jcgp.backend.modules.problem

Class TestCaseProblem<T>

java.lang.Object

jcgp.backend.modules.Module

jcgp.backend.modules.problem.Problem

jcgp.backend.modules.problem.TestCaseProblem<T>

Type Parameters:

T - the data type to be used by the TestCaseProblem.

Direct Known Subclasses:

DigitalCircuitProblem, SymbolicRegressionProblem

public abstract class TestCaseProblem<T>
extends Problem

Abstract model for a problem that uses test cases. A test case problem is any problem that compares the chromosome output to an expected output taken from a table of input-output mappings.

This class defines a basic data type for storing test cases, TestCase, and provides core functionality to add and manipulate test cases in the problem. A subclass of TestCaseProblem must simply override parseTestCase() to convert parsed problem data strings into the required data type (T).

Author:

Eduardo Pedroni

See Also:

Problem

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	TestCaseProblem.TestCase<U> Basic data type for encapsulating test cases, it simply contains arrays of inputs and outputs and associated getters.

Constructor Summary

Constructors

Constructor and Description
TestCaseProblem(Resources resources) Creates a new TestCaseProblem object.

Method Summary

Modifier and Type	Method and Description
void	addTestCase(java.lang.String[] inputs, java.lang.String[] outputs) Adds test cases to the problem instance as they get parsed from a problem data file.
void	clearTestCases() Remove all test cases.
javafx.collections.ObservableList<TestCaseProblem.TestCase<T>>	getTestCases()
int	hasImprovement(Population population) Used to assert whether a given population has a chromosome that is an improvement over the current best chromosome.
void	parseProblemData(java.io.File file, ModifiableResources resources) Parses the specified file and uses the parsed data to set up the problem type instance appropriately.

Methods inherited from class jcgp.backend.modules.problem.Problem

evaluate, getBestFitness, getFileExtension, getFitnessOrientation, getFunctionSet, hasPerfectSolution, reset

Methods inherited from class jcgp.backend.modules.Module

getLocalParameters, toString

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, wait, wait, wait

Constructor Detail

TestCaseProblem

public TestCaseProblem(Resources resources)

Creates a new TestCaseProblem object.

Parameters:

resources - a reference to the experiment's resources.

Method Detail

getTestCases

public javafx.collections.ObservableList<TestCaseProblem.TestCase<T>> getTestCases()

Returns:

a list containing the test cases.

addTestCase

public final void addTestCase(java.lang.String[] inputs,
                              java.lang.String[] outputs)

Adds test cases to the problem instance as they get parsed from a problem data file. This template method uses parseTestCase, which must be implemented by subclasses.

Parameters:

inputs - the inputs represented as strings.

outputs - the outputs represented as strings.

clearTestCases

public void clearTestCases()

Remove all test cases.

parseProblemData

public void parseProblemData(java.io.File file,
                             ModifiableResources resources)

Description copied from class: Problem

Parses the specified file and uses the parsed data to set up the problem type instance appropriately. Any necessary resource changes can be performed using the provided ModifiableResources instance.

In addition, realisations of this method should update the value of maxFitness where appropriate, as this may be displayed to the user if a GUI is in use.

Specified by:

parseProblemData in class Problem

Parameters:

file - the data file to parse.

resources - a modifiable reference to the experiment's resources.

hasImprovement

public int hasImprovement(Population population)

Description copied from class: Problem

Used to assert whether a given population has a chromosome that is an improvement over the current best chromosome. A typical implementation of this method will simply compare chromosome fitness values, though the problem type is free to implement this in any way.

Specified by:

hasImprovement in class Problem

Parameters:

population - the population potentially containing a fitter chromosome.

Returns:

the index of the first chromosome in the population that is an improvement, -1 if none is found.