From 43a97878ce14b72f0981164f87f2e35e14151312 Mon Sep 17 00:00:00 2001 From: Daniel Baumann Date: Sun, 7 Apr 2024 11:22:09 +0200 Subject: Adding upstream version 110.0.1. Signed-off-by: Daniel Baumann --- third_party/rust/rand/src/distributions/float.rs | 312 +++++++++++++++++++++++ 1 file changed, 312 insertions(+) create mode 100644 third_party/rust/rand/src/distributions/float.rs (limited to 'third_party/rust/rand/src/distributions/float.rs') diff --git a/third_party/rust/rand/src/distributions/float.rs b/third_party/rust/rand/src/distributions/float.rs new file mode 100644 index 0000000000..ce5946f7f0 --- /dev/null +++ b/third_party/rust/rand/src/distributions/float.rs @@ -0,0 +1,312 @@ +// Copyright 2018 Developers of the Rand project. +// +// Licensed under the Apache License, Version 2.0 or the MIT license +// , at your +// option. This file may not be copied, modified, or distributed +// except according to those terms. + +//! Basic floating-point number distributions + +use crate::distributions::utils::FloatSIMDUtils; +use crate::distributions::{Distribution, Standard}; +use crate::Rng; +use core::mem; +#[cfg(feature = "simd_support")] use packed_simd::*; + +#[cfg(feature = "serde1")] +use serde::{Serialize, Deserialize}; + +/// A distribution to sample floating point numbers uniformly in the half-open +/// interval `(0, 1]`, i.e. including 1 but not 0. +/// +/// All values that can be generated are of the form `n * ε/2`. For `f32` +/// the 24 most significant random bits of a `u32` are used and for `f64` the +/// 53 most significant bits of a `u64` are used. The conversion uses the +/// multiplicative method. +/// +/// See also: [`Standard`] which samples from `[0, 1)`, [`Open01`] +/// which samples from `(0, 1)` and [`Uniform`] which samples from arbitrary +/// ranges. +/// +/// # Example +/// ``` +/// use rand::{thread_rng, Rng}; +/// use rand::distributions::OpenClosed01; +/// +/// let val: f32 = thread_rng().sample(OpenClosed01); +/// println!("f32 from (0, 1): {}", val); +/// ``` +/// +/// [`Standard`]: crate::distributions::Standard +/// [`Open01`]: crate::distributions::Open01 +/// [`Uniform`]: crate::distributions::uniform::Uniform +#[derive(Clone, Copy, Debug)] +#[cfg_attr(feature = "serde1", derive(Serialize, Deserialize))] +pub struct OpenClosed01; + +/// A distribution to sample floating point numbers uniformly in the open +/// interval `(0, 1)`, i.e. not including either endpoint. +/// +/// All values that can be generated are of the form `n * ε + ε/2`. For `f32` +/// the 23 most significant random bits of an `u32` are used, for `f64` 52 from +/// an `u64`. The conversion uses a transmute-based method. +/// +/// See also: [`Standard`] which samples from `[0, 1)`, [`OpenClosed01`] +/// which samples from `(0, 1]` and [`Uniform`] which samples from arbitrary +/// ranges. +/// +/// # Example +/// ``` +/// use rand::{thread_rng, Rng}; +/// use rand::distributions::Open01; +/// +/// let val: f32 = thread_rng().sample(Open01); +/// println!("f32 from (0, 1): {}", val); +/// ``` +/// +/// [`Standard`]: crate::distributions::Standard +/// [`OpenClosed01`]: crate::distributions::OpenClosed01 +/// [`Uniform`]: crate::distributions::uniform::Uniform +#[derive(Clone, Copy, Debug)] +#[cfg_attr(feature = "serde1", derive(Serialize, Deserialize))] +pub struct Open01; + + +// This trait is needed by both this lib and rand_distr hence is a hidden export +#[doc(hidden)] +pub trait IntoFloat { + type F; + + /// Helper method to combine the fraction and a constant exponent into a + /// float. + /// + /// Only the least significant bits of `self` may be set, 23 for `f32` and + /// 52 for `f64`. + /// The resulting value will fall in a range that depends on the exponent. + /// As an example the range with exponent 0 will be + /// [20..21), which