Vpf ddlmZddlmZddlmZddlm Z ddl m Z ddl m Z mZ ddeded ed ed ed e f d Z ddeded ed ed ed e f dZdS))laxN)_const)promote_args_inexact)betaln)Array ArrayLikeknablocreturnc td|||||\}}}}}tjtj||}t |d}t |d}tjtjtj|ttjtj|||tj||}tjttj||tjtj|||t||} tj|| } tj tj |tj|tj |tj||} tj | tj | } tj tj tj ||tj ||tj ||} tj | tj| S)a Beta-binomial log probability mass function. JAX implementation of :obj:`scipy.stats.betabinom` ``logpmf`` The beta-binomial distribution's probability mass function is defined as .. math:: f(k, n, a, b) = {n \choose k}\frac{B(k+a,n-k-b)}{B(a,b)} where :math:`B(a, b)` is the :func:`~jax.scipy.special.beta` function. It is defined for :math:`n\ge 0`, :math:`a>0`, :math:`b>0`, and non-negative integers `k`. Args: k: arraylike, value at which to evaluate the PMF n: arraylike, distribution shape parameter a: arraylike, distribution shape parameter b: arraylike, distribution shape parameter loc: arraylike, distribution offset parameter Returns: array of logpmf values See Also: :func:`jax.scipy.stats.betabinom.pmf` zbetabinom.logpmfr)rrsubfloor _lax_constnegaddlog1prjnp logical_orltgtwhereinfnan) r r r r r yonezerocombilnbeta_lns log_probsy_cond n_a_b_conds ^/var/www/html/nettyfy-visnx/env/lib/python3.11/site-packages/jax/_src/scipy/stats/betabinom.pylogpmfr's8));Q1aMM/!Q1c gcillC  !1a# Aq  $ GCGCIaLL&1s1K1KSWUVWZ^^*\*\]] ^ ^' WVCGAaLL#'#'!A,,q*A*ABBF1QKK P P(ggx(() >#&CGCLL1136!SWQ__3M3M N N&i)44)~cnSVAs^^SVAt__MMsvVWY]__* :sw 2 22c Ltjt|||||S)aBeta-binomial probability mass function. JAX implementation of :obj:`scipy.stats.betabinom` ``pmf``. The beta-binomial distribution's probability mass function is defined as .. math:: f(k, n, a, b) = {n \choose k}\frac{B(k+a,n-k-b)}{B(a,b)} where :math:`B(a, b)` is the :func:`~jax.scipy.special.beta` function. It is defined for :math:`n\ge 0`, :math:`a>0`, :math:`b>0`, and non-negative integers `k`. Args: k: arraylike, value at which to evaluate the PMF n: arraylike, distribution shape parameter a: arraylike, distribution shape parameter b: arraylike, distribution shape parameter loc: arraylike, distribution offset parameter Returns: array of pmf values See Also: :func:`jax.scipy.stats.betabinom.logpmf` )rexpr')r r r r r s r&pmfr+@s$8 1aC(( ) ))r()r)jaxr jax.numpynumpyrjax._src.lax.laxrrjax._src.numpy.utilrjax._src.scipy.specialrjax._src.typingrrr'r+r(r&r4s111111444444)))))),,,,,,,,&3&3i&3I&3)&3 &3&3"'&3&3&3&3T**9**y*Y* *$******r(