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Diffstat (limited to 'src/Persistence_representations/test/persistence_heat_maps_test.cpp')
-rw-r--r-- | src/Persistence_representations/test/persistence_heat_maps_test.cpp | 324 |
1 files changed, 324 insertions, 0 deletions
diff --git a/src/Persistence_representations/test/persistence_heat_maps_test.cpp b/src/Persistence_representations/test/persistence_heat_maps_test.cpp new file mode 100644 index 00000000..b3240758 --- /dev/null +++ b/src/Persistence_representations/test/persistence_heat_maps_test.cpp @@ -0,0 +1,324 @@ +/* This file is part of the Gudhi Library - https://gudhi.inria.fr/ - which is released under MIT. + * See file LICENSE or go to https://gudhi.inria.fr/licensing/ for full license details. + * Author(s): Pawel Dlotko + * + * Copyright (C) 2016 Inria + * + * Modification(s): + * - YYYY/MM Author: Description of the modification + */ + +#define BOOST_TEST_DYN_LINK +#define BOOST_TEST_MODULE "Persistence_heat_maps_test" +#include <boost/test/unit_test.hpp> +#include <gudhi/reader_utils.h> +#include <gudhi/Persistence_heat_maps.h> +#include <gudhi/Unitary_tests_utils.h> + +#include <iostream> + +using namespace Gudhi; +using namespace Gudhi::Persistence_representations; + +double epsilon = 0.0005; + +BOOST_AUTO_TEST_CASE(check_construction_of_heat_maps) { + std::vector<std::vector<double> > filter = create_Gaussian_filter(100, 1); + Persistence_heat_maps<constant_scaling_function> p("data/file_with_diagram", filter, false, 1000, 0, 1); + p.print_to_file("data/persistence_heat_map_from_file_with_diagram"); + + Persistence_heat_maps<constant_scaling_function> q; + q.load_from_file("data/persistence_heat_map_from_file_with_diagram"); + + BOOST_CHECK(p == q); +} + +BOOST_AUTO_TEST_CASE(check_averages_of_heat_maps) { + std::vector<std::vector<double> > filter = create_Gaussian_filter(30, 1); + Persistence_heat_maps<constant_scaling_function> p("data/file_with_diagram", filter, false, 1000, 0, 10); + Persistence_heat_maps<constant_scaling_function> q("data/file_with_diagram_1", filter, false, 1000, 0, 10); + Persistence_heat_maps<constant_scaling_function> r("data/file_with_diagram_2", filter, false, 1000, 0, 10); + + Persistence_heat_maps<constant_scaling_function> av; + av.compute_average({&p, &q, &r}); + + Persistence_heat_maps<constant_scaling_function> template_average; + template_average.load_from_file("data/template_average_of_heat_maps"); + + BOOST_CHECK(av == template_average); +} + +BOOST_AUTO_TEST_CASE(check_median_of_heat_maps) { + std::vector<std::vector<double> > filter = create_Gaussian_filter(30, 1); + Persistence_heat_maps<constant_scaling_function> p("data/file_with_diagram", filter, false, 1000, 0, 1); + Persistence_heat_maps<constant_scaling_function> q("data/file_with_diagram_1", filter, false, 1000, 0, 1); + Persistence_heat_maps<constant_scaling_function> r("data/file_with_diagram_2", filter, false, 1000, 0, 1); + + std::vector<Persistence_heat_maps<constant_scaling_function>*> to_compute_median; + to_compute_median.push_back(&p); + to_compute_median.push_back(&q); + to_compute_median.push_back(&r); + Persistence_heat_maps<constant_scaling_function> median; + median.compute_median(to_compute_median); + + Persistence_heat_maps<constant_scaling_function> template_median; + template_median.load_from_file("data/template_median_of_heat_maps"); + + BOOST_CHECK(median == template_median); +} + +BOOST_AUTO_TEST_CASE(check_compute_percentage_of_active_of_heat_maps) { + std::vector<std::vector<double> > filter = create_Gaussian_filter(30, 1); + Persistence_heat_maps<constant_scaling_function> p("data/file_with_diagram", filter, false, 1000, 0, 1); + Persistence_heat_maps<constant_scaling_function> q("data/file_with_diagram_1", filter, false, 1000, 0, 1); + Persistence_heat_maps<constant_scaling_function> r("data/file_with_diagram_2", filter, false, 1000, 0, 