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+// 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
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