Vpf$ ddlmZddlmZddlmZddlm Z ddl m Z m Z dde de d e d e d e f d Z dde de d e d e d e f d ZdS))laxN)_const)promote_args_inexact)Array ArrayLikexblocscalereturnc <td||||\}}}}t|d}tjtj|||}tjtj||}tjtj|tjtj||tj|}tj tj |tj||tj |S)aePareto log probability distribution function. JAX implementation of :obj:`scipy.stats.pareto` ``logpdf``. The Pareto probability density function is given by .. math:: f(x, b) = \begin{cases} bx^{-(b+1)} & x \ge 1\\ 0 & x < 1 \end{cases} and is defined for :math:`b > 0`. Args: x: arraylike, value at which to evaluate the PDF b: arraylike, distribution shape parameter loc: arraylike, distribution offset parameter scale: arraylike, distribution scale parameter Returns: array of logpdf values. See Also: :func:`jax.scipy.stats.pareto.pdf` z pareto.logpdfr) r _lax_constrdivsublognegaddmuljnpwhereltinf)r r r r onescaled_xnormalize_term log_probss [/var/www/html/nettyfy-visnx/env/lib/python3.11/site-packages/jax/_src/scipy/stats/pareto.pylogpdfrs8*/1aeLL!QU1a# WSWQ__e , ,(7375!,,--.gcgncgcgaooswxGXGX.Y.YZZ[[) 36!SWS%0011CG8Y G GGcJtjt||||S)a^Pareto probability distribution function. JAX implementation of :obj:`scipy.stats.pareto` ``pdf``. The Pareto probability density function is given by .. math:: f(x, b) = \begin{cases} bx^{-(b+1)} & x \ge 1\\ 0 & x < 1 \end{cases} and is defined for :math:`b > 0`. Args: x: arraylike, value at which to evaluate the PDF b: arraylike, distribution shape parameter loc: arraylike, distribution offset parameter scale: arraylike, distribution scale parameter Returns: array of pdf values. See Also: :func:`jax.scipy.stats.pareto.logpdf` )rexpr)r r r r s rpdfr#:s"8 1c5)) * **r )rr)jaxr jax.numpynumpyrjax._src.lax.laxrrjax._src.numpy.utilrjax._src.typingrrrr#r rr+s111111444444,,,,,,,,!H!Hi!HI!HI!H)!HTY!H!H!H!HH++9+++y+QV++++++r