def cmpt_vasp(jdata, conf_dir, static=False):
if 'relax_incar' in jdata.keys():
vasp_str = 'vasp-relax_incar'
else:
kspacing = jdata['vasp_params']['kspacing']
vasp_str = 'vasp-k%.2f' % (kspacing)
equi_path = re.sub('confs', global_equi_name, conf_dir)
equi_path = os.path.join(equi_path, vasp_str)
equi_path = os.path.abspath(equi_path)
equi_outcar = os.path.join(equi_path, 'OUTCAR')
task_path = re.sub('confs', global_task_name, conf_dir)
if static:
if 'scf_incar' in jdata.keys():
vasp_static_str = 'vasp-static-scf_incar'
else:
kspacing = jdata['vasp_params']['kspacing']
vasp_static_str = 'vasp-static-k%.2f' % (kspacing)
task_path = os.path.join(task_path, vasp_static_str)
else:
task_path = os.path.join(task_path, vasp_str)
task_path = os.path.abspath(task_path)
equi_natoms, equi_epa, equi_vpa = vasp.get_nev(equi_outcar)
struct_path_widecard = os.path.join(task_path, 'struct-*-m*m')
struct_path_list = glob.glob(struct_path_widecard)
struct_path_list.sort()
if len(struct_path_list) == 0:
print("# cannot find results for conf %s" % (conf_dir))
sys.stdout.write("Miller_Indices: \tSurf_E(J/m^2) EpA(eV) equi_EpA(eV)\n")
result = os.path.join(task_path, 'result')
with open(result, 'w') as fp:
fp.write('conf_dir:%s\n' % (conf_dir))
fp.write("Miller_Indices: \tSurf_E(J/m^2) EpA(eV) equi_EpA(eV)\n")
for ii in struct_path_list:
structure_dir = os.path.basename(ii)
outcar = os.path.join(ii, 'OUTCAR')
natoms, epa, vpa = vasp.get_nev(outcar)
if static:
e0 = np.array(vasp.get_energies(outcar)) / natoms
epa = e0[0]
boxes = vasp.get_boxes(outcar)
AA = np.linalg.norm(np.cross(boxes[0][0], boxes[0][1]))
Cf = 1.60217657e-16 / (1e-20 * 2) * 0.001
evac = (epa * natoms - equi_epa * natoms) / AA * Cf
sys.stdout.write("%s:\t %7.3f %8.3f %8.3f\n" %
(structure_dir, evac, epa, equi_epa))
fp.write("%s:\t %7.3f %8.3f %8.3f\n" %
(structure_dir, evac, epa, equi_epa))
fp.close()
if 'upload_username' in jdata.keys():
upload_username = jdata['upload_username']
util.insert_data('surf', 'vasp', upload_username, result)
def _compute_lower(self, output_file, all_tasks, all_res):
output_file = os.path.abspath(output_file)
res_data = {}
ptr_data = os.path.dirname(output_file) + '\n'
if not self.reprod:
ptr_data += "Miller_Indices: \tSurf_E(J/m^2) EpA(eV) equi_EpA(eV)\n"
for ii in all_tasks:
with open(os.path.join(ii, 'inter.json')) as fp:
idata = json.load(fp)
inter_type = idata['type']
equi_path = os.path.abspath(
os.path.join(os.path.dirname(output_file),
'../relaxation'))
structure_dir = os.path.basename(ii)
if inter_type == 'vasp':
equi_outcar = os.path.join(equi_path, 'OUTCAR')
equi_natoms, equi_epa, equi_vpa = vasp.get_nev(equi_outcar)
outcar = os.path.join(ii, 'OUTCAR')
natoms, epa, vpa = vasp.get_nev(outcar)
if self.static:
e0 = np.array(vasp.get_energies(outcar)) / natoms
epa = e0[0]
boxes = vasp.get_boxes(outcar)
AA = np.linalg.norm(np.cross(boxes[0][0], boxes[0][1]))
elif inter_type in ['deepmd', 'meam', 'eam_fs', 'eam_alloy']:
equi_log = os.path.join(equi_path, 'log.lammps')
equi_natoms, equi_epa, equi_vpa = lammps.get_nev(equi_log)
lmp_log = os.path.join(ii, 'log.lammps')
natoms, epa, vpa = lammps.get_nev(lmp_log)
AA = lammps.get_base_area(lmp_log)
else:
raise RuntimeError('interaction type not supported')
Cf = 1.60217657e-16 / (1e-20 * 2) * 0.001
evac = (epa * natoms - equi_epa * natoms) / AA * Cf
ptr_data += "%s: \t%7.3f %8.3f %8.3f\n" % (
structure_dir, evac, epa, equi_epa)
res_data[structure_dir] = [evac, epa, equi_epa]
else:
if 'vasp_path' not in self.parameter:
