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This commit is contained in:
Hans Tangelder 2003-09-25 14:01:06 +00:00
parent 7d69818b98
commit 67e5171bc2
27 changed files with 237 additions and 89 deletions
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39
Packages/Spatial_searching/doc_tex/Spatial_searching/intro.tex
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@ -272,10 +272,28 @@ The concepts related to the spatial searching package are
\begin{itemize}
\item
\ccc{QueryItem} denoting a $d$-dimensional spatial query object. The concepts
\ccc{SpatialPoint}, \ccc{IsoBox_d}, and \ccc{Ball_d} refine \ccc{QueryItem}.
\item
\ccc{SpatialPoint}
denoting a $d$-dimensional point, as implemented by
\ccc{CGAL::Point_2<R>}, \ccc{CGAL::Point_3<R>}, and \ccc{CGAL::Point_d<R>}.
\ccc{CGAL::Point_2<Kernel>}, \ccc{CGAL::Point_3<Kernel>}, and \ccc{CGAL::Point_d<Kernel>}.
\item
\ccc{IsoBox_d}
denoting a $d$-dimensional iso-box, as implemented
by
\ccc{CGAL::Iso_rectangle_2<Kernel>}, \ccc{CGAL::Iso_cuboid_3<Kernel>},
and \ccc{CGAL::Iso_box_d<Kernel>}.
\item
\ccc{Ball_d}
denoting a $d$-dimensional ball, as implemented by
\ccc{CGAL::Circle_2<Kernel>}, \ccc{CGAL::Sphere_3<Kernel>},
and \ccc{CGAL::Sphere_d<Kernel>}.
\item
\ccc{PointContainer} denoting a container, that stores points and
@ -301,17 +319,6 @@ as implemented by \ccc{CGAL::Plane_separator<NT>}.
\ccc{TreeTraits} denoting a traits class for the construction of a tree.
\ccc{CGAL::Kd_tree_traits_point< SpatialPoint, Splitter >} provides an implementation.
\item
\ccc{QueryItem} denoting a $d$-dimensional spatial query object. Implementations
for point queries are provided by
\ccc{CGAL::Point_2<R>}, \ccc{CGAL::Point_3<R>}, and \ccc{CGAL::Point_d<R>}.
Implementations
for spherical queries are provided by
\ccc{CGAL::Circle_2<R>}, \ccc{CGAL::Sphere_3<R>}, and \ccc{CGAL::Sphere_d<R>}.
Implementations
for rectangular queries are provided by
\ccc{CGAL::Iso_rectangle_2<R>}, \ccc{CGAL::Iso_cuboid_3<R>}, and \ccc{CGAL::Iso_box_d<R>}.
\item
\ccc{GeneralDistance} denoting a general distance object. A general distance object should define distances between a query object
and the points stored in a tree and between the query object and the rectangles associated with the nodes from the tree.
@ -321,9 +328,9 @@ by \ccc{CGAL::Euclidean_distance<SpatialPoint>}, and
a weighted Minkowski metric.
An implementation for queries defined by rectangles is provided by
\ccc{CGAL::Manhattan_distance_rectangle_point<QueryItem,SpatialPoint>}.
\ccc{CGAL::Manhattan_distance_rectangle_point<IsoBox_d,SpatialPoint>}.
An implementation for queries defined by spheres is provided by
\ccc{CGAL::Euclidean_distance_sphere_point<QueryItem,SpatialPoint>}.
\ccc{CGAL::Euclidean_distance_sphere_point<Ball_d,SpatialPoint>}.
\item
\ccc{OrthogonalDistance} denoting a distance object. An orthogonal distance object should define distances
@ -336,7 +343,7 @@ by \ccc{CGAL::Euclidean_distance<SpatialPoint>}, and
a weighted Minkowski metric.
\item
\ccc{SpatialTree} denoting a tree supporting spatial searching/
\ccc{SpatialTree} denoting a tree supporting spatial searching
\ccc{CGAL::Kd_tree<TreeTraits>} provides an implementation of $k$-$d$ trees.
\end{itemize}
@ -398,7 +405,7 @@ supports also range searching using the method \\
\ccc{template <class OutputIterator, class FuzzyQueryItem>} \\
\ccc{OutputIterator CGAL::Kd_tree<Treetraits>::search(OutputIterator it, const FuzzyQueryItem& q)}.\\
Implementations for the concept \ccc{FuzzyQueryItem} are provided by
the class \ccc{CGAL::Fuzzy_iso_box_d<Point, IsoBox_d>}
the class \ccc{CGAL::Fuzzy_iso_box_d<SpatialPoint, IsoBox_d>}
and the class \ccc{CGAL::Fuzzy_sphere_d<SpatialPoint>}.
For range searching of large data sets the user may set the parameter \ccc{bucket_size}
used in building the $k$-$d$ tree to a large value (e.g. 100),

