530 lines
13 KiB
C++
530 lines
13 KiB
C++
/*
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The MIT License
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Copyright (c) 2010, Stephen Waits <steve@waits.net>
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Permission is hereby granted, free of charge, to any person obtaining a copy
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of this software and associated documentation files (the "Software"), to deal
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in the Software without restriction, including without limitation the rights
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to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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copies of the Software, and to permit persons to whom the Software is
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furnished to do so, subject to the following conditions:
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The above copyright notice and this permission notice shall be included in
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all copies or substantial portions of the Software.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
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THE SOFTWARE.
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*/
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#ifndef __de_inl__
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#define __de_inl__
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#include <cstdio>
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#include <cmath>
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#if !(defined(__de_h__))
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# error "de.inl should only be included by de.h"
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#endif
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template <unsigned int DIM, unsigned int POPSIZE>
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const double DE::Engine<DIM,POPSIZE>::DEFAULTSCALE = 0.85;
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template <unsigned int DIM, unsigned int POPSIZE>
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const double DE::Engine<DIM,POPSIZE>::DEFAULTCROSSOVER = 1.0;
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template <unsigned int DIM, unsigned int POPSIZE>
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const double DE::Engine<DIM,POPSIZE>::DEFAULTRANGE= 0.1;
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template <unsigned int DIM, unsigned int POPSIZE>
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const double DE::Engine<DIM,POPSIZE>::BIGDOUBLE = 1.79e308; // close to max double
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template <unsigned int DIM, unsigned int POPSIZE>
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inline DE::Engine<DIM,POPSIZE>::Engine()
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{
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// set defaults
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scale = DEFAULTSCALE;
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crossover = DEFAULTCROSSOVER;
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for ( unsigned int i=0;i<DIM;++i )
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{
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this->mean[i] = 0.0;
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this->variance[i] = DEFAULTRANGE;
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}
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// create an initial population
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Reset();
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return;
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}
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template <unsigned int DIM, unsigned int POPSIZE>
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inline DE::Engine<DIM,POPSIZE>::~Engine()
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{
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return;
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}
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template <unsigned int DIM, unsigned int POPSIZE>
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inline void DE::Engine<DIM,POPSIZE>::Reset()
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{
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// reset our best
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bestfitness = BIGDOUBLE;
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for ( unsigned int i=0;i<DIM;i++ )
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{
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best[i] = 0.0;
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}
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// reset all vectors
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for ( unsigned int i=0;i<POPSIZE;i++ )
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{
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// energy tied for worst
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fitness[i] = bestfitness;
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// make a new individual
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for ( unsigned int j=0;j<DIM;j++ )
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{
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population[i][j] = prng.RandGaussian(mean[j],variance[j]);
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}
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}
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// reset state
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generation = 0;
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success = false;
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return;
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}
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template <unsigned int DIM, unsigned int POPSIZE>
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inline void DE::Engine<DIM,POPSIZE>::SetRange(double minimum, double maximum)
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{
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for (unsigned int i=0;i<DIM;i++)
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{
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SetRange(i,minimum,maximum);
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}
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return;
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}
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template <unsigned int DIM, unsigned int POPSIZE>
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inline void DE::Engine<DIM,POPSIZE>::SetRange(unsigned int i, double minimum, double maximum)
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{
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if (i<DIM)
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{
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this->mean[i] = (maximum+minimum)/2.0;
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this->variance[i] = (maximum-minimum)/2.0;
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}
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return;
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}
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template <unsigned int DIM, unsigned int POPSIZE>
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inline void DE::Engine<DIM,POPSIZE>::SetRange(const Vector<DIM>& minimum, const Vector<DIM>& maximum)
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{
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for (unsigned int i=0;i<DIM;i++)
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{
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SetRange(i,minimum[i],maximum[i]);
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}
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return;
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}
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template <unsigned int DIM, unsigned int POPSIZE>
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inline const double* DE::Engine<DIM,POPSIZE>::GetBest() const
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{
