def ComputeUL(self, Fit):
"""Compute an Upper Limit using either the profil or integral method
See the ST cicerone for more information on the 2 method"""
self._log('UpperLimit', 'Compute upper Limit')
#Index given by the user
self.info("Assumed index is ", self.config['UpperLimit']['SpectralIndex'])
IdGamma = utils.getParamIndx(Fit, self.obs.srcname, 'Index')
Fit[IdGamma] = -self.config['UpperLimit']['SpectralIndex']#set the index
Fit[IdGamma].setFree(0)#the variable index is frozen to compute the UL
import scipy.stats
cl = float(self.config['UpperLimit']['cl'])
delta = 0.5*scipy.stats.chi2.isf(1-2*(cl-0.5), 1)
print cl,' ',delta
if self.config['UpperLimit']['Method'] == "Profile": #The method is Profile
import UpperLimits
ulobject = UpperLimits.UpperLimits(Fit)
ul, _ = ulobject[self.obs.srcname].compute(emin=self.obs.Emin,
emax=self.obs.Emax,delta=delta)
#delta=2.71 / 2)
self.info("Upper limit using Profile method: ")
print ulobject[self.obs.srcname].results
if self.config['UpperLimit']['Method'] == "Integral": #The method is Integral
import IntegralUpperLimit
ul, _ = IntegralUpperLimit.calc_int(Fit, self.obs.srcname, cl=cl,
verbosity=0)
print "Upper limit using Integral method: ", ul
return ul #Return the result. This is an ul on the integral flux in ph/cm2/s
def EnvelopeUL(self, Fit):
"""Compute the envelope UL. An UL is computed for different index and the maximum is taken at each energy.
This is usefull when the source index is not know or can not be constrain by theoritical argument
The index range form 1.5 to 2.5"""
import IntegralUpperLimit
import UpperLimits
self._log('EnvelopeUL', 'Compute upper limit envelope')
PhIndex = Fit.par_index(self.obs.srcname, 'Index')
Nbp = 20 #Make Nbp computations
Npgraph = 100 #The graph has Npgraph points
ener = np.logspace(np.log10(self.obs.Emin), np.log10(self.obs.Emax),
Npgraph) #the array containing the energy
Ulenv = np.array(Npgraph * [0.]) #the array containing the UL value
for i in xrange(Nbp):
indx = -1.5 - i / (Nbp - 1.)
utils.FreezeParams(Fit, self.srcname, PhIndex, indx)
#Use either the profile or the integral method
self.info("Methode used: " + self.config['UpperLimit']['Method'])
if self.config['UpperLimit']['Method'] == "Profile":
ul = UpperLimits.UpperLimits(Fit)
source_ul = ul[self.obs.srcname]
ul_val, _ = source_ul.compute(emin=self.obs.Emin,
emax=self.obs.Emax,
delta=2.71 / 2)
if self.config['UpperLimit']['Method'] == "Integral":
ul_val, _ = IntegralUpperLimit.calc_int(Fit,
self.obs.srcname,
verbosity=0)
self.success("Upper Limits calculated")
print "Index = ", indx, " UL = ", ul_val #small print
for j in xrange(Npgraph):
model_name = Fit.model.srcs[
self.obs.srcname].spectrum().genericName()
#compute the DNDE value. The computation change is
#the model is PowerLaw or PowerLaw2
#Note : Other model are not taken into account
#and no UL will be computed
if model_name == 'PowerLaw2':
newUl = ul_val * (indx + 1) * pow(ener[j], indx + 2) \
/ (pow(self.obs.Emax, indx + 1) - pow(self.obs.Emin, indx + 1))
elif model_name == 'PowerLaw':
IdEScale = utils.getParamIndx(Fit, self.obs.srcname,
'Scale')
Escale = Fit[IdEScale].value()
newUl = ul_val * pow(ener[j] / Escale,
indx + 2) * Escale**2 * 1.6022e-6
Ulenv[j] = max(Ulenv[j], newUl)
print
self.info("Result of the UL envelope")
for j in xrange(Npgraph):
print ener[j], " ", Ulenv[j]
def EnvelopeUL(self, Fit):
"""Compute the envelope UL. An UL is computed for different index and the maximum is taken at each energy.
This is usefull when the source index is not know or can not be constrain by theoritical argument
The index range form 1.5 to 2.5"""
import IntegralUpperLimit
import UpperLimits
self._log('EnvelopeUL', 'Compute upper limit envelope')
PhIndex = Fit.par_index(self.obs.srcname, 'Index')
Nbp = 20 #Make Nbp computations
Npgraph = 100#The graph has Npgraph points
ener = np.logspace(np.log10(self.obs.Emin),
np.log10(self.obs.Emax), Npgraph)#the array containing the energy
Ulenv = np.array(Npgraph * [0.])#the array containing the UL value
for i in xrange(Nbp):
indx = -1.5 - i / (Nbp - 1.)
