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Diffstat (limited to 'unsupported/Eigen/src/Skyline/SkylineMatrix.h')
| -rw-r--r-- | unsupported/Eigen/src/Skyline/SkylineMatrix.h | 862 |
1 files changed, 862 insertions, 0 deletions
diff --git a/unsupported/Eigen/src/Skyline/SkylineMatrix.h b/unsupported/Eigen/src/Skyline/SkylineMatrix.h new file mode 100644 index 000000000..a2a8933ca --- /dev/null +++ b/unsupported/Eigen/src/Skyline/SkylineMatrix.h @@ -0,0 +1,862 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2008-2009 Guillaume Saupin <guillaume.saupin@cea.fr> +// +// This Source Code Form is subject to the terms of the Mozilla +// Public License v. 2.0. If a copy of the MPL was not distributed +// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. + +#ifndef EIGEN_SKYLINEMATRIX_H +#define EIGEN_SKYLINEMATRIX_H + +#include "SkylineStorage.h" +#include "SkylineMatrixBase.h" + +namespace Eigen { + +/** \ingroup Skyline_Module + * + * \class SkylineMatrix + * + * \brief The main skyline matrix class + * + * This class implements a skyline matrix using the very uncommon storage + * scheme. + * + * \param _Scalar the scalar type, i.e. the type of the coefficients + * \param _Options Union of bit flags controlling the storage scheme. Currently the only possibility + * is RowMajor. The default is 0 which means column-major. + * + * + */ +namespace internal { +template<typename _Scalar, int _Options> +struct traits<SkylineMatrix<_Scalar, _Options> > { + typedef _Scalar Scalar; + typedef Sparse StorageKind; + + enum { + RowsAtCompileTime = Dynamic, + ColsAtCompileTime = Dynamic, + MaxRowsAtCompileTime = Dynamic, + MaxColsAtCompileTime = Dynamic, + Flags = SkylineBit | _Options, + CoeffReadCost = NumTraits<Scalar>::ReadCost, + }; +}; +} + +template<typename _Scalar, int _Options> +class SkylineMatrix +: public SkylineMatrixBase<SkylineMatrix<_Scalar, _Options> > { +public: + EIGEN_SKYLINE_GENERIC_PUBLIC_INTERFACE(SkylineMatrix) + EIGEN_SKYLINE_INHERIT_ASSIGNMENT_OPERATOR(SkylineMatrix, +=) + EIGEN_SKYLINE_INHERIT_ASSIGNMENT_OPERATOR(SkylineMatrix, -=) + + using Base::IsRowMajor; + +protected: + + typedef SkylineMatrix<Scalar, (Flags&~RowMajorBit) | (IsRowMajor ? RowMajorBit : 0) > TransposedSkylineMatrix; + + Index m_outerSize; + Index m_innerSize; + +public: + Index* m_colStartIndex; + Index* m_rowStartIndex; + SkylineStorage<Scalar> m_data; + +public: + + inline Index rows() const { + return IsRowMajor ? m_outerSize : m_innerSize; + } + + inline Index cols() const { + return IsRowMajor ? m_innerSize : m_outerSize; + } + + inline Index innerSize() const { + return m_innerSize; + } + + inline Index outerSize() const { + return m_outerSize; + } + + inline Index upperNonZeros() const { + return m_data.upperSize(); + } + + inline Index lowerNonZeros() const { + return m_data.lowerSize(); + } + + inline Index upperNonZeros(Index j) const { + return m_colStartIndex[j + 1] - m_colStartIndex[j]; + } + + inline Index lowerNonZeros(Index j) const { + return m_rowStartIndex[j + 1] - m_rowStartIndex[j]; + } + + inline const Scalar* _diagPtr() const { + return &m_data.diag(0); + } + + inline Scalar* _diagPtr() { + return &m_data.diag(0); + } + + inline const Scalar* _upperPtr() const { + return &m_data.upper(0); + } + + inline Scalar* _upperPtr() { + return &m_data.upper(0); + } + + inline const Scalar* _lowerPtr() const { + return &m_data.lower(0); + } + + inline Scalar* _lowerPtr() { + return &m_data.lower(0); + } + + inline const Index* _upperProfilePtr() const { + return &m_data.upperProfile(0); + } + + inline Index* _upperProfilePtr() { + return &m_data.upperProfile(0); + } + + inline const Index* _lowerProfilePtr() const { + return &m_data.lowerProfile(0); + } + + inline