def model_fit_lsb(sed_data, my_shape, plot=True):
from jetset.minimizer import fit_SED, ModelMinimizer
from jetset.model_manager import FitModel
from jetset.jet_model import Jet
jet_lsb = Jet.load_model('prefit_jet_gal_templ.pkl')
jet_lsb.set_gamma_grid_size(200)
fit_model_lsb = FitModel(jet=jet_lsb,
name='SSC-best-fit-lsb',
template=my_shape.host_gal)
fit_model_lsb.freeze('jet_leptonic', 'z_cosm')
fit_model_lsb.freeze('jet_leptonic', 'R_H')
fit_model_lsb.jet_leptonic.parameters.beam_obj.fit_range = [5, 50]
fit_model_lsb.jet_leptonic.parameters.R.fit_range = [10**15.5, 10**17.5]
fit_model_lsb.jet_leptonic.parameters.gmax.fit_range = [1E4, 1E8]
fit_model_lsb.host_galaxy.parameters.nuFnu_p_host.frozen = False
fit_model_lsb.host_galaxy.parameters.nu_scale.frozen = True
model_minimizer_lsb, best_fit_lsb = fit_SED(fit_model_lsb,
sed_data,
10.0**11,
10**29.0,
fitname='SSC-best-fit-lsb',
minimizer='lsb')
best_fit_lsb.save_report('best-fit-minuit-report.txt')
fit_model_lsb.save_model('fit_model_lsb.pkl')
fit_model_lsb_new = FitModel.load_model('fit_model_lsb.pkl')
model_minimizer_lsb.save_model('model_minimizer_lsb.pkl')
model_minimizer_lsb_new = ModelMinimizer.load_model(
'model_minimizer_lsb.pkl')
return jet_lsb, model_minimizer_lsb_new, fit_model_lsb_new
def test_model_fit(sed_data=None, prefit_jet=None, plot=True,sed_number=1,minimizer='lsb'):
from jetset.minimizer import fit_SED,ModelMinimizer
from jetset.model_manager import FitModel
template, jet,sed_data=test_prepare_fit(sed_data=sed_data,prefit_jet=prefit_jet,plot=plot,sed_number=sed_number)
fit_model = FitModel(jet=jet, name='SSC-best-fit-minuit', template=template)
fit_model.freeze('jet_leptonic','z_cosm')
fit_model.freeze('jet_leptonic','R_H')
fit_model.jet_leptonic.parameters.beam_obj.fit_range = [5, 50]
fit_model.jet_leptonic.parameters.R.fit_range = [10 ** 15.5, 10 ** 17.5]
if minimizer == 'minuit':
fit_model.jet_leptonic.parameters.gmin.fit_range = [2, 200]
fit_model.jet_leptonic.parameters.gmax.fit_range = [1E5, 1E7]
fit_model.jet_leptonic.parameters.B.fit_range = [1E-3,2]
if template is not None:
fit_model.host_galaxy.parameters.nuFnu_p_host.frozen = False
fit_model.host_galaxy.parameters.nu_scale.frozen = True
model_minimizer = ModelMinimizer(minimizer)
best_fit = model_minimizer.fit(fit_model, sed_data, 10 ** 11., 10 ** 29.0,
fitname='SSC-best-fit-minuit', repeat=1)
best_fit.show_report()
best_fit.save_report('best-fit-%s-report.pkl'%minimizer)
best_fit.bestfit_table.write('best-fit-%s-report.ecsv'%minimizer)
model_minimizer.save_model('model_minimizer_%s.pkl'%minimizer)
model_minimizer = ModelMinimizer.load_model('model_minimizer_%s.pkl'%minimizer)
fit_model.save_model('fit_model_%s.pkl'%minimizer)
return fit_model, model_minimizer,sed_data
def model_fit_minuit(sed_data, my_shape, plot=True):
from jetset.minimizer import fit_SED
from jetset.model_manager import FitModel
from jetset.jet_model import Jet
jet_minuit = Jet.load_model('prefit_jet_gal_templ.pkl')
jet_minuit.set_gamma_grid_size(200)
fit_model_minuit = FitModel(jet=jet_minuit,
name='SSC-best-fit-minuit',
template=my_shape.host_gal)
fit_model_minuit.freeze('z_cosm')
fit_model_minuit.freeze('R_H')
fit_model_minuit.jet_leptonic.parameters.beam_obj.fit_range = [5, 50]
fit_model_minuit.jet_leptonic.parameters.R.fit_range = [10**15.5, 10**17.5]
fit_model_minuit.host_galaxy.parameters.nuFnu_p_host.frozen = False
fit_model_minuit.host_galaxy.parameters.nu_scale.frozen = True
model_minimizer_minuit, best_fit_minuit = fit_SED(
fit_model_minuit,
sed_data,
10.0**11,
10**29.0,
fitname='SSC-best-fit-minuit',
minimizer='minuit')
best_fit_minuit.save_report('best-fit-minuit-report.txt')
fit_model_minuit.save_model('fit_model_minuit.pkl')
return jet_minuit, model_minimizer_minuit
def test_dep_par_composite_model(plot=False):
import numpy as np
from jetset.model_manager import FitModel
from jetset.jet_model import Jet
