def setUp(self):
self.norm_str = Strain.from_deformation([[1.02, 0, 0], [0, 1, 0], [0, 0, 1]])
self.ind_str = Strain.from_deformation([[1, 0.02, 0], [0, 1, 0], [0, 0, 1]])
self.non_ind_str = Strain.from_deformation([[1, 0.02, 0.02], [0, 1, 0], [0, 0, 1]])
with warnings.catch_warnings(record=True):
warnings.simplefilter("always")
self.no_dfm = Strain([[0.0, 0.01, 0.0], [0.01, 0.0002, 0.0], [0.0, 0.0, 0.0]])
def setUp(self):
self.norm_str = Strain.from_deformation([[1.02, 0, 0], [0, 1, 0],
[0, 0, 1]])
self.ind_str = Strain.from_deformation([[1, 0.02, 0], [0, 1, 0],
[0, 0, 1]])
self.non_ind_str = Strain.from_deformation([[1, 0.02, 0.02], [0, 1, 0],
[0, 0, 1]])
with warnings.catch_warnings(record=True):
warnings.simplefilter("always")
self.no_dfm = Strain([[0., 0.01, 0.], [0.01, 0.0002, 0.],
[0., 0., 0.]])
def test_energy_density(self):
film_elac = ElasticTensor.from_voigt(
[[324.32, 187.3, 170.92, 0., 0., 0.],
[187.3, 324.32, 170.92, 0., 0., 0.],
[170.92, 170.92, 408.41, 0., 0., 0.],
[0., 0., 0., 150.73, 0., 0.], [0., 0., 0., 0., 150.73, 0.],
[0., 0., 0., 0., 0., 238.74]])
dfm = Deformation([[-9.86004855e-01, 2.27539582e-01, -4.64426035e-17],
[-2.47802121e-01, -9.91208483e-01, -7.58675185e-17],
[-6.12323400e-17, -6.12323400e-17, 1.00000000e+00]])
self.assertAlmostEqual(
film_elac.energy_density(dfm.green_lagrange_strain),
0.00125664672793)
film_elac.energy_density(
Strain.from_deformation([[0.99774738, 0.11520994, -0.],
[-0.11520994, 0.99774738, 0.],
[
-0.,
-0.,
1.,
]]))
def test_from_strain_stress_list(self):
strain_list = [Strain.from_deformation(def_matrix)
for def_matrix in self.def_stress_dict['deformations']]
stress_list = [stress for stress in self.def_stress_dict['stresses']]
with warnings.catch_warnings(record = True):
et_fl = -0.1*ElasticTensor.from_strain_stress_list(strain_list, stress_list)
self.assertArrayAlmostEqual(et_fl.round(2),
[[59.29, 24.36, 22.46, 0, 0, 0],
[28.06, 56.91, 22.46, 0, 0, 0],
[28.06, 25.98, 54.67, 0, 0, 0],
[0, 0, 0, 26.35, 0, 0],
[0, 0, 0, 0, 26.35, 0],
[0, 0, 0, 0, 0, 26.35]])
def test_from_pseudoinverse(self):
strain_list = [Strain.from_deformation(def_matrix)
for def_matrix in self.def_stress_dict['deformations']]
stress_list = [stress for stress in self.def_stress_dict['stresses']]
with warnings.catch_warnings(record=True):
et_fl = -0.1*ElasticTensor.from_pseudoinverse(strain_list,
stress_list).voigt
self.assertArrayAlmostEqual(et_fl.round(2),
[[59.29, 24.36, 22.46, 0, 0, 0],
[28.06, 56.91, 22.46, 0, 0, 0],
[28.06, 25.98, 54.67, 0, 0, 0],
[0, 0, 0, 26.35, 0, 0],
[0, 0, 0, 0, 26.35, 0],
[0, 0, 0, 0, 0, 26.35]])
def run_task(self, fw_spec):
v, _ = get_vasprun_outcar(self.get("calc_dir", "."), parse_dos=False, parse_eigen=False)
stress = v.ionic_steps[-1]['stress']
defo = self['deformation']
d_ind = np.nonzero(defo - np.eye(3))
delta = Decimal((defo - np.eye(3))[d_ind][0])
# Shorthand is d_X_V, X is voigt index, V is value
dtype = "_".join(["d", str(reverse_voigt_map[d_ind][0]),
"{:.0e}".format(delta)])
strain = Strain.from_deformation(defo)
defo_dict = {'deformation_matrix': defo,
'strain': strain.tolist(),
'stress': stress}
return FWAction(mod_spec=[{'_set': {
'deformation_tasks->{}'.format(dtype): defo_dict}}])
def test_energy_density(self):
film_elac = ElasticTensor.from_voigt([
[324.32, 187.3, 170.92, 0., 0., 0.],
[187.3, 324.32, 170.92, 0., 0., 0.],
[170.92, 170.92, 408.41, 0., 0., 0.],
[0., 0., 0., 150.73, 0., 0.],
[0., 0., 0., 0., 150.73, 0.],
[0., 0., 0., 0., 0., 238.74]])
dfm = Deformation([[ -9.86004855e-01,2.27539582e-01,-4.64426035e-17],
[ -2.47802121e-01,-9.91208483e-01,-7.58675185e-17],
[ -6.12323400e-17,-6.12323400e-17,1.00000000e+00]])
self.assertAlmostEqual(film_elac.energy_density(dfm.green_lagrange_strain),
0.00125664672793)
film_elac.energy_density(Strain.from_deformation([[ 0.99774738, 0.11520994, -0. ],
[-0.11520994, 0.99774738, 0. ],
[-0., -0., 1., ]]))
def run_task(self, fw_spec):
