def log_posterior_transit(theta, params, model, t, flux, err_flux, priorbounds):
    '''
    Evaluate posterior probability given proposed model parameters and
    the observed flux timeseries.
    '''
    lp = _log_prior_transit(theta, priorbounds)
    if not np.isfinite(lp):
        return -np.inf
    else:
        return lp + _log_likelihood_transit(theta, params, model, t, flux,
                                            err_flux, priorbounds)
def log_posterior_transit(theta, params, model, t, flux, err_flux, priorbounds):
    '''
    Evaluate posterior probability given proposed model parameters and
    the observed flux timeseries.
    '''
    lp = _log_prior_transit(theta, priorbounds)
    if not np.isfinite(lp):
        return -np.inf
    else:
        return lp + _log_likelihood_transit(theta, params, model, t, flux,
                                            err_flux, priorbounds)
def log_posterior_transit ( theta , params , model , t , flux , err_flux , priorbounds ) : lp = _log_prior_transit ( theta , priorbounds ) if not np . isfinite ( lp ) : return - np . inf else : return lp + _log_likelihood_transit ( theta , params , model , t , flux , err_flux , priorbounds )
Evaluate posterior probability given proposed model parameters and
    the observed flux timeseries.
Evaluate posterior probability given proposed model parameters and the observed flux timeseries .