def update_structfile(ind, structfile, Optimizer):
if Optimizer.structure == 'Defect' or Optimizer.structure == 'Surface':
sols = Atoms()
sols.extend(ind[0])
sols.extend(ind.bulki)
elif Optimizer.structure == 'Crystal':
sols = ind[0].repeat((3,3,3))
else:
sols = ind[0].copy()
positions = sols.get_positions()
if Optimizer.vacancy_output:
for one in ind.vacancies:
sols.append(Atom(symbol='X',position=one.position))
#Optimizer.output.write('Number of positions = {0}\n'.format(len(positions)))
write_xyz(structfile, sols, ind.energy)
return positions
def stem_cost(indiv, Optimizer):
'''Function to calculate STEM_Cost fitness of individual.
Input:
indiv = structopt Individual class object to be evaluated
Optimizer = structopt Optimizer class object
Must have STEM Calc function attached
Output:
indiv = structopt Individual class object with new fitness.
'''
#logger = initialize_logger(Optimizer.loggername)
logger = logging.getLogger(Optimizer.loggername)
starting = indiv.duplicate()
cwd = os.getcwd()
try:
outs = eval_energy(Optimizer,indiv)
except Exception, e:
logger.warn('Error in energy evaluation: {0}'.format(e), exc_info=True)
stro = 'ERROR: Problem in Energy Evaluation'
print stro
print e
stro += '\n' + repr(e)
os.chdir(cwd)
f=open('problem-structures.xyz','a')
totalsol = indiv[0].copy()
totalsol.extend(indiv.bulki)
write_xyz(f,totalsol,data='Starting structure hindex={0}'.format(indiv.history_index))
indiv.energy = 10000
f.close()
print ' Writing structure to problemstructures.xyz file. Structure (hindex) : '+indiv.history_index
print ' Setting individual energy to 50000.'
outs = [10000, starting.bulki, starting, stro]
def write_pop(Optimizer,pop):
"""
Function to write the data from a given population.
Inputs:
Optimizer = structopt Optimizer class object with output file data
pop = List of structopt Individual class objects with data to be written
Outputs:
None. Data is written to output files provided by Optimizer class object
"""
Optimizer.output.write('\n--New Population--\n')
#Write structures
for ind in pop:
update_outfile(ind, Optimizer.output)
if Optimizer.genealogy:
update_genealogy(ind, Optimizer.Genealogyfile)
if Optimizer.swaplist:
swaplist_check(ind,Optimizer.structure,Optimizer.output)
if Optimizer.indiv_defect_write:
write_xyz(Optimizer.ifiles[ind.index],ind[0],ind.energy)
update_structsumfile(ind, Optimizer.files[Optimizer.nindiv])
if Optimizer.generation % 10 == 0:
positions = update_structfile(ind, Optimizer.files[ind.index], Optimizer)
Optimizer.output.write('Number of positions = {0}\n'.format(len(positions)))
if Optimizer.genealogy:
Optimizer.Genealogyfile.write('\n')
return
def surfaceenergy(indiv, Optimizer):
'''Function to calculate surface energy fitness of individual.
Input:
indiv = structopt Individual class object to be evaluated
Optimizer = structopt Optimizer class object
Output:
indiv = structopt Individual class object with new fitness.
'''
logger = logging.getLogger(Optimizer.loggername)
#logger = initialize_logger(Optimizer.loggername)
starting = indiv.duplicate()
cwd = os.getcwd()
try:
outs = eval_energy(Optimizer, indiv)
except Exception, e:
logger.warn('Error in energy evaluation: {0}'.format(e), exc_info=True)
stro = 'ERROR: Problem in Energy Evaluation'
print stro
print e
stro += '\n' + repr(e)
os.chdir(cwd)
f = open('problem-structures.xyz', 'a')
totalsol = indiv[0].copy()
totalsol.extend(indiv.bulki)
write_xyz(f,
totalsol,
data='Starting structure hindex={0}'.format(
indiv.history_index))
indiv.energy = 10000
f.close()
print ' Writing structure to problemstructures.xyz file. Structure (hindex) : ' + indiv.history_index
print ' Setting individual energy to 50000.'
outs = [10000, starting.bulki, starting, stro]
def crossover_switch(child1, child2, Optimizer):
"""Functions for selecting and pairing individuals
for crossovers"""
#logger = initialize_logger(Optimizer.loggername)
logger = logging.getLogger(Optimizer.loggername)
if 'CX' in Optimizer.debug:
debug = True
else:
debug = False
if debug:
s1 = child1[0].copy()
s2 = child2[0].copy()
if Optimizer.structure == 'Defect':
s1.extend(child1.bulki.copy())
s2.extend(child2.bulki.copy())
write_xyz(Optimizer.debugfile, s1, 'First Cx Individual - Pre ')
write_xyz(Optimizer.debugfile, s2, 'Second Cx Individual - Pre')
passflag = True
scheme = Optimizer.cx_scheme
try:
exec "from MAST.structopt.crossover.{0} import {0}".format(scheme)
nchild1, nchild2 = eval(
'{0}(child1, child2, Optimizer)'.format(scheme))
except NameError, e:
logger.warning(
'Specified Crossover not one of the available options. Please check documentation and spelling! Crossover : {0}. {1}'
.format(Optimizer.cx_scheme, e),
exc_info=True)
print 'Name Error:', e
passflag = False
def enpafit(indiv,Optimizer):
"""Fitness function to evaluate the energy per atom of an individual structure.
Inputs:
indiv = Individual class object to be evaluated
Optimizer = Optimizer class object with needed parameters
Outputs:
indiv = Evaluated Individual class object
"""
#logger = initialize_logger(Optimizer.loggername)
logger = logging.getLogger(Optimizer.loggername)
starting = indiv.duplicate()
cwd = os.getcwd()
try:
outs = eval_energy(Optimizer,indiv)
except Exception, e:
logger.warn('Error in energy evaluation: {0}'.format(e), exc_info=True)
stro = 'ERROR: Problem in Energy Evaluation'
print stro
print e
stro += '\n' + repr(e)
os.chdir(cwd)
f=open('problem-structures.xyz','a')
totalsol = indiv[0].copy()
totalsol.extend(indiv.bulki)
write_xyz(f,totalsol,data='Starting structure hindex={0}'.format(indiv.history_index))
indiv.energy = 10000
f.close()
print ' Writing structure to problemstructures.xyz file. Structure (hindex) : '+indiv.history_index
print ' Setting individual energy to 50000.'
outs = [10000, starting.bulki, starting, stro]
def enthalpyfit(indiv, Optimizer):
"""Fitness function to evaluate the enthalpy of an individual structure.
Inputs:
indiv = Individual class object to be evaluated
Optimizer = Optimizer class object with needed parameters
Outputs:
indiv = Evaluated Individual class object
"""
#logger = initialize_logger(Optimizer.loggername)
logger = logging.getLogger(Optimizer.loggername)
starting = indiv.duplicate()
cwd = os.getcwd()
try:
outs = eval_energy(Optimizer, indiv)
passflag = True
except Exception, e:
logger.warn('Error in energy evaluation: {0}'.format(e), exc_info=True)
stro = 'ERROR: Problem in Energy Evaluation'
print stro
print e
stro += '\n' + repr(e)
os.chdir(cwd)
f = open('problem-structures.xyz', 'a')
totalsol = indiv[0].copy()
totalsol.extend(indiv.bulki)
write_xyz(f,
totalsol,
data='Starting structure hindex={0}'.format(
indiv.history_index))
indiv.energy = 10000
f.close()
print ' Writing structure to problemstructures.xyz file. Structure (hindex) : ' + indiv.history_index
print ' Setting individual energy to 50000.'
outs = [10000, starting.bulki, starting, stro]
passflag = False
def crossover_switch(child1, child2, Optimizer):
"""Functions for selecting and pairing individuals
for crossovers"""
# logger = initialize_logger(Optimizer.loggername)
logger = logging.getLogger(Optimizer.loggername)
if "CX" in Optimizer.debug:
debug = True
else:
debug = False
if debug:
s1 = child1[0].copy()
s2 = child2[0].copy()
if Optimizer.structure == "Defect":
s1.extend(child1.bulki.copy())
s2.extend(child2.bulki.copy())
write_xyz(Optimizer.debugfile, s1, "First Cx Individual - Pre ")
write_xyz(Optimizer.debugfile, s2, "Second Cx Individual - Pre")
passflag = True
scheme = Optimizer.cx_scheme
try:
exec "from MAST.structopt.crossover.{0} import {0}".format(scheme)
nchild1, nchild2 = eval("{0}(child1, child2, Optimizer)".format(scheme))
except NameError, e:
logger.warning(
"Specified Crossover not one of the available options. Please check documentation and spelling! Crossover : {0}. {1}".format(
Optimizer.cx_scheme, e
),
exc_info=True,
)
print "Name Error:", e
passflag = False
def write_pop(Optimizer, pop):
"""
Function to write the data from a given population.
