aboutsummaryrefslogtreecommitdiffhomepage
path: root/Eigen/src/SparseCore/SparseVector.h
blob: 19b0fbc9d70ac8eac38ddf558e50ff2e3fda4b1c (plain)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2008-2015 Gael Guennebaud <gael.guennebaud@inria.fr>
//
// This Source Code Form is subject to the terms of the Mozilla
// Public License v. 2.0. If a copy of the MPL was not distributed
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.

#ifndef EIGEN_SPARSEVECTOR_H
#define EIGEN_SPARSEVECTOR_H

namespace Eigen { 

/** \ingroup SparseCore_Module
  * \class SparseVector
  *
  * \brief a sparse vector class
  *
  * \tparam _Scalar the scalar type, i.e. the type of the coefficients
  *
  * See http://www.netlib.org/linalg/html_templates/node91.html for details on the storage scheme.
  *
  * This class can be extended with the help of the plugin mechanism described on the page
  * \ref TopicCustomizing_Plugins by defining the preprocessor symbol \c EIGEN_SPARSEVECTOR_PLUGIN.
  */

namespace internal {
template<typename _Scalar, int _Options, typename _StorageIndex>
struct traits<SparseVector<_Scalar, _Options, _StorageIndex> >
{
  typedef _Scalar Scalar;
  typedef _StorageIndex StorageIndex;
  typedef Sparse StorageKind;
  typedef MatrixXpr XprKind;
  enum {
    IsColVector = (_Options & RowMajorBit) ? 0 : 1,

    RowsAtCompileTime = IsColVector ? Dynamic : 1,
    ColsAtCompileTime = IsColVector ? 1 : Dynamic,
    MaxRowsAtCompileTime = RowsAtCompileTime,
    MaxColsAtCompileTime = ColsAtCompileTime,
    Flags = _Options | NestByRefBit | LvalueBit | (IsColVector ? 0 : RowMajorBit) | CompressedAccessBit,
    SupportedAccessPatterns = InnerRandomAccessPattern
  };
};

// Sparse-Vector-Assignment kinds:
enum {
  SVA_RuntimeSwitch,
  SVA_Inner,
  SVA_Outer
};

template< typename Dest, typename Src,
          int AssignmentKind = !bool(Src::IsVectorAtCompileTime) ? SVA_RuntimeSwitch
                             : Src::InnerSizeAtCompileTime==1 ? SVA_Outer
                             : SVA_Inner>
struct sparse_vector_assign_selector;

}

template<typename _Scalar, int _Options, typename _StorageIndex>
class SparseVector
  : public SparseCompressedBase<SparseVector<_Scalar, _Options, _StorageIndex> >
{
    typedef SparseCompressedBase<SparseVector> Base;
    using Base::convert_index;
  public:
    EIGEN_SPARSE_PUBLIC_INTERFACE(SparseVector)
    EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATOR(SparseVector, +=)
    EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATOR(SparseVector, -=)
    
    typedef internal::CompressedStorage<Scalar,StorageIndex> Storage;
    enum { IsColVector = internal::traits<SparseVector>::IsColVector };
    
    enum {
      Options = _Options
    };
    
    EIGEN_STRONG_INLINE Index rows() const { return IsColVector ? m_size : 1; }
    EIGEN_STRONG_INLINE Index cols() const { return IsColVector ? 1 : m_size; }
    EIGEN_STRONG_INLINE Index innerSize() const { return m_size; }
    EIGEN_STRONG_INLINE Index outerSize() const { return 1; }

    EIGEN_STRONG_INLINE const Scalar* valuePtr() const { return m_data.valuePtr(); }
    EIGEN_STRONG_INLINE Scalar* valuePtr() { return m_data.valuePtr(); }

    EIGEN_STRONG_INLINE const StorageIndex* innerIndexPtr() const { return m_data.indexPtr(); }
    EIGEN_STRONG_INLINE StorageIndex* innerIndexPtr() { return m_data.indexPtr(); }

    inline const StorageIndex* outerIndexPtr() const { return 0; }
    inline StorageIndex* outerIndexPtr() { return 0; }
    inline const StorageIndex* innerNonZeroPtr() const { return 0; }
    inline StorageIndex* innerNonZeroPtr() { return 0; }
    
