1 | // This file is part of Eigen, a lightweight C++ template library |
2 | // for linear algebra. |
3 | // |
4 | // Copyright (C) 2009-2014 Gael Guennebaud <gael.guennebaud@inria.fr> |
5 | // |
6 | // This Source Code Form is subject to the terms of the Mozilla |
7 | // Public License v. 2.0. If a copy of the MPL was not distributed |
8 | // with this file, You can obtain one at http://mozilla.org/MPL/2.0/. |
9 | |
10 | #ifndef EIGEN_SPARSE_SELFADJOINTVIEW_H |
11 | #define EIGEN_SPARSE_SELFADJOINTVIEW_H |
12 | |
13 | namespace Eigen { |
14 | |
15 | /** \ingroup SparseCore_Module |
16 | * \class SparseSelfAdjointView |
17 | * |
18 | * \brief Pseudo expression to manipulate a triangular sparse matrix as a selfadjoint matrix. |
19 | * |
20 | * \param MatrixType the type of the dense matrix storing the coefficients |
21 | * \param Mode can be either \c #Lower or \c #Upper |
22 | * |
23 | * This class is an expression of a sefladjoint matrix from a triangular part of a matrix |
24 | * with given dense storage of the coefficients. It is the return type of MatrixBase::selfadjointView() |
25 | * and most of the time this is the only way that it is used. |
26 | * |
27 | * \sa SparseMatrixBase::selfadjointView() |
28 | */ |
29 | namespace internal { |
30 | |
31 | template<typename MatrixType, unsigned int Mode> |
32 | struct traits<SparseSelfAdjointView<MatrixType,Mode> > : traits<MatrixType> { |
33 | }; |
34 | |
35 | template<int SrcMode,int DstMode,typename MatrixType,int DestOrder> |
36 | void permute_symm_to_symm(const MatrixType& mat, SparseMatrix<typename MatrixType::Scalar,DestOrder,typename MatrixType::StorageIndex>& _dest, const typename MatrixType::StorageIndex* perm = 0); |
37 | |
38 | template<int Mode,typename MatrixType,int DestOrder> |
39 | void permute_symm_to_fullsymm(const MatrixType& mat, SparseMatrix<typename MatrixType::Scalar,DestOrder,typename MatrixType::StorageIndex>& _dest, const typename MatrixType::StorageIndex* perm = 0); |
40 | |
41 | } |
42 | |
43 | template<typename MatrixType, unsigned int _Mode> class SparseSelfAdjointView |
44 | : public EigenBase<SparseSelfAdjointView<MatrixType,_Mode> > |
45 | { |
46 | public: |
47 | |
48 | enum { |
49 | Mode = _Mode, |
50 | TransposeMode = ((Mode & Upper) ? Lower : 0) | ((Mode & Lower) ? Upper : 0), |
51 | RowsAtCompileTime = internal::traits<SparseSelfAdjointView>::RowsAtCompileTime, |
52 | ColsAtCompileTime = internal::traits<SparseSelfAdjointView>::ColsAtCompileTime |
53 | }; |
54 | |
55 | typedef EigenBase<SparseSelfAdjointView> Base; |
56 | typedef typename MatrixType::Scalar Scalar; |
57 | typedef typename MatrixType::StorageIndex StorageIndex; |
58 | typedef Matrix<StorageIndex,Dynamic,1> VectorI; |
59 | typedef typename internal::ref_selector<MatrixType>::non_const_type MatrixTypeNested; |
60 | typedef typename internal::remove_all<MatrixTypeNested>::type _MatrixTypeNested; |
61 | |
62 | explicit inline SparseSelfAdjointView(MatrixType& matrix) : m_matrix(matrix) |
63 | { |
64 | eigen_assert(rows()==cols() && "SelfAdjointView is only for squared matrices" ); |
65 | } |
66 | |
67 | inline Index rows() const { return m_matrix.rows(); } |
68 | inline Index cols() const { return m_matrix.cols(); } |
69 | |
70 | /** \internal \returns a reference to the nested matrix */ |
71 | const _MatrixTypeNested& matrix() const { return m_matrix; } |
72 | typename internal::remove_reference<MatrixTypeNested>::type& matrix() { return m_matrix; } |
73 | |
74 | /** \returns an expression of the matrix product between a sparse self-adjoint matrix \c *this and a sparse matrix \a rhs. |
