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/* 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): Vincent Rouvreau
*
* Copyright (C) 2020 Inria
*
* Modification(s):
* - YYYY/MM Author: Description of the modification
*/
#define BOOST_TEST_DYN_LINK
#define BOOST_TEST_MODULE "weighted_alpha_complex"
#include <boost/test/unit_test.hpp>
#include <boost/mpl/list.hpp>
#include <CGAL/Epick_d.h>
#include <CGAL/Epeck_d.h>
#include <cmath> // float comparison
#include <vector>
#include <random>
#include <array>
#include <cmath> // for std::fabs
#include <gudhi/Alpha_complex.h>
#include <gudhi/Alpha_complex_3d.h>
#include <gudhi/Simplex_tree.h>
#include <gudhi/Unitary_tests_utils.h>
// Use dynamic_dimension_tag for the user to be able to set dimension
typedef CGAL::Epeck_d< CGAL::Dynamic_dimension_tag > Exact_kernel_d;
// Use static dimension_tag for the user not to be able to set dimension
typedef CGAL::Epeck_d< CGAL::Dimension_tag<4> > Exact_kernel_s;
// Use dynamic_dimension_tag for the user to be able to set dimension
typedef CGAL::Epick_d< CGAL::Dynamic_dimension_tag > Inexact_kernel_d;
// Use static dimension_tag for the user not to be able to set dimension
typedef CGAL::Epick_d< CGAL::Dimension_tag<4> > Inexact_kernel_s;
typedef boost::mpl::list<Exact_kernel_d, Exact_kernel_s, Inexact_kernel_d, Inexact_kernel_s> list_of_kernel_variants;
BOOST_AUTO_TEST_CASE_TEMPLATE(Zero_weighted_alpha_complex, Kernel, list_of_kernel_variants) {
// Random points construction
using Point_d = typename Kernel::Point_d;
std::vector<Point_d> points;
std::uniform_real_distribution<double> rd_pts(-10., 10.);
std::random_device rand_dev;
std::mt19937 rand_engine(rand_dev());
for (int idx = 0; idx < 20; idx++) {
std::vector<double> point {rd_pts(rand_engine), rd_pts(rand_engine), rd_pts(rand_engine), rd_pts(rand_engine)};
points.emplace_back(Point_d(point.begin(), point.end()));
}
// Alpha complex from points
Gudhi::alpha_complex::Alpha_complex<Kernel, false> alpha_complex_from_points(points);
Gudhi::Simplex_tree<> simplex;
BOOST_CHECK(alpha_complex_from_points.create_complex(simplex));
std::clog << "Iterator on alpha complex simplices in the filtration order, with [filtration value]:" << std::endl;
for (auto f_simplex : simplex.filtration_simplex_range()) {
std::clog << " ( ";
for (auto vertex : simplex.simplex_vertex_range(f_simplex)) {
std::clog << vertex << " ";
}
std::clog << ") -> " << "[" << simplex.filtration(f_simplex) << "] ";
std::clog << std::endl;
}
// Alpha complex from zero weighted points
std::vector<typename Kernel::FT> weights(20, 0.);
Gudhi::alpha_complex::Alpha_complex<Kernel, true> alpha_complex_from_zero_weighted_points(points, weights);
Gudhi::Simplex_tree<> zw_simplex;
BOOST_CHECK(alpha_complex_from_zero_weighted_points.create_complex(zw_simplex));
std::clog << "Iterator on zero weighted alpha complex simplices in the filtration order, with [filtration value]:" << std::endl;
for (auto f_simplex : zw_simplex.filtration_simplex_range()) {
std::clog << " ( ";
for (auto vertex : zw_simplex.simplex_vertex_range(f_simplex)) {
std::clog << vertex << " ";
}
std::clog << ") -> " << "[" << zw_simplex.filtration(f_simplex) << "] ";
std::clog << std::endl;
}
BOOST_CHECK(zw_simplex == simplex);
}
template <typename Point_d>
bool cgal_3d_point_sort (Point_d a,Point_d b) {
if (a[0] != b[0])
return a[0] < b[0];
if (a[1] != b[1])
return a[1] < b[1];
return a[2] < b[2];
}
BOOST_AUTO_TEST_CASE(Weighted_alpha_complex_3d_comparison) {
// Random points construction
using Kernel_dD = CGAL::Epeck_d< CGAL::Dimension_tag<3> >;
using Bare_point_d = typename Kernel_dD::Point_d;
using Weighted_point_d = typename Kernel_dD::Weighted_point_d;
std::vector<Weighted_point_d> w_points_d;
using Exact_weighted_alpha_complex_3d =
Gudhi::alpha_complex::Alpha_complex_3d<Gudhi::alpha_complex::complexity::EXACT, true, false>;
using Bare_point_3 = typename Exact_weighted_alpha_complex_3d::Bare_point_3;
