1 // Copyright 2013 The Rust Project Developers. See the COPYRIGHT
2 // file at the top-level directory of this distribution and at
3 // http://rust-lang.org/COPYRIGHT.
5 // Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
6 // http://www.apache.org/licenses/LICENSE-2.0> or the MIT license
7 // <LICENSE-MIT or http://opensource.org/licenses/MIT>, at your
8 // option. This file may not be copied, modified, or distributed
9 // except according to those terms.
12 Utilities for random number generation
14 The key functions are `random()` and `Rng::gen()`. These are polymorphic
15 and so can be used to generate any type that implements `Rand`. Type inference
16 means that often a simple call to `rand::random()` or `rng.gen()` will
17 suffice, but sometimes an annotation is required, e.g. `rand::random::<f64>()`.
19 See the `distributions` submodule for sampling random numbers from
20 distributions like normal and exponential.
24 There is built-in support for a RNG associated with each task stored
25 in task-local storage. This RNG can be accessed via `task_rng`, or
26 used implicitly via `random`. This RNG is normally randomly seeded
27 from an operating-system source of randomness, e.g. `/dev/urandom` on
28 Unix systems, and will automatically reseed itself from this source
29 after generating 32 KiB of random data.
31 # Cryptographic security
33 An application that requires random numbers for cryptographic purposes
34 should prefer `OSRng`, which reads randomness from one of the source
35 that the operating system provides (e.g. `/dev/urandom` on
36 Unixes). The other random number generators provided by this module
37 are either known to be insecure (`XorShiftRng`), or are not verified
38 to be secure (`IsaacRng`, `Isaac64Rng` and `StdRng`).
40 *Note*: on Linux, `/dev/random` is more secure than `/dev/urandom`,
41 but it is a blocking RNG, and will wait until it has determined that
42 it has collected enough entropy to fulfill a request for random
43 data. It can be used with the `Rng` trait provided by this module by
44 opening the file and passing it to `reader::ReaderRng`. Since it
45 blocks, `/dev/random` should only be used to retrieve small amounts of
53 let mut rng = rand::task_rng();
54 if rng.gen() { // bool
55 println!("int: {}, uint: {}", rng.gen::<int>(), rng.gen::<uint>())
60 let tuple_ptr = rand::random::<~(f64, char)>();
61 println!("{:?}", tuple_ptr)
65 #![crate_id = "rand#0.10"]
66 #![license = "MIT/ASL2"]
67 #![crate_type = "dylib"]
68 #![crate_type = "rlib"]
69 #![doc(html_logo_url = "http://www.rust-lang.org/logos/rust-logo-128x128-blk.png",
70 html_favicon_url = "http://www.rust-lang.org/favicon.ico",
71 html_root_url = "http://static.rust-lang.org/doc/master")]
73 #![feature(macro_rules, managed_boxes, phase)]
76 #[phase(syntax, link)] extern crate log;
79 use std::kinds::marker;
84 pub use isaac::{IsaacRng, Isaac64Rng};
87 use distributions::{Range, IndependentSample};
88 use distributions::range::SampleRange;
90 pub mod distributions;
97 /// A type that can be randomly generated using an `Rng`.
99 /// Generates a random instance of this type using the specified source of
101 fn rand<R: Rng>(rng: &mut R) -> Self;
104 /// A random number generator.
106 /// Return the next random u32.
108 /// This rarely needs to be called directly, prefer `r.gen()` to
110 // FIXME #7771: Should be implemented in terms of next_u64
111 fn next_u32(&mut self) -> u32;
113 /// Return the next random u64.
115 /// By default this is implemented in terms of `next_u32`. An
116 /// implementation of this trait must provide at least one of
117 /// these two methods. Similarly to `next_u32`, this rarely needs
118 /// to be called directly, prefer `r.gen()` to `r.next_u64()`.
119 fn next_u64(&mut self) -> u64 {
120 (self.next_u32() as u64 << 32) | (self.next_u32() as u64)
123 /// Fill `dest` with random data.
125 /// This has a default implementation in terms of `next_u64` and
126 /// `next_u32`, but should be overridden by implementations that
127 /// offer a more efficient solution than just calling those
128 /// methods repeatedly.
130 /// This method does *not* have a requirement to bear any fixed
131 /// relationship to the other methods, for example, it does *not*
132 /// have to result in the same output as progressively filling
133 /// `dest` with `self.gen::<u8>()`, and any such behaviour should
134 /// not be relied upon.