raise RuntimeError(
"please provide the vasp_path for reproduction")
vasp_path = os.path.abspath(self.parameter['vasp_path'])
res_data, ptr_data = reproduce.post_repro(vasp_path, all_tasks,
ptr_data)
with open(output_file, 'w') as fp:
json.dump(res_data, fp, indent=4)
return res_data, ptr_data
def make_repro(vasp_path, path_to_work):
if not os.path.exists(vasp_path):
raise RuntimeError("please do VASP calcualtions first")
vasp_task = glob.glob(os.path.join(vasp_path, 'task.[0-9]*[0-9]'))
assert len(vasp_task) > 0, "Please do VASP calcualtions first"
vasp_task.sort()
task_num = 0
task_list = []
for ii in vasp_task:
# get vasp energy
outcar = os.path.join(ii, 'OUTCAR')
energies = vasp.get_energies(outcar)
# get xdat
xdatcar = os.path.join(ii, 'XDATCAR')
os.chdir(path_to_work)
if os.path.exists('XDATCAR'):
os.remove('XDATCAR')
os.symlink(os.path.relpath(xdatcar), 'XDATCAR')
xdat_lines = open('XDATCAR', 'r').read().split('\n')
natoms = vasp.poscar_natoms('XDATCAR')
xdat_secsize = natoms + 8
xdat_nframes = len(xdat_lines) // xdat_secsize
if xdat_nframes > len(energies):
warnings.warn(
'nframes %d in xdatcar is larger than energy %d, use the last %d frames'
% (xdat_nframes, len(energies), len(energies)))
xdat_nlines = -1 * len(energies) * xdat_secsize # 06/12 revised
xdat_lines = xdat_lines[xdat_nlines:]
xdat_nframes = len(xdat_lines) // xdat_secsize
print(xdat_nframes, len(energies))
# loop over frames
for jj in range(xdat_nframes):
output_task = os.path.join(path_to_work, 'task.%06d' % task_num)
task_num += 1
task_list.append(output_task)
os.makedirs(output_task, exist_ok=True)
os.chdir(output_task)
# clear dir
for kk in [
'INCAR', 'POTCAR', 'POSCAR.orig', 'POSCAR', 'conf.lmp',
'in.lammps'
]:
if os.path.exists(kk):
os.remove(kk)
# make conf
with open('POSCAR', 'w') as fp:
fp.write('\n'.join(xdat_lines[jj * xdat_secsize:(jj + 1) *
xdat_secsize]))
return task_list
def _cmpt_deepmd_reprod_traj(jdata, conf_dir, supercell, insert_ele,
task_name):
fp_params = jdata['vasp_params']
kspacing = fp_params['kspacing']
if 'relax_incar' in jdata.keys():
vasp_str = 'vasp-relax_incar'
else:
vasp_str = 'vasp-k%.2f' % kspacing
conf_path = os.path.abspath(conf_dir)
task_path = re.sub('confs', global_task_name, conf_path)
vasp_path = os.path.join(task_path, vasp_str)
lmps_path = os.path.join(task_path,
task_name + vasp_str.replace('vasp', ''))
copy_str = "%sx%sx%s" % (supercell[0], supercell[1], supercell[2])
struct_widecard = os.path.join(vasp_path,
'struct-%s-%s-*' % (insert_ele, copy_str))
vasp_struct = glob.glob(struct_widecard)
vasp_struct.sort()
cwd = os.getcwd()
for vs in vasp_struct:
# compute vasp
outcar = os.path.join(vs, 'OUTCAR')
vasp_ener = np.array(vasp.get_energies(outcar))
vasp_ener_file = os.path.join(vs, 'ener.vasp.out')
# compute reprod
struct_basename = os.path.basename(vs)
ls = os.path.join(lmps_path, struct_basename)
frame_widecard = os.path.join(ls, 'frame.*')
frames = glob.glob(frame_widecard)
frames.sort()
lmp_ener = []
for ii in frames:
log_lmp = os.path.join(ii, 'log.lammps')
natoms, epa, vpa = lammps.get_nev(log_lmp)
lmp_ener.append(epa)
lmp_ener = np.array(lmp_ener)
lmp_ener = np.reshape(lmp_ener, [-1, 1])
lmp_ener_file = os.path.join(ls, 'ener.lmp.out')
vasp_ener = np.reshape(vasp_ener, [-1, 1]) / natoms
error_start = 1
lmp_ener -= lmp_ener[-1] - vasp_ener[-1]
diff = lmp_ener - vasp_ener
diff = diff[error_start:]
error = np.linalg.norm(diff) / np.sqrt(np.size(lmp_ener))
np.savetxt(vasp_ener_file, vasp_ener[error_start:])
