Example #1
0
def ase_minimization(indiv, Optimizer):
    """Function to use built in ASE minimizers to minimize atomic positions in structure.
    Input:
        indiv = Individual class object to be optimized
        Optimizer = Optimizer class object with needed parameters
    Output:
        indiv = Optimized Individual class object.
    """
    if 'MU' in Optimizer.debug:
        debug = True
    else:
        debug = False
    cwd1=os.getcwd()
    olammpsmin = Optimizer.lammps_min
    if Optimizer.lammps_min:
        Optimizer.lammps_min = None
    calc2 = setup_calculator(Optimizer)
#     if 'mass' in indiv[0].get_calculator():
#         mass2 = ['1 '+ str(Optimizer.atomlist[0][2])]
#         if len(Optimizer.atomlist) > 1:
#             for i in range(len(Optimizer.atomlist)-1):
#                 mass2.append(str(i+2) + ' ' + str(Optimizer.atomlist[i+1][2]))
#         calc2=LAMMPS(parameters={ 'pair_style' : Optimizer.pair_style, 'pair_coeff' : Optimizer.pair_coeff , 'mass' : mass2 },files=[ Optimizer.pot_file ])
#     else:
#         calc2=LAMMPS(parameters={ 'pair_style' : Optimizer.pair_style, 'pair_coeff' : Optimizer.pair_coeff},files=[ Optimizer.pot_file ])
    if Optimizer.structure==Defect:
        nat=indiv[0].get_number_of_atoms
        sol=Atoms()
        sol.extend(indiv[0])
        sol.extend(indiv.bulko)
        sol.set_calculator(calc2)
        sol.set_cell(indiv.bulko.get_cell())
        sol.set_pbc(True)
        dyn=BFGS(sol)
        dyn.run(fmax=0.001, steps=2500)
        positions=sol[0:nat].get_positions()
        indiv[0].set_positions(positions)
    else:
        atomsdup=indiv[0].copy()
        atomsdup.set_calculator(calc2)
        dyn=BFGS(indiv[0])
        dyn.run(fmax=0.001, steps=2500)
        positions=atomsdup.get_positions()
        indiv[0].set_positions(positions)
    os.chdir(cwd1)
    calc2.clean()
    Optimizer.lammps_min = olammpsmin
    Optimizer.output.write('ASE Minimization mutation performed on individual = '+repr(indiv.index)+'\n')
    muttype='ASEM'
    if indiv.energy==0:
        indiv.history_index=indiv.history_index+'m'+muttype
    else:
        indiv.history_index=repr(indiv.index)+'m'+muttype
    return indiv
		
		
Example #2
0
def eval_energy(input):
    """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
    """
    if input[0]==None:
        energy=0
        bul=0
        individ=0
        rank = MPI.COMM_WORLD.Get_rank()
        signal='Evaluated none individual on '+repr(rank)+'\n'
    else:
        [Optimizer, individ]=input
    if Optimizer.calc_method=='MAST':
        energy = individ.energy
        bul = individ.energy
        signal = 'Recieved MAST structure\n'
    else:
        if Optimizer.parallel: rank = MPI.COMM_WORLD.Get_rank()
        if not Optimizer.genealogy:
            STR='----Individual ' + str(individ.index)+ ' Optimization----\n'
        else:
            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,'Recieved by eval_energy')
            Optimizer.debugfile.flush()
        if Optimizer.structure=='Defect':
            indi=indiv.copy()
            if Optimizer.alloy==True:
                bulk=individ.bulki
            else:
                bulk=individ.bulko
            nat=indi.get_number_of_atoms()
            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)
            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])
    
        if Optimizer.constrain_position:
            ts = totalsol.copy()
            indc,indb,vacant,swap,stro = find_defects(ts,Optimizer.solidbulk,0)
            sbulk = Optimizer.solidbulk.copy()
            bcom = sbulk.get_center_of_mass()
            #totalsol.translate(-bulkcom)
            #indc.translate(-bulkcom)
            #totalsol.append(Atom(position=[0,0,0]))
    # 			for one in indc:
    # 				index = [atm.index for atm in totalsol if atm.position[0]==one.position[0] and atm.position[1]==one.position[1] and atm.position[2]==one.position[2]][0]
    # 				if totalsol.get_distance(-1,index) > Optimizer.sf:
    # 					r = random.random()