v, _ = get_vasprun_outcar(self.get("calc_dir", "."),
parse_dos=False,
parse_eigen=False)
stress = v.ionic_steps[-1]['stress']
defo = self['deformation']
d_ind = np.nonzero(defo - np.eye(3))
delta = Decimal((defo - np.eye(3))[d_ind][0])
# Shorthand is d_X_V, X is voigt index, V is value
dtype = "_".join(
["d",
str(reverse_voigt_map[d_ind][0]), "{:.0e}".format(delta)])
strain = Strain.from_deformation(defo)
defo_dict = {
'deformation_matrix': defo,
'strain': strain.tolist(),
'stress': stress
}
return FWAction(mod_spec=[{
'_set': {
'deformation_tasks->{}'.format(dtype): defo_dict
}
}])
def runSimulation(self):
if self.args["pymatgen"] == True:
starting_struct = singleFromFile(self.args)
info = runCalc("all_relax", ["structures","stresses"], [starting_struct], self.args)
relaxed_struct = info["structures"][0]
relaxed_stress = info["stresses"][0]
strains = []
deformed_set = DeformedStructureSet(relaxed_struct, symmetry=True)
deformed_structs = deformed_set.deformed_structures
symmetry_dict = deformed_set.sym_dict
deformations = deformed_set.deformations
stresses = runCalc("atom_relax", ["stresses"], deformed_structs, self.args)["stresses"]
for i in range(len(deformations)):
strains.append(Strain.from_deformation(deformations[i]))
for i in range(len(deformations)):
for symm in symmetry_dict[deformations[i]]:
strains.append(strains[i].transform(symm))
stresses.append(stresses[i].transform(symm))
self.elastic_tensor = ElasticTensor.from_independent_strains(strains,stresses,eq_stress=relaxed_stress,vasp=True).zeroed().voigt
def make_vasp(jdata, conf_dir, norm_def = 2e-3, shear_def = 5e-3) :
norm_def = jdata['norm_deform']
shear_def = jdata['shear_deform']
conf_path = os.path.abspath(conf_dir)
conf_poscar = os.path.join(conf_path, 'POSCAR')
# get equi poscar
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_path)
equi_path = os.path.join(equi_path, vasp_str)
equi_contcar = os.path.join(equi_path, 'CONTCAR')
task_path = re.sub('confs', global_task_name, conf_path)
task_path = os.path.join(task_path, vasp_str)
os.makedirs(task_path, exist_ok=True)
cwd = os.getcwd()
os.chdir(task_path)
if os.path.isfile('POSCAR') :
os.remove('POSCAR')
os.symlink(os.path.relpath(equi_contcar), 'POSCAR')
os.chdir(cwd)
task_poscar = os.path.join(task_path, 'POSCAR')
# stress
equi_outcar = os.path.join(equi_path, 'OUTCAR')
stress = vasp.get_stress(equi_outcar)
np.savetxt(os.path.join(task_path, 'equi.stress.out'), stress)
# gen strcture
ss = Structure.from_file(task_poscar)
# gen defomations
norm_strains = [-norm_def, -0.5*norm_def, 0.5*norm_def, norm_def]
shear_strains = [-shear_def, -0.5*shear_def, 0.5*shear_def, shear_def]
dfm_ss = DeformedStructureSet(ss,
symmetry = False,
norm_strains = norm_strains,
shear_strains = shear_strains)
n_dfm = len(dfm_ss)
# gen incar
if 'relax_incar' in jdata.keys():
relax_incar_path = jdata['relax_incar']
assert(os.path.exists(relax_incar_path))
relax_incar_path = os.path.abspath(relax_incar_path)
fc = open(relax_incar_path).read()
kspacing =float(re.findall((r"KSPACING(.+?)\n"),fc)[0].replace('=',''))
kgamma =('T' in re.findall((r"KGAMMA(.+?)\n"),fc)[0])
else :
fp_params = jdata['vasp_params']
ecut = fp_params['ecut']
ediff = fp_params['ediff']
npar = fp_params['npar']
kpar = fp_params['kpar']
kspacing = fp_params['kspacing']
kgamma = fp_params['kgamma']
fc = vasp.make_vasp_relax_incar(ecut, ediff, True, False, False, npar=npar,kpar=kpar, kspacing = kspacing, kgamma = kgamma)
with open(os.path.join(task_path, 'INCAR'), 'w') as fp :
fp.write(fc)
# gen potcar
with open(task_poscar,'r') as fp :
lines = fp.read().split('\n')
ele_list = lines[5].split()
potcar_map = jdata['potcar_map']
potcar_list = []
for ii in ele_list :
assert os.path.exists(os.path.abspath(potcar_map[ii])),"No POTCAR in the potcar_map of %s"%(ii)
potcar_list.append(os.path.abspath(potcar_map[ii]))
with open(os.path.join(task_path,'POTCAR'), 'w') as outfile:
for fname in potcar_list:
with open(fname) as infile:
