def test_encut(self,kw={}):
start,end,step = kw.get('start'),kw.get('end'),kw.get('step')
is_login_node,kw = run_vasp.clean_parse(kw,'is_login_node',False)
kw.pop('start');kw.pop('end');kw.pop('step')
_kw = kw.copy()
prep_vasp.write_potcar(poscar=self.poscar,kw=_kw)
with open('POTCAR') as f:
lines = f.readlines()
en_line = [i for i in lines if 'ENMAX' in i]
enmax = max([float(i.split()[2].replace(';','')) for i in en_line])
remove('POTCAR')
idx = 0
for en in np.arange(start*enmax,end*enmax,step):
_kw = kw.copy()
_kw.update({'ENCUT':int(en),'job_name':'test_encut'+str(idx),'NSW':0})
prep_vasp.prep_single_vasp(poscar=self.poscar,kw=_kw)
idx += 1
for i in range(idx):
run_vasp.run_single_vasp(job_name='test_encut'+str(i),is_login_node=is_login_node)
encut_list = []
encut = np.arange(start*enmax,end*enmax,step)
for ii in range(len(encut)):
EV = ExtractValue(data_folder='test_encut'+str(ii))
encut_list.append([encut[ii],EV.get_energy(),EV.get_cpu_time()])
with open('test_encut.txt','w') as f:
f.writelines('ENMAX\tEnergy\tcpu_time\n')
for line in encut_list:
f.writelines(str(line[0])+'\t'+str(line[1])+'\t'+str(line[2])+'\n')
def test_kpts(self,kw={}):
start,end,step = kw.get('start'),kw.get('end'),kw.get('step')
is_login_node,kw = run_vasp.clean_parse(kw,'is_login_node',False)
kw.pop('start');kw.pop('end');kw.pop('step')
kpts = Kpoints()
kpts_list = set()
kppa_list = []
for kppa in range(start,end,step):
kpts.automatic_density(structure=read_vasp(self.poscar),kppa=kppa)
if tuple(kpts.kpts[0]) not in kpts_list:
kpts_list.add(tuple(kpts.kpts[0]))
kppa_list.append(kppa)
idx = 0
for kppa in kppa_list:
_kw = kw.copy()
if 'style' not in _kw:
_kw.update({'kppa':kppa,'style':'auto','job_name':'test_kpts'+str(idx),'NSW':0})
prep_vasp.prep_single_vasp(poscar=self.poscar,kw=_kw)
idx += 1
for i in range(idx):
run_vasp.run_single_vasp(job_name='test_kpts'+str(i),is_login_node=is_login_node)
kpts_res = []
for ii in range(len(kppa_list)):
EV = ExtractValue(data_folder='test_kpts'+str(ii))
kpts_res.append([kppa_list[ii],EV.get_energy(),EV.get_cpu_time()])
with open('test_kpts.txt','w') as f:
f.writelines('KPTS\tEnergy\tcpu_time\n')
for line in kpts_res:
f.writelines(str(line[0])+'\t'+str(line[1])+'\t'+str(line[2])+'\n')
def main(wd, attribute, number):
"""
Example:
pyvasp main -a gap # this can read the gap and vbm, cbm
pyvasp main -a fermi -w work_dir # this can read the fermi energy, -w is your work directory
pyvasp main -a energy # this can read the total energy
pyvasp main -a ele # this can read the electrons in your OUTCAR
pyvasp main -a ele-free # this can get electrons number of the defect-free system
pyvasp main -a Ewald # this can get the Ewald energy of your system
pyvasp main -a cpu # this can get CPU time
"""
EV = ExtractValue(wd)
if 'gap' in attribute:
get_gap(EV)
elif 'fermi' in attribute:
click.echo(EV.get_fermi())
elif 'total' in attribute.lower() or 'energy' in attribute.lower():
click.echo(EV.get_energy())
elif 'ele' in attribute.lower() and 'free' in attribute.lower():
click.echo(EV.get_Ne_defect_free())
elif 'ele' in attribute.lower() and 'free' not in attribute.lower(
) and 'static' not in attribute.lower():
click.echo(EV.get_Ne_defect())
elif 'ima' in attribute or 'ewald' in attribute.lower():
clikc.echo(EV.get_image())
elif 'elect' in attribute and 'static' in attribute:
outcar = os.path.join(wd, 'OUTCAR')
click.echo(str(number) + ' ' + str(get_ele_sta(outcar, number)))
elif 'cpu' in attribute.lower():
click.echo(EV.get_cpu_time())
def energy(wd):
EV = ExtractValue(wd)
click.echo(EV.get_energy())
def fermi(wd):
EV = ExtractValue(wd)
click.echo(EV.get_fermi())
def gap(wd, vo, co):
EV = ExtractValue(wd)
get_gap(EV, float(vo), float(co))
def ewald(wd):
EV = ExtractValue(wd)
