SkylineMatrix.h
1 // This file is part of Eigen, a lightweight C++ template library
2 // for linear algebra.
3 //
4 // Copyright (C) 2008-2009 Guillaume Saupin <guillaume.saupin@cea.fr>
5 //
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24 
25 #ifndef EIGEN_SKYLINEMATRIX_H
26 #define EIGEN_SKYLINEMATRIX_H
27 
28 #include "SkylineStorage.h"
29 #include "SkylineMatrixBase.h"
30 
31 namespace Eigen {
32 
48 namespace internal {
49 template<typename _Scalar, int _Options>
50 struct traits<SkylineMatrix<_Scalar, _Options> > {
51  typedef _Scalar Scalar;
52  typedef Sparse StorageKind;
53 
54  enum {
55  RowsAtCompileTime = Dynamic,
56  ColsAtCompileTime = Dynamic,
57  MaxRowsAtCompileTime = Dynamic,
58  MaxColsAtCompileTime = Dynamic,
59  Flags = SkylineBit | _Options,
60  CoeffReadCost = NumTraits<Scalar>::ReadCost,
61  };
62 };
63 }
64 
65 template<typename _Scalar, int _Options>
67 : public SkylineMatrixBase<SkylineMatrix<_Scalar, _Options> > {
68 public:
69  EIGEN_SKYLINE_GENERIC_PUBLIC_INTERFACE(SkylineMatrix)
70  EIGEN_SKYLINE_INHERIT_ASSIGNMENT_OPERATOR(SkylineMatrix, +=)
71  EIGEN_SKYLINE_INHERIT_ASSIGNMENT_OPERATOR(SkylineMatrix, -=)
72 
73  using Base::IsRowMajor;
74 
75 protected:
76 
78 
79  Index m_outerSize;
80  Index m_innerSize;
81 
82 public:
83  Index* m_colStartIndex;
84  Index* m_rowStartIndex;
86 
87 public:
88 
89  inline Index rows() const {
90  return IsRowMajor ? m_outerSize : m_innerSize;
91  }
92 
93  inline Index cols() const {
94  return IsRowMajor ? m_innerSize : m_outerSize;
95  }
96 
97  inline Index innerSize() const {
98  return m_innerSize;
99  }
100 
101  inline Index outerSize() const {
102  return m_outerSize;
103  }
104 
105  inline Index upperNonZeros() const {
106  return m_data.upperSize();
107  }
108 
109  inline Index lowerNonZeros() const {
110  return m_data.lowerSize();
111  }
112 
113  inline Index upperNonZeros(Index j) const {
114  return m_colStartIndex[j + 1] - m_colStartIndex[j];
115  }
116 
117  inline Index lowerNonZeros(Index j) const {
118  return m_rowStartIndex[j + 1] - m_rowStartIndex[j];
119  }
120 
121  inline const Scalar* _diagPtr() const {
122  return &m_data.diag(0);
123  }
124 
125  inline Scalar* _diagPtr() {
126  return &m_data.diag(0);
127  }
128 
129  inline const Scalar* _upperPtr() const {
130  return &m_data.upper(0);
131  }
132 
133  inline Scalar* _upperPtr() {
134  return &m_data.upper(0);
135  }
136 
137  inline const Scalar* _lowerPtr() const {
138  return &m_data.lower(0);
139  }
140 
141  inline Scalar* _lowerPtr() {
142  return &m_data.lower(0);
143  }
144 
145  inline const Index* _upperProfilePtr() const {
146  return &m_data.upperProfile(0);
147  }
148 
149  inline Index* _upperProfilePtr() {
150  return &m_data.upperProfile(0);
151  }
152 
153  inline const Index* _lowerProfilePtr() const {
154  return &m_data.lowerProfile(0);
155  }
156 
157  inline Index* _lowerProfilePtr() {
158  return &m_data.lowerProfile(0);
159  }
160 
161  inline Scalar coeff(Index row, Index col) const {
162  const Index outer = IsRowMajor ? row : col;
163  const Index inner = IsRowMajor ? col : row;
164 
165  eigen_assert(outer < outerSize());
166  eigen_assert(inner < innerSize());
167 
168  if (outer == inner)
169  return this->m_data.diag(outer);
170 
171  if (IsRowMajor) {
172  if (inner > outer) //upper matrix
173  {
