uki tddlZddlmZddlmZddlmZddlm Z ddl m Z m Z de de d e fd Z de de d e fd Zy) N)lax)numpy)_const)promote_args_inexact)Array ArrayLikexkappareturnc Xtd||\}}t|d}tjt j |||tj |dz ztjdtjzt j|zz tjS)avon Mises log probability distribution function. JAX implementation of :obj:`scipy.stats.vonmises` ``logpdf``. The von Mises probability distribution function is given by .. math:: f(x, \kappa) = \frac{1}{2\pi I_0(\kappa)}e^{\kappa\cos x} Where :math:`I_0` is the modified Bessel function :func:`~jax.scipy.special.i0` and :math:`\kappa\ge 0`, and the distribution is normalized in the interval :math:`-\pi \le x \le \pi`. Args: x: arraylike, value at which to evaluate the PDF kappa: arraylike, distribution shape parameter Returns: array of logpdf values. See Also: :func:`jax.scipy.stats.vonmises.pdf` zvonmises.logpdfr) r _lax_constjnpwherergtcoslognppi bessel_i0enan)r r zeros X/home/cdr/jupyterlab/.venv/lib/python3.12/site-packages/jax/_src/scipy/stats/vonmises.pylogpdfrs2""3Q >(!U E1 $ 366%&a(@3771ruu9WZWeWefkWlKlCm(moqouou vvc@tjt||S)avon Mises probability distribution function. JAX implementation of :obj:`scipy.stats.vonmises` ``pdf``. The von Mises probability distribution function is given by .. math:: f(x, \kappa) = \frac{1}{2\pi I_0(\kappa)}e^{\kappa\cos x} Where :math:`I_0` is the modified Bessel function :func:`~jax.scipy.special.i0` and :math:`\kappa\ge 0`, and the distribution is normalized in the interval :math:`-\pi \le x \le \pi`. Args: x: arraylike, value at which to evaluate the PDF kappa: arraylike, distribution shape parameter Returns: array of pdf values. See Also: :func:`jax.scipy.stats.vonmises.logpdf` )rexpr)r r s rpdfr6s2 5! ""r)rrjax._srcrrjax._src.lax.laxrrjax._src.numpy.utilrjax._src.typingrrrrrrr%sQ!14,wiw wew<#9#Y#5#r