def test_metal_ceramic_interface():
m1 = get_jid_data(jid="JVASP-816", dataset="dft_3d")["atoms"]
m2 = get_jid_data(jid="JVASP-32", dataset="dft_3d")["atoms"]
mat_Al = Atoms.from_dict(m1)
mat_Al2O3 = Atoms.from_dict(m2)
from jarvis.analysis.defects.surface import Surface
mat1 = Surface(atoms=mat_Al, indices=[1, 1, 1], layers=3).make_surface()
mat2 = Surface(atoms=mat_Al2O3, indices=[0, 0, 1], layers=1).make_surface()
combined = make_interface(
film=mat1, # .center_around_origin(),
max_area=500,
max_area_ratio_tol=0.09,
ltol=0.01,
apply_strain=True,
subs=mat2, # .center_around_origin(),
)["interface"]
print(combined)
# from ase.lattice.surface import surface
# from pymatgen.io.ase import AseAtomsAdaptor
# from pymatgen.symmetry.analyzer import SpacegroupAnalyzer
# from pymatgen.io.vasp.inputs import Poscar
# mat_cvn = SpacegroupAnalyzer(mat_Al.pymatgen_converter()).get_conventional_standard_structure()
# ase_atoms = AseAtomsAdaptor().get_atoms(mat_cvn)
# ase_slab = surface(ase_atoms, [1,1,1], 3)
# ase_slab.center(vacuum=18, axis=2)
# slab_pymatgen = AseAtomsAdaptor().get_structure(ase_slab)
# slab_pymatgen.sort()
# print (Poscar(slab_pymatgen))
# print ()
# print ()
print(mat1.center_around_origin().get_string(cart=False))
def test_zur():
m1 = get_jid_data("JVASP-664")["atoms"]
m2 = get_jid_data("JVASP-652")["atoms"]
s1 = Atoms.from_dict(m1)
s2 = Atoms.from_dict(m2)
info = make_interface(film=s1, subs=s2)
combined = info["interface"]
assert (
round(info["mismatch_u"], 3),
round(info["mismatch_angle"], 3),
) == (
-0.041,
0.0,
)
def get_2d_hetero_jids(jid1="JVASP-664", jid2="JVASP-52"):
from jarvis.db.figshare import get_jid_data
m1 = get_jid_data(jid1)["atoms"]
m2 = get_jid_data(jid2)["atoms"]
mat1 = Atoms.from_dict(m1)
mat2 = Atoms.from_dict(m2)
vac = max(mat1.lattice_mat[2][2], mat2.lattice_mat[2][2])
combined = make_interface(
film=mat1.center_around_origin(),
max_area=400,
max_area_ratio_tol=0.09,
ltol=0.05,
atol=0.1,
subs=mat2.center_around_origin(),
)["interface"]
return combined
def test_conv_method():
plt.switch_backend("agg")
a = Atoms.from_dict(get_jid_data("JVASP-667")["atoms"])
c = crop_square(a)
# c = a.make_supercell_matrix([2, 2, 1])
p = STEMConv(atoms=c).simulate_surface()
def test_graph():
from jarvis.core.atoms import Atoms
from jarvis.db.figshare import get_jid_data
atoms = Atoms.from_poscar(test_pos)
g = Graph.atom_dgl_multigraph(atoms=atoms, atom_features="cgcnn")
atoms = Atoms.from_dict(get_jid_data("JVASP-664")["atoms"])
feature_sets = ("atomic_number", "basic", "cfid", "cgcnn")
for i in feature_sets:
g = Graph.atom_dgl_multigraph(atoms=atoms, atom_features=i)
g = Graph.atom_dgl_multigraph(atoms=atoms, atom_features=i)
print(i, g)
batch = prepare_dgl_batch(torch.tensor([1, 1]))
batch = prepare_line_graph_batch(torch.tensor([1, 1, 1]))
g = Graph.from_atoms(atoms=atoms, features="atomic_number")
gnx = g.to_networkx()
g = Graph.from_atoms(atoms=atoms, features="atomic_number")
g = Graph.from_atoms(atoms=atoms, features="atomic_fraction")
g = Graph.from_atoms(
atoms=atoms,
features="basic",
get_prim=True,
zero_diag=True,
node_atomwise_angle_dist=True,
node_atomwise_rdf=True,
)
g = Graph.from_atoms(
atoms=atoms,
features="cfid",
get_prim=True,
zero_diag=True,
node_atomwise_angle_dist=True,
node_atomwise_rdf=True,
)
g = Graph.from_atoms(
atoms=atoms,
