raise ValueError('NSKIP must be less than num of files given: ',
len(infiles))
infiles.sort(key=get_key, reverse=True)
del infiles[:nskip]
na = int(180.0 / dang) + 1
angd, agr = adf_average(infiles,
dang=dang,
rcut=rcut,
triplets=triplets,
no_average=no_average,
specorder=specorder)
if not sigma == 0:
print(' Gaussian smearing...')
for it, t in enumerate(triplets):
agr[it, :] = gsmear(angd, agr[it, :], sigma)
if flag_plot:
plot_figures(angd, agr, triplets)
print('')
print(' RDF graphes are plotted.')
print(' Check graph_adf.png')
if out4fp:
write_out4fp(ofname, triplets, na, angd, rcut)
else:
write_normal(ofname, triplets, na, angd, agr)
print(' Wrote ' + ofname)
nspcs = len(specorder)
if nspcs < 1:
raise ValueError('--specorder must be set.')
if len(infiles) > 1:
infiles.sort(key=get_key,reverse=True)
del infiles[:nskip]
nr= int(rmax/dr) +1
rd,agr= rdf_average(infiles,nr,specorder,dr=dr,rmax=rmax,
pairwise=pairwise)
if not sigma == 0:
print(' Gaussian smearing...')
#...Smearing of total RDF
agrt= gsmear(rd,agr[0,0],sigma)
agr[0,0,:] = agrt[:]
#...Smearing of inter-species RDF
for isid in range(1,nspcs+1):
for jsid in range(1,nspcs+1):
agrt= gsmear(rd,agr[isid,jsid],sigma)
agr[isid,jsid,:] = agrt[:]
if out4fp:
write_out4fp(ofname,specorder,nspcs,agr,nr,rmax,pairs)
else:
write_normal(ofname,specorder,nspcs,rd,agr,nr,)
if plot:
plot_figures(rd,agr)
print('')
def main():
args = docopt(__doc__.format(os.path.basename(sys.argv[0])))
infiles = args['INFILE']
dr = float(args['-d'])
rmax = float(args['--rmax'])
rmin = float(args['--rmin'])
sigma = int(args['--gsmear'])
nnmax = int(args['--nnmax'])
ofname = args['-o']
if ofname == 'None':
ofname = None
specorder = [x for x in args['--specorder'].split(',')]
if specorder == ['None']:
specorder = []
plot = args['--plot']
nskip = int(args['--skip'])
SQ = args['--SQ']
if SQ:
qmax = float(args['--qmax'])
qmin = float(args['--qmin'])
lscatter = [float(x) for x in args['--scatter-length'].split(',')]
if len(lscatter) != len(specorder):
raise ValueError('--scatter-length is not set correctly.')
out4fp = args['--out4fp']
fortran = args['--fortran']
if out4fp and ofname is None:
raise ValueError("Output file name must be specified with option -o.")
if out4fp and not SQ:
pairwise = True
pairs0 = args['--pairs'].split(',')
pairs = []
for pair in pairs0:
spi, spj = pair.split('-')
try:
isid = specorder.index(spi) + 1
except:
isid = 0
try:
jsid = specorder.index(spj) + 1
except:
jsid = 0
if jsid < isid:
itmp = jsid
jsid = isid
isid = itmp
pairs.append((isid, jsid))
else:
no_pairwise = args['--no-pairwise']
pairwise = not no_pairwise
pairs = None
nspcs = len(specorder)
if nspcs < 1:
raise ValueError('--specorder must be set.')
if len(infiles) > 1:
infiles.sort(key=get_key, reverse=True)
del infiles[:nskip]
if len(infiles) < 1:
raise ValueError('No input files to be processed.')
print(infiles)
tiny = 1.0e-8
nr = int((rmax - rmin + tiny) / dr) + 1
rd, agr = rdf_average(infiles,
specorder,
dr=dr,
rmin=rmin,
rmax=rmax,
pairwise=pairwise,
nnmax=nnmax,
fortran=fortran)
if not sigma == 0:
#print(' Gaussian smearing...')
