def post(self):
import pandas as pd
df = pd.read_csv("strain_stress.txt",
sep=r"[ \t]",
engine="python",
skiprows=2,
header=None)
import numpy as np
df = np.array(df)
strain = df[:, 1] / df[0, 1] - 1
# convert to GPa
# metalE/metalV/(siE/siV)=metalE/siE*siV/metalV=1/u.si.E()*u.si.L()**2
tl.cd('minimize')
self.m.postMini()
tl.cd('..')
pxx = -df[:, 2] * 1e5 * 1e-9 * self.m.zfactor
from aces.graph import plot
plot((strain, 'Strain'), (pxx, 'Stress (GPa)'),
'stress.png',
linewidth=2,
grid=True)
dp = pd.DataFrame()
dp['Strain'] = strain
dp['Stress_GPa'] = pxx
dp.to_csv('cal_stress.txt', sep='\t', index=False, float_format="%f")
from scipy import stats
slope, intercept, r_value, p_value, std_err = stats.linregress(
strain[:50], pxx[:50])
self.YoungsModulus = slope
tl.write(slope, 'YoungsModulus.txt')
def prepareBand(self):
tl.mkcd('band')
# run vasp
tl.cp('../minimize/POSCAR', '.')
self.m.ismear = -1
self.getVaspRun_vasp()
tl.cd('..')
def getbol(self):
maindir = tl.pwd()
tl.mkcd('bol')
self.runscf()
self.runnscf()
self.runw()
tl.cd(maindir)
def profile(self):
m = self.m
tl.cd('minimize')
m.postMini()
tl.cd('..')
import profile
profile.run(**m.__dict__)
def getPhonons(self):
maindir = tl.pwd()
tl.mkcd('phonons')
self.runscf()
self.runph()
self.collect()
tl.cd(maindir)
def getvasprun(self, files):
m = self.m
maindir = pwd()
if m.engine == "vasp":
calculator = self.getVaspRun_vasp
elif m.engine == "lammps":
calculator = self.getVaspRun_lammps
self.jm = jobManager()
for file in files:
print(file)
dir = "dirs/dir_" + file
mkdir(dir)
mv(file, dir + '/POSCAR')
cd(dir)
calculator()
cd(maindir)
self.jm.run()
if m.th:
mkdir(m.pbsname)
self.thcode(files, m.pbsname)
cp("dirs", m.pbsname)
passthru("tar zcf %s.tar.gz %s" % (m.pbsname, m.pbsname))
print('start check')
self.jm.check()
if m.engine == "lammps1":
from multiprocessing.dummy import Pool
pool = Pool()
pool.map_async(lammpsvasprun, files)
pool.close()
pool.join()
def getbol(self):
maindir = tl.pwd()
tl.mkcd('bol')
self.runscf()
self.runnscf()
self.runw()
tl.cd(maindir)
def grtao(self):
cd('T300K')
# 画格林艾森系数与驰豫时间的关系
w = np.loadtxt('BTE.w_final')[:, 1]
w = np.abs(w)
q = np.loadtxt(open('../BTE.qpoints'))
n = len(q)
w = w.T.reshape([-1, n])
w = np.einsum('jk->kj', w)
w.flags.writeable = True
omega = np.loadtxt('../BTE.omega') / (2.0 * np.pi)
w[omega < omega.flatten().max() * 0.005] = float('nan')
tao = 1.0 / w + 1e-6
g = np.loadtxt('../BTE.gruneisen')
with fig("gruneisen_tao.png"):
pl.semilogy(
g.flatten(),
tao.flatten(),
ls='.',
marker='.',
color='r',
markersize=10)
pl.ylabel('Relaxation Time (ps)')
pl.xlabel('Gruneisen Coeffecient')
pl.xlim([-10, 5])
pl.ylim([0, 1e4])
def prepareet(self):
atoms = io.read('POSCAR')
from pyspglib import spglib
s = spglib.get_spacegroup(atoms)
from aces.scanf import sscanf
sgN = sscanf(s, '%s (%d)')[1]
sg = Spacegroup(sgN)
atoms.info = {'spacegroup': sg}
nelect = self.getNelect(outcar='band/OUTCAR')
