Exemplo n.º 1
0
 def read(self,filepath):
     print 'reading Procar',
     lines = nstrip(readfile(filepath))
     self.nk = int(lines[1].split(':')[1].split()[0])
     self.nbands = int(lines[1].split(':')[2].split()[0])
     self.nions = int(lines[1].split(':')[3])
     #initialize
     self.kvecs = zeros((3,self.nk),dtype = float)
     self.kweights = zeros((self.nk),dtype = float)
     self.ener = zeros((self.nk, self.nbands, self.nspin),dtype = float) 
     self.occ = zeros((self.nk, self.nbands,self.nspin),dtype = float) 
     self.weights = zeros((self.nk,self.nbands,self.nions,len(self.orbs),self.nspin),dtype = float)
     
     #read weights
     ipos = 2
     for ispin in range(self.nspin):
         ipos += 1; # print 'ipos for spin %i:  %i' % (ispin,ipos)
         for ik in range(self.nk):
             self.kvecs[:,ik] = lines[ipos].split()[3:6]
             self.kweights[ik] = float(lines[ipos].split()[8])
             ipos += 2
             for ib in range(self.nbands):
                 self.ener[ik,ib,ispin] = float(lines[ipos].split()[4])
                 self.occ[ik,ib,ispin] = float(lines[ipos].split()[7])
                 ipos += 3
                 for i in range(self.nions):
                     if mod(ipos,1e4)==0: print '-', #progress bar
                     tempw = lines[ipos].split()[1:self.norbs+1]
                     self.weights[ik,ib,i,:,ispin] = tempw
                     ipos += 1
                 ipos += 2
             ipos += 1
     print       
Exemplo n.º 2
0
def readSym(dir):
    lines = readfile('{}/sym.out'.format(dir))
    nops = int(lines[0].split(':')[1])
    IBZvolCut = float(lines[1].split(':')[1])
#     IBZvol = float(lines[2].split(':')[1])
    IBZvol = None
    return nops, IBZvolCut, IBZvol
Exemplo n.º 3
0
 def rd_ibzkpt(self,dir): #only extracts the kpoint vectors
     self.vecs = zeros((3,self.nk),dtype = float64)
     lines = nstrip(readfile(dir+'IBZKPT'))
     nk2 = int(lines[1].split()[0])
     if nk2 != self.nk: print nk2,self.nk, 'Warning! Nkpts in IBZKPTS differs from this program''s'
     for ik in range(self.nk):
         self.vecs[:,ik] = lines[ik+3].split()[:3] #don't read weights'
Exemplo n.º 4
0
def readSym(dir):
    lines = readfile('{}/sym.out'.format(dir))
    nops = int(lines[0].split(':')[1])
    IBZvolCut = float(lines[1].split(':')[1])
    #     IBZvol = float(lines[2].split(':')[1])
    IBZvol = None
    return nops, IBZvolCut, IBZvol
Exemplo n.º 5
0
 def get_eigen(self,dir):
     lines = nstrip(readfile(dir+'eigenv'))
     self.nk = int(lines[0].split()[0])
     self.nbands = int(lines[0].split()[1])
     self.ener = zeros((self.nk,self.nbands),dtype = float64)
     for ik in range(self.nk):
         for ib in range(self.nbands):
             self.ener[ik,ib] = lines[ik+1].split()[ib+1]      
Exemplo n.º 6
0
 def get_tetweights(self,dir):
     lines = nstrip(readfile(dir+'tetwgt'))
     self.ntet = int(lines[0].split()[0])
     self.nbands = int(lines[0].split()[1])
     #    nspin = int(lines[0][2]) #haven't added spin yet
     self.fwgt = zeros((self.ntet,self.nbands),dtype = float64)
     for it in range(self.ntet):
         for ib in range(self.nbands):
             self.fwgt[it,ib] = lines[it+1].split()[ib+1] #First line and first column are not weights                   
Exemplo n.º 7
0
 def rd_ibzkpt(self,dir): #only extracts the tets ids
     self.idk = zeros((4,self.ntet),dtype = int)
     self.vwgt = zeros(self.ntet,dtype = float64)
     lines = nstrip(readfile(dir+'IBZKPT'))
     nk = int(lines[1].split()[0])
     ntet2 = int(lines[4+nk].split()[0])
     self.volscale = float(lines[4+nk].split()[1])
     print 'VASP volume scale', self.volscale
     if ntet2 != self.ntet: print 'Warning! NTET in IBZKPTS differs from this program''s'
     for it in range(self.ntet):
         self.vwgt[it] = lines[5+nk+it].split()[0]
         self.idk[:,it] = lines[5+nk+it].split()[1:]         
     self.idk = self.idk -1 #(converting from Fortran counting to python)
Exemplo n.º 8
0
 def get_tetvecs(self,dir):
     lines = nstrip(readfile(dir+'tetvecs'))
     self.vecs = zeros((3,4,self.ntet),dtype = float64)
     self.vol = zeros(self.ntet,dtype = float64)
     print shape(self.vecs)
     for it in range(self.ntet):
         for ic in range(4):
             print it, ic,lines[5*it+ic+1]
             self.vecs[:,ic,it] = lines[5*it+ic+1].split()
         va = self.vecs[:,1,it]-self.vecs[:,0,it]
         vb = self.vecs[:,2,it]-self.vecs[:,0,it]
         vc = self.vecs[:,3,it]-self.vecs[:,0,it]
         self.vol[it] = abs(dot(va,cross(vb,vc))/2.0)
Exemplo n.º 9
0
 def incar(self,dir):
     print 'reading ISPIN and LORBIT from INCAR'
     lines = nstrip(readfile(dir+'INCAR'))
     for line in lines:
         if ('ISPIN' in line) or ('ispin' in line): self.nspin = int(line.split('=')[1])
         if ('LORBIT' in line) or ('lorbit' in line): 
             lorbit = int(line.split('=')[1])
             if lorbit in [0,10]: #no lm decomposition
                 self.orbs = ['s','p','d']
             elif lorbit in [1,2,11,12]:
                 self.orbs = ['s','py','pz','px','dxy','dyz','dz2','dxz','dx2']
             else:
                 sys.exit('Unrecognized LORBIT in INCAR') 
         self.norbs = len(self.orbs)              
Exemplo n.º 10
0
def read_eigenval(dir): 
    '''Read in k vectors and eigenvalues from vasp file'''
    os.chdir(dir)
    eigs = readfile('EIGENVAL')
    nb = int(eigs[5].split()[2])
    nk = int(eigs[5].split()[1])
    print nb, nk
    ks = zeros((nk,3))
    eners = zeros((nk,nb))   
    for ik in range(nk):
        istart = 7 + ik*(nb+2) 
        ks[ik,:]  = [float(eigs[istart].split()[0]), float(eigs[istart].split()[1]), float(eigs[istart].split()[2])]
        for ib in range(nb):
            eners[ik,ib] = float(eigs[istart+ib+1].split()[1])
    return [nb,nk,ks,eners]
Exemplo n.º 11
0
def read_eigenval(dir): 
    '''Read in k vectors and eigenvalues from vasp file'''
    os.chdir(dir)
    eigs = readfile('EIGENVAL')
    nb = int(eigs[5].split()[2])
    nk = int(eigs[5].split()[1])
    print nb, nk
    ks = zeros((nk,3))
    eners = zeros((nk,nb))   
    for ik in range(nk):
        istart = 7 + ik*(nb+2) 
        ks[ik,:]  = [float(eigs[istart].split()[0]), float(eigs[istart].split()[1]), float(eigs[istart].split()[2])]
        for ib in range(nb):
            eners[ik,ib] = float(eigs[istart+ib+1].split()[1])
    return [nb,nk,ks,eners]
Exemplo n.º 12
0
 def incar(self, dir):
     print 'reading ISPIN and LORBIT from INCAR'
     lines = nstrip(readfile(dir + 'INCAR'))
     for line in lines:
         if ('ISPIN' in line) or ('ispin' in line):
             self.nspin = int(line.split('=')[1])
         if ('LORBIT' in line) or ('lorbit' in line):
             lorbit = int(line.split('=')[1])
             if lorbit in [0, 10]:  #no lm decomposition
                 self.orbs = ['s', 'p', 'd']
             elif lorbit in [1, 2, 11, 12]:
                 self.orbs = [
                     's', 'py', 'pz', 'px', 'dxy', 'dyz', 'dz2', 'dxz',
                     'dx2'
                 ]
             else:
                 sys.exit('Unrecognized LORBIT in INCAR')
         self.norbs = len(self.orbs)
Exemplo n.º 13
0
    def read(self, filepath):
        print 'reading Procar',
        lines = nstrip(readfile(filepath))
        self.nk = int(lines[1].split(':')[1].split()[0])
        self.nbands = int(lines[1].split(':')[2].split()[0])
        self.nions = int(lines[1].split(':')[3])
        #initialize
        self.kvecs = zeros((3, self.nk), dtype=float)
        self.kweights = zeros((self.nk), dtype=float)
        self.ener = zeros((self.nk, self.nbands, self.nspin), dtype=float)
        self.occ = zeros((self.nk, self.nbands, self.nspin), dtype=float)
        self.weights = zeros(
            (self.nk, self.nbands, self.nions, len(self.orbs), self.nspin),
            dtype=float)

