diff options
| author | vrouvrea <vrouvrea@636b058d-ea47-450e-bf9e-a15bfbe3eedb> | 2017-01-24 09:34:04 +0000 |
|---|---|---|
| committer | vrouvrea <vrouvrea@636b058d-ea47-450e-bf9e-a15bfbe3eedb> | 2017-01-24 09:34:04 +0000 |
| commit | be37aaeadc31ed10ede53393237d939d4aa47c82 (patch) | |
| tree | 6b990088ce68cc19b3db1b8789eab831e62dc747 | |
| parent | 30a66f9431d059eed620e0535583e914fa5a3c74 (diff) | |
| parent | cd9d7681e06f29a25cf5775a384ac2e07e34abe9 (diff) | |
Merge last trunk modifications
git-svn-id: svn+ssh://scm.gforge.inria.fr/svnroot/gudhi/branches/ST_cythonize@1989 636b058d-ea47-450e-bf9e-a15bfbe3eedb
Former-commit-id: 0743b9beb802b839357ecce17e11af5d4ef2a163
102 files changed, 5903 insertions, 11145 deletions
diff --git a/CMakeLists.txt b/CMakeLists.txt index dc202553..0cfa5af7 100644 --- a/CMakeLists.txt +++ b/CMakeLists.txt @@ -122,10 +122,11 @@ else() include_directories(src/common/include/) include_directories(src/Alpha_complex/include/) include_directories(src/Bitmap_cubical_complex/include/) - include_directories(src/Bottleneck/include/) + include_directories(src/Bottleneck_distance/include/) include_directories(src/Contraction/include/) include_directories(src/Hasse_complex/include/) include_directories(src/Persistent_cohomology/include/) + include_directories(src/Rips_complex/include/) include_directories(src/Simplex_tree/include/) include_directories(src/Skeleton_blocker/include/) include_directories(src/Spatial_searching/include/) @@ -139,6 +140,7 @@ else() add_subdirectory(src/Simplex_tree/example) add_subdirectory(src/Persistent_cohomology/test) add_subdirectory(src/Persistent_cohomology/example) + add_subdirectory(src/Persistent_cohomology/benchmark) add_subdirectory(src/Skeleton_blocker/test) add_subdirectory(src/Skeleton_blocker/example) add_subdirectory(src/Contraction/example) @@ -155,6 +157,11 @@ else() add_subdirectory(src/Tangential_complex/example) add_subdirectory(src/Tangential_complex/test) add_subdirectory(src/Tangential_complex/benchmark) + add_subdirectory(src/Bottleneck_distance/example) + add_subdirectory(src/Bottleneck_distance/test) + add_subdirectory(src/Bottleneck_distance/benchmark) + add_subdirectory(src/Rips_complex/example) + add_subdirectory(src/Rips_complex/test) # data points generator add_subdirectory(data/points/generator) diff --git a/biblio/how_to_cite_gudhi.bib b/biblio/how_to_cite_gudhi.bib index 03c05728..fde1d9b1 100644 --- a/biblio/how_to_cite_gudhi.bib +++ b/biblio/how_to_cite_gudhi.bib @@ -94,4 +94,22 @@ , booktitle = "{GUDHI} User and Reference Manual" , url = "http://gudhi.gforge.inria.fr/doc/latest/group__tangential__complex.html" , year = 2016 +} + +@incollection{gudhi:RipsComplex +, author = "Cl\'ement Maria, Pawel Dlotko, Vincent Rouvreau" +, title = "Rips complex" +, publisher = "{GUDHI Editorial Board}" +, booktitle = "{GUDHI} User and Reference Manual" +, url = "http://gudhi.gforge.inria.fr/doc/latest/group__rips__complex.html" +, year = 2016 +} + +@incollection{gudhi:BottleneckDistance +, author = "Fran{{\c{c}}ois Godi" +, title = "Bottleneck distance" +, publisher = "{GUDHI Editorial Board}" +, booktitle = "{GUDHI} User and Reference Manual" +, url = "http://gudhi.gforge.inria.fr/doc/latest/group__bottleneck__distance.html" +, year = 2016 }
\ No newline at end of file diff --git a/data/distance_matrix/full_square_distance_matrix.csv b/data/distance_matrix/full_square_distance_matrix.csv new file mode 100644 index 00000000..51512b03 --- /dev/null +++ b/data/distance_matrix/full_square_distance_matrix.csv @@ -0,0 +1,7 @@ +0;6.0827625303;5.8309518948;9.4339811321;13.0384048104;18.0277563773;17.88854382; +6.0827625303;0;6.7082039325;6.3245553203;15.6524758425;19.6468827044;17.1172427686; +5.8309518948;6.7082039325;0;5;8.94427191;13.152946438;12.0830459736; +9.4339811321;6.3245553203;5;0;12.0415945788;14.7648230602;11; +13.0384048104;15.6524758425;8.94427191;12.0415945788;0;5.3851648071;9.4868329805; +18.0277563773;19.6468827044;13.152946438;14.7648230602;5.3851648071;0;7.2801098893; +17.88854382;17.1172427686;12.0830459736;11;9.4868329805;7.2801098893;0;
\ No newline at end of file diff --git a/data/distance_matrix/lower_triangular_distance_matrix.csv b/data/distance_matrix/lower_triangular_distance_matrix.csv new file mode 100644 index 00000000..d8a4c0a3 --- /dev/null +++ b/data/distance_matrix/lower_triangular_distance_matrix.csv @@ -0,0 +1,5 @@ + +1, +2,3, +4,5,6, +7,8,9,10,
\ No newline at end of file diff --git a/data/points/Kl.txt b/data/points/Kl.txt deleted file mode 100644 index c5b9539a..00000000 --- a/data/points/Kl.txt +++ /dev/null @@ -1,10000 +0,0 @@ -0.5 0 0 0 1 -0.562791 0 0.125333 0 0.998027 -0.625333 0 0.24869 0 0.992115 -0.687381 0 0.368124 0 0.982287 -0.74869 0 0.481754 0 0.968583 -0.809017 0 0.587785 0 0.951057 -0.868124 0 0.684547 0 0.929777 -0.925779 0 0.770513 0 0.904827 -0.981754 0 0.844328 0 0.876307 -1.03583 0 0.904827 0 0.844328 -1.08779 0 0.951056 0 0.809017 -1.13742 0 0.982287 0 0.770513 -1.18455 0 0.998027 0 0.728969 -1.22897 0 0.998027 0 0.684547 -1.27051 0 0.982287 0 0.637424 -1.30902 0 0.951057 0 0.587785 -1.34433 0 0.904827 0 0.535827 -1.37631 0 0.844328 0 0.481754 -1.40483 0 0.770514 0 0.42578 -1.42978 0 0.684547 0 0.368125 -1.45106 0 0.587786 0 0.309017 -1.46858 0 0.481754 0 0.24869 -1.48229 0 0.368125 0 0.187382 -1.49211 0 0.24869 0 0.125334 -1.49803 0 0.125334 0 0.0627908 -1.5 0 6.5359e-07 0 3.26795e-07 -1.49803 0 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0.210332 1.20692 0.929777 0.535827 --0.108313 0.273568 1.19936 0.929777 0.481754 --0.136689 0.345237 1.18146 0.929777 0.42578 --0.168025 0.424384 1.15377 0.929777 0.368125 --0.201889 0.509915 1.11698 0.929777 0.309017 --0.237799 0.600613 1.07188 0.929777 0.24869 --0.275231 0.695155 1.01935 0.929777 0.187382 --0.313629 0.792136 0.960343 0.929777 0.125334 --0.35241 0.890087 0.895896 0.929777 0.0627908 --0.390978 0.9875 0.827081 0.929777 3.26795e-07 --0.42873 1.08285 0.755001 0.929777 -0.0627902 --0.465065 1.17462 0.680775 0.929777 -0.125333 --0.499396 1.26133 0.605514 0.929777 -0.187381 --0.531157 1.34155 0.530311 0.929777 -0.24869 --0.559813 1.41393 0.456216 0.929777 -0.309017 --0.584871 1.47722 0.384228 0.929777 -0.368124 --0.605883 1.53029 0.315272 0.929777 -0.425779 --0.622455 1.57214 0.250194 0.929777 -0.481753 --0.634259 1.60196 0.189739 0.929777 -0.535826 --0.641028 1.61905 0.134549 0.929777 -0.587785 --0.642569 1.62295 0.0851493 0.929777 -0.637424 --0.638765 1.61334 0.0419416 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0.234619 -1.01935 0.929777 0.18738 --0.130324 0.329162 -1.07188 0.929777 0.248689 --0.166234 0.41986 -1.11698 0.929777 0.309016 --0.200098 0.505391 -1.15377 0.929777 0.368124 --0.231435 0.584538 -1.18146 0.929777 0.425778 --0.25981 0.656207 -1.19936 0.929777 0.481753 --0.284847 0.719443 -1.20692 0.929777 0.535826 --0.306229 0.773448 -1.2037 0.929777 0.587784 --0.323705 0.817587 -1.1894 0.929777 0.637423 --0.337094 0.851403 -1.16389 0.929777 0.684546 --0.346285 0.874618 -1.12715 0.929777 0.728968 --0.351244 0.887142 -1.07933 0.929777 0.770513 --0.352006 0.889067 -1.02072 0.929777 0.809016 --0.348682 0.880671 -0.951762 0.929777 0.844327 --0.341451 0.862407 -0.873033 0.929777 0.876306 --0.330558 0.834896 -0.785248 0.929777 0.904827 --0.316314 0.79892 -0.689243 0.929777 0.929776 --0.299084 0.7554 -0.585968 0.929777 0.951056 --0.279283 0.70539 -0.476475 0.929777 0.968583 --0.257373 0.65005 -0.361899 0.929777 0.982287 --0.233847 0.590631 -0.243448 0.929777 0.992115 --0.20923 0.528456 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0.125332 --0.799364 0.100984 -1.00346 0.125334 0.18738 --0.912729 0.115305 -0.996922 0.125334 0.248689 --1.01881 0.128706 -0.986088 0.125334 0.309016 --1.11594 0.140977 -0.970925 0.125334 0.368124 --1.20262 0.151927 -0.951423 0.125334 0.425778 --1.27748 0.161384 -0.927594 0.125334 0.481753 --1.33938 0.169204 -0.899477 0.125334 0.535826 --1.38735 0.175264 -0.867139 0.125334 0.587784 --1.42068 0.179474 -0.830672 0.125334 0.637423 --1.43885 0.18177 -0.790198 0.125334 0.684546 --1.44162 0.182119 -0.745864 0.125334 0.728968 --1.42897 0.180521 -0.697846 0.125334 0.770513 --1.40114 0.177006 -0.646344 0.125334 0.809016 --1.3586 0.171632 -0.591585 0.125334 0.844327 --1.30206 0.16449 -0.53382 0.125334 0.876306 --1.23246 0.155697 -0.473321 0.125334 0.904827 --1.15094 0.145398 -0.410383 0.125334 0.929776 --1.05881 0.133759 -0.345316 0.125334 0.951056 --0.957579 0.120971 -0.27845 0.125334 0.968583 --0.848888 0.10724 -0.210128 0.125334 0.982287 --0.734494 0.0927886 -0.140703 0.125334 0.992115 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-0.0627918 0.998027 -0.366193 -0.0230394 -0.24463 -0.0627918 0.992115 -0.300554 -0.0189096 -0.362057 -0.0627918 0.982287 -0.235834 -0.0148377 -0.473704 -0.0627918 0.968583 -0.172332 -0.0108424 -0.577788 -0.0627918 0.951057 -0.110336 -0.00694192 -0.672646 -0.0627918 0.929777 -0.0501289 -0.00315391 -0.756759 -0.0627918 0.904827 --0.00802152 0.000504682 -0.828779 -0.0627918 0.876307 --0.0638579 0.00401768 -0.887549 -0.0627918 0.844328 --0.117138 0.00736982 -0.932124 -0.0627918 0.809017 --0.167633 0.0105468 -0.96178 -0.0627918 0.770513 --0.215133 0.0135353 -0.976032 -0.0627918 0.728969 --0.259445 0.0163232 -0.974636 -0.0627918 0.684547 --0.300394 0.0188996 -0.9576 -0.0627918 0.637424 --0.337824 0.0212545 -0.925175 -0.0627918 0.587785 --0.371598 0.0233795 -0.877859 -0.0627918 0.535827 --0.401602 0.0252672 -0.816386 -0.0627918 0.481754 --0.427738 0.0269115 -0.741711 -0.0627918 0.42578 --0.449931 0.0283078 -0.655004 -0.0627918 0.368125 --0.468125 0.0294525 -0.557622 -0.0627918 0.309017 --0.482284 0.0303434 -0.451092 -0.0627918 0.24869 --0.492392 0.0309793 -0.337088 -0.0627918 0.187382 --0.498451 0.0313605 -0.217404 -0.0627918 0.125334 --0.500482 0.0314883 -0.0939226 -0.0627918 0.0627908 --0.498521 0.0313649 0.0314108 -0.0627918 3.26795e-07 --0.492623 0.0309939 0.15662 -0.0627918 -0.0627902 --0.482859 0.0303795 0.27973 -0.0627918 -0.125333 --0.469311 0.0295272 0.398797 -0.0627918 -0.187381 --0.452079 0.028443 0.51194 -0.0627918 -0.24869 --0.431271 0.0271339 0.617369 -0.0627918 -0.309017 --0.40701 0.0256075 0.713414 -0.0627918 -0.368124 --0.379428 0.0238721 0.798554 -0.0627918 -0.425779 --0.348664 0.0219365 0.871437 -0.0627918 -0.481753 --0.314867 0.0198102 0.930902 -0.0627918 -0.535826 --0.278194 0.0175028 0.975999 -0.0627918 -0.587785 --0.238806 0.0150247 1.00601 -0.0627918 -0.637424 --0.196871 0.0123863 1.02043 -0.0627918 -0.684547 --0.152559 0.00959837 1.01904 -0.0627918 -0.728968 --0.106045 0.00667193 1.00183 -0.0627918 -0.770513 --0.0575079 0.00361816 0.969051 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a/data/points/generator/hypergenerator.cpp b/data/points/generator/hypergenerator.cpp index 60890b44..5831de18 100644 --- a/data/points/generator/hypergenerator.cpp +++ b/data/points/generator/hypergenerator.cpp @@ -29,7 +29,7 @@ #include <iterator> #include <vector> #include <fstream> // for std::ofstream - +#include <cstdlib> typedef CGAL::Epick_d< CGAL::Dynamic_dimension_tag > K; typedef K::Point_d Point; @@ -47,24 +47,22 @@ int main(int argc, char **argv) { usage(argv[0]); } - int points_number = 0; - int returnedScanValue = sscanf(argv[4], "%d", &points_number); - if ((returnedScanValue == EOF) || (points_number <= 0)) { + int points_number = atoi(argv[4]); + if (points_number <= 0) { std::cerr << "Error: " << argv[4] << " is not correct" << std::endl; usage(argv[0]); } - int dimension = 0; - returnedScanValue = sscanf(argv[5], "%d", &dimension); - if ((returnedScanValue == EOF) || (dimension <= 0)) { + int dimension = atoi(argv[5]); + if (dimension <= 0) { std::cerr << "Error: " << argv[5] << " is not correct" << std::endl; usage(argv[0]); } double radius = 1.0; if (argc == 7) { - returnedScanValue = sscanf(argv[6], "%lf", &radius); - if ((returnedScanValue == EOF) || (radius <= 0.0)) { + radius = atof(argv[6]); + if (radius <= 0.0) { std::cerr << "Error: " << argv[6] << " is not correct" << std::endl; usage(argv[0]); } diff --git a/src/Bottleneck/concept/Persistence_diagram.h b/src/Bottleneck/concept/Persistence_diagram.h deleted file mode 100644 index eaaf8bc5..00000000 --- a/src/Bottleneck/concept/Persistence_diagram.h +++ /dev/null @@ -1,7 +0,0 @@ -typedef typename std::pair<double,double> Diagram_point; - -struct Persistence_Diagram -{ - const_iterator<Diagram_point> cbegin() const; - const_iterator<Diagram_point> cend() const; -}; diff --git a/src/Bottleneck/example/CMakeLists.txt b/src/Bottleneck/example/CMakeLists.txt deleted file mode 100644 index 77797202..00000000 --- a/src/Bottleneck/example/CMakeLists.txt +++ /dev/null @@ -1,5 +0,0 @@ -cmake_minimum_required(VERSION 2.6) -project(Bottleneck_examples) - -add_executable ( RandomDiagrams random_diagrams.cpp ) -add_test(RandomDiagrams ${CMAKE_CURRENT_BINARY_DIR}/RandomDiagrams) diff --git a/src/Bottleneck/include/gudhi/Graph_matching.h b/src/Bottleneck/include/gudhi/Graph_matching.h deleted file mode 100644 index ea47e1d5..00000000 --- a/src/Bottleneck/include/gudhi/Graph_matching.h +++ /dev/null @@ -1,197 +0,0 @@ -/* 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): Francois Godi - * - * Copyright (C) 2015 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/>. - */ - -#ifndef SRC_BOTTLENECK_INCLUDE_GUDHI_GRAPH_MATCHING_H_ -#define SRC_BOTTLENECK_INCLUDE_GUDHI_GRAPH_MATCHING_H_ - -#include <deque> -#include <list> -#include <vector> - -#include "gudhi/Layered_neighbors_finder.h" - -namespace Gudhi { - -namespace bottleneck { - -template<typename Persistence_diagram1, typename Persistence_diagram2> -double bottleneck_distance(Persistence_diagram1& diag1, Persistence_diagram2& diag2, double e = 0.); - -class Graph_matching { - public: - Graph_matching(const Persistence_diagrams_graph& g); - Graph_matching& operator=(const Graph_matching& m); - bool perfect() const; - bool multi_augment(); - void set_r(double r); - - private: - const Persistence_diagrams_graph& g; - double r; - std::vector<int> v_to_u; - std::list<int> unmatched_in_u; - - Layered_neighbors_finder* layering() const; - bool augment(Layered_neighbors_finder* layered_nf, int u_start_index, int max_depth); - void update(std::deque<int>& path); -}; - -Graph_matching::Graph_matching(const Persistence_diagrams_graph& g) - : g(g), r(0), v_to_u(g.size()), unmatched_in_u() { - for (int u_point_index = 0; u_point_index < g.size(); ++u_point_index) - unmatched_in_u.emplace_back(u_point_index); -} - -Graph_matching& Graph_matching::operator=(const Graph_matching& m) { - r = m.r; - v_to_u = m.v_to_u; - unmatched_in_u = m.unmatched_in_u; - return *this; -} - -inline bool Graph_matching::perfect() const { - return unmatched_in_u.empty(); -} - -inline bool Graph_matching::multi_augment() { - if (perfect()) - return false; - Layered_neighbors_finder* layered_nf = layering(); - double rn = sqrt(g.size()); - int nblmax = layered_nf->vlayers_number()*2 + 1; - // verification of a necessary criterion - if ((unmatched_in_u.size() > rn && nblmax > rn) || nblmax == 0) - return false; - bool successful = false; - std::list<int>* tries = new std::list<int>(unmatched_in_u); - for (auto it = tries->cbegin(); it != tries->cend(); it++) - successful = successful || augment(layered_nf, *it, nblmax); - delete tries; - delete layered_nf; - return successful; -} - -inline void Graph_matching::set_r(double r) { - this->r = r; -} - -Layered_neighbors_finder* Graph_matching::layering() const { - bool end = false; - int layer = 0; - std::list<int> u_vertices(unmatched_in_u); - std::list<int> v_vertices; - Neighbors_finder nf(g, r); - Layered_neighbors_finder* layered_nf = new Layered_neighbors_finder(g, r); - for (int v_point_index = 0; v_point_index < g.size(); ++v_point_index) - nf.add(v_point_index); - while (!u_vertices.empty()) { - for (auto it = u_vertices.cbegin(); it != u_vertices.cend(); ++it) { - std::list<int>* u_succ = nf.pull_all_near(*it); - for (auto it = u_succ->cbegin(); it != u_succ->cend(); ++it) { - layered_nf->add(*it, layer); - v_vertices.emplace_back(*it); - } - delete u_succ; - } - u_vertices.clear(); - for (auto it = v_vertices.cbegin(); it != v_vertices.cend(); it++) { - if (v_to_u.at(*it) == null_point_index()) - end = true; - else - u_vertices.emplace_back(v_to_u.at(*it)); - } - if (end) - return layered_nf; - v_vertices.clear(); - layer++; - } - return layered_nf; -} - -bool Graph_matching::augment(Layered_neighbors_finder *layered_nf, int u_start_index, int max_depth) { - std::deque<int> path; - path.emplace_back(u_start_index); - // start is a point from U - do { - if (static_cast<int>(path.size()) > max_depth) { - path.pop_back(); - path.pop_back(); - } - if (path.empty()) - return false; - int w = path.back(); - path.emplace_back(layered_nf->pull_near(w, path.size() / 2)); - while (path.back() == null_point_index()) { - path.pop_back(); - path.pop_back(); - if (path.empty()) - return false; - path.pop_back(); - path.emplace_back(layered_nf->pull_near(path.back(), path.size() / 2)); - } - path.emplace_back(v_to_u.at(path.back())); - } while (path.back() != null_point_index()); - path.pop_back(); - update(path); - return true; -} - -void Graph_matching::update(std::deque<int>& path) { - unmatched_in_u.remove(path.front()); - for (auto it = path.cbegin(); it != path.cend(); ++it) { - int tmp = *it; - ++it; - v_to_u[*it] = tmp; - } -} - -template<typename Persistence_diagram1, typename Persistence_diagram2> -double bottleneck_distance(Persistence_diagram1& diag1, Persistence_diagram2& diag2, double e) { - Persistence_diagrams_graph g(diag1, diag2, e); - std::vector<double>* sd = g.sorted_distances(); - int idmin = 0; - int idmax = sd->size() - 1; - double alpha = pow(sd->size(), 0.25); - Graph_matching m(g); - Graph_matching biggest_unperfect = m; - while (idmin != idmax) { - int pas = static_cast<int>((idmax - idmin) / alpha); - m.set_r(sd->at(idmin + pas)); - while (m.multi_augment()) {} - if (m.perfect()) { - idmax = idmin + pas; - m = biggest_unperfect; - } else { - biggest_unperfect = m; - idmin = idmin + pas + 1; - } - } - double b = sd->at(idmin); - delete sd; - return b; -} - -} // namespace bottleneck - -} // namespace Gudhi - -#endif // SRC_BOTTLENECK_INCLUDE_GUDHI_GRAPH_MATCHING_H_ diff --git a/src/Bottleneck/include/gudhi/Layered_neighbors_finder.h b/src/Bottleneck/include/gudhi/Layered_neighbors_finder.h deleted file mode 100644 index de36e00b..00000000 --- a/src/Bottleneck/include/gudhi/Layered_neighbors_finder.h +++ /dev/null @@ -1,74 +0,0 @@ -/* 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): Francois Godi - * - * Copyright (C) 2015 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/>. - */ - -#ifndef SRC_BOTTLENECK_INCLUDE_GUDHI_LAYERED_NEIGHBORS_FINDER_H_ -#define SRC_BOTTLENECK_INCLUDE_GUDHI_LAYERED_NEIGHBORS_FINDER_H_ - -#include <vector> - -#include "Neighbors_finder.h" - -// Layered_neighbors_finder is a data structure used to find if a query point from U has neighbors in V in a given -// vlayer of the vlayered persistence diagrams graph. V's points have to be added manually using their index. -// A neighbor returned is automatically removed. - -namespace Gudhi { - -namespace bottleneck { - -class Layered_neighbors_finder { - public: - Layered_neighbors_finder(const Persistence_diagrams_graph& g, double r); - void add(int v_point_index, int vlayer); - int pull_near(int u_point_index, int vlayer); - int vlayers_number() const; - - private: - const Persistence_diagrams_graph& g; - const double r; - std::vector<Neighbors_finder> neighbors_finder; -}; - -Layered_neighbors_finder::Layered_neighbors_finder(const Persistence_diagrams_graph& g, double r) : - g(g), r(r), neighbors_finder() { } - -inline void Layered_neighbors_finder::add(int v_point_index, int vlayer) { - for (int l = neighbors_finder.size(); l <= vlayer; l++) - neighbors_finder.emplace_back(Neighbors_finder(g, r)); - neighbors_finder.at(vlayer).add(v_point_index); -} - -inline int Layered_neighbors_finder::pull_near(int u_point_index, int vlayer) { - if (static_cast<int> (neighbors_finder.size()) <= vlayer) - return null_point_index(); - return neighbors_finder.at(vlayer).pull_near(u_point_index); -} - -inline int Layered_neighbors_finder::vlayers_number() const { - return neighbors_finder.size(); -} - -} // namespace bottleneck - -} // namespace Gudhi - -#endif // SRC_BOTTLENECK_INCLUDE_GUDHI_LAYERED_NEIGHBORS_FINDER_H_ diff --git a/src/Bottleneck/include/gudhi/Neighbors_finder.h b/src/Bottleneck/include/gudhi/Neighbors_finder.h deleted file mode 100644 index 98256571..00000000 --- a/src/Bottleneck/include/gudhi/Neighbors_finder.h +++ /dev/null @@ -1,96 +0,0 @@ -/* 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): Francois Godi - * - * Copyright (C) 2015 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/>. - */ - -#ifndef SRC_BOTTLENECK_INCLUDE_GUDHI_NEIGHBORS_FINDER_H_ -#define SRC_BOTTLENECK_INCLUDE_GUDHI_NEIGHBORS_FINDER_H_ - -#include <unordered_set> -#include <list> - -#include "gudhi/Planar_neighbors_finder.h" - -namespace Gudhi { - -namespace bottleneck { - -// Neighbors_finder is a data structure used to find if a query point from U has neighbors in V -// in the persistence diagrams graph. -// V's points have to be added manually using their index. A neighbor returned is automatically removed. - -class Neighbors_finder { - public: - Neighbors_finder(const Persistence_diagrams_graph& g, double r); - void add(int v_point_index); - int pull_near(int u_point_index); - std::list<int>* pull_all_near(int u_point_index); - - private: - const Persistence_diagrams_graph& g; - const double r; - Planar_neighbors_finder planar_neighbors_f; - std::unordered_set<int> projections_f; -}; - -Neighbors_finder::Neighbors_finder(const Persistence_diagrams_graph& g, double r) : - g(g), r(r), planar_neighbors_f(g, r), projections_f() { } - -inline void Neighbors_finder::add(int v_point_index) { - if (g.on_the_v_diagonal(v_point_index)) - projections_f.emplace(v_point_index); - else - planar_neighbors_f.add(v_point_index); -} - -inline int Neighbors_finder::pull_near(int u_point_index) { - int v_challenger = g.corresponding_point_in_v(u_point_index); - if (planar_neighbors_f.contains(v_challenger) && g.distance(u_point_index, v_challenger) < r) { - planar_neighbors_f.remove(v_challenger); - return v_challenger; - } - if (g.on_the_u_diagonal(u_point_index)) { - auto it = projections_f.cbegin(); - if (it != projections_f.cend()) { - int tmp = *it; - projections_f.erase(it); - return tmp; - } - } else { - return planar_neighbors_f.pull_near(u_point_index); - } - return null_point_index(); -} - -inline std::list<int>* Neighbors_finder::pull_all_near(int u_point_index) { - std::list<int>* all_pull = planar_neighbors_f.pull_all_near(u_point_index); - int last_pull = pull_near(u_point_index); - while (last_pull != null_point_index()) { - all_pull->emplace_back(last_pull); - last_pull = pull_near(u_point_index); - } - return all_pull; -} - -} // namespace bottleneck - -} // namespace Gudhi - -#endif // SRC_BOTTLENECK_INCLUDE_GUDHI_NEIGHBORS_FINDER_H_ diff --git a/src/Bottleneck/include/gudhi/Persistence_diagrams_graph.h b/src/Bottleneck/include/gudhi/Persistence_diagrams_graph.h deleted file mode 100644 index 73ad940b..00000000 --- a/src/Bottleneck/include/gudhi/Persistence_diagrams_graph.h +++ /dev/null @@ -1,147 +0,0 @@ -/* 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): Francois Godi - * - * Copyright (C) 2015 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/>. - */ - -#ifndef SRC_BOTTLENECK_INCLUDE_GUDHI_PERSISTENCE_DIAGRAMS_GRAPH_H_ -#define SRC_BOTTLENECK_INCLUDE_GUDHI_PERSISTENCE_DIAGRAMS_GRAPH_H_ - -#include <vector> -#include <set> -#include <cmath> -#include <utility> // for pair<> -#include <algorithm> // for max - -namespace Gudhi { - -namespace bottleneck { - -// Diagram_point is the type of the persistence diagram's points -typedef std::pair<double, double> Diagram_point; - -// Return the used index for encoding none of the points -int null_point_index(); - -// Persistence_diagrams_graph is the interface beetwen any external representation of the two persistence diagrams and -// the bottleneck distance computation. An interface is necessary to ensure basic functions complexity. - -class Persistence_diagrams_graph { - public: - // Persistence_diagram1 and 2 are the types of any externals representations of persistence diagrams. - // They have to have an iterator over points, which have to have fields first (for birth) and second (for death). - template<typename Persistence_diagram1, typename Persistence_diagram2> - Persistence_diagrams_graph(Persistence_diagram1& diag1, Persistence_diagram2& diag2, double e = 0.); - Persistence_diagrams_graph(); - bool on_the_u_diagonal(int u_point_index) const; - bool on_the_v_diagonal(int v_point_index) const; - int corresponding_point_in_u(int v_point_index) const; - int corresponding_point_in_v(int u_point_index) const; - double distance(int u_point_index, int v_point_index) const; - int size() const; - std::vector<double>* sorted_distances(); - - private: - std::vector<Diagram_point> u; - std::vector<Diagram_point> v; - Diagram_point get_u_point(int u_point_index) const; - Diagram_point get_v_point(int v_point_index) const; -}; - -inline int null_point_index() { - return -1; -} - -template<typename Persistence_diagram1, typename Persistence_diagram2> -Persistence_diagrams_graph::Persistence_diagrams_graph(Persistence_diagram1& diag1, Persistence_diagram2& diag2, double e) - : u(), v() { - for (auto it = diag1.cbegin(); it != diag1.cend(); ++it) - if (it->second - it->first > e) - u.emplace_back(*it); - for (auto it = diag2.cbegin(); it != diag2.cend(); ++it) - if (it->second - it->first > e) - v.emplace_back(*it); - if (u.size() < v.size()) - swap(u, v); -} - -Persistence_diagrams_graph::Persistence_diagrams_graph() - : u(), v() { } - -inline bool Persistence_diagrams_graph::on_the_u_diagonal(int u_point_index) const { - return u_point_index >= static_cast<int> (u.size()); -} - -inline bool Persistence_diagrams_graph::on_the_v_diagonal(int v_point_index) const { - return v_point_index >= static_cast<int> (v.size()); -} - -inline int Persistence_diagrams_graph::corresponding_point_in_u(int v_point_index) const { - return on_the_v_diagonal(v_point_index) ? - v_point_index - static_cast<int> (v.size()) : v_point_index + static_cast<int> (u.size()); -} - -inline int Persistence_diagrams_graph::corresponding_point_in_v(int u_point_index) const { - return on_the_u_diagonal(u_point_index) ? - u_point_index - static_cast<int> (u.size()) : u_point_index + static_cast<int> (v.size()); -} - -inline double Persistence_diagrams_graph::distance(int u_point_index, int v_point_index) const { - // could be optimized for the case where one point is the projection of the other - if (on_the_u_diagonal(u_point_index) && on_the_v_diagonal(v_point_index)) - return 0; - Diagram_point p_u = get_u_point(u_point_index); - Diagram_point p_v = get_v_point(v_point_index); - return (std::max)(std::fabs(p_u.first - p_v.first), std::fabs(p_u.second - p_v.second)); -} - -inline int Persistence_diagrams_graph::size() const { - return static_cast<int> (u.size() + v.size()); -} - -inline std::vector<double>* Persistence_diagrams_graph::sorted_distances() { - // could be optimized - std::set<double> sorted_distances; - for (int u_point_index = 0; u_point_index < size(); ++u_point_index) - for (int v_point_index = 0; v_point_index < size(); ++v_point_index) - sorted_distances.emplace(distance(u_point_index, v_point_index)); - return new std::vector<double>(sorted_distances.cbegin(), sorted_distances.cend()); -} - -inline Diagram_point Persistence_diagrams_graph::get_u_point(int u_point_index) const { - if (!on_the_u_diagonal(u_point_index)) - return u.at(u_point_index); - Diagram_point projector = v.at(corresponding_point_in_v(u_point_index)); - double x = (projector.first + projector.second) / 2; - return Diagram_point(x, x); -} - -inline Diagram_point Persistence_diagrams_graph::get_v_point(int v_point_index) const { - if (!on_the_v_diagonal(v_point_index)) - return v.at(v_point_index); - Diagram_point projector = u.at(corresponding_point_in_u(v_point_index)); - double x = (projector.first + projector.second) / 2; - return Diagram_point(x, x); -} - -} // namespace bottleneck - -} // namespace Gudhi - -#endif // SRC_BOTTLENECK_INCLUDE_GUDHI_PERSISTENCE_DIAGRAMS_GRAPH_H_ diff --git a/src/Bottleneck/include/gudhi/Planar_neighbors_finder.h b/src/Bottleneck/include/gudhi/Planar_neighbors_finder.h deleted file mode 100644 index 4af672e4..00000000 --- a/src/Bottleneck/include/gudhi/Planar_neighbors_finder.h +++ /dev/null @@ -1,119 +0,0 @@ -/* 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): Francois Godi - * - * Copyright (C) 2015 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/>. - */ - -#ifndef SRC_BOTTLENECK_INCLUDE_GUDHI_PLANAR_NEIGHBORS_FINDER_H_ -#define SRC_BOTTLENECK_INCLUDE_GUDHI_PLANAR_NEIGHBORS_FINDER_H_ - -#include <list> -#include <iostream> -#include <set> - -#include "Persistence_diagrams_graph.h" - -namespace Gudhi { - -namespace bottleneck { - -// Planar_neighbors_finder is a data structure used to find if a query point from U has planar neighbors in V with the -// planar distance. -// V's points have to be added manually using their index. A neighbor returned is automatically removed but we can also -// remove points manually using their index. - -class Abstract_planar_neighbors_finder { - public: - Abstract_planar_neighbors_finder(const Persistence_diagrams_graph& g, double r); - virtual ~Abstract_planar_neighbors_finder() = 0; - virtual void add(int v_point_index) = 0; - virtual void remove(int v_point_index) = 0; - virtual bool contains(int v_point_index) const = 0; - virtual int pull_near(int u_point_index) = 0; - virtual std::list<int>* pull_all_near(int u_point_index); - - protected: - const Persistence_diagrams_graph& g; - const double r; -}; - - -// Naive_pnf is a nave implementation of Abstract_planar_neighbors_finder - -class Naive_pnf : public Abstract_planar_neighbors_finder { - public: - Naive_pnf(const Persistence_diagrams_graph& g, double r); - void add(int v_point_index); - void remove(int v_point_index); - bool contains(int v_point_index) const; - int pull_near(int u_point_index); - - private: - std::set<int> candidates; -}; - - -// Planar_neighbors_finder is the used Abstract_planar_neighbors_finder's implementation -typedef Naive_pnf Planar_neighbors_finder; - -Abstract_planar_neighbors_finder::Abstract_planar_neighbors_finder(const Persistence_diagrams_graph& g, double r) : - g(g), r(r) { } - -inline Abstract_planar_neighbors_finder::~Abstract_planar_neighbors_finder() { } - -inline std::list<int>* Abstract_planar_neighbors_finder::pull_all_near(int u_point_index) { - std::list<int>* all_pull = new std::list<int>(); - int last_pull = pull_near(u_point_index); - while (last_pull != null_point_index()) { - all_pull->emplace_back(last_pull); - last_pull = pull_near(u_point_index); - } - return all_pull; -} - -Naive_pnf::Naive_pnf(const Persistence_diagrams_graph& g, double r) : - Abstract_planar_neighbors_finder(g, r), candidates() { } - -inline void Naive_pnf::add(int v_point_index) { - candidates.emplace(v_point_index); -} - -inline void Naive_pnf::remove(int v_point_index) { - candidates.erase(v_point_index); -} - -inline bool Naive_pnf::contains(int v_point_index) const { - return (candidates.count(v_point_index) > 0); -} - -inline int Naive_pnf::pull_near(int u_point_index) { - for (auto it = candidates.begin(); it != candidates.end(); ++it) - if (g.distance(u_point_index, *it) <= r) { - int tmp = *it; - candidates.erase(it); - return tmp; - } - return null_point_index(); -} - -} // namespace bottleneck - -} // namespace Gudhi - -#endif // SRC_BOTTLENECK_INCLUDE_GUDHI_PLANAR_NEIGHBORS_FINDER_H_ diff --git a/src/Bottleneck/test/CMakeLists.txt b/src/Bottleneck/test/CMakeLists.txt deleted file mode 100644 index 9d88ab25..00000000 --- a/src/Bottleneck/test/CMakeLists.txt +++ /dev/null @@ -1,21 +0,0 @@ -cmake_minimum_required(VERSION 2.6) -project(Bottleneck_tests) - -if (GCOVR_PATH) - # for gcovr to make coverage reports - Corbera Jenkins plugin - set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -fprofile-arcs -ftest-coverage") -endif() -if (GPROF_PATH) - # for gprof to make coverage reports - Jenkins - set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -pg") -endif() - -add_executable ( BottleneckUT bottleneck_unit_test.cpp ) -target_link_libraries(BottleneckUT ${Boost_SYSTEM_LIBRARY} ${Boost_UNIT_TEST_FRAMEWORK_LIBRARY}) - -# Unitary tests -add_test(NAME BottleneckUT - COMMAND ${CMAKE_CURRENT_BINARY_DIR}/BottleneckUT - # XML format for Jenkins xUnit plugin - --log_format=XML --log_sink=${CMAKE_SOURCE_DIR}/BottleneckUT.xml --log_level=test_suite --report_level=no) - diff --git a/src/Bottleneck/test/bottleneck_unit_test.cpp b/src/Bottleneck/test/bottleneck_unit_test.cpp deleted file mode 100644 index c60f5d8a..00000000 --- a/src/Bottleneck/test/bottleneck_unit_test.cpp +++ /dev/null @@ -1,26 +0,0 @@ -#define BOOST_TEST_DYN_LINK -#define BOOST_TEST_MODULE "bottleneck" -#include <boost/test/unit_test.hpp> - -#include "gudhi/Graph_matching.h" -#include <iostream> - -using namespace Gudhi::bottleneck; - -BOOST_AUTO_TEST_CASE(random_diagrams) { - int n = 100; - // Random construction - std::vector< std::pair<double, double> > v1, v2; - for (int i = 0; i < n; i++) { - int a = rand() % n; - v1.emplace_back(a, a + rand() % (n - a)); - int b = rand() % n; - v2.emplace_back(b, b + rand() % (n - b)); - } - // v1 and v2 are persistence diagrams containing each 100 randoms points. - double b = bottleneck_distance(v1, v2, 0); - // - std::cout << b << std::endl; - const double EXPECTED_DISTANCE = 98.5; - BOOST_CHECK(b == EXPECTED_DISTANCE); -} diff --git a/src/Bottleneck_distance/benchmark/CMakeLists.txt