| ►C_Base | |
| CPonca::BasketComputeObject< _Derived, _Base > | Base ComputeObject for the Basket classes |
| ►C_NeighborhoodFrame | |
| CPonca::internal::NoWeightFilterBase< _DataPoint, _NeighborhoodFrame > | Weighting function that set uniform weight to all samples |
| CPonca::AbstractNeighborGraph< _Traits, BufferType, _OneConnectedIndexQuery, _RangeIndexQuery > | Base class for neighbor graphs |
| ►CPonca::AbstractNeighborGraph< _Traits, KnnGraphBuffers, NeighborGraphOneConnectedQuery< StaticKnnGraphBase< _Traits > >, NeighborGraphRangeQuery< StaticKnnGraphBase< _Traits > > > | |
| ►CPonca::StaticKnnGraphBase< _Traits > | Customizable base class for KnnGraph datastructure |
| CPonca::KnnGraphBase< _Traits > | |
| ►CPonca::AbstractNeighborGraph< _Traits, NeighborGraphBuffer, NeighborGraphOneConnectedQuery< StaticNeighborGraphBase< _Traits > >, NeighborGraphRangeQuery< StaticNeighborGraphBase< _Traits > > > | |
| ►CPonca::StaticNeighborGraphBase< _Traits > | Static generic neighbor graph (does not include build functions) |
| CPonca::NeighborGraphBase< _Traits > | |
| CPonca::BasketUnitBase< DataPoint, _NFilter, T > | Base class of any computation unit of a Basket |
| CPonca::BitSet< N, T > | A simple BitSet implementation that mimics a set of indices |
| CPonca::StaticKdTreeBase< _Traits >::Buffers | Internal structure storing all the buffers used by the KdTree |
| ►CCenteredNeighborhoodFrame | |
| ►CPonca::internal::NoWeightFilterBase< DataPoint, CenteredNeighborhoodFrame > | |
| CPonca::NoWeightFilter< DataPoint > | Weighting function that set uniform weight to all samples, but transform neighbors coordinates to local frame |
| ►CPonca::CenteredNeighborhoodFrame< DataPoint > | NeighborhoodFrame that express 3d points relatively to a prescribed center |
| ►CPonca::DistWeightFilter< DataPoint, ConstantWeightKernel< Scalar > > | |
| CPonca::FilterWithAttributes< DataPoint, VectorType, DistWeightFilter< DataPoint, ConstantWeightKernel< Scalar > >, internal::ConvertDataPointToNormal< DataPoint > > | |
| ►CPonca::CenteredNeighborhoodFrame< _DataPoint > | |
| CPonca::DistWeightFilter< _DataPoint, WeightKernel > | Weight neighbors according to the Euclidean distance between a query and a reference position |
| CPonca::internal::CNCEigen< DataPoint > | This class contains some stand-alone CorrectedNormalCurrent formulas for triangles, using eigen as linear algebra backend |
| ►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::CNC< P, _method > | Corrected Normal Current Fit type |
| ►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::ComputeObject< CNC< P, UniformGeneration > > | |
| CPonca::KdTreeBase< _Traits >::DefaultConverter | Convert a custom point container to the KdTree PointContainer using DataPoint default constructor |
| CPonca::DirectProjectionOperator | Project a point using the primitive projection operator |
| CPonca::QueryOutputBase::DummyOutputParameter | |
| ►Cstd::false_type | |
| CPonca::hasFirstFundamentalForm< T, typename > | \FIXME create a macro to automatically generate the testing functions |
| ►CConcept::FittingExtensionConcept | |
| CPonca::CovarianceDer< DataPoint, _NFilter, DiffType, T > | Internal generic class computing the derivatives of covariance matrix computed by covarianceBase |
| 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 |
| ►CConcept::FittingProcedureConcept | |
| CMeanNormal< DataPoint, _NFilter, T > | Compute the mean normal of the input points |
| CMeanNormalDer< DataPoint, _NFilter, DiffType, T > | Compute the derivatives of the input points mean normal |
| CMeanPositionDer< DataPoint, _NFilter, DiffType, T > | Compute the derivatives of the input points barycenter |
| CPonca::CovarianceBase< DataPoint, _NFilter, T > | Procedure that compute and decompose the covariance matrix of the neighbors positions |
| 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::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::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 |
