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merge with default branch

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This commit is contained in:
Gael Guennebaud
2014-07-10 22:04:45 +02:00
parent 61b88d2feb d1460d9278
commit 296cb40161
49 changed files with 263 additions and 167 deletions
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37
Eigen/src/Cholesky/LDLT.h
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@@ -276,23 +276,13 @@ template<> struct ldlt_inplace<Lower>
return true;
}
RealScalar cutoff(0), biggest_in_corner;
for (Index k = 0; k < size; ++k)
{
// Find largest diagonal element
Index index_of_biggest_in_corner;
biggest_in_corner = mat.diagonal().tail(size-k).cwiseAbs().maxCoeff(&index_of_biggest_in_corner);
mat.diagonal().tail(size-k).cwiseAbs().maxCoeff(&index_of_biggest_in_corner);
index_of_biggest_in_corner += k;
if(k == 0)
{
// The biggest overall is the point of reference to which further diagonals
// are compared; if any diagonal is negligible compared
// to the largest overall, the algorithm bails.
cutoff = abs(NumTraits<Scalar>::epsilon() * biggest_in_corner);
}
transpositions.coeffRef(k) = index_of_biggest_in_corner;
if(k != index_of_biggest_in_corner)
{
@@ -323,16 +313,20 @@ template<> struct ldlt_inplace<Lower>
if(k>0)
{
temp.head(k) = mat.diagonal().head(k).asDiagonal() * A10.adjoint();
temp.head(k) = mat.diagonal().real().head(k).asDiagonal() * A10.adjoint();
mat.coeffRef(k,k) -= (A10 * temp.head(k)).value();
if(rs>0)
A21.noalias() -= A20 * temp.head(k);
}
if((rs>0) && (abs(mat.coeffRef(k,k)) > cutoff))
A21 /= mat.coeffRef(k,k);
// In some previous versions of Eigen (e.g., 3.2.1), the scaling was omitted if the pivot
// was smaller than the cutoff value. However, soince LDLT is not rank-revealing
// we should only make sure we do not introduce INF or NaN values.
// LAPACK also uses 0 as the cutoff value.
RealScalar realAkk = numext::real(mat.coeffRef(k,k));
if((rs>0) && (abs(realAkk) > RealScalar(0)))
A21 /= realAkk;
if (sign == PositiveSemiDef) {
if (realAkk < 0) sign = Indefinite;
} else if (sign == NegativeSemiDef) {
@@ -504,9 +498,14 @@ void LDLT<_MatrixType,_UpLo>::_solve_impl(const RhsType &rhs, DstType &dst) cons
// more precisely, use pseudo-inverse of D (see bug 241)
using std::abs;
EIGEN_USING_STD_MATH(max);
const Diagonal<const MatrixType> vecD = vectorD();
RealScalar tolerance = (max)( vecD.array().abs().maxCoeff() * NumTraits<Scalar>::epsilon(),
RealScalar(1) / NumTraits<RealScalar>::highest()); // motivated by LAPACK's xGELSS
const typename Diagonal<const MatrixType>::RealReturnType vecD(vectorD());
// In some previous versions, tolerance was set to the max of 1/highest and the maximal diagonal entry * epsilon
// as motivated by LAPACK's xGELSS:
// RealScalar tolerance = (max)(vectorD.array().abs().maxCoeff() *NumTraits<RealScalar>::epsilon(),RealScalar(1) / NumTraits<RealScalar>::highest());
// However, LDLT is not rank revealing, and so adjusting the tolerance wrt to the highest
// diagonal element is not well justified and to numerical issues in some cases.
// Moreover, Lapack's xSYTRS routines use 0 for the tolerance.
RealScalar tolerance = RealScalar(1) / NumTraits<RealScalar>::highest();
for (Index i = 0; i < vecD.size(); ++i)
{
@@ -582,7 +581,7 @@ MatrixType LDLT<MatrixType,_UpLo>::reconstructedMatrix() const
// L^* P
res = matrixU() * res;
// D(L^*P)
res = vectorD().asDiagonal() * res;
res = vectorD().real().asDiagonal() * res;
// L(DL^*P)
res = matrixL() * res;
// P^T (LDL^*P)

