def addPSPLSuperExpCutoff(lib, name, ra, dec, ebl=None, eflux=0,
flux_free=1, flux_value=1e-9, flux_scale=0,
flux_max=1000.0, flux_min=1e-5,
index1_free=1, index1_value=-2.0,
index1_min=-10.0, index1_max=-0.,
cutoff_free=1, cutoff_value=1e4,
cutoff_min=20, cutoff_max=3e5,
index2_free=0, index2_value=1.0,
index2_min=0.0, index2_max=10.0,extendedName=""):
"""Add a source with a SUPEREXPCUTOFF model"""
elim_min = 30
elim_max = 300000
if flux_scale == 0:
flux_scale = utils.fluxScale(flux_value)
flux_value /= flux_scale
doc = lib.ownerDocument
src = doc.createElement('source')
src.setAttribute('name', name)
if extendedName=="":
src.setAttribute('type', 'PointSource')
else:
src.setAttribute('type', 'DiffuseSource')
spec = doc.createElement('spectrum')
try:
spec.setAttribute('type', 'EblAtten::PLSuperExpCutoff')
addParameter(spec, 'tau_norm', ebl['free_tau_norm'], ebl['tau_norm'], 1.0, 0, 2.5)
addParameter(spec, 'redshift', ebl['free_redshift'], ebl['redshift'], 1.0, 0, 5)
addParameter(spec, 'ebl_model', 0, ebl['model'], 1.0, 0, 20)
except TypeError,NameError:
spec.setAttribute('type', 'PLSuperExpCutoff')
def ChangeModel(comp, E1, E2, name, Pref, Gamma):
"""Change the spectral model of a source called name
to allow a fit between E1 and E2
If the spectral model is PowerLaw, the prefactor is updated
if not the model is change to PowerLaw.
The index is frozen in all cases"""
# if approximated Gamma is outside of bounds set it to limit
Gamma_min = -5
Gamma_max = 0.5
Gamma = min(max(Gamma_min, Gamma), Gamma_max)
Eav = utils.GetE0(E1, E2)
spectrum = comp.logLike.getSource(name).getSrcFuncs()['Spectrum']
spectrum.getParam('Prefactor').setBounds(1e-5, 1e5)
spectrum.getParam('Prefactor').setScale(utils.fluxScale(Pref))
spectrum.getParam('Prefactor').setValue(utils.fluxNorm(Pref))
spectrum.getParam('Index').setBounds(Gamma_min, Gamma_max)
spectrum.getParam('Index').setValue(Gamma)
spectrum.getParam('Index').setFree(0)
spectrum.getParam('Scale').setValue(Eav)
spectrum.getParam('Scale').setBounds(20, 3e6)
return comp
def addPSPowerLaw2(lib, name, ra, dec, ebl=None, emin=200, emax=3e5,
flux_free=1, flux_value=1.6e-8, flux_scale=0,
flux_max=1000.0, flux_min=1e-5,
index_free=1, index_value=-2.0,
index_min=-5.0, index_max=-0.5,extendedName=""):
"""Add a source with a POWERLAW2 model"""
elim_min = 30
elim_max = 300000
if emin < elim_min:
elim_min = emin
if emax > elim_max:
elim_max = emax
if flux_scale == 0:
flux_scale = utils.fluxScale(flux_value)
flux_value /= flux_scale
doc = lib.ownerDocument
src = doc.createElement('source')
src.setAttribute('name', name)
if extendedName=="":
src.setAttribute('type', 'PointSource')
else:
src.setAttribute('type', 'DiffuseSource')
spec = doc.createElement('spectrum')
try:
spec.setAttribute('type', 'EblAtten::PowerLaw2')
addParameter(spec, 'tau_norm', ebl['free_tau_norm'], ebl['tau_norm'], 1.0, 0, 2.5)
addParameter(spec, 'redshift', ebl['free_redshift'], ebl['redshift'], 1.0, 0, 5)
addParameter(spec, 'ebl_model', 0, ebl['model'], 1.0, 0, 20)
except TypeError,NameError:
spec.setAttribute('type', 'PowerLaw2')
def ChangeModel(comp, E1, E2, name, Pref, Gamma):
"""Change the spectral model of a source called name
to allow a fit between E1 and E2
If the spectral model is PowerLaw, the prefactor is updated
if not the model is change to PowerLaw.
