class TestMultiCodeOptimization(unittest.TestCase):
def setUp(self):
linac = Linac()
linac.add_beamline(
'astra',
name='gun',
swd=osp.join(test_path, 'astra'),
fin='injector.in',
template=osp.join(test_path, 'astra/injector.in.000'),
pout='injector.0100.001')
linac.add_beamline(
'impactt',
name='matching',
swd=osp.join(test_path, 'impactt'),
fin='ImpactT.in',
template=osp.join(test_path, 'impactt/ImpactT.in.000'),
pout='fort.106',
charge=10e-12)
self.opt = LinacOptimization(linac)
self.opt.add_obj('f', expr='matching.out.emitx', scale=1e6)
self.opt.add_icon('g1', func=lambda a: a.gun.out.Sx * 1e3, ub=0.2)
self.opt.add_icon('g2', func=lambda a: a.matching.out.betax, ub=0.2)
self.opt.add_icon('g3', func=lambda a: a.matching.out.betay, ub=0.2)
self.opt.add_icon(
'g4',
func=lambda a: abs(a.matching.out.betax - a.matching.out.betay),
ub=0.01)
self.opt.add_var('gun/laser_spot', value=0.1, lb=0.04, ub=0.30)
self.opt.add_var('matching/MQZM1_G', value=0.0, lb=-6.0, ub=0.0)
self.opt.add_var('matching/MQZM2_G', value=0.0, lb=0.0, ub=6.0)
def tearDown(self):
for file in glob.glob(os.path.join(test_path, "astra/injector.*.001")):
os.remove(file)
os.remove(os.path.join(test_path, "astra/injector.in"))
for file in glob.glob(os.path.join(test_path, "impactt/fort.*")):
os.remove(file)
os.remove(os.path.join(test_path, "impactt/ImpactT.in"))
def test_optimization(self):
optimizer = ALPSO()
opt_f, opt_x = self.opt.solve(optimizer)
self.assertAlmostEqual(opt_f, 0.04025, delta=0.00040)
self.assertAlmostEqual(opt_x[0], 0.04000, delta=0.00010)
self.assertAlmostEqual(opt_x[1], -0.78, delta=0.030)
self.assertAlmostEqual(opt_x[2], 0.96, delta=0.040)
class TestLocalOptimizer(unittest.TestCase):
def setUp(self):
linac = Linac()
linac.add_beamline('astra',
name='gun',
swd=test_path,
fin='injector.in',
template=osp.join(test_path, 'injector.in.000'),
pout='injector.0150.001')
self.opt = LinacOptimization(linac)
# self.opt.printout = 1
self.opt.add_obj('emitx_um', expr='gun.out.emitx', scale=1.e6)
self.opt.add_var('laser_spot', value=0.1, lb=0.04, ub=0.3)
self.opt.add_var('main_sole_b', value=0.1, lb=0.0, ub=0.4)
def tearDown(self):
for file in glob.glob(osp.join(test_path, "injector.*.001")):
os.remove(file)
try:
os.remove(osp.join(test_path, "injector.in"))
except FileNotFoundError:
pass
def test_optimization_nelderMead(self):
optimizer = NelderMead()
opt_f, opt_x = self.opt.solve(optimizer)
self.assertAlmostEqual(opt_f, 0.03964, delta=0.0001)
self.assertAlmostEqual(opt_x[0], 0.04000, delta=0.0001)
self.assertAlmostEqual(opt_x[1], 0.23000, delta=0.01)
@unittest.skipIf(SKIP_SDPEN_TEST is True, "Failed to import library")
def test_optimization_sdpen(self):
optimizer = SDPEN()
opt_f, opt_x = self.opt.solve(optimizer)
self.assertAlmostEqual(opt_f, 0.03964, delta=0.0001)
self.assertAlmostEqual(opt_x[0], 0.04000, delta=0.0001)
self.assertAlmostEqual(opt_x[1], 0.23000, delta=0.01)
class TestGlobalOptimizer(unittest.TestCase):
def setUp(self):
linac = Linac()
linac.add_beamline('astra',
name='gun',
swd=test_path,
fin='injector.in',
template=osp.join(test_path, 'injector.in.000'),
pout='injector.0150.001')
self.opt = LinacOptimization(linac)
self.opt.add_obj('f', expr='gun.out.Sx', scale=1.e6)
self.opt.add_icon('g1',
func=lambda a: a['gun'].max.emitx * 1e6,
ub=0.041)
self.opt.add_econ('g2', func=lambda a: a['gun'].out.gamma, eq=10.0)
self.opt.add_var('laser_spot', value=0.1, lb=0.04, ub=0.3)
self.opt.add_var('main_sole_b', value=0.1, lb=0.0, ub=0.3)
self.opt.add_var('gun_gradient', value=130, lb=90.0, ub=130.0)
def tearDown(self):
for file in glob.glob(osp.join(test_path, "injector.*.001")):
os.remove(file)
os.remove(osp.join(test_path, "injector.in"))
def test_optimization(self):
optimizer = ALPSO()
opt_f, opt_x = self.opt.solve(optimizer)
self.assertAlmostEqual(opt_f, 65.62, delta=0.10)
self.assertAlmostEqual(opt_x[0], 0.040000, delta=0.00010)
self.assertAlmostEqual(opt_x[1], 0.2521, delta=0.0010)
self.assertAlmostEqual(opt_x[2], 100.4, delta=1.0)
name='gun',
swd='../astra_files',
fin='injector.in',
template='injector.in.000',
pout='injector.0450.001')
mapping = {
'laser_spot': 0.1,
'main_sole_b': 0.2,
}
opt = LinacOptimization(linac) # instantiate Optimization (problem)