outfile.write(infile.read())
# gen kpoints
fc = vasp.make_kspacing_kpoints(task_poscar, kspacing, kgamma)
with open(os.path.join(task_path,'KPOINTS'), 'w') as fp:
fp.write(fc)
# gen tasks
cwd = os.getcwd()
for ii in range(n_dfm) :
# make dir
dfm_path = os.path.join(task_path, 'dfm-%03d' % ii)
os.makedirs(dfm_path, exist_ok=True)
os.chdir(dfm_path)
for jj in ['POSCAR', 'POTCAR', 'INCAR', 'KPOINTS'] :
if os.path.isfile(jj):
os.remove(jj)
# make conf
dfm_ss.deformed_structures[ii].to('POSCAR', 'POSCAR')
# record strain
strain = Strain.from_deformation(dfm_ss.deformations[ii])
np.savetxt('strain.out', strain)
# link incar, potcar, kpoints
os.symlink(os.path.relpath(os.path.join(task_path, 'INCAR')), 'INCAR')
os.symlink(os.path.relpath(os.path.join(task_path, 'POTCAR')), 'POTCAR')
os.symlink(os.path.relpath(os.path.join(task_path, 'KPOINTS')), 'KPOINTS')
cwd = os.getcwd()
def make_lammps(jdata, conf_dir,task_type) :
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)
norm_def = jdata['norm_deform']
shear_def = jdata['shear_deform']
conf_path = os.path.abspath(conf_dir)
conf_poscar = os.path.join(conf_path, 'POSCAR')
# get equi poscar
equi_path = re.sub('confs', global_equi_name, conf_path)
equi_path = os.path.join(equi_path, task_type)
equi_dump = os.path.join(equi_path, 'dump.relax')
task_path = re.sub('confs', global_task_name, conf_path)
task_path = os.path.join(task_path, task_type)
os.makedirs(task_path, exist_ok=True)
task_poscar = os.path.join(task_path, 'POSCAR')
lammps.poscar_from_last_dump(equi_dump, task_poscar, type_map)
# get equi stress
equi_log = os.path.join(equi_path, 'log.lammps')
stress = lammps.get_stress(equi_log)
np.savetxt(os.path.join(task_path, 'equi.stress.out'), stress)
# gen strcture
# ss = Structure.from_file(conf_poscar)
# print(ss)
# ss = ss.from_file(task_poscar)
# print(ss)
ss = Structure.from_file(task_poscar)
# gen defomations
norm_strains = [-norm_def, -0.5*norm_def, 0.5*norm_def, norm_def]
shear_strains = [-shear_def, -0.5*shear_def, 0.5*shear_def, shear_def]
print('gen with norm '+str(norm_strains))
print('gen with shear '+str(shear_strains))
dfm_ss = DeformedStructureSet(ss,
symmetry = False,
norm_strains = norm_strains,
shear_strains = shear_strains)
n_dfm = len(dfm_ss)
# gen tasks
cwd = os.getcwd()
# make lammps.in
if task_type=='deepmd':
fc = lammps.make_lammps_elastic('conf.lmp',
ntypes,
lammps.inter_deepmd,
model_name)
elif task_type=='meam':
fc = lammps.make_lammps_elastic('conf.lmp',
ntypes,
lammps.inter_meam,
model_param)
f_lammps_in = os.path.join(task_path, 'lammps.in')
with open(f_lammps_in, 'w') as fp :
fp.write(fc)
cwd = os.getcwd()
os.chdir(task_path)
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 = [os.path.join(task_path,ii) for ii in model_name]
for ii in range(n_dfm) :
# make dir
dfm_path = os.path.join(task_path, 'dfm-%03d' % ii)
os.makedirs(dfm_path, exist_ok=True)
os.chdir(dfm_path)
for jj in ['conf.lmp', 'lammps.in'] + model_name :
if os.path.isfile(jj):
os.remove(jj)
# make conf
dfm_ss.deformed_structures[ii].to('POSCAR', 'POSCAR')
lammps.cvt_lammps_conf('POSCAR', 'conf.lmp')
ptypes = vasp.get_poscar_types('POSCAR')
lammps.apply_type_map('conf.lmp', type_map, ptypes)
# record strain
strain = Strain.from_deformation(dfm_ss.deformations[ii])
np.savetxt('strain.out', strain)
# link lammps.in
os.symlink(os.path.relpath(f_lammps_in), 'lammps.in')
# link models
for (ii,jj) in zip(share_models, model_name) :
os.symlink(os.path.relpath(ii), jj)
cwd = os.getcwd()
def make_vasp(jdata, conf_dir, norm_def=2e-3, shear_def=5e-3):
fp_params = jdata['vasp_params']
ecut = fp_params['ecut']
ediff = fp_params['ediff']
npar = fp_params['npar']
kpar = fp_params['kpar']
kspacing = fp_params['kspacing']
kgamma = fp_params['kgamma']
strain_start = jdata['strain_start']
strain_end = jdata['strain_end']
strain_step = jdata['strain_step']
strain_direct = jdata['strain_direct']
conf_path = os.path.abspath(conf_dir)
