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-/* This file is part of the Gudhi Library. The Gudhi library
- * (Geometric Understanding in Higher Dimensions) is a generic C++
- * library for computational topology.
- *
- * Author(s): Vincent Rouvreau
- *
- * Copyright (C) 2018 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_CECH_COMPLEX_INTRO_CECH_COMPLEX_H_
-#define DOC_CECH_COMPLEX_INTRO_CECH_COMPLEX_H_
-
-namespace Gudhi {
-
-namespace cech_complex {
-
-/** \defgroup cech_complex Čech complex
- *
- * \author Vincent Rouvreau
- *
- * @{
- *
- * \section cechdefinition Čech complex definition
- *
- * Čech complex
- * <a target="_blank" href="https://en.wikipedia.org/wiki/%C4%8Cech_cohomology">(Wikipedia)</a> is a
- * <a target="_blank" href="https://en.wikipedia.org/wiki/Simplicial_complex">simplicial complex</a> constructed
- * from a proximity graph. The set of all simplices is filtered by the radius of their minimal enclosing ball.
- *
- * The input shall be a point cloud in an Euclidean space.
- *
- * \remark For people only interested in the topology of the \ref cech_complex (for instance persistence),
- * \ref alpha_complex is equivalent to the \ref cech_complex and much smaller if you do not bound the radii.
- * \ref cech_complex can still make sense in higher dimension precisely because you can bound the radii.
- *
- * \subsection cechalgorithm Algorithm
- *
- * Cech_complex first builds a proximity graph from a point cloud.
- * The filtration value of each edge of the `Gudhi::Proximity_graph` is computed from
- * `Gudhi::Minimal_enclosing_ball_radius` function.
- *
- * All edges that have a filtration value strictly greater than a user given maximal radius value, \f$max\_radius\f$,
- * are not inserted into the complex.
- *
- * Vertex name correspond to the index of the point in the given range (aka. the point cloud).
- *
- * \image html "cech_one_skeleton.png" "Čech complex proximity graph representation"
- *
- * When creating a simplicial complex from this proximity graph, Cech_complex inserts the proximity graph into the
- * simplicial complex data structure, and then expands the simplicial complex when required.
- *
- * On this example, as edges \f$(x,y)\f$, \f$(y,z)\f$ and \f$(z,y)\f$ are in the complex, the minimal ball radius
- * containing the points \f$(x,y,z)\f$ is computed.
- *
- * \f$(x,y,z)\f$ is inserted to the simplicial complex with the filtration value set with
- * \f$mini\_ball\_radius(x,y,z))\f$ iff \f$mini\_ball\_radius(x,y,z)) \leq max\_radius\f$.
- *
- * And so on for higher dimensions.
- *
- * \image html "cech_complex_representation.png" "Čech complex expansion"
- *
- * The minimal ball radius computation is insured by
- * <a target="_blank" href="https://people.inf.ethz.ch/gaertner/subdir/software/miniball.html">
- * the miniball software (V3.0)</a> - Smallest Enclosing Balls of Points - and distributed with GUDHI.
- * Please refer to
- * <a target="_blank" href="https://people.inf.ethz.ch/gaertner/subdir/texts/own_work/esa99_final.pdf">
- * the miniball software design description</a> for more information about this computation.
- *
- * This radius computation is the reason why the Cech_complex is taking much more time to be computed than the
- * \ref rips_complex but it offers more topological guarantees.
- *
- * If the Cech_complex interfaces are not detailed enough for your need, please refer to
- * <a href="_cech_complex_2cech_complex_step_by_step_8cpp-example.html">
- * cech_complex_step_by_step.cpp</a> example, where the graph construction over the Simplex_tree is more detailed.
- *
- * \subsection cechpointscloudexample Example from a point cloud
- *
- * This example builds the proximity graph from the given points, and maximal radius values.
- * Then it creates a `Simplex_tree` with it.
- *
- * Then, it is asked to display information about the simplicial complex.
- *
- * \include Cech_complex/cech_complex_example_from_points.cpp
- *
- * When launching (maximal enclosing ball radius is 1., is expanded until dimension 2):
- *
- * \code $> ./Cech_complex_example_from_points
- * \endcode
- *
- * the program output is:
- *
- * \include Cech_complex/cech_complex_example_from_points_for_doc.txt
- *
- */
-/** @} */ // end defgroup cech_complex
-
-} // namespace cech_complex
-
-} // namespace Gudhi
-
-#endif // DOC_CECH_COMPLEX_INTRO_CECH_COMPLEX_H_