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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) 2016 Inria
*
* Modification(s):
* - YYYY/MM Author: Description of the modification
*/
#define BOOST_TEST_DYN_LINK
#define BOOST_TEST_MODULE "rips_complex"
#include <boost/test/unit_test.hpp>
#include <cmath> // float comparison
#include <limits>
#include <string>
#include <vector>
#include <algorithm> // std::max
#include <gudhi/Rips_complex.h>
#include <gudhi/Sparse_rips_complex.h>
// to construct Rips_complex from a OFF file of points
#include <gudhi/Points_off_io.h>
#include <gudhi/Simplex_tree.h>
#include <gudhi/distance_functions.h>
#include <gudhi/reader_utils.h>
#include <gudhi/Unitary_tests_utils.h>
// Type definitions
using Point = std::vector<double>;
using Simplex_tree = Gudhi::Simplex_tree<>;
using Filtration_value = Simplex_tree::Filtration_value;
using Rips_complex = Gudhi::rips_complex::Rips_complex<Simplex_tree::Filtration_value>;
using Sparse_rips_complex = Gudhi::rips_complex::Sparse_rips_complex<Simplex_tree::Filtration_value>;
using Distance_matrix = std::vector<std::vector<Filtration_value>>;
BOOST_AUTO_TEST_CASE(RIPS_DOC_OFF_file) {
// ----------------------------------------------------------------------------
//
// Init of a Rips complex from a OFF file
//
// ----------------------------------------------------------------------------
std::string off_file_name("alphacomplexdoc.off");
double rips_threshold = 12.0;
std::cout << "========== OFF FILE NAME = " << off_file_name << " - Rips threshold=" <<
rips_threshold << "==========" << std::endl;
Gudhi::Points_off_reader<Point> off_reader(off_file_name);
Rips_complex rips_complex_from_file(off_reader.get_point_cloud(), rips_threshold, Gudhi::Euclidean_distance());
const int DIMENSION_1 = 1;
Simplex_tree st;
rips_complex_from_file.create_complex(st, DIMENSION_1);
std::cout << "st.dimension()=" << st.dimension() << std::endl;
BOOST_CHECK(st.dimension() == DIMENSION_1);
const int NUMBER_OF_VERTICES = 7;
std::cout << "st.num_vertices()=" << st.num_vertices() << std::endl;
BOOST_CHECK(st.num_vertices() == NUMBER_OF_VERTICES);
std::cout << "st.num_simplices()=" << st.num_simplices() << std::endl;
BOOST_CHECK(st.num_simplices() == 18);
// Check filtration values of vertices is 0.0
for (auto f_simplex : st.skeleton_simplex_range(0)) {
BOOST_CHECK(st.filtration(f_simplex) == 0.0);
}
// Check filtration values of edges
for (auto f_simplex : st.skeleton_simplex_range(DIMENSION_1)) {
if (DIMENSION_1 == st.dimension(f_simplex)) {
std::vector<Point> vp;
std::cout << "vertex = (";
for (auto vertex : st.simplex_vertex_range(f_simplex)) {
std::cout << vertex << ",";
vp.push_back(off_reader.get_point_cloud().at(vertex));
}
std::cout << ") - distance =" << Gudhi::Euclidean_distance()(vp.at(0), vp.at(1)) <<
" - filtration =" << st.filtration(f_simplex) << std::endl;
BOOST_CHECK(vp.size() == 2);
GUDHI_TEST_FLOAT_EQUALITY_CHECK(st.filtration(f_simplex), Gudhi::Euclidean_distance()(vp.at(0), vp.at(1)));
}
}
const int DIMENSION_2 = 2;
Simplex_tree st2;
rips_complex_from_file.create_complex(st2, DIMENSION_2);
std::cout << "st2.dimension()=" << st2.dimension() << std::endl;
