def test_write_poscar(self):
write_poscar(structure=self.structure,
filename=posixpath.join(self.file_location,
"POSCAR_test"))
test_atoms = read_atoms(
posixpath.join(self.file_location, "POSCAR_test"))
self.assertEqual(self.structure.get_chemical_formula(),
test_atoms.get_chemical_formula())
struct = self.structure.copy()
struct.add_tag(selective_dynamics=[True, True, True])
write_poscar(structure=struct,
filename=posixpath.join(self.file_location,
"POSCAR_test"))
test_atoms = read_atoms(
posixpath.join(self.file_location, "POSCAR_test"))
truth_array = np.empty_like(struct.positions, dtype=bool)
truth_array[:] = [True, True, True]
self.assertTrue(
np.array_equal(np.array(test_atoms.selective_dynamics.list()),
truth_array))
os.remove(posixpath.join(self.file_location, "POSCAR_test"))
struct = self.structure.copy()
struct.add_tag(selective_dynamics=[True, True, True])
write_poscar(structure=struct,
filename=posixpath.join(self.file_location,
"POSCAR_test"),
cartesian=False)
test_atoms_new = read_atoms(
posixpath.join(self.file_location, "POSCAR_test"))
self.assertEqual(test_atoms, test_atoms_new)
os.remove(posixpath.join(self.file_location, "POSCAR_test"))
def test_vasp_sorter(self):
write_poscar(structure=self.structure,
filename=posixpath.join(self.file_location,
"POSCAR_test"))
test_atoms = read_atoms(
posixpath.join(self.file_location, "POSCAR_test"))
vasp_order = vasp_sorter(self.structure)
self.assertEqual(len(self.structure), len(test_atoms))
self.assertEqual(self.structure[vasp_order], test_atoms)
os.remove(posixpath.join(self.file_location, "POSCAR_test"))
def setUpClass(cls):
cls.execution_path = os.path.dirname(os.path.abspath(__file__))
cls.project = Project(os.path.join(cls.execution_path, "test_vasp"))
cls.job = cls.project.create_job("Vasp", "trial")
cls.job_metadyn = cls.project.create_job("VaspMetadyn",
"trial_metadyn")
cls.job_complete = Vasp(
project=ProjectHDFio(project=cls.project,
file_name="vasp_complete"),
job_name="vasp_complete",
)
poscar_file = posixpath.join(
cls.execution_path,
"../static/vasp_test_files/full_job_sample/POSCAR")
cls.job_complete.structure = read_atoms(poscar_file,
species_from_potcar=True)
poscar_file = posixpath.join(
cls.execution_path,
"../static/vasp_test_files/poscar_samples/POSCAR_metadyn")
cls.job_metadyn.structure = read_atoms(poscar_file)
def setUpClass(cls):
cls.execution_path = os.path.dirname(os.path.abspath(__file__))
cls.project = Project(os.path.join(cls.execution_path, "test_vasp"))
cls.job = cls.project.create_job("Vasp", "trial")
cls.job_spin = cls.project.create_job("Vasp", "spin")
cls.job_spin.structure = CrystalStructure("Fe", BravaisBasis="bcc", a=2.83)
cls.job_spin.structure = cls.job_spin.structure.repeat(2)
cls.job_spin.structure[2] = "Se"
cls.job_spin.structure[3] = "O"
cls.job_metadyn = cls.project.create_job("VaspMetadyn", "trial_metadyn")
cls.job_complete = Vasp(
project=ProjectHDFio(project=cls.project, file_name="vasp_complete"),
job_name="vasp_complete",
)
poscar_file = posixpath.join(
cls.execution_path, "../static/vasp_test_files/full_job_sample/POSCAR"
)
cls.job_complete.structure = read_atoms(poscar_file, species_from_potcar=True)
poscar_file = posixpath.join(
cls.execution_path, "../static/vasp_test_files/poscar_samples/POSCAR_metadyn"
)
cls.job_metadyn.structure = read_atoms(poscar_file)
def test_manip_contcar(self):
for f in self.file_list:
if "CONTCAR_Mg" in f:
struct = read_atoms(f)
Mg_indices = struct.select_index("Mg")
add_pos = np.zeros_like(struct.positions)
max_Mg = np.argmax(struct.positions[Mg_indices, 2])
init_z = struct.positions[max_Mg, 2]
add_pos[np.argsort(vasp_sorter(struct))[max_Mg], 2] += 5.0
manip_contcar(filename=f,
new_filename="manip_file",
add_pos=add_pos)
new_struct = read_atoms("manip_file")
Mg_indices = new_struct.select_index("Mg")
max_Mg = np.argmax(new_struct.positions[Mg_indices, 2])
final_z = new_struct.positions[max_Mg, 2]
self.assertEqual(round(final_z - init_z, 3), 5.0)
os.remove("manip_file")
break
positions = np.ones((3, 3))
positions[0] = [5., 5., 5.]
