def test_PowerSpectrum():
ns_atm = NeutrinoSample()
ns_atm.inputData(bgpath)
gs = GALAXY_LIBRARY.get_sample('analy')
if MAKE_TEST_PLOTS:
figs = FigureDict()
color = [
'r', 'orange', 'limegreen', 'skyblue', 'mediumslateblue', 'purple',
'grey'
]
figs.plot_cl('PowerSpectrum_atm',
Defaults.ell,
ns_atm.getPowerSpectrum(),
xlabel="l",
ylavel=r'$C_{l}$',
figsize=(8, 6),
colors=color)
figs.plot('PowerSpectrum_atm',
Defaults.ell,
gs.analyCL[0:3 * Defaults.NSIDE],
color='k',
linestyle='--',
lw=2)
figs.save_all(testfigpath, 'pdf')
def astroEvent_galaxy(f_diff=1.):
gs = GALAXY_LIBRARY.get_sample('analy')
eg = EventGenerator(year='IC86-2012', astroModel='observed_numu_fraction')
N_astro_north_obs = np.random.poisson(eg.nevts * 1 *
eg.f_astro_north_truth)
N_astro_north_exp = [
N_astro_north_obs[i] /
np.sum(eg._astro_gen.prob_reject()[i] * gs.density)
for i in range(Defaults.NEbin)
]
astro_map = eg.astroEvent_galaxy(np.array(N_astro_north_exp), gs.density)
file_utils.write_maps_to_fits(astro_map, astropath)
if MAKE_TEST_PLOTS:
figs = FigureDict()
figs.mollview_maps('astro', astro_map)
figs.save_all(testfigpath, 'pdf')
def atmBG():
eg = EventGenerator()
eventmap = eg.atmEvent(1.)
eventmap2 = np.zeros((Defaults.NEbin, Defaults.NPIXEL))
file_utils.write_maps_to_fits(eventmap, bgpath)
for i in range(Defaults.NEbin):
eventmap2[i] = eventmap[i]
eventmap2[i][Defaults.idx_muon] = hp.UNSEEN
mask = np.zeros(Defaults.NPIXEL)
mask[Defaults.idx_muon] = 1.
for i in range(Defaults.NEbin):
test = np.ma.masked_array(eventmap[i], mask=mask)
print(test.sum())
if MAKE_TEST_PLOTS:
figs = FigureDict()
figs.mollview_maps('eventmap_atm', eventmap2)
figs.save_all(testfigpath, 'pdf')
def test_CrossCorrelation():
ns_astro = NeutrinoSample()
ns_astro.inputData(astropath)
gs = GALAXY_LIBRARY.get_sample('analy')
w_cross = ns_astro.getCrossCorrelation(gs.overdensityalm)
if MAKE_TEST_PLOTS:
figs = FigureDict()
color = [
'r', 'orange', 'limegreen', 'skyblue', 'mediumslateblue', 'purple',
'grey'
]
o_dict = figs.setup_figure('Wcross',
xlabel="l",
ylabel=r'$w$',
figsize=(6, 8))
axes = o_dict['axes']
for i in range(Defaults.NEbin):
axes.plot(Defaults.ell,
gs.analyCL[0:3 * Defaults.NSIDE] * 10**(i * 2),
color='k',
lw=2)
w_cross[i] *= 10**(i * 2)
figs.plot_cl('Wcross',
Defaults.ell,
np.abs(w_cross),
xlabel="l",
ylabel=r'$C_{l}$',
colors=color,
ymin=1e-7,
ymax=1e10,
lw=3)
figs.save_all(testfigpath, 'pdf')
def atmBG_coszenith(energyBin=0):
eg = EventGenerator()
N_coszenith = eg.atm_gen.coszenith()[energyBin]
recovered_values = eg.atmBG_coszenith(int(np.sum(N_coszenith[:, 1])),
energyBin)
index = np.where(np.abs(recovered_values) > 1)
if len(index) > 1:
print(index, recovered_values[index])
if MAKE_TEST_PLOTS:
figs = FigureDict()
figkey = 'N_coszenith' + str(energyBin)
o_dict = figs.setup_figure(figkey,
xlabel=r'$\cos\,\theta$',
ylabel='Number of counts',
figsize=(8, 6))
fig = o_dict['fig']
axes = o_dict['axes']
axes.plot(N_coszenith[:, 0], N_coszenith[:, 1], lw=2, label='data')
axes.hist(recovered_values, N_coszenith[:, 0], label='mock')
fig.legend()
figs.save_all(testfigpath, 'pdf')
labels = []
lvals = np.arange(384)
for n_evt in n_events:
syn_maps = hp_utils.vector_generate_counts_from_pdf(
gg_density, n_evt, n_trial)
pdf_map = gg_density * n_evt
syn_cls = hp_utils.vector_cross_correlate_maps_normed(
max_map, syn_maps, Defaults.NCL)
syn_cls_means.append(syn_cls.mean(0))
syn_cls_stds.append(syn_cls.std(0))
#pdf_cls = hp.sphtfunc.anafast(pdf_map)
#syn_cls_means.append(pdf_cls)
#syn_cls_stds.append(pdf_cls*0.1)
labels.append("Syn %i" % n_evt)
#labels.append("Pdf %i" % n_evt)
o_dict = figs.plot_cl("cl",
lvals,
syn_cls_means,
ymax=10.,
ymin=1e-3,
labels=labels) #yerr=syn_cls_stds, ymin=1e-20)
testfigpath = os.path.join(Defaults.NUXGAL_PLOT_DIR, 'test')
testfigfile = os.path.join(testfigpath, 'gal_cross_sig_v_nevt_norm')
Utilityfunc.makedir_safe(testfigfile)
figs.save_all(testfigfile, 'pdf')