rust/src/libstd/rand/mod.rs

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// Copyright 2013 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.
/*!
Random number generation.
The key functions are `random()` and `Rng::gen()`. These are polymorphic
and so can be used to generate any type that implements `Rand`. Type inference
means that often a simple call to `rand::random()` or `rng.gen()` will
suffice, but sometimes an annotation is required, e.g. `rand::random::<f64>()`.
See the `distributions` submodule for sampling random numbers from
distributions like normal and exponential.
# Task-local RNG
There is built-in support for a RNG associated with each task stored
in task-local storage. This RNG can be accessed via `task_rng`, or
used implicitly via `random`. This RNG is normally randomly seeded
from an operating-system source of randomness, e.g. `/dev/urandom` on
Unix systems, and will automatically reseed itself from this source
after generating 32 KiB of random data.
# Cryptographic security
An application that requires random numbers for cryptographic purposes
should prefer `OSRng`, which reads randomness from one of the source
that the operating system provides (e.g. `/dev/urandom` on
Unixes). The other random number generators provided by this module
are either known to be insecure (`XorShiftRng`), or are not verified
to be secure (`IsaacRng`, `Isaac64Rng` and `StdRng`).
*Note*: on Linux, `/dev/random` is more secure than `/dev/urandom`,
but it is a blocking RNG, and will wait until it has determined that
it has collected enough entropy to fulfill a request for random
data. It can be used with the `Rng` trait provided by this module by
opening the file and passing it to `reader::ReaderRng`. Since it
blocks, `/dev/random` should only be used to retrieve small amounts of
randomness.
# Examples
```rust
use std::rand;
use std::rand::Rng;
fn main() {
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let mut rng = rand::rng();
if rng.gen() { // bool
println!("int: {}, uint: {}", rng.gen::<int>(), rng.gen::<uint>())
}
}
```
```rust
use std::rand;
fn main () {
let tuple_ptr = rand::random::<~(f64, char)>();
println!(tuple_ptr)
}
```
*/
use mem::size_of;
use unstable::raw::Slice;
use cast;
use cmp::Ord;
use container::Container;
use iter::{Iterator, range};
use local_data;
use prelude::*;
use str;
use vec;
pub use self::isaac::{IsaacRng, Isaac64Rng};
pub use self::os::OSRng;
use self::distributions::{Range, IndependentSample};
use self::distributions::range::SampleRange;
pub mod distributions;
pub mod isaac;
pub mod os;
pub mod reader;
pub mod reseeding;
mod rand_impls;
/// A type that can be randomly generated using an Rng
pub trait Rand {
/// Generates a random instance of this type using the specified source of
/// randomness
fn rand<R: Rng>(rng: &mut R) -> Self;
}
/// A value with a particular weight compared to other values
pub struct Weighted<T> {
/// The numerical weight of this item
weight: uint,
/// The actual item which is being weighted
item: T,
}
/// A random number generator
pub trait Rng {
/// Return the next random u32. This rarely needs to be called
/// directly, prefer `r.gen()` to `r.next_u32()`.
///
// FIXME #7771: Should be implemented in terms of next_u64
fn next_u32(&mut self) -> u32;
/// Return the next random u64. This rarely needs to be called
/// directly, prefer `r.gen()` to `r.next_u64()`.
///
/// By default this is implemented in terms of `next_u32`. An
/// implementation of this trait must provide at least one of
/// these two methods.
fn next_u64(&mut self) -> u64 {
(self.next_u32() as u64 << 32) | (self.next_u32() as u64)
}
/// Fill `dest` with random data.
///
/// This has a default implementation in terms of `next_u64` and
/// `next_u32`, but should be overriden by implementations that
/// offer a more efficient solution than just calling those
/// methods repeatedly.
///
/// This method does *not* have a requirement to bear any fixed
/// relationship to the other methods, for example, it does *not*
/// have to result in the same output as progressively filling
/// `dest` with `self.gen::<u8>()`, and any such behaviour should
/// not be relied upon.
