def interpolate_poscar(self, fw_spec):
# make folder for poscar interpolation start and end structure files.
interpolate_folder = 'interpolate'
if not os.path.exists(os.path.join(os.getcwd(), interpolate_folder)):
os.makedirs(os.path.join(os.getcwd(), interpolate_folder))
# use method of GrabFilesFromCalcLoc to grab files from previous locations.
CopyFilesFromCalcLoc(calc_dir=None, calc_loc=self["start"],
filenames=["CONTCAR"],
name_prepend=interpolate_folder + os.sep,
name_append="_0").run_task(fw_spec=fw_spec)
CopyFilesFromCalcLoc(calc_dir=None, calc_loc=self["end"],
filenames=["CONTCAR"],
name_prepend=interpolate_folder + os.sep,
name_append="_1").run_task(fw_spec=fw_spec)
# assuming first calc_dir is polar structure for ferroelectric search
s1 = Structure.from_file(os.path.join(interpolate_folder, "CONTCAR_0"))
s2 = Structure.from_file(os.path.join(interpolate_folder, "CONTCAR_1"))
structs = s1.interpolate(s2, self["nimages"], interpolate_lattices=True,
autosort_tol=self.get("autosort_tol", 0.0))
# save only the interpolation needed for this run
i = self.get("this_image")
return structs[i]
def test_to_from_file_string(self):
for fmt in ["cif", "json", "poscar", "cssr"]:
s = self.struct.to(fmt=fmt)
self.assertIsNotNone(s)
ss = IStructure.from_str(s, fmt=fmt)
self.assertArrayAlmostEqual(
ss.lattice.lengths_and_angles,
self.struct.lattice.lengths_and_angles, decimal=5)
self.assertArrayAlmostEqual(ss.frac_coords, self.struct.frac_coords)
self.assertIsInstance(ss, IStructure)
self.struct.to(filename="POSCAR.testing")
self.assertTrue(os.path.exists("POSCAR.testing"))
os.remove("POSCAR.testing")
self.struct.to(filename="Si_testing.yaml")
self.assertTrue(os.path.exists("Si_testing.yaml"))
s = Structure.from_file("Si_testing.yaml")
self.assertEqual(s, self.struct)
os.remove("Si_testing.yaml")
self.struct.to(filename="POSCAR.testing.gz")
s = Structure.from_file("POSCAR.testing.gz")
self.assertEqual(s, self.struct)
os.remove("POSCAR.testing.gz")
def relax(dim=2, submit=True, force_overwrite=False):
"""
Writes input files and (optionally) submits a self-consistent
relaxation. Should be run before pretty much anything else, in
order to get the right energy and structure of the material.
Args:
dim (int): 2 for relaxing a 2D material, 3 for a 3D material.
submit (bool): Whether or not to submit the job.
force_overwrite (bool): Whether or not to overwrite files
if an already converged vasprun.xml exists in the
directory.
"""
if force_overwrite or not utl.is_converged(os.getcwd()):
directory = os.getcwd().split('/')[-1]
# vdw_kernel.bindat file required for VDW calculations.
if VDW_KERNEL:
os.system('cp {} .'.format(VDW_KERNEL))
# KPOINTS
Kpoints.automatic_density(Structure.from_file('POSCAR'),
1000).write_file('KPOINTS')
# INCAR
INCAR_DICT.update(
{'MAGMOM': utl.get_magmom_string(Structure.from_file('POSCAR'))}
)
Incar.from_dict(INCAR_DICT).write_file('INCAR')
# POTCAR
utl.write_potcar()
# Special tasks only performed for 2D materials.
if dim == 2:
# Ensure 20A interlayer vacuum
utl.ensure_vacuum(Structure.from_file('POSCAR'), 20)
# Remove all z k-points.
kpts_lines = open('KPOINTS').readlines()
with open('KPOINTS', 'w') as kpts:
for line in kpts_lines[:3]:
kpts.write(line)
kpts.write(kpts_lines[3].split()[0] + ' '
+ kpts_lines[3].split()[1] + ' 1')
# Submission script
if dim == 2:
binary = VASP_TWOD_BIN
elif dim == 3:
binary = VASP_STD_BIN
if QUEUE_SYSTEM == 'pbs':
utl.write_pbs_runjob(directory, 1, 16, '800mb', '6:00:00', binary)
submission_command = 'qsub runjob'
elif QUEUE_SYSTEM == 'slurm':
utl.write_slurm_runjob(directory, 16, '800mb', '6:00:00', binary)
submission_command = 'sbatch runjob'
if submit:
os.system(submission_command)
def setUp(self):
"""Loading structures before tests"""
#print "TestConnectivityMethods:setUp_"
print "Loading structures from file"
self.fe_structure = Structure.from_file('Fe.cif', True, True)
self.caf2_structure = Structure.from_file('CaF2.cif', True, True)
self.licoo2_structure = Structure.from_file('LiCoO2.cif', True, True)
print "Structures from file loaded"
def test_getinterpolatedposcar(self):
nimages = 5
this_image = 1
autosort_tol = 0.5
fw1 = Firework([CopyVaspOutputs(calc_dir=self.static_outdir,
contcar_to_poscar=False,
additional_files=["CONTCAR"]),
PassCalcLocs(name="fw1")], name="fw1")
fw2 = Firework([CopyVaspOutputs(calc_dir=self.opt_outdir,
contcar_to_poscar=False,
additional_files=["CONTCAR"]),
PassCalcLocs(name="fw2")], name="fw2")
fw3 = Firework([GetInterpolatedPOSCAR(start="fw1",
end="fw2",
this_image=this_image,
nimages=nimages,
autosort_tol=autosort_tol),
PassCalcLocs(name="fw3")],
name="fw3", parents=[fw1, fw2])
fw4 = Firework([PassCalcLocs(name="fw4")], name="fw4", parents=fw3)
wf = Workflow([fw1, fw2, fw3, fw4])
self.lp.add_wf(wf)
rapidfire(self.lp)
fw4 = self.lp.get_fw_by_id(self.lp.get_fw_ids({"name": "fw4"})[0])
calc_locs = fw4.spec["calc_locs"]
self.assertTrue(os.path.exists(get_calc_loc("fw3", calc_locs)["path"] +
"/POSCAR"))
self.assertTrue(os.path.exists(get_calc_loc("fw3", calc_locs)["path"] +
"/interpolate/CONTCAR_0"))
self.assertTrue(os.path.exists(get_calc_loc("fw3", calc_locs)["path"] +
"/interpolate/CONTCAR_1"))
struct_start = Structure.from_file(get_calc_loc("fw3", calc_locs)["path"] +
"/interpolate/CONTCAR_0")
struct_end = Structure.from_file(get_calc_loc("fw3", calc_locs)["path"] +
"/interpolate/CONTCAR_1")
struct_inter = Structure.from_file(get_calc_loc("fw3", calc_locs)["path"] +
"/POSCAR")
structs = struct_start.interpolate(struct_end,
nimages,
interpolate_lattices=True,
autosort_tol=autosort_tol)
# Check x of 1st site.
self.assertAlmostEqual(structs[this_image][1].coords[0],
struct_inter[1].coords[0])
# Check c lattice parameter
self.assertAlmostEqual(structs[this_image].lattice.abc[0],
struct_inter.lattice.abc[0])
def setUp(self):
self.cscl = self.get_structure("CsCl")
self.lifepo4 = self.get_structure("LiFePO4")
self.tei = Structure.from_file(get_path("icsd_TeI.cif"),
primitive=False)
self.LiCoO2 = Structure.from_file(get_path("icsd_LiCoO2.cif"),
primitive=False)
self.p1 = Structure(Lattice.from_parameters(3, 4, 5, 31, 43, 50),
["H", "He"], [[0, 0, 0], [0.1, 0.2, 0.3]])
def setUp(self):
"""Loading structures before tests"""
print "Loading structures from file"
self.fe_structure = Structure.from_file('Fe.cif', True, True)
self.caf2_structure = Structure.from_file('CaF2.cif', True, True)
self.licoo2_structure = Structure.from_file('LiCoO2.cif', True, True)
self.fe_finder = econ.EffectiveCoordFinder(self.fe_structure)
self.caf2_finder = econ.EffectiveCoordFinder(self.caf2_structure)
self.licoo2_finder = econ.EffectiveCoordFinder(self.licoo2_structure)
print "Structures from file loaded"
def setUp(self):
self.cscl = Structure.from_spacegroup(
"Pm-3m", Lattice.cubic(4.2), ["Cs", "Cl"], [[0, 0, 0], [0.5, 0.5, 0.5]])
self.lifepo4 = self.get_structure("LiFePO4")
self.tei = Structure.from_file(get_path("icsd_TeI.cif"),
primitive=False)
self.LiCoO2 = Structure.from_file(get_path("icsd_LiCoO2.cif"),
primitive=False)
self.p1 = Structure(Lattice.from_parameters(3, 4, 5, 31, 43, 50),
["H", "He"], [[0, 0, 0], [0.1, 0.2, 0.3]])
self.graphite = self.get_structure("Graphite")
def get_competing_phases():
"""
Collect the species to which the material might decompose to.
Returns:
A list of phases as tuples formatted as
[(formula_1, Materials_Project_ID_1),
(formula_2, Materials_Project_ID_2), ...]
"""
composition = Structure.from_file('POSCAR').composition
try:
energy = Vasprun('vasprun.xml').final_energy
except:
energy = 100 # The function can work without a vasprun.xml
entries = MPR.get_entries_in_chemsys([elt.symbol for elt in composition])
my_entry = ComputedEntry(composition, energy)
entries.append(my_entry)
#pda = PDAnalyzer(PhaseDiagram(entries))
pda = PhaseDiagram(entries)
decomp = pda.get_decomp_and_e_above_hull(my_entry, allow_negative=True)
competing_phases = [(entry.composition.reduced_formula, entry.entry_id)
for entry in decomp[0]]
return competing_phases
def test_substitute(self):
structure = Structure.from_file(os.path.join(os.path.dirname(__file__),
"..", "..", "..",
"test_files", "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 __init__(self, custom_interpreter=None, custom_test_structures=None):
p = os.path.join(module_dir, "..", "test_structures", "human_interpreter.yaml")
t = os.path.join(module_dir, "..", "test_structures")
interpreter = custom_interpreter if custom_interpreter else p
test_structures = custom_test_structures if custom_test_structures else t
with open(interpreter) as f:
hi = yaml.load(f)
for k in hi.keys():
hi[k].append(len(hi[k]))
if custom_test_structures:
find_structure = glob.glob(os.path.join(test_structures, k + "*"))
else:
find_structure = glob.glob(os.path.join(test_structures, "*", k+"*"))
if len(find_structure)==0:
continue
s = Structure.from_file(find_structure[0])
s.remove_oxidation_states()
hi[k].append(s)
super(HumanInterpreter, self).__init__(params=hi)
def test_rocksalt(self):
"""Testing coordination and connectivity matrix for rock salt structure NaCl"""
rocksalt_structure = Structure.from_file("test_structures/rocksalt.cif", True, True)
cn_finder = EffectiveCoordFinder(rocksalt_structure)
cns = cn_finder.get_avg_cn(radius=3.0, anions=["Cl"])
for cation in cns:
self.assertTrue(cation == "Na", "Na should be the only ions in rocksalt NaCl structure")
if cation == "Na":
self.assertEqual(round(cns[cation]), 6, "Na should be 6-fold coordinated")
central_species = ["Na"]
peripheral_species = ["Cl"]
connectivity_matrix, connectivity_polyhedra = get_connectivity_matrix(
rocksalt_structure, False, 3.0, peripheral_species, central_species
)
self.assertIn("Na", connectivity_matrix.keys(), "Na polyhedra not found in NaCl matrix")
self.assertEqual(connectivity_matrix["Na"]["Na"]["point"], 6, "Na should not be point-sharing")
self.assertEqual(connectivity_matrix["Na"]["Na"]["edge"], 12, "Na should be edge-sharing")
self.assertEqual(connectivity_matrix["Na"]["Na"]["face"], 0, "Na should not be face-sharing")
for poly in connectivity_polyhedra:
self.assertIsInstance(poly, Polyhedra, "List of polyhedra includes a non-polyhedra element")
def test_fluorite(self):
"""Testing coordination and connectivity matrix for fluorite structure CaF2"""
caf2_structure = Structure.from_file('test_structures/fluorite.cif', True, True)
cn_finder = EffectiveCoordFinder(caf2_structure)
cns = cn_finder.get_avg_CN(radius=2.6, anions=['F'])
for cation in cns:
self.assertEqual(cation, "Ca", "Ca should be the only ions in CaF2 fluorite")
if cation == 'Ca':
self.assertEqual(round(cns[cation]), 8, "Ca should be 8-fold coordinated")
central_species = ['Ca']
peripheral_species = ['F']
connectivity_matrix, connectivity_polyhedra = \
get_connectivity_matrix(caf2_structure, False, 2.6, peripheral_species, central_species)
self.assertIn('Ca', connectivity_matrix.keys(), "Ca polyhedra not found in CaF2 fluorite matrix")
self.assertEqual(connectivity_matrix['Ca']['Ca']['point'], 0, "Ca should not be point-sharing")
self.assertEqual(connectivity_matrix['Ca']['Ca']['edge'], 12, "Ca should be edge-sharing")
self.assertEqual(connectivity_matrix['Ca']['Ca']['face'], 0, "Ca should not be face-sharing")
for poly in connectivity_polyhedra:
self.assertIsInstance(poly, Polyhedra, "List of polyhedra includes a non-polyhedra element")
def test_kpath_generation(self):
triclinic = [1, 2]
monoclinic = range(3, 16)
orthorhombic = range(16, 75)
tetragonal = range(75, 143)
rhombohedral = range(143, 168)
hexagonal = range(168, 195)
cubic = range(195, 231)
species = ['K', 'La', 'Ti']
coords = [[.345, 5, .77298], [.1345, 5.1, .77298], [.7, .8, .9]]
for i in range(230):
sg_num = i + 1
if sg_num in triclinic:
lattice = Lattice([[3.0233057319441246,0,0], [0,7.9850357844548681,0], [0,0,8.1136762279561818]])
elif sg_num in monoclinic:
lattice = Lattice.monoclinic(2, 9, 1, 99)
elif sg_num in orthorhombic:
lattice = Lattice.orthorhombic(2, 9, 1)
elif sg_num in tetragonal:
lattice = Lattice.tetragonal(2, 9)
elif sg_num in rhombohedral:
lattice = Lattice.hexagonal(2, 95)
elif sg_num in hexagonal:
lattice = Lattice.hexagonal(2, 9)
elif sg_num in cubic:
lattice = Lattice.cubic(2)
struct = Structure.from_spacegroup(sg_num, lattice, species, coords)
kpath = HighSymmKpath(struct) #Throws error if something doesn't work, causing test to fail.
