/rust/registry/src/index.crates.io-6f17d22bba15001f/rand-0.8.5/src/distributions/float.rs

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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 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
    /// [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 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<T: Copy + core::fmt::Debug + PartialEq, D: Distribution<T>>(
            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),
            ]);
        }
    }
}

Coverage Report

Created: 2023-04-25 07:07

Line	Count	Source (jump to first uncovered line)
1		// Copyright 2018 Developers of the Rand project.
2		//
3		// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
4		// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
5		// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
6		// option. This file may not be copied, modified, or distributed
7		// except according to those terms.
8
9		//! Basic floating-point number distributions
10
11		use crate::distributions::utils::FloatSIMDUtils;
12		use crate::distributions::{Distribution, Standard};
13		use crate::Rng;
14		use core::mem;
15		#[cfg(feature = "simd_support")] use packed_simd::*;
16
17		#[cfg(feature = "serde1")]
18		use serde::{Serialize, Deserialize};
19
20		/// A distribution to sample floating point numbers uniformly in the half-open
21		/// interval `(0, 1]`, i.e. including 1 but not 0.
22		///
23		/// All values that can be generated are of the form `n * ε/2`. For `f32`
24		/// the 24 most significant random bits of a `u32` are used and for `f64` the
25		/// 53 most significant bits of a `u64` are used. The conversion uses the
26		/// multiplicative method.
27		///
28		/// See also: [`Standard`] which samples from `[0, 1)`, [`Open01`]
29		/// which samples from `(0, 1)` and [`Uniform`] which samples from arbitrary
30		/// ranges.
31		///
32		/// # Example
33		/// ```
34		/// use rand::{thread_rng, Rng};
35		/// use rand::distributions::OpenClosed01;
36		///
37		/// let val: f32 = thread_rng().sample(OpenClosed01);
38		/// println!("f32 from (0, 1): {}", val);
39		/// ```
40		///
41		/// [`Standard`]: crate::distributions::Standard
42		/// [`Open01`]: crate::distributions::Open01
43		/// [`Uniform`]: crate::distributions::uniform::Uniform
44	0	#[derive(Clone, Copy, Debug)] Unexecuted instantiation: <rand::distributions::float::OpenClosed01 as core::clone::Clone>::clone Unexecuted instantiation: <rand::distributions::float::OpenClosed01 as core::clone::Clone>::clone Unexecuted instantiation: <rand::distributions::float::OpenClosed01 as core::fmt::Debug>::fmt Unexecuted instantiation: <rand::distributions::float::OpenClosed01 as core::fmt::Debug>::fmt
45		#[cfg_attr(feature = "serde1", derive(Serialize, Deserialize))]
46		pub struct OpenClosed01;
47
48		/// A distribution to sample floating point numbers uniformly in the open
49		/// interval `(0, 1)`, i.e. not including either endpoint.
50		///
51		/// All values that can be generated are of the form `n * ε + ε/2`. For `f32`
52		/// the 23 most significant random bits of an `u32` are used, for `f64` 52 from
53		/// an `u64`. The conversion uses a transmute-based method.
54		///
55		/// See also: [`Standard`] which samples from `[0, 1)`, [`OpenClosed01`]
56		/// which samples from `(0, 1]` and [`Uniform`] which samples from arbitrary
57		/// ranges.
58		///
59		/// # Example
60		/// ```
61		/// use rand::{thread_rng, Rng};
62		/// use rand::distributions::Open01;
63		///
64		/// let val: f32 = thread_rng().sample(Open01);
65		/// println!("f32 from (0, 1): {}", val);
66		/// ```
67		///
68		/// [`Standard`]: crate::distributions::Standard
69		/// [`OpenClosed01`]: crate::distributions::OpenClosed01
70		/// [`Uniform`]: crate::distributions::uniform::Uniform
71	0	#[derive(Clone, Copy, Debug)] Unexecuted instantiation: <rand::distributions::float::Open01 as core::clone::Clone>::clone Unexecuted instantiation: <rand::distributions::float::Open01 as core::clone::Clone>::clone Unexecuted instantiation: <rand::distributions::float::Open01 as core::fmt::Debug>::fmt Unexecuted instantiation: <rand::distributions::float::Open01 as core::fmt::Debug>::fmt
72		#[cfg_attr(feature = "serde1", derive(Serialize, Deserialize))]
73		pub struct Open01;
74
75
76		// This trait is needed by both this lib and rand_distr hence is a hidden export
77		#[doc(hidden)]
78		pub trait IntoFloat {
79		type F;
80
81		/// Helper method to combine the fraction and a constant exponent into a
82		/// float.
