Merge graph_expansion_blocker fix from cech_complex branch

git-svn-id: svn+ssh://scm.gforge.inria.fr/svnroot/gudhi/trunk@2932 636b058d-ea47-450e-bf9e-a15bfbe3eedb

Former-commit-id: c6397609dbf92cad0fdd6c0fc5365b96657edec9

5 files changed, 323 insertions, 69 deletions

diff --git a/src/Persistent_cohomology/example/rips_persistence_step_by_step.cpp b/src/Persistent_cohomology/example/rips_persistence_step_by_step.cpp
index 554eeba6..c1de0ef8 100644
--- a/src/Persistent_cohomology/example/rips_persistence_step_by_step.cpp
+++ b/src/Persistent_cohomology/example/rips_persistence_step_by_step.cpp
@@ -45,14 +45,7 @@
 using Simplex_tree = Gudhi::Simplex_tree<Gudhi::Simplex_tree_options_fast_persistence>;
 using Vertex_handle = Simplex_tree::Vertex_handle;
 using Filtration_value = Simplex_tree::Filtration_value;
-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 >;
-
-template< typename InputPointRange, typename Distance >
-Graph_t compute_proximity_graph(InputPointRange &points, Filtration_value threshold, Distance distance);
+using Proximity_graph = Gudhi::Proximity_graph<Simplex_tree>;
 
 using Field_Zp = Gudhi::persistent_cohomology::Field_Zp;
 using Persistent_cohomology = Gudhi::persistent_cohomology::Persistent_cohomology<Simplex_tree, Field_Zp >;
@@ -81,8 +74,9 @@ int main(int argc, char * argv[]) {
   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
-                                               , Gudhi::Euclidean_distance());
+  Proximity_graph prox_graph = Gudhi::compute_proximity_graph<Simplex_tree>(off_reader.get_point_cloud(),
+                                                                            threshold,
+                                                                            Gudhi::Euclidean_distance());
 
   // Construct the Rips complex in a Simplex Tree
   Simplex_tree st;
@@ -170,48 +164,3 @@ void program_options(int argc, char * argv[]
     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, typename Distance >
-Graph_t compute_proximity_graph(InputPointRange &points, Filtration_value threshold, Distance distance) {
-  std::vector< Edge_t > edges;
-  std::vector< Filtration_value > edges_fil;
-
-  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 = distance(*it_u, *it_v);
-      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;
-}
diff --git a/src/Simplex_tree/example/CMakeLists.txt b/src/Simplex_tree/example/CMakeLists.txt
index 8bc4ad53..b33b2d05 100644
--- a/src/Simplex_tree/example/CMakeLists.txt
+++ b/src/Simplex_tree/example/CMakeLists.txt
@@ -34,6 +34,16 @@ 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)
+
+  add_executable ( Simplex_tree_example_cech_complex_cgal_mini_sphere_3d cech_complex_cgal_mini_sphere_3d.cpp )
+  target_link_libraries(Simplex_tree_example_cech_complex_cgal_mini_sphere_3d ${Boost_PROGRAM_OPTIONS_LIBRARY} ${CGAL_LIBRARY})
+  if (TBB_FOUND)
+    target_link_libraries(Simplex_tree_example_cech_complex_cgal_mini_sphere_3d ${TBB_LIBRARIES})
+  endif()
+  add_test(NAME Simplex_tree_example_cech_complex_cgal_mini_sphere_3d COMMAND $<TARGET_FILE:Simplex_tree_example_cech_complex_cgal_mini_sphere_3d>
+      "${CMAKE_SOURCE_DIR}/data/points/tore3D_300.off" -r 0.3 -d 3)
+
+  install(TARGETS Simplex_tree_example_alpha_shapes_3_from_off DESTINATION bin)
 endif()
 
