/usr/include/ITK-4.9/itkMersenneTwisterRandomVariateGenerator.h is in libinsighttoolkit4-dev 4.9.0-4ubuntu1.
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*
* Copyright Insight Software Consortium
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0.txt
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*
*=========================================================================*/
#ifndef itkMersenneTwisterRandomVariateGenerator_h
#define itkMersenneTwisterRandomVariateGenerator_h
#include "itkMacro.h"
#include "itkObjectFactory.h"
#include "itkRandomVariateGeneratorBase.h"
#include "itkIntTypes.h"
#include "vnl/vnl_math.h"
#include <climits>
#include <ctime>
namespace itk
{
namespace Statistics
{
/** \class MersenneTwisterRandomVariateGenerator
* \brief MersenneTwisterRandom random variate generator
*
* \warning This class's instance methods are NOT neither reentrant
* nor thread-safe, but static methods are both. That is to say you
* can use separate objects concurrently.
*
* This notice was included with the original implementation.
* The only changes made were to obfuscate the author's email addresses.
*
* MersenneTwister.h
* Mersenne Twister random number generator -- a C++ class MTRand
* Based on code by Makoto Matsumoto, Takuji Nishimura, and Shawn Cokus
* Richard J. Wagner v1.0 15 May 2003 rjwagner at writeme dot com
*
* The Mersenne Twister is an algorithm for generating random numbers. It
* was designed with consideration of the flaws in various other generators.
* The period, 2^19937-1, and the order of equidistribution, 623 dimensions,
* are far greater. The generator is also fast; it avoids multiplication and
* division, and it benefits from caches and pipelines. For more information
* see the inventors' web page at http:*www.math.keio.ac.jp/~matumoto/emt.html
*
* Reference
* M. Matsumoto and T. Nishimura, "Mersenne Twister: A 623-Dimensionally
* Equidistributed Uniform Pseudo-Random Number Generator", ACM Transactions on
* Modeling and Computer Simulation, Vol. 8, No. 1, January 1998, pp 3-30.
*
* Copyright (C) 1997 - 2002, Makoto Matsumoto and Takuji Nishimura,
* Copyright (C) 2000 - 2003, Richard J. Wagner
* All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions
* are met:
*
* 1. Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
*
* 2. Redistributions in binary form must reproduce the above copyright
* notice, this list of conditions and the following disclaimer in the
* documentation and/or other materials provided with the distribution.
*
* 3. The names of its contributors may not be used to endorse or promote
* products derived from this software without specific prior written
* permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
* "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
* LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
* A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
* CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
* EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
* PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
* PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
* LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
* NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
* SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*
* The original code included the following notice:
*
* When you use this, send an email to: matumoto at math dot keio dot ac dot jp
* with an appropriate reference to your work.
*
* It would be nice to CC:
* rjwagner at writeme dot com and Cokus at math dot washington dot edu
* when you write.
*
* \ingroup Common
* \ingroup ITKCommon
*
* \wiki
* \wikiexample{Utilities/MersenneTwisterRandomVariateGenerator,Random number generator}
* \endwiki
*/
class ITKCommon_EXPORT MersenneTwisterRandomVariateGenerator:
public RandomVariateGeneratorBase
{
public:
/** Standard class typedefs. */
typedef MersenneTwisterRandomVariateGenerator Self;
typedef RandomVariateGeneratorBase Superclass;
typedef SmartPointer< Self > Pointer;
typedef SmartPointer< const Self > ConstPointer;
typedef uint32_t IntegerType;
/** Run-time type information (and related methods). */
itkTypeMacro(MersenneTwisterRandomVariateGenerator,
RandomVariateGeneratorBase);
/** \brief Method for creation through the object factory.
*
* This method allocates a new instance of a Mersenne Twister,
* and initializes it with the seed from the global instance.
*/
static Pointer New();
/** returns the global Merseene Twister instance
*
* This method returns a Singleton of the Mersenne Twister.
* The seed is initialized from the wall clock, but can be
* set using SetSeed().
*/
static Pointer GetInstance();
/** Length of state vector */
itkStaticConstMacro(StateVectorLength, IntegerType, 624);
/** initialize with a simple IntegerType */
void Initialize(const IntegerType oneSeed);
/* Initialize with clock time */
void Initialize();
/** Get a random variate in the range [0, 1] */
double GetVariateWithClosedRange();
/** Get a random variate in the range [0, n] */
double GetVariateWithClosedRange(const double & n);
/** Get a range variate in the range [0, 1) */
double GetVariateWithOpenUpperRange();
/** Get a range variate in the range [0, n) */
double GetVariateWithOpenUpperRange(const double & n);
/** Get a range variate in the range (0, 1) */
double GetVariateWithOpenRange();
/** Get a range variate in the range (0, n) */
double GetVariateWithOpenRange(const double & n);
/** Get an integer variate in [0, 2^32-1] */
IntegerType GetIntegerVariate();
/** Get an integer variate in [0, n] for n < 2^32 */
IntegerType GetIntegerVariate(const IntegerType & n);
/** Access to 53-bit random numbers (capacity of IEEE double precision)
* in the range [0,1) */
double Get53BitVariate();
/* Access to a normal random number distribution
* TODO: Compare with vnl_sample_normal */
double GetNormalVariate(const double & mean = 0.0,
const double & variance = 1.0);
/* Access to a uniform random number distribution in the range [a, b)
* TODO: Compare with vnl_sample_uniform */
double GetUniformVariate(const double & a, const double & b);
/** get a variate in the range [0, 1]
* Do NOT use for CRYPTOGRAPHY without securely hashing several returned
* values together, otherwise the generator state can be learned after
* reading 624 consecutive values.
