{"id":13471966,"url":"https://github.com/sevamoo/SOMPY","last_synced_at":"2025-03-26T15:30:52.509Z","repository":{"id":20012483,"uuid":"23280070","full_name":"sevamoo/SOMPY","owner":"sevamoo","description":"A Python Library for Self Organizing Map (SOM)","archived":false,"fork":false,"pushed_at":"2023-04-07T11:23:51.000Z","size":10383,"stargazers_count":535,"open_issues_count":48,"forks_count":242,"subscribers_count":33,"default_branch":"master","last_synced_at":"2024-10-30T04:12:10.701Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"apache-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/sevamoo.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null}},"created_at":"2014-08-24T12:06:09.000Z","updated_at":"2024-10-24T08:18:10.000Z","dependencies_parsed_at":"2022-07-08T07:00:37.453Z","dependency_job_id":"adb55c8d-2f27-4755-8254-c0f5031e57f6","html_url":"https://github.com/sevamoo/SOMPY","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sevamoo%2FSOMPY","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sevamoo%2FSOMPY/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sevamoo%2FSOMPY/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sevamoo%2FSOMPY/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/sevamoo","download_url":"https://codeload.github.com/sevamoo/SOMPY/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":245681216,"owners_count":20655153,"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":"2024-07-31T16:00:50.745Z","updated_at":"2025-03-26T15:30:52.055Z","avatar_url":"https://github.com/sevamoo.png","language":"Jupyter Notebook","funding_links":[],"categories":["Jupyter Notebook","Python"],"sub_categories":["General-Purpose Machine Learning"],"readme":"SOMPY\n-----\nA Python Library for Self Organizing Map (SOM)\n\nAs much as possible, the structure of SOM is similar to `somtoolbox` in Matlab. It has the following functionalities:\n\n1. Only Batch training, which is faster than online training. It has parallel processing option similar to `sklearn` format and it speeds up the training procedure, but it depends on the data size and mainly the size of the SOM grid.I couldn't manage the memory problem and therefore, I recommend single core processing at the moment. But nevertheless, the implementation of the algorithm is carefully done for all those important matrix calculations, such as `scipy` sparse matrix and `numexpr` for calculation of Euclidean distance.\n2. PCA (or RandomPCA (default)) initialization, using `sklearn` or random initialization.\n3. component plane visualization (different modes).\n4. Hitmap.\n5. U-Matrix visualization.\n6. 1-d or 2-d SOM with only rectangular, planar grid. (works well in comparison with hexagonal shape, when I was checking in Matlab with somtoolbox).\n7. Different methods for function approximation and predictions (mostly using Sklearn).\n\n\n### Dependencies:\nSOMPY has the following dependencies:\n- numpy\n- scipy\n- scikit-learn\n- numexpr\n- matplotlib\n- pandas\n- ipdb\n\n### Installation:\n```Python\npython setup.py install\n```\n\n\nMany thanks to @sebastiandev, the library is now standardized in a pythonic tradition. Below you can see some basic examples, showing how to use the library.\nBut I recommend you to go through the codes. There are several functionalities already implemented, but not documented. I would be very happy to add your new examples here.\n\n[Basic Example](https://gist.github.com/sevamoo/035c56e7428318dd3065013625f12a11)\n\n### Citation\n\nThere is no published paper about this library. However if possible, please cite the library as follows:\n\n```\n@misc{moosavi2014sompy,\n  title={SOMPY: A Python Library for Self Organizing Map (SOM)},\n  author={Moosavi, V and Packmann, S and Vall{\\'e}s, I},\n  note={GitHub.[Online]. Available: https://github. com/sevamoo/SOMPY},\n  year={2014}\n}\n```\n\n\nFor more information, you can contact me via sevamoo@gmail.com but please report an issue first.\n\n\n\n\nThanks a lot.\nBest Vahid Moosavi\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsevamoo%2FSOMPY","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsevamoo%2FSOMPY","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsevamoo%2FSOMPY/lists"}