def plot_flux_stage(flux_nmh,flux_imh,save=False,title='',dpi=150,outdir=""):
'''
Plots flux maps templates for NMH/IMH
'''
flav_title = {'nue':r'$\nu_e$',
'nue_bar':r'$\overline{\nu}_e$',
'numu':r'$\nu_\mu$',
'numu_bar':r'$\overline{\nu}_\mu$'}
description = ' Flux [m$^{-2}$ s$^{-1}$]'
for flav in ['nue','numu']:
plt.figure(figsize=(8,8))
flav_bar = flav+'_bar'
plt.subplot(2,2,1)
show_map(flux_nmh[flav])
plt.title(r'NMH '+flav_title[flav]+description,fontsize='large')
plt.subplot(2,2,2)
show_map(flux_nmh[flav_bar])
plt.title(r'NMH '+flav_title[flav_bar]+description,fontsize='large')
plt.subplot(2,2,3)
show_map(flux_imh[flav])
plt.title(r'IMH '+flav_title[flav]+description,fontsize='large')
plt.subplot(2,2,4)
show_map(flux_imh[flav_bar])
plt.title(r'IMH '+flav_title[flav_bar]+description,fontsize='large')
plt.tight_layout()
if save:
print "Saving Stage 1: nue Flux maps..."
filename = os.path.join(outdir,title+'_flux_maps_'+flav+'.png')
plt.savefig(filename,dpi=dpi)
return
def plot_pid_stage(nmh, imh, title='', save=False, dpi=150, outdir=""):
'''
Plots templates and asymmetry for only the final level stage
'''
h_asym = get_asymmetry(nmh, imh, ['trck', 'cscd'])
logging.info(" Total trck events (NMH): %d" % np.sum(nmh['trck']['map']))
logging.info(" Total trck events (IMH): %d" % np.sum(imh['trck']['map']))
logging.info(" Total cscd events (NMH): %d" % np.sum(nmh['cscd']['map']))
logging.info(" Total cscd events (IMH): %d" % np.sum(imh['cscd']['map']))
for chan in ['trck', 'cscd']:
plt.figure(figsize=(16, 5))
plt.subplot(1, 3, 1)
show_map(nmh[chan])
plt.title(title + ' NMH, ' + chan + ' counts', fontsize='large')
plt.subplot(1, 3, 2)
show_map(imh[chan])
plt.title(title + ' IMH, ' + chan + ' counts', fontsize='large')
plt.subplot(1, 3, 3)
sigma = np.sqrt(np.sum(h_asym[chan]['map']**2))
show_map(h_asym[chan], cmap='RdBu_r')
plt.title(title + ' ' + chan + r' asymmetry, $\sigma$ = %.3f' % sigma,
fontsize='large')
if save:
print "Saving %s chan..." % chan
filename = os.path.join(outdir, title + '_asym_' + chan + '.png')
plt.savefig(filename, dpi=dpi)
return
def plot_reco_event_rate(reco_rate_nmh,reco_rate_imh,save=False,title='',dpi=150,
outdir=''):
'''
Plots reco event rate maps for NMH/IMH
'''
flav_title = {'nue_cc':r'$\nu_e^{cc}$',
'numu_cc':r'$\nu_\mu^{cc}$',
'nutau_cc':r'$\nu_\tau^{cc}$',
'nuall_nc':r'$\nu$ all NC'}
all_flavs = list(flav_title.keys())
h_asym = get_asymmetry(reco_rate_nmh,reco_rate_imh,all_flavs)
description=' Reco Event Rate [#/yr]'
for flav in all_flavs:
plt.figure(figsize=(16,5))
plt.subplot(1,3,1)
show_map(reco_rate_nmh[flav])
plt.title(r'NMH '+flav_title[flav]+description,fontsize='large')
plt.subplot(1,3,2)
show_map(reco_rate_imh[flav])
plt.title(r'IMH '+flav_title[flav]+description,fontsize='large')
plt.subplot(1,3,3)
show_map(h_asym[flav],cmap='RdBu_r')
sigma = np.sqrt(np.sum(h_asym[flav]['map']**2))
plt.title(r'Hierarchy Asymmetry: '+flav_title[flav]+', $\sigma$ = %.3f'%sigma,
fontsize='large')
plt.tight_layout()
if save:
print "Saving Stage 4: "+flav+" reco event rate maps..."
