Rips complex reference manual¶
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class
gudhi.
RipsComplex
¶ Bases:
object
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 length is computed from a user given point cloud with a given distance function, or a distance matrix.
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__init__
()¶ RipsComplex constructor.
- Parameters
Or
- Parameters
distance_matrix¶ – A distance matrix (full square or lower triangular).
And in both cases
- Parameters
sparse¶ (float) – If this is not None, it switches to building a sparse Rips and represents the approximation parameter epsilon.
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Weighted Rips complex reference manual¶
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class
gudhi.weighted_rips_complex.
WeightedRipsComplex
(distance_matrix, weights=None, max_filtration=inf)[source]¶ Bases:
object
Class to generate a weighted Rips complex from a distance matrix and weights on vertices, in the way described in [1]. Remark that all the filtration values are doubled compared to the definition in the paper for the consistency with RipsComplex.
DTM Rips complex reference manual¶
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class
gudhi.dtm_rips_complex.
DTMRipsComplex
(points=None, distance_matrix=None, k=1, q=2, max_filtration=inf)[source]¶ Bases:
gudhi.weighted_rips_complex.WeightedRipsComplex
Class to generate a DTM Rips complex from a distance matrix or a point set, in the way described in [1]. Remark that all the filtration values are doubled compared to the definition in the paper for the consistency with RipsComplex. :Requires: SciPy
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__init__
(points=None, distance_matrix=None, k=1, q=2, max_filtration=inf)[source]¶ - Parameters
points¶ (numpy.ndarray) – array of points.
distance_matrix¶ (numpy.ndarray) – full distance matrix.
k¶ (int) – number of neighbors for the computation of DTM. Defaults to 1, which is equivalent to the usual Rips complex.
q¶ (float) – order used to compute the distance to measure. Defaults to 2.
max_filtration¶ (float) – specifies the maximal filtration value to be considered.
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