BOOST_CHECK(st2.dimension() == DIMENSION_2);
std::cout << "st2.num_vertices()=" << st2.num_vertices() << std::endl;
BOOST_CHECK(st2.num_vertices() == NUMBER_OF_VERTICES);
std::cout << "st2.num_simplices()=" << st2.num_simplices() << std::endl;
BOOST_CHECK(st2.num_simplices() == 23);
Simplex_tree::Filtration_value f01 = st2.filtration(st2.find({0, 1}));
Simplex_tree::Filtration_value f02 = st2.filtration(st2.find({0, 2}));
Simplex_tree::Filtration_value f12 = st2.filtration(st2.find({1, 2}));
Simplex_tree::Filtration_value f012 = st2.filtration(st2.find({0, 1, 2}));
std::cout << "f012= " << f012 << " | f01= " << f01 << " - f02= " << f02 << " - f12= " << f12 << std::endl;
GUDHI_TEST_FLOAT_EQUALITY_CHECK(f012, std::max(f01, std::max(f02,f12)));
Simplex_tree::Filtration_value f45 = st2.filtration(st2.find({4, 5}));
Simplex_tree::Filtration_value f56 = st2.filtration(st2.find({5, 6}));
Simplex_tree::Filtration_value f46 = st2.filtration(st2.find({4, 6}));
Simplex_tree::Filtration_value f456 = st2.filtration(st2.find({4, 5, 6}));
std::cout << "f456= " << f456 << " | f45= " << f45 << " - f56= " << f56 << " - f46= " << f46 << std::endl;
GUDHI_TEST_FLOAT_EQUALITY_CHECK(f456, std::max(f45, std::max(f56,f46)));
const int DIMENSION_3 = 3;
Simplex_tree st3;
rips_complex_from_file.create_complex(st3, DIMENSION_3);
std::cout << "st3.dimension()=" << st3.dimension() << std::endl;
BOOST_CHECK(st3.dimension() == DIMENSION_3);
std::cout << "st3.num_vertices()=" << st3.num_vertices() << std::endl;
BOOST_CHECK(st3.num_vertices() == NUMBER_OF_VERTICES);
std::cout << "st3.num_simplices()=" << st3.num_simplices() << std::endl;
BOOST_CHECK(st3.num_simplices() == 24);
Simplex_tree::Filtration_value f123 = st3.filtration(st3.find({1, 2, 3}));
Simplex_tree::Filtration_value f013 = st3.filtration(st3.find({0, 1, 3}));
Simplex_tree::Filtration_value f023 = st3.filtration(st3.find({0, 2, 3}));
Simplex_tree::Filtration_value f0123 = st3.filtration(st3.find({0, 1, 2, 3}));
std::cout << "f0123= " << f0123 << " | f012= " << f012 << " - f123= " << f123 << " - f013= " << f013 <<
" - f023= " << f023 << std::endl;
GUDHI_TEST_FLOAT_EQUALITY_CHECK(f0123, std::max(f012, std::max(f123, std::max(f013, f023))));
}
using Vector_of_points = std::vector<Point>;
bool is_point_in_list(Vector_of_points points_list, Point point) {
for (auto& point_in_list : points_list) {
if (point_in_list == point) {
return true; // point found
}
}
return false; // point not found
}
class Custom_square_euclidean_distance {
public:
template< typename Point >
auto operator()(const Point& p1, const Point& p2) -> typename Point::value_type {
auto it1 = p1.begin();
auto it2 = p2.begin();
typename Point::value_type dist = 0.;
for (; it1 != p1.end(); ++it1, ++it2) {
typename Point::value_type tmp = (*it1) - (*it2);
dist += tmp*tmp;
}
return dist;
}
};
BOOST_AUTO_TEST_CASE(Rips_complex_from_points) {
// ----------------------------------------------------------------------------
// Init of a list of points
// ----------------------------------------------------------------------------
Vector_of_points points;
std::vector<double> coords = { 0.0, 0.0, 0.0, 1.0 };
points.push_back(Point(coords.begin(), coords.end()));
coords = { 0.0, 0.0, 1.0, 0.0 };