        #read weights
        ipos = 2
        for ispin in range(self.nspin):
            ipos += 1
            # print 'ipos for spin %i:  %i' % (ispin,ipos)
            for ik in range(self.nk):
                self.kvecs[:, ik] = lines[ipos].split()[3:6]
                self.kweights[ik] = float(lines[ipos].split()[8])
                ipos += 2
                for ib in range(self.nbands):
                    self.ener[ik, ib, ispin] = float(lines[ipos].split()[4])
                    self.occ[ik, ib, ispin] = float(lines[ipos].split()[7])
                    ipos += 3
                    for i in range(self.nions):
                        if mod(ipos, 1e4) == 0: print '-',  #progress bar
                        tempw = lines[ipos].split()[1:self.norbs + 1]
                        self.weights[ik, ib, i, :, ispin] = tempw
                        ipos += 1
                    ipos += 2
                ipos += 1
        print
Exemplo n.º 14
0
]
N = len(dirs)

#x = zeros[len(dirs)]
#y = zeros[len(dirs)]
labels = ['No correction', 'Blochl correction']
if len(labels) != len(dirs):
    sys.exit(
        'Number of graphing labels is different from the number of datasets!\n  Stopping\n'
    )

fig = figure()
ax1 = fig.add_subplot(111)
for idir, dir in enumerate(dirs):
    print idir
    lines = readfile(dir + file)
    x = [lines[i].strip().split()[0] for i in range(len(lines))]
    y = [lines[i].strip().split()[1] for i in range(len(lines))]
    ax1.semilogy(x,
                 y,
                 color=cm.jet(1. * (idir + 1) / N),
                 linestyle='None',
                 marker='o',
                 label=labels[idir])
#ylim((1e-12,1e0))
legend(loc='upper right', prop={'size': 12})
title('Al:Al Tetrahedral methods\n Cubic mesh')
xlabel('n')
ylabel('error (eV)')
os.chdir(dirs[0])
os.chdir('../')
Exemplo n.º 15
0
        writefile([str(j)+'\n' for j in dets],'dets%s' % structi)
        writefile([str(j)+'\n' for j in err],'err%s' % structi)
        writefile([str(j)+'\n' for j in ef_err],'ef_err%s' % structi)
        
# log err vs n for all structs
os.chdir(tempdir)
fig = figure()
ax1 = fig.add_subplot(111)
#    ax1.set_color_cycle(['r','b','g','c', 'm', 'y', 'k'])
xlabel('n in cubic grid')
ylabel('Error (eV)') 
title('Structure noise '+title_detail+':\nTheoretical values: max n on struct 1; 1e-8 mark')
xlim((0,55))
#ylim((1e-12,1e0))
for i,structi in enumerate(structselect):  
    nlist = readfile('ns%s' % structi)
    errlist = readfile('err%s' % structi)
    ax1.semilogy(nlist, errlist,label=structi,linestyle='None',color=cm.jet(1.*(i+1)/len(structselect)), marker = 'o') # marker = 'o',
plt.legend(loc='upper right',prop={'size':14});
show()
fig.savefig('log_err_vs_n_structs') 


        
#    for structi in structselect:
#        for arr in [] 

        
#    
#    #en_per_atom vs ns  
#    titleadd = ''+ title_detail  
Exemplo n.º 16
0
from analysisToolsVasp import readfile 

file = 'structs.cubmesh/errlist_vs_n'
dirs = [
'/fslhome/bch/cluster_expansion/alal/equivk_f-16.tetra.noBlochl/', '/fslhome/bch/cluster_expansion/alal/equivk_f1-6.tetra/'
]
N = len(dirs)

