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pydos
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pydos
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#!/usr/bin/env python
from __future__ import print_function
import os, re
import numpy as np
from ase.io import read
from optparse import OptionParser
import matplotlib as mpl
mpl.use('agg')
mpl.rcParams['axes.unicode_minus'] = False
import matplotlib.pyplot as plt
from matplotlib.ticker import AutoMinorLocator
from matplotlib.patches import Polygon
import matplotlib.colors as mcolors
############################################################
__version__ = "1.0"
############################################################
def parseList(string):
def parseRange(rng):
# print(rng)
m = re.match(r'(\d+)(?:[-:](\d+))?(?:[-:](\d+))?$', rng)
if not m:
raise ValueError(
"""
The band index should be assigned with combination of the following ways:
-> 10, a single band with index 10
-> 20:30, or '20-30', a continuous range from 20 to 30, 30 included
-> 30:50:2, or '30-50:2', a continues range from 30 to 50, with step size 2
-> '1 2 3', all the patterns above in one string separated by spaces.
For example: '1 4:6 8:16:2' will be converted to '1 4 5 6 8 10 12 14 16'
"""
)
ii = m.group(1)
jj = m.group(2) or ii
ss = m.group(3) or 1
return [x-1 for x in range(int(ii), int(jj)+1, int(ss))]
ret = []
for rng in string.split():
ret += parseRange(rng)
return list(set(ret))
def getElemIdx(poscar='POSCAR'):
'''
Get the atom indices corresponding to elements in POSCAR
- poscar: POSCAR file name, default is 'POSCAR'
returns a dictionary with keys are symbols, vals are list of
corresponding indices, starting from 0
e.g. { 'Mo': [0, 1],
'S': [2, 3, 4, 5],
'Se': [6, 7],
'W': [8]}
Ionizing
'''
pos = read(poscar)
symb_num = {}
for idx, elem in enumerate(pos.get_chemical_symbols()):
if elem not in symb_num:
symb_num[elem] = [idx]
else:
symb_num[elem].append(idx)
return symb_num
def parseSpdProjection(spd):
'''
Parse spdProjections string. str -> [int]
# Ionizing
'''
spd_dict = {
's' : [0],
'p' : [1, 2, 3],
'd' : [4, 5, 6, 7, 8],
'f' : [9, 10, 11, 12, 13, 14, 15],
'py' : [1],
'pz' : [2],
'px' : [3],
'dxy' : [4],
'dyz' : [5],
'dz2' : [6],
'dxz' : [7],
'dx2' : [8],
"fy(3x2-y2)" : [9],
"fxyz " : [10],
"fyz2 " : [11],
"fz3 " : [12],
"fxz2 " : [13],
"fz(x2-y2)" : [14],
"fx(x2-3y2) " : [15],
}
ret = []
for l in spd.split():
try:
assert int(l) <= 15, "Maximum spd index should be <= 15."
ret += [int(l)]
except:
if l.lower() not in spd_dict:
raise ValueError(
"Spd-projected wavefunction character of each KS orbital.\n"
" s orbital: 0\n"
" py, pz, px orbital: 1 2 3\n"
" dxy, dyz, dz2, dxz, dx2 orbital: 4 5 6 7 8 \n"
" fy(3x2-y2), fxyz, fyz2, fz3, fxz2, fz(x2-y2), fx(x2-3y2) orbital: 9 10 11 12 13 14 15\n"
"\nFor example, --spd 's dxy 10' specifies the s/dxy/fxyz components\n"
)
ret += spd_dict[l]
return list(set(ret))
def WeightFromPro(infile='PROCAR', lsorbit=False):
"""
Contribution of selected atoms to the each KS orbital
"""
assert os.path.isfile(infile), '%s cannot be found!' % infile
FileContents = [line for line in open(infile) if line.strip()]
