def get_defect_restart_indiv(Optimizer, indiv):
"""
Function to generate an structopt Individual class object containing
a defect structure from a previously existing structure
Inputs:
Optimizer = structopt Optimizer class
indiv = ASE Atoms object containing the previously existing structure
Outputs:
individ = structopt Individual class object containing defect structure data
"""
if not Optimizer.solidbulk:
#Initialize Bulk - Generate or load positions of bulk solid
try:
rank = MPI.COMM_WORLD.Get_rank()
except:
rank = 0
outfilename = os.path.join(os.path.join(os.getcwd(),Optimizer.filename+'-rank'+repr(rank)),'Bulkfile.xyz')
if Optimizer.evalsolid:
bulk1, PureBulkEnpa, stro = gen_solid(Optimizer.solidfile,
Optimizer.solidcell,outfilename,Optimizer.calc,Optimizer.calc_method)
Optimizer.output.write(stro)
else:
bulk1 = gen_solid(Optimizer.solidfile,Optimizer.solidcell,outfilename)
PureBulkEnpa = 0
natomsbulk = len(bulk1)
Optimizer.solidbulk = bulk1.copy()
Optimizer.summary.write('CIBS Run Pure Bulk Energy per Atom:'+
repr(PureBulkEnpa)+'\n')
Optimizer.purebulkenpa = PureBulkEnpa
Optimizer.natomsbulk = natomsbulk
indiv.set_cell(Optimizer.solidcell)
indiv.set_pbc(True)
if Optimizer.restart_ints == 0:
outt = find_defects(indiv,Optimizer.solidbulk,Optimizer.sf)
else:
indicop = [atm for atm in indiv if atm.symbol != 'X']
indiv = Atoms(cell=Optimizer.solidcell, pbc=True)
for atm in indicop:
indiv.append(atm)
outt=[indiv[0:Optimizer.restart_ints],indiv[Optimizer.restart_ints::], Atoms(),
Atoms(),'Assuming first '+repr(Optimizer.restart_ints)+' are interstitials\n']
indi = outt[0].copy()
bulki = outt[1].copy()
individ = Individual(indi)
individ.bulko = bulki.copy()
individ.bulki = bulki.copy()
individ.purebulkenpa = Optimizer.purebulkenpa
individ.natomsbulk = Optimizer.natomsbulk
individ.vacancies = outt[2].copy()
individ.swaps = outt[3].copy()
Optimizer.output.write(outt[4])
return individ
def get_defect_indiv_random(Optimizer):
"""
Function to generate a structopt Individual class structure with a defect structure.
Inputs:
Optimizer = structopt Optimizer class object
Outputs:
individ = structopt Individual class object containing defect structure data
"""
#Initialize Bulk - Generate or load positions of bulk solid
if not Optimizer.solidbulk:
if 'Island_Method' not in Optimizer.algorithm_type:
outfilename = os.path.join(
os.path.join(os.getcwd(), Optimizer.filename), 'Bulkfile.xyz')
else:
from mpi4py import MPI
rank = MPI.COMM_WORLD.Get_rank()
outfilename = os.path.join(
os.path.join(os.getcwd(),
Optimizer.filename + '-rank' + repr(rank)),
'Bulkfile.xyz')
if Optimizer.evalsolid:
if Optimizer.parallel:
from MAST.structopt_stem.tools.setup_calculator import setup_calculator
Optimizer.calc = setup_calculator(Optimizer)
bulk1, PureBulkEnpa, stro = gen_solid(Optimizer.solidfile,
Optimizer.solidcell,
outfilename, Optimizer.calc,
Optimizer.calc_method)
Optimizer.output.write(stro)
else:
bulk1 = gen_solid(Optimizer.solidfile, Optimizer.solidcell,
outfilename)
PureBulkEnpa = 0
natomsbulk = len(bulk1)
Optimizer.solidbulk = bulk1.copy()
Optimizer.purebulkenpa = PureBulkEnpa
Optimizer.natomsbulk = natomsbulk
