Published January 18, 2022
| Version v0.7.4
Software
Open
GammaLearn
Authors/Creators
- 1. Univ. Savoie Mont-Blanc, CNRS, LAPP
Description
GammaLearn is a collaborative project to apply deep learning to the analysis of low-level Imaging Atmospheric Cherenkov Telescopes such as CTA.
It provides a framework to easily train and apply models from a configuration file.
Learn more at https://purl.org/gammalearn
Notes
GammaLearn Release v0.7.4
The main changes in this release concern the automatization of the releases: publication to Zenodo, generation of docker containers and pypi packages.
Changelog:
- cleaner install and auto upload to pypi
- Package nets and experiments example settings as package data
- Include GammaPhysNet in GammaLearn
- allow gammalearn --version
- Autoencoders in glearn
- Fix calls to .item()
- Replace GpuStatsMonitor with DeviceStatsMonitor and accelerator with strategy
- Zenodo automated publication of releases
- using setuptools_scm to determine version from git tag and distance to tag
- Documentation
- Docker containers
- Harmonise GammaLearn headline
- Add metadata as codemeta file
- fix classification metrics import
Files
codemeta.json
Files
(2.0 MB)
| Name | Size | Download all |
|---|---|---|
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md5:3f549932fafa58ebabc99fd8680c363a
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3.1 kB | Preview Download |
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md5:af0fbb07baa4e4d64843a1e9b97ca3e4
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2.0 MB | Preview Download |
Additional details
Related works
- Is derived from
- Software: https://gitlab.in2p3.fr/gammalearn/gammalearn (URL)