| ►C_Base | |
| CPonca::BasketComputeObject< _Derived, _Base > | Base ComputeObject for the Basket classes |
| ►C_NeighborhoodFrame | |
| CPonca::NoWeightFuncBase< DataPoint, _NeighborhoodFrame > | Base Weighting function that set uniform weight to all samples |
| ►CPonca::CenteredNeighborhoodFrame< DataPoint > | NeighborhoodFrame that express 3d points relatively to a prescribed center |
| CPonca::DistWeightFunc< DataPoint, WeightKernel > | Weight neighbors according to the euclidean distance between a query and a reference position |
| ►CPonca::ComputeObject< Derived > | ComputeObject is a virtual object that represents an algorithm which can be used with the compute functions |
| ►CPonca::BasketComputeObject< Basket< P, NF, Ext0, Exts... >, internal::BasketAggregate< P, NF, Ext0, Exts... >::type > | |
| CPonca::Basket< P, NF, Ext0, Exts > | Aggregator class used to declare specialized structures using CRTP |
| ►CPonca::BasketComputeObject< BasketDiff< BasketType, Type, Ext0, Exts... >, internal::BasketDiffAggregate< BasketType, Type, Ext0, Exts... >::type > | |
| CPonca::BasketDiff< BasketType, Type, Ext0, Exts > | Aggregator class used to declare specialized structures with derivatives computations, using CRTP |
| ►CPonca::ComputeObject< _Derived > | |
| CPonca::BasketComputeObject< _Derived, _Base > | Base ComputeObject for the Basket classes |
| CPonca::ComputeObject< Basket< P, NF, Ext0, Exts... > > | |
| CPonca::ComputeObject< BasketDiff< BasketType, Type, Ext0, Exts... > > | |
| CPonca::KdTreeBase< Traits >::DefaultConverter | Convert a custom point container to the KdTree PointContainer using DataPoint default constructor |
| CPonca::QueryOutputBase::DummyOutputParameter | |
| ►CConcept::FittingExtensionConcept | |
| CPonca::CovarianceFitDer< DataPoint, _NFilter, DiffType, T > | Internal generic class computing the derivatives of covariance matrix computed by CovarianceFitBase |
| CPonca::CovariancePlaneDerImpl< DataPoint, _NFilter, DiffType, T > | [CovariancePlaneFit Definition] |
| CPonca::GLSDer< DataPoint, _NFilter, DiffType, T > | Differentiation of GLSParam |
| CPonca::GLSParam< DataPoint, _NFilter, T > | Growing Least Squares reparametrization of the OrientedSphereFit |
| CPonca::MlsSphereFitDer< DataPoint, _NFilter, DiffType, T > | Extension performing derivation of the mls surface |
| CPonca::NormalDerivativesCurvatureEstimator< DataPoint, _NFilter, DiffType, T > | Extension to compute curvature values from the Weingarten map \( \frac{d N}{d \mathbf{x}} \) |
| CPonca::PrimitiveDer< DataPoint, _NFilter, Type, T > | Generic class performing the Fit derivation |
| ►CConcept::FittingProcedureConcept | |
| CPonca::CovarianceFitBase< DataPoint, _NFilter, T > | Procedure that compute and decompose the covariance matrix of the neighbors positions in \(3d\) |
| CPonca::CovarianceLineFitImpl< DataPoint, _NFilter, T > | Line fitting procedure that minimize the orthogonal distance between the samples and the fitted primitive |
| CPonca::CovariancePlaneFitImpl< DataPoint, _NFilter, T > | Plane fitting procedure using only points position |
| CPonca::MeanNormal< DataPoint, _NFilter, T > | Compute the mean normal of the input points |
| CPonca::MeanNormalDer< DataPoint, _NFilter, DiffType, T > | Compute the derivatives of the input points mean normal |