62
Packages/Spatial_searching/doc_tex/Spatial_searching_ref/Ball_d.tex Executable file
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@ -0,0 +1,62 @@
% +------------------------------------------------------------------------+
% | Reference manual page: Ball_d.tex
% +------------------------------------------------------------------------+
% | 1.07.2001 Johan W.H. Tangelder
% | Package: ASPAS
% |
\RCSdef{\RCSBalldRev}{$Revision$}
\RCSdefDate{\RCSBalldDate}{$Date$}
% |
%%RefPage: end of header, begin of main body
% +------------------------------------------------------------------------+
\begin{ccRefConcept}{Ball_d}
%% \ccHtmlCrossLink{} %% add further rules for cross referencing links
%% \ccHtmlIndexC[concept]{} %% add further index entries
\ccDefinition
The concept \ccRefName\ defines the requirements for $d$-dimensional balls.
{\bf Refines}
QueryItem
\ccParameters
\ccc{SpatialPoint} represents a $d$-dimensional point.
\ccTypes
\ccTypedef{Kernel_traits<SpatialPoint>::Kernel::FT NT;}{Number type.}
\ccOperations
\ccMethod{SpatialPoint center();}
{Returns the center of the ball.}
\ccMethod{NT squared_radius();}
{Returns the squared radius of the ball.}
\ccHasModels
\ccc{CGAL::Iso_circle_2<Kernel>}, \ccc{CGAL::Iso_sphere_3<Kernel>},
\ccc{CGAL::Iso_sphere_d<Kernel>}.
\ccSeeAlso
QueryItem, \ccc{CGAL::Iso_circle_2<Kernel>}, \ccc{CGAL::Iso_sphere_3<Kernel>},
\ccc{CGAL::Iso_sphere_d<Kernel>}.
\end{ccRefConcept}
% +------------------------------------------------------------------------+
%%RefPage: end of main body, begin of footer
% EOF
% +------------------------------------------------------------------------+

3
Packages/Spatial_searching/doc_tex/Spatial_searching_ref/General_priority_search.tex
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@ -48,7 +48,8 @@ The fourth template argument has default value \ccc{CGAL::Kd_tree<TreeTraits>}.
\ccTypedef{TreeTraits::Point Point;}{Point type.}
\ccTypedef{TreeTraits::NT NT;}{Number type.}
\ccTypedef{std::pair<Point*,NT> Point_with_distance;}{Pair of point and distance.}
\ccNestedType{iterator}{Input iterator for searching approximate neighbors.}
\ccNestedType{iterator}{Input iterator for searching approximate neighbors
with value type \ccc{Point_with_distance}.}
\newpage

23
Packages/Spatial_searching/doc_tex/Spatial_searching_ref/IsoBox_d.tex
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@ -20,27 +20,22 @@
The concept \ccRefName\ defines the requirements for $d$-dimensional iso-boxes.
{\bf Refines}
QueryItem
\ccParameters
\ccc{SpatialPoint} represents a $d$-dimensional point.
\ccTypes
\ccTypedef{Kernel_traits<SpatialPoint>::Kernel::FT NT;}{Number type.}
\ccCreation
\ccCreationVariable{b} %% choose variable name
\ccConstructor{IsoBox_d(SpatialPoint p, SpatialPoint q);}{introduces an iso-oriented box with diagonal opposite points
\ccc{p} and \ccc{}q.}
\ccOperations
\ccMethod{NT min();}
\ccMethod{SpatialPoint min();}
{Returns the smallest vertex of the iso-oriented box.}
\ccMethod{NT max();}
\ccMethod{SpatialPoint max();}
{Returns the largest vertex of the iso-oriented box.}
@ -49,6 +44,12 @@ The concept \ccRefName\ defines the requirements for $d$-dimensional iso-boxes.
\ccc{CGAL::Iso_rectangle_2<Kernel>}, \ccc{CGAL::Iso_cuboid_3<Kernel>},
\ccc{CGAL::Iso_box_d<Kernel>}.
\ccSeeAlso
QueryItem, \ccc{CGAL::Iso_rectangle_2<Kernel>}, \ccc{CGAL::Iso_cuboid_3<Kernel>},
\ccc{CGAL::Iso_box_d<Kernel>}.
\end{ccRefConcept}
% +------------------------------------------------------------------------+

