Java InvalidConfigurationException类代码示例

import org.jgap.InvalidConfigurationException; //导入依赖的package包/类
/**
     * Returns new Measures and other CommandGenes to also learn Preprocessing.
     *
     * @param config LinkSpecGeneticLearnerConfig
     * @return new Measures and other CommandGenes to also learn Preprocessing
     * @throws InvalidConfigurationException when an invalid value has been passed to a Configuration object
     */
    private List<CommandGene> getPreprocessingMeasures(LinkSpecGeneticLearnerConfig config) throws InvalidConfigurationException {
        List<CommandGene> nodes = new LinkedList<CommandGene>();
        nodes.add(new AtomicPreprocessingCommand("nolang", config));
        nodes.add(new AtomicPreprocessingCommand("cleaniri", config));
        nodes.add(new AtomicPreprocessingCommand("uppercase", config));
        nodes.add(new AtomicPreprocessingCommand("lowercase", config));
        nodes.add(new AtomicPreprocessingCommand("removebraces", config));
        nodes.add(new AtomicPreprocessingCommand("regularAlphabet", config));

        nodes.add(new ChainedPreprocessingCommand("nolang", config));
//		nodes.add(new ChainedPreprocessingCommand("cleaniri", config));
        nodes.add(new ChainedPreprocessingCommand("uppercase", config));
        nodes.add(new ChainedPreprocessingCommand("lowercase", config));
//		nodes.add(new ChainedPreprocessingCommand("removebraces", config));
//		nodes.add(new ChainedPreprocessingCommand("regularAlphabet", config));

        nodes.add(new StringPreprocessMeasure("trigrams", config, String.class, true));
        nodes.add(new StringPreprocessMeasure("jaccard", config, String.class, true));
        nodes.add(new StringPreprocessMeasure("cosine", config, String.class, true));
        nodes.add(new StringPreprocessMeasure("levenshtein", config, String.class, true));
        nodes.add(new StringPreprocessMeasure("overlap", config, String.class, true));
        return nodes;
    }
 

import org.jgap.InvalidConfigurationException; //导入依赖的package包/类
/**
 * Applies all GeneticOperators registered with the Configuration. The
 * chromosomes created by the operators are collected in a new Population
 * instance, which is returned.
 * 
 * @param a_config
 *            the configuration to use
 * @param a_pop
 *            the population to use as input
 * @return a new Population instance containing the new Chromosomes
 * 
 * @author Klaus Meffert
 * @author Tamas Mahr
 * @since 3.2
 */
@SuppressWarnings("rawtypes")
protected Population useGeneticOperators(Configuration a_config, Population a_pop) {
	try {
		Population newGeneration = new Population(a_config, a_pop.size());

		List geneticOperators = a_config.getGeneticOperators();
		Iterator operatorIterator = geneticOperators.iterator();
		while (operatorIterator.hasNext()) {
			GeneticOperator operator = (GeneticOperator) operatorIterator.next();
			/**@todo utilize jobs: integrate job into GeneticOperator*/
			operator.operate(a_pop, newGeneration.getChromosomes());
		}

		return newGeneration;
	} catch (InvalidConfigurationException e){
		// should never happen
		throw new IllegalStateException(e);
	}
}
 

import org.jgap.InvalidConfigurationException; //导入依赖的package包/类
@Override
  protected MLResults learn(AMapping trainingData) {

try {
	setUp(trainingData);
} catch (InvalidConfigurationException e) {
	e.printStackTrace();
	logger.error(e.getMessage());
	return null;
}
  	
  	turn++;
      fitness.addToReference(extractPositiveMatches(trainingData));
      fitness.fillCachesIncrementally(trainingData);

      Integer nGen = (Integer) getParameter(GENERATIONS);
      
      for (int gen = 1; gen <= nGen; gen++) {
          gp.evolve();
          bestSolutions.add(determineFittest(gp, gen));
      }

      MLResults result = createSupervisedResult();
      return result;
      