    /** \internal */
    inline Storage& data() { return m_data; }
    /** \internal */
    inline const Storage& data() const { return m_data; }

    inline Scalar coeff(Index row, Index col) const
    {
      eigen_assert(IsColVector ? (col==0 && row>=0 && row<m_size) : (row==0 && col>=0 && col<m_size));
      return coeff(IsColVector ? row : col);
    }
    inline Scalar coeff(Index i) const
    {
      eigen_assert(i>=0 && i<m_size);
      return m_data.at(StorageIndex(i));
    }

    inline Scalar& coeffRef(Index row, Index col)
    {
      eigen_assert(IsColVector ? (col==0 && row>=0 && row<m_size) : (row==0 && col>=0 && col<m_size));
      return coeffRef(IsColVector ? row : col);
    }

    /** \returns a reference to the coefficient value at given index \a i
      * This operation involes a log(rho*size) binary search. If the coefficient does not
      * exist yet, then a sorted insertion into a sequential buffer is performed.
      *
      * This insertion might be very costly if the number of nonzeros above \a i is large.
      */
    inline Scalar& coeffRef(Index i)
    {
      eigen_assert(i>=0 && i<m_size);

      return m_data.atWithInsertion(StorageIndex(i));
    }

  public:

    typedef typename Base::InnerIterator InnerIterator;
    typedef typename Base::ReverseInnerIterator ReverseInnerIterator;

    inline void setZero() { m_data.clear(); }

    /** \returns the number of non zero coefficients */
    inline Index nonZeros() const  { return m_data.size(); }

    inline void startVec(Index outer)
    {
      EIGEN_UNUSED_VARIABLE(outer);
      eigen_assert(outer==0);
    }

    inline Scalar& insertBackByOuterInner(Index outer, Index inner)
    {
      EIGEN_UNUSED_VARIABLE(outer);
      eigen_assert(outer==0);
      return insertBack(inner);
    }
    inline Scalar& insertBack(Index i)
    {
      m_data.append(0, i);
      return m_data.value(m_data.size()-1);
    }
    
    Scalar& insertBackByOuterInnerUnordered(Index outer, Index inner)
    {
      EIGEN_UNUSED_VARIABLE(outer);
      eigen_assert(outer==0);
      return insertBackUnordered(inner);
    }
    inline Scalar& insertBackUnordered(Index i)
    {
      m_data.append(0, i);
      return m_data.value(m_data.size()-1);
    }

    inline Scalar& insert(Index row, Index col)
    {
      eigen_assert(IsColVector ? (col==0 && row>=0 && row<m_size) : (row==0 && col>=0 && col<m_size));
      
      Index inner = IsColVector ? row : col;
      Index outer = IsColVector ? col : row;
      EIGEN_ONLY_USED_FOR_DEBUG(outer);
      eigen_assert(outer==0);
      return insert(inner);
    }
    Scalar& insert(Index i)
    {
      eigen_assert(i>=0 && i<m_size);
      
      Index startId = 0;
      Index p = Index(m_data.size()) - 1;
      // TODO smart realloc
      m_data.resize(p+2,1);

      while ( (p >= startId) && (m_data.index(p) > i) )
      {
        m_data.index(p+1) = m_data.index(p);
        m_data.value(p+1) = m_data.value(p);
        --p;
      }
      m_data.index(p+1) = convert_index(i);
      m_data.value(p+1) = 0;
      return m_data.value(p+1);
    }

    /**
      */
    inline void reserve(Index reserveSize) { m_data.reserve(reserveSize); }


    inline void finalize() {}

    /** \copydoc SparseMatrix::prune(const Scalar&,const RealScalar&) */
    void prune(const Scalar& reference, const RealScalar& epsilon = NumTraits<RealScalar>::dummy_precision())
    {
      m_data.prune(reference,epsilon);
    }

    /** Resizes the sparse vector to \a rows x \a cols
      *
      * This method is provided for compatibility with matrices.
      * For a column vector, \a cols must be equal to 1.
      * For a row vector, \a rows must be equal to 1.
      *
      * \sa resize(Index)
      */
    void resize(Index rows, Index cols)
    {
      eigen_assert((IsColVector ? cols : rows)==1 && "Outer dimension must equal 1");
      resize(IsColVector ? rows : cols);
    }

