def test_slice(self):
sliced_traj = self.traj[2:99:3]
sliced_traj_from_structs = Trajectory.from_structures(
self.structures[2:99:3])
if len(sliced_traj) == len(sliced_traj_from_structs):
self.assertTrue(
all([
sliced_traj[i] == sliced_traj_from_structs[i]
for i in range(len(sliced_traj))
]))
else:
self.assertTrue(False)
sliced_traj = self.traj[:-4:2]
sliced_traj_from_structs = Trajectory.from_structures(
self.structures[:-4:2])
if len(sliced_traj) == len(sliced_traj_from_structs):
self.assertTrue(
all([
sliced_traj[i] == sliced_traj_from_structs[i]
for i in range(len(sliced_traj))
]))
else:
self.assertTrue(False)
def test_extend_equivalent_site_props(self):
lattice = [[1, 0, 0], [0, 1, 0], [0, 0, 1]]
species = ["Si", "Si"]
frac_coords = [
[[0, 0, 0], [0.5, 0.5, 0.5]],
[[0.1, 0.1, 0.1], [0.6, 0.6, 0.6]],
[[0.2, 0.2, 0.2], [0.7, 0.7, 0.7]],
]
# Trajectories with constant site properties
site_properties_1 = [
{
"selective_dynamics": [[True, True, True], [False, False, False]],
"magmom": [5, 5],
}
]
traj_1 = Trajectory(lattice, species, frac_coords, site_properties=site_properties_1)
site_properties_2 = [
{
"selective_dynamics": [[True, True, True], [False, False, False]],
"magmom": [5, 5],
}
]
traj_2 = Trajectory(lattice, species, frac_coords, site_properties=site_properties_2)
# Test combining two trajectories with similar site_properties
traj_combined = traj_1.copy()
traj_combined.extend(traj_2)
self.assertEqual(traj_combined.site_properties, site_properties_1)
def test_extend(self):
traj = self.traj.copy()
# Case of compatible trajectories
compatible_traj = Trajectory.from_file(
os.path.join(PymatgenTest.TEST_FILES_DIR,
"Traj_Combine_Test_XDATCAR_1"))
traj.extend(compatible_traj)
full_traj = Trajectory.from_file(
os.path.join(PymatgenTest.TEST_FILES_DIR,
"Traj_Combine_Test_XDATCAR_Full"))
compatible_success = self._check_traj_equality(self.traj, full_traj)
# Case of incompatible trajectories
traj = self.traj.copy()
incompatible_traj = Trajectory.from_file(
os.path.join(PymatgenTest.TEST_FILES_DIR,
"Traj_Combine_Test_XDATCAR_2"))
incompatible_test_success = False
try:
traj.extend(incompatible_traj)
except Exception:
incompatible_test_success = True
self.assertTrue(compatible_success and incompatible_test_success)
def test_variable_lattice(self):
structure = self.structures[0]
# Generate structures with different lattices
structures = []
for i in range(10):
new_lattice = np.dot(structure.lattice.matrix,
np.diag(1 + np.random.random_sample(3) / 20))
temp_struct = structure.copy()
temp_struct.lattice = Lattice(new_lattice)
structures.append(temp_struct)
traj = Trajectory.from_structures(structures, constant_lattice=False)
# Check if lattices were properly stored
self.assertTrue(
all(
np.allclose(struct.lattice.matrix,
structures[i].lattice.matrix)
for i, struct in enumerate(traj)))