*/
virtual double GetVariate() ITK_OVERRIDE;
/** Same as GetVariate() */
double operator()();
/** Re-seeding functions with same behavior as initializers */
inline void SetSeed(const IntegerType oneSeed);
inline void SetSeed();
/** Return the current seed */
IntegerType GetSeed() { return this->m_Seed; };
/*
// Saving and loading generator state
void save( IntegerType* saveArray ) const; // to array of size SAVE
void load( IntegerType *const loadArray ); // from such array
*/
protected:
MersenneTwisterRandomVariateGenerator();
virtual ~MersenneTwisterRandomVariateGenerator();
virtual void PrintSelf(std::ostream & os, Indent indent) const ITK_OVERRIDE;
// period parameter
itkStaticConstMacro (M, unsigned int, 397);
IntegerType state[StateVectorLength]; // internal state
IntegerType *pNext; // next value to get from state
int left; // number of values left before reload
// needed
IntegerType m_Seed; // Seed value
/* Reload array with N new values */
void reload();
IntegerType hiBit(const IntegerType & u) const { return u & 0x80000000; }
IntegerType loBit(const IntegerType & u) const { return u & 0x00000001; }
IntegerType loBits(const IntegerType & u) const { return u & 0x7fffffff; }
IntegerType mixBits(const IntegerType & u, const IntegerType & v) const
{
return hiBit(u) | loBits(v);
}
IntegerType twist(const IntegerType & m, const IntegerType & s0, const IntegerType & s1) const
{
return m ^ ( mixBits(s0, s1) >> 1 ) ^ ( -static_cast<int32_t>(loBit(s1)) & 0x9908b0df );
}
static IntegerType hash(time_t t, clock_t c);
private:
/** Internal method to actually create a new object. */
static Pointer CreateInstance();
// Static/Global Variable need to be thread-safely accessed
static Pointer m_StaticInstance;
static SimpleFastMutexLock m_StaticInstanceLock;
static IntegerType m_StaticDiffer;
}; // end of class
// Declare inlined functions.... (must be declared in the header)
inline void
MersenneTwisterRandomVariateGenerator::Initialize(const IntegerType seed)
{
this->m_Seed = seed;
// 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.
IntegerType *s = state;
IntegerType *r = state;
IntegerType i = 1;
*s++ = seed & 0xffffffffUL;
for ( i = 1; i < MersenneTwisterRandomVariateGenerator::StateVectorLength; ++i )
{
*s++ = ( 1812433253UL * ( *r ^ ( *r >> 30 ) ) + i ) & 0xffffffffUL;
r++;
}
}
inline void
MersenneTwisterRandomVariateGenerator::reload()
{
// Generate N new values in state
// Made clearer and faster by Matthew Bellew
// matthew dot bellew at home dot com
// get rid of VS warning
int index = static_cast< int >(
M - MersenneTwisterRandomVariateGenerator::StateVectorLength );
IntegerType *p = state;
int i;
for ( i = MersenneTwisterRandomVariateGenerator::StateVectorLength - M; i--; ++p )
{
*p = twist(p[M], p[0], p[1]);
}
for ( i = M; --i; ++p )
{
*p = twist(p[index], p[0], p[1]);
}
*p = twist(p[index], p[0], state[0]);
left = MersenneTwisterRandomVariateGenerator::StateVectorLength, pNext = state;
}
inline void
MersenneTwisterRandomVariateGenerator::Initialize()
{
SetSeed();
}
inline void
MersenneTwisterRandomVariateGenerator::SetSeed(const IntegerType oneSeed)
{
// Seed the generator with a simple IntegerType
Initialize(oneSeed);
reload();
}
inline void
MersenneTwisterRandomVariateGenerator::SetSeed()
{
// use time() and clock() to generate a unlikely-to-repeat seed.