75 | * |
76 | * Note that there is no algorithmic advantage of performing such a product compared to a general sparse-sparse matrix product. |
77 | * Indeed, the SparseSelfadjointView operand is first copied into a temporary SparseMatrix before computing the product. |
78 | */ |
79 | template<typename OtherDerived> |
80 | Product<SparseSelfAdjointView, OtherDerived> |
81 | operator*(const SparseMatrixBase<OtherDerived>& rhs) const |
82 | { |
83 | return Product<SparseSelfAdjointView, OtherDerived>(*this, rhs.derived()); |
84 | } |
85 | |
86 | /** \returns an expression of the matrix product between a sparse matrix \a lhs and a sparse self-adjoint matrix \a rhs. |
87 | * |
88 | * Note that there is no algorithmic advantage of performing such a product compared to a general sparse-sparse matrix product. |
89 | * Indeed, the SparseSelfadjointView operand is first copied into a temporary SparseMatrix before computing the product. |
90 | */ |
91 | template<typename OtherDerived> friend |
92 | Product<OtherDerived, SparseSelfAdjointView> |
93 | operator*(const SparseMatrixBase<OtherDerived>& lhs, const SparseSelfAdjointView& rhs) |
94 | { |
95 | return Product<OtherDerived, SparseSelfAdjointView>(lhs.derived(), rhs); |
96 | } |
97 | |
98 | /** Efficient sparse self-adjoint matrix times dense vector/matrix product */ |
99 | template<typename OtherDerived> |
100 | Product<SparseSelfAdjointView,OtherDerived> |
101 | operator*(const MatrixBase<OtherDerived>& rhs) const |
102 | { |
103 | return Product<SparseSelfAdjointView,OtherDerived>(*this, rhs.derived()); |
104 | } |
105 | |
106 | /** Efficient dense vector/matrix times sparse self-adjoint matrix product */ |
107 | template<typename OtherDerived> friend |
108 | Product<OtherDerived,SparseSelfAdjointView> |
109 | operator*(const MatrixBase<OtherDerived>& lhs, const SparseSelfAdjointView& rhs) |
110 | { |
111 | return Product<OtherDerived,SparseSelfAdjointView>(lhs.derived(), rhs); |
112 | } |
113 | |
114 | /** Perform a symmetric rank K update of the selfadjoint matrix \c *this: |
115 | * \f$ this = this + \alpha ( u u^* ) \f$ where \a u is a vector or matrix. |
116 | * |
117 | * \returns a reference to \c *this |
118 | * |
119 | * To perform \f$ this = this + \alpha ( u^* u ) \f$ you can simply |
120 | * call this function with u.adjoint(). |
121 | */ |
122 | template<typename DerivedU> |
123 | SparseSelfAdjointView& rankUpdate(const SparseMatrixBase<DerivedU>& u, const Scalar& alpha = Scalar(1)); |
124 | |
125 | /** \returns an expression of P H P^-1 */ |
126 | // TODO implement twists in a more evaluator friendly fashion |
127 | SparseSymmetricPermutationProduct<_MatrixTypeNested,Mode> twistedBy(const PermutationMatrix<Dynamic,Dynamic,StorageIndex>& perm) const |
128 | { |
129 | return SparseSymmetricPermutationProduct<_MatrixTypeNested,Mode>(m_matrix, perm); |
130 | } |
131 | |
132 | template<typename SrcMatrixType,int SrcMode> |
133 | SparseSelfAdjointView& operator=(const SparseSymmetricPermutationProduct<SrcMatrixType,SrcMode>& permutedMatrix) |
134 | { |
135 | internal::call_assignment_no_alias_no_transpose(*this, permutedMatrix); |
136 | return *this; |
137 | } |
138 | |
139 | SparseSelfAdjointView& operator=(const SparseSelfAdjointView& src) |
140 | { |
141 | PermutationMatrix<Dynamic,Dynamic,StorageIndex> pnull; |
142 | return *this = src.twistedBy(pnull); |
143 | } |
144 | |
145 | template<typename SrcMatrixType,unsigned int SrcMode> |
146 | SparseSelfAdjointView& operator=(const SparseSelfAdjointView<SrcMatrixType,SrcMode>& src) |
147 | { |
148 | PermutationMatrix<Dynamic,Dynamic,StorageIndex> pnull; |
