sasktran2

The next generation SASKTRAN radiative transfer model

https://github.com/usask-arg/sasktran2

Science Score: 39.0%

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    Found codemeta.json file
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  • DOI references
    Found 4 DOI reference(s) in README
  • Academic publication links
  • Committers with academic emails
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  • Scientific vocabulary similarity
    Low similarity (13.9%) to scientific vocabulary

Keywords from Contributors

interpretability mesh standards energy-system-model parallel distributed yolov5s animations energy-system pypi
Last synced: 10 months ago · JSON representation

Repository

The next generation SASKTRAN radiative transfer model

Basic Info
  • Host: GitHub
  • Owner: usask-arg
  • License: mit
  • Language: C++
  • Default Branch: main
  • Size: 9.43 MB
Statistics
  • Stars: 4
  • Watchers: 0
  • Forks: 6
  • Open Issues: 5
  • Releases: 28
Created about 3 years ago · Last pushed 11 months ago
Metadata Files
Readme License

README.md

SASKTRAN

Anaconda-Server Badge Available on pypi Documentation Status pre-commit.ci status

The SASKTRAN radiative transfer framework is a radiative transfer tool developed at the University of Saskatchewan. Originally designed for use with the OSIRIS instrument (https://research-groups.usask.ca/osiris/) it has since evolved to be applicable to a large variety of applications. SASKTRAN is a full framework and not just a radiative transfer model, as such it contains databases or interfaces to standard climatologies and species optical properties.

SASKTRAN2 is a full re-implementation of the original SASKTRAN framework with large computational efficiency improvements, full linearizations of atmospheric input properties, and an improved Python interface.

Installation

The preferred method to install SASKTRAN2 is through the pre-compiled Conda package

conda install -c conda-forge sasktran2 these packages are made available for Python versions 3.10, 3.11, 3.12, 3.13 on Windows/Linux/Mac platforms. For Mac, both x86_64 and Arm packages are available. For Linux, arm/ppc are also supported.

Wheels are also built for the same platforms and can be installed through, pip install sasktran2

SASKTRAN2 can also be built directly from source, pip install .

When building from source it is required that a Blas/LAPACK implementation is findable by CMake.

Usage

Documentation can be found at https://sasktran2.readthedocs.io/

License

SASKTRAN2 is made available under the MIT license.

Acknowledgement

We request that users of the model contact the authors before publishing results using SASKTRAN, and that the following publications are acknowledged:

Zawada, D. J., Dueck, S. R., Rieger, L. A., Bourassa, A. E., Lloyd, N. D., and Degenstein, D. A.: High-resolution and Monte Carlo additions to the SASKTRAN radiative transfer model, Atmos. Meas. Tech., 8, 2609-2623, https://doi.org/10.5194/amt-8-2609-2015, 2015.

Bourassa, A. E., Degenstein, D. A., and Llewellyn, E. J.: SASKTRAN: A Spherical Geometry Radiative Transfer Code for Efficient Estimation of Limb Scattered Sunlight, J Quant Spectrosc Radiat Trans, Volume 109, Issue 1, 52-73, https://doi.org/10.1016/j.jqsrt.2007.07.007, 2008.

Owner

  • Name: usask-arg
  • Login: usask-arg
  • Kind: organization

GitHub Events

Total
  • Create event: 41
  • Issues event: 1
  • Release event: 18
  • Watch event: 4
  • Delete event: 21
  • Issue comment event: 12
  • Push event: 74
  • Pull request review event: 2
  • Pull request review comment event: 4
  • Gollum event: 1
  • Pull request event: 145
Last Year
  • Create event: 41
  • Issues event: 1
  • Release event: 18
  • Watch event: 4
  • Delete event: 21
  • Issue comment event: 12
  • Push event: 74
  • Pull request review event: 2
  • Pull request review comment event: 4
  • Gollum event: 1
  • Pull request event: 145

Committers

Last synced: 11 months ago

All Time
  • Total Commits: 178
  • Total Committers: 8
  • Avg Commits per committer: 22.25
  • Development Distribution Score (DDS): 0.258
Past Year
  • Commits: 89
  • Committers: 6
  • Avg Commits per committer: 14.833
  • Development Distribution Score (DDS): 0.382
Top Committers
Name Email Commits
Daniel Zawada d****a@u****a 132
dependabot[bot] 4****] 27
github-actions[bot] 4****] 7
lukasfehr f****s@g****m 4
TaranWarnock T****k 4
cremai 7****i 2
pre-commit-ci[bot] 6****] 1
Adam Bourassa 1****2 1
Committer Domains (Top 20 + Academic)

Issues and Pull Requests

Last synced: 10 months ago

All Time
  • Total issues: 5
  • Total pull requests: 138
  • Average time to close issues: 6 months
  • Average time to close pull requests: 7 days
  • Total issue authors: 1
  • Total pull request authors: 8
  • Average comments per issue: 0.0
  • Average comments per pull request: 0.09
  • Merged pull requests: 102
  • Bot issues: 0
  • Bot pull requests: 44
Past Year
  • Issues: 1
  • Pull requests: 82
  • Average time to close issues: 29 days
  • Average time to close pull requests: 3 days
  • Issue authors: 1
  • Pull request authors: 5
  • Average comments per issue: 0.0
  • Average comments per pull request: 0.05
  • Merged pull requests: 64
  • Bot issues: 0
  • Bot pull requests: 30
Top Authors
Issue Authors
  • dannyzed (5)
Pull Request Authors
  • dannyzed (85)
  • dependabot[bot] (35)
  • github-actions[bot] (8)
  • lukasfehr (4)
  • cremai (2)
  • TaranWarnock (2)
  • rileysly (1)
  • pre-commit-ci[bot] (1)
Top Labels
Issue Labels
enhancement (2)
Pull Request Labels
dependencies (35) github_actions (10) run-benchmark (8) stubs (8) build-perf-book (1)