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

# Copyright 2018 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.
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#     https://www.apache.org/licenses/LICENSE-2.0
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# Unless required by applicable law or agreed to in writing, software
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import scipy.stats as osp_stats

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 implements, promote_args_inexact
from jax._src.typing import Array, ArrayLike
from jax.scipy.special import betaln, betainc, xlogy, xlog1py


[docs] @implements(osp_stats.beta.logpdf, update_doc=False) def logpdf(x: ArrayLike, a: ArrayLike, b: ArrayLike, loc: ArrayLike = 0, scale: ArrayLike = 1) -> Array: x, a, b, loc, scale = promote_args_inexact("beta.logpdf", x, a, b, loc, scale) one = _lax_const(x, 1) shape_term = lax.neg(betaln(a, b)) y = lax.div(lax.sub(x, loc), scale) log_linear_term = lax.add(xlogy(lax.sub(a, one), y), xlog1py(lax.sub(b, one), lax.neg(y))) log_probs = lax.sub(lax.add(shape_term, log_linear_term), lax.log(scale)) return jnp.where(jnp.logical_or(lax.gt(x, lax.add(loc, scale)), lax.lt(x, loc)), -jnp.inf, log_probs)
[docs] @implements(osp_stats.beta.pdf, update_doc=False) def pdf(x: ArrayLike, a: ArrayLike, b: ArrayLike, loc: ArrayLike = 0, scale: ArrayLike = 1) -> Array: return lax.exp(logpdf(x, a, b, loc, scale))
[docs] @implements(osp_stats.beta.cdf, update_doc=False) def cdf(x: ArrayLike, a: ArrayLike, b: ArrayLike, loc: ArrayLike = 0, scale: ArrayLike = 1) -> Array: x, a, b, loc, scale = promote_args_inexact("beta.cdf", x, a, b, loc, scale) return betainc( a, b, lax.clamp( _lax_const(x, 0), lax.div(lax.sub(x, loc), scale), _lax_const(x, 1), ) )
[docs] @implements(osp_stats.beta.logcdf, update_doc=False) def logcdf(x: ArrayLike, a: ArrayLike, b: ArrayLike, loc: ArrayLike = 0, scale: ArrayLike = 1) -> Array: return lax.log(cdf(x, a, b, loc, scale))
[docs] @implements(osp_stats.beta.sf, update_doc=False) def sf(x: ArrayLike, a: ArrayLike, b: ArrayLike, loc: ArrayLike = 0, scale: ArrayLike = 1) -> Array: x, a, b, loc, scale = promote_args_inexact("beta.sf", x, a, b, loc, scale) return betainc( b, a, 1 - lax.clamp( _lax_const(x, 0), lax.div(lax.sub(x, loc), scale), _lax_const(x, 1), ) )
[docs] @implements(osp_stats.beta.logsf, update_doc=False) def logsf(x: ArrayLike, a: ArrayLike, b: ArrayLike, loc: ArrayLike = 0, scale: ArrayLike = 1) -> Array: return lax.log(sf(x, a, b, loc, scale))