def test_make_confs_0(self):
if not os.path.exists(os.path.join(self.equi_path, 'CONTCAR')):
with self.assertRaises(RuntimeError):
self.surface.make_confs(self.target_path, self.equi_path)
shutil.copy(os.path.join(self.source_path, 'mp-141.vasp'),
os.path.join(self.equi_path, 'CONTCAR'))
task_list = self.surface.make_confs(self.target_path, self.equi_path)
self.assertEqual(len(task_list), 7)
dfm_dirs = glob.glob(os.path.join(self.target_path, 'task.*'))
incar0 = Incar.from_file(os.path.join('vasp_input', 'INCAR.rlx'))
incar0['ISIF'] = 4
self.assertEqual(
os.path.realpath(os.path.join(self.equi_path, 'CONTCAR')),
os.path.realpath(os.path.join(self.target_path, 'POSCAR')))
ref_st = Structure.from_file(os.path.join(self.target_path, 'POSCAR'))
dfm_dirs.sort()
for ii in dfm_dirs:
st_file = os.path.join(ii, 'POSCAR')
self.assertTrue(os.path.isfile(st_file))
st0 = Structure.from_file(st_file)
st1_file = os.path.join(ii, 'POSCAR.tmp')
self.assertTrue(os.path.isfile(st1_file))
st1 = Structure.from_file(st1_file)
miller_json_file = os.path.join(ii, 'miller.json')
self.assertTrue(os.path.isfile(miller_json_file))
miller_json = loadfn(miller_json_file)
sl = SlabGenerator(ref_st, miller_json,
self.prop_param[0]["min_slab_size"],
self.prop_param[0]["min_vacuum_size"])
slb = sl.get_slab()
st2 = Structure(slb.lattice, slb.species, slb.frac_coords)
self.assertEqual(len(st1), len(st2))
def test_make_poscars_from_query(tmpdir):
mg_structure = Structure(Lattice.cubic(1), species=["Mg", "Mg"],
coords=[[0, 0, 0], [0.5, 0.5, 0.5]])
query = [{"full_formula": "Mg2", "task_id": "mp-1",
"total_magnetization": 0.1,
"band_gap": 0.0,
"structure": mg_structure},
{"full_formula": "O16"}]
make_poscars_from_query(query, path=Path(tmpdir))
tmpdir.chdir()
s_mg = Structure.from_file(Path("Mg_mp-1") / "POSCAR")
assert s_mg == mg_structure
actual = loadfn(Path("Mg_mp-1") / "prior_info.yaml")
expected = {'band_gap': 0.0, 'data_source': 'mp-1', 'total_magnetization': 0.1}
assert actual == expected
actual = Structure.from_file(Path("mol_O2") / "POSCAR")
expected = Structure.from_str("""Default POSCAR of O2 molecule
1.00000000000000
10.0000000000000000 0.0000000000000000 0.0000000000000000
0.0000000000000000 10.0000000000000000 0.0000000000000000
0.0000000000000000 0.0000000000000000 10.0000000000000000
O
2
Direct
0.0145089778962415 0.0000000000000000 0.0000000000000000
0.1354910221037571 0.0000000000000000 0.0000000000000000""", fmt="POSCAR")
assert actual == expected
def rmsd_pbc(file_path_1, file_path_2, original_def=True):
"""
Calculate absolute root-mean-square diffence between two structures.
No rotation nor recentering will be considered. Periodic boundary condition
will be considered.
"""
try:
a = Structure.from_file(filename=file_path_1)
b = Structure.from_file(filename=file_path_2)
except Exception:
sys.exit("File import failed.")
# check if two structures are valid for compare
natoms = check_validity(a, b)
# get fractional coords of each structure
# a_frac = [a[i].frac_coords for i in range(natoms)]
# b_frac = [b[i].frac_coords for i in range(natoms)]
a_frac = a.frac_coords
b_frac = b.frac_coords
# get frac_diff considering pbc (abs(diff) <= 0.5)
frac_diff = pbc_diff(a_frac, b_frac)
# convert to cartesian coords difference
cart_diff = a.lattice.get_cartesian_coords(frac_diff)
if original_def:
# original definition of RMSD
return np.sqrt(np.sum(cart_diff**2))
else:
# revised definition. The top 5 deviation is considered
# aiming to better compare the difference of two similar structures
return np.sum(np.sort(np.abs(cart_diff))[:5]) / 5
def test_get_endpoint_dist(self):
ep0 = Structure.from_file(get_path("POSCAR_ep0", dirname="io_files"))
ep1 = Structure.from_file(get_path("POSCAR_ep1", dirname="io_files"))
distances = get_endpoint_dist(ep0, ep1)
self.assertAlmostEqual(max(distances), 6.3461081051543893, 7)
self.assertEqual(min(distances), 0.0)
def test_make_confs_0(self):
if not os.path.exists(os.path.join(self.equi_path, 'CONTCAR')):
with self.assertRaises(RuntimeError):
self.vacancy.make_confs(self.target_path, self.equi_path)
shutil.copy(os.path.join(self.source_path, 'CONTCAR'),
os.path.join(self.equi_path, 'CONTCAR'))
task_list = self.vacancy.make_confs(self.target_path, self.equi_path)
dfm_dirs = glob.glob(os.path.join(self.target_path, 'task.*'))
self.assertEqual(len(dfm_dirs), 5)
incar0 = Incar.from_file(os.path.join('vasp_input', 'INCAR.rlx'))
incar0['ISIF'] = 4
self.assertEqual(
os.path.realpath(os.path.join(self.equi_path, 'CONTCAR')),
os.path.realpath(os.path.join(self.target_path, 'POSCAR')))
ref_st = Structure.from_file(os.path.join(self.target_path, 'POSCAR'))
sga = SpacegroupAnalyzer(ref_st)
sym_st = sga.get_symmetrized_structure()
equiv_site_seq = list(sym_st.equivalent_sites)
dfm_dirs.sort()
for ii in dfm_dirs:
st_file = os.path.join(ii, 'POSCAR')
self.assertTrue(os.path.isfile(st_file))
st0 = Structure.from_file(st_file)
vac_site = equiv_site_seq.pop(0)
vac = pmg_Vacancy(ref_st, vac_site[0], charge=0.0)
st1 = vac.generate_defect_structure(
self.prop_param[0]['supercell'])
self.assertEqual(st0, st1)
def setUp(self):
struct = Structure.from_file(f"{dir_path}/full_path_files/MnO2_full_Li.vasp")
self.fpm_li = MigrationGraph.with_distance(structure=struct, migrating_specie="Li", max_distance=4)
# Particularity difficult pathfinding since both the starting and ending positions are outside the unit cell
struct = Structure.from_file(f"{dir_path}/full_path_files/Mg_2atom.vasp")
self.fpm_mg = MigrationGraph.with_distance(structure=struct, migrating_specie="Mg", max_distance=2)
def test_ignore_species(self):
s1 = Structure.from_file(os.path.join(test_dir, "LiFePO4.cif"))
s2 = Structure.from_file(os.path.join(test_dir, "POSCAR"))
m = StructureMatcher(ignored_species=["Li"],
primitive_cell=False,
attempt_supercell=True)
self.assertTrue(m.fit(s1, s2))
self.assertTrue(m.fit_anonymous(s1, s2))
groups = m.group_structures([s1, s2])
self.assertEqual(len(groups), 1)
s2.make_supercell((2, 1, 1))
ss1 = m.get_s2_like_s1(s2, s1, include_ignored_species=True)
self.assertAlmostEqual(ss1.lattice.a, 20.820740000000001)
self.assertEqual(ss1.composition.reduced_formula, "LiFePO4")
self.assertEqual(
{
k.symbol: v.symbol
for k, v in m.get_best_electronegativity_anonymous_mapping(
s1, s2).items()
}, {
"Fe": "Fe",
"P": "P",
"O": "O"
})
def test_get_endpoints_from_index(self):
endpoints = get_endpoints_from_index(structure=self.structure, site_indices=[0, 1])
ep_0 = endpoints[0].as_dict()
ep_1 = endpoints[1].as_dict()
ep_0_expect = Structure.from_file(get_path("POSCAR_ep0", dirname="io_files")).as_dict()
ep_1_expect = Structure.from_file(get_path("POSCAR_ep1", dirname="io_files")).as_dict()
self.assertEqual(ep_0, ep_0_expect)
self.assertEqual(ep_1, ep_1_expect)
def setUpClass(cls):
cls.structures = [
Structure.from_file(
os.path.join(module_dir, "cifs",
"LiFePO4_mp-19017_computed.cif")),
Structure.from_file(
os.path.join(module_dir, "cifs",
"BaTiO3_mp-2998_computed.cif"))
]
def setUp(self):
self.gnd_real = Structure.from_file(TEST_FILES / 'POSCAR.C0.gz')
self.exd_real = Structure.from_file(TEST_FILES / 'POSCAR.C-.gz')
self.gnd_test = Structure(Lattice.cubic(1.), ['H'], [[0., 0., 0.]])
