act

Atmospheric data Community Toolkit - A python based toolkit for exploring and analyzing time series atmospheric datasets

https://github.com/arm-doe/act

Science Score: 59.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
    Found 3 DOI reference(s) in README
  • Academic publication links
    Links to: zenodo.org
  • Committers with academic emails
    10 of 23 committers (43.5%) from academic institutions
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (14.1%) to scientific vocabulary

Keywords

atmospheric-science corrections meteorological-data meteorology retrieval time-series visualization

Keywords from Contributors

projection interactive serializer cycles packaging charts network-simulation archival shellcodes hacking
Last synced: 6 months ago · JSON representation

Repository

Atmospheric data Community Toolkit - A python based toolkit for exploring and analyzing time series atmospheric datasets

Basic Info
Statistics
  • Stars: 167
  • Watchers: 10
  • Forks: 40
  • Open Issues: 10
  • Releases: 81
Topics
atmospheric-science corrections meteorological-data meteorology retrieval time-series visualization
Created almost 7 years ago · Last pushed 7 months ago
Metadata Files
Readme Contributing License Code of conduct Codeowners

README.rst

========================================
Atmospheric data Community Toolkit (ACT)
========================================

|AnacondaCloud| |CodeCovStatus| |Build| |Docs|

|CondaDownloads| |PyPiDownloads| |Zenodo| |ARM|

.. |AnacondaCloud| image:: https://anaconda.org/conda-forge/act-atmos/badges/version.svg
    :target: https://anaconda.org/conda-forge/act-atmos

.. |CondaDownloads| image:: https://anaconda.org/conda-forge/act-atmos/badges/downloads.svg
    :target: https://anaconda.org/conda-forge/act-atmos/files

.. |PyPiDownloads| image:: https://img.shields.io/pypi/dm/act_atmos.svg
    :target: https://pypi.org/project/act-atmos/

.. |Zenodo| image:: https://zenodo.org/badge/DOI/10.5281/zenodo.3855537.svg
    :target: https://doi.org/10.5281/zenodo.3855537

.. |CodeCovStatus| image:: https://codecov.io/gh/ARM-DOE/ACT/branch/main/graph/badge.svg
    :target: https://codecov.io/gh/ARM-DOE/ACT

.. |ARM| image:: https://img.shields.io/badge/Sponsor-ARM-blue.svg?colorA=00c1de&colorB=00539c
    :target: https://www.arm.gov/

.. |Docs| image:: https://github.com/ARM-DOE/ACT/actions/workflows/build-docs.yml/badge.svg
    :target: https://github.com/ARM-DOE/ACT/actions/workflows/build-docs.yml

.. |Build| image:: https://github.com/ARM-DOE/ACT/actions/workflows/ci.yml/badge.svg
    :target: https://github.com/ARM-DOE/ACT/actions/workflows/ci.yml

The 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 `_.  Overarching development goals will be updated on a regular basis as part of the `Roadmap `_  .

|act|

.. |act| image:: ./docs/source/act_plots.png

Please report any issues or feature requests by sumitting an `Issue `_.  Additionally, our `discussions boards `_ are open for ideas, general discussions or questions, and show and tell!

ACT's Third Roadmap
~~~~~~~~~~~~~~~~~~~

To meet the needs of the community and stakeholders, ACT will be creating a new roadmap.
This roadmap will continue a plan forward on features to improve on and to add in newer ACT
versions. A part of this new roadmap is a survey from the community that will provide feedback
for the developers on priorities for newer ACT versions. If time permitting, and you are a user of ACT
or are considering to use ACT the survey can be found here: `ACT Roadmap Survey `_
The feedback would be much appreciated.

Important Links
~~~~~~~~~~~~~~~

* Documentation: https://arm-doe.github.io/ACT/
* Examples: https://arm-doe.github.io/ACT/source/auto_examples/index.html
* Issue Tracker: https://github.com/ARM-DOE/ACT/issues

Citing
~~~~~~

If you use ACT to prepare a publication, please cite the DOI listed in the badge above, which is updated with every version release to ensure that contributors get appropriate credit.  DOI is provided through Zenodo.

Dependencies
~~~~~~~~~~~~

* `xarray `_
* `NumPy `_
* `SciPy `_
* `matplotlib `_
* `skyfield `_
* `pandas `_
* `dask `_
* `Pint `_
* `PyProj `_
* `Six `_
* `Requests `_
* `MetPy `_
* `ffspec `_
* `lazy_loader `_
* `cmweather `_