# Check if the file is written correctly when lattice is not constant.
traj.write_Xdatcar(filename="traj_test_XDATCAR")
# Load trajectory from written xdatcar and compare to original
written_traj = Trajectory.from_file("traj_test_XDATCAR",
constant_lattice=False)
self._check_traj_equality(traj, written_traj)
os.remove("traj_test_XDATCAR")
def load_trajectories_from_gfs(runs, db_file):
fs_id = []
fs = []
for run in runs:
if "INCAR" in run.keys():
# for backwards compatibility with older version of mpmorph
fs_id.append(run["ionic_steps_fs_id"])
fs.append('previous_runs_gfs')
elif "input" in run.keys():
fs_id.append(
run["calcs_reversed"][0]["output"]["ionic_steps_fs_id"])
fs.append('structures_fs')
for i, v in enumerate(fs_id):
mmdb = VaspMDCalcDb.from_db_file(db_file, admin=True)
ionic_steps_dict = load_ionic_steps(v, mmdb.db, fs[i])
if i == 0:
trajectory = Trajectory.from_structures([
Structure.from_dict(i['structure']) for i in ionic_steps_dict
])
else:
trajectory.extend(
Trajectory.from_structures([
Structure.from_dict(i['structure'])
for i in ionic_steps_dict
]))
return trajectory
def process_traj(data):
i, fs_id, fs, db_file = data[0], data[1], data[2], data[3]
mmdb = VaspMDCalcDb.from_db_file(db_file, admin=True)
ionic_steps_dict = load_ionic_steps(fs_id, mmdb.db, fs)
structure = Structure.from_dict(ionic_steps_dict[0]['structure'])
positions = [0] * len(ionic_steps_dict)
for i, step in enumerate(ionic_steps_dict):
_step = [atom['abc'] for atom in step["structure"]["sites"]]
positions[i] = _step
traj = Trajectory(structure.lattice.matrix, structure.species, positions,
0.002)
return i, traj.as_dict()
def test_extend_no_frame_props(self):
lattice = [[1, 0, 0], [0, 1, 0], [0, 0, 1]]
species = ['Si', 'Si']
frac_coords = [[[0, 0, 0], [0.5, 0.5, 0.5]],
[[0.1, 0.1, 0.1], [0.6, 0.6, 0.6]],
[[0.2, 0.2, 0.2], [0.7, 0.7, 0.7]]]
# Trajectory with no site_properties
traj_1 = Trajectory(lattice, species, frac_coords)
traj_2 = Trajectory(lattice, species, frac_coords)
# Test combining two trajectories with no site properties
traj_combined = traj_1.copy()
traj_combined.extend(traj_2)
self.assertEqual(traj_combined.frame_properties, None)
def test_xdatcar_write(self):
self.traj.write_Xdatcar(filename="traj_test_XDATCAR")
# Load trajectory from written xdatcar and compare to original
written_traj = Trajectory.from_file(os.path.join("./", "traj_test_XDATCAR"))
self._check_traj_equality(self.traj, written_traj)
def test_site_properties(self):
lattice = [[1, 0, 0], [0, 1, 0], [0, 0, 1]]
species = ["Si", "Si"]
frac_coords = [
[[0, 0, 0], [0.5, 0.5, 0.5]],
[[0.1, 0.1, 0.1], [0.6, 0.6, 0.6]],
[[0.2, 0.2, 0.2], [0.7, 0.7, 0.7]],
]
site_properties = [
{
"selective_dynamics": [[True, True, True], [False, False, False]],
"magmom": [5, 5],
},
{
"selective_dynamics": [[False, False, False], [False, False, False]],
"magmom": [6, 6],
},
{
"selective_dynamics": [[True, True, True], [False, False, False]],
"magmom": [5, 5],
},
]
traj = Trajectory(lattice, species, frac_coords, site_properties=site_properties)
# compare the overall site properties list
self.assertEqual(traj.site_properties, site_properties)
# # compare the site properties after slicing
self.assertEqual(traj[0].site_properties, site_properties[0])
self.assertEqual(traj[1:].site_properties, site_properties[1:])
def test_frame_properties(self):
lattice = [[1, 0, 0], [0, 1, 0], [0, 0, 1]]
species = ['Si', 'Si']
frac_coords = [[[0, 0, 0], [0.5, 0.5, 0.5]],
[[0.1, 0.1, 0.1], [0.6, 0.6, 0.6]],
[[0.2, 0.2, 0.2], [0.7, 0.7, 0.7]]]
site_properties = [{
'selective_dynamics': [[True, True, True], [False, False, False]],
'magmom': [5, 5]
}, {
'selective_dynamics': [[False, False, False],
[False, False, False]],
'magmom': [6, 6]
}, {