    # 					totalsol.set_distance(-1,index,Optimizer.sf*r,fix=0)
    # 			totalsol.pop()
    # 			totalsol.translate(bulkcom)
            com = indc.get_center_of_mass()
            dist = (sum((bcom[i] - com[i])**2 for i in range(3)))**0.5
            if dist > Optimizer.sf:
                STR+='Shifting structure to within region\n'
                r = random.random()*Optimizer.sf
                comv = numpy.linalg.norm(com)
                ncom = [one*r/comv for one in com]
                trans = [ncom[i]-com[i] for i in range(3)]
                indices = []
                for one in indc:
                    id = [atm.index for atm in totalsol if atm.position[0]==one.position[0] and atm.position[1]==one.position[1] and atm.position[2]==one.position[2]][0]
                    totalsol[id].position += trans
    
        # Check for atoms that are too close
        min_len=0.7
        #pdb.set_trace()
        if not Optimizer.fixed_region:
            if Optimizer.structure=='Defect' or Optimizer.structure=='Surface':
                cutoffs=[2.0 for one in totalsol]
                nl=NeighborList(cutoffs,bothways=True,self_interaction=False)
                nl.update(totalsol)
                for one in totalsol[0:nat]:
                    nbatoms=Atoms()
                    nbatoms.append(one)
                    indices, offsets=nl.get_neighbors(one.index)
                    for index, d in zip(indices,offsets):
                        index = int(index)
                        sym=totalsol[index].symbol
                        pos=totalsol[index].position + numpy.dot(d,totalsol.get_cell())
                        at=Atom(symbol=sym,position=pos)
                        nbatoms.append(at)
                    while True:
                        dflag=False
                        for i in range(1,len(nbatoms)):
                            d=nbatoms.get_distance(0,i)
                            if d < min_len:
                                nbatoms.set_distance(0,i,min_len+.01,fix=0.5)
                                STR+='--- WARNING: Atoms too close (<0.7A) - Implement Move ---\n'
                                dflag=True
                        if dflag==False:
                            break
                    for i in range(len(indices)):
                        totalsol[indices[i]].position=nbatoms[i+1].position
                    totalsol[one.index].position=nbatoms[0].position
                    nl.update(totalsol)
                if debug:
                    write_xyz(Optimizer.debugfile,totalsol,'After minlength check')
                    Optimizer.debugfile.flush()
            else:
                for i in range(len(indiv)):
                    for j in range(len(indiv)):
                        if i != j:
                            d=indiv.get_distance(i,j)
                            if d < min_len:
                                indiv.set_distance(i,j,min_len,fix=0.5)
                                STR+='--- WARNING: Atoms too close (<0.7A) - Implement Move ---\n'
                if debug:
                    write_xyz(Optimizer.debugfile,indiv,'After minlength check')
                    Optimizer.debugfile.flush()
    
        # Set calculator to use to get forces/energies
        if Optimizer.parallel:
            calc = setup_calculator(Optimizer)
            if Optimizer.fixed_region:
                pms=copy.deepcopy(calc.parameters)
                try:
                    pms['mass'][len(pms['mass'])-1] += '\ngroup RO id >= '+repr(nat)+'\nfix freeze RO setforce 0.0 0.0 0.0\n'
                except KeyError:
                    pms['pair_coeff'][0] += '\ngroup RO id >= '+repr(nat)+'\nfix freeze RO setforce 0.0 0.0 0.0\n'
                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)
                Optimizer.lammps_min = None
                Optimizer.static_calc = setup_calculator(Optimizer)
                Optimizer.lammps_min = lmin
        else:
            calc=Optimizer.calc
        if Optimizer.structure=='Defect' or Optimizer.structure=='Surface':
            totalsol.set_calculator(calc)