#x = zeros[len(dirs)]
#y = zeros[len(dirs)]
labels = ['No correction','Blochl correction']
if len(labels) != len(dirs): sys.exit('Number of graphing labels is different from the number of datasets!\n  Stopping\n')

fig = figure()
ax1 = fig.add_subplot(111)
for idir,dir in enumerate(dirs):
    print idir
    lines = readfile(dir+file)
    x = [lines[i].strip().split()[0] for i in range(len(lines))]
    y = [lines[i].strip().split()[1] for i in range(len(lines))]
    ax1.semilogy(x, y,color=cm.jet(1.*(idir+1)/N),linestyle = 'None', marker = 'o', label=labels[idir])
#ylim((1e-12,1e0)) 
legend(loc='upper right',prop={'size':12});
title('Al:Al Tetrahedral methods\n Cubic mesh')
xlabel('n')
ylabel('error (eV)')
os.chdir(dirs[0]);os.chdir('../')
print dirs
fig.savefig('err_vs_n_multi')

print 'done'
            if os.path.isdir(d) and d == filter2
        ])
    for struct in structs:
        if collateMeshMat: meshPlots.write('(* {} *)\n'.format(struct))
        os.chdir(struct)
        iplot += 1
        calcs = sorted(
            [d for d in os.listdir(os.getcwd()) if os.path.isdir(d)])
        if len(calcs) > maxCalcs: maxCalcs = len(calcs)
        if collateMeshMat:
            for ic, calc in enumerate(calcs):
                os.chdir(calc)
                if ic == 0: os.system('cp bounds ../')
                if os.path.exists('cell_IBZmesh.m'):
                    meshPlots.write('\t(* {} *)\n'.format(calc))
                    lines = readfile('cell_IBZmesh.m')
                    lines.append('\n\n')
                    meshPlots.writelines(lines)
                os.chdir('../')
        os.chdir(path)
    if collateMeshMat:
        meshPlots.close()

#external run paths are of the form extmethodpath/atom_convergence/11_atom
if not extpaths is None:
    for ipath, extpath in enumerate(extpaths):
        os.chdir(extpath)
        method = extpath.split('/')[0]
        if collateMeshMat:
            meshPlots = open('IBZmeshPlots', 'w')
        atomdirs = sorted([
Exemplo n.º 18
0
    latticeType, packingFraction, mink_reduce, lattvec_u,arenormal,\
    unique_anorms,points_in_ppiped #,three_perp,

from numpy import array, arccos, dot, cross, pi, floor, sum, sqrt, exp, log, asarray
from numpy import transpose, rint, inner, multiply, size, argmin, argmax, nonzero, float64, identity
from numpy import ceil, real, unravel_index

from scipy.optimize import minimize
from copy import copy, deepcopy
fprec = float64
from numpy import zeros  #use arrays, not "matrix" class
#from numpy.matlib import zeros, matrix #creates np.matrix rather than array, but limited to 2-D!!!!  uses *, but array uses matrixmultiply
from numpy.linalg import norm, det, inv, eig
from numpy.random import randint, random
from itertools import combinations

sys.path.append(
    '/bluehome2/bch/pythonscripts/cluster_expansion/analysis_scripts/')
from analysisToolsVasp import writeEnergiesOszicar, writedirnames, nstrip, writeNk, writeNkIBZ, \
  writeElConverge, writeElSteps, writeCPUtime, enerparts, getdata, readfile, writefile, \
  getms, writefermi, removezeros,getEf
'''reads chgcar from dir1 and multiplies by 2 (for superlattice of volume 2 along z axis), 
and writes it twice into CHGCAR for dir2 '''

dir1 = '/fslhome/bch/cluster_expansion/alal/cubic_al/mp_c1,3/c1_8x8x8/BANDS/'
dir2 = '/fslhome/bch/cluster_expansion/alal/cubic_al/mp_c1,3/c3_8x8x4/BANDS/'

lines1 = readfile(dir1 + 'CHGCAR')
lines2 = readfile(dir2 + 'CHGCAR')

print 'Done'
Exemplo n.º 19
0
def analyze(paths): #as used with the parameter search, paths will have only one entry.  But keep consistent with interactive vaspoutCombineRunsExtData
    extpath = None
    useSym = False
    coloring = 'method'
    # coloring = 'indiv'
    doLegend = True
    doLabel = True
    smoothFactor = 2.0
    filter = '_' #string must be in dir name to be included
    filter2 = None #'Cu_1' #for single structures.  set to None if using filter1 only
    summaryPath = paths[0]
    #count the number of plots:
    iplot = 0
    maxCalcs = 0
    maxNk = 0
    methods = []
    for ipath,path in enumerate(paths):
        method = path.split('_')[-1].split('/')[0]
        methods.append(method)
        os.chdir(path)
        if filter2 == None:
            structs = sorted([d for d in os.listdir(os.getcwd()) if os.path.isdir(d) and filter in d])
        else:
            structs = sorted([d for d in os.listdir(os.getcwd()) if os.path.isdir(d) and d==filter2])
        for struct in structs:
            os.chdir(struct)
            iplot += 1
            calcs = sorted([d for d in os.listdir(os.getcwd()) if os.path.isdir(d)])
            if len(calcs)>maxCalcs: maxCalcs = len(calcs)
            os.chdir(path)
    
    #external data is of the form extpath/atom_method/struct.csv.  The csv has energies vs nK
    if not extpath is None:
        os.chdir(extpath)
        atoms_methods = sorted([d for d in os.listdir(extpath) if os.path.isdir(d) and filter in d])# os.chdir(extpath)
        for atom_method in atoms_methods:
            atom = atom_method.split('_')[0]
            os.chdir(atom_method)
            os.system('rm -r .*lock*')
            for structfile in os.listdir(os.getcwd()):
                if atom not in structfile:
                    os.system('mv {} {}_{}'.format(structfile,atom,structfile)) #so that file has atom name at beginning
            if filter2 == None:
                structfiles = sorted([d for d in os.listdir(os.getcwd()) if os.path.getsize(d)>0])
            else:
                structfiles = sorted([d for d in os.listdir(os.getcwd()) if '_'.join(d.split('_')[:2])==filter2 and os.path.getsize(d)>0])
            for structfile in structfiles:
                iplot += 1
                #count number of points in this structfile
                lines = readfile(structfile)
                if len(lines)>maxCalcs: maxCalcs = len(lines)     
            os.chdir(extpath)
    