self.exd_test = Structure(Lattice.cubic(1.), ['H'], [[0.5, 0.5, 0.5]])
self.sct_test = Structure(Lattice.cubic(1.), ['H'],
[[0.25, 0.25, 0.25]])
self.vrs = [TEST_FILES / 'vasprun.xml.0.gz'] + \
glob.glob(str(TEST_FILES / 'lower' / '*' / 'vasprun.xml.gz'))
def test_supercell_fit(self):
sm = StructureMatcher(attempt_supercell=False)
s1 = Structure.from_file(os.path.join(test_dir, "Al3F9.json"))
s2 = Structure.from_file(os.path.join(test_dir, "Al3F9_distorted.json"))
self.assertFalse(sm.fit(s1, s2))
sm = StructureMatcher(attempt_supercell=True)
self.assertTrue(sm.fit(s1, s2))
self.assertTrue(sm.fit(s2, s1))
def test_supercell_fit(self):
sm = StructureMatcher(attempt_supercell=False)
s1 = Structure.from_file(os.path.join(test_dir, "Al3F9.json"))
s2 = Structure.from_file(os.path.join(test_dir, "Al3F9_distorted.json"))
self.assertFalse(sm.fit(s1, s2))
sm = StructureMatcher(attempt_supercell=True)
self.assertTrue(sm.fit(s1, s2))
self.assertTrue(sm.fit(s2, s1))
def test_electronegativity(self):
sm = StructureMatcher(ltol=0.2, stol=0.3, angle_tol=5)
s1 = Structure.from_file(os.path.join(test_dir, "Na2Fe2PAsO4S4.json"))
s2 = Structure.from_file(os.path.join(test_dir, "Na2Fe2PNO4Se4.json"))
self.assertEqual(sm.get_best_electronegativity_anonymous_mapping(s1, s2),
{Element('S'): Element('Se'),
Element('As'): Element('N'),
Element('Fe'): Element('Fe'),
Element('Na'): Element('Na'),
Element('P'): Element('P'),
Element('O'): Element('O'),})
self.assertEqual(len(sm.get_all_anonymous_mappings(s1, s2)), 2)
def test_electronegativity(self):
sm = StructureMatcher(ltol=0.2, stol=0.3, angle_tol=5)
s1 = Structure.from_file(os.path.join(test_dir, "Na2Fe2PAsO4S4.json"))
s2 = Structure.from_file(os.path.join(test_dir, "Na2Fe2PNO4Se4.json"))
self.assertEqual(sm.get_best_electronegativity_anonymous_mapping(s1, s2),
{Element('S'): Element('Se'),
Element('As'): Element('N'),
Element('Fe'): Element('Fe'),
Element('Na'): Element('Na'),
Element('P'): Element('P'),
Element('O'): Element('O'),})
self.assertEqual(len(sm.get_all_anonymous_mappings(s1, s2)), 2)
def test_predict(self):
s = PymatgenTest.get_structure("CsCl")
nacl = PymatgenTest.get_structure("CsCl")
nacl.replace_species({"Cs": "Na"})
nacl.scale_lattice(184.384551033)
p = RLSVolumePredictor(radii_type="ionic")
self.assertAlmostEqual(p.predict(s, nacl), 342.84905395082535)
p = RLSVolumePredictor(radii_type="atomic")
self.assertAlmostEqual(p.predict(s, nacl), 391.884366481)
lif = PymatgenTest.get_structure("CsCl")
lif.replace_species({"Cs": "Li", "Cl": "F"})
p = RLSVolumePredictor(radii_type="ionic")
self.assertAlmostEqual(p.predict(lif, nacl), 74.268402413690467)
p = RLSVolumePredictor(radii_type="atomic")
self.assertAlmostEqual(p.predict(lif, nacl), 62.2808125839)
lfpo = PymatgenTest.get_structure("LiFePO4")
lmpo = PymatgenTest.get_structure("LiFePO4")
lmpo.replace_species({"Fe": "Mn"})
p = RLSVolumePredictor(radii_type="ionic")
self.assertAlmostEqual(p.predict(lmpo, lfpo), 310.08253254420134)
p = RLSVolumePredictor(radii_type="atomic")
self.assertAlmostEqual(p.predict(lmpo, lfpo), 299.607967711)
sto = PymatgenTest.get_structure("SrTiO3")
scoo = PymatgenTest.get_structure("SrTiO3")
scoo.replace_species({"Ti4+": "Co4+"})
p = RLSVolumePredictor(radii_type="ionic")
self.assertAlmostEqual(p.predict(scoo, sto), 56.162534974936463)
p = RLSVolumePredictor(radii_type="atomic")
self.assertAlmostEqual(p.predict(scoo, sto), 57.4777835108)
# Use Ag7P3S11 as a test case:
# (i) no oxidation states are assigned and CVP-atomic scheme is selected.
aps = Structure.from_file(os.path.join(dir_path,
"Ag7P3S11_mp-683910_primitive.cif"))
apo = Structure.from_file(os.path.join(dir_path,
"Ag7P3S11_mp-683910_primitive.cif"))
apo.replace_species({"S": "O"})
p = RLSVolumePredictor(radii_type="atomic", check_isostructural=False)
self.assertAlmostEqual(p.predict(apo, aps), 1196.31384276)
# (ii) Oxidation states are assigned.
apo.add_oxidation_state_by_element({"Ag": 1, "P": 5, "O": -2})
aps.add_oxidation_state_by_element({"Ag": 1, "P": 5, "S": -2})
p = RLSVolumePredictor(radii_type="ionic")
self.assertAlmostEqual(p.predict(apo, aps), 1165.23259079)
p = RLSVolumePredictor(radii_type="atomic")
self.assertAlmostEqual(p.predict(apo, aps), 1196.31384276)
def test_predict(self):
s = PymatgenTest.get_structure("CsCl")
nacl = PymatgenTest.get_structure("CsCl")
nacl.replace_species({"Cs": "Na"})
nacl.scale_lattice(184.384551033)
p = RLSVolumePredictor(radii_type="ionic")
self.assertAlmostEqual(p.predict(s, nacl), 342.84905395082535)
p = RLSVolumePredictor(radii_type="atomic")
self.assertAlmostEqual(p.predict(s, nacl), 391.884366481)
lif = PymatgenTest.get_structure("CsCl")
lif.replace_species({"Cs": "Li", "Cl": "F"})
p = RLSVolumePredictor(radii_type="ionic")
self.assertAlmostEqual(p.predict(lif, nacl), 74.268402413690467)
p = RLSVolumePredictor(radii_type="atomic")
self.assertAlmostEqual(p.predict(lif, nacl), 62.2808125839)
lfpo = PymatgenTest.get_structure("LiFePO4")
lmpo = PymatgenTest.get_structure("LiFePO4")
lmpo.replace_species({"Fe": "Mn"})
p = RLSVolumePredictor(radii_type="ionic")
self.assertAlmostEqual(p.predict(lmpo, lfpo), 310.08253254420134)
p = RLSVolumePredictor(radii_type="atomic")
self.assertAlmostEqual(p.predict(lmpo, lfpo), 299.607967711)
sto = PymatgenTest.get_structure("SrTiO3")
scoo = PymatgenTest.get_structure("SrTiO3")
scoo.replace_species({"Ti4+": "Co4+"})
p = RLSVolumePredictor(radii_type="ionic")
self.assertAlmostEqual(p.predict(scoo, sto), 56.162534974936463)
p = RLSVolumePredictor(radii_type="atomic")
self.assertAlmostEqual(p.predict(scoo, sto), 57.4777835108)
# Use Ag7P3S11 as a test case:
# (i) no oxidation states are assigned and CVP-atomic scheme is selected.
aps = Structure.from_file(os.path.join(dir_path,
"Ag7P3S11_mp-683910_primitive.cif"))
apo = Structure.from_file(os.path.join(dir_path,
"Ag7P3S11_mp-683910_primitive.cif"))
apo.replace_species({"S": "O"})
p = RLSVolumePredictor(radii_type="atomic", check_isostructural=False)
self.assertAlmostEqual(p.predict(apo, aps), 1196.31384276)
