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-// Copyright 2018 Developers of the Rand project.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! Basic floating-point number distributions
-
-use core::mem;
-use crate::Rng;
-use crate::distributions::{Distribution, Standard};
-use crate::distributions::utils::FloatSIMDUtils;
-#[cfg(feature="simd_support")]
-use packed_simd::*;
-
-/// 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 23 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)]
-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 22 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)]
-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 contant 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
- /// [2<sup>0</sup>..2<sup>1</sup>), 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<R: Rng + ?Sized>(&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<R: Rng + ?Sized>(&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<R: Rng + ?Sized>(&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 - $fraction_bits);
- fraction.into_float_with_exponent(0) - (1.0 - EPSILON / 2.0)
- }
- }
- }
-}
-
-float_impls! { f32, u32, f32, u32, 23, 127 }
-float_impls! { f64, u64, f64, u64, 52, 1023 }
-
-#[cfg(feature="simd_support")]
-float_impls! { f32x2, u32x2, f32, u32, 23, 127 }
-#[cfg(feature="simd_support")]
-float_impls! { f32x4, u32x4, f32, u32, 23, 127 }
-#[cfg(feature="simd_support")]
-float_impls! { f32x8, u32x8, f32, u32, 23, 127 }
-#[cfg(feature="simd_support")]
-float_impls! { f32x16, u32x16, f32, u32, 23, 127 }
-
-#[cfg(feature="simd_support")]
-float_impls! { f64x2, u64x2, f64, u64, 52, 1023 }
-#[cfg(feature="simd_support")]
-float_impls! { f64x4, u64x4, f64, u64, 52, 1023 }
-#[cfg(feature="simd_support")]
-float_impls! { f64x8, u64x8, f64, u64, 52, 1023 }
-
-
-#[cfg(test)]
-mod tests {
- use crate::Rng;
- use crate::distributions::{Open01, OpenClosed01};
- use crate::rngs::mock::StepRng;
- #[cfg(feature="simd_support")]
- use packed_simd::*;
-
- const EPSILON32: f32 = ::core::f32::EPSILON;
- const EPSILON64: f64 = ::core::f64::EPSILON;
-
- macro_rules! test_f32 {
- ($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) }
-}