PSSK.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): Pawel Dlotko
4  *
5  * Copyright (C) 2016 Inria
6  *
7  * Modification(s):
8  * - YYYY/MM Author: Description of the modification
9  */
10 
11 #ifndef PSSK_H_
12 #define PSSK_H_
13 
14 // gudhi include
15 #include <gudhi/Persistence_heat_maps.h>
16 
17 #include <limits>
18 #include <utility>
19 #include <vector>
20 
21 namespace Gudhi {
22 namespace Persistence_representations {
23 
34 class PSSK : public Persistence_heat_maps<constant_scaling_function> {
35  public:
37 
38  PSSK(const std::vector<std::pair<double, double> >& interval,
39  std::vector<std::vector<double> > filter = create_Gaussian_filter(5, 1), size_t number_of_pixels = 1000,
40  double min_ = -1, double max_ = -1)
42  this->construct(interval, filter, number_of_pixels, min_, max_);
43  }
44 
45  PSSK(const char* filename, std::vector<std::vector<double> > filter = create_Gaussian_filter(5, 1),
46  size_t number_of_pixels = 1000, double min_ = -1, double max_ = -1,
47  unsigned dimension = std::numeric_limits<unsigned>::max())
49  std::vector<std::pair<double, double> > intervals_;
50  if (dimension == std::numeric_limits<unsigned>::max()) {
51  intervals_ = read_persistence_intervals_in_one_dimension_from_file(filename);
52  } else {
53  intervals_ = read_persistence_intervals_in_one_dimension_from_file(filename, dimension);
54  }
55  this->construct(intervals_, filter, number_of_pixels, min_, max_);
56  }
57 
58  protected:
59  void construct(const std::vector<std::pair<double, double> >& intervals_,
60  std::vector<std::vector<double> > filter = create_Gaussian_filter(5, 1),
61  size_t number_of_pixels = 1000, double min_ = -1, double max_ = -1);
62 };
63 
64 // if min_ == max_, then the program is requested to set up the values itself based on persistence intervals
65 void PSSK::construct(const std::vector<std::pair<double, double> >& intervals_,
66  std::vector<std::vector<double> > filter, size_t number_of_pixels, double min_, double max_) {
67  bool dbg = false;
68  if (dbg) {
69  std::cerr << "Entering construct procedure \n";
70  getchar();
71  }
72 
73  if (min_ == max_) {
74  // in this case, we want the program to set up the min_ and max_ values by itself.
75  min_ = std::numeric_limits<int>::max();
76  max_ = -std::numeric_limits<int>::max();
77 
78  for (size_t i = 0; i != intervals_.size(); ++i) {
79  if (intervals_[i].first < min_) min_ = intervals_[i].first;
80  if (intervals_[i].second > max_) max_ = intervals_[i].second;
81  }
82  // now we have the structure filled in, and moreover we know min_ and max_ values of the interval, so we know the
83  // range.
84 
85  // add some more space:
86  min_ -= fabs(max_ - min_) / 100;
87  max_ += fabs(max_ - min_) / 100;
88  }
89 
90  if (dbg) {
91  std::cerr << "min_ : " << min_ << std::endl;
92  std::cerr << "max_ : " << max_ << std::endl;
93  std::cerr << "number_of_pixels : " << number_of_pixels << std::endl;
94  getchar();
95  }
96 
97  this->min_ = min_;
98  this->max_ = max_;
99 
100  // initialization of the structure heat_map
101  std::vector<std::vector<double> > heat_map_;
102  for (size_t i = 0; i != number_of_pixels; ++i) {
103  std::vector<double> v(number_of_pixels, 0);
104  heat_map_.push_back(v);
105  }
106  this->heat_map = heat_map_;
107 
108  if (dbg) std::cerr << "Done creating of the heat map, now we will fill in the structure \n";
109 
110  for (size_t pt_nr = 0; pt_nr != intervals_.size(); ++pt_nr) {
111  // compute the value of intervals_[pt_nr] in the grid:
112  int x_grid =
113  static_cast<int>((intervals_[pt_nr].first - this->min_) / (this->max_ - this->min_) * number_of_pixels);
114  int y_grid =
115  static_cast<int>((intervals_[pt_nr].second - this->min_) / (this->max_ - this->min_) * number_of_pixels);
116 
117  if (dbg) {
118  std::cerr << "point : " << intervals_[pt_nr].first << " , " << intervals_[pt_nr].second << std::endl;
119  std::cerr << "x_grid : " << x_grid << std::endl;
120  std::cerr << "y_grid : " << y_grid << std::endl;
121  }
122 
123  // x_grid and y_grid gives a center of the kernel. We want to have its lower left corner. To get this, we need to
124  // shift x_grid and y_grid by a grid diameter.
125  x_grid -= filter.size() / 2;
126  y_grid -= filter.size() / 2;
127  // note that the numbers x_grid and y_grid may be negative.
128 
129  if (dbg) {
130  std::cerr << "After shift : \n";
131  std::cerr << "x_grid : " << x_grid << std::endl;
132  std::cerr << "y_grid : " << y_grid << std::endl;
133  std::cerr << "filter.size() : " << filter.size() << std::endl;
134  getchar();
135  }
136 
137  for (size_t i = 0; i != filter.size(); ++i) {
138  for (size_t j = 0; j != filter.size(); ++j) {
139  // if the point (x_grid+i,y_grid+j) is the correct point in the grid.
140  if (((x_grid + i) >= 0) && (x_grid + i < this->heat_map.size()) && ((y_grid + j) >= 0) &&
141  (y_grid + j < this->heat_map.size())) {
142  if (dbg) {
143  std::cerr << y_grid + j << " " << x_grid + i << std::endl;
144  }
145  this->heat_map[y_grid + j][x_grid + i] += filter[i][j];
146  this->heat_map[x_grid + i][y_grid + j] += -filter[i][j];
147  }
148  }
149  }
150  }
151 } // construct
152 
153 } // namespace Persistence_representations
154 } // namespace Gudhi
155 
156 #endif // PSSK_H_
A class implementing persistence heat maps.
Definition: Persistence_heat_maps.h:178
Definition: SimplicialComplexForAlpha.h:14
GUDHI  Version 3.3.0  - C++ library for Topological Data Analysis (TDA) and Higher Dimensional Geometry Understanding.  - Copyright : MIT Generated on Tue Aug 11 2020 11:09:13 for GUDHI by Doxygen 1.8.13