Examples of ca.nengo.math.Function

ca.nengo.math.Function

A mathematical function from an n-D space to a 1-D space. For simplicity we always map to a 1-D space, and model maps to n-D spaces with n Functions.

Instances of Function are immutable once they are created (ie their parameters do not change over time).
@author Bryan Tripp


        if (functionIndex >= functions.length) {
            throw new ConfigException("Function index out of bounds");


        }
        Function function = functionInput.getFunctions()[functionIndex];
        Plotter.plot(function, start, increment, end, title + " ("
                + function.getClass().getSimpleName() + ")");


    }

View Full Code Here

      InterruptedException, SimulationException {
    network.setName("Integrator");


    Util.debugMsg("Network building started");


    Function f = new ConstantFunction(1, 1f);
    FunctionInput input = new FunctionInput("input", new Function[] { f }, Units.UNK);


    // uiViewer.addNeoNode(uiInput);


    NEFEnsembleFactory ef = new NEFEnsembleFactoryImpl();

View Full Code Here

      InterruptedException, SimulationException {
    network.setName("Integrator");


    Util.debugMsg("Network building started");


    Function f = new ConstantFunction(1, 1f);
    FunctionInput input = new FunctionInput("input", new Function[] { f },
        Units.UNK);


    // uiViewer.addNeoNode(uiInput);

View Full Code Here

  
  
  public static Network CreateNetwork() throws StructuralException {
    NetworkImpl network = new NetworkImpl();
    
    Function f = new ConstantFunction(1, 1f);
    FunctionInput input = new FunctionInput("input", new Function[] { f }, Units.UNK);
    
    network .addNode(input);
    
    return network;

View Full Code Here

  // private static Window[] windows;
  public static Network createNetwork() throws StructuralException {


    Network network = new NetworkImpl();


    Function f = new ConstantFunction(1, 1f);
    // Function f = new SineFunction();
    FunctionInput input = new FunctionInput("input", new Function[] { f }, Units.UNK);
    network.addNode(input);


    NEFEnsembleFactory ef = new NEFEnsembleFactoryImpl();

View Full Code Here


    /**
     * @see ca.nengo.model.neuron.impl.SpikeGeneratorFactory#make()
     */
    public SpikeGenerator make() {
      Function sigmoid = new SigmoidFunction(myInflection.sample()[0], mySlope.sample()[0], 0, myMaxRate.sample()[0]);
      return new PoissonSpikeGenerator(sigmoid);
    }

View Full Code Here

   */
  public float getAdaptedRate(final float I) {
    if (I > 1) {
      RootFinder rf = new NewtonRootFinder(50, false);


      Function f = new AbstractFunction(1) {
        private static final long serialVersionUID = 1L;
        public float map(float[] from) {
          float r = from[0];
          return r - 1 / (myTauRef - myTauRC * (float) Math.log(1f - 1f/(I-G_N*myIncN*myTauN*r)));
        }

View Full Code Here


    return excitatory ? 1f / max : -1f / max; //this makes the bias function peak at 1 (or -1)
  }


  private NEFEnsemble createInterneurons(String name, int num, boolean excitatoryProjection) throws StructuralException {
    final Function f;
    if (excitatoryProjection) {
      f = new IdentityFunction(1, 0);
    } else {
      f = new AbstractFunction(1) {
        private static final long serialVersionUID = 1L;

View Full Code Here

0 1 2 3 4

TOP

Related Classes of ca.nengo.math.Function

ca.nengo.examples.IntegratorExample

ca.nengo.math.impl.CompositeApproximator

ca.nengo.math.impl.CompositeApproximatorTest

ca.nengo.math.impl.ConvolutionTest

ca.nengo.math.impl.DefaultFunctionInterpreterTest

ca.nengo.math.impl.FixedSignalFunctionTest

ca.nengo.math.impl.GradientDescentApproximatorTest

ca.nengo.math.impl.IndependentDimensionApproximator$Factory

ca.nengo.math.impl.IndependentDimensionApproximatorTest

ca.nengo.math.impl.LinearCurveFitterTest

All source code are property of their respective owners. Java is a trademark of Sun Microsystems, Inc and owned by ORACLE Inc. Contact coftware#gmail.com.