bin/0000755000175000017500000000000013121745725010223 5ustar adamadamChangelog0000644000175000017500000000475313121746143011271 0ustar adamadam Bugfix 1.01: --------------------- 2017-06-19:16 sampler.hh max replaced with std::max; fix to history flag setting procedure in four parameter sampler::sampler. Thanks to Mathieu.Fourment@uts.edu.au for pointing this out. Version 1.0 Released: --------------------- 2009-04-14:15 1.0-RC4 adopted as version 1.0 without change. Changes in version 1.0-RC4: Changes inspired by two anonymous reviewers. ------------------------------------------------------------------------ 2009-02-04:14 A number of places in which variables were passed by value have been amended to pass constant references. 2009-02-02:13 gslrnginfo has been reimplemented as a singleton. This elimiates the need for some exception handling. 2009-01-27:12 SMC_HISTORY_* and SMC_RESAMPLE_* have been replaced with enumerations to allow type checking. 2009-01-27:11 Missing const qualifiers added to szFile and szMessage in the smc::exception class. Similarly, for the szName argument to load_data in the pf example. 2009-01-27:10 Makefiles tidied up. 2009-01-27:9 Resampled bitfield in historyflags has been made unsigned. 2009-01-27:8 algorithm header included in sampler.hh to ensure availability of max() 2009-01-27:7 Clumsy mechanism to prevent copying of the smc::sampler class removed in favour of the more elegant approach of making the copy constructor private. 2008-11-27:6 A more consistent commenting style has been adopted -- C style comments have been eliminated. 2008-11-27:5 A README.txt file was added, providing a description and basic installation details. Changes in version 1.0-RC3: --------------------------- 2008-08-11:4 Corrected a bug in the RESIDUAL RESAMPLING routine, any code using residual resampling should be upgraded to at least 1.0-RC3 to avoid potential buffer overrun problems and incorrect behaviour. Thanks to Martin Sewell for a related bug report. 2008-08-09:3: Changed the parameterisation of the annealing schedule in the rare event example to match that used in the paper. Changes in version 1.0-RC2: --------------------------- 2008-08-08:2: Fixed a bug in the resampling routine which could lead to incorrect behaviour for certain weight sequences. Thanks to Roman Holenstein for pointing this out. 2008-08-07:1: Added wrappers for additional random number generators in smc::rng, specifically: Beta, Cauchy, Exponential, Gamma, Gaussian Tail, Laplacian and Lognormal distributions. 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But first, please read . doc/0000755000175000017500000000000013121745725010220 5ustar adamadamexamples/0000755000175000017500000000000013121737222011262 5ustar adamadamexamples/Makefile0000755000175000017500000000033313121737222012724 0ustar adamadamall: pf-example rare-events-example .PHONY: pf-example rare-events-example clean clean: $(MAKE) -Cpf clean $(MAKE) -Crare-events clean pf-example: $(MAKE) -Cpf all rare-events-example: $(MAKE) -Crare-events all examples/rare-events/0000755000175000017500000000000013121745725013524 5ustar adamadamexamples/rare-events/msvc/0000755000175000017500000000000013121737222014465 5ustar adamadamexamples/rare-events/msvc/rare-events.vcproj0000755000175000017500000001054213121737222020152 0ustar adamadam examples/rare-events/Makefile0000755000175000017500000000056613121737222015167 0ustar adamadaminclude ../../Makefile.in C = main.cc simfunctions.cc O = main.o simfunctions.o H = simfunctions.hh CCFLAGS := $(CCFLAGS) -I../../include -L../../lib LFLAGS := -g -I../../include -L../../lib -static $(LFLAGS) all: rare .PHONY: clean clean: -rm *.o -rm *~ -rm rare rare: $(C) $(H) $(CC) $(CCFLAGS) -c $(C) $(CC) $(O) -lsmctc $(LFLAGS) -orare cp rare ../../bin examples/rare-events/markovchains/0000755000175000017500000000000013121737222016202 5ustar adamadamexamples/rare-events/markovchains/markovchain.h0000755000175000017500000003114113121737222020660 0ustar adamadam#ifndef __MARKOVCHAIN_H #define __MARKOVCHAIN_H #include #include using namespace std; //!A template class for the elements of a Markov chain. template class mElement { public: //! Pointer to the previous element in the chain. mElement *pPrev; //! Pointer to the next element in the chain. mElement *pNext; //! Value of this element of the chain. Space value; mElement(); mElement(Space); mElement(mElement*,Space,mElement*); mElement operator=(mElement & mE) { this->value = mE.value; } mElement operator=(mElement mE) { this->value = mE.value; } }; template mElement::mElement() { pPrev = NULL; pNext = NULL; } template mElement::mElement(Space sInit) { value = sInit; pPrev = NULL; pNext = NULL; } template mElement::mElement(mElement* pPInit, Space sInit, mElement* pNInit) { value = sInit; pPrev = pPInit; pNext = pNInit; } //!A template class for a Markov Chain itself. template class mChain { private: long nLength; mElement *pRoot; mElement *pLeaf; Space (*pfKernel) (Space); public: mChain(); mChain(long nInit, Space* pElements); mChain(mChain *pMci); mChain(const mChain &mci); ~mChain(); mChain operator= (const mChain&); mChain operator+ (Space const &) const; mChain& operator+=(Space const &); mChain operator- (Space const &) const; mChain& operator-=(Space const &); const Space & AddToElement(long nIndex, const Space &); int AppendElement(const Space & ); int CheckSanity(void) const; int DeleteElement(long); int DeleteRange(long,long); void Empty(void); int KernelElement(void); int KernelRange(long); int InsertElement(long, Space); int PrependElement(Space); mElement *GetElement(long ind) const {if(ind > nLength) return NULL; mElement *pCount = pRoot; for(int i=0; i < ind; i++) pCount = pCount->pNext; return pCount; } mElement const *GetTerminal(void) const {return pLeaf;} long GetLength(void) const { return nLength; } Space (*GetKernel(void))(Space) { return pfKernel; } void SetKernel(Space (*pfKernelNew) (Space)) { pfKernel = pfKernelNew; } }; //! Constructor for an empty Markov Chain. template mChain::mChain() { nLength = 0; pRoot = NULL; pLeaf = NULL; pfKernel = NULL; } //! Constructor for an initialised Markov Chain. template mChain::mChain(long nInit, Space* pElements) { nLength = nInit; if(nInit) { pRoot = new mElement(pElements[0]); mElement *pCurrent = pRoot; for(int i = 1; i < nInit; i++) { pCurrent->pNext = new mElement(pCurrent, pElements[i], NULL); pCurrent = pCurrent->pNext; } pLeaf = pCurrent; } else { pRoot = NULL; pLeaf = NULL; } pfKernel = NULL; } //! Constructor for an initialisd Markov Chain template mChain::mChain(mChain *pMci) { nLength = pMci->mLength; if(pMci->nLength == 0) { // nLength = 0; pRoot = pLeaf = NULL; } else if(pMci->nLength == 1) { pRoot = new mElement(NULL, pMci->GetElement(0)->value,NULL); pLeaf = pRoot; // nLength = 1; } else { mElement * mEN = pMci->GetElement(0); pRoot = new mElement(NULL,mEN->value,NULL); mElement * mCurrent = pRoot; for(int i = 1; i < nLength; i++) { mCurrent->pNext = new mElement(mCurrent, mEN->value, NULL); mEN = mEN->pNext; mCurrent = mCurrent->pNext; } pLeaf = mCurrent; } } template mChain::mChain(const mChain &Mci) { /* nLength = 0; pRoot = pLeaf = NULL; for(int i = 0; i < Mci.nLength; i++) AppendElement(Mci.GetElement(i)->value); */ nLength = Mci.nLength; if(Mci.nLength == 0) { pRoot = pLeaf = NULL; } else { if(Mci.nLength == 1) { pRoot = new mElement(NULL, Mci.GetElement(0)->value,NULL); pLeaf = pRoot; } else { mElement * mEN = Mci.GetElement(0); pRoot = new mElement(NULL,mEN->value,NULL); mElement * mCurrent = pRoot; for(int i = 1; i < nLength; i++) { mCurrent->pNext = new mElement(mCurrent, mEN->pNext->value, NULL); mEN = mEN->pNext; mCurrent = mCurrent->pNext; } pLeaf = mCurrent; } } pfKernel = Mci.pfKernel; } template mChain::~mChain() { //It's wise to have something here or things leak somewhat.... if(nLength > 0) { mElement* pCurrent = pLeaf; while(pCurrent->pPrev) { pCurrent = pCurrent->pPrev; pCurrent->pNext->pPrev = NULL; delete pCurrent->pNext; pCurrent->pNext=NULL; } delete pCurrent; } pRoot=pLeaf=NULL; nLength = 0; } /// Add the specified value to the specified element of the Markov Chain template const Space & mChain::AddToElement(long nElement, const Space & sAdd) { mElement* pCurrent = pRoot; for(int n = 0; n < nElement; n++) { pCurrent=pCurrent->pNext; if(!pCurrent) return sAdd; } return pCurrent->value = pCurrent->value + sAdd; } //! Add a specified element to the end of a Markov Chain. template int inline mChain::AppendElement(const Space &snew) { if(nLength) { pLeaf->pNext = new mElement(pLeaf,snew,NULL); pLeaf = pLeaf->pNext; nLength++; return 0; } else { pRoot = new mElement(NULL,snew,NULL); pLeaf = pRoot; nLength = 1; return 0; } } //! Check that the doubly-linked list is sane template int mChain::CheckSanity(void) const { int nLengthCheck = 0, nLengthCheck2 = 0; int nLinkFails = 0; mElement *pHead = pRoot; while(pHead) { nLengthCheck++; if(pHead->pNext) { if(pHead->pNext->pPrev != pHead) nLinkFails++; } pHead=pHead->pNext; } pHead = pLeaf; while(pHead) { nLengthCheck2++; if(pHead->pPrev) { if(pHead->pPrev->pNext != pHead) nLinkFails++; } pHead=pHead->pPrev; } if(nLengthCheck != nLength || nLengthCheck2 != nLength) cerr << "LengthCheck " << nLengthCheck << "," << nLengthCheck2 << "(" << nLength << ")" << endl; if(nLinkFails) cerr << "Link Failure count..." << nLinkFails << endl; if(nLengthCheck != nLength) return -1; return nLinkFails; } //! Remove an element from a specified position in a Markov Chain. template int mChain::DeleteElement(long nPos) { if(nPos < 0 || nPos > nLength) return 1; if(nPos == 0) { mElement *pRootN = pRoot->pNext; delete pRoot; pRoot=pRootN; if(pRoot) pRoot->pPrev = NULL; nLength--; if(nLength < 2) pLeaf = pRoot; return 0; } if(nPos == nLength) { mElement *pLeafN = pLeaf->pPrev; delete pLeaf; pLeaf=pLeafN; if(pLeaf) pLeaf->pNext = NULL; nLength--; if(nLength < 2) pRoot = pLeaf; return 0; } mElement *pPoint = pRoot, *pPointN, *pPointP; for(int i = 1; i < nPos; i++) pPoint = pPoint->pNext; pPointP = pPoint->pPrev; pPointN = pPoint->pNext; delete pPoint; pPointP->pNext = pPointN; pPointN->pPrev = pPointP; nLength--; return 0; } //! Delete a contiguous region from within a Markov Chain. template int mChain::DeleteRange(long nPos1, long nPos2) { for(int i = nPos1; i < nPos2; i++) if(DeleteElement(nPos1)) return 1; return 0; //This should be replaced wite an efficient implementation at some point! } //! Remove all of the elements from a Markov chain, leaving only an empty container template void inline mChain::Empty(void) { if(nLength > 0) { mElement* pCurrent = pLeaf; while(pCurrent->pPrev) { pCurrent = pCurrent->pPrev; pCurrent->pNext->pPrev = NULL; delete pCurrent->pNext; pCurrent->pNext=NULL; } delete pCurrent; } pRoot=pLeaf=NULL; nLength = 0; } //! Insert a specified element at a specified position in a Markov Chain. template int mChain::InsertElement(long nPos, Space snew) { //If the insertion position is zero then insert the new element at the root of the chain if(nPos == 0) { return PrependElement(snew); } if(nPos == nLength) return AppendElement(snew); if(nPos > 0 && nPos < nLength) { mElement *pPoint = pRoot, *pPointN; for(int i = 1; i < nPos; i++) pPoint = pPoint->pNext; pPointN = pPoint->pNext; pPoint->pNext = new mElement(pPoint,snew,pPointN); pPointN->pPrev= pPoint->pNext; nLength++; return 0; } //If the insertion position does not lie between 0 and the length of the chain then we have a problem return 1; } //! Extend the chain by a single element obtained from the associated Markov Kernel template int mChain::KernelElement(void) { if(nLength) { pLeaf->pNext = new mElement(pLeaf, (*pfKernel)(pLeaf->value),NULL); pLeaf = pLeaf->pNext; nLength++; return 0; } else { return 1; //We can't very well extend a non-existant chain according to a kernel } } //! Extend the chain by a specified number of elements obtained by iterative application of the associated Markov Kernel. template int mChain::KernelRange(long n) { for(int i = 0; i < n; i++) { if(KernelElement()) return 1+i; } return 0; } //! Insert a specified element at the beginning of a Markov Chain. template int mChain::PrependElement(Space snew) { if(nLength) { pRoot->pPrev = new mElement(NULL,snew,pRoot); pRoot=pRoot->pPrev; nLength++; return 0; } else { pRoot = new mElement(NULL,snew,NULL); pLeaf = pRoot; nLength = 1; return 0; } } //Overloaded operators for use with these template classes //! Assigning a Markov Chain performs a deep copy /* template mChain & mChain::operator= (mChain & mci) { nLength = mci.nLength; // mChain *that = new mChain(&mci); // mElement *pi, *po; pi = mci.pRoot; Empty(); pRoot = new mElement(NULL,pi->value,NULL); po = pRoot; // po->value = pi->value; while(pi->pNext) { po->pNext = new mElement(po,pi->pNext->value,NULL); // po->pNext->value = pi->pNext->value; // po->pNext->pPrev = po; po=po->pNext; pi=pi->pNext; } pLeaf = pi; return (*this); //return *that; } */ //! Assigning a Markov Chain performs a deep copy template mChain mChain::operator= (const mChain &mci) { // First, get rid of the old stuff Empty(); // Now assign some new stuff nLength = mci.nLength; if(!nLength) return *this; // mChain *that = new mChain(&mci); // mElement *pi, *po; pi = mci.pRoot; pRoot = new mElement(NULL,pi->value,NULL); po = pRoot; while(pi->pNext) { pi=pi->pNext; po->pNext = new mElement(po,pi->value,NULL); po=po->pNext; } pLeaf = po; return (*this); //return *that; } // Provide shortcuts for shifting the entire chain template mChain mChain::operator+ (Space const & sInc) const { static mChain that; // = new mChain; that = *this; mElement *pCurrent; pCurrent = that.pRoot; do { pCurrent->value = pCurrent->value + sInc; pCurrent = pCurrent->pNext; } while (pCurrent); return that; } template mChain& mChain::operator+=(Space const & sInc) { *this = *this + sInc; return *this; } template mChain mChain::operator- (Space const & sInc) const { static mChain that; // = new mChain; that = *this; mElement *pCurrent; pCurrent = that.pRoot; do { pCurrent->value = pCurrent->value - sInc; pCurrent = pCurrent->pNext; } while (pCurrent); return that; } template mChain& mChain::operator-=(Space const & sInc) { *this = *this - sInc; return *this; } //Overloaded stream operators for use with these template classes //! Allow the use of output streams with Markov Chains. template ostream & operator<< (ostream& os, mChain& mc) { if(!mc.GetLength()) return os; mElement *me = mc.GetElement(0); os << "[" << me->value; while(me->pNext) { me = me->pNext; os << "," << me->value; } os << "]"; return os; } #endif examples/rare-events/main.cc0000755000175000017500000000275113121737222014760 0ustar adamadam#include #include #include "simfunctions.hh" ///Length of Markov Chain long lChainLength = 15; ///Number of distributions used long lIterates; ///Annealing schedule constant double dSchedule = 30.0; ///Rare event threshold double dThreshold = 5.0; int main(int argc, char** argv) { cout << "Number of Particles: "; long lNumber; cin >> lNumber; cout << "Number of Iterations: "; cin >> lIterates; cout << "Threshold: "; cin >> dThreshold; cout << "Schedule Constant: "; cin >> dSchedule; try{ ///An array of move function pointers void (*pfMoves[])(long, smc::particle > &,smc::rng*) = {fMove1, fMove2}; smc::moveset > Moveset(fInitialise, fSelect, sizeof(pfMoves) / sizeof(pfMoves[0]), pfMoves, fMCMC); smc::sampler > Sampler(lNumber, SMC_HISTORY_RAM); Sampler.SetResampleParams(SMC_RESAMPLE_STRATIFIED,0.5); Sampler.SetMoveSet(Moveset); Sampler.Initialise(); Sampler.IterateUntil(lIterates); ///Estimate the normalising constant of the terminal distribution double zEstimate = Sampler.IntegratePathSampling(pIntegrandPS, pWidthPS, NULL) - log(2.0); ///Estimate the weighting factor for the terminal distribution double wEstimate = Sampler.Integrate(pIntegrandFS, NULL); cout << zEstimate << " " << log(wEstimate) << " " << zEstimate + log(wEstimate) << endl; } catch(smc::exception e) { cerr << e; exit(e.lCode); } return 0; } examples/rare-events/simfunctions.cc0000755000175000017500000001202613121737222016551 0ustar adamadam#include #include #include #include "smctc.hh" #include "simfunctions.hh" using namespace std; ///The function corresponding to the log posterior density at specified time and position /// \param lTime The current time (i.e. the index of the current distribution) /// \param X The state to consider **/ double logDensity(long lTime, const mChain & X) { double lp; mElement *x = X.GetElement(0); mElement *y = x->pNext; //Begin with the density exluding the effect of the potential lp = log(gsl_ran_ugaussian_pdf(x->value)); while(y) { lp += log(gsl_ran_ugaussian_pdf(y->value - x->value)); x = y; y = x->pNext; } //Now include the effect of the multiplicative potential function lp -= log(1.0 + exp(-(ALPHA(lTime) * (x->value - THRESHOLD) ))); return lp; } ///A function to initialise double type markov chain-valued particles /// \param pRng A pointer to the random number generator which is to be used smc::particle > fInitialise(smc::rng *pRng) { // Create a Markov chain with the appropriate initialisation and then assign that to the particles. mChain Mc; double x = 0; for(int i = 0; i < PATHLENGTH; i++) { x += pRng->NormalS(); Mc.AppendElement(x); } return smc::particle >(Mc,0); } ///A function to select a move randomly /// \param lTime The current evolution time of the system /// \param p The current position of the particle which is to be moved /// \param pRng A pointer to the random number generator which is to be used long fSelect(long lTime, const smc::particle > & p, smc::rng *pRng) { return 0; } void fMove1(long lTime, smc::particle > & pFrom, smc::rng *pRng) { // The distance between points in the random grid. static double delta = 0.025; static double gridweight[2*GRIDSIZE+1], gridws = 0; static mChain NewPos[2*GRIDSIZE+1]; static mChain OldPos[2*GRIDSIZE+1]; // First select a new position from a grid centred on the old position, weighting the possible choises by the // posterior probability of the resulting states. gridws = 0; for(int i = 0; i < 2*GRIDSIZE+1; i++) { NewPos[i] = pFrom.GetValue() + ((double)(i - GRIDSIZE))*delta; gridweight[i] = exp(logDensity(lTime,NewPos[i])); gridws = gridws + gridweight[i]; } double dRUnif = pRng->Uniform(0,gridws); long j = -1; while(dRUnif > 0 && j <= 2*GRIDSIZE) { j++; dRUnif -= gridweight[j]; } pFrom.SetValue(NewPos[j]); // Now calculate the weight change which the particle suffers as a result double logInc = log(gridweight[j]), Inc = 0; for(int i = 0; i < 2*GRIDSIZE+1; i++) { OldPos[i] = pFrom.GetValue() - ((double)(i - GRIDSIZE))*delta; gridws = 0; for(int k = 0; k < 2*GRIDSIZE+1; k++) { NewPos[k] = OldPos[i] + ((double)(k-GRIDSIZE))*delta; gridweight[k] = exp(logDensity(lTime, NewPos[k])); gridws += gridweight[k]; } Inc += exp(logDensity(lTime-1, OldPos[i])) * exp(logDensity(lTime, pFrom.GetValue())) / gridws; } logInc -= log(Inc); pFrom.SetLogWeight(pFrom.GetLogWeight() + logInc); for(int i = 0; i < 2*GRIDSIZE+1; i++) { NewPos[i].Empty(); OldPos[i].Empty(); } return; } ///Another move function void fMove2(long lTime, smc::particle > & pFrom, smc::rng *pRng) { pFrom.SetLogWeight(pFrom.GetLogWeight() + logDensity(lTime,pFrom.GetValue()) - logDensity(lTime-1,pFrom.GetValue())); } ///An MCMC step suitable for introducing sample diversity int fMCMC(long lTime, smc::particle > & pFrom, smc::rng *pRng) { static smc::particle > pTo; mChain * pMC = new mChain; for(int i = 0; i < pFrom.GetValue().GetLength(); i++) pMC->AppendElement(pFrom.GetValue().GetElement(i)->value + pRng->Normal(0, 0.5)); pTo.SetValue(*pMC); pTo.SetLogWeight(pFrom.GetLogWeight()); delete pMC; double alpha = exp(logDensity(lTime,pTo.GetValue()) - logDensity(lTime,pFrom.GetValue())); if(alpha < 1) if (pRng->UniformS() > alpha) { return false; } pFrom = pTo; return true; } ///A function to be integrated in the path sampling step. double pIntegrandPS(long lTime, const smc::particle >& pPos, void* pVoid) { double dPos = pPos.GetValue().GetTerminal()->value; return (dPos - THRESHOLD) / (1.0 + exp(ALPHA(lTime) * (dPos - THRESHOLD))); } ///A function which gives the width distribution for the path sampling step. double pWidthPS(long lTime, void* pVoid) { if(lTime > 1 && lTime < lIterates) return ((0.5)*double(ALPHA(lTime+1.0)-ALPHA(lTime-1.0))); else return((0.5)*double(ALPHA(lTime+1.0)-ALPHA(lTime)) +(ALPHA(1)-0.0)); } //The final state weighting function -- how likely is a random path from this distribution to hit the rare set... double pIntegrandFS(const mChain& dPos, void* pVoid) { if(dPos.GetTerminal()->value > THRESHOLD) { return (1.0 + exp(-FTIME*(dPos.GetTerminal()->value-THRESHOLD))); } else return 0; } examples/rare-events/simfunctions.hh0000755000175000017500000000237213121737222016566 0ustar adamadam#include "smctc.hh" #include "markovchains/markovchain.h" extern long lIterates; extern long lNumber; extern long lChainLength; extern double dSchedule; extern double dThreshold; double logDensity(long lTime, const mChain & X); smc::particle > fInitialise(smc::rng *pRng); long fSelect(long lTime, const smc::particle > & p, smc::rng *pRng); void fMove1(long lTime, smc::particle > & pFrom, smc::rng *pRng); void fMove2(long lTime, smc::particle > & pFrom, smc::rng *pRng); int fMCMC(long lTime, smc::particle > & pFrom, smc::rng *pRng); double pIntegrandPS(long lTime, const smc::particle >& pPos, void* pVoid); double pWidthPS(long lTime, void* pVoid); double pIntegrandFS(const mChain& dPos, void* pVoid); ///The number of grid elements to either side of the current state for the single state move #define GRIDSIZE 12 ///The value of alpha at the specified time #define ALPHA(T) (double(T)*double(dSchedule) / double(lIterates)) ///The terminal version of alpha #define FTIME (ALPHA(lIterates)) ///The exceedance threshold which we are interested in. #define THRESHOLD dThreshold ///The number of steps in the Markov chain #define PATHLENGTH lChainLength examples/pf/0000755000175000017500000000000013121745725011676 5ustar adamadamexamples/pf/pffuncs.hh0000755000175000017500000000076313121737222013665 0ustar adamadam#include "smctc.hh" class cv_state { public: double x_pos, y_pos; double x_vel, y_vel; }; class cv_obs { public: double x_pos, y_pos; }; double logLikelihood(long lTime, const cv_state & X); smc::particle fInitialise(smc::rng *pRng); long fSelect(long lTime, const smc::particle & p, smc::rng *pRng); void fMove(long lTime, smc::particle & pFrom, smc::rng *pRng); extern double nu_x; extern double nu_y; extern double Delta; extern cv_obs * y; examples/pf/msvc/0000755000175000017500000000000013121737222012637 5ustar adamadamexamples/pf/msvc/pf.vcproj0000755000175000017500000001056313121737222014501 0ustar adamadam examples/pf/msvc/data.csv0000755000175000017500000000677413121737222014306 0ustar adamadam100 -1.3112368222317 3.05445446146941 -1.18084192156169 3.2026952109489 -1.31786851718686 2.88913768742942 -1.50357802721903 3.46463318923276 -1.46226396819012 3.49006369310796 -1.77395566111683 3.53281069036811 -1.58329636598704 3.45802947672192 -1.4146213179481 3.85036842928615 -1.17347691181189 3.81191420563327 -1.08267505748716 3.92139843981037 -1.41722298460544 3.50086173794325 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13.037394682276 -6.05343255791713 13.1331797169505 -6.25115479362752 12.9688423961153 -6.52454592352636 13.3655802454826 examples/pf/Makefile0000755000175000017500000000074013121737222013333 0ustar adamadaminclude ../../Makefile.in C = main.cc rng.cc history.cc simfunctions.cc H = smctc.hh sampler.hh particle.hh moveset.hh history.hh rng.hh PFC = pfexample.cc pffuncs.cc PFO = pfexample.o pffuncs.o PFH = pffuncs.hh CCFLAGS := $(CCFLAGS) -I../../include -L../../lib LFLAGS := -I../../include -L../../lib $(LFLAGS) all: pf pf: $(PFC) $(PFH) $(CC) $(CCFLAGS) -c $(PFC) $(CC) $(PFO) -lsmctc $(LFLAGS) -opf cp pf ../../bin cp data.csv ../../bin clean: -rm *.o -rm *~ -rm pfexamples/pf/data.csv0000755000175000017500000000677413121737222013336 0ustar adamadam100 -1.3112368222317 3.05445446146941 -1.18084192156169 3.2026952109489 -1.31786851718686 2.88913768742942 -1.50357802721903 3.46463318923276 -1.46226396819012 3.49006369310796 -1.77395566111683 3.53281069036811 -1.58329636598704 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-5.70252008086239 13.1944817465382 -5.78573701298091 13.2160604563087 -5.81577139983498 13.0020585013642 -5.75998162986483 12.8745793253432 -6.09326684844694 13.037394682276 -6.05343255791713 13.1331797169505 -6.25115479362752 12.9688423961153 -6.52454592352636 13.3655802454826 examples/pf/pfexample.cc0000755000175000017500000000502213121737222014161 0ustar adamadam#include "smctc.hh" #include "pffuncs.hh" #include #include #include using namespace std; ///The observations cv_obs * y; long load_data(char const * szName, cv_obs** y); double integrand_mean_x(const cv_state&, void*); double integrand_mean_y(const cv_state&, void*); double integrand_var_x(const cv_state&, void*); double integrand_var_y(const cv_state&, void*); int main(int argc, char** argv) { long lNumber = 1000; long lIterates; try { //Load observations lIterates = load_data("data.csv", &y); //Initialise and run the sampler smc::sampler Sampler(lNumber, SMC_HISTORY_NONE); smc::moveset Moveset(fInitialise, fMove, NULL); Sampler.SetResampleParams(SMC_RESAMPLE_RESIDUAL, 0.5); Sampler.SetMoveSet(Moveset); Sampler.Initialise(); for(int n=1 ; n < lIterates ; ++n) { Sampler.Iterate(); double xm,xv,ym,yv; xm = Sampler.Integrate(integrand_mean_x,NULL); xv = Sampler.Integrate(integrand_var_x, (void*)&xm); ym = Sampler.Integrate(integrand_mean_y,NULL); yv = Sampler.Integrate(integrand_var_y, (void*)&ym); cout << xm << "," << ym << "," << xv << "," << yv << endl; } } catch(smc::exception e) { cerr << e; exit(e.lCode); } } long load_data(char const * szName, cv_obs** yp) { FILE * fObs = fopen(szName,"rt"); if (!fObs) throw SMC_EXCEPTION(SMCX_FILE_NOT_FOUND, "Error: pf assumes that the current directory contains an appropriate data file called data.csv\nThe first line should contain a constant indicating the number of data lines it contains.