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blender-archive/extern/mantaflow/helper/util/randomstream.h
2020-11-06 12:06:05 +01:00

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/******************************************************************************
*
* MantaFlow fluid solver framework
* Copyright 2011 Tobias Pfaff, Nils Thuerey
*
* This program is free software, distributed under the terms of the
* Apache License, Version 2.0
* http://www.apache.org/licenses/LICENSE-2.0
*
* Random numbers
*
* Based on an example by Makoto Matsumoto, Takuji Nishimura, Shawn Cokus, and Richard J. Wagner
*
******************************************************************************/
#ifndef _RANDOMSTREAM_H
#define _RANDOMSTREAM_H
#include <iostream>
#include <stdio.h>
#include <time.h>
#include "vectorbase.h"
namespace Manta {
class MTRand {
// Data
public:
typedef unsigned long uint32; // unsigned integer type, at least 32 bits
enum { N = 624 }; // length of state vector
enum { SAVE = N + 1 }; // length of array for save()
protected:
enum { M = 397 }; // period parameter
uint32 state[N]; // internal state
uint32 *pNext; // next value to get from state
int left; // number of values left before reload needed
// Methods
public:
MTRand(const uint32 &oneSeed); // initialize with a simple uint32
MTRand(uint32 *const bigSeed, uint32 const seedLength = N); // or an array
MTRand(); // auto-initialize with /dev/urandom or time() and clock()
// Do NOT use for CRYPTOGRAPHY without securely hashing several returned
// values together, otherwise the generator state can be learned after
// reading 624 consecutive values.
// Access to 32-bit random numbers
double rand(); // real number in [0,1]
double rand(const double &n); // real number in [0,n]
double randExc(); // real number in [0,1)
double randExc(const double &n); // real number in [0,n)
double randDblExc(); // real number in (0,1)
double randDblExc(const double &n); // real number in (0,n)
uint32 randInt(); // integer in [0,2^32-1]
uint32 randInt(const uint32 &n); // integer in [0,n] for n < 2^32
double operator()()
{
return rand();
} // same as rand()
// Access to 53-bit random numbers (capacity of IEEE double precision)
double rand53(); // real number in [0,1)
// Access to nonuniform random number distributions
double randNorm(const double &mean = 0.0, const double &variance = 1.0);
// Re-seeding functions with same behavior as initializers
void seed(const uint32 oneSeed);
void seed(uint32 *const bigSeed, const uint32 seedLength = N);
void seed();
// Saving and loading generator state
void save(uint32 *saveArray) const; // to array of size SAVE
void load(uint32 *const loadArray); // from such array
friend std::ostream &operator<<(std::ostream &os, const MTRand &mtrand);
friend std::istream &operator>>(std::istream &is, MTRand &mtrand);
protected:
void initialize(const uint32 oneSeed);
void reload();
uint32 hiBit(const uint32 &u) const
{
return u & 0x80000000UL;
}
uint32 loBit(const uint32 &u) const
{
return u & 0x00000001UL;
}
uint32 loBits(const uint32 &u) const
{
return u & 0x7fffffffUL;
}
uint32 mixBits(const uint32 &u, const uint32 &v) const
{
return hiBit(u) | loBits(v);
}
uint32 twist(const uint32 &m, const uint32 &s0, const uint32 &s1) const
{
return m ^ (mixBits(s0, s1) >> 1) ^ (-loBit(s1) & 0x9908b0dfUL);
}
static uint32 hash(time_t t, clock_t c);
};
inline MTRand::MTRand(const uint32 &oneSeed)
{
seed(oneSeed);
}
inline MTRand::MTRand(uint32 *const bigSeed, const uint32 seedLength)
{
seed(bigSeed, seedLength);
}
inline MTRand::MTRand()
{
seed();
}
inline double MTRand::rand()
{