b/src/Bottleneck_distance/benchmark/CMakeLists.txt new file mode 100644 index 00000000..f70dd8ff --- /dev/null +++ b/src/Bottleneck_distance/benchmark/CMakeLists.txt @@ -0,0 +1,13 @@ +cmake_minimum_required(VERSION 2.6) +project(Bottleneck_distance_benchmark) + + +# requires CGAL 4.8 +# cmake -DCGAL_DIR=~/workspace/CGAL-4.8 ../../.. +if(CGAL_FOUND) + if (NOT CGAL_VERSION VERSION_LESS 4.8.0) + if (EIGEN3_FOUND) + add_executable ( bottleneck_chrono bottleneck_chrono.cpp ) + endif() + endif () +endif() diff --git a/src/Bottleneck_distance/benchmark/bottleneck_chrono.cpp b/src/Bottleneck_distance/benchmark/bottleneck_chrono.cpp new file mode 100644 index 00000000..456c570b --- /dev/null +++ b/src/Bottleneck_distance/benchmark/bottleneck_chrono.cpp @@ -0,0 +1,62 @@ +/* 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: Francois Godi + * + * Copyright (C) 2015 INRIA + * + * 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/>. + */ + +#include <gudhi/Bottleneck.h> +#include <chrono> +#include <fstream> +#include <random> + +using namespace Gudhi::persistence_diagram; + + +double upper_bound = 400.; // any real > 0 + +int main() { + std::ofstream result_file; + result_file.open("results.csv", std::ios::out); + + for (int n = 1000; n <= 10000; n += 1000) { + std::uniform_real_distribution<double> unif1(0., upper_bound); + std::uniform_real_distribution<double> unif2(upper_bound / 1000., upper_bound / 100.); + std::default_random_engine re; + std::vector< std::pair<double, double> > v1, v2; + for (int i = 0; i < n; i++) { + double a = unif1(re); + double b = unif1(re); + double x = unif2(re); + double y = unif2(re); + v1.emplace_back(std::min(a, b), std::max(a, b)); + v2.emplace_back(std::min(a, b) + std::min(x, y), std::max(a, b) + std::max(x, y)); + if (i % 5 == 0) + v1.emplace_back(std::min(a, b), std::min(a, b) + x); + if (i % 3 == 0) + v2.emplace_back(std::max(a, b), std::max(a, b) + y); + } + std::chrono::steady_clock::time_point start = std::chrono::steady_clock::now(); + double b = bottleneck_distance(v1, v2); + std::chrono::steady_clock::time_point end = std::chrono::steady_clock::now(); + typedef std::chrono::duration<int, std::milli> millisecs_t; + millisecs_t duration(std::chrono::duration_cast<millisecs_t>(end - start)); + result_file << n << ";" << duration.count() << ";" << b << std::endl; + } + result_file.close(); +} diff --git a/src/Bottleneck_distance/concept/Persistence_diagram.h b/src/Bottleneck_distance/concept/Persistence_diagram.h new file mode 100644 index 00000000..2706716b --- /dev/null +++ b/src/Bottleneck_distance/concept/Persistence_diagram.h @@ -0,0 +1,49 @@ +/* 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: François Godi + * + * Copyright (C) 2015 INRIA + * + * 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/>. + */ + +#ifndef CONCEPT_BOTTLENECK_DISTANCE_PERSISTENCE_DIAGRAM_H_ +#define CONCEPT_BOTTLENECK_DISTANCE_PERSISTENCE_DIAGRAM_H_ + +namespace Gudhi { + +namespace bottleneck_distance { + +/** \brief Concept of Diagram_point. std::get<0>(point) must return the birth of the corresponding component and std::get<1>(point) its death. + * A valid implementation of this concept is std::pair<double,double>. + * Death should be larger than birth, death can be std::numeric_limits<double>::infinity() for components which stay alive. + * + * \ingroup bottleneck_distance + */ +typename Diagram_point; + +/** \brief Concept of persistence diagram. It's a range of Diagram_point. + * std::begin(diagram) and std::end(diagram) must return corresponding iterators. + * + * \ingroup bottleneck_distance + */ +typename Persistence_Diagram; + +} // namespace bottleneck_distance + +} // namespace Gudhi + +#endif // CONCEPT_BOTTLENECK_DISTANCE_PERSISTENCE_DIAGRAM_H_ diff --git a/src/Bottleneck_distance/doc/Intro_bottleneck_distance.h b/src/Bottleneck_distance/doc/Intro_bottleneck_distance.h new file mode 100644 index 00000000..21187f9c --- /dev/null +++ b/src/Bottleneck_distance/doc/Intro_bottleneck_distance.h @@ -0,0 +1,51 @@ +/* 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: François Godi + * + * Copyright (C) 2015 INRIA + * + * 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/>. + */ + +#ifndef DOC_BOTTLENECK_DISTANCE_INTRO_BOTTLENECK_DISTANCE_H_ +#define DOC_BOTTLENECK_DISTANCE_INTRO_BOTTLENECK_DISTANCE_H_ + +// needs namespace for Doxygen to link on classes +namespace Gudhi { +// needs namespace for Doxygen to link on classes +namespace bottleneck_distance { + +/** \defgroup bottleneck_distance Bottleneck distance + * + * \author François Godi + * @{ + * + * \section bottleneckdefinition Definition + * + * The bottleneck distance measures the similarity between two persistence diagrams. It's the shortest distance b for which there exists a perfect matching between + * the points of the two diagrams (completed with all the points on the diagonal in order to ignore cardinality mismatchs) such that + * any couple of matched points are at distance at most b. + * + * \image html perturb_pd.png On this picture, the red edges represent the matching. The bottleneck distance is the length of the longest edge. + * + */ +/** @} */ // end defgroup bottleneck_distance + +} // namespace bottleneck_distance + +} // namespace Gudhi + +#endif // DOC_BOTTLENECK_DISTANCE_INTRO_BOTTLENECK_DISTANCE_H_ diff --git a/src/Bottleneck_distance/doc/perturb_pd.png b/src/Bottleneck_distance/doc/perturb_pd.png Binary files differnew file mode 100644 index 00000000..be638de0 --- /dev/null +++ b/src/Bottleneck_distance/doc/perturb_pd.png diff --git a/src/Bottleneck_distance/example/CMakeLists.txt b/src/Bottleneck_distance/example/CMakeLists.txt new file mode 100644 index 00000000..c66623e9 --- /dev/null +++ b/src/Bottleneck_distance/example/CMakeLists.txt @@ -0,0 +1,15 @@ +cmake_minimum_required(VERSION 2.6) +project(Bottleneck_distance_examples) + +# requires CGAL 4.8 +# cmake -DCGAL_DIR=~/workspace/CGAL-4.8 ../../.. +if(CGAL_FOUND) + if (NOT CGAL_VERSION VERSION_LESS 4.8.0) + if (EIGEN3_FOUND) + add_executable (bottleneck_read_file_example bottleneck_read_file_example.cpp) + add_executable (bottleneck_basic_example bottleneck_basic_example.cpp) + + add_test(bottleneck_basic_example ${CMAKE_CURRENT_BINARY_DIR}/bottleneck_basic_example) + endif() + endif () +endif() diff --git a/src/Bottleneck/example/random_diagrams.cpp b/src/Bottleneck_distance/example/bottleneck_basic_example.cpp index 71f152a6..d0ca4e20 100644 --- a/src/Bottleneck/example/random_diagrams.cpp +++ b/src/Bottleneck_distance/example/bottleneck_basic_example.cpp @@ -2,9 +2,9 @@ * (Geometric Understanding in Higher Dimensions) is a generic C++ * library for computational topology. * - * Author(s): Francois Godi + * Authors: Francois Godi, small modifications by Pawel Dlotko * - * Copyright (C) 2015 INRIA Saclay (France) + * Copyright (C) 2015 INRIA * * 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 @@ -20,21 +20,31 @@ * along with this program. If not, see <http://www.gnu.org/licenses/>. */ -#include "gudhi/Graph_matching.h" -#include <iostream> +#include <gudhi/Bottleneck.h> -using namespace Gudhi::bottleneck; +#include <iostream> +#include <vector> +#include <utility> // for pair +#include <limits> // for numeric_limits int main() { - int n = 100; std::vector< std::pair<double, double> > v1, v2; - for (int i = 0; i < n; i++) { - int a = rand() % n; - v1.emplace_back(a, a + rand() % (n - a)); - int b = rand() % n; - v2.emplace_back(b, b + rand() % (n - b)); - } - // v1 and v2 are persistence diagrams containing each 100 randoms points. - double b = bottleneck_distance(v1, v2, 0); - std::cout << b << std::endl; + + v1.emplace_back(2.7, 3.7); + v1.emplace_back(9.6, 14.); + v1.emplace_back(34.2, 34.974); + v1.emplace_back(3., std::numeric_limits<double>::infinity()); + + v2.emplace_back(2.8, 4.45); + v2.emplace_back(9.5, 14.1); + v2.emplace_back(3.2, std::numeric_limits<double>::infinity()); + + + double b = Gudhi::persistence_diagram::bottleneck_distance(v1, v2); + + std::cout << "Bottleneck distance = " << b << std::endl; + + b = Gudhi::persistence_diagram::bottleneck_distance(v1, v2, 0.1); + + std::cout << "Approx bottleneck distance = " << b << std::endl; } diff --git a/src/Bottleneck_distance/example/bottleneck_read_file_example.cpp b/src/Bottleneck_distance/example/bottleneck_read_file_example.cpp new file mode 100644 index 00000000..bde05825 --- /dev/null +++ b/src/Bottleneck_distance/example/bottleneck_read_file_example.cpp @@ -0,0 +1,72 @@ +/* This file is part of the Gudhi Library. The Gudhi library + * (Geometric Understanding in Higher Dimensions) is a generic C++ + * library for computational topology. + * + * Authors: Francois Godi, small modifications by Pawel Dlotko + * + * Copyright (C) 2015 INRIA + * + * 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 CGAL_HAS_THREADS + +#include <gudhi/Bottleneck.h> +#include <iostream> +#include <vector> +#include <utility> // for pair +#include <fstream> +#include <sstream> +#include <string> + +std::vector< std::pair<double, double> > read_diagram_from_file(const char* filename) { + std::ifstream in; + in.open(filename); + std::vector< std::pair<double, double> > result; + if (!in.is_open()) { + std::cerr << "File : " << filename << " do not exist. The program will now terminate \n"; + throw "File do not exist \n"; + } + + std::string line; + while (!in.eof()) { + getline(in, line); + if (line.length() != 0) { + std::stringstream lineSS; + lineSS << line; + double beginn, endd; + lineSS >> beginn; + lineSS >> endd; + result.push_back(std::make_pair(beginn, endd)); + } + } + in.close(); + return result; +} // read_diagram_from_file + +int main(int argc, char** argv) { + if (argc < 3) { + std::cout << "To run this program please provide as an input two files with persistence diagrams. Each file " << + "should contain a birth-death pair per line. Third, optional parameter is an error bound on a bottleneck" << + " distance (set by default to zero). The program will now terminate \n"; + } + std::vector< std::pair< double, double > > diag1 = read_diagram_from_file(argv[1]); + std::vector< std::pair< double, double > > diag2 = read_diagram_from_file(argv[2]); + double tolerance = 0.; + if (argc == 4) { + tolerance = atof(argv[3]); + } + double b = Gudhi::persistence_diagram::bottleneck_distance(diag1, diag2, tolerance); + std::cout << "The distance between the diagrams is : " << b << ". The tolerance is : " << tolerance << std::endl; +} diff --git a/src/Bottleneck_distance/include/gudhi/Bottleneck.h b/src/Bottleneck_distance/include/gudhi/Bottleneck.h new file mode 100644 index 00000000..b5641e29 --- /dev/null +++ b/src/Bottleneck_distance/include/gudhi/Bottleneck.h @@ -0,0 +1,104 @@ +/* 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: Francois Godi + * + * Copyright (C) 2015 INRIA + * + * 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/>. + */ + +#ifndef BOTTLENECK_H_ +#define BOTTLENECK_H_ + +#include <gudhi/Graph_matching.h> + +#include <vector> +#include <algorithm> // for max +#include <limits> // for numeric_limits + +#include <cmath> + +namespace Gudhi { + +namespace persistence_diagram { + +double bottleneck_distance_approx(Persistence_graph& g, double e) { + double b_lower_bound = 0.; + double b_upper_bound = g.diameter_bound(); + const double alpha = std::pow(g.size(), 1. / 5.); + Graph_matching m(g); + Graph_matching biggest_unperfect(g); + while (b_upper_bound - b_lower_bound > 2 * e) { + double step = b_lower_bound + (b_upper_bound - b_lower_bound) / alpha; + if (step <= b_lower_bound || step >= b_upper_bound) // Avoid precision problem + break; + m.set_r(step); + while (m.multi_augment()) {}; // compute a maximum matching (in the graph corresponding to the current r) + if (m.perfect()) { + m = biggest_unperfect; + b_upper_bound = step; + } else { + biggest_unperfect = m; + b_lower_bound = step; + } + } + return (b_lower_bound + b_upper_bound) / 2.; +} + +double bottleneck_distance_exact(Persistence_graph& g) { + std::vector<double> sd = g.sorted_distances(); + long lower_bound_i = 0; + long upper_bound_i = sd.size() - 1; + const double alpha = std::pow(g.size(), 1. / 5.); + Graph_matching m(g); + Graph_matching biggest_unperfect(g); + while (lower_bound_i != upper_bound_i) { + long step = lower_bound_i + static_cast<long> ((upper_bound_i - lower_bound_i - 1) / alpha); + m.set_r(sd.at(step)); + while (m.multi_augment()) {}; // compute a maximum matching (in the graph corresponding to the current r) + if (m.perfect()) { + m = biggest_unperfect; + upper_bound_i = step; + } else { + biggest_unperfect = m; + lower_bound_i = step + 1; + } + } + return sd.at(lower_bound_i); +} + +/** \brief Function to use in order to compute the Bottleneck distance between two persistence diagrams (see concepts). + * If the last parameter e is not 0, you get an additive e-approximation, which is a lot faster to compute whatever is + * e. + * Thus, by default, e is a very small positive double, actually the smallest double possible such that the + * floating-point inaccuracies don't lead to a failure of the algorithm. + * + * \ingroup bottleneck_distance + */ +template<typename Persistence_diagram1, typename Persistence_diagram2> +double bottleneck_distance(const Persistence_diagram1 &diag1, const Persistence_diagram2 &diag2, + double e = std::numeric_limits<double>::min()) { + Persistence_graph g(diag1, diag2, e); + if (g.bottleneck_alive() == std::numeric_limits<double>::infinity()) + return std::numeric_limits<double>::infinity(); + return std::max(g.bottleneck_alive(), e == 0. ? bottleneck_distance_exact(g) : bottleneck_distance_approx(g, e)); +} + +} // namespace persistence_diagram + +} // namespace Gudhi + +#endif // BOTTLENECK_H_ diff --git a/src/Bottleneck_distance/include/gudhi/Graph_matching.h b/src/Bottleneck_distance/include/gudhi/Graph_matching.h new file mode 100644 index 00000000..e1708c5b --- /dev/null +++ b/src/Bottleneck_distance/include/gudhi/Graph_matching.h @@ -0,0 +1,182 @@ +/* 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: Francois Godi + * + * Copyright (C) 2015 INRIA + * + * 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/>. + */ + +#ifndef GRAPH_MATCHING_H_ +#define GRAPH_MATCHING_H_ + +#include <gudhi/Neighbors_finder.h> + +#include <vector> +#include <list> + +namespace Gudhi { + +namespace persistence_diagram { + +/** \internal \brief Structure representing a graph matching. The graph is a Persistence_diagrams_graph. + * + * \ingroup bottleneck_distance + */ +class Graph_matching { + public: + /** \internal \brief Constructor constructing an empty matching. */ + explicit Graph_matching(Persistence_graph &g); + /** \internal \brief Copy operator. */ + Graph_matching& operator=(const Graph_matching& m); + /** \internal \brief Is the matching perfect ? */ + bool perfect() const; + /** \internal \brief Augments the matching with a maximal set of edge-disjoint shortest augmenting paths. */ + bool multi_augment(); + /** \internal \brief Sets the maximum length of the edges allowed to be added in the matching, 0 initially. */ + void set_r(double r); + + private: + Persistence_graph& g; + double r; + /** \internal \brief Given a point from V, provides its matched point in U, null_point_index() if there isn't. */ + std::vector<int> v_to_u; + /** \internal \brief All the unmatched points in U. */ + std::list<int> unmatched_in_u; + + /** \internal \brief Provides a Layered_neighbors_finder dividing the graph in layers. Basically a BFS. */ + Layered_neighbors_finder layering() const; + /** \internal \brief Augments the matching with a simple path no longer than max_depth. Basically a DFS. */ + bool augment(Layered_neighbors_finder & layered_nf, int u_start_index, int max_depth); + /** \internal \brief Update the matching with the simple augmenting path given as parameter. */ + void update(std::vector<int> & path); +}; + +inline Graph_matching::Graph_matching(Persistence_graph& g) + : g(g), r(0.), v_to_u(g.size(), null_point_index()), unmatched_in_u() { + for (int u_point_index = 0; u_point_index < g.size(); ++u_point_index) + unmatched_in_u.emplace_back(u_point_index); +} + +inline Graph_matching& Graph_matching::operator=(const Graph_matching& m) { + g = m.g; + r = m.r; + v_to_u = m.v_to_u; + unmatched_in_u = m.unmatched_in_u; + return *this; +} + +inline bool Graph_matching::perfect() const { + return unmatched_in_u.empty(); +} + +inline bool Graph_matching::multi_augment() { + if (perfect()) + return false; + Layered_neighbors_finder layered_nf(layering()); + int max_depth = layered_nf.vlayers_number()*2 - 1; + double rn = sqrt(g.size()); + // verification of a necessary criterion in order to shortcut if possible + if (max_depth < 0 || (unmatched_in_u.size() > rn && max_depth >= rn)) + return false; + bool successful = false; + std::list<int> tries(unmatched_in_u); + for (auto it = tries.cbegin(); it != tries.cend(); it++) + // 'augment' has side-effects which have to be always executed, don't change order + successful = augment(layered_nf, *it, max_depth) || successful; + return successful; +} + +inline void Graph_matching::set_r(double r) { + this->r = r; +} + +inline bool Graph_matching::augment(Layered_neighbors_finder & layered_nf, int u_start_index, int max_depth) { + // V vertices have at most one successor, thus when we backtrack from U we can directly pop_back 2 vertices. + std::vector<int> path; + path.emplace_back(u_start_index); + do { + if (static_cast<int> (path.size()) > max_depth) { + path.pop_back(); + path.pop_back(); + } + if (path.empty()) + return false; + path.emplace_back(layered_nf.pull_near(path.back(), static_cast<int> (path.size()) / 2)); + while (path.back() == null_point_index()) { + path.pop_back(); + path.pop_back(); + if (path.empty()) + return false; + path.pop_back(); + path.emplace_back(layered_nf.pull_near(path.back(), path.size() / 2)); + } + path.emplace_back(v_to_u.at(path.back())); + } while (path.back() != null_point_index()); + // if v_to_u.at(path.back()) has no successor, path.back() is an exposed vertex + path.pop_back(); + update(path); + return true; +} + +inline Layered_neighbors_finder Graph_matching::layering() const { + std::list<int> u_vertices(unmatched_in_u); + std::list<int> v_vertices; + Neighbors_finder nf(g, r); + for (int v_point_index = 0; v_point_index < g.size(); ++v_point_index) + nf.add(v_point_index); + Layered_neighbors_finder layered_nf(g, r); + for (int layer = 0; !u_vertices.empty(); layer++) { + // one layer is one step in the BFS + for (auto it1 = u_vertices.cbegin(); it1 != u_vertices.cend(); ++it1) { + std::vector<int> u_succ(nf.pull_all_near(*it1)); + for (auto it2 = u_succ.begin(); it2 != u_succ.end(); ++it2) { + layered_nf.add(*it2, layer); + v_vertices.emplace_back(*it2); + } + } + // When the above for finishes, we have progress of one half-step (from U to V) in the BFS + u_vertices.clear(); + bool end = false; + for (auto it = v_vertices.cbegin(); it != v_vertices.cend(); it++) + if (v_to_u.at(*it) == null_point_index()) + // we stop when a nearest exposed V vertex (from U exposed vertices) has been found + end = true; + else + u_vertices.emplace_back(v_to_u.at(*it)); + // When the above for finishes, we have progress of one half-step (from V to U) in the BFS + if (end) + return layered_nf; + v_vertices.clear(); + } + return layered_nf; +} + +inline void Graph_matching::update(std::vector<int>& path) { + unmatched_in_u.remove(path.front()); + for (auto it = path.cbegin(); it != path.cend(); ++it) { + // Be careful, the iterator is incremented twice each time + int tmp = *it; + v_to_u[*(++it)] = tmp; + } +} + + +} // namespace persistence_diagram + +} // namespace Gudhi + +#endif // GRAPH_MATCHING_H_ diff --git a/src/Bottleneck_distance/include/gudhi/Internal_point.h b/src/Bottleneck_distance/include/gudhi/Internal_point.h new file mode 100644 index 00000000..0b2d26fe --- /dev/null +++ b/src/Bottleneck_distance/include/gudhi/Internal_point.h @@ -0,0 +1,91 @@ +/* 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: Francois Godi + * + * Copyright (C) 2015 INRIA + * + * 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/>. + */ + +#ifndef INTERNAL_POINT_H_ +#define INTERNAL_POINT_H_ + +namespace Gudhi { + +namespace persistence_diagram { + +/** \internal \brief Returns the used index for encoding none of the points */ +int null_point_index(); + +/** \internal \typedef \brief Internal_point is the internal points representation, indexes used outside. */ +struct Internal_point { + double vec[2]; + int point_index; + + Internal_point() { } + + Internal_point(double x, double y, int p_i) { + vec[0] = x; + vec[1] = y; + point_index = p_i; + } + + double x() const { + return vec[ 0 ]; + } + + double y() const { + return vec[ 1 ]; + } + + double& x() { + return vec[ 0 ]; + } + + double& y() { + return vec[ 1 ]; + } + + bool operator==(const Internal_point& p) const { + return point_index == p.point_index; + } + + bool operator!=(const Internal_point& p) const { + return !(*this == p); + } +}; + +inline int null_point_index() { + return -1; +} + +struct Construct_coord_iterator { + typedef const double* result_type; + + const double* operator()(const Internal_point& p) const { + return p.vec; + } + + const double* operator()(const Internal_point& p, int) const { + return p.vec + 2; + } +}; + +} // namespace persistence_diagram + +} // namespace Gudhi + +#endif // INTERNAL_POINT_H_ diff --git a/src/Bottleneck_distance/include/gudhi/Neighbors_finder.h b/src/Bottleneck_distance/include/gudhi/Neighbors_finder.h new file mode 100644 index 00000000..cd5486f8 --- /dev/null +++ b/src/Bottleneck_distance/include/gudhi/Neighbors_finder.h @@ -0,0 +1,172 @@ +/* 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: Francois Godi + * + * Copyright (C) 2015 INRIA + * + * 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/>. + */ + +#ifndef NEIGHBORS_FINDER_H_ +#define NEIGHBORS_FINDER_H_ + +// Inclusion order is important for CGAL patch +#include <CGAL/Kd_tree.h> +#include <CGAL/Kd_tree_node.h> +#include <CGAL/Orthogonal_k_neighbor_search.h> +#include <CGAL/Weighted_Minkowski_distance.h> +#include <CGAL/Search_traits.h> + +#include <gudhi/Persistence_graph.h> +#include <gudhi/Internal_point.h> + +#include <unordered_set> +#include <vector> + +namespace Gudhi { + +namespace persistence_diagram { + +/** \internal \brief data structure used to find any point (including projections) in V near to a query point from U + * (which can be a projection). + * + * V points have to be added manually using their index and before the first pull. A neighbor pulled is automatically + * removed. + * + * \ingroup bottleneck_distance + */ +class Neighbors_finder { + typedef CGAL::Dimension_tag<2> D; + typedef CGAL::Search_traits<double, Internal_point, const double*, Construct_coord_iterator, D> Traits; + typedef CGAL::Weighted_Minkowski_distance<Traits> Distance; + typedef CGAL::Orthogonal_k_neighbor_search<Traits, Distance> K_neighbor_search; + typedef K_neighbor_search::Tree Kd_tree; + + public: + /** \internal \brief Constructor taking the near distance definition as parameter. */ + Neighbors_finder(const Persistence_graph& g, double r); + /** \internal \brief A point added will be possibly pulled. */ + void add(int v_point_index); + /** \internal \brief Returns and remove a V point near to the U point given as parameter, null_point_index() if + * there isn't such a point. */ + int pull_near(int u_point_index); + /** \internal \brief Returns and remove all the V points near to the U point given as parameter. */ + std::vector<int> pull_all_near(int u_point_index); + + private: + const Persistence_graph& g; + const double r; + Kd_tree kd_t; + std::unordered_set<int> projections_f; +}; + +/** \internal \brief data structure used to find any point (including projections) in V near to a query point from U + * (which can be a projection) in a layered graph layer given as parmeter. + * + * V points have to be added manually using their index and before the first pull. A neighbor pulled is automatically + * removed. + * + * \ingroup bottleneck_distance + */ +class Layered_neighbors_finder { + public: + /** \internal \brief Constructor taking the near distance definition as parameter. */ + Layered_neighbors_finder(const Persistence_graph& g, double r); + /** \internal \brief A point added will be possibly pulled. */ + void add(int v_point_index, int vlayer); + /** \internal \brief Returns and remove a V point near to the U point given as parameter, null_point_index() if + * there isn't such a point. */ + int pull_near(int u_point_index, int vlayer); + /** \internal \brief Returns the number of layers. */ + int vlayers_number() const; + + private: + const Persistence_graph& g; + const double r; + std::vector<std::unique_ptr<Neighbors_finder>> neighbors_finder; +}; + +inline Neighbors_finder::Neighbors_finder(const Persistence_graph& g, double r) : + g(g), r(r), kd_t(), projections_f() { } + +inline void Neighbors_finder::add(int v_point_index) { + if (g.on_the_v_diagonal(v_point_index)) + projections_f.emplace(v_point_index); + else + kd_t.insert(g.get_v_point(v_point_index)); +} + +inline int Neighbors_finder::pull_near(int u_point_index) { + int tmp; + int c = g.corresponding_point_in_v(u_point_index); + if (g.on_the_u_diagonal(u_point_index) && !projections_f.empty()) { + // Any pair of projection is at distance 0 + tmp = *projections_f.cbegin(); + projections_f.erase(tmp); + } else if (projections_f.count(c) && (g.distance(u_point_index, c) <= r)) { + // Is the query point near to its projection ? + tmp = c; + projections_f.erase(tmp); + } else { + // Is the query point near to a V point in the plane ? + Internal_point u_point = g.get_u_point(u_point_index); + std::array<double, 2> w = { + {1., 1.} + }; + K_neighbor_search search(kd_t, u_point, 1, 0., true, Distance(0, 2, w.begin(), w.end())); + auto it = search.begin(); + if (it == search.end() || g.distance(u_point_index, it->first.point_index) > r) + return null_point_index(); + tmp = it->first.point_index; + kd_t.remove(g.get_v_point(tmp)); + } + return tmp; +} + +inline std::vector<int> Neighbors_finder::pull_all_near(int u_point_index) { + std::vector<int> all_pull; + int last_pull = pull_near(u_point_index); + while (last_pull != null_point_index()) { + all_pull.emplace_back(last_pull); + last_pull = pull_near(u_point_index); + } + return all_pull; +} + +inline Layered_neighbors_finder::Layered_neighbors_finder(const Persistence_graph& g, double r) : + g(g), r(r), neighbors_finder() { } + +inline void Layered_neighbors_finder::add(int v_point_index, int vlayer) { + for (int l = neighbors_finder.size(); l <= vlayer; l++) + neighbors_finder.emplace_back(std::unique_ptr<Neighbors_finder>(new Neighbors_finder(g, r))); + neighbors_finder.at(vlayer)->add(v_point_index); +} + +inline int Layered_neighbors_finder::pull_near(int u_point_index, int vlayer) { + if (static_cast<int> (neighbors_finder.size()) <= vlayer) + return null_point_index(); + return neighbors_finder.at(vlayer)->pull_near(u_point_index); +} + +inline int Layered_neighbors_finder::vlayers_number() const { + return static_cast<int> (neighbors_finder.size()); +} + +} // namespace persistence_diagram + +} // namespace Gudhi + +#endif // NEIGHBORS_FINDER_H_ diff --git a/src/Bottleneck_distance/include/gudhi/Persistence_graph.h b/src/Bottleneck_distance/include/gudhi/Persistence_graph.h new file mode 100644 index 00000000..39efc082 --- /dev/null +++ b/src/Bottleneck_distance/include/gudhi/Persistence_graph.h @@ -0,0 +1,180 @@ +/* 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: Francois Godi + * + * Copyright (C) 2015 INRIA + * + * 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/>. + */ + +#ifndef PERSISTENCE_GRAPH_H_ +#define PERSISTENCE_GRAPH_H_ + +#include <gudhi/Internal_point.h> + +#include <vector> +#include <algorithm> +#include <limits> // for numeric_limits + +namespace Gudhi { + +namespace persistence_diagram { + +/** \internal \brief Structure representing an euclidean bipartite graph containing + * the points from the two persistence diagrams (including the projections). + * + * \ingroup bottleneck_distance + */ +class Persistence_graph { + public: + /** \internal \brief Constructor taking 2 Persistence_Diagrams (concept) as parameters. */ + template<typename Persistence_diagram1, typename Persistence_diagram2> + Persistence_graph(const Persistence_diagram1& diag1, const Persistence_diagram2& diag2, double e); + /** \internal \brief Is the given point from U the projection of a point in V ? */ + bool on_the_u_diagonal(int u_point_index) const; + /** \internal \brief Is the given point from V the projection of a point in U ? */ + bool on_the_v_diagonal(int v_point_index) const; + /** \internal \brief Given a point from V, returns the corresponding (projection or projector) point in U. */ + int corresponding_point_in_u(int v_point_index) const; + /** \internal \brief Given a point from U, returns the corresponding (projection or projector) point in V. */ + int corresponding_point_in_v(int u_point_index) const; + /** \internal \brief Given a point from U and a point from V, returns the distance between those points. */ + double distance(int u_point_index, int v_point_index) const; + /** \internal \brief Returns size = |U| = |V|. */ + int size() const; + /** \internal \brief Is there as many infinite points (alive components) in both diagrams ? */ + double bottleneck_alive() const; + /** \internal \brief Returns the O(n^2) sorted distances between the points. */ + std::vector<double> sorted_distances() const; + /** \internal \brief Returns an upper bound for the diameter of the convex hull of all non infinite points */ + double diameter_bound() const; + /** \internal \brief Returns the corresponding internal point */ + Internal_point get_u_point(int u_point_index) const; + /** \internal \brief Returns the corresponding internal point */ + Internal_point get_v_point(int v_point_index) const; + + private: + std::vector<Internal_point> u; + std::vector<Internal_point> v; + double b_alive; +}; + +template<typename Persistence_diagram1, typename Persistence_diagram2> +Persistence_graph::Persistence_graph(const Persistence_diagram1 &diag1, + const Persistence_diagram2 &diag2, double e) + : u(), v(), b_alive(0.) { + std::vector<double> u_alive; + std::vector<double> v_alive; + for (auto it = std::begin(diag1); it != std::end(diag1); ++it) { + if (std::get<1>(*it) == std::numeric_limits<double>::infinity()) + u_alive.push_back(std::get<0>(*it)); + else if (std::get<1>(*it) - std::get<0>(*it) > e) + u.push_back(Internal_point(std::get<0>(*it), std::get<1>(*it), u.size())); + } + for (auto it = std::begin(diag2); it != std::end(diag2); ++it) { + if (std::get<1>(*it) == std::numeric_limits<double>::infinity()) + v_alive.push_back(std::get<0>(*it)); + else if (std::get<1>(*it) - std::get<0>(*it) > e) + v.push_back(Internal_point(std::get<0>(*it), std::get<1>(*it), v.size())); + } + if (u.size() < v.size()) + swap(u, v); + std::sort(u_alive.begin(), u_alive.end()); + std::sort(v_alive.begin(), v_alive.end()); + if (u_alive.size() != v_alive.size()) { + b_alive = std::numeric_limits<double>::infinity(); + } else { + for (auto it_u = u_alive.cbegin(), it_v = v_alive.cbegin(); it_u != u_alive.cend(); ++it_u, ++it_v) + b_alive = std::max(b_alive, std::fabs(*it_u - *it_v)); + } +} + +inline bool Persistence_graph::on_the_u_diagonal(int u_point_index) const { + return u_point_index >= static_cast<int> (u.size()); +} + +inline bool Persistence_graph::on_the_v_diagonal(int v_point_index) const { + return v_point_index >= static_cast<int> (v.size()); +} + +inline int Persistence_graph::corresponding_point_in_u(int v_point_index) const { + return on_the_v_diagonal(v_point_index) ? + v_point_index - static_cast<int> (v.size()) : v_point_index + static_cast<int> (u.size()); +} + +inline int Persistence_graph::corresponding_point_in_v(int u_point_index) const { + return on_the_u_diagonal(u_point_index) ? + u_point_index - static_cast<int> (u.size()) : u_point_index + static_cast<int> (v.size()); +} + +inline double Persistence_graph::distance(int u_point_index, int v_point_index) const { + if (on_the_u_diagonal(u_point_index) && on_the_v_diagonal(v_point_index)) + return 0.; + Internal_point p_u = get_u_point(u_point_index); + Internal_point p_v = get_v_point(v_point_index); + return std::max(std::fabs(p_u.x() - p_v.x()), std::fabs(p_u.y() - p_v.y())); +} + +inline int Persistence_graph::size() const { + return static_cast<int> (u.size() + v.size()); +} + +inline double Persistence_graph::bottleneck_alive() const { + return b_alive; +} + +inline std::vector<double> Persistence_graph::sorted_distances() const { + std::vector<double> distances; + distances.push_back(0.); // for empty diagrams + for (int u_point_index = 0; u_point_index < size(); ++u_point_index) { + distances.push_back(distance(u_point_index, corresponding_point_in_v(u_point_index))); + for (int v_point_index = 0; v_point_index < size(); ++v_point_index) + distances.push_back(distance(u_point_index, v_point_index)); + } + std::sort(distances.begin(), distances.end()); + return distances; +} + +inline Internal_point Persistence_graph::get_u_point(int u_point_index) const { + if (!on_the_u_diagonal(u_point_index)) + return u.at(u_point_index); + Internal_point projector = v.at(corresponding_point_in_v(u_point_index)); + double m = (projector.x() + projector.y()) / 2.; + return Internal_point(m, m, u_point_index); +} + +inline Internal_point Persistence_graph::get_v_point(int v_point_index) const { + if (!on_the_v_diagonal(v_point_index)) + return v.at(v_point_index); + Internal_point projector = u.at(corresponding_point_in_u(v_point_index)); + double m = (projector.x() + projector.y()) / 2.; + return