This Source Code Form is subject to the terms of the Mozilla Public License, v. More...

Namespaces
namespace	internal
	Copyright (c) 2022 Jacques-Olivier Lachaud (`jacqu.nosp@m.es-o.nosp@m.livie.nosp@m.r.la.nosp@m.chaud.nosp@m.@uni.nosp@m.v-sav.nosp@m.oie..nosp@m.fr`) Laboratory of Mathematics (CNRS, UMR 5807), University of Savoie, France,.

Classes
class	AbstractNeighborGraph
	Base class for neighbor graphs. More...

class	AlgebraicSphere
	Algebraic Sphere primitive. More...

class	Basket
	Aggregator class used to declare specialized structures using CRTP. More...

struct	BasketComputeObject
	Base ComputeObject for the Basket classes. More...

class	BasketDiff
	Aggregator class used to declare specialized structures with derivatives computations, using CRTP. More...

class	BasketDiffUnitBase
	Base class of any computation unit of a BasketDiff. More...

class	BasketUnitBase
	Base class of any computation unit of a Basket. More...

class	BitSet
	A simple BitSet implementation that mimics a set of indices. More...

class	CenteredNeighborhoodFrame
	NeighborhoodFrame that express 3d points relatively to a prescribed center. More...

class	CNC
	Corrected Normal Current Fit type. More...

class	CompactExpWeightKernel
	Compact Exponential WeightKernel defined in $\left[0 : 1\right]$. More...

struct	ComputeObject
	ComputeObject is a virtual object that represents an algorithm which can be used with the compute functions. More...

class	ConstantWeightKernel
	Concept::WeightKernelConcept returning a constant value. More...

class	CovarianceBase
	Procedure that compute and decompose the covariance matrix of the neighbors positions. More...

class	CovarianceDer
	Internal generic class computing the derivatives of covariance matrix computed by covarianceBase. More...

class	CovarianceLineFitImpl
	Line fitting procedure that minimize the orthogonal distance between the samples and the fitted primitive. More...

class	CovariancePlaneDerImpl
	[CovariancePlaneFit Definition] More...

class	CovariancePlaneFitImpl
	Plane fitting procedure using only points position. More...

struct	DirectProjectionOperator
	Project a point using the primitive projection operator. More...

class	DistWeightFilter
	Weight neighbors according to the Euclidean distance between a query and a reference position. More...

class	DryFit
	Empty fitting object doing no computation. More...

class	FilterWithAttributes
	This class extends a NeighborFilter class to also store additional data, for use outside the scope of this class. More...

class	FundamentalFormWeingartenEstimator
	Compute a Weingarten map from fundamental forms. More...

class	GaussianWeightKernel
	Non-compact Gaussian WeightKernel. More...

class	GlobalNeighborhoodFrame
	NeighborhoodFrame that keep points in the global frame without applying any transformation This class is useful to compute direct fits in the embedding space, without paying the cost to express neighbors relatively to an evaluation point. More...

class	GLSDer
	Differentiation of GLSParam. More...

class	GLSParam
	Growing Least Squares reparametrization of the OrientedSphereFit. More...

struct	GradientDescentProjectionOperator
	Project a point using the gradinet of the sdf. More...

struct	hasFirstFundamentalForm
	\FIXME create a macro to automatically generate the testing functions More...

struct	hasFirstFundamentalForm< T, std::void_t< decltype(std::declval< T >().firstFundamentalForm())> >

struct	HashDefaultFunctor

class	HashSet
	Stores unique signed integer values in a contiguous array. More...

class	HeightField
	Internal base classe for height fields. More...

struct	IndexSquaredDistance
	Associates an index with a distance. More...

struct	KdTree
	Abstract KdTree type with KdTreeDefaultTraits. More...

class	KdTreeBase

class	KdTreeCustomizableNode
	The node type used by default by the kd-tree. More...

struct	KdTreeDefaultInnerNode

struct	KdTreeDefaultLeafNode

struct	KdTreeDefaultNode

struct	KdTreeDefaultTraits
	The default traits type used by the kd-tree. More...

struct	KdTreeDense
	Public interface for dense KdTree datastructure. More...

class	KdTreeDenseBase
	Customizable base class for dense KdTree datastructure. More...

class	KdTreeKNearestIterator
	Input iterator to read the `KdTreeKNearestQueryBase` object. More...

class	KdTreeKNearestQueryBase
	Extension of the Query class that allows to read the result of a k-nearest neighbors search on the KdTree. More...

class	KdTreeNearestIterator
	Input iterator to read the `KdTreeKNearestQueryBase` object. More...

class	KdTreeNearestQueryBase
	Extension of the Query class that allows to read the result of a nearest neighbor search on the KdTree. More...

struct	KdTreePointerTraits
	Variant to the KdTree Traits type that uses pointers as internal storage instead of an STL-like container. More...

class	KdTreeQuery
	Query object that provides a method to search neighbors on the KdTree depending on a distance threshold. More...

class	KdTreeRangeIterator
	Input iterator to read the `KdTreeRangeQueryBase` object. More...

