def make_triangle():
if just_disk:
mt=fa.make_triangle(b_disk,run_tag_disk_only,edep=True)
mt.make_triangle(return_fig=False,save_fig=True)
if poiss:
mt=fa.make_triangle(b_poiss,run_tag_poiss,edep=True)
mt.make_triangle(return_fig=False,save_fig=True,the_range=range_poiss)
if plus_IPS:
mt=fa.make_triangle(b_plus_IPS,run_tag_plus_iso,edep=True)
mt.make_triangle(return_fig=False,save_fig=True,the_range=range_NDI)
def do_analysis(minuit_new=False,add_group_ps=False,ps_number=0,fdn=True,fdrun=False):
global emin,emax, eachps_En_center, ps_norms, diffnormfix
if method=='polychord':
polychord=True
else:
polychord=False
b.run_tag = run_tag_energy
tri = fa.make_triangle(b,run_tag_energy,edep=True,polychord=polychord,minuit_new=minuit_new)
plot_name='triangle_ps_' + str(ps_number) + '.pdf'
tri.make_triangle(plot_name=plot_name)
if not minuit_new:
sle = fa.save_log_evidence(b,edep=True,polychord=polychord)
spect_dir = work_dir + 'data/spect/'
if not os.path.exists(spect_dir):
os.mkdir(spect_dir)
cs = fa.compute_spectra(b,run_tag_energy,f.CTB_en_bins[0],f.CTB_en_bins[-1],edep=True,plane_mask=plot_plane_mask,band_mask_range = [-plot_pmval,plot_pmval],lcut=plot_lcut,lmin=plot_lmin,lmax=plot_lmax,bcut=plot_bcut,bmin=plot_bmin,bmax=plot_bmax,mask_ring=plot_mask_ring,outer=plot_outer,inner=plot_inner,minuit_new = minuit_new,input_mask=force_ps_mask,the_input_mask=b.mask_total) # spectra over the whole energy range
cs.mask_total_dict['bubs']=np.logical_not(b.templates_dict_nested['bubs']['summed_templates_not_compressed'])
eachps_En_center = cs.En_center
cs.make_norm_dict()
cs.make_spectra_dict()
if not fdrun:
full_dict['nfw_ps_'+str(ps_number)] = cs.spectra_dict['nfw-0']
if add_group_ps:
full_dict['ps_comb_'+str(ps_number)] = cs.spectra_dict['ps_comb-0']
else:
diffnormfix = cs.norm_dict[diff + '-0']
def do_analysis(i=0,n_ps_groupi=0,psloop1=False,pscomball=False,psloop2bkg=False,psloop2=False,minuit_new=False):
global emin,emax, eachps_dict, eachps_En_center, TSbkg, TS, ps_norms_loop1, ps_norms
if method=='polychord':
polychord=True
else:
polychord=False
b.run_tag = run_tag_energy
tri = fa.make_triangle(b,run_tag_energy,edep=True,polychord=polychord,minuit_new=minuit_new)
if psloop1:
plot_name='triangle_psloop1_i' + str(i+1) + '.pdf'
if pscomball:
plot_name='triangle_pscomball.pdf'
if psloop2bkg:
plot_name='triangle_psloop2bkg_i' + str(i+1) + '.pdf'
if psloop2:
plot_name='triangle_psloop2_i' + str(i+1) + '.pdf'
tri.make_triangle(plot_name=plot_name)
if not minuit_new:
sle = fa.save_log_evidence(b,edep=True,polychord=polychord)
spect_dir = work_dir + 'data/spect/'
if not os.path.exists(spect_dir):
os.mkdir(spect_dir)
if not pscomball:
cs = fa.compute_spectra(b,run_tag_energy,f.CTB_en_bins[0],f.CTB_en_bins[-1],edep=True,band_mask_range=[0,0])
else:
cs = fa.compute_spectra(b,run_tag_energy,f.CTB_en_bins[0],f.CTB_en_bins[-1],edep=True,plane_mask=plot_plane_mask,band_mask_range = [-plot_pmval,plot_pmval],lcut=plot_lcut,lmin=plot_lmin,lmax=plot_lmax,bcut=plot_bcut,bmin=plot_bmin,bmax=plot_bmax,mask_ring=plot_mask_ring,outer=plot_outer,inner=plot_inner,minuit_new = minuit_new,input_mask=force_ps_mask,the_input_mask=b.mask_total) # spectra over the whole energy range
