def ctlike_binned(events_name, cntmap_name, emin, emax, enumbins, nxpix, nypix,
binsz, ra, dec, IRF, CALDB, outfile):
"""
Copied and modified from ctools/examples/make_binned_analysis.py
"""
# Bin the events first
bin = ctools.ctbin()
# We need this to explicitely open the log file in Python mode
bin.logFileOpen()
bin["evfile"].filename(events_name)
bin["outfile"].filename(cntmap_name)
bin["emin"].real(emin)
bin["emax"].real(emax)
bin["enumbins"].integer(enumbins)
bin["nxpix"].integer(nxpix)
bin["nypix"].integer(nypix)
bin["binsz"].real(binsz)
bin["coordsys"].string('GAL')
bin["xref"].real(ra)
bin["yref"].real(dec)
bin["proj"].string('CAR')
bin.execute()
# Perform maximum likelihood fitting
like = ctools.ctlike()
like.logFileOpen()
like["infile"].filename(cntmap_name)
like["srcmdl"].filename('$CTOOLS/share/models/crab.xml')
like["outmdl"].filename(outfile)
like["caldb"].string(CALDB)
like["irf"].string(IRF)
like.execute()
def ctbin(self,obsXml= None, log=False,debug=False, **kwargs):
'''
Create ctbin instance with given parameters
Parameters
---------
log : save or not the log file
debug : debug mode or not. This will print a lot of information
'''
self.info("Running ctbin to create count map")
self.bin = ct.ctbin()
self._fill_app( self.bin,log=log,debug=debug, **kwargs)
self.bin["outcube"] = join(self.outdir,self.config['file']["cntcube"])
if self.verbose:
print self.bin
# Run ctbin application. This will loop over all observations in
# the container and bin the events in counts maps
self.bin.run()
self.bin.save()
self.info("Saved counts cube to {0:s}".format(self.bin["outcube"]))
self.bin
def ctlike_binned(events_name, cntmap_name, emin, emax,
enumbins, nxpix, nypix, binsz, ra, dec, IRF, CALDB, outfile):
"""
Copied and modified from ctools/examples/make_binned_analysis.py
"""
# Bin the events first
bin = ctools.ctbin()
# We need this to explicitely open the log file in Python mode
bin.logFileOpen()
bin["evfile"].filename(events_name)
bin["outfile"].filename(cntmap_name)
bin["emin"].real(emin)
bin["emax"].real(emax)
bin["enumbins"].integer(enumbins)
bin["nxpix"].integer(nxpix)
bin["nypix"].integer(nypix)
bin["binsz"].real(binsz)
bin["coordsys"].string('GAL')
bin["xref"].real(ra)
bin["yref"].real(dec)
bin["proj"].string('CAR')
bin.execute()
# Perform maximum likelihood fitting
like = ctools.ctlike()
like.logFileOpen()
like["infile"].filename(cntmap_name)
like["srcmdl"].filename('$CTOOLS/share/models/crab.xml')
like["outmdl"].filename(outfile)
like["caldb"].string(CALDB)
like["irf"].string(IRF)
like.execute()
def ctbinning_run(ev_file, force=0):
working_dir = os.path.dirname(ev_file)
cnt_file = os.path.join(working_dir, "cntcube.fits")
log_file = os.path.join(working_dir, "ctbin.log")
if not os.path.isfile(cnt_file) or force == 1:
binning = ctools.ctbin()
binning.clear()
binning["inobs"] = ev_file
binning["outobs"] = cnt_file
binning["xref"] = OBJ["ra"]
binning["yref"] = OBJ["dec"]
binning["ebinalg"] = "LOG"
binning["emin"] = ENERGY["min"]
binning["emax"] = ENERGY["max"]
binning["enumbins"] = 20
binning["nxpix"] = 500
binning["nypix"] = 500
binning["binsz"] = 0.01
binning["coordsys"] = "CEL"
binning["proj"] = "CAR"
binning["logfile"] = log_file
binning.logFileOpen()
binning.run()
binning.save()
sys.stderr.write("File '%s' created.\n" % cnt_file)
return cnt_file
def ctbin(self, log=False, debug=False):
'''
Create ctbin instance with given parameters
Parameters
---------
log : save or not the log file
debug : debug mode or not. This will print a lot of information
'''
self.info("Running ctbin to create count map")
if self.m_obs:
bin = ct.ctbin(self.m_obs)
else:
bin = ct.ctbin()
for k in self.config.keys():
try:
for kk in self.config[k].keys():
if bin._has_par(kk):
bin[kk] = self.config[k][kk]
except:
if bin._has_par(k):
bin[k] = self.config[k]
bin["inobs"] = join(self.workdir,
self.config['file']["selectedevent"])
bin["outcube"] = join(self.workdir, self.config['file']["cube"])
# Optionally open the log file
if log:
bin.logFileOpen()
# Optionally switch-on debugging model
if debug:
bin["debug"].boolean(True)
if self.verbose:
print bin
# Run ctbin application. This will loop over all observations in
# the container and bin the events in counts maps
bin.run()
bin.save()
if self.m_obs:
# Make a deep copy of the observation that will be returned
# (the ctbin object will go out of scope one the function is
# left)
self.m_obs = bin.obs().copy()
def run_pipeline(obs, emin=0.1, emax=100.0,
enumbins=20, nxpix=200, nypix=200, binsz=0.02,
coordsys="CEL", proj="CAR", debug=False):
"""
Simulation and binned analysis pipeline.
Keywords:
emin - Minimum energy of cube [TeV] (default: 0.1)
emax - Maximum energy of cube [TeV] (default: 100.0)
enumbins - Number of energy bins in cube (default: 20)
nxpix - Number of RA pixels in cube (default: 200)
nypix - Number of DEC pixels in cube (default: 200)
binsz - Spatial cube bin size [deg] (default: 0.02)
coordsys - Cube coordinate system (CEL or GAL)
proj - Cube World Coordinate System (WCS) projection
debug - Enable debugging (default: False)
"""
# Simulate events
sim = ctools.ctobssim(obs)
sim["debug"] = debug
sim.run()
# Bin events by looping over all observations in the container
obs = gammalib.GObservations()
obs.models(sim.obs().models())
for run in sim.obs():
# Create container with a single observation
container = gammalib.GObservations()
container.append(run)
# Bin events for that observation
bin = ctools.ctbin(container)
bin["ebinalg"] = "LOG"
bin["emin"] = emin
bin["emax"] = emax
bin["enumbins"] = enumbins
bin["nxpix"] = nxpix
bin["nypix"] = nypix
bin["binsz"] = binsz
bin["coordsys"] = coordsys
bin["usepnt"] = True
bin["proj"] = proj
bin.run()
# Append result to observations
obs.extend(bin.obs())
# Perform maximum likelihood fitting
like = ctools.ctlike(obs)
like["debug"] = True # Switch this always on for results in console
like.run()
# Return
return
def create_cntcube(obs, emin=None, emax=None, ebins=20, npix=200, binsz=0.02):
"""
Create counts cube
Parameters
----------
obs : `~gammalib.GObservations`
Observation container
emin : float, optional
Minimum energy (TeV)
emax : float, optional
Maximum energy (TeV)
ebins : int, optional
Number of energy bins
npix : int, optional
Number of spatial pixels in x and y
binsz : float, optional
Spatial pixels bin size (deg)
Returns
-------
cntcube : `~gammalib.GCTAEventCube`
Counts cube
"""
# Get energy range for observation
if emin == None:
emin = obs[0].ebounds().emin().TeV()
if emax == None:
emax = obs[0].ebounds().emax().TeV()
# Setup task parameters
ctbin = ctools.ctbin(obs)
ctbin['ebinalg'] = 'LOG'
ctbin['emin'] = emin
ctbin['emax'] = emax
ctbin['enumbins'] = ebins
ctbin['coordsys'] = 'CEL'
ctbin['proj'] = 'TAN'
ctbin['usepnt'] = True
ctbin['nxpix'] = npix
ctbin['nypix'] = npix
ctbin['binsz'] = binsz
# Generate counts cube
ctbin.run()
# Extract counts cube
cntcube = ctbin.cube().copy()
# Return counts cube
return cntcube
def ctbin(self,log=False,debug=False):
# ctbin application and set parameters
self.validate()
self.info("Running ctbin to create count map")
if self.m_obs:
bin = ct.ctbin(self.m_obs)
else:
bin = ct.ctbin()
bin["evfile"] = self.m_evtfile
bin["outfile"] = self.m_cntfile
bin["ebinalg"].string(self.m_ebinalg)
bin["emin"].real(self.m_emin)
bin["emax"].real(self.m_emax)
Nbdecade = log10(self.m_emax)-log10(self.m_emin)#Compute the number of decade
bin["enumbins"].integer(int(self.m_enumbins*Nbdecade))
bin["usepnt"].boolean(self.m_usepnt) # Use pointing for map centre
bin["nxpix"].integer(self.m_nxpix)
bin["nypix"].integer(self.m_nypix)
bin["binsz"].real(self.m_binsz)
bin["coordsys"].string(self.m_coordsys)
bin["proj"].string(self.m_proj)
# Optionally open the log file
if log:
bin.logFileOpen()
# Optionally switch-on debugging model
if debug:
bin["debug"].boolean(True)
# Run ctbin application. This will loop over all observations in
# the container and bin the events in counts maps
bin.execute()
if self.m_obs:
# Make a deep copy of the observation that will be returned
# (the ctbin object will go out of scope one the function is
# left)
self.m_obs = bin.obs().copy()
def sim(src="cCrab"): #bkg, Crabbkg
"Simulates acceptance ccube and model cube"
print 30 * "-" + "\n", "Simulating", src + "\n" + 30 * "-"
#Simulate observation
sim = ctools.ctobssim()
sim["inmodel"] = modeldir + src + ".xml"
sim["outevents"] = outdir + "events_" + src + ".fits"
sim["caldb"] = caldb
sim["irf"] = irf
sim["ra"] = ra
sim["dec"] = dec
sim["rad"] = 10.0
sim["tmin"] = 0.0
sim["tmax"] = tsim
sim["emin"] = emin
sim["emax"] = emax
sim["edisp"] = False
sim.execute()
#Bin data into a cube
ctbin = ctools.ctbin()
ctbin["inobs"] = outdir + "events_" + src + ".fits"
ctbin["outcube"] = outdir + "ccube_" + src + ".fits"
ctbin["ebinalg"] = "LOG"
ctbin["emin"] = emin
ctbin["emax"] = emax
ctbin["enumbins"] = enumbins
ctbin["nxpix"] = npix
ctbin["nypix"] = npix
ctbin["binsz"] = binsz
ctbin["coordsys"] = "CEL"
ctbin["xref"] = ra
ctbin["yref"] = dec
ctbin["proj"] = "AIT"
ctbin.execute()
#Create model cube
ctmodel = ctools.ctmodel()
ctmodel["inobs"] = outdir + "events_" + src + ".fits"
ctmodel["inmodel"] = modeldir + src + ".xml"
ctmodel["incube"] = outdir + "ccube_" + src + ".fits"
ctmodel["caldb"] = "prod2"
ctmodel["caldb"] = caldb
ctmodel["irf"] = irf
ctmodel["outcube"] = outdir + "mcube_" + src + ".fits"
ctmodel["edisp"] = False
ctmodel.execute()
def create_count_cube():
"""
Create counts cube
"""
# Allocate ctbin application and set parameters
bin = ctools.ctbin()
bin['inobs'] = 'test/data/crab_events.fits'
bin['outcube'] = 'test/data/crab_cntmap.fits'
bin['ebinalg'] = 'LOG'
bin['emin'] = 1.0
bin['emax'] = 100.0
bin['enumbins'] = 5
bin['usepnt'] = True # Use pointing for map centre
bin['nxpix'] = 20
bin['nypix'] = 20
bin['binsz'] = 0.2
bin['coordsys'] = 'CEL'
bin['proj'] = 'TAN'
bin.execute()
# Return
return
def test_functional(self):
"""
Test ctbin functionnality.
"""
# Set-up ctbin
bin = ctools.ctbin()
bin["inobs"] = self.events_name
bin["outcube"] = "cntmap.fits"
bin["ebinalg"] = "LOG"
bin["emin"] = 0.1
bin["emax"] = 100.0
bin["enumbins"] = 20
bin["nxpix"] = 200
bin["nypix"] = 200
bin["binsz"] = 0.02
bin["coordsys"] = "CEL"
bin["proj"] = "CAR"
bin["xref"] = 83.63
bin["yref"] = 22.01
# Run tool
self.test_try("Run ctbin")
try:
bin.run()
self.test_try_success()
except:
self.test_try_failure("Exception occured in ctbin.")
# Save counts cube
self.test_try("Save counts cube")
try:
bin.save()
self.test_try_success()
except:
self.test_try_failure("Exception occured in saving counts cube.")
# Return
return
def test_functional(self):
"""
Test ctbin functionnality.
"""
# Set-up ctbin
bin = ctools.ctbin()
bin["inobs"].filename(self.events_name)
bin["outcube"].filename("cntmap.fits")
bin["ebinalg"].string("LOG")
bin["emin"].real(0.1)
bin["emax"].real(100.0)
bin["enumbins"].integer(20)
bin["nxpix"].integer(200)
bin["nypix"].integer(200)
bin["binsz"].real(0.02)
bin["coordsys"].string("CEL")
bin["proj"].string("CAR")
bin["xref"].real(83.63)
bin["yref"].real(22.01)
# Run tool
self.test_try("Run ctbin")
try:
bin.run()
self.test_try_success()
except:
self.test_try_failure("Exception occured in ctbin.")
# Save counts cube
self.test_try("Save counts cube")
try:
bin.save()
self.test_try_success()
except:
self.test_try_failure("Exception occured in saving counts cube.")
# Return
return
def binData(cfg):
"""
bin data with ctbin
"""
outputdir = cfg.getValue('general', 'outputdir')
if cfg.getValue('general', 'anatype') == 'binned':
bdata = ctools.ctbin()
bdata["inobs"] = outputdir + '/' + cfg.getValue('ctselect', 'output')
bdata["outcube"] = outputdir + '/' + cfg.getValue('ctbin', 'output')
bdata["ebinalg"] = "LOG"
bdata["emin"] = cfg.getValue('ctselect', 'emin')
bdata["emax"] = cfg.getValue('ctselect', 'emax')
bdata["enumbins"] = cfg.getValue('ctbin', 'enumbins')
bdata["nxpix"] = cfg.getValue('ctbin', 'nxpix')
bdata["nypix"] = cfg.getValue('ctbin', 'nypix')
bdata["binsz"] = cfg.getValue('ctbin', 'binsz')
bdata["coordsys"] = "CEL"
bdata["proj"] = "AIT"
bdata["xref"] = cfg.getValue('model', 'coords', 'ra')
bdata["yref"] = cfg.getValue('model', 'coords', 'dec')
if cfg.getValue('general', 'debug') is True:
bdata["debug"] = True
bdata.run()
bdata.save()
def stacked_pipeline(model_name, duration):
"""
Stacked analysis pipeline.
"""
# Set script parameters
caldb = "prod2"
irf = "South_50h"
ra = 83.63
dec = 22.01
rad_sim = 10.0
tstart = 0.0
tstop = duration
emin = 0.1
emax = 100.0
enumbins = 40
nxpix = 200
nypix = 200
binsz = 0.02
coordsys = "CEL"
proj = "CAR"
# Get start CPU time
cpu_start = time.clock()
# Simulate events
sim = ctools.ctobssim()
sim["inmodel"] = model_name
sim["caldb"] = caldb
sim["irf"] = irf
sim["ra"] = ra
sim["dec"] = dec
sim["rad"] = rad_sim
sim["tmin"] = tstart
sim["tmax"] = tstop
sim["emin"] = emin
sim["emax"] = emax
sim.run()
# Bin events into counts map
bin = ctools.ctbin(sim.obs())
bin["ebinalg"] = "LOG"
bin["emin"] = emin
bin["emax"] = emax
bin["enumbins"] = enumbins
bin["nxpix"] = nxpix
bin["nypix"] = nypix
bin["binsz"] = binsz
bin["coordsys"] = coordsys
bin["proj"] = proj
bin["xref"] = ra
bin["yref"] = dec
bin.run()
# Create exposure cube
expcube = ctools.ctexpcube(sim.obs())
expcube["incube"] = "NONE"
expcube["caldb"] = caldb
expcube["irf"] = irf
expcube["ebinalg"] = "LOG"
expcube["emin"] = emin
expcube["emax"] = emax
expcube["enumbins"] = enumbins
expcube["nxpix"] = nxpix
expcube["nypix"] = nypix
expcube["binsz"] = binsz
expcube["coordsys"] = coordsys
expcube["proj"] = proj
expcube["xref"] = ra
expcube["yref"] = dec
expcube.run()
# Create PSF cube
psfcube = ctools.ctpsfcube(sim.obs())
psfcube["incube"] = "NONE"
psfcube["caldb"] = caldb
psfcube["irf"] = irf
psfcube["ebinalg"] = "LOG"
psfcube["emin"] = emin
psfcube["emax"] = emax
psfcube["enumbins"] = enumbins
psfcube["nxpix"] = 10
psfcube["nypix"] = 10
psfcube["binsz"] = 1.0
psfcube["coordsys"] = coordsys
psfcube["proj"] = proj
psfcube["xref"] = ra
psfcube["yref"] = dec
psfcube.run()
# Create background cube
bkgcube = ctools.ctbkgcube(sim.obs())
bkgcube["incube"] = "NONE"
bkgcube["ebinalg"] = "LOG"
bkgcube["emin"] = emin
bkgcube["emax"] = emax
bkgcube["enumbins"] = enumbins
bkgcube["nxpix"] = 10
bkgcube["nypix"] = 10
bkgcube["binsz"] = 1.0
bkgcube["coordsys"] = coordsys
bkgcube["proj"] = proj
bkgcube["xref"] = ra
bkgcube["yref"] = dec
bkgcube.run()
# Attach background model to observation container
bin.obs().models(bkgcube.models())
# Set Exposure and Psf cube for first CTA observation
# (ctbin will create an observation with a single container)
bin.obs()[0].response(expcube.expcube(), psfcube.psfcube(), bkgcube.bkgcube())
# Get ctlike start CPU time
cpu_ctlike = time.clock()
# Perform maximum likelihood fitting
like = ctools.ctlike(bin.obs())
like.run()
# Get stop CPU time and compute elapsed times
cpu_stop = time.clock()
cpu_elapsed = cpu_stop - cpu_start
cpu_ctlike = cpu_stop - cpu_ctlike
# Return
return cpu_elapsed, cpu_ctlike
def run(self):
"""
Run the script.
"""
# Switch screen logging on in debug mode
if self._logDebug():
self._log.cout(True)
# Get parameters
self._get_parameters()
# Write observation into logger
if self._logTerse():
self._log("\n")
self._log.header1("Observation")
self._log(str(self._obs))
self._log("\n")
# Use input file directly if given
if self._use_maps:
countmap = gammalib.GSkyMap(self["inobs"].filename())
modelmap = gammalib.GSkyMap(self._modcube)
else:
# ...
if self._skip_binning:
cta_counts_cube = gammalib.GCTAEventCube(self._obs[0].events().clone())
# ...
else:
# Write header
if self._logTerse():
self._log("\n")
self._log.header1("Generate binned map (ctbin)")
# Create countsmap
bin = ctools.ctbin(self._obs)
bin["nxpix"].integer(self._nxpix)
bin["nypix"].integer(self._nypix)
bin["proj"].string(self._proj)
bin["coordsys"].string(self._coordsys)
bin["xref"].real(self._xref)
bin["yref"].real(self._yref)
bin["enumbins"].integer(self._enumbins)
bin["ebinalg"].string(self._ebinalg)
bin["emin"].real(self._emin)
bin["emax"].real(self._emax)
bin["binsz"].real(self._binsz)
bin["chatter"].integer(self._chatter)
bin["clobber"].boolean(self._clobber)
bin["debug"].boolean(self._debug)
bin.run()
# Retrieve counts cube
cta_counts_cube = bin.cube()
# Assign GCTAEventCube to skymap
countmap = cta_counts_cube.counts()
# Write header
if self._logTerse():
self._log("\n")
self._log.header1("Generate model map (ctmodel)")
# Create model map
model = ctools.ctmodel(self._obs)
model.cube(cta_counts_cube)
model["chatter"].integer(self._chatter)
model["clobber"].boolean(self._clobber)
model["debug"].boolean(self._debug)
model["edisp"].boolean(self._edisp)
model.run()
# Get model map into GSkyMap object
modelmap = model.cube().counts().copy()
# Store counts map as residual map. Note that we need a
# special construct here to avoid memory leaks. This seems
# to be a SWIG feature as SWIG creates a new object when
# calling bin.cube()
#residualmap = bin.cube().counts()
self._resmap = countmap.copy()
self._resmap.stack_maps()
modelmap.stack_maps()
# Continue calculations depending on given algorithm
if self._algorithm == "SUB":
# Subtract maps
self._resmap -= modelmap
elif self._algorithm == "SUBDIV":
# Subtract and divide by model map
self._resmap -= modelmap
self._resmap /= modelmap
#for pixel in modelmap:
# if pixel != 0.0:
# pixel = 1.0/pixel
#self._resmap *= modelmap
elif self._algorithm == "SUBDIVSQRT":
# subtract and divide by sqrt of model map
self._resmap -= modelmap
self._resmap /= modelmap.sqrt()
#for pixel in modelmap:
# if pixel != 0.0:
# pixel = 1.0/math.sqrt(pixel)
#self._resmap *= modelmap
else:
# Raise error if algorithm is unkown
raise TypeError("Algorithm \""+self._algorithm+"\" not known")
# Optionally publish map
if self._publish:
self.publish()
# Return
return
def stacked_pipeline(duration):
"""
Cube-style analysis pipeline.