Fit[PhIndex] = indx
Fit.freeze(PhIndex)#Freeze the index
#Use either the profile or the integral method
self.info("Methode used: "+self.config['UpperLimit']['Method'])
if self.config['UpperLimit']['Method'] == "Profile":
ul = UpperLimits.UpperLimits(Fit)
source_ul = ul[self.obs.srcname]
ul_val, _ = source_ul.compute(emin=self.obs.Emin,
emax=self.obs.Emax,
delta=2.71 / 2)
if self.config['UpperLimit']['Method'] == "Integral":
ul_val, _ = IntegralUpperLimit.calc_int(Fit, self.obs.srcname,
verbosity=0)
self.success("Upper Limits calculated")
print "Index = ", indx, " UL = ", ul_val #small print
for j in xrange(Npgraph):
model_name = Fit.model.srcs[self.obs.srcname].spectrum().genericName()
#compute the DNDE value. The computation change is
#the model is PowerLaw or PowerLaw2
#Note : Other model are not taken into account
#and no UL will be computed
if model_name == 'PowerLaw2':
newUl = ul_val * (indx + 1) * pow(ener[j], indx + 2) \
/ (pow(self.obs.Emax, indx + 1) - pow(self.obs.Emin, indx + 1))
elif model_name == 'PowerLaw':
IdEScale = utils.getParamIndx(Fit, self.obs.srcname, 'Scale')
Escale = Fit[IdEScale].value()
newUl = ul_val * pow(ener[j] / Escale, indx + 2)*Escale**2*1.6022e-6
Ulenv[j] = max(Ulenv[j], newUl)
print
self.info("Result of the UL envelope")
for j in xrange(Npgraph):
print ener[j], " ", Ulenv[j]
def CreateLikeObject(self):
"""Create an UnbinnedAnalysis or a BinnedAnalysis and retrun it."""
#create binnedAnalysis object
if self.config['analysis']['likelihood'] == 'binned':
Obs = BinnedObs(srcMaps=self.obs.srcMap,
expCube=self.obs.Cubename,
binnedExpMap=self.obs.BinnedMapfile,
irfs=self.obs.irfs)
Fit = BinnedAnalysis(Obs,
self.obs.xmlfile,
optimizer=self.config['fitting']['optimizer'])
#create a unbinnedAnalysis object
if self.config['analysis']['likelihood'] == 'unbinned':
Obs = UnbinnedObs(self.obs.mktimefile,
self.obs.ft2,
expMap=self.obs.Mapname,
expCube=self.obs.Cubename,
irfs=self.obs.irfs)
Fit = UnbinnedAnalysis(
Obs,
self.obs.xmlfile,
optimizer=self.config['fitting']['optimizer'])
# Fix this, EBL absorbed models use LogParabola with b=0 instead of PowerLaw, we may want to allow fixed shape for that case
if float(self.config['Spectrum']['FrozenSpectralIndex'] > 0
) and self.config['target']['spectrum'] == "PowerLaw":
parameters = dict()
parameters['Index'] = -float(
self.config['Spectrum']['FrozenSpectralIndex'])
# parameters['alpha'] = +float(self.config['Spectrum']['FrozenSpectralIndex'])
# parameters['Index1'] = -float(self.config['Spectrum']['FrozenSpectralIndex'])
# parameters['beta'] = 0
# parameters['Index2'] = 2.
# parameters['Cutoff'] = 30000. # set the cutoff to be high
for key in parameters.keys():
try:
IdGamma = utils.getParamIndx(Fit, self.obs.srcname, key)
Fit[IdGamma] = parameters[key] # set the parameter
Fit[IdGamma].setFree(
0) #the variable index is frozen to compute the UL
except:
continue
else:
self.info("Freezing %s at %s"\
%(key,str(self.config['Spectrum']['FrozenSpectralIndex'])))
return Fit #return the BinnedAnalysis or UnbinnedAnalysis object.
def CreateLikeObject(self):
"""Create an UnbinnedAnalysis or a BinnedAnalysis and retrun it."""