positions[1] = [5., 5.7, 5.7]
positions[2] = [5., -5.7, -5.7]
struct = Atoms(["O", "H", "H"],
positions=positions,
cell=10. * np.eye(3))
write_poscar(structure=struct, filename="simple_water")
add_pos = np.zeros_like(positions)
poscar_order = np.argsort(vasp_sorter(struct))
add_pos[poscar_order[struct.select_index("O")], 2] += 3
manip_contcar("simple_water", "simple_water_new", add_pos)
new_struct = read_atoms("simple_water_new")
self.assertEqual(new_struct.positions[new_struct.select_index("O"), 2],
8)
os.remove("simple_water")
os.remove("simple_water_new")
def collect_output_log(self, dir_name="randSpgOut"):
"""
general purpose routine to extract output from logfile
Args:
file_name (str): output.log - optional
"""
self._lst_of_struct = [[
file_name.replace('-', '_'),
read_atoms(filename=posixpath.join(self.working_directory,
dir_name, file_name))
] for file_name in os.listdir(
posixpath.join(self.working_directory, dir_name))]
for structure_name, structure in self._lst_of_struct:
with self.project_hdf5.open("output/structures/" +
structure_name) as h5:
structure.to_hdf(h5)
def test_read_atoms(self):
for f in self.file_list:
atoms = read_atoms(filename=f)
self.assertIsInstance(atoms, Atoms)
if f.split("/")[-1] == "POSCAR_1":
self.assertEqual(len(atoms), 744)
self.assertEqual(len(atoms.select_index("H")), 432)
self.assertEqual(len(atoms.select_index("O")), 216)
self.assertEqual(len(atoms.select_index("Mg")), 96)
if f.split("/")[-1] == "POSCAR_scaled":
self.assertEqual(len(atoms), 256)
self.assertEqual(len(atoms.select_index("Cu")), 256)
cell = np.eye(3) * 4. * 3.63
self.assertTrue(np.array_equal(atoms.cell, cell))
self.assertEqual(atoms.get_spacegroup()["Number"], 225)
if f.split("/")[-1] == "POSCAR_volume_scaled":
self.assertEqual(len(atoms), 256)
self.assertEqual(len(atoms.select_index("Cu")), 256)
cell = np.eye(3) * 4. * 3.63
self.assertTrue(np.array_equal(atoms.cell, cell))
self.assertEqual(atoms.get_spacegroup()["Number"], 225)
if f.split("/")[-1] == "POSCAR_random":
self.assertEqual(len(atoms), 33)
self.assertEqual(len(atoms.selective_dynamics), 33)
self.assertEqual(len(atoms.select_index("Zn")), 1)
self.assertFalse(
np.array_equal(atoms.selective_dynamics[0],
[True, True, True]))
self.assertTrue(
np.array_equal(atoms.selective_dynamics[0],
[False, False, False]))
self.assertTrue(
np.array_equal(atoms.selective_dynamics[-5],
[True, True, True]))
self.assertTrue(
np.array_equal(atoms.selective_dynamics[-4],
[False, False, False]))
def test_read_atoms(self):
for f in self.file_list:
if f.split("/")[-1] == "POSCAR_velocity":
atoms, velocities = read_atoms(filename=f,
return_velocities=True)
self.assertEqual(len(atoms), 19)
self.assertEqual(np.shape(velocities), (19, 3))
self.assertEqual(len(atoms.selective_dynamics), 19)
self.assertEqual(len(atoms.select_index("Mg")), 10)
