class StatLatsSetMember: """ This class delivers the statistical twiss parameters """ def __init__(self, file): self.file_out = file self.bunchtwissanalysis = BunchTwissAnalysis() def writeStatLats(self, s, bunch, lattlength = 0): self.bunchtwissanalysis.analyzeBunch(bunch) emitx = self.bunchtwissanalysis.getEmittance(0) betax = self.bunchtwissanalysis.getBeta(0) alphax = self.bunchtwissanalysis.getAlpha(0) betay = self.bunchtwissanalysis.getBeta(1) alphay = self.bunchtwissanalysis.getAlpha(1) emity = self.bunchtwissanalysis.getEmittance(1) dispersionx = self.bunchtwissanalysis.getDispersion(0) ddispersionx = self.bunchtwissanalysis.getDispersionDerivative(0) #dispersiony = self.bunchtwissanalysis.getDispersion(1, bunch) #ddispersiony = self.bunchtwissanalysis.getDispersionDerivative(1, bunch) sp = bunch.getSyncParticle() time = sp.time() if lattlength > 0: time = sp.time()/(lattlength/(sp.beta() * speed_of_light)) # if mpi operations are enabled, this section of code will # determine the rank of the present node rank = 0 # default is primary node mpi_init = orbit_mpi.MPI_Initialized() comm = orbit_mpi.mpi_comm.MPI_COMM_WORLD if (mpi_init): rank = orbit_mpi.MPI_Comm_rank(comm) # only the primary node needs to output the calculated information if (rank == 0): self.file_out.write(str(s) + "\t" + str(time) + "\t" + str(emitx)+ "\t" + str(emity)+ "\t" + str(betax)+ "\t" + str(betay)+ "\t" + str(alphax)+ "\t" + str(alphay) + "\t" + str(dispersionx) + "\t" + str(ddispersionx) +"\n") def closeStatLats(self): self.file_out.close() def resetFile(self, file): self.file_out = file
if i % 100 == 0:
lostbunch.dumpBunch(pre_list + "/lost_data/turn_" + str(i) + ".dat")
if 1:
k = 0
while k < b.getSize():
if check_bucket(b.z(k), b.dE(k)) is False:
b.deleteParticle(k)
else:
k += 1
if i < 200:
b.macroSize(num_charge_max / 200 * (i + 1))
ana.analyzeBunch(b)
curr_emitx = ana.getEmittance(0)
curr_betax = ana.getBeta(0)
curr_sx = sqrt(curr_betax * curr_emitx)
if rank == 0:
if not os.path.exists(pre_list + "/test_particles_" + str(test_name)):
os.mkdir(pre_list + "/test_particles_" + str(test_name))
p_list = []
count = 1
for ang in np.linspace(0, pi / 2, 30):
for r in np.linspace(0, 10 * curr_sx, 100):
x = cos(ang) * r
px = 0
if x == 0:
b.deleteParticle(k)
else:
k += 1
if rank == 0:
f2.flush()
# slow initialization for the first 200 turns
if i < 200:
b.macroSize(num_charge_max / 200 * (i + 1))
b.dumpBunch(pre_list + "/ready_bunch_" + str(test_name) + ".dat")
"""----------------------add test particles----------------------"""
ana.analyzeBunch(b)
curr_emitx = ana.getEmittance(0)
curr_betax = ana.getBeta(0)
curr_alphax = ana.getAlpha(0)
curr_emity = ana.getEmittance(1)
curr_betay = ana.getBeta(1)
curr_alphay = ana.getAlpha(1)
if rank == 0:
count = 1
for n_factor in np.linspace(0, 3, 51)[1:]:
for theta in np.linspace(0, 2 * pi, 101)[:-1]:
), matrix_lattice.getRingTwissDataY()
print("{} {}".format(TwissDataX[0][-1][1], TwissDataY[0][-1][1]))
twissX = TwissContainer(alpha=TwissDataX[1][0][1],
beta=TwissDataX[2][0][1],
emittance=emitx)
twissY = TwissContainer(alpha=TwissDataY[1][0][1],
beta=TwissDataY[2][0][1],
emittance=emity)
dist = GaussDist3D(twissX, twissY, twissZ)
for i in range(n_particles):
b.addParticle(*dist.getCoordinates())
print("tracking")
for i in range(n_turns):
lattice.trackBunch(b, trackDict)
bunchtwissanalysis.analyzeBunch(b)
Ex = bunchtwissanalysis.getEmittance(0)
Ey = bunchtwissanalysis.getEmittance(1)
w.write("{},{},{},{}\n".format(TwissDataX[0][-1][1],
TwissDataY[0][-1][1], Ex, Ey))
b.deleteAllParticles()
print("we are at the {}-th position".format(k))
else:
print("the problem occured: {}-th position".format(k))
w.close()