struct_file_path = os.path.join(test_dir_structs, 'ICSD_170.cif')
struct = Structure.from_file(struct_file_path)
hkp = HighSymmKpath(struct)
self.assertEqual(hkp.name, 'MCLC5')
def test_get_conversion_factor(self):
filepath = os.path.join(test_dir, 'LiFePO4.cif')
s = Structure.from_file(filepath)
# large tolerance because scipy constants changed between 0.16.1 and 0.17
self.assertAlmostEqual(41370704.343540139,
get_conversion_factor(s, "Li", 600),
delta=20)
def test_get_slabs(self):
gen = SlabGenerator(self.get_structure("CsCl"), [0, 0, 1], 10, 10)
#Test orthogonality of some internal variables.
a, b, c = gen.oriented_unit_cell.lattice.matrix
self.assertAlmostEqual(np.dot(a, gen._normal), 0)
self.assertAlmostEqual(np.dot(b, gen._normal), 0)
self.assertEqual(len(gen.get_slabs()), 1)
s = self.get_structure("LiFePO4")
gen = SlabGenerator(s, [0, 0, 1], 10, 10)
self.assertEqual(len(gen.get_slabs()), 5)
self.assertEqual(len(gen.get_slabs(bonds={("P", "O"): 3})), 2)
# There are no slabs in LFP that does not break either P-O or Fe-O
# bonds for a miller index of [0, 0, 1].
self.assertEqual(len(gen.get_slabs(
bonds={("P", "O"): 3, ("Fe", "O"): 3})), 0)
#If we allow some broken bonds, there are a few slabs.
self.assertEqual(len(gen.get_slabs(
bonds={("P", "O"): 3, ("Fe", "O"): 3},
max_broken_bonds=2)), 2)
# At this threshold, only the origin and center Li results in
# clustering. All other sites are non-clustered. So the of
# slabs is of sites in LiFePO4 unit cell - 2 + 1.
self.assertEqual(len(gen.get_slabs(tol=1e-4)), 15)
LiCoO2=Structure.from_file(get_path("icsd_LiCoO2.cif"),
primitive=False)
gen = SlabGenerator(LiCoO2, [0, 0, 1], 10, 10)
lco = gen.get_slabs(bonds={("Co", "O"): 3})
self.assertEqual(len(lco), 1)
a, b, c = gen.oriented_unit_cell.lattice.matrix
self.assertAlmostEqual(np.dot(a, gen._normal), 0)
self.assertAlmostEqual(np.dot(b, gen._normal), 0)
scc = Structure.from_spacegroup("Pm-3m", Lattice.cubic(3), ["Fe"],
[[0, 0, 0]])
gen = SlabGenerator(scc, [0, 0, 1], 10, 10)
slabs = gen.get_slabs()
self.assertEqual(len(slabs), 1)
gen = SlabGenerator(scc, [1, 1, 1], 10, 10, max_normal_search=1)
slabs = gen.get_slabs()
self.assertEqual(len(slabs), 1)
# Test whether using units of hkl planes instead of Angstroms for
# min_slab_size and min_vac_size will give us the same number of atoms
natoms = []
for a in [1, 1.4, 2.5, 3.6]:
s = Structure.from_spacegroup("Im-3m", Lattice.cubic(a), ["Fe"], [[0,0,0]])
slabgen = SlabGenerator(s, (1,1,1), 10, 10, in_unit_planes=True,
max_normal_search=2)
natoms.append(len(slabgen.get_slab()))
n = natoms[0]
for i in natoms:
self.assertEqual(n, i)
def setUp(self):
zno1 = Structure.from_file(get_path("ZnO-wz.cif"), primitive=False)
zno55 = SlabGenerator(zno1, [1, 0, 0], 5, 5, lll_reduce=False,
center_slab=False).get_slab()
Ti = Structure(Lattice.hexagonal(4.6, 2.82), ["Ti", "Ti", "Ti"],
[[0.000000, 0.000000, 0.000000],
[0.333333, 0.666667, 0.500000],
[0.666667, 0.333333, 0.500000]])
Ag_fcc = Structure(Lattice.cubic(4.06), ["Ag", "Ag", "Ag", "Ag"],
[[0.000000, 0.000000, 0.000000],
[0.000000, 0.500000, 0.500000],
[0.500000, 0.000000, 0.500000],
[0.500000, 0.500000, 0.000000]])
laue_groups = ["-1", "2/m", "mmm", "4/m",
"4/mmm", "-3", "-3m", "6/m",
"6/mmm", "m-3", "m-3m"]
self.ti = Ti
self.agfcc = Ag_fcc
self.zno1 = zno1
self.zno55 = zno55
self.h = Structure(Lattice.cubic(3), ["H"],
[[0, 0, 0]])
self.libcc = Structure(Lattice.cubic(3.51004), ["Li", "Li"],
[[0, 0, 0], [0.5, 0.5, 0.5]])
self.laue_groups = laue_groups
def asabistructure(obj):
"""
Convert obj into an AbiStructure object. Accepts:
- AbiStructure instance
- Subinstances of pymatgen.
- File paths
"""
if isinstance(obj, AbiStructure):
return obj
if isinstance(obj, Structure):
# Promote
return AbiStructure(obj)
if is_string(obj):
# Handle file paths.
if os.path.isfile(obj):
if obj.endswith(".nc"):
structure = structure_from_etsf_file(obj)
else:
structure = Structure.from_file(obj)
# Promote
return AbiStructure(structure)
raise ValueError("Don't know how to convert object %s to an AbiStructure structure" % str(obj))
def test_previous_reconstructions(self):
# Test to see if we generated all reconstruction
# types correctly and nothing changes
m = StructureMatcher()
for n in self.rec_archive.keys():
if "base_reconstruction" in self.rec_archive[n].keys():
arch = self.rec_archive[
self.rec_archive[n]["base_reconstruction"]]
sg = arch["spacegroup"]["symbol"]
else:
sg = self.rec_archive[n]["spacegroup"]["symbol"]
if sg == "Fm-3m":
rec = ReconstructionGenerator(self.Ni, 20, 20, n)
el = self.Ni[0].species_string
elif sg == "Im-3m":
rec = ReconstructionGenerator(self.Fe, 20, 20, n)
el = self.Fe[0].species_string
elif sg == "Fd-3m":
rec = ReconstructionGenerator(self.Si, 20, 20, n)
el = self.Si[0].species_string
slabs = rec.build_slabs()
s = Structure.from_file(get_path(os.path.join("reconstructions",
el + "_" + n + ".cif")))
self.assertTrue(any(
[len(m.group_structures([s, slab])) == 1 for slab in slabs]))
def test_sio2(self):
"""Testing coordination and connectivity matrix for SiO2 structure"""
sio2_structure = Structure.from_file("test_structures/SiO2.cif", True, True)
cn_finder = EffectiveCoordFinder(sio2_structure)
cns = cn_finder.get_avg_cn(radius=2.6, anions=["O"])
for cation in cns:
self.assertTrue(cation == "Si", "Si should be the only ions in SiO2 structure")
if cation == "Si":
self.assertEqual(round(cns[cation]), 4, "Si should be 6-fold coordinated")
central_species = ["Si"]
peripheral_species = ["O"]
connectivity_matrix, connectivity_polyhedra = get_connectivity_matrix(
sio2_structure, False, 2.6, peripheral_species, central_species
)
self.assertIn("Si", connectivity_matrix.keys(), "Si polyhedra not found in SiO2 matrix")
self.assertEqual(connectivity_matrix["Si"]["Si"]["point"], 4, "Si should not be point-sharing")
self.assertEqual(connectivity_matrix["Si"]["Si"]["edge"], 0, "Si should be edge-sharing")
self.assertEqual(connectivity_matrix["Si"]["Si"]["face"], 0, "Si should not be face-sharing")
for poly in connectivity_polyhedra:
self.assertIsInstance(poly, Polyhedra, "List of polyhedra includes a non-polyhedra element")
def get_convergence_data(jfile, params = ['ENCUT','KPOINTS']):
"""
returns data dict in the following format
{'Al':
{'ENCUT': [ [500,1.232], [600,0.8798] ],
'KPOINTS':[ [], [] ]
},
'W': ...
}
Note: processes only INCAR parmaters and KPOINTS
"""
cutoff_jobs = jobs_from_file(jfile)
data = {}
for j in cutoff_jobs:
jdir = os.path.join(j.parent_job_dir, j.job_dir)
poscar_file = os.path.join(jdir, 'POSCAR')
struct_m = Structure.from_file(poscar_file)
species = ''.join([tos.symbol for tos in struct_m.types_of_specie])
if data.get(species):
for p in params:
if j.vis.incar.get(p):
data[species][p].append( [ j.vis.incar[p],
j.final_energy/len(struct_m) ] )
elif p == 'KPOINTS':
data[species]['KPOINTS'].append( [ j.vis.kpoints.kpts,
j.final_energy/len(struct_m) ] )
else:
logger.warn('dont know how to parse the parameter {}'.format(p))
else:
data[species] = {}
for p in params:
data[species][p] = []
data[species][p] = []
return data
def test_corundum(self):
"""Testing coordination and connectivity matrix for corundum structure Cr2O3"""
corundum_structure = Structure.from_file('test_structures/corundum.cif', True, True)
cn_finder = EffectiveCoordFinder(corundum_structure)
cns = cn_finder.get_avg_CN(radius=2.6, anions=['O'])
for cation in cns:
self.assertTrue(cation == "Cr", "Cr should be the only ions in corundum Cr2O3")
if cation == 'Cr':
self.assertEqual(round(cns[cation]), 6, "Cr should be 6-fold coordinated")
central_species = ['Cr']
peripheral_species = ['O']
connectivity_matrix, connectivity_polyhedra = \
get_connectivity_matrix(corundum_structure, False, 2.6, peripheral_species, central_species)
self.assertIn('Cr', connectivity_matrix.keys(), "Cr polyhedra not found in corundum Cr2O3 matrix")
self.assertEqual(connectivity_matrix['Cr']['Cr']['point'], 9, "Cr should be point-sharing")
self.assertEqual(connectivity_matrix['Cr']['Cr']['edge'], 3, "Cr should be edge-sharing")
self.assertEqual(connectivity_matrix['Cr']['Cr']['face'], 1, "Cr should be face-sharing")
for poly in connectivity_polyhedra:
self.assertIsInstance(poly, Polyhedra, "List of polyhedra includes a non-polyhedra element")
def get_spacing(filename='POSCAR', cut=0.9):
"""
Returns the interlayer spacing for a 2D material.
Args:
filename (str): 'CONTCAR' or 'POSCAR', whichever file to
check.
cut (float): a fractional z-coordinate that must be within
the vacuum region.
Returns:
float. Spacing in Angstroms.
"""
structure = Structure.from_file('POSCAR')
lines = open(filename).readlines()
c_axis = lines[4].split()
lattice_parameter = lines[1].split()
split_coords = [line.split() for line in lines[8:8+structure.num_sites]]
z_coords = list()
for coord in split_coords:
z_coord = float(coord[2])
if z_coord > cut:
z_coord -= 1
z_coords.append(z_coord)
max_height = max([z_height for z_height in z_coords])
min_height = min([z_height for z_height in z_coords])
spacing = ((1.0 + min_height) - max_height) * abs(float(c_axis[2]))\
* float(lattice_parameter[0])
return spacing
def get_convergence_data(jfile):
"""
returns data dict in the following format
{'Al':
{'ENCUT': [ [500,1.232], [600,0.8798] ],
'KPOINTS':[ [], [] ]
},
'W': ...
}
Note: only ENCUT and KPOINTS
"""
cutoff_jobs = jobs_from_file(jfile)
data = {}
for j in cutoff_jobs:
jdir = os.path.join(j.parent_job_dir, j.job_dir)
poscar_file = os.path.join(jdir, 'POSCAR')
struct_m = Structure.from_file(poscar_file)
species = ''.join([tos.symbol for tos in struct_m.types_of_specie])
# energy / atom
if data.get(species):
data[species]['ENCUT'].append([j.vis.incar['ENCUT'],j.final_energy/len(struct_m)])
data[species]['KPOINTS'].append([j.vis.kpoints.kpts,j.final_energy/len(struct_m)])
else:
data[species] = {}
data[species]['ENCUT'] = []
data[species]['KPOINTS'] = []
return data
def get_hull_distance(competing_phase_directory='../competing_phases'):
"""
Calculate the material's distance to the thermodynamic hull,
based on species in the Materials Project database.
Args:
competing_phase_directory (str): absolute or relative path
to the location where your competing phases have been
relaxed. The default expectation is that they are stored
in a directory named 'competing_phases' at the same level
as your material's relaxation directory.
Returns:
float. distance (eV/atom) between the material and the
hull.