points.push_back(Point(coords.begin(), coords.end()));
coords = { 0.0, 1.0, 0.0, 0.0 };
points.push_back(Point(coords.begin(), coords.end()));
coords = { 1.0, 0.0, 0.0, 0.0 };
points.push_back(Point(coords.begin(), coords.end()));
// ----------------------------------------------------------------------------
// Init of a Rips complex from the list of points
// ----------------------------------------------------------------------------
Rips_complex rips_complex_from_points(points, 2.0, Custom_square_euclidean_distance());
std::cout << "========== Rips_complex_from_points ==========" << std::endl;
Simplex_tree st;
const int DIMENSION = 3;
rips_complex_from_points.create_complex(st, DIMENSION);
// Another way to check num_simplices
std::cout << "Iterator on Rips complex simplices in the filtration order, with [filtration value]:" << std::endl;
int num_simplices = 0;
for (auto f_simplex : st.filtration_simplex_range()) {
num_simplices++;
std::cout << " ( ";
for (auto vertex : st.simplex_vertex_range(f_simplex)) {
std::cout << vertex << " ";
}
std::cout << ") -> " << "[" << st.filtration(f_simplex) << "] ";
std::cout << std::endl;
}
BOOST_CHECK(num_simplices == 15);
std::cout << "st.num_simplices()=" << st.num_simplices() << std::endl;
BOOST_CHECK(st.num_simplices() == 15);
std::cout << "st.dimension()=" << st.dimension() << std::endl;
BOOST_CHECK(st.dimension() == DIMENSION);
std::cout << "st.num_vertices()=" << st.num_vertices() << std::endl;
BOOST_CHECK(st.num_vertices() == 4);
for (auto f_simplex : st.filtration_simplex_range()) {
std::cout << "dimension(" << st.dimension(f_simplex) << ") - f = " << st.filtration(f_simplex) << std::endl;
switch (st.dimension(f_simplex)) {
case 0:
GUDHI_TEST_FLOAT_EQUALITY_CHECK(st.filtration(f_simplex), 0.0);
break;
case 1:
case 2:
case 3:
GUDHI_TEST_FLOAT_EQUALITY_CHECK(st.filtration(f_simplex), 2.0);
break;
default:
BOOST_CHECK(false); // Shall not happen
break;
}
}
}
BOOST_AUTO_TEST_CASE(Sparse_rips_complex_from_points) {
// This is a clone of the test above
// ----------------------------------------------------------------------------
// Init of a list of points
// ----------------------------------------------------------------------------
Vector_of_points points;
std::vector<double> coords = { 0.0, 0.0, 0.0, 1.0 };
points.push_back(Point(coords.begin(), coords.end()));
coords = { 0.0, 0.0, 1.0, 0.0 };
points.push_back(Point(coords.begin(), coords.end()));
coords = { 0.0, 1.0, 0.0, 0.0 };
points.push_back(Point(coords.begin(), coords.end()));
coords = { 1.0, 0.0, 0.0, 0.0 };
points.push_back(Point(coords.begin(), coords.end()));
// ----------------------------------------------------------------------------
// Init of a Rips complex from the list of points
// ----------------------------------------------------------------------------
// .001 is small enough that we get a deterministic result matching the exact Rips
Sparse_rips_complex sparse_rips(points, Custom_square_euclidean_distance(), .001);
std::cout << "========== Sparse_rips_complex_from_points ==========" << std::endl;
Simplex_tree st;
const int DIMENSION = 3;
sparse_rips.create_complex(st, DIMENSION);
// Another way to check num_simplices
