||||
rsync -az build/doc/html/ $USER@ssh.tuxfamily.org:eigen/eigen.tuxfamily.org-web/htdocs/dox-3.0/ || { echo "upload failed"; exit 1; }
|
||||
# (the '/' at the end of path is very important, see rsync documentation)
|
||||
rsync -az --no-p --delete build/doc/html/ $USER@ssh.tuxfamily.org:eigen/eigen.tuxfamily.org-web/htdocs/dox-3.0/ || { echo "upload failed"; exit 1; }
|
||||
|
||||
echo "Uploaded successfully"
|
||||
|
||||
|
||||
@@ -124,6 +124,11 @@ template<typename MatrixType> void cholesky(const MatrixType& m)
|
||||
MatrixType neg = -symmLo;
|
||||
chollo.compute(neg);
|
||||
VERIFY(chollo.info()==NumericalIssue);
|
||||
|
||||
VERIFY_IS_APPROX(MatrixType(chollo.matrixL().transpose().conjugate()), MatrixType(chollo.matrixU()));
|
||||
VERIFY_IS_APPROX(MatrixType(chollo.matrixU().transpose().conjugate()), MatrixType(chollo.matrixL()));
|
||||
VERIFY_IS_APPROX(MatrixType(cholup.matrixL().transpose().conjugate()), MatrixType(cholup.matrixU()));
|
||||
VERIFY_IS_APPROX(MatrixType(cholup.matrixU().transpose().conjugate()), MatrixType(cholup.matrixL()));
|
||||
}
|
||||
|
||||
// LDLT
|
||||
@@ -152,6 +157,11 @@ template<typename MatrixType> void cholesky(const MatrixType& m)
|
||||
matX = ldltup.solve(matB);
|
||||
VERIFY_IS_APPROX(symm * matX, matB);
|
||||
|
||||
VERIFY_IS_APPROX(MatrixType(ldltlo.matrixL().transpose().conjugate()), MatrixType(ldltlo.matrixU()));
|
||||
VERIFY_IS_APPROX(MatrixType(ldltlo.matrixU().transpose().conjugate()), MatrixType(ldltlo.matrixL()));
|
||||
VERIFY_IS_APPROX(MatrixType(ldltup.matrixL().transpose().conjugate()), MatrixType(ldltup.matrixU()));
|
||||
VERIFY_IS_APPROX(MatrixType(ldltup.matrixU().transpose().conjugate()), MatrixType(ldltup.matrixL()));
|
||||
|
||||
if(MatrixType::RowsAtCompileTime==Dynamic)
|
||||
{
|
||||
// note : each inplace permutation requires a small temporary vector (mask)
|
||||
|
||||
@@ -28,6 +28,35 @@
|
||||
#include <Eigen/LU>
|
||||
#include <Eigen/SVD>
|
||||
|
||||
template<typename T> T bounded_acos(T v)
|
||||
{
|
||||
using std::acos;
|
||||
using std::min;
|
||||
using std::max;
|
||||
return acos((max)(T(-1),(min)(v,T(1))));
|
||||
}
|
||||
|
||||
template<typename QuatType> void check_slerp(const QuatType& q0, const QuatType& q1)
|
||||
{
|
||||
typedef typename QuatType::Scalar Scalar;
|
||||
typedef Matrix<Scalar,3,1> VectorType;
|
||||
typedef AngleAxis<Scalar> AA;
|
||||
|
||||
Scalar largeEps = test_precision<Scalar>();
|
||||
|
||||
Scalar theta_tot = AA(q1*q0.inverse()).angle();
|
||||
if(theta_tot>M_PI)
|
||||
theta_tot = 2.*M_PI-theta_tot;
|
||||
for(Scalar t=0; t<=1.001; t+=0.1)
|
||||
{
|
||||
QuatType q = q0.slerp(t,q1);
|
||||
Scalar theta = AA(q*q0.inverse()).angle();
|
||||
VERIFY(internal::abs(q.norm() - 1) < largeEps);
|
||||
if(theta_tot==0) VERIFY(theta_tot==0);
|
||||
else VERIFY(internal::abs(theta/theta_tot - t) < largeEps);
