mcmc.py 文件源码

def ln_prior(p, joker_params):
    P, phi0, ecc, omega, s, K, *v_terms = p

    lnp = 0.

    # TODO: more repeated code here and hard-coded priors
    if ecc < 0 or ecc > 1:
        return -np.inf

    lnp += beta.logpdf(ecc, 0.867, 3.03) # Kipping et al. 2013

    # TODO: do we need P_min, P_max here?

    if not joker_params._fixed_jitter:
        # DFM's idea: wide, Gaussian prior in log(s^2)
        # lnp += norm.logpdf(np.log(s), ) # TODO: put in hyper-parameters
        # TODO:
        pass

    return lnp