4
Eigen/src/Core/GeneralProduct.h
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@@ -489,7 +489,7 @@ template<> struct gemv_selector<OnTheRight,ColMajor,true>
if(!evalToDest)
{
#ifdef EIGEN_DENSE_STORAGE_CTOR_PLUGIN
int size = dest.size();
Index size = dest.size();
EIGEN_DENSE_STORAGE_CTOR_PLUGIN
#endif
if(!alphaIsCompatible)
@@ -554,7 +554,7 @@ template<> struct gemv_selector<OnTheRight,RowMajor,true>
if(!DirectlyUseRhs)
{
#ifdef EIGEN_DENSE_STORAGE_CTOR_PLUGIN
int size = actualRhs.size();
Index size = actualRhs.size();
EIGEN_DENSE_STORAGE_CTOR_PLUGIN
#endif
Map<typename _ActualRhsType::PlainObject>(actualRhsPtr, actualRhs.size()) = actualRhs;

4
Eigen/src/Core/GenericPacketMath.h Executable file → Normal file
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@@ -233,10 +233,10 @@ template<typename Scalar, typename Packet> EIGEN_DEVICE_FUNC inline void pstore(
template<typename Scalar, typename Packet> EIGEN_DEVICE_FUNC inline void pstoreu(Scalar* to, const Packet& from)
{ (*to) = from; }
template<typename Scalar, typename Packet> EIGEN_DEVICE_FUNC inline Packet pgather(const Scalar* from, int /*stride*/)
template<typename Scalar, typename Packet> EIGEN_DEVICE_FUNC inline Packet pgather(const Scalar* from, DenseIndex /*stride*/)
{ return ploadu<Packet>(from); }
template<typename Scalar, typename Packet> EIGEN_DEVICE_FUNC inline void pscatter(Scalar* to, const Packet& from, int /*stride*/)
template<typename Scalar, typename Packet> EIGEN_DEVICE_FUNC inline void pscatter(Scalar* to, const Packet& from, DenseIndex /*stride*/)
{ pstore(to, from); }
/** \internal tries to do cache prefetching of \a addr */

4
Eigen/src/Core/PlainObjectBase.h
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@@ -713,7 +713,7 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
template<typename T>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE void _init1(Index size, typename internal::enable_if<Base::SizeAtCompileTime!=1,T>::type* = 0)
EIGEN_STRONG_INLINE void _init1(Index size, typename internal::enable_if<Base::SizeAtCompileTime!=1 || !internal::is_convertible<T, Scalar>::value,T>::type* = 0)
{
EIGEN_STATIC_ASSERT(bool(NumTraits<T>::IsInteger),
FLOATING_POINT_ARGUMENT_PASSED__INTEGER_WAS_EXPECTED)
@@ -721,7 +721,7 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
}
template<typename T>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE void _init1(const Scalar& val0, typename internal::enable_if<Base::SizeAtCompileTime==1,T>::type* = 0)
EIGEN_STRONG_INLINE void _init1(const Scalar& val0, typename internal::enable_if<Base::SizeAtCompileTime==1 && internal::is_convertible<T, Scalar>::value,T>::type* = 0)
{
EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(PlainObjectBase, 1)
m_storage.data()[0] = val0;

8
Eigen/src/Core/TriangularMatrix.h
View File

@@ -384,22 +384,22 @@ template<typename _MatrixType, unsigned int _Mode> class TriangularView
/** Efficient triangular matrix times vector/matrix product */
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
TriangularProduct<Mode,true,MatrixType,false,OtherDerived, OtherDerived::IsVectorAtCompileTime>
TriangularProduct<Mode, true, MatrixType, false, OtherDerived, OtherDerived::ColsAtCompileTime==1>
operator*(const MatrixBase<OtherDerived>& rhs) const
{
return TriangularProduct
<Mode,true,MatrixType,false,OtherDerived,OtherDerived::IsVectorAtCompileTime>
<Mode, true, MatrixType, false, OtherDerived, OtherDerived::ColsAtCompileTime==1>
(m_matrix, rhs.derived());
}
/** Efficient vector/matrix times triangular matrix product */
template<typename OtherDerived> friend
EIGEN_DEVICE_FUNC
TriangularProduct<Mode,false,OtherDerived,OtherDerived::IsVectorAtCompileTime,MatrixType,false>
TriangularProduct<Mode, false, OtherDerived, OtherDerived::RowsAtCompileTime==1, MatrixType, false>
operator*(const MatrixBase<OtherDerived>& lhs, const TriangularView& rhs)
{
return TriangularProduct
<Mode,false,OtherDerived,OtherDerived::IsVectorAtCompileTime,MatrixType,false>
<Mode, false, OtherDerived, OtherDerived::RowsAtCompileTime==1, MatrixType, false>
(lhs.derived(),rhs.m_matrix);
}
#endif

