Persistent_cohomology.h
1 /* This file is part of the Gudhi Library - https://gudhi.inria.fr/ - which is released under MIT.
2  * See file LICENSE or go to https://gudhi.inria.fr/licensing/ for full license details.
3  * Author(s): ClĂ©ment Maria
4  *
5  * Copyright (C) 2014 Inria
6  *
7  * Modification(s):
8  * - YYYY/MM Author: Description of the modification
9  */
10 
11 #ifndef PERSISTENT_COHOMOLOGY_H_
12 #define PERSISTENT_COHOMOLOGY_H_
13 
14 #include <gudhi/Persistent_cohomology/Persistent_cohomology_column.h>
15 #include <gudhi/Persistent_cohomology/Field_Zp.h>
16 #include <gudhi/Simple_object_pool.h>
17 
18 #include <boost/intrusive/set.hpp>
19 #include <boost/pending/disjoint_sets.hpp>
20 #include <boost/intrusive/list.hpp>
21 
22 #include <iostream>
23 #include <map>
24 #include <unordered_map>
25 #include <utility>
26 #include <list>
27 #include <vector>
28 #include <set>
29 #include <fstream> // std::ofstream
30 #include <limits> // for numeric_limits<>
31 #include <tuple>
32 #include <algorithm>
33 #include <string>
34 #include <stdexcept> // for std::out_of_range
35 
36 namespace Gudhi {
37 
38 namespace persistent_cohomology {
39 
52 // TODO(CM): Memory allocation policy: classic, use a mempool, etc.
53 template<class FilteredComplex, class CoefficientField>
55  public:
56  // Data attached to each simplex to interface with a Property Map.
57 
68  typedef std::tuple<Simplex_handle, Simplex_handle, Arith_element> Persistent_interval;
69 
70  private:
71  // Compressed Annotation Matrix types:
72  // Column type
73  typedef Persistent_cohomology_column<Simplex_key, Arith_element> Column; // contains 1 set_hook
74  // Cell type
75  typedef typename Column::Cell Cell; // contains 2 list_hooks
76  // Remark: constant_time_size must be false because base_hook_cam_h has auto_unlink link_mode
77  typedef boost::intrusive::list<Cell,
78  boost::intrusive::constant_time_size<false>,
79  boost::intrusive::base_hook<base_hook_cam_h> > Hcell;
80 
81  typedef boost::intrusive::set<Column,
82  boost::intrusive::constant_time_size<false> > Cam;
83  // Sparse column type for the annotation of the boundary of an element.
84  typedef std::vector<std::pair<Simplex_key, Arith_element> > A_ds_type;
85 
86  public:
97  explicit Persistent_cohomology(FilteredComplex& cpx, bool persistence_dim_max = false)
98  : cpx_(&cpx),
99  dim_max_(cpx.dimension()), // upper bound on the dimension of the simplices
100  coeff_field_(), // initialize the field coefficient structure.
101  num_simplices_(cpx_->num_simplices()), // num_simplices save to avoid to call thrice the function
102  ds_rank_(num_simplices_), // union-find
103  ds_parent_(num_simplices_), // union-find
104  ds_repr_(num_simplices_, NULL), // union-find -> annotation vectors
105  dsets_(ds_rank_.data(), ds_parent_.data()), // union-find
106  cam_(), // collection of annotation vectors
107  zero_cocycles_(), // union-find -> Simplex_key of creator for 0-homology
108  transverse_idx_(), // key -> row
109  persistent_pairs_(),
110  interval_length_policy(&cpx, 0),
111  column_pool_(), // memory pools for the CAM
112  cell_pool_() {
113  if (num_simplices_ > std::numeric_limits<Simplex_key>::max()) {
114  // num_simplices must be strictly lower than the limit, because a value is reserved for null_key.
