Use markdown for main page. Fix some doxyfile

2 files changed, 286 insertions, 184 deletions

diff --git a/src/Doxyfile.in b/src/Doxyfile.in
index 1c293d1c..54a438d4 100644
--- a/src/Doxyfile.in
+++ b/src/Doxyfile.in
@@ -208,7 +208,7 @@ SEPARATE_MEMBER_PAGES  = NO
 # uses this value to replace tabs by spaces in code fragments.
 # Minimum value: 1, maximum value: 16, default value: 4.
 
-TAB_SIZE               = 4
+TAB_SIZE               = 2
 
 # This tag can be used to specify a number of aliases that act as commands in
 # the documentation. An alias has the form:
@@ -889,7 +889,7 @@ FILTER_SOURCE_PATTERNS =
 # (index.html). This can be useful if you have a project on for instance GitHub
 # and want to reuse the introduction page also for the doxygen output.
 
-USE_MDFILE_AS_MAINPAGE =
+USE_MDFILE_AS_MAINPAGE = doc/common/main_page.md
 
 #---------------------------------------------------------------------------
 # Configuration options related to source browsing
@@ -1147,7 +1147,7 @@ HTML_DYNAMIC_SECTIONS  = NO
 # Minimum value: 0, maximum value: 9999, default value: 100.
 # This tag requires that the tag GENERATE_HTML is set to YES.
 
-HTML_INDEX_NUM_ENTRIES = 100
+HTML_INDEX_NUM_ENTRIES = 2
 
 # If the GENERATE_DOCSET tag is set to YES, additional index files will be
 # generated that can be used as input for Apple's Xcode 3 integrated development
diff --git a/src/common/doc/main_page.h b/src/common/doc/main_page.md
index afe9b68c..61efd582 100644
--- a/src/common/doc/main_page.h
+++ b/src/common/doc/main_page.md
@@ -1,261 +1,289 @@
-/*! \mainpage The C++ library
- *  \tableofcontents
- * \image html "Gudhi_banner.png" "" width=20cm
- * 
- * \section Introduction Introduction
- * The GUDHI library (Geometry Understanding in Higher Dimensions) is a generic open source
- * <a class="el" target="_blank" href="http://gudhi.gforge.inria.fr/doc/latest/">C++ library</a> for
- * Computational Topology and Topological Data Analysis
- * (<a class="el" target="_blank" href="https://en.wikipedia.org/wiki/Topological_data_analysis">TDA</a>).
- * The GUDHI library intends  to help the development of new algorithmic solutions in TDA and their transfer to
- * applications. It provides robust, efficient, flexible and easy to use implementations of state-of-the-art
- * algorithms and data structures.
- * 
- * The current release of the GUDHI library includes:
- * 
- * \li Data structures to represent, construct and manipulate simplicial complexes.
- * \li Simplification of simplicial complexes by edge contraction.
- * \li Algorithms to compute persistent homology and bottleneck distance.
- * 
- * All data-structures are generic and several of their aspects can be parameterized via template classes.
- * We refer to \cite gudhilibrary_ICMS14 for a detailed description of the design of the library.
