import glob
import json
import os
import re
import numpy as np
from monty.serialization import loadfn, dumpfn
import dpgen.auto_test.lib.vasp as vasp
from dpgen import dlog
from dpgen.auto_test.Property import Property
from dpgen.auto_test.refine import make_refine
from dpgen.auto_test.reproduce import make_repro
from dpgen.auto_test.reproduce import post_repro
import dpgen.generator.lib.abacus_scf as abacus_scf
import dpgen.auto_test.lib.abacus as abacus
[docs]class EOS(Property):
def __init__(self,
parameter,inter_param=None):
parameter['reproduce'] = parameter.get('reproduce', False)
self.reprod = parameter['reproduce']
if not self.reprod:
if not ('init_from_suffix' in parameter and 'output_suffix' in parameter):
self.vol_start = parameter['vol_start']
self.vol_end = parameter['vol_end']
self.vol_step = parameter['vol_step']
parameter['vol_abs'] = parameter.get('vol_abs', False)
self.vol_abs = parameter['vol_abs']
parameter['cal_type'] = parameter.get('cal_type', 'relaxation')
self.cal_type = parameter['cal_type']
default_cal_setting = {"relax_pos": True,
"relax_shape": True,
"relax_vol": False}
if 'cal_setting' not in parameter:
parameter['cal_setting'] = default_cal_setting
else:
if "relax_pos" not in parameter['cal_setting']:
parameter['cal_setting']['relax_pos'] = default_cal_setting['relax_pos']
if "relax_shape" not in parameter['cal_setting']:
parameter['cal_setting']['relax_shape'] = default_cal_setting['relax_shape']
if "relax_vol" not in parameter['cal_setting']:
parameter['cal_setting']['relax_vol'] = default_cal_setting['relax_vol']
self.cal_setting = parameter['cal_setting']
else:
parameter['cal_type'] = 'static'
self.cal_type = parameter['cal_type']
default_cal_setting = {"relax_pos": False,
"relax_shape": False,
"relax_vol": False}
if 'cal_setting' not in parameter:
parameter['cal_setting'] = default_cal_setting
else:
if "relax_pos" not in parameter['cal_setting']:
parameter['cal_setting']['relax_pos'] = default_cal_setting['relax_pos']
if "relax_shape" not in parameter['cal_setting']:
parameter['cal_setting']['relax_shape'] = default_cal_setting['relax_shape']
if "relax_vol" not in parameter['cal_setting']:
parameter['cal_setting']['relax_vol'] = default_cal_setting['relax_vol']
self.cal_setting = parameter['cal_setting']
parameter['init_from_suffix'] = parameter.get('init_from_suffix', '00')
self.init_from_suffix = parameter['init_from_suffix']
self.parameter = parameter
self.inter_param = inter_param if inter_param != None else {'type': 'vasp'}
[docs] 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(self.inter_param,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))
if self.vol_abs :
dlog.info('treat vol_start and vol_end as absolute volume')
else :
dlog.info('treat vol_start and vol_end as relative volume')
if self.inter_param['type'] == 'abacus':
equi_contcar = os.path.join(path_to_equi,abacus.final_stru(path_to_equi))
else:
equi_contcar = os.path.join(path_to_equi, 'CONTCAR')
if not os.path.isfile(equi_contcar):
raise RuntimeError("Can not find %s, please do relaxation first" % equi_contcar)
if self.inter_param['type'] == 'abacus':
stru_data = abacus_scf.get_abacus_STRU(equi_contcar)
vol_to_poscar = abs(np.linalg.det(stru_data['cells'])) / np.array(stru_data['atom_numbs']).sum()
else:
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)
if self.inter_param['type'] == 'abacus':
POSCAR = 'STRU'
POSCAR_orig = 'STRU.orig'
scale_func = abacus.stru_scale
else:
POSCAR = 'POSCAR'
POSCAR_orig = 'POSCAR.orig'
scale_func = vasp.poscar_scale
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.)
if self.vol_abs :
scale = (vol / vol_to_poscar) ** (1. / 3.)
eos_params = {'volume': vol, 'scale': scale}
else :
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
scale_func(POSCAR_orig,POSCAR,scale)
task_num += 1
os.chdir(cwd)
return task_list
[docs] def post_process(self, task_list):
pass
[docs] def task_type(self):
return self.parameter['type']
[docs] def task_param(self):
return self.parameter
def _compute_lower(self,
output_file,
all_tasks,
all_res):
output_file = os.path.abspath(output_file)
res_data = {}
ptr_data = "conf_dir: " + os.path.dirname(output_file) + "\n"
if not self.reprod:
ptr_data += ' VpA(A^3) EpA(eV)\n'
for ii in range(len(all_tasks)):
# vol = self.vol_start + ii * self.vol_step
vol = loadfn(os.path.join(all_tasks[ii], 'eos.json'))['volume']
task_result = loadfn(all_res[ii])
res_data[vol] = task_result['energies'][-1] / sum(task_result['atom_numbs'])
ptr_data += '%7.3f %8.4f \n' % (vol, task_result['energies'][-1] / sum(task_result['atom_numbs']))
# res_data[vol] = all_res[ii]['energy'] / len(all_res[ii]['force'])
# ptr_data += '%7.3f %8.4f \n' % (vol, all_res[ii]['energy'] / len(all_res[ii]['force']))
else:
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'])
res_data, ptr_data = post_repro(init_data_path, self.parameter['init_from_suffix'],
all_tasks, ptr_data, self.parameter.get('reprod_last_frame', True))
with open(output_file, 'w') as fp:
json.dump(res_data, fp, indent=4)
return res_data, ptr_data