|
||||
}
|
||||
}
|
||||
|
||||
template<typename Scalar, int Options> void quaternion(void)
|
||||
{
|
||||
/* this test covers the following files:
|
||||
@@ -36,6 +65,7 @@ template<typename Scalar, int Options> void quaternion(void)
|
||||
|
||||
typedef Matrix<Scalar,3,3> Matrix3;
|
||||
typedef Matrix<Scalar,3,1> Vector3;
|
||||
typedef Matrix<Scalar,4,1> Vector4;
|
||||
typedef Quaternion<Scalar,Options> Quaternionx;
|
||||
typedef AngleAxis<Scalar> AngleAxisx;
|
||||
|
||||
@@ -50,7 +80,8 @@ template<typename Scalar, int Options> void quaternion(void)
|
||||
v2 = Vector3::Random(),
|
||||
v3 = Vector3::Random();
|
||||
|
||||
Scalar a = internal::random<Scalar>(-Scalar(M_PI), Scalar(M_PI));
|
||||
Scalar a = internal::random<Scalar>(-Scalar(M_PI), Scalar(M_PI)),
|
||||
b = internal::random<Scalar>(-Scalar(M_PI), Scalar(M_PI));
|
||||
|
||||
// Quaternion: Identity(), setIdentity();
|
||||
Quaternionx q1, q2;
|
||||
@@ -124,27 +155,56 @@ template<typename Scalar, int Options> void quaternion(void)
|
||||
// test bug 369 - improper alignment.
|
||||
Quaternionx *q = new Quaternionx;
|
||||
delete q;
|
||||
|
||||
q1 = AngleAxisx(a, v0.normalized());
|
||||
q2 = AngleAxisx(b, v1.normalized());
|
||||
check_slerp(q1,q2);
|
||||
|
||||
q1 = AngleAxisx(b, v1.normalized());
|
||||
q2 = AngleAxisx(b+M_PI, v1.normalized());
|
||||
check_slerp(q1,q2);
|
||||
|
||||
q1 = AngleAxisx(b, v1.normalized());
|
||||
q2 = AngleAxisx(-b, -v1.normalized());
|
||||
check_slerp(q1,q2);
|
||||
|
||||
q1.coeffs() = Vector4::Random().normalized();
|
||||
q2.coeffs() = -q1.coeffs();
|
||||
check_slerp(q1,q2);
|
||||
}
|
||||
|
||||
template<typename Scalar> void mapQuaternion(void){
|
||||
typedef Map<Quaternion<Scalar>, Aligned> MQuaternionA;
|
||||
typedef Map<const Quaternion<Scalar>, Aligned> MCQuaternionA;
|
||||
typedef Map<Quaternion<Scalar> > MQuaternionUA;
|
||||
typedef Map<const Quaternion<Scalar> > MCQuaternionUA;
|
||||
typedef Quaternion<Scalar> Quaternionx;
|
||||
typedef Matrix<Scalar,3,1> Vector3;
|
||||
typedef AngleAxis<Scalar> AngleAxisx;
|
||||
|
||||
Vector3 v0 = Vector3::Random(),
|
||||
v1 = Vector3::Random();
|
||||
Scalar a = internal::random<Scalar>(-Scalar(M_PI), Scalar(M_PI));
|
||||
|
||||
EIGEN_ALIGN16 Scalar array1[4];
|
||||
EIGEN_ALIGN16 Scalar array2[4];
|
||||
EIGEN_ALIGN16 Scalar array3[4+1];
|
||||
Scalar* array3unaligned = array3+1;
|
||||
|
||||
MQuaternionA mq1(array1);
|
||||
MCQuaternionA mcq1(array1);
|
||||
MQuaternionA mq2(array2);
|
||||
MQuaternionUA mq3(array3unaligned);
|
||||
MCQuaternionUA mcq3(array3unaligned);
|
||||
|
||||
// std::cerr << array1 << " " << array2 << " " << array3 << "\n";
|
||||
MQuaternionA(array1).coeffs().setRandom();
|
||||
(MQuaternionA(array2)) = MQuaternionA(array1);
|
||||
(MQuaternionUA(array3unaligned)) = MQuaternionA(array1);
|
||||