83		///
84		/// Only the least significant bits of `self` may be set, 23 for `f32` and
85		/// 52 for `f64`.
86		/// The resulting value will fall in a range that depends on the exponent.
87		/// As an example the range with exponent 0 will be
88		/// [2<sup>0</sup>..2<sup>1</sup>), which is [1..2).
89		fn into_float_with_exponent(self, exponent: i32) -> Self::F;
90		}
91
92		macro_rules! float_impls {
93		($ty:ident, $uty:ident, $f_scalar:ident, $u_scalar:ty,
94		$fraction_bits:expr, $exponent_bias:expr) => {
95		impl IntoFloat for $uty {
96		type F = $ty;
97		#[inline(always)]
98	0	fn into_float_with_exponent(self, exponent: i32) -> $ty {
99	0	// The exponent is encoded using an offset-binary representation
100	0	let exponent_bits: $u_scalar =
101	0	(($exponent_bias + exponent) as $u_scalar) << $fraction_bits;
102	0	$ty::from_bits(self \| exponent_bits)
103	0	} Unexecuted instantiation: <u32 as rand::distributions::float::IntoFloat>::into_float_with_exponent Unexecuted instantiation: <u64 as rand::distributions::float::IntoFloat>::into_float_with_exponent Unexecuted instantiation: <u32 as rand::distributions::float::IntoFloat>::into_float_with_exponent Unexecuted instantiation: <u64 as rand::distributions::float::IntoFloat>::into_float_with_exponent
104		}
105
106		impl Distribution<$ty> for Standard {
107	0	fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> $ty {
108	0	// Multiply-based method; 24/53 random bits; [0, 1) interval.
109	0	// We use the most significant bits because for simple RNGs
110	0	// those are usually more random.
111	0	let float_size = mem::size_of::<$f_scalar>() as u32 * 8;
112	0	let precision = $fraction_bits + 1;
113	0	let scale = 1.0 / ((1 as $u_scalar << precision) as $f_scalar);
114	0
115	0	let value: $uty = rng.gen();
116	0	let value = value >> (float_size - precision);
117	0	scale * $ty::cast_from_int(value)
118	0	} Unexecuted instantiation: <rand::distributions::Standard as rand::distributions::distribution::Distribution<f64>>::sample::<_> Unexecuted instantiation: <rand::distributions::Standard as rand::distributions::distribution::Distribution<f32>>::sample::<_> Unexecuted instantiation: <rand::distributions::Standard as rand::distributions::distribution::Distribution<f64>>::sample::<_> Unexecuted instantiation: <rand::distributions::Standard as rand::distributions::distribution::Distribution<f32>>::sample::<_>
119		}
120
121		impl Distribution<$ty> for OpenClosed01 {
122	0	fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> $ty {
123	0	// Multiply-based method; 24/53 random bits; (0, 1] interval.
124	0	// We use the most significant bits because for simple RNGs
125	0	// those are usually more random.
126	0	let float_size = mem::size_of::<$f_scalar>() as u32 * 8;
127	0	let precision = $fraction_bits + 1;
128	0	let scale = 1.0 / ((1 as $u_scalar << precision) as $f_scalar);
129	0
130	0	let value: $uty = rng.gen();
131	0	let value = value >> (float_size - precision);
132	0	// Add 1 to shift up; will not overflow because of right-shift:
133	0	scale * $ty::cast_from_int(value + 1)
134	0	} Unexecuted instantiation: <rand::distributions::float::OpenClosed01 as rand::distributions::distribution::Distribution<f64>>::sample::<_> Unexecuted instantiation: <rand::distributions::float::OpenClosed01 as rand::distributions::distribution::Distribution<f32>>::sample::<_> Unexecuted instantiation: <rand::distributions::float::OpenClosed01 as rand::distributions::distribution::Distribution<f64>>::sample::<_> Unexecuted instantiation: <rand::distributions::float::OpenClosed01 as rand::distributions::distribution::Distribution<f32>>::sample::<_>
135		}
136
137		impl Distribution<$ty> for Open01 {
138	0	fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> $ty {
139	0	// Transmute-based method; 23/52 random bits; (0, 1) interval.
140	0	// We use the most significant bits because for simple RNGs
141	0	// those are usually more random.
