1e6c6c1576
For custom scalars, zero is not necessarily represented by a zeroed-out memory block (e.g. gnu MPFR). We therefore cannot rely on `memset` if we want to fill a matrix or tensor with zeroes. Instead, we should rely on `fill`, which for trivial types does end up getting converted to a `memset` under-the-hood (at least with gcc/clang). Requires adding a `fill(begin, end, v)` to `TensorDevice`. Replaced all potentially bad instances of memset with fill. Fixes #2245.
863 lines
30 KiB
C++
863 lines
30 KiB
C++
// This file is part of Eigen, a lightweight C++ template library
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// for linear algebra.
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//
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// Copyright (C) 2008-2009 Guillaume Saupin <guillaume.saupin@cea.fr>
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//
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// This Source Code Form is subject to the terms of the Mozilla
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// Public License v. 2.0. If a copy of the MPL was not distributed
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// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
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#ifndef EIGEN_SKYLINEMATRIX_H
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#define EIGEN_SKYLINEMATRIX_H
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#include "SkylineStorage.h"
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#include "SkylineMatrixBase.h"
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namespace Eigen {
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/** \ingroup Skyline_Module
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*
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* \class SkylineMatrix
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*
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* \brief The main skyline matrix class
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*
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* This class implements a skyline matrix using the very uncommon storage
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* scheme.
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*
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* \param _Scalar the scalar type, i.e. the type of the coefficients
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* \param _Options Union of bit flags controlling the storage scheme. Currently the only possibility
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* is RowMajor. The default is 0 which means column-major.
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*
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*
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*/
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namespace internal {
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template<typename _Scalar, int _Options>
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struct traits<SkylineMatrix<_Scalar, _Options> > {
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typedef _Scalar Scalar;
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typedef Sparse StorageKind;
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enum {
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RowsAtCompileTime = Dynamic,
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ColsAtCompileTime = Dynamic,
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MaxRowsAtCompileTime = Dynamic,
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MaxColsAtCompileTime = Dynamic,
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Flags = SkylineBit | _Options,
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CoeffReadCost = NumTraits<Scalar>::ReadCost,
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};
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};
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}
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template<typename _Scalar, int _Options>
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class SkylineMatrix
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: public SkylineMatrixBase<SkylineMatrix<_Scalar, _Options> > {
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public:
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EIGEN_SKYLINE_GENERIC_PUBLIC_INTERFACE(SkylineMatrix)
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EIGEN_SKYLINE_INHERIT_ASSIGNMENT_OPERATOR(SkylineMatrix, +=)
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EIGEN_SKYLINE_INHERIT_ASSIGNMENT_OPERATOR(SkylineMatrix, -=)
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using Base::IsRowMajor;
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protected:
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typedef SkylineMatrix<Scalar, (Flags&~RowMajorBit) | (IsRowMajor ? RowMajorBit : 0) > TransposedSkylineMatrix;
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Index m_outerSize;
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Index m_innerSize;
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public:
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Index* m_colStartIndex;
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Index* m_rowStartIndex;
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SkylineStorage<Scalar> m_data;
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public:
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inline Index rows() const {
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return IsRowMajor ? m_outerSize : m_innerSize;
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}
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inline Index cols() const {
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return IsRowMajor ? m_innerSize : m_outerSize;
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}
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inline Index innerSize() const {
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return m_innerSize;
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}
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inline Index outerSize() const {
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return m_outerSize;
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}
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inline Index upperNonZeros() const {
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return m_data.upperSize();
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}
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inline Index lowerNonZeros() const {
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return m_data.lowerSize();
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}
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inline Index upperNonZeros(Index j) const {
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return m_colStartIndex[j + 1] - m_colStartIndex[j];
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}
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inline Index lowerNonZeros(Index j) const {
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return m_rowStartIndex[j + 1] - m_rowStartIndex[j];
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}
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inline const Scalar* _diagPtr() const {
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return &m_data.diag(0);
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}
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inline Scalar* _diagPtr() {
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return &m_data.diag(0);
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}
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inline const Scalar* _upperPtr() const {
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return &m_data.upper(0);
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}
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inline Scalar* _upperPtr() {
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return &m_data.upper(0);
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}
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inline const Scalar* _lowerPtr() const {
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return &m_data.lower(0);
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}
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inline Scalar* _lowerPtr() {
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return &m_data.lower(0);
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}
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inline const Index* _upperProfilePtr() const {
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return &m_data.upperProfile(0);
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}
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inline Index* _upperProfilePtr() {
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return &m_data.upperProfile(0);
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}
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inline const Index* _lowerProfilePtr() const {
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return &m_data.lowerProfile(0);
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}
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inline Index* _lowerProfilePtr() {
