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Implement _random using the MT19937 algorithm

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This commit is contained in:
Noah
2020-01-31 20:20:29 -06:00
parent 908abef5da
commit a20b6bfaaa
4 changed files with 303 additions and 84 deletions
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11
Cargo.lock generated
View File

@@ -1245,15 +1245,6 @@ dependencies = [
"getrandom",
]
[[package]]
name = "rand_distr"
version = "0.2.2"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "96977acbdd3a6576fb1d27391900035bf3863d4a16422973a409b488cf29ffb2"
dependencies = [
"rand 0.7.3",
]
[[package]]
name = "rand_hc"
version = "0.1.0"
@@ -1539,7 +1530,7 @@ dependencies = [
"paste",
"pwd",
"rand 0.7.3",
"rand_distr",
"rand_core 0.5.1",
"regex",
"result-like",
"rustc_version_runtime",

4
vm/Cargo.toml
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@@ -30,8 +30,8 @@ num-traits = "0.2.8"
num-integer = "0.1.41"
num-rational = "0.2.2"
num-iter = "0.1.39"
rand = { version = "0.7", features = ["small_rng"] }
rand_distr = "0.2"
rand = "0.7"
rand_core = "0.5"
getrandom = "0.1"
log = "0.4"
rustpython-derive = {path = "../derive", version = "0.1.1"}

170
vm/src/stdlib/random.rs
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@@ -3,22 +3,60 @@
use std::cell::RefCell;
use num_bigint::{BigInt, Sign};
use num_traits::Signed;
use rand::RngCore;
use rand::distributions::Distribution;
use rand::{RngCore, SeedableRng};
use rand::rngs::SmallRng;
use rand_distr::Normal;
use crate::function::OptionalArg;
use crate::function::OptionalOption;
use crate::obj::objint::PyIntRef;
use crate::obj::objtype::PyClassRef;
use crate::pyobject::{PyClassImpl, PyObjectRef, PyRef, PyValue, PyResult};
use crate::pyobject::{PyClassImpl, PyObjectRef, PyRef, PyResult, PyValue};
use crate::VirtualMachine;
use crate::vm::VirtualMachine;
mod mersenne;
#[derive(Debug)]
enum PyRng {
Std(rand::rngs::ThreadRng),
MT(mersenne::MT19937),
}
impl Default for PyRng {
fn default() -> Self {
PyRng::Std(rand::thread_rng())
}
}
impl RngCore for PyRng {
fn next_u32(&mut self) -> u32 {
match self {
Self::Std(s) => s.next_u32(),
Self::MT(m) => m.next_u32(),
}
}
fn next_u64(&mut self) -> u64 {
match self {
Self::Std(s) => s.next_u64(),
Self::MT(m) => m.next_u64(),
}
}
fn fill_bytes(&mut self, dest: &mut [u8]) {
match self {
Self::Std(s) => s.fill_bytes(dest),
Self::MT(m) => m.fill_bytes(dest),
}
}
fn try_fill_bytes(&mut self, dest: &mut [u8]) -> Result<(), rand::Error> {
match self {
Self::Std(s) => s.try_fill_bytes(dest),
Self::MT(m) => m.try_fill_bytes(dest),
}
}
}
#[pyclass(name = "Random")]
#[derive(Debug)]
struct PyRandom {
rng: RefCell<SmallRng>
rng: RefCell<PyRng>,
}
impl PyValue for PyRandom {
@@ -27,86 +65,74 @@ impl PyValue for PyRandom {
}
}
#[pyimpl]
#[pyimpl(flags(BASETYPE))]
impl PyRandom {
#[pyslot(new)]
fn new(cls: PyClassRef, vm: &VirtualMachine) -> PyResult<PyRef<Self>> {
PyRandom {
rng: RefCell::new(SmallRng::from_entropy())
}.into_ref_with_type(vm, cls)
}
#[pymethod]
fn seed(&self, n: Option<usize>, vm: &VirtualMachine) -> PyResult {
let rng = match n {