149 | return *this = src.twistedBy(pnull); |
150 | } |
151 | |
152 | void resize(Index rows, Index cols) |
153 | { |
154 | EIGEN_ONLY_USED_FOR_DEBUG(rows); |
155 | EIGEN_ONLY_USED_FOR_DEBUG(cols); |
156 | eigen_assert(rows == this->rows() && cols == this->cols() |
157 | && "SparseSelfadjointView::resize() does not actually allow to resize." ); |
158 | } |
159 | |
160 | protected: |
161 | |
162 | MatrixTypeNested m_matrix; |
163 | //mutable VectorI m_countPerRow; |
164 | //mutable VectorI m_countPerCol; |
165 | private: |
166 | template<typename Dest> void evalTo(Dest &) const; |
167 | }; |
168 | |
169 | /*************************************************************************** |
170 | * Implementation of SparseMatrixBase methods |
171 | ***************************************************************************/ |
172 | |
173 | template<typename Derived> |
174 | template<unsigned int UpLo> |
175 | typename SparseMatrixBase<Derived>::template ConstSelfAdjointViewReturnType<UpLo>::Type SparseMatrixBase<Derived>::selfadjointView() const |
176 | { |
177 | return SparseSelfAdjointView<const Derived, UpLo>(derived()); |
178 | } |
179 | |
180 | template<typename Derived> |
181 | template<unsigned int UpLo> |
182 | typename SparseMatrixBase<Derived>::template SelfAdjointViewReturnType<UpLo>::Type SparseMatrixBase<Derived>::selfadjointView() |
183 | { |
184 | return SparseSelfAdjointView<Derived, UpLo>(derived()); |
185 | } |
186 | |
187 | /*************************************************************************** |
188 | * Implementation of SparseSelfAdjointView methods |
189 | ***************************************************************************/ |
190 | |
191 | template<typename MatrixType, unsigned int Mode> |
192 | template<typename DerivedU> |
193 | SparseSelfAdjointView<MatrixType,Mode>& |
194 | SparseSelfAdjointView<MatrixType,Mode>::rankUpdate(const SparseMatrixBase<DerivedU>& u, const Scalar& alpha) |
195 | { |
196 | SparseMatrix<Scalar,(MatrixType::Flags&RowMajorBit)?RowMajor:ColMajor> tmp = u * u.adjoint(); |
197 | if(alpha==Scalar(0)) |
198 | m_matrix = tmp.template triangularView<Mode>(); |
199 | else |
200 | m_matrix += alpha * tmp.template triangularView<Mode>(); |
201 | |
202 | return *this; |
203 | } |
204 | |
205 | namespace internal { |
206 | |
207 | // TODO currently a selfadjoint expression has the form SelfAdjointView<.,.> |
208 | // in the future selfadjoint-ness should be defined by the expression traits |
209 | // such that Transpose<SelfAdjointView<.,.> > is valid. (currently TriangularBase::transpose() is overloaded to make it work) |
210 | template<typename MatrixType, unsigned int Mode> |
211 | struct evaluator_traits<SparseSelfAdjointView<MatrixType,Mode> > |
212 | { |
213 | typedef typename storage_kind_to_evaluator_kind<typename MatrixType::StorageKind>::Kind Kind; |
214 | typedef SparseSelfAdjointShape Shape; |
215 | }; |
216 | |
217 | struct SparseSelfAdjoint2Sparse {}; |
218 | |
219 | template<> struct AssignmentKind<SparseShape,SparseSelfAdjointShape> { typedef SparseSelfAdjoint2Sparse Kind; }; |
220 | template<> struct AssignmentKind<SparseSelfAdjointShape,SparseShape> { typedef Sparse2Sparse Kind; }; |
221 | |
222 | template< typename DstXprType, typename SrcXprType, typename Functor> |
223 | struct Assignment<DstXprType, SrcXprType, Functor, SparseSelfAdjoint2Sparse> |
224 | { |
225 | typedef typename DstXprType::StorageIndex StorageIndex; |
226 | typedef internal::assign_op<typename DstXprType::Scalar,typename SrcXprType::Scalar> AssignOpType; |
227 | |
