results['pointlike'] = dict() results['pointlike']['mc'] = sourcedict(roi,which,errors=False) roi.fit(use_gradient=False, fit_bg_first = True) results['pointlike']['fit'] = sourcedict(roi,which) roi.print_summary(galactic=True) print roi roi.plot_counts_map(filename='counts_map.pdf') roi.print_summary(galactic=True) print roi s=roi.plot_sed(which=which,filename='sed_pointlike.pdf', use_ergs=True) pointlike_sed_to_yaml(s,'sed_pointlike.yaml') roi.toXML('results_pointlike.xml') state.restore() gtlike = Gtlike(roi, savedir='gtlike_savedir', enable_edisp=True) like = gtlike.like results['gtlike'] = dict() results['gtlike']['mc'] = sourcedict(like,name,errors=False) like.fit(covar=True) results['gtlike']['fit'] = sourcedict(like,name) if args.debug: # in debug mode, there is no background model,
roi.plot_counts_map(filename='counts_before.pdf') # print out the ROI roi.print_summary(galactic=True) print roi roi.fit(fit_bg_first=True) roi.print_summary(galactic=True) print roi # Get out the paramters for Cas A and save them to a file results['pointlike'] = sourcedict(roi, name) save() # Plot the SED pointlike_sed_to_yaml(roi.plot_sed(which=name, filename='sed_pointlike.pdf'),'sed_pointlike.yaml') gtlike = Gtlike(roi, binsz=1/8., bigger_roi=False, savedir='savedir', enable_edisp=True) like=gtlike.like like.fit(covar=True) results['gtlike'] = sourcedict(like, name) save() sed = SuperSED(like, name=name, freeze_background=False) sed.plot('sed_gtlike.pdf') sed.save('sed_gtlike.yaml')