https://github.com/pluflou/tuneoptimizer
Bayesian optimization using a Gaussian process to tune through particle separator.
https://github.com/pluflou/tuneoptimizer
accelerator-physics epics-controls gaussian-processes machine-learning-algorithms python3 tuning
Last synced: about 2 months ago
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Bayesian optimization using a Gaussian process to tune through particle separator.
- Host: GitHub
- URL: https://github.com/pluflou/tuneoptimizer
- Owner: pluflou
- Created: 2019-03-21T18:14:47.000Z (about 6 years ago)
- Default Branch: master
- Last Pushed: 2021-07-02T17:57:51.000Z (almost 4 years ago)
- Last Synced: 2025-02-05T09:46:05.136Z (3 months ago)
- Topics: accelerator-physics, epics-controls, gaussian-processes, machine-learning-algorithms, python3, tuning
- Language: Jupyter Notebook
- Homepage:
- Size: 743 KB
- Stars: 1
- Watchers: 1
- Forks: 1
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# TuneOptimizer
Automated Bayesian optimization using Gaussian processes to tune the SECAR beamline.
An overview of the codes can be found in the manual (PDF). These codes depend on the image analysis output from the viewers along the beamline (see [viewer repo](https://github.com/pluflou/Viewer-Image-Analysis)).
The main packages needed for this and the viewer analysis:
GPy==1.9.9
GPyOpt==1.2.6
matplotlib==2.2.4
numpy==1.16.5
pyepics==3.3.3
scipy==1.2.2
skimage==0.17.2