136 /// This method should guarantee that `dest` is entirely filled
137 /// with new data, and may fail if this is impossible
138 /// (e.g. reading past the end of a file that is being used as the
139 /// source of randomness).
144 /// use rand::{task_rng, Rng};
146 /// let mut v = [0u8, .. 13579];
147 /// task_rng().fill_bytes(v);
148 /// println!("{:?}", v);
150 fn fill_bytes(&mut self, dest: &mut [u8]) {
151 // this could, in theory, be done by transmuting dest to a
152 // [u64], but this is (1) likely to be undefined behaviour for
153 // LLVM, (2) has to be very careful about alignment concerns,
154 // (3) adds more `unsafe` that needs to be checked, (4)
155 // probably doesn't give much performance gain if
156 // optimisations are on.
159 for byte in dest.mut_iter() {
161 // we could micro-optimise here by generating a u32 if
162 // we only need a few more bytes to fill the vector
164 num = self.next_u64();
168 *byte = (num & 0xff) as u8;
174 /// Return a random value of a `Rand` type.
179 /// use rand::{task_rng, Rng};
181 /// let mut rng = task_rng();
182 /// let x: uint = rng.gen();
183 /// println!("{}", x);
184 /// println!("{:?}", rng.gen::<(f64, bool)>());
187 fn gen<T: Rand>(&mut self) -> T {
191 /// Return a random vector of the specified length.
196 /// use rand::{task_rng, Rng};
198 /// let mut rng = task_rng();
199 /// let x: ~[uint] = rng.gen_vec(10);
200 /// println!("{:?}", x);
201 /// println!("{:?}", rng.gen_vec::<(f64, bool)>(5));
203 fn gen_vec<T: Rand>(&mut self, len: uint) -> ~[T] {
204 slice::from_fn(len, |_| self.gen())
207 /// Generate a random value in the range [`low`, `high`). Fails if
210 /// This is a convenience wrapper around
211 /// `distributions::Range`. If this function will be called
212 /// repeatedly with the same arguments, one should use `Range`, as
213 /// that will amortize the computations that allow for perfect
214 /// uniformity, as they only happen on initialization.
219 /// use rand::{task_rng, Rng};
221 /// let mut rng = task_rng();
222 /// let n: uint = rng.gen_range(0u, 10);
223 /// println!("{}", n);
224 /// let m: f64 = rng.gen_range(-40.0, 1.3e5);
225 /// println!("{}", m);
227 fn gen_range<T: Ord + SampleRange>(&mut self, low: T, high: T) -> T {
228 assert!(low < high, "Rng.gen_range called with low >= high");
229 Range::new(low, high).ind_sample(self)
232 /// Return a bool with a 1 in n chance of true
237 /// use rand::{task_rng, Rng};
239 /// let mut rng = task_rng();
240 /// println!("{:b}", rng.gen_weighted_bool(3));
242 fn gen_weighted_bool(&mut self, n: uint) -> bool {
243 n == 0 || self.gen_range(0, n) == 0
246 /// Return a random string of the specified length composed of
252 /// use rand::{task_rng, Rng};
254 /// println!("{}", task_rng().gen_ascii_str(10));
256 fn gen_ascii_str(&mut self, len: uint) -> ~str {
257 static GEN_ASCII_STR_CHARSET: &'static [u8] = bytes!("ABCDEFGHIJKLMNOPQRSTUVWXYZ\
258 abcdefghijklmnopqrstuvwxyz\
260 let mut s = str::with_capacity(len);
261 for _ in range(0, len) {
262 s.push_char(self.choose(GEN_ASCII_STR_CHARSET) as char)
267 /// Choose an item randomly, failing if `values` is empty.
268 fn choose<T: Clone>(&mut self, values: &[T]) -> T {
269 self.choose_option(values).expect("Rng.choose: `values` is empty").clone()
272 /// Choose `Some(&item)` randomly, returning `None` if values is
278 /// use rand::{task_rng, Rng};
280 /// let choices = [1, 2, 4, 8, 16, 32];
281 /// let mut rng = task_rng();
282 /// println!("{:?}", rng.choose_option(choices));
283 /// println!("{:?}", rng.choose_option(choices.slice_to(0)));
285 fn choose_option<'a, T>(&mut self, values: &'a [T]) -> Option<&'a T> {
286 if values.is_empty() {
289 Some(&values[self.gen_range(0u, values.len())])
298 /// use rand::{task_rng, Rng};
300 /// println!("{:?}", task_rng().shuffle(~[1,2,3]));
302 fn shuffle<T>(&mut self, values: ~[T]) -> ~[T] {
308 /// Shuffle a mutable vector in place.
