def setUp(self):
os.chdir(test_dir)
self.cohp_bise = Cohpcar(filename="COHPCAR.lobster.BiSe")
self.coop_bise = Cohpcar(filename="COOPCAR.lobster.BiSe",
are_coops=True)
self.cohp_fe = Cohpcar()
self.coop_fe = Cohpcar(are_coops=True)
def setUp(self):
self.cohp_bise = Cohpcar(
filename=os.path.join(test_dir, "COHPCAR.lobster.BiSe"))
self.coop_bise = Cohpcar(filename=os.path.join(test_dir,
"COOPCAR.lobster.BiSe"),
are_coops=True)
self.cohp_fe = Cohpcar(
filename=os.path.join(test_dir, "COOPCAR.lobster"))
self.coop_fe = Cohpcar(filename=os.path.join(test_dir,
"COOPCAR.lobster"),
are_coops=True)
self.orb = Cohpcar(
filename=os.path.join(test_dir, "COHPCAR.lobster.orbitalwise"))
self.orb_notot = Cohpcar(filename=os.path.join(
test_dir, "COHPCAR.lobster.notot.orbitalwise"))
# Lobster 3.1 (Test data is from prerelease of Lobster 3.1)
self.cohp_KF = Cohpcar(
filename=os.path.join(test_dir, "COHPCAR.lobster.KF"))
self.coop_KF = Cohpcar(filename=os.path.join(test_dir,
"COHPCAR.lobster.KF"),
are_coops=True)
# example with f electrons
self.cohp_Na2UO4 = Cohpcar(
filename=os.path.join(test_dir, "COHPCAR.lobster.Na2UO4"))
self.coop_Na2UO4 = Cohpcar(filename=os.path.join(
test_dir, "COOPCAR.lobster.Na2UO4"),
are_coops=True)
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)
from pymatgen.electronic_structure.cohp import Cohp
from pymatgen.electronic_structure.plotter import CohpPlotter
from pymatgen.io.lobster import Cohpcar
COHPCAR_path = "E:/Python/pymatgen-master/test_files/cohp/COHPCAR.lobster"
cohpcar = Cohpcar(filename=COHPCAR_path)
cdata = cohpcar.cohp_data
cdata_processed = {}
#测试上传是否成功
for key in cdata:
c = cdata[key]
c["efermi"] = 0
c["energies"] = cohpcar.energies
c["are_coops"] = False
cdata_processed[key] = Cohp.from_dict(c)
cp = CohpPlotter()
cp.add_cohp_dict(cdata_processed)
x = cp.get_plot()
x.ylim([-6, 6])
x.show()
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 cannot be handled yet.
are_coops = False
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"
cohp_file = Cohpcar(filename=filename, are_coops=are_coops)
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.
if fmt == "LOBSTER":
energies += efermi
if fmt == "LMTO":
# Calculate the average COHP for the LMTO file to be
# consistent with LOBSTER output.
spins = [Spin.up, Spin.down] if cohp_file.is_spin_polarized \
else [Spin.up]
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(["{:.5g}".format(a) 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)