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(j,k) += alpha * i.value() * rhs(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(i.index(),k); 328 res(i.index(),k) += numext::conj(lhs_ij) * rhs_j; 329 } 330 res(j,k) += alpha * res_j; 331 332 // handle diagonal coeff 333 if (ProcessFirstHalf && i && (i.index()==j)) 334 res(j,k) += alpha * i.value() * rhs(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