def setUp(self):
with open(os.path.join(test_dir, "CaO_2605_bandstructure.json"),
"r",
encoding='utf-8') as f:
d = json.loads(f.read())
self.bs = BandStructureSymmLine.from_dict(d)
self.plotter = BSPlotter(self.bs)
def find_dirac_nodes():
"""
Look for band crossings near (within `tol` eV) the Fermi level.
Returns:
boolean. Whether or not a band crossing occurs at or near
the fermi level.
"""
vasprun = Vasprun('vasprun.xml')
dirac = False
if vasprun.get_band_structure().get_band_gap()['energy'] < 0.1:
efermi = vasprun.efermi
bsp = BSPlotter(vasprun.get_band_structure('KPOINTS', line_mode=True,
efermi=efermi))
bands = []
data = bsp.bs_plot_data(zero_to_efermi=True)
for d in range(len(data['distances'])):
for i in range(bsp._nb_bands):
x = data['distances'][d],
y = [data['energy'][d][str(Spin.up)][i][j]
for j in range(len(data['distances'][d]))]
band = [x, y]
bands.append(band)
considered = []
for i in range(len(bands)):
for j in range(len(bands)):
if i != j and (j, i) not in considered:
considered.append((j, i))
for k in range(len(bands[i][0])):
if ((-0.1 < bands[i][1][k] < 0.1) and
(-0.1 < bands[i][1][k] - bands[j][1][k] < 0.1)):
dirac = True
return dirac
def find_dirac_nodes():
"""
Look for band crossings near (within `tol` eV) the Fermi level.
Returns:
boolean. Whether or not a band crossing occurs at or near
the fermi level.
"""
vasprun = Vasprun('vasprun.xml')
dirac = False
if vasprun.get_band_structure().get_band_gap()['energy'] < 0.1:
efermi = vasprun.efermi
bsp = BSPlotter(vasprun.get_band_structure('KPOINTS', line_mode=True,
efermi=efermi))
bands = []
data = bsp.bs_plot_data(zero_to_efermi=True)
for d in range(len(data['distances'])):
for i in range(bsp._nb_bands):
x = data['distances'][d],
y = [data['energy'][d][str(Spin.up)][i][j]
for j in range(len(data['distances'][d]))]
band = [x, y]
bands.append(band)
considered = []
for i in range(len(bands)):
for j in range(len(bands)):
if i != j and (j, i) not in considered:
considered.append((j, i))
for k in range(len(bands[i][0])):
if ((-0.1 < bands[i][1][k] < 0.1) and
(-0.1 < bands[i][1][k] - bands[j][1][k] < 0.1)):
dirac = True
return dirac
def plot_bandstructure():
if "-h" in sys.argv:
print("usage: complot_bands.py [-g] [-f fname] [-el emin] [-eh emax]")
sys.exit()
if "-g" in sys.argv:
mode = "risb"
else:
mode = "tb"
bs = get_bands_symkpath(mode=mode)
comm = MPI.COMM_WORLD
rank = comm.Get_rank()
if rank == 0:
bsplot = BSPlotter(bs)
if "-f" in sys.argv:
fname = sys.argv[sys.argv.index("-f")+1]
if ".pdf" not in fname:
fname += ".pdf"
else:
fname = "bndstr.pdf"
if "-el" in sys.argv:
emin = float(sys.argv[sys.argv.index("-el")+1])
else:
emin = numpy.min(bs.bands.values())
if "-eh" in sys.argv:
emax = float(sys.argv[sys.argv.index("-eh")+1])
else:
emax = numpy.max(bs.bands.values())
bsplot.save_plot(fname, img_format="pdf", ylim=(emin, emax), \
zero_to_efermi=False)
def make_band_plot_info(self):
bs_plotter = BSPlotter(self.bs)
plot_data = bs_plotter.bs_plot_data(zero_to_efermi=False)
distances = [list(d) for d in plot_data["distances"]]
self._composition = self.vasprun.final_structure.composition
band_info = [BandInfo(band_energies=self._remove_spin_key(plot_data),
band_edge=self._band_edge(self.bs, plot_data),
fermi_level=self.bs.efermi)]
if self.vasprun2:
bs2 = self.vasprun2.get_band_structure(self.kpoints_filename,
line_mode=True)
plot_data2 = BSPlotter(bs2).bs_plot_data(zero_to_efermi=False)
band_info.append(
BandInfo(band_energies=self._remove_spin_key(plot_data2),
band_edge=self._band_edge(bs2, plot_data2),
fermi_level=self.bs.efermi))
x = bs_plotter.get_ticks_old()
x_ticks = XTicks(_sanitize_labels(x["label"]), x["distance"])
return BandPlotInfo(band_info_set=band_info,
distances_by_branch=distances,
x_ticks=x_ticks,
title=self._title)
def plot_band_structure(ylim=(-5, 5), draw_fermi=False, fmt='pdf'):
"""
Plot a standard band structure with no projections.
Args:
ylim (tuple): minimum and maximum potentials for the plot's y-axis.
draw_fermi (bool): whether or not to draw a dashed line at E_F.
fmt (str): matplotlib format style. Check the matplotlib docs
for options.