The index is frozen in all cases"""
# if approximated Gamma is outside of bounds set it to limit
Gamma_min=-5
Gamma_max=0.5
Gamma = min(max(Gamma_min,Gamma),Gamma_max)
Eav = utils.GetE0(E1, E2)
spectrum = comp.logLike.getSource(name).getSrcFuncs()['Spectrum']
spectrum.getParam('Prefactor').setBounds(1e-5,1e5)
spectrum.getParam('Prefactor').setScale(utils.fluxScale(Pref))
spectrum.getParam('Prefactor').setValue(utils.fluxNorm(Pref))
spectrum.getParam('Index').setBounds(Gamma_min,Gamma_max)
spectrum.getParam('Index').setValue(Gamma)
spectrum.getParam('Index').setFree(False)
spectrum.getParam('Scale').setValue(Eav)
spectrum.getParam('Scale').setBounds(20,3e6)
return comp
def addPSLogparabola(lib, name, ra, dec, ebl=None, enorm=300,
norm_free=1, norm_value=1e-9, norm_scale=0,
norm_max=1000.0, norm_min=1e-5,
alpha_free=1, alpha_value=1.0,
alpha_min=.5, alpha_max=5.,
beta_free=1, beta_value=1.0,
beta_min=0, beta_max=5.0,extendedName=""):
"""Add a source with a LOGPARABOLA model"""
elim_min = 30
elim_max = 300000
if enorm == 0:
enorm = 2e5 # meanEnergy(emin,emax,index_value)
norm_value *= (enorm / 100.0) ** alpha_value
if norm_scale == 0:
norm_scale = utils.fluxScale(norm_value)
norm_value /= norm_scale
doc = lib.ownerDocument
src = doc.createElement('source')
src.setAttribute('name', name)
if extendedName=="":
src.setAttribute('type', 'PointSource')
else:
src.setAttribute('type', 'DiffuseSource')
spec = doc.createElement('spectrum')
try:
spec.setAttribute('type', 'EblAtten::LogParabola')
addParameter(spec, 'tau_norm', ebl['free_tau_norm'], ebl['tau_norm'], 1.0, 0, 2.5)
addParameter(spec, 'redshift', ebl['free_redshift'], ebl['redshift'], 1.0, 0, 5)
addParameter(spec, 'ebl_model', 0, ebl['model'], 1.0, 0, 20)
except TypeError,NameError:
spec.setAttribute('type', 'LogParabola')
def addPSPowerLaw2(lib, name, ra, dec, emin=200, emax=3e5,
flux_free=1, flux_value=1.6e-8, flux_scale=0,
flux_max=1000.0, flux_min=1e-5,
index_free=1, index_value=-2.0,
index_min=-5.0, index_max=-0.5,extendedName=""):
"""Add a source with a POWERLAW2 model"""
elim_min = 30
elim_max = 300000
if emin < elim_min:
elim_min = emin
if emax > elim_max:
elim_max = emax
if flux_scale == 0:
flux_scale = utils.fluxScale(flux_value)
flux_value /= flux_scale
doc = lib.ownerDocument
src = doc.createElement('source')
src.setAttribute('name', name)
if extendedName=="":
src.setAttribute('type', 'PointSource')
else:
src.setAttribute('type', 'DiffuseSource')
spec = doc.createElement('spectrum')
spec.setAttribute('type', 'PowerLaw2')
addParameter(spec, 'Integral',
flux_free, flux_value, flux_scale, flux_min, flux_max)
addParameter(spec, 'Index', index_free, index_value, 1.0,
index_min, index_max)
addParameter(spec, 'LowerLimit', 0, emin, 1.0, elim_min, elim_max)
addParameter(spec, 'UpperLimit', 0, emax, 1.0, elim_min, elim_max)
src.appendChild(spec)
spatial = AddSpatial(doc,ra,dec,extendedName)
src.appendChild(spatial)
lib.appendChild(src)
def addPSPowerLaw1(lib, name, ra, dec, eflux=0,
flux_free=1, flux_value=1e-9, flux_scale=0,
flux_max=1000.0, flux_min=1e-5,
index_free=1, index_value=-2.0,
index_min=-5.0, index_max=-0.5,extendedName=""):
"""Add a source with a POWERLAW1 model"""
elim_min = 30
elim_max = 300000
if flux_scale == 0:
flux_scale = utils.fluxScale(flux_value)
flux_value /= flux_scale
doc = lib.ownerDocument
src = doc.createElement('source')
src.setAttribute('name', name)
if extendedName=="":
