def __init__(self, **kwargs):
keyword_options.process(self, kwargs)
if self.point_sources == [] and self.diffuse_sources == []:
self.point_sources, self.diffuse_sources = self.get_default_sources(
)
ltcube = join(self.tempdir, 'ltcube.fits')
ds = DataSpecification(ft1files=join(self.tempdir, 'ft1.fits'),
ft2files=join(self.tempdir, 'ft2.fits'),
ltcube=ltcube,
binfile=join(self.tempdir, 'binfile.fits'))
sa = SpectralAnalysisMC(
ds,
seed=self.seed,
emin=self.emin,
emax=self.emax,
binsperdec=self.binsperdec,
event_class=self.event_class,
conv_type=self.conv_type,
roi_dir=self.roi_dir,
minROI=self.maxROI,
maxROI=self.maxROI,
irf=self.irf,
use_weighted_livetime=True,
savedir=self.tempdir,
tstart=0,
tstop=self.simtime,
ltfrac=0.9,
)
roi = sa.roi(roi_dir=self.roi_dir,
point_sources=self.point_sources,
diffuse_sources=self.diffuse_sources)
self.roi = roi
fix_pointlike_ltcube(ltcube)
def __init__(self,**kwargs):
keyword_options.process(self, kwargs)
if self.point_sources == [] and self.diffuse_sources == []:
self.point_sources, self.diffuse_sources = self.get_default_sources()
ltcube = join(self.tempdir,'ltcube.fits')
ds = DataSpecification(
ft1files = join(self.tempdir,'ft1.fits'),
ft2files = join(self.tempdir,'ft2.fits'),
ltcube = ltcube,
binfile = join(self.tempdir,'binfile.fits')
)
sa = SpectralAnalysisMC(ds,
seed=self.seed,
emin=self.emin,
emax=self.emax,
binsperdec=self.binsperdec,
event_class=self.event_class,
conv_type=self.conv_type,
roi_dir=self.roi_dir,
minROI=self.maxROI,
maxROI=self.maxROI,
irf=self.irf,
use_weighted_livetime=True,
savedir=self.tempdir,
tstart=0,
tstop=self.simtime,
ltfrac=0.9,
)
roi = sa.roi(roi_dir=self.roi_dir,
point_sources = self.point_sources,
diffuse_sources = self.diffuse_sources)
self.roi = roi
fix_pointlike_ltcube(ltcube)
def __init__(self, roi, **kwargs):
""" Build a gtlike pyLikelihood object
which is consistent with a pointlike roi. """
keyword_options.process(self, kwargs)
self.roi = roi
if not roi.quiet: print 'Running a gtlike followup'
self.old_dir = os.getcwd()
if self.savedir is not None:
self.savedata = True
if not os.path.exists(self.savedir):
os.makedirs(self.savedir)
else:
self.savedata = False
self.savedir = mkdtemp(prefix=self.savedir_prefix)
# put pfiles into savedir
os.environ['PFILES'] = self.savedir + ';' + os.environ['PFILES'].split(
';')[-1]
if not roi.quiet: print 'Saving files to ', self.savedir
if self.emin == None and self.emax == None and self.enumbins == None:
self.emin, self.emax = roi.bin_edges[0], roi.bin_edges[-1]
self.enumbins = len(roi.bin_edges) - 1
elif self.emin is not None and \
self.emax is not None and \
self.enumbins is not None:
# all set
pass
else:
raise Exception("emin, emax, and enumbins must all be set.")