"""
# Set script parameters
model_name = "${CTOOLS}/share/models/crab.xml"
caldb = "prod2"
irf = "South_50h"
ra = 83.63
dec = 22.01
rad_sim = 10.0
tstart = 0.0
tstop = duration
emin = 0.1
emax = 100.0
enumbins = 20
nxpix = 200
nypix = 200
binsz = 0.02
coordsys = "CEL"
proj = "CAR"
# Get start CPU time
tstart = time.clock()
# Simulate events
sim = ctools.ctobssim()
sim["inmodel"].filename(model_name)
sim["caldb"].string(caldb)
sim["irf"].string(irf)
sim["ra"].real(ra)
sim["dec"].real(dec)
sim["rad"].real(rad_sim)
sim["tmin"].real(tstart)
sim["tmax"].real(tstop)
sim["emin"].real(emin)
sim["emax"].real(emax)
sim.run()
# Bin events into counts map
bin = ctools.ctbin(sim.obs())
bin["ebinalg"].string("LOG")
bin["emin"].real(emin)
bin["emax"].real(emax)
bin["enumbins"].integer(enumbins)
bin["nxpix"].integer(nxpix)
bin["nypix"].integer(nypix)
bin["binsz"].real(binsz)
bin["coordsys"].string(coordsys)
bin["proj"].string(proj)
bin["xref"].real(ra)
bin["yref"].real(dec)
bin.run()
# Create exposure cube
expcube = ctools.ctexpcube(sim.obs())
expcube["incube"].filename("NONE")
expcube["caldb"].string(caldb)
expcube["irf"].string(irf)
expcube["ebinalg"].string("LOG")
expcube["emin"].real(emin)
expcube["emax"].real(emax)
expcube["enumbins"].integer(enumbins)
expcube["nxpix"].integer(nxpix)
expcube["nypix"].integer(nypix)
expcube["binsz"].real(binsz)
expcube["coordsys"].string(coordsys)
expcube["proj"].string(proj)
expcube["xref"].real(ra)
expcube["yref"].real(dec)
expcube.run()
# Create PSF cube
psfcube = ctools.ctpsfcube(sim.obs())
psfcube["incube"].filename("NONE")
psfcube["caldb"].string(caldb)
psfcube["irf"].string(irf)
psfcube["ebinalg"].string("LOG")
psfcube["emin"].real(emin)
psfcube["emax"].real(emax)
psfcube["enumbins"].integer(enumbins)
psfcube["nxpix"].integer(10)
psfcube["nypix"].integer(10)
psfcube["binsz"].real(1.0)
psfcube["coordsys"].string(coordsys)
psfcube["proj"].string(proj)
psfcube["xref"].real(ra)
psfcube["yref"].real(dec)
psfcube.run()
# Create background cube
bkgcube = ctools.ctbkgcube(sim.obs())
bkgcube["incube"].filename("NONE")
bkgcube["ebinalg"].string("LOG")
bkgcube["emin"].real(emin)
bkgcube["emax"].real(emax)
bkgcube["enumbins"].integer(enumbins)
bkgcube["nxpix"].integer(10)
bkgcube["nypix"].integer(10)
bkgcube["binsz"].real(1.0)
bkgcube["coordsys"].string(coordsys)
bkgcube["proj"].string(proj)
bkgcube["xref"].real(ra)
bkgcube["yref"].real(dec)
bkgcube.run()
# Attach background model to observation container
bin.obs().models(bkgcube.models())
# Set Exposure and Psf cube for first CTA observation
# (ctbin will create an observation with a single container)
bin.obs()[0].response(expcube.expcube(), psfcube.psfcube(), bkgcube.bkgcube())
# Get ctlike start CPU time
tctlike = time.clock()
# Perform maximum likelihood fitting
like = ctools.ctlike(bin.obs())
like.run()
# Get stop CPU time
tstop = time.clock()
telapsed = tstop - tstart
tctlike = tstop - tctlike
# Return
return telapsed, tctlike
#Move observations to destination folder.Observations are simulated and stored in the present folder, but I prefer to store them somewhere else, so I move them there.
for src_dir, dirs, files in os.walk(PATH_HERE):
dst_dir = PATH_OBS
if not os.path.exists(dst_dir):
os.makedirs(dst_dir)
for file in files:
src_file = os.path.join(PATH_HERE, file)
dst_file = os.path.join(PATH_OBS, file)
if file.endswith('.fits'):
if os.path.exists(dst_file):
os.remove(dst_file)
shutil.move(src_file, PATH_OBS)
# BIN THE DATA
binn = ctools.ctbin()
binn["inobs"] = outfile
binn["outcube"] = cntcube
binn["coordsys"] = "CEL"
binn["proj"] = "CAR"
binn["ebinalg"] = "LOG"
binn["xref"] = centerx
binn["yref"] = centery
binn["nxpix"] = nxpix
binn["nypix"] = nypix
binn["binsz"] = binsz
binn["enumbins"] = enumbins
binn["emin"] = emin
binn["emax"] = emax
binn["debug"] = True
binn.execute()
def run_pipeline(obs,
ra=83.63,
dec=22.01,
emin=0.1,
emax=100.0,
enumbins=20,
nxpix=200,
nypix=200,
binsz=0.02,
coordsys='CEL',
proj='CAR',
model='data/crab.xml',
caldb='prod2',
irf='South_0.5h',
debug=False):
"""
Simulation and stacked analysis pipeline
Parameters
----------
obs : `~gammalib.GObservations`
Observation container
ra : float, optional
Right Ascension of counts cube centre (deg)
dec : float, optional
Declination of Region of counts cube centre (deg)
emin : float, optional
Minimum energy (TeV)
emax : float, optional
Maximum energy (TeV)
enumbins : int, optional
Number of energy bins
nxpix : int, optional
Number of pixels in X axis
nypix : int, optional
Number of pixels in Y axis
binsz : float, optional
Pixel size (deg)
coordsys : str, optional
Coordinate system
proj : str, optional
Coordinate projection
model : str, optional
Model definition XML file
caldb : str, optional
Calibration database path
irf : str, optional
Instrument response function
debug : bool, optional
Debug function
"""
# Simulate events
sim = ctools.ctobssim(obs)
sim['debug'] = debug
sim['outevents'] = 'obs.xml'
sim.execute()
# Bin events into counts map
bin = ctools.ctbin()
bin['inobs'] = 'obs.xml'
bin['outcube'] = 'cntcube.fits'
bin['ebinalg'] = 'LOG'
bin['emin'] = emin
bin['emax'] = emax
bin['enumbins'] = enumbins
bin['nxpix'] = nxpix
bin['nypix'] = nypix
bin['binsz'] = binsz
bin['coordsys'] = coordsys
bin['proj'] = proj
bin['xref'] = ra
bin['yref'] = dec
bin['debug'] = debug
bin.execute()
# Create exposure cube
expcube = ctools.ctexpcube()
expcube['inobs'] = 'obs.xml'
expcube['incube'] = 'cntcube.fits'
expcube['outcube'] = 'expcube.fits'
expcube['caldb'] = caldb
expcube['irf'] = irf
expcube['ebinalg'] = 'LOG'
expcube['emin'] = emin
expcube['emax'] = emax
expcube['enumbins'] = enumbins
expcube['nxpix'] = nxpix
expcube['nypix'] = nypix
expcube['binsz'] = binsz
expcube['coordsys'] = coordsys
expcube['proj'] = proj
expcube['xref'] = ra
expcube['yref'] = dec
expcube['debug'] = debug
expcube.execute()
# Create PSF cube
psfcube = ctools.ctpsfcube()
psfcube['inobs'] = 'obs.xml'
psfcube['incube'] = 'NONE'
psfcube['outcube'] = 'psfcube.fits'
psfcube['caldb'] = caldb
psfcube['irf'] = irf
psfcube['ebinalg'] = 'LOG'
psfcube['emin'] = emin
psfcube['emax'] = emax
psfcube['enumbins'] = enumbins
psfcube['nxpix'] = 10
psfcube['nypix'] = 10
psfcube['binsz'] = 1.0
psfcube['coordsys'] = coordsys
psfcube['proj'] = proj
psfcube['xref'] = ra
psfcube['yref'] = dec
psfcube['debug'] = debug
psfcube.execute()
# Create background cube
bkgcube = ctools.ctbkgcube()
bkgcube['inobs'] = 'obs.xml'
bkgcube['inmodel'] = model
bkgcube['incube'] = 'NONE'
bkgcube['outcube'] = 'bkgcube.fits'
bkgcube['outmodel'] = 'model_bkg.xml'
bkgcube['caldb'] = caldb
bkgcube['irf'] = irf
bkgcube['ebinalg'] = 'LOG'
bkgcube['emin'] = emin
bkgcube['emax'] = emax
bkgcube['enumbins'] = enumbins
bkgcube['nxpix'] = 10
bkgcube['nypix'] = 10
bkgcube['binsz'] = 1.0
bkgcube['coordsys'] = coordsys
bkgcube['proj'] = proj
bkgcube['xref'] = ra
bkgcube['yref'] = dec
bkgcube['debug'] = debug
bkgcube.execute()
# Perform maximum likelihood fitting
like = ctools.ctlike()
like['inobs'] = 'cntcube.fits'
like['inmodel'] = 'model_bkg.xml'
like['outmodel'] = 'fit_results.xml'
like['expcube'] = 'expcube.fits'
like['psfcube'] = 'psfcube.fits'
like['bkgcube'] = 'bkgcube.fits'
like['caldb'] = caldb
like['irf'] = irf
like['debug'] = True # Switch this always on for results in console
like.execute()
# Return
return
def sim(obs, log=False, debug=False, chatter=2, edisp=False, seed=0,
emin=None, emax=None, nbins=0, onsrc=None, onrad=0.2, addbounds=False,
binsz=0.05, npix=200, proj='TAN', coord='GAL'):
"""
Simulate events for all observations in the container
Simulate events for all observations using ctobssim. If the number of
energy bins is positive, the events are binned into a counts cube using
ctbin. If multiple observations are simulated, the counts cube is a
stacked cube and the corresponding response cubes are computed using
ctexpcube, ctpsfcube, ctbkgcube and optionally ctedispcube. The response
cubes are attached to the first observation in the container, which
normally is the observation with the counts cube.
Parameters
----------
obs : `~gammalib.GObservations`
Observation container without events
log : bool, optional
Create log file(s)
debug : bool, optional
Create console dump?
chatter : int, optional
Chatter level
edisp : bool, optional
Apply energy dispersion?
seed : int, optional
Seed value for simulations
emin : float, optional
Minimum energy of counts cube for binned (TeV)
emax : float, optional
Maximum energy of counts cube for binned (TeV)
nbins : int, optional
Number of energy bins (0=unbinned)
onsrc : str, optional
Name of source for On region (None if no On/Off obs. is used)
onrad : float, optional
Radius for On region (deg)
addbounds : bool, optional
Add boundaries at observation energies
binsz : float, optional
Pixel size for binned simulation (deg/pixel)
npix : int, optional
Number of pixels in X and Y for binned simulation
proj : str, optional
Projection for binned simulation
coord : str, optional
Coordinate system for binned simulation
Returns
-------
obs : `~gammalib.GObservations`
Observation container filled with simulated events
"""
# Allocate ctobssim application and set parameters
obssim = ctools.ctobssim(obs)
obssim['seed'] = seed
obssim['edisp'] = edisp
obssim['chatter'] = chatter
obssim['debug'] = debug
# Optionally open the log file
if log:
obssim.logFileOpen()
# Run ctobssim application. This will loop over all observations in the
# container and simulation the events for each observation. Note that
# events are not added together, they still apply to each observation
# separately.
obssim.run()
# Binned option?
if nbins > 0:
# If energy boundaries are not given then determine the minimum and
# the maximum energies from all observations and use these values
# as energy boundaries. The energy boundaries are given in TeV.
if emin == None or emax == None:
emin = 1.0e30
emax = 0.0
for run in obssim.obs():
emin = min(run.events().ebounds().emin().TeV(), emin)
emax = max(run.events().ebounds().emax().TeV(), emax)
# If a On source is specified then create On/Off observations
if onsrc != None:
# Extract source position from model
model = obssim.obs().models()[onsrc]
ra = model['RA'].value()
dec = model['DEC'].value()
# Allocate csphagen application and set parameters
phagen = cscripts.csphagen(obssim.obs())
phagen['ebinalg'] = 'LOG'
phagen['emin'] = emin
phagen['emax'] = emax
phagen['enumbins'] = nbins
phagen['coordsys'] = 'CEL'
phagen['ra'] = ra
phagen['dec'] = dec
phagen['rad'] = onrad
phagen['stack'] = False
phagen['inexclusion'] = 'NONE'
phagen['bkgmethod'] = 'REFLECTED'
# Optionally open the log file
if log:
phagen.logFileOpen()
# Run csphagen application
phagen.run()
# Make a deep copy of the observation that will be returned
# (the csphagen object will go out of scope one the function is
# left)
obs = phagen.obs().copy()
# ... otherwise use binned observations
else:
# Allocate ctbin application and set parameters
binning = ctools.ctbin(obssim.obs())
binning['ebinalg'] = 'LOG'
binning['emin'] = emin
binning['emax'] = emax
binning['enumbins'] = nbins
binning['usepnt'] = True # Use pointing for map centre
binning['nxpix'] = npix
binning['nypix'] = npix
binning['binsz'] = binsz
binning['coordsys'] = coord
binning['proj'] = proj
binning['chatter'] = chatter
binning['debug'] = debug
# Optionally open the log file
if log:
binning.logFileOpen()
# Run ctbin application. This will loop over all observations in
# the container and bin the events in counts maps
binning.run()
# If we have multiple input observations then create stacked response
# cubes and append them to the observation
if len(obssim.obs()) > 1:
# Get stacked response (use pointing for map centre)
response = get_stacked_response(obssim.obs(), None, None,
binsz=binsz, nxpix=npix, nypix=npix,
emin=emin, emax=emax, enumbins=nbins,
edisp=edisp,
coordsys=coord, proj=proj,
addbounds=addbounds,
log=log, debug=debug,
chatter=chatter)
# Set stacked response
if edisp:
binning.obs()[0].response(response['expcube'],
response['psfcube'],
response['edispcube'],
response['bkgcube'])
else:
binning.obs()[0].response(response['expcube'],
response['psfcube'],
response['bkgcube'])
# Set new models
binning.obs().models(response['models'])
# Make a deep copy of the observation that will be returned
# (the ctbin object will go out of scope one the function is
# left)
obs = binning.obs().copy()
else:
# Make a deep copy of the observation that will be returned
# (the ctobssim object will go out of scope one the function is
# left)
obs = obssim.obs().copy()
# Delete the simulation
del obssim
# Return observation container
return obs
def run_pipeline(self, debug=False, seed=0):
"""
Test unbinned pipeline with FITS file saving
"""
# Set script parameters
events_name = 'events.fits'
cubefile_name = ''
selected_events_name = 'selected_events.fits'
result_name = 'results.xml'
if self.simfilename and self.eventfilename:
print('error')
exit(10)
############ Simulate events
if self.simfilename:
# Setup simulation model
if self.simfilename:
self.obs.models(gammalib.GModels(self.simfilename))
if self.runconf.WorkInMemory == 0:
print('# Generate simulated event list on disk')
# Simulate events on disk
sim = ctools.ctobssim(self.obs)
sim['outevents'] = events_name
sim['debug'] = debug
sim['seed'] = seed
sim.execute()
self.eventfilename = events_name
if self.runconf.WorkInMemory == 1:
print('# Generate simulated event list in memory')
# Simulate events on memory
sim = ctools.ctobssim(self.obs)
sim['debug'] = debug
sim['seed'] = seed
sim.run()
#if self.runfilename is not present
# import into DB if any
# exit(0)
############ Get events from DB
if not self.simfilename and not self.eventfilename:
#load from DB
print('# Load event list from DB')
#write selected_events_name
if self.runconf.timeref_timesys == 'tt':
tstart_tt = self.runconf.tmin
tstop_tt = self.runconf.tmax
if self.runconf.timeref_timesys == 'mjd':
tstart_tt = Utility.convert_mjd_to_tt(self.runconf.tmin)
tstop_tt = Utility.convert_mjd_to_tt(self.runconf.tmax)
#tstart_tt = self.runconf.tmin
#tstop_tt = self.runconf.tmax
observationid = self.obsconf.id
print("tstart" + str(tstart_tt))
print("tstop" + str(tstart_tt))
print(self.runconf.timeref_timesys)
conf_dictionary = get_path_conf()
path_base_fits = conf_dictionary['path_base_fits']
tref_mjd = self.runconf.timeref
if self.runconf.roi_frame == 'fk5':
obs_ra = self.obsconf.roi_ra
obs_dec = self.obsconf.roi_dec
else:
exit(10)
emin = self.runconf.emin
emax = self.runconf.emax
fov = self.obsconf.roi_fov
instrumentname = self.obsconf.instrument
datarepository_dictionary = get_data_repository(instrumentname)
datarepositoryid = datarepository_dictionary['datarepositoryid']
print("before write fits")
print(datetime.utcnow().strftime('%Y-%m-%d %H:%M:%S.%f')[:-3])
events_name = write_fits(tstart_tt, tstop_tt, observationid,
datarepositoryid, path_base_fits,
tref_mjd, obs_ra, obs_dec, emin, emax,
180, instrumentname)
print("after write fits")
print(datetime.utcnow().strftime('%Y-%m-%d %H:%M:%S.%f')[:-3])
print("fitsname" + events_name)
if self.runconf.WorkInMemory == 2:
print('# Load event list from disk')
#Load events from fits file on memory
sim = ctools.ctobssim(self.obs)
events = sim.obs()[0].events()
for event in events:
print(event)
#events.load(events_name)
events.load(selected_events_name)
############ Select events
if self.runconf.WorkInMemory == 1:
print('# Select event list in memory')
select = ctools.ctselect(sim.obs())
#using file
if self.runconf.WorkInMemory == 0:
print('# Select event list from disk')
select = ctools.ctselect()
select['inobs'] = events_name
select['outobs'] = selected_events_name
select['ra'] = self.runconf.roi_ra
select['dec'] = self.runconf.roi_dec
select['rad'] = self.runconf.roi_ringrad
select['tmin'] = 'MJD ' + str(self.runconf.tmin)
#select['tmin'] = 'INDEF'
#select['tmin'] = 0.0
#select['tmin'] = 'MJD 55197.0007660185'
#select['tmax'] = self.runconf.tmax
#select['tmax'] = 'INDEF'
select['tmax'] = 'MJD ' + str(self.runconf.tmax)
#select['tmax'] = 55197.0007660185 + self.runconf.tmax / 86400.