src.setAttribute('type', 'PointSource')
else:
src.setAttribute('type', 'DiffuseSource')
spec = doc.createElement('spectrum')
spec.setAttribute('type', 'PowerLaw')
addParameter(spec, 'Prefactor',
flux_free, flux_value, flux_scale, flux_min, flux_max)
addParameter(spec, 'Index', index_free, index_value, 1.0,
index_min, index_max)
addParameter(spec, 'Scale', 0, eflux, 1.0, elim_min, elim_max)
src.appendChild(spec)
spatial = AddSpatial(doc,ra,dec,extendedName)
src.appendChild(spatial)
lib.appendChild(src)
def addPSPLSuperExpCutoff(lib,
name,
ra,
dec,
eflux=0,
flux_free=1,
flux_value=1e-9,
flux_scale=0,
flux_max=1000.0,
flux_min=1e-5,
index1_free=1,
index1_value=-2.0,
index1_min=-5.0,
index1_max=-0.,
cutoff_free=1,
cutoff_value=1e4,
cutoff_min=200,
cutoff_max=3e5,
index2_free=0,
index2_value=1.0,
index2_min=0.0,
index2_max=5.0,
extendedName=""):
"""Add a source with a SUPEREXPCUTOFF model"""
elim_min = 30
elim_max = 300000
if flux_scale == 0:
flux_scale = utils.fluxScale(flux_value)
flux_value /= flux_scale
doc = lib.ownerDocument
src = doc.createElement('source')
src.setAttribute('name', name)
if extendedName == "":
src.setAttribute('type', 'PointSource')
else:
src.setAttribute('type', 'DiffuseSource')
spec = doc.createElement('spectrum')
spec.setAttribute('type', 'PLSuperExpCutoff')
addParameter(spec, 'Prefactor', flux_free, flux_value, flux_scale,
flux_min, flux_max)
addParameter(spec, 'Index1', index1_free, index1_value, 1.0, index1_min,
index1_max)
addParameter(spec, 'Scale', 0, eflux, 1.0, elim_min, elim_max)
addParameter(spec, 'Cutoff', cutoff_free, cutoff_value, 1.0, cutoff_min,
cutoff_max)
addParameter(spec, 'Index2', index2_free, index2_value, 1.0, index2_min,
index2_max)
src.appendChild(spec)
spatial = AddSpatial(doc, ra, dec, extendedName)
src.appendChild(spatial)
lib.appendChild(src)
def addPSLogparabola(lib,
name,
ra,
dec,
enorm=300,
norm_free=1,
norm_value=1e-9,
norm_scale=0,
norm_max=1000.0,
norm_min=1e-5,
alpha_free=1,
alpha_value=1.0,
alpha_min=.5,
alpha_max=5.,
beta_free=1,
beta_value=1.0,
beta_min=0.0005,
beta_max=5.0,
extendedName=""):
"""Add a source with a LOGPARABOLA model"""
elim_min = 30
elim_max = 300000
if enorm == 0:
enorm = 2e5 # meanEnergy(emin,emax,index_value)
norm_value *= (enorm / 100.0)**alpha_value
if norm_scale == 0:
norm_scale = utils.fluxScale(norm_value)
norm_value /= norm_scale
doc = lib.ownerDocument
src = doc.createElement('source')
src.setAttribute('name', name)
if extendedName == "":
src.setAttribute('type', 'PointSource')
else:
src.setAttribute('type', 'DiffuseSource')
spec = doc.createElement('spectrum')
spec.setAttribute('type', 'LogParabola')
addParameter(spec, 'norm', norm_free, norm_value, norm_scale, norm_min,
norm_max)
addParameter(spec, 'alpha', alpha_free, alpha_value, 1.0, alpha_min,
alpha_max)
addParameter(spec, 'Eb', 0, enorm, 1.0, elim_min, elim_max)
addParameter(spec, 'beta', beta_free, beta_value, 1.0, beta_min, beta_max)
src.appendChild(spec)
spatial = AddSpatial(doc, ra, dec, extendedName)
src.appendChild(spatial)
lib.appendChild(src)
def addPSPowerLaw2(lib,
name,
ra,
dec,
emin=200,
emax=3e5,
flux_free=1,
flux_value=1.6e-8,
flux_scale=0,
flux_max=1000.0,
flux_min=1e-5,
index_free=1,
index_value=-2.0,
index_min=-5.0,
index_max=-0.5,
extendedName=""):
"""Add a source with a POWERLAW2 model"""
elim_min = 30
elim_max = 300000
if emin < elim_min:
elim_min = emin
if emax > elim_max:
elim_max = emax
