Examples of BiPolarNeuralData

org.encog.ml.data.specific.BiPolarNeuralData
A NeuralData implementation designed to work with bipolar data. Bipolar data contains two values. True is stored as 1, and false is stored as -1. @author jheaton

Examples of org.encog.ml.data.specific.BiPolarNeuralData

   *            The input pattern.
   * @return The new current state.
   */
  @Override
  public final MLData compute(final MLData input) {
    final BiPolarNeuralData result = new BiPolarNeuralData(input.size());
    EngineArray.arrayCopy(input.getData(), getCurrentState().getData());
    run();


    for (int i = 0; i < getCurrentState().size(); i++) {
      result.setData(i,
          BiPolarUtil.double2bipolar(getCurrentState().getData(i)));
    }
    EngineArray.arrayCopy(getCurrentState().getData(), result.getData());
    return result;
  }

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Examples of org.encog.ml.data.specific.BiPolarNeuralData

   * @param neuronCount The number of neurons.
   */
  public ThermalNetwork(final int neuronCount) {
    this.neuronCount = neuronCount;
    this.weights = new double[neuronCount * neuronCount];
    this.currentState = new BiPolarNeuralData(neuronCount);
  }

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Examples of org.encog.ml.data.specific.BiPolarNeuralData

          + ").");
    }


    this.neuronCount = neuronCount;
    this.weights = weights;
    this.currentState = new BiPolarNeuralData(neuronCount);
    this.currentState.setData(output);
  }

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Examples of org.encog.ml.data.specific.BiPolarNeuralData

  /**
   * Set the current state.
   * @param s The current state array.
   */
  public final void setCurrentState(final double[] s) {
    this.currentState = new BiPolarNeuralData(s.length);
    EngineArray.arrayCopy(s, this.currentState.getData());
  }

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Examples of org.encog.ml.data.specific.BiPolarNeuralData

   *            The input pattern.
   * @return The new current state.
   */
  @Override
  public final MLData compute(final MLData input) {
    final BiPolarNeuralData result = new BiPolarNeuralData(input.size());
    EngineArray.arrayCopy(input.getData(), getCurrentState().getData());
    run();
    EngineArray.arrayCopy(getCurrentState().getData(), result.getData());
    return result;
  }

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Examples of org.encog.ml.data.specific.BiPolarNeuralData

    this.weightsF1toF2 = new Matrix(this.f1Count, this.f2Count);
    this.weightsF2toF1 = new Matrix(this.f2Count, this.f1Count);


    this.inhibitF2 = new boolean[this.f2Count];


    this.outputF1 = new BiPolarNeuralData(this.f1Count);
    this.outputF2 = new BiPolarNeuralData(this.f2Count);


    this.noWinner = this.f2Count;
    reset();
  }

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Examples of org.encog.ml.data.specific.BiPolarNeuralData

   *            The input data.
   * @return The class that the data belongs to.
   */
  @Override
  public final int classify(final MLData input) {
    final BiPolarNeuralData input2 = new BiPolarNeuralData(this.f1Count);
    final BiPolarNeuralData output = new BiPolarNeuralData(this.f2Count);


    if (input.size() != input2.size()) {
      throw new NeuralNetworkError("Input array size does not match.");
    }

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Examples of org.encog.ml.data.specific.BiPolarNeuralData

    if (!(input instanceof BiPolarNeuralData)) {
      throw new NeuralNetworkError(
          "Input to ART1 logic network must be BiPolarNeuralData.");
    }


    final BiPolarNeuralData output = new BiPolarNeuralData(this.f1Count);
    compute((BiPolarNeuralData) input, output);
    return output;
  }

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Examples of org.encog.ml.data.specific.BiPolarNeuralData

   * Set the F1 count.  The F1 layer is the input layer.
   * @param i The count.
   */
  public final void setF1Count(final int i) {
    this.f1Count = i;
    this.outputF1 = new BiPolarNeuralData(this.f1Count);


  }

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Examples of org.encog.ml.data.specific.BiPolarNeuralData

   * @param i The count.
   */
  public final void setF2Count(final int i) {
    this.f2Count = i;
    this.inhibitF2 = new boolean[this.f2Count];
    this.outputF2 = new BiPolarNeuralData(this.f2Count);
  }

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