plt.close(fig)
if opts.verbose and opts.time: print "\t\t", time.time()-to, "sec"
### compute basic statistics about the reconstruction
if opts.stats:
if opts.verbose:
print "\tcomputing statistics"
if opts.time: to=time.time()
statsfilename = "%s/stats-%d%s.txt"%(opts.output_dir, toa_ind, opts.tag)
### angular offset between max of the posterior and injection
cosDtheta = stats.cos_dtheta(est_theta, est_phi, inj_theta, inj_phi)
### searched area
p_value = stats.p_value(posterior, inj_theta, inj_phi, nside=nside)
searched_area = stats.searched_area(posterior, inj_theta, inj_phi, degrees=True)
### num_mode
num_mode = stats.num_modes(posterior, inj_theta, inj_phi, nside=nside)
### min{cosDtheta}
min_cosDtheta = stats.min_cos_dtheta(posterior, inj_theta, inj_phi, nside=nside)
### entropy
entropy = stats.entropy(posterior)
### information
info = stats.information(posterior)
statsfile = open(statsfilename, "w")
print >> statsfile, "cos(ang_offset) = %.6f\nsearched_area = %.6f deg2\np_value = %.6f\nnum_mode = %d\nmin{cos(ang_offset)} = %.6f\nentropy = %.6f\ninformation = %.6f"%(cosDtheta, searched_area, p_value, num_mode, min_cosDtheta, entropy, info)
fitsnames.append(fits) #================================================= # COMPUTE STATISTICS #================================================= if not opts.zero_data: print "\tp_value" to=time.time() p_value[inj_id] = stats.p_value(posterior, theta, phi, nside=nside) print "\t\t", p_value[inj_id] print "\t\t", time.time()-to print "\tsearched_area" to=time.time() searched_area[inj_id] = stats.searched_area(posterior, theta, phi, nside=nside, degrees=True) print "\t\t", searched_area[inj_id] print "\t\t", time.time()-to print "\tcos_dtheta" to=time.time() cos_dtheta[inj_id] = stats.est_cos_dtheta(posterior, theta, phi) print "\t\t", cos_dtheta[inj_id] print "\t\t", time.time()-to ### write a tool that will compute moments of frequency given a model (and log_posterior_elements?) #================================================= # ENSEMBLE AVERAGES #================================================= if not opts.zero_data:
print " pixarea=%.6f %s" % (pixarea, areaunit)
### compute statistics and report them
if opts.pvalue:
if opts.Verbose:
print " pvalue"
pvalue = stats.p_value(post, theta, phi, nside=nside)
messages.append("cdf(%s) = %.3f %s" % (opts.pvalue, pvalue * 100, "%"))
if opts.searched_area:
if opts.Verbose:
print " searched_area"
sa = stats.searched_area(post,
stheta,
sphi,
nside=nside,
degrees=opts.degrees)
messages.append("searched_area(%s) = %.3f %s" %
(opts.searched_area, sa, areaunit))
# entropy -> size
if opts.entropy:
if opts.Verbose:
print " entropy"
entropy = pixarea * 2**(stats.entropy(post, base=2.0))
messages.append("entropy = %.3f %s" % (entropy, areaunit))
# CR -> size, max(dtheta)
if opts.Verbose:
print " Credible Regions"
