def test_expand(self):
self.maxDiff = None
spec = get_spec('GW')
tests = SingleAbinitGWWork(structure, spec).convs
tests_out = {'nscf_nbands': {'test_range': (40,),
'control': 'gap', 'method': 'set_bands', 'level': 'nscf'},
'ecut': {'test_range': (52, 48, 44),
'control': 'e_ks_max', 'method': 'direct', 'level': 'scf'},
'ecuteps': {'test_range': (4, 8, 12, 16, 20),
'control': 'gap', 'method': 'direct', 'level': 'sigma'}}
self.assertEqual(expand(tests, 1), tests_out)
spec.data['code'] = 'VASP'
spec.update_code_interface()
tests = GWG0W0VaspInputSet(structure, spec).convs
tests_out = {'ENCUTGW': {'test_range': (200, 400, 600, 800), 'control': 'gap', 'method': 'incar_settings'}}
self.assertEqual(expand(tests, 1), tests_out)
def test_expand(self):
self.maxDiff = None
spec = get_spec('GW')
tests = SingleAbinitGWWork(structure, spec).convs
tests_out = {
'nscf_nbands': {
'test_range': (40, ),
'control': 'gap',
'method': 'set_bands',
'level': 'nscf'
},
'ecut': {
'test_range': (50, 48, 46, 44),
'control': 'e_ks_max',
'method': 'direct',
'level': 'scf'
},
'ecuteps': {
'test_range': (4, 8, 12, 16, 20),
'control': 'gap',
'method': 'direct',
'level': 'sigma'
}
}
self.assertEqual(expand(tests, 1), tests_out)
spec.data['code'] = 'VASP'
spec.update_code_interface()
tests = GWG0W0VaspInputSet(structure, spec).convs
tests_out = {
'ENCUTGW': {
'test_range': (200, 400, 600, 800),
'control': 'gap',
'method': 'incar_settings'
}
}
self.assertEqual(expand(tests, 1), tests_out)
def excecute_flow(self, structure, spec_data):
"""
excecute spec prepare input/jobfiles or submit to fw for a given structure
for vasp the different jobs are created into a flow
todo this should actually create and excecute a VaspGWWorkFlow(GWWorkflow)
"""
### general part for the base class
grid = 0
all_done = False
converged = is_converged(False, structure)
try:
grid = read_grid_from_file(s_name(structure)+".full_res")['grid']
all_done = read_grid_from_file(s_name(structure)+".full_res")['all_done']
except (IOError, OSError):
pass
if all_done:
print('| all is done for this material')
return
### specific part
if spec_data['mode'] == 'fw':
fw_work_flow = VaspGWFWWorkFlow()
else:
fw_work_flow = []
if spec_data['test'] or spec_data['converge']:
if spec_data['test']:
tests_prep = GWscDFTPrepVaspInputSet(structure, spec_data).tests
tests_prep.update(GWDFTDiagVaspInputSet(structure, spec_data).tests)
elif spec_data['converge'] and converged:
tests_prep = self.get_conv_res_test(spec_data, structure)['tests_prep']
else:
tests_prep = GWscDFTPrepVaspInputSet(structure, spec_data).convs
tests_prep.update(GWDFTDiagVaspInputSet(structure, spec_data).convs)
if grid > 0:
tests_prep = expand(tests=tests_prep, level=grid)
print(tests_prep)
for test_prep in tests_prep:
print('setting up test for: ' + test_prep)
for value_prep in tests_prep[test_prep]['test_range']:
print("**" + str(value_prep) + "**")
option = {'test_prep': test_prep, 'value_prep': value_prep}
self.create_job(spec_data, structure, 'prep', fw_work_flow, converged, option)
for job in spec_data['jobs'][1:]:
if job == 'G0W0':
if spec_data['test']:
tests = GWG0W0VaspInputSet(structure, spec_data).tests
elif spec_data['converge'] and converged:
tests = self.get_conv_res_test(spec_data, structure)['tests']
else:
tests = GWG0W0VaspInputSet(structure, spec_data).convs
if grid > 0:
tests = expand(tests=tests, level=grid)
print(tests)
if job in ['GW0', 'scGW0']:
input_set = GWG0W0VaspInputSet(structure, spec_data)
input_set.gw0_on()
if spec_data['test']:
tests = input_set.tests
else:
tests = input_set.tests
for test in tests:
print(' setting up test for: ' + test)
for value in tests[test]['test_range']:
print(" **" + str(value) + "**")
option.update({'test': test, 'value': value})
self.create_job(spec_data, structure, job, fw_work_flow, converged, option)
def create(self):
"""
create single abinit G0W0 flow
"""
manager = 'slurm' if 'ceci' in self.spec['mode'] else 'shell'
# an AbiStructure object has an overwritten version of get_sorted_structure that sorts according to Z
# this could also be pulled into the constructor of Abistructure
#abi_structure = self.structure.get_sorted_structure()
from abipy import abilab
item = copy.copy(self.structure.item)
self.structure.__class__ = abilab.Structure
self.structure = self.structure.get_sorted_structure_z()
self.structure.item = item
abi_structure = self.structure
manager = TaskManager.from_user_config()