#...Smearing of total RDF
agrt = gsmear(rd, agr[0, 0, :], sigma)
agr[0, 0, :] = agrt[:]
#...Smearing of inter-species RDF
for isid in range(1, nspcs + 1):
for jsid in range(isid, nspcs + 1):
agrt = gsmear(rd, agr[isid, jsid, :], sigma)
agr[isid, jsid, :] = agrt[:]
if SQ:
nsys = nappy.io.read(infiles[0])
rho = float(nsys.num_atoms()) / nsys.get_volume()
if nspcs > 1:
#...Redfine total RDF as weighted sum of g_{ij}(r) in case of multiple species
natms = [float(nsys.num_atoms())]
cs = [1.0]
for ispcs in range(1, nspcs + 1):
natms.append(float(nsys.num_atoms(ispcs)))
cs.append(natms[ispcs] / natms[0])
bmean = 0.0
for isid in range(1, nspcs + 1):
bi = lscatter[isid - 1]
ci = cs[isid]
bmean += ci * bi
agr[0, 0, :] = 0.0
for isid in range(1, nspcs + 1):
bi = lscatter[isid - 1]
ci = cs[isid]
for jsid in range(isid, nspcs + 1):
bj = lscatter[jsid - 1]
cj = cs[jsid]
wij = ci * cj * bi * bj / bmean
if isid == jsid:
agr[0, 0, :] += agr[isid, jsid, :] * wij
else:
agr[0, 0, :] += 2.0 * agr[isid, jsid, :] * wij
qs, sqs = gr_to_SQ(rd, agr[0, 0, :], rho, qmin=0.7, qmax=qmax, nq=200)
#...Regardless ofname, write out.rdf in normal format
write_rdf_normal(
'out.rdf',
specorder,
nspcs,
rd,
agr,
nr,
)
if SQ:
write_sq_out4fp('out.sq', qs, sqs)
#...Format of output (named by ofname) depends on out4fp
if ofname is not None:
if out4fp:
write_rdf_out4fp(ofname,
specorder,
nspcs,
agr,
nr,
rmax,
pairs=pairs,
rmin=rmin)
else:
write_rdf_normal(
ofname,
specorder,
nspcs,
rd,
agr,
nr,
)
if plot:
plot_figures(specorder, rd, agr)
print('')
print(' RDF graphes are plotted.')
if nspcs == 1:
print(' Check graph_rdf_total.png')
else:
print(' Check graph_rdf_total.png and graph_rdfs.png')
else:
print(' Check out.rdf with gnuplot, like')
print(" gnuplot> plot 'out.rdf' us 1:2 w l")
print('')
if ofname is not None:
print(" In addition to out.rdf, {0:s} is also written.".format(
ofname))
print('')
return None
def rdf_of_atom(ia, nsys, rmax=5.0, dr=0.1, sigma=0):
"""
Compute RDF of specified atom.
"""
#...Radial points
nr = int(rmax / dr) + 1
rd = np.array([dr * ir + dr / 2 for ir in range(nr)], )
nspcs = len(nsys.specorder)
ndri = np.zeros((nspcs + 1, nr), dtype=float)
spos = nsys.get_scaled_positions()
sids = nsys.atoms.sid
natm = nsys.num_atoms()
pi = spos[ia]
hmat = nsys.get_hmat()
#...Compute ndr of atom-ia
for ja in nsys.neighbors_of(ia, rcut=rmax):
pj = spos[ja]
jsid = sids[ja]
pij = pj - pi
pij = pij - np.round(pij)
vij = np.dot(hmat, pij)
rij2 = np.dot(vij, vij)
rij = np.sqrt(rij2)
ir = int(rij / dr)
ndri[0, ir] += 1.0
ndri[jsid, ir] += 1.0
#...Normalize to get raw RDF(ia)
#.....Total RDF(ia)
tmp = 4.0 * np.pi * (natm - 1) * dr
for ir in range(1, nr):
r = dr * ir
ndri[0, ir] /= tmp * r * r
#.....Species-decomposed RDF(ia)
natms = [float(natm)]
for isp in range(1, nspcs + 1):
natms.append(float(nsys.num_atoms(isp)))
vol = nsys.get_volume()
isid = sids[ia]
tmp0 = 4.0 * np.pi * dr / vol
for jsid in range(1, nspcs + 1):
nj = natms[jsid]
if jsid == isid:
tmp = tmp0 * (nj - 1)
else:
tmp = tmp0 * nj
for ir in range(1, nr):
r = dr * ir
ndri[jsid, ir] /= tmp * r * r
rdfi = np.zeros(ndri.shape)
#...Gaussian smearing
if not sigma == 0:
#...Total
rdfi[0, :] = gsmear(rd, ndri[0, :], sigma)
#...Species-decomposed
for jsid in range(1, nspcs + 1):
rdfi[jsid, :] = gsmear(rd, ndri[jsid, :], sigma)
return rd, rdfi
def nbplot(nsys, dr=0.1, rmin=0.0, rmax=5.0, nnmax=200, pairs=None, sigma=0):
"""
Plot RDFs of given nsys on the jupyter notebook.
