def __init__(self, *args, **kwargs):
super(TestGroundStateFinderInactiveSublatticeSameSpecies,
self).__init__(*args, **kwargs)
self.chemical_symbols = [['Ag', 'Au'], ['Ag']]
self.cutoffs = [4.3]
a = 4.0
structure_prim = bulk(self.chemical_symbols[0][1], a=a)
structure_prim.append(
Atom(self.chemical_symbols[1][0], position=(a / 2, a / 2, a / 2)))
self.structure_prim = structure_prim
self.cs = ClusterSpace(self.structure_prim, self.cutoffs,
self.chemical_symbols)
self.ce = ClusterExpansion(self.cs, [0, 0, 0.1, -0.02])
self.all_possible_structures = []
self.supercell = self.structure_prim.repeat(2)
sublattices = self.cs.get_sublattices(self.supercell)
self.n_active_sites = [
len(subl.indices) for subl in sublattices.active_sublattices
]
for i, sym in enumerate(self.supercell.get_chemical_symbols()):
if sym not in self.chemical_symbols[0]:
continue
structure = self.supercell.copy()
structure.symbols[i] = self.chemical_symbols[0][0]
self.all_possible_structures.append(structure)
def __init__(self, *args, **kwargs):
super(TestGroundStateFinderZeroParameter,
self).__init__(*args, **kwargs)
self.chemical_symbols = ['Ag', 'Au']
self.cutoffs = [4.3]
self.structure_prim = bulk(self.chemical_symbols[1], a=4.0)
self.cs = ClusterSpace(self.structure_prim, self.cutoffs,
self.chemical_symbols)
nonzero_ce = ClusterExpansion(self.cs, [0, 0, 0.1, -0.02])
lolg = LocalOrbitListGenerator(
self.cs.orbit_list, Structure.from_atoms(self.structure_prim),
self.cs.fractional_position_tolerance)
full_orbit_list = lolg.generate_full_orbit_list()
binary_parameters_zero = transform_parameters(self.structure_prim,
full_orbit_list,
nonzero_ce.parameters)
binary_parameters_zero[1] = 0
A = get_transformation_matrix(self.structure_prim, full_orbit_list)
Ainv = np.linalg.inv(A)
zero_parameters = np.dot(Ainv, binary_parameters_zero)
self.ce = ClusterExpansion(self.cs, zero_parameters)
self.all_possible_structures = []
self.supercell = self.structure_prim.repeat(2)
for i in range(len(self.supercell)):
structure = self.supercell.copy()
structure.symbols[i] = self.chemical_symbols[0]
self.all_possible_structures.append(structure)
def __init__(self, *args, **kwargs):
super(TestGroundStateFinderTwoActiveSublattices,
self).__init__(*args, **kwargs)
a = 4.0
self.chemical_symbols = [['Au', 'Pd'], ['Li', 'Na']]
self.cutoffs = [3.0]
structure_prim = bulk(self.chemical_symbols[0][0], a=a)
structure_prim.append(
Atom(self.chemical_symbols[1][0], position=(a / 2, a / 2, a / 2)))
structure_prim.wrap()
self.structure_prim = structure_prim
self.cs = ClusterSpace(self.structure_prim, self.cutoffs,
self.chemical_symbols)
parameters = [0.1, -0.45, 0.333, 2, -1.42, 0.98]
self.ce = ClusterExpansion(self.cs, parameters)
self.all_possible_structures = []
self.supercell = self.structure_prim.repeat(2)
self.sl1_indices = [
s for s, sym in enumerate(self.supercell.get_chemical_symbols())
if sym == self.chemical_symbols[0][0]
]
self.sl2_indices = [
s for s, sym in enumerate(self.supercell.get_chemical_symbols())
if sym == self.chemical_symbols[1][0]
]
for i in self.sl1_indices:
for j in self.sl2_indices:
structure = self.supercell.copy()
structure.symbols[i] = self.chemical_symbols[0][1]
structure.symbols[j] = self.chemical_symbols[1][1]