- *
- \section DataStructures Data structures
- \subsection AlphaComplexDataStructure Alpha complex
- \image html "alpha_complex_representation.png" "Alpha complex representation"
-<table border="0">
+[TOC]
+
+# The C++ library {#main_page}
+\image html "Gudhi_banner.png"
+<br><br><br><br>
+
+## Complexes {#Complexes}
+### Cubical complex
+ 
+<table>
   <tr>
-    <td width="25%">
-      <b>Author:</b> Vincent Rouvreau<br>
+    <td width="35%" rowspan=2>
+      \image html "Cubical_complex_representation.png"
+    </td>
+    <td width="50%">
+    The cubical complex is an example of a structured complex useful in computational mathematics (specially
+    rigorous numerics) and image analysis.<br>
+    </td>
+    <td width="15%">
+      <b>Author:</b> Pawel Dlotko<br>
       <b>Introduced in:</b> GUDHI 1.3.0<br>
       <b>Copyright:</b> GPL v3<br>
-      <b>Requires:</b> \ref eigen3 and<br>
-      \ref cgal &ge; 4.7.0 for Alpha_complex<br>
-      \ref cgal &ge; 4.11.0 for Alpha_complex_3d
     </td>
-    <td width="75%">
-    Alpha_complex is a simplicial complex constructed from the finite cells of a Delaunay Triangulation.<br>
+ </tr>
+ <tr>
+    <td colspan=2 height="100">
+    <b>User manual:</b> \ref cubical_complex - <b>Reference manual:</b> Gudhi::cubical_complex::Bitmap_cubical_complex
+    </td>
+ </tr>
+</table>
+
+### Simplicial complex
+
+#### Alpha complex
+
+<table>
+  <tr>
+    <td width="35%" rowspan=2>
+      \image html "alpha_complex_representation.png"
+    </td>
+    <td width="50%">
+    Alpha complex is a simplicial complex constructed from the finite cells of a Delaunay Triangulation.<br>
     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.<br>
+    </td>
+    <td width="15%">
+      <b>Author:</b> Vincent Rouvreau<br>
+      <b>Introduced in:</b> GUDHI 1.3.0<br>
+      <b>Copyright:</b> GPL v3<br>
+      <b>Requires:</b> \ref eigen3 and<br>
+      \ref cgal &ge; 4.7.0 for Alpha_complex<br>
+      \ref cgal &ge; 4.11.0 for Alpha_complex_3d
+    </td>
+ </tr>
+ <tr>
+    <td colspan=2 height="100">
     <b>User manual:</b> \ref alpha_complex - <b>Reference manual:</b> Gudhi::alpha_complex::Alpha_complex and
     Gudhi::alpha_complex::Alpha_complex_3d
     </td>
  </tr>
 </table>
- \subsection CechComplexDataStructure Čech complex
- \image html "cech_complex_representation.png" "Čech complex representation"
-<table border="0">
-  <tr>
-    <td width="25%">
+
+#### Čech complex
+
+<table>
+ <tr>
+    <td width="35%" rowspan=2>
+      \image html "cech_complex_representation.png"
+    </td>
+    <td width="50%">
+    The Čech complex is a simplicial complex constructed from a proximity graph.
+    The set of all simplices is filtered by the radius of their minimal enclosing ball.
+    </td>
+    <td width="15%">
       <b>Author:</b> Vincent Rouvreau<br>
       <b>Introduced in:</b> GUDHI 2.2.0<br>
       <b>Copyright:</b> GPL v3<br>
     </td>
-    <td width="75%">
-    The Čech complex is a simplicial complex constructed from a proximity graph.<br>
-    The set of all simplices is filtered by the radius of their minimal enclosing ball.<br>
+ </tr>
+ <tr>
+    <td colspan=2 height="100">
     <b>User manual:</b> \ref cech_complex - <b>Reference manual:</b> Gudhi::cech_complex::Cech_complex
     </td>
  </tr>
 </table>
- \subsection CubicalComplexDataStructure Cubical complex
- \image html "Cubical_complex_representation.png" "Cubical complex representation"
-<table border="0">
+
+#### Rips complex
+
+<table>
   <tr>
-    <td width="25%">
-      <b>Author:</b> Pawel Dlotko<br>
-      <b>Introduced in:</b> GUDHI 1.3.0<br>
-      <b>Copyright:</b> GPL v3<br>
+    <td width="35%" rowspan=2>
+      \image html "rips_complex_representation.png"
     </td>
-    <td width="75%">
-    The cubical complex is an example of a structured complex useful in computational mathematics (specially
-    rigorous numerics) and image analysis.<br>
-    <b>User manual:</b> \ref cubical_complex - <b>Reference manual:</b> Gudhi::cubical_complex::Bitmap_cubical_complex
+    <td width="50%">
+    Rips_complex is a simplicial complex constructed from a one skeleton graph.<br>
+    The filtration value of each edge is computed from a user-given distance function and is inserted until a
+    user-given threshold value.<br>
+    This complex can be built from a point cloud and a distance function, or from a distance matrix.
