List of addDecodedOrigin() Examples

Examples of addDecodedOrigin()

ca.nengo.model.nef.NEFEnsemble.addDecodedOrigin()
Adds an Origin that corresponds to a decoding of the activities of Nodes in this Ensemble. @param name Name of decoding @param functions Functions that define the decoding (one function for each dimension of output).All functions must have an input dimension equal to the dimension of this NEFEnsemble. @param nodeOrigin Name of the Node-level Origins from which this Ensemble-level Origin is derived(often Neuron.AXON) @return The added Origin @throws StructuralException if functions do not all have the same input dimension as thedimension of this ensemble

Examples of ca.nengo.model.nef.NEFEnsemble.addDecodedOrigin()

   * @throws StructuralException 
   */
  public void testGetOutput() throws StructuralException {
    NEFEnsembleFactory ef = new NEFEnsembleFactoryImpl();
    NEFEnsemble ensemble = ef.make("test", 70, new float[]{1, 1, 1});
    DecodedOrigin origin = (DecodedOrigin) ensemble.addDecodedOrigin("test", 
        new Function[]{new PostfixFunction("x1", 3), new PostfixFunction("x2", 3)}, Neuron.AXON);
    
    float[][] input = MU.uniform(500, 3, 1);
    float[][] directOutput = NEFUtil.getOutput(origin, input, SimulationMode.DIRECT);
    float[][] constantOutput = NEFUtil.getOutput(origin, input, SimulationMode.CONSTANT_RATE);

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Examples of ca.nengo.model.nef.NEFEnsemble.addDecodedOrigin()

    output.addDecodedTermination("recurrent", m, .005f, false);


    Function[] clipped = new Function[] { new Clip(5, 0, 0f, 1f),
        new Clip(5, 1, 0f, 1f), new Clip(5, 2, 0f, 1f),
        new Clip(5, 3, 0f, 1f), new Clip(5, 4, 0f, 1f) };
    output.addDecodedOrigin("recurrent", clipped, Neuron.AXON);


    net.addProjection(output.getOrigin("recurrent"), output
        .getTermination("recurrent"));


    /*

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Examples of ca.nengo.model.nef.NEFEnsemble.addDecodedOrigin()

    for (int i = 0; i < n; i++) {
      SpikingNeuron neuron = (SpikingNeuron) result.getNodes()[i];
      neuron.setBias(1-neuron.getScale());
    }


    DecodedOrigin o = (DecodedOrigin) result.addDecodedOrigin(NEFEnsemble.X, new Function[]{f}, Neuron.AXON);


    float[][] decoders = o.getDecoders();
    for (int i = 0; i < n; i++) {
      decoders[i] = new float[]{1f / n / 300};
    }

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