From 274a0cdf6d243bc3eb642b7d7bfa0eea8f0ea72e Mon Sep 17 00:00:00 2001 From: shivesh Date: Fri, 9 Nov 2018 22:24:00 -0600 Subject: Fri 9 Nov 22:24:00 CST 2018 --- utils/likelihood.py | 9 ++++++++- 1 file changed, 8 insertions(+), 1 deletion(-) (limited to 'utils/likelihood.py') diff --git a/utils/likelihood.py b/utils/likelihood.py index 93f3aea..7079d52 100644 --- a/utils/likelihood.py +++ b/utils/likelihood.py @@ -72,6 +72,8 @@ def lnprior(theta, paramset): prior += Gaussian().logpdf( param.nominal_value, param.value, param.std ) + print 'prioring param', param.name, '=', param.value + print 'prior', prior elif param.prior is PriorsCateg.HALFGAUSS: prior += Gaussian().logpdf( param.nominal_value, param.value, param.std @@ -177,7 +179,8 @@ def triangle_llh(theta, args, asimov_paramset, llh_paramset, fitter): n = gen_identifier(args) + '.txt' with open(args.output_measured_fr + n, 'a') as f: f.write(r'{0:.3f} {1:.3f} {2:.3f} {3:.1f}'.format( - fr[0], fr[1], fr[2], llh_paramset['logLam'].value + float(fr[0]), float(fr[1]), float(fr[2]), + llh_paramset['logLam'].value )) f.write('\n') @@ -202,6 +205,10 @@ def ln_prob(theta, args, asimov_paramset, llh_paramset, fitter): lp = lnprior(theta, paramset=llh_paramset) if not np.isfinite(lp): return -np.inf + llh = triangle_llh( + theta, args=args, asimov_paramset=asimov_paramset, + llh_paramset=llh_paramset, fitter=fitter + ) return lp + triangle_llh( theta, args=args, asimov_paramset=asimov_paramset, llh_paramset=llh_paramset, fitter=fitter -- cgit v1.2.3