{"id":24702996,"url":"https://github.com/arm-doe/act","last_synced_at":"2026-01-24T00:46:15.578Z","repository":{"id":38147363,"uuid":"175027624","full_name":"ARM-DOE/ACT","owner":"ARM-DOE","description":"Atmospheric data Community Toolkit - A python based toolkit for exploring and analyzing time series atmospheric datasets","archived":false,"fork":false,"pushed_at":"2025-05-07T16:55:07.000Z","size":300115,"stargazers_count":161,"open_issues_count":17,"forks_count":38,"subscribers_count":10,"default_branch":"main","last_synced_at":"2025-05-12T22:40:05.131Z","etag":null,"topics":["atmospheric-science","corrections","meteorological-data","meteorology","retrieval","time-series","visualization"],"latest_commit_sha":null,"homepage":"https://ARM-DOE.github.io/ACT/","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"other","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/ARM-DOE.png","metadata":{"files":{"readme":"README.rst","changelog":null,"contributing":"CONTRIBUTING.rst","funding":null,"license":"LICENSE.txt","code_of_conduct":"CODE_OF_CONDUCT.md","threat_model":null,"audit":null,"citation":null,"codeowners":"CODEOWNERS","security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2019-03-11T15:19:03.000Z","updated_at":"2025-05-10T00:30:46.000Z","dependencies_parsed_at":"2023-09-25T20:18:06.403Z","dependency_job_id":"cad511ac-03fe-42f6-82e2-4c101c4fe6e9","html_url":"https://github.com/ARM-DOE/ACT","commit_stats":{"total_commits":1475,"total_committers":21,"mean_commits":70.23809523809524,"dds":0.5383050847457627,"last_synced_commit":"0125b371a18bb51387d7dacc0413c38294788dd9"},"previous_names":[],"tags_count":80,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ARM-DOE%2FACT","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ARM-DOE%2FACT/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ARM-DOE%2FACT/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ARM-DOE%2FACT/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/ARM-DOE","download_url":"https://codeload.github.com/ARM-DOE/ACT/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":254040737,"owners_count":22004602,"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":["atmospheric-science","corrections","meteorological-data","meteorology","retrieval","time-series","visualization"],"created_at":"2025-01-27T05:51:49.987Z","updated_at":"2025-10-07T16:10:20.151Z","avatar_url":"https://github.com/ARM-DOE.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"========================================\r\nAtmospheric data Community Toolkit (ACT)\r\n========================================\r\n\r\n|AnacondaCloud| |CodeCovStatus| |Build| |Docs|\r\n\r\n|CondaDownloads| |PyPiDownloads| |Zenodo| |ARM|\r\n\r\n.. |AnacondaCloud| image:: https://anaconda.org/conda-forge/act-atmos/badges/version.svg\r\n    :target: https://anaconda.org/conda-forge/act-atmos\r\n\r\n.. |CondaDownloads| image:: https://anaconda.org/conda-forge/act-atmos/badges/downloads.svg\r\n    :target: https://anaconda.org/conda-forge/act-atmos/files\r\n\r\n.. |PyPiDownloads| image:: https://img.shields.io/pypi/dm/act_atmos.svg\r\n    :target: https://pypi.org/project/act-atmos/\r\n\r\n.. |Zenodo| image:: https://zenodo.org/badge/DOI/10.5281/zenodo.3855537.svg\r\n    :target: https://doi.org/10.5281/zenodo.3855537\r\n\r\n.. |CodeCovStatus| image:: https://codecov.io/gh/ARM-DOE/ACT/branch/main/graph/badge.svg\r\n    :target: https://codecov.io/gh/ARM-DOE/ACT\r\n\r\n.. |ARM| image:: https://img.shields.io/badge/Sponsor-ARM-blue.svg?colorA=00c1de\u0026colorB=00539c\r\n    :target: https://www.arm.gov/\r\n\r\n.. |Docs| image:: https://github.com/ARM-DOE/ACT/actions/workflows/build-docs.yml/badge.svg\r\n    :target: https://github.com/ARM-DOE/ACT/actions/workflows/build-docs.yml\r\n\r\n.. |Build| image:: https://github.com/ARM-DOE/ACT/actions/workflows/ci.yml/badge.svg\r\n    :target: https://github.com/ARM-DOE/ACT/actions/workflows/ci.yml\r\n\r\nThe Atmospheric data Community Toolkit (ACT) is an open source Python toolkit for working with atmospheric time-series datasets of varying dimensions.  