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":