"""
finished_competitors = {}
original_directory = os.getcwd()
# Determine which competing phases have been relaxed in the current
# framework and store them in a dictionary ({formula: entry}).
if os.path.isdir(competing_phase_directory):
os.chdir(competing_phase_directory)
for comp_dir in [
dir for dir in os.listdir(os.getcwd()) if os.path.isdir(dir) and
is_converged(dir)
]:
vasprun = Vasprun('{}/vasprun.xml'.format(comp_dir))
composition = vasprun.final_structure.composition
energy = vasprun.final_energy
finished_competitors[comp_dir] = ComputedEntry(composition, energy)
os.chdir(original_directory)
else:
raise ValueError('Competing phase directory does not exist.')
composition = Structure.from_file('POSCAR').composition
try:
energy = Vasprun('vasprun.xml').final_energy
except:
raise ValueError('This directory does not have a converged vasprun.xml')
my_entry = ComputedEntry(composition, energy) # 2D material
entries = MPR.get_entries_in_chemsys(
[elt.symbol for elt in composition]
)
# If the energies of competing phases have been calculated in
# the current framework, put them in the phase diagram instead
# of the MP energies.
for i in range(len(entries)):
formula = entries[i].composition.reduced_formula
if formula in finished_competitors:
entries[i] = finished_competitors[formula]
else:
entries[i] = ComputedEntry(entries[i].composition, 100)
entries.append(my_entry) # 2D material
pda = PDAnalyzer(PhaseDiagram(entries))
decomp = pda.get_decomp_and_e_above_hull(my_entry, allow_negative=True)
return decomp[1]
def find_structure(self, filename_or_structure):
"""
Finds matching structures on the Materials Project site.
Args:
filename_or_structure: filename or Structure object
Returns:
A list of matching structures.
Raises:
MPRestError
"""
try:
if isinstance(filename_or_structure, string_types):
s = Structure.from_file(filename_or_structure)
elif isinstance(filename_or_structure, Structure):
s = filename_or_structure
else:
raise MPRestError("Provide filename or Structure object.")
payload = {'structure': json.dumps(s.as_dict(), cls=MontyEncoder)}
response = self.session.post(
'{}/find_structure'.format(self.preamble), data=payload
)
if response.status_code in [200, 400]:
resp = json.loads(response.text, cls=MontyDecoder)
if resp['valid_response']:
return resp['response']
else:
raise MPRestError(resp["error"])
raise MPRestError("REST error with status code {} and error {}"
.format(response.status_code, response.text))
except Exception as ex:
raise MPRestError(str(ex))
def plot_local_potential(axis=2, ylim=(-20, 0), fmt='pdf'):
"""
Plot data from the LOCPOT file along any of the 3 primary axes.
Useful for determining surface dipole moments and electric
potentials on the interior of the material.
Args:
axis (int): 0 = x, 1 = y, 2 = z
ylim (tuple): minimum and maximum potentials for the plot's y-axis.
fmt (str): matplotlib format style. Check the matplotlib docs
for options.
"""
ax = plt.figure(figsize=(16, 10)).gca()
locpot = Locpot.from_file('LOCPOT')
structure = Structure.from_file('CONTCAR')
vd = VolumetricData(structure, locpot.data)
abs_potentials = vd.get_average_along_axis(axis)
vacuum_level = max(abs_potentials)
vasprun = Vasprun('vasprun.xml')
bs = vasprun.get_band_structure()
if not bs.is_metal():
cbm = bs.get_cbm()['energy'] - vacuum_level
vbm = bs.get_vbm()['energy'] - vacuum_level
potentials = [potential - vacuum_level for potential in abs_potentials]
axis_length = structure.lattice._lengths[axis]
positions = np.arange(0, axis_length, axis_length / len(potentials))
ax.plot(positions, potentials, linewidth=2, color='k')
ax.set_xlim(0, axis_length)
ax.set_ylim(ylim[0], ylim[1])
ax.set_xticklabels(
[r'$\mathrm{%s}$' % tick for tick in ax.get_xticks()], size=20)
ax.set_yticklabels(
[r'$\mathrm{%s}$' % tick for tick in ax.get_yticks()], size=20)
ax.set_xlabel(r'$\mathrm{\AA}$', size=24)
ax.set_ylabel(r'$\mathrm{V\/(eV)}$', size=24)
if not bs.is_metal():
ax.text(ax.get_xlim()[1], cbm, r'$\mathrm{CBM}$',
horizontalalignment='right', verticalalignment='bottom',
size=20)
ax.text(ax.get_xlim()[1], vbm, r'$\mathrm{VBM}$',
horizontalalignment='right', verticalalignment='top', size=20)
ax.fill_between(ax.get_xlim(), cbm, ax.get_ylim()[1],
facecolor=plt.cm.jet(0.3), zorder=0, linewidth=0)
ax.fill_between(ax.get_xlim(), ax.get_ylim()[0], vbm,
facecolor=plt.cm.jet(0.7), zorder=0, linewidth=0)
if fmt == "None":
return ax
else:
plt.savefig('locpot.{}'.format(fmt))
plt.close()
def setUp(self):
# This is a CHGCAR_sum file with reduced grid size
chgcar_path = os.path.join(test_dir, "CHGCAR.FePO4")
chg_FePO4 = Chgcar.from_file(chgcar_path)
self.chgcar_path = chgcar_path
self.chg_FePO4 = chg_FePO4
self.ca_FePO4 = ChargeDensityAnalyzer(chg_FePO4)
self.s_LiFePO4 = Structure.from_file(os.path.join(test_dir, "LiFePO4.cif"))
def test_calculate_vol(self):
s = Structure.from_file(os.path.join(test_dir, "LiFePO4.cif"))
a = TopographyAnalyzer(s, framework_ions=["O"],
cations=["P", "Fe"], check_volume=False)
coords = [s[i].coords for i in [20, 23, 25, 17, 24, 19]]
vol = calculate_vol(coords=coords)
vol_expected = 12.8884 # LiO6 volume calculated by VESTA
self.assertAlmostEqual(vol, vol_expected, 4)
def test_get_orthogonal_c_slab(self):
TeI = Structure.from_file(get_path("icsd_TeI.cif"),
primitive=False)
trclnc_TeI = SlabGenerator(TeI, (0, 0, 1), 10, 10)
TeI_slabs = trclnc_TeI.get_slabs()
slab = TeI_slabs[0]
norm_slab = slab.get_orthogonal_c_slab()
self.assertAlmostEqual(norm_slab.lattice.angles[0], 90)
self.assertAlmostEqual(norm_slab.lattice.angles[1], 90)
def callback_update_structure(contents, filename, last_modified):
if not contents:
raise PreventUpdate
# assume we only want the first input for now
content_type, content_string = contents.split(",")
decoded_contents = b64decode(content_string)
error = None
struct_or_mol = None
# necessary to write to file so pymatgen's filetype detection can work
with NamedTemporaryFile(suffix=filename) as tmp:
tmp.write(decoded_contents)
tmp.flush()
try:
struct_or_mol = Structure.from_file(tmp.name)
except:
try:
struct_or_mol = Molecule.from_file(tmp.name)
except:
try:
struct_or_mol = Chgcar.from_file(tmp.name)
except:
# TODO: fix these horrible try/excepts, loadfn may be dangerous
try:
struct_or_mol = loadfn(tmp.name)
except:
error = (
"Could not parse uploaded file. "
"If this seems like a bug, please report it. "
"Crystal Toolkit understands all crystal "
"structure file types and molecule file types "
"supported by pymatgen.")
return {"data": struct_or_mol, "error": error}
def __getitem__(self, idx):
cif_id, target = self.id_prop_data[idx]
crystal = Structure.from_file(
os.path.join(self.root_dir, cif_id + ".cif"))
atom_fea = np.vstack([
self.ari.get_atom_fea(crystal[i].specie.number)
for i in range(len(crystal))
])
atom_fea = torch.Tensor(atom_fea)
all_nbrs = crystal.get_all_neighbors(self.radius, include_index=True)
all_nbrs = [sorted(nbrs, key=lambda x: x[1]) for nbrs in all_nbrs]
nbr_fea_idx, nbr_fea = [], []
for nbr in all_nbrs:
if len(nbr) < self.max_num_nbr:
warnings.warn("{} not find enough neighbors to build graph. "
"If it happens frequently, consider increase "
"radius.".format(cif_id))
nbr_fea_idx.append(
list(map(lambda x: x[2], nbr)) + [0] *
(self.max_num_nbr - len(nbr)))
nbr_fea.append(
list(map(lambda x: x[1], nbr)) + [self.radius + 1.0] *
(self.max_num_nbr - len(nbr)))
if self.store_bad_indices:
self.bad_indices.add(idx)
else:
nbr_fea_idx.append(
list(map(lambda x: x[2], nbr[:self.max_num_nbr])))
nbr_fea.append(
list(map(lambda x: x[1], nbr[:self.max_num_nbr])))
nbr_fea_idx, nbr_fea = np.array(nbr_fea_idx), np.array(nbr_fea)
nbr_fea = self.gdf.expand(nbr_fea)
atom_fea = torch.Tensor(atom_fea)
nbr_fea = torch.Tensor(nbr_fea)
nbr_fea_idx = torch.LongTensor(nbr_fea_idx)
target = torch.Tensor([float(target)])
return (atom_fea, nbr_fea, nbr_fea_idx), target, cif_id
def def_energy(vac=[]):
"""
Calculation of vacancy formation energies
Args:
vac: list of Poscar vacancy structure objects
Returns:
def_list: list of defect energies
def_header_list: list of defect names
"""
def_list=[]
header_list=[]
fi=str('DEF.INFO')
f=open(fi,'w')
for v in vac:
enp,contc=smart_converge(mat=v)
#enp,contc=run_job(mat=v,incar=incar,kpoints=kpoints,jobname=str(v.comment))
strt=Structure.from_file(contc)
comm=str(v.comment)
print ("running def_energy for =",comm)
header_list.append(comm)
if comm.split('@')[0]=='bulk':
gs_energy=float(enp)*float(strt.composition.num_atoms)
print ("in def_energy gs_energy for",comm, gs_energy)
else:
chem_pot=sum_chem_pot(strt)
if comm.startswith("intl"):
chem_pot=0.0-float(chem_pot)
def_en=(float(enp)*float(strt.composition.num_atoms))-float(gs_energy)+chem_pot
print ("in def_energy def_en for",comm, def_en,"chem_pot",chem_pot)
def_list.append(def_en)
print (v.comment,'=',def_en)
line= str(v.comment)+str('=')+str(def_en)+'\n'
f.write(line)
f.close()
return def_list,header_list
def __getitem__(self, idx):
data_row = self.id_prop_data[idx]
cif_id = str(int(float(data_row.pop(0))))
# At this point we have a list of strings each with some decimal value of a property or None.
# To represent None in float datatype while converting we use float("inf")
targets = [float(x) if x else float("inf") for x in data_row]
crystal = Structure.from_file(os.path.join(self.root_dir,
cif_id+'.cif'))
atom_fea = np.vstack([self.ari.get_atom_fea(crystal[i].specie.number)
for i in range(len(crystal))])
atom_fea = torch.Tensor(atom_fea)
all_nbrs = crystal.get_all_neighbors(self.radius, include_index=True)
all_nbrs = [sorted(nbrs, key=lambda x: x[1]) for nbrs in all_nbrs]
nbr_fea_idx, nbr_fea = [], []
for nbr in all_nbrs:
if len(nbr) < self.max_num_nbr:
warnings.warn('{} not find enough neighbors to build graph. '
'If it happens frequently, consider increase '
'radius.'.format(cif_id))
nbr_fea_idx.append(list(map(lambda x: x[2], nbr)) +
[0] * (self.max_num_nbr - len(nbr)))
nbr_fea.append(list(map(lambda x: x[1], nbr)) +
[self.radius + 1.] * (self.max_num_nbr -
len(nbr)))
else:
nbr_fea_idx.append(list(map(lambda x: x[2],
nbr[:self.max_num_nbr])))
nbr_fea.append(list(map(lambda x: x[1],
nbr[:self.max_num_nbr])))
nbr_fea_idx, nbr_fea = np.array(nbr_fea_idx), np.array(nbr_fea)
nbr_fea = self.gdf.expand(nbr_fea)
atom_fea = torch.Tensor(atom_fea)
nbr_fea = torch.Tensor(nbr_fea)
nbr_fea_idx = torch.LongTensor(nbr_fea_idx)
targets = torch.Tensor(targets)
return (atom_fea, nbr_fea, nbr_fea_idx), targets, cif_id
def get_convergence_data(jfile, params=['ENCUT', 'KPOINTS']):
"""
returns data dict in the following format
{'Al':
{'ENCUT': [ [500,1.232], [600,0.8798] ],
'KPOINTS':[ [], [] ]
},
'W': ...
}
Note: processes only INCAR parmaters and KPOINTS
"""
cutoff_jobs = jobs_from_file(jfile)
data = {}
for j in cutoff_jobs:
jdir = os.path.join(j.parent_job_dir, j.job_dir)
poscar_file = os.path.join(jdir, 'POSCAR')
struct_m = Structure.from_file(poscar_file)
species = ''.join([tos.symbol for tos in struct_m.types_of_specie])
if data.get(species):
for p in params:
if j.vis.incar.get(p):
data[species][p].append(
[j.vis.incar[p], j.final_energy / len(struct_m)])
elif p == 'KPOINTS':
data[species]['KPOINTS'].append(
[j.vis.kpoints.kpts, j.final_energy / len(struct_m)])
else:
logger.warn(
'dont know how to parse the parameter {}'.format(p))
else:
data[species] = {}
for p in params:
data[species][p] = []
data[species][p] = []
return data
def setUp(self):
zno1 = Structure.from_file(get_path("ZnO-wz.cif"), primitive=False)
zno55 = SlabGenerator(zno1, [1, 0, 0], 5, 5, lll_reduce=False,
center_slab=False).get_slab()
Ti = Structure(Lattice.hexagonal(4.6, 2.82), ["Ti", "Ti", "Ti"],
[[0.000000, 0.000000, 0.000000],
[0.333333, 0.666667, 0.500000],
[0.666667, 0.333333, 0.500000]])
Ag_fcc = Structure(Lattice.cubic(4.06), ["Ag", "Ag", "Ag", "Ag"],
[[0.000000, 0.000000, 0.000000],
[0.000000, 0.500000, 0.500000],
[0.500000, 0.000000, 0.500000],
[0.500000, 0.500000, 0.000000]])
self.ti = Ti
self.agfcc = Ag_fcc
self.zno1 = zno1
self.zno55 = zno55
self.h = Structure(Lattice.cubic(3), ["H"],
[[0, 0, 0]])
self.libcc = Structure(Lattice.cubic(3.51004), ["Li", "Li"],
[[0, 0, 0], [0.5, 0.5, 0.5]])
def write_INCAR(
self,
incar_input: str = "INCAR",
incar_output: str = "INCAR.lobster",
poscar_input: str = "POSCAR",
isym: int = -1,
further_settings: dict = None,
):
"""
Will only make the run static, insert nbands, make ISYM=-1, set LWAVE=True and write a new INCAR.
