mirror of https://github.com/CGAL/cgal
Added tparam to doc
This commit is contained in:
m.overtheil
parent
d9a132b72e
commit
1e6b69ccd9
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@ -9,7 +9,7 @@ To optimize distance computations squared distances are used.
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\cgalHeading{Parameters}
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Expects for the first template argument a model of the concept
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\tparam Traits must be a model of the concept
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`SearchTraits`, for example `Search_traits_2<Simple_cartesian<double> >`.
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\cgalModels `OrthogonalDistance`
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@ -11,7 +11,7 @@ Euclidean distance between a \f$ d\f$-dimensional sphere and a
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\cgalHeading{Parameters}
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Expects for the template argument a model of the concept `SearchTraits`,
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\tparam Traits must be a model of the concept `SearchTraits`,
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for example `Simple_cartesian_d<double>`.
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\cgalModels `GeneralDistance`
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@ -10,7 +10,7 @@ by a `d`-dim square with side length \f$ \epsilon\f$.
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\cgalHeading{Parameters}
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Expects for the template argument a model of the concept
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\tparam Traits must be a model of the concept
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`SearchTraits`, for example `CGAL::Search_traits_2<CGAL::Simple_cartesian<double> >`.
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\cgalModels `FuzzyQueryItem`
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@ -10,7 +10,7 @@ as inner approximation a sphere with radius \f$ r-\epsilon\f$.
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\cgalHeading{Parameters}
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Expects for the template argument a model of the concept
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\tparam Traits must be a model of the concept
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`SearchTraits`, for example `CGAL::Cartesian_d<double>`.
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\cgalModels `FuzzyQueryItem`
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@ -8,19 +8,19 @@ on a tree. The tree may have extended or unextended nodes.
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\cgalHeading{Parameters}
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Expects for the first template argument a model of the concept `SearchTraits`,
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\tparam Traits must be a model of the concept `SearchTraits`,
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for example `Search_traits_2<Simple_cartesian<double> >`.
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Expects for the second template argument a model of the
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\tparam GeneralDistance must be a model of the
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concept `GeneralDistance`. If `Traits` is
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`Search_traits_adapter<Key,PointPropertyMap,BaseTraits>`
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the default type is `Distance_adapter<Key,PointPropertyMap,Euclidean_distance<BaseTraits> >`,
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and `Euclidean_distance<Traits>` otherwise.
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Expects for third template argument a model of the concept `Splitter`.
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\tparam Splitter must be a model of the concept `Splitter`.
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The default type is `Sliding_midpoint<Traits>`.
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Expects for fourth template argument a model of the concept `SpatialTree`.
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\tparam SpatialTree must be a model of the concept `SpatialTree`.
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The default type is `Kd_tree<Traits,Splitter,Tag_false>`. The
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template argument `Tag_false` makes that the tree is built with unextended nodes.
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@ -9,16 +9,16 @@ extended or unextended nodes.
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\cgalHeading{Parameters}
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Expects for the first template argument an implementation of the concept `SearchTraits`,
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\tparam Traits must be an implementation of the concept `SearchTraits`,
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for example `Simple_cartesian<double>`.
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Expects for the second template argument a model of the
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\tparam Splitter must be a model of the
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concept `GeneralDistance`. If `Traits` is
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`Search_traits_adapter<Key,PointPropertyMap,BaseTraits>`
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the default type is `Distance_adapter<Key,PointPropertyMap,Euclidean_distance<BaseTraits> >`,
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and `Euclidean_distance<Traits>` otherwise.
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Expects for fourth template argument an implementation of the concept `SpatialTree`.
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\tparam SpatialTree must be an implementation of the concept `SpatialTree`.
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The default type is `Kd_tree<Traits, Splitter, Tag_false>`. The
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template argument `Tag_false` makes that the tree is built with unextended nodes.
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@ -15,9 +15,11 @@ along the node's cutting dimension.
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\cgalHeading{Parameters}
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Expects for the template argument a model of the concept `SearchTraits`,
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\tparam Traits must be a model of the concept `SearchTraits`,
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for example `Search_traits_2<Simple_cartesian<double> >`, or `Cartesian_d<double>`.
