Fix default filtration value given by the graph_expansion method with blocker

git-svn-id: svn+ssh://scm.gforge.inria.fr/svnroot/gudhi/branches/graph_expansion_with_blocker_oracle@2585 636b058d-ea47-450e-bf9e-a15bfbe3eedb

Former-commit-id: 38586e3c9a622c74c6b6658bdc0a6776c5ea5d5a

3 files changed, 12 insertions, 265 deletions

diff --git a/src/Simplex_tree/example/CMakeLists.txt b/src/Simplex_tree/example/CMakeLists.txt
index 7a30979f..4557deb3 100644
--- a/src/Simplex_tree/example/CMakeLists.txt
+++ b/src/Simplex_tree/example/CMakeLists.txt
@@ -34,25 +34,8 @@ if(GMP_FOUND AND CGAL_FOUND)
       "${CMAKE_SOURCE_DIR}/data/points/bunny_5000.off")
 
   install(TARGETS Simplex_tree_example_alpha_shapes_3_from_off DESTINATION bin)
-
-  #
-  # TO BE REMOVED !!
-  #
-
-  add_executable ( Simplex_tree_example_cech_complex_step_by_step cech_complex_step_by_step.cpp )
-  target_link_libraries(Simplex_tree_example_cech_complex_step_by_step ${GMP_LIBRARIES} ${CGAL_LIBRARY} ${Boost_SYSTEM_LIBRARY} ${Boost_PROGRAM_OPTIONS_LIBRARY})
-  if (TBB_FOUND)
-    target_link_libraries(Simplex_tree_example_cech_complex_step_by_step ${TBB_LIBRARIES})
-  endif()
-  add_test(NAME Simplex_tree_example_cech_complex_step_by_step COMMAND $<TARGET_FILE:Simplex_tree_example_cech_complex_step_by_step>
-      "${CMAKE_SOURCE_DIR}/data/points/alphacomplexdoc.off" "-d" "3" "-r" "6.0")
-
 endif()
 
-#
-# TO BE REMOVED !!
-#
-
 add_executable ( Simplex_tree_example_block block.cpp )
 if (TBB_FOUND)
   target_link_libraries(Simplex_tree_example_block ${TBB_LIBRARIES})
diff --git a/src/Simplex_tree/example/block.cpp b/src/Simplex_tree/example/block.cpp
index 75b8d1ea..67697b89 100644
--- a/src/Simplex_tree/example/block.cpp
+++ b/src/Simplex_tree/example/block.cpp
@@ -24,15 +24,13 @@
 #include <gudhi/Simplex_tree.h>
 
 #include <iostream>
-#include <utility>  // for pair
-#include <vector>
 
 using Simplex_tree = Gudhi::Simplex_tree<>;
 using Simplex_handle = Simplex_tree::Simplex_handle;
 
 int main(int argc, char * const argv[]) {
 
-  // Construct the Simplex Tree
+  // Construct the Simplex Tree with a 1-skeleton graph example
   Simplex_tree simplexTree;
 
   simplexTree.insert_simplex({0, 1}, 0.);
@@ -46,31 +44,27 @@ int main(int argc, char * const argv[]) {
   simplexTree.insert_simplex({4, 5}, 8.);
   simplexTree.insert_simplex({4, 6}, 9.);
   simplexTree.insert_simplex({5, 6}, 10.);
-  simplexTree.insert_simplex({6}, 11.);
-
-  std::cout << "********************************************************************\n";
-  std::cout << "* The complex contains " << simplexTree.num_simplices() << " simplices\n";
-  std::cout << "   - dimension " << simplexTree.dimension() << "   - filtration " << simplexTree.filtration() << "\n";
-  std::cout << "* Iterator on Simplices in the filtration, with [filtration value]:\n";
-  for (auto f_simplex : simplexTree.filtration_simplex_range()) {
-    std::cout << "   " << "[" << simplexTree.filtration(f_simplex) << "] ";
-    for (auto vertex : simplexTree.simplex_vertex_range(f_simplex))
-      std::cout << "(" << vertex << ")";
-    std::cout << std::endl;
-  }
+  simplexTree.insert_simplex({6}, 10.);
 
   simplexTree.expansion_with_blockers(3, [&](Simplex_handle sh){
       bool result = false;
+      std::cout << "Blocker on [";
+      // User can loop on the vertices from the given simplex_handle i.e.
       for (auto vertex : simplexTree.simplex_vertex_range(sh)) {
+        // We block the expansion, if the vertex '6' is in the given list of vertices
         if (vertex == 6)
           result = true;
-        std::cout << "#(" << vertex << ")#";
+        std::cout << vertex << ", ";
       }
-      std::cout << std::endl;
+      std::cout << "] ( " << simplexTree.filtration(sh);
+      // User can re-assign a new filtration value directly in the blocker (default is the maximal value of boudaries)
+      simplexTree.assign_filtration(sh, simplexTree.filtration(sh) + 1.);
+
+      std::cout << " + 1. ) = " << result << std::endl;
+
       return result;
     });
 