  }
 

import org.jgap.InvalidConfigurationException; //导入依赖的package包/类
/**
 * Constructor for atomic similarity measures. @FIXME antiquated and not actually used.
 *
 * @param opName
 *         Name of the LIMES similarity measure operation (e.g. "trigram").
 * @param a_conf
 *         JGAP GPConfiguration.
 * @param a_returnType
 *         The return type of this command.
 * @param a_mutateable
 *         true: this Commandgene is mutateable, viz. the LIMES similarity measure might be changed
 *         to another one out of the allowed operations.
 * @throws InvalidConfigurationException when an invalid value has been passed to a Configuration object
 */
public StringPreprocessMeasure(String opName, final GPConfiguration a_conf,
                               final Class<?> a_returnType, boolean a_mutateable)
        throws InvalidConfigurationException {
    super(a_conf, 4, a_returnType, 1,
            new int[]{
                    ResourceTerminalType.STRINGPROPPAIR.intValue(),
                    ResourceTerminalType.THRESHOLD.intValue(),
                    ResourceTerminalType.PREPROCESS.intValue(),
                    ResourceTerminalType.PREPROCESS.intValue(),
            }
    );
    fillOperationSet();
    setOperationName(opName);
    m_mutateable = a_mutateable;
    setNoValidation(false);
}
 

import org.jgap.InvalidConfigurationException; //导入依赖的package包/类
/**
 * Constructor.
 *
 * @param KBIsource
 *         Specifies the source knowledge base.
 * @param KBItarget
 *         Specifies the target knowledge base.
 * @param propMapping
 *         A Mapping of Properties of both source and target.
 * @throws InvalidConfigurationException when an invalid value has been passed to a Configuration object
 */
public LinkSpecGeneticLearnerConfig(KBInfo KBIsource, KBInfo KBItarget, PropertyMapping propMapping) throws InvalidConfigurationException {
    super();
    this.source = KBIsource;
    this.target = KBItarget;
    this.propMap = propMapping;
    setGPFitnessEvaluator(new DeltaGPFitnessEvaluator()); // the lower the better
    setCrossoverMethod(new BranchTypingCross(this)); // standard
    setSelectionMethod(new TournamentSelector(2)); // new TournamentSelector(2) vs. FitnessProportionate
    setProgramCreationMaxTries(100);
    setMinInitDepth(1);
    setMaxInitDepth(15);
    setPreservFittestIndividual(true);
    setNewChromsPercent(0.25f); // 0.4
    setMaxCrossoverDepth(5);
    setVerifyPrograms(false);
    // seems that if we use program caches it only verifies if the first chromosome has changed.
    setUseProgramCache(false);
    setAlwaysCaculateFitness(true);
    //defaults
    this.setMutationProb(0.4f);
    this.setCrossoverProb(0.4f);
    //   this.setReproductionProb(0.7f);
    this.setPopulationSize(30);
}
 

import org.jgap.InvalidConfigurationException; //导入依赖的package包/类
/**
     * Constructor for atomic similarity measures. @FIXME antiquated and not actually used.
     *
     * @param opName
     *         Name of the LIMES similarity measure operation (e.g. "trigram").
     * @param a_conf
     *         JGAP GPConfiguration.
     * @param a_returnType
     *         The return type of this command.
     * @param a_mutateable
     *         true: this Commandgene is mutateable, viz. the LIMES similarity measure might be changed
     *         to another one out of the allowed operations.
     * @throws InvalidConfigurationException when an invalid value has been passed to a Configuration object
     */
    public StringPreprocessingMeasure(String opName, final GPConfiguration a_conf,
                                      final Class<?> a_returnType, boolean a_mutateable)
            throws InvalidConfigurationException {
        super(a_conf, 2, a_returnType, 1,
                new int[]{
                        ResourceTerminalType.STRINGPROPPAIR.intValue(),
//				ResourceTerminalType.SOURCE.intValue(),
//				ResourceTerminalType.TARGET.intValue(),
                        ResourceTerminalType.THRESHOLD.intValue(),}
        );
        fillOperationSet();
        setOperationName(opName);
        m_mutateable = a_mutateable;
        setNoValidation(false);
    }
 