    nplots = iplot 
    if nplots < len(paths): sys.exit('Stop.  Structures do not match filter')      
    data = zeros(nplots,dtype = [('ID', 'S25'),('color', 'S15'),('method', 'S15'),\
                                 ('nDone','int32'),('nAtoms','int32'),('nops','int8'),\
                                 ('IBZvolcut','float'),('IBZvol','float'),\
                                 ('eners', '{}float'.format(maxCalcs)), ('errs', '{}float'.format(maxCalcs)),\
                                 ('nKs', '{}int16'.format(maxCalcs)),('ns', '{}int8'.format(maxCalcs))])    
    # style.use('bmh')
    # for i, item in enumerate(rcParams['axes.prop_cycle']):
    #     colorsList.append(item['color']) 
    style.use('fivethirtyeight')
    # for i, item in enumerate(rcParams['axes.prop_cycle'][:-2]):
    #     colorsList.append(item['color']) 
    
    colorsList = [u'#30a2da', u'#fc4f30', u'#e5ae38', u'#6d904f', u'#8b8b8b',
                  u'#348ABD', u'#A60628', u'#7A68A6', u'#467821', u'#D55E00', 
                  u'#CC79A7', u'#56B4E9', u'#009E73', u'#F0E442', u'#0072B2']
    
    colorsList = colorsList + ['b','m','y','c','k']
    rcParams.update({'figure.autolayout': True})  
    rcParams['axes.facecolor'] = 'white' 
    rcParams['axes.linewidth'] = 1.0  
    rcParams['axes.edgecolor'] = 'black' # axisbg=axescolor
    rcParams['savefig.facecolor'] = 'white' # axisbg=axescolor
    rcParams['lines.markersize'] = 4.5
    #read all the data 
    iplot = -1
    for ipath, path in enumerate(paths): #my data
        tag = path.split('/')[-1][-7:]
        os.chdir(path)
        if filter2 == None:
            structs = sorted([d for d in os.listdir(os.getcwd()) if os.path.isdir(d) and filter in d])
        else:
            structs = sorted([d for d in os.listdir(os.getcwd()) if os.path.isdir(d) and d==filter2])
        nStructs = len(structs)
#         print structs,path
        for istruct,struct in enumerate(structs):
    #         print 'test', istruct, struct
#             print 'struct',struct
            os.chdir(struct)
            if coloring == 'indiv':
    #             if iplot < nplots -1:
                color = rgb2hex(cm.jet(1.*(iplot+1)/float(nplots)))
    #             else:
    #                 color = 'k' 
            elif coloring == 'method':
    #             color =  colorsList[ipath]     
                color = None
            calcs = sorted([d for d in os.listdir(os.getcwd()) if os.path.isdir(d) and os.path.exists('{}/OUTCAR'.format(d))])
            energies = []
            nKs = []
            ns = [] #the base n of the run run
            nDone = 0
            if useSym:
                try:
                    nops,IBZvolcut,IBZvol = readSym(calcs[0])
                except:
                    sys.exit('Stopping. readSym failed. Set useSym to False')
            for calc in calcs:  
                if electronicConvergeFinish(calc):
                    ener = getEnergy(calc) #in energy/atom
                    if not areEqual(ener,0,1e-5):
                        nDone +=1
                        energies.append(ener)
                        if 'vc' in path:
                            nK = getNkIBZ(calc,'KPOINTS')
                            
                        else:
                            nK = getNkIBZ(calc,'IBZKPT')
                        if nK > maxNk: maxNk = nK
                        nKs.append(nK)
                        ns.append(int(calc.split('_')[-1]))
            #sort by increasing number of kpoints
            if len(energies)>0: 
                iplot += 1
                nKs = array(nKs)
                energies = array(energies)
                ns = array(ns)
                order = argsort(nKs)
        #         print 'struct',struct
        #         print 'energies',energies
                energies = energies[order]
                ns = ns[order]
                nKs = sort(nKs)
                eref = energies[-1]#the last energy of each struct is that of the most kpoints   
                errs = abs(energies-eref)*1000 + 1e-4 #now in meV 
                data[iplot]['ID'] = '{} {}'.format(struct,tag)
                nAtoms = getNatoms('{}/POSCAR'.format(calc))
                data[iplot]['nAtoms'] = nAtoms
                if useSym:
                    data[iplot]['nops'] = nops
                    data[iplot]['IBZvolcut'] = IBZvolcut
                data[iplot]['nDone'] = nDone
                data[iplot]['eners'][:nDone] = energies
                data[iplot]['errs'][:nDone] = errs
                data[iplot]['nKs'][:nDone] = nKs
                data[iplot]['ns'][:nDone] = ns
                data[iplot]['color'] = color
                method = path.split('_')[-1].split('/')[0]
                data[iplot]['method'] = method
            os.chdir(path)
    # os.chdir(extpath)
    if not extpath is None:
        os.chdir(extpath)
#         print; print atoms_methods
        for atom_method in atoms_methods:
            os.chdir(atom_method)
            if coloring == 'method':
                color = None
                if 'MP' in atom_method: 
    #                 color = colorsList[len(paths)]
                    method = 'MP'
                    
                elif 'Mueller' in atom_method:
    #                 color = colorsList[len(paths)+1]
                    method = 'Mueller'
                if method not in methods:
                    methods.append(method)
            if filter2 == None:
                structfiles = sorted([d for d in os.listdir(os.getcwd()) if os.path.getsize(d)>0])
            else:
                structfiles = sorted([d for d in os.listdir(os.getcwd()) if '_'.join(d.split('_')[:2])==filter2 and os.path.getsize(d)>0])
            for structfile in structfiles:
                if useSym:
                    nops,IBZvolcut,nAtoms = copyData(structfile,data)
                if coloring == 'indiv':
                    if iplot < nplots -1:
                        color = cm.jet(1.*(iplot+1)/float(nplots))
                    else:
                        color = 'k'
                iplot += 1
                energies = []
                nKs = []
                lines = readfile(structfile)
                for line in lines:
                    nK = int(line.split('\t')[0])
                    if nK > maxNk: maxNk = nK
                    nKs.append(nK)
                    energies.append(-float(line.split('\t')[1].split('\r')[0]))
                nKs = array(nKs)
                energies = array(energies)
                nDone = len(energies)
                order = argsort(nKs)
                energies = energies[order]
                eref = energies[-1]#the last energy of each struct is that of the most kpoints
                nKs = sort(nKs)
                errs = abs(energies-eref)*1000 + 1e-4 #now in meV 
                struct = '_'.join(structfile.split('_')[:2])
                data[iplot]['ID'] = atom_method + struct
                data[iplot]['nAtoms'] = nAtoms
                if useSym:
                    data[iplot]['nops'] = nops
                    data[iplot]['IBZvolcut'] = IBZvolcut
                data[iplot]['nDone'] = len(energies)
                data[iplot]['eners'][:nDone] = energies
                data[iplot]['errs'][:nDone] = errs
                data[iplot]['nKs'][:nDone] = nKs
                data[iplot]['color'] = color
                data[iplot]['method'] = method
            os.chdir(extpath)
    nplots = iplot+1 
    
