#=================================================
if opts.verbose:
print "\n----------------------------------\n"
print "building hPrior"
if opts.time:
to = time.time()
pareto_a=config.getfloat("hPrior","pareto_a")
n_gaus_per_dec=config.getfloat("hPrior","n_gaus_per_dec")
log10_min=np.log10(config.getfloat("hPrior","min"))
log10_max=np.log10(config.getfloat("hPrior","max"))
n_gaus = max(1, int(round((log10_max-log10_min)*n_gaus_per_dec,0)))
variances=np.logspace(log10_min, log10_max, n_gaus)**2
pareto_means, pareto_covariance, pareto_amps = priors.pareto(pareto_a, analysis_n_freqs, n_pol, variances)
hprior = priors.hPrior(analysis_freqs, pareto_means, pareto_covariance, amplitudes=pareto_amps, n_gaus=n_gaus, n_pol=n_pol)
if opts.time:
print "\t", time.time()-to
#=================================================
### build posterior_obj
#=================================================
if opts.verbose:
print "\n----------------------------------\n"
print "building posterior"
posterior = posteriors.Posterior(network=network, hPrior=hprior, angPrior=angprior, seglen=seglen)
pickle.dump(waveform_args, file_obj) pickle.dump(theta_inj, file_obj) pickle.dump(phi_inj, file_obj) pickle.dump(psi_inj, file_obj) pickle.dump(hrss_inj, file_obj) pickle.dump(snrs_inj, file_obj) file_obj.close() #================================================= # PRIORS #================================================= import priors print "hPrior" to=time.time() pareto_means, pareto_covariance, pareto_amps = priors.pareto(a, n_freqs, n_pol, variances) hprior_obj = priors.hPrior(freqs, pareto_means, pareto_covariance, amplitudes=pareto_amps, n_gaus=n_gaus, n_pol=n_pol, byhand=True) print "\t", time.time()-to print "angPrior" to=time.time() angprior_obj = priors.angPrior(nside_exp, prior_type=prior_type) print "\t", time.time()-to #================================================= # POSTERIORS #================================================= import posteriors print "posterior.__init__()" to=time.time()