# Identify nearby atoms for region 2 inclusion
bulk = Optimizer.solidbulk.copy()
bulkcom = bulk.get_center_of_mass()
bulk.translate(-bulkcom)
if Optimizer.sf != 0:
bulk.append(Atom(position=[0, 0, 0]))
nbulk = Atoms(pbc=True, cell=bulk.get_cell())
nr2 = Atoms(pbc=True, cell=bulk.get_cell())
for i in range(len(bulk) - 1):
dist = bulk.get_distance(-1, i)
if dist <= Optimizer.sf:
nr2.append(bulk[i])
else:
nbulk.append(bulk[i])
else:
nbulk = bulk.copy()
nr2 = Atoms(pbc=True, cell=bulk.get_cell())
#Update atom list with atoms in region 2
natlist = []
for sym, c, m, u in Optimizer.atomlist:
atsym = [atm for atm in nr2 if atm.symbol == sym]
natlist.append((sym, len(atsym), m, u))
# Generate random individual and region 2
if 'sphere' in Optimizer.generate_flag:
ind = gen_pop_sphere(Optimizer.atomlist, Optimizer.size)
elif 'dumbbell' in Optimizer.generate_flag:
ind = Atoms(cell=[Optimizer.size for i in range(3)], pbc=True)
for sym, c, m, u in Optimizer.atomlist:
if c > 0:
dums = generate_dumbbells(c,
dumbbellsym=sym,
nindiv=1,
solid=Optimizer.solidbulk,
size=Optimizer.size)[0]
ind.extend(dums)
else:
ind = gen_pop_box(Optimizer.atomlist, Optimizer.size)
nnr2 = gen_pop_sphere(natlist, Optimizer.sf * 2.0)
nnr2.translate([-Optimizer.sf, -Optimizer.sf, -Optimizer.sf])
nnr2.set_pbc(True)
nnr2.set_cell(bulk.get_cell())
# Initialize class individual with known values
individ = Individual(ind)
individ.purebulkenpa = Optimizer.purebulkenpa
individ.natomsbulk = Optimizer.natomsbulk
# Combine individual with R2
icom = ind.get_center_of_mass()
ind.translate(-icom)
ind.extend(nnr2)
ind.set_pbc(True)
ind.set_cell(bulk.get_cell())
# Recenter structure
nbulk.translate(bulkcom)
ind.translate(bulkcom)
individ[0] = ind.copy()
individ.bulki = nbulk.copy()
individ.bulko = nbulk.copy()
bulk = nbulk.copy()
bul = bulk.copy()
for atm in individ[0]:
bul.append(atm)
indices = []
for sym, c, m, u in Optimizer.atomlist:
if c < 0:
if Optimizer.randvacst:
alist = [one for one in bul if one.symbol == sym]
count = abs(c)
while count > 0:
indices.append(random.choice(alist).index)
count -= 1
else:
pos = individ[0][0:Optimizer.natoms].get_center_of_mass()
count = abs(c)
bul.append(Atom(position=pos))
alist = [one for one in bul if one.symbol == sym]
alistd = [(bul.get_distance(len(bul) - 1,
one.index), one.index)
for one in alist]
alistd.sort(reverse=True)
bul.pop()
while count > 0:
idx = alistd.pop()[1]
indices.append(idx)
count -= 1
if len(indices) != 0:
nbulklist = [
at for at in bul
if at.index not in indices and at.index < len(bulk)
]
nalist = [
at for at in bul
if at.index not in indices and at.index >= len(bulk)
]
bulkn = Atoms(cell=bulk.get_cell(), pbc=True)
for atm in nbulklist:
bulkn.append(atm)
individ.bulki = bulkn.copy()
individ.bulko = bulkn.copy()
newind = Atoms()
for atm in nalist:
newind.append(atm)
newind.set_cell(individ[0].get_cell())
newind.set_pbc(True)
individ[0] = newind
return individ
def read_individual(indivfile, n=-1):
"""Function to write the data of an individual class object to a flat file
Input:
indivfile = String or fileobject for file to be read from
n = which individual from file to return. Default is last individual written.
