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 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')
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')
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)
quants = np.quantile(syn_cls, quantiles, axis=0)
syn_cls_means.append(quants[2])
syn_cls_2sig.append((quants[0], quants[4]))
syn_cls_1sig.append((quants[1], quants[3]))
#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,
band_1sig=syn_cls_1sig,
band_2sig=syn_cls_2sig) #yerr=syn_cls_stds, ymin=1e-20)
axes = o_dict['axes']
testfigpath = os.path.join(Defaults.NUXGAL_PLOT_DIR, 'test')
testfigfile = os.path.join(testfigpath, 'gal_cross_sig_v_nevt_norm_quantile')
Utilityfunc.makedir_safe(testfigfile)
figs.save_all(testfigfile, 'pdf')
gg_cl_map = nuXgal.Map.create_from_cl(galaxy_galaxy_cl_path)
mean_density = 1.
gg_overdensity = gg_od_map.overdensity()[0]
gg_density = mean_density * (gg_overdensity + 1)
figs.mollview('overdensity', gg_overdensity)
figs.mollview('density', gg_density)
cl_overdensity = hp.sphtfunc.anafast(gg_overdensity)
cl_density = hp.sphtfunc.anafast(gg_density) / (mean_density * mean_density)
n_cl = Defaults.NCL
cl_xvals = np.linspace(1, n_cl + 1, n_cl)
cl_data = [cl_overdensity, cl_density]
cl_labels = ['overdensity', 'density']
figs.plot_cl('cl',
cl_xvals,
cl_data,
xlabel='l',
ylabel=r'$c_{l}$',
labels=cl_labels)
testfigpath = os.path.join(Defaults.NUXGAL_PLOT_DIR, 'test')
testfigfile = os.path.join(testfigpath, 'density_v_overdensity')
Utilityfunc.makedir_safe(testfigfile)
figs.save_all(testfigfile, 'pdf')
gg_cl_map = nuXgal.Map.create_from_cl(galaxy_galaxy_cl_path)
syn_map_astr_cl = syn_map_astr.cl()
syn_map_atm_cl = syn_map_atm.cl()
gg_od_map_cl = gg_od_map.cl()
gg_cl_map_cl = gg_cl_map.cl()
n_cl = Defaults.NCL
cl_xvals = np.linspace(1, n_cl + 1, n_cl)
cl_vals = [
syn_map_astr_cl[0], syn_map_atm_cl[0], gg_od_map_cl[0],
gg_cl_map_cl[0, :n_cl]
]
labels = ['astro nu', 'atm nu', 'gg overdensity', 'gg from cl']
figs.plot_cl('cl',
cl_xvals,
cl_vals,
xlabel='l',
ylabel=r'$c_{l}$',
labels=labels)
#cl_syn_map_atm = syn_map_astr.cross_correlation(syn_map_atm)
testfigpath = os.path.join(Defaults.NUXGAL_PLOT_DIR, 'test')
testfigfile = os.path.join(testfigpath, 'cl_distrib')
Utilityfunc.makedir_safe(testfigfile)
figs.save_all(testfigfile, 'pdf')
syn_cls_means = []
syn_cls_stds = []
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_cl_from_overdensity(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,
yerr=syn_cls_stds,
ymin=1e-20)
testfigpath = os.path.join(Defaults.NUXGAL_PLOT_DIR, 'test')
testfigfile = os.path.join(testfigpath, 'cl_v_nevt')
Utilityfunc.makedir_safe(testfigfile)
figs.save_all(testfigfile, 'pdf')
