def get_point_sources(names, catalog):
""" Input is a list of the name of 1FGL sources. What is
return is a list of point source found from the names. """
cat=FermiCatalog(catalog,free_radius=180) \
if not isinstance(catalog,SourceCatalog) else catalog
point_sources = []
for name in names:
index = np.where(cat.names == name)[0]
if len(index) < 1:
raise Exception("Cannot find source %s in the catalog %s" %
(name, catalog))
if len(index) > 1:
raise Exception(
"%s has too many counterpats in the catalog %s" %
(name, catalog))
index = int(index)
point_sources.append(
PointSource(cat.dirs[index],
cat.names[index],
cat.models[index],
free_parameters=True))
if len(names) == 1:
return point_sources[0]
return point_sources
def background_fit(self):
"""Perform a fit over the full time range."""
kw = self.factory_kwargs.copy()
kw['tstart'], kw['tstop'] = self.bg_interval
f = ROIFactory(**kw)
mapper = lambda x: FermiCatalog(x, **self.catalog_kwargs)
roi = f(self.skydir, catalog_mapper=mapper, **self.roi_kwargs)
roi.fit(**self.fit_kwargs)
return roi
def fit(self, start, stop, return_likelihood=False):
"""Perform a fit over the specified interval."""
fact_kw = self.factory_kwargs.copy()
fact_kw['tstart'], fact_kw['tstop'] = start, stop
fit_kwargs = self.fit_kwargs.copy()
fit_kwargs['fit_bg_first'] = False
f = ROIFactory(**fact_kw)
mapper = lambda x: FermiCatalog(x, **self.catalog_kwargs)
roi = f(self.skydir, catalog_mapper=mapper, **self.roi_kwargs)
#roi.set_parameters(self.bg_roi.parameters().copy())
ll_0 = roi.logLikelihood(self.bg_roi.parameters().copy())
for m in roi.bgm.models:
m.free[:] = False
for m in roi.psm.models:
m.free[:] = False
for ps in roi.psm.point_sources[self.free_mask]:
ps.model.free[0] = True
roi.psm.models[0].free[1] = self.index_free
roi.fit(**fit_kwargs)
if return_likelihood:
return roi, ll_0, roi.logLikelihood(roi.parameters())
else:
return roi
def get_catalog(catalog=None, **kwargs):
if catalog is None or isinstance(catalog, SourceCatalog):
pass
elif catalog == 'PSC3Y':
catalog = Catalog3Y(
'/u/ki/kadrlica/fermi/catalogs/PSC3Y/gll_psc3yearclean_v1_assoc_v6r1p0.fit',
latextdir='/u/ki/kadrlica/fermi/catalogs/PSC3Y/',
prune_radius=0,
**kwargs)
elif catalog == '2FGL':
catalog = Catalog2FGL(
'/u/ki/kadrlica/fermi/catalogs/2FGL/gll_psc_v08.fit',
latextdir='/u/ki/kadrlica/fermi/catalogs/2FGL/Templates/',
prune_radius=0,
**kwargs)
elif catalog == "1FGL":
catalog = FermiCatalog(
'/u/ki/kadrlica/fermi/catalogs/gll_psc_v02.fit',
prune_radius=0,
**kwargs)
else:
raise Exception("Unknown catalog: %s" % catalog)
return catalog
def setup_pwn(name,pwndata,phase, free_radius=5, tempdir=None, emin=1.0e2, emax=1.0e5,maxroi=10,model=None,**kwargs):
"""Name of the source
pwndata Yaml file
returns pointlike ROI.
"""
sources=yaml.load(open(pwndata))
catalog_name=sources[name]['catalog']
ltcube=sources[name]['ltcube']
pulsar_position=SkyDir(*sources[name]['dir'])
ft2=sources[name]['ft2']
ft1=sources[name]['ft1']
# in case no list was passed
if len(phase)==2 and isinstance(phase[0],numbers.Real) and \
isinstance(phase[1],numbers.Real):