#create binnedAnalysis object
if self.config['analysis']['likelihood'] == 'binned':
use_edisp = self.config['analysis']['EnergyDispersion'] == 'yes'
edisp_bins = -2 if use_edisp==True else 0
Obs = BinnedObs(srcMaps=self.obs.srcMap,
expCube=self.obs.Cubename,
binnedExpMap=self.obs.BinnedMapfile,
irfs=self.obs.irfs)
Cfg = BinnedConfig(use_edisp=use_edisp,
edisp_bins=edisp_bins)
Fit = BinnedAnalysis(Obs, self.obs.xmlfile, config=Cfg,
optimizer=self.config['fitting']['optimizer'])
Fit.setEnergyRange(self.obs.Emin,self.obs.Emax)
print("Is edisp enabled? {0}".format(str(Fit.logLike.use_edisp())))
#create a unbinnedAnalysis object
if self.config['analysis']['likelihood'] == 'unbinned':
Obs = UnbinnedObs(self.obs.mktimefile,
self.obs.ft2,
expMap=self.obs.Mapname,
expCube=self.obs.Cubename,
irfs=self.obs.irfs)
Fit = UnbinnedAnalysis(Obs, self.obs.xmlfile,
optimizer=self.config['fitting']['optimizer'])
# Fix this, EBL absorbed models use LogParabola with b=0 instead of PowerLaw,
# we may want to allow fixed shape for that case
if float(self.config['Spectrum']['FrozenSpectralIndex']!=0):
parameters = dict()
parameters['Index'] = -float(self.config['Spectrum']['FrozenSpectralIndex'])
parameters['alpha'] = +float(self.config['Spectrum']['FrozenSpectralIndex'])
parameters['Index1'] = -float(self.config['Spectrum']['FrozenSpectralIndex'])
parameters['beta'] = 0
parameters['Index2'] = 2.
parameters['Cutoff'] = 30000. # set the cutoff to be high
for key in parameters.keys():
IdGamma = utils.getParamIndx(Fit, self.obs.srcname, key)
if (IdGamma == -1):
continue
else:
self.info("Freezing %s = %s" %(str(key),str(parameters[key])))
Fit[IdGamma] = parameters[key] # set the parameter
Fit[IdGamma].setFree(False)#the variable index is frozen to compute the UL
return Fit #return the BinnedAnalysis or UnbinnedAnalysis object.
def ComputeUL(self, Fit):
"""Compute an Upper Limit using either the profil or integral method
See the ST cicerone for more information on the 2 method"""
self._log('UpperLimit', 'Compute upper Limit')
#Index given by the user
self.info("Assumed index is "+str(self.config['UpperLimit']['SpectralIndex']))
IdGamma = utils.getParamIndx(Fit, self.obs.srcname, 'Index')
Fit[IdGamma] = -self.config['UpperLimit']['SpectralIndex']#set the index
Fit[IdGamma].setFree(0)#the variable index is frozen to compute the UL
import scipy.stats
cl = float(self.config['UpperLimit']['cl'])
delta = 0.5*scipy.stats.chi2.isf(1-2*(cl-0.5), 1)
if self.config['UpperLimit']['Method'] == "Profile": #The method is Profile
if Fit.Ts(self.obs.srcname)<2 :
self.warning("TS of the source is very low, better to use Integral method")
import UpperLimits
ulobject = UpperLimits.UpperLimits(Fit)
ul, _ = ulobject[self.obs.srcname].compute(emin=self.obs.Emin,
emax=self.obs.Emax,delta=delta)
#delta=2.71 / 2)
self.info("Upper limit using Profile method: ")
print ulobject[self.obs.srcname].results
self.warning("Be sure to have enough photons to validate the gaussian assumption")
if self.config['UpperLimit']['Method'] == "Integral": #The method is Integral
import IntegralUpperLimit
ul, _ = IntegralUpperLimit.calc_int(Fit, self.obs.srcname, cl=cl,
verbosity=0,emin=self.obs.Emin,
emax=self.obs.Emax)
print "Upper limit using Integral method: ", ul
self.warning("Be sure to have enough photons to validate the gaussian assumption")
if self.config['UpperLimit']['Method'] == "Poisson": #The method is Poisson
ul = self.PoissonUL(Fit)
print "Upper limit using Poisson statistic: ", ul
print "This is an ul on the integral flux in ph/cm2/s"
return ul #Return the result. This is an ul on the integral flux in ph/cm2/s
def CreateLikeObject(self):
"""Create an UnbinnedAnalysis or a BinnedAnalysis and retrun it."""
#create binnedAnalysis object
if self.config['analysis']['likelihood'] == 'binned':
Obs = BinnedObs(srcMaps=self.obs.srcMap,
expCube=self.obs.Cubename,
binnedExpMap=self.obs.BinnedMapfile,
irfs=self.obs.irfs)
Fit = BinnedAnalysis(Obs, self.obs.xmlfile,
optimizer=self.config['fitting']['optimizer'])
#create a unbinnedAnalysis object
if self.config['analysis']['likelihood'] == 'unbinned':
Obs = UnbinnedObs(self.obs.eventfile,
self.obs.ft2,
expMap=self.obs.Mapname,
expCube=self.obs.Cubename,
irfs=self.obs.irfs)
Fit = UnbinnedAnalysis(Obs, self.obs.xmlfile,
optimizer=self.config['fitting']['optimizer'])
if float(self.config['Spectrum']['FrozenSpectralIndex']) != 0:
parameters = dict()
parameters['Index'] = -float(self.config['Spectrum']['FrozenSpectralIndex'])
parameters['alpha'] = +float(self.config['Spectrum']['FrozenSpectralIndex'])
parameters['Index1'] = -float(self.config['Spectrum']['FrozenSpectralIndex'])
parameters['beta'] = 0
parameters['Index2'] = 2.
