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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) 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_ALPHA_COMPLEX_INTRO_ALPHA_COMPLEX_H_
#define DOC_ALPHA_COMPLEX_INTRO_ALPHA_COMPLEX_H_
// needs namespace for Doxygen to link on classes
namespace Gudhi {
// needs namespace for Doxygen to link on classes
namespace alpha_complex {
/** \defgroup alpha_complex Alpha complex
*
* \author Vincent Rouvreau
*
* @{
*
* \section definition Definition
*
* Alpha_complex is a <a target="_blank" href="https://en.wikipedia.org/wiki/Simplicial_complex">simplicial complex</a>
* constructed from the finite cells of a Delaunay Triangulation.
*
* The filtration value of each simplex is computed as the square of the circumradius of the simplex if the
* circumsphere is empty (the simplex is then said to be Gabriel), and as the minimum of the filtration
* values of the codimension 1 cofaces that make it not Gabriel otherwise.
*
* All simplices that have a filtration value strictly greater than a given alpha squared value are not inserted into
* the complex.
*
* \image html "alpha_complex_representation.png" "Alpha-complex representation"
*
* Alpha_complex is constructing a <a target="_blank"
* href="http://doc.cgal.org/latest/Triangulation/index.html#Chapter_Triangulations">Delaunay Triangulation</a>
* \cite cgal:hdj-t-15b from <a target="_blank" href="http://www.cgal.org/">CGAL</a> (the Computational Geometry
* Algorithms Library \cite cgal:eb-15b) and is able to create a `SimplicialComplexForAlpha`.
*
* The complex is a template class requiring an Epick_d <a target="_blank"
* href="http://doc.cgal.org/latest/Kernel_d/index.html#Chapter_dD_Geometry_Kernel">dD Geometry Kernel</a>
* \cite cgal:s-gkd-15b from CGAL as template parameter.
*
* \remark
* - When the simplicial complex is constructed with an infinite value of alpha, the complex is a Delaunay
* complex.
* - For people only interested in the topology of the \ref alpha_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.
*
* \section pointsexample Example from points
*
* This example builds the Delaunay triangulation from the given points in a 2D static kernel, and creates a
* `Simplex_tree` with it.
*
* Then, it is asked to display information about the simplicial complex.
*
* \include Alpha_complex/Alpha_complex_from_points.cpp
*
* When launching:
*
* \code $> ./Alpha_complex_example_from_points
* \endcode
*
* the program output is:
*
* \include Alpha_complex/alphaoffreader_for_doc_60.txt
*
* \section createcomplexalgorithm Create complex algorithm
*
* \subsection datastructure Data structure
*
* In order to create the simplicial complex, first, it is built from the cells of the Delaunay Triangulation.
* The filtration values are set to NaN, which stands for unknown value.
*
* In example, :
* \image html "alpha_complex_doc.png" "Simplicial complex structure construction example"
*
* \subsection filtrationcomputation Filtration value computation algorithm
* <br>
* \f$
* \textbf{for } \text{i : dimension } \rightarrow 0 \textbf{ do}\\
* \quad \textbf{for all } \sigma \text{ of dimension i}\\
* \quad\quad \textbf{if } \text{filtration(} \sigma ) \text{ is NaN} \textbf{ then}\\
* \quad\quad\quad \text{filtration(} \sigma ) = \alpha^2( \sigma )\\
* \quad\quad \textbf{end if}\\
* \quad\quad \textbf{for all } \tau \text{ face of } \sigma \textbf{ do}\quad\quad
* \textit{// propagate alpha filtration value}\\
* \quad\quad\quad \textbf{if } \text{filtration(} \tau ) \text{ is not NaN} \textbf{ then}\\
* \quad\quad\quad\quad \text{filtration(} \tau \text{) = min( filtration(} \tau \text{), filtration(} \sigma
* \text{) )}\\
* \quad\quad\quad \textbf{else}\\
* \quad\quad\quad\quad \textbf{if } \textbf{if } \tau \text{ is not Gabriel for } \sigma \textbf{ then}\\
* \quad\quad\quad\quad\quad \text{filtration(} \tau \text{) = filtration(} \sigma \text{)}\\
* \quad\quad\quad\quad \textbf{end if}\\
* \quad\quad\quad \textbf{end if}\\
* \quad\quad \textbf{end for}\\
* \quad \textbf{end for}\\
* \textbf{end for}\\
* \text{make_filtration_non_decreasing()}\\
* \text{prune_above_filtration()}\\
* \f$
*
* \subsubsection dimension2 Dimension 2
*
* From the example above, it means the algorithm looks into each triangle ([0,1,2], [0,2,4], [1,2,3], ...),
* computes the filtration value of the triangle, and then propagates the filtration value as described
* here :
* \image html "alpha_complex_doc_420.png" "Filtration value propagation example"
*
* \subsubsection dimension1 Dimension 1
*
* Then, the algorithm looks into each edge ([0,1], [0,2], [1,2], ...),
* computes the filtration value of the edge (in this case, propagation will have no effect).
*
* \subsubsection dimension0 Dimension 0
*
* Finally, the algorithm looks into each vertex ([0], [1], [2], [3], [4], [5] and [6]) and
* sets the filtration value (0 in case of a vertex - propagation will have no effect).
*
* \subsubsection nondecreasing Non decreasing filtration values
*
* As the squared radii computed by CGAL are an approximation, it might happen that these alpha squared values do not
* quite define a proper filtration (i.e. non-decreasing with respect to inclusion).
* We fix that up by calling `SimplicialComplexForAlpha::make_filtration_non_decreasing()`.
*
* \subsubsection pruneabove Prune above given filtration value
*
* The simplex tree is pruned from the given maximum alpha squared value (cf.
* `SimplicialComplexForAlpha::prune_above_filtration()`).
* In the following example, the value is given by the user as argument of the program.
*
*
* \section offexample Example from OFF file
*
* This example builds the Delaunay triangulation in a dynamic kernel, and initializes the alpha complex with it.
*
*
* Then, it is asked to display information about the alpha complex.
*
* \include Alpha_complex/Alpha_complex_from_off.cpp
*
* When launching:
*
* \code $> ./Alpha_complex_example_from_off ../../data/points/alphacomplexdoc.off 32.0
* \endcode
*
* the program output is:
*
* \include Alpha_complex/alphaoffreader_for_doc_32.txt
*
*/
/** @} */ // end defgroup alpha_complex
} // namespace alpha_complex
namespace alphacomplex = alpha_complex;
} // namespace Gudhi
#endif // DOC_ALPHA_COMPLEX_INTRO_ALPHA_COMPLEX_H_
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