    lines = [' ID , nKIBZ , ener , err, nAtoms, nops,IBZcut\n']  
    for iplot in range(nplots):
        n = data[iplot]['nDone']
        for icalc in range(n):#data[iplot]['eners'][:n].tolist()
            lines.append('{}_n{},{},{:15.12f},{:15.12f},{},{},{}\n'.format(data[iplot]['ID'],\
              data[iplot]['ns'][icalc], data[iplot]['nKs'][icalc],\
              data[iplot]['eners'][icalc],data[iplot]['errs'][icalc],\
              data[iplot]['nAtoms'],data[iplot]['nops'],data[iplot]['IBZvolcut']))
    writefile(lines,'{}/summary.csv'.format(summaryPath)) 
       
    #plots
    if maxNk > 1:
        if filter[0] == '_':filter = '' #labels can't begin with _
#         plotTypes = ['linear','loglog', 'loglinear'];ylabels = ['Vasp error energy/atom (eV)','Error (meV)','Error (meV)']
        # print 'plot only loglog'
        plotTypes = ['loglog']; ylabels = ['Error (meV)']
    #     plotTypes = [] 
        
        xtext = 'N k-points'
        
        for it,plotType in enumerate(plotTypes):
            fig = figure()
            ax1 = fig.add_subplot(111)
            xlabel(xtext)
            ylabel(ylabels[it]) 
            # title('Convergence vs mesh method')
            #ylim((1e-12,1e0))
            oldmethod = '' 
            methods2 = []
            for iplot in range(nplots):
                labelStr = None
                n = data[iplot]['nDone']
                if coloring == 'method':  
                    method = data[iplot]['method'] 
                    data[iplot]['color'] = colorsList[methods.index(method)] 
                    if method != oldmethod and method not in methods2:
                        if doLabel: labelStr = '{} {}'.format(filter,data[iplot]['method'])
                        plotData(fig,summaryPath,data[iplot],n,plotType,filter,doLegend,labelStr)
                        oldmethod = method;labelStr = None
                        methods2.append(method)
                    else:
                        plotData(fig,summaryPath,data[iplot],n,plotType,filter,doLegend,labelStr)
                elif coloring == 'indiv': 
                    if doLabel: labelStr = '{} {}'.format(filter,data[iplot]['ID'])
                    plotData(data[iplot],n,plotType,filter,doLegend,labelStr)
        #Method averaging
        if coloring == 'method':
    #         print 'Averaging, plotting method errors'
            nbins = int(10*ceil(log10(maxNk)))# 10 bins per decade
            nKbins = array([(10.0**(1/10.0))**i for i in range(nbins)])
            fig = figure()
            ax1 = fig.add_subplot(111)
            xlabel('N k-points (smoothed by factor {})'.format(int(smoothFactor)))
            ylabel('Error (meV)') 
            methodCostsLogs = []
            for im,method in enumerate(methods):
                methnKmax = 0 
                binCounts = zeros(nbins,dtype = int32)
                binErrs = zeros(nbins,dtype = float)
                costLogs = zeros(nbins,dtype = float) # "Costs" relative to excellent Si Monkhorst Pack, which has err = 10^3/nK^3 + 10^-3 meV.         
                for iplot in range(nplots):
                    if data[iplot]['method'] == method:
                        for icalc in range(data[iplot]['nDone']-1):
                            nK = data[iplot]['nKs'][icalc]
                            if nK>methnKmax: methnKmax = nK
                            if nK>1:
                                for ibin in range(nbins):
                                    if abs(log10(nK/nKbins[ibin])) <= log10(smoothFactor)\
                                      and nKbins[ibin]<= maxNk:
                                        binErrs[ibin] += data[iplot]['errs'][icalc]
                                        costLogs[ibin] += log10(data[iplot]['errs'][icalc]/(10**3/(nK**3.0)+0.001))
                                        binCounts[ibin] += 1
                mask = where(binCounts>0)
                binErrs2 = binErrs[mask[0]]
                binCounts2 = binCounts[mask[0]]
                nKbins2 = nKbins[mask[0]]
                costLogs2 = costLogs[mask[0]]
                nbins2 = len(nKbins2)
                avgErrs = [binErrs2[ibin]/binCounts2[ibin] for ibin in range(nbins2)]
                avgcostLogs =  [costLogs2[ibin]/binCounts2[ibin] for ibin in range(nbins2)]
                avgcostLins = [10**avgcostLogs[ibin] for ibin in range(nbins2)]
                methodCostsLogs.append(mean(avgcostLogs))
                loglog(nKbins2,avgErrs,label = method,\
                      color = colorsList[im], marker = None)
                loglog(nKbins2,avgcostLins,label = None,\
                      color = colorsList[im], marker = None,linestyle=':')
        #         print 'Method',method, 'nKmax',methnKmax, 'avgLogCost', mean(avgcostLogs)
                legend(loc='lower left',prop={'size':12});
                fig.savefig('{}/methodErrs'.format(summaryPath))
            close('all')
    if maxNk > 1:  
        return [methodCostsLogs[0],mean(data['nDone'])] #there is only one method when running this routine
    else:
        return [100,0]
Exemplo n.º 20
0
def weightfunc(FE,FEmax,FEmin):
    maxratio = 1.0
    return str(1.0 + (maxratio-1)*(FEmax-FE)/(FEmax-FEmin))

'''Reads formation energies in structures.in.  If weighted, it changes the weights.  
If not, it adds a line for each weight'''