import org.jgap.InvalidConfigurationException; //导入依赖的package包/类
/**
     * Default Constructor. A Boolean Metric is a boolean expression combining two
     * similarity measures as of now.
     *
     * @param a_conf
     *         A JGAP GPconfiguration instance.
     * @param a_returnType
     *         Define the return type of this node.
     * @throws InvalidConfigurationException when an invalid value has been passed to a Configuration object
     * TODO For a future version also allow other boolean measures to be children of this node.
     */
    public BooleanCommand(final GPConfiguration a_conf, Class<?> a_returnType, String command)
            throws InvalidConfigurationException {
        super(a_conf, 2, a_returnType, 4,
                new int[]{1, 1}
        );
        metric = command;
        // add default operators
        supportedMetrics = new ArrayList<String>();
        supportedMetrics.add("AND");
        supportedMetrics.add("OR");
//		supportedMetrics.add("XOR");
//		supportedMetrics.add("MINUS");
//		supportedMetrics.add("MIN");
//		supportedMetrics.add("MAX");
    }
 

import org.jgap.InvalidConfigurationException; //导入依赖的package包/类
public IChromosome apply (IChromosome firstMate, IChromosome secondMate, RandomGenerator generator, Configuration config) throws InvalidConfigurationException
{
	Gene[] rgGenes = new Gene[m_nElementPerOperand];
	for (int i = 0; i < m_nElementPerOperand; i++)
		rgGenes[i] = new IntegerGene (config, 0, 2 * m_nElementPerOperand - 1);
	
	int[] rgOpConfig = new int[m_mapSelectors.size ()];

	int nIdx = 0;
	for (int nID : m_listIDs)
	{
		List<Selector> list = m_mapSelectors.get (nID);
		rgOpConfig[nIdx] = generator.nextInt (list.get (0).getArgsCount ());
		for (Selector s : list)
			rgGenes[s.getIndex ()].setAllele (s.getResult (firstMate, secondMate, rgOpConfig[nIdx], m_nElementPerOperand));
		nIdx++;
	}
	
	List<Operand> listParent = new ArrayList<> (2);
	listParent.add ((Operand) firstMate.getApplicationData ());
	if (m_nOperandsCount >= 2)
		listParent.add ((Operand) secondMate.getApplicationData ());

	IChromosome c = new Chromosome (config, rgGenes);
	c.setApplicationData (new Operand (null, null, listParent, this, rgOpConfig));
	return c;
}
 

import org.jgap.InvalidConfigurationException; //导入依赖的package包/类
protected Gene newGeneInternal() {
	try {
		final IdentifiableDoubleGene result = new IdentifiableDoubleGene(id,getConfiguration(),getLowerBound(),getUpperBound());
		return result;
	} catch (final InvalidConfigurationException iex) {
		throw new IllegalStateException(iex.getMessage());
	}
}
 

import org.jgap.InvalidConfigurationException; //导入依赖的package包/类
public NaturalSelector getSelector(final Configuration config) throws InvalidConfigurationException {
	final BestChromosomesSelector selector = new BestChromosomesSelector(config,model.getValue() / 100.0);
	selector.setDoubletteChromosomesAllowed(false);
	//selector.setDoubletteChromosomesAllowed(doubletteCheckBox.isSelected());
	
	return selector;
}
 

import org.jgap.InvalidConfigurationException; //导入依赖的package包/类
@Override
protected Gene newGeneInternal() {
	try {
		final IdentifiableListGene result = new IdentifiableListGene(id,getConfiguration());
		result.value = value;
		result.validValues = new ArrayList<Object>(validValues);
		return result;
	} catch (final InvalidConfigurationException iex) {
		throw new IllegalStateException(iex.getMessage());
	}
}
 

import org.jgap.InvalidConfigurationException; //导入依赖的package包/类
public IdentifiableLongGene(final String id, final Configuration a_config, final long lowerBound, final long upperBound) throws InvalidConfigurationException {
	super(a_config);
	Preconditions.checkNotNull(id);
	this.id = id;
	this.lowerBound = lowerBound;
	this.upperBound = upperBound;
}
 

