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ulcessvp |
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#ifndef SEQ_OPTIMIZE_TEMPLATE_H
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#define SEQ_OPTIMIZE_TEMPLATE_H
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#include <iostream>
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#include <cstdlib>
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#include <sys/time.h>
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ulcessvp |
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#ifdef _OPENMP
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ulcessvp |
12 |
#include <omp.h>
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#endif
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class Siman {
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int _nvars;
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unsigned _seed;
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unsigned _seedM;
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unsigned _seedP;
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int _l;
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int _nt;
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int _NT;
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int _ns;
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int _NS;
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IntVector _param;
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DoubleVector* _x;
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DoubleVector* _lowerb;
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DoubleVector* _upperb;
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DoubleVector _vm;
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double _t;
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double _rt;
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IntVector _nacp;
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int _nacc; //The number of accepted function evaluations
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int _nrej; //The number of rejected function evaluations
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int _naccmet; //The number of metropolis accepted function evaluations
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double _nsdiv;
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int _tempcheck;
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double _simanneps;
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DoubleVector _fstar;
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double _lratio;
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double _uratio;
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double _cs;
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DoubleVector* _bestx;
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int _scale;
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int* _converge; //NN
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double* _score; //NN
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public:
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//Required Default constructor : Params()
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Siman(){
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_nvars = 0;
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_seed = 1234;
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_seedM = 1234;
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_seedP = 1234;
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_l = 0;
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_nt = 0;
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_NT = 0;
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_ns = 0;
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_NS = 0;
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_param = IntVector();
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_x = NULL;
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_lowerb = NULL;
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_upperb = NULL;
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_vm = DoubleVector();
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_t = 0.;
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_rt = 0.;
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_nacp = IntVector();
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_nacc = 0; //The number of accepted function evaluations
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_nrej = 0; //The number of rejected function evaluations
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_naccmet = 0; //The number of metropolis accepted function evaluations
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_nsdiv = 0;
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_tempcheck = 0;
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_simanneps = 0;
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_fstar = DoubleVector();
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_lratio = 0.;
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_uratio = 0.;
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_cs = 0.;
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_bestx = NULL;
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_scale = 0;
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_converge =NULL;
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_score = 0;
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}
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Siman(unsigned &seed, unsigned &seedM, unsigned &seedP, int &nvars, int &nt, int &ns, IntVector param, DoubleVector* x,
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DoubleVector* lowerb, DoubleVector* upperb, DoubleVector vm, double t, double &rt,
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double nsdiv, int &tempcheck, double &simanneps, DoubleVector fstar,
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double &lratio, double &uratio, double &cs, DoubleVector* bestx, int &scale, int* converge,
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double* score):
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_seed(seed), _seedM(seedM), _seedP(seedP), _l(0), _nvars(nvars), _nt(nt), _NT(0), _ns(ns), _NS(0), _t(t),
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_rt(rt), _nsdiv(nsdiv), _nacc(1), _tempcheck(tempcheck), _simanneps(simanneps), _lratio(lratio),
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_uratio(uratio), _cs(cs), _scale(scale){
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_param = IntVector(param);
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_x = x;
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_lowerb = lowerb;
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_upperb = upperb;
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_vm = DoubleVector(vm);
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_nacp = IntVector(_nvars, 0);
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_nrej = 0;