Inputs:
Optimizer = structopt Optimizer class object with output file data
pop = List of structopt Individual class objects with data to be written
Outputs:
None. Data is written to output files provided by Optimizer class object
"""
Optimizer.output.write('\n--New Population--\n')
#Write structures
for ind in pop:
update_outfile(ind, Optimizer.output)
if Optimizer.genealogy:
update_genealogy(ind, Optimizer.Genealogyfile)
if Optimizer.swaplist:
swaplist_check(ind, Optimizer.structure, Optimizer.output)
if Optimizer.indiv_defect_write:
write_xyz(Optimizer.ifiles[ind.index], ind[0], ind.energy)
update_structsumfile(ind, Optimizer.files[Optimizer.nindiv])
positions = update_structfile(ind, Optimizer.files[ind.index],
Optimizer)
Optimizer.output.write('Number of positions = {0}\n'.format(
len(positions)))
if Optimizer.genealogy:
Optimizer.Genealogyfile.write('\n')
return
def update_structfile(ind, structfile, Optimizer):
if Optimizer.structure == 'Defect' or Optimizer.structure == 'Surface':
sols = Atoms()
sols.extend(ind[0])
sols.extend(ind.bulki)
elif Optimizer.structure == 'Crystal':
sols = ind[0].repeat((3, 3, 3))
else:
sols = ind[0].copy()
positions = sols.get_positions()
if Optimizer.vacancy_output:
for one in ind.vacancies:
sols.append(Atom(symbol='X', position=one.position))
Optimizer.output.write('Number of positions = {0}\n'.format(
len(positions)))
write_xyz(structfile, sols, ind.energy)
return positions
def write_individual(individ, indivfile):
"""Function to write the data of an individual class object to a flat file
Input:
individ = Individual class object to be written
indivfile = String or fileobject for file to be written to
Output:
No output returned. Information is written to file
"""
if isinstance(indivfile, str):
indivfile=open(indivfile, 'a')
#Write break
indivfile.write('----------\n')
#Write structure information
indivfile.write('Structure information\n')
write_xyz(indivfile, individ[0])
indivfile.write('structure cell = {0}\n'.format(get_atom_cell(individ[0])))
#Write additional information
indivfile.write('fitness = {0}\n'.format(individ.fitness))
indivfile.write('index = {0}\n'.format(individ.index))
indivfile.write('history_index = {0}\n'.format(individ.index))
indivfile.write('energy = {0}\n'.format(individ.energy))
indivfile.write('tenergymx = {0}\n'.format(individ.tenergymx))
indivfile.write('tenergymin = {0}\n'.format(individ.tenergymin))
indivfile.write('pressure = {0}\n'.format(individ.pressure))
indivfile.write('volume = {0}\n'.format(individ.volume))
indivfile.write('force = {0}\n'.format(individ.force))
indivfile.write('purebulkenpa = {0}\n'.format(individ.purebulkenpa))
indivfile.write('natomsbulk = {0}\n'.format(individ.natomsbulk))
indivfile.write('fingerprint = {0}\n'.format(individ.fingerprint))
indivfile.write('swaplist = {0}\n'.format(individ.swaplist))
#Write additional structure information
indivfile.write('bulki\n')
write_xyz(indivfile, individ.bulki)
indivfile.write('bulki cell = {0}\n'.format(get_atom_cell(individ.bulki)))
indivfile.write('bulko\n')
write_xyz(indivfile, individ.bulko)
indivfile.write('bulko cell = {0}\n'.format(get_atom_cell(individ.bulko)))
indivfile.write('box\n')
write_xyz(indivfile, individ.box)
indivfile.write('box cell = {0}\n'.format(get_atom_cell(individ.box)))
indivfile.write('vacancies\n')
write_xyz(indivfile, individ.vacancies)
indivfile.write('vacancies cell = {0}\n'.format(get_atom_cell(individ.vacancies)))
indivfile.write('swaps\n')
write_xyz(indivfile, individ.swaps)
indivfile.write('swaps cell = {0}\n'.format(get_atom_cell(individ.swaps)))
indivfile.write('Finish')
indivfile.close()
return
'Error attempting to load back up cxTP Crossover. Something very wrong!! {1}'
.format(e),
exc_info=True)
print 'CXTP Name Error: ', e
except Exception, e:
logger.error('Error in cxtp Crossover {0}'.format(e),
exc_info=True)
print 'Exception: ', e
if passflag:
child1 = nchild1
child2 = nchild2
child1.energy = 0
child2.energy = 0
child1.fitness = 0
child2.fitness = 0
ch1hi = child1.history_index
child1.history_index = '(' + repr(child1.index) + '+' + repr(
child2.index) + ')'
child2.history_index = '(' + repr(child2.index) + '+' + repr(
child1.index) + ')'
if debug:
s1 = child1[0].copy()
s2 = child2[0].copy()
if Optimizer.structure == 'Defect':
s1.extend(child1.bulki.copy())
s2.extend(child2.bulki.copy())
write_xyz(Optimizer.debugfile, s1, 'First Cx Individual - Post')
write_xyz(Optimizer.debugfile, s2, 'Second Cx Individual - Post')
return child1, child2
# Set up calculator
parcoff = '* * SiC.edip C Si'
pair_coeff = [parcoff]
mass = ['1 12.011','2 28.0855']
parameters = { 'pair_style' : 'edip', 'pair_coeff' : pair_coeff , 'mass' : mass, 'newton': 'on' }
mincomd = '1e-8 1e-8 5000 10000'
parameters['minimize'] = mincomd
filesL = [ 'SiC.edip' ]
calc = LAMMPS(parameters=parameters, files=filesL)
# Read File
structure = read_xyz('indiv00.xyz',-1)
# Calculate Energy
structure.set_cell([13.092,13.092,13.092])
structure.set_pbc(True)
structure.set_calculator(calc)
OUT=structure.calc.calculate(structure)
totalsol=OUT['atoms']
totalsol.set_pbc(True)
en=OUT['thermo'][-1]['pe']
#Write Relaxed Structure
write_xyz('re-relaxed.xyz',totalsol,repr(en))
fe = en
for sym,u in [('C',-7.371),('Si',-5.3062)]:
nc=len([atm for atm in structure if atm.symbol==sym])
fe-= float(nc)*float(u)
print 'SiC Interstitial'
print ' Potential Energy = '+repr(en)
print ' Formation Energy = '+repr(fe)
nchild1, nchild2 = cxtp(child1, child2, Optimizer)
passflag = True
except NameError, e:
logger.error(
"Error attempting to load back up cxTP Crossover. Something very wrong!! {1}".format(e), exc_info=True
)
print "CXTP Name Error: ", e
except Exception, e:
logger.error("Error in cxtp Crossover {0}".format(e), exc_info=True)
print "Exception: ", e
if passflag:
child1 = nchild1
child2 = nchild2
child1.energy = 0
child2.energy = 0
child1.fitness = 0
child2.fitness = 0
ch1hi = child1.history_index
child1.history_index = "(" + repr(child1.index) + "+" + repr(child2.index) + ")"
child2.history_index = "(" + repr(child2.index) + "+" + repr(child1.index) + ")"
if debug:
s1 = child1[0].copy()
s2 = child2[0].copy()
if Optimizer.structure == "Defect":
s1.extend(child1.bulki.copy())
s2.extend(child2.bulki.copy())
write_xyz(Optimizer.debugfile, s1, "First Cx Individual - Post")
write_xyz(Optimizer.debugfile, s2, "Second Cx Individual - Post")
return child1, child2
'pair_style': 'edip',
'pair_coeff': pair_coeff,
'mass': mass,
'newton': 'on'
}
mincomd = '1e-8 1e-8 5000 10000'
parameters['minimize'] = mincomd
filesL = ['SiC.edip']
calc = LAMMPS(parameters=parameters, files=filesL)
# Read File
structure = read_xyz('indiv00.xyz', -1)
# Calculate Energy
structure.set_cell([13.092, 13.092, 13.092])
structure.set_pbc(True)
structure.set_calculator(calc)
OUT = structure.calc.calculate(structure)
totalsol = OUT['atoms']
totalsol.set_pbc(True)
en = OUT['thermo'][-1]['pe']
#Write Relaxed Structure
write_xyz('re-relaxed.xyz', totalsol, repr(en))
fe = en
for sym, u in [('C', -7.371), ('Si', -5.3062)]:
nc = len([atm for atm in structure if atm.symbol == sym])
fe -= float(nc) * float(u)
print 'SiC Interstitial'
print ' Potential Energy = ' + repr(en)
print ' Formation Energy = ' + repr(fe)
def find_defects(solid,
bulko,
rcutoff,
atomlistcheck=False,
trackvacs=False,
trackswaps=False,
debug=False,
dcheck=0.6):
"""Function to find interstitials, vacancies, and substitutional atoms (swaps) in a defected structure.
