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std.crypto.random * cross platform, even freestanding * can't fail. on initialization for some systems requires calling os.getrandom(), in which case there are rare but theoretically possible errors. The code panics in these cases, however the application may choose to override the default seed function and then handle the failure another way. * thread-safe * supports the full Random interface * cryptographically secure * no syscall required to initialize on Linux (AT_RANDOM) * calls arc4random on systems that support it `std.crypto.randomBytes` is removed in favor of `std.crypto.random.bytes`. I moved some of the Random implementations into their own files in the interest of organization. stage2 no longer requires passing a RNG; instead it uses this API. Closes #6704
608 lines
21 KiB
Zig
608 lines
21 KiB
Zig
// SPDX-License-Identifier: MIT
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// Copyright (c) 2015-2020 Zig Contributors
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// This file is part of [zig](https://ziglang.org/), which is MIT licensed.
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// The MIT license requires this copyright notice to be included in all copies
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// and substantial portions of the software.
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//! The engines provided here should be initialized from an external source.
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//! For a thread-local cryptographically secure pseudo random number generator,
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//! use `std.crypto.random`.
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//! Be sure to use a CSPRNG when required, otherwise using a normal PRNG will
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//! be faster and use substantially less stack space.
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//!
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//! TODO(tiehuis): Benchmark these against other reference implementations.
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const std = @import("std.zig");
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const builtin = @import("builtin");
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const assert = std.debug.assert;
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const expect = std.testing.expect;
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const expectEqual = std.testing.expectEqual;
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const mem = std.mem;
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const math = std.math;
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const ziggurat = @import("rand/ziggurat.zig");
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const maxInt = std.math.maxInt;
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/// Fast unbiased random numbers.
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pub const DefaultPrng = Xoroshiro128;
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/// Cryptographically secure random numbers.
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pub const DefaultCsprng = Gimli;
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pub const Isaac64 = @import("rand/Isaac64.zig");
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pub const Gimli = @import("rand/Gimli.zig");
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pub const Pcg = @import("rand/Pcg.zig");
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pub const Xoroshiro128 = @import("rand/Xoroshiro128.zig");
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pub const Sfc64 = @import("rand/Sfc64.zig");
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pub const Random = struct {
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fillFn: fn (r: *Random, buf: []u8) void,
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/// Read random bytes into the specified buffer until full.
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pub fn bytes(r: *Random, buf: []u8) void {
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r.fillFn(r, buf);
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}
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pub fn boolean(r: *Random) bool {
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return r.int(u1) != 0;
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}
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/// Returns a random int `i` such that `0 <= i <= maxInt(T)`.
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/// `i` is evenly distributed.
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pub fn int(r: *Random, comptime T: type) T {
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const bits = @typeInfo(T).Int.bits;
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const UnsignedT = std.meta.Int(.unsigned, bits);
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const ByteAlignedT = std.meta.Int(.unsigned, @divTrunc(bits + 7, 8) * 8);
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var rand_bytes: [@sizeOf(ByteAlignedT)]u8 = undefined;
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r.bytes(rand_bytes[0..]);
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// use LE instead of native endian for better portability maybe?
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// TODO: endian portability is pointless if the underlying prng isn't endian portable.
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// TODO: document the endian portability of this library.
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const byte_aligned_result = mem.readIntSliceLittle(ByteAlignedT, &rand_bytes);
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const unsigned_result = @truncate(UnsignedT, byte_aligned_result);
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return @bitCast(T, unsigned_result);
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}
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/// Constant-time implementation off `uintLessThan`.
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/// The results of this function may be biased.
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pub fn uintLessThanBiased(r: *Random, comptime T: type, less_than: T) T {
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comptime assert(@typeInfo(T).Int.signedness == .unsigned);
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const bits = @typeInfo(T).Int.bits;
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comptime assert(bits <= 64); // TODO: workaround: LLVM ERROR: Unsupported library call operation!
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assert(0 < less_than);
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if (bits <= 32) {
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return @intCast(T, limitRangeBiased(u32, r.int(u32), less_than));
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} else {
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return @intCast(T, limitRangeBiased(u64, r.int(u64), less_than));
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}
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}
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/// Returns an evenly distributed random unsigned integer `0 <= i < less_than`.
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/// This function assumes that the underlying `fillFn` produces evenly distributed values.
