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':
from enrico.constants import SpectrumPath
os.system("mkdir -p " + config['out'] + '/' + SpectrumPath + '/')
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
FitRunner.ModelMap(outXml)
# Make energy bins by running a *new* analysis
Nbin = config['Ebin']['NumEnergyBins']
energybin.RunEbin(folder, Nbin, Fit, FitRunner)
def run(infile):
from enrico import utils
from enrico import energybin
from enrico.config import get_config
from enrico import Loggin
mes = Loggin.Message()
"""Run an entire Fermi analysis (spectrum) by reading a config file"""
config = get_config(infile)
folder = config['out']
utils.mkdir_p(folder)
FitRunner, Fit = GenAnalysisObjects(config)
# create all the fit files and run gtlike
FitRunner.PerformFit(Fit)
sedresult = None
#plot the SED and model map if possible and asked
if float(config['UpperLimit']['TSlimit']) < Fit.Ts(
config['target']['name']):
if config['Spectrum']['ResultPlots'] == 'yes':
from enrico.constants import SpectrumPath
utils.mkdir_p("%s/%s/" % (config['out'], SpectrumPath))
sedresult = FitRunner.ComputeSED(Fit, dump=True)
else:
sedresult = FitRunner.ComputeSED(Fit, dump=False)
if (config['energy']['decorrelation_energy'] == 'yes'):
#Update the energy scale to decorrelation energy
mes.info(
'Setting the decorrelation energy as new Scale for the spectral parameters'
)
spectrum = Fit[FitRunner.obs.srcname].funcs['Spectrum']
modeltype = spectrum.genericName()
genericName = Fit.model.srcs[
FitRunner.obs.srcname].spectrum().genericName()
varscale = None
if genericName == "PowerLaw2":
varscale = None
elif genericName in [
"PowerLaw", "PLSuperExpCutoff",
"EblAtten::PLSuperExpCutoff"
]:
varscale = "Scale"
elif genericName in ["LogParabola","EblAtten::LogParabola", \
"BrokenPowerLaw", "EblAtten::BrokenPowerLaw"]:
varscale = "Eb"
if varscale is not None:
spectrum.getParam(varscale).setValue(sedresult.decE)
FitRunner.PerformFit(Fit)
#Get and dump the target specific results
Result = FitRunner.GetAndPrintResults(Fit)
utils.DumpResult(Result, config)
# Make energy bins by running a *new* analysis
Nbin = config['Ebin']['NumEnergyBins']
FitRunner.config['file']['parent_config'] = infile
if config['Spectrum']['ResultParentPlots'] == "yes":
plot_sed_fromconfig(get_config(config['file']['parent_config']),
ignore_missing_bins=True)
if config['Spectrum']['ResultPlots'] == 'yes':
outXml = utils._dump_xml(config)
# the possibility of making the model map is checked inside the function
FitRunner.ModelMap(outXml)
if Nbin > 0:
FitRunner.config['Spectrum']['ResultParentPlots'] = "yes"
plot_sed_fromconfig(get_config(infile), ignore_missing_bins=True)
energybin.RunEbin(folder, Nbin, Fit, FitRunner, sedresult)
del (sedresult)
del (Result)
del (FitRunner)