\nThe remaining lines should contain comma-separated pairs of x,y observations."); char* szBuffer = new char[1024]; fgets(szBuffer, 1024, fObs); long lIterates = strtol(szBuffer, NULL, 10); *yp = new cv_obs[lIterates]; for(long i = 0; i < lIterates; ++i) { fgets(szBuffer, 1024, fObs); (*yp)[i].x_pos = strtod(strtok(szBuffer, ",\r\n "), NULL); (*yp)[i].y_pos = strtod(strtok(NULL, ",\r\n "), NULL); } fclose(fObs); delete [] szBuffer; return lIterates; } double integrand_mean_x(const cv_state& s, void *) { return s.x_pos; } double integrand_var_x(const cv_state& s, void* vmx) { double* dmx = (double*)vmx; double d = (s.x_pos - (*dmx)); return d*d; } double integrand_mean_y(const cv_state& s, void *) { return s.y_pos; } double integrand_var_y(const cv_state& s, void* vmy) { double* dmy = (double*)vmy; double d = (s.y_pos - (*dmy)); return d*d; } examples/pf/pffuncs.cc0000755000175000017500000000327013121737222013647 0ustar adamadam#include #include #include #include "smctc.hh" #include "pffuncs.hh" using namespace std; double var_s0 = 4; double var_u0 = 1; double var_s = 0.02; double var_u = 0.001; double scale_y = 0.1; double nu_y = 10.0; double Delta = 0.1; ///The function corresponding to the log likelihood at specified time and position (up to normalisation) /// \param lTime The current time (i.e. the index of the current distribution) /// \param X The state to consider double logLikelihood(long lTime, const cv_state & X) { return - 0.5 * (nu_y + 1.0) * (log(1 + pow((X.x_pos - y[lTime].x_pos)/scale_y,2) / nu_y) + log(1 + pow((X.y_pos - y[lTime].y_pos)/scale_y,2) / nu_y)); } ///A function to initialise particles /// \param pRng A pointer to the random number generator which is to be used smc::particle fInitialise(smc::rng *pRng) { cv_state value; value.x_pos = pRng->Normal(0,sqrt(var_s0)); value.y_pos = pRng->Normal(0,sqrt(var_s0)); value.x_vel = pRng->Normal(0,sqrt(var_u0)); value.y_vel = pRng->Normal(0,sqrt(var_u0)); return smc::particle(value,logLikelihood(0,value)); } ///The proposal function. ///\param lTime The sampler iteration. ///\param pFrom The particle to move. ///\param pRng A random number generator. void fMove(long lTime, smc::particle & pFrom, smc::rng *pRng) { cv_state * cv_to = pFrom.GetValuePointer(); cv_to->x_pos += cv_to->x_vel * Delta + pRng->Normal(0,sqrt(var_s)); cv_to->x_vel += pRng->Normal(0,sqrt(var_u)); cv_to->y_pos += cv_to->y_vel * Delta + pRng->Normal(0,sqrt(var_s)); cv_to->y_vel += pRng->Normal(0,sqrt(var_u)); pFrom.AddToLogWeight(logLikelihood(lTime, *cv_to)); } examples/pf/l0000644000175000017500000060476113121737222012063 0ustar 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include/0000755000175000017500000000000013121745330011066 5ustar adamadaminclude/sampler.hh0000755000175000017500000004774513121744300013072 0ustar adamadam// SMCTC: sampler.hh // // Copyright Adam Johansen, 2008--2017. // // This file is part of SMCTC. // // SMCTC is free software: you can redistribute it and/or modify // it under the terms of the GNU General Public License as published by // the Free Software Foundation, either version 3 of the License, or // (at your option) any later version. // // SMCTC is distributed in the hope that it will be useful, // but WITHOUT ANY WARRANTY; without even the implied warranty of // MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the // GNU General Public License for more details. // // You should have received a copy of the GNU General Public License // along with SMCTC. If not, see . //! \file //! \brief Defines the overall sampler object. //! //! This file defines the smc::sampler class which is used to implement entire particle systems. #ifndef __SMC_SAMPLER_HH #define __SMC_SAMPLER_HH 1.0 #include #include #include #include "rng.hh" #include "history.hh" #include "moveset.hh" #include "particle.hh" #include "smc-exception.hh" ///Specifiers for various resampling algorithms: enum ResampleType { SMC_RESAMPLE_MULTINOMIAL = 0, SMC_RESAMPLE_RESIDUAL, SMC_RESAMPLE_STRATIFIED, SMC_RESAMPLE_SYSTEMATIC }; ///Storage types for the history of the particle system. enum HistoryType { SMC_HISTORY_NONE = 0, SMC_HISTORY_RAM }; namespace smc { /// A template class for an interacting particle system suitable for SMC sampling template class sampler { private: ///A random number generator. rng* pRng; ///Number of particles in the system. long N; ///The current evolution time of the system. long T; ///The resampling mode which is to be employed. ResampleType rtResampleMode; ///The effective sample size at which resampling should be used. double dResampleThreshold; ///Structure used internally for resampling. double* dRSWeights; ///Structure used internally for resampling. unsigned int* uRSCount; ///Structure used internally for resampling. unsigned int* uRSIndices; ///The particles within the system. particle *pParticles; ///The set of moves available. moveset Moves; ///The number of MCMC moves which have been accepted during this iteration int nAccepted; ///A flag which tracks whether the ensemble was resampled during this iteration int nResampled; ///A mode flag which indicates whether historical information is stored HistoryType htHistoryMode; ///The historical process associated with the particle system. history > History; public: ///Create an particle system containing lSize uninitialised particles with the specified mode. sampler(long lSize, HistoryType htHistoryMode); ///Create an particle system constaining lSize uninitialised particles with the specified mode and random number generator. sampler(long lSize, HistoryType htHistoryMode, const gsl_rng_type* rngType, unsigned long nSeed); ///Dispose of a sampler. ~sampler(); ///Calculates and Returns the Effective Sample Size. double GetESS(void) const; ///Returns a pointer to the History of the -particle system const history > * GetHistory(void) const { return &History; } ///Returns the number of particles within the system. long GetNumber(void) const {return N;} ///Return the value of particle n const Space & GetParticleValue(int n) { return pParticles[n].GetValue(); } ///Return the logarithmic unnormalized weight of particle n double GetParticleLogWeight(int n) { return pParticles[n].GetLogWeight(); } ///Return the unnormalized weight of particle n double GetParticleWeight(int n) { return pParticles[n].GetWeight(); } ///Returns the current evolution time of the system. long GetTime(void) const {return T;} ///Initialise the sampler and its constituent particles. void Initialise(void); ///Integrate the supplied function with respect to the current particle set. double Integrate(double(*pIntegrand)(const Space &,void*), void* pAuxiliary); ///Integrate the supplied function over the path path using the supplied width function. double IntegratePathSampling(double (*pIntegrand)(long,const particle&,void*), double (*pWidth)(long,void*), void* pAuxiliary); ///Perform one iteration of the simulation algorithm. void Iterate(void); ///Cancel one iteration of the simulation algorithm. void IterateBack(void); ///Perform one iteration of the simulation algorithm and return the resulting ess double IterateEss(void); ///Perform iterations until the specified evolution time is reached void IterateUntil(long lTerminate); ///Move the particle set by proposing an applying an appropriate move to each particle. void MoveParticles(void); ///Resample the particle set using the specified resmpling scheme. void Resample(ResampleType lMode); ///Sets the entire moveset to the one which is supplied void SetMoveSet(moveset& pNewMoveset) { Moves = pNewMoveset; } ///Set Resampling Parameters void SetResampleParams(ResampleType rtMode, double dThreshold); ///Dump a specified particle to the specified output stream in a human readable form std::ostream & StreamParticle(std::ostream & os, long n); ///Dump the entire particle set to the specified output stream in a human readable form std::ostream & StreamParticles(std::ostream & os); ///Allow a human readable version of the sampler configuration to be produced using the stream operator. /// std::ostream & operator<< (std::ostream& os, sampler & s); private: ///Duplication of smc::sampler is not currently permitted. sampler(const sampler & sFrom); ///Duplication of smc::sampler is not currently permitted. sampler & operator=(const sampler & sFrom); }; /// The constructor prepares a sampler for use but does not assign any moves to the moveset, initialise the particles /// or otherwise perform any sampling related tasks. Its main function is to allocate a region of memory in which to /// store the particle set and to initialise a random number generator. /// /// \param lSize The number of particles present in the ensemble (at time 0 if this is a variable quantity) /// \param htHM The history mode to use: set this to SMC_HISTORY_RAM to store the whole history of the system and SMC_HISTORY_NONE to avoid doing so. /// \tparam Space The class used to represent a point in the sample space. template sampler::sampler(long lSize, HistoryType htHM) { pRng = new rng(); N = lSize; pParticles = new particle[lSize]; //Allocate some storage for internal workspaces dRSWeights = new double[N]; ///Structure used internally for resampling. uRSCount = new unsigned[N]; ///Structure used internally for resampling. uRSIndices = new unsigned[N]; //Some workable defaults. htHistoryMode = htHM; rtResampleMode = SMC_RESAMPLE_STRATIFIED; dResampleThreshold = 0.5 * N; } /// The constructor prepares a sampler for use but does not assign any moves to the moveset, initialise the particles /// or otherwise perform any sampling related tasks. Its main function is to allocate a region of memory in which to /// store the particle set and to initialise a random number generator. /// /// \param lSize The number of particles present in the ensemble (at time 0 if this is a variable quantity) /// \param htHM The history mode to use: set this to SMC_HISTORY_RAM to store the whole history of the system and SMC_HISTORY_NONE to avoid doing so. /// \param rngType The type of random number generator to use /// \param rngSeed The seed to use for the random number generator /// \tparam Space The class used to represent a point in the sample space. template sampler::sampler(long lSize, HistoryType htHM, const gsl_rng_type* rngType, unsigned long rngSeed) { pRng = new rng(rngType, rngSeed); N = lSize; pParticles = new particle[lSize]; //Allocate some storage for internal workspaces dRSWeights = new double[N]; ///Structure used internally for resampling. uRSCount = new unsigned[N]; ///Structure used internally for resampling. uRSIndices = new unsigned[N]; //Some workable defaults. htHistoryMode = htHM; rtResampleMode = SMC_RESAMPLE_STRATIFIED; dResampleThreshold = 0.5 * N; } template sampler::~sampler() { delete pRng; if(dRSWeights) delete [] dRSWeights; if(uRSCount) delete [] uRSCount; if(uRSIndices) delete [] uRSIndices; } template double sampler::GetESS(void) const { long double sum = 0; long double sumsq = 0; for(int i = 0; i < N; i++) sum += expl(pParticles[i].GetLogWeight()); for(int i = 0; i < N; i++) sumsq += expl(2.0*(pParticles[i].GetLogWeight())); return expl(-log(sumsq) + 2*log(sum)); } /// At present this function resets the system evolution time to 0 and calls the moveset initialisor to assign each /// particle in the ensemble. /// /// Note that the initialisation function must be specified before calling this function. template void sampler::Initialise(void) { T = 0; for(int i = 0; i < N; i++) pParticles[i] = Moves.DoInit(pRng); if(htHistoryMode != SMC_HISTORY_NONE) { while(History.Pop()); nResampled = 0; History.Push(N, pParticles, 0, historyflags(nResampled)); } return; } /// This function returns the result of integrating the supplied function under the empirical measure associated with the /// particle set at the present time. The final argument of the integrand function is a pointer which will be supplied /// with pAuxiliary to allow for arbitrary additional information to be passed to the function being integrated. /// /// \param pIntegrand The function to integrate with respect to the particle set /// \param pAuxiliary A pointer to any auxiliary data which should be passed to the function template double sampler::Integrate(double(*pIntegrand)(const Space&,void*), void * pAuxiliary) { long double rValue = 0; long double wSum = 0; for(int i =0; i < N; i++) { rValue += expl(pParticles[i].GetLogWeight()) * pIntegrand(pParticles[i].GetValue(), pAuxiliary); wSum += expl(pParticles[i].GetLogWeight()); } rValue /= wSum; return (double)rValue; } /// This function is intended to be used to estimate integrals of the sort which must be evaluated to determine the /// normalising constant of a distribution obtain using a sequence of potential functions proportional to densities with respect /// to the initial distribution to define a sequence of distributions leading up to the terminal, interesting distribution. /// /// In this context, the particle set at each time is used to make an estimate of the path sampling integrand, and a /// trapezoidal integration is then performed to obtain an estimate of the path sampling integral which is the natural logarithm /// of the ratio of normalising densities. /// /// \param pIntegrand The quantity which we wish to integrate at each time /// \param pWidth A pointer to a function which specifies the width of each template double sampler::IntegratePathSampling(double (*pIntegrand)(long,const particle &,void*), double (*pWidth)(long,void*), void* pAuxiliary) { if(htHistoryMode == SMC_HISTORY_NONE) throw SMC_EXCEPTION(SMCX_MISSING_HISTORY, "The path sampling integral cannot be computed as the history of the system was not stored."); History.Push(N, pParticles, nAccepted, historyflags(nResampled)); double dRes = History.IntegratePathSampling(pIntegrand, pWidth, pAuxiliary); History.Pop(); return dRes; } /// The iterate function: /// -# appends the current particle set to the history if desired /// -# moves the current particle set /// -# checks the effective sample size and resamples if necessary /// -# performs a mcmc step if required /// -# increments the current evolution time template void sampler::Iterate(void) { IterateEss(); return; } template void sampler::IterateBack(void) { if(htHistoryMode == SMC_HISTORY_NONE) throw SMC_EXCEPTION(SMCX_MISSING_HISTORY, "An attempt to undo an iteration was made; unforunately, the system history has not been stored."); History.Pop(&N, &pParticles, &nAccepted, NULL); T--; return; } template double sampler::IterateEss(void) { //Initially, the current particle set should be appended to the historical process. if(htHistoryMode != SMC_HISTORY_NONE) History.Push(N, pParticles, nAccepted, historyflags(nResampled)); nAccepted = 0; //Move the particle set. MoveParticles(); //Normalise the weights to sensible values.... double dMaxWeight = -std::numeric_limits::infinity(); for(int i = 0; i < N; i++) dMaxWeight = std::max(dMaxWeight, pParticles[i].GetLogWeight()); for(int i = 0; i < N; i++) pParticles[i].SetLogWeight(pParticles[i].GetLogWeight() - (dMaxWeight)); //Check if the ESS is below some reasonable threshold and resample if necessary. //A mechanism for setting this threshold is required. double ESS = GetESS(); if(ESS < dResampleThreshold) { nResampled = 1; Resample(rtResampleMode); } else nResampled = 0; //A possible MCMC step should be included here. for(int i = 0; i < N; i++) { if(Moves.DoMCMC(T+1,pParticles[i], pRng)) nAccepted++; } // Increment the evolution time. T++; return ESS; } template void sampler::IterateUntil(long lTerminate) { while(T < lTerminate) Iterate(); } template void sampler::MoveParticles(void) { for(int i = 0; i < N; i++) { Moves.DoMove(T+1,pParticles[i], pRng); // pParticles[i].Set(pNew.value, pNew.logweight); } } template void sampler::Resample(ResampleType lMode) { //Resampling is done in place. double dWeightSum = 0; unsigned uMultinomialCount; //First obtain a count of the number of children each particle has. switch(lMode) { case SMC_RESAMPLE_MULTINOMIAL: //Sample from a suitable multinomial vector for(int i = 0; i < N; ++i) dRSWeights[i] = pParticles[i].GetWeight(); pRng->Multinomial(N,N,dRSWeights,uRSCount); break; case SMC_RESAMPLE_RESIDUAL: //Sample from a suitable multinomial vector and add the integer replicate //counts afterwards. dWeightSum = 0; for(int i = 0; i < N; ++i) { dRSWeights[i] = pParticles[i].GetWeight(); dWeightSum += dRSWeights[i]; } uMultinomialCount = N; for(int i = 0; i < N; ++i) { dRSWeights[i] = N*dRSWeights[i] / dWeightSum; uRSIndices[i] = unsigned(floor(dRSWeights[i])); //Reuse temporary storage. dRSWeights[i] = (dRSWeights[i] - uRSIndices[i]); uMultinomialCount -= uRSIndices[i]; } pRng->Multinomial(uMultinomialCount,N,dRSWeights,uRSCount); for(int i = 0; i < N; ++i) uRSCount[i] += uRSIndices[i]; break; case SMC_RESAMPLE_STRATIFIED: default: { // Procedure for stratified sampling dWeightSum = 0; double dWeightCumulative = 0; // Calculate the normalising constant of the weight vector for(int i = 0; i < N; i++) dWeightSum += exp(pParticles[i].GetLogWeight()); //Generate a random number between 0 and 1/N times the sum of the weights double dRand = pRng->Uniform(0,1.0 / ((double)N)); int j = 0, k = 0; for(int i = 0; i < N; ++i) uRSCount[i] = 0; dWeightCumulative = exp(pParticles[0].GetLogWeight()) / dWeightSum; while(j < N) { while((dWeightCumulative - dRand) > ((double)j)/((double)N) && j < N) { uRSCount[k]++; j++; dRand = pRng->Uniform(0,1.0 / ((double)N)); } k++; dWeightCumulative += exp(pParticles[k].GetLogWeight()) / dWeightSum; } break; } case SMC_RESAMPLE_SYSTEMATIC: { // Procedure for stratified sampling but with a common RV for each stratum dWeightSum = 0; double dWeightCumulative = 0; // Calculate the normalising constant of the weight vector for(int i = 0; i < N; i++) dWeightSum += exp(pParticles[i].GetLogWeight()); //Generate a random number between 0 and 1/N times the sum of the weights double dRand = pRng->Uniform(0,1.0 / ((double)N)); int j = 0, k = 0; for(int i = 0; i < N; ++i) uRSCount[i] = 0; dWeightCumulative = exp(pParticles[0].GetLogWeight()) / dWeightSum; while(j < N) { while((dWeightCumulative - dRand) > ((double)j)/((double)N) && j < N) { uRSCount[k]++; j++; } k++; dWeightCumulative += exp(pParticles[k].GetLogWeight()) / dWeightSum; } break; } } //Map count to indices to allow in-place resampling for (unsigned int i=0, j=0; i0) { uRSIndices[i] = i; while (uRSCount[i]>1) { while (uRSCount[j]>0) ++j; // find next free spot uRSIndices[j++] = i; // assign index --uRSCount[i]; // decrement number of remaining offsprings } } } //Perform the replication of the chosen. for(int i = 0; i < N ; ++i) { if(uRSIndices[i] != i) pParticles[i].SetValue(pParticles[uRSIndices[i]].GetValue()); pParticles[i].SetLogWeight(0); } } /// This function configures the resampling parameters, allowing the specification of both the resampling /// mode and the threshold at which resampling is used. /// /// \param rtMode The resampling mode to be used. /// \param dThreshold The threshold at which resampling is deemed necesary. /// /// The rtMode parameter should be set to one of the following: /// -# SMC_RESAMPLE_MULTINOMIAL to use multinomial resampling /// -# SMC_RESAMPLE_RESIDUAL to use residual resampling /// -# SMC_RESAMPLE_STRATIFIED to use stratified resampling /// -# SMC_RESAMPLE_SYSTEMATIC to use systematic resampling /// /// The dThreshold parameter can be set to a value in the range [0,1) corresponding to a fraction of the size of /// the particle set or it may be set to an integer corresponding to an actual effective sample size. template void sampler::SetResampleParams(ResampleType rtMode, double dThreshold) { rtResampleMode = rtMode; if(dThreshold < 1) dResampleThreshold = dThreshold * N; else dResampleThreshold = dThreshold; } template std::ostream & sampler::StreamParticle(std::ostream & os, long n) { os << pParticles[n] << std::endl; return os; } template std::ostream & sampler::StreamParticles(std::ostream & os) { for(int i = 0; i < N - 1; i++) os << pParticles[i] << std::endl; os << pParticles[N-1] << std::endl; return os; } } namespace std { /// Produce a human-readable display of the state of an smc::sampler class using the stream operator. /// \param os The output stream to which the display should be made. /// \param s The sampler which is to be displayed. template std::ostream & operator<< (std::ostream & os, smc::sampler & s) { os << "Sampler Configuration:" << std::endl; os << "======================" << std::endl; os << "Evolution Time: " << s.GetTime() << std::endl; os << "Particle Set Size:" << s.GetNumber() << std::endl; os << std::endl; os << "Particle Set:" << std::endl; s.StreamParticles(os); os << std::endl; return os; } } #endif include/smctc.hh0000755000175000017500000001042713121737222012530 0ustar adamadam// // smctc.h // // The principle header file for the SMC template class. // // Copyright Adam Johansen, 2008 // // // This file is part of SMCTC. // // SMCTC is free software: you can redistribute it and/or modify // it under the terms of the GNU General Public License as published by // the Free Software Foundation, either version 3 of the License, or // (at your option) any later version. // // SMCTC is distributed in the hope that it will be useful, // but WITHOUT ANY WARRANTY; without even the implied warranty of // MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the // GNU General Public License for more details. // // You should have received a copy of the GNU General Public License // along with SMCTC. If not, see . // /// \mainpage smctc -- A Template Class Library for SMC Simulation /// /// \version 1.0 /// \author Adam M. Johansen /// /// \section intro_sec Summary /// /// The SMC template class library (SMCTC) is intended to be used to implement SMC /// algorithms ranging from simple particle filter to complicated SMC algorithms /// from simple particle filters to the SMC samplers of Del Moral, Doucet and Jasra (2006) /// within a generic framework. /// /// \section license License /// /// SMCTC is free software: you can redistribute it and/or modify /// it under the terms of the GNU General Public License as published by /// the Free Software Foundation, either version 3 of the License, or /// (at your option) any later version. /// /// SMCTC is distributed in the hope that it will be useful, /// but WITHOUT ANY WARRANTY; without even the implied warranty of /// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the /// GNU General Public License for more details. /// /// You should have received a copy of the GNU General Public License /// along with SMCTC. If not, see . /// /// The software is still in development but is thought to be sufficiently fully-featured and /// stable for use. /// /// \section using_sec Using the Template Library /// /// In order to use the template libary it is necessary to place the set of header files in /// a suitable include directory and then to instantiate the various classes with the /// appropriate type for your sampler. /// /// For implementation details, please see the accompanying user guide. /// /// /// \section example_sec Examples /// /// \subsection A Simple Particle Filter /// /// This example provides a simple particle filter for the approximate filtering of /// nonlinear, nongaussian state space models. /// /// \subsection SMC Samplers for Rare Event Simulation /// /// The main.cc file provides an example of a use of the template library to estimate /// Gaussian tail probabilities within an SMC samplers framework by making use of a sequence /// of intermediate distributions defined by introducing a potential function which /// varies from flat to being very close to an indicator function on the tail event. /// /// This example is taken from from Johansen, Del Moral and Doucet (2006). /// /// \subsection Acknowledgements /// /// Thanks are due to Edmund Jackson and Mark Briers for testing SMCTC on a variety of platforms. /// The Visual C++ project and solution files are kindly provided by Mark Briers. /// //! \file //! \brief The main header file for SMCTC. //! //! This file serves as an interface between user-space programs and the SMCTC library. //! This is the only header file which applications need to include to make use of the library (it includes //! such additional files as are necessary). #ifndef __SMC_TDSMC_HH #define __SMC_TDSMC_HH 1.0 #include #include #include #include #include "smc-exception.hh" #include "sampler.hh" /// The Sequential Monte Carlo namespace /// /// The classes and functions within this namespace are intended to be used for producing /// implemenetations of SMC samplers and related simulation techniques. namespace smc {} /// The standard namespace /// The classes provided within the standard libraries reside within this namespace and /// the TDSMC class library adds a number of additional operator overloads to some of /// the standard classes to allow them to deal with our structures. namespace std {} #endif include/moveset.hh0000755000175000017500000001756413121737222013112 0ustar adamadam// SMCTC: moveset.hh // // Copyright Adam Johansen, 2008. // // This file is part of SMCTC. // // SMCTC is free software: you can redistribute it and/or modify // it under the terms of the GNU General Public License as published by // the Free Software Foundation, either version 3 of the License, or // (at your option) any later version. // // SMCTC is distributed in the hope that it will be useful, // but WITHOUT ANY WARRANTY; without even the implied warranty of // MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the // GNU General Public License for more details. // // You should have received a copy of the GNU General Public License // along with SMCTC. If not, see . // //! \file //! \brief Classes and functions which deal with collections of sampler proposal "moves". //! //! This file contains definitions of smc::moveset. //! It deals with the collections of proposal moves (including initialisation and MCMC moves) which must be dealt with by the sampler. #ifndef __SMC_MOVESET_HH #define __SMC_MOVESET_HH 1.0 #include "particle.hh" //#include "rng.hh" namespace smc { /// A template class for a set of moves for use in an SMC samplers framework. template class moveset { private: ///The number of moves which are present in the set long number; ///The function which initialises a particle. particle (*pfInitialise)(rng*); ///The function which selects a move for a given particle at a given time. long (*pfMoveSelect)(long , const particle &, rng*); ///The functions which perform actual moves. void (**pfMoves)(long, particle &, rng*); ///A Markov Chain Monte Carlo move. int (*pfMCMC)(long,particle &, rng*); public: ///Create a completely unspecified moveset moveset(); ///Create a reduced moveset with a single move moveset(particle (*pfInit)(rng*), void (*pfNewMoves)(long, particle &,rng*), int (*pfNewMCMC)(long,particle &,rng*)); ///Create a fully specified moveset moveset(particle (*pfInit)(rng*),long (*pfMoveSelector)(long , const particle &,rng*), long nMoves, void (**pfNewMoves)(long, particle &,rng*), int (*pfNewMCMC)(long,particle &,rng*)); ///Initialise a particle particle DoInit(rng * pRng) { return (*pfInitialise)(pRng);}; ///Perform an MCMC move on a particle int DoMCMC(long lTime, particle & pFrom, rng* pRng); ///Select an appropriate move at time lTime and apply it to pFrom void DoMove(long lTime, particle & pFrom,rng * pRng); ///Free the memory used for the array of move pointers when deleting ~moveset(); /// \brief Set the initialisation function. /// \param pfInit is a function which returns a particle generated according to the initial distribution void SetInitialisor( particle (*pfInit)(rng*) ) {pfInitialise = pfInit;} /// \brief Set the MCMC function /// \param pfNewMCMC The function which performs an MCMC move void SetMCMCFunction(int (*pfNewMCMC)(long,particle &,rng*)) { pfMCMC = pfNewMCMC;} /// \brief Set the move selection function /// \param pfMoveSelectNew returns the index of move to perform at the specified time given a specified particle void SetMoveSelectionFunction(long (*pfMoveSelectNew)(long , const particle &, rng*)) {pfMoveSelect = pfMoveSelectNew; }; ///Set the individual move functions to the supplied array of such functions void SetMoveFunctions(long nMoves, void (**pfNewMoves)(long, particle &, rng*)); ///Moveset assignment should allocate buffers and deep copy all members. moveset & operator= (moveset & pFrom); }; /// The argument free smc::moveset constructor simply sets the number of available moves to zero and sets /// all of the associated function pointers to NULL. template moveset::moveset() { number = 0; pfInitialise = NULL; pfMoveSelect = NULL; pfMoves = NULL; pfMCMC = NULL; } /// The three argument moveset constructor creates a new set of moves and sets all of the relevant function /// pointers to the supplied values. Only a single move should exist if this constructor is used. /// \param pfInit The function which should be used to initialise particles when the system is initialised /// \param pfNewMoves An functions which moves a particle at a specified time to a new location /// \param pfNewMCMC The function which should be called to apply an MCMC move (if any) template moveset::moveset(particle (*pfInit)(rng*), void (*pfNewMoves)(long, particle &,rng*), int (*pfNewMCMC)(long,particle &,rng*)) { SetInitialisor(pfInit); SetMoveSelectionFunction(NULL); pfMoves = NULL; //This presents an erroneous deletion by the following call SetMoveFunctions(1, &pfNewMoves); SetMCMCFunction(pfNewMCMC); } /// The five argument moveset constructor creates a new set of moves and sets all of the relevant function /// pointers to the supplied values. /// \param pfInit The function which should be used to initialise particles when the system is initialised /// \param pfMoveSelector The function which selects a move to apply, at a specified time, to a specified particle /// \param nMoves The number of moves which are defined in general /// \param pfNewMoves An array of functions which move a particle at a specified time to a new location /// \param pfNewMCMC The function which