import pylab as pl
import mystyle as ms
import time
B_multip = [0.5]
N_kicks = 3
N_turns = 2
pl.close('all')
ms.mystyle(fontsz=14)
# define machine for PyHEADTAIL
from PyHEADTAIL.particles.slicing import UniformBinSlicer
from machines_for_testing import SPS
machine = SPS(n_segments=N_kicks,
machine_configuration='Q20-injection',
accQ_x=20.,
accQ_y=20.)
machine.one_turn_map.remove(machine.longitudinal_map) # We apply it separately
# compute sigma x and y
epsn_x = 2.5e-6
epsn_y = 2.5e-6
inj_optics = machine.transverse_map.get_injection_optics()
sigma_x = np.sqrt(inj_optics['beta_x'] * epsn_x / machine.betagamma)
sigma_y = np.sqrt(inj_optics['beta_y'] * epsn_y / machine.betagamma)
# define apertures and Dh_sc to simulate headtail conditions
x_aper = 20 * sigma_x
y_aper = 20 * sigma_y
Dh_sc = 2 * x_aper / 128 / 2
non_linear_long_matching = False
# ~ #Here head is left and tail is right
b_spac_s = 25e-9
filling_pattern = [1., 1., 0., 1., 1.]
# ~ b_spac_s = 5e-9
# ~ filling_pattern = 5*([1.]+4*[0.])
macroparticlenumber = 500000
# Build machine
machine = SPS(n_segments = n_segments,
machine_configuration = 'Q20-injection', accQ_x=20., accQ_y=20.,
RF_at='end_of_transverse', longitudinal_mode = 'non-linear')
bucket_length_m = machine.circumference/(machine.longitudinal_map.harmonics[0])
b_spac_m = b_spac_s*machine.beta*clight
b_spac_buckets = np.round(b_spac_m/bucket_length_m)
#generate bunch objects
list_bunches = gmb.gen_matched_multibunch_beam(machine, macroparticlenumber, filling_pattern, b_spac_s, bunch_intensity, epsn_x, epsn_y, sigma_z, non_linear_long_matching, min_inten_slice4EC)
beam = sum(list_bunches)
import PyPARIS.slicing_tool as st
import PyPARIS.communication_helpers as ch
# Turn slices into buffer
x = np.reshape(appo[:, 1], (-1, n_part_per_turn))[::N_kicks, :]
xp = np.reshape(appo[:, 2], (-1, n_part_per_turn))[::N_kicks, :]
y = np.reshape(appo[:, 3], (-1, n_part_per_turn))[::N_kicks, :]
yp = np.reshape(appo[:, 4], (-1, n_part_per_turn))[::N_kicks, :]
z = np.reshape(appo[:, 5], (-1, n_part_per_turn))[::N_kicks, :]
zp = np.reshape(appo[:, 6], (-1, n_part_per_turn))[::N_kicks, :]
N_turns = len(x[:, 0])
pl.close('all')
ms.mystyle(fontsz=14)
# define machine for PyHEADTAIL
from PyHEADTAIL.particles.slicing import UniformBinSlicer
from machines_for_testing import SPS
machine = SPS(n_segments=N_kicks,
machine_configuration='Q20-injection',
accQ_x=20.13,
accQ_y=20.18)
#machine.one_turn_map.remove(machine.longitudinal_map)
# compute sigma x and y
epsn_x = 2.5e-6
epsn_y = 2.5e-6
inj_optics = machine.transverse_map.get_injection_optics()
sigma_x = np.sqrt(inj_optics['beta_x'] * epsn_x / machine.betagamma)
sigma_y = np.sqrt(inj_optics['beta_y'] * epsn_y / machine.betagamma)
# define apertures and Dh_sc to simulate headtail conditions
x_aper = 20 * sigma_x
y_aper = 20 * sigma_y
Dh_sc = 2 * x_aper / 128 / 2