313 /// use rand::{task_rng, Rng};
315 /// let mut rng = task_rng();
316 /// let mut y = [1,2,3];
317 /// rng.shuffle_mut(y);
318 /// println!("{:?}", y);
319 /// rng.shuffle_mut(y);
320 /// println!("{:?}", y);
322 fn shuffle_mut<T>(&mut self, values: &mut [T]) {
323 let mut i = values.len();
325 // invariant: elements with index >= i have been locked in place.
327 // lock element i in place.
328 values.swap(i, self.gen_range(0u, i + 1u));
332 /// Randomly sample up to `n` elements from an iterator.
337 /// use rand::{task_rng, Rng};
339 /// let mut rng = task_rng();
340 /// let sample = rng.sample(range(1, 100), 5);
341 /// println!("{:?}", sample);
343 fn sample<A, T: Iterator<A>>(&mut self, iter: T, n: uint) -> ~[A] {
344 let mut reservoir : ~[A] = slice::with_capacity(n);
345 for (i, elem) in iter.enumerate() {
347 reservoir.push(elem);
351 let k = self.gen_range(0, i + 1);
352 if k < reservoir.len() {
360 /// A random number generator that can be explicitly seeded to produce
361 /// the same stream of randomness multiple times.
362 pub trait SeedableRng<Seed>: Rng {
363 /// Reseed an RNG with the given seed.
368 /// use rand::{Rng, SeedableRng, StdRng};
370 /// let mut rng: StdRng = SeedableRng::from_seed(&[1, 2, 3, 4]);
371 /// println!("{}", rng.gen::<f64>());
372 /// rng.reseed([5, 6, 7, 8]);
373 /// println!("{}", rng.gen::<f64>());
375 fn reseed(&mut self, Seed);
377 /// Create a new RNG with the given seed.
382 /// use rand::{Rng, SeedableRng, StdRng};
384 /// let mut rng: StdRng = SeedableRng::from_seed(&[1, 2, 3, 4]);
385 /// println!("{}", rng.gen::<f64>());
387 fn from_seed(seed: Seed) -> Self;
390 /// Create a random number generator with a default algorithm and seed.
392 /// It returns the strongest `Rng` algorithm currently implemented in
393 /// pure Rust. If you require a specifically seeded `Rng` for
394 /// consistency over time you should pick one algorithm and create the
397 /// This is a very expensive operation as it has to read randomness
398 /// from the operating system and use this in an expensive seeding
399 /// operation. If one does not require high performance generation of
400 /// random numbers, `task_rng` and/or `random` may be more
402 #[deprecated="use `task_rng` or `StdRng::new`"]
403 pub fn rng() -> StdRng {
407 /// The standard RNG. This is designed to be efficient on the current
409 #[cfg(not(target_word_size="64"))]
410 pub struct StdRng { priv rng: IsaacRng }
412 /// The standard RNG. This is designed to be efficient on the current
414 #[cfg(target_word_size="64")]
415 pub struct StdRng { priv rng: Isaac64Rng }
418 /// Create a randomly seeded instance of `StdRng`.
420 /// This is a very expensive operation as it has to read
421 /// randomness from the operating system and use this in an
422 /// expensive seeding operation. If one is only generating a small
423 /// number of random numbers, or doesn't need the utmost speed for
424 /// generating each number, `task_rng` and/or `random` may be more
426 #[cfg(not(target_word_size="64"))]
427 pub fn new() -> StdRng {
428 StdRng { rng: IsaacRng::new() }
430 /// Create a randomly seeded instance of `StdRng`.