2
Eigen/src/Core/Visitor.h
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@@ -237,7 +237,7 @@ DenseBase<Derived>::minCoeff(IndexType* index) const
EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
internal::min_coeff_visitor<Derived> minVisitor;
this->visit(minVisitor);
*index = (RowsAtCompileTime==1) ? minVisitor.col : minVisitor.row;
*index = IndexType((RowsAtCompileTime==1) ? minVisitor.col : minVisitor.row);
return minVisitor.res;
}

8
Eigen/src/Core/arch/AVX/Complex.h
View File

@@ -92,7 +92,7 @@ template<> EIGEN_STRONG_INLINE Packet4cf ploaddup<Packet4cf>(const std::complex<
template<> EIGEN_STRONG_INLINE void pstore <std::complex<float> >(std::complex<float>* to, const Packet4cf& from) { EIGEN_DEBUG_ALIGNED_STORE pstore(&numext::real_ref(*to), from.v); }
template<> EIGEN_STRONG_INLINE void pstoreu<std::complex<float> >(std::complex<float>* to, const Packet4cf& from) { EIGEN_DEBUG_UNALIGNED_STORE pstoreu(&numext::real_ref(*to), from.v); }
template<> EIGEN_DEVICE_FUNC inline Packet4cf pgather<std::complex<float>, Packet4cf>(const std::complex<float>* from, int stride)
template<> EIGEN_DEVICE_FUNC inline Packet4cf pgather<std::complex<float>, Packet4cf>(const std::complex<float>* from, DenseIndex stride)
{
return Packet4cf(_mm256_set_ps(std::imag(from[3*stride]), std::real(from[3*stride]),
std::imag(from[2*stride]), std::real(from[2*stride]),
@@ -100,7 +100,7 @@ template<> EIGEN_DEVICE_FUNC inline Packet4cf pgather<std::complex<float>, Packe
std::imag(from[0*stride]), std::real(from[0*stride])));
}
template<> EIGEN_DEVICE_FUNC inline void pscatter<std::complex<float>, Packet4cf>(std::complex<float>* to, const Packet4cf& from, int stride)
template<> EIGEN_DEVICE_FUNC inline void pscatter<std::complex<float>, Packet4cf>(std::complex<float>* to, const Packet4cf& from, DenseIndex stride)
{
__m128 low = _mm256_extractf128_ps(from.v, 0);
to[stride*0] = std::complex<float>(_mm_cvtss_f32(_mm_shuffle_ps(low, low, 0)),
@@ -310,13 +310,13 @@ template<> EIGEN_STRONG_INLINE Packet2cd ploaddup<Packet2cd>(const std::complex<
template<> EIGEN_STRONG_INLINE void pstore <std::complex<double> >(std::complex<double> * to, const Packet2cd& from) { EIGEN_DEBUG_ALIGNED_STORE pstore((double*)to, from.v); }
template<> EIGEN_STRONG_INLINE void pstoreu<std::complex<double> >(std::complex<double> * to, const Packet2cd& from) { EIGEN_DEBUG_UNALIGNED_STORE pstoreu((double*)to, from.v); }
template<> EIGEN_DEVICE_FUNC inline Packet2cd pgather<std::complex<double>, Packet2cd>(const std::complex<double>* from, int stride)
template<> EIGEN_DEVICE_FUNC inline Packet2cd pgather<std::complex<double>, Packet2cd>(const std::complex<double>* from, DenseIndex stride)
{
return Packet2cd(_mm256_set_pd(std::imag(from[1*stride]), std::real(from[1*stride]),
std::imag(from[0*stride]), std::real(from[0*stride])));
}
template<> EIGEN_DEVICE_FUNC inline void pscatter<std::complex<double>, Packet2cd>(std::complex<double>* to, const Packet2cd& from, int stride)
template<> EIGEN_DEVICE_FUNC inline void pscatter<std::complex<double>, Packet2cd>(std::complex<double>* to, const Packet2cd& from, DenseIndex stride)
{
__m128d low = _mm256_extractf128_pd(from.v, 0);
to[stride*0] = std::complex<double>(_mm_cvtsd_f64(low), _mm_cvtsd_f64(_mm_shuffle_pd(low, low, 1)));

