/* 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): ClĂ©ment Maria * * 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 * 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 . */ #ifndef DOC_SIMPLEX_TREE_INTRO_SIMPLEX_TREE_H_ #define DOC_SIMPLEX_TREE_INTRO_SIMPLEX_TREE_H_ // needs namespace for Doxygen to link on classes namespace Gudhi { /** \defgroup simplex_tree Filtered Complexes * @{ * \author Clément Maria * * A simplicial complex \f$\mathbf{K}\f$ on a set of vertices \f$V = \{1, \cdots ,|V|\}\f$ is a collection of * simplices \f$\{\sigma\}\f$, \f$\sigma \subseteq V\f$ such that * \f$\tau \subseteq \sigma \in \mathbf{K} \rightarrow \tau \in \mathbf{K}\f$. The dimension \f$n=|\sigma|-1\f$ of * \f$\sigma\f$ is its number of elements minus \f$1\f$. * * A filtration of a simplicial complex is a function \f$f:\mathbf{K} \rightarrow \mathbb{R}\f$ satisfying * \f$f(\tau)\leq f(\sigma)\f$ whenever \f$\tau \subseteq \sigma\f$. Ordering the simplices by increasing filtration * values (breaking ties so as a simplex appears after its subsimplices of same filtration value) provides an * indexing scheme. * * \section filteredcomplexesimplementation Implementations * \subsection filteredcomplexessimplextree Simplex tree * There are two implementation of complexes. The first on is the Simplex_tree data structure. The simplex tree is an * efficient and flexible data structure for representing general (filtered) simplicial complexes. The data structure * is described in \cite boissonnatmariasimplextreealgorithmica * \image html "Simplex_tree_representation.png" "Simplex tree representation" * * \subsubsection filteredcomplexessimplextreeexamples Examples * * Here is a list of simplex tree examples : * \li * Simplex_tree/simple_simplex_tree.cpp - Simple simplex tree construction and basic function use. * * \li * Simplex_tree/simplex_tree_from_cliques_of_graph.cpp - Simplex tree construction from cliques of graph read in * a file. * * Simplex tree construction with \f$\mathbb{Z}/3\mathbb{Z}\f$ coefficients on weighted graph Klein bottle file: * \code $> ./simplex_tree_from_cliques_of_graph ../../data/points/Klein_bottle_complex.txt 3 \endcode * \code Insert the 1-skeleton in the simplex tree in 0.000404 s. max_dim = 3 Expand the simplex tree in 3.8e-05 s. Information of the Simplex Tree: Number of vertices = 10 Number of simplices = 98 \endcode * * \li * Simplex_tree/example_alpha_shapes_3_simplex_tree_from_off_file.cpp - Simplex tree is computed and displayed * from a 3D alpha complex (Requires CGAL, GMP and GMPXX to be installed). * * \li * Simplex_tree/graph_expansion_with_blocker.cpp - Simple simplex tree construction from a one-skeleton graph with * a simple blocker expansion method. * * \subsection filteredcomplexeshassecomplex Hasse complex * The second one is the Hasse_complex. The Hasse complex is a data structure representing explicitly all co-dimension * 1 incidence relations in a complex. It is consequently faster when accessing the boundary of a simplex, but is less * compact and harder to construct from scratch. * * @} */ } // namespace Gudhi #endif // DOC_SIMPLEX_TREE_INTRO_SIMPLEX_TREE_H_