from PyHEADTAIL.particles.slicing import UniformBinSlicer n_segments = 10 N_turns = 1 epsn_x = 2.5e-6 epsn_y = 2.5e-6 init_unif_edens_flag = 1 init_unif_edens = 1e11 N_MP_ele_init = 100000 N_mp_max = N_MP_ele_init * 4. # define the machine from machines_for_testing import SPS machine = SPS(n_segments=n_segments, machine_configuration='Q26-injection') # compute sigma x and y inj_optics = machine.transverse_map.get_injection_optics() sigma_x = np.sqrt(inj_optics['beta_x'] * epsn_x / machine.betagamma) sigma_y = np.sqrt(inj_optics['beta_y'] * epsn_y / machine.betagamma) # define apertures and Dh_sc to simulate headtail conditions x_aper = 20 * sigma_x y_aper = 20 * sigma_y Dh_sc = 2 * x_aper / 128 # define MP size nel_mp_ref_0 = init_unif_edens * 4 * x_aper * y_aper / N_MP_ele_init # define an electron cloud
def init_all(self): self.n_slices = n_slices self.n_segments = n_segments from machines_for_testing import SPS self.machine = SPS(n_segments = n_segments, machine_configuration = 'Q20-injection', accQ_x=20., accQ_y=20., RF_at='end_of_transverse') # We suppose that all the object that cannot be slice parallelized are at the end of the ring i_end_parallel = len(self.machine.one_turn_map)-1 #only RF is not parallelizable # split the machine sharing = shs.ShareSegments(i_end_parallel, self.ring_of_CPUs.N_nodes) myid = self.ring_of_CPUs.myid i_start_part, i_end_part = sharing.my_part(myid) self.mypart = self.machine.one_turn_map[i_start_part:i_end_part] if self.ring_of_CPUs.I_am_a_worker: print 'I am id=%d (worker) and my part is %d long'%(myid, len(self.mypart)) elif self.ring_of_CPUs.I_am_the_master: self.non_parallel_part = self.machine.one_turn_map[i_end_parallel:] print 'I am id=%d (master) and my part is %d long'%(myid, len(self.mypart)) # config e-cloud init_unif_edens_flag=1 init_unif_edens=2e11 N_MP_ele_init = 100000 N_mp_max = N_MP_ele_init*4. # define apertures and Dh_sc to simulate headtail inj_optics = self.machine.transverse_map.get_injection_optics() sigma_x = np.sqrt(inj_optics['beta_x']*epsn_x/self.machine.betagamma) sigma_y = np.sqrt(inj_optics['beta_y']*epsn_y/self.machine.betagamma) x_aper = 20*sigma_x y_aper = 20*sigma_y Dh_sc = 2*x_aper/128/2 # initial MP size nel_mp_ref_0 = init_unif_edens*4*x_aper*y_aper/N_MP_ele_init import PyECLOUD.PyEC4PyHT as PyEC4PyHT ecloud = PyEC4PyHT.Ecloud(slice_by_slice_mode=True, L_ecloud=self.machine.circumference/n_segments, slicer=None, Dt_ref=25e-12, pyecl_input_folder='../../PyECLOUD/testing/tests_PyEC4PyHT/drift_sim/', x_aper=x_aper, y_aper=y_aper, Dh_sc=Dh_sc, init_unif_edens_flag=init_unif_edens_flag, init_unif_edens=init_unif_edens, N_MP_ele_init=N_MP_ele_init, N_mp_max=N_mp_max, nel_mp_ref_0=nel_mp_ref_0, B_multip=B_multip) my_new_part = [] self.my_list_eclouds = [] for ele in self.mypart: my_new_part.append(ele) if ele in self.machine.transverse_map: ecloud_new = ecloud.generate_twin_ecloud_with_shared_space_charge() my_new_part.append(ecloud_new) self.my_list_eclouds.append(ecloud_new) self.mypart = my_new_part