8
Eigen/src/Core/arch/AVX/PacketMath.h
View File

@@ -224,17 +224,17 @@ template<> EIGEN_STRONG_INLINE void pstoreu<int>(int* to, const Packet8i&
// NOTE: leverage _mm256_i32gather_ps and _mm256_i32gather_pd if AVX2 instructions are available
// NOTE: for the record the following seems to be slower: return _mm256_i32gather_ps(from, _mm256_set1_epi32(stride), 4);
template<> EIGEN_DEVICE_FUNC inline Packet8f pgather<float, Packet8f>(const float* from, int stride)
template<> EIGEN_DEVICE_FUNC inline Packet8f pgather<float, Packet8f>(const float* from, DenseIndex stride)
{
return _mm256_set_ps(from[7*stride], from[6*stride], from[5*stride], from[4*stride],
from[3*stride], from[2*stride], from[1*stride], from[0*stride]);
}
template<> EIGEN_DEVICE_FUNC inline Packet4d pgather<double, Packet4d>(const double* from, int stride)
template<> EIGEN_DEVICE_FUNC inline Packet4d pgather<double, Packet4d>(const double* from, DenseIndex stride)
{
return _mm256_set_pd(from[3*stride], from[2*stride], from[1*stride], from[0*stride]);
}
template<> EIGEN_DEVICE_FUNC inline void pscatter<float, Packet8f>(float* to, const Packet8f& from, int stride)
template<> EIGEN_DEVICE_FUNC inline void pscatter<float, Packet8f>(float* to, const Packet8f& from, DenseIndex stride)
{
__m128 low = _mm256_extractf128_ps(from, 0);
to[stride*0] = _mm_cvtss_f32(low);
@@ -248,7 +248,7 @@ template<> EIGEN_DEVICE_FUNC inline void pscatter<float, Packet8f>(float* to, co
to[stride*6] = _mm_cvtss_f32(_mm_shuffle_ps(high, high, 2));
to[stride*7] = _mm_cvtss_f32(_mm_shuffle_ps(high, high, 3));
}
template<> EIGEN_DEVICE_FUNC inline void pscatter<double, Packet4d>(double* to, const Packet4d& from, int stride)
template<> EIGEN_DEVICE_FUNC inline void pscatter<double, Packet4d>(double* to, const Packet4d& from, DenseIndex stride)
{
__m128d low = _mm256_extractf128_pd(from, 0);
to[stride*0] = _mm_cvtsd_f64(low);

4
Eigen/src/Core/arch/AltiVec/Complex.h
View File

@@ -68,14 +68,14 @@ template<> EIGEN_STRONG_INLINE Packet2cf pset1<Packet2cf>(const std::complex<flo
return res;
}
template<> EIGEN_DEVICE_FUNC inline Packet2cf pgather<std::complex<float>, Packet2cf>(const std::complex<float>* from, int stride)
template<> EIGEN_DEVICE_FUNC inline Packet2cf pgather<std::complex<float>, Packet2cf>(const std::complex<float>* from, DenseIndex stride)
{
std::complex<float> EIGEN_ALIGN16 af[2];
af[0] = from[0*stride];
af[1] = from[1*stride];
return Packet2cf(vec_ld(0, (const float*)af));
}
template<> EIGEN_DEVICE_FUNC inline void pscatter<std::complex<float>, Packet2cf>(std::complex<float>* to, const Packet2cf& from, int stride)
template<> EIGEN_DEVICE_FUNC inline void pscatter<std::complex<float>, Packet2cf>(std::complex<float>* to, const Packet2cf& from, DenseIndex stride)
{
std::complex<float> EIGEN_ALIGN16 af[2];
vec_st(from.v, 0, (float*)af);