432 /// This is a very expensive operation as it has to read
433 /// randomness from the operating system and use this in an
434 /// expensive seeding operation. If one is only generating a small
435 /// number of random numbers, or doesn't need the utmost speed for
436 /// generating each number, `task_rng` and/or `random` may be more
438 #[cfg(target_word_size="64")]
439 pub fn new() -> StdRng {
440 StdRng { rng: Isaac64Rng::new() }
444 impl Rng for StdRng {
446 fn next_u32(&mut self) -> u32 {
451 fn next_u64(&mut self) -> u64 {
456 impl<'a> SeedableRng<&'a [uint]> for StdRng {
457 fn reseed(&mut self, seed: &'a [uint]) {
458 // the internal RNG can just be seeded from the above
460 self.rng.reseed(unsafe {cast::transmute(seed)})
463 fn from_seed(seed: &'a [uint]) -> StdRng {
464 StdRng { rng: SeedableRng::from_seed(unsafe {cast::transmute(seed)}) }
468 /// Create a weak random number generator with a default algorithm and seed.
470 /// It returns the fastest `Rng` algorithm currently available in Rust without
471 /// consideration for cryptography or security. If you require a specifically
472 /// seeded `Rng` for consistency over time you should pick one algorithm and
473 /// create the `Rng` yourself.
475 /// This will read randomness from the operating system to seed the
477 pub fn weak_rng() -> XorShiftRng {
481 /// An Xorshift[1] random number
484 /// The Xorshift algorithm is not suitable for cryptographic purposes
485 /// but is very fast. If you do not know for sure that it fits your
486 /// requirements, use a more secure one such as `IsaacRng` or `OSRng`.
488 /// [1]: Marsaglia, George (July 2003). ["Xorshift
489 /// RNGs"](http://www.jstatsoft.org/v08/i14/paper). *Journal of
490 /// Statistical Software*. Vol. 8 (Issue 14).
491 pub struct XorShiftRng {
498 impl Rng for XorShiftRng {
500 fn next_u32(&mut self) -> u32 {
502 let t = x ^ (x << 11);
507 self.w = w ^ (w >> 19) ^ (t ^ (t >> 8));
512 impl SeedableRng<[u32, .. 4]> for XorShiftRng {
513 /// Reseed an XorShiftRng. This will fail if `seed` is entirely 0.
514 fn reseed(&mut self, seed: [u32, .. 4]) {
515 assert!(!seed.iter().all(|&x| x == 0),
516 "XorShiftRng.reseed called with an all zero seed.");
524 /// Create a new XorShiftRng. This will fail if `seed` is entirely 0.
525 fn from_seed(seed: [u32, .. 4]) -> XorShiftRng {
526 assert!(!seed.iter().all(|&x| x == 0),
527 "XorShiftRng::from_seed called with an all zero seed.");
539 /// Create an xor shift random number generator with a random seed.
540 pub fn new() -> XorShiftRng {
541 let mut s = [0u8, ..16];
543 let mut r = OSRng::new();
546 if !s.iter().all(|x| *x == 0) {
550 let s: [u32, ..4] = unsafe { cast::transmute(s) };
551 SeedableRng::from_seed(s)
555 /// Controls how the task-local RNG is reseeded.
556 struct TaskRngReseeder;
558 impl reseeding::Reseeder<StdRng> for TaskRngReseeder {
559 fn reseed(&mut self, rng: &mut StdRng) {
560 *rng = StdRng::new();
563 static TASK_RNG_RESEED_THRESHOLD: uint = 32_768;
564 type TaskRngInner = reseeding::ReseedingRng<StdRng, TaskRngReseeder>;
565 /// The task-local RNG.
567 // This points into TLS (specifically, it points to the endpoint
568 // of a ~ stored in TLS, to make it robust against TLS moving
569 // things internally) and so this struct cannot be legally
570 // transferred between tasks *and* it's unsafe to deallocate the
571 // RNG other than when a task is finished.
573 // The use of unsafe code here is OK if the invariants above are
574 // satisfied; and it allows us to avoid (unnecessarily) using a
575 // GC'd or RC'd pointer.
576 priv rng: *mut TaskRngInner,
577 priv marker: marker::NoSend,
580 // used to make space in TLS for a random number generator
581 local_data_key!(TASK_RNG_KEY: ~TaskRngInner)
583 /// Retrieve the lazily-initialized task-local random number
584 /// generator, seeded by the system. Intended to be used in method
585 /// chaining style, e.g. `task_rng().gen::<int>()`.
587 /// The RNG provided will reseed itself from the operating system
588 /// after generating a certain amount of randomness.
590 /// The internal RNG used is platform and architecture dependent, even
591 /// if the operating system random number generator is rigged to give
592 /// the same sequence always. If absolute consistency is required,
593 /// explicitly select an RNG, e.g. `IsaacRng` or `Isaac64Rng`.