conf_poscar = os.path.join(conf_path, 'POSCAR')
# get equi poscar
equi_path = re.sub('confs', global_equi_name, conf_path)
equi_path = os.path.join(equi_path, 'vasp-k%.2f' % kspacing)
equi_contcar = os.path.join(equi_path, 'CONTCAR')
task_path = re.sub('confs', global_task_name, conf_path)
task_path = os.path.join(task_path, 'vasp-k%.2f' % kspacing)
os.makedirs(task_path, exist_ok=True)
cwd = os.getcwd()
os.chdir(task_path)
if os.path.isfile('POSCAR'):
os.remove('POSCAR')
os.symlink(os.path.relpath(equi_contcar), 'POSCAR')
os.chdir(cwd)
task_poscar = os.path.join(task_path, 'POSCAR')
# stress
equi_outcar = os.path.join(equi_path, 'OUTCAR')
stress = vasp.get_stress(equi_outcar)
np.savetxt(os.path.join(task_path, 'equi.stress.out'), stress)
# gen strcture
ss = Structure.from_file(task_poscar)
# gen defomations
norm_strains = np.arange(strain_start, strain_end, strain_step)
print('gen with norm ' + str(norm_strains))
deformations = []
for ii in norm_strains:
strain = Strain.from_index_amount(strain_direct, ii)
deformations.append(strain.get_deformation_matrix())
deformed_structures = [
defo.apply_to_structure(ss) for defo in deformations
]
n_dfm = len(deformed_structures)
# gen incar
fc = vasp.make_vasp_relax_incar(ecut,
ediff,
True,
False,
False,
npar=npar,
kpar=kpar,
kspacing=None,
kgamma=None)
with open(os.path.join(task_path, 'INCAR'), 'w') as fp:
fp.write(fc)
# gen potcar
with open(task_poscar, 'r') as fp:
lines = fp.read().split('\n')
ele_list = lines[5].split()
potcar_map = jdata['potcar_map']
potcar_list = []
for ii in ele_list:
assert (os.path.exists(potcar_map[ii]))
potcar_list.append(potcar_map[ii])
with open(os.path.join(task_path, 'POTCAR'), 'w') as outfile:
for fname in potcar_list:
with open(fname) as infile:
outfile.write(infile.read())
# gen kpoints
fc = vasp.make_kspacing_kpoints(task_poscar, kspacing, kgamma)
with open(os.path.join(task_path, 'KPOINTS'), 'w') as fp:
fp.write(fc)
# gen tasks
cwd = os.getcwd()
for ii in range(n_dfm):
# make dir
dfm_path = os.path.join(task_path, 'dfm-%03d' % ii)
os.makedirs(dfm_path, exist_ok=True)
os.chdir(dfm_path)
for jj in ['POSCAR', 'POTCAR', 'INCAR', 'KPOINTS']:
if os.path.isfile(jj):
os.remove(jj)
# make conf
deformed_structures[ii].to('POSCAR', 'POSCAR')
# record strain
strain = Strain.from_deformation(deformations[ii])
np.savetxt('strain.out', strain)
# link incar, potcar, kpoints
os.symlink(os.path.relpath(os.path.join(task_path, 'INCAR')), 'INCAR')
os.symlink(os.path.relpath(os.path.join(task_path, 'POTCAR')),
'POTCAR')
os.symlink(os.path.relpath(os.path.join(task_path, 'KPOINTS')),
'KPOINTS')
cwd = os.getcwd()
def make_lammps(jdata, conf_dir, task_type):
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:
models = glob.glob(os.path.join(model_dir, '*pb'))
model_name = [os.path.basename(ii) for ii in models]
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)
strain_start = jdata['strain_start']
strain_end = jdata['strain_end']
strain_step = jdata['strain_step']
strain_direct = jdata['strain_direct']
conf_path = os.path.abspath(conf_dir)
conf_poscar = os.path.join(conf_path, 'POSCAR')
# get equi poscar
equi_path = re.sub('confs', global_equi_name, conf_path)
equi_path = os.path.join(equi_path, task_type)
equi_dump = os.path.join(equi_path, 'dump.relax')
task_path = re.sub('confs', global_task_name, conf_path)
task_path = os.path.join(task_path, task_type)
os.makedirs(task_path, exist_ok=True)
task_poscar = os.path.join(task_path, 'POSCAR')
lammps.poscar_from_last_dump(equi_dump, task_poscar, type_map)
# get equi stress
equi_log = os.path.join(equi_path, 'log.lammps')
stress = lammps.get_stress(equi_log)
np.savetxt(os.path.join(task_path, 'equi.stress.out'), stress)
# gen strcture
ss = Structure.from_file(task_poscar)
# gen defomations
norm_strains = np.arange(strain_start, strain_end, strain_step)
print('gen with norm ' + str(norm_strains))
deformations = []
for ii in norm_strains:
