Move minimal enclosing balls cache to Cech_complex.h instead of the blocker

Modify cech test to be more relevant regarding the current algorithm
Do some cleaning

2 files changed, 6 insertions, 17 deletions

diff --git a/src/common/include/gudhi/distance_functions.h b/src/common/include/gudhi/distance_functions.h
index ae5168aa..a8ee4a75 100644
--- a/src/common/include/gudhi/distance_functions.h
+++ b/src/common/include/gudhi/distance_functions.h
@@ -65,19 +65,17 @@ class Euclidean_distance {
  * The points are assumed to have the same dimension. */
 class Minimal_enclosing_ball_radius {
  public:
-   /** \brief TODO
+   /** \brief Enclosing ball radius from two points using CGAL.
    *
    * @param[in] point_1
    * @param[in] point_2
-   * @return
-   * \tparam Point
+   * @return Enclosing ball radius for the two points.
+   * \tparam Point must be a Kernel::Point_d from CGAL.
    *
    */
-  //typename FT = typename Kernel::FT,
   template< typename Kernel = CGAL::Epeck_d<CGAL::Dynamic_dimension_tag>,
             typename Point= typename Kernel::Point_d>
   double operator()(const Point& point_1, const Point& point_2) const {
-    std::clog << "Added template: distance betw points 1 and 2" << std::endl;
     Kernel kernel_;
     return std::sqrt(CGAL::to_double(kernel_.squared_distance_d_object()(point_1, point_2))) / 2.;
   }
@@ -94,25 +92,21 @@ class Minimal_enclosing_ball_radius {
   template< typename Point >
   typename std::iterator_traits<typename boost::range_iterator<Point>::type>::value_type
   operator()(const Point& point_1, const Point& point_2) const {
-    std::clog << "Hind: Minimal_enclosing_ball_radius point1 et 2; Euclidean" << std::endl;
     std::clog << "#" << *point_1.begin() << "##" << *point_2.begin() << std::endl;
     return Euclidean_distance()(point_1, point_2) / 2.;
   }
 
-
-  /** \brief TODO
+  /** \brief Enclosing ball radius from a point cloud using CGAL.
    *
    * @param[in] point_cloud The points.
-   * @return
-   * \tparam Point_cloud
+   * @return Enclosing ball radius for the points.
+   * \tparam Point_cloud must be a range of Kernel::Point_d points from CGAL.
    *
    */
-  //typename FT = typename Kernel::FT,
   template< typename Kernel = CGAL::Epeck_d<CGAL::Dynamic_dimension_tag>,
             typename Point= typename Kernel::Point_d,
             typename Point_cloud = std::vector<Point>>
   double operator()(const Point_cloud& point_cloud) const {
-    std::clog << "Added template: distance in point cloud" << std::endl;
     Kernel kernel_;
     return std::sqrt(CGAL::to_double(kernel_.compute_squared_radius_d_object()(point_cloud.begin(), point_cloud.end())));
   }
@@ -133,8 +127,6 @@ class Minimal_enclosing_ball_radius {
             typename Coordinate = typename std::iterator_traits<Coordinate_iterator>::value_type>
   Coordinate
   operator()(const Point_cloud& point_cloud) const {
-    std::clog << "Hind: Minimal_enclosing_ball_radius point cloud; Miniball" << std::endl;
-
     using Min_sphere = Miniball::Miniball<Miniball::CoordAccessor<Point_iterator, Coordinate_iterator>>;
 
     Min_sphere ms(boost::size(*point_cloud.begin()), point_cloud.begin(), point_cloud.end());
diff --git a/src/common/include/gudhi/graph_simplicial_complex.h b/src/common/include/gudhi/graph_simplicial_complex.h
index 9190182c..da9dee7d 100644
--- a/src/common/include/gudhi/graph_simplicial_complex.h
+++ b/src/common/include/gudhi/graph_simplicial_complex.h
@@ -18,8 +18,6 @@
 #include <map>
 #include <tuple>  // for std::tie
 
-#include <iostream>
-
 namespace Gudhi {
 /** @file
  * @brief Graph simplicial complex methods
@@ -78,7 +76,6 @@ Proximity_graph<SimplicialComplexForProximityGraph> compute_proximity_graph(
   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) {
-      std::clog << "#idx_u" << idx_u << "#idx_v " << idx_v << std::endl;
       fil = distance(*it_u, *it_v);
       if (fil <= threshold) {
         edges.emplace_back(idx_u, idx_v);