You have to check for the rest.
Args:
incar_input (str): path to input INCAR
incar_output (str): path to output INCAR
poscar_input (str): path to input POSCAR
isym (int): isym equal to -1 or 0 are possible. Current Lobster version only allow -1.
further_settings (dict): A dict can be used to include further settings, e.g. {"ISMEAR":-5}
"""
# reads old incar from file, this one will be modified
incar = Incar.from_file(incar_input)
warnings.warn("Please check your incar_input before using it. This method only changes three settings!")
if isym == -1:
incar["ISYM"] = -1
elif isym == 0:
incar["ISYM"] = 0
else:
ValueError("isym has to be -1 or 0.")
incar["NSW"] = 0
incar["LWAVE"] = True
# get nbands from _get_nbands (use basis set that is inserted)
incar["NBANDS"] = self._get_nbands(Structure.from_file(poscar_input))
if further_settings is not None:
for key, item in further_settings.items():
incar[key] = further_settings[key]
# print it to file
incar.write_file(incar_output)
def test_znucl_typat(self):
"""Test the order of typat and znucl in the Abinit input and enforce_typat, enforce_znucl."""
# Ga Ga1 1 0.33333333333333 0.666666666666667 0.500880 1.0
# Ga Ga2 1 0.66666666666667 0.333333333333333 0.000880 1.0
# N N3 1 0.333333333333333 0.666666666666667 0.124120 1.0
# N N4 1 0.666666666666667 0.333333333333333 0.624120 1.0
gan = Structure.from_file(
os.path.join(PymatgenTest.TEST_FILES_DIR, "abinit", "gan.cif"))
# By default, znucl is filled using the first new type found in sites.
def_vars = structure_to_abivars(gan)
def_znucl = def_vars["znucl"]
self.assertArrayEqual(def_znucl, [31, 7])
def_typat = def_vars["typat"]
self.assertArrayEqual(def_typat, [1, 1, 2, 2])
# But it's possible to enforce a particular value of typat and znucl.
enforce_znucl = [7, 31]
enforce_typat = [2, 2, 1, 1]
enf_vars = structure_to_abivars(gan,
enforce_znucl=enforce_znucl,
enforce_typat=enforce_typat)
self.assertArrayEqual(enf_vars["znucl"], enforce_znucl)
self.assertArrayEqual(enf_vars["typat"], enforce_typat)
self.assertArrayEqual(def_vars["xred"], enf_vars["xred"])
assert [s.symbol for s in species_by_znucl(gan)] == ["Ga", "N"]
for itype1, itype2 in zip(def_typat, enforce_typat):
assert def_znucl[itype1 - 1] == enforce_znucl[itype2 - 1]
with self.assertRaises(Exception):
structure_to_abivars(gan,
enforce_znucl=enforce_znucl,
enforce_typat=None)
def surf_energy(surf=[]):
"""
Helper function for surface energies
Args:
surf: list of Poscar surface objects
Returns:
surf_list: list of surface energies
surf_header_list: list of surface names
"""
surf_list = []
surf_header_list = []
fi = str('SURF.INFO')
f = open(fi, 'w')
for s in surf:
enp, contc = smart_converge(mat=s)
strt = Structure.from_file(contc)
m = strt.lattice.matrix
if s.comment.split('@')[0] == 'sbulk':
gs_energy = enp
print("in surf_energy gs_energy for", s.comment, gs_energy)
else:
surf_en = 16 * (
float(enp) * (strt.composition.num_atoms) -
float(strt.composition.num_atoms) * float(gs_energy)) / (
2 * np.linalg.norm(np.cross(m[0], m[1])))
print("in surf_energy surf_en for", s.comment, surf_en)
surf_list.append(surf_en)
print(s.comment, '=', surf_en)
line = str(s.comment) + str('=') + str(surf_en) + '\n'
f.write(line)
f.close()
return surf_list, surf_header_list
def run_task(self, fw_spec):
potcar_spec = self.get("potcar_spec", False)
vasp_input_set_params = self.get("vasp_input_set_params") or {}
# update the bandgap based on output from the previous calculation,
# unless the user specified a bandgap via vasp_input_set_params
if vasp_input_set_params.get("bandgap") is None:
# First look for the gga_bandgap key in the FW spec, to save parsing time
if fw_spec.get("gga_bandgap") is not None:
vasp_input_set_params["bandgap"] = fw_spec.get("gga_bandgap")
# If not found, parse the files from the previous calc to find the bandgap
else:
parse_potcar_file = not potcar_spec
vasprun = Vasprun("vasprun.xml", parse_potcar_file=parse_potcar_file)
bandgap = vasprun.eigenvalue_band_properties[0]
vasp_input_set_params["bandgap"] = bandgap
# read the structure from the output of the previous calculation
structure = Structure.from_file("POSCAR")
vis = MPScanRelaxSet(structure, **vasp_input_set_params)
vis.write_input(".", potcar_spec=potcar_spec)
def compare_structures(args):
"""
Compare structures in files for similarity using structure matcher.
Args:
args (dict): Args from argparse.
"""
filenames = args.filenames
if len(filenames) < 2:
print("You need more than one structure to compare!")
sys.exit(-1)
try:
structures = [Structure.from_file(fn) for fn in filenames]
except Exception as ex:
print("Error converting file. Are they in the right format?")
print(str(ex))
sys.exit(-1)
m = StructureMatcher() if args.group == "species" else StructureMatcher(comparator=ElementComparator())
for i, grp in enumerate(m.group_structures(structures)):
print(f"Group {i}: ")
for s in grp:
print(f"- {filenames[structures.index(s)]} ({s.formula})")
print()
def get_structures_from_paths(paths_list):
structures = []
for path in paths_list:
try:
poscar_path = os.path.join(path, 'POSCAR.orig')
incar_path = os.path.join(path, 'INCAR.orig')
try:
incar = Incar.from_file(incar_path)
magmoms = incar.get('MAGMOM')
undecorated_structure = Structure.from_file(poscar_path)
structure = Structure(lattice=undecorated_structure.lattice,
species=undecorated_structure.species,
coords=undecorated_structure.frac_coords,
site_properties={'magmom': magmoms})
structures.append(structure)
except:
print('%s does not have a MAGMOM tag' % incar_path)
except:
print('%s does not contain a valid POSCAR or INCAR' % path)
return structures
def test_timeout(self):
s = Structure.from_file(filename=os.path.join(PymatgenTest.TEST_FILES_DIR, "garnet.cif"))
a = SpacegroupAnalyzer(s, 0.1)
s["Al3+"] = {"Al3+": 0.5, "Ga3+": 0.5}
adaptor = EnumlibAdaptor(s, 1, 1, enum_precision_parameter=0.01, timeout=0.0000000000001)
self.assertRaises(TimeoutError, adaptor._run_multienum)
# putting the atom at a halfway distance between other atoms
link = {'0': {}, '1': {}, '2': {'0': [6, 2, -1]}}
# list of indices of atoms to be removed from each molecule
remove = [[7], [7], []]
# combined_mol = combine_mols(mols, cm_dist, angle, link=link, remove=remove)
lead_acetate = Ligand(mols, cm_dist, angle=angle, link={}, remove=remove)
lead_acetate.create_ligand()
lead_acetate.to('xyz', 'lead_acetate.xyz')
# put the ligand in a box
boxed_lead_acetate = lead_acetate.get_boxed_structure(13, 13, 13)
boxed_lead_acetate.to(fmt="poscar", filename="POSCAR_diacetate_boxed.vasp")
# bulk PbS
strt_pbs = Structure.from_file(
os.path.join(PACKAGE_PATH, "test_files", "POSCAR_PbS"))
# 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 = 21
# minimum vacuum thickness in Angstroms
# the maximum distance in the lignad will be added to this value
min_vac = 10
def vac_antisite_def_struct_gen(mpid, mapi_key, cellmax, struct_file=None):
if not mpid and not struct_file:
print ("============\nERROR: Provide an mpid\n============")
return
# Get primitive structure from the Materials Project DB
if not struct_file:
if not mapi_key:
with MPRester() as mp:
struct = mp.get_structure_by_material_id(mpid)
else:
with MPRester(mapi_key) as mp:
struct = mp.get_structure_by_material_id(mpid)
else:
struct = Structure.from_file(struct_file)
sga = SpacegroupAnalyzer(struct)
prim_struct = sga.find_primitive()
#prim_struct_sites = len(prim_struct.sites)
#conv_struct = sga.get_conventional_standard_structure()
#conv_struct_sites = len(conv_struct.sites)
#conv_prim_ratio = int(conv_struct_sites / prim_struct_sites)
# Default VASP settings
def_vasp_incar_param = {'ISIF':2, 'EDIFF':1e-6, 'EDIFFG':0.001,}
kpoint_den = 15000
# Create bulk structure and associated VASP files
sc_scale = get_sc_scale(inp_struct=prim_struct, final_site_no=cellmax)
blk_sc = prim_struct.copy()
blk_sc.make_supercell(scaling_matrix=sc_scale)
site_no = blk_sc.num_sites
# Rescale if needed
while site_no > cellmax:
max_sc_dim = max(sc_scale)
i = sc_scale.index(max_sc_dim)
sc_scale[i] -= 1
blk_sc = prim_struct.copy()
blk_sc.make_supercell(scaling_matrix=sc_scale)
site_no = blk_sc.num_sites
blk_str_sites = set(blk_sc.sites)
custom_kpoints = Kpoints.automatic_density(blk_sc, kppa=kpoint_den)
mpvis = MPMetalRelaxSet(blk_sc, user_incar_settings=def_vasp_incar_param,
user_kpoints_settings=custom_kpoints)
if mpid:
root_fldr = mpid
else:
root_fldr = struct.composition.reduced_formula
fin_dir = os.path.join(root_fldr, 'bulk')
mpvis.write_input(fin_dir)
if not mpid: # write the input structure if mpid is not used
struct.to(fmt='poscar', filename=os.path.join(fin_dir, 'POSCAR.uc'))
# Create each defect structure and associated VASP files
# First find all unique defect sites
periodic_struct = sga.get_symmetrized_structure()
unique_sites = list(set([periodic_struct.find_equivalent_sites(site)[0] \
for site in periodic_struct.sites]))
temp_struct = Structure.from_sites(sorted(unique_sites))
prim_struct2 = SpacegroupAnalyzer(temp_struct).find_primitive()
prim_struct2.lattice = prim_struct.lattice # a little hacky
for i, site in enumerate(prim_struct2.sites):
vac = Vacancy(structure=prim_struct, defect_site=site)
vac_sc = vac.generate_defect_structure(supercell=sc_scale)
# Get vacancy site information
vac_str_sites = set(vac_sc.sites)
vac_sites = blk_str_sites - vac_str_sites
vac_site = next(iter(vac_sites))
site_mult = vac.get_multiplicity()
vac_site_specie = vac_site.specie
vac_symbol = vac_site_specie.symbol
custom_kpoints = Kpoints.automatic_density(vac_sc, kppa=kpoint_den)
mpvis = MPMetalRelaxSet(vac_sc,
user_incar_settings=def_vasp_incar_param,
user_kpoints_settings=custom_kpoints)
vac_dir = 'vacancy_{}_mult-{}_sitespecie-{}'.format(
str(i+1), site_mult, vac_symbol)
fin_dir = os.path.join(root_fldr, vac_dir)
mpvis.write_input(fin_dir)
# Antisites generation at the vacancy site
struct_species = blk_sc.species
for specie in set(struct_species) - set([vac_site_specie]):
specie_symbol = specie.symbol
anti_sc = vac_sc.copy()
anti_sc.append(specie, vac_site.frac_coords)
mpvis = MPMetalRelaxSet(anti_sc,
user_incar_settings=def_vasp_incar_param,
user_kpoints_settings=custom_kpoints)
anti_dir = 'antisite_{}_mult-{}_sitespecie-{}_subspecie-{}'.format(
str(i+1), site_mult, vac_symbol, specie_symbol)
fin_dir = os.path.join(root_fldr, anti_dir)
mpvis.write_input(fin_dir)
def setUp(self):
feo4 = Structure.from_file(os.path.join(test_dir, "LiFePO4.cif"))
feo4.remove_species(["Li"])
feo4.remove_oxidation_states()
self.feo4 = feo4
def make_deepmd_lammps (jdata, conf_dir) :
deepmd_model_dir = jdata['deepmd_model_dir']
deepmd_type_map = jdata['deepmd_type_map']
ntypes = len(deepmd_type_map)
deepmd_model_dir = os.path.abspath(deepmd_model_dir)
deepmd_models = glob.glob(os.path.join(deepmd_model_dir, '*pb'))
deepmd_models_name = [os.path.basename(ii) for ii in deepmd_models]
vol_start = jdata['vol_start']
vol_end = jdata['vol_end']
vol_step = jdata['vol_step']
# # get equi props
# equi_path = re.sub('confs', global_equi_name, conf_path)
# equi_path = os.path.join(equi_path, 'lmp')
# equi_log = os.path.join(equi_path, 'log.lammps')
# if not os.path.isfile(equi_log) :
# raise RuntimeError("the system should be equilibriated first")
# natoms, epa, vpa = lammps.get_nev(equi_log)
# task path
task_path = re.sub('confs', global_task_name, conf_dir)
task_path = os.path.abspath(task_path)
os.makedirs(task_path, exist_ok = True)
cwd = os.getcwd()
conf_path = os.path.abspath(conf_dir)
from_poscar = os.path.join(conf_path, 'POSCAR')
to_poscar = os.path.join(task_path, 'POSCAR')
if os.path.exists(to_poscar) :
assert(filecmp.cmp(from_poscar, to_poscar))
else :
os.chdir(task_path)
os.symlink(os.path.relpath(from_poscar), 'POSCAR')
os.chdir(cwd)
volume = vasp.poscar_vol(to_poscar)
natoms = vasp.poscar_natoms(to_poscar)
vpa = volume / natoms
# structrure
ss = Structure.from_file(to_poscar)
# lmp path
lmp_path = os.path.join(task_path, 'deepmd')
os.makedirs(lmp_path, exist_ok = True)
# # lmp conf
# conf_file = os.path.join(lmp_path, 'conf.lmp')
# lammps.cvt_lammps_conf(to_poscar, conf_file)
# ptypes = vasp.get_poscar_types(to_poscar)
# lammps.apply_type_map(conf_file, deepmd_type_map, ptypes)
os.chdir(lmp_path)
for ii in deepmd_models_name :
if os.path.exists(ii) :
os.remove(ii)
for (ii,jj) in zip(deepmd_models, deepmd_models_name) :
os.symlink(os.path.relpath(ii), jj)
share_models = glob.glob(os.path.join(lmp_path, '*pb'))
for vol in np.arange(vol_start, vol_end, vol_step) :
vol_path = os.path.join(lmp_path, 'vol-%.2f' % vol)
print('# generate %s' % (vol_path))
os.makedirs(vol_path, exist_ok = True)
os.chdir(vol_path)
#print(vol_path)
for ii in ['conf.lmp', 'conf.lmp'] + deepmd_models_name :
if os.path.exists(ii) :
os.remove(ii)
# # link conf
# os.symlink(os.path.relpath(conf_file), 'conf.lmp')
# make conf
scale_ss = ss.copy()
scale_ss.scale_lattice(vol * natoms)
scale_ss.to('POSCAR', 'POSCAR')
lammps.cvt_lammps_conf('POSCAR', 'conf.lmp')
ptypes = vasp.get_poscar_types('POSCAR')
lammps.apply_type_map('conf.lmp', deepmd_type_map, ptypes)
# link models
for (ii,jj) in zip(share_models, deepmd_models_name) :
os.symlink(os.path.relpath(ii), jj)
# make lammps input
scale = (vol / vpa) ** (1./3.)