"""
vasprun = Vasprun('vasprun.xml')
efermi = vasprun.efermi
bsp = BSPlotter(
vasprun.get_band_structure('KPOINTS', line_mode=True, efermi=efermi))
if fmt == "None":
return bsp.bs_plot_data()
else:
plot = bsp.get_plot(ylim=ylim)
fig = plot.gcf()
ax = fig.gca()
ax.set_xticklabels(
[r'$\mathrm{%s}$' % t for t in ax.get_xticklabels()])
ax.set_yticklabels(
[r'$\mathrm{%s}$' % t for t in ax.get_yticklabels()])
if draw_fermi:
ax.plot([ax.get_xlim()[0], ax.get_xlim()[1]], [0, 0], 'k--')
plt.savefig('band_structure.{}'.format(fmt), transparent=True)
plt.close()
class BSPlotterTest(unittest.TestCase):
def setUp(self):
with open(os.path.join(test_dir, "CaO_2605_bandstructure.json"),
"r",
encoding='utf-8') as f:
d = json.loads(f.read())
self.bs = BandStructureSymmLine.from_dict(d)
self.plotter = BSPlotter(self.bs)
def test_bs_plot_data(self):
self.assertEqual(len(self.plotter.bs_plot_data()['distances'][0]), 16,
"wrong number of distances in the first branch")
self.assertEqual(len(self.plotter.bs_plot_data()['distances']), 10,
"wrong number of branches")
self.assertEqual(
sum([len(e) for e in self.plotter.bs_plot_data()['distances']]),
160, "wrong number of distances")
self.assertEqual(self.plotter.bs_plot_data()['ticks']['label'][5], "K",
"wrong tick label")
self.assertEqual(len(self.plotter.bs_plot_data()['ticks']['label']),
19, "wrong number of tick labels")
def test_qvertex_target(self):
results = _qvertex_target(
[[0.0, 0.0, 0.0], [1.0, 0.0, 0.0], [1.0, 1.0, 0.0],
[0.0, 1.0, 0.0], [0.0, 0.0, 1.0], [1.0, 0.0, 1.0],
[1.0, 1.0, 1.0], [0.0, 1.0, 1.0], [0.5, 0.5, 0.5]], 8)
self.assertEqual(len(results), 6)
self.assertEqual(results[3][1], 0.5)
class BSPlotterTest(unittest.TestCase):
def setUp(self):
with open(os.path.join(test_dir, "CaO_2605_bandstructure.json"),
"r", encoding='utf-8') as f:
d = json.loads(f.read())
self.bs = BandStructureSymmLine.from_dict(d)
self.plotter = BSPlotter(self.bs)
def test_bs_plot_data(self):
self.assertEqual(len(self.plotter.bs_plot_data()['distances'][0]), 16,
"wrong number of distances in the first branch")
self.assertEqual(len(self.plotter.bs_plot_data()['distances']), 10,
"wrong number of branches")
self.assertEqual(
sum([len(e) for e in self.plotter.bs_plot_data()['distances']]),
160, "wrong number of distances")
self.assertEqual(self.plotter.bs_plot_data()['ticks']['label'][5], "K",
"wrong tick label")
self.assertEqual(len(self.plotter.bs_plot_data()['ticks']['label']),
19, "wrong number of tick labels")
def test_qvertex_target(self):
results = _qvertex_target([[0.0, 0.0, 0.0], [1.0, 0.0, 0.0],
[1.0, 1.0, 0.0], [0.0, 1.0, 0.0],
[0.0, 0.0, 1.0], [1.0, 0.0, 1.0],
[1.0, 1.0, 1.0], [0.0, 1.0, 1.0],
[0.5, 0.5, 0.5]], 8)
self.assertEqual(len(results), 6)
self.assertEqual(results[3][1], 0.5)
def setUp(self):
with open(os.path.join(test_dir, "CaO_2605_bandstructure.json"),
"r",
encoding="utf-8") as f:
d = json.loads(f.read())
self.bs = BandStructureSymmLine.from_dict(d)
self.plotter = BSPlotter(self.bs)
self.assertEqual(len(self.plotter._bs), 1,
"wrong number of band objects")
with open(os.path.join(test_dir, "N2_12103_bandstructure.json"),
"r",
encoding="utf-8") as f:
d = json.loads(f.read())
self.sbs_sc = BandStructureSymmLine.from_dict(d)
with open(os.path.join(test_dir, "C_48_bandstructure.json"),
"r",
encoding="utf-8") as f:
d = json.loads(f.read())
self.sbs_met = BandStructureSymmLine.from_dict(d)
self.plotter_multi = BSPlotter([self.sbs_sc, self.sbs_met])
self.assertEqual(len(self.plotter_multi._bs), 2,
"wrong number of band objects")
self.assertEqual(self.plotter_multi._nb_bands, [96, 96],
"wrong number of bands")
warnings.simplefilter("ignore")
def plot_simple_smoothed_band_structure(ylim=[-1.5, 3.5], filename=None):
vasprun = Vasprun('./vasprun.xml')
bs = vasprun.get_band_structure(line_mode=True)
if filename is None:
# BSPlotter(bs).get_plot(smooth=True,ylim=ylim)
BSPlotter(bs).show(smooth=True, ylim=ylim)
else:
BSPlotter(bs).save_plot(filename)
def plot_bs(vasprun_path: str):
try:
v = BSVasprun(vasprun_path)
except xml.etree.ElementTree.ParseError:
print("\tskipped due to parse error")
return
bs = v.get_band_structure(kpoints_filename="KPOINTS", line_mode=True)
plt = BSPlotter(bs)
plt.show()
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 get_bandsxy(self, bs, bandrange):
## get coords of the band structure data points
bsplot = BSPlotter(bs)
data = bsplot.bs_plot_data()
x = [k for kbranch in data["distances"] for k in kbranch]
yu = [[e - bs.efermi for e in bs.bands[Spin.up][band]] for band in bandrange]
if bs.is_spin_polarized:
yd = [[e - bs.efermi for e in bs.bands[Spin.down][band]] for band in bandrange]
else:
yd = None
return [x, yu, yd]
def __init__(self, bs):
if isinstance(bs, list):
bs = [force_branches(b) for b in bs]
else:
bs = force_branches(bs)
BSPlotter.__init__(self, bs)
# old versions of pymatgen only support a single band structure
if isinstance(self._bs, list):
self.bs = self._bs[0]
self.nbands = self._nb_bands[0]
else:
self.bs = self._bs
self.nbands = self._nb_bands
class BSPlotterTest(unittest.TestCase):
def setUp(self):
with open(os.path.join(test_dir, "CaO_2605_bandstructure.json"),
"rb") as f:
d = json.loads(f.read())
self.bs = BandStructureSymmLine.from_dict(d)
self.plotter = BSPlotter(self.bs)
def test_bs_plot_data(self):
self.assertEqual(len(self.plotter.bs_plot_data()['distances']), 160,
"wrong number of distances")
self.assertEqual(self.plotter.bs_plot_data()['ticks']['label'][5], "K",
"wrong tick label")
self.assertEqual(len(self.plotter.bs_plot_data()['ticks']['label']),
19, "wrong number of tick labels")
def setUp(self):
with open(os.path.join(test_dir, "CaO_2605_bandstructure.json"),
"r", encoding='utf-8') as f:
d = json.loads(f.read())
self.bs = BandStructureSymmLine.from_dict(d)
self.plotter = BSPlotter(self.bs)
warnings.simplefilter("ignore")
class BSPlotterTest(unittest.TestCase):
def setUp(self):
with open(os.path.join(test_dir, "CaO_2605_bandstructure.json"),
"rb") as f:
d = json.loads(f.read())
self.bs = BandStructureSymmLine.from_dict(d)
self.plotter = BSPlotter(self.bs)
def test_bs_plot_data(self):
self.assertEqual(len(self.plotter.bs_plot_data()['distances']), 160,
"wrong number of distances")
self.assertEqual(self.plotter.bs_plot_data()['ticks']['label'][5], "K",
"wrong tick label")
self.assertEqual(len(self.plotter.bs_plot_data()['ticks']['label']),
19, "wrong number of tick labels")
def get_mp_banddos():
check_matplotlib()
mpr = check_apikey()
print("input the mp-ID")
wait_sep()
in_str = wait()
mp_id = in_str
step_count = 1
proc_str = "Reading Data From " + web + " ..."
