def gtlike_followup(self, hypothesis):
name = self.name
roi = self.reload_roi(hypothesis)
cutoff = (not self.no_cutoff) and hypothesis in ['at_pulsar', 'point']
upper_limit = hypothesis=='at_pulsar'
if cutoff:
modify = import_module(self.modify)
cutoff_model=modify.get_gtlike_cutoff_model(name)
if cutoff_model is None:
pointlike_results = loaddict('results_%s_pointlike_%s.yaml' % (name,hypothesis))
cutoff_model=pointlike_results['test_cutoff']['hypothesis_1']['spectrum']
cutoff_model=pointlike_dict_to_spectrum(cutoff_model)
cutoff_model.set_default_limits(oomp_limits=True)
print 'override cutoff_model = ',cutoff_model
else:
cutoff_model=None
results=gtlike_analysis(roi, name=name,
cutoff_model = cutoff_model,
max_free = self.max_free,
seddir=self.seddir, datadir=self.datadir, plotdir=self.plotdir,
hypothesis=hypothesis,
upper_limit=upper_limit,
cutoff=cutoff,
do_bandfitter=True, do_sed=True,
)
savedict(results,'results_%s_gtlike_%s.yaml' % (name,hypothesis))
def main(self):
name=self.name
rb = RadioPSRROIBuilder(radiopsr_loader=self.radiopsr_loader)
roi = rb.build_roi(name=name, fast=self.fast)
modify = import_module(self.modify)
new_sources, deleted_sources = modify.modify_roi(roi,name)
roi.extra = dict(new_sources=new_sources,
deleted_sources=deleted_sources)
results = self.input_kwargs
savedict(results,'results_%s_general.yaml' % name)
hypothesis = 'at_pulsar'
results=pointlike_analysis(self, roi, name, hypothesis=hypothesis, upper_limit=True)
savedict(results,'results_%s_pointlike_%s.yaml' % (name,hypothesis))
if not self.no_point:
hypothesis = 'point'
results=pointlike_analysis(self, roi, name, hypothesis=hypothesis, localize=True)
savedict(results,'results_%s_pointlike_%s.yaml' % (name,hypothesis))
if not self.no_extended:
hypothesis = 'extended'
roi.modify(which=name, spatial_model=Gaussian(sigma=0.1), keep_old_center=True)
results=pointlike_analysis(self, roi, name, hypothesis=hypothesis, fit_extension=True)
savedict(results,'results_%s_pointlike_%s.yaml' % (name,hypothesis))
def variability_followup(self, hypothesis):
name = self.name
roi = self.reload_roi(hypothesis)
modify = import_module(self.modify)
good_interval = modify.get_variability_time_cuts(name)
nbins = 36
if good_interval is not None:
ft1files = roi.sa.pixeldata.ft1files
earliest_time, latest_time = CombinedVariabilityTester.get_time_range(
ft1files)
bins = b = np.round(
np.linspace(earliest_time, latest_time, nbins + 1)).astype(int)
starts = b[:-1]
stops = b[1:]
print 'Initial binning:'
print ' * starts=', starts
print ' * stops=', stops
starts,stops = zip(*[(start,stop) \
for (start,stop) in zip(starts,stops) \
if good_interval(start,stop)])
print 'Initial binning:'
print ' * starts=', starts
print ' * stops=', stops
kwargs = dict(tstarts=starts, tstops=stops)
else:
kwargs = dict(nbins=nbins)
frozen = freeze_far_away(roi,
roi.get_source(name).skydir, self.max_free)
v = CombinedVariabilityTester(roi,
name,
use_pointlike_ltcube=True,
refit_background=True,
refit_other_sources=True,
verbosity=4,
**kwargs)
unfreeze_far_away(roi, frozen)
results = v.todict()
savedict(results,
'results_%s_variability_%s.yaml' % (name, hypothesis))
try:
v.plot(filename='plots/variability_%s_hypothesis_%s.pdf' %
(name, hypothesis))
except Exception, ex:
print 'ERROR plotting variability tester:', ex
traceback.print_exc(file=sys.stdout)
def variability_followup(self, hypothesis):
name = self.name
roi = self.reload_roi(hypothesis)
modify = import_module(self.modify)
good_interval = modify.get_variability_time_cuts(name)
nbins=36
if good_interval is not None:
ft1files=roi.sa.pixeldata.ft1files
earliest_time, latest_time = CombinedVariabilityTester.get_time_range(ft1files)
bins = b = np.round(np.linspace(earliest_time, latest_time, nbins+1)).astype(int)
starts = b[:-1]
stops = b[1:]
print 'Initial binning:'
print ' * starts=',starts
print ' * stops=',stops
starts,stops = zip(*[(start,stop) \