# The remaining part takes care of writing the files required by
# BoltzTraP.
bandstructure = vasp2boltz.get_vasp_bandstructure(pathname='band/')
tl.mkcd('et')
vasp2boltz.write_bandstructure_boltztrap(
bandstructure, filename='et.energy')
vasp2boltz.write_structure_boltztrap(atoms, filename='et.struct')
vasp2boltz.write_intrans_boltztrap(
n_electrons=nelect, filename='et.intrans')
s = tl.read('et.energy')
s = s.replace('HTE', 'et')
tl.write(s, 'et.energy')
s = tl.read('et.struct')
s = s.replace('HTE', 'et')
tl.write(s, 'et.struct')
tl.cd('..')
def creatmini(self):
print('creatmini')
tl.mkdir('minimize')
tl.cd('minimize')
minimize_input(self.m)
tl.write(time.strftime('%Y-%m-%d %H:%M:%S'), 'done')
tl.cd('..')
def phonopy(self, dir, mm):
# if exists(dir+'/FORCE_CONSTANTS'):
# return
mkcd(dir)
self.creatmini(mm)
PRunner(mm).generate()
cd('..')
def run(self):
old = tl.pwd()
for job in self.jobs:
tl.cd(job.path)
job.writepbs()
job.submit()
tl.cd(old)
def checkMinimize(self):
import yaml
data = yaml.load(open('disp.yaml').read())
disps = [map(float, a['direction']) for a in data['displacements']]
maindir = pwd()
dirs = ls('dirs/dir_*')
ii = 0
L = np.linalg.norm
# d,p,d1,p1=self.m.rot
out = open('ccos.txt', 'w')
for dir in dirs:
cd(dir)
f = open('dump.force')
for i in range(9):
f.next()
for b in range(ii):
f.next()
line = f.next()
line = line.split()
force = np.array(map(float, line[1:4]))
# force=RotateVector(force,d1,-p1)
# force=RotateVector(force,d,-p)
d = disps[i]
ccos = force.dot(d) / L(force) / L(d)
ii += 1
print >> out, "%d\t%f" % (ii, ccos)
cd(maindir)
def run(self):
old = tl.pwd()
for job in self.jobs:
tl.cd(job.path)
job.writepbs()
job.submit()
tl.cd(old)
def prepareet(self):
atoms = io.read('POSCAR')
from pyspglib import spglib
s = spglib.get_spacegroup(atoms)
from aces.scanf import sscanf
sgN = sscanf(s, '%s (%d)')[1]
sg = Spacegroup(sgN)
atoms.info = {'spacegroup': sg}
nelect = self.getNelect(outcar='band/OUTCAR')
# The remaining part takes care of writing the files required by
# BoltzTraP.
bandstructure = vasp2boltz.get_vasp_bandstructure(pathname='band/')
tl.mkcd('et')
vasp2boltz.write_bandstructure_boltztrap(bandstructure,
filename='et.energy')
vasp2boltz.write_structure_boltztrap(atoms, filename='et.struct')
vasp2boltz.write_intrans_boltztrap(n_electrons=nelect,
filename='et.intrans')
s = tl.read('et.energy')
s = s.replace('HTE', 'et')
tl.write(s, 'et.energy')
s = tl.read('et.struct')
s = s.replace('HTE', 'et')
tl.write(s, 'et.struct')
tl.cd('..')
def getPhonons(self):
maindir = tl.pwd()
tl.mkcd('phonons')
self.runscf()
self.runph()
self.collect()
tl.cd(maindir)
def checkMinimize(self):
import yaml
data = yaml.load(open('disp.yaml').read())
disps = [map(float, a['direction']) for a in data['displacements']]
maindir = pwd()
dirs = ls('dirs/dir_*')
ii = 0
L = np.linalg.norm
# d,p,d1,p1=self.m.rot
out = open('ccos.txt', 'w')
for dir in dirs:
cd(dir)
f = open('dump.force')
for i in range(9):
f.next()
for b in range(ii):
f.next()
line = f.next()
line = line.split()
force = np.array(map(float, line[1:4]))
# force=RotateVector(force,d1,-p1)
# force=RotateVector(force,d,-p)
d = disps[i]
ccos = force.dot(d) / L(force) / L(d)
ii += 1
print >> out, "%d\t%f" % (ii, ccos)
cd(maindir)
def prepareet(self):
fermi = self.get_fermi()
nelect = self.get_nelect()
tl.mkcd('et')
tl.cp('../band/SYMMETRY', '.')
tl.cp('../band/EIGENVAL', '.')
tl.cp('../band/POSCAR', '.')
lpfac = 5
if(self.m.soc):
lpfac = 20
s = """VASP
0 1 0 0.0
%f 0.0005 0.40 %f
CALC
%d
BOLTZ
.15
800. 50.