procs(proc_str, step_count, sp='-->>')
data = mpr.get_entry_by_material_id(mp_id)
sepline()
print(data)
sepline()
step_count += 1
proc_str = "Reading Band Data From " + web + " ..."
procs(proc_str, step_count, sp='-->>')
band = mpr.get_bandstructure_by_material_id(mp_id)
if band is None:
print("No data obtained online, stop now!")
os.exit(0)
step_count += 1
filename = mp_id + '_band.png'
proc_str = "Writing Data to " + filename + " File..."
bsp = BSPlotter(band)
procs(proc_str, step_count, sp='-->>')
bsp.save_plot(filename=filename, img_format="png")
step_count += 1
proc_str = "Reading DOS Data From " + web + " ..."
procs(proc_str, step_count, sp='-->>')
dos = mpr.get_dos_by_material_id(mp_id)
if dos is None:
print("No data obtained online, stop now!")
step_count += 1
filename = mp_id + '_dos.png'
proc_str = "Writing Data to " + filename + " File..."
dsp = DosPlotter()
dsp.add_dos('Total', dos)
procs(proc_str, step_count, sp='-->>')
dsp.save_plot(filename=filename, img_format="png")
def get_kpt_labels(self, bs):
bsplot = BSPlotter(bs)
## get unique K-points
labels = bsplot.get_ticks()["label"]
labelspos = bsplot.get_ticks()["distance"]
labels_uniq = [labels[0]]
labelspos_uniq = [labelspos[0]]
for i in range(1, len(labels)):
if labels[i] != labels[i - 1]:
labels_uniq.append(labels[i])
labelspos_uniq.append(labelspos[i])
labels_uniq = [label.replace("$\mid$", "|") for label in labels_uniq]
## hack for dash which can't display latex :(
labels_uniq = [label.replace("$\Gamma$", u"\u0393") for label in labels_uniq]
return labels_uniq, labelspos_uniq
class BSPlotterTest(unittest.TestCase):
def setUp(self):
with open(os.path.join(test_dir, "CaO_2605_bandstructure.json"),
"r",
encoding='utf-8') as f:
d = json.loads(f.read())
self.bs = BandStructureSymmLine.from_dict(d)
self.plotter = BSPlotter(self.bs)
warnings.simplefilter("ignore")
def tearDown(self):
warnings.simplefilter("default")
def test_bs_plot_data(self):
self.assertEqual(len(self.plotter.bs_plot_data()['distances'][0]), 16,
"wrong number of distances in the first branch")
self.assertEqual(len(self.plotter.bs_plot_data()['distances']), 10,
"wrong number of branches")
self.assertEqual(
sum([len(e) for e in self.plotter.bs_plot_data()['distances']]),
160, "wrong number of distances")
self.assertEqual(self.plotter.bs_plot_data()['ticks']['label'][5], "K",
"wrong tick label")
self.assertEqual(len(self.plotter.bs_plot_data()['ticks']['label']),
19, "wrong number of tick labels")
# Minimal baseline testing for get_plot. not a true test. Just checks that
# it can actually execute.
def test_get_plot(self):
# zero_to_efermi = True, ylim = None, smooth = False,
# vbm_cbm_marker = False, smooth_tol = None
# Disabling latex is needed for this test to work.
from matplotlib import rc
rc('text', usetex=False)
plt = self.plotter.get_plot()
plt = self.plotter.get_plot(smooth=True)
plt = self.plotter.get_plot(vbm_cbm_marker=True)
self.plotter.save_plot("bsplot.png")
self.assertTrue(os.path.isfile("bsplot.png"))
os.remove("bsplot.png")
plt.close("all")
def plot_bands(self):
"""
Plot a band structure on symmetry line using BSPlotter()
"""
if self.bzt_interp is None:
raise BoltztrapError("BztInterpolator not present")
sbs = self.bzt_interp.get_band_structure()
return BSPlotter(sbs).get_plot()
def plot_bs(bs, **kwargs):
"""
Get BS plot with pymatgen.
Parameters
----------
bs :
BandStructureSymmLine object, most likely generaten from Vasprun or BSVasprun.
**kwargs : (dict)
Arguments for the get_plot function in BSPlotter in pymatgen.
Returns
-------
plt :
Matplotlib object.
"""
plotter = BSPlotter(bs)
plt = plotter.get_plot(**kwargs)
return plt
class BSPlotterTest(unittest.TestCase):
def setUp(self):
with open(os.path.join(test_dir, "CaO_2605_bandstructure.json"),
"r", encoding='utf-8') as f:
d = json.loads(f.read())
self.bs = BandStructureSymmLine.from_dict(d)
self.plotter = BSPlotter(self.bs)
warnings.simplefilter("ignore")
def tearDown(self):
warnings.resetwarnings()
def test_bs_plot_data(self):
self.assertEqual(len(self.plotter.bs_plot_data()['distances'][0]), 16,
"wrong number of distances in the first branch")
self.assertEqual(len(self.plotter.bs_plot_data()['distances']), 10,
"wrong number of branches")
self.assertEqual(
sum([len(e) for e in self.plotter.bs_plot_data()['distances']]),
160, "wrong number of distances")
self.assertEqual(self.plotter.bs_plot_data()['ticks']['label'][5], "K",
"wrong tick label")
self.assertEqual(len(self.plotter.bs_plot_data()['ticks']['label']),
19, "wrong number of tick labels")
