def distance(self, entry_id, entry_jd, rcut=50):
ids_pair = [entry_id, entry_jd]
ids_pair.sort()
distance_entry = self.pcdb.db.distances.find_one({'pair': ids_pair},
{'distance': 1})
self.pcdb.db.distances.create_index([("pair", ASCENDING)])
if distance_entry is None:
print('Distance not in DB')
fingerprints = {}
for entry_ijd in [entry_id, entry_jd]:
if self.pcdb.db.fingerprints.find_one({'_id': entry_ijd
}) is None:
structure = self.get_structure(entry_ijd)
analysis = StructureAnalysis(structure, radius=rcut)
x, ys = analysis.fp_oganov()
fingerprint = {'_id': entry_ijd}
for k in ys:
atomic_number1 = atomic_number(structure.species[k[0]])
atomic_number2 = atomic_number(structure.species[k[1]])
pair = '%06d' % min(
atomic_number1 * 1000 + atomic_number2,
atomic_number2 * 1000 + atomic_number1)
fingerprint[pair] = list(ys[k])
if self.pcdb.db.fingerprints.find_one({'_id': entry_ijd
}) is None:
self.pcdb.db.fingerprints.insert(fingerprint)
else:
self.pcdb.db.fingerprints.update({'_id': entry_ijd},
fingerprint)
fingerprints[entry_ijd] = fingerprint
else:
fingerprints[
entry_ijd] = self.pcdb.db.fingerprints.find_one(
{'_id': entry_ijd})
dij = []
for pair in fingerprints[entry_id]:
if pair in fingerprints[entry_jd] and pair != '_id':
uvect1 = unit_vector(fingerprints[entry_id][pair])
uvect2 = unit_vector(fingerprints[entry_jd][pair])
dij.append(0.5 * (1.0 - np.dot(uvect1, uvect2)))
distance = float(np.mean(dij))
self.pcdb.db.distances.insert({
'pair': ids_pair,
'distance': distance
})
else:
distance = distance_entry['distance']
return distance
def distance(self, entry_id, entry_jd, rcut=50):
ids_pair = [entry_id, entry_jd]
ids_pair.sort()
distance_entry = self.pcdb.db.distances.find_one({'pair': ids_pair}, {'distance': 1})
self.pcdb.db.distances.create_index([("pair", pymongo.ASCENDING)])
if distance_entry is None:
print('Distance not in DB')
fingerprints = {}
for entry_ijd in [entry_id, entry_jd]:
if self.pcdb.db.fingerprints.find_one({'_id': entry_ijd}) is None:
structure = self.get_structure(entry_ijd)
analysis = StructureAnalysis(structure, radius=rcut)
x, ys = analysis.fp_oganov()
fingerprint = {'_id': entry_ijd}
for k in ys:
atomic_number1 = atomic_number(structure.species[k[0]])
atomic_number2 = atomic_number(structure.species[k[1]])
pair = '%06d' % min(atomic_number1 * 1000 + atomic_number2,
atomic_number2 * 1000 + atomic_number1)
fingerprint[pair] = list(ys[k])
if self.pcdb.db.fingerprints.find_one({'_id': entry_ijd}) is None:
self.pcdb.db.fingerprints.insert(fingerprint)
else:
self.pcdb.db.fingerprints.update({'_id': entry_ijd}, fingerprint)
fingerprints[entry_ijd] = fingerprint
else:
fingerprints[entry_ijd] = self.pcdb.db.fingerprints.find_one({'_id': entry_ijd})
dij = []
for pair in fingerprints[entry_id]:
if pair in fingerprints[entry_jd] and pair != '_id':
uvect1 = unit_vector(fingerprints[entry_id][pair])
uvect2 = unit_vector(fingerprints[entry_jd][pair])
dij.append(0.5 * (1.0 - np.dot(uvect1, uvect2)))
distance = float(np.mean(dij))
self.pcdb.db.distances.insert({'pair': ids_pair, 'distance': distance})
