mirror of
https://github.com/Relintai/pmlpp.git
synced 2024-11-13 13:57:19 +01:00
143 lines
6.3 KiB
C++
143 lines
6.3 KiB
C++
#ifndef RANDOM_PCG_H
|
|
#define RANDOM_PCG_H
|
|
|
|
/*************************************************************************/
|
|
/* random_pcg.h */
|
|
/*************************************************************************/
|
|
/* This file is part of: */
|
|
/* PANDEMONIUM ENGINE */
|
|
/* https://github.com/Relintai/pandemonium_engine */
|
|
/*************************************************************************/
|
|
/* Copyright (c) 2022-present Péter Magyar. */
|
|
/* Copyright (c) 2014-2022 Godot Engine contributors (cf. AUTHORS.md). */
|
|
/* Copyright (c) 2007-2022 Juan Linietsky, Ariel Manzur. */
|
|
/* */
|
|
/* Permission is hereby granted, free of charge, to any person obtaining */
|
|
/* a copy of this software and associated documentation files (the */
|
|
/* "Software"), to deal in the Software without restriction, including */
|
|
/* without limitation the rights to use, copy, modify, merge, publish, */
|
|
/* distribute, sublicense, and/or sell copies of the Software, and to */
|
|
/* permit persons to whom the Software is furnished to do so, subject to */
|
|
/* the following conditions: */
|
|
/* */
|
|
/* The above copyright notice and this permission notice shall be */
|
|
/* included in all copies or substantial portions of the Software. */
|
|
/* */
|
|
/* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, */
|
|
/* EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF */
|
|
/* MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.*/
|
|
/* IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY */
|
|
/* CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, */
|
|
/* TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE */
|
|
/* SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. */
|
|
/*************************************************************************/
|
|
|
|
#include <math.h>
|
|
|
|
#include "math_defs.h"
|
|
|
|
#include "pcg.h"
|
|
|
|
#if defined(__GNUC__) || (_llvm_has_builtin(__builtin_clz))
|
|
#define CLZ32(x) __builtin_clz(x)
|
|
#elif defined(_MSC_VER)
|
|
#include "intrin.h"
|
|
static int __bsr_clz32(uint32_t x) {
|
|
unsigned long index;
|
|
_BitScanReverse(&index, x);
|
|
return 31 - index;
|
|
}
|
|
#define CLZ32(x) __bsr_clz32(x)
|
|
#else
|
|
#endif
|
|
|
|
#if defined(__GNUC__) || (_llvm_has_builtin(__builtin_ldexp) && _llvm_has_builtin(__builtin_ldexpf))
|
|
#define LDEXP(s, e) __builtin_ldexp(s, e)
|
|
#define LDEXPF(s, e) __builtin_ldexpf(s, e)
|
|
#else
|
|
#include "math.h"
|
|
#define LDEXP(s, e) ldexp(s, e)
|
|
#define LDEXPF(s, e) ldexp(s, e)
|
|
#endif
|
|
|
|
class RandomPCG {
|
|
pcg32_random_t pcg;
|
|
uint64_t current_seed; // The seed the current generator state started from.
|
|
uint64_t current_inc;
|
|
|
|
public:
|
|
static const uint64_t DEFAULT_SEED = 12047754176567800795U;
|
|
static const uint64_t DEFAULT_INC = PCG_DEFAULT_INC_64;
|
|
|
|
RandomPCG(uint64_t p_seed = DEFAULT_SEED, uint64_t p_inc = DEFAULT_INC);
|
|
|
|
_FORCE_INLINE_ void seed(uint64_t p_seed) {
|
|
current_seed = p_seed;
|
|
pcg32_srandom_r(&pcg, current_seed, current_inc);
|
|
}
|
|
_FORCE_INLINE_ uint64_t get_seed() { return current_seed; }
|
|
|
|
_FORCE_INLINE_ void set_state(uint64_t p_state) { pcg.state = p_state; }
|
|
_FORCE_INLINE_ uint64_t get_state() const { return pcg.state; }
|
|
|
|
void randomize();
|
|
_FORCE_INLINE_ uint32_t rand() {
|
|
return pcg32_random_r(&pcg);
|
|
}
|
|
_FORCE_INLINE_ uint32_t rand(uint32_t bounds) {
|
|
return pcg32_boundedrand_r(&pcg, bounds);
|
|
}
|
|
|
|
// Obtaining floating point numbers in [0, 1] range with "good enough" uniformity.
|
|
// These functions sample the output of rand() as the fraction part of an infinite binary number,
|
|
// with some tricks applied to reduce ops and branching:
|
|
// 1. Instead of shifting to the first 1 and connecting random bits, we simply set the MSB and LSB to 1.
|
|
// Provided that the RNG is actually uniform bit by bit, this should have the exact same effect.
|
|
// 2. In order to compensate for exponent info loss, we count zeros from another random number,
|
|
// and just add that to the initial offset.
|
|
// This has the same probability as counting and shifting an actual bit stream: 2^-n for n zeroes.
|
|
// For all numbers above 2^-96 (2^-64 for floats), the functions should be uniform.
|
|
// However, all numbers below that threshold are floored to 0.
|
|
// The thresholds are chosen to minimize rand() calls while keeping the numbers within a totally subjective quality standard.
|
|
// If clz or ldexp isn't available, fall back to bit truncation for performance, sacrificing uniformity.
|
|
_FORCE_INLINE_ double randd() {
|
|
#if defined(CLZ32)
|
|
uint32_t proto_exp_offset = rand();
|
|
if (unlikely(proto_exp_offset == 0)) {
|
|
return 0;
|
|
}
|
|
uint64_t significand = (((uint64_t)rand()) << 32) | rand() | 0x8000000000000001U;
|
|
return LDEXP((double)significand, -64 - CLZ32(proto_exp_offset));
|
|
#else
|
|
#pragma message("RandomPCG::randd - intrinsic clz is not available, falling back to bit truncation")
|
|
return (double)(((((uint64_t)rand()) << 32) | rand()) & 0x1FFFFFFFFFFFFFU) / (double)0x1FFFFFFFFFFFFFU;
|
|
#endif
|
|
}
|
|
_FORCE_INLINE_ float randf() {
|
|
#if defined(CLZ32)
|
|
uint32_t proto_exp_offset = rand();
|
|
if (unlikely(proto_exp_offset == 0)) {
|
|
return 0;
|
|
}
|
|
return LDEXPF((float)(rand() | 0x80000001), -32 - CLZ32(proto_exp_offset));
|
|
#else
|
|
#pragma message("RandomPCG::randf - intrinsic clz is not available, falling back to bit truncation")
|
|
return (float)(rand() & 0xFFFFFF) / (float)0xFFFFFF;
|
|
#endif
|
|
}
|
|
|
|
_FORCE_INLINE_ double randfn(double p_mean, double p_deviation) {
|
|
return p_mean + p_deviation * (cos(Math_TAU * randd()) * sqrt(-2.0 * log(randd()))); // Box-Muller transform
|
|
}
|
|
_FORCE_INLINE_ float randfn(float p_mean, float p_deviation) {
|
|
return p_mean + p_deviation * (cos(Math_TAU * randf()) * sqrt(-2.0 * log(randf()))); // Box-Muller transform
|
|
}
|
|
|
|
double random(double p_from, double p_to);
|
|
float random(float p_from, float p_to);
|
|
real_t randomr(real_t p_from, real_t p_to) { return random(p_from, p_to); }
|
|
int random(int p_from, int p_to);
|
|
};
|
|
|
|
#endif // RANDOM_PCG_H
|