repairtimes.java~

Java遗传算法库

            {
                if( Math.random() < 0.5 )
                {
                    SEEDS[ pl ].set( bl );
                }
            }
        }
        // final Genotype SEEDTP0 = new Genotype( "GTJqc5eJgQMpdsQijj^llE^Elf[ov_E2`Vj2rIqt[OpfXsGc4n8U`ZS6UXN1p09D", tpGenLength, 6 );
        // final Genotype SEEDTP1 = new Genotype( "UrFEZ7_gVE9iEslS0dMJ51eg3jq4cDF3ume6b5iTQuS[8cVo9blDXNncTLs[VTG^", tpGenLength, 6 );
        // final Genotype[] TP_SEEDS = { SEEDTP0, SEEDTP1 };
         final Genotype[] TP_SEEDS = { };

        // BitMutator bm = new BitMutator( BIT_MUTATION_PROB );
        // GeneticOperator m = new ExactGenotypeMutator( GENOTYPE_MUT );
         GeneticOperator m = new SAGAMutator( 1, 10 );
         //GeneticOperator m = new AdaptiveMutator( 1, genotypeLength / 5 );
        // GeneticOperator tpm = new AdaptiveMutator( 1, tpGenLength / 5 );
         GeneticOperator tpm = new ExactGenotypeMutator( GENOTYPE_MUT );
        // GeneticOperator ws = new WireSwapper( BITS_PER_VARIABLE, STABILIZERS );
         GeneticOperator spxo = new SinglePointXOver();
         GeneticOperator tpspxo = new SinglePointXOver();

        // Standard
         GeneticOperator[] geneticOps = { m, spxo };
         GeneticOperator[] tpGeneticOps = { tpm, tpspxo };

         double[] opsProbs = { MUTATION_PROB, XOVER_PROB };
         double[] tpOpsProbs = { TP_MUTATION_PROB, TP_XOVER_PROB };
        
         /* 1+1
         GeneticOperator[] geneticOps = { m };
         GeneticOperator[] tpGeneticOps = { tpm };

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

        //SingleFaultModel faultModel = new SingleStaticFaultModel( fPos );
        
        //InteractionModel interactionModel = new StandardInteractionModel( evolver, deployment, experiment );
        PopulationLogReader.fullOrderGenotypes = true;
        int eSize = 7;
        int nrEvals = 7;
        boolean overdetecting = true;
        InteractionModel inIm = new BISTPIM( evolver, deployment, circuit, experiment, faultModel, eSize, overdetecting );
        int[] numProps = { 2 };
        InteractionModel noisyIM = new NoisyPIM( inIm, deployment, experiment, numProps );
        InteractionModel interactionModel = new CircuitParsimonyPIM( noisyIM, circuit );
         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 = "Add1BIST-" + fName;
        monica.setName( dirName );
        taskQ.add( monica );
        taskQNames.add( dirName );
        ControlLib.writeGNUPlotScript( dirName, logDir, logFileName, 3 );
    }

    private static void add2MultBISTPars( SingleFaultModel faultModel )
    {

        String dirName = "2MultBISTPars";
        
        // A - Genetic Algorithms Properties
         // Standard
         final int POP_SIZE = 32;
         final int TP_POP_SIZE = 7;
         final double BIT_MUTATION_PROB = 0.05;
         final int GENOTYPE_MUT = 1;
         final double XOVER_PROB = 0.4;
         final double ALIEN_PROB = 0;
         final double WIRE_SWAP_PROB = 0.7;
         final double MUTATION_PROB = 0.6;
         final int NUM_OF_ELITES = 2;

         final double TP_XOVER_PROB = 0.5;
         final double TP_MUTATION_PROB = 0.5;
         final int TP_NUM_OF_ELITES = 2;

        final double[] TP_RANK_PROBS = { 8d, 4d, 2d, 1d };
//
        /* 1+1
         final int POP_SIZE = 7;
         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 = 1;
         final int NUM_OF_ELITES = 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;