0.
""" % (fermi, nelect, lpfac)
# Format of DOS
# iskip (not presently used) idebug setgap shiftgap
# Fermilevel (eV, please note), energygrid (Ry),\
# energy span around Fermilevel (Ry), No of electrons
# CALC (calculate expansion coeff), NOCALC read from file
# lpfac, number of latt-points per k-point
# run mode (only BOLTZ is supported)
# (efcut) energy range of chemical potential (Ry)
# Tmax, temperature grid
# energyrange of bands given individual \
# DOS output sig_xxx and dos_xxx (xxx is band number)
tl.write(s, "et.intrans")
tl.cd('..')
def getvasprun(self, files):
m = self.m
maindir = pwd()
if m.engine == "vasp":
calculator = self.getVaspRun_vasp
elif m.engine == "lammps":
calculator = self.getVaspRun_lammps
self.jm = jobManager()
for file in files:
print(file)
dir = "dirs/dir_" + file
mkdir(dir)
mv(file, dir + '/POSCAR')
cd(dir)
calculator()
cd(maindir)
self.jm.run()
if m.th:
mkdir(m.pbsname)
self.thcode(files, m.pbsname)
cp("dirs", m.pbsname)
passthru("tar zcf %s.tar.gz %s" % (m.pbsname, m.pbsname))
print('start check')
self.jm.check()
if m.engine == "lammps1":
from multiprocessing.dummy import Pool
pool = Pool()
pool.map_async(lammpsvasprun, files)
pool.close()
pool.join()
def runet(self):
tl.cd('et')
m = self.m
if(m.soc):
tl.passthru(config.x_trans_vasp + " BoltzTrap_vasp -so")
else:
tl.passthru(config.x_trans_vasp + " BoltzTrap_vasp")
tl.cd('..')
def run(name):
path=home(name)
if not exists(path):
workdir=shell_exec('pwd')
cd(dirname(path))
passthru("make")
cd(workdir)
passthru(path)
def prepareBand(self):
tl.mkcd('band')
# run vasp
tl.cp('../POSCAR', '.')
self.getVaspRun_vasp()
# cp('/home1/xggong/zhouy/tcscripts/sis/
# sis1.1/0/secondorder/dirs/dir_POSCAR-002/EIGENVAL','.')
# cp('/home1/xggong/zhouy/tcscripts/
# sis/sis1.1/0/secondorder/dirs/dir_POSCAR-002/OUTCAR','.')
tl.cd('..')
def prepareBand(self):
tl.mkcd('band')
# run vasp
tl.cp('../POSCAR', '.')
self.getVaspRun_vasp()
# cp('/home1/xggong/zhouy/tcscripts/sis/
# sis1.1/0/secondorder/dirs/dir_POSCAR-002/EIGENVAL','.')
# cp('/home1/xggong/zhouy/tcscripts/
# sis/sis1.1/0/secondorder/dirs/dir_POSCAR-002/OUTCAR','.')
tl.cd('..')
def getV(self):
if not exists('groupv'):
mkdir('groupv')
cd('groupv')
cp('../FORCE_CONSTANTS', '.')
cp('../POSCAR', '.')
cp('../disp.yaml', '.')
self.generate_vconf()
passthru(config.phonopy + "--tolerance=1e-4 v.conf")
self.drawV()
cd('..')
def getPotName(self):
maindir = tl.pwd()
tl.cd(config.qepot)
files = tl.ls("*")
tl.cd(maindir)
import re
q = [re.split("[_\.]", a)[0].capitalize() for a in files]
u = {}
for i, v in enumerate(q):
u[v] = files[i]
return u
def getV(self):
if not exists('groupv'):
mkdir('groupv')
cd('groupv')
cp('../FORCE_CONSTANTS', '.')
