{"id":17148630,"url":"https://github.com/ntamas/blockmodel","last_synced_at":"2025-04-13T11:42:00.552Z","repository":{"id":1222787,"uuid":"1143798","full_name":"ntamas/blockmodel","owner":"ntamas","description":"Fitting stochastic blockmodels to graphs","archived":false,"fork":false,"pushed_at":"2016-07-08T10:36:42.000Z","size":236,"stargazers_count":17,"open_issues_count":0,"forks_count":3,"subscribers_count":3,"default_branch":"master","last_synced_at":"2025-03-27T02:51:12.491Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"","language":"C++","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/ntamas.png","metadata":{"files":{"readme":"README.rst","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2010-12-06T17:14:10.000Z","updated_at":"2024-04-25T19:57:40.000Z","dependencies_parsed_at":"2022-07-06T12:41:20.741Z","dependency_job_id":null,"html_url":"https://github.com/ntamas/blockmodel","commit_stats":null,"previous_names":[],"tags_count":1,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ntamas%2Fblockmodel","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ntamas%2Fblockmodel/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ntamas%2Fblockmodel/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ntamas%2Fblockmodel/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/ntamas","download_url":"https://codeload.github.com/ntamas/blockmodel/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248709487,"owners_count":21149178,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2024-10-14T21:29:20.834Z","updated_at":"2025-04-13T11:42:00.533Z","avatar_url":"https://github.com/ntamas.png","language":"C++","funding_links":[],"categories":[],"sub_categories":[],"readme":"==========\nblockmodel\n==========\n----------------------------------------------------\nFitting stochastic blockmodels to empirical networks\n----------------------------------------------------\n\n:Author: Tamas Nepusz\n:Version: 0.1\n:License: GPL\n\nThis repository contains ``block-fit``, ``block-gen`` and ``block-pred``,\na suite of three programs to work with stochastic blockmodels (both\ndegree-corrected and standard ones). ``block-fit`` fits a standard or\ndegree-corrected blockmodel to a given graph, ``block-gen`` generates graphs\nfrom a fitted model and ``block-pred`` calculates the probability of existence\nfor each possible edge in a grpah from a fitted stochastic blockmodel. More\ndetails about the usage of each program are to be found in the ``doc``\nsubfolder. Please also read the references [1]_ [2]_ [3]_ [4]_ if you are\ninterested in how these models work.\n\nPrecompiled binaries\n====================\n\nSorry, we do not provide precompiled binaries yet - you have to compile the\ntools on your own.\n\nCompiling from source code\n==========================\n\nRequirements\n------------\n\n- igraph_ 0.7.1 or later. This is the library that we use to work with graphs.\n\n- CMake_ to generate the makefiles (or the project file if you are using\n  Visual Studio).\n\n.. _igraph: http://igraph.org\n.. _CMake: http://www.cmake.org\n\nCompiling using ``cmake`` and ``make``\n--------------------------------------\n\nThese instructions are for Linux or Mac OS X and assume that igraph_ is\ninstalled in a way that CMake can figure out automatically where it is.\n(This usually involves using ``pkg-config``; if you run ``pkg-config --cflags igraph``\nand it works, then it should work with CMake as well)::\n\n    $ git submodule update --init\n    $ mkdir build\n    $ cd build\n    $ cmake ..\n    $ make\n\nThe first command is required only after you have checked out the source code\nfrom GitHub for the first time. The command fetches the source code of the\nC++ interface of igraph_ from GitHub and adds it to the source tree.\n\nBugs, questions?\n================\n\nHave you found a bug in the code? Do you have questions? Let me know.\nI think you are smart enough to figure out my email address by googling\nfor my name. Or just drop me a message on GitHub.\n\nReferences\n==========\n\n.. [1] Snijders TAB, Nowicki K (1997) Estimation and prediction for stochastic\n       blockmodels for graphs with latent block structure. *J Classif*\n       **14**:75-100.\n\n.. [2] Nepusz T, Négyessy L, Tusnády G, Bazsó F (2008) Reconstructing cortical\n       networks: case of directed graphs with high level of reciprocity. In:\n       Bollobás B, Kozma R, Miklós D, editors, Handbook of Large-Scale Random\n       Networks, Springer, volume 18 of *Bolyai Society Mathematical Studies*,\n       pp. 325-368.\n\n.. [3] Karrer B, Newman MEJ (2011) Stochastic blockmodels and community\n       structure in networks. *Phys Rev E* **83**:016107.\n\n.. [4] Nepusz T, Paccanaro A (2013) De-noising protein-protein interaction\n       networks with random graph models. In preparation.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fntamas%2Fblockmodel","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fntamas%2Fblockmodel","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fntamas%2Fblockmodel/lists"}