594 pub fn task_rng() -> TaskRng {
595 local_data::get_mut(TASK_RNG_KEY, |rng| match rng {
597 let mut rng = ~reseeding::ReseedingRng::new(StdRng::new(),
598 TASK_RNG_RESEED_THRESHOLD,
600 let ptr = &mut *rng as *mut TaskRngInner;
602 local_data::set(TASK_RNG_KEY, rng);
604 TaskRng { rng: ptr, marker: marker::NoSend }
606 Some(rng) => TaskRng { rng: &mut **rng, marker: marker::NoSend }
610 impl Rng for TaskRng {
611 fn next_u32(&mut self) -> u32 {
612 unsafe { (*self.rng).next_u32() }
615 fn next_u64(&mut self) -> u64 {
616 unsafe { (*self.rng).next_u64() }
620 fn fill_bytes(&mut self, bytes: &mut [u8]) {
621 unsafe { (*self.rng).fill_bytes(bytes) }
625 /// Generate a random value using the task-local random number
631 /// use rand::random;
634 /// let x = random();
635 /// println!("{}", 2u * x);
637 /// println!("{}", random::<f64>());
641 pub fn random<T: Rand>() -> T {
645 /// A wrapper for generating floating point numbers uniformly in the
646 /// open interval `(0,1)` (not including either endpoint).
648 /// Use `Closed01` for the closed interval `[0,1]`, and the default
649 /// `Rand` implementation for `f32` and `f64` for the half-open
654 /// use rand::{random, Open01};
656 /// let Open01(val) = random::<Open01<f32>>();
657 /// println!("f32 from (0,1): {}", val);
659 pub struct Open01<F>(F);
661 /// A wrapper for generating floating point numbers uniformly in the
662 /// closed interval `[0,1]` (including both endpoints).
664 /// Use `Open01` for the closed interval `(0,1)`, and the default
665 /// `Rand` implementation of `f32` and `f64` for the half-open
670 /// use rand::{random, Closed01};
672 /// let Closed01(val) = random::<Closed01<f32>>();
673 /// println!("f32 from [0,1]: {}", val);
675 pub struct Closed01<F>(F);
680 use super::{Rng, task_rng, random, OSRng, SeedableRng, StdRng};
682 struct ConstRng { i: u64 }
683 impl Rng for ConstRng {
684 fn next_u32(&mut self) -> u32 { self.i as u32 }
685 fn next_u64(&mut self) -> u64 { self.i }
687 // no fill_bytes on purpose
691 fn test_fill_bytes_default() {
692 let mut r = ConstRng { i: 0x11_22_33_44_55_66_77_88 };
694 // check every remainder mod 8, both in small and big vectors.
695 let lengths = [0, 1, 2, 3, 4, 5, 6, 7,
696 80, 81, 82, 83, 84, 85, 86, 87];
697 for &n in lengths.iter() {
698 let mut v = slice::from_elem(n, 0u8);
701 // use this to get nicer error messages.
702 for (i, &byte) in v.iter().enumerate() {
704 fail!("byte {} of {} is zero", i, n)
711 fn test_gen_range() {
712 let mut r = task_rng();
713 for _ in range(0, 1000) {
714 let a = r.gen_range(-3i, 42);
715 assert!(a >= -3 && a < 42);
716 assert_eq!(r.gen_range(0, 1), 0);
717 assert_eq!(r.gen_range(-12, -11), -12);
720 for _ in range(0, 1000) {
721 let a = r.gen_range(10, 42);
722 assert!(a >= 10 && a < 42);
723 assert_eq!(r.gen_range(0, 1), 0);
724 assert_eq!(r.gen_range(3_000_000u, 3_000_001), 3_000_000);
731 fn test_gen_range_fail_int() {
732 let mut r = task_rng();
738 fn test_gen_range_fail_uint() {
739 let mut r = task_rng();
745 let mut r = task_rng();
746 let a = r.gen::<f64>();
747 let b = r.gen::<f64>();
748 debug!("{:?}", (a, b));
752 fn test_gen_weighted_bool() {
753 let mut r = task_rng();
754 assert_eq!(r.gen_weighted_bool(0u), true);