np.savetxt(lmp_ener_file, lmp_ener[error_start:])
print(os.path.basename(ls), 'EpA_std_err=', error)
def post_repro(vasp_path, all_tasks, ptr_data):
ptr_data += "Reproduce: VASP_path DFT_E(eV/atom) LMP_E(eV/atom) Difference(eV/atom)\n"
vasp_task = glob.glob(os.path.join(vasp_path, 'task.[0-9]*[0-9]'))
assert len(vasp_task) > 0, "Please do VASP calcualtions first"
vasp_task.sort()
vasp_ener_tot = []
lmp_ener_tot = []
res_data = {}
for ii in vasp_task:
# compute vasp
outcar = os.path.join(ii, 'OUTCAR')
vasp_ener = np.array(vasp.get_energies(outcar))
vasp_ener_file = os.path.join(ii, 'ener.vasp.out')
# compute reprod
lmp_ener = []
if len(all_tasks) < (len(vasp_ener_tot) + len(vasp_ener)):
raise RuntimeError("lammps tasks reproduced not equal to vasp")
natoms = 1
for jj in range(
len(vasp_ener_tot), (len(vasp_ener_tot) + len(vasp_ener))
): #all_tasks[len(vasp_ener_tot):(len(vasp_ener_tot) + len(vasp_ener))]:
log_lmp = os.path.join(all_tasks[jj], 'log.lammps')
if not os.path.exists(log_lmp):
raise RuntimeError("lammps reproduce not finished")
natoms, epa, vpa = lammps.get_nev(log_lmp)
lmp_ener.append(epa)
lmp_ener_tot.append(epa)
vasp_epa = list(vasp_ener)[jj - len(vasp_ener_tot)] / natoms
ptr_data += '%s %7.3f %7.3f %7.3f\n' % (vasp_task[ii], vasp_epa,
epa, epa - vasp_epa)
lmp_ener = np.array(lmp_ener)
lmp_ener = np.reshape(lmp_ener, [-1, 1])
vasp_ener_tot += list(vasp_ener)
vasp_ener = np.reshape(vasp_ener, [-1, 1]) / natoms
error_start = 1
lmp_ener -= lmp_ener[-1] - vasp_ener[-1]
diff = lmp_ener - vasp_ener
diff = diff[error_start:]
error = np.linalg.norm(diff) / np.sqrt(np.size(lmp_ener))
res_data[ii] = {'nframes': len(vasp_ener), 'error': error}
np.savetxt(vasp_ener_file, vasp_ener[error_start:])
if not len(vasp_ener_tot) == len(lmp_ener_tot):
raise RuntimeError("lammps tasks reproduced not equal to vasp")
# for ii in range(len(lmp_ener_tot)):
# ptr_data += '%7.3f %7.3f %7.3f\n' % (vasp_ener_tot[ii], lmp_ener_tot[ii],
# lmp_ener_tot[ii] - vasp_ener_tot[ii])
return res_data, ptr_data
def cmpt_vasp(jdata, conf_dir, static=False):
fp_params = jdata['vasp_params']
kspacing = fp_params['kspacing']
equi_path = re.sub('confs', global_equi_name, conf_dir)
equi_path = os.path.join(equi_path, 'vasp-k%.2f' % kspacing)
equi_path = os.path.abspath(equi_path)
equi_outcar = os.path.join(equi_path, 'OUTCAR')
task_path = re.sub('confs', global_task_name, conf_dir)
if static:
task_path = os.path.join(task_path, 'vasp-static-k%.2f' % kspacing)
else:
task_path = os.path.join(task_path, 'vasp-k%.2f' % kspacing)
task_path = os.path.abspath(task_path)
equi_natoms, equi_epa, equi_vpa = vasp.get_nev(equi_outcar)
struct_path_widecard = os.path.join(task_path, 'struct-*-m*m')
struct_path_list = glob.glob(struct_path_widecard)
struct_path_list.sort()
if len(struct_path_list) == 0:
print("# cannot find results for conf %s supercell %s" %
(conf_dir, supercell))
sys.stdout.write("Miller_Indices: \tSurf_E(J/m^2) EpA(eV) equi_EpA(eV)\n")
for ii in struct_path_list:
structure_dir = os.path.basename(ii)
outcar = os.path.join(ii, 'OUTCAR')
natoms, epa, vpa = vasp.get_nev(outcar)
if static:
e0 = np.array(vasp.get_energies(outcar)) / natoms
epa = e0[0]
boxes = vasp.get_boxes(outcar)
AA = np.linalg.norm(np.cross(boxes[0][0], boxes[0][1]))
Cf = 1.60217657e-16 / (1e-20 * 2) * 0.001
evac = (epa * natoms - equi_epa * natoms) / AA * Cf
sys.stdout.write("%s:\t %7.3f %8.3f %8.3f\n" %
(structure_dir, evac, epa, equi_epa))
def _make_reprod_traj(jdata, conf_dir, supercell, insert_ele, task_type):