#dir = '/fslhome/bch/cluster_expansion/graphene/csv1-8W/'
dir = '/fslhome/bch/cluster_expansion/graphene/test1/'
infile = dir+'structures.in.441.FEsorted'
#infile = dir+'structures.in'
outfile = dir+'structures.in'
FEs = []
indices = []
lines = readfile(infile)
if 'noweights' in lines[1]: 
    weights_in = False
    lines[1] = 'weights\n'
else: 
    weights_in = True
#print 'weights_in', weights_in
#Find maximum and min formation energies
for i, line in enumerate(lines):
    if 'FE' in line:
        energy = float(line.split()[line.split().index('FE')+2].split(',')[0])  #FE = 1.2578,  etc.  remove any ","
        FEs.append(energy)
    if '#Energy' in line:
        indices.append(i+2) #where weights should appear 
FEmax = amax(FEs)
FEmin = amin(FEs)
Exemplo n.º 21
0
def analyze(
    paths
):  #as used with the parameter search, paths will have only one entry.  But keep consistent with interactive vaspoutCombineRunsExtData
    extpath = None
    useSym = False
    coloring = 'method'
    # coloring = 'indiv'
    doLegend = True
    doLabel = True
    smoothFactor = 2.0
    filter = '_'  #string must be in dir name to be included
    filter2 = None  #'Cu_1' #for single structures.  set to None if using filter1 only
    summaryPath = paths[0]
    #count the number of plots:
    iplot = 0
    maxCalcs = 0
    maxNk = 0
    methods = []
    for ipath, path in enumerate(paths):
        method = path.split('_')[-1].split('/')[0]
        methods.append(method)
        os.chdir(path)
        if filter2 == None:
            structs = sorted([
                d for d in os.listdir(os.getcwd())
                if os.path.isdir(d) and filter in d
            ])
        else:
            structs = sorted([
                d for d in os.listdir(os.getcwd())
                if os.path.isdir(d) and d == filter2
            ])
        for struct in structs:
            os.chdir(struct)
            iplot += 1
            calcs = sorted(
                [d for d in os.listdir(os.getcwd()) if os.path.isdir(d)])
            if len(calcs) > maxCalcs: maxCalcs = len(calcs)
            os.chdir(path)

    #external data is of the form extpath/atom_method/struct.csv.  The csv has energies vs nK
    if not extpath is None:
        os.chdir(extpath)
        atoms_methods = sorted([
            d for d in os.listdir(extpath) if os.path.isdir(d) and filter in d
        ])  # os.chdir(extpath)
        for atom_method in atoms_methods:
            atom = atom_method.split('_')[0]
            os.chdir(atom_method)
            os.system('rm -r .*lock*')
            for structfile in os.listdir(os.getcwd()):
                if atom not in structfile:
                    os.system('mv {} {}_{}'.format(
                        structfile, atom,
                        structfile))  #so that file has atom name at beginning
            if filter2 == None:
                structfiles = sorted([
                    d for d in os.listdir(os.getcwd())
                    if os.path.getsize(d) > 0
                ])
            else:
                structfiles = sorted([
                    d for d in os.listdir(os.getcwd())
                    if '_'.join(d.split('_')[:2]) == filter2
                    and os.path.getsize(d) > 0
                ])
            for structfile in structfiles:
                iplot += 1
                #count number of points in this structfile
                lines = readfile(structfile)
                if len(lines) > maxCalcs: maxCalcs = len(lines)
            os.chdir(extpath)

    nplots = iplot
    if nplots < len(paths): sys.exit('Stop.  Structures do not match filter')
    data = zeros(nplots,dtype = [('ID', 'S25'),('color', 'S15'),('method', 'S15'),\
                                 ('nDone','int32'),('nAtoms','int32'),('nops','int8'),\
                                 ('IBZvolcut','float'),('IBZvol','float'),\
                                 ('eners', '{}float'.format(maxCalcs)), ('errs', '{}float'.format(maxCalcs)),\
                                 ('nKs', '{}int16'.format(maxCalcs)),('ns', '{}int8'.format(maxCalcs))])
    # style.use('bmh')
    # for i, item in enumerate(rcParams['axes.prop_cycle']):
    #     colorsList.append(item['color'])
    style.use('fivethirtyeight')
    # for i, item in enumerate(rcParams['axes.prop_cycle'][:-2]):
    #     colorsList.append(item['color'])

    colorsList = [
        u'#30a2da', u'#fc4f30', u'#e5ae38', u'#6d904f', u'#8b8b8b', u'#348ABD',
        u'#A60628', u'#7A68A6', u'#467821', u'#D55E00', u'#CC79A7', u'#56B4E9',
        u'#009E73', u'#F0E442', u'#0072B2'
    ]

    colorsList = colorsList + ['b', 'm', 'y', 'c', 'k']
    rcParams.update({'figure.autolayout': True})
    rcParams['axes.facecolor'] = 'white'
    rcParams['axes.linewidth'] = 1.0
    rcParams['axes.edgecolor'] = 'black'  # axisbg=axescolor
    rcParams['savefig.facecolor'] = 'white'  # axisbg=axescolor
    rcParams['lines.markersize'] = 4.5
    #read all the data
    iplot = -1
    for ipath, path in enumerate(paths):  #my data
        tag = path.split('/')[-1][-7:]
        os.chdir(path)
        if filter2 == None:
            structs = sorted([
                d for d in os.listdir(os.getcwd())
                if os.path.isdir(d) and filter in d
            ])
        else:
            structs = sorted([
                d for d in os.listdir(os.getcwd())
                if os.path.isdir(d) and d == filter2
            ])
        nStructs = len(structs)
        #         print structs,path
        for istruct, struct in enumerate(structs):
            #         print 'test', istruct, struct
            #             print 'struct',struct
            os.chdir(struct)
            if coloring == 'indiv':
                #             if iplot < nplots -1:
                color = rgb2hex(cm.jet(1. * (iplot + 1) / float(nplots)))
    #             else:
    #                 color = 'k'
            elif coloring == 'method':
                #             color =  colorsList[ipath]
                color = None
            calcs = sorted([
                d for d in os.listdir(os.getcwd())
                if os.path.isdir(d) and os.path.exists('{}/OUTCAR'.format(d))
            ])
            energies = []
            nKs = []
            ns = []  #the base n of the run run
            nDone = 0
            if useSym:
                try:
                    nops, IBZvolcut, IBZvol = readSym(calcs[0])
                except:
                    sys.exit('Stopping. readSym failed. Set useSym to False')
            for calc in calcs:
                if electronicConvergeFinish(calc):
                    ener = getEnergy(calc)  #in energy/atom
                    if not areEqual(ener, 0, 1e-5):
                        nDone += 1
                        energies.append(ener)
                        if 'vc' in path:
                            nK = getNkIBZ(calc, 'KPOINTS')

