def test_post_distdiff(self):
feff_dict_input = FEFFDictSet.from_directory(
os.path.join(PymatgenTest.TEST_FILES_DIR, "feff_dist_test"))
self.assertTrue(feff_dict_input.tags == Tags.from_file(
os.path.join(PymatgenTest.TEST_FILES_DIR,
"feff_dist_test/feff.inp")))
self.assertTrue(
str(feff_dict_input.header()) == str(
Header.from_file(
os.path.join(PymatgenTest.TEST_FILES_DIR,
"feff_dist_test/HEADER"))))
feff_dict_input.write_input("feff_dist_regen")
origin_tags = Tags.from_file(
os.path.join(PymatgenTest.TEST_FILES_DIR,
"feff_dist_test/PARAMETERS"))
output_tags = Tags.from_file(
os.path.join(".", "feff_dist_regen/PARAMETERS"))
origin_mole = Atoms.cluster_from_file(
os.path.join(PymatgenTest.TEST_FILES_DIR,
"feff_dist_test/feff.inp"))
output_mole = Atoms.cluster_from_file(
os.path.join(".", "feff_dist_regen/feff.inp"))
original_mole_dist = np.array(
origin_mole.distance_matrix[0, :]).astype(np.float64)
output_mole_dist = np.array(output_mole.distance_matrix[0, :]).astype(
np.float64)
original_mole_shell = [x.species_string for x in origin_mole]
output_mole_shell = [x.species_string for x in output_mole]
self.assertTrue(np.allclose(original_mole_dist, output_mole_dist))
self.assertTrue(origin_tags == output_tags)
self.assertTrue(original_mole_shell == output_mole_shell)
shutil.rmtree(os.path.join(".", "feff_dist_regen"))
def test_cluster_from_file(self):
self.atoms.write_file("ATOMS_test")
mol_1 = Atoms.cluster_from_file("ATOMS_test")
mol_2 = Atoms.cluster_from_file(os.path.join(test_dir, "ATOMS"))
self.assertEqual(mol_1.formula, mol_2.formula)
self.assertEqual(len(mol_1), len(mol_2))
os.remove("ATOMS_test")
def test_cluster_from_file(self):
self.atoms.write_file("ATOMS_test")
mol_1 = Atoms.cluster_from_file("ATOMS_test")
mol_2 = Atoms.cluster_from_file(os.path.join(test_dir, "ATOMS"))
self.assertEqual(mol_1.formula, mol_2.formula)
self.assertEqual(len(mol_1), len(mol_2))
os.remove("ATOMS_test")
def test_cluster_from_file(self):
self.atoms.write_file("ATOMS_test")
mol_1 = Atoms.cluster_from_file("ATOMS_test")
mol_2 = Atoms.cluster_from_file(
os.path.join(PymatgenTest.TEST_FILES_DIR, "ATOMS"))
self.assertEqual(mol_1.formula, mol_2.formula)
self.assertEqual(len(mol_1), len(mol_2))
os.remove("ATOMS_test")
def test_postfeffset(self):
self.mp_xanes.write_input(os.path.join(".", "xanes_3"))
feff_dict_input = FEFFDictSet.from_directory(os.path.join(".", "xanes_3"))
self.assertTrue(
feff_dict_input.tags
== Tags.from_file(os.path.join(".", "xanes_3/feff.inp"))
)
self.assertTrue(
str(feff_dict_input.header())
== str(Header.from_file(os.path.join(".", "xanes_3/HEADER")))
)
feff_dict_input.write_input("xanes_3_regen")
origin_tags = Tags.from_file(os.path.join(".", "xanes_3/PARAMETERS"))
output_tags = Tags.from_file(os.path.join(".", "xanes_3_regen/PARAMETERS"))
origin_mole = Atoms.cluster_from_file(os.path.join(".", "xanes_3/feff.inp"))
output_mole = Atoms.cluster_from_file(
os.path.join(".", "xanes_3_regen/feff.inp")
)