strain = Strain.from_index_amount(strain_direct, ii)
deformations.append(strain.get_deformation_matrix())
deformed_structures = [
defo.apply_to_structure(ss) for defo in deformations
]
n_dfm = len(deformed_structures)
# gen tasks
cwd = os.getcwd()
# make lammps.in
if task_type == 'deepmd':
fc = lammps.make_lammps_elastic('conf.lmp', ntypes,
lammps.inter_deepmd, model_name)
elif task_type == 'meam':
fc = lammps.make_lammps_elastic('conf.lmp', ntypes, lammps.inter_meam,
model_param)
f_lammps_in = os.path.join(task_path, 'lammps.in')
with open(f_lammps_in, 'w') as fp:
fp.write(fc)
cwd = os.getcwd()
if task_type == 'deepmd':
os.chdir(task_path)
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(task_path, '*pb'))
else:
share_models = models
for ii in range(n_dfm):
# make dir
dfm_path = os.path.join(task_path, 'dfm-%03d' % ii)
os.makedirs(dfm_path, exist_ok=True)
os.chdir(dfm_path)
for jj in ['conf.lmp', 'lammps.in'] + model_name:
if os.path.isfile(jj):
os.remove(jj)
# make conf
deformed_structures[ii].to('POSCAR', 'POSCAR')
lammps.cvt_lammps_conf('POSCAR', 'conf.lmp')
ptypes = vasp.get_poscar_types('POSCAR')
lammps.apply_type_map('conf.lmp', type_map, ptypes)
# record strain
strain = Strain.from_deformation(deformations[ii])
np.savetxt('strain.out', strain)
# link lammps.in
os.symlink(os.path.relpath(f_lammps_in), 'lammps.in')
# link models
for (ii, jj) in zip(share_models, model_name):
os.symlink(os.path.relpath(ii), jj)
cwd = os.getcwd()
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)
task_list = []
cwd = os.getcwd()
norm_def = self.norm_deform
shear_def = self.shear_deform
norm_strains = [-norm_def, -0.5 * norm_def, 0.5 * norm_def, norm_def]
shear_strains = [
-shear_def, -0.5 * shear_def, 0.5 * shear_def, shear_def
]
print('gen with norm ' + str(norm_strains))
print('gen with shear ' + str(shear_strains))
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)
dfm_ss = DeformedStructureSet(ss,
symmetry=False,
norm_strains=norm_strains,
shear_strains=shear_strains)
n_dfm = len(dfm_ss)
os.chdir(path_to_work)
if os.path.isfile('POSCAR'):
os.remove('POSCAR')
os.symlink(os.path.relpath(equi_contcar), 'POSCAR')
# task_poscar = os.path.join(output, 'POSCAR')
# stress
equi_outcar = os.path.join(path_to_equi, 'OUTCAR')
equi_log = os.path.join(path_to_equi, 'log.lammps')
if os.path.exists(equi_outcar):
stress = vasp.get_stress(equi_outcar)
np.savetxt('equi.stress.out', stress)
elif os.path.exists(equi_log):
stress = lammps.get_stress(equi_log)
np.savetxt('equi.stress.out', stress)
os.chdir(cwd)
if refine:
task_list = make_refine(self.parameter['init_from_suffix'],
self.parameter['output_suffix'],
path_to_work, n_dfm)
os.chdir(cwd)
else:
for ii in range(n_dfm):
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)
dfm_ss.deformed_structures[ii].to('POSCAR', 'POSCAR')
# record strain
strain = Strain.from_deformation(dfm_ss.deformations[ii])
np.savetxt('strain.out', strain)
os.chdir(cwd)
return task_list
def make_deepmd_lammps(jdata, conf_dir) :
deepmd_model_dir = jdata['deepmd_model_dir']
deepmd_type_map = jdata['deepmd_type_map']
ntypes = len(deepmd_type_map)
deepmd_model_dir = os.path.abspath(deepmd_model_dir)
deepmd_models = glob.glob(os.path.join(deepmd_model_dir, '*pb'))
deepmd_models_name = [os.path.basename(ii) for ii in deepmd_models]
norm_def = jdata['norm_deform']
shear_def = jdata['shear_deform']
conf_path = os.path.abspath(conf_dir)
conf_poscar = os.path.join(conf_path, 'POSCAR')
# get equi poscar
equi_path = re.sub('confs', global_equi_name, conf_path)
equi_path = os.path.join(equi_path, 'deepmd')
equi_dump = os.path.join(equi_path, 'dump.relax')
task_path = re.sub('confs', global_task_name, conf_path)
task_path = os.path.join(task_path, 'deepmd')
os.makedirs(task_path, exist_ok=True)
task_poscar = os.path.join(task_path, 'POSCAR')
lammps.poscar_from_last_dump(equi_dump, task_poscar, deepmd_type_map)
# get equi stress
equi_log = os.path.join(equi_path, 'log.lammps')
