{"id":17603482,"url":"https://github.com/laurentrdc/scikit-ued","last_synced_at":"2025-04-12T14:55:55.463Z","repository":{"id":52273312,"uuid":"89083179","full_name":"LaurentRDC/scikit-ued","owner":"LaurentRDC","description":"Collection of algorithms and routines for (ultrafast) electron diffraction and scattering","archived":false,"fork":false,"pushed_at":"2025-01-16T16:59:58.000Z","size":25388,"stargazers_count":138,"open_issues_count":0,"forks_count":21,"subscribers_count":8,"default_branch":"master","last_synced_at":"2025-04-03T15:08:45.740Z","etag":null,"topics":["diffraction","electron-microscopy","python","science","scikit","ultrafast-electron"],"latest_commit_sha":null,"homepage":"http://scikit-ued.readthedocs.io","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"gpl-3.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/LaurentRDC.png","metadata":{"files":{"readme":"README.md","changelog":"CHANGELOG.rst","contributing":"CONTRIBUTING.md","funding":null,"license":"LICENSE.txt","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":"2017-04-22T16:22:39.000Z","updated_at":"2025-02-01T12:12:39.000Z","dependencies_parsed_at":"2023-02-17T06:45:59.345Z","dependency_job_id":"1710176a-f940-4f27-8f9d-0bbc38d96a45","html_url":"https://github.com/LaurentRDC/scikit-ued","commit_stats":{"total_commits":4967,"total_committers":6,"mean_commits":827.8333333333334,"dds":0.02516609623515198,"last_synced_commit":"6c456eb1f7f36a3e35f0732c075ae2aed5731b1e"},"previous_names":[],"tags_count":35,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/LaurentRDC%2Fscikit-ued","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/LaurentRDC%2Fscikit-ued/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/LaurentRDC%2Fscikit-ued/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/LaurentRDC%2Fscikit-ued/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/LaurentRDC","download_url":"https://codeload.github.com/LaurentRDC/scikit-ued/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248586245,"owners_count":21128996,"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":["diffraction","electron-microscopy","python","science","scikit","ultrafast-electron"],"created_at":"2024-10-22T13:53:12.372Z","updated_at":"2025-04-12T14:55:55.435Z","avatar_url":"https://github.com/LaurentRDC.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"scikit-ued\n==========\n\n[![Documentation Build Status](https://readthedocs.org/projects/scikit-ued/badge/?version=master)](http://scikit-ued.readthedocs.io) [![PyPI Version](https://img.shields.io/pypi/v/scikit-ued.svg)](https://pypi.org/project/scikit-ued/) [![Conda-forge Version](https://img.shields.io/conda/vn/conda-forge/scikit-ued.svg)](https://anaconda.org/conda-forge/scikit-ued) [![DOI badge](https://img.shields.io/badge/DOI-10.1186%2Fs40679--018--0060--y-blue)](https://doi.org/10.1186/s40679-018-0060-y)\n\nCollection of algorithms and functions for ultrafast electron diffraction. It aims to be a fully-tested package taking advantage of Python's most recent features.\n\nFor examples, see our [tutorials](https://scikit-ued.readthedocs.io/).\n\nAPI Reference\n-------------\n\nThe [API Reference on readthedocs.io](https://scikit-ued.readthedocs.io) provides API-level documentation, as well as tutorials.\n\nInstallation\n------------\n\nscikit-ued is available on PyPI; it can be installed with [pip](https://pip.pypa.io):\n\n    python -m pip install scikit-ued\n\nTo also install optional dependencies required to view diffraction images interactively:\n\n    python -m pip install scikit-ued[diffshow]\n\nscikit-ued is also available on the conda-forge channel for the [conda package manager](https://conda.io/docs/):\n\n    conda config --add channels conda-forge\n    conda install scikit-ued\n\nTo install the latest development version from [Github](https://github.com/LaurentRDC/scikit-ued):\n\n    python -m pip install git+https://github.com/LaurentRDC/scikit-ued.git\n\nAfter installing scikit-ued you can use it like any other Python module\nas `skued`.\n\nEach version is tested against **Python 3.7+**. If you are using a\ndifferent version, tests can be run using the `pytest` package.\n\nOptional dependencies\n---------------------\n\nFor displaying diffraction images with interactive contrast using the\n`skued.diffshow` function, PyQtGraph is required.\n\nContributing\n------------\n\nIf you want to contribute to `scikit-ued`, take a look at [`CONTRIBUTING.md`](https://github.com/LaurentRDC/scikit-ued/blob/master/CONTRIBUTING.md).\n\nRelated projects\n----------------\n\nStreaming operations on NumPy arrays are available in the [npstreams package](https://pypi.org/pypi/npstreams).\n\nInteractive exploration of ultrafast electron diffraction data with the [iris-ued package](https://pypi.org/project/iris-ued/).\n\nCrystal structure manipulation (including symmetry-determination) with the [crystals package](https://pypi.org/project/crystals/). (Included\nwith scikit-ued)\n\nA graphical user interface for the dual-tree complex wavelet transform\nbaseline-removal routine is available as a [separate package](https://pypi.org/pypi/dtgui).\n\nCitations\n---------\n\nIf you find this software useful, please consider citing the following\npublication:\n\n\u003e L. P. René de Cotret, M. R. Otto, M. J. Stern. and B. J. Siwick, *An open-source software ecosystem for the interactive exploration of ultrafast electron scattering data*, Advanced Structural and Chemical Imaging 4:11 (2018) [DOI: 10.1186/s40679-018-0060-y.](https://ascimaging.springeropen.com/articles/10.1186/s40679-018-0060-y)\n\nIf you are using the baseline-removal functionality of scikit-ued,\nplease consider citing the following publication:\n\n\u003e L. P. René de Cotret and B. J. Siwick, *A general method for baseline-removal in ultrafast electron powder diffraction data using the dual-tree complex wavelet transform*, Struct. Dyn. 4 (2017) [DOI: 10.1063/1.4972518](https://doi.org/10.1063/1.4972518).\n\n\nSupport / Report Issues\n-----------------------\n\nAll support requests and issue reports should be [filed on Github as an issue](https://github.com/LaurentRDC/scikit-ued/issues).\n\nLicense\n-------\n\nscikit-ued is made available under the GPLv3 License. For more details,\nsee [LICENSE.txt](https://github.com/LaurentRDC/scikit-ued/blob/master/LICENSE.txt).\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flaurentrdc%2Fscikit-ued","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Flaurentrdc%2Fscikit-ued","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flaurentrdc%2Fscikit-ued/lists"}