Support for XISF

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// ____ ______ __
// / __ \ / ____// /
// / /_/ // / / /
// / ____// /___ / /___ PixInsight Class Library
// /_/ \____//_____/ PCL 2.4.23
// ----------------------------------------------------------------------------
// pcl/Random.h - Released 2022-03-12T18:59:29Z
// ----------------------------------------------------------------------------
// This file is part of the PixInsight Class Library (PCL).
// PCL is a multiplatform C++ framework for development of PixInsight modules.
//
// Copyright (c) 2003-2022 Pleiades Astrophoto S.L. All Rights Reserved.
//
// Redistribution and use in both source and binary forms, with or without
// modification, is permitted provided that the following conditions are met:
//
// 1. All redistributions of source code must retain the above copyright
// notice, this list of conditions and the following disclaimer.
//
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// "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED
// TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
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// CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
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// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
// POSSIBILITY OF SUCH DAMAGE.
// ----------------------------------------------------------------------------
#ifndef __PCL_Random_h
#define __PCL_Random_h
/// \file pcl/Random.h
#include <pcl/Defs.h>
#include <pcl/Diagnostics.h>
#include <pcl/AutoPointer.h>
#include <pcl/Vector.h>
namespace pcl
{
// ----------------------------------------------------------------------------
/*!
* \defgroup random_numbers Random Number Generation
*/
/*!
* Returns a 64-bit random generator seed.
*
* On UNIX/Linux platforms, this function reads the /dev/urandom system device
* to acquire a high-quality random seed. On Windows, the rand_s() CRT function
* is invoked with the same purpose.
*
* In the extremely rare cases where a system random seed cannot be obtained,
* the time() function is used to get a unique initialization value.
*
* Subsequent calls to this function are guaranteed to return unique values.
*
* This function is thread-safe. It can be safely called from multiple
* execution threads running concurrently.
*
* \ingroup random_numbers
*/
extern uint64 RandomSeed64();
/*!
* Returns a 32-bit random generator seed.
*
* This function simply calls RandomSeed64() and returns the XOR combination of
* the 32-bit words in the 64-bit random seed.
*
* As RandomSeed64(), this function is thread-safe and is guaranteed to return
* a unique value on each call.
*
* \ingroup random_numbers
*/
inline uint32 RandomSeed32()
{
union { uint64 u64; uint32 u32[ 2 ]; } seed;
seed.u64 = RandomSeed64();
return seed.u32[0] ^ seed.u32[1];
}
// ----------------------------------------------------------------------------
class FastMersenneTwister;
// ----------------------------------------------------------------------------
/*!
* \class RandomNumberGenerator
* \brief Mersenne Twister (MT19937) pseudo-random number generator.
*
* \deprecated This class has been deprecated. Use the XoShiRo256ss and
* XoRoShiRo1024ss classes for all newly produced code.
*
* Generation of pseudo-random numbers with user-selectable range and
* probability distributions.
*
* This generator supports the uniform, normal (Gaussian) and Poisson
* distributions. In addition, the upper range of generated uniform deviates
* can be arbitrarily defined.
*
* %RandomNumberGenerator is a functional class. The function call operator()()
* returns pseudo-random numbers in the range [0,ymax], where ymax is the
* user-defined arbitrary upper range.
*
* Example of use:
*
* \code
* RandomNumberGenerator R, R1( 10 ); // R's ymax = 1, R1's ymax = 10
* // ...
* double y = R(); // y = random uniform deviate in the range [0,1]
* double z = R1(); // z = random uniform deviate in the range [0,10]
* \endcode
*
* <b>References</b>
*
* Based on an adaptation of SIMD-oriented Fast Mersenne Twister (SFMT) by
* Mutsuo Saito and Makoto Matsumoto (Hiroshima University).
*
* Currently PCL implements a SFMT generator with a period of 2^19937-1.
*
* SFMT Copyright (C) 2006, 2007 Mutsuo Saito, Makoto Matsumoto and Hiroshima
* University. All rights reserved.
