def __init__(self, filename="COPL", to_eV=False):
# COPL files have an extra trailing blank line
with zopen(filename, "rt") as f:
contents = f.read().split("\n")[:-1]
# The parameters line is the second line in a COPL file. It
# contains all parameters that are needed to map the file.
parameters = contents[1].split()
num_bonds = int(parameters[0])
if int(parameters[1]) == 2:
spins = [Spin.up, Spin.down]
self.is_spin_polarized = True
else:
spins = [Spin.up]
self.is_spin_polarized = False
# The COHP data start in row num_bonds + 3
data = np.array([np.array(row.split(), dtype=float)
for row in contents[num_bonds+2:]]).transpose()
if to_eV:
# LMTO energies have 5 sig figs
self.energies = np.array([round_to_sigfigs(energy, 5)
for energy in data[0] * Ry_to_eV],
dtype=float)
self.efermi = round_to_sigfigs(float(parameters[-1])*Ry_to_eV, 5)
else:
self.energies = data[0]
self.efermi = float(parameters[-1])
cohp_data = {}
for bond in range(num_bonds):
label, length, sites = self._get_bond_data(contents[2+bond])
cohp = {spin: data[2*(bond+s*num_bonds)+1]
for s, spin in enumerate(spins)}
if to_eV:
icohp = {spin: np.array([round_to_sigfigs(i, 5) for i in
data[2*(bond+s*num_bonds)+2] * Ry_to_eV])
for s, spin in enumerate(spins)}
else:
icohp = {spin: data[2*(bond+s*num_bonds)+2]
for s, spin in enumerate(spins)}
# This takes care of duplicate labels
if label in cohp_data:
i = 1
lab = "%s-%d" % (label, i)
while lab in cohp_data:
i += 1
lab = "%s-%d" % (label, i)
label = lab
cohp_data[label] = {"COHP": cohp, "ICOHP": icohp,
"length": length, "sites": sites}
self.cohp_data = cohp_data
def test_energies(self):
self.assertEqual(self.copl_bise.efermi, -0.17223)
self.assertEqual(self.copl_bise_eV.efermi, -2.3433)
self.assertEqual(self.copl_fe.efermi, -0.085683)
ener_eV = np.array([round_to_sigfigs(energy, 5)
for energy in self.copl_bise.energies * Ry_to_eV],
dtype=float)
self.assertArrayEqual(ener_eV, self.copl_bise_eV.energies)
copl_icohp = self.copl_bise.cohp_data["Bi1-Se7"]["ICOHP"][Spin.up]
icohp = np.array([round_to_sigfigs(i, 5)
for i in copl_icohp * Ry_to_eV],
dtype=float)
icohp_eV = self.copl_bise_eV.cohp_data["Bi1-Se7"]["ICOHP"][Spin.up]
self.assertArrayEqual(icohp, icohp_eV)
def test_energies(self):
self.assertEqual(self.copl_bise.efermi, -0.17223)
self.assertEqual(self.copl_bise_eV.efermi, -2.3433)
self.assertEqual(self.copl_fe.efermi, -0.085683)
ener_eV = np.array([
round_to_sigfigs(energy, 5)
for energy in self.copl_bise.energies * Ry_to_eV
],
dtype=float)
self.assertArrayEqual(ener_eV, self.copl_bise_eV.energies)
copl_icohp = self.copl_bise.cohp_data["Bi1-Se7"]["ICOHP"][Spin.up]
icohp = np.array(
[round_to_sigfigs(i, 5) for i in copl_icohp * Ry_to_eV],
dtype=float)
icohp_eV = self.copl_bise_eV.cohp_data["Bi1-Se7"]["ICOHP"][Spin.up]
self.assertArrayEqual(icohp, icohp_eV)
def test_round(self):
vals = [
424.2425, 2.3425356, 0.000042535636653, 0.23, 2.468e6, 0, -1.392156
]
sigfigs = range(1, 6)
rounded_vals = [[400.0, 420.0, 424.0, 424.2, 424.24],
[2.0, 2.3, 2.34, 2.343, 2.3425],
[4e-5, 4.3e-5, 4.25e-5, 4.254e-5, 4.2536e-5],
[0.2, 0.23, 0.23, 0.23, 0.23],
[2e6, 2.5e6, 2.47e6, 2.468e6, 2.468e6],
[0, 0, 0, 0, 0], [-1, -1.4, -1.39, -1.392, -1.3922]]
for v, val in enumerate(vals):
for s, sig in enumerate(sigfigs):
self.assertEqual(round_to_sigfigs(val, sig),
rounded_vals[v][s])
with self.assertRaises(ValueError):
round_to_sigfigs(3.5, -2)
with self.assertRaises(TypeError):
round_to_sigfigs(3.5, 3.5)
def test_round(self):
vals = [424.2425, 2.3425356, 0.000042535636653,
0.23, 2.468e6, 0, -1.392156]
sigfigs = range(1, 6)
rounded_vals = [[400.0, 420.0, 424.0, 424.2, 424.24],
[2.0, 2.3, 2.34, 2.343, 2.3425],
[4e-5, 4.3e-5, 4.25e-5, 4.254e-5, 4.2536e-5],
[0.2, 0.23, 0.23, 0.23, 0.23],
[2e6, 2.5e6, 2.47e6, 2.468e6, 2.468e6],
[0, 0, 0, 0, 0],
[-1, -1.4, -1.39, -1.392, -1.3922]]
for v, val in enumerate(vals):
for s, sig in enumerate(sigfigs):
self.assertEqual(round_to_sigfigs(val, sig),
rounded_vals[v][s])
with self.assertRaises(ValueError):
round_to_sigfigs(3.5, -2)
with self.assertRaises(TypeError):
round_to_sigfigs(3.5, 3.5)
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 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"
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.
for label in orb_res_cohp:
if cohp_file.cohp_data[label]["COHP"] is None:
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)