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return &m_data.lowerProfile(0);
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}
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inline Scalar coeff(Index row, Index col) const {
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const Index outer = IsRowMajor ? row : col;
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const Index inner = IsRowMajor ? col : row;
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eigen_assert(outer < outerSize());
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eigen_assert(inner < innerSize());
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if (outer == inner)
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return this->m_data.diag(outer);
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if (IsRowMajor) {
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if (inner > outer) //upper matrix
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{
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const Index minOuterIndex = inner - m_data.upperProfile(inner);
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if (outer >= minOuterIndex)
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return this->m_data.upper(m_colStartIndex[inner] + outer - (inner - m_data.upperProfile(inner)));
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else
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return Scalar(0);
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}
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if (inner < outer) //lower matrix
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{
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const Index minInnerIndex = outer - m_data.lowerProfile(outer);
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if (inner >= minInnerIndex)
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return this->m_data.lower(m_rowStartIndex[outer] + inner - (outer - m_data.lowerProfile(outer)));
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else
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return Scalar(0);
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}
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return m_data.upper(m_colStartIndex[inner] + outer - inner);
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} else {
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if (outer > inner) //upper matrix
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{
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const Index maxOuterIndex = inner + m_data.upperProfile(inner);
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if (outer <= maxOuterIndex)
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return this->m_data.upper(m_colStartIndex[inner] + (outer - inner));
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else
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return Scalar(0);
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}
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if (outer < inner) //lower matrix
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{
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const Index maxInnerIndex = outer + m_data.lowerProfile(outer);
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if (inner <= maxInnerIndex)
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return this->m_data.lower(m_rowStartIndex[outer] + (inner - outer));
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else
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return Scalar(0);
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}
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}
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}
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inline Scalar& coeffRef(Index row, Index col) {
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const Index outer = IsRowMajor ? row : col;
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const Index inner = IsRowMajor ? col : row;
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eigen_assert(outer < outerSize());
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eigen_assert(inner < innerSize());
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if (outer == inner)
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return this->m_data.diag(outer);
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if (IsRowMajor) {
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if (col > row) //upper matrix
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{
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const Index minOuterIndex = inner - m_data.upperProfile(inner);
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eigen_assert(outer >= minOuterIndex && "You tried to access a coeff that does not exist in the storage");
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return this->m_data.upper(m_colStartIndex[inner] + outer - (inner - m_data.upperProfile(inner)));
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}
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if (col < row) //lower matrix
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{
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const Index minInnerIndex = outer - m_data.lowerProfile(outer);
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eigen_assert(inner >= minInnerIndex && "You tried to access a coeff that does not exist in the storage");
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return this->m_data.lower(m_rowStartIndex[outer] + inner - (outer - m_data.lowerProfile(outer)));
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}
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} else {
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if (outer > inner) //upper matrix
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{
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const Index maxOuterIndex = inner + m_data.upperProfile(inner);
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eigen_assert(outer <= maxOuterIndex && "You tried to access a coeff that does not exist in the storage");
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return this->m_data.upper(m_colStartIndex[inner] + (outer - inner));
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}
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if (outer < inner) //lower matrix
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{
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const Index maxInnerIndex = outer + m_data.lowerProfile(outer);
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eigen_assert(inner <= maxInnerIndex && "You tried to access a coeff that does not exist in the storage");
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return this->m_data.lower(m_rowStartIndex[outer] + (inner - outer));
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}
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}
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}
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inline Scalar coeffDiag(Index idx) const {
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eigen_assert(idx < outerSize());
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eigen_assert(idx < innerSize());
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return this->m_data.diag(idx);
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}
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inline Scalar coeffLower(Index row, Index col) const {
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const Index outer = IsRowMajor ? row : col;
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const Index inner = IsRowMajor ? col : row;
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eigen_assert(outer < outerSize());
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eigen_assert(inner < innerSize());
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eigen_assert(inner != outer);
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if (IsRowMajor) {
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const Index minInnerIndex = outer - m_data.lowerProfile(outer);
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if (inner >= minInnerIndex)
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return this->m_data.lower(m_rowStartIndex[outer] + inner - (outer - m_data.lowerProfile(outer)));
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else
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return Scalar(0);
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} else {
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const Index maxInnerIndex = outer + m_data.lowerProfile(outer);
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if (inner <= maxInnerIndex)
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return this->m_data.lower(m_rowStartIndex[outer] + (inner - outer));
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else
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return Scalar(0);
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}
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}
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inline Scalar coeffUpper(Index row, Index col) const {
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const Index outer = IsRowMajor ? row : col;