115  throw std::out_of_range("The number of simplices is more than Simplex_key type numeric limit.");
116  }
117  if (persistence_dim_max) {
118  ++dim_max_;
119  }
120  }
121 
123  // Clean the transversal lists
124  for (auto & transverse_ref : transverse_idx_) {
125  // Destruct all the cells
126  transverse_ref.second.row_->clear_and_dispose([&](Cell*p){p->~Cell();});
127  delete transverse_ref.second.row_;
128  }
129  }
130 
131  private:
132  struct length_interval {
133  length_interval(FilteredComplex * cpx, Filtration_value min_length)
134  : cpx_(cpx),
135  min_length_(min_length) {
136  }
137 
138  bool operator()(Simplex_handle sh1, Simplex_handle sh2) {
139  return cpx_->filtration(sh2) - cpx_->filtration(sh1) > min_length_;
140  }
141 
142  void set_length(Filtration_value new_length) {
143  min_length_ = new_length;
144  }
145 
146  FilteredComplex * cpx_;
147  Filtration_value min_length_;
148  };
149 
150  public:
152  void init_coefficients(int charac) {
153  coeff_field_.init(charac);
154  }
156  void init_coefficients(int charac_min, int charac_max) {
157  coeff_field_.init(charac_min, charac_max);
158  }
159 
168  void compute_persistent_cohomology(Filtration_value min_interval_length = 0) {
169  interval_length_policy.set_length(min_interval_length);
170  Simplex_key idx_fil = -1;
171  std::vector<Simplex_key> vertices; // so we can check the connected components at the end
172  // Compute all finite intervals
173  for (auto sh : cpx_->filtration_simplex_range()) {
174  cpx_->assign_key(sh, ++idx_fil);
175  dsets_.make_set(cpx_->key(sh));
176  int dim_simplex = cpx_->dimension(sh);
177  switch (dim_simplex) {
178  case 0:
179  vertices.push_back(idx_fil);
180  break;
181  case 1:
182  update_cohomology_groups_edge(sh);
183  break;
184  default:
185  update_cohomology_groups(sh, dim_simplex);
186  break;
187  }
188  }
189  // Compute infinite intervals of dimension 0
190  for (Simplex_key key : vertices) { // for all 0-dimensional simplices
191  if (ds_parent_[key] == key // root of its tree
192  && zero_cocycles_.find(key) == zero_cocycles_.end()) {
193  persistent_pairs_.emplace_back(
194  cpx_->simplex(key), cpx_->null_simplex(), coeff_field_.characteristic());
195  }
196  }
197  for (auto zero_idx : zero_cocycles_) {
198  persistent_pairs_.emplace_back(
199  cpx_->simplex(zero_idx.second), cpx_->null_simplex(), coeff_field_.characteristic());
200  }
201  // Compute infinite interval of dimension > 0
202  for (auto cocycle : transverse_idx_) {
203  persistent_pairs_.emplace_back(
204  cpx_->simplex(cocycle.first), cpx_->null_simplex(), cocycle.second.characteristics_);
205  }
206  }
207 
208  private:
213  void update_cohomology_groups_edge(Simplex_handle sigma) {
214  Simplex_handle u, v;
215  boost::tie(u, v) = cpx_->endpoints(sigma);
216 
217  Simplex_key ku = dsets_.find_set(cpx_->key(u));
218  Simplex_key kv = dsets_.find_set(cpx_->key(v));
219 
220  if (ku != kv) { // Destroy a connected component
221  dsets_.link(ku, kv);
222  // Keys of the simplices which created the connected components containing
223  // respectively u and v.
224  Simplex_key idx_coc_u, idx_coc_v;
225  auto map_it_u = zero_cocycles_.find(ku);
226  // If the index of the cocycle representing the class is already ku.
227  if (map_it_u == zero_cocycles_.end()) {
228  idx_coc_u = ku;
229  } else {
230  idx_coc_u = map_it_u->second;
231  }
232 
233  auto map_it_v = zero_cocycles_.find(kv);
234  // If the index of the cocycle representing the class is already kv.
235  if (map_it_v == zero_cocycles_.end()) {
236  idx_coc_v = kv;
237  } else {
238  idx_coc_v = map_it_v->second;
239  }
240 
241  if (cpx_->filtration(cpx_->simplex(idx_coc_u))
242  < cpx_->filtration(cpx_->simplex(idx_coc_v))) { // Kill cocycle [idx_coc_v], which is younger.
243  if (interval_length_policy(cpx_->simplex(idx_coc_v), sigma)) {
244  persistent_pairs_.emplace_back(
245  cpx_->simplex(idx_coc_v), sigma, coeff_field_.characteristic());
246  }
247  // Maintain the index of the 0-cocycle alive.