class	KdTreeRangeQueryBase
	Extension of the Query class that allows to read the result of a range neighbors search on the KdTree. More...

struct	KdTreeSparse
	Public interface for sparse KdTree datastructure. More...

class	KdTreeSparseBase
	Customizable base class for KdTreeSparse datastructure. More...

class	KnnGraphBase

struct	KnnGraphBuffers
	Buffer class for StaticKnnGraphBase. More...

class	LimitedPriorityQueue
	The LimitedPriorityQueue class is similar to std::priority_queue but has a limited capacity and handles the comparison differently. More...

class	Line
	A parametrized line is defined by an origin point $\mathbf{o}$ and a unit direction vector $\overrightarrow{\mathbf{d}}$ such that the line corresponds to the set $l(t)=\mathbf{o}+t\overrightarrow{\mathbf{d}}, t\in \mathbb{R}$. More...

class	MeanPlaneFitImpl
	Plane fitting procedure computing the mean position and orientation from oriented points. More...

class	MeanPosition
	Compute the barycenter of the input points. More...

struct	MLSEvaluationScheme
	Computes the fit using the Moving Least Squares approach. More...

class	MlsSphereFitDer
	Extension performing derivation of the mls surface. More...

class	MongePatch
	Monge Patch primitive, defined as $ \mathbf{x}(u,v)= (u,v,h(u,v)) $, with $h(u,v)$ defined by a Base class. More...

class	MongePatchQuadraticFitImpl
	Extension to compute the best fit quadric on 3d points expressed as $f(u,v)=h$. More...

class	MongePatchRestrictedQuadraticFitImpl
	Extension to compute the best fit restricted quadric on 3d points expressed as $f(u,v)=h$. More...

class	MultipassStatus
	Helper class to check for status of required extensions. More...

class	NeighborGraphBase

struct	NeighborGraphBuffer
	Buffer class for StaticNeighborGraphBase. More...

struct	NeighborGraphBufferBase
	Internal structure storing the buffers used by a neighbor graph. More...

struct	NeighborGraphDefaultTraits
	The default traits type used by the neighbor graph. More...

class	NeighborGraphOneConnectedIterator
	Base iterator class for NeighborGraphOneConnectedQuery. More...

class	NeighborGraphOneConnectedQuery
	Extension of the Query class that allows to read the neighbors that are directly connected to the query point in the neighbor graph. More...

struct	NeighborGraphPointerTraits
	Variant to the NeighborGraphDefaultTraits that uses pointers as internal storage instead of an STL-like container. More...

struct	NeighborGraphQueryOutputType
	Output type of the NeighborGraphOneConnectedQuery. More...

class	NeighborGraphRangeIterator
	Input iterator to read the `NeighborGraphRangeQuery` object. More...

class	NeighborGraphRangeQuery
	Extension of the Query class that allows to read the result of a range neighbor search on the KnnGraph. More...

class	NormalDerivativeWeingartenEstimator
	Compute a Weingarten map from the spatial derivatives of the normal field $ N $. More...

struct	NoWeightFilter
	Weighting function that set uniform weight to all samples, but transform neighbors coordinates to local frame. More...

struct	NoWeightFilterGlobal
	Weighting function that set uniform weight to all samples and keep neighbors coordinates in global frame. More...

class	OrientedSphereDerImpl
	[OrientedSphereFit Definition] More...

class	OrientedSphereFitImpl
	Algebraic Sphere fitting procedure on oriented point sets. More...

class	Plane
	Implicit hyperplane defined by an homogeneous vector $\mathbf{p}$. More...

class	PointPosition
	Point data type containing only containing the position vector. More...

class	PointPositionNormal
	Point data type containing the position and normal vectors. More...

class	PointPositionNormalBinding
	Variant of the PointPositionNormal data type that uses external raw data. More...

class	PointPositionNormalLazyBinding
	Variant of the PointPositionNormal data type that uses external raw data. More...

class	PolynomialSmoothWeightKernel
	Compact generalised version of SmoothWeightKernel with arbitrary degrees : $ w(x)=(x^n-1)^m $. More...

class	QuadraticHeightField
	Quadratic height field defined as $h(u,v)=h_{uu}u^2 + h_{vv}v^2 + h_{uv}uv + h_u u + h_v v + h_c $. More...

struct	Query
	Composes the Query object depending on an input type and output type. More...

struct	QueryInput
	Base class for Query input type. More...

struct	QueryInputBase
	Base class for queries input type. More...

struct	QueryInputIsIndex
	Extension of `QueryInput` that handles an index based search, in a partitioning structure. More...

struct	QueryInputIsPosition
	Extension of `QueryInput` that handles a position based search, in a partitioning structure. More...

struct	QueryOutputBase
	Base class for queries output types. More...

struct	QueryOutputIsKNearest
	Class to construct the knearest queries. More...

struct	QueryOutputIsNearest
	Class to construct the nearest query output. More...

struct	QueryOutputIsRange
	Class to construct the range query output. More...

class	RestrictedQuadraticHeightField
	Quadratic height field defined as $h(u,v)=h_{uu}u^2 + h_{vv}v^2 + h_{uv}uv + h_c $. More...