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/// Within this assumption, the runtime of this function is exponentially distributed.
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/// If `fillFn` were backed by a true random generator,
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/// the runtime of this function would technically be unbounded.
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/// However, if `fillFn` is backed by any evenly distributed pseudo random number generator,
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/// this function is guaranteed to return.
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/// If you need deterministic runtime bounds, use `uintLessThanBiased`.
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pub fn uintLessThan(r: *Random, comptime T: type, less_than: T) T {
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comptime assert(@typeInfo(T).Int.signedness == .unsigned);
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const bits = @typeInfo(T).Int.bits;
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comptime assert(bits <= 64); // TODO: workaround: LLVM ERROR: Unsupported library call operation!
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assert(0 < less_than);
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// Small is typically u32
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const small_bits = @divTrunc(bits + 31, 32) * 32;
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const Small = std.meta.Int(.unsigned, small_bits);
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// Large is typically u64
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const Large = std.meta.Int(.unsigned, small_bits * 2);
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// adapted from:
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// http://www.pcg-random.org/posts/bounded-rands.html
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// "Lemire's (with an extra tweak from me)"
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var x: Small = r.int(Small);
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var m: Large = @as(Large, x) * @as(Large, less_than);
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var l: Small = @truncate(Small, m);
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if (l < less_than) {
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// TODO: workaround for https://github.com/ziglang/zig/issues/1770
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// should be:
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// var t: Small = -%less_than;
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var t: Small = @bitCast(Small, -%@bitCast(std.meta.Int(.signed, small_bits), @as(Small, less_than)));
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if (t >= less_than) {
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t -= less_than;
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if (t >= less_than) {
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t %= less_than;
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}
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}
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while (l < t) {
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x = r.int(Small);
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m = @as(Large, x) * @as(Large, less_than);
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l = @truncate(Small, m);
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}
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}
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return @intCast(T, m >> small_bits);
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}
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/// Constant-time implementation off `uintAtMost`.
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/// The results of this function may be biased.
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pub fn uintAtMostBiased(r: *Random, comptime T: type, at_most: T) T {
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assert(@typeInfo(T).Int.signedness == .unsigned);
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if (at_most == maxInt(T)) {
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// have the full range
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return r.int(T);
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}
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return r.uintLessThanBiased(T, at_most + 1);
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}
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/// Returns an evenly distributed random unsigned integer `0 <= i <= at_most`.
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/// See `uintLessThan`, which this function uses in most cases,
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/// for commentary on the runtime of this function.
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pub fn uintAtMost(r: *Random, comptime T: type, at_most: T) T {
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assert(@typeInfo(T).Int.signedness == .unsigned);
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if (at_most == maxInt(T)) {
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// have the full range
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return r.int(T);
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}
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return r.uintLessThan(T, at_most + 1);
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}
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/// Constant-time implementation off `intRangeLessThan`.
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/// The results of this function may be biased.
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pub fn intRangeLessThanBiased(r: *Random, comptime T: type, at_least: T, less_than: T) T {
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assert(at_least < less_than);
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const info = @typeInfo(T).Int;
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if (info.signedness == .signed) {
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// Two's complement makes this math pretty easy.
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const UnsignedT = std.meta.Int(.unsigned, info.bits);
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const lo = @bitCast(UnsignedT, at_least);
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const hi = @bitCast(UnsignedT, less_than);
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const result = lo +% r.uintLessThanBiased(UnsignedT, hi -% lo);
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return @bitCast(T, result);
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} else {
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// The signed implementation would work fine, but we can use stricter arithmetic operators here.
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return at_least + r.uintLessThanBiased(T, less_than - at_least);
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}
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}
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/// Returns an evenly distributed random integer `at_least <= i < less_than`.
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/// See `uintLessThan`, which this function uses in most cases,
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/// for commentary on the runtime of this function.
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pub fn intRangeLessThan(r: *Random, comptime T: type, at_least: T, less_than: T) T {
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assert(at_least < less_than);
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const info = @typeInfo(T).Int;
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if (info.signedness == .signed) {
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// Two's complement makes this math pretty easy.
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const UnsignedT = std.meta.Int(.unsigned, info.bits);
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const lo = @bitCast(UnsignedT, at_least);
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const hi = @bitCast(UnsignedT, less_than);
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const result = lo +% r.uintLessThan(UnsignedT, hi -% lo);
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return @bitCast(T, result);
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} else {
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// The signed implementation would work fine, but we can use stricter arithmetic operators here.