228 | template<typename DestScalar,int StorageOrder> |
229 | static void run(SparseMatrix<DestScalar,StorageOrder,StorageIndex> &dst, const SrcXprType &src, const AssignOpType&/*func*/) |
230 | { |
231 | internal::permute_symm_to_fullsymm<SrcXprType::Mode>(src.matrix(), dst); |
232 | } |
233 | |
234 | // FIXME: the handling of += and -= in sparse matrices should be cleanup so that next two overloads could be reduced to: |
235 | template<typename DestScalar,int StorageOrder,typename AssignFunc> |
236 | static void run(SparseMatrix<DestScalar,StorageOrder,StorageIndex> &dst, const SrcXprType &src, const AssignFunc& func) |
237 | { |
238 | SparseMatrix<DestScalar,StorageOrder,StorageIndex> tmp(src.rows(),src.cols()); |
239 | run(tmp, src, AssignOpType()); |
240 | call_assignment_no_alias_no_transpose(dst, tmp, func); |
241 | } |
242 | |
243 | template<typename DestScalar,int StorageOrder> |
244 | static void run(SparseMatrix<DestScalar,StorageOrder,StorageIndex> &dst, const SrcXprType &src, |
245 | const internal::add_assign_op<typename DstXprType::Scalar,typename SrcXprType::Scalar>& /* func */) |
246 | { |
247 | SparseMatrix<DestScalar,StorageOrder,StorageIndex> tmp(src.rows(),src.cols()); |
248 | run(tmp, src, AssignOpType()); |
249 | dst += tmp; |
250 | } |
251 | |
252 | template<typename DestScalar,int StorageOrder> |
253 | static void run(SparseMatrix<DestScalar,StorageOrder,StorageIndex> &dst, const SrcXprType &src, |
254 | const internal::sub_assign_op<typename DstXprType::Scalar,typename SrcXprType::Scalar>& /* func */) |
255 | { |
256 | SparseMatrix<DestScalar,StorageOrder,StorageIndex> tmp(src.rows(),src.cols()); |
257 | run(tmp, src, AssignOpType()); |
258 | dst -= tmp; |
259 | } |
260 | |
261 | template<typename DestScalar> |
262 | static void run(DynamicSparseMatrix<DestScalar,ColMajor,StorageIndex>& dst, const SrcXprType &src, const AssignOpType&/*func*/) |
263 | { |
264 | // TODO directly evaluate into dst; |
265 | SparseMatrix<DestScalar,ColMajor,StorageIndex> tmp(dst.rows(),dst.cols()); |
266 | internal::permute_symm_to_fullsymm<SrcXprType::Mode>(src.matrix(), tmp); |
267 | dst = tmp; |
268 | } |
269 | }; |
270 | |
271 | } // end namespace internal |
272 | |
273 | /*************************************************************************** |
274 | * Implementation of sparse self-adjoint time dense matrix |
275 | ***************************************************************************/ |
276 | |
277 | namespace internal { |
278 | |
279 | template<int Mode, typename SparseLhsType, typename DenseRhsType, typename DenseResType, typename AlphaType> |
280 | inline void sparse_selfadjoint_time_dense_product(const SparseLhsType& lhs, const DenseRhsType& rhs, DenseResType& res, const AlphaType& alpha) |
281 | { |
282 | EIGEN_ONLY_USED_FOR_DEBUG(alpha); |
283 | |
284 | typedef typename internal::nested_eval<SparseLhsType,DenseRhsType::MaxColsAtCompileTime>::type SparseLhsTypeNested; |
285 | typedef typename internal::remove_all<SparseLhsTypeNested>::type SparseLhsTypeNestedCleaned; |
286 | typedef evaluator<SparseLhsTypeNestedCleaned> LhsEval; |
287 | typedef typename LhsEval::InnerIterator LhsIterator; |
288 | typedef typename SparseLhsType::Scalar LhsScalar; |
289 | |
290 | enum { |
291 | LhsIsRowMajor = (LhsEval::Flags&RowMajorBit)==RowMajorBit, |
292 | ProcessFirstHalf = |
293 | ((Mode&(Upper|Lower))==(Upper|Lower)) |
294 | || ( (Mode&Upper) && !LhsIsRowMajor) |
295 | || ( (Mode&Lower) && LhsIsRowMajor), |
296 | ProcessSecondHalf = !ProcessFirstHalf |
297 | }; |
298 | |
299 | SparseLhsTypeNested lhs_nested(lhs); |
300 | LhsEval lhsEval(lhs_nested); |