fc = lammps.make_lammps_press_relax('conf.lmp', ntypes, scale,lammps.inter_deepmd, deepmd_models_name)
with open(os.path.join(vol_path, 'lammps.in'), 'w') as fp :
fp.write(fc)
os.chdir(cwd)
def make_meam_lammps_fixv (jdata, conf_dir) :
meam_potfile_dir = jdata['meam_potfile_dir']
meam_potfile_dir = os.path.abspath(meam_potfile_dir)
meam_potfile = jdata['meam_potfile']
meam_potfile = [os.path.join(meam_potfile_dir,ii) for ii in meam_potfile]
meam_potfile_name = jdata['meam_potfile']
type_map = jdata['meam_type_map']
ntypes = len(type_map)
meam_param = {'meam_potfile' : jdata['meam_potfile'],
'meam_type': jdata['meam_param_type']}
vol_start = jdata['vol_start']
vol_end = jdata['vol_end']
vol_step = jdata['vol_step']
# get equi props
equi_path = re.sub('confs', global_equi_name, conf_dir)
task_path = re.sub('confs', global_task_name, conf_dir)
equi_path = os.path.join(equi_path, 'meam')
task_path = os.path.join(task_path, 'meam')
equi_path = os.path.abspath(equi_path)
task_path = os.path.abspath(task_path)
equi_log = os.path.join(equi_path, 'log.lammps')
equi_dump = os.path.join(equi_path, 'dump.relax')
os.makedirs(task_path, exist_ok = True)
task_poscar = os.path.join(task_path, 'POSCAR')
lammps.poscar_from_last_dump(equi_dump, task_poscar, type_map)
cwd = os.getcwd()
volume = vasp.poscar_vol(task_poscar)
natoms = vasp.poscar_natoms(task_poscar)
vpa = volume / natoms
# structrure
ss = Structure.from_file(task_poscar)
# make lammps.in
fc = lammps.make_lammps_equi('conf.lmp',
ntypes,
lammps.inter_meam,
meam_param,
change_box = False)
f_lammps_in = os.path.join(task_path, 'lammps.in')
with open(f_lammps_in, 'w') as fp :
fp.write(fc)
# make vols
for vol in np.arange(vol_start, vol_end, vol_step) :
vol_path = os.path.join(task_path, 'vol-%.2f' % vol)
print('# generate %s' % (vol_path))
os.makedirs(vol_path, exist_ok = True)
os.chdir(vol_path)
for ii in ['conf.lmp', 'conf.lmp', 'lammps.in'] + meam_potfile_name :
if os.path.exists(ii) :
os.remove(ii)
# make conf
scale_ss = ss.copy()
scale_ss.scale_lattice(vol * natoms)
scale_ss.to('POSCAR', 'POSCAR')
lammps.cvt_lammps_conf('POSCAR', 'conf.lmp')
ptypes = vasp.get_poscar_types('POSCAR')
lammps.apply_type_map('conf.lmp', type_map, ptypes)
# link lammps.in
os.symlink(os.path.relpath(f_lammps_in), 'lammps.in')
# link models
for (ii,jj) in zip(meam_potfile, meam_potfile_name) :
os.symlink(os.path.relpath(ii), jj)
# make lammps input
os.chdir(cwd)
import unittest
import os
from pymatgen.analysis.ferroelectricity.polarization import *
from pymatgen.core.structure import Structure
from pymatgen.io.vasp.outputs import Outcar
from pymatgen.io.vasp.inputs import Potcar
from pymatgen.util.testing import PymatgenTest
test_dir = os.path.join(os.path.dirname(__file__), "..", "..", "..", "..",
'test_files/BTO_221_99_polarization')
bto_folders = ['nonpolar_polarization']
bto_folders += ['interpolation_{}_polarization'.format(str(i)) for i in range(1,9)][::-1]
bto_folders += ['polar_polarization']
structures = [Structure.from_file(test_dir+"/"+folder+"/POSCAR") for folder in bto_folders]
ions = np.matrix([[-44.363484, -44.363484, -44.79259988],
[-44.324764, -44.324764, -69.43452043],
[-44.286055, -44.286055, -69.8792077 ],
[-44.247335, -44.247335, -70.32475473],
[-44.208626, -44.208626, -70.77139856],
[-44.169906, -44.169906, -71.21889307],
[-44.131197, -44.131197, -71.66746921],
[-44.092477, -44.092477, -72.1168782 ],
[-44.053768, -44.053768, -72.56736141],
[-44.015048, -44.015048, -73.01874336]])
class UtilsTest(PymatgenTest):
def setUp(self):
def test_get_conventional_standard_structure(self):
parser = CifParser(
os.path.join(PymatgenTest.TEST_FILES_DIR, "bcc_1927.cif"))
structure = parser.get_structures(False)[0]
s = SpacegroupAnalyzer(structure, symprec=1e-2)
conv = s.get_conventional_standard_structure()
self.assertAlmostEqual(conv.lattice.alpha, 90)
self.assertAlmostEqual(conv.lattice.beta, 90)
self.assertAlmostEqual(conv.lattice.gamma, 90)
self.assertAlmostEqual(conv.lattice.a, 9.1980270633769461)
self.assertAlmostEqual(conv.lattice.b, 9.1980270633769461)
self.assertAlmostEqual(conv.lattice.c, 9.1980270633769461)
parser = CifParser(
os.path.join(PymatgenTest.TEST_FILES_DIR, "btet_1915.cif"))
structure = parser.get_structures(False)[0]
s = SpacegroupAnalyzer(structure, symprec=1e-2)
conv = s.get_conventional_standard_structure()
self.assertAlmostEqual(conv.lattice.alpha, 90)
self.assertAlmostEqual(conv.lattice.beta, 90)
self.assertAlmostEqual(conv.lattice.gamma, 90)
self.assertAlmostEqual(conv.lattice.a, 5.0615106678044235)
self.assertAlmostEqual(conv.lattice.b, 5.0615106678044235)
self.assertAlmostEqual(conv.lattice.c, 4.2327080177761687)
parser = CifParser(
os.path.join(PymatgenTest.TEST_FILES_DIR, "orci_1010.cif"))
structure = parser.get_structures(False)[0]
s = SpacegroupAnalyzer(structure, symprec=1e-2)
conv = s.get_conventional_standard_structure()
self.assertAlmostEqual(conv.lattice.alpha, 90)
self.assertAlmostEqual(conv.lattice.beta, 90)
self.assertAlmostEqual(conv.lattice.gamma, 90)
self.assertAlmostEqual(conv.lattice.a, 2.9542233922299999)
self.assertAlmostEqual(conv.lattice.b, 4.6330325651443296)
self.assertAlmostEqual(conv.lattice.c, 5.373703587040775)
parser = CifParser(
os.path.join(PymatgenTest.TEST_FILES_DIR, "orcc_1003.cif"))
structure = parser.get_structures(False)[0]
s = SpacegroupAnalyzer(structure, symprec=1e-2)
conv = s.get_conventional_standard_structure()
self.assertAlmostEqual(conv.lattice.alpha, 90)
self.assertAlmostEqual(conv.lattice.beta, 90)
self.assertAlmostEqual(conv.lattice.gamma, 90)
self.assertAlmostEqual(conv.lattice.a, 4.1430033493799998)
self.assertAlmostEqual(conv.lattice.b, 31.437979757624728)
self.assertAlmostEqual(conv.lattice.c, 3.99648651)
parser = CifParser(
os.path.join(PymatgenTest.TEST_FILES_DIR, "orac_632475.cif"))
structure = parser.get_structures(False)[0]
s = SpacegroupAnalyzer(structure, symprec=1e-2)
conv = s.get_conventional_standard_structure()
self.assertAlmostEqual(conv.lattice.alpha, 90)
self.assertAlmostEqual(conv.lattice.beta, 90)
self.assertAlmostEqual(conv.lattice.gamma, 90)
self.assertAlmostEqual(conv.lattice.a, 3.1790663399999999)
self.assertAlmostEqual(conv.lattice.b, 9.9032878699999998)
self.assertAlmostEqual(conv.lattice.c, 3.5372412099999999)
parser = CifParser(
os.path.join(PymatgenTest.TEST_FILES_DIR, "monoc_1028.cif"))
structure = parser.get_structures(False)[0]
s = SpacegroupAnalyzer(structure, symprec=1e-2)
conv = s.get_conventional_standard_structure()
self.assertAlmostEqual(conv.lattice.alpha, 90)
self.assertAlmostEqual(conv.lattice.beta, 117.53832420192903)
self.assertAlmostEqual(conv.lattice.gamma, 90)
self.assertAlmostEqual(conv.lattice.a, 14.033435583000625)
self.assertAlmostEqual(conv.lattice.b, 3.96052850731)
self.assertAlmostEqual(conv.lattice.c, 6.8743926325200002)
parser = CifParser(
os.path.join(PymatgenTest.TEST_FILES_DIR, "hex_1170.cif"))
structure = parser.get_structures(False)[0]
s = SpacegroupAnalyzer(structure, symprec=1e-2)
conv = s.get_conventional_standard_structure()
self.assertAlmostEqual(conv.lattice.alpha, 90)
self.assertAlmostEqual(conv.lattice.beta, 90)
self.assertAlmostEqual(conv.lattice.gamma, 120)
self.assertAlmostEqual(conv.lattice.a, 3.699919902005897)
self.assertAlmostEqual(conv.lattice.b, 3.699919902005897)
self.assertAlmostEqual(conv.lattice.c, 6.9779585500000003)
structure = Structure.from_file(
os.path.join(PymatgenTest.TEST_FILES_DIR, "tric_684654.json"))
s = SpacegroupAnalyzer(structure, symprec=1e-2)
conv = s.get_conventional_standard_structure()
self.assertAlmostEqual(conv.lattice.alpha, 74.09581916308757)
self.assertAlmostEqual(conv.lattice.beta, 75.72817279281173)
self.assertAlmostEqual(conv.lattice.gamma, 63.63234318667333)
self.assertAlmostEqual(conv.lattice.a, 3.741372924048738)
self.assertAlmostEqual(conv.lattice.b, 3.9883228679270686)
self.assertAlmostEqual(conv.lattice.c, 7.288495840048958)
structure = Structure.from_file(
os.path.join(PymatgenTest.TEST_FILES_DIR, "tric_684654.json"))
structure.add_site_property("magmom", [1.0] * len(structure))
s = SpacegroupAnalyzer(structure, symprec=1e-2)
conv = s.get_conventional_standard_structure(keep_site_properties=True)
self.assertEqual(conv.site_properties["magmom"], [1.0] * len(conv))
structure = Structure.from_file(
os.path.join(PymatgenTest.TEST_FILES_DIR, "tric_684654.json"))
structure.add_site_property("magmom", [1.0] * len(structure))
s = SpacegroupAnalyzer(structure, symprec=1e-2)
conv = s.get_conventional_standard_structure(
keep_site_properties=False)
self.assertEqual(conv.site_properties.get("magmom", None), None)
def test_get_slabs(self):
gen = SlabGenerator(self.get_structure("CsCl"), [0, 0, 1], 10, 10)
#Test orthogonality of some internal variables.