12
Packages/Spatial_searching/doc_tex/Spatial_searching_ref/Kd_tree.tex
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@ -34,15 +34,17 @@ for example \ccc{CGAL::Kd_tree_traits_point<Point,Splitter>}.
\ccTypedef{TreeTraits::NT NT;}{Number type.}
\ccTypedef{Kd_tree_node<TreeTraits> Node;}{Node type.}
\ccTypedef{Kd_tree<TreeTraits> Tree;}{Tree type.}
\ccTypedef{Compact_container<Node>::iterator Node_handle;}{Node handle.}
\ccTypedef{std::vector<Point*>::iterator Point_iterator;} {Iterator over points.}
\ccTypedef{std::list<Point>::iterator input_iterator;}{Input iterator.}
% \ccTypedef{Compact_container<Node>::iterator Node_handle;}{Node handle.}
\ccTypedef{std::vector<Point*>::iterator Point_iterator;} {Random access iterator
with value type pointer to Point.}
% \ccTypedef{std::list<Point>::iterator input_iterator;}{Input iterator.}
\ccCreation
\ccCreationVariable{tree}
\ccConstructor
{Kd_tree(input_iterator first, input_iterator beyond, traits t=TreeTraits());}
\ccConstructor{
template <class input_iterator>
Kd_tree(input_iterator first, input_iterator beyond, traits t=TreeTraits());}
{
Constructs a $k$-$d$ tree on the elements from the sequence
\ccc{first, beyond} using the splitting rule implemented by \ccc{t}.

2
Packages/Spatial_searching/doc_tex/Spatial_searching_ref/Orthogonal_priority_search.tex
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@ -41,7 +41,7 @@ The third template argument has default value \ccc{CGAL::Kd_tree<TreeTraits>}.
\ccTypedef{TreeTraits::Point Point;}{Point type.}
\ccTypedef{TreeTraits::NT NT;}{Number type.}
\ccTypedef{std::pair<Pair*,NT> Point_with_distance;}{Pair of point and distance}
\ccNestedType{iterator}{Input iterator for searching approximate neighbors.}
\ccNestedType{iterator}{Input iterator for searching approximate neighbors with value type \ccc{Point_with_distance}.}
\ccCreation
\ccCreationVariable{s} %% choose variable name

9
Packages/Spatial_searching/doc_tex/Spatial_searching_ref/QueryItem.tex
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@ -21,15 +21,14 @@
The concept \ccClassTemplateName\ represents a
$d$-dimensional spatial object.
\ccHasModels
{\bf Is refined by}
\ccc{CGAL::Point_2<Kernel>, CGAL::Point_3<Kernel>, CGAL::Point_d<Kernel>,
CGAL::Iso_rectangle_2<Kernel>, CGAL::Iso_cuboid_3<Kernel>, CGAL::Iso_box_d<Kernel>,
CGAL::Circle_2<Kernel>, CGAL::Sphere_3<Kernel>, CGAL::Sphere_d<Kernel>}.
IsoBox\_d, Ball\_d.
\ccSeeAlso
GeneralDistance, OrthogonalDistance.
IsoBox\_d, Ball\_d, GeneralDistance, OrthogonalDistance.
\end{ccRefConcept}

2
Packages/Spatial_searching/doc_tex/Spatial_searching_ref/Weighted_Minkowski_distance.tex
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@ -71,7 +71,7 @@ and returns the updated distance.}
\ccMethod{NT transformed_distance(NT d);} {Returns for $0 < p <\infty$ $d^p$. Returns for $p=\infty$ $d$.}
\ccMethod{NT inverse_of_transformed_distance(NT d);} {Returns for $0 < p <\infty$ $d^{1/p}$}.
\ccMethod{NT inverse_of_transformed_distance(NT d);} {Returns for $0 < p <\infty$ $d^{1/p}$.}
{Returns for $p=\infty$ $d$.}