301 | |
302 | // work on one column at once |
303 | for (Index k=0; k<rhs.cols(); ++k) |
304 | { |
305 | for (Index j=0; j<lhs.outerSize(); ++j) |
306 | { |
307 | LhsIterator i(lhsEval,j); |
308 | // handle diagonal coeff |
309 | if (ProcessSecondHalf) |
310 | { |
311 | while (i && i.index()<j) ++i; |
312 | if(i && i.index()==j) |
313 | { |
314 | res.coeffRef(j,k) += alpha * i.value() * rhs.coeff(j,k); |
315 | ++i; |
316 | } |
317 | } |
318 | |
319 | // premultiplied rhs for scatters |
320 | typename ScalarBinaryOpTraits<AlphaType, typename DenseRhsType::Scalar>::ReturnType rhs_j(alpha*rhs(j,k)); |
321 | // accumulator for partial scalar product |
322 | typename DenseResType::Scalar res_j(0); |
323 | for(; (ProcessFirstHalf ? i && i.index() < j : i) ; ++i) |
324 | { |
325 | LhsScalar lhs_ij = i.value(); |
326 | if(!LhsIsRowMajor) lhs_ij = numext::conj(lhs_ij); |
327 | res_j += lhs_ij * rhs.coeff(i.index(),k); |
328 | res(i.index(),k) += numext::conj(lhs_ij) * rhs_j; |
329 | } |
330 | res.coeffRef(j,k) += alpha * res_j; |
331 | |
332 | // handle diagonal coeff |
333 | if (ProcessFirstHalf && i && (i.index()==j)) |
334 | res.coeffRef(j,k) += alpha * i.value() * rhs.coeff(j,k); |
335 | } |
336 | } |
337 | } |
338 | |
339 | |
340 | template<typename LhsView, typename Rhs, int ProductType> |
341 | struct generic_product_impl<LhsView, Rhs, SparseSelfAdjointShape, DenseShape, ProductType> |
342 | : generic_product_impl_base<LhsView, Rhs, generic_product_impl<LhsView, Rhs, SparseSelfAdjointShape, DenseShape, ProductType> > |
343 | { |
344 | template<typename Dest> |
345 | static void scaleAndAddTo(Dest& dst, const LhsView& lhsView, const Rhs& rhs, const typename Dest::Scalar& alpha) |
346 | { |
347 | typedef typename LhsView::_MatrixTypeNested Lhs; |
348 | typedef typename nested_eval<Lhs,Dynamic>::type LhsNested; |
349 | typedef typename nested_eval<Rhs,Dynamic>::type RhsNested; |
350 | LhsNested lhsNested(lhsView.matrix()); |
351 | RhsNested rhsNested(rhs); |
352 | |
353 | internal::sparse_selfadjoint_time_dense_product<LhsView::Mode>(lhsNested, rhsNested, dst, alpha); |
354 | } |
355 | }; |
356 | |
357 | template<typename Lhs, typename RhsView, int ProductType> |
358 | struct generic_product_impl<Lhs, RhsView, DenseShape, SparseSelfAdjointShape, ProductType> |
359 | : generic_product_impl_base<Lhs, RhsView, generic_product_impl<Lhs, RhsView, DenseShape, SparseSelfAdjointShape, ProductType> > |
360 | { |
361 | template<typename Dest> |
362 | static void scaleAndAddTo(Dest& dst, const Lhs& lhs, const RhsView& rhsView, const typename Dest::Scalar& alpha) |
363 | { |
364 | typedef typename RhsView::_MatrixTypeNested Rhs; |
365 | typedef typename nested_eval<Lhs,Dynamic>::type LhsNested; |
366 | typedef typename nested_eval<Rhs,Dynamic>::type RhsNested; |
367 | LhsNested lhsNested(lhs); |
368 | RhsNested rhsNested(rhsView.matrix()); |
369 | |
370 | // transpose everything |
371 | Transpose<Dest> dstT(dst); |
372 | internal::sparse_selfadjoint_time_dense_product<RhsView::TransposeMode>(rhsNested.transpose(), lhsNested.transpose(), dstT, alpha); |
373 | } |
374 | }; |
375 | |
376 | // NOTE: these two overloads are needed to evaluate the sparse selfadjoint view into a full sparse matrix |
377 | // TODO: maybe the copy could be handled by generic_product_impl so that these overloads would not be needed anymore |
378 | |
379 | template<typename LhsView, typename Rhs, int ProductTag> |
380 | struct product_evaluator<Product<LhsView, Rhs, DefaultProduct>, ProductTag, SparseSelfAdjointShape, SparseShape> |