///
/// This method should guarantee that `dest` is entirely filled
/// with new data, and may fail if this is impossible
/// (e.g. reading past the end of a file that is being used as the
/// source of randomness).
///
/// # Example
///
/// ```rust
/// use std::rand::{task_rng, Rng};
///
/// fn main() {
/// let mut v = [0u8, .. 13579];
/// task_rng().fill_bytes(v);
/// println!("{:?}", v);
/// }
/// ```
fn fill_bytes(&mut self, dest: &mut [u8]) {
let mut slice: Slice<u64> = unsafe { cast::transmute_copy(&dest) };
slice.len /= size_of::<u64>();
let as_u64: &mut [u64] = unsafe { cast::transmute(slice) };
for dest in as_u64.mut_iter() {
*dest = self.next_u64();
}
// the above will have filled up the vector as much as
// possible in multiples of 8 bytes.
let mut remaining = dest.len() % 8;
// space for a u32
if remaining >= 4 {
let mut slice: Slice<u32> = unsafe { cast::transmute_copy(&dest) };
slice.len /= size_of::<u32>();
let as_u32: &mut [u32] = unsafe { cast::transmute(slice) };
as_u32[as_u32.len() - 1] = self.next_u32();
remaining -= 4;
}
// exactly filled
if remaining == 0 { return }
// now we know we've either got 1, 2 or 3 spots to go,
// i.e. exactly one u32 is enough.
let rand = self.next_u32();
let remaining_index = dest.len() - remaining;
match dest.mut_slice_from(remaining_index) {
[ref mut a] => {
*a = rand as u8;
}
[ref mut a, ref mut b] => {
*a = rand as u8;
*b = (rand >> 8) as u8;
}
[ref mut a, ref mut b, ref mut c] => {
*a = rand as u8;
*b = (rand >> 8) as u8;
*c = (rand >> 16) as u8;
}
_ => fail!("Rng.fill_bytes: the impossible occurred: remaining != 1, 2 or 3")
}
}
/// Return a random value of a Rand type.
///
/// # Example
///
/// ```rust
/// use std::rand;
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/// use std::rand::Rng;
///
/// fn main() {
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/// let mut rng = rand::task_rng();
/// let x: uint = rng.gen();
/// println!("{}", x);
/// println!("{:?}", rng.gen::<(f64, bool)>());
/// }
/// ```
#[inline(always)]
fn gen<T: Rand>(&mut self) -> T {
Rand::rand(self)
}
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/// Return a random vector of the specified length.
///
/// # Example
///
/// ```rust
/// use std::rand;
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/// use std::rand::Rng;
///
/// fn main() {
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/// let mut rng = rand::task_rng();
/// let x: ~[uint] = rng.gen_vec(10);
/// println!("{:?}", x);
/// println!("{:?}", rng.gen_vec::<(f64, bool)>(5));
/// }
/// ```
fn gen_vec<T: Rand>(&mut self, len: uint) -> ~[T] {
vec::from_fn(len, |_| self.gen())
}
/// Generate a random value in the range [`low`, `high`). Fails if
/// `low >= high`.
///
/// This is a convenience wrapper around
/// `distributions::Range`. If this function will be called
/// repeatedly with the same arguments, one should use `Range`, as
/// that will amortize the computations that allow for perfect
/// uniformity, as they only happen on initialization.
///
/// # Example
///
/// ```rust
/// use std::rand;
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/// use std::rand::Rng;
///
/// fn main() {
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/// let mut rng = rand::task_rng();
/// let n: uint = rng.gen_range(0u, 10);
/// println!("{}", n);
/// let m: float = rng.gen_range(-40.0, 1.3e5);
/// println!("{}", m);
/// }
/// ```
fn gen_range<T: Ord + SampleRange>(&mut self, low: T, high: T) -> T {
assert!(low < high, "Rng.gen_range called with low >= high");
Range::new(low, high).ind_sample(self)
}
/// Return a bool with a 1 in n chance of true
///
/// # Example
///
/// ```rust
/// use std::rand;
/// use std::rand::Rng;
///
/// fn main() {
/// let mut rng = rand::rng();
/// println!("{:b}", rng.gen_weighted_bool(3));
/// }
/// ```
fn gen_weighted_bool(&mut self, n: uint) -> bool {
n == 0 || self.gen_range(0, n) == 0
}
/// Return a random string of the specified length composed of
/// A-Z,a-z,0-9.