248  if (kv != idx_coc_v) {
249  zero_cocycles_.erase(map_it_v);
250  }
251  if (kv == dsets_.find_set(kv)) {
252  if (ku != idx_coc_u) {
253  zero_cocycles_.erase(map_it_u);
254  }
255  zero_cocycles_[kv] = idx_coc_u;
256  }
257  } else { // Kill cocycle [idx_coc_u], which is younger.
258  if (interval_length_policy(cpx_->simplex(idx_coc_u), sigma)) {
259  persistent_pairs_.emplace_back(
260  cpx_->simplex(idx_coc_u), sigma, coeff_field_.characteristic());
261  }
262  // Maintain the index of the 0-cocycle alive.
263  if (ku != idx_coc_u) {
264  zero_cocycles_.erase(map_it_u);
265  }
266  if (ku == dsets_.find_set(ku)) {
267  if (kv != idx_coc_v) {
268  zero_cocycles_.erase(map_it_v);
269  }
270  zero_cocycles_[ku] = idx_coc_v;
271  }
272  }
273  cpx_->assign_key(sigma, cpx_->null_key());
274  } else if (dim_max_ > 1) { // If ku == kv, same connected component: create a 1-cocycle class.
275  create_cocycle(sigma, coeff_field_.multiplicative_identity(), coeff_field_.characteristic());
276  }
277  }
278 
279  /*
280  * Compute the annotation of the boundary of a simplex.
281  */
282  void annotation_of_the_boundary(
283  std::map<Simplex_key, Arith_element> & map_a_ds, Simplex_handle sigma,
284  int dim_sigma) {
285  // traverses the boundary of sigma, keeps track of the annotation vectors,
286  // with multiplicity. We used to sum the coefficients directly in
287  // annotations_in_boundary by using a map, we now do it later.
288  typedef std::pair<Column *, int> annotation_t;
289  thread_local std::vector<annotation_t> annotations_in_boundary;
290  annotations_in_boundary.clear();
291  int sign = 1 - 2 * (dim_sigma % 2); // \in {-1,1} provides the sign in the
292  // alternate sum in the boundary.
293  Simplex_key key;
294  Column * curr_col;
295 
296  for (auto sh : cpx_->boundary_simplex_range(sigma)) {
297  key = cpx_->key(sh);
298  if (key != cpx_->null_key()) { // A simplex with null_key is a killer, and have null annotation
299  // Find its annotation vector
300  curr_col = ds_repr_[dsets_.find_set(key)];
301  if (curr_col != NULL) { // and insert it in annotations_in_boundary with multyiplicative factor "sign".
302  annotations_in_boundary.emplace_back(curr_col, sign);
303  }
304  }
305  sign = -sign;
306  }
307  // Place identical annotations consecutively so we can easily sum their multiplicities.
308  std::sort(annotations_in_boundary.begin(), annotations_in_boundary.end(),
309  [](annotation_t const& a, annotation_t const& b) { return a.first < b.first; });
310 
311  // Sum the annotations with multiplicity, using a map<key,coeff>
312  // to represent a sparse vector.
313  std::pair<typename std::map<Simplex_key, Arith_element>::iterator, bool> result_insert_a_ds;
314 
315  for (auto ann_it = annotations_in_boundary.begin(); ann_it != annotations_in_boundary.end(); ) {
316  Column* col = ann_it->first;
317  int mult = ann_it->second;
318  while (++ann_it != annotations_in_boundary.end() && ann_it->first == col) {
319  mult += ann_it->second;
320  }
321  // The following test is just a heuristic, it is not required, and it is fine that is misses p == 0.
