ukiM ddlZddlmZddlmZddlmZddlm Z ddl m Z m Z ddl mZmZdded ed ed ed ef d Zdded ed ed ed ef dZy)N)lax)numpy)_const)promote_args_inexact)gammalnxlogy)Array ArrayLikeknplocreturnc dtd||||\}}}}t|d}tj||}tjtjt tj ||t |t tj ||}tj t ||t |tj||}tj ||}tjtj||tj |S)aINegative-binomial log probability mass function. JAX implementation of :obj:`scipy.stats.nbinom` ``logpmf``. The negative-binomial probability mass function is given by .. math:: f(k) = {{k+n-1} \choose {n-1}}p^n(1-p)^k for :math:`k \ge 0` and :math:`0 \le p \le 1`. 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 logpdf values. See Also: :func:`jax.scipy.stats.nbinom.pmf` z nbinom.logpmf) r _lax_constrsubraddrjnpwhereltnpinf) r r r roney comb_termlog_linear_term log_probss V/home/cdr/jupyterlab/.venv/lib/python3.12/site-packages/jax/_src/scipy/stats/nbinom.pylogpmfr s2&oq!QD,!Q31a# ggao!ggGGGCGGAqM "GAJ/C1I)GGE!QKq#''#q/)BC/ggi1) 366!S>BFF7I 66cDtjt||||S)aBNegative-binomial probability mass function. JAX implementation of :obj:`scipy.stats.nbinom` ``pmf``. The negative-binomial probability mass function is given by .. math:: f(k) = {{k+n-1} \choose {n-1}}p^n(1-p)^k for :math:`k \ge 0` and :math:`0 \le p \le 1`. 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.nbinom.logpmf` )rexpr )r r r rs rpmfr$=s2 1a% &&r!)r)rrjax._srcrrjax._src.lax.laxrrjax._src.numpy.utilrjax._src.scipy.specialrrjax._src.typingr r r r$r!rr+sm!141,!7i!7I!7)!7)!7E!7H'9''y'y''r!