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-rw-r--r--extern/Eigen3/Eigen/src/Cholesky/LDLT.h74
-rw-r--r--extern/Eigen3/Eigen/src/Cholesky/LLT.h20
2 files changed, 57 insertions, 37 deletions
diff --git a/extern/Eigen3/Eigen/src/Cholesky/LDLT.h b/extern/Eigen3/Eigen/src/Cholesky/LDLT.h
index 68e54b1d4ad..d026418f8a9 100644
--- a/extern/Eigen3/Eigen/src/Cholesky/LDLT.h
+++ b/extern/Eigen3/Eigen/src/Cholesky/LDLT.h
@@ -16,7 +16,10 @@
namespace Eigen {
namespace internal {
-template<typename MatrixType, int UpLo> struct LDLT_Traits;
+ template<typename MatrixType, int UpLo> struct LDLT_Traits;
+
+ // PositiveSemiDef means positive semi-definite and non-zero; same for NegativeSemiDef
+ enum SignMatrix { PositiveSemiDef, NegativeSemiDef, ZeroSign, Indefinite };
}
/** \ingroup Cholesky_Module
@@ -69,7 +72,12 @@ template<typename _MatrixType, int _UpLo> class LDLT
* The default constructor is useful in cases in which the user intends to
* perform decompositions via LDLT::compute(const MatrixType&).
*/
- LDLT() : m_matrix(), m_transpositions(), m_isInitialized(false) {}
+ LDLT()
+ : m_matrix(),
+ m_transpositions(),
+ m_sign(internal::ZeroSign),
+ m_isInitialized(false)
+ {}
/** \brief Default Constructor with memory preallocation
*
@@ -81,6 +89,7 @@ template<typename _MatrixType, int _UpLo> class LDLT
: m_matrix(size, size),
m_transpositions(size),
m_temporary(size),
+ m_sign(internal::ZeroSign),
m_isInitialized(false)
{}
@@ -93,6 +102,7 @@ template<typename _MatrixType, int _UpLo> class LDLT
: m_matrix(matrix.rows(), matrix.cols()),
m_transpositions(matrix.rows()),
m_temporary(matrix.rows()),
+ m_sign(internal::ZeroSign),
m_isInitialized(false)
{
compute(matrix);
@@ -139,7 +149,7 @@ template<typename _MatrixType, int _UpLo> class LDLT
inline bool isPositive() const
{
eigen_assert(m_isInitialized && "LDLT is not initialized.");
- return m_sign == 1;
+ return m_sign == internal::PositiveSemiDef || m_sign == internal::ZeroSign;
}
#ifdef EIGEN2_SUPPORT
@@ -153,7 +163,7 @@ template<typename _MatrixType, int _UpLo> class LDLT
inline bool isNegative(void) const
{
eigen_assert(m_isInitialized && "LDLT is not initialized.");
- return m_sign == -1;
+ return m_sign == internal::NegativeSemiDef || m_sign == internal::ZeroSign;
}
/** \returns a solution x of \f$ A x = b \f$ using the current decomposition of A.
@@ -196,7 +206,7 @@ template<typename _MatrixType, int _UpLo> class LDLT
LDLT& compute(const MatrixType& matrix);
template <typename Derived>
- LDLT& rankUpdate(const MatrixBase<Derived>& w,RealScalar alpha=1);
+ LDLT& rankUpdate(const MatrixBase<Derived>& w, const RealScalar& alpha=1);
/** \returns the internal LDLT decomposition matrix
*
@@ -235,7 +245,7 @@ template<typename _MatrixType, int _UpLo> class LDLT
MatrixType m_matrix;
TranspositionType m_transpositions;
TmpMatrixType m_temporary;
- int m_sign;
+ internal::SignMatrix m_sign;
bool m_isInitialized;
};
@@ -246,8 +256,9 @@ template<int UpLo> struct ldlt_inplace;
template<> struct ldlt_inplace<Lower>
{
template<typename MatrixType, typename TranspositionType, typename Workspace>
- static bool unblocked(MatrixType& mat, TranspositionType& transpositions, Workspace& temp, int* sign=0)
+ static bool unblocked(MatrixType& mat, TranspositionType& transpositions, Workspace& temp, SignMatrix& sign)
{
+ using std::abs;
typedef typename MatrixType::Scalar Scalar;
typedef typename MatrixType::RealScalar RealScalar;
typedef typename MatrixType::Index Index;
@@ -257,8 +268,9 @@ template<> struct ldlt_inplace<Lower>
if (size <= 1)
{
transpositions.setIdentity();
- if(sign)
- *sign = real(mat.coeff(0,0))>0 ? 1:-1;
+ if (numext::real(mat.coeff(0,0)) > 0) sign = PositiveSemiDef;
+ else if (numext::real(mat.coeff(0,0)) < 0) sign = NegativeSemiDef;
+ else sign = ZeroSign;
return true;
}
@@ -277,9 +289,6 @@ template<> struct ldlt_inplace<Lower>
// are compared; if any diagonal is negligible compared
// to the largest overall, the algorithm bails.
