mirror of https://github.com/CGAL/cgal
move example to user manual. de-advance
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@ -4,8 +4,6 @@ namespace CGAL {
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/*!
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/*!
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\ingroup PkgMatrixSearch
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\ingroup PkgMatrixSearch
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\todo advanced is missing
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The class `Dynamic_matrix` is an adaptor for an arbitrary
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The class `Dynamic_matrix` is an adaptor for an arbitrary
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matrix class `M` to provide the dynamic operations needed for monotone
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matrix class `M` to provide the dynamic operations needed for monotone
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matrix search.
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matrix search.
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@ -4,8 +4,6 @@ namespace CGAL {
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/*!
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/*!
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\ingroup PkgMatrixSearch
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\ingroup PkgMatrixSearch
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\todo advanced missing
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The class `Sorted_matrix_search_traits_adaptor` can be used
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The class `Sorted_matrix_search_traits_adaptor` can be used
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as an adaptor to create sorted matrix search traits classes for
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as an adaptor to create sorted matrix search traits classes for
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arbitrary feasibility test and matrix classes `F` resp. `M`.
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arbitrary feasibility test and matrix classes `F` resp. `M`.
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@ -3,7 +3,6 @@ namespace CGAL {
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/*!
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/*!
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\ingroup PkgMatrixSearch
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\ingroup PkgMatrixSearch
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\todo advanced missing
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The function `monotone_matrix_search` computes the maxima
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The function `monotone_matrix_search` computes the maxima
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for all rows of a totally monotone matrix.
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for all rows of a totally monotone matrix.
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@ -3,8 +3,6 @@ namespace CGAL {
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/*!
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/*!
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\ingroup PkgMatrixSearch
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\ingroup PkgMatrixSearch
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\todo advanced missing
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The function `sorted_matrix_search` selects the smallest entry
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The function `sorted_matrix_search` selects the smallest entry
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in a set of sorted matrices that fulfills a certain feasibility
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in a set of sorted matrices that fulfills a certain feasibility
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criterion.
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criterion.
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@ -56,17 +54,6 @@ Frederickson and Johnson\cite fj-fkppc-83, \cite fj-gsrsm-84 and runs in
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the number of input matrices, \f$ k\f$ denotes the maximal dimension of
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the number of input matrices, \f$ k\f$ denotes the maximal dimension of
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any input matrix and \f$ f\f$ the time needed for one feasibility test.
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any input matrix and \f$ f\f$ the time needed for one feasibility test.
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### Example ###
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In the following program we build a random vector \f$ a =
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(a_i)_{i = 1,\,\ldots,\,5}\f$ (elements drawn uniformly from \f$ \{
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0,\,\ldots,\,99 \}\f$) and construct a Cartesian matrix \f$ M\f$
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containing as elements all sums \f$ a_i + a_j,\: i,\,j \in
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\{1,\,\ldots,\,5\}\f$. If \f$ a\f$ is sorted, \f$ M\f$ is sorted as well. So
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we can apply `sorted_matrix_search` to compute the upper bound
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for the maximal entry of \f$ a\f$ in \f$ M\f$.
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\cgalexample{sorted_matrix_search.cpp}
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\sa `SortedMatrixSearchTraits`
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\sa `SortedMatrixSearchTraits`
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*/
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*/
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@ -3,7 +3,6 @@
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\ingroup PkgMatrixSearchConcepts
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\ingroup PkgMatrixSearchConcepts
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\cgalconcept
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\cgalconcept
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\todo advanced missing
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A class `BasicMatrix` has to provide the following
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A class `BasicMatrix` has to provide the following
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types and operations in order to be a model for
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types and operations in order to be a model for
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@ -3,7 +3,6 @@
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\ingroup PkgMatrixSearchConcepts
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\ingroup PkgMatrixSearchConcepts
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\cgalconcept
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\cgalconcept
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\todo advanced missing
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The concept `MonotoneMatrixSearchTraits` is a refinement of
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The concept `MonotoneMatrixSearchTraits` is a refinement of
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`BasicMatrix` and defines types and operations needed to
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`BasicMatrix` and defines types and operations needed to
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@ -3,8 +3,6 @@
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\ingroup PkgMatrixSearchConcepts
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\ingroup PkgMatrixSearchConcepts
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\cgalconcept
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\cgalconcept
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\todo advanced missing
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The concept `SortedMatrixSearchTraits` defines types and operations
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The concept `SortedMatrixSearchTraits` defines types and operations
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needed to compute the smallest entry in a set of sorted matrices
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needed to compute the smallest entry in a set of sorted matrices
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that fulfills a certain feasibility criterion using the function
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that fulfills a certain feasibility criterion using the function
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@ -17,6 +17,18 @@ the computation of all furthest neighbors for the vertices of a convex
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polygon, maximal \f$ k\f$-gons inscribed into a planar point set, and
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polygon, maximal \f$ k\f$-gons inscribed into a planar point set, and
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computing rectangular \f$ p\f$-centers.
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computing rectangular \f$ p\f$-centers.
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## Example ##
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In the following program we build a random vector \f$ a =
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(a_i)_{i = 1,\,\ldots,\,5}\f$ (elements drawn uniformly from \f$ \{
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0,\,\ldots,\,99 \}\f$) and construct a Cartesian matrix \f$ M\f$
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containing as elements all sums \f$ a_i + a_j,\: i,\,j \in
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\{1,\,\ldots,\,5\}\f$. If \f$ a\f$ is sorted, \f$ M\f$ is sorted as well. So
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we can apply `sorted_matrix_search` to compute the upper bound
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for the maximal entry of \f$ a\f$ in \f$ M\f$.
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\cgalexample{sorted_matrix_search.cpp}
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*/
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*/
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} /* namespace CGAL */
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} /* namespace CGAL */
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