The toolkit has functions for every part of the scientific process; discovery, IO, quality control, corrections, retrievals, visualization, and analysis.   It is a community platform for sharing code with the goal of reducing duplication of effort and better connecting the science community with programs such as the `Atmospheric Radiation Measurement (ARM) User Facility \u003chttp://www.arm.gov\u003e`_.  Overarching development goals will be updated on a regular basis as part of the `Roadmap \u003chttps://github.com/AdamTheisen/ACT/blob/master/guides/ACT_Roadmap_2.pdf\u003e`_  .\r\n\r\n|act|\r\n\r\n.. |act| image:: ./docs/source/act_plots.png\r\n\r\nPlease report any issues or feature requests by sumitting an `Issue \u003chttps://github.com/ARM-DOE/ACT/issues\u003e`_.  Additionally, our `discussions boards \u003chttps://github.com/ARM-DOE/ACT/discussions\u003e`_ are open for ideas, general discussions or questions, and show and tell!\r\n\r\nACT's Third Roadmap\r\n~~~~~~~~~~~~~~~~~~~\r\n\r\nTo meet the needs of the community and stakeholders, ACT will be creating a new roadmap.\r\nThis roadmap will continue a plan forward on features to improve on and to add in newer ACT\r\nversions. A part of this new roadmap is a survey from the community that will provide feedback\r\nfor the developers on priorities for newer ACT versions. If time permitting, and you are a user of ACT\r\nor are considering to use ACT the survey can be found here: `ACT Roadmap Survey \u003chttps://docs.google.com/forms/d/e/1FAIpQLScLQBH9ROP0sKMr_DvUnLKGT-K8pzc1b3zg21QqppNT_gTa2Q/viewform?usp=sf_link\u003e`_\r\nThe feedback would be much appreciated.\r\n\r\nImportant Links\r\n~~~~~~~~~~~~~~~\r\n\r\n* Documentation: https://arm-doe.github.io/ACT/\r\n* Examples: https://arm-doe.github.io/ACT/source/auto_examples/index.html\r\n* Issue Tracker: https://github.com/ARM-DOE/ACT/issues\r\n\r\nCiting\r\n~~~~~~\r\n\r\nIf you use ACT to prepare a publication, please cite the DOI listed in the badge above,\r\nwhich is updated with every version release to ensure that contributors get appropriate\r\ncredit. DOI is provided through Zenodo.\r\n\r\nDependencies\r\n~~~~~~~~~~~~\r\n\r\n* `xarray \u003chttps://xarray.pydata.org/en/stable/\u003e`_\r\n* `NumPy \u003chttps://www.numpy.org/\u003e`_\r\n* `SciPy \u003chttps://www.scipy.org/\u003e`_\r\n* `matplotlib \u003chttps://matplotlib.org/\u003e`_\r\n* `skyfield \u003chttps://rhodesmill.org/skyfield/\u003e`_\r\n* `pandas \u003chttps://pandas.pydata.org/\u003e`_\r\n* `dask \u003chttps://dask.org/\u003e`_\r\n* `Pint \u003chttps://pint.readthedocs.io/en/0.9/\u003e`_\r\n* `PyProj \u003chttps://pyproj4.github.io/pyproj/stable/\u003e`_\r\n* `Six \u003chttps://pypi.org/project/six/\u003e`_\r\n* `Requests \u003chttps://2.python-requests.org/en/master/\u003e`_\r\n* `MetPy \u003chttps://unidata.github.io/MetPy/latest/index.html\u003e`_\r\n* `ffspec \u003chttps://filesystem-spec.readthedocs.io/en/latest/\u003e`_\r\n* `lazy_loader \u003chttps://scientific-python.org/specs/spec-0001/\u003e`_\r\n* `cmweather \u003chttps://cmweather.readthedocs.io/en/latest/\u003e`_\r\n\r\nOptional Dependencies\r\n~~~~~~~~~~~~~~~~~~~~~\r\n\r\n* `MPL2NC \u003chttps://github.com/peterkuma/mpl2nc\u003e`_ Reading binary MPL data.\r\n* `Cartopy \u003chttps://scitools.org.uk/cartopy/docs/latest/\u003e`_  Mapping and geoplots\r\n* `Py-ART \u003chttps://arm-doe.github.io/pyart/\u003e`_ Reading radar files, plotting and corrections\r\n* `scikit-posthocs \u003chttps://scikit-posthocs.readthedocs.io/en/latest/\u003e`_ Using interquartile range or generalized Extreme Studentized Deviate quality control tests\r\n* `icartt \u003chttps://mbees.med.uni-augsburg.de/docs/icartt/2.0.0/\u003e`_ icartt is an ICARTT file format reader and writer for Python\r\n* `PySP2 \u003chttps://arm-doe.github.io/PySP2/\u003e`_ PySP2 is a python package for reading and processing Single Particle Soot Photometer (SP2) datasets.\r\n* `MoviePy \u003chttps://zulko.github.io/moviepy/\u003e`_ MoviePy is a python package for creating movies from images\r\n\r\nInstallation\r\n~~~~~~~~~~~~\r\n\r\nACT can be installed a few different ways. One way is to install using pip.