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const std = @import("std.zig"); const builtin = @import("builtin"); const assert = std.debug.assert; const mem = std.mem; const math = std.math; const maxInt = std.math.maxInt; |
DefaultPrngFast unbiased random numbers. |
pub const DefaultPrng = Xoshiro256; |
DefaultCsprngCryptographically secure random numbers. |
pub const DefaultCsprng = ChaCha; |
Asconrand/Ascon.zig |
pub const Ascon = @import("rand/Ascon.zig"); |
ChaCharand/ChaCha.zig |
pub const ChaCha = @import("rand/ChaCha.zig"); |
Isaac64rand/Isaac64.zig |
pub const Isaac64 = @import("rand/Isaac64.zig"); |
Pcgrand/Pcg.zig |
pub const Pcg = @import("rand/Pcg.zig"); |
Xoroshiro128rand/Xoroshiro128.zig |
pub const Xoroshiro128 = @import("rand/Xoroshiro128.zig"); |
Xoshiro256rand/Xoshiro256.zig |
pub const Xoshiro256 = @import("rand/Xoshiro256.zig"); |
Sfc64rand/Sfc64.zig |
pub const Sfc64 = @import("rand/Sfc64.zig"); |
RomuTriorand/RomuTrio.zig |
pub const RomuTrio = @import("rand/RomuTrio.zig"); |
zigguratrand/ziggurat.zig |
pub const ziggurat = @import("rand/ziggurat.zig"); |
Random |
pub const Random = struct { ptr: *anyopaque, fillFn: *const fn (ptr: *anyopaque, buf: []u8) void, |
init() |
pub fn init(pointer: anytype, comptime fillFn: fn (ptr: @TypeOf(pointer), buf: []u8) void) Random { const Ptr = @TypeOf(pointer); assert(@typeInfo(Ptr) == .Pointer); // Must be a pointer assert(@typeInfo(Ptr).Pointer.size == .One); // Must be a single-item pointer assert(@typeInfo(@typeInfo(Ptr).Pointer.child) == .Struct); // Must point to a struct const gen = struct { fn fill(ptr: *anyopaque, buf: []u8) void { const self: Ptr = @ptrCast(@alignCast(ptr)); fillFn(self, buf); } }; return .{ .ptr = pointer, .fillFn = gen.fill, }; } |
bytes()Read random bytes into the specified buffer until full. |
pub fn bytes(r: Random, buf: []u8) void { r.fillFn(r.ptr, buf); } |
boolean() |
pub fn boolean(r: Random) bool { return r.int(u1) != 0; } |
enumValue() Returns a random value from an enum, evenly distributed. |
pub inline fn enumValue(r: Random, comptime EnumType: type) EnumType { return r.enumValueWithIndex(EnumType, usize); } |
enumValueWithIndex() Returns a random value from an enum, evenly distributed. |
pub fn enumValueWithIndex(r: Random, comptime EnumType: type, comptime Index: type) EnumType { comptime assert(@typeInfo(EnumType) == .Enum); // We won't use int -> enum casting because enum elements can have // arbitrary values. Instead we'll randomly pick one of the type's values. const values = comptime std.enums.values(EnumType); comptime assert(values.len > 0); // can't return anything comptime assert(maxInt(Index) >= values.len - 1); // can't access all values comptime if (values.len == 1) return values[0]; const index = if (comptime values.len - 1 == maxInt(Index)) r.int(Index) else r.uintLessThan(Index, values.len); const MinInt = MinArrayIndex(Index); return values[@as(MinInt, @intCast(index))]; } |
int() Returns a random int |
pub fn int(r: Random, comptime T: type) T { const bits = @typeInfo(T).Int.bits; const UnsignedT = std.meta.Int(.unsigned, bits); const ceil_bytes = comptime std.math.divCeil(u16, bits, 8) catch unreachable; const ByteAlignedT = std.meta.Int(.unsigned, ceil_bytes * 8); var rand_bytes: [ceil_bytes]u8 = undefined; r.bytes(&rand_bytes); // use LE instead of native endian for better portability maybe? // TODO: endian portability is pointless if the underlying prng isn't endian portable. // TODO: document the endian portability of this library. const byte_aligned_result = mem.readInt(ByteAlignedT, &rand_bytes, .little); const unsigned_result: UnsignedT = @truncate(byte_aligned_result); return @bitCast(unsigned_result); } |
uintLessThanBiased() Constant-time implementation off |
pub fn uintLessThanBiased(r: Random, comptime T: type, less_than: T) T { comptime assert(@typeInfo(T).Int.signedness == .unsigned); assert(0 < less_than); return limitRangeBiased(T, r.int(T), less_than); } |
uintLessThan() Returns an evenly distributed random unsigned integer |
pub fn uintLessThan(r: Random, comptime T: type, less_than: T) T { comptime assert(@typeInfo(T).Int.signedness == .unsigned); const bits = @typeInfo(T).Int.bits; assert(0 < less_than); // adapted from: // http://www.pcg-random.org/posts/bounded-rands.html // "Lemire's (with an extra tweak from me)" var x = r.int(T); var m = math.mulWide(T, x, less_than); var l: T = @truncate(m); if (l < less_than) { var t = -%less_than; if (t >= less_than) { t -= less_than; if (t >= less_than) { t %= less_than; } } while (l < t) { x = r.int(T); m = math.mulWide(T, x, less_than); l = @truncate(m); } } return @intCast(m >> bits); } |
