csphagen.py
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#! /usr/bin/env python
# ==========================================================================
# Computes the PHA spectra for source/background and ARF/RMF files using the
# reflected region method
#
# Copyright (C) 2017-2018 Luigi Tibaldo
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>.
#
# ==========================================================================
import gammalib
import ctools
import math
import sys
# =============== #
# csfindobs class #
# =============== #
class csphagen(ctools.csobservation):
"""
Generate PHA, ARF and RMF files for classical IACT spectral analysis
"""
# Constructor
def __init__(self, *argv):
"""
Constructor
"""
# Initialise application by calling the appropriate class constructor
self._init_csobservation(self.__class__.__name__, ctools.__version__, argv)
# Initialise other variables
self._ebounds = gammalib.GEbounds()
self._src_dir = gammalib.GSkyDir()
self._src_reg = gammalib.GSkyRegions()
self._bkg_regs = []
self._excl_reg = None
self._has_exclusion = False
self._srcshape = ''
self._rad = 0.0
# Return
return
# Private methods
def _query_src_direction(self):
"""
Set up the source direction parameter.
Query relevant parameters.
"""
self._src_dir = gammalib.GSkyDir()
coordsys = self['coordsys'].string()
if coordsys == 'CEL':
ra = self['ra'].real()
dec = self['dec'].real()
self._src_dir.radec_deg(ra, dec)
elif coordsys == 'GAL':
glon = self['glon'].real()
glat = self['glat'].real()
self._src_dir.lb_deg(glon, glat)
def _get_parameters_bkgmethod_reflected(self):
"""
Get parameters for REFLECTED background method
"""
# Get source shape
self._srcshape = self['srcshape'].string()
# Set source region (so far only CIRCLE is supported)
if self._srcshape == 'CIRCLE':
# Query source direction
self._query_src_direction()
# Query minimum number of background regions
self['bkgregmin'].integer()
# Set circular source region
self._rad = self['rad'].real()
self._src_reg.append(gammalib.GSkyRegionCircle(self._src_dir, self._rad))
# Return
return
def _get_parameters_bkgmethod_custom(self):
"""
Get parameters for CUSTOM background method
Raises
------
RuntimeError
Only one On region is allowed
"""
# Set up source region
filename = self['srcregfile'].filename()
self._src_reg = gammalib.GSkyRegions(filename)
# Raise an exception if there is more than one source region
if len(self._src_reg) != 1:
raise RuntimeError('Only one On region is allowed')
# Set up source direction. Query parameters if neccessary.
if isinstance(self._src_reg[0], gammalib.GSkyRegionCircle):
self._src_dir = self._src_reg[0].centre()
self._rad = self._src_reg[0].radius()
else:
self._query_src_direction()
# Make sure that all CTA observations have an Off region by loading the
# Off region region the parameter 'bkgregfile' for all CTA observations
# without Off region
for obs in self.obs():
#if obs.instrument() == 'CTA':
if obs.classname() == 'GCTAObservation':
if obs.off_regions().is_empty():
filename = self['bkgregfile'].filename()
regions = gammalib.GSkyRegions(filename)
obs.off_regions(regions)
# Return
return
def _get_parameters_bkgmethod(self):
"""
Get background method parameters
"""
# Get background method
bkgmethod = self['bkgmethod'].string()
# Get background method dependent parameters
if bkgmethod == 'REFLECTED':
self._get_parameters_bkgmethod_reflected()
elif bkgmethod == 'CUSTOM':
self._get_parameters_bkgmethod_custom()
# Query parameters that are needed for all background methods
self['maxoffset'].real()
# Return
return
def _get_parameters(self):
"""
Get parameters from parfile and setup observations
"""
# Setup observations (require response and allow event list, don't
# allow counts cube)
self._setup_observations(self.obs(), True, True, False)
# Set energy bounds
self._ebounds = self._create_ebounds()
# Initialize empty src regions container
self._src_reg = gammalib.GSkyRegions()
# Exclusion map
if self['inexclusion'].filename().is_fits():
self._excl_reg = gammalib.GSkyRegionMap(self['inexclusion'].filename())
self._has_exclusion = True
else:
self._has_exclusion = False
# Query remaining parametersStacking
self['stack'].boolean()
# Query ahead output parameters
if (self._read_ahead()):
self['outobs'].string()
self['prefix'].string()
# If there are no observations in container then get them from the
# parameter file
if self.obs().is_empty():
self.obs(self._get_observations(False))
# Get background method parameters (have to come after setting up of
# observations)
self._get_parameters_bkgmethod()
# Write input parameters into logger
self._log_parameters(gammalib.TERSE)
# Return
return
def _reflected_regions(self, obs):
"""
Calculate list of reflected regions for a single observation (pointing)
Parameters
----------
obs : `~gammalib.GCTAObservation()`
CTA observation
Returns
-------
regions : `~gammalib.GSkyRegions`
List of reflected regions
"""
# Initialise list of reflected regions
regions = gammalib.GSkyRegions()
# Get offset angle of source
pnt_dir = obs.pointing().dir()
offset = pnt_dir.dist_deg(self._src_dir)
