from astropy.io import ascii, fits import pylab as plt %matplotlib inline from astropy import wcs import numpy as np import xidplus from xidplus import moc_routines import pickle from xidplus import sed SEDs, df=sed.berta_templates() priors,posterior=xidplus.load(filename='./XID+SED_prior.pkl') import xidplus.stan_fit.SED as SPM fit=SPM.MIPS_PACS_SPIRE(priors,SEDs,chains=4,iter=1000) posterior=sed.posterior_sed(fit,priors,SEDs) xidplus.save(priors, posterior, 'test_SPM')
num_done.append(int(folder.split('_')[-1].replace('.pkl',''))) if taskid in num_done: sys.exit() sources_done = [] both_result = [] lofar_result = [] help_result = [] for n,name in enumerate(ids_centre): if n%10==0: print(n) #print('loading new lofar and HELP posterior') lofar_file = 'data/fir/SPIRE_no_help/xidplus_run_{}/lofar_xidplus_fir_{}_rerun.pkl'.format(int(n/10),int(n/10)) priors_lofar,posterior_lofar = xidplus.load(lofar_file) rep_map_lofar = postmaps.replicated_maps(priors_lofar,posterior_lofar) help_file = 'data/fir/SPIRE_no_lofar/xidplus_run_{}/lofar_xidplus_fir_{}_rerun.pkl'.format(int(n/10),int(n/10)) priors_help,posterior_help = xidplus.load(help_file) rep_map_help = postmaps.replicated_maps(priors_help,posterior_help) if n%20==0: #print('loading new both posterior') both_file = 'data/fir/SPIRE/xidplus_run_{}/lofar_xidplus_fir_{}_rerun.pkl'.format(int(n/20),int(n/20)) priors_both,posterior_both = xidplus.load(both_file) rep_map_both = postmaps.replicated_maps(priors_both,posterior_both) ra_target = ras[n] dec_target = decs[n] pixels_both = find_pixels([ra_target],[dec_target],18/3600,priors_both,posterior_both)
def setUp(self): priors, posterior = xidplus.load('test.pkl') self.priors = priors self.posterior=posterior
lofar_runs = glob.glob('data/fir/SPIRE/*/*.pkl') lofar = Table.read('data/data_release/final_cross_match_catalogue-v0.5.fits') mask = (~np.isnan(lofar['F_SPIRE_250'])) | ( ~np.isnan(lofar['F_SPIRE_350'])) | (~np.isnan(lofar['F_SPIRE_500'])) lofar = lofar[~mask] batch_size = 20 sources_done = [] ks_test = [] sign = [] for file in lofar_runs: print(file) priors, posterior = xidplus.load(file) rep_map_lofar = postmaps.replicated_maps(priors, posterior) filename = file taskid = int(filename.split('_')[-2]) ind_low = taskid * batch_size if taskid * batch_size + batch_size > len(lofar): ind_up = len(lofar) else: ind_up = taskid * batch_size + batch_size ras = lofar['optRA'][ind_low:ind_up] mask = np.isnan(ras) ras[mask] = lofar['RA'][ind_low:ind_up][mask] decs = lofar['optDec'][ind_low:ind_up]