should be called to apply an MCMC move (if any) template moveset::moveset(particle (*pfInit)(rng*),long (*pfMoveSelector)(long ,const particle &,rng*), long nMoves, void (**pfNewMoves)(long, particle &,rng*), int (*pfNewMCMC)(long,particle &,rng*)) { SetInitialisor(pfInit); SetMoveSelectionFunction(pfMoveSelector); pfMoves = NULL; //This presents an erroneous deletion by the following call SetMoveFunctions(nMoves, pfNewMoves); SetMCMCFunction(pfNewMCMC); } template moveset::~moveset() { if(pfMoves) delete [] pfMoves; } template int moveset::DoMCMC(long lTime, particle & pFrom, rng *pRng) { if(pfMCMC) { return pfMCMC(lTime,pFrom,pRng); } else { return false; } } template void moveset::DoMove(long lTime, particle & pFrom, rng *pRng) { if(number > 1) pfMoves[pfMoveSelect(lTime,pFrom,pRng)](lTime,pFrom,pRng); else pfMoves[0](lTime,pFrom,pRng); } /// \param nMoves The number of moves which are defined in general. /// \param pfNewMoves An array of functions which move a particle at a specified time to a new location /// /// The move functions accept two arguments, the first of which corresponds to the system evolution time and the /// second to an initial particle position and the second to a weighted starting position. It returns a new /// weighted position corresponding to the moved particle. template void moveset::SetMoveFunctions(long nMoves,void (**pfNewMoves)(long,particle &,rng*)) { number = nMoves; if(pfMoves) delete [] pfMoves; pfMoves = (void (**)(long int, smc::particle &,rng*)) new void* [nMoves]; for(int i = 0; i < nMoves; i++) pfMoves[i] = pfNewMoves[i]; return; } template moveset & moveset::operator= (moveset & pFrom) { SetInitialisor(pFrom.pfInitialise); SetMCMCFunction(pFrom.pfMCMC); SetMoveSelectionFunction(pFrom.pfMoveSelect); SetMoveFunctions(pFrom.number, pFrom.pfMoves); return *this; } } #endif include/smc-exception.hh0000755000175000017500000000510413121737222014171 0ustar adamadam// SMCTC: smc-exception.hh // // Copyright Adam Johansen, 2008. // // This file is part of SMCTC. // // SMCTC is free software: you can redistribute it and/or modify // it under the terms of the GNU General Public License as published by // the Free Software Foundation, either version 3 of the License, or // (at your option) any later version. // // SMCTC is distributed in the hope that it will be useful, // but WITHOUT ANY WARRANTY; without even the implied warranty of // MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the // GNU General Public License for more details. // // You should have received a copy of the GNU General Public License // along with SMCTC. If not, see . //! \file //! \brief This file defines exception-handling facilities. //! //! The smc::exception class, which is used for exception handling by SMCTC, is defined. #ifndef __SMC_EXCEPT_HH #define __SMC_EXCEPT_HH 1.0 #include ///A macro which autocompletes the housekeeping components of an smc::exception #define SMC_EXCEPTION(code,error) smc::exception(__FILE__, __LINE__, code, error) ///Exception thrown if a file cannot be accessed. #define SMCX_FILE_NOT_FOUND 0x0020 ///Exception thrown if the sampler attempts to access history data which wasn't stored. #define SMCX_MISSING_HISTORY 0x0010 ///Exception thrown if an attempt is made to instantiate a class of which a single instance is permitted more than once. #define SMCX_MULTIPLE_INSTANTIATION 0x1000 namespace smc { ///SMC Exception class /// This class holds details of unrecoverable errors which occur within the SMCTC library. /// An instance of it is thrown whenever such an error occurs. class exception { public: char const * szFile; //!< The source file from which the code generating the exception was generated. long lLine; //!< The line of that source file which generates the exception. long lCode; //!< A numerical code indicating the nature of the exception generated. char const * szMessage; //!< A human-readable explanation of the cause of the exception. exception(char const *, long, long, char const *); }; } namespace std { /// Produce a human-readable display of the state of an smc::exception class using the stream operator. /// Produce a human-readable display of the state of an smc::exception class using the stream operator. /// \param os The output stream to which the display should be made. /// \param e The exception which is to be displayed. std::ostream & operator<< (std::ostream &, smc::exception &); } #endif include/particle.hh0000755000175000017500000001176213121737222013225 0ustar adamadam// SMCTC: particle.hh // // Copyright Adam Johansen, 2008. // // This file is part of SMCTC. // // SMCTC is free software: you can redistribute it and/or modify // it under the terms of the GNU General Public License as published by // the Free Software Foundation, either version 3 of the License, or // (at your option) any later version. // // SMCTC is distributed in the hope that it will be useful, // but WITHOUT ANY WARRANTY; without even the implied warranty of // MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the // GNU General Public License for more details. // // You should have received a copy of the GNU General Public License // along with SMCTC. If not, see . // //! \file //! \brief Class used to store and manipulate a single particle. //! //! This file contains the smc::particle class which is used internally and passed to move functions. #ifndef __SMC_PARTICLE_HH #define __SMC_PARTICLE_HH 1.0 #include #include #include namespace smc { /// A template class for the particles of an SMC algorithm template class particle { private: /// Value of this particle Space value; /// Natural logarithm of this particle's weight. double logweight; public: particle(); /// Constructor which initialises the particles value and weight. particle(Space sInit,double dLogWeight); /// The copy constructor performs a shallow copy. particle(const particle & pFrom); /// The assignment operator performs a shallow copy. particle & operator= (const particle & pFrom); ~particle(); /// Returns the particle's value Space const & GetValue(void) const {return value;} /// Returns a pointer to the value to allow for more efficient changes Space* GetValuePointer(void) {return &value;} /// Returns the particle's log weight. double GetLogWeight(void) const {return logweight;} /// Returns the particle's unnormalised weight. double GetWeight(void) const {return exp(logweight);} /// \brief Sets the particle's value and weight explicitly /// /// \param sValue The particle value to use /// \param dLogWeight The natural logarithm of the new particle weight void Set(Space sValue,double dLogWeight){value = sValue; logweight = dLogWeight;} /// \brief Sets the particle's value explicitly /// /// \param sValue The particle value to use void SetValue(const Space & sValue){value = sValue;} /// \brief Sets the particle's log weight explicitly /// /// \param dLogWeight The natural logarithm of the new particle weight void SetLogWeight(const double & dLogWeight) {logweight = dLogWeight;} /// \brief Sets the particles weight explicitly /// /// \param dWeight The new particle weight void SetWeight(const double & dWeight) {logweight = log(dWeight);} /// \brief Increase the log weight by a specified amount /// /// \param dIncrement The amount to add to the log weight. void AddToLogWeight(double dIncrement) { logweight += dIncrement;} /// \brief Multiply the weight by a specified factor /// /// \param dMultiplier The factor to multiply the weight by. void MultiplyWeightBy(double dMultiplier) { logweight += log(dMultiplier);} }; /// Create a particle with undefined value and weight NAN template particle::particle() { logweight = std::numeric_limits::quiet_NaN(); } ///Copy constructor template particle::particle(const particle & pFrom) { value = pFrom.value; logweight = pFrom.logweight; } /// Create a particle with value sInit and log weight dLogWeight /// \param sInit The initial value of the particle /// \param dLogWeight The initial value of the natural logarithm of the particle weight template particle::particle(Space sInit, double dLogWeight) { value = sInit; logweight =dLogWeight; } /// Dispose of a particle which is no longer required template particle::~particle() { } /// Copy the values of pFrom to the values of this to set this particle identical to pFrom in a deep /// copy sense. template particle & particle::operator= (const particle & pFrom) { this->value = pFrom.value; this->logweight = pFrom.logweight; return *this; } } namespace std { /// Produce a human readable display of an smc::particle class using the standard stream operators /// \param os The output stream to which the display should be made. /// \param p The particle which is to be displayed. template std::ostream & operator << (std::ostream & os, smc::particle & p) { Space val = p.GetValue(); os << val << "," << exp(p.GetLogWeight()); return os; } } #endif include/rng.hh0000755000175000017500000001167513121737222012213 0ustar adamadam// SMCTC: rng.hh // // Copyright Adam Johansen, 2008. // // This file is part of SMCTC. // // SMCTC is free software: you can redistribute it and/or modify // it under the terms of the GNU General Public License as published by // the Free Software Foundation, either version 3 of the License, or // (at your option) any later version. // // SMCTC is distributed in the hope that it will be useful, // but WITHOUT ANY WARRANTY; without even the implied warranty of // MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the // GNU General Public License for more details. // // You should have received a copy of the GNU General Public License // along with SMCTC. If not, see . // //! \file //! \brief Random number generation. //! //! This file contains the definitions for the smc::rng and smc::rnginfo class. //! It wraps the random number generation facilities provided by the GSL and provides a convenient interfaces to access several of its more commonly-used features. #ifndef __SMC_RNG_HH #define __SMC_RNG_HH 1.0 extern "C" { #include #include } namespace smc { ///A gsl-rng information handling class (not templated) class gslrnginfo { private: ///This is a null terminated array of the available random number generators. const gsl_rng_type** typePtArray; ///The number of available random number generators. int nNumber; protected: gslrnginfo(); public: ///Returns a reference to the sole static instance of this class. static gslrnginfo* GetInstance(); ///Returns the number of available random number generators. int GetNumber(); ///Returns the name of random number generator number nIndex. const char* GetNameByIndex(int nIndex); ///Returns a pointer to random number generator nIndex. const gsl_rng_type* GetPointerByIndex(int nIndex); ///Returns a pointer to the random number generator with name szName (or null if it doesn't exist). const gsl_rng_type* GetPointerByName(const char* szName); }; ///The global application instance of the gslrnginfo class: extern gslrnginfo rngset; ///A random number generator class. /// At present this serves as a wrapper for the gsl random number generation code. class rng { private: ///This is the type of random number generator underlying the class. const gsl_rng_type* type; ///This is a pointer to the internal workspace of the rng including its current state. gsl_rng* pWorkspace; public: ///Initialise the random number generator using default settings rng(); ///Initialise the random number generator using the default seed for the type rng(const gsl_rng_type* Type); ///Initialise the random number generator using specified type and seed rng(const gsl_rng_type* Type,unsigned long int lSeed); ///Free the workspace allocated for random number generation ~rng(); ///Provide access to the raw random number generator gsl_rng* GetRaw(void); ///Generate a multinomial random vector with parameters (n,w[1:k]) and store it in X void Multinomial(unsigned n, unsigned k, const double* w, unsigned* X); ///Returns a random integer generated uniformly between the minimum and maximum values specified long UniformDiscrete(long lMin, long lMax); ///Returns a random number generated from a Beta distribution with the specified parameters. double Beta(double da, double db); ///Returns a random number generated from a Cauchy distribution with the specified scale parameter. double Cauchy(double dScale); ///Returns a random number generated from an exponential distribution with the specified mean. double Exponential(double dMean); ///Return a random number generated from a gamma distribution with shape alpha and scale beta. double Gamma(double dAlpha, double dBeta); ///Returns a random number generated from a Laplacian distribution with the specified scale. double Laplacian(double dScale); ///Returns a random number generated from a Lognormal distribution of location mu and scale sigma double Lognormal(double dMu, double dSigma); ///Return a random number generated from a normal distribution with a specified mean and standard deviation double Normal(double dMean, double dStd); ///Return a random number generated from a standard normal distribution double NormalS(void); ///Returns a random number from a normal distribution, conditional upon it exceeding the specified threshold. double NormalTruncated(double dMean, double dStd, double dThreshold); ///Return a student-t random number generated with a specified number of degrees of freedom double StudentT(double dDF); ///Return a random number generated uniformly between dMin and dMax double Uniform(double dMin, double dMax); ///Returns a random number generated from the standard uniform[0,1) distribution double UniformS(void); }; } #endif include/history.hh0000755000175000017500000004217513121737222013125 0ustar adamadam// SMCTC: history.hh // // Copyright Adam Johansen, 2008. // // This file is part of SMCTC. // // SMCTC is free software: you can redistribute it and/or modify // it under the terms of the GNU General Public License as published by // the Free Software Foundation, either version 3 of the License, or // (at your option) any later version. // // SMCTC is distributed in the hope that it will be useful, // but WITHOUT ANY WARRANTY; without even the implied warranty of // MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the // GNU General Public License for more details. // // You should have received a copy of the GNU General Public License // along with SMCTC. If not, see . // //! \file //! \brief Classes and function related to the history of the sampler. //! //! This file contains template definitions for the classes used to store the history of an SMCTC sampler. //! It defines smc::history, smc::historyelement and smc::history. #ifndef __SMC_HISTORY_HH #define __SMC_HISTORY_HH 1.0 namespace smc { /// The historyflags class holds a set of flags which describe various properties of the particle system at a given time. class historyflags { private: /// true if the particle system was resampled during the described iteration. unsigned int Resampled : 1; public: ///Create a new set of history flags corresponding to the specified properties historyflags(int wasResampled); ///This function returns true if the flag set indicates that the ensemble was resampled during the described iteration. int WasResampled(void) {return Resampled;} }; /// A template class for the elements of a linked list to be used for the history of the sampler. template class historyelement { private: long number; //!