if flux_scale == 0:
flux_scale = utils.fluxScale(flux_value)
flux_value /= flux_scale
doc = lib.ownerDocument
src = doc.createElement('source')
src.setAttribute('name', name)
if extendedName == "":
src.setAttribute('type', 'PointSource')
else:
src.setAttribute('type', 'DiffuseSource')
spec = doc.createElement('spectrum')
spec.setAttribute('type', 'PowerLaw2')
addParameter(spec, 'Integral', flux_free, flux_value, flux_scale, flux_min,
flux_max)
addParameter(spec, 'Index', index_free, index_value, 1.0, index_min,
index_max)
addParameter(spec, 'LowerLimit', 0, emin, 1.0, elim_min, elim_max)
addParameter(spec, 'UpperLimit', 0, emax, 1.0, elim_min, elim_max)
src.appendChild(spec)
spatial = AddSpatial(doc, ra, dec, extendedName)
src.appendChild(spatial)
lib.appendChild(src)
def addPSPowerLaw1(lib,
name,
ra,
dec,
eflux=0,
flux_free=1,
flux_value=1e-9,
flux_scale=0,
flux_max=1000.0,
flux_min=1e-5,
index_free=1,
index_value=-2.0,
index_min=-5.0,
index_max=-0.5,
extendedName=""):
"""Add a source with a POWERLAW1 model"""
elim_min = 30
elim_max = 300000
if flux_scale == 0:
flux_scale = utils.fluxScale(flux_value)
flux_value /= flux_scale
doc = lib.ownerDocument
src = doc.createElement('source')
src.setAttribute('name', name)
if extendedName == "":
src.setAttribute('type', 'PointSource')
else:
src.setAttribute('type', 'DiffuseSource')
spec = doc.createElement('spectrum')
spec.setAttribute('type', 'PowerLaw')
addParameter(spec, 'Prefactor', flux_free, flux_value, flux_scale,
flux_min, flux_max)
addParameter(spec, 'Index', index_free, index_value, 1.0, index_min,
index_max)
addParameter(spec, 'Scale', 0, eflux, 1.0, elim_min, elim_max)
src.appendChild(spec)
spatial = AddSpatial(doc, ra, dec, extendedName)
src.appendChild(spatial)
lib.appendChild(src)
def ChangeModel(Fit, E1, E2, name, Pref, Gamma):
"""Change the spectral model of a source called name
to allow a fit between E1 and E2
If the spectral model is PowerLaw, the prefactor is updated
if not the model is change to PowerLaw.
The index is frozen in all cases"""
Eav = utils.GetE0(E1, E2)
# Set Parameters
Fit.logLike.getSource(name).getSrcFuncs()['Spectrum'].getParam(
'Prefactor').setBounds(1e-5, 1e5)
Fit.logLike.getSource(name).getSrcFuncs()['Spectrum'].getParam(
'Prefactor').setScale(utils.fluxScale(Pref))
Fit.logLike.getSource(name).getSrcFuncs()['Spectrum'].getParam(
'Prefactor').setValue(utils.fluxNorm(Pref))
Gamma_min = -5
Gamma_max = 0
# if approximated Gamma is outside of bounds set it to limit
if Gamma < Gamma_min:
Gamma = Gamma_min
elif Gamma > Gamma_max:
Gamma = Gamma_max
Fit.logLike.getSource(name).getSrcFuncs()['Spectrum'].getParam(
'Index').setBounds(Gamma_min, Gamma_max)
Fit.logLike.getSource(name).getSrcFuncs()['Spectrum'].getParam(
'Index').setValue(Gamma)
Fit.logLike.getSource(name).getSrcFuncs()['Spectrum'].getParam(
'Index').setFree(0)
Fit.logLike.getSource(name).getSrcFuncs()['Spectrum'].getParam(
'Scale').setValue(Eav)
Fit.logLike.getSource(name).getSrcFuncs()['Spectrum'].getParam(
'Scale').setBounds(20, 3e6)
return Fit
def addPSPLSuperExpCutoff(lib, name, ra, dec, eflux=0,
flux_free=1, flux_value=1e-9, flux_scale=0,
flux_max=1000.0, flux_min=1e-5,
index1_free=1, index1_value=-2.0,
index1_min=-10.0, index1_max=-0.,
cutoff_free=1, cutoff_value=1e4,
cutoff_min=200, cutoff_max=3e5,
index2_free=0, index2_value=1.0,
index2_min=0.0, index2_max=10.0,extendedName=""):
"""Add a source with a SUPEREXPCUTOFF model"""