Identifies species by comparison to perfect structure.
Inputs:
solid = ASE atoms class for defected structure
bulko = ASE atoms class for perfect structure
rcutoff = float value of distance to surrounding atoms to include
atomlistcheck = False/list of atom types and concentrations according to atomlist format
trackvacs = True/False whether or not to identify vacancies in defect
trackswaps = True/False whether or not to identify substitutional defects
debug = False/file object to write debug structures"""
# Combine perfect and defect structures together
b = bulko.copy()
b.extend(solid)
b.set_pbc(True)
#Debug: Write solid and bulko to file
if debug:
print len(bulko)
write_xyz(debug, b, 'Find Ints: Solid and Bulko')
# Identify nearest neighbor atoms for each atom in perfect structure
ntot = len(bulko)
ctoff1 = [1.2 for one in b]
nl = NeighborList(ctoff1, bothways=True, self_interaction=False)
nl.update(b)
slist = []
blist = []
wlist = []
#Loop over each atom in perfect structure
for one in range(ntot):
indices, offsets = nl.get_neighbors(one)
for index, d in zip(indices, offsets):
index = int(index)
if index >= ntot:
pos = b[index].position + numpy.dot(d, bulko.get_cell())
natm1 = Atom(position=pos)
dist, dx, dy, dz = calc_dist(b[one], natm1)
if dist <= dcheck:
#Assume atoms closer than 0.6 Angstroms to be equivalent
slist.append(index - ntot)
blist.append(one)
if b[one].symbol == b[index].symbol:
wlist.append(index - ntot)
#Identify those atoms corresponding to interstitials, vacancies, and substitutions
oslist = [atm.index for atm in solid if atm.index not in slist]
vlist = [atm.index for atm in bulko if atm.index not in blist]
swlist = [
atm.index for atm in solid
if atm.index not in wlist and atm.index not in oslist
]
# Create Atoms objects for each identified defect
ntot = len(solid)
cluster = Atoms()
for one in oslist:
cluster.append(solid[one])
vacant = Atoms()
if trackvacs == True:
for one in vlist:
vacant.append(
Atom(symbol=bulko[one].symbol, position=bulko[one].position))
solid.append(Atom(symbol='X', position=bulko[one].position))
oslist.append(len(solid) - 1)
stro = 'Cluster Identified with length = {0}\nIdentified {1} vacancies\n'.format(
len(cluster), len(vlist))
swaps = Atoms()
if trackswaps == True:
for one in swlist:
swaps.append(solid[one])
oslist.append(one)
stro = 'Cluster Identified with length = {0}\nIdentified {1} swaps\n'.format(
len(cluster), len(swlist))
else:
stro = 'Cluster Identified with length = {0}\n'.format(len(cluster))
#Debug: write cluster to file
if debug:
b = cluster.copy()
write_xyz(debug, b, 'Find Ints: Cluster')
debug.flush()
print 'Found cluster size = ', len(b)
# Identify atoms surrounding the identified defects in the defected structure
box = Atoms()
bulki = Atoms()
if rcutoff != 0:
if rcutoff > 2.0:
cutoffs = [rcutoff for one in solid]
else:
cutoffs = [2.0 for one in solid]
solid.set_pbc(True)
nl = NeighborList(cutoffs, bothways=True, self_interaction=False)
nl.update(solid)
nbatmsd = []
repinds = []
for one in oslist:
if one not in repinds:
if one < ntot:
nbatmsd.append((0, one))
repinds.append(one)
for one in oslist:
indices, offsets = nl.get_neighbors(one)
for index, d in zip(indices, offsets):
index = int(index)
if index not in repinds and index < ntot:
opos = copy.copy(solid[index].position)
solid[index].position = solid[index].position + numpy.dot(
d, solid.get_cell())
dist = solid.get_distance(one, index)
solid[index].position = opos
if dist <= rcutoff:
nbatmsd.append((dist, index))
repinds.append(index)
else:
nbatmsd = []
repinds = []
for one in oslist:
if one not in repinds:
if one < ntot:
nbatmsd.append((0, one))
repinds.append(one)
nbatmsd = sorted(nbatmsd, key=lambda one: one[0], reverse=True)
indices = []
natomsbox = 0
# Select only atoms closest to defects that satisfy concentrations specified by atomlist given in atomlistcheck
if atomlistcheck:
for sym, c, m, u in atomlistcheck:
i = 0
nbsym = [one for one in nbatmsd if solid[one[1]].symbol == sym]
if len(nbsym) > c:
while i < c:
a = nbsym.pop()
box.append(solid[a[1]])
indices.append(a[1])
i += 1
else:
for a in nbsym:
box.append(solid[a[1]])
indices.append(a[1])
i += 1
if len(box) - natomsbox < c:
try:
while True:
for n in range(len(nbatmsd) - 1, -1, -1):
inds, offsets = nl.get_neighbors(nbatmsd[n][1])
for one, d in zip(inds, offsets):
if len(box) - natomsbox < c:
if one not in indices and one < ntot and solid[
one].symbol == sym:
opos = copy.copy(
solid[one].position)
solid[one].position = solid[
one].position + numpy.dot(
d, solid.get_cell())
dist = solid.get_distance(
nbatmsd[n][1], one)
solid[one].position = opos
if dist <= rcutoff * 5.0:
box.append(solid[one])
indices.append(one)
else:
raise StopIteration()
for one, d in zip(inds, offsets):
if len(box) - natomsbox < c:
if one not in indices and one < ntot and solid[
one].symbol == sym:
opos = copy.copy(
solid[one].position)
solid[one].position = solid[
one].position + numpy.dot(
d, solid.get_cell())
dist = solid.get_distance(
nbatmsd[n][1], one)
solid[one].position = opos
box.append(solid[one])
indices.append(one)
else:
raise StopIteration()
except StopIteration:
pass
natomsbox = len(box)
#Double check for sanity
for sym, c, m, u in atomlistcheck:
symsbox = [one for one in box if one.symbol == sym]
if len(symsbox) != c:
stro += 'WARNING!!!! : FAILURE IN FIND_DEFECTS TO MATCH PROVIDED ATOMLIST. DEBUG!!!!\n'
# If atomlistcheck is False then use all the atoms in the given cutoff distance
else:
for a in nbatmsd:
box.append(solid[a[1]])
indices.append(a[1])
# Add remaining atoms in defect to defected bulk atoms object
for one in range(len(solid)):
if one not in indices and one < ntot:
bulki.append(solid[one])
#Check for accidental vacancy admissions
#checklist=[atm for atm in box if atm.symbol=='X']
#checklist.extend([atm for atm in bulki if atm.symbol=='X'])
#Set up new individual
indiv = box.copy()
bulki.set_cell(bulko.get_cell())
indiv.set_cell(bulko.get_cell())
bulki.set_pbc(True)
indiv.set_pbc(True)
stro += 'Atomlist check = {0}\n'.format(atomlistcheck)
stro += 'Bulko = {0}\n'.format(bulko)
stro += 'New individual ({0} atoms) : {1}\n'.format(len(indiv), indiv)
stro += 'New bulki ({0} atoms) : {1}\n'.format(len(bulki), bulki)
#Debug: write new indiv to file
if debug:
b = indiv.copy()
write_xyz(debug, b, 'Find Ints: New Individual')
#Debug: write new bulki to file
b = bulki.copy()
write_xyz(debug, b, 'Find Ints: New Bulki')
debug.flush()
print len(bulko)
return indiv, bulki, vacant, swaps, stro
def find_defects(solid, bulko, rcutoff, atomlistcheck=False, trackvacs=False, trackswaps=False, debug=False, dcheck = 0.6):
"""Function to find interstitials, vacancies, and substitutional atoms (swaps) in a defected structure.