2
Packages/Spatial_searching/doc_tex/Spatial_searching_ref/introduction.tex
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@ -35,7 +35,7 @@ that are described in the reference pages.
\ccHeading{Concepts}
\ccRefConceptPage{Ball_d} \\
\ccRefConceptPage{FuzzyQueryItem} \\
\ccRefConceptPage{GeneralDistance} \\
\ccRefConceptPage{IsoBox_d} \\

2
Packages/Spatial_searching/doc_tex/Spatial_searching_ref/main.tex
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@ -6,7 +6,7 @@
% +------------------------------------------------------------------------+
% alfabatisch
\input{introduction.tex}
\input{Ball_d.tex}
\input{Euclidean_distance.tex}
\input{Euclidean_distance_sphere_point.tex}
\input{Fair.tex}

39
Packages/Spatial_searching/doc_tex/basic/Spatial_searching/intro.tex
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@ -272,10 +272,28 @@ The concepts related to the spatial searching package are
\begin{itemize}
\item
\ccc{QueryItem} denoting a $d$-dimensional spatial query object. The concepts
\ccc{SpatialPoint}, \ccc{IsoBox_d}, and \ccc{Ball_d} refine \ccc{QueryItem}.
\item
\ccc{SpatialPoint}
denoting a $d$-dimensional point, as implemented by
\ccc{CGAL::Point_2<R>}, \ccc{CGAL::Point_3<R>}, and \ccc{CGAL::Point_d<R>}.
\ccc{CGAL::Point_2<Kernel>}, \ccc{CGAL::Point_3<Kernel>}, and \ccc{CGAL::Point_d<Kernel>}.
\item
\ccc{IsoBox_d}
denoting a $d$-dimensional iso-box, as implemented
by
\ccc{CGAL::Iso_rectangle_2<Kernel>}, \ccc{CGAL::Iso_cuboid_3<Kernel>},
and \ccc{CGAL::Iso_box_d<Kernel>}.
\item
\ccc{Ball_d}
denoting a $d$-dimensional ball, as implemented by
\ccc{CGAL::Circle_2<Kernel>}, \ccc{CGAL::Sphere_3<Kernel>},
and \ccc{CGAL::Sphere_d<Kernel>}.
\item
\ccc{PointContainer} denoting a container, that stores points and
@ -301,17 +319,6 @@ as implemented by \ccc{CGAL::Plane_separator<NT>}.
\ccc{TreeTraits} denoting a traits class for the construction of a tree.
\ccc{CGAL::Kd_tree_traits_point< SpatialPoint, Splitter >} provides an implementation.
\item
\ccc{QueryItem} denoting a $d$-dimensional spatial query object. Implementations
for point queries are provided by
\ccc{CGAL::Point_2<R>}, \ccc{CGAL::Point_3<R>}, and \ccc{CGAL::Point_d<R>}.
Implementations
for spherical queries are provided by
\ccc{CGAL::Circle_2<R>}, \ccc{CGAL::Sphere_3<R>}, and \ccc{CGAL::Sphere_d<R>}.
Implementations
for rectangular queries are provided by
\ccc{CGAL::Iso_rectangle_2<R>}, \ccc{CGAL::Iso_cuboid_3<R>}, and \ccc{CGAL::Iso_box_d<R>}.
\item
\ccc{GeneralDistance} denoting a general distance object. A general distance object should define distances between a query object
and the points stored in a tree and between the query object and the rectangles associated with the nodes from the tree.
@ -321,9 +328,9 @@ by \ccc{CGAL::Euclidean_distance<SpatialPoint>}, and
a weighted Minkowski metric.
An implementation for queries defined by rectangles is provided by
\ccc{CGAL::Manhattan_distance_rectangle_point<QueryItem,SpatialPoint>}.
\ccc{CGAL::Manhattan_distance_rectangle_point<IsoBox_d,SpatialPoint>}.
An implementation for queries defined by spheres is provided by
\ccc{CGAL::Euclidean_distance_sphere_point<QueryItem,SpatialPoint>}.
\ccc{CGAL::Euclidean_distance_sphere_point<Ball_d,SpatialPoint>}.
\item
\ccc{OrthogonalDistance} denoting a distance object. An orthogonal distance object should define distances
@ -336,7 +343,7 @@ by \ccc{CGAL::Euclidean_distance<SpatialPoint>}, and
a weighted Minkowski metric.
\item
\ccc{SpatialTree} denoting a tree supporting spatial searching/
\ccc{SpatialTree} denoting a tree supporting spatial searching
\ccc{CGAL::Kd_tree<TreeTraits>} provides an implementation of $k$-$d$ trees.
\end{itemize}
@ -398,7 +405,7 @@ supports also range searching using the method \\
\ccc{template <class OutputIterator, class FuzzyQueryItem>} \\
\ccc{OutputIterator CGAL::Kd_tree<Treetraits>::search(OutputIterator it, const FuzzyQueryItem& q)}.\\
Implementations for the concept \ccc{FuzzyQueryItem} are provided by
the class \ccc{CGAL::Fuzzy_iso_box_d<Point, IsoBox_d>}
the class \ccc{CGAL::Fuzzy_iso_box_d<SpatialPoint, IsoBox_d>}
and the class \ccc{CGAL::Fuzzy_sphere_d<SpatialPoint>}.
For range searching of large data sets the user may set the parameter \ccc{bucket_size}
used in building the $k$-$d$ tree to a large value (e.g. 100),