            totalsol.set_pbc(True)
        else:
            indiv.set_calculator(calc)
            indiv.set_pbc(True)	#Current bug in ASE optimizer-Lammps prevents pbc=false 
            if Optimizer.structure=='Cluster':
                indiv.set_cell([500,500,500])
                indiv.translate([250,250,250])
    
        cwd=os.getcwd()
        # Perform Energy Minimization
        if not Optimizer.parallel:
            Optimizer.output.flush()
        if Optimizer.ase_min == True:
            try:
                if Optimizer.structure=='Defect' or Optimizer.structure=='Surface':
                    dyn=BFGS(totalsol)
                else:
                    dyn=BFGS(indiv)
                dyn.run(fmax=Optimizer.ase_min_fmax, steps=Optimizer.ase_min_maxsteps)
            except OverflowError:
                STR+='--- Error: Infinite Energy Calculated - Implement Random ---\n'
                box=Atoms()
                indiv=gen_pop_box(Optimizer.natoms, Optimizer.atomlist, Optimizer.size)
                indiv.set_calculator(calc)
                dyn=BFGS(indiv)
                dyn.run(fmax=fmax, steps=steps)
            except numpy.linalg.linalg.LinAlgError:
                STR+='--- Error: Singular Matrix - Implement Random ---\n'
                indiv=gen_pop_box(Optimizer.natoms, Optimizer.atomlist, Optimizer.size)
                indiv.set_calculator(calc)
                dyn=BFGS(indiv)
                dyn.run(fmax=fmax, steps=steps)
            # Get Energy of Minimized Structure
            if Optimizer.structure=='Defect' or Optimizer.structure=='Surface':
                en=totalsol.get_potential_energy()
                #force=numpy.maximum.reduce(abs(totalsol.get_forces()))
                if Optimizer.fitness_scheme == 'enthalpyfit':
                    pressure=totalsol.get_isotropic_pressure(totalsol.get_stress())
                    cell_max=numpy.maximum.reduce(totalsol.get_positions())
                    cell_min=numpy.minimum.reduce(totalsol.get_positions())
                    cell=cell_max-cell_min
                    volume=cell[0]*cell[1]*cell[2]
                else:
                    pressure=0
                    volume=0
                na=totalsol.get_number_of_atoms()
                ena=en/na
                energy=en
                individ[0]=totalsol[0:nat]
                bul=totalsol[(nat):len(totalsol)]
                STR+='Number of positions = '+repr(len(bul)+len(individ[0]))+'\n'
                individ[0].set_cell(csize)
                indiv=individ[0]
            else:
                en=indiv.get_potential_energy()
                if Optimizer.fitness_scheme == 'enthalpyfit':
                    pressure=indiv.get_isotropic_pressure(indiv.get_stress())
                    cell_max=numpy.maximum.reduce(indiv.get_positions())
                    cell_min=numpy.minimum.reduce(indiv.get_positions())
                    cell=cell_max-cell_min
                    volume=cell[0]*cell[1]*cell[2]
                else: 
                    pressure=0
                    volume=0
                na=indiv.get_number_of_atoms()
                ena=en/na
                energy=ena
                individ[0]=indiv
                bul=0
        else:
            if Optimizer.structure=='Defect' or Optimizer.structure=='Surface':
                if Optimizer.calc_method=='VASP':
                    en=totalsol.get_potential_energy()
                    calcb=Vasp(restart=True)
                    totalsol=calcb.get_atoms()
                    stress=calcb.read_stress()
                else:
                    try:
                        totcop=totalsol.copy()
                        if debug: write_xyz(Optimizer.debugfile,totcop,'Individual sent to lammps')
                        OUT=totalsol.calc.calculate(totalsol)
                        totalsol=OUT['atoms']
                        totalsol.set_pbc(True)
                        if Optimizer.fixed_region:
                            if debug:
                                print 'Energy of fixed region calc = ', OUT['thermo'][-1]['pe']
                            totalsol.set_calculator(Optimizer.static_calc)
                            OUT=totalsol.calc.calculate(totalsol)
                            totalsol=OUT['atoms']
                            totalsol.set_pbc(True)
                            if debug:
                                print 'Energy of static calc = ', OUT['thermo'][-1]['pe']
                        en=OUT['thermo'][-1]['pe']
                        stress=numpy.array([OUT['thermo'][-1][i] for i in ('pxx','pyy','pzz','pyz','pxz','pxy')])*(-1e-4*GPa)
                        #force=numpy.maximum.reduce(abs(totalsol.get_forces()))
                        if debug:
                            write_xyz(Optimizer.debugfile,totalsol,'After Lammps Minimization')
                            Optimizer.debugfile.flush()
                    except Exception, e:
                        os.chdir(cwd)
                        STR+='WARNING: Exception during energy eval:\n'+repr(e)+'\n'
                        f=open('problem-structures.xyz','a')
                        write_xyz(f,totcop,data='Starting structure hindex='+individ.history_index)
                        write_xyz(f,totalsol,data='Lammps Min structure')
                        en=10
                        stress=0
                        f.close()
                if Optimizer.fitness_scheme == 'enthalpyfit':
                    pressure=totalsol.get_isotropic_pressure(stress)
                    cell_max=numpy.maximum.reduce(totalsol.get_positions())
                    cell_min=numpy.minimum.reduce(totalsol.get_positions())
                    cell=cell_max-cell_min
                    volume=cell[0]*cell[1]*cell[2]
                else:
                    pressure=totalsol.get_isotropic_pressure(stress)
                    volume=0
                na=totalsol.get_number_of_atoms()
                ena=en/na
                energy=en
                if Optimizer.structure=='Defect':
                    if Optimizer.fixed_region==True or Optimizer.finddefects==False:
                        individ[0]=totalsol[0:nat]
                        bul=totalsol[(nat):len(totalsol)]
                        individ[0].set_cell(csize)
                    else:
                        if 'FI' 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]
                else:
                    top,bul=find_top_layer(totalsol,Optimizer.surftopthick)
                    indiv=top.copy()
                    individ[0]=top.copy()
            else:
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
Example #4
0
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':
           # logger.info('M:')
            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()
            #print 'rank, eval_energy.cell',rank,origcell
            if Optimizer.forcing != 'RelaxBox':
               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])
           # logger.info('M: set cell')
        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')
            # logger.info('M:check dist')
            totalsol, STR = check_min_dist(Optimizer, 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:
           # logger.info('M:start calculator')
            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, pea, energy, pressure, volume, STR = run_energy_eval(totalsol, Optimizer.calc_method, Optimizer.fixed_region, Optimizer.fitness_scheme, STR, Optimizer.static_calc)
                else:
                  #  logger.info('M:start run_energy_eval')
                    totalsol, pea, energy, pressure, volume, STR = run_energy_eval(totalsol, Optimizer.calc_method, False, Optimizer.fitness_scheme, STR)
                    logger.info('M:finish run_energy_eval, energy = {0} @ rank ={1}'.format(energy,rank))
        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')
            if Optimizer.forcing != 'RelaxBox':
               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

        #Add pealist to include atom index based on sorted PE. 