322  if (mult != coeff_field_.additive_identity()) { // For all columns in the boundary,
323  for (auto cell_ref : col->col_) { // insert every cell in map_a_ds with multiplicity
324  Arith_element w_y = coeff_field_.times(cell_ref.coefficient_, mult); // coefficient * multiplicity
325 
326  if (w_y != coeff_field_.additive_identity()) { // if != 0
327  result_insert_a_ds = map_a_ds.insert(std::pair<Simplex_key, Arith_element>(cell_ref.key_, w_y));
328  if (!(result_insert_a_ds.second)) { // if cell_ref.key_ already a Key in map_a_ds
329  result_insert_a_ds.first->second = coeff_field_.plus_equal(result_insert_a_ds.first->second, w_y);
330  if (result_insert_a_ds.first->second == coeff_field_.additive_identity()) {
331  map_a_ds.erase(result_insert_a_ds.first);
332  }
333  }
334  }
335  }
336  }
337  }
338  }
339 
340  /*
341  * Update the cohomology groups under the insertion of a simplex.
342  */
343  void update_cohomology_groups(Simplex_handle sigma, int dim_sigma) {
344 // Compute the annotation of the boundary of sigma:
345  std::map<Simplex_key, Arith_element> map_a_ds;
346  annotation_of_the_boundary(map_a_ds, sigma, dim_sigma);
347 // Update the cohomology groups:
348  if (map_a_ds.empty()) { // sigma is a creator in all fields represented in coeff_field_
349  if (dim_sigma < dim_max_) {
350  create_cocycle(sigma, coeff_field_.multiplicative_identity(),
351  coeff_field_.characteristic());
352  }
353  } else { // sigma is a destructor in at least a field in coeff_field_
354  // Convert map_a_ds to a vector
355  A_ds_type a_ds; // admits reverse iterators
356  for (auto map_a_ds_ref : map_a_ds) {
357  a_ds.push_back(
358  std::pair<Simplex_key, Arith_element>(map_a_ds_ref.first,
359  map_a_ds_ref.second));
360  }
361 
362  Arith_element inv_x, charac;
363  Arith_element prod = coeff_field_.characteristic(); // Product of characteristic of the fields
364  for (auto a_ds_rit = a_ds.rbegin();
365  (a_ds_rit != a_ds.rend())
366  && (prod != coeff_field_.multiplicative_identity()); ++a_ds_rit) {
367  std::tie(inv_x, charac) = coeff_field_.inverse(a_ds_rit->second, prod);
368 
369  if (inv_x != coeff_field_.additive_identity()) {
370  destroy_cocycle(sigma, a_ds, a_ds_rit->first, inv_x, charac);
371  prod /= charac;
372  }
373  }
374  if (prod != coeff_field_.multiplicative_identity()
375  && dim_sigma < dim_max_) {
376  create_cocycle(sigma, coeff_field_.multiplicative_identity(prod), prod);
377  }
378  }
379  }
380 
381  /* \brief Create a new cocycle class.
382  *
383  * The class is created by the insertion of the simplex sigma.
384  * The methods adds a cocycle, representing the new cocycle class,
385  * to the matrix representing the cohomology groups.
386  * The new cocycle has value 0 on every simplex except on sigma
387  * where it worths 1.*/
388  void create_cocycle(Simplex_handle sigma, Arith_element x,
389  Arith_element charac) {
390  Simplex_key key = cpx_->key(sigma);
391  // Create a column containing only one cell,
392  Column * new_col = column_pool_.construct(key);
393  Cell * new_cell = cell_pool_.construct(key, x, new_col);
394  new_col->col_.push_back(*new_cell);
395  // and insert it in the matrix, in constant time thanks to the hint cam_.end().
396  // Indeed *new_col has the biggest lexicographic value because key is the
397  // biggest key used so far.
398  cam_.insert(cam_.end(), *new_col);
399  // Update the disjoint sets data structure.
400  Hcell * new_hcell = new Hcell;
401  new_hcell->push_back(*new_cell);
402  transverse_idx_[key] = cocycle(charac, new_hcell); // insert the new row
403  ds_repr_[key] = new_col;
404  }
405 
406  /* \brief Destroy a cocycle class.
407  *
408  * The cocycle class is destroyed by the insertion of sigma.
