def fitpred_new(pop, Optimizer):
"""Predator function to identify similar structures based on energy and replace one with new structure.
"""
fitlist = [one.fitness for one in pop]
nfitlist, nindices = remove_duplicates(fitlist, Optimizer.demin)
STR = ''
newpop = []
if len(nfitlist) != len(fitlist):
STR += 'Predator: Removed total of ' + repr(
len(fitlist) - len(nfitlist)) + ' from population\n'
otherlist = []
for i in range(len(pop)):
if i not in nindices:
STR += 'Predator: Removed ' + repr(pop[i].history_index) + '\n'
otherlist.append(pop[i])
else:
newpop.append(pop[i])
while len(newpop) < Optimizer.nindiv:
if Optimizer.structure == 'Defect' or Optimizer.structure == 'Cluster':
ind = gen_pop_box(Optimizer.atomlist, Optimizer.size)
elif Optimizer.structure == 'Crystal':
outts = gen_pop_box(Optimizer.atomlist, Optimizer.size,
Optimizer.cell_shape_options)
ind = outts[0]
elif Optimizer.structure == 'Surface':
mutopto = Optimizer.mutation_options
Optimizer.mutation_options = ['Lattice_Alteration_rdrd']
topind = random.choice(pop)[0].copy()
ind, scheme = moves_switch(topind, Optimizer)
Optimizer.mutation_options = mutopto
individ = Individual(ind)
#CHECK THIS LATER!! MAY NEED TO ADD MORE PROPERTIES!!
individ.energy = 1000
individ.fitness = 1000
newpop.append(individ)
STR += 'Predator: Adding mutated duplicates to new pop history=' + individ.history_index + '\n'
nindices.append(individ.index)
nindices.sort()
if Optimizer.natural_selection_scheme == 'fussf':
for ind in newpop:
if ind.fingerprint == 0:
ind.fingerprint = get_fingerprint(Optimizer, ind,
Optimizer.fpbin,
Optimizer.fpcutoff)
if 'lambda,mu' in Optimizer.algorithm_type:
try:
mark = [
index for index, n in enumerate(nindices)
if n > Optimizer.nindiv - 1
][0]
except:
mark = Optimizer.nindiv
Optimizer.mark = mark
pop, str1 = lambdacommamu.lambdacommamu(newpop, Optimizer)
STR += str1
else:
pop = selection_switch(newpop, Optimizer.nindiv,
Optimizer.natural_selection_scheme, Optimizer)
pop = get_best(pop, len(pop))
return pop, STR
def fitpred_new(pop,Optimizer):
"""Predator function to identify similar structures based on energy and replace one with new structure.
"""
fitlist = [one.fitness for one in pop]
nfitlist, nindices = remove_duplicates(fitlist, Optimizer.demin)
STR = ''
newpop = []
if len(nfitlist) != len(fitlist):
STR+='Predator: Removed total of '+repr(len(fitlist)-len(nfitlist))+' from population\n'
otherlist = []
for i in range(len(pop)):
if i not in nindices:
STR+='Predator: Removed '+repr(pop[i].history_index)+'\n'
otherlist.append(pop[i])
else:
newpop.append(pop[i])
while len(newpop) < Optimizer.nindiv:
if Optimizer.structure=='Defect' or Optimizer.structure=='Cluster':
ind=gen_pop_box(Optimizer.atomlist,Optimizer.size)
elif Optimizer.structure=='Crystal':
outts=gen_pop_box(Optimizer.atomlist,Optimizer.size,Optimizer.cell_shape_options)
ind=outts[0]
elif Optimizer.structure=='Surface':
mutopto=Optimizer.mutation_options
Optimizer.mutation_options=['Lattice_Alteration_rdrd']
topind=random.choice(pop)[0].copy()
ind, scheme = moves_switch(topind,Optimizer)
Optimizer.mutation_options=mutopto
individ=Individual(ind)
#CHECK THIS LATER!! MAY NEED TO ADD MORE PROPERTIES!!
individ.energy=1000
individ.fitness=1000
newpop.append(individ)
STR+='Predator: Adding mutated duplicates to new pop history='+individ.history_index+'\n'
nindices.append(individ.index)
nindices.sort()
if Optimizer.natural_selection_scheme=='fussf':
for ind in newpop:
if ind.fingerprint == 0:
ind.fingerprint = get_fingerprint(Optimizer,ind,Optimizer.fpbin,Optimizer.fpcutoff)
if 'lambda,mu' in Optimizer.algorithm_type:
try:
mark = [ index for index,n in enumerate(nindices) if n > Optimizer.nindiv-1][0]
except:
mark = Optimizer.nindiv
Optimizer.mark = mark
pop, str1 = lambdacommamu.lambdacommamu(newpop, Optimizer)
STR+=str1
else:
pop = selection_switch(newpop, Optimizer.nindiv, Optimizer.natural_selection_scheme, Optimizer)
pop = get_best(pop,len(pop))
return pop, STR
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]