self.all_possible_structures.append(structure)
def __init__(self, *args, **kwargs):
super(TestGroundStateFinder, self).__init__(*args, **kwargs)
self.chemical_symbols = ['Ag', 'Au']
self.cutoffs = [4.3]
self.structure_prim = bulk(self.chemical_symbols[1], a=4.0)
self.cs = ClusterSpace(self.structure_prim, self.cutoffs,
self.chemical_symbols)
self.ce = ClusterExpansion(self.cs, [0, 0, 0.1, -0.02])
self.all_possible_structures = []
self.supercell = self.structure_prim.repeat(2)
for i in range(len(self.supercell)):
structure = self.supercell.copy()
structure.symbols[i] = self.chemical_symbols[0]
self.all_possible_structures.append(structure)
def test_sublattice_probabilities(self):
""" Tests the sublattice_probabilities keyword argument. """
# setup system with inactive sublattice
prim = bulk('W', 'bcc', cubic=True)
prim[1].symbol = 'C'
chemical_symbols = [['W', 'Ti'], ['C', 'N']]
cs = ClusterSpace(prim, cutoffs=[0], chemical_symbols=chemical_symbols)
ce = ClusterExpansion(cs, [1] * len(cs))
structure = prim.repeat(2)
structure[0].symbol = 'Ti'
structure[1].symbol = 'N'
calculator = ClusterExpansionCalculator(structure, ce)
# test default
ensemble = WangLandauEnsemble(structure, calculator, energy_spacing=1)
probs = ensemble._get_swap_sublattice_probabilities()
self.assertEqual(len(probs), 2)
self.assertAlmostEqual(probs[0], 0.5)
self.assertAlmostEqual(probs[1], 0.5)
# test override
ensemble = WangLandauEnsemble(structure,
calculator,
energy_spacing=1,
sublattice_probabilities=[0.2, 0.8])
probs = ensemble._sublattice_probabilities
self.assertEqual(len(probs), 2)
self.assertAlmostEqual(probs[0], 0.2)
self.assertAlmostEqual(probs[1], 0.8)
def __init__(self, *args, **kwargs):
super(TestEnsembleSpectatorSublattice, self).__init__(*args, **kwargs)
lattice_parameter = 4.0
prim = bulk('Pd', a=lattice_parameter, crystalstructure='fcc')
prim.append(Atom('H', position=(lattice_parameter / 2,)*3))
self.structure = prim.repeat(3)
for i, atom in enumerate(self.structure):
if i % 3 == 0:
if atom.symbol == 'Pd':
continue
else:
atom.symbol = 'V'
cutoffs = [5, 5, 4]
elements = [['Pd'], ['H', 'V']]
self.chemical_potentials = {'H': 5, 'V': 0}
self.phis = {'H': -1.0}
self.kappa = 200.0
self.ensemble_specs = [{'ensemble': 'canonical', 'sublattice_index': 0},
{'ensemble': 'semi-grand', 'sublattice_index': 0,
'chemical_potentials': self.chemical_potentials},
{'ensemble': 'vcsgc', 'sublattice_index': 0,
'phis': self.phis, 'kappa': self.kappa}]
self.cs = ClusterSpace(prim, cutoffs, elements)
parameters = parameters = np.array([1.2] * len(self.cs))
self.ce = ClusterExpansion(self.cs, parameters)
self.temperature = 100.0
def __init__(self, *args, **kwargs):
super(TestEnsemble, self).__init__(*args, **kwargs)
# prepare cluster expansion
self.prim = Atoms('Au',
positions=[[0, 0, 0]],
cell=[1, 1, 10],
pbc=True)
cs = ClusterSpace(self.prim,
cutoffs=[1.1],
chemical_symbols=['Ag', 'Au'])
self.ce = ClusterExpansion(cs, [0, 0, 2])
# prepare initial configuration
self.structure = self.prim.repeat((2, 2, 1))
self.structure[0].symbol = 'Ag'
self.structure[1].symbol = 'Ag'
self.structure = self.structure.repeat((2, 2, 1))
# other variables and parameters
self.trial_move = 'swap'
self.energy_spacing = 1
self.flatness_limit = 0.8
