def __init__(self, config):
setup = SubfolderHandle(config['folder'], config['subfolder'])
counter = 0
for file in setup.fileiter(config['dbfiles']):
if counter == 0:
copied = False
if not exists_and_isfile(config['mother_db']):
copy(file, config['mother_db'])
copied = True
info = PySurfDB.info_database(config['mother_db'])
if 'natoms' not in info['dimensions']:
model = True
else:
model = False
mother_db = PySurfDB.load_database(
config['mother_db'],
data=info['variables'],
dimensions=info['dimensions'],
model=model,
sp=False)
counter += 1
if copied is True:
continue
CombineDBs(mother_db, file, start=config['start_value'])
print(f"Added file {file} to DB")
def _get_db_info(self, database):
db = PySurfDB.load_database(database, read_only=True)
rep = db.dbrep
natoms = rep.dimensions.get('natoms', None)
if natoms is None:
natoms = rep.dimensions['nmodes']
nstates = rep.dimensions['nstates']
return natoms, nstates, db.saved_properties
def __init__(self, main_db, added_db, start=0):
if not isinstance(main_db, PySurfDB):
info = PySurfDB.info_database(main_db)
if 'natoms' in info['dimensions']:
model = False
else:
model = True
main_db = PySurfDB.load_database(main_db,
dimensions=info['dimensions'],
data=info['variables'],
model=model)
if not isinstance(added_db, PySurfDB):
added_db = PySurfDB.load_database(added_db, read_only=True)
keys_raw = main_db.get_keys()
keys = []
for key in keys_raw:
if main_db.get_dimension(key)[0].isunlimited() is True:
keys += [key]
#check whether dbs fit together
check = True
for key in keys:
if key in added_db.get_keys():
for dim1, dim2 in zip(
main_db.get_dimension(key)[1:],
added_db.get_dimension(key)[1:]):
if dim1.size != dim2.size:
check = False
else:
check = False
if check is False:
print('Error DBs do not fit together by dimensions')
exit()
# nn = NextNeighbor(db1)
for i in range(start, len(added_db)):
# min_dist = nn.get(crd)
# if min_dist[0] > 0.25:
for key in keys:
main_db.append(key, added_db[key][i])
main_db.increase
def save_pes(self, filename, database):
db = PySurfDB.load_database(database, read_only=True)
results, _ = self._compute(db, ['energy'])
def str_join(values):
return ' '.join(str(val) for val in values)
with open(filename, 'w') as f:
f.write("\n".join(f"{i} {str_join(fitted)} {str_join(exact)}"
for i, (fitted, exact) in enumerate(results['energy'])))
def __init__(self, config):
db = PySurfDB.load_database(config['infile'], read_only=True)
if config['property'] == 'len':
print("Number of entries in database: ", len(db))
return
for idx, entry in enumerate(db[config['property']]):
print('\nEntry: {}'.format(idx))
print(entry)
def save_graddiff(self, filename, database):
db = PySurfDB.load_database(database, read_only=True)
results, _ = self._compute(db, ['gradient'])
def str_join(values):
return ' '.join(str(val) for val in values)
with open(filename, 'w') as f:
graddiff = [np.sqrt(np.mean((fitted-exact)**2)) for (fitted, exact) in results['gradient']]
f.write("\n".join(f"{i} {diff}"
for i, diff in enumerate(graddiff)))
def __init__(self, config):
dbin = PySurfDB.load_database(config['db_in'], read_only=True)
info = PySurfDB.info_database(config['db_in'])
self.thresh = config['energy_threshold']
self.trust_radius_general = config['trust_radius_general']
self.trust_radius_ci = config['trust_radius_ci']
self.crd_mode = config['crd_mode']
if 'natoms' in info['dimensions']:
model = False
else:
model = True
dbout = PySurfDB.generate_database(config['db_out'],
data=info['variables'],
dimensions=info['dimensions'],
model=model)
self.crds = None
for i, crd in enumerate(dbin['crd']):
if self.crd_mode == 'internal':
crd = internal(np.copy(crd))
else:
crd = np.copy(crd)
if i % 1000 == 0:
print(f"Processing point {i}")
crd_shape = crd.shape
crd.resize((1, crd.size))
if self.crds is None:
self.crds = crd.reshape((1, crd.size))
else:
diff = np.diff(dbin.get('energy', i))
_, (trust_general, trust_ci) = within_trust_radius(
crd,
self.crds,
radius=self.trust_radius_general,
radius_ci=self.trust_radius_ci,
metric='euclidean')
if np.min(diff) < self.thresh:
if trust_ci is True:
continue
else:
if trust_general is True:
continue
self.crds = np.concatenate((self.crds, crd))
crd.resize(crd_shape)
for prop in info['variables']:
dbout.append(prop, dbin.get(prop, i))
dbout.increase
def optimize(self, filename, properties):
db = PySurfDB.load_database(filename, read_only=True)
def _function(epsilon):
print('opt cycle', epsilon)
self.interpolator.epsilon = epsilon[0]
self.interpolator.train()
_, error = self._compute(db, properties)
print(error)
return error['rmsd']
res = minimize(_function, self.interpolator.epsilon, method='nelder-mead', tol=1e-4, options={
'maxiter': 25, 'disp': True, 'xatol': 0.0001})
print(res)
self.interpolator.epsilon = res.x[0]
self.interpolator.train(self.weightsfile)
def calc_2d_spec(files: "list", energy_start: "float", energy_end: "float",
en_points: "int", timesteps: "int") -> "meshplotdata":
result = np.zeros((en_points, timesteps))
for file in files:
db = PySurfDB.load_database(file, read_only=True)
energy = np.copy(db['energy'])
fosc = np.copy(db['fosc'])
currstate = np.copy(db['currstate']).flatten()
for idx, en in enumerate(energy):
state = int(currstate[idx])
en_diff = en[state] - en[0]
en_pos = (en_diff - energy_start) / (energy_end -
energy_start) * en_points
en_pos = int(en_pos)
if en_pos >= 0 and en_pos < en_points:
#units are arbitrary, therefor not full Einstain A coefficient ist used, but just f*v**2
result[en_pos, idx] += fosc[idx][state] * en_diff**2
X = np.arange(timesteps) * 0.5
Y = np.linspace(energy_start, energy_end, en_points) * 27.2114
return (X, Y, result)
def validate(self, filename, properties):
db = PySurfDB.load_database(filename, read_only=True)
self._compute(db, properties)
for r in x:
db.append('crd', r)
y += [
model.get(Request(r, ['energy'],
[i for i in range(nstates)]))['energy']
]
db.append(
'energy',
model.get(Request(r, ['energy'],
[i for i in range(nstates)]))['energy'])
db.increase
return db
#db1 = fill_db('db1.dat', 5000)
db1 = PySurfDB.load_database('db.dat', read_only=True)
#db2 = fill_db('db2.dat', 1000)
db2 = PySurfDB.load_database('prop.db', read_only=True)
nstates = 4
nmodes = 9
logger = get_logger('test.log', 'test')
config = {
'energy_threshold': 0.02,
'trust_radius_ci': 0.5,
'trust_radius_general': 1.0,
'inverse_distance': False
}
rbf = RbfInterpolator(config, db1, ['energy'], nstates, nmodes, logger=logger)
counter = 0