/* 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 .
*/
#define BOOST_TEST_DYN_LINK
#define BOOST_TEST_MODULE "gudhi_stat"
#include
#include
#include
#include
using namespace Gudhi;
using namespace Gudhi::Gudhi_stat;
BOOST_AUTO_TEST_CASE(check_construction_of_heat_maps)
{
std::vector< std::vector > filter = create_Gaussian_filter(100,1);
Persistence_heat_maps 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 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 > filter = create_Gaussian_filter(30,1);
Persistence_heat_maps p( "data/file_with_diagram" , filter , false , 1000 , 0 , 10 );
Persistence_heat_maps q( "data/file_with_diagram_1" , filter , false , 1000 , 0 , 10 );
Persistence_heat_maps r( "data/file_with_diagram_2" , filter , false , 1000 , 0 , 10 );
Persistence_heat_maps av;
av.compute_average( {&p,&q,&r} );
Persistence_heat_maps 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 > filter = create_Gaussian_filter(30,1);
Persistence_heat_maps p( "data/file_with_diagram" , filter , false , 1000 , 0 , 1 );
Persistence_heat_maps q( "data/file_with_diagram_1" , filter , false , 1000 , 0 , 1 );
Persistence_heat_maps r( "data/file_with_diagram_2" , filter , false , 1000 , 0 , 1 );
std::vector< Persistence_heat_maps* > to_compute_median;
to_compute_median.push_back( &p );
to_compute_median.push_back( &q );
to_compute_median.push_back( &r );
Persistence_heat_maps median;
median.compute_median( to_compute_median );
Persistence_heat_maps 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 > filter = create_Gaussian_filter(30,1);
Persistence_heat_maps p( "data/file_with_diagram" , filter , false , 1000 , 0 , 1 );
Persistence_heat_maps q( "data/file_with_diagram_1" , filter , false , 1000 , 0 , 1 );
Persistence_heat_maps r( "data/file_with_diagram_2" , filter , false , 1000 , 0 , 1 );
std::vector< Persistence_heat_maps* > 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 percentage_of_active;
percentage_of_active.compute_percentage_of_active( to_compute_percentage_of_active , 0.1 );
Persistence_heat_maps 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 > filter = create_Gaussian_filter(30,1);
Persistence_heat_maps p( "data/file_with_diagram" , filter , false , 5 , 0 , 1 );
std::vector 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 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 > filter = create_Gaussian_filter(30,1);
Persistence_heat_maps p( "data/file_with_diagram" , filter , false , 1000 , 0 , 1 );
Persistence_heat_maps q( "data/file_with_diagram_1" , filter , false , 1000 , 0 , 1 );
Persistence_heat_maps r( "data/file_with_diagram_2" , filter , false , 1000 , 0 , 1 );
//cerr << p.distance( p ) << endl;
//cerr << p.distance( q ) << endl;
//cerr << p.distance( r ) << endl;
//cerr << q.distance( p ) << endl;
//cerr << q.distance( q ) << endl;
//cerr << q.distance( r ) << endl;
//cerr << r.distance( p ) << endl;
//cerr << r.distance( q ) << endl;
//cerr << r.distance( r ) << endl;
//0 624.183 415.815
//624.183 0 528.06Z
//415.815 528.066 0
BOOST_CHECK( fabs( p.distance( p ) - 0) < 0.0005);
BOOST_CHECK( fabs( p.distance( q ) - 624.183)< 0.0005);
BOOST_CHECK( fabs( p.distance( r ) - 415.815)< 0.0005);
BOOST_CHECK( fabs( q.distance( p ) - 624.183)< 0.0005);
BOOST_CHECK( fabs( q.distance( q ) - 0)< 0.0005);
BOOST_CHECK( fabs( q.distance( r ) - 528.066)< 0.0005);
BOOST_CHECK( fabs( r.distance( p ) - 415.815)< 0.0005);
BOOST_CHECK( fabs( r.distance( q ) - 528.066)< 0.0005);
BOOST_CHECK( fabs( r.distance( r ) - 0)< 0.0005);
}