cutoff = abs(NumTraits<Scalar>::epsilon() * biggest_in_corner);
-
- if(sign)
- *sign = real(mat.diagonal().coeff(index_of_biggest_in_corner)) > 0 ? 1 : -1;
}
// Finish early if the matrix is not full rank.
@@ -301,11 +310,11 @@ template<> struct ldlt_inplace<Lower>
for(int i=k+1;i<index_of_biggest_in_corner;++i)
{
Scalar tmp = mat.coeffRef(i,k);
- mat.coeffRef(i,k) = conj(mat.coeffRef(index_of_biggest_in_corner,i));
- mat.coeffRef(index_of_biggest_in_corner,i) = conj(tmp);
+ mat.coeffRef(i,k) = numext::conj(mat.coeffRef(index_of_biggest_in_corner,i));
+ mat.coeffRef(index_of_biggest_in_corner,i) = numext::conj(tmp);
}
if(NumTraits<Scalar>::IsComplex)
- mat.coeffRef(index_of_biggest_in_corner,k) = conj(mat.coeff(index_of_biggest_in_corner,k));
+ mat.coeffRef(index_of_biggest_in_corner,k) = numext::conj(mat.coeff(index_of_biggest_in_corner,k));
}
// partition the matrix:
@@ -326,6 +335,16 @@ template<> struct ldlt_inplace<Lower>
}
if((rs>0) && (abs(mat.coeffRef(k,k)) > cutoff))
A21 /= mat.coeffRef(k,k);
+
+ RealScalar realAkk = numext::real(mat.coeffRef(k,k));
+ if (sign == PositiveSemiDef) {
+ if (realAkk < 0) sign = Indefinite;
+ } else if (sign == NegativeSemiDef) {
+ if (realAkk > 0) sign = Indefinite;
+ } else if (sign == ZeroSign) {
+ if (realAkk > 0) sign = PositiveSemiDef;
+ else if (realAkk < 0) sign = NegativeSemiDef;
+ }
}
return true;
@@ -339,9 +358,9 @@ template<> struct ldlt_inplace<Lower>
// Here only rank-1 updates are implemented, to reduce the
// requirement for intermediate storage and improve accuracy
template<typename MatrixType, typename WDerived>
- static bool updateInPlace(MatrixType& mat, MatrixBase<WDerived>& w, typename MatrixType::RealScalar sigma=1)
+ static bool updateInPlace(MatrixType& mat, MatrixBase<WDerived>& w, const typename MatrixType::RealScalar& sigma=1)
{
- using internal::isfinite;
+ using numext::isfinite;
typedef typename MatrixType::Scalar Scalar;
typedef typename MatrixType::RealScalar RealScalar;
typedef typename MatrixType::Index Index;
@@ -359,9 +378,9 @@ template<> struct ldlt_inplace<Lower>
break;
// Update the diagonal terms
- RealScalar dj = real(mat.coeff(j,j));
+ RealScalar dj = numext::real(mat.coeff(j,j));
Scalar wj = w.coeff(j);
- RealScalar swj2 = sigma*abs2(wj);
+ RealScalar swj2 = sigma*numext::abs2(wj);
RealScalar gamma = dj*alpha + swj2;
mat.coeffRef(j,j) += swj2/alpha;
@@ -372,13 +391,13 @@ template<> struct ldlt_inplace<Lower>
Index rs = size-j-1;
w.tail(rs) -= wj * mat.col(j).tail(rs);
if(gamma != 0)
- mat.col(j).tail(rs) += (sigma*conj(wj)/gamma)*w.tail(rs);
+ mat.col(j).tail(rs) += (sigma*numext::conj(wj)/gamma)*w.tail(rs);
}
return true;
}
template<typename MatrixType, typename TranspositionType, typename Workspace, typename WType>
- static bool update(MatrixType& mat, const TranspositionType& transpositions, Workspace& tmp, const WType& w, typename MatrixType::RealScalar sigma=1)