        logger.info('before sort{0}'.format(individ.energy))
        sort_pealist(Optimizer,individ,pea)
        energy = individ.energy
        logger.info('after sort {0}'.format(individ.energy))
        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
Example #5
0
def eval_energy(input):
    """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
    """
    if input[0] == None:
        energy = 0
        bul = 0
        individ = 0
        rank = MPI.COMM_WORLD.Get_rank()
        signal = 'Evaluated none individual on ' + repr(rank) + '\n'
    else:
        [Optimizer, individ] = input
    if Optimizer.calc_method == 'MAST':
        energy = individ.energy
        bul = individ.energy
        signal = 'Recieved MAST structure\n'
    else:
        if Optimizer.parallel: rank = MPI.COMM_WORLD.Get_rank()
        if not Optimizer.genealogy:
            STR = '----Individual ' + str(
                individ.index) + ' Optimization----\n'
        else:
            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, 'Recieved by eval_energy')
            Optimizer.debugfile.flush()
        if Optimizer.structure == 'Defect':
            indi = indiv.copy()
            if Optimizer.alloy == True:
                bulk = individ.bulki
            else:
                bulk = individ.bulko
            nat = indi.get_number_of_atoms()
            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)
            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])

        if Optimizer.constrain_position:
            ts = totalsol.copy()
            indc, indb, vacant, swap, stro = find_defects(
                ts, Optimizer.solidbulk, 0)
            sbulk = Optimizer.solidbulk.copy()
            bcom = sbulk.get_center_of_mass()
            #totalsol.translate(-bulkcom)
            #indc.translate(-bulkcom)
            #totalsol.append(Atom(position=[0,0,0]))
            # 			for one in indc:
            # 				index = [atm.index for atm in totalsol if atm.position[0]==one.position[0] and atm.position[1]==one.position[1] and atm.position[2]==one.position[2]][0]
            # 				if totalsol.get_distance(-1,index) > Optimizer.sf:
            # 					r = random.random()
            # 					totalsol.set_distance(-1,index,Optimizer.sf*r,fix=0)
            # 			totalsol.pop()
            # 			totalsol.translate(bulkcom)
            com = indc.get_center_of_mass()
            dist = (sum((bcom[i] - com[i])**2 for i in range(3)))**0.5
            if dist > Optimizer.sf:
                STR += 'Shifting structure to within region\n'
                r = random.random() * Optimizer.sf
                comv = numpy.linalg.norm(com)
                ncom = [one * r / comv for one in com]
                trans = [ncom[i] - com[i] for i in range(3)]
                indices = []
                for one in indc:
                    id = [
                        atm.index for atm in totalsol
                        if atm.position[0] == one.position[0]
                        and atm.position[1] == one.position[1]
                        and atm.position[2] == one.position[2]
                    ][0]
                    totalsol[id].position += trans

        # Check for atoms that are too close
        min_len = 0.7
        #pdb.set_trace()
        if not Optimizer.fixed_region:
            if Optimizer.structure == 'Defect' or Optimizer.structure == 'Surface':
                cutoffs = [2.0 for one in totalsol]
                nl = NeighborList(cutoffs,
                                  bothways=True,
                                  self_interaction=False)
                nl.update(totalsol)
                for one in totalsol[0:nat]:
                    nbatoms = Atoms()
                    nbatoms.append(one)
                    indices, offsets = nl.get_neighbors(one.index)
                    for index, d in zip(indices, offsets):
                        index = int(index)
                        sym = totalsol[index].symbol
                        pos = totalsol[index].position + numpy.dot(
                            d, totalsol.get_cell())
                        at = Atom(symbol=sym, position=pos)
                        nbatoms.append(at)
                    while True:
                        dflag = False
                        for i in range(1, len(nbatoms)):
                            d = nbatoms.get_distance(0, i)
                            if d < min_len:
                                nbatoms.set_distance(0,
                                                     i,
                                                     min_len + .01,
                                                     fix=0.5)
                                STR += '--- WARNING: Atoms too close (<0.7A) - Implement Move ---\n'
