Classes | |
class | Gudhi::persistent_cohomology::Field_Zp |
Structure representing the coefficient field ![]() | |
class | Gudhi::persistent_cohomology::Multi_field |
Structure representing coefficients in a set of finite fields simultaneously using the chinese remainder theorem. More... | |
class | Gudhi::persistent_cohomology::Persistent_cohomology< FilteredComplex, CoefficientField > |
Computes the persistent cohomology of a filtered complex. More... | |
Computation of persistent cohomology using the algorithm of [7] and [8] and the Compressed Annotation Matrix implementation of [5]
The theory of homology consists in attaching to a topological space a sequence of (homology) groups, capturing global topological features like connected components, holes, cavities, etc. Persistent homology studies the evolution – birth, life and death – of these features when the topological space is changing. Consequently, the theory is essentially composed of three elements: topological spaces, their homology groups and an evolution scheme.
The theory of homology consists in attaching to a topological space a sequence of (homology) groups, capturing global topological features like connected components, holes, cavities, etc. Persistent homology studies the evolution – birth, life and death – of these features when the topological space is changing. Consequently, the theory is essentially composed of three elements: topological spaces, their homology groups and an evolution scheme.
Topological Spaces: Topological spaces are represented by simplicial complexes. Let be a set of vertices. A simplex
is a subset of vertices
. A simplicial complex
on
is a collection of simplices
,
, such that
. The dimension
of
is its number of elements minus 1. A filtration of a simplicial complex is a function
satisfying
whenever
.
We define the concept FilteredComplex which enumerates the requirements for a class to represent a filtered complex from which persistent homology may be computed. We use the vocabulary of simplicial complexes, but the concept is valid for any type of cell complex. The main requirements are the definition of:
Indexing_tag
, which is a model of the concept IndexingTag
, describing the nature of the indexing scheme, int dimension(Simplex_handle)
returning the dimension of a simplex, Boundary_simplex_range boundary_simplex_range(Simplex_handle)
that returns a range giving access to the codimension 1 subsimplices of the input simplex, as-well-as the coefficients Simplex_handle
, Filtration_simplex_range filtration_simplex_range ()
that returns a range giving access to all the simplices of the complex read in the order assigned by the indexing scheme, Filtration_value filtration (Simplex_handle)
that returns the value of the filtration on the simplex represented by the handle.Homology: For a ring , the group of n-chains, denoted
, of
is the group of formal sums of n-simplices with
coefficients. The boundary operator is a linear operator
such that
, where
means
is omitted from the list. The chain groups form a sequence:
of finitely many groups and homomorphisms
, indexed by the dimension
. The boundary operators satisfy the property
for every
and we define the homology groups:
We refer to [13] for an introduction to homology theory and to [9] for an introduction to persistent homology.
Indexing Scheme: "Changing" a simplicial complex consists in applying a simplicial map. An indexing scheme is a directed graph together with a traversal order, such that two consecutive nodes in the graph are connected by an arrow (either forward or backward). The nodes represent simplicial complexes and the directed edges simplicial maps.
From the computational point of view, there are two types of indexing schemes of interest in persistent homology: linear ones in persistent homology [14] , and zigzag ones
in zigzag persistent homology [6]. These indexing schemes have a natural left-to-right traversal order, and we describe them with ranges and iterators. In the current release of the Gudhi library, only the linear case is implemented.
In the following, we consider the case where the indexing scheme is induced by a filtration. Ordering the simplices by increasing filtration values (breaking ties so as a simplex appears after its subsimplices of same filtration value) provides an indexing scheme.
We provide several example files: run these examples with -h for details on their use, and read the README file.
rips_persistence.cpp
computes the Rips complex of a point cloud and its persistence diagram.rips_multifield_persistence.cpp
computes the Rips complex of a point cloud and its persistence diagram with a family of field coefficients.performance_rips_persistence.cpp
provides timings for the construction of the Rips complex on a set of points sampling a Klein bottle in