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\tparam Splitter must be a model of the concept `Splitter`.
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*/
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template< typename Traits, typename Splitter, typename UseExtendedNode >
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class Kd_tree_node {
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@ -12,7 +12,7 @@ and a `d`-dimensional iso-box defined as a `k-d` tree rectangle.
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\cgalHeading{Parameters}
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Expects for the template argument a model for the concept
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\tparam Traits must be a model for the concept
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`SearchTraits`, for example `Search_traits_3<Simple_cartesian<double> >`.
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\cgalModels `GeneralDistance`
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@ -7,19 +7,19 @@ The class `Orthogonal_incremental_neighbor_search` implements incremental neares
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\cgalHeading{Parameters}
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Expects for the first template argument a model of the concept `SearchTraits`,
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\tparam Traits must be a model of the concept `SearchTraits`,
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for example `Search_traits_2<Simple_cartesian<double> >`.
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Expects for the second template argument a model of the
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concept `GeneralDistance`. If `Traits` is
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\tparam OrthogonalDistance must be a model of the
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concept `OrthogonalDistance`. If `Traits` is
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`Search_traits_adapter<Key,PointPropertyMap,BaseTraits>`
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the default type is `Distance_adapter<Key,PointPropertyMap,Euclidean_distance<BaseTraits> >`,
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and `Euclidean_distance<Traits>` otherwise.
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Expects for third template argument a model of the concept `Splitter`.
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\tparam Splitter must be a model of the concept `Splitter`.
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The default type is `Sliding_midpoint<Traits>`.
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Expects for fourth template argument a model of the concept `SpatialTree`.
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\tparam SpatialTree must be a model of the concept `SpatialTree`.
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The default type is `Kd_tree<Traits, Splitter, Tag_true>`. The
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template argument must be `Tag_true` because orthogonal search needs extended
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kd tree nodes.
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@ -10,7 +10,7 @@ Added Dimension
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\cgalModifEnd
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\cgalHeading{Parameters}
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Expects for the template argument a model of the concept `Kernel`,
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\tparam Kernel must be a model of the concept `Kernel`,
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for example `Simple_cartesian<double>` or `Simple_cartesian<Gmpq>`.
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\cgalModels `SearchTraits`
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@ -10,7 +10,7 @@ Added Dimension
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\cgalModifEnd
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\cgalHeading{Parameters}
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Expects for the template argument a model of the concept `Kernel`,
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\tparam Kernel must be a model of the concept `Kernel`,
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for example `Simple_cartesian<double>` or `Simple_cartesian<Gmpq>`.
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\cgalModels `SearchTraits`
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@ -10,12 +10,12 @@ in a nearest neighbor search algorithm, this class must be used as distance.
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\cgalHeading{Parameters}
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`Key` is a type that is associated to a point of type `Base_distance::Point_d`.
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\tparam Key is a type that is associated to a point of type `Base_distance::Point_d`.
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`PointPropertyMap` is a model of `LvaluePropertyMap`
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\tparam PointPropertyMap is a model of `LvaluePropertyMap`
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with `Key` as `key_type` and `Base_distance::Point_d` as `value_type`.
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`Base_distance` is a model of either `GeneralDistance` or `OrthogonalDistance`.
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\tparam Base_distance is a model of either `GeneralDistance` or `OrthogonalDistance`.
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\cgalModels `GeneralDistance` if Base_distance is a model of `GeneralDistance`
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\cgalModels `OrthogonalDistance` if Base_distance is a model of `OrthogonalDistance`
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@ -12,8 +12,10 @@ Added Dimension
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\cgalHeading{Parameters}
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Expects for the first template argument a model of the concept `Kernel_d`
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(for example `Cartesian_d<double>`) and for the second argument a `Dimension_tag`
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\tparam Kernel must be a model of the concept `Kernel_d`
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(for example `Cartesian_d<double>`)
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\tparam Dim must be a `Dimension_tag`
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(default value is `Dynamic_dimension_tag`).
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\cgalModels `SearchTraits`
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@ -16,12 +16,12 @@ the ratio of the resulting rectangles.