| CPonca::MeanPlaneFitImpl< DataPoint, _NFilter, T > | Plane fitting procedure computing the mean position and orientation from oriented points |
| CPonca::MeanPosition< DataPoint, _NFilter, T > | Compute the barycenter of the input points |
| CPonca::MeanPositionDer< DataPoint, _NFilter, DiffType, T > | Compute the derivatives of the input points barycenter |
| CPonca::OrientedSphereFitImpl< DataPoint, _NFilter, T > | Algebraic Sphere fitting procedure on oriented point sets |
| CPonca::SphereFitImpl< DataPoint, _NFilter, T > | Algebraic Sphere fitting procedure on point set without normals |
| CPonca::UnorientedSphereFitImpl< DataPoint, _NFilter, T > | Algebraic Sphere fitting procedure on point sets with non-oriented normals |
| CPonca::GlobalNeighborhoodFrame< DataPoint > | NeighborhoodFrame that keep points in the global frame without applying any transformation |
| ►CEigen::Hyperplane | |
| CPonca::Plane< DataPoint, _NFilter, T > | Implicit hyperplane defined by an homogeneous vector \(\mathbf{p}\) |
| CPonca::IndexSquaredDistance< Index, Scalar > | Associates an index with a distance |
| CPonca::IndexSquaredDistance< Index, DataPoint::Scalar > | |
| CPonca::IndexSquaredDistance< IndexType, Scalar > | |
| CPonca::IndexSquaredDistance< Traits::IndexType, Traits::DataPoint::Scalar > | |
| ►CInput_ | |
| ►CPonca::Query< Input_, Output_ > | |
| ►CPonca::KNearestIndexQuery< Traits::IndexType, Traits::DataPoint::Scalar > | |
| CPonca::KnnGraphKNearestQuery< Traits > | |
| ►CPonca::RangeIndexQuery< Traits::IndexType, Traits::DataPoint::Scalar > | |
| CPonca::KnnGraphRangeQuery< Traits > | |
| ►CPonca::KdTreeBase< Traits > | [KdTreeSparse type definition] |
| ►CPonca::KdTreeDenseBase< KdTreeDefaultTraits< DataPoint > > | |
| CPonca::KdTreeDense< DataPoint > | [KdTree type definition] |
| ►CPonca::KdTreeSparseBase< KdTreeDefaultTraits< DataPoint > > | |
| CPonca::KdTreeSparse< DataPoint > | [KdTreeDense type definition] |
| CPonca::KdTreeDenseBase< Traits > | Customizable base class for dense KdTree datastructure |
| CPonca::KdTreeSparseBase< Traits > | Customizable base class for KdTreeSparse datastructure |
| ►CPonca::KdTreeBase< KdTreeDefaultTraits< DataPoint > > | |
| CPonca::KdTree< DataPoint > | Abstract KdTree type with KdTreeDefaultTraits |
| ►CPonca::KdTreeCustomizableNode< Index, NodeIndex, DataPoint, LeafSize, _InnerNodeType, _LeafNodeType > | The node type used by default by the kd-tree |
| CPonca::KdTreeDefaultNode< Index, NodeIndex, DataPoint, LeafSize > | |
| CPonca::KdTreeCustomizableNode< Index, NodeIndex, DataPoint, Index, KdTreeDefaultInnerNode< NodeIndex, DataPoint::Scalar, DataPoint::Dim >, KdTreeDefaultLeafNode< Index, Index > > | |
| CPonca::KdTreeDefaultInnerNode< NodeIndex, Scalar, DIM > | |
| CPonca::KdTreeDefaultLeafNode< Index, Size > | |
| CPonca::KdTreeDefaultTraits< _DataPoint, _NodeType > | The default traits type used by the kd-tree |
| CPonca::KdTreeKNearestIterator< Index, DataPoint > | |
| CPonca::KdTreeNearestIterator< Index > | |
| ►CPonca::KdTreeQuery< Traits > | |
| CPonca::KdTreeKNearestQueryBase< Traits, IteratorType, QueryType > | |
| CPonca::KdTreeNearestQueryBase< Traits, IteratorType, QueryType > | |
| CPonca::KdTreeRangeQueryBase< Traits, IteratorType, QueryType > | |
| CPonca::KdTreeRangeIterator< Index, DataPoint, QueryT_ > | |