# write in case phase wraps around.
if phase[0]>phase[1]:
phase=[[phase[0],1.0],[0.0,phase[1]]]
else:
phase = [phase]
phase_factor=get_phase_factor(phase)
print "phase"
print phase
print "phase_factor=%.2f"%phase_factor
catalog=FermiCatalog(e("$FERMI/catalogs/gll_psc_v02.fit"),free_radius=free_radius)
catalog_source=[i for i in catalog.get_sources(SkyDir(),180) if i.name==catalog_name][0]
center=catalog_source.skydir
if tempdir is None: tempdir=mkdtemp(prefix='/scratch/')
binfile=j(tempdir,'binned_phased.fits')
# apply phase cut to ft1 file
phased_ft1 = j(tempdir,'ft1_phased.fits')
phasetools.phase_cut(ft1,phased_ft1,phaseranges=phase)
# create a temporary ltcube scaled by the phase factor
# phased_ltcube=j(tempdir,'phased_ltcube.fits')
# phase_ltcube(ltcube,phased_ltcube, phase=phase)
phased_ltcube=ltcube
from uw.like.pointspec import DataSpecification
data_specification = DataSpecification(
ft1files = phased_ft1,
ft2files = ft2,
ltcube = phased_ltcube,
binfile = binfile)
spectral_analysis = SpectralAnalysis(data_specification,
binsperdec = 4,
emin = 100,
emax = 100000,
irf = "P6_V3_DIFFUSE",
roi_dir = center,
maxROI = maxroi,
minROI = maxroi)
if model == None :
roi=spectral_analysis.roi(
roi_dir=center,
diffuse_sources=get_default_diffuse(diffdir=e("$FERMI/diffuse"),
gfile="gll_iem_v02.fit",
ifile="isotropic_iem_v02.txt"),
catalogs = catalog,
phase_factor = 1.0,
fit_emin = [emin,emin],
fit_emax = [emax,emax],
**kwargs)
else :
roi=spectral_analysis.roi(
roi_dir=center,
xmlfile = model,
phase_factor =1.0,
fit_emin = [emin,emin],
fit_emax = [emax,emax],
**kwargs)
print "---------------------Energy range--------------------"
print "emin="+str(roi.bands[0].emin)+"\n"
print "emax="+str(roi.bands[len(roi.bands)-1].emax)+"\n"
# keep overall flux of catalog source,
# but change the starting index to 2.
roi.modify(which=catalog_name, name=name, index=2,
keep_old_flux=True)
return roi
def setup_pointlike(name,pwnlist,phasing=True):
"""Name of the source
pwnlist Yaml file
phasing=true : apply phase cut
phasing=false : don't do it"""
sources=yaml.load(open(pwnlist))
catalog_name=sources[name]['catalog']
phase=sources[name]['phase']
ltcube=sources[name]['ltcube']
pulsar_position=SkyDir(*sources[name]['dir'])
if phasing==True:
phase_factor=phase[1]-phase[0] if phase[1]>phase[0] else (1-phase[0]) + (phase[1]-0)
ft1=sources[name]['ft1']
else :
phase_factor=1.0
raise Exception("Unable to phase data")
catalog=FermiCatalog(e("$FERMI/catalogs/gll_psc_v02.fit"),free_radius=5)
catalog_source=[i for i in catalog.get_sources(SkyDir(),180) if i.name==catalog_name][0]
center=catalog_source.skydir
from uw.like.pointspec import DataSpecification
data_specification = DataSpecification(
ft1files = ft1,
ltcube = ltcube,
binfile = "binned_%s.fits" % name)
spectral_analysis = SpectralAnalysis(data_specification,
binsperdec = 8,
emin = 100,
emax = 100000,
irf = "P6_V3_DIFFUSE",
roi_dir = center,
maxROI = 10,
minROI = 10)
roi=LandeROI(spectral_analysis.roi(
roi_dir=center,
diffuse_sources=get_default_diffuse(diffdir=e("$FERMI/diffuse"),
gfile="gll_iem_v02.fit",
ifile="isotropic_iem_v02.txt"),
catalogs = catalog,
fit_emin = 100,
fit_emax = 100000,
catalog_include_radius = 20,
phase_factor = phase_factor)
)
roi.del_source(catalog_name)
# make residual TS map
# add in PWN Candidate
source=PointSource(
name=name,
model=PowerLaw(p=[1,2]),
skydir=pulsar_position
)
source.model.set_flux(1e-7,emin=100,emax=100000)
roi.add_source(source)
return roi
args = parser.parse_args()
if args.num_points is not None:
from uw.utilities.convolution import AnalyticConvolution
AnalyticConvolution.set_points(args.num_points)
name=args.name
savename = name.replace(' ','_')
datafiles=imp.load_source('datafiles',args.datafiles)
start_spectral = None
manager=FermiCatalog(datafiles.catalog) if not isinstance(datafiles.catalog,SourceCatalog) else datafiles.catalog
source = manager.get_source(name) # only works with Catalog2FGL (oops)
start_spectral = source.model
skydir = source.skydir
outfile={'start_cel':[skydir.ra(),skydir.dec()],
'start_gal':[skydir.l(),skydir.b()],
'name':name}
ds = DataSpecification(
binfile = datafiles.binfile,
ltcube = datafiles.ltcube,
ft1files = datafiles.ft1files,
ft2files = datafiles.ft2file)
sa = SpectralAnalysis(ds,
def setup_region(name,pwndata,phase, free_radius=5, tempdir=None, maxroi=10,
xml=None, **kwargs):
"""Name of the source
pwndata Yaml file
returns pointlike ROI.