optional All
Output:
returns an individual class object or list of individual class objects depending on value of n
"""
if isinstance(indivfile, str):
indivfile=open(indivfile, 'r')
all_lines = indivfile.readlines()
indivfile.close()
linen = 0
all_indivs = []
while linen < len(all_lines):
if '----------' in all_lines[linen]:
individ = Individual(Atoms())
elif 'Structure information' in all_lines[linen]:
natomstruct = int(all_lines[linen+1])
atomstruct = Atoms()
for i in range(natomstruct):
a = all_lines[linen+i+3].split()
sym = a[0]
position = [float(a[1]),float(a[2]),float(a[3])]
atomstruct.append(Atom(symbol=sym,position=position))
individ = Individual(atomstruct)
linen += 2+natomstruct
elif 'structure cell' in all_lines[linen]:
cell_line = all_lines[linen].split('=')
structcell = eval(cell_line[1])
individ[0].set_cell(structcell)
elif 'fitness' in all_lines[linen]:
fitline = all_lines[linen].split('=')
individ.fitness = float(fitline[1])
elif 'history_index' in all_lines[linen]:
line = all_lines[linen].split('=')
individ.history_index = line[1].strip()
elif 'index' in all_lines[linen]:
line = all_lines[linen].split('=')
individ.index = float(line[1])
elif 'tenergymx' in all_lines[linen]:
line = all_lines[linen].split('=')
individ.tenergymx = float(line[1])
elif 'tenergymin' in all_lines[linen]:
line = all_lines[linen].split('=')
individ.tenergymin = float(line[1])
elif 'energy' in all_lines[linen]:
line = all_lines[linen].split('=')
individ.energy = float(line[1])
elif 'pressure' in all_lines[linen]:
line = all_lines[linen].split('=')
individ.pressure = float(line[1])
elif 'volume' in all_lines[linen]:
line = all_lines[linen].split('=')
individ.volume = float(line[1])
elif 'force' in all_lines[linen]:
line = all_lines[linen].split('=')
individ.force = float(line[1])
elif 'purebulkenpa' in all_lines[linen]:
line = all_lines[linen].split('=')
individ.purebulkenpa = float(line[1])
elif 'natomsbulk' in all_lines[linen]:
line = all_lines[linen].split('=')
individ.natomsbulk = float(line[1])
elif 'fingerprint' in all_lines[linen]:
line = all_lines[linen].split('=')
individ.fingerprint = eval(line[1])
elif 'swpalist' in all_lines[linen]:
line = all_lines[linen].split('=')
individ.swaplist = eval(line[1])
elif 'bulki cell' in all_lines[linen]:
line = all_lines[linen].split('=')
cell = eval(line[1])
individ.bulki.set_cell(cell)
elif 'bulki' in all_lines[linen]:
natoms = int(all_lines[linen+1])
atomstruct = Atoms()
for i in range(natoms):
a = all_lines[linen+i+3].split()
sym = a[0]
position = [float(a[1]),float(a[2]),float(a[3])]
atomstruct.append(Atom(symbol=sym,position=position))
individ.bulki = atomstruct.copy()
linen += 2+natoms
elif 'bulko cell' in all_lines[linen]:
line = all_lines[linen].split('=')
cell = eval(line[1])
individ.bulko.set_cell(cell)
elif 'bulko' in all_lines[linen]:
natoms = int(all_lines[linen+1])
atomstruct = Atoms()
for i in range(natoms):
a = all_lines[linen+i+3].split()
sym = a[0]
position = [float(a[1]),float(a[2]),float(a[3])]
atomstruct.append(Atom(symbol=sym,position=position))
individ.bulko = atomstruct.copy()
linen += 2+natoms
elif 'box cell' in all_lines[linen]:
line = all_lines[linen].split('=')
cell = eval(line[1])
individ.box.set_cell(cell)
elif 'box' in all_lines[linen]:
natoms = int(all_lines[linen+1])
atomstruct = Atoms()
