def main():
data = make_data('etas-Ds.data')
models = make_models()
prior = make_prior(8)
fitter = CorrFitter(models=make_models())
p0 = None
for N in [1, 2, 3, 4]:
print(30 * '=', 'nterm =', N)
prior = make_prior(N)
fit = fitter.chained_lsqfit(data=data, prior=prior, p0=p0)
p0 = fit.pmean
print_results(fit, prior, data)
if DISPLAYPLOTS:
fitter.display_plots()
# polish fit
print('--- polish fit')
fit = fitter.lsqfit(data=data, prior=fit.p, svdcut=1e-4)
print_results(fit, prior, data)
if DISPLAYPLOTS:
fitter.display_plots()
# fit with structured models
print('--- refit with structured models')
models = [models[:2]] + models[2:]
fitter = CorrFitter(models=make_models())
fit = fitter.chained_lsqfit(data=data, prior=prior, p0=p0)
# polish
print('--- polish fit')
fit = fitter.lsqfit(data=data, prior=fit.p, svdcut=1e-4)
print_results(fit, prior, data)
def main():
data, basis = make_data('etab.data')
fitter = CorrFitter(models=make_models(basis))
p0 = None
for N in range(1, 10):
print(30 * '=', 'nterm =', N)
prior = make_prior(N, basis)
fit = fitter.lsqfit(data=data, prior=prior, p0=p0, svdcut=0.0004)
p0 = fit.pmean
print_results(fit, basis, prior, data)
if DISPLAYPLOTS:
fitter.display_plots()
def main():
data = make_data('etas-Ds.data')
models = make_models()
prior = make_prior(8)
fitter = CorrFitter(models=make_models(), ratio=False) # 1
p0 = None
for N in [1, 2]: # 2
print(30 * '=', 'nterm =', N)
prior = make_prior(8) # 3
fit = fitter.lsqfit(data=data, prior=prior, p0=p0, nterm=(N, N)) # 4
p0 = fit.pmean
print_results(fit, prior, data)
if DISPLAYPLOTS:
fitter.display_plots()
test_fit(fitter, 'etas-Ds.data')
except KeyError:
print "Could not use initial point definitions"
fit = fitter.lsqfit(data=data,prior=prior,svdcut=df.svdcut)
else:
fit = fitter.lsqfit(data=data,prior=prior,svdcut=df.svdcut)
#bs_avg = make_bootstrap(fitter,dset,df.mdp.n_bs)
print_fit(fit,prior)
print_error_budget(fit)
#save_data(mdp.output_path +'/'+ mdp.fit_fname,fit,data)
save_data('./test.fit.out',fit,data)
save_prior_from_fit(df.define_prior,df.define_model,fit,"test.prior.out",
round_e=2,round_a=1,preserve_e_widths=True,preserve_a_widths=True)
if df.do_plot:
if df.do_default_plot:
fitter.display_plots()
plot_corr_double_log(models,data,fit,**df.fitargs)
plot_corr_normalized(models,data,fit,**df.fitargs)
plt.show()
pass #do_2pt
if df.do_3pt:
## -- test routines
if df.do_symm == "s":
if df.do_irrep == "8":
classList = [1,2,3,5,6]
elif df.do_irrep == "8'":
classList = [4,7]
elif df.do_irrep == "16":
classList = [2,3,4,6]
elif df.do_sym == "m":