                        else:
                            nK = getNkIBZ(calc, 'IBZKPT')
                        if nK > maxNk: maxNk = nK
                        nKs.append(nK)
                        ns.append(int(calc.split('_')[-1]))
            #sort by increasing number of kpoints
            if len(energies) > 0:
                iplot += 1
                nKs = array(nKs)
                energies = array(energies)
                ns = array(ns)
                order = argsort(nKs)
                #         print 'struct',struct
                #         print 'energies',energies
                energies = energies[order]
                ns = ns[order]
                nKs = sort(nKs)
                eref = energies[
                    -1]  #the last energy of each struct is that of the most kpoints
                errs = abs(energies - eref) * 1000 + 1e-4  #now in meV
                data[iplot]['ID'] = '{} {}'.format(struct, tag)
                nAtoms = getNatoms('{}/POSCAR'.format(calc))
                data[iplot]['nAtoms'] = nAtoms
                if useSym:
                    data[iplot]['nops'] = nops
                    data[iplot]['IBZvolcut'] = IBZvolcut
                data[iplot]['nDone'] = nDone
                data[iplot]['eners'][:nDone] = energies
                data[iplot]['errs'][:nDone] = errs
                data[iplot]['nKs'][:nDone] = nKs
                data[iplot]['ns'][:nDone] = ns
                data[iplot]['color'] = color
                method = path.split('_')[-1].split('/')[0]
                data[iplot]['method'] = method
            os.chdir(path)
    # os.chdir(extpath)
    if not extpath is None:
        os.chdir(extpath)
        #         print; print atoms_methods
        for atom_method in atoms_methods:
            os.chdir(atom_method)
            if coloring == 'method':
                color = None
                if 'MP' in atom_method:
                    #                 color = colorsList[len(paths)]
                    method = 'MP'

                elif 'Mueller' in atom_method:
                    #                 color = colorsList[len(paths)+1]
                    method = 'Mueller'
                if method not in methods:
                    methods.append(method)
            if filter2 == None:
                structfiles = sorted([
                    d for d in os.listdir(os.getcwd())
                    if os.path.getsize(d) > 0
                ])
            else:
                structfiles = sorted([
                    d for d in os.listdir(os.getcwd())
                    if '_'.join(d.split('_')[:2]) == filter2
                    and os.path.getsize(d) > 0
                ])
            for structfile in structfiles:
                if useSym:
                    nops, IBZvolcut, nAtoms = copyData(structfile, data)
                if coloring == 'indiv':
                    if iplot < nplots - 1:
                        color = cm.jet(1. * (iplot + 1) / float(nplots))
                    else:
                        color = 'k'
                iplot += 1
                energies = []
                nKs = []
                lines = readfile(structfile)
                for line in lines:
                    nK = int(line.split('\t')[0])
                    if nK > maxNk: maxNk = nK
                    nKs.append(nK)
                    energies.append(-float(line.split('\t')[1].split('\r')[0]))
                nKs = array(nKs)
                energies = array(energies)
                nDone = len(energies)
                order = argsort(nKs)
                energies = energies[order]
                eref = energies[
                    -1]  #the last energy of each struct is that of the most kpoints
                nKs = sort(nKs)
                errs = abs(energies - eref) * 1000 + 1e-4  #now in meV
                struct = '_'.join(structfile.split('_')[:2])
                data[iplot]['ID'] = atom_method + struct
                data[iplot]['nAtoms'] = nAtoms
                if useSym:
                    data[iplot]['nops'] = nops
                    data[iplot]['IBZvolcut'] = IBZvolcut
                data[iplot]['nDone'] = len(energies)
                data[iplot]['eners'][:nDone] = energies
                data[iplot]['errs'][:nDone] = errs
                data[iplot]['nKs'][:nDone] = nKs
                data[iplot]['color'] = color
                data[iplot]['method'] = method
            os.chdir(extpath)
    nplots = iplot + 1

    lines = [' ID , nKIBZ , ener , err, nAtoms, nops,IBZcut\n']
    for iplot in range(nplots):
        n = data[iplot]['nDone']
        for icalc in range(n):  #data[iplot]['eners'][:n].tolist()
            lines.append('{}_n{},{},{:15.12f},{:15.12f},{},{},{}\n'.format(data[iplot]['ID'],\
              data[iplot]['ns'][icalc], data[iplot]['nKs'][icalc],\
              data[iplot]['eners'][icalc],data[iplot]['errs'][icalc],\
              data[iplot]['nAtoms'],data[iplot]['nops'],data[iplot]['IBZvolcut']))
    writefile(lines, '{}/summary.csv'.format(summaryPath))

    #plots
    if maxNk > 1:
        if filter[0] == '_': filter = ''  #labels can't begin with _
        #         plotTypes = ['linear','loglog', 'loglinear'];ylabels = ['Vasp error energy/atom (eV)','Error (meV)','Error (meV)']
        # print 'plot only loglog'
        plotTypes = ['loglog']
        ylabels = ['Error (meV)']
        #     plotTypes = []

        xtext = 'N k-points'