cp('../POSCAR', '.')
cp('../disp.yaml', '.')
self.generate_vconf()
passthru(config.phonopy + "--tolerance=1e-4 v.conf")
self.drawV()
cd('..')
def getPotName(self):
maindir = tl.pwd()
tl.cd(config.qepot)
files = tl.ls("*")
tl.cd(maindir)
import re
q = [re.split("[_\.]", a)[0].capitalize() for a in files]
u = {}
for i, v in enumerate(q):
u[v] = files[i]
return u
def getepw(self):
m = self.m
maindir = tl.pwd()
tl.mkcd('epw')
"""为了保证q+k也在k的格点上，必须要求qs*cell*[nk1,nk2,nk3]为整数，即nk=N*nq
否则可能出现Error in routine createkmap (1):
"""
u = np.array(m.ekpoints) / np.array(m.kpoints)
assert np.allclose(np.floor(u + .5), u, rtol=0.01)
self.runscf()
self.runnscf()
self.runepw()
tl.cd(maindir)
def runSPOSCAR(self):
m = self.m
maindir = pwd()
file = "SPOSCAR"
dir = "dir_" + file
mkdir(dir)
cp(file, dir + '/POSCAR')
cd(dir)
if m.engine == "vasp":
self.getVaspRun_vasp()
if m.engine == "lammps":
self.getVaspRun_lammps()
cd(maindir)
def runSPOSCAR(self):
m = self.m
maindir = pwd()
file = "SPOSCAR"
dir = "dir_" + file
mkdir(dir)
cp(file, dir + '/POSCAR')
cd(dir)
if m.engine == "vasp":
self.getVaspRun_vasp()
if m.engine == "lammps":
self.getVaspRun_lammps()
cd(maindir)
def getepw(self):
m = self.m
maindir = tl.pwd()
tl.mkcd('epw')
"""为了保证q+k也在k的格点上，必须要求qs*cell*[nk1,nk2,nk3]为整数，即nk=N*nq
否则可能出现Error in routine createkmap (1):
"""
u = np.array(m.ekpoints) / np.array(m.kpoints)
assert np.allclose(np.floor(u + .5), u, rtol=0.01)
self.runscf()
self.runnscf()
self.runepw()
tl.cd(maindir)
def creatmini(self, m):
print('creatmini')
m.home = pwd()
assert m.home != ''
mkdir('minimize')
cd('minimize')
minimize_input(m)
write(time.strftime('%Y-%m-%d %H:%M:%S'), 'done')
cd('..')
if m.engine == "lammps":
return m.dump2POSCAR(m.home + '/minimize/range')
else:
return io.read(m.home + '/minimize/CONTCAR')
def tDisorder():
# disorder degree*/
now = tl.pwd()
tl.cd('minimize')
tl.mkcd('disorder')
disorderLine = tl.shell_exec(
"cp %s" % SRCHOME + "/in.disorder .;" + config.lammps +
" <in.disorder 2>err 1>log;tail -1 disorder.txt 2>err;")
k = disorderLine.split()[1:3]
if len(k) == 1:
k.append("")
disorder, rd = k
tl.cd(now)
return (disorder, rd)
def generate(self):
m = self.m
coordination = self.phontsAtoms()
content0 = "species %d\n" % (len(m.elements)) + m.phontsmasses + """
D3_cutoff %f
kpoints %s 1
delta 0.005
numerical_2der T
numerical_3der T
iter_steps 3
pdos 0. 70. 200 10.
temp 60. 400. 10
AbInitio T F
FP_interface LAMMPS
#phonons_only T
Lattice 1.0
%s
end
""" % (m.shengcut, m.toString(m.kpoints), coordination)
tl.write(content0, 'phonons_input.dat')
tl.passthru(config.phonts) # generate many displacement files
tl.mkdir('lammps')
tl.cd('lammps')
content = "units %s\n" % m.units
content += """atom_style charge
dimension 3
boundary p p p
read_data GENERIC
%s
%s
neighbor 1.1 bin
neigh_modify every 1 delay 1 check yes
dump 1 all custom 1 *.dump id fx fy fz
dump_modify 1 format "%%d %%30.20f %%30.20f %%30.20f"
dump_modify 1 sort id
run 0
""" % (m.masses, m.potential)
tl.shell_exec("mv ../*.str .")