174  const Index minOuterIndex = inner - m_data.upperProfile(inner);
175  if (outer >= minOuterIndex)
176  return this->m_data.upper(m_colStartIndex[inner] + outer - (inner - m_data.upperProfile(inner)));
177  else
178  return Scalar(0);
179  }
180  if (inner < outer) //lower matrix
181  {
182  const Index minInnerIndex = outer - m_data.lowerProfile(outer);
183  if (inner >= minInnerIndex)
184  return this->m_data.lower(m_rowStartIndex[outer] + inner - (outer - m_data.lowerProfile(outer)));
185  else
186  return Scalar(0);
187  }
188  return m_data.upper(m_colStartIndex[inner] + outer - inner);
189  } else {
190  if (outer > inner) //upper matrix
191  {
192  const Index maxOuterIndex = inner + m_data.upperProfile(inner);
193  if (outer <= maxOuterIndex)
194  return this->m_data.upper(m_colStartIndex[inner] + (outer - inner));
195  else
196  return Scalar(0);
197  }
198  if (outer < inner) //lower matrix
199  {
200  const Index maxInnerIndex = outer + m_data.lowerProfile(outer);
201 
202  if (inner <= maxInnerIndex)
203  return this->m_data.lower(m_rowStartIndex[outer] + (inner - outer));
204  else
205  return Scalar(0);
206  }
207  }
208  }
209 
210  inline Scalar& coeffRef(Index row, Index col) {
211  const Index outer = IsRowMajor ? row : col;
212  const Index inner = IsRowMajor ? col : row;
213 
214  eigen_assert(outer < outerSize());
215  eigen_assert(inner < innerSize());
216 
217  if (outer == inner)
218  return this->m_data.diag(outer);
219 
220  if (IsRowMajor) {
221  if (col > row) //upper matrix
222  {
223  const Index minOuterIndex = inner - m_data.upperProfile(inner);
224  eigen_assert(outer >= minOuterIndex && "you try to acces a coeff that do not exist in the storage");
225  return this->m_data.upper(m_colStartIndex[inner] + outer - (inner - m_data.upperProfile(inner)));
226  }
227  if (col < row) //lower matrix
228  {
229  const Index minInnerIndex = outer - m_data.lowerProfile(outer);
230  eigen_assert(inner >= minInnerIndex && "you try to acces a coeff that do not exist in the storage");
231  return this->m_data.lower(m_rowStartIndex[outer] + inner - (outer - m_data.lowerProfile(outer)));
232  }
233  } else {
234  if (outer > inner) //upper matrix
235  {
236  const Index maxOuterIndex = inner + m_data.upperProfile(inner);
237  eigen_assert(outer <= maxOuterIndex && "you try to acces a coeff that do not exist in the storage");
238  return this->m_data.upper(m_colStartIndex[inner] + (outer - inner));
239  }
240  if (outer < inner) //lower matrix
241  {
242  const Index maxInnerIndex = outer + m_data.lowerProfile(outer);
243  eigen_assert(inner <= maxInnerIndex && "you try to acces a coeff that do not exist in the storage");
244  return this->m_data.lower(m_rowStartIndex[outer] + (inner - outer));
245  }
246  }
247  }
248 
249  inline Scalar coeffDiag(Index idx) const {
250  eigen_assert(idx < outerSize());
251  eigen_assert(idx < innerSize());
252  return this->m_data.diag(idx);
253  }
254 
255  inline Scalar coeffLower(Index row, Index col) const {
256  const Index outer = IsRowMajor ? row : col;
257  const Index inner = IsRowMajor ? col : row;
258 
259  eigen_assert(outer < outerSize());
260  eigen_assert(inner < innerSize());
261  eigen_assert(inner != outer);
262 
263  if (IsRowMajor) {
264  const Index minInnerIndex = outer - m_data.lowerProfile(outer);
265  if (inner >= minInnerIndex)