# when the band number is too large, there will be no space between ";" and
# the actual band number. A bug found by Homlee Guo.
# Here, #kpts, #bands and #ions are all integers
nkpts, nbands, nions = [int(xx) for xx in re.sub(
'[^0-9]', ' ', FileContents[1]).split()]
# Weights = np.asarray([line.split()[-1] for line in FileContents
# if not re.search('[a-zA-Z]', line)], dtype=float)
Weights = np.asarray([line.split()[1:-1] for line in FileContents
if not re.search('[a-zA-Z]', line)], dtype=float)
kpt_weight = np.asarray(
[line.split()[-1] for line in FileContents if 'weight' in line], dtype=float)
energies = np.asarray([line.split()[-4] for line in FileContents
if 'occ.' in line], dtype=float)
nlmax = Weights.shape[-1]
nspin = Weights.shape[0] // (nkpts * nbands * nions)
nspin //= 4 if lsorbit else 1
if lsorbit:
Weights.resize(nspin, nkpts, nbands, 4, nions, nlmax)
Weights = Weights[:, :, :, 0, :, :]
else:
Weights.resize(nspin, nkpts, nbands, nions, nlmax)
kpt_weight.resize(nspin, nkpts)
energies.resize(nspin, nkpts, nbands)
return energies, kpt_weight, Weights
############################################################
def gradient_fill(x, y, fill_color=None, ax=None, direction=1, **kwargs):
"""
Plot a line with a linear alpha gradient filled beneath it.
Parameters
----------
x, y : array-like
The data values of the line.
fill_color : a matplotlib color specifier (string, tuple) or None
The color for the fill. If None, the color of the line will be used.
ax : a matplotlib Axes instance
The axes to plot on. If None, the current pyplot axes will be used.
Additional arguments are passed on to matplotlib's ``plot`` function.
Returns
-------
line : a Line2D instance
The line plotted.
im : an AxesImage instance
The transparent gradient clipped to just the area beneath the curve.
"""
line, = ax.plot(x, y, **kwargs)
if fill_color is None:
fill_color = line.get_color()
# print fill_color
zorder = line.get_zorder()
alpha = line.get_alpha()
alpha = 1.0 if alpha is None else alpha
z = np.empty((100, 1, 4), dtype=float)
rgb = mcolors.colorConverter.to_rgb(fill_color)
z[:, :, :3] = rgb
if direction == 1:
z[:, :, -1] = np.linspace(0, alpha, 100)[:, None]
else:
z[:, :, -1] = np.linspace(alpha, 0, 100)[:, None]
xmin, xmax, ymin, ymax = x.min(), x.max(), y.min(), y.max()
im = ax.imshow(z, aspect='auto', extent=[xmin, xmax, ymin, ymax],
origin='lower', zorder=zorder)
xy = np.column_stack([x, y])
if direction == 1:
xy = np.vstack([[xmin, ymin], xy, [xmax, ymin], [xmin, ymin]])
else:
xy = np.vstack([[xmin, ymax], xy, [xmax, ymax], [xmin, ymax]])
clip_path = Polygon(xy, lw=0.0, facecolor='none',
edgecolor='none', closed=True)
ax.add_patch(clip_path)
im.set_clip_path(clip_path)
ax.autoscale(True)
return line, im
############################################################
def lorentz_smearing(x, x0, sigma=0.03):
'''
Lorentz smearing of a Delta function.
'''
return sigma / np.pi / ((x-x0)**2 + sigma**2)
def gaussian_smearing(x, x0, sigma=0.05):
'''
Gaussian smearing of a Delta function.
'''
smear = np.zeros(x.size)
condition = np.abs(x - x0) < (sigma * 5.)
smear[condition] = 1. / (np.sqrt(2*np.pi) * sigma) * \
np.exp(-(x[condition] - x0)**2 / (2*sigma**2))
return smear
def gaussian_smearing_org(x, x0, sigma=0.05):
'''
Gaussian smearing of a Delta function.