strs = tl.shell_exec("ls *.str").split("\n")
for str in strs:
dir = str.replace("str", "dir")
tl.mkdir(dir)
tl.write(content.replace("GENERIC", str), dir + "/in")
tl.mv(str, "%s/%s" % (dir, str))
tl.cd(dir)
tl.passthru(config.lammps + " <in >out.dat")
tl.cd('..')
dirs = tl.shell_exec("ls |grep dir").split("\n")
for dir in dirs:
print(dir)
tl.cp(dir + "/0.dump", "../" + dir.replace("dir", "out"))
tl.cp("1.0000.dir/out.dat", "../1.0000.out")
tl.cd('..')
content0 = content0.replace('AbInitio T F', 'AbInitio F T')
tl.write(content0, 'phonons_input.dat')
tl.passthru(config.phonts)
def generate(self):
m = self.m
coordination = self.phontsAtoms()
content0 = "species %d\n" % (len(m.elements)) + m.phontsmasses + """
D3_cutoff %f
kpoints %s 1
delta 0.005
numerical_2der T
numerical_3der T
iter_steps 3
pdos 0. 70. 200 10.
temp 60. 400. 10
AbInitio T F
FP_interface LAMMPS
#phonons_only T
Lattice 1.0
%s
end
""" % (m.shengcut, m.toString(m.kpoints), coordination)
tl.write(content0, 'phonons_input.dat')
tl.passthru(config.phonts) # generate many displacement files
tl.mkdir('lammps')
tl.cd('lammps')
content = "units %s\n" % m.units
content += """atom_style charge
dimension 3
boundary p p p
read_data GENERIC
%s
%s
neighbor 1.1 bin
neigh_modify every 1 delay 1 check yes
dump 1 all custom 1 *.dump id fx fy fz
dump_modify 1 format "%%d %%30.20f %%30.20f %%30.20f"
dump_modify 1 sort id
run 0
""" % (m.masses, m.potential)
tl.shell_exec("mv ../*.str .")
strs = tl.shell_exec("ls *.str").split("\n")
for str in strs:
dir = str.replace("str", "dir")
tl.mkdir(dir)
tl.write(content.replace("GENERIC", str), dir + "/in")
tl.mv(str, "%s/%s" % (dir, str))
tl.cd(dir)
tl.passthru(config.lammps + " <in >out.dat")
tl.cd('..')
dirs = tl.shell_exec("ls |grep dir").split("\n")
for dir in dirs:
print(dir)
tl.cp(dir + "/0.dump", "../" + dir.replace("dir", "out"))
tl.cp("1.0000.dir/out.dat", "../1.0000.out")
tl.cd('..')
content0 = content0.replace('AbInitio T F', 'AbInitio F T')
tl.write(content0, 'phonons_input.dat')
tl.passthru(config.phonts)
def tDisorder():
# disorder degree*/
now = tl.pwd()
tl.cd('minimize')
tl.mkcd('disorder')
disorderLine = tl.shell_exec(
"cp %s" %
SRCHOME +
"/in.disorder .;" +
config.lammps +
" <in.disorder 2>err 1>log;tail -1 disorder.txt 2>err;")
k = disorderLine.split()[1:3]
if len(k) == 1:
k.append("")
disorder, rd = k
tl.cd(now)
return (disorder, rd)
def vfc(self):
c = self.m.correlation_supercell
q = []
u = [int(x / 2) * 2 + 1 for x in c]
for i in range(u[0]):
for j in range(u[1]):
for k in range(u[2]):
b = np.array([
float(i - c[0] / 2) / c[0],
float(j - c[1] / 2) / c[1],
float(k - c[2] / 2) / c[2]
])
q.append(b)
m = self.m
tl.mkcd('vqpoints')
tl.cp('../FORCE_CONSTANTS', '.')
tl.cp('../disp.yaml', '.')
tl.cp('../POSCAR', '.')