self.fill_factor_limit = 1e-4
self.flatness_check_interval = 10
self.data_container_write_period = 499
self.ensemble_data_write_interval = 1
self.trajectory_write_interval = 10
def test_restart_with_inactive_sites(self):
""" Tests restart works with inactive sites """
chemical_symbols = [['C', 'Be'], ['W']]
prim = bulk(
'W',
'bcc',
cubic=True,
)
cs = ClusterSpace(structure=prim,
chemical_symbols=chemical_symbols,
cutoffs=[5])
parameters = [1] * len(cs)
ce = ClusterExpansion(cs, parameters)
size = 4
structure = ce._cluster_space.primitive_structure.repeat(size)
calculator = ClusterExpansionCalculator(structure, ce)
# Carry out Monte Carlo simulations
dc_file = tempfile.NamedTemporaryFile()
mc = ConcreteEnsemble(structure=structure, calculator=calculator)
mc.write_data_container(dc_file.name)
mc.run(10)
# and now restart
mc = ConcreteEnsemble(structure=structure,
calculator=calculator,
dc_filename=dc_file.name)
mc.run(10)
def test_get_swap_sublattice_probabilities(self):
""" Tests the get_swap_sublattice_probabilities function. """
# setup system with inactive sublattice
prim = bulk('Al').repeat([2, 1, 1])
chemical_symbols = [['Al'], ['Ag', 'Al']]
cs = ClusterSpace(prim, cutoffs=[0], chemical_symbols=chemical_symbols)
ce = ClusterExpansion(cs, [1] * len(cs))
supercell = prim.repeat(2)
supercell[1].symbol = 'Ag'
ce_calc = ClusterExpansionCalculator(supercell, ce)
ensemble = CanonicalEnsemble(supercell, ce_calc, temperature=100)
# test get_swap_sublattice_probabilities
probs = ensemble._get_swap_sublattice_probabilities()
self.assertEqual(len(probs), 2)
self.assertEqual(probs[0], 1)
self.assertEqual(probs[1], 0)
# test raise when swap not possible on either lattice
supercell[1].symbol = 'Al'
ce_calc = ClusterExpansionCalculator(supercell, ce)
with self.assertRaises(ValueError) as context:
ensemble = CanonicalEnsemble(supercell, ce_calc, temperature=100)
self.assertIn('No canonical swaps are possible on any of the',
str(context.exception))
def test_read_write(self):
"""Tests read and write functionalities."""
# save to file
temp_file = tempfile.NamedTemporaryFile()
self.ce.write(temp_file.name)
# read from file
temp_file.seek(0)
ce_read = ClusterExpansion.read(temp_file.name)
# check cluster space
self.assertEqual(self.cs._input_structure,
ce_read._cluster_space._input_structure)
self.assertEqual(self.cs._cutoffs, ce_read._cluster_space._cutoffs)
self.assertEqual(self.cs._input_chemical_symbols,
ce_read._cluster_space._input_chemical_symbols)
# check parameters
self.assertIsInstance(ce_read.parameters, np.ndarray)
self.assertEqual(list(ce_read.parameters), list(self.parameters))
# check metadata
self.assertEqual(len(self.ce.metadata), len(ce_read.metadata))
self.assertSequenceEqual(sorted(self.ce.metadata.keys()),
sorted(ce_read.metadata.keys()))
for key in self.ce.metadata.keys():
self.assertEqual(self.ce.metadata[key], ce_read.metadata[key])
def __init__(self, *args, **kwargs):
super(TestEnsemble, self).__init__(*args, **kwargs)
prim = Atoms('Au', positions=[[0, 0, 0]], cell=[1, 1, 1], pbc=True)
self.structure = prim.repeat(3)
self.cs = ClusterSpace(prim,
cutoffs=[1.1],
chemical_symbols=['Ag', 'Au'])
self.ce = ClusterExpansion(self.cs, [0, 0, 2])
def test_init(self):
"""Tests that initialization works."""