///
/// # Example
///
/// ```rust
/// use std::rand;
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/// use std::rand::Rng;
///
/// fn main() {
/// println(rand::task_rng().gen_ascii_str(10));
/// }
/// ```
fn gen_ascii_str(&mut self, len: uint) -> ~str {
static GEN_ASCII_STR_CHARSET: &'static [u8] = bytes!("ABCDEFGHIJKLMNOPQRSTUVWXYZ\
abcdefghijklmnopqrstuvwxyz\
0123456789");
let mut s = str::with_capacity(len);
for _ in range(0, len) {
s.push_char(self.choose(GEN_ASCII_STR_CHARSET) as char)
}
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s
}
/// Choose an item randomly, failing if `values` is empty.
fn choose<T: Clone>(&mut self, values: &[T]) -> T {
self.choose_option(values).expect("Rng.choose: `values` is empty").clone()
}
/// Choose `Some(&item)` randomly, returning `None` if values is
/// empty.
///
/// # Example
///
/// ```rust
/// use std::rand;
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/// use std::rand::Rng;
///
/// fn main() {
/// println!("{:?}", rand::task_rng().choose_option([1,2,4,8,16,32]));
/// println!("{:?}", rand::task_rng().choose_option([]));
/// }
/// ```
fn choose_option<'a, T>(&mut self, values: &'a [T]) -> Option<&'a T> {
if values.is_empty() {
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None
} else {
Some(&values[self.gen_range(0u, values.len())])
}
}
/// Choose an item respecting the relative weights, failing if the sum of
/// the weights is 0
///
/// # Example
///
/// ```rust
/// use std::rand;
/// use std::rand::Rng;
///
/// fn main() {
/// let mut rng = rand::rng();
/// let x = [rand::Weighted {weight: 4, item: 'a'},
/// rand::Weighted {weight: 2, item: 'b'},
/// rand::Weighted {weight: 2, item: 'c'}];
/// println!("{}", rng.choose_weighted(x));
/// }
/// ```
fn choose_weighted<T:Clone>(&mut self, v: &[Weighted<T>]) -> T {
self.choose_weighted_option(v).expect("Rng.choose_weighted: total weight is 0")
}
/// Choose Some(item) respecting the relative weights, returning none if
/// the sum of the weights is 0
///
/// # Example
///
/// ```rust
/// use std::rand;
/// use std::rand::Rng;
///
/// fn main() {
/// let mut rng = rand::rng();
/// let x = [rand::Weighted {weight: 4, item: 'a'},
/// rand::Weighted {weight: 2, item: 'b'},
/// rand::Weighted {weight: 2, item: 'c'}];
/// println!("{:?}", rng.choose_weighted_option(x));
/// }
/// ```
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fn choose_weighted_option<T:Clone>(&mut self, v: &[Weighted<T>])
-> Option<T> {
let mut total = 0u;
for item in v.iter() {
total += item.weight;
}
if total == 0u {
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return None;
}
let chosen = self.gen_range(0u, total);
let mut so_far = 0u;
for item in v.iter() {
so_far += item.weight;
if so_far > chosen {
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return Some(item.item.clone());
}
}
unreachable!();
}
/// Return a vec containing copies of the items, in order, where
/// the weight of the item determines how many copies there are
///
/// # Example
///
/// ```rust
/// use std::rand;
/// use std::rand::Rng;
///
/// fn main() {
/// let mut rng = rand::rng();
/// let x = [rand::Weighted {weight: 4, item: 'a'},
/// rand::Weighted {weight: 2, item: 'b'},
/// rand::Weighted {weight: 2, item: 'c'}];
/// println!("{}", rng.weighted_vec(x));
/// }
/// ```
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fn weighted_vec<T:Clone>(&mut self, v: &[Weighted<T>]) -> ~[T] {
let mut r = ~[];
for item in v.iter() {
for _ in range(0u, item.weight) {
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r.push(item.item.clone());
}
}
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r
}
/// Shuffle a vec
///
/// # Example
///
/// ```rust
/// use std::rand;
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/// use std::rand::Rng;
///
/// fn main() {
/// println!("{:?}", rand::task_rng().shuffle(~[1,2,3]));
/// }
/// ```
fn shuffle<T>(&mut self, values: ~[T]) -> ~[T] {
let mut v = values;
self.shuffle_mut(v);
v
}
/// Shuffle a mutable vector in place.