Identifies species by comparison to perfect structure.
Inputs:
solid = ASE atoms class for defected structure
bulko = ASE atoms class for perfect structure
rcutoff = float value of distance to surrounding atoms to include
atomlistcheck = False/list of atom types and concentrations according to atomlist format
trackvacs = True/False whether or not to identify vacancies in defect
trackswaps = True/False whether or not to identify substitutional defects
debug = False/file object to write debug structures"""
# Combine perfect and defect structures together
b = bulko.copy()
b.extend(solid)
b.set_pbc(True)
#Debug: Write solid and bulko to file
if debug:
print len(bulko)
write_xyz(debug,b,'Find Ints: Solid and Bulko')
# Identify nearest neighbor atoms for each atom in perfect structure
ntot = len(bulko)
ctoff1 = [1.2 for one in b]
nl = NeighborList(ctoff1, bothways=True, self_interaction=False)
nl.update(b)
slist = []
blist = []
wlist = []
#Loop over each atom in perfect structure
for one in range(ntot):
indices, offsets = nl.get_neighbors(one)
for index, d in zip(indices,offsets):
index = int(index)
if index >= ntot:
pos = b[index].position + numpy.dot(d,bulko.get_cell())
natm1 = Atom(position=pos)
dist, dx, dy, dz = calc_dist(b[one],natm1)
if dist <= dcheck:
#Assume atoms closer than 0.6 Angstroms to be equivalent
slist.append(index-ntot)
blist.append(one)
if b[one].symbol == b[index].symbol:
wlist.append(index-ntot)
#Identify those atoms corresponding to interstitials, vacancies, and substitutions
oslist = [atm.index for atm in solid if atm.index not in slist]
vlist = [atm.index for atm in bulko if atm.index not in blist]
swlist = [atm.index for atm in solid if atm.index not in wlist and atm.index not in oslist]
# Create Atoms objects for each identified defect
ntot = len(solid)
cluster = Atoms()
for one in oslist:
cluster.append(solid[one])
vacant = Atoms()
if trackvacs==True:
for one in vlist:
vacant.append(Atom(symbol=bulko[one].symbol, position=bulko[one].position))
solid.append(Atom(symbol='X', position=bulko[one].position))
oslist.append(len(solid)-1)
stro = 'Cluster Identified with length = {0}\nIdentified {1} vacancies\n'.format(len(cluster),len(vlist))
swaps = Atoms()
if trackswaps==True:
for one in swlist:
swaps.append(solid[one])
oslist.append(one)
stro = 'Cluster Identified with length = {0}\nIdentified {1} swaps\n'.format(len(cluster),len(swlist))
else:
stro = 'Cluster Identified with length = {0}\n'.format(len(cluster))
#Debug: write cluster to file
if debug:
b = cluster.copy()
write_xyz(debug,b,'Find Ints: Cluster')
debug.flush()
print 'Found cluster size = ',len(b)
# Identify atoms surrounding the identified defects in the defected structure
box=Atoms()
bulki=Atoms()
if rcutoff != 0:
if rcutoff > 2.0:
cutoffs = [rcutoff for one in solid]
else:
cutoffs = [2.0 for one in solid]
solid.set_pbc(True)
nl = NeighborList(cutoffs,bothways=True,self_interaction=False)
nl.update(solid)
nbatmsd = []
repinds = []
for one in oslist:
if one not in repinds:
if one < ntot:
nbatmsd.append((0,one))
repinds.append(one)
indices, offsets = nl.get_neighbors(one)
for index,d in zip(indices,offsets):
index = int(index)
if index not in repinds and index < ntot:
opos = copy.copy(solid[index].position)
solid[index].position = solid[index].position + numpy.dot(d,solid.get_cell())
dist = solid.get_distance(one,index)
solid[index].position = opos
if dist <= rcutoff:
nbatmsd.append((dist,index))
repinds.append(index)
else:
nbatmsd = []
repinds = []
for one in oslist:
if one not in repinds:
if one < ntot:
nbatmsd.append((0,one))
repinds.append(one)
nbatmsd=sorted(nbatmsd, key=lambda one:one[0], reverse=True)
indices=[]
i=0
# Select only atoms closest to defects that satisfy concentrations specified by atomlist given in atomlistcheck
if atomlistcheck:
natomsbox=sum([c for sym,c,m,u in atomlistcheck])
if len(nbatmsd) > natomsbox:
while i<natomsbox:
a=nbatmsd.pop()
box.append(solid[a[1]])
indices.append(a[1])
i+=1
elif len(nbatmsd) <= natomsbox:
for a in nbatmsd:
box.append(solid[a[1]])
indices.append(a[1])
i+=1
if len(box) < natomsbox:
try:
while True:
for n in range(len(nbatmsd)-1,-1,-1):
inds, offsets=nl.get_neighbors(nbatmsd[n][1])
for one,d in zip(inds,offsets):
if len(box) < natomsbox:
if one not in indices and one < ntot:
opos = copy.copy(solid[one].position)
solid[one].position = solid[one].position + numpy.dot(d,solid.get_cell())
dist = solid.get_distance(nbatmsd[n][1],one)
solid[one].position = opos
if dist <= rcutoff*5.0:
box.append(solid[one])
indices.append(one)
else:
raise StopIteration()
for one,d in zip(inds,offsets):
if len(box) < natomsbox:
if one not in indices and one < ntot:
opos = copy.copy(solid[one].position)
solid[one].position = solid[one].position + numpy.dot(d,solid.get_cell())
dist = solid.get_distance(nbatmsd[n][1],one)
solid[one].position = opos
box.append(solid[one])
indices.append(one)
else:
raise StopIteration()
except StopIteration:
pass
# If atomlistcheck is False then use all the atoms in the given cutoff distance
else:
for a in nbatmsd:
box.append(solid[a[1]])
indices.append(a[1])
# Add remaining atoms in defect to defected bulk atoms object
for one in range(len(solid)):
if one not in indices and one < ntot:
bulki.append(solid[one])
#Check for accidental vacancy admissions
#checklist=[atm for atm in box if atm.symbol=='X']
#checklist.extend([atm for atm in bulki if atm.symbol=='X'])
#Set up new individual
indiv=box.copy()
bulki.set_cell(bulko.get_cell())
indiv.set_cell(bulko.get_cell())
bulki.set_pbc(True)
indiv.set_pbc(True)
stro+='New individual ({0} atoms) : {1}\n'.format(len(indiv), indiv)
stro+='New bulki ({0} atoms) : {1}\n'.format(len(bulki), bulki)
#Debug: write new indiv to file
if debug:
b=indiv.copy()
write_xyz(debug,b,'Find Ints: New Individual')
#Debug: write new bulki to file
b=bulki.copy()
write_xyz(debug,b,'Find Ints: New Bulki')
debug.flush()
print len(bulko)
return indiv,bulki,vacant,swaps,stro
def BestInds(pop, bests, Optimizer, writefile=False, fname=None):
"""Function to keep track of the best individuals throughout an optimization
Inputs:
pop = list of Individual class structures to be compared
bests = list of previously obtained best structures
Optimizer = Optimizer class structure that contains key parameters
writefile = True/False boolean to tell function whether or not to output structures
fname = filename to output structures
Outputs:
bests = list of Individual class structures updated with new options
"""
#logger = initialize_logger(Optimizer.loggername)
logger = logging.getLogger(Optimizer.loggername)
logger.info(
'best_inds_list recieved population with length = {0} and best list with length = {1} for generation {2}'
.format(len(pop), len(bests), Optimizer.generation))
pop = sorted(pop, key=attrgetter('fitness'))
tol = Optimizer.demin
if len(bests) != 0:
bfits = [ind.fitness for ind in bests]
#Identify the fitnesses in the population
popfits = [ind.fitness for ind in pop]
#Initialize a list for individuals to not be added to best list
indices = []
for i in range(len(popfits)):
for j in range(len(bfits)):
if popfits[i] == bfits[j]:
indices.append(i)
if popfits[i] < bfits[j]:
diff = abs(bfits[j] - popfits[i])
diff2 = abs(bfits[j - 1] - popfits[i])
if diff > tol:
if diff2 > tol:
if i not in indices:
bests.append(pop[i])
logger.info(
'Best list found new structure for List HI = {0}'
.format(pop[i].history_index))
indices.append(i)
b = bfits[0:j]
b.append(pop[i].fitness)
b.extend(bfits[j::])
bfits = b
else:
indices.append(i)
bests = sorted(bests, key=attrgetter('fitness'))