Internal_point(m, m, v_point_index); +} + +inline double Persistence_graph::diameter_bound() const { + double max = 0.; + for (auto it = u.cbegin(); it != u.cend(); it++) + max = std::max(max, it->y()); + for (auto it = v.cbegin(); it != v.cend(); it++) + max = std::max(max, it->y()); + return max; +} + +} // namespace persistence_diagram + +} // namespace Gudhi + +#endif // PERSISTENCE_GRAPH_H_ diff --git a/src/Bottleneck_distance/test/CMakeLists.txt b/src/Bottleneck_distance/test/CMakeLists.txt new file mode 100644 index 00000000..a6979d3c --- /dev/null +++ b/src/Bottleneck_distance/test/CMakeLists.txt @@ -0,0 +1,28 @@ +cmake_minimum_required(VERSION 2.6) +project(Bottleneck_distance_tests) + + +if (GCOVR_PATH) + # for gcovr to make coverage reports - Corbera Jenkins plugin + set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -fprofile-arcs -ftest-coverage") +endif() +if (GPROF_PATH) + # for gprof to make coverage reports - Jenkins + set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -pg") +endif() + +# requires CGAL 4.8 +# cmake -DCGAL_DIR=~/workspace/CGAL-4.8 ../../.. +if(CGAL_FOUND) + if (NOT CGAL_VERSION VERSION_LESS 4.8.0) + if (EIGEN3_FOUND) + add_executable ( bottleneckUT bottleneck_unit_test.cpp ) + target_link_libraries(bottleneckUT ${Boost_SYSTEM_LIBRARY} ${Boost_UNIT_TEST_FRAMEWORK_LIBRARY}) + + # Unitary tests + add_test(NAME bottleneckUT COMMAND ${CMAKE_CURRENT_BINARY_DIR}/bottleneckUT + # XML format for Jenkins xUnit plugin + --log_format=XML --log_sink=${CMAKE_SOURCE_DIR}/bottleneckUT.xml --log_level=test_suite --report_level=no) + endif() + endif () +endif() diff --git a/src/Bottleneck/test/README b/src/Bottleneck_distance/test/README index 0e7b8673..0e7b8673 100644 --- a/src/Bottleneck/test/README +++ b/src/Bottleneck_distance/test/README diff --git a/src/Bottleneck_distance/test/bottleneck_unit_test.cpp b/src/Bottleneck_distance/test/bottleneck_unit_test.cpp new file mode 100644 index 00000000..e39613b3 --- /dev/null +++ b/src/Bottleneck_distance/test/bottleneck_unit_test.cpp @@ -0,0 +1,167 @@ +/* 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: Francois Godi + * + * Copyright (C) 2015 INRIA + * + * 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 "bottleneck distance" +#include <boost/test/unit_test.hpp> + +#include <random> +#include <gudhi/Bottleneck.h> + +using namespace Gudhi::persistence_diagram; + +int n1 = 81; // a natural number >0 +int n2 = 180; // a natural number >0 +double upper_bound = 406.43; // any real >0 + + +std::uniform_real_distribution<double> unif(0., upper_bound); +std::default_random_engine re; +std::vector< std::pair<double, double> > v1, v2; + +BOOST_AUTO_TEST_CASE(persistence_graph) { + // Random construction + for (int i = 0; i < n1; i++) { + double a = unif(re); + double b = unif(re); + v1.emplace_back(std::min(a, b), std::max(a, b)); + } + for (int i = 0; i < n2; i++) { + double a = unif(re); + double b = unif(re); + v2.emplace_back(std::min(a, b), std::max(a, b)); + } + Persistence_graph g(v1, v2, 0.); + std::vector<double> d(g.sorted_distances()); + // + BOOST_CHECK(!g.on_the_u_diagonal(n1 - 1)); + BOOST_CHECK(!g.on_the_u_diagonal(n1)); + BOOST_CHECK(!g.on_the_u_diagonal(n2 - 1)); + BOOST_CHECK(g.on_the_u_diagonal(n2)); + BOOST_CHECK(!g.on_the_v_diagonal(n1 - 1)); + BOOST_CHECK(g.on_the_v_diagonal(n1)); + BOOST_CHECK(g.on_the_v_diagonal(n2 - 1)); + BOOST_CHECK(g.on_the_v_diagonal(n2)); + // + BOOST_CHECK(g.corresponding_point_in_u(0) == n2); + BOOST_CHECK(g.corresponding_point_in_u(n1) == 0); + BOOST_CHECK(g.corresponding_point_in_v(0) == n1); + BOOST_CHECK(g.corresponding_point_in_v(n2) == 0); + // + BOOST_CHECK(g.size() == (n1 + n2)); + // + BOOST_CHECK((int) d.size() == (n1 + n2)*(n1 + n2) + n1 + n2 + 1); + BOOST_CHECK(std::count(d.begin(), d.end(), g.distance(0, 0)) > 0); + BOOST_CHECK(std::count(d.begin(), d.end(), g.distance(0, n1 - 1)) > 0); + BOOST_CHECK(std::count(d.begin(), d.end(), g.distance(0, n1)) > 0); + BOOST_CHECK(std::count(d.begin(), d.end(), g.distance(0, n2 - 1)) > 0); + BOOST_CHECK(std::count(d.begin(), d.end(), g.distance(0, n2)) > 0); + BOOST_CHECK(std::count(d.begin(), d.end(), g.distance(0, (n1 + n2) - 1)) > 0); + BOOST_CHECK(std::count(d.begin(), d.end(), g.distance(n1, 0)) > 0); + BOOST_CHECK(std::count(d.begin(), d.end(), g.distance(n1, n1 - 1)) > 0); + BOOST_CHECK(std::count(d.begin(), d.end(), g.distance(n1, n1)) > 0); + BOOST_CHECK(std::count(d.begin(), d.end(), g.distance(n1, n2 - 1)) > 0); + BOOST_CHECK(std::count(d.begin(), d.end(), g.distance(n1, n2)) > 0); + BOOST_CHECK(std::count(d.begin(), d.end(), g.distance(n1, (n1 + n2) - 1)) > 0); + BOOST_CHECK(std::count(d.begin(), d.end(), g.distance((n1 + n2) - 1, 0)) > 0); + BOOST_CHECK(std::count(d.begin(), d.end(), g.distance((n1 + n2) - 1, n1 - 1)) > 0); + BOOST_CHECK(std::count(d.begin(), d.end(), g.distance((n1 + n2) - 1, n1)) > 0); + BOOST_CHECK(std::count(d.begin(), d.end(), g.distance((n1 + n2) - 1, n2 - 1)) > 0); + BOOST_CHECK(std::count(d.begin(), d.end(), g.distance((n1 + n2) - 1, n2)) > 0); + BOOST_CHECK(std::count(d.begin(), d.end(), g.distance((n1 + n2) - 1, (n1 + n2) - 1)) > 0); +} + +BOOST_AUTO_TEST_CASE(neighbors_finder) { + Persistence_graph g(v1, v2, 0.); + Neighbors_finder nf(g, 1.); + for (int v_point_index = 1; v_point_index < ((n2 + n1)*9 / 10); v_point_index += 2) + nf.add(v_point_index); + // + int v_point_index_1 = nf.pull_near(n2 / 2); + BOOST_CHECK((v_point_index_1 == -1) || (g.distance(n2 / 2, v_point_index_1) <= 1.)); + std::vector<int> l = nf.pull_all_near(n2 / 2); + bool v = true; + for (auto it = l.cbegin(); it != l.cend(); ++it) + v = v && (g.distance(n2 / 2, *it) > 1.); + BOOST_CHECK(v); + int v_point_index_2 = nf.pull_near(n2 / 2); + BOOST_CHECK(v_point_index_2 == -1); +} + +BOOST_AUTO_TEST_CASE(layered_neighbors_finder) { + Persistence_graph g(v1, v2, 0.); + Layered_neighbors_finder lnf(g, 1.); + for (int v_point_index = 1; v_point_index < ((n2 + n1)*9 / 10); v_point_index += 2) + lnf.add(v_point_index, v_point_index % 7); + // + int v_point_index_1 = lnf.pull_near(n2 / 2, 6); + BOOST_CHECK((v_point_index_1 == -1) || (g.distance(n2 / 2, v_point_index_1) <= 1.)); + int v_point_index_2 = lnf.pull_near(n2 / 2, 6); + BOOST_CHECK(v_point_index_2 == -1); + v_point_index_1 = lnf.pull_near(n2 / 2, 0); + BOOST_CHECK((v_point_index_1 == -1) || (g.distance(n2 / 2, v_point_index_1) <= 1.)); + v_point_index_2 = lnf.pull_near(n2 / 2, 0); + BOOST_CHECK(v_point_index_2 == -1); +} + +BOOST_AUTO_TEST_CASE(graph_matching) { + Persistence_graph g(v1, v2, 0.); + Graph_matching m1(g); + m1.set_r(0.); + int e = 0; + while (m1.multi_augment()) + ++e; + BOOST_CHECK(e > 0); + BOOST_CHECK(e <= 2 * sqrt(2 * (n1 + n2))); + Graph_matching m2 = m1; + BOOST_CHECK(!m2.multi_augment()); + m2.set_r(upper_bound); + e = 0; + while (m2.multi_augment()) + ++e; + BOOST_CHECK(e <= 2 * sqrt(2 * (n1 + n2))); + BOOST_CHECK(m2.perfect()); + BOOST_CHECK(!m1.perfect()); +} + +BOOST_AUTO_TEST_CASE(global) { + std::uniform_real_distribution<double> unif1(0., upper_bound); + std::uniform_real_distribution<double> unif2(upper_bound / 10000., upper_bound / 100.); + std::default_random_engine re; + std::vector< std::pair<double, double> > v1, v2; + for (int i = 0; i < n1; i++) { + double a = unif1(re); + double b = unif1(re); + double x = unif2(re); + double y = unif2(re); + v1.emplace_back(std::min(a, b), std::max(a, b)); + v2.emplace_back(std::min(a, b) + std::min(x, y), std::max(a, b) + std::max(x, y)); + if (i % 5 == 0) + v1.emplace_back(std::min(a, b), std::min(a, b) + x); + if (i % 3 == 0) + v2.emplace_back(std::max(a, b), std::max(a, b) + y); + } + BOOST_CHECK(bottleneck_distance(v1, v2, 0.) <= upper_bound / 100.); + BOOST_CHECK(bottleneck_distance(v1, v2, upper_bound / 10000.) <= upper_bound / 100. + upper_bound / 10000.); + BOOST_CHECK(std::abs(bottleneck_distance(v1, v2, 0.) - bottleneck_distance(v1, v2, upper_bound / 10000.)) <= upper_bound / 10000.); +} diff --git a/src/CMakeLists.txt b/src/CMakeLists.txt index 56198d81..441b9fb5 100644 --- a/src/CMakeLists.txt +++ b/src/CMakeLists.txt @@ -112,9 +112,11 @@ else() add_subdirectory(example/Bitmap_cubical_complex) add_subdirectory(example/Witness_complex) add_subdirectory(example/Alpha_complex) + add_subdirectory(example/Rips_complex) add_subdirectory(example/Spatial_searching) add_subdirectory(example/Subsampling) add_subdirectory(example/Tangential_complex) + add_subdirectory(example/Bottleneck_distance) # data points generator add_subdirectory(data/points/generator) diff --git a/src/Doxyfile b/src/Doxyfile index ea55627a..93399848 100644 --- a/src/Doxyfile +++ b/src/Doxyfile @@ -785,7 +785,8 @@ EXCLUDE = data/ \ GudhUI/ \ cmake/ \ debian/ \ - src/cython/ + src/cython/ \ + include/gudhi_patches/ # The EXCLUDE_SYMLINKS tag can be used to select whether or not files or # directories that are symbolic links (a Unix file system feature) are excluded diff --git a/src/GudhUI/CMakeLists.txt b/src/GudhUI/CMakeLists.txt index a43294ea..d3a52b60 100644 --- a/src/GudhUI/CMakeLists.txt +++ b/src/GudhUI/CMakeLists.txt @@ -1,46 +1,40 @@ cmake_minimum_required(VERSION 2.8) project(GudhUI) -find_package(Qt4) +find_package(CGAL COMPONENTS Qt5) +find_package(Qt5 COMPONENTS Widgets Xml OpenGL) find_package(QGLViewer) find_package(OpenGL) -if ( CGAL_FOUND AND QT4_FOUND AND OPENGL_FOUND AND QGLVIEWER_FOUND ) - set( QT_USE_QTXML TRUE ) - set( QT_USE_QTMAIN TRUE ) - set( QT_USE_QTSCRIPT TRUE ) - set( QT_USE_QTOPENGL TRUE ) - SET(Boost_USE_STATIC_LIBS ON) - SET(Boost_USE_MULTITHREAD OFF) - include(${QT_USE_FILE}) +if (NOT CGAL_FOUND) + message(ERROR " GudhUI requires CGAL and will not be compiled.") +endif() + +if (NOT Qt5_FOUND) + message(ERROR " GudhUI requires Qt5 and will not be compiled.") +endif() + +if (NOT OPENGL_FOUND) + message(ERROR " GudhUI requires OpenGL and will not be compiled.") +endif() + +if (NOT QGLVIEWER_FOUND) + message(ERROR " GudhUI requires QGLViewer and will not be compiled.") +endif() + + +if ( CGAL_FOUND AND Qt5_FOUND AND OPENGL_FOUND AND QGLVIEWER_FOUND ) + + set(CMAKE_AUTOMOC ON) + set(CMAKE_AUTOUIC ON) + set(CMAKE_INCLUDE_CURRENT_DIR ON) + + SET(Boost_USE_STATIC_LIBS ON) + SET(Boost_USE_MULTITHREAD OFF) include_directories (${QGLVIEWER_INCLUDE_DIR}) - include_directories(.) - # qt : ui file, created wih Qt Designer ############### - set(CMAKE_CURRENT_BINARY_DIR "${CMAKE_CURRENT_SOURCE_DIR}/gui") - qt4_wrap_ui( uis - gui/main_window.ui - gui/MenuEdgeContraction.ui - gui/KNearestNeighborsMenu.ui - gui/UniformNeighborsMenu.ui - gui/PersistenceMenu.ui - ) - - set(CMAKE_CURRENT_BINARY_DIR "${CMAKE_CURRENT_SOURCE_DIR}/gui") - qt4_automoc( - gui/MainWindow.cpp - gui/Menu_k_nearest_neighbors.cpp - gui/Menu_uniform_neighbors.cpp - gui/Menu_edge_contraction.cpp - gui/Menu_persistence.cpp - ) - - set(CMAKE_CURRENT_BINARY_DIR "${CMAKE_CURRENT_SOURCE_DIR}/view") - qt4_automoc(view/Viewer_instructor.cpp - view/Viewer.cpp - ) ##################################################################### add_executable ( GudhUI @@ -52,10 +46,9 @@ if ( CGAL_FOUND AND QT4_FOUND AND OPENGL_FOUND AND QGLVIEWER_FOUND ) gui/Menu_persistence.cpp view/Viewer_instructor.cpp view/Viewer.cpp - ${uis} ) - - target_link_libraries( GudhUI ${QT_LIBRARIES} ${QGLVIEWER_LIBRARIES} ) + target_link_libraries( GudhUI Qt5::Widgets Qt5::Xml Qt5::OpenGL ) + target_link_libraries( GudhUI ${QGLVIEWER_LIBRARIES} ) target_link_libraries( GudhUI ${OPENGL_gl_LIBRARY} ${OPENGL_glu_LIBRARY} ) if (TBB_FOUND) target_link_libraries( GudhUI ${TBB_LIBRARIES}) @@ -64,5 +57,5 @@ endif() ############################################################################### else() - message(STATUS "NOTICE: GudhUI requires CGAL, the QGLViewer, OpenGL and Qt4, and will not be compiled.") + message(STATUS "NOTICE: GudhUI requires CGAL, the QGLViewer, OpenGL and Qt5, and will not be compiled.") endif() diff --git a/src/GudhUI/gui/MainWindow.h b/src/GudhUI/gui/MainWindow.h index 3fe0d720..15664dcb 100644 --- a/src/GudhUI/gui/MainWindow.h +++ b/src/GudhUI/gui/MainWindow.h @@ -23,9 +23,6 @@ #ifndef GUI_MAINWINDOW_H_ #define GUI_MAINWINDOW_H_ -// Workaround for moc-qt4 not parsing boost headers -#include <CGAL/config.h> - // Workaround https://svn.boost.org/trac/boost/ticket/12534 #include <boost/container/flat_map.hpp> diff --git a/src/GudhUI/gui/Menu_edge_contraction.h b/src/GudhUI/gui/Menu_edge_contraction.h index 08f0bf67..2d5640e8 100644 --- a/src/GudhUI/gui/Menu_edge_contraction.h +++ b/src/GudhUI/gui/Menu_edge_contraction.h @@ -23,11 +23,8 @@ #ifndef GUI_MENU_EDGE_CONTRACTION_H_ #define GUI_MENU_EDGE_CONTRACTION_H_ -// Workaround for moc-qt4 not parsing boost headers -#include <CGAL/config.h> - #include "gui/MainWindow.h" -#include "gui/ui_MenuEdgeContraction.h" +#include "ui_MenuEdgeContraction.h" #include "model/Model.h" diff --git a/src/GudhUI/gui/Menu_k_nearest_neighbors.h b/src/GudhUI/gui/Menu_k_nearest_neighbors.h index 8088b768..77303b67 100644 --- a/src/GudhUI/gui/Menu_k_nearest_neighbors.h +++ b/src/GudhUI/gui/Menu_k_nearest_neighbors.h @@ -24,7 +24,7 @@ #define GUI_MENU_K_NEAREST_NEIGHBORS_H_ #include <QMainWindow> -#include "gui/ui_KNearestNeighborsMenu.h" +#include "ui_KNearestNeighborsMenu.h" class QWidget; diff --git a/src/GudhUI/gui/Menu_persistence.h b/src/GudhUI/gui/Menu_persistence.h index 8c4df158..1a2a2408 100644 --- a/src/GudhUI/gui/Menu_persistence.h +++ b/src/GudhUI/gui/Menu_persistence.h @@ -25,7 +25,7 @@ #define GUI_MENU_PERSISTENCE_H_ #include <QMainWindow> -#include "gui/ui_PersistenceMenu.h" +#include "ui_PersistenceMenu.h" class QWidget; diff --git a/src/GudhUI/gui/Menu_uniform_neighbors.h b/src/GudhUI/gui/Menu_uniform_neighbors.h index 0b6f65fe..61316966 100644 --- a/src/GudhUI/gui/Menu_uniform_neighbors.h +++ b/src/GudhUI/gui/Menu_uniform_neighbors.h @@ -25,7 +25,7 @@ #define GUI_MENU_UNIFORM_NEIGHBORS_H_ #include <QMainWindow> -#include "gui/ui_UniformNeighborsMenu.h" +#include "ui_UniformNeighborsMenu.h" class Menu_uniform_neighbors : public QDialog, public Ui::UniformMenu { Q_OBJECT diff --git a/src/GudhUI/utils/Persistence_compute.h b/src/GudhUI/utils/Persistence_compute.h index 97165490..2dc03c8e 100644 --- a/src/GudhUI/utils/Persistence_compute.h +++ b/src/GudhUI/utils/Persistence_compute.h @@ -29,6 +29,7 @@ #include <gudhi/Simplex_tree.h> #include <gudhi/distance_functions.h> #include <gudhi/Persistent_cohomology.h> +#include <gudhi/Rips_complex.h> #include <vector> @@ -69,21 +70,23 @@ template<typename SkBlComplex> class Persistence_compute { points.emplace_back(std::move(pt_to_add)); } + using Simplex_tree = Gudhi::Simplex_tree<>; + using Filtration_value = Simplex_tree::Filtration_value; + using Rips_complex = Gudhi::rips_complex::Rips_complex<Filtration_value>; + using Field_Zp = Gudhi::persistent_cohomology::Field_Zp; + using Persistent_cohomology = Gudhi::persistent_cohomology::Persistent_cohomology<Simplex_tree, Field_Zp>; - Graph_t prox_graph = compute_proximity_graph(points, params.threshold, euclidean_distance<Point_t>); - Gudhi::Simplex_tree<> st; - st.insert_graph(prox_graph); - st.expansion(params.max_dim); + Rips_complex rips_complex(points, params.threshold, Euclidean_distance()); - Gudhi::persistent_cohomology::Persistent_cohomology< Gudhi::Simplex_tree<>, - Gudhi::persistent_cohomology::Field_Zp > pcoh(st); + Simplex_tree st; + rips_complex.create_complex(st, params.max_dim); + Persistent_cohomology pcoh(st); // initializes the coefficient field for homology pcoh.init_coefficients(params.p); // put params.min_pers pcoh.compute_persistent_cohomology(params.min_pers); stream << "persistence: \n"; stream << "p dimension birth death: \n"; - pcoh.output_diagram(stream); } }; diff --git a/src/GudhUI/view/Viewer.h b/src/GudhUI/view/Viewer.h index 319c8e04..797ddc53 100644 --- a/src/GudhUI/view/Viewer.h +++ b/src/GudhUI/view/Viewer.h @@ -24,9 +24,6 @@ #ifndef VIEW_VIEWER_H_ #define VIEW_VIEWER_H_ -// Workaround for moc-qt4 not parsing boost headers -#include <CGAL/config.h> - #include <QGLViewer/qglviewer.h> #include <vector> diff --git a/src/GudhUI/view/Viewer_instructor.h b/src/GudhUI/view/Viewer_instructor.h index 1da28009..05c5c1fc 100644 --- a/src/GudhUI/view/Viewer_instructor.h +++ b/src/GudhUI/view/Viewer_instructor.h @@ -26,9 +26,6 @@ // todo do a viewer instructor that have directely a pointer to a QGLviewer and buffer ot not triangles -// Workaround for moc-qt4 not parsing boost headers -#include <CGAL/config.h> - #include <QFileDialog> #include <QKeyEvent> #include <QGLViewer/camera.h> diff --git a/src/Persistent_cohomology/benchmark/CMakeLists.txt b/src/Persistent_cohomology/benchmark/CMakeLists.txt new file mode 100644 index 00000000..ea792c89 --- /dev/null +++ b/src/Persistent_cohomology/benchmark/CMakeLists.txt @@ -0,0 +1,14 @@ +cmake_minimum_required(VERSION 2.6) +project(Persistent_cohomology_benchmark) + + +if(GMP_FOUND) + if(GMPXX_FOUND) + add_executable ( performance_rips_persistence EXCLUDE_FROM_ALL performance_rips_persistence.cpp ) + target_link_libraries(performance_rips_persistence ${Boost_SYSTEM_LIBRARY} ${Boost_PROGRAM_OPTIONS_LIBRARY} ${GMPXX_LIBRARIES} ${GMP_LIBRARIES}) + if (TBB_FOUND) + target_link_libraries(performance_rips_persistence ${TBB_LIBRARIES}) + endif(TBB_FOUND) + file(COPY "${CMAKE_SOURCE_DIR}/data/points/Kl.off" DESTINATION ${CMAKE_CURRENT_BINARY_DIR}/) + endif(GMPXX_FOUND) +endif(GMP_FOUND) diff --git a/src/Persistent_cohomology/example/performance_rips_persistence.cpp b/src/Persistent_cohomology/benchmark/performance_rips_persistence.cpp index b4d282ac..ba752999 100644 --- a/src/Persistent_cohomology/example/performance_rips_persistence.cpp +++ b/src/Persistent_cohomology/benchmark/performance_rips_persistence.cpp @@ -20,20 +20,26 @@ * along with this program. If not, see <http://www.gnu.org/licenses/>. */ -#include <gudhi/reader_utils.h> -#include <gudhi/graph_simplicial_complex.h> +#include <gudhi/Rips_complex.h> #include <gudhi/distance_functions.h> #include <gudhi/Simplex_tree.h> #include <gudhi/Persistent_cohomology.h> #include <gudhi/Persistent_cohomology/Multi_field.h> #include <gudhi/Hasse_complex.h> +#include <gudhi/Points_off_io.h> #include <chrono> #include <string> #include <vector> -using namespace Gudhi; -using namespace Gudhi::persistent_cohomology; +// Types definition +using Simplex_tree = Gudhi::Simplex_tree<Gudhi::Simplex_tree_options_fast_persistence>; +using Filtration_value = Simplex_tree::Filtration_value; +using Rips_complex = Gudhi::rips_complex::Rips_complex<Filtration_value>; +using Field_Zp = Gudhi::persistent_cohomology::Field_Zp; +using Multi_field = Gudhi::persistent_cohomology::Multi_field; +using Point = std::vector<double>; +using Points_off_reader = Gudhi::Points_off_reader<Point>; /* Compute the persistent homology of the complex cpx with coefficients in Z/pZ. */ template< typename FilteredComplex> @@ -66,33 +72,29 @@ int main(int argc, char * argv[]) { int elapsed_sec; { - std::string filepoints = "../../../data/points/Kl.txt"; + std::string off_file_points = "Kl.off"; Filtration_value threshold = 0.27; int dim_max = 3; int p = 2; int q = 1223; - // Extract the points from the file filepoints - typedef std::vector<double> Point_t; - std::vector< Point_t > points; - read_points(filepoints, points); + // Extract the points from the file off_file_points + Points_off_reader off_reader(off_file_points); // Compute the proximity graph of the points start = std::chrono::system_clock::now(); - Graph_t prox_graph = compute_proximity_graph(points, threshold - , euclidean_distance<Point_t>); + Rips_complex rips_complex_from_file(off_reader.get_point_cloud(), threshold, Euclidean_distance()); end = std::chrono::system_clock::now(); elapsed_sec = std::chrono::duration_cast<std::chrono::milliseconds>(end - start).count(); std::cout << "Compute Rips graph in " << elapsed_sec << " ms.\n"; // Construct the Rips complex in a Simplex Tree - Simplex_tree<Simplex_tree_options_fast_persistence> st; + Simplex_tree st; start = std::chrono::system_clock::now(); // insert the proximity graph in the simplex tree - st.insert_graph(prox_graph); // expand the graph until dimension dim_max - st.expansion(dim_max); + rips_complex_from_file.create_complex(st, dim_max); end = std::chrono::system_clock::now(); elapsed_sec = std::chrono::duration_cast<std::chrono::milliseconds>(end - start).count(); @@ -120,7 +122,7 @@ int main(int argc, char * argv[]) { // Convert the simplex tree into a hasse diagram start = std::chrono::system_clock::now(); - Hasse_complex<> hcpx(st); + Gudhi::Hasse_complex<> hcpx(st); end = std::chrono::system_clock::now(); elapsed_sec = std::chrono::duration_cast<std::chrono::milliseconds>(end - start).count(); std::cout << "Convert the simplex tree into a Hasse diagram in " << elapsed_sec << " ms.\n"; @@ -152,7 +154,7 @@ timing_persistence(FilteredComplex & cpx int elapsed_sec; { start = std::chrono::system_clock::now(); - Persistent_cohomology< FilteredComplex, Field_Zp > pcoh(cpx); + Gudhi::persistent_cohomology::Persistent_cohomology< FilteredComplex, Field_Zp > pcoh(cpx); end = std::chrono::system_clock::now(); elapsed_sec = std::chrono::duration_cast<std::chrono::milliseconds>(end - start).count(); std::cout << " Initialize pcoh in " << elapsed_sec << " ms.\n"; @@ -186,7 +188,7 @@ timing_persistence(FilteredComplex & cpx int elapsed_sec; { start = std::chrono::system_clock::now(); - Persistent_cohomology< FilteredComplex, Multi_field > pcoh(cpx); + Gudhi::persistent_cohomology::Persistent_cohomology< FilteredComplex, Multi_field > pcoh(cpx); end = std::chrono::system_clock::now(); elapsed_sec = std::chrono::duration_cast<std::chrono::milliseconds>(end - start).count(); std::cout << " Initialize pcoh in " << elapsed_sec << " ms.\n"; diff --git a/src/Persistent_cohomology/doc/Intro_persistent_cohomology.h b/src/Persistent_cohomology/doc/Intro_persistent_cohomology.h index 433cfd3e..40dd3f93 100644 --- a/src/Persistent_cohomology/doc/Intro_persistent_cohomology.h +++ b/src/Persistent_cohomology/doc/Intro_persistent_cohomology.h @@ -144,17 +144,23 @@ namespace persistent_cohomology { We provide several example files: run these examples with -h for details on their use, and read the README file. \li <a href="_persistent_cohomology_2rips_persistence_8cpp-example.html"> -Persistent_cohomology/rips_persistence.cpp</a> computes the Rips complex of a point cloud and its persistence diagram. +Persistent_cohomology/rips_persistence.cpp</a> computes the Rips complex of a point cloud and outputs its persistence +diagram. +\code $> ./rips_persistence ../../data/points/tore3D_1307.off -r 0.25 -m 0.5 -d 3 -p 3 \endcode +\code The complex contains 177838 simplices + and has dimension 3 +3 0 0 inf +3 1 0.0983494 inf +3 1 0.104347 inf +3 2 0.138335 inf \endcode \li <a href="_persistent_cohomology_2rips_multifield_persistence_8cpp-example.html"> -Persistent_cohomology/rips_multifield_persistence.cpp</a> computes the Rips complex of a point cloud and its +Persistent_cohomology/rips_multifield_persistence.cpp</a> computes the Rips complex of a point cloud and outputs its persistence diagram with a family of field coefficients. -\li <a href="_persistent_cohomology_2performance_rips_persistence_8cpp-example.html"> -Persistent_cohomology/performance_rips_persistence.cpp</a> provides timings for the construction of the Rips complex -on a set of points sampling a Klein bottle in \f$\mathbb{R}^5\f$ with a simplex tree, its conversion to a -Hasse diagram and the computation of persistent homology and multi-field persistent homology for the -different representations. +\li <a href="_persistent_cohomology_2rips_distance_matrix_persistence_8cpp-example.html"> +Persistent_cohomology/rips_distance_matrix_persistence.cpp</a> computes the Rips complex of a distance matrix and +outputs its persistence diagram. \li <a href="_persistent_cohomology_2alpha_complex_3d_persistence_8cpp-example.html"> Persistent_cohomology/alpha_complex_3d_persistence.cpp</a> computes the persistent homology with diff --git a/src/Persistent_cohomology/example/CMakeLists.txt b/src/Persistent_cohomology/example/CMakeLists.txt index 758bd6b1..38d7e9a9 100644 --- a/src/Persistent_cohomology/example/CMakeLists.txt +++ b/src/Persistent_cohomology/example/CMakeLists.txt @@ -11,9 +11,15 @@ target_link_libraries(plain_homology ${Boost_SYSTEM_LIBRARY}) add_executable(persistence_from_simple_simplex_tree persistence_from_simple_simplex_tree.cpp) target_link_libraries(persistence_from_simple_simplex_tree ${Boost_SYSTEM_LIBRARY}) +add_executable(rips_distance_matrix_persistence rips_distance_matrix_persistence.cpp) +target_link_libraries(rips_distance_matrix_persistence ${Boost_SYSTEM_LIBRARY} ${Boost_PROGRAM_OPTIONS_LIBRARY}) + add_executable(rips_persistence rips_persistence.cpp) target_link_libraries(rips_persistence ${Boost_SYSTEM_LIBRARY} ${Boost_PROGRAM_OPTIONS_LIBRARY}) +add_executable(rips_persistence_step_by_step rips_persistence_step_by_step.cpp) +target_link_libraries(rips_persistence_step_by_step ${Boost_SYSTEM_LIBRARY} ${Boost_PROGRAM_OPTIONS_LIBRARY}) + add_executable(rips_persistence_via_boundary_matrix rips_persistence_via_boundary_matrix.cpp) target_link_libraries(rips_persistence_via_boundary_matrix ${Boost_SYSTEM_LIBRARY} ${Boost_PROGRAM_OPTIONS_LIBRARY}) @@ -23,15 +29,19 @@ target_link_libraries(persistence_from_file ${Boost_SYSTEM_LIBRARY} ${Boost_PROG if (TBB_FOUND) target_link_libraries(plain_homology ${TBB_LIBRARIES}) target_link_libraries(persistence_from_simple_simplex_tree ${TBB_LIBRARIES}) + target_link_libraries(rips_distance_matrix_persistence ${TBB_LIBRARIES}) target_link_libraries(rips_persistence ${TBB_LIBRARIES}) + target_link_libraries(rips_persistence_step_by_step ${TBB_LIBRARIES}) target_link_libraries(rips_persistence_via_boundary_matrix ${TBB_LIBRARIES}) target_link_libraries(persistence_from_file ${TBB_LIBRARIES}) endif() add_test(plain_homology ${CMAKE_CURRENT_BINARY_DIR}/plain_homology) add_test(persistence_from_simple_simplex_tree ${CMAKE_CURRENT_BINARY_DIR}/persistence_from_simple_simplex_tree 1 0) -add_test(rips_persistence_3 ${CMAKE_CURRENT_BINARY_DIR}/rips_persistence ${CMAKE_SOURCE_DIR}/data/points/Kl.txt -r 0.16 -d 3 -p 3 -m 100) -add_test(rips_persistence_via_boundary_matrix_3 ${CMAKE_CURRENT_BINARY_DIR}/rips_persistence_via_boundary_matrix ${CMAKE_SOURCE_DIR}/data/points/Kl.txt -r 0.16 -d 3 -p 3 -m 100) +add_test(rips_distance_matrix ${CMAKE_CURRENT_BINARY_DIR}/rips_distance_matrix_persistence ${CMAKE_SOURCE_DIR}/data/distance_matrix/full_square_distance_matrix.csv -r 1.0 -d 3 -p 3 -m 0) +add_test(rips_persistence_3 ${CMAKE_CURRENT_BINARY_DIR}/rips_persistence ${CMAKE_SOURCE_DIR}/data/points/tore3D_1307.off -r 0.25 -m 0.5 -d 3 -p 3) +add_test(rips_persistence_step_by_step_3 ${CMAKE_CURRENT_BINARY_DIR}/rips_persistence_step_by_step ${CMAKE_SOURCE_DIR}/data/points/tore3D_1307.off -r 0.25 -m 0.5 -d 3 -p 3) +add_test(rips_persistence_via_boundary_matrix_3 ${CMAKE_CURRENT_BINARY_DIR}/rips_persistence_via_boundary_matrix ${CMAKE_SOURCE_DIR}/data/points/Kl.off -r 0.16 -d 3 -p 3 -m 100) add_test(persistence_from_file_3_2_0 ${CMAKE_CURRENT_BINARY_DIR}/persistence_from_file ${CMAKE_SOURCE_DIR}/data/filtered_simplicial_complex/bunny_5000_complex.fsc -p 2 -m 0) add_test(persistence_from_file_3_3_100 ${CMAKE_CURRENT_BINARY_DIR}/persistence_from_file ${CMAKE_SOURCE_DIR}/data/filtered_simplicial_complex/bunny_5000_complex.fsc -p 3 -m 100) @@ -39,14 +49,10 @@ if(GMP_FOUND) if(GMPXX_FOUND) add_executable(rips_multifield_persistence rips_multifield_persistence.cpp ) target_link_libraries(rips_multifield_persistence ${Boost_SYSTEM_LIBRARY} ${Boost_PROGRAM_OPTIONS_LIBRARY} ${GMPXX_LIBRARIES} ${GMP_LIBRARIES}) - add_executable ( performance_rips_persistence performance_rips_persistence.cpp ) - target_link_libraries(performance_rips_persistence ${Boost_SYSTEM_LIBRARY} ${Boost_PROGRAM_OPTIONS_LIBRARY} ${GMPXX_LIBRARIES} ${GMP_LIBRARIES}) if (TBB_FOUND) target_link_libraries(rips_multifield_persistence ${TBB_LIBRARIES}) - target_link_libraries(performance_rips_persistence ${TBB_LIBRARIES}) endif(TBB_FOUND) - - add_test(rips_multifield_persistence_2_71 ${CMAKE_CURRENT_BINARY_DIR}/rips_multifield_persistence ${CMAKE_SOURCE_DIR}/data/points/Kl.txt -r 0.2 -d 3 -p 2 -q 71 -m 100) + add_test(rips_multifield_persistence_2_71 ${CMAKE_CURRENT_BINARY_DIR}/rips_multifield_persistence ${CMAKE_SOURCE_DIR}/data/points/tore3D_1307.off -r 0.25 -m 0.5 -d 3 -p 2 -q 71) endif(GMPXX_FOUND) endif(GMP_FOUND) diff --git a/src/Persistent_cohomology/example/README b/src/Persistent_cohomology/example/README index 7803e5ab..2ac79398 100644 --- a/src/Persistent_cohomology/example/README +++ b/src/Persistent_cohomology/example/README @@ -10,13 +10,13 @@ Example of use of RIPS: Computation of the persistent homology with Z/2Z coefficients of the Rips complex on points sampling a Klein bottle: -./rips_persistence ../../data/points/Kl.txt -r 0.25 -d 3 -p 2 -m 100 +./rips_persistence ../../data/points/tore3D_1307.off -r 0.25 -m 0.5 -d 3 -p 2 output: -210 0 0 inf -210 1 0.0702103 inf -2 1 0.0702103 inf -2 2 0.159992 inf +2 0 0 inf +2 1 0.0983494 inf +2 1 0.104347 inf +2 2 0.138335 inf Every line is of this format: p1*...