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\cgalHeading{Parameters}
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Expects for the first template argument a model of
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\tparam Traits must be a model of
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the concept `SearchTraits`,
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for example `Simple_cartesian<double>`.
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Expects for the second template argument a model of the concept `SpatialSeparator`.
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It has as default value the type, `Plane_separator<Traits::FT>`.
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\tparam SpatialSeparator must be a model of the concept `SpatialSeparator`.
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It has as default value the type `Plane_separator<Traits::FT>`.
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\cgalModels `Splitter`
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@ -12,7 +12,7 @@ the transformed distance \f$ {\sigma_{i=1}^{i=d} \, w_i(r_i-q_i)^p}\f$ instead o
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\cgalHeading{Parameters}
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Expects for the template argument a model of the concept
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\tparam Traits must be a model of the concept
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`SearchTraits`, for example `Search_traits_2<Kernel>`.
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\cgalModels `OrthogonalDistance`
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@ -24,6 +24,39 @@ struct Distance {
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return distance;
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}
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template <class TreeTraits>
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double min_distance_to_rectangle(const Point& p,
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const CGAL::Kd_tree_rectangle<TreeTraits>& b,std::vector<double>& dists){
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double distance(0.0), h = p.x();
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if (h < b.min_coord(0)){
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dists[0] = (b.min_coord(0)-h);
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distance += dists[0]*dists[0];
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}
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if (h > b.max_coord(0)){
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dists[0] = (h-b.max_coord(0));
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distance += dists[0]*dists[0];
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}
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h=p.y();
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if (h < b.min_coord(1)){
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dists[1] = (b.min_coord(1)-h);
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distance += dists[1]*dists[1];
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}
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if (h > b.max_coord(1)){
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dists[1] = (h-b.max_coord(1));
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distance += dists[1]*dists[1];
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}
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h=p.z();
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if (h < b.min_coord(2)){
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dists[2] = (b.min_coord(2)-h);
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distance += dists[2]*dists[2];
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}
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if (h > b.max_coord(2)){
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dists[2] = (h-b.max_coord(2));
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distance += dists[2]*dists[2];
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}
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return distance;
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}
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template <class TreeTraits>
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double max_distance_to_rectangle(const Point& p,
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const CGAL::Kd_tree_rectangle<TreeTraits>& b) const {
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@ -41,6 +74,23 @@ struct Distance {
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return d0 + d1 + d2;
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}
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template <class TreeTraits>
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double max_distance_to_rectangle(const Point& p,
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const CGAL::Kd_tree_rectangle<TreeTraits>& b,std::vector<double>& dists){
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double h = p.x();
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dists[0] = (h >= (b.min_coord(0)+b.max_coord(0))/2.0) ?
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(h-b.min_coord(0)) : (b.max_coord(0)-h);
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h=p.y();
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dists[1] = (h >= (b.min_coord(1)+b.max_coord(1))/2.0) ?
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(h-b.min_coord(1)) : (b.max_coord(1)-h);
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h=p.z();
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dists[2] = (h >= (b.min_coord(2)+b.max_coord(2))/2.0) ?