+ static bool update(MatrixType& mat, const TranspositionType& transpositions, Workspace& tmp, const WType& w, const typename MatrixType::RealScalar& sigma=1)
{
// Apply the permutation to the input w
tmp = transpositions * w;
@@ -390,14 +409,14 @@ template<> struct ldlt_inplace<Lower>
template<> struct ldlt_inplace<Upper>
{
template<typename MatrixType, typename TranspositionType, typename Workspace>
- static EIGEN_STRONG_INLINE bool unblocked(MatrixType& mat, TranspositionType& transpositions, Workspace& temp, int* sign=0)
+ static EIGEN_STRONG_INLINE bool unblocked(MatrixType& mat, TranspositionType& transpositions, Workspace& temp, SignMatrix& sign)
{
Transpose<MatrixType> matt(mat);
return ldlt_inplace<Lower>::unblocked(matt, transpositions, temp, sign);
}
template<typename MatrixType, typename TranspositionType, typename Workspace, typename WType>
- static EIGEN_STRONG_INLINE bool update(MatrixType& mat, TranspositionType& transpositions, Workspace& tmp, WType& w, typename MatrixType::RealScalar sigma=1)
+ static EIGEN_STRONG_INLINE bool update(MatrixType& mat, TranspositionType& transpositions, Workspace& tmp, WType& w, const typename MatrixType::RealScalar& sigma=1)
{
Transpose<MatrixType> matt(mat);
return ldlt_inplace<Lower>::update(matt, transpositions, tmp, w.conjugate(), sigma);
@@ -436,7 +455,7 @@ LDLT<MatrixType,_UpLo>& LDLT<MatrixType,_UpLo>::compute(const MatrixType& a)
m_isInitialized = false;
m_temporary.resize(size);
- internal::ldlt_inplace<UpLo>::unblocked(m_matrix, m_transpositions, m_temporary, &m_sign);
+ internal::ldlt_inplace<UpLo>::unblocked(m_matrix, m_transpositions, m_temporary, m_sign);
m_isInitialized = true;
return *this;
@@ -449,7 +468,7 @@ LDLT<MatrixType,_UpLo>& LDLT<MatrixType,_UpLo>::compute(const MatrixType& a)
*/
template<typename MatrixType, int _UpLo>
template<typename Derived>
-LDLT<MatrixType,_UpLo>& LDLT<MatrixType,_UpLo>::rankUpdate(const MatrixBase<Derived>& w,typename NumTraits<typename MatrixType::Scalar>::Real sigma)
+LDLT<MatrixType,_UpLo>& LDLT<MatrixType,_UpLo>::rankUpdate(const MatrixBase<Derived>& w, const typename NumTraits<typename MatrixType::Scalar>::Real& sigma)
{
const Index size = w.rows();
if (m_isInitialized)
@@ -464,7 +483,7 @@ LDLT<MatrixType,_UpLo>& LDLT<MatrixType,_UpLo>::rankUpdate(const MatrixBase<Deri
for (Index i = 0; i < size; i++)
m_transpositions.coeffRef(i) = i;
m_temporary.resize(size);
- m_sign = sigma>=0 ? 1 : -1;
+ m_sign = sigma>=0 ? internal::PositiveSemiDef : internal::NegativeSemiDef;
m_isInitialized = true;
}
@@ -534,8 +553,7 @@ template<typename Derived>
bool LDLT<MatrixType,_UpLo>::solveInPlace(MatrixBase<Derived> &bAndX) const
{
eigen_assert(m_isInitialized && "LDLT is not initialized.");
- const Index size = m_matrix.rows();
- eigen_assert(size == bAndX.rows());
+ eigen_assert(m_matrix.rows() == bAndX.rows());
bAndX = this->solve(bAndX);