original_mole_dist = np.array(origin_mole.distance_matrix[0, :]).astype(
np.float64
)
output_mole_dist = np.array(output_mole.distance_matrix[0, :]).astype(
np.float64
)
original_mole_shell = [x.species_string for x in origin_mole]
output_mole_shell = [x.species_string for x in output_mole]
self.assertTrue(np.allclose(original_mole_dist, output_mole_dist))
self.assertTrue(origin_tags == output_tags)
self.assertTrue(original_mole_shell == output_mole_shell)
shutil.rmtree(os.path.join(".", "xanes_3"))
shutil.rmtree(os.path.join(".", "xanes_3_regen"))
reci_mp_xanes = MPXANESSet(
self.absorbing_atom, self.structure, user_tag_settings={"RECIPROCAL": ""}
)
reci_mp_xanes.write_input("xanes_reci")
feff_reci_input = FEFFDictSet.from_directory(os.path.join(".", "xanes_reci"))
self.assertTrue("RECIPROCAL" in feff_reci_input.tags)
feff_reci_input.write_input("Dup_reci")
self.assertTrue(os.path.exists(os.path.join(".", "Dup_reci", "HEADER")))
self.assertTrue(os.path.exists(os.path.join(".", "Dup_reci", "feff.inp")))
self.assertTrue(os.path.exists(os.path.join(".", "Dup_reci", "PARAMETERS")))
self.assertFalse(os.path.exists(os.path.join(".", "Dup_reci", "ATOMS")))
self.assertFalse(os.path.exists(os.path.join(".", "Dup_reci", "POTENTIALS")))
tags_original = Tags.from_file(os.path.join(".", "xanes_reci/feff.inp"))
tags_output = Tags.from_file(os.path.join(".", "Dup_reci/feff.inp"))
self.assertTrue(tags_original == tags_output)
stru_orig = Structure.from_file(os.path.join(".", "xanes_reci/Co2O2.cif"))
stru_reci = Structure.from_file(os.path.join(".", "Dup_reci/Co2O2.cif"))
self.assertTrue(stru_orig.__eq__(stru_reci))
shutil.rmtree(os.path.join(".", "Dup_reci"))
shutil.rmtree(os.path.join(".", "xanes_reci"))
def test_cluster_from_file(self):
r = CifParser(os.path.join(test_dir, "CoO19128.cif"))
structure = r.get_structures()[0]
atoms = Atoms(structure, "O", 10.0)
atoms.write_file("ATOMS_test")
mol_1 = Atoms.cluster_from_file("ATOMS_test")
mol_2 = Atoms.cluster_from_file(os.path.join(test_dir, "ATOMS"))
self.assertEqual(mol_1.formula, mol_2.formula)
self.assertEqual(len(mol_1), len(mol_2))
os.remove("ATOMS_test")
def test_cluster_from_file(self):
r = CifParser(os.path.join(test_dir, "CoO19128.cif"))
structure = r.get_structures()[0]
atoms = Atoms(structure, "O", 10.0)
atoms.write_file("ATOMS_test")
mol_1 = Atoms.cluster_from_file("ATOMS_test")
mol_2 = Atoms.cluster_from_file(os.path.join(test_dir, "ATOMS"))
self.assertEqual(mol_1.formula, mol_2.formula)
self.assertEqual(len(mol_1), len(mol_2))
os.remove("ATOMS_test")
def test_setup(self):
with cd(test_dir):
with ScratchDir('.', copy_from_current_on_enter=True):
f = FeffJob("hello", backup=True)
f.setup()
parameter = Tags.from_file('feff.inp')
parameter_orig = Tags.from_file('feff.inp.orig')
self.assertEqual(parameter, parameter_orig)
atom = Atoms.cluster_from_file('feff.inp')
atom_origin = Atoms.cluster_from_file('feff.inp.orig')
self.assertEqual(atom, atom_origin)
def test_setup(self):