# Minimal baseline testing for get_plot. not a true test. Just checks that
# it can actually execute.
def test_get_plot(self):
# zero_to_efermi = True, ylim = None, smooth = False,
# vbm_cbm_marker = False, smooth_tol = None
# Disabling latex is needed for this test to work.
from matplotlib import rc
rc('text', usetex=False)
plt = self.plotter.get_plot()
plt = self.plotter.get_plot(smooth=True)
plt = self.plotter.get_plot(vbm_cbm_marker=True)
self.plotter.save_plot("bsplot.png")
self.assertTrue(os.path.isfile("bsplot.png"))
os.remove("bsplot.png")
def get_small_plot(bs):
plot_small = BSPlotter(bs).bs_plot_data()
gap = bs.get_band_gap()["energy"]
for branch in plot_small['energy']:
for spin, v in branch.items():
new_bands = []
for band in v:
if min(band) < gap + 3 and max(band) > -3:
new_bands.append(band)
branch[spin] = new_bands
return plot_small
def plot_band_structure(ylim=(-5, 5), draw_fermi=False, fmt="pdf"):
"""
Plot a standard band structure with no projections.
Args:
ylim (tuple): minimum and maximum potentials for the plot's
y-axis.
draw_fermi (bool): whether or not to draw a dashed line at
E_F.
fmt (str): matplotlib format style. Check the matplotlib
docs for options.
"""
vasprun = Vasprun("vasprun.xml")
efermi = vasprun.efermi
bsp = BSPlotter(vasprun.get_band_structure("KPOINTS", line_mode=True, efermi=efermi))
plot = bsp.get_plot(ylim=ylim)
fig = plot.gcf()
ax = fig.gca()
ax.set_xticklabels([r"$\mathrm{%s}$" % t for t in ax.get_xticklabels()])
if draw_fermi:
ax.plot([ax.get_xlim()[0], ax.get_xlim()[1]], [0, 0], "k--")
fig.savefig("band_structure.{}".format(fmt), transparent=True)
plt.close()
from pymatgen.io.vasp.outputs import BSVasprun
from pymatgen.electronic_structure.plotter import BSPlotter
import os
os.chdir('/home/jinho93/half-metal/1.CrO2/3.band')
vrun = BSVasprun('vasprun.xml')
bs = vrun.get_band_structure('KPOINTS', line_mode=True)
bsp = BSPlotter(bs)
bsp.show()
# Copyright (c) Henniggroup.
# Distributed under the terms of the MIT License.
from __future__ import division, unicode_literals, print_function
"""
reads in KPOINTS(with labels for high symmetry kpoints) and
vasprun.xml files and plots the band structure along the high
symmetry kpoints
"""
# To use matplotlib on Hipergator, uncomment the following 2 lines:
# import matplotlib
# matplotlib.use('Agg')
from pymatgen.io.vasp.outputs import Vasprun
from pymatgen.electronic_structure.plotter import BSPlotterProjected, BSPlotter
if __name__ == "__main__":
# readin bandstructure from vasprun.xml and labeled KPOINTS
run = Vasprun("vasprun.xml", parse_projected_eigen=True)
bands = run.get_band_structure("KPOINTS", line_mode=True,
efermi=run.efermi)
bsp = BSPlotter(bands)
# Blue lines are up spin, red lines are down spin
bsp.save_plot('band_diagram.eps', ylim=(-5, 5))
# bsp = BSPlotterProjected(bands)
# plt = bsp.get_projected_plots_dots( {'Fe':['s', 'p', 'd'],
# 'Sb':['s', 'p', 'd']})
# get_elt_projected_plots_color()
dosplotter = DosPlotter()
Totaldos = dosplotter.add_dos('Total DOS', tdos)
Integrateddos = dosplotter.add_dos('Integrated DOS', idos)
#Pdos = dosplotter.add_dos('Partial DOS',pdos)
#Spd_dos = dosplotter.add_dos('spd DOS',spd_dos)
#Element_dos = dosplotter.add_dos('Element DOS',element_dos)
#Element_spd_dos = dosplotter.add_dos('Element_spd DOS',element_spd_dos)
dos_dict = {
'Total DOS': tdos,
'Integrated DOS': idos
} #'Partial DOS':pdos,'spd DOS':spd_dos,'Element DOS':element_dos}#'Element_spd DOS':element_spd_dos
add_dos_dict = dosplotter.add_dos_dict(dos_dict)
get_dos_dict = dosplotter.get_dos_dict()
dos_plot = dosplotter.get_plot()
##dosplotter.save_plot("MAPbI3_dos",img_format="png")
##dos_plot.show()
bsplotter = BSPlotter(bs)
bs_plot_data = bsplotter.bs_plot_data()
bs_plot = bsplotter.get_plot()
#bsplotter.save_plot("MAPbI3_bs",img_format="png")
#bsplotter.show()
ticks = bsplotter.get_ticks()
print ticks
bsplotter.plot_brillouin()
bsdos = BSDOSPlotter(
tick_fontsize=10,
egrid_interval=20,
dos_projection="orbitals",
bs_legend=None) #bs_projection="HPbCIN",dos_projection="HPbCIN")
bds = bsdos.get_plot(bs, cdos)
#!/nfshome/villa/anaconda3/bin/python
from pymatgen.io.vasp.outputs import Vasprun
from pymatgen.electronic_structure.plotter import BSPlotter, BSDOSPlotter
vaspout_bs = Vasprun("vasprun.xml")
vaspout_dos = Vasprun("vasprun.xml")
bandstr = vaspout_bs.get_band_structure(line_mode=True, force_hybrid_mode=True)
bs_data = BSPlotter(bandstr).bs_plot_data()
dos = vaspout_dos.complete_dos
dos_dict = dos.as_dict()
#plt = BSPlotter(bandstr).get_plot()
plt = BSDOSPlotter(bs_projection=None,
dos_projection='elements',
bs_legend=None,
fig_size=(14, 11)).get_plot(bandstr, dos)
plt.savefig("dos_bs.png")
def get_plot(
self,
n_idx,
t_idx,
zero_to_efermi=True,
estep=0.01,
line_density=100,
height=6,
width=6,
emin=None,
emax=None,
ylabel="Energy (eV)",
plt=None,
aspect=None,
distance_factor=10,
kpath=None,
style=None,
no_base_style=False,
fonts=None,
):
interpolater = self._get_interpolater(n_idx, t_idx)
bs, prop = interpolater.get_line_mode_band_structure(
line_density=line_density,
return_other_properties=True,
kpath=kpath)
fd_emin, fd_emax = self.fd_cutoffs
if not emin:
emin = fd_emin * hartree_to_ev
if zero_to_efermi:
emin -= bs.efermi
if not emax:
emax = fd_emax * hartree_to_ev
if zero_to_efermi:
emax -= bs.efermi
logger.info("Plotting band structure")
plt = pretty_plot(width=width, height=height, plt=plt)