///
/// # Example
///
/// ```rust
/// use std::rand;
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/// use std::rand::Rng;
///
/// fn main() {
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/// let mut rng = rand::task_rng();
/// let mut y = [1,2,3];
/// rng.shuffle_mut(y);
/// println!("{:?}", y);
/// rng.shuffle_mut(y);
/// println!("{:?}", y);
/// }
/// ```
fn shuffle_mut<T>(&mut self, values: &mut [T]) {
let mut i = values.len();
while i >= 2u {
// invariant: elements with index >= i have been locked in place.
i -= 1u;
// lock element i in place.
values.swap(i, self.gen_range(0u, i + 1u));
}
}
/// Randomly sample up to `n` elements from an iterator.
///
/// # Example
///
/// ```rust
/// use std::rand;
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/// use std::rand::Rng;
///
/// fn main() {
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/// let mut rng = rand::task_rng();
/// let sample = rng.sample(range(1, 100), 5);
/// println!("{:?}", sample);
/// }
/// ```
fn sample<A, T: Iterator<A>>(&mut self, iter: T, n: uint) -> ~[A] {
let mut reservoir : ~[A] = vec::with_capacity(n);
for (i, elem) in iter.enumerate() {
if i < n {
reservoir.push(elem);
continue
}
let k = self.gen_range(0, i + 1);
if k < reservoir.len() {
reservoir[k] = elem
}
}
reservoir
}
}
/// A random number generator that can be explicitly seeded to produce
/// the same stream of randomness multiple times.
pub trait SeedableRng<Seed>: Rng {
/// Reseed an RNG with the given seed.
///
/// # Example
///
/// ```rust
/// use std::rand;
/// use std::rand::Rng;
///
/// fn main() {
/// let mut rng: rand::StdRng = rand::SeedableRng::from_seed(&[1, 2, 3, 4]);
/// println!("{}", rng.gen::<f64>());
/// rng.reseed([5, 6, 7, 8]);
/// println!("{}", rng.gen::<f64>());
/// }
/// ```
fn reseed(&mut self, Seed);
/// Create a new RNG with the given seed.
///
/// # Example
///
/// ```rust
/// use std::rand;
/// use std::rand::Rng;
///
/// fn main() {
/// let mut rng: rand::StdRng = rand::SeedableRng::from_seed(&[1, 2, 3, 4]);
/// println!("{}", rng.gen::<f64>());
/// }
/// ```
fn from_seed(seed: Seed) -> Self;
}
/// Create a random number generator with a default algorithm and seed.
///
/// It returns the strongest `Rng` algorithm currently implemented in
/// pure Rust. If you require a specifically seeded `Rng` for
/// consistency over time you should pick one algorithm and create the
/// `Rng` yourself.
///
/// This is a very expensive operation as it has to read randomness
/// from the operating system and use this in an expensive seeding
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/// operation. If one does not require high performance generation of
/// random numbers, `task_rng` and/or `random` may be more
/// appropriate.
pub fn rng() -> StdRng {
StdRng::new()
}
/// The standard RNG. This is designed to be efficient on the current
/// platform.
#[cfg(not(target_word_size="64"))]
pub struct StdRng { priv rng: IsaacRng }
/// The standard RNG. This is designed to be efficient on the current
/// platform.
#[cfg(target_word_size="64")]
pub struct StdRng { priv rng: Isaac64Rng }
impl StdRng {
/// Create a randomly seeded instance of `StdRng`. This reads
/// randomness from the OS to seed the PRNG.
