Version 2016-16-01: Major update
New network models
New network measures
- generative_model.m: Implements more than 10 generative network
- evaluate_generative_model.m: Implements and evaluates the
accuracy of more than 10 generative network models.
- demo_generative_models_geometric.m and
demo_generative_models_neighbors.m: Demonstrate the capabilities of
the new generative model functions.
Removed network measures
- clustering_coef_wu_sign.m: Multiple generalizations of the
clustering coefficient for networks with positive and negative
- core_periphery_dir.m: Optimal core structure and core-ness
- gateway_coef_sign.m: Gateway coefficient (a variant of the
participation coefficient) for networks with positive and negative
- local_assortativity_sign.m: Local (nodal) assortativity for
networks with positive and negative weights.
- randmio_dir_signed.m: Random directed graph with preserved
signed in- and out- degree distribution.
Bug fixes and/or code improvements and/or documentation
- modularity_louvain_und_sign.m, modularity_finetune_und_sign.m:
This functionality is now provided by community_louvain.m.
- modularity_probtune_und_sign.m: Similar functionality is
provided by consensus_und.m
Cosmetic and MATLAB code analyzer (mlint) improvements to many
- charpath.m: Changed default behavior, such that infinitely long
paths (i.e. paths between disconnected nodes) are now included in
computations by default, but may be excluded manually.
- community_louvain.m: Included generalization for negative
weights, enforced binary network input for Potts-model Hamiltonian,
- eigenvector_centrality_und.m: Ensured the use of leading
eigenvector for computations of eigenvector centrality.
- modularity_und.m, modularity_dir.m: Enforced single node moves
during fine-tuning step.
- null_model_und_sign.m and null_model_dir_sign.m: Fixed
preservation of negative degrees in sparse networks with negative
- randmio_und_signed.m: Now allows unbiased exploration of all
- transitivity_bd.m, transitivity_wu.m, transitivity_wd.m:
removed tests for absence of nodewise 3-cycles. Expanded
- clustering_coef_wu.m, clustering_coef_wd.m: Expanded
- motif3-m and motif4-m functions: Expanded documentation.
- rich_club_wu.m, rich_club_wd.m. Expanded documentation.