"""
if not 'JPY_PARENT_PID' in os.environ:
raise Exception('This routine must be called on jupyter notebook.')
import matplotlib.pyplot as plt
try:
import seaborn as sns
sns.set(context='talk', style='ticks')
except:
pass
nspcs = len(nsys.specorder)
try:
nr = int((rmax - rmin) / dr) + 1
rd, gr = rdf(nsys, nspcs, dr, nr, rmax, rmin=rmin, nnmax=nnmax)
except:
raise Exception('rdf(..) failed.')
if sigma > 0:
#...Smearing of total RDF
grt = gsmear(rd, gr[0, 0, :], sigma)
gr[0, 0, :] = grt[:]
#...Smearing of inter-species RDF
for isid in range(1, nspcs + 1):
for jsid in range(isid, nspcs + 1):
grt = gsmear(rd, gr[isid, jsid, :], sigma)
gr[isid, jsid, :] = grt[:]
plt.figure(figsize=(8, 6))
x = rd
if not pairs:
for i in range(nspcs):
isp = i + 1
spi = nsys.specorder[i]
for j in range(nspcs):
jsp = j + 1
spj = nsys.specorder[j]
if j < i:
continue
y = gr[isp, jsp, :]
plt.plot(x, y, label='{0:s}-{1:s}'.format(spi, spj))
else: # only specified pairs are plotted in addition to total RDF
for p in pairs:
spi, spj = p
try:
isp = nsys.specorder.index(spi) + 1
jsp = nsys.specorder.index(spj) + 1
except:
raise ValueError('No such species or pairs.')
y = gr[isp, jsp, :]
plt.plot(x, y, label='{0:s}-{1:s}'.format(spi, spj))
#...Total RDF
y = gr[0, 0, :]
plt.plot(x, y, 'r--', label='Total RDF')
plt.xlabel('Distance ($\mathrm{\AA}$)')
plt.ylabel('RDF')
plt.legend(bbox_to_anchor=(1.05, 1))
plt.show()
return None
def main():
args = docopt(__doc__.format(os.path.basename(sys.argv[0])))
infiles = args['INFILE']
triplets = args['--triplets']
specorder = [x for x in args['--specorder'].split(',')]
if specorder == ['None']:
specorder = []
if triplets == 'None':
raise ValueError('Triplets must be specified.')
triplets = [t.split('-') for t in triplets.split(',')]
if len(triplets) == 0:
raise ValueError('There must be at least one triplet.')
out4fp = args['--out4fp']
dang = float(args['-w'])
drad = np.pi * dang / 180.0
rcut = float(args['-r'])
nnmax = int(args['--nnmax'])
sigma = int(args['--gsmear'])
fortran = args['--fortran']
ofname = args['-o']
if ofname == 'None':
ofname = None
flag_plot = args['--plot']
nskip = int(args['--skip'])
if out4fp and ofname is None:
raise ValueError("Output file name must be specified with option -o.")
if nskip > len(infiles):
raise ValueError('NSKIP must be less than num of files given: ',
len(infiles))
if len(infiles) > 1:
infiles.sort(key=get_key, reverse=True)
if nskip > 0 and len(infiles) > nskip:
del infiles[:nskip]
na = int(180.0 / dang)
angd, agr = adf_average(infiles,
dang=dang,
rcut=rcut,
triplets=triplets,
specorder=specorder,
fortran=fortran,
nnmax=nnmax)
if not sigma == 0:
print(' Gaussian smearing...')
for it, t in enumerate(triplets):
agr[it, :] = gsmear(angd, agr[it, :], sigma)
if flag_plot:
plot_figures(angd, agr, triplets)
print('')
print(' RDF graphes are plotted.')
print(' Check graph_adf.png')
#...Regardless ofname, write out.adf in normal format
write_normal('out.adf', triplets, na, angd, agr)
#...Format of output (named by ofname) depends on out4fp
if ofname is not None:
if out4fp:
write_out4fp(ofname, triplets, na, angd, agr, rcut)
else:
write_normal(ofname, triplets, na, angd, agr)
print(' Wrote out.adf')
if ofname is not None:
print(' Wrote {0:s}'.format(ofname))
return None