return double(randInt()) * (1.0 / 4294967295.0);
}
inline double MTRand::rand(const double &n)
{
return rand() * n;
}
inline double MTRand::randExc()
{
return double(randInt()) * (1.0 / 4294967296.0);
}
inline double MTRand::randExc(const double &n)
{
return randExc() * n;
}
inline double MTRand::randDblExc()
{
return (double(randInt()) + 0.5) * (1.0 / 4294967296.0);
}
inline double MTRand::randDblExc(const double &n)
{
return randDblExc() * n;
}
inline double MTRand::rand53()
{
uint32 a = randInt() >> 5, b = randInt() >> 6;
return (a * 67108864.0 + b) * (1.0 / 9007199254740992.0); // by Isaku Wada
}
inline double MTRand::randNorm(const double &mean, const double &variance)
{
// Return a real number from a normal (Gaussian) distribution with given
// mean and variance by Box-Muller method
double r = sqrt(-2.0 * log(1.0 - randDblExc())) * variance;
double phi = 2.0 * 3.14159265358979323846264338328 * randExc();
return mean + r * cos(phi);
}
inline MTRand::uint32 MTRand::randInt()
{
// Pull a 32-bit integer from the generator state
// Every other access function simply transforms the numbers extracted here
if (left == 0)
reload();
--left;
uint32 s1;
s1 = *pNext++;
s1 ^= (s1 >> 11);
s1 ^= (s1 << 7) & 0x9d2c5680UL;
s1 ^= (s1 << 15) & 0xefc60000UL;
return (s1 ^ (s1 >> 18));
}
inline MTRand::uint32 MTRand::randInt(const uint32 &n)
{
// Find which bits are used in n
// Optimized by Magnus Jonsson (magnus@smartelectronix.com)
uint32 used = n;
used |= used >> 1;
used |= used >> 2;
used |= used >> 4;
used |= used >> 8;
used |= used >> 16;
// Draw numbers until one is found in [0,n]
uint32 i;
do
i = randInt() & used; // toss unused bits to shorten search
while (i > n);
return i;
}
inline void MTRand::seed(const uint32 oneSeed)
{
// Seed the generator with a simple uint32
initialize(oneSeed);
reload();
}
inline void MTRand::seed(uint32 *const bigSeed, const uint32 seedLength)
{
// Seed the generator with an array of uint32's
// There are 2^19937-1 possible initial states. This function allows
// all of those to be accessed by providing at least 19937 bits (with a
// default seed length of N = 624 uint32's). Any bits above the lower 32
// in each element are discarded.
// Just call seed() if you want to get array from /dev/urandom
initialize(19650218UL);
const unsigned int Nenum = N;
int i = 1;
uint32 j = 0;
int k = (Nenum > seedLength ? Nenum : seedLength);
for (; k; --k) {
state[i] = state[i] ^ ((state[i - 1] ^ (state[i - 1] >> 30)) * 1664525UL);
state[i] += (bigSeed[j] & 0xffffffffUL) + j;
state[i] &= 0xffffffffUL;
++i;
++j;
if (i >= N) {
state[0] = state[N - 1];
i = 1;
}
if (j >= seedLength)
j = 0;
}
for (k = N - 1; k; --k) {
state[i] = state[i] ^ ((state[i - 1] ^ (state[i - 1] >> 30)) * 1566083941UL);
state[i] -= i;
state[i] &= 0xffffffffUL;
++i;
if (i >= N) {
state[0] = state[N - 1];
i = 1;
}
}
state[0] = 0x80000000UL; // MSB is 1, assuring non-zero initial array
reload();
}
inline void MTRand::seed()
{
// Seed the generator with an array from /dev/urandom if available
// Otherwise use a hash of time() and clock() values
// First try getting an array from /dev/urandom
FILE *urandom = fopen("/dev/urandom", "rb");
if (urandom) {
uint32 bigSeed[N];
uint32 *s = bigSeed;
int i = N;
bool success = true;
while (success && i--)
success = fread(s++, sizeof(uint32), 1, urandom);
fclose(urandom);
if (success) {
seed(bigSeed, N);
return;
}
}
// Was not successful, so use time() and clock() instead
seed(hash(time(nullptr), clock()));
}
inline void MTRand::initialize(const uint32 intseed)
{
// Initialize generator state with seed
// See Knuth TAOCP Vol 2, 3rd Ed, p.106 for multiplier.