409  * The methods proceeds to a reduction of the matrix representing
410  * the cohomology groups using Gauss pivoting. The reduction zeros-out
411  * the row containing the cell with highest key in
412  * a_ds, the annotation of the boundary of simplex sigma. This key
413  * is "death_key".*/
414  void destroy_cocycle(Simplex_handle sigma, A_ds_type const& a_ds,
415  Simplex_key death_key, Arith_element inv_x,
416  Arith_element charac) {
417  // Create a finite persistent interval for which the interval exists
418  if (interval_length_policy(cpx_->simplex(death_key), sigma)) {
419  persistent_pairs_.emplace_back(cpx_->simplex(death_key) // creator
420  , sigma // destructor
421  , charac); // fields
422  }
423 
424  auto death_key_row = transverse_idx_.find(death_key); // Find the beginning of the row.
425  std::pair<typename Cam::iterator, bool> result_insert_cam;
426 
427  auto row_cell_it = death_key_row->second.row_->begin();
428 
429  while (row_cell_it != death_key_row->second.row_->end()) { // Traverse all cells in
430  // the row at index death_key.
431  Arith_element w = coeff_field_.times_minus(inv_x, row_cell_it->coefficient_);
432 
433  if (w != coeff_field_.additive_identity()) {
434  Column * curr_col = row_cell_it->self_col_;
435  ++row_cell_it;
436  // Disconnect the column from the rows in the CAM.
437  for (auto& col_cell : curr_col->col_) {
438  col_cell.base_hook_cam_h::unlink();
439  }
440 
441  // Remove the column from the CAM before modifying its value
442  cam_.erase(cam_.iterator_to(*curr_col));
443  // Proceed to the reduction of the column
444  plus_equal_column(*curr_col, a_ds, w);
445 
446  if (curr_col->col_.empty()) { // If the column is null
447  ds_repr_[curr_col->class_key_] = NULL;
448  column_pool_.destroy(curr_col); // delete curr_col;
449  } else {
450  // Find whether the column obtained is already in the CAM
451  result_insert_cam = cam_.insert(*curr_col);
452  if (result_insert_cam.second) { // If it was not in the CAM before: insertion has succeeded
453  for (auto& col_cell : curr_col->col_) {
454  // re-establish the row links
455  transverse_idx_[col_cell.key_].row_->push_front(col_cell);
456  }
457  } else { // There is already an identical column in the CAM:
458  // merge two disjoint sets.
459  dsets_.link(curr_col->class_key_,
460  result_insert_cam.first->class_key_);
461 
462  Simplex_key key_tmp = dsets_.find_set(curr_col->class_key_);
463  ds_repr_[key_tmp] = &(*(result_insert_cam.first));
464  result_insert_cam.first->class_key_ = key_tmp;
465  // intrusive containers don't own their elements, we have to release them manually
466  curr_col->col_.clear_and_dispose([&](Cell*p){cell_pool_.destroy(p);});
467  column_pool_.destroy(curr_col); // delete curr_col;
468  }
469  }
470  } else {
471  ++row_cell_it;
472  } // If w == 0, pass.
473  }
474 
475  // Because it is a killer simplex, set the data of sigma to null_key().
476  if (charac == coeff_field_.characteristic()) {
477  cpx_->assign_key(sigma, cpx_->null_key());
478  }
479  if (death_key_row->second.characteristics_ == charac) {
480  delete death_key_row->second.row_;
481  transverse_idx_.erase(death_key_row);
482  } else {
483  death_key_row->second.characteristics_ /= charac;
484  }
485  }
486 
487  /*
488  * Assign: target <- target + w * other.