if len(bests) < Optimizer.number_of_bests:
bmax = bests[len(bests) - 1].fitness
for i in range(len(popfits)):
if popfits[i] > bmax:
diff = abs(popfits[i] - bmax)
if diff > tol:
bests.append(pop[i])
logger.info(
'Appending best list with lower energy structure')
bmax = pop[i].fitness
else:
logger.info('Removing extra {0} structures from best list'.format(
len(bests) - Optimizer.number_of_bests))
bests = bests[0:Optimizer.number_of_bests]
bfits = [ind.fitness for ind in bests]
else:
bests = []
bfits = []
for one in pop:
fit = one.fitness
if len(bfits) == 0:
bests.append(one)
logger.info(
'Adding new structure to best list HI = {0}'.format(
one.history_index))
bfits.append(fit)
else:
diff = abs(bfits[-1] - fit)
if diff > tol:
bests.append(one)
bfits.append(fit)
if len(bests) > Optimizer.number_of_bests:
logger.info('Removing extra {0} structures from best list'.format(
len(bests) - Optimizer.number_of_bests))
bests = bests[0:Optimizer.number_of_bests]
if writefile == True:
if fname == None:
try:
rank = MPI.COMM_WORLD.Get_rank()
except:
rank = 0
path = os.path.join(os.getcwd(),
'{0}-rank{1}'.format(Optimizer.filename, rank))
logger.info('Writing Best lists to {0}'.format(path))
fxyzname = os.path.join(path,
'Bests-{0}.xyz'.format(Optimizer.filename))
ffitname = os.path.join(
path, 'Bests-fitnesses-{0}.txt'.format(Optimizer.filename))
else:
fxyzname = '{0}.xyz'.format(fname)
ffitname = '{0}-fitnesses.txt'.format(fname)
bestfile = open(fxyzname, 'w')
bestfitfile = open(ffitname, 'w')
for one in bests:
if Optimizer.structure == 'Defect':
cbulk = Atoms()
cbulk.extend(one[0])
cbulk.extend(one.bulki)
write_xyz(bestfile, cbulk, one.energy)
else:
write_xyz(bestfile, one[0], one.energy)
bestfitfile.write(repr(one.fitness) + '\n')
bestfile.close()
bestfitfile.close()
return bests
def write_individual(individ, indivfile):
"""Function to write the data of an individual class object to a flat file
Input:
individ = Individual class object to be written
indivfile = String or fileobject for file to be written to
Output:
No output returned. Information is written to file
"""
if isinstance(indivfile, str):
indivfile = open(indivfile, 'a')
#Write break
indivfile.write('----------\n')
#Write structure information
indivfile.write('Structure information\n')
write_xyz(indivfile, individ[0])
indivfile.write('structure cell = {0}\n'.format(get_atom_cell(individ[0])))
#Write additional information
indivfile.write('fitness = {0}\n'.format(individ.fitness))
indivfile.write('index = {0}\n'.format(individ.index))
indivfile.write('history_index = {0}\n'.format(individ.index))
indivfile.write('energy = {0}\n'.format(individ.energy))
indivfile.write('tenergymx = {0}\n'.format(individ.tenergymx))
indivfile.write('tenergymin = {0}\n'.format(individ.tenergymin))
indivfile.write('pressure = {0}\n'.format(individ.pressure))
indivfile.write('volume = {0}\n'.format(individ.volume))
indivfile.write('force = {0}\n'.format(individ.force))
indivfile.write('purebulkenpa = {0}\n'.format(individ.purebulkenpa))
indivfile.write('natomsbulk = {0}\n'.format(individ.natomsbulk))
indivfile.write('fingerprint = {0}\n'.format(individ.fingerprint))
indivfile.write('swaplist = {0}\n'.format(individ.swaplist))
#Write additional structure information
indivfile.write('bulki\n')
write_xyz(indivfile, individ.bulki)
indivfile.write('bulki cell = {0}\n'.format(get_atom_cell(individ.bulki)))
indivfile.write('bulko\n')
write_xyz(indivfile, individ.bulko)
indivfile.write('bulko cell = {0}\n'.format(get_atom_cell(individ.bulko)))
indivfile.write('box\n')
write_xyz(indivfile, individ.box)
indivfile.write('box cell = {0}\n'.format(get_atom_cell(individ.box)))
indivfile.write('vacancies\n')
write_xyz(indivfile, individ.vacancies)
indivfile.write('vacancies cell = {0}\n'.format(
get_atom_cell(individ.vacancies)))
indivfile.write('swaps\n')
write_xyz(indivfile, individ.swaps)
indivfile.write('swaps cell = {0}\n'.format(get_atom_cell(individ.swaps)))
indivfile.write('Finish')
indivfile.close()
return
def formationenergy(indiv, Optimizer):
"""Function to calculate formation energy fitness of individual.
Input:
indiv = structopt Individual class object to be evaluated
Optimizer = structopt Optimizer class object
Output:
indiv = structopt Individual class object with new fitness.
"""
if Optimizer.structure != 'Defect':
if Optimizer.generation <1:
print 'WARNING: Formation Energy fitness calculator only available for Defect structure simulation.'
print ' Using total energy fitness calculator instead'
indiv = totalenfit(indiv,Optimizer)
stro = ''
else:
logger = logging.getLogger(Optimizer.loggername)
#logger = initialize_logger(Optimizer.loggername)
starting = indiv.duplicate()
cwd = os.getcwd()
try:
outs = eval_energy(Optimizer,indiv)
except Exception, e:
logger.warn('Error in energy evaluation: {0}'.format(e), exc_info=True)
stro = 'ERROR: Problem in Energy Evaluation'
print stro
print e
stro += '\n' + repr(e)
os.chdir(cwd)
f=open('problem-structures.xyz','a')
totalsol = indiv[0].copy()
totalsol.extend(indiv.bulki)
write_xyz(f,totalsol,data='Starting structure hindex={0}'.format(indiv.history_index))
indiv.energy = 10000
f.close()
print ' Writing structure to problemstructures.xyz file. Structure (hindex) : '+indiv.history_index
print ' Setting individual energy to 50000.'
outs = [10000, starting.bulki, starting, stro]
indiv.energy = outs[0]
stro=outs[3]
indiv.bulki = outs[1]
#fit = (indiv.purebulkenpa*(indiv[0].get_number_of_atoms()+indiv.bulki.get_number_of_atoms()) - indiv.energy)/(indiv[0].get_number_of_atoms()+indiv.bulki.get_number_of_atoms()-indiv.natomsbulk)
solid=Atoms()
solid.extend(indiv[0])
solid.extend(indiv.bulki)
fit=indiv.energy
passflag = True
if abs(fit) > Optimizer.energy_cutoff_factor*(len(indiv[0])+len(indiv.bulki)):
fit=10000
message = 'Warning: Found oddly large energy from Lammps in structure HI={0}'.format(indiv.history_index)
logger.warn(message)
print message
print ' Setting fitness to 10000'
passflag=False
if math.isnan(fit):
logger.warn('Found NAN energy structure HI={0}'.format(indiv.history_index))
fit=10000
passflag=False
indiv.energy = 10000
if passflag:
for sym,c,m,u in Optimizer.atomlist:
nc=len([atm for atm in solid if atm.symbol==sym])
fit-= float(nc)*float(u)
indiv.fitness=fit
def eval_energy(Optimizer, individ):
"""Function to evaluate energy of an individual
Inputs:
input = [Optimizer class object with parameters, Individual class structure to be evaluated]
Outputs:
energy, bul, individ, signal
energy = energy of Individual evaluated
bul = bulk structure of Individual if simulation structure is Defect
individ = Individual class structure evaluated
signal = string of information about evaluation
"""
#logger = initialize_logger(Optimizer.loggername)
logger = logging.getLogger(Optimizer.loggername)
if 'MAST' in Optimizer.calc_method:
energy = individ.energy
bul = individ.bulki
signal = 'Received MAST structure\n'
logger.info('Received individual index = {0} from MAST with energy {1}. Returning with no evaluation'.format(
individ.index, individ.energy))
else:
if Optimizer.parallel:
rank = MPI.COMM_WORLD.Get_rank()
logger.info('Received individual HI = {0} with energy {1} for energy evaluation'.format(
individ.history_index, individ.energy))
STR='----Individual ' + str(individ.history_index)+ ' Optimization----\n'
indiv=individ[0]
if 'EE' in Optimizer.debug:
debug = True
else:
debug = False
if debug:
write_xyz(Optimizer.debugfile,indiv,'Received by eval_energy')
Optimizer.debugfile.flush()
logger.debug('Writing recieved individual to debug file')