stress = lammps.get_stress(equi_log)
np.savetxt(os.path.join(task_path, 'equi.stress.out'), stress)
# gen strcture
# ss = Structure.from_file(conf_poscar)
# print(ss)
# ss = ss.from_file(task_poscar)
# print(ss)
ss = Structure.from_file(task_poscar)
# gen defomations
norm_strains = [-norm_def, -0.5*norm_def, 0.5*norm_def, norm_def]
shear_strains = [-shear_def, -0.5*shear_def, 0.5*shear_def, shear_def]
print('gen with norm '+str(norm_strains))
print('gen with shear '+str(shear_strains))
dfm_ss = DeformedStructureSet(ss,
symmetry = False,
norm_strains = norm_strains,
shear_strains = shear_strains)
n_dfm = len(dfm_ss)
# gen tasks
cwd = os.getcwd()
# make lammps.in
fc = lammps.make_lammps_elastic('conf.lmp',
ntypes,
lammps.inter_deepmd,
deepmd_models_name)
f_lammps_in = os.path.join(task_path, 'lammps.in')
with open(f_lammps_in, 'w') as fp :
fp.write(fc)
cwd = os.getcwd()
for ii in range(n_dfm) :
# make dir
dfm_path = os.path.join(task_path, 'dfm-%03d' % ii)
os.makedirs(dfm_path, exist_ok=True)
os.chdir(dfm_path)
for jj in ['conf.lmp', 'lammps.in'] + deepmd_models_name :
if os.path.isfile(jj):
os.remove(jj)
# make conf
dfm_ss.deformed_structures[ii].to('POSCAR', 'POSCAR')
lammps.cvt_lammps_conf('POSCAR', 'conf.lmp')
ptypes = vasp.get_poscar_types('POSCAR')
lammps.apply_type_map('conf.lmp', deepmd_type_map, ptypes)
# record strain
strain = Strain.from_deformation(dfm_ss.deformations[ii])
np.savetxt('strain.out', strain)
# link lammps.in
os.symlink(os.path.relpath(f_lammps_in), 'lammps.in')
# link models
for (ii,jj) in zip(deepmd_models, deepmd_models_name) :
os.symlink(os.path.relpath(ii), jj)
cwd = os.getcwd()
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()
equi_contcar = os.path.join(path_to_equi, 'CONTCAR')
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')
# stress, deal with unsupported stress in dpdata
#with open(os.path.join(path_to_equi, 'result.json')) as fin:
# equi_result = json.load(fin)
#equi_stress = np.array(equi_result['stress']['data'])[-1]
equi_result = loadfn(os.path.join(path_to_equi, 'result.json'))
equi_stress = equi_result['stress'][-1]
dumpfn(equi_stress, 'equi.stress.json', indent=4)
os.chdir(cwd)
if refine:
print('elastic refine starts')
task_list = make_refine(self.parameter['init_from_suffix'],
self.parameter['output_suffix'],
path_to_work)
# record strain
# df = Strain.from_deformation(dfm_ss.deformations[idid])
# dumpfn(df.as_dict(), 'strain.json', indent=4)
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('strain.json'):
os.remove('strain.json')
copyfile(os.path.join(init_from_task, 'strain.json'),
'strain.json')
#os.symlink(os.path.relpath(
# os.path.join((re.sub(self.parameter['output_suffix'], self.parameter['init_from_suffix'], ii)),
# 'strain.json')),
# 'strain.json')
os.chdir(cwd)
else:
norm_def = self.norm_deform
shear_def = self.shear_deform
norm_strains = [
-norm_def, -0.5 * norm_def, 0.5 * norm_def, norm_def
]
shear_strains = [
-shear_def, -0.5 * shear_def, 0.5 * shear_def, shear_def
]
if not os.path.exists(equi_contcar):
raise RuntimeError("please do relaxation first")
ss = Structure.from_file(equi_contcar)
dfm_ss = DeformedStructureSet(ss,
symmetry=False,
norm_strains=norm_strains,
shear_strains=shear_strains)
n_dfm = len(dfm_ss)
print('gen with norm ' + str(norm_strains))
print('gen with shear ' + str(shear_strains))
for ii in range(n_dfm):
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)
dfm_ss.deformed_structures[ii].to('POSCAR', 'POSCAR')
# record strain
df = Strain.from_deformation(dfm_ss.deformations[ii])
dumpfn(df.as_dict(), 'strain.json', indent=4)
os.chdir(cwd)
return task_list
def get_wf_elastic_constant(structure,
metadata,
strain_states=None,
stencils=None,
db_file=None,
conventional=False,
order=2,
vasp_input_set=None,
analysis=True,
sym_reduce=False,
tag='elastic',
copy_vasp_outputs=False,
**kwargs):
"""
Returns a workflow to calculate elastic constants.