kspacing = jdata['vasp_params']['kspacing']
fp_params = jdata['lammps_params']
model_dir = fp_params['model_dir']
type_map = fp_params['type_map']
model_dir = os.path.abspath(model_dir)
model_name = fp_params['model_name']
if not model_name and task_type == 'deepmd':
models = glob.glob(os.path.join(model_dir, '*pb'))
model_name = [os.path.basename(ii) for ii in models]
assert len(model_name) > 0, "No deepmd model in the model_dir"
else:
models = [os.path.join(model_dir, ii) for ii in model_name]
model_param = {
'model_name': fp_params['model_name'],
'param_type': fp_params['model_param_type']
}
ntypes = len(type_map)
conf_path = os.path.abspath(conf_dir)
task_path = re.sub('confs', global_task_name, conf_path)
vasp_path = os.path.join(task_path, 'vasp-k%.2f' % kspacing)
lmps_path = os.path.join(task_path, task_type + '-reprod-k%.2f' % kspacing)
os.makedirs(lmps_path, exist_ok=True)
copy_str = "%sx%sx%s" % (supercell[0], supercell[1], supercell[2])
struct_widecard = os.path.join(vasp_path,
'struct-%s-%s-*' % (insert_ele, copy_str))
vasp_struct = glob.glob(struct_widecard)
vasp_struct.sort()
cwd = os.getcwd()
# make lammps.in
if task_type == 'deepmd':
fc = lammps.make_lammps_eval('conf.lmp', ntypes, lammps.inter_deepmd,
model_name)
elif task_type == 'meam':
fc = lammps.make_lammps_eval('conf.lmp', ntypes, lammps.inter_meam,
model_param)
f_lammps_in = os.path.join(lmps_path, 'lammps.in')
with open(f_lammps_in, 'w') as fp:
fp.write(fc)
for vs in vasp_struct:
# get vasp energy
outcar = os.path.join(vs, 'OUTCAR')
energies = vasp.get_energies(outcar)
# get xdat
xdatcar = os.path.join(vs, 'XDATCAR')
struct_basename = os.path.basename(vs)
ls = os.path.join(lmps_path, struct_basename)
print(ls)
os.makedirs(ls, exist_ok=True)
os.chdir(ls)
if os.path.exists('XDATCAR'):
os.remove('XDATCAR')
os.symlink(os.path.relpath(xdatcar), 'XDATCAR')
xdat_lines = open('XDATCAR', 'r').read().split('\n')
natoms = vasp.poscar_natoms('XDATCAR')
xdat_secsize = natoms + 8
xdat_nframes = len(xdat_lines) // xdat_secsize
if xdat_nframes > len(energies):
warnings.warn(
'nframes %d in xdat is larger than energy %d, use the last %d frames'
% (xdat_nframes, len(energies), len(energies)))
xdat_nlines = len(energies) * xdat_secsize
xdat_lines = xdat_lines[xdat_nlines:]
xdat_nframes = len(xdat_lines) // xdat_secsize
print(xdat_nframes, len(energies))
#link lammps.in and model
for jj in ['lammps.in'] + model_name:
if os.path.islink(jj):
os.unlink(jj)
os.symlink(os.path.relpath(f_lammps_in), 'lammps.in')
if task_type == 'deepmd':
for ii in model_name:
if os.path.exists(ii):
os.remove(ii)
for (ii, jj) in zip(models, model_name):
os.symlink(os.path.relpath(ii), jj)
share_models = glob.glob(os.path.join(ls, '*pb'))
else:
share_models = models
# loop over frames
for ii in range(xdat_nframes):
frame_path = 'frame.%06d' % ii
os.makedirs(frame_path, exist_ok=True)
os.chdir(frame_path)
# clear dir
for jj in ['conf.lmp']:
if os.path.isfile(jj):
os.remove(jj)
for jj in ['lammps.in'] + model_name:
if os.path.islink(jj):
os.unlink(jj)
# link lammps in
os.symlink(os.path.relpath('../lammps.in'), 'lammps.in')
# make conf
with open('POSCAR', 'w') as fp:
fp.write('\n'.join(xdat_lines[ii * xdat_secsize:(ii + 1) *
xdat_secsize]))
lammps.cvt_lammps_conf('POSCAR', 'conf.lmp')
ptypes = vasp.get_poscar_types('POSCAR')
lammps.apply_type_map('conf.lmp', type_map, ptypes)
# link models
for (kk, ll) in zip(share_models, model_name):
os.symlink(os.path.relpath(kk), ll)
os.chdir(ls)
os.chdir(cwd)