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// Copyright 2017 The Rust Project Developers. See the COPYRIGHT
// file at the top-level directory of this distribution and at
// https://rust-lang.org/COPYRIGHT.
//
// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
// option. This file may not be copied, modified, or distributed
// except according to those terms.
//! The implementations of the `Standard` distribution for other built-in types.
use core::char;
use core::num::Wrapping;
use {Rng};
use distributions::{Distribution, Standard, Uniform};
// ----- Sampling distributions -----
/// Sample a `char`, uniformly distributed over ASCII letters and numbers:
/// a-z, A-Z and 0-9.
///
/// # Example
///
/// ```
/// use std::iter;
/// use rand::{Rng, thread_rng};
/// use rand::distributions::Alphanumeric;
///
/// let mut rng = thread_rng();
/// let chars: String = iter::repeat(())
/// .map(|()| rng.sample(Alphanumeric))
/// .take(7)
/// .collect();
/// println!("Random chars: {}", chars);
/// ```
#[derive(Debug)]
pub struct Alphanumeric;
// ----- Implementations of distributions -----
impl Distribution<char> for Standard {
#[inline]
fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> char {
let range = Uniform::new(0u32, 0x11_0000);
loop {
match char::from_u32(range.sample(rng)) {
Some(c) => return c,
// About 0.2% of numbers in the range 0..0x110000 are invalid
// codepoints (surrogates).
None => {}
}
}
}
}
impl Distribution<char> for Alphanumeric {
fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> char {
const RANGE: u32 = 26 + 26 + 10;
const GEN_ASCII_STR_CHARSET: &[u8] =
b"ABCDEFGHIJKLMNOPQRSTUVWXYZ\
abcdefghijklmnopqrstuvwxyz\
0123456789";
// We can pick from 62 characters. This is so close to a power of 2, 64,
// that we can do better than `Uniform`. Use a simple bitshift and
// rejection sampling. We do not use a bitmask, because for small RNGs
// the most significant bits are usually of higher quality.
loop {
let var = rng.next_u32() >> (32 - 6);
if var < RANGE {
return GEN_ASCII_STR_CHARSET[var as usize] as char
}
}
}
}
impl Distribution<bool> for Standard {
#[inline]
fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> bool {
// We can compare against an arbitrary bit of an u32 to get a bool.
// Because the least significant bits of a lower quality RNG can have
// simple patterns, we compare against the most significant bit. This is
// easiest done using a sign test.
(rng.next_u32() as i32) < 0
}
}
macro_rules! tuple_impl {
// use variables to indicate the arity of the tuple
($($tyvar:ident),* ) => {
// the trailing commas are for the 1 tuple
impl< $( $tyvar ),* >
Distribution<( $( $tyvar ),* , )>
for Standard
where $( Standard: Distribution<$tyvar> ),*
{
#[inline]
fn sample<R: Rng + ?Sized>(&self, _rng: &mut R) -> ( $( $tyvar ),* , ) {
(
// use the $tyvar's to get the appropriate number of
// repeats (they're not actually needed)
$(
_rng.gen::<$tyvar>()
),*
,
)
}
}
}
}
impl Distribution<()> for Standard {
#[inline]
fn sample<R: Rng + ?Sized>(&self, _: &mut R) -> () { () }
}
tuple_impl!{A}
tuple_impl!{A, B}
tuple_impl!{A, B, C}
tuple_impl!{A, B, C, D}
tuple_impl!{A, B, C, D, E}
tuple_impl!{A, B, C, D, E, F}
tuple_impl!{A, B, C, D, E, F, G}
tuple_impl!{A, B, C, D, E, F, G, H}
tuple_impl!{A, B, C, D, E, F, G, H, I}
tuple_impl!{A, B, C, D, E, F, G, H, I, J}
tuple_impl!{A, B, C, D, E, F, G, H, I, J, K}
tuple_impl!{A, B, C, D, E, F, G, H, I, J, K, L}
macro_rules! array_impl {
// recursive, given at least one type parameter:
{$n:expr, $t:ident, $($ts:ident,)*} => {
array_impl!{($n - 1), $($ts,)*}
impl<T> Distribution<[T; $n]> for Standard where Standard: Distribution<T> {
#[inline]
fn sample<R: Rng + ?Sized>(&self, _rng: &mut R) -> [T; $n] {
[_rng.gen::<$t>(), $(_rng.gen::<$ts>()),*]
}
}
};
// empty case:
{$n:expr,} => {
impl<T> Distribution<[T; $n]> for Standard {
fn sample<R: Rng + ?Sized>(&self, _rng: &mut R) -> [T; $n] { [] }
}
};
}
array_impl!{32, T, T, T, T, T, T, T, T, T, T, T, T, T, T, T, T, T, T, T, T, T, T, T, T, T, T, T, T, T, T, T, T,}
impl<T> Distribution<Option<T>> for Standard where Standard: Distribution<T> {
#[inline]
fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> Option<T> {
// UFCS is needed here: https://github.com/rust-lang/rust/issues/24066
if rng.gen::<bool>() {
Some(rng.gen())
} else {
None
}
}
}
impl<T> Distribution<Wrapping<T>> for Standard where Standard: Distribution<T> {
#[inline]
fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> Wrapping<T> {
Wrapping(rng.gen())
}
}
#[cfg(test)]
mod tests {
use {Rng, RngCore, Standard};
use distributions::Alphanumeric;
#[cfg(all(not(feature="std"), feature="alloc"))] use alloc::string::String;
#[test]
fn test_misc() {
let rng: &mut RngCore = &mut ::test::rng(820);
rng.sample::<char, _>(Standard);
rng.sample::<bool, _>(Standard);
}
#[cfg(feature="alloc")]
#[test]
fn test_chars() {
use core::iter;
let mut rng = ::test::rng(805);
// Test by generating a relatively large number of chars, so we also
// take the rejection sampling path.
let word: String = iter::repeat(())
.map(|()| rng.gen::<char>()).take(1000).collect();
assert!(word.len() != 0);
}
#[test]
fn test_alphanumeric() {
let mut rng = ::test::rng(806);
// Test by generating a relatively large number of chars, so we also
// take the rejection sampling path.
let mut incorrect = false;
for _ in 0..100 {
let c = rng.sample(Alphanumeric);
incorrect |= !((c >= '0' && c <= '9') ||
(c >= 'A' && c <= 'Z') ||
(c >= 'a' && c <= 'z') );
}
assert!(incorrect == false);
}
}