'selective_dynamics': [[True, True, True], [False, False, False]],
'magmom': [5, 5]
}]
frame_properties = {'energy_per_atom': [-3.0001, -3.0971, -3.0465]}
traj = Trajectory(lattice,
species,
frac_coords,
site_properties=site_properties,
frame_properties=frame_properties)
# compare the overall site properties list
self.assertEqual(traj.frame_properties, frame_properties)
# compare the site properties after slicing
expected_output = {'energy_per_atom': [-3.0971, -3.0465]}
self.assertEqual(traj[1:].frame_properties, expected_output)
def get_pymatgen_trajectory(self, include_shell=False):
table = self.get_structure_table(input=True,
include_shell=include_shell)
lattices, constant_lattice = self.get_md_cell()
frames = [x[table.index] for x in self.get_md_coords()]
time = self.get_step_props()["time"]
time_step = time[1] - time[0]
species_labels = self.get_species_labels()
symbols = table["label"].map(species_labels).values.tolist()
structures = [
Structure(
lattice=lattice,
species=symbols,
coords=coords,
coords_are_cartesian=True,
site_properties={"gulp_labels": table["label"]},
) for lattice, coords in zip(lattices, frames)
]
return Trajectory.from_structures(structures,
time_step=time_step,
constant_lattice=constant_lattice)
def calcs_reversed_to_trajectory(calcs_reversed: List[dict]):
"""
Converts data from calc_reversed to pymatgen Trajectory objects
that contain structure, energy, force and stress data for each
ionic step.
Args:
calcs_reversed: List of dictionaries in calcs_reversed entry
of a task document.
"""
trajectories = []
for calculation in calcs_reversed:
for step in calculation["output"]["ionic_steps"]:
structures = []
frame_props = defaultdict(list) # type: dict
structures.append(Structure.from_dict(step["structure"]))
frame_props["e_fr_energy"].append(step["e_fr_energy"])
frame_props["e_wo_entrp"].append(step["e_wo_entrp"])
frame_props["e_0_energy"].append(step["e_wo_entrp"])
frame_props["forces"].append(step["forces"])
frame_props["stresses"].append(step["stress"])
traj = Trajectory.from_structures(structures,
frame_properties=frame_props,
time_step=None).as_dict()
trajectories.append(traj)
return trajectories
def test_list_slice(self):
sliced_traj = self.traj[[10, 30, 70]]
sliced_traj_from_structs = Trajectory.from_structures([self.structures[i] for i in [10, 30, 70]])
if len(sliced_traj) == len(sliced_traj_from_structs):
self.assertTrue(all([sliced_traj[i] == sliced_traj_from_structs[i] for i in range(len(sliced_traj))]))
else:
self.assertTrue(False)
def test_slice(self):
sliced_traj = self.traj[2:99:3]
sliced_traj_from_structs = Trajectory.from_structures(self.structures[2:99:3])
if len(sliced_traj) == len(sliced_traj_from_structs):
self.assertTrue(all([sliced_traj[i] == sliced_traj_from_structs[i] for i in range(len(sliced_traj))]))
else:
self.assertTrue(False)
def test_extend(self):
traj = self.traj.copy()
# Case of compatible trajectories
compatible_traj = Trajectory.from_file(os.path.join(test_dir, "Traj_Combine_Test_XDATCAR_1"))
traj.extend(compatible_traj)
full_traj = Trajectory.from_file(os.path.join(test_dir, "Traj_Combine_Test_XDATCAR_Full"))
compatible_success = self._check_traj_equality(self.traj, full_traj)
# Case of incompatible trajectories
traj = self.traj.copy()
incompatible_traj = Trajectory.from_file(os.path.join(test_dir, "Traj_Combine_Test_XDATCAR_2"))
incompatible_test_success=False
try:
traj.extend(incompatible_traj)
except:
incompatible_test_success=True
self.assertTrue(compatible_success and incompatible_test_success)
def test_extend_frame_props(self):
lattice = [[1, 0, 0], [0, 1, 0], [0, 0, 1]]
species = ["Si", "Si"]
frac_coords = [
[[0, 0, 0], [0.5, 0.5, 0.5]],
[[0.1, 0.1, 0.1], [0.6, 0.6, 0.6]],
[[0.2, 0.2, 0.2], [0.7, 0.7, 0.7]],
