dspeed
Fast Digital Signal Processing for particle detector signals in Python
Science Score: 67.0%
This score indicates how likely this project is to be science-related based on various indicators:
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✓CITATION.cff file
Found CITATION.cff file -
✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
✓DOI references
Found 5 DOI reference(s) in README -
✓Academic publication links
Links to: zenodo.org -
○Academic email domains
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (13.5%) to scientific vocabulary
Keywords
Repository
Fast Digital Signal Processing for particle detector signals in Python
Basic Info
- Host: GitHub
- Owner: legend-exp
- License: gpl-3.0
- Language: Python
- Default Branch: main
- Homepage: https://dspeed.readthedocs.io
- Size: 1.19 MB
Statistics
- Stars: 3
- Watchers: 5
- Forks: 16
- Open Issues: 19
- Releases: 23
Topics
Metadata Files
README.md
DSPeed
```
|| ____ _____ ____ __ `,_
|| / __ \/ ___/ / __ \ ___ ___ ____/ / | `-_
[] || [] [] [] [] / / / /__ \ / // // _ \ / _ \ / _ / [] [] [] '------,_
====||===============/ /_/ /___/ // ____// __// __// /_/ /======================--,_
|| /_____//____//_/ \___/ \___/ \__,_/--,
|| ________ ________ )
\____||___/.-. .-.\______________________________________________________/.-. .-.\______,,--'
==========='-'=='-'========================================================'-'=='-'=============
``
DSPeed (pronounced dee-ess-speed) is a python-based package that performs bulk, high-performance digital signal processing (DSP) of time-series data such as digitized waveforms. This package is part of the pygama scientific computing suite.
DSPeed enables the user to define an arbitrary chain of vectorized signal processing routines that can be applied in bulk to waveforms and other data provided using the LH5-format. These routines can include numpy ufuncs, custom functions accelerated with numba, or other arbitrary functions. DSPeed will carefully manage file I/O to optimize memory usage and performance. Processing chains are defined using highly portable JSON files that can be applied to data from multiple digitizers.
See the online documentation for more information.
If you are using this software, consider citing!
Owner
- Name: LEGEND Experiment
- Login: legend-exp
- Kind: organization
- Website: http://legend-exp.org
- Repositories: 38
- Profile: https://github.com/legend-exp
Citation (CITATION.cff)
cff-version: 1.2.0
title: dspeed
doi: https://doi.org/10.5281/zenodo.10684779
date-released: 2024-02-20
message: "If you use this software, please cite it as below."
authors:
- family-names: Guinn
given-names: Ian
orcid: https://orcid.org/0000-0002-2424-3272
- family-names: Pertoldi
given-names: Luigi
orcid: https://orcid.org/0000-0002-0467-2571
- family-names: Detwiler
given-names: Jason
orcid: https://orcid.org/0000-0002-9050-4610
- family-names: Borden
given-names: Sam
orcid: https://orcid.org/0009-0003-2539-4333
- family-names: Shanks
given-names: Ben
email: benjamin.shanks@gmail.com
- family-names: Wiseman
given-names: Clint
orcid: https://orcid.org/0000-0002-4232-1326
- family-names: Mathew
given-names: Tim
email: tmathew@uoregon.edu
- family-names: D'Andrea
given-names: Valerio
orcid: https://orcid.org/0000-0003-2037-4133
- family-names: Krause
given-names: Patrick
orcid: https://orcid.org/0000-0002-9603-7865
- family-names: Marshall
given-names: George
orcid: https://orcid.org/0000-0002-5470-5132
- family-names: Agostini
given-names: Matteo
orcid: https://orcid.org/0000-0003-1151-5301
- family-names: Othman
given-names: Gulden
orcid: https://orcid.org/0009-0008-9653-3499
- family-names: León
given-names: Esteban
orcid: https://orcid.org/0000-0002-0073-5512
GitHub Events
Total
- Create event: 19
- Issues event: 30
- Release event: 9
- Watch event: 1
- Delete event: 9
- Issue comment event: 63
- Push event: 35
- Pull request review event: 2
- Pull request review comment event: 2
- Pull request event: 67
- Fork event: 1
Last Year
- Create event: 19
- Issues event: 30
- Release event: 9
- Watch event: 1
- Delete event: 9
- Issue comment event: 63
- Push event: 35
- Pull request review event: 2
- Pull request review comment event: 2
- Pull request event: 67
- Fork event: 1
Issues and Pull Requests
Last synced: 6 months ago
All Time
- Total issues: 33
- Total pull requests: 71
- Average time to close issues: 5 months
- Average time to close pull requests: 14 days
- Total issue authors: 7
- Total pull request authors: 11
- Average comments per issue: 0.91
- Average comments per pull request: 0.89
- Merged pull requests: 46
- Bot issues: 0
- Bot pull requests: 15
Past Year
- Issues: 18
- Pull requests: 31
- Average time to close issues: 2 months
- Average time to close pull requests: 15 days
- Issue authors: 4
- Pull request authors: 7
- Average comments per issue: 0.61
- Average comments per pull request: 0.87
- Merged pull requests: 14
- Bot issues: 0
- Bot pull requests: 5
Top Authors
Issue Authors
- gipert (15)
- ggmarshall (10)
- iguinn (3)
- cVogl97 (2)
- patgo25 (1)
- Jita22 (1)
- matthewfeickert (1)
Pull Request Authors
- iguinn (29)
- ggmarshall (14)
- dependabot[bot] (14)
- gipert (7)
- pre-commit-ci[bot] (5)
- SamuelBorden (3)
- esleon97 (2)
- schwarzmario (2)
- Beatricecrudele (2)
- Gl-duran (1)
- tdixon97 (1)
- patgo25 (1)
Top Labels
Issue Labels
Pull Request Labels
Packages
- Total packages: 1
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Total downloads:
- pypi 2,983 last-month
- Total dependent packages: 2
- Total dependent repositories: 0
- Total versions: 24
- Total maintainers: 1
pypi.org: dspeed
Fast Digital Signal Processing for particle detectors in Python
- Homepage: https://github.com/legend-exp/dspeed
- Documentation: https://dspeed.readthedocs.io/
- License: GNU General Public License v3 (GPLv3)
-
Latest release: 1.8.1
published 7 months ago
Rankings
Maintainers (1)
Dependencies
- actions/checkout v3 composite
- actions/download-artifact v3 composite
- actions/upload-artifact v3 composite
- pypa/gh-action-pypi-publish v1.8.6 composite
- actions/checkout v2 composite
- actions/setup-python v2 composite
- codecov/codecov-action v3 composite