mirror of https://github.com/CGAL/cgal
remove fake .h files: the code is already documented with doxygen
This commit is contained in:
Sébastien Loriot
parent
3e74fbd907
commit
81d24a0fcf
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@ -4763,18 +4763,6 @@ Point_set_2/doc/Point_set_2/Point_set_2.txt -text
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Point_set_2/doc/Point_set_2/examples.txt -text
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Point_set_2/doc/Point_set_2/fig/point_set.png -text svneol=unset#image/png
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Point_set_2/doc_tex/Point_set_2/point_set.png -text
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Point_set_processing_3/doc/Point_set_processing_3/CGAL/IO/read_off_points.h -text
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Point_set_processing_3/doc/Point_set_processing_3/CGAL/IO/read_xyz_points.h -text
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Point_set_processing_3/doc/Point_set_processing_3/CGAL/IO/write_off_points.h -text
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Point_set_processing_3/doc/Point_set_processing_3/CGAL/IO/write_xyz_points.h -text
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Point_set_processing_3/doc/Point_set_processing_3/CGAL/compute_average_spacing.h -text
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Point_set_processing_3/doc/Point_set_processing_3/CGAL/grid_simplify_point_set.h -text
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Point_set_processing_3/doc/Point_set_processing_3/CGAL/jet_estimate_normals.h -text
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Point_set_processing_3/doc/Point_set_processing_3/CGAL/jet_smooth_point_set.h -text
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Point_set_processing_3/doc/Point_set_processing_3/CGAL/mst_orient_normals.h -text
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Point_set_processing_3/doc/Point_set_processing_3/CGAL/pca_estimate_normals.h -text
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Point_set_processing_3/doc/Point_set_processing_3/CGAL/random_simplify_point_set.h -text
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Point_set_processing_3/doc/Point_set_processing_3/CGAL/remove_outliers.h -text
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Point_set_processing_3/doc/Point_set_processing_3/PackageDescription.txt -text
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Point_set_processing_3/doc/Point_set_processing_3/Point_set_processing_3.txt -text
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Point_set_processing_3/doc/Point_set_processing_3/examples.txt -text
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@ -1,63 +0,0 @@
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namespace CGAL {
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/*!
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\ingroup PkgPointSetProcessing
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`CGAL::read_off_points()` reads the point from a .off ASCII stream. More specifically, it reads only the point locations and ignores all point attributes available from the stream. The function expects for each point a line with the x y z position. If the position is followed by the nx ny nz normal, then the normal will be ignored. Faces are ignored.
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`CGAL::read_off_points_and_normals()` reads the points as well as the normals (if available) from a .off ASCII stream.
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In both cases the other primitives (segments, faces) are ignored.
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\sa `CGAL::read_xyz_points`
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\sa `CGAL::write_xyz_points`
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\sa `CGAL::write_off_points`
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\tparam OutputIterator iterator over output points.
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\tparam PointPMap is a model of `boost::WritablePropertyMap` with value type `Point_3<Kernel>`. It can be omitted if the value type of `OutputIterator` is convertible to `Point_3<Kernel>`.
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\tparam Kernel Geometric traits class. It can be omitted and deduced automatically from the value type of `PointPMap`.
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\returns `true` on success.
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\param stream input stream.
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\param output output iterator over points.
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\param point_pmap property map `OutputIterator` -> `Point_3`.
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\param kernel geometric traits.
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*/
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template<typename OutputIterator, typename PointPMap, typename Kernel>
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bool
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read_off_points(std::istream& stream, OutputIterator output, PointPMap point_pmap, const Kernel& kernel);
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/*!
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\ingroup PkgPointSetProcessing
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`CGAL::read_off_points_and_normals()` reads the points as well as the normals (if available) from a .off ASCII stream.
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Other primitives (segments, faces) are ignored. The function expects for each point a line with the x y z position, optionally followed by the nx ny nz normal. Faces are ignored.
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\tparam OutputIterator iterator over output points.
