uki ddlZddlmZddlmZddlmZddlm Z ddl m Z ddl m Z mZ dded ed ed ed ed e f dZ dded ed ed ed ed e f dZy)N)lax)numpy)_const)promote_args_inexact)betaln)Array ArrayLikeknablocreturnc td|||||\}}}}}tjtj||}t |d}t |d}tj tj tj|ttj tj|||tj ||}tjttj ||tj tj|||t||} tj || } tjtjtj||tj||d| } tjtjtj|tj |tj||tj tj |||} tj| t"j$ | } tjtjtj||tj ||tj ||} tj| t"j&| 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.logpmfrg)rrsubfloor _lax_constnegaddlog1prjnpwhere logical_andeq logical_orltgtlenpinfnan) r r r r ryonezerocombilnbeta_lns log_probsy_cond n_a_b_conds Y/home/cdr/jupyterlab/.venv/lib/python3.12/site-packages/jax/_src/scipy/stats/betabinom.pylogpmfr,s8));Q1aM/!Q1c ggciilC !1a# Aq $ GGCGGCIIaL&1s1KSWWUVWZ^*\] ^' WWVCGGAaL#''#''!A,q*ABF1QK P(gggx()iiq$4I2yY) >>#..3773<)@#&&A,O&&A5 7&ii3)~~cnnSVVAt_cffQoNPSPVPVWXZ^P_`* :rvvy 11c Ftjt|||||S)aBeta-binomial probability mass function. JAX implementation of :obj:`scipy.stats.betabinom` ``pmf``. The beta-binomial distribution's probability mass function is defined as .. math:: f(k, n, a, b) = {n \choose k}\frac{B(k+a,n-k-b)}{B(a,b)} where :math:`B(a, b)` is the :func:`~jax.scipy.special.beta` function. It is defined for :math:`n\ge 0`, :math:`a>0`, :math:`b>0`, and non-negative integers `k`. Args: k: arraylike, value at which to evaluate the PMF n: arraylike, distribution shape parameter a: arraylike, distribution shape parameter b: arraylike, distribution shape parameter loc: arraylike, distribution offset parameter Returns: array of pmf values See Also: :func:`jax.scipy.stats.betabinom.logpmf` )rexpr,)r r r r rs r+pmfr0Ds 8 1aC( ))r-)r)rr jax._srcrrjax._src.lax.laxrrjax._src.numpy.utilrjax._src.scipy.specialrjax._src.typingrr r,r0r-r+r7s!14),(2i(2I(2)(2 (2(2"'(2X*9**y*Y* *$*r-