# (ii) Oxidation states are assigned.
apo.add_oxidation_state_by_element({"Ag": 1, "P": 5, "O": -2})
aps.add_oxidation_state_by_element({"Ag": 1, "P": 5, "S": -2})
p = RLSVolumePredictor(radii_type="ionic")
self.assertAlmostEqual(p.predict(apo, aps), 1165.23259079)
p = RLSVolumePredictor(radii_type="atomic")
self.assertAlmostEqual(p.predict(apo, aps), 1196.31384276)
def test_undercoordinated_n_past_issue():
mofchecker = MOFChecker(
Structure.from_file(os.path.join(THIS_DIR, "test_files",
"axipee.cif")))
assert mofchecker.has_undercoordinated_n == False
mofchecker = MOFChecker(
Structure.from_file(
os.path.join(THIS_DIR, "test_files", "ABOVOF_FSR.cif")))
assert mofchecker.has_undercoordinated_n == False
mofchecker = MOFChecker(
Structure.from_file(os.path.join(THIS_DIR, "test_files",
"abiqae.cif")))
assert mofchecker.has_undercoordinated_n == False
def test_max_path_length(self):
s = Structure.from_file(
get_path("LYPS.cif", dirname="pathfinder_files"))
dp1 = DistinctPathFinder(s, "Li", perc_mode="1d")
self.assertAlmostEqual(dp1.max_path_length, 4.11375354207, 7)
dp2 = DistinctPathFinder(s, "Li", 5, perc_mode="1d")
self.assertAlmostEqual(dp2.max_path_length, 5.0, 7)
def get_gruneisenparameter(gruneisen_path, structure=None, structure_path=None) -> GruneisenParameter:
"""
Get Gruneisen object from gruneisen.yaml file, as obtained from phonopy (Frequencies in THz!).
The order is structure > structure path > structure from gruneisen dict.
Newer versions of phonopy include the structure in the yaml file,
the structure/structure_path is kept for compatibility.
Args:
gruneisen_path: Path to gruneisen.yaml file (frequencies have to be in THz!)
structure: pymatgen Structure object
structure_path: path to structure in a file (e.g., POSCAR)
Returns: GruneisenParameter object
"""
gruneisen_dict = loadfn(gruneisen_path)
if structure_path and structure is None:
structure = Structure.from_file(structure_path)
else:
try:
structure = get_structure_from_dict(gruneisen_dict)
except ValueError:
raise ValueError("\nPlease provide a structure.\n")
qpts, multiplicities, frequencies, gruneisen = ([] for _ in range(4))
phonopy_labels_dict = {}
for p in gruneisen_dict["phonon"]:
q = p["q-position"]
qpts.append(q)
if "multiplicity" in p:
m = p["multiplicity"]
else:
m = 1
multiplicities.append(m)
bands, gruneisenband = ([] for _ in range(2))
for b in p["band"]:
bands.append(b["frequency"])
if "gruneisen" in b:
gruneisenband.append(b["gruneisen"])
frequencies.append(bands)
gruneisen.append(gruneisenband)
if "label" in p:
phonopy_labels_dict[p["label"]] = p["q-position"]
qpts_np = np.array(qpts)
multiplicities_np = np.array(multiplicities)
# transpose to match the convention in PhononBandStructure
frequencies_np = np.transpose(frequencies)
gruneisen_np = np.transpose(gruneisen)
return GruneisenParameter(
gruneisen=gruneisen_np,
qpoints=qpts_np,
multiplicities=multiplicities_np,
frequencies=frequencies_np,
structure=structure,
)
def data():
# prepare path
pwd = Path(__file__).parent
cif1 = pmg_S.from_file(str(pwd / '1.cif'))
cif2 = pmg_S.from_file(str(pwd / '2.cif'))
# ignore numpy warning
import warnings
print('ignore NumPy RuntimeWarning\n')
warnings.filterwarnings("ignore", message="numpy.dtype size changed")
warnings.filterwarnings("ignore", message="numpy.ndarray size changed")
cifs = pd.Series([cif1, cif2], name='structure')
yield cifs
print('test over')
def test_writebandstr(self):
filepath = os.path.join(test_dir, 'CsI3Pb.cif')
structure = Structure.from_file(filepath)
excin = ExcitingInput(structure)
string = excin.write_string('primitive', bandstr=True)
bandstr = string.split('<properties>')[1].split('</properties>')[0]
coord = []
label = []
coord_ref = [[0.0, 0.0, 0.0], [0.5, 0.0, 0.0], [0.5, 0.5, 0.0],
[0.0, 0.5, 0.0],
[0.0, 0.0, 0.0], [0.0, 0.0, 0.5], [0.5, 0.0, 0.5],
[0.5, 0.5, 0.5],
[0.0, 0.5, 0.5], [0.0, 0.0, 0.5], [0.0, 0.5, 0.0],
[0.0, 0.5, 0.5],
[0.5, 0.0, 0.5], [0.5, 0.0, 0.0], [0.5, 0.5, 0.0],
[0.5, 0.5, 0.5]]
label_ref = ['GAMMA', 'X', 'S', 'Y', 'GAMMA', 'Z', 'U', 'R', 'T', 'Z',
'Y', 'T',
'U', 'X', 'S', 'R']
root = ET.fromstring(bandstr)
for plot1d in root.iter('plot1d'):
for point in plot1d.iter('point'):
coord.append([float(i) for i in point.get('coord').split()])
label.append(point.get('label'))
self.assertEqual(label, label_ref)
self.assertEqual(coord, coord_ref)
def test_substitute(self):
structure = Structure.from_file(os.path.join(PymatgenTest.TEST_FILES_DIR, "Li2O.cif"))
molecule = FunctionalGroups["methyl"]
structure_copy = copy.deepcopy(structure)
structure_copy_graph = copy.deepcopy(structure)
sg = StructureGraph.with_local_env_strategy(structure, MinimumDistanceNN())
sg_copy = copy.deepcopy(sg)
# Ensure that strings and molecules lead to equivalent substitutions
sg.substitute_group(1, molecule, MinimumDistanceNN)
sg_copy.substitute_group(1, "methyl", MinimumDistanceNN)
self.assertEqual(sg, sg_copy)
# Ensure that the underlying structure has been modified as expected
structure_copy.substitute(1, "methyl")
self.assertEqual(structure_copy, sg.structure)
# Test inclusion of graph dictionary
graph_dict = {
(0, 1): {"weight": 0.5},
(0, 2): {"weight": 0.5},
(0, 3): {"weight": 0.5},
}
sg_with_graph = StructureGraph.with_local_env_strategy(structure_copy_graph, MinimumDistanceNN())
sg_with_graph.substitute_group(1, "methyl", MinimumDistanceNN, graph_dict=graph_dict)
edge = sg_with_graph.graph.get_edge_data(11, 13)[0]
self.assertEqual(edge["weight"], 0.5)
def test_predict(self):
p = DLSVolumePredictor()
p_fast = DLSVolumePredictor(cutoff=0.0) # for speed on compressed cells
p_nolimit = DLSVolumePredictor(min_scaling=None, max_scaling=None) # no limits on scaling
fen = Structure.from_file(os.path.join(dir_path, "FeN_mp-6988.cif"))
self.assertAlmostEqual(p.predict(fen), 18.2252568873)
fen.scale_lattice(fen.volume * 3.0)
self.assertAlmostEqual(p_nolimit.predict(fen), 18.2252568873)
self.assertAlmostEqual(p.predict(fen), fen.volume * 0.5)
fen.scale_lattice(fen.volume * 0.1)
self.assertAlmostEqual(p_nolimit.predict(fen), 18.2252568873)
self.assertAlmostEqual(p.predict(fen), fen.volume * 1.5)
self.assertAlmostEqual(p_fast.predict(fen), fen.volume * 1.5)
lfpo = PymatgenTest.get_structure("LiFePO4")
lfpo.scale_lattice(lfpo.volume * 3.0)
self.assertAlmostEqual(p_nolimit.predict(lfpo), 291.62094410192924)
self.assertAlmostEqual(p.predict(lfpo), lfpo.volume * 0.5)
lfpo.scale_lattice(lfpo.volume * 0.1)
self.assertAlmostEqual(p_nolimit.predict(lfpo), 291.62094410192924)
self.assertAlmostEqual(p.predict(lfpo), lfpo.volume * 1.5)
self.assertAlmostEqual(p_fast.predict(lfpo), lfpo.volume * 1.5)
lmpo = PymatgenTest.get_structure("LiFePO4")
lmpo.replace_species({"Fe": "Mn"})
self.assertAlmostEqual(p.predict(lmpo), 290.795329052)
def setUp(self):
with open(os.path.join(test_dir, "TiO2_entries.json"), 'r') as fp:
entries = json.load(fp, cls=MontyDecoder)
self.struct_list = [e.structure for e in entries]
self.oxi_structs = [self.get_structure("Li2O"),
Structure.from_file(os.path.join(
test_dir, "POSCAR.Li2O"))]
class UtilityTest(unittest.TestCase):
"""
Unit test for outside methods in io.py
"""
structure = Structure.from_file(get_path("POSCAR", dirname="io_files"))
def test_get_endpoints_from_index(self):
endpoints = get_endpoints_from_index(structure=self.structure,
site_indices=[0, 1])
ep_0 = endpoints[0].as_dict()
ep_1 = endpoints[1].as_dict()
ep_0_expect = Structure.from_file(get_path("POSCAR_ep0",
dirname="io_files")).as_dict()
ep_1_expect = Structure.from_file(get_path("POSCAR_ep1",
dirname="io_files")).as_dict()
self.assertEqual(ep_0, ep_0_expect)
self.assertEqual(ep_1, ep_1_expect)
def test_get_endpoint_dist(self):
ep0 = Structure.from_file(get_path("POSCAR_ep0", dirname="io_files"))
ep1 = Structure.from_file(get_path("POSCAR_ep1", dirname="io_files"))
distances = get_endpoint_dist(ep0, ep1)
self.assertAlmostEqual(max(distances), 6.3461081051543893, 7)
self.assertEqual(min(distances), 0.0)
def graph_from_file(filename, rcut, elements):
"""
Takes a pymatgen compatible file, an converts it to a graph object
Args:
- filename (str): name of file to set up graph from
- rcut (float): cut-off radius node-node connections in forming clusters
- elements ([str,str,.....]): list of elements to include in setting up graph
Returns:
- graph (Graph): graph object for structure
"""
clusters = clusters_from_file(filename=filename,
rcut=rcut,
elements=elements)
structure = Structure.from_file(filename)
all_elements = set([species for species in structure.symbol_set])
remove_elements = [x for x in all_elements if x not in elements]
structure.remove_species(remove_elements)
graph = Graph(clusters=clusters, structure=structure)
return graph
def predict(args):
"""
Handle view commands.
:param args: Args from command.
"""
headers = ["Filename"]
output = []
models = []
prefix = ""
for i, mn in enumerate(args.models):
model = MEGNetModel.from_file(mn)
models.append(model)
if i == 0:
prefix = mn
else:
sm = SequenceMatcher(None, prefix, mn)
match = sm.find_longest_match(0, len(prefix), 0, len(mn))
prefix = prefix[0:match.size]
headers.append(
f"{mn} ({model.metadata.get('unit', '').strip('log10')}")
headers = [h.lstrip(prefix) for h in headers]
for fn in args.structures:
structure = Structure.from_file(fn)
row = [fn]
for model in models:
val = model.predict_structure(structure).ravel()
if "log10" in str(model.metadata.get("unit", "")):
val = 10**val
row.append(val)
output.append(row)
print(tabulate(output, headers=headers))
def run_task(self, fw_spec):
unitcell = Structure.from_file("POSCAR")
supercell = self.get("supercell", None)
if supercell is not None:
os.system('cp POSCAR POSCAR-unitcell')
unitcell.make_supercell(supercell)
lepsilon = self.get("lepsilon", False)
standardize = self.get("standardize", False)
other_params = self.get("other_params", {})
user_incar_settings = self.get("user_incar_settings", {})
finder = SpacegroupAnalyzer(unitcell)
prims = finder.get_primitive_standard_structure()
# for lepsilon runs, the kpoints should be denser
if lepsilon:
kpoint_set = Generate_kpoints(prims, 0.02)
struct = prims
elif standardize:
kpoint_set = Generate_kpoints(prims, 0.03)
struct = prims
else:
kpoint_set = Generate_kpoints(unitcell, 0.03)
struct = unitcell
vis = MPStaticSet(struct,
user_incar_settings=user_incar_settings,
user_kpoints_settings=kpoint_set,
sym_prec=self.get("sym_prec", 0.1),
lepsilon=lepsilon,
**other_params)
vis.write_input(".")
class MVLCINEBEndPointSetTest(unittest.TestCase):
endpoint = Structure.from_file(get_path("POSCAR0", dirname="io_files"))
def test_incar(self):
m = MVLCINEBEndPointSet(self.endpoint)
incar_string = m.incar.get_string(sort_keys=True, pretty=True)
incar_expect = """ALGO = Fast
EDIFF = 5e-05
EDIFFG = -0.02
ENCUT = 520
IBRION = 2
ICHARG = 1
ISIF = 2
ISMEAR = 0
ISPIN = 2
ISYM = 0
LCHARG = False
LORBIT = 11
LREAL = Auto
LWAVE = False
MAGMOM = 35*0.6
NELM = 200
NELMIN = 4
NSW = 99
PREC = Accurate
SIGMA = 0.05"""
self.assertEqual(incar_string, incar_expect)
def test_incar_user_setting(self):
user_incar_settings = {"ALGO": "Normal",
"EDIFFG": -0.05,
"NELECT": 576,
"NPAR": 4,
"NSW": 100,}
m = MVLCINEBEndPointSet(self.endpoint, user_incar_settings=user_incar_settings)
incar_string = m.incar.get_string(sort_keys=True)
incar_expect = """ALGO = Normal
EDIFF = 5e-05
EDIFFG = -0.05
ENCUT = 520
IBRION = 2
ICHARG = 1
ISIF = 2
ISMEAR = 0
ISPIN = 2
ISYM = 0
LCHARG = False
LORBIT = 11
LREAL = Auto
LWAVE = False
MAGMOM = 35*0.6
NELECT = 576
NELM = 200
NELMIN = 4
NPAR = 4
NSW = 100
PREC = Accurate
SIGMA = 0.05"""
self.assertEqual(incar_string.strip(), incar_expect.strip())
def test_make_confs(self):
shutil.copy(os.path.join(self.source_path, 'Al-fcc.json'),
os.path.join(self.equi_path, 'result.json'))
if not os.path.exists(os.path.join(self.equi_path, 'CONTCAR')):
with self.assertRaises(RuntimeError):
self.elastic.make_confs(self.target_path, self.equi_path)
shutil.copy(os.path.join(self.source_path, 'CONTCAR_Al_fcc'),
os.path.join(self.equi_path, 'CONTCAR'))
task_list = self.elastic.make_confs(self.target_path, self.equi_path)
dfm_dirs = glob.glob(os.path.join(self.target_path, 'task.*'))
incar0 = Incar.from_file(os.path.join('vasp_input', 'INCAR.rlx'))
incar0['ISIF'] = 4
self.assertEqual(
os.path.realpath(os.path.join(self.equi_path, 'CONTCAR')),
os.path.realpath(os.path.join(self.target_path, 'POSCAR')))
ref_st = Structure.from_file(os.path.join(self.target_path, 'POSCAR'))
dfm_dirs.sort()
for ii in dfm_dirs:
st_file = os.path.join(ii, 'POSCAR')
self.assertTrue(os.path.isfile(st_file))
strain_json_file = os.path.join(ii, 'strain.json')
self.assertTrue(os.path.isfile(strain_json_file))
def test_writebandstr(self):
filepath = os.path.join(test_dir, 'CsI3Pb.cif')
structure = Structure.from_file(filepath)
excin = ExcitingInput(structure)
string = excin.write_string('primitive', bandstr=True)
bandstr = string.split('<properties>')[1].split('</properties>')[0]
coord = []
label = []
coord_ref = [[0.0, 0.0, 0.0], [0.5, 0.0, 0.0], [0.5, 0.5, 0.0],
[0.0, 0.5, 0.0], [0.0, 0.0, 0.0], [0.0, 0.0, 0.5],
[0.5, 0.0, 0.5], [0.5, 0.5, 0.5], [0.0, 0.5, 0.5],
[0.0, 0.0, 0.5], [0.0, 0.5, 0.0], [0.0, 0.5, 0.5],
[0.5, 0.0, 0.5], [0.5, 0.0, 0.0], [0.5, 0.5, 0.0],
[0.5, 0.5, 0.5]]
label_ref = [
'GAMMA', 'X', 'S', 'Y', 'GAMMA', 'Z', 'U', 'R', 'T', 'Z', 'Y', 'T',
'U', 'X', 'S', 'R'
]
root = ET.fromstring(bandstr)
for plot1d in root.iter('plot1d'):
for point in plot1d.iter('point'):
coord.append([float(i) for i in point.get('coord').split()])
label.append(point.get('label'))
self.assertEqual(label, label_ref)
self.assertEqual(coord, coord_ref)
def slab_from_file(structure, hkl):
"""
Reads in structure from the file and returns slab object.