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return at_least + r.uintLessThan(T, less_than - at_least);
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}
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}
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/// Constant-time implementation off `intRangeAtMostBiased`.
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/// The results of this function may be biased.
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pub fn intRangeAtMostBiased(r: *Random, comptime T: type, at_least: T, at_most: T) T {
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assert(at_least <= at_most);
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const info = @typeInfo(T).Int;
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if (info.signedness == .signed) {
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// Two's complement makes this math pretty easy.
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const UnsignedT = std.meta.Int(.unsigned, info.bits);
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const lo = @bitCast(UnsignedT, at_least);
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const hi = @bitCast(UnsignedT, at_most);
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const result = lo +% r.uintAtMostBiased(UnsignedT, hi -% lo);
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return @bitCast(T, result);
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} else {
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// The signed implementation would work fine, but we can use stricter arithmetic operators here.
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return at_least + r.uintAtMostBiased(T, at_most - at_least);
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}
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}
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/// Returns an evenly distributed random integer `at_least <= i <= at_most`.
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/// See `uintLessThan`, which this function uses in most cases,
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/// for commentary on the runtime of this function.
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pub fn intRangeAtMost(r: *Random, comptime T: type, at_least: T, at_most: T) T {
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assert(at_least <= at_most);
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const info = @typeInfo(T).Int;
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if (info.signedness == .signed) {
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// Two's complement makes this math pretty easy.
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const UnsignedT = std.meta.Int(.unsigned, info.bits);
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const lo = @bitCast(UnsignedT, at_least);
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const hi = @bitCast(UnsignedT, at_most);
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const result = lo +% r.uintAtMost(UnsignedT, hi -% lo);
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return @bitCast(T, result);
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} else {
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// The signed implementation would work fine, but we can use stricter arithmetic operators here.
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return at_least + r.uintAtMost(T, at_most - at_least);
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}
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}
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pub const scalar = @compileError("deprecated; use boolean() or int() instead");
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pub const range = @compileError("deprecated; use intRangeLessThan()");
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/// Return a floating point value evenly distributed in the range [0, 1).
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pub fn float(r: *Random, comptime T: type) T {
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// Generate a uniform value between [1, 2) and scale down to [0, 1).
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// Note: The lowest mantissa bit is always set to 0 so we only use half the available range.
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switch (T) {
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f32 => {
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const s = r.int(u32);
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const repr = (0x7f << 23) | (s >> 9);
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return @bitCast(f32, repr) - 1.0;
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},
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f64 => {
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const s = r.int(u64);
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const repr = (0x3ff << 52) | (s >> 12);
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return @bitCast(f64, repr) - 1.0;
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},
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else => @compileError("unknown floating point type"),
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}
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}
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/// Return a floating point value normally distributed with mean = 0, stddev = 1.
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///
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/// To use different parameters, use: floatNorm(...) * desiredStddev + desiredMean.
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pub fn floatNorm(r: *Random, comptime T: type) T {
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const value = ziggurat.next_f64(r, ziggurat.NormDist);
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switch (T) {
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f32 => return @floatCast(f32, value),
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f64 => return value,
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else => @compileError("unknown floating point type"),
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}
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}
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/// Return an exponentially distributed float with a rate parameter of 1.
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///
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/// To use a different rate parameter, use: floatExp(...) / desiredRate.
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pub fn floatExp(r: *Random, comptime T: type) T {
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const value = ziggurat.next_f64(r, ziggurat.ExpDist);
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switch (T) {
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f32 => return @floatCast(f32, value),
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f64 => return value,
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else => @compileError("unknown floating point type"),
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}
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}
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/// Shuffle a slice into a random order.
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pub fn shuffle(r: *Random, comptime T: type, buf: []T) void {
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if (buf.len < 2) {
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return;
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}
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var i: usize = 0;
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while (i < buf.len - 1) : (i += 1) {
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const j = r.intRangeLessThan(usize, i, buf.len);
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mem.swap(T, &buf[i], &buf[j]);
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}
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}
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};
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/// Convert a random integer 0 <= random_int <= maxValue(T),
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/// into an integer 0 <= result < less_than.