'''
return 1. / (np.sqrt(2*np.pi) * sigma) * np.exp(-(x - x0)**2 / (2*sigma**2))
def generateDos(opts):
'''
generate dos
'''
ens, kptw, whts = WeightFromPro(opts.procar, opts.lsorbit)
nspin, nkpts, nbands, nions, nlmax = whts.shape
emin = ens.min()
emax = ens.max()
eran = emax - emin
emin = emin - eran * opts.extra
emax = emax + eran * opts.extra
xen = np.linspace(emin, emax, opts.nedos)
# tDOS = np.empty((opts.nedos, nspin))
pDOS = []
# make all the k-points weight equal
if opts.homoKpts:
kptw[...] = 1.0
tdos_smear = np.empty((nspin, nkpts, nbands, opts.nedos))
for IS in range(nspin):
sign = 1 if IS == 0 else -1
for Ik in range(nkpts):
for Ib in range(nbands):
x0 = ens[IS, Ik, Ib]
# tdos_smear[IS, Ik, Ib] = sign * gaussian_smearing(xen, x0, opts.sigma) * kptw[IS, Ik]
tdos_smear[IS, Ik, Ib] = sign * \
gaussian_smearing_org(xen, x0, opts.sigma) * kptw[IS, Ik]
# tdos_smear[IS, Ik, Ib] = sign * lorentz_smearing(xen, x0, opts.sigma) * kptw[IS, Ik]
tDOS = np.sum(tdos_smear, axis=(1, 2)).T
# tdos_smear = np.empty((nspin, nkpts, nbands, opts.nedos))
# for IS in range(nspin):
# sign = 1 if IS == 0 else -1
# for Ik in range(nkpts):
# tdos_smear[IS, Ik, :] = sign * gaussian_smearing_org(xen[np.newaxis, ...],
# ens[IS,Ik,:,np.newaxis], opts.sigma) * kptw[IS, Ik]
# tDOS = np.sum(tdos_smear, axis=(1, 2)).T
# tdos_smear = gaussian_smearing_org(xen[np.newaxis,...], ens[...,np.newaxis],
# opts.sigma) * kptw[..., np.newaxis, np.newaxis]
# tDOS = np.sum(tdos_smear, axis=(1, 2)).T
# if nspin == 2: tDOS[:,1] *= -1
if len(opts.elem_list) != 0:
elem_idx = getElemIdx(opts.posfile)
for elem in opts.elem_list:
if elem.upper() == 'XX':
opts.pdosAtom = [
' '.join([str(i+1) for i in elem_idx[k]]) for k in elem_idx]
# print(opts.pdosAtom)
opts.pdosLabel = list(elem_idx.keys())
break
opts.pdosAtom.append(" ".join([str(i+1) for i in elem_idx[elem]]))
opts.pdosLabel.append(elem)
if len(opts.pdosAtom) != 0:
# add a factor for each PDOS
factor = np.ones(len(opts.pdosAtom))
for ii in range(min(len(opts.pdosAtom), len(opts.pdosFactor))):
factor[ii] = opts.pdosFactor[ii]
# only plot DOS from selected kpoints, default from all kpoints
selected_kpts_index = [slice(None, None)
for ii in range(len(opts.pdosAtom))]
for ii in range(min(len(opts.pdosAtom), len(opts.pdosKpts))):
alist = np.array(opts.pdosKpts[ii].split(), dtype=int)
# index starting from 1
assert np.max(
alist) <= nkpts, "Maximum kpoint index must <{:d}".format(nkpts)
assert np.min(alist) >= 1, "Minimum kpoint index must >=1"
nlist = [x for x in alist if not x == -1]
cmark, = np.where(alist == -1)
for ii in cmark:
nlist += range(alist[ii + 1], alist[ii + 2] + 1)
# index starting from 0
nlist = [x - 1 for x in set(nlist)]
selected_kpts_index[ii] = nlist
for ia, atoms in enumerate(opts.pdosAtom):
# p = np.zeros((opts.nedos, nspin))
# alist = np.array(atoms.split(), dtype=int)
if '0' in atoms.split():
nlist = range(nions)
else:
nlist = parseList(atoms)
# nlist = [x for x in alist if not x == -1]
# cmark, = np.where(alist == -1)
# for ii in cmark:
# nlist += range(alist[ii + 1], alist[ii + 2] + 1)
# nlist = [x - 1 for x in set(nlist)]
if ia <= len(opts.spdProjections) - 1:
# spdList = [int(x) for x in opts.spdProjections[ia].split()]
spdList = parseSpdProjection(opts.spdProjections[ia]) # Ionizing
pwhts = np.sum(whts[..., spdList], axis=-1)
else:
pwhts = np.sum(whts, axis=-1)
pwhts = np.sum(pwhts[:, :, :, nlist], axis=-1)
# p = np.sum(pwhts[..., np.newaxis] * tdos_smear, axis=(1, 2)).T
p = np.sum(pwhts[:, selected_kpts_index[ia], :, np.newaxis] *
tdos_smear[:, selected_kpts_index[ia], ...], axis=(1, 2)).T
for IS in range(nspin):
sign = 1 if IS == 0 else -1
p[:, IS] = opts.pdosOffset * ia * sign + p[:, IS] * factor[ia]
if ia == 0:
tDOS[:, IS] += sign * opts.pdosOffset * len(opts.pdosAtom)
pDOS += [p]
return xen, tDOS, pDOS
############################################################
def readDOSFromFile(opts):
'''
Read DOS info from file.
the format of the DOS file:
first line: ISPIN, NEDOS
second line: labels of the dos
next lines:
if ISPIN = 1:
Energy pDOS1 PDOS2 ... TotalDOS
else:
Energy pDOS1_up PDOS2_up ... TotalDOS_up pDOS1_down PDOS2_down ... TotalDOS_down
'''
inp = open(opts.dosFromFile).readlines()
# the dos basic info
nspin, nedos = [int(x) for x in inp[0].split()[1:]]
labels = inp[1].split()[1:]
# data
DOS = np.array([line.split() for line in inp[2:] if line.strip()],
dtype=float)
NoPdos = (DOS.shape[1] - 1) // nspin - 1
tDOS = np.empty((nedos, nspin))
pDOS = []
xen = DOS[:, 0]
for ii in range(nspin):
tDOS[:, ii] = DOS[:, (ii + 1) * (NoPdos + 1)]
for pp in range(NoPdos):
tmp = []
for ii in range(nspin):
tmp += [DOS[:, (pp + 1) + ii * (NoPdos + 1)]]
pDOS += [np.array(tmp).T]
opts.nedos = nedos
opts.pdosAtom = ['' for x in range(NoPdos)]
opts.pdosLabel = labels
return xen, tDOS, pDOS
def saveDOSToFile(opts, xen, tDOS, pDOS):
'''
save DOS info to file.
the format of the DOS file:
first line: ISPIN, NEDOS
second line: labels of the dos
next lines:
if ISPIN = 1:
Energy pDOS1 PDOS2 ... TotalDOS
else:
Energy pDOS1_up PDOS2_up ... TotalDOS_up pDOS1_down PDOS2_down ... TotalDOS_down
'''
nspin = tDOS.shape[1]
nedos = tDOS.shape[0]
NoPdos = len(pDOS)
out = open(opts.dosToFile, 'w')
out.write('# %5d %8d\n' % (nspin, nedos))
labels = '# ' + ' '.join(opts.pdosLabel) + '\n'
out.write(labels)
for nn in range(nedos):
line = '%8.4f ' % xen[nn]
for ii in range(nspin):
for p in pDOS:
line += '%8.4f ' % p[nn, ii]
line += '%8.4f ' % tDOS[nn, ii]
line += '\n'
out.write(line)
############################################################
def dosplot(xen, tdos, pdos, opts):
'''
Use matplotlib to plot band structure
'''
width, height = opts.figsize
xmin, xmax = opts.xlim
dpi = opts.dpi
plt.style.use(opts.mpl_style)
# DO NOT use unicode minus regardless of the style
mpl.rcParams['axes.unicode_minus'] = False
fig = plt.figure()
fig.set_size_inches(width, height)
ax = plt.subplot(111)
LINES = []
nspin = tdos.shape[1]
plabels = []
LWs = []
LCs = []
if opts.pdosAtom:
plabels = ['p_%d' % ii for ii in range(len(opts.pdosAtom))]
LWs = [0.5 for ii in range(len(opts.pdosAtom))]
LCs = [None for ii in range(len(opts.pdosAtom))]
for ii in range(min(len(opts.pdosAtom), len(opts.pdosLabel))):
plabels[ii] = opts.pdosLabel[ii]
for ii in range(min(len(opts.pdosAtom), len(opts.linewidth))):
LWs[ii] = opts.linewidth[ii]
for ii in range(min(len(opts.pdosAtom), len(opts.linecolors))):
LCs[ii] = opts.linecolors[ii]