ax = plt.gca()
if zero_to_efermi:
bs.bands = {s: b - bs.efermi for s, b in bs.bands.items()}
bs.efermi = 0
bs_plotter = BSPlotter(bs)
plot_data = bs_plotter.bs_plot_data(zero_to_efermi=zero_to_efermi)
energies = np.linspace(emin, emax, int((emax - emin) / estep))
distances = np.array([d for x in plot_data["distances"] for d in x])
# rates are currently log(rate)
rates = {}
for spin, spin_data in prop.items():
rates[spin] = spin_data["rates"]
rates[spin][rates[spin] <= 0] = np.min(
rates[spin][rates[spin] > 0])
rates[spin][rates[spin] >= 15] = 15
interp_distances = np.linspace(distances.min(), distances.max(),
int(len(distances) * distance_factor))
window = np.min([len(distances) - 2, 71])
window += window % 2 + 1
mesh_data = np.full((len(interp_distances), len(energies)), 1e-2)
for spin in self.spins:
for spin_energies, spin_rates in zip(bs.bands[spin], rates[spin]):
interp_energies = interp1d(distances,
spin_energies)(interp_distances)
spin_rates = savgol_filter(spin_rates, window, 3)
interp_rates = interp1d(distances,
spin_rates)(interp_distances)
linewidths = 10**interp_rates * hbar / 2
for d_idx in range(len(interp_distances)):
energy = interp_energies[d_idx]
linewidth = linewidths[d_idx]
broadening = lorentzian(energies, energy, linewidth)
mesh_data[d_idx] = np.maximum(broadening, mesh_data[d_idx])
mesh_data[d_idx] = np.maximum(broadening, mesh_data[d_idx])
ax.pcolormesh(
interp_distances,
energies,
mesh_data.T,
rasterized=True,
norm=LogNorm(vmin=mesh_data.min(), vmax=mesh_data.max()),
)
_maketicks(ax, bs_plotter, ylabel=ylabel)
_makeplot(
ax,
plot_data,
bs,
zero_to_efermi=zero_to_efermi,
width=width,
height=height,
ymin=emin,
ymax=emax,
aspect=aspect,
)
return plt
def bs_dos_traces(bandStructureSymmLine, densityOfStates):
if bandStructureSymmLine == "error" or densityOfStates == "error":
return "error"
if bandStructureSymmLine == None or densityOfStates == None:
raise PreventUpdate
# - BS Data
bstraces = []
bs_reg_plot = BSPlotter(BSML.from_dict(bandStructureSymmLine))
bs_data = bs_reg_plot.bs_plot_data()
# -- Strip latex math wrapping
str_replace = {
"$": "",
"\\mid": "|",
"\\Gamma": "Γ",
"\\Sigma": "Σ",
"_1": "₁",
"_2": "₂",
"_3": "₃",
"_4": "₄",
}
for entry_num in range(len(bs_data["ticks"]["label"])):
for key in str_replace.keys():
if key in bs_data["ticks"]["label"][entry_num]:
bs_data["ticks"]["label"][entry_num] = bs_data[
"ticks"]["label"][entry_num].replace(
key, str_replace[key])
for d in range(len(bs_data["distances"])):
for i in range(bs_reg_plot._nb_bands):
bstraces.append(
go.Scatter(
x=bs_data["distances"][d],
y=[
bs_data["energy"][d][str(Spin.up)][i][j]
for j in range(len(bs_data["distances"][d]))
],
mode="lines",
line=dict(color=("#666666"), width=2),
hoverinfo="skip",
showlegend=False,
))
if bs_reg_plot._bs.is_spin_polarized:
bstraces.append(
go.Scatter(
x=bs_data["distances"][d],
y=[
bs_data["energy"][d][str(Spin.down)][i][j]
for j in range(len(bs_data["distances"]
[d]))
],
mode="lines",
line=dict(color=("#666666"),
width=2,
dash="dash"),
hoverinfo="skip",
showlegend=False,
))
# -- DOS Data
dostraces = []
dos = CompleteDos.from_dict(densityOfStates)
if Spin.down in dos.densities:
# Add second spin data if available
trace_tdos = go.Scatter(
x=dos.densities[Spin.down],
y=dos.energies - dos.efermi,
mode="lines",
name="Total DOS (spin ↓)",
line=go.scatter.Line(color="#444444", dash="dash"),
fill="tozeroy",
)
dostraces.append(trace_tdos)
tdos_label = "Total DOS (spin ↑)"
else:
tdos_label = "Total DOS"
# Total DOS
trace_tdos = go.Scatter(
x=dos.densities[Spin.up],
y=dos.energies - dos.efermi,
mode="lines",
name=tdos_label,
line=go.scatter.Line(color="#444444"),
fill="tozeroy",
legendgroup="spinup",
)
dostraces.append(trace_tdos)
p_ele_dos = dos.get_element_dos()
# Projected DOS
count = 0
colors = [
"#1f77b4", # muted blue
"#ff7f0e", # safety orange
"#2ca02c", # cooked asparagus green
"#d62728", # brick red
"#9467bd", # muted purple
"#8c564b", # chestnut brown
"#e377c2", # raspberry yogurt pink
"#bcbd22", # curry yellow-green
"#17becf", # blue-teal
]
for ele in p_ele_dos.keys():
if bs_reg_plot._bs.is_spin_polarized:
trace = go.Scatter(
x=p_ele_dos[ele].densities[Spin.down],
y=dos.energies - dos.efermi,
mode="lines",
name=ele.symbol + " (spin ↓)",
line=dict(width=3, color=colors[count], dash="dash"),
)
dostraces.append(trace)
spin_up_label = ele.symbol + " (spin ↑)"
else:
spin_up_label = ele.symbol
trace = go.Scatter(
x=p_ele_dos[ele].densities[Spin.up],
y=dos.energies - dos.efermi,
mode="lines",
name=spin_up_label,
line=dict(width=3, color=colors[count]),
)
dostraces.append(trace)
count += 1
traces = [bstraces, dostraces, bs_data]
return traces
# -*- coding: utf-8 -*-
"""
Created on Wed May 15 10:33:43 2019
@author: nwpuf
"""
from pymatgen.io.vasp import Vasprun, BSVasprun
from pymatgen.electronic_structure.plotter import BSPlotter, DosPlotter
import matplotlib.pyplot as plt
bsv = BSVasprun("vasprun.xml")
bs = bsv.get_band_structure(kpoints_filename="KPOINTS", line_mode=True)
print(bs.get_band_gap())
bsplot = BSPlotter(bs)
bsplot.get_plot(vbm_cbm_marker=True).show()
#dosrun = Vasprun("DOS/vasprun.xml", parse_dos=True)
#dos = dosrun.complete_dos
#dosplot = DosPlotter(sigma=0.1)
#dosplot.add_dos("Total DOS", dos)
#dosplot.add_dos_dict(dos.get_element_dos())
#ax = plt.gca()
#print(type(dosplot.get_plot()))
#dosplot.get_plot().show()