cs.mask_total_dict['bubs']=np.logical_not(b.templates_dict_nested['bubs']['summed_templates_not_compressed'])
eachps_En_center = cs.En_center
if psloop1 or pscomball or psloop2:
cs.make_norm_dict()
if psloop2 or psloop2bkg or pscomball:
cs.make_spectra_dict()
if pscomball:
cs.save_spectra_dict(spect_dir + save_spect_label,emin,emax,over_write=True)
cs.save_norm_dict(spect_dir + save_norm_label,emin,emax,over_write=True)
if psloop1:
# Add in new norm values
for j in range(n_ps_groupi):
ps_norms_loop1[i*n_ps_run+j] *= cs.norm_dict['ps_' + str(i*n_ps_run+j+1) + '-0']
# Update existing norm values if not the first loop
if i != 0:
for k in range(i*n_ps_run):
ps_norms_loop1[k] *= cs.norm_dict['ps_comb-0']
if psloop2bkg:
TSbkg = 2*b.s['nested sampling global log-evidence']
# Add norms to eachps_dict dictionary
if psloop2:
TS = 2*b.s['nested sampling global log-evidence'] - TSbkg
eachts_dict['ps_' + str(i+1)] = TS
eachps_dict['ps_' + str(i+1)] = cs.spectra_dict['ps_' + str(i+1) + '-0']
ps_norms[i] *= cs.norm_dict['ps_' + str(i+1) + '-0']
def calc_flux_array(self):
""" Function to calculate the LL for an array of fluxes in a given energy bin """
# First determine the associated spectrum
self.compute_template_spectrum()
# Calculate baseline counts to normalise fluxes we scan over
# Go from 10**(bin_min)*mean up to 10**(bin_max)*mean in nbins steps
b = self.setup_b_instance(0, add_ps_mask=True)
mean = np.sum(b.CTB_masked_compressed[0]) / len(
b.CTB_masked_compressed[0])
A_array = mean * 10**np.linspace(self.bin_min, self.bin_max,
self.nbins)
# Now setup and compute the arrays
LL_array = np.array([])
A_array_short = np.array([])
spect_array = np.array([])
for i in range(len(A_array)):
print "on i =", i
# Calculate LL
if i == 0:
b1 = self.setup_b_instance(A_array[i], add_ps_mask=True)
else:
for key in b1.fixed_template_dict_nested.keys():
b1.fixed_template_dict_nested[
key] = b1.fixed_template_dict_nested[key] * A_array[
i] / A_array[i - 1]
b1.perform_scan(run_tag=b1.tag + '_F' + str(i))
b1.load_scan(run_tag=b1.run_tag, edep=True, no_analyzer=True)
ll_val = b1.ll(b1.medians, 4, 4)
# Make triangle
mt = fa.make_triangle(b1, b1.run_tag, edep=True)
#mt.make_triangle(plot_name='triangle-E'+str(self.flux_array_ebin)+'-F'+str(i)+'.pdf')
# Append to arrays
LL_array = np.append(LL_array, ll_val)
A_array_short = np.append(A_array_short, A_array[i])
spect_array = self.spectrum * np.array(A_array_short)
# Save output
np.save(
work_dir + 'ScanOutput/' + self.tag + '/En_array-' +
str(self.flux_array_ebin) + '.npy', self.En_center)
np.save(
work_dir + 'ScanOutput/' + self.tag + '/LL_array-' +
str(self.flux_array_ebin) + '.npy', LL_array)
np.save(
work_dir + 'ScanOutput/' + self.tag + '/Flux_array-' +
str(self.flux_array_ebin) + '.npy', spect_array)
def do_analysis(minuit_new=False):
global emin,emax
if method=='polychord':
polychord=True
else:
polychord=False
b.run_tag = run_tag_energy
tri = fa.make_triangle(b,run_tag_energy,edep=True,polychord=polychord,minuit_new=minuit_new)
tri.make_triangle()
sle = fa.save_log_evidence(b,edep=True,polychord=polychord)
