1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
|
/*=========================================================================
Program: Insight Segmentation & Registration Toolkit
Module: $RCSfile: itkNormalVariateGenerator.h,v $
Language: C++
Date: $Date: 2009-03-04 15:24:04 $
Version: $Revision: 1.9 $
Copyright (c) Insight Software Consortium. All rights reserved.
See ITKCopyright.txt or http://www.itk.org/HTML/Copyright.htm for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
PURPOSE. See the above copyright notices for more information.
=========================================================================*/
#ifndef __itkNormalVariateGenerator_h
#define __itkNormalVariateGenerator_h
#include "itkObjectFactory.h"
#include "itkRandomVariateGeneratorBase.h"
namespace itk {
namespace Statistics {
/** \class NormalVariateGenerator
* \brief Normal random variate generator
*
* This generation method was initially developed and implemented by
* Martin Styner, University of North Carolina at Chapel Hill,
* and his colleagues.
*
* You should run Initialize() function before call GetNormalVariate()
* function.
*
* The followings are original comments.
*
* Revision date 31 May 1996
* This is a revised version of the algorithm decribed in
*
* ACM Transactions on Mathematical Software, Vol 22, No 1
* March 1996, pp 119-127.
*
* It is somewhat faster, and uses less memory as the vector of variates is
* updated in-situ. It has passed all the same statistical tests as decribed
* in the TOMS article, plus others. Seems OK so far.
*
* Works well with total pool of 1024 variates, and does not need
* two vectors of this size, so does less damage to cache.
* Has been tested for frequency of tail values which
* should occur once in a million. OK. Other usual tests OK.
* About 13 % faster than TOMS version.
*
* FAST GENERATOR OF PSEUDO-RANDOM UNIT NORMAL VARIATES
*
* C.S.Wallace, Monash University, 1994
*
* To use this code, files needing to call the generator should #include the
* file "FastNorm.h" and be linked with the maths library (-lm)
* FastNorm.h contains declaration of the initialization routine
* 'initnorm()', definition of a macro 'FastGauss' used to generate variates,
* and three variables used in the macro.
* Read below for calling conventions.
*
* THIS CODE ASSUMES TWO'S-COMPLEMENT 32-BIT INTEGER ARITHMATIC. IT ALSO
* ASSUMES THE 'C' COMPILER COMPILES THE LEFT-SHIFT OPERATOR "<<" AS A LOGICAL
* SHIFT, DISCARDING THE SIGN DIGIT AND SHIFTING IN ZEROS ON THE RIGHT, SO
* " X << 1" IS EQUIVALENT TO " X+X ". IT ALSO ASSUMES THE RIGHT-SHIFT
* OPERATOR ">>" IS SIGN-PRESERVING, SO ( -2 >> 1) = -1, ( -1>>1) = -1.
*
* A fast generator of pseudo-random variates from the unit Normal
* distribution. It keeps a pool of about 1000 variates, and generates new
* ones by picking 4 from the pool, rotating the 4-vector with these as its
* components, and replacing the old variates with the components of the
* rotated vector.
*
*
* The program should initialize the generator by calling
* initnorm(seed)
* with seed a int integer seed value. Different seed values will give
* different sequences of Normals.
* Then, wherever the program needs a new Normal variate, it should
* use the macro FastGauss, e.g. in statements like:
* x = FastGauss; (Sets x to a random Normal value)
*
*
* \ingroup Statistics
*/
class ITK_EXPORT NormalVariateGenerator :
public RandomVariateGeneratorBase
{
public:
/** Standard class typedefs. */
typedef NormalVariateGenerator Self;
typedef RandomVariateGeneratorBase Superclass;
typedef SmartPointer<Self> Pointer;
typedef SmartPointer<const Self> ConstPointer;
/** Run-time type information (and related methods). */
itkTypeMacro(NormalVariateGenerator,
RandomVariateGeneratorBase );
/** Method for creation through the object factory. */
itkNewMacro(Self);
/** generate random number table */
void Initialize(int randomSeed);
/** get a variate using FastNorm function */
double GetVariate();
protected:
NormalVariateGenerator();
virtual ~NormalVariateGenerator();
virtual void PrintSelf(std::ostream& os, Indent indent) const;
/** get a variate */
double FastNorm (void);
private:
double Scale;
double Rscale;
double Rcons;
int ELEN;
int LEN;
int LMASK;
int TLEN;
int gaussfaze, *gausssave;
double GScale;
int* vec1;
int nslew;
int irs, lseed;
double chic1, chic2, actualRSD;
}; // end of class
} // end of namespace Statistics
} // end of namespace itk
#endif
|