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\tparam PointPMap is a model of `boost::WritablePropertyMap` with the value type `Point_3<Kernel>`. It can be omitted if the value type of `OutputIterator` is convertible to `Point_3<Kernel>`.
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\tparam NormalPMap is a model of `boost::WritablePropertyMap` with the valuetype `Vector_3<Kernel>`.
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\tparam Kernel Geometric traits class. It can be omitted and deduced automatically from the value type of `PointPMap`.
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\returns `true` on success.
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\param stream input stream.
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\param output output iterator over points.
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\param point_pmap property map `OutputIterator` -> `Point_3`.
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\param normal_pmap property map `OutputIterator` -> `Vector_3`.
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\param kernel geometric traits.
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\sa `CGAL::read_xyz_points`
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\sa `CGAL::write_xyz_points`
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\sa `CGAL::write_off_points`
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*/
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template<typename OutputIterator, typename PointPMap, typename NormalPMap, typename Kernel>
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bool
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read_off_points_and_normals(std::istream& stream, OutputIterator output, PointPMap point_pmap, NormalPMap normal_pmap, const Kernel& kernel);
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} /* namespace CGAL */
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@ -1,60 +0,0 @@
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namespace CGAL {
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/*!
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\ingroup PkgPointSetProcessing
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`CGAL::read_xyz_points()` reads the point locations from a .xyz ASCII stream. The function expects for each point a line with the x y z position. If the position is followed by the nx ny nz normal, then the normal will be ignored. The first line may contain the number of points in the file. Empty lines and comments starting by # character are allowed.
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`CGAL::read_xyz_points_and_normals()` reads the points as well as the normals (if available) from a .xyz ASCII stream.
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\sa `CGAL::write_xyz_points`
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\sa `CGAL::read_off_points`
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\sa `CGAL::write_off_points`
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\tparam OutputIterator iterator over output points.
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\tparam PointPMap is a model of `boost::WritablePropertyMap` with value type `Point_3<Kernel>`. It can be omitted if the value type of `OutputIterator` is convertible to `Point_3<Kernel>`.
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\tparam Kernel Geometric traits class. It can be omitted and deduced automatically from the value type of `PointPMap`.
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\returns `true` on success.
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\param stream input stream.
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\param output output iterator over points.
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\param point_pmap property map `OutputIterator` -> `Point_3`.
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\param kernel geometric traits.
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*/
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template<typename OutputIterator, typename PointPMap, typename Kernel>
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bool
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read_xyz_points(std::istream& stream, OutputIterator output, PointPMap point_pmap, const Kernel& kernel);
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/*!
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\ingroup PkgPointSetProcessing
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`CGAL::read_xyz_points_and_normals()` reads the points as well as the normals (if available) from a .xyz ASCII stream.
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The function expects for each point a line with the x y z position, optionally followed by the nx ny nz normal. The first line may contain the number of points in the file. Empty lines and comments starting by # character are allowed.
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\tparam OutputIterator iterator over output points.
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\tparam PointPMap is a model of `boost::WritablePropertyMap` with value type `Point_3<Kernel>`. It can be omitted if the value type of `OutputIterator` is convertible to `Point_3<Kernel>`.
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\tparam NormalPMap is a model of `boost::WritablePropertyMap` with value type `Vector_3<Kernel>`.
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\tparam Kernel Geometric traits class. It can be omitted and deduced automatically from the value type of `PointPMap`.
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\returns `true` on success.
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\param stream input stream.
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\param output output iterator over points.
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\param point_pmap property map `OutputIterator` -> `Point_3`.
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\param normal_pmap property map `OutputIterator` -> `Vector_3`.
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\param kernel geometric traits.
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\sa `CGAL::write_xyz_points`
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\sa `CGAL::read_off_points`
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\sa `CGAL::write_off_points`
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*/
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template<typename OutputIterator, typename PointPMap, typename NormalPMap, typename Kernel>
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bool
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read_xyz_points_and_normals(std::istream& stream, OutputIterator output, PointPMap point_pmap, NormalPMap normal_pmap, const Kernel& kernel);
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} /* namespace CGAL */
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@ -1,59 +0,0 @@
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namespace CGAL {
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/*!