Index* _lowerProfilePtr() { + return &m_data.lowerProfile(0); + } + + inline Scalar coeff(Index row, Index col) const { + const Index outer = IsRowMajor ? row : col; + const Index inner = IsRowMajor ? col : row; + + eigen_assert(outer < outerSize()); + eigen_assert(inner < innerSize()); + + if (outer == inner) + return this->m_data.diag(outer); + + if (IsRowMajor) { + if (inner > outer) //upper matrix + { + const Index minOuterIndex = inner - m_data.upperProfile(inner); + if (outer >= minOuterIndex) + return this->m_data.upper(m_colStartIndex[inner] + outer - (inner - m_data.upperProfile(inner))); + else + return Scalar(0); + } + if (inner < outer) //lower matrix + { + const Index minInnerIndex = outer - m_data.lowerProfile(outer); + if (inner >= minInnerIndex) + return this->m_data.lower(m_rowStartIndex[outer] + inner - (outer - m_data.lowerProfile(outer))); + else + return Scalar(0); + } + return m_data.upper(m_colStartIndex[inner] + outer - inner); + } else { + if (outer > inner) //upper matrix + { + const Index maxOuterIndex = inner + m_data.upperProfile(inner); + if (outer <= maxOuterIndex) + return this->m_data.upper(m_colStartIndex[inner] + (outer - inner)); + else + return Scalar(0); + } + if (outer < inner) //lower matrix + { + const Index maxInnerIndex = outer + m_data.lowerProfile(outer); + + if (inner <= maxInnerIndex) + return this->m_data.lower(m_rowStartIndex[outer] + (inner - outer)); + else + return Scalar(0); + } + } + } + + inline Scalar& coeffRef(Index row, Index col) { + const Index outer = IsRowMajor ? row : col; + const Index inner = IsRowMajor ? col : row; + + eigen_assert(outer < outerSize()); + eigen_assert(inner < innerSize()); + + if (outer == inner) + return this->m_data.diag(outer); + + if (IsRowMajor) { + if (col > row) //upper matrix + { + const Index minOuterIndex = inner - m_data.upperProfile(inner); + eigen_assert(outer >= minOuterIndex && "you try to acces a coeff that do not exist in the storage"); + return this->m_data.upper(m_colStartIndex[inner] + outer - (inner - m_data.upperProfile(inner))); + } + if (col < row) //lower matrix + { + const Index minInnerIndex = outer - m_data.lowerProfile(outer); + eigen_assert(inner >= minInnerIndex && "you try to acces a coeff that do not exist in the storage"); + return this->m_data.lower(m_rowStartIndex[outer] + inner - (outer - m_data.lowerProfile(outer))); + } + } else { + if (outer > inner) //upper matrix + { + const Index maxOuterIndex = inner + m_data.upperProfile(inner); + eigen_assert(outer <= maxOuterIndex && "you try to acces a coeff that do not exist in the storage"); + return this->m_data.upper(m_colStartIndex[inner] + (outer - inner)); + } + if (outer < inner) //lower matrix + { + const Index maxInnerIndex = outer + m_data.lowerProfile(outer); + eigen_assert(inner <= maxInnerIndex && "you try to acces a coeff that do not exist in the storage"); + return this->m_data.lower(m_rowStartIndex[outer] + (inner - outer)); + } + } + } + + inline Scalar coeffDiag(Index idx) const { + eigen_assert(idx < outerSize()); + eigen_assert(idx < innerSize()); + return this->m_data.diag(idx); + } + + inline Scalar coeffLower(Index row, Index col) const { + const Index outer = IsRowMajor ? row : col; + const Index inner = IsRowMajor ? col : row; + + eigen_assert(outer < outerSize()); + eigen_assert(inner < innerSize()); + eigen_assert(inner != outer); + + if (IsRowMajor) { + const Index minInnerIndex = outer - m_data.lowerProfile(outer); + if (inner >= minInnerIndex) + return this->m_data.lower(m_rowStartIndex[outer] + inner - (outer - m_data.lowerProfile(outer))); + else + return Scalar(0); + + } else { + const Index maxInnerIndex = outer + m_data.lowerProfile(outer); + if (inner <= maxInnerIndex) + return