Merge master and resolve commits

4 files changed, 110 insertions, 89 deletions

diff --git a/src/python/include/Alpha_complex_factory.h b/src/python/include/Alpha_complex_factory.h
index d699ad9b..3d20aa8f 100644
--- a/src/python/include/Alpha_complex_factory.h
+++ b/src/python/include/Alpha_complex_factory.h
@@ -31,15 +31,34 @@ namespace Gudhi {
 
 namespace alpha_complex {
 
-template <typename CgalPointType>
-std::vector<double> pt_cgal_to_cython(CgalPointType const& point) {
-  std::vector<double> vd;
-  vd.reserve(point.dimension());
-  for (auto coord = point.cartesian_begin(); coord != point.cartesian_end(); coord++)
-    vd.push_back(CGAL::to_double(*coord));
-  return vd;
-}
+// template Functor that transforms a CGAL point to a vector of double as expected by cython
+template<typename CgalPointType, bool Weighted>
+struct Point_cgal_to_cython;
+
+// Specialized Unweighted Functor
+template<typename CgalPointType>
+struct Point_cgal_to_cython<CgalPointType, false> {
+  std::vector<double> operator()(CgalPointType const& point) const 
+  {
+    std::vector<double> vd;
+    vd.reserve(point.dimension());
+    for (auto coord = point.cartesian_begin(); coord != point.cartesian_end(); coord++)
+      vd.push_back(CGAL::to_double(*coord));
+    return vd;
+  }
+};
 
+// Specialized Weighted Functor
+template<typename CgalPointType>
+struct Point_cgal_to_cython<CgalPointType, true> {
+  std::vector<double> operator()(CgalPointType const& weighted_point) const 
+  {
+    const auto& point = weighted_point.point();
+    return Point_cgal_to_cython<decltype(point), false>()(point);
+  }
+};
+
+// Function that transforms a cython point (aka. a vector of double) to a CGAL point
 template <typename CgalPointType>
 static CgalPointType pt_cython_to_cgal(std::vector<double> const& vec) {
   return CgalPointType(vec.size(), vec.begin(), vec.end());
@@ -48,24 +67,38 @@ static CgalPointType pt_cython_to_cgal(std::vector<double> const& vec) {
 class Abstract_alpha_complex {
  public:
   virtual std::vector<double> get_point(int vh) = 0;
+
   virtual bool create_simplex_tree(Simplex_tree_interface<>* simplex_tree, double max_alpha_square,
                                    bool default_filtration_value) = 0;
+  
+  virtual std::size_t num_vertices() const = 0;
+
+  virtual ~Abstract_alpha_complex() = default;
 };
 
-class Exact_Alphacomplex_dD : public Abstract_alpha_complex {
+template <bool Weighted = false>
+class Exact_alpha_complex_dD final : public Abstract_alpha_complex {
  private:
   using Kernel = CGAL::Epeck_d<CGAL::Dynamic_dimension_tag>;
-  using Point = typename Kernel::Point_d;
+  using Bare_point = typename Kernel::Point_d;
+  using Point = std::conditional_t<Weighted, typename Kernel::Weighted_point_d,
+                                             typename Kernel::Point_d>;
 
  public:
-  Exact_Alphacomplex_dD(const std::vector<std::vector<double>>& points, bool exact_version)
+  Exact_alpha_complex_dD(const std::vector<std::vector<double>>& points, bool exact_version)
     : exact_version_(exact_version),
-      alpha_complex_(boost::adaptors::transform(points, pt_cython_to_cgal<Point>)) {
+      alpha_complex_(boost::adaptors::transform(points, pt_cython_to_cgal<Bare_point>)) {
+  }
+
+  Exact_alpha_complex_dD(const std::vector<std::vector<double>>& points,
+                           const std::vector<double>& weights, bool exact_version)
+    : exact_version_(exact_version),
+      alpha_complex_(boost::adaptors::transform(points, pt_cython_to_cgal<Bare_point>), weights) {
   }
 
   virtual std::vector<double> get_point(int vh) override {
-    Point const& point = alpha_complex_.get_point(vh);
-    return pt_cgal_to_cython(point);
+    // Can be a Weighted or a Bare point in function of Weighted
+    return Point_cgal_to_cython<Point, Weighted>()(alpha_complex_.get_point(vh));
   }
 
   virtual bool create_simplex_tree(Simplex_tree_interface<>* simplex_tree, double max_alpha_square,
@@ -73,65 +106,49 @@ class Exact_Alphacomplex_dD : public Abstract_alpha_complex {
     return alpha_complex_.create_complex(*simplex_tree, max_alpha_square, exact_version_, default_filtration_value);
   }
 
