// 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 or the MIT license // , 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::()`. 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; let mut rng = rand::rng(); if rng.gen() { // bool println!("int: {}, uint: {}", rng.gen::(), rng.gen::()) } ``` ```rust use std::rand; 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(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. /// /// By default this is implemented in terms of `next_u32`. An /// implementation of this trait must provide at least one of /// these two methods. Similarly to `next_u32`, this rarely needs /// to be called directly, prefer `r.gen()` to `r.next_u64()`. 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::()`, 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}; /// /// 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::{task_rng, Rng}; /// /// let mut rng = task_rng(); /// let x: uint = rng.gen(); /// println!("{}", x); /// println!("{:?}", rng.gen::<(f64, bool)>()); /// ``` #[inline(always)] fn gen(&mut self) -> T { Rand::rand(self) } /// Return a random vector of the specified length. /// /// # Example /// /// ```rust /// use std::rand::{task_rng, Rng}; /// /// let mut rng = task_rng(); /// let x: ~[uint] = rng.gen_vec(10); /// println!("{:?}", x); /// println!("{:?}", rng.gen_vec::<(f64, bool)>(5)); /// ``` fn gen_vec(&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::{task_rng, Rng}; /// /// let mut rng = 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(&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::{task_rng, Rng}; /// /// let mut rng = task_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::{task_rng, Rng}; /// /// println(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(&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::{task_rng, Rng}; /// /// let choices = [1, 2, 4, 8, 16, 32]; /// let mut rng = 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::{task_rng, Rng}; /// /// println!("{:?}", task_rng().shuffle(~[1,2,3])); /// ``` fn shuffle(&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::{task_rng, Rng}; /// /// let mut rng = task_rng(); /// let mut y = [1,2,3]; /// rng.shuffle_mut(y); /// println!("{:?}", y); /// rng.shuffle_mut(y); /// println!("{:?}", y); /// ``` fn shuffle_mut(&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::{task_rng, Rng}; /// /// let mut rng = task_rng(); /// let sample = rng.sample(range(1, 100), 5); /// println!("{:?}", sample); /// ``` fn sample>(&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: Rng { /// Reseed an RNG with the given seed. /// /// # Example /// /// ```rust /// use std::rand::{Rng, SeedableRng, StdRng}; /// /// let mut rng: StdRng = SeedableRng::from_seed(&[1, 2, 3, 4]); /// println!("{}", rng.gen::()); /// rng.reseed([5, 6, 7, 8]); /// println!("{}", rng.gen::()); /// ``` fn reseed(&mut self, Seed); /// Create a new RNG with the given seed. /// /// # Example /// /// ```rust /// use std::rand::{Rng, SeedableRng, StdRng}; /// /// let mut rng: StdRng = SeedableRng::from_seed(&[1, 2, 3, 4]); /// println!("{}", rng.gen::()); /// ``` 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 for TaskRngReseeder { fn reseed(&mut self, rng: &mut StdRng) { *rng = StdRng::new(); } } static TASK_RNG_RESEED_THRESHOLD: uint = 32_768; type TaskRngInner = reseeding::ReseedingRng; /// 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::()`. /// /// 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; /// /// if random() { /// let x = random(); /// println!("{}", 2u * x); /// } else { /// println!("{}", random::()); /// } /// ``` #[inline] pub fn random() -> 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}; /// /// println!("f32 from (0,1): {}", *random::>()); /// /// let x: Open01 = random(); /// println!("f64 from (0,1): {}", *x); /// ``` pub struct Open01(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}; /// /// println!("f32 from [0,1]: {}", *random::>()); /// /// let x: Closed01 = random(); /// println!("f64 from [0,1]: {}", *x); /// ``` pub struct Closed01(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::(); let b = r.gen::(); 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::(0u).len(), 0u); assert_eq!(r.gen_vec::(10u).len(), 10u); assert_eq!(r.gen_vec::(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::(); 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> = 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::(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::(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::(); } }); bh.bytes = size_of::() 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::(); } }); bh.bytes = size_of::() 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::(); } }); bh.bytes = size_of::() 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::(); } }); bh.bytes = size_of::() 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); }) } }