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Revert "Revert "Adds EIGEN_CONSTEXPR and EIGEN_NOEXCEPT to rows(), cols(), innerStride(), outerStride(), and size()""
This reverts commit 5f0b4a4010.
This commit is contained in:
Steve Bronder
@@ -12,19 +12,19 @@
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#define EIGEN_INCOMPLETE_LUT_H
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namespace Eigen {
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namespace Eigen {
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namespace internal {
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/** \internal
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* Compute a quick-sort split of a vector
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* Compute a quick-sort split of a vector
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* On output, the vector row is permuted such that its elements satisfy
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* abs(row(i)) >= abs(row(ncut)) if i<ncut
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* abs(row(i)) <= abs(row(ncut)) if i>ncut
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* abs(row(i)) <= abs(row(ncut)) if i>ncut
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* \param row The vector of values
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* \param ind The array of index for the elements in @p row
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* \param ncut The number of largest elements to keep
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**/
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**/
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template <typename VectorV, typename VectorI>
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Index QuickSplit(VectorV &row, VectorI &ind, Index ncut)
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{
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@@ -34,15 +34,15 @@ Index QuickSplit(VectorV &row, VectorI &ind, Index ncut)
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Index mid;
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Index n = row.size(); /* length of the vector */
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Index first, last ;
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ncut--; /* to fit the zero-based indices */
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first = 0;
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last = n-1;
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first = 0;
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last = n-1;
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if (ncut < first || ncut > last ) return 0;
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do {
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mid = first;
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RealScalar abskey = abs(row(mid));
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mid = first;
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RealScalar abskey = abs(row(mid));
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for (Index j = first + 1; j <= last; j++) {
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if ( abs(row(j)) > abskey) {
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++mid;
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@@ -53,12 +53,12 @@ Index QuickSplit(VectorV &row, VectorI &ind, Index ncut)
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/* Interchange for the pivot element */
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swap(row(mid), row(first));
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swap(ind(mid), ind(first));
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if (mid > ncut) last = mid - 1;
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else if (mid < ncut ) first = mid + 1;
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else if (mid < ncut ) first = mid + 1;
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} while (mid != ncut );
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return 0; /* mid is equal to ncut */
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return 0; /* mid is equal to ncut */
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}
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}// end namespace internal
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@@ -71,23 +71,23 @@ Index QuickSplit(VectorV &row, VectorI &ind, Index ncut)
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*
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* During the numerical factorization, two dropping rules are used :
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* 1) any element whose magnitude is less than some tolerance is dropped.
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* This tolerance is obtained by multiplying the input tolerance @p droptol
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* This tolerance is obtained by multiplying the input tolerance @p droptol
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* by the average magnitude of all the original elements in the current row.
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* 2) After the elimination of the row, only the @p fill largest elements in
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* the L part and the @p fill largest elements in the U part are kept
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* (in addition to the diagonal element ). Note that @p fill is computed from
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* the input parameter @p fillfactor which is used the ratio to control the fill_in
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* 2) After the elimination of the row, only the @p fill largest elements in
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* the L part and the @p fill largest elements in the U part are kept
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* (in addition to the diagonal element ). Note that @p fill is computed from
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* the input parameter @p fillfactor which is used the ratio to control the fill_in
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* relatively to the initial number of nonzero elements.
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*
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*
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* The two extreme cases are when @p droptol=0 (to keep all the @p fill*2 largest elements)
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* and when @p fill=n/2 with @p droptol being different to zero.
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*
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* References : Yousef Saad, ILUT: A dual threshold incomplete LU factorization,
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* and when @p fill=n/2 with @p droptol being different to zero.
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*
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* References : Yousef Saad, ILUT: A dual threshold incomplete LU factorization,
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* Numerical Linear Algebra with Applications, 1(4), pp 387-402, 1994.