489  */
490  void plus_equal_column(Column & target, A_ds_type const& other // value_type is pair<Simplex_key,Arith_element>
491  , Arith_element w) {
492  auto target_it = target.col_.begin();
493  auto other_it = other.begin();
494  while (target_it != target.col_.end() && other_it != other.end()) {
495  if (target_it->key_ < other_it->first) {
496  ++target_it;
497  } else {
498  if (target_it->key_ > other_it->first) {
499  Cell * cell_tmp = cell_pool_.construct(Cell(other_it->first // key
500  , coeff_field_.additive_identity(), &target));
501 
502  cell_tmp->coefficient_ = coeff_field_.plus_times_equal(cell_tmp->coefficient_, other_it->second, w);
503 
504  target.col_.insert(target_it, *cell_tmp);
505 
506  ++other_it;
507  } else { // it1->key == it2->key
508  // target_it->coefficient_ <- target_it->coefficient_ + other_it->second * w
509  target_it->coefficient_ = coeff_field_.plus_times_equal(target_it->coefficient_, other_it->second, w);
510  if (target_it->coefficient_ == coeff_field_.additive_identity()) {
511  auto tmp_it = target_it;
512  ++target_it;
513  ++other_it; // iterators remain valid
514  Cell * tmp_cell_ptr = &(*tmp_it);
515  target.col_.erase(tmp_it); // removed from column
516 
517  cell_pool_.destroy(tmp_cell_ptr); // delete from memory
518  } else {
519  ++target_it;
520  ++other_it;
521  }
522  }
523  }
524  }
525  while (other_it != other.end()) {
526  Cell * cell_tmp = cell_pool_.construct(Cell(other_it->first, coeff_field_.additive_identity(), &target));
527  cell_tmp->coefficient_ = coeff_field_.plus_times_equal(cell_tmp->coefficient_, other_it->second, w);
528  target.col_.insert(target.col_.end(), *cell_tmp);
529 
530  ++other_it;
531  }
532  }
533 
534  /*
535  * Compare two intervals by length.
536  */
537  struct cmp_intervals_by_length {
538  explicit cmp_intervals_by_length(FilteredComplex * sc)
539  : sc_(sc) {
540  }
541  bool operator()(const Persistent_interval & p1, const Persistent_interval & p2) {
542  return (sc_->filtration(get < 1 > (p1)) - sc_->filtration(get < 0 > (p1))
543  > sc_->filtration(get < 1 > (p2)) - sc_->filtration(get < 0 > (p2)));
544  }
545  FilteredComplex * sc_;
546  };
547 
548  public:
559  void output_diagram(std::ostream& ostream = std::cout) {
560  cmp_intervals_by_length cmp(cpx_);
561  std::sort(std::begin(persistent_pairs_), std::end(persistent_pairs_), cmp);
562  for (auto pair : persistent_pairs_) {
563  ostream << get<2>(pair) << " " << cpx_->dimension(get<0>(pair)) << " "
564  << cpx_->filtration(get<0>(pair)) << " "
565  << cpx_->filtration(get<1>(pair)) << " " << std::endl;
566  }
567  }
568 
569  void write_output_diagram(std::string diagram_name) {
570  std::ofstream diagram_out(diagram_name.c_str());
571  diagram_out.exceptions(diagram_out.failbit);
572  cmp_intervals_by_length cmp(cpx_);
573  std::sort(std::begin(persistent_pairs_), std::end(persistent_pairs_), cmp);
574  for (auto pair : persistent_pairs_) {
575  diagram_out << cpx_->dimension(get<0>(pair)) << " "
576  << cpx_->filtration(get<0>(pair)) << " "
577  << cpx_->filtration(get<1>(pair)) << std::endl;
578  }
579  }
580 
584  std::vector<int> betti_numbers() const {
585  // Init Betti numbers vector with zeros until Simplicial complex dimension and don't allocate a vector of negative
586  // size for an empty complex
587  std::vector<int> betti_numbers(std::max(dim_max_, 0));
588 
589  for (auto pair : persistent_pairs_) {
590  // Count never ended persistence intervals
591  if (cpx_->null_simplex() == get<1>(pair)) {
592  // Increment corresponding betti number
593  betti_numbers[cpx_->dimension(get<0>(pair))] += 1;
594  }
595  }
596  return betti_numbers;
597  }
598 
604  int betti_number(int dimension) const {
605  int betti_number = 0;
606 
607  for (auto pair : persistent_pairs_) {
608  // Count never ended persistence intervals
609  if (cpx_->null_simplex() == get<1>(pair)) {
610  if (cpx_->dimension(get<0>(pair)) == dimension) {
611  // Increment betti number found
612  ++betti_number;
613  }
614  }
615  }
616  return betti_number;
617  }
618 
624  std::vector<int> persistent_betti_numbers(Filtration_value from, Filtration_value to) const {
625  // Init Betti numbers vector with zeros until Simplicial complex dimension and don't allocate a vector of negative
626  // size for an empty complex
627  std::vector<int> betti_numbers(std::max(dim_max_, 0));
628  for (auto pair : persistent_pairs_) {
629  // Count persistence intervals that covers the given interval
630  // null_simplex test : if the function is called with to=+infinity, we still get something useful. And it will
631  // still work if we change the complex filtration function to reject null simplices.