| CPonca::KnnGraphBase< Traits > | Customizable base class for KnnGraph datastructure |
| CPonca::KnnGraphDefaultTraits< _DataPoint > | The default traits type used by the kd-tree |
| CPonca::KnnGraphRangeIterator< Traits > | |
| CPonca::limited_priority_queue< T, CompareT > | The limited_priority_queue class is similar to std::priority_queue but has a limited capacity and handles the comparison differently |
| CPonca::limited_priority_queue< IndexSquaredDistance< Index, Scalar > > | |
| CPonca::limited_priority_queue< Ponca::IndexSquaredDistance< Index, DataPoint::Scalar > > | |
| CPonca::limited_priority_queue< Ponca::IndexSquaredDistance< Index, Scalar > > | |
| CPonca::limited_priority_queue< Ponca::IndexSquaredDistance< Traits::IndexType, Traits::DataPoint::Scalar > > | |
| ►COutput_ | |
| CPonca::Query< Input_, Output_ > | |
| ►CEigen::ParametrizedLine | |
| CPonca::Line< DataPoint, _NFilter, T > | 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 \(l(t)=\mathbf{o}+t\overrightarrow{\mathbf{d}}, t\in \mathbb{R}\) |
| CPonca::PrimitiveBase< DataPoint, _NFilter, T > | Primitive base class |
| ►CPonca::QueryInputBase | Base class for queries input type |
| CPonca::QueryInput< Traits::IndexType > | |
| ►CPonca::QueryInput< Index > | |
| ►CPonca::QueryInputIsIndex< Index > | Base class for queries storing points |
| ►CPonca::Query< QueryInputIsIndex< Index >, QueryOutputIsKNearest< Index, Scalar > > | |
| CPonca::KNearestIndexQuery< Index, Scalar > | Base Query class combining QueryInputIsIndex and QueryOutputIsKNearest |
| ►CPonca::Query< QueryInputIsIndex< Index >, QueryOutputIsNearest< Index, Scalar > > | |
| CPonca::NearestIndexQuery< Index, Scalar > | Base Query class combining QueryInputIsIndex and QueryOutputIsNearest |
| ►CPonca::Query< QueryInputIsIndex< Index >, QueryOutputIsRange< Index, Scalar > > | |
| CPonca::RangeIndexQuery< Index, Scalar > | Base Query class combining QueryInputIsIndex and QueryOutputIsRange |
| ►CPonca::QueryInput< DataPoint::VectorType > | |
| ►CPonca::QueryInputIsPosition< DataPoint > | Base class for queries storing points |
| ►CPonca::Query< QueryInputIsPosition< DataPoint >, QueryOutputIsKNearest< Index, DataPoint::Scalar > > | |
| CPonca::KNearestPointQuery< Index, DataPoint > | Base Query class combining QueryInputIsPosition and QueryOutputIsKNearest |
| ►CPonca::Query< QueryInputIsPosition< DataPoint >, QueryOutputIsNearest< Index, DataPoint::Scalar > > | |
| CPonca::NearestPointQuery< Index, DataPoint > | Base Query class combining QueryInputIsPosition and QueryOutputIsNearest |
| ►CPonca::Query< QueryInputIsPosition< DataPoint >, QueryOutputIsRange< Index, DataPoint::Scalar > > | |
| CPonca::RangePointQuery< Index, DataPoint > | Base Query class combining QueryInputIsPosition and QueryOutputIsRange |
| ►CPonca::QueryInput< InputType_ > | Base class for typed queries input type |
| ►CPonca::QueryInputIsIndex< Traits::IndexType > | |
| CPonca::Query< QueryInputIsIndex< Traits::IndexType >, QueryOutputIsKNearest< Traits::IndexType, Traits::DataPoint::Scalar > > | |
| CPonca::Query< QueryInputIsIndex< Traits::IndexType >, QueryOutputIsRange< Traits::IndexType, Traits::DataPoint::Scalar > > | |
| ►CPonca::QueryOutputBase | Base class for queries output type |
| ►CPonca::QueryOutputIsKNearest< Index, DataPoint::Scalar > | |
