def make_confs(self, path_to_work, path_to_equi, refine=False): path_to_work = os.path.abspath(path_to_work) if os.path.exists(path_to_work): dlog.warning('%s already exists' % path_to_work) else: os.makedirs(path_to_work) path_to_equi = os.path.abspath(path_to_equi) if 'start_confs_path' in self.parameter and os.path.exists( self.parameter['start_confs_path']): init_path_list = glob.glob( os.path.join(self.parameter['start_confs_path'], '*')) struct_init_name_list = [] for ii in init_path_list: struct_init_name_list.append(ii.split('/')[-1]) struct_output_name = path_to_work.split('/')[-2] assert struct_output_name in struct_init_name_list path_to_equi = os.path.abspath( os.path.join(self.parameter['start_confs_path'], struct_output_name, 'relaxation', 'relax_task')) cwd = os.getcwd() task_list = [] if self.reprod: print('eos reproduce starts') if 'init_data_path' not in self.parameter: raise RuntimeError( "please provide the initial data path to reproduce") init_data_path = os.path.abspath(self.parameter['init_data_path']) task_list = make_repro( init_data_path, self.init_from_suffix, path_to_work, self.parameter.get('reprod_last_frame', True)) os.chdir(cwd) else: if refine: print('eos refine starts') task_list = make_refine(self.parameter['init_from_suffix'], self.parameter['output_suffix'], path_to_work) os.chdir(cwd) init_from_path = re.sub( self.parameter['output_suffix'][::-1], self.parameter['init_from_suffix'][::-1], path_to_work[::-1], count=1)[::-1] task_list_basename = list(map(os.path.basename, task_list)) for ii in task_list_basename: init_from_task = os.path.join(init_from_path, ii) output_task = os.path.join(path_to_work, ii) os.chdir(output_task) if os.path.isfile('eos.json'): os.remove('eos.json') if os.path.islink('eos.json'): os.remove('eos.json') os.symlink( os.path.relpath( os.path.join(init_from_task, 'eos.json')), 'eos.json') os.chdir(cwd) else: print('gen eos from ' + str(self.vol_start) + ' to ' + str(self.vol_end) + ' by every ' + str(self.vol_step)) equi_contcar = os.path.join(path_to_equi, 'CONTCAR') if not os.path.exists(equi_contcar): raise RuntimeError("please do relaxation first") vol_to_poscar = vasp.poscar_vol( equi_contcar) / vasp.poscar_natoms(equi_contcar) self.parameter['scale2equi'] = [] task_num = 0 while self.vol_start + self.vol_step * task_num < self.vol_end: # for vol in np.arange(int(self.vol_start * 100), int(self.vol_end * 100), int(self.vol_step * 100)): # vol = vol / 100.0 vol = self.vol_start + task_num * self.vol_step #task_num = int((vol - self.vol_start) / self.vol_step) output_task = os.path.join(path_to_work, 'task.%06d' % task_num) os.makedirs(output_task, exist_ok=True) os.chdir(output_task) for ii in [ 'INCAR', 'POTCAR', 'POSCAR.orig', 'POSCAR', 'conf.lmp', 'in.lammps' ]: if os.path.exists(ii): os.remove(ii) task_list.append(output_task) os.symlink(os.path.relpath(equi_contcar), 'POSCAR.orig') # scale = (vol / vol_to_poscar) ** (1. / 3.) scale = vol**(1. / 3.) eos_params = { 'volume': vol * vol_to_poscar, 'scale': scale } dumpfn(eos_params, 'eos.json', indent=4) self.parameter['scale2equi'].append(scale) # 06/22 vasp.poscar_scale('POSCAR.orig', 'POSCAR', scale) task_num += 1 os.chdir(cwd) return task_list
def make_confs(self, path_to_work, path_to_equi, refine=False): path_to_work = os.path.abspath(path_to_work) if os.path.exists(path_to_work): dlog.warning('%s already exists' % path_to_work) else: os.makedirs(path_to_work) path_to_equi = os.path.abspath(path_to_equi) if 'start_confs_path' in self.parameter and os.path.exists( self.parameter['start_confs_path']): init_path_list = glob.glob( os.path.join(self.parameter['start_confs_path'], '*')) struct_init_name_list = [] for ii in init_path_list: struct_init_name_list.append(ii.split('/')[-1]) struct_output_name = path_to_work.split('/')[-2] assert struct_output_name in struct_init_name_list path_to_equi = os.path.abspath( os.path.join(self.parameter['start_confs_path'], struct_output_name, 'relaxation', 'relax_task')) task_list = [] cwd = os.getcwd() if self.reprod: print('vacancy reproduce starts') if 'init_data_path' not in self.parameter: raise RuntimeError( "please provide the initial data path to reproduce") init_data_path = os.path.abspath(self.parameter['init_data_path']) task_list = make_repro( init_data_path, self.init_from_suffix, path_to_work, self.parameter.get('reprod_last_frame', False)) os.chdir(cwd) else: if refine: print('vacancy refine starts') task_list = make_refine(self.parameter['init_from_suffix'], self.parameter['output_suffix'], path_to_work) init_from_path = re.sub( self.parameter['output_suffix'][::-1], self.parameter['init_from_suffix'][::-1], path_to_work[::-1], count=1)[::-1] task_list_basename = list(map(os.path.basename, task_list)) for ii in task_list_basename: init_from_task = os.path.join(init_from_path, ii) output_task = os.path.join(path_to_work, ii) os.chdir(output_task) if os.path.isfile('supercell.json'): os.remove('supercell.json') if os.path.islink('supercell.json'): os.remove('supercell.json') os.symlink( os.path.relpath( os.path.join(init_from_task, 'supercell.json')), 'supercell.json') os.chdir(cwd) else: equi_contcar = os.path.join(path_to_equi, 'CONTCAR') if not os.path.exists(equi_contcar): raise RuntimeError("please do relaxation first") ss = Structure.from_file(equi_contcar) vds = VacancyGenerator(ss) dss = [] for jj in vds: dss.append(jj.generate_defect_structure(self.supercell)) print('gen vacancy with supercell ' + str(self.supercell)) os.chdir(path_to_work) if os.path.isfile('POSCAR'): os.remove('POSCAR') if os.path.islink('POSCAR'): os.remove('POSCAR') os.symlink(os.path.relpath(equi_contcar), 'POSCAR') # task_poscar = os.path.join(output, 'POSCAR') for ii in range(len(dss)): output_task = os.path.join(path_to_work, 'task.%06d' % ii) os.makedirs(output_task, exist_ok=True) os.chdir(output_task) for jj in [ 'INCAR', 'POTCAR', 'POSCAR', 'conf.lmp', 'in.lammps' ]: if os.path.exists(jj): os.remove(jj) task_list.append(output_task) dss[ii].to('POSCAR', 'POSCAR') # np.savetxt('supercell.out', self.supercell, fmt='%d') dumpfn(self.supercell, 'supercell.json') os.chdir(cwd) return task_list
def make_confs(self, path_to_work, path_to_equi, refine=False): path_to_work = os.path.abspath(path_to_work) if os.path.exists(path_to_work): dlog.warning('%s already exists' % path_to_work) else: os.makedirs(path_to_work) path_to_equi = os.path.abspath(path_to_equi) if 'start_confs_path' in self.parameter and os.path.exists(self.parameter['start_confs_path']): init_path_list = glob.glob(os.path.join(self.parameter['start_confs_path'], '*')) struct_init_name_list = [] for ii in init_path_list: struct_init_name_list.append(ii.split('/')[-1]) struct_output_name = path_to_work.split('/')[-2] assert struct_output_name in struct_init_name_list path_to_equi = os.path.abspath(os.path.join(self.parameter['start_confs_path'], struct_output_name, 'relaxation', 'relax_task')) task_list = [] cwd = os.getcwd() if self.reprod: print('surface reproduce starts') if 'init_data_path' not in self.parameter: raise RuntimeError("please provide the initial data path to reproduce") init_data_path = os.path.abspath(self.parameter['init_data_path']) task_list = make_repro(init_data_path, self.init_from_suffix, path_to_work, self.parameter.get('reprod_last_frame', True)) os.chdir(cwd) else: if refine: print('surface refine starts') task_list = make_refine(self.parameter['init_from_suffix'], self.parameter['output_suffix'], path_to_work) os.chdir(cwd) # record miller init_from_path = re.sub(self.parameter['output_suffix'][::-1], self.parameter['init_from_suffix'][::-1], path_to_work[::-1], count=1)[::-1] task_list_basename = list(map(os.path.basename, task_list)) for ii in task_list_basename: init_from_task = os.path.join(init_from_path, ii) output_task = os.path.join(path_to_work, ii) os.chdir(output_task) if os.path.isfile('miller.json'): os.remove('miller.json') if os.path.islink('miller.json'): os.remove('miller.json') os.symlink(os.path.relpath(os.path.join(init_from_task, 'miller.json')), 'miller.json') os.chdir(cwd) else: equi_contcar = os.path.join(path_to_equi, 'CONTCAR') if not os.path.exists(equi_contcar): raise RuntimeError("please do relaxation first") ptypes = vasp.get_poscar_types(equi_contcar) # gen structure ss = Structure.from_file(equi_contcar) # gen slabs all_slabs = generate_all_slabs(ss, self.miller, self.min_slab_size, self.min_vacuum_size) os.chdir(path_to_work) if os.path.isfile('POSCAR'): os.remove('POSCAR') if os.path.islink('POSCAR'): os.remove('POSCAR') os.symlink(os.path.relpath(equi_contcar), 'POSCAR') # task_poscar = os.path.join(output, 'POSCAR') for ii in range(len(all_slabs)): output_task = os.path.join(path_to_work, 'task.%06d' % ii) os.makedirs(output_task, exist_ok=True) os.chdir(output_task) for jj in ['INCAR', 'POTCAR', 'POSCAR', 'conf.lmp', 'in.lammps']: if os.path.exists(jj): os.remove(jj) task_list.append(output_task) print("# %03d generate " % ii, output_task, " \t %d atoms" % len(all_slabs[ii].sites)) # make confs all_slabs[ii].to('POSCAR', 'POSCAR.tmp') vasp.regulate_poscar('POSCAR.tmp', 'POSCAR') vasp.sort_poscar('POSCAR', 'POSCAR', ptypes) vasp.perturb_xz('POSCAR', 'POSCAR', self.pert_xz) # record miller dumpfn(all_slabs[ii].miller_index, 'miller.json') os.chdir(cwd) return task_list
