def setUp(self):
element_profile = {"Ni": {"r": 0.5, "w": 1}}
describer1 = BispectrumCoefficients(rcutfac=4.1,
twojmax=8,
element_profile=element_profile,
quadratic=False,
pot_fit=True)
model1 = SKLModel(describer=describer1, model=LinearRegression())
model1.model.coef_ = coeff
model1.model.intercept_ = intercept
snap1 = SNAPotential(model=model1)
self.ff_settings1 = snap1
describer2 = BispectrumCoefficients(rcutfac=4.1,
twojmax=8,
element_profile=element_profile,
quadratic=True,
pot_fit=True)
model2 = SKLModel(describer=describer2, model=LinearRegression())
model2.model.coef_ = coeff
model2.model.intercept_ = intercept
snap2 = SNAPotential(model=model2)
self.ff_settings2 = snap2
self.struct = Structure.from_spacegroup("Fm-3m", Lattice.cubic(3.506),
["Ni"], [[0, 0, 0]])
def setUp(self):
profile = {'Mo': {'r': 0.6, 'w': 1.}}
self.describer1 = BispectrumCoefficients(cutoff=4.6,
twojmax=6,
element_profile=profile,
quadratic=False,
pot_fit=True)
model1 = SKLModel(describer=self.describer1, model=LinearRegression())
self.potential1 = SNAPotential(model=model1, name='test')
self.describer2 = BispectrumCoefficients(cutoff=4.6,
twojmax=6,
element_profile=profile,
quadratic=True,
pot_fit=True)
model2 = SKLModel(describer=self.describer2, model=LinearRegression())
self.potential2 = SNAPotential(model=model2, name='test')
self.test_pool = test_datapool
self.test_structures = []
self.test_energies = []
self.test_forces = []
self.test_stresses = []
for d in self.test_pool:
self.test_structures.append(d['structure'])
self.test_energies.append(d['outputs']['energy'])
self.test_forces.append(d['outputs']['forces'])
self.test_stresses.append(d['outputs']['virial_stress'])
self.test_struct = self.test_pool[-1]['structure']
def setUp(self):
profile = {"Mo": {"r": 0.6, "w": 1.0}}
self.describer1 = BispectrumCoefficients(rcutfac=4.6,
twojmax=6,
element_profile=profile,
quadratic=False,
pot_fit=True)
model1 = SKLModel(describer=self.describer1, model=LinearRegression())
self.potential1 = SNAPotential(model=model1, name="test")
self.describer2 = BispectrumCoefficients(rcutfac=4.6,
twojmax=6,
element_profile=profile,
quadratic=True,
pot_fit=True)
model2 = SKLModel(describer=self.describer2, model=LinearRegression())
self.potential2 = SNAPotential(model=model2, name="test")
self.test_pool = test_datapool
self.test_structures = []
self.test_energies = []
self.test_forces = []
self.test_stresses = []
for d in self.test_pool:
self.test_structures.append(d["structure"])
self.test_energies.append(d["outputs"]["energy"])
self.test_forces.append(d["outputs"]["forces"])
self.test_stresses.append(d["outputs"]["virial_stress"])
self.test_struct = self.test_pool[-1]["structure"]
def setUp(self):
element_profile = {'Ni': {'r': 0.5, 'w': 1}}
describer = BispectrumCoefficients(cutoff=4.1, twojmax=8,
element_profile=element_profile,
pot_fit=True)
model = SKLModel(describer=describer, model=LinearRegression())
model.model.coef_ = coeff
model.model.intercept_ = intercept
snap = SNAPotential(model=model)
self.ff_settings = snap
def setUp(self):
element_profile = {'Ni': {'r': 0.5, 'w': 1}}
describer = BispectrumCoefficients(cutoff=4.1, twojmax=8,
element_profile=element_profile,
pot_fit=True)
model = SKLModel(describer=describer, model=LinearRegression())
model.model.coef_ = coeff
model.model.intercept_ = intercept
snap = SNAPotential(model=model)
self.struct = Structure.from_spacegroup('Fm-3m', Lattice.cubic(3.506),
['Ni'], [[0, 0, 0]])
self.ff_settings = snap
class SNAPotentialTest(unittest.TestCase):
