uki+ ddlZddlmZddlmZddlmZddlmZ ddl m Z m Z m Z ddlmZmZdded ed ed ed ef d Zdded ed ed ed ef dZy)N)lax)numpy)promote_args_inexact)_const)gammalnxlogyxlog1py)Array ArrayLikeknplocreturnc td||||\}}}}tj||}t|d}tjt |dztj t |dzt ||z dz}tj t ||ttj||tj|}tj ||}tjtjtj||tj||tj||} tj| d|}tjtj||tj|||zdzz|t j" S)aEBinomial log probability mass function. JAX implementation of :obj:`scipy.stats.binom` ``logpmf``. The binomial probability mass function is defined as .. math:: f(k, n, p) = {n \choose k}p^k(1-p)^{n-k} for :math:`0\le p\le 1` and non-negative integers :math:`k`. Args: k: arraylike, value at which to evaluate the PMF n: arraylike, distribution shape parameter p: arraylike, distribution shape parameter loc: arraylike, distribution offset parameter Returns: array of logpmf values. See Also: :func:`jax.scipy.stats.binom.pmf` z binom.logpmfrg)rrsub _lax_constraddrr negjnp logical_or logical_andeqwheregeltnpinf) r r rryzero comb_termlog_linear_term log_probsy_n_conds U/home/cdr/jupyterlab/.venv/lib/python3.12/site-packages/jax/_src/scipy/stats/binom.pylogpmfr's@2&naAsC,!Q3 ggao! Aq $gg a!en ggga!enga!eai01)GGE!QKA )KL/ggi1) ^^COOCFF1dOSVVAt_MFF?D9;(ii"i0) 366!S>CFF1cAgk$::Iw OOcDtjt||||S)a@Binomial probability mass function. JAX implementation of :obj:`scipy.stats.binom` ``pmf``. The binomial probability mass function is defined as .. math:: f(k, n, p) = {n \choose k}p^k(1-p)^{n-k} for :math:`0\le p\le 1` and non-negative integers :math:`k`. Args: k: arraylike, value at which to evaluate the PMF n: arraylike, distribution shape parameter p: arraylike, distribution shape parameter loc: arraylike, distribution offset parameter Returns: array of pmf values. See Also: :func:`jax.scipy.stats.binom.logpmf` )rexpr')r r rrs r&pmfr+As2 1a% &&r()r)rrjax._srcrrjax._src.numpy.utilrjax._src.lax.laxrrjax._src.scipy.specialrrr jax._src.typingr r r'r+r(r&r2sv!41::,%Pi%PI%P)%P)%PE%PP'9''y'y''r(