diff options
Diffstat (limited to 'src/Gudhi_stat')
| -rw-r--r-- | src/Gudhi_stat/utilities/Landscape_bootstrap.cpp | 34 |
1 files changed, 16 insertions, 18 deletions
diff --git a/src/Gudhi_stat/utilities/Landscape_bootstrap.cpp b/src/Gudhi_stat/utilities/Landscape_bootstrap.cpp index 0827bfdf..e6e96e68 100644 --- a/src/Gudhi_stat/utilities/Landscape_bootstrap.cpp +++ b/src/Gudhi_stat/utilities/Landscape_bootstrap.cpp @@ -28,16 +28,14 @@ #include <gudhi/persistence_representations/Vector_distances_in_diagram.h> //persistence part: #include <gudhi/reader_utils.h> -#include <gudhi/graph_simplicial_complex.h> +#include <gudhi/Rips_complex.h> #include <gudhi/distance_functions.h> #include <gudhi/Simplex_tree.h> #include <gudhi/Persistent_cohomology.h> -using namespace Gudhi; -using namespace Gudhi::Gudhi_stat; -using namespace Gudhi::persistent_cohomology; +using Persistence_landscape = Gudhi::Gudhi_stat::Persistence_landscape; typedef int Vertex_handle; typedef double Filtration_value; @@ -64,18 +62,18 @@ public: { points_in_subsample.push_back( this->points[ numbers_to_sample[i] ] ); } - //construct a Rips complex based on it and compute its persistence: - Graph_t prox_graph = compute_proximity_graph(points_in_subsample, this->threshold , euclidean_distance< std::vector< double > >); - // Construct the Rips complex in a Simplex Tree - Simplex_tree<Simplex_tree_options_fast_persistence> st; - // insert the proximity graph in the simplex tree - st.insert_graph(prox_graph); - // expand the graph until dimension dim_max - st.expansion(this->dim + 1); - // Sort the simplices in the order of the filtration - st.initialize_filtration(); - // Compute the persistence diagram of the complex - persistent_cohomology::Persistent_cohomology<Simplex_tree<Simplex_tree_options_fast_persistence>, Field_Zp > pcoh(st); + + using Stree = Gudhi::Simplex_tree<Gudhi::Simplex_tree_options_fast_persistence>; + using Filtration_value = Stree::Filtration_value; + using Rips_complex = Gudhi::rips_complex::Rips_complex<Filtration_value>; + //construct a Rips complex based on it and compute its persistence: + Rips_complex rips_complex(points_in_subsample, this->threshold, Euclidean_distance()); + // Construct the Rips complex in a Simplex Tree + Stree st; + // expand the graph until dimension dim_max + rips_complex.create_complex(st, this->dim + 1); + // Compute the persistence diagram of the complex + Gudhi::persistent_cohomology::Persistent_cohomology<Stree, Gudhi::persistent_cohomology::Field_Zp > pcoh(st); // initializes the coefficient field for homology pcoh.init_coefficients( this->coeficient_field ); pcoh.compute_persistent_cohomology(this->min_persistence); @@ -159,7 +157,7 @@ int main( int argc , char** argv ) std::cout << "Now we will read points from the file : " << filename << " and then perform " << number_of_repetitions_of_bootstrap << " times the bootstrap 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 = Gudhi::Gudhi_stat::read_numbers_from_file_line_by_line( filename ); std::cout << "Read : " << points.size() << " points.\n"; @@ -172,7 +170,7 @@ int main( int argc , char** argv ) //CharacteristicFunction is just identity, transforming std::vector< size_t > to itself. //DistanceBetweenPointsCharacteristics is the place were all happens. This class hace 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< + double result = Gudhi::Gudhi_stat::bootstrap< Persistence_landscape , //PointCloudCharacteristics, persistence landascapes constructed based on vector of //pairs of birth--death values in a cartain dimension. compute_persistence_landscape_of_a_point_cloud_in_certain_dimension , //CharacteristicFunction, in this case, we will need to compute persistence in a certain dimension. |