Package ca.nengo.math.impl

Examples of ca.nengo.math.impl.IndicatorPDF


    @Override
    protected NodeFactory createNodeFactory(ConfigResult configuredProperties) {
        Float tauRC = (Float) configuredProperties.getValue(pTauRC);
        Float tauRef = (Float) configuredProperties.getValue(pTauRef);
        Float tauN = (Float) configuredProperties.getValue(pTauN);
        IndicatorPDF maxRate = (IndicatorPDF) configuredProperties.getValue(pMaxRate);
        IndicatorPDF intercept = (IndicatorPDF) configuredProperties.getValue(pIntercept);
        IndicatorPDF incN = (IndicatorPDF) configuredProperties.getValue(pIncN);

        return new ALIFNeuronFactory(maxRate, intercept, incN, tauRef, tauRC, tauN);
    }
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    @Override
    protected NodeFactory createNodeFactory(ConfigResult configuredProperties) {
        Float tauRC = (Float) configuredProperties.getValue(pTauRC);
        Float tauRef = (Float) configuredProperties.getValue(pTauRef);
        IndicatorPDF maxRate = (IndicatorPDF) configuredProperties.getValue(pMaxRate);
        IndicatorPDF intercept = (IndicatorPDF) configuredProperties.getValue(pIntercept);

        return new LIFNeuronFactory(tauRC, tauRef, maxRate, intercept);
    }
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        super("Linear Neuron", LinearNeuronFactory.class);
    }

    @Override
    protected NodeFactory createNodeFactory(ConfigResult configuredProperties) {
        IndicatorPDF maxRate = (IndicatorPDF) configuredProperties.getValue(pMaxRate);
        IndicatorPDF intercept = (IndicatorPDF) configuredProperties.getValue(pIntercept);
        Boolean rectified = (Boolean) configuredProperties.getValue(pRectified);

        LinearNeuronFactory factory = new PoissonSpikeGenerator.LinearNeuronFactory(maxRate,
                intercept, rectified);
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        super("Sigmoid Neuron", SigmoidNeuronFactory.class);
    }

    @Override
    protected NodeFactory createNodeFactory(ConfigResult configuredProperties) {
        IndicatorPDF slope = (IndicatorPDF) configuredProperties.getValue(pSlope);
        IndicatorPDF inflection = (IndicatorPDF) configuredProperties.getValue(pInflection);
        IndicatorPDF maxRate = (IndicatorPDF) configuredProperties.getValue(pMaxRate);

        return new PoissonSpikeGenerator.SigmoidNeuronFactory(slope, inflection, maxRate);
    }
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        Class<?> synapticIntegratorClass = ((ClassWrapper) configuredProperties
                .getValue(pSynapticIntegrator)).getWrapped();
        Class<?> spikeGeneratorClass = ((ClassWrapper) configuredProperties
                .getValue(pSpikeGenerator)).getWrapped();

        IndicatorPDF scale = (IndicatorPDF) configuredProperties.getValue(pScale);
        IndicatorPDF bias = (IndicatorPDF) configuredProperties.getValue(pBias);

        /*
         * Construct Objects from Classes
         */
        SynapticIntegratorFactory synapticIntegratorFactory = (SynapticIntegratorFactory) constructFromClass(synapticIntegratorClass);
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            try {
                Float min = new Float(minStr);
                Float max = new Float(maxStr);

                return new IndicatorPDF(min, max);
            } catch (NumberFormatException e) {
              setStatusMsg("Invalid number format");
                return null;
            } catch (IllegalArgumentException e) {
              setStatusMsg("Low must be less than or equal to high");
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        }

        @Override
        public void setValue(Object value) {
            if (value instanceof IndicatorPDF) {
                IndicatorPDF pdf = (IndicatorPDF) value;
                lowValue.setText((new Float(pdf.getLow())).toString());
                highValue.setText((new Float(pdf.getHigh())).toString());
            }
        }
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    public static void main(String[] args) {
        SpikingNeuronFactory factory = new SpikingNeuronFactory(
                new LinearSynapticIntegrator.Factory(),
                new LIFSpikeGenerator.Factory(),
                new IndicatorPDF(1),
                new IndicatorPDF(0));

        ConfigUtil.configure((Frame) null, factory);
    }
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        Plotter.plot(rate, -1, .001f, 1, "rate");
        Plotter.plot(current, 0, dt, T, "current");
        Plotter.plot(pattern);

        //      SigmoidNeuronFactory snf = new SigmoidNeuronFactory(new IndicatorPDF(-10, 10), new IndicatorPDF(-1, 1), new IndicatorPDF(100, 200));
        LinearNeuronFactory lnf = new LinearNeuronFactory(new IndicatorPDF(200, 400), new IndicatorPDF(-1, 1), true);
        NEFEnsembleFactory ef = new NEFEnsembleFactoryImpl();
        ef.setNodeFactory(lnf);

        try {
            NEFEnsemble ensemble = ef.make("test", 20, 1);
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    /**
     * Set reasonable defaults
     */
    public Factory() {
      myTauRef = new IndicatorPDF(.002f);
      myTauRC = new IndicatorPDF(.02f);
    }
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