     </td>
- </tr>
-</table>
- \subsection RipsComplexDataStructure Rips complex
- \image html "rips_complex_representation.png" "Rips complex representation"
-<table border="0">
-  <tr>
-    <td width="25%">
+    <td width="15%">
       <b>Author:</b> Cl&eacute;ment Maria, Pawel Dlotko, Vincent Rouvreau, Marc Glisse<br>
       <b>Introduced in:</b> GUDHI 2.0.0<br>
       <b>Copyright:</b> GPL v3<br>
     </td>
-    <td width="75%">
-    Rips_complex is a simplicial complex constructed from a one skeleton graph.<br>
-    The filtration value of each edge is computed from a user-given distance function and is inserted until a
-    user-given threshold value.<br>
-    This complex can be built from a point cloud and a distance function, or from a distance matrix.<br>
+ </tr>
+ <tr>
+    <td colspan=2 height="100">
     <b>User manual:</b> \ref rips_complex - <b>Reference manual:</b> Gudhi::rips_complex::Rips_complex
     </td>
  </tr>
 </table>
- \subsection SimplexTreeDataStructure Simplex tree
- \image html "Simplex_tree_representation.png" "Simplex tree representation"
-<table border="0">
+
+#### Witness complex
+
+<table>
   <tr>
-    <td width="25%">
-      <b>Author:</b> Cl&eacute;ment Maria<br>
-      <b>Introduced in:</b> GUDHI 1.0.0<br>
+    <td width="35%" rowspan=2>
+      \image html "Witness_complex_representation.png"
+    </td>
+    <td width="50%">
+    Witness complex \f$ Wit(W,L) \f$  is a simplicial complex defined on two sets of points in \f$\mathbb{R}^D\f$.
+    The data structure is described in \cite boissonnatmariasimplextreealgorithmica .
+    </td>
+    <td width="15%">
+      <b>Author:</b> Siargey Kachanovich<br>
+      <b>Introduced in:</b> GUDHI 1.3.0<br>
       <b>Copyright:</b> GPL v3<br>
+      <b>Euclidean version requires:</b> \ref cgal &ge; 4.6.0 and \ref eigen3
     </td>
-    <td width="75%">
-    The simplex tree is an efficient and flexible
- data structure for representing general (filtered) simplicial complexes. The data structure
- is described in \cite boissonnatmariasimplextreealgorithmica .<br>
-    <b>User manual:</b> \ref simplex_tree - <b>Reference manual:</b> Gudhi::Simplex_tree
+ </tr>
+ <tr>
+    <td colspan=2 height="100">
+    <b>User manual:</b> \ref witness_complex - <b>Reference manual:</b> Gudhi::witness_complex::SimplicialComplexForWitness
     </td>
  </tr>
 </table>
- \subsection CoverComplexDataStructure Cover Complexes
- \image html "gicvisu.jpg" "Graph Induced Complex of a point cloud."
-<table border="0">
+
+### Cover Complexes
+<table>
   <tr>
-    <td width="25%">
-      <b>Author:</b> Mathieu Carri&egrave;re<br>
-      <b>Introduced in:</b> GUDHI 2.1.0<br>
-      <b>Copyright:</b> GPL v3<br>
-      <b>Requires:</b> \ref cgal &ge; 4.8.1
+    <td width="35%" rowspan=2>
+      \image html "gicvisu.jpg"
     </td>
-    <td width="75%">
+    <td width="50%">
     Nerves and Graph Induced Complexes are cover complexes, i.e. simplicial complexes that provably contain
     topological information about the input data. They can be computed with a cover of the
     data, that comes i.e. from the preimage of a family of intervals covering the image
     of a scalar-valued function defined on the data. <br>
     <b>User manual:</b> \ref cover_complex - <b>Reference manual:</b> Gudhi::cover_complex::Cover_complex
     </td>
+    <td width="15%">
+      <b>Author:</b> Mathieu Carri&egrave;re<br>
+      <b>Introduced in:</b> GUDHI 2.1.0<br>
+      <b>Copyright:</b> GPL v3<br>
+      <b>Requires:</b> \ref cgal &ge; 4.8.1
+    </td>
+ </tr>
+ <tr>
+    <td colspan=2 height="100">
+    <b>User manual:</b> \ref cover_complex - <b>Reference manual:</b> Gudhi::cover_complex::Cover_complex
+    </td>
  </tr>
 </table>
- \subsection SkeletonBlockerDataStructure Skeleton blocker
- \image html "ds_representation.png" "Skeleton blocker representation"
-<table border="0">
+
+## Data structures and basic operations {#DataStructuresAndBasicOperations}
+
+### Data structures
+
+#### Simplex tree
+<table>
   <tr>
-    <td width="25%">
-      <b>Author:</b> David Salinas<br>
-      <b>Introduced in:</b> GUDHI 1.1.0<br>
+    <td width="35%" rowspan=2>
+      \image html "Simplex_tree_representation.png"
+    </td>
+    <td width="50%">
+    The simplex tree is an efficient and flexible
+ data structure for representing general (filtered) simplicial complexes. The data structure
+ is described in \cite boissonnatmariasimplextreealgorithmica .