mq1 = AngleAxisx(a, v0.normalized());
|
||||
mq2 = mq1;
|
||||
mq3 = mq1;
|
||||
|
||||
Quaternionx q1 = MQuaternionA(array1);
|
||||
Quaternionx q2 = MQuaternionA(array2);
|
||||
Quaternionx q3 = MQuaternionUA(array3unaligned);
|
||||
Quaternionx q1 = mq1;
|
||||
Quaternionx q2 = mq2;
|
||||
Quaternionx q3 = mq3;
|
||||
Quaternionx q4 = MCQuaternionUA(array3unaligned);
|
||||
|
||||
VERIFY_IS_APPROX(q1.coeffs(), q2.coeffs());
|
||||
@@ -154,6 +214,23 @@ template<typename Scalar> void mapQuaternion(void){
|
||||
if(internal::packet_traits<Scalar>::Vectorizable)
|
||||
VERIFY_RAISES_ASSERT((MQuaternionA(array3unaligned)));
|
||||
#endif
|
||||
|
||||
VERIFY_IS_APPROX(mq1 * (mq1.inverse() * v1), v1);
|
||||
VERIFY_IS_APPROX(mq1 * (mq1.conjugate() * v1), v1);
|
||||
|
||||
VERIFY_IS_APPROX(mcq1 * (mcq1.inverse() * v1), v1);
|
||||
VERIFY_IS_APPROX(mcq1 * (mcq1.conjugate() * v1), v1);
|
||||
|
||||
VERIFY_IS_APPROX(mq3 * (mq3.inverse() * v1), v1);
|
||||
VERIFY_IS_APPROX(mq3 * (mq3.conjugate() * v1), v1);
|
||||
|
||||
VERIFY_IS_APPROX(mcq3 * (mcq3.inverse() * v1), v1);
|
||||
VERIFY_IS_APPROX(mcq3 * (mcq3.conjugate() * v1), v1);
|
||||
|
||||
VERIFY_IS_APPROX(mq1*mq2, q1*q2);
|
||||
VERIFY_IS_APPROX(mq3*mq2, q3*q2);
|
||||
VERIFY_IS_APPROX(mcq1*mq2, q1*q2);
|
||||
VERIFY_IS_APPROX(mcq3*mq2, q3*q2);
|
||||
}
|
||||
|
||||
template<typename Scalar> void quaternionAlignment(void){
|
||||
|
||||
@@ -448,6 +448,29 @@ template<typename Scalar> void transform_alignment()
|
||||
#endif
|
||||
}
|
||||
|
||||
template<typename Scalar, int Dim, int Options> void transform_products()
|
||||
{
|
||||
typedef Matrix<Scalar,Dim+1,Dim+1> Mat;
|
||||
typedef Transform<Scalar,Dim,Projective,Options> Proj;
|
||||
typedef Transform<Scalar,Dim,Affine,Options> Aff;
|
||||
typedef Transform<Scalar,Dim,AffineCompact,Options> AffC;
|
||||
|
||||
Proj p; p.matrix().setRandom();
|
||||
Aff a; a.linear().setRandom(); a.translation().setRandom();
|
||||
AffC ac = a;
|
||||
|
||||
Mat p_m(p.matrix()), a_m(a.matrix());
|
||||
|
||||
VERIFY_IS_APPROX((p*p).matrix(), p_m*p_m);
|
||||
VERIFY_IS_APPROX((a*a).matrix(), a_m*a_m);
|
||||
VERIFY_IS_APPROX((p*a).matrix(), p_m*a_m);
|
||||
VERIFY_IS_APPROX((a*p).matrix(), a_m*p_m);
|
||||
VERIFY_IS_APPROX((ac*a).matrix(), a_m*a_m);
|
||||
VERIFY_IS_APPROX((a*ac).matrix(), a_m*a_m);
|
||||
VERIFY_IS_APPROX((p*ac).matrix(), p_m*a_m);
|
||||
VERIFY_IS_APPROX((ac*p).matrix(), a_m*p_m);
|
||||
}
|
||||
|
||||
void test_geo_transformations()
|
||||
{
|
||||
for(int i = 0; i < g_repeat; i++) {
|
||||
@@ -470,5 +493,9 @@ void test_geo_transformations()
|
||||
|
||||
CALL_SUBTEST_6(( transformations<double,Projective,RowMajor|AutoAlign>() ));
|
||||
CALL_SUBTEST_6(( transformations<double,Projective,RowMajor|DontAlign>() ));
|
||||
|
||||
|
||||
CALL_SUBTEST_7(( transform_products<double,3,RowMajor|AutoAlign>() ));
|
||||