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const Index inner = IsRowMajor ? col : row;
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eigen_assert(outer < outerSize());
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eigen_assert(inner < innerSize());
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eigen_assert(inner != outer);
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if (IsRowMajor) {
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const Index minOuterIndex = inner - m_data.upperProfile(inner);
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if (outer >= minOuterIndex)
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return this->m_data.upper(m_colStartIndex[inner] + outer - (inner - m_data.upperProfile(inner)));
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else
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return Scalar(0);
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} else {
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const Index maxOuterIndex = inner + m_data.upperProfile(inner);
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if (outer <= maxOuterIndex)
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return this->m_data.upper(m_colStartIndex[inner] + (outer - inner));
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else
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return Scalar(0);
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}
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}
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inline Scalar& coeffRefDiag(Index idx) {
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eigen_assert(idx < outerSize());
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eigen_assert(idx < innerSize());
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return this->m_data.diag(idx);
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}
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inline Scalar& coeffRefLower(Index row, Index col) {
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const Index outer = IsRowMajor ? row : col;
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const Index inner = IsRowMajor ? col : row;
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eigen_assert(outer < outerSize());
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eigen_assert(inner < innerSize());
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eigen_assert(inner != outer);
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if (IsRowMajor) {
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const Index minInnerIndex = outer - m_data.lowerProfile(outer);
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eigen_assert(inner >= minInnerIndex && "You tried to access a coeff that does not exist in the storage");
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return this->m_data.lower(m_rowStartIndex[outer] + inner - (outer - m_data.lowerProfile(outer)));
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} else {
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const Index maxInnerIndex = outer + m_data.lowerProfile(outer);
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eigen_assert(inner <= maxInnerIndex && "You tried to access a coeff that does not exist in the storage");
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return this->m_data.lower(m_rowStartIndex[outer] + (inner - outer));
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}
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}
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inline bool coeffExistLower(Index row, Index col) {
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const Index outer = IsRowMajor ? row : col;
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const Index inner = IsRowMajor ? col : row;
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eigen_assert(outer < outerSize());
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eigen_assert(inner < innerSize());
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eigen_assert(inner != outer);
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if (IsRowMajor) {
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const Index minInnerIndex = outer - m_data.lowerProfile(outer);
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return inner >= minInnerIndex;
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} else {
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const Index maxInnerIndex = outer + m_data.lowerProfile(outer);
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return inner <= maxInnerIndex;
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}
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}
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inline Scalar& coeffRefUpper(Index row, Index col) {
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const Index outer = IsRowMajor ? row : col;
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const Index inner = IsRowMajor ? col : row;
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eigen_assert(outer < outerSize());
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eigen_assert(inner < innerSize());
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eigen_assert(inner != outer);
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if (IsRowMajor) {
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const Index minOuterIndex = inner - m_data.upperProfile(inner);
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eigen_assert(outer >= minOuterIndex && "You tried to access a coeff that does not exist in the storage");
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return this->m_data.upper(m_colStartIndex[inner] + outer - (inner - m_data.upperProfile(inner)));
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} else {
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const Index maxOuterIndex = inner + m_data.upperProfile(inner);
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eigen_assert(outer <= maxOuterIndex && "You tried to access a coeff that does not exist in the storage");
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return this->m_data.upper(m_colStartIndex[inner] + (outer - inner));
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}
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}
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inline bool coeffExistUpper(Index row, Index col) {
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const Index outer = IsRowMajor ? row : col;
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const Index inner = IsRowMajor ? col : row;
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eigen_assert(outer < outerSize());
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eigen_assert(inner < innerSize());
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eigen_assert(inner != outer);
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if (IsRowMajor) {
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const Index minOuterIndex = inner - m_data.upperProfile(inner);
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return outer >= minOuterIndex;
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} else {
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const Index maxOuterIndex = inner + m_data.upperProfile(inner);
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return outer <= maxOuterIndex;
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}
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}
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protected:
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public:
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class InnerUpperIterator;
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class InnerLowerIterator;
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class OuterUpperIterator;
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class OuterLowerIterator;
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/** Removes all non zeros */
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inline void setZero() {
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m_data.clear();
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std::fill_n(m_colStartIndex, m_outerSize + 1, Index(0));
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std::fill_n(m_rowStartIndex, m_outerSize + 1, Index(0));
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}
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/** \returns the number of non zero coefficients */
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inline Index nonZeros() const {
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return m_data.diagSize() + m_data.upperSize() + m_data.lowerSize();
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}
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/** Preallocates \a reserveSize non zeros */
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inline void reserve(Index reserveSize, Index reserveUpperSize, Index reserveLowerSize) {
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m_data.reserve(reserveSize, reserveUpperSize, reserveLowerSize);
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}
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/** \returns a reference to a novel non zero coefficient with coordinates \a row x \a col.