Args:
structure (str): Structure file in any format supported by pymatgen.
Will accept a pymatgen.Structure object directly.
hkl (tuple): Miller index of the slab in the input file.
Returns:
Slab object
"""
if type(structure) == str:
slab_input = Structure.from_file(structure)
else:
slab_input = structure
return Slab(
slab_input.lattice,
slab_input.species_and_occu,
slab_input.frac_coords,
hkl,
Structure.from_sites(slab_input, to_unit_cell=True),
# this OUC is not correct, need to get it from slabgenerator
shift=0,
scale_factor=np.eye(3, dtype=np.int),
site_properties=slab_input.site_properties)
def test_make_defect_entries(tmpdir, supercell_info):
tmpdir.chdir()
supercell_info.to_json_file()
defect_set = DefectSet({SimpleDefect(None, "He1", [-1, 0])})
defect_set.to_yaml()
args = Namespace()
make_defect_entries(args)
names = {str(name) for name in Path(".").glob("*")}
assert names == {
'Va_He1_-1', 'defect_in.yaml', 'perfect', 'Va_He1_0',
'supercell_info.json'
}
perfect_structure = Structure.from_file(str(Path("perfect") / "POSCAR"))
assert perfect_structure == supercell_info.structure
file_names = {
str(file_name.name)
for file_name in Path("Va_He1_-1").glob("*")
}
assert file_names == {"POSCAR", "defect_entry.json", "prior_info.yaml"}
expected = """charge: -1
"""
assert Path("Va_He1_-1/prior_info.yaml").read_text() == expected
def test_lone_molecule():
mofchecker = MOFChecker(
Structure.from_file(
os.path.join(THIS_DIR, "test_files", "ABAVIJ_clean.cif")))
assert mofchecker.has_lone_molecule == False
mofchecker = MOFChecker(
Structure.from_file(
os.path.join(THIS_DIR, "test_files", "HKUST_floating.cif")))
assert mofchecker.has_lone_molecule == True
assert mofchecker.lone_molecule_indices == [[144]]
atoms = read(os.path.join(THIS_DIR, "test_files", "overvalent_h.cif"))
mofchecker = MOFChecker.from_ase(atoms, primitive=False)
assert len(mofchecker.lone_molecule_indices) == 3
def test_get_poscar_from_mp(tmpdir):
args = Namespace(mpid="mp-110",
poscar="POSCAR",
prior_info=Path("prior_info.yaml"))
tmpdir.chdir()
get_poscar_from_mp(args)
expected = """Mg1
1.0
-1.789645 1.789645 1.789645
1.789645 -1.789645 1.789645
1.789645 1.789645 -1.789645
1
direct
0.000000 0.000000 0.000000 Mg
"""
assert Structure.from_file("POSCAR") == Structure.from_str(expected,
fmt="POSCAR")
assert Path("prior_info.yaml").read_text() == """band_gap: 0.0
data_source: mp-110
icsd_ids:
- 180455
- 642652
total_magnetization: 0.0001585
"""
# Need to remove file to avoid the side effect for other unittests.
os.remove("prior_info.yaml")
def test_electronegativity(self):
sm = StructureMatcher(ltol=0.2, stol=0.3, angle_tol=5)
s1 = Structure.from_file(os.path.join(test_dir, "Na2Fe2PAsO4S4.json"))
s2 = Structure.from_file(os.path.join(test_dir, "Na2Fe2PNO4Se4.json"))
self.assertEqual(
sm.get_best_electronegativity_anonymous_mapping(s1, s2),
{
Element("S"): Element("Se"),
Element("As"): Element("N"),
Element("Fe"): Element("Fe"),
Element("Na"): Element("Na"),
Element("P"): Element("P"),
Element("O"): Element("O"),
},
)
self.assertEqual(len(sm.get_all_anonymous_mappings(s1, s2)), 2)
def test_ignore_species(self):
s1 = Structure.from_file(os.path.join(test_dir, "LiFePO4.cif"))
s2 = Structure.from_file(os.path.join(test_dir, "POSCAR"))
m = StructureMatcher(ignored_species=["Li"], primitive_cell=False, attempt_supercell=True)
self.assertTrue(m.fit(s1, s2))
self.assertTrue(m.fit_anonymous(s1, s2))
groups = m.group_structures([s1, s2])
self.assertEqual(len(groups), 1)
s2.make_supercell((2, 1, 1))
ss1 = m.get_s2_like_s1(s2, s1, include_ignored_species=True)
self.assertAlmostEqual(ss1.lattice.a, 20.820740000000001)
self.assertEqual(ss1.composition.reduced_formula, "LiFePO4")
self.assertEqual(
{k.symbol: v.symbol for k, v in m.get_best_electronegativity_anonymous_mapping(s1, s2).items()},
{"Fe": "Fe", "P": "P", "O": "O"},
)
def setUp(self):
"""
1) Basic check for pymatgen configurations.
2) Setup all test workflow.
"""
super(TestNudgedElasticBandWorkflow, self).setUp()
# Structures used for test:
parent = PymatgenTest.get_structure("Li2O")
parent.remove_oxidation_states()
parent.make_supercell(2)
ep0, ep1 = get_endpoints_from_index(parent, [0, 1])
neb_dir = [os.path.join(module_dir, "..", "..", "test_files", "neb_wf", "4", "inputs", "{:02}",
"POSCAR").format(i) for i in range(5)]
self.structures = [Structure.from_file(n) for n in neb_dir]
# Run fake vasp
test_yaml = os.path.join(module_dir, "../../test_files/neb_wf/config/neb_unittest.yaml")
with open(test_yaml, 'r') as stream:
self.config = yaml.safe_load(stream)
# Use scratch directory as destination directory for testing
self.config["common_params"]["_fw_env"] = {"run_dest_root": self.scratch_dir}
# Config 1: The parent structure & two endpoint indexes provided; need relaxation first.
self.config_1 = copy.deepcopy(self.config)
self.config_1["common_params"]["is_optimized"] = False
self.config_1["common_params"]["wf_name"] = "NEB_test_1"
# Config 2: The parent structure & two endpoint indexes provided; no need to relax.
self.config_2 = copy.deepcopy(self.config)
del self.config_2["fireworks"][0]
self.config_2["common_params"]["is_optimized"] = True
self.config_2["common_params"]["wf_name"] = "NEB_test_2"
# Config 3: Two endpoints provided; need to relax two endpoints.
self.config_3 = copy.deepcopy(self.config)
del self.config_3["fireworks"][0]
self.config_3["common_params"]["is_optimized"] = False
self.config_3["common_params"]["wf_name"] = "NEB_test_3"
# Config 4: Two relaxed endpoints provided; no need to relax two endpoints.
self.config_4 = copy.deepcopy(self.config_3)
del self.config_4["fireworks"][0]
self.config_4["common_params"]["is_optimized"] = True
self.config_4["common_params"]["wf_name"] = "NEB_test_4"