BOOST_AUTO_TEST_CASE(check_projections_to_R_for_heat_maps)
{
std::vector< std::vector > filter = create_Gaussian_filter(30,1);
Persistence_heat_maps p( "data/file_with_diagram" , filter , false , 1000 , 0 , 1 );
Persistence_heat_maps q( "data/file_with_diagram_1" , filter , false , 1000 , 0 , 1 );
Persistence_heat_maps r( "data/file_with_diagram_2" , filter , false , 1000 , 0 , 1 );
//cerr << p.project_to_R(0) << endl;
//cerr << q.project_to_R(0) << endl;
//cerr << r.project_to_R(0) << endl;
BOOST_CHECK( fabs( p.project_to_R(0) - 44.3308 )< 0.0005);
BOOST_CHECK( fabs( q.project_to_R(0) - 650.568 )< 0.0005);
BOOST_CHECK( fabs( r.project_to_R(0) - 429.287 )< 0.0005);
}
BOOST_AUTO_TEST_CASE(check_scalar_products_for_heat_maps)
{
std::vector< std::vector > filter = create_Gaussian_filter(30,1);
Persistence_heat_maps p( "data/file_with_diagram" , filter , false , 1000 , 0 , 1 );
Persistence_heat_maps q( "data/file_with_diagram_1" , filter , false , 1000 , 0 , 1 );
Persistence_heat_maps r( "data/file_with_diagram_2" , filter , false , 1000 , 0 , 1 );
//cerr << p.compute_scalar_product( p ) << endl;
//cerr << p.compute_scalar_product( q ) << endl;
//cerr << p.compute_scalar_product( r ) << endl;
//cerr << q.compute_scalar_product( p ) << endl;
//cerr << q.compute_scalar_product( q ) << endl;
//cerr << q.compute_scalar_product( r ) << endl;
//cerr << r.compute_scalar_product( p ) << endl;
//cerr << r.compute_scalar_product( q ) << endl;
//cerr << r.compute_scalar_product( r ) << endl;
BOOST_CHECK( fabs( p.compute_scalar_product( p ) - 0.0345687 )< 0.0005);
BOOST_CHECK( fabs( p.compute_scalar_product( q ) - 0.0509357 )< 0.0005);
BOOST_CHECK( fabs( p.compute_scalar_product( r ) - 0.0375608 )< 0.0005);
BOOST_CHECK( fabs( q.compute_scalar_product( p ) - 0.0509357 )< 0.0005);
BOOST_CHECK( fabs( q.compute_scalar_product( q ) - 1.31293 )< 0.0005);
BOOST_CHECK( fabs( q.compute_scalar_product( r ) - 0.536799)< 0.0005);
BOOST_CHECK( fabs( r.compute_scalar_product( p ) - 0.0375608)< 0.0005);
BOOST_CHECK( fabs( r.compute_scalar_product( q ) - 0.536799)< 0.0005);
BOOST_CHECK( fabs( r.compute_scalar_product( r ) - 0.672907)< 0.0005);
}
BOOST_AUTO_TEST_CASE(check_arythmetic_operations_for_heat_maps)
{
std::vector< std::vector > filter = create_Gaussian_filter(30,1);
Persistence_heat_maps p( "data/file_with_diagram" , filter , false , 1000 , 0 , 1 );
Persistence_heat_maps q( "data/file_with_diagram_1" , filter , false , 1000 , 0 , 1 );
Persistence_heat_maps sum = p + q;
Persistence_heat_maps difference = p - q;
Persistence_heat_maps 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 sum_template;
sum_template.load_from_file( "data/heat_map_sum" );
Persistence_heat_maps difference_template;
difference_template.load_from_file( "data/heat_map_difference" );
Persistence_heat_maps multiply_by_scalar_template;
multiply_by_scalar_template.load_from_file( "data/heat_map_multiply_by_scalar" );
BOOST_CHECK( sum == sum_template );
}
//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 > 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 > 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 > 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 > 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 > 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 > 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 > 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 > 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 > 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" );
*/