mod.rs

// 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.

/*!
Utilities for 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() {
    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 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 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 overridden 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]) {
        // this could, in theory, be done by transmuting dest to a
        // [u64], but this is (1) likely to be undefined behaviour for
        // LLVM, (2) has to be very careful about alignment concerns,
        // (3) adds more `unsafe` that needs to be checked, (4)
        // probably doesn't give much performance gain if
        // optimisations are on.
        let mut count = 0;
        let mut num = 0;
        for byte in dest.mut_iter() {
            if count == 0 {
                // we could micro-optimise here by generating a u32 if
                // we only need a few more bytes to fill the vector
                // (i.e. at most 4).
                num = self.next_u64();
                count = 8;
            }

            *byte = (num & 0xff) as u8;
            num >>= 8;
            count -= 1;
        }
    }

    /// Return a random value of a Rand type.
    ///
    /// # Example
    ///
    /// ```rust
    /// use std::rand;
    /// use std::rand::Rng;
    ///
    /// fn main() {
    ///    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)
    }

    /// Return a random vector of the specified length.
    ///
    /// # Example
    ///
    /// ```rust
    /// use std::rand;
    /// use std::rand::Rng;
    ///
    /// fn main() {
    ///    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;
    /// use std::rand::Rng;
    ///
    /// fn main() {
    ///    let mut rng = rand::task_rng();
    ///    let n: uint = rng.gen_range(0u, 10);
    ///    println!("{}", n);
    ///    let m: f64 = 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;
    /// 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)
        }
        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;
    /// use std::rand::Rng;
    ///
    /// fn main() {
    ///     let choices = [1, 2, 4, 8, 16, 32];
    ///     let mut rng = rand::task_rng();
    ///     println!("{:?}", rng.choose_option(choices));
    ///     println!("{:?}", rng.choose_option(choices.slice_to(0)));
    /// }
    /// ```
    fn choose_option<'a, T>(&mut self, values: &'a [T]) -> Option<&'a T> {
        if values.is_empty() {
            None
        } else {
            Some(&values[self.gen_range(0u, values.len())])
        }
    }

    /// Shuffle a vec
    ///
    /// # Example
    ///
    /// ```rust
    /// use std::rand;
    /// 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;
    /// use std::rand::Rng;
    ///
    /// fn main() {
    ///    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;
    /// use std::rand::Rng;
    ///
    /// fn main() {
    ///    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::{Rng, SeedableRng, StdRng};
    ///
    /// fn main() {
    ///     let mut rng: StdRng = 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
/// 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<'a> SeedableRng<&'a [uint]> for StdRng {
    fn reseed(&mut self, seed: &'a [uint]) {
        // the internal RNG can just be seeded from the above
        // randomness.
        self.rng.reseed(unsafe {cast::transmute(seed)})
    }

    fn from_seed(seed: &'a [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.
///
/// 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;
        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;
            }
        }
        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;
type TaskRngInner = reseeding::ReseedingRng<StdRng, TaskRngReseeder>;
/// The task-local RNG.
#[no_send]
pub struct TaskRng {
    // This points into TLS (specifically, it points to the endpoint
    // of a ~ stored in TLS, to make it robust against TLS moving
    // things internally) and so this struct cannot be legally
    // transferred between tasks *and* it's unsafe to deallocate the
    // RNG other than when a task is finished.
    //
    // The use of unsafe code here is OK if the invariants above are
    // satisfied; and it allows us to avoid (unnecessarily) using a
    // GC'd or RC'd pointer.
    priv rng: *mut TaskRngInner
}

// used to make space in TLS for a random number generator
local_data_key!(TASK_RNG_KEY: ~TaskRngInner)

/// 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() -> TaskRng {
    local_data::get_mut(TASK_RNG_KEY, |rng| match rng {
        None => {
            let mut rng = ~reseeding::ReseedingRng::new(StdRng::new(),
                                                        TASK_RNG_RESEED_THRESHOLD,
                                                        TaskRngReseeder);
            let ptr = &mut *rng as *mut TaskRngInner;

            local_data::set(TASK_RNG_KEY, rng);

            TaskRng { rng: ptr }
        }
        Some(rng) => TaskRng { rng: &mut **rng }
    })
}

impl Rng for TaskRng {
    fn next_u32(&mut self) -> u32 {
        unsafe { (*self.rng).next_u32() }
    }

    fn next_u64(&mut self) -> u64 {
        unsafe { (*self.rng).next_u64() }
    }

    #[inline]
    fn fill_bytes(&mut self, bytes: &mut [u8]) {
        unsafe { (*self.rng).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()
}

/// A wrapper for generating floating point numbers uniformly in the
/// open interval `(0,1)` (not including either endpoint).
///
/// Use `Closed01` for the closed interval `[0,1]`, and the default
/// `Rand` implementation for `f32` and `f64` for the half-open
/// `[0,1)`.
///
/// # Example
/// ```rust
/// use std::rand::{random, Open01};
///
/// fn main() {
///     println!("f32 from (0,1): {}", *random::<Open01<f32>>());
///
///     let x: Open01<f64> = random();
///     println!("f64 from (0,1): {}", *x);
/// }
/// ```
pub struct Open01<F>(F);

