Vpf ~ddlmZddlmZddlmZmZddlm Z m Z ddl m Z m Z de de de d e fd Zde de de d e fd ZdS) )laxN)promote_args_inexactpromote_args_numeric)gammalnxlogy)Array ArrayLikexnpreturnc\td|\}td||\}}tj|jtjst d|jd|j||j}||j}t|dztj t||t|dzz dz}tj tj tj |||tj S)aMultinomial log probability mass function. JAX implementation of :obj:`scipy.stats.multinomial` ``logpdf``. The multinomial probability distribution is given by .. math:: f(x, n, p) = n! \prod_{i=1}^k \frac{p_i^{x_i}}{x_i!} with :math:`n = \sum_i x_i`. Args: x: arraylike, value at which to evaluate the PMF n: arraylike, distribution shape parameter p: arraylike, distribution shape parameter Returns: array of logpmf values. See Also: :func:`jax.scipy.stats.multinomial.pmf` zmultinomial.logpmfz-x and n must be of integer type; got x.dtype=z , n.dtype=)axis)rrjnp issubdtypedtypeinteger ValueErrorastypersumrwhereequalinf)r r r logprobss `/var/www/html/nettyfy-visnx/env/lib/python3.11/site-packages/jax/_src/scipy/stats/multinomial.pylogpmfrs00!44"! 2Aq 9 9$!Q  - -c aQWaaXYX_aa b bbhhqw!hhqw! QU^^cgeAqkkGAENN&BLLL L( 39SWQZZ++Xx @ @@cHtjt|||S)aMultinomial probability mass function. JAX implementation of :obj:`scipy.stats.multinomial` ``pmf``. The multinomial probability distribution is given by .. math:: f(x, n, p) = n! \prod_{i=1}^k \frac{p_i^{x_i}}{x_i!} with :math:`n = \sum_i x_i`. Args: x: arraylike, value at which to evaluate the PMF n: arraylike, distribution shape parameter p: arraylike, distribution shape parameter Returns: array of pmf values See Also: :func:`jax.scipy.stats.multinomial.logpmf` )rexpr)r r r s rpmfr"9s0 1a ! !!r)jaxr jax.numpynumpyrjax._src.numpy.utilrrjax._src.scipy.specialrrjax._src.typingrr rr"rrr*s JJJJJJJJ11111111,,,,,,,,AiAIA)AAAAAD"9""y"U""""""r