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 ewald(wd, number): outcar = os.path.join(wd, 'OUTCAR') click.echo(': '.join(get_ele_sta(outcar, number)))
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)