Examples of ca.nengo.model.Network

ca.nengo.model.Network

A neural circuit, consisting of Nodes such as Ensembles and ExternalInputs. A Network is the usual object of a simulation. If you are new to this code, what you probably want to do is create some Neurons, group them into Ensembles, connect the Ensembles in a Network, and run the Network in a Simulator.

Note: Multiple steps are needed to add a Projection between Ensembles. First, an Origin must be created on the presynaptic Ensemble, and a Termination with the same dimensionality must be created on the post-synaptic Ensemble. Then the Origin and Termination can be connected with the method addProjection(Origin, Termination). We don't do this in one step (ie automatically create the necessary Origin and Termination as needed) because there are various ways of doing so, and in fact some types of Origins and Terminations can only be created in the course of constructing the Ensemble. Creation of an Origin or Termination can also be a complex process. Rather than try to abstract these varied procedures into something that can be driven from the Network level, we just assume here that the necessary Origins and Terminations exist, and provide a method for connecting them.
@author Bryan Tripp

    ExpandableSpikingNeuron neuron = new ExpandableSpikingNeuron(integrator, generator, 1, 0, "neuron");    
    Termination t = neuron.addTermination("input", MU.I(1), .001f, false);
    
    FunctionInput input = new FunctionInput("input", new Function[]{new ConstantFunction(1, I)}, Units.UNK);
    
    Network network = new NetworkImpl();
    network.addNode(input);
    network.addNode(neuron);
    network.addProjection(input.getOrigin(FunctionInput.ORIGIN_NAME), t);
    
    Probe v = network.getSimulator().addProbe("neuron", IzhikevichSpikeGenerator.V, true);
    Probe u = network.getSimulator().addProbe("neuron", IzhikevichSpikeGenerator.U, true);
    
    network.run(0, 1);
    
    Plotter.plot(v.getData(), "voltage");
    Plotter.plot(u.getData(), "recovery");
  }

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//  private static Window window;


  // 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();


    NEFEnsemble integrator = ef.make("integrator", 500, 1, "integrator1", false);
    network.addNode(integrator);
    integrator.collectSpikes(true);


    // Plotter.plot(integrator);
    // Plotter.plot(integrator, NEFEnsemble.X);


    float tau = .05f;


    Termination interm = integrator.addDecodedTermination("input",
        new float[][] { new float[] { tau } }, tau, false);
    // Termination interm = integrator.addDecodedTermination("input", new
    // float[][]{new float[]{1f}}, tau);
    network.addProjection(input.getOrigin(FunctionInput.ORIGIN_NAME), interm);


    Termination fbterm = integrator.addDecodedTermination("feedback",
        new float[][] { new float[] { 1f } }, tau, false);
    network.addProjection(integrator.getOrigin(NEFEnsemble.X), fbterm);


    // System.out.println("Network creation: " + (System.currentTimeMillis()
    // - start));
    return network;
  }

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    if (myNodeMap.containsKey(name)) {
      Node node = myNodeMap.get(name);


      if(node instanceof Network)
      {
        Network net = (Network)node;
        Probe[] probes = net.getSimulator().getProbes();
        for (Probe probe : probes) {
                    try
          {
            net.getSimulator().removeProbe(probe);
          }
          catch(SimulationException se)
          {
            System.err.println(se);
            return;
          }
                }


        Node[] nodes = net.getNodes();
        for (Node node2 : nodes) {
                    net.removeNode(node2.getName());
                }
      }
      else if(node instanceof DecodableEnsembleImpl)
      {
        NEFEnsembleImpl pop = (NEFEnsembleImpl)node;

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                    childCollecting = true;
                }


            } else if (node instanceof Network) {
                Network subNet = (Network) node;


                DefaultMutableTreeNode netNode = createSortableNode(top, subNet);


                if(!addSpikePatterns(netNode, subNet)) {
                    top.remove(top.getIndex(netNode));

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Related Classes of ca.nengo.model.Network

ca.nengo.examples.IntegratorExample

ca.nengo.model.impl.EnsembleOrigin

ca.nengo.model.impl.EnsembleTermination

ca.nengo.model.impl.NetworkImpl

ca.nengo.model.impl.ProjectionImplTest

ca.nengo.model.nef.impl.NEFEnsembleImplTest

ca.nengo.model.neuron.impl.ALIFSpikeGeneratorTest

ca.nengo.model.neuron.impl.IzhikevichSpikeGeneratorTest

ca.nengo.model.neuron.impl.PoissonSpikeGeneratorTest

ca.nengo.plot.PlotterFunctional

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