8
Eigen/src/Core/arch/AltiVec/PacketMath.h
View File

@@ -190,7 +190,7 @@ pbroadcast4<Packet4i>(const int *a,
a3 = vec_splat(a3, 3);
}
template<> EIGEN_DEVICE_FUNC inline Packet4f pgather<float, Packet4f>(const float* from, int stride)
template<> EIGEN_DEVICE_FUNC inline Packet4f pgather<float, Packet4f>(const float* from, DenseIndex stride)
{
float EIGEN_ALIGN16 af[4];
af[0] = from[0*stride];
@@ -199,7 +199,7 @@ template<> EIGEN_DEVICE_FUNC inline Packet4f pgather<float, Packet4f>(const floa
af[3] = from[3*stride];
return vec_ld(0, af);
}
template<> EIGEN_DEVICE_FUNC inline Packet4i pgather<int, Packet4i>(const int* from, int stride)
template<> EIGEN_DEVICE_FUNC inline Packet4i pgather<int, Packet4i>(const int* from, DenseIndex stride)
{
int EIGEN_ALIGN16 ai[4];
ai[0] = from[0*stride];
@@ -208,7 +208,7 @@ template<> EIGEN_DEVICE_FUNC inline Packet4i pgather<int, Packet4i>(const int* f
ai[3] = from[3*stride];
return vec_ld(0, ai);
}
template<> EIGEN_DEVICE_FUNC inline void pscatter<float, Packet4f>(float* to, const Packet4f& from, int stride)
template<> EIGEN_DEVICE_FUNC inline void pscatter<float, Packet4f>(float* to, const Packet4f& from, DenseIndex stride)
{
float EIGEN_ALIGN16 af[4];
vec_st(from, 0, af);
@@ -217,7 +217,7 @@ template<> EIGEN_DEVICE_FUNC inline void pscatter<float, Packet4f>(float* to, co
to[2*stride] = af[2];
to[3*stride] = af[3];
}
template<> EIGEN_DEVICE_FUNC inline void pscatter<int, Packet4i>(int* to, const Packet4i& from, int stride)
template<> EIGEN_DEVICE_FUNC inline void pscatter<int, Packet4i>(int* to, const Packet4i& from, DenseIndex stride)
{
int EIGEN_ALIGN16 ai[4];
vec_st(from, 0, ai);

4
Eigen/src/Core/arch/NEON/Complex.h
View File

@@ -111,7 +111,7 @@ 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_DEVICE_FUNC inline Packet2cf pgather<std::complex<float>, Packet2cf>(const std::complex<float>* from, int stride)
template<> EIGEN_DEVICE_FUNC inline Packet2cf pgather<std::complex<float>, Packet2cf>(const std::complex<float>* from, DenseIndex stride)
{
Packet4f res;
res = vsetq_lane_f32(std::real(from[0*stride]), res, 0);
@@ -121,7 +121,7 @@ template<> EIGEN_DEVICE_FUNC inline Packet2cf pgather<std::complex<float>, Packe
return Packet2cf(res);
}
template<> EIGEN_DEVICE_FUNC inline void pscatter<std::complex<float>, Packet2cf>(std::complex<float>* to, const Packet2cf& from, int stride)
template<> EIGEN_DEVICE_FUNC inline void pscatter<std::complex<float>, Packet2cf>(std::complex<float>* to, const Packet2cf& from, DenseIndex stride)
{
to[stride*0] = std::complex<float>(vgetq_lane_f32(from.v, 0), vgetq_lane_f32(from.v, 1));
to[stride*1] = std::complex<float>(vgetq_lane_f32(from.v, 2), vgetq_lane_f32(from.v, 3));

8
Eigen/src/Core/arch/NEON/PacketMath.h
View File

@@ -222,7 +222,7 @@ 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_DEVICE_FUNC inline Packet4f pgather<float, Packet4f>(const float* from, int stride)
template<> EIGEN_DEVICE_FUNC inline Packet4f pgather<float, Packet4f>(const float* from, DenseIndex stride)
{
Packet4f res;
res = vsetq_lane_f32(from[0*stride], res, 0);
@@ -231,7 +231,7 @@ template<> EIGEN_DEVICE_FUNC inline Packet4f pgather<float, Packet4f>(const floa
res = vsetq_lane_f32(from[3*stride], res, 3);
return res;
}
template<> EIGEN_DEVICE_FUNC inline Packet4i pgather<int, Packet4i>(const int* from, int stride)
template<> EIGEN_DEVICE_FUNC inline Packet4i pgather<int, Packet4i>(const int* from, DenseIndex stride)
{
Packet4i res;
res = vsetq_lane_s32(from[0*stride], res, 0);
@@ -241,14 +241,14 @@ template<> EIGEN_DEVICE_FUNC inline Packet4i pgather<int, Packet4i>(const int* f
return res;
}
template<> EIGEN_DEVICE_FUNC inline void pscatter<float, Packet4f>(float* to, const Packet4f& from, int stride)
template<> EIGEN_DEVICE_FUNC inline void pscatter<float, Packet4f>(float* to, const Packet4f& from, DenseIndex stride)
{
to[stride*0] = vgetq_lane_f32(from, 0);
to[stride*1] = vgetq_lane_f32(from, 1);
to[stride*2] = vgetq_lane_f32(from, 2);
to[stride*3] = vgetq_lane_f32(from, 3);
}
template<> EIGEN_DEVICE_FUNC inline void pscatter<int, Packet4i>(int* to, const Packet4i& from, int stride)
template<> EIGEN_DEVICE_FUNC inline void pscatter<int, Packet4i>(int* to, const Packet4i& from, DenseIndex stride)
{
to[stride*0] = vgetq_lane_s32(from, 0);
to[stride*1] = vgetq_lane_s32(from, 1);