self.assertIsInstance(self.ce, ClusterExpansion)
# test whether method raises Exception
with self.assertRaises(ValueError) as context:
ClusterExpansion(self.cs, [0.0])
self.assertTrue('cluster_space (5) and parameters (1) must have the'
' same length' in str(context.exception))
def __init__(self, *args, **kwargs):
super(TestCECalculatorTernaryHCP, self).__init__(*args, **kwargs)
self.structure = bulk('Al', 'hcp', a=4.0, c=3.1)
self.cutoffs = [6, 6, 6]
self.subelements = ['Al', 'Ge', 'H']
self.cs = ClusterSpace(self.structure, self.cutoffs, self.subelements)
params_len = len(self.cs)
params = [1.0] * params_len
self.ce = ClusterExpansion(self.cs, params)
def __init__(self, *args, **kwargs):
super(TestCECalculatorBinaryBCC, self).__init__(*args, **kwargs)
self.structure = bulk('Al', 'bcc', a=4.0)
self.cutoffs = [6, 6, 6]
self.subelements = ['Al', 'Ge']
self.cs = ClusterSpace(self.structure, self.cutoffs, self.subelements)
params_len = len(self.cs)
params = [1.1] * params_len
self.ce = ClusterExpansion(self.cs, params)
def __init__(self, *args, **kwargs):
super(TestCEObserver, self).__init__(*args, **kwargs)
self.structure = bulk('Al').repeat(3)
cutoffs = [6, 6, 5]
subelements = ['Al', 'Ge']
cs = ClusterSpace(self.structure, cutoffs, subelements)
params_len = len(cs)
params = list(range(params_len))
self.ce = ClusterExpansion(cs, params)
def __init__(self, *args, **kwargs):
super(TestGroundStateFinderTriplets, self).__init__(*args, **kwargs)
self.chemical_symbols = ['Au', 'Pd']
self.cutoffs = [3.0, 3.0]
structure_prim = fcc111(self.chemical_symbols[0],
a=4.0,
size=(1, 1, 6),
vacuum=10,
periodic=True)
structure_prim.wrap()
self.structure_prim = structure_prim
self.cs = ClusterSpace(self.structure_prim, self.cutoffs,
self.chemical_symbols)
parameters = [0.0] * 4 + [0.1] * 6 + [-0.02] * 11
self.ce = ClusterExpansion(self.cs, parameters)
self.all_possible_structures = []
self.supercell = self.structure_prim.repeat((2, 2, 1))
for i in range(len(self.supercell)):
structure = self.supercell.copy()
structure.symbols[i] = self.chemical_symbols[1]
self.all_possible_structures.append(structure)
def __init__(self, *args, **kwargs):
super(TestEnsemble, self).__init__(*args, **kwargs)
self.structure = bulk('Al').repeat(3)
for i, atom in enumerate(self.structure):
if i % 2 == 0:
atom.symbol = 'Ga'
cutoffs = [5, 5, 4]
elements = ['Al', 'Ga']
self.cs = ClusterSpace(self.structure, cutoffs, elements)
parameters = parameters = np.array([1.2] * len(self.cs))
self.ce = ClusterExpansion(self.cs, parameters)
self.temperature = 100.0
def test_init_fails_for_faulty_chemical_symbols(self):
"""Tests that initialization fails if species exists on
mutliple sublattices"""
structure = bulk('Al').repeat(2)
cutoffs = [4.0]
elements = [['Al', 'Ga']] * 4 + [['Al', 'Ge']] * 4
cs = ClusterSpace(structure, cutoffs, elements)
ce = ClusterExpansion(cs, np.arange(0, len(cs)))
calc = ClusterExpansionCalculator(structure, ce)
with self.assertRaises(ValueError) as context:
ConcreteEnsemble(structure, calc)
self.assertIn('found on multiple active sublattices',
str(context.exception))
def test_init_fails_for_ternary_with_one_active_sublattice(self):
"""Tests that initialization fails for a ternary system with one active
sublattice."""
