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run rustfmt on librand folder
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@ -10,7 +10,7 @@
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//! The ChaCha random number generator.
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use {Rng, SeedableRng, Rand};
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use {Rand, Rng, SeedableRng};
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const KEY_WORDS: usize = 8; // 8 words for the 256-bit key
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const STATE_WORDS: usize = 16;
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@ -216,7 +216,8 @@ mod tests {
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let s = ::test::rng().gen_iter::<u32>().take(8).collect::<Vec<u32>>();
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let mut ra: ChaChaRng = SeedableRng::from_seed(&*s);
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let mut rb: ChaChaRng = SeedableRng::from_seed(&*s);
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assert!(ra.gen_ascii_chars().take(100)
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assert!(ra.gen_ascii_chars()
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.take(100)
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.eq(rb.gen_ascii_chars().take(100)));
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}
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@ -225,7 +226,8 @@ mod tests {
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let seed: &[_] = &[0, 1, 2, 3, 4, 5, 6, 7];
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let mut ra: ChaChaRng = SeedableRng::from_seed(seed);
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let mut rb: ChaChaRng = SeedableRng::from_seed(seed);
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assert!(ra.gen_ascii_chars().take(100)
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assert!(ra.gen_ascii_chars()
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.take(100)
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.eq(rb.gen_ascii_chars().take(100)));
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}
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@ -13,8 +13,8 @@
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#[cfg(not(test))] // only necessary for no_std
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use FloatMath;
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use {Rng, Rand};
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use distributions::{ziggurat, ziggurat_tables, Sample, IndependentSample};
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use {Rand, Rng};
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use distributions::{IndependentSample, Sample, ziggurat, ziggurat_tables};
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/// A wrapper around an `f64` to generate Exp(1) random numbers.
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///
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@ -88,7 +88,7 @@ impl IndependentSample<f64> for Exp {
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#[cfg(test)]
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mod tests {
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use distributions::{Sample, IndependentSample};
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use distributions::{IndependentSample, Sample};
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use super::Exp;
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#[test]
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@ -16,9 +16,9 @@ use self::ChiSquaredRepr::*;
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#[cfg(not(test))] // only necessary for no_std
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use FloatMath;
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use {Rng, Open01};
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use {Open01, Rng};
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use super::normal::StandardNormal;
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use super::{IndependentSample, Sample, Exp};
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use super::{Exp, IndependentSample, Sample};
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/// The Gamma distribution `Gamma(shape, scale)` distribution.
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///
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@ -291,8 +291,8 @@ impl IndependentSample<f64> for StudentT {
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#[cfg(test)]
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mod tests {
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use distributions::{Sample, IndependentSample};
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use super::{ChiSquared, StudentT, FisherF};
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use distributions::{IndependentSample, Sample};
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use super::{ChiSquared, FisherF, StudentT};
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#[test]
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fn test_chi_squared_one() {
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@ -22,11 +22,11 @@ use core::num::Float;
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use core::marker::PhantomData;
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use {Rng, Rand};
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use {Rand, Rng};
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pub use self::range::Range;
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pub use self::gamma::{Gamma, ChiSquared, FisherF, StudentT};
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pub use self::normal::{Normal, LogNormal};
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pub use self::gamma::{ChiSquared, FisherF, Gamma, StudentT};
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pub use self::normal::{LogNormal, Normal};
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pub use self::exponential::Exp;
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pub mod range;
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@ -266,8 +266,8 @@ fn ziggurat<R: Rng, P, Z>(rng: &mut R,
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#[cfg(test)]
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mod tests {
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use {Rng, Rand};
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use super::{RandSample, WeightedChoice, Weighted, Sample, IndependentSample};
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use {Rand, Rng};
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use super::{IndependentSample, RandSample, Sample, Weighted, WeightedChoice};
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#[derive(PartialEq, Debug)]
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struct ConstRand(usize);
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@ -13,8 +13,8 @@
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#[cfg(not(test))] // only necessary for no_std
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use FloatMath;
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use {Rng, Rand, Open01};
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use distributions::{ziggurat, ziggurat_tables, Sample, IndependentSample};
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use {Open01, Rand, Rng};
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use distributions::{IndependentSample, Sample, ziggurat, ziggurat_tables};
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/// A wrapper around an `f64` to generate N(0, 1) random numbers
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/// (a.k.a. a standard normal, or Gaussian).
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@ -145,8 +145,8 @@ impl IndependentSample<f64> for LogNormal {
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#[cfg(test)]
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mod tests {
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use distributions::{Sample, IndependentSample};
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use super::{Normal, LogNormal};
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use distributions::{IndependentSample, Sample};
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use super::{LogNormal, Normal};
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#[test]
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fn test_normal() {
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@ -14,7 +14,7 @@
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use core::marker::Sized;
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use Rng;
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use distributions::{Sample, IndependentSample};
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use distributions::{IndependentSample, Sample};
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/// Sample values uniformly between two bounds.