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\ingroup PkgPointSetProcessing
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`CGAL::write_off_points()` saves the points of an iterator range to a .off ASCII stream. More specifically, it saves only the point locations and ignores all other attributes. The function writes for each point a line.
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\tparam ForwardIterator iterator over input points.
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\tparam PointPMap is a model of `boost::ReadablePropertyMap` with value type `Point_3<Kernel>`. It can be omitted if the value type of `ForwardIterator` is convertible to `Point_3<Kernel>`.
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\tparam Kernel Geometric traits class. It can be omitted and deduced automatically from the value type of `PointPMap`.
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\returns `true` on success.
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\param stream output stream.
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\param first,beyond iterator range over the input points.
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\param point_pmap property map `ForwardIterator` -> `Point_3`.
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\param kernel geometric traits.
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\sa `CGAL::read_xyz_points`
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\sa `CGAL::write_xyz_points`
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\sa `CGAL::read_off_points`
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*/
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template<typename ForwardIterator, typename PointPMap, typename Kernel>
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bool
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write_off_points(std::ostream& stream, ForwardIterator first, ForwardIterator beyond, PointPMap point_pmap, const Kernel& kernel);
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/*!
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\ingroup PkgPointSetProcessing
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`CGAL::write_off_points_and_normals()` saves the points as well the normals of an iterator range to a .off ASCII stream. The function writes for each point a line with the x y z position followed by the nx ny nz normal.
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\tparam ForwardIterator iterator over input points.
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\tparam PointPMap is a model of `boost::ReadablePropertyMap` with value type `Point_3<Kernel>`. It can be omitted if the value type of `ForwardIterator` is convertible to `Point_3<Kernel>`.
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\tparam NormalPMap is a model of `boost::WritablePropertyMap` with value type `Vector_3<Kernel>`.
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\tparam Kernel Geometric traits class. It can be omitted and deduced automatically from the value type of `PointPMap`.
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\returns `true` on success.
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\param stream output stream.
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\param first, beyond iterator range over the input points.
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\param point_pmap property map `ForwardIterator` -> `Point_3`.
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\param normal_pmap property map `ForwardIterator` -> `Vector_3`.
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\param kernel geometric traits.
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\sa `CGAL::read_xyz_points`
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\sa `CGAL::write_xyz_points`
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\sa `CGAL::read_off_points`
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*/
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template<typename ForwardIterator, typename PointPMap, typename NormalPMap, typename Kernel>
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bool
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write_off_points_and_normals(std::ostream& stream, ForwardIterator first, ForwardIterator beyond, PointPMap point_pmap, NormalPMap normal_pmap, const Kernel& kernel);
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} /* namespace CGAL */
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@ -1,59 +0,0 @@
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namespace CGAL {
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/*!
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\ingroup PkgPointSetProcessing
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`CGAL::write_xyz_points()` writes points (positions only) to a .xyz ASCII stream.
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\tparam ForwardIterator iterator over input points.
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\tparam PointPMap is a model of `boost::ReadablePropertyMap` with value type `Point_3<Kernel>`. It can be omitted if the value type of `ForwardIterator` is convertible to `Point_3<Kernel>`.
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\tparam Kernel Geometric traits class. It can be omitted and deduced automatically from the value type of `PointPMap`.
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\returns `true` on success.
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\param stream` output stream.
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\param first, beyond iterator range over the input points.
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\param point_pmap property map `ForwardIterator` -> `Point_3`.
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\param kernel geometric traits.
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\sa `CGAL::read_xyz_points`
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\sa `CGAL::read_off_points`
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\sa `CGAL::write_off_points`
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*/
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template<typename ForwardIterator, typename PointPMap, typename Kernel>
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bool
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write_xyz_points(std::ostream& stream, ForwardIterator first, ForwardIterator beyond, PointPMap point_pmap, const Kernel& kernel);
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/*!
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\ingroup PkgPointSetProcessing
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`CGAL::write_xyz_points_and_normals()` saves points (positions + normals) to a .xyz ASCII stream. The function writes for each point a line with the x y z position followed by the nx ny nz normal.