struct	SingleEvaluationScheme
	SingleEvaluationScheme. More...

class	SingularWeightKernel
	Compact singular WeightKernel defined in $\left]0 : 1\right]$. More...

class	SmoothWeightKernel
	Compact smooth WeightKernel of 2nd degree, defined in $\left[0 : 1\right]$ Special case of PolynomialSmoothWeightKernel<Scalar, 2, 2> More...

class	SphereFitImpl
	Algebraic Sphere fitting procedure on point set without normals. More...

class	Stack
	Stack with fixed-size storage. More...

struct	StaticKdTree
	A KdTree type with KdTreeDefaultTraits that doesn't define the build function. More...

class	StaticKdTreeBase
	Customizable static base class for KdTree datastructure implementations. More...

class	StaticKnnGraphBase
	Customizable base class for KnnGraph datastructure. More...

class	StaticNeighborGraphBase
	Static generic neighbor graph (does not include build functions) More...

class	UnorientedSphereDerImpl

class	UnorientedSphereFitImpl
	Algebraic Sphere fitting procedure on point sets with non-oriented normals. More...

struct	WeingartenCurvatureEstimator
	Compute principal curvatures from a base class providing fundamental forms. More...

struct	WeingartenCurvatureEstimatorDer
	Compute principal curvatures from a base class providing fundamental forms. More...

class	WendlandWeightKernel
	Compact Wendland WeightKernel defined in $\left[0 : 1\right]$. More...

Typedefs
template<class DataPoint , class _NFilter , typename T >
using	CovarianceLineFit = CovarianceLineFitImpl< DataPoint, _NFilter, CovarianceBase< DataPoint, _NFilter, MeanPosition< DataPoint, _NFilter, Line< DataPoint, _NFilter, T > > > >
	Helper alias for Line fitting on 3D points using CovarianceLineFitImpl.

template<class DataPoint , class _NFilter , typename T >
using	CovariancePlaneFit = CovariancePlaneFitImpl< DataPoint, _NFilter, CovarianceBase< DataPoint, _NFilter, MeanPosition< DataPoint, _NFilter, Plane< DataPoint, _NFilter, T > > > >
	Helper alias for Plane fitting on 3D points using CovariancePlaneFitImpl [CovariancePlaneFit Definition].

template<class DataPoint , class _NFilter , int DiffType, typename T >
using	CovariancePlaneDer = CovariancePlaneDerImpl< DataPoint, _NFilter, DiffType, CovarianceDer< DataPoint, _NFilter, DiffType, MeanPositionDer< DataPoint, _NFilter, DiffType, T > > >
	Helper alias for Plane fitting on 3D points using CovariancePlaneFitImpl.

template<class DataPoint , class _NFilter , typename T >
using	MeanPlaneFit = MeanPlaneFitImpl< DataPoint, _NFilter, MeanNormal< DataPoint, _NFilter, MeanPosition< DataPoint, _NFilter, Plane< DataPoint, _NFilter, T > > > >
	Helper alias for Plane fitting on points using MeanPlaneFitImpl [MeanPlaneFit Definition].

template<class DataPoint , class _NFilter , typename T >
using	MongePatchQuadraticFit = WeingartenCurvatureEstimator< DataPoint, _NFilter, FundamentalFormWeingartenEstimator< DataPoint, _NFilter, MongePatchQuadraticFitImpl< DataPoint, _NFilter, MongePatch< DataPoint, _NFilter, QuadraticHeightField< DataPoint, _NFilter, HeightField< DataPoint, _NFilter, CovariancePlaneFit< DataPoint, _NFilter, T > > > > > > >

template<class DataPoint , class _NFilter , typename T >
using	MongePatchRestrictedQuadraticFit = WeingartenCurvatureEstimator< DataPoint, _NFilter, FundamentalFormWeingartenEstimator< DataPoint, _NFilter, MongePatchRestrictedQuadraticFitImpl< DataPoint, _NFilter, MongePatch< DataPoint, _NFilter, RestrictedQuadraticHeightField< DataPoint, _NFilter, HeightField< DataPoint, _NFilter, CovariancePlaneFit< DataPoint, _NFilter, T > > > > > > >

template<class DataPoint , class _NFilter , typename T >
using	OrientedSphereFit = OrientedSphereFitImpl< DataPoint, _NFilter, MeanPosition< DataPoint, _NFilter, MeanNormal< DataPoint, _NFilter, AlgebraicSphere< DataPoint, _NFilter, T > > > >
	Helper alias for Oriented Sphere fitting on 3D points using OrientedSphereFitImpl [OrientedSphereFit Definition].

template<class DataPoint , class _NFilter , int DiffType, typename T >
using	OrientedSphereDer = OrientedSphereDerImpl< DataPoint, _NFilter, DiffType, MeanPositionDer< DataPoint, _NFilter, DiffType, T > >
	Helper alias for Oriented Sphere fitting on 3D points using OrientedSphereDerImpl.