*
* \ingroup random_numbers
*/
class PCL_CLASS RandomNumberGenerator
{
public:
/*!
* Constructs a %RandomNumberGenerator object.
*
* \param ymax Upper bound of uniform deviates. The function call
* operator double operator()() and the Uniform() member
* function (which are synonyms) will return uniform
* pseudo-random deviates in the range [0,ymax]. The default
* value is 1.0.
*
* \param seed 32-bit initialization seed. If this parameter is zero, a
* unique random seed will be generated automatically. The
* default value is zero.
*/
RandomNumberGenerator( double ymax = 1.0, uint32 seed = 0 );
/*!
* Destroys a %RandomNumberGenerator object.
*/
virtual ~RandomNumberGenerator();
/*!
* Generates a floating point uniform deviate in the range [0,UpperBound()]
*/
double operator ()()
{
return m_rmax*Rand32();
}
/*!
* Generates a 32-bit unsigned integer uniform deviate.
*/
uint32 Rand32();
/*!
* Generates a floating point uniform deviate in the range [0,1] (i.e.,
* ignoring UpperBound()).
*/
double Rand1()
{
return double( Rand32() )/uint32_max;
}
/*!
* Generates a floating point uniform deviate in the range [0,UpperBound()]
*
* This is a convenience alias for operator()().
*/
double Uniform()
{
return operator()();
}
/*!
* Generates a floating point normal deviate with the specified \a mean and
* standard deviation \a sigma.
*/
double Normal( double mean = 0, double sigma = 1 );
/*!
* Generates a floating point normal deviate with the specified \a mean and
* standard deviation \a sigma.
*
* This is a convenience alias for Normal( mean, sigma ).
*/
double Gaussian( double mean = 0, double sigma = 1 )
{
return Normal( mean, sigma );
}
/*!
* Generates a discrete random deviate from a Poisson distribution with the
* specified expected value \a lambda.
*/
int Poisson( double lambda );
/*!
* Returns the current upper bound of this random number generator.
*/
double UpperBound() const
{
return m_ymax;
}
/*!
* Sets the upper bound \a ymax > 0 for this random number generator.
*/
void SetUpperBound( double ymax )
{
PCL_PRECONDITION( ymax > 0 )
PCL_PRECONDITION( 1 + ymax != 1 )
m_rmax = (m_ymax = ymax)/double( uint32_max );
m_normal = false;
}
private:
AutoPointer<FastMersenneTwister> m_generator;
double m_ymax;
double m_rmax;
bool m_normal;
double m_vs; // second result from BoxMuller transform
DVector m_lambda; // precalculated for current Poisson lambda
};
// ----------------------------------------------------------------------------
/*!
* \class XorShift1024
* \brief Implementation of the XorShift1024* pseudo-random number generator.
*
* \deprecated This class has been deprecated. Use the XoShiRo256ss and
* XoRoShiRo1024ss classes for all newly produced code.
*
* Generation of pseudo-random uniform deviates using the xorshift1024*
* generator developed in 2014 by Sebastiano Vigna. This is a fast, top-quality
* generator with a period of 2^1024-1, passing strong statistical test suites.
*
* Examples of use:
*
* \code
* XorShift1024 X; // initialized automatically
* // ...
* double x = X(); // x = random uniform deviate in the range [0,1)
* uint64 y = X.UI64(); // y = 64-bit unsigned integer random uniform deviate
* uint32 z = X.UI32(); // z = 32-bit unsigned integer random uniform deviate
* uint32 t = X.UIN( 100 ); // t = integer uniform deviate in the range [0,99]
* \endcode
*
* <b>References</b>
*
* Sebastiano Vigna (2014), <em>An experimental exploration of Marsaglia's
* xorshift generators, scrambled</em>, arXiv:1402.6246
*
* Sebastiano Vigna (2014), <em>Further scramblings of Marsaglia's xorshift
* generators</em>, arXiv:1404.0390
*
* See also: http://xorshift.di.unimi.it/
*
* \ingroup random_numbers
*/
class PCL_CLASS XorShift1024
{
public:
/*!