-  simplexTree.initialize_filtration();
   std::cout << "********************************************************************\n";
   std::cout << "* The complex contains " << simplexTree.num_simplices() << " simplices\n";
   std::cout << "   - dimension " << simplexTree.dimension() << "   - filtration " << simplexTree.filtration() << "\n";
diff --git a/src/Simplex_tree/example/cech_complex_step_by_step.cpp b/src/Simplex_tree/example/cech_complex_step_by_step.cpp
deleted file mode 100644
index 1805c792..00000000
--- a/src/Simplex_tree/example/cech_complex_step_by_step.cpp
+++ /dev/null
@@ -1,230 +0,0 @@
-/*    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):       Clément Maria
- *
- *    Copyright (C) 2014  INRIA Sophia Antipolis-Méditerranée (France)
- *
- *    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/>.
- */
-
-#include <gudhi/graph_simplicial_complex.h>
-#include <gudhi/distance_functions.h>
-#include <gudhi/Simplex_tree.h>
-#include <gudhi/Points_off_io.h>
-
-// #include <CGAL/Epick_d.h>
-// #include <CGAL/Euclidean_distance.h>
-// #include <CGAL/Search_traits_d.h>
-#include <CGAL/Epick_d.h>
-#include <CGAL/Min_sphere_of_spheres_d.h>
-#include <CGAL/Min_sphere_of_points_d_traits_d.h>
-
-#include <boost/program_options.hpp>
-
-#include <string>
-#include <vector>
-#include <limits>  // infinity
-#include <utility>  // for pair
-#include <map>
-
-// ----------------------------------------------------------------------------
-// rips_persistence_step_by_step is an example of each step that is required to
-// build a Rips over a Simplex_tree. Please refer to rips_persistence to see
-// how to do the same thing with the Rips_complex wrapper for less detailed
-// steps.
-// ----------------------------------------------------------------------------
-
-// Types definition
-using Simplex_tree = Gudhi::Simplex_tree<Gudhi::Simplex_tree_options_fast_persistence>;
-using Vertex_handle = Simplex_tree::Vertex_handle;
-using Simplex_handle = Simplex_tree::Simplex_handle;
-using Filtration_value = Simplex_tree::Filtration_value;
-using Siblings = Simplex_tree::Siblings;
-using Graph_t = boost::adjacency_list < boost::vecS, boost::vecS, boost::undirectedS
-, boost::property < vertex_filtration_t, Filtration_value >
-, boost::property < edge_filtration_t, Filtration_value >
->;
-using Edge_t = std::pair< Vertex_handle, Vertex_handle >;
-
-using Kernel = CGAL::Epick_d< CGAL::Dimension_tag<2> >;// CGAL::Dynamic_dimension_tag >;
-using Point = Kernel::Point_d;
-using Traits = CGAL::Min_sphere_of_points_d_traits_d<Kernel,Filtration_value,2>;
-using Min_sphere = CGAL::Min_sphere_of_spheres_d<Traits>;
-
-using Points_off_reader = Gudhi::Points_off_reader<Point>;
-
-class Cech_blocker {
- public:
-  bool operator()(Simplex_handle sh) {
-    std::vector<Point> points;
-    for (auto vertex : simplex_tree_.simplex_vertex_range(sh)) {
-      points.push_back(point_cloud_[vertex]);
-      std::cout << "#(" << vertex << ")#";
-    }
-    Min_sphere ms(points.begin(),points.end());
-    Filtration_value radius = ms.radius();
-    std::cout << "radius = " << radius << " - " << (radius > threshold_) << std::endl;
-    simplex_tree_.assign_filtration(sh, radius);
-    return (radius > threshold_);
-  }
-  Cech_blocker(Simplex_tree& simplex_tree, Filtration_value threshold, const std::vector<Point>& point_cloud)
-    : simplex_tree_(simplex_tree),
-      threshold_(threshold),
-      point_cloud_(point_cloud) { }
- private:
-  Simplex_tree simplex_tree_;
-  Filtration_value threshold_;
-  std::vector<Point> point_cloud_;
-};
-
-template< typename InputPointRange>
-Graph_t compute_proximity_graph(InputPointRange &points, Filtration_value threshold);
-
-void program_options(int argc, char * argv[]
-                     , std::string & off_file_points
-                     , Filtration_value & threshold
-                     , int & dim_max);
-
-int main(int argc, char * argv[]) {
-  std::string off_file_points;
-  Filtration_value threshold;
-  int dim_max;
-
-  program_options(argc, argv, off_file_points, threshold, dim_max);
-
-  // Extract the points from the file filepoints
-  Points_off_reader off_reader(off_file_points);
-
-  // Compute the proximity graph of the points
-  Graph_t prox_graph = compute_proximity_graph(off_reader.get_point_cloud(), threshold);
-
-  //Min_sphere sph1(off_reader.get_point_cloud()[0], off_reader.get_point_cloud()[1], off_reader.get_point_cloud()[2]);