cs = fa.compute_spectra(b,run_tag_energy,f.CTB_en_bins[0],f.CTB_en_bins[-1],plane_mask=plot_plane_mask,band_mask_range = [-plot_pmval,plot_pmval],lcut=plot_lcut,lmin=plot_lmin,lmax=plot_lmax,bcut=plot_bcut,bmin=plot_bmin,bmax=plot_bmax,mask_ring=plot_mask_ring,outer=plot_outer,inner=plot_inner,minuit=True,input_mask=force_ps_mask,the_input_mask=b.mask_total,edep=True)
cs.mask_total_dict['bubs']=np.logical_not(b.templates_dict_nested['bubs']['summed_templates_not_compressed'])
cs.make_spectra_dict()
for i in cs.spectra_dict.keys():
print i,"has flux:",cs.spectra_dict[i]
def do_analysis(i=0,n_ps_groupi=0,psloop1=False,pscomball=False,psloop2=False,minuit_new=False):
global emin,emax, eachps_dict, eachps_En_center
if method=='polychord':
polychord=True
else:
polychord=False
b.run_tag = run_tag_energy
tri = fa.make_triangle(b,run_tag_energy,edep=True,polychord=polychord,minuit_new=minuit_new)
tri.make_triangle()
if not minuit_new:
sle = fa.save_log_evidence(b,edep=True,polychord=polychord)
spect_dir = work_dir + 'data/spect/'
if not os.path.exists(spect_dir):
os.mkdir(spect_dir)
cs = fa.compute_spectra(b,run_tag_energy,f.CTB_en_bins[0],f.CTB_en_bins[-1],edep=True,plane_mask=plot_plane_mask,band_mask_range = [-plot_pmval,plot_pmval],lcut=plot_lcut,lmin=plot_lmin,lmax=plot_lmax,bcut=plot_bcut,bmin=plot_bmin,bmax=plot_bmax,mask_ring=plot_mask_ring,outer=plot_outer,inner=plot_inner,minuit_new = minuit_new,input_mask=force_ps_mask,the_input_mask=b.mask_total) # spectra over the whole energy range
cs.mask_total_dict['bubs']=np.logical_not(b.templates_dict_nested['bubs']['summed_templates_not_compressed'])
eachps_En_center = cs.En_center
if psloop1 or pscomball:
cs.make_norm_dict()
if psloop2 or pscomball:
cs.make_spectra_dict()
if pscomball:
cs.save_spectra_dict(spect_dir + save_spect_label,emin,emax,over_write= False)
cs.save_norm_dict(spect_dir + save_norm_label,emin,emax,over_write= False)
if psloop1:
# Create pslooptemp and psalltemp
pslooptempar = np.zeros(hp.nside2npix(nside))
if os.path.exists(ps_temp_dir + pslooptemp):
pslooptempar += fits.open(ps_temp_dir + pslooptemp)[0].data
for j in range(n_ps_groupi):
pstempj = b.templates_dict['ps_' + str(i*n_ps_run+j+1) + '-0'][0]
psnormj = cs.norm_dict['ps_' + str(i*n_ps_run+j+1) + '-0']
pswritej = pstempj*psnormj
pslooptempar += pswritej
fits.append(ps_temp_dir + psalltemp, pswritej)
fits.writeto(ps_temp_dir + pslooptemp,pslooptempar,clobber=True)
# Add norms to eachps_dict dictionary
if psloop2:
eachps_dict['ps_' + str(i+1)] = cs.spectra_dict['ps_' + str(i+1) + '-0']
def make_triangle():
mt=fa.make_triangle(b,run_tag,edep=True)
mt.make_triangle(return_fig=False,save_fig=True)
mt=fa.make_triangle(b_disk,run_tag_disk_only,edep=True)
mt.make_triangle(return_fig=False,save_fig=True)
mt=fa.make_triangle(b_poiss,run_tag_poiss,edep=True)
mt.make_triangle(return_fig=False,save_fig=True)
mt=fa.make_triangle(b_just_NFW,run_tag_just_NFW,edep=True)
mt.make_triangle(return_fig=False,save_fig=True)
mt=fa.make_triangle(b_iso,run_tag_iso,edep=True)
mt.make_triangle(return_fig=False,save_fig=True)
if plus_IPS:
mt=fa.make_triangle(b_plus_IPS,run_tag_plus_iso,edep=True)
mt.make_triangle(return_fig=False,save_fig=True)
print 'Performing an NPTF ...'