* Constructs a %XorShift1024 pseudo-random number generator.
*
* \param seed 64-bit initialization seed. If this parameter is zero, a
* unique random seed will be generated automatically. The
* default value is zero.
*/
XorShift1024( uint64 seed = 0 ) noexcept( false )
{
Initialize( seed );
}
/*!
* Returns a double precision uniform random deviate in the [0,1) range.
*/
double operator ()() noexcept
{
return 5.4210108624275221703311e-20 * UI64(); // 1.0/(2^64 -1)
}
/*!
* Returns a 64-bit unsigned integer uniform random deviate.
*/
uint64 UI64() noexcept
{
uint64 s0 = m_s[m_p];
uint64 s1 = m_s[m_p = (m_p + 1) & 15];
s1 ^= s1 << 31; // a
s1 ^= s1 >> 11; // b
s0 ^= s0 >> 30; // c
return (m_s[m_p] = s0 ^ s1) * 1181783497276652981ull;
}
/*!
* Returns a 32-bit unsigned integer uniform random deviate.
*/
uint32 UI32() noexcept
{
return uint32( UI64() );
}
/*!
* Returns a 64-bit unsigned integer uniform random deviate in the range
* [0,n-1].
*/
uint64 UI64N( uint64 n ) noexcept
{
return UI64() % n;
}
/*!
* Returns an unsigned integer uniform random deviate in the range [0,n-1].
*/
uint32 UIN( uint32 n ) noexcept
{
return UI64() % n;
}
/*!
* A synonym for UIN().
*/
uint32 UI32N( uint32 n ) noexcept
{
return UIN( n );
}
/*!
* Reinitializes this generator with a new \a seed.
*
* If the specified \a seed is zero, a unique, high-quality random seed will
* be generated automatically by calling RandomSeed64().
*/
void Initialize( uint64 x )
{
if ( x == 0 )
x = RandomSeed64();
// Use a xorshift64* generator to initialize the state space.
for ( int i = 0; i < 16; ++i )
{
x ^= x >> 12; // a
x ^= x << 25; // b
x ^= x >> 27; // c
m_s[i] = x * 2685821657736338717ull;
}
m_p = 0;
}
private:
uint64 m_s[ 16 ]; // state space
int m_p; // current index
};
// ----------------------------------------------------------------------------
/*!
* \class XoRoShiRo1024ss
* \brief Base class of xoshiro and xoroshiro pseudo-random number generators.
*/
class PCL_CLASS XoShiRoBase
{
public:
/*!
* Default constructor.
*/
XoShiRoBase() = default;
protected:
/*!
* \internal
* The left rotation function used by the generator.
*/
static uint64 RotL( const uint64 x, int k ) noexcept
{
return (x << k) | (x >> (64 - k));
}
/*!
* \internal
* The SplitMix64 generator used for state space initialization, as
* recommended by Blackman/Vigna.
*/
static uint64 SplitMix64( uint64& x ) noexcept
{
uint64 z = (x += 0x9e3779b97f4a7c15);
z = (z ^ (z >> 30)) * 0xbf58476d1ce4e5b9;
z = (z ^ (z >> 27)) * 0x94d049bb133111eb;
return z ^ (z >> 31);
}
/*!
* \internal
* Conversion of a 64-bit unsigned inteter to 64-bit floating point with
* uniform probability over the entire 53-bit significant digits.
* See: http://prng.di.unimi.it/#remarks
*/
static double UI64ToDouble( uint64 x ) noexcept
{
return (x >> 11) * 0x1.0p-53;
}
};
// ----------------------------------------------------------------------------
/*!
* \class XoShiRo256ss
* \brief Implementation of the xoshiro256** pseudo-random number generator.
*
* Generation of pseudo-random uniform deviates using the xoroshiro1024**
* generator developed in 2019 by David Blackman and Sebastiano Vigna. This is
* a fast, top-quality generator with a period of 2^256-1, passing strong
* statistical test suites&mdash;actually, it passes all tests we are aware of.