                                dflag = True
                        if dflag == False:
                            break
                    for i in range(len(indices)):
                        totalsol[indices[i]].position = nbatoms[i + 1].position
                    totalsol[one.index].position = nbatoms[0].position
                    nl.update(totalsol)
                if debug:
                    write_xyz(Optimizer.debugfile, totalsol,
                              'After minlength check')
                    Optimizer.debugfile.flush()
            else:
                for i in range(len(indiv)):
                    for j in range(len(indiv)):
                        if i != j:
                            d = indiv.get_distance(i, j)
                            if d < min_len:
                                indiv.set_distance(i, j, min_len, fix=0.5)
                                STR += '--- WARNING: Atoms too close (<0.7A) - Implement Move ---\n'
                if debug:
                    write_xyz(Optimizer.debugfile, indiv,
                              'After minlength check')
                    Optimizer.debugfile.flush()

        # Set calculator to use to get forces/energies
        if Optimizer.parallel:
            calc = setup_calculator(Optimizer)
            if Optimizer.fixed_region:
                pms = copy.deepcopy(calc.parameters)
                try:
                    pms['mass'][
                        len(pms['mass']) - 1] += '\ngroup RO id >= ' + repr(
                            nat) + '\nfix freeze RO setforce 0.0 0.0 0.0\n'
                except KeyError:
                    pms['pair_coeff'][0] += '\ngroup RO id >= ' + repr(
                        nat) + '\nfix freeze RO setforce 0.0 0.0 0.0\n'
                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)
                Optimizer.lammps_min = None
                Optimizer.static_calc = setup_calculator(Optimizer)
                Optimizer.lammps_min = lmin
        else:
            calc = Optimizer.calc
        if Optimizer.structure == 'Defect' or Optimizer.structure == 'Surface':
            totalsol.set_calculator(calc)
            totalsol.set_pbc(True)
        else:
            indiv.set_calculator(calc)
            indiv.set_pbc(
                True)  #Current bug in ASE optimizer-Lammps prevents pbc=false
            if Optimizer.structure == 'Cluster':
                indiv.set_cell([500, 500, 500])
                indiv.translate([250, 250, 250])

        cwd = os.getcwd()
        # Perform Energy Minimization
        if not Optimizer.parallel:
            Optimizer.output.flush()
        if Optimizer.ase_min == True:
            try:
                if Optimizer.structure == 'Defect' or Optimizer.structure == 'Surface':
                    dyn = BFGS(totalsol)
                else:
                    dyn = BFGS(indiv)
                dyn.run(fmax=Optimizer.ase_min_fmax,
                        steps=Optimizer.ase_min_maxsteps)
            except OverflowError:
                STR += '--- Error: Infinite Energy Calculated - Implement Random ---\n'
                box = Atoms()
                indiv = gen_pop_box(Optimizer.natoms, Optimizer.atomlist,
                                    Optimizer.size)
                indiv.set_calculator(calc)
                dyn = BFGS(indiv)
                dyn.run(fmax=fmax, steps=steps)
            except numpy.linalg.linalg.LinAlgError:
                STR += '--- Error: Singular Matrix - Implement Random ---\n'
                indiv = gen_pop_box(Optimizer.natoms, Optimizer.atomlist,
                                    Optimizer.size)
                indiv.set_calculator(calc)
                dyn = BFGS(indiv)
                dyn.run(fmax=fmax, steps=steps)
            # Get Energy of Minimized Structure
            if Optimizer.structure == 'Defect' or Optimizer.structure == 'Surface':
                en = totalsol.get_potential_energy()
                #force=numpy.maximum.reduce(abs(totalsol.get_forces()))
                if Optimizer.fitness_scheme == 'enthalpyfit':
                    pressure = totalsol.get_isotropic_pressure(
                        totalsol.get_stress())
                    cell_max = numpy.maximum.reduce(totalsol.get_positions())
                    cell_min = numpy.minimum.reduce(totalsol.get_positions())
                    cell = cell_max - cell_min
                    volume = cell[0] * cell[1] * cell[2]
                else:
                    pressure = 0
                    volume = 0
                na = totalsol.get_number_of_atoms()
                ena = en / na
                energy = en
                individ[0] = totalsol[0:nat]
                bul = totalsol[(nat):len(totalsol)]
                STR += 'Number of positions = ' + repr(