]
# Trajectories with constant site properties
frame_properties_1 = {"energy": [-3, -3.9, -4.1]}
traj_1 = Trajectory(lattice, species, frac_coords, frame_properties=frame_properties_1)
frame_properties_2 = {"energy": [-4.2, -4.25, -4.3]}
traj_2 = Trajectory(lattice, species, frac_coords, frame_properties=frame_properties_2)
# Test combining two trajectories with similar site_properties
traj_combined = traj_1.copy()
traj_combined.extend(traj_2)
expected_frame_properties = {"energy": [-3, -3.9, -4.1, -4.2, -4.25, -4.3]}
self.assertEqual(traj_combined.frame_properties, expected_frame_properties)
# Mismatched frame propertied
frame_properties_3 = {"energy": [-4.2, -4.25, -4.3], "pressure": [2, 2.5, 2.5]}
traj_3 = Trajectory(lattice, species, frac_coords, frame_properties=frame_properties_3)
traj_combined = traj_1.copy()
traj_combined.extend(traj_3)
expected_frame_properties = {
"energy": [-3, -3.9, -4.1, -4.2, -4.25, -4.3],
"pressure": [None, None, None, 2, 2.5, 2.5],
}
self.assertEqual(traj_combined.frame_properties, expected_frame_properties)
def test_displacements(self):
poscar = Poscar.from_file(os.path.join(test_dir, "POSCAR"))
structures = [poscar.structure]
displacements = np.zeros((11, *np.shape(structures[-1].frac_coords)))
for i in range(10):
displacement = np.random.random_sample(np.shape(structures[-1].frac_coords)) / 20
new_coords = displacement + structures[-1].frac_coords
structures.append(Structure(structures[-1].lattice, structures[-1].species, new_coords))
displacements[i+1, :, :] = displacement
traj = Trajectory.from_structures(structures, constant_lattice=True)
traj.to_displacements()
self.assertTrue(np.allclose(traj.frac_coords, displacements))
def test_displacements(self):
poscar = Poscar.from_file(os.path.join(PymatgenTest.TEST_FILES_DIR, "POSCAR"))
structures = [poscar.structure]
displacements = np.zeros((11, *np.shape(structures[-1].frac_coords)))
for i in range(10):
displacement = np.random.random_sample(np.shape(structures[-1].frac_coords)) / 20
new_coords = displacement + structures[-1].frac_coords
structures.append(Structure(structures[-1].lattice, structures[-1].species, new_coords))
displacements[i + 1, :, :] = displacement
traj = Trajectory.from_structures(structures, constant_lattice=True)
traj.to_displacements()
self.assertTrue(np.allclose(traj.frac_coords, displacements))
def test_changing_lattice(self):
structure = self.structures[0]
# Generate structures with different lattices
structures = []
for i in range(10):
new_lattice = np.dot(structure.lattice.matrix, np.diag(1 + np.random.random_sample(3)/20))
temp_struct = structure.copy()
temp_struct.modify_lattice(Lattice(new_lattice))
structures.append(temp_struct)
traj = Trajectory.from_structures(structures, constant_lattice=False)
# Check if lattices were properly stored
self.assertTrue(
all([np.allclose(struct.lattice.matrix, structures[i].lattice.matrix) for i, struct in enumerate(traj)]))
def setUp(self):
xdatcar = Xdatcar(os.path.join(test_dir, "Traj_XDATCAR"))
self.traj = Trajectory.from_file(os.path.join(test_dir, "Traj_XDATCAR"))
self.structures = xdatcar.structures
def setUp(self):
xdatcar = Xdatcar(os.path.join(test_dir, "Traj_XDATCAR"))
self.traj = Trajectory.from_file(os.path.join(test_dir,
"Traj_XDATCAR"))
self.structures = xdatcar.structures
def test_to_from_dict(self):
d = self.traj.as_dict()
traj = Trajectory.from_dict(d)
self.assertEqual(type(traj), Trajectory)
def test_to_from_dict(self):
d = self.traj.as_dict()
traj = Trajectory.from_dict(d)
self.assertEqual(type(traj), Trajectory)
def insert_task(self,
task_doc,
parse_dos=False,
parse_bs=False,
md_structures=False):
"""
Inserts a task document (e.g., as returned by Drone.assimilate()) into the database.