# Distributed under the terms of the MIT License.
from __future__ import division, print_function, unicode_literals, \
absolute_import
"""
reads in KPOINTS(with labels for high symmetry kpoints) and
vasprun.xml files and plots the band structure along the high
symmetry kpoints
"""
# To use matplotlib on Hipergator, uncomment the following 2 lines:
# import matplotlib
# matplotlib.use('Agg')
from pymatgen.io.vasp.outputs import Vasprun
from pymatgen.electronic_structure.plotter import BSPlotter
if __name__ == "__main__":
# readin bandstructure from vasprun.xml and labeled KPOINTS
run = Vasprun("vasprun.xml", parse_projected_eigen=True)
bands = run.get_band_structure("KPOINTS",
line_mode=True,
efermi=run.efermi)
bsp = BSPlotter(bands)
# Blue lines are up spin, red lines are down spin
bsp.save_plot('band_diagram.eps', ylim=(-5, 5))
# bsp = BSPlotterProjected(bands)
# plt = bsp.get_projected_plots_dots( {'Fe':['s', 'p', 'd'],
# 'Sb':['s', 'p', 'd']})
# get_elt_projected_plots_color()
def projected_band_structure():
step_count=1
filename='vasprun.xml'
check_file(filename)
proc_str="Reading Data From "+ filename +" File ..."
procs(proc_str,step_count,sp='-->>')
vsr=Vasprun(filename)
filename='PROCAR'
check_file(filename)
step_count+=1
proc_str="Reading Data From "+ filename +" File ..."
procs(proc_str,step_count,sp='-->>')
procar=Procar(filename)
nbands=procar.nbands
nions=procar.nions
norbitals=len(procar.orbitals)
nkpoints=procar.nkpoints
step_count+=1
filename='KPOINTS'
check_file(filename)
proc_str="Reading Data From "+ filename +" File ..."
procs(proc_str,step_count,sp='-->>')
bands = vsr.get_band_structure(filename, line_mode=True, efermi=vsr.efermi)
struct=vsr.final_structure
(atom_index,in_str)=atom_selection(struct)
if len(atom_index)==0:
print("No atoms selected!")
return
# print(atom_index)
if vsr.is_spin:
proc_str="This Is a Spin-polarized Calculation."
procs(proc_str,0,sp='-->>')
ISPIN=2
contrib=np.zeros((nkpoints,nbands,norbitals,2))
for i in atom_index:
contrib[:,:,:,0]=contrib[:,:,:,0]+procar.data[Spin.up][:,:,i,:]
contrib[:,:,:,1]=contrib[:,:,:,1]+procar.data[Spin.down][:,:,i,:]
for ispin in range(2):
proj_band=contrib[:,:,:,ispin].reshape(nkpoints*nbands,norbitals)
step_count+=1
if ispin==0:
filename="PBAND_Up.dat"
else:
filename="PBAND_Down.dat"
proc_str="Writting Projected Band Structure Data to "+ filename +" File ..."
procs(proc_str,step_count,sp='-->>')
band_data=bands.bands[Spin.up]
y_data=band_data.reshape(1,nbands*nkpoints)[0]-vsr.efermi #shift fermi level to 0
x_data=np.array(bands.distance*nbands)
data=np.vstack((x_data,y_data,proj_band.T)).T
tmp1_str="#%(key1)+12s%(key2)+12s"
tmp2_dic={'key1':'K-Distance','key2':'Energy(ev)'}
for i in range(norbitals):
tmp1_str+="%(key"+str(i+3)+")+12s"
tmp2_dic["key"+str(i+3)]=procar.orbitals[i]
# print(tmp1_str)
atom_index_str=[str(x+1) for x in atom_index]
head_line1="#String: "+in_str+'\n#Selected atom: ' +' '.join(atom_index_str)+'\n'
head_line2=tmp1_str % tmp2_dic
head_line=head_line1+head_line2
write_col_data(filename,data,head_line,nkpoints)
else:
if vsr.parameters['LNONCOLLINEAR']:
proc_str="This Is a Non-Collinear Calculation."
procs(proc_str,0,sp='-->>')
ISPIN=3
else:
proc_str="This Is a Non-Spin Calculation."
procs(proc_str,0,sp='-->>')
ISPIN=1
contrib=np.zeros((nkpoints,nbands,norbitals))
for i in atom_index:
contrib[:,:,:]=contrib[:,:,:]+procar.data[Spin.up][:,:,i,:]
proj_band=contrib.reshape(nkpoints*nbands,norbitals)
step_count+=1
filename="PBAND.dat"
proc_str="Writting Projected Band Structure Data to "+ filename +" File ..."
procs(proc_str,step_count,sp='-->>')
band_data=bands.bands[Spin.up]
y_data=band_data.reshape(1,nbands*nkpoints)[0]-vsr.efermi #shift fermi level to 0
x_data=np.array(bands.distance*nbands)
data=np.vstack((x_data,y_data,proj_band.T)).T
tmp1_str="#%(key1)+12s%(key2)+12s"
tmp2_dic={'key1':'K-Distance','key2':'Energy(ev)'}
for i in range(norbitals):
tmp1_str+="%(key"+str(i+3)+")+12s"
tmp2_dic["key"+str(i+3)]=procar.orbitals[i]
# print(tmp1_str)
atom_index_str=[str(x+1) for x in atom_index]
head_line1="#String: "+in_str+'\n#Selected atom: ' +' '.join(atom_index_str)+'\n'
head_line2=tmp1_str % tmp2_dic
head_line=head_line1+head_line2
write_col_data(filename,data,head_line,nkpoints)
step_count+=1
bsp=BSPlotter(bands)
filename="HighSymmetricPoints.dat"
proc_str="Writting Label infomation to "+ filename +" File ..."
