The simplex tree is an efficient and flexible data structure for representing general (filtered) simplicial complexes. The data structure is d

The CubicalComplex is an example of a structured complex useful in computational mathematics (specially rigorous numerics) and image analysis.

@brief Compute the Euclidean distance between two Points given by a range of coordinates. The points are assumed to * have the same dimension. */

Class wrapping several implementations for computing the k nearest neighbors in a point set. :Requires: `PyKeOps <installation.html#pykeops>

The data structure is a one skeleton graph, or Rips graph, containing edges when the edge length is less or equal to a given threshold. Edge lengt

The PeriodicCubicalComplex is an example of a structured complex useful in computational mathematics (specially rigorous numerics) and image a

AlphaComplex is a simplicial complex constructed from the finite cells of a Delaunay Triangulation. The filtration value of each simplex is compu

Class to compute the distance to the empirical measure defined by a point set, as introduced in :cite:`dtmgeoinference2011`.

Compute Betti curves from persistence diagrams. There are several modes of operation: with a given resolution (with or without a sample_range), w

Cover complex data structure. The data structure is a simplicial complex, representing a Graph Induced simplicial Complex (GIC) or a Nerve, a

This is a class for computing persistence entropy. Persistence entropy is a statistic for persistence diagrams inspired from Shannon entropy. Thi

This is a class for computing persistence landscapes from a list of persistence diagrams. A persistence landscape is a collection of 1D piecewise

Vertex tag for Boost PropertyGraph. */

This is a class for computing the persistence diagrams from a cubical complex.

This is a class for computing persistence silhouettes from a list of persistence diagrams. A persistence silhouette is computed by taking a weigh

This clustering algorithm needs a neighborhood graph on the points, and an estimation of the density at each point. A few possible graph cons

This is a class for constructing Vietoris-Rips filtrations (possibly implicitly) and computing their persistence diagrams. It does not alway

r""" This is a class for computing the bottleneck distance matrix from a list of persistence diagrams. :Requires: `CGAL <installation.html#cg

Density estimator based on the distance to the empirical measure defined by a point set, as defined in :cite:`dtmdensity`. Note that this imp

DelaunayComplex is a simplicial complex constructed from the finite cells of a Delaunay Triangulation. When :paramref:`~gudhi.DelaunayComplex.cre

This is a class for preprocessing persistence diagrams with a given list of scalers, such as those included in scikit-learn.

This is a TensorFlow layer for vectorizing persistence diagrams in a differentiable way within a neural network. This function implements the Per

Constructs (strong) witness complex for a given table of nearest landmarks with respect to witnesses.

Point cloud transformation class. Embeds time-series data in the R^d according to `Takens' Embedding Theorem <https://en.wikipedia.org/wiki/Takens

This is a class for computing the Wasserstein distance matrix from a list of persistence diagrams.

Edge tag for Boost PropertyGraph. */

This is a class for the affine transformation (x,y) -> (x,y-x) to be applied on persistence diagrams.

This is a class for computing the same persistent homology as the Čech complex, while being significantly smaller, using internally a :class:

This is a class for extracting finite or essential points in persistence diagrams.

Constructs strong witness complex for given sets of witnesses and landmarks in Euclidean space.

Constructs (weak) witness complex for given sets of witnesses and landmarks in Euclidean space.

\internal \typedef \brief Internal_point is the internal points representation, indexes used outside. */

\brief Class that represents an ordered set partition of a set {0,...,n-1} in k parts as * a pair of an unordered set partition given in lexi

This is a class for computing the sliced Wasserstein distance matrix from a list of persistence diagrams. The Sliced Wasserstein distance is comp

Class to generate a weighted Rips complex from a distance matrix and weights on vertices, in the way described in :cite:`dtmfiltrations` with

Constructs (weak) witness complex for a given table of nearest landmarks with respect to witnesses.

This class allows to vectorise measures (e.g. point clouds, persistence diagrams, etc) after a quantisation step. ATOL paper: :cite:`royer20

Class to generate a DTM Rips complex from a distance matrix or a point set, in the way described in :cite:`dtmfiltrations`. Remark that a

DelaunayCechComplex is a simplicial complex constructed from the finite cells of a Delaunay Triangulation. The filtration value of each simplex i

This is a class to select persistence diagrams in a specific dimension from its index.

This is a class for computing a transformation function for persistence diagram points. This function turns persistence diagram points into 1D co

This is a class for computing the persistence Fisher kernel matrix from a list of persistence diagrams. The persistence Fisher kernel is computed

This is a class for computing persistence images from a list of persistence diagrams. A persistence image is a 2D function computed from a persis

This is a class that returns the sorted N-longest persistence lengths. If the input does not contain enough values, the output will be filled

This is a class for computing the persistence scale space kernel matrix from a list of persistence diagrams. The persistence scale space kernel i

This is a class for computing the persistence weighted Gaussian kernel matrix from a list of persistence diagrams. The persistence weighted Gauss

This is a class for computing a differentiable weight function for persistence diagram points. This function is defined as a constant multiplied

This is a class for computing the sliced Wasserstein kernel matrix from a list of persistence diagrams. The sliced Wasserstein kernel is computed

The class Tangential_complex represents a tangential complex. After the computation of the complex, an optional post-processing called perturbatio

This is a class for computing the same persistent homology as the Weighted Čech complex, while being significantly smaller, using internally

This is a class for clamping a list of values. It is not meant to be called directly on (a list of) persistence diagrams, but it is rather meant

This is a class for computing complex polynomials from a list of persistence diagrams. The persistence diagram points are seen as the roots of so

Functor for compute_tangential_complex function

TensorFlow layer for computing the persistent homology of a cubical complex

This is a class for computing graph induced simplicial complexes on point clouds or distance matrices.

pre declaration needed before C++20 for friends with templates defined inside a class

This is a class for computing topological vectors from a list of persistence diagrams. The topological vector associated to a persistence diagram

* @class Z2_field_element Z2_field.h gudhi/Fields/Z2_field.h * @ingroup persistence_fields * * @brief Class representing an element of the \f$ \mat

The class Distance contains a distance function defined on the set of points {0, 1, 2, 3} * and computes a distance according to the matrix: * 0 1 2

* \class Function_Sm_in_Rd * \brief A class for the function that defines an m-dimensional implicit sphere embedded * in the d-dimensional Euclidean