class fitnessFunc():
def __init__(self, args, tempdir, scaling=4, overwrite=True, verbose=False, summary=False, clean=False):
self.cons = constraintsClass()
self.beam = rbf.beam()
self.twiss = rtf.twiss()
self.tmpdir = tempdir
self.scaling = scaling
self.verbose = verbose
self.summary = summary
self.parameters = list(args)
self.dirname = os.path.basename(self.tmpdir)
self.framework = Framework(self.dirname, clean=clean, verbose=False)
self.framework.loadSettings('Lattices/claraX400_v12_80MVm.def')
if not os.name == 'nt':
self.framework.defineASTRACommand(['mpiexec','-np',str(3*scaling),'/opt/ASTRA/astra_MPICH2.sh'])
self.framework.defineGeneratorCommand(['/opt/ASTRA/generator.sh'])
self.framework.defineCSRTrackCommand(['/opt/OpenMPI-1.4.3/bin/mpiexec','-n',str(3*scaling),'/opt/CSRTrack/csrtrack_openmpi.sh'])
# self.framework.defineElegantCommand(['mpiexec','-np',str(3*scaling),'Pelegant'])
# else:
self.framework.defineElegantCommand(['elegant'])
self.framework.setElementType('quadrupole','k1', self.parameters)
def between(self, value, minvalue, maxvalue, absolute=True):
if absolute:
result = max([minvalue,min([maxvalue,abs(value)])])
else:
result = np.sign(value)*max([minvalue,min([maxvalue,abs(value)])])
return result
def calculateBeamParameters(self):
twiss = self.twiss
# try:
startS = self.framework['L02'].startObject['position_start'][2]
self.framework['L02'].file_block['input']['prefix'] = '../../basefiles_'+str(self.scaling)+'/'
self.framework.track()
constraintsList = {}
constraintsListQuads = {
'max_k': {'type': 'lessthan', 'value': [abs(p) for p in self.parameters], 'limit': 2.5, 'weight': 10},
}
# constraintsList = merge_two_dicts(constraintsList, constraintsListQuads)
twiss.reset_dicts()
twiss.read_astra_emit_files( self.dirname+'/'+'L04.Xemit.001' )
constraintsListSigmas = {
'max_xrms': {'type': 'lessthan', 'value': 1e3*twiss['sigma_x'], 'limit': 1, 'weight': 10},
'max_yrms': {'type': 'lessthan', 'value': 1e3*twiss['sigma_y'], 'limit': 1, 'weight': 10},
'min_xrms': {'type': 'greaterthan', 'value': 1e3*twiss['sigma_x'], 'limit': 0.1, 'weight': 0},
'min_yrms': {'type': 'greaterthan', 'value': 1e3*twiss['sigma_y'], 'limit': 0.1, 'weight': 0},
'last_exn': {'type': 'lessthan', 'value': 1e6*twiss['enx'][-1], 'limit': 0.6, 'weight': 1},
'last_eyn': {'type': 'lessthan', 'value': 1e6*twiss['eny'][-1], 'limit': 0.6, 'weight': 1},
}
# constraintsList = merge_two_dicts(constraintsList, constraintsListSigmas)
# tdc_position = self.framework['CLA-S07-TDC-01-R']['position_start'][2]
# tdc_screen_position = self.framework['CLA-S07-DIA-SCR-03-W']['position_start'][2]
# dechirper_position = self.framework['CLA-S07-DCP-01']['position_start'][2]
# constraintsListS07 = {
# 'tdc_phase_advance': {'type': 'equalto', 'value': (twiss.interpolate(tdc_screen_position,'muy', index='s') - twiss.interpolate(tdc_position,'muy', index='s')) % 0.25, 'limit': 0, 'weight': 1},
# 'tdc_screen_beta_y': {'type': 'greaterthan', 'value': twiss.extract_values('betay', tdc_position, tdc_screen_position), 'limit': 5, 'weight': 1},
# 'dechirper_sigma_x': {'type': 'lessthan', 'value': 1e3*twiss.interpolate(dechirper_position, 'Sx', index='s'), 'limit': 0.1, 'weight': 10},
# 'dechirper_sigma_y': {'type': 'lessthan', 'value': 1e3*twiss.interpolate(dechirper_position, 'Sy', index='s'), 'limit': 0.1, 'weight': 10},
# 'dechirper_sigma_xy': {'type': 'equalto', 'value': 1e3*twiss.interpolate(dechirper_position, 'Sy', index='s'), 'limit': 1e3*twiss.interpolate(dechirper_position, 'Sx', index='s'), 'weight': 35},
# }
# constraintsList = merge_two_dicts(constraintsList, constraintsListS07)
fitness = self.cons.constraints(constraintsList)
if self.verbose:
print self.cons.constraintsList(constraintsList)
if self.summary:
self.framework.createHDF5Summary(reference='Transverse_GA')
return fitness
class fitnessFunc():
def __init__(self, args, tempdir, scaling=4, overwrite=True, verbose=False, summary=False):
self.cons = constraintsClass()
self.beam = rbf.beam()
self.twiss = rtf.twiss()
self.tmpdir = tempdir
self.verbose = verbose
self.summary = summary
self.parameters = list(args)
self.dirname = os.path.basename(self.tmpdir)
self.framework = Framework(self.dirname, clean=False)
self.framework.loadSettings('Lattices/clara400_v12_elegant.def')
if not os.name == 'nt':
self.framework.defineASTRACommand(['mpiexec','-np',str(3*scaling),'/opt/ASTRA/astra_MPICH2.sh'])
self.framework.defineGeneratorCommand(['/opt/ASTRA/generator.sh'])
self.framework.defineCSRTrackCommand(['/opt/OpenMPI-1.4.3/bin/mpiexec','-n',str(3*scaling),'/opt/CSRTrack/csrtrack_openmpi.sh'])
self.framework.generator.number_of_particles = 2**(3*scaling)
else:
self.framework.generator.number_of_particles = 2**(3*3)
self.framework.setElementType('quadrupole','k1', self.parameters)
def between(self, value, minvalue, maxvalue, absolute=True):
if absolute:
result = max([minvalue,min([maxvalue,abs(value)])])
else:
result = np.sign(value)*max([minvalue,min([maxvalue,abs(value)])])
return result
def calculateBeamParameters(self):
twiss = self.twiss
try:
self.framework.track(run=True)
constraintsList = {}
constraintsListQuads = {
'max_k': {'type': 'lessthan', 'value': [abs(p) for p in self.parameters], 'limit': 2.5, 'weight': 10},
}
constraintsList = merge_two_dicts(constraintsList, constraintsListQuads)
twiss.read_astra_emit_files( [ self.dirname+'/'+n+'.Zemit.001' for n in self.framework.fileSettings.keys() if self.framework.fileSettings[n]['code'].upper() == 'ASTRA'] )
constraintsListSigmas = {
'max_xrms': {'type': 'lessthan', 'value': 1e3*twiss['sigma_x'], 'limit': 1, 'weight': 10},
'max_yrms': {'type': 'lessthan', 'value': 1e3*twiss['sigma_y'], 'limit': 1, 'weight': 10},
'min_xrms': {'type': 'greaterthan', 'value': 1e3*twiss['sigma_x'], 'limit': 0.1, 'weight': 10},
'min_yrms': {'type': 'greaterthan', 'value': 1e3*twiss['sigma_y'], 'limit': 0.1, 'weight': 10},
'last_exn': {'type': 'lessthan', 'value': 1e6*twiss['enx'][-1], 'limit': 0.6, 'weight': 1},
'last_eyn': {'type': 'lessthan', 'value': 1e6*twiss['eny'][-1], 'limit': 0.6, 'weight': 1},
}
constraintsList = merge_two_dicts(constraintsList, constraintsListSigmas)
twiss.read_astra_emit_files(self.dirname+'/S07.Zemit.001')
tdc_position = self.framework['CLA-S07-TDC-01-R']['position_start'][2]
tdc_screen_position = self.framework['CLA-S07-DIA-SCR-03-W']['position_start'][2]
dechirper_position = self.framework['CLA-S07-DCP-01']['position_start'][2]
constraintsListS07 = {
'tdc_phase_advance': {'type': 'equalto', 'value': twiss.interpolate(tdc_screen_position,'muy') - twiss.interpolate(tdc_position,'muy'), 'limit': 0.25, 'weight': 1},
'tdc_screen_beta_y': {'type': 'greaterthan', 'value': twiss.extract_values('beta_y', tdc_position, tdc_screen_position), 'limit': 5, 'weight': 1},
'dechirper_sigma_x': {'type': 'equalto', 'value': 1e3*twiss.interpolate(dechirper_position, 'sigma_x'), 'limit': 0.1, 'weight': 10},
'dechirper_sigma_y': {'type': 'equalto', 'value': 1e3*twiss.interpolate(dechirper_position, 'sigma_y'), 'limit': 0.1, 'weight': 10},
'dechirper_sigma_xy': {'type': 'equalto', 'value': 1e3*twiss.interpolate(dechirper_position, 'sigma_y') - 1e3*twiss.interpolate(dechirper_position, 'sigma_x'), 'limit': 0.0, 'weight': 20},
}
constraintsList = merge_two_dicts(constraintsList, constraintsListS07)
fitness = self.cons.constraints(constraintsList)
if self.verbose:
print self.cons.constraintsList(constraintsList)
if self.summary:
self.astra.createHDF5Summary(reference='Transverse_GA')
return fitness
except:
return 1e6