-  // Construct the Rips complex in a Simplex Tree
-  Simplex_tree st;
-  // insert the proximity graph in the simplex tree
-  st.insert_graph(prox_graph);
-  // expand the graph until dimension dim_max
-  st.expansion_with_blockers(dim_max, Cech_blocker(st, threshold, off_reader.get_point_cloud()));
-
-  std::cout << "The complex contains " << st.num_simplices() << " simplices \n";
-  std::cout << "   and has dimension " << st.dimension() << " \n";
-
-  // Sort the simplices in the order of the filtration
-  st.initialize_filtration();
-
-  std::cout << "********************************************************************\n";
-  // Display the Simplex_tree - Can not be done in the middle of 2 inserts
-  std::cout << "* The complex contains " << st.num_simplices() << " simplices\n";
-  std::cout << "   - dimension " << st.dimension() << "   - filtration " << st.filtration() << "\n";
-  std::cout << "* Iterator on Simplices in the filtration, with [filtration value]:\n";
-  for (auto f_simplex : st.filtration_simplex_range()) {
-    std::cout << "   " << "[" << st.filtration(f_simplex) << "] ";
-    for (auto vertex : st.simplex_vertex_range(f_simplex)) {
-      std::cout << static_cast<int>(vertex) << " ";
-    }
-    std::cout << std::endl;
-  }
-
-  return 0;
-}
-
-void program_options(int argc, char * argv[]
-                     , std::string & off_file_points
-                     , Filtration_value & threshold
-                     , int & dim_max) {
-  namespace po = boost::program_options;
-  po::options_description hidden("Hidden options");
-  hidden.add_options()
-      ("input-file", po::value<std::string>(&off_file_points),
-       "Name of an OFF file containing a point set.\n");
-
-  po::options_description visible("Allowed options", 100);
-  visible.add_options()
-      ("help,h", "produce help message")
-      ("max-edge-length,r",
-       po::value<Filtration_value>(&threshold)->default_value(std::numeric_limits<Filtration_value>::infinity()),
-       "Maximal length of an edge for the Rips complex construction.")
-      ("cpx-dimension,d", po::value<int>(&dim_max)->default_value(1),
-       "Maximal dimension of the Rips complex we want to compute.");
-
-  po::positional_options_description pos;
-  pos.add("input-file", 1);
-
-  po::options_description all;
-  all.add(visible).add(hidden);
-
-  po::variables_map vm;
-  po::store(po::command_line_parser(argc, argv).
-            options(all).positional(pos).run(), vm);
-  po::notify(vm);
-
-  if (vm.count("help") || !vm.count("input-file")) {
-    std::cout << std::endl;
-    std::cout << "Construct a Cech complex defined on a set of input points.\n \n";
-
-    std::cout << "Usage: " << argv[0] << " [options] input-file" << std::endl << std::endl;
-    std::cout << visible << std::endl;
-    std::abort();
-  }
-}
-
-/** Output the proximity graph of the points.
- *
- * If points contains n elements, the proximity graph is the graph
- * with n vertices, and an edge [u,v] iff the distance function between
- * points u and v is smaller than threshold.
- *
- * The type PointCloud furnishes .begin() and .end() methods, that return
- * iterators with value_type Point.
- */
-template< typename InputPointRange>
-Graph_t compute_proximity_graph(InputPointRange &points, Filtration_value threshold) {
-  std::vector< Edge_t > edges;
-  std::vector< Filtration_value > edges_fil;
-
-  Kernel k;
-  Vertex_handle idx_u, idx_v;
-  Filtration_value fil;
-  idx_u = 0;
-  for (auto it_u = points.begin(); it_u != points.end(); ++it_u) {
-    idx_v = idx_u + 1;
-    for (auto it_v = it_u + 1; it_v != points.end(); ++it_v, ++idx_v) {
-      fil = k.squared_distance_d_object()(*it_u, *it_v);
-      // For Cech Complex, threshold is a radius (distance /2)
-      fil = std::sqrt(fil) / 2.;
-      if (fil <= threshold) {
-        edges.emplace_back(idx_u, idx_v);
-        edges_fil.push_back(fil);
-      }
-    }
-    ++idx_u;
-  }
-
-  Graph_t skel_graph(edges.begin()
-                     , edges.end()
-                     , edges_fil.begin()
-                     , idx_u);  // number of points labeled from 0 to idx_u-1
-
-  auto vertex_prop = boost::get(vertex_filtration_t(), skel_graph);
-
-  boost::graph_traits<Graph_t>::vertex_iterator vi, vi_end;
-  for (std::tie(vi, vi_end) = boost::vertices(skel_graph);
-       vi != vi_end; ++vi) {
-    boost::put(vertex_prop, *vi, 0.);
-  }
-
-  return skel_graph;
-}