+  virtual std::size_t num_vertices() const {
+    return alpha_complex_.num_vertices();
+  }
+
  private:
   bool exact_version_;
-  Alpha_complex<Kernel> alpha_complex_;
+  Alpha_complex<Kernel, Weighted> alpha_complex_;
 };
 
-class Inexact_Alphacomplex_dD : public Abstract_alpha_complex {
+template <bool Weighted = false>
+class Inexact_alpha_complex_dD final : public Abstract_alpha_complex {
  private:
   using Kernel = CGAL::Epick_d<CGAL::Dynamic_dimension_tag>;
-  using Point = typename Kernel::Point_d;
+  using Bare_point = typename Kernel::Point_d;
+  using Point = std::conditional_t<Weighted, typename Kernel::Weighted_point_d,
+                                             typename Kernel::Point_d>;
 
  public:
-  Inexact_Alphacomplex_dD(const std::vector<std::vector<double>>& points, bool exact_version)
-    : exact_version_(exact_version),
-      alpha_complex_(boost::adaptors::transform(points, pt_cython_to_cgal<Point>)) {
+  Inexact_alpha_complex_dD(const std::vector<std::vector<double>>& points)
+    : alpha_complex_(boost::adaptors::transform(points, pt_cython_to_cgal<Bare_point>)) {
+  }
+
+  Inexact_alpha_complex_dD(const std::vector<std::vector<double>>& points, const std::vector<double>& weights)
+    : alpha_complex_(boost::adaptors::transform(points, pt_cython_to_cgal<Bare_point>), weights) {
   }
 
   virtual std::vector<double> get_point(int vh) override {
-    Point const& point = alpha_complex_.get_point(vh);
-    return pt_cgal_to_cython(point);
+    // Can be a Weighted or a Bare point in function of Weighted
+    return Point_cgal_to_cython<Point, Weighted>()(alpha_complex_.get_point(vh));
   }
   virtual bool create_simplex_tree(Simplex_tree_interface<>* simplex_tree, double max_alpha_square,
                                    bool default_filtration_value) override {
-    return alpha_complex_.create_complex(*simplex_tree, max_alpha_square, exact_version_, default_filtration_value);
+    return alpha_complex_.create_complex(*simplex_tree, max_alpha_square, false, default_filtration_value);
   }
 
- private:
-  bool exact_version_;
-  Alpha_complex<Kernel> alpha_complex_;
-};
-
-template <complexity Complexity>
-class Alphacomplex_3D : public Abstract_alpha_complex {
- private:
-  using Point = typename Alpha_complex_3d<Complexity, false, false>::Bare_point_3;
-
-  static Point pt_cython_to_cgal_3(std::vector<double> const& vec) {
-    return Point(vec[0], vec[1], vec[2]);
-  }
-
- public:
-  Alphacomplex_3D(const std::vector<std::vector<double>>& points)
-    : alpha_complex_(boost::adaptors::transform(points, pt_cython_to_cgal_3)) {
-  }
-
-  virtual std::vector<double> get_point(int vh) override {
-    Point const& point = alpha_complex_.get_point(vh);
-    return pt_cgal_to_cython(point);
-  }
-
-  virtual bool create_simplex_tree(Simplex_tree_interface<>* simplex_tree, double max_alpha_square,
-                           bool default_filtration_value) override {
-    return alpha_complex_.create_complex(*simplex_tree, max_alpha_square);
+  virtual std::size_t num_vertices() const {
+    return alpha_complex_.num_vertices();
   }
 
  private:
-  Alpha_complex_3d<Complexity, false, false> alpha_complex_;
+  Alpha_complex<Kernel, Weighted> alpha_complex_;
 };
 
