ocelot.cpbd.match

Module Contents

Functions

weights_default(val)
match(lat, constr, vars, tw, verbose=True, max_iter=1000, method='simplex', weights=weights_default, vary_bend_angle=False, min_i5=False)	Function to match twiss parameters
weights_default(val)
match_beam(lat, constr, vars, p_array, navi, verbose=True, max_iter=1000, method='simplex', weights=weights_default, vary_bend_angle=False, min_i5=False)	Function to match twiss paramters
match_matrix(lat, beam, varz, target_matrix)
match_tunes(lat, tw0, quads, nu_x, nu_y, ncells=1, print_proc=0)
closed_orbit(lattice, eps_xy=1e-07, eps_angle=1e-07, energy=0)

ocelot.cpbd.match.weights_default(val)

ocelot.cpbd.match.match(lat, constr, vars, tw, verbose=True, max_iter=1000, method='simplex', weights=weights_default, vary_bend_angle=False, min_i5=False)

Function to match twiss parameters

Parameters

• lat – MagneticLattice

• constr –

  dictionary, constrains. Example: ‘periodic’:True - means the “match” function tries to find periodic solution at the ends of lattice:

  constr = {elem1:{‘beta_x’:15, ‘beta_y’:2}, ‘periodic’:True}

  ”hard” constrains on the end of elements (elem1, elem2):

  constr = {elem1:{‘alpha_x’:5, ‘beta_y’:5}, elem2:{‘Dx’:0 ‘Dyp’:0, ‘alpha_x’:5, ‘beta_y’:5}}

  or mixture of “soft” and hard constrains:

  constr = {elem1:{‘alpha_x’:[“>”, 5], ‘beta_y’:5}, elem2:{‘Dx’:0 ‘Dyp’:0, ‘alpha_x’:5, ‘beta_y’:[“>”, 5]}}

  in case one needs global control on beta function, the constrains can be written following way.

  constr = {elem1:{‘alpha_x’:5, ‘beta_y’:5}, ‘global’: {‘beta_x’: [‘>’, 10]}}

• vars – list of elements e.g. vars = [QF, QD] or it can be initial twiss parameters: vars = [[tws0, ‘beta_x’], [tws0, ‘beta_y’], [tws0, ‘alpha_x’], [tws0, ‘alpha_y’]]

• tw – initial Twiss

• verbose – allow print output of minimization procedure

• max_iter –

• method – string, available ‘simplex’, ‘cg’, ‘bfgs’

• weights –

  function returns weights, for example def weights_default(val):

  if val == ‘periodic’: return 10000001.0 if val == ‘total_len’: return 10000001.0 if val in [‘Dx’, ‘Dy’, ‘Dxp’, ‘Dyp’]: return 10000002.0 if val in [‘alpha_x’, ‘alpha_y’]: return 100007.0 if val in [‘mux’, ‘muy’]: return 10000006.0 if val in [‘beta_x’, ‘beta_y’]: return 100007.0 return 0.0001

• vary_bend_angle – False, allow to vary “angle” of the dipoles instead of the focusing strength “k1”

• min_i5 – minimization of the radiation integral I5. Can be useful for storage rings.

Returns

result

ocelot.cpbd.match.weights_default(val)

ocelot.cpbd.match.match_beam(lat, constr, vars, p_array, navi, verbose=True, max_iter=1000, method='simplex', weights=weights_default, vary_bend_angle=False, min_i5=False)

Function to match twiss paramters

Parameters

• lat – MagneticLattice

• constr – dict in format {elem1:{‘beta_x’:15, ‘beta_y’:2}, ‘periodic’:True} try to find periodic solution or constr = {elem1:{‘alpha_x’:5, ‘beta_y’:5}, elem2:{‘Dx’:0 ‘Dyp’:0, ‘alpha_x’:5, ‘beta_y’:5} and so on.

• vars – lsit of elements e.g. vars = [QF, QD]

• p_array – initial ParticleArray

• navi – Navigator with added PhysProcess if needed

• verbose – allow print output of minimization procedure

• max_iter –

• method – string, available ‘simplex’, ‘cg’, ‘bfgs’

• weights –

  function returns weights, for example def weights_default(val):

  if val == ‘periodic’: return 10000001.0 if val == ‘total_len’: return 10000001.0 if val in [‘Dx’, ‘Dy’, ‘Dxp’, ‘Dyp’]: return 10000002.0 if val in [‘alpha_x’, ‘alpha_y’]: return 100007.0 if val in [‘mux’, ‘muy’]: return 10000006.0 if val in [‘beta_x’, ‘beta_y’]: return 100007.0 return 0.0001

• vary_bend_angle – False, allow to vary “angle” of the dipoles instead of the focusing strength “k1”

• min_i5 – minimization of the radiation integral I5. Can be useful for storage rings.

Returns

result

ocelot.cpbd.match.match_matrix(lat, beam, varz, target_matrix)

ocelot.cpbd.match.match_tunes(lat, tw0, quads, nu_x, nu_y, ncells=1, print_proc=0)

ocelot.cpbd.match.closed_orbit(lattice, eps_xy=1e-07, eps_angle=1e-07, energy=0)