FERN - A Java Framework for Stochastic Simulation and Evaluation of Reaction Networks

Requirements

Network net = new FernMLNetwork(new File("mapk.xml"));
Simulator sim = new GibsonBruckSimulator(net);
IntervalObserver obs = 
	(IntervalObserver) sim.addObserver(
	new AmountIntervalObserver(sim,10,"E0*","E1*","E2*","E3*","E4*","E5*")
	);
 
GnuPlot gp = new GnuPlot();
gp.setDefaultStyle("with lines");
 
for (int i=1; i<=100; i++) {
	sim.start(1000);
	if (i<=10 || i%10==0) {
		gp.getCommands().clear();
		gp.addCommand("set title \"MAPK time course after "+i+" repeats");
 
		obs.toGnuplot(gp);
		gp.plot();
 
		gp.saveImage(new File(String.format("images/mapk%03d.png",i)));
		gp.clearData();
	}
}

This piece of java code creates images, below presented as an animated gif.

Code explanation

For a more comprehensive documentation of FERN's classes and their interplay, please refer to the documentation.

First, three object are created:

1. a FernMLNetwork is read from the file mapk.xml
2. a Simulator object is created containing the algorithm of Gibson and Bruck
3. a Observer, which is going to record the amounts of the species E0*-E5* every 10 time units; it is also registered at the simulator

Then, an object of the class GnuPlot is instanciated and configured, which is an interface to the popular tool gnuplot and a method for creating time courses of molecular species.

Within the for loop, 100 simulations up to the time 1000 are performed. After some runs (e.g. the first 10 and then every 10th) a time course is created: First, a meaningful title for the plot is set. Then, the simulation data is passed to the gnuplot object and is plotted therein. Note, how the toGnuplot method behaves if it is invoked after multiple simulation runs: always the average simulation data is passed to gnuplot (if you want only the recent one, you have to call toGnuplotRecent). Last, the plot is saved as an image and the data is cleared from gnuplot (without clearing, every call toGnuplot would add another 6 data axes and hence another six trend curves to the plot).