diff --git a/Surface_reconstruction_3/doc_tex/Surface_reconstruction_3_ref/APSS_implicit_function.tex b/Surface_reconstruction_3/doc_tex/Surface_reconstruction_3_ref/APSS_implicit_function.tex index 1a4e9d8e9a9..d23fe132c03 100644 --- a/Surface_reconstruction_3/doc_tex/Surface_reconstruction_3_ref/APSS_implicit_function.tex +++ b/Surface_reconstruction_3/doc_tex/Surface_reconstruction_3_ref/APSS_implicit_function.tex @@ -41,14 +41,13 @@ The full template declaration is: %START-AUTO(\ccParameters) template$<$ \\ -class Gt, \\ -class \ccc{PointWithNormal_3}$>$ \\ +class Gt$>$ \\ class \ccc{APSS_implicit_function}; \begin{description} \item[Parameters:] \begin{description} -\item[Gt]Geometric traits class. \item[\ccc{PointWithNormal_3}]Model of \ccc{PointWithNormal_3} concept. \end{description} +\item[Gt]Geometric traits class. \end{description} \end{description} %END-AUTO(\ccParameters) @@ -58,7 +57,7 @@ class \ccc{APSS_implicit_function}; % The section below is automatically generated. Do not edit! %START-AUTO(\ccIsModel) -Model of the \ccc{Reconstruction_implicit_function} concept. +Model of the ReconstructionImplicitFunction concept. %END-AUTO(\ccIsModel) @@ -99,12 +98,10 @@ Kernel's geometric traits. \ccGlue \ccNestedType{Point_with_normal} { -Model of \ccc{PointWithNormal_3} concept. } \ccGlue \ccNestedType{Normal} { -Model of \ccc{Kernel::Vector_3} concept. } \ccGlue \ccNestedType{Vector} @@ -123,7 +120,7 @@ Model of \ccc{Kernel::Vector_3} concept. \ccConstructor{APSS_implicit_function(InputIterator first, InputIterator beyond, unsigned int k, FT projection_error = 3.16e-4);} { Create an APSS implicit function from a point set. -Precondition: the value type of InputIterator must be convertible to \ccc{Point_with_normal}. +Precondition: the value type of InputIterator must be convertible to \ccc{Point_with_normal_3}. } \ccGlue \begin{description} @@ -132,7 +129,7 @@ Precondition: the value type of InputIterator must be convertible to \ccc{Point_ \item[first]First point of point set. \item[beyond]Past-the-end point of point set. \item[k]Number of nearest neighbours. \item[\ccc{projection_error}]Dichotomy error when projecting point. \end{description} \end{description} \ccGlue -\ccConstructor{APSS_implicit_function(const APSS_implicit_function& other);} +\ccConstructor{APSS_implicit_function(const APSS_implicit_function& other);} { } \ccGlue @@ -144,7 +141,7 @@ Precondition: the value type of InputIterator must be convertible to \ccc{Point_ % The section below is automatically generated. Do not edit! %START-AUTO(\ccOperations) -\ccMethod{APSS_implicit_function& operator=(const APSS_implicit_function& other);} +\ccMethod{APSS_implicit_function& operator=(const APSS_implicit_function& other);} { } \ccGlue diff --git a/Surface_reconstruction_3/doc_tex/Surface_reconstruction_3_ref/Lightweight_vector_3.tex b/Surface_reconstruction_3/doc_tex/Surface_reconstruction_3_ref/Lightweight_vector_3.tex index 3c71321ac5e..63258ff80ed 100644 --- a/Surface_reconstruction_3/doc_tex/Surface_reconstruction_3_ref/Lightweight_vector_3.tex +++ b/Surface_reconstruction_3/doc_tex/Surface_reconstruction_3_ref/Lightweight_vector_3.tex @@ -115,7 +115,7 @@ Vector is (0,0,0) by default. Copy constructor. } \ccGlue -\ccConstructor{Lightweight_vector_3(const