this->m_data.lower(m_rowStartIndex[outer] + (inner - outer)); + else + return Scalar(0); + } + } + + inline Scalar coeffUpper(Index row, Index col) const { + const Index outer = IsRowMajor ? row : col; + const Index inner = IsRowMajor ? col : row; + + eigen_assert(outer < outerSize()); + eigen_assert(inner < innerSize()); + eigen_assert(inner != outer); + + if (IsRowMajor) { + const Index minOuterIndex = inner - m_data.upperProfile(inner); + if (outer >= minOuterIndex) + return this->m_data.upper(m_colStartIndex[inner] + outer - (inner - m_data.upperProfile(inner))); + else + return Scalar(0); + } else { + const Index maxOuterIndex = inner + m_data.upperProfile(inner); + if (outer <= maxOuterIndex) + return this->m_data.upper(m_colStartIndex[inner] + (outer - inner)); + else + return Scalar(0); + } + } + + inline Scalar& coeffRefDiag(Index idx) { + eigen_assert(idx < outerSize()); + eigen_assert(idx < innerSize()); + return this->m_data.diag(idx); + } + + inline Scalar& coeffRefLower(Index row, Index col) { + const Index outer = IsRowMajor ? row : col; + const Index inner = IsRowMajor ? col : row; + + eigen_assert(outer < outerSize()); + eigen_assert(inner < innerSize()); + eigen_assert(inner != outer); + + if (IsRowMajor) { + const Index minInnerIndex = outer - m_data.lowerProfile(outer); + eigen_assert(inner >= minInnerIndex && "you try to acces a coeff that do not exist in the storage"); + return this->m_data.lower(m_rowStartIndex[outer] + inner - (outer - m_data.lowerProfile(outer))); + } else { + const Index maxInnerIndex = outer + m_data.lowerProfile(outer); + eigen_assert(inner <= maxInnerIndex && "you try to acces a coeff that do not exist in the storage"); + return this->m_data.lower(m_rowStartIndex[outer] + (inner - outer)); + } + } + + inline bool coeffExistLower(Index row, Index col) { + const Index outer = IsRowMajor ? row : col; + const Index inner = IsRowMajor ? col : row; + + eigen_assert(outer < outerSize()); + eigen_assert(inner < innerSize()); + eigen_assert(inner != outer); + + if (IsRowMajor) { + const Index minInnerIndex = outer - m_data.lowerProfile(outer); + return inner >= minInnerIndex; + } else { + const Index maxInnerIndex = outer + m_data.lowerProfile(outer); + return inner <= maxInnerIndex; + } + } + + inline Scalar& coeffRefUpper(Index row, Index col) { + const Index outer = IsRowMajor ? row : col; + const Index inner = IsRowMajor ? col : row; + + eigen_assert(outer < outerSize()); + eigen_assert(inner < innerSize()); + eigen_assert(inner != outer); + + if (IsRowMajor) { + const Index minOuterIndex = inner - m_data.upperProfile(inner); + eigen_assert(outer >= minOuterIndex && "you try to acces a coeff that do not exist in the storage"); + return this->m_data.upper(m_colStartIndex[inner] + outer - (inner - m_data.upperProfile(inner))); + } else { + const Index maxOuterIndex = inner + m_data.upperProfile(inner); + eigen_assert(outer <= maxOuterIndex && "you try to acces a coeff that do not exist in the storage"); + return this->m_data.upper(m_colStartIndex[inner] + (outer - inner)); + } + } + + inline bool coeffExistUpper(Index row, Index col) { + const Index outer = IsRowMajor ? row : col; + const Index inner = IsRowMajor ? col : row; + + eigen_assert(outer < outerSize()); + eigen_assert(inner < innerSize()); + eigen_assert(inner != outer); + + if (IsRowMajor) { + const Index minOuterIndex = inner - m_data.upperProfile(inner); + return outer >= minOuterIndex; + } else { + const Index maxOuterIndex = inner + m_data.upperProfile(inner); + return outer <= maxOuterIndex; + } + } + + +protected: + +public: + class InnerUpperIterator; + class InnerLowerIterator; + + class OuterUpperIterator; + class OuterLowerIterator; + + /** Removes all non zeros */ + inline void