def overlay_on_plot(name, axes, header, roi, deleted_sources, superfile):
""" Overlay:
* Deleted 2FGL sources
* the SNR + best fit extension.
* Any avaliable SNR contours
"""
for source in deleted_sources:
axes['gal'].plot([source.skydir.l()],[source.skydir.b()], marker='*', color='green',
markeredgecolor='white', markersize=12)
source = roi.get_source(name)
# plot the best fit SNR position/center in blue
ROISmoothedSource.overlay_source(source, axes, color='blue', zorder=10)
if isinstance(source,ExtendedSource):
# overlay the best fit SNR size in blue
ROISmoothedSource.overlay_extension(source, axes, header, extension_color='blue',
extension_zorder=10)
# overlay the green catalog SNR in red
ROISmoothedSource.overlay_extension(get_snr(name,superfile), axes, header, extension_color='red',
extension_zorder=10)
name=args.name
superfile=args.superfile
results=dict(name=name)
# *) Build the ROI
roi=setup_roi(name,superfile,
roi_dict=dict(fit_emin=args.emin, fit_emax=args.emax),
catalog_dict=dict(free_radius=2, max_free=10),
)
# get the SNR as an extended source object.
snr_radio_template = get_snr(name, superfile)
snrsize = snr_radio_template.spatial_model['sigma']
# *) modify the ROI to remove overlaping background sources.
deleted_sources = []
for source in roi.get_sources():
if np.degrees(source.skydir.difference(snr_radio_template.skydir)) < snrsize + 0.1:
deleted_sources.append(roi.del_source(source))
for source in roi.get_sources():
# Freeze the spectrum (but not flux) of all other sources in the ROI.
if np.any(source.model.free):
free=np.asarray([True]+[False]*(len(source.model._p)-1))
roi.modify(which=source,free=free)
fit_kwargs = dict(name=name, emin=args.emin, emax=args.emax, snrsize=snrsize)