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*
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* \warning This function can be extremely slow if the non zero coefficients
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* are not inserted in a coherent order.
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*
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* After an insertion session, you should call the finalize() function.
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*/
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EIGEN_DONT_INLINE Scalar & insert(Index row, Index col) {
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const Index outer = IsRowMajor ? row : col;
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const Index inner = IsRowMajor ? col : row;
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eigen_assert(outer < outerSize());
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eigen_assert(inner < innerSize());
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if (outer == inner)
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return m_data.diag(col);
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if (IsRowMajor) {
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if (outer < inner) //upper matrix
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{
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Index minOuterIndex = 0;
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minOuterIndex = inner - m_data.upperProfile(inner);
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if (outer < minOuterIndex) //The value does not yet exist
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{
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const Index previousProfile = m_data.upperProfile(inner);
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m_data.upperProfile(inner) = inner - outer;
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const Index bandIncrement = m_data.upperProfile(inner) - previousProfile;
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//shift data stored after this new one
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const Index stop = m_colStartIndex[cols()];
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const Index start = m_colStartIndex[inner];
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for (Index innerIdx = stop; innerIdx >= start; innerIdx--) {
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m_data.upper(innerIdx + bandIncrement) = m_data.upper(innerIdx);
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}
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for (Index innerIdx = cols(); innerIdx > inner; innerIdx--) {
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m_colStartIndex[innerIdx] += bandIncrement;
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}
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//zeros new data
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std::fill_n(this->_upperPtr() + start, bandIncrement - 1, Scalar(0));
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return m_data.upper(m_colStartIndex[inner]);
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} else {
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return m_data.upper(m_colStartIndex[inner] + outer - (inner - m_data.upperProfile(inner)));
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}
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}
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if (outer > inner) //lower matrix
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{
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const Index minInnerIndex = outer - m_data.lowerProfile(outer);
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if (inner < minInnerIndex) //The value does not yet exist
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{
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const Index previousProfile = m_data.lowerProfile(outer);
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m_data.lowerProfile(outer) = outer - inner;
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const Index bandIncrement = m_data.lowerProfile(outer) - previousProfile;
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//shift data stored after this new one
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const Index stop = m_rowStartIndex[rows()];
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const Index start = m_rowStartIndex[outer];
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for (Index innerIdx = stop; innerIdx >= start; innerIdx--) {
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m_data.lower(innerIdx + bandIncrement) = m_data.lower(innerIdx);
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}
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for (Index innerIdx = rows(); innerIdx > outer; innerIdx--) {
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m_rowStartIndex[innerIdx] += bandIncrement;
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}
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//zeros new data
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std::fill_n(this->_lowerPtr() + start, bandIncrement - 1, Scalar(0));
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return m_data.lower(m_rowStartIndex[outer]);
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} else {
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return m_data.lower(m_rowStartIndex[outer] + inner - (outer - m_data.lowerProfile(outer)));
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}
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}
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} else {
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if (outer > inner) //upper matrix
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{
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const Index maxOuterIndex = inner + m_data.upperProfile(inner);
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if (outer > maxOuterIndex) //The value does not yet exist
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{
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const Index previousProfile = m_data.upperProfile(inner);
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m_data.upperProfile(inner) = outer - inner;
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const Index bandIncrement = m_data.upperProfile(inner) - previousProfile;
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//shift data stored after this new one
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const Index stop = m_rowStartIndex[rows()];
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const Index start = m_rowStartIndex[inner + 1];
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for (Index innerIdx = stop; innerIdx >= start; innerIdx--) {
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m_data.upper(innerIdx + bandIncrement) = m_data.upper(innerIdx);
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}
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for (Index innerIdx = inner + 1; innerIdx < outerSize() + 1; innerIdx++) {
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m_rowStartIndex[innerIdx] += bandIncrement;
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}
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std::fill_n(this->_upperPtr() + m_rowStartIndex[inner] + previousProfile + 1, bandIncrement - 1, Scalar(0));
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return m_data.upper(m_rowStartIndex[inner] + m_data.upperProfile(inner));
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} else {
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return m_data.upper(m_rowStartIndex[inner] + (outer - inner));
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}
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}
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if (outer < inner) //lower matrix
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{
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const Index maxInnerIndex = outer + m_data.lowerProfile(outer);
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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;
|
|
}
|
|
std::fill_n(this->_lowerPtr() + m_colStartIndex[outer] + previousProfile + 1, bandIncrement - 1, Scalar(0));
|
|
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;
|
|
std::fill_n(m_colStartIndex, cols + 1, Index(0));
|
|
std::fill_n(m_rowStartIndex, rows + 1, Index(0));
|
|
}
|
|
|
|
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
|