1); + + std::vector<Persistence_heat_maps<constant_scaling_function>*> to_compute_percentage_of_active; + to_compute_percentage_of_active.push_back(&p); + to_compute_percentage_of_active.push_back(&q); + to_compute_percentage_of_active.push_back(&r); + Persistence_heat_maps<constant_scaling_function> percentage_of_active; + percentage_of_active.compute_percentage_of_active(to_compute_percentage_of_active, 0.1); + + Persistence_heat_maps<constant_scaling_function> template_percentage_of_active; + template_percentage_of_active.load_from_file("data/template_percentage_of_active_of_heat_maps"); + + BOOST_CHECK(percentage_of_active == template_percentage_of_active); +} + +BOOST_AUTO_TEST_CASE(check_vectorize_for_heat_maps) { + std::vector<std::vector<double> > filter = create_Gaussian_filter(30, 1); + Persistence_heat_maps<constant_scaling_function> p("data/file_with_diagram", filter, false, 5, 0, 1); + + std::vector<double> p_vect_template; + + p_vect_template.push_back(0.0606728); + p_vect_template.push_back(0.0610023); + p_vect_template.push_back(0.0607978); + p_vect_template.push_back(0.0600647); + p_vect_template.push_back(0.0588224); + p_vect_template.push_back(0.0619829); + p_vect_template.push_back(0.0623218); + p_vect_template.push_back(0.0621152); + p_vect_template.push_back(0.0613686); + p_vect_template.push_back(0.0601016); + p_vect_template.push_back(0.0627679); + p_vect_template.push_back(0.0631134); + p_vect_template.push_back(0.0629066); + p_vect_template.push_back(0.0621528); + p_vect_template.push_back(0.0608719); + p_vect_template.push_back(0.0630073); + p_vect_template.push_back(0.0633564); + p_vect_template.push_back(0.0631511); + p_vect_template.push_back(0.0623968); + p_vect_template.push_back(0.0611132); + p_vect_template.push_back(0.0626947); + p_vect_template.push_back(0.0630445); + p_vect_template.push_back(0.0628425); + p_vect_template.push_back(0.0620941); + p_vect_template.push_back(0.060819); + + std::vector<double> p_vect = p.vectorize(0); + for (size_t i = 0; i != p_vect.size(); ++i) { + BOOST_CHECK(almost_equal(p_vect_template[i], p_vect[i])); + } +} + +BOOST_AUTO_TEST_CASE(check_distance_for_heat_maps) { + std::vector<std::vector<double> > filter = create_Gaussian_filter(30, 1); + Persistence_heat_maps<constant_scaling_function> p("data/file_with_diagram", filter, false, 1000, 0, 1); + Persistence_heat_maps<constant_scaling_function> q("data/file_with_diagram_1", filter, false, 1000, 0, 1); + Persistence_heat_maps<constant_scaling_function> r("data/file_with_diagram_2", filter, false, 1000, 0, 1); + + GUDHI_TEST_FLOAT_EQUALITY_CHECK(p.distance(p), 0., epsilon); + GUDHI_TEST_FLOAT_EQUALITY_CHECK(p.distance(q), 624.183, epsilon); + GUDHI_TEST_FLOAT_EQUALITY_CHECK(p.distance(r), 415.815, epsilon); + GUDHI_TEST_FLOAT_EQUALITY_CHECK(q.distance(p), 624.183, epsilon); + GUDHI_TEST_FLOAT_EQUALITY_CHECK(q.distance(q), 0., epsilon); + GUDHI_TEST_FLOAT_EQUALITY_CHECK(q.distance(r), 528.066, epsilon); + GUDHI_TEST_FLOAT_EQUALITY_CHECK(r.distance(p), 415.815, epsilon); + GUDHI_TEST_FLOAT_EQUALITY_CHECK(r.distance(q), 528.066, epsilon); + GUDHI_TEST_FLOAT_EQUALITY_CHECK(r.distance(r), 0., epsilon); +} + +BOOST_AUTO_TEST_CASE(check_projections_to_R_for_heat_maps) { + std::vector<std::vector<double> > filter = create_Gaussian_filter(30, 1); + Persistence_heat_maps<constant_scaling_function> p("data/file_with_diagram", filter, false, 1000, 0, 1); + Persistence_heat_maps<constant_scaling_function> q("data/file_with_diagram_1", filter, false, 1000, 0, 1); + Persistence_heat_maps<constant_scaling_function> r("data/file_with_diagram_2", filter, false, 1000, 0, 1); + + GUDHI_TEST_FLOAT_EQUALITY_CHECK(p.project_to_R(0), 44.3308, epsilon); + GUDHI_TEST_FLOAT_EQUALITY_CHECK(q.project_to_R(0), 650.568, epsilon); + GUDHI_TEST_FLOAT_EQUALITY_CHECK(r.project_to_R(0), 429.287, epsilon); +} + +BOOST_AUTO_TEST_CASE(check_scalar_products_for_heat_maps) { + std::vector<std::vector<double> > filter = create_Gaussian_filter(30, 1); + Persistence_heat_maps<constant_scaling_function> p("data/file_with_diagram", filter, false, 1000, 0, 1); + Persistence_heat_maps<constant_scaling_function> q("data/file_with_diagram_1", filter, false, 1000, 0, 1); + Persistence_heat_maps<constant_scaling_function> r("data/file_with_diagram_2", filter, false, 1000, 0, 1); + + GUDHI_TEST_FLOAT_EQUALITY_CHECK(p.compute_scalar_product(p), 0.0345687, epsilon); + GUDHI_TEST_FLOAT_EQUALITY_CHECK(p.compute_scalar_product(q), 0.0509357, epsilon); + GUDHI_TEST_FLOAT_EQUALITY_CHECK(p.compute_scalar_product(r), 0.0375608, epsilon); + GUDHI_TEST_FLOAT_EQUALITY_CHECK(q.compute_scalar_product(p), 0.0509357, epsilon); + GUDHI_TEST_FLOAT_EQUALITY_CHECK(q.compute_scalar_product(q), 1.31293, epsilon); + GUDHI_TEST_FLOAT_EQUALITY_CHECK(q.compute_scalar_product(r), 0.536799, epsilon); + GUDHI_TEST_FLOAT_EQUALITY_CHECK(r.compute_scalar_product(p), 0.0375608, epsilon); + GUDHI_TEST_FLOAT_EQUALITY_CHECK(r.compute_scalar_product(q), 0.536799, epsilon); + GUDHI_TEST_FLOAT_EQUALITY_CHECK(r.compute_scalar_product(r), 0.672907, epsilon); +} + +BOOST_AUTO_TEST_CASE(check_arythmetic_operations_for_heat_maps) { + std::vector<std::vector<double> > filter = create_Gaussian_filter(30, 1); + Persistence_heat_maps<constant_scaling_function> p("data/file_with_diagram", filter, false, 1000, 0, 1); + Persistence_heat_maps<constant_scaling_function> q("data/file_with_diagram_1", filter, false, 1000, 0, 1); + + Persistence_heat_maps<constant_scaling_function> sum = p + q; + Persistence_heat_maps<constant_scaling_function> difference = p - q; + Persistence_heat_maps<constant_scaling_function> multiply_by_scalar = 2 * p; + + // sum.print_to_file( "sum" ); + // difference.print_to_file( "difference" ); + // multiply_by_scalar.print_to_file( "multiply_by_scalar" ); + + Persistence_heat_maps<constant_scaling_function> sum_template; + sum_template.load_from_file("data/heat_map_sum"); + Persistence_heat_maps<constant_scaling_function> difference_template; + difference_template.load_from_file("data/heat_map_difference"); + Persistence_heat_maps<constant_scaling_function> multiply_by_scalar_template; + multiply_by_scalar_template.load_from_file("data/heat_map_multiply_by_scalar"); + + BOOST_CHECK(sum == sum_template); +} + +BOOST_AUTO_TEST_CASE(check_distance_of_heat_maps_infinite_power_parameters) { + std::vector<std::vector<double> > filter = create_Gaussian_filter(100, 1); + Persistence_heat_maps<constant_scaling_function> p("data/file_with_diagram", filter, false, 1000, 0, 1); + + std::vector<std::vector<double> > filter_2 = create_Gaussian_filter(150, 1); + Persistence_heat_maps<constant_scaling_function> q("data/file_with_diagram", filter_2, true, 1000, 0, 1); + + double distance_max_double_parameter = p.distance(q, std::numeric_limits<double>::max()); + double distance_inf_double_parameter = p.distance(q, std::numeric_limits<double>::infinity()); + + // std::cerr << "distance_max_double_parameter: " << distance_max_double_parameter << std::endl; + // std::cerr << "distance_inf_double_parameter: " << distance_inf_double_parameter << std::endl; + + BOOST_CHECK(distance_max_double_parameter == distance_inf_double_parameter); +} + +// Below I am storing the code used to generate tests for that functionality. +/* + std::vector< std::pair< double,double > > intervals; + intervals.push_back( std::make_pair(0.5,0.5) ); + std::vector< std::vector<double> > filter = create_Gaussian_filter(5,1); + Persistence_heat_maps p( intervals , filter , constant_function, false , 100 , 0 , 1 ); + p.plot( "heat_map_1" ); + + + std::vector< std::pair< double,double > > intervals2; + intervals2.push_back( std::make_pair(7,12) ); + Persistence_heat_maps q( intervals2 , filter , constant_function, false , 100 , 0 , 10 ); + q.plot( "heat_map_2" ); +*/ +/* + std::vector< std::pair< double,double > > intervals; + intervals.push_back( std::make_pair(0.5,0.5) ); + std::vector< std::vector<double> > filter = create_Gaussian_filter(5,1); + Persistence_heat_maps p( intervals , filter , constant_function, false , 10 , 0 , 1 ); + p.write_to_file( "aaa" ); + + Persistence_heat_maps q; + q.load_from_file( "aaa" ); + + cerr << ( p == q ) << endl; + */ + +/* + std::vector< std::vector<double> > filter = create_Gaussian_filter(30,1); + Persistence_heat_maps p( "file_with_diagram" , filter , constant_function, false , 100 , 0 , 1 ); + p.plot( "heat_map_1" ); +*/ + +/* + //test to construct persistence heat map: + std::vector< std::vector<double> > filter = create_Gaussian_filter(100,1); + Persistence_heat_maps p( "file_with_diagram" , filter , constant_function, false , 1000 , 0 , 1 ); + p.print_to_file( "persistence_heat_map_from_file_with_diagram" ); + + Persistence_heat_maps q; + q.load_from_file( "persistence_heat_map_from_file_with_diagram" ); + + cerr << (p == q) << endl; +*/ +/* + //test of computations of a mean: + std::vector< std::pair< double,double > > intervals; + intervals.push_back( std::make_pair(5,5) ); + std::vector< std::vector<double> > filter = create_Gaussian_filter(5,1); + Persistence_heat_maps p( intervals , filter , constant_function, false , 100 , 0 , 10 ); + p.plot( "heat_map_1" ); + + + std::vector< std::pair< double,double > > intervals2; + intervals2.push_back( std::make_pair(7,7) ); + Persistence_heat_maps q( intervals2 , filter , constant_function, false , 100 , 0 , 10 ); + q.plot( "heat_map_2" ); + + + Persistence_heat_maps av; + av.compute_average( { &P , &q } ); + av.plot( "average" ); +*/ + +/* + std::vector< std::vector<double> > filter = create_Gaussian_filter(30,1); + Persistence_heat_maps p( "file_with_diagram" , filter , constant_function, false , 1000 , 0 , 10 ); + Persistence_heat_maps q( "file_with_diagram_1" , filter , constant_function, false , 1000 , 0 , 10 ); + Persistence_heat_maps r( "file_with_diagram_2" , filter , constant_function, false , 1000 , 0 , 10 ); + Persistence_heat_maps av; + av.compute_average( {&p,&q,&r} ); + + av.print_to_file( "template_average_of_heat_maps" ); +*/ + +/* + std::vector< std::pair< double,double > > intervals; + intervals.push_back( std::make_pair(5,5) ); + std::vector< std::vector<double> > filter = create_Gaussian_filter(5,1); + Persistence_heat_maps p( intervals , filter , constant_function, false , 10 , 0 , 10 ); + p.plot( "heat_map_1" ); + + std::vector< std::pair< double,double > > intervals2; + intervals2.push_back( std::make_pair(7,7) ); + Persistence_heat_maps q( intervals2 , filter , constant_function, false , 10 , 0 , 10 ); + q.plot( "heat_map_2" ); + + Persistence_heat_maps median; + median.compute_median( {&p,&q} ); + median.plot( "median" ); +*/ + +/* + std::vector< std::vector<double> > filter = create_Gaussian_filter(30,1); + Persistence_heat_maps p( "file_with_diagram" , filter , constant_function, false , 1000 , 0 , 1 ); + Persistence_heat_maps q( "file_with_diagram_1" , filter , constant_function, false , 1000 , 0 , 1 ); + Persistence_heat_maps r( "file_with_diagram_2" , filter , constant_function, false , 1000 , 0 , 1 ); + Persistence_heat_maps median; + median.compute_median( {&p,&q,&r} ); + median.print_to_file( "template_median_of_heat_maps" ); +*/ + +/* + std::vector< std::vector<double> > filter = create_Gaussian_filter(30,1); + Persistence_heat_maps p( "file_with_diagram" , filter , constant_function, false , 1000 , 0 , 1 ); + Persistence_heat_maps q( "file_with_diagram_1" , filter , constant_function, false , 1000 , 0 , 1 ); + Persistence_heat_maps r( "file_with_diagram_2" , filter , constant_function, false , 1000 , 0 , 1 ); + + Persistence_heat_maps percentage_of_active; + percentage_of_active.compute_percentage_of_active( {&p,&q,&r} , 0.1 ); + + percentage_of_active.print_to_file( "template_percentage_of_active_of_heat_maps" ); + //percentage_of_active.plot( "template_percentage_of_active_of_heat_maps" ); +*/ |