# Copyright 2020 The JAX Authors. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # https://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import scipy.stats as osp_stats from jax.scipy.special import expit, logit from jax import lax import jax.numpy as jnp from jax._src.lax.lax import _const as _lax_const from jax._src.numpy.util import _wraps, promote_args_inexact from jax._src.typing import Array, ArrayLike @_wraps(osp_stats.logistic.logpdf, update_doc=False) def logpdf(x: ArrayLike, loc: ArrayLike = 0, scale: ArrayLike = 1) -> Array: x, loc, scale = promote_args_inexact("logistic.logpdf", x, loc, scale) x = lax.div(lax.sub(x, loc), scale) two = _lax_const(x, 2) half_x = lax.div(x, two) return lax.sub(lax.mul(lax.neg(two), jnp.logaddexp(half_x, lax.neg(half_x))), lax.log(scale)) @_wraps(osp_stats.logistic.pdf, update_doc=False) def pdf(x: ArrayLike, loc: ArrayLike = 0, scale: ArrayLike = 1) -> Array: return lax.exp(logpdf(x, loc, scale)) @_wraps(osp_stats.logistic.ppf, update_doc=False) def ppf(x: ArrayLike, loc: ArrayLike = 0, scale: ArrayLike = 1) -> Array: x, loc, scale = promote_args_inexact("logistic.ppf", x, loc, scale) return lax.add(lax.mul(logit(x), scale), loc) @_wraps(osp_stats.logistic.sf, update_doc=False) def sf(x: ArrayLike, loc: ArrayLike = 0, scale: ArrayLike = 1) -> Array: x, loc, scale = promote_args_inexact("logistic.sf", x, loc, scale) return expit(lax.neg(lax.div(lax.sub(x, loc), scale))) @_wraps(osp_stats.logistic.isf, update_doc=False) def isf(x: ArrayLike, loc: ArrayLike = 0, scale: ArrayLike = 1) -> Array: x, loc, scale = promote_args_inexact("logistic.isf", x, loc, scale) return lax.add(lax.mul(lax.neg(logit(x)), scale), loc) @_wraps(osp_stats.logistic.cdf, update_doc=False) def cdf(x: ArrayLike, loc: ArrayLike = 0, scale: ArrayLike = 1) -> Array: x, loc, scale = promote_args_inexact("logistic.cdf", x, loc, scale) return expit(lax.div(lax.sub(x, loc), scale))