/*-------------------------------------------------------------------------- Author: Thomas Nowotny Institute: Institute for Nonlinear Dynamics University of California San Diego La Jolla, CA 92093-0402 email to: tnowotny@ucsd.edu initial version: 2005-08-17 --------------------------------------------------------------------------*/ using namespace std; #include #include "gauss.h" #include "randomGen.h" #include "randomGen.cc" randomGen RG(1,2,3); randomGen R(1,2,3); #include "CN_ValAdaptneuron.h" #include "CN_absynapse.h" #include "CN_NeuronModel.h" #include "CN_rk65n.h" #include "CN_DCInput.h" #include "CN_ValAdaptneuron.cc" #include "CN_absynapse.cc" #include "CN_NeuronModel.cc" #include "CN_DCInput.cc" int main(int argc, char *argv[]) { list neurs; list syns; neuron *n; // synapse *s; synapse *ins; double *x, *xn, *tmp; int N; cerr << RG.n() << endl; double IDC= atof(argv[1]); vector pos(3, 0); n= new ValAdaptneuron(1,pos); neurs.push_back(n); // s= new absynapse(n, n2, 0.5, 0.0, -20.0, 0.1, 0.2, 5.0, 0.0); // syns.append(s); ins= new DCInput(n, IDC); syns.push_back(ins); NeuronModel model(&neurs, &syns, N, cerr); x= new double[N]; xn= new double[N]; //n->init(x, ECN_INIVARS); n->init(x, ValA_INIVARS); // s->init(x, ABSYN_INIVARS); rk65n machine(N, 0.1, 1e-8, 1e-12, 1e-6); double dt= 0.1; double dtx= 0.1; for (int i= 0; i < 100000; i++) { dtx= machine.integrate(x, xn, &model, dt); // cerr << dtx << endl; dt= dtx; tmp= x; x= xn; xn= tmp; cout << x[0] << " " << n->E(x) << endl; if (n->start_spiking) cerr << x[0] << endl; } return 0; }