*
* Examples of use:
*
* \code
* XoShiRo256ss X; // initialized automatically
* // ...
* double x = X(); // x = random uniform deviate in the range [0,1)
* uint64 y = X.UI64(); // y = 64-bit unsigned integer random uniform deviate
* uint32 z = X.UI32(); // z = 32-bit unsigned integer random uniform deviate
* uint32 t = X.UIN( 100 ); // t = integer uniform deviate in the range [0,99]
* \endcode
*
* <b>References</b>
*
* David Blackman and Sebastiano Vigna (2019), <em>Scrambled linear
* pseudorandom number generators</em> (preprint).
*
* See also: http://prng.di.unimi.it/
*
* \ingroup random_numbers
*/
class PCL_CLASS XoShiRo256ss : public XoShiRoBase
{
public:
/*!
* Constructs a %XoShiRo256ss pseudo-random number generator.
*
* \param seed 64-bit initialization seed. If this parameter is zero, a
* unique random seed will be generated automatically. The
* default value is zero.
*/
XoShiRo256ss( uint64 seed = 0 ) noexcept( false )
{
Initialize( seed );
}
/*!
* Returns a double precision uniform random deviate in the [0,1) range.
*/
double operator ()() noexcept
{
return UI64ToDouble( UI64() );
}
/*!
* Returns a 64-bit unsigned integer uniform random deviate.
*/
uint64 UI64() noexcept
{
const uint64 result = RotL( m_s[1]*5, 7 ) * 9;
const uint64 t = m_s[1] << 17;
m_s[2] ^= m_s[0];
m_s[3] ^= m_s[1];
m_s[1] ^= m_s[2];
m_s[0] ^= m_s[3];
m_s[2] ^= t;
m_s[3] = RotL( m_s[3], 45 );
return result;
}
/*!
* Returns a 32-bit unsigned integer uniform random deviate.
*/
uint32 UI32() noexcept
{
return uint32( UI64() );
}
/*!
* Returns a 64-bit unsigned integer uniform random deviate in the range
* [0,n-1].
*/
uint64 UI64N( uint64 n ) noexcept
{
return UI64() % n;
}
/*!
* Returns an unsigned integer uniform random deviate in the range [0,n-1].
*/
uint32 UIN( uint32 n ) noexcept
{
return UI64() % n;
}
/*!
* A synonym for UIN().
*/
uint32 UI32N( uint32 n ) noexcept
{
return UIN( n );
}
/*!
* Reinitializes this generator with a new \a seed.
*
* If the specified \a seed is zero, a unique, high-quality random seed will
* be generated automatically by calling RandomSeed64().
*/
void Initialize( uint64 x )
{
if ( x == 0 )
x = RandomSeed64();
// Use a SplitMix64 generator to initialize the state space.
for ( int i = 0; i < 4; ++i )
m_s[i] = SplitMix64( x );
}
private:
uint64 m_s[ 4 ];
};
// ----------------------------------------------------------------------------
/*!
* \class XoRoShiRo1024ss
* \brief Implementation of the xoroshiro1024** pseudo-random number generator.
*
* Generation of pseudo-random uniform deviates using the xoroshiro1024**
* generator developed in 2019 by David Blackman and Sebastiano Vigna. This is
* a fast, top-quality generator with a period of 2^1024-1, passing strong
* statistical test suites&mdash;actually, it passes all tests we are aware of.
*
* Examples of use:
*
* \code
* XoRoShiRo1024ss X; // initialized automatically
* // ...
* double x = X(); // x = random uniform deviate in the range [0,1)
* uint64 y = X.UI64(); // y = 64-bit unsigned integer random uniform deviate
* uint32 z = X.UI32(); // z = 32-bit unsigned integer random uniform deviate
* uint32 t = X.UIN( 100 ); // t = integer uniform deviate in the range [0,99]
* \endcode
*
* <b>References</b>
*
* David Blackman and Sebastiano Vigna (2019), <em>Scrambled linear
* pseudorandom number generators</em> (preprint).