62
Packages/Spatial_searching/doc_tex/basic/Spatial_searching_ref/Ball_d.tex Executable file
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@ -0,0 +1,62 @@
% +------------------------------------------------------------------------+
% | Reference manual page: Ball_d.tex
% +------------------------------------------------------------------------+
% | 1.07.2001 Johan W.H. Tangelder
% | Package: ASPAS
% |
\RCSdef{\RCSBalldRev}{$Revision$}
\RCSdefDate{\RCSBalldDate}{$Date$}
% |
%%RefPage: end of header, begin of main body
% +------------------------------------------------------------------------+
\begin{ccRefConcept}{Ball_d}
%% \ccHtmlCrossLink{} %% add further rules for cross referencing links
%% \ccHtmlIndexC[concept]{} %% add further index entries
\ccDefinition
The concept \ccRefName\ defines the requirements for $d$-dimensional balls.
{\bf Refines}
QueryItem
\ccParameters
\ccc{SpatialPoint} represents a $d$-dimensional point.
\ccTypes
\ccTypedef{Kernel_traits<SpatialPoint>::Kernel::FT NT;}{Number type.}
\ccOperations
\ccMethod{SpatialPoint center();}
{Returns the center of the ball.}
\ccMethod{NT squared_radius();}
{Returns the squared radius of the ball.}
\ccHasModels
\ccc{CGAL::Iso_circle_2<Kernel>}, \ccc{CGAL::Iso_sphere_3<Kernel>},
\ccc{CGAL::Iso_sphere_d<Kernel>}.
\ccSeeAlso
QueryItem, \ccc{CGAL::Iso_circle_2<Kernel>}, \ccc{CGAL::Iso_sphere_3<Kernel>},
\ccc{CGAL::Iso_sphere_d<Kernel>}.
\end{ccRefConcept}
% +------------------------------------------------------------------------+
%%RefPage: end of main body, begin of footer
% EOF
% +------------------------------------------------------------------------+

3
Packages/Spatial_searching/doc_tex/basic/Spatial_searching_ref/General_priority_search.tex
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@ -48,7 +48,8 @@ The fourth template argument has default value \ccc{CGAL::Kd_tree<TreeTraits>}.
\ccTypedef{TreeTraits::Point Point;}{Point type.}
\ccTypedef{TreeTraits::NT NT;}{Number type.}
\ccTypedef{std::pair<Point*,NT> Point_with_distance;}{Pair of point and distance.}
\ccNestedType{iterator}{Input iterator for searching approximate neighbors.}
\ccNestedType{iterator}{Input iterator for searching approximate neighbors
with value type \ccc{Point_with_distance}.}
\newpage

