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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): Clement Jamin
*
* Copyright (C) 2016 Inria
*
* Modification(s):
* - YYYY/MM Author: Description of the modification
*/
#ifndef DOC_SPATIAL_SEARCHING_INTRO_SPATIAL_SEARCHING_H_
#define DOC_SPATIAL_SEARCHING_INTRO_SPATIAL_SEARCHING_H_
// needs namespaces for Doxygen to link on classes
namespace Gudhi {
namespace spatial_searching {
/** \defgroup spatial_searching Spatial_searching
*
* \author Clément Jamin
*
* @{
*
* \section introduction Introduction
*
* This Gudhi component is a wrapper around
* <a target="_blank" href="http://doc.cgal.org/latest/Spatial_searching/index.html">CGAL dD spatial searching algorithms</a>.
* It provides a simplified API to perform (approximate) neighbor searches. Contrary to CGAL default behavior, the tree
* does not store the points themselves, but stores indices.
*
* For more details about the data structure or the algorithms, or for more advanced usages, reading
* <a target="_blank" href="http://doc.cgal.org/latest/Spatial_searching/index.html">CGAL documentation</a>
* is highly recommended.
*
* \section spatial_searching_examples Example
*
* This example generates 500 random points, then performs all-near-neighbors searches, and queries for nearest and furthest neighbors using different methods.
*
* \include Spatial_searching/example_spatial_searching.cpp
*
*/
/** @} */ // end defgroup spatial_searching
} // namespace spatial_searching
} // namespace Gudhi
#endif // DOC_SPATIAL_SEARCHING_INTRO_SPATIAL_SEARCHING_H_
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