jet = Jet(emitters_distribution='plc')
fit_model = FitModel(jet=jet, name='SSC-best-fit-lsb', template=None)
fit_model.jet_leptonic.parameters.beam_obj.fit_range = [5, 50]
fit_model.jet_leptonic.parameters.R_H.val = 5E17
fit_model.jet_leptonic.parameters.R_H.frozen = False
fit_model.jet_leptonic.parameters.R_H.fit_range = [1E15, 1E19]
fit_model.jet_leptonic.parameters.R.fit_range = [10 ** 15.5, 10 ** 17.5]
fit_model.jet_leptonic.add_user_par(name='B0', units='G', val=1E3, val_min=0, val_max=None)
fit_model.jet_leptonic.add_user_par(name='R0', units='cm', val=5E13, val_min=0, val_max=None)
fit_model.jet_leptonic.parameters.R0.frozen = True
fit_model.jet_leptonic.parameters.B0.frozen = True
par_expr = 'B0*(R0/R_H)'
fit_model.jet_leptonic.make_dependent_par(par='B', depends_on=['B0', 'R0', 'R_H'], par_expr=par_expr)
B0=fit_model.jet_leptonic.parameters.B0.val
R0 = fit_model.jet_leptonic.parameters.R0.val
R_H = fit_model.jet_leptonic.parameters.R_H.val
np.testing.assert_allclose(fit_model.jet_leptonic.parameters.B.val, eval(par_expr))
fit_model.save_model('test_composite.pkl')
new_fit_model=FitModel.load_model('test_composite.pkl')
new_fit_model.jet_leptonic.parameters.B0.val=1E4
B0 = new_fit_model.jet_leptonic.parameters.B0.val
R0 = new_fit_model.jet_leptonic.parameters.R0.val
R_H = new_fit_model.jet_leptonic.parameters.R_H.val
np.testing.assert_allclose(new_fit_model.jet_leptonic.parameters.B.val, eval(par_expr))
def model_fit_lsb(sed_data, ):
from jetset.minimizer import fit_SED
from jetset.model_manager import FitModel
from jetset.jet_model import Jet
jet = Jet.load_model('prefit_jet.dat')
fit_model = FitModel(jet=jet, name='SSC-best-fit', template=None)
fit_model.freeze('z_cosm')
fit_model.freeze('R_H')
fit_model.parameters.R.fit_range = [10**15.5, 10**17.5]
fit_model.parameters.gmax.fit_range = [1E4, 1E8]
model_minimizer_lsb, best_fit_lsb = fit_SED(fit_model,
sed_data,
10.0**11,
10**29.0,
fitname='SSC-best-fit',
minimizer='lsb')
best_fit_lsb.save_report('best-fit-lsb-report.txt')
fit_model.save_model('fit_model_lsb.dat')
def test_model_fit_dep_pars(sed_data=None, prefit_jet=None, plot=True,sed_number=1,minimizer='lsb'):
from jetset.minimizer import fit_SED,ModelMinimizer
from jetset.model_manager import FitModel
template, jet,sed_data=test_prepare_fit(sed_data=sed_data,prefit_jet=prefit_jet,plot=plot,sed_number=sed_number)
fit_model = FitModel(jet=jet, name='SSC-best-fit-minuit', template=template)
fit_model.freeze('jet_leptonic','z_cosm')
fit_model.jet_leptonic.parameters.beam_obj.fit_range = [5, 50]
fit_model.jet_leptonic.parameters.R_H.val = 5E17
fit_model.jet_leptonic.parameters.R_H.frozen = False
fit_model.jet_leptonic.parameters.R_H.fit_range = [1E15, 1E19]
fit_model.jet_leptonic.parameters.R.fit_range = [10 ** 15.5, 10 ** 17.5]
fit_model.jet_leptonic.add_user_par(name='B0', units='G', val=1E3, val_min=0, val_max=None)
fit_model.jet_leptonic.add_user_par(name='R0', units='cm', val=5E13, val_min=0, val_max=None)
fit_model.jet_leptonic.parameters.R0.frozen = True
fit_model.jet_leptonic.parameters.B0.frozen = True
fit_model.jet_leptonic.make_dependent_par(par='B', depends_on=['B0', 'R0', 'R_H'], par_expr='B0*(R0/R_H)')
if minimizer == 'minuit':
fit_model.jet_leptonic.parameters.gmin.fit_range = [2, 200]
fit_model.jet_leptonic.parameters.gmax.fit_range = [1E5, 1E7]
if template is not None:
fit_model.host_galaxy.parameters.nuFnu_p_host.frozen = False
fit_model.host_galaxy.parameters.nu_scale.frozen = True
model_minimizer = ModelMinimizer(minimizer)
best_fit = model_minimizer.fit(fit_model, sed_data, 10 ** 11., 10 ** 29.0,
fitname='SSC-best-fit-minuit', repeat=1)
best_fit.show_report()
best_fit.save_report('best-fit-%s-report.pkl'%minimizer)
best_fit.bestfit_table.write('best-fit-%s-report.ecsv'%minimizer)
model_minimizer.save_model('model_minimizer_%s.pkl'%minimizer)