procs(proc_str,step_count,sp='-->>')
head_line="#%(key1)+12s%(key2)+12s%(key3)+12s"%{'key1':'index','key2':'label','key3':'position'}
line=head_line+'\n'
for i,label in enumerate(bsp.get_ticks()['label']):
new_line="%(key1)12d%(key2)+12s%(key3)12f\n"%{'key1':i,'key2':label,'key3':bsp.get_ticks()['distance'][i]}
line+=new_line
write_col_data(filename,line,'',str_data=True)
def band_structure():
check_matplotlib()
step_count=1
filename='vasprun.xml'
check_file(filename)
proc_str="Reading Data From "+ filename +" File ..."
procs(proc_str,step_count,sp='-->>')
vsr=Vasprun(filename)
step_count+=1
filename='KPOINTS'
check_file(filename)
proc_str="Reading Data From "+ filename +" File ..."
procs(proc_str,step_count,sp='-->>')
bands = vsr.get_band_structure(filename, line_mode=True, efermi=vsr.efermi)
step_count+=1
filename='OUTCAR'
check_file(filename)
proc_str="Reading Data From "+ filename +" File ..."
procs(proc_str,step_count,sp='-->>')
outcar=Outcar('OUTCAR')
mag=outcar.as_dict()['total_magnetization']
if vsr.is_spin:
proc_str="This Is a Spin-polarized Calculation."
procs(proc_str,0,sp='-->>')
tdos=vsr.tdos
SpinUp_gap=tdos.get_gap(spin=Spin.up)
cbm_vbm_up=tdos.get_cbm_vbm(spin=Spin.up)
SpinDown_gap=tdos.get_gap(spin=Spin.down)
cbm_vbm_down=tdos.get_cbm_vbm(spin=Spin.up)
if SpinUp_gap > min_gap and SpinDown_gap > min_gap:
is_metal=False
is_semimetal=False
elif SpinUp_gap > min_gap and SpinDown_gap < min_gap:
is_metal=False
is_semimetal=True
elif SpinUp_gap < min_gap and SpinDown_gap > min_gap:
is_metal=False
is_semimetal=True
elif SpinUp_gap < min_gap and SpinDown_gap < min_gap:
is_metal=True
is_semimetal=False
if is_metal:
proc_str="This Material Is a Metal."
procs(proc_str,0,sp='-->>')
if not is_metal and is_semimetal:
proc_str="This Material Is a Semimetal."
procs(proc_str,0,sp='-->>')
else:
proc_str="This Material Is a Semiconductor."
procs(proc_str,0,sp='-->>')
proc_str="Total magnetization is "+str(mag)
procs(proc_str,0,sp='-->>')
if mag > min_mag:
proc_str="SpinUp : vbm=%f eV cbm=%f eV gap=%f eV"%(cbm_vbm_up[1],cbm_vbm_up[0],SpinUp_gap)
procs(proc_str,0,sp='-->>')
proc_str="SpinDown: vbm=%f eV cbm=%f eV gap=%f eV"%(cbm_vbm_down[1],cbm_vbm_down[0],SpinUp_gap)
procs(proc_str,0,sp='-->>')
else:
proc_str="SpinUp : vbm=%f eV cbm=%f eV gap=%f eV"%(cbm_vbm_up[1],cbm_vbm_up[0],SpinUp_gap)
procs(proc_str,0,sp='-->>')
step_count+=1
filename="BAND.dat"
proc_str="Writting Band Structure Data to "+ filename +" File ..."
procs(proc_str,step_count,sp='-->>')
band_data_up=bands.bands[Spin.up]
band_data_down=bands.bands[Spin.down]
y_data_up=band_data_up.reshape(1,band_data_up.shape[0]*band_data_up.shape[1])[0]-vsr.efermi #shift fermi level to 0
y_data_down=band_data_down.reshape(1,band_data_down.shape[0]*band_data_down.shape[1])[0]-vsr.efermi #shift fermi level to 0
x_data=np.array(bands.distance*band_data_up.shape[0])
data=np.vstack((x_data,y_data_up,y_data_down)).T
head_line="#%(key1)+12s%(key2)+13s%(key3)+15s"%{'key1':'K-Distance','key2':'UpEnergy(ev)','key3':'DownEnergy(ev)'}
write_col_data(filename,data,head_line,band_data_up.shape[1])
else:
if vsr.parameters['LNONCOLLINEAR']:
proc_str="This Is a Non-Collinear Calculation."
else:
proc_str="This Is a Non-Spin Calculation."
procs(proc_str,0,sp='-->>')
cbm=bands.get_cbm()['energy']
vbm=bands.get_vbm()['energy']
gap=bands.get_band_gap()['energy']
if not bands.is_metal():
proc_str="This Material Is a Semiconductor."
procs(proc_str,0,sp='-->>')
proc_str="vbm=%f eV cbm=%f eV gap=%f eV"%(vbm,cbm,gap)
procs(proc_str,0,sp='-->>')
else:
proc_str="This Material Is a Metal."
procs(proc_str,0,sp='-->>')
step_count+=1
filename3="BAND.dat"
proc_str="Writting Band Structure Data to "+ filename3 +" File ..."
procs(proc_str,step_count,sp='-->>')
band_data=bands.bands[Spin.up]
y_data=band_data.reshape(1,band_data.shape[0]*band_data.shape[1])[0]-vsr.efermi #shift fermi level to 0
x_data=np.array(bands.distance*band_data.shape[0])
data=np.vstack((x_data,y_data)).T
head_line="#%(key1)+12s%(key2)+13s"%{'key1':'K-Distance','key2':'Energy(ev)'}
write_col_data(filename3,data,head_line,band_data.shape[1])
step_count+=1
bsp=BSPlotter(bands)
filename4="HighSymmetricPoints.dat"
proc_str="Writting Label infomation to "+ filename4 +" File ..."
