diff options
Diffstat (limited to 'src/Gudhi_stat/include/gudhi/multiplicative_bootstrap.h')
| -rw-r--r-- | src/Gudhi_stat/include/gudhi/multiplicative_bootstrap.h | 180 |
1 files changed, 180 insertions, 0 deletions
diff --git a/src/Gudhi_stat/include/gudhi/multiplicative_bootstrap.h b/src/Gudhi_stat/include/gudhi/multiplicative_bootstrap.h new file mode 100644 index 00000000..c350349c --- /dev/null +++ b/src/Gudhi_stat/include/gudhi/multiplicative_bootstrap.h @@ -0,0 +1,180 @@ +/* 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): Pawel Dlotko + * + * Copyright (C) 2015 INRIA (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 BOOTSTRAP_H +#define BOOTSTRAP_H + +//concretizations +#include <gudhi/persistence_representations/Vector_distances_in_diagram.h> +#include <gudhi/persistence_representations/Persistence_landscape.h> +#include <gudhi/persistence_representations/Persistence_landscape_on_grid.h> +#include <gudhi/persistence_representations/Persistence_heat_maps.h> + +#ifdef GUDHI_USE_TBB +#include <tbb/parallel_sort.h> +#include <tbb/task_scheduler_init.h> +#endif + +#include <vector> +#include <algorithm> +#include <omp.h> +#include <random> +#include <ctime> + +namespace Gudhi +{ +namespace Gudhi_stat +{ + +template < typename TopologicalObject > +class difference_of_objects +{ +public: + TopologicalObject operator()( const TopologicalObject& first, const TopologicalObject& second )const + { + return first-second; + } +}; + +template < typename TopologicalObject > +class norm_of_objects +{ +public: + norm_of_objects():power(1){} + norm_of_objects( double power_ ):power(power_){} + double operator()( const TopologicalObject& obj )const + { + TopologicalObject empty; + double dist = empty.distance( obj , power ); + //std::cerr << "dist : " << dist << std::endl;getchar(); + return dist; + } +private: + double power; +}; + + + +/** +* This is a generic function to perform multiplicative bootstrap. +**/ +template < typename TopologicalObject , typename OperationOnObjects , typename NormOnObjects > +double multiplicative_bootstrap( const std::vector< TopologicalObject* >& topological_objects , size_t number_of_bootstrap_operations , const OperationOnObjects& oper , const NormOnObjects& norm , double quantile = 0.95 , size_t maximal_number_of_threads_in_TBB = std::numeric_limits<size_t>::max() ) +{ + bool dbg = false; + + #ifdef GUDHI_USE_TBB + tbb::task_scheduler_init init(maximal_number_of_threads_in_TBB == std::numeric_limits<size_t>::max() ? tbb::task_scheduler_init::automatic : maximal_number_of_threads_in_TBB); + #endif + + //initialization of a random number generator: + std::random_device rd; + std::mt19937 generator( time(NULL) ); + std::normal_distribution<> norm_distribution(0.,1.); + + + //first compute an average of topological_objects + TopologicalObject average; + average.compute_average( topological_objects ); + + std::vector< double > vector_of_intermediate_characteristics( number_of_bootstrap_operations , 0 ); + + + #ifdef GUDHI_USE_TBB + tbb::parallel_for ( tbb::blocked_range<size_t>(0, number_of_bootstrap_operations), [&](const tbb::blocked_range<size_t>& range) + { + for ( size_t it_no = range.begin() ; it_no != range.end() ; ++it_no ) + #else + for ( size_t it_no = 0 ; it_no < number_of_bootstrap_operations ; ++it_no ) + #endif + { + if ( dbg ) + { + std::cout << "Still : " << number_of_bootstrap_operations-it_no << " tests to go. \n The subsampled vector consist of points number : "; + } + + + //and compute the intermediate characteristic: + TopologicalObject result; + for ( size_t i = 0 ; i != topological_objects.size() ; ++i ) + { + double rand_variable = norm_distribution( generator ); + result = result + rand_variable*oper(*(topological_objects[i]) , average); + } + if ( dbg ) + { + std::cerr << "Result 1 : " << result << std::endl; + getchar(); + } + //HERE THE NORM SEEMS TO BE MISSING!! + result = result.abs(); + if ( dbg ) + { + std::cerr << "Result 2 : " << result << std::endl; + getchar(); + } + result = result*(1.0/sqrt( topological_objects.size() )); + if ( dbg ) + { + std::cerr << "Result 3 : " << result << std::endl; + getchar(); + } + //NEED TO TAKE MAX + if ( dbg ) + { + std::cerr << "Result 4 : " << norm(result) << std::endl; + getchar(); + } + vector_of_intermediate_characteristics[it_no] = norm(result); + } + #ifdef GUDHI_USE_TBB + } + ); + #endif + + + + size_t position_of_quantile = floor(quantile*vector_of_intermediate_characteristics.size()); + if ( position_of_quantile ) --position_of_quantile; + if ( dbg ) + { + std::cout << "position_of_quantile : " << position_of_quantile << ", and here is the array : " << std::endl; + for ( size_t i = 0 ; i != vector_of_intermediate_characteristics.size() ; ++i ) + { + std::cout << vector_of_intermediate_characteristics[i] << std::endl; + } + std::cout << std::endl; + } + + //now we need to sort the vector_of_distances and find the quantile: + std::nth_element (vector_of_intermediate_characteristics.begin(), vector_of_intermediate_characteristics.begin()+position_of_quantile, vector_of_intermediate_characteristics.end()); + double result = vector_of_intermediate_characteristics[ position_of_quantile ]/(sqrt( topological_objects.size() )); + if ( dbg )std::cout << "Result : " << result << std::endl; + + return result; + +}//multiplicative_bootstrap + +}//namespace Gudhi_stat +}//namespace Gudhi + +#endif |