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return best;
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}
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template <unsigned int DIM, unsigned int POPSIZE>
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inline void DE::Engine<DIM,POPSIZE>::Select(
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unsigned int candidate,
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unsigned int *r1,
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unsigned int *r2,
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unsigned int *r3,
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unsigned int *r4,
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unsigned int *r5
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)
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{
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if ( r1 )
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{
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do
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{
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*r1 = prng.RandU32(0,POPSIZE-1);
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}
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while ( *r1 == candidate );
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}
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if ( r2 )
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{
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do
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{
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*r2 = prng.RandU32(0,POPSIZE-1);
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}
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while ( (*r2 == candidate) || (*r2 == *r1) );
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}
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if ( r3 )
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{
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do
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{
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*r3 = prng.RandU32(0,POPSIZE-1);
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}
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while ( (*r3 == candidate) || (*r3 == *r2) || (*r3 == *r1) );
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}
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if ( r4 )
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{
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do
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{
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*r4 = prng.RandU32(0,POPSIZE-1);
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}
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while ( (*r4 == candidate) || (*r4 == *r3) || (*r4 == *r2) || (*r4 == *r1) );
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}
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if ( r5 )
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{
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do
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{
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*r5 = prng.RandU32(0,POPSIZE-1);
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}
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while ( (*r5 == candidate) || (*r5 == *r4) || (*r5 == *r3) || (*r5 == *r2) || (*r5 == *r1) );
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}
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return;
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}
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template <unsigned int DIM, unsigned int POPSIZE>
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inline bool DE::Engine<DIM,POPSIZE>::Solve(unsigned int maxgenerations)
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{
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// spawn a new generation
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Reset();
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// run generations until max or success
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while(!success && generation<maxgenerations)
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{
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success = RunOneGeneration();
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}
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// output
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printf("====== RUN COMPLETE =============================================\n\n");
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Dump(bestfitness,best);
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// finished
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return success;
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}
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template <unsigned int DIM, unsigned int POPSIZE>
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bool DE::Engine<DIM,POPSIZE>::RunOneGeneration()
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{
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printf("====== GENERATION %07d =============================================\n\n",++generation);
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// attempt to improve each individual in the population
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for (int candidate=0;candidate<POPSIZE && !success;candidate++)
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{
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// create a new trial individual to test
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Vector<DIM> trial;
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MakeTrial_randtobest1exp(candidate,trial);
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// determine fitness of trial individual
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double trialfitness = TestFitness(trial,success);
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// see if the trial improved current candidate in population
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if ( trialfitness < fitness[candidate] )
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{
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// it did improve, save it
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fitness[candidate] = trialfitness;
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population[candidate] = trial;
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// see if it also improved upon our current best
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if ( trialfitness < bestfitness )
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{
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// it's better than the best, save it
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bestfitness = trialfitness;
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best = trial;
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// output new best
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Dump(bestfitness,best);
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}
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}
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}
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return success;
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}
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template <unsigned int DIM, unsigned int POPSIZE>
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inline void DE::Engine<DIM,POPSIZE>::Dump(const double& fitness, DE::Vector<DIM>& individual) const
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{
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printf(" fitness = %24.16f\n",fitness);
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for (unsigned int i=0;i<DIM;i++)
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{
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printf(" [%03d] = %24.16e\n",i,individual[i]);
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}
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printf("\n");
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}
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template <unsigned int DIM, unsigned int POPSIZE>
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inline void DE::Engine<DIM,POPSIZE>::MakeTrial_best1exp(unsigned int candidate, DE::Vector<DIM>& trial)