Prun(m).getvqpoints(q)
tl.cd('..')
def vfc(self):
c = self.m.correlation_supercell
q = []
u = [int(x / 2) * 2 + 1 for x in c]
for i in range(u[0]):
for j in range(u[1]):
for k in range(u[2]):
b = np.array([
float(i - c[0] / 2) / c[0],
float(j - c[1] / 2) / c[1],
float(k - c[2] / 2) / c[2]
])
q.append(b)
m = self.m
tl.mkcd('vqpoints')
tl.cp('../FORCE_CONSTANTS', '.')
tl.cp('../disp.yaml', '.')
tl.cp('../POSCAR', '.')
Prun(m).getvqpoints(q)
tl.cd('..')
def getlead(self):
cd('center')
left = self.findlead('left')
right = self.findlead('right')
cd('..')
return
from aces.io.vasp import writevasp
mkcd('leftlead')
writevasp(left, 'POSCAR')
self.runlead()
cd('..')
mkcd('rightlead')
writevasp(right, 'POSCAR')
self.runlead()
cd('..')
def ineq(m):
now = tl.pwd()
species = m.species
if not (species in ["CN-small"]):
return 0.0
tl.cd('minimize')
tl.mkdir('nonequ')
tl.cd('nonequ')
ie = inequality()
nonequ5 = ie.run()
tl.cd(now)
return nonequ5
def ineq(m):
now = tl.pwd()
species = m.species
if not (species in ["CN-small"]):
return 0.0
tl.cd('minimize')
tl.mkdir('nonequ')
tl.cd('nonequ')
ie = inequality()
nonequ5 = ie.run()
tl.cd(now)
return nonequ5
def generate(self):
# m = self.m
self.minimizePOSCAR()
# cp('minimize/POSCAR','.')
mkdir('secondorder')
cd('secondorder')
self.pSecond()
self.fc2()
cd('..')
self.third()
self.vasprun3()
self.force_constant3()
cd('..')
self.pSheng()
self.runsheng()
def creatmini(self, dir):
cur = tl.pwd()
tl.mkdir(dir)
tl.cd(dir)
minimize_input(self.m)
tl.cd(cur)
def writeatoms(self, atoms, label='atoms'):
tl.mkcd(label)
self.watoms(atoms)
tl.cd('..')
def runet(self):
tl.cd('et')
tl.passthru(config.x_trans + " BoltzTraP")
tl.cd('..')
def creatmini(self, dir):
cur = tl.pwd()
tl.mkdir(dir)
tl.cd(dir)
minimize_input(self.m)
tl.cd(cur)
def writeatoms(self, atoms, label='atoms'):
tl.mkcd(label)
self.watoms(atoms)
tl.cd('..')
def post(self):
cd('T300K')
try:
df = pd.read_csv(
"BTE.kappa_scalar",
sep=r"[ \t]+",
header=None,
names=['step', 'kappa'],
engine='python')
ks = np.array(df['kappa'])
plot(
(np.array(df['step']), 'Iteration Step'),
(ks, 'Thermal Conductivity (W/mK)'),
'kappa_scalar.png',
grid=True,
linewidth=2)
except Exception as e:
print(e)
try:
df = pd.read_csv(
"BTE.cumulative_kappa_scalar",
sep=r"[ \t]+",
header=None,
names=['l', 'kappa'],
engine='python')
ks = np.array(df['kappa'])
plot(
(np.array(df['l']),
'Cutoff Mean Free Path for Phonons (Angstrom)'),
(ks, 'Thermal Conductivity (W/mK)'),
'cumulative_kappa_scalar.png',
grid=True,
linewidth=2,
logx=True)
except Exception as e:
print(e)
try:
omega = np.loadtxt('../BTE.omega') / (2.0 * np.pi)
kappa = np.loadtxt('BTE.kappa')[-1, 1:]
kappa = np.einsum('jji', kappa.reshape([3, 3, -1])) / 3.0
plot(
(np.arange(len(omega[0])), 'Band'),
(kappa, 'Thermal Conductivity (W/mK)'),
'kappa_band.png',
grid=True,
linewidth=2)
plot(
(np.arange(len(omega[0])), 'Band'),
(kappa.cumsum(), 'Thermal Conductivity (W/mK)'),