#[cfg(not(target_word_size="64"))]
pub fn new() -> StdRng {
StdRng { rng: IsaacRng::new() }
}
/// Create a randomly seeded instance of `StdRng`. This reads
/// randomness from the OS to seed the PRNG.
#[cfg(target_word_size="64")]
pub fn new() -> StdRng {
StdRng { rng: Isaac64Rng::new() }
}
}
impl Rng for StdRng {
#[inline]
fn next_u32(&mut self) -> u32 {
self.rng.next_u32()
}
#[inline]
fn next_u64(&mut self) -> u64 {
self.rng.next_u64()
}
}
impl<'self> SeedableRng<&'self [uint]> for StdRng {
fn reseed(&mut self, seed: &'self [uint]) {
// the internal RNG can just be seeded from the above
// randomness.
self.rng.reseed(unsafe {cast::transmute(seed)})
}
fn from_seed(seed: &'self [uint]) -> StdRng {
StdRng { rng: SeedableRng::from_seed(unsafe {cast::transmute(seed)}) }
}
}
/// Create a weak random number generator with a default algorithm and seed.
///
/// It returns the fastest `Rng` algorithm currently available in Rust without
/// consideration for cryptography or security. If you require a specifically
/// seeded `Rng` for consistency over time you should pick one algorithm and
/// create the `Rng` yourself.
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///
/// This will read randomness from the operating system to seed the
/// generator.
pub fn weak_rng() -> XorShiftRng {
XorShiftRng::new()
}
/// 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).
pub struct XorShiftRng {
priv x: u32,
priv y: u32,
priv z: u32,
priv w: u32,
}
impl Rng for XorShiftRng {
#[inline]
fn next_u32(&mut self) -> u32 {
let x = self.x;
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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
}
}
impl SeedableRng<[u32, .. 4]> for XorShiftRng {
/// Reseed an XorShiftRng. This will fail 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 = seed[0];
self.y = seed[1];
self.z = seed[2];
self.w = seed[3];
}
/// Create a new XorShiftRng. This will fail 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: seed[0],
y: seed[1],
z: seed[2],
w: seed[3]
}
}
}
impl XorShiftRng {
/// Create an xor shift random number generator with a random seed.
pub fn new() -> XorShiftRng {
let mut s = [0u8, ..16];
loop {
let mut r = OSRng::new();
r.fill_bytes(s);
if !s.iter().all(|x| *x == 0) {
break;
}
}
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let s: [u32, ..4] = unsafe { cast::transmute(s) };
SeedableRng::from_seed(s)
}
}
/// Controls how the task-local RNG is reseeded.
struct TaskRngReseeder;
impl reseeding::Reseeder<StdRng> for TaskRngReseeder {
fn reseed(&mut self, rng: &mut StdRng) {
*rng = StdRng::new();
}
}
static TASK_RNG_RESEED_THRESHOLD: uint = 32_768;
/// The task-local RNG.
pub type TaskRng = reseeding::ReseedingRng<StdRng, TaskRngReseeder>;
// used to make space in TLS for a random number generator
local_data_key!(TASK_RNG_KEY: @mut TaskRng)
/// Retrieve the lazily-initialized task-local random number
/// generator, seeded by the system. Intended to be used in method
/// chaining style, e.g. `task_rng().gen::<int>()`.
///
/// The RNG provided will reseed itself from the operating system
/// after generating a certain amount of randomness.
///
/// The internal RNG used is platform and architecture dependent, even
/// if the operating system random number generator is rigged to give
/// the same sequence always. If absolute consistency is required,
/// explicitly select an RNG, e.g. `IsaacRng` or `Isaac64Rng`.
pub fn task_rng() -> @mut TaskRng {
let r = local_data::get(TASK_RNG_KEY, |k| k.map(|k| *k));
match r {
None => {
let rng = @mut reseeding::ReseedingRng::new(StdRng::new(),
TASK_RNG_RESEED_THRESHOLD,
TaskRngReseeder);
local_data::set(TASK_RNG_KEY, rng);
rng
}
Some(rng) => rng
}
}
// Allow direct chaining with `task_rng`
impl<R: Rng> Rng for @mut R {
#[inline]
fn next_u32(&mut self) -> u32 {
(**self).next_u32()
}
#[inline]
fn next_u64(&mut self) -> u64 {
(**self).next_u64()
}
#[inline]
fn fill_bytes(&mut self, bytes: &mut [u8]) {
(**self).fill_bytes(bytes);
}
}
/// Generate a random value using the task-local random number
/// generator.