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{
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unsigned int r1, r2;
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unsigned int n;
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Select(candidate, &r1, &r2);
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n = prng.RandU32(0,DIM-1);
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trial = population[candidate];
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for (unsigned int i=0; (prng.RandDouble(0.0,1.0) < crossover) && (i < DIM); i++)
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{
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trial[n] = best[n] + scale * (population[r1][n] - population[r2][n]);
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n = (n + 1) % DIM;
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}
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return;
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}
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template <unsigned int DIM, unsigned int POPSIZE>
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inline void DE::Engine<DIM,POPSIZE>::MakeTrial_rand1exp(unsigned int candidate, DE::Vector<DIM>& trial)
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{
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unsigned int r1, r2, r3;
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unsigned int n;
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Select(candidate, &r1, &r2, &r3);
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n = prng.RandU32(0,DIM-1);
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trial = population[candidate];
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for (unsigned int i=0; (prng.RandDouble(0.0,1.0) <= crossover) && (i < DIM); i++)
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{
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trial[n] = population[r1][n] + scale * (population[r2][n] - population[r3][n]);
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n = (n + 1) % DIM;
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}
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return;
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}
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template <unsigned int DIM, unsigned int POPSIZE>
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inline void DE::Engine<DIM,POPSIZE>::MakeTrial_randtobest1exp(unsigned int candidate, DE::Vector<DIM>& trial)
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{
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unsigned int r1, r2;
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unsigned int n;
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Select(candidate, &r1, &r2);
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n = prng.RandU32(0,DIM-1);
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trial = population[candidate];
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for (unsigned int i=0; (prng.RandDouble(0.0,1.0) <= crossover) && (i < DIM); i++)
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{
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trial[n] += scale * (best[n] - trial[n]) + scale * (population[r1][n] - population[r2][n]);
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n = (n + 1) % DIM;
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}
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return;
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}
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template <unsigned int DIM, unsigned int POPSIZE>
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inline void DE::Engine<DIM,POPSIZE>::MakeTrial_best2exp(unsigned int candidate, DE::Vector<DIM>& trial)
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{
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unsigned int r1, r2, r3, r4;
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unsigned int n;
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Select(candidate, &r1, &r2, &r3, &r4);
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n = prng.RandU32(0,DIM-1);
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trial = population[candidate];
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for (unsigned int i=0; (prng.RandDouble(0.0,1.0) <= crossover) && (i < DIM); i++)
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{
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trial[n] = best[n] + scale * (population[r1][n] + population[r2][n] - population[r3][n] - population[r4][n]);
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n = (n + 1) % DIM;
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}
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return;
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}
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template <unsigned int DIM, unsigned int POPSIZE>
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inline void DE::Engine<DIM,POPSIZE>::MakeTrial_rand2exp(unsigned int candidate, DE::Vector<DIM>& trial)
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{
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unsigned int r1, r2, r3, r4, r5;
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unsigned int n;
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Select(candidate, &r1, &r2, &r3 ,&r4, &r5);
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n = prng.RandU32(0,DIM-1);
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trial = population[candidate];
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for (unsigned int i=0; (prng.RandDouble(0.0,1.0) <= crossover) && (i < DIM); i++)
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{
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trial[n] = population[r1][n] + scale * (population[r2][n] + population[r3][n] - population[r4][n] - population[r5][n]);
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n = (n + 1) % DIM;
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}
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return;
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}
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template <unsigned int DIM, unsigned int POPSIZE>
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inline void DE::Engine<DIM,POPSIZE>::MakeTrial_best1bin(unsigned int candidate, DE::Vector<DIM>& trial)
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{
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unsigned int r1, r2;
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unsigned int n;
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Select(candidate, &r1, &r2);
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n = prng.RandU32(0,DIM-1);
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trial = population[candidate];
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for (unsigned int i=0; i < DIM; i++)
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{
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if ( (prng.RandDouble(0.0,1.0) <= crossover) || (i == (DIM - 1)) )
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{
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trial[n] = best[n] + scale * (population[r1][n] - population[r2][n]);
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}
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n = (n + 1) % DIM;
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}
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return;
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}
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template <unsigned int DIM, unsigned int POPSIZE>
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inline void DE::Engine<DIM,POPSIZE>::MakeTrial_rand1bin(unsigned int candidate, DE::Vector<DIM>& trial)
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{
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unsigned int r1, r2, r3;
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unsigned int n;
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Select(candidate, &r1, &r2, &r3);
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n = prng.RandU32(0,DIM-1);
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trial = population[candidate];
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for (unsigned int i=0; i < DIM; i++)
