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/* RCSid $Id: pmaprand.h,v 2.7 2016/05/17 17:39:47 rschregle Exp $ */
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/*
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======================================================================
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Random number generators for photon distribution
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Roland Schregle (roland.schregle@{hslu.ch, gmail.com})
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(c) Fraunhofer Institute for Solar Energy Systems,
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(c) Lucerne University of Applied Sciences and Arts,
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supported by the Swiss National Science Foundation (SNSF, #147053)
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======================================================================
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$Id: pmaprand.h,v 2.7 2016/05/17 17:39:47 rschregle Exp $
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*/
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#ifndef PMAPRAND_H
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#define PMAPRAND_H
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/* According to the analytical validation, skipping sequential samples
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* when sharing a single RNG among multiple sampling domains introduces
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* overlapping photon rays (reported as 'duplicate keys' when building
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* the underlying data structure) and therefore bias. This is aggravated
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* when running parallel photon distribution subprocesses, where photon
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* rays from different subprocesses may correlate.
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* We therefore maintain a separate RNG state for each sampling domain
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* (e.g. photon emission, scattering, and russian roulette). With
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* multiprocessing, each subprocess has its own instance of the RNG
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* state, which is independently seeded for decorellation -- see
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* distribPhotons() and distribPhotonContrib().
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* The pmapSeed() and pmapRandom() macros below can be adapted to
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* platform-specific RNGs if necessary. */
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#if defined(_WIN32) || defined(_WIN64)
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/* Use standard RNG without state management; the generated sequences
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* will be suboptimal */
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#include "random.h"
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#define pmapSeed(seed, state) srandom(seed)
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#define pmapRandom(state) frandom()
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#else
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/* Assume NIX and manage RNG state via erand48() */
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#define pmapSeed(seed, state) (state [0] += seed, state [1] += seed, \
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state [2] += seed)
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#define pmapRandom(state) erand48(state)
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#endif
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extern unsigned short partState [3], emitState [3], cntState [3],
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mediumState [3], scatterState [3], rouletteState [3],
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randSeed;
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#endif
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