click.echo(EV.get_image())
def electron_number(wd):
EV = ExtractValue(wd)
click.echo(EV.get_Ne_defect())
def electron_defect_free(wd):
EV = ExtractValue(wd)
click.echo(EV.get_Ne_defect_free())
def get_defect_formation_energy(data_dir, defect_dirs):
print('The main direcroty is: ', data_dir)
f = open(os.path.join(data_dir, 'defect-log.txt'), 'w')
fig, ax = plt.subplots()
for defect_dir in defect_dirs:
print('Reading ', defect_dir)
f.write(defect_dir + '\n')
SC_energy = ExtractValue(os.path.join(data_dir,
'supercell/scf/')).get_energy()
print('Energy of supcell is: ' + str(SC_energy) + ' eV')
f.write('Energy of supcell is: ' + str(SC_energy) + ' eV\n')
res = ExtractValue(os.path.join(data_dir, 'supercell/scf/')).get_gap()
if len(res) == 3:
Evbm, Ecbm, gap = res
elif len(res) == 2:
Evbm, Ecbm, gap = res[0]
print('Evbm, Ecbm, gap of supcell is: ', Evbm, Ecbm, gap)
f.write('Evbm: ' + str(Evbm) + ' eV\n' + 'Ecbm: ' + str(Ecbm) +
' eV\n' + 'gap: ' + str(gap) + ' eV\n')
chg_state = []
f.write(
'charge\t\tenergy\t\tE_PA\t\tE_IC\tfar_atom_def_sys\tfar_atom_def_fr_system\n'
)
for chg_fd in os.listdir(os.path.join(defect_dir)):
if 'charge_state_' in chg_fd:
q = chg_fd.split('_')[-1]
e = ExtractValue(os.path.join(defect_dir, chg_fd,
'scf')).get_energy()
no_def_poscar = os.path.join(data_dir, 'supercell',
'scf/CONTCAR')
def_poscar = os.path.join(defect_dir, chg_fd, 'POSCAR')
num_def, num_no_def = get_farther_atom_num(
no_def_poscar, def_poscar)
pa_def = get_ele_sta(
os.path.join(defect_dir, chg_fd, 'scf', 'OUTCAR'), num_def)
pa_no_def = get_ele_sta(
os.path.join(data_dir, 'supercell', 'scf', 'OUTCAR'),
num_no_def)
E_imagecor = ExtractValue(os.path.join(
data_dir, 'image_corr')).get_image()
chg_state.append([
int(float(q)), e, pa_def - pa_no_def, E_imagecor, num_def,
num_no_def
])
ele_in_out = read_incar('element-in-out')
incar_para = read_incar(os.path.join(data_dir, 'defect-incar'))
incar_para['mu_Vacc'] = 0
if 'epsilon' in incar_para:
epsilon = float(incar_para['epsilon'])
else:
epsilon = 1e10
warnings.warn(
"You should specify epsilon in your defect-incar, here we just ignore this correlation"
)
chg_state = np.asarray(chg_state)
chg_state[:, 2] = chg_state[:, 2] * chg_state[:, 0]
chg_state[:,
3] = -2 / 3 * chg_state[:, 0]**2 * chg_state[:, 3] / epsilon
for c in chg_state:
f.write(
'{:2d}\t\t{:.5f}\t{:+.5f}\t{:+.5f}\t{:d}\t\t\t{:d}\n'.format(
int(c[0]), c[1], c[2], c[3], int(c[4]), int(c[5])))
mu = 0
for key, val in ele_in_out.items():
if 'mu_' + key in incar_para:
mu += float(incar_para['mu_' + key]) * int(val)
f.write('chemical potential of ' + key.title() + ': ' +
str(incar_para['mu_' + key]) + ' eV\n')
else:
raise ValueError('chemical potential mu_' + key.title() +
' cannot found')
os.system('rm element-in-out')
for key, val in ele_in_out.items():
if int(val) == -1:
f.writelines(key.title() + ' has been doped\n')
else:
f.writelines(key.title() + ' has been removed\n')
f.writelines('\n')
Ef = np.linspace(Evbm, Ecbm, 1000)
chg_state = np.asarray(chg_state)
E = []
for idx in range(np.shape(chg_state)[0]):
E.append(chg_state[idx, 1] - SC_energy + mu +
chg_state[idx, 0] * Ef + chg_state[idx, 2] +
chg_state[idx, 3])
E = np.asarray(E)
ax.set_aspect('equal')
ax.plot(Ef - Evbm, np.min(E, axis=0), label=defect_dir)
f.close()
plt.xlabel(r'$E_F$ (eV)')
plt.ylabel(r'$\Delta E (eV)$')
plt.legend()
plt.savefig(os.path.join(data_dir, 'defect_formation_energy.png'), dpi=450)
def get_grd_state(job_name,start_job_num,end_job_num):
energy = []
for ii in range(start_job_num,end_job_num+1):
EV = ExtractValue(data_folder=job_name+str(ii))
energy.append(EV.get_energy())
return np.argmin(energy)
def gap(wd):
EV = ExtractValue(wd)
get_gap(EV)
def cpu(wd):
EV = ExtractValue(wd)
click.echo(EV.get_cpu_time())