diff --git a/extern/Eigen3/Eigen/src/Cholesky/LLT.h b/extern/Eigen3/Eigen/src/Cholesky/LLT.h
index 41d14e532f1..2e6189f7dab 100644
--- a/extern/Eigen3/Eigen/src/Cholesky/LLT.h
+++ b/extern/Eigen3/Eigen/src/Cholesky/LLT.h
@@ -190,6 +190,7 @@ template<typename Scalar, int UpLo> struct llt_inplace;
template<typename MatrixType, typename VectorType>
static typename MatrixType::Index llt_rank_update_lower(MatrixType& mat, const VectorType& vec, const typename MatrixType::RealScalar& sigma)
{
+ using std::sqrt;
typedef typename MatrixType::Scalar Scalar;
typedef typename MatrixType::RealScalar RealScalar;
typedef typename MatrixType::Index Index;
@@ -199,7 +200,7 @@ static typename MatrixType::Index llt_rank_update_lower(MatrixType& mat, const V
typedef Matrix<Scalar,Dynamic,1> TempVectorType;
typedef typename TempVectorType::SegmentReturnType TempVecSegment;
- int n = mat.cols();
+ Index n = mat.cols();
eigen_assert(mat.rows()==n && vec.size()==n);
TempVectorType temp;
@@ -211,12 +212,12 @@ static typename MatrixType::Index llt_rank_update_lower(MatrixType& mat, const V
// i.e., for sigma > 0
temp = sqrt(sigma) * vec;
- for(int i=0; i<n; ++i)
+ for(Index i=0; i<n; ++i)
{
JacobiRotation<Scalar> g;
g.makeGivens(mat(i,i), -temp(i), &mat(i,i));
- int rs = n-i-1;
+ Index rs = n-i-1;
if(rs>0)
{
ColXprSegment x(mat.col(i).tail(rs));
@@ -229,12 +230,12 @@ static typename MatrixType::Index llt_rank_update_lower(MatrixType& mat, const V
{
temp = vec;
RealScalar beta = 1;
- for(int j=0; j<n; ++j)
+ for(Index j=0; j<n; ++j)
{
- RealScalar Ljj = real(mat.coeff(j,j));
- RealScalar dj = abs2(Ljj);
+ RealScalar Ljj = numext::real(mat.coeff(j,j));
+ RealScalar dj = numext::abs2(Ljj);
Scalar wj = temp.coeff(j);
- RealScalar swj2 = sigma*abs2(wj);
+ RealScalar swj2 = sigma*numext::abs2(wj);
RealScalar gamma = dj*beta + swj2;
RealScalar x = dj + swj2/beta;
@@ -250,7 +251,7 @@ static typename MatrixType::Index llt_rank_update_lower(MatrixType& mat, const V
{
temp.tail(rs) -= (wj/Ljj) * mat.col(j).tail(rs);
if(gamma != 0)
- mat.col(j).tail(rs) = (nLjj/Ljj) * mat.col(j).tail(rs) + (nLjj * sigma*conj(wj)/gamma)*temp.tail(rs);
+ mat.col(j).tail(rs) = (nLjj/Ljj) * mat.col(j).tail(rs) + (nLjj * sigma*numext::conj(wj)/gamma)*temp.tail(rs);
}
}
}
@@ -263,6 +264,7 @@ template<typename Scalar> struct llt_inplace<Scalar, Lower>
template<typename MatrixType>
static typename MatrixType::Index unblocked(MatrixType& mat)
{
+ using std::sqrt;
typedef typename MatrixType::Index Index;
eigen_assert(mat.rows()==mat.cols());
@@ -275,7 +277,7 @@ template<typename Scalar> struct llt_inplace<Scalar, Lower>
Block<MatrixType,1,Dynamic> A10(mat,k,0,1,k);
Block<MatrixType,Dynamic,Dynamic> A20(mat,k+1,0,rs,k);
- RealScalar x = real(mat.coeff(k,k));
+ RealScalar x = numext::real(mat.coeff(k,k));
if (k>0) x -= A10.squaredNorm();
if (x<=RealScalar(0))
return k;
generated by cgit v1.2.3 (git 2.25.1) at 2024-09-03 21:24:54 +0300