{"id":23382128,"url":"https://github.com/chiefenne/pywos","last_synced_at":"2025-04-08T08:44:45.439Z","repository":{"id":62199081,"uuid":"558724545","full_name":"chiefenne/PyWOS","owner":"chiefenne","description":"Monte Carlo method based on a recursive walk-on-spheres implementation in Python.","archived":false,"fork":false,"pushed_at":"2022-11-01T06:57:38.000Z","size":392,"stargazers_count":2,"open_issues_count":0,"forks_count":1,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-02-14T05:41:18.029Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/chiefenne.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE.md","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2022-10-28T06:40:11.000Z","updated_at":"2023-07-10T10:33:14.000Z","dependencies_parsed_at":"2023-01-21T03:17:20.975Z","dependency_job_id":null,"html_url":"https://github.com/chiefenne/PyWOS","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/chiefenne%2FPyWOS","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/chiefenne%2FPyWOS/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/chiefenne%2FPyWOS/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/chiefenne%2FPyWOS/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/chiefenne","download_url":"https://codeload.github.com/chiefenne/PyWOS/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":247808087,"owners_count":20999654,"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":"2024-12-21T21:17:31.773Z","updated_at":"2025-04-08T08:44:45.421Z","avatar_url":"https://github.com/chiefenne.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"\n```diff\n- WORK IN PROGRESS\n```\n\n# PyWOS\n![](images/WOS_example.png)\n\nMonte Carlo method based on a walk-on-spheres implementation for solving a 2D Poisson PDE written in Python.\n\nBased on the excellent [video](https://youtu.be/bZbuKOxH71o) by Keenan Crane from Carnegie Mellon University and a code snippet he provided [here](https://www.cs.cmu.edu/~kmcrane/Projects/MonteCarloGeometryProcessing/WoSPoisson2D.cpp.html).\n\nThe version presented here utilizes recursion.\n\nAssociated literature and [video](https://youtu.be/dXROl0KGPXc) from the original author:\n[\"Grid-Free Monte Carlo for PDEs with Spatially Varying Coefficients\"](https://arxiv.org/abs/2201.13240) by Sawhney, Seyb, Jarosz, Crane.\n\n## Usage\n\n\nPrint help on usage:\n```code\npython Random_walks_Poisson_solver.py -h \n```\nDo a single walk and plot it.\n```code\npython Random_walks_Poisson_solver.py -d -v \n```\nRun the solver using dedicated settings for number of walks, accuracy, and maximum number of steps per walk.\n```code\npython Random_walks_Poisson_solver.py -w 100 -e 0.01 -s 30 \n```\n\n## Requirements\n\n- Python 3.9+ (due to the version of argparse which is used)\n- Numpy\n- Matplotlib\n\n## License\n\n2022 Andreas Ennemoser – andreas.ennemoser@aon.at\n\nDistributed under the MIT license. See [LICENSE](https://github.com/chiefenne/PyWOS/blob/main/LICENSE.md) for more information.","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fchiefenne%2Fpywos","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fchiefenne%2Fpywos","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fchiefenne%2Fpywos/lists"}