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/// This function introduces a minor bias.
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pub fn limitRangeBiased(comptime T: type, random_int: T, less_than: T) T {
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comptime assert(@typeInfo(T).Int.signedness == .unsigned);
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const bits = @typeInfo(T).Int.bits;
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const T2 = std.meta.Int(.unsigned, bits * 2);
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// adapted from:
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// http://www.pcg-random.org/posts/bounded-rands.html
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// "Integer Multiplication (Biased)"
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var m: T2 = @as(T2, random_int) * @as(T2, less_than);
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return @intCast(T, m >> bits);
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}
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const SequentialPrng = struct {
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const Self = @This();
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random: Random,
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next_value: u8,
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pub fn init() Self {
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return Self{
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.random = Random{ .fillFn = fill },
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.next_value = 0,
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};
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}
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fn fill(r: *Random, buf: []u8) void {
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const self = @fieldParentPtr(Self, "random", r);
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for (buf) |*b| {
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b.* = self.next_value;
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}
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self.next_value +%= 1;
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}
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};
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test "Random int" {
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testRandomInt();
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comptime testRandomInt();
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}
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fn testRandomInt() void {
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var r = SequentialPrng.init();
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expect(r.random.int(u0) == 0);
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r.next_value = 0;
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expect(r.random.int(u1) == 0);
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expect(r.random.int(u1) == 1);
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expect(r.random.int(u2) == 2);
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expect(r.random.int(u2) == 3);
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expect(r.random.int(u2) == 0);
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r.next_value = 0xff;
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expect(r.random.int(u8) == 0xff);
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r.next_value = 0x11;
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expect(r.random.int(u8) == 0x11);
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r.next_value = 0xff;
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expect(r.random.int(u32) == 0xffffffff);
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r.next_value = 0x11;
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expect(r.random.int(u32) == 0x11111111);
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r.next_value = 0xff;
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expect(r.random.int(i32) == -1);
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r.next_value = 0x11;
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expect(r.random.int(i32) == 0x11111111);
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r.next_value = 0xff;
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expect(r.random.int(i8) == -1);
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r.next_value = 0x11;
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expect(r.random.int(i8) == 0x11);
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r.next_value = 0xff;
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expect(r.random.int(u33) == 0x1ffffffff);
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r.next_value = 0xff;
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expect(r.random.int(i1) == -1);
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r.next_value = 0xff;
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expect(r.random.int(i2) == -1);
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r.next_value = 0xff;
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expect(r.random.int(i33) == -1);
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}
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test "Random boolean" {
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testRandomBoolean();
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comptime testRandomBoolean();
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}
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fn testRandomBoolean() void {
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var r = SequentialPrng.init();
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expect(r.random.boolean() == false);
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expect(r.random.boolean() == true);
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expect(r.random.boolean() == false);
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expect(r.random.boolean() == true);
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}
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test "Random intLessThan" {
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@setEvalBranchQuota(10000);
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testRandomIntLessThan();