def make_confs(self, path_to_work, path_to_equi, refine=False): path_to_work = os.path.abspath(path_to_work) path_to_equi = os.path.abspath(path_to_equi) if 'start_confs_path' in self.parameter and os.path.exists( self.parameter['start_confs_path']): init_path_list = glob.glob( os.path.join(self.parameter['start_confs_path'], '*')) struct_init_name_list = [] for ii in init_path_list: struct_init_name_list.append(ii.split('/')[-1]) struct_output_name = path_to_work.split('/')[-2] assert struct_output_name in struct_init_name_list path_to_equi = os.path.abspath( os.path.join(self.parameter['start_confs_path'], struct_output_name, 'relaxation', 'relax_task')) task_list = [] cwd = os.getcwd() if self.reprod: print('interstitial reproduce starts') if 'init_data_path' not in self.parameter: raise RuntimeError( "please provide the initial data path to reproduce") init_data_path = os.path.abspath(self.parameter['init_data_path']) task_list = make_repro( init_data_path, self.init_from_suffix, path_to_work, self.parameter.get('reprod_last_frame', False)) os.chdir(cwd) else: if refine: print('interstitial refine starts') task_list = make_refine(self.parameter['init_from_suffix'], self.parameter['output_suffix'], path_to_work) init_from_path = re.sub( self.parameter['output_suffix'][::-1], self.parameter['init_from_suffix'][::-1], path_to_work[::-1], count=1)[::-1] task_list_basename = list(map(os.path.basename, task_list)) os.chdir(path_to_work) if os.path.isfile('element.out'): os.remove('element.out') if os.path.islink('element.out'): os.remove('element.out') os.symlink( os.path.relpath(os.path.join(init_from_path, 'element.out')), 'element.out') os.chdir(cwd) for ii in task_list_basename: init_from_task = os.path.join(init_from_path, ii) output_task = os.path.join(path_to_work, ii) os.chdir(output_task) if os.path.isfile('supercell.json'): os.remove('supercell.json') if os.path.islink('supercell.json'): os.remove('supercell.json') os.symlink( os.path.relpath( os.path.join(init_from_task, 'supercell.json')), 'supercell.json') os.chdir(cwd) else: equi_contcar = os.path.join(path_to_equi, 'CONTCAR') if not os.path.exists(equi_contcar): raise RuntimeError("please do relaxation first") ss = Structure.from_file(equi_contcar) # gen defects dss = [] insert_element_task = os.path.join(path_to_work, 'element.out') if os.path.isfile(insert_element_task): os.remove(insert_element_task) for ii in self.insert_ele: vds = InterstitialGenerator(ss, ii) for jj in vds: temp = jj.generate_defect_structure(self.supercell) smallest_distance = list( set(temp.distance_matrix.ravel()))[1] if 'conf_filters' in self.parameter and 'min_dist' in self.parameter[ 'conf_filters']: min_dist = self.parameter['conf_filters'][ 'min_dist'] if smallest_distance >= min_dist: dss.append(temp) with open(insert_element_task, 'a+') as fout: print(ii, file=fout) else: dss.append(temp) with open(insert_element_task, 'a+') as fout: print(ii, file=fout) # dss.append(jj.generate_defect_structure(self.supercell)) print('gen interstitial with supercell ' + str(self.supercell) + ' with element ' + str(self.insert_ele)) os.chdir(path_to_work) if os.path.isfile('POSCAR'): os.remove('POSCAR') if os.path.islink('POSCAR'): os.remove('POSCAR') os.symlink(os.path.relpath(equi_contcar), 'POSCAR') # task_poscar = os.path.join(output, 'POSCAR') for ii in range(len(dss)): output_task = os.path.join(path_to_work, 'task.%06d' % ii) os.makedirs(output_task, exist_ok=True) os.chdir(output_task) for jj in [ 'INCAR', 'POTCAR', 'POSCAR', 'conf.lmp', 'in.lammps' ]: if os.path.exists(jj): os.remove(jj) task_list.append(output_task) dss[ii].to('POSCAR', 'POSCAR') # np.savetxt('supercell.out', self.supercell, fmt='%d') dumpfn(self.supercell, 'supercell.json') os.chdir(cwd) return task_list