select['emin'] = self.runconf.emin
select['emax'] = self.runconf.emax
if self.runconf.WorkInMemory == 1:
select.run()
if self.runconf.WorkInMemory == 0:
select.execute()
print("after select events")
print(datetime.utcnow().strftime('%Y-%m-%d %H:%M:%S.%f')[:-3])
#print(self.runconf.roi_ra)
#print(self.runconf.roi_dec)
#print(self.obsconf.obs_fov)
#print(self.runconf.tmin)
#print(self.runconf.tmax)
#print(self.runconf.emin)
#print(self.runconf.emax)
#print(select.obs()[0])
print("select --")
print(select)
print("select --")
if self.runconf.WorkInMemory == 2:
print('# Load event list from disk')
#Load events from fits file on memory
sim = ctools.ctobssim(self.obs)
events = sim.obs()[0].events()
for event in events:
print(event)
#events.load(events_name)
events.load(selected_events_name)
print('Event list generated ----------------------')
if self.runconf.WorkInMemory == 0:
print(self.obs)
print("obs --")
print(self.obs[0])
print("obs 0 --")
localobs = self.obs
if self.runconf.WorkInMemory == 1:
print(select.obs())
print(select.obs()[0])
localobs = select.obs()
for run in localobs:
print('run ---' + selected_events_name)
print("before ctbin")
print(datetime.utcnow().strftime('%Y-%m-%d %H:%M:%S.%f')[:-3])
print(run)
# Create container with a single observation
container = gammalib.GObservations()
container.append(run)
if self.runconf.MakeCtsMap == 1:
cubefile_name = 'cube.fits'
#event file in memory or read from fits file on memory
if self.runconf.WorkInMemory == 1:
bin = ctools.ctbin(container)
if self.runconf.WorkInMemory == 0:
#event file on disk
bin = ctools.ctbin()
bin['inobs'] = selected_events_name
#make binned map on disk
bin['outcube'] = cubefile_name
#common configs
bin['ebinalg'] = self.runconf.cts_ebinalg
bin['emin'] = self.runconf.emin
bin['emax'] = self.runconf.emax
bin['enumbins'] = self.runconf.cts_enumbins
bin['nxpix'] = ceil(self.runconf.roi_ringrad * 2 /
self.runconf.cts_binsz)
bin['nypix'] = ceil(self.runconf.roi_ringrad * 2 /
self.runconf.cts_binsz)
bin['binsz'] = self.runconf.cts_binsz
bin['coordsys'] = self.runconf.cts_coordsys
bin['usepnt'] = self.runconf.cts_usepnt # Use pointing for map centre
bin['proj'] = self.runconf.cts_proj
bin['xref'] = self.runconf.roi_ra
bin['yref'] = self.runconf.roi_dec
print("-- bin")
print(bin)
#make binned map on disk
if self.runconf.WorkInMemory == 0:
bin.execute()
# Set observation ID if make binned map on disk
bin.obs()[0].id(cubefile_name)
bin.obs()[0].eventfile(cubefile_name)
os.system('mkdir -p ' + self.runconf.resdir)
shutil.copy(
'./cube.fits', self.runconf.resdir + '/' +
self.runconf.runprefix + '_cube.fits')
if self.runconf.CtsMapToPng == 1:
title = 'OBS ' + str(
self.obsconf.id) + ' / MJD ' + str(
self.runconf.tmin) + ' - ' + 'MJD ' + str(
self.runconf.tmax)
SkyImage.display(cubefile_name, "sky1.png", 2, title)
#SkyImage.dispalywithds9_cts1(cubefile_name, "sky2", 10)
#copy results
os.system('mkdir -p ' + self.runconf.resdir)
shutil.copy(
'./sky1.png', self.runconf.resdir + '/' +
self.runconf.runprefix + '_sky1.png')
#make binned map on memory
if self.runconf.WorkInMemory == 1:
bin.run()
# Append result to observations
#localobs.extend(bin.obs())
print("after ctbin")
print(datetime.utcnow().strftime('%Y-%m-%d %H:%M:%S.%f')[:-3])
#print(obs)
#print(obs[0])
print(str(self.obsconf.caldb))
#hypothesis builders
#3GHextractor
# 3GH Extractor code
if self.runconf.HypothesisGenerator3GH and cubefile_name:
self.analysisfilename = CTA3GHextractor_wrapper.extract_source(
cubefile_name)
print(self.analysisfilename)
#cv2.waitKey(0)
print('HypothesisGeneratorEG3')
#eseguire MLE
print('analysisfilename: ' + self.analysisfilename)
if self.analysisfilename:
print('before MLE')
print(datetime.utcnow().strftime('%Y-%m-%d %H:%M:%S.%f')[:-3])
# Perform maximum likelihood fitting
if self.runconf.WorkInMemory == 1:
like = ctools.ctlike(select.obs())
if self.runconf.WorkInMemory == 0:
like = ctools.ctlike()
if (self.runconf.binned == "1"):
like['inobs'] = cubefile_name
like['expcube'] = "NONE"
like['psfcube'] = "NONE"
like['edispcube'] = "NONE"
like['bkgcube'] = "NONE"
like['statistic'] = "CHI2"
if (self.runconf.binned == "0"):
like['inobs'] = selected_events_name
like['statistic'] = "DEFAULT"
like['inmodel'] = self.analysisfilename
like['outmodel'] = result_name
like['caldb'] = str(self.obsconf.caldb)
like['irf'] = self.obsconf.irf
like.execute()
print(like)
logL = like.opt().value()
print(like.obs().models())
print("after MLE")
print(datetime.utcnow().strftime('%Y-%m-%d %H:%M:%S.%f')[:-3])
# insert logL into results.xml
tree = etree.parse(result_name)
contentnav = tree.find(".//source[@type='PointSource']")
#contentdiv = contentnav.getparent()
#contentnav.set("ts",str(logL))
contentnav.set("runid", str(self.runconf.runid))
#print(etree.tostring(tree,encoding="unicode",pretty_print=True))
f = open(result_name, 'w')
f.write(
etree.tostring(tree, encoding="unicode",
pretty_print=True))
f.close()
os.system('mkdir -p ' + self.runconf.resdir)
shutil.copy(
'./results.xml', self.runconf.resdir + '/' +
self.runconf.runprefix + '_results.xml')
if self.runconf.deleterun == "1":
cmd = 'rm -r ' + self.runconf.rundir
os.system(cmd)
if self.runconf.HypothesisGenerator3GH:
CTA3GHextractor_wrapper.print_graphs(self.simfilename,
result_name,
self.analysisfilename)
#cv2.destroyAllWindows()
print('HypothesisGeneratorEG3')
# Return
return
def stacked_pipeline(model_name, duration):
"""
Stacked analysis pipeline.
"""
# Set script parameters
caldb = "prod2"
irf = "South_50h"
ra = 83.63
dec = 22.01
rad_sim = 10.0
tstart = 0.0
tstop = duration
emin = 0.1
emax = 100.0
enumbins = 40
nxpix = 200
nypix = 200
binsz = 0.02
coordsys = "CEL"
proj = "CAR"
# Get start CPU time
cpu_start = time.clock()
# Simulate events
sim = ctools.ctobssim()
sim["inmodel"] = model_name
sim["caldb"] = caldb
sim["irf"] = irf
sim["ra"] = ra
sim["dec"] = dec
sim["rad"] = rad_sim
sim["tmin"] = tstart
sim["tmax"] = tstop
sim["emin"] = emin
sim["emax"] = emax
sim.run()
# Bin events into counts map
bin = ctools.ctbin(sim.obs())
bin["ebinalg"] = "LOG"
bin["emin"] = emin
bin["emax"] = emax
bin["enumbins"] = enumbins
bin["nxpix"] = nxpix
bin["nypix"] = nypix
bin["binsz"] = binsz
bin["coordsys"] = coordsys
bin["proj"] = proj
bin["xref"] = ra
bin["yref"] = dec
bin.run()
# Create exposure cube
expcube = ctools.ctexpcube(sim.obs())
expcube["incube"] = "NONE"
expcube["caldb"] = caldb
expcube["irf"] = irf
expcube["ebinalg"] = "LOG"
expcube["emin"] = emin
expcube["emax"] = emax
expcube["enumbins"] = enumbins
expcube["nxpix"] = nxpix
expcube["nypix"] = nypix
expcube["binsz"] = binsz
expcube["coordsys"] = coordsys
expcube["proj"] = proj
expcube["xref"] = ra
expcube["yref"] = dec
expcube.run()
# Create PSF cube
psfcube = ctools.ctpsfcube(sim.obs())
psfcube["incube"] = "NONE"
psfcube["caldb"] = caldb
psfcube["irf"] = irf
psfcube["ebinalg"] = "LOG"
psfcube["emin"] = emin
psfcube["emax"] = emax
psfcube["enumbins"] = enumbins
psfcube["nxpix"] = 10
psfcube["nypix"] = 10
psfcube["binsz"] = 1.0
psfcube["coordsys"] = coordsys
psfcube["proj"] = proj
psfcube["xref"] = ra
psfcube["yref"] = dec
psfcube.run()
# Create background cube
bkgcube = ctools.ctbkgcube(sim.obs())
bkgcube["incube"] = "NONE"
bkgcube["ebinalg"] = "LOG"
bkgcube["emin"] = emin
bkgcube["emax"] = emax
bkgcube["enumbins"] = enumbins
bkgcube["nxpix"] = 10
bkgcube["nypix"] = 10
bkgcube["binsz"] = 1.0
bkgcube["coordsys"] = coordsys
bkgcube["proj"] = proj
bkgcube["xref"] = ra
bkgcube["yref"] = dec
bkgcube.run()
# Attach background model to observation container
bin.obs().models(bkgcube.models())
# Set Exposure and Psf cube for first CTA observation
# (ctbin will create an observation with a single container)
bin.obs()[0].response(expcube.expcube(), psfcube.psfcube(),
bkgcube.bkgcube())
# Get ctlike start CPU time
cpu_ctlike = time.clock()
# Perform maximum likelihood fitting
like = ctools.ctlike(bin.obs())
like.run()
# Get stop CPU time and compute elapsed times
cpu_stop = time.clock()
cpu_elapsed = cpu_stop - cpu_start
cpu_ctlike = cpu_stop - cpu_ctlike
# Return
return cpu_elapsed, cpu_ctlike
def sim(obs,
log=False,
debug=False,
chatter=2,
edisp=False,
seed=0,
emin=None,
emax=None,
nbins=0,
onsrc=None,
onrad=0.2,
addbounds=False,
binsz=0.05,
npix=200,
proj='TAN',
coord='GAL'):
"""
Simulate events for all observations in the container
Simulate events for all observations using ctobssim. If the number of
energy bins is positive, the events are binned into a counts cube using
ctbin. If multiple observations are simulated, the counts cube is a
stacked cube and the corresponding response cubes are computed using
ctexpcube, ctpsfcube, ctbkgcube and optionally ctedispcube. The response
cubes are attached to the first observation in the container, which
normally is the observation with the counts cube.
Parameters
----------
obs : `~gammalib.GObservations`
Observation container without events
log : bool, optional
Create log file(s)
debug : bool, optional
Create console dump?
chatter : int, optional
Chatter level
edisp : bool, optional
Apply energy dispersion?
seed : int, optional
Seed value for simulations
emin : float, optional
Minimum energy of counts cube for binned (TeV)
emax : float, optional
Maximum energy of counts cube for binned (TeV)
nbins : int, optional
Number of energy bins (0=unbinned)
onsrc : str, optional
Name of source for On region (None if no On/Off obs. is used)
onrad : float, optional
Radius for On region (deg)
addbounds : bool, optional
Add boundaries at observation energies
binsz : float, optional
Pixel size for binned simulation (deg/pixel)
npix : int, optional
Number of pixels in X and Y for binned simulation
proj : str, optional
Projection for binned simulation
coord : str, optional
Coordinate system for binned simulation
Returns
-------
obs : `~gammalib.GObservations`
Observation container filled with simulated events
"""
# Allocate ctobssim application and set parameters
obssim = ctools.ctobssim(obs)
obssim['seed'] = seed
obssim['edisp'] = edisp
obssim['chatter'] = chatter
obssim['debug'] = debug
# Optionally open the log file
if log:
obssim.logFileOpen()
# Run ctobssim application. This will loop over all observations in the
# container and simulation the events for each observation. Note that
# events are not added together, they still apply to each observation
# separately.
obssim.run()
# Binned option?
if nbins > 0:
# If energy boundaries are not given then determine the minimum and
# the maximum energies from all observations and use these values
# as energy boundaries. The energy boundaries are given in TeV.
if emin == None or emax == None:
emin = 1.0e30
emax = 0.0
for run in obssim.obs():
emin = min(run.events().ebounds().emin().TeV(), emin)
emax = max(run.events().ebounds().emax().TeV(), emax)
# If a On source is specified then create On/Off observations
if onsrc != None:
# Extract source position from model
model = obssim.obs().models()[onsrc]
ra = model['RA'].value()
dec = model['DEC'].value()
# Allocate csphagen application and set parameters
phagen = cscripts.csphagen(obssim.obs())
phagen['ebinalg'] = 'LOG'
phagen['emin'] = emin
phagen['emax'] = emax
phagen['enumbins'] = nbins
phagen['coordsys'] = 'CEL'
phagen['ra'] = ra
phagen['dec'] = dec
phagen['rad'] = onrad
phagen['stack'] = False
phagen['inexclusion'] = 'NONE'
# Optionally open the log file
if log:
phagen.logFileOpen()
# Run csphagen application
phagen.run()
# Make a deep copy of the observation that will be returned
# (the csphagen object will go out of scope one the function is
# left)
obs = phagen.obs().copy()
# ... otherwise use binned observations
else:
# Allocate ctbin application and set parameters
binning = ctools.ctbin(obssim.obs())
binning['ebinalg'] = 'LOG'
binning['emin'] = emin
binning['emax'] = emax
binning['enumbins'] = nbins
binning['usepnt'] = True # Use pointing for map centre
binning['nxpix'] = npix
binning['nypix'] = npix
binning['binsz'] = binsz
binning['coordsys'] = coord
binning['proj'] = proj
binning['chatter'] = chatter
binning['debug'] = debug
# Optionally open the log file
if log:
binning.logFileOpen()
# Run ctbin application. This will loop over all observations in
# the container and bin the events in counts maps
binning.run()
# If we have multiple input observations then create stacked response
# cubes and append them to the observation
if len(obssim.obs()) > 1:
# Get stacked response (use pointing for map centre)
response = get_stacked_response(obssim.obs(),
None,
None,
binsz=binsz,
nxpix=npix,
nypix=npix,
emin=emin,
emax=emax,
enumbins=nbins,
edisp=edisp,
coordsys=coord,
proj=proj,
addbounds=addbounds,
log=log,
debug=debug,
chatter=chatter)
# Set stacked response
if edisp:
binning.obs()[0].response(response['expcube'],
response['psfcube'],
response['edispcube'],
response['bkgcube'])
else:
binning.obs()[0].response(response['expcube'],
response['psfcube'],
response['bkgcube'])
# Set new models
binning.obs().models(response['models'])
# Make a deep copy of the observation that will be returned
# (the ctbin object will go out of scope one the function is
# left)
obs = binning.obs().copy()
else:
# Make a deep copy of the observation that will be returned
# (the ctobssim object will go out of scope one the function is
# left)
obs = obssim.obs().copy()
# Delete the simulation
del obssim
# Return observation container
return obs
def sim(obs,
log=False,
debug=False,
chatter=2,
edisp=False,
seed=0,
nbins=31,
binsz=0.02,
npix=50,
proj="CAR",
coord="CEL",
outfile=""):
"""
Simulate events for all observations in the container.
Parameters:
obs - Observation container
Keywords:
log - Create log file(s)
debug - Create console dump?
edisp - Apply energy dispersion?
seed - Seed value for simulations (default: 0)
nbins - Number of energy bins (default: 0=unbinned)
binsz - Pixel size for binned simulation (deg/pixel)
npix - Number of pixels in X and Y for binned simulation
"""
# Allocate ctobssim application and set parameters
sim = ctools.ctobssim(obs)
sim["seed"] = seed
sim["edisp"] = edisp
sim["outevents"] = outfile
sim['nthreads'] = 2
# Optionally open the log file
if log:
sim.logFileOpen()
# Optionally switch-on debugging model
if debug:
sim["debug"] = True
# Set chatter level
sim["chatter"] = chatter
# Run ctobssim application. This will loop over all observations in the
# container and simulation the events for each observation. Note that
# events are not added together, they still apply to each observation
# separately.
sim.run()
# Binned option?
if nbins > 0:
# Determine common energy boundaries for observations
emin = None
emax = None
for run in sim.obs():
run_emin = run.events().ebounds().emin().TeV()
run_emax = run.events().ebounds().emax().TeV()
if emin == None:
emin = run_emin
elif run_emin > emin:
emin = run_emin
if emax == None:
emax = run_emax
elif run_emax > emax:
emax = run_emax
# Allocate ctbin application and set parameters
bin = ctools.ctbin(sim.obs())
bin["ebinalg"] = "LOG"
bin["emin"] = emin
bin["emax"] = emax
bin["enumbins"] = nbins
bin["usepnt"] = True # Use pointing for map centre
bin["nxpix"] = npix
bin["nypix"] = npix
bin["binsz"] = binsz
bin["coordsys"] = coord
bin["proj"] = proj
bin['nthreads'] = 2
# Optionally open the log file
if log:
bin.logFileOpen()
# Optionally switch-on debugging model
if debug:
bin["debug"] = True
# Set chatter level
bin["chatter"] = chatter
# Run ctbin application. This will loop over all observations in
# the container and bin the events in counts maps
bin.run()
# Make a deep copy of the observation that will be returned
# (the ctbin object will go out of scope one the function is
# left)
obs = bin.obs().copy()
else:
# Make a deep copy of the observation that will be returned
# (the ctobssim object will go out of scope one the function is
# left)
obs = sim.obs().copy()
# Optionally save file
if (len(outfile) > 0):
sim.save()
# Delete the simulation
del sim
# Return observation container
return obs
def get_stacked_obs(cls, obs):
"""
Bin an observation and return an observation container with a single
binned observation
Parameters
----------
cls : `~ctools.cscript`
cscript class
obs : `~gammalib.GObservations`
Observation container
Returns
-------
obs : `~gammalib.GObservations`
Observation container where the first observation is a binned observation
"""
# Write header
if cls._logExplicit():
cls._log.header3('Binning events')
# Bin events
cntcube = ctools.ctbin(obs)
cntcube['usepnt'] = False
cntcube['ebinalg'] = 'LOG'
cntcube['xref'] = cls['xref'].real()
cntcube['yref'] = cls['yref'].real()
cntcube['binsz'] = cls['binsz'].real()
cntcube['nxpix'] = cls['nxpix'].integer()
cntcube['nypix'] = cls['nypix'].integer()
cntcube['enumbins'] = cls['enumbins'].integer()
cntcube['emin'] = cls['emin'].real()
cntcube['emax'] = cls['emax'].real()
cntcube['coordsys'] = cls['coordsys'].string()
cntcube['proj'] = cls['proj'].string()
cntcube.run()
# Write header
if cls._logExplicit():
cls._log.header3('Creating stacked response')
# Get stacked response
response = get_stacked_response(obs,
cls['xref'].real(),
cls['yref'].real(),
binsz=cls['binsz'].real(),
nxpix=cls['nxpix'].integer(),
nypix=cls['nypix'].integer(),
emin=cls['emin'].real(),
emax=cls['emax'].real(),
enumbins=cls['enumbins'].integer(),
edisp=cls['edisp'].boolean(),
coordsys=cls['coordsys'].string(),
proj=cls['proj'].string())
# Retrieve a new oberservation container
new_obs = cntcube.obs().copy()
# Set stacked response
if cls['edisp'].boolean():
new_obs[0].response(response['expcube'], response['psfcube'],
response['edispcube'], response['bkgcube'])
else:
new_obs[0].response(response['expcube'], response['psfcube'],
response['bkgcube'])
# Get new models
models = response['models']
# Set models for new oberservation container
new_obs.models(models)
# Return new oberservation container
return new_obs
def run_pipeline(obs, ra=83.63, dec=22.01, emin=0.1, emax=100.0, \
enumbins=20, nxpix=200, nypix=200, binsz=0.02, \
coordsys="CEL", proj="CAR", debug=False):
"""
Simulation and stacked analysis pipeline.
Keywords:
ra - RA of cube centre [deg] (default: 83.6331)
dec - DEC of cube centre [deg] (default: 22.0145)
emin - Minimum energy of cube [TeV] (default: 0.1)
emax - Maximum energy of cube [TeV] (default: 100.0)
enumbins - Number of energy bins in cube (default: 20)
nxpix - Number of RA pixels in cube (default: 200)
nypix - Number of DEC pixels in cube (default: 200)
binsz - Spatial cube bin size [deg] (default: 0.02)
coordsys - Cube coordinate system (CEL or GAL)
proj - Cube World Coordinate System (WCS) projection
debug - Enable debugging (default: False)
"""
# Simulate events
sim = ctools.ctobssim(obs)
sim["debug"].boolean(debug)
sim.run()
# Bin events into counts map
bin = ctools.ctbin(sim.obs())
bin["ebinalg"].string("LOG")
bin["emin"].real(emin)
bin["emax"].real(emax)
bin["enumbins"].integer(enumbins)
bin["nxpix"].integer(nxpix)
bin["nypix"].integer(nypix)
bin["binsz"].real(binsz)
bin["coordsys"].string(coordsys)
bin["proj"].string(proj)
bin["xref"].real(ra)
bin["yref"].real(dec)
bin["debug"].boolean(debug)
bin.run()
# Create exposure cube
expcube = ctools.ctexpcube(sim.obs())
expcube["incube"].filename("NONE")
expcube["ebinalg"].string("LOG")
expcube["emin"].real(emin)
expcube["emax"].real(emax)
expcube["enumbins"].integer(enumbins)
expcube["nxpix"].integer(nxpix)
expcube["nypix"].integer(nypix)
expcube["binsz"].real(binsz)
expcube["coordsys"].string(coordsys)
expcube["proj"].string(proj)
expcube["xref"].real(ra)
expcube["yref"].real(dec)
expcube["debug"].boolean(debug)
expcube.run()
# Create PSF cube
psfcube = ctools.ctpsfcube(sim.obs())
psfcube["incube"].filename("NONE")
psfcube["ebinalg"].string("LOG")
psfcube["emin"].real(emin)
psfcube["emax"].real(emax)
psfcube["enumbins"].integer(enumbins)
psfcube["nxpix"].integer(10)
psfcube["nypix"].integer(10)
psfcube["binsz"].real(1.0)
psfcube["coordsys"].string(coordsys)
psfcube["proj"].string(proj)
psfcube["xref"].real(ra)
psfcube["yref"].real(dec)
psfcube["debug"].boolean(debug)
psfcube.run()
# Create background cube
bkgcube = ctools.ctbkgcube(sim.obs())
bkgcube["incube"].filename("NONE")
bkgcube["ebinalg"].string("LOG")
bkgcube["emin"].real(emin)
bkgcube["emax"].real(emax)
bkgcube["enumbins"].integer(enumbins)
bkgcube["nxpix"].integer(10)
bkgcube["nypix"].integer(10)
bkgcube["binsz"].real(1.0)
bkgcube["coordsys"].string(coordsys)
bkgcube["proj"].string(proj)
bkgcube["xref"].real(ra)
bkgcube["yref"].real(dec)
bkgcube["debug"].boolean(debug)
bkgcube.run()
# Attach background model to observation container
bin.obs().models(bkgcube.models())
# Set Exposure and Psf cube for first CTA observation
# (ctbin will create an observation with a single container)
bin.obs()[0].response(expcube.expcube(), psfcube.psfcube(), bkgcube.bkgcube())
# Perform maximum likelihood fitting
like = ctools.ctlike(bin.obs())
like["debug"].boolean(True) # Switch this always on for results in console
like.run()
# Return
return
def run_pipeline(obs, ra=83.63, dec=22.01, emin=0.1, emax=100.0, \
enumbins=20, nxpix=200, nypix=200, binsz=0.02, \
coordsys="CEL", proj="CAR", \
model="${CTOOLS}/share/models/crab.xml", \
caldb="prod2", irf="South_50h", \
debug=False):
"""
Simulation and stacked analysis pipeline.