with cd(test_dir):
with ScratchDir('.', copy_from_current_on_enter=True):
f = FeffJob("hello", backup=True)
f.setup()
parameter = Tags.from_file('feff.inp')
parameter_orig = Tags.from_file('feff.inp.orig')
self.assertEqual(parameter, parameter_orig)
atom = Atoms.cluster_from_file('feff.inp')
atom_origin = Atoms.cluster_from_file('feff.inp.orig')
self.assertEqual(atom, atom_origin)
def test_postfeffset(self):
self.mp_xanes.write_input(os.path.join('.', 'xanes_3'))
feff_dict_input = FEFFDictSet.from_directory(os.path.join('.', 'xanes_3'))
self.assertTrue(feff_dict_input.tags == Tags.from_file(os.path.join('.', 'xanes_3/feff.inp')))
self.assertTrue(str(feff_dict_input.header()) == str(Header.from_file(os.path.join('.', 'xanes_3/HEADER'))))
feff_dict_input.write_input('xanes_3_regen')
origin_tags = Tags.from_file(os.path.join('.', 'xanes_3/PARAMETERS'))
output_tags = Tags.from_file(os.path.join('.', 'xanes_3_regen/PARAMETERS'))
origin_mole = Atoms.cluster_from_file(os.path.join('.', 'xanes_3/feff.inp'))
output_mole = Atoms.cluster_from_file(os.path.join('.', 'xanes_3_regen/feff.inp'))
original_mole_dist = np.array(origin_mole.distance_matrix[0, :]).astype(np.float64)
output_mole_dist = np.array(output_mole.distance_matrix[0, :]).astype(np.float64)
original_mole_shell = [x.species_string for x in origin_mole]
output_mole_shell = [x.species_string for x in output_mole]
self.assertTrue(np.allclose(original_mole_dist, output_mole_dist))
self.assertTrue(origin_tags == output_tags)
self.assertTrue(original_mole_shell == output_mole_shell)
shutil.rmtree(os.path.join('.', 'xanes_3'))
shutil.rmtree(os.path.join('.', 'xanes_3_regen'))
reci_mp_xanes = MPXANESSet(self.absorbing_atom, self.structure,
user_tag_settings={"RECIPROCAL": ""})
reci_mp_xanes.write_input('xanes_reci')
feff_reci_input = FEFFDictSet.from_directory(os.path.join('.', 'xanes_reci'))
self.assertTrue("RECIPROCAL" in feff_reci_input.tags)
feff_reci_input.write_input('Dup_reci')
self.assertTrue(os.path.exists(os.path.join('.', 'Dup_reci', 'HEADER')))
self.assertTrue(os.path.exists(os.path.join('.', 'Dup_reci', 'feff.inp')))
self.assertTrue(os.path.exists(os.path.join('.', 'Dup_reci', 'PARAMETERS')))
self.assertFalse(os.path.exists(os.path.join('.', 'Dup_reci', 'ATOMS')))
self.assertFalse(os.path.exists(os.path.join('.', 'Dup_reci', 'POTENTIALS')))
tags_original = Tags.from_file(os.path.join('.', 'xanes_reci/feff.inp'))
tags_output = Tags.from_file(os.path.join('.', 'Dup_reci/feff.inp'))
self.assertTrue(tags_original == tags_output)
stru_orig = Structure.from_file(os.path.join('.', 'xanes_reci/Co2O2.cif'))
stru_reci = Structure.from_file(os.path.join('.', 'Dup_reci/Co2O2.cif'))
self.assertTrue(stru_orig.__eq__(stru_reci))
shutil.rmtree(os.path.join('.', 'Dup_reci'))
shutil.rmtree(os.path.join('.', 'xanes_reci'))
def from_directory(input_dir):
"""
Read in a set of FEFF input files from a directory, which is
useful when existing FEFF input needs some adjustment.