is [1..2). + fn into_float_with_exponent(self, exponent: i32) -> Self::F; +} + +macro_rules! float_impls { + ($ty:ident, $uty:ident, $f_scalar:ident, $u_scalar:ty, + $fraction_bits:expr, $exponent_bias:expr) => { + impl IntoFloat for $uty { + type F = $ty; + #[inline(always)] + fn into_float_with_exponent(self, exponent: i32) -> $ty { + // The exponent is encoded using an offset-binary representation + let exponent_bits: $u_scalar = + (($exponent_bias + exponent) as $u_scalar) << $fraction_bits; + $ty::from_bits(self | exponent_bits) + } + } + + impl Distribution<$ty> for Standard { + fn sample(&self, rng: &mut R) -> $ty { + // Multiply-based method; 24/53 random bits; [0, 1) interval. + // We use the most significant bits because for simple RNGs + // those are usually more random. + let float_size = mem::size_of::<$f_scalar>() as u32 * 8; + let precision = $fraction_bits + 1; + let scale = 1.0 / ((1 as $u_scalar << precision) as $f_scalar); + + let value: $uty = rng.gen(); + let value = value >> (float_size - precision); + scale * $ty::cast_from_int(value) + } + } + + impl Distribution<$ty> for OpenClosed01 { + fn sample(&self, rng: &mut R) -> $ty { + // Multiply-based method; 24/53 random bits; (0, 1] interval. + // We use the most significant bits because for simple RNGs + // those are usually more random. + let float_size = mem::size_of::<$f_scalar>() as u32 * 8; + let precision = $fraction_bits + 1; + let scale = 1.0 / ((1 as $u_scalar << precision) as $f_scalar); + + let value: $uty = rng.gen(); + let value = value >> (float_size - precision); + // Add 1 to shift up; will not overflow because of right-shift: + scale * $ty::cast_from_int(value + 1) + } + } + + impl Distribution<$ty> for Open01 { + fn sample(&self, rng: &mut R) -> $ty { + // Transmute-based method; 23/52 random bits; (0, 1) interval. + // We use the most significant bits because for simple RNGs + // those are usually more random. + use core::$f_scalar::EPSILON; + let float_size = mem::size_of::<$f_scalar>() as u32 * 8; + + let value: $uty = rng.gen(); + let fraction = value >> (float_size - $fraction_bits); + fraction.into_float_with_exponent(0) - (1.0 - EPSILON / 2.0) + } + } + } +} + +float_impls! { f32, u32, f32, u32, 23, 127 } +float_impls! { f64, u64, f64, u64, 52, 1023 } + +#[cfg(feature = "simd_support")] +float_impls! { f32x2, u32x2, f32, u32, 23, 127 } +#[cfg(feature = "simd_support")] +float_impls! { f32x4, u32x4, f32, u32, 23, 127 } +#[cfg(feature = "simd_support")] +float_impls! { f32x8, u32x8, f32, u32, 23, 127 } +#[cfg(feature = "simd_support")] +float_impls! { f32x16, u32x16, f32, u32, 23, 127 } + +#[cfg(feature = "simd_support")] +float_impls! { f64x2, u64x2, f64, u64, 52, 1023 } +#[cfg(feature = "simd_support")] +float_impls! { f64x4, u64x4, f64, u64, 52, 1023 } +#[cfg(feature = "simd_support")] +float_impls! { f64x8, u64x8, f64, u64, 52, 1023 } + + +#[cfg(test)] +mod tests { + use super::*; + use crate::rngs::mock::StepRng; + + const EPSILON32: f32 = ::core::f32::EPSILON; + const EPSILON64: f64 = ::core::f64::EPSILON; + + macro_rules! test_f32 { + ($fnn:ident, $ty:ident, $ZERO:expr, $EPSILON:expr) => { + #[test] + fn $fnn() { + // Standard + let mut zeros = StepRng::new(0, 0); + assert_eq!(zeros.gen::<$ty>(), $ZERO); + let mut one = StepRng::new(1 << 8 | 1 << (8 + 32), 0); + assert_eq!(one.gen::<$ty>(), $EPSILON / 2.0); + let mut max = StepRng::new(!0, 0); + assert_eq!(max.gen::<$ty>(), 1.0 - $EPSILON / 2.0); + + // OpenClosed01 + let mut zeros = StepRng::new(0, 0); + assert_eq!(zeros.sample::<$ty, _>(OpenClosed01), 0.0 + $EPSILON / 2.0); + let mut one = StepRng::new(1 << 8 | 1 << (8 + 32), 0); + assert_eq!(one.sample::<$ty, _>(OpenClosed01), $EPSILON); + let mut max = StepRng::new(!0, 0); + assert_eq!