def plot_local_potential(axis=2, ylim=(-20, 0), fmt='pdf'):
"""
Plot data from the LOCPOT file along any of the 3 primary axes.
Useful for determining surface dipole moments and electric
potentials on the interior of the material.
Args:
axis (int): 0 = x, 1 = y, 2 = z
ylim (tuple): minimum and maximum potentials for the plot's y-axis.
fmt (str): matplotlib format style. Check the matplotlib docs
for options.
"""
ax = plt.figure(figsize=(16, 10)).gca()
locpot = Locpot.from_file('LOCPOT')
structure = Structure.from_file('CONTCAR')
vd = VolumetricData(structure, locpot.data)
abs_potentials = vd.get_average_along_axis(axis)
vacuum_level = max(abs_potentials)
vasprun = Vasprun('vasprun.xml')
bs = vasprun.get_band_structure()
if not bs.is_metal():
cbm = bs.get_cbm()['energy'] - vacuum_level
vbm = bs.get_vbm()['energy'] - vacuum_level
potentials = [potential - vacuum_level for potential in abs_potentials]
axis_length = structure.lattice._lengths[axis]
positions = np.arange(0, axis_length, axis_length / len(potentials))
ax.plot(positions, potentials, linewidth=2, color='k')
ax.set_xlim(0, axis_length)
ax.set_ylim(ylim[0], ylim[1])
ax.set_xticklabels(
[r'$\mathrm{%s}$' % tick for tick in ax.get_xticks()], size=20)
ax.set_yticklabels(
[r'$\mathrm{%s}$' % tick for tick in ax.get_yticks()], size=20)
ax.set_xlabel(r'$\mathrm{\AA}$', size=24)
ax.set_ylabel(r'$\mathrm{V\/(eV)}$', size=24)
if not bs.is_metal():
ax.text(ax.get_xlim()[1], cbm, r'$\mathrm{CBM}$',
horizontalalignment='right', verticalalignment='bottom',
size=20)
ax.text(ax.get_xlim()[1], vbm, r'$\mathrm{VBM}$',
horizontalalignment='right', verticalalignment='top', size=20)
ax.fill_between(ax.get_xlim(), cbm, ax.get_ylim()[1],
facecolor=plt.cm.jet(0.3), zorder=0, linewidth=0)
ax.fill_between(ax.get_xlim(), ax.get_ylim()[0], vbm,
facecolor=plt.cm.jet(0.7), zorder=0, linewidth=0)
if fmt == "None":
return ax
else:
plt.savefig('locpot.{}'.format(fmt))
plt.close()
def plot_local_potential(axis=2, ylim=(-20, 0), fmt='pdf'):
"""
Plot data from the LOCPOT file along any of the 3 primary axes.
Useful for determining surface dipole moments and electric
potentials on the interior of the material.
Args:
axis (int): 0 = x, 1 = y, 2 = z
ylim (tuple): minimum and maximum potentials for the plot's y-axis.
fmt (str): matplotlib format style. Check the matplotlib docs
for options.