"""
sub_d = {}
for fname, ftype in [("HEADER", Header), ("PARAMETERS", Tags)]:
fullzpath = zpath(os.path.join(input_dir, fname))
sub_d[fname.lower()] = ftype.from_file(fullzpath)
# Generation of FEFFDict set requires absorbing atom, need to search
# the index of absorption atom in the structure according to the
# distance matrix and shell species information contained in feff.inp
absorber_index = []
radius = None
feffinp = zpath(os.path.join(input_dir, 'feff.inp'))
if "RECIPROCAL" not in sub_d["parameters"]:
input_atoms = Atoms.cluster_from_file(feffinp)
shell_species = np.array([x.species_string for x in input_atoms])
# First row of distance matrix represents the distance from the absorber to
# the rest atoms
distance_matrix = input_atoms.distance_matrix[0, :]
# Get radius value
from math import ceil
radius = int(ceil(input_atoms.get_distance(input_atoms.index(input_atoms[0]),
input_atoms.index(input_atoms[-1]))))
for site_index, site in enumerate(sub_d['header'].struct):
if site.specie == input_atoms[0].specie:
site_atoms = Atoms(sub_d['header'].struct, absorbing_atom=site_index,
radius=radius)
site_distance = np.array(site_atoms.get_lines())[:, 5].astype(np.float64)
site_shell_species = np.array(site_atoms.get_lines())[:, 4]
shell_overlap = min(shell_species.shape[0], site_shell_species.shape[0])
if np.allclose(distance_matrix[:shell_overlap], site_distance[:shell_overlap]) and \
np.all(site_shell_species[:shell_overlap] == shell_species[:shell_overlap]):
absorber_index.append(site_index)
if "RECIPROCAL" in sub_d["parameters"]:
absorber_index = sub_d["parameters"]["TARGET"]
absorber_index[0] = int(absorber_index[0]) - 1
# Generate the input set
if 'XANES' in sub_d["parameters"]:
CONFIG = loadfn(os.path.join(MODULE_DIR, "MPXANESSet.yaml"))
if radius is None:
radius = 10
return FEFFDictSet(absorber_index[0], sub_d['header'].struct, radius=radius,
config_dict=CONFIG, edge=sub_d["parameters"]["EDGE"],
nkpts=1000, user_tag_settings=sub_d["parameters"])
def from_directory(input_dir):
"""
Read in a set of FEFF input files from a directory, which is
useful when existing FEFF input needs some adjustment.
"""
sub_d = {}
for fname, ftype in [("HEADER", Header), ("PARAMETERS", Tags)]:
fullzpath = zpath(os.path.join(input_dir, fname))
sub_d[fname.lower()] = ftype.from_file(fullzpath)
# Generation of FEFFDict set requires absorbing atom, need to search
# the index of absorption atom in the structure according to the
# distance matrix and shell species information contained in feff.inp
absorber_index = []
radius = None
feffinp = zpath(os.path.join(input_dir, 'feff.inp'))
if "RECIPROCAL" not in sub_d["parameters"]:
input_atoms = Atoms.cluster_from_file(feffinp)
shell_species = np.array([x.species_string for x in input_atoms])
# First row of distance matrix represents the distance from the absorber to
# the rest atoms
distance_matrix = input_atoms.distance_matrix[0, :]
# Get radius value
from math import ceil
radius = int(ceil(input_atoms.get_distance(input_atoms.index(input_atoms[0]),
input_atoms.index(input_atoms[-1]))))
for site_index, site in enumerate(sub_d['header'].struct):
if site.specie == input_atoms[0].specie:
site_atoms = Atoms(sub_d['header'].struct, absorbing_atom=site_index,
radius=radius)
site_distance = np.array(site_atoms.get_lines())[:, 5].astype(np.float64)
site_shell_species = np.array(site_atoms.get_lines())[:, 4]
shell_overlap = min(shell_species.shape[0], site_shell_species.shape[0])
if np.allclose(distance_matrix[:shell_overlap], site_distance[:shell_overlap]) and \
np.all(site_shell_species[:shell_overlap] == shell_species[:shell_overlap]):
absorber_index.append(site_index)
if "RECIPROCAL" in sub_d["parameters"]:
absorber_index = sub_d["parameters"]["TARGET"]
absorber_index[0] = int(absorber_index[0]) - 1
# Generate the input set
if 'XANES' in sub_d["parameters"]:
CONFIG = loadfn(os.path.join(MODULE_DIR, "MPXANESSet.yaml"))
if radius is None:
radius = 10
return FEFFDictSet(absorber_index[0], sub_d['header'].struct, radius=radius,
config_dict=CONFIG, edge=sub_d["parameters"]["EDGE"],
nkpts=1000, user_tag_settings=sub_d["parameters"])
def test_post_distdiff(self):
feff_dict_input = FEFFDictSet.from_directory(os.path.join(test_dir, 'feff_dist_test'))
self.assertTrue(feff_dict_input.tags == Tags.from_file(os.path.join(test_dir, 'feff_dist_test/feff.inp')))
self.assertTrue(
str(feff_dict_input.header()) == str(Header.from_file(os.path.join(test_dir, 'feff_dist_test/HEADER'))))
feff_dict_input.write_input('feff_dist_regen')
origin_tags = Tags.from_file(os.path.join(test_dir, 'feff_dist_test/PARAMETERS'))
output_tags = Tags.from_file(os.path.join('.', 'feff_dist_regen/PARAMETERS'))
origin_mole = Atoms.cluster_from_file(os.path.join(test_dir, 'feff_dist_test/feff.inp'))
output_mole = Atoms.cluster_from_file(os.path.join('.', 'feff_dist_regen/feff.inp'))
original_mole_dist = np.array(origin_mole.distance_matrix[0, :]).astype(np.float64)
output_mole_dist = np.array(output_mole.distance_matrix[0, :]).astype(np.float64)
original_mole_shell = [x.species_string for x in origin_mole]
output_mole_shell = [x.species_string for x in output_mole]
self.assertTrue(np.allclose(original_mole_dist, output_mole_dist))
self.assertTrue(origin_tags == output_tags)
self.assertTrue(original_mole_shell == output_mole_shell)
shutil.rmtree(os.path.join('.', 'feff_dist_regen'))
def run_task(self, fw_spec):
calc_dir = os.getcwd()
if "calc_dir" in self:
calc_dir = self["calc_dir"]
elif self.get("calc_loc"):
calc_dir = get_calc_loc(self["calc_loc"],
fw_spec["calc_locs"])["path"]
logger.info("PARSING DIRECTORY: {}".format(calc_dir))
db_file = env_chk(self.get('db_file'), fw_spec)
cluster_dict = None
tags = Tags.from_file(filename="feff.inp")
if "RECIPROCAL" not in tags:
cluster_dict = Atoms.cluster_from_file("feff.inp").as_dict()
doc = {
"input_parameters":
tags.as_dict(),
"cluster":
cluster_dict,
"structure":
self["structure"].as_dict(),
"absorbing_atom":
self["absorbing_atom"],
"spectrum_type":
self["spectrum_type"],
"spectrum":
np.loadtxt(os.path.join(calc_dir, self["output_file"])).tolist(),
"edge":
self.get("edge", None),
"metadata":
self.get("metadata", None),
"dir_name":
os.path.abspath(os.getcwd()),
"last_updated":
datetime.utcnow()
}
if not db_file:
with open("feff_task.json", "w") as f:
f.write(json.dumps(doc, default=DATETIME_HANDLER))
else:
db = FeffCalcDb.from_db_file(db_file, admin=True)
db.insert(doc)
logger.info("Finished parsing the spectrum")
return FWAction(stored_data={"task_id": doc.get("task_id", None)})
def run_task(self, fw_spec):
calc_dir = os.getcwd()
if "calc_dir" in self:
calc_dir = self["calc_dir"]
elif self.get("calc_loc"):
calc_dir = get_calc_loc(self["calc_loc"], fw_spec["calc_locs"])["path"]
logger.info("PARSING DIRECTORY: {}".format(calc_dir))
db_file = env_chk(self.get('db_file'), fw_spec)
cluster_dict = None
tags = Tags.from_file(filename="feff.inp")
if "RECIPROCAL" not in tags:
cluster_dict = Atoms.cluster_from_file("feff.inp").as_dict()
doc = {"input_parameters": tags.as_dict(),
"cluster": cluster_dict,
"structure": self["structure"].as_dict(),
"absorbing_atom": self["absorbing_atom"],
"spectrum_type": self["spectrum_type"],
"spectrum": np.loadtxt(os.path.join(calc_dir, self["output_file"])).tolist(),
"edge": self.get("edge", None),
"metadata": self.get("metadata", None),
"dir_name": os.path.abspath(os.getcwd()),
"last_updated": datetime.today()}
if not db_file:
with open("feff_task.json", "w") as f:
f.write(json.dumps(doc, default=DATETIME_HANDLER))
# db insertion
else:
db = MMFeffDb.from_db_file(db_file, admin=True)
db.insert(doc)
logger.info("Finished parsing the spectrum")
return FWAction(stored_data={"task_id": doc.get("task_id", None)})