for (start,stop) in zip(starts,stops) \
if good_interval(start,stop)])
print 'Initial binning:'
print ' * starts=',starts
print ' * stops=',stops
kwargs=dict(tstarts=starts, tstops=stops)
else:
kwargs=dict(nbins=nbins)
frozen = freeze_far_away(roi, roi.get_source(name).skydir, self.max_free)
v = CombinedVariabilityTester(roi,name,
use_pointlike_ltcube=True, refit_background=True,
refit_other_sources=True,
verbosity=4, **kwargs)
unfreeze_far_away(roi, frozen)
results = v.todict()
savedict(results,'results_%s_variability_%s.yaml' % (name,hypothesis))
try:
v.plot(filename='plots/variability_%s_hypothesis_%s.pdf' % (name,hypothesis))
except Exception, ex:
print 'ERROR plotting variability tester:', ex
traceback.print_exc(file=sys.stdout)
def main(self):
name = self.name
rb = RadioPSRROIBuilder(radiopsr_loader=self.radiopsr_loader)
roi = rb.build_roi(name=name, fast=self.fast)
modify = import_module(self.modify)
new_sources, deleted_sources = modify.modify_roi(roi, name)
roi.extra = dict(new_sources=new_sources,
deleted_sources=deleted_sources)
results = self.input_kwargs
savedict(results, 'results_%s_general.yaml' % name)
hypothesis = 'at_pulsar'
results = pointlike_analysis(self,
roi,
name,
hypothesis=hypothesis,
upper_limit=True)
savedict(results, 'results_%s_pointlike_%s.yaml' % (name, hypothesis))
if not self.no_point:
hypothesis = 'point'
results = pointlike_analysis(self,
roi,
name,
hypothesis=hypothesis,
localize=True)
savedict(results,
'results_%s_pointlike_%s.yaml' % (name, hypothesis))
if not self.no_extended:
hypothesis = 'extended'
roi.modify(which=name,
spatial_model=Gaussian(sigma=0.1),
keep_old_center=True)
results = pointlike_analysis(self,
roi,
name,
hypothesis=hypothesis,
fit_extension=True)
savedict(results,
'results_%s_pointlike_%s.yaml' % (name, hypothesis))
def gtlike_followup(self, hypothesis):
name = self.name
roi = self.reload_roi(hypothesis)
cutoff = (not self.no_cutoff) and hypothesis in ['at_pulsar', 'point']
upper_limit = hypothesis == 'at_pulsar'
if cutoff:
modify = import_module(self.modify)
cutoff_model = modify.get_gtlike_cutoff_model(name)
if cutoff_model is None:
pointlike_results = loaddict('results_%s_pointlike_%s.yaml' %
(name, hypothesis))
cutoff_model = pointlike_results['test_cutoff'][
'hypothesis_1']['spectrum']
cutoff_model = pointlike_dict_to_spectrum(cutoff_model)
cutoff_model.set_default_limits(oomp_limits=True)
print 'override cutoff_model = ', cutoff_model
else:
cutoff_model = None
results = gtlike_analysis(
roi,
name=name,
cutoff_model=cutoff_model,
max_free=self.max_free,
seddir=self.seddir,
datadir=self.datadir,
plotdir=self.plotdir,
hypothesis=hypothesis,
upper_limit=upper_limit,
cutoff=cutoff,
do_bandfitter=True,
do_sed=True,
)
savedict(results, 'results_%s_gtlike_%s.yaml' % (name, hypothesis))
def main(self):
do_at_pulsar = not self.no_at_pulsar
do_point = not self.no_point
do_extended = not self.no_extended
do_cutoff = not self.no_cutoff
name = self.name
if not self.fast:
emin = self.emin
emax = self.emax
binsperdec = self.binsperdec
free_radius = 5
roi_size = 10
max_free = self.max_free
else:
emin = 1e4
emax = 1e5
binsperdec = 2
free_radius = 2
roi_size = 5
max_free = 2
pwnphase = yaml.load(open(self.pwnphase))[name]
phase = pwnphase['phase']
print 'phase = ', phase
pwndata = yaml.load(open(self.pwndata))[name]
savedir = None if self.no_savedir else join(os.getenv('PWD'),
'savedir')
results = r = defaultdict(lambda: defaultdict(dict))
results['name'] = name
results['phase'] = phase
pointlike_kwargs = dict(name=name, max_free=max_free)
print 'Building the ROI'
reg = PWNRegion(pwndata=self.pwndata, savedir=savedir)
roi = reg.get_roi(name=name,
phase=phase,
catalog_kwargs=dict(free_radius=free_radius,
max_free=max_free),
fit_emin=emin,
fit_emax=emax,
binsperdec=binsperdec,
roi_size=roi_size,
extended=False)
modify = import_module(self.modify)
roi.extra['phase'] = phase
