evothreemults.java~

Java遗传算法库

        writeGNUPlotScript( dirName, 1 );
    }        
    
    /*
    private static void add2MultPost1Plus1( int id, String genes)
    {

        // 1+1
         final int POP_SIZE = 20;
         final int TP_POP_SIZE = 2;
         final double BIT_MUTATION_PROB = 0.05;
         final int GENOTYPE_MUT = 1;
         final double XOVER_PROB = 0;
         final double MUTATION_PROB = 0.8;
         final int NUM_OF_ELITES = 1;
         final double CHOP_PROB = 0.1;
         final double STRETCH_PROB = 0.1;

         final double TP_XOVER_PROB = 0;
         final double TP_MUTATION_PROB = 1;
         final int TP_NUM_OF_ELITES = 1;

         final double[] RANK_PROBS = { 1d, 0d };
         final double[] TP_RANK_PROBS = { 1d, 0d };
        //
        // D -  Circuit Structure Properties
         final int BITS_PER_VARIABLE = 5;
         final int LUT_INPUTS = 2;

        // D - Simulator Properties
         final int SIMULATOR_GATE_DELAY = 1;
         final double T_SETUP = 0.45;
        // final int INPUT_SAMPLE_SEPARATION = 1;

        // E - Experiment Properties
         final int TEST_LENGTH = 50;

        // M - Log Properties
         int DUMP_POP_EVERY = 1;
        int GENERATIONS = 20000;

        // E - EXPERIMENT set up
         Experiment inExperiment = new MultiplierExperiment( 2, T_SETUP );
        Experiment aonExperiment = new AllOrNothingExperiment( inExperiment );
        
         Experiment tpexp = new TestPattern4EvolvingExperiment( inExperiment );        

        // D - DEPLOYMENT set up
        // SimulatorCircuit circuit = new SimulatorLUTCircuit( SIMULATOR_GATE_DELAY, BITS_PER_VARIABLE , LUT_INPUTS, experiment.getNumOfInputs(), experiment.getNumOfOutputs() );
         ElementDelayModel delayModel = new ConstantDelayModel( SIMULATOR_GATE_DELAY );
         CircuitMapping circuitMapping = new LUTAbsoluteMapping( inExperiment.getNumOfInputs(), inExperiment.getNumOfOutputs(), BITS_PER_VARIABLE, LUT_INPUTS, delayModel );
         SimulatorSimpleCircuit circuit = new SimulatorSimpleCircuit( circuitMapping );
         SimulatorDeployment inDeployment = new SimulatorDeployment( circuit );

        // E - For Parsimony Experiment
        BufferedIndividualDeployment deployment = new BufferedIndividualDeployment( inDeployment );
        Experiment experiment = new VarLenGenParsimonyExperiment( aonExperiment, deployment );
        
         int lutSize = 1 << LUT_INPUTS;
         int blockSize = lutSize + LUT_INPUTS * BITS_PER_VARIABLE;
         int genotypeLength = ( ( 1 << BITS_PER_VARIABLE ) - experiment.getNumOfInputs() ) * blockSize;
         int blockLength = BITS_PER_VARIABLE * LUT_INPUTS + 1 << LUT_INPUTS;
         int testPatLength = ( 1 << experiment.getNumOfInputs() ) * 2;
         int tpGenLength = testPatLength * experiment.getNumOfInputs();

        final Genotype SEED0 = new Genotype( genes );
         final Genotype[] SEEDS = { SEED0 };
         final Genotype[] TP_SEEDS = { };

         GeneticOperator m = new ExactGenotypeMutator( GENOTYPE_MUT );
         GeneticOperator chop = new Chopper( 1 );
         GeneticOperator stretch = new Stretcher( 1, 0 );

         GeneticOperator tpm = new ExactGenotypeMutator( GENOTYPE_MUT );
        GeneticOperator spxo = new TracingSinglePointXOver();
         GeneticOperator tpspxo = new SinglePointXOver();