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\sa `CGAL::read_xyz_points`
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\sa `CGAL::read_off_points`
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\sa `CGAL::write_off_points`
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\tparam ForwardIterator iterator over input points.
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\tparam PointPMap is a model of `boost::ReadablePropertyMap` with value type `Point_3<Kernel>`. It can be omitted if the value type of `ForwardIterator` is convertible to `Point_3<Kernel>`.
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\tparam NormalPMap is a model of `boost::WritablePropertyMap` with value type `Vector_3<Kernel>`.
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\tparam Kernel Geometric traits class. It can be omitted and deduced automatically from the value type of `PointPMap`.
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\returns `true` on success.
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\param stream output stream.
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\param first iterator range over the input points.
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\param point_pmap property map `ForwardIterator` -> `Point_3`.
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\param normal_pmap property map `ForwardIterator` -> `Vector_3`.
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\param kernel geometric traits.
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*/
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template<typename ForwardIterator, typename PointPMap, typename NormalPMap, typename Kernel>
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bool
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write_xyz_points_and_normals(std::ostream& stream, ForwardIterator first, ForwardIterator beyond, PointPMap point_pmap, NormalPMap normal_pmap, const Kernel& kernel);
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} /* namespace CGAL */
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@ -1,30 +0,0 @@
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namespace CGAL {
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/*!
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\ingroup PkgPointSetProcessing
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`CGAL::compute_average_spacing()` computes the average spacing of all points from the input set to their `k` nearest neighbors. This value depends on the `k` parameter which can be set to 6 for isotropically sampled surfaces.
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\pre k \f$ >\f$= 2.
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\tparam InputIterator iterator over input points.
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\tparam PointPMap is a model of `boost::ReadablePropertyMap` with value type `Point_3<Kernel>`. It can be omitted if the value type of `InputIterator` is convertible to `Point_3<Kernel>`.
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\tparam Kernel Geometric traits class. It can be omitted and deduced automatically from the value type of `PointPMap`.
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\returns average spacing (scalar).
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\param first, beyond iterator range of the input points.
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\param point_pmap property map `InputIterator` -> `Point_3`.
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\param k number of neighbors.
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\param kernel geometric traits.
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*/
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template<typename InputIterator, typename PointPMap, typename Kernel> Kernel::FT compute_average_spacing(InputIterator first, InputIterator beyond, PointPMap point_pmap, unsigned int k, const Kernel& kernel);
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} /* namespace CGAL */
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namespace CGAL {
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/*!
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\ingroup PkgPointSetProcessing
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Merges points which belong to the same cell of a grid of cell size = epsilon.
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This method modifies the order of input points so as to pack all remaining points first, and returns an iterator over the first point to remove (see erase-remove idiom). For this reason it should not be called on sorted containers.
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\pre epsilon \f$ >\f$ 0.
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\tparam ForwardIterator iterator over input points.
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\tparam PointPMap is a model of `boost::ReadablePropertyMap` with value type `Point_3<Kernel>`. It can be omitted if the value type of `ForwardIterator` is convertible to `Point_3<Kernel>`.
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\tparam Kernel Geometric traits class. It can be omitted and deduced automatically from the value type of `PointPMap`.
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\returns iterator over the first point to remove.
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\param first, beyond iterator range of the input points.
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\param point_pmap property map `ForwardIterator` -> `Point_3`.
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\param epsilon tolerance value when merging 3D points.
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\param kernel geometric traits.
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\sa `CGAL::random_simplify_point_set`
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*/
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template<typename ForwardIterator, typename PointPMap, typename Kernel> ForwardIterator grid_simplify_point_set(ForwardIterator first, ForwardIterator beyond, PointPMap point_pmap, double epsilon, const Kernel& kernel);
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} /* namespace CGAL */
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namespace CGAL {
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/*!
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\ingroup PkgPointSetProcessing
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`CGAL::jet_estimate_normals()` estimates normal directions of all points from the input set by fitting jet surfaces over the `k` nearest neighbors. The default jet surface is a quadric, and the result is an unoriented normal vector for each input point.