print 'The PSF (sigma) is ', sigma_PSF_deg_red, ' in degrees.'
else:
if computing_spectra:
#b.configure_for_edep_scan() - this is already called in initiate poissonian edep
b.initiate_poissonian_edep()
#########################
#perform scan / load scan
if run:
print 'The nside for this scan is ', b.nside
b.perform_scan(run_tag = run_tag_energy)
if analysis:
b.run_tag = run_tag_energy
#make triangle plot
tri = fa.make_triangle(b,run_tag_energy,edep=True)
tri.make_triangle()
sle = fa.save_log_evidence(b,edep=True)
spect_dir = work_dir + 'data/spect/'
if not os.path.exists(spect_dir):
os.mkdir(spect_dir)
if computing_spectra:
#(self,b,run_tag,En_min,En_max,edep=False,ebin=0,*args,**kwargs)
cs = fa.compute_spectra(b,run_tag_energy,b.CTB_en_bins[0],b.CTB_en_bins[-1], band_mask_range = [-mask_b_plot,mask_b_plot],mask_ring = False,edep=True)
cs.mask_total_dict['bubs']=np.logical_not(b.templates_dict_nested['bubs']['summed_templates_not_compressed'])
cs.make_spectra_dict()
cs.make_norm_dict()
if save_spect_label != 'False' or save_spect_label != 'false':
cs.save_spectra_dict(spect_dir + save_spect_label,emin,emax,over_write= False)
if save_norm_label != 'False' or save_norm_label != 'false':
for ell_i, b_i, ps_string_i in map(None,ell_0,b_0,ps_string):
b.add_poiss_model(ps_string_i,'${(l10A_{ps})}_{l = '+str(round(ell_i,3))+ '}^{b = ' + str(round(b_i,3))+'}$',[-6,6],True)
#####perform the scan
b.configure_for_scan()
b.initiate_poissonian()
print 'Performing the scan ...'
