pyaml-test-lattice

Lattices and configuration files used for pyAML integration tests and tutorials.

Usage

The package discovers files automatically from its packaged data/lattice and data/configuration directories. Access them through separate registries:

from pyaml_test_lattice import configurations, lattices

lattice_file = lattices["fodo_1gev_6d.json"]
config_file = configurations["pyaml/tango/fodo_1gev_6d_pyaml.yaml"]

Registry entries are filesystem paths, so they can be passed directly to lattice and configuration loaders:

simulator = Simulator(name="design", lattice=lattice_file)
accelerator = Accelerator.load(config_file)

New files placed below either data directory are available automatically using their path relative to that directory.

Optional descriptions can be added without changing the registry. Place a file named <filename>.description next to any lattice or configuration file. Its text is displayed when printing the registry:

fodo_1gev_6d.json.description

To list the available files and their description, print a registry:

print(configurations)

Named arrays and tuning tools

The fodo_1gev_6d pyAML configurations (pyaml/tango/tango-pyaml/fodo_1gev_6d_pyaml.yaml and pyaml/tango/pyaml-cs-oa/fodo_1gev_6d_pyaml-oa.yaml) declare the arrays and tools used by the pyAML examples/use_cases notebooks, under the same canonical names:

Name	Description
QForTune	Quadrupoles used for tune correction (all QF_* and QD_*)
HCorr / VCorr	Horizontal / vertical orbit correctors (COR_*.hcorrector, COR_*.vcorrector)
BPM	Beam position monitors (BPM_*)
BETATRON_TUNE	Betatron tune monitor
CHROMATICITY_MONITOR	Chromaticity monitor (RF frequency scan)
DEFAULT_TUNE_CORRECTION	Tune correction tool → SR.tune (uses pyaml/trm.json)
DEFAULT_TUNE_RESPONSE_MATRIX	Tune response matrix tool → SR.trm
DEFAULT_ORBIT_CORRECTION	Orbit correction tool → SR.orbit (uses pyaml/orm.json)
DEFAULT_ORBIT_RESPONSE_MATRIX	Orbit response matrix tool → SR.orm
DEFAULT_DISPERSION	Dispersion measurement tool → SR.dispersion

pyaml/trm.json and pyaml/orm.json are shared by both configurations; they were measured in design mode (pyAT) and are loaded automatically.

from pyaml.accelerator import Accelerator
from pyaml_test_lattice import configurations

sr = Accelerator.load(configurations["pyaml/tango/pyaml-cs-oa/fodo_1gev_6d_pyaml-oa.yaml"])
SR = sr.design
SR.tune.set([0.19, 0.28], iter=10, wait_time=0.0)