                    len(bul) + len(individ[0])) + '\n'
                individ[0].set_cell(csize)
                indiv = individ[0]
            else:
                en = indiv.get_potential_energy()
                if Optimizer.fitness_scheme == 'enthalpyfit':
                    pressure = indiv.get_isotropic_pressure(indiv.get_stress())
                    cell_max = numpy.maximum.reduce(indiv.get_positions())
                    cell_min = numpy.minimum.reduce(indiv.get_positions())
                    cell = cell_max - cell_min
                    volume = cell[0] * cell[1] * cell[2]
                else:
                    pressure = 0
                    volume = 0
                na = indiv.get_number_of_atoms()
                ena = en / na
                energy = ena
                individ[0] = indiv
                bul = 0
        else:
            if Optimizer.structure == 'Defect' or Optimizer.structure == 'Surface':
                if Optimizer.calc_method == 'VASP':
                    en = totalsol.get_potential_energy()
                    calcb = Vasp(restart=True)
                    totalsol = calcb.get_atoms()
                    stress = calcb.read_stress()
                else:
                    try:
                        totcop = totalsol.copy()
                        if debug:
                            write_xyz(Optimizer.debugfile, totcop,
                                      'Individual sent to lammps')
                        OUT = totalsol.calc.calculate(totalsol)
                        totalsol = OUT['atoms']
                        totalsol.set_pbc(True)
                        if Optimizer.fixed_region:
                            if debug:
                                print 'Energy of fixed region calc = ', OUT[
                                    'thermo'][-1]['pe']
                            totalsol.set_calculator(Optimizer.static_calc)
                            OUT = totalsol.calc.calculate(totalsol)
                            totalsol = OUT['atoms']
                            totalsol.set_pbc(True)
                            if debug:
                                print 'Energy of static calc = ', OUT[
                                    'thermo'][-1]['pe']
                        en = OUT['thermo'][-1]['pe']
                        stress = numpy.array([
                            OUT['thermo'][-1][i]
                            for i in ('pxx', 'pyy', 'pzz', 'pyz', 'pxz', 'pxy')
                        ]) * (-1e-4 * GPa)
                        #force=numpy.maximum.reduce(abs(totalsol.get_forces()))
                        if debug:
                            write_xyz(Optimizer.debugfile, totalsol,
                                      'After Lammps Minimization')
                            Optimizer.debugfile.flush()
                    except Exception, e:
                        os.chdir(cwd)
                        STR += 'WARNING: Exception during energy eval:\n' + repr(
                            e) + '\n'
                        f = open('problem-structures.xyz', 'a')
                        write_xyz(f,
                                  totcop,
                                  data='Starting structure hindex=' +
                                  individ.history_index)
                        write_xyz(f, totalsol, data='Lammps Min structure')
                        en = 10
                        stress = 0
                        f.close()
                if Optimizer.fitness_scheme == 'enthalpyfit':
                    pressure = totalsol.get_isotropic_pressure(stress)
                    cell_max = numpy.maximum.reduce(totalsol.get_positions())
                    cell_min = numpy.minimum.reduce(totalsol.get_positions())
                    cell = cell_max - cell_min
                    volume = cell[0] * cell[1] * cell[2]
                else:
                    pressure = totalsol.get_isotropic_pressure(stress)
                    volume = 0
                na = totalsol.get_number_of_atoms()
                ena = en / na
                energy = en
                if Optimizer.structure == 'Defect':
                    if Optimizer.fixed_region == True or Optimizer.finddefects == False:
                        individ[0] = totalsol[0:nat]
                        bul = totalsol[(nat):len(totalsol)]
                        individ[0].set_cell(csize)
                    else:
                        if 'FI' 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]
                else:
                    top, bul = find_top_layer(totalsol, Optimizer.surftopthick)
                    indiv = top.copy()
                    individ[0] = top.copy()
            else:
Example #6
0
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