std::cout << "Iterator on Rips complex simplices in the filtration order, with [filtration value]:" << std::endl;
int num_simplices = 0;
for (auto f_simplex : st.filtration_simplex_range()) {
num_simplices++;
std::cout << " ( ";
for (auto vertex : st.simplex_vertex_range(f_simplex)) {
std::cout << vertex << " ";
}
std::cout << ") -> " << "[" << st.filtration(f_simplex) << "] ";
std::cout << std::endl;
}
BOOST_CHECK(num_simplices == 15);
std::cout << "st.num_simplices()=" << st.num_simplices() << std::endl;
BOOST_CHECK(st.num_simplices() == 15);
std::cout << "st.dimension()=" << st.dimension() << std::endl;
BOOST_CHECK(st.dimension() == DIMENSION);
std::cout << "st.num_vertices()=" << st.num_vertices() << std::endl;
BOOST_CHECK(st.num_vertices() == 4);
for (auto f_simplex : st.filtration_simplex_range()) {
std::cout << "dimension(" << st.dimension(f_simplex) << ") - f = " << st.filtration(f_simplex) << std::endl;
switch (st.dimension(f_simplex)) {
case 0:
GUDHI_TEST_FLOAT_EQUALITY_CHECK(st.filtration(f_simplex), 0.0);
break;
case 1:
case 2:
case 3:
GUDHI_TEST_FLOAT_EQUALITY_CHECK(st.filtration(f_simplex), 2.0);
break;
default:
BOOST_CHECK(false); // Shall not happen
break;
}
}
}
BOOST_AUTO_TEST_CASE(Rips_doc_csv_file) {
// ----------------------------------------------------------------------------
//
// Init of a Rips complex from a OFF file
//
// ----------------------------------------------------------------------------
std::string csv_file_name("full_square_distance_matrix.csv");
double rips_threshold = 12.0;
std::cout << "========== CSV FILE NAME = " << csv_file_name << " - Rips threshold=" <<
rips_threshold << "==========" << std::endl;
Distance_matrix distances = Gudhi::read_lower_triangular_matrix_from_csv_file<Filtration_value>(csv_file_name);
Rips_complex rips_complex_from_file(distances, rips_threshold);
const int DIMENSION_1 = 1;
Simplex_tree st;
rips_complex_from_file.create_complex(st, DIMENSION_1);
std::cout << "st.dimension()=" << st.dimension() << std::endl;
BOOST_CHECK(st.dimension() == DIMENSION_1);
const int NUMBER_OF_VERTICES = 7;
std::cout << "st.num_vertices()=" << st.num_vertices() << std::endl;
BOOST_CHECK(st.num_vertices() == NUMBER_OF_VERTICES);
std::cout << "st.num_simplices()=" << st.num_simplices() << std::endl;
BOOST_CHECK(st.num_simplices() == 18);
// Check filtration values of vertices is 0.0
for (auto f_simplex : st.skeleton_simplex_range(0)) {
BOOST_CHECK(st.filtration(f_simplex) == 0.0);
}
// Check filtration values of edges
for (auto f_simplex : st.skeleton_simplex_range(DIMENSION_1)) {
if (DIMENSION_1 == st.dimension(f_simplex)) {
std::vector<Simplex_tree::Vertex_handle> vvh;
std::cout << "vertex = (";
for (auto vertex : st.simplex_vertex_range(f_simplex)) {
std::cout << vertex << ",";
vvh.push_back(vertex);
}
std::cout << ") - filtration =" << st.filtration(f_simplex) << std::endl;
BOOST_CHECK(vvh.size() == 2);
GUDHI_TEST_FLOAT_EQUALITY_CHECK(st.filtration(f_simplex), distances[vvh.at(0)][vvh.at(1)]);
}
}
const int DIMENSION_2 = 2;
Simplex_tree st2;
rips_complex_from_file.create_complex(st2, DIMENSION_2);
std::cout << "st2.dimension()=" << st2.dimension() << std::endl;
BOOST_CHECK(st2.dimension() == DIMENSION_2);