# If ...
if offset <= self._rad or offset >= self['maxoffset'].real():
self._log_string(gammalib.EXPLICIT, 'Observation %s pointed at %.3f '
'deg from source' % ((obs.id(), offset)))
# ... otherwise
else:
posang = pnt_dir.posang_deg(self._src_dir)
if self._srcshape == 'CIRCLE':
# angular separation of reflected regions wrt camera center
# and number
alpha = 1.05 * 2.0 * self._rad / offset
# 1.05 ensures background regions do not overlap due to
# numerical precision issues
N = int(2.0 * math.pi / alpha)
if N < self['bkgregmin'].integer() + 3:
self._log_string(gammalib.EXPLICIT, 'Observation %s: '
'insufficient regions for background '
'estimation' % (obs.id()))
# Otherwise loop over position angle to create reflected
# regions
else:
alpha = 360.0 / N
for s in range(2, N - 1):
dphi = s * alpha
ctr_dir = pnt_dir.clone()
ctr_dir.rotate_deg(posang + dphi, offset)
region = gammalib.GSkyRegionCircle(ctr_dir, self._rad)
if self._has_exclusion:
if self._excl_reg.overlaps(region):
self._log_string(gammalib.VERBOSE, 'Observation '
'%s: reflected region overlaps '
'with exclusion region' %
(obs.id()))
else:
regions.append(region)
else:
regions.append(region)
# Return reflected regions
return regions
def _set_models(self, obs):
"""
Set models in observation container
The method replaces all "CTA", "HESS", "VERITAS", and "MAGIC"
background models by "CTAOnOff" background models.
Parameters
----------
obs : `~gammalib.GObservations()`
Observation container
Returns
-------
obs : `~gammalib.GObservations()`
Observation container
"""
# Initialise model container
models = gammalib.GModels()
# Loop over all models and replace CTA/HESS/VERITAS/MAGIC background
# models by CTAOnOff background model
for model in self.obs().models():
if 'GCTA' in model.classname():
if 'CTA' in model.instruments() or \
'HESS' in model.instruments() or \
'VERITAS' in model.instruments() or \
'MAGIC' in model.instruments():
model.instruments('CTAOnOff')
models.append(model)
# Append model to observation container
obs.models(models)
# Return observation container
return obs
def _etrue_ebounds(self):
"""
Set true energy boundaries
Returns
-------
ebounds : `~gammalib.GEbounds()`
True energy boundaries
"""
# Determine minimum and maximum energies
emin = self._ebounds.emin() * 0.5
emax = self._ebounds.emax() * 1.2
if emin.TeV() < self['etruemin'].real():
emin = gammalib.GEnergy(self['etruemin'].real(), 'TeV')
if emax.TeV() > self['etruemax'].real():
emax = gammalib.GEnergy(self['etruemax'].real(), 'TeV')
# Determine number of energy bins
n_decades = (emax.log10TeV() - emin.log10TeV())
n_bins = int(n_decades * float(self['etruebins'].integer())) + 1
# Set energy boundaries
ebounds = gammalib.GEbounds(n_bins, emin, emax)
# Write header
self._log_header1(gammalib.TERSE, 'True energy binning')
# Log true energy bins
for i in range(ebounds.size()):
value = '%s - %s' % (str(ebounds.emin(i)), str(ebounds.emax(i)))
self._log_value(gammalib.TERSE, 'Bin %d' % (i+1), value)
# Return energy boundaries
return ebounds
def _set_background_regions(self, obs):
"""
Set background regions for an observation
Parameters
----------
obs : `~gammalib.GCTAObservation()`
CTA observation
Returns
-------
regions : `~gammalib.GSkyRegions()`
Background regions
"""
# Initialise empty background regions for this observation
bkg_reg = gammalib.GSkyRegions()
# If reflected background is requested then created reflected
# background regions
if self['bkgmethod'].string() == 'REFLECTED':
bkg_reg = self._reflected_regions(obs)
