def banddos(pref='',storedir=None):
ru=str("vasprun.xml")
kpfile=str("KPOINTS")
run = Vasprun(ru, parse_projected_eigen = True)
bands = run.get_band_structure(kpfile, line_mode = True, efermi = run.efermi)
bsp = BSPlotter(bands)
zero_to_efermi=True
bandgap=str(round(bands.get_band_gap()['energy'],3))
print "bg=",bandgap
data=bsp.bs_plot_data(zero_to_efermi)
plt = get_publication_quality_plot(12, 8)
band_linewidth = 3
x_max = data['distances'][-1][-1]
print (x_max)
for d in range(len(data['distances'])):
for i in range(bsp._nb_bands):
plt.plot(data['distances'][d],
[data['energy'][d]['1'][i][j]
for j in range(len(data['distances'][d]))], 'b-',
linewidth=band_linewidth)
if bsp._bs.is_spin_polarized:
plt.plot(data['distances'][d],
[data['energy'][d]['-1'][i][j]
for j in range(len(data['distances'][d]))],
'r--', linewidth=band_linewidth)
bsp._maketicks(plt)
if bsp._bs.is_metal():
e_min = -10
e_max = 10
band_linewidth = 3
for cbm in data['cbm']:
plt.scatter(cbm[0], cbm[1], color='r', marker='o',
s=100)
for vbm in data['vbm']:
plt.scatter(vbm[0], vbm[1], color='g', marker='o',
s=100)
plt.xlabel(r'$\mathrm{Wave\ Vector}$', fontsize=30)
ylabel = r'$\mathrm{E\ -\ E_f\ (eV)}$' if zero_to_efermi \
else r'$\mathrm{Energy\ (eV)}$'
plt.ylabel(ylabel, fontsize=30)
plt.ylim(-4,4)
plt.xlim(0,x_max)
plt.tight_layout()
plt.savefig('BAND.png',img_format="png")
plt.close()
def bandstr(vrun="", kpfile="", filename=".", plot=False):
"""
Plot electronic bandstructure
Args:
vrun: path to vasprun.xml
kpfile:path to line mode KPOINTS file
Returns:
matplotlib object
"""
run = Vasprun(vrun, parse_projected_eigen=True)
bands = run.get_band_structure(kpfile, line_mode=True, efermi=run.efermi)
bsp = BSPlotter(bands)
zero_to_efermi = True
bandgap = str(round(bands.get_band_gap()["energy"], 3))
# print "bg=",bandgap
data = bsp.bs_plot_data(zero_to_efermi)
plt = get_publication_quality_plot(12, 8)
plt.close()
plt.clf()
band_linewidth = 3
x_max = data["distances"][-1][-1]
# print (x_max)
for d in range(len(data["distances"])):
for i in range(bsp._nb_bands):
plt.plot(
data["distances"][d],
[
data["energy"][d]["1"][i][j]
for j in range(len(data["distances"][d]))
],
"b-",
linewidth=band_linewidth,
)
if bsp._bs.is_spin_polarized:
plt.plot(
data["distances"][d],
[
data["energy"][d]["-1"][i][j]
for j in range(len(data["distances"][d]))
],
"r--",
linewidth=band_linewidth,
)
bsp._maketicks(plt)
if bsp._bs.is_metal():
e_min = -10
e_max = 10
band_linewidth = 3
for cbm in data["cbm"]:
plt.scatter(cbm[0], cbm[1], color="r", marker="o", s=100)
for vbm in data["vbm"]:
plt.scatter(vbm[0], vbm[1], color="g", marker="o", s=100)
plt.xlabel(r"$\mathrm{Wave\ Vector}$", fontsize=30)
ylabel = (
r"$\mathrm{E\ -\ E_f\ (eV)}$" if zero_to_efermi else r"$\mathrm{Energy\ (eV)}$"
)
plt.ylabel(ylabel, fontsize=30)
plt.ylim(-4, 4)
plt.xlim(0, x_max)
plt.tight_layout()
if plot == True:
plt.savefig(filename, img_format="png")
plt.close()
return plt