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_naccmet = 0;
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randomizeParams();
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_fstar = DoubleVector(fstar);
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_bestx = bestx;
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_converge = converge;
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_score = score;
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}
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//Required Copy constructor : Params(const Params& other)
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Siman(const Siman& other): _nvars(other._nvars), _seed(other._seed), _seedM(other._seedM), _seedP(other._seedP),
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_l(other._l), _nt(other._nt), _NT(other._NT), _ns(other._ns), _NS(other._NS), _param(IntVector(other._param)),
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_x(other._x), _lowerb(other._lowerb),_upperb(other._upperb), _vm(DoubleVector(other._vm)), _t(other._t),
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_rt(other._rt), _nacp(IntVector(other._nacp)), _nacc(other._nacc), _nrej(other._nrej),
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_naccmet(other._naccmet), _nsdiv(other._nsdiv), _tempcheck(other._tempcheck), _simanneps(other._simanneps),
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_fstar(DoubleVector(other._fstar)), _lratio(other._lratio), _uratio(other._uratio), _cs(other._cs),
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_bestx(other._bestx), _scale(other._scale), _converge(other._converge), _score(other._score){}
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//Required operator= : Params& operator= (const Params& other)
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Siman& operator= (const Siman& other){
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_nvars = other._nvars;
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_seed = other._seed;
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_seedM = other._seedM;
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_seedP = other._seedP;
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_l = other._l;
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_nt = other._nt;
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_NT = other._NT;
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_ns = other._ns;
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_NS = other._NS;
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_param = IntVector(other._param);
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_x = other._x;
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_lowerb = other._lowerb;
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_upperb = other._upperb;
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_vm = DoubleVector(other._vm);
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_t = other._t;
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_rt = other._rt;
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_nacp = IntVector(other._nacp);
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_nacc = other._nacc; //The number of accepted function evaluations
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_nrej = other._nrej; //The number of rejected function evaluations
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_naccmet = other._naccmet; //The number of metropolis accepted function evaluations
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_nsdiv = other._nsdiv;
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_tempcheck = other._tempcheck;
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_simanneps = other._simanneps;
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_fstar = DoubleVector(other._fstar);
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_lratio = other._lratio;
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_uratio = other._uratio;
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_cs = other._cs;
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_bestx = other._bestx;
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_scale = other._scale;
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_converge =other._converge;
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_score = other._score;
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return *this;
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}
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//Destructor : ~Params()
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~Siman(){
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}
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unsigned* getSeed(){return &_seed;}
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unsigned* getSeedM(){return &_seedM;}
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unsigned getSeedM_(){return _seedM;}
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void setSeedM(unsigned val){_seedM = val;}
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int getNvars(){return _nvars;}
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int getL(){return _l;}
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void incrementL() { _l = (_l +1) % _nvars;}
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IntVector& getParam(){return _param;}
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DoubleVector& getX(){return *_x;}
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void setX(DoubleVector* point) {_x=point;}
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DoubleVector& getLowerb(){return *_lowerb;}
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DoubleVector& getUpperb(){return *_upperb;}
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DoubleVector& getVm(){return _vm;}
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void setVm(DoubleVector vm){_vm = vm;}
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DoubleVector& getFstar(){return _fstar;}
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double getT(){return _t;}
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void setT(double val){_t = val;}
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void incrementNacc() {_nacc++;}
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void incrementNrej(){_nrej++;}
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void incrementNaccmet(){_naccmet++;}
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void incrementNacp(int i){_nacp[i]++;}
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void randomizeParams(){
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int rnumber, rcheck, i, rchange = 0;
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while (rchange < _nvars) {
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rnumber = rand_r(&_seedP) % _nvars;
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rcheck = 1;