# Config 5: All images including two endpoints are provided.
self.config_5 = copy.deepcopy(self.config)
del self.config_5["fireworks"][0: 2]
self.config_5["common_params"]["wf_name"] = "NEB_test_5"
self.wf_1 = wf_nudged_elastic_band([parent], parent, self.config_1)
self.wf_2 = wf_nudged_elastic_band([parent], parent, self.config_2)
self.wf_3 = wf_nudged_elastic_band([ep0, ep1], parent, self.config_3)
self.wf_4 = wf_nudged_elastic_band([ep0, ep1], parent, self.config_4)
self.wf_5 = wf_nudged_elastic_band(self.structures, parent, self.config_5)
# Workflow without the config file
self.wf_6 = wf_nudged_elastic_band(self.structures, parent)
def setUp(self):
filepath = os.path.join(test_dir, 'Li.cif')
self.s = Structure.from_file(filepath)
self.bulk = MVLGBSet(self.s)
self.slab = MVLGBSet(self.s, slab_mode=True)
self.d_bulk = self.bulk.all_input
self.d_slab = self.slab.all_input
def test_electronegativity(self):
sm = StructureMatcher(ltol=0.2, stol=0.3, angle_tol=5)
s1 = Structure.from_file(os.path.join(test_dir, "Na2Fe2PAsO4S4.json"))
s2 = Structure.from_file(os.path.join(test_dir, "Na2Fe2PNO4Se4.json"))
self.assertEqual(sm.get_best_electronegativity_anonymous_mapping(s1, s2),
{Element('S'): Element('Se'),
Element('As'): Element('N'),
Element('Fe'): Element('Fe'),
Element('Na'): Element('Na'),
Element('P'): Element('P'),
Element('O'): Element('O'),})
self.assertEqual(len(sm.get_all_anonymous_mappings(s1, s2)), 2)
# test include_dist
dists = {Element('N'): 0, Element('P'): 0.0010725064}
for mapping, d in sm.get_all_anonymous_mappings(s1, s2, include_dist=True):
self.assertAlmostEqual(dists[mapping[Element('As')]], d)
def setUp(self):
filepath = self.TEST_FILES_DIR / 'Li.cif'
self.s = Structure.from_file(filepath)
self.bulk = MVLGBSet(self.s)
self.slab = MVLGBSet(self.s, slab_mode=True)
self.d_bulk = self.bulk.get_vasp_input()
self.d_slab = self.slab.get_vasp_input()
warnings.simplefilter("ignore")
def handle_input_event(self, abiinput, outdir, event):
try:
old_abiinput = abiinput.deepcopy()
# Read the last structure dumped by ABINIT before aborting.
filepath = outdir.has_abiext("DILATMX_STRUCT.nc")
last_structure = Structure.from_file(filepath)
abiinput.set_structure(last_structure)
return Correction(self, self.compare_inputs(abiinput, old_abiinput), event, False)
except Exception as exc:
logger.warning('Error while trying to apply the handler {}.'.format(str(self)), exc)
return None
def test_mix(self):
structures = [self.get_structure("Li2O"), self.get_structure("Li2O2"), self.get_structure("LiFePO4")]
for fname in ["POSCAR.Li2O", "POSCAR.LiFePO4"]:
structures.append(Structure.from_file(os.path.join(test_dir, fname)))
sm = StructureMatcher(comparator=ElementComparator())
groups = sm.group_structures(structures)
for g in groups:
formula = g[0].composition.reduced_formula
if formula in ["Li2O", "LiFePO4"]:
self.assertEqual(len(g), 2)
else:
self.assertEqual(len(g), 1)
def test_ordering_enumeration(self):
# simple afm
structure = Structure.from_file(
os.path.join(test_dir, "magnetic_orderings/LaMnO3.json"))
enumerator = MagneticStructureEnumerator(structure)
self.assertEqual(enumerator.input_origin, "afm")
# ferrimagnetic (Cr produces net spin)
structure = Structure.from_file(
os.path.join(test_dir, "magnetic_orderings/Cr2NiO4.json"))
enumerator = MagneticStructureEnumerator(structure)
self.assertEqual(enumerator.input_origin, "ferri_by_Cr")
# antiferromagnetic on single magnetic site
structure = Structure.from_file(
os.path.join(test_dir, "magnetic_orderings/Cr2WO6.json"))
enumerator = MagneticStructureEnumerator(structure)
self.assertEqual(enumerator.input_origin, "afm_by_Cr")
# afm requiring large cell size
# (enable for further development of workflow, too slow for CI)
# structure = Structure.from_file(os.path.join(ref_dir, "CuO.json"))
# enumerator = MagneticOrderingsenumerator(structure, default_magmoms={'Cu': 1.73},
# transformation_kwargs={'max_cell_size': 4})
# self.assertEqual(enumerator.input_origin, "afm")
# antiferromagnetic by structural motif
structure = Structure.from_file(
os.path.join(test_dir, "magnetic_orderings/Ca3Co2O6.json"))
enumerator = MagneticStructureEnumerator(
structure,
strategies=("antiferromagnetic_by_motif",),
# this example just misses default cut-off, so do not truncate
truncate_by_symmetry=False,
transformation_kwargs={"max_cell_size": 2},
)
self.assertEqual(enumerator.input_origin, "afm_by_motif_2a")
def setup(self):
"""
Performs initial setup for VaspJob, including overriding any settings
and backing up.
"""
files = os.listdir(".")
num_structures = 0
if not set(files).issuperset({"INCAR", "POSCAR", "POTCAR", "KPOINTS"}):
for f in files:
try:
struct = Structure.from_file(f)
num_structures += 1
except:
pass
if num_structures != 1:
raise RuntimeError("{} structures found. Unable to continue."
.format(num_structures))
else:
self.default_vis.write_input(struct, ".")
if self.backup:
for f in VASP_INPUT_FILES:
shutil.copy(f, "{}.orig".format(f))
if self.auto_npar:
try:
incar = Incar.from_file("INCAR")
#Only optimized NPAR for non-HF and non-RPA calculations.
if not (incar.get("LHFCALC") or incar.get("LRPA") or
incar.get("LEPSILON")):
if incar.get("IBRION") in [5, 6, 7, 8]:
# NPAR should not be set for Hessian matrix
# calculations, whether in DFPT or otherwise.
del incar["NPAR"]
else:
import multiprocessing
# try sge environment variable first
# (since multiprocessing counts cores on the current machine only)
ncores = os.environ.get('NSLOTS') or multiprocessing.cpu_count()
ncores = int(ncores)
for npar in range(int(round(math.sqrt(ncores))),
ncores):
if ncores % npar == 0:
incar["NPAR"] = npar
break
incar.write_file("INCAR")
except:
pass
if self.settings_override is not None:
VaspModder().apply_actions(self.settings_override)
def correct(self, task):
#Idea: decrease dilatxm and restart from the last structure.
#We would like to end up with a structures optimized with dilatmx 1.01
#that will be used for phonon calculations.
# Read the last structure dumped by ABINIT before aborting.
print("in dilatmx")
filepath = task.outdir.has_abiext("DILATMX_STRUCT.nc")
last_structure = Structure.from_file(filepath)
task._change_structure(last_structure)
#changes = task._modify_vars(dilatmx=1.05)
task.history.append("Take last structure from DILATMX_STRUCT.nc, will try to restart")
return 1
def test_incar(self):
filepath = os.path.join(test_dir, 'Li.cif')
structure = Structure.from_file(filepath)
vis = MPNMRSet(structure)
self.assertTrue(vis.incar.get("LCHIMAG", None))
self.assertEqual(vis.incar.get("QUAD_EFG", None), None)
vis = MPNMRSet(structure, mode="efg")
self.assertFalse(vis.incar.get("LCHIMAG", None))
self.assertEqual(vis.incar.get("QUAD_EFG", None), [-0.808])
vis = MPNMRSet(structure, mode="efg", isotopes=["Li-7"])
self.assertFalse(vis.incar.get("LCHIMAG", None))
self.assertEqual(vis.incar.get("QUAD_EFG", None), [-40.1])
def test_ln_magmom(self):
YAML_PATH = os.path.join(os.path.dirname(__file__), "../VASPIncarBase.yaml")
MAGMOM_SETTING = loadfn(YAML_PATH)["MAGMOM"]
structure = Structure.from_file(os.path.join(test_dir, "La4Fe4O12.cif"))
structure.add_oxidation_state_by_element({"La": +3, "Fe": +3, "O": -2})
for ion in MAGMOM_SETTING:
s = structure.copy()
s.replace_species({"La3+": ion})
vis = MPRelaxSet(s)
fe_pos = vis.poscar.comment.index("Fe")
if fe_pos == 0:
magmom_ans = [5] * 4 + [MAGMOM_SETTING[ion]] * 4 + [0.6] * 12
else:
magmom_ans = [MAGMOM_SETTING[ion]] * 4 + [5] * 4 + [0.6] * 12
self.assertEqual(vis.incar["MAGMOM"], magmom_ans)
def test_predict(self):
p = DLSVolumePredictor()
fen = Structure.from_file(os.path.join(dir_path, "FeN_mp-6988.cif"))
self.assertAlmostEquals(p.predict(fen), 18.2252568873)
fen.scale_lattice(3.0)
self.assertAlmostEquals(p.predict(fen), 18.2252568873)
fen.scale_lattice(0.24)
self.assertAlmostEquals(p.predict(fen), 18.2252568873)
lfpo = PymatgenTest.get_structure("LiFePO4")
lfpo.scale_lattice(10.1)
self.assertAlmostEqual(p.predict(lfpo), 291.62094410192924)
lfpo.scale_lattice(0.2)
self.assertAlmostEqual(p.predict(lfpo), 291.62094410192924)
lmpo = PymatgenTest.get_structure("LiFePO4")
lmpo.replace_species({"Fe": "Mn"})
self.assertAlmostEquals(p.predict(lmpo), 290.795329052)
def handle_task_event(self, task, event):