chemical_symbols = ['Au', 'Ag', 'Pd']
cs = ClusterSpace(self.structure_prim,
cutoffs=self.cutoffs,
chemical_symbols=chemical_symbols)
ce = ClusterExpansion(cs, [0.0] * len(cs))
with self.assertRaises(NotImplementedError) as cm:
icet.tools.ground_state_finder.GroundStateFinder(ce,
self.supercell,
verbose=False)
self.assertTrue(
'Currently, systems with more than two allowed species on any sublattice '
'are not supported.' in str(cm.exception))
def test_property_metadata(self):
""" Test metadata property. """
user_metadata = dict(parameters=[1, 2, 3], fit_method='ardr')
ce = ClusterExpansion(self.cs, self.parameters, metadata=user_metadata)
metadata = ce.metadata
# check for user metadata
self.assertIn('parameters', metadata.keys())
self.assertIn('fit_method', metadata.keys())
# check for default metadata
self.assertIn('date_created', metadata.keys())
self.assertIn('username', metadata.keys())
self.assertIn('hostname', metadata.keys())
self.assertIn('icet_version', metadata.keys())
def test_mc_with_one_filled_sublattice(self):
""" Tests if WL simulation works with two sublattices
where one sublattice is filled/empty. """
# setup two sublattices
prim = bulk('W', crystalstructure='bcc', a=1.0, cubic=True)
cs = ClusterSpace(prim, [1.5], [['W', 'Ti'], ['C', 'Be']])
ce = ClusterExpansion(cs, [1] * len(cs))
# setup supercell with one filled sublattice
structure = prim.copy()
structure[1].symbol = 'C'
structure = structure.repeat(4)
structure[2].symbol = 'Ti'
# run mc
calculator = ClusterExpansionCalculator(structure, ce)
mc = WangLandauEnsemble(structure, calculator, energy_spacing=1)
mc.run(50)
def __init__(self, *args, **kwargs):
super(TestEnsemble, self).__init__(*args, **kwargs)
# setup supercell
self.structure = bulk('Al').repeat(3)
for i, atom in enumerate(self.structure):
if i % 2 == 0:
atom.symbol = 'Ga'
# setup cluster expansion
cutoffs = [5, 5, 4]
elements = ['Al', 'Ga']
cs = ClusterSpace(self.structure, cutoffs, elements)
parameters = parameters = np.array([1.2] * len(cs))
self.ce = ClusterExpansion(cs, parameters)
self.T_start = 1000.0
self.T_stop = 0.0
self.n_steps = 500
def test_read_write_pruned(self):
"""Tests read and write functionalities."""
# save to file
temp_file = tempfile.NamedTemporaryFile()
self.ce.prune(indices=[2, 3])
self.ce.prune(tol=3)
pruned_params = self.ce.parameters
pruned_cs_len = len(self.ce._cluster_space)
self.ce.write(temp_file.name)
# read from file
temp_file.seek(0)
ce_read = ClusterExpansion.read(temp_file.name)
params_read = ce_read.parameters
cs_len_read = len(ce_read._cluster_space)
# check cluster space
self.assertEqual(cs_len_read, pruned_cs_len)
self.assertEqual(list(params_read), list(pruned_params))
def print_timing_ratios(structure, local_iters, total_iters, sizes, cutoffs):
""" Prints timing ratios between local and total energy calculations. """
print(
'# 1:size 2:local_iters 3:total_iters 4:atom size, 5:ce calc init time (sec)'
', 6:t_local 7:t_total 8:t_total/t_local')
cs = ClusterSpace(structure, cutoffs, chemical_symbols=['Al', 'Ga'])
parameters = np.array([1.2 for _ in range(len(cs))])
ce = ClusterExpansion(cs, parameters)
for size in sizes:
structure_cpy = structure.repeat(size)
occupations = structure_cpy.get_atomic_numbers()
t0 = time.time()
calculator = ClusterExpansionCalculator(structure_cpy, ce)
time_ce_init = time.time() - t0
t_local = time_local_energy(calculator, occupations, local_iters)