4
Eigen/src/Core/arch/SSE/Complex.h
View File

@@ -114,13 +114,13 @@ template<> EIGEN_STRONG_INLINE void pstore <std::complex<float> >(std::complex<f
template<> EIGEN_STRONG_INLINE void pstoreu<std::complex<float> >(std::complex<float> * to, const Packet2cf& from) { EIGEN_DEBUG_UNALIGNED_STORE pstoreu(&numext::real_ref(*to), Packet4f(from.v)); }
template<> EIGEN_DEVICE_FUNC inline Packet2cf pgather<std::complex<float>, Packet2cf>(const std::complex<float>* from, int stride)
template<> EIGEN_DEVICE_FUNC inline Packet2cf pgather<std::complex<float>, Packet2cf>(const std::complex<float>* from, DenseIndex stride)
{
return Packet2cf(_mm_set_ps(std::imag(from[1*stride]), std::real(from[1*stride]),
std::imag(from[0*stride]), std::real(from[0*stride])));
}
template<> EIGEN_DEVICE_FUNC inline void pscatter<std::complex<float>, Packet2cf>(std::complex<float>* to, const Packet2cf& from, int stride)
template<> EIGEN_DEVICE_FUNC inline void pscatter<std::complex<float>, Packet2cf>(std::complex<float>* to, const Packet2cf& from, DenseIndex stride)
{
to[stride*0] = std::complex<float>(_mm_cvtss_f32(_mm_shuffle_ps(from.v, from.v, 0)),
_mm_cvtss_f32(_mm_shuffle_ps(from.v, from.v, 1)));

12
Eigen/src/Core/arch/SSE/PacketMath.h
View File

@@ -383,32 +383,32 @@ template<> EIGEN_STRONG_INLINE void pstoreu<double>(double* to, const Packet2d&
template<> EIGEN_STRONG_INLINE void pstoreu<float>(float* to, const Packet4f& from) { EIGEN_DEBUG_UNALIGNED_STORE pstoreu(reinterpret_cast<double*>(to), Packet2d(_mm_castps_pd(from))); }
template<> EIGEN_STRONG_INLINE void pstoreu<int>(int* to, const Packet4i& from) { EIGEN_DEBUG_UNALIGNED_STORE pstoreu(reinterpret_cast<double*>(to), Packet2d(_mm_castsi128_pd(from))); }
template<> EIGEN_DEVICE_FUNC inline Packet4f pgather<float, Packet4f>(const float* from, int stride)
template<> EIGEN_DEVICE_FUNC inline Packet4f pgather<float, Packet4f>(const float* from, DenseIndex stride)
{
return _mm_set_ps(from[3*stride], from[2*stride], from[1*stride], from[0*stride]);
}
template<> EIGEN_DEVICE_FUNC inline Packet2d pgather<double, Packet2d>(const double* from, int stride)
template<> EIGEN_DEVICE_FUNC inline Packet2d pgather<double, Packet2d>(const double* from, DenseIndex stride)
{
return _mm_set_pd(from[1*stride], from[0*stride]);
}
template<> EIGEN_DEVICE_FUNC inline Packet4i pgather<int, Packet4i>(const int* from, int stride)
template<> EIGEN_DEVICE_FUNC inline Packet4i pgather<int, Packet4i>(const int* from, DenseIndex stride)
{
return _mm_set_epi32(from[3*stride], from[2*stride], from[1*stride], from[0*stride]);
}
template<> EIGEN_DEVICE_FUNC inline void pscatter<float, Packet4f>(float* to, const Packet4f& from, int stride)
template<> EIGEN_DEVICE_FUNC inline void pscatter<float, Packet4f>(float* to, const Packet4f& from, DenseIndex stride)
{
to[stride*0] = _mm_cvtss_f32(from);
to[stride*1] = _mm_cvtss_f32(_mm_shuffle_ps(from, from, 1));
to[stride*2] = _mm_cvtss_f32(_mm_shuffle_ps(from, from, 2));
to[stride*3] = _mm_cvtss_f32(_mm_shuffle_ps(from, from, 3));
}
template<> EIGEN_DEVICE_FUNC inline void pscatter<double, Packet2d>(double* to, const Packet2d& from, int stride)
template<> EIGEN_DEVICE_FUNC inline void pscatter<double, Packet2d>(double* to, const Packet2d& from, DenseIndex stride)
{
to[stride*0] = _mm_cvtsd_f64(from);
to[stride*1] = _mm_cvtsd_f64(_mm_shuffle_pd(from, from, 1));
}
template<> EIGEN_DEVICE_FUNC inline void pscatter<int, Packet4i>(int* to, const Packet4i& from, int stride)
template<> EIGEN_DEVICE_FUNC inline void pscatter<int, Packet4i>(int* to, const Packet4i& from, DenseIndex stride)
{
to[stride*0] = _mm_cvtsi128_si32(from);
to[stride*1] = _mm_cvtsi128_si32(_mm_shuffle_epi32(from, 1));