if run:
b.perform_scan(run_tag = run_tag_energy)
##################
###perform anaysis
if analysis:
#make triangle plot
tri = fa.make_triangle(b,run_tag_energy)
tri.make_triangle()
sle = fa.save_log_evidence(b)
spect_dir = work_dir + 'data/spect/'
spect_dir_ps = spect_dir + '/ps/'
for d in [spect_dir,spect_dir_ps]:
if not os.path.exists(d):
os.mkdir(d)
# cs = fa.compute_spectra(b,run_tag_energy,f.CTB_en_bins[0],f.CTB_en_bins[-1],band_mask_range = [-0.,0.],mask_ring = True,outer=sigma_PSF_deg,lat= 90 - mask_b,lng = mask_ell) #spectra over whole energy range
cs = fa.compute_spectra(b,run_tag_energy,f.CTB_en_bins[0],f.CTB_en_bins[-1],band_mask_range = [-0.,0.],mask_ring = False) #spectra over whole energy range
# cs.mask_total_dict['bubs']=np.logical_not(b.templates_dict_nested['bubs']['summed_templates_not_compressed'])
cs.make_spectra_dict()
def do_analysis(minuit_new=False):
global emin,emax
if method=='polychord':
polychord=True
else:
polychord=False
b.run_tag = run_tag_energy
tri = fa.make_triangle(b,run_tag_energy,edep=True,polychord=polychord,minuit_new=minuit_new)
tri.make_triangle()
sle = fa.save_log_evidence(b,edep=True,polychord=polychord)
spect_dir = work_dir + 'data/spect/'
if not os.path.exists(spect_dir):
os.mkdir(spect_dir)
if save_norm_label != 'False' and save_norm_label != 'false':
cs = fa.compute_spectra(b,run_tag_energy,f.CTB_en_bins[0],f.CTB_en_bins[-1],edep=True,plane_mask=plot_plane_mask,band_mask_range = [-plot_pmval,plot_pmval],lcut=plot_lcut,lmin=plot_lmin,lmax=plot_lmax,bcut=plot_bcut,bmin=plot_bmin,bmax=plot_bmax,mask_ring=plot_mask_ring,outer=plot_outer,inner=plot_inner,minuit_new = minuit_new,input_mask=force_ps_mask,the_input_mask=b.mask_total) # spectra over the whole energy range
cs.mask_total_dict['bubs']=np.logical_not(b.templates_dict_nested['bubs']['summed_templates_not_compressed'])
cs.make_spectra_dict()
cs.make_norm_dict()
cs.save_spectra_dict(spect_dir + save_spect_label,emin,emax,over_write= False)
cs.save_norm_dict(spect_dir + save_norm_label,emin,emax,over_write= False)
else:
cs = fa.compute_edep_spectra(b,run_tag_energy,b.CTB_en_bins,polychord=polychord,plane_mask=plot_plane_mask,band_mask_range = [-plot_pmval,plot_pmval],lcut=plot_lcut,lmin=plot_lmin,lmax=plot_lmax,bcut=plot_bcut,bmin=plot_bmin,bmax=plot_bmax,mask_ring=plot_mask_ring,outer=plot_outer,inner=plot_inner,minuit_new = minuit_new,input_mask=force_ps_mask,the_input_mask=b.mask_total) #,edep=True)
cs.make_spectra_dict()
cs.save_spectra_dict(spect_dir + save_spect_label)
if n_ebins>1:
##plot spectrum
msp_inst = msp.make_spectra_plot(spect_dir + save_spect_label + '.npy')
if not fixed_background:
msp_inst.plot_spectra_median('back',color='Orange',label='back',linestyle='-')
if nfw_dm:
msp_inst.plot_spectra_median('nfw',color='Chartreuse',label='nfw',linestyle='-')
if not fixed_background:
msp_inst.plot_spectra_band('back',interpolate=True, alpha=0.5,linewidth=0,facecolor='Orange')
if nfw_dm:
msp_inst.plot_spectra_band('nfw',interpolate=True, alpha=0.5,linewidth=0,facecolor='Chartreuse')
if not poiss:
colors=['Blue','Green','Purple'][0:len(ps_list)]
for mod,color in map(None,ps_list,colors):
msp_inst.plot_spectra_median(mod + '-np',color=color,label=mod+'-np',linestyle='--')
msp_inst.plot_spectra_band(mod + '-np',interpolate=True, alpha=0.5,linewidth=0,facecolor=color)
plt.axhline(y=0.,color='k',ls='dashed')
plt.xscale('log')
plt.xlabel('E [GeV]', fontsize=14)
plt.ylabel('$E^2 dN / dE$ [GeV / cm$^2$ / s / sr]', fontsize=18)
plt.title('Spectrum',fontsize=14)
plt.legend(fontsize=12,loc=3)
plt.savefig(b.plots_dir_for_run + save_spect_label + '.pdf',bbox_inches='tight')
plt.close()
if not poiss:
print 'medians: ', b.medians_not_log
print 'norm_non_poiss: ', b.norms_non_poiss
##save PS templates/medians
if len(ps_save_list)>0:
for comp, filename in map(None,ps_save_list,ps_save_filename_list):
spti=fa.save_ps_template_info(b,run_tag_energy,edep=True,polychord=polychord,minuit_new = minuit_new)
spti.save_ps_template(comp,filename)
##plot dn/ds across energies
for ebin_num in range(b.number_energy_bins):
p3FGL = fa.plot_3FGL(f,CTB_en_min=b.CTB_en_bins[ebin_num],CTB_en_max=b.CTB_en_bins[ebin_num+1],plane_mask=plot_plane_mask,band_mask_range = [-plot_pmval,plot_pmval],lcut=plot_lcut,lmin=plot_lmin,lmax=plot_lmax,bcut=plot_bcut,bmin=plot_bmin,bmax=plot_bmax,mask_ring=plot_mask_ring,outer=plot_outer,inner=plot_inner,input_mask=force_ps_mask,the_input_mask=b.mask_total)
p3FGL.configure_3FGL(flux_min=10**-12,flux_max=10**-8,n_flux_bins = 25,only_gal = not(high_lat),error_range = 0.68)
pdnds = fa.plot_dnds(b,plane_mask=plot_plane_mask,band_mask_range = [-plot_pmval,plot_pmval],lcut=plot_lcut,lmin=plot_lmin,lmax=plot_lmax,bcut=plot_bcut,bmin=plot_bmin,bmax=plot_bmax,mask_ring=plot_mask_ring,outer=plot_outer,inner=plot_inner,input_mask=force_ps_mask,the_input_mask=b.mask_total)
plt.figure(figsize=(8,6))
p3FGL.plot_3FGL(fmt = 'o', color='black',markersize=7,label='3FGL PS')
colors=['Orange','Chartreuse','Blue'][0:len(ps_list)]
line_colors=['Red','Green','Purple'][0:len(ps_list)]
alpha_list=[1,0.75,0.5][0:len(ps_list)]
for mod,color,line_color,alpha in map(None,ps_list,colors,line_colors,alpha_list):
print 'plotting source-count function for ', mod
pdnds.plot_source_count_band(mod,edep=True,ebin=ebin_num,nsteps=100,calculate_dnds=True,facecolor=color,interpolate=True, alpha=alpha,linewidth=0)
pdnds.plot_source_count_median(mod,edep=True,ebin=ebin_num,color=line_color,linestyle='--',label=mod + ' (median)')
if len(ps_fixed_filename_list) > 0:
for comp in map(None,ps_fixed_list):
pdnds.plot_fixed_source_count(comp,ebin=ebin_num,linestyle='-',label=comp + ' (fixed)')
plt.xscale('log')
plt.yscale('log')
plt.ylim((2*10**(5),10**12))
plt.xlim(10**-12., 10**-8.)