self.assertIsInstance(atoms.selective_dynamics, SparseList)
neon_indices = atoms.select_index("Ne")
hydrogen_indices = atoms.select_index("H")
oxygen_indices = atoms.select_index("O")
truth_array = np.empty_like(atoms.positions[neon_indices],
dtype=bool)
truth_array[:, :] = True
sel_dyn = np.array(atoms.selective_dynamics.list())
self.assertTrue(
np.array_equal(sel_dyn[neon_indices],
np.logical_not(truth_array)))
truth_array = np.empty_like(atoms.positions[oxygen_indices],
dtype=bool)
truth_array[:, :] = True
self.assertTrue(
np.array_equal(sel_dyn[oxygen_indices], truth_array))
truth_array = np.empty_like(atoms.positions[hydrogen_indices],
dtype=bool)
truth_array[:, :] = True
self.assertTrue(
np.array_equal(sel_dyn[hydrogen_indices], truth_array))
velocities_neon = np.zeros_like(
np.array(velocities)[neon_indices])
self.assertTrue(
np.array_equal(
np.array(velocities)[neon_indices], velocities_neon))
if f.split("/")[-1] == "POSCAR_no_species":
atoms = read_atoms(filename=f)
self.assertEqual(len(atoms), 33)
self.assertEqual(len(atoms.selective_dynamics), 33)
elif f.split("/")[-1] != "POSCAR_spoilt":
atoms = read_atoms(filename=f)
self.assertIsInstance(atoms, Atoms)
if f.split("/")[-1] == "POSCAR_1":
self.assertEqual(len(atoms), 744)
self.assertEqual(len(atoms.select_index("H")), 432)
self.assertEqual(len(atoms.select_index("O")), 216)
self.assertEqual(len(atoms.select_index("Mg")), 96)
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter("always")
atoms_new, velocities = read_atoms(
filename=f, return_velocities=True)
self.assertEqual(w[-1].category, UserWarning)
warning_string = "The velocities are either not available or they are incomplete/corrupted. " \
"Returning empty list instead"
self.assertEqual(str(w[-1].message), warning_string)
self.assertEqual(atoms_new, atoms)
self.assertEqual(velocities, list())
if f.split("/")[-1] == "POSCAR_scaled":
self.assertEqual(len(atoms), 256)
self.assertEqual(len(atoms.select_index("Cu")), 256)
cell = np.eye(3) * 4. * 3.63
self.assertTrue(np.array_equal(atoms.cell, cell))
self.assertEqual(atoms.get_spacegroup()["Number"], 225)
if f.split("/")[-1] == "POSCAR_volume_scaled":
self.assertEqual(len(atoms), 256)
self.assertEqual(len(atoms.select_index("Cu")), 256)
cell = np.eye(3) * 4. * 3.63
self.assertTrue(np.array_equal(atoms.cell, cell))
self.assertEqual(atoms.get_spacegroup()["Number"], 225)
if f.split("/")[-1] == "POSCAR_random":
self.assertEqual(len(atoms), 33)
self.assertEqual(len(atoms.selective_dynamics), 33)
self.assertEqual(len(atoms.select_index("Zn")), 1)
self.assertIsInstance(atoms.selective_dynamics, SparseList)
truth_array = np.empty_like(atoms.positions, dtype=bool)
truth_array[:] = [True, True, True]
truth_array[0] = [False, False, False]
truth_array[-4:] = [False, False, False]
self.assertTrue(
np.array_equal(atoms.selective_dynamics.list(),
truth_array))
