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]