142	0	use core::$f_scalar::EPSILON;
143	0	let float_size = mem::size_of::<$f_scalar>() as u32 * 8;
144	0
145	0	let value: $uty = rng.gen();
146	0	let fraction = value >> (float_size - $fraction_bits);
147	0	fraction.into_float_with_exponent(0) - (1.0 - EPSILON / 2.0)
148	0	} Unexecuted instantiation: <rand::distributions::float::Open01 as rand::distributions::distribution::Distribution<f32>>::sample::<_> Unexecuted instantiation: <rand::distributions::float::Open01 as rand::distributions::distribution::Distribution<f64>>::sample::<_> Unexecuted instantiation: <rand::distributions::float::Open01 as rand::distributions::distribution::Distribution<f32>>::sample::<_> Unexecuted instantiation: <rand::distributions::float::Open01 as rand::distributions::distribution::Distribution<f64>>::sample::<_>
149		}
150		}
151		}
152
153		float_impls! { f32, u32, f32, u32, 23, 127 }
154		float_impls! { f64, u64, f64, u64, 52, 1023 }
155
156		#[cfg(feature = "simd_support")]
157		float_impls! { f32x2, u32x2, f32, u32, 23, 127 }
158		#[cfg(feature = "simd_support")]
159		float_impls! { f32x4, u32x4, f32, u32, 23, 127 }
160		#[cfg(feature = "simd_support")]
161		float_impls! { f32x8, u32x8, f32, u32, 23, 127 }
162		#[cfg(feature = "simd_support")]
163		float_impls! { f32x16, u32x16, f32, u32, 23, 127 }
164
165		#[cfg(feature = "simd_support")]
166		float_impls! { f64x2, u64x2, f64, u64, 52, 1023 }
167		#[cfg(feature = "simd_support")]
168		float_impls! { f64x4, u64x4, f64, u64, 52, 1023 }
169		#[cfg(feature = "simd_support")]
170		float_impls! { f64x8, u64x8, f64, u64, 52, 1023 }
171
172
173		#[cfg(test)]
174		mod tests {
175		use super::*;
176		use crate::rngs::mock::StepRng;
177
178		const EPSILON32: f32 = ::core::f32::EPSILON;
179		const EPSILON64: f64 = ::core::f64::EPSILON;
180
181		macro_rules! test_f32 {
182		($fnn:ident, $ty:ident, $ZERO:expr, $EPSILON:expr) => {
183		#[test]
184		fn $fnn() {
185		// Standard
186		let mut zeros = StepRng::new(0, 0);
187		assert_eq!(zeros.gen::<$ty>(), $ZERO);
188		let mut one = StepRng::new(1 << 8 \| 1 << (8 + 32), 0);
189		assert_eq!(one.gen::<$ty>(), $EPSILON / 2.0);
190		let mut max = StepRng::new(!0, 0);
191		assert_eq!(max.gen::<$ty>(), 1.0 - $EPSILON / 2.0);
192
193		// OpenClosed01
194		let mut zeros = StepRng::new(0, 0);
195		assert_eq!(zeros.sample::<$ty, _>(OpenClosed01), 0.0 + $EPSILON / 2.0);
196		let mut one = StepRng::new(1 << 8 \| 1 << (8 + 32), 0);
197		assert_eq!(one.sample::<$ty, _>(OpenClosed01), $EPSILON);
198		let mut max = StepRng::new(!0, 0);
199		assert_eq!(max.sample::<$ty, _>(OpenClosed01), $ZERO + 1.0);
200
201		// Open01
202		let mut zeros = StepRng::new(0, 0);
203		assert_eq!(zeros.sample::<$ty, _>(Open01), 0.0 + $EPSILON / 2.0);
204		let mut one = StepRng::new(1 << 9 \| 1 << (9 + 32), 0);
205		assert_eq!(one.sample::<$ty, _>(Open01), $EPSILON / 2.0 * 3.0);
206		let mut max = StepRng::new(!0, 0);
207		assert_eq!(max.sample::<$ty, _>(Open01), 1.0 - $EPSILON / 2.0);
208		}
209		};
210		}
211		test_f32! { f32_edge_cases, f32, 0.0, EPSILON32 }
212		#[cfg(feature = "simd_support")]
213		test_f32! { f32x2_edge_cases, f32x2, f32x2::splat(0.0), f32x2::splat(EPSILON32) }
214		#[cfg(feature = "simd_support")]
215		test_f32! { f32x4_edge_cases, f32x4, f32x4::splat(0.0), f32x4::splat(EPSILON32) }
216		#[cfg(feature = "simd_support")]
217		test_f32! { f32x8_edge_cases, f32x8, f32x8::splat(0.0), f32x8::splat(EPSILON32) }
