| // This file is part of Eigen, a lightweight C++ template library |
| // for linear algebra. |
| // |
| // Copyright (C) 2008-2009 Guillaume Saupin <guillaume.saupin@cea.fr> |
| // |
| // Eigen is free software; you can redistribute it and/or |
| // modify it under the terms of the GNU Lesser General Public |
| // License as published by the Free Software Foundation; either |
| // version 3 of the License, or (at your option) any later version. |
| // |
| // Alternatively, you can redistribute it and/or |
| // modify it under the terms of the GNU General Public License as |
| // published by the Free Software Foundation; either version 2 of |
| // the License, or (at your option) any later version. |
| // |
| // Eigen is distributed in the hope that it will be useful, but WITHOUT ANY |
| // WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS |
| // FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the |
| // GNU General Public License for more details. |
| // |
| // You should have received a copy of the GNU Lesser General Public |
| // License and a copy of the GNU General Public License along with |
| // Eigen. If not, see <http://www.gnu.org/licenses/>. |
| |
| #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 |
