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/* This file is part of the Gudhi Library. The Gudhi library
* (Geometric Understanding in Higher Dimensions) is a generic C++
* library for computational topology.
*
* Author(s): Siargey Kachanovich
*
* Copyright (C) 2015 INRIA Sophia Antipolis-Méditerranée (France)
*
* This program is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
#ifndef STRONG_WITNESS_COMPLEX_H_
#define STRONG_WITNESS_COMPLEX_H_
#include <utility>
#include <vector>
#include <list>
#include <limits>
#include "Active_witness/Active_witness.h"
#include <gudhi/Kd_tree_search.h>
namespace gss = Gudhi::spatial_searching;
namespace Gudhi {
namespace witness_complex {
template< class Kernel_ >
class Strong_witness_complex {
private:
typedef Kernel_ K;
typedef typename K::Point_d Point_d;
typedef typename K::FT FT;
typedef std::vector<Point_d> Point_range;
typedef gss::Kd_tree_search<Kernel_, Point_range> Kd_tree;
typedef typename Kd_tree::INS_range Nearest_landmark_range;
typedef typename std::vector<Nearest_landmark_range> Nearest_landmark_table;
typedef typename Nearest_landmark_range::iterator Nearest_landmark_row_iterator;
typedef std::vector< double > Point_t;
typedef std::vector< Point_t > Point_Vector;
typedef FT Filtration_value;
typedef std::ptrdiff_t Witness_id;
typedef typename Nearest_landmark_range::Point_with_transformed_distance Id_distance_pair;
typedef typename Id_distance_pair::first_type Landmark_id;
typedef Active_witness<Id_distance_pair, Nearest_landmark_range> ActiveWitness;
typedef std::list< ActiveWitness > ActiveWitnessList;
typedef std::vector< Landmark_id > typeVectorVertex;
typedef std::pair< typeVectorVertex, Filtration_value> typeSimplex;
private:
Point_range witnesses_, landmarks_;
Kd_tree landmark_tree_;
public:
/////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
/* @name Constructor
*/
//@{
/*
* \brief Initializes member variables before constructing simplicial complex.
* \details The parameters should satisfy InputIterator C++ concepts.
*/
template< typename InputIteratorLandmarks,
typename InputIteratorWitnesses >
Strong_witness_complex(InputIteratorLandmarks landmarks_first,
InputIteratorLandmarks landmarks_last,
InputIteratorWitnesses witnesses_first,
InputIteratorWitnesses witnesses_last)
: witnesses_(witnesses_first, witnesses_last), landmarks_(landmarks_first, landmarks_last), landmark_tree_(landmarks_)
{
}
/** \brief Returns the point corresponding to the given vertex.
*/
Point_d get_point( std::size_t vertex ) const
{
return landmarks_[vertex];
}
/** \brief Outputs the (strong) witness complex with
* squared relaxation parameter 'max_alpha_square'
* to simplicial complex 'complex'.
* The parameter 'limit_dimension' represents the maximal dimension of the simplicial complex
* (default value = no limit).
*/
template < typename SimplicialComplexForWitness >
bool create_complex(SimplicialComplexForWitness& complex,
FT max_alpha_square,
Landmark_id limit_dimension = std::numeric_limits<Landmark_id>::max())
{
std::size_t nbL = landmarks_.size();
Landmark_id complex_dim = 0;
if (complex.num_vertices() > 0) {
std::cerr << "Strong witness complex cannot create complex - complex is not empty.\n";
return false;
}
if (max_alpha_square < 0) {
std::cerr << "Strong witness complex cannot create complex - squared relaxation parameter must be non-negative.\n";
return false;
}
if (limit_dimension < 0) {
std::cerr << "Strong witness complex cannot create complex - limit dimension must be non-negative.\n";
return false;
}
typeVectorVertex vv;
for (unsigned i = 0; i != nbL; ++i) {
// initial fill of 0-dimensional simplices
vv = {i};
complex.insert_simplex(vv, Filtration_value(0.0));
}
for (auto w: witnesses_) {
ActiveWitness aw(landmark_tree_.query_incremental_nearest_neighbors(w));
typeVectorVertex simplex;
typename ActiveWitness::iterator aw_it = aw.begin();
float lim_dist2 = aw.begin()->second + max_alpha_square;
while ((Landmark_id)simplex.size() <= limit_dimension + 1 && aw_it != aw.end() && aw_it->second < lim_dist2) {
simplex.push_back(aw_it->first);
complex.insert_simplex_and_subfaces(simplex, aw_it->second - aw.begin()->second);
aw_it++;
}
if ((Landmark_id)simplex.size() - 1 > complex_dim)
complex_dim = simplex.size() - 1;
}
complex.set_dimension(complex_dim);
return true;
}
//@}
};
} // namespace witness_complex
} // namespace Gudhi
#endif
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