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comptime testRandomIntLessThan();
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}
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fn testRandomIntLessThan() void {
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var r = SequentialPrng.init();
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r.next_value = 0xff;
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expect(r.random.uintLessThan(u8, 4) == 3);
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expect(r.next_value == 0);
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expect(r.random.uintLessThan(u8, 4) == 0);
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expect(r.next_value == 1);
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r.next_value = 0;
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expect(r.random.uintLessThan(u64, 32) == 0);
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// trigger the bias rejection code path
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r.next_value = 0;
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expect(r.random.uintLessThan(u8, 3) == 0);
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// verify we incremented twice
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expect(r.next_value == 2);
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r.next_value = 0xff;
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expect(r.random.intRangeLessThan(u8, 0, 0x80) == 0x7f);
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r.next_value = 0xff;
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expect(r.random.intRangeLessThan(u8, 0x7f, 0xff) == 0xfe);
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r.next_value = 0xff;
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expect(r.random.intRangeLessThan(i8, 0, 0x40) == 0x3f);
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r.next_value = 0xff;
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expect(r.random.intRangeLessThan(i8, -0x40, 0x40) == 0x3f);
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r.next_value = 0xff;
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expect(r.random.intRangeLessThan(i8, -0x80, 0) == -1);
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r.next_value = 0xff;
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expect(r.random.intRangeLessThan(i3, -4, 0) == -1);
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r.next_value = 0xff;
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expect(r.random.intRangeLessThan(i3, -2, 2) == 1);
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}
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test "Random intAtMost" {
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@setEvalBranchQuota(10000);
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testRandomIntAtMost();
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comptime testRandomIntAtMost();
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}
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fn testRandomIntAtMost() void {
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var r = SequentialPrng.init();
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r.next_value = 0xff;
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expect(r.random.uintAtMost(u8, 3) == 3);
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expect(r.next_value == 0);
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expect(r.random.uintAtMost(u8, 3) == 0);
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// trigger the bias rejection code path
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r.next_value = 0;
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expect(r.random.uintAtMost(u8, 2) == 0);
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// verify we incremented twice
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expect(r.next_value == 2);
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r.next_value = 0xff;
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expect(r.random.intRangeAtMost(u8, 0, 0x7f) == 0x7f);
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r.next_value = 0xff;
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expect(r.random.intRangeAtMost(u8, 0x7f, 0xfe) == 0xfe);
|
|
|
|
r.next_value = 0xff;
|
|
expect(r.random.intRangeAtMost(i8, 0, 0x3f) == 0x3f);
|
|
r.next_value = 0xff;
|
|
expect(r.random.intRangeAtMost(i8, -0x40, 0x3f) == 0x3f);
|
|
r.next_value = 0xff;
|
|
expect(r.random.intRangeAtMost(i8, -0x80, -1) == -1);
|
|
|
|
r.next_value = 0xff;
|
|
expect(r.random.intRangeAtMost(i3, -4, -1) == -1);
|
|
r.next_value = 0xff;
|
|
expect(r.random.intRangeAtMost(i3, -2, 1) == 1);
|
|
|
|
expect(r.random.uintAtMost(u0, 0) == 0);
|
|
}
|
|
|
|
test "Random Biased" {
|
|
var r = DefaultPrng.init(0);
|
|
// Not thoroughly checking the logic here.
|
|
// Just want to execute all the paths with different types.
|
|
|
|
expect(r.random.uintLessThanBiased(u1, 1) == 0);
|
|
expect(r.random.uintLessThanBiased(u32, 10) < 10);
|
|
expect(r.random.uintLessThanBiased(u64, 20) < 20);
|
|
|
|
expect(r.random.uintAtMostBiased(u0, 0) == 0);
|
|
expect(r.random.uintAtMostBiased(u1, 0) <= 0);
|
|
expect(r.random.uintAtMostBiased(u32, 10) <= 10);
|
|
expect(r.random.uintAtMostBiased(u64, 20) <= 20);
|
|
|
|
expect(r.random.intRangeLessThanBiased(u1, 0, 1) == 0);
|
|
expect(r.random.intRangeLessThanBiased(i1, -1, 0) == -1);
|
|
expect(r.random.intRangeLessThanBiased(u32, 10, 20) >= 10);
|
|
expect(r.random.intRangeLessThanBiased(i32, 10, 20) >= 10);
|
|
expect(r.random.intRangeLessThanBiased(u64, 20, 40) >= 20);
|
|
expect(r.random.intRangeLessThanBiased(i64, 20, 40) >= 20);
|
|
|
|
// uncomment for broken module error:
|
|
//expect(r.random.intRangeAtMostBiased(u0, 0, 0) == 0);
|
|
expect(r.random.intRangeAtMostBiased(u1, 0, 1) >= 0);
|
|
expect(r.random.intRangeAtMostBiased(i1, -1, 0) >= -1);
|
|
expect(r.random.intRangeAtMostBiased(u32, 10, 20) >= 10);
|
|
expect(r.random.intRangeAtMostBiased(i32, 10, 20) >= 10);
|
|
expect(r.random.intRangeAtMostBiased(u64, 20, 40) >= 20);
|
|
expect(r.random.intRangeAtMostBiased(i64, 20, 40) >= 20);
|
|
}
|
|
|
|
// Generator to extend 64-bit seed values into longer sequences.
|
|
//
|
|
// The number of cycles is thus limited to 64-bits regardless of the engine, but this
|
|
// is still plenty for practical purposes.