template<class DataPoint , class _NFilter , typename T >
using	SphereFit = SphereFitImpl< DataPoint, _NFilter, AlgebraicSphere< DataPoint, _NFilter, T > >
	Helper alias for Sphere fitting on 3D points using SphereFitImpl.

template<class DataPoint , class _NFilter , typename T >
using	UnorientedSphereFit = UnorientedSphereFitImpl< DataPoint, _NFilter, MeanPosition< DataPoint, _NFilter, AlgebraicSphere< DataPoint, _NFilter, T > > >
	Helper alias for Oriented Sphere fitting on 3D points using UnorientedSphereFitImpl.

template<class DataPoint , class _NFilter , int DiffType, typename T >
using	UnorientedSphereDer = UnorientedSphereDerImpl< DataPoint, _NFilter, DiffType, MeanPositionDer< DataPoint, _NFilter, DiffType, T > >

template<typename Traits >
using	KdTreeKNearestIndexQuery = KdTreeKNearestQueryBase< Traits, KdTreeKNearestIterator, KNearestIndexQuery< typename Traits::IndexType, typename Traits::DataPoint::Scalar, Traits::MAX_KNN_SIZE > >
	Extension of the Query class that allows to read the result of a k-nearest neighbors search on the KdTree.

template<typename Traits >
using	KdTreeKNearestPointQuery = KdTreeKNearestQueryBase< Traits, KdTreeKNearestIterator, KNearestPointQuery< typename Traits::IndexType, typename Traits::DataPoint, Traits::MAX_KNN_SIZE > >
	Extension of the Query class that allows to read the result of a k-nearest neighbors search on the KdTree.

template<typename Traits >
using	KdTreeNearestIndexQuery = KdTreeNearestQueryBase< Traits, KdTreeNearestIterator, NearestIndexQuery< typename Traits::IndexType, typename Traits::DataPoint::Scalar > >
	Extension of the Query class that allows to read the result of a nearest neighbor search on the KdTree.

template<typename Traits >
using	KdTreeNearestPointQuery = KdTreeNearestQueryBase< Traits, KdTreeNearestIterator, NearestPointQuery< typename Traits::IndexType, typename Traits::DataPoint > >
	Extension of the Query class that allows to read the result of a nearest neighbor search on the KdTree.

template<typename Traits >
using	KdTreeRangeIndexQuery = KdTreeRangeQueryBase< Traits, KdTreeRangeIterator, RangeIndexQuery< typename Traits::IndexType, typename Traits::DataPoint::Scalar > >
	Extension of the Query class that allows to read the result of a range neighbors search on the KdTree.

template<typename Traits >
using	KdTreeRangePointQuery = KdTreeRangeQueryBase< Traits, KdTreeRangeIterator, RangePointQuery< typename Traits::IndexType, typename Traits::DataPoint > >
	Extension of the Query class that allows to read the result of a range neighbors search on the KdTree.

template<typename DataPoint >
using	KnnGraph = KnnGraphBase< NeighborGraphDefaultTraits< DataPoint > >
	Public interface for the KnnGraph datastructure.

template<typename DataPoint >
using	NeighborGraph = NeighborGraphBase< NeighborGraphDefaultTraits< DataPoint > >
	Public interface for the NeighborGraph datastructure.

template<typename Index , typename DataPoint , int MAX_KNN_SIZE>
using	KNearestPointQuery = Query< QueryInputIsPosition< DataPoint >, QueryOutputIsKNearest< Index, typename DataPoint::Scalar, MAX_KNN_SIZE > >
	Base Query alias combining QueryInputIsIndex and QueryOutputIs##OUT_TYPE##.

template<typename Index , typename DataPoint >
using	NearestPointQuery = Query< QueryInputIsPosition< DataPoint >, QueryOutputIsNearest< Index, typename DataPoint::Scalar > >

template<typename Index , typename DataPoint >
using	RangePointQuery = Query< QueryInputIsPosition< DataPoint >, QueryOutputIsRange< Index, typename DataPoint::Scalar > >

template<typename Index , typename Scalar , int MAX_KNN_SIZE>
using	KNearestIndexQuery = Query< QueryInputIsIndex< Index >, QueryOutputIsKNearest< Index, Scalar, MAX_KNN_SIZE > >

template<typename Index , typename Scalar >
using	NearestIndexQuery = Query< QueryInputIsIndex< Index >, QueryOutputIsNearest< Index, Scalar > >

template<typename Index , typename Scalar >
using	RangeIndexQuery = Query< QueryInputIsIndex< Index >, QueryOutputIsRange< Index, Scalar > >

Enumerations
enum	TriangleGenerationMethod { UniformGeneration , HexagramGeneration , IndependentGeneration , AvgHexagramGeneration }
	\breif Generation method of the triangles for the Corrected Normal Current formula More...

enum	FIT_RESULT : unsigned char { STABLE = 0 , UNSTABLE = 1 , UNDEFINED = 2 , NEED_OTHER_PASS = 3 , CONFLICT_ERROR_FOUND = 4 , NBMAX }
	Enum corresponding to the state of a fitting method (and what the finalize function returns) More...

enum	DiffType : unsigned int { FitScaleDer = 0x01 , FitSpaceDer = 0x02 , FitScaleSpaceDer = FitScaleDer \| FitSpaceDer }
	Flags defining which derivatives need to be computed. More...