Keywords:
ra - RA of cube centre [deg] (default: 83.6331)
dec - DEC of cube centre [deg] (default: 22.0145)
emin - Minimum energy of cube [TeV] (default: 0.1)
emax - Maximum energy of cube [TeV] (default: 100.0)
enumbins - Number of energy bins in cube (default: 20)
nxpix - Number of RA pixels in cube (default: 200)
nypix - Number of DEC pixels in cube (default: 200)
binsz - Spatial cube bin size [deg] (default: 0.02)
coordsys - Cube coordinate system (CEL or GAL)
proj - Cube World Coordinate System (WCS) projection
debug - Enable debugging (default: False)
"""
# Simulate events
sim = ctools.ctobssim(obs)
sim["debug"].boolean(debug)
sim["outevents"].filename("obs.xml")
sim.execute()
# Bin events into counts map
bin = ctools.ctbin()
bin["inobs"].filename("obs.xml")
bin["outcube"].filename("cntcube.fits")
bin["ebinalg"].string("LOG")
bin["emin"].real(emin)
bin["emax"].real(emax)
bin["enumbins"].integer(enumbins)
bin["nxpix"].integer(nxpix)
bin["nypix"].integer(nypix)
bin["binsz"].real(binsz)
bin["coordsys"].string(coordsys)
bin["proj"].string(proj)
bin["xref"].real(ra)
bin["yref"].real(dec)
bin["debug"].boolean(debug)
bin.execute()
# Create exposure cube
expcube = ctools.ctexpcube()
expcube["inobs"].filename("obs.xml")
expcube["incube"].filename("cntcube.fits")
expcube["outcube"].filename("expcube.fits")
expcube["caldb"].string(caldb)
expcube["irf"].string(irf)
expcube["ebinalg"].string("LOG")
expcube["emin"].real(emin)
expcube["emax"].real(emax)
expcube["enumbins"].integer(enumbins)
expcube["nxpix"].integer(nxpix)
expcube["nypix"].integer(nypix)
expcube["binsz"].real(binsz)
expcube["coordsys"].string(coordsys)
expcube["proj"].string(proj)
expcube["xref"].real(ra)
expcube["yref"].real(dec)
expcube["debug"].boolean(debug)
expcube.execute()
# Create PSF cube
psfcube = ctools.ctpsfcube()
psfcube["inobs"].filename("obs.xml")
psfcube["incube"].filename("NONE")
psfcube["outcube"].filename("psfcube.fits")
psfcube["caldb"].string(caldb)
psfcube["irf"].string(irf)
psfcube["ebinalg"].string("LOG")
psfcube["emin"].real(emin)
psfcube["emax"].real(emax)
psfcube["enumbins"].integer(enumbins)
psfcube["nxpix"].integer(10)
psfcube["nypix"].integer(10)
psfcube["binsz"].real(1.0)
psfcube["coordsys"].string(coordsys)
psfcube["proj"].string(proj)
psfcube["xref"].real(ra)
psfcube["yref"].real(dec)
psfcube["debug"].boolean(debug)
psfcube.execute()
# Create background cube
bkgcube = ctools.ctbkgcube()
bkgcube["inobs"].filename("obs.xml")
bkgcube["inmodel"].filename(model)
bkgcube["incube"].filename("cntcube.fits")
bkgcube["outcube"].filename("bkgcube.fits")
bkgcube["outmodel"].filename("model_bkg.xml")
bkgcube["caldb"].string(caldb)
bkgcube["irf"].string(irf)
bkgcube["ebinalg"].string("LOG")
bkgcube["emin"].real(emin)
bkgcube["emax"].real(emax)
bkgcube["enumbins"].integer(enumbins)
bkgcube["nxpix"].integer(10)
bkgcube["nypix"].integer(10)
bkgcube["binsz"].real(1.0)
bkgcube["coordsys"].string(coordsys)
bkgcube["proj"].string(proj)
bkgcube["xref"].real(ra)
bkgcube["yref"].real(dec)
bkgcube["debug"].boolean(debug)
bkgcube.execute()
# Perform maximum likelihood fitting
like = ctools.ctlike()
like["inobs"].filename("cntcube.fits")
like["inmodel"].filename("model_bkg.xml")
like["outmodel"].filename("fit_results.xml")
like["expcube"].filename("expcube.fits")
like["psfcube"].filename("psfcube.fits")
like["bkgcube"].filename("bkgcube.fits")
like["caldb"].string(caldb)
like["irf"].string(irf)
like["debug"].boolean(True) # Switch this always on for results in console
like.execute()
# Return
return
def _bin_observation(self, obs):
"""
Bin an observation is a binned analysis was requested.
Args:
obs: Observation container.
Returns:
Observation container with a binned.
"""
# Header
if self._logExplicit():
self._log.header3("Binning events")
# Bin events
cntcube = ctools.ctbin(obs)
cntcube["usepnt"] = False
cntcube["ebinalg"] = "LOG"
cntcube["xref"] = self["xref"].real()
cntcube["yref"] = self["yref"].real()
cntcube["binsz"] = self["binsz"].real()
cntcube["nxpix"] = self["nxpix"].integer()
cntcube["nypix"] = self["nypix"].integer()
cntcube["enumbins"] = self["enumbins"].integer()
cntcube["emin"] = self["emin"].real()
cntcube["emax"] = self["emax"].real()
cntcube["coordsys"] = self["coordsys"].string()
cntcube["proj"] = self["proj"].string()
cntcube.run()
# Header
if self._logExplicit():
self._log.header3("Creating exposure cube")
# Create exposure cube
expcube = ctools.ctexpcube(obs)
expcube["incube"] = "NONE"
expcube["usepnt"] = False
expcube["ebinalg"] = "LOG"
expcube["xref"] = self["xref"].real()
expcube["yref"] = self["yref"].real()
expcube["binsz"] = self["binsz"].real()
expcube["nxpix"] = self["nxpix"].integer()
expcube["nypix"] = self["nypix"].integer()
expcube["enumbins"] = self["enumbins"].integer()
expcube["emin"] = self["emin"].real()
expcube["emax"] = self["emax"].real()
expcube["coordsys"] = self["coordsys"].string()
expcube["proj"] = self["proj"].string()
expcube.run()
# Header
if self._logExplicit():
self._log.header3("Creating point spread function cube")
# Compute spatial binning for point spread function and
# energy dispersion cubes
binsz = 10.0 * self["binsz"].real()
nxpix = self["nxpix"].integer() // 10 # Make sure result is int
nypix = self["nypix"].integer() // 10 # Make sure result is int
if nxpix < 2:
nxpix = 2
if nypix < 2:
nypix = 2
# Create point spread function cube
psfcube = ctools.ctpsfcube(obs)
psfcube["incube"] = "NONE"
psfcube["usepnt"] = False
psfcube["ebinalg"] = "LOG"
psfcube["xref"] = self["xref"].real()
psfcube["yref"] = self["yref"].real()
psfcube["binsz"] = binsz
psfcube["nxpix"] = nxpix
psfcube["nypix"] = nypix
psfcube["enumbins"] = self["enumbins"].integer()
psfcube["emin"] = self["emin"].real()
psfcube["emax"] = self["emax"].real()
psfcube["coordsys"] = self["coordsys"].string()
psfcube["proj"] = self["proj"].string()
psfcube.run()
# Check if we need to include energy dispersion
if self["edisp"].boolean():
# Header
if self._logExplicit():
self._log.header3("Creating energy dispersion cube")
# Create energy dispersion cube
edispcube = ctools.ctedispcube(obs)
edispcube["incube"] = "NONE"
edispcube["usepnt"] = False
edispcube["ebinalg"] = "LOG"
edispcube["xref"] = self["xref"].real()
edispcube["yref"] = self["yref"].real()
edispcube["binsz"] = binsz
edispcube["nxpix"] = nxpix
edispcube["nypix"] = nypix
edispcube["enumbins"] = self["enumbins"].integer()
edispcube["emin"] = self["emin"].real()
edispcube["emax"] = self["emax"].real()
edispcube["coordsys"] = self["coordsys"].string()
edispcube["proj"] = self["proj"].string()
edispcube.run()
# Header
if self._logExplicit():
self._log.header3("Creating background cube")
# Create background cube
bkgcube = ctools.ctbkgcube(obs)
bkgcube["incube"] = "NONE"
bkgcube["usepnt"] = False
bkgcube["ebinalg"] = "LOG"
bkgcube["xref"] = self["xref"].real()
bkgcube["yref"] = self["yref"].real()
bkgcube["binsz"] = self["binsz"].real()
bkgcube["nxpix"] = self["nxpix"].integer()
bkgcube["nypix"] = self["nypix"].integer()
bkgcube["enumbins"] = self["enumbins"].integer()
bkgcube["emin"] = self["emin"].real()
bkgcube["emax"] = self["emax"].real()
bkgcube["coordsys"] = self["coordsys"].string()
bkgcube["proj"] = self["proj"].string()
bkgcube.run()
# Retrieve a new oberservation container
new_obs = cntcube.obs().copy()
# Get new models
models = bkgcube.models()
# Set stacked response
if self["edisp"].boolean():
new_obs[0].response(expcube.expcube(), psfcube.psfcube(),
edispcube.edispcube(), bkgcube.bkgcube())
else:
new_obs[0].response(expcube.expcube(), psfcube.psfcube(),
bkgcube.bkgcube())
# Fix background models if required
if self["fix_bkg"].boolean():
for model in models:
if model.classname() != "GModelSky":
for par in model:
par.fix()
# Set models for new oberservation container
new_obs.models(models)
# Return new oberservation container
return new_obs
def _test_python(self):
"""
Test ctbin from Python
"""
# Allocate ctbin
binning = ctools.ctbin()
# Check that empty ctbin has an empty observation container and counts
# cube
self.test_value(
binning.obs().size(), 0,
'Check that empty ctbin has an empty observation container')
self.test_value(binning.cubes(), 0,
'Check that empty ctbin has an empty counts cube')
# Check that saving does not nothing
binning['logfile'] = 'ctbin_py0.log'
binning['outobs'] = 'ctbin_py0.fits'
binning.logFileOpen()
binning.save()
self.test_assert(not os.path.isfile('ctbin_py0.fits'),
'Check that no counts cube has been created')
# Check that publishing does not lead to an exception or segfault
binning.publish()
# Check that clearing does not lead to an exception or segfault
binning.clear()
# Now set ctbin parameters
binning['inobs'] = self._events
binning['outobs'] = 'ctbin_py1.fits'
binning['ebinalg'] = 'LOG'
binning['emin'] = 1.0
binning['emax'] = 100.0
binning['enumbins'] = 10
binning['nxpix'] = 40
binning['nypix'] = 40
binning['binsz'] = 0.1
binning['coordsys'] = 'CEL'
binning['proj'] = 'CAR'
binning['xref'] = 83.63
binning['yref'] = 22.01
binning['logfile'] = 'ctbin_py1.log'
binning['chatter'] = 2
# Run ctbin tool
binning.logFileOpen()
binning.run()
# Check content of observation container and counts cube
self._check_observation(binning, 245)
self._check_cube(binning.cube(), 245)
# Copy ctbin tool
cpy_bin = binning.copy()
# Check content of observation container and counts cube
self._check_observation(cpy_bin, 245)
self._check_cube(cpy_bin.cube(), 245)
# Run copy of ctbin tool again
cpy_bin['logfile'] = 'ctbin_py2.log'
cpy_bin['chatter'] = 3
cpy_bin.logFileOpen()
cpy_bin.run()
# Check content of observation container and number of counts cubes.
# There should be a single binned observation in the observation
# container, which is the one that was produced in the run before.
# Since ctbin finds no unbinned observation in the container, the
# number of cubes should be zero.
self._check_observation(cpy_bin, 245)
self.test_value(cpy_bin.cubes(), 0,
'Check that there are no counts cubes')
# Save counts cube
binning.save()
# Load counts cube and check content
evt = gammalib.GCTAEventCube('ctbin_py1.fits')
self._check_cube(evt, 245)
# Now clear ctbin tool
binning.clear()
# Check that cleared ctbin has an empty observation container and
# counts cube
self.test_value(
binning.obs().size(), 0,
'Check that empty ctbin has an empty observation container')
self.test_value(binning.cubes(), 0,
'Check that empty ctbin has an empty counts cube')
# Prepare observation container for stacking of events into a
# single counts cube
obs = self._obs_events()
# Set-up ctbin using an observation container
binning = ctools.ctbin(obs)
binning['outobs'] = 'ctbin_py3.fits'
binning['ebinalg'] = 'LOG'
binning['emin'] = 1.0
binning['emax'] = 100.0
binning['enumbins'] = 10
binning['nxpix'] = 40
binning['nypix'] = 40
binning['binsz'] = 0.1
binning['coordsys'] = 'CEL'
binning['proj'] = 'CAR'
binning['xref'] = 83.63
binning['yref'] = 22.01
binning['publish'] = True
binning['logfile'] = 'ctbin_py3.log'
binning['chatter'] = 3
# Execute ctbin tool
binning.logFileOpen()
binning.execute()
# Check content of observation and cube (need multiplier=3 since
# three identical observations have been appended)
self._check_observation(binning, 245, multiplier=3)
self._check_cube(binning.cube(), 245, multiplier=3)
# Load counts cube and check content.
evt = gammalib.GCTAEventCube('ctbin_py3.fits')
self._check_cube(evt, 245, multiplier=3)
# Now go for a fully Pythonic version with all parameters being
# specified in a dictionary
pars = {
'inobs': self._events,
'ebinalg': 'LIN',
'emin': 1.0,
'emax': 100.0,
'enumbins': 10,
'nxpix': 40,
'nypix': 40,
'binsz': 0.1,
'coordsys': 'CEL',
'proj': 'CAR',
'xref': 83.63,
'yref': 22.01,
'outobs': 'ctbin_py4.fits',
'logfile': 'ctbin_py4.log',
'chatter': 2
}
binning = ctools.ctbin()
binning.pardict(pars)
binning.logFileOpen()
binning.execute()
# Load counts cube and check content
evt = gammalib.GCTAEventCube('ctbin_py4.fits')
self._check_cube(evt, 245)
# Test unstacked version
binning = ctools.ctbin()
binning['inobs'] = self._inobs_two
binning['stack'] = False
binning['prefix'] = 'cntcube_py5_'
binning['ebinalg'] = 'LOG'
binning['emin'] = 1.0
binning['emax'] = 100.0
binning['enumbins'] = 10
binning['nxpix'] = 40
binning['nypix'] = 40
binning['binsz'] = 0.1
binning['coordsys'] = 'CEL'
binning['proj'] = 'CAR'
binning['xref'] = 83.63
binning['yref'] = 22.01
binning['outobs'] = 'ctbin_py5.xml'
binning['logfile'] = 'ctbin_py5.log'
binning['chatter'] = 2
binning.logFileOpen()
binning.run()
# Check individual cubes
self._check_cube(binning.cube(0), 245)
self._check_cube(binning.cube(1), 245)
# Save counts cube
binning.save()
# Load observations
obs = gammalib.GObservations('ctbin_py5.xml')
self.test_value(obs.size(), 2, 'Check number of output observations')
# Check counts cubes
evt = obs[0].events()
self._check_cube(evt, 245)
evt = obs[1].events()
self._check_cube(evt, 245)
# Load counts cubes and check content
evt = gammalib.GCTAEventCube('cntcube_py5_cta_00001.fits')
self._check_cube(evt, 245)
evt = gammalib.GCTAEventCube('cntcube_py5_cta_00002.fits')
self._check_cube(evt, 245)
# Return
return
def run(self):
"""
Run the script.
"""
# Switch screen logging on in debug mode
if self.logDebug():
self.log.cout(True)
# Get parameters
self.get_parameters()
# Write input parameters into logger
if self.logTerse():
self.log_parameters()
self.log("\n")
# Write observation into logger
if self.logTerse():
self.log("\n")
self.log.header1("Observation")
self.log(str(self.obs))
self.log("\n")
# Write header
if self.logTerse():
self.log("\n")
self.log.header1("Adjust model parameters")
# Adjust model parameters dependent on input user parameters
for model in self.obs.models():