features="atomic_number",
get_prim=True,
zero_diag=True,
node_atomwise_angle_dist=True,
node_atomwise_rdf=True,
)
g = Graph.from_atoms(atoms=atoms, features="basic")
g = Graph.from_atoms(
atoms=atoms, features=["Z", "atom_mass", "max_oxid_s"]
)
g = Graph.from_atoms(atoms=atoms, features="cfid", max_cut=10000)
print(g)
d = g.to_dict()
g = Graph.from_dict(d)
num_nodes = g.num_nodes
num_edges = g.num_edges
print(num_nodes, num_edges)
assert num_nodes == 48
assert num_edges == 2256
assert (g.adjacency_matrix.shape) == (48, 48)
def test_magnetism_setup():
from jarvis.db.figshare import get_jid_data
atoms = Atoms.from_dict(
get_jid_data(jid="JVASP-78681", dataset="dft_3d")["atoms"]
)
mag = MagneticOrdering(atoms)
symm_list, ss = mag.get_minimum_configs(min_configs=3)
assert len(symm_list) == 3
assert ss.num_atoms == 8
mag_atoms = mag.get_mag_ions()
assert mag_atoms == ["Mn"]
tc = mag.tc_mean_field()
assert round(tc["Tc"], 2) == round(3868.17, 2)
def test_magnetism_setup():
from jarvis.db.figshare import get_jid_data
from jarvis.core.atoms import get_supercell_dims
atoms = Atoms.from_dict(
get_jid_data(jid="JVASP-78681", dataset="dft_3d")["atoms"]
)
dim = get_supercell_dims(atoms)
print("dim=", dim)
dim = [2, 2, 2]
symm_list, ss = get_unique_magnetic_structures(
atoms, supercell_dim=dim, magnetic_ions=["Mn"]
)
print("dim=", dim, len(symm_list))
assert len(symm_list)==5
assert ss.num_atoms == 16
def test_graph():
from jarvis.core.atoms import Atoms
from jarvis.db.figshare import get_jid_data
atoms = Atoms.from_dict(get_jid_data("JVASP-664")["atoms"])
g = Graph.from_atoms(atoms=atoms, features="atomic_number")
g = Graph.from_atoms(
atoms=atoms,
features="basic",
get_prim=True,
zero_diag=True,
node_atomwise_angle_dist=True,
node_atomwise_rdf=True,
)
g = Graph.from_atoms(
atoms=atoms,
features="cfid",
get_prim=True,
zero_diag=True,
node_atomwise_angle_dist=True,
node_atomwise_rdf=True,
)
g = Graph.from_atoms(
atoms=atoms,
features="atomic_number",
get_prim=True,
zero_diag=True,
node_atomwise_angle_dist=True,
node_atomwise_rdf=True,
)
g = Graph.from_atoms(atoms=atoms, features="basic")
g = Graph.from_atoms(atoms=atoms,
features=["Z", "atom_mass", "max_oxid_s"])
g = Graph.from_atoms(atoms=atoms, features="cfid")
print(g)
d = g.to_dict()
g = Graph.from_dict(d)
num_nodes = g.num_nodes
num_edges = g.num_edges
print(num_nodes, num_edges)
assert num_nodes == 48
assert num_edges == 2304
assert (g.adjacency_matrix.shape) == (48, 48)
def test_basic_atoms():
box = [[2.715, 2.715, 0], [0, 2.715, 2.715], [2.715, 0, 2.715]]
coords = [[0, 0, 0], [0.25, 0.2, 0.25]]
elements = ["Si", "Si"]
Si = Atoms(lattice_mat=box, coords=coords, elements=elements)
dim = get_supercell_dims(Si)
assert dim == [3, 3, 3]
polar = Si.check_polar
Si.props = ["a", "a"]
vac_pad = VacuumPadding(Si)
den_2d = round(vac_pad.get_effective_2d_slab().density, 2)
den_0d = round(vac_pad.get_effective_molecule().density, 2)
den_lll_red = round(Si.get_lll_reduced_structure().density, 2)
strng = Si.get_string()
scell_nat = Si.make_supercell([2, 2, 2]).num_atoms
scell_nat2 = Si.make_supercell_matrix([[2, 0, 0], [0, 2, 0],
[0, 0, 2]]).num_atoms
# print("scell_nat,scell_nat2", scell_nat, scell_nat2)
# print(Si.make_supercell([2, 2, 2]))
# print()
# print(Si.make_supercell_matrix([[2, 0, 0], [0, 2, 0], [0, 0, 2]]))
com = round(Si.get_center_of_mass()[0], 3)