# Read the last structure dumped by ABINIT before aborting.
filepath = task.outdir.has_abiext("DILATMX_STRUCT.nc")
last_structure = Structure.from_file(filepath)
task._change_structure(last_structure)
#read the suggested dilatmx
# new_dilatmx = 1.05
# if new_dilatmx > self.max_dilatmx:
# msg = "Suggested dilatmx ({}) exceeds maximux configured value ({}).".format(new_dilatmx, self.max_dilatmx)
# return self.NOT_FIXED
# task.strategy.abinit_input.set_vars(dilatmx=new_dilatmx)
msg = "Take last structure from DILATMX_STRUCT.nc, will try to restart with dilatmx %s" % task.get_inpvar("dilatmx")
task.log_correction(event, msg)
# Note that we change the structure but we don't try restart from the previous WFK|DEN file
# because Abinit called mpi_abort and therefore no final WFK|DEN file has been produced.
return self.FIXED
def _get_cgcnn_data(task="classification"):
"""
Get cgcnn sample data.
Args:
task (str): Classification or regression,
decided which sample data to return.
Returns:
id_prop_data (list): List of property data.
elem_embedding (list): List of element features.
struct_list (list): List of structure object.
"""
if task == "classification":
cgcnn_data_path = os.path.join(os.path.dirname(cgcnn.__file__),
"..", "data", "sample-classification")
else:
cgcnn_data_path = os.path.join(os.path.dirname(cgcnn.__file__),
"..", "data", "sample-regression")
struct_list = list()
cif_list = list()
with open(os.path.join(cgcnn_data_path, "id_prop.csv")) as f:
reader = csv.reader(f)
id_prop_data = [row[1] for row in reader]
with open(os.path.join(cgcnn_data_path, "atom_init.json")) as f:
elem_embedding = json.load(f)
for file in os.listdir(cgcnn_data_path):
if file.endswith('.cif'):
cif_list.append(int(file[:-4]))
cif_list = sorted(cif_list)
for cif_name in cif_list:
crystal = Structure.from_file(os.path.join(cgcnn_data_path,
'{}.cif'.format(
cif_name)))
struct_list.append(crystal)
return id_prop_data, elem_embedding, struct_list
#!/usr/bin/env python
from Generate_Surface import get_SD_along_vector
from Classes_Pymatgen import Poscar
from pymatgen.core import Structure
import argparse
parser = argparse.ArgumentParser()
parser.add_argument('lower_bound', help='vector to begin freezing at',
default=None, type=float)
parser.add_argument('upper_bound', help='vector to end freezing at',
default=None, type=float)
parser.add_argument('--vector', help='Vector to Freeze along (default = 2)',
default=2, type=int)
parser.add_argument('--input', help='file to read (default = CONTCAR)',
default='CONTCAR', type=str)
parser.add_argument('--output', help='file to write (default = CONTCAR.sd)',
default='CONTCAR.sd', type=str)
args = parser.parse_args()
lb = args.lower_bound
ub = args.upper_bound
v = args.vector
s = Structure.from_file(args.input)
sd = get_SD_along_vector(s, v, [lb, ub])
Poscar(s, selective_dynamics=sd).write_file(args.output)
def test_left_handed_lattice(self):
"""Ensure Left handed lattices are accepted"""
sm = StructureMatcher()
s = Structure.from_file(os.path.join(test_dir, "Li3GaPCO7.json"))
self.assertTrue(sm.fit(s, s))
adsorb_on_species=iface.adsorb_on_species,
primitive=False, from_ase=True,
x_shift=x, y_shift=y)
iface.create_interface()
energy = iface.calc_energy()
iface.sort()
if energy < ecut:
ifaces.append((energy, iface))
# ifaces.zip(energy, iface)
return ifaces
if __name__ == '__main__':
# PbS 100 surface with single hydrazine as ligand
# sample pre-relaxed structure files for Bulk (strt) and Molecule
strt = Structure.from_file("POSCAR_PbS")
mol_struct = Structure.from_file("POSCAR_Hydrazine")
mol = Molecule(mol_struct.species, mol_struct.cart_coords)
hydrazine = Ligand([mol])
# intital supercell, this wont be the final supercell if
# surface coverage is specified
supercell = [1, 1, 1]
# miller index
hkl = [1, 0, 0]
# minimum slab thickness in Angstroms
min_thick = 19
# minimum vacuum thickness in Angstroms
from pymatgen.io.abinitio.works import RelaxWork
from pymatgen.io.abinitio.tasks import TaskManager
from pymatgen.io.abinitio.flows import Flow
from pymatgen.io.abinitio.strategies import RelaxStrategy
from pymatgen.io.abinitio.abiobjects import KSampling, RelaxationMethod, AbiStructure
from pymatgen.core import Structure
from myscripts.pseudos import all_pseudos
scratchdir = '/p/lscratchd/damewood'
basename = '2014_Trilayer/abinit_6z'
workdir = os.path.join(scratchdir,basename)
logging.basicConfig()
structure = Structure.from_file('trilayer_6z.json')
manager = TaskManager.from_user_config()
ksampling = KSampling(mode='monkhorst',kpts=((6,6,2),), kpt_shifts=((0.5,0.5,0.5),(0.5,0.0,0.0),(0.0,0.5,0.0),(0.0,0.0,0.5)))
relax_ion = RelaxationMethod(ionmov = 2, optcell = 0)
relax_ioncell = RelaxationMethod(ionmov = 2, optcell = 1)
pseudos = all_pseudos()
flow = Flow(manager = manager, workdir = os.path.join(workdir, 'trilayer_6z'))
spins = numpy.zeros([len(structure),3])
spins[:4,2] = 3.
ion_input = RelaxStrategy(structure, pseudos, ksampling,
relax_ion, accuracy="high", smearing = "fermi_dirac:0.025 eV",
ecut = 40., pawecutdg = 80., chkprim = 0, tolmxf = 5.e-6, spinat = spins,
restartxf = -2, nband = 60, nstep = 100)
ioncell_input = ion_input.copy()
ioncell_input.relax_algo = relax_ioncell
def run_task(self, fw_spec):
label = self["label"]
assert label in ["parent", "ep0", "ep1"] or "neb" in label, "Unknown label!"
d_img = float(self.get("d_img", 0.7)) # Angstrom
wf_name = fw_spec["wf_name"]
src_dir = os.path.abspath(".")
dest_dir = os.path.join(fw_spec["_fw_env"]["run_dest_root"], wf_name, label)
shutil.copytree(src_dir, dest_dir)
# Update fw_spec based on the type of calculations.
if "neb" in label:
# Update all relaxed images.
subs = glob.glob("[0-2][0-9]")
nimages = len(subs)
concar_list = ["{:02}/CONTCAR".format(i) for i in range(nimages)[1:-1]]
images = [Structure.from_file(contcar) for contcar in concar_list]
# Update the two ending "images".
images.insert(0, Structure.from_file("00/POSCAR"))
images.append(Structure.from_file("{:02}/POSCAR".format(nimages - 1)))
images = [s.as_dict() for s in images]
neb = fw_spec.get("neb")
neb.append(images)
update_spec = {"neb": neb, "_queueadapter": {"nnodes": str(len(images) - 2),
"nodes": str(len(images) - 2)}}
# Use neb walltime if it is in fw_spec
if fw_spec["neb_walltime"] is not None:
update_spec["_queueadapter"].update({"walltime": fw_spec.get("neb_walltime")})
elif label in ["ep0", "ep1"]:
# Update relaxed endpoint structures.
file = glob.glob("CONTCAR*")[0]
ep = Structure.from_file(file, False) # One endpoint
if fw_spec.get("incar_images"): # "incar_images": pre-defined image number.
