def diffusefun(gal ='ring_24month_P74_v1.fits', energy=1000, nside=512):
""" an HParray object wrapping the galactic diffuse """
f = os.path.expandvars(os.path.join('$FERMI', 'diffuse', gal))
t = skymaps.DiffuseFunction(f)
def skyplotfun(skydir):
return t.value(skydir, energy)
return HPskyfun('galactic', skyplotfun, nside=nside)
def mapcube_to_healpix(inputfile,
suffix='_nside256_bpd4',
inpath= '$FERMI/diffuse',
outpath=None,
energy_bins=np.logspace(1.75,6.5, 20),
emin=58.5 ):
""" convert a MapCube to column format, consistent with diffuse group
"""
fullinputfile = os.path.expandvars(os.path.join(inpath,inputfile))
assert os.path.exists(fullinputfile), 'File not found: %s' % fullinputfile
d = skymaps.DiffuseFunction(fullinputfile)
galbands = []
energies = np.sqrt( energy_bins[:-1] * energy_bins[1:] )
for elow, ehigh in zip(energy_bins[:-1], energy_bins[1:]):
print elow,ehigh
d.setEnergyRange(max(elow, emin), ehigh)
t = HPskyfun('e_%d'%np.sqrt(elow*ehigh), d, 256)
t.setcol()
t.vec /= (ehigh-elow)
galbands.append(t)
tt = HEALPixFITS(galbands)
flux_table = tt.make_table()
energy_column = pyfits.Column('MeV', format='E', unit='MeV', array=energies)
energy_table = pyfits.new_table([energy_column])
energy_table.name='ENERGIES'
hdus = [ pyfits.PrimaryHDU(header=None), flux_table, energy_table]
fulloutfile = os.path.expandvars(os.path.join(outpath if outpath is not None else inpath,
inputfile.replace('.fits', suffix+'.fits')))
if os.path.exists(fulloutfile):
os.remove(fulloutfile)
print 'writing output file %s' %fulloutfile
pyfits.HDUList(hdus).writeto(fulloutfile)
def make_exposure():
if dataset.exposure_cube is not None:
## use pregenerated gtexpcube2 cube; turn off interpolation
return [
skymaps.DiffuseFunction(f, 1000., False)
for f in dataset.exposure_cube
]
skymaps.EffectiveArea.set_CALDB(dataset.CALDBManager.CALDB)
skymaps.Exposure.set_cutoff(np.cos(np.radians(dataset.thetacut)))
inst = ['front', 'back']
aeff_files = dataset.CALDBManager.get_aeff()
ok = [os.path.exists(file) for file in aeff_files]
if not all(ok):
raise DataSetError('one of CALDB aeff files not found: %s' %
aeff_files)
self.ea = [skymaps.EffectiveArea('', file) for file in aeff_files]
if dataset.verbose: print ' -->effective areas at 1 GeV: ', \
['%s: %6.1f'% (inst[i],self.ea[i](1000)) for i in range(len(inst))]
if dataset.use_weighted_livetime and hasattr(
dataset, 'weighted_lt'):
return [
skymaps.Exposure(dataset.lt, dataset.weighted_lt, ea)
for ea in self.ea
]
else:
return [skymaps.Exposure(dataset.lt, ea) for ea in self.ea]
def __init__(self,livetime,aeff,
correction=None,
weighted_livetime=None,
exposure_cube=None,
cthetamin=.4):
self.aeff = aeff
self.lt = livetime
self.weighted_lt = weighted_livetime
if correction is not None:
self.correction = correction
else:
self.correction = lambda x: 1.0
if exposure_cube is not None:
self._cpp_exposure = skymaps.DiffuseFunction(exposure_cube,1000.,False)
else:
skymaps.Exposure.set_cutoff(cthetamin)
if self.weighted_lt is None:
self._cpp_exposure = skymaps.Exposure(self.lt, self.aeff)
else:
self._cpp_exposure = skymaps.Exposure(self.lt,self.weighted_lt,self.aeff)
def make_exposure():
if dataset.exposure_cube is not None:
## use pregenerated gtexpcube2 cube; turn off interpolation
return [
skymaps.DiffuseFunction(f, 1000., False)
for f in dataset.exposure_cube
]
type_names = datadict.get('type_names', ('FRONT', 'BACK'))
if type_names == 'psf':
type_names = ['PSF{}'.format(i) for i in range(4)]
skymaps.EffectiveArea.set_CALDB(dataset.CALDBManager.CALDB)
skymaps.Exposure.set_cutoff(np.cos(np.radians(dataset.thetacut)))
aeff_files = dataset.CALDBManager.get_aeff()
ok = [os.path.exists(file) for file in aeff_files]
if not all(ok):
raise DataSetError('one of CALDB aeff files not found: %s' %
aeff_files)
if pyfits.open(aeff_files[0])[1].name != 'EFFECTIVE AREA':
# new format with combined
self.ea = [
skymaps.EffectiveArea('', file, 'EFFECTIVE AREA_' + name)
for file, name in zip(aeff_files, type_names)
]
else:
self.ea = [
skymaps.EffectiveArea('', file) for file in aeff_files
]
if dataset.verbose: print ' -->effective areas at 1 GeV: ', \
['%s: %6.1f'% (type_names[i],self.ea[i](1000)) for i in range(len(type_names))]
if dataset.use_weighted_livetime and hasattr(
dataset, 'weighted_lt'):
return [
skymaps.Exposure(dataset.lt, dataset.weighted_lt, ea)
for ea in self.ea
]
else:
return [skymaps.Exposure(dataset.lt, ea) for ea in self.ea]
