Package de.torstennahm.integrate.visualizerdata

Examples of de.torstennahm.integrate.visualizerdata.StartIntegration

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    Series<double[]> series = generator.makeSeries(function.inputDimension());
   
    QMCResult result = new QMCResult();
   
    Visualizers.submitToList(visualizers, new Integrand(function));
    Visualizers.submitToList(visualizers, new StartIntegration());
   
    double sum = 0.0;
    int count = 0;
    while (! condition.stop(result)) {
      sum += function.sEvaluate(series.next());
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    int dimension = integrand.inputDimension();
   
    ProductResult result = new ProductResult();
   
    Visualizers.submitToList(visualizers, new Integrand(integrand));
    Visualizers.submitToList(visualizers, new StartIntegration());
   
    while (! condition.stop(result)) {
      int[] nodes = getNodesForEvals(dimension, result.points * 2 + 1);
      result.value = integrator.integrateWithNodes(integrand, nodes);
      result.points += integrator.neededEvaluations(nodes);
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        return new HashSet<IntegrationInfo>();
      }
    };
   
    Visualizers.submitToList(visualizers, new Integrand(function));
    Visualizers.submitToList(visualizers, new StartIntegration());
   
    int count = 0;
    while (! condition.stop(result)) {
      for (int j = 0; j < dimension; j++) {
        x[j] = random.nextDouble();
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    IntegrationResult integrate() throws IntegrationFailedException {
      result = new SparseResult();
      Index zeroIndex = new FastIndex();
     
      Visualizers.submitToList(visualizers, new Integrand(evaluator));
      Visualizers.submitToList(visualizers, new StartIntegration());
     
      if (dimension == 0) {
        currentDimension = 1;
      } else {
        currentDimension = dimension;
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    Queue<IndexData> queue = new PriorityQueue<IndexData>();
    Map<Index, IndexData> indexMap = new HashMap<Index, IndexData>();
   
    Visualizers.submitToList(visualizers, new Integrand(evaluator));
    Visualizers.submitToList(visualizers, new StartIntegration());
   
    Index zeroIndex = new FastIndex();
   
    if (! condition.stop(result)) {
      IndexData indexData = evaluateIndex(zeroIndex, evaluator, result, visualizers);
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    SparseResult result = new SparseResult();
   
    FlatIndexGenerator indexGenerator = new FlatIndexGenerator(evaluator.dimension());
   
    Visualizers.submitToList(visualizers, new Integrand(evaluator));
    Visualizers.submitToList(visualizers, new StartIntegration());
   
    lastValue = Double.NaN;
    int lastLevel = 0;
    while (! condition.stop(result)) {
      Index index = indexGenerator.next();
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    IntegrationResult integrate() throws IntegrationFailedException {
      result = new SparseResult();
      estimator = new FastConvergenceEstimator();

      Visualizers.submitToList(visualizers, new Integrand(evaluator));
      Visualizers.submitToList(visualizers, new StartIntegration());
     
      activateIndex(zeroIndex);
     
      while (! condition.stop(result)) {
        Index index = hybridManager.nextIndex();
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Related Classes of de.torstennahm.integrate.visualizerdata.StartIntegration

  • de.torstennahm.integrate.MCIntegrator
  • de.torstennahm.integrate.ProductIntegrator
  • de.torstennahm.integrate.QMCIntegrator
  • de.torstennahm.integrate.sparse.EstimateIntegrator$InternalIntegrator
  • de.torstennahm.integrate.sparse.EvaluateIntegrator$InternalIntegrator
  • de.torstennahm.integrate.sparse.SimplexIntegrator
  • de.torstennahm.integrate.sparse.WeightedIntegrator
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