4
Eigen/src/Core/functors/NullaryFunctors.h
View File

@@ -92,7 +92,7 @@ struct linspaced_op_impl<Scalar,true>
template<typename Index>
EIGEN_STRONG_INLINE const Packet packetOp(Index i) const
{ return internal::padd(m_lowPacket, pmul(m_stepPacket, padd(pset1<Packet>(i),m_interPacket))); }
{ return internal::padd(m_lowPacket, pmul(m_stepPacket, padd(pset1<Packet>(Scalar(i)),m_interPacket))); }
const Scalar m_low;
const Scalar m_step;
@@ -112,7 +112,7 @@ template <typename Scalar, bool RandomAccess> struct functor_traits< linspaced_o
template <typename Scalar, bool RandomAccess> struct linspaced_op
{
typedef typename packet_traits<Scalar>::type Packet;
linspaced_op(const Scalar& low, const Scalar& high, DenseIndex num_steps) : impl((num_steps==1 ? high : low), (num_steps==1 ? Scalar() : (high-low)/(num_steps-1))) {}
linspaced_op(const Scalar& low, const Scalar& high, DenseIndex num_steps) : impl((num_steps==1 ? high : low), (num_steps==1 ? Scalar() : (high-low)/Scalar(num_steps-1))) {}
template<typename Index>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator() (Index i) const { return impl(i); }

4
Eigen/src/Core/products/SelfadjointMatrixVector.h
View File

@@ -219,7 +219,7 @@ struct SelfadjointProductMatrix<Lhs,LhsMode,false,Rhs,0,true>
if(!EvalToDest)
{
#ifdef EIGEN_DENSE_STORAGE_CTOR_PLUGIN
int size = dest.size();
Index size = dest.size();
EIGEN_DENSE_STORAGE_CTOR_PLUGIN
#endif
MappedDest(actualDestPtr, dest.size()) = dest;
@@ -228,7 +228,7 @@ struct SelfadjointProductMatrix<Lhs,LhsMode,false,Rhs,0,true>
if(!UseRhs)
{
#ifdef EIGEN_DENSE_STORAGE_CTOR_PLUGIN
int size = rhs.size();
Index size = rhs.size();
EIGEN_DENSE_STORAGE_CTOR_PLUGIN
#endif
Map<typename _ActualRhsType::PlainObject>(actualRhsPtr, rhs.size()) = rhs;

2
Eigen/src/Core/products/TriangularMatrixVector.h
View File

@@ -355,7 +355,7 @@ template<int Mode> struct trmv_selector<Mode,RowMajor>
if(!DirectlyUseRhs)
{
#ifdef EIGEN_DENSE_STORAGE_CTOR_PLUGIN
int size = actualRhs.size();
Index size = actualRhs.size();
EIGEN_DENSE_STORAGE_CTOR_PLUGIN
#endif
Map<typename ActualRhsTypeCleaned::PlainObject>(actualRhsPtr, actualRhs.size()) = actualRhs;