Lightweight_vector_3& that);} +\ccConstructor{templateLightweight_vector_3(const Lightweight_vector_3& that);} { } \ccGlue @@ -225,18 +225,17 @@ Get (a copy of) the actual vector. %END-AUTO(\ccOperations) -\ccHeading{Friends And Related Functions} +\ccHeading{Related Functions} % The section below is automatically generated. Do not edit! -%START-AUTO(\ccHeading{Friends And Related Functions}) +%START-AUTO(\ccHeading{Related Functions}) \ccFunction{Vector operator*(FT c, const Lightweight_vector_3& vector);} { -[friend] \\ } \ccGlue -%END-AUTO(\ccHeading{Friends And Related Functions}) +%END-AUTO(\ccHeading{Related Functions}) \ccSeeAlso diff --git a/Surface_reconstruction_3/doc_tex/Surface_reconstruction_3_ref/Orientable_normal_3.tex b/Surface_reconstruction_3/doc_tex/Surface_reconstruction_3_ref/Orientable_normal_3.tex index a67cf32cea5..15654785e26 100644 --- a/Surface_reconstruction_3/doc_tex/Surface_reconstruction_3_ref/Orientable_normal_3.tex +++ b/Surface_reconstruction_3/doc_tex/Surface_reconstruction_3_ref/Orientable_normal_3.tex @@ -124,7 +124,7 @@ Normal vector is (0,0,0) by default. Normal is oriented by default. Copy constructor. } \ccGlue -\ccConstructor{Orientable_normal_3(const Orientable_normal_3& that);} +\ccConstructor{templateOrientable_normal_3(const Orientable_normal_3& that);} { } \ccGlue diff --git a/Surface_reconstruction_3/doc_tex/Surface_reconstruction_3_ref/Point_with_normal_3.tex b/Surface_reconstruction_3/doc_tex/Surface_reconstruction_3_ref/Point_with_normal_3.tex index f2643190457..04793edf703 100644 --- a/Surface_reconstruction_3/doc_tex/Surface_reconstruction_3_ref/Point_with_normal_3.tex +++ b/Surface_reconstruction_3/doc_tex/Surface_reconstruction_3_ref/Point_with_normal_3.tex @@ -132,7 +132,7 @@ Point is (0,0,0) by default. Normal is (0,0,0) by default. Normal is oriented by Copy constructor. } \ccGlue -\ccConstructor{Point_with_normal_3(const Point_with_normal_3& pwn);} +\ccConstructor{templatePoint_with_normal_3(const Point_with_normal_3& pwn);} { } \ccGlue diff --git a/Surface_reconstruction_3/doc_tex/Surface_reconstruction_3_ref/Poisson_implicit_function.tex b/Surface_reconstruction_3/doc_tex/Surface_reconstruction_3_ref/Poisson_implicit_function.tex index d307dc76ad7..a1be603b0a4 100644 --- a/Surface_reconstruction_3/doc_tex/Surface_reconstruction_3_ref/Poisson_implicit_function.tex +++ b/Surface_reconstruction_3/doc_tex/Surface_reconstruction_3_ref/Poisson_implicit_function.tex @@ -58,7 +58,7 @@ class \ccc{Poisson_implicit_function}; % The section below is automatically generated. Do not edit! %START-AUTO(\ccIsModel) -Model of the \ccc{Reconstruction_implicit_function} concept. +Model of the ReconstructionImplicitFunction concept. %END-AUTO(\ccIsModel) @@ -135,7 +135,7 @@ Create a Poisson indicator function f() piecewise-linear over the tetrahedra of \item[pdt]\ccc{ImplicitFctDelaunayTriangulation_3} base of the Poisson indicator function. \end{description} \end{description} \ccGlue -\ccConstructor{Poisson_implicit_function(Triangulation& pdt, InputIterator first, InputIterator beyond);} +\ccConstructor{templatePoisson_implicit_function(Triangulation& pdt, InputIterator first, InputIterator beyond);} { Create an implicit function from a point set. Insert the