| ►CGlobalNeighborhoodFrame | |
| ►CPonca::internal::NoWeightFilterBase< DataPoint, GlobalNeighborhoodFrame > | |
| CPonca::NoWeightFilterGlobal< DataPoint > | Weighting function that set uniform weight to all samples and keep neighbors coordinates in global frame |
| CPonca::GlobalNeighborhoodFrame< DataPoint > | 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 |
| CPonca::GradientDescentProjectionOperator | Project a point using the gradinet of the sdf |
| CPonca::HashDefaultFunctor< N, T > | |
| CPonca::HashSet< N, T, _HashFunctor, OFFSET > | Stores unique signed integer values in a contiguous array |
| ►CPonca::internal::HexagramBase< P > | |
| CPonca::internal::TriangleGenerator< AvgHexagramGeneration, P > | |
| CPonca::internal::TriangleGenerator< HexagramGeneration, P > | |
| ►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< IndexType, Scalar > | |
| ►CInput_ | |
| ►CPonca::Query< Input_, Output_ > | Composes the Query object depending on an input type and output type |
| CPonca::NeighborGraphRangeQuery< NeighborGraph > | |
| CPonca::NeighborGraphRangeQuery< _NeighborGraph > | Extension of the Query class that allows to read the result of a range neighbor search on the KnnGraph |
| ►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, MAX_KNN_SIZE > | Input iterator to read the KdTreeKNearestQueryBase object |
| CPonca::KdTreeNearestIterator< Index > | Input iterator to read the KdTreeKNearestQueryBase object |
| CPonca::KdTreePointerTraits< _DataPoint, _NodeType > | Variant to the KdTree Traits type that uses pointers as internal storage instead of an STL-like container |
| ►CPonca::KdTreeQuery< Traits > | Query object that provides a method to search neighbors on the KdTree depending on a distance threshold |
| CPonca::KdTreeKNearestQueryBase< Traits, IteratorType, QueryType > | Extension of the Query class that allows to read the result of a k-nearest neighbors search on the KdTree |
| CPonca::KdTreeNearestQueryBase< Traits, IteratorType, QueryType > | Extension of the Query class that allows to read the result of a nearest neighbor search on the KdTree |
| CPonca::KdTreeRangeQueryBase< Traits, IteratorType, QueryType > | Extension of the Query class that allows to read the result of a range neighbors search on the KdTree |
| CPonca::KdTreeRangeIterator< Index, DataPoint, QueryT_ > | Input iterator to read the KdTreeRangeQueryBase object |
| CPonca::LimitedPriorityQueue< T, N, CompareT > | The LimitedPriorityQueue class is similar to std::priority_queue but has a limited capacity and handles the comparison differently |
| CPonca::LimitedPriorityQueue< IndexSquaredDistance< Index, Scalar >, MAX_KNN_SIZE > | |
| CPonca::MLSEvaluationScheme< Scalar > | Computes the fit using the Moving Least Squares approach |
| ►CNeighborFilter | |
| CPonca::FilterWithAttributes< _DataPoint, DataType, NeighborFilter, DataConverter > | This class extends a NeighborFilter class to also store additional data, for use outside the scope of this class |
| ►CPonca::NeighborGraphBufferBase< _Traits > | Internal structure storing the buffers used by a neighbor graph |
| CPonca::KnnGraphBuffers< Traits > | |
| CPonca::NeighborGraphBuffer< Traits > | |
| CPonca::KnnGraphBuffers< _Traits > | Buffer class for StaticKnnGraphBase |
| CPonca::NeighborGraphBuffer< _Traits > | Buffer class for StaticNeighborGraphBase |
| CPonca::NeighborGraphBufferBase< Traits > | |
| CPonca::NeighborGraphDefaultTraits< _DataPoint > | The default traits type used by the neighbor graph |
| CPonca::NeighborGraphOneConnectedIterator< ContainerPtr, Index > | Base iterator class for NeighborGraphOneConnectedQuery |
| CPonca::NeighborGraphPointerTraits< _DataPoint > | Variant to the NeighborGraphDefaultTraits that uses pointers as internal storage instead of an STL-like container |
| CPonca::NeighborGraphRangeIterator< _NeighborGraph > | Input iterator to read the NeighborGraphRangeQuery object |