t_total = time_total_energy(calculator, occupations, total_iters)
print(size, local_iters, total_iters, len(structure_cpy), time_ce_init,
t_local, t_total, t_total / t_local)
def test_mc_with_one_filled_sublattice(self):
""" Tests if canonical ensemble works with two sublattices
where one sublattice is filled/empty. """
# setup two sublattices
prim = bulk('W', 'bcc', a=3.0, cubic=True)
cs = ClusterSpace(prim, [4.0], [['W', 'Ti'], ['C', 'Be']])
ce = ClusterExpansion(cs, np.arange(0, len(cs)))
# setup supercell with one filled sublattice
supercell = prim.copy()
supercell[1].symbol = 'C'
supercell = supercell.repeat(4)
supercell[2].symbol = 'Ti'
# run mc
calc = ClusterExpansionCalculator(supercell, ce)
mc = CanonicalEnsemble(supercell, calc, 300)
mc.run(50)
def __init__(self, *args, **kwargs):
super(TestEnsembleSublattices, self).__init__(*args, **kwargs)
lattice_parameter = 4.0
prim = bulk('Pd', a=lattice_parameter, crystalstructure='fcc')
prim.append(Atom('H', position=(lattice_parameter / 2, ) * 3))
self.structure = prim.repeat(3)
for i, atom in enumerate(self.structure):
if i % 3 == 0:
if atom.symbol == 'Pd':
atom.symbol = 'Au'
else:
atom.symbol = 'V'
cutoffs = [5, 5, 4]
elements = [['Pd', 'Au'], ['H', 'V']]
self.phis = {'Au': -1.3, 'H': -1.0}
self.kappa = 200.0
self.cs = ClusterSpace(prim, cutoffs, elements)
parameters = parameters = np.array([1.2] * len(self.cs))
self.ce = ClusterExpansion(self.cs, parameters)
self.temperature = 100.0
def __init__(self, *args, **kwargs):
super(TestEnsemble, self).__init__(*args, **kwargs)
self.structure = bulk('Al').repeat(3)
for i, atom in enumerate(self.structure):
if i % 2 == 0:
atom.symbol = 'Ga'
cutoffs = [5, 5, 4]
elements = ['Al', 'Ga']
self.chemical_potentials = {'Al': 5, 'Ga': 0}
self.phis = {'Al': -1.3}
self.kappa = 10.0
self.ensemble_specs = [{'ensemble': 'canonical', 'sublattice_index': 0},
{'ensemble': 'semi-grand', 'sublattice_index': 0,
'chemical_potentials': self.chemical_potentials},
{'ensemble': 'vcsgc', 'sublattice_index': 0,
'phis': self.phis, 'kappa': self.kappa}]
self.cs = ClusterSpace(self.structure, cutoffs, elements)
parameters = parameters = np.array([1.2] * len(self.cs))
self.ce = ClusterExpansion(self.cs, parameters)
self.temperature = 100.0
def test_get_sublattice_probabilities(self):
""" Tests the get_swap/flip_sublattice_probabilities function. """
# setup system with inactive sublattice
prim = bulk('Al').repeat([2, 1, 1])
chemical_symbols = [['Al'], ['Ag', 'Al']]
cs = ClusterSpace(prim, cutoffs=[0], chemical_symbols=chemical_symbols)
ce = ClusterExpansion(cs, [1] * len(cs))
structure = prim.repeat(2)
structure[1].symbol = 'Ag'
calculator = ClusterExpansionCalculator(structure, ce)
ensemble = WangLandauEnsemble(structure, calculator, energy_spacing=1)
# test get_swap_sublattice_probabilities
probs = ensemble._get_swap_sublattice_probabilities()
self.assertEqual(len(probs), 2)
self.assertEqual(probs[0], 1)
self.assertEqual(probs[1], 0)
# test get_flip_sublattice_probabilities
probs = ensemble._get_flip_sublattice_probabilities()
self.assertEqual(len(probs), 2)
self.assertEqual(probs[0], 1)
self.assertEqual(probs[1], 0)
# test raise when swap not possible on either lattice
structure[1].symbol = 'Al'
calculator = ClusterExpansionCalculator(structure, ce)
with self.assertRaises(ValueError) as context:
ensemble = WangLandauEnsemble(structure,
calculator,
energy_spacing=1)
self.assertIn('No swaps are possible on any of the',
str(context.exception))