        for it, plotType in enumerate(plotTypes):
            fig = figure()
            ax1 = fig.add_subplot(111)
            xlabel(xtext)
            ylabel(ylabels[it])
            # title('Convergence vs mesh method')
            #ylim((1e-12,1e0))
            oldmethod = ''
            methods2 = []
            for iplot in range(nplots):
                labelStr = None
                n = data[iplot]['nDone']
                if coloring == 'method':
                    method = data[iplot]['method']
                    data[iplot]['color'] = colorsList[methods.index(method)]
                    if method != oldmethod and method not in methods2:
                        if doLabel:
                            labelStr = '{} {}'.format(filter,
                                                      data[iplot]['method'])
                        plotData(fig, summaryPath, data[iplot], n, plotType,
                                 filter, doLegend, labelStr)
                        oldmethod = method
                        labelStr = None
                        methods2.append(method)
                    else:
                        plotData(fig, summaryPath, data[iplot], n, plotType,
                                 filter, doLegend, labelStr)
                elif coloring == 'indiv':
                    if doLabel:
                        labelStr = '{} {}'.format(filter, data[iplot]['ID'])
                    plotData(data[iplot], n, plotType, filter, doLegend,
                             labelStr)
        #Method averaging
        if coloring == 'method':
            #         print 'Averaging, plotting method errors'
            nbins = int(10 * ceil(log10(maxNk)))  # 10 bins per decade
            nKbins = array([(10.0**(1 / 10.0))**i for i in range(nbins)])
            fig = figure()
            ax1 = fig.add_subplot(111)
            xlabel('N k-points (smoothed by factor {})'.format(
                int(smoothFactor)))
            ylabel('Error (meV)')
            methodCostsLogs = []
            for im, method in enumerate(methods):
                methnKmax = 0
                binCounts = zeros(nbins, dtype=int32)
                binErrs = zeros(nbins, dtype=float)
                costLogs = zeros(
                    nbins, dtype=float
                )  # "Costs" relative to excellent Si Monkhorst Pack, which has err = 10^3/nK^3 + 10^-3 meV.
                for iplot in range(nplots):
                    if data[iplot]['method'] == method:
                        for icalc in range(data[iplot]['nDone'] - 1):
                            nK = data[iplot]['nKs'][icalc]
                            if nK > methnKmax: methnKmax = nK
                            if nK > 1:
                                for ibin in range(nbins):
                                    if abs(log10(nK/nKbins[ibin])) <= log10(smoothFactor)\
                                      and nKbins[ibin]<= maxNk:
                                        binErrs[ibin] += data[iplot]['errs'][
                                            icalc]
                                        costLogs[ibin] += log10(
                                            data[iplot]['errs'][icalc] /
                                            (10**3 / (nK**3.0) + 0.001))
                                        binCounts[ibin] += 1
                mask = where(binCounts > 0)
                binErrs2 = binErrs[mask[0]]
                binCounts2 = binCounts[mask[0]]
                nKbins2 = nKbins[mask[0]]
                costLogs2 = costLogs[mask[0]]
                nbins2 = len(nKbins2)
                avgErrs = [
                    binErrs2[ibin] / binCounts2[ibin] for ibin in range(nbins2)
                ]
                avgcostLogs = [
                    costLogs2[ibin] / binCounts2[ibin]
                    for ibin in range(nbins2)
                ]
                avgcostLins = [10**avgcostLogs[ibin] for ibin in range(nbins2)]
                methodCostsLogs.append(mean(avgcostLogs))
                loglog(nKbins2,avgErrs,label = method,\
                      color = colorsList[im], marker = None)
                loglog(nKbins2,avgcostLins,label = None,\
                      color = colorsList[im], marker = None,linestyle=':')
                #         print 'Method',method, 'nKmax',methnKmax, 'avgLogCost', mean(avgcostLogs)
                legend(loc='lower left', prop={'size': 12})
                fig.savefig('{}/methodErrs'.format(summaryPath))
            close('all')
    if maxNk > 1:
        return [methodCostsLogs[0], mean(data['nDone'])
                ]  #there is only one method when running this routine
    else:
        return [100, 0]
        structs = sorted([d for d in os.listdir(os.getcwd()) if os.path.isdir(d) and filter in d])
    else:
        structs = sorted([d for d in os.listdir(os.getcwd()) if os.path.isdir(d) and d==filter2])
    for struct in structs:
        if collateMeshMat:meshPlots.write('(* {} *)\n'.format(struct))
        os.chdir(struct)
        iplot += 1
        calcs = sorted([d for d in os.listdir(os.getcwd()) if os.path.isdir(d)])
        if len(calcs) > maxCalcs: maxCalcs = len(calcs)
        if collateMeshMat:
            for ic, calc in enumerate(calcs):
                os.chdir(calc)
                if ic == 0: os.system('cp bounds ../')
                if os.path.exists('cell_IBZmesh.m'):
                    meshPlots.write('\t(* {} *)\n'.format(calc))
                    lines = readfile('cell_IBZmesh.m')
                    lines.append( '\n\n')
                    meshPlots.writelines(lines)
                os.chdir('../')          
        os.chdir(path)
    if collateMeshMat:
        meshPlots.close()
        
#external run paths are of the form extmethodpath/atom_convergence/11_atom 
if not extpaths is None:
    for ipath,extpath in enumerate(extpaths):
        os.chdir(extpath)
        method = extpath.split('/')[0]
        if collateMeshMat:
            meshPlots = open('IBZmeshPlots','w')
        atomdirs = sorted([d for d in os.listdir(extpath) if os.path.isdir(d) and filter in d])# os.chdir(extpath)
Exemplo n.º 23
0

'''Reads formation energies in structures.in or .holdout  
Ignores weights, and writes for energy a scaled formation energy that spreads differences in FE for low energy,
and compresses differences in FE for high FE'''

#dir = '/fslhome/bch/cluster_expansion/graphene/csv1-8W/'
dir = '/fslhome/bch/cluster_expansion/graphene/test1/'
#infile = dir+'structures.in.441.FEsorted'
infile = dir + 'structures.holdout'
#infile = dir+'structures.in'
#outfile = dir+'structures.in'
outfile = dir + 'structures.holdout'
FEs = []
indices = []
lines = readfile(infile)

#Find maximum and min formation energies
for i, line in enumerate(lines):
    if 'FE' in line:
        energy = float(
            line.split()[line.split().index('FE') +
                         2].split(',')[0])  #FE = 1.2578,  etc.  remove any ","
        FEs.append(energy)
    if '#Energy' in line:
        indices.append(i)  #where label 'Energy' appeared
FEmax = amax(FEs)
FEmin = amin(FEs)
indices = array(indices)

#Write new Fes
Exemplo n.º 24
0
    latticeType, packingFraction, mink_reduce, lattvec_u,arenormal,\
    unique_anorms,points_in_ppiped #,three_perp,

from numpy import array, arccos, dot, cross, pi,  floor, sum, sqrt, exp, log, asarray
from numpy import transpose,rint,inner,multiply,size,argmin,argmax,nonzero,float64, identity
from numpy import ceil,real,unravel_index

from scipy.optimize import minimize
from copy import copy,deepcopy
fprec=float64
from numpy import zeros #use arrays, not "matrix" class
#from numpy.matlib import zeros, matrix #creates np.matrix rather than array, but limited to 2-D!!!!  uses *, but array uses matrixmultiply
from numpy.linalg import norm, det, inv, eig
from numpy.random import randint,random
from itertools import combinations

sys.path.append('/bluehome2/bch/pythonscripts/cluster_expansion/analysis_scripts/') 
from analysisToolsVasp import writeEnergiesOszicar, writedirnames, nstrip, writeNk, writeNkIBZ, \
  writeElConverge, writeElSteps, writeCPUtime, enerparts, getdata, readfile, writefile, \
  getms, writefermi, removezeros,getEf

'''reads chgcar from dir1 and multiplies by 2 (for superlattice of volume 2 along z axis), 
and writes it twice into CHGCAR for dir2 '''

dir1 = '/fslhome/bch/cluster_expansion/alal/cubic_al/mp_c1,3/c1_8x8x8/BANDS/'
dir2 = '/fslhome/bch/cluster_expansion/alal/cubic_al/mp_c1,3/c3_8x8x4/BANDS/'

lines1 = readfile(dir1 + 'CHGCAR')
lines2 = readfile(dir2 + 'CHGCAR')

print 'Done'