\r\nWhen installing with pip, the ACT dependencies found in\r\n`requirements.txt \u003chttps://github.com/ARM-DOE/ACT/blob/master/requirements.txt\u003e`_ will also be installed. To install using pip::\r\n\r\n    pip install act-atmos\r\n\r\nThe easiest method for installing ACT is to use the conda packages from\r\nthe latest release. To do this you must download and install\r\n`Anaconda \u003chttps://www.anaconda.com/download/#\u003e`_ or\r\n`Miniconda \u003chttps://conda.io/miniconda.html\u003e`_.\r\nWith Anaconda or Miniconda install, it is recommended to create a new conda\r\nenvironment when using ACT or even other packages. To create a new\r\nenvironment based on the `environment.yml \u003chttps://github.com/ARM-DOE/ACT/blob/master/environment.yml\u003e`_::\r\n\r\n    conda env create -f environment.yml\r\n\r\nOr for a basic environment and downloading optional dependencies as needed::\r\n\r\n    conda create -n act_env -c conda-forge python=3.12 act-atmos\r\n\r\nBasic command in a terminal or command prompt to install the latest version of\r\nACT::\r\n\r\n    conda install -c conda-forge act-atmos\r\n\r\nTo update an older version of ACT to the latest release use::\r\n\r\n    conda update -c conda-forge act-atmos\r\n\r\nIf you are using mamba::\r\n\r\n    mamba install -c conda-forge act-atmos\r\n\r\nIf you do not wish to use Anaconda or Miniconda as a Python environment or want\r\nto use the latest, unreleased version of ACT see the section below on\r\n**Installing from source**.\r\n\r\nInstalling from Source\r\n~~~~~~~~~~~~~~~~~~~~~~\r\n\r\nInstalling ACT from source is the only way to get the latest updates and\r\nenhancement to the software that have no yet made it into a release.\r\nThe latest source code for ACT can be obtained from the GitHub repository,\r\nhttps://github.com/ARM-DOE/ACT. Either download and unpack the\r\n`zip file \u003chttps://github.com/ARM-DOE/ACT/archive/master.zip\u003e`_ of\r\nthe source code or use git to checkout the repository::\r\n\r\n    git clone https://github.com/ARM-DOE/ACT.git\r\n\r\nOnce you have the directory locally, you can install ACT in\r\ndevelopment mode using::\r\n\r\n    pip install -e .\r\n\r\nIf you want to install the repository directly, you can use::\r\n\r\n    pip install git+https://github.com/ARM-DOE/ACT.git\r\n\r\nContributing\r\n~~~~~~~~~~~~\r\n\r\nACT is an open source, community software project. Contributions to the\r\npackage are welcomed from all users.\r\n\r\nThe latest source code can be obtained with the command::\r\n\r\n    git clone https://github.com/ARM-DOE/ACT.git\r\n\r\nIf you are planning on making changes that you would like included in ACT,\r\nforking the repository is highly recommended.\r\n\r\nWe welcome contributions for all uses of ACT, provided the code can be\r\ndistributed under the BSD 3-clause license. A copy of this license is\r\navailable in the **LICENSE.txt** file in this directory. For more on\r\ncontributing, see the `contributor's guide. \u003chttps://github.com/ARM-DOE/ACT/blob/master/CONTRIBUTING.rst\u003e`_\r\n\r\nTesting\r\n~~~~~~~\r\nFor testing, we use pytest for running the unit tests and arm-test-data for\r\ntest files that are used for the unit tests. To install pytest::\r\n\r\n   $ conda install -c conda-forge pytest\r\n\r\nAnd for matplotlib image testing with pytest::\r\n\r\n   $ conda install -c conda-forge pytest-mpl\r\n\r\nTo install arm-test-data::\r\n\r\n   $ conda install -c conda-forge arm-test-data\r\n\r\nAfter installation of both pytest and arm-test-data, you can launch the test\r\nsuite from outside the source directory (you will need to have pytest\r\ninstalled and for the mpl argument need pytest-mpl)::\r\n\r\n   $ pytest --mpl --pyargs act\r\n\r\nIn-place installs can be tested using the `pytest` command from within\r\nthe source directory.\r\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Farm-doe%2Fact","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Farm-doe%2Fact","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Farm-doe%2Fact/lists"}