filename = os.path.join(outdir,title+'_reco_event_rate_'+flav+'.png')
plt.savefig(filename,dpi=dpi)
return
def plot_pid_stage(nmh, imh, title='', save=False, dpi=150, outdir=""):
'''
Plots templates and asymmetry for only the final level stage
'''
h_asym = get_asymmetry(nmh, imh, ['trck','cscd'])
logging.info(" Total trck events (NMH): %d"%np.sum(nmh['trck']['map']))
logging.info(" Total trck events (IMH): %d"%np.sum(imh['trck']['map']))
logging.info(" Total cscd events (NMH): %d"%np.sum(nmh['cscd']['map']))
logging.info(" Total cscd events (IMH): %d"%np.sum(imh['cscd']['map']))
for chan in ['trck','cscd']:
plt.figure(figsize=(16,5))
plt.subplot(1,3,1)
show_map(nmh[chan])
plt.title(title+' NMH, '+chan+' counts',fontsize='large')
plt.subplot(1,3,2)
show_map(imh[chan])
plt.title(title+' IMH, '+chan +' counts',fontsize='large')
plt.subplot(1,3,3)
sigma = np.sqrt(np.sum(h_asym[chan]['map']**2))
show_map(h_asym[chan],cmap='RdBu_r')
plt.title(title+' '+chan+r' asymmetry, $\sigma$ = %.3f'%sigma,
fontsize='large')
if save:
print "Saving %s chan..."%chan
filename = os.path.join(outdir,title+'_asym_'+chan+'.png')
plt.savefig(filename,dpi=dpi)
return
def plot_flux_stage(flux_nmh,
flux_imh,
save=False,
title='',
dpi=150,
outdir=""):
'''
Plots flux maps templates for NMH/IMH
'''
flav_title = {
'nue': r'$\nu_e$',
'nue_bar': r'$\overline{\nu}_e$',
'numu': r'$\nu_\mu$',
'numu_bar': r'$\overline{\nu}_\mu$'
}
description = ' Flux [m$^{-2}$ s$^{-1}$]'
for flav in ['nue', 'numu']:
plt.figure(figsize=(8, 8))
flav_bar = flav + '_bar'
plt.subplot(2, 2, 1)
show_map(flux_nmh[flav])
plt.title(r'NMH ' + flav_title[flav] + description, fontsize='large')
plt.subplot(2, 2, 2)
show_map(flux_nmh[flav_bar])
plt.title(r'NMH ' + flav_title[flav_bar] + description,
fontsize='large')
plt.subplot(2, 2, 3)
show_map(flux_imh[flav])
plt.title(r'IMH ' + flav_title[flav] + description, fontsize='large')
plt.subplot(2, 2, 4)
show_map(flux_imh[flav_bar])
plt.title(r'IMH ' + flav_title[flav_bar] + description,
fontsize='large')
plt.tight_layout()
if save:
print "Saving Stage 1: nue Flux maps..."
filename = os.path.join(outdir,
title + '_flux_maps_' + flav + '.png')
plt.savefig(filename, dpi=dpi)
return
def plot_reco_event_rate(reco_rate_nmh,
reco_rate_imh,
save=False,
title='',
dpi=150,
outdir=''):
'''
Plots reco event rate maps for NMH/IMH
'''
flav_title = {
'nue_cc': r'$\nu_e^{cc}$',
'numu_cc': r'$\nu_\mu^{cc}$',
'nutau_cc': r'$\nu_\tau^{cc}$',
'nuall_nc': r'$\nu$ all NC'
}
all_flavs = list(flav_title.keys())
h_asym = get_asymmetry(reco_rate_nmh, reco_rate_imh, all_flavs)
description = ' Reco Event Rate [#/yr]'
for flav in all_flavs:
plt.figure(figsize=(16, 5))
plt.subplot(1, 3, 1)
show_map(reco_rate_nmh[flav])
plt.title(r'NMH ' + flav_title[flav] + description, fontsize='large')
plt.subplot(1, 3, 2)
show_map(reco_rate_imh[flav])
plt.title(r'IMH ' + flav_title[flav] + description, fontsize='large')
plt.subplot(1, 3, 3)
show_map(h_asym[flav], cmap='RdBu_r')
sigma = np.sqrt(np.sum(h_asym[flav]['map']**2))
plt.title(r'Hierarchy Asymmetry: ' + flav_title[flav] +
', $\sigma$ = %.3f' % sigma,
fontsize='large')
plt.tight_layout()
if save:
print "Saving Stage 4: " + flav + " reco event rate maps..."