/// A wrapper for generating floating point numbers uniformly in the
/// closed interval `[0,1]` (including both endpoints).
///
/// Use `Open01` for the closed interval `(0,1)`, and the default
/// `Rand` implementation of `f32` and `f64` for the half-open
/// `[0,1)`.
///
/// # Example
/// ```rust
/// use std::rand::{random, Closed01};
///
/// fn main() {
///     println!("f32 from [0,1]: {}", *random::<Closed01<f32>>());
///
///     let x: Closed01<f64> = random();
///     println!("f64 from [0,1]: {}", *x);
/// }
/// ```
pub struct Closed01<F>(F);

#[cfg(test)]
mod test {
    use iter::{Iterator, range};
    use option::{Option, Some};
    use vec;
    use super::*;

    struct ConstRng { i: u64 }
    impl Rng for ConstRng {
        fn next_u32(&mut self) -> u32 { self.i as u32 }
        fn next_u64(&mut self) -> u64 { self.i }

        // no fill_bytes on purpose
    }

    #[test]
    fn test_fill_bytes_default() {
        let mut r = ConstRng { i: 0x11_22_33_44_55_66_77_88 };

        // check every remainder mod 8, both in small and big vectors.
        let lengths = [0, 1, 2, 3, 4, 5, 6, 7,
                       80, 81, 82, 83, 84, 85, 86, 87];
        for &n in lengths.iter() {
            let mut v = vec::from_elem(n, 0u8);
            r.fill_bytes(v);

            // use this to get nicer error messages.
            for (i, &byte) in v.iter().enumerate() {
                if byte == 0 {
                    fail!("byte {} of {} is zero", i, n)
                }
            }
        }
    }

    #[test]
    fn test_gen_range() {
        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() {
        let mut r = rng();
        r.gen_range(5i, -2);
    }

    #[test]
    #[should_fail]
    fn test_gen_range_fail_uint() {
        let mut r = rng();
        r.gen_range(5u, 2u);
    }

    #[test]
    fn test_gen_f64() {
        let mut r = rng();
        let a = r.gen::<f64>();
        let b = r.gen::<f64>();
        debug!("{:?}", (a, b));
    }

    #[test]
    fn test_gen_weighted_bool() {
        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() {
        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() {
        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);
    }

    #[test]
    fn test_choose() {
        let mut r = rng();
        assert_eq!(r.choose([1, 1, 1]), 1);
    }

    #[test]
    fn test_choose_option() {
        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_shuffle() {
        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() {
        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
        }));
    }

    #[test]
    fn test_std_rng_seeded() {
        let s = OSRng::new().gen_vec::<uint>(256);
        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);
        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);
    }
}

#[cfg(test)]
static RAND_BENCH_N: u64 = 100;

#[cfg(test)]
mod bench {
    use extra::test::BenchHarness;
    use rand::{XorShiftRng, StdRng, IsaacRng, Isaac64Rng, Rng, RAND_BENCH_N};
    use mem::size_of;
    use iter::range;
    use option::{Some, None};

    #[bench]
    fn rand_xorshift(bh: &mut BenchHarness) {
        let mut rng = XorShiftRng::new();
        bh.iter(|| {
            for _ in range(0, RAND_BENCH_N) {
                rng.gen::<uint>();
            }
        });
        bh.bytes = size_of::<uint>() as u64 * RAND_BENCH_N;
    }

    #[bench]
    fn rand_isaac(bh: &mut BenchHarness) {
        let mut rng = IsaacRng::new();
        bh.iter(|| {
            for _ in range(0, RAND_BENCH_N) {
                rng.gen::<uint>();
            }
        });
        bh.bytes = size_of::<uint>() as u64 * RAND_BENCH_N;
    }

    #[bench]
    fn rand_isaac64(bh: &mut BenchHarness) {
        let mut rng = Isaac64Rng::new();
        bh.iter(|| {
            for _ in range(0, RAND_BENCH_N) {
                rng.gen::<uint>();
            }
        });
        bh.bytes = size_of::<uint>() as u64 * RAND_BENCH_N;
    }

    #[bench]
    fn rand_std(bh: &mut BenchHarness) {
        let mut rng = StdRng::new();
        bh.iter(|| {
            for _ in range(0, RAND_BENCH_N) {
                rng.gen::<uint>();
            }
        });
        bh.bytes = size_of::<uint>() as u64 * RAND_BENCH_N;
    }

    #[bench]
    fn rand_shuffle_100(bh: &mut BenchHarness) {
        let mut rng = XorShiftRng::new();
        let x : &mut[uint] = [1,..100];
        bh.iter(|| {
            rng.shuffle_mut(x);
        })
    }
}