first...beyond point set into pdt and create a Poisson indicator function f() piecewise-linear over the tetrahedra of pdt. Precondition: the value type of InputIterator must be convertible to \ccc{Point_with_normal}. @@ -155,7 +155,7 @@ Precondition: the value type of InputIterator must be convertible to \ccc{Point_ % The section below is automatically generated. Do not edit! %START-AUTO(\ccOperations) -\ccMethod{int insert(InputIterator first, InputIterator beyond);} +\ccMethod{templateint insert(InputIterator first, InputIterator beyond);} { Insert points. Precondition: the value type of InputIterator must be convertible to \ccc{Point_with_normal}. diff --git a/Surface_reconstruction_3/doc_tex/Surface_reconstruction_3_ref/ReconstructionImplicitFunction.tex b/Surface_reconstruction_3/doc_tex/Surface_reconstruction_3_ref/ReconstructionImplicitFunction.tex index a90336ae1cf..549fe01def7 100644 --- a/Surface_reconstruction_3/doc_tex/Surface_reconstruction_3_ref/ReconstructionImplicitFunction.tex +++ b/Surface_reconstruction_3/doc_tex/Surface_reconstruction_3_ref/ReconstructionImplicitFunction.tex @@ -93,7 +93,7 @@ Model of \ccc{Kernel::Vector_3} concept. % The section below is automatically generated. Do not edit! %START-AUTO(\ccCreation) -\ccConstructor{ReconstructionImplicitFunction(InputIterator first, InputIterator beyond);} +\ccConstructor{templateReconstructionImplicitFunction(InputIterator first, InputIterator beyond);} { Create an implicit function from a point set. Precondition: the value type of InputIterator must be convertible to \ccc{Point_with_normal}. diff --git a/Surface_reconstruction_3/doc_tex/Surface_reconstruction_3_ref/average_spacing_3.tex b/Surface_reconstruction_3/doc_tex/Surface_reconstruction_3_ref/average_spacing_3.tex index 20ddfec6ece..a4ebfdcfac5 100644 --- a/Surface_reconstruction_3/doc_tex/Surface_reconstruction_3_ref/average_spacing_3.tex +++ b/Surface_reconstruction_3/doc_tex/Surface_reconstruction_3_ref/average_spacing_3.tex @@ -41,7 +41,7 @@ Precondition: KNN $>$= 2. \item[query]3D point whose spacing we want to compute \item[tree]KD-tree \item[KNN]number of neighbors \end{description} \end{description} \ccGlue -\ccFunction{Kernel::FT average_spacing_3(InputIterator first, InputIterator beyond, unsigned int KNN, const Kernel &);} +\ccFunction{Kernel::FT average_spacing_3(InputIterator first, InputIterator beyond, unsigned int KNN, const Kernel& );} { Compute average spacing from K nearest neighbors. This variant requires the kernel. Precondition: KNN $>$= 2. @@ -95,13 +95,13 @@ template$<$ \\ typename Kernel, \\ typename Tree$>$ \\ \ccc{Kernel::FT} \\ -\ccc{average_spacing_3} (const typename \ccc{Kernel::Point_3} \&query, Tree \&tree, unsigned int KNN); \\ +\ccc{average_spacing_3} (const typename \ccc{Kernel::Point_3}\& query, Tree\& tree, unsigned int KNN); \\ \\ template$<$ \\ typename InputIterator, \\ typename Kernel$>$ \\ \ccc{Kernel::FT} \\ -\ccc{average_spacing_3} (InputIterator first, InputIterator beyond, unsigned int KNN, const Kernel \&); \\ +\ccc{average_spacing_3} (InputIterator first, InputIterator beyond, unsigned int KNN, const Kernel\& ); \\ \\ template$<$ \\ typename InputIterator, \\ diff --git a/Surface_reconstruction_3/doc_tex/Surface_reconstruction_3_ref/estimate_normals_jet_fitting_3.tex