std::cout << "st2.num_vertices()=" << st2.num_vertices() << std::endl;
BOOST_CHECK(st2.num_vertices() == NUMBER_OF_VERTICES);
std::cout << "st2.num_simplices()=" << st2.num_simplices() << std::endl;
BOOST_CHECK(st2.num_simplices() == 23);
Simplex_tree::Filtration_value f01 = st2.filtration(st2.find({0, 1}));
Simplex_tree::Filtration_value f02 = st2.filtration(st2.find({0, 2}));
Simplex_tree::Filtration_value f12 = st2.filtration(st2.find({1, 2}));
Simplex_tree::Filtration_value f012 = st2.filtration(st2.find({0, 1, 2}));
std::cout << "f012= " << f012 << " | f01= " << f01 << " - f02= " << f02 << " - f12= " << f12 << std::endl;
GUDHI_TEST_FLOAT_EQUALITY_CHECK(f012, std::max(f01, std::max(f02,f12)));
Simplex_tree::Filtration_value f45 = st2.filtration(st2.find({4, 5}));
Simplex_tree::Filtration_value f56 = st2.filtration(st2.find({5, 6}));
Simplex_tree::Filtration_value f46 = st2.filtration(st2.find({4, 6}));
Simplex_tree::Filtration_value f456 = st2.filtration(st2.find({4, 5, 6}));
std::cout << "f456= " << f456 << " | f45= " << f45 << " - f56= " << f56 << " - f46= " << f46 << std::endl;
GUDHI_TEST_FLOAT_EQUALITY_CHECK(f456, std::max(f45, std::max(f56,f46)));
const int DIMENSION_3 = 3;
Simplex_tree st3;
rips_complex_from_file.create_complex(st3, DIMENSION_3);
std::cout << "st3.dimension()=" << st3.dimension() << std::endl;
BOOST_CHECK(st3.dimension() == DIMENSION_3);
std::cout << "st3.num_vertices()=" << st3.num_vertices() << std::endl;
BOOST_CHECK(st3.num_vertices() == NUMBER_OF_VERTICES);
std::cout << "st3.num_simplices()=" << st3.num_simplices() << std::endl;
BOOST_CHECK(st3.num_simplices() == 24);
Simplex_tree::Filtration_value f123 = st3.filtration(st3.find({1, 2, 3}));
Simplex_tree::Filtration_value f013 = st3.filtration(st3.find({0, 1, 3}));
Simplex_tree::Filtration_value f023 = st3.filtration(st3.find({0, 2, 3}));
Simplex_tree::Filtration_value f0123 = st3.filtration(st3.find({0, 1, 2, 3}));
std::cout << "f0123= " << f0123 << " | f012= " << f012 << " - f123= " << f123 << " - f013= " << f013 <<
" - f023= " << f023 << std::endl;
GUDHI_TEST_FLOAT_EQUALITY_CHECK(f0123, std::max(f012, std::max(f123, std::max(f013, f023))));
}
#ifdef GUDHI_DEBUG
BOOST_AUTO_TEST_CASE(Rips_create_complex_throw) {
// ----------------------------------------------------------------------------
//
// Init of a Rips complex from a OFF file
//
// ----------------------------------------------------------------------------
std::string off_file_name("alphacomplexdoc.off");
double rips_threshold = 12.0;
std::cout << "========== OFF FILE NAME = " << off_file_name << " - Rips threshold=" <<
rips_threshold << "==========" << std::endl;
Gudhi::Points_off_reader<Point> off_reader(off_file_name);
Rips_complex rips_complex_from_file(off_reader.get_point_cloud(), rips_threshold, Gudhi::Euclidean_distance());
Simplex_tree stree;
std::vector<int> simplex = {0, 1, 2};
stree.insert_simplex_and_subfaces(simplex);
std::cout << "Check exception throw in debug mode" << std::endl;
// throw excpt because stree is not empty
BOOST_CHECK_THROW (rips_complex_from_file.create_complex(stree, 1), std::invalid_argument);
}
#endif
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