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/* 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): Mathieu Carrière
*
* Copyright (C) 2017 INRIA Saclay (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/>.
*/
#define BOOST_TEST_DYN_LINK
#define BOOST_TEST_MODULE "graph_induced_complex"
#include <boost/test/unit_test.hpp>
#include <cmath> // float comparison
#include <limits>
#include <string>
#include <vector>
#include <algorithm> // std::max
#include <gudhi/GIC.h>
#include <gudhi/distance_functions.h>
#include <gudhi/reader_utils.h>
BOOST_AUTO_TEST_CASE(check_nerve) {
using Point = std::vector<float>;
Gudhi::graph_induced_complex::Graph_induced_complex<Point> GIC;
std::string cloud_file_name("data/cloud"); GIC.read_point_cloud(cloud_file_name);
std::string graph_file_name("data/graph"); GIC.set_graph_from_file(graph_file_name);
std::string cover_file_name("data/cover"); GIC.set_cover_from_file(cover_file_name);
GIC.set_color_from_coordinate();
GIC.find_Nerve_simplices(); Gudhi::graph_induced_complex::Simplex_tree stree; GIC.create_complex(stree);
BOOST_CHECK(stree.num_vertices() == 3);
BOOST_CHECK((stree.num_simplices()-stree.num_vertices()) == 0);
BOOST_CHECK(stree.dimension() == 0);
}
BOOST_AUTO_TEST_CASE(check_GICMAP) {
using Point = std::vector<float>;
Gudhi::graph_induced_complex::Graph_induced_complex<Point> GIC;
std::string cloud_file_name("data/cloud"); GIC.read_point_cloud(cloud_file_name); GIC.set_color_from_coordinate();
std::string graph_file_name("data/graph"); GIC.set_graph_from_file(graph_file_name);
std::string cover_file_name("data/cover"); GIC.set_cover_from_file(cover_file_name);
GIC.find_GICMAP_simplices_with_functional_minimal_cover(); Gudhi::graph_induced_complex::Simplex_tree stree; GIC.create_complex(stree);
BOOST_CHECK(stree.num_vertices() == 3);
BOOST_CHECK((stree.num_simplices()-stree.num_vertices()) == 2);
BOOST_CHECK(stree.dimension() == 1);
}
BOOST_AUTO_TEST_CASE(check_GICcover) {
using Point = std::vector<float>;
Gudhi::graph_induced_complex::Graph_induced_complex<Point> GIC;
std::string cloud_file_name("data/cloud"); GIC.read_point_cloud(cloud_file_name); GIC.set_color_from_coordinate();
std::string graph_file_name("data/graph"); GIC.set_graph_from_file(graph_file_name);
std::string cover_file_name("data/cover"); GIC.set_cover_from_file(cover_file_name);
GIC.find_GIC_simplices(); Gudhi::graph_induced_complex::Simplex_tree stree; GIC.create_complex(stree);
BOOST_CHECK(stree.num_vertices() == 3);
BOOST_CHECK((stree.num_simplices()-stree.num_vertices()) == 4);
BOOST_CHECK(stree.dimension() == 2);
}
BOOST_AUTO_TEST_CASE(check_GICvoronoi) {
using Point = std::vector<float>;
Gudhi::graph_induced_complex::Graph_induced_complex<Point> GIC;
std::string cloud_file_name("data/cloud"); GIC.read_point_cloud(cloud_file_name); GIC.set_color_from_coordinate();
std::string graph_file_name("data/graph"); GIC.set_graph_from_file(graph_file_name);
GIC.set_cover_from_Voronoi(Gudhi::Euclidean_distance(),2);
GIC.find_GIC_simplices(); Gudhi::graph_induced_complex::Simplex_tree stree; GIC.create_complex(stree);
BOOST_CHECK(stree.num_vertices() == 2);
BOOST_CHECK((stree.num_simplices()-stree.num_vertices()) == 1);
BOOST_CHECK(stree.dimension() == 1);
}
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