*pr dim b d @@ -29,31 +29,45 @@ where with Z/3Z coefficients: -./rips_persistence ../../data/points/Kl.txt -r 0.25 -d 3 -p 3 -m 100 +./rips_persistence ../../data/points/tore3D_1307.off -r 0.25 -m 0.5 -d 3 -p 3 output: -3 0 0 inf -3 1 0.0702103 inf +3 0 0 inf +3 1 0.0983494 inf +3 1 0.104347 inf +3 2 0.138335 inf and the computation with Z/2Z and Z/3Z coefficients simultaneously: -./rips_multifield_persistence ../../data/points/Kl.txt -r 0.25 -d 3 -p 2 -q 3 -m 100 +./rips_multifield_persistence ../../data/points/tore3D_1307.off -r 0.25 -m 0.12 -d 3 -p 2 -q 3 output: -6 0 0 inf -6 1 0.0702103 inf -2 1 0.0702103 inf -2 2 0.159992 inf +6 0 0 inf +6 1 0.0983494 inf +6 1 0.104347 inf +6 2 0.138335 inf +6 0 0 0.122545 +6 0 0 0.121171 +6 0 0 0.120964 +6 0 0 0.12057 +6 0 0 0.12047 +6 0 0 0.120414 and finally the computation with all Z/pZ for 2 <= p <= 71 (20 first prime numbers): - ./rips_multifield_persistence ../../data/points/Kl.txt -r 0.25 -d 3 -p 2 -q 71 -m 100 + ./rips_multifield_persistence ../../data/points/Kl.off -r 0.25 -m 0.5 -d 3 -p 2 -q 71 output: -557940830126698960967415390 0 0 inf -557940830126698960967415390 1 0.0702103 inf -2 1 0.0702103 inf -2 2 0.159992 inf +557940830126698960967415390 0 0 inf +557940830126698960967415390 1 0.0983494 inf +557940830126698960967415390 1 0.104347 inf +557940830126698960967415390 2 0.138335 inf +557940830126698960967415390 0 0 0.122545 +557940830126698960967415390 0 0 0.121171 +557940830126698960967415390 0 0 0.120964 +557940830126698960967415390 0 0 0.12057 +557940830126698960967415390 0 0 0.12047 +557940830126698960967415390 0 0 0.120414 *********************************************************************************************************************** Example of use of ALPHA: diff --git a/src/Persistent_cohomology/example/alpha_complex_3d_persistence.cpp b/src/Persistent_cohomology/example/alpha_complex_3d_persistence.cpp index 48fbb91a..978dc942 100644 --- a/src/Persistent_cohomology/example/alpha_complex_3d_persistence.cpp +++ b/src/Persistent_cohomology/example/alpha_complex_3d_persistence.cpp @@ -4,7 +4,7 @@ * * Author(s): Vincent Rouvreau * - * Copyright (C) 2014 INRIA Saclay (France) + * Copyright (C) 2014 INRIA * * 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 @@ -64,6 +64,7 @@ typedef std::list<Alpha_shape_3::Vertex_handle> Vertex_list; // gudhi type definition typedef Gudhi::Simplex_tree<Gudhi::Simplex_tree_options_fast_persistence> ST; +typedef ST::Filtration_value Filtration_value; typedef ST::Vertex_handle Simplex_tree_vertex; typedef std::map<Alpha_shape_3::Vertex_handle, Simplex_tree_vertex > Alpha_shape_simplex_tree_map; typedef std::pair<Alpha_shape_3::Vertex_handle, Simplex_tree_vertex> Alpha_shape_simplex_tree_pair; @@ -132,7 +133,7 @@ int main(int argc, char * const argv[]) { int coeff_field_characteristic = atoi(argv[2]); Filtration_value min_persistence = 0.0; - int returnedScanValue = sscanf(argv[3], "%lf", &min_persistence); + int returnedScanValue = sscanf(argv[3], "%f", &min_persistence); if ((returnedScanValue == EOF) || (min_persistence < -1.0)) { std::cerr << "Error: " << argv[3] << " is not correct\n"; usage(argv[0]); diff --git a/src/Persistent_cohomology/example/alpha_complex_persistence.cpp b/src/Persistent_cohomology/example/alpha_complex_persistence.cpp index 2412569a..9e84e91f 100644 --- a/src/Persistent_cohomology/example/alpha_complex_persistence.cpp +++ b/src/Persistent_cohomology/example/alpha_complex_persistence.cpp @@ -11,6 +11,9 @@ #include <string> #include <limits> // for numeric_limits +using Simplex_tree = Gudhi::Simplex_tree<>; +using Filtration_value = Simplex_tree::Filtration_value; + void program_options(int argc, char * argv[] , std::string & off_file_points , std::string & output_file_diag @@ -34,7 +37,7 @@ int main(int argc, char **argv) { using Kernel = CGAL::Epick_d< CGAL::Dynamic_dimension_tag >; Gudhi::alpha_complex::Alpha_complex<Kernel> alpha_complex_from_file(off_file_points); - Gudhi::Simplex_tree<> simplex; + Simplex_tree simplex; if (alpha_complex_from_file.create_complex(simplex, alpha_square_max_value)) { // ---------------------------------------------------------------------------- // Display information about the alpha complex @@ -48,7 +51,7 @@ int main(int argc, char **argv) { std::cout << "Simplex_tree dim: " << simplex.dimension() << std::endl; // Compute the persistence diagram of the complex - Gudhi::persistent_cohomology::Persistent_cohomology< Gudhi::Simplex_tree<>, + Gudhi::persistent_cohomology::Persistent_cohomology< Simplex_tree, Gudhi::persistent_cohomology::Field_Zp > pcoh(simplex); // initializes the coefficient field for homology pcoh.init_coefficients(coeff_field_characteristic); diff --git a/src/Persistent_cohomology/example/periodic_alpha_complex_3d_persistence.cpp b/src/Persistent_cohomology/example/periodic_alpha_complex_3d_persistence.cpp index a199fea1..dbc42706 100644 --- a/src/Persistent_cohomology/example/periodic_alpha_complex_3d_persistence.cpp +++ b/src/Persistent_cohomology/example/periodic_alpha_complex_3d_persistence.cpp @@ -4,7 +4,7 @@ * * Author(s): Vincent Rouvreau * - * Copyright (C) 2014 INRIA Saclay (France) + * Copyright (C) 2014 INRIA * * 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 @@ -39,6 +39,7 @@ #include <utility> #include <list> #include <vector> +#include <cstdlib> // Traits using K = CGAL::Exact_predicates_inexact_constructions_kernel; @@ -70,6 +71,7 @@ using Vertex_list = std::list<Alpha_shape_3::Vertex_handle>; // gudhi type definition using ST = Gudhi::Simplex_tree<Gudhi::Simplex_tree_options_fast_persistence>; +using Filtration_value = ST::Filtration_value; using Simplex_tree_vertex = ST::Vertex_handle; using Alpha_shape_simplex_tree_map = std::map<Alpha_shape_3::Vertex_handle, Simplex_tree_vertex >; using Alpha_shape_simplex_tree_pair = std::pair<Alpha_shape_3::Vertex_handle, Simplex_tree_vertex>; @@ -136,19 +138,8 @@ int main(int argc, char * const argv[]) { usage(argv[0]); } - int coeff_field_characteristic = 0; - int returnedScanValue = sscanf(argv[3], "%d", &coeff_field_characteristic); - if ((returnedScanValue == EOF) || (coeff_field_characteristic <= 0)) { - std::cerr << "Error: " << argv[3] << " is not correct\n"; - usage(argv[0]); - } - - Filtration_value min_persistence = 0.0; - returnedScanValue = sscanf(argv[4], "%lf", &min_persistence); - if ((returnedScanValue == EOF) || (min_persistence < -1.0)) { - std::cerr << "Error: " << argv[4] << " is not correct\n"; - usage(argv[0]); - } + int coeff_field_characteristic = atoi(argv[3]); + Filtration_value min_persistence = strtof(argv[4], nullptr); // Read points from file std::string offInputFile(argv[1]); diff --git a/src/Persistent_cohomology/example/persistence_from_simple_simplex_tree.cpp b/src/Persistent_cohomology/example/persistence_from_simple_simplex_tree.cpp index ba772f04..7ca9410a 100644 --- a/src/Persistent_cohomology/example/persistence_from_simple_simplex_tree.cpp +++ b/src/Persistent_cohomology/example/persistence_from_simple_simplex_tree.cpp @@ -4,7 +4,7 @@ * * Author(s): Vincent Rouvreau * - * Copyright (C) 2014 INRIA Sophia Antipolis-Méditerranée (France) + * Copyright (C) 2014 INRIA * * 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 @@ -29,13 +29,12 @@ #include <utility> #include <vector> -using namespace Gudhi; -using namespace Gudhi::persistent_cohomology; - -typedef std::vector< Vertex_handle > typeVectorVertex; -typedef std::pair<typeVectorVertex, Filtration_value> typeSimplex; -typedef std::pair< Simplex_tree<>::Simplex_handle, bool > typePairSimplexBool; -typedef Simplex_tree<> typeST; +// Types definition +using Simplex_tree = Gudhi::Simplex_tree<>; +using Filtration_value = Simplex_tree::Filtration_value; +using Field_Zp = Gudhi::persistent_cohomology::Field_Zp; +using Persistent_cohomology = Gudhi::persistent_cohomology::Persistent_cohomology<Simplex_tree, Field_Zp >; +using typeVectorVertex = std::vector< Simplex_tree::Vertex_handle >; void usage(char * const progName) { std::cerr << "Usage: " << progName << " coeff_field_characteristic[integer > 0] min_persistence[float >= -1.0]\n"; @@ -66,7 +65,7 @@ int main(int argc, char * const argv[]) { // TEST OF INSERTION std::cout << "********************************************************************" << std::endl; std::cout << "TEST OF INSERTION" << std::endl; - typeST st; + Simplex_tree st; // ++ FIRST std::cout << " - INSERT (0,1,2)" << std::endl; @@ -166,7 +165,7 @@ int main(int argc, char * const argv[]) { std::cout << "**************************************************************" << std::endl; // Compute the persistence diagram of the complex - persistent_cohomology::Persistent_cohomology< Simplex_tree<>, Field_Zp > pcoh(st); + Persistent_cohomology pcoh(st); // initializes the coefficient field for homology pcoh.init_coefficients(coeff_field_characteristic); diff --git a/src/Persistent_cohomology/example/rips_distance_matrix_persistence.cpp b/src/Persistent_cohomology/example/rips_distance_matrix_persistence.cpp new file mode 100644 index 00000000..8517e7f6 --- /dev/null +++ b/src/Persistent_cohomology/example/rips_distance_matrix_persistence.cpp @@ -0,0 +1,144 @@ +/* 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, Vincent Rouvreau + * + * Copyright (C) 2016 INRIA + * + * 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/>. + */ + +#include <gudhi/Rips_complex.h> +#include <gudhi/Simplex_tree.h> +#include <gudhi/Persistent_cohomology.h> +#include <gudhi/reader_utils.h> + +#include <boost/program_options.hpp> + +#include <string> +#include <vector> +#include <limits> // infinity + +// Types definition +using Simplex_tree = Gudhi::Simplex_tree<Gudhi::Simplex_tree_options_fast_persistence>; +using Filtration_value = Simplex_tree::Filtration_value; +using Rips_complex = Gudhi::rips_complex::Rips_complex<Filtration_value>; +using Field_Zp = Gudhi::persistent_cohomology::Field_Zp; +using Persistent_cohomology = Gudhi::persistent_cohomology::Persistent_cohomology<Simplex_tree, Field_Zp >; +using Distance_matrix = std::vector<std::vector<Filtration_value>>; + +void program_options(int argc, char * argv[] + , std::string & csv_matrix_file + , std::string & filediag + , Filtration_value & threshold + , int & dim_max + , int & p + , Filtration_value & min_persistence); + +int main(int argc, char * argv[]) { + std::string csv_matrix_file; + std::string filediag; + Filtration_value threshold; + int dim_max; + int p; + Filtration_value min_persistence; + + program_options(argc, argv, csv_matrix_file, filediag, threshold, dim_max, p, min_persistence); + + Distance_matrix distances = read_lower_triangular_matrix_from_csv_file<Filtration_value>(csv_matrix_file); + Rips_complex rips_complex_from_file(distances, threshold); + + // Construct the Rips complex in a Simplex Tree + Simplex_tree simplex_tree; + + rips_complex_from_file.create_complex(simplex_tree, dim_max); + std::cout << "The complex contains " << simplex_tree.num_simplices() << " simplices \n"; + std::cout << " and has dimension " << simplex_tree.dimension() << " \n"; + + // Sort the simplices in the order of the filtration + simplex_tree.initialize_filtration(); + + // Compute the persistence diagram of the complex + Persistent_cohomology pcoh(simplex_tree); + // initializes the coefficient field for homology + pcoh.init_coefficients(p); + + pcoh.compute_persistent_cohomology(min_persistence); + + // Output the diagram in filediag + if (filediag.empty()) { + pcoh.output_diagram(); + } else { + std::ofstream out(filediag); + pcoh.output_diagram(out); + out.close(); + } + return 0; +} + +void program_options(int argc, char * argv[] + , std::string & csv_matrix_file + , std::string & filediag + , Filtration_value & threshold + , int & dim_max + , int & p + , Filtration_value & min_persistence) { + namespace po = boost::program_options; + po::options_description hidden("Hidden options"); + hidden.add_options() + ("input-file", po::value<std::string>(&csv_matrix_file), + "Name of file containing a distance matrix. Can be square or lower triangular matrix. Separator is ';'."); + + po::options_description visible("Allowed options", 100); + visible.add_options() + ("help,h", "produce help message") + ("output-file,o", po::value<std::string>(&filediag)->default_value(std::string()), + "Name of file in which the persistence diagram is written. Default print in std::cout") + ("max-edge-length,r", + po::value<Filtration_value>(&threshold)->default_value(std::numeric_limits<Filtration_value>::infinity()), + "Maximal length of an edge for the Rips complex construction.") + ("cpx-dimension,d", po::value<int>(&dim_max)->default_value(1), + "Maximal dimension of the Rips complex we want to compute.") + ("field-charac,p", po::value<int>(&p)->default_value(11), + "Characteristic p of the coefficient field Z/pZ for computing homology.") + ("min-persistence,m", po::value<Filtration_value>(&min_persistence), + "Minimal lifetime of homology feature to be recorded. Default is 0. Enter a negative value to see zero length intervals"); + + po::positional_options_description pos; + pos.add("input-file", 1); + + po::options_description all; + all.add(visible).add(hidden); + + po::variables_map vm; + po::store(po::command_line_parser(argc, argv). + options(all).positional(pos).run(), vm); + po::notify(vm); + + if (vm.count("help") || !vm.count("input-file")) { + std::cout << std::endl; + std::cout << "Compute the persistent homology with coefficient field Z/pZ \n"; + std::cout << "of a Rips complex defined on a set of distance matrix.\n \n"; + std::cout << "The output diagram contains one bar per line, written with the convention: \n"; + std::cout << " p dim b d \n"; + std::cout << "where dim is the dimension of the homological feature,\n"; + std::cout << "b and d are respectively the birth and death of the feature and \n"; + std::cout << "p is the characteristic of the field Z/pZ used for homology coefficients." << std::endl << std::endl; + + std::cout << "Usage: " << argv[0] << " [options] input-file" << std::endl << std::endl; + std::cout << visible << std::endl; + std::abort(); + } +} diff --git a/src/Persistent_cohomology/example/rips_multifield_persistence.cpp b/src/Persistent_cohomology/example/rips_multifield_persistence.cpp index c5cd775d..7674b5a5 100644 --- a/src/Persistent_cohomology/example/rips_multifield_persistence.cpp +++ b/src/Persistent_cohomology/example/rips_multifield_persistence.cpp @@ -4,7 +4,7 @@ * * Author(s): Clément Maria * - * Copyright (C) 2014 INRIA Sophia Antipolis-Méditerranée (France) + * Copyright (C) 2014 INRIA * * 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 @@ -20,26 +20,29 @@ * along with this program. If not, see <http://www.gnu.org/licenses/>. */ -#include <gudhi/reader_utils.h> -#include <gudhi/graph_simplicial_complex.h> +#include <gudhi/Rips_complex.h> #include <gudhi/distance_functions.h> #include <gudhi/Simplex_tree.h> #include <gudhi/Persistent_cohomology.h> #include <gudhi/Persistent_cohomology/Multi_field.h> +#include <gudhi/Points_off_io.h> #include <boost/program_options.hpp> #include <string> #include <vector> -using namespace Gudhi; -using namespace Gudhi::persistent_cohomology; - -typedef int Vertex_handle; -typedef double Filtration_value; +// Types definition +using Simplex_tree = Gudhi::Simplex_tree<Gudhi::Simplex_tree_options_fast_persistence>; +using Filtration_value = Simplex_tree::Filtration_value; +using Rips_complex = Gudhi::rips_complex::Rips_complex<Filtration_value>; +using Multi_field = Gudhi::persistent_cohomology::Multi_field; +using Persistent_cohomology = Gudhi::persistent_cohomology::Persistent_cohomology<Simplex_tree, Multi_field >; +using Point = std::vector<double>; +using Points_off_reader = Gudhi::Points_off_reader<Point>; void program_options(int argc, char * argv[] - , std::string & filepoints + , std::string & off_file_points , std::string & filediag , Filtration_value & threshold , int & dim_max @@ -48,7 +51,7 @@ void program_options(int argc, char * argv[] , Filtration_value & min_persistence); int main(int argc, char * argv[]) { - std::string filepoints; + std::string off_file_points; std::string filediag; Filtration_value threshold; int dim_max; @@ -56,33 +59,26 @@ int main(int argc, char * argv[]) { int max_p; Filtration_value min_persistence; - program_options(argc, argv, filepoints, filediag, threshold, dim_max, min_p, max_p, min_persistence); - - // Extract the points from the file filepoints - typedef std::vector<double> Point_t; - std::vector< Point_t > points; - read_points(filepoints, points); + program_options(argc, argv, off_file_points, filediag, threshold, dim_max, min_p, max_p, min_persistence); - // Compute the proximity graph of the points - Graph_t prox_graph = compute_proximity_graph(points, threshold - , euclidean_distance<Point_t>); + Points_off_reader off_reader(off_file_points); + Rips_complex rips_complex_from_file(off_reader.get_point_cloud(), threshold, Euclidean_distance()); // Construct the Rips complex in a Simplex Tree - typedef Simplex_tree<Simplex_tree_options_fast_persistence> ST; - ST st; - // insert the proximity graph in the simplex tree - st.insert_graph(prox_graph); - // expand the graph until dimension dim_max - st.expansion(dim_max); + Simplex_tree simplex_tree; + + rips_complex_from_file.create_complex(simplex_tree, dim_max); + std::cout << "The complex contains " << simplex_tree.num_simplices() << " simplices \n"; + std::cout << " and has dimension " << simplex_tree.dimension() << " \n"; // Sort the simplices in the order of the filtration - st.initialize_filtration(); + simplex_tree.initialize_filtration(); // Compute the persistence diagram of the complex - Persistent_cohomology<ST, Multi_field > pcoh(st); + Persistent_cohomology pcoh(simplex_tree); // initializes the coefficient field for homology pcoh.init_coefficients(min_p, max_p); - // compute persistent homology, disgarding persistent features of life shorter than min_persistence + pcoh.compute_persistent_cohomology(min_persistence); // Output the diagram in filediag @@ -98,7 +94,7 @@ int main(int argc, char * argv[]) { } void program_options(int argc, char * argv[] - , std::string & filepoints + , std::string & off_file_points , std::string & filediag , Filtration_value & threshold , int & dim_max @@ -108,8 +104,8 @@ void program_options(int argc, char * argv[] namespace po = boost::program_options; po::options_description hidden("Hidden options"); hidden.add_options() - ("input-file", po::value<std::string>(&filepoints), - "Name of file containing a point set. Format is one point per line: X1 ... Xd \n"); + ("input-file", po::value<std::string>(&off_file_points), + "Name of an OFF file containing a point set.\n"); po::options_description visible("Allowed options"); visible.add_options() diff --git a/src/Persistent_cohomology/example/rips_persistence.cpp b/src/Persistent_cohomology/example/rips_persistence.cpp index cab49395..c6378de7 100644 --- a/src/Persistent_cohomology/example/rips_persistence.cpp +++ b/src/Persistent_cohomology/example/rips_persistence.cpp @@ -4,7 +4,7 @@ * * Author(s): Clément Maria * - * Copyright (C) 2014 INRIA Sophia Antipolis-Méditerranée (France) + * Copyright (C) 2014 INRIA * * 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 @@ -20,11 +20,11 @@ * along with this program. If not, see <http://www.gnu.org/licenses/>. */ -#include <gudhi/reader_utils.h> -#include <gudhi/graph_simplicial_complex.h> +#include <gudhi/Rips_complex.h> #include <gudhi/distance_functions.h> #include <gudhi/Simplex_tree.h> #include <gudhi/Persistent_cohomology.h> +#include <gudhi/Points_off_io.h> #include <boost/program_options.hpp> @@ -32,14 +32,17 @@ #include <vector> #include <limits> // infinity -using namespace Gudhi; -using namespace Gudhi::persistent_cohomology; - -typedef int Vertex_handle; -typedef double Filtration_value; +// Types definition +using Simplex_tree = Gudhi::Simplex_tree<Gudhi::Simplex_tree_options_fast_persistence>; +using Filtration_value = Simplex_tree::Filtration_value; +using Rips_complex = Gudhi::rips_complex::Rips_complex<Filtration_value>; +using Field_Zp = Gudhi::persistent_cohomology::Field_Zp; +using Persistent_cohomology = Gudhi::persistent_cohomology::Persistent_cohomology<Simplex_tree, Field_Zp >; +using Point = std::vector<double>; +using Points_off_reader = Gudhi::Points_off_reader<Point>; void program_options(int argc, char * argv[] - , std::string & filepoints + , std::string & off_file_points , std::string & filediag , Filtration_value & threshold , int & dim_max @@ -47,40 +50,30 @@ void program_options(int argc, char * argv[] , Filtration_value & min_persistence); int main(int argc, char * argv[]) { - std::string filepoints; + std::string off_file_points; std::string filediag; Filtration_value threshold; int dim_max; int p; Filtration_value min_persistence; - program_options(argc, argv, filepoints, filediag, threshold, dim_max, p, min_persistence); - - // Extract the points from the file filepoints - typedef std::vector<double> Point_t; - std::vector< Point_t > points; - read_points(filepoints, points); + program_options(argc, argv, off_file_points, filediag, threshold, dim_max, p, min_persistence); - // Compute the proximity graph of the points - Graph_t prox_graph = compute_proximity_graph(points, threshold - , euclidean_distance<Point_t>); + Points_off_reader off_reader(off_file_points); + Rips_complex rips_complex_from_file(off_reader.get_point_cloud(), threshold, Euclidean_distance()); // Construct the Rips complex in a Simplex Tree - typedef Simplex_tree<Simplex_tree_options_fast_persistence> ST; - ST st; - // insert the proximity graph in the simplex tree - st.insert_graph(prox_graph); - // expand the graph until dimension dim_max - st.expansion(dim_max); + Simplex_tree simplex_tree; - std::cout << "The complex contains " << st.num_simplices() << " simplices \n"; - std::cout << " and has dimension " << st.dimension() << " \n"; + rips_complex_from_file.create_complex(simplex_tree, dim_max); + std::cout << "The complex contains " << simplex_tree.num_simplices() << " simplices \n"; + std::cout << " and has dimension " << simplex_tree.dimension() << " \n"; // Sort the simplices in the order of the filtration - st.initialize_filtration(); + simplex_tree.initialize_filtration(); // Compute the persistence diagram of the complex - persistent_cohomology::Persistent_cohomology<ST, Field_Zp > pcoh(st); + Persistent_cohomology pcoh(simplex_tree); // initializes the coefficient field for homology pcoh.init_coefficients(p); @@ -99,7 +92,7 @@ int main(int argc, char * argv[]) { } void program_options(int argc, char * argv[] - , std::string & filepoints + , std::string & off_file_points , std::string & filediag , Filtration_value & threshold , int & dim_max @@ -108,15 +101,16 @@ void program_options(int argc, char * argv[] namespace po = boost::program_options; po::options_description hidden("Hidden options"); hidden.add_options() - ("input-file", po::value<std::string>(&filepoints), - "Name of file containing a point set. Format is one point per line: X1 ... Xd "); + ("input-file", po::value<std::string>(&off_file_points), + "Name of an OFF file containing a point set.\n"); po::options_description visible("Allowed options", 100); visible.add_options() ("help,h", "produce help message") ("output-file,o", po::value<std::string>(&filediag)->default_value(std::string()), "Name of file in which the persistence diagram is written. Default print in std::cout") - ("max-edge-length,r", po::value<Filtration_value>(&threshold)->default_value(std::numeric_limits<Filtration_value>::infinity()), + ("max-edge-length,r", + po::value<Filtration_value>(&threshold)->default_value(std::numeric_limits<Filtration_value>::infinity()), "Maximal length of an edge for the Rips complex construction.") ("cpx-dimension,d", po::value<int>(&dim_max)->default_value(1), "Maximal dimension of the Rips complex we want to compute.") diff --git a/src/Persistent_cohomology/example/rips_persistence_step_by_step.cpp b/src/Persistent_cohomology/example/rips_persistence_step_by_step.cpp new file mode 100644 index 00000000..c8f0921a --- /dev/null +++ b/src/Persistent_cohomology/example/rips_persistence_step_by_step.cpp @@ -0,0 +1,210 @@ +/* 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): Clément Maria + * + * Copyright (C) 2014 INRIA Sophia Antipolis-Méditerranée (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/>. + */ + +#include <gudhi/graph_simplicial_complex.h> +#include <gudhi/distance_functions.h> +#include <gudhi/Simplex_tree.h> +#include <gudhi/Persistent_cohomology.h> +#include <gudhi/Points_off_io.h> + +#include <boost/program_options.hpp> + +#include <string> +#include <vector> +#include <limits> // infinity +#include <utility> // for pair +#include <map> + +// Types definition +using Simplex_tree = Gudhi::Simplex_tree<Gudhi::Simplex_tree_options_fast_persistence>; +using Vertex_handle = Simplex_tree::Vertex_handle; +using Filtration_value = Simplex_tree::Filtration_value; +using Graph_t = boost::adjacency_list < boost::vecS, boost::vecS, boost::undirectedS +, boost::property < vertex_filtration_t, Filtration_value > +, boost::property < edge_filtration_t, Filtration_value > +>; +using Edge_t = std::pair< Vertex_handle, Vertex_handle >; + +template< typename InputPointRange, typename Distance > +Graph_t compute_proximity_graph(InputPointRange &points, Filtration_value threshold, Distance distance); + +using Field_Zp = Gudhi::persistent_cohomology::Field_Zp; +using Persistent_cohomology = Gudhi::persistent_cohomology::Persistent_cohomology<Simplex_tree, Field_Zp >; +using Point = std::vector<double>; +using Points_off_reader = Gudhi::Points_off_reader<Point>; + +void program_options(int argc, char * argv[] + , std::string & off_file_points + , std::string & filediag + , Filtration_value & threshold + , int & dim_max + , int & p + , Filtration_value & min_persistence); + +int main(int argc, char * argv[]) { + std::string off_file_points; + std::string filediag; + Filtration_value threshold; + int dim_max; + int p; + Filtration_value min_persistence; + + program_options(argc, argv, off_file_points, filediag, threshold, dim_max, p, min_persistence); + + // Extract the points from the file filepoints + Points_off_reader off_reader(off_file_points); + + // Compute the proximity graph of the points + Graph_t prox_graph = compute_proximity_graph(off_reader.get_point_cloud(), threshold + , Euclidean_distance()); + + // Construct the Rips complex in a Simplex Tree + Simplex_tree st; + // insert the proximity graph in the simplex tree + st.insert_graph(prox_graph); + // expand the graph until dimension dim_max + st.expansion(dim_max); + + std::cout << "The complex contains " << st.num_simplices() << " simplices \n"; + std::cout << " and has dimension " << st.dimension() << " \n"; + + // Sort the simplices in the order of the filtration + st.initialize_filtration(); + + // Compute the persistence diagram of the complex + Persistent_cohomology pcoh(st); + // initializes the coefficient field for homology + pcoh.init_coefficients(p); + + pcoh.compute_persistent_cohomology(min_persistence); + + // Output the diagram in filediag + if (filediag.empty()) { + pcoh.output_diagram(); + } else { + std::ofstream out(filediag); + pcoh.output_diagram(out); + out.close(); + } + + return 0; +} + +void program_options(int argc, char * argv[] + , std::string & off_file_points + , std::string & filediag + , Filtration_value & threshold + , int & dim_max + , int & p + , Filtration_value & min_persistence) { + namespace po = boost::program_options; + po::options_description hidden("Hidden options"); + hidden.add_options() + ("input-file", po::value<std::string>(&off_file_points), + "Name of an OFF file containing a point set.\n"); + + po::options_description visible("Allowed options", 100); + visible.add_options() + ("help,h", "produce help message") + ("output-file,o", po::value<std::string>(&filediag)->default_value(std::string()), + "Name of file in which the persistence diagram is written. Default print in std::cout") + ("max-edge-length,r", + po::value<Filtration_value>(&threshold)->default_value(std::numeric_limits<Filtration_value>::infinity()), + "Maximal length of an edge for the Rips complex construction.") + ("cpx-dimension,d", po::value<int>(&dim_max)->default_value(1), + "Maximal dimension of the Rips complex we want to compute.") + ("field-charac,p", po::value<int>(&p)->default_value(11), + "Characteristic p of the coefficient field Z/pZ for computing homology.") + ("min-persistence,m", po::value<Filtration_value>(&min_persistence), + "Minimal lifetime of homology feature to be recorded. Default is 0. Enter a negative value to see zero length intervals"); + + po::positional_options_description pos; + pos.add("input-file", 1); + + po::options_description all; + all.add(visible).add(hidden); + + po::variables_map vm; + po::store(po::command_line_parser(argc, argv). + options(all).positional(pos).run(), vm); + po::notify(vm); + + if (vm.count("help") || !vm.count("input-file")) { + std::cout << std::endl; + std::cout << "Compute the persistent homology with coefficient field Z/pZ \n"; + std::cout << "of a Rips complex defined on a set of input points.\n \n"; + std::cout << "The output diagram contains one bar per line, written with the convention: \n"; + std::cout << " p dim b d \n"; + std::cout << "where dim is the dimension of the homological feature,\n"; + std::cout << "b and d are respectively the birth and death of the feature and \n"; + std::cout << "p is the characteristic of the field Z/pZ used for homology coefficients." << std::endl << std::endl; + + std::cout << "Usage: " << argv[0] << " [options] input-file" << std::endl << std::endl; + std::cout << visible << std::endl; + std::abort(); + } +} + +/** Output the proximity graph of the points. + * + * If points contains n elements, the proximity graph is the graph + * with n vertices, and an edge [u,v] iff the distance function between + * points u and v is smaller than threshold. + * + * The type PointCloud furnishes .begin() and .end() methods, that return + * iterators with value_type Point. + */ +template< typename InputPointRange, typename Distance > +Graph_t compute_proximity_graph(InputPointRange &points, Filtration_value threshold, Distance distance) { + std::vector< Edge_t > edges; + std::vector< Filtration_value > edges_fil; + + Vertex_handle idx_u, idx_v; + Filtration_value fil; + idx_u = 0; + for (auto it_u = points.begin(); it_u != points.end(); ++it_u) { + idx_v = idx_u + 1; + for (auto it_v = it_u + 1; it_v != points.end(); ++it_v, ++idx_v) { + fil = distance(*it_u, *it_v); + if (fil <= threshold) { + edges.emplace_back(idx_u, idx_v); + edges_fil.push_back(fil); + } + } + ++idx_u; + } + + Graph_t skel_graph(edges.begin() + , edges.end() + , edges_fil.begin() + , idx_u); // number of points labeled from 0 to idx_u-1 + + auto vertex_prop = boost::get(vertex_filtration_t(), skel_graph); + + boost::graph_traits<Graph_t>::vertex_iterator vi, vi_end; + for (std::tie(vi, vi_end) = boost::vertices(skel_graph); + vi != vi_end; ++vi) { + boost::put(vertex_prop, *vi, 0.); + } + + return skel_graph; +} diff --git a/src/Persistent_cohomology/example/rips_persistence_via_boundary_matrix.cpp b/src/Persistent_cohomology/example/rips_persistence_via_boundary_matrix.cpp index 4c6656f5..63da9847 100644 --- a/src/Persistent_cohomology/example/rips_persistence_via_boundary_matrix.cpp +++ b/src/Persistent_cohomology/example/rips_persistence_via_boundary_matrix.cpp @@ -4,8 +4,7 @@ * * Author(s): Clément Maria, Marc Glisse * - * Copyright (C) 2014 INRIA Sophia Antipolis-Méditerranée (France), - * 2015 INRIA Saclay ÃŽle de France) + * Copyright (C) 2014 INRIA * * 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 @@ -21,12 +20,12 @@ * along with this program. If not, see <http://www.gnu.org/licenses/>. */ -#include <gudhi/reader_utils.h> -#include <gudhi/graph_simplicial_complex.h> -#include <gudhi/distance_functions.h> #include <gudhi/Simplex_tree.h> #include <gudhi/Persistent_cohomology.h> +#include <gudhi/Rips_complex.h> #include <gudhi/Hasse_complex.h> +#include <gudhi/Points_off_io.h> +#include <gudhi/distance_functions.h> #include <boost/program_options.hpp> @@ -44,14 +43,16 @@ // // //////////////////////////////////////////////////////////////// -using namespace Gudhi; -using namespace Gudhi::persistent_cohomology; - -typedef int Vertex_handle; -typedef double Filtration_value; +// Types definition +using Simplex_tree = Gudhi::Simplex_tree<>; +using Filtration_value = Simplex_tree::Filtration_value; +using Rips_complex = Gudhi::rips_complex::Rips_complex<Filtration_value>; +using Field_Zp = Gudhi::persistent_cohomology::Field_Zp; +using Point = std::vector<double>; +using Points_off_reader = Gudhi::Points_off_reader<Point>; void program_options(int argc, char * argv[] - , std::string & filepoints + , std::string & off_file_points , std::string & filediag , Filtration_value & threshold , int & dim_max @@ -59,30 +60,21 @@ void program_options(int argc, char * argv[] , Filtration_value & min_persistence); int main(int argc, char * argv[]) { - std::string filepoints; + std::string off_file_points; std::string filediag; Filtration_value threshold; int dim_max; int p; Filtration_value min_persistence; - program_options(argc, argv, filepoints, filediag, threshold, dim_max, p, min_persistence); - - // Extract the points from the file filepoints - typedef std::vector<double> Point_t; - std::vector< Point_t > points; - read_points(filepoints, points); + program_options(argc, argv, off_file_points, filediag, threshold, dim_max, p, min_persistence); - // Compute the proximity graph of the points - Graph_t prox_graph = compute_proximity_graph(points, threshold - , euclidean_distance<Point_t>); + Points_off_reader off_reader(off_file_points); + Rips_complex rips_complex_from_file(off_reader.get_point_cloud(), threshold, Euclidean_distance()); // Construct the Rips complex in a Simplex Tree - Simplex_tree<>& st = *new Simplex_tree<>; - // insert the proximity graph in the simplex tree - st.insert_graph(prox_graph); - // expand the graph until dimension dim_max - st.expansion(dim_max); + Simplex_tree& st = *new Simplex_tree; + rips_complex_from_file.create_complex(st, dim_max); std::cout << "The complex contains " << st.num_simplices() << " simplices \n"; std::cout << " and has dimension " << st.dimension() << " \n"; @@ -99,7 +91,7 @@ int main(int argc, char * argv[]) { st.assign_key(sh, count++); // Convert to a more convenient representation. - Hasse_complex<> hcpx(st); + Gudhi::Hasse_complex<> hcpx(st); #ifdef GUDHI_USE_TBB ts.terminate(); @@ -109,7 +101,7 @@ int main(int argc, char * argv[]) { delete &st; // Compute the persistence diagram of the complex - persistent_cohomology::Persistent_cohomology< Hasse_complex<>, Field_Zp > pcoh(hcpx); + Gudhi::persistent_cohomology::Persistent_cohomology< Gudhi::Hasse_complex<>, Field_Zp > pcoh(hcpx); // initializes the coefficient field for homology pcoh.init_coefficients(p); @@ -126,7 +118,7 @@ int main(int argc, char * argv[]) { } void program_options(int argc, char * argv[] - , std::string & filepoints + , std::string & off_file_points , std::string & filediag , Filtration_value & threshold , int & dim_max @@ -135,7 +127,7 @@ void program_options(int argc, char * argv[] namespace po = boost::program_options; po::options_description hidden("Hidden options"); hidden.add_options() - ("input-file", po::value<std::string>(&filepoints), + ("input-file", po::value<std::string>(&off_file_points), "Name of file containing a point set. Format is one point per line: X1 ... Xd "); po::options_description visible("Allowed options", 100); diff --git a/src/Persistent_cohomology/include/gudhi/Persistent_cohomology.h b/src/Persistent_cohomology/include/gudhi/Persistent_cohomology.h index 8e7901cc..672fda48 100644 --- a/src/Persistent_cohomology/include/gudhi/Persistent_cohomology.h +++ b/src/Persistent_cohomology/include/gudhi/Persistent_cohomology.h @@ -300,8 +300,7 @@ class Persistent_cohomology { // with multiplicity. We used to sum the coefficients directly in // annotations_in_boundary by using a map, we now do it later. typedef std::pair<Column *, int> annotation_t; - // Danger: not thread-safe! - static std::vector<annotation_t> annotations_in_boundary; + thread_local std::vector<annotation_t> annotations_in_boundary; annotations_in_boundary.clear(); int sign = 1 - 2 * (dim_sigma % 2); // \in {-1,1} provides the sign in the // alternate sum in the boundary. diff --git a/src/Persistent_cohomology/test/persistent_cohomology_unit_test_multi_field.cpp b/src/Persistent_cohomology/test/persistent_cohomology_unit_test_multi_field.cpp index 703682e1..1a6e3296 100644 --- a/src/Persistent_cohomology/test/persistent_cohomology_unit_test_multi_field.cpp +++ b/src/Persistent_cohomology/test/persistent_cohomology_unit_test_multi_field.cpp @@ -21,7 +21,7 @@ using namespace boost::unit_test; typedef Simplex_tree<> typeST; -std::string test_rips_persistence(int min_coefficient, int max_coefficient, int min_persistence) { +std::string test_rips_persistence(int min_coefficient, int max_coefficient, double min_persistence) { // file name is given as parameter from CMakeLists.txt const std::string inputFile(framework::master_test_suite().argv[1]); @@ -74,7 +74,7 @@ void test_rips_persistence_in_dimension(int min_dimension, int max_dimension) { std::cout << "********************************************************************" << std::endl; std::cout << "TEST OF RIPS_PERSISTENT_COHOMOLOGY_MULTI_FIELD MIN_DIM=" << min_dimension << " MAX_DIM=" << max_dimension << " MIN_PERS=0" << std::endl; - std::string str_rips_persistence = test_rips_persistence(min_dimension, max_dimension, static_cast<Filtration_value> (0.0)); + std::string str_rips_persistence = test_rips_persistence(min_dimension, max_dimension, 0.0); std::cout << "str_rips_persistence=" << str_rips_persistence << std::endl; BOOST_CHECK(str_rips_persistence.find(value0) != std::string::npos); // Check found diff --git a/src/Rips_complex/concept/Simplicial_complex_for_rips.h b/src/Rips_complex/concept/Simplicial_complex_for_rips.h new file mode 100644 index 00000000..dc871177 --- /dev/null +++ b/src/Rips_complex/concept/Simplicial_complex_for_rips.h @@ -0,0 +1,55 @@ +/* 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): Vincent Rouvreau + * + * Copyright (C) 2016 INRIA + * + * 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/>. + */ + +#ifndef CONCEPT_RIPS_COMPLEX_SIMPLICIAL_COMPLEX_FOR_RIPS_H_ +#define CONCEPT_RIPS_COMPLEX_SIMPLICIAL_COMPLEX_FOR_RIPS_H_ + +namespace Gudhi { + +namespace rips_complex { + +/** \brief The concept SimplicialComplexForRips describes the requirements for a type to implement a simplicial + * complex, that can be created from a `Rips_complex`. The only available model for the moment is the `Simplex_tree`. + */ +struct SimplicialComplexForRips { + /** \brief Handle to specify the simplex filtration value. */ + typedef unspecified Filtration_value; + + /** \brief Inserts a given range `Gudhi::rips_complex::Rips_complex::OneSkeletonGraph` in the simplicial + * complex. */ + template<class OneSkeletonGraph> + void insert_graph(const OneSkeletonGraph& skel_graph); + + /** \brief Expands the simplicial complex containing only its one skeleton until a given maximal dimension as + * explained in \ref ripsdefinition. */ + void expansion(int max_dim); + + /** \brief Returns the number of vertices in the simplicial complex. */ + std::size_t num_vertices(); + +}; + +} // namespace rips_complex + +} // namespace Gudhi + +#endif // CONCEPT_RIPS_COMPLEX_SIMPLICIAL_COMPLEX_FOR_RIPS_H_ diff --git a/src/Rips_complex/doc/Intro_rips_complex.h b/src/Rips_complex/doc/Intro_rips_complex.h new file mode 100644 index 00000000..64fd34bc --- /dev/null +++ b/src/Rips_complex/doc/Intro_rips_complex.h @@ -0,0 +1,152 @@ +/* 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): Clément Maria, Pawel Dlotko, Vincent Rouvreau + * + * Copyright (C) 2016 INRIA + * + * 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/>. + */ + +#ifndef DOC_RIPS_COMPLEX_INTRO_RIPS_COMPLEX_H_ +#define DOC_RIPS_COMPLEX_INTRO_RIPS_COMPLEX_H_ + +namespace Gudhi { + +namespace rips_complex { + +/** \defgroup rips_complex Rips complex + * + * \author Clément Maria, Pawel Dlotko, Vincent Rouvreau + * + * @{ + * + * \section ripsdefinition Rips complex definition + * + * Rips_complex + * <a target="_blank" href="https://en.wikipedia.org/wiki/Vietoris%E2%80%93Rips_complex">(Wikipedia)</a> is a + * one skeleton graph that allows to construct a + * <a target="_blank" href="https://en.wikipedia.org/wiki/Simplicial_complex">simplicial complex</a> + * from it. + * The input can be a point cloud with a given distance function, or a distance matrix. + * + * The filtration value of each edge is computed from a user-given distance function, or directly from the distance + * matrix. + * + * All edges that have a filtration value strictly greater than a given threshold value are not inserted into + * the complex. + * + * When creating a simplicial complex from this one skeleton graph, rips inserts the one skeleton graph into the data + * structure, and then expands the simplicial when required. + * + * \image html "rips_complex_representation.png" "Rips-complex one skeleton graph representation" + * + * On this example, as edges (4,5), (4,6) and (5,6) are in the complex, simplex (4,5,6) is added with the filtration + * value set with \f$max(filtration(4,5), filtration(4,6), filtration(5,6))\f$. + * And so on for simplex (0,1,2,3). + * + * \section ripspointsdistance Point cloud and distance function + * + * \subsection ripspointscloudexample Example from a point cloud and a distance function + * + * This example builds the one skeleton graph from the given points, threshold value, and distance function. + * Then it creates a `Simplex_tree` with it. + * + * Then, it is asked to display information about the simplicial complex. + * + * \include Rips_complex/example_one_skeleton_rips_from_points.cpp + * + * When launching (rips maximal distance between 2 points is 12.0, is expanded until dimension 1 - one skeleton graph + * in other words): + * + * \code $> ./oneskeletonripspoints + * \endcode + * + * the program output is: + * + * \include Rips_complex/one_skeleton_rips_for_doc.txt + * + * \subsection ripsoffexample Example from OFF file + * + * This example builds the Rips_complex from the given points in an OFF file, threshold value, and distance + * function. + * Then it creates a `Simplex_tree` with it. + * + * + * Then, it is asked to display information about the rips complex. + * + * \include Rips_complex/example_rips_complex_from_off_file.cpp + * + * When launching: + * + * \code $> ./ripsoffreader ../../data/points/alphacomplexdoc.off 12.0 3 + * \endcode + * + * the program output is: + * + * \include Rips_complex/full_skeleton_rips_for_doc.txt + * + * + * + * \section ripsdistancematrix Distance matrix + * + * \subsection ripsdistancematrixexample Example from a distance matrix + * + * This example builds the one skeleton graph from the given distance matrix and threshold value. + * Then it creates a `Simplex_tree` with it. + * + * Then, it is asked to display information about the simplicial complex. + * + * \include Rips_complex/example_one_skeleton_rips_from_distance_matrix.cpp + * + * When launching (rips maximal distance between 2 points is 1.0, is expanded until dimension 1 - one skeleton graph + * with other words): + * + * \code $> ./oneskeletonripsdistance + * \endcode + * + * the program output is: + * + * \include Rips_complex/one_skeleton_rips_for_doc.txt + * + * \subsection ripscsvdistanceexample Example from a distance matrix read in a csv file + * + * This example builds the one skeleton graph from the given distance matrix read in a csv file and threshold value. + * Then it creates a `Simplex_tree` with it. + * + * + * Then, it is asked to display information about the rips complex. + * + * \include Rips_complex/example_rips_complex_from_csv_distance_matrix_file.cpp + * + * When launching: + * + * \code $> ./ripscsvdistancereader ../../data/distance_matrix/full_square_distance_matrix.csv 1.0 3 + * \endcode + * + * the program output is: + * + * \include Rips_complex/full_skeleton_rips_for_doc.txt + * + * \copyright GNU General Public License v3. + * \verbatim Contact: gudhi-users@lists.gforge.inria.fr \endverbatim + */ +/** @} */ // end defgroup rips_complex + +} // namespace rips_complex + +} // namespace Gudhi + +#endif // DOC_RIPS_COMPLEX_INTRO_RIPS_COMPLEX_H_ diff --git a/src/Rips_complex/doc/rips_complex_representation.ipe b/src/Rips_complex/doc/rips_complex_representation.ipe new file mode 100644 index 00000000..7f6028f4 --- /dev/null +++ b/src/Rips_complex/doc/rips_complex_representation.ipe @@ -0,0 +1,326 @@ +<?xml version="1.0"?> +<!DOCTYPE ipe SYSTEM "ipe.dtd"> +<ipe version="70107" creator="Ipe 7.1.10"> +<info created="D:20150603143945" 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ripsoffreader example_rips_complex_from_off_file.cpp ) +target_link_libraries(ripsoffreader ${Boost_SYSTEM_LIBRARY}) + +add_executable ( oneskeletonripspoints example_one_skeleton_rips_from_points.cpp ) +target_link_libraries(oneskeletonripspoints ${Boost_SYSTEM_LIBRARY}) + +# Distance matrix +add_executable ( oneskeletonripsdistance example_one_skeleton_rips_from_distance_matrix.cpp ) +target_link_libraries(oneskeletonripsdistance ${Boost_SYSTEM_LIBRARY}) + +add_executable ( ripscsvdistancereader example_rips_complex_from_csv_distance_matrix_file.cpp ) +target_link_libraries(ripscsvdistancereader ${Boost_SYSTEM_LIBRARY}) + +if (TBB_FOUND) + target_link_libraries(ripsoffreader ${TBB_LIBRARIES}) + target_link_libraries(oneskeletonripspoints ${TBB_LIBRARIES}) + target_link_libraries(oneskeletonripsdistance ${TBB_LIBRARIES}) + target_link_libraries(ripscsvdistancereader ${TBB_LIBRARIES}) +endif() + +add_test(oneskeletonripspoints ${CMAKE_CURRENT_BINARY_DIR}/oneskeletonripspoints) +add_test(oneskeletonripsdistance ${CMAKE_CURRENT_BINARY_DIR}/oneskeletonripsdistance) + +# Do not forget to copy test files in current binary dir +file(COPY "${CMAKE_SOURCE_DIR}/data/points/alphacomplexdoc.off" DESTINATION ${CMAKE_CURRENT_BINARY_DIR}/) +add_test(ripsoffreader_doc_12_1 ${CMAKE_CURRENT_BINARY_DIR}/ripsoffreader alphacomplexdoc.off 12.0 1 ${CMAKE_CURRENT_BINARY_DIR}/ripsoffreader_result_12_1.txt) +add_test(ripsoffreader_doc_12_3 ${CMAKE_CURRENT_BINARY_DIR}/ripsoffreader alphacomplexdoc.off 12.0 3 ${CMAKE_CURRENT_BINARY_DIR}/ripsoffreader_result_12_3.txt) + +file(COPY "${CMAKE_SOURCE_DIR}/data/distance_matrix/full_square_distance_matrix.csv" DESTINATION ${CMAKE_CURRENT_BINARY_DIR}/) +add_test(ripscsvdistancereader_doc_12_1 ${CMAKE_CURRENT_BINARY_DIR}/ripscsvdistancereader full_square_distance_matrix.csv 12.0 1 ${CMAKE_CURRENT_BINARY_DIR}/ripscsvreader_result_12_1.txt) +add_test(ripscsvdistancereader_doc_12_3 ${CMAKE_CURRENT_BINARY_DIR}/ripscsvdistancereader full_square_distance_matrix.csv 12.0 3 ${CMAKE_CURRENT_BINARY_DIR}/ripscsvreader_result_12_3.txt) + + +if (DIFF_PATH) + # Do not forget to copy test results files in current binary dir + file(COPY "one_skeleton_rips_for_doc.txt" DESTINATION ${CMAKE_CURRENT_BINARY_DIR}/) + file(COPY "full_skeleton_rips_for_doc.txt" DESTINATION ${CMAKE_CURRENT_BINARY_DIR}/) + + add_test(ripsoffreader_doc_12_1_diff_files ${DIFF_PATH} ${CMAKE_CURRENT_BINARY_DIR}/ripsoffreader_result_12_1.txt ${CMAKE_CURRENT_BINARY_DIR}/one_skeleton_rips_for_doc.txt) + add_test(ripsoffreader_doc_12_3_diff_files ${DIFF_PATH} ${CMAKE_CURRENT_BINARY_DIR}/ripsoffreader_result_12_3.txt ${CMAKE_CURRENT_BINARY_DIR}/full_skeleton_rips_for_doc.txt) + add_test(ripscsvreader_doc_12_1_diff_files ${DIFF_PATH} ${CMAKE_CURRENT_BINARY_DIR}/ripscsvreader_result_12_1.txt ${CMAKE_CURRENT_BINARY_DIR}/one_skeleton_rips_for_doc.txt) + add_test(ripscsvreader_doc_12_3_diff_files ${DIFF_PATH} ${CMAKE_CURRENT_BINARY_DIR}/ripscsvreader_result_12_3.txt ${CMAKE_CURRENT_BINARY_DIR}/full_skeleton_rips_for_doc.txt) +endif() diff --git a/src/Rips_complex/example/example_one_skeleton_rips_from_distance_matrix.cpp b/src/Rips_complex/example/example_one_skeleton_rips_from_distance_matrix.cpp new file mode 100644 index 00000000..90bd8e38 --- /dev/null +++ b/src/Rips_complex/example/example_one_skeleton_rips_from_distance_matrix.cpp @@ -0,0 +1,58 @@ +#include <gudhi/Rips_complex.h> +#include <gudhi/Simplex_tree.h> +#include <gudhi/distance_functions.h> + +#include <iostream> +#include <string> +#include <vector> +#include <limits> // for std::numeric_limits + +int main() { + // Type definitions + using Simplex_tree = Gudhi::Simplex_tree<>; + using Filtration_value = Simplex_tree::Filtration_value; + using Rips_complex = Gudhi::rips_complex::Rips_complex<Filtration_value>; + using Distance_matrix = std::vector<std::vector<Filtration_value>>; + + // User defined distance matrix is: + // | 0 0.94 0.77 0.99 0.11 | + // | 0.94 0 0.26 0.99 0.39 | + // | 0.77 0.26 0 0.28 0.97 | + // | 0.99 0.99 0.28 0 0.30 | + // | 0.11 0.39 0.97 0.30 0 | + + Distance_matrix distances; + distances.push_back({}); + distances.push_back({0.94}); + distances.push_back({0.77, 0.26}); + distances.push_back({0.99, 0.99, 0.28}); + distances.push_back({0.11, 0.39, 0.97, 0.30}); + + // ---------------------------------------------------------------------------- + // Init of a rips complex from points + // ---------------------------------------------------------------------------- + double threshold = 1.0; + Rips_complex rips_complex_from_points(distances, threshold); + + Simplex_tree stree; + rips_complex_from_points.create_complex(stree, 1); + // ---------------------------------------------------------------------------- + // Display information about the one skeleton rips complex + // ---------------------------------------------------------------------------- + std::cout << "Rips complex is of dimension " << stree.dimension() << + " - " << stree.num_simplices() << " simplices - " << + stree.num_vertices() << " vertices." << std::endl; + + std::cout << "Iterator on rips complex simplices in the filtration order, with [filtration value]:" << + std::endl; + for (auto f_simplex : stree.filtration_simplex_range()) { + std::cout << " ( "; + for (auto vertex : stree.simplex_vertex_range(f_simplex)) { + std::cout << vertex << " "; + } + std::cout << ") -> " << "[" << stree.filtration(f_simplex) << "] "; + std::cout << std::endl; + } + + return 0; +} diff --git a/src/Rips_complex/example/example_one_skeleton_rips_from_points.cpp b/src/Rips_complex/example/example_one_skeleton_rips_from_points.cpp new file mode 100644 index 00000000..5d1216a0 --- /dev/null +++ b/src/Rips_complex/example/example_one_skeleton_rips_from_points.cpp @@ -0,0 +1,52 @@ +#include <gudhi/Rips_complex.h> +#include <gudhi/Simplex_tree.h> +#include <gudhi/distance_functions.h> + +#include <iostream> +#include <string> +#include <vector> +#include <limits> // for std::numeric_limits + +int main() { + // Type definitions + using Point = std::vector<double>; + using Simplex_tree = Gudhi::Simplex_tree<Gudhi::Simplex_tree_options_fast_persistence>; + using Filtration_value = Simplex_tree::Filtration_value; + using Rips_complex = Gudhi::rips_complex::Rips_complex<Filtration_value>; + + std::vector<Point> points; + points.push_back({1.0, 1.0}); + points.push_back({7.0, 0.0}); + points.push_back({4.0, 6.0}); + points.push_back({9.0, 6.0}); + points.push_back({0.0, 14.0}); + points.push_back({2.0, 19.0}); + points.push_back({9.0, 17.0}); + + // ---------------------------------------------------------------------------- + // Init of a rips complex from points + // ---------------------------------------------------------------------------- + double threshold = 12.0; + Rips_complex rips_complex_from_points(points, threshold, Euclidean_distance()); + + Simplex_tree stree; + rips_complex_from_points.create_complex(stree, 1); + // ---------------------------------------------------------------------------- + // Display information about the one skeleton rips complex + // ---------------------------------------------------------------------------- + std::cout << "Rips complex is of dimension " << stree.dimension() << + " - " << stree.num_simplices() << " simplices - " << + stree.num_vertices() << " vertices." << std::endl; + + std::cout << "Iterator on rips complex simplices in the filtration order, with [filtration value]:" << + std::endl; + for (auto f_simplex : stree.filtration_simplex_range()) { + std::cout << " ( "; + for (auto vertex : stree.simplex_vertex_range(f_simplex)) { + std::cout << vertex << " "; + } + std::cout << ") -> " << "[" << stree.filtration(f_simplex) << "] "; + std::cout << std::endl; + } + return 0; +} diff --git a/src/Rips_complex/example/example_rips_complex_from_csv_distance_matrix_file.cpp b/src/Rips_complex/example/example_rips_complex_from_csv_distance_matrix_file.cpp new file mode 100644 index 00000000..cc6c3a33 --- /dev/null +++ b/src/Rips_complex/example/example_rips_complex_from_csv_distance_matrix_file.cpp @@ -0,0 +1,72 @@ +#include <gudhi/Rips_complex.h> +// to construct Rips_complex from a OFF file of points +#include <gudhi/reader_utils.h> +#include <gudhi/Simplex_tree.h> +#include <gudhi/distance_functions.h> + +#include <iostream> +#include <string> +#include <vector> + +void usage(int nbArgs, char * const progName) { + std::cerr << "Error: Number of arguments (" << nbArgs << ") is not correct\n"; + std::cerr << "Usage: " << progName << " filename.csv threshold dim_max [ouput_file.txt]\n"; + std::cerr << " i.e.: " << progName << " ../../data/distance_matrix/full_square_distance_matrix.csv 1.0 3\n"; + exit(-1); // ----- >> +} + +int main(int argc, char **argv) { + if ((argc != 4) && (argc != 5)) usage(argc, (argv[0] - 1)); + + std::string csv_file_name(argv[1]); + double threshold = atof(argv[2]); + int dim_max = atoi(argv[3]); + + // Type definitions + using Simplex_tree = Gudhi::Simplex_tree<>; + using Filtration_value = Simplex_tree::Filtration_value; + using Rips_complex = Gudhi::rips_complex::Rips_complex<Filtration_value>; + using Distance_matrix = std::vector<std::vector<Filtration_value>>; + + // ---------------------------------------------------------------------------- + // Init of a rips complex from a distance matrix in a csv file + // Default separator is ';' + // ---------------------------------------------------------------------------- + Distance_matrix distances = read_lower_triangular_matrix_from_csv_file<Filtration_value>(csv_file_name); + Rips_complex rips_complex_from_file(distances, threshold); + + std::streambuf* streambufffer; + std::ofstream ouput_file_stream; + + if (argc == 5) { + ouput_file_stream.open(std::string(argv[4])); + streambufffer = ouput_file_stream.rdbuf(); + } else { + streambufffer = std::cout.rdbuf(); + } + + Simplex_tree stree; + rips_complex_from_file.create_complex(stree, dim_max); + std::ostream output_stream(streambufffer); + + // ---------------------------------------------------------------------------- + // Display information about the rips complex + // ---------------------------------------------------------------------------- + output_stream << "Rips complex is of dimension " << stree.dimension() << + " - " << stree.num_simplices() << " simplices - " << + stree.num_vertices() << " vertices." << std::endl; + + output_stream << "Iterator on rips complex simplices in the filtration order, with [filtration value]:" << + std::endl; + for (auto f_simplex : stree.filtration_simplex_range()) { + output_stream << " ( "; + for (auto vertex : stree.simplex_vertex_range(f_simplex)) { + output_stream << vertex << " "; + } + output_stream << ") -> " << "[" << stree.filtration(f_simplex) << "] "; + output_stream << std::endl; + } + + ouput_file_stream.close(); + return 0; +} diff --git a/src/Rips_complex/example/example_rips_complex_from_off_file.cpp b/src/Rips_complex/example/example_rips_complex_from_off_file.cpp new file mode 100644 index 00000000..b6c961d0 --- /dev/null +++ b/src/Rips_complex/example/example_rips_complex_from_off_file.cpp @@ -0,0 +1,71 @@ +#include <gudhi/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 <iostream> +#include <string> +#include <vector> + +void usage(int nbArgs, char * const progName) { + std::cerr << "Error: Number of arguments (" << nbArgs << ") is not correct\n"; + std::cerr << "Usage: " << progName << " filename.off threshold dim_max [ouput_file.txt]\n"; + std::cerr << " i.e.: " << progName << " ../../data/points/alphacomplexdoc.off 60.0\n"; + exit(-1); // ----- >> +} + +int main(int argc, char **argv) { + if ((argc != 4) && (argc != 5)) usage(argc, (argv[0] - 1)); + + std::string off_file_name(argv[1]); + double threshold = atof(argv[2]); + int dim_max = atoi(argv[3]); + + // Type definitions + using Point = std::vector<float>; + using Simplex_tree = Gudhi::Simplex_tree<>; + using Filtration_value = Simplex_tree::Filtration_value; + using Rips_complex = Gudhi::rips_complex::Rips_complex<Filtration_value>; + + // ---------------------------------------------------------------------------- + // Init of a rips complex from an OFF file + // ---------------------------------------------------------------------------- + Gudhi::Points_off_reader<Point> off_reader(off_file_name); + Rips_complex rips_complex_from_file(off_reader.get_point_cloud(), threshold, Euclidean_distance()); + + std::streambuf* streambufffer; + std::ofstream ouput_file_stream; + + if (argc == 5) { + ouput_file_stream.open(std::string(argv[4])); + streambufffer = ouput_file_stream.rdbuf(); + } else { + streambufffer = std::cout.rdbuf(); + } + + Simplex_tree stree; + rips_complex_from_file.create_complex(stree, dim_max); + std::ostream output_stream(streambufffer); + + // ---------------------------------------------------------------------------- + // Display information about the rips complex + // ---------------------------------------------------------------------------- + output_stream << "Rips complex is of dimension " << stree.dimension() << + " - " << stree.num_simplices() << " simplices - " << + stree.num_vertices() << " vertices." << std::endl; + + output_stream << "Iterator on rips complex simplices in the filtration order, with [filtration value]:" << + std::endl; + for (auto f_simplex : stree.filtration_simplex_range()) { + output_stream << " ( "; + for (auto vertex : stree.simplex_vertex_range(f_simplex)) { + output_stream << vertex << " "; + } + output_stream << ") -> " << "[" << stree.filtration(f_simplex) << "] "; + output_stream << std::endl; + } + + ouput_file_stream.close(); + return 0; +} diff --git a/src/Rips_complex/example/full_skeleton_rips_for_doc.txt b/src/Rips_complex/example/full_skeleton_rips_for_doc.txt new file mode 100644 index 00000000..319931e0 --- /dev/null +++ b/src/Rips_complex/example/full_skeleton_rips_for_doc.txt @@ -0,0 +1,26 @@ +Rips complex is of dimension 3 - 24 simplices - 7 vertices. +Iterator on rips complex simplices in the filtration order, with [filtration value]: + ( 0 ) -> [0] + ( 1 ) -> [0] + ( 2 ) -> [0] + ( 3 ) -> [0] + ( 4 ) -> [0] + ( 5 ) -> [0] + ( 6 ) -> [0] + ( 3 2 ) -> [5] + ( 5 4 ) -> [5.38516] + ( 2 0 ) -> [5.83095] + ( 1 0 ) -> [6.08276] + ( 3 1 ) -> [6.32456] + ( 2 1 ) -> [6.7082] + ( 2 1 0 ) -> [6.7082] + ( 3 2 1 ) -> [6.7082] + ( 6 5 ) -> [7.28011] + ( 4 2 ) -> [8.94427] + ( 3 0 ) -> [9.43398] + ( 3 1 0 ) -> [9.43398] + ( 3 2 0 ) -> [9.43398] + ( 3 2 1 0 ) -> [9.43398] + ( 6 4 ) -> [9.48683] + ( 6 5 4 ) -> [9.48683] + ( 6 3 ) -> [11] diff --git a/src/Rips_complex/example/one_skeleton_rips_for_doc.txt b/src/Rips_complex/example/one_skeleton_rips_for_doc.txt new file mode 100644 index 00000000..b0e25cc5 --- /dev/null +++ b/src/Rips_complex/example/one_skeleton_rips_for_doc.txt @@ -0,0 +1,20 @@ +Rips complex is of dimension 1 - 18 simplices - 7 vertices. +Iterator on rips complex simplices in the filtration order, with [filtration value]: + ( 0 ) -> [0] + ( 1 ) -> [0] + ( 2 ) -> [0] + ( 3 ) -> [0] + ( 4 ) -> [0] + ( 5 ) -> [0] + ( 6 ) -> [0] + ( 3 2 ) -> [5] + ( 5 4 ) -> [5.38516] + ( 2 0 ) -> [5.83095] + ( 1 0 ) -> [6.08276] + ( 3 1 ) -> [6.32456] + ( 2 1 ) -> [6.7082] + ( 6 5 ) -> [7.28011] + ( 4 2 ) -> [8.94427] + ( 3 0 ) -> [9.43398] + ( 6 4 ) -> [9.48683] + ( 6 3 ) -> [11] diff --git a/src/Rips_complex/include/gudhi/Rips_complex.h b/src/Rips_complex/include/gudhi/Rips_complex.h new file mode 100644 index 00000000..f0f39db8 --- /dev/null +++ b/src/Rips_complex/include/gudhi/Rips_complex.h @@ -0,0 +1,186 @@ +/* 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): Clément Maria, Pawel Dlotko, Vincent Rouvreau + * + * Copyright (C) 2016 INRIA + * + * 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/>. + */ + +#ifndef RIPS_COMPLEX_H_ +#define RIPS_COMPLEX_H_ + +#include <gudhi/Debug_utils.h> +#include <gudhi/graph_simplicial_complex.h> + +#include <boost/graph/adjacency_list.hpp> + +#include <iostream> +#include <vector> +#include <map> +#include <string> +#include <limits> // for numeric_limits +#include <utility> // for pair<> + + +namespace Gudhi { + +namespace rips_complex { + +/** + * \class Rips_complex + * \brief Rips complex data structure. + * + * \ingroup rips_complex + * + * \details + * The data structure is a one skeleton graph, or Rips graph, containing edges when the edge length is less or equal + * to a given threshold. Edge length is computed from a user given point cloud with a given distance function, or a + * distance matrix. + * + * \tparam Filtration_value must meet `SimplicialComplexForRips` concept. + */ +template<typename Filtration_value> +class Rips_complex { + public: + /** + * \brief Type of the one skeleton graph stored inside the Rips complex structure. + */ + typedef typename boost::adjacency_list < boost::vecS, boost::vecS, boost::undirectedS + , boost::property < vertex_filtration_t, Filtration_value > + , boost::property < edge_filtration_t, Filtration_value >> OneSkeletonGraph; + + private: + typedef int Vertex_handle; + + public: + /** \brief Rips_complex constructor from a list of points. + * + * @param[in] points Range of points. + * @param[in] threshold rips value. + * @param[in] distance distance function that returns a `Filtration_value` from 2 given points. + * + * \tparam InputPointRange must be a range for which `std::begin` and `std::end` return input iterators on a + * point. + * + * \tparam Distance furnishes `operator()(const Point& p1, const Point& p2)`, where + * `Point` is a point from the `InputPointRange`, and that returns a `Filtration_value`. + */ + template<typename InputPointRange, typename Distance > + Rips_complex(const InputPointRange& points, Filtration_value threshold, Distance distance) { + compute_proximity_graph<InputPointRange, Distance >(points, threshold, distance); + } + + /** \brief Rips_complex constructor from a distance matrix. + * + * @param[in] distance_matrix Range of distances. + * @param[in] threshold rips value. + * + * \tparam InputDistanceRange must have a `size()` method and on which `distance_matrix[i][j]` returns + * the distance between points \f$i\f$ and \f$j\f$ as long as \f$ 0 \leqslant i \leqslant j \leqslant + * distance\_matrix.size().\f$ + */ + template<typename InputDistanceRange> + Rips_complex(const InputDistanceRange& distance_matrix, Filtration_value threshold) { + compute_proximity_graph(boost::irange((size_t)0, distance_matrix.size()), threshold, + [&](size_t i, size_t j){return distance_matrix[j][i];}); + } + + /** \brief Initializes the simplicial complex from the Rips graph and expands it until a given maximal + * dimension. + * + * \tparam SimplicialComplexForRips must meet `SimplicialComplexForRips` concept. + * + * @param[in] complex SimplicialComplexForRips to be created. + * @param[in] dim_max graph expansion for rips until this given maximal dimension. + * @exception std::invalid_argument In debug mode, if `complex.num_vertices()` does not return 0. + * + */ + template <typename SimplicialComplexForRips> + void create_complex(SimplicialComplexForRips& complex, int dim_max) { + GUDHI_CHECK(complex.num_vertices() == 0, + std::invalid_argument("Rips_complex::create_complex - simplicial complex is not empty")); + + // insert the proximity graph in the simplicial complex + complex.insert_graph(rips_skeleton_graph_); + // expand the graph until dimension dim_max + complex.expansion(dim_max); + } + + private: + /** \brief Computes the proximity graph of the points. + * + * If points contains n elements, the proximity graph is the graph with n vertices, and an edge [u,v] iff the + * distance function between points u and v is smaller than threshold. + * + * \tparam InputPointRange furnishes `.begin()` and `.end()` + * methods. + * + * \tparam Distance furnishes `operator()(const Point& p1, const Point& p2)`, where + * `Point` is a point from the `InputPointRange`, and that returns a `Filtration_value`. + */ + template< typename InputPointRange, typename Distance > + void compute_proximity_graph(const InputPointRange& points, Filtration_value threshold, + Distance distance) { + std::vector< std::pair< Vertex_handle, Vertex_handle > > edges; + std::vector< Filtration_value > edges_fil; + + // Compute the proximity graph of the points. + // If points contains n elements, the proximity graph is the graph with n vertices, and an edge [u,v] iff the + // distance function between points u and v is smaller than threshold. + // -------------------------------------------------------------------------------------------- + // Creates the vector of edges and its filtration values (returned by distance function) + Vertex_handle idx_u = 0; + for (auto it_u = std::begin(points); it_u != std::end(points); ++it_u) { + Vertex_handle idx_v = idx_u + 1; + for (auto it_v = it_u + 1; it_v != std::end(points); ++it_v, ++idx_v) { + Filtration_value fil = distance(*it_u, *it_v); + if (fil <= threshold) { + edges.emplace_back(idx_u, idx_v); + edges_fil.push_back(fil); + } + } + ++idx_u; + } + + // -------------------------------------------------------------------------------------------- + // Creates the proximity graph from edges and sets the property with the filtration value. + // Number of points is labeled from 0 to idx_u-1 + // -------------------------------------------------------------------------------------------- + // Do not use : rips_skeleton_graph_ = OneSkeletonGraph(...) -> deep copy of the graph (boost graph is not + // move-enabled) + rips_skeleton_graph_.~OneSkeletonGraph(); + new(&rips_skeleton_graph_)OneSkeletonGraph(edges.begin(), edges.end(), edges_fil.begin(), idx_u); + + auto vertex_prop = boost::get(vertex_filtration_t(), rips_skeleton_graph_); + + using vertex_iterator = typename boost::graph_traits<OneSkeletonGraph>::vertex_iterator; + vertex_iterator vi, vi_end; + for (std::tie(vi, vi_end) = boost::vertices(rips_skeleton_graph_); + vi != vi_end; ++vi) { + boost::put(vertex_prop, *vi, 0.); + } + } + + private: + OneSkeletonGraph rips_skeleton_graph_; +}; + +} // namespace rips_complex + +} // namespace Gudhi + +#endif // RIPS_COMPLEX_H_ diff --git a/src/Rips_complex/test/CMakeLists.txt b/src/Rips_complex/test/CMakeLists.txt new file mode 100644 index 00000000..87bad2ed --- /dev/null +++ b/src/Rips_complex/test/CMakeLists.txt @@ -0,0 +1,25 @@ +cmake_minimum_required(VERSION 2.6) +project(Rips_complex_tests) + +if (GCOVR_PATH) + # for gcovr to make coverage reports - Corbera Jenkins plugin + set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -fprofile-arcs -ftest-coverage") +endif() +if (GPROF_PATH) + # for gprof to make coverage reports - Jenkins + set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -pg") +endif() + +add_executable ( rips_complex_UT test_rips_complex.cpp ) +target_link_libraries(rips_complex_UT ${Boost_SYSTEM_LIBRARY} ${Boost_UNIT_TEST_FRAMEWORK_LIBRARY}) +if (TBB_FOUND) + target_link_libraries(rips_complex_UT ${TBB_LIBRARIES}) +endif() + +# Do not forget to copy test files in current binary dir +file(COPY "${CMAKE_SOURCE_DIR}/data/points/alphacomplexdoc.off" DESTINATION ${CMAKE_CURRENT_BINARY_DIR}/) +file(COPY "${CMAKE_SOURCE_DIR}/data/distance_matrix/full_square_distance_matrix.csv" DESTINATION ${CMAKE_CURRENT_BINARY_DIR}/) + +add_test(rips_complex_UT ${CMAKE_CURRENT_BINARY_DIR}/rips_complex_UT + # XML format for Jenkins xUnit plugin + --log_format=XML --log_sink=${CMAKE_SOURCE_DIR}/rips_complex_UT.xml --log_level=test_suite --report_level=no) diff --git a/src/Rips_complex/test/README b/src/Rips_complex/test/README new file mode 100644 index 00000000..28236b52 --- /dev/null +++ b/src/Rips_complex/test/README @@ -0,0 +1,12 @@ +To compile: +*********** + +cmake . +make + +To launch with details: +*********************** + +./rips_complex_UT --report_level=detailed --log_level=all + + ==> echo $? returns 0 in case of success (non-zero otherwise) diff --git a/src/Rips_complex/test/test_rips_complex.cpp b/src/Rips_complex/test/test_rips_complex.cpp new file mode 100644 index 00000000..1bdd0512 --- /dev/null +++ b/src/Rips_complex/test/test_rips_complex.cpp @@ -0,0 +1,353 @@ +/* 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): Vincent Rouvreau + * + * Copyright (C) 2016 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 "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> +// 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> + +// 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 Distance_matrix = std::vector<std::vector<Filtration_value>>; + +bool are_almost_the_same(float a, float b) { + return std::fabs(a - b) < std::numeric_limits<float>::epsilon(); +} + +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, 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 =" << Euclidean_distance()(vp.at(0), vp.at(1)) << + " - filtration =" << st.filtration(f_simplex) << std::endl; + BOOST_CHECK(vp.size() == 2); + BOOST_CHECK(are_almost_the_same(st.filtration(f_simplex), 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; + BOOST_CHECK(are_almost_the_same(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; + BOOST_CHECK(are_almost_the_same(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; + BOOST_CHECK(are_almost_the_same(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: + BOOST_CHECK(are_almost_the_same(st.filtration(f_simplex), 0.0)); + break; + case 1: + case 2: + case 3: + BOOST_CHECK(are_almost_the_same(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 = 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); + BOOST_CHECK(are_almost_the_same(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; + BOOST_CHECK(are_almost_the_same(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; + BOOST_CHECK(are_almost_the_same(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; + BOOST_CHECK(are_almost_the_same(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, 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 diff --git a/src/Simplex_tree/example/simple_simplex_tree.cpp b/src/Simplex_tree/example/simple_simplex_tree.cpp index 5146b906..60f9a35e 100644 --- a/src/Simplex_tree/example/simple_simplex_tree.cpp +++ b/src/Simplex_tree/example/simple_simplex_tree.cpp @@ -4,7 +4,7 @@ * * Author(s): Vincent Rouvreau * - * Copyright (C) 2014 INRIA Sophia Antipolis-Méditerranée (France) + * Copyright (C) 2014 * * 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 @@ -27,10 +27,11 @@ #include <utility> // for pair #include <vector> -using namespace Gudhi; - -typedef std::vector< Vertex_handle > typeVectorVertex; -typedef std::pair< Simplex_tree<>::Simplex_handle, bool > typePairSimplexBool; +using Simplex_tree = Gudhi::Simplex_tree<>; +using Vertex_handle = Simplex_tree::Vertex_handle; +using Filtration_value = Simplex_tree::Filtration_value; +using typeVectorVertex = std::vector< Vertex_handle >; +using typePairSimplexBool = std::pair< Simplex_tree::Simplex_handle, bool >; int main(int argc, char * const argv[]) { const Filtration_value FIRST_FILTRATION_VALUE = 0.1; @@ -42,7 +43,7 @@ int main(int argc, char * const argv[]) { std::cout << "********************************************************************" << std::endl; std::cout << "EXAMPLE OF SIMPLE INSERTION" << std::endl; // Construct the Simplex Tree - Simplex_tree<> simplexTree; + Simplex_tree simplexTree; /* Simplex to be inserted: */ /* 1 */ @@ -212,7 +213,7 @@ int main(int argc, char * const argv[]) { // ------------------------------------------------------------------------------------------------------------------ // Find in the simplex_tree // ------------------------------------------------------------------------------------------------------------------ - Simplex_tree<>::Simplex_handle simplexFound = simplexTree.find(secondSimplexVector); + Simplex_tree::Simplex_handle simplexFound = simplexTree.find(secondSimplexVector); std::cout << "**************IS THE SIMPLEX {1} IN THE SIMPLEX TREE ?