218		#[cfg(feature = "simd_support")]
219		test_f32! { f32x16_edge_cases, f32x16, f32x16::splat(0.0), f32x16::splat(EPSILON32) }
220
221		macro_rules! test_f64 {
222		($fnn:ident, $ty:ident, $ZERO:expr, $EPSILON:expr) => {
223		#[test]
224		fn $fnn() {
225		// Standard
226		let mut zeros = StepRng::new(0, 0);
227		assert_eq!(zeros.gen::<$ty>(), $ZERO);
228		let mut one = StepRng::new(1 << 11, 0);
229		assert_eq!(one.gen::<$ty>(), $EPSILON / 2.0);
230		let mut max = StepRng::new(!0, 0);
231		assert_eq!(max.gen::<$ty>(), 1.0 - $EPSILON / 2.0);
232
233		// OpenClosed01
234		let mut zeros = StepRng::new(0, 0);
235		assert_eq!(zeros.sample::<$ty, _>(OpenClosed01), 0.0 + $EPSILON / 2.0);
236		let mut one = StepRng::new(1 << 11, 0);
237		assert_eq!(one.sample::<$ty, _>(OpenClosed01), $EPSILON);
238		let mut max = StepRng::new(!0, 0);
239		assert_eq!(max.sample::<$ty, _>(OpenClosed01), $ZERO + 1.0);
240
241		// Open01
242		let mut zeros = StepRng::new(0, 0);
243		assert_eq!(zeros.sample::<$ty, _>(Open01), 0.0 + $EPSILON / 2.0);
244		let mut one = StepRng::new(1 << 12, 0);
245		assert_eq!(one.sample::<$ty, _>(Open01), $EPSILON / 2.0 * 3.0);
246		let mut max = StepRng::new(!0, 0);
247		assert_eq!(max.sample::<$ty, _>(Open01), 1.0 - $EPSILON / 2.0);
248		}
249		};
250		}
251		test_f64! { f64_edge_cases, f64, 0.0, EPSILON64 }
252		#[cfg(feature = "simd_support")]
253		test_f64! { f64x2_edge_cases, f64x2, f64x2::splat(0.0), f64x2::splat(EPSILON64) }
254		#[cfg(feature = "simd_support")]
255		test_f64! { f64x4_edge_cases, f64x4, f64x4::splat(0.0), f64x4::splat(EPSILON64) }
256		#[cfg(feature = "simd_support")]
257		test_f64! { f64x8_edge_cases, f64x8, f64x8::splat(0.0), f64x8::splat(EPSILON64) }
258
259		#[test]
260		fn value_stability() {
261		fn test_samples<T: Copy + core::fmt::Debug + PartialEq, D: Distribution<T>>(
262		distr: &D, zero: T, expected: &[T],
263		) {
264		let mut rng = crate::test::rng(0x6f44f5646c2a7334);
265		let mut buf = [zero; 3];
266		for x in &mut buf {
267		*x = rng.sample(&distr);
268		}
269		assert_eq!(&buf, expected);
270		}
271
272		test_samples(&Standard, 0f32, &[0.0035963655, 0.7346052, 0.09778172]);
273		test_samples(&Standard, 0f64, &[
274		0.7346051961657583,
275		0.20298547462974248,
276		0.8166436635290655,
277		]);
278
279		test_samples(&OpenClosed01, 0f32, &[0.003596425, 0.73460525, 0.09778178]);
280		test_samples(&OpenClosed01, 0f64, &[
281		0.7346051961657584,
282		0.2029854746297426,
283		0.8166436635290656,
284		]);
285
286		test_samples(&Open01, 0f32, &[0.0035963655, 0.73460525, 0.09778172]);
287		test_samples(&Open01, 0f64, &[
288		0.7346051961657584,
289		0.20298547462974248,
290		0.8166436635290656,
291		]);
292
293		#[cfg(feature = "simd_support")]
294		{
295		// We only test a sub-set of types here. Values are identical to
296		// non-SIMD types; we assume this pattern continues across all
297		// SIMD types.
298
299		test_samples(&Standard, f32x2::new(0.0, 0.0), &[
300		f32x2::new(0.0035963655, 0.7346052),
301		f32x2::new(0.09778172, 0.20298547),
302		f32x2::new(0.34296435, 0.81664366),
303		]);
304
305		test_samples(&Standard, f64x2::new(0.0, 0.0), &[
306		f64x2::new(0.7346051961657583, 0.20298547462974248),
307		f64x2::new(0.8166436635290655, 0.7423708925400552),
308		f64x2::new(0.16387782224016323, 0.9087068770169618),
309		]);
310		}
311		}
312		}