setZero() { + m_data.clear(); + memset(m_colStartIndex, 0, (m_outerSize + 1) * sizeof (Index)); + memset(m_rowStartIndex, 0, (m_outerSize + 1) * sizeof (Index)); + } + + /** \returns the number of non zero coefficients */ + inline Index nonZeros() const { + return m_data.diagSize() + m_data.upperSize() + m_data.lowerSize(); + } + + /** Preallocates \a reserveSize non zeros */ + inline void reserve(Index reserveSize, Index reserveUpperSize, Index reserveLowerSize) { + m_data.reserve(reserveSize, reserveUpperSize, reserveLowerSize); + } + + /** \returns a reference to a novel non zero coefficient with coordinates \a row x \a col. + + * + * \warning This function can be extremely slow if the non zero coefficients + * are not inserted in a coherent order. + * + * After an insertion session, you should call the finalize() function. + */ + EIGEN_DONT_INLINE Scalar & insert(Index row, Index col) { + const Index outer = IsRowMajor ? row : col; + const Index inner = IsRowMajor ? col : row; + + eigen_assert(outer < outerSize()); + eigen_assert(inner < innerSize()); + + if (outer == inner) + return m_data.diag(col); + + if (IsRowMajor) { + if (outer < inner) //upper matrix + { + Index minOuterIndex = 0; + minOuterIndex = inner - m_data.upperProfile(inner); + + if (outer < minOuterIndex) //The value does not yet exist + { + const Index previousProfile = m_data.upperProfile(inner); + + m_data.upperProfile(inner) = inner - outer; + + + const Index bandIncrement = m_data.upperProfile(inner) - previousProfile; + //shift data stored after this new one + const Index stop = m_colStartIndex[cols()]; + const Index start = m_colStartIndex[inner]; + + + for (Index innerIdx = stop; innerIdx >= start; innerIdx--) { + m_data.upper(innerIdx + bandIncrement) = m_data.upper(innerIdx); + } + + for (Index innerIdx = cols(); innerIdx > inner; innerIdx--) { + m_colStartIndex[innerIdx] += bandIncrement; + } + + //zeros new data + memset(this->_upperPtr() + start, 0, (bandIncrement - 1) * sizeof (Scalar)); + + return m_data.upper(m_colStartIndex[inner]); + } else { + return m_data.upper(m_colStartIndex[inner] + outer - (inner - m_data.upperProfile(inner))); + } + } + + if (outer > inner) //lower matrix + { + const Index minInnerIndex = outer - m_data.lowerProfile(outer); + if (inner < minInnerIndex) //The value does not yet exist + { + const Index previousProfile = m_data.lowerProfile(outer); + m_data.lowerProfile(outer) = outer - inner; + + const Index bandIncrement = m_data.lowerProfile(outer) - previousProfile; + //shift data stored after this new one + const Index stop = m_rowStartIndex[rows()]; + const Index start = m_rowStartIndex[outer]; + + + for (Index innerIdx = stop; innerIdx >= start; innerIdx--) { + m_data.lower(innerIdx + bandIncrement) = m_data.lower(innerIdx); + } + + for (Index innerIdx = rows(); innerIdx > outer; innerIdx--) { + m_rowStartIndex[innerIdx] += bandIncrement; + } + + //zeros new data + memset(this->_lowerPtr() + start, 0, (bandIncrement - 1) * sizeof (Scalar)); + return m_data.lower(m_rowStartIndex[outer]); + } else { + return m_data.lower(m_rowStartIndex[outer] + inner - (outer - m_data.lowerProfile(outer))); + } + } + } else { + if (outer > inner) //upper matrix + { + const Index maxOuterIndex = inner + m_data.upperProfile(inner); + if (outer > maxOuterIndex) //The value does not yet exist + { + const Index previousProfile = m_data.upperProfile(inner); + m_data.upperProfile(inner) = outer - inner; + + const Index bandIncrement = m_data.upperProfile(inner) - previousProfile; + //shift data stored after this new one + const Index stop = m_rowStartIndex[rows()]; + const Index start = m_rowStartIndex[inner + 1]; + + for (Index innerIdx = stop; innerIdx >= start; innerIdx--) { + m_data.upper(innerIdx + bandIncrement) = m_data.upper(innerIdx); + } + + for (Index innerIdx = inner + 1; innerIdx < outerSize() + 1; innerIdx++) { + m_rowStartIndex[innerIdx] += bandIncrement; + } + memset(this->_upperPtr() + m_rowStartIndex[inner] + previousProfile + 1, 0, (bandIncrement - 1) * sizeof (Scalar)); + return m_data.upper(m_rowStartIndex[inner] + m_data.upperProfile(inner)); + } else { + return m_data.upper(m_rowStartIndex[inner] + (outer - inner)); + } + } + + if (outer < inner) //lower matrix + { + const Index maxInnerIndex = outer + m_data.lowerProfile(outer); + if (inner > maxInnerIndex) //The value does not yet exist + { + const Index previousProfile = m_data.lowerProfile(outer); + m_data.lowerProfile(outer) = inner - outer; + + const Index bandIncrement = m_data.lowerProfile(outer) - previousProfile; + //shift data stored after this new one + const Index stop = m_colStartIndex[cols()]; + const Index start = m_colStartIndex[outer + 1]; + + for (Index innerIdx = stop; innerIdx >= start; innerIdx--) { + m_data.lower(innerIdx + bandIncrement) = m_data.lower(innerIdx); + } + + for (Index innerIdx = outer + 1; innerIdx < outerSize() + 1; innerIdx++) { + m_colStartIndex[innerIdx] += bandIncrement; + } + memset(this->_lowerPtr() + m_colStartIndex[outer] + previousProfile + 1, 0, (bandIncrement - 1) * sizeof (Scalar)); + return m_data.lower(m_colStartIndex[outer] + m_data.lowerProfile(outer)); + } else { + return m_data.lower(m_colStartIndex[outer] + (inner - outer)); + } + } + } + } + + /** Must be called after inserting a set of non zero entries. + */ + inline void finalize() { + if (IsRowMajor) { + if (rows() > cols()) + m_data.resize(cols(), cols(), rows(), m_colStartIndex[cols()] + 1, m_rowStartIndex[rows()] + 1); + else + m_data.resize(rows(), cols(), rows(), m_colStartIndex[cols()] + 1, m_rowStartIndex[rows()] + 1); + + // eigen_assert(rows() == cols() && "memory reorganisatrion only works with suare matrix"); + // + // Scalar* newArray = new Scalar[m_colStartIndex[cols()] + 1 + m_rowStartIndex[rows()] + 1]; + // Index dataIdx = 0; + // for (Index row = 0; row < rows(); row++) { + // + // const Index nbLowerElts = m_rowStartIndex[row + 1] - m_rowStartIndex[row]; + // // std::cout << "nbLowerElts" << nbLowerElts << std::endl; + // memcpy(newArray + dataIdx, m_data.m_lower + m_rowStartIndex[row], nbLowerElts * sizeof (Scalar)); + // m_rowStartIndex[row] = dataIdx; + // dataIdx += nbLowerElts; + // + // const Index nbUpperElts = m_colStartIndex[row + 1] - m_colStartIndex[row]; + // memcpy(newArray + dataIdx, m_data.m_upper + m_colStartIndex[row], nbUpperElts * sizeof (Scalar)); + // m_colStartIndex[row] = dataIdx; + // dataIdx += nbUpperElts; + // + // + // } + // //todo : don't access m_data profile directly : add an accessor from SkylineMatrix + // m_rowStartIndex[rows()] = m_rowStartIndex[rows()-1] + m_data.lowerProfile(rows()-1); + // m_colStartIndex[cols()] = m_colStartIndex[cols()-1] + m_data.upperProfile(cols()-1); + // + // delete[] m_data.m_lower; + // delete[] m_data.m_upper; + // + // m_data.m_lower = newArray; + // m_data.m_upper = newArray; + } else { + if (rows() > cols()) + m_data.resize(cols(), rows(), cols(), m_rowStartIndex[cols()] + 1, m_colStartIndex[cols()] + 1); + else + m_data.resize(rows(), rows(), cols(), m_rowStartIndex[rows()] + 1, m_colStartIndex[rows()] + 1); + } + } + + inline void squeeze() { + finalize(); + m_data.squeeze(); + } + + void prune(Scalar reference, RealScalar epsilon = dummy_precision<RealScalar > ()) { + //TODO + } + + /** Resizes the matrix to a \a rows x \a cols matrix and initializes it to zero + * \sa resizeNonZeros(Index), reserve(), setZero() + */ + void resize(size_t rows, size_t cols) { + const Index diagSize = rows > cols ? cols : rows; + m_innerSize = IsRowMajor ? cols : rows; + + eigen_assert(rows == cols && "Skyline matrix must be square matrix"); + + if (diagSize % 2) { // diagSize is odd + const Index k = (diagSize - 1) / 2; + + m_data.resize(diagSize, IsRowMajor ? cols : rows, IsRowMajor ? rows : cols, + 2 * k * k + k + 1, + 2 * k * k + k + 1); + + } else // diagSize is even + { + const Index k = diagSize / 2; + m_data.resize(diagSize, IsRowMajor ? cols : rows, IsRowMajor ? rows : cols, + 2 * k * k - k + 1, + 2 * k * k - k + 1); + } + + if (m_colStartIndex && m_rowStartIndex) { + delete[] m_colStartIndex; + delete[] m_rowStartIndex; + } + m_colStartIndex = new Index [cols + 1]; + m_rowStartIndex = new Index [rows + 1]; + m_outerSize = diagSize; + + m_data.reset(); + m_data.clear(); + + m_outerSize = diagSize; + memset(m_colStartIndex, 0, (cols + 1) * sizeof (Index)); + memset(m_rowStartIndex, 0, (rows + 1) * sizeof (Index)); + } + + void resizeNonZeros(Index size) { + m_data.resize(size); + } + + inline SkylineMatrix() + : m_outerSize(-1), m_innerSize(0), m_colStartIndex(0), m_rowStartIndex(0) { + resize(0, 0); + } + + inline SkylineMatrix(size_t rows, size_t cols) + : m_outerSize(0), m_innerSize(0), m_colStartIndex(0), m_rowStartIndex(0) { + resize(rows, cols); + } + + template<typename OtherDerived> + inline SkylineMatrix(const SkylineMatrixBase<OtherDerived>& other) + : m_outerSize(0), m_innerSize(0), m_colStartIndex(0), m_rowStartIndex(0) { + *this = other.derived(); + } + + inline SkylineMatrix(const SkylineMatrix & other) + : Base(), m_outerSize(0), m_innerSize(0), m_colStartIndex(0), m_rowStartIndex(0) { + *this = other.derived(); + } + + inline void swap(SkylineMatrix & other) { + //EIGEN_DBG_SKYLINE(std::cout << "SkylineMatrix:: swap\n"); + std::swap(m_colStartIndex, other.m_colStartIndex); + std::swap(m_rowStartIndex, other.m_rowStartIndex); + std::swap(m_innerSize, other.m_innerSize); + std::swap(m_outerSize, other.m_outerSize); + m_data.swap(other.m_data); + } + + inline SkylineMatrix & operator=(const SkylineMatrix & other) { + std::cout << "SkylineMatrix& operator=(const SkylineMatrix& other)\n"; + if (other.isRValue()) { + swap(other.const_cast_derived()); + } else { + resize(other.rows(), other.cols()); + memcpy(m_colStartIndex, other.m_colStartIndex, (m_outerSize + 1) * sizeof (Index)); + memcpy(m_rowStartIndex, other.m_rowStartIndex, (m_outerSize + 1) * sizeof (Index)); + m_data = other.m_data; + } + return *this; + } + + template<typename OtherDerived> + inline SkylineMatrix & operator=(const SkylineMatrixBase<OtherDerived>& other) { + const bool needToTranspose = (Flags & RowMajorBit) != (OtherDerived::Flags & RowMajorBit); + if (needToTranspose) { + // TODO + // return *this; + } else { + // there is no special optimization + return SkylineMatrixBase<SkylineMatrix>::operator=(other.derived()); + } + } + + friend std::ostream & operator <<(std::ostream & s, const SkylineMatrix & m) { + + EIGEN_DBG_SKYLINE( + std::cout << "upper elements : " << std::endl; + for (Index i = 0; i < m.m_data.upperSize(); i++) + std::cout << m.m_data.upper(i) << "\t"; + std::cout << std::endl; + std::cout << "upper profile : " << std::endl; + for (Index i = 0; i < m.m_data.upperProfileSize(); i++) + std::cout << m.m_data.upperProfile(i) << "\t"; + std::cout << std::endl; + std::cout << "lower startIdx : " << std::endl; + for (Index i = 0; i < m.m_data.upperProfileSize(); i++) + std::cout << (IsRowMajor ? m.m_colStartIndex[i] : m.m_rowStartIndex[i]) << "\t"; + std::cout << std::endl; + + + std::cout << "lower elements : " << std::endl; + for (Index i = 0; i < m.m_data.lowerSize(); i++) + std::cout << m.m_data.lower(i) << "\t"; + std::cout << std::endl; + std::cout << "lower profile : " << std::endl; + for (Index i = 0; i < m.m_data.lowerProfileSize(); i++) + std::cout << m.m_data.lowerProfile(i) << "\t"; + std::cout << std::endl; + std::cout << "lower startIdx : " << std::endl; + for (Index i = 0; i < m.m_data.lowerProfileSize(); i++) + std::cout << (IsRowMajor ? m.m_rowStartIndex[i] : m.m_colStartIndex[i]) << "\t"; + std::cout << std::endl; + ); + for (Index rowIdx = 0; rowIdx < m.rows(); rowIdx++) { + for (Index colIdx = 0; colIdx < m.cols(); colIdx++) { + s << m.coeff(rowIdx, colIdx) << "\t"; + } + s << std::endl; + } + return s; + } + + /** Destructor */ + inline ~SkylineMatrix() { + delete[] m_colStartIndex; + delete[] m_rowStartIndex; + } + + /** Overloaded for performance */ + Scalar sum() const; +}; + +template<typename Scalar, int _Options> +class SkylineMatrix<Scalar, _Options>::InnerUpperIterator { +public: + + InnerUpperIterator(const SkylineMatrix& mat, Index outer) + : m_matrix(mat), m_outer(outer), + m_id(_Options == RowMajor ? mat.m_colStartIndex[outer] : mat.m_rowStartIndex[outer] + 1), + m_start(m_id), + m_end(_Options == RowMajor ? mat.m_colStartIndex[outer + 1] : mat.m_rowStartIndex[outer + 1] + 1) { + } + + inline InnerUpperIterator & operator++() { + m_id++; + return *this; + } + + inline InnerUpperIterator & operator+=(Index shift) { + m_id += shift; + return *this; + } + + inline Scalar value() const { + return m_matrix.m_data.upper(m_id); + } + + inline Scalar* valuePtr() { + return const_cast<Scalar*> (&(m_matrix.m_data.upper(m_id))); + } + + inline Scalar& valueRef() { + return const_cast<Scalar&> (m_matrix.m_data.upper(m_id)); + } + + inline Index index() const { + return IsRowMajor ? m_outer - m_matrix.m_data.upperProfile(m_outer) + (m_id - m_start) : + m_outer + (m_id - m_start) + 1; + } + + inline Index row() const { + return IsRowMajor ? index() : m_outer; + } + + inline Index col() const { + return IsRowMajor ? m_outer : index(); + } + + inline size_t size() const { + return m_matrix.m_data.upperProfile(m_outer); + } + + inline operator bool() const { + return (m_id < m_end) && (m_id >= m_start); + } + +protected: + const SkylineMatrix& m_matrix; + const Index m_outer; + Index m_id; + const Index m_start; + const Index m_end; +}; + +template<typename Scalar, int _Options> +class SkylineMatrix<Scalar, _Options>::InnerLowerIterator { +public: + + InnerLowerIterator(const SkylineMatrix& mat, Index outer) + : m_matrix(mat), + m_outer(outer), + m_id(_Options == RowMajor ? mat.m_rowStartIndex[outer] : mat.m_colStartIndex[outer] + 1), + m_start(m_id), + m_end(_Options == RowMajor ? mat.m_rowStartIndex[outer + 1] : mat.m_colStartIndex[outer + 1] + 1) { + } + + inline InnerLowerIterator & operator++() { + m_id++; + return *this; + } + + inline InnerLowerIterator & operator+=(Index shift) { + m_id += shift; + return *this; + } + + inline Scalar value() const { + return m_matrix.m_data.lower(m_id); + } + + inline Scalar* valuePtr() { + return const_cast<Scalar*> (&(m_matrix.m_data.lower(m_id))); + } + + inline Scalar& valueRef() { + return const_cast<Scalar&> (m_matrix.m_data.lower(m_id)); + } + + inline Index index() const { + return IsRowMajor ? m_outer - m_matrix.m_data.lowerProfile(m_outer) + (m_id - m_start) : + m_outer + (m_id - m_start) + 1; + ; + } + + inline Index row() const { + return IsRowMajor ? m_outer : index(); + } + + inline Index col() const { + return IsRowMajor ? index() : m_outer; + } + + inline size_t size() const { + return m_matrix.m_data.lowerProfile(m_outer); + } + + inline operator bool() const { + return (m_id < m_end) && (m_id >= m_start); + } + +protected: + const SkylineMatrix& m_matrix; + const Index m_outer; + Index m_id; + const Index m_start; + const Index m_end; +}; + +} // end namespace Eigen + +#endif // EIGEN_SkylineMatrix_H |