https://github.com/python-accelerator-middle-layer/pyaml

Python accelerator middle layer for charged particle accelerator control, tuning and development
https://github.com/python-accelerator-middle-layer/pyaml

digital-twin operation synchrotron tuning

Last synced: 5 months ago
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Python accelerator middle layer for charged particle accelerator control, tuning and development

• Host: GitHub
• URL: https://github.com/python-accelerator-middle-layer/pyaml
• Owner: python-accelerator-middle-layer
• License: apache-2.0
• Created: 2024-11-22T12:25:34.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2026-01-19T18:57:38.000Z (6 months ago)
• Last Synced: 2026-01-19T19:33:51.758Z (6 months ago)
• Topics: digital-twin, operation, synchrotron, tuning
• Language: Python
• Homepage: https://pyaml.readthedocs.io/en/latest/index.html
• Size: 22.8 MB
• Stars: 6
• Watchers: 9
• Forks: 0
• Open Issues: 15
• Metadata Files:
  • Readme: README.md
  • Contributing: CONTRIBUTING.md
  • License: LICENSE

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README

          
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# Python Accelerator Middle Layer

Python Accelerator Middle Layer (pyAML) is a joint technology platform for design, commissioning and operation of particle accelerators.

The code is still under development. The features include among others:

- A control system agnostic interface to interact with the accelerator.

- Same interface to different backends: live accelerator, virtual accelerator and simulator.

- Machine independence allowing configuration of different type of accelerators and facility specific naming conventions.

- Unit conversions.

- Automatic generation of metadata and standardized format for measurement data.

- A set of standard applications and a framework for developing new applications.

**This repository is for the core of pyAML.** It is control system independent and provides the core functionality of pyAML. It is intended to be used together with a package that implements the control system specific interface.

Available packages for bindings:

TANGO: [tango-pyaml](https://github.com/python-accelerator-middle-layer/tango-pyaml)

TANGO or EPICS: [pyaml-cs-oa](https://github.com/python-accelerator-middle-layer/pyaml-cs-oa)

#### Installation

Installation instructions for both user and development installation can be found in the [documentation](https://pyaml.readthedocs.io/en/latest/?badge=latest).

#### Documentation

The documentation is available [here](https://pyaml.readthedocs.io/en/latest/?badge=latest).

In the documentation there are both examples and Jupyter notebooks available for how to use the package.