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The output of the normal estimation algorithm highly depends on the `k` parameter.
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The number of neighbors controls the size of the point subset considered for jet fitting at each input point. As this parameter is application-specific we do not provide any default value. Larger values lead to smoother normal fields and are more time consuming. For point sets with limited noise this value can be set to small number such as 18. For noisy point sets this value must be increased.
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\tparam InputIterator iterator over input points.
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\tparam PointPMap is a model of `boost::ReadablePropertyMap` with value type `Point_3<Kernel>`. It can be omitted if the value type of `InputIterator` is convertible to `Point_3<Kernel>`.
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\tparam NormalPMap is a model of `boost::WritablePropertyMap` with value type `Vector_3<Kernel>`.
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\tparam Kernel Geometric traits class. It can be omitted and deduced automatically from the value type of `PointPMap`.
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\param first, beyond iterator range of the input points.
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\param point_pmap property map `InputIterator` -> `Point_3`.
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\param normal_pmap property map `InputIterator` -> `Vector_3`.
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\param k number of neighbors.
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\param kernel geometric traits.
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\sa `CGAL::pca_estimate_normals`
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\sa `CGAL::mst_orient_normals`
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*/
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template<typename InputIterator, typename PointPMap, typename NormalPMap, typename Kernel> void jet_estimate_normals(InputIterator first, InputIterator beyond, PointPMap point_pmap, NormalPMap normal_pmap, unsigned int k, const Kernel& kernel, unsigned int degree_fitting = 2);
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} /* namespace CGAL */
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namespace CGAL {
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/*!
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\ingroup PkgPointSetProcessing
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`CGAL::jet_smooth_point_set()` smoothes a point set by fitting for each point a jet surface and projecting it onto the jet. The default jet surface is a quadric.
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The output of the smoothing algorithm highly depends on the `k` parameter.
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The number of neighbors controls the size of the point subset considered for jet fitting at each input point. As this parameter is application-specific we do not provide any default value. Larger values lead to smoother point sets and are more time consuming. For point sets with limited noise this value can be set to small number such as 24. For noisy point sets this value must be increased.
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As this method relocates the points, it should not be called on containers sorted w.r.t. point locations.
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\pre k \f$ >\f$= 2.
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\tparam InputIterator iterator over input points.
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\tparam PointPMap is a model of `boost::ReadablePropertyMap` with value type `Point_3<Kernel>`. It can be omitted if the value type of `InputIterator` is convertible to `Point_3<Kernel>`.
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\tparam Kernel Geometric traits class. It can be omitted and deduced automatically from the value type of `PointPMap`.
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\param first, beyond iterator range of the input points.
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\param point_pmap property map `InputIterator` -> `Point_3`.
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\param k number of neighbors.
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\param kernel geometric traits.
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*/
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template<typename InputIterator, typename PointPMap, typename Kernel> void jet_smooth_point_set(InputIterator first, InputIterator beyond, PointPMap point_pmap, unsigned int k, const Kernel& kernel, unsigned int degree_fitting = 2, unsigned int degree_monge = 2);
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||||
|
||||
} /* namespace CGAL */
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||||
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||||
|
|
@ -1,38 +0,0 @@
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|||
namespace CGAL {
|
||||
|
||||
/*!
|
||||
\ingroup PkgPointSetProcessing
|
||||
|
||||
`CGAL::mst_orient_normals()` orients the normals of a point set using the propagation of a seed orientation through a minimum spanning tree computed over the Riemannian graph.
|
||||
|
||||
The seed is chosen as the top point of the point set. Its normal is oriented towards +Z axis. The success of the orientation algorithm depends on the `k` parameter.
|
||||
The number of neighbors controls the number of candidates to propagate the orientation to around each input point. In general the value 18 works well. With smaller values the propagation may be blocked by large gaps in sparse point sets as the graph may be disconnected. Large values cause problems with points scattered over thin objects as the algorithm may incorrectly propagate the orientation from one side of the object to the other. In presence of disconnected clusters of points the algorithm may fail propagating the orientation from one cluster to the others and may only orient the top cluster.