a, b, c = gen.oriented_unit_cell.lattice.matrix
self.assertAlmostEqual(np.dot(a, gen._normal), 0)
self.assertAlmostEqual(np.dot(b, gen._normal), 0)
self.assertEqual(len(gen.get_slabs()), 1)
s = self.get_structure("LiFePO4")
gen = SlabGenerator(s, [0, 0, 1], 10, 10)
self.assertEqual(len(gen.get_slabs()), 5)
self.assertEqual(len(gen.get_slabs(bonds={("P", "O"): 3})), 2)
# There are no slabs in LFP that does not break either P-O or Fe-O
# bonds for a miller index of [0, 0, 1].
self.assertEqual(
len(gen.get_slabs(bonds={
("P", "O"): 3,
("Fe", "O"): 3
})), 0)
#If we allow some broken bonds, there are a few slabs.
self.assertEqual(
len(
gen.get_slabs(bonds={
("P", "O"): 3,
("Fe", "O"): 3
},
max_broken_bonds=2)), 2)
# At this threshold, only the origin and center Li results in
# clustering. All other sites are non-clustered. So the of
# slabs is of sites in LiFePO4 unit cell - 2 + 1.
self.assertEqual(len(gen.get_slabs(tol=1e-4)), 15)
LiCoO2 = Structure.from_file(get_path("icsd_LiCoO2.cif"),
primitive=False)
gen = SlabGenerator(LiCoO2, [0, 0, 1], 10, 10)
lco = gen.get_slabs(bonds={("Co", "O"): 3})
self.assertEqual(len(lco), 1)
a, b, c = gen.oriented_unit_cell.lattice.matrix
self.assertAlmostEqual(np.dot(a, gen._normal), 0)
self.assertAlmostEqual(np.dot(b, gen._normal), 0)
scc = Structure.from_spacegroup("Pm-3m", Lattice.cubic(3), ["Fe"],
[[0, 0, 0]])
gen = SlabGenerator(scc, [0, 0, 1], 10, 10)
slabs = gen.get_slabs()
self.assertEqual(len(slabs), 1)
gen = SlabGenerator(scc, [1, 1, 1], 10, 10, max_normal_search=1)
slabs = gen.get_slabs()
self.assertEqual(len(slabs), 1)
# Test whether using units of hkl planes instead of Angstroms for
# min_slab_size and min_vac_size will give us the same number of atoms
natoms = []
for a in [1, 1.4, 2.5, 3.6]:
s = Structure.from_spacegroup("Im-3m", Lattice.cubic(a), ["Fe"],
[[0, 0, 0]])
slabgen = SlabGenerator(s, (1, 1, 1),
10,
10,
in_unit_planes=True,
max_normal_search=2)
natoms.append(len(slabgen.get_slab()))
n = natoms[0]
for i in natoms:
self.assertEqual(n, i)
def test_SiC_conv(self):
"""
Testing a full convergence calculation cycle on SiC using precomupted data.
"""
# the current version uses refence data from a run using the production version on zenobe
# once all checks out the run should be done using the input generated using this version to replace the
# reference
wdir = tempfile.mkdtemp()
os.chdir(wdir)
temp_ABINIT_PS_EXT = os.environ.get('ABINIT_PS_EXT', None)
temp_ABINIT_PS = os.environ.get('ABINIT_PS', None)
os.environ['ABINIT_PS_EXT'] = '.psp8'
os.environ['ABINIT_PS'] = wdir
reference_dir = os.path.join(__reference_dir__, 'SiC_test_case')
if not os.path.isdir(reference_dir): raise RuntimeError('py.test needs to be started in the HTGW root, '
'%s does not exist' % __reference_dir__)
# copy input
print(wdir)
self.assertTrue(os.path.isdir(reference_dir))
src_files = os.listdir(reference_dir)
for file_name in src_files:
full_file_name = os.path.join(reference_dir, file_name)
if os.path.isfile(full_file_name):
shutil.copy(full_file_name, wdir)
self.assertEqual(len(os.listdir(wdir)), 6)
print(os.listdir(wdir))
structure = Structure.from_file('SiC.cif')
structure.item = 'SiC.cif'
print(' ==== generate flow === ')
gwsetup(update=False)
self.assertTrue(os.path.isdir(os.path.join(wdir, 'SiC_SiC.cif')))
print(os.listdir(os.path.join(wdir)))
print(os.listdir(os.path.join(wdir, 'SiC_SiC.cif')))
self.assertTrue(os.path.isfile(os.path.join(wdir, 'SiC_SiC.cif', '__AbinitFlow__.pickle')))
self.assertEqual(len(os.listdir(os.path.join(wdir, 'SiC_SiC.cif', 'w0'))), 48)
print(' ==== copy reference results from first calculation === ')
shutil.rmtree(os.path.join(wdir, 'SiC_SiC.cif'))
shutil.copytree(os.path.join(reference_dir, 'ref_res', 'SiC_SiC.cif'), os.path.join(wdir, 'SiC_SiC.cif'))
self.assertTrue(os.path.isdir(os.path.join(wdir, 'SiC_SiC.cif')))
self.assertEqual(len(os.listdir(os.path.join(wdir, 'SiC_SiC.cif', 'w0'))), 68)
print(' ==== process output === ')
gwoutput()
print(os.listdir('.'))
self.assertTrue(os.path.isfile('plot-fits'))
self.assertTrue(os.path.isfile('plots'))
self.assertEqual(is_converged(hartree_parameters=True, structure=structure, return_values=True),
{u'ecut': 44.0, u'ecuteps': 4.0, u'gap': 6.816130591466406, u'nbands': 60})
self.assertTrue(os.path.isfile('SiC_SiC.cif.full_res'))
print(' ==== generate next flow === ')
print(' version with bandstructure and dos ')
gwsetup(update=False)
self.assertTrue(os.path.isdir('SiC_SiC.cif.conv'))
print(os.listdir(os.path.join(wdir, 'SiC_SiC.cif.conv', 'w0')))
self.assertEqual(len(os.listdir(os.path.join(wdir, 'SiC_SiC.cif.conv', 'w0'))), 15)
print(' ==== copy reference from second flow === ')
time.sleep(1) # the .conv directory should be older than the first one
shutil.rmtree(os.path.join(wdir, 'SiC_SiC.cif.conv'))
shutil.copytree(os.path.join(reference_dir, 'ref_res', 'SiC_SiC.cif.conv'),
os.path.join(wdir, 'SiC_SiC.cif.conv'))
self.assertTrue(os.path.isdir(os.path.join(wdir, 'SiC_SiC.cif.conv')))
self.assertEqual(len(os.listdir(os.path.join(wdir, 'SiC_SiC.cif.conv', 'w0'))), 13)
print(' ==== process output === ')
backup = sys.stdout
sys.stdout = StringIO() # capture output
gwoutput()
out = sys.stdout.getvalue() # release output
sys.stdout.close() # close the stream
sys.stdout = backup # restore original stdout
print('=== *** ====\n'+out+'=== *** ====\n')
gap = 0
for l in out.split('\n'):
if 'values' in l:
gap = float(l.split(' ')[6])
self.assertEqual(gap, 7.114950664158926)
print(os.listdir('.'))
print('processed')
self.assertTrue(os.path.isfile('SiC_SiC.cif.full_res'))
full_res = read_grid_from_file(s_name(structure)+'.full_res')
self.assertEqual(full_res, {u'all_done': True, u'grid': 0})
self.assertTrue(os.path.isdir(os.path.join(wdir, 'SiC_SiC.cif.res')))
self.assertEqual(len(os.listdir(os.path.join(wdir, 'SiC_SiC.cif.res'))), 5)
print(os.listdir(os.path.join(wdir, 'SiC_SiC.cif.res')))
msrf = MySigResFile(os.path.join(wdir, 'SiC_SiC.cif.res', 'out_SIGRES.nc'))
self.assertEqual(msrf.h**o, 6.6843830378711786)
self.assertEqual(msrf.lumo, 8.0650328308487982)
self.assertEqual(msrf.homo_gw, 6.2325949743130034)
self.assertEqual(msrf.lumo_gw, 8.2504215095164763)
self.assertEqual(msrf.fundamental_gap('ks'), msrf.lumo - msrf.h**o)
self.assertEqual(msrf.fundamental_gap('gw'), msrf.lumo_gw - msrf.homo_gw)
self.assertAlmostEqual(msrf.fundamental_gap('gamma'), gap, places=3)
# since we now have a mysigresfile object we test the functionality
msrf.get_scissor()
# return self.qplist_spin[0].build_scissors(domains=[[-200, mid], [mid, 200]], k=1, plot=False)
res = msrf.get_scissor_residues()
self.assertEqual(res, [0.05322754684319431, 0.34320373172956475])
# return sc.residues
#msrf.plot_scissor(title='')
#msrf.plot_qpe(title='')
# to be continued
if temp_ABINIT_PS is not None:
os.environ['ABINIT_PS_EXT'] = temp_ABINIT_PS_EXT
os.environ['ABINIT_PS'] = temp_ABINIT_PS
def plot_ion_hull_and_voltages(ion, fmt='pdf'):
"""
Plots the phase diagram between the pure material and pure ion,
Connecting the points on the convex hull of the phase diagram.
Args:
ion (str): name of atom that was intercalated, e.g. 'Li'.
fmt (str): matplotlib format style. Check the matplotlib
docs for options.
"""
# Calculated with the relax() function in
# mat2d.stability.startup. If you are using other input
# parameters, you need to recalculate these values!
ion_ev_fu = {'Li': -1.7540797, 'Mg': -1.31976062, 'Al': -3.19134607}
energy = Vasprun('vasprun.xml').final_energy
composition = Structure.from_file('POSCAR').composition
# Get the formula (with single-digit integers preceded by a '_').
twod_material = list(composition.reduced_formula)
twod_formula = str()
for i in range(len(twod_material)):
try:
int(twod_material[i])
twod_formula += '_{}'.format(twod_material[i])
except:
twod_formula += twod_material[i]
twod_ev_fu = energy / composition.get_reduced_composition_and_factor()[1]
data = [(0, 0, 0, twod_ev_fu)] # (at% ion, n_ions, E_F, abs_energy)
dirs = [dir for dir in os.listdir(os.getcwd()) if os.path.isdir(dir)]
for directory in dirs:
if is_converged(directory):
os.chdir(directory)
energy = Vasprun('vasprun.xml').final_energy
composition = Structure.from_file('POSCAR').composition
ion_fraction = composition.get_atomic_fraction(ion)
no_ion_comp_dict = composition.as_dict()
no_ion_comp_dict.update({ion: 0})
no_ion_comp = Composition.from_dict(no_ion_comp_dict)
n_twod_fu = no_ion_comp.get_reduced_composition_and_factor()[1]
n_ions = composition[ion] / n_twod_fu
E_F = ((energy - composition[ion] * ion_ev_fu[ion] -
twod_ev_fu * n_twod_fu)/ composition.num_atoms)
data.append((ion_fraction, n_ions, E_F, energy / n_twod_fu))
os.chdir('../')
data.append((1, 1, 0, ion_ev_fu[ion])) # Pure ion
sorted_data = sorted(data, key=operator.itemgetter(0))