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(h-b.min_coord(2)) : (b.max_coord(2)-h);
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return dists[0] * dists[0] + dists[1] * dists[1] + dists[2] * dists[2];
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}
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double new_distance(double& dist, double old_off, double new_off,
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int /* cutting_dimension */) const {
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return dist + new_off*new_off - old_off*old_off;
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@ -1,6 +1,8 @@
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struct Point {
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double vec[3];
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Point(){}
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Point() { vec[0]= vec[1] = vec[2] = 0; }
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Point (double x, double y, double z) { vec[0]=x; vec[1]=y; vec[2]=z; }
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@ -71,41 +71,65 @@ namespace CGAL {
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typedef typename SearchTraits::Point_d Point_d;
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typedef Point_d Query_item;
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typedef typename internal::Euclidean_distance_base<SearchTraits>::Dimension D;
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typedef typename internal::Euclidean_distance_base<SearchTraits>::Dimension D;
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// default constructor
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Euclidean_distance(const SearchTraits& traits_=SearchTraits()):traits(traits_) {}
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// default constructor
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Euclidean_distance(const SearchTraits& traits_=SearchTraits()):traits(traits_) {}
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inline FT transformed_distance(const Query_item& q, const Point_d& p) const {
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return transformed_distance(q,p, D());
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}
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//Dynamic version for runtime dimension
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inline FT transformed_distance(const Query_item& q, const Point_d& p, Dynamic_dimension_tag dt) const {
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FT distance = FT(0);
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typename SearchTraits::Construct_cartesian_const_iterator_d construct_it=traits.construct_cartesian_const_iterator_d_object();
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typename SearchTraits::Cartesian_const_iterator_d qit = construct_it(q),
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qe = construct_it(q,1), pit = construct_it(p);
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for(; qit != qe; qit++, pit++){
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distance += ((*qit)-(*pit))*((*qit)-(*pit));
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}
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return distance;
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FT distance = FT(0);
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typename SearchTraits::Construct_cartesian_const_iterator_d construct_it=traits.construct_cartesian_const_iterator_d_object();
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typename SearchTraits::Cartesian_const_iterator_d qit = construct_it(q),
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qe = construct_it(q,1), pit = construct_it(p);
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for(; qit != qe; qit++, pit++){
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distance += ((*qit)-(*pit))*((*qit)-(*pit));
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}
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return distance;
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}
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//Generic version for DIM > 3
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template < int DIM >
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inline FT transformed_distance(const Query_item& q, const Point_d& p, Dimension_tag<DIM> dt) const {
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std::cerr << "here goes the generic code" <<std::endl;
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return 0;
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}
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FT distance = FT(0);
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typename SearchTraits::Construct_cartesian_const_iterator_d construct_it=traits.construct_cartesian_const_iterator_d_object();
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typename SearchTraits::Cartesian_const_iterator_d qit = construct_it(q),
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qe = construct_it(q,1), pit = construct_it(p);
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for(; qit != qe; qit++, pit++){
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distance += ((*qit)-(*pit))*((*qit)-(*pit));
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}
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return distance;
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}
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// template <>
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//DIM = 2 loop unrolled
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inline FT transformed_distance(const Query_item& q, const Point_d& p, Dimension_tag<2> dt) const {
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std::cerr << "here goes the unrolled code for 3D" <<std::endl;
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return 0;
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}
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typename SearchTraits::Construct_cartesian_const_iterator_d construct_it=traits.construct_cartesian_const_iterator_d_object();
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typename SearchTraits::Cartesian_const_iterator_d qit = construct_it(q),pit = construct_it(p);
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FT distance = square(*qit - *pit);
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qit++;pit++;
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distance += square(*qit - *pit);
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return distance;
