posted Jan 15, 2017, 10:44 AM by Mikail Rubinov
New network models  generate_fc.m: Generation of synthetic functional connectivity matrices based on structural network measures.
 predict_fc.m: Prediction of functional connectivity matrices from structural connectivity matrices.
 mleme_constraint_model.m: Unbiased sampling of networks with soft module and hub constraints (maximumlikelihood estimation of maximum entropy networks).
New measures and demos  clique_communities.m: Overlapping community structure via the clique percolation method.
 rentian_scaling_2d.m and rentian_scaling_3d.m: Updated rentian scaling functions to replace rentian_scaling.m.
 diffusion_efficiency.m: Global mean and pairwise effiency based on a diffusion process.
 distance_wei_floyd.m: All pairs shortest paths via the FloydWarshall algorithm.
 mean_first_passage_time.m: Mean first passage time.
 path_transitivity.m: Transitivity based on shortest paths.
 resource_efficiency_bin.m: Resource efficiency and shortest path probability.
 rout_efficiency.m: Mean, pairwise and local routing efficiency.
 retrieve_shortest_path.m: Retrieval of shortest path between source and target nodes.
 search_information.m: Search information based on shortest paths.
 demo_efficiency_measures.m: Demonstration of efficiency measures.
Removed functions  rentian_scaling.m: Replaced with rentian_scaling_2d.m and rentian_scaling_3d.m.
Bug fixes and/or code improvements and/or documentation improvements  efficiency_wei.m: Included a modified weighted variant of the local efficiency.
 partition_distance.m: Generalized computation of distances to input partition matrices.
 clustering_coef_wu_sign.m: Fixed computation of the denominator in the Constantini and Perugini versions of the weighted clustering coefficient.
 modularity_dir.m and modularity_und.m: Updated documentation and simplified code to clarify that these are deterministic algorithms.
 weight_conversion.m: Corrected bug in weight autofix.
Cosmetic and MATLAB code analyzer (mlint) improvements to many other functions 
posted Jan 17, 2016, 12:18 PM by Mikail Rubinov
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updated Jan 17, 2016, 12:23 PM
]
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.
New network measures  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 coreness 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.
Removed network measures  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
Bug fixes and/or code improvements and/or documentation improvements  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 Pottsmodel 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 finetuning 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 3cycles. Expanded documentation.
 clustering_coef_wu.m, clustering_coef_wd.m: Expanded documentation.
 motif3m and motif4m functions: Expanded documentation.
 rich_club_wu.m, rich_club_wd.m. Expanded documentation.
Cosmetic and MATLAB code analyzer (mlint) improvements to many other functions 
posted Jan 17, 2016, 12:16 PM by Mikail Rubinov
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updated Jan 17, 2016, 12:23 PM
]
Includes two new communitydetection scripts and multiple improvements New community detection scripts: 1. community_louvain.m (supersedes modularity_louvain.m and modularity_finetune.m scripts); 2. link_communities.m.
 added autofix flag to weight_conversion.m for fixing common weight problems.
 other function improvements: participation_coef.m, charpath.m, reorder_mod.m.
 bug fixes: modularity_finetune_und_sign.m, modularity_probtune_und_sign.m, threshold_proportional.m
 changed help files: assortativity_wei.m, distance_wei.m

posted Jan 17, 2016, 12:09 PM by Mikail Rubinov
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updated Jan 17, 2016, 12:22 PM
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 consensus_und.m is now a selfcontained function
 headers in charpath.m and in threshold_proportional.m have been corrected