CALL_SUBTEST_7(( transform_products<float,2,AutoAlign>() ));
|
||||
}
|
||||
}
|
||||
|
||||
@@ -25,6 +25,25 @@
|
||||
#define EIGEN_NO_STATIC_ASSERT
|
||||
#include "product.h"
|
||||
|
||||
// regression test for bug 447
|
||||
void product1x1()
|
||||
{
|
||||
Matrix<float,1,3> matAstatic;
|
||||
Matrix<float,3,1> matBstatic;
|
||||
matAstatic.setRandom();
|
||||
matBstatic.setRandom();
|
||||
VERIFY_IS_APPROX( (matAstatic * matBstatic).coeff(0,0),
|
||||
matAstatic.cwiseProduct(matBstatic.transpose()).sum() );
|
||||
|
||||
MatrixXf matAdynamic(1,3);
|
||||
MatrixXf matBdynamic(3,1);
|
||||
matAdynamic.setRandom();
|
||||
matBdynamic.setRandom();
|
||||
VERIFY_IS_APPROX( (matAdynamic * matBdynamic).coeff(0,0),
|
||||
matAdynamic.cwiseProduct(matBdynamic.transpose()).sum() );
|
||||
}
|
||||
|
||||
|
||||
void test_product_small()
|
||||
{
|
||||
for(int i = 0; i < g_repeat; i++) {
|
||||
@@ -33,6 +52,7 @@ void test_product_small()
|
||||
CALL_SUBTEST_3( product(Matrix3d()) );
|
||||
CALL_SUBTEST_4( product(Matrix4d()) );
|
||||
CALL_SUBTEST_5( product(Matrix4f()) );
|
||||
CALL_SUBTEST_6( product1x1() );
|
||||
}
|
||||
|
||||
#ifdef EIGEN_TEST_PART_6
|
||||
|
||||
@@ -69,7 +69,7 @@ struct get_boxes_helper<ObjectList, VolumeList, int> {
|
||||
*
|
||||
* \param _Scalar The underlying scalar type of the bounding boxes
|
||||
* \param _Dim The dimension of the space in which the hierarchy lives
|
||||
* \param _Object The object type that lives in the hierarchy. It must have value semantics. Either internal::bounding_box(_Object) must
|
||||
* \param _Object The object type that lives in the hierarchy. It must have value semantics. Either bounding_box(_Object) must
|
||||
* be defined and return an AlignedBox<_Scalar, _Dim> or bounding boxes must be provided to the tree initializer.
|
||||
*
|
||||
* This class provides a simple (as opposed to optimized) implementation of a bounding volume hierarchy analogous to a Kd-tree.
|
||||
@@ -92,14 +92,14 @@ public:
|
||||
|
||||
KdBVH() {}
|
||||
|
||||
/** Given an iterator range over \a Object references, constructs the BVH. Requires that internal::bounding_box(Object) return a Volume. */
|
||||
/** Given an iterator range over \a Object references, constructs the BVH. Requires that bounding_box(Object) return a Volume. */
|
||||
template<typename Iter> KdBVH(Iter begin, Iter end) { init(begin, end, 0, 0); } //int is recognized by init as not being an iterator type
|
||||
|
||||
/** Given an iterator range over \a Object references and an iterator range over their bounding boxes, constructs the BVH */
|
||||
template<typename OIter, typename BIter> KdBVH(OIter begin, OIter end, BIter boxBegin, BIter boxEnd) { init(begin, end, boxBegin, boxEnd); }
|
||||
|
||||
/** Given an iterator range over \a Object references, constructs the BVH, overwriting whatever is in there currently.