\n"; if (simplexFound != simplexTree.null_simplex()) std::cout << "***+ YES IT IS!\n"; diff --git a/src/Simplex_tree/example/simplex_tree_from_cliques_of_graph.cpp b/src/Simplex_tree/example/simplex_tree_from_cliques_of_graph.cpp index 58085014..d1b8b2de 100644 --- a/src/Simplex_tree/example/simplex_tree_from_cliques_of_graph.cpp +++ b/src/Simplex_tree/example/simplex_tree_from_cliques_of_graph.cpp @@ -4,7 +4,7 @@ * * Author(s): Clément Maria * - * Copyright (C) 2014 INRIA Sophia Antipolis-Méditerranée (France) + * Copyright (C) 2014 INRIA * * 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 @@ -26,9 +26,16 @@ #include <iostream> #include <ctime> #include <string> +#include <utility> // for std::pair using namespace Gudhi; +typedef int Vertex_handle; +typedef double Filtration_value; +typedef boost::adjacency_list < boost::vecS, boost::vecS, boost::undirectedS, + boost::property < vertex_filtration_t, Filtration_value >, + boost::property < edge_filtration_t, Filtration_value > > Graph_t; + int main(int argc, char * const argv[]) { if (argc != 3) { std::cerr << "Usage: " << argv[0] @@ -43,7 +50,7 @@ int main(int argc, char * const argv[]) { Simplex_tree<> st; start = clock(); - auto g = read_graph(filegraph); + auto g = read_graph<Graph_t, Filtration_value, Vertex_handle>(filegraph); // insert the graph in the simplex tree as 1-skeleton st.insert_graph(g); end = clock(); diff --git a/src/Simplex_tree/include/gudhi/Simplex_tree.h b/src/Simplex_tree/include/gudhi/Simplex_tree.h index 63e3f0e5..317bce23 100644 --- a/src/Simplex_tree/include/gudhi/Simplex_tree.h +++ b/src/Simplex_tree/include/gudhi/Simplex_tree.h @@ -1029,7 +1029,7 @@ class Simplex_tree { Dictionary_it next = siblings->members().begin(); ++next; - static std::vector<std::pair<Vertex_handle, Node> > inter; // static, not thread-safe. + thread_local std::vector<std::pair<Vertex_handle, Node> > inter; for (Dictionary_it s_h = siblings->members().begin(); s_h != siblings->members().end(); ++s_h, ++next) { Simplex_handle root_sh = find_vertex(s_h->first); diff --git a/src/Simplex_tree/test/simplex_tree_unit_test.cpp b/src/Simplex_tree/test/simplex_tree_unit_test.cpp index 28bf202b..b06d7ec9 100644 --- a/src/Simplex_tree/test/simplex_tree_unit_test.cpp +++ b/src/Simplex_tree/test/simplex_tree_unit_test.cpp @@ -1,4 +1,5 @@ #include <iostream> +#include <fstream> #include <string> #include <algorithm> #include <utility> // std::pair, std::make_pair @@ -19,19 +20,19 @@ using namespace Gudhi; typedef boost::mpl::list<Simplex_tree<>, Simplex_tree<Simplex_tree_options_fast_persistence>> list_of_tested_variants; -const Vertex_handle DEFAULT_VERTEX_HANDLE = (const Vertex_handle) - 1; -const Filtration_value DEFAULT_FILTRATION_VALUE = (const Filtration_value) 0.0; template<class typeST> void test_empty_simplex_tree(typeST& tst) { - BOOST_CHECK(tst.null_vertex() == DEFAULT_VERTEX_HANDLE); - BOOST_CHECK(tst.filtration() == DEFAULT_FILTRATION_VALUE); + typedef typename typeST::Vertex_handle Vertex_handle; + const Vertex_handle DEFAULT_VERTEX_VALUE = Vertex_handle(- 1); + BOOST_CHECK(tst.null_vertex() == DEFAULT_VERTEX_VALUE); + BOOST_CHECK(tst.filtration() == 0.0); BOOST_CHECK(tst.num_vertices() == (size_t) 0); BOOST_CHECK(tst.num_simplices() == (size_t) 0); typename typeST::Siblings* STRoot = tst.root(); BOOST_CHECK(STRoot != nullptr); BOOST_CHECK(STRoot->oncles() == nullptr); - BOOST_CHECK(STRoot->parent() == DEFAULT_VERTEX_HANDLE); + BOOST_CHECK(STRoot->parent() == DEFAULT_VERTEX_VALUE); BOOST_CHECK(tst.dimension() == -1); } @@ -59,7 +60,7 @@ void test_iterators_on_empty_simplex_tree(typeST& tst) { BOOST_AUTO_TEST_CASE_TEMPLATE(simplex_tree_when_empty, typeST, list_of_tested_variants) { typedef std::pair<typename typeST::Simplex_handle, bool> typePairSimplexBool; - typedef std::vector<Vertex_handle> typeVectorVertex; + typedef std::vector<typename typeST::Vertex_handle> typeVectorVertex; std::cout << "********************************************************************" << std::endl; std::cout << "TEST OF DEFAULT CONSTRUCTOR" << std::endl; @@ -72,8 +73,7 @@ BOOST_AUTO_TEST_CASE_TEMPLATE(simplex_tree_when_empty, typeST, list_of_tested_va std::cout << "TEST OF EMPTY INSERTION" << std::endl; typeVectorVertex simplexVectorEmpty; BOOST_CHECK(simplexVectorEmpty.empty() == true); - typePairSimplexBool returnEmptyValue = st.insert_simplex(simplexVectorEmpty, - DEFAULT_FILTRATION_VALUE); + typePairSimplexBool returnEmptyValue = st.insert_simplex(simplexVectorEmpty, 0.0); BOOST_CHECK(returnEmptyValue.first == typename typeST::Simplex_handle(nullptr)); BOOST_CHECK(returnEmptyValue.second == true); @@ -141,12 +141,13 @@ void test_simplex_tree_contains(typeST& simplexTree, typeSimplex& simplex, int p template<class typeST, class typePairSimplexBool> void test_simplex_tree_insert_returns_true(const typePairSimplexBool& returnValue) { BOOST_CHECK(returnValue.second == true); - typename typeST::Simplex_handle shReturned = returnValue.first; // Simplex_handle = boost::container::flat_map< Vertex_handle, Node >::iterator + // Simplex_handle = boost::container::flat_map< typeST::Vertex_handle, Node >::iterator + typename typeST::Simplex_handle shReturned = returnValue.first; BOOST_CHECK(shReturned != typename typeST::Simplex_handle(nullptr)); } // Global variables -Filtration_value max_fil = DEFAULT_FILTRATION_VALUE; +double max_fil = 0.0; int dim_max = -1; template<class typeST, class Filtration_value> @@ -179,8 +180,9 @@ void set_and_test_simplex_tree_dim_fil(typeST& simplexTree, int vectorSize, cons } BOOST_AUTO_TEST_CASE_TEMPLATE(simplex_tree_insertion, typeST, list_of_tested_variants) { + typedef typename typeST::Filtration_value Filtration_value; typedef std::pair<typename typeST::Simplex_handle, bool> typePairSimplexBool; - typedef std::vector<Vertex_handle> typeVectorVertex; + typedef std::vector<typename typeST::Vertex_handle> typeVectorVertex; typedef std::pair<typeVectorVertex, Filtration_value> typeSimplex; const Filtration_value FIRST_FILTRATION_VALUE = 0.1; const Filtration_value SECOND_FILTRATION_VALUE = 0.2; @@ -188,7 +190,7 @@ BOOST_AUTO_TEST_CASE_TEMPLATE(simplex_tree_insertion, typeST, list_of_tested_var const Filtration_value FOURTH_FILTRATION_VALUE = 0.4; // reset since we run the test several times dim_max = -1; - max_fil = DEFAULT_FILTRATION_VALUE; + max_fil = 0.0; // TEST OF INSERTION std::cout << "********************************************************************" << std::endl; @@ -303,7 +305,8 @@ BOOST_AUTO_TEST_CASE_TEMPLATE(simplex_tree_insertion, typeST, list_of_tested_var returnValue = st.insert_simplex(tenthSimplex.first, tenthSimplex.second); BOOST_CHECK(returnValue.second == false); - typename typeST::Simplex_handle shReturned = returnValue.first; // Simplex_handle = boost::container::flat_map< Vertex_handle, Node >::iterator + // Simplex_handle = boost::container::flat_map< typeST::Vertex_handle, Node >::iterator + typename typeST::Simplex_handle shReturned = returnValue.first; BOOST_CHECK(shReturned == typename typeST::Simplex_handle(nullptr)); BOOST_CHECK(st.num_vertices() == (size_t) 4); // Not incremented !! BOOST_CHECK(st.dimension() == dim_max); @@ -317,7 +320,8 @@ BOOST_AUTO_TEST_CASE_TEMPLATE(simplex_tree_insertion, typeST, list_of_tested_var returnValue = st.insert_simplex(eleventhSimplex.first, eleventhSimplex.second); BOOST_CHECK(returnValue.second == false); - shReturned = returnValue.first; // Simplex_handle = boost::container::flat_map< Vertex_handle, Node >::iterator + // Simplex_handle = boost::container::flat_map< typeST::Vertex_handle, Node >::iterator + shReturned = returnValue.first; BOOST_CHECK(shReturned == typename typeST::Simplex_handle(nullptr)); BOOST_CHECK(st.num_vertices() == (size_t) 4); // Not incremented !! BOOST_CHECK(st.dimension() == dim_max); @@ -375,8 +379,8 @@ BOOST_AUTO_TEST_CASE_TEMPLATE(simplex_tree_insertion, typeST, list_of_tested_var BOOST_AUTO_TEST_CASE_TEMPLATE(NSimplexAndSubfaces_tree_insertion, typeST, list_of_tested_variants) { typedef std::pair<typename typeST::Simplex_handle, bool> typePairSimplexBool; - typedef std::vector<Vertex_handle> typeVectorVertex; - typedef std::pair<typeVectorVertex, Filtration_value> typeSimplex; + typedef std::vector<typename typeST::Vertex_handle> typeVectorVertex; + typedef std::pair<typeVectorVertex, typename typeST::Filtration_value> typeSimplex; std::cout << "********************************************************************" << std::endl; std::cout << "TEST OF RECURSIVE INSERTION" << std::endl; typeST st; @@ -394,7 +398,7 @@ BOOST_AUTO_TEST_CASE_TEMPLATE(NSimplexAndSubfaces_tree_insertion, typeST, list_o // Check it is well inserted BOOST_CHECK(true == returnValue.second); position = 0; - std::sort(SimplexVector1.begin(), SimplexVector1.end(), std::greater<Vertex_handle>()); + std::sort(SimplexVector1.begin(), SimplexVector1.end(), std::greater<typename typeST::Vertex_handle>()); for (auto vertex : st.simplex_vertex_range(returnValue.first)) { // Check returned Simplex_handle std::cout << "vertex = " << vertex << " | vector[" << position << "] = " << SimplexVector1[position] << std::endl; @@ -413,7 +417,7 @@ BOOST_AUTO_TEST_CASE_TEMPLATE(NSimplexAndSubfaces_tree_insertion, typeST, list_o // Check it is well inserted BOOST_CHECK(true == returnValue.second); position = 0; - std::sort(SimplexVector2.begin(), SimplexVector2.end(), std::greater<Vertex_handle>()); + std::sort(SimplexVector2.begin(), SimplexVector2.end(), std::greater<typename typeST::Vertex_handle>()); for (auto vertex : st.simplex_vertex_range(returnValue.first)) { // Check returned Simplex_handle std::cout << "vertex = " << vertex << " | vector[" << position << "] = " << SimplexVector2[position] << std::endl; @@ -432,7 +436,7 @@ BOOST_AUTO_TEST_CASE_TEMPLATE(NSimplexAndSubfaces_tree_insertion, typeST, list_o // Check it is well inserted BOOST_CHECK(true == returnValue.second); position = 0; - std::sort(SimplexVector3.begin(), SimplexVector3.end(), std::greater<Vertex_handle>()); + std::sort(SimplexVector3.begin(), SimplexVector3.end(), std::greater<typename typeST::Vertex_handle>()); for (auto vertex : st.simplex_vertex_range(returnValue.first)) { // Check returned Simplex_handle std::cout << "vertex = " << vertex << " | vector[" << position << "] = " << SimplexVector3[position] << std::endl; @@ -462,7 +466,7 @@ BOOST_AUTO_TEST_CASE_TEMPLATE(NSimplexAndSubfaces_tree_insertion, typeST, list_o // Check it is well inserted BOOST_CHECK(true == returnValue.second); position = 0; - std::sort(SimplexVector5.begin(), SimplexVector5.end(), std::greater<Vertex_handle>()); + std::sort(SimplexVector5.begin(), SimplexVector5.end(), std::greater<typename typeST::Vertex_handle>()); for (auto vertex : st.simplex_vertex_range(returnValue.first)) { // Check returned Simplex_handle std::cout << "vertex = " << vertex << " | vector[" << position << "] = " << SimplexVector5[position] << std::endl; @@ -481,7 +485,7 @@ BOOST_AUTO_TEST_CASE_TEMPLATE(NSimplexAndSubfaces_tree_insertion, typeST, list_o // Check it is well inserted BOOST_CHECK(true == returnValue.second); position = 0; - std::sort(SimplexVector6.begin(), SimplexVector6.end(), std::greater<Vertex_handle>()); + std::sort(SimplexVector6.begin(), SimplexVector6.end(), std::greater<typename typeST::Vertex_handle>()); for (auto vertex : st.simplex_vertex_range(returnValue.first)) { // Check returned Simplex_handle std::cout << "vertex = " << vertex << " | vector[" << position << "] = " << SimplexVector6[position] << std::endl; @@ -504,12 +508,12 @@ BOOST_AUTO_TEST_CASE_TEMPLATE(NSimplexAndSubfaces_tree_insertion, typeST, list_o /* A facet [3,4,5] */ /* A cell [0,1,6,7] */ - typeSimplex simplexPair1 = std::make_pair(SimplexVector1, DEFAULT_FILTRATION_VALUE); - typeSimplex simplexPair2 = std::make_pair(SimplexVector2, DEFAULT_FILTRATION_VALUE); - typeSimplex simplexPair3 = std::make_pair(SimplexVector3, DEFAULT_FILTRATION_VALUE); - typeSimplex simplexPair4 = std::make_pair(SimplexVector4, DEFAULT_FILTRATION_VALUE); - typeSimplex simplexPair5 = std::make_pair(SimplexVector5, DEFAULT_FILTRATION_VALUE); - typeSimplex simplexPair6 = std::make_pair(SimplexVector6, DEFAULT_FILTRATION_VALUE); + typeSimplex simplexPair1 = std::make_pair(SimplexVector1, 0.0); + typeSimplex simplexPair2 = std::make_pair(SimplexVector2, 0.0); + typeSimplex simplexPair3 = std::make_pair(SimplexVector3, 0.0); + typeSimplex simplexPair4 = std::make_pair(SimplexVector4, 0.0); + typeSimplex simplexPair5 = std::make_pair(SimplexVector5, 0.0); + typeSimplex simplexPair6 = std::make_pair(SimplexVector6, 0.0); test_simplex_tree_contains(st, simplexPair1, 6); // (2,1,0) is in position 6 test_simplex_tree_contains(st, simplexPair2, 7); // (3) is in position 7 test_simplex_tree_contains(st, simplexPair3, 8); // (3,0) is in position 8 @@ -600,7 +604,7 @@ void test_cofaces(typeST& st, const std::vector<Vertex_handle>& expected, int di } BOOST_AUTO_TEST_CASE_TEMPLATE(coface_on_simplex_tree, typeST, list_of_tested_variants) { - typedef std::vector<Vertex_handle> typeVectorVertex; + typedef std::vector<typename typeST::Vertex_handle> typeVectorVertex; std::cout << "********************************************************************" << std::endl; std::cout << "TEST COFACE ALGORITHM" << std::endl; typeST st; @@ -629,7 +633,7 @@ BOOST_AUTO_TEST_CASE_TEMPLATE(coface_on_simplex_tree, typeST, list_of_tested_var // FIXME st.set_dimension(3); - std::vector<Vertex_handle> simplex_result; + std::vector<typename typeST::Vertex_handle> simplex_result; std::vector<typename typeST::Simplex_handle> result; std::cout << "First test - Star of (3):" << std::endl; @@ -649,7 +653,7 @@ BOOST_AUTO_TEST_CASE_TEMPLATE(coface_on_simplex_tree, typeST, list_of_tested_var result.push_back(st.find(simplex_result)); simplex_result.clear(); - std::vector<Vertex_handle> vertex = {3}; + std::vector<typename typeST::Vertex_handle> vertex = {3}; test_cofaces(st, vertex, 0, result); vertex.clear(); result.clear(); @@ -699,7 +703,7 @@ BOOST_AUTO_TEST_CASE_TEMPLATE(coface_on_simplex_tree, typeST, list_of_tested_var } BOOST_AUTO_TEST_CASE_TEMPLATE(copy_move_on_simplex_tree, typeST, list_of_tested_variants) { - typedef std::vector<Vertex_handle> typeVectorVertex; + typedef std::vector<typename typeST::Vertex_handle> typeVectorVertex; std::cout << "********************************************************************" << std::endl; std::cout << "TEST COPY MOVE CONSTRUCTORS" << std::endl; typeST st; @@ -771,12 +775,11 @@ void test_simplex_is_vertex(typeST& st, typename typeST::Simplex_handle sh, type BOOST_AUTO_TEST_CASE(non_contiguous) { typedef Simplex_tree<> typeST; - typedef typeST::Vertex_handle Vertex_handle; typedef typeST::Simplex_handle Simplex_handle; std::cout << "********************************************************************" << std::endl; std::cout << "TEST NON-CONTIGUOUS VERTICES" << std::endl; typeST st; - Vertex_handle e[] = {3,-7}; + typeST::Vertex_handle e[] = {3,-7}; std::cout << "Insert" << std::endl; st.insert_simplex_and_subfaces(e); BOOST_CHECK(st.num_vertices() == 2); diff --git a/src/Tangential_complex/benchmark/CMakeLists.txt b/src/Tangential_complex/benchmark/CMakeLists.txt index 56dd8128..788c2b4d 100644 --- a/src/Tangential_complex/benchmark/CMakeLists.txt +++ b/src/Tangential_complex/benchmark/CMakeLists.txt @@ -1,15 +1,6 @@ cmake_minimum_required(VERSION 2.6) project(Tangential_complex_benchmark) -if (GCOVR_PATH) - # for gcovr to make coverage reports - Corbera Jenkins plugin - set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -fprofile-arcs -ftest-coverage") -endif() -if (GPROF_PATH) - # for gprof to make coverage reports - Jenkins - set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -pg") -endif() - # need CGAL 4.8 if(CGAL_FOUND) if (NOT CGAL_VERSION VERSION_LESS 4.8.0) diff --git a/src/Witness_complex/example/witness_complex_from_file.cpp b/src/Witness_complex/example/witness_complex_from_file.cpp index bb641b3c..5dd18d0a 100644 --- a/src/Witness_complex/example/witness_complex_from_file.cpp +++ b/src/Witness_complex/example/witness_complex_from_file.cpp @@ -4,7 +4,7 @@ * * Author(s): Siargey Kachanovich * - * Copyright (C) 2015 INRIA Sophia Antipolis-Méditerranée (France) + * Copyright (C) 2015 INRIA * * 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 @@ -36,7 +36,8 @@ #include <string> #include <vector> -typedef std::vector< Vertex_handle > typeVectorVertex; +typedef Gudhi::Simplex_tree<> Simplex_tree; +typedef std::vector< Simplex_tree::Vertex_handle > typeVectorVertex; typedef std::vector< std::vector <double> > Point_Vector; int main(int argc, char * const argv[]) { @@ -51,7 +52,7 @@ int main(int argc, char * const argv[]) { clock_t start, end; // Construct the Simplex Tree - Gudhi::Simplex_tree<> simplex_tree; + Simplex_tree simplex_tree; // Read the OFF file (input file name given as parameter) and triangulate points Gudhi::Points_off_reader<std::vector <double>> off_reader(off_file_name); @@ -69,7 +70,7 @@ int main(int argc, char * const argv[]) { std::vector<std::vector< int > > knn; Point_Vector landmarks; Gudhi::subsampling::pick_n_random_points(point_vector, 100, std::back_inserter(landmarks)); - Gudhi::witness_complex::construct_closest_landmark_table(point_vector, landmarks, knn); + Gudhi::witness_complex::construct_closest_landmark_table<Simplex_tree::Filtration_value>(point_vector, landmarks, knn); end = clock(); std::cout << "Landmark choice for " << nbL << " landmarks took " << static_cast<double>(end - start) / CLOCKS_PER_SEC << " s. \n"; diff --git a/src/Witness_complex/example/witness_complex_sphere.cpp b/src/Witness_complex/example/witness_complex_sphere.cpp index e6f88274..60e02225 100644 --- a/src/Witness_complex/example/witness_complex_sphere.cpp +++ b/src/Witness_complex/example/witness_complex_sphere.cpp @@ -4,7 +4,7 @@ * * Author(s): Siargey Kachanovich * - * Copyright (C) 2015 INRIA Sophia Antipolis-Méditerranée (France) + * Copyright (C) 2015 INRIA * * 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 @@ -40,6 +40,8 @@ #include "generators.h" +typedef Gudhi::Simplex_tree<> Simplex_tree; + /** Write a gnuplot readable file. * Data range is a random access range of pairs (arg, value) */ @@ -62,7 +64,7 @@ int main(int argc, char * const argv[]) { clock_t start, end; // Construct the Simplex Tree - Gudhi::Simplex_tree<> simplex_tree; + Simplex_tree simplex_tree; std::vector< std::pair<int, double> > l_time; @@ -77,7 +79,7 @@ int main(int argc, char * const argv[]) { start = clock(); std::vector<std::vector< int > > knn; Gudhi::subsampling::pick_n_random_points(point_vector, 100, std::back_inserter(landmarks)); - Gudhi::witness_complex::construct_closest_landmark_table(point_vector, landmarks, knn); + Gudhi::witness_complex::construct_closest_landmark_table<Simplex_tree::Filtration_value>(point_vector, landmarks, knn); // Compute witness complex Gudhi::witness_complex::witness_complex(knn, number_of_landmarks, point_vector[0].size(), simplex_tree); diff --git a/src/Witness_complex/include/gudhi/Construct_closest_landmark_table.h b/src/Witness_complex/include/gudhi/Construct_closest_landmark_table.h index ef711c34..a8cdd096 100644 --- a/src/Witness_complex/include/gudhi/Construct_closest_landmark_table.h +++ b/src/Witness_complex/include/gudhi/Construct_closest_landmark_table.h @@ -4,7 +4,7 @@ * * Author(s): Siargey Kachanovich * - * Copyright (C) 2015 INRIA Sophia Antipolis-Méditerranée (France) + * Copyright (C) 2015 INRIA * * 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 @@ -51,7 +51,8 @@ namespace witness_complex { * Closest_landmark_range needs to have push_back operation. */ - template <typename WitnessContainer, + template <typename FiltrationValue, + typename WitnessContainer, typename LandmarkContainer, typename KNearestNeighbours> void construct_closest_landmark_table(WitnessContainer const &points, @@ -72,7 +73,8 @@ namespace witness_complex { int landmarks_i = 0; for (landmarks_it = landmarks.begin(), landmarks_i = 0; landmarks_it != landmarks.end(); ++landmarks_it, landmarks_i++) { - dist_i dist = std::make_pair(euclidean_distance(points[points_i], *landmarks_it), landmarks_i); + dist_i dist = std::make_pair(Euclidean_distance()(points[points_i], *landmarks_it), + landmarks_i); l_heap.push(dist); } for (int i = 0; i < dim + 1; i++) { diff --git a/src/Witness_complex/include/gudhi/Witness_complex.h b/src/Witness_complex/include/gudhi/Witness_complex.h index 489cdf11..1eb126f1 100644 --- a/src/Witness_complex/include/gudhi/Witness_complex.h +++ b/src/Witness_complex/include/gudhi/Witness_complex.h @@ -72,7 +72,6 @@ class Witness_complex { typedef std::vector< Point_t > Point_Vector; typedef std::vector< Vertex_handle > typeVectorVertex; - typedef std::pair< typeVectorVertex, Filtration_value> typeSimplex; typedef std::pair< Simplex_handle, bool > typePairSimplexBool; typedef int Witness_id; diff --git a/src/Witness_complex/test/simple_witness_complex.cpp b/src/Witness_complex/test/simple_witness_complex.cpp index 03df78ee..6be39f58 100644 --- a/src/Witness_complex/test/simple_witness_complex.cpp +++ b/src/Witness_complex/test/simple_witness_complex.cpp @@ -33,7 +33,7 @@ #include <vector> typedef Gudhi::Simplex_tree<> Simplex_tree; -typedef std::vector< Vertex_handle > typeVectorVertex; +typedef std::vector< Simplex_tree::Vertex_handle > typeVectorVertex; typedef Gudhi::witness_complex::Witness_complex<Simplex_tree> WitnessComplex; BOOST_AUTO_TEST_CASE(simple_witness_complex) { diff --git a/src/Witness_complex/test/witness_complex_points.cpp b/src/Witness_complex/test/witness_complex_points.cpp index d40bbf14..92f53417 100644 --- a/src/Witness_complex/test/witness_complex_points.cpp +++ b/src/Witness_complex/test/witness_complex_points.cpp @@ -34,8 +34,8 @@ #include <vector> typedef std::vector<double> Point; -typedef std::vector< Vertex_handle > typeVectorVertex; typedef Gudhi::Simplex_tree<> Simplex_tree; +typedef std::vector< Simplex_tree::Vertex_handle > typeVectorVertex; typedef Gudhi::witness_complex::Witness_complex<Simplex_tree> WitnessComplex; BOOST_AUTO_TEST_CASE(witness_complex_points) { @@ -51,7 +51,7 @@ BOOST_AUTO_TEST_CASE(witness_complex_points) { // First test: random choice Simplex_tree complex1; Gudhi::subsampling::pick_n_random_points(points, 100, std::back_inserter(landmarks)); - Gudhi::witness_complex::construct_closest_landmark_table(points, landmarks, knn); + Gudhi::witness_complex::construct_closest_landmark_table<Simplex_tree::Filtration_value>(points, landmarks, knn); assert(!knn.empty()); WitnessComplex witnessComplex1(knn, 100, 3, complex1); BOOST_CHECK(witnessComplex1.is_witness_complex(knn, b_print_output)); diff --git a/src/cmake/modules/FindQGLViewer.cmake b/src/cmake/modules/FindQGLViewer.cmake index 1f3dbc1f..56c1b3cf 100644 --- a/src/cmake/modules/FindQGLViewer.cmake +++ b/src/cmake/modules/FindQGLViewer.cmake @@ -15,7 +15,7 @@ find_path(QGLVIEWER_INCLUDE_DIR ) find_library(QGLVIEWER_LIBRARY_RELEASE - NAMES qglviewer-qt4 QGLViewer-qt4 qglviewer QGLViewer QGLViewer2 + NAMES qglviewer-qt5 QGLViewer-qt5 qglviewer QGLViewer QGLViewer2 PATHS /usr/lib /usr/local/lib ENV QGLVIEWERROOT diff --git a/src/cmake/modules/GUDHI_user_version_target.txt b/src/cmake/modules/GUDHI_user_version_target.txt index a48f0ee3..742cbe8c 100644 --- a/src/cmake/modules/GUDHI_user_version_target.txt +++ b/src/cmake/modules/GUDHI_user_version_target.txt @@ -50,7 +50,7 @@ if (NOT CMAKE_VERSION VERSION_LESS 2.8.11) add_custom_command(TARGET user_version PRE_BUILD COMMAND ${CMAKE_COMMAND} -E copy_directory ${CMAKE_SOURCE_DIR}/src/GudhUI ${GUDHI_USER_VERSION_DIR}/GudhUI) - set(GUDHI_MODULES "common;Alpha_complex;Bitmap_cubical_complex;Contraction;Hasse_complex;Persistent_cohomology;Simplex_tree;Skeleton_blocker;Spatial_searching;Subsampling;Tangential_complex;Witness_complex") + set(GUDHI_MODULES "common;Alpha_complex;Bitmap_cubical_complex;Bottleneck_distance;Contraction;Hasse_complex;Persistent_cohomology;Rips_complex;Simplex_tree;Skeleton_blocker;Spatial_searching;Subsampling;Tangential_complex;Witness_complex") foreach(GUDHI_MODULE ${GUDHI_MODULES}) # doc files diff --git a/src/common/doc/main_page.h b/src/common/doc/main_page.h index 1a2cb6ba..ca5a919c 100644 --- a/src/common/doc/main_page.h +++ b/src/common/doc/main_page.h @@ -28,6 +28,7 @@ <b>Author:</b> Vincent Rouvreau<br> <b>Introduced in:</b> GUDHI 1.3.0<br> <b>Copyright:</b> GPL v3<br> + <b>Requires:</b> \ref cgal ≥ 4.7.0 and \ref eigen3 </td> <td width="75%"> Alpha_complex is a simplicial complex constructed from the finite cells of a Delaunay Triangulation.<br> @@ -55,6 +56,24 @@ <b>User manual:</b> \ref cubical_complex - <b>Reference manual:</b> Gudhi::cubical_complex::Bitmap_cubical_complex </td> </tr> + \subsection RipsComplexDataStructure Rips complex + \image html "rips_complex_representation.png" "Rips complex representation" +<table border="0"> + <tr> + <td width="25%"> + <b>Author:</b> Clément Maria, Pawel Dlotko, Vincent Rouvreau<br> + <b>Introduced in:</b> GUDHI 1.4.0<br> + <b>Copyright:</b> GPL v3<br> + </td> + <td width="75%"> + Rips_complex is a simplicial complex constructed from a one skeleton graph.<br> + The filtration value of each edge is computed from a user-given distance function and is inserted until a + user-given threshold value.<br> + This complex can be built from a point cloud and a distance function, or from a distance matrix.<br> + <b>User manual:</b> \ref rips_complex - <b>Reference manual:</b> Gudhi::rips_complex::Rips_complex + </td> + </tr> +</table> </table> \subsection SimplexTreeDataStructure Simplex tree \image html "Simplex_tree_representation.png" "Simplex tree representation" @@ -130,6 +149,26 @@ </table> \section Toolbox Toolbox + \subsection BottleneckDistanceToolbox Bottleneck distance + \image html "perturb_pd.png" "Bottleneck distance is the length of the longest edge" +<table border="0"> + <tr> + <td width="25%"> + <b>Author:</b> François Godi<br> + <b>Introduced in:</b> GUDHI 1.4.0<br> + <b>Copyright:</b> GPL v3<br> + <b>Requires:</b> \ref cgal ≥ 4.8.0 and \ref eigen3 + </td> + <td width="75%"> + Bottleneck distance measures the similarity between two persistence diagrams. + It's the shortest distance b for which there exists a perfect matching between + the points of the two diagrams (+ all the diagonal points) such that + any couple of matched points are at distance at most b. + <br> + <b>User manual:</b> \ref bottleneck_distance + </td> + </tr> +</table> \subsection ContractionToolbox Contraction \image html "sphere_contraction_representation.png" "Sphere contraction example" <table border="0"> @@ -196,24 +235,22 @@ make \endverbatim * \verbatim make test \endverbatim * * \section optionallibrary Optional third-party library - * \subsection gmp GMP: + * \subsection gmp GMP * The multi-field persistent homology algorithm requires GMP which is a free library for arbitrary-precision * arithmetic, operating on signed integers, rational numbers, and floating point numbers. * * The following example requires the <a target="_blank" href="http://gmplib.org/">GNU Multiple Precision Arithmetic * Library</a> (GMP) and will not be built if GMP is not installed: - * \li <a href="_persistent_cohomology_2performance_rips_persistence_8cpp-example.html"> - * Persistent_cohomology/performance_rips_persistence.cpp</a> * \li <a href="_persistent_cohomology_2rips_multifield_persistence_8cpp-example.html"> * Persistent_cohomology/rips_multifield_persistence.cpp</a> * * Having GMP version 4.2 or higher installed is recommended. * - * \subsection cgal CGAL: - * The \ref alpha_complex data structure and few examples requires CGAL, which is a C++ library which provides easy - * access to efficient and reliable geometric algorithms. + * \subsection cgal CGAL + * The \ref alpha_complex data structure, \ref bottleneck_distance, and few examples requires CGAL, which is a C++ + * library which provides easy access to efficient and reliable geometric algorithms. * - * Having CGAL version 4.4 or higher installed is recommended. The procedure to install this library according to + * Having CGAL version 4.4.0 or higher installed is recommended. The procedure to install this library according to * your operating system is detailed here http://doc.cgal.org/latest/Manual/installation.html * * The following examples require the <a target="_blank" href="http://www.cgal.org/">Computational Geometry Algorithms @@ -223,11 +260,11 @@ make \endverbatim * \li <a href="_simplex_tree_2example_alpha_shapes_3_simplex_tree_from_off_file_8cpp-example.html"> * Simplex_tree/example_alpha_shapes_3_simplex_tree_from_off_file.cpp</a> * - * The following example requires CGAL version ≥ 4.6: + * The following example requires CGAL version ≥ 4.6.0: * \li <a href="_witness_complex_2witness_complex_sphere_8cpp-example.html"> * Witness_complex/witness_complex_sphere.cpp</a> * - * The following example requires CGAL version ≥ 4.7: + * The following example requires CGAL version ≥ 4.7.0: * \li <a href="_alpha_complex_2_alpha_complex_from_off_8cpp-example.html"> * Alpha_complex/Alpha_complex_from_off.cpp</a> * \li <a href="_alpha_complex_2_alpha_complex_from_points_8cpp-example.html"> @@ -239,7 +276,13 @@ make \endverbatim * \li <a href="_persistent_cohomology_2custom_persistence_sort_8cpp-example.html"> * Persistent_cohomology/custom_persistence_sort.cpp</a> * - * \subsection eigen3 Eigen3: + * The following example requires CGAL version ≥ 4.8.0: + * \li <a href="_bottleneck_distance_2_bottleneck_basic_example_8cpp-example.html"> + * Bottleneck_distance/bottleneck_basic_example.cpp</a> + * \li <a href="_bottleneck_distance_2_bottleneck_read_file_example_8cpp-example.html"> + * Bottleneck_distance/bottleneck_read_file_example.cpp</a> + * + * \subsection eigen3 Eigen3 * The \ref alpha_complex data structure and few examples requires * <a target="_blank" href="http://eigen.tuxfamily.org/">Eigen3</a> is a C++ template library for linear algebra: * matrices, vectors, numerical solvers, and related algorithms. @@ -247,9 +290,13 @@ make \endverbatim * The following example requires the <a target="_blank" href="http://eigen.tuxfamily.org/">Eigen3</a> and will not be * built if Eigen3 is not installed: * \li <a href="_alpha_complex_2_alpha_complex_from_off_8cpp-example.html"> - * Alpha_complex/Alpha_complex_from_off.cpp</a> (requires also Eigen3) + * Alpha_complex/Alpha_complex_from_off.cpp</a> * \li <a href="_alpha_complex_2_alpha_complex_from_points_8cpp-example.html"> - * Alpha_complex/Alpha_complex_from_points.cpp</a> (requires also Eigen3) + * Alpha_complex/Alpha_complex_from_points.cpp</a> + * \li <a href="_bottleneck_distance_2_bottleneck_basic_example_8cpp-example.html"> + * Bottleneck_distance/bottleneck_basic_example.cpp</a> + * \li <a href="_bottleneck_distance_2_bottleneck_read_file_example_8cpp-example.html"> + * Bottleneck_distance/bottleneck_read_file_example.cpp</a> * \li <a href="_persistent_cohomology_2alpha_complex_persistence_8cpp-example.html"> * Persistent_cohomology/alpha_complex_persistence.cpp</a> * \li <a href="_persistent_cohomology_2periodic_alpha_complex_3d_persistence_8cpp-example.html"> @@ -257,7 +304,7 @@ make \endverbatim * \li <a href="_persistent_cohomology_2custom_persistence_sort_8cpp-example.html"> * Persistent_cohomology/custom_persistence_sort.cpp</a> * - * \subsection tbb Threading Building Blocks: + * \subsection tbb Threading Building Blocks * <a target="_blank" href="https://www.threadingbuildingblocks.org/">Intel® TBB</a> lets you easily write parallel * C++ programs that take full advantage of multicore performance, that are portable and composable, and that have * future-proof scalability. @@ -291,22 +338,28 @@ make \endverbatim * Persistent_cohomology/alpha_complex_persistence.cpp</a> * \li <a href="_persistent_cohomology_2rips_persistence_via_boundary_matrix_8cpp-example.html"> * Persistent_cohomology/rips_persistence_via_boundary_matrix.cpp</a> - * \li <a href="_persistent_cohomology_2performance_rips_persistence_8cpp-example.html"> - * Persistent_cohomology/performance_rips_persistence.cpp</a> * \li <a href="_persistent_cohomology_2persistence_from_file_8cpp-example.html"> * Persistent_cohomology/persistence_from_file.cpp</a> * \li <a href="_persistent_cohomology_2persistence_from_simple_simplex_tree_8cpp-example.html"> * Persistent_cohomology/persistence_from_simple_simplex_tree.cpp</a> * \li <a href="_persistent_cohomology_2plain_homology_8cpp-example.html"> * Persistent_cohomology/plain_homology.cpp</a> + * \li <a href="_persistent_cohomology_2rips_distance_matrix_persistence_8cpp-example.html"> + * Persistent_cohomology/rips_distance_matrix_persistence.cpp</a> * \li <a href="_persistent_cohomology_2rips_multifield_persistence_8cpp-example.html"> * Persistent_cohomology/rips_multifield_persistence.cpp</a> * \li <a href="_persistent_cohomology_2rips_persistence_8cpp-example.html"> * Persistent_cohomology/rips_persistence.cpp</a> + * \li <a href="_persistent_cohomology_2rips_persistence_step_by_step_8cpp-example.html"> + * Persistent_cohomology/rips_persistence_step_by_step.cpp</a> * \li <a href="_persistent_cohomology_2periodic_alpha_complex_3d_persistence_8cpp-example.html"> * Persistent_cohomology/periodic_alpha_complex_3d_persistence.cpp</a> * \li <a