         // 1+1
         GeneticOperator[] geneticOps = { m, chop, stretch };
        //GeneticOperator[] geneticOps = { m };
         GeneticOperator[] tpGeneticOps = { tpm };

         double[] opsProbs = { MUTATION_PROB, CHOP_PROB, STRETCH_PROB };
        //double[] opsProbs = { MUTATION_PROB };
         double[] tpOpsProbs = { TP_MUTATION_PROB };
         //
        // Selector selector = new FitnessProportionateSelector();
         Selector selector = new RankSelector( RANK_PROBS );
         //Selector selector = new RankSelector(  );
         Selector tpSelector = new RankSelector( TP_RANK_PROBS );

         Evolver evolver = new StandardEvolver( POP_SIZE, genotypeLength, geneticOps, opsProbs, selector, NUM_OF_ELITES, SEEDS );
         Evolver tpEvolver = new StandardEvolver( TP_POP_SIZE, tpGenLength, tpGeneticOps, tpOpsProbs, tpSelector, TP_NUM_OF_ELITES, TP_SEEDS );

         Evolver[] evolvers = { evolver, tpEvolver };
         Experiment[] experiments = { experiment, tpexp };

         InteractionModel interactionModel = new StandardInteractionModel( evolver, deployment, experiment );
         int[] evolutionFrequency = { 1 , 4 };
        // InteractionModel interactionModel = new CircuitTestPatternIM( evolvers, deployment, experiments, evolutionFrequency );

        Monica monica = new Monica( interactionModel, DUMP_POP_EVERY, java.lang.Integer.MAX_VALUE );
        String dirName = "2MultPost1Plus1-" + id;
        monica.setName( dirName );        
        taskQ.add( monica );
        taskQNames.add( dirName );
        writeGNUPlotScript( dirName, 1 );
    }    
  */  
    private static void add2MultPostParsimony1Plus1( int id, String genes)
    {

        // 1+1
         final int POP_SIZE = 11;
         final int TP_POP_SIZE = 2;
         final double BIT_MUTATION_PROB = 0.05;
         final int GENOTYPE_MUT = 1;
         final double XOVER_PROB = 0;
         final double MUTATION_PROB = 0.6;
         final int NUM_OF_ELITES = 1;
         final double CHOP_PROB = 0.1;
         final double STRETCH_PROB = 0.1;

         final double TP_XOVER_PROB = 0;
         final double TP_MUTATION_PROB = 1;
         final int TP_NUM_OF_ELITES = 1;

         final double[] RANK_PROBS = { 1d, 0d };
         final double[] TP_RANK_PROBS = { 1d, 0d };
        //
        // D -  Circuit Structure Properties
         final int BITS_PER_VARIABLE = 5;
         final int LUT_INPUTS = 2;

        // D - Simulator Properties
         final int SIMULATOR_GATE_DELAY = 1;
         final double T_SETUP = 0.45;
        // final int INPUT_SAMPLE_SEPARATION = 1;

        // E - Experiment Properties
         final int TEST_LENGTH = 50;

        // M - Log Properties
         int DUMP_POP_EVERY = 1;
        int GENERATIONS = 50000;

        // E - EXPERIMENT set up
         Experiment inExperiment = new MultiplierExperiment( 2, T_SETUP );
        Experiment aonExperiment = new AllOrNothingExperiment( inExperiment );
        
         Experiment tpexp = new TestPattern4EvolvingExperiment( inExperiment );        

        // D - DEPLOYMENT set up
        // SimulatorCircuit circuit = new SimulatorLUTCircuit( SIMULATOR_GATE_DELAY, BITS_PER_VARIABLE , LUT_INPUTS, experiment.getNumOfInputs(), experiment.getNumOfOutputs() );
         ElementDelayModel delayModel = new ConstantDelayModel( SIMULATOR_GATE_DELAY );
         CircuitMapping circuitMapping = new LUTAbsoluteMapping( inExperiment.getNumOfInputs(), inExperiment.getNumOfOutputs(), BITS_PER_VARIABLE, LUT_INPUTS, delayModel );
         SimulatorSimpleCircuit circuit = new SimulatorSimpleCircuit( circuitMapping );
         SimulatorDeployment deployment = new SimulatorDeployment( circuit );

