def parse_value(value, unit=None, value_unit=None):
""" Converts a float/str to proper value """
if isinstance(value, str):
value, value_unit = value.split()
if len(value_unit) == 0:
value_unit = None
if value_unit is None:
value_unit = unit
value = float(value)
# Now parse unit
if unit == value_unit:
return value
return value * units(value_unit, unit)
def __call__(dos_self, parser, ns, value, option_string=None):
import matplotlib.pyplot as plt
if not hasattr(ns, '_weight'):
# Try and read in the k-point-weights
ns._weight = kpSileSiesta(
str(self.file).replace('EIG', 'KP')).read_data()[1]
if ns._Emap is None:
# We will plot the DOS in the entire energy window
ns._Emap = [ns._eigs.min(), ns._eigs.max()]
if len(ns._weight) != ns._eigs.shape[1]:
raise SileError(
str(self) +
' --dos the number of k-points for the eigenvalues and k-point weights '
'are different, please use --weight correctly.')
# Specify default settings
dE = 0.005 # 5 meV
kT = units('K', 'eV') * 300
distr = get_distribution('gaussian', smearing=kT)
out = None
if len(value) > 0:
i = 0
try:
dE = float(value[i])
i += 1
except:
pass
try:
kT = float(value[i])
i += 1
except:
pass
try:
distr = get_distribution(value[i], smearing=kT)
i += 1
except:
pass
try:
out = value[i]
except:
pass
# Now we are ready to process
E = np.arange(ns._Emap[0] - kT * 4, ns._Emap[1] + kT * 4, dE)
def myplot(ax, legend, E, eig, w):
DOS = np.zeros(len(E))
for ib in range(eig.shape[0]):
for e in eig[ib, :]:
DOS += distr(E - e) * w[ib]
ax.plot(E, DOS, label=legend)
ax.set_ylim(0, None)
plt.figure()
ax = plt.gca()
ax.set_title('DOS kT={:.1f} K'.format(kT * units('eV', 'K')))
ax.set_xlabel('E - Ef [eV]')
ax.set_xlim(E.min(), E.max())
ax.set_ylabel('DOS [1/eV]')
if ns._eigs.shape[0] == 2:
for i, ud in enumerate(['up', 'down']):
myplot(ax, ud, E, ns._eigs[i, :, :], ns._weight)
plt.legend()
else:
myplot(ax, '', E, ns._eigs[0, :, :], ns._weight)
if out is None:
plt.show()
else:
plt.savefig(out)
