def get_population(Optimizer):
"""
Function to generate a population of structures.
Inputs:
Optimizer = structopt_stem Optimizer class object
Outputs:
pop = List of structopt_stem Individual class objects containing new structures.
"""
index1 = 0
pop = []
for i in range(Optimizer.nindiv):
if Optimizer.structure == 'Defect':
individ = get_defect_indiv(Optimizer)
elif Optimizer.structure == 'Surface':
individ = get_surface_indiv(Optimizer)
elif Optimizer.structure == 'Crystal':
individ = get_crystal_indiv(Optimizer)
else:
if 'sphere' in Optimizer.generate_flag:
ind = gen_pop_sphere(Optimizer.atomlist,Optimizer.size)
else:
ind = gen_pop_box(Optimizer.atomlist,Optimizer.size)
individ = Individual(ind)
individ.index = index1
if Optimizer.genealogy:
individ.history_index = repr(index1)
Optimizer.output.write('Generated cluster individual with natoms = '+
repr(individ[0].get_number_of_atoms())+'\n')
pop.append(individ)
index1=index1+1
# Generate new atomlist concentrations based on cluster+box
if Optimizer.structure == 'Defect':
if Optimizer.alloy:
concents=[]
for ind in pop:
cs=[]
for sym,c,u,m in Optimizer.atomlist:
sylen=[atm for atm in ind[0] if atm.symbol==sym]
cs.append(len(sylen))
concents.append(cs)
natmlist=[0]*len(Optimizer.atomlist)
for i in range(len(concents[0])):
alls=[cs[i] for cs in concents]
avgall=int(sum(alls)/len(alls))
if avgall>=Optimizer.atomlist[i][1]:
natmlist[i]=(Optimizer.atomlist[i][0], avgall,
Optimizer.atomlist[i][2],Optimizer.atomlist[i][3])
else:
natmlist[i]=(Optimizer.atomlist[i][0], Optimizer.atomlist[i][1],
Optimizer.atomlist[i][2],Optimizer.atomlist[i][3])
else:
natmlist=[0]*len(Optimizer.atomlist)
for i in range(len(Optimizer.atomlist)):
atms1=[inds for inds in pop[0][0] if inds.symbol==Optimizer.atomlist[i][0]]
natmlist[i]=(Optimizer.atomlist[i][0], len(atms1),Optimizer.atomlist[i][2],
Optimizer.atomlist[i][3])
Optimizer.atomlist=natmlist
Optimizer.output.write('\n\nNew atomlist concentrations based on cluster+box = '+
repr(Optimizer.atomlist)+'\n')
return pop
def get_crystal_indiv(Optimizer):
"""
Function to generate an structopt Individual class object containing a crystal structure.
Inputs:
Optimizer = structopt Optimizer class
Outputs:
individ = structopt Individual class object containing crystal structure data
"""
if 'sphere' in Optimizer.generate_flag:
outts = gen_pop_sphere(Optimizer.atomlist,Optimizer.size,Optimizer.cell_shape_options)
else:
outts = gen_pop_box(Optimizer.atomlist,Optimizer.size,Optimizer.cell_shape_options)
ind = outts[0]
Optimizer.output.write(outts[1])
individ = Individual(ind)
return individ
def get_crystal_indiv(Optimizer):
"""
Function to generate an structopt Individual class object containing a crystal structure.
Inputs:
Optimizer = structopt Optimizer class
Outputs:
individ = structopt Individual class object containing crystal structure data
"""
if 'sphere' in Optimizer.generate_flag:
outts = gen_pop_sphere(Optimizer.atomlist, Optimizer.size,
Optimizer.cell_shape_options)
else:
outts = gen_pop_box(Optimizer.atomlist, Optimizer.size,
Optimizer.cell_shape_options)
ind = outts[0]
Optimizer.output.write(outts[1])
individ = Individual(ind)
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 get_population(Optimizer):
"""
Function to generate a population of structures.
Inputs:
Optimizer = structopt_stem Optimizer class object
Outputs:
pop = List of structopt_stem Individual class objects containing new structures.
"""
index1 = 0
pop = []
for i in range(Optimizer.nindiv):
if Optimizer.structure == 'Defect':
individ = get_defect_indiv(Optimizer)
elif Optimizer.structure == 'Surface':
individ = get_surface_indiv(Optimizer)
elif Optimizer.structure == 'Crystal':
individ = get_crystal_indiv(Optimizer)
else:
if 'sphere' in Optimizer.generate_flag:
ind = gen_pop_sphere(Optimizer.atomlist, Optimizer.size)
else:
ind = gen_pop_box(Optimizer.atomlist, Optimizer.size)
individ = Individual(ind)
individ.index = index1
if Optimizer.genealogy:
individ.history_index = repr(index1)
Optimizer.output.write('Generated cluster individual with natoms = ' +
repr(individ[0].get_number_of_atoms()) + '\n')
pop.append(individ)
index1 = index1 + 1
# Generate new atomlist concentrations based on cluster+box
if Optimizer.structure == 'Defect':
if Optimizer.alloy:
concents = []
for ind in pop:
cs = []
for sym, c, u, m in Optimizer.atomlist:
sylen = [atm for atm in ind[0] if atm.symbol == sym]
cs.append(len(sylen))
concents.append(cs)
natmlist = [0] * len(Optimizer.atomlist)
for i in range(len(concents[0])):
alls = [cs[i] for cs in concents]
avgall = int(sum(alls) / len(alls))
if avgall >= Optimizer.atomlist[i][1]:
natmlist[i] = (Optimizer.atomlist[i][0], avgall,
Optimizer.atomlist[i][2],
Optimizer.atomlist[i][3])
else:
natmlist[i] = (Optimizer.atomlist[i][0],
Optimizer.atomlist[i][1],
Optimizer.atomlist[i][2],
Optimizer.atomlist[i][3])
else:
natmlist = [0] * len(Optimizer.atomlist)
for i in range(len(Optimizer.atomlist)):
atms1 = [
inds for inds in pop[0][0]
if inds.symbol == Optimizer.atomlist[i][0]
]
natmlist[i] = (Optimizer.atomlist[i][0], len(atms1),
Optimizer.atomlist[i][2],
Optimizer.atomlist[i][3])
Optimizer.atomlist = natmlist
Optimizer.output.write(
'\n\nNew atomlist concentrations based on cluster+box = ' +
repr(Optimizer.atomlist) + '\n')
return pop
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