+    </td>
+    <td width="15%">
+      <b>Author:</b> Cl&eacute;ment Maria<br>
+      <b>Introduced in:</b> GUDHI 1.0.0<br>
       <b>Copyright:</b> GPL v3<br>
     </td>
-    <td width="75%">
+ </tr>
+ <tr>
+    <td colspan=2 height="100">
+    <b>User manual:</b> \ref simplex_tree - <b>Reference manual:</b> Gudhi::Simplex_tree
+    </td>
+ </tr>
+</table>
+
+#### Skeleton blocker
+
+<table>
+  <tr>
+    <td width="35%" rowspan=2>
+      \image html "ds_representation.png"
+    </td>
+    <td width="50%">
     The Skeleton-Blocker data-structure proposes a light encoding for simplicial complexes by storing only an *implicit*
     representation of its simplices \cite socg_blockers_2011,\cite blockers2012. Intuitively, it just stores the
     1-skeleton of a simplicial complex with a graph and the set of its "missing faces" that is very small in practice.
     This data-structure handles all simplicial complexes operations such as simplex enumeration or simplex removal but
     operations that are particularly efficient are operations that do not require simplex enumeration such as edge
-    iteration, link computation or simplex contraction.<br>
-    <b>User manual:</b> \ref skbl - <b>Reference manual:</b> Gudhi::skeleton_blocker::Skeleton_blocker_complex
+    iteration, link computation or simplex contraction.
     </td>
- </tr>
-</table>
- \subsection TangentialComplexDataStructure Tangential complex
- \image html "tc_examples.png" "Tangential complex representation"
-<table border="0">
-  <tr>
-    <td width="25%">
-      <b>Author:</b> Cl&eacute;ment Jamin<br>
-      <b>Introduced in:</b> GUDHI 2.0.0<br>
+    <td width="15%">
+      <b>Author:</b> David Salinas<br>
+      <b>Introduced in:</b> GUDHI 1.1.0<br>
       <b>Copyright:</b> GPL v3<br>
-      <b>Requires:</b> \ref cgal &ge; 4.8.1 and \ref eigen3
     </td>
-    <td width="75%">
-    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$-dimensional manifold embedded in \f$ d \f$-dimensional Euclidean space. 
-    The input is a point sample coming from an unknown manifold.
-    The running time depends only linearly on the extrinsic dimension \f$ d \f$
-    and exponentially on the intrinsic dimension \f$ k \f$.<br>
-    <b>User manual:</b> \ref tangential_complex - <b>Reference manual:</b> Gudhi::tangential_complex::Tangential_complex
+ </tr>
+ <tr>
+    <td colspan=2 height="100">
+    <b>User manual:</b> \ref skbl - <b>Reference manual:</b> Gudhi::skeleton_blocker::Skeleton_blocker_complex
     </td>
  </tr>
 </table>
- \subsection ToplexMapDataStructure Toplex Map
- \image html "map.png" "Toplex map representation"
-<table border="0">
+
+#### Toplex Map
+
+<table>
   <tr>
-    <td width="25%">
-      <b>Author:</b> Fran&ccedil;ois Godi<br>
-      <b>Introduced in:</b> GUDHI 2.1.0<br>
-      <b>Copyright:</b> GPL v3<br>
+    <td width="35%" rowspan=2>
+      \image html "map.png"
     </td>
-    <td width="75%">
+    <td width="50%">
     The Toplex map data structure is composed firstly of a raw storage of toplices (the maximal simplices)
     and secondly of a map which associate any vertex to a set of pointers toward all toplices
     containing this vertex.