Handles putting DOS and band structure into GridFS as needed.
Args:
task_doc: (dict) the task document
parse_dos: (bool) attempt to parse dos in task_doc and insert into Gridfs
parse_bs: (bool) attempt to parse bandstructure in task_doc and insert into Gridfs
Returns:
(int) - task_id of inserted document
"""
# insert dos into GridFS
if parse_dos and "calcs_reversed" in task_doc:
if "dos" in task_doc["calcs_reversed"][0]: # only store idx=0 DOS
dos = json.dumps(task_doc["calcs_reversed"][0]["dos"],
cls=MontyEncoder)
gfs_id, compression_type = self.insert_gridfs(dos, "dos_fs")
task_doc["calcs_reversed"][0][
"dos_compression"] = compression_type
task_doc["calcs_reversed"][0]["dos_fs_id"] = gfs_id
del task_doc["calcs_reversed"][0]["dos"]
# insert band structure into GridFS
if parse_bs and "calcs_reversed" in task_doc:
if "bandstructure" in task_doc["calcs_reversed"][
0]: # only store idx=0 BS
bs = json.dumps(task_doc["calcs_reversed"][0]["bandstructure"],
cls=MontyEncoder)
gfs_id, compression_type = self.insert_gridfs(
bs, "bandstructure_fs")
task_doc["calcs_reversed"][0][
"bandstructure_compression"] = compression_type
task_doc["calcs_reversed"][0]["bandstructure_fs_id"] = gfs_id
del task_doc["calcs_reversed"][0]["bandstructure"]
# insert structures at each ionic step into GridFS
if md_structures and "calcs_reversed" in task_doc:
# insert ionic steps into gridfs
#TODO: Depricate this and move to only storing trajectory
ionic_steps_json = json.dumps(
task_doc["calcs_reversed"][0]['output']['ionic_steps'],
cls=MontyEncoder)
gfs_id, compression_type = self.insert_gridfs(
ionic_steps_json, "structures_fs")
task_doc["calcs_reversed"][0]['output'][
'ionic_steps_compression'] = compression_type
task_doc["calcs_reversed"][0]['output'][
'ionic_steps_fs_id'] = gfs_id
# Aggregate a trajectory
## Convert from a list of dictionaries to a dictionary of lists
ionic_steps_dict = task_doc["calcs_reversed"][0]['output'][
'ionic_steps']
del task_doc["calcs_reversed"][0]['output']['ionic_steps']
ionic_steps_defaultdict = defaultdict(list)
for d in ionic_steps_dict:
for key, val in d.items():
ionic_steps_defaultdict[key].append(val)
ionic_steps = dict(ionic_steps_defaultdict.items())
## extract structures from dictionary
structures = [
Structure.from_dict(struct)
for struct in ionic_steps['structure']
]
del ionic_steps['structure']
frame_properties = {}
for key in [
'e_fr_energy', 'e_wo_entrp', 'e_0_energy', 'kinetic',
'lattice kinetic', 'nosepot', 'nosekinetic', 'total'
]:
frame_properties[key] = ionic_steps[key]
# Create trajectory
trajectory = Trajectory.from_structures(
structures,
constant_lattice=True,
frame_properties=frame_properties,
time_step=task_doc['input']['incar']['POTIM'])
traj_dict = json.dumps(trajectory.as_dict(), cls=MontyEncoder)
gfs_id, compression_type = self.insert_gridfs(
traj_dict, "trajectories_fs")
task_doc['trajectory'] = {
'formula': trajectory[0].composition.formula.replace(' ', ''),
'temperature': int(task_doc["input"]["incar"]["TEBEG"]),
'compression': compression_type,
'fs_id': gfs_id,
'dimension': list(np.shape(trajectory.frac_coords)),
'time_step': task_doc["input"]["incar"]["POTIM"],
}
# insert the task document and return task_id
return self.insert(task_doc)
def setUp(self):
xdatcar = Xdatcar(os.path.join(PymatgenTest.TEST_FILES_DIR, "Traj_XDATCAR"))