update_spec = {label: ep.as_dict(),
"_queueadapter": {"nnodes": fw_spec["incar_images"],
"nodes": fw_spec["incar_images"]}}
else:
# Calculate number of images if "IMAGES" tag is not provided.
index = int(label[-1])
ep_1_dict = fw_spec.get("ep{}".format(1 - index)) # Another endpoint
try:
ep_1 = Structure.from_dict(ep_1_dict)
except:
ep_1 = ep_1_dict
max_dist = max(get_endpoint_dist(ep, ep_1))
nimages = round(max_dist / d_img) or 1
update_spec = {label: ep, "_queueadapter": {"nnodes": int(nimages),
"nodes": int(nimages)}}
# Use neb walltime if it is in fw_spec
if fw_spec["neb_walltime"] is not None:
update_spec["_queueadapter"].update({"walltime": fw_spec.get("neb_walltime")})
else: # label == "parent"
f = glob.glob("CONTCAR*")[0]
s = Structure.from_file(f, False)
ep0, ep1 = get_endpoints_from_index(s, fw_spec["site_indices"])
update_spec = {"parent": s.as_dict(), "ep0": ep0.as_dict(), "ep1": ep1.as_dict()}
# Clear current directory.
for d in os.listdir(src_dir):
try:
os.remove(os.path.join(src_dir, d))
except:
shutil.rmtree(os.path.join(src_dir, d))
return FWAction(update_spec=update_spec)
import sys
from pymatgen.core import Molecule, Structure
from pymatgen.io.vasp.inputs import Poscar
from mpinterfaces.interface import Interface, Ligand
if __name__ == '__main__':
# PbS 100 surface with single hydrazine as ligand
# strt=get_struct_from_mp("PbS",MAPI_KEY=MAPI_KEY)
# using smiles_to_xyz.py you can obtain molecule xyz
# using openbabel.
# example structure files are provided and set in dev_scripts
# bulk structure of slab
strt = Structure.from_file("dev_scripts/POSCAR_PbS")
# pre-relaxed Ligand in a box
mol_struct = Structure.from_file("dev_scripts/POSCAR_TCPO")
mol = Molecule(mol_struct.species, mol_struct.cart_coords)
hydrazine = Ligand([mol])
# intital supercell, this wont be the final supercell if
# surface coverage is specified
supercell = [1, 1, 1]
# miller index
hkl = [1, 0, 0]
# minimum slab thickness in Angstroms
min_thick = 19
import sys
from pymatgen.core import Structure
from pymatgen.io.vasp.inputs import Poscar
from mpinterfaces.interface import Interface
if __name__=='__main__':
# input structure file: bulk
fin = 'POSCAR.bulk'
# output file name
fout = 'POSCAR'
hkl = [0,0,1] # hkl wrt the input structure
min_thick = 15 # angstroms
min_vac = 30 # angstroms
#use ase to create an orthogonal slab
bulk = Structure.from_file(fin)
iface = Interface(bulk, hkl=hkl,
min_thick=min_thick, min_vac=min_vac,
primitive= False, from_ase = True)
iface.create_interface()
iface.sort()
#set selective dynamics flags
# 1 --> T and 0 --> F
sd_flags = [[1,1,1] for i in iface.sites]
iface_poscar = Poscar(iface, selective_dynamics= sd_flags)
#write to file
iface_poscar.write_file(fout)
"""
import shutil as shu
from pymatgen.io.vaspio.vasp_input import Incar, Poscar, Potcar, Kpoints
from pymatgen.core import Structure, Molecule
from mpinterfaces.interface import Interface, Ligand
#create ligand, interface and slab from the starting POSCARs
strt= Structure.from_file("POSCAR_PbS_bulk_with_vdw") #using POSCAR of vdW relaxed PbS
mol_struct= Structure.from_file("POSCAR_DMF") #using POSCAR of vdW relaxed PbS
mol= Molecule(mol_struct.species, mol_struct.cart_coords)
DMF= Ligand([mol]) #create Ligand DMF
supercell = [1,1,1]
# slab thickness and vacuum set manual for now to converged values, surface coverage fixed at 0.014 ligand/sq.Angstrom
#for consistency, best ligand spacing at the coverage
min_thick= 19
min_vac= 12
surface_coverage= 0.014
#hkl of facet to reproduce
hkl= [1,0,0]
# specify the species on slab to adsorb over
slab_species= 'Pb'
# specify the species onb ligand serving as the bridge atom
adatom_on_ligand= 'O'
def test_sublattice_generation(self):
struc = PymatgenTest.get_structure("CsCl")
sc_struc = struc.copy()
sc_struc.make_supercell(3)
# test for vacancy and sub (should not change structure)
Cs_index = sc_struc.indices_from_symbol("Cs")[0]
cs_vac = Vacancy(sc_struc, sc_struc[Cs_index])
decorated_cs_vac = create_saturated_interstitial_structure(cs_vac)
self.assertEqual(len(decorated_cs_vac), len(sc_struc))
Cl_index = sc_struc.indices_from_symbol("Cl")[0]
cl_vac = Vacancy(sc_struc, sc_struc[Cl_index])
decorated_cl_vac = create_saturated_interstitial_structure(cl_vac)
self.assertEqual(len(decorated_cl_vac), len(sc_struc))
sub_site = PeriodicSite("Sr", sc_struc[Cs_index].coords, sc_struc.lattice,
coords_are_cartesian=True)
sub = Substitution(sc_struc, sub_site)
decorated_sub = create_saturated_interstitial_structure(sub)
self.assertEqual(len(decorated_sub), len(sc_struc))
# test interstitial in symmorphic structure type
inter_site = PeriodicSite("H", [0., 1.05225, 2.1045], struc.lattice,
coords_are_cartesian=True) # voronoi type
interstitial = Interstitial(struc, inter_site)
decorated_inter = create_saturated_interstitial_structure(interstitial)
self.assertEqual(len(decorated_inter), 14)
inter_site = PeriodicSite("H", [0.10021429, 0.10021429, 2.1045], struc.lattice,
coords_are_cartesian=True) # InFit type
interstitial = Interstitial(struc, inter_site)
decorated_inter = create_saturated_interstitial_structure(interstitial)
self.assertEqual(len(decorated_inter), 14)
inter_site = PeriodicSite("H", [4.10878571, 1.10235714, 2.1045], struc.lattice,
coords_are_cartesian=True) # InFit type
interstitial = Interstitial(struc, inter_site)
decorated_inter = create_saturated_interstitial_structure(interstitial)
self.assertEqual(len(decorated_inter), 26)
inter_site = PeriodicSite("H", [0., 0., 0.5], struc.lattice,
coords_are_cartesian=False) # a reasonable guess type
interstitial = Interstitial(struc, inter_site)
decorated_inter = create_saturated_interstitial_structure(interstitial)
self.assertEqual(len(decorated_inter), 5)
# test interstitial in non-symmorphic structure type
# (voronoi and InFit generator of different types...)
ns_struc = Structure.from_file(os.path.join(test_dir, "CuCl.cif"))
inter_site = PeriodicSite("H", [0.45173594, 0.41157895, 5.6604067], ns_struc.lattice,
coords_are_cartesian=True) # InFit type
interstitial = Interstitial(ns_struc, inter_site)
decorated_inter = create_saturated_interstitial_structure(interstitial)
self.assertEqual(len(decorated_inter), 40)
inter_site = PeriodicSite("H", [0.47279906, 0.82845998, 5.62015285], ns_struc.lattice,
coords_are_cartesian=True) # InFit type
interstitial = Interstitial(ns_struc, inter_site)
decorated_inter = create_saturated_interstitial_structure(interstitial)
self.assertEqual(len(decorated_inter), 40)
inter_site = PeriodicSite("H", [0.70845255, 6.50298148, 5.16979425], ns_struc.lattice,
coords_are_cartesian=True) # InFit type
interstitial = Interstitial(ns_struc, inter_site)
decorated_inter = create_saturated_interstitial_structure(interstitial)
self.assertEqual(len(decorated_inter), 40)
inter_site = PeriodicSite("H", [0.98191329, 0.36460337, 4.64718203], ns_struc.lattice,
coords_are_cartesian=True) # InFit type
interstitial = Interstitial(ns_struc, inter_site)
decorated_inter = create_saturated_interstitial_structure(interstitial)
self.assertEqual(len(decorated_inter), 40)
inter_site = PeriodicSite("H", [0.39286561, 3.92702149, 1.05802631], ns_struc.lattice,
coords_are_cartesian=True) # InFit type
interstitial = Interstitial(ns_struc, inter_site)
decorated_inter = create_saturated_interstitial_structure(interstitial)
self.assertEqual(len(decorated_inter), 40)
