Release Name: 2016-01-16 release

Notes:
Version 2016-16-01: Major update

New network models

• generative_model.m: Implements more than 10 generative network models.
• 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.

• clustering_coef_wu_sign.m: Multiple generalizations of the clustering coefficient for networks with positive and negative weights.
• core_periphery_dir.m: Optimal core structure and core-ness statistic.
• gateway_coef_sign.m: Gateway coefficient (a variant of the participation coefficient) for networks with positive and negative weights.
• 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.

• 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

• 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, streamlined code.
• 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 weights.
• randmio_und_signed.m: Now allows unbiased exploration of all network configurations.
• transitivity_bd.m, transitivity_wu.m, transitivity_wd.m: removed tests for absence of nodewise 3-cycles. Expanded documentation.
• clustering_coef_wu.m, clustering_coef_wd.m: Expanded documentation.
• motif3-m and motif4-m functions: Expanded documentation.
• rich_club_wu.m, rich_club_wd.m. Expanded documentation.