def get_eos_fits_dataframe(self, eos_names="murnaghan"):
"""
Fit energy as function of volume to get the equation of state,
equilibrium volume, bulk modulus and its derivative wrt to pressure.
Args:
eos_names: String or list of strings with EOS names.
For the list of available models, see pymatgen.analysis.eos.
Return:
(fits, dataframe) namedtuple.
fits is a list of ``EOSFit object``
dataframe is a |pandas-DataFrame| with the final results.
"""
# Read volumes and energies from the GSR files.
energies, volumes = [], []
for label, gsr in self.items():
energies.append(float(gsr.energy))
volumes.append(float(gsr.structure.volume))
# Order data by volumes if needed.
if np.any(np.diff(volumes) < 0):
ves = sorted(zip(volumes, energies), key=lambda t: t[0])
volumes = [t[0] for t in ves]
energies = [t[1] for t in ves]
# Note that eos.fit expects lengths in Angstrom, and energies in eV.
# I'm also monkey-patching the plot method.
from pymatgen.analysis.eos import EOS
if eos_names == "all":
# Use all the available models.
eos_names = [
n for n in EOS.MODELS
if n not in ("deltafactor", "numerical_eos")
]
else:
eos_names = list_strings(eos_names)
fits, index, rows = [], [], []
for eos_name in eos_names:
try:
fit = EOS(eos_name=eos_name).fit(volumes, energies)
except Exception as exc:
cprint("EOS %s raised exception:\n%s" % (eos_name, str(exc)))
continue
# Replace plot with plot_ax method
fit.plot = fit.plot_ax
fits.append(fit)
index.append(eos_name)
rows.append(
OrderedDict([(aname, getattr(fit, aname))
for aname in ("v0", "e0", "b0_GPa", "b1")]))
dataframe = pd.DataFrame(
rows, index=index, columns=list(rows[0].keys()) if rows else None)
return dict2namedtuple(fits=fits, dataframe=dataframe)
def get_eos_fits_dataframe(self, eos_names="murnaghan"):
"""
Fit energy as function of volume to get the equation of state,
equilibrium volume, bulk modulus and its derivative wrt to pressure.
Args:
eos_names: String or list of strings with EOS names.
For the list of available models, see pymatgen.analysis.eos.
Return:
(fits, dataframe) namedtuple.
fits is a list of ``EOSFit object``
dataframe is a |pandas-DataFrame| with the final results.
"""
# Read volumes and energies from the GSR files.
energies, volumes = [], []
for label, gsr in self.items():
energies.append(float(gsr.energy))
volumes.append(float(gsr.structure.volume))
# Order data by volumes if needed.
if np.any(np.diff(volumes) < 0):
ves = sorted(zip(volumes, energies), key=lambda t: t[0])
volumes = [t[0] for t in ves]
energies = [t[1] for t in ves]
# Note that eos.fit expects lengths in Angstrom, and energies in eV.
# I'm also monkey-patching the plot method.
from pymatgen.analysis.eos import EOS
if eos_names == "all":
# Use all the available models.
eos_names = [n for n in EOS.MODELS if n not in ("deltafactor", "numerical_eos")]
else:
eos_names = list_strings(eos_names)
fits, index, rows = [], [], []
for eos_name in eos_names:
try:
fit = EOS(eos_name=eos_name).fit(volumes, energies)
except Exception as exc:
cprint("EOS %s raised exception:\n%s" % (eos_name, str(exc)))
continue
# Replace plot with plot_ax method
fit.plot = fit.plot_ax
fits.append(fit)
index.append(eos_name)
rows.append(OrderedDict([(aname, getattr(fit, aname)) for aname in
("v0", "e0", "b0_GPa", "b1")]))
dataframe = pd.DataFrame(rows, index=index, columns=list(rows[0].keys()) if rows else None)
return dict2namedtuple(fits=fits, dataframe=dataframe)
def analyze_eos_flow(flow, **kwargs):
work = flow[0]
etotals = work.read_etotals(unit="eV")
eos_fit = EOS(eos_name="birch_murnaghan").fit(flow.volumes, etotals)
return eos_fit.plot(**kwargs)