< The number of particles (presently redundant as this is not a function of iteration) int nAccepted; //!< Number of MCMC moves accepted during this iteration. Particle* value; //!< The particles themselves (values and weights) historyflags flags; //!< Flags associated with this iteration. historyelement *pLast; //!< The parent of this node. historyelement *pNext; //!< The child of this node. public: /// The null constructor creates an empty history element. historyelement(); /// A constructor with four arguments initialises the particle set. historyelement(long lNumber, Particle* pNew, int nAccepts, historyflags hf); /// A constructor with six arguments initialises the whole structure. historyelement(long lNumber, Particle* pNew, historyelement* pParent, historyelement* pChild, int nAccepts, historyflags hf); /// The destructor tidies up. ~historyelement(); /// Returns the effective sample size of this particle generation. double GetESS(void) const; /// Returns the flags historyflags GetFlags(void) const{return flags;} /// Returns the parent of this element. historyelement * GetLast(void) const { return pLast; } /// Returns the child of this element. historyelement * GetNext(void) const { return pNext; } /// Returns the number of particles present. long GetNumber(void) const {return number;} /// Returns a pointer to the current particle set. Particle * GetValues(void) const { return value; } /// Add a new history element with the specified values after the current one and maintain the list structure. void InsertAfter(long lNumber, Particle * pNew); /// Integrate the supplied function according to the empirical measure of the particle ensemble. long double Integrate(long lTime, double (*pIntegrand)(long,const Particle&,void*), void* pAuxiliary); /// Sets the elements parent. void SetLast(historyelement* pParent) {pLast = pParent; } /// Sets the elements child. void SetNext(historyelement* pChild) {pNext = pChild; } /// Sets the particle set to the specified values. void SetValue(long lNumber, Particle * pNew); /// Returns the number of MCMC moves accepted during this iteration. int AcceptCount(void) {return nAccepted; } /// Returns true if the particle set int WasResampled(void) {return flags.WasResampled(); } /// \brief The left shift operator returns the element a number of positions prior to this one. /// /// \param ulCount The number of positions by which to shift. /// \return The element a number of positions before this one. historyelement operator<<(unsigned long ulCount) { if(ulCount) return this->pLast << (--ulCount); else return *this; } ///\brief The right shift operator returns the element a number of positions after this one. /// /// \param ulCount The number of positions by which to shift. /// \return The right shift operator returns the element a number of positions after this one. historyelement operator>>(unsigned long ulCount) { if(ulCount) return this->pNext << (--ulCount); else return *this; } }; template historyelement::historyelement() { number = 0; value = NULL; nAccepted = 0; pLast = NULL; pNext = NULL; } /// \param lNumber The number of particles present in the particle generation /// \param pNew The array of particles which are present in the particle generation /// \param nAccepts The number of MCMC moves that were accepted during this particle generation /// \param hf The historyflags associated with the particle generation template historyelement::historyelement(long lNumber, Particle* pNew, int nAccepts, historyflags hf) : flags(hf) { number = lNumber; value = new Particle[number]; for(int i = 0; i < number; i++) value[i] = pNew[i]; nAccepted = nAccepts; pLast = NULL; pNext = NULL; } /// \param lNumber The number of particles present in the particle generation /// \param pNew The array of particles which are present in the particle generation /// \param pParent A pointer to the previous particle generation /// \param pChild A pointer to the next particle generation /// \param nAccepts The number of MCMC moves that were accepted during this particle generation /// \param hf The historyflags associated with the particle generation template historyelement::historyelement(long lNumber, Particle* pNew, historyelement* pParent, historyelement* pChild, int nAccepts, historyflags hf) : flags(hf) { number = lNumber; value = new Particle[number]; for(int i = 0; i < number; i++) value[i] = pNew[i]; nAccepted = nAccepts; pLast = pParent; pNext = pChild; } template historyelement::~historyelement(void) { if(value) delete [] value; } template double historyelement::GetESS(void) const { double sum = 0; double sumsq = 0; for(int i = 0; i < number; i++) { sum += exp(value[i].GetLogWeight()); sumsq += exp(2.0*value[i].GetLogWeight()); } return (sum*sum)/sumsq; } /// \param lTime The timestep at which the integration is to be carried out /// \param pIntegrand The function which is to be integrated /// \param pAuxiliary A pointer to additional information which is passed to the integrand function template long double historyelement::Integrate(long lTime, double (*pIntegrand)(long,const Particle&,void*), void* pAuxiliary) { long double rValue = 0; long double wSum = 0; for(int i =0; i < number; i++) { rValue += expl(value[i].GetLogWeight()) * (long double)pIntegrand(lTime, value[i], pAuxiliary); wSum += expl(value[i].GetLogWeight()); } rValue /= wSum; return rValue; } /// \param lNumber The number of particles in the generation to be inserted /// \param pNew The value of the particle generation to be inserted template void historyelement::InsertAfter(long lNumber, Particle * pNew) { pNext = new historyelement(lNumber, pNew, this, pNext); } /// A template class for the history associated with a particle system evolving in SMC. /// The history is a template class which should have an associated class type corresponding to /// a _particle_ of the desired type, not the type itself. /// /// Essentially, this is implemented as a doubly linked list. template class history { private: ///The length of the history in time steps long lLength; ///The first time step historyelement *pRoot; ///The most recent time step historyelement *pLeaf; public: ///The argument free constructor creates an empty list. history(); ///This function returns a pointer to the first element of the history. const historyelement * GetElement(void) const {return pRoot; } /// Returns the effective sample size of the specified particle generation. double GetESS(long lGeneration) const; ///Returns the number of generations recorded within the history. long GetLength (void) const { return lLength; } ///Integrate the supplied function over the path of the particle ensemble. double IntegratePathSampling(double (*pIntegrand)(long,const Particle&,void*), double (*pWidth)(long,void*), void* pAuxiliary); double IntegratePathSamplingFinalStep(double (*pIntegrand)(long,const Particle&,void*), void* pAuxiliary) const; ///Output a vector indicating the number of accepted MCMC moves at each time instance void OstreamMCMCRecordToStream(std::ostream &os) const; ///Output a 0-1 value vector indicating the times at which resampling occured to an output stream void OstreamResamplingRecordToStream(std::ostream &os) const; ///Remove the terminal particle generation from the list and return that particle. Particle * Pop(void); ///Remove the terminal particle generation from the list and stick it in the supplied data structures void Pop(long* plNumber, Particle** ppNew, int* pnAccept, historyflags * phf); ///Append the supplied particle generation to the end of the list. void Push(long lNumber, Particle * pNew, int nAccept, historyflags hf); ///Display the list of particles in a human readable form. // void StreamParticles(std::ostream & os); }; /// This constructor simply sets the root and leaf pointers to NULL and the list length to zero. template history::history() { pRoot = NULL; pLeaf = NULL; lLength = 0; } /// Returns the effective sample size of the specified particle generation. template double history::GetESS(long lGeneration) const { historyelement * pCurrent = pRoot; for(long l = 0; l < lGeneration; l++) pCurrent = pCurrent->GetNext(); return pRoot->GetESS(); } /// This function records the MCMC acceptance history to the specified output stream as a list of /// the number of moves accepted at each time instant. /// /// \param os The output stream to send the data to. template void history:: OstreamMCMCRecordToStream(std::ostream &os) const { historyelement * pCurrent = pRoot; while(pCurrent) { os << pCurrent->AcceptCount() << std::endl; pCurrent = pCurrent->GetNext(); } } /// This function records the resampling history to the specified output stream as a 0-1 valued list which takes /// the value 1 for those time instances when resampling occured and 0 otherwise. /// /// \param os The output stream to send the data to. template void history:: OstreamResamplingRecordToStream(std::ostream &os) const { historyelement * pCurrent = pRoot; while(pCurrent) { if(pCurrent->WasResampled()) os << "1\t"; else os << "0\t"; os << pCurrent->GetESS() << std::endl; pCurrent = pCurrent->GetNext(); } } /// This function performs a trapezoidal integration of the type which is useful when using path sampling to estimate the /// normalising constant of a potential function in those cases where a sequence of distributions is produced by deforming /// the initial distribution by a sequence of progressively more influential potential functions which are proportional /// to the density of some other distribution with respect to the starting distribution. /// /// The integrand is integrated at every time point in the particle system history. The results of this integration are /// taken to be point-evaluations of the path sampling integrand which are spaced on a grid of intervals given by the /// width function. The path sampling integral is then calculated by performing a suitable trapezoidal integration and /// the results of this integration is returned. /// /// pAuxiliary is passed to both of the user specified functions to allow the user to pass additional data to either or /// both of these functions in a convenient manner. It is safe to use NULL if no such data is used by either function. /// /// \param pIntegrand The function to integrated. The first argument is evolution time, the second a particle at which the function is to be evaluated and the final argument is always pAuxiliary. /// \param pWidth The function which returns the width of the path sampling grid at the specified evolution time. The final argument is always pAuxiliary /// \param pAuxiliary A pointer to auxiliary data to pass to both of the above functions template double history::IntegratePathSampling(double (*pIntegrand)(long,const Particle&,void*), double (*pWidth)(long,void*), void* pAuxiliary) { long lTime = 0; long double rValue = 0.0; historyelement * pCurrent = pRoot; lTime = 1; pCurrent=pCurrent->GetNext(); while(pCurrent) { rValue += pCurrent->Integrate(lTime, pIntegrand, pAuxiliary) * (long double)pWidth(lTime,pAuxiliary); pCurrent = pCurrent->GetNext(); lTime++; } return ((double)rValue); } template double history::IntegratePathSamplingFinalStep(double (*pIntegrand)(long,const Particle&,void*), void* pAuxiliary) const { return pLeaf->Integrate(lLength-1,pIntegrand,pAuxiliary); } /// Pop() operates just as the standard stack operation does. It removes the particle generation currently occupying /// the terminal position in the chain, decrements the length counter and returns the particle set as an array. template Particle * history::Pop(void) { if(lLength == 0) return NULL; Particle * rValue = pLeaf->GetValues(); lLength--; if(lLength == 0) pRoot = pLeaf = 0; else { pLeaf = pLeaf->GetLast(); delete pLeaf->GetNext(); pLeaf->SetNext(NULL); } return rValue; } /// Pop operates as the usual stack operation /// /// If called with four pointers of this sort, it removes the last particle generation from the history stack and /// places them in the reference objects. template void history::Pop(long* plNumber, Particle** ppNew, int* pnAccept, historyflags * phf) { if(plNumber) (*plNumber) = pLeaf->GetNumber(); if(ppNew) { for(long l = 0; l < *plNumber; l++) (*ppNew)[l] = pLeaf->GetValues()[l]; } if(pnAccept) (*pnAccept) = pLeaf->AcceptCount(); if(phf) (*phf) = pLeaf->GetFlags(); if(lLength <= 1) { pRoot = NULL; pLeaf = NULL; } else { pLeaf = pLeaf->GetLast(); // delete pLeaf->GetNext(); pLeaf->SetNext(NULL); } lLength--; return; } /// Push operates just like the standard stack operation: it adds the specified particle set generation to the history /// of the particle set and increments the stack counter. /// /// \param lNumber The number of particles present in this generation of