SetSeed( hash( time(ITK_NULLPTR), clock() ) );
}
/** Get an integer variate in [0, 2^32-1] */
inline MersenneTwisterRandomVariateGenerator::IntegerType
MersenneTwisterRandomVariateGenerator::GetIntegerVariate()
{
if ( left == 0 ) { reload(); }
--left;
IntegerType s1 = *pNext++;
s1 ^= ( s1 >> 11 );
s1 ^= ( s1 << 7 ) & 0x9d2c5680;
s1 ^= ( s1 << 15 ) & 0xefc60000;
return ( s1 ^ ( s1 >> 18 ) );
}
inline double
MersenneTwisterRandomVariateGenerator::GetVariateWithClosedRange()
{
return double( GetIntegerVariate() ) * ( 1.0 / 4294967295.0 );
}
/** Get a random variate in the range [0, n] */
inline double
MersenneTwisterRandomVariateGenerator::GetVariateWithClosedRange(
const double & n)
{
return GetVariateWithClosedRange() * n;
}
/** Get a range variate in the range [0, 1) */
inline double
MersenneTwisterRandomVariateGenerator::GetVariateWithOpenUpperRange()
{
return double( GetIntegerVariate() ) * ( 1.0 / 4294967296.0 );
}
/** Get a range variate in the range [0, n) */
inline double
MersenneTwisterRandomVariateGenerator::GetVariateWithOpenUpperRange(
const double & n)
{
return GetVariateWithOpenUpperRange() * n;
}
/** Get a range variate in the range (0, 1) */
inline double
MersenneTwisterRandomVariateGenerator::GetVariateWithOpenRange()
{
return ( double( GetIntegerVariate() ) + 0.5 ) * ( 1.0 / 4294967296.0 );
}
/** Get a range variate in the range (0, n) */
inline double
MersenneTwisterRandomVariateGenerator::GetVariateWithOpenRange(
const double & n)
{
return GetVariateWithOpenRange() * n;
}
inline MersenneTwisterRandomVariateGenerator::IntegerType
MersenneTwisterRandomVariateGenerator::GetIntegerVariate(
const IntegerType & n)
{
// Find which bits are used in n
// Optimized by Magnus Jonsson magnus at smartelectronix dot com
IntegerType 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]
IntegerType i;
do
{
i = GetIntegerVariate() & used; // toss unused bits to shorten search
}
while ( i > n );
return i;
}
/** Access to 53-bit random numbers (capacity of IEEE double precision)
* in the range [0,1) */
inline double
MersenneTwisterRandomVariateGenerator::Get53BitVariate()
{
IntegerType a = GetIntegerVariate() >> 5, b = GetIntegerVariate() >> 6;
return ( a * 67108864.0 + b ) * ( 1.0 / 9007199254740992.0 ); // by Isaku
// Wada
}
/* Access to a normal random number distribution */
// TODO: Compare with vnl_sample_normal
inline double
MersenneTwisterRandomVariateGenerator::GetNormalVariate(
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 = std::sqrt(-2.0 * std::log( 1.0 - GetVariateWithOpenRange() ) * variance);
double phi = 2.0 * vnl_math::pi
* GetVariateWithOpenUpperRange();
return mean + r *std::cos(phi);
}
/* Access to a uniform random number distribution */
// TODO: Compare with vnl_sample_uniform
inline double
MersenneTwisterRandomVariateGenerator::GetUniformVariate(
const double & a, const double & b)
{
double u = GetVariateWithOpenUpperRange();
return ( ( 1.0 - u ) * a + u * b );
}
inline double
MersenneTwisterRandomVariateGenerator::GetVariate()
{
return GetVariateWithClosedRange();
}
inline double
MersenneTwisterRandomVariateGenerator::operator()()
{
return GetVariate();
}
/* Change log from MTRand.h */
// Change log:
//
// v0.1 - First release on 15 May 2000
// - Based on code by Makoto Matsumoto, Takuji Nishimura, and Shawn Cokus
// - Translated from C to C++
// - Made completely ANSI compliant
// - Designed convenient interface for initialization, seeding, and
// obtaining numbers in default or user-defined ranges
// - Added automatic seeding from /dev/urandom or time() and clock()
// - Provided functions for saving and loading generator state
//
// v0.2 - Fixed bug which reloaded generator one step too late
//
// v0.3 - Switched to clearer, faster reload() code from Matthew Bellew
//
// v0.4 - Removed trailing newline in saved generator format to be consistent
// with output format of built-in types
//
// v0.5 - Improved portability by replacing static const int's with enum's and
// clarifying return values in seed(); suggested by Eric Heimburg
// - Removed MAXINT constant; use 0xffffffffUL instead
//
// v0.6 - Eliminated seed overflow when uint32 is larger than 32 bits
// - Changed integer [0,n] generator to give better uniformity
//
// v0.7 - Fixed operator precedence ambiguity in reload()
// - Added access for real numbers in (0,1) and (0,n)
//
// v0.8 - Included time.h header to properly support time_t and clock_t
//
// v1.0 - Revised seeding to match 26 Jan 2002 update of Nishimura and Matsumoto
// - Allowed for seeding with arrays of any length
// - Added access for real numbers in [0,1) with 53-bit resolution
// - Added access for real numbers from normal (Gaussian) distributions
// - Increased overall speed by optimizing twist()
// - Doubled speed of integer [0,n] generation
// - Fixed out-of-range number generation on 64-bit machines
// - Improved portability by substituting literal constants for long enum's
// - Changed license from GNU LGPL to BSD
} // end of namespace Statistics
} // end of namespace itk
#endif
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