# Set TS flag for all models to false.
# Source of interest will be set to true later
model.tscalc(False)
# Log model name
if self.logExplicit():
self.log.header3(model.name())
# Deal with the source of interest
if model.name() == self.m_srcname:
if self.m_calc_ts:
model.tscalc(True)
elif self.m_fix_bkg and not model.classname() == "GModelSky":
for par in model:
if par.is_free() and self.logExplicit():
self.log(" Fixing \""+par.name()+"\"\n")
par.fix()
elif self.m_fix_srcs and model.classname() == "GModelSky":
for par in model:
if par.is_free() and self.logExplicit():
self.log(" Fixing \""+par.name()+"\"\n")
par.fix()
# Write header
if self.logTerse():
self.log("\n")
self.log.header1("Generate lightcurve")
# Initialise FITS Table with extension "LIGHTCURVE"
table = gammalib.GFitsBinTable(self.m_tbins.size())
table.extname("LIGHTCURVE")
# Add Header for compatibility with gammalib.GMWLSpectrum
table.card("INSTRUME", "CTA", "Name of Instrument")
table.card("TELESCOP", "CTA", "Name of Telescope")
# Create FITS table columns
MJD = gammalib.GFitsTableDoubleCol("MJD", self.m_tbins.size())
MJD.unit("days")
e_MJD = gammalib.GFitsTableDoubleCol("e_MJD", self.m_tbins.size())
e_MJD.unit("days")
# Create a FITS column for every free parameter
columns = []
for par in self.obs.models()[self.m_srcname]:
if par.is_free():
col = gammalib.GFitsTableDoubleCol(par.name(), self.m_tbins.size())
col.unit(par.unit())
columns.append(col)
e_col = gammalib.GFitsTableDoubleCol("e_"+par.name(), self.m_tbins.size())
e_col.unit(par.unit())
columns.append(e_col)
# Create TS and upper limit columns
TSvalues = gammalib.GFitsTableDoubleCol("TS", self.m_tbins.size())
ulim_values = gammalib.GFitsTableDoubleCol("UpperLimit", self.m_tbins.size())
ulim_values.unit("ph/cm2/s")
# Loop over energy bins
for i in range(self.m_tbins.size()):
# Log information
if self.logTerse():
self.log("\n")
self.log.header2("Time bin "+str(i))
# Get time boundaries
tmin = self.m_tbins.tstart(i)
tmax = self.m_tbins.tstop(i)
# Compute time bin center and time width
tmean = (tmin + tmax)
tmean *= 0.5
twidth = (tmax - tmin)
twidth *= 0.5
# Store time as MJD
MJD[i] = tmean.mjd()
e_MJD[i] = twidth.days()
# Log information
if self.logExplicit():
self.log.header3("Selecting events")
# Select events
select = ctools.ctselect(self.obs)
select["emin"].real(self.m_emin)
select["emax"].real(self.m_emax)
select["tmin"].real(tmin.convert(select.time_reference()))
select["tmax"].real(tmax.convert(select.time_reference()))
select["rad"].value("UNDEFINED")
select["ra"].value("UNDEFINED")
select["dec"].value("UNDEFINED")
select.run()
# Retrieve observation
obs = select.obs()
# Binned analysis
if self.m_binned:
# Header
if self.logTerse():
self.log.header3("Binning events")
# Bin events
bin = ctools.ctbin(select.obs())
bin["usepnt"].boolean(False)
bin["ebinalg"].string("LOG")
bin["xref"].real(self.m_xref)
bin["yref"].real(self.m_yref)
bin["binsz"].real(self.m_binsz)
bin["nxpix"].integer(self.m_nxpix)
bin["nypix"].integer(self.m_nypix)
bin["enumbins"].integer(self.m_ebins)
bin["emin"].real(self.m_emin)
bin["emax"].real(self.m_emax)
bin["coordsys"].string(self.m_coordsys)
bin["proj"].string(self.m_proj)
bin.run()
# Header
if self.logTerse():
self.log.header3("Creating exposure cube")
# Create exposure cube
expcube = ctools.ctexpcube(select.obs())
expcube["incube"].filename("NONE")
expcube["usepnt"].boolean(False)
expcube["ebinalg"].string("LOG")
expcube["xref"].real(self.m_xref)
expcube["yref"].real(self.m_yref)
expcube["binsz"].real(self.m_binsz)
expcube["nxpix"].integer(self.m_nxpix)
expcube["nypix"].integer(self.m_nypix)
expcube["enumbins"].integer(self.m_ebins)
expcube["emin"].real(self.m_emin)
expcube["emax"].real(self.m_emax)
expcube["coordsys"].string(self.m_coordsys)
expcube["proj"].string(self.m_proj)
expcube.run()
# Header
if self.logTerse():
self.log.header3("Creating PSF cube")
# Create psf cube
psfcube = ctools.ctpsfcube(select.obs())
psfcube["incube"].filename("NONE")
psfcube["usepnt"].boolean(False)
psfcube["ebinalg"].string("LOG")
psfcube["xref"].real(self.m_xref)
psfcube["yref"].real(self.m_yref)
psfcube["binsz"].real(self.m_binsz)
psfcube["nxpix"].integer(self.m_nxpix)
psfcube["nypix"].integer(self.m_nypix)
psfcube["enumbins"].integer(self.m_ebins)
psfcube["emin"].real(self.m_emin)
psfcube["emax"].real(self.m_emax)
psfcube["coordsys"].string(self.m_coordsys)
psfcube["proj"].string(self.m_proj)
psfcube.run()
# Header
if self.logTerse():
self.log.header3("Creating background cube")
# Create background cube
bkgcube = ctools.ctbkgcube(select.obs())
bkgcube["incube"].filename("NONE")
bkgcube["usepnt"].boolean(False)
bkgcube["ebinalg"].string("LOG")
bkgcube["xref"].real(self.m_xref)
bkgcube["yref"].real(self.m_yref)
bkgcube["binsz"].real(self.m_binsz)
bkgcube["nxpix"].integer(self.m_nxpix)
bkgcube["nypix"].integer(self.m_nypix)
bkgcube["enumbins"].integer(self.m_ebins)
bkgcube["emin"].real(self.m_emin)
bkgcube["emax"].real(self.m_emax)
bkgcube["coordsys"].string(self.m_coordsys)
bkgcube["proj"].string(self.m_proj)
bkgcube.run()
# Set new binned observation
obs = bin.obs()
# Set precomputed binned response
obs[0].response(expcube.expcube(), psfcube.psfcube(), bkgcube.bkgcube())
# Get new models
models = bkgcube.models()
# Fix background models if required
if self.m_fix_bkg:
for model in models:
if not model.classname() == "GModelSky":
for par in model:
par.fix()
# Set new models to binned observation
obs.models(models)
# Header
if self.logTerse():
self.log.header3("Performing fit")
# Likelihood
like = ctools.ctlike(obs)
like.run()
# Skip bin if no event was present
if like.obs().logL() == 0.0:
# Log information
if self.logTerse():
self.log("No event in this time bin. Bin is skipped\n")
# Set all values to 0
for col in columns:
col[i] = 0.0
TSvalues[i] = 0.0
ulim_values[i] = 0.0
continue
# Get results
fitted_models = like.obs().models()
source = fitted_models[self.m_srcname]
# Calculate Upper Limit
ulimit_value = -1.0
if self.m_calc_ulimit:
# Logging information
if self.logTerse():
self.log.header3("Computing upper limit")
# Create upper limit object
ulimit = ctools.ctulimit(like.obs())
ulimit["srcname"].string(self.m_srcname)
ulimit["eref"].real(1.0)
# Try to run upper limit and catch exceptions
try:
ulimit.run()
ulimit_value = ulimit.flux_ulimit()
except:
if self.logTerse():
self.log("Upper limit calculation failed\n")
ulimit_value = -1.0
# Get TS value
TS = -1.0
if self.m_calc_ts:
TS = source.ts()
# Set values for storage
TSvalues[i] = TS
# Set FITS column values
for col in columns:
if "e_" == col.name()[:2]:
col[i] = source.spectral()[col.name()[2:]].error()
else:
col[i] = source.spectral()[col.name()].value()
# Store upper limit value if available
if ulimit_value > 0.0:
ulim_values[i] = ulimit_value
# Log information
if self.logExplicit():
self.log.header3("Results of bin "+str(i)+": MJD "+str(tmin.mjd())+"-"+str(tmax.mjd()))
for col in columns:
if "e_" == col.name()[:2]:
continue
value = source.spectral()[col.name()].value()
error = source.spectral()[col.name()].error()
unit = source.spectral()[col.name()].unit()
self.log(" > "+col.name()+": "+str(value)+" +- "+str(error)+" "+unit+"\n")
if self.m_calc_ts and TSvalues[i] > 0.0:
self.log(" > TS = "+str(TS)+" \n")
if self.m_calc_ulimit and ulim_values[i] > 0.0:
self.log(" > UL = "+str(ulim_values[i])+" [ph/cm2/s]")
self.log("\n")
# Append filles columns to fits table
table.append(MJD)
table.append(e_MJD)
for col in columns:
table.append(col)
table.append(TSvalues)
table.append(ulim_values)
# Create the FITS file now
self.fits = gammalib.GFits()
self.fits.append(table)
# Return
return
def _test_python(self):
"""
Test ctbin from Python
"""
# Set-up ctbin
bin = ctools.ctbin()
bin['inobs'] = self._events
bin['outcube'] = 'cntmap.fits'
bin['ebinalg'] = 'LOG'
bin['emin'] = 0.1
bin['emax'] = 100.0
bin['enumbins'] = 20
bin['nxpix'] = 200
bin['nypix'] = 200
bin['binsz'] = 0.02
bin['coordsys'] = 'CEL'
bin['proj'] = 'CAR'
bin['xref'] = 83.63
bin['yref'] = 22.01
bin['logfile'] = 'ctbin_py1.log'
bin['chatter'] = 2
# Run ctbin tool
#bin.logFileOpen() # Make sure we get a log file, but this leads
# to a segmentation fault on Linux, e.g. CentOS 6.
# see issue #1823 (need to fix that)
bin.run()
# Check content of observation and cube
self._check_observation(bin, 5542)
self._check_cube(bin.cube(), 5542)
# Test copy constructor
cpy_bin = bin.copy()
# Check content of observation and cube
self._check_observation(cpy_bin, 5542)
self._check_cube(cpy_bin.cube(), 5542)
# Run copy of ctbin tool again
cpy_bin['logfile'] = 'ctbin_py2.log'
cpy_bin['chatter'] = 3
cpy_bin.run()
# Check content of observation and cube. We expect now an empty
# event cube as on input the observation is binned, and any binned
# observation will be skipped, hence the counts cube should be
# empty.
self._check_observation(cpy_bin, 0)
self._check_cube(cpy_bin.cube(), 0)
# Save counts cube
bin.save()
# Load counts cube and check content.
evt = gammalib.GCTAEventCube('cntmap.fits')
self._check_cube(evt, 5542)
# Prepare observation container for stacked analysis
cta = gammalib.GCTAObservation(self._events)
obs = gammalib.GObservations()
cta.id('0001')
obs.append(cta)
cta.id('0002')
obs.append(cta)
cta.id('0003')
obs.append(cta)
# Set-up ctbin using an observation container
bin = ctools.ctbin(obs)
bin['outcube'] = 'cntmap.fits'
bin['ebinalg'] = 'LOG'
bin['emin'] = 0.1
bin['emax'] = 100.0
bin['enumbins'] = 20
bin['nxpix'] = 200
bin['nypix'] = 200
bin['binsz'] = 0.02
bin['coordsys'] = 'CEL'
bin['proj'] = 'CAR'
bin['xref'] = 83.63
bin['yref'] = 22.01
bin['logfile'] = 'ctbin_py3.log'
bin['chatter'] = 4
# Run ctbin tool
bin.logFileOpen() # Make sure we get a log file
bin.run()
# Check content of observation and cube (need multiplier=3 since
# three identical observations have been appended)
self._check_observation(bin, 5542, multiplier=3)
self._check_cube(bin.cube(), 5542, multiplier=3)
# Set-up ctbin using an observation container
bin = ctools.ctbin(obs)
bin['outcube'] = 'cntmap2.fits'
bin['ebinalg'] = 'LOG'
bin['emin'] = 0.1
bin['emax'] = 100.0
bin['enumbins'] = 20
bin['nxpix'] = 200
bin['nypix'] = 200
bin['binsz'] = 0.02
bin['coordsys'] = 'CEL'
bin['proj'] = 'CAR'
bin['xref'] = 83.63
bin['yref'] = 22.01
bin['logfile'] = 'ctbin_py4.log'
bin['chatter'] = 4
# Execute ctbin tool
bin.execute()
# Load counts cube and check content.
evt = gammalib.GCTAEventCube('cntmap2.fits')
self._check_cube(evt, 5542, multiplier=3)
# Return
return
def binned_pipeline(model_name, duration):
"""
Binned analysis pipeline.
"""
# Set script parameters
caldb = "prod2"
irf = "South_50h"
ra = 83.63
dec = 22.01
rad_sim = 10.0
tstart = 0.0
tstop = duration
emin = 0.1
emax = 100.0
enumbins = 40
nxpix = 200
nypix = 200
binsz = 0.02
coordsys = "CEL"
proj = "CAR"
# Get start CPU time
cpu_start = time.clock()
# Simulate events
sim = ctools.ctobssim()
sim["inmodel"] = model_name
sim["caldb"] = caldb
sim["irf"] = irf
sim["ra"] = ra
sim["dec"] = dec
sim["rad"] = rad_sim
sim["tmin"] = tstart
sim["tmax"] = tstop
sim["emin"] = emin
sim["emax"] = emax
sim.run()
# Bin events into counts map
bin = ctools.ctbin(sim.obs())
bin["ebinalg"] = "LOG"
bin["emin"] = emin
bin["emax"] = emax
bin["enumbins"] = enumbins
bin["nxpix"] = nxpix
bin["nypix"] = nypix
bin["binsz"] = binsz
bin["coordsys"] = coordsys
bin["xref"] = ra
bin["yref"] = dec
bin["proj"] = proj
bin.run()
# Get ctlike start CPU time
cpu_ctlike = time.clock()
# Perform maximum likelihood fitting
like = ctools.ctlike(bin.obs())
like.run()
# Get stop CPU time and compute elapsed times
cpu_stop = time.clock()
cpu_elapsed = cpu_stop - cpu_start
cpu_ctlike = cpu_stop - cpu_ctlike
# Return
return cpu_elapsed, cpu_ctlike
def run_pipeline(obs,
emin=0.1,
emax=100.0,
enumbins=20,
nxpix=200,
nypix=200,
binsz=0.02,
coordsys='CEL',
proj='CAR',
debug=False):
"""
Simulation and binned analysis pipeline
Parameters
----------
obs : `~gammalib.GObservations`
Observation container
emin : float, optional
Minimum energy (TeV)
emax : float, optional
Maximum energy (TeV)
enumbins : int, optional
Number of energy bins
nxpix : int, optional
Number of pixels in X axis
nypix : int, optional
Number of pixels in Y axis
binsz : float, optional
Pixel size (deg)
coordsys : str, optional
Coordinate system
proj : str, optional
Coordinate projection
debug : bool, optional
Debug function
"""
# Simulate events
sim = ctools.ctobssim(obs)
sim['debug'] = debug
sim.run()
# Bin events by looping over all observations in the container
obs = gammalib.GObservations()
obs.models(sim.obs().models())
for run in sim.obs():
# Create container with a single observation
container = gammalib.GObservations()
container.append(run)
# Bin events for that observation
bin = ctools.ctbin(container)
bin['ebinalg'] = 'LOG'
bin['emin'] = emin
bin['emax'] = emax
bin['enumbins'] = enumbins
bin['nxpix'] = nxpix
bin['nypix'] = nypix
bin['binsz'] = binsz
bin['coordsys'] = coordsys
bin['usepnt'] = True
bin['proj'] = proj
bin.run()
# Append result to observations
obs.extend(bin.obs())
# Perform maximum likelihood fitting
like = ctools.ctlike(obs)
like['debug'] = True # Switch this always on for results in console
like.run()
# Return
return
def sim(obs, log=False, debug=False, seed=0, nbins=0, binsz=0.05, npix=200):
"""
Simulate events for all observations in the container.
Parameters:
obs - Observation container
Keywords:
log - Create log file(s)
debug - Create screen dump
seed - Seed value for simulations (default: 0)
nbins - Number of energy bins (default: 0=unbinned)
binsz - Pixel size for binned simulation (deg/pixel)
npix - Number of pixels in X and Y for binned simulation
"""
# Allocate ctobssim application and set parameters
sim = ctools.ctobssim(obs)
sim['seed'].integer(seed)
# Optionally open the log file
if log:
sim.logFileOpen()
# Optionally switch-on debugging model
if debug:
sim["debug"].boolean(True)
# Run ctobssim application. This will loop over all observations in the
# container and simulation the events for each observation. Note that
# events are not added together, they still apply to each observation
# separately.
sim.run()
# Binned option?
if nbins > 0:
# Determine common energy boundaries for observations
emin = None
emax = None
for run in sim.obs():
run_emin = run.events().ebounds().emin().TeV()
run_emax = run.events().ebounds().emax().TeV()
if emin == None:
emin = run_emin
elif run_emin > emin:
emin = run_emin
if emax == None:
emax = run_emax
elif run_emax > emax:
emax = run_emax
# Allocate ctbin application and set parameters
bin = ctools.ctbin(sim.obs())
bin["ebinalg"].string("LOG")
bin["emin"].real(emin)
bin["emax"].real(emax)
bin["enumbins"].integer(nbins)
bin["usepnt"].boolean(True) # Use pointing for map centre
bin["nxpix"].integer(npix)
bin["nypix"].integer(npix)
bin["binsz"].real(binsz)
bin["coordsys"].string("GAL")
bin["proj"].string("TAN")
# Optionally open the log file
if log:
bin.logFileOpen()
# Optionally switch-on debugging model
if debug:
bin["debug"].boolean(True)
# Run ctbin application. This will loop over all observations in
# the container and bin the events in counts maps
bin.run()
# Make a deep copy of the observation that will be returned
# (the ctbin object will go out of scope one the function is
# left)
obs = bin.obs().copy()
else:
# Make a deep copy of the observation that will be returned
# (the ctobssim object will go out of scope one the function is
# left)
obs = sim.obs().copy()
# Delete the simulation
del sim
# Return observation container
return obs
def counts_cube(output_dir,
map_reso,
map_coord,
map_fov,
emin,
emax,
enumbins,
ebinalg,
stack=True,
logfile=None,
silent=False):
"""
Compute counts cube.
http://cta.irap.omp.eu/ctools/users/reference_manual/ctbin.html
Parameters
----------
- output_dir (str): directory where to get input files and
save outputs
- map_reso (float): the resolution of the map (can be an
astropy.unit object, or in deg)
- map_coord (float): a skycoord object that give the center of the map
- map_fov (float): the field of view of the map (can be an
astropy.unit object, or in deg)
- emin/emax (float): min and max energy in TeV
- enumbins (int): the number of energy bins
- ebinalg (str): the energy binning algorithm
- stack (bool): do we use stacking of individual event files or not
- silent (bool): use this keyword to print information
Outputs
--------
- Ana_Countscube.fits: the fits file cubed data, in case stack is requested
- Ana_Countscube.xml: the xml file cubed data, in case stack is not requested
- Ana_Countscubecta_{obsIDs}.fits: the fits files of individual event files
cubed data, in case stack is not requested
"""
npix = utilities.npix_from_fov_def(map_fov, map_reso)
ctscube = ctools.ctbin()
ctscube['inobs'] = output_dir + '/Ana_EventsSelected.xml'
if stack:
ctscube['outobs'] = output_dir + '/Ana_Countscube.fits'
else:
ctscube['outobs'] = output_dir + '/Ana_Countscube.xml'
ctscube['stack'] = stack
ctscube['prefix'] = output_dir + '/Ana_Countscube'
ctscube['ebinalg'] = ebinalg
ctscube['emin'] = emin.to_value('TeV')
ctscube['emax'] = emax.to_value('TeV')
ctscube['enumbins'] = enumbins
ctscube['ebinfile'] = 'NONE'
ctscube['usepnt'] = False
ctscube['nxpix'] = npix
ctscube['nypix'] = npix
ctscube['binsz'] = map_reso.to_value('deg')
ctscube['coordsys'] = 'CEL'
ctscube['proj'] = 'TAN'
ctscube['xref'] = map_coord.icrs.ra.to_value('deg')
ctscube['yref'] = map_coord.icrs.dec.to_value('deg')
if logfile is not None: ctscube['logfile'] = logfile
if logfile is not None: ctscube.logFileOpen()
ctscube.execute()
if logfile is not None: ctscube.logFileClose()
if not silent:
print(ctscube)
print('')
return ctscube
def run_pipeline(obs, ra=83.63, dec=22.01, emin=0.1, emax=100.0,
enumbins=20, nxpix=200, nypix=200, binsz=0.02,
coordsys='CEL', proj='CAR', debug=False):
"""
Simulation and stacked analysis pipeline
Parameters
----------
obs : `~gammalib.GObservations`
Observation container
ra : float, optional
Right Ascension of counts cube centre (deg)
dec : float, optional
Declination of Region of counts cube centre (deg)
emin : float, optional
Minimum energy (TeV)
emax : float, optional
Maximum energy (TeV)
enumbins : int, optional
Number of energy bins
nxpix : int, optional
Number of pixels in X axis
nypix : int, optional
Number of pixels in Y axis
binsz : float, optional
Pixel size (deg)
coordsys : str, optional
Coordinate system
proj : str, optional
Coordinate projection
debug : bool, optional
Debug function
"""
# Simulate events
sim = ctools.ctobssim(obs)
sim['debug'] = debug
sim.run()
# Bin events into counts map
bin = ctools.ctbin(sim.obs())
bin['ebinalg'] = 'LOG'
bin['emin'] = emin
bin['emax'] = emax
bin['enumbins'] = enumbins
bin['nxpix'] = nxpix
bin['nypix'] = nypix
bin['binsz'] = binsz
bin['coordsys'] = coordsys
bin['proj'] = proj
bin['xref'] = ra
bin['yref'] = dec
bin['debug'] = debug
bin.run()
# Create exposure cube
expcube = ctools.ctexpcube(sim.obs())
expcube['incube'] = 'NONE'
expcube['ebinalg'] = 'LOG'
expcube['emin'] = emin
expcube['emax'] = emax
expcube['enumbins'] = enumbins
expcube['nxpix'] = nxpix
expcube['nypix'] = nypix
expcube['binsz'] = binsz
expcube['coordsys'] = coordsys
expcube['proj'] = proj
expcube['xref'] = ra
expcube['yref'] = dec
expcube['debug'] = debug
expcube.run()
# Create PSF cube
psfcube = ctools.ctpsfcube(sim.obs())
psfcube['incube'] = 'NONE'
psfcube['ebinalg'] = 'LOG'
psfcube['emin'] = emin
psfcube['emax'] = emax
psfcube['enumbins'] = enumbins
psfcube['nxpix'] = 10
psfcube['nypix'] = 10
psfcube['binsz'] = 1.0
psfcube['coordsys'] = coordsys
psfcube['proj'] = proj
psfcube['xref'] = ra
psfcube['yref'] = dec
psfcube['debug'] = debug
psfcube.run()
# Create background cube
bkgcube = ctools.ctbkgcube(sim.obs())
bkgcube['incube'] = 'NONE'
bkgcube['ebinalg'] = 'LOG'
bkgcube['emin'] = emin
bkgcube['emax'] = emax
bkgcube['enumbins'] = enumbins
bkgcube['nxpix'] = 10
bkgcube['nypix'] = 10
bkgcube['binsz'] = 1.0
bkgcube['coordsys'] = coordsys
bkgcube['proj'] = proj
bkgcube['xref'] = ra
bkgcube['yref'] = dec
bkgcube['debug'] = debug
bkgcube.run()
# Attach background model to observation container
bin.obs().models(bkgcube.models())
# Set Exposure and Psf cube for first CTA observation
# (ctbin will create an observation with a single container)
bin.obs()[0].response(expcube.expcube(), psfcube.psfcube(), bkgcube.bkgcube())
# Perform maximum likelihood fitting
like = ctools.ctlike(bin.obs())
like['debug'] = True # Switch this always on for results in console
like.run()
# Return
return
def run(self):
"""
Run the script.