|
|
pub const SplitMix64 = struct {
|
|
s: u64,
|
|
|
|
pub fn init(seed: u64) SplitMix64 {
|
|
return SplitMix64{ .s = seed };
|
|
}
|
|
|
|
pub fn next(self: *SplitMix64) u64 {
|
|
self.s +%= 0x9e3779b97f4a7c15;
|
|
|
|
var z = self.s;
|
|
z = (z ^ (z >> 30)) *% 0xbf58476d1ce4e5b9;
|
|
z = (z ^ (z >> 27)) *% 0x94d049bb133111eb;
|
|
return z ^ (z >> 31);
|
|
}
|
|
};
|
|
|
|
test "splitmix64 sequence" {
|
|
var r = SplitMix64.init(0xaeecf86f7878dd75);
|
|
|
|
const seq = [_]u64{
|
|
0x5dbd39db0178eb44,
|
|
0xa9900fb66b397da3,
|
|
0x5c1a28b1aeebcf5c,
|
|
0x64a963238f776912,
|
|
0xc6d4177b21d1c0ab,
|
|
0xb2cbdbdb5ea35394,
|
|
};
|
|
|
|
for (seq) |s| {
|
|
expect(s == r.next());
|
|
}
|
|
}
|
|
|
|
// Actual Random helper function tests, pcg engine is assumed correct.
|
|
test "Random float" {
|
|
var prng = DefaultPrng.init(0);
|
|
|
|
var i: usize = 0;
|
|
while (i < 1000) : (i += 1) {
|
|
const val1 = prng.random.float(f32);
|
|
expect(val1 >= 0.0);
|
|
expect(val1 < 1.0);
|
|
|
|
const val2 = prng.random.float(f64);
|
|
expect(val2 >= 0.0);
|
|
expect(val2 < 1.0);
|
|
}
|
|
}
|
|
|
|
test "Random shuffle" {
|
|
var prng = DefaultPrng.init(0);
|
|
|
|
var seq = [_]u8{ 0, 1, 2, 3, 4 };
|
|
var seen = [_]bool{false} ** 5;
|
|
|
|
var i: usize = 0;
|
|
while (i < 1000) : (i += 1) {
|
|
prng.random.shuffle(u8, seq[0..]);
|
|
seen[seq[0]] = true;
|
|
expect(sumArray(seq[0..]) == 10);
|
|
}
|
|
|
|
// we should see every entry at the head at least once
|
|
for (seen) |e| {
|
|
expect(e == true);
|
|
}
|
|
}
|
|
|
|
fn sumArray(s: []const u8) u32 {
|
|
var r: u32 = 0;
|
|
for (s) |e|
|
|
r += e;
|
|
return r;
|
|
}
|
|
|
|
test "Random range" {
|
|
var prng = DefaultPrng.init(0);
|
|
testRange(&prng.random, -4, 3);
|
|
testRange(&prng.random, -4, -1);
|
|
testRange(&prng.random, 10, 14);
|
|
testRange(&prng.random, -0x80, 0x7f);
|
|
}
|
|
|
|
fn testRange(r: *Random, start: i8, end: i8) void {
|
|
testRangeBias(r, start, end, true);
|
|
testRangeBias(r, start, end, false);
|
|
}
|
|
fn testRangeBias(r: *Random, start: i8, end: i8, biased: bool) void {
|
|
const count = @intCast(usize, @as(i32, end) - @as(i32, start));
|
|
var values_buffer = [_]bool{false} ** 0x100;
|
|
const values = values_buffer[0..count];
|
|
var i: usize = 0;
|
|
while (i < count) {
|
|
const value: i32 = if (biased) r.intRangeLessThanBiased(i8, start, end) else r.intRangeLessThan(i8, start, end);
|
|
const index = @intCast(usize, value - start);
|
|
if (!values[index]) {
|
|
i += 1;
|
|
values[index] = true;
|
|
}
|
|
}
|
|
}
|
|
|
|
test "CSPRNG" {
|
|
var secret_seed: [DefaultCsprng.secret_seed_length]u8 = undefined;
|
|
std.crypto.random.bytes(&secret_seed);
|
|
var csprng = DefaultCsprng.init(secret_seed);
|
|
const a = csprng.random.int(u64);
|
|
const b = csprng.random.int(u64);
|
|
const c = csprng.random.int(u64);
|
|
expect(a ^ b ^ c != 0);
|
|
}
|
|
|
|
test "" {
|
|
std.testing.refAllDecls(@This());
|
|
}
|