23
Packages/Spatial_searching/doc_tex/basic/Spatial_searching_ref/IsoBox_d.tex
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@ -20,27 +20,22 @@
The concept \ccRefName\ defines the requirements for $d$-dimensional iso-boxes.
{\bf Refines}
QueryItem
\ccParameters
\ccc{SpatialPoint} represents a $d$-dimensional point.
\ccTypes
\ccTypedef{Kernel_traits<SpatialPoint>::Kernel::FT NT;}{Number type.}
\ccCreation
\ccCreationVariable{b} %% choose variable name
\ccConstructor{IsoBox_d(SpatialPoint p, SpatialPoint q);}{introduces an iso-oriented box with diagonal opposite points
\ccc{p} and \ccc{}q.}
\ccOperations
\ccMethod{NT min();}
\ccMethod{SpatialPoint min();}
{Returns the smallest vertex of the iso-oriented box.}
\ccMethod{NT max();}
\ccMethod{SpatialPoint max();}
{Returns the largest vertex of the iso-oriented box.}
@ -49,6 +44,12 @@ The concept \ccRefName\ defines the requirements for $d$-dimensional iso-boxes.
\ccc{CGAL::Iso_rectangle_2<Kernel>}, \ccc{CGAL::Iso_cuboid_3<Kernel>},
\ccc{CGAL::Iso_box_d<Kernel>}.
\ccSeeAlso
QueryItem, \ccc{CGAL::Iso_rectangle_2<Kernel>}, \ccc{CGAL::Iso_cuboid_3<Kernel>},
\ccc{CGAL::Iso_box_d<Kernel>}.
\end{ccRefConcept}
% +------------------------------------------------------------------------+

12
Packages/Spatial_searching/doc_tex/basic/Spatial_searching_ref/Kd_tree.tex
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@ -34,15 +34,17 @@ for example \ccc{CGAL::Kd_tree_traits_point<Point,Splitter>}.
\ccTypedef{TreeTraits::NT NT;}{Number type.}
\ccTypedef{Kd_tree_node<TreeTraits> Node;}{Node type.}
\ccTypedef{Kd_tree<TreeTraits> Tree;}{Tree type.}
\ccTypedef{Compact_container<Node>::iterator Node_handle;}{Node handle.}
\ccTypedef{std::vector<Point*>::iterator Point_iterator;} {Iterator over points.}
\ccTypedef{std::list<Point>::iterator input_iterator;}{Input iterator.}
% \ccTypedef{Compact_container<Node>::iterator Node_handle;}{Node handle.}
\ccTypedef{std::vector<Point*>::iterator Point_iterator;} {Random access iterator
with value type pointer to Point.}
% \ccTypedef{std::list<Point>::iterator input_iterator;}{Input iterator.}
\ccCreation
\ccCreationVariable{tree}
\ccConstructor
{Kd_tree(input_iterator first, input_iterator beyond, traits t=TreeTraits());}
\ccConstructor{
template <class input_iterator>
Kd_tree(input_iterator first, input_iterator beyond, traits t=TreeTraits());}
{
Constructs a $k$-$d$ tree on the elements from the sequence
\ccc{first, beyond} using the splitting rule implemented by \ccc{t}.

2
Packages/Spatial_searching/doc_tex/basic/Spatial_searching_ref/Orthogonal_priority_search.tex
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@ -41,7 +41,7 @@ The third template argument has default value \ccc{CGAL::Kd_tree<TreeTraits>}.
\ccTypedef{TreeTraits::Point Point;}{Point type.}
\ccTypedef{TreeTraits::NT NT;}{Number type.}
\ccTypedef{std::pair<Pair*,NT> Point_with_distance;}{Pair of point and distance}
\ccNestedType{iterator}{Input iterator for searching approximate neighbors.}
\ccNestedType{iterator}{Input iterator for searching approximate neighbors with value type \ccc{Point_with_distance}.}
\ccCreation
\ccCreationVariable{s} %% choose variable name

9
Packages/Spatial_searching/doc_tex/basic/Spatial_searching_ref/QueryItem.tex
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@ -21,15 +21,14 @@
The concept \ccClassTemplateName\ represents a
$d$-dimensional spatial object.
\ccHasModels
{\bf Is refined by}
\ccc{CGAL::Point_2<Kernel>, CGAL::Point_3<Kernel>, CGAL::Point_d<Kernel>,
CGAL::Iso_rectangle_2<Kernel>, CGAL::Iso_cuboid_3<Kernel>, CGAL::Iso_box_d<Kernel>,
CGAL::Circle_2<Kernel>, CGAL::Sphere_3<Kernel>, CGAL::Sphere_d<Kernel>}.
IsoBox\_d, Ball\_d.
\ccSeeAlso
GeneralDistance, OrthogonalDistance.
IsoBox\_d, Ball\_d, GeneralDistance, OrthogonalDistance.
\end{ccRefConcept}