266  return this->m_data.lower(m_rowStartIndex[outer] + inner - (outer - m_data.lowerProfile(outer)));
267  else
268  return Scalar(0);
269 
270  } else {
271  const Index maxInnerIndex = outer + m_data.lowerProfile(outer);
272  if (inner <= maxInnerIndex)
273  return this->m_data.lower(m_rowStartIndex[outer] + (inner - outer));
274  else
275  return Scalar(0);
276  }
277  }
278 
279  inline Scalar coeffUpper(Index row, Index col) const {
280  const Index outer = IsRowMajor ? row : col;
281  const Index inner = IsRowMajor ? col : row;
282 
283  eigen_assert(outer < outerSize());
284  eigen_assert(inner < innerSize());
285  eigen_assert(inner != outer);
286 
287  if (IsRowMajor) {
288  const Index minOuterIndex = inner - m_data.upperProfile(inner);
289  if (outer >= minOuterIndex)
290  return this->m_data.upper(m_colStartIndex[inner] + outer - (inner - m_data.upperProfile(inner)));
291  else
292  return Scalar(0);
293  } else {
294  const Index maxOuterIndex = inner + m_data.upperProfile(inner);
295  if (outer <= maxOuterIndex)
296  return this->m_data.upper(m_colStartIndex[inner] + (outer - inner));
297  else
298  return Scalar(0);
299  }
300  }
301 
302  inline Scalar& coeffRefDiag(Index idx) {
303  eigen_assert(idx < outerSize());
304  eigen_assert(idx < innerSize());
305  return this->m_data.diag(idx);
306  }
307 
308  inline Scalar& coeffRefLower(Index row, Index col) {
309  const Index outer = IsRowMajor ? row : col;
310  const Index inner = IsRowMajor ? col : row;
311 
312  eigen_assert(outer < outerSize());
313  eigen_assert(inner < innerSize());
314  eigen_assert(inner != outer);
315 
316  if (IsRowMajor) {
317  const Index minInnerIndex = outer - m_data.lowerProfile(outer);
318  eigen_assert(inner >= minInnerIndex && "you try to acces a coeff that do not exist in the storage");
319  return this->m_data.lower(m_rowStartIndex[outer] + inner - (outer - m_data.lowerProfile(outer)));
320  } else {
321  const Index maxInnerIndex = outer + m_data.lowerProfile(outer);
322  eigen_assert(inner <= maxInnerIndex && "you try to acces a coeff that do not exist in the storage");
323  return this->m_data.lower(m_rowStartIndex[outer] + (inner - outer));
324  }
325  }
326 
327  inline bool coeffExistLower(Index row, Index col) {
328  const Index outer = IsRowMajor ? row : col;
329  const Index inner = IsRowMajor ? col : row;
330 
331  eigen_assert(outer < outerSize());
332  eigen_assert(inner < innerSize());
333  eigen_assert(inner != outer);
334 
335  if (IsRowMajor) {
336  const Index minInnerIndex = outer - m_data.lowerProfile(outer);
337  return inner >= minInnerIndex;
338  } else {
339  const Index maxInnerIndex = outer + m_data.lowerProfile(outer);
340  return inner <= maxInnerIndex;
341  }
342  }
343 
344  inline Scalar& coeffRefUpper(Index row, Index col) {
345  const Index outer = IsRowMajor ? row : col;
346  const Index inner = IsRowMajor ? col : row;
347 
348  eigen_assert(outer < outerSize());
349  eigen_assert(inner < innerSize());
350  eigen_assert(inner != outer);
351 
352  if (IsRowMajor) {
353  const Index minOuterIndex = inner - m_data.upperProfile(inner);
354  eigen_assert(outer >= minOuterIndex && "you try to acces a coeff that do not exist in the storage");
355  return this->m_data.upper(m_colStartIndex[inner] + outer - (inner - m_data.upperProfile(inner)));
356  } else {
