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')