381 | : public evaluator<typename Product<typename Rhs::PlainObject, Rhs, DefaultProduct>::PlainObject> |
382 | { |
383 | typedef Product<LhsView, Rhs, DefaultProduct> XprType; |
384 | typedef typename XprType::PlainObject PlainObject; |
385 | typedef evaluator<PlainObject> Base; |
386 | |
387 | product_evaluator(const XprType& xpr) |
388 | : m_lhs(xpr.lhs()), m_result(xpr.rows(), xpr.cols()) |
389 | { |
390 | ::new (static_cast<Base*>(this)) Base(m_result); |
391 | generic_product_impl<typename Rhs::PlainObject, Rhs, SparseShape, SparseShape, ProductTag>::evalTo(m_result, m_lhs, xpr.rhs()); |
392 | } |
393 | |
394 | protected: |
395 | typename Rhs::PlainObject m_lhs; |
396 | PlainObject m_result; |
397 | }; |
398 | |
399 | template<typename Lhs, typename RhsView, int ProductTag> |
400 | struct product_evaluator<Product<Lhs, RhsView, DefaultProduct>, ProductTag, SparseShape, SparseSelfAdjointShape> |
401 | : public evaluator<typename Product<Lhs, typename Lhs::PlainObject, DefaultProduct>::PlainObject> |
402 | { |
403 | typedef Product<Lhs, RhsView, DefaultProduct> XprType; |
404 | typedef typename XprType::PlainObject PlainObject; |
405 | typedef evaluator<PlainObject> Base; |
406 | |
407 | product_evaluator(const XprType& xpr) |
408 | : m_rhs(xpr.rhs()), m_result(xpr.rows(), xpr.cols()) |
409 | { |
410 | ::new (static_cast<Base*>(this)) Base(m_result); |
411 | generic_product_impl<Lhs, typename Lhs::PlainObject, SparseShape, SparseShape, ProductTag>::evalTo(m_result, xpr.lhs(), m_rhs); |
412 | } |
413 | |
414 | protected: |
415 | typename Lhs::PlainObject m_rhs; |
416 | PlainObject m_result; |
417 | }; |
418 | |
419 | } // namespace internal |
420 | |
421 | /*************************************************************************** |
422 | * Implementation of symmetric copies and permutations |
423 | ***************************************************************************/ |
424 | namespace internal { |
425 | |
426 | template<int Mode,typename MatrixType,int DestOrder> |
427 | void permute_symm_to_fullsymm(const MatrixType& mat, SparseMatrix<typename MatrixType::Scalar,DestOrder,typename MatrixType::StorageIndex>& _dest, const typename MatrixType::StorageIndex* perm) |
428 | { |
429 | typedef typename MatrixType::StorageIndex StorageIndex; |
430 | typedef typename MatrixType::Scalar Scalar; |
431 | typedef SparseMatrix<Scalar,DestOrder,StorageIndex> Dest; |
432 | typedef Matrix<StorageIndex,Dynamic,1> VectorI; |
433 | typedef evaluator<MatrixType> MatEval; |
434 | typedef typename evaluator<MatrixType>::InnerIterator MatIterator; |
435 | |
436 | MatEval matEval(mat); |
437 | Dest& dest(_dest.derived()); |
438 | enum { |
439 | StorageOrderMatch = int(Dest::IsRowMajor) == int(MatrixType::IsRowMajor) |
440 | }; |
441 | |
442 | Index size = mat.rows(); |
443 | VectorI count; |
444 | count.resize(size); |
445 | count.setZero(); |
446 | dest.resize(size,size); |
447 | for(Index j = 0; j<size; ++j) |
448 | { |
449 | Index jp = perm ? perm[j] : j; |
450 | for(MatIterator it(matEval,j); it; ++it) |
451 | { |
452 | Index i = it.index(); |
453 | Index r = it.row(); |
454 | Index c = it.col(); |
455 | Index ip = perm ? perm[i] : i; |
456 | if(Mode==(Upper|Lower)) |
457 | count[StorageOrderMatch ? jp : ip]++; |
458 | else if(r==c) |
459 | count[ip]++; |
460 | else if(( Mode==Lower && r>c) || ( Mode==Upper && r<c)) |
461 | { |
462 | count[ip]++; |
463 | count[jp]++; |
464 | } |
465 | } |
466 | } |
467 | Index nnz = count.sum(); |
468 | |
469 | // reserve space |
470 | dest.resizeNonZeros(nnz); |
471 | dest.outerIndexPtr()[0] = 0; |
472 | for(Index j=0; j<size; ++j) |