-
 }  // namespace alpha_complex
 
 }  // namespace Gudhi
diff --git a/src/python/include/Alpha_complex_interface.h b/src/python/include/Alpha_complex_interface.h
index 23be194d..671af4a4 100644
--- a/src/python/include/Alpha_complex_interface.h
+++ b/src/python/include/Alpha_complex_interface.h
@@ -27,10 +27,23 @@ namespace alpha_complex {
 
 class Alpha_complex_interface {
  public:
-  Alpha_complex_interface(const std::vector<std::vector<double>>& points, bool fast_version, bool exact_version)
-  : points_(points),
-    fast_version_(fast_version),
-    exact_version_(exact_version) {
+  Alpha_complex_interface(const std::vector<std::vector<double>>& points,
+                          const std::vector<double>& weights,
+                          bool fast_version, bool exact_version) {
+    const bool weighted = (weights.size() > 0);
+    if (fast_version) {
+      if (weighted) {
+        alpha_ptr_ = std::make_unique<Inexact_alpha_complex_dD<true>>(points, weights);
+      } else {
+        alpha_ptr_ = std::make_unique<Inexact_alpha_complex_dD<false>>(points);
+      }
+    } else {
+      if (weighted) {
+        alpha_ptr_ = std::make_unique<Exact_alpha_complex_dD<true>>(points, weights, exact_version);
+      } else {
+        alpha_ptr_ = std::make_unique<Exact_alpha_complex_dD<false>>(points, exact_version);
+      }
+    }
   }
 
   std::vector<double> get_point(int vh) {
@@ -39,38 +52,13 @@ class Alpha_complex_interface {
 
   void create_simplex_tree(Simplex_tree_interface<>* simplex_tree, double max_alpha_square,
                            bool default_filtration_value) {
-    if (points_.size() > 0) {
-      std::size_t dimension = points_[0].size();
-      if (dimension == 3 && !default_filtration_value) {
-        if (fast_version_)
-          alpha_ptr_ = std::make_unique<Alphacomplex_3D<Gudhi::alpha_complex::complexity::FAST>>(points_);
-        else if (exact_version_)
-          alpha_ptr_ = std::make_unique<Alphacomplex_3D<Gudhi::alpha_complex::complexity::EXACT>>(points_);
-        else
-          alpha_ptr_ = std::make_unique<Alphacomplex_3D<Gudhi::alpha_complex::complexity::SAFE>>(points_);
-        if (!alpha_ptr_->create_simplex_tree(simplex_tree, max_alpha_square, default_filtration_value)) {
-          // create_simplex_tree will fail if all points are on a plane - Retry with dD by setting dimension to 2
-          dimension--;
-          alpha_ptr_.reset();
-        }
-      }
-      // Not ** else ** because we have to take into account if 3d fails
-      if (dimension != 3 || default_filtration_value) {
-        if (fast_version_) {
-          alpha_ptr_ = std::make_unique<Inexact_Alphacomplex_dD>(points_, exact_version_);
-        } else {
-          alpha_ptr_ = std::make_unique<Exact_Alphacomplex_dD>(points_, exact_version_);
-        }
-        alpha_ptr_->create_simplex_tree(simplex_tree, max_alpha_square, default_filtration_value);
-      }
-    }
+    // Nothing to be done in case of an empty point set
+    if (alpha_ptr_->num_vertices() > 0)
+      alpha_ptr_->create_simplex_tree(simplex_tree, max_alpha_square, default_filtration_value);
   }
 
  private:
   std::unique_ptr<Abstract_alpha_complex> alpha_ptr_;
-  std::vector<std::vector<double>> points_;
-  bool fast_version_;
-  bool exact_version_;
 };
 
 }  // namespace alpha_complex
diff --git a/src/python/include/Simplex_tree_interface.h b/src/python/include/Simplex_tree_interface.h
index dd8d715c..aa3dac18 100644
--- a/src/python/include/Simplex_tree_interface.h
+++ b/src/python/include/Simplex_tree_interface.h
@@ -15,7 +15,9 @@
 #include <gudhi/distance_functions.h>
 #include <gudhi/Simplex_tree.h>
 #include <gudhi/Points_off_io.h>
+#ifdef GUDHI_USE_EIGEN3
 #include <gudhi/Flag_complex_edge_collapser.h>
+#endif
 
 #include <iostream>
 #include <vector>
@@ -39,6 +41,7 @@ class Simplex_tree_interface : public Simplex_tree<SimplexTreeOptions> {
   using Skeleton_simplex_iterator = typename Base::Skeleton_simplex_iterator;
   using Complex_simplex_iterator = typename Base::Complex_simplex_iterator;
   using Extended_filtration_data = typename Base::Extended_filtration_data;
+  using Boundary_simplex_iterator = typename Base::Boundary_simplex_iterator;
   typedef bool (*blocker_func_t)(Simplex simplex, void *user_data);
 
  public:
@@ -162,6 +165,7 @@ class Simplex_tree_interface : public Simplex_tree<SimplexTreeOptions> {
   }
 