# Establish individual structure for evaluation. Piece together regions when necessary.
if Optimizer.structure=='Defect':
indi=indiv.copy()
bulk=individ.bulki
nat=indi.get_number_of_atoms()
if debug:
logger.info('Extending defect structure to include bulk len(r1+r2)={0} len(bulk)={1}'.format(nat,len(bulk)))
csize=bulk.get_cell()
totalsol=Atoms(cell=csize, pbc=True)
totalsol.extend(indi)
totalsol.extend(bulk)
for sym,c,m,u in Optimizer.atomlist:
nc=len([atm for atm in totalsol if atm.symbol==sym])
STR+='Defect configuration contains '+repr(nc)+' '+repr(sym)+' atoms\n'
elif Optimizer.structure=='Surface':
totalsol=Atoms()
totalsol.extend(indiv)
nat=indiv.get_number_of_atoms()
totalsol.extend(individ.bulki)
if debug:
logger.info('Extending surface structure to include bulk len(r1+r2)={0} len(bulk)={1}'.format(nat,len(individ.bulki)))
for sym,c,m,u in Optimizer.atomlist:
nc=len([atm for atm in totalsol if atm.symbol==sym])
STR+='Surface-Bulk configuration contains '+repr(nc)+' '+repr(sym)+' atoms\n'
cell=numpy.maximum.reduce(indiv.get_cell())
totalsol.set_cell([cell[0],cell[1],500])
totalsol.set_pbc([True,True,False])
elif Optimizer.structure=='Cluster':
totalsol = indiv.copy()
nat = len(totalsol)
if debug:
logger.info('Extending cluster with {0} atoms to center of evaluation box of size {1}'.format(nat,Optimizer.large_box_size))
origcell = indiv.get_cell()
totalsol.set_cell([Optimizer.large_box_size,Optimizer.large_box_size,Optimizer.large_box_size])
totalsol.translate([Optimizer.large_box_size/2.0,Optimizer.large_box_size/2.0,Optimizer.large_box_size/2.0])
elif Optimizer.structure=='Crystal':
totalsol = indiv.copy()
nat = len(totalsol)
else:
print 'WARNING: In EvalEnergy. Optimizer.structure not recognized'
logger.warning('Optimizer.structure not recognized')
# Check for atoms that are too close or out of constrained location
if Optimizer.constrain_position:
if Optimizer.structure=='Defect':
if debug:
logger.info('Constraining positions of defect')
totalsol, stro = constrain_positions(totalsol, Optimizer.solidbulk, Optimizer.sf)
if debug:
logger.info(stro)
STR+=str0
min_len=0.7
if not Optimizer.fixed_region:
if debug:
logger.info('Running check minimum distance')
totalsol, STR = check_min_dist(totalsol, Optimizer.structure, nat, min_len, STR)
if debug:
write_xyz(Optimizer.debugfile,totalsol,'After minlength check')
Optimizer.debugfile.flush()
logger.debug('Writing individual after checking minimum length')
# Set calculator to use to get forces/energies
if Optimizer.parallel:
calc = setup_calculator(Optimizer)
if Optimizer.fixed_region:
if debug:
logger.info('Setting up fixed region calculator')
pms=copy.deepcopy(calc.parameters)
try:
pms['mass'][len(pms['mass'])-1] += '\ngroup RO id >= {0}\nfix freeze RO setforce 0.0 0.0 0.0\n'.format(nat)
except KeyError:
pms['pair_coeff'][0] += '\ngroup RO id >= {0}\nfix freeze RO setforce 0.0 0.0 0.0\n'.format(nat)
calc = LAMMPS(parameters=pms, files=calc.files, keep_tmp_files=calc.keep_tmp_files, tmp_dir=calc.tmp_dir)
lmin = copy.copy(Optimizer.lammps_min)
if debug:
logger.info('Setting up no local minimization calculator')
Optimizer.lammps_min = None
Optimizer.static_calc = setup_calculator(Optimizer)
Optimizer.lammps_min = lmin
else:
calc=Optimizer.calc
totalsol.set_calculator(calc)
totalsol.set_pbc(True)
# Perform Energy Minimization
if not Optimizer.parallel:
if debug:
write_xyz(Optimizer.debugfile,totalsol,'Individual sent to Energy Minimizer')
logger.debug('Writing structure sent to energy minimizer')
try:
cwd = os.getcwd()
if Optimizer.ase_min == True:
if debug:
logger.info('Running ASE minimizer')
if Optimizer.calc_method=='LennardJones':
logger.warn('Must run ase LJ calculator with pbc=False')
totalsol.set_pbc(False)
totalsol, energy, pressure, volume, STR = run_ase_min(totalsol, Optimizer.ase_min_fmax, Optimizer.ase_min_maxsteps, Optimizer.fitness_scheme, STR)
else:
if debug:
logger.info('Running local energy calculator')
if Optimizer.fixed_region:
totalsol, energy, pressure, volume, STR = run_energy_eval(totalsol, Optimizer.calc_method, Optimizer.fixed_region, Optimizer.fitness_scheme, STR, Optimizer.static_calc)
else:
totalsol, energy, pressure, volume, STR = run_energy_eval(totalsol, Optimizer.calc_method, False, Optimizer.fitness_scheme, STR)
except Exception, e:
logger.critical('Error in energy evaluation: {0}'.format(e), exc_info=True)
path = os.path.join(cwd,'TroubledLammps')
if not os.path.exists(path):
os.mkdir(path)
#Copy files over
shutil.copyfile(calc.trajfile,os.path.join(path,os.path.basename(calc.trajfile)))
shutil.copyfile(calc.infile,os.path.join(path,os.path.basename(calc.infile)))
shutil.copyfile(calc.logfile,os.path.join(path,os.path.basename(calc.logfile)))
shutil.copyfile(calc.datafile,os.path.join(path,os.path.basename(calc.datafile)))
raise RuntimeError('{0}:{1}'.format(Exception,e))
if not Optimizer.parallel:
if debug:
write_xyz(Optimizer.debugfile,totalsol,'Individual after Energy Minimization')
Optimizer.debugfile.flush()
logger.debug('Writing structure recieved from energy minimizer')
# Separate structures into distinct pieces
if Optimizer.structure=='Defect':
if Optimizer.fixed_region==True or Optimizer.finddefects==False:
if debug:
logger.info('Identifying atoms in defect structure based on ID')
individ[0]=totalsol[0:nat]
bul=totalsol[(nat):len(totalsol)]
individ[0].set_cell(csize)
else:
if debug:
logger.info('Applying find defects scheme to identify R1 and R2 for Defect')
if 'FD' in Optimizer.debug:
outt=find_defects(totalsol,Optimizer.solidbulk,Optimizer.sf,atomlistcheck=Optimizer.atomlist,trackvacs=Optimizer.trackvacs,trackswaps=Optimizer.trackswaps,debug=Optimizer.debugfile)
else:
outt=find_defects(totalsol,Optimizer.solidbulk,Optimizer.sf,atomlistcheck=Optimizer.atomlist,trackvacs=Optimizer.trackvacs,trackswaps=Optimizer.trackswaps,debug=False)
individ[0]=outt[0]
bul=outt[1]
individ.vacancies = outt[2]
individ.swaps = outt[3]
STR += outt[4]
indiv=individ[0]
elif Optimizer.structure=='Surface':
if debug:
logger.info('Finding surface top layer')
top,bul=find_top_layer(totalsol,Optimizer.surftopthick)
indiv=top.copy()
individ[0]=top.copy()
bul = Atoms()
elif Optimizer.structure=='Crystal':
if debug:
logger.info('Checking crystal cell type')
celltype = check_cell_type(totalsol)
STR+='Cell structure = {0}\n'.format(celltype)
bul = Atoms()
individ[0] = totalsol.copy()
elif Optimizer.structure=='Cluster':
volume = get_cluster_volume(totalsol)
bul = Atoms()
if debug:
logger.info('Translating cluster back to smaller box size location')
totalsol.translate([-Optimizer.large_box_size/2.0,-Optimizer.large_box_size/2.0,-Optimizer.large_box_size/2.0])
totalsol.set_cell(origcell)
individ[0] = totalsol.copy()
# Add concentration energy dependence
if Optimizer.forcing=='energy_bias':
if debug:
logger.info('Applying energy bias for atoms with different number of atoms of type than in atomlist')
n=[0]*len(Optimizer.atomlist)
for i in range(len(Optimizer.atomlist)):
n[i]=len([inds for inds in totalsol if inds.symbol==Optimizer.atomlist[i][0]])