|
||||
* Requires that internal::bounding_box(Object) return a Volume. */
|
||||
* Requires that bounding_box(Object) return a Volume. */
|
||||
template<typename Iter> void init(Iter begin, Iter end) { init(begin, end, 0, 0); }
|
||||
|
||||
/** Given an iterator range over \a Object references and an iterator range over their bounding boxes,
|
||||
|
||||
@@ -640,7 +640,7 @@ LevenbergMarquardt<FunctorType,Scalar>::lmdif1(
|
||||
|
||||
NumericalDiff<FunctorType> numDiff(functor);
|
||||
// embedded LevenbergMarquardt
|
||||
LevenbergMarquardt<NumericalDiff<FunctorType> > lm(numDiff);
|
||||
LevenbergMarquardt<NumericalDiff<FunctorType>, Scalar > lm(numDiff);
|
||||
lm.parameters.ftol = tol;
|
||||
lm.parameters.xtol = tol;
|
||||
lm.parameters.maxfev = 200*(n+1);
|
||||
|
||||
@@ -64,7 +64,7 @@ public:
|
||||
template<typename T0, typename T1>
|
||||
NumericalDiff(const T0& a0, const T1& a1) : Functor(a0, a1), epsfcn(0) {}
|
||||
template<typename T0, typename T1, typename T2>
|
||||
NumericalDiff(const T0& a0, const T1& a1, const T1& a2) : Functor(a0, a1, a2), epsfcn(0) {}
|
||||
NumericalDiff(const T0& a0, const T1& a1, const T2& a2) : Functor(a0, a1, a2), epsfcn(0) {}
|
||||
|
||||
enum {
|
||||
InputsAtCompileTime = Functor::InputsAtCompileTime,
|
||||
|
||||
@@ -104,7 +104,7 @@ class SparseLU
|
||||
void setOrderingMethod(int m)
|
||||
{
|
||||
eigen_assert( (m&~OrderingMask) == 0 && m!=0 && "invalid ordering method");
|
||||
m_flags = m_flags&~OrderingMask | m&OrderingMask;
|
||||
m_flags = (m_flags & ~OrderingMask) | (m & OrderingMask);
|
||||
}
|
||||
|
||||
int orderingMethod() const
|
||||
|
||||
@@ -24,9 +24,15 @@
|
||||
|
||||
#include "main.h"
|
||||
#include <Eigen/StdVector>
|
||||
#include <Eigen/Geometry>
|
||||
#include <unsupported/Eigen/BVH>
|
||||
|
||||
inline double SQR(double x) { return x * x; }
|
||||
namespace Eigen {
|
||||
|
||||
template<typename Scalar, int Dim> AlignedBox<Scalar, Dim> bounding_box(const Matrix<Scalar, Dim, 1> &v) { return AlignedBox<Scalar, Dim>(v); }
|
||||
|
||||
}
|
||||
|
||||
|
||||
template<int Dim>
|
||||
struct Ball
|
||||
@@ -41,16 +47,10 @@ EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF_VECTORIZABLE_FIXED_SIZE(double, Dim)
|
||||
VectorType center;
|
||||
double radius;
|
||||
};
|
||||
|
||||
namespace Eigen {
|
||||
namespace internal {
|
||||
|
||||
template<typename Scalar, int Dim> AlignedBox<Scalar, Dim> bounding_box(const Matrix<Scalar, Dim, 1> &v) { return AlignedBox<Scalar, Dim>(v); }
|
||||
template<int Dim> AlignedBox<double, Dim> bounding_box(const Ball<Dim> &b)
|
||||
{ return AlignedBox<double, Dim>(b.center.array() - b.radius, b.center.array() + b.radius); }
|
||||
|
||||
} // end namespace internal
|
||||
}
|
||||
inline double SQR(double x) { return x * x; }
|
||||
|
||||
template<int Dim>
|
||||
struct BallPointStuff //this class provides functions to be both an intersector and a minimizer, both for a ball and a point and for two trees
|
||||
|
||||
Reference in New Issue
Block a user