self.traj = Trajectory.from_file(os.path.join(PymatgenTest.TEST_FILES_DIR, "Traj_XDATCAR"))
self.structures = xdatcar.structures
def test_extend_inequivalent_site_props(self):
lattice = [[1, 0, 0], [0, 1, 0], [0, 0, 1]]
species = ["Si", "Si"]
frac_coords = [
[[0, 0, 0], [0.5, 0.5, 0.5]],
[[0.1, 0.1, 0.1], [0.6, 0.6, 0.6]],
[[0.2, 0.2, 0.2], [0.7, 0.7, 0.7]],
]
# Trajectories with constant site properties
site_properties_1 = [
{
"selective_dynamics": [[False, False, False], [False, False, False]],
"magmom": [5, 5],
}
]
traj_1 = Trajectory(lattice, species, frac_coords, site_properties=site_properties_1)
site_properties_2 = [
{
"selective_dynamics": [[True, True, True], [False, False, False]],
"magmom": [5, 5],
}
]
traj_2 = Trajectory(lattice, species, frac_coords, site_properties=site_properties_2)
# Test combining two trajectories with similar site_properties
traj_combined = traj_1.copy()
traj_combined.extend(traj_2)
expected_site_props = [
{
"selective_dynamics": [[False, False, False], [False, False, False]],
"magmom": [5, 5],
},
{
"selective_dynamics": [[False, False, False], [False, False, False]],
"magmom": [5, 5],
},
{
"selective_dynamics": [[False, False, False], [False, False, False]],
"magmom": [5, 5],
},
{
"selective_dynamics": [[True, True, True], [False, False, False]],
"magmom": [5, 5],
},
{
"selective_dynamics": [[True, True, True], [False, False, False]],
"magmom": [5, 5],
},
{
"selective_dynamics": [[True, True, True], [False, False, False]],
"magmom": [5, 5],
},
]
self.assertEqual(traj_combined.site_properties, expected_site_props)
# Trajectory with const site_properties and trajectory with changing site properties
site_properties_1 = [
{
"selective_dynamics": [[True, False, False], [False, False, False]],
"magmom": [5, 5],
}
]
traj_1 = Trajectory(lattice, species, frac_coords, site_properties=site_properties_1)
site_properties_2 = [
{
"selective_dynamics": [[False, True, True], [False, False, False]],
"magmom": [5, 5],
},
{
"selective_dynamics": [[True, False, True], [False, False, False]],
"magmom": [5, 5],
},
{
"selective_dynamics": [[True, True, False], [False, False, False]],
"magmom": [5, 5],
},
]
traj_2 = Trajectory(lattice, species, frac_coords, site_properties=site_properties_2)
# Test combining two trajectories with similar site_properties
traj_combined = traj_1.copy()
traj_combined.extend(traj_2)
expected_site_props = [
{
"selective_dynamics": [[True, False, False], [False, False, False]],
"magmom": [5, 5],
},
{
"selective_dynamics": [[True, False, False], [False, False, False]],
"magmom": [5, 5],
},
{
"selective_dynamics": [[True, False, False], [False, False, False]],
"magmom": [5, 5],
},
{
"selective_dynamics": [[False, True, True], [False, False, False]],
"magmom": [5, 5],
},
{
"selective_dynamics": [[True, False, True], [False, False, False]],
"magmom": [5, 5],
},
{
"selective_dynamics": [[True, True, False], [False, False, False]],
"magmom": [5, 5],
},
]
self.assertEqual(traj_combined.site_properties, expected_site_props)
# The other way around
traj_combined = traj_2.copy()
traj_combined.extend(traj_1)
expected_site_props = [
{
"selective_dynamics": [[False, True, True], [False, False, False]],
"magmom": [5, 5],
},
{
"selective_dynamics": [[True, False, True], [False, False, False]],
"magmom": [5, 5],
},
{
"selective_dynamics": [[True, True, False], [False, False, False]],
"magmom": [5, 5],
},
{
