def get_nonselfconsistent_energies(self, type='beefvdw'):
from gpaw.xc.bee import BEEFEnsemble
if type not in ['beefvdw', 'mbeef', 'mbeefvdw']:
raise NotImplementedError('Not implemented for type = %s' % type)
assert self.scf.converged
bee = BEEFEnsemble(self)
x = bee.create_xc_contributions('exch')
c = bee.create_xc_contributions('corr')
if type == 'beefvdw':
return np.append(x, c)
elif type == 'mbeef':
return x.flatten()
elif type == 'mbeefvdw':
return np.append(x.flatten(), c)
def get_nonselfconsistent_energies(self, type='beefvdw'):
from gpaw.xc.bee import BEEFEnsemble
if type not in ['beefvdw', 'mbeef', 'mbeefvdw']:
raise NotImplementedError('Not implemented for type = %s' % type)
assert self.scf.converged
bee = BEEFEnsemble(self)
x = bee.create_xc_contributions('exch')
c = bee.create_xc_contributions('corr')
if type == 'beefvdw':
return np.append(x, c)
elif type == 'mbeef':
return x.flatten()
elif type == 'mbeefvdw':
return np.append(x.flatten(), c)
def getXCcontribs(jobID):
jobObject = db2BulkJob(jobID)
if jobObject.dftCode == 'gpaw':
from gpaw import restart
from gpaw.xc.bee import BEEFEnsemble
atoms, calc = restart('inp.gpw',
setups='sg15',
xc='mBEEF',
convergence={'energy': 5e-4},
txt='mbeef.txt')
atoms.get_potential_energy()
beef = BEEFEnsemble(calc)
return beef.mbeef_exchange_energy_contribs()
else:
return np.zeros((8, 8))
def run_task(self,fw_spec):
jobID = fw_spec['jobID']
job = db2object(jobID)
if job.dftcode == 'gpaw':
from gpaw import restart
from gpaw.xc.bee import BEEFEnsemble
atoms,calc = restart('inp.gpw', setups='sg15', xc='mBEEF', convergence={'energy': 5e-4}, txt='mbeef.txt')
atoms.get_potential_energy()
beef = BEEFEnsemble(calc)
xcContribs = beef.mbeef_exchange_energy_contribs()
else:
xcContribs = np.zeros((8,8))
return FWAction( stored_data={'xcContribs': xcContribs}
,mod_spec=[{'_push': {'xcContribs': xcContribs}}])
def run_task(self,fw_spec):
from gpaw import restart
from gpaw.xc.bee import BEEFEnsemble
job,params,atoms = initialize(fw_spec)
atoms.set_calculator(job.PBEcalc())
atoms.get_potential_energy()
atoms.calc.write('inp.gpw', mode='all')
atoms,calc = restart('inp.gpw', setups='sg15', xc='mBEEF', convergence={'energy': 5e-4}, txt='mbeef.txt')
atoms.get_potential_energy()
beef = BEEFEnsemble(calc)
xcContribs = beef.mbeef_exchange_energy_contribs()
ase.io.write('final.traj',atoms)
resultDict = misc.mergeDicts([params,trajDetails(ase.io.read('final.traj'))
,{'xcContribs': pickle.dumps(xcContribs)}])
with open('result.json', 'w') as outfile: json.dumps(resultDict, outfile)
return fireworks.core.firework.FWAction( stored_data=resultDict)
def XCcontribsScript():
import cPickle, json, ase
from gpaw import restart
from gpaw.xc.bee import BEEFEnsemble
params, optAtoms = initialize(
) # Remove old .out/.err files, load from fw_spec, and write 'init.traj'
pbeParams = copy.deepcopy(params)
pbeParams['xc'] = 'PBE'
atoms.set_calculator(makeCalc(pbeParams))
atoms.get_potential_energy()
atoms.calc.write('inp.gpw', mode='all')
atoms, calc = restart('inp.gpw',
setups='sg15',
xc='mBEEF',
convergence={'energy': 5e-4},
txt='mbeef.txt')
atoms.get_potential_energy()
beef = BEEFEnsemble(calc)
xcContribs = beef.mbeef_exchange_energy_contribs()
################################
print "Storing Results..."
#-------------------------------
ase.io.write('final.traj', atoms)
resultDict = mergeDicts([
params,
trajDetails(ase.io.read('final.traj')), {
'xcContribs': cPickle.dumps(xcContribs)
}
])
with open('result.json', 'w') as outfile:
outfile.write(json.dumps(resultDict))
if rank() == 0:
with open('result.json', 'r') as outfile:
json.loads(outfile.read()) #test that dictionary isn't 'corrupted'
log(params, atoms)
return 0
mode=PW(800),
xc='PBE',
eigensolver=Davidson(5),
mixer=Mixer(0.1, 5, 100),
kpts=kpts,
occupations=FermiDirac(0.2),
nbands=-16,
txt='pbe.txt')
atoms.get_potential_energy()
atoms.calc.write('inp.gpw', mode='all')
#This uses libxc for MBEEF, you can use for relaxations, etc... (might be
#a little bit faster)
#atoms,calc = restart('inp.gpw', setups='sg15', xc='MGGA_X_MBEEF+GGA_C_PBE_SOL', convergence={'energy': 5e-6}, txt='mbeef.txt')
#But for xc energy contribution output (i.e. single-point calculations)
#only the python version works:
atoms, calc = restart('inp.gpw',
setups='sg15',
xc='mBEEF',
convergence={'energy': 5e-6},
txt='mbeef.txt')
f = paropen('total_energy_and_xc_coefficients.txt', 'w')
print >> f, atoms.get_potential_energy()
from gpaw.xc.bee import BEEFEnsemble
beef = BEEFEnsemble(calc)
print >> f, beef.mbeef_exchange_energy_contribs()