# Determine which compositions are on the convex hull.
energy_profile = np.array([[item[0], item[2]] for item in sorted_data
if item[2] <= 0])
hull = ConvexHull(energy_profile)
convex_ion_fractions = [energy_profile[vertex, 0] for vertex in hull.vertices]
convex_formation_energies = [energy_profile[vertex, 1] for vertex in hull.vertices]
convex_ion_fractions.append(convex_ion_fractions.pop(0))
convex_formation_energies.append(convex_formation_energies.pop(0))
concave_ion_fractions = [pt[0] for pt in sorted_data
if pt[0] not in convex_ion_fractions]
concave_formation_energies = [pt[2] for pt in sorted_data
if pt[0] not in convex_ion_fractions]
voltage_profile = []
j = 0
k = 0
for i in range(1, len(sorted_data) - 1):
if sorted_data[i][0] in convex_ion_fractions:
voltage = -(((sorted_data[i][3] - sorted_data[k][3])-
(sorted_data[i][1] - sorted_data[k][1]) * ion_ev_fu[ion])
/ (sorted_data[i][1] - sorted_data[k][1]))
voltage_profile.append((sorted_data[k][0], voltage))
voltage_profile.append((sorted_data[i][0], voltage))
j += 1
k = i
voltage_profile.append((voltage_profile[-1][0], 0))
voltage_profile.append((1, 0))
voltage_profile_x = [tup[0] for tup in voltage_profile]
voltage_profile_y = [tup[1] for tup in voltage_profile]
ax = plt.figure(figsize=(14, 10)).gca()
ax.plot([0, 1], [0, 0], 'k--')
ax.plot(convex_ion_fractions, convex_formation_energies, 'b-', marker='o',
markersize=12, markeredgecolor='none')
ax.plot(concave_ion_fractions, concave_formation_energies, 'r', marker='o',
linewidth=0, markersize=12, markeredgecolor='none')
ax2 = ax.twinx()
ax2.plot(voltage_profile_x, voltage_profile_y, 'k-', marker='o')
ax.text(0, 0.002, r'$\mathrm{%s}$' % twod_formula, family='serif', size=24)
ax.text(0.99, 0.002, r'$\mathrm{%s}$' % ion, family='serif', size=24,
horizontalalignment='right')
ax.set_xticklabels(ax.get_xticks(), family='serif', size=20)
ax.set_yticklabels(ax.get_yticks(), family='serif', size=20)
ax2.set_yticklabels(ax2.get_yticks(), family='serif', size=20)
ax.set_xlabel('at% {}'.format(ion), family='serif', size=28)
ax.set_ylabel(r'$\mathrm{E_F\/(eV/atom)}$', size=28)
ax2.yaxis.set_label_position('right')
if ion == 'Li':
ax2.set_ylabel(r'$\mathrm{Potential\/vs.\/Li/Li^+\/(V)}$', size=28)
elif ion == 'Mg':
ax2.set_ylabel(r'$\mathrm{Potential\/vs.\/Mg/Mg^{2+}\/(V)}$', size=28)
elif ion == 'Al':
ax2.set_ylabel(r'$\mathrm{Potential\/vs.\/Al/Al^{3+}\/(V)}$', size=28)
plt.savefig('{}_hull.{}'.format(ion, fmt), transparent=True)
def setUp(self):
self.maxDiff = None
# trivial example, simple square lattice for testing
structure = Structure(Lattice.tetragonal(5.0, 50.0), ['H'], [[0, 0, 0]])
self.square_sg = StructureGraph.with_empty_graph(structure, edge_weight_name="", edge_weight_units="")
self.square_sg.add_edge(0, 0, from_jimage=(0, 0, 0), to_jimage=(1, 0, 0))
self.square_sg.add_edge(0, 0, from_jimage=(0, 0, 0), to_jimage=(-1, 0, 0))
self.square_sg.add_edge(0, 0, from_jimage=(0, 0, 0), to_jimage=(0, 1, 0))
self.square_sg.add_edge(0, 0, from_jimage=(0, 0, 0), to_jimage=(0, -1, 0))
#TODO: decorating still fails because the structure graph gives a CN of 8 for this square lattice
# self.square_sg.decorate_structure_with_ce_info()
# body-centered square lattice for testing
structure = Structure(Lattice.tetragonal(5.0, 50.0), ['H', 'He'], [[0, 0, 0], [0.5, 0.5, 0.5]])
self.bc_square_sg = StructureGraph.with_empty_graph(structure, edge_weight_name="", edge_weight_units="")
self.bc_square_sg.add_edge(0, 0, from_jimage=(0, 0, 0), to_jimage=(1, 0, 0))
self.bc_square_sg.add_edge(0, 0, from_jimage=(0, 0, 0), to_jimage=(-1, 0, 0))
self.bc_square_sg.add_edge(0, 0, from_jimage=(0, 0, 0), to_jimage=(0, 1, 0))
self.bc_square_sg.add_edge(0, 0, from_jimage=(0, 0, 0), to_jimage=(0, -1, 0))
self.bc_square_sg.add_edge(0, 1, from_jimage=(0, 0, 0), to_jimage=(0, 0, 0))
self.bc_square_sg.add_edge(0, 1, from_jimage=(0, 0, 0), to_jimage=(-1, 0, 0))
self.bc_square_sg.add_edge(0, 1, from_jimage=(0, 0, 0), to_jimage=(-1, -1, 0))
self.bc_square_sg.add_edge(0, 1, from_jimage=(0, 0, 0), to_jimage=(0, -1, 0))
# body-centered square lattice for testing
# directions reversed, should be equivalent to as bc_square
structure = Structure(Lattice.tetragonal(5.0, 50.0), ['H', 'He'], [[0, 0, 0], [0.5, 0.5, 0.5]])
self.bc_square_sg_r = StructureGraph.with_empty_graph(structure, edge_weight_name="", edge_weight_units="")
self.bc_square_sg_r.add_edge(0, 0, from_jimage=(0, 0, 0), to_jimage=(1, 0, 0))
self.bc_square_sg_r.add_edge(0, 0, from_jimage=(0, 0, 0), to_jimage=(-1, 0, 0))
self.bc_square_sg_r.add_edge(0, 0, from_jimage=(0, 0, 0), to_jimage=(0, 1, 0))
self.bc_square_sg_r.add_edge(0, 0, from_jimage=(0, 0, 0), to_jimage=(0, -1, 0))
self.bc_square_sg_r.add_edge(0, 1, from_jimage=(0, 0, 0), to_jimage=(0, 0, 0))
self.bc_square_sg_r.add_edge(1, 0, from_jimage=(-1, 0, 0), to_jimage=(0, 0, 0))
self.bc_square_sg_r.add_edge(1, 0, from_jimage=(-1, -1, 0), to_jimage=(0, 0, 0))
self.bc_square_sg_r.add_edge(1, 0, from_jimage=(0, -1, 0), to_jimage=(0, 0, 0))
# MoS2 example, structure graph obtained from critic2
# (not ground state, from mp-1023924, single layer)
stdout_file = os.path.join(os.path.dirname(__file__), "..", "..", "..",
'test_files/critic2/MoS2_critic2_stdout.txt')
with open(stdout_file, 'r') as f:
reference_stdout = f.read()
self.structure = Structure.from_file(os.path.join(os.path.dirname(__file__), "..", "..", "..",
'test_files/critic2/MoS2.cif'))
c2o = Critic2Output(self.structure, reference_stdout)
self.mos2_sg = c2o.structure_graph(edge_weight="bond_length", edge_weight_units="Å")
latt = Lattice.cubic(4.17)
species = ["Ni", "O"]
coords = [[0, 0, 0],
[0.5, 0.5, 0.5]]
self.NiO = Structure.from_spacegroup(225, latt, species, coords).get_primitive_structure()
# BCC example.
self.bcc = Structure(Lattice.cubic(5.0), ['He', 'He'], [[0, 0, 0], [0.5, 0.5, 0.5]])
warnings.simplefilter("ignore")
# make new structure if not matched (not already existed)
struc_matched = False
find_comp = subs_db.find({
"nspecies": nspecies,
"species": species
})
for y in find_comp:
basedir_comp = x["basedir"]
positionfilename_comp = y["positionfile"]
struc_comp = StructureNode(basedir_comp)
current_dir_comp = struc_comp.get_currentdir()
filename_comp = os.path.join(current_dir_comp,
positionfilename_comp)
struc_comp = Structure.from_file(filename_comp)
struc_matcher = StructureMatcher()
match = struc_matcher.fit(new_struc, struc_comp)
if match:
struc_matched = True
if not struc_matched:
print("new_basedir", new_basedir)
metadata = {
"purpose": "converged_ionic",
"achievement": "to_relax"
}
structurenode = StructureNode(new_basedir)
structurenode.place_files(new_struc,
source_uuid=source_uuid,
metadata=metadata)
def make_confs(self, path_to_work, path_to_equi, refine=False):
path_to_work = os.path.abspath(path_to_work)
if os.path.exists(path_to_work):
dlog.warning('%s already exists' % path_to_work)
else:
os.makedirs(path_to_work)
path_to_equi = os.path.abspath(path_to_equi)
if 'start_confs_path' in self.parameter and os.path.exists(
self.parameter['start_confs_path']):
init_path_list = glob.glob(
os.path.join(self.parameter['start_confs_path'], '*'))
struct_init_name_list = []
for ii in init_path_list:
struct_init_name_list.append(ii.split('/')[-1])
struct_output_name = path_to_work.split('/')[-2]
assert struct_output_name in struct_init_name_list
path_to_equi = os.path.abspath(
os.path.join(self.parameter['start_confs_path'],
struct_output_name, 'relaxation', 'relax_task'))
task_list = []
cwd = os.getcwd()
equi_contcar = os.path.join(path_to_equi, 'CONTCAR')
os.chdir(path_to_work)
if os.path.isfile('POSCAR'):
os.remove('POSCAR')
if os.path.islink('POSCAR'):
os.remove('POSCAR')
os.symlink(os.path.relpath(equi_contcar), 'POSCAR')
# task_poscar = os.path.join(output, 'POSCAR')
# stress, deal with unsupported stress in dpdata
#with open(os.path.join(path_to_equi, 'result.json')) as fin:
# equi_result = json.load(fin)
#equi_stress = np.array(equi_result['stress']['data'])[-1]
equi_result = loadfn(os.path.join(path_to_equi, 'result.json'))
equi_stress = equi_result['stress'][-1]
dumpfn(equi_stress, 'equi.stress.json', indent=4)
os.chdir(cwd)
if refine:
print('elastic refine starts')
task_list = make_refine(self.parameter['init_from_suffix'],
self.parameter['output_suffix'],
path_to_work)
# record strain
# df = Strain.from_deformation(dfm_ss.deformations[idid])
# dumpfn(df.as_dict(), 'strain.json', indent=4)
init_from_path = re.sub(self.parameter['output_suffix'][::-1],
self.parameter['init_from_suffix'][::-1],
path_to_work[::-1],
count=1)[::-1]
task_list_basename = list(map(os.path.basename, task_list))
for ii in task_list_basename:
init_from_task = os.path.join(init_from_path, ii)
output_task = os.path.join(path_to_work, ii)
os.chdir(output_task)
if os.path.isfile('strain.json'):
os.remove('strain.json')
copyfile(os.path.join(init_from_task, 'strain.json'),
'strain.json')
#os.symlink(os.path.relpath(
# os.path.join((re.sub(self.parameter['output_suffix'], self.parameter['init_from_suffix'], ii)),
# 'strain.json')),
# 'strain.json')
os.chdir(cwd)
else:
norm_def = self.norm_deform
shear_def = self.shear_deform
norm_strains = [
-norm_def, -0.5 * norm_def, 0.5 * norm_def, norm_def
]
shear_strains = [
-shear_def, -0.5 * shear_def, 0.5 * shear_def, shear_def
]
if not os.path.exists(equi_contcar):
raise RuntimeError("please do relaxation first")
ss = Structure.from_file(equi_contcar)
dfm_ss = DeformedStructureSet(ss,
symmetry=False,
norm_strains=norm_strains,
shear_strains=shear_strains)
n_dfm = len(dfm_ss)
print('gen with norm ' + str(norm_strains))
print('gen with shear ' + str(shear_strains))
for ii in range(n_dfm):
output_task = os.path.join(path_to_work, 'task.%06d' % ii)
os.makedirs(output_task, exist_ok=True)
os.chdir(output_task)
for jj in [
'INCAR', 'POTCAR', 'POSCAR', 'conf.lmp', 'in.lammps'
]:
if os.path.exists(jj):
os.remove(jj)
task_list.append(output_task)
dfm_ss.deformed_structures[ii].to('POSCAR', 'POSCAR')
# record strain
df = Strain.from_deformation(dfm_ss.deformations[ii])
dumpfn(df.as_dict(), 'strain.json', indent=4)
os.chdir(cwd)
return task_list
def write_KPOINTS(
POSCAR_input: str = "POSCAR",
KPOINTS_output="KPOINTS.lobster",
reciprocal_density: int = 100,
isym: int = -1,
from_grid: bool = False,
input_grid: list = [5, 5, 5],
line_mode: bool = True,
kpoints_line_density: int = 20,
symprec: float = 0.01,
):
"""
writes a KPOINT file for lobster (only ISYM=-1 and ISYM=0 are possible), grids are gamma centered
Args:
POSCAR_input (str): path to POSCAR
KPOINTS_output (str): path to output KPOINTS
reciprocal_density (int): Grid density
isym (int): either -1 or 0. Current Lobster versions only allow -1.
from_grid (bool): If True KPOINTS will be generated with the help of a grid given in input_grid. Otherwise,
they will be generated from the reciprocal_density
input_grid (list): grid to generate the KPOINTS file
line_mode (bool): If True, band structure will be generated
kpoints_line_density (int): density of the lines in the band structure
symprec (float): precision to determine symmetry
"""
structure = Structure.from_file(POSCAR_input)
if not from_grid:
kpointgrid = Kpoints.automatic_density_by_vol(
structure, reciprocal_density).kpts
mesh = kpointgrid[0]
else:
mesh = input_grid
# The following code is taken from: SpacegroupAnalyzer
# we need to switch off symmetry here
latt = structure.lattice.matrix
positions = structure.frac_coords
unique_species = [] # type: List[Any]
zs = []
magmoms = []
for species, g in itertools.groupby(structure,
key=lambda s: s.species):
if species in unique_species:
ind = unique_species.index(species)
zs.extend([ind + 1] * len(tuple(g)))
else:
unique_species.append(species)
zs.extend([len(unique_species)] * len(tuple(g)))
for site in structure:
if hasattr(site, "magmom"):
magmoms.append(site.magmom)
elif site.is_ordered and hasattr(site.specie, "spin"):
magmoms.append(site.specie.spin)
else:
magmoms.append(0)
# For now, we are setting magmom to zero. (Taken from INCAR class)
cell = latt, positions, zs, magmoms
# TODO: what about this shift?
mapping, grid = spglib.get_ir_reciprocal_mesh(mesh,
cell,
is_shift=[0, 0, 0])
# exit()
# get the kpoints for the grid
if isym == -1:
kpts = []
weights = []
all_labels = []
for gp in grid:
kpts.append(gp.astype(float) / mesh)
weights.append(float(1))
all_labels.append("")
elif isym == 0:
# time reversal symmetry: k and -k are equivalent
kpts = []
weights = []
all_labels = []
newlist = [list(gp) for gp in list(grid)]
mapping = []
for gp in newlist:
minus_gp = [-k for k in gp]
if minus_gp in newlist and minus_gp not in [[0, 0, 0]]:
mapping.append(newlist.index(minus_gp))
else:
mapping.append(newlist.index(gp))
for igp, gp in enumerate(newlist):
if mapping[igp] > igp:
kpts.append(np.array(gp).astype(float) / mesh)
weights.append(float(2))
all_labels.append("")
elif mapping[igp] == igp:
kpts.append(np.array(gp).astype(float) / mesh)
weights.append(float(1))
all_labels.append("")
else:
ValueError("Only isym=-1 and isym=0 are allowed.")
# line mode
if line_mode:
kpath = HighSymmKpath(structure, symprec=symprec)
if not np.allclose(kpath.prim.lattice.matrix,
structure.lattice.matrix):
raise ValueError(
"You are not using the standard primitive cell. The k-path is not correct. Please generate a "
"standard primitive cell first.")
frac_k_points, labels = kpath.get_kpoints(
line_density=kpoints_line_density, coords_are_cartesian=False)
for k, f in enumerate(frac_k_points):
kpts.append(f)
weights.append(0.0)
all_labels.append(labels[k])
if isym == -1:
comment = ("ISYM=-1, grid: " +
str(mesh) if not line_mode else "ISYM=-1, grid: " +
str(mesh) + " plus kpoint path")
elif isym == 0:
comment = ("ISYM=0, grid: " +
str(mesh) if not line_mode else "ISYM=0, grid: " +
str(mesh) + " plus kpoint path")
KpointObject = Kpoints(
comment=comment,
style=Kpoints.supported_modes.Reciprocal,
num_kpts=len(kpts),
kpts=kpts,
kpts_weights=weights,
labels=all_labels,
)
KpointObject.write_file(filename=KPOINTS_output)
def from_file(cls, fmt, filename=None,
structure_file=None, are_coops=False):
"""
Creates a CompleteCohp object from an output file of a COHP
calculation. Valid formats are either LMTO (for the Stuttgart
LMTO-ASA code) or LOBSTER (for the LOBSTER code).