Optional Dependencies
~~~~~~~~~~~~~~~~~~~~~

* `MPL2NC `_ Reading binary MPL data.
* `Cartopy `_  Mapping and geoplots
* `Py-ART `_ Reading radar files, plotting and corrections
* `scikit-posthocs `_ Using interquartile range or generalized Extreme Studentized Deviate quality control tests
* `icartt `_ icartt is an ICARTT file format reader and writer for Python
* `PySP2 `_ PySP2 is a python package for reading and processing Single Particle Soot Photometer (SP2) datasets.
* `MoviePy `_ MoviePy is a python package for creating movies from images

Installation
~~~~~~~~~~~~

ACT can be installed a few different ways. One way is to install using pip.
When installing with pip, the ACT dependencies found in
`requirements.txt `_ will also be installed. To install using pip::

    pip install act-atmos

The easiest method for installing ACT is to use the conda packages from
the latest release. To do this you must download and install
`Anaconda `_ or
`Miniconda `_.
With Anaconda or Miniconda install, it is recommended to create a new conda
environment when using ACT or even other packages. To create a new
environment based on the `environment.yml `_::

    conda env create -f environment.yml

Or for a basic environment and downloading optional dependencies as needed::

    conda create -n act_env -c conda-forge python=3.12 act-atmos

Basic command in a terminal or command prompt to install the latest version of
ACT::

    conda install -c conda-forge act-atmos

To update an older version of ACT to the latest release use::

    conda update -c conda-forge act-atmos

If you are using mamba::

    mamba install -c conda-forge act-atmos

If you do not wish to use Anaconda or Miniconda as a Python environment or want
to use the latest, unreleased version of ACT see the section below on
**Installing from source**.

Installing from Source
~~~~~~~~~~~~~~~~~~~~~~

Installing ACT from source is the only way to get the latest updates and
enhancement to the software that have no yet made it into a release.
The latest source code for ACT can be obtained from the GitHub repository,
https://github.com/ARM-DOE/ACT. Either download and unpack the
`zip file `_ of
the source code or use git to checkout the repository::

    git clone https://github.com/ARM-DOE/ACT.git

Once you have the directory locally, you can install ACT in
development mode using::

    pip install -e .

If you want to install the repository directly, you can use::

    pip install git+https://github.com/ARM-DOE/ACT.git

Contributing
~~~~~~~~~~~~

ACT is an open source, community software project. Contributions to the
package are welcomed from all users.

The latest source code can be obtained with the command::

    git clone https://github.com/ARM-DOE/ACT.git

If you are planning on making changes that you would like included in ACT,
forking the repository is highly recommended.

We welcome contributions for all uses of ACT, provided the code can be
distributed under the BSD 3-clause license. A copy of this license is
available in the **LICENSE.txt** file in this directory. For more on
contributing, see the `contributor's guide. `_

