Package de.torstennahm.integrate

Examples of de.torstennahm.integrate.IntegrationFailedException

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      }
     
      while (! condition.stop(result)) {
        Index index = hybridManager.nextIndex();
        if (index == null) {
          throw new IntegrationFailedException("Could not expand index set");
        }
        EvalData evalData = indexMap.get(index);
       
        evalData.completed = true;
       
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  @Override
  public IntegrationResult integrate(Evaluator evaluator, StopCondition condition, List<Visualizer> visualizers) throws IntegrationFailedException {
    int dimension = evaluator.dimension();
   
    if (dimension == 0) {
      throw new IntegrationFailedException("Cannot integrate integrands with indefinite dimension");
    }
   
    SparseResult result = new SparseResult();
   
    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);
      indexMap.put(zeroIndex, indexData);
      indexData.priority = 0.0;
      queue.add(indexData);
    }
   
    while (! condition.stop(result)) {
      if(queue.isEmpty()) {
        throw new IntegrationFailedException("Index queue is empty");
      }
     
      IndexData indexData = queue.poll();
      Index index = indexData.index;
     
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      this.condition = condition;
      this.visualizers = visualizers;
      dimension = evaluator.dimension();
     
      if (dimension == 0) {
        throw new IntegrationFailedException("Cannot integrate integrands with indefinite dimension");
      }
     
      hybridManager = new HybridManager(simplexQuota);
      indexMap = new HashMap<Index, EstimateData>();
    }
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      activateIndex(zeroIndex);
     
      while (! condition.stop(result)) {
        Index index = hybridManager.nextIndex();
        if (index == null) {
          throw new IntegrationFailedException("Could not expand index set");
        }
       
        EstimateData indexData = indexMap.get(index);
       
        if (indexData.calls != 0) {
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    for (int i = 0; i < qf.length; i++) {
      int level = index.get(i);
     
      if (level > generator.maxLevel()) {
        throw new IntegrationFailedException("Generator does not support level " + level);
      }
      qf[i] = generator.getByLevel(level);
    }
   
    return new InternalIntegrator(function, qf).value;
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  public double integrateWithNodes(Function function, int[] nodes) throws IntegrationFailedException {
    QuadratureFormula[] qf = new QuadratureFormula[function.inputDimension()];
   
    for (int i = 0; i < qf.length; i++) {
      if (nodes[i] > generator.maxNodes()) {
        throw new IntegrationFailedException("Generator does not support " + nodes[i] + "nodes");
      }
      qf[i] = generator.getByNodes(nodes[i]);
    }
   
    return new InternalIntegrator(function, qf).value;
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Related Classes of de.torstennahm.integrate.IntegrationFailedException

  • de.torstennahm.integrate.sparse.EstimateIntegrator$InternalIntegrator
  • de.torstennahm.integrate.sparse.EvaluateIntegrator$InternalIntegrator
  • de.torstennahm.integrate.sparse.ProductWeightIntegrator
  • de.torstennahm.integrate.sparse.WeightedIntegrator
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