1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
|
// Copyright 2017 The Rust Project Developers. See the COPYRIGHT
// file at the top-level directory of this distribution and at
// http://rust-lang.org/COPYRIGHT.
//
// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
// http://www.apache.org/licenses/LICENSE-2.0> or the MIT license
// <LICENSE-MIT or http://opensource.org/licenses/MIT>, at your
// option. This file may not be copied, modified, or distributed
// except according to those terms.
//! Xorshift generators
use core::num::Wrapping as w;
use {Rng, SeedableRng, Rand};
/// An Xorshift[1] random number
/// generator.
///
/// The Xorshift algorithm is not suitable for cryptographic purposes
/// but is very fast. If you do not know for sure that it fits your
/// requirements, use a more secure one such as `IsaacRng` or `OsRng`.
///
/// [1]: Marsaglia, George (July 2003). ["Xorshift
/// RNGs"](http://www.jstatsoft.org/v08/i14/paper). *Journal of
/// Statistical Software*. Vol. 8 (Issue 14).
#[allow(missing_copy_implementations)]
#[derive(Clone, Debug)]
pub struct XorShiftRng {
x: w<u32>,
y: w<u32>,
z: w<u32>,
w: w<u32>,
}
impl XorShiftRng {
/// Creates a new XorShiftRng instance which is not seeded.
///
/// The initial values of this RNG are constants, so all generators created
/// by this function will yield the same stream of random numbers. It is
/// highly recommended that this is created through `SeedableRng` instead of
/// this function
pub fn new_unseeded() -> XorShiftRng {
XorShiftRng {
x: w(0x193a6754),
y: w(0xa8a7d469),
z: w(0x97830e05),
w: w(0x113ba7bb),
}
}
}
impl Rng for XorShiftRng {
#[inline]
fn next_u32(&mut self) -> u32 {
let x = self.x;
let t = x ^ (x << 11);
self.x = self.y;
self.y = self.z;
self.z = self.w;
let w_ = self.w;
self.w = w_ ^ (w_ >> 19) ^ (t ^ (t >> 8));
self.w.0
}
}
impl SeedableRng<[u32; 4]> for XorShiftRng {
/// Reseed an XorShiftRng. This will panic if `seed` is entirely 0.
fn reseed(&mut self, seed: [u32; 4]) {
assert!(!seed.iter().all(|&x| x == 0),
"XorShiftRng.reseed called with an all zero seed.");
self.x = w(seed[0]);
self.y = w(seed[1]);
self.z = w(seed[2]);
self.w = w(seed[3]);
}
/// Create a new XorShiftRng. This will panic if `seed` is entirely 0.
fn from_seed(seed: [u32; 4]) -> XorShiftRng {
assert!(!seed.iter().all(|&x| x == 0),
"XorShiftRng::from_seed called with an all zero seed.");
XorShiftRng {
x: w(seed[0]),
y: w(seed[1]),
z: w(seed[2]),
w: w(seed[3]),
}
}
}
impl Rand for XorShiftRng {
fn rand<R: Rng>(rng: &mut R) -> XorShiftRng {
let mut tuple: (u32, u32, u32, u32) = rng.gen();
while tuple == (0, 0, 0, 0) {
tuple = rng.gen();
}
let (x, y, z, w_) = tuple;
XorShiftRng { x: w(x), y: w(y), z: w(z), w: w(w_) }
}
}
|
