# print 'setting up the classes'
# print 'getting matter randoms'
# theta_g, phi_g = pcc.eq2ang(ra_g, dec_g)
# nside_mask = 128
# ind_g_f = hp.ang2pix(nside_mask, theta_g, phi_g)
# mask_d = np.zeros(hp.nside2npix(nside_mask))
# mask_d[ind_g_f] = 1
# plt.figure()
# hp.mollview(mask_d)
# plt.savefig('/global/project/projectdirs/des/shivamp/actxdes/data_set/buzzard_sims/measurements/' + 'data_m_sky.png')
# pdb.set_trace()
# ra_rand_m, dec_rand_m, z_rand_m = CF_m.create_random_cat_masked(0.0, zmax_hrlum,ind_g_f,nside_mask)
if do_m:
CF_m = pcc.Catalog_funcs(ra_m, dec_m, z_m ,cosmo_params_dict,other_params_dict)
print 'getting matter jk'
bin_n_all_m,jk_all_m = CF_m.get_jk_stats()
CF_m.save_cat(ra_m, dec_m, z_m,bin_n_all_m,jk_all_m,save_dir,save_filename_matter)
if do_rm:
ra_rand_m, dec_rand_m, z_rand_m = ra_rand_g, dec_rand_g, z_rand_g
print ' nrand_g: ',len(ra_rand_g), ', ng:',len(ra_g),' nrand_m: ',len(ra_rand_m), ', nm:',len(ra_m)
CF_rand_m = pcc.Catalog_funcs(ra_rand_m, dec_rand_m, z_rand_m ,cosmo_params_dict,other_params_dict)
print 'getting matter randoms jk'
bin_n_all_rand_m,jk_all_rand_m = CF_rand_m.get_jk_stats()
CF_rand_m.save_cat(ra_rand_m, dec_rand_m, z_rand_m,bin_n_all_rand_m,jk_all_rand_m,save_dir,save_filename_matter_randoms)
if do_g:
CF_g = pcc.Catalog_funcs(ra_g, dec_g, z_g ,cosmo_params_dict,other_params_dict)
print 'getting galaxy jk'
if os.path.isfile(save_dir + save_filename_jk_obj):
jkobj_map_radec_centers = pk.load(
open(save_dir + save_filename_jk_obj, 'rb'))['jkobj_map_radec_centers']
jkobj_map_radec = KMeans(jkobj_map_radec_centers)
else:
ind_jk_g = np.where((z_g_hdens > other_params_dict['zmin_bins'][0]) & (
z_g_hdens < (other_params_dict['zmin_bins'][0] + 0.1)))[0]
jkobj_map_radec = pcc.get_jkobj(
np.transpose([ra_g_hdens[ind_jk_g], dec_g_hdens[ind_jk_g]]), njk_radec)
jk_dict = {'jkobj_map_radec_centers': jkobj_map_radec.centers}
pk.dump(jk_dict, open(save_dir + save_filename_jk_obj, 'wb'), protocol=2)
other_params_dict['jkobj_map_radec'] = jkobj_map_radec
CF_hdens_all = pcc.Catalog_funcs(ra_g_hdens_all, dec_g_hdens_all,
z_g_hdens_all, cosmo_params_dict,
other_params_dict)
nz_unnorm, z_edge = np.histogram(z_g_hdens_all, zarray_edges)
nz_unnorm_smooth = spsg.savgol_filter(nz_unnorm, 21, 5)
nz_normed = nz_unnorm / (integrate.simps(nz_unnorm, zarray))
nz_normed_smooth = nz_unnorm_smooth / (integrate.simps(nz_unnorm_smooth,
zarray))
ra_rand_g_hdens_all, dec_rand_g_hdens_all, z_rand_g_hdens_all = CF_hdens_all.create_random_cat_uniform_esutil(
zarray=zarray,
nz_normed=nz_normed_smooth,
nrand_fac=10,
ra_min=0,
ra_max=90,
dec_min=0,
dec_max=90)
ind_hdens = np.where((z_rand_g_hdens_all > zmin_hdens)