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{
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if ( (prng.RandDouble(0.0,1.0) <= crossover) || (i == (DIM - 1)) )
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{
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trial[n] = population[r1][n] + scale * (population[r2][n] - population[r3][n]);
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}
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n = (n + 1) % DIM;
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}
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return;
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}
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template <unsigned int DIM, unsigned int POPSIZE>
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inline void DE::Engine<DIM,POPSIZE>::MakeTrial_randtobest1bin(unsigned int candidate, DE::Vector<DIM>& trial)
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{
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unsigned int r1, r2;
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unsigned int n;
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Select(candidate, &r1, &r2);
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n = prng.RandU32(0,DIM-1);
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trial = population[candidate];
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for (unsigned int i=0; i < DIM; i++)
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{
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if ( (prng.RandDouble(0.0,1.0) <= crossover) || (i == (DIM - 1)) )
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{
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trial[n] += scale * (best[n] - trial[n]) + scale * (population[r1][n] - population[r2][n]);
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}
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n = (n + 1) % DIM;
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}
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return;
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}
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template <unsigned int DIM, unsigned int POPSIZE>
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inline void DE::Engine<DIM,POPSIZE>::MakeTrial_best2bin(unsigned int candidate, DE::Vector<DIM>& trial)
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{
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unsigned int r1, r2, r3, r4;
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unsigned int n;
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Select(candidate, &r1, &r2, &r3, &r4);
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n = prng.RandU32(0,DIM-1);
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trial = population[candidate];
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for (unsigned int i=0; i < DIM; i++)
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{
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if ( (prng.RandDouble(0.0,1.0) <= crossover) || (i == (DIM - 1)) )
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{
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trial[n] = best[n] + scale * (population[r1][n] + population[r2][n] - population[r3][n] - population[r4][n]);
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}
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n = (n + 1) % DIM;
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}
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return;
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}
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template <unsigned int DIM, unsigned int POPSIZE>
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inline void DE::Engine<DIM,POPSIZE>::MakeTrial_rand2bin(unsigned int candidate, DE::Vector<DIM>& trial)
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{
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unsigned int r1, r2, r3, r4, r5;
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unsigned int n;
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Select(candidate, &r1, &r2, &r3, &r4, &r5);
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n = prng.RandU32(0,DIM-1);
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trial = population[candidate];
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for (unsigned int i=0; i < DIM; i++)
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{
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if ( (prng.RandDouble(0.0,1.0) <= crossover) || (i == (DIM - 1)) )
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{
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trial[n] = population[r1][n] + scale * (population[r2][n] + population[r3][n] - population[r4][n] - population[r5][n]);
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}
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n = (n + 1) % DIM;
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}
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return;
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}
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template <unsigned int DIM, unsigned int POPSIZE>
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inline DE::Engine<DIM,POPSIZE>::ErrorAccumulator::ErrorAccumulator()
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{
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Clear();
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}
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template <unsigned int DIM, unsigned int POPSIZE>
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inline DE::Engine<DIM,POPSIZE>::ErrorAccumulator::~ErrorAccumulator()
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{
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// empty
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}
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template <unsigned int DIM, unsigned int POPSIZE>
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inline void DE::Engine<DIM,POPSIZE>::ErrorAccumulator::Clear()
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{
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num_tests = 0;
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sum_error_squared = 0.0;
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error_rmse = 0.0; // initial error == zero
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}
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template <unsigned int DIM, unsigned int POPSIZE>
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inline void DE::Engine<DIM,POPSIZE>::ErrorAccumulator::AddTestCase(double expected, double actual)
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{
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double e = expected - actual; // compute error
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sum_error_squared += e * e; // add to sum of error^2
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num_tests += 1; // increment total test count
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error_rmse = -1.0; // mark as dirty
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}
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template <unsigned int DIM, unsigned int POPSIZE>
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inline double DE::Engine<DIM,POPSIZE>::ErrorAccumulator::GetRMSE()
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{
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if ( error_rmse < 0.0 ) // recalculate if set to "dirty"
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CalculateError();
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return error_rmse;
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}
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template <unsigned int DIM, unsigned int POPSIZE>
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inline void DE::Engine<DIM,POPSIZE>::ErrorAccumulator::CalculateError()
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{
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// convert squared error to root mean squared error
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error_rmse = ::sqrt(sum_error_squared / (double)num_tests);
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}
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#endif // __de_inl__
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