755 assert_eq!(r.gen_weighted_bool(1u), true);
759 fn test_gen_ascii_str() {
760 let mut r = task_rng();
761 debug!("{}", r.gen_ascii_str(10u));
762 debug!("{}", r.gen_ascii_str(10u));
763 debug!("{}", r.gen_ascii_str(10u));
764 assert_eq!(r.gen_ascii_str(0u).len(), 0u);
765 assert_eq!(r.gen_ascii_str(10u).len(), 10u);
766 assert_eq!(r.gen_ascii_str(16u).len(), 16u);
771 let mut r = task_rng();
772 assert_eq!(r.gen_vec::<u8>(0u).len(), 0u);
773 assert_eq!(r.gen_vec::<u8>(10u).len(), 10u);
774 assert_eq!(r.gen_vec::<f64>(16u).len(), 16u);
779 let mut r = task_rng();
780 assert_eq!(r.choose([1, 1, 1]), 1);
784 fn test_choose_option() {
785 let mut r = task_rng();
787 assert!(r.choose_option(v).is_none());
791 assert_eq!(r.choose_option(v), Some(&i));
796 let mut r = task_rng();
797 let empty: ~[int] = ~[];
798 assert_eq!(r.shuffle(~[]), empty);
799 assert_eq!(r.shuffle(~[1, 1, 1]), ~[1, 1, 1]);
804 let mut r = task_rng();
806 assert_eq!(r.shuffle(~[1, 1, 1]), ~[1, 1, 1]);
807 assert_eq!(r.gen_range(0u, 1u), 0u);
812 // not sure how to test this aside from just getting some values
813 let _n : uint = random();
814 let _f : f32 = random();
815 let _o : Option<Option<i8>> = random();
817 (~uint, @int, ~Option<~(@u32, ~(@bool,))>),
818 (u8, i8, u16, i16, u32, i32, u64, i64),
819 (f32, (f64, (f64,)))) = random();
827 let mut r = task_rng();
828 let vals = range(min_val, max_val).collect::<~[int]>();
829 let small_sample = r.sample(vals.iter(), 5);
830 let large_sample = r.sample(vals.iter(), vals.len() + 5);
832 assert_eq!(small_sample.len(), 5);
833 assert_eq!(large_sample.len(), vals.len());
835 assert!(small_sample.iter().all(|e| {
836 **e >= min_val && **e <= max_val
841 fn test_std_rng_seeded() {
842 let s = OSRng::new().gen_vec::<uint>(256);
843 let mut ra: StdRng = SeedableRng::from_seed(s.as_slice());
844 let mut rb: StdRng = SeedableRng::from_seed(s.as_slice());
845 assert_eq!(ra.gen_ascii_str(100u), rb.gen_ascii_str(100u));
849 fn test_std_rng_reseed() {
850 let s = OSRng::new().gen_vec::<uint>(256);
851 let mut r: StdRng = SeedableRng::from_seed(s.as_slice());
852 let string1 = r.gen_ascii_str(100);
856 let string2 = r.gen_ascii_str(100);
857 assert_eq!(string1, string2);
862 static RAND_BENCH_N: u64 = 100;
867 use self::test::BenchHarness;
868 use {XorShiftRng, StdRng, IsaacRng, Isaac64Rng, Rng, RAND_BENCH_N};
869 use std::mem::size_of;
872 fn rand_xorshift(bh: &mut BenchHarness) {
873 let mut rng = XorShiftRng::new();
875 for _ in range(0, RAND_BENCH_N) {
879 bh.bytes = size_of::<uint>() as u64 * RAND_BENCH_N;
883 fn rand_isaac(bh: &mut BenchHarness) {
884 let mut rng = IsaacRng::new();
886 for _ in range(0, RAND_BENCH_N) {
890 bh.bytes = size_of::<uint>() as u64 * RAND_BENCH_N;
894 fn rand_isaac64(bh: &mut BenchHarness) {
895 let mut rng = Isaac64Rng::new();
897 for _ in range(0, RAND_BENCH_N) {
901 bh.bytes = size_of::<uint>() as u64 * RAND_BENCH_N;
905 fn rand_std(bh: &mut BenchHarness) {
906 let mut rng = StdRng::new();
908 for _ in range(0, RAND_BENCH_N) {
912 bh.bytes = size_of::<uint>() as u64 * RAND_BENCH_N;
916 fn rand_shuffle_100(bh: &mut BenchHarness) {
917 let mut rng = XorShiftRng::new();
918 let x : &mut[uint] = [1,..100];