2
Packages/Spatial_searching/doc_tex/basic/Spatial_searching_ref/Weighted_Minkowski_distance.tex
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@ -71,7 +71,7 @@ and returns the updated distance.}
\ccMethod{NT transformed_distance(NT d);} {Returns for $0 < p <\infty$ $d^p$. Returns for $p=\infty$ $d$.}
\ccMethod{NT inverse_of_transformed_distance(NT d);} {Returns for $0 < p <\infty$ $d^{1/p}$}.
\ccMethod{NT inverse_of_transformed_distance(NT d);} {Returns for $0 < p <\infty$ $d^{1/p}$.}
{Returns for $p=\infty$ $d$.}

2
Packages/Spatial_searching/doc_tex/basic/Spatial_searching_ref/introduction.tex
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@ -35,7 +35,7 @@ that are described in the reference pages.
\ccHeading{Concepts}
\ccRefConceptPage{Ball_d} \\
\ccRefConceptPage{FuzzyQueryItem} \\
\ccRefConceptPage{GeneralDistance} \\
\ccRefConceptPage{IsoBox_d} \\

2
Packages/Spatial_searching/doc_tex/basic/Spatial_searching_ref/main.tex
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@ -6,7 +6,7 @@
% +------------------------------------------------------------------------+
% alfabatisch
\input{introduction.tex}
\input{Ball_d.tex}
\input{Euclidean_distance.tex}
\input{Euclidean_distance_sphere_point.tex}
\input{Fair.tex}

2
Packages/Spatial_searching/include/CGAL/Euclidean_distance.h
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@ -45,6 +45,8 @@ namespace CGAL {
assert(the_dimension>0);
}
Euclidean_distance(const int d) : the_dimension(d) {}
~Euclidean_distance() {}

2
Packages/Spatial_searching/include/CGAL/Euclidean_distance_sphere_point.h
View File

@ -38,6 +38,7 @@ namespace CGAL {
public:
// default constructor
Euclidean_distance_sphere_point() {
Point p;
@ -45,6 +46,7 @@ namespace CGAL {
assert(the_dimension>0);
}
Euclidean_distance_sphere_point(const int d) : the_dimension(d) {}
~Euclidean_distance_sphere_point() {}

1
Packages/Spatial_searching/include/CGAL/Fuzzy_iso_box_d.h
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@ -43,6 +43,7 @@ namespace CGAL {
// default constructor
Fuzzy_iso_box_d() {}
// constructor
Fuzzy_iso_box_d(const Point& p, const Point& q, NT epsilon=NT(0)) :
eps(epsilon), dim(p.dimension())

4
Packages/Spatial_searching/include/CGAL/Fuzzy_iso_rectangle_d.h
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@ -43,9 +43,7 @@ namespace CGAL {
// default constructor
Fuzzy_iso_rectangle_d() {}
// constructor
Fuzzy_iso_rectangle_d(const Point& p, const Point& q, NT epsilon=NT(0)) :
eps(epsilon), dim(p.dimension())

3
Packages/Spatial_searching/include/CGAL/Kd_tree.h
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@ -39,7 +39,7 @@ public:
typedef typename TreeTraits::Point Point;
typedef typename TreeTraits::Container Point_container;
typedef typename std::list<Point>::iterator input_iterator;
// typedef typename std::list<Point>::iterator input_iterator;
typedef typename TreeTraits::NT NT;
typedef Kd_tree_node<TreeTraits> Node;
typedef Kd_tree<TreeTraits> Tree;
@ -175,6 +175,7 @@ public:
//introduced for backward compability
Kd_tree() {}
template <class input_iterator>
Kd_tree(input_iterator first, input_iterator beyond,
TreeTraits t = TreeTraits()) : tr(t) {
assert(first != beyond);

1
Packages/Spatial_searching/include/CGAL/Manhattan_distance_rectangle_point.h
View File

@ -46,6 +46,7 @@ namespace CGAL {
assert(the_dimension>0);
}
Manhattan_distance_rectangle_point(const int d) : the_dimension(d) {}
//copy constructor

1
Packages/Spatial_searching/include/CGAL/Weighted_Minkowski_distance.h
View File

@ -45,7 +45,6 @@ namespace CGAL {
public:
// default constructor
Weighted_Minkowski_distance(): power(2)
{