-    <b>User manual:</b> \ref toplex_map - <b>Reference manual:</b> Gudhi::Toplex_map
-    </td>
- </tr>
-
- \subsection WitnessComplexDataStructure Witness complex
- \image html "Witness_complex_representation.png" "Witness complex representation"
-<table border="0">
-  <tr>
-    <td width="25%">
-      <b>Author:</b> Siargey Kachanovich<br>
-      <b>Introduced in:</b> GUDHI 1.3.0<br>
-      <b>Copyright:</b> GPL v3<br>
-      <b>Euclidean version requires:</b> \ref cgal &ge; 4.6.0 and \ref eigen3
     </td>
-    <td width="75%">
-    Witness complex \f$ Wit(W,L) \f$  is a simplicial complex defined on two sets of points in \f$\mathbb{R}^D\f$.
-    The data structure is described in \cite boissonnatmariasimplextreealgorithmica .<br>
-    <b>User manual:</b> \ref witness_complex - <b>Reference manual:</b> Gudhi::witness_complex::SimplicialComplexForWitness
-    </td>
- </tr>
-</table>
- 
- \section Toolbox Toolbox
- 
- \subsection BottleneckDistanceToolbox Bottleneck distance
- \image html "perturb_pd.png" "Bottleneck distance is the length of the longest edge"
-<table border="0">
-  <tr>
-    <td width="25%">
+    <td width="15%">
       <b>Author:</b> Fran&ccedil;ois Godi<br>
-      <b>Introduced in:</b> GUDHI 2.0.0<br>
+      <b>Introduced in:</b> GUDHI 2.1.0<br>
       <b>Copyright:</b> GPL v3<br>
-      <b>Requires:</b> \ref cgal &ge; 4.8.1
     </td>
-    <td width="75%">
-    Bottleneck distance measures the similarity between two persistence diagrams. 
-    It's the shortest distance b for which there exists a perfect matching between 
-    the points of the two diagrams (+ all the diagonal points) such that 
-    any couple of matched points are at distance at most b.
-    <br>
-    <b>User manual:</b> \ref bottleneck_distance
+ </tr>
+ <tr>
+    <td colspan=2 height="100">
+    <b>User manual:</b> \ref toplex_map - <b>Reference manual:</b> Gudhi::Toplex_map
     </td>
  </tr>
 </table>
- \subsection ContractionToolbox Contraction
- \image html "sphere_contraction_representation.png" "Sphere contraction example"
-<table border="0">
+
+### Basic operations
+
+#### Contraction
+
+<table>
   <tr>
-    <td width="25%">
+    <td width="35%" rowspan=2>
+      \image html "sphere_contraction_representation.png"
+    </td>
+    <td width="15%">
       <b>Author:</b> David Salinas<br>
       <b>Introduced in:</b> GUDHI 1.1.0<br>
       <b>Copyright:</b> GPL v3<br>
     </td>
-    <td width="75%">
+    <td width="50%">
     The purpose of this package is to offer a user-friendly interface for edge contraction simplification of huge
     simplicial complexes. It uses the \ref skbl data-structure whose size remains small  during simplification of most
     used geometrical complexes of topological data analysis such as the Rips or the Delaunay complexes. In practice,
-    the size of this data-structure is even much lower than the total number of simplices.<br>
+    the size of this data-structure is even much lower than the total number of simplices.
+    </td>
+ </tr>
+ <tr>
+    <td colspan=2 height="100">
     <b>User manual:</b> \ref contr
     </td>
  </tr>
 </table>
- \subsection PersistentCohomologyToolbox Persistent Cohomology
- \image html "3DTorus_poch.png" "Rips Persistent Cohomology on a 3D Torus"
-<table border="0">
+
+## Topological descriptors computation {#TopologicalDescriptorsComputation}
+
+### Persistent Cohomology
+
+<table>
   <tr>
-    <td width="25%">
-      <b>Author:</b> Cl&eacute;ment Maria<br>
-      <b>Introduced in:</b> GUDHI 1.0.0<br>
-      <b>Copyright:</b> GPL v3<br>
+    <td width="35%" rowspan=2>
+      \image html "3DTorus_poch.png"
     </td>
-    <td width="75%">
+    <td width="50%">
     The theory of homology consists in attaching to a topological space a sequence of (homology) groups, capturing
     global topological features like connected components, holes, cavities, etc. Persistent homology studies the
     evolution -- birth, life and death -- of these features when the topological space is changing. Consequently, the
@@ -263,27 +291,101 @@
     scheme.
