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TECA

TECA, theToolkit for Extreme Climate Analysis, contains a collection of climate anlysis algorithms targetted at extreme event detection and analysis.

https://github.com/LBL-EESA/TECA

Science Score: 67.0%

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
    5 of 9 committers (55.6%) from academic institutions
  • ✓
    Institutional organization owner
    Organization lbl-eesa has institutional domain (eesa.lbl.gov)
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (14.8%) to scientific vocabulary
Last synced: 6 months ago · JSON representation

Repository

TECA, theToolkit for Extreme Climate Analysis, contains a collection of climate anlysis algorithms targetted at extreme event detection and analysis.

Basic Info
  • Host: GitHub
  • Owner: LBL-EESA
  • License: other
  • Language: C++
  • Default Branch: develop
  • Size: 40.8 MB
Statistics
  • Stars: 61
  • Watchers: 4
  • Forks: 22
  • Open Issues: 179
  • Releases: 5
Created about 10 years ago · Last pushed 7 months ago
Metadata Files
Readme License

README.md

PyPI version DOI

The Toolkit for Extreme Climate Analysis

TECA is a collection of climate analysis algorithms geared toward extreme event detection and tracking implemented in a scalable parallel framework. The code has been successfully deployed and run at massive scales on current DOE supercomputers. TECA's core is written in modern C++ and exploits MPI + X parallelism where X is one of threads, OpenMP, or GPUs. The framework supports a number of parallel design patterns including distributed data parallelism and map-reduce. While modern C++ delivers the highest performance, Python bindings make the code approachable and easy to use.

Documentation

The TECA User's Guide is the authorotative source for documentation on topics such as installing TECA, running TECA's command line applications, and Python development. The TECA source code is documented on our Doxygen site.

Tutorials

The TECA tutorials subversion repository contains slides from previous tutorials.

Examples

The TECA examples repository contains batch scripts and codes illustrating the use of TECA at scale.

Python

The TECA Python package is available on PyPi or by installing from sources. For more information see the TECA User's Guide sections on installing TECA and Python development.

CI and Testing

For the latest regression suite results see the TECA CDash project site.

Copyright Notice

TECA, Copyright (c) 2015, The Regents of the University of California, through Lawrence Berkeley National Laboratory (subject to receipt of any required approvals from the U.S. Dept. of Energy). All rights reserved.

If you have questions about your rights to use or distribute this software, please contact Berkeley Lab's Innovation & Partnerships Office at IPO@lbl.gov.

NOTICE. This software is owned by the U.S. Department of Energy. As such, the U.S. Government has been granted for itself and others acting on its behalf a paid-up, nonexclusive, irrevocable, worldwide license in the Software to reproduce, prepare derivative works, and perform publicly and display publicly. Beginning five (5) years after the date permission to assert copyright is obtained from the U.S. Department of Energy, and subject to any subsequent five (5) year renewals, the U.S. Government is granted for itself and others acting on its behalf a paid-up, nonexclusive, irrevocable, worldwide license in the Software to reproduce, prepare derivative works, distribute copies to the public, perform publicly and display publicly, and to permit others to do so.

Owner

  • Name: LBL-EESA
  • Login: LBL-EESA
  • Kind: organization
  • Location: Berkeley, CA

Lawrence Berkeley National Laboratory's Earth and Environmental Sciences Area

GitHub Events

Total
  • Watch event: 5
  • Delete event: 1
  • Issue comment event: 2
  • Push event: 101
  • Pull request event: 7
  • Pull request review event: 37
  • Pull request review comment event: 34
  • Fork event: 1
  • Create event: 4
Last Year
  • Watch event: 5
  • Delete event: 1
  • Issue comment event: 2
  • Push event: 101
  • Pull request event: 7
  • Pull request review event: 37
  • Pull request review comment event: 34
  • Fork event: 1
  • Create event: 4

Committers

Last synced: 7 months ago

All Time
  • Total Commits: 1,865
  • Total Committers: 9
  • Avg Commits per committer: 207.222
  • Development Distribution Score (DDS): 0.097
Past Year
  • Commits: 18
  • Committers: 3
  • Avg Commits per committer: 6.0
  • Development Distribution Score (DDS): 0.389
Top Committers
Name Email Commits
Burlen Loring b****g@l****v 1,684
elbashandy a****y@g****m 69
Travis A. O'Brien o****a@i****u 43
Amanda S. Dufek a****k@g****m 39
Jeffrey Johnson j****n@l****v 12
Kitware Robot k****t@k****m 11
Harinarayan Krishnan h****n@l****v 5
noel n****n@l****v 1
Jeffrey Johnson j****t@g****m 1
Committer Domains (Top 20 + Academic)
lbl.gov: 4 kitware.com: 1 iu.edu: 1

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 426
  • Total pull requests: 385
  • Average time to close issues: 8 months
  • Average time to close pull requests: about 1 month
  • Total issue authors: 10
  • Total pull request authors: 7
  • Average comments per issue: 1.75
  • Average comments per pull request: 1.74
  • Merged pull requests: 313
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 11
  • Average time to close issues: N/A
  • Average time to close pull requests: about 1 month
  • Issue authors: 0
  • Pull request authors: 3
  • Average comments per issue: 0
  • Average comments per pull request: 0.27
  • Merged pull requests: 4
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • burlen (301)
  • taobrienlbl (93)
  • elbashandy (13)
  • jeff-cohere (5)
  • bedassa (4)
  • venugopalrt (3)
  • dchandan (1)
  • Steve-JJ (1)
  • Hwenshuo (1)
  • lpassarella (1)
Pull Request Authors
  • burlen (271)
  • elbashandy (50)
  • taobrienlbl (31)
  • amandasd (16)
  • jeff-cohere (10)
  • ghweber (8)
  • HarinarayanKrishnan (3)
Top Labels
Issue Labels
2_medium_priority (138) feature (68) 1_high_priority (58) 3_low_priority (55) bug (53) documentation (38) testing (38) I/O (28) python (18) temporal reductions (8) deployment (6) build (6) data model (5) GPUization (4) duplicate (4) wontfix (3) good first issue (3) discussion (3) user engagement (2) TECA_superbuild (2) run (1)
Pull Request Labels
feature (25) bug (15) testing (7) documentation (3) 1_high_priority (2) 2_medium_priority (1)

Packages

  • Total packages: 1
  • Total downloads:
    • pypi 20 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 1
  • Total versions: 7
  • Total maintainers: 2
pypi.org: teca

The Toolkit for Extreme Climate Analysis

  • Versions: 7
  • Dependent Packages: 0
  • Dependent Repositories: 1
  • Downloads: 20 Last month
Rankings
Dependent packages count: 7.3%
Forks count: 8.3%
Stargazers count: 9.3%
Average: 19.9%
Dependent repos count: 22.1%
Downloads: 52.6%
Maintainers (2)
bloring obrientaiu
Last synced: 6 months ago

Dependencies

doc/rtd/requirements.txt pypi
  • breathe *
  • sphinx <7
  • sphinxcontrib-bibtex *
setup.py pypi
  • mpi4py *
docker/teca_cpu_debug/Dockerfile docker
  • obrientaiu/teca_prereqs cpu build
docker/teca_gpu_debug/Dockerfile docker
  • obrientaiu/teca_prereqs gpu build
docker/teca_prereqs_cpu/Dockerfile docker
  • ubuntu 24.04 build
docker/teca_prereqs_gpu/Dockerfile docker
  • obrientaiu/teca_prereqs cpu build