///
/// # Example
///
/// ```rust
/// use std::rand::random;
///
/// fn main() {
/// if random() {
/// let x = random();
/// println!("{}", 2u * x);
/// } else {
/// println!("{}", random::<f64>());
/// }
/// }
/// ```
#[inline]
pub fn random<T: Rand>() -> T {
task_rng().gen()
}
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#[cfg(test)]
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mod test {
use iter::{Iterator, range};
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use option::{Option, Some};
use super::*;
#[test]
fn test_fill_bytes_default() {
let mut r = weak_rng();
let mut v = [0u8, .. 100];
r.fill_bytes(v);
}
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#[test]
fn test_gen_range() {
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let mut r = rng();
for _ in range(0, 1000) {
let a = r.gen_range(-3i, 42);
assert!(a >= -3 && a < 42);
assert_eq!(r.gen_range(0, 1), 0);
assert_eq!(r.gen_range(-12, -11), -12);
}
for _ in range(0, 1000) {
let a = r.gen_range(10, 42);
assert!(a >= 10 && a < 42);
assert_eq!(r.gen_range(0, 1), 0);
assert_eq!(r.gen_range(3_000_000u, 3_000_001), 3_000_000);
}
}
#[test]
#[should_fail]
fn test_gen_range_fail_int() {
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let mut r = rng();
r.gen_range(5i, -2);
}
#[test]
#[should_fail]
fn test_gen_range_fail_uint() {
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let mut r = rng();
r.gen_range(5u, 2u);
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}
#[test]
fn test_gen_f64() {
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let mut r = rng();
let a = r.gen::<f64>();
let b = r.gen::<f64>();
debug!("{:?}", (a, b));
}
#[test]
fn test_gen_weighted_bool() {
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let mut r = rng();
assert_eq!(r.gen_weighted_bool(0u), true);
assert_eq!(r.gen_weighted_bool(1u), true);
}
#[test]
fn test_gen_ascii_str() {
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let mut r = rng();
debug!("{}", r.gen_ascii_str(10u));
debug!("{}", r.gen_ascii_str(10u));
debug!("{}", r.gen_ascii_str(10u));
assert_eq!(r.gen_ascii_str(0u).len(), 0u);
assert_eq!(r.gen_ascii_str(10u).len(), 10u);
assert_eq!(r.gen_ascii_str(16u).len(), 16u);
}
#[test]
fn test_gen_vec() {
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let mut r = rng();
assert_eq!(r.gen_vec::<u8>(0u).len(), 0u);
assert_eq!(r.gen_vec::<u8>(10u).len(), 10u);
assert_eq!(r.gen_vec::<f64>(16u).len(), 16u);
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}
#[test]
fn test_choose() {
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let mut r = rng();
assert_eq!(r.choose([1, 1, 1]), 1);
}
#[test]
fn test_choose_option() {
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let mut r = rng();
let v: &[int] = &[];
assert!(r.choose_option(v).is_none());
let i = 1;
let v = [1,1,1];
assert_eq!(r.choose_option(v), Some(&i));
}
#[test]
fn test_choose_weighted() {
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let mut r = rng();
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assert!(r.choose_weighted([
Weighted { weight: 1u, item: 42 },
]) == 42);
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assert!(r.choose_weighted([
Weighted { weight: 0u, item: 42 },
Weighted { weight: 1u, item: 43 },
]) == 43);
}
#[test]
fn test_choose_weighted_option() {
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let mut r = rng();
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assert!(r.choose_weighted_option([
Weighted { weight: 1u, item: 42 },
]) == Some(42));
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assert!(r.choose_weighted_option([