"selective_dynamics": [[True, False, False], [False, False, False]],
"magmom": [5, 5],
},
{
"selective_dynamics": [[True, False, False], [False, False, False]],
"magmom": [5, 5],
},
{
"selective_dynamics": [[True, False, False], [False, False, False]],
"magmom": [5, 5],
},
]
self.assertEqual(traj_combined.site_properties, expected_site_props)
# Trajectory with no and trajectory with changing site properties
site_properties_1 = None
traj_1 = Trajectory(lattice, species, frac_coords, site_properties=site_properties_1)
site_properties_2 = [
{
"selective_dynamics": [[False, True, True], [False, False, False]],
"magmom": [5, 5],
},
{
"selective_dynamics": [[True, False, True], [False, False, False]],
"magmom": [5, 5],
},
{
"selective_dynamics": [[True, True, False], [False, False, False]],
"magmom": [5, 5],
},
]
traj_2 = Trajectory(lattice, species, frac_coords, site_properties=site_properties_2)
# Test combining two trajectories with similar site_properties
traj_combined = traj_1.copy()
traj_combined.extend(traj_2)
expected_site_props = [
None,
None,
None,
{
"selective_dynamics": [[False, True, True], [False, False, False]],
"magmom": [5, 5],
},
{
"selective_dynamics": [[True, False, True], [False, False, False]],
"magmom": [5, 5],
},
{
"selective_dynamics": [[True, True, False], [False, False, False]],
"magmom": [5, 5],
},
]
self.assertEqual(traj_combined.site_properties, expected_site_props)
# The other way around
traj_combined = traj_2.copy()
traj_combined.extend(traj_1)
expected_site_props = [
{
"selective_dynamics": [[False, True, True], [False, False, False]],
"magmom": [5, 5],
},
{
"selective_dynamics": [[True, False, True], [False, False, False]],
"magmom": [5, 5],
},
{
"selective_dynamics": [[True, True, False], [False, False, False]],
"magmom": [5, 5],
},
None,
None,
None,
]
self.assertEqual(traj_combined.site_properties, expected_site_props)
'''
分析AIMD结果，计算MSD 和 conductivity
'''
import os
from pymatgen.core.trajectory import Trajectory
from pymatgen.io.vasp.outputs import Xdatcar
from pymatgen import Structure
from pymatgen.analysis.diffusion_analyzer import DiffusionAnalyzer
import numpy as np
import pickle
# 这一步是读取 XDATCAR，得到一系列结构信息
traj = Trajectory.from_file('XDATCAR')
# 这一步是实例化 DiffusionAnalyzer 的类
# 并用 from_structures 方法初始化这个类； 900 是温度，2 是POTIM 的值，1是间隔步数
# 间隔步数（step_skip）不太容易理解，但是根据官方教程:
# dt = timesteps * self.time_step * self.step_skip
diff = DiffusionAnalyzer.from_structures(traj,'Li',900,2,1)
# 可以用内置的 plot_msd 方法画出 MSD 图像
# 有些终端不能显示图像，这时候可以调用 export_msdt() 方法，得到数据后再自己作图
diff.plot_msd()
# 接下来直接得到 离子迁移率， 单位是 mS/cm
C = diff.conductivity
with open('result.dat','w') as f:
f.write('# AIMD result for Li-ion\n')
f.write('temp\tconductivity\n')
rc('text', usetex=True)
import matplotlib.pylab as pylab
params = {
'legend.fontsize': '15',
'figure.figsize': (7, 6),
'axes.labelsize': 20,
'axes.titlesize': 20,
'xtick.labelsize': 16,
'ytick.labelsize': 16
}
pylab.rcParams.update(params)
trajectory = Trajectory.from_file("./vasprun_md.xml")
trajectory.write_Xdatcar(filename='XDATCAR_temp')
images = read_vasp_xdatcar('XDATCAR_temp', index=None)
print("total number of frames: " + str(len(images)))
os.remove('./XDATCAR_temp')
reference_frame = read_vasp('./SPOSCAR')
desc = SOAP(species=[55, 51, 53],
rcut=6.0,
nmax=9,
lmax=9,
sigma=0.3,
periodic=True,
crossover=True,
sparse=False)
ref_features = desc.create(reference_frame)