the system. /// \param pNew An array containing the particles present in this generation of the system. /// \param nAccepts The number of accepted MCMC moves during this iteration of the system /// \param hf The historyflags associated with this generation of the system. template void history::Push(long lNumber, Particle * pNew, int nAccepts, historyflags hf) { if(lLength == 0) { pRoot = new historyelement(lNumber, pNew, nAccepts, hf); pLeaf = pRoot; } else { pLeaf = new historyelement(lNumber, pNew, pLeaf, NULL, nAccepts, hf); pLeaf->GetLast()->SetNext(pLeaf); } lLength++; } } namespace std { /// This function will ultimately allow the standard stream operators to be used to display a particle history in a human readable form. /// It isn't yet fully implemented. template ostream & operator<<(ostream & os, smc::history h) { h.StreamParticles(os); return os; } } #endif lib/0000755000175000017500000000000013121745725010221 5ustar adamadamMakefile0000755000175000017500000000073013121737221011106 0ustar adamadam.PHONY: docs clean distclean examples default: libraries examples all: libraries docs examples clean: make -Csrc clean make -Cexamples clean -rm *~ -rm */*~ distclean: clean -rm bin/* -rm lib/* -rm -Rf doc/* libraries: make -Csrc all docs: make -Csrc/doxygen all make -Cdoc/latex all cp doc/latex/refman.pdf doc examples: make -Cexamples all dist: distclean tar -cf ../smctc.tar * bzip2 ../smctc.tar tar -cf ../smctc.tar * zip -r ../smctc.zip *Makefile.in0000644000175000017500000000010213121737221011501 0ustar adamadamCCFLAGS = -O3 CC = g++ CBLAS = gslcblas LFLAGS = -lgsl -l$(CBLAS) msvc/0000755000175000017500000000000013121737222010414 5ustar adamadammsvc/smctc.vcproj0000755000175000017500000000751513121737222012765 0ustar adamadam README.txt0000644000175000017500000001003313121737221011136 0ustar adamadamSMCTC 1.0: Sequential Monte Carlo Template Class ---------------------------------------------------- Last modified: 2009-04-15 Author / Maintainer: Adam M. Johansen (a.m.johansen@warwick.ac.uk) Website: http://www2.warwick.ac.uk/fac/sci/statistics/staff/academic/johansen/smctc/ This file provides a very brief overview of the SMCTC software. It is not intended to replace the documentation available both in the form of the automatically generated reference guide or the accompanying article. 1. Overview: Sequential Monte Carlo methods are a very general class of Monte Carlo methods for sampling from sequences of distributions. Simple examples of these algorithms are used very widely in the tracking and signal processing literature. Recent developments illustrate that these techniques have much more general applicability, and can be applied very effectively to statistical inference problems. Unfortunately, these methods are often perceived as being computationally expensive and difficult to implement. This software and the accompanying article (SMCTC: Sequential Monte Carlo in C++) seeks to address both of these problems. A C++ template class library for the efficient and convenient implementation of very general Sequential Monte Carlo algorithms is provided. Two example applications are provided: a simple particle filter for illustrative purposes and a state-of-the-art algorithm for rare event estimation. 2. Installation: 2.1 Prerequisites Use of this software requires a working C++ implementation and that the GNU Scientific Library (GSL) is installed and working. It is necessary to either have a working make environment or to make use of the proprietary project and solution file approach provided by Microsoft Visual Studio. If the libraries are not available in the directories searched by the compiler then it may be necessary to modify the Makefile so that the appropriate search paths are supplied to the compiler and linker. 2.2 Installation Procedure This section assumes that the Makefile is being used from a command line interpreter of some description. Windows users may prefer to make use of the Visual studio solution and project files which are provided. See the main documentation and the project file itself for details of this alternative. In a sense, installation is a minimal procedure. The software should be placed in an appropriate directory and the command make libraries within the top-level directory will compile the binary portion of the library and copy it to the lib subdirectory. Several optional steps will make it easier to make use of the library: After compiling the library there will be a static library named libsmctc.a within the lib subdirectory. This should either be copied to your preferred library location (typically /usr/lib on a Linux system) or its locations must be specified every time the library is used. The header files contained within the include subdirectory should be copied to a system-wide include directory (such as /usr/include) or it will be necessary to specify the location of the SMCTC include directory whenever a file which makes use of the library is compiled. 3. Using SMCTC: In order to use the library one simply needs to write C++ code which makes use of the templated-objects provided by the library and then to link the resulting object files against the SMCTC library as well as the GSL. The example programs can be compiled by entering the command: make examples in the top-level directory. The use of a Makefile is not essential at this stage; compilation proceeds rather simply in the case of self-contained applications. The following commands, for example, are sufficient to compile the example program described in section 5.1: g ++ -I ../../ include -c pfexample . cc pffuncs . cc g ++ pfexample . o pffuncs . o -L ../../ lib - lsmctc - lgsl - lgslcblas - opf It is, of course, advisable to include some additional options to encourage the compiler to optimise the code as much as possible once it has been debugged. Please see the associated documentation for more details. smctc.sln0000755000175000017500000000413113121737221011274 0ustar adamadam Microsoft Visual Studio Solution File, Format Version 9.00 # Visual C++ Express 2005 Project("{8BC9CEB8-8B4A-11D0-8D11-00A0C91BC942}") = "smctc", "msvc\smctc.vcproj", "{F1098C35-639C-408B-A6B7-C3625938DCF5}" EndProject Project("{8BC9CEB8-8B4A-11D0-8D11-00A0C91BC942}") = "pf", "examples\pf\msvc\pf.vcproj", "{2E16E037-35C3-44A3-B565-52A223C2E375}" ProjectSection(ProjectDependencies) = postProject {F1098C35-639C-408B-A6B7-C3625938DCF5} = {F1098C35-639C-408B-A6B7-C3625938DCF5} EndProjectSection EndProject Project("{8BC9CEB8-8B4A-11D0-8D11-00A0C91BC942}") = "rare-events", "examples\rare-events\msvc\rare-events.vcproj", "{45B2C46E-3497-43E7-9D21-EADB14093CDB}" ProjectSection(ProjectDependencies) = postProject {F1098C35-639C-408B-A6B7-C3625938DCF5} = {F1098C35-639C-408B-A6B7-C3625938DCF5} EndProjectSection EndProject Global GlobalSection(SolutionConfigurationPlatforms) = preSolution Debug|Win32 = Debug|Win32 Release|Win32 = Release|Win32 EndGlobalSection GlobalSection(ProjectConfigurationPlatforms) = postSolution {F1098C35-639C-408B-A6B7-C3625938DCF5}.Debug|Win32.ActiveCfg = Debug|Win32 {F1098C35-639C-408B-A6B7-C3625938DCF5}.Debug|Win32.Build.0 = Debug|Win32 {F1098C35-639C-408B-A6B7-C3625938DCF5}.Release|Win32.ActiveCfg = Release|Win32 {F1098C35-639C-408B-A6B7-C3625938DCF5}.Release|Win32.Build.0 = Release|Win32 {2E16E037-35C3-44A3-B565-52A223C2E375}.Debug|Win32.ActiveCfg = Debug|Win32 {2E16E037-35C3-44A3-B565-52A223C2E375}.Debug|Win32.Build.0 = Debug|Win32 {2E16E037-35C3-44A3-B565-52A223C2E375}.Release|Win32.ActiveCfg = Release|Win32 {2E16E037-35C3-44A3-B565-52A223C2E375}.Release|Win32.Build.0 = Release|Win32 {45B2C46E-3497-43E7-9D21-EADB14093CDB}.Debug|Win32.ActiveCfg = Debug|Win32 {45B2C46E-3497-43E7-9D21-EADB14093CDB}.Debug|Win32.Build.0 = Debug|Win32 {45B2C46E-3497-43E7-9D21-EADB14093CDB}.Release|Win32.ActiveCfg = Release|Win32 {45B2C46E-3497-43E7-9D21-EADB14093CDB}.Release|Win32.Build.0 = Release|Win32 EndGlobalSection GlobalSection(SolutionProperties) = preSolution HideSolutionNode = FALSE EndGlobalSection EndGlobal src/0000755000175000017500000000000013121745725010242 5ustar adamadamsrc/history.cc0000755000175000017500000000076213121737222012253 0ustar adamadam#include "smctc.hh" //! \file //! \brief This file contains the untemplated functions used for storing the history of the system. namespace smc { /// This constructor produces an initialised historyflags instance. /// /// \param wasResampled An indicator which should be nonzero if the particle /// system was resampled during the iteration being described historyflags::historyflags(int wasResampled) { if(wasResampled) Resampled = 1; else Resampled = 0; } } src/Makefile0000755000175000017500000000044413121737222011700 0ustar adamadaminclude ../Makefile.in SMCC = rng.cc history.cc smc-exception.cc SMCO = rng.o history.o smc-exception.o all: libsmctc.a .PHONY: clean clean: -rm *.o -rm *.a -rm *~ libsmctc.a: $(SMCC) Makefile $(CC) $(CCFLAGS) -c -I../include $(SMCC) ar rcs libsmctc.a $(SMCO) cp libsmctc.a ../lib src/rng.cc0000755000175000017500000002151513121737222011337 0ustar adamadam#include #include //! \file //! \brief This file contains the untemplated functions used for dealing with random number generation. #include "rng.hh" #include "smctc.hh" namespace smc { ///The GSL provides a mechanism for obtaining a list of available random number generators. /// ///This class provides a wrapper for this mechanism and makes it simple to implement software which allows ///the nature of the random number generator to be specified at runtime (and to allow it to be a user-specifiable ///parameter). /// ///For example, gslrnginfo::GetNumber can be used to determine how many RNGs are available and gslrnginfo::GetNameByIndex ///can then be used to populate a list box with their names. Once the user has selected on the gslrnginfo::GetPointerByName ///function can be used to obtain a pointer to the appropriate type and this can be used to produce a random number generator ///of the desired type. /// ///There should be exactly one instance of this class in any program, and that instance is created by ///the library. A singleton DP implementation ensures that any additional attempt to instatiate the class simply returns ///a reference to the existing instance. gslrnginfo::gslrnginfo() { typePtArray = gsl_rng_types_setup(); const gsl_rng_type** ptIndex = typePtArray; nNumber = 0; while(ptIndex[0]) { ptIndex++; nNumber++; } return; } ///Returns a pointer to a single instance of this class. gslrnginfo* gslrnginfo::GetInstance() { static gslrnginfo ginfo; return &ginfo; } ///This function returns the number of available generators int gslrnginfo::GetNumber(void) { return nNumber; } ///This function returns the name of the specified generator const char* gslrnginfo::GetNameByIndex(int nIndex) { if(0 <= nIndex && nIndex < nNumber) return typePtArray[nIndex]->name; return NULL; } ///This function returns a pointer to the specified generator type const gsl_rng_type* gslrnginfo::GetPointerByIndex(int nIndex) { if(0 <= nIndex && nIndex < nNumber) return typePtArray[nIndex]; return NULL; } ///This function returns a pointer to the specified generator type const gsl_rng_type* gslrnginfo::GetPointerByName(const char* szName) { for(int n = 0; n < nNumber; n++) if(!strcmp(typePtArray[n]->name, szName)) return typePtArray[n]; return NULL; } ///When called without any arguments, the constructor for the smc::rng class simply allocates a buffer for a ///random number generator of type gsl_rng_default (something which can be set at run-time via an environment ///variable) using its default seed (which again can be over-ridden using an environment variable). rng::rng(void) { gsl_rng_env_setup(); type = gsl_rng_default; pWorkspace = gsl_rng_alloc(gsl_rng_default); } ///When called with a single argument, the constructor for the smc::rng class allocates a buffer for a ///random number generator of the specified type and initialises it with the default seed (which can be set using ///and environment variable if one wishes to vary it at run-time). /// ///\param Type The type of a GSL random number generator rng::rng(const gsl_rng_type* Type) { gsl_rng_env_setup(); type = Type; pWorkspace = gsl_rng_alloc(Type); } ///When called with a pair of arguments, the constructor for the smc::rng class allocates a buffer for the specified ///random number generator type and initialises it with the specified seed (note that zero has special significance and ///is used to specify the seed with which the generator was originally used). /// ///\param Type The type of a GSL random number generator ///\param lSeed The value with which the generator is to be seeded rng::rng(const gsl_rng_type* Type, unsigned long int lSeed) { gsl_rng_env_setup(); type = Type; pWorkspace = gsl_rng_alloc(Type); gsl_rng_set(pWorkspace, lSeed); } ///The destructor presently does no more than call the gsl_rng_free function to deallocate the memory which was ///previously allocate to the random number generator. rng::~rng() { gsl_rng_free(pWorkspace); } ///This function returns a pointer to the underlying GSL random number generator which may be used to provide random ///number facilities which are not explicitly provided by the intermediate layer of smc::rng. gsl_rng* rng::GetRaw(void) { return pWorkspace; } ///This function simply passes the relevant arguments on to gsl_ran_multinomial. /// \param n Number of entities to assign. /// \param k Number of categories. /// \param w Weights of category elements /// \param X Array in which to return the sample values. void rng::Multinomial(unsigned n, unsigned k, const double* w, unsigned* X) { gsl_ran_multinomial(pWorkspace, k, n, w, X); } ///This function simply calls gsl_rng_uniform_int and shifts the /// result as appropriate such that the result is an integer generated uniformly from those between /// the two arguments (inclusive of those points). /// /// \param lMin The smallest value which can be returned /// \param lMax the largest value which can be returned long rng::UniformDiscrete(long lMin, long