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///
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@ -148,7 +148,7 @@ float_impl! { f64 }
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#[cfg(test)]
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mod tests {
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use distributions::{Sample, IndependentSample};
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use distributions::{IndependentSample, Sample};
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use super::Range;
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#[should_panic]
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@ -16,7 +16,7 @@ use core::slice;
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use core::iter::repeat;
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use core::num::Wrapping as w;
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use {Rng, SeedableRng, Rand};
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use {Rand, Rng, SeedableRng};
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type w32 = w<u32>;
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type w64 = w<u64>;
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@ -591,14 +591,15 @@ mod tests {
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use std::prelude::v1::*;
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use {Rng, SeedableRng};
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use super::{IsaacRng, Isaac64Rng};
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use super::{Isaac64Rng, IsaacRng};
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#[test]
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fn test_rng_32_rand_seeded() {
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let s = ::test::rng().gen_iter::<u32>().take(256).collect::<Vec<u32>>();
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let mut ra: IsaacRng = SeedableRng::from_seed(&s[..]);
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let mut rb: IsaacRng = SeedableRng::from_seed(&s[..]);
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assert!(ra.gen_ascii_chars().take(100)
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assert!(ra.gen_ascii_chars()
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.take(100)
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.eq(rb.gen_ascii_chars().take(100)));
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}
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#[test]
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@ -606,7 +607,8 @@ mod tests {
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let s = ::test::rng().gen_iter::<u64>().take(256).collect::<Vec<u64>>();
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let mut ra: Isaac64Rng = SeedableRng::from_seed(&s[..]);
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let mut rb: Isaac64Rng = SeedableRng::from_seed(&s[..]);
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assert!(ra.gen_ascii_chars().take(100)
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assert!(ra.gen_ascii_chars()
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.take(100)
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.eq(rb.gen_ascii_chars().take(100)));
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}
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@ -615,7 +617,8 @@ mod tests {
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let seed: &[_] = &[1, 23, 456, 7890, 12345];
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let mut ra: IsaacRng = SeedableRng::from_seed(seed);
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let mut rb: IsaacRng = SeedableRng::from_seed(seed);
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assert!(ra.gen_ascii_chars().take(100)
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assert!(ra.gen_ascii_chars()
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.take(100)
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.eq(rb.gen_ascii_chars().take(100)));
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}
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#[test]
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@ -623,7 +626,8 @@ mod tests {
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let seed: &[_] = &[1, 23, 456, 7890, 12345];
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let mut ra: Isaac64Rng = SeedableRng::from_seed(seed);
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let mut rb: Isaac64Rng = SeedableRng::from_seed(seed);
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assert!(ra.gen_ascii_chars().take(100)
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assert!(ra.gen_ascii_chars()
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.take(100)
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.eq(rb.gen_ascii_chars().take(100)));
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}
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@ -47,10 +47,10 @@ use core::f64;
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use core::intrinsics;
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use core::marker::PhantomData;
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pub use isaac::{IsaacRng, Isaac64Rng};
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pub use isaac::{Isaac64Rng, IsaacRng};
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pub use chacha::ChaChaRng;
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use distributions::{Range, IndependentSample};
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use distributions::{IndependentSample, Range};
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use distributions::range::SampleRange;
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#[cfg(test)]
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@ -67,7 +67,7 @@ mod rand_impls;
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// depend on libstd. This will go away when librand is integrated
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// into libstd.
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#[doc(hidden)]
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trait FloatMath : Sized {
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trait FloatMath: Sized {
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fn exp(self) -> Self;
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fn ln(self) -> Self;
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fn sqrt(self) -> Self;
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@ -102,14 +102,14 @@ impl FloatMath for f64 {
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/// A type that can be randomly generated using an `Rng`.
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#[doc(hidden)]
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pub trait Rand : Sized {
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pub trait Rand: Sized {
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/// Generates a random instance of this type using the specified source of
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/// randomness.
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fn rand<R: Rng>(rng: &mut R) -> Self;
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}
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/// A random number generator.
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pub trait Rng : Sized {
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pub trait Rng: Sized {
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/// Return the next random u32.
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///
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/// This rarely needs to be called directly, prefer `r.gen()` to
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self.bytes_generated = 0;
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}
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/// Create a new `ReseedingRng` from the given reseeder and
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/// seed. This uses a default value for `generation_threshold`.
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/// Create a new `ReseedingRng` from the given reseeder and
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/// seed. This uses a default value for `generation_threshold`.
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fn from_seed((rsdr, seed): (Rsdr, S)) -> ReseedingRng<R, Rsdr> {
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ReseedingRng {
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rng: SeedableRng::from_seed(seed),
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@ -122,8 +122,8 @@ impl Default for ReseedWithDefault {
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mod tests {
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use std::prelude::v1::*;
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use super::{ReseedingRng, ReseedWithDefault};
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use {SeedableRng, Rng};
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use super::{ReseedWithDefault, ReseedingRng};
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use {Rng, SeedableRng};
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struct Counter {
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i: u32,
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@ -166,7 +166,8 @@ mod tests {
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fn test_rng_seeded() {
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let mut ra: MyRng = SeedableRng::from_seed((ReseedWithDefault, 2));
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let mut rb: MyRng = SeedableRng::from_seed((ReseedWithDefault, 2));
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assert!(ra.gen_ascii_chars().take(100)
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assert!(ra.gen_ascii_chars()
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.take(100)
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.eq(rb.gen_ascii_chars().take(100)));
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}
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