| ►COutput_ | |
| CPonca::Query< Input_, Output_ > | Composes the Query object depending on an input type and output type |
| ►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::PointPosition< _Scalar, _Dim > | Point data type containing only containing the position vector |
| CPonca::PointPositionNormal< _Scalar, _Dim > | Point data type containing the position and normal vectors |
| CPonca::PointPositionNormalBinding< _Scalar, _Dim > | Variant of the PointPositionNormal data type that uses external raw data |
| CPonca::PointPositionNormalLazyBinding< _Scalar, _Dim > | Variant of the PointPositionNormal data type that uses external raw data. |
| ►CPonca::QueryInputBase | Base class for queries input type |
| CPonca::QueryInput< _NeighborGraph::Traits::IndexType > | |
| ►CPonca::QueryInput< Index > | |
| CPonca::QueryInputIsIndex< Index > | Extension of QueryInput that handles an index based search, in a partitioning structure |
| ►CPonca::QueryInput< DataPoint::VectorType > | |
| CPonca::QueryInputIsPosition< DataPoint > | Extension of QueryInput that handles a position based search, in a partitioning structure |
| ►CPonca::QueryInput< InputType_ > | Base class for Query input type |
| ►CPonca::QueryInputIsIndex< _NeighborGraph::Traits::IndexType > | |
| ►CPonca::Query< QueryInputIsIndex< _NeighborGraph::Traits::IndexType >, NeighborGraphQueryOutputType > | |
| CPonca::NeighborGraphOneConnectedQuery< _NeighborGraph > | Extension of the Query class that allows to read the neighbors that are directly connected to the query point in the neighbor graph |
| ►CPonca::QueryOutputBase | Base class for queries output types |
| ►CPonca::NeighborGraphQueryOutputType | Output type of the NeighborGraphOneConnectedQuery |
| CPonca::Query< QueryInputIsIndex< _NeighborGraph::Traits::IndexType >, NeighborGraphQueryOutputType > | |
| CPonca::QueryOutputIsKNearest< Index, Scalar, MAX_KNN_SIZE > | Class to construct the knearest queries |
| CPonca::QueryOutputIsNearest< Index, Scalar > | Class to construct the nearest query output |
| CPonca::QueryOutputIsRange< Index, Scalar > | Class to construct the range query output |
| ►CQueryType | |
| CPonca::KdTreeKNearestQueryBase< Traits, IteratorType, QueryType > | Extension of the Query class that allows to read the result of a k-nearest neighbors search on the KdTree |
| CPonca::KdTreeNearestQueryBase< Traits, IteratorType, QueryType > | Extension of the Query class that allows to read the result of a nearest neighbor search on the KdTree |
| CPonca::KdTreeRangeQueryBase< Traits, IteratorType, QueryType > | Extension of the Query class that allows to read the result of a range neighbors search on the KdTree |
| CPonca::SingleEvaluationScheme | SingleEvaluationScheme |
| CPonca::internal::CNCEigen< DataPoint >::SphericalTriangle | Represents a triangle on a sphere of radius one |
| CPonca::Stack< T, N > | Stack with fixed-size storage |
| CPonca::Stack< Ponca::IndexSquaredDistance< IndexType, Scalar >, 2 *Traits::MAX_DEPTH > | |
| ►CPonca::StaticKdTreeBase< _Traits > | Customizable static base class for KdTree datastructure implementations |
| ►CPonca::KdTreeBase< KdTreeDefaultTraits< DataPoint > > | |
| CPonca::KdTree< DataPoint > | Abstract KdTree type with KdTreeDefaultTraits |
| ►CPonca::KdTreeBase< Traits > | |
| CPonca::KdTreeDenseBase< Traits > | Customizable base class for dense KdTree datastructure |
| CPonca::KdTreeSparseBase< Traits > | Customizable base class for KdTreeSparse datastructure |
| ►CPonca::KdTreeBase< _Traits > | |
| ►CPonca::KdTreeDenseBase< KdTreeDefaultTraits< DataPoint > > | |
| CPonca::KdTreeDense< DataPoint > | Public interface for dense KdTree datastructure |
| ►CPonca::KdTreeSparseBase< KdTreeDefaultTraits< DataPoint > > | |
| CPonca::KdTreeSparse< DataPoint > | Public interface for sparse KdTree datastructure |
| ►CPonca::StaticKdTreeBase< KdTreeDefaultTraits< DataPoint > > | |