roi.extra['new_sources'] = modify.modify_roi(name, roi)
roi.extra['pwnphase'] = pwnphase
savedict(results, 'results_%s_general.yaml' % name)
assert all_params_limited(roi, except_sources=[name])
mapper0 = roi.get_model(which=name).get_mapper(0)
assert isinstance(mapper0,
LogMapper) or (type(mapper0) == type
and issubclass(mapper0, LogMapper))
cutoff_model = modify.get_cutoff_model(name)
override_localization = modify.get_override_localization(name)
if do_at_pulsar:
hypothesis = 'at_pulsar'
results = pointlike_analysis(roi,
hypothesis=hypothesis,
seddir=self.seddir,
datadir=self.datadir,
plotdir=self.plotdir,
cutoff=do_cutoff,
**pointlike_kwargs)
savedict(results,
'results_%s_pointlike_%s.yaml' % (name, hypothesis))
if do_point:
hypothesis = 'point'
results = pointlike_analysis(
roi,
hypothesis=hypothesis,
localize=True,
seddir=self.seddir,
datadir=self.datadir,
plotdir=self.plotdir,
cutoff=do_cutoff,
cutoff_model=cutoff_model,
override_localization=override_localization,
**pointlike_kwargs)
savedict(results,
'results_%s_pointlike_%s.yaml' % (name, hypothesis))
if do_extended:
hypothesis = 'extended'
roi.modify(which=name,
spatial_model=Gaussian(sigma=0.1),
keep_old_center=True)
results = pointlike_analysis(roi,
hypothesis=hypothesis,
cutoff=False,
seddir=self.seddir,
datadir=self.datadir,
plotdir=self.plotdir,
fit_extension=True,
**pointlike_kwargs)
savedict(results,
'results_%s_pointlike_%s.yaml' % (name, hypothesis))
def main(self):
do_at_pulsar = not self.no_at_pulsar
do_point = not self.no_point
do_extended = not self.no_extended
do_cutoff = not self.no_cutoff
name=self.name
if not self.fast:
emin=self.emin
emax=self.emax
binsperdec=self.binsperdec
free_radius=5
roi_size=10
max_free=self.max_free
else:
emin=1e4
emax=1e5
binsperdec=2
free_radius=2
roi_size=5
max_free=2
pwnphase=yaml.load(open(self.pwnphase))[name]
phase=pwnphase['phase']
print 'phase = ',phase
pwndata=yaml.load(open(self.pwndata))[name]
savedir=None if self.no_savedir else join(os.getenv('PWD'),'savedir')
results=r=defaultdict(lambda: defaultdict(dict))
results['name']=name
results['phase']=phase
pointlike_kwargs=dict(name=name, max_free=max_free)
print 'Building the ROI'
reg=PWNRegion(pwndata=self.pwndata, savedir=savedir)
roi=reg.get_roi(name=name, phase=phase,
catalog_kwargs=dict(free_radius=free_radius, max_free=max_free),
fit_emin=emin, fit_emax=emax,
binsperdec=binsperdec,
roi_size=roi_size,
extended=False)
modify = import_module(self.modify)
roi.extra['phase'] = phase
roi.extra['new_sources'] = modify.modify_roi(name,roi)
roi.extra['pwnphase'] = pwnphase
savedict(results,'results_%s_general.yaml' % name)
assert all_params_limited(roi, except_sources=[name])
mapper0 = roi.get_model(which=name).get_mapper(0)
assert isinstance(mapper0,LogMapper) or (type(mapper0)==type and issubclass(mapper0,LogMapper))
cutoff_model=modify.get_cutoff_model(name)
override_localization=modify.get_override_localization(name)
if do_at_pulsar:
hypothesis = 'at_pulsar'
results=pointlike_analysis(roi, hypothesis=hypothesis,
seddir=self.seddir, datadir=self.datadir, plotdir=self.plotdir,
cutoff=do_cutoff, **pointlike_kwargs)
savedict(results,'results_%s_pointlike_%s.yaml' % (name,hypothesis))
if do_point:
hypothesis = 'point'
results=pointlike_analysis(roi, hypothesis=hypothesis, localize=True,
seddir=self.seddir, datadir=self.datadir, plotdir=self.plotdir,
cutoff=do_cutoff,
cutoff_model = cutoff_model,
override_localization=override_localization,
**pointlike_kwargs)
savedict(results,'results_%s_pointlike_%s.yaml' % (name,hypothesis))
if do_extended:
hypothesis = 'extended'
roi.modify(which=name, spatial_model=Gaussian(sigma=0.1), keep_old_center=True)
results=pointlike_analysis(roi, hypothesis=hypothesis, cutoff=False,
seddir=self.seddir, datadir=self.datadir, plotdir=self.plotdir,
fit_extension=True,
**pointlike_kwargs)
savedict(results,'results_%s_pointlike_%s.yaml' % (name,hypothesis))