Firework 1 : write vasp input set for structural relaxation,
run vasp,
pass run location,
database insertion.
Firework 2 - number of total deformations: Static runs on the deformed structures
last Firework : Analyze Stress/Strain data and fit the elastic tensor
Args:
structure (Structure): input structure to be optimized and run.
strain_states (list of Voigt-notation strains): list of ratios of nonzero elements
of Voigt-notation strain, e. g. [(1, 0, 0, 0, 0, 0), (0, 1, 0, 0, 0, 0), etc.].
stencils (list of floats, or list of list of floats): values of strain to multiply
by for each strain state, i. e. stencil for the perturbation along the strain
state direction, e. g. [-0.01, -0.005, 0.005, 0.01]. If a list of lists,
stencils must correspond to each strain state provided.
db_file (str): path to file containing the database credentials.
conventional (bool): flag to convert input structure to conventional structure,
defaults to False.
order (int): order of the tensor expansion to be determined. Defaults to 2 and
currently supports up to 3.
vasp_input_set (VaspInputSet): vasp input set to be used. Defaults to static
set with ionic relaxation parameters set. Take care if replacing this,
default ensures that ionic relaxation is done and that stress is calculated
for each vasp run.
analysis (bool): flag to indicate whether analysis task should be added
and stresses and strains passed to that task
sym_reduce (bool): Whether or not to apply symmetry reductions
tag (str):
copy_vasp_outputs (bool): whether or not to copy previous vasp outputs.
kwargs (keyword arguments): additional kwargs to be passed to get_wf_deformations
Returns:
Workflow
"""
# Convert to conventional if specified
if conventional:
structure = SpacegroupAnalyzer(
structure).get_conventional_standard_structure()
uis_elastic = {
"IBRION": 2,
"NSW": 99,
"ISIF": 2,
"ISTART": 1,
"PREC": "High"
}
vis = vasp_input_set or MPStaticSet(structure,
user_incar_settings=uis_elastic)
strains = []
if strain_states is None:
strain_states = get_default_strain_states(order)
if stencils is None:
stencils = [np.linspace(-0.01, 0.01, 5 +
(order - 2) * 2)] * len(strain_states)
if np.array(stencils).ndim == 1:
stencils = [stencils] * len(strain_states)
for state, stencil in zip(strain_states, stencils):
strains.extend(
[Strain.from_voigt(s * np.array(state)) for s in stencil])
# Remove zero strains
strains = [strain for strain in strains if not (abs(strain) < 1e-10).all()]
# Adding the zero strains for the purpose of calculating at finite pressure or thermal expansion
_strains = [Strain.from_deformation([[1, 0, 0], [0, 1, 0], [0, 0, 1]])]
strains.extend(_strains)
"""
"""
vstrains = [strain.voigt for strain in strains]
if np.linalg.matrix_rank(vstrains) < 6:
# TODO: check for sufficiency of input for nth order
raise ValueError(
"Strain list is insufficient to fit an elastic tensor")
deformations = [s.get_deformation_matrix() for s in strains]
"""
print(strains)
print(deformations)
"""
if sym_reduce:
# Note this casts deformations to a TensorMapping
# with unique deformations as keys to symmops
deformations = symmetry_reduce(deformations, structure)
wf_elastic = get_wf_deformations(structure,
deformations,
tag=tag,
db_file=db_file,
vasp_input_set=vis,
copy_vasp_outputs=copy_vasp_outputs,
**kwargs)
if analysis:
defo_fws_and_tasks = get_fws_and_tasks(
wf_elastic,
fw_name_constraint="deformation",
task_name_constraint="Transmuted")
for idx_fw, idx_t in defo_fws_and_tasks:
defo = \
wf_elastic.fws[idx_fw].tasks[idx_t]['transformation_params'][0][
'deformation']
pass_dict = {
'strain': Deformation(defo).green_lagrange_strain.tolist(),
'stress': '>>output.ionic_steps.-1.stress',
'deformation_matrix': defo
}
if sym_reduce:
pass_dict.update({'symmops': deformations[defo]})
mod_spec_key = "deformation_tasks->{}".format(idx_fw)
pass_task = pass_vasp_result(pass_dict=pass_dict,
mod_spec_key=mod_spec_key)
wf_elastic.fws[idx_fw].tasks.append(pass_task)
fw_analysis = Firework(ElasticTensorToDb(structure=structure,
db_file=db_file,
order=order,