# Note that this formulation makes the gtlike slightly smaller than
# the pointlike ROI (so the gtlike ROI is inside the pointlike ROI)
roi_radius = np.degrees(max(_.radius_in_rad for _ in roi.bands))
if self.bigger_roi:
npix = int(math.ceil(2.0 * roi_radius / self.binsz))
else:
npix = int(math.ceil(np.sqrt(2.0) * roi_radius / self.binsz))
ct = roi.sa.pixeldata.conv_type
cmap_file = join(self.savedir, 'ccube.fits')
srcmap_file = join(self.savedir, 'srcmap.fits')
bexpmap_file = join(self.savedir, 'bexpmap.fits')
input_srcmdl_file = join(self.savedir, 'srcmdl.xml')
cut_ft1 = join(self.savedir, "ft1_cut.fits")
ft2 = Gtlike.get_ft2(roi)
ltcube = roi.sa.pixeldata.ltcube
if self.fix_pointlike_ltcube:
print 'Fixing pointlike ltcube %s' % ltcube
livetime.fix_pointlike_ltcube(ltcube)
irfs = Gtlike.get_gtlike_irfs(roi)
if self.galactic:
x, y, coordsys_str = roi.roi_dir.l(), roi.roi_dir.b(), 'GAL'
else:
x, y, coordsys_str = roi.roi_dir.ra(), roi.roi_dir.dec(), 'CEL'
Gtlike.save_xml(roi,
input_srcmdl_file,
extended_dir_name=self.extended_dir_name)
evfile = Gtlike.make_evfile(roi, self.savedir)
if not os.path.exists(cut_ft1):
if not roi.quiet: print 'Running gtselect'
gtselect = GtApp('gtselect', 'dataSubselector')
gtselect.run(infile=evfile,
outfile=cut_ft1,
ra=0,
dec=0,
rad=180,
tmin=0,
tmax=0,
emin=self.emin,
emax=self.emax,
zmax=180,
convtype=ct,
chatter=self.chatter)
else:
if not roi.quiet: print '... Skiping gtselect'
if not os.path.exists(cmap_file):
if not roi.quiet: print 'Running gtbin (ccube)'
gtbin = GtApp('gtbin', 'evtbin')
gtbin.run(algorithm='ccube',
nxpix=npix,
nypix=npix,
binsz=self.binsz,
evfile=cut_ft1,
outfile=cmap_file,
scfile=ft2,
xref=x,
yref=y,
axisrot=0,
proj=self.proj,
ebinalg='LOG',
emin=self.emin,
emax=self.emax,
enumbins=self.enumbins,
coordsys=coordsys_str,
chatter=self.chatter)
else:
if not roi.quiet: print '... Skiping gtbin (ccube)'
if not os.path.exists(bexpmap_file):
# Use the default binning all sky, 1deg/pixel
if not roi.quiet: print 'Running gtexpcube'
gtexpcube = GtApp('gtexpcube2', 'Likelihood')
gtexpcube.run(infile=ltcube,
cmap='none',
ebinalg='LOG',
emin=self.emin,
emax=self.emax,
enumbins=self.enumbins,
outfile=bexpmap_file,
proj='CAR',
nxpix=360,
nypix=180,
binsz=1,
irfs=irfs,
coordsys=coordsys_str,
chatter=self.chatter)
else:
if not roi.quiet: print '... Skiping gtexpcube'
if not os.path.exists(srcmap_file):
if not roi.quiet: print 'Running gtsrcmaps'
gtsrcmaps = GtApp('gtsrcmaps', 'Likelihood')
gtsrcmaps.run(scfile=ft2,
expcube=ltcube,
cmap=cmap_file,
srcmdl=input_srcmdl_file,
bexpmap=bexpmap_file,
outfile=srcmap_file,
irfs=irfs,
rfactor=self.rfactor,
resample=self.resample,
minbinsz=self.minbinsz,
chatter=self.chatter)
else:
if not roi.quiet: print '... Skiping gtsrcmaps'
if not roi.quiet: print 'Creating Binned LIKE'
obs = BinnedObs(srcMaps=srcmap_file,
expCube=ltcube,
binnedExpMap=bexpmap_file,
irfs=irfs)
self.like = BinnedAnalysis(binnedData=obs,
srcModel=input_srcmdl_file,
optimizer=self.optimizer)
if self.enable_edisp:
if not roi.quiet: print 'Enabeling energy dispersion'
self.like.logLike.set_edisp_flag(True)
if not roi.quiet: print 'Binned LIKE Created!'
def __init__(self, roi, **kwargs):
""" Build a gtlike pyLikelihood object
which is consistent with a pointlike roi. """
keyword_options.process(self, kwargs)
self.roi = roi
if not roi.quiet: print 'Running a gtlike followup'
self.old_dir=os.getcwd()
if self.savedir is not None:
self.savedata = True
if not os.path.exists(self.savedir):
os.makedirs(self.savedir)
else:
self.savedata = False
self.savedir=mkdtemp(prefix=self.savedir_prefix)
# put pfiles into savedir
os.environ['PFILES']=self.savedir+';'+os.environ['PFILES'].split(';')[-1]
if not roi.quiet: print 'Saving files to ',self.savedir
if self.emin==None and self.emax==None and self.enumbins==None:
self.emin,self.emax=roi.bin_edges[0],roi.bin_edges[-1]
self.enumbins=len(roi.bin_edges)-1
elif self.emin is not None and \
self.emax is not None and \
self.enumbins is not None:
# all set
pass
else:
raise Exception("emin, emax, and enumbins must all be set.")