model_minimizer = ModelMinimizer.load_model('model_minimizer_%s.pkl'%minimizer)
fit_model.save_model('fit_model_%s.pkl'%minimizer)
return fit_model, model_minimizer,sed_data
def test_ebl_jet(plot=True,):
from jetset.jet_model import Jet
from jetset.template_2Dmodel import EBLAbsorptionTemplate
from jetset.model_manager import FitModel
my_jet = Jet(electron_distribution='lppl', name='jet_flaring')
my_jet.parameters.z_cosm.val = 0.01
ebl_franceschini = EBLAbsorptionTemplate.from_name('Franceschini_2008')
composite_model = FitModel(nu_size=500, name='EBL corrected')
composite_model.add_component(my_jet)
composite_model.add_component(ebl_franceschini)
composite_model.show_pars()
composite_model.link_par(par_name='z_cosm', from_model='Franceschini_2008', to_model='jet_flaring')
v=0.03001
my_jet.parameters.z_cosm.val = v
assert (composite_model.Franceschini_2008.parameters.z_cosm.val==v)
assert (composite_model.Franceschini_2008.parameters.z_cosm.linked==True)
assert (composite_model.Franceschini_2008.parameters.z_cosm.val == composite_model.jet_flaring.parameters.z_cosm.val)
composite_model.composite_expr = '%s*%s'%(my_jet.name,ebl_franceschini.name)
composite_model.eval()
if plot is True:
composite_model.plot_model()
composite_model.save_model('ebl_jet.pkl')
new_composite_model=FitModel.load_model('ebl_jet.pkl')
v=2.0
new_composite_model.jet_flaring.parameters.z_cosm.val=v
assert (new_composite_model.Franceschini_2008.parameters.z_cosm.val == v)
assert (new_composite_model.Franceschini_2008.parameters.z_cosm.linked == True)
def test_ebl_jet_fit(plot=True,sed_number=2,minimizer='lsb'):
from .test_model_fit import test_prepare_fit
template, jet,sed_data = test_prepare_fit(sed_number=sed_number)
from jetset.template_2Dmodel import EBLAbsorptionTemplate
ebl_franceschini = EBLAbsorptionTemplate.from_name('Franceschini_2008')
ebl_franceschini.show_model()
from jetset.model_manager import FitModel
composite_model = FitModel(nu_size=500, name='EBL corrected', template=template)
composite_model.add_component(jet)
composite_model.add_component(ebl_franceschini)
composite_model.link_par(par_name='z_cosm', from_model='Franceschini_2008', to_model=jet.name)
if template is not None:
composite_model.composite_expr = '(%s+host_galaxy)*Franceschini_2008'%jet.name
else:
composite_model.composite_expr = '(%s)*Franceschini_2008' % jet.name
assert (composite_model.Franceschini_2008.parameters.z_cosm.val == composite_model.jet_leptonic.parameters.z_cosm.val)
assert (composite_model.Franceschini_2008.parameters.z_cosm.linked is True)
composite_model.show_model()
composite_model.eval()
if plot is True:
composite_model.plot_model()
from jetset.minimizer import ModelMinimizer
composite_model.freeze(jet, 'R_H')
composite_model.freeze(jet, 'z_cosm')
if minimizer == 'minuit':
composite_model.jet_leptonic.parameters.gmin.fit_range = [2, 200]
composite_model.jet_leptonic.parameters.gmax.fit_range = [1E5, 1E7]
if template is not None:
composite_model.host_galaxy.parameters.nuFnu_p_host.frozen = False
composite_model.host_galaxy.parameters.nu_scale.frozen = True
composite_model.jet_leptonic.parameters.beam_obj.fit_range = [5, 50]
composite_model.jet_leptonic.parameters.R.fit_range = [10 ** 15.5, 10 ** 17.5]
composite_model.jet_leptonic.parameters.gmax.fit_range = [1E4, 1E8]
composite_model.jet_leptonic.nu_size = 200
composite_model.jet_leptonic.IC_nu_size = 100
model_minimizer = ModelMinimizer(minimizer)
best_fit = model_minimizer.fit(composite_model, sed_data, 10 ** 11., 10 ** 29.0,
fitname='SSC-best-fit-minuit', repeat=1)
best_fit.show_report()
best_fit.save_report('best-fit-%s-report.pkl' % minimizer)
best_fit.bestfit_table.write('best-fit-%s-report.ecsv' % minimizer)
model_minimizer.save_model('model_minimizer_%s.pkl' % minimizer)
model_minimizer = ModelMinimizer.load_model('model_minimizer_%s.pkl' % minimizer)
composite_model.save_model('fit_model_%s.pkl' % minimizer)