def extract_statical_polarizability(label,rtol,atol,path,input_for_alpha,posinp,code,ref):
# seek for the field convergence
ints=[1e-2,5e-3,1e-3,5e-4,1e-4]
alpha_field=D.Dataset(label=label+'(field)',run_dir=path)
for f in ints:
alpha_field.append_run(id={'f':f},runner=SP.build_alpha_dataset(input=input_for_alpha,\
posinp=posinp,run_dir=path,runner=code,intensity=f))
try:
data_field=alpha_field.seek_convergence(rtol=rtol,atol=atol)
intensity=data_field[0]['f']
except:
print ('Convergence in field not reached')
intensity=ints[-1]
# seek for the rmult convergence
rmult_fine=input_for_alpha['dft']['rmult'][1]
rmult_list=map(float,range(int(input_for_alpha['dft']['rmult'][0]),11))
alpha_rmult=D.Dataset(label=label+'(domain)',run_dir=path)
for rm in rmult_list:
input_for_alpha.set_rmult(coarse=rm,fine=rmult_fine)
alpha_rmult.append_run(id={'f':intensity,'rmult':rm},\
runner=SP.build_alpha_dataset(input=input_for_alpha,posinp=posinp,run_dir=path,runner=code,intensity=intensity))
try:
import numpy as np
data_final=alpha_rmult.seek_convergence(rtol=rtol,atol=atol)
AuToA = 0.5291772085**3
alpha_ref_ii = np.array(ref)/AuToA
eps = 100.0 * (data_final[1]-alpha_ref_ii)/alpha_ref_ii
print ('Relative difference in %',eps.tolist())
except LookupError as e:
print ('Convergence in domain not reached',e)
data_final=None
return {'alpha_convergence': data_final, 'dataset_field': alpha_field, 'dataset_rmult': alpha_rmult}
def extract_statical_polarizability_linearity(label,rtol,atol,path,input_for_alpha,posinp,code,ref):
#ints=[1e-2,5e-3,1e-3,5e-4,1e-4]
ints= [1e-3,2e-3,3e-3,4e-3,5e-3] #for comparison with the MWL plots
results = {}
results['alpha_values'] = {}
rmult_fine=input_for_alpha['dft']['rmult'][1]
rmult_list=map(float,range(int(input_for_alpha['dft']['rmult'][0]),15))
for intensity in ints:
# seek for the rmult convergence
alpha_rmult=D.Dataset(label=label+'(domain)',run_dir=path)
for rm in rmult_list:
input_for_alpha.set_rmult(coarse=rm,fine=rmult_fine)
alpha_rmult.append_run(id={'f':intensity,'rmult':rm},\
runner=SP.build_alpha_dataset(input=input_for_alpha,posinp=posinp,run_dir=path,runner=code,intensity=intensity))
try:
import numpy as np
data_final=alpha_rmult.seek_convergence(rtol=rtol,atol=atol)
AuToA = 0.5291772085**3
alpha_ref_ii = np.array(ref)/AuToA
eps = 100.0 * (data_final[1]-alpha_ref_ii)/alpha_ref_ii
print ('Relative difference in %',eps.tolist())
except LookupError as e:
print ('Convergence in domain not reached',e)
data_final=None
results['alpha_values'][intensity] = {'alpha_convergence': data_final, 'dataset_rmult': alpha_rmult}
return results
def find_gs_domain(label,rtol,atol,path,input,posinp,code):
"""
Use the seek_convergence method of Dataset to perform a convergence procedure on
the rmult value for a gs computation.