None => SmallRng::from_entropy(),
Some(n) => {
let seed = n as u64;
SmallRng::seed_from_u64(seed)
}
};
*self.rng.borrow_mut() = rng;
Ok(vm.ctx.none())
rng: RefCell::new(PyRng::default()),
}
.into_ref_with_type(vm, cls)
}
#[pymethod]
fn getrandbits(&self, k: usize, vm: &VirtualMachine) -> PyResult {
let bytes = (k - 1) / 8 + 1;
let mut bytearray = vec![0u8; bytes];
self.rng.borrow_mut().fill_bytes(&mut bytearray);
fn random(&self) -> f64 {
gen_res53(&mut *self.rng.borrow_mut())
}
let bits = bytes % 8;
if bits > 0 {
bytearray[0] >>= 8 - bits;
#[pymethod]
fn seed(&self, n: OptionalOption<PyIntRef>) {
let new_rng = match n.flat_option() {
None => PyRng::default(),
Some(n) => {
let (_, mut key) = n.as_bigint().abs().to_u32_digits();
if cfg!(target_endian = "big") {
key.reverse();
}
PyRng::MT(mersenne::MT19937::new_with_slice_seed(&key))
}
};
*self.rng.borrow_mut() = new_rng;
}
#[pymethod]
fn getrandbits(&self, mut k: usize) -> BigInt {
let mut rng = self.rng.borrow_mut();
let mut gen_u32 = |k| rng.next_u32() >> (32 - k) as u32;
if k <= 32 {
return gen_u32(k).into();
}
println!("{:?}", k);
println!("{:?}", bytearray);
let result = BigInt::from_bytes_be(Sign::Plus, &bytearray);
Ok(vm.ctx.new_bigint(&result))
let words = (k - 1) / 8 + 1;
let mut wordarray = vec![0u32; words];
let it = wordarray.iter_mut();
#[cfg(target_endian = "big")]
let it = it.rev();
for word in it {
*word = gen_u32(k);
k -= 32;
}
BigInt::from_slice(Sign::NoSign, &wordarray)
}
}
pub fn make_module(vm: &VirtualMachine) -> PyObjectRef {
let ctx = &vm.ctx;
let random_type = PyRandom::make_class(ctx);
py_module!(vm, "_random", {
"Random" => random_type,
"gauss" => ctx.new_function(random_normalvariate), // TODO: is this the same?
"normalvariate" => ctx.new_function(random_normalvariate),
"random" => ctx.new_function(random_random),
// "weibull", ctx.new_function(random_weibullvariate),
"Random" => PyRandom::make_class(ctx),
})
}
fn random_normalvariate(mu: f64, sigma: f64, vm: &VirtualMachine) -> PyResult<f64> {
let normal = Normal::new(mu, sigma).map_err(|rand_err| {
vm.new_exception_msg(
vm.ctx.exceptions.arithmetic_error.clone(),
format!("invalid normal distribution: {:?}", rand_err),
)
})?;
let value = normal.sample(&mut rand::thread_rng());
Ok(value)
// taken from the translated mersenne twister
/* generates a random number on [0,1) with 53-bit resolution*/
fn gen_res53<R: RngCore>(rng: &mut R) -> f64 {
let a = rng.next_u32() >> 5;
let b = rng.next_u32() >> 6;
(a as f64 * 67108864.0 + b as f64) * (1.0 / 9007199254740992.0)
}
fn random_random(_vm: &VirtualMachine) -> f64 {
rand::random()
}
/*
* TODO: enable this function:
fn random_weibullvariate(vm: &VirtualMachine, args: PyFuncArgs) -> PyResult {
arg_check!(vm, args, required = [(alpha, Some(vm.ctx.float_type())), (beta, Some(vm.ctx.float_type()))]);
let alpha = objfloat::get_value(alpha);
let beta = objfloat::get_value(beta);
let weibull = Weibull::new(alpha, beta);
let value = weibull.sample(&mut rand::thread_rng());
let py_value = vm.ctx.new_float(value);
Ok(py_value)
}
*/
/* These real versions are due to Isaku Wada, 2002/01/09 added */

