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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
+ *
+ * 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_TANGENTIAL_COMPLEX_INTRO_TANGENTIAL_COMPLEX_H_
+#define DOC_TANGENTIAL_COMPLEX_INTRO_TANGENTIAL_COMPLEX_H_
+
+// needs namespaces for Doxygen to link on classes
+namespace Gudhi {
+namespace tangential_complex {
+
+/** \defgroup tangential_complex Tangential complex
+
+\author Cl&eacute;ment Jamin
+
+@{
+
+\section tangentialdefinition Definition
+
+A Tangential Delaunay complex is a <a target="_blank" href="https://en.wikipedia.org/wiki/Simplicial_complex">simplicial complex</a>
+designed to reconstruct a \f$k\f$-dimensional smooth manifold embedded in \f$d\f$-dimensional Euclidean space.
+The input is a point sample coming from an unknown manifold, which means that the points lie close to a structure of "small" intrinsic dimension.
+The running time depends only linearly on the extrinsic dimension \f$ d \f$
+and exponentially on the intrinsic dimension \f$ k \f$.
+
+An extensive description of the Tangential complex can be found in \cite tangentialcomplex2014.
+
+\subsection whatisthetc What is a Tangential Complex?
+
+Let us start with the description of the Tangential complex of a simple example, with \f$ k=1 \f$ and \f$ d=2 \f$.
+The input data is 4 points \f$ P \f$ located on a curve embedded in 2D.
+\image html "tc_example_01.png" "The input"
+For each point \f$ p \f$, estimate its tangent subspace \f$ T_p \f$ (e.g. using PCA).
+\image html "tc_example_02.png" "The estimated normals"
+Let us add the Voronoi diagram of the points in orange. For each point \f$ p \f$, construct its star in the Delaunay triangulation of \f$ P \f$ restricted to \f$ T_p \f$.
+\image html "tc_example_03.png" "The Voronoi diagram"
+The Tangential Delaunay complex is the union of those stars.
+
+In practice, neither the ambient Voronoi diagram nor the ambient Delaunay triangulation is computed.
+Instead, local \f$ k \f$-dimensional regular triangulations are computed with a limited number of points as we only need the star of each point.
+More details can be found in \cite tangentialcomplex2014.
+
+\subsection inconsistencies Inconsistencies
+
+Inconsistencies between the stars can occur.
+An inconsistency occurs when a simplex is not in the star of all its vertices.
+
+Let us take the same example.
+\image html "tc_example_07_before.png" "Before"
+Let us slightly move the tangent subspace \f$ T_q \f$
+\image html "tc_example_07_after.png" "After"
+Now, the star of \f$ Q \f$ contains \f$ QP \f$, but the star of \f$ P \f$ does not contain \f$ QP \f$. We have an inconsistency.
+\image html "tc_example_08.png" "After"
+
+One way to solve inconsistencies is to randomly perturb the positions of the points involved in an inconsistency.
+In the current implementation, this perturbation is done in the tangent subspace of each point.
+The maximum perturbation radius is given as a parameter to the constructor.
+
+In most cases, we recommend to provide a point set where the minimum distance between any two points
+is not too small. This can be achieved using the functions provided by the Subsampling module. Then, a good value to start with for
+the maximum perturbation radius would be around half the minimum distance between any two points.
+The \ref example_with_perturb below shows an example of such a process.
+
+In most cases, this process is able to dramatically reduce the number of inconsistencies, but is not guaranteed to succeed.
+
+\subsection output Output
+
+The result of the computation is exported as a `Simplex_tree`. It is the union of the stars of all the input points.
+A vertex in the Simplex Tree is the index of the point in the range provided by the user.
+The point corresponding to a vertex can also be obtained through the `Tangential_complex::get_point` function.
+Note that even if the positions of the points are perturbed, their original positions are kept (e.g. `Tangential_complex::get_point` returns the original position of the point).
+
+The result can be obtained after the computation of the Tangential complex itself and/or after the perturbation process.
+
+\section simple_example Simple example
+
+This example builds the Tangential complex of point set.
+Note that the dimension of the kernel here is dynamic, which is slower, but more flexible:
+the intrinsic and ambient dimensions does not have to be known at compile-time.
+
+\include Tangential_complex/example_basic.cpp
+
+\section example_with_perturb Example with perturbation
+
+This example builds the Tangential complex of a point set, then tries to solve inconsistencies
+by perturbing the positions of points involved in inconsistent simplices.
+Note that the dimension of the kernel here is static, which is the best choice when the
+dimensions are known at compile-time.
+
+\include Tangential_complex/example_with_perturb.cpp
+
+\copyright GNU General Public License v3.
+\verbatim Contact: gudhi-users@lists.gforge.inria.fr \endverbatim
+ */
+/** @} */ // end defgroup tangential_complex
+
+} // namespace tangential_complex
+
+} // namespace Gudhi
+
+#endif // DOC_TANGENTIAL_COMPLEX_INTRO_TANGENTIAL_COMPLEX_H_