🧑‍🤝‍🧑 Core-Periphery

Submodules

hypergraphx.communities.core_periphery.model module

hypergraphx.communities.core_periphery.model.aggregate_local_core_values(nodes, order, local_core_values)[source]
hypergraphx.communities.core_periphery.model.aggregation_function(values)[source]
hypergraphx.communities.core_periphery.model.core_periphery(hypergraph, greedy_start=False, N_ITER=1000, *, seed=None, rng=None)[source]

Implementation of the core-periphery model described in: https://arxiv.org/pdf/2202.12769.pdf

Parameters:

  • hypergraph (Hypergraph) – Hypergraph object

  • greedy_start (bool) – If True, use a greedy approach to find the initial permutation of nodes (default: False)

  • N_ITER (int) – Number of iterations (default: 1000)

Returns:

Dictionary with coreness scores for each node

Return type:

dict

hypergraphx.communities.core_periphery.model.get_adj(d)[source]
hypergraphx.communities.core_periphery.model.get_core_quality(edges, order, local_core_values)[source]
hypergraphx.communities.core_periphery.model.relabel_nodes(d, w)[source]
hypergraphx.communities.core_periphery.model.sample_params(*, rng=None)[source]
hypergraphx.communities.core_periphery.model.sort_by_degree(d)[source]
hypergraphx.communities.core_periphery.model.transition_function(i, N_nodes, a, b)[source]

Module contents