n[i]=abs(n[i]-Optimizer.atomlist[i][1])
factor=sum(n)**3
energy=(energy+factor)/totalsol.get_number_of_atoms()
STR+='Energy with Bias = {0}\n'.format(energy)
elif Optimizer.forcing=='chem_pot':
if debug:
logger.info('Applying chemical potential bias for atoms with different number of atoms of type than in atomlist')
n=[0]*len(Optimizer.atomlist)
for i in range(len(Optimizer.atomlist)):
n[i]=len([inds for inds in totalsol if inds.symbol==Optimizer.atomlist[i][0]])
n[i]=n[i]*Optimizer.atomlist[i][3]
factor=sum(n)
energy=(energy+factor)/totalsol.get_number_of_atoms()
STR+='Energy with Chemical Potential = {0}\n'.format(energy)
individ.energy=energy
individ.buli=bul
individ.pressure=pressure
individ.volume=volume
if Optimizer.fingerprinting:
if debug:
logger.info('Identifying fingerprint of new structure')
individ.fingerprint=get_fingerprint(Optimizer,individ,Optimizer.fpbin,Optimizer.fpcutoff)
if Optimizer.parallel:
calc.clean()
signal = 'Evaluated individual {0} on {1}\n'.format(individ.index,rank)
signal +=STR
else:
signal=STR
def eval_energy(Optimizer, individ):
"""Function to evaluate energy of an individual
Inputs:
input = [Optimizer class object with parameters, Individual class structure to be evaluated]
Outputs:
energy, bul, individ, signal
energy = energy of Individual evaluated
bul = bulk structure of Individual if simulation structure is Defect
individ = Individual class structure evaluated
signal = string of information about evaluation
"""
#logger = initialize_logger(Optimizer.loggername)
logger = logging.getLogger(Optimizer.loggername)
if 'MAST' in Optimizer.calc_method:
energy = individ.energy
bul = individ.bulki
signal = 'Received MAST structure\n'
logger.info(
'Received individual index = {0} from MAST with energy {1}. Returning with no evaluation'
.format(individ.index, individ.energy))
else:
if Optimizer.parallel:
rank = MPI.COMM_WORLD.Get_rank()
logger.info(
'Received individual HI = {0} with energy {1} for energy evaluation'
.format(individ.history_index, individ.energy))
STR = '----Individual ' + str(
individ.history_index) + ' Optimization----\n'
indiv = individ[0]
if 'EE' in Optimizer.debug:
debug = True
else:
debug = False
if debug:
write_xyz(Optimizer.debugfile, indiv, 'Received by eval_energy')
Optimizer.debugfile.flush()
logger.debug('Writing recieved individual to debug file')
# Establish individual structure for evaluation. Piece together regions when necessary.
if Optimizer.structure == 'Defect':
indi = indiv.copy()
bulk = individ.bulki
nat = indi.get_number_of_atoms()
if debug:
logger.info(
'Extending defect structure to include bulk len(r1+r2)={0} len(bulk)={1}'
.format(nat, len(bulk)))
csize = bulk.get_cell()
totalsol = Atoms(cell=csize, pbc=True)
totalsol.extend(indi)
totalsol.extend(bulk)
for sym, c, m, u in Optimizer.atomlist:
nc = len([atm for atm in totalsol if atm.symbol == sym])
STR += 'Defect configuration contains ' + repr(
nc) + ' ' + repr(sym) + ' atoms\n'
elif Optimizer.structure == 'Surface':
totalsol = Atoms()
totalsol.extend(indiv)
nat = indiv.get_number_of_atoms()
totalsol.extend(individ.bulki)
if debug:
logger.info(
'Extending surface structure to include bulk len(r1+r2)={0} len(bulk)={1}'
.format(nat, len(individ.bulki)))
for sym, c, m, u in Optimizer.atomlist:
nc = len([atm for atm in totalsol if atm.symbol == sym])
STR += 'Surface-Bulk configuration contains ' + repr(
nc) + ' ' + repr(sym) + ' atoms\n'
cell = numpy.maximum.reduce(indiv.get_cell())
totalsol.set_cell([cell[0], cell[1], 500])
totalsol.set_pbc([True, True, False])
elif Optimizer.structure == 'Cluster':
totalsol = indiv.copy()
nat = len(totalsol)
if debug:
logger.info(
'Extending cluster with {0} atoms to center of evaluation box of size {1}'
.format(nat, Optimizer.large_box_size))
origcell = indiv.get_cell()
totalsol.set_cell([
Optimizer.large_box_size, Optimizer.large_box_size,
Optimizer.large_box_size
])
totalsol.translate([
Optimizer.large_box_size / 2.0, Optimizer.large_box_size / 2.0,
Optimizer.large_box_size / 2.0
])
elif Optimizer.structure == 'Crystal':
totalsol = indiv.copy()
nat = len(totalsol)
else:
print 'WARNING: In EvalEnergy. Optimizer.structure not recognized'
logger.warning('Optimizer.structure not recognized')
# Check for atoms that are too close or out of constrained location
if Optimizer.constrain_position:
if Optimizer.structure == 'Defect':
if debug:
logger.info('Constraining positions of defect')
totalsol, stro = constrain_positions(totalsol,
Optimizer.solidbulk,
Optimizer.sf)
if debug:
logger.info(stro)
STR += str0
min_len = 0.7
if not Optimizer.fixed_region:
if debug:
logger.info('Running check minimum distance')
totalsol, STR = check_min_dist(totalsol, Optimizer.structure, nat,
min_len, STR)
if debug:
write_xyz(Optimizer.debugfile, totalsol,
'After minlength check')
Optimizer.debugfile.flush()
logger.debug(
'Writing individual after checking minimum length')
# Set calculator to use to get forces/energies
if Optimizer.parallel:
calc = setup_calculator(Optimizer)
if Optimizer.fixed_region:
if debug:
logger.info('Setting up fixed region calculator')
pms = copy.deepcopy(calc.parameters)
try:
pms['mass'][
len(pms['mass']) -
1] += '\ngroup RO id >= {0}\nfix freeze RO setforce 0.0 0.0 0.0\n'.format(
nat)
except KeyError:
pms['pair_coeff'][
0] += '\ngroup RO id >= {0}\nfix freeze RO setforce 0.0 0.0 0.0\n'.format(
nat)
calc = LAMMPS(parameters=pms,
files=calc.files,
keep_tmp_files=calc.keep_tmp_files,
tmp_dir=calc.tmp_dir)
lmin = copy.copy(Optimizer.lammps_min)
if debug:
logger.info('Setting up no local minimization calculator')
Optimizer.lammps_min = None
Optimizer.static_calc = setup_calculator(Optimizer)
Optimizer.lammps_min = lmin
else:
calc = Optimizer.calc
totalsol.set_calculator(calc)
totalsol.set_pbc(True)
# Perform Energy Minimization
if not Optimizer.parallel:
if debug:
write_xyz(Optimizer.debugfile, totalsol,
'Individual sent to Energy Minimizer')
logger.debug('Writing structure sent to energy minimizer')
try:
cwd = os.getcwd()
if Optimizer.ase_min == True:
if debug:
logger.info('Running ASE minimizer')
if Optimizer.calc_method == 'LennardJones':
logger.warn('Must run ase LJ calculator with pbc=False')
totalsol.set_pbc(False)
totalsol, energy, pressure, volume, STR = run_ase_min(
totalsol, Optimizer.ase_min_fmax,
Optimizer.ase_min_maxsteps, Optimizer.fitness_scheme, STR)
else:
if debug:
logger.info('Running local energy calculator')
if Optimizer.fixed_region:
totalsol, energy, pressure, volume, STR = run_energy_eval(
totalsol, Optimizer.calc_method,
Optimizer.fixed_region, Optimizer.fitness_scheme, STR,
Optimizer.static_calc)
else:
totalsol, energy, pressure, volume, STR = run_energy_eval(
totalsol, Optimizer.calc_method, False,
Optimizer.fitness_scheme, STR)
except Exception, e:
logger.critical('Error in energy evaluation: {0}'.format(e),
exc_info=True)
path = os.path.join(cwd, 'TroubledLammps')
if not os.path.exists(path):
os.mkdir(path)
#Copy files over
shutil.copyfile(
calc.trajfile,
os.path.join(path, os.path.basename(calc.trajfile)))
shutil.copyfile(calc.infile,
