at.tracking.utils

Utility functions for tracking simulations

Functions

get_bunches(r_in, nbunch[, selected_bunches])	Function to get the bunches particles 6D coordinates
get_bunches_std_mean(r_in, nbunch[, ...])	Function to get the bunches standard deviation and center of mass
unfold_beam(ring, beam, **kwargs)	Function to unfold the beam based on the ring fill pattern.

get_bunches(r_in, nbunch, selected_bunches=None)

Function to get the bunches particles 6D coordinates

Parameters:

• r_in (ndarray) – 6 x n_particles Fortran-ordered numpy array.

• nbunch (int) – integer, total number of bunches

• selected_bunches (Optional[ndarray]) – integer or array of integers, index

• bunches (of the selected) –

Returns:

• List of ndarray containing the 6 x n particles coordinates

• of the selected bunches

get_bunches_std_mean(r_in, nbunch, selected_bunches=None)

Function to get the bunches standard deviation and center of mass

Parameters:

• r_in (ndarray) – 6 x n_particles Fortran-ordered numpy array.

• nbunch (int) – integer, total number of bunches

• selected_bunches (Optional[ndarray]) – integer or array of integers, index

• bunches (of the selected) –

Returns:

• Lists of ndarray containing the 6D standard deviation

• and center of mass (std, mean)

unfold_beam(ring, beam, **kwargs)

Function to unfold the beam based on the ring fill pattern. The input particle distribution has to be in on bucket 0. Particle are distributed in bunches using i%ring.nbunch where i is the particle index. For each bunches the absolute ct is computed using the 6D closed orbit search, this closed orbit is added to the input particles.

Parameters:

• ring (Lattice) – Lattice description

• beam (ndarray) – array with shape(6, nparticles)

Keyword Arguments:

• convergence (float) – Convergence criterion for 6D orbit Default: DConstant.OrbConvergence

• max_iterations (int) – Maximum number of iterations for 6D orbit. Default: DConstant.OrbMaxIter

Returns:

beam (numpy.ndarray) – unfolded beam

Return type:

ndarray