*
* See also: http://prng.di.unimi.it/
*
* \ingroup random_numbers
*/
class PCL_CLASS XoRoShiRo1024ss : public XoShiRoBase
{
public:
/*!
* Constructs a %XoRoShiRo1024ss pseudo-random number generator.
*
* \param seed 64-bit initialization seed. If this parameter is zero, a
* unique random seed will be generated automatically. The
* default value is zero.
*/
XoRoShiRo1024ss( uint64 seed = 0 ) noexcept( false )
{
Initialize( seed );
}
/*!
* Returns a double precision uniform random deviate in the [0,1) range.
*/
double operator ()() noexcept
{
return UI64ToDouble( UI64() );
}
/*!
* Returns a 64-bit unsigned integer uniform random deviate.
*/
uint64 UI64() noexcept
{
const int q = m_p;
const uint64 s0 = m_s[m_p = (m_p + 1) & 15];
uint64 s15 = m_s[q];
const uint64 result = RotL( s0*5, 7 ) * 9;
s15 ^= s0;
m_s[q] = RotL( s0, 25 ) ^ s15 ^ (s15 << 27);
m_s[m_p] = RotL( s15, 36 );
return result;
}
/*!
* Returns a 32-bit unsigned integer uniform random deviate.
*/
uint32 UI32() noexcept
{
return uint32( UI64() );
}
/*!
* Returns a 64-bit unsigned integer uniform random deviate in the range
* [0,n-1].
*/
uint64 UI64N( uint64 n ) noexcept
{
return UI64() % n;
}
/*!
* Returns an unsigned integer uniform random deviate in the range [0,n-1].
*/
uint32 UIN( uint32 n ) noexcept
{
return UI64() % n;
}
/*!
* A synonym for UIN().
*/
uint32 UI32N( uint32 n ) noexcept
{
return UIN( n );
}
/*!
* Reinitializes this generator with a new \a seed.
*
* If the specified \a seed is zero, a unique, high-quality random seed will
* be generated automatically by calling RandomSeed64().
*/
void Initialize( uint64 x )
{
if ( x == 0 )
x = RandomSeed64();
// Use a SplitMix64 generator to initialize the state space.
for ( int i = 0; i < 16; ++i )
m_s[i] = SplitMix64( x );
m_p = 0;
}
private:
uint64 m_s[ 16 ];
int m_p;
};
// ----------------------------------------------------------------------------
/*!
* \class NormalRandomDeviates
* \brief Generation of random normal (Gaussian) deviates.
* \ingroup random_numbers
*/
template <class RNG>
class PCL_CLASS NormalRandomDeviates
{
public:
/*!
* Constructs a %NormalRandomDeviates objects using the specified
* pseudo-random number generator \a R.
*/
NormalRandomDeviates( RNG& R ) noexcept( false )
: m_R( R )
{
}
/*!
* Returns a random deviate from a Gaussian distribution with zero mean and
* unit standard deviation.
*/
double operator ()() noexcept
{
/*
* Marsaglia polar method.
*/
double x;
if ( m_first )
{
do
{
double u1 = m_R();
double u2 = m_R();
m_v1 = 2*u1 - 1;
m_v2 = 2*u2 - 1;
m_s = m_v1*m_v1 + m_v2*m_v2;
}
while ( m_s >= 1 || m_s <= std::numeric_limits<double>::epsilon() );
x = m_v1 * Sqrt( -2*Ln( m_s )/m_s );
}
else
x = m_v2 * Sqrt( -2*Ln( m_s )/m_s );
m_first = !m_first;
return x;
}
private:
RNG& m_R;
double m_v1 = 0;
double m_v2 = 0;
double m_s = 0;
bool m_first = true;
};
// ----------------------------------------------------------------------------
/*!
* \class PoissonRandomDeviates
* \brief Generation of random Poisson deviates.
* \ingroup random_numbers
*/
template <class RNG>
class PCL_CLASS PoissonRandomDeviates
{
public:
/*!
* Constructs a %PoissonRandomDeviates objects using the specified
* pseudo-random number generator \a R.
