sg_helpme_params.py 文件源码

def chivecfn(theta):
            """A version of lnprobfn that returns the simple uncertainty 
            normalized residual instead of the log-posterior, for use with 
            least-squares optimization methods like Levenburg-Marquardt.
            """
            lnp_prior = model.prior_product(theta)
            if not np.isfinite(lnp_prior):
                return -np.infty

            # Generate mean model
            t1 = time.time()
            try:
                spec, phot, x = model.mean_model(theta, obs, sps=sps)
            except(ValueError):
                return -np.infty
            d1 = time.time() - t1

            chispec = chi_spec(spec, obs)
            chiphot = chi_phot(phot, obs)
            return np.concatenate([chispec, chiphot])

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