# This scripts runs in about 6 seconds on an i7-6700K CPU.
import matplotlib.pyplot as plt
from ase.db import connect
from icet import ClusterExpansion
# step 1: Compile predicted and reference data for plotting
ce = ClusterExpansion.read('mixing_energy.ce')
data = {'concentration': [], 'reference_energy': [], 'predicted_energy': []}
db = connect('reference_data.db')
for row in db.select('natoms<=6'):
data['concentration'].append(row.concentration)
# the factor of 1e3 serves to convert from eV/atom to meV/atom
data['reference_energy'].append(1e3 * row.mixing_energy)
data['predicted_energy'].append(1e3 * ce.predict(row.toatoms()))
# step 2: Plot results
fig, ax = plt.subplots(figsize=(4, 3))
ax.set_xlabel(r'Pd concentration')
ax.set_ylabel(r'Mixing energy (meV/atom)')
ax.set_xlim([0, 1])
ax.set_ylim([-69, 15])
ax.scatter(data['concentration'], data['reference_energy'],
marker='o', label='reference')
ax.scatter(data['concentration'], data['predicted_energy'],
marker='x', label='CE prediction')
plt.savefig('mixing_energy_comparison.png', bbox_inches='tight')
class TestGroundStateFinderTwoActiveSublattices(unittest.TestCase):
"""Container for test of the class functionality for a system with
two active sublattices."""
def __init__(self, *args, **kwargs):
super(TestGroundStateFinderTwoActiveSublattices,
self).__init__(*args, **kwargs)
a = 4.0
self.chemical_symbols = [['Au', 'Pd'], ['Li', 'Na']]
self.cutoffs = [3.0]
structure_prim = bulk(self.chemical_symbols[0][0], a=a)
structure_prim.append(
Atom(self.chemical_symbols[1][0], position=(a / 2, a / 2, a / 2)))
structure_prim.wrap()
self.structure_prim = structure_prim
self.cs = ClusterSpace(self.structure_prim, self.cutoffs,
self.chemical_symbols)
parameters = [0.1, -0.45, 0.333, 2, -1.42, 0.98]
self.ce = ClusterExpansion(self.cs, parameters)
self.all_possible_structures = []
self.supercell = self.structure_prim.repeat(2)
self.sl1_indices = [
s for s, sym in enumerate(self.supercell.get_chemical_symbols())
if sym == self.chemical_symbols[0][0]
]
self.sl2_indices = [
s for s, sym in enumerate(self.supercell.get_chemical_symbols())
if sym == self.chemical_symbols[1][0]
]
for i in self.sl1_indices:
for j in self.sl2_indices:
structure = self.supercell.copy()
structure.symbols[i] = self.chemical_symbols[0][1]
structure.symbols[j] = self.chemical_symbols[1][1]
self.all_possible_structures.append(structure)
def shortDescription(self):
"""Silences unittest from printing the docstrings in test cases."""
return None
def setUp(self):
"""Setup before each test."""
self.gsf = icet.tools.ground_state_finder.GroundStateFinder(
self.ce, self.supercell, verbose=False)
def test_init(self):
"""Tests that initialization of tested class work."""
# initialize from ClusterExpansion instance
gsf = icet.tools.ground_state_finder.GroundStateFinder(self.ce,
self.supercell,
verbose=False)
self.assertIsInstance(gsf,
icet.tools.ground_state_finder.GroundStateFinder)
def test_get_ground_state(self):
"""Tests get_ground_state functionality."""
target_val = min([
self.ce.predict(structure)
for structure in self.all_possible_structures
])
# Provide counts for the first/first species
species_count = {
self.chemical_symbols[0][0]: len(self.sl1_indices) - 1,
self.chemical_symbols[1][0]: len(self.sl2_indices) - 1
}
ground_state = self.gsf.get_ground_state(species_count=species_count)
predicted_species00 = self.ce.predict(ground_state)
self.assertEqual(predicted_species00, target_val)
# Provide counts for the first/second species
species_count = {
self.chemical_symbols[0][0]: len(self.sl1_indices) - 1,
self.chemical_symbols[1][1]: 1
}
ground_state = self.gsf.get_ground_state(species_count=species_count)
predicted_species01 = self.ce.predict(ground_state)
self.assertEqual(predicted_species01, predicted_species00)
# Provide counts for second/second species
species_count = {
self.chemical_symbols[0][1]: 1,
self.chemical_symbols[1][1]: 1
}
ground_state = self.gsf.get_ground_state(species_count=species_count)
predicted_species11 = self.ce.predict(ground_state)
self.assertEqual(predicted_species11, predicted_species01)
def _test_ground_state_cluster_vectors_in_database(self, db_name):
"""Tests get_ground_state functionality by comparing the cluster
vectors for the structures in the databases."""