Testing
~~~~~~~
For testing, we use pytest for running the unit tests and arm-test-data for
test files that are used for the unit tests. To install pytest::

   $ conda install -c conda-forge pytest

And for matplotlib image testing with pytest::

   $ conda install -c conda-forge pytest-mpl

To install arm-test-data::

   $ conda install -c conda-forge arm-test-data

After installation of both pytest and arm-test-data, you can launch the test
suite from outside the source directory (you will need to have pytest
installed and for the mpl argument need pytest-mpl)::

   $ pytest --mpl --pyargs act

In-place installs can be tested using the `pytest` command from within
the source directory.

Owner

  • Name: ARM User Facility
  • Login: ARM-DOE
  • Kind: organization

GitHub Events

Total
  • Create event: 15
  • Release event: 7
  • Issues event: 27
  • Watch event: 25
  • Delete event: 11
  • Issue comment event: 89
  • Push event: 112
  • Pull request review comment event: 25
  • Pull request event: 140
  • Pull request review event: 84
  • Fork event: 5
Last Year
  • Create event: 15
  • Release event: 7
  • Issues event: 27
  • Watch event: 25
  • Delete event: 11
  • Issue comment event: 89
  • Push event: 112
  • Pull request review comment event: 25
  • Pull request event: 140
  • Pull request review event: 84
  • Fork event: 5

Committers

Last synced: 6 months ago

All Time
  • Total Commits: 1,520
  • Total Committers: 23
  • Avg Commits per committer: 66.087
  • Development Distribution Score (DDS): 0.546
Past Year
  • Commits: 81
  • Committers: 10
  • Avg Commits per committer: 8.1
  • Development Distribution Score (DDS): 0.556
Top Committers
Name Email Commits
Adam Theisen a****n@a****v 690
Kenneth Kehoe k****e@o****u 346
Zach Sherman z****n@a****v 232
Robert Jackson r****n@a****v 79
Max Grover m****2@g****m 48
Robert Clyde Jackson r****n@c****v 35
Corey Godine c****e@o****u 22
ajsockol 4****l 20
dependabot[bot] 4****] 13
jhemedin j****r@g****m 8
Joe O'Brien o****j@a****v 8
Jenni Kyrouac j****c@a****v 3
Israel Silber 5****r 2
Maxwell Levin 2****n 2
Robert Jackson r****n@e****v 2
Robert Jackson r****n@c****v 2
Alyssa Sockol a****0@g****m 2
Chirag H Shah 3****h 1
Leah D Gibson 6****n 1
Max Levin m****n 1
Robert Jackson r****n@R****l 1
Jason Hemedinger j****r@J****l 1
dennyh-ssec 1****c 1
Committer Domains (Top 20 + Academic)

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 99
  • Total pull requests: 403
  • Average time to close issues: 3 months
  • Average time to close pull requests: 3 days
  • Total issue authors: 17
  • Total pull request authors: 13
  • Average comments per issue: 2.97
  • Average comments per pull request: 1.63
  • Merged pull requests: 364
  • Bot issues: 0
  • Bot pull requests: 27
Past Year
  • Issues: 22
  • Pull requests: 149
  • Average time to close issues: 11 days
  • Average time to close pull requests: 3 days
  • Issue authors: 7
  • Pull request authors: 9
  • Average comments per issue: 1.09
  • Average comments per pull request: 0.81
  • Merged pull requests: 133
  • Bot issues: 0
  • Bot pull requests: 17
Top Authors
Issue Authors
  • AdamTheisen (40)
  • kenkehoe (13)
  • mgrover1 (11)
  • zssherman (10)
  • jrobrien91 (7)
  • cgodine (3)
  • caghili (2)
  • isilber (2)
  • Aifang-Zhou (2)
  • mtuftedal (2)
  • sophiaanr (1)
  • dennyh-ssec (1)
  • rcjackson (1)
  • wxwolff (1)
  • sgupta92 (1)
Pull Request Authors
  • zssherman (169)
  • AdamTheisen (107)
  • kenkehoe (49)
  • dependabot[bot] (27)
  • mgrover1 (24)
  • rcjackson (8)
  • jrobrien91 (6)
  • isilber (4)
  • ajsockol (2)
  • leahgibson (2)
  • maxwelllevin (2)
  • shahchiragh (2)
  • cgodine (1)
Top Labels
Issue Labels
enhancement (31) V2.0.0 (12) bug (9) good first issue (6) High Priority (4) question (1) blog-post (1) dependencies (1)
Pull Request Labels
dependencies (27) V2.0.0 (7) github_actions (1)

Packages

  • Total packages: 4
  • Total downloads:
    • pypi 5,270 last-month
  • Total docker downloads: 1,095
  • Total dependent packages: 5
    (may contain duplicates)
  • Total dependent repositories: 20
    (may contain duplicates)
  • Total versions: 269
  • Total maintainers: 3
pypi.org: act-atmos

Package for working with atmospheric time series datasets

  • Versions: 79
  • Dependent Packages: 3
  • Dependent Repositories: 16
  • Downloads: 5,270 Last month
  • Docker Downloads: 1,095
Rankings
Dependent packages count: 2.4%
Docker downloads count: 3.3%
Dependent repos count: 3.6%
Average: 4.9%
Downloads: 6.4%
Stargazers count: 6.5%
Forks count: 7.1%
Last synced: 6 months ago
proxy.golang.org: github.com/ARM-DOE/ACT
  • Versions: 80
  • Dependent Packages: 0
  • Dependent Repositories: 0
Rankings
Dependent packages count: 5.4%
Average: 5.6%
Dependent repos count: 5.8%
Last synced: 6 months ago
proxy.golang.org: github.com/arm-doe/act
  • Versions: 80
  • Dependent Packages: 0
  • Dependent Repositories: 0
Rankings
Dependent packages count: 5.4%
Average: 5.6%
Dependent repos count: 5.8%
Last synced: 6 months ago
conda-forge.org: act-atmos

The Atmospheric data Community Toolkit (ACT) is an open source Python toolkit for working with atmospheric time-series datasets of varying dimensions. The toolkit is meant to have functions for every part of the scientific process; discovery, IO, quality control, corrections, retrievals, visualization, and analysis. It is meant to be 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.

  • Versions: 30
  • Dependent Packages: 2
  • Dependent Repositories: 4
Rankings
Dependent repos count: 16.2%
Dependent packages count: 19.6%
Average: 25.1%
Forks count: 31.5%
Stargazers count: 32.9%
Last synced: 6 months ago

Dependencies

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