Functions
template<typename DataPoint >
DataPoint	getPointOnSphere (const typename DataPoint::Scalar _radius, const typename DataPoint::VectorType _vCenter, const bool _bAddPositionNoise=true, const bool _bAddNormalNoise=true, const bool _bReverseNormals=false)
	Generate points on a sphere.

template<typename VectorType >
VectorType	getPointOnCircle (typename VectorType::Scalar _radius, VectorType _vCenter)
	Sample points on a circle in the xy plane.

template<typename DataPoint >
DataPoint	getPointOnRectangularPlane (const typename DataPoint::VectorType &_vPosition, const typename DataPoint::VectorType &, const typename DataPoint::Scalar &_width, const typename DataPoint::Scalar &_height, const typename DataPoint::VectorType &_localxAxis, const typename DataPoint::VectorType &_localyAxis, const bool _bAddPositionNoise=true)
	Generate points on a plane without normals.

template<typename DataPoint >
DataPoint	getPointOnPlane (const typename DataPoint::VectorType _vPosition, const typename DataPoint::VectorType _vNormal, const typename DataPoint::Scalar _radius, const bool _bAddPositionNoise=true, const bool _bAddNormalNoise=true, const bool _bReverseNormals=false)
	Generate points on a plane.

template<typename DataPoint >
DataPoint	getPointOnParaboloid (const typename DataPoint::Scalar _a, const typename DataPoint::Scalar _b, const typename DataPoint::Scalar _s, const bool _bAddNoise=true)
	Generate point samples on the primitive z = ax^2 + by^2.

template<typename DataPoint >
DataPoint	getPointOnParaboloid (typename DataPoint::Scalar _a, typename DataPoint::Scalar _b, typename DataPoint::Scalar _c, typename DataPoint::Scalar _d, typename DataPoint::Scalar _e, typename DataPoint::Scalar _f, typename DataPoint::Scalar _s, bool _bAddNoise=true)
	Generate point samples on the primitive z = ax^2 + by^2 Points (x,y) are generated in the interval [-_s, -s]^2 See getParaboloidZ and getParaboloidNormal.

template<typename DataPoint , typename Params >
DataPoint	getPointOnParaboloid (const Params &_params, typename DataPoint::Scalar _s, bool _bAddNoise=true)

template<typename DataPoint >
DataPoint	getRandomPoint ()
	Generate a random points.

template<class DataPoint , class _NFilter , typename T >
Ponca::MeanPosition T	barycenter () const
	where $\left[\mathbf{p_i} \in \text{neighborhood}(\mathbf{x})\right]$ are all the point samples in $\mathbf{x}$'s neighborhood

Scalar	barycenterDistance () const
	The distance between the barycenter and the basis center.

Variables
Ponca::MeanPosition	f$

Detailed Description

This Source Code Form is subject to the terms of the Mozilla Public License, v.

Copyright (c) 2022 Jacques-Olivier Lachaud (jacqu.nosp@m.es-o.nosp@m.livie.nosp@m.r.la.nosp@m.chaud.nosp@m.@uni.nosp@m.v-sav.nosp@m.oie..nosp@m.fr) Laboratory of Mathematics (CNRS, UMR 5807), University of Savoie, France,.

2.0. If a copy of the MPL was not distributed with this file, You can obtain one at http://mozilla.org/MPL/2.0/.

Author: Thibault Lejemble

2.0. If a copy of the MPL was not distributed with this file, You can obtain one at http://mozilla.org/MPL/2.0/.

Author: Thibault Lejemble - Main source code; Nicolas Mellado - Improved error handling and bound check

Typedef Documentation

◆ CovarianceLineFit

template<class DataPoint , class _NFilter , typename T >

using Ponca::CovarianceLineFit = typedef CovarianceLineFitImpl< DataPoint, _NFilter, CovarianceBase<DataPoint, _NFilter, MeanPosition<DataPoint, _NFilter, Line<DataPoint, _NFilter, T> >> >

Helper alias for Line fitting on 3D points using CovarianceLineFitImpl.

Definition at line 64 of file covarianceLineFit.h.

◆ CovariancePlaneDer

template<class DataPoint , class _NFilter , int DiffType, typename T >

using Ponca::CovariancePlaneDer = typedef CovariancePlaneDerImpl< DataPoint, _NFilter, DiffType, CovarianceDer<DataPoint, _NFilter, DiffType, MeanPositionDer<DataPoint, _NFilter, DiffType, T> >>

Helper alias for Plane fitting on 3D points using CovariancePlaneFitImpl.

Definition at line 124 of file covariancePlaneFit.h.

◆ CovariancePlaneFit

template<class DataPoint , class _NFilter , typename T >

using Ponca::CovariancePlaneFit = typedef CovariancePlaneFitImpl< DataPoint, _NFilter, CovarianceBase<DataPoint, _NFilter, MeanPosition<DataPoint, _NFilter, Plane<DataPoint, _NFilter, T> >> >

Helper alias for Plane fitting on 3D points using CovariancePlaneFitImpl [CovariancePlaneFit Definition].