else:
distance = distance_entry['distance']
return distance
def worker(db_settings, entry_id, workdir, target_forces, relaxator_params):
pcdb = get_database(db_settings)
pcm_log.info('[%s]: Starting relaxation. Target forces: %7.3e' %
(str(entry_id), target_forces))
if pcdb.is_locked(entry_id):
return
else:
pcdb.lock(entry_id)
structure = pcdb.get_structure(entry_id)
structure = structure.scale()
print('relaxator_params', relaxator_params)
relaxer = IonRelaxation(structure,
workdir=workdir,
target_forces=target_forces,
waiting=False,
binary=relaxator_params['binary'],
encut=1.3,
kp_grid=None,
kp_density=1E4,
relax_cell=True,
max_calls=10)
print('relaxing on:', relaxer.workdir)
relaxer.run(relaxator_params['nmpiparal'])
pcm_log.info('[%s]: Finished relaxation. Target forces: %7.3e' %
(str(entry_id), target_forces))
filename = workdir + os.sep + 'OUTCAR'
if os.path.isfile(filename):
forces, stress, total_energy = relaxer.get_forces_stress_energy()
if forces is not None:
magnitude_forces = np.apply_along_axis(np.linalg.norm, 1, forces)
print('Forces: Max: %9.3e Avg: %9.3e' %
(np.max(magnitude_forces), np.average(magnitude_forces)))
print('Stress: ', np.max(np.abs(stress.flatten())))
if forces is None:
pcm_log.error('No forces found on %s' % filename)
if stress is None:
pcm_log.error('No stress found on %s' % filename)
if total_energy is None:
pcm_log.error('No total_energy found on %s' % filename)
new_structure = relaxer.get_final_geometry()
if forces is not None and stress is not None and total_energy is not None and new_structure is not None:
pcm_log.info('[%s]: Updating properties' % str(entry_id))
pcdb.update(entry_id, structure=new_structure)
te = total_energy
pcdb.entries.update({'_id': entry_id}, {
'$set': {
'status.relaxation':
'succeed',
'status.target_forces':
target_forces,
'properties.forces':
generic_serializer(forces),
'properties.stress':
generic_serializer(stress),
'properties.energy':
te,
'properties.energy_pa':
te / new_structure.natom,
'properties.energy_pf':
te / new_structure.get_composition().gcd
}
})
# Fingerprint
# Update the fingerprints only if the two structures are really different
diffnatom = structure.natom != new_structure.natom
diffcell = np.max(
np.abs((structure.cell - new_structure.cell).flatten()))
diffreduced = np.max(
np.abs((structure.reduced - new_structure.reduced).flatten()))
if diffnatom != 0 or diffcell > 1E-7 or diffreduced > 1E-7:
analysis = StructureAnalysis(new_structure, radius=50)
x, ys = analysis.fp_oganov(delta=0.01, sigma=0.01)
fingerprint = {'_id': entry_id}
for k in ys:
atomic_number1 = atomic_number(new_structure.species[k[0]])
atomic_number2 = atomic_number(new_structure.species[k[1]])
pair = '%06d' % min(atomic_number1 * 1000 + atomic_number2,
atomic_number2 * 1000 + atomic_number1)
fingerprint[pair] = list(ys[k])
if pcdb.db.fingerprints.find_one({'_id': entry_id}) is None:
pcdb.db.fingerprints.insert(fingerprint)
else:
pcdb.db.fingerprints.update({'_id': entry_id}, fingerprint)
else:
pcm_log.debug('Original and new structures are very similar.')