*/
PoissonRandomDeviates( RNG& R ) noexcept( false )
: m_R( R )
{
}
/*!
* Returns a random Poisson deviate for the specified \a value.
*/
int operator ()( double value ) noexcept
{
if ( value < 30 )
{
/*
* Implementation of the algorithm by Donald E. Knuth, 1969.
*
* This algorithm is slow (unusable) for large values.
*/
double p = 1, L = Exp( -value );
int k = 0;
do
{
++k;
p *= m_R();
}
while ( p > L );
return k-1;
}
/*
* Code adapted from 'Random number generation in C++', by John D. Cook:
*
* https://www.johndcook.com/blog/cpp_random_number_generation/
*
* The algorithm is from "The Computer Generation of Poisson Random
* Variables" by A. C. Atkinson, Journal of the Royal Statistical
* Society Series C (Applied Statistics) Vol. 28, No. 1. (1979)
*
* This algorithm is slow (unusable) for small values.
*/
double c = 0.767 - 3.36/value;
double beta = Const<double>::pi()/Sqrt( 3*value );
double alpha = beta*value;
double k = Ln( c ) - value - Ln( beta );
for ( ;; )
{
double u = m_R();
double x = (alpha - Ln( (1 - u)/u ))/beta;
int n = int( Floor( x + 0.5 ) );
if ( n < 0 )
continue;
double v = m_R();
double y = alpha - beta*x;
double temp = 1 + Exp( y );
double lhs = y + Ln( v/temp/temp );
double rhs = k + n*Ln( value ) - LnFactorial( n );
if ( lhs <= rhs )
return n;
}
}
private:
RNG& m_R;
};
// ----------------------------------------------------------------------------
/*!
* \class GammaRandomDeviates
* \brief Generation of random gamma deviates.
* \ingroup random_numbers
*/
template <class RNG>
class PCL_CLASS GammaRandomDeviates
{
public:
/*!
* Constructs a %GammaRandomDeviates objects using the specified
* pseudo-random number generator \a R.
*/
GammaRandomDeviates( RNG& R, double shape = 1, double scale = 1 ) noexcept( false )
: m_R( R )
, m_shape( shape )
, m_scale( scale )
, m_normal( R )
{
if ( m_shape <= 0 )
throw Error( "GammaRandomDeviates(): The function shape parameter must be > 0." );
if ( m_scale <= 0 )
throw Error( "GammaRandomDeviates(): The scale parameter must be > 0." );
m_d = ((m_shape >= 1) ? m_shape : m_shape + 1) - 1.0/3.0;
m_c = 1/Sqrt( 9*m_d );
}
/*!
* Returns a random deviate from a Gaussian distribution with zero mean and
* unit standard deviation.
*/
double operator ()() noexcept
{
/*
* Code adapted from 'Random number generation in C++', by John D. Cook:
* https://www.johndcook.com/blog/cpp_random_number_generation/
*
* Implementation based on "A Simple Method for Generating Gamma
* Variables" by George Marsaglia and Wai Wan Tsang. ACM Transactions on
* Mathematical Software Vol 26, No 3, September 2000, pages 363-372.
*/
for ( ;; )
{
double x, v;
do
{
x = m_normal();
v = 1 + m_c*x;
}
while ( v <= 0 );
v = v*v*v;
double u = m_R();
double xsquared = x*x;
if ( u < 1 - 0.0331*xsquared*xsquared || Ln( u ) < 0.5*xsquared + m_d*(1 - v + Ln( v )) )
{
double g = m_scale*m_d*v;
if ( m_shape < 1 )
g *= Pow( m_R(), 1/m_shape );
return g;
}
}
}
private:
RNG& m_R;
double m_shape;
double m_scale;
double m_d;
double m_c;
NormalRandomDeviates<RNG> m_normal;
};
// ----------------------------------------------------------------------------
} // pcl
#endif // __PCL_Random_h
// ----------------------------------------------------------------------------
// EOF pcl/Random.h - Released 2022-03-12T18:59:29Z