// In previous versions, most significant bits (MSBs) of the seed affect
// only MSBs of the state array. Modified 9 Jan 2002 by Makoto Matsumoto.
uint32 *s = state;
uint32 *r = state;
int i = 1;
*s++ = intseed & 0xffffffffUL;
for (; i < N; ++i) {
*s++ = (1812433253UL * (*r ^ (*r >> 30)) + i) & 0xffffffffUL;
r++;
}
}
inline void MTRand::reload()
{
// Generate N new values in state
// Made clearer and faster by Matthew Bellew (matthew.bellew@home.com)
uint32 *p = state;
int i;
for (i = N - M; i--; ++p)
*p = twist(p[M], p[0], p[1]);
for (i = M; --i; ++p)
*p = twist(p[M - N], p[0], p[1]);
*p = twist(p[M - N], p[0], state[0]);
left = N, pNext = state;
}
inline MTRand::uint32 MTRand::hash(time_t t, clock_t c)
{
// Get a uint32 from t and c
// Better than uint32(x) in case x is floating point in [0,1]
// Based on code by Lawrence Kirby (fred@genesis.demon.co.uk)
static uint32 differ = 0; // guarantee time-based seeds will change
uint32 h1 = 0;
unsigned char *p = (unsigned char *)&t;
for (size_t i = 0; i < sizeof(t); ++i) {
h1 *= std::numeric_limits<unsigned char>::max() + 2U;
h1 += p[i];
}
uint32 h2 = 0;
p = (unsigned char *)&c;
for (size_t j = 0; j < sizeof(c); ++j) {
h2 *= std::numeric_limits<unsigned char>::max() + 2U;
h2 += p[j];
}
return (h1 + differ++) ^ h2;
}
inline void MTRand::save(uint32 *saveArray) const
{
uint32 *sa = saveArray;
const uint32 *s = state;
int i = N;
for (; i--; *sa++ = *s++) {
}
*sa = left;
}
inline void MTRand::load(uint32 *const loadArray)
{
uint32 *s = state;
uint32 *la = loadArray;
int i = N;
for (; i--; *s++ = *la++) {
}
left = *la;
pNext = &state[N - left];
}
inline std::ostream &operator<<(std::ostream &os, const MTRand &mtrand)
{
const MTRand::uint32 *s = mtrand.state;
int i = mtrand.N;
for (; i--; os << *s++ << "\t") {
}
return os << mtrand.left;
}
inline std::istream &operator>>(std::istream &is, MTRand &mtrand)
{
MTRand::uint32 *s = mtrand.state;
int i = mtrand.N;
for (; i--; is >> *s++) {
}
is >> mtrand.left;
mtrand.pNext = &mtrand.state[mtrand.N - mtrand.left];
return is;
}
// simple interface to mersenne twister
class RandomStream {
public:
inline RandomStream(long seed) : mtr(seed){};
~RandomStream()
{
}
/*! get a random number from the stream */
inline float getRandNorm(float mean, float var)
{
return mtr.randNorm(mean, var);
};
#if FLOATINGPOINT_PRECISION == 1
inline Real getReal()
{
return getFloat();
}
inline Real getReal(float min, float max)
{
return getFloat(min, max);
}
#else
inline Real getReal()
{
return getDouble();
}
inline Real getReal(double min, double max)
{
return getDouble(min, max);
}
#endif
inline Vec3 getVec3()
{
Real a = getReal(), b = getReal(), c = getReal();
return Vec3(a, b, c);
}
inline Vec3 getVec3Norm()
{
Vec3 a = getVec3();
normalize(a);
return a;
}
private:
MTRand mtr;
inline double getDouble(void)
{
return mtr.rand();
};
inline float getFloat(void)
{
return (float)mtr.rand();
};
inline double getDouble(double min, double max)
{
return mtr.rand(max - min) + min;
};
inline float getFloat(float min, float max)
{
return (float)(mtr.rand(max - min) + min);
};
};
} // namespace Manta
#endif