pcm_log.debug('Max diff cell: %10.3e' % np.max(
np.absolute(
(structure.cell - new_structure.cell).flatten())))
if structure.natom == new_structure.natom:
pcm_log.debug(
'Max diff reduced coordinates: %10.3e' % np.max(
np.absolute((structure.reduced -
new_structure.reduced).flatten())))
else:
pcdb.entries.update({'_id': entry_id},
{'$set': {
'status.relaxation': 'failed'
}})
pcm_log.error(
'Bad data after relaxation. Tagging relaxation as failed')
else:
pcm_log.error('ERROR: File not found %s' % filename)
pcm_log.info('[%s]: Unlocking the entry' % str(entry_id))
pcdb.unlock(entry_id)
def worker(db_settings, entry_id, workdir, target_forces, relaxator_params):
pcdb = get_database(db_settings)
pcm_log.info('[%s]: Starting relaxation. Target forces: %7.3e' % (str(entry_id), target_forces))
if pcdb.is_locked(entry_id):
return
else:
pcdb.lock(entry_id)
structure = pcdb.get_structure(entry_id)
structure = structure.scale()
print('relaxator_params', relaxator_params)
relaxer = IonRelaxation2(structure, workdir=workdir, target_forces=target_forces, waiting=False,
binary=relaxator_params['binary'], encut=1.3, kp_grid=None, kp_density=1E4,
relax_cell=True)
print('relaxing on:', relaxer.workdir)
relaxer.run(relaxator_params['nmpiparal'])
pcm_log.info('[%s]: Finished relaxation. Target forces: %7.3e' % (str(entry_id), target_forces))
filename = workdir + os.sep + 'OUTCAR'
if os.path.isfile(filename):
forces, stress, total_energy = relaxer.get_forces_stress_energy()
if forces is not None:
magnitude_forces = np.apply_along_axis(np.linalg.norm, 1, forces)
print('Forces: Max: %9.3e Avg: %9.3e' % (np.max(magnitude_forces), np.average(magnitude_forces)))
print('Stress: ', np.max(np.abs(stress.flatten())))
if forces is None:
pcm_log.error('No forces found on %s' % filename)
if stress is None:
pcm_log.error('No stress found on %s' % filename)
if total_energy is None:
pcm_log.error('No total_energy found on %s' % filename)
new_structure = relaxer.get_final_geometry()
if forces is not None and stress is not None and total_energy is not None and new_structure is not None:
pcm_log.info('[%s]: Updating properties' % str(entry_id))
pcdb.update(entry_id, structure=new_structure)
te = total_energy
pcdb.entries.update({'_id': entry_id},
{'$set': {'status.relaxation': 'succeed',
'status.target_forces': target_forces,
'properties.forces': generic_serializer(forces),
'properties.stress': generic_serializer(stress),
'properties.energy': te,
'properties.energy_pa': te / new_structure.natom,
'properties.energy_pf': te / new_structure.get_composition().gcd}})
# Fingerprint
# Update the fingerprints only if the two structures are really different
diffnatom = structure.natom != new_structure.natom
diffcell = np.max(np.abs((structure.cell - new_structure.cell).flatten()))
diffreduced = np.max(np.abs((structure.reduced - new_structure.reduced).flatten()))
if diffnatom != 0 or diffcell > 1E-7 or diffreduced > 1E-7:
analysis = StructureAnalysis(new_structure, radius=50)
x, ys = analysis.fp_oganov(delta=0.01, sigma=0.01)
fingerprint = {'_id': entry_id}
for k in ys:
atomic_number1 = atomic_number(new_structure.species[k[0]])
atomic_number2 = atomic_number(new_structure.species[k[1]])
pair = '%06d' % min(atomic_number1 * 1000 + atomic_number2,
atomic_number2 * 1000 + atomic_number1)
fingerprint[pair] = list(ys[k])
if pcdb.db.fingerprints.find_one({'_id': entry_id}) is None:
pcdb.db.fingerprints.insert(fingerprint)
else:
pcdb.db.fingerprints.update({'_id': entry_id}, fingerprint)
else:
pcm_log.debug('Original and new structures are very similar.')
pcm_log.debug('Max diff cell: %10.3e' % np.max(np.absolute((structure.cell -
new_structure.cell).flatten())))
if structure.natom == new_structure.natom:
pcm_log.debug('Max diff reduced coordinates: %10.3e' %
np.max(np.absolute((structure.reduced - new_structure.reduced).flatten())))
else:
pcdb.entries.update({'_id': entry_id}, {'$set': {'status.relaxation': 'failed'}})
pcm_log.error('Bad data after relaxation. Tagging relaxation as failed')
else:
pcm_log.error('ERROR: File not found %s' % filename)
pcm_log.info('[%s]: Unlocking the entry' % str(entry_id))
pcdb.unlock(entry_id)