uintAtMostBiased() Constant-time implementation off |
pub fn uintAtMostBiased(r: Random, comptime T: type, at_most: T) T { assert(@typeInfo(T).Int.signedness == .unsigned); if (at_most == maxInt(T)) { // have the full range return r.int(T); } return r.uintLessThanBiased(T, at_most + 1); } |
uintAtMost() Returns an evenly distributed random unsigned integer |
pub fn uintAtMost(r: Random, comptime T: type, at_most: T) T { assert(@typeInfo(T).Int.signedness == .unsigned); if (at_most == maxInt(T)) { // have the full range return r.int(T); } return r.uintLessThan(T, at_most + 1); } |
intRangeLessThanBiased() Constant-time implementation off |
pub fn intRangeLessThanBiased(r: Random, comptime T: type, at_least: T, less_than: T) T { assert(at_least < less_than); const info = @typeInfo(T).Int; if (info.signedness == .signed) { // Two's complement makes this math pretty easy. const UnsignedT = std.meta.Int(.unsigned, info.bits); const lo: UnsignedT = @bitCast(at_least); const hi: UnsignedT = @bitCast(less_than); const result = lo +% r.uintLessThanBiased(UnsignedT, hi -% lo); return @bitCast(result); } else { // The signed implementation would work fine, but we can use stricter arithmetic operators here. return at_least + r.uintLessThanBiased(T, less_than - at_least); } } |
intRangeLessThan() Returns an evenly distributed random integer |
pub fn intRangeLessThan(r: Random, comptime T: type, at_least: T, less_than: T) T { assert(at_least < less_than); const info = @typeInfo(T).Int; if (info.signedness == .signed) { // Two's complement makes this math pretty easy. const UnsignedT = std.meta.Int(.unsigned, info.bits); const lo: UnsignedT = @bitCast(at_least); const hi: UnsignedT = @bitCast(less_than); const result = lo +% r.uintLessThan(UnsignedT, hi -% lo); return @bitCast(result); } else { // The signed implementation would work fine, but we can use stricter arithmetic operators here. return at_least + r.uintLessThan(T, less_than - at_least); } } |
intRangeAtMostBiased() Constant-time implementation off |
pub fn intRangeAtMostBiased(r: Random, comptime T: type, at_least: T, at_most: T) T { assert(at_least <= at_most); const info = @typeInfo(T).Int; if (info.signedness == .signed) { // Two's complement makes this math pretty easy. const UnsignedT = std.meta.Int(.unsigned, info.bits); const lo: UnsignedT = @bitCast(at_least); const hi: UnsignedT = @bitCast(at_most); const result = lo +% r.uintAtMostBiased(UnsignedT, hi -% lo); return @bitCast(result); } else { // The signed implementation would work fine, but we can use stricter arithmetic operators here. return at_least + r.uintAtMostBiased(T, at_most - at_least); } } |
intRangeAtMost() Returns an evenly distributed random integer |
pub fn intRangeAtMost(r: Random, comptime T: type, at_least: T, at_most: T) T { assert(at_least <= at_most); const info = @typeInfo(T).Int; if (info.signedness == .signed) { // Two's complement makes this math pretty easy. const UnsignedT = std.meta.Int(.unsigned, info.bits); const lo: UnsignedT = @bitCast(at_least); const hi: UnsignedT = @bitCast(at_most); const result = lo +% r.uintAtMost(UnsignedT, hi -% lo); return @bitCast(result); } else { // The signed implementation would work fine, but we can use stricter arithmetic operators here. return at_least + r.uintAtMost(T, at_most - at_least); } } |
float()Return a floating point value evenly distributed in the range [0, 1). |
pub fn float(r: Random, comptime T: type) T { // Generate a uniformly random value for the mantissa. // Then generate an exponentially biased random value for the exponent. // This covers every possible value in the range. switch (T) { f32 => { // Use 23 random bits for the mantissa, and the rest for the exponent. // If all 41 bits are zero, generate additional random bits, until a // set bit is found, or 126 bits have been generated. const rand = r.int(u64); var rand_lz = @clz(rand); if (rand_lz >= 41) { // TODO: when #5177 or #489 is implemented, // tell the compiler it is unlikely (1/2^41) to reach this point. // (Same for the if branch and the