357  const Index maxOuterIndex = inner + m_data.upperProfile(inner);
358  eigen_assert(outer <= maxOuterIndex && "you try to acces a coeff that do not exist in the storage");
359  return this->m_data.upper(m_colStartIndex[inner] + (outer - inner));
360  }
361  }
362 
363  inline bool coeffExistUpper(Index row, Index col) {
364  const Index outer = IsRowMajor ? row : col;
365  const Index inner = IsRowMajor ? col : row;
366 
367  eigen_assert(outer < outerSize());
368  eigen_assert(inner < innerSize());
369  eigen_assert(inner != outer);
370 
371  if (IsRowMajor) {
372  const Index minOuterIndex = inner - m_data.upperProfile(inner);
373  return outer >= minOuterIndex;
374  } else {
375  const Index maxOuterIndex = inner + m_data.upperProfile(inner);
376  return outer <= maxOuterIndex;
377  }
378  }
379 
380 
381 protected:
382 
383 public:
384  class InnerUpperIterator;
385  class InnerLowerIterator;
386 
387  class OuterUpperIterator;
388  class OuterLowerIterator;
389 
391  inline void setZero() {
392  m_data.clear();
393  memset(m_colStartIndex, 0, (m_outerSize + 1) * sizeof (Index));
394  memset(m_rowStartIndex, 0, (m_outerSize + 1) * sizeof (Index));
395  }
396 
398  inline Index nonZeros() const {
399  return m_data.diagSize() + m_data.upperSize() + m_data.lowerSize();
400  }
401 
403  inline void reserve(Index reserveSize, Index reserveUpperSize, Index reserveLowerSize) {
404  m_data.reserve(reserveSize, reserveUpperSize, reserveLowerSize);
405  }
406 
415  EIGEN_DONT_INLINE Scalar & insert(Index row, Index col) {
416  const Index outer = IsRowMajor ? row : col;
417  const Index inner = IsRowMajor ? col : row;
418 
419  eigen_assert(outer < outerSize());
420  eigen_assert(inner < innerSize());
421 
422  if (outer == inner)
423  return m_data.diag(col);
424 
425  if (IsRowMajor) {
426  if (outer < inner) //upper matrix
427  {
428  Index minOuterIndex = 0;
429  minOuterIndex = inner - m_data.upperProfile(inner);
430 
431  if (outer < minOuterIndex) //The value does not yet exist
432  {
433  const Index previousProfile = m_data.upperProfile(inner);
434 
435  m_data.upperProfile(inner) = inner - outer;
436 
437 
438  const Index bandIncrement = m_data.upperProfile(inner) - previousProfile;
439  //shift data stored after this new one
440  const Index stop = m_colStartIndex[cols()];
441  const Index start = m_colStartIndex[inner];
442 
443 
444  for (Index innerIdx = stop; innerIdx >= start; innerIdx--) {
445  m_data.upper(innerIdx + bandIncrement) = m_data.upper(innerIdx);
446  }
447 
448  for (Index innerIdx = cols(); innerIdx > inner; innerIdx--) {
449  m_colStartIndex[innerIdx] += bandIncrement;
450  }
451 
452  //zeros new data
453  memset(this->_upperPtr() + start, 0, (bandIncrement - 1) * sizeof (Scalar));
454 
455  return m_data.upper(m_colStartIndex[inner]);
456  } else {
457  return m_data.upper(m_colStartIndex[inner] + outer - (inner - m_data.upperProfile(inner)));
458  }
459  }
460 
461  if (outer > inner) //lower matrix
462  {
463  const Index minInnerIndex = outer - m_data.lowerProfile(outer);
464  if (inner < minInnerIndex) //The value does not yet exist
465  {
466  const Index previousProfile = m_data.lowerProfile(outer);
467  m_data.lowerProfile(outer) = outer - inner;
468 
469  const Index bandIncrement = m_data.lowerProfile(outer) - previousProfile;