elim_min = 30
elim_max = 300000
if flux_scale == 0:
flux_scale = utils.fluxScale(flux_value)
flux_value /= flux_scale
doc = lib.ownerDocument
src = doc.createElement('source')
src.setAttribute('name', name)
if extendedName=="":
src.setAttribute('type', 'PointSource')
else:
src.setAttribute('type', 'DiffuseSource')
spec = doc.createElement('spectrum')
spec.setAttribute('type', 'PLSuperExpCutoff')
addParameter(spec, 'Prefactor',
flux_free, flux_value, flux_scale, flux_min, flux_max)
addParameter(spec, 'Index1', index1_free, index1_value, 1.0,
index1_min, index1_max)
addParameter(spec, 'Scale', 0, eflux, 1.0, elim_min, elim_max)
addParameter(spec, 'Cutoff', cutoff_free, cutoff_value, 1.0,
cutoff_min, cutoff_max)
addParameter(spec, 'Index2', index2_free, index2_value, 1.0,
index2_min, index2_max)
src.appendChild(spec)
spatial = AddSpatial(doc,ra,dec,extendedName)
src.appendChild(spatial)
lib.appendChild(src)
def addPSLogparabola(lib, name, ra, dec, enorm=300,
norm_free=1, norm_value=1e-9, norm_scale=0,
norm_max=1000.0, norm_min=1e-5,
alpha_free=1, alpha_value=1.0,
alpha_min=.5, alpha_max=5.,
beta_free=1, beta_value=1.0,
beta_min=0.0005, beta_max=5.0,extendedName=""):
"""Add a source with a LOGPARABOLA model"""
elim_min = 30
elim_max = 300000
if enorm == 0:
enorm = 2e5 # meanEnergy(emin,emax,index_value)
norm_value *= (enorm / 100.0) ** alpha_value
if norm_scale == 0:
norm_scale = utils.fluxScale(norm_value)
norm_value /= norm_scale
doc = lib.ownerDocument
src = doc.createElement('source')
src.setAttribute('name', name)
if extendedName=="":
src.setAttribute('type', 'PointSource')
else:
src.setAttribute('type', 'DiffuseSource')
spec = doc.createElement('spectrum')
spec.setAttribute('type', 'LogParabola')
addParameter(spec, 'norm',
norm_free, norm_value, norm_scale, norm_min, norm_max)
addParameter(spec, 'alpha', alpha_free, alpha_value, 1.0,
alpha_min, alpha_max)
addParameter(spec, 'Eb', 0, enorm, 1.0, elim_min, elim_max)
addParameter(spec, 'beta', beta_free, beta_value, 1.0, beta_min, beta_max)
src.appendChild(spec)
spatial = AddSpatial(doc,ra,dec,extendedName)
src.appendChild(spatial)
lib.appendChild(src)
def ChangeModel(Fit, E1, E2, name, Pref, Gamma):
"""Change the spectral model of a source called name
to allow a fit between E1 and E2
If the spectral model is PowerLaw, the prefactor is updated
if not the model is change to PowerLaw.
The index is frozen in all cases"""
Eav = utils.GetE0(E1, E2)
# Set Parameters
Fit.logLike.getSource(name).getSrcFuncs()['Spectrum'].getParam('Prefactor').setBounds(1e-5,1e5)
Fit.logLike.getSource(name).getSrcFuncs()['Spectrum'].getParam('Prefactor').setScale(utils.fluxScale(Pref))
Fit.logLike.getSource(name).getSrcFuncs()['Spectrum'].getParam('Prefactor').setValue(utils.fluxNorm(Pref))
Gamma_min=-5
Gamma_max=0
# if approximated Gamma is outside of bounds set it to limit
if Gamma < Gamma_min:
Gamma = Gamma_min
elif Gamma > Gamma_max:
Gamma = Gamma_max
Fit.logLike.getSource(name).getSrcFuncs()['Spectrum'].getParam('Index').setBounds(Gamma_min,Gamma_max)
Fit.logLike.getSource(name).getSrcFuncs()['Spectrum'].getParam('Index').setValue(Gamma)
Fit.logLike.getSource(name).getSrcFuncs()['Spectrum'].getParam('Index').setFree(0)
Fit.logLike.getSource(name).getSrcFuncs()['Spectrum'].getParam('Scale').setValue(Eav)
Fit.logLike.getSource(name).getSrcFuncs()['Spectrum'].getParam('Scale').setBounds(20,3e6)
return Fit