|
||||
|
||||
This method modifies the order of the input points so as to pack all successfully oriented normals first, and returns an iterator over the first point with an unoriented normal (see erase-remove idiom). For this reason it should not be called on sorted containers.
|
||||
|
||||
|
||||
\pre Normals must be unit vectors. k \f$ >\f$= 2.
|
||||
|
||||
\tparam ForwardIterator iterator over input points.
|
||||
\tparam PointPMap is a model of `boost::ReadablePropertyMap` with value type `Point_3<Kernel>`. It can be omitted if the value type of `ForwardIterator` is convertible to `Point_3<Kernel>`.
|
||||
\tparam NormalPMap is a model of `boost::ReadWritePropertyMap` with value type `Vector_3<Kernel>`.
|
||||
\tparam Kernel Geometric traits class. It can be omitted and deduced automatically from the value type of `PointPMap`.
|
||||
|
||||
\returns iterator over the first point with an unoriented normal.
|
||||
|
||||
\param first, beyond iterator range of the input points.
|
||||
\param point_pmap property map `ForwardIterator` -> `Point_3`.
|
||||
\param normal_pmap property map `ForwardIterator` -> `Vector_3`.
|
||||
\param k number of neighbors.
|
||||
\param kernel geometric traits.
|
||||
|
||||
|
||||
\sa `CGAL::pca_estimate_normals`
|
||||
\sa `CGAL::jet_estimate_normals`
|
||||
|
||||
|
||||
*/
|
||||
template<typename ForwardIterator, typename PointPMap, typename NormalPMap, typename Kernel> ForwardIterator mst_orient_normals(ForwardIterator first, ForwardIterator beyond, PointPMap point_pmap, NormalPMap normal_pmap, unsigned int k, const Kernel& kernel);
|
||||
|
||||
} /* namespace CGAL */
|
||||
|
||||
|
|
@ -1,33 +0,0 @@
|
|||
namespace CGAL {
|
||||
|
||||
/*!
|
||||
\ingroup PkgPointSetProcessing
|
||||
|
||||
`CGAL::pca_estimate_normals()` estimates normal directions at all points of an input point set by linear least squares fitting of a plane over their `k` nearest neighbors. The result is an unoriented normal for each input point.
|
||||
|
||||
The output of the normal estimation algorithm highly depends on the `k` parameter.
|
||||
The number of neighbors controls the size of the point subset considered for plane fitting at each input point. As this parameter is application-specific we do not provide any default value. For noise-free point sets this value can be set to a small number, e.g., 18. Larger values (e.g., 30 or more) lead to smoother normal fields and are more time consuming. We thus recommend using them only for noisy data sets.
|
||||
|
||||
\pre k \f$ >\f$= 2.
|
||||
|
||||
\tparam InputIterator iterator over input points.
|
||||
\tparam PointPMap is a model of `boost::ReadablePropertyMap` with value type `Point_3<Kernel>`. It can be omitted if the value type of `InputIterator` is convertible to `Point_3<Kernel>`.
|
||||
\tparam NormalPMap is a model of `boost::WritablePropertyMap` with value type `Vector_3<Kernel>`.
|
||||
\tparam Kernel Geometric traits class. It can be omitted and deduced automatically from the value type of `PointPMap`.
|
||||
|
||||
|
||||
\param first, beyond iterator range of the input points.
|
||||
\param point_pmap property map `InputIterator` -> `Point_3`.
|
||||
\param normal_pmap property map `InputIterator` -> `Vector_3`.
|
||||
\param k number of neighbors.
|
||||
\param kernel geometric traits.
|
||||
|
||||
|
||||
\sa `CGAL::jet_estimate_normals`
|
||||
\sa `CGAL::mst_orient_normals`
|
||||
|
||||
*/
|
||||
template<typename InputIterator, typename PointPMap, typename NormalPMap, typename Kernel> void pca_estimate_normals(InputIterator first, InputIterator beyond, PointPMap point_pmap, NormalPMap normal_pmap, unsigned int k, const Kernel& kernel);
|
||||
|
||||
} /* namespace CGAL */
|
||||
|
||||
|
|
@ -1,27 +0,0 @@
|
|||
namespace CGAL {
|
||||
|
||||
/*!
