def test_init(self):
filepath = os.path.join(test_dir, 'PROCAR.simple')
p = Procar(filepath)
self.assertAlmostEqual(p.get_occupation(0, 'd')[Spin.up], 0)
self.assertAlmostEqual(
p.get_occupation(0, 's')[Spin.up], 0.35381249999999997)
self.assertAlmostEqual(p.get_occupation(0, 'p')[Spin.up], 1.19540625)
self.assertRaises(ValueError, p.get_occupation, 1, 'm')
self.assertEqual(p.nbands, 10)
self.assertEqual(p.nkpoints, 10)
self.assertEqual(p.nions, 3)
lat = Lattice.cubic(3.)
s = Structure(lat, ["Li", "Na", "K"],
[[0., 0., 0.], [0.25, 0.25, 0.25], [0.75, 0.75, 0.75]])
d = p.get_projection_on_elements(s)
self.assertAlmostEqual(d[Spin.up][2][2], {
'Na': 0.042,
'K': 0.646,
'Li': 0.042
})
filepath = os.path.join(test_dir, 'PROCAR')
p = Procar(filepath)
self.assertAlmostEqual(
p.get_occupation(0, 'dxy')[Spin.up], 0.96214813853000025)
self.assertAlmostEqual(
p.get_occupation(0, 'dxy')[Spin.down], 0.85796295426000124)
def process_PROCAR(self,
procar_path=None,
poscar_path=None,
dir_to_save=None):
"""
This function process PROCAR file obtained by VASP using pymatgen.io.vasp.outputs.Procar class
and saves ion_names, orbital_names and data array
data array contains projections in the following form: data[kpoint][band][ion_number][orbital_number]
All numberings start from 0
:param procar_path: path to PROCAR file
:param poscar_path: path to POSCAR file
:param dir_to_save: directory to save data
:return:
"""
if procar_path == None:
procar_path = self.procar_path
if poscar_path == None:
poscar_path = self.poscar_path
if dir_to_save == None:
dir_to_save = self.dir_to_save
procar = Procar(procar_path)
for key in procar.data.keys():
self.procar_data = procar.data[key]
self.orbital_names = procar.orbitals
self.ion_names = self._get_atom_types(poscar_path=poscar_path)
for var in ['procar_data', 'orbital_names', 'ion_names']:
self.save(var, dir_to_save)
def test_phase_factors(self):
filepath = os.path.join(test_dir, 'PROCAR.phase')
p = Procar(filepath)
self.assertAlmostEqual(p.phase_factors[Spin.up][0, 0, 0, 0],
-0.746+0.099j)
self.assertAlmostEqual(p.phase_factors[Spin.down][0, 0, 0, 0],
0.372-0.654j)
# Two Li should have same phase factor.
self.assertAlmostEqual(p.phase_factors[Spin.up][0, 0, 0, 0],
p.phase_factors[Spin.up][0, 0, 1, 0])
self.assertAlmostEqual(p.phase_factors[Spin.up][0, 0, 2, 0],
-0.053+0.007j)
self.assertAlmostEqual(p.phase_factors[Spin.down][0, 0, 2, 0],
0.027-0.047j)
def test_init(self):
filepath = os.path.join(test_dir, "PROCAR.simple")
p = Procar(filepath)
self.assertAlmostEqual(p.get_occupation(0, "d")[Spin.up], 0)
self.assertAlmostEqual(p.get_occupation(0, "s")[Spin.up], 0.35381249999999997)
self.assertAlmostEqual(p.get_occupation(0, "p")[Spin.up], 1.19540625)
self.assertRaises(ValueError, p.get_occupation, 1, "m")
self.assertEqual(p.nbands, 10)
self.assertEqual(p.nkpoints, 10)
self.assertEqual(p.nions, 3)
lat = Lattice.cubic(3.0)
s = Structure(lat, ["Li", "Na", "K"], [[0.0, 0.0, 0.0], [0.25, 0.25, 0.25], [0.75, 0.75, 0.75]])
d = p.get_projection_on_elements(s)
self.assertAlmostEqual(d[Spin.up][2][2], {"Na": 0.042, "K": 0.646, "Li": 0.042})
filepath = os.path.join(test_dir, "PROCAR")
p = Procar(filepath)
self.assertAlmostEqual(p.get_occupation(0, "dxy")[Spin.up], 0.96214813853000025)
self.assertAlmostEqual(p.get_occupation(0, "dxy")[Spin.down], 0.85796295426000124)
def test_init(self):
filepath = os.path.join(test_dir, 'PROCAR.simple')
p = Procar(filepath)
self.assertAlmostEqual(p.get_occupation(1, 'd'), 0)
self.assertAlmostEqual(p.get_occupation(1, 's'), 0.3538125)
self.assertAlmostEqual(p.get_occupation(1, 'p'), 1.19540625)
self.assertRaises(ValueError, p.get_occupation, 1, 'm')
self.assertEqual(p.nb_bands, 10)
self.assertEqual(p.nb_kpoints, 10)
lat = Lattice.cubic(3.)