procs(proc_str,step_count,sp='-->>')
head_line="#%(key1)+12s%(key2)+12s%(key3)+12s"%{'key1':'index','key2':'label','key3':'position'}
line=head_line+'\n'
for i,label in enumerate(bsp.get_ticks()['label']):
new_line="%(key1)12d%(key2)+12s%(key3)12f\n"%{'key1':i,'key2':label,'key3':bsp.get_ticks()['distance'][i]}
line+=new_line
line+='\n'
write_col_data(filename4,line,'',str_data=True)
try:
step_count+=1
filename5="BAND.png"
proc_str="Saving Plot to "+ filename5 +" File ..."
procs(proc_str,step_count,sp='-->>')
bsp.save_plot(filename5, img_format="png")
except:
print("Figure output fails !!!")
from pymatgen.io.vasp import Vasprun
from pymatgen.electronic_structure.plotter import BSPlotter, BSPlotterProjected
vr = Vasprun("nself/vasprun.xml")
bs = vr.get_band_structure(kpoints_filename="nself/KPOINTS", line_mode=True)
bsp = BSPlotter(bs)
#plt = bsp.get_elt_projected_plots(zero_to_efermi=False)
#plt.savefig("band_structure.png", format="png")
bsp.save_plot(filename="band_structure.png", img_format="png")
def setUp(self):
with open(os.path.join(test_dir, "CaO_2605_bandstructure.json"),
"rb") as f:
d = json.loads(f.read())
self.bs = BandStructureSymmLine.from_dict(d)
self.plotter = BSPlotter(self.bs)
# !/usr/bin/env python
# -*- coding: utf-8 -*-
from pymatgen.io.vasp.outputs import Vasprun
from pymatgen.electronic_structure.plotter import BSPlotter
vasprun = Vasprun("vasprun.xml")
bss = vasprun.get_band_structure(kpoints_filename="KPOINTS", line_mode=True)
plotter = BSPlotter(bss)
#plotter.save_plot("bandStructure.svg", img_format="svg")
#plotter.save_plot("bandStructure.png", img_format="png")
#plotter.save_plot("lim_bandStructure.svg", img_format="svg", ylim=(-.2, 1.4))
plotter.save_plot("MAPbI3-primitive.png", img_format="png", ylim=(-5, 5))
plotter.plot_brillouin()
def get_plot(
self,
n_idx,
t_idx,
zero_to_efermi=True,
estep=0.01,
line_density=100,
height=3.2,
width=3.2,
emin=None,
emax=None,
amin=5e-5,
amax=1e-1,
ylabel="Energy (eV)",
plt=None,
aspect=None,
kpath=None,
cmap="viridis",
colorbar=True,
style=None,
no_base_style=False,
fonts=None,
):
interpolater = self._get_interpolater(n_idx, t_idx)
bs, prop = interpolater.get_line_mode_band_structure(
line_density=line_density,
return_other_properties=True,
kpath=kpath,
symprec=self.symprec,
)
bs, rates = force_branches(bs, {s: p["rates"] for s, p in prop.items()})
fd_emin, fd_emax = self.fd_cutoffs
if not emin:
emin = fd_emin
if zero_to_efermi:
emin -= bs.efermi
if not emax:
emax = fd_emax
if zero_to_efermi:
emax -= bs.efermi
logger.info("Plotting band structure")
if isinstance(plt, (Axis, SubplotBase)):
ax = plt
else:
plt = pretty_plot(width=width, height=height, plt=plt)
ax = plt.gca()
if zero_to_efermi:
bs.bands = {s: b - bs.efermi for s, b in bs.bands.items()}
bs.efermi = 0
bs_plotter = BSPlotter(bs)
plot_data = bs_plotter.bs_plot_data(zero_to_efermi=zero_to_efermi)
energies = np.linspace(emin, emax, int((emax - emin) / estep))
distances = np.array([d for x in plot_data["distances"] for d in x])
# rates are currently log(rate)
mesh_data = np.full((len(distances), len(energies)), 0.0)
for spin in self.spins:
for spin_energies, spin_rates in zip(bs.bands[spin], rates[spin]):
for d_idx in range(len(distances)):
energy = spin_energies[d_idx]
linewidth = 10 ** spin_rates[d_idx] * hbar / 2
broadening = lorentzian(energies, energy, linewidth)
broadening /= 1000 # convert 1/eV to 1/meV
mesh_data[d_idx] += broadening
im = ax.pcolormesh(
distances,
energies,
mesh_data.T,
rasterized=True,
cmap=cmap,
norm=LogNorm(vmin=amin, vmax=amax),
shading="auto",
)
if colorbar:
pos = ax.get_position()
cax = plt.gcf().add_axes([pos.x1 + 0.035, pos.y0, 0.035, pos.height])
cbar = plt.colorbar(im, cax=cax)
cbar.ax.tick_params(axis="y", length=rcParams["ytick.major.size"] * 0.5)
cbar.ax.set_ylabel(
r"$A_\mathbf{k}$ (meV$^{-1}$)", rotation=270, va="bottom"
)
_maketicks(ax, bs_plotter, ylabel=ylabel)
_makeplot(
ax,
plot_data,
bs,
zero_to_efermi=zero_to_efermi,
width=width,
height=height,
ymin=emin,
ymax=emax,
aspect=aspect,
)
return plt
from __future__ import division, unicode_literals, print_function
"""
reads in KPOINTS(with labels for high symmetry kpoints) and
vasprun.xml files and plots the band structure along the high
symmetry kpoints
"""
# To use matplotlib on Hipergator, uncomment the following 2 lines:
# import matplotlib
# matplotlib.use('Agg')
from pymatgen.io.vasp.outputs import Vasprun
from pymatgen.electronic_structure.plotter import BSPlotterProjected, BSPlotter
if __name__ == "__main__":
# readin bandstructure from vasprun.xml and labeled KPOINTS
run = Vasprun("vasprun.xml", parse_projected_eigen=True)
bands = run.get_band_structure("KPOINTS", line_mode=True, efermi=run.efermi)
bsp = BSPlotter(bands)
# Blue lines are up spin, red lines are down spin
bsp.save_plot("band_diagram.eps", ylim=(-5, 5))
# bsp = BSPlotterProjected(bands)
# plt = bsp.get_projected_plots_dots( {'Fe':['s', 'p', 'd'],
# 'Sb':['s', 'p', 'd']})
# get_elt_projected_plots_color()