# Initialize the flow.
flow = Flow(self.work_dir, manager, pickle_protocol=0)
# flow = Flow(self.work_dir, manager)
# kpoint grid defined over density 40 > ~ 3 3 3
if self.spec['converge'] and not self.all_converged:
# (2x2x2) gamma centered mesh for the convergence test on nbands and ecuteps
# if kp_in is present in the specs a kp_in X kp_in x kp_in mesh is used for the convergence studie
if 'kp_in' in self.spec.keys():
if self.spec['kp_in'] > 9:
print('WARNING:\nkp_in should be < 10 to generate an n x n x n mesh\nfor larger values a grid with '
'density kp_in will be generated')
scf_kppa = self.spec['kp_in']
else:
scf_kppa = 2
else:
# use the specified density for the final calculation with the converged nbands and ecuteps of other
# stand alone calculations
scf_kppa = self.spec['kp_grid_dens']
gamma = True
# 'standard' parameters for stand alone calculation
nb = self.get_bands(self.structure)
nscf_nband = [10 * nb]
nksmall = None
ecuteps = [8]
ecutsigx = 44
extra_abivars = dict(
paral_kgb=1,
inclvkb=2,
ecut=44,
pawecutdg=88,
gwmem='10',
getden=-1,
istwfk="*1",
timopt=-1,
nbdbuf=8
)
# read user defined extra abivars from file 'extra_abivars' should be dictionary
extra_abivars.update(read_extra_abivars())
#self.bands_fac = 0.5 if 'gwcomp' in extra_abivars.keys() else 1
#self.convs['nscf_nbands']['test_range'] = tuple([self.bands_fac*x for x in self.convs['nscf_nbands']['test_range']])
response_models = ['godby']
if 'ppmodel' in extra_abivars.keys():
response_models = [extra_abivars.pop('ppmodel')]
if self.option is not None:
for k in self.option.keys():
if k in ['ecuteps', 'nscf_nbands']:
pass
else:
extra_abivars.update({k: self.option[k]})
if k == 'ecut':
extra_abivars.update({'pawecutdg': self.option[k]*2})
try:
grid = read_grid_from_file(s_name(self.structure)+".full_res")['grid']
all_done = read_grid_from_file(s_name(self.structure)+".full_res")['all_done']
workdir = os.path.join(s_name(self.structure), 'w'+str(grid))
except (IOError, OSError):
grid = 0
all_done = False
workdir = None
if not all_done:
if (self.spec['test'] or self.spec['converge']) and not self.all_converged:
if self.spec['test']:
print('| setting test calculation')
tests = SingleAbinitGWWork(self.structure, self.spec).tests
response_models = []
else:
if grid == 0:
print('| setting convergence calculations for grid 0')
#tests = SingleAbinitGWWorkFlow(self.structure, self.spec).convs
tests = self.convs
else:
print('| extending grid')
#tests = expand(SingleAbinitGWWorkFlow(self.structure, self.spec).convs, grid)
tests = expand(self.convs, grid)
ecuteps = []
nscf_nband = []
for test in tests:
if tests[test]['level'] == 'scf':
if self.option is None:
extra_abivars.update({test + '_s': tests[test]['test_range']})
elif test in self.option:
extra_abivars.update({test: self.option[test]})
else:
extra_abivars.update({test + '_s': tests[test]['test_range']})
else:
for value in tests[test]['test_range']:
if test == 'nscf_nbands':
nscf_nband.append(value * self.get_bands(self.structure))
#scr_nband takes nscf_nbands if not specified
#sigma_nband takes scr_nbands if not specified
if test == 'ecuteps':
ecuteps.append(value)
if test == 'response_model':
response_models.append(value)
elif self.all_converged:
print('| setting up for testing the converged values at the high kp grid ')