plabels += ['total']
xen -= opts.zero
for ip, p in enumerate(pdos):
for ii in range(nspin):
fill_direction = 1 if ii == 0 else -1
lc = LCs[ip] if ii == 0 else line.get_color()
if opts.fill:
line, im = gradient_fill(xen, p[:, ii], ax=ax, lw=LWs[ip],
color=lc,
direction=fill_direction)
else:
line, = ax.plot(xen, p[:, ii], lw=LWs[ip], alpha=0.6,
color=lc)
if ii == 0:
LINES += [line]
if opts.showtotal:
for ii in range(nspin):
fill_direction = 1 if ii == 0 else -1
lc = 'k' if ii == 0 else line.get_color()
if opts.fill:
line, im = gradient_fill(xen, tdos[:, ii], ax=ax,
color=lc,
lw=0.5,
# zorder=-1,
direction=fill_direction,
)
else:
line, = ax.plot(xen, tdos[:, ii], color=lc,
lw=0.5, alpha=0.6)
if ii == 0:
LINES += [line]
ax.set_xlabel('Energy [eV]', # fontsize='small',
labelpad=5)
ax.set_ylabel('DOS [arb. unit]', # fontsize='small',
labelpad=10)
ax.tick_params(which='both', labelsize='small')
ax.set_xlim(xmin, xmax)
if opts.ylim is not None:
ymin, ymax = opts.ylim
ax.set_ylim(ymin, ymax)
# ax.set_yticklabels([])
ax.xaxis.set_minor_locator(AutoMinorLocator(2))
ax.yaxis.set_minor_locator(AutoMinorLocator(2))
opts.pdosLabel = plabels
ax.legend(LINES, plabels,
loc=opts.legendloc,
fontsize='small',
frameon=True,
framealpha=0.6)
plt.tight_layout(pad=0.50)
plt.savefig(opts.dosimage, dpi=opts.dpi)
############################################################
def command_line_arg():
usage = "usage: %prog [options] arg1 arg2"
par = OptionParser(usage=usage, version=__version__)
par.add_option("-i", '--input',
action='store', type="string", dest='procar',
default='PROCAR',
help='location of the PROCAR')
par.add_option("-p", '--pdos',
action='append', type="string", dest='pdosAtom',
default=[],
help='specify which atoms to plot the pdos, 0 for all atoms')
par.add_option("-k", '--kpts',
action='append', type="string", dest='pdosKpts',
default=[],
help='specify which k-points to plot the pdos')
par.add_option("--homokpts",
action='store_true', dest='homoKpts',
default=False,
help='Homogeneous k-points weights')
par.add_option('--pdosoffset',
action='store', type="float", dest='pdosOffset',
default=0.0,
help='offset in pdos plot')
par.add_option("-l", '--label',
action='append', type="string", dest='pdosLabel',
default=[],
help='label of the pdos')
par.add_option('--lloc',
action='store', type="string", dest='legendloc',
default='upper right',
help='legend location of dos plot')
par.add_option('--fac',
action='append', type="float", dest='pdosFactor',
default=[],
help='scale factor of the pdos')
par.add_option('-z', '--zero',
action='store', type="float",
dest='zero', default=0.0,
help='energy reference of the band plot')
par.add_option('--sigma',
action='store', type="float",
dest='sigma', default=0.05,
help='smearing parameter, default 0.05')
par.add_option('-n', '--nedos',
action='store', type="int",
dest='nedos', default=5000,
help='number of point in DOS plot')
par.add_option('-o', '--output',
action='store', type="string", dest='dosimage',
default='dos.png',
help='output image name, "dos.png" by default')
par.add_option('-s', '--size', nargs=2,
action='store', type="float", dest='figsize',
default=(4.8, 3.0),
help='figure size of the output plot')