Definition at line 80 of file covariancePlaneFit.h.

◆ KdTreeKNearestIndexQuery

template<typename Traits >

using Ponca::KdTreeKNearestIndexQuery = typedef KdTreeKNearestQueryBase< Traits, KdTreeKNearestIterator, KNearestIndexQuery<typename Traits::IndexType, typename Traits::DataPoint::Scalar, Traits::MAX_KNN_SIZE> >

Extension of the Query class that allows to read the result of a k-nearest neighbors search on the KdTree.

Output result of a KdTreeBase::kNearestNeighbors query made with the index of the point to evaluate.

See also: KNearestIndexQuery

Definition at line 84 of file kdTreeKNearestQueries.h.

◆ KdTreeKNearestPointQuery

template<typename Traits >

using Ponca::KdTreeKNearestPointQuery = typedef KdTreeKNearestQueryBase< Traits, KdTreeKNearestIterator, KNearestPointQuery<typename Traits::IndexType, typename Traits::DataPoint, Traits::MAX_KNN_SIZE> >

Extension of the Query class that allows to read the result of a k-nearest neighbors search on the KdTree.

Output result of a KdTreeBase::kNearestNeighbors query made with the position of the point to evaluate.

See also: KNearestPointQuery

Definition at line 94 of file kdTreeKNearestQueries.h.

◆ KdTreeNearestIndexQuery

template<typename Traits >

using Ponca::KdTreeNearestIndexQuery = typedef KdTreeNearestQueryBase<Traits, KdTreeNearestIterator, NearestIndexQuery<typename Traits::IndexType, typename Traits::DataPoint::Scalar> >

Extension of the Query class that allows to read the result of a nearest neighbor search on the KdTree.

Output result of a KdTreeBase::nearestNeighbor query made with the index of the point to evaluate.

See also: NearestIndexQuery

Definition at line 73 of file kdTreeNearestQueries.h.

◆ KdTreeNearestPointQuery

template<typename Traits >

using Ponca::KdTreeNearestPointQuery = typedef KdTreeNearestQueryBase<Traits, KdTreeNearestIterator, NearestPointQuery<typename Traits::IndexType, typename Traits::DataPoint> >

Extension of the Query class that allows to read the result of a nearest neighbor search on the KdTree.

Output result of a KdTreeBase::nearestNeighbor query made with the position of the point to evaluate.

See also: NearestPointQuery

Definition at line 84 of file kdTreeNearestQueries.h.

◆ KdTreeRangeIndexQuery

template<typename Traits >

using Ponca::KdTreeRangeIndexQuery = typedef KdTreeRangeQueryBase<Traits, KdTreeRangeIterator, RangeIndexQuery<typename Traits::IndexType, typename Traits::DataPoint::Scalar> >

Extension of the Query class that allows to read the result of a range neighbors search on the KdTree.

Output result of a KdTreeBase::rangeNeighbors query made with the index of the point to evaluate.

See also: RangeIndexQuery

Definition at line 124 of file kdTreeRangeQueries.h.

◆ KdTreeRangePointQuery

template<typename Traits >

using Ponca::KdTreeRangePointQuery = typedef KdTreeRangeQueryBase<Traits, KdTreeRangeIterator, RangePointQuery<typename Traits::IndexType, typename Traits::DataPoint> >

Extension of the Query class that allows to read the result of a range neighbors search on the KdTree.

Output result of a KdTreeBase::rangeNeighbors query made with the position of the point to evaluate.

See also: RangePointQuery

Definition at line 134 of file kdTreeRangeQueries.h.

◆ KnnGraph

template<typename DataPoint >

using Ponca::KnnGraph = typedef KnnGraphBase<NeighborGraphDefaultTraits<DataPoint> >

Public interface for the KnnGraph datastructure.

Provides default implementation of the KnnGraph

See also: NeighborGraphDefaultTraits for the default trait interface documentation.; KnnGraphBase, AbstractNeighborGraph for complete API

Definition at line 180 of file knnGraph.h.

◆ MeanPlaneFit

template<class DataPoint , class _NFilter , typename T >

using Ponca::MeanPlaneFit = typedef MeanPlaneFitImpl< DataPoint, _NFilter, MeanNormal<DataPoint, _NFilter, MeanPosition<DataPoint, _NFilter, Plane<DataPoint, _NFilter, T> >> >

Helper alias for Plane fitting on points using MeanPlaneFitImpl [MeanPlaneFit Definition].

Definition at line 58 of file meanPlaneFit.h.

◆ MongePatchQuadraticFit

template<class DataPoint , class _NFilter , typename T >

using Ponca::MongePatchQuadraticFit = typedef WeingartenCurvatureEstimator< DataPoint, _NFilter, FundamentalFormWeingartenEstimator< DataPoint, _NFilter, MongePatchQuadraticFitImpl< DataPoint, _NFilter, MongePatch<DataPoint, _NFilter, QuadraticHeightField< DataPoint, _NFilter, HeightField<DataPoint, _NFilter, CovariancePlaneFit<DataPoint, _NFilter, T> >> >> >>

Definition at line 179 of file mongePatch.h.