 add_executable ( Simplex_tree_example_graph_expansion_with_blocker graph_expansion_with_blocker.cpp )
diff --git a/src/Simplex_tree/example/cech_complex_cgal_mini_sphere_3d.cpp b/src/Simplex_tree/example/cech_complex_cgal_mini_sphere_3d.cpp
new file mode 100644
index 00000000..217e251f
--- /dev/null
+++ b/src/Simplex_tree/example/cech_complex_cgal_mini_sphere_3d.cpp
@@ -0,0 +1,234 @@
+/*    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/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>
+
+// -------------------------------------------------------------------------------
+// cech_complex_cgal_mini_sphere_3d is an example of each step that is required to
+// build a Cech over a Simplex_tree. Please refer to cech_persistence to see
+// how to do the same thing with the Cech_complex wrapper for less detailed
+// steps.
+// -------------------------------------------------------------------------------
+
+// Types definition
+using Simplex_tree = Gudhi::Simplex_tree<>;
+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 < Gudhi::vertex_filtration_t, Filtration_value >
+, boost::property < Gudhi::edge_filtration_t, Filtration_value >
+>;
+using Edge_t = std::pair< Vertex_handle, Vertex_handle >;
+
+using Kernel = CGAL::Epick_d< CGAL::Dimension_tag<3> >;
+using Point = Kernel::Point_d;
+using Traits = CGAL::Min_sphere_of_points_d_traits_d<Kernel,Filtration_value,3>;
+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;
+#if DEBUG_TRACES
+    std::cout << "Cech_blocker on [";
+#endif  // DEBUG_TRACES
+    for (auto vertex : simplex_tree_.simplex_vertex_range(sh)) {
+      points.push_back(point_cloud_[vertex]);
+#if DEBUG_TRACES
+      std::cout << vertex << ", ";
+#endif  // DEBUG_TRACES
+    }
+    Min_sphere ms(points.begin(),points.end());
+    Filtration_value radius = ms.radius();
+#if DEBUG_TRACES
+    std::cout << "] - radius = " << radius << " - returns " << (radius > threshold_) << std::endl;
+#endif  // DEBUG_TRACES
+    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();
+
+#if DEBUG_TRACES
+  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 - dimension=" << st.dimension() << "\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;
+  }
+#endif  // DEBUG_TRACES
+  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 3d 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 Cech complex construction.")
+      ("cpx-dimension,d", po::value<int>(&dim_max)->default_value(1),
+       "Maximal dimension of the Cech 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(Gudhi::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;
+}
diff --git a/src/Simplex_tree/include/gudhi/Simplex_tree.h b/src/Simplex_tree/include/gudhi/Simplex_tree.h
index 7da767cb..5d8a90ee 100644
--- a/src/Simplex_tree/include/gudhi/Simplex_tree.h
+++ b/src/Simplex_tree/include/gudhi/Simplex_tree.h
@@ -1145,7 +1145,7 @@ class Simplex_tree {
         Siblings * new_sib = new Siblings(siblings,  // oncles
                                           simplex->first,  // parent
                                           boost::adaptors::reverse(intersection));  // boost::container::ordered_unique_range_t
-        std::vector<Simplex_handle> blocked_new_sib_list;
+        std::vector<Vertex_handle> blocked_new_sib_vertex_list;
         // As all intersections are inserted, we can call the blocker function on all new_sib members
         for (auto new_sib_member = new_sib->members().begin();
              new_sib_member != new_sib->members().end();
@@ -1153,17 +1153,19 @@ class Simplex_tree {
            bool blocker_result = block_simplex(new_sib_member);
            // new_sib member has been blocked by the blocker function
            // add it to the list to be removed - do not perform it while looping on it
-           if (blocker_result)
-             blocked_new_sib_list.push_back(new_sib_member);
+           if (blocker_result) {
+             blocked_new_sib_vertex_list.push_back(new_sib_member->first);
+           }
         }
-        bool removed = false;
-        for (auto& blocked_new_sib_member : blocked_new_sib_list){
-          removed = removed || remove_maximal_simplex(blocked_new_sib_member);
-        }
-        if (removed) {
+        if (blocked_new_sib_vertex_list.size() == new_sib->members().size()) {
+          // Specific case where all have to be deleted
+          delete new_sib;
           // ensure the children property
           simplex->second.assign_children(siblings);
         } else {
+          for (auto& blocked_new_sib_member : blocked_new_sib_vertex_list) {
+            new_sib->members().erase(blocked_new_sib_member);
+          }
           // ensure recursive call
           simplex->second.assign_children(new_sib);
           siblings_expansion_with_blockers(new_sib, max_dim, k - 1, block_simplex);
@@ -1338,16 +1340,14 @@ class Simplex_tree {
  public:
   /** \brief Remove a maximal simplex.
    * @param[in] sh Simplex handle on the maximal simplex to remove.
-   * @return a boolean value that is an implementation detail, and that the user is supposed to ignore
    * \pre Please check the simplex has no coface before removing it.
    * \exception std::invalid_argument In debug mode, if sh has children.
-   * \post Be aware that removing is shifting data in a flat_map (`initialize_filtration()` to be done).
+   * \post Be aware that removing is shifting data in a flat_map (initialize_filtration to be done).
    * \post Note that the dimension of the simplicial complex may be lower after calling `remove_maximal_simplex()`
    * than it was before. However, `upper_bound_dimension()` will return the old value, which remains a valid upper
    * bound. If you care, you can call `dimension()` to recompute the exact dimension.
-   * \internal @return true if the leaf's branch has no other leaves (branch's children has been re-assigned), false otherwise.
    */
-  bool remove_maximal_simplex(Simplex_handle sh) {
+  void remove_maximal_simplex(Simplex_handle sh) {
     // Guarantee the simplex has no children
     GUDHI_CHECK(!has_children(sh),
                 std::invalid_argument("Simplex_tree::remove_maximal_simplex - argument has children"));
@@ -1365,9 +1365,7 @@ class Simplex_tree {
       delete child;
       // dimension may need to be lowered
       dimension_to_be_lowered_ = true;
-      return true;
     }
-    return false;
   }
 