filename = os.path.join(
outdir, title + '_reco_event_rate_' + flav + '.png')
plt.savefig(filename, dpi=dpi)
return
def plot_true_event_rate(event_rate_nmh,
event_rate_imh,
title='',
save=False,
dpi=150,
outdir=''):
'''
Plots true event rate maps
'''
flav_title = {
'nue': r'$\nu_e^{cc}$',
'nue_bar': r'$\overline{\nu}_e^{cc}$',
'numu': r'$\nu_\mu^{cc}$',
'numu_bar': r'$\overline{\nu}_\mu^{cc}$',
'nutau': r'$\nu_\tau^{cc}$',
'nutau_bar': r'$\overline{\nu}_\tau^{cc}$'
}
all_flavs = list(flav_title.keys())
h_asym = get_asymmetry(event_rate_nmh,
event_rate_imh,
all_flavs,
iType='cc')
description = ' True Event Rate [#/yr]'
for flav in ['nue', 'numu', 'nutau']:
plt.figure(figsize=(16, 8))
plt.subplot(2, 3, 1)
show_map(event_rate_nmh[flav]['cc'], vmin=0.0)
plt.title(r'NMH ' + flav_title[flav] + description, fontsize='large')
plt.subplot(2, 3, 2)
show_map(event_rate_imh[flav]['cc'], vmin=0.0)
plt.title(r'IMH ' + flav_title[flav] + description, fontsize='large')
plt.subplot(2, 3, 3)
show_map(h_asym[flav], cmap='RdBu_r')
sigma = np.sqrt(np.sum(h_asym[flav]['map']**2))
plt.title(r'Hierarchy Asymmetry: ' + flav_title[flav] +
', $\sigma$ = %.3f' % sigma,
fontsize='large')
flav_bar = flav + '_bar'
plt.subplot(2, 3, 4)
show_map(event_rate_nmh[flav_bar]['cc'], vmin=0.0)
plt.title(r'NMH ' + flav_title[flav_bar] + description,
fontsize='large')
plt.subplot(2, 3, 5)
show_map(event_rate_imh[flav_bar]['cc'], vmin=0.0)
plt.title(r'IMH ' + flav_title[flav_bar] + description,
fontsize='large')
plt.subplot(2, 3, 6)
show_map(h_asym[flav_bar], cmap='RdBu_r')
sigma = np.sqrt(np.sum(h_asym[flav_bar]['map']**2))
plt.title(r'Hierarchy Asymmetry: ' + flav_title[flav_bar] +
', $\sigma$ = %.3f' % sigma,
fontsize='large')
plt.tight_layout()
if save:
print "Saving Stage 3: " + flav + " true event rate maps..."
filename = os.path.join(
outdir, title + '_true_event_rate_' + flav + '.png')
plt.savefig(filename, dpi=dpi)
return
def plot_osc_flux_stage(osc_flux_nmh,
osc_flux_imh,
save=False,
title='',
dpi=150,
outdir=""):
'''
Plots osc flux maps templates for NMH/IMH
'''
flav_title = {
'nue': r'$\nu_e$',
'nue_bar': r'$\overline{\nu}_e$',
'numu': r'$\nu_\mu$',
'numu_bar': r'$\overline{\nu}_\mu$',
'nutau': r'$\nu_\tau$',
'nutau_bar': r'$\overline{\nu}_\tau$'
}
all_flavs = list(flav_title.keys())
h_asym = get_asymmetry(osc_flux_nmh, osc_flux_imh, all_flavs)
description = r' Oscillated Flux [m$^{-2}$ s$^{-1}$]'
for flav in ['nue', 'numu', 'nutau']:
plt.figure(figsize=(16, 8))
plt.subplot(2, 3, 1)
show_map(osc_flux_nmh[flav])
plt.title(r'NMH ' + flav_title[flav] + description, fontsize='large')
plt.subplot(2, 3, 2)
show_map(osc_flux_imh[flav])
plt.title(r'IMH ' + flav_title[flav] + description, fontsize='large')
plt.subplot(2, 3, 3)
show_map(h_asym[flav], cmap='RdBu_r')
sigma = np.sqrt(np.sum(h_asym[flav]['map']**2))
plt.title(r'Hierarchy Asymmetry: ' + flav_title[flav] +
', $\sigma$ = %.3f' % sigma,
fontsize='large')
flav_bar = flav + '_bar'
plt.subplot(2, 3, 4)
show_map(osc_flux_nmh[flav_bar])
plt.title(r'NMH ' + flav_title[flav_bar] + description,
fontsize='large')
plt.subplot(2, 3, 5)
show_map(osc_flux_imh[flav_bar])
plt.title(r'IMH ' + flav_title[flav_bar] + description,
fontsize='large')
plt.subplot(2, 3, 6)
show_map(h_asym[flav_bar], cmap='RdBu_r')
sigma = np.sqrt(np.sum(h_asym[flav_bar]['map']**2))
plt.title(r'Hierarchy Asymmetry: ' + flav_title[flav_bar] +
', $\sigma$ = %.3f' % sigma,
fontsize='large')
plt.tight_layout()
if save:
print "Saving Stage 2: " + flav + " osc flux maps..."