b/Surface_reconstruction_3/doc_tex/Surface_reconstruction_3_ref/estimate_normals_jet_fitting_3.tex index 4cd902fce23..e5d1eeb5ec1 100644 --- a/Surface_reconstruction_3/doc_tex/Surface_reconstruction_3_ref/estimate_normals_jet_fitting_3.tex +++ b/Surface_reconstruction_3/doc_tex/Surface_reconstruction_3_ref/estimate_normals_jet_fitting_3.tex @@ -24,7 +24,7 @@ % The section below is automatically generated. Do not edit! %START-AUTO(\ccDefinition) -\ccFunction{OutputIterator estimate_normals_jet_fitting_3(InputIterator first, InputIterator beyond, OutputIterator normals, const unsigned int KNN, const Kernel &, const unsigned int degre_fitting = 2);} +\ccFunction{OutputIterator estimate_normals_jet_fitting_3(InputIterator first, InputIterator beyond, OutputIterator normals, const unsigned int KNN, const Kernel& , const unsigned int degre_fitting = 2);} { Estimate normal directions using jet fitting on the KNN nearest neighbors. This variant requires the kernel. Precondition: KNN $>$= 2. @@ -77,7 +77,7 @@ typename InputIterator, \\ typename OutputIterator, \\ typename Kernel$>$ \\ OutputIterator \\ -\ccc{estimate_normals_jet_fitting_3} (InputIterator first, InputIterator beyond, OutputIterator normals, const unsigned int KNN, const Kernel \&, const unsigned int \ccc{degre_fitting}=2); \\ +\ccc{estimate_normals_jet_fitting_3} (InputIterator first, InputIterator beyond, OutputIterator normals, const unsigned int KNN, const Kernel\& , const unsigned int \ccc{degre_fitting}=2); \\ \\ template$<$ \\ typename InputIterator, \\ diff --git a/Surface_reconstruction_3/doc_tex/Surface_reconstruction_3_ref/estimate_normals_pca_3.tex b/Surface_reconstruction_3/doc_tex/Surface_reconstruction_3_ref/estimate_normals_pca_3.tex index 67c4e7ae52e..3175f22d7b7 100644 --- a/Surface_reconstruction_3/doc_tex/Surface_reconstruction_3_ref/estimate_normals_pca_3.tex +++ b/Surface_reconstruction_3/doc_tex/Surface_reconstruction_3_ref/estimate_normals_pca_3.tex @@ -24,7 +24,7 @@ % The section below is automatically generated. Do not edit! %START-AUTO(\ccDefinition) -\ccFunction{OutputIterator estimate_normals_pca_3(InputIterator first, InputIterator beyond, OutputIterator normals, const unsigned int KNN, const Kernel &);} +\ccFunction{OutputIterator estimate_normals_pca_3(InputIterator first, InputIterator beyond, OutputIterator normals, const unsigned int KNN, const Kernel& );} { Estimate normals direction using linear least squares fitting of a plane on the K nearest neighbors. This variant requires the kernel. Precondition: KNN $>$= 2. @@ -77,7 +77,7 @@ typename InputIterator, \\ typename OutputIterator, \\ typename Kernel$>$ \\ OutputIterator \\ -\ccc{estimate_normals_pca_3} (InputIterator first, InputIterator beyond, OutputIterator normals, const unsigned int KNN, const Kernel \&); \\ +\ccc{estimate_normals_pca_3} (InputIterator first, InputIterator beyond, OutputIterator normals, const unsigned int KNN, const Kernel\& ); \\ \\ template$<$ \\ typename InputIterator, \\ diff --git a/Surface_reconstruction_3/doc_tex/Surface_reconstruction_3_ref/merge_epsilon_nearest_points_3.tex b/Surface_reconstruction_3/doc_tex/Surface_reconstruction_3_ref/merge_epsilon_nearest_points_3.tex index 709d45b7fb3..9baf9468ea0 100644 --- a/Surface_reconstruction_3/doc_tex/Surface_reconstruction_3_ref/merge_epsilon_nearest_points_3.tex +++ b/Surface_reconstruction_3/doc_tex/Surface_reconstruction_3_ref/merge_epsilon_nearest_points_3.tex @@ -22,7 +22,7 @@ % The section below is automatically generated. Do not edit! %START-AUTO(\ccDefinition) -\ccFunction{OutputIterator merge_epsilon_nearest_points_3(InputIterator first, InputIterator beyond, OutputIterator output, double epsilon, const Kernel &);} +\ccFunction{OutputIterator merge_epsilon_nearest_points_3(InputIterator first, InputIterator beyond, OutputIterator output, double epsilon, const Kernel& );} { Merge points which belong to the same cell of a grid of cell size = epsilon. This variant requires the kernel. Precondition: epsilon $>$ 0. @@ -41,7 +41,7 @@ Precondition: epsilon $>$ 0. \item[first]input points \item[output]output points \item[epsilon]tolerance value when comparing 3D points \end{description} \end{description} \ccGlue -\ccFunction{ForwardIterator merge_epsilon_nearest_points_3(ForwardIterator first, ForwardIterator beyond, double epsilon, const Kernel &);} +\ccFunction{ForwardIterator merge_epsilon_nearest_points_3(ForwardIterator first, ForwardIterator beyond, double epsilon, const Kernel& );} { Merge points which belong to the same cell of a grid of cell size = epsilon. This function is mutating the input point set. This variant requires the kernel. Warning: This method modifies the order of points, thus Precondition: epsilon $>$ 0. @@ -115,13 +115,13 @@ typename InputIterator, \\ typename OutputIterator, \\ typename Kernel$>$ \\ OutputIterator \\ -\ccc{merge_epsilon_nearest_points_3} (InputIterator first, InputIterator beyond, OutputIterator output, double epsilon, const Kernel \&); \\ +\ccc{merge_epsilon_nearest_points_3} (InputIterator first, InputIterator beyond, OutputIterator output, double epsilon, const Kernel\& ); \\ \\ template$<$ \\ typename ForwardIterator, \\ typename Kernel$>$ \\ ForwardIterator \\ -\ccc{merge_epsilon_nearest_points_3} (ForwardIterator first, ForwardIterator beyond, double epsilon, const Kernel \&); \\ +\ccc{merge_epsilon_nearest_points_3} (ForwardIterator first, ForwardIterator beyond, double epsilon, const Kernel\& ); \\ \\ template$<$ \\ typename InputIterator, \\ diff --git a/Surface_reconstruction_3/doc_tex/Surface_reconstruction_3_ref/remove_outliers_wrt_avg_knn_sq_distance_3.tex b/Surface_reconstruction_3/doc_tex/Surface_reconstruction_3_ref/remove_outliers_wrt_avg_knn_sq_distance_3.tex index 08a5cc43ce2..2e7145e64e6 100644 --- a/Surface_reconstruction_3/doc_tex/Surface_reconstruction_3_ref/remove_outliers_wrt_avg_knn_sq_distance_3.tex +++ b/Surface_reconstruction_3/doc_tex/Surface_reconstruction_3_ref/remove_outliers_wrt_avg_knn_sq_distance_3.tex @@ -22,7 +22,7 @@ % The section below is automatically generated. Do not edit! %START-AUTO(\ccDefinition) -\ccFunction{OutputIterator remove_outliers_wrt_avg_knn_sq_distance_3(InputIterator first, InputIterator beyond, OutputIterator output, unsigned int KNN, const Kernel &, double threshold_percent);} +\ccFunction{OutputIterator remove_outliers_wrt_avg_knn_sq_distance_3(InputIterator first, InputIterator beyond, OutputIterator output, unsigned int KNN, const Kernel& , double threshold_percent);} { Remove outliers:\begin{itemize} \item compute average squared distance to the K nearest neighbors,\item percentage of points to remove. This variant requires the kernel.