songsenand
/
cgal
mirror of https://github.com/CGAL/cgal
1
0
Fork 0
Code Issues Packages Projects Releases Wiki Activity

*** empty log message ***

This commit is contained in:
Andreas Fabri 2003-11-19 20:10:07 +00:00
parent c9448250da
commit 86f1dd500a
6 changed files with 22 additions and 18 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

16
Packages/Spatial_searching/doc_tex/Spatial_searching/intro.tex
View File

@ -178,6 +178,7 @@ example illustrates distance browsing and the last example illustrates
nearest and furthest neighbour searching using a user defined point
and distance class.
\newpage
\subsection{Example of Nearest Neighbor Searching}
The first example illustrates nearest neighbor searching. The random
@ -189,8 +190,9 @@ computes squared distances instead of the Euclidean distance itself.
Finally, if the Euclidean distance is reported the square root is
taken.
\ccIncludeExampleCode{../../examples/Spatial_searching/Nearest_neighbor_searching.C}
\ccIncludeExampleCode{../../../examples/Spatial_searching/Nearest_neighbor_searching.C}
\newpage
\subsection{Example of Selecting a Splitting Rule and Setting the Bucket Size.}
This example program illustrates selecting a splitting rule and
@ -198,7 +200,7 @@ setting the maximal allowed bucket size. The only differences with
the previous example are the declaration of the Fair
splitting rule, needed to set the maximal allowed bucket size.
\ccIncludeExampleCode{../../examples/Spatial_searching/Using_fair_splitting_rule.C}
\ccIncludeExampleCode{../../../examples/Spatial_searching/Using_fair_splitting_rule.C}
\subsection{Example of General Neighbor Searching}
@ -207,7 +209,7 @@ neighbor searching using 4-dimensional Cartesian coordinates. Five
approximate nearest and furthest neighbors of the query rectangle
$[0.1,0.2]^4$ are computed.
\ccIncludeExampleCode{../../examples/Spatial_searching/General_neighbor_searching.C}
\ccIncludeExampleCode{../../../examples/Spatial_searching/General_neighbor_searching.C}
\subsection{Example of a Range Query}
@ -215,7 +217,7 @@ This example program illustrates approximate range querying for
4-dimensional fuzzy iso-rectangles and spheres using homogeneous
coordinates.
\ccIncludeExampleCode{../../examples/Spatial_searching/Fuzzy_range_query.C}
\ccIncludeExampleCode{../../../examples/Spatial_searching/Fuzzy_range_query.C}
\subsection{Example of Incremental Searching}
@ -225,7 +227,7 @@ points with a positive first coordinate using orthogonal priority
search.
\ccIncludeExampleCode{../../examples/Spatial_searching/Distance_browsing.C}
\ccIncludeExampleCode{../../../examples/Spatial_searching/Distance_browsing.C}
\subsection{Example Illustrating Use of User Defined Point and Distance Class}
@ -236,10 +238,10 @@ implementation of the Euclidean distance.
We first have to introduce a point class. We have put the glue layer
in this file as well.
\ccIncludeExampleCode{../../examples/Spatial_searching/Point.h}
\ccIncludeExampleCode{../../../examples/Spatial_searching/Point.h}
\ccIncludeExampleCode{../../examples/Spatial_searching/User_defined_point_and_distance.C}
\ccIncludeExampleCode{../../../examples/Spatial_searching/User_defined_point_and_distance.C}
\section{Software Design}

2
Packages/Spatial_searching/doc_tex/Spatial_searching/main.tex
View File

@ -1,5 +1,5 @@
\chapter{Spatial Searching}
\label{ChapterUserSpatialSearching}
\input{Spatial_searching/intro.tex}
\input{intro.tex}
%% EOF

2
Packages/Spatial_searching/doc_tex/Spatial_searching_ref/Euclidean_distance.tex
View File

@ -28,7 +28,7 @@ To optimize distance computations squared distances are used.
\ccParameters
Expects for the template argument a model of the concept
\ccc{SearchTraits}, for example \ccc{CGAL::Search_traits_2<Kernel>}.
\ccc{SearchTraits}, for example \ccc{CGAL::Search_traits_2<CGAL::Cartesian_double> >}.
\ccIsModel