"""
ax = plt.figure(figsize=(16, 10)).gca()
locpot = Locpot.from_file('LOCPOT')
structure = Structure.from_file('CONTCAR')
vd = VolumetricData(structure, locpot.data)
abs_potentials = vd.get_average_along_axis(axis)
vacuum_level = max(abs_potentials)
vasprun = Vasprun('vasprun.xml')
bs = vasprun.get_band_structure()
if not bs.is_metal():
cbm = bs.get_cbm()['energy'] - vacuum_level
vbm = bs.get_vbm()['energy'] - vacuum_level
potentials = [potential - vacuum_level for potential in abs_potentials]
axis_length = structure.lattice.lengths[axis]
positions = np.arange(0, axis_length, axis_length / len(potentials))
ax.plot(positions, potentials, linewidth=2, color='k')
ax.set_xlim(0, axis_length)
ax.set_ylim(ylim[0], ylim[1])
ax.set_xticklabels(
[r'$\mathrm{%s}$' % tick for tick in ax.get_xticks()], size=20)
ax.set_yticklabels(
[r'$\mathrm{%s}$' % tick for tick in ax.get_yticks()], size=20)
ax.set_xlabel(r'$\mathrm{\AA}$', size=24)
ax.set_ylabel(r'$\mathrm{V\/(eV)}$', size=24)
if not bs.is_metal():
ax.text(ax.get_xlim()[1], cbm, r'$\mathrm{CBM}$',
horizontalalignment='right', verticalalignment='bottom',
size=20)
ax.text(ax.get_xlim()[1], vbm, r'$\mathrm{VBM}$',
horizontalalignment='right', verticalalignment='top', size=20)
ax.fill_between(ax.get_xlim(), cbm, ax.get_ylim()[1],
facecolor=plt.cm.jet(0.3), zorder=0, linewidth=0)
ax.fill_between(ax.get_xlim(), ax.get_ylim()[0], vbm,
facecolor=plt.cm.jet(0.7), zorder=0, linewidth=0)
if fmt == "None":
return ax
else:
plt.savefig('locpot.{}'.format(fmt))
plt.close()
def get_freysoldt_correction(defect_type, defect_specie, path_to_defect_locpot,path_to_pure_locpot,charge,
dielectric_constant,defect_site_coordinates,energy_cutoff=500,get_plot=False):
''' Function to perform charge corrections according to the method proposed py Freysoldt
If this correction is used, please reference Freysoldt's original paper.
doi: 10.1103/PhysRevLett.102.016402
Args:
defect_type: 'vacancy' or 'interstitial'
defect_specie: string with element occupying the defect site
path_to_defect_locpot: path to LOCPOT file of defect structure
path_to_pure_locpot: path to LOCPOT file of Pure structure
charge: Charge of the defected system
dielectric_constant: Dielectric constant
defect_site_coordinates: numpy array with fractional coordinates of defect site
energy_cutoff: Cut-off of plane wave expansion
get_plot: return also Matplotlib object with plot
Returns:
Freysoldt corrections values as a dictionary
'''
# acquiring data from LOCPOT files
locpot_pure = Locpot.from_file(path_to_pure_locpot)
vol_data_pure = VolumetricData(locpot_pure.structure,locpot_pure.data)
locpot_defect = Locpot.from_file(path_to_defect_locpot)
vol_data_defect = VolumetricData(locpot_defect.structure,locpot_defect.data)
parameters = {}
parameters['axis_grid'] = []
parameters['bulk_planar_averages'] = []
parameters['defect_planar_averages'] = []
for i in range(0,3):
parameters['axis_grid'].append(vol_data_pure.get_axis_grid(i))
parameters['bulk_planar_averages'].append(vol_data_pure.get_average_along_axis(i))
parameters['defect_planar_averages'].append(vol_data_defect.get_average_along_axis(i))
parameters['initial_defect_structure'] = locpot_defect.structure
parameters['defect_frac_sc_coords'] = defect_site_coordinates
structure_bulk = locpot_pure.structure
defect_site = PeriodicSite(defect_specie, coords=defect_site_coordinates, lattice = locpot_pure.structure.lattice)
module = importlib.import_module("pymatgen.analysis.defects.core")
defect_class = getattr(module,defect_type)
defect = defect_class(structure_bulk, defect_site, charge=charge, multiplicity=None)
defect_entry = DefectEntry(defect,None,corrections=None,parameters=parameters)
freysoldt_class = FreysoldtCorrection(dielectric_constant,energy_cutoff=energy_cutoff)
freysoldt_corrections = freysoldt_class.get_correction(defect_entry)
if get_plot:
plt = freysoldt_class.plot(1)
return freysoldt_corrections , plt
else:
return freysoldt_corrections
def from_file(cls, filename):
(poscar, data, data_aug) = VolumetricData.parse_file(filename)
return cls(poscar, data, data_aug=data_aug)