473 | dest.outerIndexPtr()[j+1] = dest.outerIndexPtr()[j] + count[j]; |
474 | for(Index j=0; j<size; ++j) |
475 | count[j] = dest.outerIndexPtr()[j]; |
476 | |
477 | // copy data |
478 | for(StorageIndex j = 0; j<size; ++j) |
479 | { |
480 | for(MatIterator it(matEval,j); it; ++it) |
481 | { |
482 | StorageIndex i = internal::convert_index<StorageIndex>(it.index()); |
483 | Index r = it.row(); |
484 | Index c = it.col(); |
485 | |
486 | StorageIndex jp = perm ? perm[j] : j; |
487 | StorageIndex ip = perm ? perm[i] : i; |
488 | |
489 | if(Mode==(Upper|Lower)) |
490 | { |
491 | Index k = count[StorageOrderMatch ? jp : ip]++; |
492 | dest.innerIndexPtr()[k] = StorageOrderMatch ? ip : jp; |
493 | dest.valuePtr()[k] = it.value(); |
494 | } |
495 | else if(r==c) |
496 | { |
497 | Index k = count[ip]++; |
498 | dest.innerIndexPtr()[k] = ip; |
499 | dest.valuePtr()[k] = it.value(); |
500 | } |
501 | else if(( (Mode&Lower)==Lower && r>c) || ( (Mode&Upper)==Upper && r<c)) |
502 | { |
503 | if(!StorageOrderMatch) |
504 | std::swap(ip,jp); |
505 | Index k = count[jp]++; |
506 | dest.innerIndexPtr()[k] = ip; |
507 | dest.valuePtr()[k] = it.value(); |
508 | k = count[ip]++; |
509 | dest.innerIndexPtr()[k] = jp; |
510 | dest.valuePtr()[k] = numext::conj(it.value()); |
511 | } |
512 | } |
513 | } |
514 | } |
515 | |
516 | template<int _SrcMode,int _DstMode,typename MatrixType,int DstOrder> |
517 | void permute_symm_to_symm(const MatrixType& mat, SparseMatrix<typename MatrixType::Scalar,DstOrder,typename MatrixType::StorageIndex>& _dest, const typename MatrixType::StorageIndex* perm) |
518 | { |
519 | typedef typename MatrixType::StorageIndex StorageIndex; |
520 | typedef typename MatrixType::Scalar Scalar; |
521 | SparseMatrix<Scalar,DstOrder,StorageIndex>& dest(_dest.derived()); |
522 | typedef Matrix<StorageIndex,Dynamic,1> VectorI; |
523 | typedef evaluator<MatrixType> MatEval; |
524 | typedef typename evaluator<MatrixType>::InnerIterator MatIterator; |
525 | |
526 | enum { |
527 | SrcOrder = MatrixType::IsRowMajor ? RowMajor : ColMajor, |
528 | StorageOrderMatch = int(SrcOrder) == int(DstOrder), |
529 | DstMode = DstOrder==RowMajor ? (_DstMode==Upper ? Lower : Upper) : _DstMode, |
530 | SrcMode = SrcOrder==RowMajor ? (_SrcMode==Upper ? Lower : Upper) : _SrcMode |
531 | }; |
532 | |
533 | MatEval matEval(mat); |
534 | |
535 | Index size = mat.rows(); |
536 | VectorI count(size); |
537 | count.setZero(); |
538 | dest.resize(size,size); |
539 | for(StorageIndex j = 0; j<size; ++j) |
540 | { |
541 | StorageIndex jp = perm ? perm[j] : j; |
542 | for(MatIterator it(matEval,j); it; ++it) |
543 | { |
544 | StorageIndex i = it.index(); |
545 | if((int(SrcMode)==int(Lower) && i<j) || (int(SrcMode)==int(Upper) && i>j)) |
546 | continue; |
547 | |
548 | StorageIndex ip = perm ? perm[i] : i; |
549 | count[int(DstMode)==int(Lower) ? (std::min)(ip,jp) : (std::max)(ip,jp)]++; |
550 | } |
551 | } |
552 | dest.outerIndexPtr()[0] = 0; |
553 | for(Index j=0; j<size; ++j) |
554 | dest.outerIndexPtr()[j+1] = dest.outerIndexPtr()[j] + count[j]; |
555 | dest.resizeNonZeros(dest.outerIndexPtr()[size]); |
556 | for(Index j=0; j<size; ++j) |
557 | count[j] = dest.outerIndexPtr()[j]; |
558 | |
559 | for(StorageIndex j = 0; j<size; ++j) |
560 | { |
561 | |
562 | for(MatIterator it(matEval,j); it; ++it) |
563 | { |
564 | StorageIndex i = it.index(); |
565 | if((int(SrcMode)==int(Lower) && i<j) || (int(SrcMode)==int(Upper) && i>j)) |
566 | continue; |
567 | |
568 | StorageIndex jp = perm ? perm[j] : j; |
569 | StorageIndex ip = perm? perm[i] : i; |
570 | |