"""
# Switch screen logging on in debug mode
if self.logDebug():
self.log.cout(True)
# Get parameters
self.get_parameters()
# Write input parameters into logger
if self.logTerse():
self.log_parameters()
self.log("\n")
# Write observation into logger
if self.logTerse():
self.log("\n")
self.log.header1("Observation")
self.log(str(self.obs))
self.log("\n")
# Use input file directly if given
if self.m_use_maps:
countmap = gammalib.GSkyMap(self["inobs"].filename())
modelmap = gammalib.GSkyMap(self.m_modcube)
else:
if self.m_skip_binning:
cta_counts_cube = gammalib.GCTAEventCube(self.obs[0].events().clone())
else:
# Write header
if self.logTerse():
self.log("\n")
self.log.header1("Generate binned map (ctbin)")
# Create countsmap
bin = ctools.ctbin(self.obs)
bin["nxpix"].integer(self.m_nxpix)
bin["nypix"].integer(self.m_nypix)
bin["proj"].string(self.m_proj)
bin["coordsys"].string(self.m_coordsys)
bin["xref"].real(self.m_xref)
bin["yref"].real(self.m_yref)
bin["enumbins"].integer(self.m_enumbins)
bin["ebinalg"].string(self.m_ebinalg)
bin["emin"].real(self.m_emin)
bin["emax"].real(self.m_emax)
bin["binsz"].real(self.m_binsz)
bin["chatter"].integer(self.m_chatter)
bin["clobber"].boolean(self.m_clobber)
bin["debug"].boolean(self.m_debug)
bin.run()
# Retrieve counts cube
cta_counts_cube = bin.cube()
# Assign GCTAEventCube to skymap
countmap = cta_counts_cube.map()
# Write header
if self.logTerse():
self.log("\n")
self.log.header1("Generate model map (ctmodel)")
# Create model map
model = ctools.ctmodel(self.obs)
model.cube(cta_counts_cube)
model["chatter"].integer(self.m_chatter)
model["clobber"].boolean(self.m_clobber)
model["debug"].boolean(self.m_debug)
model["edisp"].boolean(self.m_edisp)
model.run()
# Get model map into GSkyMap object
modelmap = model.cube().map().copy()
# Store counts map as residual map. Note that we need a
# special construct here to avoid memory leaks. This seems
# to be a SWIG feature as SWIG creates a new object when
# calling bin.cube()
#residualmap = bin.cube().map()
self.resmap = countmap.copy()
self.resmap.stack_maps()
modelmap.stack_maps()
# Continue calculations depending on given algorithm
if self.m_algorithm == "SUB":
# Subtract maps
self.resmap -= modelmap
elif self.m_algorithm == "SUBDIV":
# Subtract and divide by model map
self.resmap -= modelmap
self.resmap /= modelmap
#for pixel in modelmap:
# if pixel != 0.0:
# pixel = 1.0/pixel
#self.resmap *= modelmap
elif self.m_algorithm == "SUBDIVSQRT":
# subtract and divide by sqrt of model map
self.resmap -= modelmap
self.resmap /= modelmap.sqrt()
#for pixel in modelmap:
# if pixel != 0.0:
# pixel = 1.0/math.sqrt(pixel)
#self.resmap *= modelmap
else:
# Raise error if algorithm is unkown
raise TypeError("Algorithm \""+self.m_algorithm+"\" not known")
# Return
return
def get_stacked_obs(cls, obs):
"""
Bin an observation and return an observation container with a single
binned observation
Parameters
----------
cls : `~ctools.cscript`
cscript class
obs : `~gammalib.GObservations`
Observation container
Returns
-------
obs : `~gammalib.GObservations`
Observation container where the first observation is a binned observation
"""
# Write header
if cls._logExplicit():
cls._log.header3('Binning events')
# Bin events
cntcube = ctools.ctbin(obs)
cntcube['usepnt'] = False
cntcube['ebinalg'] = 'LOG'
cntcube['xref'] = cls['xref'].real()
cntcube['yref'] = cls['yref'].real()
cntcube['binsz'] = cls['binsz'].real()
cntcube['nxpix'] = cls['nxpix'].integer()
cntcube['nypix'] = cls['nypix'].integer()
cntcube['enumbins'] = cls['enumbins'].integer()
cntcube['emin'] = cls['emin'].real()
cntcube['emax'] = cls['emax'].real()
cntcube['coordsys'] = cls['coordsys'].string()
cntcube['proj'] = cls['proj'].string()
cntcube.run()
# Write header
if cls._logExplicit():
cls._log.header3('Creating stacked response')
# Get stacked response
response = get_stacked_response(obs,
cls['xref'].real(),
cls['yref'].real(),
binsz=cls['binsz'].real(),
nxpix=cls['nxpix'].integer(),
nypix=cls['nypix'].integer(),
emin=cls['emin'].real(),
emax=cls['emax'].real(),
enumbins=cls['enumbins'].integer(),
edisp=cls['edisp'].boolean(),
coordsys=cls['coordsys'].string(),
proj=cls['proj'].string())
# Retrieve a new oberservation container
new_obs = cntcube.obs().copy()
# Set stacked response
if cls['edisp'].boolean():
new_obs[0].response(response['expcube'], response['psfcube'],
response['edispcube'], response['bkgcube'])
else:
new_obs[0].response(response['expcube'], response['psfcube'],
response['bkgcube'])
# Get new models
models = response['models']
# Set models for new oberservation container
new_obs.models(models)
# Return new oberservation container
return new_obs
def run_pipeline(obs, ra=83.63, dec=22.01, emin=0.1, emax=100.0,
enumbins=20, nxpix=200, nypix=200, binsz=0.02,
coordsys="CEL", proj="CAR",
model="${CTOOLS}/share/models/crab.xml",
caldb="prod2", irf="South_50h",
debug=False):
"""
Simulation and stacked analysis pipeline.
Keywords:
ra - RA of cube centre [deg] (default: 83.6331)
dec - DEC of cube centre [deg] (default: 22.0145)
emin - Minimum energy of cube [TeV] (default: 0.1)
emax - Maximum energy of cube [TeV] (default: 100.0)
enumbins - Number of energy bins in cube (default: 20)
nxpix - Number of RA pixels in cube (default: 200)
nypix - Number of DEC pixels in cube (default: 200)
binsz - Spatial cube bin size [deg] (default: 0.02)
coordsys - Cube coordinate system (CEL or GAL)
proj - Cube World Coordinate System (WCS) projection
debug - Enable debugging (default: False)
"""
# Simulate events
sim = ctools.ctobssim(obs)
sim["debug"] = debug
sim["outevents"] = "obs.xml"
sim.execute()
# Bin events into counts map
bin = ctools.ctbin()
bin["inobs"] = "obs.xml"
bin["outcube"] = "cntcube.fits"
bin["ebinalg"] = "LOG"
bin["emin"] = emin
bin["emax"] = emax
bin["enumbins"] = enumbins
bin["nxpix"] = nxpix
bin["nypix"] = nypix
bin["binsz"] = binsz
bin["coordsys"] = coordsys
bin["proj"] = proj
bin["xref"] = ra
bin["yref"] = dec
bin["debug"] = debug
bin.execute()
# Create exposure cube
expcube = ctools.ctexpcube()
expcube["inobs"] = "obs.xml"
expcube["incube"] = "cntcube.fits"
expcube["outcube"] = "expcube.fits"
expcube["caldb"] = caldb
expcube["irf"] = irf
expcube["ebinalg"] = "LOG"
expcube["emin"] = emin
expcube["emax"] = emax
expcube["enumbins"] = enumbins
expcube["nxpix"] = nxpix
expcube["nypix"] = nypix
expcube["binsz"] = binsz
expcube["coordsys"] = coordsys
expcube["proj"] = proj
expcube["xref"] = ra
expcube["yref"] = dec
expcube["debug"] = debug
expcube.execute()
# Create PSF cube
psfcube = ctools.ctpsfcube()
psfcube["inobs"] = "obs.xml"
psfcube["incube"] = "NONE"
psfcube["outcube"] = "psfcube.fits"
psfcube["caldb"] = caldb
psfcube["irf"] = irf
psfcube["ebinalg"] = "LOG"
psfcube["emin"] = emin
psfcube["emax"] = emax
psfcube["enumbins"] = enumbins
psfcube["nxpix"] = 10
psfcube["nypix"] = 10
psfcube["binsz"] = 1.0
psfcube["coordsys"] = coordsys
psfcube["proj"] = proj
psfcube["xref"] = ra
psfcube["yref"] = dec
psfcube["debug"] = debug
psfcube.execute()
# Create background cube
bkgcube = ctools.ctbkgcube()
bkgcube["inobs"] = "obs.xml"
bkgcube["inmodel"] = model
bkgcube["incube"] = "cntcube.fits"
bkgcube["outcube"] = "bkgcube.fits"
bkgcube["outmodel"] = "model_bkg.xml"
bkgcube["caldb"] = caldb
bkgcube["irf"] = irf
bkgcube["ebinalg"] = "LOG"
bkgcube["emin"] = emin
bkgcube["emax"] = emax
bkgcube["enumbins"] = enumbins
bkgcube["nxpix"] = 10
bkgcube["nypix"] = 10
bkgcube["binsz"] = 1.0
bkgcube["coordsys"] = coordsys
bkgcube["proj"] = proj
bkgcube["xref"] = ra
bkgcube["yref"] = dec
bkgcube["debug"] = debug
bkgcube.execute()
# Perform maximum likelihood fitting
like = ctools.ctlike()
like["inobs"] = "cntcube.fits"
like["inmodel"] = "model_bkg.xml"
like["outmodel"] = "fit_results.xml"
like["expcube"] = "expcube.fits"
like["psfcube"] = "psfcube.fits"
like["bkgcube"] = "bkgcube.fits"
like["caldb"] = caldb
like["irf"] = irf
like["debug"] = True # Switch this always on for results in console
like.execute()
# Return
return
def binned_pipeline(duration):
"""
Binned analysis pipeline.
"""
# Set script parameters
model_name = "${CTOOLS}/share/models/crab.xml"
caldb = "prod2"
irf = "South_50h"
ra = 83.63
dec = 22.01
rad_sim = 10.0
tstart = 0.0
tstop = duration
emin = 0.1
emax = 100.0
enumbins = 20
nxpix = 200
nypix = 200
binsz = 0.02
coordsys = "CEL"
proj = "CAR"
# Get start CPU time
tstart = time.clock()
# Simulate events
sim = ctools.ctobssim()
sim["inmodel"].filename(model_name)
sim["caldb"].string(caldb)
sim["irf"].string(irf)
sim["ra"].real(ra)
sim["dec"].real(dec)
sim["rad"].real(rad_sim)
sim["tmin"].real(tstart)
sim["tmax"].real(tstop)
sim["emin"].real(emin)
sim["emax"].real(emax)
sim.run()
# Bin events into counts map
bin = ctools.ctbin(sim.obs())
bin["ebinalg"].string("LOG")
bin["emin"].real(emin)
bin["emax"].real(emax)
bin["enumbins"].integer(enumbins)
bin["nxpix"].integer(nxpix)
bin["nypix"].integer(nypix)
bin["binsz"].real(binsz)
bin["coordsys"].string(coordsys)
bin["xref"].real(ra)
bin["yref"].real(dec)
bin["proj"].string(proj)
bin.run()
# Get ctlike start CPU time
tctlike = time.clock()
# Perform maximum likelihood fitting
like = ctools.ctlike(bin.obs())
like.run()
# Get stop CPU time
tstop = time.clock()
telapsed = tstop - tstart
tctlike = tstop - tctlike
# Return
return telapsed, tctlike
def run(self):
"""
Run the script.
"""
# Switch screen logging on in debug mode
if self.logDebug():
self.log.cout(True)
# Get parameters
self.get_parameters()
# Write input parameters into logger
if self.logTerse():
self.log_parameters()
self.log("\n")
# Write observation into logger
if self.logTerse():
self.log("\n")
self.log.header1("Observation")
self.log(str(self.obs))
self.log("\n")
# Write header
if self.logTerse():
self.log("\n")
self.log.header1("Adjust model parameters")
# Adjust model parameters dependent on input user parameters
for model in self.obs.models():
# Set TS flag for all models to false.
# Source of interest will be set to true later
model.tscalc(False)
# Log model name
if self.logExplicit():
self.log.header3(model.name())
# Deal with the source of interest
if model.name() == self.m_srcname:
for par in model:
if par.is_free() and self.logExplicit():
self.log(" Fixing \""+par.name()+"\"\n")
par.fix()
if par.is_fixed() and self.logExplicit():
self.log(" Freeing \""+par.name()+"\"\n")
model.spectral()[0].free()
if self.m_calc_ts:
model.tscalc(True)
elif self.m_fix_bkg and not model.classname() == "GModelSky":
for par in model:
if par.is_free() and self.logExplicit():
self.log(" Fixing \""+par.name()+"\"\n")
par.fix()
elif self.m_fix_srcs and model.classname() == "GModelSky":
for par in model:
if par.is_free() and self.logExplicit():
self.log(" Fixing \""+par.name()+"\"\n")
par.fix()
# Write header
if self.logTerse():
self.log("\n")
self.log.header1("Generate spectrum")
# Initialise FITS Table with extension "SPECTRUM"
table = gammalib.GFitsBinTable(self.m_ebounds.size())
table.extname("SPECTRUM")
# Add Header for compatibility with gammalib.GMWLSpectrum
table.card("INSTRUME", "CTA", "Name of Instrument")
table.card("TELESCOP", "CTA", "Name of Telescope")
# Create FITS table columns
energy = gammalib.GFitsTableDoubleCol("Energy", self.m_ebounds.size())
energy.unit("TeV")
energy_low = gammalib.GFitsTableDoubleCol("ed_Energy", self.m_ebounds.size())
energy_low.unit("TeV")
energy_high = gammalib.GFitsTableDoubleCol("eu_Energy", self.m_ebounds.size())
energy_high.unit("TeV")
flux = gammalib.GFitsTableDoubleCol("Flux", self.m_ebounds.size())
flux.unit("erg/cm2/s")
flux_err = gammalib.GFitsTableDoubleCol("e_Flux", self.m_ebounds.size())
flux_err.unit("erg/cm2/s")
TSvalues = gammalib.GFitsTableDoubleCol("TS", self.m_ebounds.size())
ulim_values = gammalib.GFitsTableDoubleCol("UpperLimit", self.m_ebounds.size())
ulim_values.unit("erg/cm2/s")
# Loop over energy bins
for i in range(self.m_ebounds.size()):
# Log information
if self.logTerse():
self.log("\n")
self.log.header2("Energy bin "+str(i))
# Get energy boundaries
emin = self.m_ebounds.emin(i)
emax = self.m_ebounds.emax(i)
elogmean = self.m_ebounds.elogmean(i)
elogmean2 = elogmean.MeV() * elogmean.MeV()
# Store energy as TeV
energy[i] = elogmean.TeV()
# Store energy errors
energy_low[i] = (elogmean - emin).TeV()
energy_high[i] = (emax - elogmean).TeV()
# Log information
if self.logExplicit():
self.log.header3("Selecting events")
# Select events
select = ctools.ctselect(self.obs)
select["emin"].real(emin.TeV())
select["emax"].real(emax.TeV())
select["tmin"].value("UNDEFINED")
select["tmax"].value("UNDEFINED")
select["rad"].value("UNDEFINED")
select["ra"].value("UNDEFINED")
select["dec"].value("UNDEFINED")
select.run()
# Retrieve observation
obs = select.obs()
# Binned analysis
if self.m_binned:
# Header
if self.logTerse():
self.log.header3("Binning events")
# Bin events
bin = ctools.ctbin(select.obs())
bin["usepnt"].boolean(False)
bin["ebinalg"].string("LOG")
bin["xref"].real(self.m_xref)
bin["yref"].real(self.m_yref)
bin["binsz"].real(self.m_binsz)
bin["nxpix"].integer(self.m_nxpix)
bin["nypix"].integer(self.m_nypix)
bin["enumbins"].integer(self.m_ebins)
bin["emin"].real(emin.TeV())
bin["emax"].real(emax.TeV())
bin["coordsys"].string(self.m_coordsys)
bin["proj"].string(self.m_proj)
bin.run()
# Header
if self.logTerse():
self.log.header3("Creating exposure cube")
# Create exposure cube
expcube = ctools.ctexpcube(select.obs())
expcube["incube"].filename("NONE")
expcube["usepnt"].boolean(False)
expcube["ebinalg"].string("LOG")
expcube["xref"].real(self.m_xref)
expcube["yref"].real(self.m_yref)
expcube["binsz"].real(self.m_binsz)
expcube["nxpix"].integer(self.m_nxpix)
expcube["nypix"].integer(self.m_nypix)
expcube["enumbins"].integer(self.m_ebins)
expcube["emin"].real(emin.TeV())
expcube["emax"].real(emax.TeV())
expcube["coordsys"].string(self.m_coordsys)
expcube["proj"].string(self.m_proj)
expcube.run()
# Header
if self.logTerse():
self.log.header3("Creating PSF cube")
# Create psf cube
psfcube = ctools.ctpsfcube(select.obs())
psfcube["incube"].filename("NONE")
psfcube["usepnt"].boolean(False)
psfcube["ebinalg"].string("LOG")
psfcube["xref"].real(self.m_xref)
psfcube["yref"].real(self.m_yref)
psfcube["binsz"].real(self.m_binsz)
psfcube["nxpix"].integer(self.m_nxpix)
psfcube["nypix"].integer(self.m_nypix)
psfcube["enumbins"].integer(self.m_ebins)
psfcube["emin"].real(emin.TeV())
psfcube["emax"].real(emax.TeV())
psfcube["coordsys"].string(self.m_coordsys)
psfcube["proj"].string(self.m_proj)
psfcube.run()
# Header
if self.logTerse():
self.log.header3("Creating background cube")
# Create background cube
bkgcube = ctools.ctbkgcube(select.obs())
bkgcube["incube"].filename("NONE")
bkgcube["usepnt"].boolean(False)
bkgcube["ebinalg"].string("LOG")
bkgcube["xref"].real(self.m_xref)
bkgcube["yref"].real(self.m_yref)
bkgcube["binsz"].real(self.m_binsz)
bkgcube["nxpix"].integer(self.m_nxpix)
bkgcube["nypix"].integer(self.m_nypix)
bkgcube["enumbins"].integer(self.m_ebins)
bkgcube["emin"].real(emin.TeV())
bkgcube["emax"].real(emax.TeV())
bkgcube["coordsys"].string(self.m_coordsys)
bkgcube["proj"].string(self.m_proj)
bkgcube.run()
# Set new binned observation
obs = bin.obs()
# Set precomputed binned response
obs[0].response(expcube.expcube(), psfcube.psfcube(), bkgcube.bkgcube())
# Get new models
models = bkgcube.models()
# Fix background models if required
if self.m_fix_bkg:
for model in models:
if not model.classname() == "GModelSky":
for par in model:
par.fix()
# Set new models to binned observation
obs.models(models)
# Header
if self.logTerse():
self.log.header3("Performing fit")
# Likelihood
like = ctools.ctlike(obs)
like.run()
# Skip bin if no event was present
if like.obs().logL() == 0.0:
# Log information
if self.logTerse():
self.log("No event in this bin. Bin is skipped\n")
# Set all values to 0
flux[i] = 0.0
flux_err[i] = 0.0
TSvalues[i] = 0.0
ulim_values[i] = 0.0
continue
# Get results
fitted_models = like.obs().models()
source = fitted_models[self.m_srcname]
# Calculate Upper Limit
ulimit_value = -1.0
if self.m_calc_ulimit:
# Logging information
if self.logTerse():
self.log.header3("Computing upper limit")
# Create upper limit object
ulimit = ctools.ctulimit(like.obs())
ulimit["srcname"].string(self.m_srcname)
ulimit["eref"].real(elogmean.TeV())
# Try to run upper limit and catch exceptions
try:
ulimit.run()
ulimit_value = ulimit.diff_ulimit()
except:
if self.logTerse():
self.log("Upper limit calculation failed\n")
ulimit_value = -1.0
# Get TS value
TS = -1.0
if self.m_calc_ts:
TS = source.ts()
# Get differential flux
fitted_flux = source.spectral().eval(elogmean,gammalib.GTime())
# Compute flux error
parvalue = source.spectral()[0].value()
rel_error = source.spectral()[0].error()/parvalue
e_flux = fitted_flux*rel_error
# Set values for storage
TSvalues[i] = TS
# Convert fluxes to nuFnu
flux[i] = fitted_flux * elogmean2 * gammalib.MeV2erg
flux_err[i] = e_flux * elogmean2 * gammalib.MeV2erg
if ulimit_value > 0.0:
ulim_values[i] = ulimit_value * elogmean2 * gammalib.MeV2erg
# Log information
if self.logExplicit():
self.log("Bin "+str(i)+" ["+str(emin.TeV())+"-"+str(emax.TeV())+"] TeV: ")
self.log("Flux = "+str(flux[i]))
self.log(" +- "+str(flux_err[i])+" [erg/cm2/s]")
if self.m_calc_ts and TSvalues[i] > 0.0:
self.log(", TS = "+str(TS))
if self.m_calc_ulimit and ulim_values[i] > 0.0:
self.log(", UL = "+str(ulim_values[i])+" [erg/cm2/s]")
self.log("\n")
# Append filles columns to fits table
table.append(energy)
table.append(energy_low)
table.append(energy_high)
table.append(flux)
table.append(flux_err)
table.append(TSvalues)
table.append(ulim_values)
# Create the FITS file now
self.fits = gammalib.GFits()
self.fits.append(table)
# Return
return
sim['irf'] = irf
sim['outevents'] = 'events_nu_' + 's_' + irf + '_' + str(
int(tobscta)) + 's_' + str(i + 1) + '.fits'
sim['ra'] = ra
sim['dec'] = dec
sim['rad'] = 5.0
sim['tmin'] = '2020-05-31T12:00:00'
sim['tmax'] = '2020-05-31T12:10:00'
sim['emin'] = emin
sim['emax'] = emax
sim['maxrate'] = 1.0e9
sim['debug'] = debug
sim['edisp'] = edisp
sim.execute()
c_bin = ctools.ctbin()
c_bin['inobs'] = 'events_nu_' + 's_' + irf + '_' + str(
int(tobscta)) + 's_' + str(i + 1) + '.fits'
c_bin['xref'] = ra
c_bin['yref'] = dec
c_bin['proj'] = 'CAR'
c_bin['coordsys'] = 'CEL'
c_bin['binsz'] = binz
c_bin['nxpix'] = x_pixs
c_bin['nypix'] = y_pixs
c_bin['ebinalg'] = 'LOG'
c_bin['emin'] = emin
c_bin['emax'] = emax
c_bin['enumbins'] = n_bins
c_bin['outcube'] = 'cube_' + str(i + 1) + '.fits'
c_bin['debug'] = debug
def binned_pipeline(model_name, duration):
"""
Binned analysis pipeline.