"""
crmult=input['dft']['rmult'][0]
rmult_fine=input['dft']['rmult'][1]
rmult_list=map(float,range(int(crmult),11))
seek_for_rmult = D.Dataset(label=label+'(GS)',run_dir=path,posinp=posinp)
for rm in rmult_list:
input.set_rmult(coarse=rm,fine=rmult_fine)
seek_for_rmult.append_run(id={'rmult':rm},runner=code,input=input)
input_gs,log_gs=get_converged_input_energy(seek_for_rmult,rtol,atol)
return {'input_gs':input_gs, 'dataset_gs': seek_for_rmult,'log_gs':log_gs}
def build_alpha_dataset(**kwargs):
"""
Create the dataset and append the runs needed to compute the statical polarizability
for a specific choice of the input parameters. Set also a postprocessing function
to extract the value of alpha. The postprocessing function is set to the :py:func:`eval_alpha` function
Args:
kwargs['run_dir'] : th run_dir
kwargs['intensity'] : the intensity of the field
kwargs['input'] : the input file
kwargs['posinp'] : the posinp
kwargs['runner'] : the instance of SystemCalculator
"""
from BigDFT import InputActions as A, Datasets as D
lbl = 'alpha_' + str(kwargs['intensity'])
study = D.Dataset(label=lbl, **kwargs)
study.set_postprocessing_function(eval_alpha)
#study.set_postprocessing_function(eval_alpha_from_energy)
f = kwargs['intensity']
inp = kwargs['input']
hgrids = inp['dft']['hgrids']
gnrm_cv = inp['dft']['gnrm_cv']
for ind, sign in enumerate(['+', '-']):
for idir, coord in enumerate(['x', 'y', 'z']):
el = np.zeros(3)
el[idir] = (1 - 2 * ind) * f
inp.apply_electric_field(el.tolist())
idd = {
'hgrids': hgrids,
'gnrm_cv': gnrm_cv,
'rmult': inp['dft']['rmult'][0],
'dir': coord,
'sign': sign,
'F': f
}
study.append_run(process_id_default_values(idd),
runner=kwargs['runner'],
input=inp)
return study
def build_alpha_dataset(**kwargs):
"""
Create the dataset and append the runs needed to compute the statical polarizability
for a specific choice of the input parameters. Set also a postprocessing function
to extract the value of alpha.
Args:
kwargs['run_dir'] : th run_dir
kwargs['intensity'] : the intensity of the field
kwargs['input'] : the input file
kwargs['posinp'] : the posinp
kwargs['ppf'] : the postprocessing function
kwargs['runner'] : the instance of SystemCalculator
"""
lbl = 'alpha_' + str(kwargs['intensity'])
study = D.Dataset(label=lbl,
run_dir=kwargs['run_dir'],
intensity=kwargs['intensity'],
posinp=kwargs['posinp'])
study.set_postprocessing_function(kwargs['ppf'])
f = kwargs['intensity']
inp = kwargs['input']
for ind, sign in enumerate(['+', '-']):
for idir, coord in enumerate(['x', 'y', 'z']):
el = np.zeros(3)
el[idir] = (1 - 2 * ind) * f
inp.apply_electric_field(el.tolist())
idd = {
'rmult': inp['dft']['rmult'][0],
'dir': coord,
'sign': sign,
'F': f
}
study.append_run(id=idd, runner=kwargs['runner'], input=inp)
return study
def get_converged_input_energy(dataset,rtol,atol):
data=dataset.seek_convergence(atol=atol,rtol=rtol,attribute='energy')
return dataset.runs[dataset.names.index(D.name_from_id(data[0]))]['input'],data[1]
def nsp_workflow(alpha_conv=1.0e-2,wf_convergence=1.0e-6,hgrids=0.3,\
rmult_fine=9.0,term_verb=True,data_folder='Data',**kwargs):
"""
Perform the complete nsp workflow to compute the statical polarizability
of a molecule in a specific study(xc+psp)
Args:
kwargs['molecule'] : the molecule type
kwargs['study'] : the tuple (xc,psp)
kwargs['code'] : the instance of SystemCalculator
"""
molecule = kwargs['molecule']
study = kwargs['study']
code = kwargs['code']
code.update_global_options(verbose=term_verb)
results = {}
if not os.path.isdir(data_folder): os.mkdir(data_folder)
os.chdir(data_folder)
if not os.path.isdir(molecule): os.mkdir(molecule)
os.chdir(molecule)
path = study[0] + '-' + study[1]
if not os.path.isdir(path): os.mkdir(path)
print 'Compute alpha for : ', molecule, study[0], study[1]
posinp = Molecules.Molecule(molecule)