par.add_option('-x', nargs=2,
action='store', type="float", dest='xlim',
default=(-6, 6),
help='x limit of the dos plot')
par.add_option('-y', nargs=2,
action='store', type="float", dest='ylim',
default=None,
help='energy range of the band plot')
par.add_option('-e',
action='store', type="float", dest='extra',
default=0.05,
help='extra energy range of the band plot')
par.add_option('--lw',
action='append', type="float", dest='linewidth',
default=[],
help='linewidth of the band plot')
par.add_option('--lc',
action='append', type="string", dest='linecolors',
default=[],
help='linecolors of the band plot')
par.add_option('--fill',
action='store_true', dest='fill',
default=True,
help='fill under the DOS')
par.add_option('--nofill',
action='store_false', dest='fill',
help='no fill under the DOS')
par.add_option('--dpi',
action='store', type="int", dest='dpi',
default=360,
help='resolution of the output image')
par.add_option('--tot',
action='store_true', dest='showtotal',
default=True,
help='show total dos')
par.add_option('--notot',
action='store_false', dest='showtotal',
help='not show total dos')
par.add_option('--style',
action='store', type='string', dest='mpl_style',
default='default',
help='plot style of matplotlib. See "plt.style.available" for list of available styles.')
par.add_option('--fromfile',
action='store', type='string', dest='dosFromFile',
default=None,
help='plot the dos contained in the file')
par.add_option('--tofile',
action='store', type='string', dest='dosToFile',
default=None,
help='save DOS to file.')
par.add_option('--spd',
action='append', type="string", dest='spdProjections',
default=[],
help="Spd-projected wavefunction character of each KS orbital.\n"
" s orbital: 0\n"
" py, pz, px orbital: 1 2 3\n"
" dxy, dyz, dz2, dxz, dx2 orbital: 4 5 6 7 8 \n"
" fy(3x2-y2), fxyz, fyz2, fz3, fxz2, fz(x2-y2), fx(x2-3y2) orbital: 9 10 11 12 13 14 15\n"
"\nFor example, --spd 's dxy 9\n"
)
par.add_option('--lsorbit',
action='store_true', dest='lsorbit',
help='Spin orbit coupling on, special treament of PROCAR')
par.add_option('-q', '--quiet',
action='store_true', dest='quiet',
help='not show the resulting image')
par.add_option('--elem',
action='append', type='string', dest='elem_list',
default=[],
help='display the PDOS of given element(s), if --elem == "XX", show all of them respectively.') # Ionizing
par.add_option('--poscar',
action='store', type='string', dest='posfile',
default='POSCAR',
help='specify which poscar to read, if "--elem" is not empty') # Ionizing
return par.parse_args()
############################################################
if __name__ == '__main__':
from time import time
opts, args = command_line_arg()
if opts.dosFromFile:
xen, tdos, pdos = readDOSFromFile(opts)
else:
t0 = time()
xen, tdos, pdos = generateDos(opts)
t1 = time()
print('DOS calc completed! Time Used: %.2f [sec]' % (t1 - t0))
t0 = time()
dosplot(xen, tdos, pdos, opts)
t1 = time()
print('DOS plot completed! Time Used: %.2f [sec]' % (t1 - t0))
# save dos to file
if opts.dosToFile:
saveDOSToFile(opts, xen, tdos, pdos)
if not opts.quiet:
try:
from subprocess import call
call(['feh', '-xdF', opts.dosimage])
except:
# do nothing if image view fails
pass