Package ca.nengo.model

Examples of ca.nengo.model.Network.addNode()


//    DecodedOrigin baseOrigin = (DecodedOrigin) pre.getOrigin(NEFEnsemble.X);
    network.addNode(pre);
   
    NEFEnsemble post = ef.make("post", 200, 1, "nefe_post", false);
//    DecodedTermination baseTermination = (DecodedTermination) post.addDecodedTermination("pre", MU.I(1), tauPSC, false);
    network.addNode(post);
   
    network.addProjection(input.getOrigin(FunctionInput.ORIGIN_NAME), pre.getTermination("input"));
    Projection projection = network.addProjection(pre.getOrigin(NEFEnsemble.X), post.getTermination("pre"));
   
    Probe pPost = network.getSimulator().addProbe("post", NEFEnsemble.X, true);
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                weights[i] = new float[]{1};
            }
            EnsembleImpl ensemble = new EnsembleImpl("ensemble", neurons);
            ensemble.addTermination("input", weights, .005f, false);
            ensemble.collectSpikes(true);
            network.addNode(ensemble);

            FunctionInput input = new FunctionInput("input", new Function[]{new PiecewiseConstantFunction(new float[]{0.2f}, new float[]{0, 0.5f})}, Units.UNK);
            network.addNode(input);

            network.addProjection(input.getOrigin(FunctionInput.ORIGIN_NAME), ensemble.getTermination("input"));
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            ensemble.addTermination("input", weights, .005f, false);
            ensemble.collectSpikes(true);
            network.addNode(ensemble);

            FunctionInput input = new FunctionInput("input", new Function[]{new PiecewiseConstantFunction(new float[]{0.2f}, new float[]{0, 0.5f})}, Units.UNK);
            network.addNode(input);

            network.addProjection(input.getOrigin(FunctionInput.ORIGIN_NAME), ensemble.getTermination("input"));

//          Probe vProbe = network.getSimulator().addProbe("ensemble", 0, "V", true);
//          Probe nProbe = network.getSimulator().addProbe("ensemble", 0, "N", true);
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    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);
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    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);
   
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    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);
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    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);
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