f64 calculations below.) rand_lz = 41 + @clz(r.int(u64)); if (rand_lz == 41 + 64) { // It is astronomically unlikely to reach this point. rand_lz += @clz(r.int(u32) | 0x7FF); } } const mantissa: u23 = @truncate(rand); const exponent = @as(u32, 126 - rand_lz) << 23; return @bitCast(exponent | mantissa); }, f64 => { // Use 52 random bits for the mantissa, and the rest for the exponent. // If all 12 bits are zero, generate additional random bits, until a // set bit is found, or 1022 bits have been generated. const rand = r.int(u64); var rand_lz: u64 = @clz(rand); if (rand_lz >= 12) { rand_lz = 12; while (true) { // It is astronomically unlikely for this loop to execute more than once. const addl_rand_lz = @clz(r.int(u64)); rand_lz += addl_rand_lz; if (addl_rand_lz != 64) { break; } if (rand_lz >= 1022) { rand_lz = 1022; break; } } } const mantissa = rand & 0xFFFFFFFFFFFFF; const exponent = (1022 - rand_lz) << 52; return @bitCast(exponent | mantissa); }, else => @compileError("unknown floating point type"), } } |
floatNorm() Return a floating point value normally distributed with mean = 0, stddev = 1. |
pub fn floatNorm(r: Random, comptime T: type) T { const value = ziggurat.next_f64(r, ziggurat.NormDist); switch (T) { f32 => return @floatCast(value), f64 => return value, else => @compileError("unknown floating point type"), } } |
floatExp() Return an exponentially distributed float with a rate parameter of 1. |
pub fn floatExp(r: Random, comptime T: type) T { const value = ziggurat.next_f64(r, ziggurat.ExpDist); switch (T) { f32 => return @floatCast(value), f64 => return value, else => @compileError("unknown floating point type"), } } |
shuffle() Shuffle a slice into a random order. |
pub inline fn shuffle(r: Random, comptime T: type, buf: []T) void { r.shuffleWithIndex(T, buf, usize); } |
shuffleWithIndex() Shuffle a slice into a random order, using an index of a specified type to maintain distribution across targets. Asserts the index type can represent |
pub fn shuffleWithIndex(r: Random, comptime T: type, buf: []T, comptime Index: type) void { const MinInt = MinArrayIndex(Index); if (buf.len < 2) { return; } // `i <= j < max <= maxInt(MinInt)` const max: MinInt = @intCast(buf.len); var i: MinInt = 0; while (i < max - 1) : (i += 1) { const j: MinInt = @intCast(r.intRangeLessThan(Index, i, max)); mem.swap(T, &buf[i], &buf[j]); } } |
weightedIndex() Randomly selects an index into |
pub fn weightedIndex(r: std.rand.Random, comptime T: type, proportions: []const T) usize { // This implementation works by summing the proportions and picking a random // point in [0, sum). We then loop over the proportions, accumulating // until our accumulator is greater than the random point. var sum: T = 0; for (proportions) |v| { sum += v; } const point = if (comptime std.meta.trait.isSignedInt(T)) r.intRangeLessThan(T, 0, sum) else if (comptime std.meta.trait.isUnsignedInt(T)) r.uintLessThan(T, sum) else if (comptime std.meta.trait.isFloat(T)) // take care that imprecision doesn't lead to a value slightly greater than sum @min(r.float(T) * sum, sum - std.math.floatEps(T)) else @compileError("weightedIndex does not support proportions of type " ++ @typeName(T)); std.debug.assert(point < sum); var accumulator: T = 0; for (proportions, 0..) |p, index| { accumulator += p; if (point < accumulator) return index; } unreachable; } fn MinArrayIndex(comptime Index: type) type { const index_info = @typeInfo(Index).Int; assert(index_info.signedness == .unsigned); return if (index_info.bits >= @typeInfo(usize).Int.bits) usize else Index; } }; |
limitRangeBiased() Returns the smallest of |
pub fn limitRangeBiased(comptime T: type, random_int: T, less_than: T) T { comptime assert(@typeInfo(T).Int.signedness == .unsigned); const bits = @typeInfo(T).Int.bits; // adapted from: // http://www.pcg-random.org/posts/bounded-rands.html // "Integer Multiplication (Biased)" const m = math.mulWide(T, random_int, less_than); return @intCast(m >> bits); } // 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. |
SplitMix64 |
pub const SplitMix64 = struct { s: u64, |
init() |
pub fn init(seed: u64) SplitMix64 { return SplitMix64{ .s = seed }; } |
next() |
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 { std.testing.refAllDecls(@This()); _ = @import("rand/test.zig"); } |
Generated by zstd-browse2 on 2023-11-04 14:12:19 -0400. |