filename = os.path.join(outdir,
title + '_osc_flux_maps_' + flav + '.png')
plt.savefig(filename, dpi=dpi)
return
if final_map_key == 'nue_bar':
finaltitle = r'$\bar{\nu}_e$'
if final_map_key == 'numu':
finaltitle = r'$\nu_{\mu}$'
if final_map_key == 'numu_bar':
finaltitle = r'$\bar{\nu}_{\mu}$'
if final_map_key == 'nutau':
finaltitle = r'$\nu_{\tau}$'
if final_map_key == 'nutau_bar':
finaltitle = r'$\bar{\nu}_{\tau}$'
plottitle = '%s to %s NH Oscillogram'%(inittitle,finaltitle)
plt.figure(figsize = (16,5))
plt.subplot(1,4,1)
show_map(bestmapobj)
plt.xlabel(r'$\cos\theta_Z$')
plt.ylabel(r'Energy [GeV]')
plt.title('Oversampling = 1000')
plt.subplot(1,4,2)
show_map(currentmapobj)
plt.xlabel(r'$\cos\theta_Z$')
plt.ylabel(r'Energy [GeV]')
plt.title('Oversampling = %s'%oversample)
plt.subplot(1,4,3)
show_map(diffmapobj)
plt.xlabel(r'$\cos\theta_Z$')
plt.ylabel(r'Energy [GeV]')
plt.title('Difference between maps')
cake_map['ebins'] = binning['bin_edges']
if binning['name'] == 'true_coszen':
cake_map['czbins'] = binning['bin_edges']
if binning['name'] == 'reco_energy':
cake_map['ebins'] = binning['bin_edges']
if binning['name'] == 'reco_coszen':
cake_map['czbins'] = binning['bin_edges']
RatioMapObj = ratio_map(cake_map, pisa_map)
DiffMapObj = delta_map(pisa_map, cake_map)
DiffRatioMapObj = ratio_map(DiffMapObj, pisa_map)
plt.figure(figsize = (20,5))
plt.subplot(1,5,1)
show_map(pisa_map)
plt.xlabel(r'$\cos\theta_Z$')
plt.ylabel(r'Energy [GeV]')
plt.title('%s %s PISA V2'%(titles[cake_dict['name']],args.stage))
plt.subplot(1,5,2)
show_map(cake_map)
plt.xlabel(r'$\cos\theta_Z$')
plt.ylabel(r'Energy [GeV]')
plt.title('%s %s PISA V3'%(titles[cake_dict['name']],args.stage))
plt.subplot(1,5,3)
show_map(RatioMapObj)
plt.xlabel(r'$\cos\theta_Z$')
plt.ylabel(r'Energy [GeV]')
plt.title('%s %s PISA V3/V2'%(titles[cake_dict['name']],args.stage))
# Second for anti-neutrinos:
kNuBar = -1
barger_prop.SetMNS(sin2th12Sq,sin2th13Sq,sin2th23Sq,args.deltam21,mAtm,
args.deltacp,energy,kSquared,kNuBar)
barger_prop.DefinePath(coszen, args.prod_height)
barger_prop.propagate(kNuBar)
for nu in ['nue_bar','numu_bar']:
nu_i = nu_barger[nu]
for to_nu in anti_neutrinos:
nu_f = nu_barger[to_nu]
osc_prob_dict[nu+'_maps'][to_nu][ie][icz]=barger_prop.GetProb(nu_i, nu_f)
logging.info("Saving to file: %s"%args.outfile)
to_json(osc_prob_dict,args.outfile)
logging.info("Finished in %s seconds!"%(datetime.now() - start_time))
if args.plot:
from matplotlib import pyplot as plt
from pisa.utils.plot import show_map
pmap = {'map':osc_prob_dict['numu_maps']['numu'],
'ebins':osc_prob_dict['ebins'],
'czbins': osc_prob_dict['czbins']}
show_map(pmap)
plt.show()
def plot_true_event_rate(event_rate_nmh,event_rate_imh,title='',save=False,
dpi=150,outdir=''):
'''
Plots true event rate maps
'''
flav_title = {'nue':r'$\nu_e^{cc}$',
'nue_bar':r'$\overline{\nu}_e^{cc}$',
'numu':r'$\nu_\mu^{cc}$',
'numu_bar':r'$\overline{\nu}_\mu^{cc}$',
'nutau':r'$\nu_\tau^{cc}$',