470  //shift data stored after this new one
471  const Index stop = m_rowStartIndex[rows()];
472  const Index start = m_rowStartIndex[outer];
473 
474 
475  for (Index innerIdx = stop; innerIdx >= start; innerIdx--) {
476  m_data.lower(innerIdx + bandIncrement) = m_data.lower(innerIdx);
477  }
478 
479  for (Index innerIdx = rows(); innerIdx > outer; innerIdx--) {
480  m_rowStartIndex[innerIdx] += bandIncrement;
481  }
482 
483  //zeros new data
484  memset(this->_lowerPtr() + start, 0, (bandIncrement - 1) * sizeof (Scalar));
485  return m_data.lower(m_rowStartIndex[outer]);
486  } else {
487  return m_data.lower(m_rowStartIndex[outer] + inner - (outer - m_data.lowerProfile(outer)));
488  }
489  }
490  } else {
491  if (outer > inner) //upper matrix
492  {
493  const Index maxOuterIndex = inner + m_data.upperProfile(inner);
494  if (outer > maxOuterIndex) //The value does not yet exist
495  {
496  const Index previousProfile = m_data.upperProfile(inner);
497  m_data.upperProfile(inner) = outer - inner;
498 
499  const Index bandIncrement = m_data.upperProfile(inner) - previousProfile;
500  //shift data stored after this new one
501  const Index stop = m_rowStartIndex[rows()];
502  const Index start = m_rowStartIndex[inner + 1];
503 
504  for (Index innerIdx = stop; innerIdx >= start; innerIdx--) {
505  m_data.upper(innerIdx + bandIncrement) = m_data.upper(innerIdx);
506  }
507 
508  for (Index innerIdx = inner + 1; innerIdx < outerSize() + 1; innerIdx++) {
509  m_rowStartIndex[innerIdx] += bandIncrement;
510  }
511  memset(this->_upperPtr() + m_rowStartIndex[inner] + previousProfile + 1, 0, (bandIncrement - 1) * sizeof (Scalar));
512  return m_data.upper(m_rowStartIndex[inner] + m_data.upperProfile(inner));
513  } else {
514  return m_data.upper(m_rowStartIndex[inner] + (outer - inner));
515  }
516  }
517 
518  if (outer < inner) //lower matrix
519  {
520  const Index maxInnerIndex = outer + m_data.lowerProfile(outer);
521  if (inner > maxInnerIndex) //The value does not yet exist
522  {
523  const Index previousProfile = m_data.lowerProfile(outer);
524  m_data.lowerProfile(outer) = inner - outer;
525 
526  const Index bandIncrement = m_data.lowerProfile(outer) - previousProfile;
527  //shift data stored after this new one
528  const Index stop = m_colStartIndex[cols()];
529  const Index start = m_colStartIndex[outer + 1];
530 
531  for (Index innerIdx = stop; innerIdx >= start; innerIdx--) {
532  m_data.lower(innerIdx + bandIncrement) = m_data.lower(innerIdx);
533  }
534 
535  for (Index innerIdx = outer + 1; innerIdx < outerSize() + 1; innerIdx++) {
536  m_colStartIndex[innerIdx] += bandIncrement;
537  }
538  memset(this->_lowerPtr() + m_colStartIndex[outer] + previousProfile + 1, 0, (bandIncrement - 1) * sizeof (Scalar));
539  return m_data.lower(m_colStartIndex[outer] + m_data.lowerProfile(outer));
540  } else {
541  return m_data.lower(m_colStartIndex[outer] + (inner - outer));
542  }
543  }
544  }
545  }
546 
549  inline void finalize() {
550  if (IsRowMajor) {
551  if (rows() > cols())
552  m_data.resize(cols(), cols(), rows(), m_colStartIndex[cols()] + 1, m_rowStartIndex[rows()] + 1);
553  else
554  m_data.resize(rows(), cols(), rows(), m_colStartIndex[cols()] + 1, m_rowStartIndex[rows()] + 1);
555 
556  // eigen_assert(rows() == cols() && "memory reorganisatrion only works with suare matrix");
557  //
