test10.cpp

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#include "indii/fmri/hemodynamic/LogNeuralBalloonModel.hpp"
#include "indii/fmri/hemodynamic/LogBOLDCalculator.hpp"
#include "indii/ml/ode/AdaptiveRungeKutta.hpp"

#include <iostream>
#include <string.h>
#include <math.h>

using namespace std;
using namespace indii::fmri::hemodynamic;
using namespace indii::ml::ode;

/**
 * @file test10.cpp
 *
 * Basic test of LogNeuralBalloonModel.
 *
 * This test uses a default LogNeuralBalloonModel with a driving
 * neural activity function \f$u(t)\f$ consisting of a brief 1 s long
 * burst of activity followed by no activity. Results are output on
 * stdout, tab delimited, with columns representing:
 *
 * \li \f$t\f$; time
 * \li \f$f_{in}(t)\f$
 * \li \f$f_{out}(t)\f$
 * \li \f$u(t)\f$
 * \li \f$ln(q)\f$
 * \li \f$ln(v)\f$
 * \li \f$ln(f)\f$
 * \li \f$s\f$
 * \li \f$y\f$; BOLD response
 *
 * Results are as follows:
 *
 * \image html test10.png "Results, c.f. test3.cpp"
 * \image latex test10.eps "Results, c.f. test3.cpp"
 */


/**
 * Duration of simulation (s).
 */
static const double END = 30.0;

/**
 * \f$u(t)\f$; 1 for 1 s, then 0.
 */
double U(double t, const double y[], void* o) {
  double u;
  if (t < 1.0) {
    u = 1.0;
  } else {
    u = 0.0;
  }
  return u;
}

/**
 * Run tests.
 */
int main(int argc, const char* argv[]) {
  LogNeuralBalloonModel balloonModel;
  LogBOLDCalculator boldCalculator(&balloonModel);
  AdaptiveRungeKutta ode(&balloonModel, balloonModel.suggestInitialState());

  /* set up balloon model */
  balloonModel.setFunction(LogNeuralBalloonModel::U, U);

  double t = 0.0;
  while (t < END) {
    cout << t << "\t";
    cout << balloonModel.getFunction(LogNeuralBalloonModel::F_IN) << "\t";
    cout << balloonModel.getFunction(LogNeuralBalloonModel::F_OUT) << "\t";
    cout << balloonModel.getFunction(LogNeuralBalloonModel::U) << "\t";
    cout << ode.getVariable(LogNeuralBalloonModel::LN_Q) << "\t";
    cout << ode.getVariable(LogNeuralBalloonModel::LN_V) << "\t";
    cout << ode.getVariable(LogNeuralBalloonModel::LN_F) << "\t";
    cout << ode.getVariable(LogNeuralBalloonModel::S) << "\t";
    cout << boldCalculator.calculate(ode.getState()) * 100.0 << "\t";
    cout << endl;
    t = ode.step(END);
  }

  return 0;
}

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