s = Structure(lat, ["Li", "Na", "K"], [[0., 0., 0.],
[0.25, 0.25, 0.25],
[0.75, 0.75, 0.75]])
d = p.get_projection_on_elements(s)
self.assertAlmostEqual(d[1][2][2], {'Na': 0.042, 'K': 0.646, 'Li': 0.042})
filepath = os.path.join(test_dir, 'PROCAR')
p = Procar(filepath)
self.assertAlmostEqual(p.get_occupation(0, 'd'), 4.3698147704200059)
self.assertAlmostEqual(p.get_occupation(0, 'dxy'), 0.85796295426000124)
#%%
import os
from pymatgen.io.vasp import Vasprun
from pymatgen.electronic_structure.plotter import BSDOSPlotter
from pymatgen.io.vasp.outputs import Procar
os.chdir('/home/jinho93/oxides/perobskite/strontium-vanadate')
os.chdir('/home/jinho93/oxides/perobskite/strontium-Molybdate')
plt = BSDOSPlotter()
bands = Vasprun("./band/vasprun.xml").get_band_structure("./band/KPOINTS",
line_mode=True)
data = Procar("./band/PROCAR").data
# density of states
dosrun = Vasprun("./loptics/dos/prj/vasprun.xml")
plt.get_plot(bands, dosrun.complete_dos).show()
# %%
# ---------
# kpoints labels can be read from the built-in functions. Right now, set manually.
# path = HighSymmKpath(mg.Structure.from_file("./CONTCAR")).kpath["path"]
path = [["X", "\Gamma", "R", "A", "Z", "\Gamma"]]
labels = [
"X", r"$\boldsymbol{\Gamma}$", "R", "A", "Z", r"$\boldsymbol{\Gamma}$"
] #[r"$%s$" % lab for lab in path[0][0:6]]
# bands object prepared using pymatgen library. contains eigenvalue information
bands = Vasprun("./vasprun.xml").get_band_structure("./KPOINTS",
line_mode=True)
# projected bands read from procar files
data = Procar("./PROCAR").data
# set up matplotlib plot
# ----------------------
# general options for plot
font = {'family': 'serif', 'size': 20, 'weight': 'bold'}
plt.rc('font', **font)
markers = ("o", "^", "h", "*", "s", "D")
colorlist = ("r", "g", "b", "m", "c", "y")
# set ylim for the plot
# ---------------------
ax = plt.axes()
vasprun_file = 'vasprun_a_-4%.xml'
kpoints_file = 'KPOINTS'
procar_file = 'PROCAR_a_-4%'
saving_dictory = '/mnt/c/Users/a/OneDrive/Calculation_Data/Mg2C_Graphene/Picture/Band/'
saving_file = '{}'.format('Atom_' + Plot_Atom + '_Bands' +
vasprun_file.strip('vasprun' + '.xml'))
# vasprun.xml位置
vasprun = Vasprun("{}".format(vasprun_dirctory + vasprun_file),
parse_projected_eigen=True)
# 生成独立的band数据
bands = vasprun.get_band_structure("{}".format(vasprun_dirctory +
kpoints_file),
line_mode=True,
efermi=vasprun.efermi)
# 读取投影数据
procar = Procar("{}".format(vasprun_dirctory + procar_file))
Atom_symbol = vasprun.atomic_symbols
dot_size = np.zeros(((3, bands.nb_bands, len(bands.kpoints))))
for n in range(bands.nb_bands):
for k in range(len(bands.kpoints)):
# 挑选出投影原子的点大小数据
for atom_nb in range(len(Atom_symbol)):
if Atom_symbol[atom_nb] == Plot_Atom:
dot_size[0][n][k] += procar.data[
Spin.up][k][n][atom_nb][3] * 300
dot_size[1][n][k] += procar.data[
Spin.up][k][n][atom_nb][1] * 300
dot_size[2][n][k] += procar.data[
Spin.up][k][n][atom_nb][2] * 300
for nb_p in range(3):
# 选定能量区间
if __name__ == "__main__":
os.chdir('/home/jinho93/interface/pzt-bso/loose/opti/')
# Load Structure
structure = Structure.from_file("./band/dense/POSCAR")
# Load Band Structure Calculations
bands_K = Vasprun("./band/dense/vasprun.xml")
# Load Band Structure Calculations
bands = bands_K.get_band_structure("./band/dense/KPOINTS", line_mode=True)
# projected bands
data = Procar("./band/dense/PROCAR").data
# density of states
dosrun = Vasprun("./dos/vasprun.xml")
# labels
# general options for plot
# set up 2 graph with aspec ration 2/1
# plot 1: bands diagram
# plot 2: Density of States
gs = GridSpec(1, 2, width_ratios=[1, 1])
fig = plt.figure(figsize=(11.69, 8.27))
# fig.suptitle("$BN_2 Monolayer$")
ax1 = plt.subplot(gs[0])
ax2 = plt.subplot(gs[1]) # , sharey=ax1)