plt.tick_params(axis='x', length=5,width=2,labelsize=18)
plt.tick_params(axis='y',length=5,width=2,labelsize=18)
plt.xlabel('$F$ [photons / cm$^2$ / s]', fontsize=18)
plt.ylabel('$dN/dF$ [photons$^{-1}$ cm$^2$ s deg$^{-2}$]', fontsize=18)
plt.legend(fontsize=15)
plt.title('Energy: '+str(np.round(b.CTB_en_bins[ebin_num],3)) + '-'+str(np.round(b.CTB_en_bins[ebin_num+1],3)),fontsize=15)
plt.savefig(b.plots_dir_for_run + 'dnds_plot_en_'+str(np.round(b.CTB_en_bins[ebin_num],3)) + '-'+str(np.round(b.CTB_en_bins[ebin_num+1],3)) + '.pdf',bbox_inches='tight')
plt.close()
def do_triangle():
mt=fa.make_triangle(b,run_tag,edep=True)
mt.make_triangle(return_fig=False,save_fig=True)
#b.configure_for_edep_scan() - this is already called in initiate poissonian edep
b.initiate_poissonian_edep()
#########################
#perform scan / load scan
if run:
print 'The nside for this scan is ', b.nside
if method=='multinest':
b.perform_scan(run_tag = run_tag)
elif method=='minuit':
b.perform_scan_minuit(run_tag = run_tag)
b.save_minuit()
b.run_tag = run_tag
#make triangle plot
tri = fa.make_triangle(b,run_tag,edep=True,minuit_new=minuit_new)
tri.make_triangle(plot_name='triangle_2MASS_'+str(twomass_temp)+' '+str(base_sigma_v*xsec)+".pdf")
if not minuit_new:
sle = fa.save_log_evidence(b,edep=True)
if twomass_temp:
print 'logevidence with twomass '+ str(twomass_temp) + ' is ', sle.lge
lge2 = sle.lge
else:
print 'logevidence with twomass '+ str(twomass_temp) + ' is ', sle.lge
lge1 = sle.lge
# Get BF from the two runs
print 'lge1 (2MASS false) is', lge1
print 'lge2 (2MASS true) is', lge2
BF = np.exp(lge2-lge1)
print 'Bayes factor is', BF
b.add_poiss_model('iso','$A_{iso}$',[0,2],False)
if twomass_temp:
b.add_poiss_model('2mass','$A_{2mass}$',[-9,2],True)
#b.configure_for_edep_scan() - this is already called in initiate poissonian edep
b.initiate_poissonian_edep()
#########################
#perform scan / load scan
if run:
print 'The nside for this scan is ', b.nside
b.perform_scan(run_tag = run_tag)
b.run_tag = run_tag
#make triangle plot
tri = fa.make_triangle(b,run_tag,edep=True)
tri.make_triangle(plot_name='triangle_2MASS_'+str(twomass_temp)+' '+str(base_sigma_v*xsec)+".pdf")
sle = fa.save_log_evidence(b,edep=True)
if twomass_temp:
print 'logevidence with twomass '+ str(twomass_temp) + ' is ', sle.lge
lge2 = sle.lge
else:
print 'logevidence with twomass '+ str(twomass_temp) + ' is ', sle.lge
lge1 = sle.lge
# Get BF from the two runs
print 'lge1 (2MASS false) is', lge1
print 'lge2 (2MASS true) is', lge2
BF = np.exp(lge2-lge1)
print 'Bayes factor is', BF
if BF > BF_limit:
#########################
#perform scan / load scan
if run:
print 'The nside for this scan is ', b.nside
#b.perform_scan(run_tag = run_tag_energy)
if polychord:
b.perform_scan_polychord(run_tag = run_tag_energy)
else:
b.perform_scan(run_tag = run_tag_energy)
if analysis:
b.run_tag = run_tag_energy
#make triangle plot
tri = fa.make_triangle(b,run_tag_energy,edep=True,polychord=polychord)
tri.make_triangle()
sle = fa.save_log_evidence(b,edep=True,polychord=polychord)
spect_dir = work_dir + 'data/spect/'
if not os.path.exists(spect_dir):
os.mkdir(spect_dir)
cs = fa.compute_edep_spectra(b,run_tag_energy,b.CTB_en_bins,polychord=polychord,band_mask_range = [-mask_b_plot,mask_b_plot],mask_ring = True,outer=outer_plot) #spectra over whole energy range
#cs.mask_total_dict['bubs']=np.logical_not(b.templates_dict_nested['bubs']['summed_templates_not_compressed'])
cs.make_spectra_dict()
cs.save_spectra_dict(spect_dir + save_spect_label)
##plot spectrum
msp_inst = msp.make_spectra_plot(spect_dir + save_spect_label + '.npy')
def do_triangle():
mt = fa.make_triangle(b, run_tag, edep=True)
mt.make_triangle(return_fig=False, save_fig=True)