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Diffstat (limited to 'src/Gudhi_stat/utilities/Hausdorff_subsampling.cpp')
| -rw-r--r-- | src/Gudhi_stat/utilities/Hausdorff_subsampling.cpp | 138 |
1 files changed, 0 insertions, 138 deletions
diff --git a/src/Gudhi_stat/utilities/Hausdorff_subsampling.cpp b/src/Gudhi_stat/utilities/Hausdorff_subsampling.cpp deleted file mode 100644 index 44de1029..00000000 --- a/src/Gudhi_stat/utilities/Hausdorff_subsampling.cpp +++ /dev/null @@ -1,138 +0,0 @@ -/* 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/>. - */ - - -#include <gudhi/Hausdorff_distances.h> -#include <gudhi/bootstrap.h> -#include <gudhi/read_persistence_from_file.h> -#include <gudhi/persistence_vectors.h> - - -using namespace Gudhi; -using namespace Gudhi::Persistence_representations; -using namespace Gudhi::Gudhi_stat; - - - -int main( int argc , char** argv ) -{ - std::cout << "The parameters of this program are : " << std::endl; - std::cout << "(a) a name of a file with points," << std:: endl; - std::cout << "(b) a number of repetitions of bootstrap (integer)," << std::endl; - std::cout << "(c) a size of subsample (integer, smaller than the number of points," << std::endl; - std::cout << "(d) a quantile (real number between 0 and 1. If you do not know what to set, set it to 0.95." << std::endl; - if ( argc != 5 ) - { - std::cerr << "Wrong number of parameters, the program will now terminate.\n"; - return 1; - } - - const char* filename = argv[1]; - size_t number_of_repetitions_of_subsampling = (size_t)atoi( argv[2] ); - size_t size_of_subsample = (size_t)atoi( argv[3] ); - double quantile = atof( argv[4] ); - - std::cout << "Now we will read points from the file : " << filename << " and then perform " << number_of_repetitions_of_subsampling << " times the subsampling on it by choosing subsample of a size " << size_of_subsample << std::endl; - - std::vector< std::vector< double > > points = read_numbers_from_file_line_by_line( filename ); - /* - std::vector< std::vector< double > > points; - std::vector< double > point1(2); - point1[0] = -1; - point1[1] = 0; - std::vector< double > point2(2); - point2[0] = 1; - point2[1] = 0; - std::vector< double > point3(2); - point3[0] = -1; - point3[1] = 3; - std::vector< double > point4(2); - point4[0] = 1; - point4[1] = 3; - points.push_back( point1 ); - points.push_back( point2 ); - points.push_back( point3 ); - points.push_back( point4 ); - size_of_subsample = 2; - */ -// std::vector< std::vector<double> > all_to_all_distance_matrix_between_points = compute_all_to_all_distance_matrix_between_points< std::vector<double> , Euclidean_distance >( points ); -// Hausdorff_distance_between_subspace_and_the_whole_metric_space distance( all_to_all_distance_matrix_between_points ); - - - std::cout << "Read : " << points.size() << " points.\n"; - - //comute all-to-all distance matrix: - std::vector< std::vector<double> > all_to_all_distance_matrix_between_points = compute_all_to_all_distance_matrix_between_points< std::vector<double> , Euclidean_distance >( points ); - Hausdorff_distance_between_subspace_and_the_whole_metric_space distance( all_to_all_distance_matrix_between_points ); - identity< std::vector<size_t> > identity_char; - - - double max = -1; - for ( size_t i = 0 ; i != all_to_all_distance_matrix_between_points.size() ; ++i ) - { - double min = 10000000; - for ( size_t j = 0 ; j != all_to_all_distance_matrix_between_points.size() ; ++j ) - { - double distance = 0; - if ( i > j ) - { - distance = all_to_all_distance_matrix_between_points[i][j]; - } - else - { - if ( i < j )distance = all_to_all_distance_matrix_between_points[j][i]; - } - if ( (distance < min)&&(distance != 0) )min = distance; - } - std::cerr << "min : " << min << std::endl; - //getchar(); - if ( min > max )max = min; - } - std::cerr << "Max element in distance matrix : " << max << std::endl; - getchar(); - -// std::vector<size_t> characteristic_of_all_points = {0,1,2,3}; -// std::vector<size_t> characteristic_of_subsampled_points = {2,3}; -// std::cerr << "DISTANCE BETWEEN SAMPLE AND SUBSAMPLE: " << distance( characteristic_of_subsampled_points , characteristic_of_all_points ) << std::endl; - - - - - - //and now we can run the real bootstrap. - //template < typename PointCloudCharacteristics , typename CharacteristicFunction , typename DistanceBetweenPointsCharacteristics > - //In this case, the PointCloudCharacteristics is just a vector of numbers of points (in a order fixed on points vector). - //CharacteristicFunction is just identity, transforming std::vector< size_t > to itself. - //DistanceBetweenPointsCharacteristics is the place were all happens. This class have the information about the coordinates of the points, and allows to compute a Hausdorff distance between - //the collection of all points, and the subsample. - double result = bootstrap< - std::vector< size_t > , //PointCloudCharacteristics - identity< std::vector<size_t> > , //CharacteristicFunction - Hausdorff_distance_between_subspace_and_the_whole_metric_space //DistanceBetweenPointsCharacteristics. This function have the information about point's coordinates. - > - ( points.size() , identity_char , distance , number_of_repetitions_of_subsampling , size_of_subsample , quantile ); - - std::cout << "result of the subsampling : " << 2*result << std::endl; - - - return 0; -} |