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for (i = 0; i < rchange; i++)
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if ((_param)[i] == rnumber)
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rcheck = 0;
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if (rcheck) {
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(_param)[rchange] = rnumber;
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rchange++;
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}
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}
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}
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int getNs() const {return _ns;}
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int getNS() const {return _NS;}
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void setNS(int ns = 0) {_NS = ns;}
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void incrementNS() {_NS++;}
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int getNt() const {return _nt;}
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int getNT() const {return _NT;}
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void setNT(int nt) {_NT = nt;}
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void incrementNT() {_NT++;};
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double getSimanneps() const {return _simanneps;}
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int getTempcheck() const {return _tempcheck;}
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const int getNacp(int i) const {return _nacp[i];}
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void setNacp(int i, int val) {_nacp[i] = val;}
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double getCs() const {return _cs;}
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double getLratio() const {return _lratio;}
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double getUratio() const {return _uratio;}
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void setConverge(int val) {(*_converge) = val;}
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DoubleVector* getBestx() {return _bestx;}
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int getScale() const {return _scale;}
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double getRt() const {return _rt;}
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double getNsdiv() const {return _nsdiv;}
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int* getConverge() const {return _converge;}
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int getNacc() const {return _nacc;}
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int getNaccmet() const {return _naccmet;}
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int getNrej() const {return _nrej;}
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void setNrej(int nrej) {_nrej = nrej;};
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double* getScore() const {return _score;}
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};
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/* IMPROVEMENTS:
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- OpenMP parallel implementation added
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ulcessvp |
16 |
- Can be compiled with OpenMP using macro _OPENMP
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ulcessvp |
12 |
- Memory for items is dynamically reused in the parallel searches
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- Items whose evaluation has not begun when a new optimum is found are not evaluated (only possible in TBB search)
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*/
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/// Performs a reproducible optimization process, sequentially in seq_opt or in parallel in paral_opt
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template<class SEED_T, class PARAMS_T, class CONTROL_T, double Evaluator(
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const PARAMS_T&), void BuildNewParams(SEED_T&, PARAMS_T&)>
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class ReproducibleSearch {
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const SEED_T initialSeed_;
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const PARAMS_T initialParams_;
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const int maxIters_;
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SEED_T seed_;
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PARAMS_T p_;
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int iters_;
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double optimumValue_;
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double funcval_;
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double searchTime_;
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/// Stores an individual item to evaluate and the data to restore the search state
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/// if it is chosen as new optimum item
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struct ParalEvalItem_t {
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int order_;
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PARAMS_T p_;
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SEED_T seed_; ///< seed AFTER generation of p_
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double value_;
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ParalEvalItem_t(int order, const PARAMS_T& p, const SEED_T& seed,
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double value = 0.) :
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order_(order), p_(p), seed_(seed), value_(value) {
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}
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ParalEvalItem_t() :
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value_(0.) {
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}
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void evaluateItem() {
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value_ = Evaluator(p_);
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}
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void print() const {
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std::cout << order_ << ' ' << p_ << " v= " << value_ << std::endl;
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}
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};
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/// Internal storage for search items with a padding field to avoid false sharing
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struct ParalEvalItemStorage_t {
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ParalEvalItem_t pei_;
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char padding_[128];
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};
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public:
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ReproducibleSearch(const SEED_T& seed, const PARAMS_T& params, int max_iters = 200) :