Weighted { weight: 0u, item: 42 },
Weighted { weight: 1u, item: 43 },
]) == Some(43));
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let v: Option<int> = r.choose_weighted_option([]);
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assert!(v.is_none());
}
#[test]
fn test_weighted_vec() {
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let mut r = rng();
let empty: ~[int] = ~[];
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assert_eq!(r.weighted_vec([]), empty);
assert!(r.weighted_vec([
Weighted { weight: 0u, item: 3u },
Weighted { weight: 1u, item: 2u },
Weighted { weight: 2u, item: 1u },
]) == ~[2u, 1u, 1u]);
}
#[test]
fn test_shuffle() {
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let mut r = rng();
let empty: ~[int] = ~[];
assert_eq!(r.shuffle(~[]), empty);
assert_eq!(r.shuffle(~[1, 1, 1]), ~[1, 1, 1]);
}
#[test]
fn test_task_rng() {
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let mut r = task_rng();
r.gen::<int>();
assert_eq!(r.shuffle(~[1, 1, 1]), ~[1, 1, 1]);
assert_eq!(r.gen_range(0u, 1u), 0u);
}
#[test]
fn test_random() {
// not sure how to test this aside from just getting some values
let _n : uint = random();
let _f : f32 = random();
let _o : Option<Option<i8>> = random();
let _many : ((),
(~uint, @int, ~Option<~(@u32, ~(@bool,))>),
(u8, i8, u16, i16, u32, i32, u64, i64),
(f32, (f64, (f64,)))) = random();
}
#[test]
fn test_sample() {
let MIN_VAL = 1;
let MAX_VAL = 100;
let mut r = rng();
let vals = range(MIN_VAL, MAX_VAL).to_owned_vec();
let small_sample = r.sample(vals.iter(), 5);
let large_sample = r.sample(vals.iter(), vals.len() + 5);
assert_eq!(small_sample.len(), 5);
assert_eq!(large_sample.len(), vals.len());
assert!(small_sample.iter().all(|e| {
**e >= MIN_VAL && **e <= MAX_VAL
}));
}
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#[test]
fn test_std_rng_seeded() {
let s = OSRng::new().gen_vec::<uint>(256);
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let mut ra: StdRng = SeedableRng::from_seed(s.as_slice());
let mut rb: StdRng = SeedableRng::from_seed(s.as_slice());
assert_eq!(ra.gen_ascii_str(100u), rb.gen_ascii_str(100u));
}
#[test]
fn test_std_rng_reseed() {
let s = OSRng::new().gen_vec::<uint>(256);
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let mut r: StdRng = SeedableRng::from_seed(s.as_slice());
let string1 = r.gen_ascii_str(100);
r.reseed(s);
let string2 = r.gen_ascii_str(100);
assert_eq!(string1, string2);
}
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}
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#[cfg(test)]
mod bench {
use extra::test::BenchHarness;
use rand::*;
use mem::size_of;
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#[bench]
fn rand_xorshift(bh: &mut BenchHarness) {
let mut rng = XorShiftRng::new();
do bh.iter {
rng.gen::<uint>();
}
bh.bytes = size_of::<uint>() as u64;
}
#[bench]
fn rand_isaac(bh: &mut BenchHarness) {
let mut rng = IsaacRng::new();
do bh.iter {
rng.gen::<uint>();
}
bh.bytes = size_of::<uint>() as u64;
}
#[bench]
fn rand_isaac64(bh: &mut BenchHarness) {
let mut rng = Isaac64Rng::new();
do bh.iter {
rng.gen::<uint>();
}
bh.bytes = size_of::<uint>() as u64;
}
#[bench]
fn rand_std(bh: &mut BenchHarness) {
let mut rng = StdRng::new();
do bh.iter {
rng.gen::<uint>();
}
bh.bytes = size_of::<uint>() as u64;
}
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#[bench]
fn rand_shuffle_100(bh: &mut BenchHarness) {
let mut rng = XorShiftRng::new();
let x : &mut[uint] = [1,..100];
do bh.iter {
rng.shuffle_mut(x);
}
}
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}