#rel tol for the gs convergence (using the total energy as control quantity)
gs_rtol = 10 * wf_convergence
inp = I.Inputfile()
inp.set_hgrid(hgrids)
set_xc[study](inp, molecule)
inp.set_wavefunction_convergence(wf_convergence)
if term_verb: print 'Seek for gs convergence'
rmult_coarse = [1.0 * i for i in range(3, 12)]
data = []
for r in rmult_coarse:
gs_study = D.Dataset(label=molecule + '_GS',
run_dir=path,
posinp=posinp)
gs_study.set_postprocessing_function(SP.get_energy)
inp.set_rmult(coarse=r, fine=rmult_fine)
idd = {'rmult': r}
gs_study.append_run(id=idd, runner=code, input=inp)
data.append(gs_study)
results['gs_conv'] = SP.seek_convergence(rt=gs_rtol,term_verb=term_verb,\
label='rmult',values=rmult_coarse,data=data)
if term_verb: print 'Seek for alpha convergence'
# field intensity convergence
gs_conv = results['gs_conv']['converged_value']
inp.set_rmult(coarse=gs_conv, fine=rmult_fine)
if term_verb: print 'Convergence on the field intensity'
results['field_conv']=SP.perform_field_convergence(term_verb=term_verb,rt=alpha_conv,\
run_dir=path,input=inp,runner=code,posinp=posinp,ppf=SP.eval_alpha)
f = results['field_conv']['converged_value']
# rmult convergence
rmult_list = SP.build_rmult_list([gs_conv, rmult_fine])
if term_verb: print 'Convergence on rmult'
results['rmult_conv']=SP.perform_rmult_convergence(term_verb=term_verb,\
rt=alpha_conv,run_dir=path,intensity=f,rmult=rmult_list,input=inp,\
runner=code,posinp=posinp,ppf=SP.eval_alpha)
os.chdir('../../')
return results
def single_study_workflow(alpha_conv=1.0e-2,
wf_convergence=1.0e-6,
hgrids=0.3,
rmult_fine=9.0,
term_verb=True,
**kwargs):
"""
Perform the complete workflow to compute the statical polarizability
of a specific study(molecule+xc+psp)
Args:
kwargs['molecule'] : the molecule type
kwargs['xc'] : the xc functional
kwargs['psp'] : the pseudopotential
"""
molecule = kwargs['molecule']
xc = kwargs['xc']
psp = kwargs['psp']
study = {}
if not os.path.isdir(molecule): os.mkdir(molecule)
os.chdir(molecule)
path = xc + '-' + psp
if not os.path.isdir(path): os.mkdir(path)
print ''
print 'Compute alpha for : ', molecule, xc, psp
posinp = Molecules.Molecule(molecule)
gs_rtol = 10 * wf_convergence #rel tol for the gs convergence (using the total energy as control quantity)
inp = I.Inputfile()
inp.set_hgrid(hgrids)
inp.set_xc(xc.upper())
inp.set_wavefunction_convergence(wf_convergence)
#gs convergence
rmult_coarse = [1.0 * i for i in range(3, 12)]
data = []
code = C.SystemCalculator(skip=True, verbose=False)
for r in rmult_coarse:
gs_study = D.Dataset(label=molecule + '_GS',
run_dir=path,
posinp=posinp)
gs_study.set_postprocessing_function(SP.get_energy)
inp.set_rmult(coarse=r, fine=rmult_fine)
idd = {'rmult': r}
gs_study.append_run(id=idd, runner=code, input=inp)
data.append(gs_study)
if term_verb: print 'Seek for gs convergence'
study['gs_conv'] = SP.seek_convergence(rt=gs_rtol,
term_verb=term_verb,
label='rmult',
values=rmult_coarse,
data=data)
if term_verb: print 'Seek for alpha convergence'
# alpha field intensity convergence
conv_val = study['gs_conv']['converged_value']
gslog = 'log-' + data[rmult_coarse.index(conv_val)].names[0] + '.yaml'
gs = lf.Logfile(path + os.sep + gslog)
inp.set_rmult(gs.log['dft']['rmult'])
if term_verb: 'Convergence on the field intensity'
study['field_conv'] = SP.perform_field_convergence(term_verb=term_verb,
rt=alpha_conv,
run_dir=path,
input=inp,
runner=code,
posinp=posinp,
ppf=SP.eval_alpha)
f = study['field_conv']['converged_value']
# alpha rmult convergence
rmult_list = SP.build_rmult_list(gs)
if term_verb: 'Convergence on rmult'
study['rmult_conv'] = SP.perform_rmult_convergence(term_verb=term_verb,
rt=alpha_conv,
run_dir=path,
intensity=f,
rmult=rmult_list,
input=inp,
runner=code,
posinp=posinp,
ppf=SP.eval_alpha)
os.chdir('../')
return study