filename = inspect.getframeinfo(inspect.currentframe()).filename
path = os.path.dirname(os.path.abspath(filename))
db = db_connect(os.path.join(path, db_name))
# Select the structure set with the lowest pairwise correlations
selections = ['id={}'.format(i) for i in [7, 13, 15, 62, 76]]
for selection in selections:
row = db.get(selection)
structure = row.toatoms()
target_cluster_vector = self.cs.get_cluster_vector(structure)
species_count = {
self.chemical_symbols[0][0]:
structure.get_chemical_symbols().count(
self.chemical_symbols[0][0]),
self.chemical_symbols[1][0]:
structure.get_chemical_symbols().count(
self.chemical_symbols[1][0])
}
ground_state = self.gsf.get_ground_state(
species_count=species_count)
gs_cluster_vector = self.cs.get_cluster_vector(ground_state)
mean_diff = np.mean(abs(target_cluster_vector - gs_cluster_vector))
self.assertLess(mean_diff, 1e-8)
def test_ground_state_cluster_vectors(self):
"""Tests get_ground_state functionality by comparing the cluster
vectors for ground states obtained from simulated annealing."""
self._test_ground_state_cluster_vectors_in_database(
'../../../structure_databases/annealing_ground_states.db')
def test_get_ground_state_fails_for_faulty_species_to_count(self):
"""Tests that get_ground_state fails if species_to_count is faulty."""
# Check that get_ground_state fails if counts are provided for a both species on one
# of the active sublattices
species_count = {
self.chemical_symbols[0][0]: len(self.sl1_indices) - 1,
self.chemical_symbols[0][1]: 1,
self.chemical_symbols[1][1]: 1
}
with self.assertRaises(ValueError) as cm:
self.gsf.get_ground_state(species_count=species_count)
self.assertTrue(
'Provide counts for at most one of the species on each active sublattice '
'({}), not {}!'.format(self.gsf._active_species,
list(species_count.keys())) in str(
cm.exception))
# Check that get_ground_state fails if the count exceeds the number sites on the first
# sublattice
faulty_species = self.chemical_symbols[0][1]
faulty_count = len(self.supercell)
species_count = {
faulty_species: faulty_count,
self.chemical_symbols[1][1]: 1
}
n_active_sites = len([
sym for sym in self.supercell.get_chemical_symbols()
if sym == self.chemical_symbols[0][0]
])
with self.assertRaises(ValueError) as cm:
self.gsf.get_ground_state(species_count=species_count)
self.assertTrue(
'The count for species {} ({}) must be a positive integer and cannot '
'exceed the number of sites on the active sublattice '
'({})'.format(faulty_species, faulty_count, n_active_sites) in str(
cm.exception))
# Check that get_ground_state fails if the count exceeds the number sites on the second
# sublattice
faulty_species = self.chemical_symbols[1][1]
faulty_count = len(self.supercell)
species_count = {
faulty_species: faulty_count,
self.chemical_symbols[0][1]: 1
}
n_active_sites = len([
sym for sym in self.supercell.get_chemical_symbols()
if sym == self.chemical_symbols[1][0]
])
with self.assertRaises(ValueError) as cm:
self.gsf.get_ground_state(species_count=species_count)
self.assertTrue(
'The count for species {} ({}) must be a positive integer and cannot '
'exceed the number of sites on the active sublattice '
'({})'.format(faulty_species, faulty_count, n_active_sites) in str(
cm.exception))
def test_get_ground_state_passes_for_partial_species_to_count(self):
# Check that get_ground_state passes if a single count is provided
species_count = {self.chemical_symbols[0][1]: 1}
self.gsf.get_ground_state(species_count=species_count)
# Check that get_ground_state passes no counts are provided
gs = self.gsf.get_ground_state()
self.assertEqual(gs.get_chemical_formula(), "Au8Li8")
