Vpf ddlmZmZddlmZddlmZddlm Z ddl m Z ddl mZmZdded ed ed efd Zdded ed ed efd Zdded ed ed efdZdded ed ed efdZdded ed ed efdZdded ed ed efdZdS))expitlogit)laxN)_const)promote_args_inexact)Array ArrayLikexlocscalereturnc td|||\}}}tjtj|||}t |d}tj||}tjtjtj|tj|tj|tj |S)aLogistic log probability distribution function. JAX implementation of :obj:`scipy.stats.logistic` ``logpdf``. The logistic probability distribution function is given by .. math:: f(x) = \frac{e^{-x}}{(1 + e^{-x})^2} Args: x: arraylike, value at which to evaluate the PDF a: 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.logistic.cdf` - :func:`jax.scipy.stats.logistic.pdf` - :func:`jax.scipy.stats.logistic.sf` - :func:`jax.scipy.stats.logistic.isf` - :func:`jax.scipy.stats.logistic.ppf` zlogistic.logpdf) rrdivsub _lax_constmulnegjnp logaddexplog)r r r twohalf_xs ]/var/www/html/nettyfy-visnx/env/lib/python3.11/site-packages/jax/_src/scipy/stats/logistic.pylogpdfrs6''8!S%HH-!S% gcgaoou%%!1a# 71c??& s}VSWV__'M'MNNPSPWX]P^P^ _ __cHtjt|||S)aLogistic probability distribution function. JAX implementation of :obj:`scipy.stats.logistic` ``pdf``. The logistic probability distribution function is given by .. math:: f(x) = \frac{e^{-x}}{(1 + e^{-x})^2} 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.logistic.cdf` - :func:`jax.scipy.stats.logistic.sf` - :func:`jax.scipy.stats.logistic.isf` - :func:`jax.scipy.stats.logistic.logpdf` - :func:`jax.scipy.stats.logistic.ppf` )rexprr r r s rpdfr!:s 4 3&& ' ''rctd|||\}}}tjtjt |||S)aLogistic distribution percent point function. JAX implementation of :obj:`scipy.stats.logistic` ``ppf``. The percent point function is defined as the inverse of the cumulative distribution function, :func:`jax.scipy.stats.logistic.cdf`. Args: x: arraylike, value at which to evaluate the PPF loc: arraylike, distribution offset parameter scale: arraylike, distribution scale parameter Returns: array of ppf values. See Also: - :func:`jax.scipy.stats.logistic.cdf` - :func:`jax.scipy.stats.logistic.pdf` - :func:`jax.scipy.stats.logistic.sf` - :func:`jax.scipy.stats.logistic.isf` - :func:`jax.scipy.stats.logistic.logpdf` z logistic.ppf)rraddrrr s rppfr$WsA.'~q#uEE-!S% q5))3 / //rc td|||\}}}ttjtjtj|||S)aLogistic distribution survival function. JAX implementation of :obj:`scipy.stats.logistic` ``sf`` The survival function is defined as .. math:: f_{sf}(x, k) = 1 - f_{cdf}(x, k) where :math:`f_{cdf}(x, k)` is the cumulative distribution function, :func:`jax.scipy.stats.logistic.cdf`. Args: x: arraylike, value at which to evaluate the SF loc: arraylike, distribution offset parameter scale: arraylike, distribution scale parameter Returns: array of sf values. See Also: - :func:`jax.scipy.stats.logistic.cdf` - :func:`jax.scipy.stats.logistic.pdf` - :func:`jax.scipy.stats.logistic.isf` - :func:`jax.scipy.stats.logistic.logpdf` - :func:`jax.scipy.stats.logistic.ppf` z logistic.sf)rrrrrrr s rsfr&rsK:'}aeDD-!S% swswswq#6677 8 88rc td|||\}}}tjtjtjt |||S)awLogistic distribution inverse survival function. JAX implementation of :obj:`scipy.stats.logistic` ``isf``. Returns the inverse of the survival function, :func:`jax.scipy.stats.logistic.sf`. Args: x: arraylike, value at which to evaluate the ISF loc: arraylike, distribution offset parameter scale: arraylike, distribution scale parameter Returns: array of isf values. See Also: - :func:`jax.scipy.stats.logistic.cdf` - :func:`jax.scipy.stats.logistic.pdf` - :func:`jax.scipy.stats.logistic.sf` - :func:`jax.scipy.stats.logistic.logpdf` - :func:`jax.scipy.stats.logistic.ppf` z logistic.isf)rrr#rrrr s risfr(sK.'~q#uEE-!S% q**E22C 8 88rctd|||\}}}ttjtj|||S)aLogistic cumulative distribution function. JAX implementation of :obj:`scipy.stats.logistic` ``cdf``. The cdf is defined as .. math:: f_{cdf}(x, k) = \int_{-\infty}^x f_{pdf}(y, k)\mathrm{d}y where :math:`f_{pdf}` is the probability density function, :func:`jax.scipy.stats.logistic.pdf`. Args: x: arraylike, value at which to evaluate the CDF loc: arraylike, distribution offset parameter scale: arraylike, distribution scale parameter Returns: array of cdf values. See Also: - :func:`jax.scipy.stats.logistic.pdf` - :func:`jax.scipy.stats.logistic.sf` - :func:`jax.scipy.stats.logistic.isf` - :func:`jax.scipy.stats.logistic.logpdf` - :func:`jax.scipy.stats.logistic.ppf` z logistic.cdf)rrrrrr s rcdfr*sA:'~q#uEE-!S% swswq#.. / //r)rr )jax.scipy.specialrrjaxr jax.numpynumpyrjax._src.lax.laxrrjax._src.numpy.utilrjax._src.typingrr rr!r$r&r(r*rrr3s+*******111111444444,,,,,,,,``i`i`I`e````D((9(9((5((((:009090050000699)9)9 9%9999B999999959999600909005000000r