"""
# Set script parameters
caldb = "prod2"
irf = "South_50h"
ra = 83.63
dec = 22.01
rad_sim = 10.0
tstart = 0.0
tstop = duration
emin = 0.1
emax = 100.0
enumbins = 40
nxpix = 200
nypix = 200
binsz = 0.02
coordsys = "CEL"
proj = "CAR"
# Get start CPU time
cpu_start = time.clock()
# Simulate events
sim = ctools.ctobssim()
sim["inmodel"] = model_name
sim["caldb"] = caldb
sim["irf"] = irf
sim["ra"] = ra
sim["dec"] = dec
sim["rad"] = rad_sim
sim["tmin"] = tstart
sim["tmax"] = tstop
sim["emin"] = emin
sim["emax"] = emax
sim.run()
# Bin events into counts map
bin = ctools.ctbin(sim.obs())
bin["ebinalg"] = "LOG"
bin["emin"] = emin
bin["emax"] = emax
bin["enumbins"] = enumbins
bin["nxpix"] = nxpix
bin["nypix"] = nypix
bin["binsz"] = binsz
bin["coordsys"] = coordsys
bin["xref"] = ra
bin["yref"] = dec
bin["proj"] = proj
bin.run()
# Get ctlike start CPU time
cpu_ctlike = time.clock()
# Perform maximum likelihood fitting
like = ctools.ctlike(bin.obs())
like.run()
# Get stop CPU time and compute elapsed times
cpu_stop = time.clock()
cpu_elapsed = cpu_stop - cpu_start
cpu_ctlike = cpu_stop - cpu_ctlike
# Return
return cpu_elapsed, cpu_ctlike
sim['outevents'] = 'events_nu_' + irf + '_' + str(
int(tobscta)) + 's_' + str(i + 1) + '.fits'
sim['ra'] = ra
sim['dec'] = dec
sim['rad'] = 5.0
sim['tmin'] = '2020-05-31T12:00:00'
sim['tmax'] = '2020-05-31T12:10:00'
sim['emin'] = 0.02
sim['emax'] = 199.0
sim['maxrate'] = 1.0e9
sim['seed'] = nuseed
sim['debug'] = debug
sim['edisp'] = edisp
sim.execute()
binning = ctools.ctbin()
binning['inobs'] = 'events_nu_' + irf + '_' + str(
int(tobscta)) + 's_' + str(i + 1) + '.fits'
binning['xref'] = ra
binning['yref'] = dec
binning['coordsys'] = 'CEL'
binning['proj'] = 'CAR'
binning['binsz'] = 0.02
binning['nxpix'] = 500
binning['nypix'] = 500
binning['ebinalg'] = 'LOG'
binning['emin'] = 0.02
binning['emax'] = 199.0
binning['enumbins'] = 40
binning['outcube'] = 'cntcube_nu_' + irf + '_' + str(
int(tobscta)) + 's_' + str(i + 1) + '.fits'
def run_pipeline(obs, emin=0.1, emax=100.0, \
enumbins=20, nxpix=200, nypix=200, binsz=0.02, \
coordsys="CEL", proj="CAR", \
model="${CTOOLS}/share/models/crab.xml", \
caldb="prod2", irf="South_50h", \
debug=False):
"""
Simulation and binned analysis pipeline.
Keywords:
emin - Minimum energy of cube [TeV] (default: 0.1)
emax - Maximum energy of cube [TeV] (default: 100.0)
enumbins - Number of energy bins in cube (default: 20)
nxpix - Number of RA pixels in cube (default: 200)
nypix - Number of DEC pixels in cube (default: 200)
binsz - Spatial cube bin size [deg] (default: 0.02)
coordsys - Cube coordinate system (CEL or GAL)
proj - Cube World Coordinate System (WCS) projection
model - Model Xml file
caldb - Calibration database path (default: "dummy")
irf - Instrument response function (default: cta_dummy_irf)
debug - Enable debugging (default: False)
"""
# Simulate events
sim = ctools.ctobssim(obs)
sim["debug"].boolean(debug)
sim["outevents"].filename("obs.xml")
sim.execute()
# Bin events by looping over all observations in the container
sim_obs = gammalib.GObservations("obs.xml")
obs = gammalib.GObservations()
for run in sim_obs:
# Get event filename and set counts cube filename
eventfile = run.eventfile()
cubefile = "cube_"+eventfile
# Bin events for that observation
bin = ctools.ctbin()
bin["inobs"].filename(eventfile)
bin["outcube"].filename(cubefile)
bin["ebinalg"].string("LOG")
bin["emin"].real(emin)
bin["emax"].real(emax)
bin["enumbins"].integer(enumbins)
bin["nxpix"].integer(nxpix)
bin["nypix"].integer(nypix)
bin["binsz"].real(binsz)
bin["coordsys"].string(coordsys)
bin["usepnt"].boolean(True)
bin["proj"].string(proj)
bin.execute()
# Set observation ID
bin.obs()[0].id(cubefile)
bin.obs()[0].eventfile(cubefile)
# Append result to observations
obs.extend(bin.obs())
# Save XML file
xml = gammalib.GXml()
obs.write(xml)
xml.save("obs_cube.xml")
# Perform maximum likelihood fitting
like = ctools.ctlike()
like["inobs"].filename("obs_cube.xml")
like["inmodel"].filename(model)
like["outmodel"].filename("fit_results.xml")
like["expcube"].filename("NONE")
like["psfcube"].filename("NONE")
like["bkgcube"].filename("NONE")
like["caldb"].string(caldb)
like["irf"].string(irf)
like["debug"].boolean(True) # Switch this always on for results in console
like.execute()
# Return
return
def prepare(obsname, bkgname, rad=2.0, emin=0.3, emax=50.0, ebins=20):
"""
Prepare events for analysis
Parameters
----------
obsname : str
Observation definition XML file
bkgname : str
Background model definition XML file
rad : float, optional
Selection radius (degrees)
emin : float, optional
Minimum energy for analysis (TeV)
emax : float, optional
Maximum energy for analysis (TeV)
ebins : int, optional
Number of energy bins
"""
# Set filenames
cntcube = 'rx_stacked%2.2d_cntcube.fits' % ebins
expcube = 'rx_stacked%2.2d_expcube.fits' % ebins
psfcube = 'rx_stacked%2.2d_psfcube.fits' % ebins
edispcube = 'rx_stacked%2.2d_edispcube.fits' % ebins
bkgcube = 'rx_stacked%2.2d_bkgcube.fits' % ebins
obsname_binned = add_attribute(obsname, '_binned%2.2d' % ebins)
bkgname_stacked = add_attribute(bkgname, '_stacked')
obsname_stacked = add_attribute(obsname, '_stacked%2.2d' % ebins)
obsname_stacked_edisp = add_attribute(obsname_stacked, '_edisp')
# Generate background lookup
generate_background_lookup()
# Continue only if selected events do not exist
if not os.path.isfile(obsname):
# Setup task parameters
select = ctools.ctselect()
select['inobs'] = '$HESSDATA/obs/obs_rx.xml'
select['outobs'] = obsname
select['ra'] = 'UNDEF'
select['dec'] = 'UNDEF'
select['rad'] = rad
select['tmin'] = 'UNDEF'
select['tmax'] = 'UNDEF'
select['emin'] = emin
select['emax'] = emax
select['usethres'] = 'DEFAULT'
select['logfile'] = 'rx_hess_select_events.log'
select.logFileOpen()
# Select events
select.execute()
# Continue only if background model does not exist
if not os.path.isfile(bkgname):
# Setup task parameters
bkg = cscripts.csbkgmodel()
bkg['inobs'] = '$HESSDATA/obs/obs_rx.xml'
bkg['outmodel'] = bkgname
bkg['instrument'] = 'HESS'
bkg['spatial'] = 'LOOKUP'
bkg['slufile'] = 'off_lookup.fits'
bkg['gradient'] = True
bkg['spectral'] = 'NODES'
bkg['ebinalg'] = 'LOG'
bkg['emin'] = emin
bkg['emax'] = 30.0
bkg['enumbins'] = 8
bkg['runwise'] = True
bkg['rad'] = rad
bkg['logfile'] = 'rx_hess_create_background.log'
bkg.logFileOpen()
# Generate background model
bkg.execute()
# Continue only if counts cube does not exist
if not os.path.isfile(cntcube):
# Setup task parameters
ctbin = ctools.ctbin()
ctbin['inobs'] = obsname
ctbin['outobs'] = cntcube
ctbin['ebinalg'] = 'LOG'
ctbin['emin'] = emin
ctbin['emax'] = emax
ctbin['enumbins'] = ebins
ctbin['coordsys'] = 'CEL'
ctbin['proj'] = 'TAN'
ctbin['xref'] = 258.1125
ctbin['yref'] = -39.6867
ctbin['nxpix'] = 300
ctbin['nypix'] = 300
ctbin['binsz'] = 0.02
ctbin['logfile'] = 'rx_hess_create_cntcube.log'
ctbin.logFileOpen()
# Generate counts cube
ctbin.execute()
# Continue only if counts cubes for binned analysis do not exist
if not os.path.isfile(obsname_binned):
# Setup task parameters
ctbin = ctools.ctbin()
ctbin['inobs'] = obsname
ctbin['outobs'] = obsname_binned
ctbin['stack'] = False
ctbin['usepnt'] = True
ctbin['ebinalg'] = 'LOG'
ctbin['emin'] = emin
ctbin['emax'] = emax
ctbin['enumbins'] = ebins
ctbin['coordsys'] = 'CEL'
ctbin['proj'] = 'TAN'
ctbin['nxpix'] = 200
ctbin['nypix'] = 200
ctbin['binsz'] = 0.02
ctbin['logfile'] = 'rx_hess_create_cntcube_binned.log'
ctbin.logFileOpen()
# Generate counts cubes
ctbin.execute()
# Continue only if exposure cube does not exist
if not os.path.isfile(expcube):
# Setup task parameters
ctexpcube = ctools.ctexpcube()
ctexpcube['inobs'] = obsname
ctexpcube['incube'] = 'NONE'
ctexpcube['ebinalg'] = 'LOG'
ctexpcube['emin'] = 0.1 # Full energy range
ctexpcube['emax'] = 100.0 # Full energy range
ctexpcube['enumbins'] = 300 # Factor ~3 oversampling of IRF
ctexpcube['coordsys'] = 'CEL'
ctexpcube['proj'] = 'TAN'
ctexpcube['xref'] = 258.1125
ctexpcube['yref'] = -39.6867
ctexpcube['nxpix'] = 300
ctexpcube['nypix'] = 300
ctexpcube['binsz'] = 0.02
ctexpcube['outcube'] = expcube
ctexpcube['logfile'] = 'rx_hess_create_expcube.log'
ctexpcube.logFileOpen()
# Generate exposure cube
ctexpcube.execute()
# Continue only if PSF cube does not exist
if not os.path.isfile(psfcube):
# Setup task parameters
ctpsfcube = ctools.ctpsfcube()
ctpsfcube['inobs'] = obsname
ctpsfcube['incube'] = 'NONE'
ctpsfcube['ebinalg'] = 'LOG'
ctpsfcube['emin'] = 0.1 # Full energy range
ctpsfcube['emax'] = 100.0 # Full energy range
ctpsfcube['enumbins'] = 300 # Factor ~3 oversampling of IRF
ctpsfcube['coordsys'] = 'CEL'
ctpsfcube['proj'] = 'TAN'
ctpsfcube['xref'] = 258.1125
ctpsfcube['yref'] = -39.6867
ctpsfcube['nxpix'] = 30
ctpsfcube['nypix'] = 30
ctpsfcube['binsz'] = 0.2
ctpsfcube['amax'] = 0.7 # Full H.E.S.S. PSF range
ctpsfcube['anumbins'] = 300 # Factor ~2 oversampling of IRF
ctpsfcube['outcube'] = psfcube
ctpsfcube['logfile'] = 'rx_hess_create_psfcube.log'
ctpsfcube.logFileOpen()
# Generate PSF cube
ctpsfcube.execute()
# Continue only if energy dispersion cube does not exist
if not os.path.isfile(edispcube):
# Setup task parameters
ctedispcube = ctools.ctedispcube()
ctedispcube['inobs'] = obsname
ctedispcube['incube'] = 'NONE'
ctedispcube['ebinalg'] = 'LOG'
ctedispcube['emin'] = 0.1 # Full energy range
ctedispcube['emax'] = 100.0 # Full energy range
ctedispcube['enumbins'] = 300 # Factor ~3 oversampling of IRF
ctedispcube['coordsys'] = 'CEL'
ctedispcube['proj'] = 'TAN'
ctedispcube['xref'] = 258.1125
ctedispcube['yref'] = -39.6867
ctedispcube['nxpix'] = 30
ctedispcube['nypix'] = 30
ctedispcube['binsz'] = 0.2
ctedispcube['migramax'] = 5.0
ctedispcube['migrabins'] = 300
ctedispcube['outcube'] = edispcube
ctedispcube['logfile'] = 'rx_hess_create_edispcube.log'
ctedispcube.logFileOpen()
# Generate energy dispersion cube
ctedispcube.execute()
# Continue only if background cube does not exist
if not os.path.isfile(bkgcube):
# Setup task parameters
ctbkgcube = ctools.ctbkgcube()
ctbkgcube['inobs'] = obsname
ctbkgcube['incube'] = cntcube
ctbkgcube['inmodel'] = bkgname
ctbkgcube['outcube'] = bkgcube
ctbkgcube['outmodel'] = bkgname_stacked
ctbkgcube['logfile'] = 'rx_hess_create_bkgcube.log'
ctbkgcube.logFileOpen()
# Generate background cube
ctbkgcube.execute()
# Continue only if stacked observation definition XML file does not
# exist
if not os.path.isfile(obsname_stacked):
# Build stacked observation
run = gammalib.GCTAObservation(cntcube, expcube, psfcube, bkgcube)
run.name('RX J1713.7-3946')
run.instrument('HESS')
# Append to observation container
obs = gammalib.GObservations()
obs.append(run)
# Save observation container
obs.save(obsname_stacked)
# Continue only if stacked observation definition XML file with energy
# energy dispersion enabled does not exist
if not os.path.isfile(obsname_stacked_edisp):
# Build stacked observation
run = gammalib.GCTAObservation(cntcube, expcube, psfcube, edispcube,
bkgcube)
run.name('RX J1713.7-3946')
run.instrument('HESS')
# Append to observation container
obs = gammalib.GObservations()
obs.append(run)
# Save observation container
obs.save(obsname_stacked_edisp)
# Continue only if stacked model definition XML file does exist
if os.path.isfile(bkgname_stacked):
# Load model definition XML files
joint = gammalib.GModels(bkgname)
stacked = gammalib.GModels(bkgname_stacked)
# Get spectral component of joint file and remplace it as spectral
# component of stacked file
spectrum = joint[0].spectral()
for i in range(spectrum.nodes()):
spectrum.intensity(i, 1.0)
spectrum.autoscale()
stacked[0].spectral(spectrum)
# Save stacked model
stacked.save(bkgname_stacked)
# Return
return
def sim(obs,
log=False,
debug=False,
chatter=2,
edisp=False,
seed=0,
emin=None,
emax=None,
nbins=0,
binsz=0.05,
npix=200,
proj='TAN',
coord='GAL'):
"""
Simulate events for all observations in the container
Parameters
----------
obs : `~gammalib.GObservations`
Observation container without events
log : bool, optional
Create log file(s)
debug : bool, optional
Create console dump?
chatter : int, optional
Chatter level
edisp : bool, optional
Apply energy dispersion?
seed : int, integer
Seed value for simulations
emin : float, optional
Minimum energy of counts cube for binned (TeV)
emax : float, optional
Maximum energy of counts cube for binned (TeV)
nbins : int, optional
Number of energy bins (0=unbinned)
binsz : float, optional
Pixel size for binned simulation (deg/pixel)
npix : int, optional
Number of pixels in X and Y for binned simulation
proj : str, optional
Projection for binned simulation
coord : str, optional
Coordinate system for binned simulation
Returns
-------
obs : `~gammalib.GObservations`
Observation container filled with simulated events
"""
# Allocate ctobssim application and set parameters
sim = ctools.ctobssim(obs)
sim['seed'] = seed
sim['edisp'] = edisp
sim['chatter'] = chatter
sim['debug'] = debug
# Optionally open the log file
if log:
sim.logFileOpen()
# Run ctobssim application. This will loop over all observations in the
# container and simulation the events for each observation. Note that
# events are not added together, they still apply to each observation
# separately.
sim.run()
# Binned option?
if nbins > 0:
# If energy boundaries are not given then determine common energy
# boundaries for all observations
if emin == None or emax == None:
emin = None
emax = None
for run in sim.obs():
run_emin = run.events().ebounds().emin().TeV()
run_emax = run.events().ebounds().emax().TeV()
if emin == None:
emin = run_emin
elif run_emin > emin:
emin = run_emin
if emax == None:
emax = run_emax
elif run_emax > emax:
emax = run_emax
# Allocate ctbin application and set parameters
bin = ctools.ctbin(sim.obs())
bin['ebinalg'] = 'LOG'
bin['emin'] = emin
bin['emax'] = emax
bin['enumbins'] = nbins
bin['usepnt'] = True # Use pointing for map centre
bin['nxpix'] = npix
bin['nypix'] = npix
bin['binsz'] = binsz
bin['coordsys'] = coord
bin['proj'] = proj
bin['chatter'] = chatter
bin['debug'] = debug
# Optionally open the log file
if log:
bin.logFileOpen()
# Run ctbin application. This will loop over all observations in
# the container and bin the events in counts maps
bin.run()
# Make a deep copy of the observation that will be returned
# (the ctbin object will go out of scope one the function is
# left)
obs = bin.obs().copy()
else:
# Make a deep copy of the observation that will be returned
# (the ctobssim object will go out of scope one the function is
# left)
obs = sim.obs().copy()
# Delete the simulation
del sim
# Return observation container
return obs
def stackedPipeline(
name="Crab",
obsfile="index.xml",
l=0.01,
b=0.01,
emin=0.1,
emax=100.0,
enumbins=20,
nxpix=200,
nypix=200,
binsz=0.02,
coordsys="CEL",
proj="CAR",
caldb="prod2",
irf="acdc1a",
debug=False,
inmodel="Crab",
outmodel="results",
):
"""
Simulation and stacked analysis pipeline
Parameters
----------
obs : `~gammalib.GObservations`
Observation container
ra : float, optional
Right Ascension of counts cube centre (deg)
dec : float, optional
Declination of Region of counts cube centre (deg)
emin : float, optional
Minimum energy (TeV)
emax : float, optional
Maximum energy (TeV)
enumbins : int, optional
Number of energy bins
nxpix : int, optional
Number of pixels in X axis
nypix : int, optional
Number of pixels in Y axis
binsz : float, optional
Pixel size (deg)
coordsys : str, optional
Coordinate system
proj : str, optional
Coordinate projection
debug : bool, optional
Debug function
"""
# Bin events into counts map
bin = ctools.ctbin()
bin["inobs"] = obsfile
bin["ebinalg"] = "LOG"
bin["emin"] = emin
bin["emax"] = emax
bin["enumbins"] = enumbins
bin["nxpix"] = nxpix
bin["nypix"] = nypix
bin["binsz"] = binsz
bin["coordsys"] = coordsys
bin["proj"] = proj
bin["xref"] = l
bin["yref"] = b
bin["debug"] = debug
bin["outobs"] = "cntcube.fits"
bin.execute()
print("Datacube : done!")