\end{itemize} @@ -42,7 +42,7 @@ Precondition: KNN $>$= 2. \item[first]input points \item[output]output points \item[KNN]number of neighbors \item[\ccc{threshold_percent}]percentage of points to remove \end{description} \end{description} \ccGlue -\ccFunction{ForwardIterator remove_outliers_wrt_avg_knn_sq_distance_3(ForwardIterator first, ForwardIterator beyond, unsigned int KNN, const Kernel &, double threshold_percent);} +\ccFunction{ForwardIterator remove_outliers_wrt_avg_knn_sq_distance_3(ForwardIterator first, ForwardIterator beyond, unsigned int KNN, const Kernel& , double threshold_percent);} { Remove outliers:\begin{itemize} \item compute average squared distance to the K nearest neighbors,\item percentage of points to remove. This function is mutating the input point set. This variant requires the kernel.\end{itemize} @@ -119,13 +119,13 @@ typename InputIterator, \\ typename OutputIterator, \\ typename Kernel$>$ \\ OutputIterator \\ -\ccc{remove_outliers_wrt_avg_knn_sq_distance_3} (InputIterator first, InputIterator beyond, OutputIterator output, unsigned int KNN, const Kernel \&, double \ccc{threshold_percent}); \\ +\ccc{remove_outliers_wrt_avg_knn_sq_distance_3} (InputIterator first, InputIterator beyond, OutputIterator output, unsigned int KNN, const Kernel\& , double \ccc{threshold_percent}); \\ \\ template$<$ \\ typename ForwardIterator, \\ typename Kernel$>$ \\ ForwardIterator \\ -\ccc{remove_outliers_wrt_avg_knn_sq_distance_3} (ForwardIterator first, ForwardIterator beyond, unsigned int KNN, const Kernel \&, double \ccc{threshold_percent}); \\ +\ccc{remove_outliers_wrt_avg_knn_sq_distance_3} (ForwardIterator first, ForwardIterator beyond, unsigned int KNN, const Kernel\& , double \ccc{threshold_percent}); \\ \\ template$<$ \\ typename InputIterator, \\ diff --git a/Surface_reconstruction_3/doc_tex/Surface_reconstruction_3_ref/smooth_jet_fitting_3.tex b/Surface_reconstruction_3/doc_tex/Surface_reconstruction_3_ref/smooth_jet_fitting_3.tex index 3e12ee76947..1a6b1212b7a 100644 --- a/Surface_reconstruction_3/doc_tex/Surface_reconstruction_3_ref/smooth_jet_fitting_3.tex +++ b/Surface_reconstruction_3/doc_tex/Surface_reconstruction_3_ref/smooth_jet_fitting_3.tex @@ -41,7 +41,7 @@ Precondition: KNN $>$= 2. \item[query]3D point to project \item[tree]KD-tree \end{description} \end{description} \ccGlue -\ccFunction{OutputIterator smooth_jet_fitting_3(InputIterator first, InputIterator beyond, OutputIterator output, const unsigned int KNN, const Kernel &, const unsigned int degre_fitting = 2, const unsigned int degree_monge = 2);} +\ccFunction{OutputIterator smooth_jet_fitting_3(InputIterator first, InputIterator beyond, OutputIterator output, const unsigned int KNN, const Kernel& , const unsigned int degre_fitting = 2, const unsigned int degree_monge = 2);} { Smooth a point set using jet fitting on the KNN nearest neighbors and reprojection onto the jet. This variant requires the kernel. Precondition: KNN $>$= 2. @@ -60,7 +60,7 @@ Precondition: KNN $>$= 2. \item[first]input points \item[output]output points \item[KNN]number of neighbors \end{description} \end{description} \ccGlue -\ccFunction{void smooth_jet_fitting_3(ForwardIterator first, ForwardIterator beyond, unsigned int KNN, const Kernel &, const unsigned int degre_fitting = 2, const unsigned int degree_monge = 2);} +\ccFunction{void smooth_jet_fitting_3(ForwardIterator first, ForwardIterator beyond, unsigned int KNN, const Kernel& , const unsigned int degre_fitting = 2, const unsigned int degree_monge = 2);} { Smooth a point set using jet fitting on the KNN nearest neighbors and reprojection onto the jet. This function is mutating the input point set. This variant requires the kernel. Warning: This method moves the points, thus Precondition: KNN $>$= 2. @@ -124,20 +124,20 @@ template$<$ \\ typename Kernel, \\ typename Tree$>$ \\ \ccc{Kernel::Point_3} \\ -\ccc{smooth_jet_fitting_3} (const typename \ccc{Kernel::Point_3} \&query, Tree \&tree, const unsigned int KNN, const unsigned int \ccc{degre_fitting}, const unsigned int \ccc{degree_monge}); \\ +\ccc{smooth_jet_fitting_3} (const typename \ccc{Kernel::Point_3}\& query, Tree\& tree, const unsigned int KNN, const unsigned int \ccc{degre_fitting}, const unsigned int \ccc{degree_monge}); \\ \\ template$<$ \\ typename InputIterator, \\ typename OutputIterator, \\ typename Kernel$>$ \\ OutputIterator \\ -\ccc{smooth_jet_fitting_3} (InputIterator first, InputIterator beyond, OutputIterator output, const unsigned int KNN, const Kernel \&, const unsigned int \ccc{degre_fitting}=2, const unsigned int \ccc{degree_monge}=2); \\ +\ccc{smooth_jet_fitting_3} (InputIterator first, InputIterator beyond, OutputIterator output, const unsigned int KNN, const Kernel\& , const unsigned int \ccc{degre_fitting}=2, const unsigned int \ccc{degree_monge}=2); \\ \\ template$<$ \\ typename ForwardIterator, \\ typename Kernel$>$ \\ void \\ -\ccc{smooth_jet_fitting_3} (ForwardIterator first, ForwardIterator beyond, unsigned int KNN, const Kernel \&, const unsigned int \ccc{degre_fitting}=2, const unsigned int \ccc{degree_monge}=2); \\ +\ccc{smooth_jet_fitting_3} (ForwardIterator first, ForwardIterator beyond, unsigned int KNN, const Kernel\& , const unsigned int \ccc{degre_fitting}=2, const unsigned int \ccc{degree_monge}=2); \\ \\ template$<$ \\ typename InputIterator, \\ diff --git a/Surface_reconstruction_3/include/CGAL/APSS_implicit_function.h b/Surface_reconstruction_3/include/CGAL/APSS_implicit_function.h index 6512b3a0cce..628589f7cb2 100644 --- a/Surface_reconstruction_3/include/CGAL/APSS_implicit_function.h +++ b/Surface_reconstruction_3/include/CGAL/APSS_implicit_function.h @@ -42,7 +42,7 @@ CGAL_BEGIN_NAMESPACE /// See "Algebraic Point Set Surfaces" by Guennebaud and Gross (2007). /// /// @heading Is Model for the Concepts: -/// Model of the Reconstruction_implicit_function concept. +/// Model of the ReconstructionImplicitFunction concept. /// /// @heading Design Pattern: /// A model of ReconstructionImplicitFunction is a @@ -99,7 +99,7 @@ private: typedef Search_traits_3 TreeTraits; typedef Orthogonal_k_neighbor_search Neighbor_search; typedef typename Neighbor_search::Tree Tree; - typedef typename Neighbor_search::Point_with_transformed_distance + typedef typename Neighbor_search::Point_with_transformed_distance Point_with_transformed_distance; // Public methods @@ -141,13 +141,13 @@ public: FT maxdist2 = (--search.end())->second; // squared distance to furthest neighbor m->radii.push_back(sqrt(maxdist2)/2.); } - + // Compute barycenter, bounding box, bounding sphere and standard deviation. update_bounding_box(first, beyond); // Find a point inside the surface. find_inner_point(); - + // Dichotomy error when projecting point (squared) m->sqError = projection_error * projection_error * Gt().compute_squared_radius_3_object()(m->bounding_sphere); } @@ -259,7 +259,7 @@ public: FT operator()(const Point& p) const { // Is 'p' close to the surface? - // Optimization: test first if 'p' is close to one of the neighbors + // Optimization: test first if 'p' is close to one of the neighbors // computed during the previous call. typename Geom_traits::Compute_squared_distance_3 sqd; m->cached_nearest_neighbor.second = sqd(p, m->cached_nearest_neighbor.first); @@ -269,7 +269,7 @@ public: KdTreeElement query(p); Neighbor_search search_1nn(*(m->tree), query, 1); m->cached_nearest_neighbor = *(search_1nn.begin()); - + // Is 'p' close to the surface? if (!isValid(m->cached_nearest_neighbor, p)) { @@ -283,16 +283,16 @@ public: return length(h) * ( dot(n,h)>0. ? 1. : -1.); } } - + // Compute k nearest neighbors and cache the first one KdTreeElement query(p); Neighbor_search search_knn(*(m->tree), query, m->nofNeighbors); m->cached_nearest_neighbor = *(search_knn.begin()); - - // If 'p' is close to the surface, fit an algebraic sphere + + // If 'p' is close to the surface, fit an algebraic sphere // on a set of neigbors in a Moving Least Square sense. fit(search_knn); - + // return the distance to the sphere return m->as.euclideanDistance(p); } @@ -576,7 +576,7 @@ private: // Try random points until we find a point / value < 0 Point center = m->bounding_sphere.center(); FT radius = sqrt(m->bounding_sphere.squared_radius()); - CGAL::Random_points_in_sphere_3 rnd(radius); + CGAL::Random_points_in_sphere_3 rnd(radius); while (min_f > 0) { // Create random point in bounding sphere @@ -593,17 +593,17 @@ private: // Data members private: - struct Private + struct Private { Private() : tree(NULL), count(1) {} - + ~Private() { delete tree; tree = NULL; } - + Tree* tree; std::vector treeElements; std::vector radii; diff --git a/Surface_reconstruction_3/include/CGAL/Poisson_implicit_function.h b/Surface_reconstruction_3/include/CGAL/Poisson_implicit_function.h index 0adb8387eb0..a32f860006a 100644 --- a/Surface_reconstruction_3/include/CGAL/Poisson_implicit_function.h +++ b/Surface_reconstruction_3/include/CGAL/Poisson_implicit_function.h @@ -108,7 +108,7 @@ public: /// solver. One vertex must be constrained. /// /// @heading Is Model for the Concepts: -/// Model of the Reconstruction_implicit_function concept. +/// Model of the ReconstructionImplicitFunction concept. /// /// @heading Design Pattern: /// A model of ReconstructionImplicitFunction is a @@ -420,7 +420,7 @@ public: #endif m_dt.invalidate_bounding_box(); - + CGAL_TRACE("End of delaunay_refinement()\n"); return nb_vertices_added; @@ -673,7 +673,7 @@ public: { if(!v->constrained()) { - B[v->index()] = is_normalized ? div_normalized(v) + B[v->index()] = is_normalized ? div_normalized(v) : div(v); // rhs -> divergent assemble_poisson_row(solver,v,B,lambda); }