rem = (Si.make_supercell([2, 2, 2]).remove_site_by_index(site=0)).num_atoms
prim = Si.get_primitive_atoms
print(prim.cart_coords)
assert round(prim.cart_coords[0][0], 2) == round(4.37815150, 2)
# print ('raw_distance_matrix', prim.raw_distance_matrix)
# print ('raw_distance_matrix', Si.raw_distance_matrix)
# print ('distance_matrix', Si.pymatgen_converter().distance_matrix)
assert round(prim.raw_distance_matrix[0][1],
2) == round(4.42386329832851, 2)
print(prim.raw_angle_matrix)
d = Si.to_dict()
new_at = Atoms.from_dict(d)
angs_a = d["angles"][0]
Si_2_den = Atoms(
lattice_mat=d["lattice_mat"],
coords=d["coords"],
elements=d["elements"],
).density
Si_xyz = Si.get_xyz_string
Si.write_xyz(filename="atoms.xyz")
tmp = Atoms.from_xyz(filename="atoms.xyz")
cmd = 'rm atoms.xyz'
os.system(cmd)
Si.center_around_origin()
# print ('scell_nat', Si_2)
assert (
round(Si.volume, 2),
Si.atomic_numbers,
Si.num_atoms,
Si.frac_coords[0][0],
Si.cart_coords[0][0],
round(Si.density, 2),
Si.spacegroup(),
Si.pymatgen_converter() != {},
polar,
Si.props[0],
den_2d,
den_0d,
round(Si.packing_fraction, 2),
Si.composition.to_dict(),
strng != "",
den_lll_red,
scell_nat,
com,
rem,
angs_a,
round(Si_2_den, 2),
) == (
40.03,
[14, 14],
2,
0,
0.0,
2.33,
"C2/m (12)",
True,
False,
"a",
0.35,
0.01,
0.28,
{
"Si": 2
},
True,
2.33,
16,
0.679,
15,
60.0,
2.33,
)
cc = Si.center()
cc = Si.center(axis=[0, 0, 1])
m1 = Atoms.from_dict(get_jid_data("JVASP-6640")["atoms"])
assert m1.check_polar == True
print("Strain test")
print(m1)
m1.apply_strain(0.1)
print(m1)
assert m1.lattice_mat[2][2] == 32.8717576
m1.apply_strain([0, 0, 0.1])
assert m1.lattice_mat[2][2] == 36.158933360000006
filename = "atoms.cif"
m1.write_cif(filename)
a = Atoms.from_cif(filename)
filename = "POSCAR"
m1.write_poscar(filename)
m2 = Atoms.from_poscar(filename)
filename = "atoms.xyz"
m1.write_xyz(filename)
m3 = Atoms.from_xyz(filename)
cmd = "rm atoms.xyz POSCAR atoms.cif"
os.system(cmd)
from jarvis.tasks.lammps.lammps import LammpsJob, JobFactory
from jarvis.core.atoms import Atoms
from jarvis.db.figshare import get_jid_data
from jarvis.analysis.structure.spacegroup import Spacegroup3D
# atoms = Atoms.from_poscar('POSCAR')
# Get Aluminum FCC
tmp_dict = get_jid_data(jid="JVASP-816", dataset="dft_3d")["atoms"]
atoms = Atoms.from_dict(tmp_dict)
# Get conventional cell
spg = Spacegroup3D(atoms)
cvn_atoms = spg.conventional_standard_structure
ff = "/users/knc6/Software/LAMMPS/lammps-master/potentials/Al_zhou.eam.alloy"
mod = "/users/knc6/Software/Devs/jarvis/jarvis/tasks/lammps/templates/inelast.mod"
cmd = "/users/knc6/Software/LAMMPS/lammps-master/src/lmp_serial<in.main>out"
parameters = {
"pair_style": "eam/alloy",
"pair_coeff": ff,
"atom_style": "charge",
"control_file": mod,
}
# Test LammpsJob
lmp = LammpsJob(atoms=cvn_atoms,
parameters=parameters,
lammps_cmd=cmd,
jobname="Test").runjob()
# Test high-throughput
job_fact = JobFactory(pair_style="eam/alloy", name="my_first_lammps_run")
job_fact.all_props_eam_alloy(atoms=cvn_atoms, ff_path=ff, lammps_cmd=cmd)
from jarvis.db.figshare import data, get_jid_data
from jarvis.core.atoms import Atoms, crop_square
from jarvis.io.prismatic.inputs import write_prismatic_xyz
a = Atoms.from_dict(get_jid_data("JVASP-667")["atoms"])
def test_inputs():
c = crop_square(a)
lines = write_prismatic_xyz(c)