# Create exposure cube
expcube = ctools.ctexpcube()
# expcube['incube']=bin.obs()
expcube["inobs"] = obsfile
expcube["incube"] = "NONE"
expcube["ebinalg"] = "LOG"
expcube["caldb"] = caldb
expcube["irf"] = irf
expcube["emin"] = emin
expcube["emax"] = emax
expcube["enumbins"] = enumbins
expcube["nxpix"] = nxpix
expcube["nypix"] = nypix
expcube["binsz"] = binsz
expcube["coordsys"] = coordsys
expcube["proj"] = proj
expcube["xref"] = l
expcube["yref"] = b
expcube["debug"] = debug
expcube["outcube"] = "cube_exp.fits"
expcube.execute()
print("Expcube : done!")
# Create PSF cube
psfcube = ctools.ctpsfcube()
psfcube["inobs"] = obsfile
psfcube["incube"] = "NONE"
psfcube["ebinalg"] = "LOG"
psfcube["caldb"] = caldb
psfcube["irf"] = irf
psfcube["emin"] = emin
psfcube["emax"] = emax
psfcube["enumbins"] = enumbins
psfcube["nxpix"] = 10
psfcube["nypix"] = 10
psfcube["binsz"] = 1.0
psfcube["coordsys"] = coordsys
psfcube["proj"] = proj
psfcube["xref"] = l
psfcube["yref"] = b
psfcube["debug"] = debug
psfcube["outcube"] = "psf_cube.fits"
psfcube.execute()
print("Psfcube : done!")
edispcube = ctools.ctedispcube()
edispcube["inobs"] = obsfile
edispcube["ebinalg"] = "LOG"
edispcube["incube"] = "NONE"
edispcube["caldb"] = caldb
edispcube["irf"] = irf
edispcube["xref"] = l
edispcube["yref"] = b
edispcube["proj"] = proj
edispcube["coordsys"] = coordsys
edispcube["binsz"] = 1.0
edispcube["nxpix"] = 10
edispcube["nypix"] = 10
edispcube["emin"] = emin
edispcube["emax"] = emax
edispcube["enumbins"] = enumbins
edispcube["outcube"] = "edisp_cube.fits"
edispcube["debug"] = debug
edispcube.execute()
print("Edispcube : done!")
# Create background cube
bkgcube = ctools.ctbkgcube()
bkgcube["inobs"] = obsfile
bkgcube["incube"] = "cntcube.fits"
bkgcube["caldb"] = caldb
bkgcube["irf"] = irf
bkgcube["debug"] = debug
bkgcube["inmodel"] = str(inmodel)
bkgcube["outcube"] = "bkg_cube.fits"
bkgcube["outmodel"] = "bkg_cube.xml"
bkgcube.execute()
print("Bkgcube : done!")
# Fix the instrumental background parameters
bkgcube.models()["BackgroundModel"]["Prefactor"].fix()
bkgcube.models()["BackgroundModel"]["Index"].fix()
#
# # Attach background model to observation container
bin.obs().models(bkgcube.models())
#
#
# # Set Exposure and Psf cube for first CTA observation
# # (ctbin will create an observation with a single container)
bin.obs()[0].response(expcube.expcube(), psfcube.psfcube(),
edispcube.edispcube(), bkgcube.bkgcube())
# Perform maximum likelihood fitting
like = ctools.ctlike(bin.obs())
# like['inmodel']='bkg_cube.xml'
like["edisp"] = True
# like['edispcube'] = 'edisp_cube.fits'
# like['expcube'] = 'cube_exp.fits'
# like['psfcube'] = 'psf_cube.fits'
# like['bkgcube'] = 'bkg_cube.fits'
like["outmodel"] = str(outmodel)
# like['outcovmat']=inmodel+'_covmat.txt'
like["debug"] = debug # Switch this always on for results in console
# like['statistic']='CSTAT'
like.execute()
print("Likelihood : done!")
# Set the best-fit models (from ctlike) for the counts cube
bin.obs().models(like.obs().models())
# Obtain the best-fit butterfly
try:
butterfly = ctools.ctbutterfly(bin.obs())
butterfly["srcname"] = name
butterfly["inmodel"] = str(outmodel)
butterfly["edisp"] = True
butterfly["emin"] = emin
butterfly["emax"] = emax
butterfly["outfile"] = str(outmodel.parent) + "/" + str(
outmodel.stem) + ".txt"
butterfly[
"debug"] = debug # Switch this always on for results in console
# like['statistic']='CSTAT'
butterfly.execute()
print("Butterfly : done!")
except:
print("I COULDN'T CALCULATE THE BUTTERFLY....")
# Extract the spectrum
try:
csspec = cscripts.csspec(bin.obs())
csspec["srcname"] = name
csspec["inmodel"] = str(outmodel)
csspec["method"] = "AUTO"
csspec["ebinalg"] = "LOG"
csspec["emin"] = emin
csspec["emax"] = emax
csspec["enumbins"] = 10
csspec["edisp"] = True
csspec["outfile"] = str(outmodel.parent) + "/" + str(
outmodel.stem) + ".fits"
csspec["debug"] = debug # Switch this always on for results in console
csspec.execute()
print("Csspec : done!")
except:
print("I COULDN'T CALCULATE THE SPECTRUM....")
# Return
return
def _test_python(self):
"""
Test ctbin from Python
"""
# Allocate ctbin
binning = ctools.ctbin()
# Check that empty ctbin has an empty observation container and counts
# cube
self.test_value(binning.obs().size(), 0,
'Check that empty ctbin has an empty observation container')
self.test_value(binning.cube().size(), 0,
'Check that empty ctbin has an empty counts cube')
# Check that saving does not nothing
binning['logfile'] = 'ctbin_py0.log'
binning['outcube'] = 'ctbin_py0.fits'
binning.logFileOpen()
binning.save()
self.test_assert(not os.path.isfile('ctbin_py0.fits'),
'Check that no counts cube has been created')
# Check that publishing does not lead to an exception or segfault
binning.publish()
# Check that clearing does not lead to an exception or segfault
binning.clear()
# Now set ctbin parameters
binning['inobs'] = self._events
binning['outcube'] = 'ctbin_py1.fits'
binning['ebinalg'] = 'LOG'
binning['emin'] = 0.1
binning['emax'] = 100.0
binning['enumbins'] = 10
binning['nxpix'] = 40
binning['nypix'] = 40
binning['binsz'] = 0.1
binning['coordsys'] = 'CEL'
binning['proj'] = 'CAR'
binning['xref'] = 83.63
binning['yref'] = 22.01
binning['logfile'] = 'ctbin_py1.log'
binning['chatter'] = 2
# Run ctbin tool
binning.logFileOpen()
binning.run()
# Check content of observation container and counts cube
self._check_observation(binning, 3105)
self._check_cube(binning.cube(), 3105)
# Copy ctbin tool
cpy_bin = binning.copy()
# Check content of observation container and counts cube
self._check_observation(cpy_bin, 3105)
self._check_cube(cpy_bin.cube(), 3105)
# Run copy of ctbin tool again
cpy_bin['logfile'] = 'ctbin_py2.log'
cpy_bin['chatter'] = 3
cpy_bin.logFileOpen()
cpy_bin.run()
# Check content of observation container and counts cube. Now an empty
# event cube is expected since on input the observation is binned, and
# any binned observation will be skipped.
self._check_observation(cpy_bin, 0)
self._check_cube(cpy_bin.cube(), 0)
# Save counts cube
binning.save()
# Load counts cube and check content
evt = gammalib.GCTAEventCube('ctbin_py1.fits')
self._check_cube(evt, 3105)
# Now clear ctbin tool
binning.clear()
# Check that cleared ctbin has an empty observation container and
# counts cube
self.test_value(binning.obs().size(), 0,
'Check that empty ctbin has an empty observation container')
self.test_value(binning.cube().size(), 0,
'Check that empty ctbin has an empty counts cube')
# Prepare observation container for stacking of events into a
# single counts cube
obs = self._obs_events()
# Set-up ctbin using an observation container
binning = ctools.ctbin(obs)
binning['outcube'] = 'ctbin_py3.fits'
binning['ebinalg'] = 'LOG'
binning['emin'] = 0.1
binning['emax'] = 100.0
binning['enumbins'] = 10
binning['nxpix'] = 40
binning['nypix'] = 40
binning['binsz'] = 0.1
binning['coordsys'] = 'CEL'
binning['proj'] = 'CAR'
binning['xref'] = 83.63
binning['yref'] = 22.01
binning['publish'] = True
binning['logfile'] = 'ctbin_py3.log'
binning['chatter'] = 3
# Execute ctbin tool
binning.logFileOpen()
binning.execute()
# Check content of observation and cube (need multiplier=3 since
# three identical observations have been appended)
self._check_observation(binning, 3105, multiplier=3)
self._check_cube(binning.cube(), 3105, multiplier=3)
# Load counts cube and check content.
evt = gammalib.GCTAEventCube('ctbin_py3.fits')
self._check_cube(evt, 3105, multiplier=3)
# And finally go for a fully Pythonic version with all parameters
# being specified in a dictionary
pars = {'inobs': self._events, 'ebinalg': 'LIN', 'emin': 0.1,
'emax': 100.0, 'enumbins': 10, 'nxpix': 40, 'nypix': 40,
'binsz': 0.1, 'coordsys': 'CEL', 'proj': 'CAR',
'xref': 83.63, 'yref': 22.01, 'outcube': 'ctbin_py4.fits',
'logfile': 'ctbin_py4.log', 'chatter': 2}
binning = ctools.ctbin()
binning.pardict(pars)
binning.logFileOpen()
binning.execute()
# Load counts cube and check content
evt = gammalib.GCTAEventCube('ctbin_py4.fits')
self._check_cube(evt, 3105)
# Return
return
def run_pipeline(obs, emin=0.1, emax=100.0,
enumbins=20, nxpix=200, nypix=200, binsz=0.02,
coordsys='CEL', proj='CAR',
model='data/crab.xml',
caldb='prod2', irf='South_0.5h',
debug=False):
"""
Simulation and binned analysis pipeline
Parameters
----------
obs : `~gammalib.GObservations`
Observation container
emin : float, optional
Minimum energy (TeV)
emax : float, optional
Maximum energy (TeV)
enumbins : int, optional
Number of energy bins
nxpix : int, optional
Number of pixels in X axis
nypix : int, optional
Number of pixels in Y axis
binsz : float, optional
Pixel size (deg)
coordsys : str, optional
Coordinate system
proj : str, optional
Coordinate projection
model : str, optional
Model definition XML file
caldb : str, optional
Calibration database path
irf : str, optional
Instrument response function
debug : bool, optional
Debug function
"""
# Simulate events
sim = ctools.ctobssim(obs)
sim['debug'] = debug
sim['outevents'] = 'obs.xml'
sim.execute()
# Bin events by looping over all observations in the container
sim_obs = gammalib.GObservations('obs.xml')
obs = gammalib.GObservations()
for run in sim_obs:
# Get event filename and set counts cube filename
eventfile = run.eventfile().url()
cubefile = 'cube_'+eventfile
# Bin events for that observation
bin = ctools.ctbin()
bin['inobs'] = eventfile
bin['outcube'] = cubefile
bin['ebinalg'] = 'LOG'
bin['emin'] = emin
bin['emax'] = emax
bin['enumbins'] = enumbins
bin['nxpix'] = nxpix
bin['nypix'] = nypix
bin['binsz'] = binsz
bin['coordsys'] = coordsys
bin['usepnt'] = True
bin['proj'] = proj
bin.execute()
# Set observation ID
bin.obs()[0].id(cubefile)
bin.obs()[0].eventfile(cubefile)
# Append result to observations
obs.extend(bin.obs())
# Save XML file
xml = gammalib.GXml()
obs.write(xml)
xml.save('obs_cube.xml')
# Perform maximum likelihood fitting
like = ctools.ctlike()
like['inobs'] = 'obs_cube.xml'
like['inmodel'] = model
like['outmodel'] = 'fit_results.xml'
like['expcube'] = 'NONE'
like['psfcube'] = 'NONE'
like['bkgcube'] = 'NONE'
like['caldb'] = caldb
like['irf'] = irf
like['debug'] = True # Switch this always on for results in console
like.execute()
# Return
return
def run_pipeline(obs, ra=83.63, dec=22.01, emin=0.1, emax=100.0,
enumbins=20, nxpix=200, nypix=200, binsz=0.02,
coordsys="CEL", proj="CAR", debug=False):
"""
Simulation and stacked analysis pipeline.
Keywords:
ra - RA of cube centre [deg] (default: 83.6331)
dec - DEC of cube centre [deg] (default: 22.0145)
emin - Minimum energy of cube [TeV] (default: 0.1)
emax - Maximum energy of cube [TeV] (default: 100.0)
enumbins - Number of energy bins in cube (default: 20)
nxpix - Number of RA pixels in cube (default: 200)
nypix - Number of DEC pixels in cube (default: 200)
binsz - Spatial cube bin size [deg] (default: 0.02)
coordsys - Cube coordinate system (CEL or GAL)
proj - Cube World Coordinate System (WCS) projection
debug - Enable debugging (default: False)
"""
# Simulate events
sim = ctools.ctobssim(obs)
sim["debug"] = debug
sim.run()
# Bin events into counts map
bin = ctools.ctbin(sim.obs())
bin["ebinalg"] = "LOG"
bin["emin"] = emin
bin["emax"] = emax
bin["enumbins"] = enumbins
bin["nxpix"] = nxpix
bin["nypix"] = nypix
bin["binsz"] = binsz
bin["coordsys"] = coordsys
bin["proj"] = proj
bin["xref"] = ra
bin["yref"] = dec
bin["debug"] = debug
bin.run()
# Create exposure cube
expcube = ctools.ctexpcube(sim.obs())
expcube["incube"] = "NONE"
expcube["ebinalg"] = "LOG"
expcube["emin"] = emin
expcube["emax"] = emax
expcube["enumbins"] = enumbins
expcube["nxpix"] = nxpix
expcube["nypix"] = nypix
expcube["binsz"] = binsz
expcube["coordsys"] = coordsys
expcube["proj"] = proj
expcube["xref"] = ra
expcube["yref"] = dec
expcube["debug"] = debug
expcube.run()
# Create PSF cube
psfcube = ctools.ctpsfcube(sim.obs())
psfcube["incube"] = "NONE"
psfcube["ebinalg"] = "LOG"
psfcube["emin"] = emin
psfcube["emax"] = emax
psfcube["enumbins"] = enumbins
psfcube["nxpix"] = 10
psfcube["nypix"] = 10
psfcube["binsz"] = 1.0
psfcube["coordsys"] = coordsys
psfcube["proj"] = proj
psfcube["xref"] = ra
psfcube["yref"] = dec
psfcube["debug"] = debug
psfcube.run()
# Create background cube
bkgcube = ctools.ctbkgcube(sim.obs())
bkgcube["incube"] = "NONE"
bkgcube["ebinalg"] = "LOG"
bkgcube["emin"] = emin
bkgcube["emax"] = emax
bkgcube["enumbins"] = enumbins
bkgcube["nxpix"] = 10
bkgcube["nypix"] = 10
bkgcube["binsz"] = 1.0
bkgcube["coordsys"] = coordsys
bkgcube["proj"] = proj
bkgcube["xref"] = ra
bkgcube["yref"] = dec
bkgcube["debug"] = debug
bkgcube.run()
# Attach background model to observation container
bin.obs().models(bkgcube.models())
# Set Exposure and Psf cube for first CTA observation
# (ctbin will create an observation with a single container)
bin.obs()[0].response(expcube.expcube(), psfcube.psfcube(), bkgcube.bkgcube())
# Perform maximum likelihood fitting
like = ctools.ctlike(bin.obs())
like["debug"] = True # Switch this always on for results in console
like.run()
# Return
return
def run(self):
"""
Run the script
"""
# Switch screen logging on in debug mode
if self._logDebug():
self._log.cout(True)
# Get parameters
self._get_parameters()
# Write observation into logger
self._log_observations(gammalib.NORMAL, self.obs(), 'Observation')
# If a counts and model cube are specified then load them as sky map
if self._use_maps:
countmap = gammalib.GSkyMap(self['inobs'].filename())
modelmap = gammalib.GSkyMap(self['modcube'].filename())
# ... otherwise build a counts cube and model cube
else:
# Do not build counts cube if we have already one in the observation
# container
if self._skip_binning:
cta_counts_cube = gammalib.GCTAEventCube(self.obs()[0].events())
# ... otherwise generate one now from the event list
else:
# Write header
self._log_header1(gammalib.TERSE, 'Generate binned map (ctbin)')
# Create countsmap
binning = ctools.ctbin(self.obs())
binning['xref'] = self['xref'].real()
binning['yref'] = self['yref'].real()
binning['proj'] = self['proj'].string()
binning['coordsys'] = self['coordsys'].string()
binning['ebinalg'] = self['ebinalg'].string()
binning['nxpix'] = self['nxpix'].integer()
binning['nypix'] = self['nypix'].integer()
binning['binsz'] = self['binsz'].real()
if self['ebinalg'].string() == 'FILE':
binning['ebinfile'] = self['ebinfile'].filename().file()
else:
binning['enumbins'] = self['enumbins'].integer()
binning['emin'] = self['emin'].real()
binning['emax'] = self['emax'].real()
binning['chatter'] = self['chatter'].integer()
binning['clobber'] = self['clobber'].boolean()
binning['debug'] = self['debug'].boolean()
binning.run()
# Retrieve counts cube
cta_counts_cube = binning.cube()
# Assign GCTAEventCube to skymap
countmap = cta_counts_cube.counts()
# Write header
self._log_header1(gammalib.TERSE, 'Generate model map (ctmodel)')
# Create model map
model = ctools.ctmodel(self.obs())
model.cube(cta_counts_cube)
model['chatter'] = self['chatter'].integer()
model['clobber'] = self['clobber'].boolean()
model['debug'] = self['debug'].boolean()
model['edisp'] = self['edisp'].boolean()
model.run()
# Get model map into GSkyMap object
modelmap = model.cube().counts().copy()
# Calculate residual maps
# Note that we need a special
# construct here to avoid memory leaks. This seems to be a SWIG feature
# as SWIG creates a new object when calling binning.cube()
countmap1 = countmap.copy()
countmap1.stack_maps()
modelmap.stack_maps()
self._resmap = obsutils.residuals(self,countmap1,modelmap)
# Optionally publish map
if self['publish'].boolean():
self.publish()
# Return
return
def _bin_evlist(self, obs):
"""
Turn single event list into counts cube
Parameters
----------
obs : `~gammalib.GObservations`
Observation container with single event list
Returns
-------
obs, info : `~gammalib.GObservations`, dict
Binned observation container and dictionary with event list ROI
and energy range information
"""
# Retrieve information about ROI in event list
roi = obs[0].roi()
ra = roi.centre().dir().ra_deg()
dec = roi.centre().dir().dec_deg()
rad = roi.radius()
# We will cover the whole ROI with 0.02 deg binning
npix = int(2.0 * rad / 0.02) + 1
# Log binning of events
self._log_string(gammalib.EXPLICIT, 'Binning events')
# Bin events
cntcube = ctools.ctbin(obs)
cntcube['xref'] = ra
cntcube['yref'] = dec
cntcube['binsz'] = 0.02
cntcube['nxpix'] = npix
cntcube['nypix'] = npix
cntcube['proj'] = 'TAN'
cntcube['coordsys'] = 'CEL'
cntcube['ebinalg'] = self['ebinalg'].string()
if self['ebinalg'].string() == 'FILE':
cntcube['ebinfile'] = self['ebinfile'].filename()
else:
cntcube['enumbins'] = self['enumbins'].integer()
cntcube['emin'] = self['emin'].real()
cntcube['emax'] = self['emax'].real()
cntcube.run()
# Retrieve the binned observation container
binned_obs = cntcube.obs().copy()
# Check if energy boundaries provided by user extend beyond the
# content of the event list
if self['emin'].real() > obs[0].events().emin().TeV():
emin = 'INDEF'
else:
emin = obs[0].events().emin().TeV()
if self['emax'].real() < obs[0].events().emax().TeV():
emax = 'INDEF'
else:
emax = obs[0].events().emax().TeV()
# Log energy range
self._log_value(gammalib.EXPLICIT, 'Minimum energy (TeV)', emin)
self._log_value(gammalib.EXPLICIT, 'Maximum energy (TeV)', emax)
# Put ROI and E bound info in dictionary
info = {
'was_list': True,
'roi_ra': ra,
'roi_dec': dec,
'roi_rad': rad,
'emin': emin,
'emax': emax
}
# Return new oberservation container
return binned_obs, info