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initialSeed_(seed), initialParams_(params), maxIters_(max_iters) {}
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// Set the problem in its initial state
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void reset() {
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seed_ = initialSeed_;
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p_ = initialParams_;
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std::cout << ": " << p_ << " v= " << Evaluator(p_) << std::endl;
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}
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//########################################################
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void seq_opt(double funcval) {
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struct timeval t0, t1, t;
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338 : |
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reset();
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339 : |
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CONTROL_T control_object;
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gettimeofday(&t0, NULL);
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342 : |
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seed_.setX(&p_);
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344 : |
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funcval_ = funcval;
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optimumValue_ = funcval_;
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347 : |
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bool quit = false;
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for (iters_ = 1; iters_ <= maxIters_; ++iters_) {
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PARAMS_T p = p_;
|
350 : |
|
|
|
351 : |
|
|
BuildNewParams(seed_, p);
|
352 : |
|
|
|
353 : |
|
|
const double prev_val = funcval_;
|
354 : |
|
|
const double val = Evaluator(p);
|
355 : |
|
|
|
356 : |
|
|
if (control_object.mustAccept(prev_val, val, seed_, iters_)) {
|
357 : |
|
|
int i;
|
358 : |
|
|
for (i = 0; i < seed_.getNvars(); i++){
|
359 : |
|
|
p_[i] = p[i];
|
360 : |
|
|
}
|
361 : |
|
|
funcval_ = val;
|
362 : |
|
|
} else if ((*seed_.getConverge()) == -1) return;
|
363 : |
|
|
|
364 : |
|
|
control_object.optimum(val, optimumValue_, iters_, p_, initialParams_, seed_);
|
365 : |
|
|
|
366 : |
|
|
if ((quit=control_object.mustTerminate(optimumValue_, funcval_, seed_, iters_))) {
|
367 : |
|
|
break;
|
368 : |
|
|
}
|
369 : |
|
|
}
|
370 : |
|
|
|
371 : |
|
|
control_object.printResult(quit, seed_, iters_);
|
372 : |
|
|
gettimeofday(&t1, NULL);
|
373 : |
|
|
timersub(&t1, &t0, &t);
|
374 : |
|
|
searchTime_ = t.tv_sec + t.tv_usec / 1000000.0;
|
375 : |
|
|
}
|
376 : |
|
|
|
377 : |
|
|
void paral_opt_omp(double funcval, int nthreads, int paral_tokens = -1) {
|
378 : |
|
|
struct timeval t0, t1, t;
|
379 : |
|
|
|
380 : |
|
|
reset();
|
381 : |
|
|
|
382 : |
|
|
CONTROL_T control_object;
|
383 : |
|
|
|
384 : |
|
|
gettimeofday(&t0, NULL);
|
385 : |
|
|
|
386 : |
|
|
#if defined(_OPENMP)
|
387 : |
|
|
omp_set_num_threads(nthreads);
|
388 : |
|
|
#endif
|
389 : |
|
|
|
390 : |
|
|
if (paral_tokens < 0) {
|
391 : |
|
|
paral_tokens = nthreads;
|
392 : |
|
|
}
|
393 : |
|
|
|
394 : |
|
|
seed_.setX(&p_);
|
395 : |
|
|
funcval_ = funcval;
|
396 : |
|
|
optimumValue_ = funcval_;
|
397 : |
|
|
bool quit = false;
|
398 : |
|
|
|
399 : |
|
|
ParalEvalItemStorage_t * const storage =
|
400 : |
|
|
new ParalEvalItemStorage_t[paral_tokens]; //Guarda los datos de los diferentes threads
|
401 : |
|
|
|
402 : |
|
|
int old_paral_tokens = paral_tokens;
|
403 : |
|
|
for (iters_ = 1; iters_ <= maxIters_;) {
|
404 : |
|
|
|
405 : |
|
|
if ((seed_.getL() + paral_tokens -1) >= seed_.getNvars())
|
406 : |
|
|
paral_tokens = seed_.getNvars() - seed_.getL();
|
407 : |
|
|
|
408 : |
|
|
if ((iters_ + paral_tokens - 1) > maxIters_) {
|
409 : |
|
|
paral_tokens = maxIters_ - (iters_ - 1);
|
410 : |
|
|
}
|
411 : |
|
|
|
412 : |
|
|
for (int i = 0; i < paral_tokens; i++) {
|
413 : |
|
|
storage[i].pei_.p_ = p_;
|
414 : |
|
|
BuildNewParams(seed_, storage[i].pei_.p_);
|
415 : |
|
|
storage[i].pei_.seed_ = seed_;
|
416 : |
|
|
seed_.incrementL();
|
417 : |
|
|
}
|
418 : |
|
|
const double prev_val = funcval_;
|
419 : |
|
|
|
420 : |
|
|
#pragma omp parallel for
|
421 : |
|
|
for (int i = 0; i < paral_tokens; i++) {
|
422 : |
|
|
storage[i].pei_.evaluateItem();
|
423 : |
|
|
}
|
424 : |
|
|
|
425 : |
|
|
int j, i=0; //Notice that we need it after the loop
|
426 : |
|
|
if (control_object.mustAccept(prev_val, storage[i].pei_.value_, storage[i].pei_.seed_, iters_+i)) {
|
427 : |
|
|
for (j = 0; j < seed_.getNvars(); j++)
|
428 : |
|
|
p_[j] = storage[i].pei_.p_[j];
|
429 : |
|
|
funcval_ = storage[i].pei_.value_;
|
430 : |
|
|
} else{
|
431 : |
|
|
if ((*storage[i].pei_.seed_.getConverge()) == -1) return;
|
432 : |
|
|
|
433 : |
|
|
for (i = 1; i < paral_tokens; i++) {
|
434 : |
|
|
storage[i].pei_.seed_.setSeedM(storage[i-1].pei_.seed_.getSeedM_());
|
435 : |
|
|
if (control_object.mustAccept(prev_val, storage[i].pei_.value_, storage[i].pei_.seed_, iters_+i)) {
|
436 : |
|
|
for (j = 0; j < seed_.getNvars(); j++)
|
437 : |
|
|
p_[j] = storage[i].pei_.p_[j];
|
438 : |
|
|
funcval_ = storage[i].pei_.value_;
|
439 : |
|
|
break;
|
440 : |
|
|
} else if ((*storage[i].pei_.seed_.getConverge()) == -1) return;
|
441 : |
|
|
}
|
442 : |
|
|
}
|
443 : |
|
|
i = (i == paral_tokens) ? (i - 1) : i;
|
444 : |
|
|
|
445 : |
|
|
seed_ = storage[i].pei_.seed_;
|
446 : |
|
|
seed_.setNrej(seed_.getNrej()+i);
|
447 : |
|
|
control_object.optimum(storage[i].pei_.value_, optimumValue_, iters_,
|
448 : |
|
|
storage[i].pei_.p_, initialParams_, seed_);
|
449 : |
|
|
|
450 : |
|
|
iters_ += i+1;
|
451 : |
|
|
|
452 : |
|
|
if ((quit=control_object.mustTerminate(optimumValue_, funcval_, seed_, iters_))) {
|
453 : |
|
|
break;
|
454 : |
|
|
}
|
455 : |
|
|
paral_tokens = old_paral_tokens;
|
456 : |
|
|
}
|
457 : |
|
|
control_object.printResult(quit, seed_ ,iters_);
|
458 : |
|
|
|
459 : |
|
|
gettimeofday(&t1, NULL);
|
460 : |
|
|
timersub(&t1, &t0, &t);
|
461 : |
|
|
searchTime_ = t.tv_sec + t.tv_usec / 1000000.0;
|
462 : |
|
|
|
463 : |
|
|
delete[] storage;
|
464 : |
|
|
}
|
465 : |
|
|
|
466 : |
|
|
/// Only used by sequential search when verbose
|
467 : |
|
|
void print(int iter, double val) const {
|
468 : |
|
|
ParalEvalItem_t v(iter, p_, seed_, val);
|
469 : |
|
|
v.print();
|
470 : |
|
|
}
|
471 : |
|
|
|
472 : |
|
|
const PARAMS_T& getResult() const {
|
473 : |
|
|
return p_;
|
474 : |
|
|
}
|
475 : |
|
|
|
476 : |
|
|
double getOptimumValue() const {
|
477 : |
|
|
return funcval_;
|
478 : |
|
|
}
|
479 : |
|
|
|
480 : |
|
|
double getSearchTime() const {
|
481 : |
|
|
return searchTime_;
|
482 : |
|
|
}
|
483 : |
|
|
|
484 : |
|
|
int iterations() const {
|
485 : |
|
|
return iters_;
|
486 : |
|
|
}
|
487 : |
|
|
|
488 : |
|
|
};
|
489 : |
|
|
|
490 : |
|
|
#endif
|