Class ExperimentCustom

public abstract class ExperimentCustom
extends Object
implements Serializable

Base class for all custom experiments
The experiment scenario should be defined in the overridden run() method

Custom experiment may be executed from another experiment - in this case the latter should be passed as an argument to the constructor of the custom experiment. Experiment is executed by calling run() method.
A sample action code of some Main agent which runs custom experiment:

 // Create custom experiment, pass currently running experiment
 // as an argument to the constructor:
 MyCustomExperiment e = new MyCustomExperiment(getExperiment());
 // setup some custom fields defined in the
 // additional class code of MyCustomExperiment:
 e.day = getDayOfWeek();
 // run experiment
 e.run();
 // collect results from custom fields defined in the
 // additional class code of MyCustomExperiment:
 traceln( "result: " + e.myResult );

(In the example above, custom experiment has Code (which is actually inside run() method) which gets field day (defined in the additional class code), uses it in the experiment and then sets some result value to the field myResult)

Usage notes
Use createEngine() to create new Engine instance Use Engine.runFast() method to run experiment in the fastest possible mode
Don't forget to setup stop time or stop date to the engine before
Use ExperimentOptimization.createOptimization(Engine) to create new OptQuest Optimization instance

The simplest example of run() code:

 // Create Engine, initialize random number generator:
 Engine engine = createEngine();
 // Set stop time
 engine.setStopTime( 100 );
 // Create new top-level agent:
 Main root = new Main(engine, null, null);
 // Setup parameters of top-level agent here
 root.myParameter = 10;
 // Prepare Engine for simulation:
 engine.start( root );
 // Start simulation in fast mode:
 engine.runFast();
 // Obtain results of simulation here
 traceln( root.myResult );
 // Destroy the model:
 engine.stop();
 

This object is only available in the AnyLogic Professional

See also an example of optimization performed within custom experiment.