|
||||
\ingroup PkgPointSetProcessing
|
||||
|
||||
`CGAL::random_simplify_point_set()` randomly deletes a user-specified fraction of the input points. This method modifies the order of input points so as to pack all remaining points first, and returns an iterator over the first point to remove (see erase-remove idiom). For this reason it should not be called on sorted containers.
|
||||
|
||||
|
||||
\tparam ForwardIterator iterator over input points.
|
||||
\tparam PointPMap is a model of `boost::ReadablePropertyMap` with value type `Point_3<Kernel>`. It can be omitted if the value type of `ForwardIterator` is convertible to `Point_3<Kernel>`.
|
||||
\tparam Kernel Geometric traits class. It can be omitted and deduced automatically from the value type of `PointPMap`.
|
||||
|
||||
\returns iterator over the first point to remove.
|
||||
|
||||
\param first, beyond iterator range of the input points.
|
||||
\param point_pmap property map `ForwardIterator` -> `Point_3`.
|
||||
\param removed_percentage percentage of points to remove.
|
||||
\param kernel geometric traits.
|
||||
|
||||
\sa `CGAL::grid_simplify_point_set`
|
||||
|
||||
|
||||
*/
|
||||
template<typename ForwardIterator, typename PointPMap, typename Kernel> ForwardIterator random_simplify_point_set(ForwardIterator first, ForwardIterator beyond, PointPMap point_pmap, double removed_percentage, const Kernel& kernel);
|
||||
|
||||
} /* namespace CGAL */
|
||||
|
||||
|
|
@ -1,39 +0,0 @@
|
|||
namespace CGAL {
|
||||
|
||||
/*!
|
||||
\ingroup PkgPointSetProcessing
|
||||
|
||||
`CGAL::remove_outliers()` deletes a user-specified fraction of outliers from the input point set. More specifically, it sorts the input points in increasing order of average squared distances to the `k` nearest neighbors and computes the points with largest value.
|
||||
|
||||
The outliers detection depends on the `k` parameter, specifically the detection of clusters of outliers.
|
||||
The number of neighbors should be higher than the size of clusters of outliers in the point set.
|
||||
For datasets with no cluster of outliers, this value can be set to a few rings, e.g. 24. Larger value leads to longer computation times.
|
||||
For these reasons, we do not provide any default value for this parameter.
|
||||
|
||||
This method modifies the order of input points so as to pack all remaining points first, and returns an iterator over the first point to remove (see erase-remove idiom). For this reason it should not be called on sorted containers.
|
||||
|
||||
|
||||
|
||||
\pre k \f$>\f$= 2.
|
||||
|
||||
\tparam InputIterator iterator over input points.
|
||||
|
||||
\tparam PointPMap is a model of `boost::ReadablePropertyMap` with value type `Point_3<Kernel>`. It can be omitted if the value type of `InputIterator` is convertible to `Point_3<Kernel>`.
|
||||
|
||||
\tparam Kernel Geometric traits class. It can be omitted and deduced automatically from the value type of `PointPMap`.
|
||||
|
||||
|
||||
\returns iterator over the first point to remove.
|
||||
|
||||
|
||||
\param first, beyond iterator range of the input points.
|
||||
\param point_pmap property map `InputIterator` -> `Point_3`.
|
||||
\param k number of neighbors.
|
||||
\param threshold_percent percentage of points to remove.
|
||||
\param kernel geometric traits.
|
||||
|
||||
*/
|
||||
template<typename InputIterator, typename PointPMap, typename Kernel> InputIterator remove_outliers(InputIterator first, InputIterator beyond, PointPMap point_pmap, unsigned int k, double threshold_percent, const Kernel& kernel);
|
||||
|
||||
} /* namespace CGAL */
|
||||
|
||||
Loading…
Reference in New Issue