(max.sample::<$ty, _>(OpenClosed01), $ZERO + 1.0); + + // Open01 + let mut zeros = StepRng::new(0, 0); + assert_eq!(zeros.sample::<$ty, _>(Open01), 0.0 + $EPSILON / 2.0); + let mut one = StepRng::new(1 << 9 | 1 << (9 + 32), 0); + assert_eq!(one.sample::<$ty, _>(Open01), $EPSILON / 2.0 * 3.0); + let mut max = StepRng::new(!0, 0); + assert_eq!(max.sample::<$ty, _>(Open01), 1.0 - $EPSILON / 2.0); + } + }; + } + test_f32! { f32_edge_cases, f32, 0.0, EPSILON32 } + #[cfg(feature = "simd_support")] + test_f32! { f32x2_edge_cases, f32x2, f32x2::splat(0.0), f32x2::splat(EPSILON32) } + #[cfg(feature = "simd_support")] + test_f32! { f32x4_edge_cases, f32x4, f32x4::splat(0.0), f32x4::splat(EPSILON32) } + #[cfg(feature = "simd_support")] + test_f32! { f32x8_edge_cases, f32x8, f32x8::splat(0.0), f32x8::splat(EPSILON32) } + #[cfg(feature = "simd_support")] + test_f32! { f32x16_edge_cases, f32x16, f32x16::splat(0.0), f32x16::splat(EPSILON32) } + + macro_rules! test_f64 { + ($fnn:ident, $ty:ident, $ZERO:expr, $EPSILON:expr) => { + #[test] + fn $fnn() { + // Standard + let mut zeros = StepRng::new(0, 0); + assert_eq!(zeros.gen::<$ty>(), $ZERO); + let mut one = StepRng::new(1 << 11, 0); + assert_eq!(one.gen::<$ty>(), $EPSILON / 2.0); + let mut max = StepRng::new(!0, 0); + assert_eq!(max.gen::<$ty>(), 1.0 - $EPSILON / 2.0); + + // OpenClosed01 + let mut zeros = StepRng::new(0, 0); + assert_eq!(zeros.sample::<$ty, _>(OpenClosed01), 0.0 + $EPSILON / 2.0); + let mut one = StepRng::new(1 << 11, 0); + assert_eq!(one.sample::<$ty, _>(OpenClosed01), $EPSILON); + let mut max = StepRng::new(!0, 0); + assert_eq!(max.sample::<$ty, _>(OpenClosed01), $ZERO + 1.0); + + // Open01 + let mut zeros = StepRng::new(0, 0); + assert_eq!(zeros.sample::<$ty, _>(Open01), 0.0 + $EPSILON / 2.0); + let mut one = StepRng::new(1 << 12, 0); + assert_eq!(one.sample::<$ty, _>(Open01), $EPSILON / 2.0 * 3.0); + let mut max = StepRng::new(!0, 0); + assert_eq!(max.sample::<$ty, _>(Open01), 1.0 - $EPSILON / 2.0); + } + }; + } + test_f64! { f64_edge_cases, f64, 0.0, EPSILON64 } + #[cfg(feature = "simd_support")] + test_f64! { f64x2_edge_cases, f64x2, f64x2::splat(0.0), f64x2::splat(EPSILON64) } + #[cfg(feature = "simd_support")] + test_f64! { f64x4_edge_cases, f64x4, f64x4::splat(0.0), f64x4::splat(EPSILON64) } + #[cfg(feature = "simd_support")] + test_f64! { f64x8_edge_cases, f64x8, f64x8::splat(0.0), f64x8::splat(EPSILON64) } + + #[test] + fn value_stability() { + fn test_samples>( + distr: &D, zero: T, expected: &[T], + ) { + let mut rng = crate::test::rng(0x6f44f5646c2a7334); + let mut buf = [zero; 3]; + for x in &mut buf { + *x = rng.sample(&distr); + } + assert_eq!(&buf, expected); + } + + test_samples(&Standard, 0f32, &[0.0035963655, 0.7346052, 0.09778172]); + test_samples(&Standard, 0f64, &[ + 0.7346051961657583, + 0.20298547462974248, + 0.8166436635290655, + ]); + + test_samples(&OpenClosed01, 0f32, &[0.003596425, 0.73460525, 0.09778178]); + test_samples(&OpenClosed01, 0f64, &[ + 0.7346051961657584, + 0.2029854746297426, + 0.8166436635290656, + ]); + + test_samples(&Open01, 0f32, &[0.0035963655, 0.73460525, 0.09778172]); + test_samples(&Open01, 0f64, &[ + 0.7346051961657584, + 0.20298547462974248, + 0.8166436635290656, + ]); + + #[cfg(feature = "simd_support")] + { + // We only test a sub-set of types here. Values are identical to + // non-SIMD types; we assume this pattern continues across all + // SIMD types. + + test_samples(&Standard, f32x2::new(0.0, 0.0), &[ + f32x2::new(0.0035963655, 0.7346052), + f32x2::new(0.09778172, 0.20298547), + f32x2::new(0.34296435, 0.81664366), + ]); + + test_samples(&Standard, f64x2::new(0.0, 0.0), &[ + f64x2::new(0.7346051961657583, 0.20298547462974248), + f64x2::new(0.8166436635290655, 0.7423708925400552), + f64x2::new(0.16387782224016323, 0.9087068770169618), + ]); + } + } +} -- cgit v1.2.3