def compute(self, function, data):
""" Compute descriptor for one structure to the database. """
if function['type'] in ['BehlerParrinello', 'ACSF']:
from pyxtal_ff.descriptors.ACSF import ACSF
d = ACSF(function['parameters'], function['Rc'], function['force'],
function['stress'], False).calculate(data['structure'])
elif function['type'] in ['wACSF', 'wacsf']:
from pyxtal_ff.descriptors.ACSF import ACSF
d = ACSF(function['parameters'], function['Rc'], function['force'],
function['stress'], True).calculate(data['structure'])
elif function['type'] in ['SO4', 'Bispectrum', 'bispectrum']:
from pyxtal_ff.descriptors.SO4 import SO4_Bispectrum
d = SO4_Bispectrum(
function['parameters']['lmax'],
function['Rc'],
derivative=function['force'],
stress=function['stress'],
normalize_U=function['parameters']['normalize_U']).calculate(
data['structure'])
elif function['type'] in ['SO3', 'SOAP', 'soap']:
from pyxtal_ff.descriptors.SO3 import SO3
d = SO3(function['parameters']['nmax'],
function['parameters']['lmax'],
function['Rc'],
derivative=function['force'],
stress=function['stress']).calculate(data['structure'])
elif function['type'] in ['EAMD', 'eamd']:
from pyxtal_ff.descriptors.EAMD import EAMD
d = EAMD(function['parameters'], function['Rc'], function['force'],
function['stress']).calculate(data['structure'])
else:
msg = f"{function['type']} is not implemented"
raise NotImplementedError(msg)
if d['rdxdr'] is not None:
N = d['x'].shape[0]
L = d['x'].shape[1]
rdxdr = np.zeros([N, L, 3, 3])
for _m in range(N):
ids = np.where(d['seq'][:, 0] == _m)[0]
rdxdr[_m, :, :, :] += np.einsum('ijkl->jkl',
d['rdxdr'][ids, :, :, :])
d['rdxdr'] = rdxdr.reshape([N, L, 9])[:, :, [0, 4, 8, 1, 2, 5]]
#d['rdxdr'] = np.einsum('ijklm->iklm', d['rdxdr'])\
#.reshape([shp[0], shp[2], shp[3]*shp[4]])[:, :, [0, 4, 8, 1, 2, 5]] #need to change
d['energy'] = np.asarray(data['energy'])
d['force'] = np.asarray(data['force'])
if data['stress'] is not None:
d['stress'] = np.asarray(data['stress'])
else:
d['stress'] = data['stress']
d['group'] = data['group']
return d
class TestwACSF(unittest.TestCase):
struc = get_rotated_struc(nacl)
wACSF0 = ACSF(symmetry_parameters=acsf_params,
Rc=rc,
derivative=True,
atom_weighted=True).calculate(struc)
struc = get_rotated_struc(nacl, 10, 'x')
wACSF1 = ACSF(symmetry_parameters=acsf_params,
Rc=rc,
derivative=True,
atom_weighted=True).calculate(struc)
def test_wACSF_rotation_variance(self):
array1 = self.wACSF0['x']
array2 = self.wACSF1['x']
self.assertTrue(np.allclose(array1, array2))
def test_dwACSFdR_rotation_variance(self):
for i in range(len(self.wACSF0['x'])):
array1 = np.linalg.norm(self.wACSF0['dxdr'][i, :, :], axis=1)
array2 = np.linalg.norm(self.wACSF1['dxdr'][i, :, :], axis=1)
self.assertTrue(np.allclose(array1, array2))
def test_dwACSFdR_vs_numerical(self):
shp = self.wACSF0['x'].shape
array1 = np.zeros([shp[0], shp[0], shp[1], 3])
for _m in range(shp[0]):
ids = np.where(self.wACSF0['seq'][:, 1] == _m)[0]
array1[self.wACSF0['seq'][ids, 0],
_m, :, :] += self.wACSF0['dxdr'][ids, :, :]
for j in range(shp[0]):
for k in range(3):
struc = get_perturbed_struc(nacl, j, k, eps)
wACSF2 = ACSF(symmetry_parameters=acsf_params,
Rc=rc,
derivative=False,
atom_weighted=True).calculate(struc)
array2 = (wACSF2['x'] - self.wACSF0['x']) / eps
self.assertTrue(
np.allclose(array1[:, j, :, k], array2, atol=1e-6))
class TestACSF(unittest.TestCase):
from pyxtal_ff.descriptors.ACSF import ACSF
symmetry = {'G2': {'eta': [0.003214], 'Rs': [0]},
'G4': {'lambda': [1], 'zeta':[1], 'eta': [0.000357]},
'G5': {'lambda': [-1], 'zeta':[1], 'eta': [0.004]},
}
struc = get_rotated_struc(cu)
g0 = ACSF(symmetry, rcut, derivative=True).calculate(struc)