        /* For NANDC
         final int BITS_PER_VARIABLE = 5;
         final int STABILIZERS = 1;
         final int GATE_INPUTS = 2;
        */

        // D - Simulator Properties
         final int SIMULATOR_GATE_DELAY = 0;
         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 = 30;

        // E - EXPERIMENT set up
        BooleanFunction boolFunQ = new Add1bitQFun();
        BooleanFunction boolFunC = new Add1bitCFun();
        // BooleanFunction boolFun = new MUXFunction( 2 , 4 );
        // BooleanFunction boolFun = new VertorHorizFun();
        // BooleanFunction boolFun = new FLEXToneDetectFun();
         /*Experiment experimentQ = new ArbitraryFunctionExperiment( boolFunQ, T_SETUP );
        Experiment experimentC = new ArbitraryFunctionExperiment( boolFunC, T_SETUP );
        Experiment[] exps = { experimentQ, experimentC };
        Experiment experiment = new MultiOutputExperiment( exps );*/
        ConfigurableRandomInputExperiment experiment = new MultiplierExperiment( 2, T_SETUP );
        
         Experiment tpexp = new TestPattern4EvolvingExperiment( experiment );

        // 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 );
        //ElementDelayModel delayModel = new GaussianDelayModel( 0.5, 0.5 );
         CircuitMapping circuitMapping = new LUTAbsoluteMapping( experiment.getNumOfInputs(), experiment.getNumOfOutputs() + 1, BITS_PER_VARIABLE, LUT_INPUTS, delayModel );
         SimulatorFaultyCircuit circuit = new SimulatorFaultyCircuit( circuitMapping );
         SimulatorDeployment deployment = new SimulatorDeployment( circuit );

        // FLEXDeployment deployment = new FLEXDeployment( vFileName,  path2Prog, path2MaxPlus, wrkDir, BITS_PER_VARIABLE, STABILIZERS, GATE_INPUTS, experiment.getNumOfInputs(), experiment.getNumOfOutputs(), PORT_ADD );

        // A - Genetic Operators Set up
        /* For CNAND
         int genotypeLength = GATE_INPUTS * STABILIZERS * ( ( 1 << BITS_PER_VARIABLE ) - experiment.getNumOfInputs() ) * ( BITS_PER_VARIABLE + 1 );        
        */
         int genotypeLength = ( ( 1 << BITS_PER_VARIABLE ) - experiment.getNumOfInputs() ) * ( ( 1 << LUT_INPUTS ) + LUT_INPUTS * BITS_PER_VARIABLE );
         int testPatLength = ( 1 << experiment.getNumOfInputs() ) * 2;
         int tpGenLength = testPatLength * experiment.getNumOfInputs();

        final Genotype SEED0 = new FullOrderGenotype( genotypeLength ); // SF8 from log
        Genotype[] SEEDS = new Genotype[ POP_SIZE ];
        for( int pl = 0; pl < POP_SIZE; pl++ )
        {
            SEEDS[ pl ] = ( FullOrderGenotype ) SEED0.clone();
            for( int bl = 0; bl < SEEDS[ pl ].length(); bl++ )
            {
                if( Math.random() < 0.5 )
                {
                    SEEDS[ pl ].set( bl );
                }
            }
        }