| CPonca::Query< QueryInputIsPosition< DataPoint >, QueryOutputIsKNearest< Index, DataPoint::Scalar > > | |
| ►CPonca::QueryOutputIsKNearest< Traits::IndexType, Traits::DataPoint::Scalar > | |
| CPonca::Query< QueryInputIsIndex< Traits::IndexType >, QueryOutputIsKNearest< Traits::IndexType, Traits::DataPoint::Scalar > > | |
| ►CPonca::QueryOutputIsNearest< Index, DataPoint::Scalar > | |
| CPonca::Query< QueryInputIsPosition< DataPoint >, QueryOutputIsNearest< Index, DataPoint::Scalar > > | |
| ►CPonca::QueryOutputIsRange< Traits::IndexType, Traits::DataPoint::Scalar > | |
| CPonca::Query< QueryInputIsIndex< Traits::IndexType >, QueryOutputIsRange< Traits::IndexType, Traits::DataPoint::Scalar > > | |
| ►CPonca::QueryOutputIsRange< Index, DataPoint::Scalar > | |
| CPonca::Query< QueryInputIsPosition< DataPoint >, QueryOutputIsRange< Index, DataPoint::Scalar > > | |
| ►CPonca::QueryOutputIsKNearest< Index, Scalar > | Base class for knearest queries |
| CPonca::Query< QueryInputIsIndex< Index >, QueryOutputIsKNearest< Index, Scalar > > | |
| ►CPonca::QueryOutputIsNearest< Index, Scalar > | Base class for nearest queries |
| CPonca::Query< QueryInputIsIndex< Index >, QueryOutputIsNearest< Index, Scalar > > | |
| ►CPonca::QueryOutputIsRange< Index, Scalar > | Base class for range queries |
| CPonca::Query< QueryInputIsIndex< Index >, QueryOutputIsRange< Index, Scalar > > | |
| ►CQueryType | |
| CPonca::KdTreeKNearestQueryBase< Traits, IteratorType, QueryType > | |
| CPonca::KdTreeNearestQueryBase< Traits, IteratorType, QueryType > | |
| CPonca::KdTreeRangeQueryBase< Traits, IteratorType, QueryType > | |
| CPonca::Stack< T, N > | Stack with fixed-size storage |
| CPonca::Stack< Ponca::IndexSquaredDistance< IndexType, Scalar >, 2 *Traits::MAX_DEPTH > | |
| ►CT | |
| CPonca::AlgebraicSphere< DataPoint, _NFilter, T > | Algebraic Sphere primitive |
| CPonca::CovarianceFitBase< DataPoint, _NFilter, T > | Procedure that compute and decompose the covariance matrix of the neighbors positions in \(3d\) |
| CPonca::CovarianceFitDer< DataPoint, _NFilter, DiffType, T > | Internal generic class computing the derivatives of covariance matrix computed by CovarianceFitBase |
| CPonca::CovarianceLineFitImpl< DataPoint, _NFilter, T > | Line fitting procedure that minimize the orthogonal distance between the samples and the fitted primitive |
| CPonca::CovariancePlaneDerImpl< DataPoint, _NFilter, DiffType, T > | [CovariancePlaneFit Definition] |
| CPonca::CovariancePlaneFitImpl< DataPoint, _NFilter, T > | Plane fitting procedure using only points position |
| CPonca::CurvatureEstimatorBase< DataPoint, _NFilter, DiffType, T > | Base class for any 3d curvature estimator: holds \(k_{\min}\), \(k_{\max}\) and associated vectors, such that \( k_{\min} <= k_{\max} \) |
| CPonca::DryFit< DataPoint, _NFilter, T > | Empty fitting object doing no computation |
| CPonca::GLSDer< DataPoint, _NFilter, DiffType, T > | Differentiation of GLSParam |
| CPonca::GLSParam< DataPoint, _NFilter, T > | Growing Least Squares reparametrization of the OrientedSphereFit |
| CPonca::Line< DataPoint, _NFilter, T > | 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 \(l(t)=\mathbf{o}+t\overrightarrow{\mathbf{d}}, t\in \mathbb{R}\) |
| CPonca::MeanNormal< DataPoint, _NFilter, T > | Compute the mean normal of the input points |
