def run_anaddb(self, dipdip=1):
print("Run anaddb")
#os.system('cp ./abinit.mrgddb.tmpl %s/abinit.mrgddb.in' % self.dirname)
gen_mrgddb_input(self.dirname)
os.chdir(self.dirname)
os.system('mrgddb <abinit.mrgddb.in>abinit.mrgddb.log')
myDDB = DdbFile(filepath='abinit_mrgddb.out', read_blocks=True)
nqpts = ' '.join(map(str, myDDB._guess_ngqpt()))
natifc = len(self.atoms)
atifc = ' '.join([str(i + 1) for i in range(len(self.atoms))])
dipdip = dipdip
tdict = {
'nqpts': nqpts,
'natifc': natifc,
'atifc': atifc,
'dipdip': dipdip
}
with open("../abinit_ifc.in.tmpl") as myfile:
tmpl = string.Template(myfile.read())
text = tmpl.substitute(tdict)
os.system('cp ../abinit_ifc.files.tmpl abinit_ifc.files')
with open('abinit_ifc.in', 'w') as myfile:
myfile.write(text)
#os.system('cp ../abinit_ifc.in.tmpl %s/abinit_ifc.in' % self.dirname)
os.system('anaddb <abinit_ifc.files >abinit_ifc.log')
os.chdir('../')
def analyze_all_modes(self):
self.results = OrderedDict()
self.results[
'lattice_parameter'] = self.atoms.get_cell_lengths_and_angles()
# emacro & BEC
myDDB = DdbFile(filepath='%s/abinit_mrgddb.out' % (self.dirname),
read_blocks=True)
emacro, becs = myDDB.anaget_emacro_and_becs()
self.results['dielectric_tensor'] = emacro[0].reduced_tensor
self.results['Born_effective_charges'] = becs
self.results['number_of_qpoints'] = myDDB._guess_ngqpt()
self.results['ecut'] = myDDB.params[u'ecut']
self.results['tsmear'] = myDDB.params[u'tsmear']
self.results['nsppol'] = myDDB.params[u'nsppol']
self.results['nkpt'] = myDDB.params[u'nkpt']
filefname = os.path.join(self.dirname, 'abinit.files')
with open(filefname) as myfile:
self.results['pseudopotentials'] = [
os.path.split(x)[-1].strip() for x in myfile.readlines()[5:]
]
# Phonon
self.results['phonon'] = OrderedDict()
qpoints = OrderedDict([('Gamma', (0, 0, 0)), ('X', (0.5, 0, 0)),
('M', (0.5, 0.5, 0)), ('R', (0.5, 0.5, 0.5))])
# Phonon: Gamma_reduced
qname = 'Gamma_reduced'
self.results['phonon'][qname] = OrderedDict()
hamk, freqs, evals, evecs, edisps, dc, ds = self.analyze_gamma(
ibands=None, label='DYM_Gamma_reduced', is_asr=False)
self.results['phonon'][qname]['dynamic_matrix'] = hamk
self.results['phonon'][qname]['eigenvalues'] = evals
self.results['phonon'][qname]['frequencies'] = freqs
self.results['phonon'][qname]['eigenvectors'] = evecs
self.results['phonon'][qname]['eigen_displacements'] = edisps
self.results['phonon'][qname]['dynamic_matrix_contributions'] = dc
self.results['phonon'][qname]['dynamic_matrix_sensitivities'] = ds
# Phonon: Other Qpoints
for qname in qpoints:
qpoint = qpoints[qname]
self.results['phonon'][qname] = OrderedDict()
self.results['phonon'][qname]['qpoint'] = qpoint
hamk, freqs, evals, evecs, edisps, dc, ds = self.analyze_qpoint(
qpoint=qpoint, qpt_name=qname, ibands=None)
self.results['phonon'][qname]['dynamic_matrix'] = hamk
self.results['phonon'][qname]['eigenvalues'] = evals
self.results['phonon'][qname]['frequencies'] = freqs
self.results['phonon'][qname]['eigenvectors'] = evecs
self.results['phonon'][qname]['eigen_displacements'] = edisps
self.results['phonon'][qname]['dynamic_matrix_contributions'] = dc
self.results['phonon'][qname]['dynamic_matrix_sensitivities'] = ds
#with open('data/%s.json' % (self.dirname), 'w') as myfile:
# json.dump(self.results, myfile)
with open('data/%s.pickle' % (self.dirname), 'wb') as myfile:
cPickle.dump(self.results, myfile)
datadir = 'data/%s' % self.dirname
if not os.path.exists(datadir):
os.makedirs(datadir)
os.system('cp %s/*.in %s' % (self.dirname, datadir))
os.system('cp %s/*.nc %s' % (self.dirname, datadir))
os.system('cp %s/*DDB %s' % (self.dirname, datadir))
os.system('cp %s/*.files %s' % (self.dirname, datadir))
os.system('cp %s/CONTCAR %s' % (self.dirname, datadir))
os.system('cp %s/*.txt %s' % (self.dirname, datadir))
os.system('cp %s/*.out %s' % (self.dirname, datadir))
os.system('tar -zcvf data/%s.tar.gz %s' % (self.dirname, datadir))
