System.m

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namespace models{
namespace motoneuron{


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class System
  :public models.BaseFirstOrderSystem {
    public: /* ( Transient ) */

        d = "[]";
    public: /* ( Constant ) */

        static const dm = 6;
        static const .double C_m_slow = 0.58;
        static const C_m_fast = 1;

        
    public:

        noiseGen;
        upperlimit_poly;
    public:

        System(models.BaseFullModel model) {
            this = this@models.BaseFirstOrderSystem(model);

            this.addParam(" fibre_type ", 0, " Range ", [0 1]);
            this.addParam(" mean_current_factor ", 3, " Range ", [0 9]);

            this.NumStateDofs= 6;

            /*  Setup noise input */
            ng = models.motoneuron.NoiseGenerator;
            this.noiseGen= ng;
            this.Inputs[1] = @ng.getInput;

            /*  Load mean current limiting polynomial */
            s = load(models.motoneuron.Model.FILE_UPPERLIMITPOLY);
            this.upperlimit_poly= s.upperlimit_poly;

            /* % Set system components
             * Core nonlinearity */
            this.f= models.motoneuron.Dynamics(this);

            /*  Linear input B for motoneuron
             * input conversion matrix, depends on fibre type. Has only one
             * entry in second row. */
            B = dscomponents.AffLinInputConv;
            /*  Base noise input mapping */
            B.addMatrix(" 1./(pi*(exp(log(100)*mu(1,:))*3.55e-05 + 77.5e-4).^2) ",...
                sparse(2,1,1,6,2));
            /*  Independent noise input mapping with µ_2 as mean current factor */
            B.addMatrix(" mu(2,:)./(pi*(exp(log(100)*mu(1,:))*3.55e-05 + 77.5e-4).^2) ",...
                sparse(2,2,1,6,2));
            this.B= B;

            /*  Constant initial values */
            this.x0= dscomponents.ConstInitialValue(zeros(6,1));

            this.updateDimensions;
        }
        function  prepareSimulation(colvec<double> mu,integer inputidx) {

            /*  Limit mean current depending on fibre type */
            if this.Model.FibreTypeDepMaxMeanCurrent
                mu(2) = min(polyval(this.upperlimit_poly,mu(1)),mu(2));
            end

            prepareSimulation@models.BaseFirstOrderSystem(this, mu, inputidx);
        }
        function  setConfig(colvec<double> mu,integer inputidx) {
            setConfig@models.BaseFirstOrderSystem(this, mu, inputidx);
            this.noiseGen.setFibreType(mu(1));
            this.MaxTimestep= this.Model.dt*1000;            
        }


        function pm = plot(double t,matrix<double> y,pm) {
            if nargin < 4
                n = 2;
                if ~isempty(this.mu)
                    n = 3;
                end
                pm = PlotManager(false,1,n);
                pm.LeaveOpen= true;
            end

            /*  Input */
            h = pm.nextPlot(" input "," Input currents (base + indep) "," time "," value ");
            plot(h,t,this.noiseGen.getInput(t));

            /*  Effective input */
            if ~isempty(this.mu)
                h = pm.nextPlot(" eff_input "," Effective input current "," time "," value ");
                B = this.B.compose([],this.mu);
                plot(h,t,B(2,:)*this.noiseGen.getInput(t));
            end

            /*  Firing rate */
            h = pm.nextPlot(" moto "," Motoneuron V_s "," time "," value ");
            plot(h,t,y(2,:));

            if nargin < 4
                pm.done;
            end
        }


};
}
}