pyglotaran
A Python library for Global and Target Analysis of time-resolved spectroscopy data
Science Score: 59.0%
This score indicates how likely this project is to be science-related based on various indicators:
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○CITATION.cff file
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✓codemeta.json file
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✓.zenodo.json file
Found .zenodo.json file -
✓DOI references
Found 10 DOI reference(s) in README -
✓Academic publication links
Links to: zenodo.org -
✓Committers with academic emails
4 of 22 committers (18.2%) from academic institutions -
○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (15.9%) to scientific vocabulary
Keywords
Keywords from Contributors
Repository
A Python library for Global and Target Analysis of time-resolved spectroscopy data
Basic Info
Statistics
- Stars: 57
- Watchers: 4
- Forks: 18
- Open Issues: 11
- Releases: 16
Topics
Metadata Files
README.md
pyglotaran
A framework written in Python for global and target analysis; commonly used for the analysis of time-resolved spectroscopy measurements in the study of energy transfer pathways in photosynthesis, or the characterization of energy transfer (in-)efficiencies in photovoltaics.
The Future of Global and Target Analysis
A scientific publication titled "pyglotaran: a lego-like Python framework for global and target analysis of time-resolved spectra" (DOI: 10.1007/s43630-023-00460-y) covers aspects of the architecture and the design of the software while illustrating its flexibility as an analysis tool through some exciting case studies. This publication, along with other pyglotaran-publications demonstrates why we believe this framework is the future of global and target analysis.
Usage of pyglotaran
If you just want to get started analyzing your data, jump straight to the getting started guide that is part of our documentation.
Afterwards, you may also want to have a look at our comprehensive collection of real-world examples in the pyglotaran-examples repository. There most like is an example that aligns well with your use case.
For state of the art usage of this framework you may want to check out the list of pyglotaran-publications.
Example analysis results
Results of a target analysis of Photosystem I (see study_florescence in the examples.)
Plot created with the plot_overview function of the pyglotaran-extras package.
Notice: This is (still) an early access release, please refer to the usage notice prior to committing to use pyglotaran to avoid surprises down the line.
Glotaran legacy
The pyglotaran package derives its name from the Glotaran software package (now called glotaran-legacy), first released in 2011 and described in a highly-cited publication in the Journal of Statistical Software, under the title Glotaran: A Java-Based Graphical User Interface for the R Package TIMP (DOI: 10.18637/jss.v049.i03).
The pyglotaran framework can be considered the spiritual successor of the glotaran-legacy software and has the backing of many of its original creators.
Community Support
For questions / suggestion please reach out to us via:
Credits
The credits can be found in the documentation authors section
Owner
- Name: GloTarAn
- Login: glotaran
- Kind: organization
- Email: github@glotaran.org
- Location: Amsterdam
- Website: http://www.glotaran.org
- Twitter: glotaran
- Repositories: 28
- Profile: https://github.com/glotaran
Modeling frameworks for global and target analysis (GloTarAn)
GitHub Events
Total
- Issues event: 5
- Watch event: 1
- Delete event: 36
- Issue comment event: 180
- Push event: 39
- Pull request review event: 31
- Pull request event: 69
- Create event: 36
Last Year
- Issues event: 5
- Watch event: 1
- Delete event: 36
- Issue comment event: 180
- Push event: 39
- Pull request review event: 31
- Pull request event: 69
- Create event: 36
Committers
Last synced: almost 3 years ago
Top Committers
| Name | Commits | |
|---|---|---|
| Joern Weissenborn | j****n@g****m | 488 |
| Sebastian Weigand | s****y@g****m | 424 |
| Joris Snellenburg | j****g@v****l | 119 |
| Joris Snellenburg | j****l@u****m | 117 |