using Weighted_point_3 = typename Exact_weighted_alpha_complex_3d::Weighted_point_3;
std::vector<Weighted_point_3> w_points_3;
std::uniform_real_distribution<double> rd_pts(-10., 10.);
std::uniform_real_distribution<double> rd_wghts(-0.5, 0.5);
std::random_device rand_dev;
std::mt19937 rand_engine(rand_dev());
for (int idx = 0; idx < 20; idx++) {
std::vector<double> point {rd_pts(rand_engine), rd_pts(rand_engine), rd_pts(rand_engine)};
double weight = rd_wghts(rand_engine);
w_points_d.emplace_back(Weighted_point_d(Bare_point_d(point.begin(), point.end()), weight));
w_points_3.emplace_back(Weighted_point_3(Bare_point_3(point[0], point[1], point[2]), weight));
}
// Structures necessary for comparison
using Points = std::vector<std::array<double,3>>;
using Points_and_filtrations = std::map<Points, double>;
Points_and_filtrations pts_fltr_dD;
Points_and_filtrations pts_fltr_3d;
// Weighted alpha complex for dD version
Gudhi::alpha_complex::Alpha_complex<Kernel_dD, true> alpha_complex_dD_from_weighted_points(w_points_d);
Gudhi::Simplex_tree<> w_simplex_d;
BOOST_CHECK(alpha_complex_dD_from_weighted_points.create_complex(w_simplex_d));
std::clog << "Iterator on weighted alpha complex dD simplices in the filtration order, with [filtration value]:" << std::endl;
for (auto f_simplex : w_simplex_d.filtration_simplex_range()) {
Points points;
for (auto vertex : w_simplex_d.simplex_vertex_range(f_simplex)) {
CGAL::NT_converter<Kernel_dD::RT, double> cgal_converter;
Bare_point_d pt = alpha_complex_dD_from_weighted_points.get_point(vertex).point();
points.push_back({cgal_converter(pt[0]), cgal_converter(pt[1]), cgal_converter(pt[2])});
}
std::clog << " ( ";
std::sort (points.begin(), points.end());
for (auto point : points) {
std::clog << point[0] << " " << point[1] << " " << point[2] << " | ";
}
std::clog << ") -> " << "[" << w_simplex_d.filtration(f_simplex) << "] ";
std::clog << std::endl;
pts_fltr_dD[points] = w_simplex_d.filtration(f_simplex);
}
// Weighted alpha complex for 3D version
Exact_weighted_alpha_complex_3d alpha_complex_3D_from_weighted_points(w_points_3);
Gudhi::Simplex_tree<> w_simplex_3;
BOOST_CHECK(alpha_complex_3D_from_weighted_points.create_complex(w_simplex_3));
std::clog << "Iterator on weighted alpha complex 3D simplices in the filtration order, with [filtration value]:" << std::endl;
for (auto f_simplex : w_simplex_3.filtration_simplex_range()) {
Points points;
for (auto vertex : w_simplex_3.simplex_vertex_range(f_simplex)) {
Bare_point_3 pt = alpha_complex_3D_from_weighted_points.get_point(vertex).point();
CGAL::NT_converter<Exact_weighted_alpha_complex_3d::Kernel::RT, double> cgal_converter;
points.push_back({cgal_converter(pt[0]), cgal_converter(pt[1]), cgal_converter(pt[2])});
}
std::clog << " ( ";
std::sort (points.begin(), points.end());
for (auto point : points) {
std::clog << point[0] << " " << point[1] << " " << point[2] << " | ";
}
std::clog << ") -> " << "[" << w_simplex_3.filtration(f_simplex) << "] ";
std::clog << std::endl;
pts_fltr_3d[points] = w_simplex_d.filtration(f_simplex);
}
// Compares structures
auto d3_itr = pts_fltr_3d.begin();
auto dD_itr = pts_fltr_dD.begin();
for (; d3_itr != pts_fltr_3d.end() && dD_itr != pts_fltr_dD.end(); ++d3_itr) {
if (d3_itr->first != dD_itr->first) {
for(auto point : d3_itr->first)
std::clog << point[0] << " " << point[1] << " " << point[2] << " | ";
std::clog << " versus ";
for(auto point : dD_itr->first)
std::clog << point[0] << " " << point[1] << " " << point[2] << " | ";
std::clog << std::endl;
BOOST_CHECK(false);
}
// I had to make a hard limit as it is converted from Kernel::FT
if (std::fabs(d3_itr->second - dD_itr->second) > 1e-5) {
std::clog << d3_itr->second << " versus " << dD_itr->second << " diff " << std::fabs(d3_itr->second - dD_itr->second) << std::endl;
BOOST_CHECK(false);
}
++dD_itr;
}
}
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