    /** Resizes the sparse vector to \a newSize
      * This method deletes all entries, thus leaving an empty sparse vector
      *
      * \sa  conservativeResize(), setZero() */
    void resize(Index newSize)
    {
      m_size = newSize;
      m_data.clear();
    }

    /** Resizes the sparse vector to \a newSize, while leaving old values untouched.
      *
      * If the size of the vector is decreased, then the storage of the out-of bounds coefficients is kept and reserved.
      * Call .data().squeeze() to free extra memory.
      *
      * \sa reserve(), setZero()
      */
    void conservativeResize(Index newSize)
    {
      if (newSize < m_size)
      {
        Index i = 0;
        while (i<m_data.size() && m_data.index(i)<newSize) ++i;
        m_data.resize(i);
      }
      m_size = newSize;
    }

    void resizeNonZeros(Index size) { m_data.resize(size); }

    inline SparseVector() : m_size(0) { check_template_parameters(); resize(0); }

    explicit inline SparseVector(Index size) : m_size(0) { check_template_parameters(); resize(size); }

    inline SparseVector(Index rows, Index cols) : m_size(0) { check_template_parameters(); resize(rows,cols); }

    template<typename OtherDerived>
    inline SparseVector(const SparseMatrixBase<OtherDerived>& other)
      : m_size(0)
    {
      #ifdef EIGEN_SPARSE_CREATE_TEMPORARY_PLUGIN
        EIGEN_SPARSE_CREATE_TEMPORARY_PLUGIN
      #endif
      check_template_parameters();
      *this = other.derived();
    }

    inline SparseVector(const SparseVector& other)
      : Base(other), m_size(0)
    {
      check_template_parameters();
      *this = other.derived();
    }

    /** Swaps the values of \c *this and \a other.
      * Overloaded for performance: this version performs a \em shallow swap by swaping pointers and attributes only.
      * \sa SparseMatrixBase::swap()
      */
    inline void swap(SparseVector& other)
    {
      std::swap(m_size, other.m_size);
      m_data.swap(other.m_data);
    }

    template<int OtherOptions>
    inline void swap(SparseMatrix<Scalar,OtherOptions,StorageIndex>& other)
    {
      eigen_assert(other.outerSize()==1);
      std::swap(m_size, other.m_innerSize);
      m_data.swap(other.m_data);
    }

    inline SparseVector& operator=(const SparseVector& other)
    {
      if (other.isRValue())
      {
        swap(other.const_cast_derived());
      }
      else
      {
        resize(other.size());
        m_data = other.m_data;
      }
      return *this;
    }

    template<typename OtherDerived>
    inline SparseVector& operator=(const SparseMatrixBase<OtherDerived>& other)
    {
      SparseVector tmp(other.size());
      internal::sparse_vector_assign_selector<SparseVector,OtherDerived>::run(tmp,other.derived());
      this->swap(tmp);
      return *this;
    }

    #ifndef EIGEN_PARSED_BY_DOXYGEN
    template<typename Lhs, typename Rhs>
    inline SparseVector& operator=(const SparseSparseProduct<Lhs,Rhs>& product)
    {
      return Base::operator=(product);
    }
    #endif

    friend std::ostream & operator << (std::ostream & s, const SparseVector& m)
    {
      for (Index i=0; i<m.nonZeros(); ++i)
        s << "(" << m.m_data.value(i) << "," << m.m_data.index(i) << ") ";
      s << std::endl;
      return s;
    }

    /** Destructor */
    inline ~SparseVector() {}

    /** Overloaded for performance */
    Scalar sum() const;

  public:

    /** \internal \deprecated use setZero() and reserve() */
    EIGEN_DEPRECATED void startFill(Index reserve)
    {
      setZero();
      m_data.reserve(reserve);
    }

    /** \internal \deprecated use insertBack(Index,Index) */
    EIGEN_DEPRECATED Scalar& fill(Index r, Index c)
    {
      eigen_assert(r==0 || c==0);
      return fill(IsColVector ? r : c);
    }

    /** \internal \deprecated use insertBack(Index) */
    EIGEN_DEPRECATED Scalar& fill(Index i)
    {
      m_data.append(0, i);
      return m_data.value(m_data.size()-1);
    }

