hxrand.cpp

linux下的一款播放器

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/*
 * 
 * (c) Copyright 1989 OPEN SOFTWARE FOUNDATION, INC.
 * (c) Copyright 1989 HEWLETT-PACKARD COMPANY
 * (c) Copyright 1989 DIGITAL EQUIPMENT CORPORATION
 * To anyone who acknowledges that this file is provided "AS IS"
 * without any express or implied warranty:
 *                 permission to use, copy, modify, and distribute this
 * file for any purpose is hereby granted without fee, provided that
 * the above copyright notices and this notice appears in all source
 * code copies, and that none of the names of Open Software
 * Foundation, Inc., Hewlett-Packard Company, or Digital Equipment
 * Corporation be used in advertising or publicity pertaining to
 * distribution of the software without specific, written prior
 * permission.  Neither Open Software Foundation, Inc., Hewlett-
 * Packard Company, nor Digital Equipment Corporation makes any
 * representations about the suitability of this software for any
 * purpose.
 * 
 */

/****************************************************************************
**
**    U U I D   T R U E   R A N D O M   N U M B E R   G E N E R A T O R
**
*****************************************************************************
**
** This random number generator (RNG) was found in the ALGORITHMS Notesfile.
**
** (Note 16.7, July 7, 1989 by Robert (RDVAX::)Gries, Cambridge Research Lab,
**  Computational Quality Group)
**
** It is really a "Multiple Prime Random Number Generator" (MPRNG) and is
** completely discussed in reference #1 (see below).
**
**   References:
**   1) "The Multiple Prime Random Number Generator" by Alexander Hass
**      pp. 368 to 381 in ACM Transactions on Mathematical Software,
**      December, 1987
**   2) "The Art of Computer Programming: Seminumerical Algorithms
**      (vol 2)" by Donald E. Knuth, pp. 39 to 113.
**
** A summary of the notesfile entry follows:
**
** Gries discusses the two RNG's available for ULTRIX-C.  The default RNG
** uses a Linear Congruential Method (very popular) and the second RNG uses
** a technique known as a linear feedback shift register.
**
** The first (default) RNG suffers from bit-cycles (patterns/repetition),
** ie. it's "not that random."
**
** While the second RNG passes all the emperical tests, there are "states"
** that become "stable", albeit contrived.
**
** Gries then presents the MPRNG and says that it passes all emperical
** tests listed in reference #2.  In addition, the number of calls to the
** MPRNG before a sequence of bit position repeats appears to have a normal
** distribution.
**
** Note (mbs): I have coded the Gries's MPRNG with the same constants that
** he used in his paper.  I have no way of knowing whether they are "ideal"
** for the range of numbers we are dealing with.
**
****************************************************************************/

#include "hxtypes.h"
#include "hxrand.h"
#include "hxtick.h"

#ifdef _WINDOWS
#include <windows.h>
#endif

#include "hxheap.h"
#ifdef _DEBUG
#undef HX_THIS_FILE		
static const char HX_THIS_FILE[] = __FILE__;
#endif

/*
 * optimal/recommended starting values according to the reference
 */
#define RAND_M_INIT	    971;      
#define RAND_IA_INIT	    11113;    
#define RAND_IB_INIT	    104322;   
#define RAND_IRAND_INIT	    4181;

CMultiplePrimeRandom::CMultiplePrimeRandom()
{
    m_rand_m	    = RAND_M_INIT;      
    m_rand_ia	    = RAND_IA_INIT;    
    m_rand_ib	    = RAND_IB_INIT;   
    m_rand_irand    = RAND_IRAND_INIT;
    SetSeed(HX_GET_TICKCOUNT());
}

CMultiplePrimeRandom::CMultiplePrimeRandom(ULONG32 seed)
{
    m_rand_m	    = RAND_M_INIT;      
    m_rand_ia	    = RAND_IA_INIT;    
    m_rand_ib	    = RAND_IB_INIT;   
    m_rand_irand    = RAND_IRAND_INIT;
    SetSeed(seed);
}

void CMultiplePrimeRandom::SetSeed(ULONG32 seed)
{
    // seed the generator
    m_rand_irand += seed; 
}

ULONG32 CMultiplePrimeRandom::GetRandomNumber(void)
{
    m_rand_m += 7;
    m_rand_ia += 1907;
    m_rand_ib += 73939;

    if (m_rand_m >= 9973) m_rand_m -= 9871;
    if (m_rand_ia >= 99991) m_rand_ia -= 89989;
    if (m_rand_ib >= 224729) m_rand_ib -= 96233;

    m_rand_irand = (m_rand_irand * m_rand_m) + m_rand_ia + m_rand_ib;

    return m_rand_irand;
}