# Store detected errors
if 'error' in locals():
HT.updateResults({'error': error}, cinfo['id'])
else:
print('Gathering results')
results = gather(cinfo['results'])
print('Updating results.')
# updateresults could be assumed from dictionary keys and automated.
HT.updateResults(results, cinfo['id'])
print(
'Energy OK. Ending calculation, deleting junk files and fetching results.'
)
HT.end(cinfo['id'])
#cleanup function
# Can change this to a step dictionary
os.remove('CHG')
print('Updating settings.')
# Update POTCAR INFO
POTCAR_version = execute('grep -a \'TITEL\' POTCAR | awk \'{ print $4 }\'')
cinfo['settings']['POTCAR'] = POTCAR_version.strip().replace('\n', ', ')
HT.updateSettings(cinfo['settings'], cinfo['id'])
# Update priority with Machine Learning model
#if step == 21:
elif energy == '' or not 'energy' in locals():
HT.updateResults({'error': 'Energy missing'}, cid)
print('Energy missing! Error...')
elif not os.path.isfile('CHGCAR') and not os.path.isfile('CHG'):
HT.updateResults({'error': 'CHGCAR and CHG missing. VASP Error?'}, cid)
print('CHGCAR/CHG missing. VASP Error?')
else:
print(
'Energy OK. Ending calculation, deleting junk files and fetching results.'
)
print('This is the HT.end cid: ' + str(cid))
ended = 0
tries = 0
while (ended == 0 and tries < 10):
ended = HT.end(cid)
tries = tries + 1
print tries
time.sleep(random.randint(10, 100))
if (ended == 0):
print('ERROR: I tried to end calculation ' + str(cid) + str(tries) +
' times, but no succes.') #tries should always be 10
HT.updateResults({'error': 'Ending calculation failed'}, cid)
else:
if status < 15:
#os.remove('CHGCAR')
os.remove('CHG')
results = HT.getResults(cid)
#END CALCULATION AND FETCH RESULTS
energy = execute('grep \'energy without entropy\' OUTCAR | tail -1 | awk \'{ print $4 }\'')
if 'error' in locals():
HT.updateResults({'error':error}, cid)
elif energy=='' or not 'energy' in locals():
HT.updateResults({'error':'Energy missing'}, cid)
print('Energy missing! Error...')
elif not os.path.isfile('CHGCAR') and not os.path.isfile('CHG'):
HT.updateResults({'error':'CHGCAR and CHG missing. VASP Error?'}, cid)
print('CHGCAR/CHG missing. VASP Error?')
else:
print('Energy OK. Ending calculation, deleting junk files and fetching results.')
HT.end(cid)
if status<19:
os.remove('CHG')
results = HT.getResults(cid)
#could leave this out when working with QZP's
numberofatoms = lines[6][:-1].lstrip()
numberofatoms = " ".join(numberofatoms.split())
numberofatoms = sum(map(int, numberofatoms.split(' ')))
energy = float(energy)
if step == 1:
#END CALCULATION AND FETCH RESULTS
energy = execute('grep \'energy without entropy\' OUTCAR | tail -1 | awk \'{ print $4 }\'')
if 'error' in locals():
HT.updateResults({'error':error}, cid)
elif energy=='' or not 'energy' in locals():
HT.updateResults({'error':'Energy missing'}, cid)
print('Energy missing! Error...')
elif not os.path.isfile('CHGCAR') and not os.path.isfile('CHG'):
HT.updateResults({'error':'CHGCAR and CHG missing. VASP Error?'}, cid)
print('CHGCAR/CHG missing. VASP Error?')
else:
print('Energy OK. Ending calculation, deleting junk files and fetching results.')
HT.end(cid)
if status<19:
os.remove('CHG')
results = HT.getResults(cid)
#could leave this out when working with QZP's
numberofatoms = lines[6][:-1].lstrip()
numberofatoms = " ".join(numberofatoms.split())
numberofatoms = sum(map(int, numberofatoms.split(' ')))
energy = float(energy)
if step == 1:
#HTML.setMLPriority(newq, 2, ['mass','Ecoh','EN','IP'], N_init)
#
#for i in range(N_init):
# calc = HTc.fetchgetstart(newq)
# HTc.updateResults({target: rdict[calc['file']]})
#
# if rdict[calc['file']] < limit:
# stable += 1
# print('Found ' + str(stable) + ' stable materials (' + str(int(round(100*stable/tstable,0))) + ' %) in ' + str(i+1) + ' samples.')
# HTc.end()
for i in range(nsample):
if i % batch_size == 0:
HTML.updateMLPriority(
newq,
stat=2,
modelClass='sklearn.gaussian_process.GaussianProcessRegressor',
target='Ehull',
features=['mass', 'Ecoh', 'EN', 'IP'],
maxParallel=1)
calc = HTc.fetchgetstart(newq)
print(calc)
HTc.updateResults({target: rdict[calc['file']]})
if rdict[calc['file']] < limit:
stable += 1
print('Found ' + str(stable) + ' stable materials (' +
str(int(round(100 * stable / tstable, 0))) + ' %) in ' + str(i + 1) +
' samples.')
HTc.end()