     Computation of persistent cohomology using the algorithm of \cite DBLP:journals/dcg/SilvaMV11 and
     \cite DBLP:journals/corr/abs-1208-5018 and the Compressed Annotation Matrix implementation of
-    \cite DBLP:conf/esa/BoissonnatDM13 .<br>
+    \cite DBLP:conf/esa/BoissonnatDM13 .
+    </td>
+    <td width="15%">
+      <b>Author:</b> Cl&eacute;ment Maria<br>
+      <b>Introduced in:</b> GUDHI 1.0.0<br>
+      <b>Copyright:</b> GPL v3<br>
+    </td>
+ </tr>
+ <tr>
+    <td colspan=2 height="100">
     <b>User manual:</b> \ref persistent_cohomology - <b>Reference manual:</b> Gudhi::persistent_cohomology::Persistent_cohomology
     </td>
  </tr>
-</table> 
- \subsection PersistenceRepresentationsToolbox Persistence representations
- \image html "average_landscape.png" "Persistence representations"
-<table border="0">
+</table>
+
+## Manifold reconstruction {#ManifoldReconstruction}
+
+### Tangential complex
+
+<table>
+  <tr>
+    <td width="35%" rowspan=2>
+      \image html "tc_examples.png"
+    </td>
+    <td width="50%">
+    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$-dimensional manifold embedded in \f$ d \f$-dimensional Euclidean space. 
+    The input is a point sample coming from an unknown manifold.
+    The running time depends only linearly on the extrinsic dimension \f$ d \f$
+    and exponentially on the intrinsic dimension \f$ k \f$.
+    </td>
+    <td width="15%">
+      <b>Author:</b> Cl&eacute;ment Jamin<br>
+      <b>Introduced in:</b> GUDHI 2.0.0<br>
+      <b>Copyright:</b> GPL v3<br>
+      <b>Requires:</b> \ref cgal &ge; 4.8.1 and \ref eigen3
+    </td>
+ </tr>
+ <tr>
+    <td colspan=2 height="100">
+    <b>User manual:</b> \ref tangential_complex - <b>Reference manual:</b> Gudhi::tangential_complex::Tangential_complex
+    </td>
+ </tr>
+</table>
+
+## Topological descriptors tools {#TopologicalDescriptorsTools}
+
+### Bottleneck distance
+
+<table>
   <tr>
-    <td width="25%">
+    <td width="35%" rowspan=2>
+      \image html "perturb_pd.png"
+    </td>
+    <td width="50%">
+    Bottleneck distance measures the similarity between two persistence diagrams. 
+    It's the shortest distance b for which there exists a perfect matching between 
+    the points of the two diagrams (+ all the diagonal points) such that 
+    any couple of matched points are at distance at most b.
+    </td>
+    <td width="15%">
+      <b>Author:</b> Fran&ccedil;ois Godi<br>
+      <b>Introduced in:</b> GUDHI 2.0.0<br>
+      <b>Copyright:</b> GPL v3<br>
+      <b>Requires:</b> \ref cgal &ge; 4.8.1
+    </td>
+ </tr>
+ <tr>
+    <td colspan=2 height="100">
+    <b>User manual:</b> \ref bottleneck_distance
+    </td>
+ </tr>
+</table>
+
+### Persistence representations
+
+<table>
+  <tr>
+    <td width="35%" rowspan=2>
+      \image html "average_landscape.png"
+    </td>
+    <td width="50%">
+    It contains implementation of various representations of persistence diagrams; diagrams themselves, persistence
+    landscapes (rigorous and grid version), persistence heath maps, vectors and others. It implements basic
+    functionalities which are neccessary to use persistence in statistics and machine learning.
+    </td>
+    <td width="15%">
       <b>Author:</b> Pawel Dlotko<br>
       <b>Introduced in:</b> GUDHI 2.1.0<br>
       <b>Copyright:</b> GPL v3<br>      
     </td>
-    <td width="75%">
-    It contains implementation of various representations of persistence diagrams; diagrams themselves, persistence
-    landscapes (rigorous and grid version), persistence heath maps, vectors and others. It implements basic
-    functionalities which are neccessary to use persistence in statistics and machine learning.<br>
+ </tr>
+ <tr>
+    <td colspan=2 height="100">
     <b>User manual:</b> \ref Persistence_representations
     </td>
  </tr>
 </table>
- 
-*/