| CPonca::StaticKdTree< DataPoint > | A KdTree type with KdTreeDefaultTraits that doesn't define the build function |
| CPonca::StaticKdTreeBase< Traits > | |
| ►CT | |
| CMeanNormal< DataPoint, _NFilter, T > | Compute the mean normal of the input points |
| CMeanNormalDer< DataPoint, _NFilter, DiffType, T > | Compute the derivatives of the input points mean normal |
| CMeanPositionDer< DataPoint, _NFilter, DiffType, T > | Compute the derivatives of the input points barycenter |
| CPonca::AlgebraicSphere< DataPoint, _NFilter, T > | Algebraic Sphere primitive |
| CPonca::BasketDiffUnitBase< DataPoint, _NFilter, Type, T > | Base class of any computation unit of a BasketDiff |
| CPonca::CovarianceBase< DataPoint, _NFilter, T > | Procedure that compute and decompose the covariance matrix of the neighbors positions |
| CPonca::CovarianceDer< DataPoint, _NFilter, DiffType, T > | Internal generic class computing the derivatives of covariance matrix computed by covarianceBase |
| 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::DryFit< DataPoint, _NFilter, T > | Empty fitting object doing no computation |
| CPonca::FundamentalFormWeingartenEstimator< DataPoint, _NFilter, T > | Compute a Weingarten map from fundamental forms |
| CPonca::GLSDer< DataPoint, _NFilter, DiffType, T > | Differentiation of GLSParam |
| CPonca::GLSParam< DataPoint, _NFilter, T > | Growing Least Squares reparametrization of the OrientedSphereFit |
| CPonca::HeightField< DataPoint, _NFilter, T > | Internal base classe for height fields |
| 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::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::MlsSphereFitDer< DataPoint, _NFilter, DiffType, T > | Extension performing derivation of the mls surface |
| CPonca::MongePatch< DataPoint, _NFilter, T > | Monge Patch primitive, defined as \( \mathbf{x}(u,v)= (u,v,h(u,v)) \), with \(h(u,v)\) defined by a Base class |
| ►CPonca::MultipassStatus< DataPoint, _NFilter, T > | Helper class to check for status of required extensions |
| CPonca::MongePatchQuadraticFitImpl< DataPoint, _NFilter, T > | Extension to compute the best fit quadric on 3d points expressed as \(f(u,v)=h\) |
| CPonca::MongePatchRestrictedQuadraticFitImpl< DataPoint, _NFilter, T > | Extension to compute the best fit restricted quadric on 3d points expressed as \(f(u,v)=h\) |
| CPonca::NormalDerivativeWeingartenEstimator< DataPoint, _NFilter, DiffType, T > | Compute a Weingarten map from the spatial derivatives of the normal field \( N \) |
| 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::QuadraticHeightField< DataPoint, _NFilter, T > | Quadratic height field defined as \(h(u,v)=h_{uu}u^2 + h_{vv}v^2 + h_{uv}uv + h_u u + h_v v + h_c \) |
| CPonca::RestrictedQuadraticHeightField< DataPoint, _NFilter, T > | Quadratic height field defined as \(h(u,v)=h_{uu}u^2 + h_{vv}v^2 + h_{uv}uv + h_c \) |
| 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 |
| ►CPonca::internal::WeingartenCurvatureEstimatorBase< DataPoint, _NFilter, T > | Compute principal curvatures from a base class providing fundamental forms |
| CPonca::WeingartenCurvatureEstimator< DataPoint, _NFilter, T > | Compute principal curvatures from a base class providing fundamental forms. |
| CPonca::WeingartenCurvatureEstimatorDer< DataPoint, _NFilter, DiffType, T > | Compute principal curvatures from a base class providing fundamental forms. |
| CPonca::internal::Triangle< DataPoint > | Stores the three points and normals of the triangles and provides access to Corrected Normal Current formula |
| CPonca::internal::TriangleGenerator< Method, P > | |
| CPonca::internal::TriangleGenerator< IndependentGeneration, P > | |
| CPonca::internal::TriangleGenerator< UniformGeneration, P > | |
| ►Cstd::true_type | |
| CPonca::hasFirstFundamentalForm< T, std::void_t< decltype(std::declval< T >().firstFundamentalForm())> > | |
| ►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::ConstantWeightKernel< Scalar > | |
| 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