fw_spec_field='tags',
metadata=metadata,
vasp_input_set=vis),
name="Analyze Elastic Data",
spec={"_allow_fizzled_parents": True})
wf_elastic.append_wf(Workflow.from_Firework(fw_analysis),
wf_elastic.leaf_fw_ids)
wf_elastic.name = "{}:{}".format(structure.composition.reduced_formula,
"elastic constants")
return wf_elastic
def make_vasp(jdata, conf_dir):
default_norm_def = 2e-3
default_shear_def = 5e-3
norm_def = jdata.get('norm_deform', default_norm_def)
shear_def = jdata.get('shear_deform', default_shear_def)
conf_path = os.path.abspath(conf_dir)
conf_poscar = os.path.join(conf_path, 'POSCAR')
if 'relax_incar' in jdata.keys():
vasp_str = 'vasp-relax_incar'
else:
kspacing = jdata['vasp_params']['kspacing']
vasp_str = 'vasp-k%.2f' % kspacing
# get equi poscar
equi_path = re.sub('confs', global_equi_name, conf_path)
equi_path = os.path.join(equi_path, vasp_str)
equi_contcar = os.path.join(equi_path, 'CONTCAR')
task_path = re.sub('confs', global_task_name, conf_path)
task_path = os.path.join(task_path, vasp_str)
os.makedirs(task_path, exist_ok=True)
cwd = os.getcwd()
os.chdir(task_path)
if os.path.isfile('POSCAR'):
os.remove('POSCAR')
os.symlink(os.path.relpath(equi_contcar), 'POSCAR')
os.chdir(cwd)
task_poscar = os.path.join(task_path, 'POSCAR')
# stress
equi_outcar = os.path.join(equi_path, 'OUTCAR')
stress = vasp.get_stress(equi_outcar)
np.savetxt(os.path.join(task_path, 'equi.stress.out'), stress)
# gen strcture
ss = Structure.from_file(task_poscar)
# gen defomations
norm_strains = [-norm_def, -0.5 * norm_def, 0.5 * norm_def, norm_def]
shear_strains = [-shear_def, -0.5 * shear_def, 0.5 * shear_def, shear_def]
dfm_ss = DeformedStructureSet(ss,
symmetry=False,
norm_strains=norm_strains,
shear_strains=shear_strains)
n_dfm = len(dfm_ss)
# gen incar
if 'relax_incar' in jdata.keys():
relax_incar_path = jdata['relax_incar']
assert (os.path.exists(relax_incar_path))
relax_incar_path = os.path.abspath(relax_incar_path)
incar = incar_upper(Incar.from_file(relax_incar_path))
if incar.get('ISIF') != 2:
dlog.info("%s:%s setting ISIF to 2" %
(__file__, make_vasp.__name__))
incar['ISIF'] = 2
fc = incar.get_string()
kspacing = incar['KSPACING']
kgamma = incar['KGAMMA']
else:
fp_params = jdata['vasp_params']
ecut = fp_params['ecut']
ediff = fp_params['ediff']
npar = fp_params['npar']
kpar = fp_params['kpar']
kspacing = fp_params['kspacing']
kgamma = fp_params['kgamma']
fc = vasp.make_vasp_relax_incar(ecut,
ediff,
True,
False,
False,
npar=npar,
kpar=kpar,
kspacing=kspacing,
kgamma=kgamma)
with open(os.path.join(task_path, 'INCAR'), 'w') as fp:
fp.write(fc)
# gen potcar
with open(task_poscar, 'r') as fp:
lines = fp.read().split('\n')
ele_list = lines[5].split()
potcar_map = jdata['potcar_map']
potcar_list = []
for ii in ele_list:
assert os.path.exists(os.path.abspath(
potcar_map[ii])), "No POTCAR in the potcar_map of %s" % (ii)
potcar_list.append(os.path.abspath(potcar_map[ii]))
with open(os.path.join(task_path, 'POTCAR'), 'w') as outfile:
for fname in potcar_list:
with open(fname) as infile:
outfile.write(infile.read())
# gen kpoints
fc = vasp.make_kspacing_kpoints(task_poscar, kspacing, kgamma)
with open(os.path.join(task_path, 'KPOINTS'), 'w') as fp:
fp.write(fc)
# gen tasks
cwd = os.getcwd()
for ii in range(n_dfm):
# make dir
dfm_path = os.path.join(task_path, 'dfm-%03d' % ii)
os.makedirs(dfm_path, exist_ok=True)
os.chdir(dfm_path)
for jj in ['POSCAR', 'POTCAR', 'INCAR', 'KPOINTS']:
if os.path.isfile(jj):
os.remove(jj)
# make conf
dfm_ss.deformed_structures[ii].to('POSCAR', 'POSCAR')
# record strain
strain = Strain.from_deformation(dfm_ss.deformations[ii])
np.savetxt('strain.out', strain)
# link incar, potcar, kpoints
os.symlink(os.path.relpath(os.path.join(task_path, 'INCAR')), 'INCAR')
os.symlink(os.path.relpath(os.path.join(task_path, 'POTCAR')),
'POTCAR')
os.symlink(os.path.relpath(os.path.join(task_path, 'KPOINTS')),
'KPOINTS')
#copy cvasp
if ('cvasp' in jdata) and (jdata['cvasp'] == True):
shutil.copyfile(cvasp_file, os.path.join(dfm_path, 'cvasp.py'))
os.chdir(cwd)