558  // Scalar* newArray = new Scalar[m_colStartIndex[cols()] + 1 + m_rowStartIndex[rows()] + 1];
559  // Index dataIdx = 0;
560  // for (Index row = 0; row < rows(); row++) {
561  //
562  // const Index nbLowerElts = m_rowStartIndex[row + 1] - m_rowStartIndex[row];
563  // // std::cout << "nbLowerElts" << nbLowerElts << std::endl;
564  // memcpy(newArray + dataIdx, m_data.m_lower + m_rowStartIndex[row], nbLowerElts * sizeof (Scalar));
565  // m_rowStartIndex[row] = dataIdx;
566  // dataIdx += nbLowerElts;
567  //
568  // const Index nbUpperElts = m_colStartIndex[row + 1] - m_colStartIndex[row];
569  // memcpy(newArray + dataIdx, m_data.m_upper + m_colStartIndex[row], nbUpperElts * sizeof (Scalar));
570  // m_colStartIndex[row] = dataIdx;
571  // dataIdx += nbUpperElts;
572  //
573  //
574  // }
575  // //todo : don't access m_data profile directly : add an accessor from SkylineMatrix
576  // m_rowStartIndex[rows()] = m_rowStartIndex[rows()-1] + m_data.lowerProfile(rows()-1);
577  // m_colStartIndex[cols()] = m_colStartIndex[cols()-1] + m_data.upperProfile(cols()-1);
578  //
579  // delete[] m_data.m_lower;
580  // delete[] m_data.m_upper;
581  //
582  // m_data.m_lower = newArray;
583  // m_data.m_upper = newArray;
584  } else {
585  if (rows() > cols())
586  m_data.resize(cols(), rows(), cols(), m_rowStartIndex[cols()] + 1, m_colStartIndex[cols()] + 1);
587  else
588  m_data.resize(rows(), rows(), cols(), m_rowStartIndex[rows()] + 1, m_colStartIndex[rows()] + 1);
589  }
590  }
591 
592  inline void squeeze() {
593  finalize();
594  m_data.squeeze();
595  }
596 
597  void prune(Scalar reference, RealScalar epsilon = dummy_precision<RealScalar > ()) {
598  //TODO
599  }
600 
604  void resize(size_t rows, size_t cols) {
605  const Index diagSize = rows > cols ? cols : rows;
606  m_innerSize = IsRowMajor ? cols : rows;
607 
608  eigen_assert(rows == cols && "Skyline matrix must be square matrix");
609 
610  if (diagSize % 2) { // diagSize is odd
611  const Index k = (diagSize - 1) / 2;
612 
613  m_data.resize(diagSize, IsRowMajor ? cols : rows, IsRowMajor ? rows : cols,
614  2 * k * k + k + 1,
615  2 * k * k + k + 1);
616 
617  } else // diagSize is even
618  {
619  const Index k = diagSize / 2;
620  m_data.resize(diagSize, IsRowMajor ? cols : rows, IsRowMajor ? rows : cols,
621  2 * k * k - k + 1,
622  2 * k * k - k + 1);
623  }
624 
625  if (m_colStartIndex && m_rowStartIndex) {
626  delete[] m_colStartIndex;
627  delete[] m_rowStartIndex;
628  }
629  m_colStartIndex = new Index [cols + 1];
630  m_rowStartIndex = new Index [rows + 1];
631  m_outerSize = diagSize;
632 
633  m_data.reset();
634  m_data.clear();
635 
636  m_outerSize = diagSize;
637  memset(m_colStartIndex, 0, (cols + 1) * sizeof (Index));
638  memset(m_rowStartIndex, 0, (rows + 1) * sizeof (Index));
639  }
640 
641  void resizeNonZeros(Index size) {
642  m_data.resize(size);
643  }
644 
645  inline SkylineMatrix()
646  : m_outerSize(-1), m_innerSize(0), m_colStartIndex(0), m_rowStartIndex(0) {
647  resize(0, 0);
648  }
649 
650  inline SkylineMatrix(size_t rows, size_t cols)
651  : m_outerSize(0), m_innerSize(0), m_colStartIndex(0), m_rowStartIndex(0) {
652  resize(rows, cols);
653  }
654 
655  template<typename OtherDerived>
656  inline SkylineMatrix(const SkylineMatrixBase<OtherDerived>& other)