        // E - For Parsimony Experiment
        final int TARGET_GATES = 6;
        Experiment experiment = new ElementParsimonyExperiment( aonExperiment, circuit, TARGET_GATES );
        
         int lutSize = 1 << LUT_INPUTS;
         int blockSize = lutSize + LUT_INPUTS * BITS_PER_VARIABLE;
         int genotypeLength = ( ( 1 << BITS_PER_VARIABLE ) - experiment.getNumOfInputs() ) * blockSize;
         int blockLength = BITS_PER_VARIABLE * LUT_INPUTS + 1 << LUT_INPUTS;
         int testPatLength = ( 1 << experiment.getNumOfInputs() ) * 2;
         int tpGenLength = testPatLength * experiment.getNumOfInputs();

        final Genotype SEED0 = new Genotype( genes, genotypeLength, 6 );
         final Genotype[] SEEDS = { SEED0 };
         final Genotype[] TP_SEEDS = { };

         GeneticOperator m = new ExactGenotypeMutator( GENOTYPE_MUT );
        GeneticOperator bmin0 = new BunchMutator( BITS_PER_VARIABLE, 1, blockSize, lutSize );
        GeneticOperator bmin1 = new BunchMutator( BITS_PER_VARIABLE, 1, blockSize, lutSize + BITS_PER_VARIABLE );
        GeneticOperator bmf = new BunchMutator( lutSize, 1, blockSize );
        GeneticOperator bc = new BlockCopy ( blockSize, blockSize );
         GeneticOperator chop = new Chopper( 1 );
         GeneticOperator stretch = new Stretcher( 1, 0 );

         GeneticOperator tpm = new ExactGenotypeMutator( GENOTYPE_MUT );
        GeneticOperator spxo = new TracingSinglePointXOver();
         GeneticOperator tpspxo = new SinglePointXOver();

         // 1+1
         GeneticOperator[] geneticOps = { bmin0, bmin1, bmf, bc };
         GeneticOperator[] tpGeneticOps = { tpm };

         double[] opsProbs = { 0.2,0.3,0.3,0.2 };
         double[] tpOpsProbs = { TP_MUTATION_PROB };
         //
        // Selector selector = new FitnessProportionateSelector();
         Selector selector = new RankSelector( RANK_PROBS );
         //Selector selector = new RankSelector(  );
         Selector tpSelector = new RankSelector( TP_RANK_PROBS );

         Evolver evolver = new StandardEvolver( POP_SIZE, genotypeLength, geneticOps, opsProbs, selector, NUM_OF_ELITES, SEEDS );
         Evolver tpEvolver = new StandardEvolver( TP_POP_SIZE, tpGenLength, tpGeneticOps, tpOpsProbs, tpSelector, TP_NUM_OF_ELITES, TP_SEEDS );

         Evolver[] evolvers = { evolver, tpEvolver };
         Experiment[] experiments = { experiment, tpexp };

         InteractionModel interactionModel = new StandardInteractionModel( evolver, deployment, experiment );
         int[] evolutionFrequency = { 1 , 4 };
        // InteractionModel interactionModel = new CircuitTestPatternIM( evolvers, deployment, experiments, evolutionFrequency );

        Monica monica = new Monica( interactionModel, DUMP_POP_EVERY, GENERATIONS );
        String dirName = "2MultPostParimony1Plus1-" + id;
        monica.setName( dirName );        
        taskQ.add( monica );
        taskQNames.add( dirName );
        writeGNUPlotScript( dirName, 1 );
    }    

    private static void add2MultParsimony1Plus1( int id )
    {

        // A - Genetic Algorithms Properties
        // 1+1
         final int POP_SIZE = 11;
         final int TP_POP_SIZE = 2;
         final double BIT_MUTATION_PROB = 0.05;