{"id":13869799,"url":"https://github.com/statphysandml/pystatplottools","last_synced_at":"2025-07-15T18:32:00.866Z","repository":{"id":113511061,"uuid":"320233920","full_name":"statphysandml/pystatplottools","owner":"statphysandml","description":"Easy evaluation and plotting of statistical data and high-dimensional distributions in python - Fast generation, loading and storing of custom datasets.","archived":false,"fork":false,"pushed_at":"2024-06-01T14:40:40.000Z","size":509,"stargazers_count":8,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"master","last_synced_at":"2024-11-23T15:35:42.749Z","etag":null,"topics":["contour-plots","custom-datasets","distributions","expectation-values","high-dimensional-data"],"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/statphysandml.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,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2020-12-10T10:16:41.000Z","updated_at":"2024-06-01T14:40:43.000Z","dependencies_parsed_at":"2024-11-23T15:42:07.940Z","dependency_job_id":null,"html_url":"https://github.com/statphysandml/pystatplottools","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/statphysandml/pystatplottools","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/statphysandml%2Fpystatplottools","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/statphysandml%2Fpystatplottools/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/statphysandml%2Fpystatplottools/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/statphysandml%2Fpystatplottools/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/statphysandml","download_url":"https://codeload.github.com/statphysandml/pystatplottools/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/statphysandml%2Fpystatplottools/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":265451450,"owners_count":23767768,"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":["contour-plots","custom-datasets","distributions","expectation-values","high-dimensional-data"],"created_at":"2024-08-05T20:01:17.772Z","updated_at":"2025-07-15T18:32:00.431Z","avatar_url":"https://github.com/statphysandml.png","language":"Python","funding_links":[],"categories":["Python"],"sub_categories":[],"readme":"pystatplottools\n=================\n\nA Python library that simplifies working with and plotting of statistical data and high-dimensional distributions. The library utilizes standard numpy operations in a smart way for an easy processing of more complicated data evaluation methods. Further, the pytorch_data_generation module simplifies the generation and the storage of custom datasets. The pystatsplottools library currently consists of the following main modules:\n\n- **distributions** - Convenient computation of joint and marginal distributions. In addition, binned statistics can be evaluated.\n- **expectation_values** - Computation of expectation values.\n- **plotting** - Wrapper for plotting 2D contour plots with linear and logarithmic scales.\n- **pytorch_data_generation** - Tools for an easy generation and storage of a custom PyTorch datasets. The data can be pregenerated and stored as a .pt file. Alternatively, data can be generated in real time.\n- **visualization** - Contains a class for visualizing samples and batches from the dataset and a decorator for handling figures\n- **pdf_env** - Adapted tool for an easy saving of plots as pdfs and pngs. The original code can be found on http://bkanuka.com/posts/native-latex-plots/.\n\nExamples\n--------\n\nExamples to the different Python modules can be found in the examples/ folder. A more detailed example which covers almost all functionalities of the library can be found here: https://github.com/statphysandml/pystatplottools/blob/master/examples/cheat_sheet.ipynb.\n\nIntegration\n-----------\n\nSo far, the library needs to be build locally. This can be done by\n\n```bash\ncd path_to_pystatplottools/\n\npython setup.py sdist\npip install -e .\n```\n\nFor virtual environments, the library needs to be activate beforehand.\n\nAfter this step, the different modules of the library can be used, for example, by\n\n```python\nimport pystatplottools\n\nfrom pystatplottools.distributions.joint_distribution import JointDistribution\n```\n\nDependencies\n------------\n\n- matplotlib\n- numpy\n- pandas\n- scipy\n- (pytorch)\n- (jupyter lab)\n\nProjects using the pystatplottools library\n------------------------------------------\n\n- MCMCEvalutionLib (https://github.com/statphysandml/MCMCEvaluationLib)\n\nSupport and Development\n----------------------\n\nFor bug reports/suggestions/complaints please file an issue on GitHub.\n\nOr start a discussion on our mailing list: statphysandml@thphys.uni-heidelberg.de\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fstatphysandml%2Fpystatplottools","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fstatphysandml%2Fpystatplottools","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fstatphysandml%2Fpystatplottools/lists"}