for i in range(natoms):
a = all_lines[linen+i+3].split()
sym = a[0]
position = [float(a[1]),float(a[2]),float(a[3])]
atomstruct.append(Atom(symbol=sym,position=position))
individ.box = atomstruct.copy()
linen += 2+natoms
elif 'vacancies cell' in all_lines[linen]:
line = all_lines[linen].split('=')
cell = eval(line[1])
individ.vacancies.set_cell(cell)
elif 'vacancies' in all_lines[linen]:
natoms = int(all_lines[linen+1])
atomstruct = Atoms()
for i in range(natoms):
a = all_lines[linen+i+3].split()
sym = a[0]
position = [float(a[1]),float(a[2]),float(a[3])]
atomstruct.append(Atom(symbol=sym,position=position))
individ.vacancies = atomstruct.copy()
linen += 2+natoms
elif 'swaps cell' in all_lines[linen]:
line = all_lines[linen].split('=')
cell = eval(line[1])
individ.swaps.set_cell(cell)
elif 'swaps' in all_lines[linen]:
natoms = int(all_lines[linen+1])
atomstruct = Atoms()
for i in range(natoms):
a = all_lines[linen+i+3].split()
sym = a[0]
position = [float(a[1]),float(a[2]),float(a[3])]
atomstruct.append(Atom(symbol=sym,position=position))
individ.swaps = atomstruct.copy()
linen += 2+natoms
elif 'Finish' in all_lines[linen]:
all_indivs.append(individ.duplicate())
linen+=1
if n=='All':
return all_indivs
else:
return all_indivs[n]
def get_defect_restart_indiv(Optimizer, indiv):
"""
Function to generate an structopt Individual class object containing
a defect structure from a previously existing structure
Inputs:
Optimizer = structopt Optimizer class
indiv = ASE Atoms object containing the previously existing structure
Outputs:
individ = structopt Individual class object containing defect structure data
"""
if not Optimizer.solidbulk:
#Initialize Bulk - Generate or load positions of bulk solid
try:
rank = MPI.COMM_WORLD.Get_rank()
except:
rank = 0
outfilename = os.path.join(
os.path.join(os.getcwd(),
Optimizer.filename + '-rank' + repr(rank)),
'Bulkfile.xyz')
if Optimizer.evalsolid:
bulk1, PureBulkEnpa, stro = gen_solid(Optimizer.solidfile,
Optimizer.solidcell,
outfilename, Optimizer.calc,
Optimizer.calc_method)
Optimizer.output.write(stro)
else:
bulk1 = gen_solid(Optimizer.solidfile, Optimizer.solidcell,
outfilename)
PureBulkEnpa = 0
natomsbulk = len(bulk1)
Optimizer.solidbulk = bulk1.copy()
Optimizer.summary.write('CIBS Run Pure Bulk Energy per Atom:' +
repr(PureBulkEnpa) + '\n')
Optimizer.purebulkenpa = PureBulkEnpa
Optimizer.natomsbulk = natomsbulk
indiv.set_cell(Optimizer.solidcell)
indiv.set_pbc(True)
if Optimizer.restart_ints == 0:
outt = find_defects(indiv, Optimizer.solidbulk, Optimizer.sf)
else:
indicop = [atm for atm in indiv if atm.symbol != 'X']
indiv = Atoms(cell=Optimizer.solidcell, pbc=True)
for atm in indicop:
indiv.append(atm)
outt = [
indiv[0:Optimizer.restart_ints], indiv[Optimizer.restart_ints::],
Atoms(),
Atoms(), 'Assuming first ' + repr(Optimizer.restart_ints) +
' are interstitials\n'
]
indi = outt[0].copy()
bulki = outt[1].copy()
individ = Individual(indi)
individ.bulko = bulki.copy()
individ.bulki = bulki.copy()
individ.purebulkenpa = Optimizer.purebulkenpa
individ.natomsbulk = Optimizer.natomsbulk
individ.vacancies = outt[2].copy()
individ.swaps = outt[3].copy()
Optimizer.output.write(outt[4])
return individ
def get_defect_indiv_random(Optimizer):
"""
Function to generate a structopt Individual class structure with a defect structure.
