def FitOnePixel(self,ra,dec,i,j) :
"""Run a evaluation of the pixel (i,j) corresponding to position (ra,dec)"""
outXml = utils._dump_xml(self.config)
folder = self.config['out']
Fit = GetFitObjectForTSmap(self.config,xmlfile=outXml) #get the Fit object
src = GetSrc(Fit,ra,dec) # get the Source object at postion ra dec
if self.config['TSMap']['RemoveTarget'] : # remove the target is asked
Fit.deleteSource(self.config['target']['name'])
if self.config['TSMap']['Re-Fit']: # reoptimze before is asked
Fit.fit(0,optimizer=self.config['fitting']['optimizer'])
for par in xrange(Fit.logLike.getNumParams()): # freeze all the source parameters
Fit[par].setFree(0)
Fit.addSource(src)# add a spurious source
# dump the *new* xml file
Fit.writeXml(self.tsfolder+"/model_"+str(ra)+"_"+str(dec)+".xml")
# a new Fit object with the new xml file is needed.
# just changing the position of the spurious source does not work
TSFit = GetFitObjectForTSmap(self.config,xmlfile=self.tsfolder+"/model_"+str(ra)+"_"+str(dec)+".xml")
TSFit.fit(0,optimizer=self.config['fitting']['optimizer'])
# save the result
fsave = open(self._PixelFile(i,j),'w')
fsave.write(str(ra)+"\t"+str(dec)+"\t"+
str(TSFit.Ts("Spurious"))+"\t"+
str(TSFit.logLike.value()))
fsave.close()
def run(infile):
"""Run an entire Fermi analysis (spectrum) by reading a config file"""
config = get_config(infile)
folder = config['out']
os.system('mkdir -p ' + folder)
FitRunner,Fit = GenAnalysisObjects(config)
# create all the fit files and run gtlike
FitRunner.PerformFit(Fit)
Result = FitRunner.GetAndPrintResults(Fit)#Get and dump the target specific results
if config['verbose'] == 'yes' :
utils.GetFluxes(Fit,FitRunner.obs.Emin,FitRunner.obs.Emax) #print the flux of all the sources
utils.DumpResult(Result, config)
#plot the SED and model map if possible and asked
if config['Spectrum']['ResultPlots'] == 'yes' :
os.system("mkdir -p "+config['out'] + '/Spectrum/')
if float(config['UpperLimit']['TSlimit']) < Fit.Ts(config['target']['name']):
FitRunner.ComputeSED(Fit)
outXml = utils._dump_xml(config)
if config['Spectrum']['SummedLike'] == 'yes': # the possiblity of making the model map is checked inside the function
FitRunnerback.ModelMap(outXml)
FitRunnerfront.ModelMap(outXml)
else:
FitRunner.ModelMap(outXml)
# Make energy bins by running a *new* analysis
Nbin = config['Ebin']['NumEnergyBins']
energybin.RunEbin(folder,Nbin,Fit,FitRunner)
def run(infile):
"""Run an entire Fermi analysis (spectrum) by reading a config file"""
config = get_config(infile)
folder = config['out']
os.system('mkdir -p ' + folder)
runfit,Fit = GenAnalysisObject(config)
# create all the fit files and run gtlike
runfit.PerformFit(Fit)
if config['verbose'] == 'yes' :
utils.GetFluxes(Fit,runfit.obs.Emin,runfit.obs.Emax) #print the flux of all the sources
Result = runfit.GetAndPrintResults(Fit)#Get and dump the target specific results
utils.DumpResult(Result, config)
#plot the SED and model map if possible and asked
if config['Spectrum']['ResultPlots'] == 'yes' :
os.system("mkdir -p "+config['out'] + '/Spectrum/')
if float(config['UpperLimit']['TSlimit']) < Fit.Ts(config['target']['name']):
runfit.ComputeSED(Fit)
outXml = utils._dump_xml(config)
if SummedLike == 'yes': # the possiblity of making the model map is checked inside the function
runfitback.ModelMap(outXml)
runfitfront.ModelMap(outXml)
else:
runfit.ModelMap(outXml)
# Make energy bins by run a *new* analysis
Nbin = config['Ebin']['NumEnergyBins']
if int(Nbin) > 0:
configfiles = utils.PrepareEbin(Fit, runfit)
ind = 0
enricodir = environ.DIRS.get('ENRICO_DIR')
fermidir = environ.DIRS.get('FERMI_DIR')
for conf in configfiles:
pathconf = folder + "/Ebin" + str(Nbin) +"/" + conf
Newconfig = get_config(pathconf)
cmd = enricodir+"/enrico/RunGTlike.py "+pathconf
if Newconfig['Ebin']['Submit'] == 'no' : #run directly
os.system(cmd)
else : #submit a job to a cluster
prefix = Newconfig['out'] + "/Ebin" + str(ind)
scriptname = prefix + "_Script.sh"
JobLog = prefix + "_Job.log"
JobName = (Newconfig['target']['name'] + "_" +
Newconfig['analysis']['likelihood'] +
"_Ebin_" + str(ind) + "_" + Newconfig['file']['tag'])
call(cmd, enricodir, fermidir, scriptname, JobLog, JobName)# submition
ind+=1
def PerformFit(self, Fit):
"""Run gtlile tool. First it run gtlike with the DRNMGB optimizer
and the user optimizer after. A dictionnay is return with all
the releveant results"""
self._log('gtlike', 'Run likelihood analysis')
try:
Fit.fit(0) #first try to run gtlike to approche the minimum
except:
pass
# Now the precise fit will be done
#change the fit tolerance to the one given by the user
Fit.ftol = float(self.config['fitting']['ftol'])
#fit with the user optimizer and ask gtlike to compute the covariance matrix
self.log_like = Fit.fit(0,covar=True, optimizer=self.config['fitting']['optimizer'])
#fit with the user optimizer and ask gtlike to compute the covariance matrix
Fit.writeXml(utils._dump_xml(self.config))