| CPonca::MeanNormalDer< DataPoint, _NFilter, DiffType, T > | Compute the derivatives of the input points mean normal |
| CPonca::MeanPlaneFitImpl< DataPoint, _NFilter, T > | Plane fitting procedure computing the mean position and orientation from oriented points |
| CPonca::MeanPosition< DataPoint, _NFilter, T > | Compute the barycenter of the input points |
| CPonca::MeanPositionDer< DataPoint, _NFilter, DiffType, T > | Compute the derivatives of the input points barycenter |
| CPonca::MlsSphereFitDer< DataPoint, _NFilter, DiffType, T > | Extension performing derivation of the mls surface |
| CPonca::MongePatch< DataPoint, _NFilter, T > | Extension to compute the best fit quadric on 3d points expressed as \(f(u,v)=h\) |
| CPonca::NormalCovarianceCurvatureEstimator< DataPoint, _NFilter, DiffType, T > | Extension to compute curvature values based on a covariance analysis of normal vectors of neighbors |
| CPonca::NormalDerivativesCurvatureEstimator< DataPoint, _NFilter, DiffType, T > | Extension to compute curvature values from the Weingarten map \( \frac{d N}{d \mathbf{x}} \) |
| CPonca::OrientedSphereDerImpl< DataPoint, _NFilter, DiffType, T > | [OrientedSphereFit Definition] |
| CPonca::OrientedSphereFitImpl< DataPoint, _NFilter, T > | Algebraic Sphere fitting procedure on oriented point sets |
| CPonca::Plane< DataPoint, _NFilter, T > | Implicit hyperplane defined by an homogeneous vector \(\mathbf{p}\) |
| CPonca::PrimitiveDer< DataPoint, _NFilter, Type, T > | Generic class performing the Fit derivation |
| CPonca::ProjectedNormalCovarianceCurvatureEstimator< DataPoint, _NFilter, DiffType, T > | Extension to compute curvature values based on a covariance analysis of normal vectors of neighbors projected onto the tangent plane |
| CPonca::SphereFitImpl< DataPoint, _NFilter, T > | Algebraic Sphere fitting procedure on point set without normals |
| CPonca::UnorientedSphereDerImpl< DataPoint, _NFilter, DiffType, T > | |
| CPonca::UnorientedSphereFitImpl< DataPoint, _NFilter, T > | Algebraic Sphere fitting procedure on point sets with non-oriented normals |
| ►Cinternal::BasketAggregate::type | |
| CPonca::BasketComputeObject< Basket< P, NF, Ext0, Exts... >, internal::BasketAggregate< P, NF, Ext0, Exts... >::type > | |
| ►Cinternal::BasketDiffAggregate::type | |
| CPonca::BasketComputeObject< BasketDiff< BasketType, Type, Ext0, Exts... >, internal::BasketDiffAggregate< BasketType, Type, Ext0, Exts... >::type > | |
| ►CConcept::WeightKernelConcept | |
| CPonca::CompactExpWeightKernel< _Scalar > | Compact Exponential WeightKernel defined in \(\left[0 : 1\right]\) |
| CPonca::ConstantWeightKernel< _Scalar > | Concept::WeightKernelConcept returning a constant value |
| CPonca::GaussianWeightKernel< _Scalar > | Non-compact Gaussian WeightKernel |
| CPonca::PolynomialSmoothWeightKernel< _Scalar, m, n > | Compact generalised version of SmoothWeightKernel with arbitrary degrees : \( w(x)=(x^n-1)^m \) |
| CPonca::SingularWeightKernel< _Scalar > | Compact singular WeightKernel defined in \(\left]0 : 1\right]\) |
| CPonca::SmoothWeightKernel< _Scalar > | Compact smooth WeightKernel of 2nd degree, defined in \(\left[0 : 1\right]\) Special case of PolynomialSmoothWeightKernel<Scalar, 2, 2> |
| CPonca::WendlandWeightKernel< _Scalar > | Compact Wendland WeightKernel defined in \(\left[0 : 1\right]\) |
1.9.8