Inputs:
Optimizer = structopt Optimizer class object
Outputs:
individ = structopt Individual class object containing defect structure data
"""
#Initialize Bulk - Generate or load positions of bulk solid
if not Optimizer.solidbulk:
if 'Island_Method' not in Optimizer.algorithm_type:
outfilename = os.path.join(os.path.join(os.getcwd(),Optimizer.filename),'Bulkfile.xyz')
else:
from mpi4py import MPI
rank = MPI.COMM_WORLD.Get_rank()
outfilename = os.path.join(os.path.join(os.getcwd(),Optimizer.filename+'-rank'+repr(rank)),'Bulkfile.xyz')
if Optimizer.evalsolid:
if Optimizer.parallel:
from MAST.structopt_stem.tools.setup_calculator import setup_calculator
Optimizer.calc = setup_calculator(Optimizer)
bulk1, PureBulkEnpa, stro = gen_solid(Optimizer.solidfile,
Optimizer.solidcell,outfilename,Optimizer.calc,Optimizer.calc_method)
Optimizer.output.write(stro)
else:
bulk1 = gen_solid(Optimizer.solidfile,Optimizer.solidcell,outfilename)
PureBulkEnpa = 0
natomsbulk = len(bulk1)
Optimizer.solidbulk = bulk1.copy()
Optimizer.purebulkenpa = PureBulkEnpa
Optimizer.natomsbulk = natomsbulk
# Identify nearby atoms for region 2 inclusion
bulk = Optimizer.solidbulk.copy()
bulkcom = bulk.get_center_of_mass()
bulk.translate(-bulkcom)
if Optimizer.sf != 0:
bulk.append(Atom(position=[0,0,0]))
nbulk = Atoms(pbc=True, cell=bulk.get_cell())
nr2 = Atoms(pbc=True, cell=bulk.get_cell())
for i in range(len(bulk)-1):
dist = bulk.get_distance(-1,i)
if dist <= Optimizer.sf:
nr2.append(bulk[i])
else:
nbulk.append(bulk[i])
else:
nbulk = bulk.copy()
nr2 = Atoms(pbc=True, cell=bulk.get_cell())
#Update atom list with atoms in region 2
natlist = []
for sym,c,m,u in Optimizer.atomlist:
atsym = [atm for atm in nr2 if atm.symbol==sym]
natlist.append((sym,len(atsym),m,u))
# Generate random individual and region 2
if 'sphere' in Optimizer.generate_flag:
ind = gen_pop_sphere(Optimizer.atomlist,Optimizer.size)
elif 'dumbbell' in Optimizer.generate_flag:
ind = Atoms(cell=[Optimizer.size for i in range(3)], pbc=True)
for sym,c,m,u in Optimizer.atomlist:
if c > 0:
dums = generate_dumbbells(c, dumbbellsym=sym, nindiv=1, solid = Optimizer.solidbulk, size=Optimizer.size)[0]
ind.extend(dums)
else:
ind = gen_pop_box(Optimizer.atomlist,Optimizer.size)
nnr2 = gen_pop_sphere(natlist, Optimizer.sf*2.0)
nnr2.translate([-Optimizer.sf,-Optimizer.sf,-Optimizer.sf])
nnr2.set_pbc(True)
nnr2.set_cell(bulk.get_cell())
# Initialize class individual with known values
individ = Individual(ind)
individ.purebulkenpa = Optimizer.purebulkenpa
individ.natomsbulk = Optimizer.natomsbulk
# Combine individual with R2
icom = ind.get_center_of_mass()
ind.translate(-icom)
ind.extend(nnr2)
ind.set_pbc(True)
ind.set_cell(bulk.get_cell())
# Recenter structure
nbulk.translate(bulkcom)
ind.translate(bulkcom)
individ[0] = ind.copy()
individ.bulki = nbulk.copy()
individ.bulko = nbulk.copy()
bulk = nbulk.copy()
bul = bulk.copy()
for atm in individ[0]:
bul.append(atm)
indices = []
for sym,c,m,u in Optimizer.atomlist:
if c < 0:
if Optimizer.randvacst:
alist = [one for one in bul if one.symbol==sym]
count = abs(c)
while count > 0:
indices.append(random.choice(alist).index)
count -= 1
else:
pos = individ[0][0:Optimizer.natoms].get_center_of_mass()
count = abs(c)
bul.append(Atom(position=pos))
alist = [one for one in bul if one.symbol==sym]
alistd = [(bul.get_distance(len(bul)-1,one.index),one.index)
for one in alist]
alistd.sort(reverse=True)
bul.pop()
while count > 0:
idx = alistd.pop()[1]
indices.append(idx)
count-=1
if len(indices) !=0:
nbulklist = [at for at in bul if at.index not in indices and at.index<len(bulk)]
nalist = [at for at in bul if at.index not in indices and at.index>=len(bulk)]
bulkn = Atoms(cell=bulk.get_cell(),pbc=True)
for atm in nbulklist:
bulkn.append(atm)
individ.bulki = bulkn.copy()
individ.bulko = bulkn.copy()
newind = Atoms()
for atm in nalist:
newind.append(atm)
newind.set_cell(individ[0].get_cell())
newind.set_pbc(True)
individ[0] = newind
return individ