'cumulative_kappa_band.png',
grid=True,
linewidth=2)
except Exception as e:
print(e)
try:
kappa = np.loadtxt('BTE.cumulative_kappaVsOmega_tensor')
with fig("atc_freq.png"):
pl.plot(kappa[:, 0], kappa[:, 1], label="${\kappa_{xx}}$")
pl.plot(kappa[:, 0], kappa[:, 5], label="${\kappa_{xx}}$")
pl.plot(kappa[:, 0], kappa[:, 9], label="${\kappa_{xx}}$")
pl.xlabel("Frequency (THz)")
pl.ylabel("Cumulative Thermal Conductivity(W/mK)")
with fig("tc_freq.png"):
pl.plot(
kappa[:, 0],
np.gradient(kappa[:, 1]),
label="${\kappa_{xx}}$")
pl.plot(
kappa[:, 0],
np.gradient(kappa[:, 5]),
label="${\kappa_{xx}}$")
pl.plot(
kappa[:, 0],
np.gradient(kappa[:, 9]),
label="${\kappa_{xx}}$")
pl.xlabel("Frequency (THz)")
pl.ylabel("Cumulative Thermal Conductivity(W/mK)")
except Exception as e:
print(e)
try:
g = np.loadtxt('../BTE.gruneisen')
y = (g.flatten(), 'Gruneisen')
plot(
(omega.flatten(), 'Frequency (THz)'),
y,
'gruneisen_freq.png',
grid=True,
scatter=True)
with fig('gruneisen_freq.png'):
pl.scatter(
omega.flatten(), g.flatten(), marker='.', color='r', s=50)
pl.xlabel('Frequency (THz)')
pl.ylabel('Gruneisen Coeffecient')
# pl.grid(True)
pl.xlim([0, omega.max()])
pl.ylim([-10, 5])
# pl.tick_params(axis='both', which='major', labelsize=14)
to_txt(['freq', 'gruneisen'],
np.c_[omega.flatten(), g.flatten()], 'gruneisen_freq.txt')
g = np.loadtxt('../BTE.P3')
with fig('p3_freq.png'):
pl.scatter(
omega.flatten(),
g.flatten() * 1e6,
marker='.',
color='r',
s=50)
pl.xlabel('Frequency (THz)')
pl.ylabel('P3 $(\\times 10^{-6})$')
# pl.grid(True)
pl.xlim([0, omega.max()])
pl.ylim([0, g.max() * 1e6])
to_txt(['freq', 'p3'],
np.c_[omega.flatten(), g.flatten()], 'p3_freq.txt')
except Exception as e:
print(e)
self.draw_gv()
self.draw_branch_scatter()
self.draw_tau()
cd('..')
def third(self):
mkdir('thirdorder')
cd('thirdorder')
cp('../POSCAR', '.')
self.generate_supercells3()
def pSheng(self):
mkdir('SHENG')
cd('SHENG')
cp('../secondorder/FORCE_CONSTANTS', 'FORCE_CONSTANTS_2ND')
cp('../thirdorder/FORCE_CONSTANTS_3RD', '.')
self.getControl()
fp = open('qloops.txt')
dirs = []
for line in fp:
obj = json.loads(line)
#if not obj['id']%3==0:continue
dirs.append(dict(id=obj['id'], latysmall=obj['latysmall']))
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
from aces import tools
ys = []
dp = pd.DataFrame()
for dir in dirs:
tools.cd(str(dir['id']))
df = pd.read_csv("VDOS.txt", sep=r"[ \t]", engine="python")
x, y = getDos(df['Freq_THz'], df['vdos_av'])
dp['freq'] = x
dp["latysmall=%s" % dir['latysmall']] = y
tools.cd('..')
dp.to_csv('total_dos.txt', sep='\t', index=False, float_format="%f")
for dir in dirs:
label = "latysmall=%s" % dir['latysmall']
plt.plot(dp['freq'], dp[label], linewidth=1, label=label)
plt.grid(True)
plt.xlim(min(x), max(x))
plt.xlabel('Frequency(THz)')
plt.ylabel('Density of states')
plt.legend(loc='best').get_frame().set_alpha(0.0)
plt.savefig('smoothVDOS.png', bbox_inches='tight', transparent=True)