◆ MongePatchRestrictedQuadraticFit

template<class DataPoint , class _NFilter , typename T >

using Ponca::MongePatchRestrictedQuadraticFit = typedef WeingartenCurvatureEstimator< DataPoint, _NFilter, FundamentalFormWeingartenEstimator< DataPoint, _NFilter, MongePatchRestrictedQuadraticFitImpl< DataPoint, _NFilter, MongePatch<DataPoint, _NFilter, RestrictedQuadraticHeightField< DataPoint, _NFilter, HeightField<DataPoint, _NFilter, CovariancePlaneFit<DataPoint, _NFilter, T> >> >> >>

Definition at line 191 of file mongePatch.h.

◆ NeighborGraph

template<typename DataPoint >

using Ponca::NeighborGraph = typedef NeighborGraphBase<NeighborGraphDefaultTraits<DataPoint> >

Public interface for the NeighborGraph datastructure.

Provides default implementation of the NeighborGraph

See also: NeighborGraphDefaultTraits for the default trait interface documentation.; NeighborGraphBase, AbstractNeighborGraph for complete API

Definition at line 155 of file neighborGraph.h.

◆ OrientedSphereDer

template<class DataPoint , class _NFilter , int DiffType, typename T >

using Ponca::OrientedSphereDer = typedef OrientedSphereDerImpl<DataPoint, _NFilter, DiffType, MeanPositionDer<DataPoint, _NFilter, DiffType, T> >

Helper alias for Oriented Sphere fitting on 3D points using OrientedSphereDerImpl.

Definition at line 134 of file orientedSphereFit.h.

◆ OrientedSphereFit

template<class DataPoint , class _NFilter , typename T >

using Ponca::OrientedSphereFit = typedef OrientedSphereFitImpl< DataPoint, _NFilter, MeanPosition<DataPoint, _NFilter, MeanNormal<DataPoint, _NFilter, AlgebraicSphere<DataPoint, _NFilter, T> >> >

Helper alias for Oriented Sphere fitting on 3D points using OrientedSphereFitImpl [OrientedSphereFit Definition].

Definition at line 52 of file orientedSphereFit.h.

◆ SphereFit

template<class DataPoint , class _NFilter , typename T >

using Ponca::SphereFit = typedef SphereFitImpl<DataPoint, _NFilter, AlgebraicSphere<DataPoint, _NFilter, T> >

Helper alias for Sphere fitting on 3D points using SphereFitImpl.

Definition at line 89 of file sphereFit.h.

◆ UnorientedSphereDer

template<class DataPoint , class _NFilter , int DiffType, typename T >

using Ponca::UnorientedSphereDer = typedef UnorientedSphereDerImpl<DataPoint, _NFilter, DiffType, MeanPositionDer<DataPoint, _NFilter, DiffType, T> >

Definition at line 154 of file unorientedSphereFit.h.

◆ UnorientedSphereFit

template<class DataPoint , class _NFilter , typename T >

using Ponca::UnorientedSphereFit = typedef UnorientedSphereFitImpl<DataPoint, _NFilter, MeanPosition<DataPoint, _NFilter, AlgebraicSphere<DataPoint, _NFilter, T> >>

Helper alias for Oriented Sphere fitting on 3D points using UnorientedSphereFitImpl.

Definition at line 81 of file unorientedSphereFit.h.

Enumeration Type Documentation

◆ DiffType

enum Ponca::DiffType : unsigned int

Flags defining which derivatives need to be computed.

Warning: Flags have to be combined using |

Enumerator
FitScaleDer	Flag indicating a scale differentiation.
FitSpaceDer	Flag indicating a space differentiation.
FitScaleSpaceDer	Flag indicating a scale-space differentiation.

Definition at line 33 of file enums.h.

◆ FIT_RESULT

enum Ponca::FIT_RESULT : unsigned char

Enum corresponding to the state of a fitting method (and what the finalize function returns)

Enumerator
STABLE	The fitting is stable and ready to use.
UNSTABLE	The fitting is ready to use but it is considered as unstable (if the number of neighbors is low for example)
UNDEFINED	The fitting is undefined, you can't use it for valid results.
NEED_OTHER_PASS	The fitting procedure needs to analyse the neighborhood another time.
CONFLICT_ERROR_FOUND	Multiple classes of the fitting procedure initialize the primitive. Should be treated as error.
NBMAX	Nb enums.

Definition at line 14 of file enums.h.

◆ TriangleGenerationMethod

enum Ponca::TriangleGenerationMethod

\breif Generation method of the triangles for the Corrected Normal Current formula

Definition at line 89 of file cnc.h.

Function Documentation

◆ barycenter()

template<class DataPoint , class _NFilter , typename T >

Ponca::MeanPosition T Ponca::barycenter ( ) const

where $\left[\mathbf{p_i} \in \text{neighborhood}(\mathbf{x})\right]$ are all the point samples in $\mathbf{x}$'s neighborhood

Definition at line 204 of file mean.h.