| dependabot[bot] | 4****]@u****m | 109 |
| Joern Weissenborn | j****n@v****l | 66 |
| pre-commit-ci[bot] | 6****]@u****m | 29 |
| dependabot-preview[bot] | 2****]@u****m | 24 |
| pyup-bot | g****t@p****o | 13 |
| Stefan Schütz | y****n@g****m | 12 |
| Joern Weissenborn | j****n@l****n | 5 |
| s-weigand | s****d@u****m | 4 |
| Joris Snellenburg | j****g@i****m | 3 |
| Joris Snellenburg | j****s@d****n | 3 |
| ism200 | i****o@f****l | 3 |
| sourcery-ai[bot] | 5****]@u****m | 2 |
| Joern Weissenborn | j****n@w****e | 2 |
| Ivo van Stokkum | 1****0@u****m | 1 |
| Patrick Hätti | 4****0@u****m | 1 |
| Patrick Hätti | 9****i@u****m | 1 |
| lgtm-com[bot] | 4****]@u****m | 1 |
| s-weigand | 4****]@u****m | 1 |
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: 6 months ago
All Time
- Total issues: 71
- Total pull requests: 427
- Average time to close issues: almost 2 years
- Average time to close pull requests: 16 days
- Total issue authors: 8
- Total pull request authors: 9
- Average comments per issue: 2.86
- Average comments per pull request: 4.21
- Merged pull requests: 213
- Bot issues: 0
- Bot pull requests: 299
Past Year
- Issues: 1
- Pull requests: 76
- Average time to close issues: N/A
- Average time to close pull requests: 25 days
- Issue authors: 1
- Pull request authors: 5
- Average comments per issue: 0.0
- Average comments per pull request: 3.41
- Merged pull requests: 3
- Bot issues: 0
- Bot pull requests: 72
Top Authors
Issue Authors
- jsnel (33)
- s-weigand (29)
- joernweissenborn (7)
- luccablois (1)
- ism200 (1)
- SanjoyPatraIISc (1)
- ankit7540 (1)
- anmolbhatia05 (1)
Pull Request Authors
- dependabot[bot] (348)
- s-weigand (100)
- jsnel (38)
- pre-commit-ci[bot] (33)
- joernweissenborn (16)
- sourcery-ai[bot] (9)
- snyk-bot (2)
- ism200 (2)
- gdrosos (1)
Top Labels
Issue Labels
Pull Request Labels
Packages
- Total packages: 4
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Total downloads:
- pypi 1,553 last-month
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Total dependent packages: 2
(may contain duplicates) -
Total dependent repositories: 7
(may contain duplicates) - Total versions: 44
- Total maintainers: 2
pypi.org: pyglotaran
The Glotaran fitting engine.
- Homepage: https://github.com/glotaran/pyglotaran
- Documentation: https://pyglotaran.readthedocs.io
- License: LGPL-3.0
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Latest release: 0.7.3
published over 1 year ago
Rankings
pypi.org: glotaran
The Glotaran fitting engine.
- Homepage: https://github.com/glotaran/pyglotaran
- Documentation: https://glotaran.readthedocs.io
- License: GPLv3
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Latest release: 0.1.0
published over 5 years ago
Rankings
pypi.org: pyglotaran-alias
Convenience module, which allows to use pyglotaran as alias in the CLI and imports
- Homepage: https://github.com/glotaran/pyglotaran-alias
- Documentation: https://pyglotaran-alias.readthedocs.io/
- License: Apache-2.0
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Latest release: 0.0.5
published almost 5 years ago
Rankings
conda-forge.org: pyglotaran
Pyglotaran is a python library for global analysis of time-resolved spectroscopy data. It is designed to provide a state of the art modeling toolbox to researchers, in a user-friendly manner. Its features are: - user-friendly modeling with a custom YAML (*.yml) based modeling language - parameter optimization using variable projection and non-negative least-squares algorithms - easy to extend modeling framework - battle-hardened model and algorithms for fluorescence dynamics - build upon and fully integrated in the standard Python science stack (NumPy, SciPy, Jupyter) pyglotaran is ideal for researchers and scientists who require a powerful, yet user-friendly tool for analyzing complex systems, from time-resolved spectroscopy to broader applications in scientific modeling.
- Homepage: https://github.com/glotaran/pyglotaran
- License: LGPL-3.0-only
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Latest release: 0.6.0
published over 3 years ago
Rankings
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