# Note that this formulation makes the gtlike slightly smaller than
# the pointlike ROI (so the gtlike ROI is inside the pointlike ROI)
roi_radius=np.degrees(max(_.radius_in_rad for _ in roi.bands))
if self.bigger_roi:
npix=int(math.ceil(2.0*roi_radius/self.binsz))
else:
npix=int(math.ceil(np.sqrt(2.0)*roi_radius/self.binsz))
ct = roi.sa.pixeldata.conv_type
cmap_file=join(self.savedir,'ccube.fits')
srcmap_file=join(self.savedir,'srcmap.fits')
bexpmap_file=join(self.savedir,'bexpmap.fits')
input_srcmdl_file=join(self.savedir,'srcmdl.xml')
cut_ft1=join(self.savedir,"ft1_cut.fits")
ft2=Gtlike.get_ft2(roi)
ltcube=roi.sa.pixeldata.ltcube
if self.fix_pointlike_ltcube:
print 'Fixing pointlike ltcube %s' % ltcube
livetime.fix_pointlike_ltcube(ltcube)
irfs=Gtlike.get_gtlike_irfs(roi)
if self.galactic:
x,y,coordsys_str=roi.roi_dir.l(),roi.roi_dir.b(),'GAL'
else:
x,y,coordsys_str=roi.roi_dir.ra(),roi.roi_dir.dec(),'CEL'
Gtlike.save_xml(roi, input_srcmdl_file, extended_dir_name=self.extended_dir_name)
evfile=Gtlike.make_evfile(roi,self.savedir)
if not os.path.exists(cut_ft1):
if not roi.quiet: print 'Running gtselect'
gtselect=GtApp('gtselect','dataSubselector')
gtselect.run(infile=evfile,
outfile=cut_ft1,
ra=0, dec=0, rad=180,
tmin=0, tmax=0,
emin=self.emin, emax=self.emax,
zmax=180, convtype=ct,
chatter=self.chatter)
else:
if not roi.quiet: print '... Skiping gtselect'
if not os.path.exists(cmap_file):
if not roi.quiet: print 'Running gtbin (ccube)'
gtbin=GtApp('gtbin','evtbin')
gtbin.run(algorithm='ccube',
nxpix=npix, nypix=npix, binsz=self.binsz,
evfile=cut_ft1,
outfile=cmap_file,
scfile=ft2,
xref=x, yref=y, axisrot=0, proj=self.proj,
ebinalg='LOG', emin=self.emin, emax=self.emax, enumbins=self.enumbins,
coordsys=coordsys_str,
chatter=self.chatter)
else:
if not roi.quiet: print '... Skiping gtbin (ccube)'
if not os.path.exists(bexpmap_file):
# Use the default binning all sky, 1deg/pixel
if not roi.quiet: print 'Running gtexpcube'
gtexpcube=GtApp('gtexpcube2','Likelihood')
gtexpcube.run(infile=ltcube,
cmap='none',
ebinalg='LOG', emin=self.emin, emax=self.emax, enumbins=self.enumbins,
outfile=bexpmap_file, proj='CAR',
nxpix=360, nypix=180, binsz=1,
irfs=irfs,
coordsys=coordsys_str,
chatter=self.chatter)
else:
if not roi.quiet: print '... Skiping gtexpcube'
if not os.path.exists(srcmap_file):
if not roi.quiet: print 'Running gtsrcmaps'
gtsrcmaps=GtApp('gtsrcmaps','Likelihood')
gtsrcmaps.run(scfile=ft2,
expcube=ltcube,
cmap=cmap_file,
srcmdl=input_srcmdl_file,
bexpmap=bexpmap_file,
outfile=srcmap_file,
irfs=irfs,
rfactor=self.rfactor,
resample=self.resample,
minbinsz=self.minbinsz,
chatter=self.chatter)
else:
if not roi.quiet: print '... Skiping gtsrcmaps'
if not roi.quiet: print 'Creating Binned LIKE'
obs=BinnedObs(srcMaps=srcmap_file,expCube=ltcube,binnedExpMap=bexpmap_file,irfs=irfs)
self.like = BinnedAnalysis(binnedData=obs,srcModel=input_srcmdl_file,optimizer=self.optimizer)
if self.enable_edisp:
if not roi.quiet: print 'Enabeling energy dispersion'
self.like.logLike.set_edisp_flag(True)
if not roi.quiet: print 'Binned LIKE Created!'
