def __init__(self, input, uselogger=True):
if input:
parameters = inp_out.read_parameter_input(input, uselogger)
else:
parameters = inp_out.read_parameter_input({'atomlist':[('Xx',1,0,0)],'structure':'Cluster'}, uselogger)
self.__dict__.update(parameters)
if self.loggername:
global logger
logger = logging.getLogger(self.loggername)
if self.restart_optimizer:
try:
rank = MPI.COMM_WORLD.Get_rank()
except:
rank = 0
if rank==0:
logger.info('restarting output')
outdict = inp_out.restart_output(self)
self.__dict__.update(outdict)
logger.info('Loading individual files')
poplist = []
for indfile in self.population:
ind = inp_out.read_individual(indfile)
poplist.append(ind)
self.population = poplist
logger.info('Loading bests')
bestlist = []
for bestfile in self.BESTS:
ind = inp_out.read_individual(bestfile)
bestlist.append(ind)
self.BESTS = bestlist
self.restart = True
if self.structure == 'Defect':
bulk = inp_out.read_xyz(self.solidfile)
bulk.set_pbc(True)
bulk.set_cell(self.solidcell)
self.solidbulk = bulk.copy()
else:
self.solidbulk = None
else:
self.convergence = False
self.generation = 0
self.Runtimes = [time.time()]
self.Evaluations = list()
self.CXs = list()
self.Muts = list()
self.cxattempts = 0
self.mutattempts = list()
self.BESTS = list()
self.genrep = 0
self.minfit = 0
self.convergence = False
self.overrideconvergence = False
self.population = list()
self.calc = None
self.static_calc = None
def read(self,optfile):
parameters = inp_out.read_parameter_input(optfile,True)
self.__dict__.update(parameters)
outdict = inp_out.restart_output(self)
self.__dict__.update(outdict)
poplist = []
for indfile in self.population:
ind = inp_out.read_individual(indfile)
poplist.append(ind)
self.population = poplist
bestlist = []
for bestfile in self.BESTS:
ind = inp_out.read_individual(bestfile)
bestlist.append(ind)
self.BESTS = bestlist
self.restart = True
return self
def __init__(self, input, uselogger=True):
if input:
parameters = inp_out.read_parameter_input(input, uselogger)
else:
parameters = inp_out.read_parameter_input({'atomlist':[('Xx',1,0,0)],'structure':'Cluster'}, uselogger)
self.__dict__.update(parameters)
try:
rank = MPI.COMM_WORLD.Get_rank()
except:
rank = 0
if 'stem' in parameters['fitness_scheme']:
if rank == 0 :
nk = self.stemcalc.parameters['Pixels']
self.stemcalc.psf = np.empty([nk,nk],dtype=float)
fileobj = open('PSF.txt', 'r')
lines = fileobj.readlines()
for x in range(0,nk):
self.stemcalc.psf[x] = lines[x].split()
fileobj.close()
#self.stemcalc.psf = tools.StemCalc.get_probe_function(self.stemcalc.parameters)
else:
self.stemcalc.psf = None
self.stemcalc.psf = MPI.COMM_WORLD.bcast(self.stemcalc.psf,root=0)
if self.loggername:
global logger
logger = logging.getLogger(self.loggername)
if self.restart_optimizer:
try:
rank = MPI.COMM_WORLD.Get_rank()
except:
rank = 0
if rank==0:
logger.info('restarting output')
outdict = inp_out.restart_output(self)
self.__dict__.update(outdict)
logger.info('Loading individual files')
poplist = []
for indfile in self.population:
ind = inp_out.read_individual(indfile)
poplist.append(ind)
self.population = poplist
logger.info('Loading bests')
bestlist = []
for bestfile in self.BESTS:
ind = inp_out.read_individual(bestfile)
bestlist.append(ind)
self.BESTS = bestlist
self.restart = True
if self.structure == 'Defect':
bulk = inp_out.read_xyz(self.solidfile)
bulk.set_pbc(True)
bulk.set_cell(self.solidcell)
self.solidbulk = bulk.copy()
else:
self.solidbulk = None
else:
self.convergence = False
self.generation = 0
self.Runtimes = [time.time()]
self.Evaluations = list()
self.CXs = list()
self.Muts = list()
self.cxattempts = 0
self.mutattempts = list()
self.BESTS = list()
self.genrep = 0
self.minfit = 0
self.convergence = False
self.overrideconvergence = False
self.population = list()
self.calc = None
self.static_calc = None