# ... otherwise if custom background is requested then get the
# background regions from the observation. We use a copy here since
# otherwise the background regions go out of scope once the observations
# are replaced by the On/Off observations.
elif self['bkgmethod'].string() == 'CUSTOM':
bkg_reg = obs.off_regions().copy()
# Return background regions
return bkg_reg
# Public methods
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')
# Set true energy bins
etrue_ebounds = self._etrue_ebounds()
# Write header
self._log_header1(gammalib.TERSE, 'Spectral binning')
# Log reconstructed energy bins
for i in range(self._ebounds.size()):
value = '%s - %s' % (str(self._ebounds.emin(i)),
str(self._ebounds.emax(i)))
self._log_value(gammalib.TERSE, 'Bin %d' % (i+1), value)
# Write header
self._log_header1(gammalib.NORMAL,
'Generation of source and background spectra')
# Initialise run variables
outobs = gammalib.GObservations()
self._bkg_regs = []
# Loop through observations and generate pha, arf, rmf files
for obs in self.obs():
# Skip non CTA observations
#if obs.instrument() != 'CTA':
if obs.classname() != 'GCTAObservation':
self._log_string(gammalib.NORMAL, 'Skip %s observation "%s"' % \
(obs.instrument(), obs.id()))
continue
# Log current observation
self._log_string(gammalib.NORMAL, 'Process observation "%s"' % \
(obs.id()))
# Set background regions for this observation
bkg_reg = self._set_background_regions(obs)
# If there are background regions then create On/Off observation
# and append it to the output container
if bkg_reg.size() >= self['bkgregmin'].integer():
onoff = gammalib.GCTAOnOffObservation(obs, self._src_dir,
etrue_ebounds,
self._ebounds,
self._src_reg,
bkg_reg)
onoff.id(obs.id())
outobs.append(onoff)
self._bkg_regs.append({'regions': bkg_reg, 'id': obs.id()})
else:
self._log_string(gammalib.NORMAL, 'Observation %s not included '
'in spectra generation' % (obs.id()))
# Stack observations
if outobs.size() > 1 and self['stack'].boolean() == True:
# Write header
self._log_header1(gammalib.NORMAL, 'Stacking %d observations' %
(outobs.size()))
# Stack observations
stacked_obs = gammalib.GCTAOnOffObservation(outobs)
# Put stacked observations in output container
outobs = gammalib.GObservations()
outobs.append(stacked_obs)
# Set models in output container
outobs = self._set_models(outobs)
# Set observation container
self.obs(outobs)
# Return
return
def save(self):
"""
Save data
"""
# Write header
self._log_header1(gammalib.TERSE, 'Save data')
# Get XML output filename, prefix and clobber
outobs = self['outobs'].string()
prefix = self['prefix'].string()
clobber = self['clobber'].boolean()
# Loop over all observation in container
for obs in self.obs():
# Set filenames
if self['stack'].boolean():
onname = prefix + '_stacked_pha_on.fits'
offname = prefix + '_stacked_pha_off.fits'
arfname = prefix + '_stacked_arf.fits'
rmfname = prefix + '_stacked_rmf.fits'
elif self.obs().size() > 1:
onname = prefix + '_%s_pha_on.fits' % (obs.id())
offname = prefix + '_%s_pha_off.fits' % (obs.id())
arfname = prefix + '_%s_arf.fits' % (obs.id())
rmfname = prefix + '_%s_rmf.fits' % (obs.id())
else:
onname = prefix + '_pha_on.fits'
offname = prefix + '_pha_off.fits'
arfname = prefix + '_arf.fits'
rmfname = prefix + '_rmf.fits'
# Save files
obs.on_spec().save(onname, clobber)
obs.off_spec().save(offname, clobber)
obs.arf().save(arfname, clobber)
obs.rmf().save(rmfname, clobber)
# Log file names
self._log_value(gammalib.NORMAL, 'PHA on file', onname)
self._log_value(gammalib.NORMAL, 'PHA off file', offname)
self._log_value(gammalib.NORMAL, 'ARF file', arfname)
self._log_value(gammalib.NORMAL, 'RMF file', arfname)
# Save observation definition XML file
self.obs().save(outobs)
# Log file name
self._log_value(gammalib.NORMAL, 'Obs. definition XML file', outobs)
# Save ds9 On region file
regname = prefix + '_on.reg'
self._src_reg.save(regname)
self._log_value(gammalib.NORMAL, 'On region file', regname)
# Save ds9 Off region files
for bkg_reg in self._bkg_regs:
# Set filename
if len(self._bkg_regs) > 1:
regname = prefix + '_%s_off.reg' % (bkg_reg['id'])
else:
regname = prefix + '_off.reg'
# Save ds9 region file
bkg_reg['regions'].save(regname)
# Log file name
self._log_value(gammalib.NORMAL, 'Off region file', regname)
# Return
return
# ======================== #
# Main routine entry point #
# ======================== #
if __name__ == '__main__':
# Create instance of application
app = csphagen(sys.argv)
# Execute application
app.execute()