632  if (cpx_->filtration(get<0>(pair)) <= from &&
633  (get<1>(pair) == cpx_->null_simplex() || cpx_->filtration(get<1>(pair)) > to)) {
634  // Increment corresponding betti number
635  betti_numbers[cpx_->dimension(get<0>(pair))] += 1;
636  }
637  }
638  return betti_numbers;
639  }
640 
647  int persistent_betti_number(int dimension, Filtration_value from, Filtration_value to) const {
648  int betti_number = 0;
649 
650  for (auto pair : persistent_pairs_) {
651  // Count persistence intervals that covers the given interval
652  // null_simplex test : if the function is called with to=+infinity, we still get something useful. And it will
653  // still work if we change the complex filtration function to reject null simplices.
654  if (cpx_->filtration(get<0>(pair)) <= from &&
655  (get<1>(pair) == cpx_->null_simplex() || cpx_->filtration(get<1>(pair)) > to)) {
656  if (cpx_->dimension(get<0>(pair)) == dimension) {
657  // Increment betti number found
658  ++betti_number;
659  }
660  }
661  }
662  return betti_number;
663  }
664 
668  const std::vector<Persistent_interval>& get_persistent_pairs() const {
669  return persistent_pairs_;
670  }
671 
676  std::vector< std::pair< Filtration_value , Filtration_value > >
677  intervals_in_dimension(int dimension) {
678  std::vector< std::pair< Filtration_value , Filtration_value > > result;
679  // auto && pair, to avoid unnecessary copying
680  for (auto && pair : persistent_pairs_) {
681  if (cpx_->dimension(get<0>(pair)) == dimension) {
682  result.emplace_back(cpx_->filtration(get<0>(pair)), cpx_->filtration(get<1>(pair)));
683  }
684  }
685  return result;
686  }
687 
688  private:
689  /*
690  * Structure representing a cocycle.
691  */
692  struct cocycle {
693  cocycle()
694  : row_(nullptr),
695  characteristics_() {
696  }
697  cocycle(Arith_element characteristics, Hcell * row)
698  : row_(row),
699  characteristics_(characteristics) {
700  }
701 
702  Hcell * row_; // points to the corresponding row in the CAM
703  Arith_element characteristics_; // product of field characteristics for which the cocycle exist
704  };
705 
706  public:
707  FilteredComplex * cpx_;
708  int dim_max_;
709  CoefficientField coeff_field_;
710  size_t num_simplices_;
711 
712  /* Disjoint sets data structure to link the model of FilteredComplex
713  * with the compressed annotation matrix.
714  * ds_rank_ is a property map Simplex_key -> int, ds_parent_ is a property map
715  * Simplex_key -> simplex_key_t */
716  std::vector<int> ds_rank_;
717  std::vector<Simplex_key> ds_parent_;
718  std::vector<Column *> ds_repr_;
719  boost::disjoint_sets<int *, Simplex_key *> dsets_;
720  /* The compressed annotation matrix fields.*/
721  Cam cam_;
722  /* Dictionary establishing the correspondence between the Simplex_key of
723  * the root vertex in the union-find ds and the Simplex_key of the vertex which
724  * created the connected component as a 0-dimension homology feature.*/
725  std::unordered_map<Simplex_key, Simplex_key> zero_cocycles_;
726  /* Key -> row. */
727  std::map<Simplex_key, cocycle> transverse_idx_;
728  /* Persistent intervals. */
729  std::vector<Persistent_interval> persistent_pairs_;
730  length_interval interval_length_policy;
731 
732  Simple_object_pool<Column> column_pool_;
733  Simple_object_pool<Cell> cell_pool_;
734 };
735 
736 } // namespace persistent_cohomology
737 
738 } // namespace Gudhi
739 
740 #endif // PERSISTENT_COHOMOLOGY_H_
Computes the persistent cohomology of a filtered complex.
Definition: Persistent_cohomology.h:54
std::vector< std::pair< Filtration_value, Filtration_value > > intervals_in_dimension(int dimension)
Returns persistence intervals for a given dimension.