657  : m_outerSize(0), m_innerSize(0), m_colStartIndex(0), m_rowStartIndex(0) {
658  *this = other.derived();
659  }
660 
661  inline SkylineMatrix(const SkylineMatrix & other)
662  : Base(), m_outerSize(0), m_innerSize(0), m_colStartIndex(0), m_rowStartIndex(0) {
663  *this = other.derived();
664  }
665 
666  inline void swap(SkylineMatrix & other) {
667  //EIGEN_DBG_SKYLINE(std::cout << "SkylineMatrix:: swap\n");
668  std::swap(m_colStartIndex, other.m_colStartIndex);
669  std::swap(m_rowStartIndex, other.m_rowStartIndex);
670  std::swap(m_innerSize, other.m_innerSize);
671  std::swap(m_outerSize, other.m_outerSize);
672  m_data.swap(other.m_data);
673  }
674 
675  inline SkylineMatrix & operator=(const SkylineMatrix & other) {
676  std::cout << "SkylineMatrix& operator=(const SkylineMatrix& other)\n";
677  if (other.isRValue()) {
678  swap(other.const_cast_derived());
679  } else {
680  resize(other.rows(), other.cols());
681  memcpy(m_colStartIndex, other.m_colStartIndex, (m_outerSize + 1) * sizeof (Index));
682  memcpy(m_rowStartIndex, other.m_rowStartIndex, (m_outerSize + 1) * sizeof (Index));
683  m_data = other.m_data;
684  }
685  return *this;
686  }
687 
688  template<typename OtherDerived>
689  inline SkylineMatrix & operator=(const SkylineMatrixBase<OtherDerived>& other) {
690  const bool needToTranspose = (Flags & RowMajorBit) != (OtherDerived::Flags & RowMajorBit);
691  if (needToTranspose) {
692  // TODO
693  // return *this;
694  } else {
695  // there is no special optimization
696  return SkylineMatrixBase<SkylineMatrix>::operator=(other.derived());
697  }
698  }
699 
700  friend std::ostream & operator <<(std::ostream & s, const SkylineMatrix & m) {
701 
702  EIGEN_DBG_SKYLINE(
703  std::cout << "upper elements : " << std::endl;
704  for (Index i = 0; i < m.m_data.upperSize(); i++)
705  std::cout << m.m_data.upper(i) << "\t";
706  std::cout << std::endl;
707  std::cout << "upper profile : " << std::endl;
708  for (Index i = 0; i < m.m_data.upperProfileSize(); i++)
709  std::cout << m.m_data.upperProfile(i) << "\t";
710  std::cout << std::endl;
711  std::cout << "lower startIdx : " << std::endl;
712  for (Index i = 0; i < m.m_data.upperProfileSize(); i++)
713  std::cout << (IsRowMajor ? m.m_colStartIndex[i] : m.m_rowStartIndex[i]) << "\t";
714  std::cout << std::endl;
715 
716 
717  std::cout << "lower elements : " << std::endl;
718  for (Index i = 0; i < m.m_data.lowerSize(); i++)
719  std::cout << m.m_data.lower(i) << "\t";
720  std::cout << std::endl;
721  std::cout << "lower profile : " << std::endl;
722  for (Index i = 0; i < m.m_data.lowerProfileSize(); i++)
723  std::cout << m.m_data.lowerProfile(i) << "\t";
724  std::cout << std::endl;
725  std::cout << "lower startIdx : " << std::endl;
726  for (Index i = 0; i < m.m_data.lowerProfileSize(); i++)
727  std::cout << (IsRowMajor ? m.m_rowStartIndex[i] : m.m_colStartIndex[i]) << "\t";
728  std::cout << std::endl;
729  );
730  for (Index rowIdx = 0; rowIdx < m.rows(); rowIdx++) {
731  for (Index colIdx = 0; colIdx < m.cols(); colIdx++) {
732  s << m.coeff(rowIdx, colIdx) << "\t";
733  }
734  s << std::endl;
735  }
736  return s;
737  }
738 
740  inline ~SkylineMatrix() {
741  delete[] m_colStartIndex;
742  delete[] m_rowStartIndex;
743  }
744 
746  Scalar sum() const;
747 };
748 
749 template<typename Scalar, int _Options>
