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move example to user manual. de-advance

This commit is contained in:
Andreas Fabri 2012-09-24 08:50:09 +00:00
parent 190dd77c6f
commit 5c1d6e5ef6
8 changed files with 12 additions and 22 deletions
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2
Matrix_search/doc/Matrix_search/CGAL/Dynamic_matrix.h
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@ -4,8 +4,6 @@ namespace CGAL {
/*!
\ingroup PkgMatrixSearch
\todo advanced is missing
The class `Dynamic_matrix` is an adaptor for an arbitrary
matrix class `M` to provide the dynamic operations needed for monotone
matrix search.

2
Matrix_search/doc/Matrix_search/CGAL/Sorted_matrix_search_traits_adaptor.h
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@ -4,8 +4,6 @@ namespace CGAL {
/*!
\ingroup PkgMatrixSearch
\todo advanced missing
The class `Sorted_matrix_search_traits_adaptor` can be used
as an adaptor to create sorted matrix search traits classes for
arbitrary feasibility test and matrix classes `F` resp. `M`.

1
Matrix_search/doc/Matrix_search/CGAL/monotone_matrix_search.h
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@ -3,7 +3,6 @@ namespace CGAL {
/*!
\ingroup PkgMatrixSearch
\todo advanced missing
The function `monotone_matrix_search` computes the maxima
for all rows of a totally monotone matrix.

13
Matrix_search/doc/Matrix_search/CGAL/sorted_matrix_search.h
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@ -3,8 +3,6 @@ namespace CGAL {
/*!
\ingroup PkgMatrixSearch
\todo advanced missing
The function `sorted_matrix_search` selects the smallest entry
in a set of sorted matrices that fulfills a certain feasibility
criterion.
@ -56,17 +54,6 @@ Frederickson and Johnson\cite fj-fkppc-83, \cite fj-gsrsm-84 and runs in
the number of input matrices, \f$ k\f$ denotes the maximal dimension of
any input matrix and \f$ f\f$ the time needed for one feasibility test.
### Example ###
In the following program we build a random vector \f$ a =
(a_i)_{i = 1,\,\ldots,\,5}\f$ (elements drawn uniformly from \f$ \{
0,\,\ldots,\,99 \}\f$) and construct a Cartesian matrix \f$ M\f$
containing as elements all sums \f$ a_i + a_j,\: i,\,j \in
\{1,\,\ldots,\,5\}\f$. If \f$ a\f$ is sorted, \f$ M\f$ is sorted as well. So
we can apply `sorted_matrix_search` to compute the upper bound
for the maximal entry of \f$ a\f$ in \f$ M\f$.
\cgalexample{sorted_matrix_search.cpp}
\sa `SortedMatrixSearchTraits`
*/

1
Matrix_search/doc/Matrix_search/Concepts/BasicMatrix.h
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@ -3,7 +3,6 @@
\ingroup PkgMatrixSearchConcepts
\cgalconcept
\todo advanced missing
A class `BasicMatrix` has to provide the following
types and operations in order to be a model for

1
Matrix_search/doc/Matrix_search/Concepts/MonotoneMatrixSearchTraits.h
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@ -3,7 +3,6 @@
\ingroup PkgMatrixSearchConcepts
\cgalconcept
\todo advanced missing
The concept `MonotoneMatrixSearchTraits` is a refinement of
`BasicMatrix` and defines types and operations needed to

2
Matrix_search/doc/Matrix_search/Concepts/SortedMatrixSearchTraits.h
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@ -3,8 +3,6 @@
\ingroup PkgMatrixSearchConcepts
\cgalconcept
\todo advanced missing
The concept `SortedMatrixSearchTraits` defines types and operations
needed to compute the smallest entry in a set of sorted matrices
that fulfills a certain feasibility criterion using the function

12
Matrix_search/doc/Matrix_search/Matrix_search.txt
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@ -17,6 +17,18 @@ the computation of all furthest neighbors for the vertices of a convex
polygon, maximal \f$ k\f$-gons inscribed into a planar point set, and
computing rectangular \f$ p\f$-centers.
## Example ##
In the following program we build a random vector \f$ a =
(a_i)_{i = 1,\,\ldots,\,5}\f$ (elements drawn uniformly from \f$ \{
0,\,\ldots,\,99 \}\f$) and construct a Cartesian matrix \f$ M\f$
containing as elements all sums \f$ a_i + a_j,\: i,\,j \in
\{1,\,\ldots,\,5\}\f$. If \f$ a\f$ is sorted, \f$ M\f$ is sorted as well. So
we can apply `sorted_matrix_search` to compute the upper bound
for the maximal entry of \f$ a\f$ in \f$ M\f$.
\cgalexample{sorted_matrix_search.cpp}
*/
} /* namespace CGAL */