message: doc review: explain briefly test aims
diff: #include <gudhi/Simplex_tree.h>
  #include <gudhi/Unitary_tests_utils.h>
  -// Use dynamic_dimension_tag for the user to be able to set dimension
  -typedef CGAL::Epeck_d< CGAL::Dynamic_dimension_tag > Exact_kernel_d;
  -// Use static dimension_tag to set dimension at 4
  -typedef CGAL::Epeck_d< CGAL::Dimension_tag<4> > Exact_kernel_s;
  +using list_of_exact_kernel_variants = boost::mpl::list<CGAL::Epeck_d< CGAL::Dynamic_dimension_tag >,
  + CGAL::Epeck_d< CGAL::Dimension_tag<4> >
  + > ;
  -typedef boost::mpl::list<Exact_kernel_d, Exact_kernel_s> list_of_kernel_variants;
  +BOOST_AUTO_TEST_CASE_TEMPLATE(Zero_weighted_alpha_complex, Kernel, list_of_exact_kernel_variants) {
  + // Check that in exact mode for static dimension 4 the code for dD unweighted and for dD weighted with all weights
  + // 0 give exactly the same simplex tree (simplices and filtration values).
  -BOOST_AUTO_TEST_CASE_TEMPLATE(Zero_weighted_alpha_complex, Kernel, list_of_kernel_variants) {
  // Random points construction
  using Point_d = typename Kernel::Point_d;
  std::vector<Point_d> points;
  @@ -89,6 +89,8 @@ bool cgal_3d_point_sort (Point_d a,Point_d b) {
  }
  BOOST_AUTO_TEST_CASE(Weighted_alpha_complex_3d_comparison) {
  + // check that for random weighted 3d points in safe mode the 3D and dD codes give the same result with some tolerance
  +
  // Random points construction
  using Kernel_dD = CGAL::Epeck_d< CGAL::Dimension_tag<3> >;
  using Bare_point_d = typename Kernel_dD::Point_d;
  @@ -186,17 +188,25 @@ BOOST_AUTO_TEST_CASE(Weighted_alpha_complex_3d_comparison) {
  }
  }
  -BOOST_AUTO_TEST_CASE(Weighted_alpha_complex_non_visible_points) {
  - using Point_d = typename Exact_kernel_d::Point_d;
  +using list_of_1d_kernel_variants = boost::mpl::list<CGAL::Epeck_d< CGAL::Dynamic_dimension_tag >,
  + CGAL::Epeck_d< CGAL::Dimension_tag<1>>,
  + CGAL::Epick_d< CGAL::Dynamic_dimension_tag >,
  + CGAL::Epick_d< CGAL::Dimension_tag<1>>
  + >;
  +
  +BOOST_AUTO_TEST_CASE_TEMPLATE(Weighted_alpha_complex_non_visible_points, Kernel, list_of_1d_kernel_variants) {
  + // check that for 2 closed weighted 1-d points, one with a high weight to hide the second one with a small weight,
  + // that the point with a small weight has the same high filtration value than the edge formed by the 2 points
  + using Point_d = typename Kernel::Point_d;
  std::vector<Point_d> points;
  std::vector<double> p1 {0.};
  points.emplace_back(p1.begin(), p1.end());
  // closed enough points
  std::vector<double> p2 {0.1};
  points.emplace_back(p2.begin(), p2.end());
  - std::vector<typename Exact_kernel_d::FT> weights {100., 0.01};
  + std::vector<typename Kernel::FT> weights {100., 0.01};
  - Gudhi::alpha_complex::Alpha_complex<Exact_kernel_d, true> alpha_complex(points, weights);
  + Gudhi::alpha_complex::Alpha_complex<Kernel, true> alpha_complex(points, weights);
  Gudhi::Simplex_tree<> stree;
  BOOST_CHECK(alpha_complex.create_complex(stree));
  