Definition: Persistent_cohomology.h:677
void output_diagram(std::ostream &ostream=std::cout)
Output the persistence diagram in ostream.
Definition: Persistent_cohomology.h:559
std::tuple< Simplex_handle, Simplex_handle, Arith_element > Persistent_interval
Type for birth and death FilteredComplex::Simplex_handle. The Arith_element field is used for the mul...
Definition: Persistent_cohomology.h:68
FilteredComplex::Simplex_handle Simplex_handle
Handle to specify a simplex.
Definition: Persistent_cohomology.h:61
Persistent_cohomology(FilteredComplex &cpx, bool persistence_dim_max=false)
Initializes the Persistent_cohomology class.
Definition: Persistent_cohomology.h:97
int persistent_betti_number(int dimension, Filtration_value from, Filtration_value to) const
Returns the persistent Betti number of the dimension passed by parameter.
Definition: Persistent_cohomology.h:647
int betti_number(int dimension) const
Returns the Betti number of the dimension passed by parameter.
Definition: Persistent_cohomology.h:604
FilteredComplex::Simplex_key Simplex_key
Data stored for each simplex.
Definition: Persistent_cohomology.h:59
void compute_persistent_cohomology(Filtration_value min_interval_length=0)
Compute the persistent homology of the filtered simplicial complex.
Definition: Persistent_cohomology.h:168
void init_coefficients(int charac)
Initializes the coefficient field.
Definition: Persistent_cohomology.h:152
std::vector< int > betti_numbers() const
Returns Betti numbers.
Definition: Persistent_cohomology.h:584
void init_coefficients(int charac_min, int charac_max)
Initializes the coefficient field for multi-field persistent homology.
Definition: Persistent_cohomology.h:156
const std::vector< Persistent_interval > & get_persistent_pairs() const
Returns a list of persistence birth and death FilteredComplex::Simplex_handle pairs.
Definition: Persistent_cohomology.h:668
std::vector< int > persistent_betti_numbers(Filtration_value from, Filtration_value to) const
Returns the persistent Betti numbers.
Definition: Persistent_cohomology.h:624
CoefficientField::Element Arith_element
Type of element of the field.
Definition: Persistent_cohomology.h:65
FilteredComplex::Filtration_value Filtration_value
Type for the value of the filtration function.
Definition: Persistent_cohomology.h:63
Gudhi namespace.
Definition: SimplicialComplexForAlpha.h:14
Concept describing the requirements for a class to represent a field of coefficients to compute persi...
Definition: CoefficientField.h:14
Element additive_identity()
Element multiplicative_identity()
unspecified Element
Type of element of the field.
Definition: CoefficientField.h:19
Element characteristic()
void plus_equal(Element x, Element y)
The concept FilteredComplex describes the requirements for a type to implement a filtered cell comple...
Definition: FilteredComplex.h:17
unspecified Simplex_key
Data stored for each simplex.
Definition: FilteredComplex.h:91
Filtration_value filtration(Simplex_handle sh)
Returns the filtration value of a simplex.
void assign_key(Simplex_handle sh, Simplex_key n)
Store a number for a simplex, which can later be retrieved with key(sh).
Simplex_handle null_simplex()
Returns a Simplex_handle that is different from all simplex handles of the simplices.
Filtration_simplex_range filtration_simplex_range()
Returns a range over the simplices of the complex in the order of the filtration.
unspecified Simplex_handle
Handle to specify a simplex.
Definition: FilteredComplex.h:19
Simplex_key null_key()
Returns a constant dummy number that is either negative, or at least as large as num_simplices()....
Simplex_key key(Simplex_handle sh)
Returns the number stored for a simplex by assign_key.
unspecified Filtration_value
Type for the value of the filtration function.
Definition: FilteredComplex.h:23
int dimension(Simplex_handle sh)
Returns the dimension of a simplex.
Simplex_handle simplex(size_t idx)
Returns the simplex that has index idx in the filtration.
Boundary_simplex_range boundary_simplex_range(Simplex_handle sh)
Returns a range giving access to all simplices of the boundary of a simplex, i.e. the set of codimens...
Value type for a filtration function on a cell complex.
Definition: FiltrationValue.h:20