202
vm/src/stdlib/random/mersenne.rs Normal file
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@@ -0,0 +1,202 @@
/*
A C-program for MT19937, with initialization improved 2002/1/26.
Coded by Takuji Nishimura and Makoto Matsumoto.
Before using, initialize the state by using init_genrand(seed)
or init_by_array(init_key, key_length).
Copyright (C) 1997 - 2002, Makoto Matsumoto and Takuji Nishimura,
All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions
are met:
1. Redistributions of source code must retain the above copyright
notice, this list of conditions and the following disclaimer.
2. Redistributions in binary form must reproduce the above copyright
notice, this list of conditions and the following disclaimer in the
documentation and/or other materials provided with the distribution.
3. The names of its contributors may not be used to endorse or promote
products derived from this software without specific prior written
permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
"AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
Any feedback is very welcome.
http://www.math.sci.hiroshima-u.ac.jp/~m-mat/MT/emt.html
email: m-mat @ math.sci.hiroshima-u.ac.jp (remove space)
*/
// this was translated from c; all rights go to copyright holders listed above
// https://gist.github.com/coolreader18/b56d510f1b0551d2954d74ad289f7d2e
/* Period parameters */
const N: usize = 624;
const M: usize = 397;
const MATRIX_A: u32 = 0x9908b0dfu32; /* constant vector a */
const UPPER_MASK: u32 = 0x80000000u32; /* most significant w-r bits */
const LOWER_MASK: u32 = 0x7fffffffu32; /* least significant r bits */
pub struct MT19937 {
mt: [u32; N], /* the array for the state vector */
mti: usize, /* mti==N+1 means mt[N] is not initialized */
}
impl Default for MT19937 {
fn default() -> Self {
MT19937 {
mt: [0; N],
mti: N + 1,
}
}
}
impl std::fmt::Debug for MT19937 {
fn fmt(&self, f: &mut std::fmt::Formatter) -> std::fmt::Result {
f.pad("MT19937")
}
}
impl MT19937 {
pub fn new_with_slice_seed(init_key: &[u32]) -> Self {
let mut state = Self::default();
state.seed_slice(init_key);
state
}
/* initializes self.mt[N] with a seed */
fn seed(&mut self, s: u32) {
self.mt[0] = s & 0xffffffffu32;
self.mti = 1;
while self.mti < N {
self.mt[self.mti] = 1812433253u32
.wrapping_mul(self.mt[self.mti - 1] ^ (self.mt[self.mti - 1] >> 30))
+ self.mti as u32;
/* See Knuth TAOCP Vol2. 3rd Ed. P.106 for multiplier. */
/* In the previous versions, MSBs of the seed affect */
/* only MSBs of the array self.mt[]. */
/* 2002/01/09 modified by Makoto Matsumoto */
self.mt[self.mti] &= 0xffffffffu32;
/* for >32 bit machines */
self.mti += 1;
}
}
/* initialize by an array with array-length */
/* init_key is the array for initializing keys */
/* key_length is its length */
/* slight change for C++, 2004/2/26 */
pub fn seed_slice(&mut self, init_key: &[u32]) {
let mut i;
let mut j;
let mut k;
self.seed(19650218);
i = 1;
j = 0;
k = if N > init_key.len() {
N
} else {
init_key.len()
};
while k != 0 {
self.mt[i] = (self.mt[i]
^ ((self.mt[i - 1] ^ (self.mt[i - 1] >> 30)).wrapping_mul(1664525u32)))
+ init_key[j]
+ j as u32; /* non linear */
self.mt[i] &= 0xffffffffu32; /* for WORDSIZE > 32 machines */
i += 1;
j += 1;
if i >= N {
self.mt[0] = self.mt[N - 1];
i = 1;
}
if j >= init_key.len() {
j = 0;
}
k -= 1;
}
k = N - 1;
while k != 0 {
self.mt[i] = (self.mt[i]
^ ((self.mt[i - 1] ^ (self.mt[i - 1] >> 30)).wrapping_mul(1566083941u32)))
- i as u32; /* non linear */
self.mt[i] &= 0xffffffffu32; /* for WORDSIZE > 32 machines */
i += 1;
if i >= N {
self.mt[0] = self.mt[N - 1];
i = 1;
}
k -= 1;
}
self.mt[0] = 0x80000000u32; /* MSB is 1; assuring non-zero initial array */
}
/* generates a random number on [0,0xffffffff]-interval */
fn gen_u32(&mut self) -> u32 {
let mut y: u32;
let mag01 = |x| if (x & 0x1) == 1 { MATRIX_A } else { 0 };
/* mag01[x] = x * MATRIX_A for x=0,1 */
if self.mti >= N {
/* generate N words at one time */
if self.mti == N + 1
/* if seed() has not been called, */
{
self.seed(5489u32);
} /* a default initial seed is used */
for kk in 0..N - M {
y = (self.mt[kk] & UPPER_MASK) | (self.mt[kk + 1] & LOWER_MASK);
self.mt[kk] = self.mt[kk + M] ^ (y >> 1) ^ mag01(y);
}
for kk in N - M..N - 1 {
y = (self.mt[kk] & UPPER_MASK) | (self.mt[kk + 1] & LOWER_MASK);
self.mt[kk] = self.mt[kk.wrapping_add(M.wrapping_sub(N))] ^ (y >> 1) ^ mag01(y);
}
y = (self.mt[N - 1] & UPPER_MASK) | (self.mt[0] & LOWER_MASK);
self.mt[N - 1] = self.mt[M - 1] ^ (y >> 1) ^ mag01(y);
self.mti = 0;
}
y = self.mt[self.mti];
self.mti += 1;
/* Tempering */
y ^= y >> 11;
y ^= (y << 7) & 0x9d2c5680u32;
y ^= (y << 15) & 0xefc60000u32;
y ^= y >> 18;
y
}
}
impl rand::RngCore for MT19937 {
fn next_u32(&mut self) -> u32 {
self.gen_u32()
}
fn next_u64(&mut self) -> u64 {
rand_core::impls::next_u64_via_u32(self)
}
fn fill_bytes(&mut self, dest: &mut [u8]) {
rand_core::impls::fill_bytes_via_next(self, dest)
}
fn try_fill_bytes(&mut self, dest: &mut [u8]) -> Result<(), rand::Error> {
Ok(self.fill_bytes(dest))
}
}