lMax) { return gsl_rng_uniform_int(pWorkspace, lMax - lMin + 1) + lMin; } ///This function simply calls gsl_ran_beta with the specified parameters. /// \param da The parameter associated with "x". /// \paran db The parameter associated with "1-x". double rng::Beta(double da, double db) { return gsl_ran_beta(pWorkspace, da, db); } ///This function simply calls gsl_ran_cauchy with the specified parameter. /// \param dScale The scale parameter of the distribution. double rng::Cauchy(double dScale) { return gsl_ran_cauchy(pWorkspace, dScale); } ///This function simply calls gsl_ran_exponential with the specified parameters. /// \param dMean The scale (not rate) (and mean) of the distribution. double rng::Exponential(double dMean) { return gsl_ran_exponential(pWorkspace, dMean); } ///This function simply calls gsl_ran_gamma with the specified parameters. /// \param dAlpha The shape of the distribution (integers lead to Erlang distributions) /// \param dBeta The scale (not rate) of the distribution. double rng::Gamma(double dAlpha, double dBeta) { return gsl_ran_gamma(pWorkspace, dAlpha, dBeta); } ///This function simply calls gsl_ran_laplace with the specified parameters. /// \param dScale The scale (not rate) of the distribution. /// double rng::Laplacian(double dScale) { return gsl_ran_laplace(pWorkspace, dScale); } ///This function simply calls gsl_ran_lognormal with the specified parameters. /// \param dMu The location parameter of the distribution. /// \param dSigma The scale parameter of the distribution. double rng::Lognormal(double dMu, double dSigma) { return gsl_ran_lognormal(pWorkspace, dMu, dSigma); } ///This function simply calls gsl_ran_gaussian with the specified standard deviation and shifts the result. /// \param dMean The mean of the distribution. /// \param dStd The standard deviation of the distribution double rng::Normal(double dMean, double dStd) { return dMean + gsl_ran_gaussian(pWorkspace, dStd); } ///This function simply calls gsl_ran_ugaussian returns the result. double rng::NormalS(void) { return gsl_ran_ugaussian(pWorkspace); } ///This function simply calls gsl_ran_gaussian_tail with the specified parameters and performs appropriate shifting. /// \param dMean The mean of the distribution. /// \param dStd The standard deviation of the distribution /// \param dThreshold The lower truncation threshold. double rng::NormalTruncated(double dMean, double dStd, double dThreshold) { return dMean + gsl_ran_gaussian_tail(pWorkspace, dThreshold - dMean, dStd); } ///This function simply calls gsl_ran_tdist with the specified number of degrees of freedom. /// \param dDF The number of degrees of freedom. double rng::StudentT(double dDF) { return gsl_ran_tdist(pWorkspace, dDF); } ///This function simply calls gsl_rng_uniform and scales and shifts appropriately. /// \param dMin The lowest value with positive density. /// \param dMax The largest value with positive density. double rng::Uniform(double dMin, double dMax) { double rValue; rValue = gsl_rng_uniform(pWorkspace); rValue *= (dMax - dMin); rValue += dMin; return rValue; } ///This function simply calls gsl_rng_uniform. double rng::UniformS(void) { return gsl_rng_uniform(pWorkspace); } } src/smc-exception.cc0000755000175000017500000000237013121737222013325 0ustar adamadam#include "smc-exception.hh" //! \file //! \brief The untemplated smc::exception class is implemented here. namespace smc { //! Generate an SMCTC Exception class with the specified initialisation. //! This constructor fills the four elements of the class with their specified values. //! It is used to allow a single-line command to create and throw an exception. //! //! \param szN The name of the source file generating the exception. //! \param lL The line in that file responsible for the exception. //! \param lC The numerical code identifying the exception. //! \param szM An textual explanation of the problem. exception::exception(char const * szN, long lL, long lC, char const * szM) { szFile = szN; lLine = lL; lCode = lC; szMessage = szM; } } namespace std { ///Display a human-readable version of an SMC exception. /// \param os The stream to write to. /// \param e The exception class to display. /// \return os std::ostream & operator<< (std::ostream & os, smc::exception & e) { os << "SMC Exception: #" << e.lCode << endl; os << "Error occured in file " << e.szFile << " at line " << e.lLine << "." << endl; os << "Details: " << endl << '\t' << e.szMessage << endl; return os; } } src/doxygen/0000755000175000017500000000000013121737222011710 5ustar adamadamsrc/doxygen/Makefile0000755000175000017500000000002713121737222013352 0ustar adamadamall: doxygen Doxyfile src/doxygen/header.tex0000755000175000017500000000204313121737222013664 0ustar adamadam\documentclass[a4paper]{book} \usepackage{a4wide} \usepackage{makeidx} \usepackage{fancyhdr} \usepackage{graphicx} \usepackage{multicol} \usepackage{float} \usepackage{textcomp} \usepackage{alltt} \usepackage{times} \usepackage{ifpdf} \ifpdf \usepackage[pdftex, pagebackref=true, colorlinks=true, linkcolor=blue, unicode ]{hyperref} \else \usepackage[ps2pdf, pagebackref=true, colorlinks=true, linkcolor=blue, unicode ]{hyperref} \usepackage{pspicture} \fi \usepackage[utf8]{inputenc} \usepackage{doxygen} \makeindex \setcounter{tocdepth}{1} \renewcommand{\footrulewidth}{0.4pt} \begin{document} \begin{titlepage} \vspace*{7cm} \begin{center} {\Large SMC Template Class 1.0 \\[1ex]\large Adam M. Johansen }\\ \vspace*{1cm} {Generated by Doxygen 1.5.5}\\ \vspace*{0.5cm} {\small Mon Jul 14 16:34:16 2008}\\ \end{center} \end{titlepage} \clearemptydoublepage \pagenumbering{roman} \tableofcontents \clearemptydoublepage \pagenumbering{arabic} src/doxygen/Doxyfile0000755000175000017500000002445613121737222013434 0ustar adamadam# Doxyfile 1.5.5 #--------------------------------------------------------------------------- # Project related configuration options #--------------------------------------------------------------------------- DOXYFILE_ENCODING = UTF-8 PROJECT_NAME = "SMC Template Class 1.0" PROJECT_NUMBER = 1.0 OUTPUT_DIRECTORY = ../../doc/ CREATE_SUBDIRS = NO OUTPUT_LANGUAGE = English BRIEF_MEMBER_DESC = YES REPEAT_BRIEF = YES ABBREVIATE_BRIEF = "The $name class" \ "The $name widget" \ "The $name file" \ is \ provides \ specifies \ contains \ represents \ a \ an \ the ALWAYS_DETAILED_SEC = NO INLINE_INHERITED_MEMB = NO FULL_PATH_NAMES = YES STRIP_FROM_PATH = ../../ STRIP_FROM_INC_PATH = SHORT_NAMES = NO JAVADOC_AUTOBRIEF = NO QT_AUTOBRIEF = NO MULTILINE_CPP_IS_BRIEF = NO DETAILS_AT_TOP = NO INHERIT_DOCS = YES SEPARATE_MEMBER_PAGES = NO TAB_SIZE = 5 ALIASES = OPTIMIZE_OUTPUT_FOR_C = NO OPTIMIZE_OUTPUT_JAVA = NO OPTIMIZE_FOR_FORTRAN = NO OPTIMIZE_OUTPUT_VHDL = NO BUILTIN_STL_SUPPORT = NO CPP_CLI_SUPPORT = NO SIP_SUPPORT = NO DISTRIBUTE_GROUP_DOC = NO SUBGROUPING = YES TYPEDEF_HIDES_STRUCT = NO #--------------------------------------------------------------------------- # Build related configuration options #--------------------------------------------------------------------------- EXTRACT_ALL = YES EXTRACT_PRIVATE = YES EXTRACT_STATIC = YES EXTRACT_LOCAL_CLASSES = YES EXTRACT_LOCAL_METHODS = YES EXTRACT_ANON_NSPACES = NO HIDE_UNDOC_MEMBERS = NO HIDE_UNDOC_CLASSES = NO HIDE_FRIEND_COMPOUNDS = NO HIDE_IN_BODY_DOCS = NO INTERNAL_DOCS = NO CASE_SENSE_NAMES = YES HIDE_SCOPE_NAMES = NO SHOW_INCLUDE_FILES = YES INLINE_INFO = YES SORT_MEMBER_DOCS = YES SORT_BRIEF_DOCS = NO SORT_GROUP_NAMES = NO SORT_BY_SCOPE_NAME = NO GENERATE_TODOLIST = YES GENERATE_TESTLIST = YES GENERATE_BUGLIST = YES GENERATE_DEPRECATEDLIST= YES ENABLED_SECTIONS = MAX_INITIALIZER_LINES = 30 SHOW_USED_FILES = YES SHOW_DIRECTORIES = NO FILE_VERSION_FILTER = #--------------------------------------------------------------------------- # configuration options related to warning and progress messages #--------------------------------------------------------------------------- QUIET = YES WARNINGS = NO WARN_IF_UNDOCUMENTED = NO WARN_IF_DOC_ERROR = NO WARN_NO_PARAMDOC = NO WARN_FORMAT = "$file:$line: $text" WARN_LOGFILE = #--------------------------------------------------------------------------- # configuration options related to the input files #--------------------------------------------------------------------------- INPUT = ../../include \ ../../src INPUT_ENCODING = UTF-8 FILE_PATTERNS = *.c \ *.cc \ *.cxx \ *.cpp \ *.c++ \ *.d \ *.java \ *.ii \ *.ixx \ *.ipp \ *.i++ \ *.inl \ *.h \ *.hh \ *.hxx \ *.hpp \ *.h++ \ *.idl \ *.odl \ *.cs \ *.php \ *.php3 \ *.inc \ *.m \ *.mm \ *.dox \ *.C \ *.CC \ *.C++ \ *.II \ *.I++ \ *.H \ *.HH \ *.H++ \ *.CS \ *.PHP \ *.PHP3 \ *.M \ *.MM RECURSIVE = NO EXCLUDE = EXCLUDE_SYMLINKS = NO EXCLUDE_PATTERNS = EXCLUDE_SYMBOLS = EXAMPLE_PATH = EXAMPLE_PATTERNS = * EXAMPLE_RECURSIVE = NO IMAGE_PATH = INPUT_FILTER = FILTER_PATTERNS = FILTER_SOURCE_FILES = NO #--------------------------------------------------------------------------- # configuration options related to source browsing #--------------------------------------------------------------------------- SOURCE_BROWSER = YES INLINE_SOURCES = NO STRIP_CODE_COMMENTS = YES REFERENCED_BY_RELATION = YES REFERENCES_RELATION = YES REFERENCES_LINK_SOURCE = YES USE_HTAGS = NO VERBATIM_HEADERS = YES #--------------------------------------------------------------------------- # configuration options related to the alphabetical class index #--------------------------------------------------------------------------- ALPHABETICAL_INDEX = NO COLS_IN_ALPHA_INDEX = 5 IGNORE_PREFIX = #--------------------------------------------------------------------------- # configuration options related to the HTML output #--------------------------------------------------------------------------- GENERATE_HTML = YES HTML_OUTPUT = html HTML_FILE_EXTENSION = .html HTML_HEADER = HTML_FOOTER = HTML_STYLESHEET = HTML_ALIGN_MEMBERS = YES GENERATE_HTMLHELP = NO GENERATE_DOCSET = NO DOCSET_FEEDNAME = "Doxygen generated docs" DOCSET_BUNDLE_ID = org.doxygen.Project HTML_DYNAMIC_SECTIONS = NO CHM_FILE = HHC_LOCATION = GENERATE_CHI = NO BINARY_TOC = NO TOC_EXPAND = NO DISABLE_INDEX = NO ENUM_VALUES_PER_LINE = 4 GENERATE_TREEVIEW = YES TREEVIEW_WIDTH = 250 #--------------------------------------------------------------------------- # configuration options related to the LaTeX output #--------------------------------------------------------------------------- GENERATE_LATEX = YES LATEX_OUTPUT = latex LATEX_CMD_NAME = latex MAKEINDEX_CMD_NAME = makeindex COMPACT_LATEX = NO PAPER_TYPE = a4wide EXTRA_PACKAGES = LATEX_HEADER = header.tex PDF_HYPERLINKS = YES USE_PDFLATEX = YES LATEX_BATCHMODE = NO LATEX_HIDE_INDICES = NO #--------------------------------------------------------------------------- # configuration options related to the RTF output #--------------------------------------------------------------------------- GENERATE_RTF = NO RTF_OUTPUT = rtf COMPACT_RTF = NO RTF_HYPERLINKS = NO RTF_STYLESHEET_FILE = RTF_EXTENSIONS_FILE = #--------------------------------------------------------------------------- # configuration options related to the man page output #--------------------------------------------------------------------------- GENERATE_MAN = NO MAN_OUTPUT = man MAN_EXTENSION = .3 MAN_LINKS = NO #--------------------------------------------------------------------------- # configuration options related to the XML output #--------------------------------------------------------------------------- GENERATE_XML = NO XML_OUTPUT = xml XML_SCHEMA = XML_DTD = XML_PROGRAMLISTING = YES #--------------------------------------------------------------------------- # configuration options for the AutoGen Definitions output #--------------------------------------------------------------------------- GENERATE_AUTOGEN_DEF = NO #--------------------------------------------------------------------------- # configuration options related to the Perl module output #--------------------------------------------------------------------------- GENERATE_PERLMOD = NO PERLMOD_LATEX = NO PERLMOD_PRETTY = YES PERLMOD_MAKEVAR_PREFIX = #--------------------------------------------------------------------------- # Configuration options related to the preprocessor #--------------------------------------------------------------------------- ENABLE_PREPROCESSING = YES MACRO_EXPANSION = NO EXPAND_ONLY_PREDEF = NO SEARCH_INCLUDES = YES INCLUDE_PATH = INCLUDE_FILE_PATTERNS = PREDEFINED = EXPAND_AS_DEFINED = SKIP_FUNCTION_MACROS = YES #--------------------------------------------------------------------------- # Configuration::additions related to external references #--------------------------------------------------------------------------- TAGFILES = GENERATE_TAGFILE = ALLEXTERNALS = NO EXTERNAL_GROUPS = YES PERL_PATH = /usr/bin/perl #--------------------------------------------------------------------------- # Configuration options related to the dot tool #--------------------------------------------------------------------------- CLASS_DIAGRAMS = YES MSCGEN_PATH = HIDE_UNDOC_RELATIONS = NO HAVE_DOT = YES CLASS_GRAPH = YES COLLABORATION_GRAPH = YES GROUP_GRAPHS = YES UML_LOOK = NO TEMPLATE_RELATIONS = YES INCLUDE_GRAPH = YES INCLUDED_BY_GRAPH = YES CALL_GRAPH = YES CALLER_GRAPH = NO GRAPHICAL_HIERARCHY = YES DIRECTORY_GRAPH = YES DOT_IMAGE_FORMAT = png DOT_PATH = DOTFILE_DIRS = DOT_GRAPH_MAX_NODES = 50 MAX_DOT_GRAPH_DEPTH = 1000 DOT_TRANSPARENT = NO DOT_MULTI_TARGETS = NO GENERATE_LEGEND = YES DOT_CLEANUP = YES #--------------------------------------------------------------------------- # Configuration::additions related to the search engine #--------------------------------------------------------------------------- SEARCHENGINE = NO Thanks0000644000175000017500000000044313121746163010624 0ustar adamadamThanks for testing the software on a variety of platforms: Mark Briers (who also kindly contributed the visual C++ project and solution files) Edmund Jackson Bug reports: Mathieu Fourment Roman Holenstein Martin Sewell Several useful suggestions were also made by two anonymous referees.