Skip to main content

An accelerator physics tools package for the OMC team at CERN.

Project description

omc3 logo 3

Tests GitHub last commit GitHub release DOI

This is the python-tool package of the Optics Measurements and Corrections team (OMC) at CERN.

Most of the codes are generic and not limited to CERN accelerators, and the package can easily be used for your favorite circular accelerator. To see how to adapt this for your machine, see our documentation, Model section. To contribute, see our guidelines on the OMC website.

Documentation

Installing

The package is deployed on PyPI and can easily be installed via pip:

python -m pip install omc3

For development purposes, we recommend creating a new virtual environment and installing from VCS in editable mode with all extra dependencies (cern for packages only available in the CERN GPN, test for pytest and relevant plugins, and doc for packages needed to build documentation).

git clone https://github.com/pylhc/omc3
python -m pip install --editable "omc3[all]"

Functionality

Codes can then be run with either python -m omc3.SCRIPT --FLAG ARGUMENT or calling the .py file directly.

Main Scripts

Main scripts to be executed lie in the /omc3 directory. These include:

  • hole_in_one.py to perform frequency analysis on turn by turn BPM data and infer optics (and more) for a given accelerator.
  • kmod_importer.py to average, import and calculate lumi-imbalace K-modulation results.
  • knob_extractor.py to extract from NXCALS the value of given knobs in the machine at a given time.
  • model_creator.py to generate optics models required for optics analysis.
  • global_correction.py to calculate corrections from measurement files.
  • response_creator.py to provide correction response files.
  • tbt_converter.py to convert different turn by turn data types to SDDS, potentially adding noise.
  • amplitude_detuning_analysis.py to perform amp. det. analysis on optics data with tune correction.
  • madx_wrapper.py to start a MAD-X run with a file or string as input.
Plotting Scripts

Plotting scripts for analysis outputs can be found in /omc3/plotting:

  • plot_spectrum.py to generate plots from files generated by frequency analysis.
  • plot_bbq.py to generate plots from files generated by BBQ analysis.
  • plot_amplitude_detuning.py to generate plots from files generated by amplitude detuning analysis.
  • plot_optics_measurements.py to generate plots from files generated by optics_measurements.
  • plot_tfs.py all-purpose tfs-file plotter.
  • plot_kmod_results.py to plot the beta and waist of the K-modulation results.
Other Scripts

Other general utility scripts are in /omc3/scripts:

  • update_nattune_in_linfile.py to update the natural tune columns in the lin files by finding the highest peak in the spectrum in a given interval.
  • write_madx_macros.py to generate MAD-X tracking macros with observation points from a TWISS file.
  • merge_kmod_results.py to merge LSA results files created by kmod, and add the luminosity imbalance if the 4 needed IP/Beam files combination are present.
  • fake_measurement_from_model.py to create a fake measurement based on a model TWISS file.
  • betabeatsrc_output_converter.py to convert outputs from our old codes to omc3's new standardized format.
  • linfile_clean.py to automatically clean given columns in lin files.
  • kmod_average.py to calculate the average of multiple K-modulation measurements.
  • kmod_import.py to import a K-modulation measurement into an optics-measurement directory.
  • kmod_lumi_imbalace.py to calculate the luminosity imbalance between two IPs from averaged K-modulation files.
  • bad_bpms_summary.py to collect and summarize the bad BPMs from GUI runs.
  • resync_bpms.py to perform re-synchronisation of SuperKEKB BPMs data after a first optics analysis.

Example use for these scripts can be found in the tests files. Documentation including relevant flags and parameters can be found at https://pylhc.github.io/omc3/.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

omc3-0.28.1.tar.gz (17.5 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

omc3-0.28.1-py3-none-any.whl (17.9 MB view details)

Uploaded Python 3

File details

Details for the file omc3-0.28.1.tar.gz.

File metadata

  • Download URL: omc3-0.28.1.tar.gz
  • Upload date:
  • Size: 17.5 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.11.2 {"installer":{"name":"uv","version":"0.11.2","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Ubuntu","version":"24.04","id":"noble","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":true}

File hashes

Hashes for omc3-0.28.1.tar.gz
Algorithm Hash digest
SHA256 1efb986ac4be045be91f00b8e2523aca1babf0719989d82abed1299d0aae8d58
MD5 dd3a682d61bc3e8841277395f86d6809
BLAKE2b-256 c19bc3691ca985bf31c94cc56ba6c077975c9c02ae8cb6cefb90f5bd70672a25

See more details on using hashes here.

File details

Details for the file omc3-0.28.1-py3-none-any.whl.

File metadata

  • Download URL: omc3-0.28.1-py3-none-any.whl
  • Upload date:
  • Size: 17.9 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.11.2 {"installer":{"name":"uv","version":"0.11.2","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Ubuntu","version":"24.04","id":"noble","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":true}

File hashes

Hashes for omc3-0.28.1-py3-none-any.whl
Algorithm Hash digest
SHA256 cb2aec4d911054dec0137ad1793151e73bf312800fdcb53f1d814a102f2b9a1b
MD5 e23ec0c30ec457f0732afae7b011f39f
BLAKE2b-256 da0561965ed2fa067a548869f9a2af67dcea44dbeb575cb9dae93a88fc09da97

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page