571 | Index k = count[int(DstMode)==int(Lower) ? (std::min)(ip,jp) : (std::max)(ip,jp)]++; |
572 | dest.innerIndexPtr()[k] = int(DstMode)==int(Lower) ? (std::max)(ip,jp) : (std::min)(ip,jp); |
573 | |
574 | if(!StorageOrderMatch) std::swap(ip,jp); |
575 | if( ((int(DstMode)==int(Lower) && ip<jp) || (int(DstMode)==int(Upper) && ip>jp))) |
576 | dest.valuePtr()[k] = numext::conj(it.value()); |
577 | else |
578 | dest.valuePtr()[k] = it.value(); |
579 | } |
580 | } |
581 | } |
582 | |
583 | } |
584 | |
585 | // TODO implement twists in a more evaluator friendly fashion |
586 | |
587 | namespace internal { |
588 | |
589 | template<typename MatrixType, int Mode> |
590 | struct traits<SparseSymmetricPermutationProduct<MatrixType,Mode> > : traits<MatrixType> { |
591 | }; |
592 | |
593 | } |
594 | |
595 | template<typename MatrixType,int Mode> |
596 | class SparseSymmetricPermutationProduct |
597 | : public EigenBase<SparseSymmetricPermutationProduct<MatrixType,Mode> > |
598 | { |
599 | public: |
600 | typedef typename MatrixType::Scalar Scalar; |
601 | typedef typename MatrixType::StorageIndex StorageIndex; |
602 | enum { |
603 | RowsAtCompileTime = internal::traits<SparseSymmetricPermutationProduct>::RowsAtCompileTime, |
604 | ColsAtCompileTime = internal::traits<SparseSymmetricPermutationProduct>::ColsAtCompileTime |
605 | }; |
606 | protected: |
607 | typedef PermutationMatrix<Dynamic,Dynamic,StorageIndex> Perm; |
608 | public: |
609 | typedef Matrix<StorageIndex,Dynamic,1> VectorI; |
610 | typedef typename MatrixType::Nested MatrixTypeNested; |
611 | typedef typename internal::remove_all<MatrixTypeNested>::type NestedExpression; |
612 | |
613 | SparseSymmetricPermutationProduct(const MatrixType& mat, const Perm& perm) |
614 | : m_matrix(mat), m_perm(perm) |
615 | {} |
616 | |
617 | inline Index rows() const { return m_matrix.rows(); } |
618 | inline Index cols() const { return m_matrix.cols(); } |
619 | |
620 | const NestedExpression& matrix() const { return m_matrix; } |
621 | const Perm& perm() const { return m_perm; } |
622 | |
623 | protected: |
624 | MatrixTypeNested m_matrix; |
625 | const Perm& m_perm; |
626 | |
627 | }; |
628 | |
629 | namespace internal { |
630 | |
631 | template<typename DstXprType, typename MatrixType, int Mode, typename Scalar> |
632 | struct Assignment<DstXprType, SparseSymmetricPermutationProduct<MatrixType,Mode>, internal::assign_op<Scalar,typename MatrixType::Scalar>, Sparse2Sparse> |
633 | { |
634 | typedef SparseSymmetricPermutationProduct<MatrixType,Mode> SrcXprType; |
635 | typedef typename DstXprType::StorageIndex DstIndex; |
636 | template<int Options> |
637 | static void run(SparseMatrix<Scalar,Options,DstIndex> &dst, const SrcXprType &src, const internal::assign_op<Scalar,typename MatrixType::Scalar> &) |
638 | { |
639 | // internal::permute_symm_to_fullsymm<Mode>(m_matrix,_dest,m_perm.indices().data()); |
640 | SparseMatrix<Scalar,(Options&RowMajor)==RowMajor ? ColMajor : RowMajor, DstIndex> tmp; |
641 | internal::permute_symm_to_fullsymm<Mode>(src.matrix(),tmp,src.perm().indices().data()); |
642 | dst = tmp; |
643 | } |
644 | |
645 | template<typename DestType,unsigned int DestMode> |
646 | static void run(SparseSelfAdjointView<DestType,DestMode>& dst, const SrcXprType &src, const internal::assign_op<Scalar,typename MatrixType::Scalar> &) |
647 | { |
648 | internal::permute_symm_to_symm<Mode,DestMode>(src.matrix(),dst.matrix(),src.perm().indices().data()); |
649 | } |
650 | }; |
651 | |
652 | } // end namespace internal |
653 | |
654 | } // end namespace Eigen |
655 | |
656 | #endif // EIGEN_SPARSE_SELFADJOINTVIEW_H |
657 | |