def test_unique_structure_substitutions( self ):
# integration test
# Create a pymatgen structure with 16 sites in a 4x4 square grid
coords = np.array( [ [ 0.0, 0.0, 0.0 ],
[ 0.25, 0.0, 0.0 ],
[ 0.5, 0., 0.0 ],
[ 0.75, 0.0, 0.0 ],
[ 0.0, 0.25, 0.0 ],
[ 0.25, 0.25, 0.0 ],
[ 0.5, 0.25, 0.0 ],
[ 0.75, 0.25, 0.0 ],
[ 0.0, 0.5, 0.0 ],
[ 0.25, 0.5, 0.0 ],
[ 0.5, 0.5, 0.0 ],
[ 0.75, 0.5, 0.0 ],
[ 0.0, 0.75, 0.0 ],
[ 0.25, 0.75, 0.0 ],
[ 0.5, 0.75, 0.0 ],
[ 0.75, 0.75, 0.0 ] ] )
atom_list = [ 'Li' ] * len( coords )
lattice = Lattice.from_parameters( a = 3.0, b=3.0, c=3.0, alpha=90, beta=90, gamma=90 )
parent_structure = Structure( lattice, atom_list, coords )
parent_structure.replace( 0, 'O' ) # substitute one site with 'O'
ns = unique_structure_substitutions( parent_structure, 'Li', { 'Na':1, 'Li':14 } )
self.assertEqual( len( ns ), 5 )
distances = np.array( sorted( [ s.get_distance( s.indices_from_symbol('O')[0], s.indices_from_symbol('Na')[0] ) for s in ns ] ) )
np.testing.assert_array_almost_equal( distances, np.array( [ 0.75 , 1.06066 , 1.5 , 1.677051, 2.12132 ] ) )
np.testing.assert_array_equal( np.array( sorted( [ s.number_of_equivalent_configurations for s in ns ] ) ), np.array( [ 1, 2, 4, 4, 4 ] ) )
np.testing.assert_array_equal( np.array( sorted( [ s.full_configuration_degeneracy for s in ns ] ) ), np.array( [ 1, 2, 4, 4, 4 ] ) )
def create_TiAlN_structure(shuffle=True):
''' Attributes:
number_of_lattice > maximum Total number of atoms in structure
a > lattice parameter
Returns:
Pymatgen structure TiAlN. Creates possible largest square supercell '''
lattice = Lattice.cubic(a=4.16)
coords = [
[0, 0, 0],
[0.5, 0.5, 0],
[0.5, 0, 0.5],
[0, 0.5, 0.5],
[0, 0, 0.5],
[0.5, 0, 0],
[0, 0.5, 0],
[0.5, 0.5, 0.5],
]
matrix = [[1, 0, 0], [0, 5, 0], [0, 0, 5]]
struct = Structure(lattice, ["Ti", "Ti", "Al", "Al", "N", "N", "N", "N"],
coords)
struct.make_supercell(matrix)
site_size = len(struct)
element_number = int(site_size / 4)
Al_Ti_array = ['Al'] * element_number + ['Ti'] * element_number
if shuffle == True:
random.shuffle(Al_Ti_array)
for e, i in enumerate(Al_Ti_array):
struct.replace(e, i)
return struct
def test_unique_structure_substitutions(self):
# integration test
# Create a pymatgen structure with 16 sites in a 4x4 square grid
coords = np.array([[0.0, 0.0, 0.0], [0.25, 0.0, 0.0], [0.5, 0., 0.0],
[0.75, 0.0, 0.0], [0.0, 0.25, 0.0],
[0.25, 0.25, 0.0], [0.5, 0.25, 0.0],
[0.75, 0.25, 0.0], [0.0, 0.5,
0.0], [0.25, 0.5, 0.0],
[0.5, 0.5, 0.0], [0.75, 0.5, 0.0], [0.0, 0.75, 0.0],
[0.25, 0.75, 0.0], [0.5, 0.75, 0.0],
[0.75, 0.75, 0.0]])
atom_list = ['Li'] * len(coords)
lattice = Lattice.from_parameters(a=3.0,
b=3.0,
c=3.0,
alpha=90,
beta=90,
gamma=90)
parent_structure = Structure(lattice, atom_list, coords)
parent_structure.replace(0, 'O') # substitute one site with 'O'
ns = unique_structure_substitutions(parent_structure, 'Li', {
'Na': 1,
'Li': 14
})
self.assertEqual(len(ns), 5)
distances = np.array(
sorted([
s.get_distance(
s.indices_from_symbol('O')[0],
s.indices_from_symbol('Na')[0]) for s in ns
]))
np.testing.assert_array_almost_equal(
distances, np.array([0.75, 1.06066, 1.5, 1.677051, 2.12132]))
np.testing.assert_array_equal(
np.array(
sorted([s.number_of_equivalent_configurations for s in ns])),
np.array([1, 2, 4, 4, 4]))
np.testing.assert_array_equal(
np.array(sorted([s.full_configuration_degeneracy for s in ns])),
np.array([1, 2, 4, 4, 4]))