◆ barycenterDistance()

Scalar Ponca::barycenterDistance ( ) const

inline

The distance between the barycenter and the basis center.

Returns: 0 for invalid fits

Definition at line 53 of file mean.h.

◆ getPointOnCircle()

template<typename VectorType >

VectorType Ponca::getPointOnCircle	(	typename VectorType::Scalar	_radius,
		VectorType	_vCenter
	)

Sample points on a circle in the xy plane.

Definition at line 61 of file pointGeneration.h.

◆ getPointOnParaboloid() [1/3]

template<typename DataPoint , typename Params >

DataPoint Ponca::getPointOnParaboloid	(	const Params &	_params,
		typename DataPoint::Scalar	_s,
		bool	_bAddNoise = `true`
	)

Definition at line 262 of file pointGeneration.h.

◆ getPointOnParaboloid() [2/3]

template<typename DataPoint >

DataPoint Ponca::getPointOnParaboloid	(	const typename DataPoint::Scalar	_a,
		const typename DataPoint::Scalar	_b,
		const typename DataPoint::Scalar	_s,
		const bool	_bAddNoise = `true`
	)

Generate point samples on the primitive z = ax^2 + by^2.

Points (x,y) are generated in the interval [-_s, -s]^2

Definition at line 209 of file pointGeneration.h.

◆ getPointOnParaboloid() [3/3]

template<typename DataPoint >

DataPoint Ponca::getPointOnParaboloid	(	typename DataPoint::Scalar	_a,
		typename DataPoint::Scalar	_b,
		typename DataPoint::Scalar	_c,
		typename DataPoint::Scalar	_d,
		typename DataPoint::Scalar	_e,
		typename DataPoint::Scalar	_f,
		typename DataPoint::Scalar	_s,
		bool	_bAddNoise = `true`
	)

Generate point samples on the primitive z = ax^2 + by^2 Points (x,y) are generated in the interval [-_s, -s]^2 See getParaboloidZ and getParaboloidNormal.

Definition at line 235 of file pointGeneration.h.

◆ getPointOnPlane()

template<typename DataPoint >

DataPoint Ponca::getPointOnPlane	(	const typename DataPoint::VectorType	_vPosition,
		const typename DataPoint::VectorType	_vNormal,
		const typename DataPoint::Scalar	_radius,
		const bool	_bAddPositionNoise = `true`,
		const bool	_bAddNormalNoise = `true`,
		const bool	_bReverseNormals = `false`
	)

Generate points on a plane.

Definition at line 107 of file pointGeneration.h.

◆ getPointOnRectangularPlane()

template<typename DataPoint >

DataPoint Ponca::getPointOnRectangularPlane	(	const typename DataPoint::VectorType &	_vPosition,
		const typename DataPoint::VectorType &	,
		const typename DataPoint::Scalar &	_width,
		const typename DataPoint::Scalar &	_height,
		const typename DataPoint::VectorType &	_localxAxis,
		const typename DataPoint::VectorType &	_localyAxis,
		const bool	_bAddPositionNoise = `true`
	)

Generate points on a plane without normals.

Definition at line 80 of file pointGeneration.h.

◆ getPointOnSphere()

template<typename DataPoint >

DataPoint Ponca::getPointOnSphere	(	const typename DataPoint::Scalar	_radius,
		const typename DataPoint::VectorType	_vCenter,
		const bool	_bAddPositionNoise = `true`,
		const bool	_bAddNormalNoise = `true`,
		const bool	_bReverseNormals = `false`
	)

Generate points on a sphere.

Definition at line 25 of file pointGeneration.h.

◆ getRandomPoint()

template<typename DataPoint >

DataPoint Ponca::getRandomPoint ( )

Generate a random points.

Definition at line 271 of file pointGeneration.h.

Namespaces

Classes

Typedefs

Enumerations

Functions

Variables

Detailed Description

Typedef Documentation

◆ CovarianceLineFit

◆ CovariancePlaneDer

◆ CovariancePlaneFit

◆ KdTreeKNearestIndexQuery

◆ KdTreeKNearestPointQuery

◆ KdTreeNearestIndexQuery

◆ KdTreeNearestPointQuery

◆ KdTreeRangeIndexQuery

◆ KdTreeRangePointQuery

◆ KnnGraph

◆ MeanPlaneFit

◆ MongePatchQuadraticFit

◆ MongePatchRestrictedQuadraticFit

◆ NeighborGraph

◆ OrientedSphereDer

◆ OrientedSphereFit

◆ SphereFit

◆ UnorientedSphereDer

◆ UnorientedSphereFit

Enumeration Type Documentation

◆ DiffType

◆ FIT_RESULT

◆ TriangleGenerationMethod

Function Documentation

◆ barycenter()

◆ barycenterDistance()

◆ getPointOnCircle()

◆ getPointOnParaboloid() [1/3]

◆ getPointOnParaboloid() [2/3]

◆ getPointOnParaboloid() [3/3]

◆ getPointOnPlane()

◆ getPointOnRectangularPlane()

◆ getPointOnSphere()

◆ getRandomPoint()