import org.jgap.InvalidConfigurationException; //导入依赖的package包/类
public NaturalSelector getSelector(final Configuration config) throws InvalidConfigurationException {
		final int size = (Integer) tournamentSizeModel.getValue();
		final double probability = selectionProbabilityModel.getValue() / 100.0;
		final TournamentSelector selector = new TournamentSelector(config,size,probability);
//		selector.setDoubletteChromosomesAllowed(doubletteCheckBox.isSelected());
		
		return selector;
	}
 

import org.jgap.InvalidConfigurationException; //导入依赖的package包/类
/**
     * Constructs normal String Measures without preprocessing children.
     *
     * @param config LinkSpecGeneticLearnerConfig
     * @return normal String Measures without preprocessing children
     * @throws InvalidConfigurationException when an invalid value has been passed to a Configuration object
     */
    private List<CommandGene> getStringMeasures(LinkSpecGeneticLearnerConfig config) throws InvalidConfigurationException {
        List<CommandGene> nodes = new LinkedList<CommandGene>();
        nodes.add(new StringMeasure(MeasureFactory.COSINE, config, String.class, 1, true));
        nodes.add(new StringMeasure(MeasureFactory.JACCARD, config, String.class, 1, true));
        nodes.add(new StringMeasure(MeasureFactory.TRIGRAM, config, String.class, 1, true));
        nodes.add(new StringMeasure(MeasureFactory.LEVENSHTEIN, config, String.class, 1, true));
        nodes.add(new StringMeasure(MeasureFactory.OVERLAP, config, String.class, 1, true));
        nodes.add(new StringMeasure(MeasureFactory.QGRAMS, config, String.class, 1, true));
//        nodes.add(new StringMeasure(MeasureFactory.EXACTMATCH, config, String.class, 1, true));
        return nodes;
    }
 

import org.jgap.InvalidConfigurationException; //导入依赖的package包/类
/**
 * Configures EAGLE.
 *
 * @param trainingData training data
 * @throws InvalidConfigurationException
 */
private void setUp(AMapping trainingData) throws InvalidConfigurationException {
	PropertyMapping pm = (PropertyMapping) getParameter(PROPERTY_MAPPING);
	if(!pm.wasSet()) {
		pm.setDefault(configuration.getSourceInfo(), configuration.getTargetInfo());
	}
    LinkSpecGeneticLearnerConfig jgapConfig = new LinkSpecGeneticLearnerConfig(configuration.getSourceInfo(), configuration.getTargetInfo(), pm);

    jgapConfig.sC = sourceCache;
    jgapConfig.tC = targetCache;
    
    jgapConfig.setPopulationSize((Integer) getParameter(POPULATION));
    jgapConfig.setCrossoverProb((Float) getParameter(CROSSOVER_RATE));
    jgapConfig.setMutationProb((Float) getParameter(MUTATION_RATE));
    jgapConfig.setPreservFittestIndividual((Boolean) getParameter(PRESERVE_FITTEST));
    jgapConfig.setReproductionProb((Float) getParameter(REPRODUCTION_RATE));
    jgapConfig.setPropertyMapping(pm);

    if(trainingData != null) { // supervised
    	
    	FMeasure fm = (FMeasure) getParameter(MEASURE);
    	fitness = ExpressionFitnessFunction.getInstance(jgapConfig, fm, trainingData);
    	org.jgap.Configuration.reset();
    	jgapConfig.setFitnessFunction(fitness);
    	
    } else { // unsupervised
    	
    	PseudoFMeasure pfm = (PseudoFMeasure) getParameter(PSEUDO_FMEASURE);
    	fitness = PseudoFMeasureFitnessFunction.getInstance(jgapConfig, pfm, sourceCache, targetCache);
    	org.jgap.Configuration.reset();
    	jgapConfig.setFitnessFunction(fitness);
    	
    }
    

    GPProblem gpP;

    gpP = new ExpressionProblem(jgapConfig);
    gp = gpP.create();
}