Source code for jax._src.scipy.stats.uniform

# Copyright 2018 The JAX Authors.
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# Licensed under the Apache License, Version 2.0 (the "License");
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#     https://www.apache.org/licenses/LICENSE-2.0
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import scipy.stats as osp_stats

from jax import lax
from jax import numpy as jnp
from jax.numpy import where, inf, logical_or
from jax._src.typing import Array, ArrayLike
from jax._src.numpy.util import implements, promote_args_inexact


[docs] @implements(osp_stats.uniform.logpdf, update_doc=False) def logpdf(x: ArrayLike, loc: ArrayLike = 0, scale: ArrayLike = 1) -> Array: x, loc, scale = promote_args_inexact("uniform.logpdf", x, loc, scale) log_probs = lax.neg(lax.log(scale)) return where(logical_or(lax.gt(x, lax.add(loc, scale)), lax.lt(x, loc)), -inf, log_probs)
[docs] @implements(osp_stats.uniform.pdf, update_doc=False) def pdf(x: ArrayLike, loc: ArrayLike = 0, scale: ArrayLike = 1) -> Array: return lax.exp(logpdf(x, loc, scale))
[docs] @implements(osp_stats.uniform.cdf, update_doc=False) def cdf(x: ArrayLike, loc: ArrayLike = 0, scale: ArrayLike = 1) -> Array: x, loc, scale = promote_args_inexact("uniform.cdf", x, loc, scale) zero, one = jnp.array(0, x.dtype), jnp.array(1, x.dtype) conds = [lax.lt(x, loc), lax.gt(x, lax.add(loc, scale)), lax.ge(x, loc) & lax.le(x, lax.add(loc, scale))] vals = [zero, one, lax.div(lax.sub(x, loc), scale)] return jnp.select(conds, vals)
[docs] @implements(osp_stats.uniform.ppf, update_doc=False) def ppf(q: ArrayLike, loc: ArrayLike = 0, scale: ArrayLike = 1) -> Array: q, loc, scale = promote_args_inexact("uniform.ppf", q, loc, scale) return where( jnp.isnan(q) | (q < 0) | (q > 1), jnp.nan, lax.add(loc, lax.mul(scale, q)) )