# add a bandstructure and dos calculation
nksmall = 30
# in this case a convergence study has already been performed.
# The resulting parameters are passed as option
ecuteps = [self.option['ecuteps'], self.option['ecuteps'] + self.convs['ecuteps']['test_range'][1] -
self.convs['ecuteps']['test_range'][0]]
nscf_nband = [self.option['nscf_nbands'], self.option['nscf_nbands'] + self.convs['nscf_nbands'][
'test_range'][1] - self.convs['nscf_nbands']['test_range'][0]]
# for option in self.option:
# if option not in ['ecuteps', 'nscf_nband']:
# extra_abivars.update({option + '_s': self.option[option]})
else:
print('| all is done for this material')
return
logger.info('ecuteps : ', ecuteps)
logger.info('extra : ', extra_abivars)
logger.info('nscf_nb : ', nscf_nband)
work = g0w0_extended_work(abi_structure, self.pseudo_table, scf_kppa, nscf_nband, ecuteps, ecutsigx,
accuracy="normal", spin_mode="unpolarized", smearing=None, response_models=response_models,
charge=0.0, sigma_nband=None, scr_nband=None, gamma=gamma, nksmall=nksmall, **extra_abivars)
flow.register_work(work, workdir=workdir)
return flow.allocate()
def excecute_flow(self, structure, spec_data):
"""
excecute spec prepare input/jobfiles or submit to fw for a given structure
for vasp the different jobs are created into a flow
todo this should actually create and excecute a VaspGWWorkFlow(GWWorkflow)
"""
### general part for the base class
grid = 0
all_done = False
converged = is_converged(False, structure)
try:
grid = read_grid_from_file(s_name(structure) + ".full_res")['grid']
all_done = read_grid_from_file(s_name(structure) +
".full_res")['all_done']
except (IOError, OSError):
pass
if all_done:
print('| all is done for this material')
return
### specific part
if spec_data['mode'] == 'fw':
fw_work_flow = VaspGWFWWorkFlow()
else:
fw_work_flow = []
if spec_data['test'] or spec_data['converge']:
if spec_data['test']:
tests_prep = GWscDFTPrepVaspInputSet(structure,
spec_data).tests
tests_prep.update(
GWDFTDiagVaspInputSet(structure, spec_data).tests)
elif spec_data['converge'] and converged:
tests_prep = self.get_conv_res_test(spec_data,
structure)['tests_prep']
else:
tests_prep = GWscDFTPrepVaspInputSet(structure,
spec_data).convs
tests_prep.update(
GWDFTDiagVaspInputSet(structure, spec_data).convs)
if grid > 0:
tests_prep = expand(tests=tests_prep, level=grid)
print(tests_prep)
for test_prep in tests_prep:
print('setting up test for: ' + test_prep)
for value_prep in tests_prep[test_prep]['test_range']:
print("**" + str(value_prep) + "**")
option = {'test_prep': test_prep, 'value_prep': value_prep}
self.create_job(spec_data, structure, 'prep', fw_work_flow,
converged, option)
for job in spec_data['jobs'][1:]:
if job == 'G0W0':
if spec_data['test']:
tests = GWG0W0VaspInputSet(
structure, spec_data).tests
elif spec_data['converge'] and converged:
tests = self.get_conv_res_test(
spec_data, structure)['tests']
else:
tests = GWG0W0VaspInputSet(
structure, spec_data).convs
if grid > 0:
tests = expand(tests=tests, level=grid)
print(tests)
if job in ['GW0', 'scGW0']:
input_set = GWG0W0VaspInputSet(
structure, spec_data)
input_set.gw0_on()
if spec_data['test']:
tests = input_set.tests
else:
tests = input_set.tests
for test in tests:
print(' setting up test for: ' + test)
for value in tests[test]['test_range']:
print(" **" + str(value) + "**")
option.update({'test': test, 'value': value})
self.create_job(spec_data, structure, job,
fw_work_flow, converged,
option)
def create(self):
"""
create single abinit G0W0 flow
"""
manager = 'slurm' if 'ceci' in self.spec['mode'] else 'shell'
# an AbiStructure object has an overwritten version of get_sorted_structure that sorts according to Z
# this could also be pulled into the constructor of Abistructure
#abi_structure = self.structure.get_sorted_structure()
from abipy import abilab
item = copy.copy(self.structure.item)
self.structure.__class__ = abilab.Structure
self.structure = self.structure.get_sorted_structure_z()
self.structure.item = item
abi_structure = self.structure
manager = TaskManager.from_user_config()