16
Packages/Spatial_searching/doc_tex/basic/Spatial_searching/intro.tex
View File

@ -178,6 +178,7 @@ example illustrates distance browsing and the last example illustrates
nearest and furthest neighbour searching using a user defined point
and distance class.
\newpage
\subsection{Example of Nearest Neighbor Searching}
The first example illustrates nearest neighbor searching. The random
@ -189,8 +190,9 @@ computes squared distances instead of the Euclidean distance itself.
Finally, if the Euclidean distance is reported the square root is
taken.
\ccIncludeExampleCode{../../examples/Spatial_searching/Nearest_neighbor_searching.C}
\ccIncludeExampleCode{../../../examples/Spatial_searching/Nearest_neighbor_searching.C}
\newpage
\subsection{Example of Selecting a Splitting Rule and Setting the Bucket Size.}
This example program illustrates selecting a splitting rule and
@ -198,7 +200,7 @@ setting the maximal allowed bucket size. The only differences with
the previous example are the declaration of the Fair
splitting rule, needed to set the maximal allowed bucket size.
\ccIncludeExampleCode{../../examples/Spatial_searching/Using_fair_splitting_rule.C}
\ccIncludeExampleCode{../../../examples/Spatial_searching/Using_fair_splitting_rule.C}
\subsection{Example of General Neighbor Searching}
@ -207,7 +209,7 @@ neighbor searching using 4-dimensional Cartesian coordinates. Five
approximate nearest and furthest neighbors of the query rectangle
$[0.1,0.2]^4$ are computed.
\ccIncludeExampleCode{../../examples/Spatial_searching/General_neighbor_searching.C}
\ccIncludeExampleCode{../../../examples/Spatial_searching/General_neighbor_searching.C}
\subsection{Example of a Range Query}
@ -215,7 +217,7 @@ This example program illustrates approximate range querying for
4-dimensional fuzzy iso-rectangles and spheres using homogeneous
coordinates.
\ccIncludeExampleCode{../../examples/Spatial_searching/Fuzzy_range_query.C}
\ccIncludeExampleCode{../../../examples/Spatial_searching/Fuzzy_range_query.C}
\subsection{Example of Incremental Searching}
@ -225,7 +227,7 @@ points with a positive first coordinate using orthogonal priority
search.
\ccIncludeExampleCode{../../examples/Spatial_searching/Distance_browsing.C}
\ccIncludeExampleCode{../../../examples/Spatial_searching/Distance_browsing.C}
\subsection{Example Illustrating Use of User Defined Point and Distance Class}
@ -236,10 +238,10 @@ implementation of the Euclidean distance.
We first have to introduce a point class. We have put the glue layer
in this file as well.
\ccIncludeExampleCode{../../examples/Spatial_searching/Point.h}
\ccIncludeExampleCode{../../../examples/Spatial_searching/Point.h}
\ccIncludeExampleCode{../../examples/Spatial_searching/User_defined_point_and_distance.C}
\ccIncludeExampleCode{../../../examples/Spatial_searching/User_defined_point_and_distance.C}
\section{Software Design}

2
Packages/Spatial_searching/doc_tex/basic/Spatial_searching/main.tex
View File

@ -1,5 +1,5 @@
\chapter{Spatial Searching}
\label{ChapterUserSpatialSearching}
\input{Spatial_searching/intro.tex}
\input{intro.tex}
%% EOF

2
Packages/Spatial_searching/doc_tex/basic/Spatial_searching_ref/Euclidean_distance.tex
View File

@ -28,7 +28,7 @@ To optimize distance computations squared distances are used.
\ccParameters
Expects for the template argument a model of the concept
\ccc{SearchTraits}, for example \ccc{CGAL::Search_traits_2<Kernel>}.
\ccc{SearchTraits}, for example \ccc{CGAL::Search_traits_2<CGAL::Cartesian_double> >}.
\ccIsModel