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*
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*
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* NOTE : The following implementation is derived from the ILUT implementation
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* in the SPARSKIT package, Copyright (C) 2005, the Regents of the University of Minnesota
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* released under the terms of the GNU LGPL:
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* in the SPARSKIT package, Copyright (C) 2005, the Regents of the University of Minnesota
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* released under the terms of the GNU LGPL:
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* http://www-users.cs.umn.edu/~saad/software/SPARSKIT/README
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* However, Yousef Saad gave us permission to relicense his ILUT code to MPL2.
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* See the Eigen mailing list archive, thread: ILUT, date: July 8, 2012:
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@@ -115,24 +115,24 @@ class IncompleteLUT : public SparseSolverBase<IncompleteLUT<_Scalar, _StorageInd
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};
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public:
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IncompleteLUT()
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: m_droptol(NumTraits<Scalar>::dummy_precision()), m_fillfactor(10),
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m_analysisIsOk(false), m_factorizationIsOk(false)
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{}
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template<typename MatrixType>
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explicit IncompleteLUT(const MatrixType& mat, const RealScalar& droptol=NumTraits<Scalar>::dummy_precision(), int fillfactor = 10)
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: m_droptol(droptol),m_fillfactor(fillfactor),
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m_analysisIsOk(false),m_factorizationIsOk(false)
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{
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eigen_assert(fillfactor != 0);
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compute(mat);
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compute(mat);
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}
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Index rows() const { return m_lu.rows(); }
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Index cols() const { return m_lu.cols(); }
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EIGEN_CONSTEXPR Index rows() const EIGEN_NOEXCEPT { return m_lu.rows(); }
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EIGEN_CONSTEXPR Index cols() const EIGEN_NOEXCEPT { return m_lu.cols(); }
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/** \brief Reports whether previous computation was successful.
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*
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@@ -144,36 +144,36 @@ class IncompleteLUT : public SparseSolverBase<IncompleteLUT<_Scalar, _StorageInd
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eigen_assert(m_isInitialized && "IncompleteLUT is not initialized.");
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return m_info;
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}
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template<typename MatrixType>
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void analyzePattern(const MatrixType& amat);
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template<typename MatrixType>
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void factorize(const MatrixType& amat);
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/**
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* Compute an incomplete LU factorization with dual threshold on the matrix mat
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* No pivoting is done in this version
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*
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*
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**/
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template<typename MatrixType>
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IncompleteLUT& compute(const MatrixType& amat)
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{
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analyzePattern(amat);
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analyzePattern(amat);
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factorize(amat);
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return *this;
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}
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void setDroptol(const RealScalar& droptol);
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void setFillfactor(int fillfactor);
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void setDroptol(const RealScalar& droptol);
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void setFillfactor(int fillfactor);
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template<typename Rhs, typename Dest>
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void _solve_impl(const Rhs& b, Dest& x) const
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{
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x = m_Pinv * b;
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x = m_lu.template triangularView<UnitLower>().solve(x);
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x = m_lu.template triangularView<Upper>().solve(x);
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x = m_P * x;
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x = m_P * x;
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}
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protected:
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@@ -200,22 +200,22 @@ protected:
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/**
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* Set control parameter droptol
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* \param droptol Drop any element whose magnitude is less than this tolerance
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**/
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* \param droptol Drop any element whose magnitude is less than this tolerance
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**/
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template<typename Scalar, typename StorageIndex>
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void IncompleteLUT<Scalar,StorageIndex>::setDroptol(const RealScalar& droptol)
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{
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this->m_droptol = droptol;
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this->m_droptol = droptol;
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}
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/**
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* Set control parameter fillfactor
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* \param fillfactor This is used to compute the number @p fill_in of largest elements to keep on each row.
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**/
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* \param fillfactor This is used to compute the number @p fill_in of largest elements to keep on each row.
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**/
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template<typename Scalar, typename StorageIndex>
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void IncompleteLUT<Scalar,StorageIndex>::setFillfactor(int fillfactor)
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{
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this->m_fillfactor = fillfactor;
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this->m_fillfactor = fillfactor;
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}
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template <typename Scalar, typename StorageIndex>
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