# Initialize the flow.
flow = Flow(self.work_dir, manager, pickle_protocol=0)
# flow = Flow(self.work_dir, manager)
# kpoint grid defined over density 40 > ~ 3 3 3
if self.spec['converge'] and not self.all_converged:
# (2x2x2) gamma centered mesh for the convergence test on nbands and ecuteps
# if kp_in is present in the specs a kp_in X kp_in x kp_in mesh is used for the convergence studie
if 'kp_in' in self.spec.keys():
if self.spec['kp_in'] > 9:
print(
'WARNING:\nkp_in should be < 10 to generate an n x n x n mesh\nfor larger values a grid with '
'density kp_in will be generated')
scf_kppa = self.spec['kp_in']
else:
scf_kppa = 2
else:
# use the specified density for the final calculation with the converged nbands and ecuteps of other
# stand alone calculations
scf_kppa = self.spec['kp_grid_dens']
gamma = True
# 'standard' parameters for stand alone calculation
scf_nband = self.get_bands(self.structure)
nscf_nband = [10 * scf_nband]
nksmall = None
ecuteps = [8]
ecutsigx = 44
extra_abivars = dict(paral_kgb=1,
inclvkb=2,
ecut=44,
pawecutdg=88,
gwmem='10',
getden=-1,
istwfk="*1",
timopt=-1,
nbdbuf=8,
prtsuscep=0)
# read user defined extra abivars from file 'extra_abivars' should be dictionary
extra_abivars.update(read_extra_abivars())
#self.bands_fac = 0.5 if 'gwcomp' in extra_abivars.keys() else 1
#self.convs['nscf_nbands']['test_range'] = tuple([self.bands_fac*x for x in self.convs['nscf_nbands']['test_range']])
response_models = ['godby']
if 'ppmodel' in extra_abivars.keys():
response_models = [extra_abivars.pop('ppmodel')]
if self.option is not None:
for k in self.option.keys():
if k in ['ecuteps', 'nscf_nbands']:
pass
else:
extra_abivars.update({k: self.option[k]})
if k == 'ecut':
extra_abivars.update({'pawecutdg': self.option[k] * 2})
try:
grid = read_grid_from_file(s_name(self.structure) +
".full_res")['grid']
all_done = read_grid_from_file(
s_name(self.structure) + ".full_res")['all_done']
workdir = os.path.join(s_name(self.structure), 'w' + str(grid))
except (IOError, OSError):
grid = 0
all_done = False
workdir = None
if not all_done:
if (self.spec['test']
or self.spec['converge']) and not self.all_converged:
if self.spec['test']:
print('| setting test calculation')
tests = SingleAbinitGWWork(self.structure, self.spec).tests
response_models = []
else:
if grid == 0:
print('| setting convergence calculations for grid 0')
#tests = SingleAbinitGWWorkFlow(self.structure, self.spec).convs
tests = self.convs
else:
print('| extending grid')
#tests = expand(SingleAbinitGWWorkFlow(self.structure, self.spec).convs, grid)
tests = expand(self.convs, grid)
ecuteps = []
nscf_nband = []
for test in tests:
if tests[test]['level'] == 'scf':
if self.option is None:
extra_abivars.update(
{test + '_s': tests[test]['test_range']})
elif test in self.option:
extra_abivars.update({test: self.option[test]})
else:
extra_abivars.update(
{test + '_s': tests[test]['test_range']})
else:
for value in tests[test]['test_range']:
if test == 'nscf_nbands':
nscf_nband.append(
value * self.get_bands(self.structure))
#scr_nband takes nscf_nbands if not specified
#sigma_nband takes scr_nbands if not specified
if test == 'ecuteps':
ecuteps.append(value)
if test == 'response_model':
response_models.append(value)
elif self.all_converged:
print(
'| setting up for testing the converged values at the high kp grid '
)
# add a bandstructure and dos calculation
if os.path.isfile('bands'):
nksmall = -30
#negative value > only bandstructure
else:
nksmall = 30
# in this case a convergence study has already been performed.
# The resulting parameters are passed as option
ecuteps = [
self.option['ecuteps'], self.option['ecuteps'] +
self.convs['ecuteps']['test_range'][1] -
self.convs['ecuteps']['test_range'][0]
]
nscf_nband = [
self.option['nscf_nbands'], self.option['nscf_nbands'] +
self.convs['nscf_nbands']['test_range'][1] -
self.convs['nscf_nbands']['test_range'][0]
]
# for option in self.option:
# if option not in ['ecuteps', 'nscf_nband']:
# extra_abivars.update({option + '_s': self.option[option]})
else:
print('| all is done for this material')
return
logger.info('ecuteps : ', ecuteps)
logger.info('extra : ', extra_abivars)
logger.info('nscf_nb : ', nscf_nband)
work = g0w0_extended_work(abi_structure,
self.pseudo_table,
scf_kppa,
nscf_nband,
ecuteps,
ecutsigx,
scf_nband,
accuracy="normal",
spin_mode="unpolarized",
smearing=None,
response_models=response_models,
charge=0.0,
sigma_nband=None,
scr_nband=None,
gamma=gamma,
nksmall=nksmall,
**extra_abivars)
flow.register_work(work, workdir=workdir)
return flow.allocate()