  private:
diff --git a/src/common/include/gudhi/graph_simplicial_complex.h b/src/common/include/gudhi/graph_simplicial_complex.h
index 5fe7c826..d84421b2 100644
--- a/src/common/include/gudhi/graph_simplicial_complex.h
+++ b/src/common/include/gudhi/graph_simplicial_complex.h
@@ -28,6 +28,9 @@
 #include <utility>  // for pair<>
 #include <vector>
 #include <map>
+#include <tuple>  // for std::tie
+
+namespace Gudhi {
 
 /* Edge tag for Boost PropertyGraph. */
 struct edge_filtration_t {
@@ -39,4 +42,64 @@ struct vertex_filtration_t {
   typedef boost::vertex_property_tag kind;
 };
 
+template <typename SimplicialComplexForProximityGraph>
+using Proximity_graph = typename boost::adjacency_list < boost::vecS, boost::vecS, boost::undirectedS
+, boost::property < vertex_filtration_t, typename SimplicialComplexForProximityGraph::Filtration_value >
+, boost::property < edge_filtration_t, typename SimplicialComplexForProximityGraph::Filtration_value >>;
+
+/** \brief Computes 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.
+ *
+ * \tparam ForwardPointRange furnishes `.begin()` and `.end()` methods.
+ *
+ * \tparam Distance furnishes `operator()(const Point& p1, const Point& p2)`, where
+ * `Point` is a point from the `ForwardPointRange`, and that returns a `Filtration_value`.
+ */
+template< typename SimplicialComplexForProximityGraph
+          , typename ForwardPointRange
+          , typename Distance >
+Proximity_graph<SimplicialComplexForProximityGraph> compute_proximity_graph(
+    const ForwardPointRange& points,
+    typename SimplicialComplexForProximityGraph::Filtration_value threshold,
+    Distance distance) {
+  using Vertex_handle = typename SimplicialComplexForProximityGraph::Vertex_handle;
+  using Filtration_value = typename SimplicialComplexForProximityGraph::Filtration_value;
+
+  std::vector<std::pair< Vertex_handle, Vertex_handle >> edges;
+  std::vector< Filtration_value > edges_fil;
+  std::map< Vertex_handle, Filtration_value > vertices;
+
+  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 = distance(*it_u, *it_v);
+      if (fil <= threshold) {
+        edges.emplace_back(idx_u, idx_v);
+        edges_fil.push_back(fil);
+      }
+    }
+    ++idx_u;
+  }
+
+  // Points are labeled from 0 to idx_u-1
+  Proximity_graph<SimplicialComplexForProximityGraph> skel_graph(edges.begin(), edges.end(), edges_fil.begin(), idx_u);
+
+  auto vertex_prop = boost::get(vertex_filtration_t(), skel_graph);
+
+  typename boost::graph_traits<Proximity_graph<SimplicialComplexForProximityGraph>>::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;
+}
+
+}  // namespace Gudhi
+
 #endif  // GRAPH_SIMPLICIAL_COMPLEX_H_