'nutau_bar':r'$\overline{\nu}_\tau^{cc}$'}
all_flavs = list(flav_title.keys())
h_asym = get_asymmetry(event_rate_nmh,event_rate_imh,all_flavs,iType='cc')
description=' True Event Rate [#/yr]'
for flav in ['nue','numu','nutau']:
plt.figure(figsize=(16,8))
plt.subplot(2,3,1)
show_map(event_rate_nmh[flav]['cc'],vmin=0.0)
plt.title(r'NMH '+flav_title[flav]+description,fontsize='large')
plt.subplot(2,3,2)
show_map(event_rate_imh[flav]['cc'],vmin=0.0)
plt.title(r'IMH '+flav_title[flav]+description,fontsize='large')
plt.subplot(2,3,3)
show_map(h_asym[flav],cmap='RdBu_r')
sigma = np.sqrt(np.sum(h_asym[flav]['map']**2))
plt.title(r'Hierarchy Asymmetry: '+flav_title[flav]+', $\sigma$ = %.3f'%sigma,
fontsize='large')
flav_bar = flav+'_bar'
plt.subplot(2,3,4)
show_map(event_rate_nmh[flav_bar]['cc'],vmin=0.0)
plt.title(r'NMH '+flav_title[flav_bar]+description,fontsize='large')
plt.subplot(2,3,5)
show_map(event_rate_imh[flav_bar]['cc'],vmin=0.0)
plt.title(r'IMH '+flav_title[flav_bar]+description,fontsize='large')
plt.subplot(2,3,6)
show_map(h_asym[flav_bar],cmap='RdBu_r')
sigma = np.sqrt(np.sum(h_asym[flav_bar]['map']**2))
plt.title(r'Hierarchy Asymmetry: '+flav_title[flav_bar]+
', $\sigma$ = %.3f'%sigma,fontsize='large')
plt.tight_layout()
if save:
print "Saving Stage 3: "+flav+" true event rate maps..."
filename = os.path.join(outdir,title+'_true_event_rate_'+flav+'.png')
plt.savefig(filename,dpi=dpi)
return
def plot_osc_flux_stage(osc_flux_nmh,osc_flux_imh,save=False,title='',
dpi=150,outdir=""):
'''
Plots osc flux maps templates for NMH/IMH
'''
flav_title = {'nue':r'$\nu_e$',
'nue_bar':r'$\overline{\nu}_e$',
'numu':r'$\nu_\mu$',
'numu_bar':r'$\overline{\nu}_\mu$',
'nutau':r'$\nu_\tau$',
'nutau_bar':r'$\overline{\nu}_\tau$'}
all_flavs = list(flav_title.keys())
h_asym = get_asymmetry(osc_flux_nmh,osc_flux_imh,all_flavs)
description = r' Oscillated Flux [m$^{-2}$ s$^{-1}$]'
for flav in ['nue','numu','nutau']:
plt.figure(figsize=(16,8))
plt.subplot(2,3,1)
show_map(osc_flux_nmh[flav])
plt.title(r'NMH '+flav_title[flav]+description,fontsize='large')
plt.subplot(2,3,2)
show_map(osc_flux_imh[flav])
plt.title(r'IMH '+flav_title[flav]+description,fontsize='large')
plt.subplot(2,3,3)
show_map(h_asym[flav],cmap='RdBu_r')
sigma = np.sqrt(np.sum(h_asym[flav]['map']**2))
plt.title(r'Hierarchy Asymmetry: '+flav_title[flav]+', $\sigma$ = %.3f'%sigma,
fontsize='large')
flav_bar = flav+'_bar'
plt.subplot(2,3,4)
show_map(osc_flux_nmh[flav_bar])
plt.title(r'NMH '+flav_title[flav_bar]+description,fontsize='large')
plt.subplot(2,3,5)
show_map(osc_flux_imh[flav_bar])
plt.title(r'IMH '+flav_title[flav_bar]+description,fontsize='large')
plt.subplot(2,3,6)
show_map(h_asym[flav_bar],cmap='RdBu_r')
sigma = np.sqrt(np.sum(h_asym[flav_bar]['map']**2))
plt.title(r'Hierarchy Asymmetry: '+flav_title[flav_bar]+
', $\sigma$ = %.3f'%sigma,fontsize='large')
plt.tight_layout()
if save:
print "Saving Stage 2: "+flav+" osc flux maps..."