        
        //final Genotype SEED0 = new Genotype( "01000001000110011000000001110110001010011000011111011100100100001110110001111101110100011110011111000111101111111010010101101000010011011100010110000101100110000000011101010000000011011000111111011001000011101111110111000001100100001100011100000100000001000001111101111110111010110111010110000010100100000001001110001101000110011101001100111110110010000101111011101010010110100011101001011111" );
        // final Genotype SEED1 = new Genotype( "6WS_iRZCj6Y8ELA2eO6ZJ8eMnPDTCdlHHtQFdj95jMhqg7bcFi9PGfu86JVoIpWkQjmvWSX6S[shXWjEjlRQiieI9QV95HvQD6iK\\EHNY\\RKa\\hB5^aF\\3OL9cl3r7r07rdbpQJkrOYaivRCqCK5IWPFM4USapH2mi3_RR2BX[5i^cCfnLZRR]N5t94Ms0iiLfmLuh72feoUuHWV6CHTh[0etY9[[Iv9KTBf`iZZojZteMsirncWvonRShJ0", genotypeLength, 6 );
        // final Genotype SEED2 = new Genotype( "2GS_i17CiQY8ELA2eO6ZJ8eMnPDTC_jrLtUVdjDG8EEQS\\beNi9PKfu87Jjc3jRiaIqH[ALYJsE11WIqSMRIgj04oBe09jKAhLiLaMVU_08qdSQaImCtgaB4cc[3r3raARcfpAJli0jWiJ0kq4Nk0WPF64USqpH2gi3bBKu2]SRe`cCfknjBqEMKTO7Iu5ru1_THNb72V3n6rWD824uaHW0etY9[[Iv9KTBf`gtYM_AhAq6hNldYCEAdb1i0", genotypeLength, 6 );
        // final Genotype[] SEEDS = { SEED0, SEED1, SEED2 };
        // final Genotype[] SEEDS = { SEED0, SEED1 };
         //final Genotype[] SEEDS = { SEED0 };
        // final Genotype[] SEEDS = { };
        // final Genotype SEEDTP0 = new Genotype( "GTJqc5eJgQMpdsQijj^llE^Elf[ov_E2`Vj2rIqt[OpfXsGc4n8U`ZS6UXN1p09D", tpGenLength, 6 );
        // final Genotype SEEDTP1 = new Genotype( "UrFEZ7_gVE9iEslS0dMJ51eg3jq4cDF3ume6b5iTQuS[8cVo9blDXNncTLs[VTG^", tpGenLength, 6 );
        // final Genotype[] TP_SEEDS = { SEEDTP0, SEEDTP1 };
         final Genotype[] TP_SEEDS = { };

        // BitMutator bm = new BitMutator( BIT_MUTATION_PROB );
         //GeneticOperator m = new ExactGenotypeMutator( GENOTYPE_MUT );
         GeneticOperator m = new SAGAMutator( 1, 10 );
        //GeneticOperator m = new LockingExactGenotypeMutator( GENOTYPE_MUT, 1000 );
         //GeneticOperator m = new AdaptiveMutator( 1, genotypeLength / 5 );
        // GeneticOperator tpm = new AdaptiveMutator( 1, tpGenLength / 5 );
         GeneticOperator tpm = new ExactGenotypeMutator( GENOTYPE_MUT );
        // GeneticOperator ws = new WireSwapper( BITS_PER_VARIABLE, STABILIZERS );
         GeneticOperator spxo = new SinglePointXOver();
         GeneticOperator tpspxo = new SinglePointXOver();

        // Standard
         GeneticOperator[] geneticOps = { m, spxo };
         GeneticOperator[] tpGeneticOps = { tpm, tpspxo };

         double[] opsProbs = { MUTATION_PROB, XOVER_PROB };
         double[] tpOpsProbs = { TP_MUTATION_PROB, TP_XOVER_PROB };
        ///
         /* 1+1
         GeneticOperator[] geneticOps = { m };
         GeneticOperator[] tpGeneticOps = { tpm };

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

        //SingleFaultModel faultModel = new SingleStaticFaultModel( fPos );
        
        //InteractionModel interactionModel = new StandardInteractionModel( evolver, deployment, experiment );
        PopulationLogReader.fullOrderGenotypes = true;
        int eSize = 9;
        boolean od = true;
        InteractionModel bistIm= new BISTPIM( evolver, deployment, circuit, experiment, faultModel, eSize, od );
        int[] np = { 2 };
        int nrevals = 1;
        InteractionModel noisyIm = new NoisyPIM( bistIm, deployment, experiment, np, nrevals );
        InteractionModel interactionModel = new CircuitParsimonyPIM( noisyIm, circuit );
         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 );
        
        
        monica.setName( dirName );
        taskQ.add( monica );
        taskQNames.add( dirName );
        ControlLib.writeGNUPlotScript( dirName, logDir, logFileName, 3, false );
    }    
    
}