| // 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 tried to access a coeff that does 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 tried to access a coeff that does 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 tried to access a coeff that does 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 tried to access a coeff that does 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 tried to access a coeff that does 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 tried to access a coeff that does 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 tried to access a coeff that does 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 tried to access a coeff that does 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 |