    /** \internal \deprecated use insert(Index,Index) */
    EIGEN_DEPRECATED Scalar& fillrand(Index r, Index c)
    {
      eigen_assert(r==0 || c==0);
      return fillrand(IsColVector ? r : c);
    }

    /** \internal \deprecated use insert(Index) */
    EIGEN_DEPRECATED Scalar& fillrand(Index i)
    {
      return insert(i);
    }

    /** \internal \deprecated use finalize() */
    EIGEN_DEPRECATED void endFill() {}
    
    // These two functions were here in the 3.1 release, so let's keep them in case some code rely on them.
    /** \internal \deprecated use data() */
    EIGEN_DEPRECATED Storage& _data() { return m_data; }
    /** \internal \deprecated use data() */
    EIGEN_DEPRECATED const Storage& _data() const { return m_data; }
    
#   ifdef EIGEN_SPARSEVECTOR_PLUGIN
#     include EIGEN_SPARSEVECTOR_PLUGIN
#   endif

protected:
  
    static void check_template_parameters()
    {
      EIGEN_STATIC_ASSERT(NumTraits<StorageIndex>::IsSigned,THE_INDEX_TYPE_MUST_BE_A_SIGNED_TYPE);
      EIGEN_STATIC_ASSERT((_Options&(ColMajor|RowMajor))==Options,INVALID_MATRIX_TEMPLATE_PARAMETERS);
    }
    
    Storage m_data;
    Index m_size;
};

namespace internal {

template<typename _Scalar, int _Options, typename _Index>
struct evaluator<SparseVector<_Scalar,_Options,_Index> >
  : evaluator_base<SparseVector<_Scalar,_Options,_Index> >
{
  typedef SparseVector<_Scalar,_Options,_Index> SparseVectorType;
  typedef evaluator_base<SparseVectorType> Base;
  typedef typename SparseVectorType::InnerIterator InnerIterator;
  typedef typename SparseVectorType::ReverseInnerIterator ReverseInnerIterator;
  
  enum {
    CoeffReadCost = NumTraits<_Scalar>::ReadCost,
    Flags = SparseVectorType::Flags
  };

  evaluator() : Base() {}
  
  explicit evaluator(const SparseVectorType &mat) : m_matrix(&mat)
  {
    EIGEN_INTERNAL_CHECK_COST_VALUE(CoeffReadCost);
  }
  
  inline Index nonZerosEstimate() const {
    return m_matrix->nonZeros();
  }
  
  operator SparseVectorType&() { return m_matrix->const_cast_derived(); }
  operator const SparseVectorType&() const { return *m_matrix; }
  
  const SparseVectorType *m_matrix;
};

template< typename Dest, typename Src>
struct sparse_vector_assign_selector<Dest,Src,SVA_Inner> {
  static void run(Dest& dst, const Src& src) {
    eigen_internal_assert(src.innerSize()==src.size());
    typedef internal::evaluator<Src> SrcEvaluatorType;
    SrcEvaluatorType srcEval(src);
    for(typename SrcEvaluatorType::InnerIterator it(srcEval, 0); it; ++it)
      dst.insert(it.index()) = it.value();
  }
};

template< typename Dest, typename Src>
struct sparse_vector_assign_selector<Dest,Src,SVA_Outer> {
  static void run(Dest& dst, const Src& src) {
    eigen_internal_assert(src.outerSize()==src.size());
    typedef internal::evaluator<Src> SrcEvaluatorType;
    SrcEvaluatorType srcEval(src);
    for(Index i=0; i<src.size(); ++i)
    {
      typename SrcEvaluatorType::InnerIterator it(srcEval, i);
      if(it)
        dst.insert(i) = it.value();
    }
  }
};

template< typename Dest, typename Src>
struct sparse_vector_assign_selector<Dest,Src,SVA_RuntimeSwitch> {
  static void run(Dest& dst, const Src& src) {
    if(src.outerSize()==1)  sparse_vector_assign_selector<Dest,Src,SVA_Inner>::run(dst, src);
    else                    sparse_vector_assign_selector<Dest,Src,SVA_Outer>::run(dst, src);
  }
};

}

} // end namespace Eigen

#endif // EIGEN_SPARSEVECTOR_H