"""
phase = PhaseRange(phase)
sources=yaml.load(open(pwndata))
catalog_name=sources[name]['catalog']['2fgl']
ltcube=sources[name]['ltcube']
pulsar_position=SkyDir(*sources[name]['dir'])
ft2=sources[name]['ft2']
ft1=sources[name]['ft1']
catalog=FermiCatalog(e("$FERMI/catalogs/gll_psc_v02.fit"))
catalog=Catalog2FGL('$FERMI/catalogs/gll_psc_v05.fit',
latextdir='$FERMI/extended_archives/gll_psc_v05_templates',
free_radius=free_radius)
catalog_source=catalog.get_source(catalog_name)
center=catalog_source.skydir
if tempdir is None: tempdir=mkdtemp(prefix='/scratch/')
binfile=j(tempdir,'binned_phased.fits')
if np.allclose(phase.phase_fraction,1):
phased_ltcube = ltcube
phased_ft1 = ft1
else:
# create a temporary ltcube scaled by the phase factor
phased_ltcube=j(tempdir,'phased_ltcube.fits')
phase_ltcube(ltcube,phased_ltcube, phase=phase)
# apply phase cut to ft1 file
phased_ft1 = j(tempdir,'ft1_phased.fits')
phasetools.phase_cut(ft1,phased_ft1,phaseranges=phase.tolist(dense=False))
from uw.like.pointspec import DataSpecification
ds = DataSpecification(
ft1files = phased_ft1,
ft2files = ft2,
ltcube = phased_ltcube,
binfile = binfile)
sa = SpectralAnalysis(ds,
binsperdec = 8,
emin = 100,
emax = 100000,
irf = "P6_V11_DIFFUSE",
roi_dir = center,
maxROI = maxroi,
minROI = maxroi)
if xml is None:
roi=sa.roi(
diffuse_sources=get_default_diffuse(diffdir="/afs/slac/g/glast/groups/diffuse/mapcubes",
gfile="gll_iem_v02.fit",
ifile="isotropic_iem_v02.txt"),
catalogs = catalog,
phase_factor =1,
**kwargs)
else:
roi=sa.roi_from_xml(
roi_dir=center,
xmlfile = xml,
phase_factor =1,
**kwargs)
print 'bins ',roi.bin_edges
roi.del_source(catalog_name)
return roi
def setup_pwn(name,pwndata,phase, free_radius=5, tempdir=None, **kwargs):
"""Name of the source
pwndata Yaml file
returns pointlike ROI.
"""
sources=yaml.load(open(pwndata))
catalog_name=sources[name]['catalog']
ltcube=sources[name]['ltcube']
pulsar_position=SkyDir(*sources[name]['dir'])
ft2=sources[name]['ft2']
ft1=sources[name]['ft1']
# in case no list was passed
if len(phase)==2 and isinstance(phase[0],numbers.Real) and \
isinstance(phase[1],numbers.Real):
# write in case phase wraps around.
if phase[0]>phase[1]:
phase=[[phase[0],1.0],[0.0,phase[1]]]
else:
phase = [phase]
phase_factor=get_phase_factor(phase)
catalog=FermiCatalog(e("$FERMI/catalogs/gll_psc_v02.fit"),free_radius=free_radius)
catalog_source=[i for i in catalog.get_sources(SkyDir(),180) if i.name==catalog_name][0]
center=catalog_source.skydir
if tempdir is None: tempdir=mkdtemp(prefix='/scratch/')
binfile=j(tempdir,'binned_phased.fits')
# apply phase cut to ft1 file
phased_ft1 = j(tempdir,'ft1_phased.fits')
phasetools.phase_cut(ft1,phased_ft1,phaseranges=phase)
# create a temporary ltcube scaled by the phase factor
# phased_ltcube=j(tempdir,'phased_ltcube.fits')
# phase_ltcube(ltcube,phased_ltcube, phase=[0.0,1.0])
phased_ltcube=ltcube
from uw.like.pointspec import DataSpecification
data_specification = DataSpecification(
ft1files = phased_ft1,
ft2files = ft2,
ltcube = phased_ltcube,
binfile = binfile)
spectral_analysis = SpectralAnalysis(data_specification,
binsperdec = 4,
emin = 100,
emax = 100000,
irf = "P6_V3_DIFFUSE",
roi_dir = center,
maxROI = 10,
minROI = 10)
roi=spectral_analysis.roi(
roi_dir=center,
diffuse_sources=get_default_diffuse(diffdir=e("$FERMI/diffuse"),
gfile="gll_iem_v02.fit",
ifile="isotropic_iem_v02.txt"),
catalogs = catalog,
phase_factor = phase_factor,
**kwargs) # phaseing already done to the ltcube
print "phase_factor=%.2f"%phase_factor
# keep overall flux of catalog source,
# but change the starting index to 2.
roi.modify(which=catalog_name, name=name, index=2,
keep_old_flux=True)
roi.toXML(filename="essai")
print roi
roi.print_summary()
for names in roi.get_names():
try :
roi.modify(names,Norm=roi.get_model(names)[0]*roi.phase_factor)
except :
try :
roi.modify(names,Int_flux=roi.get_model(names)[0]*roi.phase_factor)
except :
print names
table=roi.get_names()
print roi.modify(which=table[len(table)-2],model=PowerLaw(p=[1.0*phase_factor,0.1]),free=[True,False])
print roi.modify(which=table[len(table)-1],model=PowerLaw(p=[1.0*phase_factor,0.1]),free=[True,False])
# print roi.modify(which='eg_v02',free=[False])
print roi
return roi
