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