struc = get_rotated_struc(cu, 10, 'x')
g1 = ACSF(symmetry, rcut, derivative=True).calculate(struc)
struc = get_perturbed_struc(cu, eps)
g2 = ACSF(symmetry, rcut, derivative=False).calculate(struc)
def test_G2_value(self):
self.assertAlmostEqual(self.g0['x'][0,0], 0.36925589)
def test_G4_value(self):
self.assertAlmostEqual(self.g0['x'][0,1], 0.00232827)
def test_G_rotation_variance(self):
array1 = self.g0['x'].flatten()
array2 = self.g1['x'].flatten()
self.assertTrue(np.allclose(array1, array2))
def test_dGdR_rotation_variance(self):
array1 = np.linalg.norm(self.g0['dxdr'][0,:,:], axis=1)
array2 = np.linalg.norm(self.g1['dxdr'][0,:,:], axis=1)
self.assertTrue(np.allclose(array1, array2))
def test_dGdR_vs_numerical(self):
array1 = (self.g2['x'][0] - self.g0['x'][0]).flatten()/eps
array2 = self.g0['dxdr'][0, :, 0].flatten()
if not np.allclose(array1, array2):
print('\n Numerical dGdR')
print((self.g2['x'][0] - self.g0['x'][0])/eps)
print('\n precompute')
print(array2)
self.assertTrue(np.allclose(array1, array2))
def test_dACSFdR_vs_numerical(self):
shp = self.ACSF0['x'].shape
array1 = np.zeros([shp[0], shp[0], shp[1], 3])
for _m in range(shp[0]):
ids = np.where(self.ACSF0['seq'][:, 1] == _m)[0]
array1[self.ACSF0['seq'][ids, 0],
_m, :, :] += self.ACSF0['dxdr'][ids, :, :]
for j in range(shp[0]):
for k in range(3):
struc = get_perturbed_struc(nacl, j, k, eps)
ACSF2 = ACSF(symmetry_parameters=acsf_params,
Rc=rc,
derivative=False).calculate(struc)
array2 = (ACSF2['x'] - self.ACSF0['x']) / eps
self.assertTrue(
np.allclose(array1[:, j, :, k], array2, atol=1e-6))
def compute_descriptor(function, structure):
""" Compute descriptor for one structure. """
if function['type'] in ['BehlerParrinello', 'ACSF']:
from pyxtal_ff.descriptors.ACSF import ACSF
d = ACSF(function['parameters'], function['Rc'], function['force'],
function['stress'], function['cutoff'],
False).calculate(structure)
elif function['type'] in ['wACSF', 'wacsf']:
from pyxtal_ff.descriptors.ACSF import ACSF
d = ACSF(function['parameters'], function['Rc'], function['force'],
function['stress'], function['cutoff'],
True).calculate(structure)
elif function['type'] in ['SO4', 'Bispectrum', 'bispectrum']:
from pyxtal_ff.descriptors.SO4 import SO4_Bispectrum
d = SO4_Bispectrum(
function['parameters']['lmax'],
function['Rc'],
derivative=True,
stress=True,
normalize_U=function['parameters']['normalize_U'],
cutoff_function=function['cutoff']).calculate(structure)
elif function['type'] in ['SO3', 'SOAP', 'soap']:
from pyxtal_ff.descriptors.SO3 import SO3
d = SO3(function['parameters']['nmax'],
function['parameters']['lmax'],
function['Rc'],
derivative=True,
stress=True).calculate(structure)
elif function['type'] in ['EAD', 'ead']:
from pyxtal_ff.descriptors.EAD import EAD
d = EAMD(function['parameters'], function['Rc'], True, True,
function['cutoff']).calculate(structure)
elif function['type'] in ['SNAP', 'snap']:
from pyxtal_ff.descriptors.SNAP import SO4_Bispectrum
d = SO4_Bispectrum(
function['weights'],
function['parameters']['lmax'],
function['Rc'],
derivative=True,
stress=True,
normalize_U=function['parameters']['normalize_U'],
cutoff_function=function['cutoff']).calculate(structure)
else:
msg = f"{function['type']} is not implemented"
raise NotImplementedError(msg)
if d['rdxdr'] is not None:
#shp = d['rdxdr'].shape
#d['rdxdr'] = np.einsum('ijklm->iklm', d['rdxdr'])\
# .reshape([shp[0], shp[2], shp[3]*shp[4]])[:, :, [0,4,8,1,2,5]]
N = d['x'].shape[0]
L = d['x'].shape[1]
rdxdr = np.zeros([N, L, 3, 3])
for _m in range(N):
ids = np.where(d['seq'][:, 0] == _m)[0]
rdxdr[_m, :, :, :] += np.einsum('ijkl->jkl',
d['rdxdr'][ids, :, :, :])
d['rdxdr'] = rdxdr.reshape([N, L, 9])[:, :, [0, 4, 8, 1, 2, 5]]
return d