9
Eigen/src/Core/util/Memory.h
View File

@@ -607,12 +607,9 @@ template<typename T> class aligned_stack_memory_handler
* The underlying stack allocation function can controlled with the EIGEN_ALLOCA preprocessor token.
*/
#ifdef EIGEN_ALLOCA
// The native alloca() that comes with llvm aligns buffer on 16 bytes even when AVX is enabled.
#if defined(__arm__) || defined(_WIN32) || EIGEN_ALIGN_BYTES > 16
#define EIGEN_ALIGNED_ALLOCA(SIZE) reinterpret_cast<void*>((reinterpret_cast<size_t>(EIGEN_ALLOCA(SIZE+EIGEN_ALIGN_BYTES)) & ~(size_t(EIGEN_ALIGN_BYTES-1))) + EIGEN_ALIGN_BYTES)
#else
#define EIGEN_ALIGNED_ALLOCA EIGEN_ALLOCA
#endif
// We always manually re-align the result of EIGEN_ALLOCA.
// If alloca is already aligned, the compiler should be smart enough to optimize away the re-alignment.
#define EIGEN_ALIGNED_ALLOCA(SIZE) reinterpret_cast<void*>((reinterpret_cast<size_t>(EIGEN_ALLOCA(SIZE+EIGEN_ALIGN_BYTES-1)) + EIGEN_ALIGN_BYTES-1) & ~(size_t(EIGEN_ALIGN_BYTES-1)))
#define ei_declare_aligned_stack_constructed_variable(TYPE,NAME,SIZE,BUFFER) \
Eigen::internal::check_size_for_overflow<TYPE>(SIZE); \

19
Eigen/src/Core/util/Meta.h
View File

@@ -80,6 +80,25 @@ template<typename T> struct add_const_on_value_type<T*> { typedef T const
template<typename T> struct add_const_on_value_type<T* const> { typedef T const* const type; };
template<typename T> struct add_const_on_value_type<T const* const> { typedef T const* const type; };
template<typename From, typename To>
struct is_convertible
{
private:
struct yes {int a[1];};
struct no {int a[2];};
template<typename T>
static yes test (const T&) {}
template<typename> static no test (...) {}
public:
static From ms_from;
enum { value = sizeof(test<To>(ms_from))==sizeof(yes) };
};
/** \internal Allows to enable/disable an overload
* according to a compile time condition.
*/

2
Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h
View File

@@ -355,6 +355,7 @@ template<typename _MatrixType> class SelfAdjointEigenSolver
bool m_eigenvectorsOk;
};
namespace internal {
/** \internal
*
* \eigenvalues_module \ingroup Eigenvalues_Module
@@ -371,7 +372,6 @@ template<typename _MatrixType> class SelfAdjointEigenSolver
* Implemented from Golub's "Matrix Computations", algorithm 8.3.2:
* "implicit symmetric QR step with Wilkinson shift"
*/
namespace internal {
template<int StorageOrder,typename RealScalar, typename Scalar, typename Index>
EIGEN_DEVICE_FUNC
static void tridiagonal_qr_step(RealScalar* diag, RealScalar* subdiag, Index start, Index end, Scalar* matrixQ, Index n);

2
Eigen/src/Jacobi/Jacobi.h
View File

@@ -255,13 +255,13 @@ void JacobiRotation<Scalar>::makeGivens(const Scalar& p, const Scalar& q, Scalar
* Implementation of MatrixBase methods
****************************************************************************************/
namespace internal {
/** \jacobi_module
* Applies the clock wise 2D rotation \a j to the set of 2D vectors of cordinates \a x and \a y:
* \f$ \left ( \begin{array}{cc} x \\ y \end{array} \right ) = J \left ( \begin{array}{cc} x \\ y \end{array} \right ) \f$
*
* \sa MatrixBase::applyOnTheLeft(), MatrixBase::applyOnTheRight()
*/
namespace internal {
template<typename VectorX, typename VectorY, typename OtherScalar>
void apply_rotation_in_the_plane(VectorX& _x, VectorY& _y, const JacobiRotation<OtherScalar>& j);
}

4
Eigen/src/OrderingMethods/Ordering.h
View File

@@ -136,12 +136,12 @@ class COLAMDOrdering
Index stats [COLAMD_STATS];
internal::colamd_set_defaults(knobs);
Index info;
IndexVector p(n+1), A(Alen);
for(Index i=0; i <= n; i++) p(i) = mat.outerIndexPtr()[i];
for(Index i=0; i < nnz; i++) A(i) = mat.innerIndexPtr()[i];
// Call Colamd routine to compute the ordering
info = internal::colamd(m, n, Alen, A.data(), p.data(), knobs, stats);
Index info = internal::colamd(m, n, Alen, A.data(), p.data(), knobs, stats);
EIGEN_UNUSED_VARIABLE(info);
eigen_assert( info && "COLAMD failed " );
perm.resize(n);

4
Eigen/src/SparseCore/CompressedStorage.h
View File

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

40
Eigen/src/SparseCore/SparseBlock.h
View File

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

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

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

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

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