def create_fortran_model(self, model_dir='__fortress_tmp', **kwargs):
from fortress import make_smc
from .translate import smc, write_prior_file
smc_file = smc(self)
model_linear = self.compile_model()
other_files = {'data.txt': model_linear.yy,
'prior.txt': 'prior.txt'}
make_smc(smc_file, model_dir, other_files=other_files, **kwargs)
write_prior_file(model_linear.prior, model_dir)
def create_fortran_model(self):
if self.smc_file is None:
smc_file = smc(self.model)
else:
smc_file = self.smc_file
model_linear = self.model.compile_model()
other_files = {'data.txt': model_linear.yy,
'prior.txt': 'prior.txt'}
make_smc(smc_file, other_files=other_files,
output_directory=self.fortran_directory)
write_prior_file(model_linear.prior, self.fortran_directory)
def make_fortran_model(model, **kwargs):
t0 = kwargs.pop('t0',0)
from fortress import make_smc
model_file = smc(model, t0=t0)
modelc = model.compile_model()
r = make_smc(model_file, other_files={'data.txt': modelc.yy,
'prior.txt': 'prior.txt'}, **kwargs)
output_dir = kwargs.pop('output_directory','_fortress_tmp')
write_prior_file(modelc.prior, output_dir)
return r
def make_fortran_model(model, **kwargs):
t0 = kwargs.pop("t0", 0)
from fortress import make_smc
model_file = smc(model, t0=t0)
modelc = model.compile_model()
r = make_smc(
model_file,
other_files={"data.txt": modelc.yy, "prior.txt": "prior.txt"},
**kwargs
)
output_dir = kwargs.pop("output_directory", "_fortress_tmp")
write_prior_file(modelc.prior, output_dir)
return r
modelfile = open('ms_minnpr.f90', 'r').read()
modelfile = modelfile.format(data=dat,
prior=args.prior,
m=args.m,
v=args.v,
p=swz.p,
cons=swz.cons,
nA=6,
nF=48,
mu_prior=mu_prior)
lib_path = '/home/eherbst/anaconda3/lib'
inc_path = '/home/eherbst/anaconda3/include'
smc = make_smc(modelfile,
other_files=other_files,
output_directory=args.output_dir,
lib_path=lib_path,
inc_path=inc_path)
elif args.prior == 'rfb':
print('You`ve selected the RFB prior')
lam = [1.0, 1.2, 1.0, 1.0, 1.0, 1.0]
rfb = MinnesotaPrior([], lam, presample_moments=premom, p=5)
rfb.ny = 3
other_files = {'data.txt': dat, 'qmean.txt': qmean, 'qvar.txt': qvar}
other_parameters = {
'lam{:d}'.format(d + 1): '{}_wp'.format(val)
for d, val in enumerate(lam)
}
varfile = open('svar.f90', 'r').read()
varfile = varfile.format(assign_para='\n'.join(A0str + Apstr), **vars(ei))
other_files = {
'data.txt': data['1993':'2007-06'][model['yy']].values,
'proxy.txt': proxy.values,
'priordraws.txt': priorsim[:args.nsim].T,
'phistar.txt': phihatT.flatten(order='F'),
'iw_Psi.txt': S,
'Omega_inv.txt': np.linalg.inv(omega)
}
output_dir = '_fortress_' + args.model
smc = make_smc(varfile,
other_files=other_files,
output_directory=output_dir)
if 'fin' in args.model:
print(
"For financial shock, you need to impose the sign restriction manually in the fortran code!"
)
smc.run(npart=args.nsim,
nblocks=25,
nproc=args.nproc,
bend=2.7,
conditional_covariance=True,
initial_particles=output_dir + '/priordraws.txt',
output_file='%s.json' % args.model)