Args:
cohp_file: Name of the COHP output file. Defaults to COPL
for LMTO and COHPCAR.lobster/COOPCAR.lobster for LOBSTER.
are_coops: Indicates whether the populations are COOPs or
COHPs. Defaults to False for COHPs.
fmt: A string for the code that was used to calculate
the COHPs so that the output file can be handled
correctly. Can take the values "LMTO" or "LOBSTER".
structure_file: Name of the file containing the structure.
If no file name is given, use CTRL for LMTO and POSCAR
for LOBSTER.
Returns:
A CompleteCohp object.
"""
fmt = fmt.upper()
if fmt == "LMTO":
# LMTO COOPs and orbital-resolved COHP cannot be handled yet.
are_coops = False
orb_res_cohp = None
if structure_file is None:
structure_file = "CTRL"
if filename is None:
filename = "COPL"
cohp_file = LMTOCopl(filename=filename, to_eV=True)
elif fmt == "LOBSTER":
if structure_file is None:
structure_file = "POSCAR"
if filename is None:
filename = "COOPCAR.lobster" if are_coops \
else "COHPCAR.lobster"
warnings.warn(
"The bond labels are currently consistent with ICOHPLIST.lobster/ICOOPLIST.lobster, not with "
"COHPCAR.lobster/COOPCAR.lobster. Please be aware!")
cohp_file = Cohpcar(filename=filename, are_coops=are_coops)
orb_res_cohp = cohp_file.orb_res_cohp
else:
raise ValueError("Unknown format %s. Valid formats are LMTO "
"and LOBSTER." % fmt)
structure = Structure.from_file(structure_file)
efermi = cohp_file.efermi
cohp_data = cohp_file.cohp_data
energies = cohp_file.energies
# Lobster shifts the energies so that the Fermi energy is at zero.
# Shifting should be done by the plotter object though.
spins = [Spin.up, Spin.down] if cohp_file.is_spin_polarized \
else [Spin.up]
if fmt == "LOBSTER":
energies += efermi
if orb_res_cohp is not None:
# If no total COHPs are present, calculate the total
# COHPs from the single-orbital populations. Total COHPs
# may not be present when the cohpgenerator keyword is used
# in LOBSTER versions 2.2.0 and earlier.
# TODO: Test this more extensively
for label in orb_res_cohp:
if cohp_file.cohp_data[label]["COHP"] is None:
# print(label)
cohp_data[label]["COHP"] = {
sp: np.sum([orb_res_cohp[label][orbs]["COHP"][sp] for orbs in orb_res_cohp[label]], axis=0)
for sp in spins}
if cohp_file.cohp_data[label]["ICOHP"] is None:
cohp_data[label]["ICOHP"] = \
{sp: np.sum([orb_res_cohp[label][orbs]["ICOHP"][sp]
for orbs in orb_res_cohp[label]],
axis=0) for sp in spins}
if fmt == "LMTO":
# Calculate the average COHP for the LMTO file to be
# consistent with LOBSTER output.
avg_data = {"COHP": {}, "ICOHP": {}}
for i in avg_data:
for spin in spins:
rows = np.array([cohp_data[label][i][spin]
for label in cohp_data])
avg = np.average(rows, axis=0)
# LMTO COHPs have 5 significant figures
avg_data[i].update({spin: np.array([round_to_sigfigs(a, 5)
for a in avg], dtype=float)})
avg_cohp = Cohp(efermi, energies,
avg_data["COHP"],
icohp=avg_data["ICOHP"])
else:
avg_cohp = Cohp(efermi, energies,
cohp_data["average"]["COHP"],
icohp=cohp_data["average"]["COHP"],
are_coops=are_coops)
del cohp_data["average"]
cohp_dict = {label: Cohp(efermi, energies,
cohp_data[label]["COHP"],
icohp=cohp_data[label]["ICOHP"],
are_coops=are_coops)
for label in cohp_data}
bond_dict = {label: {"length": cohp_data[label]["length"],
"sites": [structure.sites[site]
for site in cohp_data[label]["sites"]]}
for label in cohp_data}
return CompleteCohp(structure, avg_cohp, cohp_dict, bonds=bond_dict,
are_coops=are_coops, orb_res_cohp=orb_res_cohp)
def test_writevaspfrominterpolatedposcar(self):
nimages = 5
this_image = 1
autosort_tol = 0.5
fw1 = Firework([
CopyVaspOutputs(calc_dir=self.static_outdir,
contcar_to_poscar=False,
additional_files=["CONTCAR"]),
PassCalcLocs(name="fw1")
],
name="fw1")
fw2 = Firework([
CopyVaspOutputs(calc_dir=self.opt_outdir,
contcar_to_poscar=False,
additional_files=["CONTCAR"]),
PassCalcLocs(name="fw2")
],
name="fw2")
fw3 = Firework([
WriteVaspFromIOSetFromInterpolatedPOSCAR(
start="fw1",
end="fw2",
this_image=this_image,
nimages=nimages,
autosort_tol=autosort_tol,
vasp_input_set="MPStaticSet"),
PassCalcLocs(name="fw3")
],
name="fw3",
parents=[fw1, fw2])
fw4 = Firework([PassCalcLocs(name="fw4")], name="fw4", parents=fw3)
wf = Workflow([fw1, fw2, fw3, fw4])
self.lp.add_wf(wf)
rapidfire(self.lp)
fw4 = self.lp.get_fw_by_id(self.lp.get_fw_ids({"name": "fw4"})[0])
calc_locs = fw4.spec["calc_locs"]
print(get_calc_loc("fw3", calc_locs)["path"])
# Check existence of structure files.
self.assertTrue(
os.path.exists(get_calc_loc("fw3", calc_locs)["path"] + "/POSCAR"))
self.assertTrue(
os.path.exists(
get_calc_loc("fw3", calc_locs)["path"] +
"/interpolate/CONTCAR_0"))
self.assertTrue(
os.path.exists(
get_calc_loc("fw3", calc_locs)["path"] +
"/interpolate/CONTCAR_1"))
self.assertTrue(
os.path.exists(get_calc_loc("fw3", calc_locs)["path"] + "/INCAR"))
self.assertTrue(
os.path.exists(
get_calc_loc("fw3", calc_locs)["path"] + "/KPOINTS"))
self.assertTrue(
os.path.exists(get_calc_loc("fw3", calc_locs)["path"] + "/POTCAR"))
# Check interpolation.
struct_start = Structure.from_file(
get_calc_loc("fw3", calc_locs)["path"] + "/interpolate/CONTCAR_0")
struct_end = Structure.from_file(
get_calc_loc("fw3", calc_locs)["path"] + "/interpolate/CONTCAR_1")
struct_inter = Structure.from_file(
get_calc_loc("fw3", calc_locs)["path"] + "/POSCAR")
structs = struct_start.interpolate(struct_end,
nimages,
interpolate_lattices=True,
autosort_tol=autosort_tol)
# Check x of 1st site.
self.assertAlmostEqual(structs[this_image][1].coords[0],
struct_inter[1].coords[0])
# Check c lattice parameter
self.assertAlmostEqual(structs[this_image].lattice.abc[0],
struct_inter.lattice.abc[0])
def standard_calculations_from_vasp_files(
cls,
POSCAR_input: str = "POSCAR",
INCAR_input: str = "INCAR",
POTCAR_input: str | None = None,
dict_for_basis: dict | None = None,
option: str = "standard",
):
"""
will generate Lobsterin with standard settings
Args:
POSCAR_input(str): path to POSCAR
INCAR_input(str): path to INCAR
POTCAR_input (str): path to POTCAR
dict_for_basis (dict): can be provided: it should look the following:
dict_for_basis={"Fe":'3p 3d 4s 4f', "C": '2s 2p'} and will overwrite all settings from POTCAR_input
option (str): 'standard' will start a normal lobster run where COHPs, COOPs, DOS, CHARGE etc. will be
calculated
'standard_from_projection' will start a normal lobster run from a projection
'standard_with_fatband' will do a fatband calculation, run over all orbitals
'onlyprojection' will only do a projection
'onlydos' will only calculate a projected dos
'onlycohp' will only calculate cohp
'onlycoop' will only calculate coop
'onlycohpcoop' will only calculate cohp and coop
Returns:
Lobsterin Object with standard settings
"""
warnings.warn(
"Always check and test the provided basis functions. The spilling of your Lobster calculation might help"
)
# warn that fatband calc cannot be done with tetrahedron method at the moment
if option not in [
"standard",
"standard_from_projection",
"standard_with_fatband",
"onlyprojection",
"onlydos",
"onlycohp",
"onlycoop",
"onlycobi",
"onlycohpcoop",
"onlycohpcoopcobi",
"onlymadelung",
]:
raise ValueError("The option is not valid!")
Lobsterindict = {} # type: Dict[Any,Any]
# this basis set covers most elements
Lobsterindict["basisSet"] = "pbeVaspFit2015"
# energies around e-fermi
Lobsterindict["COHPstartEnergy"] = -35.0
Lobsterindict["COHPendEnergy"] = 5.0
if option in [
"standard",
"onlycohp",
"onlycoop",
"onlycobi",
"onlycohpcoop",
"onlycohpcoopcobi",
"standard_with_fatband",
]:
# every interaction with a distance of 6.0 is checked
Lobsterindict["cohpGenerator"] = "from 0.1 to 6.0 orbitalwise"
# the projection is saved
Lobsterindict["saveProjectionToFile"] = True
if option == "standard_from_projection":
Lobsterindict["cohpGenerator"] = "from 0.1 to 6.0 orbitalwise"
Lobsterindict["loadProjectionFromFile"] = True
# TODO: add cobi here! might be relevant lobster version
if option == "onlycohp":
Lobsterindict["skipdos"] = True
Lobsterindict["skipcoop"] = True
Lobsterindict["skipPopulationAnalysis"] = True
Lobsterindict["skipGrossPopulation"] = True
# lobster-4.1.0
Lobsterindict["skipcobi"] = True
Lobsterindict["skipMadelungEnergy"] = True
if option == "onlycoop":
Lobsterindict["skipdos"] = True
Lobsterindict["skipcohp"] = True
Lobsterindict["skipPopulationAnalysis"] = True
Lobsterindict["skipGrossPopulation"] = True
# lobster-4.1.0
Lobsterindict["skipcobi"] = True
Lobsterindict["skipMadelungEnergy"] = True
if option == "onlycohpcoop":
Lobsterindict["skipdos"] = True
Lobsterindict["skipPopulationAnalysis"] = True
Lobsterindict["skipGrossPopulation"] = True
# lobster-4.1.0
Lobsterindict["skipcobi"] = True
Lobsterindict["skipMadelungEnergy"] = True
if option == "onlycohpcoopcobi":
Lobsterindict["skipdos"] = True
Lobsterindict["skipPopulationAnalysis"] = True
Lobsterindict["skipGrossPopulation"] = True
Lobsterindict["skipMadelungEnergy"] = True
if option == "onlydos":
Lobsterindict["skipcohp"] = True
Lobsterindict["skipcoop"] = True
Lobsterindict["skipPopulationAnalysis"] = True
Lobsterindict["skipGrossPopulation"] = True
# lobster-4.1.0
Lobsterindict["skipcobi"] = True
Lobsterindict["skipMadelungEnergy"] = True
if option == "onlyprojection":
Lobsterindict["skipdos"] = True
Lobsterindict["skipcohp"] = True
Lobsterindict["skipcoop"] = True
Lobsterindict["skipPopulationAnalysis"] = True
Lobsterindict["skipGrossPopulation"] = True
Lobsterindict["saveProjectionToFile"] = True
# lobster-4.1.0
Lobsterindict["skipcobi"] = True
Lobsterindict["skipMadelungEnergy"] = True
if option == "onlycobi":
Lobsterindict["skipdos"] = True
Lobsterindict["skipcohp"] = True
Lobsterindict["skipPopulationAnalysis"] = True
Lobsterindict["skipGrossPopulation"] = True
# lobster-4.1.0
Lobsterindict["skipcobi"] = True
Lobsterindict["skipMadelungEnergy"] = True
if option == "onlymadelung":
Lobsterindict["skipdos"] = True
Lobsterindict["skipcohp"] = True
Lobsterindict["skipcoop"] = True
Lobsterindict["skipPopulationAnalysis"] = True
Lobsterindict["skipGrossPopulation"] = True
Lobsterindict["saveProjectionToFile"] = True
# lobster-4.1.0
Lobsterindict["skipcobi"] = True
incar = Incar.from_file(INCAR_input)
if incar["ISMEAR"] == 0:
Lobsterindict["gaussianSmearingWidth"] = incar["SIGMA"]
if incar["ISMEAR"] != 0 and option == "standard_with_fatband":
raise ValueError(
"ISMEAR has to be 0 for a fatband calculation with Lobster")
if dict_for_basis is not None:
# dict_for_basis={"Fe":'3p 3d 4s 4f', "C": '2s 2p'}
# will just insert this basis and not check with poscar
basis = [
key + " " + value for key, value in dict_for_basis.items()
]
elif POTCAR_input is not None:
# get basis from POTCAR
potcar_names = Lobsterin._get_potcar_symbols(
POTCAR_input=POTCAR_input)
basis = Lobsterin.get_basis(
structure=Structure.from_file(POSCAR_input),
potcar_symbols=potcar_names)
else:
raise ValueError("basis cannot be generated")
Lobsterindict["basisfunctions"] = basis
if option == "standard_with_fatband":
Lobsterindict["createFatband"] = basis
return cls(Lobsterindict)