os.path.join(path, os.path.basename(calc.infile)))
shutil.copyfile(calc.logfile,
os.path.join(path, os.path.basename(calc.logfile)))
shutil.copyfile(
calc.datafile,
os.path.join(path, os.path.basename(calc.datafile)))
raise RuntimeError('{0}:{1}'.format(Exception, e))
if not Optimizer.parallel:
if debug:
write_xyz(Optimizer.debugfile, totalsol,
'Individual after Energy Minimization')
Optimizer.debugfile.flush()
logger.debug(
'Writing structure recieved from energy minimizer')
# Separate structures into distinct pieces
if Optimizer.structure == 'Defect':
if Optimizer.fixed_region == True or Optimizer.finddefects == False:
if debug:
logger.info(
'Identifying atoms in defect structure based on ID')
individ[0] = totalsol[0:nat]
bul = totalsol[(nat):len(totalsol)]
individ[0].set_cell(csize)
else:
if debug:
logger.info(
'Applying find defects scheme to identify R1 and R2 for Defect'
)
if 'FD' in Optimizer.debug:
outt = find_defects(totalsol,
Optimizer.solidbulk,
Optimizer.sf,
atomlistcheck=Optimizer.atomlist,
trackvacs=Optimizer.trackvacs,
trackswaps=Optimizer.trackswaps,
debug=Optimizer.debugfile)
else:
outt = find_defects(totalsol,
Optimizer.solidbulk,
Optimizer.sf,
atomlistcheck=Optimizer.atomlist,
trackvacs=Optimizer.trackvacs,
trackswaps=Optimizer.trackswaps,
debug=False)
individ[0] = outt[0]
bul = outt[1]
individ.vacancies = outt[2]
individ.swaps = outt[3]
STR += outt[4]
indiv = individ[0]
elif Optimizer.structure == 'Surface':
if debug:
logger.info('Finding surface top layer')
top, bul = find_top_layer(totalsol, Optimizer.surftopthick)
indiv = top.copy()
individ[0] = top.copy()
bul = Atoms()
elif Optimizer.structure == 'Crystal':
if debug:
logger.info('Checking crystal cell type')
celltype = check_cell_type(totalsol)
STR += 'Cell structure = {0}\n'.format(celltype)
bul = Atoms()
individ[0] = totalsol.copy()
elif Optimizer.structure == 'Cluster':
volume = get_cluster_volume(totalsol)
bul = Atoms()
if debug:
logger.info(
'Translating cluster back to smaller box size location')
totalsol.translate([
-Optimizer.large_box_size / 2.0,
-Optimizer.large_box_size / 2.0,
-Optimizer.large_box_size / 2.0
])
totalsol.set_cell(origcell)
individ[0] = totalsol.copy()
# Add concentration energy dependence
if Optimizer.forcing == 'energy_bias':
if debug:
logger.info(
'Applying energy bias for atoms with different number of atoms of type than in atomlist'
)
n = [0] * len(Optimizer.atomlist)
for i in range(len(Optimizer.atomlist)):
n[i] = len([
inds for inds in totalsol
if inds.symbol == Optimizer.atomlist[i][0]
])
n[i] = abs(n[i] - Optimizer.atomlist[i][1])
factor = sum(n)**3
energy = (energy + factor) / totalsol.get_number_of_atoms()
STR += 'Energy with Bias = {0}\n'.format(energy)
elif Optimizer.forcing == 'chem_pot':
if debug:
logger.info(
'Applying chemical potential bias for atoms with different number of atoms of type than in atomlist'
)
n = [0] * len(Optimizer.atomlist)
for i in range(len(Optimizer.atomlist)):
n[i] = len([
inds for inds in totalsol
if inds.symbol == Optimizer.atomlist[i][0]
])
n[i] = n[i] * Optimizer.atomlist[i][3]
factor = sum(n)
energy = (energy + factor) / totalsol.get_number_of_atoms()
STR += 'Energy with Chemical Potential = {0}\n'.format(energy)
individ.energy = energy
individ.buli = bul
individ.pressure = pressure
individ.volume = volume
if Optimizer.fingerprinting:
if debug:
logger.info('Identifying fingerprint of new structure')
individ.fingerprint = get_fingerprint(Optimizer, individ,
Optimizer.fpbin,
Optimizer.fpcutoff)
if Optimizer.parallel:
calc.clean()
signal = 'Evaluated individual {0} on {1}\n'.format(
individ.index, rank)
signal += STR
else:
signal = STR
def BestInds(pop, bests, Optimizer, writefile=False, fname=None):
"""Function to keep track of the best individuals throughout an optimization
Inputs:
pop = list of Individual class structures to be compared
bests = list of previously obtained best structures
Optimizer = Optimizer class structure that contains key parameters
writefile = True/False boolean to tell function whether or not to output structures
fname = filename to output structures
Outputs:
bests = list of Individual class structures updated with new options
"""
#logger = initialize_logger(Optimizer.loggername)
logger = logging.getLogger(Optimizer.loggername)
logger.info('best_inds_list recieved population with length = {0} and best list with length = {1} for generation {2}'.format(
len(pop),len(bests),Optimizer.generation))
pop = sorted(pop, key=attrgetter('fitness'))
tol=Optimizer.demin
if len(bests)!=0:
bfits=[ind.fitness for ind in bests]
#Identify the fitnesses in the population
popfits=[ind.fitness for ind in pop]
#Initialize a list for individuals to not be added to best list
indices=[]
for i in range(len(popfits)):
for j in range(len(bfits)):
if popfits[i]==bfits[j]:
indices.append(i)
if popfits[i] < bfits[j]:
diff = abs(bfits[j] - popfits[i])
diff2 = abs(bfits[j-1] - popfits[i])
if diff > tol:
if diff2 > tol:
if i not in indices:
bests.append(pop[i])
logger.info('Best list found new structure for List HI = {0}'.format(pop[i].history_index))
indices.append(i)
b=bfits[0:j]
b.append(pop[i].fitness)
b.extend(bfits[j::])
bfits=b
else:
indices.append(i)
bests = sorted(bests, key=attrgetter('fitness'))
if len(bests) < Optimizer.number_of_bests:
bmax = bests[len(bests)-1].fitness
for i in range(len(popfits)):
if popfits[i] > bmax:
diff = abs(popfits[i]-bmax)
if diff > tol:
bests.append(pop[i])
logger.info('Appending best list with lower energy structure')
bmax = pop[i].fitness
else:
logger.info('Removing extra {0} structures from best list'.format(len(bests)-Optimizer.number_of_bests))
bests = bests[0:Optimizer.number_of_bests]
bfits=[ind.fitness for ind in bests]
else:
bests = []
bfits = []
for one in pop:
fit = one.fitness
if len(bfits) == 0:
bests.append(one)
logger.info('Adding new structure to best list HI = {0}'.format(one.history_index))
bfits.append(fit)
else:
diff = abs(bfits[-1]-fit)
if diff > tol:
bests.append(one)
bfits.append(fit)
if len(bests) > Optimizer.number_of_bests:
logger.info('Removing extra {0} structures from best list'.format(len(bests)-Optimizer.number_of_bests))
bests = bests[0:Optimizer.number_of_bests]
if Optimizer.generation % 10 == 0:
if writefile==True:
if fname==None:
try:
rank = MPI.COMM_WORLD.Get_rank()
except:
rank = 0
path = os.path.join(os.getcwd(),'{0}-rank{1}'.format(Optimizer.filename,rank))
logger.info('Writing Best lists to {0}'.format(path))
fxyzname=os.path.join(path,'Bests-{0}.xyz'.format(Optimizer.filename))
ffitname=os.path.join(path,'Bests-fitnesses-{0}.txt'.format(Optimizer.filename))
else:
fxyzname='{0}.xyz'.format(fname)
ffitname='{0}-fitnesses.txt'.format(fname)
bestfile=open(fxyzname,'w')
bestfitfile=open(ffitname,'w')
for one in bests:
if Optimizer.structure=='Defect':
cbulk=Atoms()
cbulk.extend(one[0])
cbulk.extend(one.bulki)
write_xyz(bestfile,cbulk,one.energy)
else:
write_xyz(bestfile,one[0],one.energy)
bestfitfile.write(repr(one.fitness)+'\n')
bestfile.close()
bestfitfile.close()
return bests