@classmethod
def setUpClass(cls):
cls.this_dir = os.path.dirname(os.path.abspath(__file__))
cls.test_dir = tempfile.mkdtemp()
os.chdir(cls.test_dir)
@classmethod
def tearDownClass(cls):
os.chdir(CWD)
shutil.rmtree(cls.test_dir)
def setUp(self):
profile = {'Mo': {'r': 0.6, 'w': 1.}}
self.describer1 = BispectrumCoefficients(cutoff=4.6,
twojmax=6,
element_profile=profile,
quadratic=False,
pot_fit=True)
model1 = SKLModel(describer=self.describer1, model=LinearRegression())
self.potential1 = SNAPotential(model=model1, name='test')
self.describer2 = BispectrumCoefficients(cutoff=4.6,
twojmax=6,
element_profile=profile,
quadratic=True,
pot_fit=True)
model2 = SKLModel(describer=self.describer2, model=LinearRegression())
self.potential2 = SNAPotential(model=model2, name='test')
self.test_pool = test_datapool
self.test_structures = []
self.test_energies = []
self.test_forces = []
self.test_stresses = []
for d in self.test_pool:
self.test_structures.append(d['structure'])
self.test_energies.append(d['outputs']['energy'])
self.test_forces.append(d['outputs']['forces'])
self.test_stresses.append(d['outputs']['virial_stress'])
self.test_struct = self.test_pool[-1]['structure']
def test_train(self):
self.potential1.train(train_structures=self.test_structures,
train_energies=self.test_energies,
train_forces=self.test_forces,
train_stresses=self.test_stresses)
self.assertEqual(len(self.potential1.model.model.coef_),
len(self.describer1.subscripts) + 1)
self.potential2.train(train_structures=self.test_structures,
train_energies=self.test_energies,
train_forces=self.test_forces,
train_stresses=self.test_stresses)
nss = len(self.describer2.subscripts)
self.assertEqual(len(self.potential2.model.model.coef_), nss + int(
(1 + nss) * nss / 2) + 1)
def test_evaluate(self):
self.potential1.train(train_structures=self.test_structures,
train_energies=self.test_energies,
train_forces=self.test_forces,
train_stresses=self.test_stresses)
df_orig, df_tar = self.potential1.evaluate(
test_structures=self.test_structures,
test_energies=self.test_energies,
test_forces=self.test_forces,
test_stresses=self.test_stresses)
self.assertEqual(df_orig.shape[0], df_tar.shape[0])
self.potential2.train(train_structures=self.test_structures,
train_energies=self.test_energies,
train_forces=self.test_forces,
train_stresses=self.test_stresses)
df_orig, df_tar = self.potential2.evaluate(
test_structures=self.test_structures,
test_energies=self.test_energies,
test_forces=self.test_forces,
test_stresses=self.test_stresses)
self.assertEqual(df_orig.shape[0], df_tar.shape[0])
def test_predict_efs(self):
self.potential1.train(train_structures=self.test_structures,
train_energies=self.test_energies,
train_forces=self.test_forces,
train_stresses=self.test_stresses)
energy, forces, stress = self.potential1.predict_efs(self.test_struct)
self.assertEqual(len(forces), len(self.test_struct))
self.assertEqual(len(stress), 6)
self.potential2.train(train_structures=self.test_structures,
train_energies=self.test_energies,
train_forces=self.test_forces,
train_stresses=self.test_stresses)
energy, forces, stress = self.potential2.predict_efs(self.test_struct)
self.assertEqual(len(forces), len(self.test_struct))
self.assertEqual(len(stress), 6)
def test_from_config(self):
snap = SNAPotential.from_config(param_file, coeff_file)
self.assertTrue(getattr(snap.model.model, 'coef_') is not None)
def test_from_config(self):
snap = SNAPotential.from_config(param_file, coeff_file)
self.assertTrue(getattr(snap.model.model, 'coef_') is not None)