parameters['Cutoff'] = 30000. # set the cutoff to be high
for key in parameters.keys():
try:
IdGamma = utils.getParamIndx(Fit, self.obs.srcname, key)
Fit[IdGamma] = parameters[key] # set the parameter
Fit[IdGamma].setFree(0)#the variable index is frozen to compute the UL
except:
continue
else:
self.info("Freezing %s at %s"\
%(key,str(self.config['Spectrum']['FrozenSpectralIndex'])))
return Fit #return the BinnedAnalysis or UnbinnedAnalysis object.
def ComputeUL(self, Fit):
"""Compute an Upper Limit using either the profil or integral method
See the ST cicerone for more information on the 2 method"""
self._log('UpperLimit', 'Compute upper Limit')
#Index given by the user
self.info("Assumed index is "+str(self.config['UpperLimit']['SpectralIndex']))
IdGamma = utils.getParamIndx(Fit, self.obs.srcname, 'Index')
Fit[IdGamma] = -self.config['UpperLimit']['SpectralIndex']#set the index
Fit[IdGamma].setFree(0)#the variable index is frozen to compute the UL
import scipy.stats
cl = float(self.config['UpperLimit']['cl'])
delta = 0.5*scipy.stats.chi2.isf(1-2*(cl-0.5), 1)
if self.config['UpperLimit']['Method'] == "Profile": #The method is Profile
if Fit.Ts(self.obs.srcname)<2 :
self.warning("TS of the source is very low, better to use Integral method")
import UpperLimits
ulobject = UpperLimits.UpperLimits(Fit)
ul, _ = ulobject[self.obs.srcname].compute(emin=self.obs.Emin,
emax=self.obs.Emax,delta=delta)
#delta=2.71 / 2)
self.info("Upper limit using Profile method: ")
print ulobject[self.obs.srcname].results
self.warning("Be sure to have enough photons to validate the gaussian assumption")
if self.config['UpperLimit']['Method'] == "Integral": #The method is Integral
import IntegralUpperLimit
ul, _ = IntegralUpperLimit.calc_int(Fit, self.obs.srcname, cl=cl,
verbosity=0,emin=self.obs.Emin,
emax=self.obs.Emax)
print "Upper limit using Integral method: ", ul
self.warning("Be sure to have enough photons to validate the gaussian assumption")
if self.config['UpperLimit']['Method'] == "Poisson": #The method is Poisson
ul = self.PoissonUL(Fit)
print "Upper limit using Poisson statistic: ", ul
print "This is an ul on the integral flux in ph/cm2/s"
return ul #Return the result. This is an ul on the integral flux in ph/cm2/s
def ComputeUL(self, Fit):
"""Compute an Upper Limit using either the profil or integral method
See the ST cicerone for more information on the 2 method"""
self._log('UpperLimit', 'Compute upper Limit')
#Index given by the user
print "Assumed index is ", self.config['UpperLimit']['SpectralIndex']
IdGamma = utils.getParamIndx(Fit, self.obs.srcname, 'Index')
Fit[IdGamma] = -self.config['UpperLimit'][
'SpectralIndex'] #set the index
Fit[IdGamma].setFree(
0) #the variable index is frozen to compute the UL
import scipy.stats
cl = float(self.config['UpperLimit']['cl'])
delta = 0.5 * scipy.stats.chi2.isf(1 - 2 * (cl - 0.5), 1)
print cl, ' ', delta
if self.config['UpperLimit'][
'Method'] == "Profile": #The method is Profile
import UpperLimits
ulobject = UpperLimits.UpperLimits(Fit)
ul, _ = ulobject[self.obs.srcname].compute(emin=self.obs.Emin,
emax=self.obs.Emax,
delta=delta)
#delta=2.71 / 2)
print "Upper limit using Profile method: "
print ulobject[self.obs.srcname].results
if self.config['UpperLimit'][
'Method'] == "Integral": #The method is Integral
import IntegralUpperLimit
ul, _ = IntegralUpperLimit.calc_int(Fit,
self.obs.srcname,
cl=cl,
verbosity=0)
print "Upper limit using Integral method: ", ul
return ul #Return the result. This is an ul on the integral flux in ph/cm2/s