href="_persistent_cohomology_2custom_persistence_sort_8cpp-example.html"> * Persistent_cohomology/custom_persistence_sort.cpp</a> + * \li <a href="_rips_complex_2example_one_skeleton_rips_from_points_8cpp-example.html"> + * Rips_complex/example_one_skeleton_rips_from_points.cpp</a> + * \li <a href="_rips_complex_2example_rips_complex_from_off_file_8cpp-example.html"> + * Rips_complex/example_rips_complex_from_off_file.cpp</a> * * \section Contributions Bug reports and contributions * Please help us improving the quality of the GUDHI library. You may report bugs or suggestions to: @@ -331,6 +384,8 @@ make \endverbatim /*! @file Examples * @example Alpha_complex/Alpha_complex_from_off.cpp * @example Alpha_complex/Alpha_complex_from_points.cpp + * @example Bottleneck_distance/bottleneck_basic_example.cpp + * @example Bottleneck_distance/bottleneck_read_file_example.cpp * @example Bitmap_cubical_complex/Bitmap_cubical_complex.cpp * @example Bitmap_cubical_complex/Bitmap_cubical_complex_periodic_boundary_conditions.cpp * @example Bitmap_cubical_complex/Random_bitmap_cubical_complex.cpp @@ -341,14 +396,17 @@ make \endverbatim * @example Persistent_cohomology/alpha_complex_3d_persistence.cpp * @example Persistent_cohomology/alpha_complex_persistence.cpp * @example Persistent_cohomology/rips_persistence_via_boundary_matrix.cpp - * @example Persistent_cohomology/performance_rips_persistence.cpp * @example Persistent_cohomology/periodic_alpha_complex_3d_persistence.cpp * @example Persistent_cohomology/persistence_from_file.cpp * @example Persistent_cohomology/persistence_from_simple_simplex_tree.cpp * @example Persistent_cohomology/plain_homology.cpp * @example Persistent_cohomology/rips_multifield_persistence.cpp + * @example Persistent_cohomology/rips_distance_matrix_persistence.cpp * @example Persistent_cohomology/rips_persistence.cpp * @example Persistent_cohomology/custom_persistence_sort.cpp + * @example Persistent_cohomology/rips_persistence_step_by_step.cpp + * @example Rips_complex/example_one_skeleton_rips_from_points.cpp + * @example Rips_complex/example_rips_complex_from_off_file.cpp * @example Simplex_tree/mini_simplex_tree.cpp * @example Simplex_tree/simple_simplex_tree.cpp * @example Simplex_tree/example_alpha_shapes_3_simplex_tree_from_off_file.cpp diff --git a/src/common/example/example_CGAL_3D_points_off_reader.cpp b/src/common/example/example_CGAL_3D_points_off_reader.cpp index d48bb17d..665b7a29 100644 --- a/src/common/example/example_CGAL_3D_points_off_reader.cpp +++ b/src/common/example/example_CGAL_3D_points_off_reader.cpp @@ -32,7 +32,7 @@ int main(int argc, char **argv) { // Retrieve the triangulation std::vector<Point_3> point_cloud = off_reader.get_point_cloud(); - int n {0}; + int n {}; for (auto point : point_cloud) { ++n; std::cout << "Point[" << n << "] = (" << point[0] << ", " << point[1] << ", " << point[2] << ")\n"; diff --git a/src/common/example/example_CGAL_points_off_reader.cpp b/src/common/example/example_CGAL_points_off_reader.cpp index 4522174a..8c6a6b54 100644 --- a/src/common/example/example_CGAL_points_off_reader.cpp +++ b/src/common/example/example_CGAL_points_off_reader.cpp @@ -34,7 +34,7 @@ int main(int argc, char **argv) { // Retrieve the triangulation std::vector<Point_d> point_cloud = off_reader.get_point_cloud(); - int n {0}; + int n {}; for (auto point : point_cloud) { std::cout << "Point[" << n << "] = "; for (std::size_t i {0}; i < point.size(); i++) diff --git a/src/common/include/gudhi/distance_functions.h b/src/common/include/gudhi/distance_functions.h index cd518581..5891ef0e 100644 --- a/src/common/include/gudhi/distance_functions.h +++ b/src/common/include/gudhi/distance_functions.h @@ -4,7 +4,7 @@ * * Author(s): Clément Maria * - * Copyright (C) 2014 INRIA Sophia Antipolis-Méditerranée (France) + * Copyright (C) 2014 INRIA * * 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 @@ -25,19 +25,25 @@ #include <cmath> // for std::sqrt -/* Compute the Euclidean distance between two Points given - * by a range of coordinates. The points are assumed to have - * the same dimension. */ -template< typename Point > -double euclidean_distance(Point &p1, Point &p2) { - double dist = 0.; - auto it1 = p1.begin(); - auto it2 = p2.begin(); - for (; it1 != p1.end(); ++it1, ++it2) { - double tmp = *it1 - *it2; - dist += tmp*tmp; +/** @file + * @brief Global distance functions + */ + +/** @brief Compute the Euclidean distance between two Points given by a range of coordinates. The points are assumed to + * have the same dimension. */ +class Euclidean_distance { + public: + template< typename Point > + auto operator()(const Point& p1, const Point& p2) -> typename std::decay<decltype(*std::begin(p1))>::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 std::sqrt(dist); } - return std::sqrt(dist); -} +}; #endif // DISTANCE_FUNCTIONS_H_ diff --git a/src/common/include/gudhi/graph_simplicial_complex.h b/src/common/include/gudhi/graph_simplicial_complex.h index 042ef516..5fe7c826 100644 --- a/src/common/include/gudhi/graph_simplicial_complex.h +++ b/src/common/include/gudhi/graph_simplicial_complex.h @@ -4,7 +4,7 @@ * * Author(s): Clément Maria * - * Copyright (C) 2014 INRIA Sophia Antipolis-Méditerranée (France) + * Copyright (C) 2014 INRIA * * 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 @@ -39,61 +39,4 @@ struct vertex_filtration_t { typedef boost::vertex_property_tag kind; }; -typedef int Vertex_handle; -typedef double Filtration_value; -typedef boost::adjacency_list < boost::vecS, boost::vecS, boost::undirectedS -, boost::property < vertex_filtration_t, Filtration_value > -, boost::property < edge_filtration_t, Filtration_value > -> Graph_t; -typedef std::pair< Vertex_handle, Vertex_handle > Edge_t; - -/** \brief Output the proximity graph of the points. - * - * If points contains n elements, the proximity graph is the graph - * with n vertices, and an edge [u,v] iff the distance function between - * points u and v is smaller than threshold. - * - * The type PointCloud furnishes .begin() and .end() methods, that return - * iterators with value_type Point. - */ -template< typename PointCloud -, typename Point > -Graph_t compute_proximity_graph(PointCloud &points - , Filtration_value threshold - , Filtration_value distance(Point p1, Point p2)) { - std::vector< Edge_t > edges; - std::vector< Filtration_value > edges_fil; - std::map< Vertex_handle, Filtration_value > vertices; - - Vertex_handle idx_u, idx_v; - Filtration_value fil; - idx_u = 0; - for (auto it_u = points.begin(); it_u != points.end(); ++it_u) { - idx_v = idx_u + 1; - for (auto it_v = it_u + 1; it_v != points.end(); ++it_v, ++idx_v) { - fil = distance(*it_u, *it_v); - if (fil <= threshold) { - edges.emplace_back(idx_u, idx_v); - edges_fil.push_back(fil); - } - } - ++idx_u; - } - - Graph_t skel_graph(edges.begin() - , edges.end() - , edges_fil.begin() - , idx_u); // number of points labeled from 0 to idx_u-1 - - auto vertex_prop = boost::get(vertex_filtration_t(), skel_graph); - - boost::graph_traits<Graph_t>::vertex_iterator vi, vi_end; - for (std::tie(vi, vi_end) = boost::vertices(skel_graph); - vi != vi_end; ++vi) { - boost::put(vertex_prop, *vi, 0.); - } - - return skel_graph; -} - #endif // GRAPH_SIMPLICIAL_COMPLEX_H_ diff --git a/src/common/include/gudhi/reader_utils.h b/src/common/include/gudhi/reader_utils.h index 899f9df6..97a87edd 100644 --- a/src/common/include/gudhi/reader_utils.h +++ b/src/common/include/gudhi/reader_utils.h @@ -2,9 +2,9 @@ * (Geometric Understanding in Higher Dimensions) is a generic C++ * library for computational topology. * - * Author(s): Clément Maria + * Author(s): Clement Maria, Pawel Dlotko * - * Copyright (C) 2014 INRIA Sophia Antipolis-Méditerranée (France) + * Copyright (C) 2014 INRIA * * 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 @@ -30,18 +30,25 @@ #include <iostream> #include <fstream> #include <map> -#include <limits> // for numeric_limits<> +#include <limits> // for numeric_limits #include <string> #include <vector> +#include <utility> // for pair + +// Keep this file tag for Doxygen to parse the code, otherwise, functions are not documented. +// It is required for global functions and variables. + +/** @file + * @brief This file includes common file reader for GUDHI + */ /** - * \brief Read a set of points to turn it - * into a vector< vector<double> > by filling points + * @brief Read a set of points to turn it into a vector< vector<double> > by filling points. * - * File format: 1 point per line - * X11 X12 ... X1d - * X21 X22 ... X2d - * etc + * File format: 1 point per line<br> + * X11 X12 ... X1d<br> + * X21 X22 ... X2d<br> + * etc<br> */ inline void read_points(std::string file_name, std::vector< std::vector< double > > & points) { std::ifstream in_file(file_name.c_str(), std::ios::in); @@ -66,23 +73,29 @@ inline void read_points(std::string file_name, std::vector< std::vector< double } /** - * \brief Read a graph from a file. + * @brief Read a graph from a file. + * + * \tparam Graph_t Type for the return graph. Must be constructible from iterators on pairs of Vertex_handle + * \tparam Filtration_value Type for the value of the read filtration + * \tparam Vertex_handle Type for the value of the read vertices * - * File format: 1 simplex per line - * Dim1 X11 X12 ... X1d Fil1 - * Dim2 X21 X22 ... X2d Fil2 - * etc + * File format: 1 simplex per line<br> + * Dim1 X11 X12 ... X1d Fil1<br> + * Dim2 X21 X22 ... X2d Fil2<br> + * etc<br> * * The vertices must be labeled from 0 to n-1. * Every simplex must appear exactly once. * Simplices of dimension more than 1 are ignored. */ -inline Graph_t read_graph(std::string file_name) { +template< typename Graph_t, typename Filtration_value, typename Vertex_handle > +Graph_t read_graph(std::string file_name) { std::ifstream in_(file_name.c_str(), std::ios::in); if (!in_.is_open()) { std::cerr << "Unable to open file " << file_name << std::endl; } + typedef std::pair< Vertex_handle, Vertex_handle > Edge_t; std::vector< Edge_t > edges; std::vector< Filtration_value > edges_fil; std::map< Vertex_handle, Filtration_value > vertices; @@ -130,7 +143,7 @@ inline Graph_t read_graph(std::string file_name) { Graph_t skel_graph(edges.begin(), edges.end(), edges_fil.begin(), vertices.size()); auto vertex_prop = boost::get(vertex_filtration_t(), skel_graph); - boost::graph_traits<Graph_t>::vertex_iterator vi, vi_end; + typename boost::graph_traits<Graph_t>::vertex_iterator vi, vi_end; auto v_it = vertices.begin(); for (std::tie(vi, vi_end) = boost::vertices(skel_graph); vi != vi_end; ++vi, ++v_it) { boost::put(vertex_prop, *vi, v_it->second); @@ -140,12 +153,12 @@ inline Graph_t read_graph(std::string file_name) { } /** - * \brief Read a face from a file. + * @brief Read a face from a file. * - * File format: 1 simplex per line - * Dim1 X11 X12 ... X1d Fil1 - * Dim2 X21 X22 ... X2d Fil2 - * etc + * File format: 1 simplex per line<br> + * Dim1 X11 X12 ... X1d Fil1<br> + * Dim2 X21 X22 ... X2d Fil2<br> + * etc<br> * * The vertices must be labeled from 0 to n-1. * Every simplex must appear exactly once. @@ -166,18 +179,16 @@ bool read_simplex(std::istream & in_, std::vector< Vertex_handle > & simplex, Fi } /** - * \brief Read a hasse simplex from a file. - * - * File format: 1 simplex per line - * Dim1 k11 k12 ... k1Dim1 Fil1 - * Dim2 k21 k22 ... k2Dim2 Fil2 - * etc - * - * The key of a simplex is its position in the filtration order - * and also the number of its row in the file. - * Dimi ki1 ki2 ... kiDimi Fili means that the ith simplex in the - * filtration has dimension Dimi, filtration value fil1 and simplices with - * key ki1 ... kiDimi in its boundary.*/ + * @brief Read a hasse simplex from a file. + * + * File format: 1 simplex per line<br> + * Dim1 k11 k12 ... k1Dim1 Fil1<br> + * Dim2 k21 k22 ... k2Dim2 Fil2<br> + * etc<br> + * + * The key of a simplex is its position in the filtration order and also the number of its row in the file. + * Dimi ki1 ki2 ... kiDimi Fili means that the ith simplex in the filtration has dimension Dimi, filtration value + * fil1 and simplices with key ki1 ... kiDimi in its boundary.*/ template< typename Simplex_key, typename Filtration_value > bool read_hasse_simplex(std::istream & in_, std::vector< Simplex_key > & boundary, Filtration_value & fil) { int dim; @@ -195,4 +206,93 @@ bool read_hasse_simplex(std::istream & in_, std::vector< Simplex_key > & boundar return true; } +/** + * @brief Read a lower triangular distance matrix from a csv file. We assume that the .csv store the whole + * (square) matrix. + * + * @author Pawel Dlotko + * + * Square matrix file format:<br> + * 0;D12;...;D1j<br> + * D21;0;...;D2j<br> + * ...<br> + * Dj1;Dj2;...;0<br> + * + * lower matrix file format:<br> + * 0<br> + * D21;<br> + * D31;D32;<br> + * ...<br> + * Dj1;Dj2;...;Dj(j-1);<br> + * + **/ +template< typename Filtration_value > +std::vector< std::vector< Filtration_value > > read_lower_triangular_matrix_from_csv_file(const std::string& filename, + const char separator = ';') { +#ifdef DEBUG_TRACES + std::cout << "Using procedure read_lower_triangular_matrix_from_csv_file \n"; +#endif // DEBUG_TRACES + std::vector< std::vector< Filtration_value > > result; + std::ifstream in; + in.open(filename.c_str()); + if (!in.is_open()) { + return result; + } + + std::string line; + + // the first line is emtpy, so we ignore it: + std::getline(in, line); + std::vector< Filtration_value > values_in_this_line; + result.push_back(values_in_this_line); + + int number_of_line = 0; + + // first, read the file line by line to a string: + while (std::getline(in, line)) { + // if line is empty, break + if (line.size() == 0) + break; + + // if the last element of a string is comma: + if (line[ line.size() - 1 ] == separator) { + // then shrink the string by one + line.pop_back(); + } + + // replace all commas with spaces + std::replace(line.begin(), line.end(), separator, ' '); + + // put the new line to a stream + std::istringstream iss(line); + // and now read the doubles. + + int number_of_entry = 0; + std::vector< Filtration_value > values_in_this_line; + while (iss.good()) { + double entry; + iss >> entry; + if (number_of_entry <= number_of_line) { + values_in_this_line.push_back(entry); + } + ++number_of_entry; + } + if (!values_in_this_line.empty())result.push_back(values_in_this_line); + ++number_of_line; + } + in.close(); + +#ifdef DEBUG_TRACES + std::cerr << "Here is the matrix we read : \n"; + for (size_t i = 0; i != result.size(); ++i) { + for (size_t j = 0; j != result[i].size(); ++j) { + std::cerr << result[i][j] << " "; + } + std::cerr << std::endl; + } +#endif // DEBUG_TRACES + + return result; +} // read_lower_triangular_matrix_from_csv_file + #endif // READER_UTILS_H_ diff --git a/src/common/include/gudhi_patches/Bottleneck_distance_CGAL_patches.txt b/src/common/include/gudhi_patches/Bottleneck_distance_CGAL_patches.txt new file mode 100644 index 00000000..a588d113 --- /dev/null +++ b/src/common/include/gudhi_patches/Bottleneck_distance_CGAL_patches.txt @@ -0,0 +1,3 @@ +CGAL/Kd_tree.h +CGAL/Kd_tree_node.h +CGAL/Orthogonal_incremental_neighbor_search.h diff --git a/src/common/include/gudhi_patches/CGAL/Kd_tree.h b/src/common/include/gudhi_patches/CGAL/Kd_tree.h new file mode 100644 index 00000000..f085b0da --- /dev/null +++ b/src/common/include/gudhi_patches/CGAL/Kd_tree.h @@ -0,0 +1,582 @@ +// Copyright (c) 2002,2011,2014 Utrecht University (The Netherlands), Max-Planck-Institute Saarbruecken (Germany). +// All rights reserved. +// +// This file is part of CGAL (www.cgal.org). +// 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. +// +// Licensees holding a valid commercial license may use this file in +// accordance with the commercial license agreement provided with the software. +// +// This file is provided AS IS with NO WARRANTY OF ANY KIND, INCLUDING THE +// WARRANTY OF DESIGN, MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. +// +// $URL$ +// $Id$ +// +// Author(s) : Hans Tangelder (<hanst@cs.uu.nl>), +// : Waqar Khan <wkhan@mpi-inf.mpg.de> + +#ifndef CGAL_KD_TREE_H +#define CGAL_KD_TREE_H + +#include "Kd_tree_node.h" + +#include <CGAL/basic.h> +#include <CGAL/assertions.h> +#include <vector> + +#include <CGAL/algorithm.h> +#include <CGAL/internal/Get_dimension_tag.h> +#include <CGAL/Search_traits.h> + + +#include <deque> +#include <boost/container/deque.hpp> +#include <boost/optional.hpp> + +#ifdef CGAL_HAS_THREADS +#include <CGAL/mutex.h> +#endif + +namespace CGAL { + +//template <class SearchTraits, class Splitter_=Median_of_rectangle<SearchTraits>, class UseExtendedNode = Tag_true > +template <class SearchTraits, class Splitter_=Sliding_midpoint<SearchTraits>, class UseExtendedNode = Tag_true > +class Kd_tree { + +public: + typedef SearchTraits Traits; + typedef Splitter_ Splitter; + typedef typename SearchTraits::Point_d Point_d; + typedef typename Splitter::Container Point_container; + + typedef typename SearchTraits::FT FT; + typedef Kd_tree_node<SearchTraits, Splitter, UseExtendedNode > Node; + typedef Kd_tree_leaf_node<SearchTraits, Splitter, UseExtendedNode > Leaf_node; + typedef Kd_tree_internal_node<SearchTraits, Splitter, UseExtendedNode > Internal_node; + typedef Kd_tree<SearchTraits, Splitter> Tree; + typedef Kd_tree<SearchTraits, Splitter,UseExtendedNode> Self; + + typedef Node* Node_handle; + typedef const Node* Node_const_handle; + typedef Leaf_node* Leaf_node_handle; + typedef const Leaf_node* Leaf_node_const_handle; + typedef Internal_node* Internal_node_handle; + typedef const Internal_node* Internal_node_const_handle; + typedef typename std::vector<const Point_d*>::const_iterator Point_d_iterator; + typedef typename std::vector<const Point_d*>::const_iterator Point_d_const_iterator; + typedef typename Splitter::Separator Separator; + typedef typename std::vector<Point_d>::const_iterator iterator; + typedef typename std::vector<Point_d>::const_iterator const_iterator; + + typedef typename std::vector<Point_d>::size_type size_type; + + typedef typename internal::Get_dimension_tag<SearchTraits>::Dimension D; + +private: + SearchTraits traits_; + Splitter split; + + + // wokaround for https://svn.boost.org/trac/boost/ticket/9332 +#if (_MSC_VER == 1800) && (BOOST_VERSION == 105500) + std::deque<Internal_node> internal_nodes; + std::deque<Leaf_node> leaf_nodes; +#else + boost::container::deque<Internal_node> internal_nodes; + boost::container::deque<Leaf_node> leaf_nodes; +#endif + + Node_handle tree_root; + + Kd_tree_rectangle<FT,D>* bbox; + std::vector<Point_d> pts; + + // Instead of storing the points in arrays in the Kd_tree_node + // we put all the data in a vector in the Kd_tree. + // and we only store an iterator range in the Kd_tree_node. + // + std::vector<const Point_d*> data; + + + #ifdef CGAL_HAS_THREADS + mutable CGAL_MUTEX building_mutex;//mutex used to protect const calls inducing build() + #endif + bool built_; + bool removed_; + + // protected copy constructor + Kd_tree(const Tree& tree) + : traits_(tree.traits_),built_(tree.built_) + {}; + + + // Instead of the recursive construction of the tree in the class Kd_tree_node + // we do this in the tree class. The advantage is that we then can optimize + // the allocation of the nodes. + + // The leaf node + Node_handle + create_leaf_node(Point_container& c) + { + Leaf_node node(true , static_cast<unsigned int>(c.size())); + std::ptrdiff_t tmp = c.begin() - data.begin(); + node.data = pts.begin() + tmp; + + leaf_nodes.push_back(node); + Leaf_node_handle nh = &leaf_nodes.back(); + + + return nh; + } + + + // The internal node + + Node_handle + create_internal_node(Point_container& c, const Tag_true&) + { + return create_internal_node_use_extension(c); + } + + Node_handle + create_internal_node(Point_container& c, const Tag_false&) + { + return create_internal_node(c); + } + + + + // TODO: Similiar to the leaf_init function above, a part of the code should be + // moved to a the class Kd_tree_node. + // It is not proper yet, but the goal was to see if there is + // a potential performance gain through the Compact_container + Node_handle + create_internal_node_use_extension(Point_container& c) + { + Internal_node node(false); + internal_nodes.push_back(node); + Internal_node_handle nh = &internal_nodes.back(); + + Separator sep; + Point_container c_low(c.dimension(),traits_); + split(sep, c, c_low); + nh->set_separator(sep); + + int cd = nh->cutting_dimension(); + if(!c_low.empty()){ + nh->lower_low_val = c_low.tight_bounding_box().min_coord(cd); + nh->lower_high_val = c_low.tight_bounding_box().max_coord(cd); + } + else{ + nh->lower_low_val = nh->cutting_value(); + nh->lower_high_val = nh->cutting_value(); + } + if(!c.empty()){ + nh->upper_low_val = c.tight_bounding_box().min_coord(cd); + nh->upper_high_val = c.tight_bounding_box().max_coord(cd); + } + else{ + nh->upper_low_val = nh->cutting_value(); + nh->upper_high_val = nh->cutting_value(); + } + + CGAL_assertion(nh->cutting_value() >= nh->lower_low_val); + CGAL_assertion(nh->cutting_value() <= nh->upper_high_val); + + if (c_low.size() > split.bucket_size()){ + nh->lower_ch = create_internal_node_use_extension(c_low); + }else{ + nh->lower_ch = create_leaf_node(c_low); + } + if (c.size() > split.bucket_size()){ + nh->upper_ch = create_internal_node_use_extension(c); + }else{ + nh->upper_ch = create_leaf_node(c); + } + + + + + return nh; + } + + + // Note also that I duplicated the code to get rid if the if's for + // the boolean use_extension which was constant over the construction + Node_handle + create_internal_node(Point_container& c) + { + Internal_node node(false); + internal_nodes.push_back(node); + Internal_node_handle nh = &internal_nodes.back(); + Separator sep; + + Point_container c_low(c.dimension(),traits_); + split(sep, c, c_low); + nh->set_separator(sep); + + if (c_low.size() > split.bucket_size()){ + nh->lower_ch = create_internal_node(c_low); + }else{ + nh->lower_ch = create_leaf_node(c_low); + } + if (c.size() > split.bucket_size()){ + nh->upper_ch = create_internal_node(c); + }else{ + nh->upper_ch = create_leaf_node(c); + } + + + + return nh; + } + + + +public: + + Kd_tree(Splitter s = Splitter(),const SearchTraits traits=SearchTraits()) + : traits_(traits),split(s), built_(false), removed_(false) + {} + + template <class InputIterator> + Kd_tree(InputIterator first, InputIterator beyond, + Splitter s = Splitter(),const SearchTraits traits=SearchTraits()) + : traits_(traits),split(s), built_(false), removed_(false) + { + pts.insert(pts.end(), first, beyond); + } + + bool empty() const { + return pts.empty(); + } + + void + build() + { + // This function is not ready to be called when a tree already exists, one + // must call invalidate_built() first. + CGAL_assertion(!is_built()); + CGAL_assertion(!removed_); + const Point_d& p = *pts.begin(); + typename SearchTraits::Construct_cartesian_const_iterator_d ccci=traits_.construct_cartesian_const_iterator_d_object(); + int dim = static_cast<int>(std::distance(ccci(p), ccci(p,0))); + + data.reserve(pts.size()); + for(unsigned int i = 0; i < pts.size(); i++){ + data.push_back(&pts[i]); + } + Point_container c(dim, data.begin(), data.end(),traits_); + bbox = new Kd_tree_rectangle<FT,D>(c.bounding_box()); + if (c.size() <= split.bucket_size()){ + tree_root = create_leaf_node(c); + }else { + tree_root = create_internal_node(c, UseExtendedNode()); + } + + //Reorder vector for spatial locality + std::vector<Point_d> ptstmp; + ptstmp.resize(pts.size()); + for (std::size_t i = 0; i < pts.size(); ++i){ + ptstmp[i] = *data[i]; + } + for(std::size_t i = 0; i < leaf_nodes.size(); ++i){ + std::ptrdiff_t tmp = leaf_nodes[i].begin() - pts.begin(); + leaf_nodes[i].data = ptstmp.begin() + tmp; + } + pts.swap(ptstmp); + + data.clear(); + + built_ = true; + } + +private: + //any call to this function is for the moment not threadsafe + void const_build() const { + #ifdef CGAL_HAS_THREADS + //this ensure that build() will be called once + CGAL_SCOPED_LOCK(building_mutex); + if(!is_built()) + #endif + const_cast<Self*>(this)->build(); //THIS IS NOT THREADSAFE + } +public: + + bool is_built() const + { + return built_; + } + + void invalidate_built() + { + if(removed_){ + // Walk the tree to collect the remaining points. + // Writing directly to pts would likely work, but better be safe. + std::vector<Point_d> ptstmp; + //ptstmp.resize(root()->num_items()); + root()->tree_items(std::back_inserter(ptstmp)); + pts.swap(ptstmp); + removed_=false; + CGAL_assertion(is_built()); // the rest of the cleanup must happen + } + if(is_built()){ + internal_nodes.clear(); + leaf_nodes.clear(); + data.clear(); + delete bbox; + built_ = false; + } + } + + void clear() + { + invalidate_built(); + pts.clear(); + removed_ = false; + } + + void + insert(const Point_d& p) + { + invalidate_built(); + pts.push_back(p); + } + + template <class InputIterator> + void + insert(InputIterator first, InputIterator beyond) + { + invalidate_built(); + pts.insert(pts.end(),first, beyond); + } + +private: + struct Equal_by_coordinates { + SearchTraits const* traits; + Point_d const* pp; + bool operator()(Point_d const&q) const { + typename SearchTraits::Construct_cartesian_const_iterator_d ccci=traits->construct_cartesian_const_iterator_d_object(); + return std::equal(ccci(*pp), ccci(*pp,0), ccci(q)); + } + }; + Equal_by_coordinates equal_by_coordinates(Point_d const&p){ + Equal_by_coordinates ret = { &traits(), &p }; + return ret; + } + +public: + void + remove(const Point_d& p) + { + remove(p, equal_by_coordinates(p)); + } + + template<class Equal> + void + remove(const Point_d& p, Equal const& equal_to_p) + { +#if 0 + // This code could have quadratic runtime. + if (!is_built()) { + std::vector<Point_d>::iterator pi = std::find(pts.begin(), pts.end(), p); + // Precondition: the point must be there. + CGAL_assertion (pi != pts.end()); + pts.erase(pi); + return; + } +#endif + bool success = remove_(p, 0, false, 0, false, root(), equal_to_p); + CGAL_assertion(success); + + // Do not set the flag is the tree has been cleared. + if(is_built()) + removed_ |= success; + } +private: + template<class Equal> + bool remove_(const Point_d& p, + Internal_node_handle grandparent, bool parent_islower, + Internal_node_handle parent, bool islower, + Node_handle node, Equal const& equal_to_p) { + // Recurse to locate the point + if (!node->is_leaf()) { + Internal_node_handle newparent = static_cast<Internal_node_handle>(node); + // FIXME: This should be if(x<y) remove low; else remove up; + if (traits().construct_cartesian_const_iterator_d_object()(p)[newparent->cutting_dimension()] <= newparent->cutting_value()) { + if (remove_(p, parent, islower, newparent, true, newparent->lower(), equal_to_p)) + return true; + } + //if (traits().construct_cartesian_const_iterator_d_object()(p)[newparent->cutting_dimension()] >= newparent->cutting_value()) + return remove_(p, parent, islower, newparent, false, newparent->upper(), equal_to_p); + + CGAL_assertion(false); // Point was not found + } + + // Actual removal + Leaf_node_handle lnode = static_cast<Leaf_node_handle>(node); + if (lnode->size() > 1) { + iterator pi = std::find_if(lnode->begin(), lnode->end(), equal_to_p); + // FIXME: we should ensure this never happens + if (pi == lnode->end()) return false; + iterator lasti = lnode->end() - 1; + if (pi != lasti) { + // Hack to get a non-const iterator + std::iter_swap(pts.begin()+(pi-pts.begin()), pts.begin()+(lasti-pts.begin())); + } + lnode->drop_last_point(); + } else if (!equal_to_p(*lnode->begin())) { + // FIXME: we should ensure this never happens + return false; + } else if (grandparent) { + Node_handle brother = islower ? parent->upper() : parent->lower(); + if (parent_islower) + grandparent->set_lower(brother); + else + grandparent->set_upper(brother); + } else if (parent) { + tree_root = islower ? parent->upper() : parent->lower(); + } else { + clear(); + } + return true; + } + +public: + //For efficiency; reserve the size of the points vectors in advance (if the number of points is already known). + void reserve(size_t size) + { + pts.reserve(size); + } + + //Get the capacity of the underlying points vector. + size_t capacity() + { + return pts.capacity(); + } + + + template <class OutputIterator, class FuzzyQueryItem> + OutputIterator + search(OutputIterator it, const FuzzyQueryItem& q) const + { + if(! pts.empty()){ + + if(! is_built()){ + const_build(); + } + Kd_tree_rectangle<FT,D> b(*bbox); + return tree_root->search(it,q,b); + } + return it; + } + + + template <class FuzzyQueryItem> + boost::optional<Point_d> + search_any_point(const FuzzyQueryItem& q) const + { + if(! pts.empty()){ + + if(! is_built()){ + const_build(); + } + Kd_tree_rectangle<FT,D> b(*bbox); + return tree_root->search_any_point(q,b); + } + return boost::none; + } + + + ~Kd_tree() { + if(is_built()){ + delete bbox; + } + } + + + const SearchTraits& + traits() const + { + return traits_; + } + + Node_const_handle + root() const + { + if(! is_built()){ + const_build(); + } + return tree_root; + } + + Node_handle + root() + { + if(! is_built()){ + build(); + } + return tree_root; + } + + void + print() const + { + if(! is_built()){ + const_build(); + } + root()->print(); + } + + const Kd_tree_rectangle<FT,D>& + bounding_box() const + { + if(! is_built()){ + const_build(); + } + return *bbox; + } + + const_iterator + begin() const + { + return pts.begin(); + } + + const_iterator + end() const + { + return pts.end(); + } + + size_type + size() const + { + return pts.size(); + } + + // Print statistics of the tree. + std::ostream& + statistics(std::ostream& s) const + { + if(! is_built()){ + const_build(); + } + s << "Tree statistics:" << std::endl; + s << "Number of items stored: " + << root()->num_items() << std::endl; + s << "Number of nodes: " + << root()->num_nodes() << std::endl; + s << " Tree depth: " << root()->depth() << std::endl; + return s; + } + + +}; + +} // namespace CGAL + +#endif // CGAL_KD_TREE_H diff --git a/src/common/include/gudhi_patches/CGAL/Kd_tree_node.h b/src/common/include/gudhi_patches/CGAL/Kd_tree_node.h new file mode 100644 index 00000000..909ee260 --- /dev/null +++ b/src/common/include/gudhi_patches/CGAL/Kd_tree_node.h @@ -0,0 +1,586 @@ +// Copyright (c) 2002,2011 Utrecht University (The Netherlands). +// All rights reserved. +// +// This file is part of CGAL (www.cgal.org). +// 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. +// +// Licensees holding a valid commercial license may use this file in +// accordance with the commercial license agreement provided with the software. +// +// This file is provided AS IS with NO WARRANTY OF ANY KIND, INCLUDING THE +// WARRANTY OF DESIGN, MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. +// +// $URL$ +// $Id$ +// +// +// Authors : Hans Tangelder (<hanst@cs.uu.nl>) + +#ifndef CGAL_KD_TREE_NODE_H +#define CGAL_KD_TREE_NODE_H + +#include "CGAL/Splitters.h" + +#include <CGAL/Compact_container.h> +#include <boost/cstdint.hpp> + +namespace CGAL { + + template <class SearchTraits, class Splitter, class UseExtendedNode> + class Kd_tree; + + template < class TreeTraits, class Splitter, class UseExtendedNode > + class Kd_tree_node { + + friend class Kd_tree<TreeTraits,Splitter,UseExtendedNode>; + + typedef typename Kd_tree<TreeTraits,Splitter,UseExtendedNode>::Node_handle Node_handle; + typedef typename Kd_tree<TreeTraits,Splitter,UseExtendedNode>::Node_const_handle Node_const_handle; + typedef typename Kd_tree<TreeTraits,Splitter,UseExtendedNode>::Internal_node_handle Internal_node_handle; + typedef typename Kd_tree<TreeTraits,Splitter,UseExtendedNode>::Internal_node_const_handle Internal_node_const_handle; + typedef typename Kd_tree<TreeTraits,Splitter,UseExtendedNode>::Leaf_node_handle Leaf_node_handle; + typedef typename Kd_tree<TreeTraits,Splitter,UseExtendedNode>::Leaf_node_const_handle Leaf_node_const_handle; + typedef typename TreeTraits::Point_d Point_d; + + typedef typename TreeTraits::FT FT; + typedef typename Kd_tree<TreeTraits,Splitter,UseExtendedNode>::Separator Separator; + typedef typename Kd_tree<TreeTraits,Splitter,UseExtendedNode>::Point_d_iterator Point_d_iterator; + typedef typename Kd_tree<TreeTraits,Splitter,UseExtendedNode>::iterator iterator; + typedef typename Kd_tree<TreeTraits,Splitter,UseExtendedNode>::D D; + + bool leaf; + + public : + Kd_tree_node(bool leaf_) + :leaf(leaf_){} + + bool is_leaf() const{ + return leaf; + } + + std::size_t + num_items() const + { + if (is_leaf()){ + Leaf_node_const_handle node = + static_cast<Leaf_node_const_handle>(this); + return node->size(); + } + else { + Internal_node_const_handle node = + static_cast<Internal_node_const_handle>(this); + return node->lower()->num_items() + node->upper()->num_items(); + } + } + + std::size_t + num_nodes() const + { + if (is_leaf()) return 1; + else { + Internal_node_const_handle node = + static_cast<Internal_node_const_handle>(this); + return node->lower()->num_nodes() + node->upper()->num_nodes(); + } + } + + int + depth(const int current_max_depth) const + { + if (is_leaf()){ + return current_max_depth; + } + else { + Internal_node_const_handle node = + static_cast<Internal_node_const_handle>(this); + return + (std::max)( node->lower()->depth(current_max_depth + 1), + node->upper()->depth(current_max_depth + 1)); + } + } + + int + depth() const + { + return depth(1); + } + + template <class OutputIterator> + OutputIterator + tree_items(OutputIterator it) const { + if (is_leaf()) { + Leaf_node_const_handle node = + static_cast<Leaf_node_const_handle>(this); + if (node->size()>0) + for (iterator i=node->begin(); i != node->end(); i++) + {*it=*i; ++it;} + } + else { + Internal_node_const_handle node = + static_cast<Internal_node_const_handle>(this); + it=node->lower()->tree_items(it); + it=node->upper()->tree_items(it); + } + return it; + } + + + boost::optional<Point_d> + any_tree_item() const { + boost::optional<Point_d> result = boost::none; + if (is_leaf()) { + Leaf_node_const_handle node = + static_cast<Leaf_node_const_handle>(this); + if (node->size()>0){ + return boost::make_optional(*(node->begin())); + } + } + else { + Internal_node_const_handle node = + static_cast<Internal_node_const_handle>(this); + result = node->lower()->any_tree_item(); + if(! result){ + result = node->upper()->any_tree_item(); + } + } + return result; + } + + + void + indent(int d) const + { + for(int i = 0; i < d; i++){ + std::cout << " "; + } + } + + + void + print(int d = 0) const + { + if (is_leaf()) { + Leaf_node_const_handle node = + static_cast<Leaf_node_const_handle>(this); + indent(d); + std::cout << "leaf" << std::endl; + if (node->size()>0) + for (iterator i=node->begin(); i != node->end(); i++) + {indent(d);std::cout << *i << std::endl;} + } + else { + Internal_node_const_handle node = + static_cast<Internal_node_const_handle>(this); + indent(d); + std::cout << "lower tree" << std::endl; + node->lower()->print(d+1); + indent(d); + std::cout << "separator: dim = " << node->cutting_dimension() << " val = " << node->cutting_value() << std::endl; + indent(d); + std::cout << "upper tree" << std::endl; + node->upper()->print(d+1); + } + } + + + template <class OutputIterator, class FuzzyQueryItem> + OutputIterator + search(OutputIterator it, const FuzzyQueryItem& q, + Kd_tree_rectangle<FT,D>& b) const + { + if (is_leaf()) { + Leaf_node_const_handle node = + static_cast<Leaf_node_const_handle>(this); + if (node->size()>0) + for (iterator i=node->begin(); i != node->end(); i++) + if (q.contains(*i)) + {*it++=*i;} + } + else { + Internal_node_const_handle node = + static_cast<Internal_node_const_handle>(this); + // after splitting b denotes the lower part of b + Kd_tree_rectangle<FT,D> b_upper(b); + b.split(b_upper, node->cutting_dimension(), + node->cutting_value()); + + if (q.outer_range_contains(b)) + it=node->lower()->tree_items(it); + else + if (q.inner_range_intersects(b)) + it=node->lower()->search(it,q,b); + if (q.outer_range_contains(b_upper)) + it=node->upper()->tree_items(it); + else + if (q.inner_range_intersects(b_upper)) + it=node->upper()->search(it,q,b_upper); + }; + return it; + } + + + template <class FuzzyQueryItem> + boost::optional<Point_d> + search_any_point(const FuzzyQueryItem& q, + Kd_tree_rectangle<FT,D>& b) const + { + boost::optional<Point_d> result = boost::none; + if (is_leaf()) { + Leaf_node_const_handle node = + static_cast<Leaf_node_const_handle>(this); + if (node->size()>0) + for (iterator i=node->begin(); i != node->end(); i++) + if (q.contains(*i)) + { result = *i; break; } + } + else { + Internal_node_const_handle node = + static_cast<Internal_node_const_handle>(this); + // after splitting b denotes the lower part of b + Kd_tree_rectangle<FT,D> b_upper(b); + b.split(b_upper, node->cutting_dimension(), + node->cutting_value()); + + if (q.outer_range_contains(b)){ + result = node->lower()->any_tree_item(); + }else{ + if (q.inner_range_intersects(b)){ + result = node->lower()->search_any_point(q,b); + } + } + if(result){ + return result; + } + if (q.outer_range_contains(b_upper)){ + result = node->upper()->any_tree_item(); + }else{ + if (q.inner_range_intersects(b_upper)) + result = node->upper()->search_any_point(q,b_upper); + } + } + return result; + } + + }; + + + template < class TreeTraits, class Splitter, class UseExtendedNode > + class Kd_tree_leaf_node : public Kd_tree_node< TreeTraits, Splitter, UseExtendedNode >{ + + friend class Kd_tree<TreeTraits,Splitter,UseExtendedNode>; + + typedef typename Kd_tree<TreeTraits,Splitter,UseExtendedNode>::iterator iterator; + typedef Kd_tree_node< TreeTraits, Splitter, UseExtendedNode> Base; + typedef typename TreeTraits::Point_d Point_d; + + private: + + // private variables for leaf nodes + boost::int32_t n; // denotes number of items in a leaf node + iterator data; // iterator to data in leaf node + + + public: + + // default constructor + Kd_tree_leaf_node() + {} + + Kd_tree_leaf_node(bool leaf_ ) + : Base(leaf_) + {} + + Kd_tree_leaf_node(bool leaf_,unsigned int n_ ) + : Base(leaf_), n(n_) + {} + + // members for all nodes + + // members for leaf nodes only + inline + unsigned int + size() const + { + return n; + } + + inline + iterator + begin() const + { + return data; + } + + inline + iterator + end() const + { + return data + n; + } + + inline + void + drop_last_point() + { + --n; + } + + }; //leaf node + + + + template < class TreeTraits, class Splitter, class UseExtendedNode> + class Kd_tree_internal_node : public Kd_tree_node< TreeTraits, Splitter, UseExtendedNode >{ + + friend class Kd_tree<TreeTraits,Splitter,UseExtendedNode>; + + typedef Kd_tree_node< TreeTraits, Splitter, UseExtendedNode> Base; + typedef typename Kd_tree<TreeTraits,Splitter,UseExtendedNode>::Node_handle Node_handle; + typedef typename Kd_tree<TreeTraits,Splitter,UseExtendedNode>::Node_const_handle Node_const_handle; + + typedef typename TreeTraits::FT FT; + typedef typename Kd_tree<TreeTraits,Splitter,UseExtendedNode>::Separator Separator; + + private: + + // private variables for internal nodes + boost::int32_t cut_dim; + FT cut_val; + Node_handle lower_ch, upper_ch; + + + // private variables for extended internal nodes + FT upper_low_val; + FT upper_high_val; + FT lower_low_val; + FT lower_high_val; + + + public: + + // default constructor + Kd_tree_internal_node() + {} + + Kd_tree_internal_node(bool leaf_) + : Base(leaf_) + {} + + + // members for internal node and extended internal node + + inline + Node_const_handle + lower() const + { + return lower_ch; + } + + inline + Node_const_handle + upper() const + { + return upper_ch; + } + + inline + Node_handle + lower() + { + return lower_ch; + } + + inline + Node_handle + upper() + { + return upper_ch; + } + + inline + void + set_lower(Node_handle nh) + { + lower_ch = nh; + } + + inline + void + set_upper(Node_handle nh) + { + upper_ch = nh; + } + + // inline Separator& separator() {return sep; } + // use instead + inline + void set_separator(Separator& sep){ + cut_dim = sep.cutting_dimension(); + cut_val = sep.cutting_value(); + } + + inline + FT + cutting_value() const + { + return cut_val; + } + + inline + int + cutting_dimension() const + { + return cut_dim; + } + + // members for extended internal node only + inline + FT + upper_low_value() const + { + return upper_low_val; + } + + inline + FT + upper_high_value() const + { + return upper_high_val; + } + + inline + FT + lower_low_value() const + { + return lower_low_val; + } + + inline + FT + lower_high_value() const + { + return lower_high_val; + } + + /*Separator& + separator() + { + return Separator(cutting_dimension,cutting_value); + }*/ + + + };//internal node + + template < class TreeTraits, class Splitter> + class Kd_tree_internal_node<TreeTraits,Splitter,Tag_false> : public Kd_tree_node< TreeTraits, Splitter, Tag_false >{ + + friend class Kd_tree<TreeTraits,Splitter,Tag_false>; + + typedef Kd_tree_node< TreeTraits, Splitter, Tag_false> Base; + typedef typename Kd_tree<TreeTraits,Splitter,Tag_false>::Node_handle Node_handle; + typedef typename Kd_tree<TreeTraits,Splitter,Tag_false>::Node_const_handle Node_const_handle; + + typedef typename TreeTraits::FT FT; + typedef typename Kd_tree<TreeTraits,Splitter,Tag_false>::Separator Separator; + + private: + + // private variables for internal nodes + boost::uint8_t cut_dim; + FT cut_val; + + Node_handle lower_ch, upper_ch; + + public: + + // default constructor + Kd_tree_internal_node() + {} + + Kd_tree_internal_node(bool leaf_) + : Base(leaf_) + {} + + + // members for internal node and extended internal node + + inline + Node_const_handle + lower() const + { + return lower_ch; + } + + inline + Node_const_handle + upper() const + { + return upper_ch; + } + + inline + Node_handle + lower() + { + return lower_ch; + } + + inline + Node_handle + upper() + { + return upper_ch; + } + + inline + void + set_lower(Node_handle nh) + { + lower_ch = nh; + } + + inline + void + set_upper(Node_handle nh) + { + upper_ch = nh; + } + + // inline Separator& separator() {return sep; } + // use instead + + inline + void set_separator(Separator& sep){ + cut_dim = sep.cutting_dimension(); + cut_val = sep.cutting_value(); + } + + inline + FT + cutting_value() const + { + return cut_val; + } + + inline + int + cutting_dimension() const + { + return cut_dim; + } + + /* Separator& + separator() + { + return Separator(cutting_dimension,cutting_value); + }*/ + + + };//internal node + + + +} // namespace CGAL +#endif // CGAL_KDTREE_NODE_H diff --git a/src/common/include/gudhi_patches/CGAL/Orthogonal_incremental_neighbor_search.h b/src/common/include/gudhi_patches/CGAL/Orthogonal_incremental_neighbor_search.h new file mode 100644 index 00000000..e29ce14f --- /dev/null +++ b/src/common/include/gudhi_patches/CGAL/Orthogonal_incremental_neighbor_search.h @@ -0,0 +1,620 @@ +// Copyright (c) 2002,2011 Utrecht University (The Netherlands). +// All rights reserved. +// +// This file is part of CGAL (www.cgal.org). +// 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. +// +// Licensees holding a valid commercial license may use this file in +// accordance with the commercial license agreement provided with the software. +// +// This file is provided AS IS with NO WARRANTY OF ANY KIND, INCLUDING THE +// WARRANTY OF DESIGN, MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. +// +// $URL$ +// $Id$ +// +// +// Author(s) : Hans Tangelder (<hanst@cs.uu.nl>) + +#ifndef CGAL_ORTHOGONAL_INCREMENTAL_NEIGHBOR_SEARCH +#define CGAL_ORTHOGONAL_INCREMENTAL_NEIGHBOR_SEARCH + +#include <CGAL/Kd_tree.h> +#include <cstring> +#include <list> +#include <queue> +#include <memory> +#include <CGAL/Euclidean_distance.h> +#include <CGAL/tuple.h> + +namespace CGAL { + + template <class SearchTraits, + class Distance_= typename internal::Spatial_searching_default_distance<SearchTraits>::type, + class Splitter_ = Sliding_midpoint<SearchTraits>, + class Tree_= Kd_tree<SearchTraits, Splitter_, Tag_true> > + class Orthogonal_incremental_neighbor_search { + + public: + typedef Splitter_ Splitter; + typedef Tree_ Tree; + typedef Distance_ Distance; + typedef typename SearchTraits::Point_d Point_d; + typedef typename Distance::Query_item Query_item; + typedef typename SearchTraits::FT FT; + typedef typename Tree::Point_d_iterator Point_d_iterator; + typedef typename Tree::Node_const_handle Node_const_handle; + + typedef std::pair<Point_d,FT> Point_with_transformed_distance; + typedef CGAL::cpp11::tuple<Node_const_handle,FT,std::vector<FT> > Node_with_distance; + typedef std::vector<Node_with_distance*> Node_with_distance_vector; + typedef std::vector<Point_with_transformed_distance*> Point_with_transformed_distance_vector; + + template<class T> + struct Object_wrapper + { + T object; + Object_wrapper(const T& t):object(t){} + const T& operator* () const { return object; } + const T* operator-> () const { return &object; } + }; + + class Iterator_implementation { + SearchTraits traits; + public: + + int number_of_neighbours_computed; + int number_of_internal_nodes_visited; + int number_of_leaf_nodes_visited; + int number_of_items_visited; + + private: + + typedef std::vector<FT> Distance_vector; + + Distance_vector dists; + + Distance Orthogonal_distance_instance; + + FT multiplication_factor; + + Query_item query_point; + + FT distance_to_root; + + bool search_nearest_neighbour; + + FT rd; + + + class Priority_higher { + public: + + bool search_nearest; + + Priority_higher(bool search_the_nearest_neighbour) + : search_nearest(search_the_nearest_neighbour) + {} + + //highest priority is smallest distance + bool + operator() (Node_with_distance* n1, Node_with_distance* n2) const + { + return (search_nearest) ? (CGAL::cpp11::get<1>(*n1) > CGAL::cpp11::get<1>(*n2)) : (CGAL::cpp11::get<1>(*n2) > CGAL::cpp11::get<1>(*n1)); + } + }; + + class Distance_smaller { + + public: + + bool search_nearest; + + Distance_smaller(bool search_the_nearest_neighbour) + : search_nearest(search_the_nearest_neighbour) + {} + + //highest priority is smallest distance + bool operator() (Point_with_transformed_distance* p1, Point_with_transformed_distance* p2) const + { + return (search_nearest) ? (p1->second > p2->second) : (p2->second > p1->second); + } + }; + + + std::priority_queue<Node_with_distance*, Node_with_distance_vector, + Priority_higher> PriorityQueue; + + public: + std::priority_queue<Point_with_transformed_distance*, Point_with_transformed_distance_vector, + Distance_smaller> Item_PriorityQueue; + + + public: + + int reference_count; + + + + // constructor + Iterator_implementation(const Tree& tree,const Query_item& q, const Distance& tr, + FT Eps=FT(0.0), bool search_nearest=true) + : traits(tree.traits()),number_of_neighbours_computed(0), number_of_internal_nodes_visited(0), + number_of_leaf_nodes_visited(0), number_of_items_visited(0), + Orthogonal_distance_instance(tr), multiplication_factor(Orthogonal_distance_instance.transformed_distance(FT(1.0)+Eps)), + query_point(q), search_nearest_neighbour(search_nearest), + PriorityQueue(Priority_higher(search_nearest)), Item_PriorityQueue(Distance_smaller(search_nearest)), + reference_count(1) + + + { + if (tree.empty()) return; + + typename SearchTraits::Construct_cartesian_const_iterator_d ccci=traits.construct_cartesian_const_iterator_d_object(); + int dim = static_cast<int>(std::distance(ccci(q), ccci(q,0))); + + dists.resize(dim); + for(int i=0 ; i<dim ; ++i){ + dists[i] = 0; + } + + if (search_nearest){ + distance_to_root= + Orthogonal_distance_instance.min_distance_to_rectangle(q, tree.bounding_box(),dists); + Node_with_distance *The_Root = new Node_with_distance(tree.root(), + distance_to_root, dists); + PriorityQueue.push(The_Root); + + // rd is the distance of the top of the priority queue to q + rd=CGAL::cpp11::get<1>(*The_Root); + Compute_the_next_nearest_neighbour(); + } + else{ + distance_to_root= + Orthogonal_distance_instance.max_distance_to_rectangle(q, + tree.bounding_box(), dists); + Node_with_distance *The_Root = new Node_with_distance(tree.root(), + distance_to_root, dists); + PriorityQueue.push(The_Root); + + // rd is the distance of the top of the priority queue to q + rd=CGAL::cpp11::get<1>(*The_Root); + Compute_the_next_furthest_neighbour(); + } + + + } + + // * operator + const Point_with_transformed_distance& + operator* () const + { + return *(Item_PriorityQueue.top()); + } + + // prefix operator + Iterator_implementation& + operator++() + { + Delete_the_current_item_top(); + if(search_nearest_neighbour) + Compute_the_next_nearest_neighbour(); + else + Compute_the_next_furthest_neighbour(); + return *this; + } + + // postfix operator + Object_wrapper<Point_with_transformed_distance> + operator++(int) + { + Object_wrapper<Point_with_transformed_distance> result( *(Item_PriorityQueue.top()) ); + ++*this; + return result; + } + + // Print statistics of the general priority search process. + std::ostream& + statistics (std::ostream& s) const { + s << "Orthogonal priority search statistics:" + << std::endl; + s << "Number of internal nodes visited:" + << number_of_internal_nodes_visited << std::endl; + s << "Number of leaf nodes visited:" + << number_of_leaf_nodes_visited << std::endl; + s << "Number of items visited:" + << number_of_items_visited << std::endl; + s << "Number of neighbours computed:" + << number_of_neighbours_computed << std::endl; + return s; + } + + + //destructor + ~Iterator_implementation() + { + while (!PriorityQueue.empty()) { + Node_with_distance* The_top=PriorityQueue.top(); + PriorityQueue.pop(); + delete The_top; + } + while (!Item_PriorityQueue.empty()) { + Point_with_transformed_distance* The_top=Item_PriorityQueue.top(); + Item_PriorityQueue.pop(); + delete The_top; + } + } + + private: + + void + Delete_the_current_item_top() + { + Point_with_transformed_distance* The_item_top=Item_PriorityQueue.top(); + Item_PriorityQueue.pop(); + delete The_item_top; + } + + void + Compute_the_next_nearest_neighbour() + { + // compute the next item + bool next_neighbour_found=false; + if (!(Item_PriorityQueue.empty())) { + next_neighbour_found= + (multiplication_factor*rd > Item_PriorityQueue.top()->second); + } + typename SearchTraits::Construct_cartesian_const_iterator_d construct_it=traits.construct_cartesian_const_iterator_d_object(); + typename SearchTraits::Cartesian_const_iterator_d query_point_it = construct_it(query_point); + // otherwise browse the tree further + while ((!next_neighbour_found) && (!PriorityQueue.empty())) { + Node_with_distance* The_node_top=PriorityQueue.top(); + Node_const_handle N= CGAL::cpp11::get<0>(*The_node_top); + dists = CGAL::cpp11::get<2>(*The_node_top); + PriorityQueue.pop(); + delete The_node_top; + FT copy_rd=rd; + while (!(N->is_leaf())) { // compute new distance + typename Tree::Internal_node_const_handle node = + static_cast<typename Tree::Internal_node_const_handle>(N); + number_of_internal_nodes_visited++; + int new_cut_dim=node->cutting_dimension(); + FT new_rd,dst = dists[new_cut_dim]; + FT val = *(query_point_it + new_cut_dim); + FT diff1 = val - node->upper_low_value(); + FT diff2 = val - node->lower_high_value(); + if (diff1 + diff2 < FT(0.0)) { + new_rd= + Orthogonal_distance_instance.new_distance(copy_rd,dst,diff1,new_cut_dim); + + CGAL_assertion(new_rd >= copy_rd); + dists[new_cut_dim] = diff1; + Node_with_distance *Upper_Child = + new Node_with_distance(node->upper(), new_rd, dists); + PriorityQueue.push(Upper_Child); + dists[new_cut_dim] = dst; + N=node->lower(); + + } + else { // compute new distance + new_rd=Orthogonal_distance_instance.new_distance(copy_rd,dst,diff2,new_cut_dim); + CGAL_assertion(new_rd >= copy_rd); + dists[new_cut_dim] = diff2; + Node_with_distance *Lower_Child = + new Node_with_distance(node->lower(), new_rd, dists); + PriorityQueue.push(Lower_Child); + dists[new_cut_dim] = dst; + N=node->upper(); + } + } + // n is a leaf + typename Tree::Leaf_node_const_handle node = + static_cast<typename Tree::Leaf_node_const_handle>(N); + number_of_leaf_nodes_visited++; + if (node->size() > 0) { + for (typename Tree::iterator it=node->begin(); it != node->end(); it++) { + number_of_items_visited++; + FT distance_to_query_point= + Orthogonal_distance_instance.transformed_distance(query_point,*it); + Point_with_transformed_distance *NN_Candidate= + new Point_with_transformed_distance(*it,distance_to_query_point); + Item_PriorityQueue.push(NN_Candidate); + } + // old top of PriorityQueue has been processed, + // hence update rd + + if (!(PriorityQueue.empty())) { + rd = CGAL::cpp11::get<1>(*PriorityQueue.top()); + next_neighbour_found = + (multiplication_factor*rd > + Item_PriorityQueue.top()->second); + } + else // priority queue empty => last neighbour found + { + next_neighbour_found=true; + } + + number_of_neighbours_computed++; + } + } // next_neighbour_found or priority queue is empty + // in the latter case also the item priority quee is empty + } + + + void + Compute_the_next_furthest_neighbour() + { + // compute the next item + bool next_neighbour_found=false; + if (!(Item_PriorityQueue.empty())) { + next_neighbour_found= + (rd < multiplication_factor*Item_PriorityQueue.top()->second); + } + typename SearchTraits::Construct_cartesian_const_iterator_d construct_it=traits.construct_cartesian_const_iterator_d_object(); + typename SearchTraits::Cartesian_const_iterator_d query_point_it = construct_it(query_point); + // otherwise browse the tree further + while ((!next_neighbour_found) && (!PriorityQueue.empty())) { + Node_with_distance* The_node_top=PriorityQueue.top(); + Node_const_handle N= CGAL::cpp11::get<0>(*The_node_top); + dists = CGAL::cpp11::get<2>(*The_node_top); + PriorityQueue.pop(); + delete The_node_top; + FT copy_rd=rd; + while (!(N->is_leaf())) { // compute new distance + typename Tree::Internal_node_const_handle node = + static_cast<typename Tree::Internal_node_const_handle>(N); + number_of_internal_nodes_visited++; + int new_cut_dim=node->cutting_dimension(); + FT new_rd,dst = dists[new_cut_dim]; + FT val = *(query_point_it + new_cut_dim); + FT diff1 = val - node->upper_low_value(); + FT diff2 = val - node->lower_high_value(); + if (diff1 + diff2 < FT(0.0)) { + diff1 = val - node->upper_high_value(); + new_rd= + Orthogonal_distance_instance.new_distance(copy_rd,dst,diff1,new_cut_dim); + Node_with_distance *Lower_Child = + new Node_with_distance(node->lower(), copy_rd, dists); + PriorityQueue.push(Lower_Child); + N=node->upper(); + dists[new_cut_dim] = diff1; + copy_rd=new_rd; + + } + else { // compute new distance + diff2 = val - node->lower_low_value(); + new_rd=Orthogonal_distance_instance.new_distance(copy_rd,dst,diff2,new_cut_dim); + Node_with_distance *Upper_Child = + new Node_with_distance(node->upper(), copy_rd, dists); + PriorityQueue.push(Upper_Child); + N=node->lower(); + dists[new_cut_dim] = diff2; + copy_rd=new_rd; + } + } + // n is a leaf + typename Tree::Leaf_node_const_handle node = + static_cast<typename Tree::Leaf_node_const_handle>(N); + number_of_leaf_nodes_visited++; + if (node->size() > 0) { + for (typename Tree::iterator it=node->begin(); it != node->end(); it++) { + number_of_items_visited++; + FT distance_to_query_point= + Orthogonal_distance_instance.transformed_distance(query_point,*it); + Point_with_transformed_distance *NN_Candidate= + new Point_with_transformed_distance(*it,distance_to_query_point); + Item_PriorityQueue.push(NN_Candidate); + } + // old top of PriorityQueue has been processed, + // hence update rd + + if (!(PriorityQueue.empty())) { + rd = CGAL::cpp11::get<1>(*PriorityQueue.top()); + next_neighbour_found = + (multiplication_factor*rd < + Item_PriorityQueue.top()->second); + } + else // priority queue empty => last neighbour found + { + next_neighbour_found=true; + } + + number_of_neighbours_computed++; + } + } // next_neighbour_found or priority queue is empty + // in the latter case also the item priority quee is empty + } + }; // class Iterator_implementaion + + + + + + + + + + public: + class iterator; + typedef iterator const_iterator; + + // constructor + Orthogonal_incremental_neighbor_search(const Tree& tree, + const Query_item& q, FT Eps = FT(0.0), + bool search_nearest=true, const Distance& tr=Distance()) + : m_tree(tree),m_query(q),m_dist(tr),m_Eps(Eps),m_search_nearest(search_nearest) + {} + + iterator + begin() const + { + return iterator(m_tree,m_query,m_dist,m_Eps,m_search_nearest); + } + + iterator + end() const + { + return iterator(); + } + + std::ostream& + statistics(std::ostream& s) + { + begin()->statistics(s); + return s; + } + + + + + class iterator { + + public: + + typedef std::input_iterator_tag iterator_category; + typedef Point_with_transformed_distance value_type; + typedef Point_with_transformed_distance* pointer; + typedef const Point_with_transformed_distance& reference; + typedef std::size_t size_type; + typedef std::ptrdiff_t difference_type; + typedef int distance_type; + + //class Iterator_implementation; + Iterator_implementation *Ptr_implementation; + + + public: + + // default constructor + iterator() + : Ptr_implementation(0) + {} + + int + the_number_of_items_visited() + { + return Ptr_implementation->number_of_items_visited; + } + + // constructor + iterator(const Tree& tree,const Query_item& q, const Distance& tr=Distance(), FT eps=FT(0.0), + bool search_nearest=true) + : Ptr_implementation(new Iterator_implementation(tree, q, tr, eps, search_nearest)) + {} + + // copy constructor + iterator(const iterator& Iter) + { + Ptr_implementation = Iter.Ptr_implementation; + if (Ptr_implementation != 0) Ptr_implementation->reference_count++; + } + + iterator& operator=(const iterator& Iter) + { + if (Ptr_implementation != Iter.Ptr_implementation){ + if (Ptr_implementation != 0 && --(Ptr_implementation->reference_count)==0) { + delete Ptr_implementation; + } + Ptr_implementation = Iter.Ptr_implementation; + if (Ptr_implementation != 0) Ptr_implementation->reference_count++; + } + return *this; + } + + + const Point_with_transformed_distance& + operator* () const + { + return *(*Ptr_implementation); + } + + // -> operator + const Point_with_transformed_distance* + operator-> () const + { + return &*(*Ptr_implementation); + } + + // prefix operator + iterator& + operator++() + { + ++(*Ptr_implementation); + return *this; + } + + // postfix operator + Object_wrapper<Point_with_transformed_distance> + operator++(int) + { + return (*Ptr_implementation)++; + } + + + bool + operator==(const iterator& It) const + { + if ( + ((Ptr_implementation == 0) || + Ptr_implementation->Item_PriorityQueue.empty()) && + ((It.Ptr_implementation == 0) || + It.Ptr_implementation->Item_PriorityQueue.empty()) + ) + return true; + // else + return (Ptr_implementation == It.Ptr_implementation); + } + + bool + operator!=(const iterator& It) const + { + return !(*this == It); + } + + std::ostream& + statistics (std::ostream& s) + { + Ptr_implementation->statistics(s); + return s; + } + + ~iterator() + { + if (Ptr_implementation != 0) { + Ptr_implementation->reference_count--; + if (Ptr_implementation->reference_count==0) { + delete Ptr_implementation; + Ptr_implementation = 0; + } + } + } + + + }; // class iterator + + //data members + const Tree& m_tree; + Query_item m_query; + Distance m_dist; + FT m_Eps; + bool m_search_nearest; + }; // class + + template <class Traits, class Query_item, class Distance> + void swap (typename Orthogonal_incremental_neighbor_search<Traits, + Query_item, Distance>::iterator& x, + typename Orthogonal_incremental_neighbor_search<Traits, + Query_item, Distance>::iterator& y) + { + typename Orthogonal_incremental_neighbor_search<Traits, + Query_item, Distance>::iterator::Iterator_implementation + *tmp = x.Ptr_implementation; + x.Ptr_implementation = y.Ptr_implementation; + y.Ptr_implementation = tmp; + } + +} // namespace CGAL + +#endif // CGAL_ORTHOGONAL_INCREMENTAL_NEIGHBOR_SEARCH_H diff --git a/src/common/include/gudhi_patches/Tangential_complex_CGAL_patches.txt b/src/common/include/gudhi_patches/Tangential_complex_CGAL_patches.txt new file mode 100644 index 00000000..5b9581a0 --- /dev/null +++ b/src/common/include/gudhi_patches/Tangential_complex_CGAL_patches.txt @@ -0,0 +1,82 @@ +CGAL/Regular_triangulation_traits_adapter.h +CGAL/Triangulation_ds_vertex.h +CGAL/Triangulation_data_structure.h +CGAL/transforming_pair_iterator.h +CGAL/NewKernel_d/static_int.h +CGAL/NewKernel_d/Cartesian_LA_functors.h +CGAL/NewKernel_d/Cartesian_change_FT.h +CGAL/NewKernel_d/Wrapper/Vector_d.h +CGAL/NewKernel_d/Wrapper/Hyperplane_d.h +CGAL/NewKernel_d/Wrapper/Ref_count_obj.h +CGAL/NewKernel_d/Wrapper/Cartesian_wrap.h +CGAL/NewKernel_d/Wrapper/Point_d.h +CGAL/NewKernel_d/Wrapper/Segment_d.h +CGAL/NewKernel_d/Wrapper/Weighted_point_d.h +CGAL/NewKernel_d/Wrapper/Sphere_d.h +CGAL/NewKernel_d/Cartesian_per_dimension.h +CGAL/NewKernel_d/Kernel_object_converter.h +CGAL/NewKernel_d/KernelD_converter.h +CGAL/NewKernel_d/Vector/sse2.h +CGAL/NewKernel_d/Vector/avx4.h +CGAL/NewKernel_d/Vector/determinant_of_vectors_small_dim_internal.h +CGAL/NewKernel_d/Vector/determinant_of_iterator_to_points_from_points.h +CGAL/NewKernel_d/Vector/determinant_of_points_from_vectors.h +CGAL/NewKernel_d/Vector/array.h +CGAL/NewKernel_d/Vector/determinant_of_iterator_to_points_from_iterator_to_vectors.h +CGAL/NewKernel_d/Vector/determinant_of_iterator_to_vectors_from_vectors.h +CGAL/NewKernel_d/Vector/determinant_of_vectors_small_dim.h +CGAL/NewKernel_d/Vector/vector.h +CGAL/NewKernel_d/Vector/v2int.h +CGAL/NewKernel_d/Vector/mix.h +CGAL/NewKernel_d/Cartesian_static_filters.h +CGAL/NewKernel_d/Cartesian_LA_base.h +CGAL/NewKernel_d/Lazy_cartesian.h +CGAL/NewKernel_d/Coaffine.h +CGAL/NewKernel_d/store_kernel.h +CGAL/NewKernel_d/Dimension_base.h +CGAL/NewKernel_d/Kernel_3_interface.h +CGAL/NewKernel_d/Cartesian_complete.h +CGAL/NewKernel_d/Cartesian_base.h +CGAL/NewKernel_d/Cartesian_filter_K.h +CGAL/NewKernel_d/functor_tags.h +CGAL/NewKernel_d/Filtered_predicate2.h +CGAL/NewKernel_d/functor_properties.h +CGAL/NewKernel_d/Define_kernel_types.h +CGAL/NewKernel_d/LA_eigen/LA.h +CGAL/NewKernel_d/LA_eigen/constructors.h +CGAL/NewKernel_d/Types/Aff_transformation.h +CGAL/NewKernel_d/Types/Sphere.h +CGAL/NewKernel_d/Types/Hyperplane.h +CGAL/NewKernel_d/Types/Line.h +CGAL/NewKernel_d/Types/Ray.h +CGAL/NewKernel_d/Types/Iso_box.h +CGAL/NewKernel_d/Types/Weighted_point.h +CGAL/NewKernel_d/Types/Segment.h +CGAL/NewKernel_d/Kernel_d_interface.h +CGAL/NewKernel_d/utils.h +CGAL/NewKernel_d/Kernel_2_interface.h +CGAL/NewKernel_d/Cartesian_filter_NT.h +CGAL/NewKernel_d/function_objects_cartesian.h +CGAL/Convex_hull.h +CGAL/Triangulation_ds_full_cell.h +CGAL/Regular_triangulation.h +CGAL/Epick_d.h +CGAL/transforming_iterator.h +CGAL/iterator_from_indices.h +CGAL/Delaunay_triangulation.h +CGAL/IO/Triangulation_off_ostream.h +CGAL/typeset.h +CGAL/Triangulation_full_cell.h +CGAL/Triangulation.h +CGAL/internal/Static_or_dynamic_array.h +CGAL/internal/Combination_enumerator.h +CGAL/internal/Triangulation/utilities.h +CGAL/internal/Triangulation/Triangulation_ds_iterators.h +CGAL/internal/Triangulation/Dummy_TDS.h +CGAL/argument_swaps.h +CGAL/Epeck_d.h +CGAL/determinant_of_vectors.h +CGAL/TDS_full_cell_default_storage_policy.h +CGAL/TDS_full_cell_mirror_storage_policy.h +CGAL/Triangulation_face.h +CGAL/Triangulation_vertex.h diff --git a/src/common/test/CMakeLists.txt b/src/common/test/CMakeLists.txt index 7ccdb752..baa24539 100644 --- a/src/common/test/CMakeLists.txt +++ b/src/common/test/CMakeLists.txt @@ -13,12 +13,21 @@ endif() add_executable ( poffreader_UT test_points_off_reader.cpp ) target_link_libraries(poffreader_UT ${Boost_SYSTEM_LIBRARY} ${Boost_UNIT_TEST_FRAMEWORK_LIBRARY}) +add_executable ( distancematrixreader_UT test_distance_matrix_reader.cpp ) +target_link_libraries(distancematrixreader_UT ${Boost_SYSTEM_LIBRARY} ${Boost_UNIT_TEST_FRAMEWORK_LIBRARY}) + # Do not forget to copy test files in current binary dir file(COPY "${CMAKE_SOURCE_DIR}/data/points/alphacomplexdoc.off" DESTINATION ${CMAKE_CURRENT_BINARY_DIR}/) +file(COPY "${CMAKE_SOURCE_DIR}/data/distance_matrix/lower_triangular_distance_matrix.csv" DESTINATION ${CMAKE_CURRENT_BINARY_DIR}/) +file(COPY "${CMAKE_SOURCE_DIR}/data/distance_matrix/full_square_distance_matrix.csv" DESTINATION ${CMAKE_CURRENT_BINARY_DIR}/) # Unitary tests add_test(poffreader_UT ${CMAKE_CURRENT_BINARY_DIR}/poffreader_UT # XML format for Jenkins xUnit plugin --log_format=XML --log_sink=${CMAKE_SOURCE_DIR}/poffreader_UT.xml --log_level=test_suite --report_level=no) +add_test(distancematrixreader_UT ${CMAKE_CURRENT_BINARY_DIR}/distancematrixreader_UT + # XML format for Jenkins xUnit plugin + --log_format=XML --log_sink=${CMAKE_SOURCE_DIR}/distancematrixreader_UT.xml --log_level=test_suite --report_level=no) + diff --git a/src/common/test/test_distance_matrix_reader.cpp b/src/common/test/test_distance_matrix_reader.cpp new file mode 100644 index 00000000..95a73bd9 --- /dev/null +++ b/src/common/test/test_distance_matrix_reader.cpp @@ -0,0 +1,85 @@ +/* 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): Vincent Rouvreau + * + * Copyright (C) 2016 INRIA + * + * 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/>. + */ + +#include <gudhi/reader_utils.h> + +#include <iostream> +#include <string> +#include <vector> + +#define BOOST_TEST_DYN_LINK +#define BOOST_TEST_MODULE "distance_matrix_reader" +#include <boost/test/unit_test.hpp> + +using Distance_matrix = std::vector<std::vector<double>>; + +BOOST_AUTO_TEST_CASE( lower_triangular_distance_matrix ) +{ + Distance_matrix from_lower_triangular; + // Read lower_triangular_distance_matrix.csv file where the separator is a ',' + from_lower_triangular = read_lower_triangular_matrix_from_csv_file<double>("lower_triangular_distance_matrix.csv", + ','); + for (auto& i : from_lower_triangular) { + for (auto j : i) { + std::cout << j << " "; + } + std::cout << std::endl; + } + std::cout << "from_lower_triangular size = " << from_lower_triangular.size() << std::endl; + BOOST_CHECK(from_lower_triangular.size() == 5); + + for (std::size_t i = 0; i < from_lower_triangular.size(); i++) { + std::cout << "from_lower_triangular[" << i << "] size = " << from_lower_triangular[i].size() << std::endl; + BOOST_CHECK(from_lower_triangular[i].size() == i); + } + std::vector<double> expected = {1}; + BOOST_CHECK(from_lower_triangular[1] == expected); + + expected = {2,3}; + BOOST_CHECK(from_lower_triangular[2] == expected); + + expected = {4,5,6}; + BOOST_CHECK(from_lower_triangular[3] == expected); + + expected = {7,8,9,10}; + BOOST_CHECK(from_lower_triangular[4] == expected); + +} + +BOOST_AUTO_TEST_CASE( full_square_distance_matrix ) +{ + Distance_matrix from_full_square; + // Read full_square_distance_matrix.csv file where the separator is the default one ';' + from_full_square = read_lower_triangular_matrix_from_csv_file<double>("full_square_distance_matrix.csv"); + for (auto& i : from_full_square) { + for (auto j : i) { + std::cout << j << " "; + } + std::cout << std::endl; + } + std::cout << "from_full_square size = " << from_full_square.size() << std::endl; + BOOST_CHECK(from_full_square.size() == 7); + for (std::size_t i = 0; i < from_full_square.size(); i++) { + std::cout << "from_full_square[" << i << "] size = " << from_full_square[i].size() << std::endl; + BOOST_CHECK(from_full_square[i].size() == i); + } +} diff --git a/src/common/test/test_points_off_reader.cpp b/src/common/test/test_points_off_reader.cpp index b4f71182..0a78d190 100644 --- a/src/common/test/test_points_off_reader.cpp +++ b/src/common/test/test_points_off_reader.cpp @@ -4,7 +4,7 @@ * * Author(s): Vincent Rouvreau * - * Copyright (C) 2015 INRIA Saclay (France) + * Copyright (C) 2015 * * 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 |