# There are two options to access a parameter of a linac:
# 1. Use a string: the string must have the form
# beamline_name.WatchParameters_name.param_name
# or
# beamline_name.LineParameters_name.param_name.
# 2. Use a function object: the function has only one argument which is
# the linac instance.
# add the objective (the horizontal emittance at the end of the 'gun' beamline)
opt.add_obj('emitx_um', expr='gun.out.emitx', scale=1e6)
# add variables with lower boundary (lb) and upper boundary (ub)
opt.add_var('laser_spot', value=0.10, lb=0.04, ub=0.3)
opt.add_var('main_sole_b', value=0.20, lb=0.00, ub=0.4)
optimizer = NelderMead() # instantiate an optimizer
opt.solve(optimizer) # run the optimization
pout='injector.0450.001')
# Add the second beamline
#
# Note: 'charge' is required for an ImpactT simulation but this argument
# will be ignored if the code is Astra.
linac.add_beamline('impactt',
name='chicane',
swd='../impactt_files',
fin='ImpactT.in',
template='ImpactT.in.000',
pout='fort.106',
charge=1e-15)
opt = LinacOptimization(linac)
opt.add_obj('St_betaxy',
func=lambda a: max(a['chicane'].out.emitx * 1e6, a['chicane'].out.
betax, a['chicane'].out.betay))
opt.add_var('gun/laser_spot', value=0.1, lb=0.04, ub=0.30)
opt.add_var('gun/main_sole_b', value=0.1, lb=0.00, ub=0.40)
opt.add_var('chicane/MQZM1_G', value=0.0, lb=-10, ub=10)
opt.add_var('chicane/MQZM3_G', value=0.0, lb=-10, ub=10)
opt.add_covar('chicane/MQZM2_G', 'chicane/MQZM1_G', scale=-1)
opt.add_covar('chicane/MQZM4_G', 'chicane/MQZM3_G', scale=-1)
optimizer = NelderMead()
opt.solve(optimizer)
from liso import Linac, LinacOptimization, ALPSO
from liso.logging import logger
logger.setLevel('DEBUG')
linac = Linac()
linac.add_beamline('astra',
name='gun',
swd='../astra_files',
fin='injector.in',
template='injector.in.000',
pout='injector.0450.001')
opt = LinacOptimization(linac)
opt.add_obj('St', expr='gun.out.St', scale=1e15)
# equality constraint (the No. of particles at the end of the 'gun' beamline)
opt.add_econ('n_pars', expr='gun.out.n', eq=2000)
# inequality constraint (the beta [x] function at the end of the 'gun' beamline) with the upper boundary.
opt.add_icon('emitx', expr='gun.out.emitx', scale=1e6, ub=0.3)
# inequality constraint (the Lorentz factor at the end of the 'gun' beamline) with the lower boundary.
opt.add_icon('gamma', func=lambda a: a['gun'].out.gamma, lb=20.0)
# inequality constraint (the maximum beam size [x] throughout the 'gun' beamline) with upper boundary.
opt.add_icon('max_Sx', func=lambda a: a['gun'].max.Sx * 1e3, ub=3.0)
opt.add_var('laser_spot', value=0.1, lb=0.04, ub=0.5)
opt.add_var('main_sole_b', value=0.2, lb=0.00, ub=0.4)
opt.add_var('gun_phase', value=0.0, lb=-10, ub=10)
opt.add_var('tws_phase', value=0.0, lb=-90, ub=0)