filename = os.path.join(outdir,title+'_osc_flux_maps_'+flav+'.png')
plt.savefig(filename,dpi=dpi)
return
plottitle = 'Honda South Pole 2015 (SolMax)'
Hondamapobj = {}
Hondamapobj['ebins'] = flux_dict['ebins']
Hondamapobj['czbins'] = flux_dict['czbins']
Hondamapobj['map'] = flux_dict[prim]
Hondalogmapobj = {}
Hondalogmapobj['ebins'] = flux_dict['ebins']
Hondalogmapobj['czbins'] = flux_dict['czbins']
Hondalogmapobj['map'] = np.log10(Hondamapobj['map'])
plt.figure(figsize = (8,5))
plt.subplot(1,2,1)
show_map(Hondamapobj)
plt.xlabel(r'$\cos\theta_Z$')
plt.ylabel(r'Energy [GeV]')
plt.title('%s Flux'%titles[prim])
plt.subplot(1,2,2)
show_map(Hondalogmapobj)
plt.xlabel(r'$\cos\theta_Z$')
plt.ylabel(r'Energy [GeV]')
plt.title('%s Log Flux'%titles[prim])
plt.tight_layout()
plt.subplots_adjust(top=0.8)
plt.suptitle(plottitle, fontsize=18)
# Second for anti-neutrinos:
kNuBar = -1
barger_prop.SetMNS(sin2th12Sq, sin2th13Sq, sin2th23Sq, args.deltam21,
mAtm, args.deltacp, energy, kSquared, kNuBar)
barger_prop.DefinePath(coszen, args.prod_height)
barger_prop.propagate(kNuBar)
for nu in ['nue_bar', 'numu_bar']:
nu_i = nu_barger[nu]
for to_nu in anti_neutrinos:
nu_f = nu_barger[to_nu]
osc_prob_dict[nu +
'_maps'][to_nu][ie][icz] = barger_prop.GetProb(
nu_i, nu_f)
logging.info("Saving to file: %s" % args.outfile)
to_json(osc_prob_dict, args.outfile)
logging.info("Finished in %s seconds!" % (datetime.now() - start_time))
if args.plot:
from matplotlib import pyplot as plt
from pisa.utils.plot import show_map
pmap = {
'map': osc_prob_dict['numu_maps']['numu'],
'ebins': osc_prob_dict['ebins'],
'czbins': osc_prob_dict['czbins']
}
show_map(pmap)
plt.show()
cake_map2["ebins"] = binning["bin_edges"]
if binning["name"] == "true_coszen":
cake_map2["czbins"] = binning["bin_edges"]
if binning["name"] == "reco_energy":
cake_map2["ebins"] = binning["bin_edges"]
if binning["name"] == "reco_coszen":
cake_map2["czbins"] = binning["bin_edges"]
RatioMapObj = ratio_map(cake_map1, cake_map2)
DiffMapObj = delta_map(cake_map1, cake_map2)
DiffRatioMapObj = ratio_map(DiffMapObj, cake_map1)
plt.figure(figsize=(20, 5))
plt.subplot(1, 5, 1)
show_map(cake_map1)
plt.xlabel(r"$\cos\theta_Z$")
plt.ylabel(r"Energy [GeV]")
plt.title("%s %s PISA V3(1)" % (titles[cake_dict1["name"]], args.description1))
plt.subplot(1, 5, 2)
show_map(cake_map2)
plt.xlabel(r"$\cos\theta_Z$")
plt.ylabel(r"Energy [GeV]")
plt.title("%s %s PISA V3(2)" % (titles[cake_dict1["name"]], args.description2))
plt.subplot(1, 5, 3)
show_map(RatioMapObj)
plt.xlabel(r"$\cos\theta_Z$")
plt.ylabel(r"Energy [GeV]")
plt.title("%s PISA V3(1)/V3(2)" % (titles[cake_dict1["name"]]))
