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//! Randomization of big integers
use rand::distributions::uniform::{SampleUniform, UniformSampler};
use rand::prelude::*;
use rand::AsByteSliceMut;
use BigInt;
use BigUint;
use Sign::*;
use big_digit::BigDigit;
use bigint::{into_magnitude, magnitude};
use integer::Integer;
use traits::Zero;
pub trait RandBigInt {
/// Generate a random `BigUint` of the given bit size.
fn gen_biguint(&mut self, bit_size: usize) -> BigUint;
/// Generate a random BigInt of the given bit size.
fn gen_bigint(&mut self, bit_size: usize) -> BigInt;
/// Generate a random `BigUint` less than the given bound. Fails
/// when the bound is zero.
fn gen_biguint_below(&mut self, bound: &BigUint) -> BigUint;
/// Generate a random `BigUint` within the given range. The lower
/// bound is inclusive; the upper bound is exclusive. Fails when
/// the upper bound is not greater than the lower bound.
fn gen_biguint_range(&mut self, lbound: &BigUint, ubound: &BigUint) -> BigUint;
/// Generate a random `BigInt` within the given range. The lower
/// bound is inclusive; the upper bound is exclusive. Fails when
/// the upper bound is not greater than the lower bound.
fn gen_bigint_range(&mut self, lbound: &BigInt, ubound: &BigInt) -> BigInt;
}
impl<R: Rng + ?Sized> RandBigInt for R {
fn gen_biguint(&mut self, bit_size: usize) -> BigUint {
use super::big_digit::BITS;
let (digits, rem) = bit_size.div_rem(&BITS);
let mut data = vec![BigDigit::default(); digits + (rem > 0) as usize];
// `fill_bytes` is faster than many `gen::<u32>` calls
self.fill_bytes(data[..].as_byte_slice_mut());
// Swap bytes per the `Rng::fill` source. This might be
// unnecessary if reproducibility across architectures is not
// desired.
data.to_le();
if rem > 0 {
data[digits] >>= BITS - rem;
}
BigUint::new(data)
}
fn gen_bigint(&mut self, bit_size: usize) -> BigInt {
loop {
// Generate a random BigUint...
let biguint = self.gen_biguint(bit_size);
// ...and then randomly assign it a Sign...
let sign = if biguint.is_zero() {
// ...except that if the BigUint is zero, we need to try
// again with probability 0.5. This is because otherwise,
// the probability of generating a zero BigInt would be
// double that of any other number.
if self.gen() {
continue;
} else {
NoSign
}
} else if self.gen() {
Plus
} else {
Minus
};
return BigInt::from_biguint(sign, biguint);
}
}
fn gen_biguint_below(&mut self, bound: &BigUint) -> BigUint {
assert!(!bound.is_zero());
let bits = bound.bits();
loop {
let n = self.gen_biguint(bits);
if n < *bound {
return n;
}
}
}
fn gen_biguint_range(&mut self, lbound: &BigUint, ubound: &BigUint) -> BigUint {
assert!(*lbound < *ubound);
if lbound.is_zero() {
self.gen_biguint_below(ubound)
} else {
lbound + self.gen_biguint_below(&(ubound - lbound))
}
}
fn gen_bigint_range(&mut self, lbound: &BigInt, ubound: &BigInt) -> BigInt {
assert!(*lbound < *ubound);
if lbound.is_zero() {
BigInt::from(self.gen_biguint_below(magnitude(&ubound)))
} else if ubound.is_zero() {
lbound + BigInt::from(self.gen_biguint_below(magnitude(&lbound)))
} else {
let delta = ubound - lbound;
lbound + BigInt::from(self.gen_biguint_below(magnitude(&delta)))
}
}
}
/// The back-end implementing rand's `UniformSampler` for `BigUint`.
#[derive(Clone, Debug)]
pub struct UniformBigUint {
base: BigUint,
len: BigUint,
}
impl UniformSampler for UniformBigUint {
type X = BigUint;
#[inline]
fn new(low: Self::X, high: Self::X) -> Self {
assert!(low < high);
UniformBigUint {
len: high - &low,
base: low,
}
}
#[inline]
fn new_inclusive(low: Self::X, high: Self::X) -> Self {
assert!(low <= high);
Self::new(low, high + 1u32)
}
#[inline]
fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> Self::X {
&self.base + rng.gen_biguint_below(&self.len)
}
#[inline]
fn sample_single<R: Rng + ?Sized>(low: Self::X, high: Self::X, rng: &mut R) -> Self::X {
rng.gen_biguint_range(&low, &high)
}
}
impl SampleUniform for BigUint {
type Sampler = UniformBigUint;
}
/// The back-end implementing rand's `UniformSampler` for `BigInt`.
#[derive(Clone, Debug)]
pub struct UniformBigInt {
base: BigInt,
len: BigUint,
}
impl UniformSampler for UniformBigInt {
type X = BigInt;
#[inline]
fn new(low: Self::X, high: Self::X) -> Self {
assert!(low < high);
UniformBigInt {
len: into_magnitude(high - &low),
base: low,
}
}
#[inline]
fn new_inclusive(low: Self::X, high: Self::X) -> Self {
assert!(low <= high);
Self::new(low, high + 1u32)
}
#[inline]
fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> Self::X {
&self.base + BigInt::from(rng.gen_biguint_below(&self.len))
}
#[inline]
fn sample_single<R: Rng + ?Sized>(low: Self::X, high: Self::X, rng: &mut R) -> Self::X {
rng.gen_bigint_range(&low, &high)
}
}
impl SampleUniform for BigInt {
type Sampler = UniformBigInt;
}
/// A random distribution for `BigUint` and `BigInt` values of a particular bit size.
#[derive(Clone, Copy, Debug)]
pub struct RandomBits {
bits: usize,
}
impl RandomBits {
#[inline]
pub fn new(bits: usize) -> RandomBits {
RandomBits { bits }
}
}
impl Distribution<BigUint> for RandomBits {
#[inline]
fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> BigUint {
rng.gen_biguint(self.bits)
}
}
impl Distribution<BigInt> for RandomBits {
#[inline]
fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> BigInt {
rng.gen_bigint(self.bits)
}
}