Vpf nddlmZddlmZddlmZddlmZm Z d de de de d efd Z d de de de d efd Z dS) )laxN)promote_args_inexact)Array ArrayLikexlocscalereturnc\td|||\}}}tj|}tjtj|||}tjtj||}tjtj ||tj |S)aExponential log probability distribution function. JAX implementation of :obj:`scipy.stats.expon` ``logpdf``. The Exponential probability distribution function is .. math:: f(x) = \begin{cases} e^{-x} & x \ge 0 \\ 0 & \mathrm{otherwise} \end{cases} Args: x: arraylike, value at which to evaluate the PDF loc: arraylike, distribution offset parameter scale: arraylike, distribution scale parameter Returns: array of logpdf values. See Also: :func:`jax.scipy.stats.expon.pdf` z expon.logpdf) rrlogdivsubnegaddjnpwhereltinf)rr r log_scale linear_term log_probss Z/var/www/html/nettyfy-visnx/env/lib/python3.11/site-packages/jax/_src/scipy/stats/expon.pylogpdfrs2'~q#uEE-!S%genn)3//+gcgk95566) 36!S>>CG8Y 7 77cHtjt|||S)aExponential probability distribution function. JAX implementation of :obj:`scipy.stats.expon` ``pdf``. The Exponential probability distribution function is .. math:: f(x) = \begin{cases} e^{-x} & x \ge 0 \\ 0 & \mathrm{otherwise} \end{cases} Args: x: arraylike, value at which to evaluate the PDF loc: arraylike, distribution offset parameter scale: arraylike, distribution scale parameter Returns: array of pdf values. See Also: :func:`jax.scipy.stats.expon.logpdf` )rexpr)rr r s rpdfr5s 2 3&& ' ''r)rr) jaxr jax.numpynumpyrjax._src.numpy.utilrjax._src.typingrrrrrrr%s444444,,,,,,,,88i8i8I8e8888@((9(9((5((((((r