   Simplex_tree_interface* collapse_edges(int nb_collapse_iteration) {
+#ifdef GUDHI_USE_EIGEN3
     using Filtered_edge = std::tuple<Vertex_handle, Vertex_handle, Filtration_value>;
     std::vector<Filtered_edge> edges;
     for (Simplex_handle sh : Base::skeleton_simplex_range(1)) {
@@ -187,6 +191,9 @@ class Simplex_tree_interface : public Simplex_tree<SimplexTreeOptions> {
       collapsed_stree_ptr->insert({std::get<0>(remaining_edge), std::get<1>(remaining_edge)}, std::get<2>(remaining_edge));
     }
     return collapsed_stree_ptr;
+#else
+    throw std::runtime_error("Unable to collapse edges as it requires Eigen3 >= 3.1.0.");
+#endif
   }
 
   void expansion_with_blockers_callback(int dimension, blocker_func_t user_func, void *user_data) {
@@ -227,6 +234,15 @@ class Simplex_tree_interface : public Simplex_tree<SimplexTreeOptions> {
     // this specific case works because the range is just a pair of iterators - won't work if range was a vector
     return Base::skeleton_simplex_range(dimension).end();
   }
+
+  std::pair<Boundary_simplex_iterator, Boundary_simplex_iterator> get_boundary_iterators(const Simplex& simplex) {
+    auto bd_sh = Base::find(simplex);
+    if (bd_sh == Base::null_simplex())
+      throw std::runtime_error("simplex not found - cannot find boundaries");
+    // this specific case works because the range is just a pair of iterators - won't work if range was a vector
+    auto boundary_srange = Base::boundary_simplex_range(bd_sh);
+    return std::make_pair(boundary_srange.begin(), boundary_srange.end());
+  }
 };
 
 }  // namespace Gudhi
diff --git a/src/python/include/Subsampling_interface.h b/src/python/include/Subsampling_interface.h
index cdda851f..6aee7231 100644
--- a/src/python/include/Subsampling_interface.h
+++ b/src/python/include/Subsampling_interface.h
@@ -11,6 +11,7 @@
 #ifndef INCLUDE_SUBSAMPLING_INTERFACE_H_
 #define INCLUDE_SUBSAMPLING_INTERFACE_H_
 
+#include <gudhi/distance_functions.h>
 #include <gudhi/choose_n_farthest_points.h>
 #include <gudhi/pick_n_random_points.h>
 #include <gudhi/sparsify_point_set.h>
@@ -27,14 +28,13 @@ namespace subsampling {
 
 using Subsampling_dynamic_kernel = CGAL::Epick_d< CGAL::Dynamic_dimension_tag >;
 using Subsampling_point_d = Subsampling_dynamic_kernel::Point_d;
-using Subsampling_ft = Subsampling_dynamic_kernel::FT;
 
 // ------ choose_n_farthest_points ------
 std::vector<std::vector<double>> subsampling_n_farthest_points(const std::vector<std::vector<double>>& points,
                                                                unsigned nb_points) {
   std::vector<std::vector<double>> landmarks;
-  Subsampling_dynamic_kernel k;
-  choose_n_farthest_points(k, points, nb_points, random_starting_point, std::back_inserter(landmarks));
+  choose_n_farthest_points(Euclidean_distance(), points, nb_points,
+                           random_starting_point, std::back_inserter(landmarks));
 
   return landmarks;
 }
@@ -42,8 +42,8 @@ std::vector<std::vector<double>> subsampling_n_farthest_points(const std::vector
 std::vector<std::vector<double>> subsampling_n_farthest_points(const std::vector<std::vector<double>>& points,
                                                                unsigned nb_points, unsigned starting_point) {
   std::vector<std::vector<double>> landmarks;
-  Subsampling_dynamic_kernel k;
-  choose_n_farthest_points(k, points, nb_points, starting_point, std::back_inserter(landmarks));
+  choose_n_farthest_points(Euclidean_distance(), points, nb_points,
+                           starting_point, std::back_inserter(landmarks));
 
   return landmarks;
 }