750 class SkylineMatrix<Scalar, _Options>::InnerUpperIterator {
751 public:
752 
753  InnerUpperIterator(const SkylineMatrix& mat, Index outer)
754  : m_matrix(mat), m_outer(outer),
755  m_id(_Options == RowMajor ? mat.m_colStartIndex[outer] : mat.m_rowStartIndex[outer] + 1),
756  m_start(m_id),
757  m_end(_Options == RowMajor ? mat.m_colStartIndex[outer + 1] : mat.m_rowStartIndex[outer + 1] + 1) {
758  }
759 
760  inline InnerUpperIterator & operator++() {
761  m_id++;
762  return *this;
763  }
764 
765  inline InnerUpperIterator & operator+=(Index shift) {
766  m_id += shift;
767  return *this;
768  }
769 
770  inline Scalar value() const {
771  return m_matrix.m_data.upper(m_id);
772  }
773 
774  inline Scalar* valuePtr() {
775  return const_cast<Scalar*> (&(m_matrix.m_data.upper(m_id)));
776  }
777 
778  inline Scalar& valueRef() {
779  return const_cast<Scalar&> (m_matrix.m_data.upper(m_id));
780  }
781 
782  inline Index index() const {
783  return IsRowMajor ? m_outer - m_matrix.m_data.upperProfile(m_outer) + (m_id - m_start) :
784  m_outer + (m_id - m_start) + 1;
785  }
786 
787  inline Index row() const {
788  return IsRowMajor ? index() : m_outer;
789  }
790 
791  inline Index col() const {
792  return IsRowMajor ? m_outer : index();
793  }
794 
795  inline size_t size() const {
796  return m_matrix.m_data.upperProfile(m_outer);
797  }
798 
799  inline operator bool() const {
800  return (m_id < m_end) && (m_id >= m_start);
801  }
802 
803 protected:
804  const SkylineMatrix& m_matrix;
805  const Index m_outer;
806  Index m_id;
807  const Index m_start;
808  const Index m_end;
809 };
810 
811 template<typename Scalar, int _Options>
812 class SkylineMatrix<Scalar, _Options>::InnerLowerIterator {
813 public:
814 
815  InnerLowerIterator(const SkylineMatrix& mat, Index outer)
816  : m_matrix(mat),
817  m_outer(outer),
818  m_id(_Options == RowMajor ? mat.m_rowStartIndex[outer] : mat.m_colStartIndex[outer] + 1),
819  m_start(m_id),
820  m_end(_Options == RowMajor ? mat.m_rowStartIndex[outer + 1] : mat.m_colStartIndex[outer + 1] + 1) {
821  }
822 
823  inline InnerLowerIterator & operator++() {
824  m_id++;
825  return *this;
826  }
827 
828  inline InnerLowerIterator & operator+=(Index shift) {
829  m_id += shift;
830  return *this;
831  }
832 
833  inline Scalar value() const {
834  return m_matrix.m_data.lower(m_id);
835  }
836 
837  inline Scalar* valuePtr() {
838  return const_cast<Scalar*> (&(m_matrix.m_data.lower(m_id)));
839  }
840 
841  inline Scalar& valueRef() {
842  return const_cast<Scalar&> (m_matrix.m_data.lower(m_id));
843  }
844 
845  inline Index index() const {
846  return IsRowMajor ? m_outer - m_matrix.m_data.lowerProfile(m_outer) + (m_id - m_start) :
847  m_outer + (m_id - m_start) + 1;
848  ;
849  }
850 
851  inline Index row() const {
852  return IsRowMajor ? m_outer : index();
853  }
854 
855  inline Index col() const {
856  return IsRowMajor ? index() : m_outer;
857  }
858 
859  inline size_t size() const {
860  return m_matrix.m_data.lowerProfile(m_outer);
861  }
862 
863  inline operator bool() const {
864  return (m_id < m_end) && (m_id >= m_start);
865  }
866 
867 protected:
868  const SkylineMatrix& m_matrix;
869  const Index m_outer;
870  Index m_id;
871  const Index m_start;
872  const Index m_end;
873 };
874 
875 } // end namespace Eigen
876 
877 #endif // EIGEN_SkylineMatrix_H