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}
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inline FT transformed_distance(const Query_item& q, const Point_d& p) const {
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return transformed_distance(q,p, D());
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}
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//DIM = 3 loop unrolled
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inline FT transformed_distance(const Query_item& q, const Point_d& p, Dimension_tag<3> dt) const {
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typename SearchTraits::Construct_cartesian_const_iterator_d construct_it=traits.construct_cartesian_const_iterator_d_object();
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typename SearchTraits::Cartesian_const_iterator_d qit = construct_it(q),pit = construct_it(p);
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FT distance = square(*qit - *pit);
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qit++;pit++;
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distance += square(*qit - *pit);
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qit++;pit++;
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distance += square(*qit - *pit);
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return distance;
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}
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inline FT min_distance_to_rectangle(const Query_item& q,
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@ -119,9 +119,11 @@ namespace CGAL {
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}
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//Dynamic version for runtime dimension
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inline
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FT
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transformed_distance(const Query_item& q, const Point_d& p) const
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transformed_distance(const Query_item& q, const Point_d& p, Dynamic_dimension_tag dt) const
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{
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FT distance = FT(0);
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typename SearchTraits::Construct_cartesian_const_iterator_d construct_it=
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@ -140,7 +142,87 @@ namespace CGAL {
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the_weights[i] * std::pow(CGAL::abs((*qit)-(*pit)),power);
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return distance;
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}
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//Generic version for DIM > 3
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template <int DIM>
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inline FT
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transformed_distance(const Query_item& q, const Point_d& p, Dimension_tag<DIM> dt) const
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{
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FT distance = FT(0);
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typename SearchTraits::Construct_cartesian_const_iterator_d construct_it=
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traits.construct_cartesian_const_iterator_d_object();
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Coord_iterator qit = construct_it(q),
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qe = construct_it(q,1),
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pit = construct_it(p);
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if (power == FT(0)) {
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for (unsigned int i = 0; qit != qe; ++qit, ++i)
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if (the_weights[i] * CGAL::abs((*qit) - (*pit)) > distance)
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distance = the_weights[i] * CGAL::abs((*qit)-(*pit));
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}
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else
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for (unsigned int i = 0; qit != qe; ++qit, ++i)
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distance +=
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the_weights[i] * std::pow(CGAL::abs((*qit)-(*pit)),power);
|
||||
return distance;
|
||||
}
|
||||
|
||||
//DIM = 2 loop unrolled
|
||||
inline FT
|
||||
transformed_distance(const Query_item& q, const Point_d& p, Dimension_tag<2> dt) const
|
||||
{
|
||||
FT distance = FT(0);
|
||||
typename SearchTraits::Construct_cartesian_const_iterator_d construct_it=
|
||||
traits.construct_cartesian_const_iterator_d_object();
|
||||
Coord_iterator qit = construct_it(q),
|
||||
pit = construct_it(p);
|
||||
if (power == FT(0)) {
|
||||
if (the_weights[0] * CGAL::abs((*qit) - (*pit)) > distance)
|
||||
distance = the_weights[0] * CGAL::abs((*qit)-(*pit));
|
||||
qit++;pit++;
|
||||
if (the_weights[1] * CGAL::abs((*qit) - (*pit)) > distance)
|
||||
distance = the_weights[1] * CGAL::abs((*qit)-(*pit));
|
||||
}
|
||||
else{
|
||||
distance +=
|
||||
the_weights[0] * std::pow(CGAL::abs((*qit)-(*pit)),power);
|
||||
qit++;pit++;
|
||||
distance +=
|
||||
the_weights[1] * std::pow(CGAL::abs((*qit)-(*pit)),power);
|
||||
}
|
||||
return distance;
|
||||
}
|
||||
|
||||
//DIM = 3 loop unrolled
|
||||
inline FT
|
||||
transformed_distance(const Query_item& q, const Point_d& p, Dimension_tag<3> dt) const
|
||||
{
|
||||
FT distance = FT(0);
|
||||
typename SearchTraits::Construct_cartesian_const_iterator_d construct_it=
|
||||
traits.construct_cartesian_const_iterator_d_object();
|
||||
Coord_iterator qit = construct_it(q),
|
||||
pit = construct_it(p);
|
||||
if (power == FT(0)) {
|
||||
if (the_weights[0] * CGAL::abs((*qit) - (*pit)) > distance)
|
||||
distance = the_weights[0] * CGAL::abs((*qit)-(*pit));
|
||||
qit++;pit++;
|
||||
if (the_weights[1] * CGAL::abs((*qit) - (*pit)) > distance)
|
||||
distance = the_weights[1] * CGAL::abs((*qit)-(*pit));
|
||||
qit++;pit++;
|
||||
if (the_weights[2] * CGAL::abs((*qit) - (*pit)) > distance)
|
||||
distance = the_weights[2] * CGAL::abs((*qit)-(*pit));
|
||||
}
|
||||
else{
|
||||
distance +=
|
||||
the_weights[0] * std::pow(CGAL::abs((*qit)-(*pit)),power);
|
||||
qit++;pit++;
|
||||
distance +=
|
||||
the_weights[1] * std::pow(CGAL::abs((*qit)-(*pit)),power);
|
||||
qit++;pit++;
|
||||
distance +=
|
||||
the_weights[2] * std::pow(CGAL::abs((*qit)-(*pit)),power);
|
||||
}
|
||||
return distance;
|
||||
}
|
||||
|
||||
inline
|
||||
FT
|
||||
|
|
|
|||
Loading…
Reference in New Issue